diff --git a/the_code/Human/MM_Cbust_Homer_Motif.ipynb b/the_code/Human/MM_Cbust_Homer_Motif.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..4eb3494c70a0a1861fd362742a69cc9fad183a7e --- /dev/null +++ b/the_code/Human/MM_Cbust_Homer_Motif.ipynb @@ -0,0 +1,1243 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# This notebook shows ClusterBuster and Homer experiments.\n", + "#### It uses contribution scores and TFModisco scores generated in the MM_EFS_TFModisco notebook.\n", + "#### The motif database file is provided in ./data/tomtom folder\n", + "#### It consists of:\n", + "* Getting TFModisco patterns and saving as txt file to be later used by ClusterBuster.\n", + "* Running Tomtom on TFModisco patterns.\n", + "* Running ClusterBuster by using TFModisco pattern PWMs on the sequences generated by in silico evolution, motif implantation, and GAN.\n", + "* Running Homer using Random and Evolved sequences as foreground and background sequences, and vice versa.\n", + "#### ClusterBuster results are in ./data/cbust folder.\n", + "#### Homer results are in ./data/homer folder.\n", + "#### Figures are saved to ./figures/cbust folder" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import pandas as pd\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42\n", + "\n", + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading the contribution scores calculated in the MM_EFS_TFModisco script" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "tasks = {}\n", + "task_to_scores = {}\n", + "task_to_hyp_scores = {}\n", + "onehot_data = {}\n", + "for i in [4]:\n", + " f = open(\"data/tfmodisco/MMEFS_M4_topic16_shapvalues.pkl\", \"rb\")\n", + " tasks[i] = pickle.load(f)\n", + " task_to_scores[i] = pickle.load(f)\n", + " task_to_hyp_scores[i] = pickle.load(f)\n", + " onehot_data[i] = pickle.load(f)\n", + " f.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading the TFModisco results calculated in the MM_EFS_TFModisco script\n", + "### Trimming the identified patterns and saving them as text and =.cb files to be used by ClusterBuster and TOMTOM" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# From TFModisco\n", + "# def get_ic_trimming_indices(ppm, background, threshold, pseudocount=0.001):\n", + "# \"\"\"Return tuple of indices to trim to if ppm is trimmed by info content.\n", + "# The ppm will be trimmed from the left and from the right until a position\n", + "# that meets the information content specified by threshold is found. A\n", + "# base of 2 is used for the infromation content.\n", + "# Arguments:\n", + "# threshold: the minimum information content.\n", + "# remaining arguments same as for compute_per_position_ic\n", + "# Returns:\n", + "# (start_idx, end_idx). start_idx is inclusive, end_idx is exclusive.\n", + "# \"\"\"\n", + "# per_position_ic = compute_per_position_ic(\n", + "# ppm=ppm, background=background, pseudocount=pseudocount)\n", + "# passing_positions = np.where(per_position_ic >= threshold)\n", + "# return (passing_positions[0][0], passing_positions[0][-1]+1)\n", + "\n", + "# def compute_per_position_ic(ppm, background, pseudocount):\n", + "# \"\"\"Compute information content at each position of ppm.\n", + "# Arguments:\n", + "# ppm: should have dimensions of length x alphabet. Entries along the\n", + "# alphabet axis should sum to 1.\n", + "# background: the background base frequencies\n", + "# pseudocount: pseudocount to be added to the probabilities of the ppm\n", + "# to prevent overflow/underflow.\n", + "# Returns:\n", + "# total information content at each positon of the ppm.\n", + "# \"\"\"\n", + "# assert len(ppm.shape)==2\n", + "# assert ppm.shape[1]==len(background),\\\n", + "# \"Make sure the letter axis is the second axis\"\n", + "# assert (np.max(np.abs(np.sum(ppm, axis=1)-1.0)) < 1e-7),(\n", + "# \"Probabilities don't sum to 1 along axis 1 in \"\n", + "# +str(ppm)+\"\\n\"+str(np.sum(ppm, axis=1)))\n", + "# alphabet_len = len(background)\n", + "# ic = ((np.log((ppm+pseudocount)/(1 + pseudocount*alphabet_len))/np.log(2))\n", + "# *ppm - (np.log(background)*background/np.log(2))[None,:])\n", + "# return np.sum(ic,axis=1)\n", + "\n", + "# import h5py\n", + "# hdf5_results = h5py.File(\"data/tfmodisco/MMEFS_M4_results.hdf5\",\"r\")\n", + "\n", + "# metacluster_names = [x.decode(\"utf-8\") for x in list(hdf5_results[\"metaclustering_results\"][\"all_metacluster_names\"][:])]\n", + "\n", + "# n_mut = 4\n", + "# motif_dict = {}\n", + "# with open(\"data/tfmodisco/selected_patterns.txt\", 'w') as fw_pattern:\n", + "# for metacluster_name in metacluster_names:\n", + "# motif_dict[metacluster_name] = {}\n", + "# metacluster_grp = (hdf5_results[\"metacluster_idx_to_submetacluster_results\"][metacluster_name])\n", + "# pattern_names = [x.decode(\"utf-8\") for x in list(metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][\"all_pattern_names\"][:])]\n", + "\n", + "# background = np.mean(onehot_data[n_mut], axis=(0,1))\n", + "# for pattern_name in pattern_names:\n", + "# pattern = metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][pattern_name]\n", + "# pattern_array = np.array(pattern[\"sequence\"][\"fwd\"])\n", + "# start, end = get_ic_trimming_indices(pattern_array, background=np.mean(onehot_data[n_mut], axis=(0,1)), threshold=0.1)\n", + "# # Motif(pattern_array).plot_logo()\n", + "# # Motif(pattern_array[start:end,:]).plot_logo()\n", + "# #motif_dict[metacluster_name][pattern_name] = Motif(np.array(pattern[\"sequence\"][\"fwd\"])).trim(0.1)\n", + "\n", + "# print(f'{metacluster_name}_{pattern_name}',file=fw_pattern)\n", + "\n", + "# with open(f'data/cbust/EFS_M4_motifs/MMFS_M{n_mut}_{metacluster_name}_{pattern_name}.cb', 'w') as fw:\n", + "# print(f'>{metacluster_name}_{pattern_name}',file=fw)\n", + "# for i in pattern_array[start:end,:]*100:\n", + "# print(*i,file=fw)\n", + "\n", + "# n_mut = 4\n", + "# background = np.mean(onehot_data[n_mut], axis=(0,1))\n", + "# with open(\"data/tomtom/EFS_M4_motifs.txt\", 'w') as fw_pattern:\n", + "# for metacluster_name in metacluster_names:\n", + "# metacluster_grp = (hdf5_results[\"metacluster_idx_to_submetacluster_results\"][metacluster_name])\n", + "# pattern_names = [x.decode(\"utf-8\") for x in list(metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][\"all_pattern_names\"][:])]\n", + "\n", + "# for pattern_name in pattern_names:\n", + "# pattern = metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][pattern_name]\n", + "# pattern_array = np.array(pattern[\"sequence\"][\"fwd\"])\n", + "# start, end = get_ic_trimming_indices(pattern_array, background=background, threshold=0.1)\n", + " \n", + "# print(' ',file=fw_pattern)\n", + "# for i in pattern_array[start:end,:]:\n", + "# print(*i,file=fw_pattern, sep='\\t')\n", + "\n", + "\n", + "# hdf5_results.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Running TOMTOM on the TFModisco patterns" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "motif-4\n", + "motif-3\n", + "motif-2\n", + "motif-1\n", + "motif-4\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "The following have been reloaded with a version change:\n", + " 1) cluster/wice/dedicated_big_gpu => cluster/wice/bigmem\n", + "\n", + "The output directory './motif-4' already exists.\n", + "Its contents will be overwritten.\n", + "Processing query 1 out of 1 \n", + "# Computing q-values.\n", + "# Estimating pi_0 from all 48906 observed p-values.\n", + "# Estimating pi_0.\n", + "# Minimal pi_zero = 1.00151\n", + "# Estimated pi_0=1\n", + "The output directory './motif-3' already exists.\n", + "Its contents will be overwritten.\n", + "Processing query 1 out of 1 \n", + "# Computing q-values.\n", + "# Estimating pi_0 from all 48906 observed p-values.\n", + "# Estimating pi_0.\n", + "# Minimal pi_zero = 0.996969\n", + "# Estimated pi_0=0.996969\n", + "The output directory './motif-2' already exists.\n", + "Its contents will be overwritten.\n", + "Processing query 1 out of 1 \n", + "# Computing q-values.\n", + "# Estimating pi_0 from all 48906 observed p-values.\n", + "# Estimating pi_0.\n", + "# Minimal pi_zero = 0.97176\n", + "# Estimated pi_0=0.973172\n", + "The output directory './motif-1' already exists.\n", + "Its contents will be overwritten.\n", + "Processing query 1 out of 1 \n", + "# Computing q-values.\n", + "# Estimating pi_0 from all 48906 observed p-values.\n", + "# Estimating pi_0.\n", + "# Minimal pi_zero = 0.984075\n", + "# Estimated pi_0=0.986332\n", + "The output directory './motif-4' already exists.\n", + "Its contents will be overwritten.\n", + "Processing query 1 out of 1 \n", + "# Computing q-values.\n", + "# Estimating pi_0 from all 48906 observed p-values.\n", + "# Estimating pi_0.\n", + "# Minimal pi_zero = 1.00151\n", + "# Estimated pi_0=1\n" + ] + } + ], + "source": [ + "%%bash\n", + "cd ./data/tomtom/\n", + "\n", + "module load cluster/wice/bigmem\n", + "module load MEME/5.5.1-GCC-10.3.0\n", + "\n", + "LC_ALL=en_US.utf8 ls motif-*.meme | parallel -j 12 --plus '\n", + "sampleName=\"{/.}\"\n", + "echo $sampleName\n", + "tomtom -thresh 0.3 \\\n", + " -oc ./$sampleName \\\n", + " $sampleName.meme \\\n", + " ./motif2gene_names.all.meme\n", + "'\n", + "\n", + "LC_ALL=en_US.utf8 ls motif-4*.meme | parallel -j 12 --plus '\n", + "sampleName=\"{/.}\"\n", + "echo $sampleName\n", + "tomtom -thresh 1 \\\n", + " -oc ./$sampleName \\\n", + " $sampleName.meme \\\n", + " ./motif2gene_names.all.meme\n", + "'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Printing synthetic sequences (generated via in silico evolution) as fasta file for different mutational steps" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# import pickle\n", + "# f = open(\"data/deepmel2/MM_EFS_4000_withmut.pkl\", \"rb\")\n", + "# evolved_seq_4000_dict = pickle.load(f)\n", + "# f.close()\n", + "\n", + "# for n_mut in range(16):\n", + "# with open(f'data/cbust/EFS_fasta/MMEFS_M{n_mut}.fa','w') as fw:\n", + "# for id_ in range(len(evolved_seq_4000_dict[\"X\"])):\n", + "# start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + "# for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:n_mut]):\n", + "# #print(i,end=\",\")\n", + "# start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8') \n", + "# print(f'>{id_}', file=fw)\n", + "# for nuc in start_x[0]:\n", + "# if nuc[0]==1:\n", + "# print(\"A\",end=\"\", file=fw)\n", + "# if nuc[1]==1:\n", + "# print(\"C\",end=\"\", file=fw)\n", + "# if nuc[2]==1:\n", + "# print(\"G\",end=\"\", file=fw)\n", + "# if nuc[3]==1:\n", + "# print(\"T\",end=\"\", file=fw)\n", + "# print(\"\", file=fw)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Running ClusterBuster on synthetic (generated via in silico evolution), Genomic, GAN-generated, and background sequences using the motifs identified by TFModisco" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# %%bash\n", + "\n", + "# fasta_folder=data/cbust/EFS_fasta\n", + "# folder=data/cbust/EFS_M4_results\n", + "# matrix_prefix=data/cbust/EFS_M4_motifs/MMEFS_M4_\n", + "\n", + "# module load Cluster-Buster/20220421-GCC-11.3.0\n", + "# for i in {0..15}\n", + "# do\n", + "# echo seq_M${i}\n", + "# cd ${folder}\n", + "# mkdir seq_M${i}\n", + "\n", + "# while read -r line\n", + "# do\n", + "# matrix_file=${matrix_prefix}${line}.cb\n", + "# cbust -c 0 -m 3 -f 5 ${matrix_file} ${fasta_folder}/MMEFS_M${i}.fa > ${folder}/seq_M${i}/MMEFS_M${i}.${line}.bed\n", + "# done < selected_patterns.txt\n", + "# cat ${folder}/seq_M${i}/MMEFS_M${i}.*.bed | grep -v \"#\" | awk '{if ($11 == \"motif\") print $0;}' | cut -f1-6 > ${folder}/seq_M${i}/MMEFS_M${i}.selected.motif.gff\n", + "# done\n", + "\n", + "# module load BEDTools/2.30.0-GCC-10.3.0\n", + "# for i in {0..15}\n", + "# do\n", + "# echo seq_M${i}\n", + "# cd ${folder}\n", + "\n", + "# while read -r line\n", + "# do\n", + "# cat ${folder}/seq_M${i}/MMEFS_M${i}.${line}.bed | grep -v \"#\" | awk '{if ($11 == \"motif\") print $0;}' | cut -f1-6 | sort -k1,1 -k2,2n > ${folder}/seq_M${i}/MMEFS_M${i}.${line}.motif.bed\n", + "# bedtools merge -c 4,5 -o first,max -d -4 -i ${folder}/seq_M${i}/MMEFS_M${i}.${line}.motif.bed > ${folder}/seq_M${i}/MMEFS_M${i}.${line}.motif.merged.bed\n", + "# done < selected_patterns.txt\n", + "# cat ${folder}/seq_M${i}/MMEFS_M${i}.*.motif.merged.bed > ${folder}/seq_M${i}/MMEFS_M${i}.selected.motif.merged.gff\n", + "# done" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# def gff_to_npz_as_array(filename):\n", + "# with open(filename) as file:\n", + "# result = []\n", + "# for line in file:\n", + "# if line.startswith(\"#\"):\n", + "# continue\n", + "# tabs = line.strip().split('\\t')\n", + "# seq_name = int(tabs[0])\n", + "# start = int(tabs[1])\n", + "# end = int(tabs[2])\n", + "# motif_name = tabs[3]\n", + "# metacluster_name = int(motif_name.split('_')[1])\n", + "# pattern_name = int(motif_name.split('_')[3])\n", + "# score = float(tabs[4])\n", + "# # strand = 0 if tabs[5]=='-' else 1\n", + "# result.append([seq_name, metacluster_name, pattern_name, start, end, score,])# strand]) \n", + "# return np.array(result)\n", + "\n", + "# cbust_mot_array_merged = {}\n", + "# for n_mut in range(16):\n", + "# gff_filename = f'data/cbust/EFS_M4_results/seq_M{n_mut}/MMEFS_M{n_mut}.selected.motif.merged.gff'\n", + "# cbust_mot_array_merged[n_mut] = gff_to_npz_as_array(gff_filename) \n", + " \n", + "# import pickle\n", + "# f = open(\"data/cbust/EFS_M4_results/EFS_cbust_mot_array_merged.pkl\", \"wb\")\n", + "# pickle.dump(cbust_mot_array_merged, f)\n", + "# f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# %%bash\n", + "# module load BEDTools/2.30.0-GCC-10.3.0\n", + "# module load Cluster-Buster/20220421-GCC-11.3.0\n", + "\n", + "\n", + "# folder=data/cbust/EFS_M4_results\n", + "# matrix_prefix=data/cbust/EFS_M4_motifs/MMFS_M4_\n", + "# MEL_fasta=data/deepmel2/Genomic_MEL_regions.fa\n", + "\n", + "# cd ${folder}\n", + "\n", + "# while read -r line\n", + "# do\n", + "# matrix_file=${matrix_prefix}${line}.cb\n", + "# cbust -c 0 -m 3 -f 5 ${matrix_file} ${MEL_fasta} > ${folder}/genomic/MEL_genomic.${line}.bed\n", + "# cat ${folder}/genomic/MEL_genomic.${line}.bed | grep -v \"#\" | awk '{if ($11 == \"motif\") print $0;}' | cut -f1-6 | sort -k1,1 -k2,2n > ${folder}/genomic/MEL_genomic.${line}.motif.bed\n", + "# bedtools merge -c 4,5 -o first,max -d -4 -i ${folder}/genomic/MEL_genomic.${line}.motif.bed > ${folder}/genomic/MEL_genomic.${line}.motif.merged.bed\n", + "# done < selected_patterns.txt\n", + "# cat ${folder}/genomic/MEL_genomic.*.motif.merged.bed > ${folder}/genomic/MEL_genomic.selected.motif.merged.gff" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# import pandas as pd\n", + "# def gff_to_npz_as_pandas(filename):\n", + "# with open(filename) as file:\n", + "# result = []\n", + "# for line in file:\n", + "# if line.startswith(\"#\"):\n", + "# continue\n", + "# tabs = line.strip().split('\\t')\n", + "# seq_name = tabs[0]\n", + "# start = int(tabs[1])\n", + "# end = int(tabs[2])\n", + "# motif_name = tabs[3]\n", + "# metacluster_name = int(motif_name.split('_')[1])\n", + "# pattern_name = int(motif_name.split('_')[3])\n", + "# score = float(tabs[4])\n", + "# # strand = 0 if tabs[5]=='-' else 1\n", + "# result.append([seq_name, metacluster_name, pattern_name, start, end, score,])# strand]) \n", + "# return pd.DataFrame(result, columns = [\"seq_name\", \"metacluster_name\", \"pattern_name\", \"start\", \"end\", \"score\", ])#\"strand\"])\n", + "\n", + "# gff_filename = '=data/cbust/EFS_M4_results/genomic/MEL_genomic.selected.motif.merged.gff'\n", + "# cbust_mot_array_genomic = gff_to_npz_as_pandas(gff_filename) \n", + "\n", + "# import pickle\n", + "# f = open(\"data/cbust/EFS_M4_results/Genomic_cbust_mot_array_merged.pkl\", \"wb\")\n", + "# pickle.dump(cbust_mot_array_genomic, f)\n", + "# f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# import pickle \n", + "# with open('data/gan/GAN_data_dict.pkl', 'rb') as f:\n", + "# GAN_data_dict = pickle.load(f)\n", + " \n", + "# for iter_ in GAN_data_dict['MMgan']:\n", + "# with open(f'data/cbust/GAN_fasta/MMGAN_I{iter_}.fa','w') as fw:\n", + "# for seq in range(len(GAN_data_dict['MMgan'][iter_]['seq'])):\n", + "# print(f'>{seq}', file=fw)\n", + "# for nuc in GAN_data_dict['MMgan'][iter_]['seq'][seq]:\n", + "# if nuc[0]==1:\n", + "# print(\"A\",end=\"\", file=fw)\n", + "# if nuc[1]==1:\n", + "# print(\"C\",end=\"\", file=fw)\n", + "# if nuc[2]==1:\n", + "# print(\"G\",end=\"\", file=fw)\n", + "# if nuc[3]==1:\n", + "# print(\"T\",end=\"\", file=fw)\n", + "# print(\"\", file=fw)\n", + "\n", + "# for iter_ in GAN_data_dict['bg']:\n", + "# with open(f'data/cbust/BG_fasta/bg_I{iter_}.fa','w') as fw:\n", + "# for seq in range(len(GAN_data_dict['bg'][iter_]['seq'])):\n", + "# print(f'>{seq}', file=fw)\n", + "# for nuc in GAN_data_dict['bg'][iter_]['seq'][seq]:\n", + "# if nuc[0]==1:\n", + "# print(\"A\",end=\"\", file=fw)\n", + "# if nuc[1]==1:\n", + "# print(\"C\",end=\"\", file=fw)\n", + "# if nuc[2]==1:\n", + "# print(\"G\",end=\"\", file=fw)\n", + "# if nuc[3]==1:\n", + "# print(\"T\",end=\"\", file=fw)\n", + "# print(\"\", file=fw)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# %%bash\n", + "# module load BEDTools/2.30.0-GCC-10.3.0\n", + "# module load Cluster-Buster/20220421-GCC-11.3.0\n", + "\n", + "# for i in $(seq 0 10000 160000)\n", + "# do\n", + "# echo seq_I${i}\n", + "# fasta_folder=data/cbust/GAN_fasta\n", + "# folder=data/cbust/GAN_M4_results\n", + "# matrix_prefix=data/cbust/EFS_M4_motifs/MMFS_M4_\n", + "# cd ${folder}\n", + "# mkdir seq_I${i}\n", + "\n", + "# while read -r line\n", + "# do\n", + "# matrix_file=${matrix_prefix}${line}.cb\n", + "# cbust -c 0 -m 3 -f 5 ${matrix_file} ${fasta_folder}/MMGAN_I${i}.fa > ${folder}/seq_I${i}/MMGAN_I${i}.${line}.bed\n", + "# cat ${folder}/seq_I${i}/MMGAN_I${i}.${line}.bed | grep -v \"#\" | awk '{if ($11 == \"motif\") print $0;}' | cut -f1-6 | sort -k1,1 -k2,2n > ${folder}/seq_I${i}/MMGAN_I${i}.${line}.motif.bed\n", + "# bedtools merge -c 4,5 -o first,max -d -4 -i ${folder}/seq_I${i}/MMGAN_I${i}.${line}.motif.bed > ${folder}/seq_I${i}/MMGAN_I${i}.${line}.motif.merged.bed\n", + "# done < selected_patterns.txt\n", + "# cat ${folder}/seq_I${i}/MMGAN_I${i}.*.motif.merged.bed > ${folder}/seq_I${i}/MMGAN_I${i}.selected.motif.merged.gff\n", + "# done\n", + "\n", + "\n", + "# for i in $(seq 0 1 4)\n", + "# do\n", + "# echo seq_I${i}\n", + "# fasta_folder=data/cbust/BG_fasta\n", + "# folder=data/cbust/BG_M4_results\n", + "# matrix_prefix=data/cbust/EFS_M4_motifs/MMFS_M4_\n", + "# cd ${folder}\n", + "# mkdir seq_I${i}\n", + "\n", + "# while read -r line\n", + "# do\n", + "# matrix_file=${matrix_prefix}${line}.cb\n", + "# cbust -c 0 -m 3 -f 5 ${matrix_file} ${fasta_folder}/bg_I${i}.fa > ${folder}/seq_I${i}/bg_I${i}.${line}.bed\n", + "# cat ${folder}/seq_I${i}/bg_I${i}.${line}.bed | grep -v \"#\" | awk '{if ($11 == \"motif\") print $0;}' | cut -f1-6 | sort -k1,1 -k2,2n > ${folder}/seq_I${i}/bg_I${i}.${line}.motif.bed\n", + "# bedtools merge -c 4,5 -o first,max -d -4 -i ${folder}/seq_I${i}/bg_I${i}.${line}.motif.bed > ${folder}/seq_I${i}/bg_I${i}.${line}.motif.merged.bed\n", + "# done < selected_patterns.txt\n", + "# cat ${folder}/seq_I${i}/bg_I${i}.*.motif.merged.bed > ${folder}/seq_I${i}/bg_I${i}.selected.motif.merged.gff\n", + "# done" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# cbust_mot_array_GAN = {}\n", + "# for n_mut in GAN_data_dict['MMgan']:\n", + "# gff_filename = f'data/cbust/GAN_M4_results/seq_I{n_mut}/MMGAN_I{n_mut}.selected.motif.merged.gff'\n", + "# cbust_mot_array_GAN[n_mut] = gff_to_npz_as_array(gff_filename) \n", + "\n", + "# import pickle\n", + "# f = open(\"data/cbust/GAN_M4_results/GAN_cbust_mot_array_merged.pkl\", \"wb\")\n", + "# pickle.dump(cbust_mot_array_GAN, f)\n", + "# f.close()\n", + "\n", + "\n", + "# cbust_mot_array_bg = {}\n", + "# for n_mut in GAN_data_dict['bg']:\n", + "# gff_filename = f'data/cbust/BG_M4_results/seq_I{n_mut}/bg_I{n_mut}.selected.motif.merged.gff'\n", + "# cbust_mot_array_bg[n_mut] = gff_to_npz_as_array(gff_filename) \n", + "\n", + "# import pickle\n", + "# f = open(\"data/cbust/BG_M4_results/BG_cbust_mot_array_merged.pkl\", \"wb\")\n", + "# pickle.dump(cbust_mot_array_bg, f)\n", + "# f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/cbust/EFS_M4_results/EFS_cbust_mot_array_merged.pkl\", \"rb\")\n", + "EFS_cbust_mot_array_merged = pickle.load(f)\n", + "f.close()\n", + "\n", + "import pickle\n", + "f = open(\"data/cbust/EFS_M4_results/Genomic_cbust_mot_array_merged.pkl\", \"rb\")\n", + "Genomic_cbust_mot_array_merged = pickle.load(f)\n", + "f.close()\n", + "\n", + "import pickle\n", + "f = open(\"data/cbust/GAN_M4_results/GAN_cbust_mot_array_merged.pkl\", \"rb\")\n", + "GAN_cbust_mot_array_merged = pickle.load(f)\n", + "f.close()\n", + "\n", + "import pickle\n", + "f = open(\"data/cbust/BG_M4_results/BG_cbust_mot_array_merged.pkl\", \"rb\")\n", + "BG_cbust_mot_array_merged = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#EFS #4000\n", + "#Genomic #3885\n", + "#GAN #3968\n", + "#BG #3968" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the motif enrichment results at different mutational steps" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SOX10 threshold: 5.983922503108955\n", + "MITF threshold: 5.627510330271076\n", + "TFAP2 threshold: 5.691823528631348\n", + "ZEB2 threshold: 5.90920590448853\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(4,5))\n", + "for i, [metacluster_name, pattern_name, TF_name] in enumerate([[0,3,\"SOX10\"],[0,4,\"MITF\"],[0,9,\"TFAP2\"],[1,0,\"ZEB2\"]]):\n", + " data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==metacluster_name,EFS_cbust_mot_array_merged[0][:,2]==pattern_name))]\n", + " th_ = np.mean(data_)+1*np.std(data_)\n", + " print(f'{TF_name} threshold: {th_}')\n", + " ratios = []\n", + " for n_mut in range(16):\n", + " data_ = np.sum(EFS_cbust_mot_array_merged[n_mut][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[n_mut][:,1]==metacluster_name,EFS_cbust_mot_array_merged[n_mut][:,2]==pattern_name))]>th_)\n", + " ratios.append(data_/4000)\n", + " plt.scatter(n_mut,data_/4000,color=f'C{i}')\n", + " data_ = np.sum(Genomic_cbust_mot_array_merged['score'][(Genomic_cbust_mot_array_merged['metacluster_name'] == metacluster_name) & (Genomic_cbust_mot_array_merged['pattern_name'] == pattern_name)]>th_)\n", + " plt.scatter(16,data_/3885,color=f'C{i}',label=TF_name)\n", + " ratios.append(data_/3885)\n", + " _ = plt.ylim(bottom=0)\n", + "plt.ylabel(\"# Hits / # Regions\")\n", + "plt.xlabel(\"# Mutations\")\n", + "plt.title(\"In silico evolution\")\n", + "plt.legend()\n", + "_ = plt.xticks(range(17),list(range(16))+[\"Genomic\"],rotation=90)\n", + "plt.savefig(\"figures/cbust/EFS_motif.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the motif enrichment results at different iterations of GAN" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SOX10 threshold: 5.983922503108955\n", + "MITF threshold: 5.627510330271076\n", + "TFAP2 threshold: 5.691823528631348\n", + "ZEB2 threshold: 5.90920590448853\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(4,5))\n", + "for i, [metacluster_name, pattern_name, TF_name] in enumerate([[0,3,\"SOX10\"],[0,4,\"MITF\"],[0,9,\"TFAP2\"],[1,0,\"ZEB2\"]]):\n", + " data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==metacluster_name,EFS_cbust_mot_array_merged[0][:,2]==pattern_name))]\n", + " th_ = np.mean(data_)+1*np.std(data_)\n", + " print(f'{TF_name} threshold: {th_}')\n", + " ratios = []\n", + " for n_mut in GAN_cbust_mot_array_merged:\n", + " data_ = np.sum(GAN_cbust_mot_array_merged[n_mut][:,5][np.logical_and.reduce((GAN_cbust_mot_array_merged[n_mut][:,1]==metacluster_name,GAN_cbust_mot_array_merged[n_mut][:,2]==pattern_name))]>th_)\n", + " ratios.append(data_/3968)\n", + " plt.scatter(n_mut,data_/3968,color=f'C{i}')\n", + " data_ = np.sum(Genomic_cbust_mot_array_merged['score'][(Genomic_cbust_mot_array_merged['metacluster_name'] == metacluster_name) & (Genomic_cbust_mot_array_merged['pattern_name'] == pattern_name)]>th_)\n", + " plt.scatter(170000,data_/3885,color=f'C{i}',label=TF_name)\n", + " ratios.append(data_/3885)\n", + " _ = plt.ylim(bottom=0)\n", + "plt.ylabel(\"# Hits / # Regions\")\n", + "plt.xlabel(\"# Iterations\")\n", + "plt.legend()\n", + "plt.title(\"GAN generated\")\n", + "_ = plt.xticks(range(0,180000,10000),list(range(0,170000,10000))+[\"Genomic\"],rotation=90)\n", + "plt.savefig(\"figures/cbust/GAN_motif.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the motif enrichment results at different orders used to generate background sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SOX10 threshold: 5.983922503108955\n", + "MITF threshold: 5.627510330271076\n", + "TFAP2 threshold: 5.691823528631348\n", + "ZEB2 threshold: 5.90920590448853\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(2,5))\n", + "for i, [metacluster_name, pattern_name, TF_name] in enumerate([[0,3,\"SOX10\"],[0,4,\"MITF\"],[0,9,\"TFAP2\"],[1,0,\"ZEB2\"]]):\n", + " data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==metacluster_name,EFS_cbust_mot_array_merged[0][:,2]==pattern_name))]\n", + " th_ = np.mean(data_)+1*np.std(data_)\n", + " print(f'{TF_name} threshold: {th_}')\n", + " ratios = []\n", + " for n_mut in BG_cbust_mot_array_merged:\n", + " data_ = np.sum(BG_cbust_mot_array_merged[n_mut][:,5][np.logical_and.reduce((BG_cbust_mot_array_merged[n_mut][:,1]==metacluster_name,BG_cbust_mot_array_merged[n_mut][:,2]==pattern_name))]>th_)\n", + " ratios.append(data_/3968)\n", + " plt.scatter(n_mut,data_/3968,color=f'C{i}')\n", + " data_ = np.sum(Genomic_cbust_mot_array_merged['score'][(Genomic_cbust_mot_array_merged['metacluster_name'] == metacluster_name) & (Genomic_cbust_mot_array_merged['pattern_name'] == pattern_name)]>th_)\n", + " plt.scatter(5,data_/3885,color=f'C{i}',label=TF_name)\n", + " ratios.append(data_/3885)\n", + " _ = plt.ylim(bottom=0)\n", + "plt.ylabel(\"# Hits / # Regions\")\n", + "plt.xlabel(\"# Order\")\n", + "plt.title(\"Background sequences\")\n", + "plt.legend()\n", + "_ = plt.xticks(range(6),list(range(5))+[\"Genomic\"],rotation=90)\n", + "plt.savefig(\"figures/cbust/BG_motif.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the delta motif enrichment results at different mutational steps" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(16,4))\n", + "for i, [metacluster_name, pattern_name, TF_name] in enumerate([[0,3,\"SOX10\"],[0,4,\"MITF\"],[0,9,\"TFAP2\"],[1,0,\"ZEB2\"]]): \n", + " ax = fig.add_subplot(1,4,i+1)\n", + " x = []\n", + " for n_mut in range(16):\n", + " data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==metacluster_name,EFS_cbust_mot_array_merged[0][:,2]==pattern_name))]\n", + " th_ = np.mean(data_)+1*np.std(data_)\n", + " cbust_mot_data = pd.DataFrame(EFS_cbust_mot_array_merged[n_mut], columns = [\"seq_name\", \"metacluster_name\", \"pattern_name\", \"start\", \"end\", \"score\", ])#\"strand\"])\n", + " x.append(len(cbust_mot_data[(cbust_mot_data['metacluster_name'] == metacluster_name) & \n", + " (cbust_mot_data['pattern_name'] == pattern_name) & \n", + " (cbust_mot_data['score'] >= th_)]))\n", + "\n", + " plt.bar(range(15),np.diff(x))\n", + " plt.title(TF_name)\n", + " plt.xlabel(\"Mutations\")\n", + " plt.ylabel(\"Delta #motif in each step\")\n", + " plt.xticks(range(15),list(range(1,16)))\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/cbust/EFS_delta_motif.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Selecting the sequences to be tested" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5., 8., 9., 11., 12., 15., 16., 17., 18., 19., 20., 22., 23.,\n", + " 25., 26., 27., 29., 31., 32., 33., 34., 38., 39., 40., 41., 42.,\n", + " 45., 46., 49., 50., 51., 54., 59., 60., 62., 63., 65., 68., 69.,\n", + " 71., 72., 73., 74., 75., 80., 81., 83., 84., 88., 91.])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_mut = 15\n", + "cbust_mot_data = pd.DataFrame(EFS_cbust_mot_array_merged[n_mut], columns = [\"seq_name\", \"metacluster_name\", \"pattern_name\", \"start\", \"end\", \"score\"])\n", + "\n", + "data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==0,EFS_cbust_mot_array_merged[0][:,2]==3))]\n", + "th_ = np.mean(data_)+1*np.std(data_)\n", + "SOX_set = set(cbust_mot_data['seq_name'][ (cbust_mot_data['metacluster_name']==0) & (cbust_mot_data['pattern_name']==3) & (cbust_mot_data['score']>th_)])\n", + "\n", + "data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==0,EFS_cbust_mot_array_merged[0][:,2]==4))]\n", + "th_ = np.mean(data_)+1*np.std(data_)\n", + "MITF_set = set(cbust_mot_data['seq_name'][ (cbust_mot_data['metacluster_name']==0) & (cbust_mot_data['pattern_name']==4) & (cbust_mot_data['score']>th_)])\n", + "\n", + "np.sort(list(set(SOX_set) & set(MITF_set)))[:50]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 8., 9., 17., 18., 19., 22., 25., 27., 29., 32., 38., 39., 42.,\n", + " 45., 46., 49., 50., 54., 65., 68.])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_mut = 15\n", + "cbust_mot_data = pd.DataFrame(EFS_cbust_mot_array_merged[n_mut], columns = [\"seq_name\", \"metacluster_name\", \"pattern_name\", \"start\", \"end\", \"score\"])\n", + "\n", + "data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==0,EFS_cbust_mot_array_merged[0][:,2]==3))]\n", + "th_ = np.mean(data_)+1*np.std(data_)\n", + "SOX_set = set(cbust_mot_data['seq_name'][ (cbust_mot_data['metacluster_name']==0) & (cbust_mot_data['pattern_name']==3) & (cbust_mot_data['score']>th_)])\n", + "\n", + "data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==0,EFS_cbust_mot_array_merged[0][:,2]==4))]\n", + "th_ = np.mean(data_)+1*np.std(data_)\n", + "MITF_set = set(cbust_mot_data['seq_name'][ (cbust_mot_data['metacluster_name']==0) & (cbust_mot_data['pattern_name']==4) & (cbust_mot_data['score']>th_)])\n", + "\n", + "data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==0,EFS_cbust_mot_array_merged[0][:,2]==9))]\n", + "th_ = np.mean(data_)+1*np.std(data_)\n", + "TFAP_set = set(cbust_mot_data['seq_name'][ (cbust_mot_data['metacluster_name']==0) & (cbust_mot_data['pattern_name']==9) & (cbust_mot_data['score']>th_)])\n", + "\n", + "np.sort(list(set(SOX_set) & set(MITF_set) & set(TFAP_set)))[:20]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Selected IDs: 15 17 19 22 27 45 49 60 68 72\n" + ] + } + ], + "source": [ + "print(\"Selected IDs:\",*[15,17,19,22,27,45,49,60,68,72])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Printing the number of motif hits at different mutational steps" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "------\n", + "EFS-1_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "104591 15.0 0.0 3.0 292.0 312.0 10.5\n", + "104592 15.0 0.0 3.0 315.0 335.0 10.7\n", + "104593 15.0 0.0 3.0 373.0 392.0 10.7\n", + "EFS-1_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "114258 15.0 0.0 4.0 348.0 358.0 7.06\n", + "114261 15.0 0.0 4.0 476.0 486.0 6.67\n", + "EFS-1_mut15_TFAP2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "EFS-1_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-2_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "105287 17.0 0.0 3.0 300.0 320.0 9.51\n", + "EFS-2_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "114955 17.0 0.0 4.0 275.0 285.0 7.68\n", + "EFS-2_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "179179 17.0 0.0 9.0 286.0 295.0 7.81\n", + "EFS-2_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-3_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "105933 19.0 0.0 3.0 273.0 292.0 9.72\n", + "105934 19.0 0.0 3.0 354.0 374.0 12.70\n", + "EFS-3_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "115640 19.0 0.0 4.0 248.0 258.0 7.17\n", + "EFS-3_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "179855 19.0 0.0 9.0 297.0 307.0 5.98\n", + "EFS-3_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-4_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "106699 22.0 0.0 3.0 144.0 164.0 12.60\n", + "106700 22.0 0.0 3.0 171.0 194.0 6.72\n", + "106701 22.0 0.0 3.0 309.0 329.0 12.50\n", + "EFS-4_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "116691 22.0 0.0 4.0 269.0 279.0 6.17\n", + "EFS-4_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "180837 22.0 0.0 9.0 239.0 248.0 7.56\n", + "EFS-4_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-5_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "107756 27.0 0.0 3.0 279.0 298.0 6.59\n", + "107758 27.0 0.0 3.0 369.0 389.0 12.40\n", + "107759 27.0 0.0 3.0 453.0 476.0 7.79\n", + "EFS-5_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "118504 27.0 0.0 4.0 96.0 106.0 5.72\n", + "118505 27.0 0.0 4.0 256.0 266.0 6.98\n", + "EFS-5_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "182477 27.0 0.0 9.0 442.0 452.0 8.38\n", + "EFS-5_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-6_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "110678 45.0 0.0 3.0 57.0 76.0 9.93\n", + "110679 45.0 0.0 3.0 158.0 178.0 11.90\n", + "EFS-6_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "123311 45.0 0.0 4.0 242.0 252.0 6.32\n", + "123313 45.0 0.0 4.0 453.0 463.0 6.93\n", + "EFS-6_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "186975 45.0 0.0 9.0 103.0 113.0 9.55\n", + "186976 45.0 0.0 9.0 208.0 218.0 8.32\n", + "EFS-6_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-7_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "110804 49.0 0.0 3.0 115.0 134.0 9.47\n", + "110805 49.0 0.0 3.0 235.0 256.0 9.29\n", + "EFS-7_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "123435 49.0 0.0 4.0 298.0 308.0 6.84\n", + "123437 49.0 0.0 4.0 417.0 427.0 6.23\n", + "EFS-7_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "187098 49.0 0.0 9.0 179.0 189.0 7.91\n", + "EFS-7_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-8_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "111179 60.0 0.0 3.0 214.0 233.0 6.63\n", + "111180 60.0 0.0 3.0 239.0 259.0 10.70\n", + "EFS-8_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "123840 60.0 0.0 4.0 281.0 291.0 6.89\n", + "EFS-8_mut15_TFAP2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "EFS-8_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-9_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "111457 68.0 0.0 3.0 328.0 347.0 10.90\n", + "111458 68.0 0.0 3.0 371.0 391.0 10.80\n", + "111459 68.0 0.0 3.0 392.0 411.0 6.68\n", + "EFS-9_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "124125 68.0 0.0 4.0 272.0 282.0 6.73\n", + "EFS-9_mut15_TFAP2\n", + " seq_name metacluster_name pattern_name start end score\n", + "187730 68.0 0.0 9.0 175.0 185.0 8.13\n", + "EFS-9_mut15_ZEB2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "------\n", + "EFS-10_mut15_SOX10\n", + " seq_name metacluster_name pattern_name start end score\n", + "111609 72.0 0.0 3.0 83.0 103.0 7.75\n", + "111610 72.0 0.0 3.0 210.0 231.0 8.22\n", + "EFS-10_mut15_MITF\n", + " seq_name metacluster_name pattern_name start end score\n", + "124265 72.0 0.0 4.0 171.0 181.0 6.82\n", + "EFS-10_mut15_TFAP2\n", + "Empty DataFrame\n", + "Columns: [seq_name, metacluster_name, pattern_name, start, end, score]\n", + "Index: []\n", + "EFS-10_mut15_ZEB2\n", + " seq_name metacluster_name pattern_name start end score\n", + "201735 72.0 1.0 0.0 460.0 466.0 6.43\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "for i,seq_id in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " print(\"------\")\n", + " for k, [metacluster_name, pattern_name, TF_name] in enumerate([[0,3,\"SOX10\"],[0,4,\"MITF\"],[0,9,\"TFAP2\"],[1,0,\"ZEB2\"]]):\n", + " data_ = EFS_cbust_mot_array_merged[0][:,5][np.logical_and.reduce((EFS_cbust_mot_array_merged[0][:,1]==metacluster_name,EFS_cbust_mot_array_merged[0][:,2]==pattern_name))]\n", + " th_ = np.mean(data_)+1*np.std(data_)\n", + "\n", + " print(f'EFS-{i+1}_mut15_{TF_name}')\n", + " n_mut = 15\n", + " cbust_mot_data = pd.DataFrame(EFS_cbust_mot_array_merged[n_mut], columns = [\"seq_name\", \"metacluster_name\", \"pattern_name\", \"start\", \"end\", \"score\"])\n", + " print(cbust_mot_data[(cbust_mot_data['seq_name']==seq_id) & (cbust_mot_data['metacluster_name']==metacluster_name) & (cbust_mot_data['pattern_name']==pattern_name) & (cbust_mot_data['score']>th_)])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Running Homer using Random and Evolved sequences as foreground and background sequences, and vice versa. " + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# %%bash\n", + "\n", + "# module load HOMER/4.10.4-foss-2018a\n", + "\n", + "# cd data/homer/M15_vs_M0\n", + "# target_fasta=data/cbust/EFS_fasta/MMEFS_M15.fa\n", + "# background_fasta=data/cbust/EFS_fasta/MMEFS_M0.fa\n", + "# findMotifs.pl ${target_fasta} fasta ./ -fasta ${background_fasta}\n", + "\n", + "# cd data/homer/M0_vs_M15\n", + "# background_fasta=data/cbust/EFS_fasta/MMEFS_M15.fa\n", + "# target_fasta=data/cbust/EFS_fasta/MMEFS_M0.fa\n", + "# findMotifs.pl ${target_fasta} fasta ./ -fasta ${background_fasta}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/the_code/Human/MM_ChromBPnet_Experiments.ipynb b/the_code/Human/MM_ChromBPnet_Experiments.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..671eb692cfc7691e7a1a653471f8d5dae708e7ee --- /dev/null +++ b/the_code/Human/MM_ChromBPnet_Experiments.ipynb @@ -0,0 +1,832 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "62c91560-1f6a-4a3e-838a-fb7053efb935", + "metadata": {}, + "source": [ + "# This notebooks shows scoring synthetic and genomic enhancers by using the ChromBPNet models trained on MM001 and MM047 cell lines." + ] + }, + { + "cell_type": "markdown", + "id": "2004cbb0-29fe-4c5c-950d-247cc3a7fdc6", + "metadata": {}, + "source": [ + "#### It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. \n", + "#### The model files are provided in ./data/chrombpnet.\n", + "#### Figures are saved to ./figures/chrombpnet folder." + ] + }, + { + "cell_type": "markdown", + "id": "4e0c2f9c-4a36-4b63-a68e-a66b6191a5b1", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "aa2fdeca-7ddb-4df8-aa51-d797741598da", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING: IF upgrading from v1.0 or v1.1 to v1.2, note that chrombpnet has undergone linting to generate a modular structure for release on pypi.Hard-coded script paths are no longer necessary. Please refer to the updated README to ensure your script calls are compatible with v1.2\n" + ] + }, + { + "ename": "RuntimeError", + "evalue": "module compiled against API version 0x10 but this version of numpy is 0xf", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;31mRuntimeError\u001b[0m: module compiled against API version 0x10 but this version of numpy is 0xf" + ] + } + ], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import chrombpnet.evaluation.interpret.shap_utils as shap_utils\n", + "import tensorflow as tf\n", + "from tensorflow.python.keras.backend import set_session\n", + "tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)\n", + "\n", + "import sys\n", + "sys.path.insert(0, 'data/chrombpnet/chrombpnet_utils')\n", + "import one_hot\n", + "\n", + "import matplotlib\n", + "import matplotlib.patches as mpatches\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "c9a840ce-290c-4a8c-96ea-cd6234e29e58", + "metadata": {}, + "source": [ + "### Loading ChromBPNet models" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "04383f16-0835-41d4-8145-f236d1211e47", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2023-06-25 16:29:32.085015: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA\n", + "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", + "2023-06-25 16:29:38.458263: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 78965 MB memory: -> device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:bf:00.0, compute capability: 8.0\n" + ] + } + ], + "source": [ + "models = {}\n", + "models[\"MM001\"] = tf.keras.models.load_model('data/chrombpnet/chrombpnet_wo_bias_MM001.h5')\n", + "models[\"MM047\"] = tf.keras.models.load_model('data/chrombpnet/chrombpnet_wo_bias_MM047.h5')" + ] + }, + { + "cell_type": "markdown", + "id": "b502d8a5-311f-4e17-a705-dcaaa455024f", + "metadata": {}, + "source": [ + "### Loading flanking sequences in the vector around the tested enhancers" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "2a571739-86fb-45c6-b651-28da9da6ea11", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "upstream_seq = one_hot.dna_to_one_hot([\"gggtcacatgatcacccatattatgaagaaatgcagtcagctccttagggcctccgatcgttgtcagaagtaagttggccgcggtgttgtcgctcatggtaatggcagcactacacaattctcttaccgtcatgccatccgtaagatgcttttccgtgaccggcgagtactcaaccaagtcgttttgtgagtagtgtatacggcgaccaagctgctcttgcccggcgtctatacgggacaacaccgcgccacatagcagtactttgaaagtgctcatcatcgggaatcgttcttcggggcggaaagactcaaggatcttgccgctattgagatccagttcgatatagcccactcttgcacccagttgatcttcagcatcttttactttcaccagcgtttcggggtgtgcaaaaacaggcaagcaaaatgccgcaaagaagggaatgagtgcgacacgaaaatgttggatgctcatactcgtcctttttcaatattattgaagcatttatcagggttactagtacgtctctcaaggataagtaagtaatattaaggtacgggaggtattggacaggccgcaataaaatatctttattttcattacatctgtgtgttggttttttgtgtgaatcgatagtactaacatacgctctccatcaaaacaaaacgaaacaaaacaaactagcaaaataggctgtccccagtgcaagtgcaggtgccagaacatttctctggcctaactggccggtacctgagctcccgtcgacgaattctgcagatatcCAAGTTTGTACAAAAAAGCAGGCT\"])\n", + "downstream_seq = one_hot.dna_to_one_hot([\"ACCCAGCTTTCTTGTACAAAGTGGgataaacccgctgatcagcctcgactgtgctcgaggatatcaagatctggcctcggcggccaagcttagacactagagggtatataatggaagctcgacttccagcttggcaatccggtactgttggtaaagccaccatggaagatgccaaaaacattaagaagggcccagcgccattctacccactcgaagacgggaccgccggcgagcagctgcacaaagccatgaagcgctacgccctggtgcccggcaccatcgcctttaccgacgcacatatcgaggtggacattacctacgccgagtacttcgagatgagcgttcggctggcagaagctatgaagcgctatgggctgaatacaaaccatcggatcgtggtgtgcagcgagaatagcttgcagttcttcatgcccgtgttgggtgccctgttcatcggtgtggctgtggccccagctaacgacatctacaacgagcgcgagctgctgaacagcatgggcatcagccagcccaccgtcgtattcgtgagcaagaaagggctgcaaaagatcctcaacgtgcaaaagaagctaccgatcatacaaaagatcatcatcatggatagcaagaccgactaccagggcttccaaagcatgtacaccttcgtgacttcccatttgccacccggcttcaacgagtacgacttcgtgcccgagagcttcgaccgggacaaaaccatcgccctgatcatgaacagtagtggcagtaccggattgcccaagggcgtagccctaccgcaccgcaccgctt\"])" + ] + }, + { + "cell_type": "markdown", + "id": "219ab4d4-08f2-4e58-81c9-ccef0f79bf05", + "metadata": {}, + "source": [ + "### Loading the generated sequences via in silico evolution\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "d3f1f342-10b5-4fcc-a570-5d0776b25776", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/deepmel2/MM_EFS_4000_withmut.pkl\", \"rb\")\n", + "evolved_seq_4000_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "b760e174-e95c-40cc-9061-df37b1ffb408", + "metadata": {}, + "source": [ + "### Calculating prediction scores using ChromBPNet on the generated sequences via in silico evolution by DeepMEL2" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3936e826-751e-42c9-802d-0f5bcb3cb644", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15, " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2023-06-25 16:29:47.711968: I tensorflow/stream_executor/cuda/cuda_dnn.cc:368] Loaded cuDNN version 8100\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17, 19, 22, 27, 45, 49, 60, 68, 72, \n", + "15, 17, 19, 22, 27, 45, 49, 60, 68, 72, \n" + ] + } + ], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}\n", + "\n", + "predictions_efs = {}\n", + "for MM_line in [\"MM001\",\"MM047\"]:\n", + " predictions_efs[MM_line] = {}\n", + " predictions_efs[MM_line]['track'] = {}\n", + " predictions_efs[MM_line]['scalar'] = {}\n", + " for id_ in [15,17,19,22,27,45,49,60,68,72]:\n", + " print(id_, end=', ')\n", + " predictions_efs[MM_line]['track'][id_] = []\n", + " predictions_efs[MM_line]['scalar'][id_] = []\n", + "\n", + " start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + " pred = models[MM_line].predict(np.hstack((upstream_seq,start_x,downstream_seq)))\n", + " predictions_efs[MM_line]['track'][id_].append(pred[0][0])\n", + " predictions_efs[MM_line]['scalar'][id_].append(pred[1][0][0])\n", + "\n", + " for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + " pred = models[MM_line].predict(np.hstack((upstream_seq,start_x,downstream_seq)))\n", + " predictions_efs[MM_line]['track'][id_].append(pred[0][0])\n", + " predictions_efs[MM_line]['scalar'][id_].append(pred[1][0][0])\n", + "\n", + " print(\"\")\n", + "\n", + "for id_, muts in [\n", + " [22,[\"113_A\",\"164_A\",\"210_C\",\"215_C\",\"216_A\",\"259_G\",\"291_G\",\"300_T\"]],\n", + " [15,[\"247_C\",\"281_C\",\"284_G\",\"312_G\",\"338_C\",\"339_A\",\"365_C\",\"369_T\",\"420_T\",\"411_C\",\"431_A\",\"463_C\"]],\n", + " [60,[\"160_C\",\"178_T\",\"183_C\",\"184_A\",\"204_T\",\"205_G\",\"350_C\",\"352_G\",\"384_A\"]]]:\n", + " start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + " for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + " for i, mut_ in enumerate(muts):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + " for MM_line in [\"MM001\",\"MM047\"]:\n", + " pred = models[MM_line].predict(np.hstack((upstream_seq,start_x,downstream_seq)))\n", + " predictions_efs[MM_line]['track'][id_].append(pred[0][0])\n", + " predictions_efs[MM_line]['scalar'][id_].append(pred[1][0][0])" + ] + }, + { + "cell_type": "markdown", + "id": "71d72422-ac23-4a04-939c-190535168788", + "metadata": {}, + "source": [ + "### Plotting scalar prediction scores of synthetic enhancer at different mutational and repressed steps" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "91f495cf-f289-43d4-912b-aa02faf80464", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,5))\n", + "for i, MM_line in enumerate(models):\n", + " ax = fig.add_subplot(1,2,i+1)\n", + " for k,id_ in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " _ = plt.plot(predictions_efs[MM_line]['scalar'][id_],label=\"EFS-\"+str(k+1),linestyle=\"\",marker=\"o\",color=\"C\"+str(k))\n", + " plt.legend()\n", + " for k,id_ in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " _ = plt.plot(predictions_efs[MM_line]['scalar'][id_],label=\"EFS-\"+str(k+1),linestyle=\"--\",linewidth=0.5,color=\"C\"+str(k))\n", + " _ = plt.xticks(range(17),list(range(16))+[\"R\"])\n", + " plt.axvline(x=15,linestyle=\"--\",color=\"gray\")\n", + " plt.xlabel(\"Number of mutations\")\n", + " plt.ylabel(\"Prediction score\")\n", + " plt.title(MM_line)\n", + " plt.ylim(3,9.5)\n", + "plt.savefig(\"figures/chrombpnet/EFS_SelectedSeqs_Prediction_MM001_MM047_scalar.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "6d3c8a4a-30bf-4e95-af97-8712841016b7", + "metadata": {}, + "source": [ + "### Plotting track prediction scores of synthetic enhancer at different mutational and repressed steps" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "12d0ca98-6aa6-4b00-9997-526a1515043f", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "id_=22\n", + "name_=\"EFS-4\"\n", + "MM_line = \"MM001\"\n", + "muts = [3,4,7,8,12,15,16]\n", + "n_tracks = len(muts) + 2\n", + "\n", + "fig = plt.figure(figsize=(5,0.8*n_tracks))\n", + "fig.suptitle(name_)\n", + "\n", + "ax = fig.add_subplot(n_tracks,1,1)\n", + "values = predictions_efs[\"MM001\"]['track'][id_][0]\n", + "ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + "ax.set_title(\"Random Sequence\")\n", + "ax.set_xticks([])\n", + "ax.margins(x=0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(True)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "\n", + "for i, n_mut in enumerate(muts):\n", + " \n", + " ax = fig.add_subplot(n_tracks,1,i+2)\n", + " values = predictions_efs[\"MM001\"]['track'][id_][n_mut] - predictions_efs[\"MM001\"]['track'][id_][0]\n", + " ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + " ax.set_ylim(0,6)\n", + " if n_mut==16:\n", + " ax.set_title(\"Mut:15 + Repr\")\n", + " else:\n", + " ax.set_title(\"Mut:\"+str(n_mut))\n", + " ax.margins(x=0)\n", + " \n", + " ax.spines['right'].set_visible(False)\n", + " ax.spines['top'].set_visible(False)\n", + " ax.spines['left'].set_visible(True)\n", + " ax.spines['bottom'].set_visible(False)\n", + " \n", + " if i!=len(muts)-1:\n", + " ax.set_xticks([])\n", + " \n", + "ax = fig.add_subplot(n_tracks,1,n_tracks)\n", + "rect = mpatches.Rectangle((250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([0,1000])\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(False)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "plt.savefig(\"figures/chrombpnet/ChromBPNet_\"+name_+\"_steps_prediction_track_\"+MM_line+\".pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fe1356d4-1aff-4f6f-8e20-d7a1a5ec9eb0", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "id_=15\n", + "name_=\"EFS-1\"\n", + "MM_line = \"MM001\"\n", + "muts = [1,2,5,11,12,15,16]\n", + "n_tracks = len(muts) + 2\n", + "\n", + "fig = plt.figure(figsize=(5,0.8*n_tracks))\n", + "fig.suptitle(name_)\n", + "\n", + "ax = fig.add_subplot(n_tracks,1,1)\n", + "values = predictions_efs[\"MM001\"]['track'][id_][0]\n", + "ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + "ax.set_title(\"Random Sequence\")\n", + "ax.set_xticks([])\n", + "ax.margins(x=0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(True)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "\n", + "for i, n_mut in enumerate(muts):\n", + " \n", + " ax = fig.add_subplot(n_tracks,1,i+2)\n", + " values = predictions_efs[\"MM001\"]['track'][id_][n_mut] - predictions_efs[\"MM001\"]['track'][id_][0]\n", + " ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + " ax.set_ylim(0,6)\n", + " if n_mut==16:\n", + " ax.set_title(\"Mut:15 + Repr\")\n", + " else:\n", + " ax.set_title(\"Mut:\"+str(n_mut))\n", + " ax.margins(x=0)\n", + " \n", + " ax.spines['right'].set_visible(False)\n", + " ax.spines['top'].set_visible(False)\n", + " ax.spines['left'].set_visible(True)\n", + " ax.spines['bottom'].set_visible(False)\n", + " \n", + " if i!=len(muts)-1:\n", + " ax.set_xticks([])\n", + " \n", + "ax = fig.add_subplot(n_tracks,1,n_tracks)\n", + "rect = mpatches.Rectangle((250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([0,1000])\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(False)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "plt.savefig(\"figures/chrombpnet/ChromBPNet_\"+name_+\"_steps_prediction_track_\"+MM_line+\".pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "5f1895be-5675-4aea-8508-9704037daca3", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "id_=60\n", + "name_=\"EFS-8\"\n", + "MM_line = \"MM001\"\n", + "muts = [2,7,8,9,12,13,14,15,16]\n", + "n_tracks = len(muts) + 2\n", + "\n", + "fig = plt.figure(figsize=(5,0.8*n_tracks))\n", + "fig.suptitle(name_)\n", + "\n", + "ax = fig.add_subplot(n_tracks,1,1)\n", + "values = predictions_efs[\"MM001\"]['track'][id_][0]\n", + "ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + "ax.set_title(\"Random Sequence\")\n", + "ax.set_xticks([])\n", + "ax.margins(x=0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(True)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "\n", + "for i, n_mut in enumerate(muts):\n", + " \n", + " ax = fig.add_subplot(n_tracks,1,i+2)\n", + " values = predictions_efs[\"MM001\"]['track'][id_][n_mut] - predictions_efs[\"MM001\"]['track'][id_][0]\n", + " ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + " ax.set_ylim(0,6)\n", + " if n_mut==16:\n", + " ax.set_title(\"Mut:15 + Repr\")\n", + " else:\n", + " ax.set_title(\"Mut:\"+str(n_mut))\n", + " ax.margins(x=0)\n", + " \n", + " ax.spines['right'].set_visible(False)\n", + " ax.spines['top'].set_visible(False)\n", + " ax.spines['left'].set_visible(True)\n", + " ax.spines['bottom'].set_visible(False)\n", + " \n", + " if i!=len(muts)-1:\n", + " ax.set_xticks([])\n", + " \n", + "ax = fig.add_subplot(n_tracks,1,n_tracks)\n", + "rect = mpatches.Rectangle((250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([0,1000])\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(False)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "plt.savefig(\"figures/chrombpnet/ChromBPNet_\"+name_+\"_steps_prediction_track_\"+MM_line+\".pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "d10133d1-65bb-4509-a95f-2a02e91a05a4", + "metadata": {}, + "source": [ + "### Loading the IRF4 enhancer sequence with different motif modifications and calculating prediction scores" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "3e57150b-6c97-4390-b613-292ffabc6683", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "irf4_onehot = {}\n", + "irf4_onehot[\"wild-type\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"more_ZEB2\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGGTGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTACCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACCTTGGTAGGTAAAAGAAGGTAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACCTAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACCTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_MITF\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATAATGTAAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCAATATAACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_SOX10\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGGATGACAGCTTGTGTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAGGTATCTCCATGTGCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_ZEB2\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCGGATCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCGGATTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "\n", + "predictions_irf4 = {}\n", + "predictions_irf4['track'] = {}\n", + "predictions_irf4['scalar'] = {}\n", + "\n", + "for seq_ in irf4_onehot:\n", + " pred = models[MM_line].predict(np.hstack((upstream_seq,irf4_onehot[seq_],downstream_seq)))\n", + " predictions_irf4['track'][seq_]=pred[0][0]\n", + " predictions_irf4['scalar'][seq_]=pred[1][0][0]" + ] + }, + { + "cell_type": "markdown", + "id": "bd2f300b-62e9-4aff-850e-9df0b1ccab12", + "metadata": {}, + "source": [ + "### Plotting scalar prediction scores for the IRF4 enhancer sequence with different motif modifications" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "808e31a1-c802-4769-b5aa-0fb2d5cc37aa", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(4,5))\n", + "plt.title(\"IRF4-MM001\")\n", + "\n", + "for i,key in enumerate(predictions_irf4['scalar']):\n", + " plt.bar(i,np.array(predictions_irf4['scalar'][key]),label=key,color=\"C0\")\n", + "plt.ylim(3,7.5)\n", + "plt.xticks(range(5),['WT',\"Repr\",\"No MITF\",\"No SOX10\",\"No ZEB2\"],rotation=45)\n", + "plt.savefig(\"figures/chrombpnet/ChromBPNet_IRF4_mutations_prediction_scalar.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "82482b5e-cd26-4f38-a83a-ff53972677c7", + "metadata": {}, + "source": [ + "### Plotting track prediction scores for the IRF4 enhancer sequence with different motif modifications" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a004ee64-acb5-42c7-8360-c9ff5f9dd13e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "start = 0\n", + "end = 1000\n", + "\n", + "n_tracks = 6\n", + "fig = plt.figure(figsize=(10,0.8*n_tracks))\n", + "#plt.title(\"IRF4-MM001\")\n", + "ax = fig.add_subplot(n_tracks,1,1)\n", + "values = predictions_irf4['track'][\"wild-type\"]\n", + "ax.fill_between(np.linspace(0, len(values), num=len(values)),0,values)\n", + "ax.set_xticks([])\n", + "ax.set_title(\"wild-type\")\n", + "ax.margins(x=0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(True)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "for i,key in enumerate(['more_ZEB2', 'no_MITF', 'no_SOX10', 'no_ZEB2']):\n", + " ax = fig.add_subplot(n_tracks,1,i+2)\n", + " values = predictions_irf4['track'][key] - predictions_irf4['track'][\"wild-type\"]\n", + " ax.fill_between(np.linspace(start, end, num=len(values)),0,values) \n", + " ax.set_ylim(-5,1)\n", + " ax.set_title(key)\n", + " ax.margins(x=0)\n", + " if i!=3:\n", + " ax.set_xticks([])\n", + " ax.spines['right'].set_visible(False)\n", + " ax.spines['top'].set_visible(False)\n", + " ax.spines['left'].set_visible(True)\n", + " ax.spines['bottom'].set_visible(False)\n", + " \n", + "ax = fig.add_subplot(n_tracks,1,n_tracks)\n", + "rect = mpatches.Rectangle((250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([0,1000])\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['left'].set_visible(False)\n", + "ax.spines['bottom'].set_visible(False)\n", + "\n", + "plt.savefig(\"figures/chrombpnet/ChromBPNet_IRF4_mutations_prediction_track.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "ca118db1-804f-404e-967a-5850e72a8dff", + "metadata": {}, + "source": [ + "### Calculating in silico saturation mutagenesis scores on wild-type IRF4 enhancer by using the ChromBPNet model" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a968c0c2-bd6e-4173-b5b9-966336d051f7", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1500/1500 [00:57<00:00, 26.07it/s]\n" + ] + } + ], + "source": [ + "from tqdm import tqdm\n", + "\n", + "modified_sequence_one_hot = np.hstack((upstream_seq,irf4_onehot[\"wild-type\"],downstream_seq))\n", + "\n", + "irf4_ism = utils.create_saturation_mutagenesis_x(irf4_onehot[\"wild-type\"])\n", + "irf4_ism['Prediction'] = []\n", + "\n", + "for i in tqdm(range(500*3)):\n", + " modified_sequence_one_hot = np.copy(np.hstack((upstream_seq,irf4_onehot[\"wild-type\"],downstream_seq)))\n", + " modified_sequence_one_hot[:,807:807+500,:] = irf4_ism['X'][i]\n", + " pred = models[\"MM001\"].predict(modified_sequence_one_hot)\n", + " irf4_ism['Prediction'].append(pred[1][0][0])\n", + "\n", + "modified_sequence_one_hot = np.copy(np.hstack((upstream_seq,irf4_onehot[\"wild-type\"],downstream_seq)))\n", + "irf4_original_pred = models[\"MM001\"].predict(modified_sequence_one_hot)[1][0][0]" + ] + }, + { + "cell_type": "markdown", + "id": "0c773939-a66b-4ca4-8431-776d4c90e7ae", + "metadata": {}, + "source": [ + "### Function that plots saturation mutagenesis values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e176160-fe35-4d71-881d-8eb7a86a40fc", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def plot_mutagenesis_givenax_fast(mut_scores,ids_,original_prediction, fig, ntrack, track_no, title='Enformer ISM'):\n", + " seq_shape = (500,4)\n", + " arr_a = np.zeros(seq_shape[0])\n", + " arr_c = np.zeros(seq_shape[0])\n", + " arr_g = np.zeros(seq_shape[0])\n", + " arr_t = np.zeros(seq_shape[0])\n", + " mut_preds = mut_scores\n", + " delta_pred = original_prediction - mut_preds\n", + " for i,mut in enumerate(ids_):\n", + " if mut.endswith(\"A\"):\n", + " arr_a[int(mut.split(\"_\")[0])]=delta_pred[i]\n", + " if mut.endswith(\"C\"):\n", + " arr_c[int(mut.split(\"_\")[0])]=delta_pred[i]\n", + " if mut.endswith(\"G\"):\n", + " arr_g[int(mut.split(\"_\")[0])]=delta_pred[i]\n", + " if mut.endswith(\"T\"):\n", + " arr_t[int(mut.split(\"_\")[0])]=delta_pred[i]\n", + "\n", + " arr_a[arr_a == 0] = None\n", + " arr_c[arr_c == 0] = None\n", + " arr_g[arr_g == 0] = None\n", + " arr_t[arr_t == 0] = None\n", + " \n", + " ax = fig.add_subplot(ntrack, 1, track_no)\n", + " ax.set_ylabel('In silico\\nMutagenesis\\n')\n", + " ax.set_title(title)\n", + " ax.scatter(range(seq_shape[0]), -1*arr_a, label='A', color='green')\n", + " ax.scatter(range(seq_shape[0]), -1*arr_c, label='C', color='blue')\n", + " ax.scatter(range(seq_shape[0]), -1*arr_g, label='G', color='orange')\n", + " ax.scatter(range(seq_shape[0]), -1*arr_t, label='T', color='red')\n", + " ax.legend()\n", + " ax.axhline(y=0, linestyle='--', color='gray')\n", + " ax.set_xlim((0, seq_shape[0]))\n", + " _ = ax.set_xticks(np.arange(0, seq_shape[0]+1, 10))\n", + "\n", + " return ax" + ] + }, + { + "cell_type": "markdown", + "id": "09ecb49d-69bc-4d96-9573-c1b2de373963", + "metadata": {}, + "source": [ + "### Plotting saturation mutagenesis values of IRF4 enhancer calculated by using ChromBPNet MM001 model." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "b65f7620-c005-4a9b-bac1-7cd0a7e8068b", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ntrack = 1\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "st = 50\n", + "end = 350\n", + "ax1 = plot_mutagenesis_givenax_fast(irf4_ism['Prediction'], irf4_ism[\"ids\"], irf4_original_pred, fig, ntrack, 1, title=\"DNase\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/chrombpnet/IRF4_ISM_MM001_scalar.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d3938daf-3476-4af8-a72d-1ff0665465b1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ChromBPNet", + "language": "python", + "name": "chrombpnet" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_EFS.ipynb b/the_code/Human/MM_EFS.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6512ddcf9505248764d2264c4595137603e8a4ad --- /dev/null +++ b/the_code/Human/MM_EFS.ipynb @@ -0,0 +1,852 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5d3a1346-b58d-4637-89ef-eca128775494", + "metadata": {}, + "source": [ + "## This notebook shows how to design synthetic sequences by using in silico evolution." + ] + }, + { + "cell_type": "markdown", + "id": "33fa5e0c-a0b8-4439-85c4-c63bac338f98", + "metadata": {}, + "source": [ + "#### It consists of:\n", + "*\t\tGenerating GC-adjusted random sequences:\n", + "*\t\tPerforming in silico evolution and random drift experiments.\n", + "*\t\tPlotting the findings.\n", + "*\t\tPrinting generated DNA sequences in nucleotide letters." + ] + }, + { + "cell_type": "markdown", + "id": "95b60cb5-297f-4e3d-b15e-72322844ac22", + "metadata": {}, + "source": [ + "#### Luciferase values are in ./data/luciferase folder\n", + "#### Intermediate files are saved to ./data/deepmel2 folder\n", + "#### Figures are saved to ./figures/evolution_from_scratch" + ] + }, + { + "cell_type": "markdown", + "id": "758bb1fa-5053-4134-b1df-8f1e45979507", + "metadata": {}, + "source": [ + "### General imports¶\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "d9131ce0-69f4-420e-80af-53e290feac19", + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "eaa0b7be-f866-4501-b30c-909a3fb8e74e", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "126d6f8d-72bf-48ea-a210-e1a5bd9fe10a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "73c85453-0f07-49a9-8afd-5b847dd3b5fb", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "dc4aed56-8ae7-4cae-a859-4684bf78316b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4b16c2d7-6faf-4be8-abc1-4122cf6024fa", + "metadata": {}, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "id": "a528f921-6bee-45f2-8097-ca83e1c550da", + "metadata": {}, + "source": [ + "### This code:\n", + "* Takes genomic regions fasta file and creates GC adjusted random sequences\n", + "* Performs in silico evolution on random sequences" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "703a5c54-f47f-4597-a14c-11bdf78c2720", + "metadata": {}, + "outputs": [], + "source": [ + "# path_to_use_GC_content = \"./data/deepmel2/Genomic_MEL_regions.fa\"\n", + "# number_of_random_regions = 4000\n", + "# seq_len = 500\n", + "\n", + "# evolved_seq_4000_dict = {}\n", + "# evolved_seq_4000_dict[\"X\"] = utils.random_sequence_gc_adjusted(seq_len, number_of_random_regions, path_to_use_GC_content)\n", + "\n", + "# path_to_save = \"data/deepmel2/MM_EFS_4000_withmut.pkl\"\n", + "\n", + "# evolved_seq_4000_dict[\"mut_pred\"], \\\n", + "# evolved_seq_4000_dict[\"mut_loc\"] = utils.insilico_evolution(regions = evolved_seq_4000_dict[\"X\"],\n", + "# model = model_dict[\"deepmel2\"],\n", + "# class_no = 16,\n", + "# n_mutation = 20,\n", + "# rc = True\n", + "# )\n", + "# # save the final file\n", + "# import pickle\n", + "# f = open(path_to_save, \"wb\")\n", + "# pickle.dump(evolved_seq_4000_dict,f)\n", + "# f.close()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "afe9e054-7a5c-4d78-a196-c73a5bd431dd", + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/deepmel2/MM_EFS_4000_withmut.pkl\", \"rb\")\n", + "evolved_seq_4000_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "ac436024-0a98-4220-ad16-40f4e1ac14b1", + "metadata": {}, + "source": [ + "### This code:\n", + "* Performs in random drift mutations on the random sequences generated above" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "150c4398-10be-4568-aad6-17c90d29c1af", + "metadata": {}, + "outputs": [], + "source": [ + "# random_drift_4000_dict = {}\n", + "# random_drift_4000_dict[\"X\"] = np.copy(evolved_seq_4000_dict[\"X\"])\n", + "\n", + "# random_drift_4000_dict[\"mut_pred\"], \\\n", + "# random_drift_4000_dict[\"mut_loc\"] = utils.random_drift(regions = random_drift_4000_dict[\"X\"],\n", + "# model = model_dict[\"deepmel2\"],\n", + "# class_no = 16,\n", + "# n_mutation = 20,\n", + "# rc = True\n", + "# )\n", + "# # save the final file\n", + "# import pickle\n", + "# f = open(data/deepmel2/MM_RandomDrift_4000_withmut.pkl, \"wb\")\n", + "# pickle.dump(evolved_seq_4000_dict,f)\n", + "# f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9b689a46-e0b0-41d3-ae4b-df608bd943a2", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/deepmel2/MM_RandomDrift_4000_withmut.pkl\", \"rb\")\n", + "random_drift_4000_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "e5c0e2c0-19b7-4f49-be00-82f81c15465f", + "metadata": {}, + "source": [ + "### Reading fasta file" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "7742c2d8-3263-4016-84da-481c92bea69d", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "Genomic_MEL = utils.prepare_data(\"./data/deepmel2/Genomic_MEL_regions.fa\")\n", + "Genomic_MEL_dict = {\"ids\":np.array(Genomic_MEL[1]),\"X\":Genomic_MEL[0]}" + ] + }, + { + "cell_type": "markdown", + "id": "4034b926-7ead-46d4-9b85-bc17c1b5664f", + "metadata": {}, + "source": [ + "### Plotting GC-content comparison of Genomic and GC-adjusted random sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "688f486b-d03d-4b3e-b519-f353066e5b3b", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Average GC-content')" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5,))\n", + "plt.plot(np.sum(Genomic_MEL_dict[\"X\"][:,:,1]+Genomic_MEL_dict[\"X\"][:,:,2],axis=0)/len(Genomic_MEL_dict[\"X\"]), label=\"Genomic sequences\")\n", + "plt.plot(np.sum(evolved_seq_4000_dict[\"X\"][:,:,1]+evolved_seq_4000_dict[\"X\"][:,:,2],axis=0)/len(evolved_seq_4000_dict[\"X\"]), label=\"GC-adjusted random sequences\")\n", + "plt.legend()\n", + "plt.xlabel(\"Position (bp)\")\n", + "plt.ylabel(\"Average GC-content\")" + ] + }, + { + "cell_type": "markdown", + "id": "7168a4c6-5c6f-472a-bee7-f1705b3d50cc", + "metadata": {}, + "source": [ + "### Smoothed plotting GC-content comparison of Genomic and GC-adjusted random sequences¶" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "d9de05ff-2777-4600-8cd4-4cf303f35a3f", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def smooth(y, box_pts):\n", + " box = np.ones(box_pts)/box_pts\n", + " y_smooth = np.convolve(y, box, mode='valid')\n", + " return y_smooth\n", + "\n", + "plt.figure(figsize=(6,5))\n", + "plt.plot((np.mean(evolved_seq_4000_dict[\"X\"][:,:,1] + evolved_seq_4000_dict[\"X\"][:,:,2],axis=0)),color=\"C2\",linewidth=0.2)\n", + "plt.plot((np.mean(Genomic_MEL_dict[\"X\"][:,:,1] + Genomic_MEL_dict[\"X\"][:,:,2],axis=0)),color=\"C3\",linewidth=0.2)\n", + "\n", + "smt_val = 10\n", + "plt.plot(range(5,496),smooth(np.mean(evolved_seq_4000_dict[\"X\"][:,:,1] + evolved_seq_4000_dict[\"X\"][:,:,2],axis=0),smt_val),label=\"GC-adjusted random sequences\",color=\"C2\")\n", + "plt.plot(range(5,496),smooth(np.mean(Genomic_MEL_dict[\"X\"][:,:,1] + Genomic_MEL_dict[\"X\"][:,:,2],axis=0),smt_val),label=\"Genomic sequences\",color=\"C3\")\n", + "\n", + "plt.legend()\n", + "plt.xlabel(\"Position (bp)\")\n", + "plt.ylabel(\"Average GC-content\")\n", + "plt.savefig(\"figures/evolution_from_scratch/GC_content_Genomic_vs_Random.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "f28c30c4-5386-485b-8731-d5cc4cbd7405", + "metadata": {}, + "source": [ + "### Plotting prediction scores at each mutational step for both random drift and directed evolution" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "3bdf7398-2250-4e02-a37c-377884198709", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "c=\"C0\"\n", + "_ = plt.boxplot(evolved_seq_4000_dict[\"mut_pred\"][:,:,15],notch=True,showfliers=False, whis=[5,95],\n", + " boxprops=dict(color=c),\n", + " capprops=dict(color=c),\n", + " whiskerprops=dict(color=c),\n", + " flierprops=dict(color=c, markeredgecolor=c),\n", + " medianprops=dict(color=c),\n", + " )\n", + "plt.plot([],label=\"Directed evolution\",color=\"C0\")\n", + "\n", + "c=\"C1\"\n", + "_ = plt.boxplot(random_drift_4000_dict[\"mut_pred\"][:,:,15],notch=True,showfliers=False, whis=[5,95],\n", + " boxprops=dict(color=c),\n", + " capprops=dict(color=c),\n", + " whiskerprops=dict(color=c),\n", + " flierprops=dict(color=c, markeredgecolor=c),\n", + " medianprops=dict(color=c),\n", + " )\n", + "plt.plot([], label=\"Random drift\",color=\"C1\")\n", + "\n", + "_ = plt.xticks(range(1,22),list(range(21)))\n", + "plt.legend()\n", + "plt.xlabel(\"Number of mutations\")\n", + "plt.ylabel(\"Prediction score\")\n", + "plt.savefig(\"figures/evolution_from_scratch/EFS_vs_RandomDrift_PredistionDist.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "0c95e53a-8d92-4217-9ebf-53e5908e7dbf", + "metadata": {}, + "source": [ + "### Plotting prediction scores at each mutational step for selected regions" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "ee7dc150-50cc-4257-b0ad-23110e3aad8c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "for k,i in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " _ = plt.plot(evolved_seq_4000_dict[\"mut_pred\"][i,:21,15].T,label=\"EFS-\"+str(k+1),linestyle=\"\",marker=\"o\",color=\"C\"+str(k))\n", + "plt.legend()\n", + "for k,i in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " _ = plt.plot(evolved_seq_4000_dict[\"mut_pred\"][i,:21,15].T,label=\"EFS-\"+str(k+1),linestyle=\"--\",linewidth=0.5,color=\"C\"+str(k))\n", + "_ = plt.xticks(range(21),list(range(21)))\n", + "plt.axvline(x=15,linestyle=\"--\",color=\"gray\")\n", + "plt.xlabel(\"Number of mutations\")\n", + "plt.ylabel(\"Prediction score\")\n", + "plt.savefig(\"figures/evolution_from_scratch/EFS_SelectedSeqs_Prediction.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "5f62d9e8-9abb-442f-aac2-283c27ef5d16", + "metadata": {}, + "source": [ + "### Loading luciferase data" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "87146796-0e65-45fd-ba25-56b453169fdf", + "metadata": {}, + "outputs": [], + "source": [ + "luciferase_dict = {\"ids\":[],\"values\":[]}\n", + "with open(\"data/luciferase/EFSall_IRF4_TYR_MLANA.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " luciferase_dict[\"ids\"].append(sep[0])\n", + " luciferase_dict[\"values\"].append(sep[1:])\n", + "luciferase_dict[\"values\"] = np.array(luciferase_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "markdown", + "id": "383afa03-d8b6-43d7-89b1-fc8fad1155c5", + "metadata": {}, + "source": [ + "### Plotting luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "a3dc1ebf-29eb-4c48-b8b9-96450c9a679a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "mean = np.mean(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "\n", + "index = np.argsort(mean)[::-1]\n", + "temp = sorted(mean)[::-1]\n", + "res = [temp.index(i) for i in mean]\n", + "\n", + "plt.bar(res[:10],mean[:10],color=\"green\",label=\"Evolution from scratch\",yerr=std[:10],capsize=3)\n", + "plt.bar(res[10:],mean[10:],color=\"red\",label=\"Genomic\",yerr=std[10:],capsize=3)\n", + "plt.legend()\n", + "\n", + "for i in range(13):\n", + " for k in np.log2(luciferase_dict[\"values\"][i]):\n", + " plt.scatter(res[i],k,color=\"black\",zorder=10,s=8)\n", + " \n", + "_ = plt.xticks(range(13),np.array(luciferase_dict[\"ids\"])[index],rotation=90)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "plt.savefig(\"figures/evolution_from_scratch/EFS_SelectedSeqs_luciferase_withdot.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "fd48fa19-2d6e-445d-a82c-bbd5266c7244", + "metadata": {}, + "source": [ + "### Plotting contribution scores of random and fully evolved sequences." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "716ba2d6-3053-42d6-8747-bfc26b654499", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0,1,2,3,4,5,6,7,8,9,10,11,12,13,14," + ] + }, + { + "data": { + "image/png": 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l+bOnAGH437L/afhLw1VcWRxWeW/wl6RGzzvrqqiQpk41wVUffijNnRvGREAt6N13pXXrzIX4fv3Med9xx5nnUlL8E35cfrn0+uvRqxfQXlVXm/PGtLQwN3AFTGCUeXRcTxzy5vI3VVpdqr/P/nusqwIAAACgjbpr6l16Yt4TuunLm2JdFaC+nd/UXl/2SJnDpONeMdep7QGDU22147d6nR6TKsYFd7W09C75xrINvUf66WypY8CEsLYkaehfpHNWSMnpMakmACC2bDaTJej225seI13vOY9b2vgf6YuB0g83SbkfSDunmMDjH28x6ze9GuYALgChrN69OmSZtYUm6+3Agf51e/dKa9Y0vk1hocyBoPMg/8rd3wX3retIdpjAB++9tubwWP4b8dO3TG+iJBBdBH/Fo23bJPkHxCUFzE4eGBCWnCx1q81kuHFjGMFfdoeU1tMs78+rP+t5apZkD3c0AVDf9u3SrbdKBx8sjRkjXXCBdOqp5vGf/uTPBBW2rKwIRrjUSksz2x2AaVum+ZZnbJ3RYJlFOxeF3E+Fs+GsYXFj6V/kawaGPy4deb/pENmTTWfJnmwuOB56szTswYh2vXOnf/nYY/0zcADt2eyc2UGP6x4/AjN2rlnjzwLWpNQsf+a9wvnNGrxXWio9+6x0003Sr34l3XKL9OabTb/+dROv0z9m/yPi1wKAePO/pf9T2j/TgoIsYqYiX5p/vfTV0dLqR6WC6dLeBdL2idLi26TPB7TLi8srd60MCo6WpHnb5kW3Et7gL08jwV9AC7jx8xu1fNdyfbH+i5BlPZZHUzZP8T2u24+sq6LC9Oeys6Wzz5auvtoEWJ1yij/4Kho++sh/bvfmm1KHDubaVF0OR9wn7AXahJoa0y0IO5O6OyCQ2dG5VerUUrw3yXbt3yWrnfV9AAAAgLiTlyctWRL8M3mymV1m8uT6z+XlxbrGYfl+2/eSpB/zf4xxTYAGFMzwZyEY9WLTZW0JPJiiYLpUsV2Sx2RgOfoRs77uPXFbktR5gHTk36JeRQBA7Lnd0tixUseOEWzkcUqzzjFBXs4Ss86qTQFkuSVZkmu/CQ6z2RrdDYDwbdq3KWSZ+dvNxMGHHRa8fvp0c1+sLqczIDNYxhBJtXEPe773j6kMVBuwlZzkD/5q7p/48oLlvuWvN37dvJ0ArSCBzyDj2N69KqwoVG5JriTpkMxDfE95L2B5eQeSh5X2UJI69Tf/VzRwwa5TtnT+eulni6XREyKsNBKZZUn/+Ic0YID00kuqlyqzulr6979NMFhD7p1+rx6d82j9J7KzpfXrzXTi3p8JDfxuTpjgf379+oZHmVmWVFMi7d9m/m9iYMnkjZN9y19t/KrBMqt2h8785bE8qnRWhiwXExX5UvFySR6px0nSkD81flHR7pB6nxXR7quqzKDApCQpM/OAawu0Cd9u/bbJx4HBXwsXhjmAL62npNpZJPb+2PBJSyP27ZP+/ncTgHvXXdL//mcyRLz6qnTddeaY/fbb9Q+Hu/fv1psr3tTfZv2NQXgA2rzH5z2uane1nl/4fGwrUrpR+mqYlPO2JKv2wnLtMdZ3cbm0XV5cDszyZa/tb87MmRndSthTzf/eC/tAC3N5XPLU9tkmbZwUsvySnUtUVlPmexwYCFbXvHnSIYeYCVX27q3//IYNDW9XVSW9/LI0bJiUkWECtXr3lm68UdrUyHX30upS2R6y6Zcf/LLecy6XNHOmyTR2zjnS6ac3HPjlFXKCIgAhJSWZboE73NPAwOCvpNSGy+zPM1ml9y2RdkyWtr4j7ZnfcNlWUu2q1vJd/htm6/euj+rrAwAAAAklL08aPFgaOTL457zzzOwy551X/7nBg+M+AKzSWamd5WY20v3O/SqrLguxBRBlBdMkyyllnSAddEqTWQkSWsF0yeYwY1WOHe8brNsgu0PqdUb06gYAiCsnndRwYEijFt9u2hmvzoOkox427c3Rj0jph9c+wbgooKXkl+WHLOMNqOrdOzgvyLffNjyWMikpID6i86H+Mc6uMqngW8lTZ7B67d+0N/grN7fpe9pN+XqTP+Br0oZJjKNE3Ig8fQSiYuH2hZIkm2wa1XuUcopz5LE8WrB9gTyWxzdoLjtbWrXKpDXMywtjZuXOA6R9P0j7cxt+vlO2+UG753SahrElMjI9+qj0t4AJdjp3ln72M5Nud+9e6euvpcrKhjvgpdWlenze45KkP5/4ZyUn1Wlps7ND/2IPGSIdc0zDz9UUS5tfldY+I1UFpKPq0Ec6/A5p0I1SSqZvtcfy6Mv1X/oef77uc/3n5/+Rrc4g3I17NzZdp1pLdi7RSdknmT/QwkL/Ezt3SsXFZjkz0/RmJCVblv545plS165KDqPXkZycrD/+8Y++5bAV+LObacRTphPUVEYhy10/W2ATKivN71akidtaQqdHO6nCWSHP3zz1vrdIRPrZNvu7SETerH5VVaHLerVAVr/W9s2mbySZttuSpW82fSPLsny/hz16mL8Lj8cEf4XidErJ6UP8K9wVUvFqKfPIkDPA5eSYCx8FBeb1pPr/5+dL48ZJ11wTvO1n6z7zLS8rWKYRvUeEriyANise27uWqpNlWdqw10RFTN0yNaxtGtOxY0ddf/31vuWI6uQpk2acYQKPLLfJQjXoRqnfL6TkDKlim7TheWnXTLXHi8tz8ub4lvul91NuSa427N2gfZX71K1Dt+hUwtHB/F+x3QyMTyLjNVpW4EQ9kzZMktvjVpK98fOnutkIJ2+crOfOea5eueXLTaavykoTsG+zmXPtww4zwVjz50tLlyZr6tQ/avJkc+yxLNPHe+QRcz5us/mD/QsKTMau119P1k03/VGPPhp8DPRmLft03af16rJ0qVRebpZ/9avavmoLNgPtuT0Cmis11fwNV1eHuUHQNZAG+hT786QvB0ueBs7Fx34v9RjdnGpGLLBvIJmJlw7POryR0gCAaPJ4TLuTltbu5iVBHKB/DcRIYWFk9+MkU76wMK7TetedXGralmn6xZBfxKg2aCntpq2o3ieVrDbLvcaGHouRyHZ+bSbLO2iMlHFE6PJ8lgASUHPau7htIyOQnJysvn3/qD//WXK5knXaaaEn2fa97/xvlLz0IclmSY7O0vDHpUN/J3Pd3JJkk4beI21+Xcpp20kyEvn3o130G9uZwsrCkGW8EwLabNKgQdLq2m7zN9+Yie671RlCUl0tzZhhJsBXl0PNBAtem15pNKnFQem7tbc8Sxs2NP8655cb/OPId1fs1opdK3R0r6Ob3Oa9le/pyk+v1J9P/LOeHPtk814YCIHMX3FqwfYFctgdSrIlaVjPYRqQOUCSVFZT5hvAKEl9+/oH23z3nRl80xiXS1KnQyTZpZoic8M/lC6SIm3r2sAA/UTk8ZggrJ//3Mz4nZJifnd69ZL++tfmT941ZYp0//1mOS1Nuuceads26aOPpFdekT75xDy+4w7J0cA1GO/gMql+lpwDYlnS6seliX2kpX8JDvySpMp8s37KcUHR30t3LtXeSv906gX7CxrM8rWtdFtY1Viyc0nDM6p5Z1OrM6OabdQoZZ5yijJHjZJtW+jXsNlsyszMVGZmZmSBTjunmhmUUrOk7seHvkAWQeCX5J+VOtqzvRdWFKrCWSFJWlqw9ID2Feln2+zvIhGFk9UvMKNfU1n94kR+Wb427jNBod6B7AXlBb51kgn86tHDLG/dGhwP2pDkZEnpgxXUXdv6Rsi6FBUnacwYafduc+zv0kW6+25pyRJp82aTPeK668zfZ0MTUny4+kPf8idrPwn5egDatpZs73aU7tCHqz5UaXVpXNRpUf4i33KNu0ZbirY0+zXsdruys7OVnZ0texizJ/j2n5Eh2483S5U7TeBXzzOlC7ZKo56Xep4hdR8l9T1fOnOGdOYsKTVKwVBRYlmWZuXM8j0+ru9xssl83nWzWreqzoNqLwJaUtnm6L0uEsbn6z73LVe6KjV/e9NZdL7e+HXQ4y1FW5RbHDxJT1mZdNFFZryVx2NOG1etkr76SvrXv6TnnjPd5EmTbOrb1xzPJJv++Efpzjv9WcI6dpROOEEaM8ZkfnW5JMuyafHiTHXrFnwMfG/le77lnOKcoPp8+63//O7ss1s28EuKz/OveKwTEot3Qp3ScLtW9oBsX+4GIsaqCxsO/JKk8i0Nr28FkzdMDnoceG0QABB9hYXSE09I/fubPl7Hjub+0XHHSW+/HXm8ANCYttS/tixLtodssj1kY1ZnIE5N2hCceb3ueQbaprbUVjRp92z5JmXpeWbIST0TVmWBVFqbDbzXTyVPEwPevAj8ApCAmtPexW0bGQGbzabi4kyVlWUqJcWmI8KIEbbZbMrMSFfmujtMsIctSTrlUxP4ZXeYTJz2FPO/zS4NvE4aWX9yxrYkkX8/2kW/sZ2pcoW+kJhX4h+oPnSoP3lJTY306qu1cQ61nE7pnXf8E5Sqy6HBO9vxhVS1yz/+2+Oq7YtLRxy8WnabW+vXN++9FFcV64cdPwStC8wE1piXF70sSXpp0UvNe2EgDJxhxqPu3TVv2zy5PC65LJeG9hiqo3oe5Rskt2D7Al/Rvn39m02d2vTgm6QkmaxeVu2BrmBa6JPnLElPS5oxod0M0E9EU6eaQV7nnmuCtbw36zweadcu6cknpVNOiTA1rkxDe+21pgF2OKSJE6V//tMksgrUrZv09NPmubreXfmub/n9Ve9HVoHGWJa09C5p+b2Su1KSJXU5TBp6r5nJYei95rFqZ3cIuED01cav6u2uoXXVDQ2iaUB5TfmBzajWGiyPtPMbcyzo1ToXG9PSzNcQ7RvDH63+yLf8zop3ovviiEx2tsnY5/0ZMiT4eW9GP+9PnLcrM7bOkGSyfg3JGiJb7b9vtwQHtfbp41+ePLnpoG2PR1JSqtSpv3/l5tclT9PHn+tvPUQ7dphj9C9+IW3fbjI/DB8uDRwoHX+89L//mQC0w+tMrl5UWRQ0SP+DVR80+VpAa6moML+7W7eaweuMsWgbTnvzNF3+yeW6e9rdsa6KpPoBrJ+urZ/JptUVr5S2fWwCv7qOkE6bJHXoafpf3ouK3r5ojxOlUeOjX8dWlFuSqz0VeyRJfbr00YheI2S32eWwOzQvb170KpI+2L9csjJo8gfgQFmWpY/Xfhy0LjAYrK6y6jIt2GGu62R19E+cM23LtKByjz5qJlJxu81595dfmjlFpOAs3mPHmr6dJD37rPT882a5WzfpH/+QduwwGcJmzZK2bDHXBE491T9hh1dxVXFQlsTAcyvJ7MPjMf3Hgw5q6hMB0FI6dTL/5+SEmf0rMLOls6w1qtQiPlv/mSTJXns9am7e3AOePKC9sixL+yr2+SY6AoCW5HRKt91mrlf+9a9Sbm7t9UiZ64qLF5t+6LHHBg+6ABLB4p2LfcsLdyyMYU0ANMSyLN+1F3vtkKfP138uj+WJZbUAv7INZrC5PUXKGt1ugr88HpN14eqrpaOOMpMHDBsmXX65ydRQ93pjSLUDcyVJfc6JeEJiAED7V1Fh7oelp0cwAX3hAqmqQJIlDfmLGRvZWPCw3SFlHtlS1QUS2vbS7WGVKygv8C0fdljw3/bzz5sJUt1u0/d0Os24c5/OdYK/PE5pzi/9j6t2S6sekSQN7r1eSXa3du2S9u+P9N1I0zZPq3eOWXcSkrpcHpdm55k+bllNmYqriiN/YSAM7eMMs51x9+0TdCF5aI+hOqLHEXLYHXLYHUHBX/36+QeOT5nS9H5tNtVm/qodPbtrloliDyVL0tFD2s0A/UTz3nvSOeeYQWOS+XoefFD673+lF16QrrrKBG517x46NW5dM2b4M8s8/LB01lkNd7RtNtMRHzs2eP2+yn2autk/uOzjNR+HFf0d0sb/SOueMcud+ktjJknnr5eOelgafIf5//z1Zn2HPkGbfrGh/mzDgek7fWr/jJJsSbps6GXafsd2309qUqrvObcV2RUud1KSpo4dq6ljx8rtCX2B2u12a+rUqZo6darc4V5NqymSavaZ5Z5hzqAUobQ083tRXR3dG8NvLX/Lt/z2irfl9kR6hdEv0s+2Wd8F2o1vt3wru80uS5ZO6neSrNqDxPQt04PKHXqof6DuN980HrTt8cg/80TXo+XrsjlLpC1vBP/dBgxgX7XtCH3+dabcbum006QPPpA6dzbHZm+Mgfc43auX9FKdSSa+WP9F0HFrU9EmrdmzJrwPAThA1dUmY+j555uLd/36mYDFrCxzwv/YY/7+DFpOS7V3TrdTm/ZtkiR9sPrAAkdbok6WZdULYA3MbBjpa9TU1OiVV17RK6+8opowZkzw7f+rT+RWssm4evJH5v/GbmDak6Uug0Luuy2ZmzdXkgmOHt5ruIb1HCa35TYXvXJnh9i6BaUHRDuXrpOvM++VmiXZ01RPSuaBvW7xKmnZPdLUk6XJR0pfHyPNvlDa+rbkLA+9PdqENXvW+GYoS6r9+/547ceNzg4/K2eWXB6XbLJpZO+RkszfyDebvvGV8Xikt94yF7aPOsrMcmZZDZ9v2+1uzZ07Ve+/P1V3322OZ336SD/+aDJzZ2QElz/9dGnGDLcuuij4GPjZus/kCuhXvrMyeDKNfftMHY46KoIPJwLxeP4Vj3VCYhk82Fz39XikdevC2MDR2b9cvKxVrvccqI17N/oyC/ZL7ydJcltuTds8rYmtEteHqz9U96e6a8C/B8S6KgDamepqM1ngCy/47zGed54ZYPHaa2bCwOHDzfrkZHMPCThQbal//b9l//Mtv7Hsjai+NtDisrL8aYXDlZZmtotTq/esVn55viSpd5fekqS9lXu1ZOeSWFYLLaAttRVNclVIsksp3aSkCAfhxKn//c8Ee515prn/vHKlmTxg1Srp00/NmKTjj49wbEjVbkl2c9+k6/B2EyQHAC2tOe1d3LaREXC73XI6p+qMM6aqY8cI3veUyZpaeLbctg7SkfeFbl/aePuTyL8f7aLf2I5s2bclrHKBSTcOOyx44vzt26ULLzQJJ2pqzCQDQZm70g4KvhcmSXvmSd+eLi2+Q/p2jOQsNvvuvUFOt+mLb9oU+fv5apM/YUjvzua8c/72+SqpKml0m7pJAj5Z80kjJYED07ZbrnZqxtYZvtk8bbLp/hn3a9qWaXJ6nHJ5XPpojX/25ZEj/dvt3m0G9zR0Mu121x7AOgYEZu382sxAj3Zr5kzpmmvMIJFu3aTPPze/B/ffb2Zs/O1vTeK2/Hzp0ksj3/9775mbfl27Snfd5Q9oaEzdjKmfrv00KMhgv3N/0IC3ZqkplpbcYZY7HSKdtUDqfZZ5bHeYi2ve2Rx6nyWd8KZv08KKQi3ON7P59e7cWz069pBkGu26Udg7ynaYXdrsGth1oPqm9/X9HNTpoNr3a1NucW5EF9Xddrvmn3SS5p90ktxdu4Yu73Zr/vz5mj9/fvgdU1fAQNOOB4cXBBqhLl38WVqamzo1UjnFOb4Z9CVpT8WeoAxGkYr0s23Wd9FCLMvSvxf8u14HEtFhWZa+3vS1b7aHi4ZcZNbL0vQt04OCEEeN8h8Lp05tfPZ2yzIBtpKkzGHBFxvWPSt5aiSP22TyC/DOvKuUlGQpOVl6/31/8G1DHA6pQ4fgdYGBEV4fr/m43jqgpc2ebYK9LrlE+vpr/+yA3r8Xb//l5JObzpiHyLVUexeYKbWoqkgrdq2IaZ1W7V6lnJIcSVL3Dt0lST/m/6gdpTua9Ro1NTXauXOndu7cGXbw1/z58zV/k11uj6ReZ5jArsZmFfNqZzNbzs2bq2R7shx2h47uebSGHTTM99yP+T+2zMQP4UjtLiVnmuXSdfX7v52yzeQQo+tkue7Qu3mvl/+NCfb6api09mmpcJ5UsloqWirtmCzNv1b6eoRpz9Hmfb7en+VrUDcTwJlTnKN1hQ1HakzdPNUXJDZ2oJkhxZKlqZun+vqNCxaY83RJuvde0x7WPZ/2crvdWrBgvtavny+Hw63kZHPu369fw4N0k5PNNpYVfAwMzMotSct3LfcF9UpmljXJn4mopcXj+Vc81gnt033f3qdXFr1Sb/0wf7OppUvD6Ad3+Yl8l/uLlikeL/1P3jjZlyn7+L7HSzLXvydvnBzjmsWnF398UZK0e/9uldcQOA6gZViWdN115tqjZZlJeHJzTabZm24y95Ruv91k/vrhBzPIF2gJbaV/Xe2q1oQV/usD76x8R5XOyqi9PtDisrPNzdrFi/0/E+pcA5swIfj59evjesLfSRsmyS570MQ6dps95CzsiH9tpa0IyV0h2SQ5OjZeZn+etG+JuV689R1pz/yoVS8SlmWyxf7mN2aCRptNOukkk4Hh1VelZ5+VzjjD3I/2eCKcNMC139wDd3Rq/N5I3c8pjj8rAGgtzWnv4raNjIDb7ZbDMV+jR8+XyxXm+3a5NH9ziuYXjZb7oDNNGxMlNTVm3MtHH0nvvmuus3jv9bWmRP79aBf9xhiqrpbmz5e++sr8fP+9Cbpqrn1V+4IeT7l6ilb9fpVW/X6V/nzin31Zm6td1b4JSY84ov5+5swxE4Z37ixNqnuKZ7NJGUPrb7RnrrR+nFTmv7d9WK8NvuVFiyIba+axPEHnl2P6j5FNNnksj6ZtaXwyw7dXvB30+M3lbzZSEjgw8XcHGPpkrT/a05KlT9d+qh92/OBbt69yny/14RFHBMeU3H9/wyfTSUnS+PGSOveXucogqXqvyf51AJlxEL+8F2EsywR+zZ9vZtux283vSEqKP9NXt25mQFkkvNk5XC7p4osjSK0boO5M4pL03sr3It9RoNz3/DMbn/KplNqt8eAme7KUku57+M2mb2TJkk02nXLIKTqp30m+RjswQ1lxVbH2O00uULflVs/OPYN226tzL0kmjefW4q31L6rXvaAu+S+qz53rX9evXzM+AL/nFjyn/uP6a2vR1uAnXAE3qRo7yfFeRGvmBccjAzIiz58fnYH6dQcrStKElQ181u3QtC3TdPuU2/XTt39aL90sWt/GfRu1a/8uSVKn5E46ru9xvuDR0ppSLStY5it7/PH+oJZ9+8wF8brnlJYllZaaWdMkSRlHSFZAZHfZRmnm2ZKzyFwUX24O4B6PTW/NvVZut03nnCP17Bn62ByYeay0ulRTt5hjXbe0br71B5rBBwjlgw/MjaG9e012kt/9zkxo4M1ysHu3NG6cGfzavXvjGfMQW68sDh6w/NqS12JUE+PTtZ/KVnveM6rPKN8g48/WfRabCmVfFpfZN1rb2yveltPjlNPj1H+X/Fdj3hjj+15cHpfeXv52iD20oPTB5v+CGfWCpyWZALCMIfXXR2r1Y9Ksc6SSNeZ8o8/PpdFvSmdMk8Z8KQ27X+pyqJTcRbK3j1lfE13gNZwz+p8hu80uu82uL9bXzyotmcAHt+WWJUunHHKKBnYdKEkqqynTovxFkkzb6HBIHTua2c3CHTThdpvyo0ZF1l7urdirGVvNzAPefqwkfbTaP/mQd3KPxoLQADTPjzt+1KNzH9XvJv+uXnDPkCH+yTxWrQo96ZIcHfxZRIuWSfY6J4SNZbqUDjzbZZi8x0ZLli4YfIFv+Yv1X3A9o46c4hzNyZvje/zOivrXUQGgOX74wUwa5fFIl10mffaZyRwrmXtGycn+vuSIEdKbjFFAgvlyw5cqrS71PS6vKQ+a9ANok7KzpWOO8f8MqXMNbMiQ4OfjOPBLMtnLPfLIkqXzDjtPkhmcF7Nrv0Bd9hTJUuOTf+3Pk74cLH0zUpp9njT/amnaiXEZ1HTvvSY7rGTu5W3dKs2aZcYiXXutdMst0pQpJkvDmDER7tx7/7uxSfMa+pzi+LMCkBgKC6Xly80kfitWSMXFsa5RYti/P8yCVbv9y33Pa/X785ZlJje++mozluW008y1lquuki64QOrbVzruOOnll/332YBY8njMmO8rrjBjxk88Ufr5z83PSSeZdbfcUn8sYzi2Fm2VPWBy+1MPOVVHHHSEjjjoCI3oNUIemXtAlixtL90uSRo6tOF7Xx5PE3XoOlyyhb4Rflhvf/DXl1+Gvnce+HrLC5arsKJQkjSo6yCd3O9kSVKSLUlfb/y6we331+z3jRtIc5h7cXPz5vrea0xV7ZG2TjBjWVb8TVr9uJT3seQsDb0t4hLBX3Hoh+0/BD22av8Fen/V+5LMAKBRo/zrp06Vvv02ONDC5TLBF7NmyQR6ZAZMG7vljfoDAdAuLFxoBoZ4PNJzz5nZGVtysPSWLf6Zvy+5xLxOJArKCzQ7Z7Ykk2WrU7IJQvpi/RfaXxNuj70BG182/2edIHU7JnRWq4DnJ2+crCRbkmw2m07oe4JOOPgE2W12OeyOoGwWucW5vmWP5VHPTsHBX3279PUNat1SVJvONPCiet0L6pL/ovrw4eG/1ya4PW79ccoflVuSq7/N+lvwk0kBA31cDXzWgRfRmnnBcehQf3Dh4sXNCw6MhGVZenOZ/y609/fpw9UfJsSMjA/Pfti3PHHtxBjWJDH958f/+Ja7deimB2Y8oIzUDP/zi/zPjxwZfNLy+OPmWBp4km9Z0oMPSuXecX/djqn/onvmSZ/0kD5Kl3aZgbortw1TflFfSWaG3kiDLidvmCyXxyWbbBo7aKyyM8zNvTV71mjj3o2R7QwI05Il0pVXmt/7YcOkNWvMTaQRI/wD3Xv0MBcXliyRbrihzg6q90o570sLrpemnSJ9fYw09WRp3tXSlrekyoKov6dEtKN0h77eZC5wJNf2rd5Y/kb0sjo14IPVH/jOoS4cfKFv+cM19TMcRkWfc1sl22o821q01ZfRWjJZdnNLcoPObSeui2K/JfNIyeaQqveYdrQ1JkFZ96y0/K9mufdZ0sX50pjPpUN+JfX6qQkEO+J+6fyN0vAnW/71EXX5ZflasnOJJHMOcuHhF8pjeeSxPEFBYV4b9240E4TIXBzul95PI3uPlL32nzcowpvV/ac/rZ+pNZTrrms4I3xTJq6bKI/lMf3A2mxkUvCELem186aUl9fdGsCB+Od3//Qt/3fxf4Oe69BBOuQQs7xgQZjXVroda2bLLlpe/zlvpsufLQ7OdlkoaUOx6XB7fyZPlt55x/wfuH7JEikvL+L3KZmB03Py5vj6Auf85BzfBEp7K/dq6c6lzdpve/XSopeCHo9bOE4WIwQAtIAXXzTXXHr0kN56y6xrLMDY4QiegBJIBP9b+r+w1gGIjb0Ve30TJyfZknTpEZcqJcnclF6+a7l2lu2MZfUAI6mjJKvxwZTVhZKngfsn5VtatVqRysmRnqy9jH3RRWY82sEHm8feCQO8Y0J69jSTnkbE+zm5Khp+vrHPSYq7zwpA+7Z+vfT3v5thfT16mKF9o0dLRx9tAn5OOskkZeDSXevZv9+MVQ3JVeZf7vyThu/Ph5gQv7hY+vhj6cYbTWKO7GxpwAAzRvvuu6WZM02Wr9JS6dJLpXPPNZM61tSYxAz33GMSePz2t6bdXLRI+u9/mVyxWTwuc19/xd+keVdK310kzb1cWnyHlP9NrGvX5niD9S+5xASAeTzSeeeZoP4//tEELErmd7Y5Y323FG1RUm021y4pXXwBUJLUu0vvoLLeZBYdOphx7RHJGBY8iX4junUuUmbHIkmmH1sZwRDirzd9rSRbkpJsSTo5+2Qdf/DxsmTJbbk1aeOkBu/VfLH+C98YqeG9hvvWH3AylObyuKVNr0hTjpc+7SnNv8Yf+LXiAWnupdLH3aW5V0gWCYTamkgSLiNKcktypRATgE/ZNEW3n3C7JBN9u3Chf5D3HXdI8+b5OwzV1dL//V/Axr3GmlnILZeU8470k5ul7scFd3aYabVF7KvYJ7vdrsy0zKi/tvcGXrduZkaBls6SUVLiX87OjjB9u6SP13wsSbLb7Dr70LO1Z/8efbXxK1W5q/Tlhi91xZFXRF6pih1Sce3gloG/MbM3hDnItsZVo0/XfCp3bUO2eOdieSyPeWyZAcSvXvCqHHaH+RsN4B2oEvjYYXfI6XFqR9kOWZYlW5R78IGZeiasmKDHz3xcfdNNUIgcnf0FK/Prf06hLqL1GB3y9ZOTzSD+xYtNhzDk7NQyAxQj/T3yWr5ruTbsM9H6h3U/TEOyhuiL9V+owlmhSRsm6dIjLjUF8/LMNCyBdu70T8WSmSn17u2vUBswN2+u5m2b53v80OyH9Ishv2j53znLI5Wuq/39qJGSOkidD5U69Ay9bVtleUx7uW+R5Ky9QODoJHUdIWUe5Que/nC1P5BgR9kOPfX9U75jiWSyz7x6wauSTEriwYOltWvNcyUlpo1+800zg4TdbmbffemlgAx6nQdJji7BFykasKfMn6Xh2GMjP+5/uOZD2W12WZalMYeMUcfkjnpr+VuyZOmTtZ/onpPviWyHQBgefdT83vfqJc2eLXXq1HCb4f19/sMfaleUb5UW3y7t+FKSZQI60nqaTDrVe6W9P0i570gd+5kgi6TUKL2jxPTGsjd8g3hH9h6pBTsWqLS6VBPXTtSvhv0q6vXZuHej1haaA22n5E66ctiVuvXrW+WxPJqTO0eFFYVKd6SH2EsLS85seP3+PNO2SlLlTqmmWOo8MKz+VrwLDMxvzOL8xVGoSa0ugyVv4NmWN6QeJ7fs/mtKzMUySTr4QumUT3wv5+tr22zmeCVJPU9r2ddHTHy5/kvfxB+j+43WSf1Okt1ml8fyaFH+Iu0q3xWUKfqh2Q/5lt2WW32e6RO0v+cWPqdHznzEd77du7e58B7O+ZRkzqd+9rPIL8h7syhbsnTx4Rdr6papKqwo1Oo9q7W+cL0GZw1W167mV3jlysj2DaBxq3av0hcb/FkCH5/3uG459halOvx91+HDpdxc6fvvpW3bwkgS33W4lPe+VLNPKlohZR5hgsG8OmWbH69CSXdJcl4dfsXT0syIhwizAby25DW5POZaS7cO3fT60td1UMeDtKvcZNJ+/ofn9cZFb0S0z/aq0lnpC/5KsaeoxlOjdYXr9F3udxrTP9Kp1AHAb+9ek/XL5ZJ+8xvTfwzV1yQDOxJJQXmBvtlsBpBldciSI8mhgvICTdsyTTtKd/jvswGImdeWvOa7Ft23S19N3jBZ2RnZ2rRvkyTplcWv6MHTHoxlFQEp7SAzgNJZKpVtlLr8JNY1apbnnjN9xQ4dzKQBNlvjfUe73QQ9RDREIbmz+ZzclVLVLnOfDwDiiMtlJm5+4gnzOClJGjtWOv54qWNHM9Hz3LkmKUN1tZnQFq1n5kxzfbzJ6xTugPGOjgZms/FOiN/AuMiS4xfqgX8fpxdfNPfmHA6TuatvXzOea/Nm6ZlnpPfeM+O6fvpTad06c7n84YfN99+pkxnDbVn+ay7z50vjxh3w208sNUXSyoekza9JrnJzj8OeKjk6SO4a03dwvyjpvljXtM3YuFE65RRzbbBrV+npp6Vf/cr087wZr5KSpKoqadq05r3GlqItctZm2wu8Py6Z5CB1y54+4HRJJoA2Ly+Cobo9TpQUXrTtYb3X64fNJ6iy0sx3+OtfN34M8Xj899hf+OEF39jPZQXL9I/v/iGbbLJkaff+3fp83ee6aMhFQdu/veJtX5lLhlyiBdsXyJKlN5e/qT+f9Ocw31wLqciX5vxS2rtAkk3qfqzU93wp60TTB68plnbNknZ8IZVtCr6PiDaBzF9xyHsTvClLC/wzoY4eHZzdY+VKM9PAxx9Ln35qos4XB46p63laQOSrJS28wfzvfV2PU9ofHNyCyK0vXK/uT3VX1ye6qqy66QH7rWHOHNMgXnJJ62RdCgxebk6MydvL35YlSx7LozGHjNFp/U+TJNll14QVE5reuDHVe/3LXY+OaPaG/y37n2o8Nb5iH67+0BegJklVrirfgLjc4lzfAD+pfmcl8HGNu0a79+9WNLk8Lt0/4/6gdY/OedT/ILWblFyblWjXjFbLQnHCCaaztGSJGagUKjtccwO/JBPglmRLksPu0LmHnquzBp0lyQQXvr3ibVMoL89E3YwcGfxz3nkm//LVV5tl7/qTAwYEb9vW/Mq1ssCsX5K0cvdKfbOphWa3cFdJG1+SZp0nfZQpTT5Cmj5GmjFWmnayNLGX9PkAaelfYjIDQEF5gV5Z/IpvoFiLKVwgzblE+rib9NUwk1Fo8R3mZ+EN0jfHSF8dKblrVOOqUX55vm9Tj+WR0+OUJyCIuqiqSKVV/pndxowJ/n2fMMFcIHr3Xekf/zDPB2XtstmkrNEK1W2rrPGnhYg0Q8Tu8t36cv2X8lgeWbK0pnCNiquK5bbc8lgevfDDC5HtEAjDhg2mr+pySX/6k7kQFlZbkPeJOR7lf2VumB33snRRnnTxdum8tdJFudIv8qUT3pB6nETgVyvzWB69vPhl3+Nrjr5GkmSTLWh9NAVm0OjesbsemPmAunfoLskENjw+5/HoV6qhmYdaINtqtHk80rJlZqKJq67yJ7U96ijpzDPNLGZff21mOpuyeUrI/e2u2B3W+W+L6Drc31/JfVdyljRZPGIbx5sZSu3J0qjxkmxNZ9m2t9BcPFW7pe1fSptelTaMN//nfyNV72uZ/aNJD8x8wJetfebWmerxVA/fTF+WLN09/e6g8jO3zmxyf+XOcuWV5PnOtyM91+7SJfLz/20l2zQzZ6Z/4FR6Xx3f93hfNrJXl5hJDE44wdykWrtW2rMnstcA0LCgazWSdu/frTeXBwdPH3WUfwDVK6/4b8I1xOlUbXtXez668T+SQhxIyiRFmDVaVVX1J9YJw/hF433LRZVFumf6PVq1Z5XvOBo4sUqi+2D1ByqpNn2VwGCv5394PlZVAtBOLFvmv+7461+HP8kAkCjeWWGyH9ttdp03+Dydf9j5SrIlyWazNf/eJYAW9cKP/vtVeaV5unri1b7AL6l+Bl1IG/Zu0BUfX6Fpm5s5ihOR63GKfANSd041E6u2MZWV0ssvm+sQ11/f+OSNgSIeN9RtpH85/xszVg0A4oTbbSbbe+wxc9/loYekoiKTPeZvfzPjGx5+WPruO3Op9MorY13j9m/u3DDGkzg6+ZedDYzXbWRC/DXbh+joMUM1fryZN/7JJ02wTE6OCd764Qdzb2zBAhPk9e9/m/tlaWnSrFnSnXeatlLyZ8b0tpvHHiu9/XYz3nCi2jNfmjRE2vCClJQmDfu7dPZC6bIy6ZeF0mWl0nnrpBFPxbqmbcptt5ljVZ8+0tKl0rXX+scWJiX57y+npZkMds2xcd9G3/LB6QcHPReY+SvZnqytxVt9j087LcIcDZlH12aQDe3kw+bJ4TD98vHjGw/8cjrN8V0yY8N3lvszSi/ftVxfrP/Cdy9dkl5aHHzeuWf/Hk3ZPEWWLNltdl0//Hqlp5oJqVfvWa1Vu1eF++4OnLNUmnKsSXbQoa905kzzNzT0Hqnn6SZRUK+fSkf9Q/r5Kmn4o6H3mSCcbqembJqiHaU7Yl2VkCK+rO90OjVw4ECtWbOmNeqDOpLtyUpNSlVqUqovJaIklVaV+gYUjRlT/yR60yYTmXv55SbCPEiPUxT01Zeul779qZlpXpJ2fyf9+PuWfzMJxGN59JvPf+N7/Ndv/xr1OnhnCu/Zs3USGKUHJEvYubPpwSd1zd82Xz/k/+B7fP3n1+vP0/5sgsHk0eSNk5Vb3IwARCvgYpC9gfR5TQywfXvxi0FFnR6nLxLd641lb0gy2fkcAYM1e3aqE/zVqWfQINa6mcJa24QVE3wdJG8n4pUlr/g/U5td6n22idgumF5/B6lZkr2B2S8kKSUz7HqMHGk6Rh6P9OyzTZf1eMzMAs1R46rR8wufl9tyy+VxadqWaXp96eu+4MIvN3ypzfs2mx5sVSMZzUJpbuVa2eL8xZq2xVyo/0k3/4xhD3/3cIPpZSOy4yvp84HSj7eY2cIH3SCd8ql0/iYTZHHuSunYl6Ss46U9c6M+A4BlWRo2fph+N+l3GvafYQf+fiVz4j//emnqaDOzQZ+fSSe+I11cIF3pMj+/3COd/KGUfZmUlBL24LTXl73uWz7jjPrH5RkzzICLv//dpAKvp0/oM6vOqeW+5dLSJgo2oG62spcXvawvN3zpe7yjbIfm5c1raNOE5bE8uvC9C3XNp9e0zO9fAvr6a9OHTU6Wfve7MAO/SjdI864wwakDrjUnogOvlzoEzxKj1Cyp/5XmbxitasqmKdpWaoKk+3Tuo4sGX6Rke7IsWZqdO1vr9tQ9GWl9H635yLe8vXS7Xlr0kvZW+tvyuoOqo6JiW/DsCVLobKtx5vPPpSOOkEaMMDc08vJMrPwll0jnnmsuhL/xhvl7TkmR1u31f/c22ZRsT1ayPTmoHy1Jc3LnROcNHDTGnwHXXSUtu7dl97/5NUke00fo2Mf0uVtL2Wbpx1ulz7KlT3tK310orXpIWj9OWvmgNOsc6ZPuJlifG+atpqC8QHsq/FFQbsutand10IXfrzZ+5VuuclUFTRrQmP/8+B9leOfq2BXZgNwG+5Eh/G3W34Ien/j6iZq8cbI8tf/+vfDfkkyAp/e8f+rUOpMVAIjY5n2b9f6q9yUFZ5R/ZM4jQdeUjjnGf/744otNX9ZITpaZDMkr520ze19T5ytdJEU6J1BampSVFdEmHo9HG/f6b/xZsnyTjXhVuiq1evfqCCvT/liWpWcX+C+k3TLqFqUlmet0E9dN1LaS+J2gCED8Ky72L/fq1byJ/YD2yuPx6F/z/yWP5ZHH8qiDo4NSklJ8fZZnFzwrT6hZDgG0qipXle9adGMK9hcETciY6DyWR2e9dZY+WP2BzppwliqcFbGuUmJIH2zuU0nSrpn1x640Nh4jgrEYra2gQKqo/XX5+c9b6UUyh0vJtQOPCqbXn7S4hcatAEBzvPqq9O235h7Nt99K99xjsn1J/uAe7/iGjAzpjjtiV9dEYLebbEQhx6emdPMv7/3RnwyjCS53ki57/kNtL+ioo482QV133CH171+/DsccI11zjRkH6fGYcqNGNT0xo8NxYBPiJ5SqPdKsn5n/e401YxSPuE/qOiL43nuXQdKgG6NfP3eNtGeetO7f0vfXStNOlb45Tpp6kjT7ImnlP6T8r819mTgye7b0zTfm7+eZZ0wAWFO/k835fbUsy3fvIsmWpL5dgjOnd0npotTaibs9lqde8FdE7EnSQXViIBpx0XFfy+UyF0CXLvX/7QZyucw10+eeM4+998ab8v2274Me/2XaX3z3uzomd9TFH16slCT/OcAd30SxkVj9qFRZICV1kH72Q22mNJnJib0Xg212/0TGPc+IXt3i3K1f36qfvfMzHfzswXK643swRMSjkZKTk1VdXS0bdwRajb22obLb7Cq7t0xV91ep6v4qvX6hf+B4pbtSeSV5kkwaxmOOieAmTUpGbQaRgA32zJE+z5beT5Nm/FSqZhrnulbsWqFffvBLfbMxdEadlxe9rO+3+w/wL/z4QtQHzafVXgOpqmqd2Rv79/e/xuefR3aT8JE5j4Qs84/v/hF5pbzZrCQT6FW3A9/EANtFu9eG3P2C7Qskmehub5BEki1JXTt0DSrXs3PPoAF/zQpkayan26m/zfQP3rt++PWSJLfHHfyZ9j7LZD6o2iXtWxz8WXXKls5fL/1ssTS6zkyGdQfXN+H44/3LL79sLhA2dl/MbjfR9c3x/A/PB2VtW71ntRbvXBxU5sFZD5qBSWmNXBwMpXv35m3Xyv4555++NuOWUbfokIxDJJnf1e9yv2v+jndOlWb/3Px+HHmfdOFm6ZinTfrXLoOkjv2kzCOlQddLJ70vnfJJS7ydiLy06CUVVpqZxvdU7GmZ7DI/3GwGx3U8WDprgXlv2ZdJHQICPFOzpIMvNjOLSPpq01cN76uOwNn0zjijGQMr+pwrqekby9lZeb7lSAfkfrD6g6DHTo+zXiaWJ+c9Gf4OE8Aj3z2iLzZ8oQkrJ/gyYsSDwkKTcXH+fGnhQmnVKjM7XzwqKjIXwbp1CzNbnWVJP95sljOOkI5/RbI5Gs9gaU9uMPiipkZavVqaNEn65BOTfWzKFGnLltBZKlHf7yb9zrecX56vvs/2DQqgv+GLG6Janx93/KhKl/+XvqGMjIWVhSEHCbS4vA9jkiWzJViWCei66CIpP1964glp3z6TafjZZ6UHHjCZKz/5RNq+vfbcwFGt8moTlGyTTaf3P133nnyv7j35Xt1xQvCFrcCZeVtVUoppw221Vys3vWQynAb8boRzA6BR3nPo9CHmwm9djWQgjohlSSselCYdLm1+xQS0nTFNurRUumibdP4G6eId0iVF0phJUvfjWy3LL6R/ff+vkGX2VOzR7nKTCdqbSTqUSRsmacQIc2F92jSpujr8Ou3fbwIzI4lLD5U12Olx6vN1n2vkSP+she+/3/jMaADC88S8J2Sz2WSTTTeOuFEnHmxuvuSV5OmDVf7zs7POMln9JNN/vuuuhvdnWSartNIOkjKOlGSTXPulVQ83vIFXlqSnJc2YIC1ebH4m1LkWNCHgucWLpfXrpezsiN7vh6s/DLpW1ph/Lwh9U629e2flO1qxa4UkyWF3aN72ecrOMJ+3ZVm6/ZvbY1g7IEBenrkAEfgzebL0zjvmZ/Lk+s/n5YXeL1pV4PWX5s6TBrRX761+L2hm5/8s+o9e/NE/ceSu/btiM6EQAJ//Lv5vWOUC/3YT3Ys/vKjcUv9YhXum3xPD2iQQm03qdZa5Fp3/tRnAHHgd2jse4wDGYrS2wHuLnTu3UsZYe5IZ2G1LknZ+I7nr3NBs7HOS4uqzAtD+lJSYYC9Juvlm6aSTmg7ukZhcpbXZbNKOHWYi0qbGQnkcAWNHd3xpgh0CNRBY/OK0P2j19iNkt9v1/vtm/EpjwS82m/TZZ2bMicMh3X136N8NiczrYVt6l7mv0aG3GYuY3Lk2YKWBDzCa98BdFdLqx6XP+prJVze/aoL7+11kJtPv/yupc3+pYJr04x+k2iCnePHmm+b39fDDpV/+snXu8e7ev1tVbnOx0W6zq3fn4L6azWbTQZ0OkmQmVA2cLHDAADNJVUQOOi30gbfLYJ145+vqFhAT+pe/mHEu3rFhTqe5v3bhhSa7nyR9uf7L+vuqo6ymzBe/IQVPUF1eU67vcr9TYUWhb92MnBn1xmFGqqpK+uIL6cEHzdidQw+Vevc2n92AAdLZZ0v/uK9AnjX/kuSRjvirlNYz9N9K3eNkgvou9zu9svgV3+N/fvfPA9thKweBNutb+7//+z898cQTevXVV+UgLLnFeW+EH5JxiFId/oZgaI+hQeUWbF+gQzLNQP9rrzX3zsKWfYlUOF+qe9PdE8GoogSyq3yXjn7JzJz76bpPtfYPa3V41uENlt1Wsk13TTMjMdIcaapymUbtus+v08rfr1Sao5nBJxEaMEDavduklm2NP9NOnaTzz5cmTpQ++kgaNy78bb/d+m3IMhPXTtSrF0Q4mL5Tf9NJry6Uct+VDr4grM12uKTqMBrXSleldu/frU1Fm3wDiLt16OYLvvEKzARmt9kjyvyVnJys3//+977lSMv/9du/+gYz90vvp/6Z/WWTTZYsvb70dV0//HqdlH2SuYjmtfQv0pl1vpNO2ebnAAwdagJTly0znY/f/Eb68kvTYQo88XG7penTTefkgQcif51wgn6+WP+F9IsJZoBSob9jpbVrpauvDi48YYI0ZIiSLUu/Ly+XMjOVPHBgyNeI9Ls7UF+s/0KfrfvM9/jTdZ8G/S5e9elV2n7n9sh3XL1X+v4qSXbp0N+aFK9edfvM3lnKUg+K/HUOwLrCdbpjihk4nmRLktty6/Zvbtdp/U9r9NgcUt7H5rhhs5ugr8xhZn1DHdyAdQXlBb7lgZkDdc/J/psm4xaO05o9JlPqrv27fOu7dzcD+KZPjyBrYpefSB0PkSoaP54M6rlFR2Wv0Mptw/TOOzbdckt4uy6vKQ8rCGJGzowwK9v+Td08NShLxs2Tb9aI3iM0qs+oqNdlxw6TIn7yZBPQlJkpHXSQydDpdEplZSYV/aGHSt99Z2agihedOpkT6vLy0GUlSVUFZoZESTryftOg2OscmPbnmX6AZLLa1hRLnQdqQ9Fovfqq6bfk5JjMRb16mYG0brfJlrd1q5nRZdUqKTW+rsW0qgPpe+SU5oQ8fszfPl9VrqqI+sAHUqdbZ90a1ms898Nzuu/394X9Gh07dtTll1/uWw67TguuU3KZW8r7yBc47OO9uNzQ5ARxNGvlG29Ir7xiLgJ++635+/H25ZKS6l/QHjZM+mHnYrks07+2ZOn2E27X+YPP9+9z2RvaU7FHDrtDc7fN1W9H/jY6byb7UhPo7bXo/0xWtsP/ZC7Cbvuo8W1D8faLPNX1LzR6MxA39F2P/V7qMTq819jwvBnEn9RROnOGycDqcftnZfJKyTSZfvu21pSskKRvNgcHTQX2xQMDTt9a/pbuOuku5RTl+M7N7LLr54f93Dex0rKCZdpWsk2WLO2p2KPLL5f+8x/TRk6aZC44N3Zen5ycrMsu+71OP11yuZL1+uvS/fc3fR3Ae4zasHeDHvrwoZDv9Zn5z+jCwy/U6adLX31l6vTdd9Lo0Y3fIHC7w7vhVbdO3uWWLt8c8VgntA+L8hfpv0v8gxYnbZyk0mr/zPQ3T7pZlx95uRx2h9LSpKuuMjPNulzSSy9JPXpIDz9sHtts5m9twgRzbe7qqyX95GbTxknS+uek9MOlQ3/nb58CB5xJJgDs6CFSt2MarvCQIeYCzwGYu21uWOVW7l55QK/THtw34z7fstvj1r8X/NvXrliyNHHdRJVWlSo9LT1WVQRMENfgwZFHD6WlNSuAtL0prynXil0rdHTPo9UppVNUX/uQQ/zLU6dKV15JUD+iJ97710/MfSJkmafnP63rR1zf6nUBEoq72syeX7pWKl0v7c8xgytlmWtgnQ4xWZS6Dtfc3Nlh7bLuLOyJal3hOt+4lRR7imo8NXr+h+d1/mHna+ygsSG2jo14bysi0vN0c+/Z7ZKW3SOd8Frw852ypYwhsalbGLoGzH+8dat03HGt1G/sNVba9qm5t7f6cWnYg8EDvOP8cwLQPq1Z48+cffPNMa2KpOa1d3HdRobJ+x4WL5aqq817eOAB6bLLzDXxhgKqUlOTNTy9g0Zn/j975x0fRfW18e/M7mbTew8JEHrvvfciiIjSrChgxy5ixYoiKqiIKCooiFgA6SBI7y303gIkhPSebJl5/7hbs5uGoLz+ePjsh93N3Zk7d+7ce8pzzvkEXdZV4aP1irH7Uq2BxcVpkH0Mtt/L3C2CNzhkCNSqVX6/MjLE+QMDRYD0v43/zPwwF8O5H8T7Bi9bkj2XcDQ68IF0BUk8dnsseMfeWLnRmANr2on5EtoWuq2C4BaCr6QYBZdSRcwxSSN4l5qKZL/+55CeLvxJJavZXU+czTxre29WzUT5uQbqR/tF2/hFZzLP2L6XJOjVC+bPF/10B5fnPbxT+cmXPQLR+Mdx993w7bfi2CYT9O0L48YJ//ulS8LfduSI4MGoquqUGEgra9FZgqdUVFssAMCWC1sY2XgkG85vIN+YX2ZXFFXhqz1f8WTrivGZHFFQAB98ANOmCXP8HXeIwgPPPgsxMWL80tPhwAFQrpxAxjKIcXe5PkNQKq+uwpyV/yCyirIY/ttwp+/e2fQOvWv0Flz7a8H5+dehZ6XjmkJCdu7cybp161izZg2NGjXCx8fZObFw4cLr0rn/VaiqioRE44jGTt87Etp1so4dl3YwrKEgII4YAc89VwkSebV7IWE8KG4ykt+CE3KLc+k9t7fTdz1/6MmuMbuI9ot2+l5RFO7+9W4KjKL++ZB6QziVfopdSbs4nXGap1Y8xTe3Vywj1d/F6NGi6sf27YLEXK9e5YhXFcGIESLw68oVQQq9//6yCWZmM5zJPOm0CZaGjKIMUvNTCfMJq3iHZK2Ipj82BS4uBkOmKBNv3cRKIdiuKrH3JjySQHyQCPY5kXaCVrNa2f62+vRqp6jtCN8ISsLxO42kcWpfHiRJIjy84oE0ju1zinKYvM1emedizkVbgAwIAeS+Rfdx9umzQpnxryeM6Cl/wakZUHOs+w3/b+CZZ8S8AFFVpU8fEeTl7S0I/1ot/PabKIncsGHlj19kKnISBktDriGXc5nnqB5XvXxygYXUJAGVCWmq7L0rCyl5KWy9uJVe8b3w0/u5bTNu5Tinz5sTNzt9vpx7mdkJs3mw6YOVPPlfdgGvyftCWXFHYC5OswuA8I8JgQazgWG/DaPYLIKVRzcfzcy9Myk2FzP8t+HsGrPLqWxuhXFpiZj/Ia0grBShrcR1F3tVsTmQdLKOgXUGOpHXE7MTOZl+EpNiYv+V/eQU5+CvF+SsBx8Uz0RZcFJcJAmqDIJTX4JaiqbjV48HHovlxVcltm0TQeGNGpVtiDebYf259U7fNYtshq+HsFAk5yXbKrLkGfJIyk1y2fv+13Ah6wJDfx0K2IMPFVXhjp/v4MCjBwjx/mcqBaqqyObx/vsi2OuZZ0RibXdLnKIIWeBmCvwCwR81m0WVkuXLRVBkmTYWY679vWeEa3Cmm+AKVYWXf/6Aj5a3JTZWYsIEGDbM2WnliOTk/63AL/h7sseTv5ZvmFBRmbx1Mm90eaPcttejT+ezz9u+D/EKcVLE/zr3F3mGPCQkzmadrdQ5ZFmmbt2KBxjb+lRvEOxeCdlH4cLPEHuXfe66MS7bcBNlrXzxRfH/uHHiuS0vM5lWC1sStyBLso2o3CiikVObppFNWXt2LSbF5LIP3VBE97UniwCxpx55X7z+LvzrQ9pWUdWrcYkqK2VUICbvbMVkqPyLsO858b7FVAi2BByXDPyy4laGphsKk2KyVXiWJZlOcZ24s96dtr+/9tdr5BpykSWZI6lHAFh9drUt2U/LmJYsGbHE1n7mnpk8tlw4HFLyU4iqf4bw8BpcvSqq7Q0aVHpfJEmiVq1wmjcXBN45c+CVV9yL8Y6/CQkJZ9up2U6VeHQOmb+sMg7AsbRjqKrKkCESy5aJv99/v5AvwHX/NplEpcDK8Lr/ztp/o3Az9ukW/hsYu2Ss0+eEKwlOn/OMebyx/g3e7yH2p4ceEkFfVrzzjqjy+/DDQnadP1/Y55o0sTSodg/se96S5EuF3Y9DYZIIdvYIgMIropLkP4hdl3fZ3reObs2i4Ytsn1//63V+OPADJtXE4dTDGM1GdJqbxOH8D+NgykEnO6KK6lRV1/rd+LXjmTFgxj/dvVu4hVu4DkjNT6X6tOrkG/Px8/DjzLgzlfOB/E00aCCIDAcOiGQDDzzwj536Fm7hppavi03FHLl6xPZZlmQ0Fn+Zk26UeqzSSY5u4RZuoRQUJMHht+DcXNCHQJU7RKUknziR4R9J+AQKL0PabghpRUKKSBYhIdG5amem97dX+HphzQusObMGBYWElATBufkfLsFhNBsZ/ttwDGbBB3qu3XN8sPUDAO5bdB/HnjhGkFcpjpJ/ETfzXlFpxAwAWS9087PfQexgiO7vvnIFQBpw4Bg4FCwhOdkefRAYKFL7OyI09IYlVoiMFLLjsWMiOVzJfLrXDdH9xJioZjg6SawFgY1u2bdv4RZu4V+FY2Upvf7fr+p1LfvdTb1HVhDWa+jbV3AKjxwRHNWRI2HBAsF/sfqnFEX4sGfNkli6ZAiDxowXf9j1CHRb6XzgEgnxc4v8AIngYPtxykJgoOC5ZGeLQAzPf1A9VFVxzsJCMS+9vECv/4/MD2O2/b1XtPvALwc+kBOvM7j8ZKvXfM1bRwh+bVBTUVxB0lkPCO74iR43n4wdECB441eulN/2WnEu65ztvaIqLpW/AGIDYtmdtBtFVcgozKDAWIC3TiRe7ttXJD4vDWqJGjcEtxJjbch0/wNJAyFtARg1CmY61JYoKoLJk8WrJA6kHHAK5Jo7eK4tRkNVVYInB5NVlIVW1vLX+b8Y2XgkPx4oo+MOWHRskQj+Skx0Ll4Bdrm/hMxfbJAY9GJd/trmRZs2sHChkNMNBrH+WfenGjWgaVPQZshgze1fMhEkXL+kxf8hqKrK2KVjbUF/IxqOYP7h+aioDP99OIcfO0yAZ0A5R3GDoqvXuafOuKaCkoGBgQwZMoQ+ffoQHR1NQECA0+tG4ssvv6R69ep4enrSokULNm/eXGb7jRs30qJFCzw9PYmPj+crR0+5Bb///jv169dHr9dTv359Fi1a5NKmvPOqqsrEiROJjo7Gy8uLrl27cuTIEZfjVBRaWUuDsAZO3/l6+NoI10bF6JQxNSwM+vcvO7jH6W+eoSIATKqAwix7CoLcfwGqKggOV/6CCwvg7A9w+hs4/TWcnQPnf4ak1VBwGVSVQmMhA+cP5GDKQQA6xXUCRFBFjzk9SC9Idzr806ueZuflnbbP8w7NY1eSndwwa/8sfjv62z9woTB8uKhmASIwEOzlKt2hrJK4paFfP3EOSRJk0IMHS4++NpmEQ/GXo78gOyw9Z8edJfvlbLJfzmbv2L1Ov/n92O+V71T8w8IwpBTD9vsByb6RWQm2ffc6lYZflg8ai5Et0DOQxhGN8dP74af3o3l0c1sQhFbWsuTEEjIKM2y/reJXxaULkb72OqQmxcT5rPOVv45rwNhlY50yzLvDuaxzrDmzRnxo+gFgab/3WZENWlXAWgWtvOj4CmDoUCGPWAWN9etFxPmYMfDqq9CqlZir1zL/AJafXO50zdP7T2fjgxvZ+OBGFg9bbPteQmLBkQV/40oqB6NRBN7Mng3PPw9jx4psMGPHOr8fP14IZadO2YN3151dR+THkQz5ZQhBHwaxL9m1rOOBKwecKsppJA06WedE1gR4c/01kLkcSUUaN1YMqxC4qgVsHCCI6tvvhT/bQ+r2yp+vkug6u6ttTdZIGhYdX2Rzwh5IOUD3Od2v7cDlWWvcXPf2ZV1tQWhGxUjzKOdM6M2jmttK9iqqwsbz9oyEgwaJqkdlwUVxqTay9MAvAK0nw++3K5F33SWMDWWty2fPwm/HfkNrMaD7eviye8xuNo3axKZRm1g2YpmtvYTEomOuMtL/EnKKcmgzqw3ZxcLo0DK6JQ3DReTq5dzLtJ3V9m+Xaa4oJkwQpM/YWNi9W+z1pfl3ZPnaAmxvNLp3FwGKsgzvvVeBjIFeUahWQ0radtd9yk1wxeu/vsPkZeOJjZXYvl0QZEsL/AJXv9ktlA5VVdmfvN/2Ocw7jNtq3WZ7+ejsi9yOSzv+kT6l5KWwJ2kPIPaIJ1s/yR/D/7C9HmjyADpZh4rKn2f/tCVsuKGIvdNeRn3XIyKDreM64RMnqmz417nxfbkGqKrYS0CsMRVNNrLpwibbe2+dN1UDqjr9vUlEE9veczHnIsm5yfwjkHWC+O5SzvQ6oP54sS5l7hM6paNMZU1C4Q4VrfKWf86+7kV0dR/0lZ8IGfvE6/JyODfvH5HP/hexJXELuQYRlKyoCk+0eoJxbcbZXrfVug2NpEFRFRafWEx6QbptfdLJOtpVcTactoxuaQvCkpBYd34N994r7Di7d8PTT4t27nR6a5ayBx8Uz+j580LfKEu8NZlE0Y3FxxcjWZ6HhuENMbxusL2+GWhPXJNakMrBlIPcey/Uri327gsXhD63f79YKwwG8QKh44y6lQz/Fm7BLVLyUtifYpehHPV5yWF/mr5rOqpFKWzVSlTac7TtrlkjkhrccYdwdDutDx6Blkpf1h+ocPgdWBgOCyPgjzhIWsY/hbSCNNsaqJW1dK/enWi/aNurZ3xPW8XQPEPe/3SW/oo6CVefKSebzC3cwo1GXJwQJvbutb/mznVtN3euc5v/8apfZzPP0npWaxuBINeQS5tZbZwy4/4TeOopsW/s3CmChyucVPIWbuE/jOWnlqNgF6hGNxvN651f5/XOrzO2uT1wX0VlyYkl7g5xC7fwn0VWFmzbJvSOOXNEEMiXX4rqxHPnChvAoUNQXFyZgx6BVS3hzHdQ7zkYdE4kO4ruC0GNRcJJ3+rifWRvaPQq53KSOZlxEhABmn1r9qVBeAPbq2/NvjaT36WcSxxPO369h+L/FXr+0JMDKQcAYWv6dMentqr1KfkpNJvZ7N/s3v8GvCKh7nPYaHmbBsOhicI/oJic7cdpwAtA93uhRQv7a8AAEXV1773ivePfWrQQ1XgTK56IuDKQJHjpJSE3bt4MW7aU7nO24po4Hz5xUOtxYcNQjLC+NyT+Kv6mGO3jdQu3cAu38A+idm178vvFi2/pzTcaqqryx/E/WHpiqc0m7ghJEpV5rDbw5cuhcWPBU7WioEDwD8eOhUvZNSCkneBFJ6+Cg6+LRiX3E0Xc2FqRp9DIRrZX0KU6YICw1RuN8OmnFZsfbi6rXBQXw7Jl8MIL0K2bqMJ5zz3i83vvCb7Qs88Kbljz5sJPOHMmJCRc2/n+dXiE2P3pGXuBEhdRXrLVGwFTPiStED76us+IwC93Saod/fPn5990/vk77xTzNCEBNm4sX6a7FpzLPGfjfwBuK39F+UbZOJ6AE6d68GDw9y/9+C4FSTQeEP9Q6YUuVLPg6iCenQ4dKlY4ZeWplU59bFOlje29JEm0q9IOCQmTYmLZyWUoisJGS4VqCYnW0a1t3OWND25kYK2BtuPtTtqN4dxpIcOXlOutcn8JmX9yu4Ws26InJET4BUMtYRweHq5cAA8PkAPr2Z+j8z+6BoD9G8/RTY7Hlj/Gr0eF/iEhsSVxiy3p06WcS7T8uuW1HdjLtajM9cQ1BX99//33Zb5uFBYsWMAzzzzDq6++yv79++nUqRP9+vUjsRRl9ty5c/Tv359OnTqxf/9+XnnlFcaNG8fvv9sDSrZv386wYcO47777OHDgAPfddx9Dhw5l5057AE9Fzjt58mQ++eQTvvjiC3bv3k1kZCS9evUiNzeXa4FRMVI/rL7L943DG9uIAAlXEig22a1ozzxTtjDh8rc6T5dNIkcS0a8DTzhFu/+/g6qKjXV9f/ijqjCo5J0Fn+oQ3lFk14kZCOGdBenSlAee4SiqSr3p9WyLMzhX1jmefpz4z+LJKcoBRMbG6bunO51asvxzxOglo/8RYri3twjIkiT4808h4FpJYY6wfj51qvLn8PQUxl1VFVU7evUShl6jUcw3g8H+//TpgrA29+BcmwOlflh9qgdVx1/vj7/en2aRzQj3ERH2siQz7+C8ynfKvxbEDRPZgS4vg20jwVwoNjJVEXM5qKmNYGtQYU0BmFUFCcsG7bAzypJMm5g2tk175Wl7NgitpCXSL7JkD/D18LVtACpqhSpTWWE2m9mwYQMbNmzAXAHtwNr+z3V/8ufpP23f+3n4USekju0lO2SQ+mavhcQXMxAiewllRykWlQRWt4aLv8PVLXDpD9j19+pX6/UwZYqzUpGTA999J6Ln9+yxf38tlel+PPijTUDy1nkztsVYOlftTOeqnRlUd5AtiFZFZU7CnEod+1ruxcqVG5gwYQNBQWaefloIVePGiQzdX30lHCJffy3ez5gBjz8Ot98uykYrGHl13av0/LGn/ZiqmRZft+CzHZ+hODC5vtj9hW1t0UgaHmr2EKObj2Z089G2IFWAxJxEDlmy4FUYYR1AYxECT0xznwWgNBgyym/zN/D13q/ZfsmuIJlVM1fzr2J2CADZenErs/bNqvzBY24Xgn/6LjH/lfKt02sL7IGjgEvwV4voFrb3WlnL2rNrbZ+9vOCxx0rPGCNJ9gBeG0LbQFjHUhQXCTyjiI4WlR4kCc6dg86dsRkojEb7S1Fg0SIY86iBRccWYVJMtqoVGgcyee2Q2oR4hVj69M8GUd6MaDKzCSn5KbbPOy/v5PDVw7bPpzNP0/n7zv9IXxZYbsXgwSKotqzKm1B+dqJ/A5IEr70m5uP27YKorijuDQ2qCorGjyvB4wFZVOkpulpucMXSfQMBIaNER1cgwOx/ENcqe8xbOo9zmSJ7j4TE293eZtnIZbbX460etxl3Vp9ZTVJu0g3v09wlc21JBsyqmc5VnZ/HzlU72yonmMwm5iyeU+FzGAwGZs+ezezZszFYoxsqcg07jmBu/JH40pgD67qJiquK0TKxLRP+Bu+h1wpJElnhtVr444+KyWuKqrAlcYstQL9BWAOXLLuNIho5VbHYenHrde13majztKWyWjkBYJVNghLdDwIaiX16xwOQe8Z+f0tJQgFUvMqbTzVsJpyrm2wOCRscA9Udg/T/oQD9/zX8cfwPJwO2Y5VB62frM5BVlMWMPTNsn42KkVbRrZzaN4poZDueLMmsOr2K11+HiAjx3H35pchkePGiaG8w2MkU27ebGT9+AyEhG2jVyoxWC99/L6qBZ2eLvdWqSlh/s3Klmfc/XoL+kh4ZGa2spXe8c8XzbtW62d5rJA2/HPkFrRY+/9x+vOPHRUDK6NFCz5k+Xeg3w4ZBZimJ1krDta79FW1/LbgZ+3QL///xxa4vnGyFo5qO4rGWj/FYy8foV6uf7fscQw7rzq2zfXZ89iqEhq+C1h+n/U4xCBn6OiT7qQxWnV5lC3A1KSbaVmnr9HfHz1pZy/JTy//R/t0sMJqN/HDwBwBkZHrF97IlzMp+OZtPen9ia3su6xy7L+/+t7p6C7cgEBcnmCXWV716rm3q1XNu8y8FfimVWkBvDH4+/DONZjSykRqaRIhyjeeyztFoRiMWHP4bNrfERJGJzPG1fLkoEb98ucvfhne4SGSkkDPvuw+WWOJYSpJ1rZ8///zau3YLt+CIm1m+/n7/9zZfk7/eny9v+5LXu7zO611eZ/pt0wnyFNmkNJKG7/ffOC7ELdzCzYIjR0R1SGtCz337RHbxTp3gttsEwbRPH5GoQqMRyT8rhaMfQFEKhLSExu8Ie5okOxMprSTK5FVw/meW77frUmbV7JJYp11sO5vtRZbk/1m9AuDXI7+yKdGenEtFpdhc7JRQ9UL2BV5e+/K/0b0ycTPvFdeE+uNFZTtkwc06/A6sag4J4+HQW4KfcZ2hqqpb4vy1YPhwCA8Xz/mgQSLZs9nsap9QFPH9pUvXeKJGb9ptGMVpguOzYQCcnQ2Jv8CZa/D938It3MIt/A1ERooAG1kWATYpKeUHuN6IYAorrmW/u+n3SAv2Ju2l+dfNuWPBHdz+8+20/qa1LQGt4zUMGGCmQwc7L+bsWRHQERsLdeuK/WrBAtBozNSps4EN6rOYVYtj+/C7sOE2yD3pfPJCwV949+7XUFQN+/cLX1d5ZqSqVeGJJ8T++OGHItdRWfffZKp8AOGWLVC/Ptx9N4SECD/9rl3w00/CTvPhh4J3OX06/PKLmU8+2cADD2xg9GgzTZuWn//8ppwfsgYaTwQkOP4J5F8skw9kVjVsSO/KhvSumDVlRA1Z21/LNct6e3GVoqu48Av+n/jnBw0Sz4tGI5JC5eWVvaZdS0C/Y+UvwG3lryjfKJuvCLDxjUDwKB9+2D0fRasVRUpcUOPh0v1d+jAIaw+I52HKlPKfQ60WEdBl0ZuCPINckhy3rdLWZj9KyU/hl6O/2LjhkiQxotEIG3e5c9XO3N/0fhuvNdeQy4ZzG8ruRAkkEY2MQlQU+PqWzw3EM1T4B5Hg2BQRJ+EYq3A9khb/h7Dz0k5m7rWXhVNRuZhzkSKTPUDudOZpnl31bOUPXnXE9ehiqbhmGqjJZGLt2rXMnDnTFuCUlJREXl7edetcSXzyySc8/PDDjB49mnr16jF16lRiY2OZMWOG2/ZfffUVcXFxTJ06lXr16jF69GgeeughpkyZYmszdepUevXqxYQJE6hbty4TJkygR48eTJ06tcLnVVWVqVOn8uqrr3LnnXfSsGFD5syZQ0FBAT/99NM1X6+74K8G4Q1shCCTYiLhSoLtb927iyjd0hbAjh1LfBnUGGo/SenTQIVmk/9/B36BEOA2DoCco3DbEWj9FcQ/AKGtRdYo7xghKBgyhVBnyof0PTy+/HGnyjrukFOcwx0L7kBRFcatGmczOMrIjGo6iidaPcETrZ5gcN3Btt9kF2czdcfUG3nFNkycKDY+WYbffoOaNYXwl2LhrRuNIrvjsGEi+v9acO+99qziGRkimKFmTVHRaPJkoQxVqyaCE9Pkw5xIPwEIMkefGn2cjiVJEn1q9EEra1FUha0Xt3I553LlO9X2Wzvx8sICWBQD+1+CzP1iQ8vcL4JagK2FUGCRKWRJpn1se5fDtY9tbwuGcCzrKUkSET7uI3RDvexE0cTsimdbMpvNbNy4kY0bN1bYoLlx40a2bdlGXrF9/V00bBHHnzxuez3X9jmb4PHbsd9EQJAkQdvZQtixCqoZe2HrcFjbCTYPgYy/TyQZMUIQFcsjC5crnJRAZmEmy08tx6yakSWZ7tW7OxEwAfrW7Gv77nj6cVvFqIrgWu7Frl0b8fTcSLt2ZjZvFgbRqlXdB11oNOJvWq2o5OXxrgfvb3nf7bGfXv00Xu97cSnnEpdyLjE7YTYqKlpZy8hGI/l64Nd8eduXfHnbl/w+9HfbvdbKWt7b/F6FrxkAn6rQ0hLIevBNYVAFu0JlJS+XJC5DxcnL14CsoizeWP+G7bOn1pO6oXVtL2vAJcDr618nqyircieIGyIqYgJsGwFZlrlSxnWvtgSOAug1euqG1nU6ZKx/LAF6URHVpJhcMnO//joEB7tXulXVXuHBCQ1eLV1xqSHKK7z5JvTsKebdsWMiAKxTJ/jiC/jhB/j4Y2EkGDoULmnX26pWgDPJF8Q61616N1vlii2JW0jNT3V//v84fjzwY4UqOW6/tJ3Vp1aJwPMjk2Df88KBc/RDODlDOCrO/gDnfhDvT88SCteJaXD8Mzg5HS6vAGPZCQRatBD3eMsWUZL6RhoTbyTuukso8CCyEHXrJrKVlFx2z50T1c6GTnxFrFPmQljTDtItUcSKEbxj7cEVbUXAb/va25AkhS1byq6E97+Ma5U9zuw/g4ckytirqPSv1d+p3W21bnNKeFCZIOxr7VPeqTy0iH1fI2lciMWOAdIekgdXj16t8DkMBgMXLlzgwoULFQ7+sl1DjUch9m5AhuJ02DsOlsSLSmAJLwnZa8OAco/5b2HePBHQvmGDyPRpNpdu8DOb4UTaCVuFRJ2so1mkaxZZa9VEa5stiVtc2twwaL2g+ae4ZAtzhF/dyidBkSRo/yNo/YSDenVLODFV3HOwV3kLcEOKrQh84qCZJZBw79NCp4GKBerfpMGF/1+hqiq/HfvNtsbF+MXYqrRb0SG2g814rZW1/HrkVyddpWW0c4YoD40HjSMaA4LAtPbcWnz8jCxcKAKXZRnmzxe69ogRIqPfm2+KfbNHDzPBwRvZsmUjP/9sJjhY6BjffitIWs89JzJTrlwpvmvSBIYMMVMrbj9d6YqMjEkx0a26sxxYPai67brMqpl5h+ahqiq9ews93wpFEck9nnpKnGvp0msb12td+yva/r/Sp1v4/43somym7pyKiopG0tArvhff3P4N0/pNY1q/afw+9Hf8PEQWEI2k4e2Nb9t+26KFyOJZVlIHJ7uLZzi0+Zoy9zsrKhvwXEksO7ms1EyJANUCq9mSjpgUE38c/+OG9eVmxuLji7mafxUABYXhDYfbEmb56/0Z3nC4zfaslbV8sfuLf7O7t3ALNz0u51zm0+2fIr0loX1Hi/SWxBe7viAlL6X8H19n/HjgR0b8PsKp+rS1EgdAgbGA4b8PZ+5BN/bW8pCYWKlssbRogVeT2qyZk4ynp7CTDBkCvXsLedFatSU7G775RlRsv4E5P2/hfww3q3ydkpfCitMrMKtmNJKGvjX6OiVIkyWZ/rX6o5W1mFUzq8+s/ucqmN/CLfwL2LIFGjYUNsHFi0WVyLFjha8pPl7YGsLDBdG2Th2x1Tz2mEgIWmHoQwAVilLBXFx2kiMLgfKPPZ/Y/GmyJLvYVppGNkUni+xv1uoR/ymoKpgKofAK5F8QnIfc05BzSrzPOw8FSeTnp/DSny/Zfual9aJ1TGvaxLShTUwbWzAriOQk18TFuIG4WfeKa4ZHAHRcIIIbrWThrEOC0HzkPbhqSUQdCkwB/pp7TZV1zYqZDec3cPcvdyO/LSO/LTP016FsOL8Bc8nny4LMwkx+PPAjEVMi8J/kz8CfBrLu7DqMZrvx38NDVBzR64V82LEjPP+8OK0jzp8XyUnvu+8ax0kfAh1+ch6npOWwayxsuwfOfHONB76FW7iFW7h2vPqqkHsKCkTA+yZLXLXJZA8OMpvtvIa//rpxfbmW/e5m3yMPXDlA4xmNaflNSyf+857kPTT/ujlNv2rK4SuHbdegKGZ++gkCAux2cEURgccnTkBhofhOls3UrbuRjTuPYm7hwClPWgErGsGa9rDxdvizI2wWVYGaVD3Ic/1E4q2nnhJ8V2uwsyO/xOofz88X8yM2VgTRtGsnuFjWvxsM4mX97Zkz8MgjlRuf558XAW533y14Mo4VkWRZ+AG1WvHeeq83bfoPzI+6z4F/XcH/WdsZ0naI7134QLMxqzIbM7qyMaMrv6yuw6efikpsU6eKhPxffy1sW/ZE/fZr/uknM2vXimIZZcbMy1po/rF4f2giZB+xF6AoDzeRf16SBGdQr4ejR4WJcKslN6+1sIe1yAeIys6VxemM0078ILeVv/yibG0kJJeAsbFj3QdomUwiLsIFAfUgpI1FhnSApIEao52Si7RtK3zspfnYZBnwzGLH5R2oqKKISGw7lyTHbWLaYLIU3NFIGqbvmm7jACiqQs/4nk7tu1Xr5uTX+SZttVi0HGX6knK/g8x/14yeSBoNR48K/VxRKlDZr+7z4FdTPDer28ClxeJ71Qxe0TDgOPTeee1JiwGSk0tPRuYuIVnyzWdHMykmnlzxpO2zRtIQHxRPjaAa1Aiqga+Hr+1vM/fOrBBn1AkeAdepp+5RSaq9wIULF+jbty+JiYkUFxfTq1cv/Pz8mDx5MkVFRXz11VfXu58YDAb27t3Lyy87Z5/p3bs327Ztc/ub7du307u3c+biPn368O2332I0GtHpdGzfvp1nn33WpY01+Ksi5z137hxXrlxxOpder6dLly5s27aNRyq7eyMWtzqhdVy+rx9W35YhXZZkdl7e6eQwnzoVVq0SDhrrQqjRiNdLL7kcDpp+CEkrhYHIqQqYLCJjwzu5+dH/M6gWyUqVHKqlOCzKVuOhQznDz7JgZqq1pUS/mv0Y2mCo7e9/nf+LHw6ITKzrz6/nzgV38scJYUDUSBoeafkI0/vbq4Cpqkr779qz+/JuzKqZ1/56jTvq3kHN4JrX/XIdodXCwoUisOvnn8Ua+tpr4iXLzpkKWl5jdUIQwoHBIAhfWq3wN378sWtfMmN+RiNpMKtmTIqJ7tW7uxyre/Xu/HjwR0AEHfx69FeeaftM5Tqk9YGeG2B9P0jfAcY8OP6xeJXA8nyxEJoQhLaSJGEQEdtWwUOWZFt0t1k1lxr8FekbyaVckdooz5BHTnEO/vrysww4YnbCbL7a/xVnM8/aCLRW+Ov9iQ+MZ0yTMbbvrOTCGL8YF+LeqGajmLJdBL5qZS2vr3+dxcMXg3c09NoEf3aC4tSysz9fIxlIkkSlq8RE2LbNNUOGdY16333cU6n47ehvNmOlqqouwYQAveJ78fF2cd+1spa5B+cyudfkSl9DZZGaKiqc+fuLZ8PDw7WNqgrhdNXZpdyz8J5yj2kwG2j9TWs6xnW0ZesyKSbua+xsRQ3zCaNPjT6sPrMak2LilyO/8E63d6gVUqviFxA/CgxZcGACbLtXVCipdi9EdAe/GoJ87Htj16+SeGzZY6QVpNk+r7l3DZ2q2veoTRc20WV2F0BUYnxi+RPMG1LJ6oGtZoBGD2e+FUElVQZbKuT1AM8Icd2eotpfjhn22YtvOlVrsEKSJFpGt+Svc3+honIi/QRX8q4Q6SuO4e8Pn30mgiMdodEIUu6gQW76GNVH3IerG+3Pq6QVQnu0CBywVmcZNEhUftRohLNuSwlevVYLWdG/oZW1mBQTiqq4VMkB6FK1C78f/R0Q68zi44sZ02KMS7v/Mg6mHGTMUnHNMjJNI5uy4cENNiXPYDbQ4usWXMgSQeOzVwyhT5iF0HPnVfAMcz1oYbL9pfEC/9oQ0sq1XSn44QdBzlm1Cnr0gEmThNNFGHfsa61GI74rLBSZUm42yLIwtERGCiL7tm0ic2h4uCAYeXhAUpLIJijL0LSpF/TZIZw9V9YKo1xYB4juC2GdQecvqllagiI+u38c2QUBzN8+ks6dxV7Tp4+Y/9ZMhJIkxkmSbt5xullhNWrUC61HXIBzkEz72Pb4eviSZ8hDURVm7p3J+I7jnaqR3ghYK8w2j2qOt87b6W9RflFUC6zG+azztr7/I5AkaD8XthpEZVVkKLhUusPyBhOwK4tatYSD99574ZNPYMUKePJJsfbUcVBZs7Nh82aYsXOLzdJgUkxOgV5W1AutZ5OrjYqRDec3/DMXY0XVocI4e/htN3+URUXQa0mCEtQEem8VToO8syIBRcLLYp3yjBQVV6xG6mtB3WfBkC4Civ/sCFWHQ/yDENLaHqhenCayIu9y2KtvYID+/yIOXz3MpRyh62kkDV2rdXVp0yiiEV5aLwpNhZgUE0dSj9iyevnofNzK5m1j2nIo5RBGxUiBsYCdl3fSsU1Hli4VBu38fKE//Pyz8+8cdY0qVYSxvmtXuHxZOCWnTRMvR5Tc6yQkpwBZK3rX6M3cg3MxKSYuZF9g/5X9NI9qzuTJQt/5+muxxJU0Mlv31X8KiqJQZCqiyFhEniGPrKIsVFQC9AH46f3Qa/R4aj2Rb8ZSqLfwP4UZe2bYiP9m1cz9Te53+run1pNhDYYx+8BsTIqJzYmb2XZxmy1R0fvvw8mTYi92Z1upVXJpibsLGk0UTkkXSOLVYhpUucZ9rwIwKSZWnFphWwNj/GJsOrGtJ5JEh9gOLDslMiqezDjJ+azzVAusdkP6dLNi2s5pNvlIQmJg7YFOf4/yi6JldEv2JO3BpJiYf2g+U3pNIczHjb55C//zKC4WsoPVPqCq9v265L5tI1HL4r1WK4gAPj7/bJ+vB1LzU/nlyC88ufJJp++tdvOnVj7FUyufAuCbAd8wpP4QgryCXI5zPTHv4DweXPyg7bOfhx+1Q2rbPp9MP2lLzPTg4geRJZmRjUaWPMx1R6O6RrZsETaS1FRYu1bYEcHZd6TRQOPGN7w7t3AL/yp+OmRP5GpWzU7VWK3oW7Mv8w4Jf4MkScw9OJcXO7z4j/XxFm7hn4SjruGYYKI0Pf+a9P8mkwQ/5dJiWNcDWk0XdjVVEZwVswHHRBZ5CmwoBMXyXf2w+vh4OAsrHhoPmkc1Z+flnaiobLu0jczCzBu+199Q5JyA5Y0E36X9T1BthEhs5QhHX5Mhixf3LSIxx56YdkHvdxjY6nnb5yNXj9BoRiNUVIpMRTyw+AHW3Lfmhtvt/6cR0U0EgG0ZJj6X5psI94TWncrWz62VdRH8iB2XdvDsrKHsvLzTpemvR3/l16O/AtCuSjs+7v0xVQOqMvfgXMavG+/SftmpZSw7tQwQ9st5d86jd43etGrlxaZNItDz6lXh2542TSSADgiA3FxBTgdBJL5mRPeFDvNh6whAKn2c4KbzodzCLdzCfxO+voJ7P3y4COzq3VvwF267TQQR+PgIP8nmzYLj7ucn2txC2Sg2FfPZzs94ee3LNr++OxxIOUDbWW15GTtnOy5OJK7p1cvuM3OEi1xa/R5QMkXFTRB7S5r7akyT73mDoJajefO9QF5/XfAcBwwQ9zQmRtjYjh8X509Kgo0bRSWuoUNFAtWxY0WCxAEDhB3FwwOuXBE+9iNHKs/LHTBAHH/XLhE8VqOGCC6z8n8c4TQOa7tCdBeodg+gWoKUVCFaF6WCIU34kgsdCrzsfgIogHovQLBrUtd/FLIOem2B7Q9A0jJxPVY+UHhXS2UiFbKPOf3smdeq2YphlAaDQfCqQBTKcMfldIvaT4kxO/we/NlBBBXVHCOC1Bz989nHRNUvK24y/3yrVrB9OwweLAL3u3cXAYyDBkH16uL5OXdO8A1DQsT6Vxmczjhte++p8bQlOnSEYzUwrazlbOZZp7/XrSuepVmznG2Td9wh1l+3aP6J4D3boBGFMOo979J01izhY0tIcA4ys64dg55dy+6D9mrSJatNA7SOaW17b1bN7Li8w8YrD/UOpUFYA6f2Id4hNIloQkJKgkh+eOIPsm+fRUBcxWT+Hs3h5zC45x7BL33iCRg3Ttw7d8jNBT8/L+izE7bdJxIqbB0OCVUhZgCEtAWtt0hIf/G30vtQHmbOhLfeqnj7N98UlWxuIry98W32Jtsn+swBM3m4+cO2z2cyzlDnizqYVTNGs5ERv49g86jNLvzgfwvX1Iunn36ali1bcuDAAUJCQmzfDx48mNGjR1+3zjkiLS0Ns9lMRIRzoEVERARXrlxx+5srV664bW8ymUhLSyMqKqrUNtZjVuS81v/dtblwofTKUcXFxRQX25njOTk5tvdVPMPxPnRcfEhNhbQ08JOpr14EQEZCVRXG7Xka1j4N/cQkjAW2TSnitlebcjlTkB3DAgpZOnEpVc7mEBV7G1Ek8/BDYiEAQPsGKO+B5FDaNGgYaEax+f376VRNBOIwspSQ0exjkIEIHClKgxX3QhZcaHqIJRsDOHTai4PHtJy+5EmRSYuKhF5nIj4im8ZVk/hucDPIAlPsSP7MfoutB3w4eFjDgdM+ZOZ7YFIkPHQKkcGFNItPQW09kgU+4npreccys/GrtA1uJMYoLR3VV2JuwWYmnFtAhllUaRq17Fse7TWD1uZaUO1uCG4hDIgeIVCcgaPxsFiBCbbAL6jlE8vvtV/DMyVHnAO437cPFwP2sCH7KCpw5PAm0FlrqKmM9+8vIlYt907yk3kzsBP9Lu1ARqLYXEzNVRZGxnCDEFxARMekpUFoKITphJHOMq7x9doyrPkC+nY5RpeeCvgEgz4APILF72UNoIDZKLI8Xd0KiQfQZ8FPL+zl4c5+fL4gjKWbAlBVyRI8InauUP9CHu55DH6yWGOGpIM+2LlPAL5mCNW43GtNaFu+fWI6j3Xz5s3PQlixW5AOJElFVcU5bm9zmhO1fyBFNVvGSaZzpr/TOBEaSnetxjbHFVXhmbPPwtln4faz4Fu99DmYLPoUFd+dKJJp1AjmfP8ZeG6ElO/AZBX6JPv91tflr5w8TFxCBlQkWqXqIMu5T631eU59AtAgKv5EpBY4XwOAn0yMQWEvgkSXWcUX/98DIKAB3Ha49GvIAPLs69mTK5/EiPuyCjnFOSSkJPDMmmd4lVct/RMYEzUAeX+CU5/q+8m08q3OnrxzmBUTfzzyBVEjkmkemczy5UDsT5A4GYpWg2SdG5b/vdsx/WIdXsz4Hk5UJUgfxvr2M6ntW9VpnC7r0uiy+zmSDJmgqhSEmCALaPkZfmEdWDdF4tl3Q/h6ZRVMZtk2P+IjMvnhmcWEHfgAkk+CLgDuzip7nIpTWbFtFioqMsLY37MwymU+dfIuQidpMKsKJsXE5NSP4KePoMPPUHVY6edIToXcq7avZtz9Ak8/egm8vMHTH7wiQNKBRisCcBQTZJ8HhGAWU7yaenX607e/hlatRCBPSAh4eakoChQVSaSmwtmLBYw+ebvtLsd4hrOi9TSqFGghXVSJOKpNYsDZKWSbC0jOS2bD0cWYMSMBoR5BdM8KdL5uP5kHdPGsUM3ISAQXBVFrtYVQ4LiOl7HeiOeoK6+PX8TgLj9Cxka4OtbyQ1msOYp9/5q/bRgj2i+ADf3gTjfalNXpgLh3RZlX8Ex40LVPjihKFcTl4lSSM06x4IhguUpAr7C2dEr3geOrbXO8s59M76CG/Jl5GEU189M7vfjrrmSiSGbfXgTZOn8LXP0dDMdAKgbZA3QR4N8P/PsR1bYJUTzOvi2dIeNHuLTKXvnMFjQs+nvSCIoYDRSgjUe827WglcmbdajISEwNU4mcEyWeC8u+PaIOFD+nY8y0BpjMgnzXrWkyv7y8DHmLRFSX2+zXYIVxHCiJIFkUJ20UhH8Gp87BX/UhC7yq3MHqSa+z9g4/3poeytajwrllfe4kVAa3O82Oqr+RoZiQAb2sp/kV4KrzfOoi51meNQkFlTEnxsKJsRWeT+rye9lxqC2b0h/mpHkwRq03PgEaQsJkdDoJWQNmBUwGhavJJnpGvMPQuEmQBfld97Nqmz87DvmwdY+eExe9KDJq0GhUAn0MtKmTTLva53g+rnJWNNVKiozuD12XO18D2Pc7gOJUXvz+eYrNxZb7rTCz1rP4HTnlNE7Tq9zFbVlTkJHYl19AsiaS8MCraC4sEAH1sta+3wOcmgmH3ShCYR2h1+Zy++R9cRHL+3/NyrB+fHtxLn17B+DrL9O9O4SFqfj7CyNPTo7E6dOQJO0isUMbzIAk61nc+hN6hbV1mbMPJ81kfuo2UFVSYz3w0RdAYBPon1Bun3au3EObwtec5jjgtC7jhzB8GDJFkGni68hZ8G73OdxWsw2zFofw86ogrl7VsG6daiGUi+evbe2LHD0ZQZSXmVYxH7Bk7jrIXgKpOyDVMmaO+zyg05qYN/IeHqk/k68vL2L43QHIOg3du0NEhEpAgFDqs7Mlzp2DNMMlEnvGUqSCJHvwY/P3uDOqu8s4PXf1R75KXguqyvGqKnF5ZigIhB7rUFXYuM7Epwui2H02hNwiHd6eJupXzWbc7fvY6vMpXxattfTPh+Req/HWermMU43N95FsyAJVJeDNRKJI5qPJIuAGYwok/wr5fwKZIJlB4wveTSFgAM3Hjib5RA5VdcnscIwzSd4GWdNAugy6cAh/Grw62P7cwTeB3TssKqI5Gy59BwVrQM4X2XK0IeB3JyAC2q2yx6DANi5roM5Ppp9/fX5L2wXAbN8LyF9qKErVsybgCFsSfDl+Ts+R0x5k52vRe8kYjSo6yUj9qlfoeLubPhkSIWkuFG4EuUD0SRMAPn2w7sHWPnXzqu92Xe6ur8p3nEd2TAYx2Rf62wcq42wWD7xfm80nwokOLeT78dtpEGvXlap+HIFZK7O704/U8o1zuncmHzPtdz7JifwUnuMl2zU8OkbLww+9DlV6QNKHoFy2iFoOc9anAyO/nM36NT6Wtd/S76JTkPwDFO0BKRs0nuDVBPx6sVepSqct99vm05YO39LIv5ZLnzrvepqE/AtCRqtpsQDXHw9NPxDvy3i2OfoR3Y6v49RoL77JP8HspSE89ZQXiiLh7Q2BASoGA6SlizGNG3UUqmKT0Rpl611kNC8/qK4P5WyRkLcS/A/ATxLUelyQPdzBQQ7cMOcXusZ9J76voJ5q1RNse6p6O3glQsE8kKzSmAwBg8HzHtEfgOr3Qbsfyj3Hu1Mimf5JOFEUsW/X95C9VLyKj8PVTZRcnwDIBGa0gF5bMOHFpn2+/L7CkxXbg8ko0KOoEn5eBro0usRd7Q7y5AcdiGIIdw1sxSuP/AiJy+HcHPEseMUJ8ocpHwoEwWPaqnF88OPLluveZz9vynHImAryUdB4Q8jDEDgEJJmoFlFEkcya1WI5AiBpHWQvAg6CpIBXPQgYCAG3wQmLgTOiO/RYJ96XMZ8mzvuKt/IX27qilTR4azzRo0VVFAySmXxzEWYHh49t3x54EvxqlX4Oy73u8tO97DYBSNwXN5iZTV51WQuWGvYw/NgXqKjc7QtzPIxO+9fpi3qmfefLkq2hZBbo0WoVokMKGN3nEJ7Nv7DOFsyqmY7Euaw3Wj+Z9r7x/JV1RNx11WxbdVr613XR1/CTaZVv4kvFiAaJHt4qHZd2gizo2W8viUs1fDY/jI/mhJNXpEWyUZglYkMdqoVO9qVmmy84/WsrflgezKRZYZxP8ba0FHnKtBozw7vaCSES0NS/NgFHz7j0qVuhntmKCRmJ1p4qzRe2gCyQ+u3lq7HQo3ogT34QQ2q23iJniiPWis7gu3FbkN4aZDvHQ7GDeKXWQ/hlF4qy4cBFj0xeuvIT67KPoENn021ZGAHDM+3XZb3fjvPJQXf2/9C/VN25JIIkLPu8ji8avcKouNtdrvu1tAV8cnkFOkXLc1icgr/4wr0OlR/L6ZPj3pKRreGL7334YXUEafmeyDKEBxbwcO/DPNprK35myzlazYBajzofH1zm+O4F39Iqbr34mzuZvMRzl3U1m3pNOzmvgaY0uDwHCtZa9nkJNEEQ0B8C74LTvUS7ph+I/aKcPm37eT7tqy6vcJ+U/KvIu+4vvX0JvcJccJX6P93PRQWQNLxR5zFerjXK5d5NyVrKGxd+B1RmFLTngUYbK9wnRzsX/faSmqllzXY/Vv6lZ0NCIDlFHqiAr5eRjvUv06/ZMR6qc7toX2041HsRRRGBWVPmx3AsyZ8CgxZ/XyMdGqTy8l07+D5tMoqkIAMesgd3FFVz0efvNUcwy/LcKai0X9LB1ic98PtrEs8QwjcrqmBSJNvaMqjtGWbev5UoqTdRJHP7QKsfZSD4ZELeNyAVYNuPtBEQ+SobFp2ja1xV13FyRCm2X7X3TrYeDGDzfl+27dGx94QvucUeqCp46U00rJpG/UbbyK2Va7G7QUe/Bm5ltHYGT5aoCjISTYqiqT9N2ABjvGM52X2RSLzhME553gVU2TEOg2q02aBOnKrNeo8lJJwN5sQlbwJDtQQESGg8ZCRJwmxSKMo3k5yYR8EdYRw2Acg8Gj+CTxo859KnX4u28+CJmaio9L3SjUVfrkavh507hZ2nLFzMvkiDaXGYVKF//dH6U3qGtXE5xz2XPmdR+h5URcGE2WqJo0NQE8JOXITUfU7t79bXYDe7kZGomxdJ1SnhAAR7hnGux1JR6cBB5ir2MVBt031kmwucbXUd5osEJMCJfflM+zmC33bFUWjU0LJOOuNu30evZjtoc/Q9zpkUQGJE7O182/QNl2tYZdzPkKPTRDVgb5XfPE1Oe2rCCS++muvDih0hZBXq0WpVwgMLuLfbMdp1XMiQ5I8wWPSv+S0+4PbILi7nGJcym1lX1oOqcjIklCpBV8A7Du6w+F7KkD0ObDxME+UF1zlehh3D5qTvugKi+5V+Dkv7er0GkHWmgNq+yWxcXwgFeyFtCxTuBlJBMgl7gDYUvFuTkNSPfmP6OK/LxWeErlO0VTyrskasy/59IPAOoto2J4pkPphkpnf7nVB4AHIOguEUUCjsubKH0Nk8qtLyyRkcvlgPPz9BRCoXuWfgh5q2e6eqsPe4F98t8GHZthAyC/TIskqwXzFDOpxkVLdd1A96TPy29TdQsxS/oIPdvtd93Tm8FQdbXQHkboC0xeI6JAPIetBFgn9fUs0Dadyvvmi/R4GCfVCYANm77O0lCWQv8IgHfTzhu39x3w83GLNsDIe+XM8fi98jOkri01mxhEfY9USpxBtVUcFcRPU1PhjSdKwPOcL6PX6cuqjnYrKWYvR46GWQJQzFZjyUXKKDElnd+14Uy2Hivauwp/NcArOKbPMpM7SAVqde42zRVcyqmfvuN/F8gsWmuccEhYegYDdkbQZjotBdZB1oAsG7Ffi0hg+LIBe7LebYMZG9w4rvPodqQU62GH6sStNq93LilxeYszSYz+aFcPaKkBsdfUft6iYR7GsmStKKPu3KgbwtUHQYcvaB6bKwScgakP1BXxN0cUTdNqWE/mWES3Mh7y+Qz4vv9PHg1w0C74ZTloRUNUZDG0uilDKe7VffjeG7L0Ocz1F0DJJmQ/E+kApB4wHaSAgcLHSXkxYiSEXXAqtcENXLpjuvXqkwe1ko649FkFukIzSgmB7Nk3m03z5ez3iVzRZ7bbR3FU73sFScKbF/RW5/AgUFRVHQWjQfSePJ2rYzaBfc2GUNvOvip6zISHCyD3XsAJ99kgr5OyBjJxQlIAR1xbLeRIBnXTYmhNMl/vvSr9uNPGTVnVeugIigy1CwEzK2QvFBoEBMDY0X6GuDTys4+YUYp6Cm0PZbANatMfPd0lA2HI0gq9CDQF8D3Zul8GBPu14aNskXvYcPV/uscx6n0FAUX4Wg9UNAkZxsK7/M11Ld6iZM3gVZC4A9Yg561YOgu8GvJ9U7RhJUdJXatRySZ6Sch4xfgQ0gZYEuFALvgMAhLNowG0VVbLb+PgWuvqbeemHXtfoJP+l4L/PZxw9zRIUkcY4zkDEX2AiyEbwaQ9gj4NWYyN6NkNLTaBWTzJIllvZXkyB9CbACpHTRp6AREDiI9XvDGPmon6tvIHk7ZH0P8nFxr/36QMgDws9x3OLj7f4nRPZ0vtfgsn81nvcQh8x2HaehXw3iNMF4GyUUFJLVbE4ZrpBmEjpni5y67GlxvPT5VOI5OpC0l67LX6XYon/NbPIG91bp7zLHx6f+xOdJq0FV2RWr0rDADDk6kQAMSErVMX22N79uCCMp05sAXwO3d7jE4/320ihqJ1ya5mKPTthRxPtzYvjzSDSyrDK4YyLj79oOfvtod2wqBSpIko4vGrvXCd9M/5WPLi1DVRRqoOcsIoFDp7C2rG473XnO+snsl87SKeEdFBTUnEgCp+x0vXdXL0P6VyBvFmtm4F0QOhoknc0W89KLglws2l+C9AXAaiEbeNWG0MfApxW7Vr1C62qrS78XJZ7tvKtX8D3yoGt7Rzj45DrHppHw8mQ+XPESt/UcRNc+vnTuLEissbGg16vodCLYvKBA4vhx+GR3NbZLQjZrEdyUzR2+dRmnC7qrNNgzXpB8VZXAiee5q0lXPntrCaxqA96RYu56xYDWT5BPc89C4gKOGxRM2H1ynb3rudUrOkoh7EQ8q5/ndyBoUXCFx8m69hvTtWwKP8pfu/04eUFPYpKGAkWP3lNj2+f1Si5VAlNZ9FQ98XtHm2YZ+1epNs3S+nR1mz3RcRV3GSNx8jXlKjDrDDbZo0VAPQbIXWG13Z/awE9mZHg7frq6DUU1c+XEIXzfFues4hPHye6LXO5dtlceMTuest07m17Ra4s9GC01ld07Fe7/phMZ+TqmPr6bEZ0SSM6/SLsjk7mqgCTJfNfsPYbF9Ha5dwnSOXoenITRrDit/TbfgK1PK0CeDfqqUOVThNMJW/uVy7R2m2ZqKqSdAyaDnAWxH4O3RZmzrpkVtGl+/6M/r4yv5ubZToH0aSBvE/M2YgL4igQu1md78SKIi6sG1eZB4mtgPuXsG5B8ocrTGM99iO6PqoLL1HeP+/vtoJ+/9PPnTMlZ7r5dCWy/tJ3237WvUFuAfGM+dyy4g9R48MqBFsZYjvy0lNlLQ5j5SxAnL/tw/rwzH6haRA5xPR7C+y2RUNTHI5BLPVei13i47PNVN91LuinXSb75eia0bFkDqs6Di2+A+WQJH4oegu6m+/7f2WEshBNVGRTdm/ktJrnMp03mo/Q7PBkVlWp50Zz3FuuTvz6EA13mE6EPcepTgXcRTbc9wiVDhrMPpcsSkSgWytxTTyyeRJ2IIyJJ9VAHMn0pz/apvaeplfOk+FyBPTU54xSNf3+KfMueOqPxa9wfO8Dlut9I/4Upl5aDqqJ+t5nAC1VL6J3n4fIXUJwAUpFFpqsBIQ+RlBVPdG6fCvfJSXeugE1TLUyl3dxxHFSFzbdDaBv+bPelaOew3hzTXKTVvjdQUNAZPDBqBedP1nhxuvtiIj1DXfyprbc/zuGCi07zadxTIkk6SgFc/hXylmLTzzW+Qk4Lupttm1bTvvri0q+7xL1beWotQ9ZPAUCj8eJQ11+o5h3t0qeOO8exL++cU59sPE3VCJcXQe5C4IrQ8TS+Yn0KvpfRHw1g+R9G+71TVWEDuPIDFB+w3Ds96KKFPyugH1GtahBFEvu2HIP87VB8DgpOgpoDHl7iOTIXA56omnAaHdnFWTMgaXip1sNMrPOIy3z6LGclE84tQEXlo7yOPNGk4vZop/lRWf2rykAuhb/Hnzv92LJDy+YEf67meGJUZPQ6M7HhBXRpmEin6jO5u/WMyvVpxb0Up3mwPuggG/YFcOqinpQ0DUaNJ1q9jCRLGIvNaM0FBGlTWfZgbcKyYO3w7vzSaxazlwbz1y4/DhywsB4lFcWyBnrrjXRufpmxbVfTueZm7h3tBT4h4BkgqhvKHmDMAlOu4JgVJkNhGiQtFH0sj6fp4Hvo4JtA6xZaplvdqampkPYn8DNIGaCPhfBnQd/c9hvfSb6EePjzfI176R/eESkrEzIzMQf6syhvG58mLiTTJJ43NRRxL7os4VJuNdbu9GPdZh0bEwLJKvBAUSW8PE00r3GVno1Psrl2L9YaACQGRfdmXvN3kdPSnebTnPwNPH56NioqdfKjSfCy86mb+ddhbNU78S4wQm4u+d46Zqat4EDeWcw4RGdM9oWOP9DKvzaH5+sY9WoUa/eHAnZOSURgPjOeWMIBy0/ubZTAL/O7QrUFcOl9MFoXREfuaCMI6oB87Cte9QhiyILDTPkxgmWbA5g+Xcf06WK/E/FT4n4P6ZcJ04MJy4J1E2bxU48ezFsZxNqdfsybJzNvnjPPJT4ik/d738cb/VqTnN+MuE69CAjR4hcgWSqZCd6USF6skpujUj9wA5ufncj0tY/Tpf3dNG2lo107aNZM8A+9vQX/sKBA4uJF+zCRsQdaTILAhrjg4EQ7R0nRgcUnF7Z2Du3CWrJEb8Bj92qne7fMsJcRx77AjELjnFrsaHZU/K2ye4UjT7OMPbXtnX24kGAkmons3dADshdC2q5S+EB2/pXBIILz6tZ1vWy3+MUX2n5pt2mW0Sdh03yMNpHNWPztfDj9I5yYKvZ9//qg8xOcxByhL6flBhPqlyGqGFd2nJp/IpLBltOnbj8+zwa1nGg3B+glKAqBxllw6Id9zPgtjAVrgth91IfPP7fMcexztkOTVPhJ+B5o9BY0esP9gS2yqVp0lYzcKzZ7arhHINL+/eKDwz4fJZ0HhL5mVIx8cvpT2POpkz4/bUA6CeuaseuMEOprx2Tx/T0LkDZrbBzK++4FW72f1FxQR4BkKRAgaSD8XThyAdLGwamfbDYDb2Dlh1rGvh7B4u0RNt95RFAhM578i33ZcwArL9xMm8JgF/tQkB/Ee4ZxrigVFZEA0er/6hPUSlx3iT21r0csCSQgI/FmdnsCFgaKv1XQJzfkyr10fDacGRkJ/DA/mClT9MTECB09MlJFIwuuzqFDIjlD0j5hW+7d6y0+eLWr4KzkbYcTnwGfUZK38sKxWnysPQWnWlDVK4qpDZ6na2hLcQ3p6ag+Er8Ubee187/ZbERqGPAu0GsjaH1d7dEAX70D1QJRijNodfBNjr31FiDzePxIpjR41mWcfinaxqgTX6Oi8mhmRz5peY2yxx0XwbuKc3tweo6MBVeYtvkdm0+uhncsDyiNnHTnGn4yj0Z158ukPzGrJmodktH+rCu9TyWf7dRE9/f3OkFS1ZJ5/spHaGgoW7dupU6dOvj5+XHgwAHi4+M5f/489evXp6Cg4Lp3NCkpiZiYGLZt20a7dvaIyvfee48ff/yR48ePu/ymdu3ajBo1igkTJti+27p1Kx07diQ5OZnIyEg8PDyYM2cOI0aMsLWZN28eDz/8MEVFRRU677Zt2+jQoQNJSUlERdmjU8eMGcPFixdZtWqV22uaOHEib7mJfpzUEmoWwF1HXX+T5wGz7LIZD0ZA4B+u7dIIYRkDUJAZwDLCSYXYWCaaGzIxaaXrDySgBRAAnAfOiK/3dOxO6FBRszvu3pVIHkFw8TI07YJUXIzqoUH6yCzKkFuw+7savLHuc1bRj0YNzIwYAQNu1xAXJ7IeSJLIPp2UBJs2mGmwWMv+VY/zNm+QJkdw+20m+vaXadpMJj4edDpRheHoUTiwX2HpyWfZEPOZ2zEtDW9OfoyJBTPEdQYDVRB2IC1CDvBFrNoeQEAwX6cHUZAoBqHXGWiQ6nrMS/7wW33xPiukFp5hiXgeL6ZKjvt7pwIzW0KRxT7V5c46BHnmEd72UbzqP+g8rno9/H4vUva3tt+bTBJaLdD+Z6hmqUKmmsFapr0oGQquQNEV2DIUVANZv7jOj4tUYROdySQIPcXEcJle/IkuNoqdj/sR4ZNNWOuH8W44xqlPgMv9/utH6O5meh+gMQdpTDYBBJFJM/ZTn2Os6NSEgzVP4HmsiMAieDDB/f36ymGcWgxoTKx/OqEt7sOnyRPl9mnia+2ZeM5NNcBqiPvuBRQCF4EL8Gf7RuytcwrPY0X4GGDMPtefAsxsAYU6MMpQXM0P37NiI7vjOFTLcm2/pgYctSTejajSmXadz6D1DiFm+PIyr8Gg6Jh0RgjXZw69R9UMI20vQe100Fr4j2YJTobArhg4F6IjvrFo7//ne0hmI8MOQ1SeS5fYUUW8AE6deZSwHD0Ti6c5N/IGGgKBQB5wGMiB+V2r82DncxgsUpp/MTy5CwItBfPydTC9NaRZCmxoVDi0D+otc+1HKqEsYwD5+NCIQ3RmExKwuX8fYvseBo0HVR/YVO69TsgMZNXeQjyPFaNV4IldTjX9bJjb2N6vqB5taRNxkcA6vQno8HaF78WEbufx6Py9/aCK0WJkSRbPXOEVDJvuYdJpkelxwnvvoTMauUgsh2lIBsEU4UkhXsgoeFKEJ0VUiZU40HETyjmhid11FKq4IWQcC4XVlkJbmVUa4OV7Gs/jxdRJg36nXdsXasV6A6BIntzdPxBNjpnQNo+gi2wPV67CiDFIRiOqTgcf9UfKsy8WE78YyMQrS50PGgjURqydGsCIeJbS4XSfetRsd0xkrRic5NqhgxOdglxMZplLWWK/jOz2Cvrqt5e7Bn6+OBzzRUEQv+0k1MpwPc3JEFhh4QMnJ/fD60ptMcf7AkMQ89ts6b8VquXlFcHEe4cysehz54NGA/GAJ2KCFSGI2r4RfFrdC+nceQC6nIdmbmLRD4fD2njxvm4EtMX9vn2YBmyhI6GkMZhFaFDEvp02kImFX7r+wBNojtjHEoAcIDaWrQ0v0sHNNr+LVhynLjn4E0wGLdlDbU6xoFdzzlU5iuexIsLzYeQh198qEnzeWhTQBOg2pDYB+nzC2z2OV737y7x3abkhtHtxLadzm/LcM2beeU/G21scyGSyZ56WJJGdRqMB0nZw9aHOfL/0WSYxgWwCaVLfSNtOWlq2lAgKEr89exZ27TBz6rRK2h16UjwU186Xgtezu/BQ9dPog6sRecfP5a43qy5VI+F4Mp7HionMg+GlxPF+1wxy9OJ91tFRTMz/HsIRz08AEBEM3j6g04KnAl750CINNDB+Txceq34aD/8oou5aVG6fAKd9XkHiIrEcpT6JxFGMHg1mvCmgNic53DWRR7taqpQoMHEDvLbJ9RpqjIOzFrviM1mdeTr+DFqfUGKGLSu3TxdS4whYlUngqlzXA5eC0wOgZom9ogAv1tKTFCIw4IE/OXRgK/GcY3rgq6QW5jnvXzrE+hSGkOWMCEX4KlA/lCzfNNs4qcBlYjhKfc5TjSI8kVFs40TjFDoPPo0qgayIZ/uvEjEfBTqIeAHy9OKAz3rCGzvEvfiTnjzHJxymEVqMmBwMThpMmNESdf8dXKn+h+2Z2vItdLjofI7LflDleWydfnP63UxM+1XEXI0BmmGL0Xba/Cxr3JyNT3Fujuw8Tp0tv1VFG2sEq2G1jknxlv3uvffwkIxizexlGVvZ4fgqGMw6Jp1zlj0GnISabtblvVGw2cIlbh0jsfLoy3x2bDy6kABG3W+i/0AN7dpJeHo6XIIZDh4sZsmSD+x9CjTCaISMUnIdBwxGHZPOO/epz2mol+bap/2RsLEaqBodOb0crtsonOgXiKMrG7hILGa0yJjQoDDX+x6OvSSMpJOZjMFcQJcL8OcPzrdgWht4pi/oJHsQg+PxbYgBaiLW80zgBJANS0NHsTfXX9w7X2AY0BX7fbPCcv82pQXRPSNTDIsKdVNh39fg4WALf7czvNHNvo5/lt+ZgbFn8K3SnJDeX1Z6vQHIx5vdtOIUtSjECw8MBJNBG3biX8PMjE6ZeB8XdoGH9gvZsSQW1YULgeK9qWNn7oo7g3dUQ8L6zSpfDrzQmEDfdADihi9C8o4qV0+dOOZRJha4qVLuj9hTZeAIkALExvL+0HhGVj2NV3gdwgfMKbdP20+1ZfWkNq7ydSTiXnshyg1nAUlAtQiSIlKIXgILGcwjzCSNMLQYMUs6/PzEvpiTA5LZSFSsjofkrky8sNH5+IFADcQ+o0OsgZlAOuz178XSU/Wd+1QNeA2xXjrOqQPAz7FMzOzFxFwLCUWDmIO34fzsmS3jlRzLK0nxjK1+Go+AKkQN+a3ccfr5UgwjCi+73ocysF7ThGoBaYQ0vwffpk+VeQ6zCo326znmWwyS4EEfmAGN7HkdMMlQ7wk4EwSqDA1l2LxXzPHzVOUpPmc5tyGjYHbKmaQgATXj8niwSzzep8QcvPsIxLjZ+jZWhf0WE1FynQYESUKGb5QCPc65tk/yg18aiPdBvjDIx1VuzCKAtfQklTB0GInhMl10G/joVZH5sOR6Y0ZmHT24SCxFeBJCOl3YSIgunUmv2tfNRslGep517VOqN8xrLN77ecMQP9c+mZHZTjsO0AQtJtqzjYYcxhxXBf8HLlOoqZjZ0TH4a2TIXGqOshh0S3m2HfW1eRnvkeRrRKsIOUeriHtv0oBJEvc8uBCMGrhi4QRpFHh5C7z7l2tfht4t7D1ah7V8ZND31Hx4S4X7NOG99zAZtbzO23zJExjwQCmxgUko1I3NZ/y9/egSdR7/Gl0I6vJhBdabNkQFC7mu6oMbBVG+jDWw2OjBpEceE2uBN3AP0BHxHMs4QwH0EXyztxa9Ys7hV60dwd0/LbdPO0+3IiJI6IJx969F0vqW2SdVhQsZMQBEdn0ZffwdZeoVuQo0PKwl0dMEEmjNkPCVs73ueCg0fkzcZ1QYdqU5HzQQzq+K2jTTfwHPP7x5g7eYxjOY0aLFSK16Olvmw0uX4MhBE1FVNCxoKNPOon8tZQAvMZnj1LPJfVZY5cJ7+7xOg+gpeB4rKtV+qEgwvRWYLfdmZDiEL3Ftd4kYVtIPE1q6soF6HBc6JLWZeHGd6w90iP3OHyEnHxTjdLBNZ/zvETbQuGG/IvnEljtOyQvg0JJePMcnHKEhEaEmunaTad1WpkoVMU5pabBrl8LZU2aGxjXBeE4kZWp7SbxK4kwQLK0j3s9q5cvR4Dyb7HLoS2h41bn9kjowyGrOz6pCz/nTWZtyO/eMVHjtNahbr+TktqPYVEyd14K44Flom09nPoO4bHsbkwx1n4SzQUKGitn+PJdXT8HfX1Q7LQ+Hrx6m+fRGGCWQVYjPhCNfOsto66tB9wftnz/YE44+TVxoq8uuOgI47xW/NvJlW3SeTRhdPg/6n3Juv7guDB5u/3xmL8Q7mHv+4HaGsQAzGpvuYp2/Izy/ZP7LT9jaNk+CvV+79mlqW3i+NygyxOtg7y6xV+ynKaOZxT5auOhGADJmQjosJbXXYHFeMzy7Az760/UcdZ+EE5Y5+HhGJ16seRbZw5fYe9eWuz4lZ0ZSrIj1N+a2qWgj2pZrg1p0vDXNwi4TVH8A/m1fK/cc3254iIs/+DKx3WdCdvIHFA+IaCMqfGt9wVwEWQcgeTNXi6vz5WM9xbocg9B1auNW18GMsFk93oGJDRfCnQj/RnBHiOkLIS3AN14knMk5ARsHgWpk6b4BTPvxCTwzJV7/vRkanWSzv7j7X6tmU/3rWgT+AbtpyYPM5igN3N47DSaiY7W8d28HOkVdIKBmNwI7Typ3nH7ZcTdHv45monGauI7bEDJpKba6Arkakx8axMS60+A+IAoREBfRCcLaCjukqkL2UTj+CaDw/OoAPC9lE1YAPc46y4BWWPXUZF/488gK9if3o3NnkbG5PKhmE1NbPMFbBz5EGxLIs0+buW2gTKNGklNlFBC67YkTKuvfqYnxvBC0bj8h1oOScFwDUy73Q3+1NhNrT4MHLNdtBgJqQ3gHkeFYMUDWYbiyHbyDOHPRA42sENn5BfQ17yp3ju+YC21L2A8VJDbTiTPUIB8fAsimBXtpwFHWho1gtyGACf2+gj6W+xbcESLai4zQugBhL8/YI7IgozBx9ON2m2Y88CTCRqZilz+sdlk1lo8OVufuuDN4RdYnvP935c6nTcc68ddHzcVzFI8Yq5q4zicr+10TwYFLARW2aQJsmgudLeN0hnjG8RkruK3UfT7ohXAyfYVwIqlQ/A7oSpgrj4VC/Sft1y8h9hmNAu0vwsbvnW0MO6pAu9H29m/O7szE1E1wF9ADYRv2bQCRHSCwkaiCYS6E1C2Q+CvHk2rhqRcEvtghPyIH1Cpfd35sFBOl74XMaOWI6yMhqgv4xIuglaKrkPwXGHL587sUeln8hGepztNMYxkDXcZJgwlZp/Dqq5MAeI/3MGIk533wc8ixAJDiA5EvOusITrpOZ8TaCc56qgY4GcvEudFMPONQASUcGG/539GWpgDpsGlFQ7bFnMbzWBG+Bhhdip/QyfZ74h4mZs6z/zECeBPhP7HOcWuffoTpO0rYNPXA80AD7FnmrKrTBUj8tg3fXW7rrM93Ah6xtHe8bgPwfSxLekTSODSJoAaD8G8zodzn6OETcXwnV5yIUj0nlL+qiQGI7vcxuqgOZT5HP+fCCIvPRKPA6xvhTTdr7R3D4I+6gAT3+8G0TXa98xfuZgzfkI+Py3OnIjG99nsMqzfRSU/9gft4kNloMDvIN0Y0KExq05/n+/1l69Oje+CLFa596nsvrK6Bi9OxThoc/8K1/Z/x0NuS20Iq8uGNT0c73zsvYCLC3+S4Bp4DZscyMa8ZE1MchH5v4A2EX9vaB+t8WgjbM3sSdYeQr6s+sEEkiirj2TaYtCRlRwAQ1f01PKoNKHcN3DMPWlrGJo0QjlHP5ncoRo8RneVdMT7kM/GZDRwNSLP199RnrvbiSR3hte5CbgR4c9LT9nGycjgiEc+q1jJWBsvLJ4JPQzyRzl0AoOt5aFqOT87brzm9B1p0wnuWI+lDyl0DZ3x8D6/tm4Y5IISnnzIzcJBM06YWjoYDFAVOnlRZ9m3XG27T/PCZBxnvORsCJeFjigoTjD4PD9DIoDWAPhtqHAUZZv4WRmGy2I+6n4PGbjihiQGw0BK39nZXHZmeYn3VKGB4R+gwjjgeCvUc9q/L+yG6hJ6aRgi1OUkO/pjRIKGyjfaYW5yj40AhlMkK3H8AvnfjJ/2iNYzr52yLcbGrRwGTEfNFAY6BYYrOZuNya4d/EWhk+U0hMA4Ii+WVuypn0zyU2JDfJ/ZwfrYlxLrc0aFPCoJPeTWWiTndmWghkDohEqiHmOeXgeNATCwvDKnOk/Fn0PmGEz10Sfm2mOQqvJt4ha67TYQWwN1HwbvE5Rfo4Nf6giuxNQ78/byJO1NAaIHQH0s+pyqwLl48SydCYFQY1M50tgeqwG5acZT65OGLD/nU4hQd2Mo994cwv3q6bS1YO8fVDrorBtqMsQyhCm98PoKJGfNdxynCMk464ApwDFQTNHghgGM+2bZzJMyAJg7zXAU6PSTkKLMMgcX+ZOkFAUOjwLDDMG+h86nG94Qp7e3r0+/mNjQPu0RQ/dvwb/t6ufdi8/EOxIadB1lH1Qct5PQynu203GDyDCJwMrrvh+iiu5S5Lh8thgaWLbs036UiQeyzkOQvPnvsG8mE1WFizoYCQ4F2uPqaLPtLzuXqZHgKoSy617voYnuWu1fMOdyhwjZNVYWw0zrSLQm8PI2QO8nOgbJidlMYNQiQQFZkFNneYMGvMPSIc/sMLwh9yeL/UuHNmQOYeGWZ2EPuxq6/OOohDte980RXIkKFMaUiNs1Z2TDGomdqFBi/Bd4rYV/eHwnNLbFwqPDmN/3sPM2ewGCEX8cqA5bo06qtw9nxbYS4d/URuk4VytR15nzYjgfuWwxRWogdDnF3QlQP0Pnb2+cnwtLaFJqKaXxAx2lfcS9kBbZ/C60d3DbHQqHpo2DQimu4M6UpH9cXe0vciCVIXuHl7l9Hkmvg41FERIen8KxzT7nzactcqLsyhAlM4ntGYUZDiyYm2nTQ0aCBqFCenw/798OOLQZqhuziywF3o8kxE9l7MpJXhDMPSisjPaOIsUbMwY9/e5h3DnyMR2gA4180M+B2mbp13bHMIDlZ5eRDMl1KcCIL8WQjXbhEFQrxwpsC4jlLB7agfKrHMzxfBLN3L2HgyjsPy+qBUuT09c7E+hXiaRqCnX0PTvvdfQhOlHVOWeaKYZGOSQ3Fb6z6V0Vwfi/4Lw3kZT5gFqNRkAn0NdGuk46aNYXv8upV2LzJjCxBo0ExLAu1LMQqdDsPdx2xi7GHw2FGS+GPA2iXEktT5Qq1DxgJz4cRh1y5fooEPzWCVD/3/nxbX6nKWnpSjJ6GHKYTmzHptKXLBsFAXYQPPh/hn08DmkSRVS3ZZb87QgP20JI8fNFgJohMOrOJ6Fgtp5pcpFYJnks2/qyjB6mEYUSHH7m0Yjf1OEagNpsckz9vvFHBYjkFl8gaGWvrUzKRJNCUDIIpxMvGP/SiEL2uiNOvCsPShAXv4RHsIcqkhQSBjzfo9CBLoDOALhNi9mBAa5tT7/EeRtVIq8uCy2tdms4GwqfthK0cCeplhLCipiB2RPf7CF1Up3Kf7QVHK87TBJi75R5OfxfqLHNpgFoI2UCP8IVngSFDx6RR4hrGvjeDy8YqpBJGpncMhIWBpyeKVg+qgmwyYDYWcfYBsf+ODPqe0FqdKmfTdOyTP1AdMac8EByAPNGvgqA40vsWo8lXKszT/DavIz2iz+Ef34Ggrh+X26fJp2oxvfg0uYpqs1OA8HWYZTsvBCAyF7zNsOuCq4/3MtFspAvZBKAiEUgWndlElViZGSOq0a/KWXzjWhPS87Ny+zTrdB3Szp/H81gxEXkwwg2vLtcDvnWIfbg/AoLd6AYmNPzGXRjwYBgL0GMQ/i+lPhMvr3b9AQi+RHVgP5Bu+a5bGFn+qW55mjtpzV5aEEgWg1mEF0Vkx8cwvVMm3icEz+Xhfa42KxD+qbNB4r0aEYaUIvbIzhegebJre0c+q6dvY/rebtUJFyJ5R5e7p15ZAJEO+lcuvhymIcepSz4+qEh4UkRNTtMkNoPPpBAmJq537oQOsf6FIOZsMYIXkwGTu9dkfF03BOQysMuzHmHeOYS1GYN3g4fLnB9FCtQ8rOWyxcfrYYILUyHSgd+uSFD/CTFWqgQts2rza3zlbJpbzjeiil8GoS3ux6fJ4+XO2e9/jyE7SQhAHRKhlRvK81UfsR8BaD3iGXCXOFaVO2ahCW5Y5hqYUwABYyA7Oxt/f3/Xg/9NXFPwV3BwMFu2bKF+/fpOwV9btmxhyJAhpJRXQ/EaYDAY8Pb25tdff2Xw4MG2759++mkSEhLY6MYz07lzZ5o1a8a0afaFd9GiRQwdOpSCggJ0Oh1xcXE8++yzPGsLBYVPP/2UqVOncuHChQqd9+zZs9SoUYN9+/bRrFkzW5tBgwYRGBjInDluFHrcV/6KjY0le+NG/H197Q0dol/xsyg2lgx9B1UNZ3ILSM5N5oolyt83p4jAfBNZPlrwBz+1mBi9D5F6T3KC6pBr9HBp75dTjEajIctHS56/2KQjfSOJ8ouC6tVI91S5kHWBxGyhUQan5hGUb8bsbUQNFbtFvJc/ypWaPPvsePLyPHntNQ1vvSVKjuqc/YMO9xXGjjnHnB+qEx2tsnatRL167n+jqoLsrdNB8aXz3L3sAZamuGEtO2BS7EDGh7biENoyx8l6zdbr7lN/ADV845wPViLStOS9IKAm+NZ2/xs37feFBLPP08M2rlXPpPP2i8ttP538UQ/yqnviqxbRQC/RN3cDGswo7X9Crmbx2qtmyws4/A4cedfp9AevSJwJfpLkogKX6zb6mJEtpCfr/Eit2ZLkoMhS+wQwY3JHcqvrqebli7/UmMJMtdT55O4c0VV7UiW8RFahMiqClBwnsM8/k9mE5Keihkr4qkUV6pO7Od44tkXp99tdlZKy7rXj/LC296vBvpBgFqVucboGv5xitBqt03NUzSOAi/vEsSf064eHozXZTZ8MhRlM2p1Rdnt3fQIOqhq2JJ2p8DhpA4MZuu9lihQ3Uo0DZCQ21H6IAJ8apT53ZrMZxR9kP/BWi4nSexPoGUhqzZbskIrLHad4L3/ivLyJ92xHNX0z5w5cp/kUr/PiSIKIoJowLAKPuhYLjaqI6grgFNTkSPRrGJtOisH1uXO3Lpf5TJRy7yq73iQv3k7Ud248WKVg65jOXO3SudR7l+uvd5kfer9Azicds7RX0aDim1sofuNvRgoQS1WMtw9h3t5cjWzClaA4t/ci00eDOVQmUC2s2L12HCeH6z6oSATm/UycZNEo9KFQdTjE3iWqt5mL4NJiOPQ2oHLwqo4zgY+6XTOv115R1r7tbs0sbd8urU/VoutRnJt1/dblv7l/GS405/UXJgNw8KAow2wlF5UGkwk6dkhj564QatWS+OorUW5aZLkRxiRVFZ+tAeJeWcmQLDSoYrOBU/mJ/HluHck5l+nmVZ9mIdWJCPJDMmaBIYtDRjhdWGwbp6hL2Tw2bYtTP34d15S0Kr72cQpvT5WqPSs8TmXda8fnKEBTSKyPH551OnDVL6jcPTg5PsD2XBgKo93uee7WGw+tRL9UYZ2UkegX3oFlbaY5zdksr0KCDgmPi4REy6DajO34wg3rU6Tek2y/6uSpvpXaK3KC6nAyI73C+5feL9Dtc1Fanz4wXmZpxn5MqmBmnuq+mJoFnrZx+t6wiYcS7azHr+MG0SakDdOWBPP9d6Mt2XBkvLygVy+ReSk3F9atg8xMqHbbAs63Gm67F1PqP8uzNe5x2r8WFW7lzgPv2NpMCOlNl6DqdFDnoJeK0EgqBDaG6veLMvcaT8jYD7tGi30KOHhVxxbtnVwpyiNal8WY0G3idyXguH81ii+ktfoD0ZpkZOtzqvECr2hx3IJLGMw4BEc3w8O3iuszAS77172f3M68DY1p0gT+/BOCLUGGJQlyIHS/SZMEGah9/GU6SXPQSUbRf10gVBspKhWoKqTtwnD+t0r3yVCYyaQDYqxCwy+Rki/WkPnfvsnZE81QVEePvkpwUBrjnhbEtclMpsCS8bepfx2iZX8wGCjSwoacgyioeODBK7wCQMN4Eyn5ldtTzblXaK98S5CchezmvjliQYqW4Tkm22cPSYde0oKqYpZUChyqdd4ZUJ+XWz7GAW/P6/Zs30iZvyw5MNenLqnawArpqRVZn0ruqVGN27nVg8vqU0XPYb3XOp9Avp3VmsXLOwEKzZrJPPww3H03hFuSaRUUwJIlsH07PDxqNWeObKmUruO4BmbmX+SJsE34a4rsz7gFqgrngx4iN3qo5RxJtNGsobn3pVL3bcW3LgkNp7AvK7lS88kq12UYstmTeZQ/Ujaw8NJaVFVheHh3Bka3oaU+mADVUCHZw3oOq54a7tma/tveplApRkaipk8cj4X2FZ5BYKvpFL9l2YmA1nV84wlvXn1nFHn5PqiKBkmCzp2henVho9i9G06eFFn19i23yx4ucxwqJsP/DbnRcf+K9PDjYFYboOz1xnFPDffwZVd2F6CEHnmd+uS4FqR7htJ161iyTKUHh9fzimB9/EN8dUR4KEztTSTmieeu5P22zqfK6s4YMjmafZIGx0SyB42kYUR0H35s/o7LdTc/OYH9+RecyKaV7VOtGJg4eRinT9dCVcVm5+8PVauK5+3cOTElmzWDWcv3sS95X4XneKh3KLk+ddmTl21bn0rrk+P6ZM7Mp63yvfPeEtgIAuqLTmXuh1xBdthn8GBfnbe5UJhXqT45rsvl9am89la9wtpeq9Tkjh2TyDQJwo5O0hKlCxKKAXDFnI1BFfthoOzJ7rqPkhNTq8z1o2SfLifWZcIr95OUHIqfn8xrr4lEdQ65vgAxXdavhzq1xLq8aE11fvxhlGAtqTKSBHXqgJ+fcIRfEPxEWrQws2fp1dLXj7/x3FnlZTmqzQ21/cZ5ebPwt0FM/3IgXl4Kb78tM26c4B0aDEK2kyS7DVeSENdbkTXTct2Lrm7jzrOC+CUj80G9p3ix5v1O4/Ro8iy+TdkoZPY1H8K2l6heXSQJqQh2H1hJ28UDUFCQkekb3p7nQwbYIrvWmA7z4VV7lNRnMbfRSN+TQ1ckLmXkk2tU0Wr88DXJeJskivQeoFfQq8X4ShqiAj0pbp7Hg5uesR2jdWADGupioKgYBYVF+XvIVgrFvdD6cqjVFEJDW1V4nE7nnKG2peKWVtIwLLo3c5u/67QGDj37HouubsWEqKq2qt4L5Bn1JOcms2lXHAu+fx1XBpSAJCl4vxJDvk7MIz+NN9n9NiGlpTn16Ykr3/HNlfUYLfrTLzUe4/Dh1rz/8UjMZg2qqiEqSjxL1aqJubF/P/zyC9SqX8Cx2wMxKIKE0SqwAbs6/eCipwYfGmPppUR3v3g+bPsci4qSKyx7VHa9Ka+99Ry2NdArhPpp24g0HUfV+CA1ehPqPCX0NKv9HhkKk0SEj1LEwas6soIG0la7BA1moet4hkO1e8GvpvhN6na48BMAKfkSET4qqj4cqcsfENpWBNtIGmGnzE+Eq5vt2S2Bg1dgi3YQVwx2XaEsGT47sDZrtzfl4y+GoigSqqqhXTu47z6oVUtsFUeOwJw54tkuuX9B2Xb7UO9QzAWh1Ev/gRhNslgf/OsK/a7KYJEJ21wIF36FA68ACsl5MlG+Corshdx4ItR5WmQ4VxyIOxn7YY2QhcgE6s+FgHplP0eWNTavUMeSixFsPpuDSfbE2ysIvc4PH1lGb5ZQdbKFjaigM6vs2FWD31fWIjoa9uwRPJKSZHAXVHINxJDFlaINRBrXoagScs2HodFE8I6xZFEyi3tecAmW1gal2GXfdrwXjnbWivpQSs6PaL2WOn478VXTkcLaQOtZENgAFBOClWlR7NN2wpq2tvl3xv9hJDWZ/l6r0EqKiw5ihepbh/0NP660XmEojMY38wxtWYCMIJ2h9RHzySsalGK4sg6yhW24PPnG0abpOE6Hzhr54INXKCoSekJpCHxkMDlRS0RVFOBcj6XOVQD8ZFYbE+h7WNhKdci0967BxgJ75O6btcbSTIqylex7NetXjhVdRkHFV/ZgWe2xtDbNRk8+cmhrUWUmuIWw2aiW+4EKmYdgtfBt7CuCfbVe44KRCslDHnkaWufMQYsBOaQFtJgGYRb93vrsFVy2ERetNvXDl734YNIrFBb6ljpOOp3BJfjrRLeF1Pat6rR/JXCGZjuecJLHrbpOlHk3g4MOlnofFN+6HA5/hTNnTpKcm0x+wXmeCN+Ep2Rya19RVAlzUGt0zRaV/qy6sWM4ymj5Bed5JGwLvnJxqfP8WOA4jNH92bLjV1LykhkVsp04j0y37RVVIj+oG+eiX7LZAEJM+xkatM+tfi6uoRWHms2otF4R79mOYKkWv1/5i7VpO/npsp3dWk8fwz2R7ekX3ITm+oBK+QbivfwxmgsZu28xIKp+31ulP983neiyBjY88SJHCgTZRoPE7iZvs/3KedZuqc2ieS9SmqwCQp+a/Z3dVrJua00Wzh1v+avzYEkoNGuTy8H+ITa7b9vAhmzvNMelT2GHHrFls7Y8VQCEegSSWrJanZ/Mz4VbGXF8urhWZF4I6UHroDa2dXZI4H4aeSW53G9FhctB95AZfZ/tGtLyLjMqdAcxuqxS59PJwCfIa/YQi44tqrBOWJYdzZ1Priwbl6ONAcRecZ4cns7cbrmPMq/XHsObdcbaxkn1lah74nlOFopjhWi8WdngJS4VmCpsRyvTn2+5d5X1ZzmO075Vt/H55/cQEqKyZ49EbKx727Uj9iVXTJ+vjGxaWZ+LdZysvqY28QOoGtzcqQ9ljVOPw5/wV549Oudq77WE6YOc5vh682G6H3wfEPvXaL+29Iro7tSn5T+OI+FQDxSLDUSSzESGJvLepBd56NLvgNDvhkb3Yn6L991W8n753AJkNC5rv/UcQ332Ut//itOz8WvuII5eaea2fWxhBmNqbLe1VVVYmt2QovC7qdlhQKXvXcl70dTrEncGHXD6jaqCCS07gj4kILqBW1tuqb6Ba7BHV5YrUWmeC2VzSkrKjalSAaMzRPCTVtIwrvpwPnastB0aysSrP/Lu2fmW+qfwfdVRBOhiKjxOql7Pcxe/waAa0SDTJqghk6Lus+nze9RzPJ9kD9AeH9GJYp0vUy/Zsx80869DMF5gNJInm9iZf8L2tyGBwoeS4FW+D+Xv2Ooqq6dOOraHDWmHMalmJCQu91pJVC62e7dZOknnU28DYj99PqID90T3JyH5AHd4L8ZHNjj7CGUPkVTCARWVl69Vd/7h0nFWp5zCZPFjHujyM439azmtN49d+ZZvr2yw2Ris0EoaxsQN5svGE5zm0+LCbQw+IK5bRuKVkD60DGpKM/OPxGouW2QnCaJ6i0p/Wm/IOQUnP8e6w5d33Y73LsbTk7F7l5NYkIaCQogugOTeq9GlZ9n69MjFz/ju8ipMlmRyv9d6ClR/qhn+oJnegQnvGWHpk49IrpC0ClRxTw5e1VEU3J2WmjWAKtY9fRjE3S0SoZgLIWk1ZO4FxNqDxhup23KI6Cp0NdlBWS1hM0hKg1Z5QSQZRXYSCQlf2dNyIMhXi1Es4xOk8WZ33UfIjq5ZKTtrRee4Vf8ypHfgiScfJy/fk44dNUyfLirsKoqwJVmT11jtjbt2QeyCR4j6xE2mIjeYxjieYRrBwcK2ERpavj5/MKFsn1zJNbCF31li9KfArxZ0Xwc+sc73wGITcsS+IthX42UumLVlPkc5Vb0oOtYBcN7vWnpf4PZANxEWOHMA/Ovl8Napr8k25bltG6T14eO4QYwKrMfypBDue/kesnN8iI/X8PHHcNttQi4ymy1JhCxjd+4cVNVf5o31b/Le6W/dHtsRTbyjWV/zQYJCGpW+H5XCibwW/5cjB+B6c0rK4nK547ks3/wAaw91IyAklEce8aFqVYmoKMGZ0GjEmJrN4pWVJcwCWtn9HLxWP6EjRynGK4ATKU2AigUHVtUHs732aJIjq1ZYJ7wmO6t3KIbCaM4mJtmuoeR1W+9dhE8UaVerlHndpY1TVL8oLuZdvO59ivSNJL7Ym14vzUDjYJMtD3vitCR8+y4X5Ir75MqUA6+Dj7ckjxz+pmz6L/m/ynq2rwfPpcLytcN1l8VfvhYOyvUYp/oxTfnw7A98f7FElo8SeDd2AK+EtmZ/aEilOP0KtRmx5yNAyGyjYm9nQsggQaIDVpoO8tRlEWcjAR/G9KFH/duvq+xh/Y31OWodPLDSXOTK2MVCFC23D/zx5gr+GjZsGAEBAXz99df4+flx8OBBwsLCGDRoEHFxcXz//ffXvaMAbdq0oUWLFnz5pb0CRv369Rk0aJCNHOiI8ePHs3TpUo4etadRfeyxx0hISGD79u22a8nNzWXFCjspvl+/fgQGBjJ//vwKnVdVVaKjo3n22Wd56SVRgtxgMBAeHs6HH37II488UqHry8nJISAg4Ibd7H8CDz8snH9NmsDeveW3374d2lvWyp07oXnzCjjLHGAwG5idMJtHltnHuG5IXab2nUrvGr2RymKX32zYtw9atLB/3rtXDIgVpkJIWi6yJxpzRQY/nQ94BAsnrzFHbCiqWTheVBPUewHC2rmc6pr75K5ft3Bd4Uh2njBhAh4eHte1/d/F8dTjdJ3TlZR8EeTrr/dHJ+tILxQR6YGegay6ZxVtqrS5of34J+A0tq3X4eEXBUFNhKLuGy8IHIZsQdxQjBgyjjNpqXBA/RP3olJwRzJIThYaY2CgK5MtKsr1u/+P2P0knPoSUKHGGGj1BUiWTcYawJe2y04QAei7F0o6RW6hbJSxfykKLF4Mn3wC58/DQw9Bp05Qrx5ERDgHehsMcPkyvPkmzJ0rjBwHDoh2lZENykViomBiFhWV39YRnp5w4oTIkPNP4AbswU2+asLBFEGOCPEKIfXFVCdZae3ZtfT6sRcAsiTzUa+PeK7dcze0Tzcjzmedp+ZnNTFbHChtq7SlR/Uetr/P2j+LK3lXkJCoHlidE0+dYNsWLd27C2Octze88go88YRYYq0oLITvv4cFSzLY3C4UFRWNpOHu+ncz/y7nrIYT1k5gyvYpmBRhEDo06i8a7h4GhgzQeEP7uVDldkG6kS0PUtpuWNPa+WL67hVBYktrQ0GihXToDOdKl6fwuDQfUIQToe6zUGeccDwAXFmPYW0fe/tH++ER0drlmCWRmysI7yCe7xEjRLW/0uC0B9f7Eg9zupB3m30ENcdanFIiKwyZBzGsbF/pPrmToVatgn793Lf388vj+ec/BuCXwF84muWmVIcDnLJTV1YuUBVY3xdS/hL3TNZB/Cio+7wgsJkL4PhUOGrXgUfQh59PlZLlyNonWUfOyzl46jyd//A/8mzfjJg5Ex615Bd4+WV47z2xjpRMhFJWQpVKYfsoOP+j27UAgKDm0M+iyJ/4AvY+Vf4xZU8YeAJ8LPvjPzGfKnCOGbtn8PiKx8s9VIuoFuwes5v0dIlmzYSIbDbDgw+KtbxWLef2q1eLdezHH6/DdVwnXItO+E/rkQApeSlM2zmNSVvsa9fn/T7noWYP4a3zLr1Ppcia13TdZgNe73mhWAgG7aq0Y9vDrpXDgz8MJrMos/S1vAJ9OnZsAr/+6oGiQJUq8MIL8Mgj2Kpd5uXB55+L4PC1a0t04Fqeo/JsSmYDrOsK6bvEGhDRAxq9CeGd7G0y9sEqh2M46kY3ok/X0H7hsYUM+WVI6cew4OchPzOs4bBKnUNVhRN7zRoRpLdhA0RHl072M5mEnrJ+PfToYXd633efWD9q1rS33bRJrPGpqaIL/5+xY4fQ6UwmmD1bBPSUR4isLAxmAxFTIsgqykJGpmPVjmx80J74TVVVqnxahaTcJCQkqmWMIfW7mZhM8PPPMGiQuB9Go73CtCTZnecajXg9t/o5Pt3xabn9aRjWkAOPHUCWyhBgS0G3Od3YcH5Due3WP7CertW6Vvr4Q38dyqLjizApJjy1nqS/lI63zhuA3OJcQj8KxWA2oJW1DK0/lHlDBAEuORnq1xfcuLK8QwFj7iKvymLMFtkh9cVUQr1Dndr0mNODv86LNNeyJLOpTz49u3pSXCwCIL/+Gu66S7Q1W0QQnU4EwP7wA6wIHMCq06swq2a0spbcCbl4au3y6qrTq+g3TwjpEhJf9P+Cx1s57PH/xvpU8jcnv4Q9Twg9pc9uCGhgD4YBQfApToPsY07BWWi8wFwMWi9oOR2q3WNhM1kGKvMgrC4RENh3j9DxZJ3z8d0QiADosgxibiv92hywcSP07CnuU7VqsHAhNG3qLIta3+/bd43i3YaBkLQCUKHpJKg/3pWUVtJWB9DxF4i9U+iFjnAT9HYjbXtDh8Jvv0HXrvDXXzfkFOJ61nYBVGg7G+IfcE5GVtp8upE2za33wIWfwa+GOI/Gu2JzvMsy2DoCTPlgIfcS2RNC24t7mbYdki2BJteiV2QeEMFm5mLx/DV5F2o+CjpfS3CkLNpUVL5xsxbk5wt/5/nz4tnQaoUfdNQoCAqClBT44gv49VcIH/EqGXU/wmgJkNr44EY6V+3sdLxv9n7D2GVjbZ9nDZzF6+tfJznPTVrgEvh24Dc8lPWLsBUENBDrjSS7kjrLmx9lXbe5GFY1F5UEI7pBt1VioyiDOApQ0HkfTbs34+xZMU56PTz2GIwZI5IipaUJ/fe77wy8+KJz8NeGBzbQpVoXp2tdeWol/X/q7yqPF5yEVS1FYF9ZsM4nrxhY1x3StlmC40qBf33ottI+/yqLzXeLJHNlnSOwkXgmfOLg2Cew//myj+lXD7qvEu2L0mBpTTBml97ev564X47XcI36udFsRCtrK+ZjL2M+FRoL8Z3ka9O/Olft7CTT2bo+yZ9cgwi0qhVci5NPnWTPHmjXTsicZaFZM7t8ffUq1K5ddpXWFi1A92g7dl7eiYqKl9aLvFfynOS8lLwUIj+OBEAra/HSetn6p5N1FL9W7DI2X+7+kidXPIlqIUl/e/u3PNTsIfHHi4th82BKRVAz6OegJBx5Hw68hj3kzA3czdnKyjfXGaqq0mxmMw6mHERFJc4/joRHE2xjdSjlEJ1n29fED3t+yEsdXvrH+mdDGeM0apTgubRsKQjl1+X4Jc5R2T79Exi7dCzfJ3xv80UcfPQgjSIaObWZf2g+IxeOBITM/0nvT3i67dO2v1+9CpGR7nWL+atPM2K73cA2qM4gFg9f7NLunY3v8Pamt5EUyb0tJj8R/qiOTaYAkDQYwm9j0pbmru0B9j4HJz9zsIVKIvnAbUdcs1RW9t4pRlhSEwou4vK8ShpoPhXqPOn+t/9hqKpKnS/qcDrjNCoqNYNrcuqpU05tWnzdgn3JYt2L9osm8ZlENLLG3eFKxZRtU3jxzxfLbRfpG8n5p8+jkTVETYkirTCtzPY6WUfWy1k2vdqGm8AutuvyLtrMEnqShMT73d/nyTb2OTZu5Th+OPADZtWMTtaR+GwikZ4BQhbOPSmeA32o8DPVfgJ0fiL469jHluQbFlRSXi7zGkr8ZvHxxQxeYN8Tvx7wNWNajHFq3mhGIw5fFYEsoV6h+On9OJclAlTdzadnVj3D9N3TbWvY2afOUP3wi0I2QxGJIVpMFXumdqd1HAABAABJREFUNdgtI8FV56zEdf9x/A/uWHCH7fPguoOpFyoSkBjMBqbumIpJNSEhMaLRCObdOc9Z/vOpCo3fEUmLHXX7K+vhr+4OnZLFNXgEQYvPoOowIf8rloQgWQeddZ3Q9tB7Ky4oxWawufYHdF7+smv7Elg0bBF31L3D9Q/XcY6bTNCli9h/W7aEzZvFMl2WzdFoBF1axXlQz34cw9SfwqlVS+LkyfITFl8zFKNIsJZ3FgqvCC6nbNmbDOlgKgAkQSJHhWr3Q0RH++9LeY4MDRu6+kPyL4i9qBQ9xIkDYPnNpZxLTN81nQ+2fgDAO93eYWyLsYT7iIyUiiJsvzt3Cll70yahB5fmo7TaWgGeXvk0n+/63CYTVw2oysWcizZ9oElEE7Y9tA1vD2/3B3N3Df9P/F+VhaKIeIf0dDH/TSb7WGq14hUSIjhTFZmnf3ec5M4yEzdNtCWzqeJfhZS8FJt9Iz4ont2jdxPsHex6oPLWgsREeyAFwLFjwqngiLlzBYnMitDQCvGyrhvH9nr7tq+Fk1aSj3aLv3EL/xIUVWHJiSU8seIJknJFKax2VdrxYc8P6VS1Uzm/LhsPLHqAHw7+UG67mkE1OfbkMbSO9ki4/n6d64Ey+nSj44GuiUr76aef0q1bN+rXr09RUREjR47k1KlThIaG2gKmbgSee+457rvvPlq2bEm7du34+uuvSUxM5FELW2rChAlcvnyZH34QE+TRRx/liy++4LnnnmPMmDFs376db7/91qmPTz/9NJ07d+bDDz9k0KBB/PHHH6xdu5YtW7ZU+LySJPHMM8/w/vvvU6tWLWrVqsX777+Pt7c3I0eOvGHjcTPCx0cIyDk5QjCR5bKJnY4G2Ojostu6g4fGg7EtxvJg0wdZeHQhYT5hdK/e/f9X0FdFofWCuLvE60bBncBVEo7fVVDYuoX/DuqG1eXisxd5Yc0LfLbrM3KKc2x/G9loJLMGzsJL5/Uv9vAGocdaSxrrTGEcMReDKVMYiDwjhLLuVROoeHWtfxT/lWCuyiD/Apz+ClCFAbPlF+7blRQUb+G6QpbhzjvFy2gUmX9OnYLly6G4WLysxAm9Xuizy5YJWWLsWOEsut5Ewv9lDKg1gKOpRzEpJtIL07mUc4nYAHvGqd2Xd6ORNJhVM4qqMMCzsTM7tTy5AP4TskG1wGp0rtqZ9efXo6Ky/dJ29iTtAUBFtTkQVFSeavMUkqpl5Egxb729BYm7ZUvXoEUvLzGvBw0KZvCKluxO2o1ZNbPtoivpfMflHbbzhHqH0iDzLyhOF06AHusEKQCcnQKlOccu/Az559z/rSQSfwFZgYCG0HMj6Pyd10mPgIodpwR8fATxPTlZEKnvuUcYNSsk+xtzQSNDl6UQ2cNO9tNYjHHXQMJ1B1UVxHxZthUQcYKVqAqwcuRKGs5qaCN+BHkG4evhy8Wci6JLSMwbPI+ji8oOECsVJ7+EK3+K9341ofta8I4DVHG9Ol+ocodT8Nf8vu9j0Piw8PhCQATk1wutx/ZLIulJlG8Ue8bscQ38uoV/DQUF8Prr4v0994A1n4275+K6BH7lX4BzP+BEkCgJc5GQdSUtJJRwnod3hujbRAKEK2vhsqUailIkyIXXSpK7QXis1WN8uuNTTmWcKrWNRtKwcNhCJEli/Hh74NeHH8JLL7lfC3r0gG7dbmDH/8OI8I3g/R7v83LHlzmVforGEY3Raa7H5K44PDQeVA+szpnMMwA24oAjCo2FZBbZM55eKxYuFHOoRQtBDvf2dpYNfH3hxRftAaA3HCc/E9U4UETl0Lbf26qF/n/CnfXu5J2u7/D6BrGAysj0q9WPladX2pzIb3Z5033gVzlYuhRWWpJAz5olVOiydBGtVgT33323cMDqdCLxRb9+rutH+/YiePTriiWivanx88/i/9q14YEHbsw5PDQejGo6is92foZZNbM1cSvnMs/h6+ELwMn0kzank4rKc/c0YthrYnynToV33xVVp5s0EVV5PD3FvSwsFDbrrCyxzr/b7V1m7JlBkalsJ+ys22ddU+AXwPIRy4n6OIocg7CfaSQNeq2eAmOBrc2DTR68psAvgJc7vsyvR38FoMhUhM/7Pra1S3UgIJoUEy93tBN6xo0TCRrKSwvond2CvCqLbZ9PpZ9yCf46nn7c9r52SG1ee9kTo1EEfm3ZIvz21mfJ8Zny9YXHHwePfXew/NRyWz/3Ju2lQ1wHW7utiVvRylpMigkVlYG1B5Y/MP8kzMWwz0Lgqj8eAhs66yhlBWaZi4Vs1X2dqNxj1b2sOk/JeSdpRbvKwMMNKaMUvPyyWL+qVhWBnkFB4ntHWdT6vlEj19+Xi7RdkLRMvG8xDWpbEg2UtM2V/BzWUWQ3L4nSxraw/CCaa8Vzzwmddts2mDJFfHasdugIo1HsFZV2Ve0aC0gQM1AEfoFz4Fdp8+kGXjcXFwIK1HxEBC2WDPwqrU+HJoqM9CgimVqLz0QwomIEVMg6bA/+uha9YtdYS1IcD+i+BkI72PsmXx85c/x4Yc9UFGHr+eUXERwJ4t7WqCGIcRMmwIOf1iHFoSrdxeyLLse7mHMRnayzEagahjfk6wFfM/Dnste2WP9YHqreGlZayLEtPnMf+PV358eZWSJwTKOHdj9aCi6Vf46X3wjkzBkxTm3bClk4IsKu34aHiz36uedEYIUj3AW+uQ2GU1XYOdqV2Kj1FfOyONX+nXU+Ja+B1E2ux5JkZ1k456i4LscAxIriylq4+Fv57bIOiXP0+MuZYF0aco/Z+3TobSglQ78NOceu/RpK4HrpaV46L2L9Y7mQLcrgns0869ImpzjHZl+TJZnGEY1RFBFk6Sin3HMPfPCB8BdkZ8O0aXY7ihXPPSeSbJQFRYEe8T3Yk7wHk2Ki0FTI2cyz1Ay2Z244kGKv4mNSTET7RXMiXVSEMSpGCk2FLkEBGYUZaGSNzZ4b5Wvxx6kqHHoT5/phJWC1xfjEieSuh98pva0Vf2fO3iBIksQrnV5h2G9CF0vMSSR4sns5RCfreLTlP6UMVxxPPil0woQEMb/Gjy99n68ID+b/C6oHVnf6nJyX7BL8lZyXjCzJKKqCoipUD3L+zcKF7o+t1cLurb5Oxfvyjflu2xaaCsu2wyQtx+XZUM1iHcYNeU9V4dycEkmwVLFe5p4C/9quv6kMzv0oEu65g2qGC/P+J4O/JElibIuxvPSnCO48nXGabRe3EesvfJHpBem2wC8ZmdHNRlc68AvgmbbP8N6m98gqziqz3bS+09Br9QDsfWQv9b6oR4FJ6ONRvlHoNDpbpQKtrGXbw9tcA79uErSOaU3TyKYkXElARWXCXxOY8NcEt23vbnA3kb6RsOdpEdSPIhJBdVkiZGerfCd7iO//IfSo3sOm32tlLTsv73QK/iowFnA0VfjVtLKWAXUGEOMXwwdbPsCsmjmdcZqUvBQifCNsv/nz7J+2/bdZZDOqG87BJcuiFP+gsw3UGoDzN/kht9e5nRCvEFuC7MXHF7NMFrquoiq2BDoqKhO7TIS887Df4m/xqwW9toiArpI6i4sPVhXtem8H3xr2fpdmsMw+LALbghqLz+XYsjpV7cz8IfO5f9H9Nv3k9tq3s+TkEkDIZtP7T7cHfpXHJ/wbnIFdu4SeDfDll+UHfoFlb64ED+qFybD7AmzdCiNHCnkyLMyeLMoRsvw3khPLOgioL143GhWRG0ugin8VJvWcxPs9REXPkvzaefPEvdBqRTyOTlf2WDjep2n9pnFfk/voP68/qQWpNj0A4Mv+X/JYq8cq1df/MmRZBHeFhPzbPREY32E8dzW8i77z+pKYncilnEu2v73b7V1e6fTKtXGxKxoEVTIY7J9OzH29ERcn+u+4ZkLZSfqLi0V762/+R7hZt3DzQZZk7qh7B4PqDGLHpR1467xpEtnkuhx7Uo9JzD001+bPLQ2Te012Dfy6BRdc0whFR0eTkJDA/Pnz2bdvH4qi8PDDD3PPPffg5XXjSP/Dhg0jPT2dt99+m+TkZBo2bMiKFSuoWrUqAMnJySQm2hXs6tWrs2LFCp599lmmT59OdHQ0n332GUOG2DPEtm/fnp9//pnXXnuN119/nRo1arBgwQLatGlT4fMCvPTSSxQWFvL444+TmZlJmzZtWLNmDX5+fjdsPG5GvPWWqOa1bx8MHiyydwYFuc9UbjRChw7CEX/4sHD2LlzoPtO5I6yZdR3hofFgeKPh1/+CbiRuoGJ0zf2prMD1/13Yugmh1WoZPXq07f31bn89oNPomNZvGk0jm/LQEpG5bkqvKTzX7rn/VOCl27H1CBIvd+0VhdGjo53b38K/h2NTxP86f2jygevfHbOg3sI/Ap1OEARrl+NPeeMN8b+i3KBsS+Up2uBe2f4PKM59avbh/S3v2z7vurzLKfjLmvEUoLkhlFrtB/7vGWIsmHHbDOpOr2v7rKiKcG46MHm9dd6Maz2ONWtE1ToQhNNWrUo3SGu1gvAyoPYA9iXvw6yaScxJJL0gnRDvENu5dl/eLdrLWobU7IN04jNsZO3glq4PR36i+/VMVSyG39IJBlrJxOjYrwEJrWQGfYggTZUM/HJpD1rNAPcXWgKyLMiDffsKMnVWliAWOiZAccywptVqGTzgLkIO9kdLEdR9yTnwq8R1X0ufSu7zBw/CkSOlty8q8mT//kFMnAjRQdEcfeIozWY2I60gTVSHcSDGLBy2kNtr3077kPa241cYqioy/ALoAgQR1CvaMjgO993Nvflt6G88vuJxvtrzFVlFWbbAr+qB1dkxeocta9st3Bz47juxFel0glBS4YDIa8Wxjy2VJMpoYyUPVRthIWQinrtGb0KD/2PvPMPbqNI2fI8k915jJ07iON3pPSGVkgYhJPQAoffe68KylKUsLHUbZSkfZekdAgkQ0kgIKaT34hSnOe5d0nw/jtVsSZZkub/3denyaObMzJFHOjPnnPd5nwdU4IKuqwBcm/irBbPs8mUMfWWoXZh5y6hb+OfKf1JtrcaAgS/O/4IucV0oKoL33lNjERddpAQB4P56mEzuRWHNSSB9wuboR9qIDYtlWMe6getN1Rce2GEguwt2Y9WtHCk9QrWl2qUNtwV8ACoB58Aqrh9xvV91uuIKsFhMpKXBvHl1hV+O8koc0ejoOmz7F2CFpJEw6nU1+R8kAXXABDgu9qeJfyI1OpVrvr4GK1YW7llonyj412n/CjiI8Msv1TXp1893kecXX6jsnAAvvghTpqjl2u2H7fpffTWtHtvzWmO3hZcOutTuymXRLWS9mOW+PmhcMOACEiPggQfUS9dV9+7QIdWdqahQbXxSkuquJCfXJG4IjeTTcz9lxvsz7N+hG0bcwFt/vEVJlYocvnfsvQ1yt48MjWTrTVsZ9O9BHCk9gkW3MK7zOH7Y9QMAVw+7mv/M+E/Axx+aPpSE8AS7aBVcRV82kiOT7QGcmzYp5yIbBoMSol51leoKf/21Cq4+cAAiC4fYg5YAth/fzpjOY+zvK8wV5BarAH2jZqSXZRZfLlTbnnhCCb/qaz5P73U6Gho6OgbNwNJ9S13EX4tyFtkDuQZ2GOjSh20RVB51iCCSRtVtWyuPuRdiAGCFAQ+5Cr9suOvj6WbI+Rg6z3btG0V1UcHflceUwKOqANBVcFjKGHzh119Vnw2UU2FCgvc5moCSE2x4VAnYorpArxvd92vdjdWF+Hmz9EPw5i+jR8P69fDcc6rdf/551faPG6eSG0ZHq99UUZFqh3JylMO9z+hWKNoGWKHjNFe3b/D+faoqCPyD1YcxQp236rh/zw/HVSIdIjrBlBWOYMZgCLMK1itHU4Chz0LK2LpjBg3kyBEVeKjr0LmzEnLHxbl+dW3jP/37w6O39GFmTTfJZDC5PlfWkFOY4xLg0Du5N6MyRnHzyJt58bcXAUiJTGF239m8skqNc8SGxSq3JMthx4HCkv0LWvX1d1GyS/1OIzMgIq3udjffweMlCfzzra5YrUoY99136hnX+XlI09SrY0cTPSYN4O6FN2HGjEEz2O8jzhwsPmgPDH6FV3h1xquYjv0CeSschcJSYOS/IeMMde1zPoYlTkJRq1kJEJ3HxLIug/5/UmLEkj1KvGsLDg40sckfD2F3ZagPawVsfaGugC22j3J1LNoKBX+4li9YD7v+S53OvCG0po9ucS3fwpKzDOwwkJzCHHR0cotzsVgtLkH+ewscAaEGzUC/lH58+CGsW6fWRUUp5+3Zsx1jh0lJ8PDDKuHcn/6kyu3Yofr1zoIxg0ElW66uhj+c/q2TMifx+OLH7e/XHlrrIv5ae2itPUEaQJ/kPuw4vsP+Pq8sj8g4V2FAXlmei2glLbrm93N0qXLl8IazcG/z3xzjMfXRAq/3mX3PdBG4emJUxihiw4Kf9bqhDBum7vPPPAP/+Ie6B0ydChMmqMRmMTHqO1hSou7ze/eqMe7WTreEbvbnbcBtu5xbnItRM9rvYbUFY//7X82wY62mymyGZb9EgVMfu7TKg/irulztg2r7/3Xqv1zHYg79VCPedY3QN1HOleecAHHZruVLd6tnlzpo6nfZUPHX9n/iXdhZ1bDjt2LmDpzr4so19r9j3ZazYuXSwZcGdA6TwcS8i+Yx/o3x9jbnssGX8c32bzhSegSAOf3ncG6/c+37dInrwrrr1jHslWEUVhaSW5JLhEnFN4YaQ1ly2RKGdxweUH0CIoBxsQv7X8jaQ2vrPfQ1Q69R7rs7XgGsENtbCb+MYXWfmZswsDYmLIYTOp/Akr1LMFvNLMlZ4rJ9de5qeztjtpo5tcep9Erq5XLffmjhQ4zoqByyS6tK7WIxDY05/efA1hfVZ4zMgFGvqZ1qJ2hpYHyIpmk8cuIj3PDtDYAah9HR0dBcxlAGpw2mZ1JPWPfnmgfiEJj0nXo29+n/rsPIV12FX7bP4DbOxQDzT4CeN0DnWWqMwmByHTMoOwCFm1Syv5QxnJ8yhg5RHZjyzhTMVrM9OQ/Ap+d+yhl9zlBvfIknbEDMQJkjRxKJiY2THLhTJ+V4/vnnalysf3/Vjx87Vv2NjFTnLS1V473Hj8Prrwe/HoFSZz6kZBfsfANv/RD7/LkWiqnyEgjNtG/zFNu3YYMa8+nUSV1yfxnecThrrlnDhDcn2JM/LJi7gJOzAhOatrb5r+YiGP+nvil9WX31as743xks3adcBD8+52POyj7L22GalRYdY9uli+8xU+1VJCe0aDRNc5kLCgYdYzvy1MlPcdcC1VcwaAZO73U6C/cspLBSuQid0fsMZvf14p4u2Am4FYuIiODyyy/n8ssvD2Z96uX666/n+uuvd7vtzTffrLNu4sSJrHZ2LHDD2Wefzdlne3dT8nZeUF/2hx9+mIcfftjrcdo6CQnw889q8usf/1APyJMnw+mnq0GxhATVp8nPVxPwmzerDMizZqkMu6NGqcyjZ5yhJptrs3+/clNorMyyTUYjd4yE1ovBYKBTp06NVj6YXDbkMk7qdpLbDF9tgdZ0LQQ37P4/NQHQ/QrlnOhMc2XJFXzihhuUE8q//w3XXKOeH4LieOKMPx3tNsSYjDFEmCIoN5dj1Iy8s+4dl4G9n/f8jFW3YtSMnJx1MhpfNGNtm5feyb05u+/ZfLxZRUWmRKUwvcd03v7jbftc3rOTn8VgMPDKK2owOD0d5sypX7wREgLTekzjzwsdEWBPLnmSgR1UJraDJQft2S/NVjMXpyRBTo3TZvY9qAo4Dch6a9Nyv4fibV7rY9B0OoUfdKzoe7cKoPEQfOhS3uC7QrNTJ5U19dtv4f33Vf+guloFz8XFqWCOigo1eb5unYE7pn/NtaP3q0mZ3je7F37VfG6DhqNOlYd8qk/t+/Y776jAVLPZfXmr1UROzmAGD1bvM2Iz+GrOV4z971i7gABU9itbFryAngvyVkBFzb1oyNNK+OXj5Jumabw8/WWOlR6zf3eTI5L56ZKfRPjVAtm2TX3nevRQgYSNSnUJ7Hi1TnCEW6wVsOcdR9kT3lVOCy1BKOInyVHJfHPBNwx7ZRjV1mr+8/t/7MEAT09+mtN6nQbABx+ohGoA999fvxCvpWV1DqQf0hL7Lk3V/8pOyebrbV/bs1UfKD5AZnymfbtzNsoqvYo+3fr4fB6DwUBVVSe+/169v/NONbblbQ6pSeYejy6F0pos+33vdF8mCIEPftHAcbGrh13NvsJ9PLb4Mftz071j721Q9vjychWo5o8g74031HNgZqbqu9SHs9i9tTJ3rhrz3bFD9dmuuqpxAjIGpg0k3BRerytXp5hOJEa4BrSr4HL1qo/pPafz7JRnue372wBYnLPYLvya3We2PQtuQ0iLTuPz8z5n/BvjsegWu/BrRMcRvDjtxQYf/4EJD3DnDx5+2zU8PPFh+/I//qGumcWi/r79Npxfk1PNYFDf5TPPhIkTIbxwiH2/EEMI2/NcHTV35e+yi810dPJ+OR+TST3bX3aZb21ch+gO9Ezqyba8bVh1Kw/+/CDPLHvGvv1omcPJZWrW1PoP2NSEJjocZIq3gnWq6/N7WDIYwt3314wR0PNa930vT328Xy+BisPQ42oloLFWA5oS10SkQcIg1Xcq3QdRvj9kvvqqul7p6XDeeY3wu7Za4OC3gBV6XqeeNX11SDv8MxRsVAGLzv8rd6K36CyfBW+B0qGDEkg+8QTs26faw927lXiuslK19eHhajzrlFP8bPs1g3KDs5Spz1Xb/cLb9ynavUg2KAx+HFZeD1ueU32D+AGOPrrzdQB1LSrzlFvYwW+UyOWEd5TwK0huXABs/7cSKRkjoPvV7scMGpj46/PPHUHsb7yhnhG8Jfs5oZcjMk5Dcyv+2l2w2x4QmhiRSHx4PADPT3ueLce28MOuHzhadpQvtjjG5D477zM1/1KVCKFJUJUPO/4Nw19yPbi7a+Hv7yI8Vf0+yw+rgGFjpOsX2M138MtVM7FYVZn//lfdAzz9n0JDDQztM5CDC9UYjkkzuXf+Ks61C4MPcpDBvQZj+P0KdZ11C0RlKgetyM5O38VM14McXQTlBxzvBz4G/R9wOD9EdVXvbeKvQChYD3m/Oq3QoPdNamwtNEH9Ztb9yXWf/V84+tuaEUb9F7Iudmzf/Dysuc3xft+nrmKHqK4w9HkV0GupVMff7LhvtjT6pfRj3o55VFursegWDhYfdBFy7ynYY182W81kp2Tz2M0OEclzz8HMmWq781fRYFABu08/rd7/5z9qnc21YdQoJQbLqmka161Tjr2gxsidXUfWHlrL2dmOOJE1h9bYl9Oi0+ie0B2DZrD/do+XH68jRj9ecdxF2GkXf219XrVVtQV/tbFWQNk+2PWG69hNTE/oe5f6fe9+R43XtGBMBhOXDLqE19a85rXca6d7396cpKQoR/gnn1T39+3b1d8FC1T3VdchLEzd50eObIJkTk2As5DLZPDQLpfkunzHneMCjhyBRYs8uwpXFLmKJcvN5e7L1fT9bG1/esd0DLZ/rq7D4R/djm0aDEY6heyATpNdNxxb7r5CmlG13128x4d5pewAHF/lvYy5zOHq187oEN2BDlEdOFx62Gu5uLC4BsWYjMoYxaunv8qlX1wKqISXtnmaER1H8Pbst+vs0z2xO5+f/zknvqUUibbv41uz3mJEpxEB18VvAhwXu33zZh4yPeTxdwSQGZ/JhMwJsPcDxzPbyFfVs3iQkyUEwoyeM1i8dzEAW/O28vDChwkzKne2xTmL7c+AGhqTu08mLizOPrcN8MqqV+xJEpzR0ZndeRgsqZlH7XldTWfMqVAQY0SuH3E9L/32EluPbUVHp39Kf7ondueTzZ8Aqj3931n/U33hHa+o9ivjDIjpXvdgnvoukRk1yV987DuPfhOMoXBwnkqCULJHJUQIiQQMyklWM0HCUOh7u323E7udyAdnf8BZH55lf955febrDuFXEzBokJorLipS41a2Z7xgYzTCWWepFyih1969qm9fUaHu66GhakyxWwsLgaszH7LjtXoTPrrM6VcfBzLrPU90tPo/FBY6xg79pVNsJ9Zft55PNn3C6IzRSgQZIG1l/quxCdb/KSkyiZ8u+YkPNnzAgNQBDE4f3LCKNXJibonrFITWx51j72Rz3mb+u+a/WHUroYZQu/Crf2p/Pjrno2auYesh4BCDbdu2sXDhQo4cOeKSAR/gIZtlg9AuiY5WQdsPPAC//64yJG3eDN98ox6cdR0iIqB7d+WMEB+vsissXaomBh59FC6/XA2uZWWpANmyMhUcV1GhhGKtXvzVEgnkgasNuKAIDaNrfNf6CwlCU6NbobpGKBHTqyagxGlUormy5Ao+cf/98NtvShQ+aZLKojy7JqlDVZVjklfTVGBFYaEaDGz11Jfhzd06P+/DIcYQMmIz2H58OxbdwudbP+fzrZ/XKWfRLXTIHgFbn26XDmk23pz1Jj/v+Zm88jwOlRwiMz7TPug9vcd0rh1xLRUVyiXCYoFLL/V9sndY+jDlJFYzYfrMr56DNAbGpgIGFeTmblLAW5uWO79ugEFcf5XRrXATHFnoWl4zKHcxX4MP/ZwMMRqV6Ov009X7sjIVKHfkiPp9h4RAbCz07AmJG1fCvhqHoQg3kbuePncA7bjFooJePQm/PDE6YzRvnPEGl3yuOifnZJ/D/ePv9/v8LuR8pK6ZwQSZF7m/Fl4C2IwGI++c+Q4LnllAQWUBP13yk4uoQWg52O5nngIjgsrBb+r+XjSDCiKqKlABxM7YMjR3Oh26ntcEFWw8BnQYwIvTX+S6b66jwqL+B1O6T+G2MY5guvffV39HjlQOJULbJjsl2yUL+d6CvS7tpHPwoa28P7zzjnoW0DS4+OImEnfVx97/qXtLaBxkzGq0+3xT88iJj/D9ju9ZmbuSAakDGizS6dNHtcnr1qnMrvHx3p/rDh9WAYBWqxJEmc31X+/WLvwC5Z7wyitK2HPbbSq51913q+y41U4J/nVdBUsEGiQAKsPfBxs/8FrmmuE+qO7q4eZRN/Pp5k9ZnLOYdYeVM0NSRBL/mfGfoDncj+k8hn+c+g+u/UYJFBPDE/nsvM8IM4U1+Ni3jbqNl1e8zJ7CPQBcOvhSzFazSvaBRveE7lw/QiW1Ky6GN990BEa/9JISfjl/10NClFvx0qVw9tkdSI1KtbuWbTvumlhiW57jvVW3cmx7FmYznHaaGv/3lcy4TPuxqixVLoIvZxoccNAYmCKVQ+qGx2D9X6DLeUo8YRO5uBNjrLlbOa6mnazcfmvjqa/T/y9wfAX8fhOs/zN0OBniB6lzGExQXaz6eXkrlCBgej0BqU7k5Kh2bPjwxhF0Yi7Gno06MgPlkuOEt36tpRJ+OR3GfQBJI8BapRxvQH32qC51HbKaAE1rpNxCPa9TgpEtz0GP6yA03nHvDoa4JxB6XKscybY+DwsmKTF5rxtV3UAJcGyBzboVjq2EvOVqLKLjqdBhUvDrtP9Ldfyu5yoHA2eCFNT50UeqfezeHU72IUl5UnQcyZHJHCs7RrW12iWpgI3d+bvty9nJjudMTdN4c9abZP8jm4LKAnuw9G2jb+OkbiepQqFx6nfw02TY9g913Xvfosa+nducqC7qRhw/oCaJhx8/6h5Xq+9exVHV1oz+r7qmtoBTN6LLD18/FaNRo2tX39xTuyd3sQf1WnWrR5GBzYUm1BhKml4KufNs/y0Y/5lqS5yfa2snK9nzvkMs1v0KJfRyLheMe/yedx3nABj8pBLq2I6dNrmu+Mv+vdRg9BuQeaHr9tRa7igHvnIcPywFTv65ph1Fffc7n9O04i8/XUqyDR1c+1+Fe12EU3sL99q/DwBp2gA2bFDbRo9WiQY8YTKpZ3iz2fX5ZsAA+OEHJUS01yNbJa+94gqICo1icIfB/J77O2armffWv0eludJedt72eVh0CxoaJ2WeRMeYji6il+PldZ2E8sry7OPGBs2gkjCZS2uun48DjkeXqn1sJI+Gk39R3ydDiBJ/tnDxF8AL017g0y2f2v9Pj5/0OL/s+YX5u+ajoXFuv3PpnRyAjUQTo2kqTsUmIGzLOItvNDQOldRNrnag+ID9Ox4fHk90aLR927ffeh/fDDEZCTeG28flbA5ftSk3l7v81pzPQeFGJX52h26GoyvUM5Qzx1Yolx29um75/LWeK+wLB77Eq+sXQPEWh6tfOxSAXTH0Cv662Ps4zQUDLmjweS4edDGfbP6Er7Z9xcajGwEIM4bxzpnvYPKQVG9S5iT+M+M/XPO1Gk/40/g/cX7/8xtcl6bAYDDw7JRnuf5b1cdPiUzh5VNf5sJPL7Q/O70x8w1VeM976jklohOkjq97sCAkSwiEkZ1GujiWP7boMfvYi8VqsW+LD4+3J0oYkjaEZfuXeT1uhCmCHloR9t+lu7nOIMeIfHzOxwz4l3JZ312w2+64rqHx8MSH1f3u6FKoqGlXe1ytxFi1Xbw89V0yL3J9Fq/vM5hLoPOF0HG6Y52uq3ZPt6p+tIdn4DP7nskD4x/g8cWPc+ngS7l8SC0jiPriCRsYM5CSAu++CzNmwLPPqt1uvFGNNZpMrtW2WtVL1xueQDgqSj0nZvs3BdD86LojGbaNqEwY8jflLn90Kay+XbnV+8mFF8Jf/6pMHf76VxX7G4jQPTIkkrmD5vq/o9DshBpDvV+7AJwrGTo0eBVsizSySE4QWhrPTnmWr7d9zZHSI/ak1kbNyNuz3ibE2LRj/K2ZgEIQXn31Va677jqSk5NJS0tzmQTVNE3EXwKgHv5GjlQvXxg3Tr1Aiby2bFEPk9XVKlggPV1lRW+UycemppE7Rg2qlzwUNCsWi4Xly1UmqtGjR2Os5wvvb3nBd+RatGa0GrFDNVgraTFZcgWfMBjgs89Uts6//EVlHM/KUpO9w4erW6TZDLt2wcqVSjyyzPt4b8unCW28R3Qcwfbj2+std1bfsyC+fT8XRIVG8dhJj3HdN2rS8KUVKqOyhsZTpzwFqMBgW2DBiBG+P6caDUYyYjPcZoF2JjIkkujweED37NjjrU3LX+MaYND3Lhj8BFATlb7hcSx//JnlBaMAGN1dwxiRVvc4TpMJFt3oKF+eT0PudpGRMHBg3fUWi4Wlu6KgZAyjO6XUew6XOll0n+rkfN/WtNEcOeJ9r5CQKkaN+oh334VzzjmH0FAVbHjxoItZvHcxW45t4c1ZbzomqQJ9Lsj5SF2z9NNUIKkzPgawhZnCyL/Xw2S40GLo31/dz7ZvVyLIbt0asa+7/3PXgLTo7jD2PUgaqSYbf78FdvzTUV4zqsnAwU+qzJSG1v1ce82wa/h88+d8v0vZMb0z+x0MThOmBw+qubJhw1pnxuZA2puW2Hex16mggNEdOmC0XQgPE0cWq5Xlu3ZBVBSjp03z+TPUFnPtKdjDRCba3+8t2EuIIYRqazVGjBTtKGLp7qU+9wkPHFjOmDHq3pKS0vz/VwDKD6rff8JQ94HxQRRU+0wQxsU0TWPpFUvJK88jMSKxwSKdW2+Fl1+Go0fh5puVkM9bm7Bpk9oOykWgRQj9mohLL1Vi/dtuU32255+H8ePV83BGhvqfHTum+muFhTBvXn1HdM8TJz/Bhxs/tAf+DEsfRoW5wh7QFWoM5e4T7m7w5zFoBv5v9v+R+UKmfd0bZ7xBSlRKg4/tzNXDrubFFS+y6dgmPj//czrFBifLqMFg4Nmpz3LWhypt8a78XfYAZh2dv0/9u/33sXCh6kODEjxfc43777jJBElJKgHb5xEj+Wb7N1h1K5uObnIptz1vO0bNaA8ErS5Tz6+Jif4J/64fcb3dEc3j59QMnN8vwIC8QIIS/OkL938QDn4Hx1fD9yNh+MsqO7euK1FSRLpy5dJMkDhUib9AuYb5Q0x3GPiQevY/tkIFrR5fCYd+UOcxRqhxrcyL1HOeH5ZTtkQYjfZIYHKKwK8qQAnBnE7mrV/bdQ7kfAg/jIG0U5SYInWC+r+iQ9lBOLIISnbCyH830gdoQgY+Cvs/U/2/hdNg3IfqutoEbnZxj0WJ/7A2vvBN02DYc8ohY/0jsO5BWPcQxPZV3+mQGNWvKNmlxIcRnRwJJjJmuxfnNdR11BYAHtNTndsY6tgWhKDOggIlFLFa1dikr21adko2i/YuAlR77IxVt9oD6k0GE/1S+7lsT49J5/UzXre3532T+9YVt6edDOM/ht+ugdV3wM7Xodsl0GEixA1Q/wdLhWofjvyi2oqJX+AzoQkw5m1YeCrsfluNrQ99HsJT6joNJg6lqKCa+YtCsFhU9vz6/k8Wi4WVy1cyJXQKC6oWYNEt7C/aX6fcvsJ96OgYMTI1dCq/LvyG0boRo2aBzAsgcXD9nyV/LWBV7mWDnqwbONtQdCvsetvRz+5+JWTXei5xG3RuUPXKuhS6uQmoqy3WswdsajDp2xrRm9PvyUe3+KAQgEtJdtdQuMzxfm/BXsZ1Gefy3mQwUW2txqAZOLjB4QrwyCP1J1jQNJWQwXabDw2F775TY47O30WTSQUVP/useh8T5rD73V2wmxdWvGB/bxOr6ejEhseSFp1mf9YByCvPq1MPm9MMqGB1o8EIB+YrwbIzUd2gz23qe7Pxr64Bubnfu7rbTfxGfWdt17iVuLFHhkbyyKRHuOm7m9DRWX94PUv3LVW/aYORv035W3NXUahFSmSK3XXZolvcinIPFDmcFGsnGluxQv3GPCVWM5shIiTCLv4qqy5zW67cXG5v+0cxil3rdtFrUi81FnP4JzyJrSy6keVbKkCvNXZzdEld4ZeNsn3u1/tKzice6+OCtUI9l7RD8dcD4x7gmWXPUGVR7eDoTqMxGUws2bcEUMGdj534WIPPo2kar818jT4v9yG/Qj0f/m3y3+iV1MvrflcPu5odx3dQUF7AX078S4Pr4TcNGBe7pvM1PL/iebblbeNo2VHWH1mP2WpGQ2NGrxlM6jZJ9QVzv1P3lK7n1k2UG0QHLH8Z32W8S3JMi25x+1Ma0dHhxHbzqJvrFX9NypwE1YWOFf70t48BG3ZD/mr13scxg36p/bh08KW8sfYNCisLeX+DyjKXFJnEraNvVWUrHM8IJA73T5AW1QV7EpVA0TQlhPWBx056jMdO8vK7bOR4wtNOgw8+gOuuU2Oz//mPerScMEHNp4WGQnm5MiFYtAhWrVImBO0FlzmdPtEYy536URGdYNoq1Tc3hKgELeEpWH46zWn+3OrT/HlWFvztb3DTTcq8ITFRXROLpa4Qr7q64QK8+mgr81+NTZP9nwJ0rvQ3pslX2lRcp8RsC+2I+PB4Xp/5Oqe/f7p9/u/ecfcyJH1IM9esdRHQiOBjjz3G448/zj333BPs+ggCoO77gwc3dy0aGblpC26wWCwsWLAAgBEjRvj0YOpPecF35Fq0YjQNYnpA0RY48I3KgOpMc2XJFXzGaITrr4crr1SBFitWKIHXc8+pcQSTSY17jx4Np5zSOgO1XTh2rH7hlzsqKtS+fjxPXDv8Wt7b8J7XMlEhUeIUVMMVQ67g6aVPs7tgN8fKVZsxd+Bce/a2SkdSWCIi/EsaPLX7VF5d/arXMiM7jlRBATbx19FlKojPeXLATdZlQAXlrHCKruhwohJyOAcKdJyOZe1fWHBsCgAj+m/2QWhlcJS3+ia08heLxcKCPVlAFiOql7s/h1NwoEudIrv6LP6y3bdNJnXftlg8lw8JqSItbQc7dkBVVZVd/AXw6sy61zHg54LymgyAqRNdM9qDOFe2MS6+WAUyHTgAd92lhM+Ngm5VAUS2QCVDKEz8SgVJgmpPelzhKv7SLeo7GNdC0h36647pRiDy7lnvct+P9zGr96w6wfy2tjwsrImc2IJMIO1NS+y7uNTp8ccxVnsI0KmZOLKEhLDgAZW9f0SfPhi7u3HHdEPvpN72zPImg6mOI8Pewr324INO0Z1Y9LMK3vW1T5ievoD0dNiwYQQ0yl0yACzlgA7GcPfbPQXcN3ZijCCMi4UYQ0iLdiNcD4CYGPj3v1Xg8nvvqUftf/9bNSnOE9m25cNOpompqUGpQqti7Fjl2LxmDSxZAr/+qpxUi4tVWxoRoUT+p58euPtXt4RunJN9Dp9s/gQdnTn957Azfydbjm0B4M4xdxJqCq3nKL7RNb4rT53yFPcsuIfMuExO7316UI7rjKZpbLxhY9CPC8olLSshi135u+yiA4BeSb04rddp9verVzsCM++9V10bT31poxEuuABylg/l2x3fous6W49t5aUVL9nFZJ9v+dw+Odc5pjNxsepCFxX5d81P73W6i4jMqBkxaAbMVrP9+Nkp2RgC6fg3RVCCIQQmL1bOX5ufhcVnqX5c6jjVfzNFKzFGwR9KpGQLNrW51temvnY5Ih06z1KvINGxo7pmNreVoGMIUSLk/D9g15vQ81rX7fWN1Q15SolcjvyihEeWWo4Rxij3IorWiCkCTl4Iyy6Co4vg62wlukqbrBy0QmKV2KngDzi0AArWw6QminhLGQsnfQ9VhXD8d8j7TQm+qovVNY4fCN0vV9d5y7OqL5JxhnvhV0NdR52tlGuPxXj6DR0DdlX7FNS5fWMkFksfAGbO9H28Jzs5m1/3/Uq1tbqOqOlI6RG7qMSqW+mdVNf55sy+Z9IjoQc78nfwwdkfEG5y8/zW+UxInwo7XlWJPtY/BGvdtHHGSOV44C/pU2DKclhxhXKM2P+lass6TFJtm8GkgliPLObAjljM5tcBmDat/v+T7Zl/DGP4iZ+wYGF/YV3x18HigwAYMDCsfBgL1hQyokcYRsqg3/11A5jdUhMo2+1iCEsMvnDm+GqoqPnOGsJg0BM+7mhVdR/wZ98EaTYxUKcZkDS8QVVuDvocd3wpTAZTHaflPQV77Pf/rnFdWbIoBJNJPa9MmuSbs+6CBY7nm4svVvc0d9/FkBCHq8O0HtP4ec/P9m3O7mTOnNfvPBcnInDv/HWszDFmkR5dE6x/aH5NksIaRUzKeDhxXk2bqCnx7AJHIhKOLnaM3Qx5uiZ4t3VmmLh8yOU8tPAhjpcf55PNn9j/v5cMuoSM2Ixmrp1QG03T6BLXhW1527DqVvYV1hVG2cTLBs1Q5/61bJln4ZeNyJBIuzCnwuz+uby8Wjl/hRDCFKbw+5LfmTx+shqLObIIz+IvAwv29YV9CxxjN5ZKKFhX/4cPBHO5eiZtqCCjjRMZGskto27h77/+HYDRGaOJCYvh1/2/AnDl0CtJjPQzGYYHUqNSeW3ma3YB/Q0jb/Bpv6cnPx2U8wdMgONiBs3AA+Mf4JLPLwHgzTVvAkq0/MD4GqdTc2mNcB+VMKL2M7OnuaZjwOo1cLjmXhbsxCmoBDa9knrZx3Y84ew8dU72OVz2xWWUm1U/sFt8N2LDYvnj8B/2MveOvRcMTkIrS1ldh2B3/YRjwJ1A9YPAg+4r42XM4JETH+Hd9e9SZamyu689duJjRIXWJEBxFoK7S9rhLRFKbRF5feXbQJLjc8+FU0+F116Dr75Sc2hlbjTD8fEqYVF7wmX+JDoEo62foBlV0hib8AvUM2RIQq05fd/EXwA33KDib+66C265RQnxzjkHpk5Vpg22xF8LFqifwnPPNcIHrqGtzH81Nk32fwokrimAmCZfkbhOQWi9zOg1g0mZk1i4ZyEAD05w8xzW2En9AsGfOpWUNGpVAhoxys/P55xzzgl2XQRBEARBEIJD9t2w/DI1wZa/FuL61xVLtMNMa62N0FA1iDR1anPXpJFJTlYDxf4OlISHq339YHzX8ZgMJvsAtDtGdvLRtrUdEGIM4alTnuLcj8+1r3vkxEfsy3FxjrKHDvmX4erGkTfWK/66aOBFKqAnsiuU5cCmJ5Rooza12zSrGTY/7QgQCYmDE95zHxTljKcoHY/Bh5le6x8Uji2H6hIIiXZd7xwcWLQfdq5R65NH+X2KRYsczh2gAkaee07N52zaBOedp1zeGh1LlSMbaUgs3i+W0NoJC4Mnn1Tfs88/h6uvVo4zBkPd4KYGZc/L/8ORFR9gwF8gtnf9AWapE1VbUjvQqKEZ+v0lEHdMNwHbSZFJvHL6K253jY9Xfw8fbiNO4+2RvDzwUfwVERJBRmwG+4pUMNPeAlfx1878nfbgw34p/SDAcVlrS4oBCokDDFDl4WbmTkjeThNjzJ6tnALmzlWi3O++U9llp02DzEzVRu/bBz/8ANu2OfarL9CtLTNkiHrddFPjHP+KoVfw4aYPAfhq21cuv9FLB18a1HPddcJd3DLqFhd3yNaC0WDk/nH3c+VXV7qsf2D8Ay6fZ+VKJfhKTITzz6//+SIsTAVq2oKeq63V3Pr9rfbtzsHQYSFhDBoE69er344/zy8Gg4Gp3afy3Y7vAOif2p9Te57KCytesDsDXD/iet8OVpumCkowhiuX5V43wL7P4fDPSjCx+22nMhHKsSosVYl6Dv0I5rK6jr/N0C7PnQvvvw9btsD338PJJzeCo+GAh2HRTOUMdfA7JWbyNlbn/CwamaGEEqCcaUt3q4BGNOUqFpXZ6t1qXYjqDKcshH2fws5XYd8nsOfdmo21Ap87n9X09QuNUw5UaSe73350KWCA2B7KMao2wXAdDU0Ec4lK/lU7k707MeHuHXD53VB5Wd1j2XDqUxRzIvAToEwXfNWe9knuY79PlVaXUlhRSFy4Gjxydn+36lb6JPdxe4ztN2+v/0SmKOhzq3pZzSrAvfyQcuoyhEFkp5rx8AB/F0nDYfoaODhPuQvmzldub86Ed6DYcJf9bUqKf8m5TJqJar2aw6WHXdbrus7RMuWGFKKFOL7uejUkj/AjSUnNb6WXbwHgfuMsKsi8AMKSfN83fRpEdfWtrE0M1Pdu9330piQAl5Ko5GQ6fXwCB4qVa1Dt5Bs78ndg1a1oaAzsMJD5/1DP1hMm+P4c8ccfjufxO+7wbnxpcxK7dNCl3LPAe5Jjg2ZgQpcJbMlzBKebDCa34i+bqAVwuLsemu8QfhnDYcxb6vdp+10aaok7bUH6kV1U294Kn0ltRIREcPcJd3Pvj/fahV8aGveMbYbE0o0dLOZvwqJAztEE9Ezsyfa87ejo9t+rjQpzBcVVxYBK0tAtvpt9W2WlGj+vD7sIAqi0VLot48kRDFDjm/6IrfLXOH5/7qhXQOyF46u8H1uwc9ngy/jbMuX29+XWL4kJi7E/J10x5IqgnuvMvmeSd1ceoabQVtmn95c5/edw/4/3c6D4APuLlZB+YteJjMqomR+zOP2eTJF17ymNIILyh1m9Z/HksSc9btfQOCfbEZNqMBi4bfRtPLX0KTRNY3qP6UzpPoVZH8wCYHDaYCZkToB8p+ez/V+qZzRnwZW7vvaG3TWf2Q+cxgwyYjPsdQPISsjiiqFO3+8Qp4nk8sM1c39OuOu7LJsL1fkq2UY7THIcHQ233qpeFgts3KjmbiorVbKpzp2hZ0//ErK2OQ587egnZF0OyaPr/s4b0G/QNOW+Nns2PPUUfP01PPSQejnnYQEYN87zcYQ2SCBxTQHENAmC0D54/8z3eWTRI5zT7xzCTLVE+y3MaTDgOjUiAd3pzznnHH744Qeuvfba+gsLgiAIgiA0NV0vgLX3Q8UhWHIunLJITcC6y6jkU6ZQQWhE6ps4B7eT54FOEs7sNZPPt36OhsaErhO4YMAF3PjtjfZJt1tH3+r3MdsyZ2efbV8+r995dI13BGfEx0NGBuzfDx9+qALmfGVgh4F0je3K3iIV9HD7mNtJjUzl3h/vBSDCFMHcgXNVQEC/e2Hl9crNcOd/VSZtT1irlYjo4DyVQRgg80IIT60/aKDsgPv1QRRa+Y25FHa9Dj1vqDtQbQsOjO4PrAn4FCtXurr9/Pe/cOGFKmhp5Ei1feDAgA/vOwYT9uAkaxV1Mpm28Yx+7ZELLoCDB+Huu+H115Xb5dy5KruhLXve4cPwySfw++/w5psBnOTQfIcQNKIjZN/lWwBRyri65YKRod9fmiBge/Ro5XLxzTdq13AP5khCCybJj0BLoFdiL/YV7cNsNfPDzh+45TvHJPofh1TGWAMGeib2hN01G9audUTBewoWc1IA7dzpV5Ual7h+oH0Ex1ZAxVH3QdiSHMPO1Knq+v3zn/DFF0roNW+eaxlNUw7Etku/ebMKeBYBafA5udvJpEWncajkEEtyltgDxcZkjKFnUs+gnkvTtLoTTK2IiwZexP0/3c+RUpXpOj06nTn957iUsT33Tpigkq3Uh67DpMxJLutqu1/Y6JnYk+uvV88rR4/C//7nm8DMxl1j7+LbHd8CSjBx7fBreWKJclGJDInk8sFe+kDeaOqghMgM6H2jeum6Crozl6ugb1vQXdFW+LoPmIuVm1XP6zz3dZqIadOgVy/Yvh3uuw+WLlVtnad2zRY87xedZkDcACjapMbqxn8K6ZPrihl0K6Cr/meEG3dHgxFievh58laIpkGXs9TLWg15K9V3x1Km3HzDkpWLTHgLDKAxlwJWCE1ovHN0Pgu2vQg5H8Hwl90njHH+DR1eDZVuMud7wIqjL+SPoKlPch+XdnJb3jb6pfYDYEfejjplg4LBpByEgo1mgE6nqheo61pdrALeTVEQEo9xtSPi0pubujeKq4opry4nIiQCUCIam1jEdt+3kzTavVuWuyQlmkG5n8X3r3vS0hzVxjQksUnhJiU81Ksh67Kaevn4MJh1mfpdu5urcEdkF+Um2RIIwKWkR2IPDhQfwGw18+XWLympcmTY2HjE4YqaFdOHL2q0jyee6LuQ/I8a04+hQ6FPPT8r270rNTqV6JBoSqpVXWyuoxbdYv8NZ8ZlYjAYHE5eqGD0vLI8l2Pquk5RpXLzNGkmOsV0UsHdxU5Czv4PqjbJ+TviKSA36xLfXOFaONeNuI7HFj9mv97n9js36M/v9dLYwWKBJCwClWHhk08c8z0tIHt5VkIWJoOJamu1vT9hw+b6BSoZRLcEh/jLWXzpjZjQGPtypdm9+Ku0utT9ztZqJfz3h4L13rfruvft3jj2q/p9OveLQhOg89lQeQT2fxH4sdsYfVP6MqLjCFYeXMmugl329X2S+jC8Y/DdLIPlJNYaCDGGcN+4+7jxuxvt6/404U+OAianZ2NzSd37ijsB0eo1DRJB+cOdJ9zJ35b9zf6st/CShby//n1eW/MaoMR8tZ2/z+l3Dn9d8lfQYf6u+YQaQzFqRrtTPAAJAyFxuHJo3faSuqfWpnY/QdsN4Y83aMzgnrH32MVff5v8N0zO9/jEoY75mT3/B/0fqr//3+t62PQk5Hys+jq1+1WtZRw3CAJso7GJ5mdbG/lrHPlDe17XaKfp3FklrXz5ZXU5ly1ToStmM0RFwaBB6iW0IwJICNISEx8IgtAySItJ45+n/dP9xhbmNBhwnRqRgMRfPXr04MEHH2T58uUMGDCAkFojbzfffHNQKicIgiAIghAQxlA44W34+VQo3gnfDYIhz0CXs1WmZef0j8fXwK43YcTLzVploZ0TwMR5oFw59Eo+3fIpAPnl+UzoOsEu/IoLi+O0nqc1ST1aC5qm8em5n/LfNf/lmcnPuGwzGOCaa+DPf1bZ7Q8f9i/T8ZwBc3jmV3VMDY2o0Cg0NAyagZm9ZxJqqonIzLpUib7yV8OKK6F4G/S7X2WIs9qClwxqwuD4ajUpULABu3jIm1jMmbzfoOKIEorVJkhCK7/RjLDhMeg0UwVS+hoY4wfObtuDB7uK+EwmdU2va7yxcweaQQVQmUvUvat20FA7yOjX3tA0uOsuGD4crroKduyARx5RbYozJhMMGBDgSfKc1I1dz/exYgZIOaFuoFEwMvS3QK66Cv79bygqUoHqF17YAKc1ITgsWeIaUe5u4shsVjdfULOQflBmdmS/3V+8n3/9/i/7e1ugqRUrZdVlJFITODJunIo+dIctkCskBB54AFCZr7dsUYH0/gQMNwpZl8D6PwNmJTLoe2fzOga0AmJi4J571KuwEH77Tf21WiE2FkaMUFloU1NV2/HWWzBpUnPXum1iNBi5YsgVPL74cZcA8CuHXullr/ZJmCmMu0+4mzvn3wnAvePuJcTouKEdPgxHauI4hw3zLaDaaIQRHUf4dP4JXScwYoQ69po16hln4kTVbHs6j8XiEBeN7TyWmNAYiquK2XF8Bz/s/AFQrhun9jg1cGFecwYlaDWuVKYo1/WxvSHtFOUOtu4h5YAV08Nz29wESYs0DR57TCUhWLNGOX998YX6V1itjutkE30dPVr33+bTSSZ9DQsmQNl++HkqdD0PMudC+hTH5y9YrxzT8n6Hyb8E9XO2Wgwh6vk85YTmrolv2NtrDw9BHt3F/Uhq0vMa2PqcEsNtexmy7/YulEhM8EsIGkOxfTkvD7r6aNLUPcHVjXbkayPdltPQ6BLXyoKf3LRnMY5YfvbvV/1WX8XwZifXlEMlh+xigtxiR3IRa22Xl6QRNW2i07X2lKREt7gXxXkqD/4lNilYr4RfER0hZax/Qp30yf6Nb3U5p1UnsCuvLrcvHy49zAcbP7C/twmtdHSKShzfCVtCnPo4flzdkwBmzPDPeXRqj6l8ulmNkfdM6smpPU7l3fXv2t3ozu6nEoLFh8cTYgih2lqNjl7H+auossj+OTRNIy06DY443b+M4dD7tvqvn2ZS4srMC9tEfy02LJZbR93KY4sfA+D+8fc3fSUaO1gs0MCvykr1hfVEU2cvB7rFd7P3tyrMFZRUlRAdqsQjzuIvW1kbK1eqR7z6tFRxYQ7nm0pLJbquo9WybPHo/FWyy+nZwkdKdjoEum5pgF378VWgO9U9PBVO/tnhTLnqNtj6fODHb2NcPexqVh5cWWdd7esv+M/lQy63i78SwhM4uZuTK68xQongLWVw9FfIdONAUCdZQjoeHb+CTFJkEuO6jGPR3kXo6BwrO8bW41vt7dC5/c6ts8+gDoPIjMtkT+Eeth/fzrwd8+zlnV3C6HMbLLtQ/Va3vqxcYD1933QLdMlo8JhBQkQCL057kT8O/8HsPrNdy4anqvnNA1/CrjccjtbeyLocNv5V1W/9wzDsBe/l/Ukq0FS0RLeOloqvLqLOamvdosRfcdmQOKTRqwhNGsoitHTkyyAIQlMgToP1EtDI0SuvvEJ0dDS//PILv/ziOvmiaZqIvwRBEARBaH7SToGTvodFZ0FlHvx6sXLOSZusBtosFXBsmcrAmBj8DGOC0FKZmDnRPmG94egGluYsBVRQ3bQe0zAaWmcgQWMyu+9sZved7XbbpZfCQw+pgLjLLoOvv1bLvgQoTOsxjSeXPgnAr/t+5UjpETRNw6JbmN5juqOgMRxOmg+/nA5Hl8Cmp2DL8ypzevJoMIQpp8Ocj5UwLGEIVOerfaO6QuIw3z6oblVBdr1vbUFBBpoSnMwfCxO+hKThrhMZVk8TuIHx1FN1A0WMRrjxRuUA0uikToDc72HfJzD0mbrbW0tGP8EvTjxRuSysXw+ffgrffquClywWiItT2+fMcdWu+0zxNuwBDd3m4kgH6IXw9LpBys1FEwzsDR2qghQ3bFBOF1Onqt19CVQXGonBg+u3pKmqcoi//CQ7JZtf9/9qf1/t4V4yrOMwDq87HNA5AF57Td1Xmp2oLpB2Mhz+CbY8o4IJI9I93+tbYsBAMxIXB5Mnu9924YXw6qsqafvLL0NkpPdnQH+CUQUHlw6+lMcXP25/H24Kdw3sEexcPexqu/jriiFXuGxbvdqxPHy47/cyg8FAQngC+RX5XsvZApyefhqmTFFiszFjlEPy2LHq+28yqecZW3Do55/DWWep5RBjCDN7z+S99e+ho/PFli/Q0LDqVmb1meV6MufAGE9BMc4kJ6sbfkti0F9h/jioLoQF42DMu9BxqmqDNWPNP6nm4W//19D5jEav0jnnwDPPwJ13wvLl0K2buj6XXqrEzFarel564w11CZYvD+AkUV1g6u/w61zInaf6sHv/p+47phiwlKuXZoL4QLMfCM2OKRowKHc7dzgnNgk0qUlsb0iZAMeWwroH1fel4zT34gqrGTp39Cuos+sxE0xVy/PmqWzzvrjdZSZk+lT9EGNImxh/69pVZXwvLVVt+qmnBnac3JJch/irxIsAK3lM3edUT0lKQI35Wy3KMdCX8v4kNilY5ziHP8KvyAyVzKk23tzIEofVDAj4fpqWRL/Ufvx28Df7e08uokOTx/F6zXJkpG/PKuudzH0GDvQv8ca1w6/lk82f2Ov09OSn+efvjsG/a4ZdA6jYl5TIFA6WHMRitXC8wlX85SwGM1vNyimscINDeJI+HUwR9VdIt6jvR2xv3z9EC+eW0bfYxV8DO4htR8A0dvZyoFtCN5ffZm5xrt2pzVmUaytr4/ff1W+1PvevmLAYl/dVlqo6yR2chaIuBOLSWByAYMxXjv8OOB17yLMQ4+Rq122uiL+cOLffudz07U1UWNS916gZuWigGyFSS8NXMYYzTexsEhESwYQuE1iUs4i7x97tKqjTNMiYDTkfqLkmXxLgBjIOHxamnqdtAw5+/J9m9JrB4pzFGDCwfP9yVh5QIkGDZuCUrFPqHEbTNC4YcIFy/wK25G0BYHCHwS7tEp3PhrjHlWvyqptVssXsu9X8p20s1PZ8WF0Ea++Hkf9q8LW7adRNnjf2uBr2f6aSoKy+A4Y977ms1QKRHdX1O/AFbH0RwjuohKC1x2xt7Xbpfojp5v54zUVLdOtoifjjIuqUeM5Op5l1+zuCIPjG2rWOgZ4WeJ8XhHZPS3QaDOR5uREJKKJv924/bbUFQRAEQRCagw4nwmnrYesLsOstqDyiMithAPSarDgmSB3f3DVtPdQ34C2d4BZPZEgk47uO56fdP2G2mpm3cx4GzYBVt7oKjgSfyMiAiy+G//s/FYM+Zw68/bYaK3IOUjCb1XzLyy/DLbeodWM6jyEyJJKy6jJW564mtyTXPsk6pfsU1xOFxsHJP8Hmp2HbP6D8IOz/Qk3cAI6M2gaI6Q35Ne5c6dPUBIBPgSgabHpaZV4PS2oZArCRr8HKuVB+CL4fobIp97gaYrMBK+Svh22vAdMCPkVIiApGHTBABap6KtMkdDkPDn4LpXuUM2XCwOBndm4FE5ftEU1TgUoDB8LDDwfxwKV71N/wVEgY7Ns+psggVqCB1DewB3UH9wL4vv75z3D22XDoEIwfDz/8AFlZrkIvm2jj55/hlLrzz0IrYkzGGF5f83q95U7udjLv8V5A5zAadF56Cc47D4YM8RwsbDaD6WATtMt97oRDC1RSjJ9OUlmpIzqqbbZnBN2KXXQd4a+dS/vk4ovhX/9SLqKXXgoff+y5rNmsXiL+8p8eiT0Y23ksS/eppBXn9TuvTvCgoIgJi2H7TdvtrsLObNumAqKtVuVe509wdK+kXqw4sMLjdoNmoHeyClQ+6STVH5o7V92ux42DQYNUoozMTHU/XbsW/vtfSEtziL8AZvaeybvr3wVgxYEV6OgYNAPTezr1U9tK9uikETD+E1h0JlTmw8JpKtg76zKI7q7Gqwo3KAfo8A5NIv4CuOMOJea4/HIoLoZ331XX0xmjUT2zBkx4Mkz6FvLXwp53Yff/qfG6qprgeUM4dJ4N3a8MMPuB0OyEpwC6CtauLoGQ6LplgpHYZNQrMG8EmEth0SzIvgd636LO7/zdOTQfdr8DY9/1uR1IQ7WVv/+uEnTc76NhjclgItQYSpWlymu51Eg3juutkLAwmDULPvhAib/+85/AjnPZF5eRFJEEwNHSo+4LGSP8c4eDmmRI9djRBEJ1kUrCBBDXTwkMa4+hlea4Fyy4E7Z6cyMD1Zd3N0bn6RwtjLGdx/LG2jfqLTexm2OOxmr17RawYYPDdWjIEP8StYzJGIPJYMJsNbPj+A42HtlIhVldg7ToNBd3o/SYdA6WHERH53CJa4KQvPI8+7KOrpy/in7Hnoiny1k+JtjQHc5BtWkl17o2yZHJWB9qgMNSgyvQyAmFWljgV0Nw/r4D3Pb9beq7DGw+6vrdc3auXLeufuEXQHRoNEbNaHfpKTeX1xV/mT2Iv4q21CRH8EHMVboPQrtD8RYa5O7lCXM5lDjFykV2gcw5ruP3Vh/+Ie2I2LBYzut/Hm/98RYAp/c+nZSolGauVT34I8ZwJixMZQeyjVM3wfz5z5f+XJMzxM0NM/N82PsuVB6FA19Dx1O934syOvkXYJubqzr03pwMwWP/fHqP6dw1/y4Aftz9I6XVpQCM7jSa+PB4t4c6p985dvGXjTkD5rgWMobCifPhhzFQfgD+uA+2/wO6X6ESBJui1Hzjnndh38cQ29d7/YNB2mRIGqXEo1tfUG3G4CcBg0O0Y3N5rToOa++B0a/BvHVQuhv+eAAO/Qi9b1ZJQW1tTslu2PYi5K2CKUsa/3MIwSdQF1FbVoiMWTJmIgiBMm6cGqj2RGsYXxaEtk5Lcxr0V5BWUgITJzZadVpANJ8gCIIgCEIjEtkJhjwNg56AIz/D8VVqgtYQrjIpZpwBYYnNXcvWQVsJshI4tcep/LT7JwCW71vuWXAk+MS//qWCDdauVZntf/wRrr4aLrkEkpJU0NzHH8NLL6n5HJv4K9QYyuSsyXyx9QsqLBXsLlATh/1S+pEe4ybo2mBS2d2y74Uji2DvB2rywlIBoQnKBazrHMhbATn/U/t0nO6H+EtXE0E/T4VTFqps3bWDSxorY6Ynup4NUUmwbA5U5cPRX+HoUtcy1nAaIv6yjetNn14ThO+ml9xkLj8ZM5UoWTfDmjuU4M8b7gKMvBHoxKW05a2T6iL1AuWI6iuah+9UWLJ6fqodkOZvAJ6/NMHA3llnqYDOv/4Vdu5U7hazZsENN0D37qptWLYMnntOBZU5u6cIrY+pPabWW0ZDo2t814DPoaPMyaZPh/nzVSCis5jQdr/Z9H0OA89ugna541To/xBseASKd6jg0m4XQ9/bVYZq3aockTc/q8QGU5b5/ZnbI6NGwaRJsHixiu+54gr4xz+UwMt2ra1WNQd//DjcdRe89VazVrnVcuXQK+3ir8uHXN7MtWnZ9Ejs4XZ9ebkSfEVFqT6KP5ySdYpd/BVhimBMxhj2FOxhV8EuALondHcpf8EFkJKiRJEHD6q+0q23uh7TZFLiL2em9ZhmD8I+WqaC/8d2HktihNOYTVvKHt1pBkxeBMsugpKdULwT1t7rWkYzKfFXE3L22Sp+7/PPlYvlTz853NqMRuXsc+ONDdRlaRokDlGvIU9D5XHlEmWMUH1bY1j9xxBaLmmTYcOjajl3ngpIa4zkMrG94cTv4OfpYCmDjY+rhDlpU9SYr6VcjR+U7FQO6X5y7rmwapV6bdqk+gje3L9sySI6RHVgX9E+r8d2cSdo5ZxzjhKK5uXBm2+qsTBfXNKc2Za3rf5CITH+OWyBSnbQGN89ZxFOfL+6272JueIH1h3L8eZGppkgxs293dM5yr04pzUTvow3GzUjnZMdDyilpar/VN93af16dW8ymZR42R+iQqMYnj6c5QfU2Pg3278BlKh9ctZkl0D6jNgMVueuRkcnryzP5TjOzl+ghGMc3O0YQ02f6ruzcmxfR/C3DW/fpxZ4vWvjVpDQVDR2pvBAEhbZxBKVlb5/Dj8d7gMhNcpVlDxvxzz7tXN2BDNoBkKNyqld11WCCV+IDo1Wx6t5piyvLq8j7rCJL+vgj/CxKg/o7irQcoe5TP22/BWiF27ERVTW57a6zowtIaFeC+PyIZfbxV9XDrmymWvjA4GKMSorvQuhGmHOxaAZPDuDpk1R7srmYvjtWjh1PYTGu/+O2r7H/ozDr17tX1tmo6Z/nj1kCOnR6eSW5LL+iMPKc0Yvz//DQR0GkRmXyZ7CPfZ1bp3hIzvCtJWwaDYcW6bEXuv/ol4uGIKffNEdBiNM+EIluCzPhS1/hz3vQI9r1biAKRoqDsOuN5Qzdlw/1S8+5Rc1X1u4EQ7/pF4hsWqexlKuPhc6JI5o/M/gL40twG73GFXfKHGo/30kQRACo6WOLwuC0LT487xcVNSoVfG553n77bfz6KOPEhUVxe233+617N///vcGV0wQBKE9YjKZuOSSS+zLwS4v+I5cizaIwagCn/0JfhZcaUtBVu2caT2mcef8OwHYX7wfgOyUbPeCI6FeIiKU4Ou002DpUsjPhyeeUC9nNK3uuPX0HtP5YusXLuu8TW6oAxmgwyT1ckfJLpQTmFVlOfYy4WjSzFzS6U21nH4iHF4ABX/A132hz+3Q6waHC1BVAaYtz3JJv3Uw/IVGu9/Vuad2nAqzD8K+T2Hby3DsV9fyHUZzSe9ekDza5zrZznHuuWA2q32mT/fsgBAREc7kyVMxGCA8PNz/z+ArofHQaSYc+AIO/wxr7lbBkFaLIwOgDasFirZBvIeswO4IdOJS2vLWiXOgQ8oEHzNNowIn3RHVBU7fqgLTynOhqkAJv1LGBKW6zc1jj6mgsUcfVe31J5+oV22GDWv6unkjkPamJfZdmrL/lRGbgYaG7sUFIDYs1nGOw4cxzZjhGuHuJljMpOtckpcHcXFERIRwzz0qCHbYMDjjDLjnHujXT4mB1qxRzwlJe4/xXlO1ywMeBmsVbHoSrJWw49/q5eL8BSQObzsukY3sWqxpyuliyBA4fFg5GX3xBdx0kwqEjo6GI0fglVeUc062H7dswZWzs8/msi8uA2B8F3HuDoTKSvWdjYjwf99LB1/K44sfB8CiW5h/8Xwu/+Jycgpz0NG5aOBFdfaZPFn9BL//XiXL+P57R9KF2FglELvpJtd9YsNimdR1Egt2L7Cvm91ntv8Vbk0kj4bTt8ORX2D7v1VGdovKeE5IPHQ9D3rd5PUQjUF4OJx/vnqZzVBYqPpKsbGNkBhDMyg3MCTIq82QPMYRaHrgS+h8Vv37BErKWJjyK6y+HQ79oJ5nDn7jVKDmOSc0we9Dn3mmEm6DitVdvlw9x7kbNzCb1eNZSIgSdtUn/hrQwY37UytlyhSIjISyMrjtNhg7ViXQcOd2qusmTjnlEjp1gsfffrxeUy6T0cQloyth74eYTAHYp5oCuOn5QpGz+GtQ3XE3b2Iud85f3ojp4b4f7+kcVQX+Hb8J6BzXud7+V2JEIpGRDpfSdevUPag+Dh9Wv78BAwK7P52cdTK/HfwNq25lcc5iDJoBq25lUuYkl3Lp0emYDCaqrdUcr3AVe9UWg6XHpDvGY2L7qABtX4nLriv+8vZ9aoHXu8XR2AmFAjn+tm2NJ0gLkNrzQhbd4raNjgpxuAsfO6YSmftCVEgUmpNCxZ3Ll038ZcbM7ym/89KpL6nxnsL1XhPSucxvGGfUJBWop2LFW5Wo8vSt/gnACv5wLBvCoMfVIvbyAec+vC8JmdoNjT3nYgyFfvcq16iKQ/DTScqBOaITyi6s5qHWalHjhBseqXGjaho0TeP0XqfzyupXMDs55rk4f7vZZ86AOTyxRE2+DuowyHNShfBUmLwE8lbC9n/B3vfV57QR0Ql6Xa8cp5uCiA6q3/LTKcrRsPKY+p9veMS1nHNivsiOap+dr8HWF5ULmLkMzE59DUOYEpC1NBpbgN1W8EMkZzKbueTNN+F8DZNWCZGd3fcTSnPU96twc917ZCukrcx/NTbt9f8U0LzimDFwzTWYfLGvFQRBaMH43HKvWbOG6prZuTVr1ngs16zZewRBEFo5BoOBzMzMRisv+I5cC0EQ2jLZKdl0iOrA4dLD9syNM3q2zkG/lkJcHCxcqLKjP/MMrFCJ8TEaVdCCrqss0Q8+6Lqfu8muaT0Cd7EClPhLMwIGiHAj6HMa+DVoOpmRe9T6ge/A2go4tlRNBq29Gzb8RWXM1q1Qtg+DpYLMhCHQiPc8t/dUYzhkXqBeVflqElfTIDQJQ2gc/tbGYDDQtWsmf/yhrk1YmApQ8iT+MplMnHDC6IZ9Bl8Z/gIcWqAC5Tb/TWUpH/QExPZylDGXw5ZnIfcH5RYgCO5wFn/F9vI903RlnmfHwKgu/mfFbSVoGjzyiHK7eP55eOcdFaSuaQ63i+RkuPbaZq1mHQJpb1pi36Wp+1/x4fHkV+SrY2kGjJoRi26xPxd1ieviOIeP5zGA/X5010jl9PTUU+re8vnn6lWbC/sG/BH8R9Ng8BPQ4UR1fzm0wPG8YNuuW6A6u224RDaRa3FqKixaBOPHq+DTvDx4+GH1ckaGzBtGdGg0m67fRKgxVOYfAsT2U/Ahj0EdshKyiAyJpKy6jCpLFfuL9rP52GbMupokH5o+1O1+NpeoU09V78vLlTOHO0GAjVl9ZrmIv2b2nul/hVsbmuaa3MNqBrS6yR+aCZPJf7c4oZ1jMEHHU2Hfxypzfb8/qaQRnoKjfXYr90B8PzjpeyjarhLGHP5RjRsYwyGqK3S/KiABWlYWzJwJ33yjhPtz5sD//R+Ehrq6EVksyvH9ttuU89XA1IEs2uu9n35C5xP8rk9LJSICnnwSbr5Z/R9OOUUJ3089VfWnjEb1PwoJgR9+MPDSS5n88APERcRxrOyY12MnRSWRmazD0RzAQ8IqTw7V4N7JwVt5X12tqwpRThEoF11/CE30TygQ60eH4RiwYTfk11hVt6AEDs79L3d0i++GyQSDBysjkZ9/9k3MZXu+ycgIrF6TMifZBe4bjmyw9wdri7/SotPs4rXCikJ0Xbc/kx4vP+4ibkuLSoGKGkeulHH+tXFx/cEQGtiHEVoPTeBwHwjhpnDP7ls1ODuEbd9ed7umweWXq7mS119XCQRA9eeccXeeKksVADo6ljiLGo/RdZX8zAsu8xsGrSYxng9YK9QciV/ir/WghYBeDUkjHEnzBK9omkbJfSXouo5JxHJNS9971BzS0SXq+/tlFnS7VCV9jEiD6mL1vL7lOfXc3ITiL1BCr1dWv2J/nxKZwqAOg7zuc072OXbx15z+c7yfQNMgeaR6jfgnVB5VjlkhcRCW0vR97shOyoFt36ew+Rk4vrJWfY3Q+Wzo94BjXUg09LkVet+sxnKP/arE38YI1X51PS+gRBdNQgu937Uo/HARtc897JkNFVaIrt8d2KDhuEdWHmqMT9DotJX5r8amvf6fAppXTE6GPXsarU6CIAhNhc89q59//tntsiAIgiAIgtBO8CP7kJ3w8LpWR0Kzo2kaM3rN4PU1r9vXNVhwJGAyKdHA2WfD77+r4KCCAoiJUbHHkybVDfzNjM+ke0J3dubvBCDCFNHwIKDiHWoCMjqrbqBLrYFfF6oK4MRv4Y8/qazzehWYS6Foq1MhDYzRdfdtSkITgjKZUVAAVWpOmcGDvQehggpaqq9MUIjMgHH/g4UzAF1NBO3/XDlXRnRU1+Twz2pyOmFIE1RIaLWU7sbuAuhpIqhGCOqCuUQFVsT1aYpatjgGDlTuPU8+CT/9pAQ8ISEqEeWUKSrYU2j9jO08lm+3fwvA4A6Dmd5zOv/3x/+RU5QDwClZDXML1jTl7DV2rHKTW7lSPSdYapJVG40qQ33G4GTY7efzNTTsGTt9inoVbIScj1TgAxqEp0CXc2FnOVS87f9xW5pLZBO6FnfvDhs3wj//Cc8+q54xTCYVp6Zp6hmie/e6gjDBP/qmNKVasu1he461uW/5g0EzMCRtCEv3LQVge952tuc5oj09ib9q44vr2Om9T+fG724EVKB198TurgXaw7iEBEQKbYGMMyDnAyUsXzoHpiwDqxtRo815NBjE9lTJVILIK69A374qeP3TT2HJEvjTn+Cyy5TD5/Hj8PLLKglQj5ou1wmdT+DllS97Pe7J3U4Oaj2bmxtugG+/hR9+gAMH4LTT4IQT4NJLITFRieP/+1+VKGlIzTBGenR6veKvjtEdVWArqEBdd9R2qC7cpJIZgXJG8FYeAnO1ttbYaRojwBjm2z42jH4KBUJifSt3DLgTqH4QeNBzuWZK4HByt5P5bMtnAIzrMo6LBl7E44seZ0/hHgDO6H0GoJxD161TArDSUoiK8nRERVnNJQ5E3A4wJmMMJoMJs9VMbokSbKVFp9Et3tVFJD0m3e5KUm2tpqy6jKhQVbnj5ccxGoyYrWYiTBFEW4odLkUxPUA3g+bjQIJz4idBaGKSI5LZX7zfa5nOsZ3ty7t3191+443w4otqedgwuPBCtRwdGu3i/lde7dqm67puF38ZNAMxYTFqQ1W+wxXXV0p2+lfeH8oOqN80QOoElbRBnt19wtZmtgoC6XMGQlP0Uw1GmPAFLJgABRvAWg07X1Wv2vgqgrcR6P/J6XOf3O1k+30YYEavGfUm/BmcNti+fE6/c3w/rykCTC1gzNJggq7nqlf+H0qwai5VgrTEoUog5g7N4BjTFdoW/ojkrBbYelAtx/Som2RAHGMFoX6CcP8SBEFoCUhPVBAEoQVhsVhYtWoVAMOGDcNYT2o7f8sLviPXQhDcUF/2oZrMQy40UfZQwX+mdp9qF3+FGEIY22VsM9eobTF8uHr5woxeM3hhhQpQOiXrFEKNDVQWFNdkw3Q3WVNr4NeiG1hVOAyAYRX5GE1RMOw56Hc/bH0Rdv8fVOWhgsI7YMm6ilXFY+C33xrtftcU92CLxcLixasYMQJWrRrGyJFGLBbPWYWrqqr44osvADjjjDMIrUf90eDngo7T4YR3YcXlYK1SQSO5P7iWcZfBuj5kQLN9UbK75nuiQWRH123ehKAARxZCTFa7zjidmgrnn9/ctaifQNvAltZ3aer+14xeM/hm+zfo6KRGpfLYSY/x9h8OwdPM3jODUqfTT4cZM2DxYnj/fTh6VDmBpabCxRfDyJFdIMe37J4uBOMZO76fetVhdcOO205JSIAHHlCuH++9p7pNJSVq/ahRcPrpnh1GBaEpCA9XgsRA49dGdBzBigMrsFgtrD201u7ekRiRSHq0BzeWAOgS52jbTu91upsCbsYlmqLNFATBP7qcA5uehMKNyoXolxkw6jWItAWNaypQrbpAZb0f/ERz1tYjHTrAV1/BSScp4f6RI8rh6uabXR2CwTGeMLW7q8P76zNf50DRAR5a+BAA8WHxpEWnNdVHUG6ozm1mbeenIDhBGQzw0UcwcaJKhKTrsGyZermWs9Ct2yp++w26xXVj/ZH1Xo/bI6EHv+02QcFQhsWvxWitdu9o7exQHdfPIf6qLnTvutRQR2tLJSo5kp/CL3Dfx/bmRmYMc2QU8EYxEIDAu6kSOEzpPoWPN38MQGRIJFcOvZL7f7zfvn1y98kAnHiick8GJbg8/3zviZhszzWBJmmJCo1iePpwlh9Ybg88n5w1uU7geYeoDi7vb/7uZrs45Ze9v2C1KiFrXHicGm+xn6Ar4KYfWZpTNxEP+C8OFIQg0jGmY73ir55JDrfDvXtV0hNzjRaqSxf4298cZS+4QI2DHDigfmsWq8W+rdzsKv5ydgIzYaJDQQd+++03hmWFuPsFueAyv2GxYizZpcZDdUs9ewZAeS7YRGypE8Xiu63ihxOPC5WVEBbmfp/m7KeGxsEpi5S715ZnwFwOOCVg0Ezqeanjqf4dN9D/k9PnjgmLYWznsfyy9xcATu1Zfx00TeO20bexOnc1WQl+CtZaGgmD1EsQfMBisbDq1wWQP4RhcaswxvRQImQvMQUu90irXu89tSXSVua/Gpv2+n8KaA7v0CH4/HOGJSVhdJ6wkfFlQWj91DcGWntdK/9dByz+WrlyJR999BE5OTlU2dKl1/Dpp582uGKCIAjtEYvFwnfffQfA4MGDfXow9ae84DtyLQTBA/5kHxJaNM6OFpMyJzVccCQEzLQe0+ziL18mN7yi61C2Ty1HZ7kPcnHCohv57uhpAAy2OA38hqfAoEfVy7l8VRXfPaGCshrrftcU92CLxcKaNd9x2mmwdu1gRo40ugRt1aaqqopNmzYBMH36dJ/EXw1+Lsg8HzpMgnUPws7/4jIhByqgaeQr/h0zCBNyQiuiZLdyAYzqWlcs6C0DIMDRpdDz2satnxAUAm0DW1rfpan7X9kp2fas0zvzd2LVrfZM77btwaqTpsGECerlFnm+blNERsKVVzZ3LQShLjbxV2EhlJf75sLlzND0oZitZoyakVW5q+zrh6cPrzczt7+kR6eTW5LL9J7T3ReQdlMQWj4GE4x6HX4Yrd4fWqCST/S+CZJPUAKe/DVK+BXdHRKv829yHpqsnzp2LMybp+7vu3c7BF+1xxB61Rj2JEYm2tsxgL7JfTE4jcv46pYYFHJylBW9N+VvkJygoqNh6VJ47jl45BGH07rVqoRxVivExFgYOPA7vvsO+ozqw5d86fWY/ZL78d0v1cB0Bsesxli4ERIGe6+Is1NW/h+QPtXruFhAWKsALbBkKRY318KdG9mKK6HikArIRlfnc8abYKwF4uzguuP4DirNlRwtO2pf1ydZOY+PHau+LxaLcs2tLyGLqSbSxdIAjcfJWSez/MBy+/tJmZPqlCmpKnF5//a6t9FqrolFt2CtGbMrrSqF0r2OgtHd6zoeekvG407cKAhNRFZiFr8d/M1rmYEdBtqX9+513XbBBY7fJChR2FVXqd9yfc5fzmIwEyaSDiTx3YHvGHzJYB/EX07zG9Ya8VftNjNYVDjGjUgeHVhyNqF10Nb6nKFxMPBh6HMLbHkBji6GiqNqfVw/6HunchHylyD8n2b0mmEXfznPW3vj71P/3qBzCkJrxGKx8N2Py4HTGBy7FmNMz3rdJz3GALQi2sr8V2PTXv9PDZrDu+8+jIFmEREEoeXhyxgouI6DBjgG2lIISPz1v//9j4svvpgpU6Ywf/58pkyZwvbt2zl06BCzZ88Odh0FQRAEQRAEQQgyCREJ9uXaWYmFpmVi14n25QZfC2sVWGtS/UZ1qzfrl6Do3991crrFEJEGo16Foc8qMU55rsoCnDwKojIDyy7a1iYuBc+U7lZ/o7r5uaMGud+BpRyMfkaGC0IrITsl2768r2gfB4sO2jO9x4bFkhKZQnV1IKnz2wBtxSUykM/R0j6DIASRjh0dgdHr18PIkf7tbxMrWHQLm48qAYZBMzC8o492x36w4+YdFFYU0iG6Q/2FGwN/M0SCJEsQBHckDYeR/4EVVwE6WCuV2Ks2R6rgTD8n56FJJ+hPPFH97F96CV5/3dEEGAwwZAjceKNydbWRnZJtF3/lFOaQU5iDyWBCQ3N5Dm10jh3z/5muAU5Q4eFw331w6aXw8cewaBEcPw5JScoV7Iwz1P8PYHDa4HqPNzR9KCtY4Vhx7FeIy/YuugpLhPAOUHEYjv/eOGIaW5BlTf+hbh28CLMs5XXXQV03srAUJf6yVrkXrzkLxspzIWYN8KBfH6Mp6ZvsEH/tK9pHTqHDHSstOs3uohUdDePGwZIlsGuXctZ96in3w19mM5SVqeXKysDrNilzEo8vftzlfW16JLoGxJs9XHvl/LXX4ToU1bVuIW/JeNwJSbx9n6JbueOJ0KLon9K/3jKjOo2yL+/e7XD9Apgzx/W3ajLBtGnKDSwqJMrlOM5OX+7e2yk/iBJyecnaVpvSHNA9tM8NxSbSjcxwFRsLQmshNEGJwFoQ03tM5675dwEQHx7fvJURhNZERHrwk1wIgiAIQmulicdAWwIBhbf99a9/5bnnnuOGG24gJiaGF154gW7dunHNNdeQXjtDuCAIgiAIgiAILZKOMR05WHyQKd2nNHdV2jURIQ5xRbcEf0UatbA6BapHdpKBXx9p8d3YkFjo6MH5QBA8YQsqiw5A/FWZB9v+Ab1vq5ul2obVXG9mQUFoqSRFJpEQnkB+RT4V5grWHVln35adkh10F5tWRVtxiazvc7SGzyAIQWSok9HMb7/B4MHgT3LT3sm9CTWGUmWpYm+hSvNv1a2N4mATGRJJZEhk0I/rE4FkiIRWnyVSEBqN7leoBCYrLlfjFXotex7NCMVW/yfnockn6END4Y471KugAIqLISFBiVVqk52SzaK9i7DqVrv4C5RgxOZw1JZJT4ebblIvZ2xuYACjO4922Ta281isupVf9/9qXzcifYSr+CtvJfTwwaE6aTQc+EqJvxoDQxhK0FjlfnttYVbpXvj9BrWt/KD6LdQnSjOGqb+ezmE7j00wZhkA4Y+32AQOSZFJJEYkcrz8uOp/HXb0vwakDnAp++ijDtfkZ59VApK//EWJSkwm5SJnMMDbbzuch4qLA6/bmIwxLu+7xdcdQ+mX2s+nYyVFJNU4fxlUJcP8/N/qZtBqPaDV/j5VFaj10VmQMqbOIQQhUGondYgwRWDVrVRaHOrKIelD7Ms7dzrKZmXBwIHUITQUxo9Xzl/OODt9gasTmLNDGGX7lQOiXis5T3gqVBe7F9SW7a+7LhhYq6G6SC3HD2qccwhCOyQ7JZseCT08O38LguAeQ1hz10AQBEEQhGYkoCidnTt3ctppyhY0LCyM0tJSNE3jtttu46STTuIvf/lLUCspCIIgCIIgCELw2X+bmghr1wHOLQT9z35kr/SGc1CIISwwZ6h2hsEgJh9CG8UmBg1L8lOoZVV/NjwK3eZCaJL7fUX4JbRy+qX2Y0nOEgDW5K4BwKgZ6wQftkjqc6VpqCNNW3GJbCufQxCCQI8eEBEB5eWwahWE+GCEouuO7oTJYGJA6gBW5a4ivyLfXsY5ALRNEEiGSGj1WSIFoVHJnAOp42H9X2Dfp1B1XK03xUDHU6HTHGBWc9bQb+Lj1csTfZL7YLaaMRqM5BTmsKdgj90pqD2Iv3yhU0wnYsNiKapUgfTPT3ue0qpSJr01CahxgwqPcd3p6GLfxrmShsPBr5UAoPKY/wKc+jCGAVawlIFu9ezMZRdmVcGqm5X4sWCdb4majOHqb2Web3VqBQkc+qf2Z9HeRQCsPbQWUM8X/VNd3YbGj4cZM2DePOUq9MQT8M038Oc/Q9eucPQovPyyWhcfr8b13Jl0+kpUqMORaHj6cLfj5LWFK57oENUBqvJrXL8y/U/KZTW7d7ar7QwnCI3ApMxJaGh28dXWG7ey4cgGTn3vVAC6xnXFVDMWqOtw4IBj3/HjXfsONqqqlENmHfFXdS3xl5MYzKpbnTbkYh+ntNHtEhj9X+Xw9f0IKC903V5xyMdP7CeVTu1rwiBJiiUIQULTNLbfvL25qyEIrQ8RfwmCIAhCuyag3mhiYiLFNSmUOnXqxIYNGxgwYAAFBQWUlZUFtYKCIAiCIAiCIDQOIvpqg7iIv0IAcf6qj6QkMHowNhKEVo1N/KWFAH4ITKO7Q+kelc124QyY8BmEpzkCGqxmFeC28QmIv8y7AMXdOnHWEVoIA1IHsGzfMqy6lc3HNmPUjOjoZKdkN3fVvOOLK4040giCUAuDQQVeLlumXr50BS0W5bBhY2SnkazKXWV/Hx0a7dYdQxAEoQ6RGTDqVRj5Hyg7AFghopPqY6xe3dy1Czp9kvugo2O2mtlbuJdd+bvs23on927GmrUsusV344/DfwCQW5xLaXWpfVv3hO6uhbUQKN4BufOhw4neA+4Thztc5na9Bb1v8V7eFycuZ4wRSuWgV6vvc1TnesqHQnQPKN4KBeuV4119hCYAGhRu9L1eLTzxwYDUASzJWeLS/zJbzW77X//8JwwaBEVF6nlk3To466y6xwwPh5ISJUIpKoLY2MDq1iupF9vytjEqY5THMiGGEKqt1R63A3SK7QR6EaCrds9fzCVgaib3U6HdE2YKIyUqhSOlRwDILckltyTXvr1nUk/78rFjUOkwBGPECKiurussHBqqHMHKnUSW4N35y0ot8Zeza2hILAx/SQkrIzMg6wrY+HfHdqtZCTAbg4rDjuXoLPwaaxUEQRCEYOOufxOWDIZwsLqZN4jObPQqCYIgCEKzkZysBon8SewXHt6qs4QHJP4aP3488+fPZ8CAAZx77rnccsst/PTTT8yfP5+TTz452HUUBEEQBEEQBEEQfME5CEGcv3yidtJjQWgz2NoDg5/ir4wzYcvf1PLx3+GbATD6deg4AwxGKNoCyy6Eoxa49sn6B9FEhCK0UPom90XXdTQ0duXvwqpbW4f4KxBXGnGkEQQBGDkSVq6EbduUAGzUKO9JEAy18kgMTR9a570kFBEEwS80Q/1CmTZA7ySHwGtX/i578Hy4KZxOMZ2ariItPPChV1Iv1h9Zj1W3kluSS2lVKQbNgAGDi8gAUEIrDdj4GKRP9nxQqxkShzneb/sH9LnVe0V8EWM54xz0X/AHRHaq3+EpcRiU7IDC9b6dI7YvHJwHpXvBUq4EZ62c7JRse/9rT8EeLDWCDnf9r86d4YcfYMIE5RxksdQpgsGgvq5mZarHhg1wwgmB1e2GETdw+/e3c16/8zyWiQqNoqCiwOtxshKywLoS0MEYgIiraAuEp/q/nyAEie4J3R3ir+Jccotz7W5fzqLcvXtd9xszpq7wy0ZWFuwtdjh/GTQDFWbX+1Lt93bKc13f97jaIZA0mKDzbFfxV1UBjSbKqjjiWA7vAJq4fgmCIAjNiHMyWBtRXeD0rQ63yqL9sHONWk72nORAEARBEFo9Xbqo+BPnpMUAublQUKCW4+Ndg8NaecLigHqkL7/8MhU1A8X33XcfISEhLFmyhDPPPJMHH3wwqBUUBEEQBEEQBEEQfMQl2MRNZIRk/apDWlpz10AQGglbZlxvGc7dET8Q0k6Bwz+rY1QXwOKaFNua0XHconqchzwhIhShhZCdko1eExR0oPiAfblvct/mrJYgCEKjMXSoysgP8Le/wWefeS5bXQ1Ll8KkSY51Q9KGuJQZnj48+JUUBKH9EYhACVp0dtaOMR2JMEVQbi4npzDHHtTeK6lX04pm6wt8qB30AE0a+JCVkIVRM2LUjHbnL5sbbx1nSUMoUA1HFkHOxyrgv7Zoy2pWQqnwFIjKVI7Wpbth2z+h53Xu+8ZWMxz4Sh3PV+L6OZYLN0L6FNA8qB5sxA+AnA+gMk8JCOoT+MT3V4I3UIKghCHey7cCnPtfB4sP2td76n8NHw7Ll8MFF8DGjcqN1GxWoi+rFRIT4dFHYe5cVX7tWrWPJwGKN24edTM3j7rZa5mE8IR6xV89E3vC0aXqjT9ucjYKNkDy6JrvuyA0PT0Se/Dbgd+w6lYOlRziUMkhNDSsutWlXT5wwLFPSAgMGOD5mCEhyjHYhkEzuDh9QV0nMDuVh13fdzodpQS2HazW76wyz/1xjBHqVXXcc0Xrw1n8FdFJku4JgiAIzYs78RcoAVhUTX8uuj+wpsmqJAiCIAjNSpcu7Sr+JCDxV2Jion3ZYDBw9913c/fddwetUoIgCO0Vk8nEnDlz7MvBLi/4jlwLQRAEoVXiHBxgqQLd6ioIq5X1y1R6kDldD0J4Gqa0sfUevinud01xDzaZTHz00RyqqmDCBBO67n2+Njw8nAkTJtiXG6NOghB0bL993U8haEx3GPMOfDcEKo+47u/uWEKzEmgb2NLaqObofzlnmD9Wpu6LEaYIMmIzmq1OgiAIjcmECeqZV9fh88/ht9+UIKx2k6XrKrD6pZdcxV/9U/u7lKvtBNYmaIMiFEFo8QSSmRVadHZWTdPoldSLPw7/QXFVsX39gFQv0fGNRQsKfKj9vNwtvhtmqxmjwaicv6pLsegWu8jApfyxHNj7Nuhm+PViMH4EHacDmrq5WauV48vvN8K4D6Dn9bD2XsAK6x6ClLEq0YmzAMxqVsKqbS/5J/6K6AimaDCXKPGXL0Kd+IGO/vS+T6D7ld7FQTEO9ziOr4W4/oGJiVoQzv2v4+VKgJEcmUxCRILHfQYOhNWr4Ztv4NNPIScHkpJgxgw480yIjobLL1ei9RUr4LrrGq/+yZHJ7C7Y7bVMv5R+cLgmEDeQ61W0WdyEhGalW3w35cCoGcgtySW3JBez1axEuQkO8Zft9gzQp48SeHnCaoWokCj7ew2tjtjLWQxmwUK/k/oxMHUApt8fdWi9DGGQNNp1rsNajUmzMKfjuwCYLDfVrUB4Gkxbqf7OHwt5v9X7f3BLxRFHUixPAt7SHCjcHNjxBUEQBMELJpOJOTPHwO83YtIs4Ek4XXufVj5f0Vbmvxqb9vp/kjk8QRDaMz63YkVFRT4fNDY2NqDKCIIgtHcMBgO9evVqtPKC78i1EARBEFolzgEn1ioVuVlb1OSU9cuQOJRenf04fBPc75riHmwwGNi6tRdmM5x3nsoc7G2S2mQyceKJJzZqnQQh6NgCjazV1GkIaglBKc9VgXLRWZAyRq078Tv4abLKiltb9KUZ62ZZF5qFQNvAltZGNUf/Ky06jejQaEqqSuyBRn2S+9jdGKRPKAhCW6NrV5gyBRYsAIsFzj0XfvkFOnZ0PAvrunpdfjnsrhXfHGYKo1diL7Yd3wa0UfFXGxShCEKroAUJlILFgA4D+OPwHy7reif19lC6fVD7eblbQjd0dMxWMweLD1JSVYJVtwLKFcylfOptsOe/atlSDovOgN43Q9ZlEBIHB7+FjU9AWJIq0/0KWPcgWCuVm/WCiTDuI+g4zVGhI4tg8ZmqH+wPmgaxfeH4Sshf59s+sX0cy7veVE5k3ojvj+rH65C3HLIu8a+OLZCUyBTiwuIorCyk0lIJ1BWWuyM0FGbPVi939OqlnME++wz+8x+lx24M0mPS6y3TK6mXEhWC5zETb8l4Cje7ClsEoYnpltCNams1JoOJ3OJc9hXtszv2OTt/FRU5XPjqGwaxWCAyJNJlnc0R0917K1a6ZnWlV1IirHIaj0weA8ZaYltDCAbNSq+o7TUnK6xbgey7lfBLM0D2PbD4LO8V9kTlEcAAWBz3GmdKc+Cr3nV/2+W5gZ1PEARBEJwwGAz06t4VNtfc80p3Q9II9+7Gzvu08vmKtjL/1di01/+TzOEJgtCe8Vn8FR8fbw9+8ISu62iahsUimaAFQRAEQRAEQRCaHOessuYSwAqIQMMdVhVPRGqqCnAVhDaHLVu0O/EXuAhB3ZIwCE7bAL9dDfu/BJx+KLF9IP0h4LwgVlgQmhZN0+ib3JeVB1fag5kGdhjYzLUSBEFoXG66Cb7/Xi3v3QsnnAD/939w0klqXW4u3HCDcgYbMqTu/iM6jbCLv3oltdHJ8jYoQhEEoenpk9Sn7rrkuuvaM1kJDtHVvqJ9lFaV2t87O8wASgzV5XzY95FKTqJbYMtz6uWMLSA/LBF6XgvbXlZlzSWwcLpy0IrLhqKtUOAqzvOLhEGQv0Ydo3QfRNWTWSm6G5hiwFysXGeOLYfE4e6DNXUrVOZBZBco26ucwob/w7soqD5L+xaApmn0S+nHsv3L7OuC4YY3dChs2QLFxfDBB3DBBZ4TPJnNdR1PfaVLrOuzQYghBF3XMetK7KWhEWoKdVxTT87pzsl4bIl4drwCR5coJzlf0K0iEhMaBZvAy2w1c7DkIAeLDtq3ObfZhYWu4q/qas+/O6MRDAYj4cZwKixKGOXs9AXUcQKLDo2GikOuB+owSYkrvQS5U1WAEmjVDPwbI2ucFmv2icr0vG99VBwBdDBFgdGNyrTymHtRZ1VB4OcUBEEQBGdCncTHxTuw3+8EQRAEQWh3+Dy89fPPPzdmPQRBEATAYrGwfv16AAYMGIDR6D1Y29/ygu/ItRAEQRBaJc7OXyW7PZeroSXe75qiTtXVFgYOVPuEhAygPoFcVVUV8+bNA2DatGmEhoZ6LS/PBUKLwCYGrS4OPCgoPBUmfA7lh+DwQuUomDAYEgbC6tVBqqjQEAJpb1piG9Vc96MBqQNYeXCl/X12Snaz16lekpNVOvsKN0FFnggPV/sJgtDumT4d+vZV5lZWKxw8CCefDBkZEBengqe95fYb3GEw765/FwCjofnvH4IgCC2V3sl1Xb7au/ir9vNyl7guaGjo6OQW51JWXQYoUU1adFrd5+vhL8GRn6HiKD4FOvb7E+x5FyqPO8oXblAvFwIQTcX1UwIcgN1vQfa93gUJ1YXQ8VQl5NLN8Mef4OQF7stqBtjxbyUwK8tRQrADX0GnGa5Jn1zQA/scTcyADgNcxF/O/a9AGToU3lWPJjz1FMyd67lsQ8RfIzuNhJquY4QpgttG38bGoxv5YusXAHSI7qA22sZmrdWeD1Y7GU/RZji2TIldCtZB3IAWL+YT2ibOwtt9hfs4WnYUUM5diRGJ9m2FhY6vaPfu3o9pqBmSjAiJoMJSgY5eR+xVXl1uvx8YMHBw+0Eqqw4xQDdg1Gra2viBuGvnLLqB9cUqkc+AigKMmtHRPqdOgJAYR2GbM18glB9S7XdYPWJfQRAEQWgELBYL6zfvg5JRDIhaibFkh2tMgKd9Wtg8kL+0lfmvxqa9/p9a7ByeIAhCE+Dz8NbEiRMbsx6CIAgC6kHziy/UREF2drZPD6b+lBd8R66FIAiC0CoxmCAkAarzoXSXl6AQRUu83zVFnaqqLMyapfYxGrPRtPrFX2vWrAHgpJNO8kn8Jc8FQrNjCFN/S/c0PCN0RBpknu+6LhABCogIJcgE0t60xDaque5HtYMN+yb3bfY61UuXLkq1ceyY6/rcXCgogPh4SE933ZacLC42giAAKvjyX/+CE090Xb9/v3rVLlubIenKDiyknn6GIAhCe6e20EtDo2dSz2aqTcug9vNyaGgoadFp5JbkcrT0KNYagVaXuC4YNANVlirX5+vwZBj3Mfx0igrA9+SsZCM8Gca+Dz9NqadmAdjBx2VjF5Tt+I8Sf3k8vAX2/g+yLoOcD9S6wz/Cqlth2PN1y2/8Kxz8DjrNhIPfqP03Pw2dZ3s+h7kCQiL9/xxNTO3+VzDEX2efDbffrpY3b4YXX4RbbnGvnfrHP+COOwI7z4hOI+zLZquZx056jH+s/Adfbv0SHZ0haTWWqb6Iv2oT21d9pwH2vAeDHqe+RFWC0Bh0iumEyWBSzl/FB6m0VALQNa4rmtOPqqhIGQ4CdOvm2fXLmciQSPIr8tF1N+IvczkGzYBFt2DEyJL5SwDI7m50En/1BzfJJyy6kS8Oz1LlqzZgdG7Tk0ep36Kt7+JNpFsfNieyiA6BH0MQBEEQAsRisfDFl18C08nuvhpj8Q7f9mlh80D+0lbmvxqb9vp/arFzeIIgCE1AwL3b/Px8Xn/9dTZv3oymafTt25fLLruMxMTE+ncWBEEQBEEQBEEQGofoLMhfBSW7mrsmLRazU5LPQDP+CkKLJzIDirdCaf0ugAFRnwAFRIQitHgaI/iwSejSRX5HgiAEzMSJcPfd8PTTjqDN2hiNdW/hAEPThwJw4YALG7GGgiAIrZ8eiT0waAasNe4jGbEZhJvCm7lWLY/uid3JLcm1C78AeiZ6EcmljoMpy2DhqVBxGOUCo4NmVDe1PrWUPWmnwKjX4beram56zo5hmnr1u9//iiePUQlXrJVQth/2/B9kzq0rLNAtYCmHnA/hxPkQ3qGm3sDWF8BSqYQ+YYnKtXvjX2HTk5AwBLqcDRv+osoeWw57P4QuZ6nPWpvtL0P23f5/jiamMfpfGRlK1L5woXI1vf12Nexw0UXqva6r55onnoCPPgpc/JUWnWZfrrZWU1pdyvHy43Yn1PTomgcnQwiggaXM94PHOZKQsOstGPio++sMSshybDmkjvfzEwhC/RgNRjpGdySnKIe8sjz7+trtcmGh+n0BZGX5duyo0CgArLqVCrNrIqkKc4USl9Xum2hGoBo0E0R1o16qClyFwckneP4t+YtN0BmWGpzjCYIgCELAGMAH8ZcgCIIgCG2XgMLcfvnlF2bOnElcXBzDhw8H4MUXX+SRRx7hyy+/FJcwQRAEQRAEQRCE5iKmJ+SvEfGXFyxOc8Amk/tswILQ6onpDkd+gZI9jXcOEaAIrZy+KX1d3mfGZzZPRQRBEJqYRx+FI0fgjTfqbjMaoXNn5Y5Rm4SIBPQ/B+CQIgiC0M4IN4WTEZNBTlEO0IqSDDQxPRJ7sCRnicu67ondve+UOBRm7oK9H8CBr8BSodZ1vxKiM+uW736ZSpS05g44vsqxPn4QDP2bEoj5S0gMZMyCfZ8ox6bfb4L4IRDfz+Ewo+vqtWi2EiQYjND7FvjjTzhcw/4Nu/4LEelQcUQJxez16w+x2VC0Sb3/9WJVLqVGzKBblcv35meVs1grFH8lRwbHFfyqq+Cnn9SyrsOll8J338GFF0J1Nbz+Onz1FQwZEvg54sLiCDGEUF0jADlefpy8sjw01KCiXRxmE3+V7vPj4NlgjFDXv+IQ7H0fus5xfJecMYTAnndE/CU0Gj2SepBTlOMiys1KcFV42cRfmgYdO/p23JjQGAB0dMqqXcWR5dXl9t+S0cX1rsaKODrLN9euynxcFGTJo1U7GQxs4q9wEX8JgiAIzYxmhMqjKnlESExz10YQBEEQhGYgoJ7uDTfcwHnnncfu3bv59NNP+fTTT9m1axfnn38+N9xwQ7DrKAiCIAiCIAiCIPhKTFbNwG8emP3IMtuOcHY4EOGX0GaJ6gboKhN5xdHmro0gtEi6xDnEizGhMfas7YIgCG2dkBAVCP3ii64OXyYTXHAB/Pab6LsFQRAaSr/UfvZlEX+5Jyu+rmVMt3gf3F1MkUrUNeFTOPFbGPSYe+GXjQ4TYdrvcNomOGk+nLoBTl0TmPDLRuaFSvgFYC6FhVNVMiYb5iJYdiEcWuBY1/N6CEsGnAajrFVQutdV+GWj+2XYwzmslcrxbP0jULQdCtbB8itgzV2Bf4Ymxu6OBWTGZQbtuGedpZ5nbGN8Fgu89x6cdhrMmqWEXw1F0zRSoxyij+PlxzlecRyrbsVsNZMeU/PZQhPUuGz5fiXQ8wVjOGTMVu5GAGvuVmJAq9m1nG6F7a9A3sqGfyBB8ED3hLoC3G4Jru3y8ePqb4cOEBrq23HjwuLsy6VVpS7bys2O9i8iJMJpS81vKLaPbyepyncsx/SAkFjf9vMFm6OYMdzVXUwQBEEQmhq9RpB86Me6z4uCIAiCILQLAhJ/7dy5kzvuuAOj0REQYTQauf3229m5c2fQKicIgiAIgiAIgiD4SXSWY+BX3L/c4tSVxSzj4kJbJSrTEYwgbYEguMXglAG6V1KvZqyJIAhC06NpcNNNkJMDy5fDwoVw8CC8/TakpDR37QRBEFo/fZMdLrN9kn0MXG9n1BYUeFoXNOL6KsFXfL/6y9ZHx2kQ5uQAU3EEvh8F34+GhafBZ50h50PXfULjYNQruDjTeCPrclf3J3MJbHgEvu4F3w1RrmG+HqsFoDllYOqd3Dtoxw0JgZdeck321Bg4i9fyyvLIK8vDolvQ0R3OX1FdAatyCao85vvBu57vEBNWHIafpypBoNXsCOo99CP8LomYhcbFnQC39rr8Go1V166+HzcmzOFM4s75y0ZkSKRjg01AGdvbt+B2c6FjObav53KBYPt9aqbGb2wEQRAEwRcOfBU8h0tBEARBEFoVAT0BDB06lM2bN9dZv3nzZgYPHtzQOgmCIAiCIAiCIAiBEu2UNfnwjyrYQHDBZHIsm80yXyu0UaKdAjOKt0kGQEHwQHx4PAA9Ens0b0UEQRCaCZMJRo2CiRNF9CUIghBMnAVfIv5yT1ZCXecvd+taJIYQyL4LFxcvgLwVcPBbMBc7F3YsZpwBvW70cmAN0iarxbBEyL637jlaMYkRiQD0TOoZ1OOeeSbMmOGa8Kk2hgbGxnaO64xWcy2Olx/nSOkR+za7MCyyiyMRT+ke3w+ePgVCHM5IFG6Er3rApqdg7/vw6yWwcLpDgCIIjYQvotzimuYtLc3340aHRmPU1A/UWewFUGGuQK8RsrqIv2zi1qgu2F3AvFFd4nTCrOA6dNmOpYljvCAIgtBCOPCV706zgiAIgiC0KQIa4rr55pu55ZZbeOaZZ1iyZAlLlizhmWee4bbbbuPWW29l3bp19pcgCIIgCIIgCILQhDiLvw7Oc80QLAAi/hLaCc7ir7wVkgFQEDzQMbojIOIvQRAEQRAEIbiI+Kt+fHGYadH0urlmHK6+/natoMxhL0KfO9WyZnL92+0SGPS4o2y/e2uED17O0YrECMmRyQD0TAyu+EvTlHvpgAHuBWAGA4wc2bBzpEWnYTKo63S8/DjHyo65bANqnL9qKN4JVh/FJ8Yw6HGN67WsOALr/gS/Xgy73w6ukEUQPOCuDc6Mz3R5bxN/xcXVKeqR6NBou/t6mbmW85e5HGtN8Hp0WHTdnSO7ONpIrzi1tdHdff/9+YLt92cw0ZocFwVBEIQ2iLFGKF15FA587TkJrCSHFQRBEIQ2iy895DrMmTMHgLvvvtvtNk3T0HUdTdOwWGQQShAEwVdMJhNnn322fTnY5QXfkWshCIIgtFoiMlSggG6BI7+AuRxMEW6LtsT7XVPUKTTUxEcfnY2uw3XX1b9PeHg4o0ePti83Rp0EIeiEpYAhHKwVkPtD/eIv3SoCsVZIIO1NS2yjmvN+NKLTCDYd28TgtMEtpk6CIAiCIAhC66d3cm/7ckqkWCu6e15Oi04j1BhKlaUKgNiwWOLC4zyWb3EYQ2HkK/DTKV4KGSBtiusqTYOhf4Osi2Hby1CyS43n9bwOkmsplIzhMPYD+PFEsFRSR0immSAiPRifpkm4YcQN3D3/bk7MPDHox05IgJ9/hssug88/V/9mUH8vuwyef75hx0+PTkdHx2QwkVeeR0FFgX2bW/FX6d4awYiP4ry+d8H2f9VyjXODZoScHDjmEJ+xebNrmdrvk5OhSxff6iG0a2q7fCWEJxAd6hBkWa1QVqPdio0Fi8W7456NqJAo+3KFucJlW3m1k/grNFq1/avvwKTVxJpFd/M4ZmnSLJyd9qF92U509+AmxbPWuO75JEITBEEQhODi0jc6shoOfaOeM7e+AJ1nud8nJIyzB+ZCr5tabn+qHtrK/Fdj017/TzKHJwhCeyagVmz37t3BrocgCIIAGAwG+vXr12jlBd+RayEIgiC0WgxGFTBSthcs5ZDzIWRe4Hay06BBv66Rrg5B3g7dBPe7prgHGwwGtm7th9kMeXn1lzeZTEydOrVR6yQIQUfTVHbw4m1QvB3K9kFkZ8/ldR20pqueEBwCbQNbWhvVnP2vN2e9yZuz3mxRdRIEQRAEQRBaP86CL02Tzpa752VN0+gc25md+TsBV3eZVvN8nXYSjP4vLL8M1al2coTRjJAyDgY87H7f+AEw8j/1nyN5FJz4AyycDuYylACs5lxRXWHkaw39FE3GzaNu5uZRNzfa8ePj4bPPYNMmJQQzGmH6dOjatd5d6yUtOg2z1UyIIYS8sjyKq5RIKzIkkqjQGmFLRLoSh+hmKNlZ4xLkI+HJMOgxWHWL93LHLNC7N1RUeC5z0UW1jh0OW7eKAEyol5TIFMJN4XaBVm3Xr5ISNYQIyvnLavVN/OUsIKs0V7psKzeXO8qFR6u2f8dWKK0Ru0Z09Hhcg2alX8ymuhtiezkUoE1BWLIjCZcz0VlNVwdBEAShzeLSNwqfCblfquUjC2HL36H3ra5CaV3HsPER+oX/Bq2hT+WBtjL/1di01/+TzOEJgtCeCUj81dXL6JjN8UsQBEEQBEEQBEFoJlLHwd4DKtBg15uQdYmHgjrs/wL63NqElWsZmExgNkNurloWhDZJTE8l/gLY8x70ucNz4JHBx0zUgiAIgiAIgiAIQr1omkZyZDIdYzwHrQvQK6mXXfzVK7FXM9cmQLIuhZBYWH0XlO5S6wyh0OMaGPwEmOp3ka+X1HEwKwe2vgSHfwRDGHQ9H7rNDa67TRshO1u9gkl6jHJYs+gWDpUcsjsVpUalOgppBghPg/L9cHSx/w7rPa+DA1+ra6xb3ZdJvgQqbvXvuBUVyilMxF9CPWiaRpe4LmzLU+OJvZJc2+XCQsdybKxDCFYf0aHRWKzKmau0upTFexfbtx0sPqjOjeYQUppr7MU0A4TG+/spIDLI33WtZtxUt7jfHtUFTt8KlcegPBeqCpTwK2VMcOshCIIgCB1PdX2/9l5IHA6pE8BarfoGB7+DjY9D/KDmqaMgCIIgCI1KQCFuc+fO5V//+hfR0dEu6/fs2cPcuXNZvHixhz0FQRAEb1itVjZv3gxA3759MRi8Twr4W17wHbkWgiAIQqsmfTrseVctH1kIez+Azme5ij6sZqyFW9m8eiFYJreY+11T3IOtVivDhm0mPx8OHqx/H7PZzI8//gjAySefjKketZg8FwgthviBkPu9EoLueRey73FfTrdAwUZIGNi09RMaTKBtYEtro1pi/6sl1kkQBEEQBEFoXRy962hzV6HF4Ol5uXtCd3uZrISsesu3WDqfCZ3OgLzlSrQQPxAiOgT3HKEJMOAh9RKanLToNACsupXDJYft6zvFdHItGN1Nib+KtkLFUQhPwWcMITDhc/hpChxbit3hzeYmNuwFKB3X4M8iCN7omdjTLv7qFt/NZVtRkWM5Ls73Y+7K34UVJWisslQx4c0Jdcro6Ow8tpONGzdCfgZ9I45hCE9xCK/cYNUNbC7pA0Df6C0YNKtyCjOG+l45X7AlzdLNnstEdVEvQRAEQQgydfpGicPh+CpAV4KvBZOg20WQMBiOrYCcD9U98nhH2LixdfSn3NBW5r8am/b6f5I5PEEQ2jMBtWCbNm1iwIABLF261L7urbfeYtCgQXToEORBTEEQhHaE2Wzm448/5uOPP8Zs9jJ4GGB5wXfkWgiCIAitmvQpqOCAGn67FiqPqAFgAKsZdCvmxRfy8fYhLep+1xT3YLPZzOTJH3PuuR9z5Ej9+1RUVLB8+XKWL19ORUVFo9RJEBqF9MmOoISC9bD/K/X7r41mhB2vNG3dhKAQaBvY0tqoltj/aol1atHk5MDq1Y5XzSSanc2bXbfn5DRPPQVBEARBEIRmwdPzcreEbm6XW+XztcEIKWNVXzzYwi+h2UmPTrcvHy5ziL8yYjNcC0ZnKbEWQO48x3isO9xtM0XCKb/AmLchYQhEdYVOM2H6H9D75oZ8BEHwCWchrnO7DK7OX3FxYPSsy3LB4skxyw0ff/wxHx+YiVk3Kic9L5h1Ix8fOpePD52rygNEpHvdJyBcnL80r0UFQRAEIdjU6RtlXVarhA67/w9W3wE5H6p9dCMf7xjRuvpTtWgr81+NTXv9P8kcniAI7ZmAnL9WrFjBn/70J0466STuuOMOtm/fzrx583jhhRe4/PLLg11HQRAEQRAEQRAEwR/CU1R2r/w16n11AcyfACP/Ax0mQfF2+O1qKNoEzG6+erYAcnObuwaC0IgknwCGcLDWiBZ/uwpmbIaQONBq8gFZLbDzdTi2rPnqKQhC6yYnB3r3Bm8C6Ysucn0fHg5bt0IXyYotCIIgCILQnnF2lantMCMILYnUqFT78vGy4wBoaHZHMDtRXR3L+z6BbnM9H9QQ4mG9Ue3nbV9BaCS8tcuBir/iwnyzCYsyRbmuCERI2yjir5rQOqsZNBF/CYIgCM1Mt7nwx/1QXVh/WUEQBEEQ2hwBib9MJhNPPvkkYWFhPProo5hMJn755RfGjBkT7PoJgiAIgiAIgiAIgdD1fMj/A7Cq9yU74adTahXyEGDQjjhyBKxWMATkiy0ILRxjGKROgEMLACtUHIalc2DchxASq8oc+xXW3AExPZu1qoIgtGKOHfMu/HJHRYXaT8RfgiAIgiAI7RpnhxnnZUFoaYQYQ4gPj6egooDCSkegbR3xV3x/hwt77vdgLlNuXu6oKoDQ+EapryAEiidHRoCiIsdyYqLvx4wPj/epXGRIrd9KPc5frhgc++h6cEVadvFXleM8giAIgtBchMRAvwdg7T2A3ty1EQRBEAShiQmoV1pdXc0dd9zBU089xX333ceYMWOYPXs23377bbDrJwiCIAiCIAiCIARC1/ObuwatAosF8vObuxaC0IhkzMRl8if3e/iqF6y4GhbNggUTwFzSXLUTBEEQBEEQBEEQ2jHOwoIucZIYQGjZpEUpIUq5uRwAHZ306FouQ6kTHcuWCtjyd9CtdQ+mW2HXm41UU0EIHGe3r9rtsrPzV3y878dMjPBNKRYTFuO6IjxNuW35gk3sFZEOerXvlfMFQ434q/KoOH8JgiAILYNe16v7pObBhtPTekEQBEEQWj0Bib+GDx/Ol19+ycKFC3n88cdZuHAht912G2eeeSbXX399sOsoCIIgCIIgCIIg+EtUF8i8wJGVUvBIbm5z10AQGpHOZ9VdV3EYdr4K+79AsgIKgiAIgiAIgiAIzUVsWKx9OcwU1ow1EYT66RTbCQCrk5irjvNXeCrE9HK83/AYlOx2FbBYzVCwAfa825jVFYSAcBblhhpDXbYVFoKxJpY8Nhaf8Vn8FVpL/BXRwb140i01oqzwlOAPd9rmWCqOBPnAgiAIghAgpiiY9JUHkZcGBulbCYIgCEJbJWDx19q1axk9ejQAmqZxzz33sHz5chYtWhTUCgqCIAiCIAiCIAgB0u8+0H3MjNmO2boVzPJvEtoqEWnQaaYIQQVBEARBEARBEARBEBqATfzlTHpMet2CaZMd4zDWSvj1YvXXalYvcwksvwR0SyPXWBD8x1mUW5vSUjDURJnFxHgsVofkyGSfytVx/gpN9N9pKyw5+G4n4Snqr4i/BEEQhJZE4jAY9yGYYtW9z/YKTYCx/2vu2gmCIAiC0EgEJP56/fXXiYqKqrN+8ODBrFq1qsGVEgRBEARBEARBEIJAXDZ0vwqPXb9gT4K2Un77rblrIAiNjE9C0ICGiARBEARBEARBEAShQWy5YQs7btrR3NUQhHpJi0qru6628xdA+mTXcZhjy+DrbNj2Imx5Dr7Jhvy1gVUiORnCw/3bJzxc7ScIPmLSTHSM6VhnvaVGr6hpEBnp+/FSolJ8KhcfHl+rIlH+z2GEpYIh2OKvNFWPisPBPa4gCIIgNJSMM+CMXZB9L3Q9H/r9CWbugrSTmrtmgiAIgiA0En6lff7www+ZNWsWoaHK2nvPnj107twZY42vd1lZGS+//DJ333138GsqCILQDjAajZxxxhn25WCXF3xHroUgCILQZhj2AhxbDkWbamWTNWAMieSM6RMhNL7F3O+a4h5sNBo56aQzuPlmsFiM/PYbmLz0jkNDQxk0aAgGA/b+cLDrJAiNSvIoSBmvgo08ZpW2NmmVhOAQaBvY0tqoltj/aol1EgRBEARBEITWirfn5d7Jvf0qLwjNRW2XL4NmcO9olHYKGELBWuVYV5YDq+9oeCW6dIGtW+HYMdf1ublQUADx8ZBey40sOVntJwg+Uv1Qtdv1NvFXdLTDAcwXkiN8Ex8mRCZw4sQk2PIcRs0CphjQPJ/IqFk4o8PnNcs1gsuIDr5XzFfCUwEDVBeCtRoMIcE/hyAIgiB4oN6+UVgSDHrMdR+LpdX3p9rK/Fdj017/TzKHJwhCe0bTdV33tbDRaCQ3N5fU1FQAYmNjWbt2LVlZWQAcPnyYjh07YrGIPX0gFBUVERcXR2FhIbGxnq3UBUEQBEEQBEEQ/KI0B5ZdBEcXg2ZS4o/obnDCe0oU0g6xWiEsDMxmiImB/HyQcT6hTVO0Fb4bApbyuts0I/S6EYY93+TVEgShDbB6NQwb5v9+q1bB0KHBr48gCIIgCIIgCEIj8L8N/2POJ3Ps71MiUzhy1xH3hRefA/s/85KEB0gYAtNXB7mWgtB43Hsv/P3vkJoK+/f7vl+VuYqwx8PqLffmGW9ySWIULDlHrZi8BFLGui98fDXMcx6L0AAdzjxcI9aqp/y0VZBYMybhblzDecxi01PwxwPq93zmIQhvBIGZIAiCIAiCIAiC0CZobD2QH7lYoLZOzA/dWIPJz89n7ty5xMXFERcXx9y5cykoKPC6j67rPPzww3Ts2JGIiAgmTZrExo0bXcpUVlZy0003kZycTFRUFDNnzmR/rVEKX859yy23MGzYMMLCwhg8eHAQPrEgCIIgCIIgCEKQiOoCp/wC4z6Gfg/AyH/DaZvarfALVGbS5JqEo8XFsGYNNGEXVxCantjeMOq1mjdOw0GaESLSYeAjzVItQRAEQRAEQRAEQRCE1kB6tKujVm0nMBf63Opd+CUIrRCrVf0NDfVvv1CTbzskRSSBudSxwhTjx1lqBvdD4/3Yx0fCOzh+zxUeBJ+CIAiCIAiCIAiC0AT4Jf5qTi644ALWrl3LvHnzmDdvHmvXrmXu3Lle93n66af5+9//zssvv8zKlStJS0tj8uTJFBcX28vceuutfPbZZ/zvf/9jyZIllJSUMGPGDBf3Ml/Ores6l19+Oeedd15wP7ggCO0Kq9XKtm3b2LZtG1bb6GkQywu+I9dCEARBaHNoGnQ5CwY+DD2uBmNYi7zfNUWdbPsMGbINg0Ht8+234MnE2mw28+mnP/Pzzz9jNpsbpU6C0CRkXgAnfg+RHR3rOp+tMt2GiAN5a6QhbWBLaqPa6/1IEARBEARBENoL8nwttAXSotNc3mfEZngunHwCxA/Ca0iOZgxOxQShibCNnxsD+OpqaPWWSYpIYtve42wr7YVVN0BItNfyVt3AttKebCvtqcqbosHgpzLNF8KcnMTKDwb/+IIgCILghbYyD+Qv7fVz+0t7/T/JGIMgCO2ZViH+2rx5M/PmzeO1115jzJgxjBkzhldffZWvv/6arVu3ut1H13Wef/55HnjgAc4880z69+/PW2+9RVlZGe+99x4AhYWFvP766zz77LOccsopDBk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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#[15,17,19,22,27,45,49,60,68,72]\n", + "id_ = 22\n", + "st = 80\n", + "end = 350\n", + "\n", + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}\n", + "start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + "\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(43,ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 17)\n", + "\n", + "for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + " print(i,end=\",\")\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 17)\n", + "\n", + "for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + " \n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/evolution_from_scratch/EFS4_deepexplainer_mut0_mut15_st80_end350.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "8764a750-8ba7-4ae4-a3ac-bb2b52801760", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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gKWL6K7ls2TJNmTJFn3zySdtzTz75pL7zne9o4MCBcQsOAOAcOyeWRKbla4aKJehh3nknfBDU+PHS119Lp58u7bef9LvfSW+8YW7C9XQ+n08vvviiXnzxRfkiHPkVyzZO49b9jkW0++3W44TIpKLt7fDu0A6fqR3tsTwaWhBMLNmyY0uX25ZsL4lLTLSLyDnx2CYjJifuN4D4SMf2PXNmx9VIuk3S6E5pqTRhgjR1avi/E0+UzjvP/DvxxPavT5hgto2AZQVvzNbVRXBNl5EjebLNsne75HFgGZaerP5btZWBGXSUqUrSldz+CQ8pGunYvp3Cicc2Hc4J6QtBT7dokbRqVXhSyahR0l/+YiqZHHzwThtsejM4a+/Yn0l5I9t/l3sypd5DpeGnJTDy1Kmqkg45RHriieBkYbYtPf209H//J23d2uXmAAAAAJKo9bI7qkrQdWuDy0WTpKKJ7auVtLGkIcfFGp4j0LeRRP4maeFV6rqMN7NMA+kopsSS+fPn6+yzz9bhhx+u3/72tzrzzDN12WWX6b777tOLL74Y7xgBAA4QmliyfXuEA+qtllEl3Q0MABzmzTeDF+vZ2dILL0hZWeafZGa4Peooafr01MUIAIhMZUNl23J+dr6Kc4vbHtc117VVJenI6q3BSiW+AB2NAAAEAtIzz4Qn4h90kLR4sXlu6VIzeDEmVVVSY2P02zU2tq9y0oW8PPOztQhKtzJbqnY3RzzLBiLVUGpmkpfMbIlWN3fN7e7K5wIA0tlrr4Unsn73u9KKFdJFF0nnny998on0q1+1vBjwSdu/Dq48+nx1PuDFkoaemKCoU8fnk447Tlq3Lrwyt2Qer18vXXJJamIDAAAA0F7reXtUE/iEVgQeepK5FuqM5THJJ0AkVv9VatggkkcA94lpirXMzEz94Q9/UE5Ojm6//XZlZmZq9uzZOuigg+IdHwDAIfLyzGD6QMBULIkoQ97KkGyv1Lw9PUo7wBUCAVONpHWg1NVXS3vu2fHF+513Sqel52R2AJA2KuuDiSWFOYXKycxRTkaOmvxNkqSqhioNKRjS4bartqxqWy6tLtWYPmMSGywAAA73+efSlpCCXxMnSu+9F0zCHz9emjXLVHp0qvx8afNmadOmCDfIKpKat5qKJYiv+m9NldvMAql4Svd9R3agixkXAQDp7rXXggOt+vWTXnzR9NmG3qu4917pZz+TtGOjpJaExLyRUr/9O39jyyMVTkhU2Cnz2GPSF190/rrPZyrAAAAAAD2Gr0Fa/Tep4kMzQcnwH0gjzpI8u1pK2Rm8LXP2ZmaacSueSLrB6kskK8uMzRp0FGOzEB92QFr2R5FUArhTTIklXq9X1113nR566CHNmDFDc+bM0WmnnabHH39cxx9/fLxjBAA4gGWZwRc1NSaxJLKKJS1XOc1bg9VLAIdbvTo42a1lSb/8ZeczQliWdNJJyYsNABC90IolfXL7SJIKcgrU1GASSyrrKztPLNkaHGGxassqEkucbtGi8BFFZWXB6eiLi6XBg8PX799fGjEiScEBQHr4z3/M9ZHfL/XuLb3yivnT2/rnNzNTsm3z/E9+ktpYO1NYaH5u3BjhBtnFUr06rliS01/y5EqBGCqtQKpbKykgFYyLrN/IE9PtDABAGigvN5d8rf7yF3NJt/MEWJYl3XWXpLp1wScHH9t9cqLtT6t7GNu2Sddf3/16NmOEAAAA0FNs+UL64Fgz/kiSZEnrX5SW3Cod+aHUa1Aqo4uL1slPI5rot1X9t5ICkidb2u3/ur+uCXglT1asIcItKmZLOzaEPzf8B9Kka02F7zUzpW8eTE1sABIupjsx06ZNU0NDgz788EMdeOCBsm1bd999t37wgx/oZz/7mR5++OF4xwkAcIDCwmBiSUQ8WZJfLYklzp5R8uuKr9Xsa9a+Q/ZNdShIsdWrg8uHHioNG9b5uhkZ0imnJD4mAEDsQiuW9O3VV5JUlFOkqgaTRRiaeLKzb7Z807a8eutqHaNjEhQl4uL//i84nVMkcnOllStJLgGAKLz6anCm8Isuknbfvf3MeVlZ0qhR0llnJTu6yBQXm59VVeZrI6u7+6g5/czPjiqW5I2QTlopNVVJ1culuedJBZKyJEXxlaTcXDM61m3qS8zPPL6LAQBd+/DD4PKAAdKZZ3Y82CozUxoyRNLakuCTg4+OILHEltJoYt/HHjP3cgAAAIC0sHWh9N7hkr9BwQoKLT/r1kjzfyEd9kaqokut2jUmUb5wDykjp/v1SSpBJEpfMlWB7JZsp/G/kqY9IAX85tp6nz9K/faTlt0dv8/01rRUJJptPnvYKdLIc6WM7Ph9BoCIxJxY8sADDygvL0+SZFmWrr32Wh1zzDE677zz4hogAMA5ioqkDRuiSCzJLpa81VLTlkSGFRdTHpkiSbJvZoout1uzxgyMCgSkU0/teqCRZUmDev7EFwCQ1iobKpVhZShgB9oSS1orl0jhiSc7W1G1om05tHoJ0kRjoxlVTGIJAESkuVlavjz4+OKLO1/XsqTTT098TLEoKjI/bVvavLnryQQkSdl9JHmk5u0dv543Ijwxor+keyRNeVoqmmieW75cCu03f/ppaeLEkG1cWEXL32QSciQpb2TazRQPAIivVatM0ojPZ75Su6qo7vVKWXXrJCtLsr3SgMO6r3qVRlWxbFt65BHTv91qjz2k22+X9ttP+vJL6YYbpKVLUxejk82bJ338sfl9O/54acKEVEcEAADgcv4mac6ZJqnE9rd/3fZJjRXJjysBWpPnWyuXRKRurfmZNzLu8cCl7ICpBtSaVDLge9LU+8yyp7X/1pJGniM1lMXnMzd/KM0+WfLVySSNeaQNr0hf3SQdOVvKHxWfzwEQkZh6yWbOnNnh83vvvbcWLFiwSwEBAJyrT8sYzMgTS/qZsotNW7tf1yEafY3KzcxNdRhIoTVrTCWSQEA66aTuZ6/1+aIsRQoASKrK+kp5LI8sy1JxbrEkqV9vM/O4x/J0WrGk2d+sjbUb2x6HVi8BAMCN1q0LDlDcd19p/PjO1/V4pKFDkxNXtAoKzDWf3y+tXx9BYklWsZmFzRvFtN/9JX1notS3k6qoEyeag+hmDRuCy71HmNnuMkgsAQB0LLTK9BlndJ1YkpUlqW6dpICUmS/l9N3lzw8EzGd29blOsXCh9O23wccTJkiffWYKpGVlmYouRx0lHXBA6mJ0opISU3Hv88/NKYltS9OnS6edJj35pDmHBAAAQAos+0PL+X0Xk8Ta0WRiOFfruBO/v32V6A4FfFLjZrOcN6r7So1AJLYuCP5eSdIBf+t83QmX7frnlb8rfXiC+X1ua+ctNyJ2bJLm/1w64r1d/xwAEYtqGOS///1vnXrqqcrONuWFSkpKNHz4cGW03PBpaGjQgw8+qGuuuSb+kQIAUq5vy/2XrRHmidi5A031+GZnJ5ZU1AdnL1hRtUJ7D9o7dcEg5VavNskigwdLY8d2v35EF/QOlpGRoVNOOaVtOVHbOI1b9zsW0e63W48TIpOKtjf729nyBUyH8ieln+jsF8/WssplkiTbtvX+uvd1+QGXt9uuZHuJAnZwes/Q6iW0i8SJ6djuvbd0yy3K8HcwU1WqYkrw7zm/U0DPkU7tO3RA58knd59k31X1x1TKzzfXcX6/VFoq7b9/N/kM2cVmFGnAK/l2SJm9khVqeqsPGfGaN7JHVitJp/btNE48tulwTkhfCHqylSvNuUffviYhots+2brVZjbjvFExf6ZtS//+t3TffSYxw+ORjj1Wuvpq6bDDYn7bhHvhhWASbZ8+0ltvBZNKJPPTsszzP/lJamN1iqVLpe9/X9q2zTwO7V54/XXpF7+Qnn8+NbEBAAC4WtMWaemd6jKpJI1EXbGkYYPaBuDnjTQD8zOyExGaY9C3kQRbPpNkSbJNBdCC3Ttfd1cTmZq2SHPOMX3vHbVz2xfdhE8A4iKqxJJzzz1XZWVlGjBggCRpr7320qJFizRmzBhJUm1trWbMmEFiCQCkqaIic0Ni8+bIBojYWf1kWRnmRNDBllYsDVsmscTdVq40Nw27mn03VDokluy9994J38Zp3LrfsYh2v916nBCZVLS9NVvXyG7piFq1dZVWb1vdljBiy9bKLSs73G7VllVhj0urS+UL+JTpyaRdJFBMx3b4cGnRImfFlODfc36ngJ4jndr36tXm+icQkE49tftrIadWdgydbXr9ejNwsMv7iVlF5iJRkpq3kVgSL43BST5UMFby9LybuunUvp3Gicc2Hc4J6QtBT7aq5RL90EMj7I+tW2t+5o+O6fO8Xunii6XHHzefZ9vmnOHtt6X//ld65BHpooucWcHkueeCiRHTp5vqbDufl2VmSoMGST/+cfLjc5qGBpM0vXVreEJJK7/fVO4DAABACqyZ2TLgvEVWoTTxGmn0+ZJ/h7TqEembB2N//9JSqaoq/LmyMmn7dqm42MxGGqp/f2nEiNg/T+a+5bi/jNMJu5+gN374RthrrX2UEc+jFjZxy6geOXFLtOjbSIKabyQrU7K90tifmTbo6WyA4C4OmFpwpeTdrq4rEiVmYkEAnYvq9p5t210+BgCkt+Li4KyeGzdKo0Z1vb6d3VeSR/LVSgF/+CCBnP6SJ1cKNLbfMLs4fkFHYGnl0g6X4T6BgOk7kEy1Ett25s1BAEDk6prr2pZt2e2uY6sbqzvcbvXW1WGP/bZfpdWlGtNnTPyDBACgB1i92tzctCxpzz27H9QZ9bVU//5mOu3GDvoJupKba7aNUEFBME+kpKTrBBifT8rMLg7evKpbK/UeEl186JgdMiig967dkAcApLfa2mAV9d13775qmvxNwQTG/NHmezzKAVa/+IX0z3+a5UCwmGnbzMGPPWYST5ympkb6tmVsWW6udOmlnR+rzEzp9NOTF5tTXX+9OScM/X/eWcQzRgMAACB+bNsklrRW5MjoJR32ltRvP8mTKdkBad8/ScXfkb75S/TvX1oqTZgQXV9kbq6ZqXQXkks+3/S5JOmDkg/avdY6uW/EITWWB5d76MQtcKCaFabv1sqUhp3SRVKJdm1AVfVyqeSfO7+hVDTRXNfXrYn9vQHsEofOGwcAcKKiouDymjXSyJFdnyNm9OoXfOCtlnL6Bh/njZBOWik1VZmTxbnnBV/rtVPWf4KFViz5uuLrpH42nKWsTGpuNstjx5qZ6bLTu1KoAoGAVq82g6fHjRsnTwRT/sWyjdO4db9jEe1+u/U4ITKpaHtN/qYuX69tru3w+VVbV7V/bssqjekzhnaRQDEd282bpd1317g1a+TpaiRIMmNK8O85v1NAz5FO7fubb8w10pgxCapGMmKEuTEbOkvg8uXSeeeFr/f009LEicHHUc4UWFAQHDi4bl3XCTK2LVOxpHXGtLrVUv8Dur6ZhsiEzjaZmZ+6OHZBOrVvp3HisU2Hc0L6QtBTrQkZSzJuXNcJAJKkHWVq++7OG20mveqyPFm4556Tnnoq6jAdYWVIUdYTTpD69Ol6/fye+RUcN2vXSg880P53avhwqalJqqjoeLtdtWSJObfOzzdVeHpREA8AAKC9bQul2m+Cj7/7nNR//2DSuNVyfTr2p+H9TJGqqop+gpvGRunjj8P7JqOscLJk8xJJUoO3od3bt/a5RnweGmgOLueNinCj1KhurNb3nvierjr4Kp2/1/kxvw99G0lQvcz83O3/TJWgRPnmLy2VUVoy+fsfLB34D6lwvHlc+an06Y8S9/kAOsVfSQBAxIqKgh3sa9aYASVdyu4bnNWzeWv71/NGSH33NdnGKbR48+LgcvniLtZEugu9STlmTPcz8KYDn8+nZ599Vs8++6x8EU69Fss2TuPW/Y5FtPvt1uOEyKSi7fm7KY/b6O2403jllpXtnmtNNqFdJE5Mx/azz/Tsj34kXxQDhSRFPMN9Mv6/+Z0C0lc6te8VK8zPceMS+CEjRkj77hv8N7GD/oKJE8PXiXKGwNDEkjXdTHqWmanwqqp166L6LHQh9Ia/1TPnv0qn9u00Tjy26XBOSF8IeqrQ7+vx4yOYCMgfcp2fN8rMZhyhmhpTiaSnVrFevjy4fNZZ3d/DcXuz/vOfw+8BTJsmffmlmbx682bpnXdMkkm8fPyxNGWKtNde0hlnSMceKw0cKN1wA/8XAAAA7ZS+FOwz2u0QadjJnVciHPvT5MV13nnS1KnBfyeeaJ478cTw56dONRVRSkvDNv9q81dty3ZrWeUWOTnm5+bNEcbSgyZumVM6R4s3L9av/verXXof+jYSzN8k7dholounBMf8xZtvh7Tun8Gkkn77SYe/I+WPDa7Tb3/pyNlS7sDExACgU1HfsXn77bdV1DJlfSAQ0Hvvvaevvzazu2/fvj2uwQEAnKWoSPK3nDOWlERwcyWnr9rKUjZtkQoSOfokNrZth1UpWV+zXg3eBvXO6p3CqJAqmzYFlydMSNAsvACApKlprOl2HZ/dcQfiyiqTWJJhZchv+2XJ0uqtq+MaH+Jszpzgl3cCZrgHADfzeqUNG8xy60zhPTURP7Qa6+rVpmplZwNULUstFUta1JdQrSReAl5JliRb8kSZHAoAcJXVq03BEb/fJJZ0K3TW3twBwZmMI/DII1JtbUvVMkkDBkjXXy+dfrqZnPipp6S7744u/mRasULKyjLnbscdZ5a74ub+7x07pH/8I5jQsf/+0nvvmTkoWh12mEkG+eUvd/3zHn1UuvTS9s/X1kp33GHuTTz++K5/DgAAQNrYtig4qH3SdaYvqdN+OYdmhjc2msooIfeiviz/sm352+pvNap4VNvjAQNMn2vkFUt6zsQti8oXSZKqm6pTGwi6VrdGbRVAC8ebNthZQteu2PCK5Kszy5n50mFvSp6c8H5iT6bUa7C0773x/3wAXYr6G+UnP/lJ2OOLLroo7LHVU6dwAQB0K3Twxbp13d+U8Hr6qm2VHZsSd8K5C8rrylXbXNv22Jat5ZXLNXXI1BRGhVRpDrnnOHp06uIAAMRHR1VHOtLQ3KDe2cGk0mZ/szbWmtlYduu9m8rry2XL1jdbvunsLeAEe+/d9dS1rTPcAwCitnFjsMrHuHFmAF63s4U71ODBwWW/X1q2zHyFdMTvlzKoWJIYtk+S1XU/UX2p1FQl7SiTmreb5/LHSLsdlIwIAQAOUVlpBldlZkqDBkWwgR0yuCojJ+LP8fulBx4InvMMGybNnm3GgLUmYNx0k3T44dJvfxt5/GFKS83AslBlZdL27VJxcfiJihT1hAjLl5v9GDTIVGlD5156ySR1SFJhofT22yapJDTZJitLGjJEuu++XfusN9+ULrkkmLC0M9uWlizpZGNfg7Tpf1LFbDNwsM/e0vDTpdzddi0oAK5QXi698IK0cKH5+3boodIpp5i/e9gFti1VzpG+fV6qWy1lFkhDjpOG/yC86imAXbNtkSRbyh0kDTm264TxKKoUplKjr7Ht/qNkki12TizJyJC2bTPJ4t2NyepJE7eEJtTYtp2QMcZLNi/RI188ohn/N0PDi+JYetBNakLurRdOlKwETbJU/q5JhrJ90vjLzPdnR/3EniypaFJiYgDQqai+VQOtPWkAAFcKTSz5JoJxlRXV/TS09UHtKingN1dBDrK0cmmHz5FY4k7ekHuOvSlaAwA9XqQVRlZvW629Bu7V9njdtnUK2Ob6d3jRcJXXl0uSllcuj3+QAAD0ADt2BJd3371nz249dGj444ULpT337PhG7caN0oh+IZ0hdVQvi5u2wQCd3HOoL5X+M0EKNLZ/7ahPSS4BABdpnQxo2LAIK6b5Q2YP8kSeCfvmm8GK1jk50kcfmc8MPe/JyJC++90Yq5aUlpoy2Y0dfLd1JjdXWrky4uSSJUtMYswee8QQn8vMmmX+b30+afp0k4jT0e2rrCzz3xarsjLp7LNNJbzOEkskkxDUzsY3pLk/kZq3Bgd02T7pi19JU/8i7X5RS4k9AAjn90v33GOqbgUCwb9vf/+7lJ8v/etf0kknpTbGHquxUpr3M2nTG8EBsfJI61+UvvyNdMiL0sDvpzpKoOfz1kiNZWZ5xJlqq6DQwy2rXBb2eHH5Yp26x6ltjwcODJ4zbt1qHnepB03c8vmmz9uWN9RsSEjix4X/uVDzN85Xdka27j/2/ri/vyvUfmN+n2x/S2JJgq43ti4wv79WhrTH9K5/hwO+HpM8BqSLyGv/AgBcr7g4uNxdYonfL63b2Df4RM3KLspSps7Sig4SSzp4Du7Q3By8LurJA6UAAEbJ9pKI1lu1ZVXY49aEFEuWxvUdp95ZJttwfc16+QK+uMYIAEBPEFrdsX//CAd1OtTOE4EvXtzx/vh8pppJ2GyjO8okb10iw3MPK1OSLdmdJJY0VXWcVCJJdWsTFhYAwHlaz0N69YpwAzvkut3qpJO3vlTautD82/hfad0zeu35zW19wpdcIo0c2XHiaWamSS6JWlVVdEklkll/5wonnfB6pZISszxxYrDyCjr2+efmfC8nR7r88q7nROsw6SNCN90kNTQE/z9GjpT++Efpk0+kl1+WTj65kw1X3C/NPik4+M/2tlTjsc3v+JrH3JFUYndxvrjzelsXSktuN4k3S26TtnzRdTYPkKYCAemHP5Suu878/bJt8/fO1/L1WF8v3XxzamPssRorpbf3k8reNI/bzjla/k41b5cWXpWKyID0sz1kzE6//RLznd6/v0nkTqJF5YvCHodW8ZBMIknr3+uKigjeMNKJW96aKs0+UZp7nvk362Cpcm5Use+KRl+jSqtL2x4vKFuQkM9pvS/c0QTDiFBjhfm9yugl9R6SmM8I+KSalskcBx/bfTVGkkqApIu51a1cuVJ/+ctftHz5clmWpT322EOXXXaZ9mAKFABIW6EVS+rqpPXrpeGdJJHbtrRyXV/9X+s2tSsd2cnd0QXF1xVfpyASOIHXa35NLatnD5QCABjra9ZHtN7OCSirtq6Sx/Iow8rQ0IKhGpQ/SGu3rZXf9uvb7d9qeD7lkwEA7hKaWJKTk7o44iE7W+rb18z6J0lfftn5QMKVK6Vjj8mXZKltZsTalVJfqpzuMk+W2o5pwOvIyUgAAM7g9Zr7DR0leXQobKbTDgZYdVIVa/7sRfL5BiozU5oxo+vbGT6f8yYm2rAhmACxxx4mxuzIC7a4SlNTcPK0U0+V+vTpev2ukk66smmT9MQTwf+XQw6RXn9dysszv88+n3TaadJf/iI99VTIhutflhZOb3ngwgyhgE9a83dp3dPSlnkmsaRwgjTiLDObcXZR+Pq1a6R5P5UqP25p/x5JAWnJzVL/g6SDnpEKRqdiT4CU+O1vpX//u/PXybeKkb9Z+vAEqWGDmcW9Qy78mw0kSnXImJ0++yZmYPmIEabzLzSRe/ly6bzzgo+fftpkbXf0WgwWly8Oe7xzgsWAAcHljRulyZO7GWbV2r/Wmoxr7TTIpbuJW5JUteSrzV+FPV6waUFYpZZ42Vy/WZL0ZdmX3azpblVV0sMPm0T3deuk3r2lY46RfvpT6Xt5LTcCeg9LXAC135j+YEkacqwUaI6q2iiAxIvpW/fFF1/Uueeeq2nTpumgg8wXzLx58zRlyhT961//0plnnhnXIAEAzjBoUPjjTz6Rzjij4xsomZnSl18XSd9t6cCt6abESYos3hy8cMuwMuS3/WHPwV1aZw0jqQQA0sOm2k0RrRc6S45kKpa0nhcMKxymUcWjtHbb2rbXSCwBorRtsbTqUWnTG1LTFim7jzT0RGncRVLffVMdHYAIhCaWpMMAxaFDg4kl8+aZWaR79w5fJzPTvHbFFR4pq0Dy1pgXquZJxVO42bWrQhNJSCyBk9i2VLNCKntHaqqUcvpLg46Seo1LdWSAazU3m6YZ8TlI6HeKv7n96x0Mrmr2ZWn5xkmSTKLBbt1MmOq0pBJJ2rEjuDxhQhSJOC60bFkw2ePII03yUkzHq2qetO4p853hq5fyRkrDTpbG/j8pt7/+/OfgAO4pU6T33jMDA1t/f1p/XnppyO9cY6U096fhn1OwuzTge1JGjrT1S6nq0xiC7SFq10gfny5tX6yw5O6aFdLS30sb/iMd93kwgWzLF9K73zOD0aSWwd4hA763fC7N/ZF0dBofMyDEp59Kd90V/twhh0hTp5q/dbNnS18zv2JsVvxJ2vqF2v4uWZnSmAuk/LGmv2D9S2agLID42L5EsrIkBaTC3RP3OSNGmH+dmThR2rflHkZrhZNoqhDm5prtWuycSLKhZoOqG6tVlGsSZwcODL5WXm4Skbs8T7VCJm6xfZLlzP7KBZvC9/uzTZ/F/TMq6yvblrfs2CKv36usDC6Kdvbyy9IvfiHV1ASviWpqpGeekZ58Uvr0/mYdOECyMhJYzWdbSKJRn31bfo8BOElM3V7XXHONZsyYodtuuy3s+ZtvvlnXXnstiSUAkKaKi6X8fFOtRJLmz5e6+pO/5GuPdFiB5K02N2Kbq9vPJJRCtm1rWeUySVJ2RrYG9B6gDbUbtLF2o+qa65SfnZ/iCJFs2dnBktBukZGRoeOOO65tOVHbOI1b9zsW0e63W48TIpPstldRH0mdaGlj7cawxyu3rJS3ZaaUoYVDNbxwuDKsDAXsgFZtXaUjRx/Zs9rFprelkqel8vckf4PUe7g09ARp90ukvC46zFPAiX9zkhGTE/c7LgJ+afEMafk9ZtCH3XKStWOHtOZxafXfpMm3SFNudGR1QyAe0qV9B0Im3UyHRPyRI81gGts2g2vefls66aTwQaKbN5tJCyWZ787qloqnVXOl8ZcmPea0E3rDsLFCyh+VslBilS7t24lSdmyrl0mf/VKq/EiSp+X8xS8poIy+B+u4718n5Q7sseeE9IWgp/J4zOVCINJJwMOSFztILOnA0g17yhcw2x1zzC4kGqRQU1NwuU8fLrG6smhRcHnatBj+r3310ueXSeueMAOLW691GzebQcfL7pYOfEIvvnhq22CtRx81PztKSvJ4pLPOanmw9E7JX6+2AYLjL5P2uTc4G7Xlkb55SCp5Jsqge4C6EmnWIVJTa3/eTmUVbH9LyfmW76Pa1dL7R0qBps6rB9g+ye9NVMSAo9i2dPXVpsqS3y/16iXde6/0y1+ax63fpddfbxLdEIXmbdLS36nt71LBOOm7z0t99jZVliyPNOUm6YvLW5JPAOyymuWS7TVVy5wyuUu0FU4kk1TSkrhi23bbJLd5WXmq99ZLMtU8Dhl5iKTwxJKKigiqTIUl1Tc551jt5Iuy8L+Nn2/8XLZty4rhoqWzfop5G+aFrffV5q80dcjULrdxm2eflX70I7O88+9W6xipqopmWQPsrn+X6kvNhA07yqTm7VL+mOiq32xfHLyOKt6Li1fAgWJKLCkvL9ePf/zjds+fd955+uMf/7jLQQEAnGvkSGlpy1iK+fM7LwG+dq1UWyspu9gklkjStkXSgEMdc1K4qXaT6ppNlszQgqEaXjRcG2o3SJKWVy7XfkP3S2V4SIGsrOAFVE+8eRiLjIwM7b///gnfxmncut+xiHa/3XqcEJlkt738rPAk0ayQDtbWxBFJ7ZJJV1StaFseVjhMwwqHyWN55LE8WrVlVc9pF01bpE/Pl8reDB/oUF1tOuVX3C9Ne1Aa+3PHnJ858dgmIyYn7vcuC/ileRe0DHaxg79/rVofb3xN2uumZEcHJE26tO/QGcKbIxufmXq+emlHuZTZW8odFPZdN2yYGdTnbTkd+M9/zOzkrbxe6fXXQ96rYLwZcC7bzEyNXZcZUiKmfl2PTSxJh/btRCk5tpvelj46WbJbR64HQpaljG2faX/dLh0a2ayaTjwnpC8EPVXreUjE5yChA2C8NabDt5tr3gXrpsoMFrV0wAEJ6heOwwzHXQk9Pjk5UcbmMosWBe8FTJoU5ca+eumD44JVQ8KudW2T4OCt0da592vt2lMlSYcfLh18cNdv6/dLnsZN0qqHgkkSBz0pjf5xyO9wy+/x7hdLg4+JMnCH8zdJHx5vJqlr3f+M3lLheNOm69aYfq62Gbltae6Pzf9H6/rF35H2uFLKHWiSfFb+Wdr2pcIqmABp7N13pblzzXJurvTZZ8Gxza338z0e6Q9/kD74IDUx9ljL/yT5WkqDFe4hHbvADOa2PFJGy3mHnSEd8Ji09omUhQmkFW+t+VkY7clagkVT4WQn31Z/2zY+aXDBYK3eulqWLC0qX9SWWDJgQHD9lSsjuC4JTSxp2CgV7RHJXiRda9KHJUu2bG1r3KYNNRs0vGh41O/VWT/F3A1z2z0OTSxxe9/G/PkmByo0oaSwUBoyxIzt27TJvOaRTyahvZNh5fWl0n8mtKsCqqM+jTy5ZPsScw7fe4SUxYTPgBPFNL/cYYcdpo8//rjd83PmzNEhhxyyy0EBAJxr3LjgPZiFCzu+B+L1hnRIZfcLvrD1CzOrgEMsrVzatrx73901rs84ZbTMdBT6GtyjRw6WAgB0qld2r7blQ0YcouYbm9v+jS4eLckkm/TKDK7X7G/WptpNbY+HFgzV0IKh8gV88ga8WrV1VfJ2YFfsKJfe+a5U/o553G5Qv9/M6LjqYccklSDNfH17MKlEMjOKDvieNPwMacBhwRlGd56BFIAjhV4rhc6G7Ti2LW14XXr7YOmFIuk/46RXhkivDpW+vMZUUpU0dGj4TbRXXzV5l60zoWdlSY8/HvK++aODN9Pq1piZ2LBreofcOK5bJwWc018EF6qYI80+0cw2vPN5cyvb1/ls6AASKivLXLZ6I/2qCE0sqV8X0T2JhSX7KivDq+xsaY9EjcVqneF4wYLgv6efDl/n6afDX1+5suuBayFC+7NDz93Q3tKl5vdpwoQoj5VtS3MvMEklrd8Jnhyp/4HS4KPNjNpmRX22cnLbZpdd1v3vb1aWpPUvme8iSRr+A5NUIrXvt7EyzPlpOll5v1SzIvg9PPQk6eS10nFfSsfMl07dIO0xPdiXsP4lU0nQ9pkBlVNulY79Qhr1Q2nIsdKoH0nHfi7t9bvwAZcpEAiYwXrcc0KiPf10sCrSLbeYsc0dTRBpWSbhrVP+Zmnrl1LlJ+Zardvp8l2g5GlJAUmWSfrzZLX/29L6t3p0+0maAcTA3zIQKaswtXHE0eJyU63EY3k0ru+44PMtVUwkU22qd8tcLIsWRXD7LrtPcLluddgEGU7R6GvUyipTFrpvr75tzy8oWxDXz/lk/Sdhj+eun9vJmu7j90s//Wnw9yk7W7r5ZlN8Z/lyacMG6ZNPzPWRqeRpdd5X21TVPqlEkurWhj2sr5defln69a+l88+XrrhCevFFqa5OwYTxPnvFcS8BxFNMFUtOPvlkXXvttVqwYIEOPPBASdK8efP0wgsv6NZbb9XrIdO5nXzyyfGJFM7hb5RK/iWVvydVLzU3Vfvuazpphp1qsvIBpK3Ro4OzejY1mRk8TzstPFM+K0t64YWWB3nDW2YEsqWKD6WJV6Ug6o4trVjaNvv4mD5jNKRgiCzLUpaVpaUVJJa4Uejv8caN0vjxqYslWQKBgEpLSyVJI0aMkMfT/fd4LNs4jVv3OxbR7rdbjxMik+y2V15b3rbcr1e/sNf69OqjddvXyRfwqbKhsu35BZsWKBDS8fry8pe1rHKZ7JbB759t/Mz57SLgkz461Qx8bR3o0HuENOR4KatAaiiVSl/qfNBcCjnx2CYjJifu9y6pXi4t/Z3akkb6TpMO+JvUZ+/gOtuXSPMvlAKMrEB661Ht2w5I61+WNr3ZMjGE38zEOegIZXt+Isnc1ayvT15IUalfL312oVT2tsx8SiE3UneUSSv+ZCoSHLdQQ4dmyBfyNbhtm3T11dLf/24eP/64NG+etM8+LSvkjQ7/3tz4ujTy3PCBJAHnfa86Wt7I4HJDqXpiomGPat89TFKPra9e+uTslsEXAXO/Y8IV0sTpZsKc5q3SivsVWHG/Smv6SiUlPfackL4Q9FStA/+3b49wg5zdgst169RW5aELyzZOlNefrX32SnAV612Y4bg7mSF3/X2clnSptmUC7KirlWx8XVr/YvDxoCOl/R8LT/IoeVZaeKXmrthLmZnm/+KwwyL8vaqY3TLaK1Pa515zPm51MCpc6vz5nqixQlpym9rOB6c9KI2/NDyhMyNX2ueeltmNbWnRdWo75//OnaZSSegYBU9Lg9jzOil/bJJ2JNwHH0j33ivNnm0G0FmWNGWKdNZZ0pVXBgeNAvHy3nvmb87w4dL06R0nlbQKBEz1kjD135q2tf7V8AGjvYZIE6+Wdr80WJ3DTXaUS/UlZnnYqVK/bma8t/2MmQLioTWxJCOn8wqE9aVmkPuOMjMJTP6YyCsmpMCi8kXK9GTKtm1N3m2y3lr9lmzZ+mLTF2Hr9e8vlZaaZGi/v+u/58obFVyuLzH9kw77W/3V5q/kbzmvG1U8Slt2bJHH8mjBpgU6dY9To36/jvopfAGfPttoKsxmWBny2359VPpRl9u4yeOPmwQSSdptN+mjj8xYqNDDMG2atGSJ9OVfs2USS2K7d2fb0r/+Zc5FKirMdVDreccDD5jf71UP7FCxJGX37ebdAKRKTIkll1xyiSTp4Ycf1sMPP9zha5JkWZb8fmZwShu2LX37vLToN6Z8mpURvKG6fbG05m/SoGOk7/83vTqzAIQZNcpcvLT6179MJ2iobdtM59WUKZIKJpgbsrZXqvio647wJFtaaRJLbNvWqOJRGlIwRL6AT5YsLalYkurwkAL9QsYcr1xpKvSk+zWlz+fTk08+KUmaMWOGsiOYoi2WbZzGrfsdi2j3263HCZFJdtvbXL9ZkpTpyVRRblHYa62z4tiyVV4XTEB5c/WbYetNf2e67JBZ2bbs2KK6xjpnt4tVD0tb5ptlT4406TfSntebWVvtgLm5PmWV9MUlLbPCOEdS/+aUlprpeEKVlZnRSsXF0uDBwc94882ExpR2f2sXXK62wVsjz5UOfrr9DN+FE6WjP5WW3JLs6ICk6jHtu+Ij6YtfSdu/armGb+nzq1khrX9Z2Q1vS3pVkrRmjfR//5fgQZfRat4mvXd4cLCHOpidz/ab70BPhoYPb//y44+bgat9+kiPPLLTi/mjFJb4UPJM+1lIPTF1tbtXTn9znhJoMgOYPNkdvJ7b8Qx42cVJCbE7PaZ990BJPbZL7zCDxRSQCsZJh/5HKhwfHAzWa7C0953yjfiJnnzwBWnFkz32nJC+EPRUubnmZ1mZmewqJ6ebDbKLpMwCyVdrzg0iqFZQ15gvKYHVSpIg9Lh0VGkeQTt2mJ/5+VFs5G8y58utyQyTb5T2uq19cvGIM6ShJ+rTO9bJ75fGjjXnl92ybWnzh+acddipLeefLvHtc8HBoyPPNUklUvt7iZYlFe8p1a42k6lIUv+Dup7QzsqQRp0T/5i7sH69dMkl0htvmIGgrfdUbVv66ivp66/N7M2ffdbNQFEgCuvXmwnzJOmii7qf4T7s3qdtm3PiJbdKsttPRrRjk7TwKqn8femw/8Qz7J6h8uPg8oTLux/rkOIqSUBnGrwN2ly3WUMLhyrbYYkHHWqtOujJkumT2+kPW32p9J8J7fuNjvrUsckli8oXyR/wy5at/YbsJ0uWbNlaVrlMvoBPmS19i4MGmdtXTU3SqlVdX6P4ckYEB//WlTgysW3BpgWyZMljeTR5t8laUGYm+Pt80+fhK+7CPbuvK75Wo8/8LvTr1U8VDRXaULNBm+s2a2D+QNf3bdx/f3D5qac6HgeVlWVOCabuny2tUcd9st3w+aQzzpBeey14LtJaubH1nHjLFmlbVaOK+8kkj6dJ4hiQbmK62xUIOK9sFpJg0XXS8rtlTtZ2uqBsXW7e4pgB4wASY9Qok03c6q23TJZxv37BDtLHHw+ZEatwQvCiz1sjbVsk9dnHERc0i8oXydfS6T+6z2gNKRgiyQwwDS03CfcYMya4vHq1+T122TUlAKSVLTtM0oQlS8W5xWGv9e3VVx7Lo4AdCEssWbI5PLk00EHZ6Pkb5sc/2Hhp2iotmtHywJIOedlUl2w992r9mT9aOnyW9OW1KQkz5UpLTU3nSEbbZGVJ119vltevN6NC0Lkd5VL5u2Y5f4x04EyzvPNNVU+mSXTa84bkxgegvZJ/SZ/+KNinF9bnZ+74DOyzte2p1au7H6SSVLYtzTlHql/XEq8ljfqRNPl6qdcwyb/DVGJZcotak0NGjer4bdollLTKGx3+uPw9k5yZ3cd8t9q25K2N3z65gWVJvYZK9WvNjcKd5Y2QTlopVXwszT0v/LVeg5MTI9Kfv1Fafq+kgJTRSzr0dalgbPt+S8sTPgsogKQaOdL009q2VFJiLuW6lT/KVDaoW9f+tQ6SFxube0mKsoJAVwOfpLDBT2369++6YskuCO3HbmhIyEekjdaugNzcTmbt70jFbKlhvVkeeIRJKpHaJxd7siRZ+mL1ZNm2dOCBEQZVu8rcZ5ekgYeZGYJ3TrxNV2XvmOEHGXnS1D+bvoLO7iFaGdLm99Q2XmGfP0oBb9cDuQO+pCWBV1RIhx4qbdhgHrcOoGutXiMF77GSVIJ4+jgk9+GII6KcNG/pHdJXof1zlqkwmZkvNZa1TExkm4GdblTxsWRlmT87/Q9iPBR6rKP/ebQ+Wf+JrjjgCt1/7P2pDqd7npasaX9zx+cFTVUdD3yvW+vYwedflH0hu6VvcuJuEzW4YLA21W6SN+DVyqqV2nPAnpKkoUNNt5ltm8oSY8Z0PmbFysqTsvpI3m0tE7fsdM7jgIlbFpQtkMfyyG/7td/Q/fTkVybB4/NNn8u2bVmWtcv37OaunyurJfloTN8xqmyolC1b8zbM0yl7nJKoXesRNm+Wli0zy6eeKh17bOfrWpaC1yD1pV2fl3fgV7+SXn/dLNu2SZI691wznnDrVum556RNm6TMjPRLHAPSzS5fQTc2Niq3daoYpK9vHmpJKpEkWyqaJE26Vir+jumsqfpUWnZX+xlIAaSdnQdfNDVJP/qRNGuWebxunXTTTSErFIwP36D0RanP3uHPhcwCniyBQEBfbf6q7fG7a99VQXZB2+PyunJtqt3UlmwCdxg50nS2BgJmFt5MJpwFgB6r2d+suua6tsc7J5YU5xS3JZZUNQQHgqzeurrb9563cV7c4oy7srckf8sIkj2ulIYc1/Ho39ZB/VNuSWp4jlFVFdsUrlu2kFjSnbJ3gsv7/slUPuh0QIjHYaPTu7Bjs7T6UWnN41JTpen/yCqShv9AmnCFVDQx1RECsan4SJrbUnnD9ku9hkiTrpMGHGLab/UyadmdKlSd+vY1N4BWr3bYtdLaf0jlLX97cgdJh78jFU8J3vjKypfG/lwa82Np6R8kmfGcrdd+Edl5xmjbb2ZsPegJ89iypJV/jsfeuEvBmJbEkm87fj1vBH9fkVibZ5uqOZK054yWSiWdDBSjKhGQMmPHBm8hLF8u7b57BANmC8ZL25eaxNOdtSYvNlVJ1culueep0WcGruXkRJhoEM3Ap1C5uaZUdgKSS0IrlqxaJR18sMMqzPV0m94y58eStP9fu05W8GSqvsH80n7nO1JzcwQTWFV8FFwe+H33JJUEvNLmD8y5+4gzzeDH7voJyt8z5/k5/aTdvtv9ZyTpO9znk045xYxv9PtNotpll0m/+Y3JKfN6pTffNOMgU3BbFGnuo4/MdXpWljR1ahSJJZveDE8qGXqitPddZjyQZNrmun+2TNTg0gmIN39gJtHsd5CU0V3ZNMC5Pln/iSTprdVvpTiSCLW2txiqJjhRdWO1NtRsaHs8ps8Yje83XptqN0mSFm9e3JZYMmCA+Zvu9Zq/7//v/3X+vhkZMtc327eFVHIO4YCJW+ZtmCd/y3jSqUOmqji3WNsbt2vrjq3aULNBw4uG7/I9u7kb5sqyLAXsgL4z8Duav2G+MqwMzd0w1/WJJe+/H1y+5hpzntpVgnNG3iBJfnNh3LBRyuug9HcHXn1nmB591Cz36iXdcIM0fbo5N2n9zDvuMNVTfIGWseb+prRJHAPSTUzTxfv9ft1+++0aOnSo8vPztXbtWknSjTfeqJkzZ8Y1QDjA9iXSgivNspUpHTBTOn6JKUXb5ztSv2nS7pdIp6wzN2kBpLXRo9s/9+670g9+IN16q3TCCTvNhlW40/Rha2aaTqgwye+Imr9xvrwBb9vjJxY9ob989pewdf636n/JDgsplp0dnERu7dooZ/QBADhKaLKI3/a3TyzJLW6bvaamqUb+gOnU3Fi7sdv33rmqiaNs/K+5bsvuI+11e9c34y0PA+QQf2VvB38Hh57U9ayhUvevp5q3Tpr/C+nVYdKS26SGUlP9INBsEkzWzJQ+OMbMnAb0NM3bTaWP1lFNk2ZIJ6+Tdv+lmRCieLI0/DTpuC+l79yh3Xc3q63uPgczeWxb+vp2s+zJkg77n1S4h3kcelPKk2lm55tiZsLIzpYGDoziczLzpOy+4c+te1L65kGpeZu06q/Shldi3w+3yhtlvjPq1krN1amOBjtZUbVC1q2WfvTyj1IdSuKUvWl+Bz3Z0h5XMfsw4FDjxgWXW6tMdytvlGnTjRXm/L3d6yOkvvu2JTBmesyb+nwR5r7HOvCpsbF9lZM4GRIyR9aKFT0nhz8uSkulhQvD//33v9Izz5h///1v2Gu5tvmdaGyMZvD1f01lv92+a6pbddGf4vdLXq/5D8jPj/D9a1aYGfGzCqWiyRFulAa2fBacIGXQkeHVEztiB6TyWSbRe+D3Ex9fFO65R5o/3/z/T55sJuK7806TVCKZQXXHHSctXixdfHFqY0X6WbrUfIcdcEAUSYXempaJJjySLOnAJ6Tv/Sd80kjLI436oXTSN1L/g+MfeE9Q19IJstshJqkQ6IFakxckaeWWlWrw9oDydhmmoqAaK1MbR5yETnrbv3d/5WXnaXzf8cr0ZCrLk6VF5YvaXh85MjgZzkcfqUt1dZIKdpfkkWo76bRN4cQtjb5Graha0fZ4fL/xGt8v+D2zoGxBXD7n49KPFWgZh3boiENly5bf9mtO6Zy4vH9PNmuWSVQqKJD23z+CqnkFE4Jj+qqXRpQR7fNn6P9df4Asy1xfvfCCdO21Zl6FjAzTF5+RYSZDuOoqabdBrRWJ0iNxDEhHMQ2X/P3vf68nnnhCd999t7JDpteYMmWK/v73v8ctODjE0jvUNuj7gMekMRe0DEAKuSL1tNx8GX9pKiIEkESFhaZM3c5eeUW65Rbpm292eiGnv5QZrASipkqp5F/Bjhc7IAWSX+1o1tpZYY+9AW9YookkLjJcanzLdeyaNamNAwCwayrrg53NATvQYWJJa8lpW7a27NgiySSZdGfNNod+SQT80qY3zE34wcdKmb2738bpg/rRs9gBadP/zO/goCOjKpHtSM3bpfe+L619omVwS0Dqs4+ZVGPcRdLAI8xglpz+0v9n77zDo6jaNv6bLem9kEISeu8JvfcmAmKv2LCiqK/dT8WGL+KL2BFBpSgo0qVK7y2hl9ATIL33ZMt8f5yt2U2yCQSC7s2Vi9nZszPnzJzynKfcj/JfwibrxD8L5+dASSqgh+YvQMcpoi9bOskZ14mwIbRsKQxAdSqwJPekmY2v9ZuCBKeitU2SwMIOVu0EVMaAFUscfAH+DIADTs+wGsGzgeFAhtTNTiedOobZccLW89ux325yTWoRV1cZnIR7OyY7O+GEEzcFUVFm5xeHs0x7NTI7qGcdskN2ZQ13F+HQUlJy6wZkeHqaSZNOnap5hrkzZ+DNN6FdO4iIEM+/SxeYOhVSUq5ffa8bjNljYmKs/0aNgoceEn+jRll9535OOPYVFFRxbSMKL0O+wfgVNkxk2agEZRa8A66uDvYpY3CFR8Stv5euDlK3mgM7w4ZXracqvAQaQ0ByyEBB+lAHoNPB//4n/O4CA4UDn7+/beCSWi3OVcY87oQTNYFxPqtWQqwrqwQjOHpo9Ro0Hi/Olw+cU6jFvNRp2vWo6q0FWRZs6iDm539r1hYnbnksObnE6vMtQbDqEghIkHv8ZtfkuuDbA9+ajjOLMnH/xJ2fDv+EVq9Fo9fw8+GfTd937ChkCxCZ0OLjzZ8todHArl0I/ZpCCZocQR5eh3As9ZgpW4mvqy8B7gG0Dm6NSqFCpVARm3TtgSUZRRlcyrkEgFqhZnDjwabvDiYdRKOrXHb/p2PDBhF82q+fA0ElILL5GpEfb7v3cQ0SBE4W2Bnfm/RMN2RZZOsbMaLie6lU4OljCBwrrprs0QknnLg5qJFKad68ecyaNYtBgwbxjAWdQvv27Tl9+nQlv3TiloO2GK4sF44SkeOg8WM3u0ZOOOFERUhMtGW6Sk6GnBxx7OdntioYERRUo5TrrVrBTkdjLiRJMJtkW2wIYidBUHeRzURSwNG3q12Ha8X+q/urLFOn2cidqDU0bQo7dsDZs5CdLZT/lUGjqQb7jxNOOOGEEzcM6UXWLEb2Akt0FsGt6YXpeKg9TArOypCUl1RlmVqBXitYGS/Oh5QNglUOJbj6Q8Qdgl1eYwiMCR8plH3OwBH7CAoSVDnVZZi1F2HthBkFF4XxAoRDyK3cB/Va2HE3ZB8yM6G2/xiCDeyMsiz2OgUX4OKCm1tXJ5yoKS79BsgiYCL6f5WXlZQ0bSq6fWGhUDeUVzHcFFxZLhzRZL3IqFyVE57CbNFq21YwCmsctS36thGMylWxKDthglYLW7aIv5wcYVAMDBTZbjt3Bskjyvw8U7dAxOibWl8nzJBlmbmH55o+n0w/Sevg1jexRrWAoiSxjsOtL7c44cQ/HCqVCHBISIBjxxzMMOHZCFNEafI6COxaqZzg7iIyWKSmOlipmu4p3dzM6QtqAW3bCjmtJub6I0fg2Wdhzx6xZls6r12+LJJ9fP+9CDxxKRdX/8yqZ/gh7ge+HvE1E7tOvLZGVBc1yB7jTT4gc+KEg1FEmXvNx+G3iWxXlcDSXlBW5hDJL2iLABmUlQQ6FiYKJ/DiZEGE4NUYgns4cPE6jJJUQAFeDcDVAZ2LxoIQxq+dIL6sA9i1y2yinTZNDPPKgrv0+mpky/m3QNaDtlDoYFTeVns3J6pGkTE2zaMa/SvxD7GfdguBDh9XXlZS/jszX+tLMckTKg/AzrphnJvhnzU/O/GPwqLji6w+/3HiD+5qfddNqo2D8GsrsqMXXRFZxdWOpoGrmziUcsh0LCNTorWWXzOLMk3HHTta//a//4Wff8YGajXMmwfD3mtoJmtJXi90vXVEv/H1/q9Nx4WaQupNq0eRpgitob6z42bz0cCPrslmt/eKWVZvFtiMel71CHAPIKs4i1JdKcfSjtE28F+UEbAc0tLE/716ib1J+b2cDTwbIXIV6CHvjO367xkFt8dD2g7Y8xAASw+MQ6WSUakk3nuvajlE8ogAlJBztPKCTjjhxE1DjST/q1ev0tQy77ABer0ejcOWOCduCSSvNaedava8YMB1buKdcKLuwcjIVBMjRnx8tYNL2rSBvXsdTDkP4N8Oco6YnQU0uYL5t/4YEeGcuqV69b4OiM+Mr7LMxZyLN6AmTtQ1NGkiDD2yDKtXw733Vh444gwqccIJJ5yom7DMWAL2A0tkC9ry9KJ0K8UtgFJSIhloJXV6nam8I1lNrjsSF8OBZ6E0UzgwmJxaNcJgdW4WqH3M5cMdYHn8NyMqSsjBloHZp04JJlMjFiwQEdVaLaxdK85FRt7Yet5qsHLwaHtr98ELv0DqRnEcdTf0WmjtDWSknPVsCO3eu9G1c8KJa0fBJciOE8cOEsk0bWrWA6xeDePHV74fuiFB+Il/CgekwM7gHlqtn3boUA29BgijbBVs504IpKXBJ5/Ar79CZqZwqjNOm3o9fPAB9OwJ2xY3MBsorq6Czl/drCo7UQ47EneQUWyWk34+9DPThv7DGIpLLeTAoB63ttzihBP/ArRoIQJL9u6FvDyRWb1SeDU0HydvgPYfVlo8zC8JhaTj0CEHbaCO7CnBvK80ooZkX46idWvYuhUuXXLQaciANWvgzjvNAbcNGoimNGokAkyOHxfrekCA7TVlWeaHuB8AmL5n+o0PLKkB2nKc7fQlPt7Fsedkudf1aVllChKVSvxptWZn7yphumYFUSiFibCqBejL2QGH7L61nZe1hYAMat+Ky1gG1GRakMapvCsvDzfMyXvxYvHO1Wq4776qMwY5g0oM0OSLfcClhcIRVrbwNQrsDg3vhwb3isAHJxyCQ4FsIJy0k9eZCWYlB9a/CuTlV9a/QovAFjzd+WnHK3qrwPK5yDps5uiK5ma49ednJ/4xSM5PZs+VPQC4qdwo0Zaw6swqijRFeKjrcOZO37bmdSH3BAR1s/7emDWh/Phz8bsh1asuEnMTK/1eRuZo6lHah7QnNFTI3VlZ4rtff4UpUyAkxCxDaDSwbZvYgoi9j2F+SloHrV6trWZUG/uu7jMda/VaG1LA1MJU9Ho9imuw2c1f8TaSIfBPgYLJWyfj5eJFVrF4gPOPzGfqwKm108A6Dq3WvMerilDXBKWLCB4pvATZh+0TNHhGga/Y5+r1En/svQetVmLkSBHkWiX82sPlJcLmXZIGbvUcrJwTTjhxo1CjwJI2bdqwY8cOGjRoYHV+8eLFdOrU6bpUzIk6gsQ/hdOSiz+E9P93pd51wolbCTVgZALEbzIyqm3IaNvWfqrFCuHXAeR51ueKk+HczGrd93rial7VKfVySnJqvyJO1Dk0aWLu33/9ZWsLLI+iIgc3R3UUSqWSwYMHm45r6zd1Df/WdtcE1W23vfJaLezeDStWwLp1QhGm0wkngD59YMwYGDr01h5LTjiGGzn20ovSUUgK9AYHUHuBJVblC9NxV7tbnXup+0sEewQDwrluzdk1yMiUyWUMHDQQhaSo8bhwGLIMxz6A4x8AkjC0R90FDR4E78bCoJV9FC4tgKxYKMsGZHAJsH+98uyWUKcY1K7HnOMwoqIql4NbtYLoaJQ6HYMNmtfaqtMNbXdtQmfhMaPytF/mVmHxO/s9oBDK8R4LAMk+0YZTT+JEFaiz4/vyEkzMYw0fcMih2pJn6K+/4MknKy9/Q4Lw804Bco0ydXXoUA2nGwDf1oAzsKQq7N4t5PvsbCHzh4TAuHHCQVWnEzbhFSuguBhUvo3NPyy8BFmHwL/DLTO31tnxfR0w59Acq88/Hf6JKYOmoFZWPsZafNOC7OJsUl9NNQVo1wQ35NlqC83HLhU4s1rILcqCqwyODgTXgFtWJnTqQpy4ldG8uciApdGIANe77qpC1vBsaD7O3A/FKZUGocY0imNF7FjS0kTWkhBHfJir2lOCaV95o2D0s5JlkXmkd2+RfaQi6HSi3Nix4nfBwQbW42Hm64BwYJs2DVatsr2GJUPwxZyLXMi+QGP/xrYFaws1YDfuyGE0qEEHJ05Ale4N2kJAIYjqlRVEoZTTt7i73kO+Vs2JEw7KxUoDE762gkiU0gz7jssFF+refro6MBKnVJQJoTKnbXtBODfJyXvJEjFmbr8d3N2rLv+vhywLQo+DE4UuSVICsshaIymFfjNzPxQnQdMJN7u2twS8DET+RUUOBi6lbgF9mThucB8VBrVVge0J2/li7xcAPNLhERv9+i0PhdqQJVUn5ufyj6miuRlu/fnZiWuCbBCirmVffL2w9NRSE2lam+A2xCbHUqItYd25dYxrNe6m1EmW4ehRWL4cli6FCxegtBRcXUVg87hxcO+wdpjCs7MPQUAn60xldrImAOBeF1IsW6NEW2KTocQeVsavpH1IeyRJbCE2bRLPSqOBjz+Gb78V5fR6IV9+bEw25Wnhv5u2FUqzwLUCG+ENRkJOQqXfy8jEJsfSpX6XGtvs1p9fb+rjJzNOEr8jHp1sdmhbdnoZnw/5/MboNhITrYNjQKSUzMkRx35+tmnAa5F8wJJUyZL4p0r4tobCBJG5sYr+dDG9Eal5Yq89bpyDZFP+HQwBm0BWHIQNtdYH32KBY0448U9EjQJL3n//fR5++GGuXr2KXq9n6dKlxMfHM2/ePP7666/rXUcnbibyzwmFTujAW8ag54QTTtQ+unatpvOFf0fqkvOFXtZTrC02fZbKpa01bjpkZNIK06jn6YyO/jehSRPz8cqVUFgInhX4RWo0wkl+3M3RuVwXKJVKevXqVeu/qWv4t7a7Jqhuuy3LyzIsXAgvvih0KCqVUHYFBgqj9uXLglxk0yY4c6a2WuBEXcKNHHtphWkoJaUpsMTX1dpZzNfN/FlCIq0wjTJdmVUwygf9P8DTRSwCjU40YvXZ1QBo0RLWOoymAbaZPK9nGwA4+50hqASRhaTXIlB5iQFmdHL3iITIsXD8Izg6WWgG7e3fbgEGtWuZc2oLN6JOdbHdNYJkoS3W28loewv0QUAEaxkzOTSfWPGYcsIJB1Bnx3fhJeEc4dUYPCIc+ollYMn69ZCfD94VkASDCByoVacqvRb0peLYLZQKHcsqCGZr27aa9wvscg2V/Xdg924YNEgwpIeEwA8/wG23ie+MhkwXF+Es8NdfiL7nHibeDcCFnyDmy5tS95qgovFaUgK7dsHBg1BQIBy7/PygZ08l3bv3qtTBty4gvzSfP47/AYCn2pNCTSFZxVmsPbeW0S1GV/i72KRYzmSKjd3qs6sZ1XxUjetQJ+bOcnKLEugFkA9kNapSbrmhMmFiIhw5Yv2l0XHBwmlBCfRydxdOC9UILKmTcqcT/zo0bWomA1q4EO6/v+KyWi2oVB4Wa4wMF+dDy5cqDEKNaRSLTi/M5vv3w8iRDg+TOoWWLc22m0WLBKFLZZAk+M9/zMGge/ZA/friO3sZF0bbWQa+3Ge9dn+z/xumD5teg9rXEDXIHtMx3h0eEHahgwcFmVqlzk+SCjCkOZf1tvtDO3vdDhFR7Izvzd69kmMOXEZyhsJL1Q6YvqVR04AasM4k40j5WnLylmWRsQ/EmKtOtqB/JWQ9xP0H4meIz37toelTIjOJa5A4pyuGKyuFs7DyHxaoUEsw7s1Pn3bwB6Vp5uOALo5lLLGDj7Z/ZDqec2jOLZG1qtpQuoO2QBBbVBQE54QT5eD3Xz/yyvI49fwpWga1vKl1WXR8kel4ZLORxCbHopAU/HHijwoDS0pLYedOof87cULoAF1dhbw4aJAIQg4Pr1l9jh8XWZDj4oS8rdNBRIQIkCsshGPH4ORJWDC3BWc/USChh7Tt0OwZ24tZZE2oy9hwfoND5XYl7jIdR0eLjCTGbBPffSfk9LffFrLHI4+I7zt1ArxbgNINdCXCWT9hkQjMvMnyZE5JDqW60irLLTu9TASWOAhLPUWptpTc0lzTd3pZb7LxGnEl78qN0W0kJopUm9UlhXZzE/uZWggucXUVez5ZFsGnDvv5ebcA6W+RNejyEmj8aIX9KafIz3TcurWDQfV+7c3H2YcgdJD1HusWChxzwol/Kmok9d5+++38/vvvTJkyBUmSeO+994iOjmbVqlUMGTLketfRiZsJjWHxVfvbV5SBLeNtXWQadcKJfzpqwMgEiN8EBVX7dh06mNN4VwaT4cG/I4LKqWZsJ9cb5dNMPt7pcTqFCkqqC9kXmL7XbPQ4l3XOGVjyL0Pr1ubhVFwsDJXjx9vfAKnVgqXtVg4sccKJ2oJGA88/Dz/+KBQW/frBY48J9mI/P1GmtBQ2bhRGaze3m1rdfx32XdnHL4d/4eUeL9M8sPnNrk6tIL0w3RQsCpVnLFEpVKQXpZNemG4KRvFy8TIFlQDU965v9ftzWeccDiypMbTFcPR9cRw2FPquNDu4WzolGJV5riGAXohcujJbFk0ng5oTtQ3LLCUl6bZ6hFulDyYuFo5DChdo9PBNN8A44UStQJOHyHDlX3GZcjo/P6/GBAf3ID1d7Jfmz4cJE+zvlTQaWLu2lvdKFsxzwtmvnMdeFcFs3sE9iIoSNj+H4Boo2M8LL9WsvtcblTHg3WD2OxCGyWefFY50jRrBjh3ilka2XEvnOldXwYyOJEHoULj0qyA3OjtTOJX5tLolHXa2boVPPxWG/dJS4SBhbL9OJ4LsW7WCw4frtrPh4pOLKdGJcdOvYT/WnF0DCEexygJL3t3yrun47U1vc1uz2+oEO2uFUHuZj8tyRCe2rO8tI7fUwHGhFp0WnHCittC2rZhHAdasgfR0kV3DHkx2ibDhIqBE1sK5H6DFixVev1ODQ6bjvXthxIjrVPEbjJYWfot//glffVU5c/2uXSKQBuCzz4SzWmWOQOWDba7mXeXPk38CoFao0eg1zIqdxYcDPsTLxcvOFWoJ1cwe07qt2ca1caOQaSuFyguTfUuTb5vpys6a0av5Lvae68apUy4UFJizCVQIvw7CcUunEay9gV1uDMGBXivul3NUZGaRJFD7CEdz39bVoDWuIYzrcWGCqEt1ZMCsWPGcFDdXsCotNQe++fhU45HVMXn+huHcj+agkubPQ/QMQLbWvSjdIXKcCDZxwiHExIg5/dAhB0keapCJCbDyBTqYdJCNFzaaik/ZMYWnYp7CpaLr3arw7wTpO4Vju5N4xgkHcDjlMHllIvjxzY1vsvy+5TetLikFKey6LIIV1Ao1j3V8jI+2f4Re1rMifgXFmmKrTEM5OfD++zBrlthiqlTg4SGWpbIyoff49VeIjISzZ4V+pzpYuhQeeEDIYBERIsD5zjvF9Yy4elVkAlu/3hXJqzEUnIMrK4S9THVrBhvuvrzb6rPSIpjPMrPGuexzpuOuXc1BJUa88w58/bWQPbKzLS/oAvX6QfLfgB5OfAKNHhFBgzdx3lpxeoVD5XYk7Kj5PeKrvodO1nE87Tht61WXZaiayMiovs8eiN9kZFjJeVeviqw+hYViP+ftLdb6gAoShyw4uoD3t77P7NtnM6DRANN5SRIyQVGRyAzkMHmCTwtzZsHzcyrNIFdSZnby8PBw8PoekaDyBm0+JP4Jbd6yLXOLBI454cQ/FTW2zgwbNoxhw4Zdz7o4URdh3MDLmuox3tYlplEnnPg3oAaMTECNlZCuriK4JDa28nJGRSoufuDXTiim6wBOpJ2w+vxM52foHN4ZgKT8JKvAkhNpJ+gZ2fOG1s+JmwtXVxg4UDBw6HRCeXLXXWKzZrnR0mqFca48IeStBr1eT3KyYIcNCwtD4UCO7Jr8pq7h39rumqC67TaW/+UXmDMnDKVSwf/+B5Mm2aY+dXUVrDZGFmMnbgz0sp7uc7oDsOniJs68cOPSxdzIsZdelI5Ob1bI+rj6WH1fPtAkvTCd+Mx4NIYsC+UDSSJ8zGzuChScunCKdu7tqjUuqtsGLv4CZVniOPoLQKqcPc4yFXHuCZFK+BYzdtV0znG0fF2tU11sd43gEY4poDx1C4QMuOX6IAAlqeJ/76bWwTKWcJJsOOEg6uz4Nur87GUXggp1frcNSmXBn/XQaoWj4hNPCCdPy2rKsjlzXa0GlihcRECJrDWQ45Qjs3DAKTwmBq5cMTuqVongPlB0xWxYq7Bubma23dpAHXQkX7tWGDxBGLmDghx0TA3pDxfnimNZC3sfg2H7QK8T2dn0VTzrmwjjeC0pgSlTwvjpJwVKJfTuLQJnhg+H0FDRvy5ehDVr9Jw7l0x6eh1bv8thVuwsJCRkZB7r8BgbL2ykTFfG6jOrK8zsu+/KPtaeW2v6fCztGCviVzC25dga1eGGzJ2uFh7p6TshqLt19rXy95AlkkuFg2eYXqaqO9wwmfDcOQgIICw5GUUV1JN6SSLZ4KQalp6OwoH5oM7KnU7869C7t5kMSKeDyZPh229ty2m1sGGDyDhC6BC48LP4ouA8HH4DYmZY/8Awbur5phPim0Jqbijz58NHH3FLol494fiXkyPMRQsWCDNRRYHA774rHAZDQkQWGHtZSirDzIMzTc5w3SO6syNxB4WaQuYdmcdzXZ675vbUFlxcoHlzwYa9fLlwzPOvJN5a51ofkzYmdQvUH1VlAET3pnvR6oRz9e7dwuZQ6fOt19d8nLoFAqKt99OuQULGLC/fuvhVWg+7kGVIWgPxX4o1UFds+MLYSmOURFsYGVu7gRv+0cIPQauBrAMQ2M1xPULq5koDxm4ULAOGS0sdZIKug/L8DYGuBI5NBiSIGAudv6m4rJPko1ro0wemG8zbu3dD//5VOI8q3TARFNkL6nIg6/DH2z+2Op1ckMyCowt4vNPj19CSOoiQ/pCxB/JOQ1m2NUFHRXMz1Gx+duIfgdf+fs10vCJ+BXsu76FH5PXTG6eminG+e7fI7pGXJ8a7r69wPO/ZE3r0EMGOX+/72kTA1tivMXuv7CXYI5j0onRKtCX8dOgnnu/6PCCCjceOFVm4fH1FZowxY6C9RWKBrCyh/9m6tfpBJRcuwH33CXl9xAj44w+xhpaXU+vXF8QlEyYABztB4UXQFQndUZMnbsn1Qa/Xo5SU6GQdrkpXpgyaYvpu0fFFxCbFokePTme2afaooMukpFRwk9DBhsASoDgJ4l6CbrPN38uOKj+vH4xZbatCamFqta5rqadYfmq5Q7/57ehvPN9K9PVa021cIyF0bKzITLNxo30iJEmCAQNg3TrrcVOqLeXhZQ8DcNfiu0h/LR2FhTzdsaMg+dy4sRqBJUHdMenaM/dB9lERdG5nD+TpWmg6Lihw8PqSJLKWZOyC7DjIOW4gGqp+BjW9XjxyrVbMSy4utR8b74QT/wbUeJbMyclh9uzZvP3222RlCUeXuLg4rl69et0q50QdgNpP/F9YAXVfRQbaggu1ViUnnHCiAkRFCbYl418rO5G7RkYm4981KB979qw6hZ2V8jRsqIFB9ObjRPoJKxaARn6NTMehXqGoDZtRtULNifQTNr934p+P224zOxYlJYmMJUql+ZxGI4ijnn765tXxekGr1TJ79mxmz56Ntqo0RNfwm7qGf2u7a4LqtttYXqudjVKp5cUX4YUXxHf21o3qGqyduHbMiZtjOj6bdZZV8atu2L1v5NhLLkg2Kcw91Z4oyymjLANLdLKO9KJ04jPiTeeifK3lpDBvM0ugm+RG3p68ao+Las8flxYCMoQMMijsqlCoBfc2H19deVMUxdeKms45tTk334g61cV21wgu/oLFDyB5va2S2Whstftbv1qtWrWgN6RnV1ZgHTMa19fFwLZRIhX33z0hfc+Nq6MTtwzq7PhW+QCSIUjCznpRgc7v9r6nTdlL4+OFobe8HU6S4MUX4fz5619tmxu5GRzc07bXyOGtQ4fKWbxtjFDBPawzpdiDdyu4PV6wqtUWasKAZ2S/qyV8843YN3foIBwEqtIZmRAywPpzVixsHQVlmeJz5v7rWs/rCeN4XbBgNr/+qiUgQLBvbt0qsje2bCmcewMCoFMneOUVLY0b18H12wL7ruxj39V9yMgoJAUeLh60rye8SPSynul7ptv93f9t+T+bc+9sfgd9DeXRGzJ3uoeCdwtxnLS2SucUraxi9uWnmH35KbS6qj1Gb5hMuGMHs596Cq0Dm2utSsXsp54S5Y2pRK9znZz4lyIxEeLirP9WrxZ0xr/+Ko7Lf+9wyjABV1cRsGd0hPnuOxEQYNkttVq4fBmmGP20QgdZXyT+KzHewRxcm3XA9HXXxvtRKGQuXxbXLs8QbAldFeLAzYIkicBe45Qwdap4LuWDaPV60YYjR8T3gwZVX0dXoi3h2wPm6J6JXSaajr/Y+0WN14AbhS5dRJvLymDGjMrfqTK0FygM+8PkdbaBD3b2ut2b7jUdz5xZ9fPVukaCu4HkJGWj7brkGSVkzB4LrM+7l8tqURWKk2HLcLGXTdsJDR+CPsvgrix4QCv+7kiCHvMhfHjtZwMJGWg+Tl5vuzepUI+ghNSttrL5TdA7KBRmdubz5x102KuD8vz1QlZxFp5TPOk0sxNy+SibC78IMg9Jgo6fimByJ64LeluohTdscOAHRj8gENkAyr+rKogaTqafNLHER/mY974fb//YiuzpH4F6fc3kEsnrrQk6jHPz8Nhrn5+d+Edg04VNVpl8AP6z4T+282ENcPw4jB4tCCzGjRPyqr8/dO4sHMfVapg92zq7sKWsFp8VzwNLHyC9KN107rPdnwGQmyv8I9LSRKDa2bPw1lvQrp11HQIC4J574Mcfq1//t94SU014uNCduLlVrDtSqw2BK4FdzPPTqWmVE6/VYRxKPWQKxm4T3IZXerxi+hvTYowpyCEhL4FijQj4DQ+HBg2qcZOQQYCFHHV+Dpz+wvxZk3eNrag+0grTTH5Z9TzrET8x3vT3ULuHUBn8xzKKMqo1Riz1FCm5FUXaWCMxO7H2dRtGQujYWPPfggW25RYssCqTs/8M49+NonNnkSE8Ohq+/x5On4bMTPEXFwfTpoks0eXHzee7PzcdZxVnMffwXKvvhw8X8urx49UQJf3ai6wiRux9VMjddvZ4gd6ZpuP9+yvfR1shIMbsQ3jiY4eDSrRaMf+99JLI7OPuDp6eIiDOzU2QLYweDR9/DGduHLemE07841CjwJKjR4/SvHlzpk6dyrRp08jJyQFg2bJlvPWWndRETty6CO4pJvG0rTdFyHDCCSfqLrp1q1ogtGTpIWRg1YyeUPusnsDxtOOmY3eVOwHuZnZvhaQwMZJr9BqOptaNLCtO3FiMHGmtQ125Eh5+WDC9AezdK4xtec6l0QknKoWXl2CQdLJC1B2kFqTynw3/sTr3zOpnKChzlELk1kFqgZnhpny2EhAygMrg9K6X9STlJ5FUkASASqEi0ifSqryL0oUANyEzaGRHtWLXiJI08b9304rpDgsTISsOrq6GlE3g1VScT1pz6zr1O3Fro/5twsCTfQhK0q0VzbeKsVXtB0hQXIFRwkmycctAlkWWgFWr4NNPYeJEeOopEQzxxhswdy4cPFizDPW3PIK6C2bg0gxI3+2wQ8+Q3slWTnE//ywcFo3Oinq9YEn94YdaqLM9RIwVusuUvwX7rSUcWPe6d7d2SC0Pm6CTQAu2toqgcqvdoBIwM+BVBwb2u9pCQoJwyOzSxUGWZiM8G5id+41IXgdLQ+F3D4h94brWs7ag1wvj78iR4nN5I69CUY1gm5uIl9e/bDrWy3pu++02DiYfBEBGZvqe6ejLeSfvStxlcpxp7N+YPlF9ADiZfpIlJ5fcoJrXEBG3izkkYw9o8q2/q3QO8a39ulUXO3dW7LhgdFrYudN8LtJ6v+OEEzWGkXU/Jsb6b9QokSrjoYfEcfnvW7SodnDJqFHWARKPPQZ//23+fO4c3H47FBUZTrjVA7+OiKyKADJsvQ32PQkX5sL+p+GAOatG7xbmMfLOOxU7h+v11WBivQm4+26sAoHvu08cW8prCoV4NcWGRBXu7tVcv4FPd3xKdkk2AGFeYWSWZOKpFhkfz2WdsyI2qYsYMsT8nL74QjhU2pMLNRo4Ge8mGOtR2A8ssRP0EeqXSn3/KwCsWAGnTlUud6pUCDuapILUTZB1yDZzm2cU+NohlXMUei1sGy2u79cBbj8FXWeKDCyWDPzuYdDgXoieVvN7lUNhWSFFmiLbL9xDwKe1OL683FaXVVFADTqRtTBpXZ1w8u7TR8wZS5c6GFhSB+X56wG9rOfhpQ9TpCnicOphZsXOsi6QfVj0cZ9W4NPCvgOhpa7z4q9OEg8HERQkMjGB2I8XFlZeXhvQF9P6mLCoagKFcvhkxycoJAUSEk/FPEXn8M4AXMy5yJ8n/6xm7es4Artjcq07OdV+4F9A9LXNz078I6CX9byy4RXT506hgoBpz5U9rDpzbQRvs2eL4JF16+Dxx+HSJRH8sXChkGNmzIBly+DqVSEfu7vDibQT5JbmVnrdxNxEckpyeOcdkcHN11esZb6+QjaxZ9+tiW4jMVFkKNFqhd1Yoah6vVQoEPKIUQ9XcAGOvmdb8DoE7dQ2DiUfAkApKWkZ1NLquyYBTdAaZD69rLfyZbr77moEf/t3sM7MChD3CqxpD9tuh+131Lj+NcXeq3tNATXtQ9rTPLC56a9bRDfTd9kl2VzNrxmR/ZV8IW8rUDCu5TjSXk0z/XWP6G4qdznv8jW2xkFUkxBa3zGacZMi+fVXaNZMBGYsWyayhLdoIYK5AgLE+H/xRTEXWOJC9gU+3P4hgClLySvrXyGzyBzsMXiwOYh+8eLK9yQmSBJE3W0O/Mg+JPbRkkLsKSzsfpGBV2gWcgaQWbq0GnNE5FizD2HiYkE2VFF2dQP+WO5Ho0Zwxx2waZPI4PLbb3DihAgiOXBABJQEBcGiRU7VlxNOXAtqFFjyyiuv8Oijj3L27FncLDa8I0aMYPv27detck7UAUTdIyZxvQYS/7SdwCsyrjidkpxw4h8PS+YTe1AoyjEYBPepmkHgRrB6AodTDps2KVG+UUjldsRNApqYjp2BJf9ONGwoNmeWXWPBAggOBm9v6NtXKGuccMKJytG0qUi17AwsqTt4ad1L5JcJh6kBDQU7dFJ+EpO3Tr6JtaodZBablWa+braOX5Ik4e3ibfp8Ne+qiU1TQjIFmlqivk/9WqhpJVC5i/91RfYHkr2sCQXnAAVkHoCMvfaN6zbGeOqWU78TtzbChhmM0TIc/T/7Djd13dga2Fk43BddFmPpn8a0+C9AXh589hk0aSL+Pv5YOL03bSpYrDp0EAaOP/8UDon/StS/zcy6nLDQdp2pQOfnHeDFsGHWxt833xTP9JFHRFaG//zH5me1h8g7hO5SVwxXllfbqaxfv8r9uWyYq/3agdKj8jrVNqszOMaAV479jvj4a8pcWxWMfUKnq4H8H3WnHZ2RLN7rLYJ+/URQya2ckbFMW8beK3srLaPRa5h/dL7VuSdXPolk+Ne+Xnsa+zc2fTdx7UTKtGW1Ut/rgrDhYg6RtXDi02oExIbe2Ho6go4dK3ZcMDotdOx4bfc4fNh+RorrkI2iziP3pGB73fcUbOgNyyLgzyBYEgzLo2DTYDj4AlxcUHFwshPXjNGjrYM+c3LE3BsdLfS17doJhxIrNLwPc2AJgCzYe/dPgHOzsAwYfaTPPBSGoqdPC8cdsPZV0+lEoMHbb1+/dl1vDBok9HFGrFwJDz4I6QZy6owMIbctWWJevy9frt76rdfrmbprqulzckEyz69+nkKN2ZP57U11+CEBd95pfk75+TB0qAhKsnS00mjgyhV4+WUgbIQ4WZgA539yKOhjdMxKVEoZvV5kP1epbLPHgLjnhg0YWPENAmjsi7b76WvFyf8Khy2lO/RbITKkSArbYA6wdZzWFEDiEjjyLuy4B/5qI+a/ZfVhRUPY0FM4m536HLIOWw2cVfGr8PrUC88pnlzJu2J7r/Dhwmkt54iYR6sTUHP4dazHONdH71DNTEz3dr+ETidz6RIcOuRAVqM6KM9fD3y++3PWnFtj+jxx7UTikuPMBfSlgAzKCjZhzgyx9iHLUJQEqdvEGnbqczjxX/H/udkie0/RVQYNlFGpRKDcO+9UfkmVdygE9QQUwg+oGgRFWzMu89ux39DLemRkVsSvILs42/T9U6uesglGv6Wh9gL/joAkgqPO/2w7TznhBDDvyDyTb0lT/6ZW2dxeWf8KZbqa7Y0PHBAkOTodfPklzJlj7SytVFrr6ZoauMem7JiCI5i68zNmzxbXnzRJ+EI4FCRZDVy1iBno1q0ajueeUVCvj1kmOvGJyEIIQgeo19R5I3RKQYrJXilJkpUvEkDTgKZWnw+nHDYdjxvnYBAAiGcUdZc5EMCInGNw9S/Q3ljG1BJtCaczTgOgVqhpGWgdUNM8sDmyxV4sNim2Rve5lHsJEM82OiyaYM9g019MWAxqg0xrDO6pa/jyS9iyRYyJVaugbVtxvvwYkSTbc7Is8+zqZ01zy+3NbwcgpzSH1ze+birXpYvI6AHw4YciY2Nly7Tpu8i7rMmjLy2Av/sIYsPUrXDEnL34nu5/oFTCjh1iv1mVGKDXA/X6mbOiyHrYMgzyz1uvsRaBr7M2T+DeJxqTkSHIfY4dg08+gTFjoHVrEZjTubOw98yeDXv2iCA7J5xwomaokTbiwIEDPP300zbn69evT0qKU2H6j0JAjHkSPznVYGSxY1ypy0yjTjjhRK2gQQNBLFbRPk2WRUo9E9ReENSDSpeeG8DqqZf1nMk057trFtDMpkwT/yYmBvPM4kyyirNqtU5O1E08/rjtubrORueEE3UNVbFiOXFj8f2B71l0YhEAbio3hjQeYmIvmb5nOitOr7iZ1buu0Og05JWalaSW2cksYZnJxDL9t0avsRtE0sCvAVJ5Y3Vtwq+jUAInrQNdqe33FWVNQA/IsO8J+3u4uuzQ78Stj8BuoDYEc52fLTLp3GrG1sg7QeUljs/OtHXmcZJs1GlcuSKCHN56SxgSLl2Cffvgu+/gueeEE93jjwt2vFWrhB9QdYlibwkUp4j1I+F34fRw5js496NgfL28DPLPQfgosc5cnCsceCzHaiU6v0cftXWUOn5cGHSO3mhuhnr9QGUIFD30mlgvLZlWq3Aqc3MTzpcVGcx9y8emKlTCqFbeSGuEpIKQAdVrQ01RFQOeBfsd0dG17oTWooV4jtu2VW08tEGTJ63llVsQTZrcEiSZleLbA99aGfVVChVqhdpkhDfiq31fmY5n7J3B6czTyIZ/K+JXMO/IPNP3aYVpNhkT6xSCe5uDxU7/TziKlQ9Qq+sBsTcSvXvbz0hxnbJR1EmkboW1nWB1W0haDwGdoecCsUbemQbjUuC2E9D5K/BtJxg962LgUW3CEedouC4O0sHBMGKEbRDfoUPCgcWu01XDBx12Ngv1S2Xc7dmm63/7rZAbiy3iHLOzYdgw4aRSV6FWC2caS/nGyNYaHg4REUJuAyHrKBSwfr1w+HN0Df/+4PeUltNTyOWyumUUZ/D3+b+pq3BzE+/X+L5jY6F/f7E/MGLDBjH1pacD4SMQ+haE3FmSVuVe9+URX6Az/GTHDrj/ftFPjX1Vrxd/a9fCBx8g5hCjbJu+E45NNhS8TmQHiX8CMkSOE1nj7AWUlM8WkbwR9j8rAuliXwR9GTR/DgZvg1GnYcwlGHkUev0uZPOCC+DbwjTu/j7/N6MXjTZdvt8v/UgpKOdPUn+02WktdhKUplfJVox3CxGYnHsSjhg86MvLk5XIl7Is883+b5i6c6qJJdz8nKqfiWnMB9EoEe/ptdeqdsjVaqlz8vy1YkfCDt7a9BYA/m4iA45Wr+WO3+8gpyRHFHIPB2SxH9XaCSJ3Zoi1RvYRkVlraQisi4bzs6AsG9Q+4BEh9G+aXBFssn0sE54oM80v334rGM/BNkASYNYszJkAck/AhV8c0wkAz+6xTlF6IOkA57PPmz7nleUxedvka25+nUKLFzAFo8a9LJ5Z+TnmVtN/OnFdUVBWwJMrnzR9Ppd9jidWPWH6fD77PE+teqpG1379dTGOBwwQASZgJ8OuBYxrUHxmvOmcq9KVhn4NTX9KC3KPkylnKTWIdWFhtaPb8LDgaMnNdSAA0xJNJliPt9hJsHkIXJwH536Anfddt3rWBo6kHDEda/Vam0CSJv7mQBO1Qs2RVHP5bt3EHqgyWPWFJk9aBwLcRBxLPWaSsbR6LS2CrLMVtwg0f1YpVMQm1yywxAidrKNNvTZW59oEtzHVoaR8pus6AuPW+c47hfhZHcKaT3d+yobzGwDwUHvQtl5bVAad9U+HfmLu4bmAuOaoUeL/lBQxjygUFQe8m8gagrqDVxOsgrjTd8L2MbB5ECSvNZ2+s+sSdDoJnQ5eeKHyOQoM30sKaPo0Jh/C0kzY2FeM69JMKLoqbIzA4UsdeO7n7wCZmTPFvsrYtvLPzMVFXN/Lq/I6OGELWYbz50XmqzlzRCDS228LW9v77wsb219/CSIOh4PenLhlUaPAEjc3N/LybCMZ4+PjCa5qRbtGfPfddzRq1Ag3NzdiYmLYsWNHpeW3bdtGTEwMbm5uNG7cmJkzZ9qUWbJkCa1bt8bV1ZXWrVuzzLjDqsZ9ZVlm8uTJhIeH4+7uTv/+/TlhQ4tzC0KSoNEjYjLPPwN7xovz5TeVTsOKE078K/HQQxV/p1DAwIHlTjZ9GpPi3fYX4Nv6OtWsYlzMvmgyeKgVahr5N7Ip09CvIbLFjvlE2j9gPnei2nj8cfDzq7rc9WbscMKJfxLOnoWdOwW73z8FR1OPEv1DNGMWjrFi4arryCjK4IW1L5g+l2hLeHvz26YMHTIy9y+5v26zCVcDltlKAALdA+2W83f3Nx0XaYpMgTaA3YwlkT6RpuDTG4JWrwolcGm6YFItb5yqyLndp7VwbM09KZTq2oJyDC+3tuOmE3UcChW0myyOZT3suheS1xs+68zn6zJUHtBovMHhfh6kbnbY4d6Jm48hQ0RwydixwoEuwjCdKxTCqGD8MxocHGbIuxWQug12PyJY1HfeDWlbxXhzCxb7bc8o0b8LL4l1pYEhU7G2UBiEdCW2DtV2dH533CGc6KsyEN0QwkCFGhqPF05lRVdgxzhhASnviFbJvHP77fYNaSqVYD+3QaMHKzbSylqD0+G/D6+8IhwDLlyA336r5h7AqxHUv73igB1LKNyEDFTHcOpUNfu8XiOyy535DvY/DdvHwe6HYdeDsOsh2P2QON5+Jxx+Cy6vFAbVWsSOxB2mIGoPtQdPxTxl+mtXr53pu9OZpynWFCPLMu9vfd/qGsYAE0vMjJ2JRldHN4VKV2jzFiAJR9ntYyHbwGJpnDfqutziRO0hcbFwWMo7C/1WwsB10OQx8GoIKk9hN5OUoPYW62yTx0Sf+jeiKudouG4O0u+8U00HBo8IQ3CJY2vMa6+UWV3/55+Fg90dd4jsKPXriyDKuo6JE23PaTSQnGy9RgcFCXlYp4OPPqpavjOaTX499qtD9ZgdN9t0nJICK1aI+zzwADz6qPh75BEYP17o4++7TzBlL1ok1laj02FmUSY95/Qk8LNAlp2ytePXFJMmWcuBhw4JB76wMAgMFA5YSUmGL32aQ4MHxLgvy4Ktw4Xt3HKdKKe3aRZ6jnGjckx7j0WLoFcvWL5cPI9jx0Q2lLFjDQFMLr7Q5g1MLhzHP4ItI4Qjueke12NNrUBosZctYssQsXeIGA1jLkLHKYI53C1I7C0UauHk7hkJDe6DLt+JjCjAtkvbuH2hYE42OrBeyL5A/1/6k1GUYb5vSD8IHSzGaVmWYELOMGRR02tFYI1czgO1xSTzuVOfwd4nQFtkKF9m+N8OSQuQW5LLHb/fwQtrX+DNTW8ycO5A22CXaiKAbEYq1qFSymzaJJyvwL7jrFYrsgT9k3Ai7QRDFww16Zo7hnaksZ/IYpeYm0j32d1FBosmBidrTS7Ez7ANmnISeZhx5jtYGy0Cwrr9CHckQc9fofmL0OhRERTSeDw0fwF6zofhB+jU2ZWxY8VeVpYF0/1zzwlmciNycuC222DmTASxilHXfXCiyBpk+U7s6AQuaOB09iXTZ6WkNAWjWxIyfbXvKytb+y2Phg+BZ0NAIfrv+q5w6n/WZQov3YSKOVFX8OiyR9GVX6vKYd6Redbrn4NITRXriTETiSNIL0w3ZYxSKVS83ut1Lk66aPp7rONjJlvXxsQ1BAaK8XrwYO1kYm3eHEJChN7k66+r6V8RdQ+4hWAlv6RsFJnSDr4ABWevd3WvKw6nHLYK5LEMJAFhpzSS4Gn0GqvMHQqFkI8reydWU21ANAT3sZMV2A5qWb8WmxxrWhdkZJoHNrf6PtI30kRkotPr2H91f43uo7LY57UJLhdYUq+NSUd1Q0kDqwHj3qy6NoqkvCTe3fyu6XOJtoSpu6ZazUNP/fUURWVFgAgQMPaVefMEEUFBgbi/Xm/eYy9eDC+9ZLiAJBl0ZlWv5x0bHKZls2KUSrHnmT5dnC8vCxs/L1pkONH0aevs36XpQiZZEgTLIwxZRmH32Z7o9QokSeKhhxybQ+p4MiMryLJ8U+WmixdFhs2QELjnHti0SeyHb7tN7Ncfe0zoRJo1E2UbN761s3Y74RhqFFgyZswYPvzwQzSG2U2SJBITE3nzzTe58847r2sFLfH777/z0ksv8c4773Do0CH69OnDiBEjSKyA9ejixYuMHDmSPn36cOjQId5++21efPFFlixZYiqzZ88e7r33Xh5++GGOHDnCww8/zD333MO+ffuqdd/PPvuM6dOn880333DgwAFCQ0MZMmQI+fn5tfY8bhhavwkeDYTgkbgYto6EvJPiO73WVpHjhBNO/Gtwzz32zyuVMHgw+PuX+yLqbnApf9IIPTS4/3pWzy5OpJuDRHSyjoZ+DW3KNPRraBK4JSSr3zjx74GnJ7z5ZtUbjltpQ+KEEzcaSqVgpdBoKjf6V4uZ5iahRFvC25vepsPMDhxKOcTKMysJ+TyEP0/+eUsYSCasnGClTFIpVKY/I4q1xVapcW9lpBeas48oJSV+bn52y1lmMpGRrQJL6nvbZiyp713fxlGuVuHXxuxkefgNSNsuHBaMfa4i5/b2H5iPr66ElU0E65wmX+zfStNxwolaRfPnwaeV0COUZgqHlO13CMeQ/HPi/0N1fL5p8aJwkJF1wuE+dbM4b3Ti8YwCb9vsh07cXGg0ZrakIUPEuaqc4/4xODgJNvUXrJmDNsOQHdD+Y7EPrz8KQvpD2DCIGCPGaJdvDd/dLsZqzlHY0EMYZkH0/QrYNpVKkWa+KkbrGyYidfjEYGBWQMrfsLqNYFi2RGmm3Z+CcBK1V1etVjBU2yBkILjYD1pF7WvI1vrvQ48eguVbqRQGSEtnUHuweeYtX66CVVGCoF5C9qnlbLc1wZ498Mcf1XB2XhEFux4ApRu0fRf6LhUOYb1+hV4LREaEXr9C74XCIbr+CPAQ8qlOr2PR8UU0nNGQrj92tXI6qCkyijJYdWYVMjIqhYqH2z/MtyO/5ZuR3/DNyG/47+D/muTgIk0Ry08vZ9PFTVZZAiN9ImkT3IY2wW1o5GcmctHqtSw8vvCa61hraPWqcBKTlFB0GdZ3F86pefGCNTv/DBz/+GbXsm5g586KM1Jch2wUdQ7HPxHzUgPDWgpCPrSEJbN/wh+QfnPSWBy8epDfjv1Gfuk/wCZZBbp3FxlDquXE0Or1qpl7vVvA7fF07hPKffdZO6rk5YlAgLVrrZ1z6zKaNoUXX6xaFnZ1hSefFO394Qf42DDd2VvPjPq9xNxE9l0VdnQFCp6JeYYzE8+Y/sa1Gmdynvvr7F9s31tA374iY8r69YKQbPZs+OUX8TdvHsydCz/9JIJT//MfuOsuEYukVMKfJ/8kfHo4e67sIas4i3F/jOOexfdY6X5qioYNRWBH+eeUkgJZ9hLZd/oMFK6ABDnHYE0Hkb0kKw4KzkPWQZuf/Pe9JCsbwsGDcPfdInilY0f46qtycnWLSQbSAkMnTF4Hq5rBxn6weShsu73mDY4cJ+p+eSkUXq4Gu74MPeYJ/ZSktHZWLD8PXvwV0vcwO242A+YOMBG91fOsh7eLyMYSnxlPwxkNuZh90Xyd6Bnm44Lzor17H4eERXB5icgmaomgbuYMjAAXfoK/WsKJKXD+Jzj5Keyw9VvZe3kv7b5vx4p4c+bmHYk7aPNdG9afM5Bi1DAT01fbO+HiKiFJ8N//CiZlozuJ8R1rNILp98knbS93q0Kr0xIzK4YSrZkJfMulLVzIMWcZic+MF0FGXo2h8WOiD538rxgz5TNOOok8IPc0HHwe0Is9Qv1R5my6ShfxV5wMOcch97g5w1D6HqZOtb7U999Do0bCbt+vn1gf1qwxfOkRDh0/E8faQtg0CE5NBZ0hm4ydjfLX2WbnXAmJ8R3HMyF6AhOiJzCk8RBzE0pz2XJpy3V8KDcZChVEf4GJQFNfBodfhxWNYdNgWNcFdj94U6voxM1DXmkeq8+trrKcjMx3B76r9vU7dxYy0datIhDVkQxzy06bA3G1ei39GvSz+r5fw36mTA5FmiLufVGkIJ4zB44cqVq3UV27rrs7TJ0qppU//hBs+FVdw/S90gVivsQR5/a6SEZimYEEsMlYAtbBJkfTjpoCNUHIxhVBkiAgoNzJVq9V7ccZ0KXW9WuxSbEoFWaZsXxgiUJS0NhfBKHKyBxIOlAje7vWsM9TK9Sm6xnROthMbKx0JNjmJmD0aPEely8XJACOjq0JqyagtyB1lpCQZWs7d5mujNf+fg0QwV0vvWTe9/zyizj3zTewcqXYh40aJQgAsi15NRuNB+/mZjmkAkhKN+bNzjWJDq++KoKiygdTX70KDz4I06YZTrgFQfvJVBj4bkCwTzoyCmRZXLOm2TKu5l3lnU3v8O3+bynW2Mmed4NRpitj5sGZKD5UoPhQwbRd0yjSFN3QOqxbB23awK+/in1KbKzQC9x+u0jO2LKl6CsdO4rM7888I4jbnPjno0axQ59//jkjR46kXr16FBcX069fP1JSUujRoweffPLJ9a6jCdOnT+eJJ57gScNOe8aMGaxfv57vv/+eTz/91Kb8zJkziYqKYsaMGQC0atWKgwcP8vnnn5sCYGbMmMGQIUN4y0Ab8dZbb7Ft2zZmzJjBwoULHbqvLMvMmDGDd955h3HjxgEwd+5cQkJC+O2333j66adr7ZncEKi9hGFrQy/BXJi8HpI3CPY9n1ZCGWt0sPgnoTQLCi8KJjhNHuhKzYwNxpVQkgxMNDKo/cWC5x4KbvVB7VHhpZ1w4p+C8HChhNqxw1rA1eng4Yft/EDpCk2fEexB5Tczaj/BSFTLOJF2AqWkRCfr0Mt6K0O3EZbnVArVTclYkleax+aLm7mYfZGhTYbSOrg1kjOC4YbjueeEQS0hwf4mTpIEm5oTTjhhH2q1YN7r2lXY2Tp2tN7oy7Iok5MDgYWJkFGOqSc5WXwJIoVQWDkDUlDQDXFU+XTHp0zeNpkynfAecFG4UKYvQ6PXcPfiuwlyD2LV/avoHtm91utSExxPO87K+JWAUCx1rd+Vkc1Gmr7//fjvnM48jV7WMyt2Fq/2fNVuto5bCelFZucChaSoNLBEQjI5yWktDOr2nkGETwRavRY1N5DevvM38HdvYSzcMlQ4vjV7FjwbiO/tscl7NRaK9oPPi8+lGbB/gvhzwokbAYUaev8unNR1JUL2v7Jc/N0q8GkOvRaKgBhtEWwZBkE9heNzYFehH8g+UvV1nLihUKvFHnXnTli4UDApKZX/AvYkvQbOfCOOmzwh+i+Y9Vgg1pHiZPNxWY4o1+0nwbRZdFk4pGwdKfp4YDcxljPss8XdfTfMmCEc4+wZclQq+2TltQK1D/RZChv7imeRfwZ23AHeTcEjUjjIZB2q8OeRkdCnD+zebb3v8/ODnj3t/EChgkYPw5mvrXUbkkoEAJR3Ov4XYeZMEYyTkyMcfz/8EJ54wpZ45PJlwYD3yisWJ0P6Q9R9cHlxBQZwWThz1sGgEhD6gSeeEE4e48eLcaFQmA22Ol05vYK2EEZcEMzk5WEcr8axCqArpsi7DZO3TWZW7CxyS3MBSMhNoPOPnekU2omJXSfyeKfHa1T/3479hs7ATqzVa632CwD9G/ZHrVCj0WtQSkpmxc6iUFNo0rH5uflx7sVzuCiFZVGWZZp/05zzWecBeG/Le9zf9n7Uyjo4PpRu0PsP2NgH9LLQ91/4SfxZoQ7W/UajY8eKrcfGbBR1GYnV1DtofAAF5J0xz0vlnalXtQC92ZEWgCG7Ibj2gwyzi7NZcHQBk7dNJqvY7AH/SPtHeCrmKXpF9ar1OtwsfPYZdOliMNE54nvk10bso8/+gP2M6gpBemVYY777TmQlSUur2LHnVpAv33tPBG3k5Nhvh1IpyJWmToUDB4QDybvvwq5dIuPJiBHmdaykBH7/HTZsgKjHvjc5FevRMyFmAs0CzUH3j3d8nKWnlgJQVFLGkAGuaErh00/hjTeEM2RFAS8KhVnVdzTlKAPmDiCrxNy/jWvR4pOL+fPknzzS4RF+HvPzNdlOPv5YOFNduFDx+zYFGnnUhx5zYaeBdU3Wwunp4q8CNG1cyqxZYm9SGUx9SuUJvReLoHG9wQatyRFkI+VRXefJNm/BlRUiqHz7GOi7QrRJlkGhNDv1p+0Q2UpMkKHgnAjAsnQqq2AejCuBCeWcyJILkq0+F2oK6fpjVy5MuoC3q7cYp5a6LGS48LP4qwjdfoT1XaA4RbyL4qtw7P0Kiz+84f9YEL/W7ndZxVkM/3U4/Rr0Y8v4LUhRUVXrncutfQ0ROnAjD+uiRfDnn4LpNzISCgsF+29iInTqVPmlbyV8vONjUwBRZVh7bi17Lu+hR/sPBaFB0WXRz9t/JNiq1d4i2Mk9zG7mzH8tZFn4UltOcxXJIEDzIbuZObOHVfBScrL4s4Rp2mzxophfrqwQmTiOvAPxXwlCBZWnyIhtQIYOZuYJB2ClpOS25rcxZ/Qc0/dFmiKCpwVTpClCKSn5aPtHDGw08NqfgYOQZTHO8vJEIKhxDyZJYh5XKMDNDXx9xf/VXjoix0Kz5+Ds95gc3Asvir/yuBHO7ZXJtvbsaaWlIqLUXnm4qTa4Wx3Tdk2jVGueB3c+tpOY8BjT5zELx7Dxwkb06Jm2exrPd3meQI8KCEvsYMYMsX5cuCD0DfPmiT5tL8OBLAvxYdHxRUiScDRXKVT0iLTen1gGmqgUKvJaT6dbt7kcPAhDhwqn85EjRUCkcfyA+KxWi3FmQzJbBR56SAQX794t1saPPxZ6IZVKjFmFQtTdxUWM3UWLhAM6ILKWnP9J+CZWFDDu3UpkmaxjeqMDVw+YiP/cVe7U86xnU6ZVcCuOph5FJ+so0hRxMfsiTQJEsEmDBiKTwMyZtrKqLAsnbyvUHwVhw8VaW9Gz6vBJ9Z9TNeecvRd3mGyuaoWaKF/b+7Wt15azWWfRy3qyirO4mn+1xvbpZoHNrAJZAII8gghwCyCrJMsUgFLX8N57sGoVnDwpshguXy6yRsiybVYOrVaMl8Mph1lzTkSJSkj0a9CP0S1Gm8rNPzqfI6lH0Mt65hyawxu93yDKN4qPPoItW0TwmE4nsiFZ6WYNsFofFSoho2+tJEO3dwsYuIEunqFMny4CWGRZ7B+XLBH2msBAEbi/bZuYR6xk4Zb/EcHkOccqDIoa12UpQ9v9zaaTgxkzRmLXLrGWV7Qv1+nMz0+WZVbGr+SHgz+w9rx5LzBx7USe7fwsz3Z+lnYh7Spsnl7Wo9FpcFVdvwy1JdoS3vj7DX46/BMFZQWm869vfJ23N73Nwx0eZvqw6RX6N1xPLFki9NkdOgiCB6j4uVrqup3456NGai8fHx927tzJli1biI2NRa/XEx0dzeDBtecQXFZWRmxsLG+++abV+aFDh7J79267v9mzZw9Dhw61Ojds2DDmzJmDRqNBrVazZ88eXn75ZZsyxmAUR+578eJFUlJSrO7l6upKv3792L17d+0FlmgL4eRn4n/fNoJVS9aaAx2QoSRNsNKWZYtyng3Bt6XBmCpDw/sdY3jw7wj918D20eI6sg6S1oi/8qiDEcDVxqn/waFXwa0ejEu1X6a8gc8zAgK73NBqOuFEXcCXX4ooVSNUKvH5vvsq+EHLl+D8HCjLtBYKO/5XBJ5UF9U0CJ6I32FVtKKMJUZo9BqOph2tfr2qiezibJaeWsrENRMp0dkqAo3o36A/X474krb12lpFmztRO/DyEhu5zp2Fvs2SAUSpFGysNpv1WwxKpZJ+/fqZjmvrN3UN/9Z21wTVbbdl+ZEjldx1l2Ar7tQJ2rWDMWMEq4FSKVgpVq8Gr6xE/jrbQlipqwM3t1plQc0pyeG1v19jdtxsq/Nlemt6yoziDPr80oevhn/F052frlPzs17W8+TKJ4WBXRZBFn/c/YeVAm9U81HEzBKLuUav4YW1L7Ds3mUVXbJCyLJMkaaI/LJ8copzSC1MpVRXSqB7IMGewXi5eOGp8qzZ2OvSBC4vRbmqBfT4HvzaI5xBLLRbJali/1OSRvp5CzY0WYtf+mYht5fb+/i5+qFUKK0CSkAoOS2zmRhR30ewROvRs53tdA7vXO1xUe35wzMKhu6GbWMhOw5OToOTU8Xew6OBkKey7TjLNn9OONfGvSScnypQxm050Z9ZW57F6+8W3HUfeHgIhZss2zroGI1w7u5w9KhId1uvnshMdL3iX69lzqmtuflG1Kkutvua4dcOBm6GzYMMwSWVKO7rqh4hYgz0WQI77wX0kLEbdtrXQd2QNtjzBKjKABwWZnvuH45Vq2D4cNi+XbAhf/ghDBhgNk7q9eb5DCA9HYKDa68+N2R8K9TQ+HG4MBsuzoX6t4kARL3GwCisEI6Uxz8o90MljLkAg7fAxv5QmADIkLlf/Nncx9zPFQph6OrYUTxDS8OmUinY8gzq1RuDoG7CMXz3g+aAtvxz4q887IzX6dOFg6olPv5YOFvaRZt34OI8oXM1evmovKFdxY5s/wa0aCEyd4wZI/YAr78Ob70l9s4NGoh+cvo07N0r9tk2xsuu30HaFhEUayW7KKDZMxBsL9Ln5sE4XnU6eOEFJdOni+CSGTME4+DQoRARIeads2dh/Xol7vqGDG48D6UkC4bm0EHWYxVsxmuJHn7Kk3g+vWLv6UMph3hi5RN8uO1Dfrz9RwY3HlwtJ9sfY380HasUKhsHMA+1B/0b9mfTxU3oZB1bE7ZalR/fYbwpqARElvunop/izU1vopf1JOQmMP/ofIcDX264bBTYGQb8LQJJ9WV25RalpKdfwFaQVCjdH6mVOtV2u//VupDERDFJVUfv4AG8IQG7YesowVLt29KQRVILujLssuaW2UtzcP1wIu0E7215j6Wnl9r9ft7Recw7Og+AuWPncnfru3FXu9dqnaqNhN/h8JvCBhc9QxC2mZ6lZNrbCztnurBzejcVzq0Zu2jv1Yif53zOgw/bmrklqYJM69HThbN83mnrMS6pxLVbmzMq+vsLmXLIEMjPtw2iVSqhvm2S0zoHPz8RCNKnj+j6lrpthUI4BX7zjZB3NmwQ2RXWrhUM0uvWCV/SyEjR/kuXxLOI7lbE6oPfm5zjIrwj6BRq7SE/uPFgPNQegmlVoUP2uwipzTh+XKxLsmx2iioPvR60WpnFp39jwqoJFGutWWQ1xgySCMfmuUfmklWcxQ+jfiDMu2b7Hjc3EVgyYIAwNdl7380tCZaj7hLBJXseNUQ3VUIrbJA7H30UzpwRwTX2AqKUynLbtuAe0GuReS9q7x7eLZAHrCcdN+bs+JTtCds5lXGKhNwEXJWulOpKCXAPoHVQa1oGt+S1Hq/RJKAJyn4rYc94SN0kMnw0Hg9hIyCknwjY9owSY7M8Ng6Ezl+LrCcKlZBfdKWUnwePl8LAq5iIXHxcfXii0xMmOSEpP4n5R+cD5mCOvx/+Gw+1h9BlafLgyFuV6rJM8rx7KAzaCn/3siM/mlGshxfSFSzIsx9UYoltCdsY+/tY5o6dWyNHrjvuEE6zzzxj7usrVliX+Sc5Y228sJEPt30IiAxG41qNY+Fd5kx1+aX5NP2qKVklWUhIjPtjHMeePUbQ0L0io0zGLjj0hghmCBsKPi3FvPxvJ/LwbQldf4ADz8Huh6HbDxAxVuwXdGUGGaQClGXxxBOQlCScVY26EEsolRbOqpICev0miFWS1wEKoWdPsM04+GUOaAxDXifreKS9tUzsofbgntb3sODYArR6LVsvbWXflX10i+hW0ydRJdauFc7vbm5in9mhg7DtVoUNG+DNN8Va+Ntv0KRJ1b8BhHNtcQpcsS+HgQL8OkK/ZbXr3F4T2bYmqGUb3D8ByfnJfL77c2RkJCTah7S3CfB+odsLbLiwAYBiTTFTdkzhf8P+5/A9AgJEpqF77hEkHfv3w6RJIotfy5bWQR+HD8PW/Rlsy9xmynoRExYj1lkLRPpGEukTyeW8y2j1WpbFL+Himlk8/4wrixcLnUaXLmJ8DRwo5MKyMoiLExnoLl8W5LPVgVIp5MxnnxWBK2+/LWSjkSOhb18xdgsLxXVXrxbj0hRYIklirtrYT2QXtdmzKyB8WJ0LKinWFFtl8Grk38iurqaJfxMUksIkYx9JPWIKLAHxrBYsgIICsw5WpRLPaPTocheTJCGr/tVaBCeX1681Hg9hQ6gWqjnnlCrh9DvidgCN/RvbtZ03D2yOUlKa+mpsUqxDgSVKpZKWMS2ZGTsTPXqUkpIOIR3slm1Trw07EnegR89WtvJqj1frlG7DxUXsPR96SPT9Fi3g8ceFfaNPH7NuOjNTBIUcPqJnfeQEE9GLUqFk/rj5Vs9tQKMBdPpB7NF0eh0T10xk5f0rcXcXY7B/fzhxwn72I5XKNqCF8OEiw9nh121/gEIEMxnG3qRJIoDko4/EdbRaERhX/h42wSt9l4vxXXTVzviWUEaO4ve1LRn7oMS2bWLue+UVEQhRfonSaODQIVi1poyW4xbz6IpHbfwAjPj+4Pd8f/B7okOj+Xrk13QI6cCuy7t4e9PbnM8+T05Jjs1vGvg24Pbmt/Nar9eI9Imslv5VL+v5/fjvTFg1gUJNod0yWlnLz4d/Zt6ReXx323c81vExFJKCk+knScpPIjE3kYs5FynVluLp4klDv4ZE+URR36e+GFOK6vXvhx8WwSXx8YJ0+emnRd/Q6WwDGLVaa9vaLY/KbK727K32BOvrbKO9cEGshTqduJ1OZ3+sGvUKxbWYeKfagSV6vZ5ffvmFpUuXcunSJSRJolGjRoSGhiLLcq2xqWdkZKDT6QgJCbE6HxISQkpKit3fpKSk2C2v1WrJyMggLCyswjLGazpyX+P/9sokJCRU2KbS0lJKS81Ry3l5Im18xKe+RNePZmtPgzEnPV1osrwVpLhm0erg6+hlPc1VOg5EGRRoD9hRXhcmwvZxVkwFchbEnoxhR9r9nJEeoUzlgYtHKUHBEiq1hEIpodfL6LQyGWlazp8u5uiuMsJIJi7WGxouh4w5kL0I0GGSAtADrlwNeogue+dQ+HkDJIUrX7d/h4cjbzO3AcBbwf9y/+KjhKXIsky0xo84VSrIEBPYmc09f7Bpd6prNm0OvoFG1oIskxtQCjnA0L2gVKPVwrxFLizd4sf+i8Fo9RKtonIY1eU8jw7dxLDz75KgAyQFTza6n/+1ecWmTn9rj3D3ya+R0fN4SRO+aE3lVEcWBr7zZdA7EYpkkBSufNX+bR6JHGVzj2k5K/kkcTl6vZ6WOi/ilVkgQ3RgDFt6zrJpd5prNi0OviaiH/Va1GiFQ6DKi809f6CTb0tz+aAg8Ib7D09mTdZh8ZyaGPpXcB8YYmCysXTC99JBkGG2L01n/QY1jz7ayvC+ja+2GK4sgMJtoLgiFnT3duA9mBNSMwZtv59iQ7u/aPcmj0WNtmn31JwVfJq4AlmW0S6Zh8+RPtb3AEhLgszvQbEL3BpCyFvgZmA4Om2IWri3VKQ5tGxHUBAEq4WjYGk6lGQQ1nggYSQT3Uko78T1UyBzNfAXKLLAJQwCHgafYTyy5X1WFK0DGZRqb9KGbkSlUNk82+Y7x5NalmvdB9v+H0TeYXp3cQd0PDarB8l57gztnMysF9bjJqXR49DXnJYyQIZ2/h3Y2fsnm/ed5JJJm9g3hNBsp59blTfUidIM4cRQlgP579q+7/LIPQVZ4n0f/PswnVWGoDnLOaSSZ8uah2za3T49nSl3BfP6omhAxtNVwy9P/oFyzSUe/Oo+Nm/0tH3frm9DyWsgGQLhfMdBXmfhdXCote37tkRJukirXZoO50/DwJdAY1usIhyf6Ik+SIcCMXM1TMiF5DirZ1vPS8ZVUqGRdcjIbCvcDp9IVu3evU3DTysDWX80jMJSNQ3CChjX4wzPDtvFxHPfsFa6BDJ0DIhmS88fxEbJ4n0nqNPocug9SvVlyHo9+XIlSkALbE3YSoeZHZCDEO/CvxN0Fx39wM5SflwexKYToWQVuuLvXcagmGSeGHwYlSaWzvUN+Y8deN8JGafpvuwl07xW0Xz+ec4qPk5chizL6JbMx/tIb+v3XXoRkmZDSRwoigULpLo++N8L3gMh3qBMdHB8r/t6PsM7r4eAzjD8gO0DsmThvU79vDWw9gMtj37WmksZXigkPXpZwV29zvDd4yt5ZPhYLhxLY1Tbv3jnPxdArQc3T2F8UagN41cGvU44ahWlETbsZ8JIZt9eC2E8NR6yFoBiHyj04NEZgp4E16aExYTZzmvp6ZBxFJgNihRwbQhh74JrY57a/AG/F60EGVzUfiQNXYdaobaZQ1rtfIyksmzzmvE70PVHaPqk9XMC85pRmo6yJIP+Zd/B2d2wCxhhHuAXjxUw6ctG7D5Xj0DfUt4ff4z7ex9iT/ZRRp79UZCfqbzY0WsObX2a2tTpwcMf8FfWIWS9nghFGVcN6/djDe9lRttXbfrgWs0hHjj1LXr0DMhqz/LO+x1638rSdPo3yBDMa9fY7qtpar6f68Ffu/1JzPTC3U3LgE6pPNjvGMPbH0W6/K7NfL57m4Yflgax/ngEWlmiS/N0Hh9ylLu6xZrLW4xvOS2dZevcmbKiDRczvIgKKeTtB09wZ/cjxB2/Uq3xba+fazTw5zIl3y8L5Xy6N8UaJX7eZfRre5lJt+3ix2U92LwtkDCOmMe3rIEri6FgJSiSQekFPkNR+t1Ff5/6sCcGcuDUgv189Uc4v2/w5/AxD44dA4VCRgJ0egCJR3oWCAfAamA9Q3m05BfCGiQTF2t4X7IWrvwOBRtAkSDkFo8Y8L0NPPsg/dW5Wvfoqwtmu9Kc+eK+8GGMjxyFIjcP8vLIdylhctoSjhddQavX8tya5/iw61jb8Z1yHLJ/A8UBw/iOgYBHwb216TlZvu9j+4v5+Jf67D8fRF6JGh8vDTHNsvi/+3ajLTxcrfd95OpB9l3dh4QIwXiw/nCizmdA+ilTP4/2VjDYrw2bck6i02u5K3s5fCuRfDmU9W57OHjKg0tJruSVqCjTq3B1U6DVyaDT4qrNIdI/g3n97CvsKkLo5CTCOGI9r6Wehqw/gX2gyANVIPgMRul3JyFXT9HKexloXIQCyx7O/WiSzwsFgTMqQCPL+LkPhVPJkH7Uag7xS09Cp9eiAJSyAp0kduZhroFIhwzBGhbrd4TyiuFmejazmdjkzcz8+DMUKi+29JxFR98WNvPaA4c/YLVhXmuvLOPYNhzel8hnh+A57wfCSCPu4LfgugpyVkHJUcg8AJkmod30GMIeTCKMZN79vzjuuKMPRM2Gqx+D7pLB71VhLu81gM/Xf8ya2J60zoUfKyGBtMK3El1ygDFiXivbLzFngSsrt/ty8FIwOhmaR+QyIuYCE4fvJDDnVciBXLc+rC2by4ETHpw5K3E6wZ1inRq1mwKNRsZNWUbLiAxu73iYp9u/bLPG7NtRxrRfw9gWH4ZKJTO2dwKvjNlH/+AEIQuXn8/LI/cUJIt5cNeiP+jVYKU4b28/bSyfBcrSdPIU63l46xewjUrft81+7Hcc2o8pS9PxSjTILb9TK+tYpe02/qbcHpGSDDSrHmVL3AAOuM/hQrIHJQoP/AKVeHmDUq0ECfQ6HSVFetKTitm8vMRCblFBg98h8RPQ7Lbtgx5dOZh8O51934UVDRxex4x7vnf/TzhtoMuHpD+hYB2QAQotKL3F3tVvLA9OuYfN68qs5VRNKlz5Hkr2g6IIlO6gjoTAR8CzF2Gdww3zeQPUjZdD9h+QvRjkIjDNqnpAAfXugbRFog013X/LMpSchJTFhjoVC8ZYpb+Qm31vg2l3QEV2azt4kAVsJoww4izanQxX50HxXrE3VrqDezT4DAOvvvS8rYRxnZbx8ovJKD09wd0XXP0FS6VSJdot64QRvegqJMwV13Ww3R8v/Zlpmb+DDH7uoRzq+xsBLr5WY6nUs4wue54noTS9wv138ulcvl8cxPxdjcgtVtOqQS7PjzrMPd0P4F32BzvuO8bKhqP54dJcRgz3xsdXQdu20Ka1jKenjE4HlxIkjh+X8PSSOTS6ep499vZj548UMGtpIMsPRpKe70aQXwljel3hqWGxeGWeEOt3LY7vBz99GxL688SA2QzM7QTB3SCoB/h3EBlCg3qI7CRFV+HYZEBH2IOXzXJL/YWQ8wekzQSKse7nEoQ+AqfmwowGpnaHAJs+KGL8f1tx8GIgSoUenV5B+0ZZzP3PeuLm+vHoax2tx54uH678BEUbQVEo5DVVMPjfCT6j4IyBQdHB+fzBl3qyeaWb4R6R0HAZpH0NeasMhRWYCHhUIRDxEhx6S7TDQj7vnJnOi0Mb8NWGlgB0b5XOUw0Xw3YXwvrdZn8/VvoY8AVIsrhPvXfg5BUOHl5PZzeDg01Fa4ylbqOcfF4cPI6dh73YsFnF+v1+pOa6U6ZT4OGmpXVUBiOjT9Mp7Bv6t1pV+T0sdECrz/3NA1v+Z9Irbu35Ix18m1cot1iNPYt+fuVkHj/8Gcif+6NIzXMn2L+Eu/ol8vSwg0R5bYGkeTTNgdjZccxeHsS81QEcOOHJxo2gVIgccXq9hELS063ZVcIklfV8DuD6ERR/BNJlQx+Uwf8+kB5i15R76OW7WNTLQkawlNfwNqwxBn1Z2OgnzP1cJUPpOUhdBkU7RB+UAKUneHQDn6GE9R1j+75T4iB7CXAYFAWg8gOvPij9xtFfkQInXmCQPzy44CSfzQth3W4fPvxQxYcfyigN04vY+ygZ2v9O/v61BW+M/owRmvtwj+wIIYPEWPVsJObliNEi286BZ0DWEnPOi5OSmb0u2MWfjj4t8NBJUFZGupxHXPElSmQNCbkJDF0wFDkIcpJ92eyzn/0nfdh33BOdpMTXT4GkViIpJPQaLcVFGrLzLnJy3HFTyHYf/454HT9jI6eOkkL5W9ajRKJemR/JLtkoERlOHnfrITxMLPrUwy4RvCnLKJHQIfPOqid4eeUTDunPZVlmbqiesWUa2AXJnY+wdrcvh+Ld2X/YhUvJrpTplCiVevy8NMQ0Tca3VSy/h79qkte295pNO59mtnqHIx/yV2YcyDIe7120eN8eQm65/Alo9trILUqPTnjlDqKz9l34urF1H7Q0OvqroDQDZVk2/Y0622roHdR7DPJaRWtGORnSas2oQp9qKr/mISFrG8a3LMOmDTq+WhzG4UR/CkpVeHload8omxdujyNAvZsuEXbWMTv3MM1rRqZ7B9exexe8xx964XAT7duSnztOpr3F+5O9JH4r3slrFxeSbMjk42swoqrUPizr8j/6BkZbvW+dl45xh95la85JIrL1nKjMCdMO1hcNZcKHs3iw6698+voqWN0WvBtByGBwCxHM6i1fhoJLkPg7JufqbaOg+8/Q+FHbixp1l4Z2D5n/OvtJqtQ+lu6aQ/ODr6KX9ej1egoc1CMDjF8+nndXjidRD14oGB42gJ87TsYru9D0LmQvia/z1/H+pSXk6IoYmhPN+i5x4gKO6pnsve/ysFi/Y//8mZj6l8At2H52lwtzbQNiszHr1yQ1D7Q+SuEkV/7zQ3MKSlQmx5RJY4/wn66xhEkjbedz6Q3Q/xekE2C0ELh1gOAPIHYBHHzKtMbESHDgZxfufS2S2LO+KCSxjsmyxMguF5j79E74bXy12l2dfaiNjGCQWxKT1cz93Y0/tgSRVuCBTpbw9yxleOcLPDFwPx1VT1mt39HAho80PDatFWdTfEzyWqPQfH56+W/aJm2HbV/imwOrPohlaT8/flwexMa93mRkSGRnyYL5WpZQq3S0iFlKXGmuScK6J7if0J9YzOeu3gpG+7Xn9/S9SBLMersd2VufY/6mh2nWtBOjx0jExAgCGm9vGVdX4aBSUgwJiRI7L8TyQfJDpkfS2COCz1u/RGCRDLm54OvLioI9TE8Um6NVZ1axcpVBLnLQPkbKZtj9mel9twT2z1HzwOsR7Dzhb3rfyHBnr3P8OH4XYdIwC7mlDTScB5cng+5cuTVDAu/BQCEk7hZy54hYptwF7bz8mfjf+mTlu6BU6NHrJZDg7t5n+fH5PYRJQy30ig2gwXy4/BboLmIlnysDIPz/UPyvod2mGrNHZBVnsfPyTnZe3imIc84NJXTBL4Qxlbit24W+8txswb4vAwoX0WjZbHQLezCJvlHb+PT1JTTe85TIhhsyCHxbi8Dq1m9CwQW49Cug5/EEX3KlXBTIKCQFG7t+Qxe/NhbzWgdaNCzh/y4tRkbP7su7aeKSSxinDe0eCpF+cHUyyKnW7ZbcoP4kwvpNMozvDDG+IxdCwidQulnU3/JdePbh7bNezCk0k2U+1+BuprWehJSZCRmZEBTI/zKW8O4FEZS3Mn4lfkv9RWEHxzdnDXaDHHh8RCwDl7rwxpfh/LExAEC8b1lCliXCA/KZOn4//GYgbXXEHlqSwd23qxnaagOdogvoPKQFuPuJtUjtI7yOSrNAmysCIIuSOLi3gM6BBnu0A/O5vjiN5r8+Qrpe2AU/aDWRSY0fsJHX3spYyHdJf4MsE6p1QVbIKACVpOTz8EdRHT5q+o2/t4JpUXfyxJkfAZmUghTaeWpEP9/zBWrVashbDUWxcPUvuLra/L4t+qB433Hm+Tx5F+SsAI4JmV7lBx7dwW806w/14NEXvKz3obIMSasgbwUoLoh9qGcP8L8L3NubfREc3X9b7UMN99CkwNW5ULwHFNlW+pbtpV7cvvcp036sQvtYOTm1d4Qfz9y7lEG6CaB6BkIHgn+0GHvtPxZ+AiUpgmACWayVv4yCEbG8extE+/jw5AeRpGS7olDIBiIhiZYRmcx/aRthUg/zvDb2Y1AMgeSpoE8DWTJ4fRp1eF34+ewJdBShADyUHtxWGG69B/BW8JA+lF/0WpQo0KFnbGQUYcSZ7SWyBq78AQXLQJEr7CVKf6GX8r+PwLX9yTJ011CXQAYFd6W9IgxVUQkycEnKYGfxaQ4XJgLQ/MDLwHRcXERQiUP4VmJoDgx9//9IcruHzQu9+Wy3ku2HfcgscEWjV+DmoqN5/Sz6tbnAzpORnDrman7fnm9DvSZC90AJJpkCwLM7RE0TOkJw2P49bGAQw1qvo2t0Kr1HhoG7P7j4iD9JKZzDNcbxfZWj6zJoX02bGmqq5VPxIAvYXDLQbIPTZkHBDshcD2VnQKERdnBVEHj1Ba9+hPUebG0f02ZB0kIo/BsU+aCQQeEDXn3Q+oylx5Z7OGOwAz/V+EGmtX7JZs7ZqD3KXSe/QkbPEHc9f7qVmdbvnHwl6/f4sGqDKzuP+pBf5oJCAX5eJQzumMDwmMO8pHqELMO8Nq3tq0xoMM7mHh9nLWXalb9AllkYJjGytMRK73DkjDtf/ezNlkO+5BS74O6qo2FoAc+MOEJ2828o0ZWgBHTITAy53WZvPMJLQZiLH6lluehlHXuevRPpoiDki4tz4GUkrafDzuEce0DNAv1ZvlscxOuvefDKKxLeXjJBQWKaS06B0lKJFiP3ou+qR4nomYM92lrXydDuIe6N+TnvMhISPwQUErzQjT86wPq+Z/jmj2A27fdh714F778nG+YQCb0shO6hd+7C78PeJrt/VfYxo57JLQd+7tKJ+zv/zqylQazZ6cNvvylZ+Ju4h3GtdHPR0sA3gzBJtp5r630FRW+BZj9m4jkJfO8A98fhW8muH5dlu/HWm3RGu+L20KuZQUZwVD437n0cWL+vpB1HL+tNsnNLZajdd9G0KA2NXoMKBQM99IzbfKewAxj6YDiwa2oRA17rTEa+KzLQOiqHjR8sQb0Hk+7SSr/m/hGUTgHpCib9mt+doHqCB0flsnl1EfWlKxzcflisw6WXoCgetJkIZZYMCg9QhUOOd7Xs+Fd8QKswa2Vbq8Pttrt5Yaa53TkdGRM3FuIqeRcWug2l1262slWMPRnaaPzt3qO91o2dgIyOEt0xHtg7CvZUvP+29NO08ru81+DrVB7l9vim/lGNfUnU7s/YNhSWjz7Hl4vqMfM7T778Ujw9L0/hVF5UDCDRcehBDqsOosBg9w8fTsS5NEg/YWp3R0u7v6zl3txVprERMCKW/T9IfDwnlM/mhqDRKqzk1OgmKfz6n12EST2t53N5IHg8AYXzQNKa2+J7O7g9bB57/p34YMxs7mjpzvMfh7L7pD8go1TI6PRCro9pksLjg88TJjW2Ht9hP8ClN0B7BCtiSZ8REPwhfsuj2DIY1vWdy4y/x/DO29785z8KAgOheTM9Li6Qmytx8pREWRm0+L/6xC/LMF1GJSnxUnqgQgQHlKChwOBTHZcSR6+fetl/X+WQkJvANwe+4ZsD3xjmfsfRqiiSUx6XTZ/rufgzKqQvgVo1FBeT5yKzJvcAl0vT0ck6nv7raZ7+q3oJDXrqgtitzKi6oAVSXqvHjHUvMf2Tl/jsM3cGDRLZyMPCZLy9hKmyoAAyMyWSk+HdfImialw/uqAJ57zPgwwB7uGs6vqFjSycoErltrh3uFyaAbJMnt7sU39bvd482eAO6herTEEc55UZ/JCzka25pwAYogvlb6Xw4W/gHsaTUWPpFxiDIjcXcnIpdCtlSeF+5qXtpMRAWCEfpVo2V8ZVr/zexl3p/pHBf+1+nXX2TyPKzSFNmjwIiKxd995b9T0M4Qa1AkmWHUoSDAgG2ttvv501a9bQoUMHWrZsiSzLnDp1imPHjjF69GiWL19eKxVNSkqifv367N69mx49zErGTz75hPnz53P69Gmb3zRv3pzHHnuMt956y3Ru165d9O7dm+TkZEJDQ3FxcWHu3Lncf//9pjK//vorTzzxBCUlJQ7dd/fu3fTq1YukpCTCLCKMJkyYwOXLl1m3bp3dNk2ePJkPPvjA9os3wU+G7Km2X+2NgB6GvaxahlnLx/Goaik0bwZhEeDtBa5uwtivLoJ6qwyO25Bb5EPnV7ZwLj+aFybq+WyahJubmIjLRzcpFCK67Nw5WNDyDSbrPrOuiAfQAghDSKKJwDk42CaELmNEhg+FHkbHw7LfbdvRZQIcDAckCNB4kaUqMK0JJ7+BVuXmt897whuDQW8YX9mHwG+FON5PF55kNsdoh0LEohp+pUeBTOtmZzn+YCvTtWKS4OAs2zp90gfeHwA6BZDZhA9njeFdv+kQCPipISIYAgLBxRXUKlCWgks+ND/HhhIYliSuo9TDU7Hw3Wrbe4y5T2QllSVw1aspVYiJylULhZ+Astxo/LsxDDUSPcgGUc/wnP78He48ZXuPVs/DaQPT5od5/Xi+5RGUPpH43LENEq9A2y5IhoAm2UWJNE0HBpLGcylNWPD6neb33Rp4FvAzXNw4v+kAJSxMDuCBgixTu9/ZDh9sta3TU7fDnE6G93dyHO8vaWrbp54A+hvuoQOKgHcAj0gSXtPj7VaIV5fXUbd+xqodsqsrLH0MKWem6VKT3+rP5ESLiqiAl4GOmPx+TP8fh7bF7pzwM4fwZUyFwHIRfTLg+i5oDN3r9EFo8Zd1mY0MYjQrKcMFHSoU6IghljXSMOq9l2N6d/Xz4Mp02+d0IhjaPm++YfY+b/zW5dsWrAAfvVK9952QHoW3h1hh/IbPQwrpXeWzjV9o224jttCfI3TgXn4nDLFYLwl8imM5frbvGyAA6AokA0cM5yKr+b4zQPOKArXOTnhmBdjYMoy9vdNQn9KhlOE/u62zBxsxszPkuorjsf7mdpfgyiS+ZBZPo0KDFqPXsB4lerzJo+0z3dkZetZ0rVkrYUI5pcDt98PaZoY5B+ibq6TlWR3NMmHQBWifZl2vfDWsbg7xQbC/PryZCf3WGR9DIG/yX37icZToLOqEqY5vtJnN65NeAxx73zuKoa/Bd1ahhweOwfxlts9pwHjY2hBRWcvxHQY8CHTCNGeYYPysCSEhT1Wt8Z2f54K3T5kw4A7627ZCRydbGR2vZz8vwZU/uIdMAunMQfqwE4DL/2lMZPQFqDcQ+i4BFz/xA1lvcLpLFo53xSmw826Qy5j8+CQml35pvngD4P8AV4tnZYzfXBrJ5INNrOc1EHPaJEN5445FD3wNfbt4syMk39SJznwFzbKsf17gAt5vmz+v0Hehd8RZ3BuPwK3Pt1XOIQDFi8F9ufnzeoYyhhVoUaJDjXGyvZs/GDngWR7rZ14zXt0N/91oXaccNwh+DbRKTKS/4uYw8iys/q38W4EfYuCZUaJsk4Io9jev3vteGX9t7f6aibzOZ2hQo7OI2TaOvQcit/FtdH+T3KJFybt8yH9522oOUaJFh4rHIjcyvs0Q0/gG0KHgAX7lD+4zqOKVpv/HsYTP2nyG/6Qz1Wq3sZ/LwFe8yBTeJo0Q03XLt6Nb4FmG58w2z+dewEtAK8xrqqgsaIHFkeS4XDa124gr1GcLA8giAB1KfMijO3tpE5nHV8PCeTTkBAqvULwG/AgpqXD3w0gaw8ZOpUB6SW+SS85lNmHBVxZySz1gItDYUCfLsaQEzkQSnZ/OIR/HFV/jL7elqXQK9SkdLTNgTLxtmTKl6IdFhqm3+GC58d0KeA0hj5Sv05pItmVeNr3veJrzNp+wlLvKrTHmdzGxzUI+mPQc4Nj7lmX4dI0/yoRsAO4+CY2zbdtxNATWNhXHLQMC+engLFYlj6X/AImJz8n0GyARGGi7Ymo0cOqknjsWqdGU6slwBxcduOjFWLd8TmVKIfe66eDJP8vJazHAM1jPg8ZnVQbnfuvFhvPNec7zZwj3h/rhEOAHHl6C2kSlBKkY1DkQfhCNJPPpWh9cL4k5Ydh56GiHj2BnFOyKFMcpUS0J9DyL+pSO8Hx4+Kht+SI1fN1VHJ8NgDkGm6NSB4MvwroF1uX31YfuE8yfQ4qVpLrpQAK1Di7NgHALcU8Gej4h1nq9YV/y/nd32spSQQhZ3cPwo3zgMhAewuSzA5ictci28vWBloZnnAUcAwohfWBzYkvDKdoTiLptC+SAQPQe3ijcXcwbQ70eSZbRlWrw8FLQtfAx0/hewwgm8g2XaIiEbDGHyCjR0SKyiOktQ1ny9wzmMp6opq48Pl7HsJEKOnSQrFhNdDo4dkzmxJ4zjNvQ0mqNmcarvM40q7GhQoOEzF+Rz1Ly2LFqzed7znajRbgY1P73HwIXX+uxVK78/2XAlCzzfmzRYrj3hO1jbvoinBc+A9Xej9VEbqnuOlbddm88PohHvviFLDmCH77X88CDEmoX8RCMmR/AOv3x5AYDbOUWEPN3e8QaUoDog9mQ0CYG70nnq9XuyS/cJ/q5C/AQ0Bcxzxp8u00wzLdLdj/OsZlBYiz5AHci9p8S9uXUvBAmv3Sf9XwOYvx0AHwN5Yzt8Inko7sb13z/3QqxJw7DVnY21sszhPU7Q+nucR7XiF64dnqzyrVyyYlxHPvDYv89CrjL8IzstTvfF7xzwbsZDNtvlmv1WiHbgpBtsw/DzntALuOj2Or18w+u+DO5WCxESj1MiIXvy+lPPu4L7w0wj7fy+++9dGMka8jDxyR/GWWY4axl2YgnkV2TTHOIFiXnacJx2nKV+pTiigotPuTRmpO0iMol/NFTlFYjtmTrXvN+TAa+5gVe5zN0KG3WbwV6preZwv2TvgJqb3wv2T+OY980tZaNGgLuiLHigpDTyhB92SOEyavt9HM10AyIQvSVVOA0EBDJtjaXreRUI/RIrOJ2ztOERlxkDCtQIHMutDcL0nuKOqmBMcAIQ10sn7dRH6YLYeX5qGtrtxE+iLUywNDmswj9ZUQkOdG2cqqxGku4kwyCeJRfcKMUIiOZLNnZjxkRAbQFTiDWYmo2r8UvhOZ/wWye5A2mkk0AKjTUC1fTrh24ukJ2NsQe0FFSAg8PXM70+4SS2JH5/INMmJyJaY81fyk8ZEfWafASJPqJY8t+DvA79/AksynG3Wrvo0SLGyUs7fgcfRrOt1q/AS7QiG30Iwc/lOgIJJOhbCA40p3Jhb3syy1KoBviPZ4z/AF7Bg6mo8cO3P8qtf1NBZjsapDPGyPkzfpUOtdOfrmV+X1LwB3AWIt6WZYHiAul+FKKVbv1SBymIwfpTAFeKNDjSy692EWzyBI+sGy3F2K8BSHGidpwH435eFZgDLs9DtPqsI6mWTDulK0uq1ANP3cSe/1DgW6EnpjMt+f+Q6u2Kt5/T8+gwRL+/vY0YIJwcs7jrShIFDaW7legX4JtuavesKC9OM72DsMrQujXPDUw0U6SI4C5HSDFC04HwS+dDI9RD8/vhy/tzCd33w1LWos1YJwXTNkQxUcbPmYR9+PqoWTcaB2duqjo2BF8fIQj8rlzcDhOx1+p3xPf/AXTPT7ZBG/ssr5+mRL834Aig+/H+z/1tz++/YF2mOWW40AWXGnWjvoXj1nZ0KvCyvdqV14DSMisXy392rb55vG9jLG8wVTO0hwlGoM+R8CoqxjbZgdzJo0Gam8de+psBD9yxfEHi/DxLDDokDzLhE0m3ByDxfedYWkrTANmxpVu16Z3UCLW13BEvY3yZxkiJtMzhONtXWkblQiNRkL/bzE58BgrEf8FnDWvvQ3PupEgl4AkTHmZn4F/ObXFwrbwwF3mz2MzVUQf0eKpgQePQkg5kksZWNMMjteDcwGwr7ELx/wdD0a5Efq15QdHk7rCj6c950HD+hBSD/x9wN1T7EFdNCAViWDrsIOgkMn5A7vrdzpBLOFOynBhMBtpzamq1+9OQAiQDhidWDqGUtwwxWYdA2GH3E1PVGgZzjqach4iI1n5WGitj29juy8TwZPM5m+GIKFHX447UoWGsEg189tIduU1HQpWMIZLNCSKRMayHBW6Ctt9mQg2MYhs/FGiI4gMhrMO/0hPPulfivpCOgB3nIbmmbb3OxQKG5qI4671oXuZ0KeW4sJpWnKS1hTgRQlulOCGGg1ulOBKKY2iitg+eAWu8aWo9PB0LHjZ6cKbGhlszUBZt+rtS8BWt21ELNHsoA8qtIxkDY25KPpURXJLGELudAUyEXvEImBEIMWumTb30KBiHcM5Q3O8yec2VlOfJHGPtHG28jlApOEeCiABOAVERPLmYCVblJfwLYEWGdAuDaJyQSWLuSDNE+IDYV+EWAN12U0YuLqcnkkJNELYKFwRetViQ1u8Qph8ppyeydfQ5jDADbNdVwsUwpxGnUn2OIz6lJZWGcJXoDx0EnzTFUoM3dhGn2pEI6C54R5XgJNAeCXj2xuxZ/dBrN+HgTzY27kdGzueQn1KS0AxPBln3y74Wzu47COOWw26dnsJQBJhbKMfV6mPO8V0Yx8dOYwqMrza9m8Tor+Ali9ZnytMFE4IFoSj1dUz5emgyzEVZzzNgs49x6HbVfNtNjWCNRYZfO5OaU17bTzqUzpaZMJYW5cddBJ81U30Qajgffsg9lXeiPddhNiL+oYwOdlCPlcDjwH9qND2eG5Hbxb82NPcz12BJ4Ge5X5jPN4Rycp61ZvPrfahSmAYcDdme125Os264M/TOrMuZPJW+L9yvqYlKiGnlhhEMRs51QcINfx5IOQQreFZFQH1AymWbOccHQp20IdDdEKJjr5spwNHkCqa1yTEfNAUsXfPQcw52fDD2M6kB4nx3SQb7jqJDXQSTO8BesMgs3rf/RA6uUCs7UoYPitDuGOnjuX1HHeGbC7Bql2RZG0IJ10dTlloFJqAEBS+3khqFbJShSTLoNchl5bh7g7NXScR+FcgbzOFn3gcHSqaNCije28XWrYUDrR5ebB/v56De3UoXdVMzLHjM6VG6DpDEPElR4EMqu/vYImYL6HFi9bnKhjfvsU5SAV6vHt+hBTY0Uq2ldVq+Hw0Uv4S02/+Tm9PV68L1dcrun0m9K99LN6Vqze4+ItsjyWpwqvbM4TJDxj0TB7AeKAH5vhAy4lXB4Xu9Qg7kkm+Smyu/Yoh9XNhX7LEQ3fAonbCp6KJGo4dAHm5O+8zmS94BR0qVGjwDVQTGir01ZcvQ0mBhnrNctDeFUaaqw5kYZM5MAvaWHSx7VEwaLy5fi/oYepRMZ8fJIaXmMEuetvY7Iy6yDaNrnD3gKa4xYv54vkD9uWW9U3gcKg4/vnYfuLzuhAdDbGxtmVtkH+O4keaWY3vYtyIJYZjtKMIDxTo8SafaOJoG5nFZ/2LTPLamHhoaWdYHQwX8zpA5/rQs8x6HStDzR56cII2FOGBC2UEk84AtnCiq57BI8X1lXoYcBH+nm99/d2R0OsJ8+fyeiYQ/hdb6c8FGlOEBx4U0ZBLDGQzV0K7mPWK5dEAYe/SA4cwjb34RjpabE+q8pEasadLN1pMqN3995fLQylJEgbKmGQYfMG2Hpf84Pc24jjQBx50tS+nXiaCvxiFK6XcyRJ8yatcTlUC3RHr63mEfhThx6XumMDoO9ZDkDtE3CVITkL7GwJWXYQ9IO8MrO0A+jKunA3BW1OIR5vxqBrfVeWc89XhUIqTHW+3wiWKJ+53XG7RyTBlrR8ul3IAGHUG2qTb3mN/fdjSUMjGX/R2I81N7L8VeuGX61NOxfhHG7j3bsMHGfLqeeDtWgTRH0Cblw1zhcWEdmIKnPzU9LG69hKwlSHLUBNLDEfoQCGeKNDjQx5dOECbyBym9itBeVE01hG7f/cw6Kq17VP5eLGBoVyiIR4UMYhNNOds5fsSX6AzQg45idCHR9q3G8jAeZqwnb5kEYA/2fRhB804y3lLu0F5NESMbx1Cnk8X94jvcNnKTqRDwSlaEUsM2fijQY0bJTTkEl04wIqxkeyIiKPdIT2Ns4WPraKcX26eK8zrAPkuEBcGl6MURCTqicyFHleEb4Gbxbp0xVv4bh8LEfqWJjof5jZ23LO/e0p9mqiSaXdIT0AxPHpY8BZbQi+JfclVbzgZDBlhbpxVlZDrCu4a8C0F71LhY6xVQL6r8G3UKMBTA9FFTVkdfo4ihdnGVhFUWnDXQeJJs74lC38u0ohEorhKfUpwQ0ZCjYZQUmgaWcpXt+1jfmiyw+1unhPMVe90Cg1yskondM9BhuiUXFcxTksNy6xaB146BdkujvuC9syOYrd/osPlAS4rQ/EuKXB4XvsisTuPBx93WK94pSSciFaGNamigLmjk618HF/76DVyTjejQedg+j0tSNBk2ZyhRJIkQ/IP8VmrKGHQk53Izc3Fx8enWu2vCtUKLPn555+ZNGkSK1asYMCAAVbfbd68mbFjx/LNN9/wyCOPVHCFmqOsrAwPDw8WL17MHabwSpg0aRKHDx9m27ZtNr/p27cvnTp14ssvzRPdsmXLuOeeeygqKkKtVhMVFcXLL7/Myy+/bCrzxRdfMGPGDBISEhy674ULF2jSpAlxcXF06tTJVGbMmDH4+fkxd+5cu22yl7EkMjIS3gTcoGDETjxV7laRkYuKd3H/6W8BUCLxeuBguvh3Izk/mZQCsSB75ZXgV6glx1OF0l/GQ1GGl6KU4qw2PD35ZwC2bxcps6qCLMOxI+s5f2Jnhfco8BERmaFeoYR5h/F28nzOFCaiR8ZN4UL28K24ZeWZIiNT3fIJO/4sMqBEQWePcPYVCYOBUlLycuMHrCLRZS+J5qdf4VyJCFgJVLqzps0bXC3SsnmfP99+8xIgI8vlrYEC0Z30lIxvyckcISG5SGoKR+5ElZltFaU6LnE6KzJj0Rus2X+3ep18jUuV7W7q7UWQhxtjLs5Ha3C0iPZtSWzfX20iYUOPP0uqJlfUAwV6CdNvTvX/k5bejaze9+c5q3jj4iJTnYxQoGBa60m80uQhm4hvr01jKDRE7QW7+jJl6Ock5CSQmJtIg/OZfPiatcfG95/1JrmxL43dfYhy96CsOJzibBmX4n0Md9+IhIyigoVmr9SAHmeElVElKRkfOYrZHd6zaffIS/9lbbbZWr2x9evklZmfbWu3ZO4LsPa618kSqbp6nA56D79O3YlLjquwHZ9NG0RBIze85BIaunvhI7WnOFsmOT+Z1IJk7vc/SHO3NLvt0MsSw9KD2ZibZjp3buBymnhGWj3bYo9SPDaPMZXprqvH6y2eMrWhtMSdb6bMobjYC9lCC6KQdIzsuZLtw+43RVP6qDzJHWHQFlm87z1yPD0Pi8VChYIHPDoxNnxEhX0QH/CWS/GQSwlz9aCsZV9SgqNMzwkgIL0A77xSVEoVOg8NcpB4CMb3ne/ZknSVX5XPtnz/sFcnnU6H3gcU3pjq5OfmR55/C4fGknEOoVFDMt1km3b4F+rI9lSiC1LgJxeb3refrg2F+Qqr6/vmFOFRoEGpVKJ30yL7iXbXd/Uk1NWN8Ho9iWgw2LozVJIN5qis5Hx+EZez0/jqmwlcOBONLFfkdSTToXMRPNKVY1mn0COjkpSMDumHm0aG0lKukMX2ArN29dV6vZjWZiJ4Nbe+lAN1OpeSx6efvkFOVkiF8yBATIyOWauOODSWGrv7EOHmzv37/iSjTAjB9Vz8SRn6N1JGhml8l3rq8Dn6BGWGVIQd3UOZ2/JFMvIv0It5qNCglAzzl29rcA8HXbFgVzdGfpe5ENfiQxKKC6o5vpPIKEhCJenxLSjCq6AMpVKBzkcGLzGvhnp4EuzuTnK9TiQHNCAh9/J17+fhrm4MDNqNUtJB9HTBUlgeRyfbMOwdTZE4HzCR5JIitCVneSpoNy6S1maekmXAvxPHwj+1Wos9FKW8FLwVV4XWKk2kLIMGNRMK+/Jbyja0hnfzV9cZ3BbSx6pPHZLPEb1vIhISIdSjT1A7hnS/h8TcxErXjPxGrjRw88KDUDSl9aBYJqUgmdOJemZ98TWlJe5Ya4MFPn5lOTPDnuNqYQoyMqGugVwdsg5FRqapTj/mruXpU19iTzht592Uo/1/t1ljJmcu5pPLK9Ea3bPIGAABAABJREFU0rhObfcEAQ27V9nPG7n5ECT7UOjemHw//2q3Wy6SmfVrdzasv81Obc3oHKNjzuyNpvf309xxxO4dbvcZAcRE6/hpzkar971myXPE7h2BfXOXzKRH9/PIFLXD49vYzwsz4YtZg9i1s5+pXEiIkBE9PCAlBTZvBp1Opm/fVD7+cA9piXFkFCRyh/sSAlVFKCTbt6XXS6SrO3M28GnSUi6RUuDYOqZpO5hk/9BqrWPG8ZpfcJY7PJbjoSgzzzvl6+XVEkWbeZAr5kqdrCOhKJm9ibs5kXGKGLdGdA5sQkSAHwpNrsgGBuDbtOL52Q4jsnF+Ts5PxqXsJI8G7jUw9NmplH8njoaJ8R13BqZ99gZlZe7I+orn884xOn6oxnwe5e5BY7ceNHTtZH2hChh65NIcGj45kSuZPjz2mILZs4WzlsraX8EKsgxSSrJtqlA765hcmkV6Xg5nZAVpmhJSCpLx0x7mfn+hPbeXAFOvl8hw6cyZgMr7lKV8HuHlRZOQ7jQIiHao3dV938Z2fJoZx5dpKzDwWPJh82doQxDk5SN7e/Pu1bnEF11BBiKkUD5qeA+PXfwKGRkFEk9G3cFHwfeIHMbATs5y56UZ4lkALwX35NGIUaY+5Ygs5ertR2l+ToXrWL6Pa7V+o/HUofAWj8IoSxnlu6UbGrFg3uNIkq5COaR9eygtyePMWS/GjVPw22/iPZdPn2uELMskJ6dz4dwu0hLjSClIZsnK3mxe+6jd8pKko2/fdD74Np4zJWdM8zmYZUitTovkLSMHSSaZIsgjyEYWtvyN5ZzTyM2HxKwCvr2wlwwyUEoK3ms+gXebT7Dq51pPHe6bb0cnywQRRH23QJ4b/EqVa0xyY1+H16VrWccqanf531juEZfOfIpVq/rTpg0cP27/nZXH0cP2dQjeeaUolUqH9gCOrGO67AK66X8hQJEt5li1DzS4TzBBKd0gLx6OvoeRMfBomprLfo/QS7kYb0W+9XqhdANdKVhIIUfT1Jz3e4bkkqJKx56pHe17VNqG8s/W2I562XF0RJRTKBSC+bXhA+DVRAQpp22FYx8Cso3sDFX3c7FW6mmmWUJbFzseHhbQu4agKE0F9zDkIbuRvBpafKkTz+fYh3DiI9PpuBIFca2mVCjPl293pJs7M84cY3XqQdPcOTqkH0F6VygppUCt58+snegN82QfrwZ80eRJLhWWkJyfTNwpL375dhp6vcLuvKOQdNwx8grvfXy6Ql2WvXktvMFgIur1FE2V9SSXZBCbuJfk7ES6h3ahaXA4ntoCu+v94uX92Lr+4QqfqyTJ9OmTzoffnbKap6oa37rCIPQaybTuhV3J5dkvd1pde/GLHSmqrzbvvz0bkC/5XJc1w14/bxjeym554/iuaM0o1CiI0c0lXJlsIRNJoPYV/VxrjrKseT+3v4erSbvLy6mKsG529RrVmdcs22Gp2zDOBwV5kXz0wb0cPNQSpVLmuecknnsOWra07k+lpbB1K/z2G0z6b5yVTGh5j/Kyc1pJNm8cE9Y9taTilSYP8t9WL1qtY4UeJXhvHmuaCftRn0lNHyM5P5m/t7dk+cJXsfX+MUJPp04Kfvmpcj2y8dmWlylqU27J9W6Ev3yBaFYBMgoXH4gcBw0eAL+2gv018wBsHwOyzmL+L6SzciNdPBLtyqgg2H7TVI7vfcJdPPFS+lHo2xCtpLZbvqJ2t4+MoYlXlHUFKtiXvDozhv8t70HDhnD2rJC9lBVvMQSSK5Hnwe7ep1LZuZwuK6comYCjU0z9q09AJ7b3mm1zjyanJnGhJB0JifoFnXBdspSLCfV56CEVX30Fvr5QViZkSeN70WoBZBKSL9D35z4ky+KZ9growI5ec6zqtFVzhAGxbwDCvvK8Xx/6B/V1aHyHeIYSVuxNz/8tIiQ5VTioVQJZkkgPCuJEmJJzn08iUVnosN6hKhmvKhkS7M85nvoSwqUgPKXmUCyzaFUrFv/xAMax7esLw4aJxCu5ubBhA+TkyPTpk8aH352uUN62N69VJXNatts4n9dTdWJC3A/szTlW6bN9r/5w3q/Xg1Nqd3rGfUCetrDS8gAvB/fggQ4PcNjdrUZ6h+u1H9P7g8IPPKRSwjw8WFWSzneZp0w2oD9jPuPO8EFW4/uxpO9ZkLbLZEuKj5lG8/CB1g2sLNO5b1P2lpXQY9djVT6nDyJG8n/B3TgcFEScm4vD8nlle6trXb+Ne3yNexhFxdTq+u2ojGBcY9Kbdrary7oe+1DLPnjycAjvTRlPUbHQGUVEwPjxIuOHUgkJCTB/vgj2r2gtrkpeq8yGU77dlrKzTR8Eu/oWS/m5uvK5I/08LjDAqs8an+u1jO+bIbc4ak8z3mNY61EVyweW7wLs7mVqS89UHbmlOnUy3qOqfYm9dlRap2r0qZrOa/bed2VziD17aKfSHPyKL+EZEIlb88dReNQHt1Dh3F2SAn/3Ab21d2RsCRxq8iYJOpVD83moKppXjs1nffpeqsJjgZ34IWoMar8WNdafV+d9Z+QnMMxtFRHqnAp9FwBkr5Ycq/c258+fISX/KsNcV9DQJavC38heLTjU9n/E5SRXS24x6lvaan+jqepihXsGgDz35oSdSKRIV4KERAefZhzqt9CqD64u2ceow+8DoEDi1YCBdA/oUavrWE3mtZqN70KiylYR43oUvYz5XUhKkFTW/TbXFdovYUdhMr9cWcXKlO1kaHKsbndHYGduC+jAeP+2qLQFVfap8u0+XdqD5995gaIiV2JilHz9NXTrZqi2ISBAoRA2kbIyWLYMWrWons+Uo7pOL7mEhm6e9Ck+R1DZedT1B0Onz8A1GFwDxDOyE1gCEFcCcRbjG6onn1uWr2hecylQEZ33G24UoFC5QbPnIOoeCOxsZt3OioP13UDWcjRNTZLfg/RQLsFbUSBsiAo1RIwF/46iPdlHIUEwCU5JUvJuod4kC6/oMp3RytamdSzfo5R6x56hRNagRCLaI5yP/N9gwgf3cOVqMGq1gokT4YEHICbG/Gw0GtixA7ZsgfEP7qb70pFkGvy0KkNDtR97Wz5NqsqXJbvDmPK/B9HphA7SxQWGD4ewMCguFte/eNGQdWS1Y/axqubByuS1XL/mFGhd65S8Nod8ZqVsNl3+lcYP0pYQKMhH9vLik6SFXCxJRUbGR+HKkhaTKpXPr0U2cng/ZsefKa1he7t+VhXJ55WNJXvrd9eA2x2z0YLDa+W1zueDvE/RQtoNHlEwaJPZFqEwGIMLE0WfzT1lysARVwJxzf6PBA211u7K5C/Lexh1IRGuHekY0AXJchGu0P6dzUeX9/N9xgFSSUNGtvWh8VbwTPJs5qRuM/meLGk2EUn2q/hd+IG3stS0xy9r1JcU/+r57VV3X3Ijxnd19yU1tRvU9viu9Fldo66zsvKlacm4SCokH2Wt3eN6+DtUd84xPtvWLe4yPddSXRlnChPYfGkrezMOE6ry4856XWkXHIGvysN0j0RXPzrHvkd6mZ1IKAu4SiriWj5L69CeZLmE8FDc/7Ej6zAFOtscKf5KD4b4tuDnyFF4KF2QfZowM/MoX1z4jbOFtkEmKhTEeDfi6wZ30MXF1+E5xzivuQb3tjv/X9P49hNzSH0PT0I93MhVN6JA4+VwP1fJngx6ec3NDywZOnQoAwcO5M0337T7/ZQpU9i2bRvr16+/bhW0RLdu3YiJieG7774znWvdujVjxozh008/tSn/xhtvsGrVKk6eNIfKP/vssxw+fJg9e/YAcO+995Kfn8+aNeb0pyNGjMDPz4+FCxc6dF9ZlgkPD+fll1/m9ddfB0QgTL169Zg6dSpPP+1YSqK8vDx8fX1NgSUnnjtB6+DWVmWm7pzKO5vfQWdYwJbdu4yxLcc6dH1ZFs6B33wDp07B0KHQowe0bg0REcIYo1IJQ4xGA1evCtl32DCHLm/CrNhZPPPXMyYHgTUPrGFEsxGm73869BNPrDSHJa+8byVf7P2C7Ze2o0OHl4sX8++Yj8ogsJxOP81rG18zlZ8xbAaTuk/i3Dno2FEI7Xq9MCTdf79whnRxgRMnYOZMaNEC+n/6Cl/v/xqtXjjYHn3mKO1C2lnVu/70+iTliyixBr4NuPTSpWq1u98v/diRsAMZGbVCTeHbhaiVZm+ptMI0Qj4PAUQATXRYNAeSDpi+X3TnIu5ta53D6OGlD7Pw+ELT+zZCrVDzbOdn+XKEdXRoTkkO/lP9TZ+HNx3O2gfXmgvExVnvqECEwEeXc7jLPQlrO4Feg8mxxq+DMLbKWkjbDcWXydRBkEVU8fAmw1n70FrKo+13bTmRfsJU95L/K0Fhmd5pXVfIisUyra0Jt50E31bW58q3w14bjDj/M+x73P53Bjye5cP8rEKTYHhwwkFiwq2fU3J+MuHTw02fhzQewoaHN5g+T54MH31knfnHCKUSIj5rSkK+YKtUSAq072qthVtg3bl1jPhVjBW1Qs1L3V/isyF2onNrE9V5tv9CPPsszJpl/Z7r1QNvb+GAXWiwYXbqBMs3J9LgywZVXjPcO5zElxJRKqqy8NtCr4cBA2DXLsHwDdCvHzz1lJA3MzJgzhwx99tNpVrF+35lvfXcGT8xnuaBZuFz26Vt9J/bHxD9eurgqbza8X5Y21EIh7IOIu6ANm9CYFfzfdK2wcb+5s/DY8Ho+Hsj+uD1vkfOcYj/ElI2Q0g/CO4Fvm3BqxEoXIXQX5wkmJ7zz0DhZYgcA4FdBNPDhp6QdVA8L3vwbgEDN4CnhaJ25z1wean930hKlnqP4M5YEa6vkBT8b+j/eKn7S1bF/jjxB/f+eS9q1LzDOwC89dZbuLgYaDsrWTPKyspMstdbb72FWu1C796wb5+5L5ZHdDRM+GEmz65+1nRu5X0r6dPAHOk6fMFw9l/9f/bOOz6qKv3Dz52S3jsBEnrvVZCOYsGCYhd7Lz91bWvvZXXtbXd1de3dtSv2VVRQBBHpnVACIYEkkDrl/v44UzMzyUySmUyS9+EzH+6de+69505uOfec9/t+f1XCk6Q8bHYbe6pVtoWshCz2XOebZuKijy/ihWUvuM7TJRcuYVQXj79ngL93w2MI9bjz82/kwgvd9rZms8qsWliobCA/+ww2bvS+9v79b7jgAhql4bX65ZdNt8Wac30D3HabenYB9O6tnmUnn+wd7L1rFzz6aD0JCY7f6oYbiPntXCh60525vAH1djP3b3ScU1fMIya9d+MH0FJsdardsn9d4OvIiSEOjl7rfT2FC2s1fDpIXfP+2jjgur731hUwZAiUlKhrKDsbrr8ezjtPZeGtrIQXX4QHHoD8/Ob9vYOuthUSE9WAySOPgIf+vlXwufaq1sAX41RmK7+ysjY4p4LA8zj+GfdPdtXuarS8571285DNvLTCf/IBT7ITstly1RYSzAktr3AYWLAApk1zt4tycuCGG2DKFPU+tmIF3HOPOqfWKVMllixR96zGBlobniMrVsQwblzg54vZXM/NN/u5n7cinnW6l3uxa3ZOG3oaLx/3sle5Tfs20fuJ3q3ybA24TgueYwFp5B6yfbv6O770kho4u+ACVTQ31/+m9u9XbeMW09R9zVqjBiwrV6nn0ZBbYfBNaqBSt6uBzbLf4Mvx3ttNGeh+XsSkQ/+roP+VKhOZboP1/4Df/s9d3rOd2tJj8HccRe8qRztQ79xT3ldtSLtFHQtA6a/ex9GcOq36Oyy73j1vToU+F0JiIVgPwNa3YZ/j4aLFwuhHVRvWWqUuWFOiylKmGaC+EpwCTFutypKa7Xb4Dea4qy3VZD2YRY21ptFqa2iUXFdCVoJK33XggAqe27Yt8D0BCD7bXyvwxhtq8NoToxEyMpS7hNXayH0qmOv73nuJcWQ7Coq4OFi7Fgoi0NYJFl2HhWfAljcAO5iSoO8lMOh6iHWkZtv2ISyY416nJddeO+Wee1T7PC4OvvoKJk4M/Ly0Wr2dooKhsq6S9AfSset2NDSO6HMEn57uHSj1287fGPvcWABMBhN/OegvPHjogyxapPpbrU04NPh9L4kGds6H/zn6prMnweT/qnPPc8C87Df4Yqx7ncOXwK5vvO+doO7VcdnqHrlvWcjt1IDP71bG+a6Xn69uCfHxQQhLIsCgpwexunQ1AKmxqez76z6v/tEaSw1J9ydh1+3EEMNNKJvVJUtu5IMPYho95z1/2we0B6jRazBoBvZev5fUuFRXueu/up5HFz3q6kNYc9ka+mf1D6r+Xn+/I44gxlN9X1wM5eVKkeFwta+3Wrn/c9VXHvE2YRDH0K/fjZx2miqfmQl33QXnnKPOF2cmvNpa+M9/6ikpaYXzNoR26v66/Ty9+Glu/OZG13d5SXk8feTTzBkwx2ts4ZftvzDxhYnYA/RRgG9ffjSxo3IH3R/tjo6OyWDi3BHn8q+j/+Varus6eQ/lUVJdgobGsNxhLLt4WbP2VW+t5+GFD3Prt7diw7sxdcawM7h3xr10T+3uf2UZN2gzNm9WP31lpWonPPssnHKKIyER6lq12VR/3ooVMGRI29ZXEIQIYq1W7+a6VX2qtqn3dc0IdXtBt6h+kMbe2f3cz+12O3PfnssHaz9wfdcnvQ8b9m0A1Lv6+SPP59ljng3jwTVA1+GH42DnJ+4xgOR+0Ps8iM1Ux7vhX3BAjcW7xgHWPglrHiZQv7OLhuMGwbZbVtwDy291z8flqMB7V3/LW7BHJYj4vz1G/lmBKx5h21+20S2lm2vV8z86n5f+eAmr3YpRM7LtL9uUQKEjsOFZ+NUZM6VBt2Nh6O1KaADe72zg0yewv24/i7Yvon9WfwpSW9bfYbHAQQfBH3+o/7//Xp1ejSXWairxVlAE25aqL4fqHcoFpL7MkWrcBrUlYKlSHQF1+1S/YZfDIOfgFlasEWz18HFfqNkByX1g2mfq3EZzi0pACUvmexxbYqE6Bt0KA66GwTcrkYy9Xl2K5ctd79+VNui2LYH9lmqMGDm096H886h/ujb17qp3ufara13zn5z6KQ9ecCQ//aTedz//HAYOVO2hhn0oNpv7PfjrjV9z6KuHNnnIf1z8B8Nyh/H776pfpq5OtbFuvBH+7//Ue5PzXcluh08/hVdfhbfeCvXH7RjU2+opfLSQXVWNj48BvHH8G5wy9JQI1EpoErsF3owD7DDmKdVP63lNBxCzATD1E+jaeNLNSNCc/rWG43y6QeeKcVfw8GEPe5Xr9XgvNpdvVtNpvdhwxQaf2D5BEJqH1W51xXf5Y+7Aubw852USYnxjI9aWruX+H+9nwdYFHDPgGK4afxWFaYFjMuusdXy6/lMe+vkhchNzuWnyTYzJH9Phrmen3iAcwpKQmr/Lly/nwQcDBzkfccQRPPHEEy2uVCCuvvpqzjjjDMaMGcOECRN49tlnKSoq4uKLLwbUw2LHjh28/LIK7rj44ot56qmnuPrqq7ngggtYuHAhzz//vEswAsp5ZMqUKTzwwAMce+yxfPjhh3z99df8+OOPQe9X0zSuuuoq7rvvPvr27Uvfvn257777SEhI4LSGo8shsLV8q4+wZGvFVgyawSU0aLi8MTQNZs5UH4C9e1XA46ZNSmhSX69epMxmFQgUEwO9erkbxsFy6pBTuWr+VdRY1eDN44sep9bqbnD8Y/E/MGDAjp28xDyO7HskaXFpTHlxCgAH6g9w3FvH+d12rDGWi8ZchN0OZ5+tBjbsdhg3TnWmDh+ujkPT1DvV9dfDY4/BpJ4zeXTRo67tLC1e6iUsKasuc4lKTAYTh/UJUU0DHNb7MH4q+gmbbsNit7BqzyqG5w13LV+y0x3VYNNtzBkwxyUsMRvM/LH7Dx9hyW/Fv7n+1gWpBS61m9VudTVkPNlSvsU1bTaYGZLdjB5k3Q6LznN0yugqG8LIv0Ovs9xlHIEtGQZI0uCAoy9ma8VWv5t0/rbO4/ASlZT+CnsX+1kLlaFiy+sw/G7/y5uirgyWNh0NmWOvxDNZbXltuU8Zz++MmpG8pDzX/J49KtDTn6gE1PloKc8Go+rMsut2qi3VJMYkepWrqHVnSdDRyYzPbLLuQuRYuFCJ1Zz06qVEG9OmqXmLRQWCOHWOBWkF/OPIf3DJZ+4g+oz4DOqsdVRZlAIlxhjDz+f+3CxRCcCTTyoHKoC8PFWfI490d3BZrSrI6csvVXBwqJwy5BTXvVND49vN33oJS77d/C1GzYhNt2HX7Zw0+CT45Ty3qGT4/UpUYm8QfWJqjWjDKCJtCIx/Tk1bDsCBTVC1RX3s9eqjGVUwXmwmpI+EjDGq/Kb/QNkvjW9//1r18u7s1C5fCUXvBC6v2xhtdT8jjJqRdWXrfIqtK1unRJyBx92D5vvv4eefGy9jNMLZI87m2i+vdV0Dx7x5TMDyfznoL3yw5gOXsGRvzV5sdpvP9bJz/05XQAhAr/RezTyK0LjOrXll1ix4+mno00fdC4xGePhh+PvfVaciwO7dcOWV3tvIz4djjlGDwl9/7ZsJ3mKByy9XbZpAzxgILaDMyR9/uEUlQ4aov2Fysq+DQF4e3Hmnes4BsOtrVyYhF5pJBcHWlUH9Xu9l9WVAmEUAqx+CyjW4BocSC1VHWOY41Tm24VlYcZdaZq9VQWCREJb8eWfjohJwXd8XvFFGSUkCNhscdxy89ppb9A2Qnq46rS+9FG6/PbzVNpngzTdVQNFttyn3mrPPhthY1RHvGcjbmOtEUOg6/HK+GmBw/v1SB8HA61S2vdrdanCu0qONGYlzKkSeOvIpTvjvCY2W6Z7SHZQJGLdPu51XVr7SaOATwM2Tb45aUcn+/d6B1FdcAX/7m/d5O2CAEqu98op6LysrU9nVR40KfjDObocwGKK2GJtuY9WeVT7f+3vetne6dVNt4CefhFWrlEjouefUOWAyqb+RrrufRRkZcNVVrTDY2hRbXoUKRybrsf9UIglnx4XzfdPgpxLO50XWRJj+BZjiVTsN1P8Z43zXCRd2G/x+HaBB+nA4ZIFyTgG3qAT8H0coVKyBP25yz/e9BIbfC6YU1WbXNMg71D0ArNdB1viwBvUnmBP48owvmfKfKa6kJLHGWDRN8+o/emPuGy5RCajnUlOiEnAH2YWb8nL1bHZaTsfFqXbT1Vera8BmU31Sd90VmfpELVvfgC2vqenkvnDIDyrYxrNvKKFr29QtSti4UZ0nug633KKCWxrri23OPTYlNoWBWQNZuWclOjrLdi/zKbOixP1CYrVbmdh9IjYbnHuu93U1fTrcfDN07api6e+7T73PRCW6DstuAAwqaGnG1+r9RdPU/6AGzCvXeq9XvR3+uNk9n9Ifxj0LOVPc3218ARZe7J6Ponbq7berhCO3366CbK67Dg45RCVg8icwKS52aSHCyvQe09mwdwMWu4WKugrlxuQRLLe6dLWrjazZY1zmOEccodocwb77Ot1b7bqd91e/z9H9j3Yte3/1+1jtVjQ0xncdH7SoxIcRI9QASmPU16tIpyjlEkeXZW6uSlpTWOi+vzjvQXFxqj3+0EORrVtybDI3TLqBy8ZexvNLnyc/JZ8TBp3gPa7gYHy38ZRdX8bRbxzNj0VqXE9DUy6RmoHXj3/dZ9wlmuia0pVpPabx/dbvsdqtfLr+U3Rddw10r9qzipJqt9v6OSOadh0JRIwphhsn38iFoy/k6i+u5uXlL5MSm8L3Z3/PiLwRLT0UIUzcf796/4qNVeLTsWN974fO+f7NvKUJgtBOMSWoj5Ok1hkbMRgMvH/K+3y7+VuOffNYDtQfcIlKuiR14eNTP/ZJ0Bh2tr4JOz5U06ZE1a/R9zK8BCO501QCI1DjAHt+9BWVxGZB7gzlkFH8hUqY4Swf6rjBvuXw5x2OGU31aQ+9TSWcc+4za6Krv+WSFBtPlbtXv/qLq5lcoBKv6ei8seINrHYrBs3AcQOP6ziiksq17iQuxnglTsid5j12HJvd6CaSY5M5tHfTooBg+OADd0KEV19tWlQCEejn9CQmTX0YHMGdBmD901C9TfWZTv1UORtoHi+Uno4GnjjHxUY/Cf0vd39vcLw/ebTpU4xw3qA5PPbH69iwMX/jfHo83sNvdbqndKf2zyNcsREvv6zaPoHeEz3ffQ/pfQifnfYZJ75zomuMekbPGXy7WbltZMRnMP/0+QzLHYauK2c4Z+zcp5+qfhDn9pzvSgaDelc95JBAP2DHJ8YYw6vHv8ohrzT+IwzKHiSikmhCM0F8F+V2tu8P7z7apojJCF+9IoiGhsVu4cuN3gkotldud8ViGjUj84bN63BB6ILQlpgMJp4/9nmuO/g6Tnn3FP7Y/QegnvHvnfQeY7uODbhu/6z+vDjnxaD3FWuK5fiBx3P8wONbWu1OS0hN4L1795IbKC0lkJuby759jdvVtISTTz6ZsrIy7rrrLoqLixkyZAifffYZhYVKfVRcXExRkdvGpmfPnnz22Wf85S9/4emnnyY/P58nnniCuXPnuspMnDiRN998k1tuuYVbb72V3r1789ZbbzHe6XUYxH4Brr/+empqarj00kvZt28f48eP58svvyS5mak6NTS/QfpbyrdgsatMhSaDqUXBkxkZ6jM28DXZLJJjkzmo20F8t+U77LqdLzZ9wReb/LvYHNr7UIwGI5MLJ5MVn0VpTWmj2z5uwHHEmeL473/VYAeoYMjvvnOP43iO52RnOzpd66a4gp/NBjNLi5dy1gi3UOL3Xb+7pq12K4f0DL31f0ivQ7j5W/eA45LiJd7CkuIlrjoAnD70dB5Z+AhlNWVY7VaW7Vrmtb06ax3ry9YD6m99SK9D+Hz95xQfKEZHZ+O+jT512FruPmcsdktIwiMXW96AMoe9bXw+HPG7b+PQEdiiadDLDMsdlqDFBxrYO6JU6vtq3fcFn8G6tY+phqvuJ+2hblWdOs0Vlqx9UmUDaYghxpEVW5Ft9A75bEpYYtAMZCe4OzjeeUdlKwiE1QrVe/LQ8jRX0ExlXaWPsKSyrtK9jt3qFUAjtC26rgJ6jUYVHHTCCSpI0rNDwmxWA/annqoCwQEuHnsxJqOJCz5WFgWpsalsqdkCQFJMEr9d8FujCtrGqK2FmxzxYfHx8MUXKlgA3B1czv+nT1duBKEyNn8sXZO7smP/DgCe/vVpyqrLXMv/s+w/rnva2PyxFJiA4i8BXWUJGuxwOGtpMFx7wpwE6cPUpynsVvjj1qbLgXen9vp/qI67RpwZCox2UmOTqajbj8VuYU3pGp8y68rWqYFqWv4yfOed7usjEFYrxJnimNlzJh+t+6jR7TkzXq3cs5LFOxdjtVux63ZKqkp8OtOLKt1tv6SYJNLi0lpyKEHjvO+fdJLKROM8dmeQvcEAf/2r223koYe8nxVXXqnEJ85ARKNROVL84x/uMq+9BuvXN12XxkQngXj2WXWPiI2F+fOVK0agznGvTtk/70RF9zh22uciGHYPxGUpceqaR2HJjX62EiZqS2HV/bgGanqeAWP/oZ71zqDc/NluYUmkqCuDtU/g1cLQTNDlUDAmqPaNo42yZXcu//1IDQCOH6/OJ6PRtzPcZFLf3XNP+Kt/3HEwaZISmLz/vgp07NNHCQKSk5XYxGKB6mqVObOmBj78sBk7Kv7CW2Dc52IY/ZhDjGdS98mUATB/csBNRANH9z+aK8ZdwRO/qiQLOYk5HNv/WJ5bqkSH6XHpfHnGl7z69KsAdE3uyl3T7uKW724B1D1vcsFk/iz509VuHps/lisPutLP3qKDF19UDpe6DmecAY8/7lvGeT884ww1uHLCCeq+t3q1clebOROSknzXczrAgRq0WbnSe/lBB8Hxx6t76iuvqHOwLVi/1/cGvb5sfas8V6MRs1klchg+vOmyYUe3w6oHAU0NRPf14xJbVeQ7qKlWhsQeMH2+GszWGkTXRrLduv19JUQGGPWYEpU03H/A4wiB36/B9Zwc9FcY8TePDCJtl75+UsEkvjnzGw555RDsup1YYyzJscmud4835r7hFQRaUqKEvJ7tzVNOUe9pXbsqwf1998Ea32Zv2LjvPpU5Wtehb1/VpiosdL8nGo1KaHXMMUpY1yx+/NG7kebMiA9eWfFdZGVFl1sJqPYhGphTYMZXKpCn4YBlKAOYHZD//U+1rUC5xYXLWWJq4VTWla3DYrewc/9O9tftJznW3Xe9omQFZoPZ1fc8sftE3nhDPbtB9bnedx9cc40782ffvqrP4bHHVNsx6tj5KZSrASpG3KfONUODQBh/WRhXerxjdD1KuZw0JDV6U8IbjUr4e+ml8NtvsHixEgGXlrqFoeB+H+3WTbmchztgalLBJJ75ze0Kv3z3cq93/OW7l7um7Qb3C/RPP7lFEMGQZE5in0W1q8/5yH8Qvo7OqUNPDX6jHZAah3HYf/+rHh2B/v4tSibQQpJjk7lqwlVNlkuLS+PrM77mjPfP4J1V77j64L858xum9ZgW3kq2AmcNP4vvtnwHwI79O+jzRB/MRvXD76txj6201nmbmZDJS8e9xAvHvoBBM0igTBSzZ49yj7RalXh53LjG2wlteb0KgtDxmNFzBisuWcGApwdQa62lV1ovFp2/iOzExkUArY7dBkuuAGef28Q3IP8I3z6Uhn086//lGEtzxCAMuQWG3O5eb89P8NWk5tfr92vc08PuVk66jTxTB8VCXkImuxzjrO+seof3Vr8HKIcyZ/vFrts5eVD0imJDZsOzqi8PYMIrykUSvP9+EWyLlJS4d1dQ0LzEbZ2GlfehxvzPVcI1z79TY44G2KH78d6iEs/1GvR1XjH8FB77o+mOs9OHns4Td2tomuqHcCb/DJYj+h7BT+f+xNQXp1JRV+ESlXRJ6sJP5/5Ez/SegHqH/tORz+iRR7xFJQ0xmSJ6+kYlM3vN5P4Z93Pjt2psOD0unRMHncizS5WrVfeU7iw4e0FbVlFoiKbBId/Dt4fAxufUc3LoHSoORbcr0cnsP9VYNwaoK4HaMkjp6+2C1gFYsWcF1355rSvJn2e/lE23RXWSCkFozwzIGsBvF/7GPT/cQ3V9NXdOv5N4c3xbV0toQEhDBTabDVMjowtGoxGr1U9weCty6aWXcumll/pd9uKLL/p8N3XqVJY6JecBOOGEEzjhhMYzzDa2X1CuJXfccQd33HFHo9sJFpPB5CUScLJxr1tM0Du9t8o0HoVcNPoiV0d4Y1wx/grX9GOHP8a89+e55tPi0rDYLC7FuMlg4rljVHDWe++5G+lvv60GNv2dms4M38mxyYzJH8MvO37BYre4nEKcLC1e6iX6mN5zesjHPLrLaJJjktlfvx+zwcySnUs4d+S5ruW/7fzN1SHQM60nhWmFTO85nfdXv49Nt7GkeInX9laXrnbVx2q3Mq1wGtsrt7vEG073Ek+2lG/BoBlcmd2aJSzZ/DKugNGD34SY9EaDawbEwAqL2md5bTl11jpiTbGu5cX73WITs8FM34y+7pXtVtj+kX9RiZPGljWG3QrrnvIOvO52nHJfSe4NBzbDrxfCrq/JMeJl/O4phPH3nY5OTmKOaz6YABFjXSZGg9GVVb+irsInOLqirsLrPMxMEMeSaGHxYuVICyqw9uWXVTB2w44Cg0Etd7oAAJw/6nyW7VrG04uf9nIaevuEt5ufFRH45hsV0AsqyHjw4MCdGmYz9OgR+j40TWNQ9iB27N+Bjs6KPSu44/s7XMs9XSKG5Axx3D8cXrPD/EQ+B8pc0lnZ+SnUegjyDLEw7E5lk22MUwGTy2/xXsdaBZtebFRUAqDtX80Yo8a3jgyNq0t9f/NVe1Zh020YaFmv6Zo1KhAqWJ47+jk+fvhj1zPRH4f3OZyMhAx6pXkLaIsPFPvcOz2fMz3TegZfkRZis0H37vCf/6i2hr/rz2iEkSNh3z7vQMgHH/R2PHFyxhkwzEOT9OST7kAfUAH9//d/KjHq8uXwxBMqmDFUqqvVfcxqVZlH8/ND6PgsXwYGxyDAiAdg0PXuZZoBsiMsAFj/tDurWM5UOOhFXPchJ23RXt70kpeIlfRRMPVjSMhX8x6DVm8vOgmDQcdu13jtNbfznj+acq9pTbKz1fn2f45kYlVVUFSkgtGczjwJCWrwJSen8W0FZMU9uNqd/a+C0Y96LzeYvLP2RzGPHf4Y68rWMX/jfEqqSlyDghoaH5/6sXIs8eDmKTeztmwtryx/BR2dwrRCfihSqbbyk/P55sxvIn4MofD22+r/ggL4178ad7k0GFTQ98KF8PvvSqz0zDMqcDY2Vp1HCQkqsK26Wt2bTj9drfvMM97CxccfV0GSFova3y23wMUX+99vuDBrZiy6hcq6Ssqqy7za7K3pBiY0wu7/wQGVKZOB1yl3Ks97RaMDmyhXK2Ocb2BxpNupG/8NGCBjJORO9V0e6DhqfBM6BMSyXwm/dZtyzBt+n/o+SkY8p/ecziOzHuGqL66isr6SynrVsLlu4nWcMsQ7i92//63uD06c7SlncPspp8CcOXD44e5A2XBSV6faana7et969111T2zYJjQa1T2w2QSTET+a2b8R9v6mpgffBPFdwyOgauc43ZchvH/uid0negX1r9qzivHd3MmV/tz9p0tUUphaSHZCDrff7n4nufdeJZYCbwEVqDZjI/mo2o7iL5XAO6ErdPHjUF1X6v954Zl0Z+JrKiCtoQAqSvvlPTGZlCj3oIPauiaKyYXu90WDZuDPkj+9nMP/3P2nS9xk0kwubc977ynxy913q7Zlw6zCuu4WZwGMzBvJt9u+bbI+JwxsfEyoMzBuHEyc2Na1aB1iTbG8ecKbWN6y8NvO3/js9M+8XOujmSP6HuE1v6l8k99yWQlZXuMSLaW5LtpC5PjPf1Qb2GxWwpJwiU8FQejAODt0naxu8O7VcL5BsoLCtEL2Xr+Xoooieme0UWxK6ULVbgfodxl0O7rx8k72/OCePugF6NVAcGyIpdnUl8Pu71R/S84UGHJzk6sAnNrvMB5d5g4s8OdobTaYO05mZbsNNr+q4j26Hg0Fc33LRLhPYNAg95jb99+rBFsizPSD3eK+7jJGq7+h5vFDBXqXdjLgavX3DyKxQ88YAxO7TeTn7T8H3FyMMYa7Z9zN4MvcCV4aG5MIxPC84Xx71reMftbtuvTDOT+4RCWgxjtMJkhMVAmymmp/SfsMbph8A6vLVvPyHy+zr3Yfryx/BVAO1fPnzScjoWO4XHQoknvD7BWw5XXY/Ap81Eu59WZPVjGCpmQ1zm2tVC7w9eUwK/A12t7wjFN5bNFjLndUz/inBHNC82IuBUEICpPBxB3T7mjragiNENKbn67rnH322cTG+n/JqmssZb8QEjbdxpaKLV7f6brOtsptgBp4ieZO8ZOHnMy5H51LtaU6YJncxFzG5I9xzZ8+7HTeWfUOH6/7GF3XueHgG/hw7Ycs3L4QgH8d9S+SYpKwWODjj90BR84M/YFwBuZNLpjMLzt+AWDR9kUMfGqgK7HFjsodrmD+Hqk9muUUYTQYGZE3ggVFC7DYLfxzyT95efnLruVV9VWuxolz0HZa4TTeXfUuACVVJby07CVXpsDvNnsLc6YUTmHZrmV8t/k7LHYLB+oPUFFbQWpcqqvM1oqtGDWjqxNiYHYTP05DrDVQ8j/ADoUnQ07TwaG9zWD0ELMUHyimR1oP1/Kd+3e6N2+30jvdwzah7FeweaQk9oetVr1khmI9C7Dra6h3OyvQfS5Mets9n1ioAmLnjybb42XPqBmbdCyx2q2ubCw7d8LPP7s7IAJhqs/yyl5cUVvhU6aitgKDZnCdi+JYEj18/bU7qPHxxxvPPmEywYQGQv1HD3uUP0v+5IetqhPzwUMe9BkwDJX//lftKz7e7abSGM3t1Dhv1Hl8tekr17zny5QnV4y7An49HrBD3mEQn+ddoLEAv1CC4zoSm192OzZpBiXm63a0O6tS3qG+wpLtHzZ933QwNlbn+1ojVruNXQd2UW2pdmVb0HWddWXrADC2MFP1u+/6upXk58OMGWrM4ocfvMvnJOVw+djLeWrxU6qe+WM5Z8Q5XPKZSj+aYErg+WOeB6Bnek+vc654fzF46EpsdhtlNepeb9AM9M9svlirOdx/v+pwbiyjkcGgrldngOOECf5FJeAWogBs2OC24wY1nvPbbyqYBlS2/osvhtHNcJz/6is44DD0uuSSwMIYv2gmwALdT/AWlTiJ9MDSzs/U4I1mUoNDut72KaZ0XWXhckaWpw6Gmd+AycOawRDnmnz1p3nY7cqtJBh3qYjarnuQmNh0uztknEKlhAIYcX8rbzyyaJrGi3NeZNAzg9hbs5e9NXsBuHXKrRxccDD19fU+6zx2+GN8tv4zymrKeG35a67vXzjmBa/s4dHG7t0qa7TTEt5sDn4AZ+RI930OVADggQMqoNZsVgI6XVf3V4AFC9zPl0ceUaIS8B7se+IJd/lIYNHdUYvr9673EpasLVuLxW7BjIxGhkwogQ7lHoGieYf4CtAaG9iMzYL8w72zWLZVO7VqG2CH9JH+R0IDHUd9efD72PWVO1nDiL+pjGNR5gxxxfgrWFK8xDXgOLPnTO6f6X1RW60qk75TXHnjje72lLMN42yTff21EpmEm0WLlIskKEeAIUMCN0Ha6tkdFWx9w33O9TrLv6ikpQKqDsCIEe5+pY8/hqOOCs95c3DBwV7zK0pWeAlLnNbzJs3EtB7T2LwZNjlim0eOVAGtgc5zo1E5uEYdlgpAh7gAgdixWaptHui5MeIBh8NVdN072yvdUrqRn5zPzv070XSNpcVLqap393EsLV7qEjcNyx0Gu9T3EybAAw8oV8+TT4YxY9S7cHKyekZs3Ai//urez+1Tb+fbVxsXlvRJ70N+Sn6rH2OrsmyZ+2YQqG3UgkRvuq4CpSyWjhNMZ9AMvH/K+21djZDJScyhR2oPnzHBhpw25LTIVEiIGjZuVM/eAQOiVMApCEJ0U1QE/fu7X179MW+e93xcHKxd6yUuiTfHtyhRXovZ8bFjXAIYdq/v8kDJQjSjGjvofryvqARa1sbfOd+dAG74fSrhpef7boA63TP+Uh5b9kajidfmDJiDoa3HOFqLPQtUpnuAnmcGnxwmjH0C06fD2Wer5GtnnKHeI3JzA4+ROROadDo0k3sM27Lfd3lj79IJBZB9sO/3jfR1vj73dfo91Y96mxpH+eSUT7jks0tc8XFPHfEUJoOJrCxYtw62b29+3pxRXUbx5bwveXbps9w06Sb6ZPTxWv7OO+o167TT2neul0jz9JFP82PRj2zat4kaqxoUf/KIJyUwP5oxJUKfC9THblHJmSvXqsSotnolDDP1gYJTlOikA5FoSqTcWg6o+Fybn6Suk7q3wNVMEAShAxDSG8lZZ51FTk4Oqampfj85OTmceeaZ4aprp8Ku273cSUA5JjgbYAbNwODswW1RtaC5bqI7arJbSjcVIBXjDpC6Z4ZvNvu7p9/tsvp8avFTLlFJj7QenDlcnVs//gj7He8uc+YEP3bimSVYR2dN2RrWlKrP/nr3y1BLXCLyk92DUXbdzoH6A66PZwdBYWohACPyRnitf/aHZzP37bnMfXuuK+AWlAK/MK2QgdkDXYNroIQknmwp3+IKwM1JzCElNiW0Ayj53p1du8cZKotAQxpkjehjBotH0O+Oyh1exXfsd8/r6N4vZru+8rWlbUjlatWhUOXr0NIom19xdzKlj4KD31DTzk4izeAatc/xqIJBMwQUlngKQ5yZwf773+CqY6zP9Mo6Ulnnm2K+4XeZ8eJYEi188YUKYhowAI48sunBVluDS8dsNPPfk/5Lelw64/LHce3Ea1tUH5tNZfu2WlVG3nAO/p448ESvDEQGDBg1o9f1kBKbwoi84VDtuE67HOadqR8aD/ALJTiuo1BfDts/9gj0exC6HeN9T/QXoL/9Y//3Tc+AdQejYsHqcR/fsHeDa7qspsz17GusAzsYPvjA+5w/8UTVqffKKyrbzwcf+J6jd8+4m8SYRHR0lhQvYdnuZYDK7H/dwde5XEl6pfs6lnhSWl3qurcaNaNXRplwYzardkgw199PP7ljQf7+98bbLs6O0LffdgdtxcbCJ58owY7R6P7k5MCnn6qxnlDYvds9PWJEiJ3iulU9X0c/2qRzTtixVsFeh51Uz3mQ2NM7+1FbsW8p7F+rpjUDTH5PXaN+rN137M3nz23DAI1TTvHOstupGHKLu93WjslNyuWV415xzY/vOp5bp94asHxGfAbPHa0cGe0OIdLZw8/2ytocjXz4oXv65JNbNrBmNkN6uhq8y8jwvac6tz1mjHI4iTacIk0nToewloo2Ox3OQIfRo92fhoEN8+a5lz1wr9LuaQb/rkbOgU1/dD8BCFLAAeFtp7oCGAKk1wt0HEm9fL8LxHZH8IU5RTl7+Qvq37u0Td0iNE3jX0f9i1ijSmLz9olv+2TP/v13KHY0A3Nz4dYAt1ajUbW5rrwynDVWfP21O+HArbe2va41ain+UgmasidBnJ9oyNYQUHUAJkxQgiijUSWOqKxsul3YHBe7wtRCr77ZG7+5kZH/GsnIf41k2D+GsbtKvShYdStj88fy/ffude+5x7evoyFR2ZY1pwEa1OzyvzyxAI5eC4cvgamfwIRXoctsde80JUPhKb7Pmii4d7ZnnG7WNmy8seINku5Pcn3+t/V/rnJ9Mt19yPPnwx9/wEUXKbHTtdeqpkOXLspJ9Mgj4aOP3Ps4qPtBdE1220X1SO3BpIJJXn1Z1x/sJ1FCtDFpUtNto0kegQ7btoW8i5EjO46opL1z4egLmyxz+9TbI1ATIZpw5nMMkO9REAShcUpLGxeV+KO21jvxRzSw7T01LpEzGWJSvZc5hQnzR8PCBu0l3abG00Y90vpjGds/UNuOzYKsCb6ikgB1SrCVc+nYSzE4/s3sOZO3TnjLtTzGGMMTRzzRunVtS4q/cLxbJSnHkmCTw4S5T+DJJ2HqVNixAwYPVkmLivyEolgs8Msv6v2j06FpkDtdnecbn/MVYnm+Szvfp7MnAQaID10NW5hWyBXjrnC9s72/9n2XqKRvRl/OG3UeAOefr8p/9hksWdJ8nf2hvQ/lnRPfYWSXkV7f22yqTwZg6NAW6fg7HUkxSbx74ruu+bkD53L+qPPbsEZCSBjMkNJPJUHtcyH0vxz6XqLG37PG+T5/2zkze830mjcbzD6ubDdOvjGSVRIEQYg6Qore+c9//hOueggeGDQDduxsKd/i9b3nvNVujXpl7/UHX8/DCx/mQP0BtlduJzcp1xXE2i2lG+eOPNdnnaG5Qzlx0Im8vepttldud31/9/S7XQ/xb75Rg/cGgxo0CjaD39kjzubKL5qOLjim/zHBbdAP5408j7dWvtVkuUvGqKzsnlkBG6NbskpP3vBvvqV8i8re5mDD3g2uAOGhOc1wtCme78g+YIC8Gb7BmX6yRvRu8P7v6VDinDd4OJr0zvBIxb3z8+A6cuy1qmMhWNcS3a46dJwB28PuBDTfF15H8E52g8MMJCwxGowu4U52gnIs+fprtZlgHEs8Vc4VdX4cS+oqvMQn4lgSHVRXu11pDjkkuMwk/pZnJmSy9697W6VOmzbBvn1qes6c8GYWNBgMHNX3KD5c+yE6OvnJ+UzvOZ1P13/qysY+b+g8sNe5r2dzCj4Be4I3xV+AM+N5fD70v6Lp7Ei6HYob3DdT+sOkdyFtCFSsge+PVNkkgNEN4hDv+v4uBmYpuwFnZxy4g5mby5o17un+/VWWH0+hw9FHw913w1sej8fUuFSuHH8l9y64F5tu49XlrwIQZ4rjivFXuMp5CktMBpNyLPHAU2hitVt9hCjh5KCDlINDMCxYoDofx46Fg/0k6fHH66+7g8Uuv1wFVTe8t5jNShgSambgujp38GOzMiEXnAgJ3ZqxYiuz52f39dBtjiMLu5+2S6QDvkp+QOn37SqAuZEsLnsqs13TEyZ0woAezaR+qp5nRN7tJkwc2fdIDu5+MD9t+4k35r7h0xHZkOMGHses3rP4cuOXADxy2CORqGaLWLlS3TtyctTAWzhx3gfvvDN6MinHGeKw2C0YNANvrniTGotK/mCxW1wi+5Y+WzsdoQY6HEDdO3Q7VG/3fSY5BzbrSlWGw7q9sMiRBCVtiMoiaYyCdHOJPVQihdJFAZY3OI76ciUqyZ7gv7w/dn6q3ou7HB68UwRE3C0i3hxP7S2Bz4GlS93v3Vde2fi9wGxWznnh5osvVPtu+HDIlJwQgal3vAMn923berQDHn1UuT0WF6vz6umn4RhHF6XT+EzT1DleVQX//nfoIipN00iJTXH1z+6p3sOe6j1+y3ZL6cb737udUg87rOm+kGh4TvvQ9ShY9wRUb1MOoPlH+gYzJRa4+xx1HZZere6dudODuHd6bCuQeEXwwlPw0RjOxExOhg1THye6rtqHznGC+npvF7uHZj3Eqe+pl+W8pDxun3o7h75yKKD6GjpkgEtZWXA2mB6E9bptypHO33dZWV4Z0jsT10y4hod+foi9terZ+fYJb/PNpm/49+//BuDEwSeSkZDRllUU2oAsxxBRUVEnzpguCELzycpSgzWh9LnExblvPtFA9Q444EjG2vUYX8eLxpKFAHQ7DhILAy9vLru+VGMT+UcSagKTGybdwD9++wd23c6i7YuY0XMGGhqapnH2iLPJS8pr/fq2FXVl6v+kXmCMHpVkUpKKOXrrLbjrLpUw5NZbVTO0Xz/1jrF/vzIQrKpSY3udklEPw2fDlYPByvtgyK3ersue79IAOz6C0l/AWu1/e4FcThxJdK6ZeA1P/PoE9bZ63lzxpmvx7VNvx+AYQz/rLHj8cVixAs48E778UiWhCTTWabeHlgzGM6GG0dh8V5TOysguI7l50s18sekL/n3Mv9HkBxSilBsn3ch7695zzZ8y5BSKKor4fqvKspOXmMe0HtPaqHaCIAjRQceI3umglFaXUm+rJ8YR8LC13NudwhkcGq0kmBM4Z8Q5PPXrU+joPL34aUBlI790zKWuxn9D7px+J2+vets13zejL6cOcUdM7t2rGvB9+kBCQvD1SYlLIT0unX21+xotF0xmqEDM7DnTS0ThjwRzAoVpqgPDZDCRl5jHrqrGBx4nF04GvP/mGprPOVFUoVIpmA1mhuQMCf0A9i5xZPyYDsZ43+V+OkI8hSUGzeDlUALKwcSoGbHrdgyagR5pPdQCy34oWxx6HYOhqghsjhfW5H5qELkRPIUldt0etGOJrsP//uebJTI1VQXabd7szmJgqveONKmo9SMsqa3wEp+kx6c3Wm8hMvz8s/vvOGtW0yKiSODMlAGqgyvcwRv3zryXD9Z+ACgB1GOHPcZry18D1HV/5/Q7wRCLK5DaWgUNXTAas8QNJetyR6F8udtCuN/lBCXEObAZLB73DnMKHLIAYhz3iuQ+MO55+FZF0vU0qa06/xLvr3mfjzSVwtPzOWXHzqixo4g1xWIMcnTSaDQyYcIEVq4Eu12tYzLBm2/6dt4ZDHDddbB+vff3Vx10FQ///DC1tlqqLFUAXDb2MjLi3YPkeUl5mA1mLHYLGppf8aITHZ2eacE7ljiPwTkd7DqLFk3AZoNp04xBBTnv3QsbHGYxhx6q7idNiTmqq2HVKuc+4eqrA3d8Go3KjjkU0tLcz669e5VLQGMYjUYmDMmC7R9i1OzQ+3zlahbAHcSo2ZmQ9pOaNswOrXKhUPI/x3VkcwR9NS2IBcIfLLtvucMZzQ79r2z0t6qqc6uTknyNhzokrmtv04sYqYeMsWD0k5G/qki1PStWR+6cCoHG7iE/nvtjSOVfOOYFTn3vVM4cfma7aP/t36/aQ7mhJx4LCudv9cwzYLMZKSxUDm2B74Oh38+bWyeA2KWx7K/bj1238/mGz5m/YT7g7QBmw0ZS7ySG5gwN+dnqnG7t8lFNqIEOfwJWVI/W2idhxH2+wkLPgU1brVtYYozzHRFsq3Zq30tg5ydQsRJ2fAZdZvkGMDccoA0FXXcH9WcdpBwFDR6CmnbkKLhkiWrzGAxw8cVNt6XCLUTbv1/VCYJLPtCpr2+nk6VmdoiAG9zMmwgq6Ezk5cHy5XDJJfDOOzB3rhItHXKIEprExKgEEz/8AAsXwqBBzXPnGZM/hh1rdzRZbna/2Vz2tXp/OfjgdhzImncIZI5TfZ5/3Kzm0QKLmg9shroSNd3lsCYD17zaqdamA/o71PXdTE4afBKvr3i9yXJnDD+DIl31dfv7rTRNXRdOGv62cwbMITkmmf31+/llxy+8v/p9DBhAgwtHXdisAJdI3M/V+/cQeP55jEFYExntdiY4bFKNZ54Z1Pb795/ACy+o/pwtW2DgwMafrc06b52OdE217xo6scTFwdq1nVJcEmOK4ZyR5/DYoscAWL57OT9u+9E1XnDx6IvbsHZCWzFnDjz8MJSUwLvvwvHHR6mQUxCE6KSgQD1XGzqQFBdDebkaKOjSxXtZtIk86zzqnnWQf+faxuh6lG+bHlqWkErXod4xVpcxSiWR04JPYNItpRtH9zuaD9d+SJWlipf+eAkdHV3XuXTMpc2rU7RiqwV0//3/0KZ9ApqmnENPOUU5l/z4o3rXLitTovXcXJVgYfJkGB9crtiOR9pQGHANrHkIlt+m3pdHPQIxaeq6ApQTs9mREQY1Xle5Bmp2qsSKnjSRRCcvKY9LxlzC47887ho37pnWk5OHnOzahMGgEvPNmqVub4MHwy23qHHS/Aa7W7NGJYYJpe8kJsbdTb11qwhLmsM9M+/hnpn3tHU1hA5Os/tbHOuMyB/BlMIpLNi6AB2dw3ofxsfrPsagGdB1nesOvi5sdRcEQWgviLAkCnEGe+ro3PTNTWTGq4D0n7b9hIaGjo6GRr/Mfm1ZzaC4aPRFPPnrkwD8sPUHQAUhnzPynIDrDMgawBnDzuCV5a8AcO+MezF6BONVValgyGCzhHtyULeD+HzD5wGXJ8UktSgLhMFgoG9GX9aWrQXAqBkxG83U2+pdf9fRXUZ7rTO+23g+XPtho9s9Y9gZgBIapMWluUQOL/3xEpvLVWb6elu9ywXDYrc0T3hkcUSrh5C5I98EZoMRi92GUTP6Bv0e2Ok69rykPJdQin2/Q7gy+VasdE/3PENlpG0kW3ScARI1qNLBpttcLgye7KvZ5xUslpOYw4YNUNFAHzJtGnz8sQoOXbBAZeqvqABjnTu7i1EzUllXSUM8RU/JMclNZrgWIsNOj1N6ypRmZvdvZTzHZOP9aMBam0HZgxiYNZDVpavZX7+fl/94GTt2NDRm9JzhdteJz1UdQSXfKwcOTzw7i6D5WZc7CuUrHE4LGvQ6J7hM/ft+x0sqMvQOiMlwB6wbTGByPxw1DVJikqioPwCo9oU/4aNm0Dj6yKNDqr7RaGTWrFm88IL7u8MPV+4Z/tB1tz2xk6yELC4deymPLFLZ+WOMMVwz8RqvMgbNQPfU7mzatwmr3erlUAL4OJiE4ljiPIZQ0HUj8+erdY4/Pjih2S+/uKcPPji4Tsi1a93bnjXLtzO0IaFmyfbMrvTqqyp4rbFBaaPRyKze26D+OxUQmDnOv4jDJQKwMSv7K8fKfwutcqFQ+osSZ6WPcDglNaCNbNTZ5xDqJveB7ImNFk2IdWduqqoKb7WiBaPRyKxp46H0cECH7Mm+bbUGoiCjhvucqm9GBGUYCPUe0lj5rild+eGcH1qramHHGd8WSqavUDAajYwcOYsPHa9Ip53WeGax5tzPm1Mn5z66be5G6S73oLbeUEyLEpYcP/t4eqaHJnhsrXOq3dGcQId9f4eSd2DDv2DgNY42UYD2lCFWCU90m+Odt8HfrK3aqflHQMoAlfVv6VUwa6F6ngUKkmjivda3fL3b2cuUTHt2FFy0SAW3jxsH6UHo78IdbLd9u/teOH160+U79fVtTlP/15f5d2hsDWeeDkRmJrz9Nvz6K7z/Pnz2Gbz2mvo4iYtTrjwnnOCdKDRYju1/bJP9kJnxmezZbWKHQ38ydWr0OIeFjKbBiAfgm5lQsQq+mgxT3ld9n54BZnabKlvn4eCSMarJwDXvd5+zmqxOh7q+m8nsfk0Lxc0GMwNyBjBg1oCgt9vwtzVi5MzhZ/L04qfR0Xlv9XvYsWPAwJnDmxZgBLOP1i7vWmfuXPXiHkTbyAjMgqCDQI1GIyecMIsrr1TCyBdfVP3XrX0cITvSOamtVetGU0BrBDlz+Jk8vPBhAD5c+yEr96hxjvzkfFfyMaFzcfDBMHIk/PEH3HefEpqIc4kgCCFRUNC+n6vWA+5pc3Lo6+dM8S8qaUlCKnsdrhgHUxLN6W+5fNzlrveydWXrABjfdTzD84aHvK2oxpwMGLyT5nkSJX0CXbvCySerj9CAkQ9CQlf4/XrY/ApseRWyp6gEObGZqv9x71LY8QnE5jiSrllVMqDh9zSeDMgP1028jsd/edw1f9vU23xiZgYNUm4yV16pRCbXX68+AwZAt26qrbRxo+q/GzYs9KQcM2fC/Plq/PTuu0NbVxCEyNDs/haPdU4fejoLti7AoBn4ZtM3fLXpK1cszUmDT2rV+gqCILRHoiA8VmiMxxY95sqeZdftrqAVk8FErCl67CIDMThnMAd1O4hF2xdxwBHYeuyAY5sUb9w+9XaXsGTuoLley2Ji1DhffX3o9blp0k0uYUm8KZ4/L/mTa768ho/Xfgy0Ttan26fezmn/VanDR+SN4LcLfyP/4XxXMOxd0+/yKn/KkFO8BnS7Jnel1lpLWY2yBjVpJqb3cEcqOJ1e7NhZWryU5buXA74BTYEcYRrF6ohoNCb4zyTpB4MGPRKzWL9/N3bd7uNYUlRR5Mqq5SWG2rsUl7tBa1Oxwh041OP0oIJvMoxQ5XClcP72npTXlWOzq+OINcaSGJPoylDqpGtX9ZLpFB5MmKAG/486Ckz1bmGJQTO4RECeeApLPDP2C21LVZUjyYYOyc3oswwHnm5NBw4ELteazBs2j1u+vQUdnffXvA+o+85pQzysEnqeCasfgh0fq86/mDTvjbQk43JHY98yVED1JIgPUtC4b6mjQ84GKQOVeKdhh1yD+12/tEIWl6ykMbqldAu+3g1YtsxtC3zWWYGDjYxGFQjYkGsmXuMSllww6gK/7YN+Gf3YtG8TOrrLmctJ8YFiTAYTVrsVDc3lCBYunO5FoO71wQRx/fqrKmuzBZ/pd7VHoqyTT246iCvUIK8BA9Qz6pdf4Lnn4Iorml7HXrIQg26FlP5gbmCtEWggBsLrDlLveG6mNsOlLVzYrSobEygHuCai/bKT3YFrv/yiggXaZcBeqNTsxBXYnT0Jn8G3dpRFvzOSnKxO672+WuxW448/3NPjxkVXZrCx+WNZtmtZo2WMmjEkUYlA6IEOFbfDp2+rgemvp8GMrxxtKoP3CeMUY8Skq3vL7u9gwF98t9cW7VRNg1GPwfezYf8GmD8WJr0FmWMdWf8MqHulpgSdJQsgLwgVg2v7Ho0O3Up7dRSsq3O3jUaPblxoFik8xaBdukhgX6OkDlIC+V1f+88SC/Ke6Idx49Tn/vvV87a0VPWDJiSoIAlPl4ZQOXnwyZz70bmueac7r2e/4si8kZR5dI0ddFB0JNloNrnTYPK78NMpyj304/6QfzgUngppw9R5eWAzFL2lnE2cmDqJpWCEMRlM5CTkUFJdErBM74ym3V+C4dyR57pc1HdX7Qbg8N6H0yW5S2OrRQdhDAI1meCii1SQ+kcfwa5dkJ3d+PMs5ED2UB3pnMTFqXU7KcNyhzEoexCr9qziz5I/Xd+fM+Kc5o33tISiIm9xk2dnlb/5aMtw30HQNLj5ZiUoXb5cjTW9/766VBo+my0Wt8ufIAhCh8HTedXmJziksb6NmAxI8tM/19KEVJrHe629nub0t8zoOYNe6b3YtG+Ta9EV44MYqGlvJBaqMc3966F2N8T5scCWPoHoRtNgwFUqQc66p2Hbe7D7G/XxTIZoiIGCEyF9GGx9U5XtMQ9S+oWURKdrSldOHXIqb6x4A1CB3/7IylJxOHfeCZ9+Ch9+qBLTrF6tqpyUpNpNp54aelKOSy5R2ywqUgk/Djusk4zbCUIn4/iBx3Ppp5di0218uv5TVwLqCd0mtCh+RhAEoaMg3UtRjk23YbVbsdqtXlnG21PQ+WVjL/OaD8bCs3dGb3Zds4u91+/16TBPSlINf08XgWCZ0H0CKTEqo3WNtQaAlSUrsTv+HdP/mNA32oAZPWe4pv8s+ZPi/cUuUUmsMZYJ3bwzLJw46EQSze4M85+f/jnXTLgGo2bEqBmZO2guBo+eYM8GjI6OxW7BYrdgtVu9tjutx7TQK290RKvbavyLSpwdIQ3onaY6ZWy6jUXbFvH4osddnxUlKwAlpuiT3se90t7ffd/gkvvAkFug+wmh192TcrVPTMn+O4yqipSwxcPiNs9jYMyfY8ne6r2uQXani9DSpd4vkTfcoDrunYNsJhPMnq2CX0z13unkK2p9hSXlteWuaZcDhNDm1NerUzWaBmU83Ql++00NGoWbkwef7LoGlhYvBVQwwHEDj3MX6nWO6iC0W2DVA03bOTS4b3UarNVQvU1NZ4xxZ5Juir1L3WV7nqkEgE1wUF7TAffDsodRXl5OeXk5ejAWHICu6+zbp9bRNJ2EBDjmmMY71vxtOj85n/xkZcdx/cHX+12vd0ZvzI5OR3+OJc5AqNykXLcrVpDHEOpxx8TopKeXk5ZWzv79elCOJXv3qntIYSGkpgZXt9Wr3b/lscc23WHZnA7Niy9WgZkrVsBddzVe1mLRqSjZTLklDT3Dj0KowUCMrmuUW9JU+bp9vuVbC2e2MlNicPYxkWD/ercFePow0P3coKuKXG2Qbpk7GNx1BaDz5pudo3Na13XK95Wq80PXlB16Qwccn3U8zqko+VuHeg9pzj0nWunVSwWWbdqkBldaG13XWbq0nPR09YwZM6bxILZI/Lae+zi89+FNls9NyG3Ws7WznlPNInUATHgZ0JSg77Nh8MctULXFXUa3qWD2BXNRghMTFM8PnCWxLcg/DCa9rQZfq4vgi3Hw2XBY8whsexeK3oY/b4cPe8Dv1zS5OS8MJncARt0efER8zqyQhy9Rn6mfwIRX4dCfo8otYuVKt7h39Gi3qLkt8YyRjfPtIvGhU1/fPU5Twqb6fbDz8877DtgCMjKgXz8YMkQ9g1siKgFIiEmga3JX1/yIvBHMHTjXKwPoCYNOoNptrEdaWnSJPJtF9+Pg8KWQMVZlGN7+sRKafDoIPu4L382CTS+p93Un/t65G/SNerVTE5sWlXao67sFnDn8TAyOoalxXcfx2WmfeTmQXjDqgla5d47MG8ng7MFe5c4fdb6/1YMiEvfzcO/DWf6kk8qx23WsVuXIarUGfsZarTp794Z43jod6ZYs8f588olK/fvqq2q64fK1azu9OOGcEef4fOd0tI8YRUXQv79qfDk/8+Z5l5k3z3t5//7heUEUmDsXbrxRTX/9NQweDA8+CLt3u8tUV8NLL8GZzTNkEgRBiF48xd41O5TToCf++jaSHPEImX7GMloDg9H9TlC9HZ+QqyD6Wwyagf8b93+uVdLj0pk70DvZaoeg+1zArt6tNr/qHjsR2h8p/WHMEzBnOxyxDCa8AmOfgfHPw9RP4YS9avmg61WckfUAfDPdnbzB82/vvI7r/Y8f3jblNjQ0LhlzCWZj44NmffooR5Jvv1XtIZtNfSor4YMPVPK+UPszDj8c8hx5EM87TxlHBorF6MSv9YLQprRGf0tWQhaH9DoEwCv5ybxh8wJtQhAEoVMRJSGygicNrfz80TOt/WQ/PWGQt0hges/gMmzmJuWSHp/u8/3w4arhvmePCuy3h2B4YTQYmdlrpkus8vO2n9m4byMAcaY4xncbH/zGGqn3oKxBANTb6vlgzQeuZZMLJ/s4zRgNRiYXTnYFxv6x+w+W7V6Gjo5dt/sIRBoOhvlDQ6NvZt/QK++0kK3e7n+5Z0eIRydIucffYFP5Jq7+8mrXxynSsOt2b8FG+TLvYOqEbnDIDzD0Lpj8DnQ/MfT6O9nn2Haan9/KmVV9/mhY6G4QdvG47PyJPjxdTLITswFYvNj9Etm1q8r05i9L1J13gtGS5jrvdHQq6yp99rG/br9ruilXHyFyJCSo+4zNFhkBRzB07w49eqjpDz6ITCBy74zejMgbAcABiwrmPqz3YaTFpbkLpfSHzINUduRVD8DWN1Rnob+XObvF28K6M1G5BlcGl9TB/oNVPALPXdS5nQ0oOCFwhhcPju45xWvebDC7RBpOphdM5/HHH+fxxx/HEuRJbrFYeOKJx7nkkscxmSxMm9b8AKcdV+9Av12nINV/4EBuYi4WR4fjrgO7mPj8RNfnjRVvuJZlx2eHtF+LxRLycVutFq688nGuuupxli2zBHXMNTXqEghWVAKwapW65+TkqCCucHDiiSpAzWSC229X4hKbzduVxRlUUlJi4YmN5/H4lquwJA3xnxnMA4tu4vEtV6ny1nD2qjq37ZEVyZMAgtiwZmEvX+6eTh/pnVEN3O0QjzbI6Qe/hsEACxfCli3efwN/RENAbUuwWCw8/tK36vzQTWBKaHqdiJ1TwRPqPaQ595xoZc4c9zvYW2+1fvvIYrFQU/M4V175OBkZFro1kRgoEr+t5z4O6XFIk+WHZg9t1rO1s55Tzabn6TDlfTDGqaySq/4GH/WC/+bBhz3hnXT43xGw/UPlWKJbVRt0/T+bFvY2DFQIJ92Ph8N+gayJar5iBSy7QQU8/3w6rLxPPT+0ZtgFOBMtFH8V2CkiY5T6dJ2tftMoEpUArF/vnh4/PjpEmJ5ikmASsXfq6zt3BsQ4MiOseqDp0fxgRfdCizhz+JmYDCbMBjPju47nqSOfciWsMWgG5g2b5+UU3VIxS9SQNhgOWwjHbIYR96v7bnJfSOwB6aOUo9Xw+9zl6/f59mc0CBKzHPyBu52aNqbJKnSo67sFHD/weOwOF+ud+3cyq/csdlbu9FreGvdOTdO4aPRFrjIZ8Rkc1e+oZtc7EvfzcO/DWf699x7nyistaJp6F50xQ72PqjKqve/c3ObNFp55phnnbUEBjBrl/Zk9G04/XX1mz/Zd3slFJQCnDT3NNVYESiDVP6t/ZCtRWhq620xtrbfDidCq3HsvPPqoSny1Y4dyMcnPV9m68/JU/+EFF8C6dW1dU0EQhFYmsQcYHLEVOz7x/07ZsG/D2d8cH8ax9rSh6v+dn/k4Lvitk5/+lrOGn+Wavmj0RT4xJB2C5N7qXQsNNv67rWsjtAaaBunDoec86Hsx9D4Xuh6pEsCBujYmvaPEJXVl8OUE+GYGbHsfDmyCqq1Q8r3q9/ze/7vZgOwB2G+388zsZ0KunsHQ8sQYRiM88YSaLilRLq7ff6/mLRb3x7n8pptatj9BEEKntfpbTh1yqlcZDc0nxlUQBKGzIsKSKCQnMafJMsNzh0egJq1DnCmOPhkqM8QJg05osWX37Nnul4H//jc0YQnAIb0OQdd1DJqBLzZ+4crAP6VgSkiZzhvj8D6Hu47zq01fYdAMGDQDh/U+zG/56T2mo2kaJoOJP3b9wZKdS7DrdnR0phR6BwU3dDzxR3JscvMqnj5cBavsWQC2Ov9lnB0hHp0g3VO7exWx63bXx5NeGY5ATl2H/Q16uMf+SwWAOv+4g/xnrm8Su8297dTBvgPAAextc4xg0lQqZE+Bh5N9te6MCfnJ+ei6SqLm5NJL/b+kms3qnC0sMJIco/4uNruNijpf8cqBehVkbzKYxLEkikjySIazPYDmKtJomgoKN5ngf/+DigglXW5oN3va0NN8Cx30H3cn78IzYOnVUNPAYspuha1vwcJOmkLN6aoEkD7CN8jPT+C5F8l9lcNTEEzvNsZLsHpM/2N8XpCPGdByt67DD8cr8MgfjWWbbwznvdHJwu0LXR/Pe3OtLcQB7xby1VfBtUFqa9WjKDaEMYE//1TbHjiw+fVrivh4+PxzSElRf5vbb1eCtb//HX7/XSUJ/eEHOOMMGDjAI8DPnOST8LzNcHZU26r9O60FEMSGNWC2YqU78DdtmO9yP+2Qkye8hd2uoevuBKCBkquEatndLvCXpSyQKAggqUdYqyM0Tc+eMMxxer/0Ungd3YYODd+2m0ucKc7lYAjQN6Mvkwsmewk3nVmOhAjQ7Vg4ej0MvxsSCtV3tbuVc4l1P6BB7nQY/Tgk9Vbzy29TTnCBnBN0OxBiR0NLSR8Oh/6ggp2H3AFZB0PKAEgd4qj/EzBtfujb7Xacei6V/hxdTi0hUFPjnu7du+3q4UmChyayuLj9iz7DisGk3BY1ozoPl1ypvvcnrrdbg3JlFFrOxO4TsdqtWOwWlu9ezso9K13LhuQMITEmkfh4d3lP95IOQVIP1e846yc4eh0cuxmOWAIjH4TsSe5ye35UosSGeAaJ5TftZCb4Mjp/tKsffnvldpbvXu56p89NzKUwtbDV9uXZd3XOiHOazHjbmbjvPuU+q2nw88/Qt6/q33nxRTXu8vLLql97SNNmuEIrkp+cz8yeM13z5448tw1rI0QLmgZXXQVr1sD110N2tuo7LCtTziUWi+rrmz27rWsqCILQypjiocss9U654xP/4wANcboQGuPD947Z/XjAoJJd1hQ3axPp8enEGVUf+EVjLmqidDump2MsuHINLL6s8bLSJ9Ax6HYMzPgKzClqfvf/4KeT4aPeypX525kqTiCSiX1C5MQT1XgpqL6/Qw+FQYPg4Yfhtdfg+eeVG0q3bjC/GV22giBEB3MGzPGKpZneY3pQMbuCIAidARGWRCE905t2Izm44OAI1KT1+OiUj7h72t08etijLd5WdrbKUqlpqtEe6gD+zJ4zXW4gi3csBpTq9NDeh7a4bk4O6XWIS1SxbNcyl8giUIDR1MKp2HU7VruV33b+xubyzYCyPR2Y5R1VemivputZkNLMzF5djlADprZa9YIX5MvcsFw/gZN+GJs/Vk1Ub1f7cJLcV2Uy8Ayubm7HQc12sDuim1OHgB6cOjnb6I6TrbXVUt8gG7vTYcRkMJGTmMO2bbDfQ39yxBG+biVO7HZ1zmbEZwDKscQzGBqgzlrnyrqvoYmwJIoY5nF6f/5508HzkWLOHJXV3mqFG26IzD5PGnyS1/zR/Y72LZQ6AKZ8oLL068Dax1Un0XdHwKLz4KdT1fzCMwK7I3V09q8FzXG/Sx3kuzyAAM5FztSgvXVNBhMHdTvINX9s/2M5c7hb0NMjtQfdUppIBR8E48eHL4vt6PzRQZXrntK96UKtSGmpEmA01Q4xm1WbJdiknlYrbFbNAAYODF1AGwq9esGiRcp1C1TGw5tuUklCBwxQGUtffRVMBo8bnyGGqFGWmByd0vs3BC7jRxAbViyVgAbxXd1OcE3QK2czR83cjtEIP/2kxCUWi69zifOef/vtrV/tNsXiK+htmAmaSe+6l2W13GFQaDknn6xEaStXNn1ONuXC0xjdI3trD5qTBp/kcgGbM2AOn5/+uastD3DKkFPasHZBUFSk7D+dn9UNXNJWr/ZeXlTUNvUMloSuMPgmOHYTzFqosuJNeBmmfAjHblUDmfmHwahHAF29L347C3Z+rtZ3/u2cTnu1u2DptW1zLEk9YOitMOtHOGo1zP4TZn4D/S+HuIzQt9f1aPWOr9tgyxuBxTRRTE2NW1QZLa4J3bq5RXXffde2dWkXDL0N4ruoQKB1T6uslAccDV671X1e7v0Nfr2k7erZifBMWvNnyZ/8uftPDJoBk8HEtMJpgLeAavfuTiSgis+F5H5qeteXQTmFCqETY4xhXNdxrvn5G1QkjkEzMK3HNLRWVNNnJrgFweeMOKfVttsRMBrh3Xfh4ovVs9ZggC++gAsvVIFU558Pn30WXiG54J+zRrgzmLfJu0VWlrdFWzDExan1hLDSt68She3cqfqQPvhAXcdff60yZne4PiNBEASAbnNUv0bNDij+2n+iIk+cbclA42it4XTe7RhcSUnW/6PpuIYAMRfVN1djv81Oj7Qewe+7vdH7PPXbakbY+Bz8ejHUV6i/qbMvzu5wGd76VlvXtvXoaP2voZI7HY7bAeNfgPSRvsvju0G/JoRGbcy11yoBSXKyuq2sWQM33gjnnAOXXAJvv93WNRQEoaWkxqVyZN8jXfOnDzu9kdKCIAidiwBh0EJbMixnGD+V/OSaN2pGlxDCyazes9qias1mYPZAbpl6S6tt7/jj4ddflT379dfD448HLmuzeWdJ75fZj9zEXHZX7XYJOHR0ryxQLWVK4RRMBhNWu5XtlSpwOj0uPaAAY1SXUcSZ4qi11rJ011LX39rpZOLJgOwBaGgupxWjZsSgGbDara7vBmY3M8V53gyVzVS3QtGbKvgmCMZ3DS7Ab1J3R9a/yjXeC/peqjoLPAdr/dnGBoO1yj2dOsgdvN0EOUaweVxj5bXlLiWyrusuYYmGRk5iDjt2eOwm1Vt80BC7HcaNgw82Z7vOuX013sIS5/ZBnY+eWZCFtmXQIDUmVlqqBmguvbSta6Q46CBld19cDP/6F0ybBiec4N8VwmZTFq0zZrRsnwWpbtFa34y+gd2RuhwKM76GxRer7P3oUNwwXYemsgVFgqIi9Qd04q/zzpOsLChopkAvGCwOB46Ebm5L7lDImazu00He38blj+OX7b8AsK5sHQfqD6ChoWka47u1ToB2rxD620NlYveJQZXrn9U/fJUIwF13wYcfNl4mNlZ1OAab5XfbNncQ9sCBajqcQZR9+8K6dfDWW/DQQ8otxROTCY4+1uNcs1uABgMyzoEYf4KocLpLZIxSma/3LgZbTeTuKY3hFM7GpIe02gt/W8TgI09g7171t1iwQIkGzz0XEhOhqko5Q9x/vxJZ3313GOreVuxbClnjHKIlDxIL1AcgaQjwe8SrJgTm3HPhwQehshLuvRe6dIHLLlOiKLPjluF8D1u+XAnWmkOosUyRYlSXUVjsFjQ01pWtY8Net8AtJzEnujMaFRVB//7KUisQTvskJ3FxysoqnO2j1kAzQNZBgZd3OwYGXA1rHgFLOfxwjBrY7HspJHZX75I758PmF1WSgo5A5ngwp6nj/eNmKDhRzRuaaSXXBtTVuYNdm+uA19qkpMDo0bB4MXzzTfTUK2qJSYMpH8HXk8FaowJFit5Rwqfk/urdZu9vUPKD/2ADodXJTMikd3pvNu7byP76/SzeqRLvWO1W1/tXfr669nRdtU0P70zGHF2PgrVPQOlC9WxwOiUKrcrUwqn8vO1n7Lqdn7f/jEEzoOs6kwsmt/q+yq4rY1/tPnpnRIn1VRRhMsEzz8Bf/6r+/+c/VRvfSXKyEpoIkeW4Ace5ptskAVVBgWr/e/anguqILi+HtDT1EuhJuPtTBS9MJpgYXJepIAhC+yd/NirZlQ6LL4IjlyuRgj/3Et3uFo3Yahp3Oq8rVW4j9eVK+BBKUqqUgZBQANVFsOoB1d+SMiCwMD2AcLo1BdVRizkJJr8HX04AWx1s+BdseQ36XgKZ49RvVrkO1j0BsdnQ49S2rnHL6cj9r6FgSoDe56jPgS1QW6L6gGLSIaV/cA5Ebcy556okW6++Co88osZTncTHw9lnw1/+0mbVEwShFThtyGl8tPYjwPtdXBAEobMT/S21TsjMXm6Bg4bGyYNPZkrhFNd3CeYEcpNy26JqUcNZZ0FSkpp+4gm3sMQzG64zk96yZd7raprGYX2UYMKZVTY1NpXhecNbrX6JMYmuDPHOfczqPQtDgJcjs9HMwd2VC42nwGBqj6l+y3u62hza61Cum3gdsaZY13ez+zbT79qUqAKW0WDzy7B3SeNZPxxZJSd0b7qjRUMjPyVfzVSuwSvbeffjWi8DoKcTSkxawI6ahuQYwe4RKFteW+6arrJUucQ+dt1OTmIOu3a5150ypfFAEpNJCUtyE93Xref2ASrqKlzTVrtVHEuiCE2Dww5Tf8dvvw0uODxYZ4KWYDDAs8+qIA9dhzPPhNtuU8HHNptyVrHZVIbfu+6Cm29unf1OLVT3Jb9uJZ7kTIIj/1QCk9zpHtl/DJDQHUY+CNM+b51KNYaz8270aPenYWfdvHney/v3D29mGKerkjk1xBUdz5CcaSHdM53Brza7jXVl61hXts5l6Tm6S3BuII0RHx/ehITBOqqMyBsRvkr4wWCAjz5q3D3NZlO/D8CmTSowsilqatzTAwa4A7TDSWysuof88YcKkHz3XXj5ZXV8W7fCc//2EHva63x0JW3mLpE7TXVC2y2w56fosEm31wE6GGObLOpJdmYdX32lMkMbjSrz5BVXqPauyaT+v+wy2L69AwavlvzgKyoRop68PHjuOXfiv8svV+KRr79WgWjV1UpQcswxKtNxc4mJCa9zU3MZ1UUpZXR0Vu9Zzfq96wH1zuNyaYxWSksbH9T0R22tb1BZe2Xk36HXuWpaM8K+3+HXC+C7w2HBXJU50W6hw3SXGYwqMyQGqN8L3x/jfnZ6ojsaM9s/ingVmyImRt1ros0t4bDD1DP5jz+grKyta9MOyBip3g3jHMI73Q7bP4TVDyqxV8kPdJjrrp0wrcc0NEff3OKdi139Xk6X7NRUGDxYlf3++w7YBm2MvFnue+Xqh9z3SKFVmVww2XXerSxZiV23o6MzubD1hSUZCRkiKmmCwkJ44AHleLB5s3q+bd6s5u+7r61r1/lIjEnEfpsd+21t+DJUUKBe8jw/s2fD6aer/xsu60hBkIIgCEJ0EZ8L3eeqfpwDm2DBCaofvqErq92qxt/qHH1YNTt8t+WkpU7nmgaD/urYbz38bzZUb/Mdo7Bb1GfVA6Ftv6ORPhymz1fjAJoRrAdg9d/hxxPhhzmw7Hqo3q4SoHYEOnv/qz+SeqgEY9kTIXVguxCVOElMhIsuUo4l+/ap8V6n3vqZZ1QCP0EQ2i9H9TvKNZ0eH1riSEEQhI5M+2mtdSKmFE5xCRB0dP52yN84adBJrsE+l+tDJyYnB5580j1/1VUqcP+XX9zBBlu3quz9F1zgu35Dd5JDeh0SUPTRXA7r7e32cWivQxstP73HdJ/vnAHcDZnVaxZmgxmzwcyIvBHcOvVWaq3ul9PD+7QgjWCP0wFddXwsOBGs1f7FJXYrVKsOmaSYpCZ/vwSzR1b+yjXujoHEnpBY2Pz6NsTmEbUbQuby7AYD5J7CD89pm24jOyGb3bvdmpVx45oWEiQnq+xizmBuTwERQEVthdd8ZoI4lkQThx6qhGsVFXDPPdET4Dh7trJa1TQlJLnvPujZU90T77tPZcjo0UMJS4IJaA+G+fPms+uaXfztkL81XVjTIG8mzPgKTqmBk+vgVCvMKYKB10JMSutUqjGisfPOGXhuCC3wHE1THa4JXUNabXS+Eo/YsbNyz0rWlK3BYrdg1+2uZS2hsBVv4YGIMzWdst4p6IwUzvvABRcoIQZ4C1ztdtWxuHSpekZYLLBkSWD3dSee12paWtD6yFZB02DMGJg7F844A44+WmUq9mL/Jv+uYs6BmIxRkB+hdMbZDjEswM7P8FW8tAF2K6AHHgBxurs0JKkXw4fDwoXubNDO4D1n29Y5Pz6MWp3IY4A9C9q6EkIzOfFEJWp18vvvcOSRKhA1MVHFFn38ccv2YbFE9j4YLIOzB7va9ZvLN7O2dC1GzYjRYGRM/pg2rp3QKJoBxv8bpn8BGY6/lWZyfMyApsS/fS9p02q2KkPvgPgugEE5fX3SH7Z/4F2meqd6///zjsjXrwni4tztp9Z6p2kNZs5Uz2hdj653xKgm6yA4diuMe05ldm1I+jAY9Ujk69VJmdh9osv5ePM+5a6bl5TnJew/5BAlcv7tN28BfIcnZ4pb+LzqAdi/0TdozUmg74UmmdB9gmu8Y+f+nYDqYx6cPbgtq9XpiY1VfYnDhqn/o9VBsDOgaVrnyGIuCIIgCMEw5ikwJgIaFM+Hj3rDlle9hRxb34CP+qgklJoRyn4NbzKqvhdD5kFqX9Xb4JMBsPQvbmGL3Qo7PlHfF70Tvnq0F3KmwLGboN8VjvFRg0qip5nVb4imEusJQpSiaWrctmdPlXgrRvKlCUKHIDEmEeutVqy3Sh+fIAiCJyIsiUJiTbEUprqjNLdWbGVrxVZMBhNmg5khOUPasHbRwxlnqGBOZ9/64sUwaZJqwJvN0Ls3vPee/3X9CUtam4bbbGofnq40AMkxyQzNHeq37KDsQVjtVmy6jS0VWyiqcGfWT4lNIScxp5m1BnqeDWnD1At81Wb4bJgjWBPV+eL8rP8HLDzTa7+N4enWQeVa0B1KjC6Htm6nju7R2PMX1BkgoDOnQdFAwhLA5VhicqwzZkxwmRuzErJcA6ZVliqvZQ2FJuJYEl3MmuX+ez/0kAoUtzbyXvFIBGNhnnhCBXE62bMHnnoK7rxTCfBKSlp3f3GmOHKTcjEbm2GjYIyJzujQSGO3oIQlAX7DQIHnuk0FBWp+bjhVRbB3KVSs9lnUN6OvS5ixcd9GVu1Z5Vo2Mm9kc47Ai549my7TUrITspssMyQ7su2j445T9/6aGjjlFJg2DX78UQlbV65U12DfvuqadLJgQeP3DvAOmIzKAI69S6Ink1BsBqQ6go42PKss6xtrU0Qi6MsYC2gOAZkfPN1dpn4CE16FQ392ZUQbPBg++UQF7x15pBL2JCWp/w8/XImon3oq/IcRUWpLYN9ysEsm6PbIHXfAY4+p89Rfe9hkUg5PzaWuLjqbDrGmWAZmDQSUQ+WyXcuw63asdqvLzUSIYjQNusyCWQthxjcqw2Tv86H//8GYJ2HONuhzXlvXsvUwJ8HBbzguJg2qtsKPJ8HHfeGbGfDFODW97d0mN9UWeLaHdu5su3o0ZMIEd92eflq1/wK185pq/3UqjDHQ53w4ZiPMWqTaQ9PmwxHL4PClypFOiAhO52Rwuy03THAzdao6f61W+Pe/mz6XO8y5boqHfv8HGMBWAz8c6z/7sG6DmuI2qWJHICU2xTXOUedIFDSp+ySMhg5qj7NsmepQXLoUVvv23bB6tVrW0H5dEARBEARBUK4lB7+GSjSlqXb4onPg7UR4Px/eSlBxCzU7wJSk2u6WSti/IXx10gww+V2IyVTjdnYLrH0C3suGN+PgzRhYcLxyWREU8V1g9CMqAeHIv0P/K6HfpSopyuwVMOrBtq6hIAiC0AkxGowdtz9KEAShmXQQL8GOx9CcoWwp34KOztbyrWwp34JNt2HX7QzKHtTW1YsKNE0N3msaPPusCmSy2VSWSGemyEBBSF1TupKbmMvuqt2Ar9CkNWiYqbYwrfGU7uO6jiPGGEO9rR7wdq5pyKDsQejo6LrOxr0b2VK+xWtZizJZGYxw0H/gC0c67OoiZUGaPVllj7RboHQhlP8J6e6A5EFZg1i4fSEABakFDM4ZzNKdS9lVtQuA4XnD3fvwHHTNnqQ6d1orSNXgkRrAXu+73BnQ6bLBLYb6crK1ZHjpWFexxoQl2YnZ7Nrlzpo6dmzTAXMWixKL2B2D0LXWWiw2iys4v6LO27FEhCXRRZcucPnlSqhhscBRR8G//gXHHqvuNwaD+t5qhZtugu+/h7/+NTJ1M5ngo4/gxRfhmmuU7arJpOrivC+mpsLNN0emPkIQGBzZsP25QYH3fcpxj2L5LVC1BRK6+5avKoKP+4PdjzNLTTHGjFGMzBvJwu0LqbXWsr1yOwDdU7qTHp+O1WplzBj1zDIEGf1rMBhYunQMViv06WPAZgtOYNdcuiZ3ZVvltoDLzQZz0HV3YjAYmnXcznUuu8zAsmWwcaO6zr7/Hqb7mo8REwPZ2UpgsmBB0/cGTwcsczP0W+HAYDAwpqAKKlZjKF+mBBr+XEs8y4f42zabLrOUE5q1Cn67XAXOBiQCjiYGh7DE1khK9cQC9WmE0aPVvb0j4jo/6koxVDuiD1fcCZMDKMKJ8DkVJKHWKRqPoTXQNLjySjj1VOWW9uGHsGWLWpaRAYcdpsQnoWAwGCgqGsOuXWC3R8dv628f47qOY0XJCnR0/iz505X1fVSXUS1+xoT1nMrKUtHwoTi6xcWp9ToamgZ5M9Sno5MzGaZ8CAvmqmQMuk0FV7RGgEVRkbfbX6BgWU+ysqCg8Wehk+4ezd9fflHzpijozYyNVe+Ijzyi2m8nnADz56vD8mwX22ywa5eB0tIxHH54535meGEwQVaHsmFrd/TL7EdqbKpXf5Sn2ARg8mT39L33wtlnK1cyf6elrqtrIRquz1Zh6G2w6UWo36veNz4dBINvggHXgClBCU7WPIph+f2MyZkLBSfK9d0MpvWYxp8lf7rmPRMvRWN7u1l1GjAAXnsNw913u+0o/TFvnlrHaGTMYYeB0Yhhx44ms3lE4neS81YQBEEQhKig61Ew5QP48QRHIkyrcifxjDvQTGBOhhrHWEDJD5DUM3Cit5aS0BVmfAU/ngj71+Mag/BMPOV0yhXcxOXAwKvbuhaCIAhCO0X6NgRBEMKPvMFEKYNzBvP5hs+VsKRiKxv3bnQFpA/MHtjGtYsezGYV3H322WpAf+lS7+X5+Wrg0x8ze87k9RWvA9Ano0+r181kMJEUk8SB+gMc1PWgJsvHmmIZ33U8C4oWADC9h5/oVAee4qLN5ZvZWr7Vtc9hOcNaWHMgYxRMfBV+Og3VAaLDngXq44U7WuK4gcfxy45fsOt2RncZzXsnv8e458a5hCVzB851r1Zf5p7OHNdocGrIGGPd07YAwVJ+AjqzbN4ilIs/uZhrvrwGgFqL93Yy4jMoLlaB+7m5kJnZdLVMJsiMz8SmuwcQK+sqyUxQK1fUegtLMuOD2KgQUW67DV56SQk3du+GOXNg7lw47TRIT4dNm+Cee1Qw5ciWm0CEhMEA556rHBQ+/FAFuJeVqXpNm6YEMBkZka2T0AiGJhwNwPc+9dul6n9/wpK6Uv+iElCiFFTwq1P852xPjO+qArlMJhOzZ88O5QgwmUx8/vlsLBb4+98Ju7BkVP4oFu1YBKispuO7jmdz+WY27FXBkAWpwQUmetLc4/Zc56eflKPRsmVusaF3efWZMgXef18FG27dqgIiA/VXeAZiRUvGX5PJxOwpA+CXv6svKlZA+ojGy4f42zabfperLGAAW99UDiaDb1IDS872hd2iAmhX3gvD7g5vfQyOdkjNjvDupx3jOj/sNnj3crAegG3/hV3fQc4kv4N8JgPMnpAPGRF+wDZCqOd5RK+LNiAnRzmXPPYYVFWp+1dKSvPcRkwmE/v2zWb+fLXdYMqH+7f1t49RXUbx/O/PA7gcJNPj0uma3BVN05r/jCkqguXL3QsaBuQ75k3A7C5dVIB+KFG8BQWwdq23EACguFg1dNPSlKrakxBEAEIU03U2HPYLLL4MSn9yuOA5Mn3qFjClwMDrQttmURH079+0UMkRLOsiLk6dh0GcVyNGqHuJrsOSJXDiiaFVMZzcfDM89xxUVMC6dcp57M474eqr3SL/xx+HW2810b//bJ58MrjtdvRnhhAdaJrG5ILJfLL+E9d3Bxd4C0syM1WfwoIFqh/k0kvhlVd83/+c8w8+CLffHqEDCDfmFJjwEnx/tJq31cLy29THGOfqczQBs3sshyNeDGqzcn17M6lgEk/++qTXvJNobG83q059+8LHHwe/js3G7M8c7uF33NGksCQSv5Oct4IgCIIgRA3djoYj/4Tfr4MdzsxMGi5BR5dZMPJR+HyYGoPb/r5yzWyKliTNSB+m6rT2UVh5P1g8x/w1yJsJY58N4SCFdo8k9hEEQQgr0rchCIIQfkRYEqUMyh6ExW7BqBnZUr6FLRVbXMsGZomwpCETJqgAg507lbjEalWxDQMGBA5mmt5jOq+veB2TwdQyh49GGJI9hEU7FjGu67igyk/vMd0lLPHM0NaQvKQ8l2iltLqUDXs3YDaYsem21nO0KTwZjAmw6GzVAaJ7ZlRz/F4J+a5veqf3dokmtlYooYszKz5A74ze7tUdgc4YYiC5lUU9Bg9hSe3uoN1QYowxXvP7avexr3af37JpsWnscMSLdu0aXLU0zdeFxFNYUllXiUEzuAK+M+JFBRBtpKfDa68ptxJnAPl776lPQ9oqQ2d6uhLanX122+w/KonGzjunAK7e/z3GB2u1suwGJSxpwi3CH6O6jPL5bnT+6JC24Ymuu0UPsbGNl20NjhtwHM8sfgaAlJgUvjzjS678/Er+8ds/AJjdt206AbKyVObsZ55RmfpLStzLTCY45hgVTPj220pYYrPBrbfCyy8H3qZngFYop22TAx8tyBQOKCGoa1/vQtpQR0BqG5PUE/peDOv/odoqy2+F4vlw0EuQ7Gh77P0NFp4JpuTwC0viuwA2dc1Wb4eEbuHdX3vGYIT+V8DKvwF2WHQWTP8CUvp5n1u6Dao2qyC+acEHZAltR2Jiy7cxYoSKv9u1S4llgxFyRxrPZ2uNtQZQrpUtercMJki/BQH6LgoKRCjSWUkfDocugL1LYNeXyvnOmADZB0OXQ1UgdSiUlobYYHFQW6vWDeI8TE5WMbWbNql+n3CKmUMlLU21A08/Xc3X1MD11ysXy4wM2Ls3eoTCguCPgwsOdglL4kxxDMv1TVZz330wcaKafvVV9Vx++WXV/2CzKcF8ZSWcdRbs2NGBhCWgBHkHvaj6RtEAh0W2VyIbyXDYEjyFJABju45to5oIgiAIgiAI7YaUfjD1Q6jdAyXfq+RrMRmQO005YQBkjIbSn2Hn51CxGpL7qf5of2zZCAOHtCxphjEGBv0VBlwL+36Hakd/S9Z4iElv8SEL7QxJ7CMIgiAIgiC0c0RYEqU4xSM23cbGfRsprVYvHZnxmaTHy8tnIPLz1ScYDutzGACXjrk0bPV57+T3WLhtITN6zgiq/NQeU+EHNT2yS+CMzJqmMTBrIIt3LgZgTdkarHYrOnrrOtp0OxqO2agygW/7L1SuAoyQORYKToI+F7qKegpHduzfgV23s6d6j3t5umO5tcadpT+5T+sHpcakuacrVkD+4aDFBCzuiUkzYdWbjvrISFCOJQB5ecFXraFY5MZvbiQ7IRuAxTsXozvUCnHGOMzGMFnyCi3iiCOUuOT005VYyGbzLWM0BpddW4gQ0dh5Z0oGdKjZCZYDYE5qvHztLvd0YndcwSwhMLqLr4jE+Z2u61RXVwOQkJAQVECs1aoTH6/WMZsTcAkOw0Sv9F6u6d1Vu9F1nZ37d2K1W9E0jZ7pjWfw9EdzjtvfOmYzXHklXHEF/PmnciRJTIRx4yDJ8ac95hi49lo1/corcM45MHmyrwjNYvEOPty/P8iDCXMgsq7rVBsLQE8ngX1oG/4JQ24JGNmp6zrVVftBMwb927aIYXfD1reVI5pugz0/wcd9wJSk3Eqc7Y70CLhdpA1TolaAvUshPj8ogWtnwus66n812prHwFYN1dtg/igY8Xfof7l7hQ3PoS+5muqEYVBVFZlzKghCvYc0557TWdF1ncGDq4mJAas1gaVLNWbODOz0FInf1t8+huUO8xKGgxKWNLdOuq5TvWMHGAwE82TVgeqEBLWPPXvQZOBRCBZNg8wx6tNOOOgg1cb67Teoq2ta2GyxKIfbSHDaabB+vUoq78Rq9RYcg05MTDVVVfLMEKKLg7u7HUrGdx2PyU8CgwkTlAvqJ5+oPpDPP4eBA+G885SLb0kJvPCC+j/S7q0RodeZSjz+y/kqOEwzgW51/a/H51M9+OGg26lyfXuTn+zuyE+PSyfOFOeaj8b2drPqVFcHCQkkVFcH1XPi1cbT9abbhBH4neS8FQRBEAQhKonLhoIT/C/LnQZlv6jxgiVXwowvA29nTysmzTAY212fixAmJLGPIAhC2JC+DUEQhPAjwpIoZUDWANf0+tL1rukhOUPaojodku6p3dFv18O6j/zkfOYOmht0+YO6HeSa9jeY68mw3GH8tvM3dHTWla1Dd1i8tppjiZOYNBh6m/o0gks4Auyp2kNJVQlWu4qOTTQnut066svcK6WEwX0nLk8FkloPQPkK5YoS7KrmOA7UH2i0jFEzouuwx6GZyc0NvmrVlmqv+fdWv4fmGB606TbX39BitwS/USHinHIK9OmjAsNXrFBx1QaDCl7SNLjgAnjwwbaupeBFtHXepfRXgSigBHueThD+sNW5pxO6qwCWEOmf1Z9YYyx1HttyZlq3WCw89NBDANx4443ExDR936yqsnD99Wodk+lGtCAFfM2le0p3V/CuxW6hvLacbZXb0NHRdd1LeBIszTnuxtbRNBg2TH0a0qcPnHCCci2xWpXz0WuvwZw5at4ZLL1hg8pw7WTdOpg0CZqsWnOyhYeQKdxisfDQI48CV3Jj7/uJqSuDVQ8ocYkfgailvo6HHn4UCP63bRExaTB9Pnw1yZE92BHkbW3wTI+Ew0q6xwlQ/gfkHyHCkgb4XEfD74GlV6uFtlpY8n/w522qTVe7G+r3YrGbeej3I+D3hyJzTgVBqPeQ5txzOisWi4UVKx7i+uvh3ntvZMmSGKZNCywsicRv628fCeYE+mT0YV3ZOle5ljxbLRYLD335JVx/PTfeey8xlsbfCSxmMw9df73ah82GnFFCR2b0aHjzTSW6ff11pZdtTDgSKVGJk9tug9RU+OtfwW73FgqbTBATY+GIIx7ioYfkmSFEF05BJMDkgskByz3zDCxcqNxKbDb1GvHAA77loslRqFXpcigctUY5IxbPV5mRY7Ogy2FYsmby0N8fB36Q67uZ5CXlsevALsbme7uVRGN7u1l1CqF9B6G38SLxO8l5KwiCIAhCu6P3BQ6nbGDXV7Dyfhh8o3cZ3ZE9cNO/I1s3QRAEQRBahPRtCIIghB+JcopSEmMSXRm7dlW5M5WLsKRjk2BO4NXjXuV/Z/2vybKeApKdlTtd63dN7hqu6jVKYkwimfGZgBJJrCxZ6VrWM72nW+1b5yksGaAyibcmmgapg9V0xcrGyzYgOSa5yTKxxlgqKpSIAJRjSRBjggAUpHoH71rtVix2Cxa7xSvTcYxRGrDRzpgxsHw5LFkC990HN9wAzz+vTDD+8Q9IbvpUEjozaR7P8n3Lmr4PejopxeU1K0jdZDAxLNcd8J6fnE9mQmbI23HiGdyrh1ejCYDZaKZLkttZpvhAMTv373TN90wL3bEk0txyi9vlqLoajj8eTj4Z3n0XPv5YOZ6MG6eMdJy/7+rV0Ric5XherXrAcf42cPqy27zP2UiRMVJlHYvLCSAg0SAxdAFSyMTlgTlNTe/7AwziQNYk/a6Arsfi9Wpavw8qV0P93jarlhA9vP125IPEg2V81/Fe805hiSAIrcuoUUqwAfDww423j6xWWLUqMvVyomlw1VWwcqX6v08fJTTp1Uu18RYvjmx9BCFY4s3xrumDCw4OWC4/H776CuLjfV0XnSgRVWvXMIowxUP342Dcv2DKf2H8s1AwF0wJbV2zdk+f9D4ADM0d2sY1iUIym99vIwiCIAiC0KlJ6gEFJ7kTtf1xE/xyIVg8klHVlsJ3h0PJgjapoiAIgiAIgiAIQrQijiVRzNCcoezcv9PLvaDV3SiEqOP0YacHVW5Q9iCXw8X++v0ADMwa2KZ2bX0y+lC2QwlHVuxZAYCGRv/M/u5CDYUlhKG+6SNg71KoXKuyjQSZoTwtLo3iA8WNlkmKSWKXW+tFXl7wQdU904MLfE6KSQpug0KbomkqwGmUxA8KoZIyABVAbVcCuKaEIp7CkxYEqY/vOp7FOxe7pluCZ4Cv1RoZcUnvjN7s2L8DUILKkqoS17Jg769tybBhcNllKtuv3a5+s7ffVh9PDAbo3h22bo1SYUlsNlh2gq0GvpoCk96GrrPdz1vrfvjfscCMyNct+2A4ajWs+htsfg1qtqvvUwdDr7OVgCHcaBqkD4eS76H4C/U7GeObXq8zYzDCwa/D/2ZDyf8CFBI74s7M77+rz7Bh0XdPHNVlFK8sfwVQbfj2IHQUhPbI2LGQmAhVVUq88dJLcMYZ/gPcTSZ45BH4dxskHO3TB/7+d/XxpL4+8nURhGAxGUxY7VYvF2V/DBsGy5bBaafBr7+qa81uV+8vVqta/sYbkamz0LH48NQPWVWyipFdRrZ1VcLLjz96P7iKi1VmCYC0NOjiSKZhtcLnn6vp7t0jWUNBEARBEISOxbA7YNs77vmNz8GWVyBzPNjroOxX0O1A/0BbEARBEARBEARB6JSIsCSKGZIzhC82fuH1nQhLBCee54JTYOKZjb4t6J/Vn8U7F2PX7Wwo2wCA0WCkT0Yfd6G6Uvd0YiEYwnAbSh2ssqXrusqmnj6y8cBt3Q6aweW40uim41LZvds9n5cXfIBbnCkuqHLBOKcIgtCOMcap+1/VZtVx3ZT4zUtY0vwUsJ5Z1Ed3Gd3s7YD3fS9SgXJ9M/ryU9FP2HQbm8o3UWerAyA9Lr3dCPIefhh++01lrXa6lzTEaIShQ6GoSAlLoo6B18LyawAdbNXw/VGQOQ6yJkLtbtj+ocPKqw2EJQAxaTDibzD8frBUquvLHOHzI30U7PkZrAdgy5vQc15gUZijDdLpMSXAjK9h9d9hleNv51qWDP2ug432wOsLHRaTSd1S7rgDPvywrWvji+ezdVSXUW0n8pds1kJbkZUFcXFQWxvaenFxat0gSUyEc89V7pBWK1x+uYq1nT7d3S51OppcfDEsXRpadQShM1N7s7p+jYamO7d694aff1bx8R98ALt3Q3Y2zJkDU6ZEnwBUaB9kxGcwqXBSW1cj/IwYEZytT329W1giCIIgCIIgNJ+U/jDsbuVW4sRWq5JCeZUzRaRvQxAEQRAEQRAEob0gwpIoZmDWwKC+Ezon3VO6E2+Kp8Za4/qurYVHfdL7oDkySm8u34xRM2K1W72FJfVlqKzTOsTlhKciaUPU9gE2vQSjm8p4p8rmJuU2uenM+ExK3Eny6do1tIFzo2bEpgeIJnaQFpcW/AYFQWifpA+Hqq1Q+gtUbYPERrJQ6lb3dAvEeKPzR/udbinV1a22qUbpld4LTdMwYmRt2Vqv79sLMTHw0Udw3HEqIKuh04vRqMYhBg2CL76A7dvV75uQ0MSGmxPU2dxBj97nw5bnYP865VICSiBV9qtHoeY767QamgYxqW2z7/RhoDsEYWsehl5nBS7bXFFJURGUeoh1G6qQGs5nZUFBQfP2FSkMRhh8Awy4Wg3u1e5WbcWcqWDT4MP727qGQhtgdTwCP/oIvvoKZszwbXtHwjUrECPyRrimx+aP9V9o2TJ3dmp/ikHnd1aP532gjNaSzVqINgoKYO1a72cSBM7C7qQZz6XLLoMnn1TT1dUwezY88ABceKFqK23cCH/9K7z/Pozs4EnvBaE1CUZQ4lXeCFOnqo8gCIIgCIIgCEJUM+gGKPsNtr+PK3agITkxEevbEARBEARBEARBaA+IsCSKaSgSSIlNIScxTIH4QrtD0zQGZA3g912/u75ra2FJ74ze2HQbBs1A8f5i7LpKGdo7vbe7UF2Zyh6uWyEmTJl1U4e4p7e+ASMfAmMjGeF0O2hGuiZ3bXLTuUm5Xtn58/NDq1qsKZZqS+NR2JkJknFYEDo8qUNgxyfqXrjpBRh8c2DRiM3DsQQ/QeixWWCIA7sfUUGSW3ThKU71zLDeUoqKvGNfw0XPtJ5Y7VaMmpGt+7YCoKHRL7NfyzfenKDfZpKdDf/7n3Ivefpp2LZNfZ+SAvPmwb33quy/Fsef/Ysv4OijG/+NrfkFmBob+GjNQQ9jLEx5Hz4fCbY6QFwkfOhyBOpatUPFStj8KvQ83dedyG6B6h2Q1CO07RcVQf/+jQuJ5s3zno+LU4Nj7WGgyxgDXQ71/s4WIWskIeoYMABWrFDikWOPhc8+UxnRNU25ExiN8MILbVe/lNgU13TAZ+ukSe6buj+c16vZDDffrKYzM1Va+MaQbNZCtFBQEJHnS//+MHeuaifZbOoS+MtflJgkMRH27Qt7FQRBEARBEARBEARBaE9oGkx6E36/HtY+BprJnczN2V8/6K8R69sQBEEQBEEQBEFoD4iwJIoZmO3tTjIwayCaprVRbYRoZFjusOgSljgEJHbdTkl1Cboj80fvjAbCEoerid9M4lVFUFcKFX4Ce4MlLhviclWm67pS2Phv6HOh/6Btu0UFd3c/joLUpjuMuiR1wbbXPR9qsvckc1KTwpLshOzQNioIQvsjfbi783r9MyprUqBmmTHWPa37ETYkFsDRa9X9DqCmGOrLlagke4KrmNnodpFoTaHq5s1gaKbpQig4nUlsuo3t+7cDYNAMreNY0pyg323bmg76DYDJpIIgr7tO/X5WK/ToAbGOP/VAjybgm28qh5OmthfRgY+U/jDtM/hhDlgPuJ1LBEV8LnSdDTs/U7/NrxdCfBfIne5ui9gt6lr99WKYMT+07ZeWhuZOA6p8aakMjgntjosvhssvV9M1NXDEEXDeeXDiieq0fvFF+O9/4aab2rSaQOuKNikra/YzRhA6Mo88okS3VVVut6L6erySP0BorqKCIAiCIAiCIAiCIHRgDGYY/SgUngwbn4c9P6t++i6HQ+9z1XiHIAiCIAiCIAiC4EKEJVFMWlwaWQlZlFarQNFhucPauEZCtOGZfT7OGBeUMCKc9Mno45oury0HwGww0y2lm7tQXRlgB1OS6sjxpKoIPu7vP+t+TXFolSk8DdY9qYKwV94LBXOVQ4qnuMRuhfoK2PAcdD8uqODkgtQCrCXu+ZhGjFD8kRKXQkl1SaNl8pNDtEERBKH90eUwMMSCvQ5qS2DVAzDkVpU9yRO7FSrXes/7I7FAfZrgzblvUllX6fWdwWBg+PDhrulgMBgM7N49nOJi2LQpAqoSoGd6T9f07gO70dCw6TZ6pvVsZK3AGAwGhnfrBp98gsEenOuGwW5n+LJlavrII1sc9Gsw+N/EgAHu6Y8/dpuOBKKqSmXqDhd+z5HcaXDEUpXpa/uHbtFTcn8MA29ieFKKd/nORu/zYcfHatpeBz8cC0PvVEJXYzxsexeW3Qixnc+lrLn3nFDXCTeh1ikajyFa8fytZs40cMcdShel60pM8vTT6uPEaDRQVDSco48O32/b2N/vyD5H8tmGz+ib0de7fEufMS2okyB0VAoK4Pnn4eSTA5cxGiE9PXJ1CgZ5ZghCx0Wu7/ARjb9tJOoU7n10lPcxQRAEQRCEkMk6SH0EQRAEQWjXSN+GIAhC+BFhSZQzOHsw32/9HvAWEQgCeDuU9M3si0Fr28ZPRnwGSTFJHKg/4HLl6J7a3btedaUqe7e/QMq6Uv+iElDZ90Oh5zxY+6iartkJ38yEWT8D8UrQYreAvR6+PQQc9fMMBgMligGw2N1Z7Huk9WC/R1x3qJlQU2P9uLQ0oGtK19A2KghC+8OcDN2OU8HluhX+vAOSe0PhKW77bbsVKtfAuifc69nr/W4uWE4e4huFZzKZmDNnTkjbMZlM6PocPvlEaWFstvBnhs5OyCbOFEettZaymjKXK1ZzHUtMJhNzRo6E888Pfh2bjTkffKBmbr21WfsNhtRUKCyErVtVhv6nn1YOJyY/LXerFd59F846K2zVCXyOJPWCye8q0eiBzWBOgeS+mDSNOX18i3cq8mdDYk+o2gLoYKuBZderjyedUFjS3HtOqOuEm1DrFI3HEK00/K2efbZx5yabzcTvv8/h+ecjVydPPj39U//lw/yMkXNK6KycdBJUVChHI2c71InRCN27w7//3Xb184c8MwSh4yLXd/iIxt82EnUK9z46yvuYIAiCIAiCIAiCIAidE+nbEARBCD8iwYtyhuYMdU17iggEAbzPieG5w9uwJgpN01yZ4+26ysw7IHOAd6Ha3er/2KzwViZ9JCT3BxzZ/ytWwuejYNNLsPd32PIqfD4Syv9wrdIn0zsK9tQhp3L+KO9gsKG5Q7Fa3aYC/oJ8GyMroenjLkwtDG2jgiC0T3qe4XZ5QIdF58Dy25RDk6UCNj4H38xQAelOrFVtUlV/9OqlssdbLLBrV/j3p2kaPVJ7AFBlcf8Onk4mHYlTT3WLdR5+GLZtUyIST6xW2LkTXn458vXzIjYTMsdASj9f153OisEIox8FhwBKEITmM2cOnHGGcnkSBEEAuOAC+O47mD7d/V1SElx2GSxerJxNBEEQBEEQBEEQBEEQBEEQBEEQBEEQhNCQ0IxoZNs216SncECEJUJDeqT1cE1Hy/kxIMtbSNIno0HK8rpS9X+4M3RrGgy8Gq+AzgMb4dcLYP4oWHQu7F/vtUqcKY60uDTX/MVjLuavB//Vq0y/zH4uYUlzYmdzEnOaLNPc7PuCILQzuhwGCR5Rb3YLrLwP3s+Hd9Jg8aVQtweXQA6geptyMmlFdF2nvr6e+vp6dD24IHhd1+nRox6DoR7Q2bBBiUzCTd9M5SzlFC8aNSPdUro1a1u6rlNvtVJvNgcd+q8D9WazWifMB3zyye4M3Pv2waxZcOCAEvKA+r+mBg47TC0PJ6GeI805pzok3Y6F7ie4XYj80diyDkpz7znRdk7JdRE+/P1W//63cikA7za4EpvoXHBBeH/bZv29w/yMkXNK6OxMmQJffQVlZbBlC+zZA48/DllhzmHRHOSZIQgdF7m+w0c0/raRqFO499FR3scEQRAEQRAEQRAEQeicSN+GIAhC+BFhSTRSVuaaHJg90DXd3MBJoeNiNLiDEaNFWNJQSOIjLLGUq/9jwiwsAeh5NiT3CyJo030rzIx316u8tpzy2nLXfJI5iRhjjCvQN1S3EoAuSV2aLNM7o3foGxYEof1hMMLwe5su53kPq94G2Fu1GhaLhfvvv5/7778fi1O1EMQ6q1bdz80334/ZbGHBAl83jXDQO937/pifnI/J0IybMY7j/vxz7r/5Zixmc3DrmM3cf/PNah3nwyBMDB8OfTweoRs2wOjR8NprsHIlvPkmjBoFa9aEtRpA6OdIc86pDsu4f0HqEP9tEc0IpsTI16mNae49J9rOKbkuwoe/3yomRt3/nnkGCj3M/UaOhHfftVBSEt7ftll/7zA/Y+ScEgRFRoa6L8TFtXVNAiPPDEHouMj1HT6i8beNRJ3CvY+O8j4mCIIgCIIgCIIgCELnRPo2BEEQwk/zIvGEiOEpFtCaY48gdBqiRVjSMOjXRyRhdzTQYjNBt4MWRn2bMQbGPwdfT22ioDtIu0tSFzbu2wgoYUmCOcG1LDNBiU6MjtjQ5sQUd0v1FogZNAO6rqN75DJOikkKfcOCILRPepwOG56D0p9AD3BT0cwqAF23KWGJFlyAaiT5/HO45ZbGy1itzRPkedIzvafXfN+Mvi3bYBSjaXD55fCXv7jdYDZtgnPOadt6CSESmwGHfA8/nQzFX4BmAjTQLZDUG8b/p61rKAjtBoMBLrkELroIdu9Wz5TsbKivhxUr2rp2rUxmBET4QutTVASlpe751at9yzT8LisLCgp8ywkdl2XL3I3ihueDcz4Sim1BEARBEARBEARBEARBEARBEARBEIQGiLAkyslOyG7rKghRTv/M/qwtW+sTbNtWNBSSNBSaoDtEHLGZoFtBiwlvhXKmwLC7Yfmtgcv0Pt81mZec5xJ7NBSW5CblAioGRNfdgb6hMLPnTNe0QTNgvdXK/A3zOfL1IwHolizOREIno6kAvI4efKdpcNAL8MV45ejkIy7RlLNJXB7U7HAIS6JPaPrLL1BRAampgcsYmzKPCoJe6b285n1csSJJBIJ+zzsP7rsP9uxp3jNHiBJiUmH6fNi7BLa9r0S22ZOg6+zmCWyzslRa9tra4NeJi1PrCUIHwGCALk2bAEYPP/7orawsLobycjWdluY+GKtVKTUBunePZA2F1qCoCPr3b/rePG+e93xcHKxd27Hat0LjTJoEgTKiOc8PsxluvllNb9sGvcXVVBAEQRAEQRAEQRAEQRAEQRAEQRCE8CPCkihH0zTqbq4TtxIhIGsuX9PWVfCiYZBvj7Qe3gWcQdPmFIhUkOwQRxr95berAE7d5s7+P+RW6HuJq2hOQg5GzYiu6eyr3Ue8Od61rEuSCvoyGt0BvqFm4M9KcAd12nU7VZYqKuoq3MsTJehT6EQEE4DXGYLvknvDoT/A11Ogbh8uFyXNBOgw4gFYfosSllRta8uaBsRmg9degwsuUHFw/qivh9jYlu2nobCk4XyzidKg36QkePhhOOOMsO9KiAQZo9WnpRQUqPugpygP3Oet5znrpKOJ8gShPTFiBMQEIaavr3c/Y4T2R2lpaII/J7W1al25RwuBKCsTYYkgCIIgCIIgCIIgCIIgCIIgCIIgCBFBhCXtgBhTmB0dBKEVyU/O95qPNTWIItY9A6YjyJBboMdpsPYpqC6ChG7Q73JI9hbCZCcqlyANzeVYYtSMaJpGTmIO4B17bLeHVo2M+Ayv+YraCipq3cKS3MTc0DYoCO2Z5gTgddTgu9RBcPQGWPsEbHkd7PWQdwgMvhGSesLGnlD6q3IsiTJMJpV0+eWX4dJL/ZexWuHbb+GII1q2r4ZixVZz64rioN/TT1einS+/9P/MMRph3LiIVkmIBgoKOt59UBAEQRAEQRAEQRAEQRAEQRAEQRAEQRAEQRCENkOEJYIgtCoGzeCa9hFJ6DruTPzGyFXKSVIvGP1Io0VyEnOw2q0YDUaXsMR5TP6EJRZLcLHITkwGE0kxSRyoPwBAZV0llXWVGB2/h1PYIghCJyQmDYbepj4NSeyuHJcsFWCtBlNCxKsXCKtV/f/LL/DuuzBnjvd9UteVHuMf/2i5sCTBnECCKYFqazXQio4lUYymwXvvwaGHwsKFbscsAIMBRo2CRx9tu/oJgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAI7R9D00UEQRBCI8GsAp4LUwu9F+geqdY1I2gRrFSQ5CTmoKNjs9sory2nvLYcAJtu8yssKSsLfR/pcemu6Yq6CirqKjBoBgyagcz4zJZUXxCEjkpCd9AdCo59y7zVBW2M0UMneOGFylDGKTYBJYy47DLYvr119leY5n629ExrJceSKCchAb76Cv72N0hNVd8lJ8M998B330F8fNvWTxAEQRAEQRAEQRAEQRAEQRAEQRAEQRAEQRAEQWjfiGNJNJIpgeVC+6ZrclfW711PQVqB9wLd5p7WjESjsiQ7QTmG6OjsrdlLgjkBu27Hrttdy8xmd/niYigo8LelRvaRmM22ym0AVNRWUFFb4dpnVkJWyw9CEISOR0J3wCEmKfkfZI4FzRy4vN0ChkaWe2AwGBg0aJBrOtR1xo418OOPSuuybx8cfji89hoMHgx1dXDrrfDiizByZFCbbpLeGb1ZXboagIz4jGZvp6XHHew6rUVCAlx/PVx7LRw4AElJyrEkEoR63G35OwnRT3u79gIh10X4iMbfNhJ1isbjFgShdTAYDAzq0gW+/hpDEAJxg64zaOVKNX3kkeGuniAILUCe3+EjGn/bjtAm7CjvY4IgCIIgCIIgCIIgdE6kb0MQBCH8iLAkGuneva1rIAgtIishi/V719MtuZv3Ah9hSfThdCUBKK0uJcGcgM1Rb+cyT+3Xjh1gt4cW3JubmOuarqyrpLK+0iVeEccSQRD8kuDRNihZAINvarx8kKISAJPJxIknnhhSdTzX2bkTfvzRveyPP2D4cOjVS7mX7NsX0qabpGeq26VE05ovUGzpcbcVBgOkpER2n6EedzT8TkL00l6vvYbIdRE+ovG3jUSdovG4BUFoHUwmEyeOGQMXXRRceauVE995R83ccEMYayYIQkuR53f4iMbftiO0CTvK+5ggCIIgCIIgCIIgCJ0T6dsQBEEIPyIsEQSh1RmSM4SF2xcyIGtAgyV296TmR4kRmwWGOLDX+i5L6tWqdQxEdmK2a3pf7T6SYpJ8luXlucvv2gVWK8TEhLYPo2bEptuoqFOOJU7xijiWCILgF09hyZ4FYKsHYyM3nhAcS1rKiSfC1VcrxxInNhusXx+e/RWmFYZnw4IgCILQHikqUkpOJ6tX+5Zp+F1WVui2i4IgCIIgCIIgCIIgCIIgCIIgCIIgCIIgdGhEWCIIQqvz7NHP8uzRz/pZ4iEm0e2+ixML4Oi1UOcIjKophvpyJSrJnhCOqvqQEZ+BQTNg1+1U1lVSVlPmWuZ0LGkoLAmVzPhMDA5hTUVtBXtr9rqXJYhjiSAIfojNBEMs2OvAWgW7voIuh4HBT1POboOy3yJ238zPh9NPh9dfV4KScNMzXTmWJMckh39ngiAIghDNFBVB//5Q60eY78m8ed7zcXGwdq2ISwRBEARBEARBEARBEARBEARBEARBEARBcCHCEkEQIodnALQeIPo4sUB92giDZiAtNo29tXvZX7efOFOca1lmvBJ9pKeDyaScSnbtAnOIpgBZCVno6Bg0A5V1lZTXlnstEwRB8EHTIH04lP2q5re9B/lHBC67+9ughSX19fXcf//9ANx4443EBGHB1HCdm26K4dVXG1/HaAyqOk1SkKKeEQnmhBZtpzWOO5h1OgKhHndn/Z2E4Ogo155cF+EjGn/bSNSpWfv4z3/ghhu48d57ibF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ffPCBb5133XUXo0aN4rnnnuOCCy7gs88+47vvvmPhwoVBbxfg4MGDJCcnk5KSAsCWLVsAk4kkISGB2NhYbrzxRu69917atm1LmzZtuO+++zj22GM5++yz6/zYScUKCwt58cUXAbjvvvsIDw+vk2VCTXPdbxEREal91T1HCMVziuZ6blSTfcjOzuall14C4N5776Vly5a1Wr4pHFeRutAUvmtFRERCiX5bRURERPyawrlRqLbxNoVjK6GjPtr09R4UERERqblQvS4RqUijCiS5/PLLOXDgAE8++SSpqakMGjSIr776im7dugEmw0dycrKvfI8ePfjqq6+4++67ee2110hMTOSf//wnf/jDH3xlTj75ZD788EMeeeQRHn30UXr16sWsWbMYPnx40NsF+Pzzz7n++ut9j6+44goAHn/8cSZNmgTAP/7xD5xOJ5dddhl5eXmcddZZvPvuuzgcjjo5XhI8l8tVL8uEmua63yIiIlL7qnuOEIrnFM313CgU9yEU6yQSCprCd62IiEgo0W+riIiIiF9TODcK1TbepnBsJXSE4ntWRERERPxC9bpEpDyNKpAEYPz48YwfP77c5959990y804//XRWrlxZ6TovueQSLrnkkhpvF+C6667juuuuq3QdkZGRvPrqq7z66quVlhMREREREREREREREREREREREREREREREakL9oaugIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiNQPBZKIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIg0EwokERERERERERERERERERERERERERERERERaSYUSCIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiItJMOBu6AiINzWaz0a1bN990XS0TaprrfouIiEjtq+45QiieUzTXc6Oa7IPdbiciIsI3Xdvlm8JxFakLTeG7VkREJJTot1VERETErymcG4VqG29TOLYSOuqjTV/vQREREZGaC9XrEpGK2CzLshq6EhK8rKwsYmNjyczMJCYmpqGrIyIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiISDYeIOqQ81FRERERERERERERERERERERERERERERESkSVAgiYiIiIiIiIiIiIiIiIiIiIiIiIiIiIiISDPhbOgKiDS0wsJCXnnlFQDuuusuwsPD62SZUNNc91tERERqX3XPEULxnKK5nhvVZB+ys7N56aWXALj33ntp2bJlrZZvCsdVpC40he9aERGRUKLfVhERERG/pnBuFKptvE3h2EroqI82fb0HRURERGouVK9LRCqiQBIRIDc3t16WCTXNdb9FRESk9lX3HCEUzyma67lRKO5DKNZJJBQ0he9aERGRUKLfVhERERG/pnBuFKptvE3h2EroCMX3rIiIiIj4hep1iUh57A1dAREREREREREREREREREREREREREREREREakfCiQRERERERERERERERERERERERERERERERFpJhRIIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi0kwokERERERERERERERERERERERERERERERERKSZUCCJiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhIM+Fs6AqINDSbzUZiYqJvuq6WCTXNdb9FRESk9lX3HCEUzyma67lRTfbBbrcTFhbmm67t8k3huIrUhabwXSsiIhJK9NsqIiIi4tcUzo1CtY23KRxbCR310aav96CIiIhIzYXqdYlIRWyWZVkNXQkJXlZWFrGxsWRmZhITE9PQ1RERERERERERERERERERERERERERERERkRAQbLxB1aHmIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi0iQokERERERERERERERERERERERERERERERERKSZcDZ0BUQamsvl4rXXXgPg9ttvJywsrE6WCTXNdb9FRESk9lX3HCEUzyma67lRTfYhNzeXF198EYD77ruPqKioWi3fFI6rSF1oCt+1IiIioUS/rSIiIiJ+TeHcKFTbeJvCsZXQUR9t+noPioiIiNRcqF6XiFREgSTS7FmWRWZmpm+6rpYJNc11v0VERKT2VfccIRTPKZrruVFN9sHr9frKer3eWi/fFI6rSF1oCt+1IiIioUS/rSIiIiJ+TeHcKFTbeJvCsZXQUR9t+noPioiIiNRcqF6XiFTE3tAVEBERERERERERERERERERERERERERERERkfqhQBIREREREREREREREREREREREREREREREZFmQoEkIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIizYSzoSsgIiIiIiIiIiIiIiI1kJ8BWyaDKwu6XAwdflflIhs3wqpV0KsXjBhR91UUERERERERERERERGR0KNAEhERERERERERERGRxiYvDb47A7K3ATb47Q049SPoclGFi3z+OfzhD+B2m8cvvgj33lsvtRUREREREREREREREZEQokASafZsNhvt2rXzTdfVMqGmue63iIiI1L7qniOE4jlFcz03qsk+2O12HA6Hb7q2yzeF4ypSF5rCd62IiNQiyws/jDFBJJanaKYNFlwCY5dC22FlFvnuO7j4YvB6/fPuuw8iI+H22+un2qFEv60iIiIifk3h3ChU23ibwrGV0FEfbfp6D4qIiIjUXKhel4hUxGZZltXQlZDgZWVlERsbS2ZmJjExMQ1dHRERERERERERERGpb8kfw8LLys63OSFhNPzuq4DZXi8cdxxs2hQYSALQqhXs3Wv+FxERERERERERERERkcYt2HiDqkPNRUREREREREREREQkNFheWPsY5TbvW25I/R8c3hgw+/PPYcOGskEkADk5MGtW3VRVREREREREREREREREQpMCSUREREREREREREREGouUryFrM1BOVAiYrCQ73guYNWkS2Cu4G+D1wrRptVpDERERERERERERERERCXHOhq6ASENzuVz861//AuDmm28mLCysTpYJNc11v0VERKT2VfccIRTPKZrruVFN9iE3N5eXX34ZgHvuuYeoqKhaLd8UjqtIXWgK37UiIlJL9nxigkUsd/nPW27Y/7Pv4bZtsGZN5avMzq7F+jUS+m0VERER8WsK50ah2sbbFI6thI76aNPXe1BERESk5kL1ukSkIgokkWbPsiwyMjJ803W1TKhprvstIiIita+65wiheE7RXM+NarIPXq8Xj8fjm67t8k3huIrUhabwXSsiIrXA64HdcyoOIinmKfBNfvaZyUZS2amYsxneKdBvq4iIiIhfUzg3CtU23qZwbCV01Eebvt6DIiIiIjUXqtclIhWpIJm9iIiIiIiIiIiIiIiElANLofBg1eVs/siQTz6Bqu49uauISxEREREREREREREREZGmRYEkIiIiIiIiIiIiIiKNwd7PA4JEKlSUsSQjAxYvrjqQRERERERERERERERERJoXBZKIiIiIiIiIiIiIiDQGaT/4gkSCMX++gkhERERERERERERERESkLAWSiIiIiIiIiIiIiIiEOk8BHFpdrUWWLIGwsLqpjoiIiIiIiIiIiIiIiDReCiQREREREREREREREQkBOTmwfDn89ls5Tx5eB5YrcF5kAvzuWzh3HXS5uMwiv/wCrlKLjBsH//kP3HJL7dVbREREREREREREREREGhdnQ1dApKHZbDZiY2N903W1TKhprvstIiIita+65wiheE7RXM+NarIPdrvdV9Zur3psguqWbwrHVaQuNIXvWhERqdz69XDuubB7t3l8663wz3+WyChyeE3gAmExMOYXiOoKNjuc+hHMvwBS5gLg9cKaUotceSXMmAGWBdddB506wWOP1eluhSz9toqIiIj4NYVzo1Bt420Kx1ZCR3206es9KCIiIlJzoXpdIlIRm2VZVkNXQoKXlZVFbGwsmZmZxMTENHR1REREREREREREROQorVkDI0dCYSF4PGaezQZjx8JXX5lplt8Fv73uz0rS/z444TkTRAJgeSBrK8wdAK0Hs6PvSnr18m8jKgr27oWYGCjuO+T1Qr9+0LIlrFxZb7srIiIiIiIiIiIiIiIidSTYeIOqQ81FRERERERERERERKROWBbcdltgEEnx/K+/hnnzimYcWuUPIrGHQb97gRKjk9kcENsfOo4FYO3awO1cf31gEAmY7d1zT63vkoiIiIiIiIiIiIiIiIQ4BZKIiIiIiIiIiIiIiDSQDz6AxYsDg0iK2Wzw4ouYqJLDa/xPdL0cWiQUpSopweuG/n8FTCCJ02lmOxzwwANl1x8WBjfcAK1b186+iIiIiIiIiIiIiIiISOPgbOgKiDQ0l8vFu+++C8B1111HWFhYnSwTaprrfouIiEjtq+45QiieUzTXc6Oa7ENubi6TJ08GYMKECURFRdVq+aZwXEXqQlP4rhURkbIsC554wsSDWFb5zx84AOSlgCvL/0SPP4HXA3ZH4AJ2JyT8DiLiWb0avF4z+8wzoWvX8uvgcMD//V9t7E3jot9WEREREb+mcG4Uqm28TeHYSuiojzZ9vQdFREREai5Ur0tEKqJAEmn2LMsiJSXFN11Xy4Sautjv5GQzemKrVjBmjH/EQxEREWnaqnteEYrnUjonDH4fvF4vLpfLN13b5ZvCcRWpC03hu1ZERMpatQq2bq28jM0GZG0qMcMB7U4pG0RSUtwJrFnjDyQZNQpcLpOBpDTLgiFDql31Rk+/rSIiIiJ+TeHcKFTbeJvCsZXQUR9t+noPioiIiNRcqF6XiFRE3bxFpFbMmgU33AC5uebxKaeYeZ06NWy9REREREREREREQtW0aWYwFre74jJeL5C3zz8j7lhwVjKCrLcQ2pxAerp/1umnm8wj5XE6YejQalVbREREREREREREREREGjl7Q1eguqZOnUqPHj2IjIxk6NChLFiwoNLy8+fPZ+jQoURGRtKzZ0/eeOONMmVmz57NgAEDiIiIYMCAAcyZM6fa27Usi0mTJpGYmEiLFi0444wz2LBhQ0CZM844A5vNFvB3xRVX1OAoiISWWbPgiisgL88/b+lSGDHCH1giIiIiIiIiIiIifh4PTJ9eeRCJT0GGyUQC0O5UsDwVl7WHUxB9ItnZ5mFYGJx0EtgruRvQqlXQ1RYREREREREREREREZEmoFEFksyaNYsJEybw8MMPs2rVKk477TTOOecckpOTyy2/c+dOzj33XE477TRWrVrFQw89xJ133sns2bN9ZRYvXszll1/ONddcw5o1a7jmmmu47LLLWLp0abW2+/zzz/Pyyy8zZcoUli1bRkJCAqNHj+bIkSMBdbr55ptJTU31/b355pu1fJRE6teBA3DbbWCzQcmsWm43pKTA6683XN1ERERERERERERC1cqVcPBgkIXz0/E157ceApa30uIZed190wMHQkREjaooIiIiIiIiIiIiIiIiTVSjCiR5+eWXufHGG7npppvo378/kydPpkuXLrxeQU/1N954g65duzJ58mT69+/PTTfdxA033MCLL77oKzN58mRGjx7NxIkT6devHxMnTuSss85i8uTJQW/XsiwmT57Mww8/zMUXX8ygQYN47733yM3N5f333w+oU1RUFAkJCb6/2NjY2j9QIvXowQchKyswiKSY1wulPgIiIiIiIiIiIiICfP992Swh0dHwf/8HQ4eWKlyQDhQ1wLUZAvawStedvt///HHHVV0Xl6vqMiIiIiIiIiIiIiIiItJ0NJpAksLCQlasWMGYMWMC5o8ZM4ZFixaVu8zixYvLlB87dizLly/HVXRnrKIyxesMZrs7d+4kLS0toExERASnn356mbrNnDmT+Ph4Bg4cyH333VcmY4lIY3LwILz3Hng8FZdxOOqvPiIiIiIiIiIiIo3FggWBj7t1g6VL4csvYflyeOqpEk/m7wPLDTYHxPSvct3p6f7p446DwsLKy6sNT0REREREREREREREpHlxNnQFgrV//348Hg8dOnQImN+hQwfS0tLKXSYtLa3c8m63m/3799OxY8cKyxSvM5jtFv9fXpmkpCTf46uvvpoePXqQkJDA+vXrmThxImvWrGHevHkV7ndBQQEFBQW+x1lZWRWWlZqLioqql2VCzdHu97Rp4HZXXr6q50VERKRpqO55RSieS+mcMHSEYp1EQkFT+K4VERHDsmDRIpPRt9h770GfPv7HjzxiAkqSk4HcVDOzVW9whFe5/vQ0N8XN/4MHg7OKOwGlM6M0F/ptFREREfFrCudGodrG2xSOrYSOUHzPioiIiIhfqF6XiJTHZlmW1dCVCEZKSgqdOnVi0aJFjBw50jf/73//O9OnT2fz5s1llunTpw/XX389EydO9M375ZdfOPXUU0lNTSUhIYHw8HDee+89rrzySl+ZmTNncuONN5Kfnx/UdhctWsQpp5xCSkoKHTt29JW5+eab2b17N19//XW5+7RixQqGDRvGihUrGDJkSLllJk2axBNPPFFmfmZmJjExMZUcMZG6ZVnQty9s22amKzJ4MKxcWX/1EhERERERERERCXU7d0LPnv7HY8bAN98ElvF4YMcOuOoqWPZQF8jbAx3Hwu/Kb28u6aUXvfz1QTseD+zeDZ071/IOiIiIiIiIiIiIiIiISEjKysoiNja2yniDRjPOWHx8PA6Ho0z2kfT09DKZQIolJCSUW97pdNK2bdtKyxSvM5jtJiQkAFSrbgBDhgwhLCyM3377rcIyEydOJDMz0/e3e/fuCsuK1KeNG+G33yoPIhEREREREREREZGyli71T9ts8OKLZTP7OhzQuzeMGwcUHjAzI9sHtf70DLsvy0hRU7iIiIiIiIiIiIiIiIiIT6MJJAkPD2fo0KHMmzcvYP68efM4+eSTy11m5MiRZcp/++23DBs2jLCwsErLFK8zmO326NGDhISEgDKFhYXMnz+/wroBbNiwAZfLFZDFpLSIiAhiYmIC/kRCwf/+h+9mdLGWLeGCC2D48Iapk4iIiIiIiIiISGOwdCkUNVFz/PFw7LHgdJYt5/XCRefngifPzIhoD1532YKlpKebAWCioqBFi1qsuIiIiIiIiIiIiIiIiDQJ5dyaCl333HMP11xzDcOGDWPkyJG89dZbJCcnc+uttwIme8fevXuZNm0aALfeeitTpkzhnnvu4eabb2bx4sW8/fbbfPDBB7513nXXXYwaNYrnnnuOCy64gM8++4zvvvuOhQsXBr1dm83GhAkTePrpp+nduze9e/fm6aefJioqiquuugqA7du3M3PmTM4991zi4+PZuHEj9957L4MHD+aUU06pr0Mo5XC5XMycOROAq6++2hdkVNvLhJqj3e8ffrga8C8zYAB8+SX06GEeT50Kd9xR69UWERGREFTd84pQPJfSOWHw+5Cbm8s///lPAO68806ioqJqtXxTOK4idaEpfNeKiDQn/1rxL/785Z95/PTHmXTGpDLPb9kCLpeZHjvWZCMpL5DEbocBPTNgY9GMyPZgeavc/r59Zp2dOtV8H5o6/baKiIiI+DWFc6NQbeNtCsdWQkd9tOnrPSgiIiJSc6F6XSJSkUYVSHL55Zdz4MABnnzySVJTUxk0aBBfffUV3bp1AyA1NZXk5GRf+R49evDVV19x991389prr5GYmMg///lP/vCHP/jKnHzyyXz44Yc88sgjPProo/Tq1YtZs2YxvERKhaq2C/DAAw+Ql5fH+PHjOXToEMOHD+fbb7+lVatWgMls8v333/PKK6+QnZ1Nly5d+L//+z8ef/xxHA5HXR86qYRlWSQlJfmm62qZUHO0+71kiYW36J61wwGzZkGXLv6y48fD6tWwfHlt1lpERERCUXXPK0LxXErnhMHvg9frpaCgwDdd2+WbwnEVqQtN4btWRKQ5WZm6EoAle5aU+3yJZmzOPbds5t+SHK50/4OIdmCzVbn9lBTzf/v2VRZttvTbKiIiIuLXFM6NQrWNtykcWwkd9dGmr/egiIiISM2F6nWJSEUaVSAJwPjx4xk/fny5z7377rtl5p1++umsXLmy0nVecsklXHLJJTXeLpisJJMmTWLSpEnlPt+lSxfmz59f6TZEGpPsbP/0LbfAwIGB97C9XnjuObjoovqvm4iIiIiIiIiISEPKyM0AILMgs9zniwM9wsJgxIjKA0ncOen+hvzIDmCrulk/vSj2RIEkIiIiIiIiIiIiIiIiUp5Kbk+JiFSsOGgkKgqefrrs83Y7tGoFN9xQv/USERERERERERFpaKnZqQDsy95X5jmXCw4dMtPHHw/h4ZWvy1kyI0lUYpUZSSwLDh400wokERERERERERERERERkfIokESkLngK4Mg2yEtt6JrUGYfD/D96NMTGln//2umEc86p33qJiIiIiIiIiIg0tJQsk3KkOKCkpLQ0//Tw4Sazb6UKD4CtqDEusurIkNxcKCgw0+3bm8AVERERERERERERERERkZIUSCJSmywLdr0Pn3WHL3rDnET4+SLI3tHQNat1brf5//zzK78Z3a5d/dRHREREREREREQkVKQcMYEk+e78Ms+llogtGTIEPJ4qVuYtBIpGcQlvW+W280tssl0702QpIiIiIiIiIiIiIiIiUpICSURq04a/w6KrIX+ff97eL+F/QyE7qeHqVYfOPx/Cwip+vjjgREREREREREREpLko9Bb6pr1WYMqRlBT/dLdulbetmRW4ARs4o8ERUeW2SwamtG8Pdt0FEBERERERERERERERkVKcDV0BkVAQVuXd2iCWSf4Y1j5a9KDEMH+WG9xHYMWdcPpnNa9kHajpfufkmOljjoH4+MrL22w1qJiIiIg0OtU9r6jJeUhdq5VzwkYoFPchFOskEgqawnetiEhzkFOYE/A4PSedhJYJvscpKabNzLKgS5cgVmgVRYY4ooLafsmBXVq1UiBJZfTbKiIiIuLXFM6NQrWNtykcWwkdofieFRERERG/UL0uESmPzbKU2L4xycrKIjY2lszMTGJiYhq6OlLMlQ2fdYXCQxWXaT0Uzllef3WqI2lp0LGjmb7uOnjnHQWLiIiIiIiIiIiIFNuUsYkBUwf4Hi+5cQnDOw/3PX7kEXj+eXC5ICvLBHtUas3DsPEFiIyHi1KqKAzJySbTCcDnn8O4cTXZCxEREREREREREREREWmMgo030FhkIrVhyytQmFlFIW+9VKWu7d7tnx450tzwrrGc3eYm+LonIXWeGYZRRERERERERESkEUvKTKr0cUqKaQaLjAwiiAT8GUlsjqC27/H4pzWImYiIiIiIiIiIiIiIiJRHgSQiR8udAxufpakEilRlzx7/dK9eEB5eg5VYFqx+CD7vCWsehPVPwY9jYN4pkLun6uVFRERERERERERCVNLhpEof79kDbrc/62+VvG7zv80ZVHG32z/tDG6RCm3cCJddBlFR5u/KK2Hz5qNbp4iIiIiIiIiIiIiIiDS8o7yNJNL4ud1uPvroIwAuu+wynEHcXQ1Y5sQCnO7swAKOSGhzIhTsh6xNtV7n2lDT/d606SOuvhpmzbqM7t1r8BViWbDqPtj8comZRUE4B5bBd7+Dsb9CROvqr1tEREQaRHXPK2pyHlLXjvqcMET2o7pqsg/5+fm8+uqrANxxxx1ERkbWavmmcFxF6kJT+K4VEWkudh3eFfC4dEaS4oy/iYlBrjCYjCQ5yaYtMi8VT5IXGAccXUaSuXPhggvAZvMHp/z3vzB7Nnz/PZx2Ws3XHQr02yoiIiLi1xTOjUK1jbcpHFsJHfXRpq/3oIiIiEjNhep1iUhF9G6TZs/r9fLbb7/5pqu9TLslmOQ+Rcu2HwUnz4SozuZx0kew5NparvXRq+l+u1y/0bs32Gze4G92l7RzeqkgkhIsN+TsgtUPwPB/1WDlIiIi0hCqe15Rk/OQunbU54Qhsh/VVZN9cLvd5Obm+qZru3xTOK4idaEpfNeKiDQXpQNHSgeWZGWZ/4MPJCn6HrdVkGA8Jxm+6AvefAA8ewZQHEhir2FO8oUL4aKLwOs148IUc7vNOu+/H5Ysqdm6Q4V+W0VERET8msK5Uai28TaFYyuhoz7a9PUeFBEREam5UL0uEamIAklEjlb6fLAVfXlHd4NRn0FYK//zXf8A7hzY+mrD1K+OxMRAixbVXMiVBSvvAWyAVX4Zyw0HVxxl7URERERERERERBrG9kPbK33sKUowkphoph2VJBoB/JlIijOTlFaw3xdEAuCw+8sF0Ueo7OoK4E9/MnWzymnC83prtl4REREREREREREREREJHQokETlaltvERdjscNon4Iz239wFM93reshJqnAVjVHnzjVYaMOzUHiICoNIfGo4VKKIiIiIiIiIiEgDK85A4rQ5cVtudmfuDni+OAijZcsgA0nsTtP+6A0uesNp95erScDH5Mmwa1f5QSTFNCiaiIiIiIiIiIiIiIhI46be2iJHy1YUj9XxHGgzBOxhZctYXuh9S/3Wq4516lTNBdx5sPU1oNRd5viRkHguOEtkcSldRkREREREREREpBEo9BSSkZMBQIswk843x5XD4fzDvjLFGUmcwQ7zZHOYcVkqykhSytFkJMnNhb//vfIgEhEREREREREREREREWn8lJFE5GgVZyTpfSt4XeUHktjs0KJjvVetLnXubG4o22xBLrD3c3Bn+R9HtodRn0P8cPO48BAsuQH2fFrbVZVmpKAANm400wMHQnh4w9ZHREREREREypeeDrNmwYED0LMnXHIJREU1dK1Ejt6erD1YRdl4YyNjOVJ4BICkw0nEJcQB/uCO4ANJigpaQWYkcfjLuVxBbqPIrFlw5Ij/cVgYjB8PN99s2gLffBPeeKN66xQREREREREREREREZHQo4wkIrUhLBY6/r78IJJi3mretQ1x8fHVHNEw6QMzeiKAowWc8ZXJ4FIsLBZOnQXxJ9dqPaV5cLlg0iTo2BGGDDF/iYnwt79Vf+RNERERERERqTteLzz4oMl0OmECPP00XHutuYabMaOhaydy9JIOJwFgw0abyDbYMKOwJGUm+coUt1WEVdKUGKC4TS3YQBK7v5zHYz53wZo+HexFdw1sNnj3XXj5ZejfHwYMgFdegbfeCn59IiIiIiIiIiIiIiIiEpqUkUSkNiSeA/YqPk6VBZk0QmFhZhTCoLiyYO9XYHnM4yGTIe4EsDv8ZWx2sOxw+hcw/4Jarq00ZVlZcNFF8OOPge/JAwfgsccgLQ2mTGm4+omIiIiIiIjhdsMVV8Ann/iv34o7uGdmwjXXmE7v117bcHUUOVrFASN2m5320e2x2+x4La8vwAT873uHo7w1lMPuBCwozAyquMPu8U0fPmw+V/YghpRKS4OffvJ/PidNgquuKlvu+ushNzeoqoiIiIiIiIiIiIiIiEiIsllW0F3BJQRkZWURGxtLZmYmMTExDV2d5m3/Evh2pJke8R/ofnWTCxYpT6tWkJ0NTz0FDzwA4eFBLLT3S5g/zkxHJsCFyRUfK8sLm/4BA+6ttTpL02VZcN558M03plNEeYYNg2XL6rdepRUWmqwpUVFmNE8REREREZHm6MknTcf0ylojBw+GlSvrrUoite6Jn57gbwv+hsfr4Zrjr2Hammk47U7uGn4XL455ETDtA3l58MwzcM89QbSvbXgG1j5mMpJcchjCYwOfP7gSvh7qf5jdmra3HATguedM9p9g2vDeeAPGjzef0U6dYNcucFYwdo7LVY2MKiIiIiIiIiIiIiIiIlJvgo03CGIcMhEpV9ZW/3TsoGYRRAJm9FCo5o3izI1gKxpi8ZibgSp60vcoZ6hDkXK88QZ89VXFQSRQ+XN1be5cGD0aIiOhZUvo3h3+9jeN2ikiIiIiIs3PsmXwxBNVZzcNJmuCSChLykzCa3mxsOga0xUAj9fDrsO7fGWKM5EUt7NVydnSn+m3cH+VxaPC/Q0P6enBf65Wr/YHjvzlL5WX1UAZIiIiIiIiIiIiIiIijZtuzYrU1JHfwFYUTRHTp2HrUo+8XvN/8Q3voGRuxBc80uMaf1BJeWx2aNGxptWTZuTgQbj//rLz27aFNm3qvz4lud1w770mW8qPP/o7SiUnw+OPw/DhZlpERERERKS5uP/+sh3PTz4ZrrwS+vb1zytudzhaJ/3rJGxP2Eg+rIsvqV87Du3Aa5k3cq82vQCwsNh+cLuvTHGwRtCBJJHtgaLGhby0qouHFxAVngOYQJKKsoqUtm6dyTRit8ONN1a+XLDrlIpt3QqPPQaXXAJ//CPMnAk5OQ1dKxERERERERERERERaS50u0eaPbfbzZw5cwC46KKLcAZxF9TtdjNnUS7kXsRFXX7EGVZx2p9QVdP9vvjiOXg84HJdRNBfIYfXgeWG2AHQqnfV5b2uZpPhRWpu6lTIy/M/7t8f3nwTTjvNPP7pJ7jllgapGg88AJMnm+nSGVG8Xti8GW67zWQsERFpCqp7XlGT85C6VuNzwhDbj+qqyT7k5+czdepUAMaPH09kZGStlm8Kx1WkLjSF71ppvlavhvnz/Y87dDDXQ0OH+ufNnAnXX19721yWsgyAX1N+pWtc19pbsUgVdhza4ZvuF9/PN52UmeSbrnZGkoh2/um8VLC8ZjCWSrRpeYDcg9Gkpwe3CcuC9evN9KhR0K5d5eWbgob6bXW54KGH4MUXzXvB6zXBOzNnQvv28MUXcNJJNVq1iIiISI01hXaHUG3jbQrHVkJHfbTp6z0oIiIiUnOhel0iUhFlJJFmz+v1snHjRjZu3Ig3yGEvvV4vG9Nj2Jg9AG/LIAIjQlBN97tfv40MHLgRlyvIIUItC7I2m+nWQ4JbxqYfQqmc2w2vveYfqfaEE+CXX2DkSH+ZU0818445pn7r9vHH8I9/+LOQlMftJuiOHCIijUF1zytqch5S12p8Thhi+1FdNdkHt9vNkSNHOHLkCO4gej9Wt3xTOK4idaEpfNdK8/X66/7sBYmJ5lrtuOMCy1xxBXz6KYTV8rgSK1NX1u4KRSrhtbykZqf6Hvdr2w97UcDHofxD5LpyAf/n4ciRILP+Rrb3T+enmwFbqtAhdh8QfPtDRgZkZZnpM84wwQ5NXUP8trrdJoPtSy+Zxx6PaUMqHohk/34YP75GqxYRERE5Kk2h3SFU23ibwrGV0FEfbfp6D4qIiIjUXKhel4hURIEkIkerVa+GrkGDKJ1loUJ5e8FjbpIT2x+8hVUvY7PVuF7SPMydC2lpZjoqCr75Blq18nfEADMdF2cCTupLdra52V/yLRwTA1ddBbfeCv38A5EG/xkSERERERFpxPLyYNo0f+aFV16Brl3LBow4HPD738Nllx39No8UHPFNF2cmEakPadlpuL3mzR7hiCA2Mpa4iDjf88mZyYA/eCQlpQaBJAXlRIZExIM9cETZxNYpgDfoQJKNG/3TAwaYDBlS+/76V5g3r+IBSLzeygcnERERERERERERERERqS26HSRytFp0Bm8zGKKvlMLCIOM9Mjf5p2MHAsHcHRep3Pff+zsd3X03tG0bGERSzOk0z9WXf/8bDhzw3/C/8EJITYWZM01Ay6ZN8M47tT/CroiIiIiISKhauxby8830kCFwySUVXxPZbPDnPx/9NktmIVm2V4EkUn+SDif5puOj4rHZbHRo2aHM87Gx5nFKSpArDm8LFDXE5WeUzeYb3RXGbYGRM3yzOsSk47R7yMgIbhMbN/rb+o4/PsgAF6mWBQvg5ZcDA0VatoRRo8wxL6ZAEhERERERERERERERqQ8KJBEJUoU38BwRzfLu3r59QXaGz9qM70Z33LFg111oOXpLl4LLBeHhcM89lXduqK8RNF0ueOEF/9fBDTfA7NkQGRlYjz/9Cf73P3XIEBERERGR5mHlSn/n9DvuMNdOFbHZIDr66LdZMgtJZkEme7P2Hv1KRYKQlOkPJElomQBAYqvEMs936WIep6YGuWK7A8LizHR+OtjKaeyI7mqyARdpH5uOzWZRWAhHjpQtXtrGjWZADqcTevQIsl4SNMuC++/3twfZbPD445CRAfPnw+rV8NtvMHhwg1ZTRERERERERERERESakXLGbxeRYnPnmgwD8+ZBTg60awfjxsHtt5coZG+eqQX27AmyoCvTjJJoA6K71WWVpJnweMyItgAXXABt2jRsfYp9/71/JNFOnWDKlPKDWBwOOPNMuPTS+q2fiIiIiIhIQ1i50lwHOZ1w5ZVVD0pRG2N1lAwkAViespxOMZ2OfsUiVVibthY7drx4iQ6PZnnKcsId4dixY7PZWJtmGjQ6dzafiaADSQAi48F1CPL3BVW8fUw6Hq+JWti/H1q1qrx8aiq43dCnjzKp1oWffzYDo4BpL/roI7j44sCMz927w6JF8Ne/NkgVRUREmrbkZHNSVFJqKhw+bKbj4qBjx8Dn4+Oha9f6qJ2IiIiIiIiISINQIIlIObKy4I9/hC++MJ0dPB4zPyMDpk2DmTNh4sSiwhUFkuQkQ0FRg2ReKhQehpY9od3Iuq5+vdgb7GCe3kLzf3gbsCkFgxy9rVshP99MjxoFhYUmM0lDW7zYdAJxu+Gxx8x0ZW67rX7qJSIiIiIi0pB+/dVcJw0ZAhERVZevjeyNi3cvDni8LGUZF/S74OhXLFKFz7d+jhcvAD8n/cyJ/zrR/6QFc7fNZQpTSEw0AQT5+aYdMiYmiJVHJsCR34qy/1atXasMvJb5QG3YYPpAVvb5KigwgVzduwe1eqmm117ztzOPH182iARMW5LdDk891TB1FBERabKSk6FvX//NpWBFRsKWLQ0STJKZaeJeYmLMQIciIiIiIiIiInWhnLHSRZq3zEw46yz46ivzuDiIpJjbDV5viRled9mV5CTDF33h66Hmb/55sPiPMO9kyFhctnwjVJx5oUqeApONxB4CPf2r8PzC57E9YeOur+9q6KpIJVas8E+fdFJoBJGACSTxeEyD/nXXVT56p80G0dH1VjUREREREZEGUVgIGzea6cGDS7Wn1JGDeQfZnbU7YN6ve3+t+w2LAPtyKs8Wsj/XDDqTmGjaGKEaWUladATsUJDhH7ymEu1j033Ta9aUbeMsLS/P/B9MwJdUj2XBjz+a1yAmBp5+uuKydjtERdVf3URERJqF/furH0QCZpnSWUzqkNcL774LQ4dC69ZwzDHQvj307g3PPus/XxMRERERERERqS02y7Kshq6EBC8rK4vY2FgyMzOJCWqoOqmKZVm4XC4AnM4wLr7Yxpdf+m+uxsXBOeeY/1NSYO5ccLstDvyrHS0jswg77mFsgyYGBkocXGkCSMozcgb0uLpO9ykYJfc7LCwMW+kh8CpY5pFHXEyeDLm5YWRl2WjVqoqFVtwNW1+D6K5w/rbyyxRnbynO3AINkr3ljHfPYH7SfPq06cOWO7bU67YlePfcA1OmmM9oTo4ZEKqheb3mO+LIEbjiCvjgg+CWsSucU0SaiOqeV9TkPKSu1fTcKNT2o7pqsg9er5fc3FwAoqKisFfxg1bd8k3huIrUhabwXSvNz+rVJoAE4M03TdB9XQ8G8O32bxk7YywAUWFR5LpyiYmI4fBfD+tzIHUu/KlwXF5Xhc/bbXY8j3n47DO48EIzb948OPvsIFa+/A747U2wXHDmPOhwJthKnVeVaJNcm3wsx09cC8Bll8GsWZWv/uSTzSAZl14KH30URH2agPr6bd21C3r0MNN//Sv8/e+1k31JRERESvF64PAayCyKZo8bBHHHwarVJjqjJlasMOkV69i+fXDeebB8uRmMrHQPDpsNTjzRnK/V1b2lptDuEKptvE3h2EroqI82fb0HRURERGouVK9LpPkJNt7AWY91EglJNpuN8KJeDHPmwGef+Z/74x9h8mRo29bf6XvjRrj5Zhs2bITbXeAtwKTcaFxK7nd1lunSJdw34s3evdCvX1ULFTVCWBUMO1qcvcVbzkhAoxfVazDJwuSFAGw9uLXetinVl5RkRu3s3z80gkgAfvvNBJEAjBhhRt2t6uOlIBIRaUqqe15Rk/OQulbTc6NQ24/qqsk+2O12WrZsWWflm8JxFakLTeG7VpqftDT/dH1llFyeshwbNiwsOsd0ZuuBrWQVZLHr8C56tO5R9xVoapKTy47CnJoKhw+bERU6dgx8Lj4eunatr9qFFK/XW2kQCYDX8pJbmEvHjv6UE0lJ4HJVntkUgIj2/umDq6D9KLBV/KFqHxOYkSRYzen+VH39ti5a5J++4AK1CYmIiNQ6rxu2vQlrH4PCg4HPRbSF8AkNUq1gpaSYoN49e8zj8oYBtay6H6CsKbQ7hGobb1M4thI66qNNX+9BERERkZoL1esSkYookESkiMsFd95pGuC8XnjhBbjvPjMN/oa5Pn3gl18g872iu7t5e8Be1Z3eRspTAO5sCIsFu/m66NzZ34C5cyf07VvFDWZ7uImz8RaW/3zB/vKDSACyd9RbIEnqkVQ8lsf3eNvBbRzT5ph62bZUT16eeQ9269bQNfFbutQ/fcop9dM5SkREREREJNTll7jcT0ysn23+uvdXLEzDxcB2A9l2cBtey8uylGUKJKmu5GTT8JNfQbtNeSIjYcuWZhlMsvPwzqDKrUxbSffEU32PV6yA668PYsHI9mC5zfSBpYHZkcsR38ofAFQ8AEZlmYWLB+sorKAJT2pu0SITKGSzmcHQm1OwjoiISJ3L3gE/ngNHKhgkruAAZH9oTnaqc14LZpn4+KOvYyW8XpM9bu9e8BTdpjz/fLjnHnMNdfAg/Oc/8O9/+58XEREREREREaktCiSRZs/tdvPll1+ybx+kpp6H1+vk9783QSRQdmQXpxMKC938cGQstsLDnNdmW6P8IBXvN8B5552H01m0F64s2PYv2PQS5Kf6F4g7Dnffv5K+rwUXXmjjiy/O47ffnJx1VhWd5u0RYFFxsEgd2pu1l1xXLr3b9q6y7Lfbvw14/PW2r/nLSX+pq6rJUSjKuhsy2UgAdu823w02Gxx/fEPXRkSk/lV4XlFL5etDTeoUivtRXTXZh/z8fN566y0A/vznPxNZxY9ydcs3heMqUheawnetND8l+2lFRBzduvZk7iHcGU776PaVlluyZ4lveljiMD7b8hlOu5PlKcu5bOBlR1eJ5mb//up3tsvPN8s1w0CSX/f+GlS5FSkrGD70VGw2M1DG0qVVjyxtWWCLbA9FQVJk/FLldpwOD7EtDpOZF4fXCwsWwNix4HCUX764DgUFQe1Gk1Brv61eNyR/DJtfNp1Y3XkQ1griR8KAB1iw4DRcLhvDh2vwERERkVqVnw7fnwm5e/zzWvaCuEFm+tBayNkJ7cNNsHPJTHubNsEf/xi4vhkzoH9//+N6yLb35ptmAEOADh1g1iw4/XQTNOJwmPPA4cNhwgR4/PE6rUqTaHcI1TbepnBsJXTUR5u+3oMiItIY7NoFkyfD3LkmADsiwpy+jx8PV1yhdjhpOKF6XSJSESVRl2bP6/WyZs0a0tLWEB7uxW6HqVOrGtXFy9oD3Vlz5AS8R3bUV1VrVfF+r1mzBq/Xa1oiNzwLczrBqvsDg0gADq/Hu/g6du9ZywknrMFu9/LLL0GcdDnCAQsKDpqbqPWo8z8602dKHw7nH66y7Nfbvg54/L9t/6ujWsnRKu7QEEon/Hl5JoikbVszwqSISHNT5ryilsvXh5rUKRT3o7pqsg9ut5tDhw5x6NAh3G53rZdvCsdVpC40he9aaX5cLv/00bR557vz6TK5Cx1e7FBpubTsNPbl7AOgVXgrhiQMwWt5cXvdAQEmInVhzb41QZXbkLGBsDBo3do8Xru26uANtxuI6uyfkZ8GOUlVbiuxdYpvesECf5bh0lwuM3CHzQapqeWXaYpq5bd1x3vwWXdYdBUcXGkG6bFcUHgQUr+B704nLfkwYDqBaiTxavLkm2M8bxR81gPmdIavjoPVD0JOckPXTkREGpJlwaJrTBCJ5YHoHjByGozbCqM+NX/nb4Ph70CLjqZH2ZAh/r+SASPF+vcPLFPHQSQeDzzyiJkOC4MvvjBZ78Ef/FucyeyYY+C11+q0Ok2i3SFU23ibwrGV0FEfbfp6DwbKzzfZoU47Dbp3h06d4Nhj4YEHIKnqS3MREallyckmUKRXL5gyBbZtM4EkqamwbBlcey2MHFnUpirSAEL1ukSkIgokESnB7YZhw6BHj4pH5yuj4KC5QVhSRDzYKxjFITzuaKpYNywLVt4LayaCOxuwIKItdL0Met0IncaBvWzv+F+qHvwQT1gCWG6zziNbar3qFdl+cLtv+pNNn1Ra1uP1+AJHnHbTs+WHnT9Q4K78Lr7X8mJ7wobtCdtR1laqo3gU28LChq1HSXlFMVItWjRsPUREREREREJJyQEujybLwdytc33T6/atq7Dc8pTlvul+8f3o387fOWxF6gq8lhrfpe5sORBcu1dxm1VionnsdsPixZUHGISFAbEDgBJtUClfg9dV0SIADOmxEofDRI/8+GPFAV0Oh+kY43CYwbp1nypIG56FJddBXlHAjiMc2p8Bnc6DtsNNp1Ygv9C0q7Ztq0CSoHndsO5J+KSjOcYZv0DOLsjbC4fXwaYXTQDP0ptB3+0iIs3TzumQ9q35vY0dBOeugW5XgK1E9webHXr8EU75sOHqWYlffzUd3gD++lcYOrTi8zWnE+Li6q1qIiKCuV5/4gno2BFuuAEWLTKBIykpsH49vPyy6Vt00026jhYRqS/bt5sgkdmzzXevx2OC/EaNMoO4FPfbsqyjG9xKRKQ50delSCm//725IKzWycSRbdBmiP9xdFcYtwUK9kPmJlhcIjVyi461Vtdas/3fsOUfZjqyPQx6FHrdBI4SPT7y98P6l8Afn8HevSbKt9IBeWIH+KcPrzONufa6/+p5f937vulpa6Zxw+AbKiy7MnUlmQWZAHSJ6cLOwzvJd+fzy+5fOLPHmRUuN3/XfN90cmYyXWPrdmQiMaKizP/5+Q1bj5KKR/S0KaZIRERERETEp2QgydFcw01fO903PXPdTJ7t8Gy55ZbtXeYbIGJg+4F0ie1ChCOCAk8Bua5cth7YSr/4fjWvSHMTH29exOq8eJGRZrlmKNoZ7Zt22Bwktkr0PU7NTsXtNUPgRYWbho2uXU3HE4C5c83IphUxbZXREN3NdKYH2DoFet9SaZ2O67KWDxdfDcDSpbBqFRx3XNkBdLKyTCdGyzKDZezdC126BLHTtcDjgXnzzIA1WVkmA21CAvzhD+YmcMhK+tgMygMQ1gr6ToC+d0FEG3+ZI9tg47MUuExaXQ1AEiRPASy8FPZ+CRQ1ukV3g7YngiPCZONJX2CeO7Q6sMOwiIg0HzveAezgjIIzvgRHi/LvP9rDCAjGDSGff+6/H33//WCv4idNHeFEROpPQQFccom5Xi/uC9C9O5x4orluTU6Gn382z61ZU/V3uIiIHL3MTBg9GtLTTXvpGWfAxIkwZoy/TFaWyeT33XcNVk0RkUZHp7Iipfzf/9XgIi9zfdkRAKO7muCS2HJSI4eaVfeb/yM7wJjFcMytgUEkYDKUHPtYmUXnzAFXJYMfOlqX2P/MjWUL1EH2FsuyeG/Ne77HPyf9zN6svRWW/2b7N9htdmzYGNpxKAB2m52vt31d6XbeXvW2b/q91e9VUlJqU4sWJmBj166GrolfcUeA4swkUk2WBQdXwq73YdtbZiSx9J/Bq2E6RUREREQas5Kdpjdv9t94r45DeYeY+5s/I8m0NdMqzCzy7up3cXvduL1uvt32LcPeGoatRMT/Wyveqn4FmrOuXU16ihUr/H8zZgSWmTEj8PktW6oYcaTpynHnYCvqpHhCwgkk353s+zu92+m+crmuXAD69SvKNAJ8803F2ZG9XlhXnIinzRB8TfqZ6yH120qzkhzXdS0er/8z8OyzZbfjdsOrr5r5xdky1q6t+9FU9+2DBx4wI7uec46p2+uvwyuvmPk9ephgktrK4OHxevDUZjvDstsAG4TFwdnzYdBjgUEkAC17wkn/wuE0r5nbXXubb7IsC5beBHvnAha0HgKnfwHnb4NTZ8HIaeZ4n7/NtGFbajsSEWmW8jPMPQS80OcOaNG58kHs6mGAu5r45BNzfnDKKRAT09C1ERGRYpZlsox89ZWZHjoUvvwSfvsNPvwQpk2Dn34yo+LfdpsyT4qI1Je77zaBfG43/OUvJgPz734XWCYmxgRpv/9++euokczNsHuO6cuU/F84sKxmNztEREJUaLaaiDSgnj1rEEiS+i30+FOd1KdeWF7TM/+0TyCqS/kNqjYb2Px3mp1OE0Dy2Wdw110Vr3pXSizdI9pBQQZkbSq77uLsLekLAjO3QI2zt6xMXcn2Q/7UKRYWH67/kHtPvrfc8l9u/dLXCeWcY87hv5v+i9fyMnfrXJ4f/Xy5yxzOP8zHGz/2PX5r5Vs8POph7BoBr851727ef1u2mMCNGo/maHnh4ArI3QOefHBGQ0x/iOld7VW1aGGuEQ4dMg1FFXX+kFJykkzgyK73/SOqlhTeFnrfBsc9odElRURERESOgtsN2dnmOr5ly/obFf+YY/zTK1bAqaeaURurY/am2b5MDmAyOyxMXsiobqMCynm9XnZn7fY9TslOISU7JaDMDzt/qN7GxQSFVBYY0r8/DBlS8fPNyPaD27GKsid0iukU8FzHVh1x2Bx4LA87Du4AYPhwePll8/y6dbBypckWUnqkabvdDOQyeDAQdzzs+dy0aQBsfB46lhhyzxsYqXBc17UBj2fPht27ITHRtF14veZvyhRo185fbsMGM7pfdT+vvmOx3WwnPx+io6FPH+jQwf/8r7/CuHFw4IBpR4mMNNtLTITCQli+3ByTpKTaaWNZn76eY18/lhbOFuQ+nHv0KwTwFoDdglM+LMrAXE5Fi9oyIiId5OZBbq6y2VZp7+ewqyhgLWG0CSKx2cu2C0V3h5Neh92f1ncNRUQkFOyZgy9rVferGuUP7OHDsHWrmR43zlyrFQcZi4hIw/r8c/84GqNHwxdfmGvT0v2IunWDqVPh00/rvYoiIs1OVpYJDvF4zKA0r75q5pd3Du10Qps2ZedXS26KyYK4ayZkbS77fItE6D0eBk5UfyYRafT0LSZSSmQFyTEqlfJVIx/9zIL2p0G7k4tSPFeteAS9BQtgz57yR1nwes1FNrGDzIz9i/03ukuK7lqrmVveX1c2rHja2mnllj2cf5hlKcsAk4Xk4v4XE+4wd8k37t9IypGUcpf7cP2HFHoKfY/3ZO3hp10/HWXNJRhDhpgGda/XpImttozF8Out8EkH+OYkWHAxLLoKfr4AvuwDX/Q1HTEqGOG2PB06mM9Efj5s2lSDOjVHSbPgywGw8TkTRBLZ3tzw6X0b9LjWjNpZeABSv9FFl4iIiIhIDaSkmNH9x46FqCho3RratzfTffvCQw/BkiV1O3BWt27QqpWZXrmyZp3Sp60pez0/c+3MMvOW7F3i68RfkW0Ht1W/AiJBSs5MBsBpd5IQnRDwXIfoDr7BR/Ye2YvX8jJ8eODy991XNojE7YaNG80oqADEHQdWiWCRfd/Dhmf8j3OTApbvGJdKXKy/vMcDl10WmFH1uusgPd3cdC1uF126tPqf1/XrYeJE6N3bBJH97nfmpu6oUSbryIgR8MYb5nvnd7+D/ftNkMmUKWb7n39uvrPeecdkRFm3Ds46q3p1qMhzC58DIM+dx56sPbWzUoC2wyFxbJWjnEdHm86tW7aog2iVtk41gxlFd4NRc8yxLa+9uritqMuF9Vo9EREJEWnfAw5odQzEDWqU9xAyM/3TffuWPQ8UEZGGM3WqCRzp1s0M7OB0lv89XRxYcuGF9Vo9EZFm6eOPzQA0AM88U3U2qKNqg9s9B77sB+smmSCS8NbQ5WLoeQN0uwKiOkNeCuz5rFFei4iIlKYmCQlKXp65gZiaCgUFptNBz55mJLymNvJ+YWHVZcoudMhkJUk4O+hAjNBimY7bXle16+92wx13mAvokjweE2Dy/vtw55SBkLEQ8tNh30/QflSdpZH2eD1MXzsdABs2BrQbwIaMDazdt5bN+zfTL75fQPlPNn3iy0bSNbYrSZlJ9Gnbh/Xp6wH4eMPH3DWibMqVt1a8VWbe26ve5sweZ9b2LkkpQ4f6p5ctM4ElQXVu8BTAyrvht9fBVvT+63AWxI8ARwtwHYa07+DQakj+GAY8EHSdSnb++OUXM9JmTUftbBa2vgbL/wLYoPXxMPhl6HC6ucCyvP4LrUOrYfs7DVlTEREREZFGx+2Gp5+Gp54y1+Y2mxnlf8AAc9N73z5YtQpeeMGMrvjbbxARUTd1sdnMNdv8+SaQpLr2ZO1hYfJCADrHdCYtOw23182H6z/k1XNf9Q0EATBn05yKVuOT48oh351PpDMSkpNNT/ZiqalmWGCAuDjT872k+PjKM3NIs5ZTmENmgekNaMNGQsvAQJKElgm+9ieX10V6TjpduybQpg0cPGjK/PgjfPutCbIovtHpdML995vBNABoU072lzUPwf5FENkBkj4OeMpmg6HH5/LDghhf0NiSJaYdY8wYk/lj4UJ/2b59zaAdX31lsmdERVW97243PPYYPPusaSf2eODEE802WrQwnSS//95kIXG5zHrz800GlJ9/Nm3MxR1ySg4mPmAAPPdc1duvStLhJGau8wef/WPxP3hp7EtHv2Is6HldUO2pJ5xggvsWLaqFzTZl2bsgbR5gwTG3gj0iIEO2iIiIT+FBwGOyzFckJxkK9kNeKhQeNoNXtRtZXzWsUm6JJGktWzbKpCoiIk3Srl0wb54ZeOXWW02bWVPrEyUi0hj95z/mnHnQIDj++Drc0La3zODEALEDYPALJmtu6X6O+5fAjvfqsCIiIvXHZll1Oe6g1LasrCxiY2PJzMwkJiamTrdVWAj/+peJ6Fy0yNzoK61VK7j8cjOaXGO9eLIsiy++yOXKKyE3N4oNG2wMGFD1Mrm5ubD8DqL2TseGGzqdD6d/VrbwwZXwdYme779fUf5N33pmWRa52z6BxX8iypGL7eJUaJFQ9TK5uVgWdO8exYED/lbNefPg9NPNjW7LMidv551nbpKunPU6LLsdE7ByDYwsJztI6eMENTpW3+/4nrOnnw3AkI5DOLvH2by02NwcnnjqRJ4686mA8n2n9GXrga0Vrq9zTGd23707YN66fes47o3jAOgf35/kzGRyXDmEO8LZd98+4iLjqlVnqR6PxzSq5+fDH/4A//1vEAt5XfDD2ZC+0Lw5B06E/vdDWIx5zrJM8ILdCbl7YMurMDj43gol63TddWb0zKoa/Ys/J81OTjJ83suMoNr5Ajj1Y8BWfnCZ5VGHAZFGwnduBERFRWGr4guuuuXrQ03qFIr7UV012Qev18uBAwcAaNu2LfbS+dyPsnxTOK4idaEpfNdK3cvJMaMgfv+9efznP8P48XDccYHlDhyAjz6C2bPhu+/qtk733w+vvGI6m6ekQELlTQ+4XP5O9C/88gIPfv8gNmzcNOQmNu/fzPyk+QB8evmnXNDvAt9yI/89kiV7l1RZn48u+YhLWw03Pebz84PfkchIk06guQeTrFwZOMLDihUmWqiZ25ixkYFTBwImkGTKuVMYf+J43/PT10znT5/+yfd4yY1LGN55OOPGmaCN4kCRxET44gv/IX3oITPC3uDBRcFYlgWftDedIoP02KoUnpnc0ZdduCKDB8Oxx5pBYdxu07bxxz9WPHqfy2VGXx03Dr7+2sy7806TlaRDB7NPXq8pY7ebDK4PPABffmnKzp0Lo0fXfYaOO/53B1N+neJ7HOmMZO89e2nTok3NfltLtqdetBeiEqusw7PPwiOPmPajlJSycWpSZNPLsOp+00Z3cRpEtG3oGomISKj69hQTSNv1Mjh1Vtnnc5JN9nlvqfP90Yv8wSSlz2uhXs9td+2CHj3M9Jdfwv/9X71stlIN2e5gWRar01aT0DKBjq1qfrIUqm28atNppupoAIv6aNNvzu/Bl182bVl2O6SlQVtdloiIhIT4eHNf48EHzSBadZLRL3cPfNbD9GdK/D84bbbps6T+TFJNoXpdIs1PsPEGykgi5Vq6FK64ApKSTLDIFVfAWWfBsGHmvnlmphmtbt48M0pdYw0iAbDZbAwcGO0b+eV//4PevSu/iWmz2YiOjobuY2Hvf8zMlLlweD3E9G0UWUlsNhvRznxwFu24M7r8gsUj9gC2vFSii0btOf30kXz2mT9V3FVXmRvNZ59tbiRPmGBuCA8eDMQdBxTFrCXNgsEvQUR8nfSi/8/q/+AoOlH7XbffcXKXk3l+0fMAvLv6XZ444wlfw4jX62XbwW2Vrm9P1h4K3YWEO/2jnL696m3fNi7sdyFb9m/h0y2f4vK4+GDdB9x24m21vl/i53CYkRyXLIHPPzftb/HxFZe3LLBtewvSfzY3ok//EjqO8We9KP15bZFYrSCS4joNG2a+F3/4IbggEa+3cX931tj6vwGWSf148kxzYVVRqkdddIk0Gr5zozoqXx9qUqdQ3I/qqsk+2O122rVrV2flm8JxFakLTeG7Vures8+aa5KICBMkcu65+LIQlNS2Ldx8s2nvqWtDhvgHJ3n9dXj00cpv8pRsj/nP6v/4sjiM6jqKji07siBpAQDvrX4vIJAkLTstqPpsytgEBb2qF0QCpvz+/QokkXIlHU7yTVtYdIjuEPB8h5aBj5MykxjeeTijRplAkmIpKXDKKTBypMketHFjqQ3ZbNDuVNjzOeAlGCNPzKkyiKTYoEH+74zJk+H66ysuGxYG//63aUu12Uxw2h/+4G8PKQ4gKdanDxw5YtpC+vc33091bX/ufv614l8AtAxvSXZhNvnufKYum8ojox6p2W9ryfbUsFblFyzRnkpeKqf0CMPjGQOYzDOXXlr3ATSNUkEG2B0Q0b7iIJLSo8tDyI0wLyIi9aD4N9idXf7zBfvLBpEAZO8Imd+Mkv03tm0LDKhvKA3Z7jBz3UyumXMNAK5HXTjL66xXR3Wqj/YTtek0Q8nJdTaARX206Tfn92BGhrlubd++joNISgcagT/YSJlyRUTKyMkx/8fFlcjeXNs2PA1YEBYHp3xo+pOpP5PUQKhel4hUpPIwc2mW1q2DU0+F3bvNKJY7dsC0aSZQYOBA6NXLdAK49VYzQt6HHzZ0jY9er17QrZuZ/vrrajTUdfw92IoasiwP/HwheArAKnHG4g3yTm1DcEb5pz15ZZ8vHrHn66Hmb/55sPiPMO9kRo/YEXBilpEBY8bAMceY0RNff73EetqOgPCiq2xvIayZWCdBJIfzDzNz3Uw8lgeP5eGlJS9x4awLfc/vObKHf6/6t+/xV7995euQUpkZ62b4po8UHOHN5W/6tpFVkIXT7sRrebGweHrh07W6TzVmecGdZ/6C2MfG5qSTzOfU5YKXXqr8IsEqzIK1j5oHPf4Eib+v+EQfKn+uEiefbDpDJSebDlvlZXEqqUwnDq8HMjfBrg9h8z9gw7NmJMYd78LBVea7pbFzZcOOd8z3Zd8JYI+s8fEWEREREZFAu3fD88+b66P77oPf/97Mr+jy2+k0g4fUhvXp61mYtLDc5wYP9k+//rrJgFsRtxt++81Mf7b5Mzbt3+R77uo5VzNp/iS8Rf/mbJnDnqw9AHgtLxm5GQA4bU5uGnwT2+7Y5vtr06INAA6bg5TsFHPzPTKyejsZGVn5KAZSoZcXvYz9CTsTv5vY0FWpM0mZSdjwf9gSWgam3in52GFz+AJPzjyzbJtGfr4JNigTRFKs41h8A7YE4bQR2UG3dZ5/vn/QmLVrTRbY8oJQPB7T9vHQQ+Y75sor4ZJLKm/uczjMOj0euOii8tdb215d+iqFHvOlc9Wgq3yv0UuLXyLXlVuzlQa0p5bTKayc9tRheRfgsJsdfuONqtuei1+DZsfrMm/tigZpKnlsi9upi9qqyVhcr1UVEZEGFtHe3J89uKLR3gNr08afkeSLLxo+iKQhpWWncftXt/sev/DLCw1YG5Fasn9/zQewkAZVfI+/Tr+XiwONhg4N/DvvPJMa9Lzzyj7Xt69ZTkSkmSpuzs/Lq5Muh6Y/07Z/mf5M/e4CZwv1ZxKRZkPfdhLA7YY//clMjxhhbha2bm0el75QCi9K0FAy6H3TJnjxRbj2WjjuOLNsdLTpmJCQYLJV3HMPfPopvgwgDc3tdjN37lyuuGIuERFuFiwwQf6VdUx3u9188cVc5s5biDv+DHwfpeztsOBi/4hzAPtD8yaW2+1m7q+HmZt+Lm6vA/b9ZG7WlVRqxB6318Hc9HOZm34uY4avLjOqqWXB9u0mlVwAuwO6X+kPutn+Nmx6qdoBNwcOwObNJthp0yYzIEPJOvzt579VuY4pS6f4pmeumxnwXJg9zPdX0scbP/ZNT5o/ifwSN4nfWP4GszfN9j3ek7WHjzd8TL07vAHWPQk/XwSfdocPnPBRtPn7wGlS7/18MWx+BY7srP/61bLizDcAr7wC6enld0BwuyFr+wIoPGRmDHyo/JsKOclwcKX52zsXds4MvAGdv99kNPntDVjzMKy8D1Y9AOuegqSP4PA6Rpzk8tXh8ccrv3DxeGD6dMwbOOV/8OO55rX66jjY+DTsXwpHfoNDK+G3qTDvFPiyX+MPJsnfZy66AOKHm++G0qp6LST0eF1wZBscWmOCng5vgMLMhq5Vs7QydSVXz76ahcnld+KsS8XnU3PnzsUdRI+w6pavDzWpUyjuR3XVZB/y8/OZOnUqU6dOJT+Im2HVLd8UjqtIXWgK37Vy9NxeN7d8fgsPf/9wmedmzDDXGlFRMHFiYCaAitRG+vcN6Rs49vVjOe3d05i+ZnqZ5/v0gc6dzXRGBjz3XMVtLk4n/OMfZvq5X6rOFDnpp0kAbD+4nRyXGZLMbbkZ0XkEvdr08v0d1+E4ADyWhyV7lpjGrC1bYMUK8zdjRtmVz5jhf37FiqBGBZWyNu/fzL3z7sXC4tlfnmV12uqGrlKdSDqcFDBqcukMJCUzlNhtdpIyTSDJCSfUID6p0/lUJ5CkZUsvZ58dXFbUvn3h2GP9bRrXXmuCP0oOluF2w/Ll8PDD5jNtWfDYY8GNBFh8KhgdXYcjBxY5kHuAlxa/hFV0rMb0GsPQxKGAGYzmH4v/UbPf1l8P+dtTMxZU2Z4K0CI8n+O7rgFgwQL46afKByBplhlsAcLjAMtkJil9XKHi0eXBjDAvIiLNR6f/A8tt7jlkLPLfdygWEW8GsiotPK5eqhesP/zBXAP9/DNkV5BcpT41RLuDZVnc+uWtZBVk+eY99tNjbMyoKKq69utUH+0natNphupwAIv6aNNvzu/BuDhznZuRUfXAkTWmQCMRkWrrUNS8unRpHQX75e8z1xgA8SPLzzii/kwSpFC9LhGpSC3cLpaQV42UiD8uacXq1b0BeO01c0Ovqk4FTqf5kb73XvjlF3Oz8aqrzEh0xx0HLVua9aSkwKpVsH69GRWzutfNdcXr9bJ8+XJatACvdzQuFzz4oBkdrrJlVq5cDsDoKy6HjO/8T6bNg897QrtTID8DDq3yP7cfWLMJYkusrPi1gDpJUXkg9wDtX2yP1/Ky4s8rGNJxiG8flq9PBk5idPw82PkudLsscOHihtaiG3Re7CzPPMnsd1cnw4fDsmVB3vjtdgVs9QdxsPoBcxI24AEIi4V9P5RZZNXaFnzwlbnBunWrOTSxsaZTTH4+HDliRlzt2hXOOQfebTWzzDpKW5+xntzCXKLCo9iXs883PyE6gWuOv8b3+KMNH/lu6qdnp/vmv7f6vYD1eUo3TgNPL3iaSwdeWmVdakXmJlh2G6TPh5gB0PM66H8fxB0LYUV5sQsz4fA6OLwWet0Ijoj6qVsdOvdck/kmJcVEm48ZY0brjI31f2e5XHDoEMx8K5O7TypaMLJD2Yjx4tEMy7sR3fce85nOXAetT4CE0WakqxbRYLnAdQT2fgHr/8bYMb8SFxfG4cMm0Ompp+CJJ8qu0u02acpnTsvlpu7nQfqPEDsQRrwDXS4BR3jZhSyPCS5p7K9dyVTkXrcJ6in5elT2WoxeFDIp55s9dx7s/gT2fGoukD25EN0VnK3Ma+zONp07CvZD+zOKUn6WeO09BZCTBIUHzfvA5jDfVy27g1NpGmsq6XASQ98ynaLeX/8+W/6yhT5t+9Tb9ovPpwBGjx5d6+XrQ03qFIr7UV012Qe3201GRoZvurbLN4XjKlIXmsJ3rRwdy7L48xd/5j+r/wNAq4hWPHjqg77n9+83wSMdOpjr5vqQkZPBOTPP8T3+06d/omfrnpzS9RTfPLsdbr/ddDr3euFvf4Pu3eG66/yd1b1eU+6220wbk9vrZunepVVuf/am2fz7/H+zLGVZwPy+8X0DHg+IH8Avyb/g8rrYkLGBAncBEV27Vt7e0r+/SckrNZZdmM35H5wfMO/8D85nza1raN2idQPVqm4kZSYFtBGVDBwBiI+Kx26z47W8uL1udh3eBZiAgWuvNYNkBH1vKCoRWg8ObHOsiD0SIuK56CL43/8qL1rcnnLNNaZt1LLMQEDnnAOTJ8Pll5t5H34IEyaYNt9iHTsGF7wWF2facZKSaieQrTI3fX6TL8AM4JKPLwl4/rGfHuMvQ/9S/d/W9bvxtafu+A90uTiwUKn21GIXDZvD6uQheL02brnFDJTjdpc9Dh4PLFwIp58e/L42Ge1PNzfs3W7T7tDl4oqzk4iISPOW+H9gDwdvIeyaDu1ODnw+uiuM2wLpC0z2qmItSt2DbWDnn28GaAT45z/hr3+tPKDU5arbEfJrs93hiZ+e4IutX/Dehe8xsP3ACtfx0YaP+GzLZwD0a9uPzQc24/a6uXbOtSy5aQmO8gYkq8V9qOky1aU2nWaoeACL4n46mzaZTBMlzZhh2h6KBdkvpD7a9Jvze/D0080lidsNn3wCF19cB9+9xYFG1QkmUaZcEWnmrroKnnwSvv0W9u3zB5bUmpKBI16P+jPJUQnV6xKRiiiQpKkrTokY5AXIfq4APgBMOt1gbujNn28CQ9xumDrV3PR3uUxDV8kbiHFxZhTKK68M7sZiQ2jZ0nQ8f+stky3ynHPKNtiVzsJB54th9V2mI20xdw6kfhtYbj9wH+Aq1UBQlcjIGo96mZ6Tzu/e+x3eogwMI/49gp+v/5kRnUcEFrQ5TH0zN0GrY/w36IobWgv2m+d+ud6/TIsExo83N7uDEn8ytOoLR7YCljnh2vSC+SvlUE4cl77yMd9v6M+pp5qb0+eeazLblFZQAIsXQ//Bh3h2sj8wxGFz+EaC9FpeXEWj2FlY/LDzB87qeRa/7P4FMJlILh90Oc+Pft63fIQjgmd/eRa3183qtNUcyjvEkcIjHMgrnW6lrLXpa02nFGcdd/rP3AzzTgVXJgz4Kxz/tAk4KH2DNTzWBDbFD28yN18dDtMR6dFHTYejdevg5JNhyhQoPpf64QdTZvSx7aA4kCR7B8QOCuzUXtlohlteNsEdZ3wB0d38wQ/FbJibFZaHKJuDO+80naK8XnMBk5UFL71kHnu9JpPTL7/AhRd6+eLeSyBjvun8MXqBWU9Fr4/NAW1PKv+5xiSygwk2cB+BlLmQeE7g81WNLKkLr4a39ytYdJX5zetzBwx62ARZlSc/3WTycWXB7v/Cns9N4EmLRGh9PIS1AkcL8BaY383MTeDKhbG/HFXQVGqqyY6Vm2tOf1wuiIgwP6ctW5o2+djYqtdTGZfHxaUfXcrPyT/z7oXvcn7f86teqA7ty97HGe+dETDvjHfPYOlNS+kS26VB6iQiIiK1y7Is7v32Xl8QCcDE7ycSFxnHrcNuBUy7i9dr+ijUdQcjgAJ3ARd8eAG7s3YHzB/3wThW3rKS7nHdffNuuMF//eb1wo03mgEj7rsP2rY1wfYPP2wy4w4eDIt3L/a1ZQA47U5smKgTr+X1ddg/nH+Y1COpLE9ZTpg9zHft37dtYCBJ3/i+vmXcXjdr963lxE4n1voxET/Lsrjhsxv47eBvAJza5VQW7l7I7qzdXP3J1Xx51ZfYSw/00IhtP7Td956NcETQMrxlwPMOu4PYiFgO5R/CwmL7oe2+5665xrQdVKZMW2qXP5gBQ8oZ4MQn/lQ4ZSZEd2XcOBO4VaZds4TivkTXXgsPPeQfOCY93dyovekm87g4y3RcnH/ZXbtg4MCqM2lcfDG8+SbMnAnPPx8YjFKbsguz+Xzr55WW8VpeHvr+IdrTvmYbsTkg5WuToTO6W8XtqUWdV28f8xpPz32SvDwbW7eazklffGGOo9PpDyqZPdsE7ixaVLNqNWrtToVWvc0x/W0qdLs88PkKgnSAkBthXuqBZZn2wsyNpl3Jk2famOxhpr3JEWXeTzH9ys+KLCKNW1hLSDzXDPS1/W3oeQO0GRJ4jyW6K8T2r3gdNbT94Hacdifd4rod9bpGjjRt1ZmZZnCy8883t/XLu5bzeCAnJ/AcLBRZlsUzC59h0vxJABz/xvEsvnFxuddfmzI2cf1n/nvPo3uOJqsgi5TsFJanLue2ubfx1ri36qvqIrVPA1g0SqeeCr17m7aqqVPNoApVKW+QgEqVDjSCssFGNQw0EhFpqv70J3j8cTP9j3/AM8/4B6oqj8dTzay/LRLA2dIMnJr6FST+PvB59WcSkSas0d2tmzp1Kj169CAyMpKhQ4eyYMGCSsvPnz+foUOHEhkZSc+ePXmjnDQTs2fPZsCAAURERDBgwADmzJlT7e1alsWkSZNITEykRYsWnHHGGWzYsCGgTEFBAXfccQfx8fFER0dz/vnns2fPnhochbrTjSTf9LJlwaVq/OMfobAQbr7ZBJGAaeAqL1jE6QzdIBLwn3BYFlxxhRkN0OMxx8HlMheA2dkmsMEnrCX0v59Q+zilHEnh1HdODUj96/K6OPO9M1mQVOpzY3nM38/nm+wV3hKjUER3NY2v5TS2Xnpp+cEdJflOymw2GPQoUMkda6DQHcaIxxfz06YzuPxy+Oknc5O5ou1ERJiL+S+2zw6Yv+zmZeQ/kk/+I/nkPZxHq3CzAqfdyQcbPuDnpJ8p9BQC5ricmBjYgHlipxNxFx0HL16+2/Ed09dM93VcAZhyzhSmXzSd6RdN59FRj/rmey0vn2+p/GZ1rVjzoAkiiR8JJzxrIqFLByIUp9VL+QqSPmpSKfXGjw8cZXfrVpOZJDYWYmJMgNv27bBi9+nmhj52WPNIYBAJVJziHKDTeXDqLIgq6ohtd5qMIflpkLkeDq836Qp3fQgZi7njDmjRwr/45MkwYIAJKnn1VROgdtZZEOPczak9/2eCUo57ymy/oteuOCVi0izz+lkWZO+ClP/B5n/A2sdg9cOw6kFY9VdY/ZCZt3ky7PsJ8lIr7ylSnxyRJmMOdnNzJy8VvCV+aCp7LdQhoOGlfAPzx5mb86fPhcEvQNxxFZePbA82J3zeA1ZMgISzTWeac5bDiLdh8Etw3JNwwvNw4hsw+mcYu7jaQSQuF/z73zBunGnYHT/eBLnu329+wyMiTNBhSgp89pk5V6lutuiSUo+kcsa7Z/DZ1s84lH+ICz68gMd/fByPt5IOXHVod+ZuTnnnFN+Ixmd0O8PUMzuVU945he0Ht1e8sIiIiDQaE76ewD+W/AOAzjGdfde4t829jVeWvALAZUVJRo8cMaPZBpPdIKgMo+Uu5+W0/5zG4j3mGrNLTBdO63oaAIfyDzHsrWHsyfK3ebVvD7fc4m8jsCx49llo185c1/Xta4JIir2//n3f4BDhjnCOTDxC4aOFFD5ayOa/bPaVs9vszNowiyV7lviCSGIiYoiPChyhsV98P18nfxu2MhlMpPZd/t/L+Xjjx4Bpi8lx5RBWdN37v23/49yZ5zZk9Wpd8fk4mOwjtnLuYia0TPBN7870B2Adf7xpO6iszbTMZ7X7lVVc69uh57WmXQ9ISDDtERXdPLXZzOcUzP833li2bG6uP4gETBBI586m3o8+GtyN2XvuMddpWVnw979XXT7oLC2lvLPynYBgtIp8sumTmm0AitpT3TD/PJOxtor21NbRh5lwS7rvdV6yxLz2zz1nBh35+mu4+mrTSelorlkbNZsNeo830+k/w4ZnAp8vDtIZOaPssiE2wrzUEcsLO2fAj+fAp11h9YOQtdkMVtKypxmwp1UfCG8DeXtM+6MVxE0uEWmcet8WeH8zd4/5nih5jlSL90ZyCnP4y1d/4ZhXj6H7K915ZsEzvvuINeV0wmOPmen8fDOo3rp15nHJ8z+v17Rv33nnUW2uznktL/d8cw8P//Cwb57H8jDq3VF8v+P7MuVHTx9NnjvP93jKsimkZKf4Hv9r5b/4Zts3dVtpEZFSbDZzrxHg559NR+XKuFzmO7raunY1gUTFf/1L9ccpDjQq/lMQiYg0c927w6hRpg3y+efh008rvr/h8dTg3ocjEvrdC9hh278hf19ge5/6M4lIE9aoMpLMmjWLCRMmMHXqVE455RTefPNNzjnnHDZu3EjXck6ad+7cybnnnsvNN9/MjBkz+OWXXxg/fjzt2rXjD3/4AwCLFy/m8ssv56mnnuKiiy5izpw5XHbZZSxcuJDhw4cHvd3nn3+el19+mXfffZc+ffrwt7/9jdGjR7NlyxZaFfWAnzBhAl988QUffvghbdu25d577+W8885jxYoVOKoVAlkN1YxkH2nBuAdz+erHKG691d9YVdkoljk55se3XTvzf70GiliW/6adzWE6rFYWblqFm2+G//wHNmww+3XvvfDee2ZkwLg42LsXXn8dDh40I2X69L8HtrwCrsMVrzweeDkCBs/239iqxRSmJS3ds5TT/nOarxNFpDOScEc4WQVZ5LnzGPXuKJ773XP+BQZMhM1PmtHe5p0Mg1+EzuebVG14zHEtCrooqUULuOsuePrpik/AAt7a3a+Crf80HeOt8htXdx/owtbUfgBcd515P1X18XA6YdqaadhsNizLIjYiluMTjvfXwe7g7J5n8/mWz3F73Xyy6RPaRLbBaXf6GnlP6hSY7aFkYInT7uTrbV/z3Y7vsIoCYY7vcDy3n3S7r4zb62bykskcKTyCw+bgXyv/xaUDL6284kfLU2AaxZ0VDN9YUVq9JpJSLy4OXn4Z/vznwPlZWYGP3d5w0+F94WUmC8aWV6HvHf40hBWMFAkUZQGxBX6vVJKuMH70Ip55ZmRAY/6WLWYkqZJyC0pEwBRkUCbAqrKUiGExEHc89LweEsaYLEKlO9578iE7CVr1Khs409D63gWbXjTBCD+OhTPnQUQ7U8/KXgt1CGh4+34ALPNadKwgjWJeqv8vJwmW3w7YYOS70P2awM+S3QE5e83rXbxs4WFz4z/I76i9e00Wos2bzU20//7XBI64XGZTdrv583pNY4HNVs0RgUr594p/c/e3d5NdmA1A68jWHMo/xJM/P8nsTbOZc/kcerftXfMNVFN6djo9/9kz4IblT0k/+aZ3Z+2m96u92TVhF11ja6eBeW/WXrYd2sbwTsOJdFbQUFJdq1cHvjCpqXD4sPmi71jqs9+xY9l5IkJenvkobd1qvhtzc825eulrs8JC833YrZvJQNm7t+kAWtNLKK/Xi81mK7ezrIjUnvPeP4+5v831PS4ZoAEw4ZsJpGWn8czZz3Dbbabd4qmn4Iwz4IQTKr6mLh4wo2QwfLB+P/P3AcEYu7N2B2QmOZB3gL5T+pL1YBaOolHAJ02Cjz6CAwf8bQiWZb7DSrKHufhg3Qe4vW5s2Di166kB5x29WvcisVUiKUdSsCyLd1e/y5YDW3zP923bt8z3UskMJQ67g+Upy6u/0xK0aWum+YJIwLSZrEpbFVDmm+3f8MqSV7hrxF31Xb1aV+gpJCMnw/e4ZMBISYmtEtm0fxMAOa4cDucfJi4yDjCfj+JgsNLsdujQodTMlj2hxzWwa2b5bWzO6DLZHJ54Ar77rvxtWFZg+8rf/w4ffmhGx66IwwEvvGCyT3/+ufnuue22ituH3W5zDnL11fD++yaYrEUL03mydBal4u+IQ4dMm3N1eC0vry1/zff4mNbHMP3i6b7H87bP47GfTI/NA/lVZx6uUP/7YcszkLUF5p0CQ/5hRir0ugGvaasu1bl04oQ03p2VQHq6OSdLSYFHHql5FWrbrsO7eG7hc2TkZnDfyfcxvNPw+j/P63WDyUaSvRPWPGSynA561NzMtyyI6myyTEjz43XBd2fA/kUmg/R5G00AibcQbGHmoiYn2bQzOaNN23lYazi4qkm0hYtUypMP+5dA1ibI2WMCqBwtij4bRWUswCo02Xsi2kPLHhDdA+KONYNnNUYdx0Cvm03QWH46zB0IfW6HgQ/7O3K5sipdRbC+2fYNN39xc8A1z0M/PMSsDbN4+/y3GZo4tMbrvvNOk61t7VrYvRuGDTPnS/fea4KBDx+Gd94xgwUMGFALO1NH8lx5DH9ruO/aLNwRTteYrmw7tI18dz5nTz+b+0++n+dHPw/A9DXT2Xtkb8A6rHIGI7zp85vYNWGX77pSRKQ+3HCDyUayc6fJ2JmVZQZQiCy6LLHZzDVdWJgZGPXZZ+H7svFyzVa+K59wZ3hIZKJ1uUx3ufx80y7hdpvXLyzM3JqMjTV/usUh0jhMmQInnWQGEr3sMjOo7x13mMGqSn6+160zbZVvvlnNDfSbAJtfNv2ZfhhT1J8pXv2ZRKTJC7HepZV7+eWXufHGG7npppsAmDx5Mt988w2vv/46z5QTBv7GG2/QtWtXJk+eDED//v1Zvnw5L774oi+QZPLkyYwePZqJEycCMHHiRObPn8/kyZP54IMPgtquZVlMnjyZhx9+mIsvvhiA9957jw4dOvD+++9zyy23kJmZydtvv8306dM5++yzAZgxYwZdunThu+++Y+zYsXV34KqRMtMGvDkNjj0Wdu2CE080jVMnnuiP1izukOksitm47DLzw/vPf8JFF8FxRYOTVxRQUvrGYFBSvzUZFfLSzEhuEfFmVKmINmCPMIEOlsc0jhYcgsKD5gZC3j4IizadrhPPqfLs3+mE2bPhlFP8I5mvXQv33x9Yrkz9w2Jg2JTAk4QADogfARe87xsJsEJHmcJ056GdnDntTF8QCUC+O598d2CH9Ed+fISHKYqGGTgRcjdD8sdw5Df4+QKI6QuJ55mMK/kZsOv9crf38MPm5m9Skjlepd1+e4kHNhuc9CZ8M8J04qds9EmXtrvp1Xk/u1LbMmOGjTFjzMleZe+ZpEN7WJi8EAsLh83BmF5jylyUju45mk83f+o7Hh9v/NjX8bZVeCuOaXNMQPmOrTrSIboD+3L24fa6mbN5DofyDwHgsDk4v+/5AeWddifn9D6HTzZ9gtvr5rsd37E7czddYrtUXPGjNeCvpmN36rew/T/Q63pzg7qqwIHCg3VXp3p2003w5Zcwd2757z8o6jTV5RLocR3sfBdW3AkZC8zNhNZFAUfRXc1f6dGjdrxrUqJHdgguIKPwIH/5CyxYAJ98UnGdDuW2462lT/Pn4Q/BiruhzVBzw8brMZ3rK9PmRDirgp4fJTvxFx6GPTugoFRvk+IO2tAwnbTDY+H0z+Cn/zMjBs4daDpfdL/a/zpEdzXZkSS0dDjTBAHlpULqPEg4y8wv+X3725uw/olSC1rms1X6N7iygKkgA94WLzYxmWA630QUxVSV/s0oDiipKcuy+MtXf2Hq8qkB84t/FwA2ZGygz5Q+LL5xMSM6j6j5xoJU4C7golkXVTnqnYXFuPfHsfimxUSFRVVatiLbD25nxtoZvLbsNTJy/R3kRvcYzaUDL+XqY6/GeTSXFaeeGlwaPDDp4yZNqvm2RJqgRx6Bl16CY44xHbR79646aK74ZldNbDu4jS+2fMHE7ydS4CkA4JrjruHqY6/mjO5nEOGsXmYpEancjLUzAoJIKvLcL89xTu9zeOKJUSxYAOvXm7aNhx82HbvjixJ0FH/+XS749luT2a2cxLyV+nTzp8zbMc/32EZgQFlxFoBcVy4PzHuAl8a+BJg6zJgBlTWBORyQl/gNmQXmesBmszG2V+ACNpuNc445h/fWvIfb62bNvjW+55x2J4PaDyqz3i6xXYhwRFDgKcDtdbNo96Lq7bQELS07jXu/udf3ONIZSY+4HtiwYWGRlJlErsuktXj0x0e5oN8FdI/r3kC1rR17svYEdHrrFNOp3HIdW3XEYXPgsUxjQdLhJOIS4gC45BIzot6iRWWzcHi98MAD5axw0COwc3o5T9ih/72mg3UJJ58MZ55pMjiWbK+w2UwzwLhx/nlt25pMzdddV8FOY75PLr8cvvoKpk83I7YuWGA62Qwq9TH0eEzWjbffNu3ISUnm8eOPwxdfmE46V15pminA3Ox9+23TLvvTTxXXoTxfbv2SrQe2miNhs3PbibcFXKMd2/5Ynl74NPnufBwcRYfEgY9AzibY86lp3/jpHIgdaLLbOluagUN2zgxYpFUrL19+aV4Lr7fiQdLrasyp8hS6C3lh0Qt8uOFD1qev982fvWk2rSNbc/nAy3n8jMcrDJCqdWEx8Luv4ZuRpg1z47MmsKTnddB2uLkXsF/f4U2Vx+thx6Ed7M3ay4D2A2gf3d7/ZO5e/2vf83r/d5y9qAN8LbQziTRK294y2aCdLU0np97Hly1THGRVg4F8Qt7QVyBzAxxYaoJkNr1oBhOL6mR+aHN3V72OSuS78xn21jA2ZGwo9/k1+9Yw7F/DuLDvhcy+fHaNOswW35seMcIE3bvd5rppRjkJuOrzHKG6zp52dkCAf6GnkG2HtgWUeWHRC3SP687lAy9nwjcTAHM92S22Gw+PehhbUeTTitQVvL78dQD2HNnDlF+nNIkAdGnkUlPNX+l5DXnPVepMTIzJGjlypBlk9tlnTWDJddfB8OHmfmRysrlu3bABBg9u6Bo3vBUpK/hi6xc8Md9/n/jcY87l+sHXM7bXWFpFtKpk6dozf77pv7RmjWmD7N7dDGrRsaMJBCq+l+xymd/d1avN/zt3Qnq6eX0vughat66X6opINR17rBn85g9/MO2NDz1kMkddeaXpGltQAAsXwo8/1vC7OTwORs0xGYizNpn+TAMegG5XQXQXf3+mWgpYFxEJFY0mkKSwsJAVK1bw4IMPBswfM2YMixaVf+Ng8eLFjBkzJmDe2LFjefvtt3G5XISFhbF48WLuvvvuMmWKg0+C2e7OnTtJS0sL2FZERASnn346ixYt4pZbbmHFihW4XK6AMomJiQwaNIhFixZVO5Dk41e+5Jjjj6NNGxthTtOoUvq+kw1wFxaStOwHcOfQbWAPYju0p8WO3cSXKLf/t1W4w3L9dc9eyQ+vHOCuly/np5UDOPlkLwMH2jnzTDOSZWSkibhfvBh++MGif7e9vPr4Hv76/FBOOcXJddfBNdfYOP74sqNapqXBypXQOvu/ePKzaZMQR5uO8VSl3boLcZAHx06CYx8vW6C44zSA5aEgJ49lv2RDxDF07NGBaG8rOPhLuet2uf13TtO//Svk2/n0nyO46v7z2LU7EssK7GFlswUe6RkzzGi+YWFX0zVmE12z/o5VdHscwIsTr60FW1tPJ3Pur3jyf/Dtt/O3LZTe+5Kvx8atUaxeG8mhfYc4fng7YhM606JVFE7PfsK86dgtFxZO3PbWFDo6siNzA3etOJVcKxdsEG4L4+7+19KmaOQdt+XmtS3vk5qfEbDNlydtANedXHJ8GL0cH5r9zNpiRtQrYgEWJXrmpv8M5BBpC+O9yTGcefEgcNjweMzxststThp8hCt/v53//ncw2dmm/SQ+/gTi2n7KwIxxWNiw4/GtH2wcirmKaW+m8uDjbmbOTCAlxcsdd9gZO9ZEEJd5/Vzw4v9m+G7YeywPwyN6kLZuYUC5E9ytfWVswL6cfb7nBkX3IG3tAmylehkPie3LNznpeLHIz87D5jSdHjyWhyGF8WW2cUpkbz4q6tBrYTH/6+v5XWR/Cm2toVV/HLHHkJNrx+Ox4fHasCxw2C0cDouICIvDe3fh2rKcFpkH6DRoEDgisR/IwnbkiFlnq1Z449v4tlfgsrN0xyuc3eUxYpbegHfPZ9h73QjtToaItv5o6PQFviCnT3f049Ch74hsvZ6RA4YRWTqTBVDodbE1a5fZRoaL6HW7cO9J45gh/YmIbklYRDj2/QexHTlSpk4Aa5LTyXUV0DaxPR37dKdFq5iyL1wJSZv3cih5G3k5BRx/5nDCo6JwVhY55C2kReZ3HNp3CEdMD/75wDEUZJ3Bt/Nbl/q8WthscMqJmfz4UxxJSe9wXMQQTrDux5Y8G5JnY4vqZG5CO1uYGyj7fsICUg52ZH92e47tsh7b18Ogz+3Yul4GMX0qjzI/sAyb18U7z7WnIKsvn3/TFvPu9tfL6fDSprWb+KFXsMztZLD1OI7/DYXuV2HrdiW0HRq4jYMr4debcXscOB0evNnJ2HKSsUV3NQF0Xo/pyG+zw29vwPonfdtK/XcCHX9Mq/T4B2gN+XecSnLvvrTsMoTodp2JjW9Dbq6dPanh5OfbcTggppWbzomFpgPqvh+hIN2M8BfTG3dEDw4eCiM3z05unnm/t2jhJaqFl9hWbrbvimTl2g60sV7n7IRJRBXuwrvmMexrHjLZVcLiwJMLmZuxgOxCJ//deRxkfkRij2Uc32lguVXfm7uPQ4XmYm3X+p3kHc4gLDyc04edQVxc2zKf75Lv8wNphzmYvJPszByOO3Ew/Tv0I7xF2UwLmzN34C7q8ONefRDXkSN19j4/kpvLdwu/JD87jy59ejCsxzAio8t+Ce7OTSOz0HxHuDbn4j14gPDICHoNHUSLVq3K7HdJqfvC+XlJHPuS0xk4uC1xCR2IbdcGLDcRnt04vNlYtjBc9ra4He2AsexO/YIL211Fi/n/h7f3Xdh7/tEfkAXQ+xYzMmjR52LHvh4kttlL5LJbsfLTsR1zs/l+gnJ7zGQXOpm5YwDh+6fRte8GBib2K7fu+/L2k1FwCCvSyenDRzJ/6TGMv83DP191kJBgVl1eXEJ4OKTu2Mv2habjY/eB3XCGVx7dmuPO5YavH+DnQn8HxfiI1iS2MMPiur0etmfvpsBrMned9s6p3Bn3Ap0OjA38/W7ZgjBvOk7vgRK/37EUOhJxFbo4sOIDcnKg7/EdaN+pVbm/ecXcXjdXfXMPi/L8ozrf0/dazurovwG8KGM1f9/wBgBr09fyp7dP5s1+Yzmw54Dv8014O7KOOMjLt/s+3y0iPbRo4SUuLp9b//s3Psv6hUzyytQBYN7OeczbOY8/f/lnhrc+nnO4CICn7lrC8Scl+M5bAMI8+wjz7MNjj6PA0QVPiVjSr65/iJ6929KmXRTRqUm0nuhP43TomUfx9Ojme/zznr78NnENXlc+vQe2pn2PXtidDpyeg4R507FZhXhtLSh0JOK1R5OWuont22eRl23nlJH96NMh0ddIXNKu7L1kFmT7Hk99/i7i2scxYsAI4mLblimfkX+QffkH8JTYkW2z7qRNz5OI7diZFi2jcLthX0Y4hw47iWnloUO7QiIiLBPsnPYdFB4yIz+27AEtOmJZsDc1nMwsJzabRWyMh8QE8127av4WcvbvJapVBIn9B5kOM5XcmN6fcpiUTevJOpjFsaOG0iImttzvNQg8Fy7e7+H9T6J1XNmhn9Py9rO/4BCFhf7ejVs/eoAWHU/G0aorHqLxeGxYlg1v0a1fu81Lodv/Hprx5n306t2dY7sMAWfZN3pqXgbpuf6g15cfX4flctN7YByJ3doQbsvEhhub5cKGBwsnli0Mry2MQ/vdZO1YRFYWDDujG7FxYeW+3iV9+W1b9qXk0rKljS7HtKZD90TCPBnYrXzsVgHgwWuLxLJF4LbHsGVHazZuNKNzDx9usnkUf17DPGmEedLx2GMocHQDm43cvCOsWfEP8vLgmL7tGdFrULmf75Lf57s39Cc9qYX/fd69OxH2A0V1ysduFeK1ReC1ReImmtentiE/38Gll1r07x9cdMjM6S/hKsghJr4VJ/UcTFg5AbP78w+Rlm+yRi3ftI456V/xq2dLmXIA09dOZ/pa05G1c2QHzu94NgPS4yjMKaBj7y4M7zGcFi2jyyy3K3sv2W5z7dPLSiUqJ4PsHDvRHQfSrucxOBx28vLspKWHkZPrIDbGTccOhSZQJj8DDi4zo462GWJGpw5vg2VBWnoYBw+FERHhpUM7F61amvf54rnL8eQfpk1ie9p06W46KlbCmbcN25GNHEjLJKb78IDPd/p+8/lu1bLqzzdAQYGN7bvM5/CYHvmEhxf9Dh5cCTk7ATvEDYSWx/g+33tSzDYSEwpp28YNrhK9fn+9HdoP9u03wJFsB0m7I4iM9NKrez6U+Hyz8l5oYc7XDruP4eAhJy63ncJCG17LRniYl7Awi6gWXn7btYIdSRuwWYUMHTaKdtGdwB74e+m1vGzM3A6Ap8CLbX06uVm5dDv2GFp37FjueUtJPyz+mQMHdhMWHs6JQ0aQ2KZTmfOWw4VH2JNrzmVjrBz6ksK+5PSA89TafL2re772/+yddZhVVdvGf/vUdHfPAEN3dyuCAaiAgYGYWCC+KiYWig12IGWBKBLS3SDdNcB0d5/a3x/r5JwzM2dGQN/34+aai5lz1o6194rnuZ8qq6hk/Y4VVJVVEt+8KZ0SOjvtt3ntBNCfqcCQ77q89uvxtTx99m2QQSFJNPeO5/0uz6E0jZEKfRWP/fU6edWFyMgMXziMXV3v59dpnrw29w5+XtuN11+Xee016N5donVrEXCblSUMKZWVRkb0Ps6OBQdRKBU0ad+kzmcEcDDnFON2TAJAgUSMZwRbr1uIm00W42cOvMvilNUYZCMf7fmIHuXpDPCIoKxcQfuINsyd1ZsHn2kBMhiM9rqSr6+B8AEfc7pYwoiMUTbS0RDkoH93VUUzx0lArdFoIKRMdmgPEOcZwdnSSwBoLhpZ+f4b6Cr1dBjcA6/kNGoWfLDlZ8oqKlmx/TcoN5DQohkd4jo6Xdcse6VRS9bJduSmeDnILQpjJWpjFkpjuUkejABJRWlOOuXn1/+tfSw0IcHyndqQidJYSrUqAVkSY/nsmfXkZu9Gq5Po3bslLYIjHIIPK/RVXCgTDnf6agPS8Vwqbea3d3LtvKLOqGfEqofI11orI//e5xM6BVn1uDMlFxm84T6MyJRpy3hgwSAWtx9DQVqB3fyurFSQmuGoh4LMD3+sQF9dgm9IAB2adsHbw9HB3VZH1CVrkbLzGsU7SN4J6D2bo/CMoqrayumAldM5VLbPcqgSBb6VWrKObnOQ17wr9RZ2IFIJpXvf4mypn6XfX74VRc8RHaisVKA3iGMlSWbUDfkMbJ9ag18DaEaM32vEFVu5UhklFepWHC2cjP/uo7QKOwgohMMoMOtVT/re3J6yCiUGg4QkySgV8M17J1EXlwkDKYB7GPcN9yHjxWhenBGPJMkWzkWhkDEaJZ55NA0p5xzzX0umc3wHnn+3A4sWSSxaBLGxEj16CG64qAi2bYPiYpkhvdPxzNrAuq+VPPHWEOb8FMmhQzKTJklMmiTWKL0eE2dmpH0HBT8s+AhddRl+wT70atrVaYWMYm0pqRVZyLLMf3a9aQlckmUj/YzRDmvCiIh+LEvbZAnqAfjsnSeIbR5fp/5dUGlNevHR6ydBN5UxHTQ0Uf4KSEjFJ4Qzq+V9CEggEiFlb6ZzVDF/zAth3EMtqbB517ZHdO1Qyu7F6xrEn+8/dozktBNUV2rp2acPsYGxDuNcZ9RzpuQiAPllRXx+8Hu26487Ox0gkid8deArvjrwFd0C2zJFcSe+ZfrLwDsYcDOk2PAOweiVoo+bN0NOThPiQ/YxoektBEpHMeoqUJyZbXduM9u2PT2e82WBSGW/0qbDBWI8HdeDSkM1SaUpAEiyjs7yRYpzilD6JuAZmkBQVITpftUUFqmQJAjw1xMeKoiFRWs3UF6YjYeXhh7t+uPpHuIwv6sM1ZwvTUFGJjfHg9xTXWrhW1JQGsuRJRV6RRA6pQiUCKpYQkVxGZKbPwHhwSTEQ2WlgvQsDZWVCou8FhqsIzBAj1R2HkpOikQswT2ETKj0pKBQRXauGq1OgVolOMiwEB2l5eX8tupPMFQSEh9L19geTvUxW/n8/LHzaIsL0Gg09O86gAD/4Dr5tcpcLT7HkhvEI09P+oOjuktsp/ZxCOCt8mRc3A08ahhBF9Vq5CMvI7mHIQWZKgAYdaaK6rVEZ6UsFtXkVVbnNb0eki4JA1azhEqLc3ZD9e+klDSOnt5FWXE5bbt2oE14a6f698ni8xhNXNiV5hVr8ufmcV5dLZGa4UZlpeiPh4eR2KhqoZvUopdUVUlk5WgoK1fi76cnPFToY6eT0th9YBfoy2nZvisJgYmiclANnC9NocqUgODMnq4UZWkd5RbZiLs+CYVcTbUqDoNCvCdbuaVvn9YkBoU5yC3muQeg1So4s6snxTlFRMV6EBoTQlC0yXlX1uOhPw9IVKqaijUZYa+8eFEkoGnTRiRoMA9zjT4VlbEIrTLCskbl5sJffwknw86dBScQaBrWCmM57vpLGBSeVCvjLdkbxLomnBETE4U9ETDZ+fKQZD0GhQ/VyhiQFHb97tenNc2c9LvaoOVcaTIA7bK/JMxQiRw6CMmWpzXDSZDVoYsdKA+5E8+QeCKbOQ+AtUVt67nSWIzGkIFC1iKjxKDwMvVD5bCuhYUqyM1Xo9VJVFcrMBpBo5Fx0xjx8TZwMukQSReFHtq+cx8ifWId9FDbNUerVXB2V0+KcopIiJvJdZFvE8kajChRGKuh7ILlOPOecSi5K+VLd+EZeI7IZlH12mi3ndvP1BNvk2bMoz78ceYPen7ekRf041BX6Fye32beQZtVzMrPBzP++Rs5m+RlY820QqGQ8fcuZ9uCZQBExofg6e+ok9TEzn1+JCXJGHXVJLbxJywhwaSXlKExZKGQKzEofNAqI9HbcLYz3niH7j2b0SY8zqlecrbkEpW6asvfR3Ks/PnI6ME097HqJsvSNlp0scdXPc6X6z+hQCf4PxmZN1o+ynVqqy1geEwi60+v4kJZCkZkXlwzDf3W4yiqILp5PN0SujmX18ozKaiyOvXlrHue6ip7ngkEB1tQqCIqQktgQP18i14PF1Pc8ffVExJssgPL9npJ52bd8XCvnU+15ZFXvPMWnYbUvZ7bcrYr3nmTJu0bzrd06dSD6KBoh/27UFtCeoWwk5cW+JNyrI2j3AIojGW465MxSu5UqZrUu64BaPQZKOQyqlXxyJLgCc6fp1Y+VWXIR2PIQK8IQquKFH2vrm6QvQRAU3YQXdFFB14RICNLvO/IcNP7hlp5RYCKCgUXU9zx9DAQH1ttScaT+uhbxCxfW/eN2OBsTDNSh/WlJCbGJd6hukrHmZ17qSgpr5dfsx0faz56Bw8P93rl84oqreX3z9+bwpDe/QgNjHQqt+RVFZJenmP5O2PlVFAH4BmaaMc7FBYpKShSCx7SjFLnciqIuXQh2Z3YqGrc3cVKV12p4681e0FfTkSLZngFRTiVU21xdv8ZSnPS/75eAkiyFnf9RfQKX3RKa9CPeR/7/u0Inp3Zh9PnvakoNzJ7tv11JEn4IzQNOsyOBUdc5tecve+6+Baoe5ynpmsoKlYREaYlOKjucS7L4pkUFqlwcxM6hq9P4/jUX/evYUH6YvYbzjn9ftX5Vaw6vwqACPcQRocPpXVuYIPsBqknWpKT7OnAr6kNwuYqyTpkyQ2tMgIdvtxys5GSUgW33ioqs9aHzp1h9+IlNE8sI7Cf0L+r0yArrfZjbPXvHn36EOdE/7bTlSqrSTt2gqqyKuKaN6FzQhen8zujIocCU7LNlBPJlBdmo9Zo6N65FxGBkQ7j3MyFgJP1PCyU4CADCrkMhaxFkrWAAqOkQZbc0CmC2bjVi5wcCAmsolWzEuJjylDIVUgYUJg8xIwoQFZglNScPH+E7JyjVOnVDOjbniaBwQ5yqt6o57SJd5BkHV3kSxRmF1KlboHRqylqnwh0OgWyLGGQJSQJFMhIkoxGYyTj1HGMZWn4Bahd0sfq5h3M/g4qO94ha98SqsrKCI/1J655MD71xDjtP3aMS2nH0VbqGNh/MKF+YQ7vW5ZlzpRcRC8bqKisIv3YKarKKolMjKNHk+5O33dyeQalunLAiV3QwiOXm+S1CgwKX7TKCGRJQ0bmCZKTfqO8DDr3iKdDRBOn8tqp4iQMpqRPZ/Z0oShL56CPCRt7LpKsR6/wRauMAklR6/6tMFaiMaSjkCswSu7olGEYFH6N2r8bup4rdLm4lf1Fq9Icvn9rNM+8N5T8QjfKymS++cZedlYpjYCCjJ9vQW3IxqPZcNwTb7drI4FIBFOdK+x62iKOng3hwNlm+FY8x02tvsdTm4bx8MsoDr8g/GA0AaJaSfEpB3+miIS/6FiLP1NaRTZFJq467WQrsi85e9+O8rksaRplNzi+bT+VxUVXjHeo1kr8sTqEwuxCB/1bkqtx1wv7YZWqmUUmbKj+nZFxnOQLv1NeBh26x9A5MtGh37a2SoB2xgvoi4rQKRzlluwcNaXlSuJjqqxrVx1yS2WlguQ0NyLCtPj5in2yIXKLrbxm9Xewvm8Q8rabIZ0qVQKypLFL/vT44yIYyp53qMTNcBGj5EW1yupD09B1rTZ/ZBBchcaQiV4RiFYl+ILyymKOHphFZSXENw+kd9P2eHs5ztWk0hQqTRxQ8vFLVBTloNZo6NqpB1H16CUFWSXkpyQ1yG/v3P4TaCvK8AsJoFfrnvjV4dcDoE/WQXau6+O8AfK5GTv3+XH+vNGJP1O+aa3VYpTcTf5M3mj06fhXrScnB4Ji4wiLUBMYQK32MUmCH5YuR1ddgn9oED0TeyNp/Bzuw1ZGOHMsyeF7Z5Bkuba8V/8uZGRkEBUVxc6dO+ndu7fl8xkzZjB//nzOnHF0aGnevDn3338/L774ouWzXbt20adPHzIyMoiIiECj0TBv3jzuuusuS5uffvqJCRMmUF1d7dJ1zedMT08nMjLS0ubhhx8mOTmZtWvX2p3TFtdffz0JCQl8XUstrerqartjSkpKiImJISammJSUuhd5gOTj54k7air1fpfpVR88CF1sSuzuXAMtQ8TGWJUHq8ZDEdDsEbaXTWHpZn/WbPPiVKq33bmVCiM9WmTzxaPP0UH5A0WZfvxiPMrK7X4cOuNBZp6GuDjw8RFRoBkZUFFmYNT1RSy626QCjc4Es7E3JUWUAQHwNkCw0nJPzz2dw8j2v9K2nYRf53uEs7FHpHBGlVRw8n04NdPa79xY4kJS7Ptte43gYAhRQ2Um2rIs3pn7FwDTlG+jSXwAEh+mqlri/S+9+WZlJGmFVuWlXUIhz96+h4tewki88u3h/LXHtMPIRkj7Ccq+BcnkjOjZC8Kmgn9rONTavt813wXAph+gZTBU5eHbfixeZXnc2nEzn7+zFioOgjYFvKNEVn+llyB/dSVQcpGP04N5puyS5VTLu33MzeH9Bbtt6neKKocOux+l3KCzVCRZ+fZwHnpAxcMPA7pMSJ8DlStBsvHCVQai9R7FO/tjrc9qxB7L1wd3VXHr6+1JzhPj5JGbz/Lxgxvx8FcTMeBGIshk3VprFlQytkDxFyCZFiuFLwRPhIA74Nxg5Lxy9p0dxi/589l20IcL6Rrim6rw8wMvL6ishNJSSDpnIOqOiRyPmG+5l4tDVhDvGWnXb9lbJnbb3aSZqnEoAfP++1LiRN5qOcnaHsBHwcyiZbxwcREATfR+XFAJpc1f7UPesI0oJaX1GB8FOW6FhO0xlWApjqbdL3+SWhjDM9P8eeJJETiiUAhHZoVC8G1Go3B21ulA/YcvvqtK4Xdcwnma0o/txChT2LdhG5RugKpToEsTVXvcggEZqrKF0AtINjp8iDqAh+NG00EKFw8TOEkGX+dvIFMn+vp+WX+evbDN5XsCwJxs0cX5XbLpMXw9SsEjCkan1d4exDGFx2Hzs2KdGn4AEMTTzC98mPV7DLmlQpAIC6hkyuhDPDv+FNGDRxBBJo8+Ag9PyIbSjVCwBnQnwTY4TNKAR2ee/eV9flzUlHb+R1m3eDWU74LqJNC4i3VH7SscBavzrQaJQsQ9DVoL7sEYjfDZHA8+WhJjmRfuagN3DDzLO+PX0Pyxx/GqyKdP7BmWzPkTyndDxQmQi0QwhcrDeg3gfFZTHvrkG+7vO5/7xp4A3zDwSwTflqD2E4Y6bYHIgnnqY8Bgvadmj0Diw6J0w/galZO+ehOaJ4gxUvIL5OxEm6dmmftp/tjiz18nPElKc0OtkfD2Fut5cTF4uunomJDF9kmxbD/cjxUVC9h5PJiCKk86dFJYFEmlEioqxDGHDsGB/TKhchYdQjJZs0ornm3ucqjeZb/moACPTszMCuWFnNWWT7f3/o6+QZ3s5neBeynNd0wgX19GTYRqAng07nbaEwalQjE7SSZfFawnQ1sEQDO9P+dV4vcAtQ+5TuZ3tlshEXuesASkyYlXdpy/tm4Ob1z61dKPw/1/poNfc7t+V3lqids+nhxTtgM5uMb7Bod1DR+TsUJbyLNfdeHHP+KJIJODf1VAyQYo3wGlu6Bm4IA6GjzaE3HzdyRoLrD21834sBmqT4PSCF5xIuudQm0KgDoAyPhOLCaUbB4Z9Av/eWw7VB0Hj0AIaC/ay3qhlGkLIWczyzLDGFVmDfRr5hnDdSE9CNW7QUUFFe5KtpUfY69NoKMxCDYfHMTyrJfYl94Tg8aDtu0VJCQIpyWNRpQrLi8XU2BYyDM80PtjcbAzGaHGu0jOO03875MtzSbFjeGzds8j5eVZnm22eyl9z0/nfJW4d8U7JYRWl3JPr5W89/IGqDwMhgLwbyHWD5UXGKpAXwpFp0jOiiLOeBhKsaxrgDWblb8/BKjEs9UWUl6ZQ/iRNzGP+NsjhrC4y0y7e8JHwcSMr/k+eysAHwVLjM6PZdHOcWyvmEZWiRdxzdS0bSsyK7m7i/ldWSlktiPHq9ja3xoRrEBBjEcYQQovFHoDWllPtrGEbL3YL9SoLXLF3q+Hs2qlqVpc2o9Q9itIGdZ+qcLQ+tzKO/uE2WRa07fRjDcZMeqRUyOaDDat5zIP37UTyrZDyW4wptuPWRTg1pTbj+n5TbpoukcVH7SZzNjI60R6oYICjF4wu3gtM9NW2PXhbd5Gh45fOr/DuKjrHebSLcnvs6LgkN0x0zy/RjNkJdVaibk/aXhzYQIZRVZF0tdTy9TbDjH5ht/xLXwPikC+4QAb9vqwbKsff2z0JT3fXhmODi5ldM9TzL6zh/ig3evQ7lXxex1ryJb5vzAwdp74u55xbisLm/v9W9f3uTVisEO/b0/9mN/y/sITT55DpMXeunUqmzbZ6wk1UVZWxocfimz07/EeFVQ4XiM4mPPKDLrueZwKg97yXAdXrqdrXx88mg0TOoDZqCcpRSB5da4Iqiw9x5bfdjPQ99fa55KnEfxNBIWJEEwcN5aJfb9nysMHcHMvAr8mQm53DwWFu6gUZqgSjhfFJ/C9YSFelaViH1sDGKshbQ6U/wFSvvWaSn/wvZGXkhXMyLZmCj864Bfa+Sba9bvaS0vctvFkm9bzyNdTubPrz0wct5tWTS+KPd+/tVhrFe5irTVWg74CCg5y8cg5Fvw5nM2nBtOkXx+at1KSkCARHy/WQbXaKnPm58OuzM28mjTYck/zO77OvTE3Obzv6y/OYH2RcOjylKCiAcyBn9aHYk2p5e9LQ1YS5xlh1298IG7b3aSYZJ2a+9jJC+58Os+beesiqdJZrREhflU8ecthnrl+Gl7FWywyoVYn8fOaAN6dE8xpG91VqTBy58CzPDtyGx2CHxEfurh/s+9ByKuCyhAYvAadDhb8omH6ggTSCqw6op+XlufGHOCpYUvxzn/fTk69kKbhxQ+DWL4nhEqt6IeXu46RPS8wY/w64qqesuu3LMNPi1W893MMR1NF2jNJkhncKYvX7t7OplLh4Gurjx0+48GLHwWz/lCQxRk1PLCSicMOo26xDoDzyxLI97+NFu09SGyuID5eZJs36yY6HZSVwaVLMm+lKUkyiBfe2a8l+/v94LDHLK7axbhTnwHQtCyW851c07+pzuVE1mE6Ln8BcwiAK/rYB8EwFSzPtqpa4odVgbw/N5iz6dZ3oVQYGdP/PM/eso0uYQ816H03VF77dtsfPHz6K8u153Z8jftjbrEb50e4QP+/plJiELKVRYZ0cT2/6bsn+dMolDgvpQcnBv5qP5d8FOyWz9D38BsYzXKqeS4NWsvh5BiWbPTn93U+DpyOr2c1o3qc4dO7+zao3zM2zOelCz9bzrOt93f0q0c+dyanbtuk55U5cWw7HWZ5d2MHpvDWPdsYnfwfjiIcFgLUPuQN2yQy+9amf9fA0q4fMCpikMOYGpc2i8W5ewEojvax73dt/EyHVlCdy+q92xlx5G27ryXTP7PTqrGG82r49AyrHvowUH0RMuZB1doafEsABNzBln16Bjb5VnzmgpxqKxvZ8S05WZD/GUgmPUrTBGJmky97kLBuCKWmU48I7cOfPWY7PKcthuMMOjoDqGV+1yGvFRYnE7XoEYs2cX/MzcztON3hGk9nz2N2hlifPgyGZwBdvorlHmf4Y7Mfe497kZTmhlJl1UNLSsDbXUvY0A9J6mrlepd1+4hbwgc4XOPOtNn8krvH+fu2fa7g8Gy3byhkxEM3UqHzYdUqaxUdZxUkJAn2pO2h79xelhHwavOHeL3Fow739EHRCv5zUcyf94PhWbDbMwDOHipnxIsdScoR1p6pY04y8/7NKL3dnPNrubmQ9y1Iv4m/3VpA7Jeg9IOz/SG/3LKPmdsfO6Rn4FtDKSh3Q6My8Psb27ix8wlQl8Cplxzu6cdFKl76vomF22gSUco7E3YydlgaHHvIMr9TfR5nycYAflvjxa5T/nbJPtzUBm7omsyH90+jqW6x5RqnLrqzYGUgc/8IILvIagmUkOnfLp37x+9hQuUYy+cPx97Kl+2nocjLtzzbdLciBiS9QVKVWDfCFBLZRvE2+gV2Yluf7xzexZ/aA9x04kOnOkBd8lqBrtI5n6rNgIw5UPmnA5+K30gwZsPFVXbP9lKGhhfeD2LprlC0ejH+YkPLeXrkISbfdRpFhuv7WHV5JrE/P0COqd+DgrqyqffXDv1eqzvMDcffAyCyIpQMT6tzWDPPGIba6d8KtpUfZ59toqEG7mPPvhrDj98FmHiHKijdJHS4sh0gWx2iAFDHgGdHIm762jrOg2So2A9Z80C7157DU0VQ6DmA+IO/UNKQdU0N5/2wvIsLaRp+XhvIwuV+nEmzd2BqHVvAPQMPM63JEBqEte8Tvvtu0e99pVCyVvBfZXuBGtUyVBHg0R5S1rL/RBeWli9m48EwCircaNVW5cCvFRXB8aM6tj0ViHdlGVnZbVhYsoYNe305fNqN3GI3oqKEHqDTQVoaeLlVE3LrBM43te7fyUNWEluPfF4TwRp/AhReqAwyBowUyuXk6q0yf2N4ZGm6620BmFFM/5BDTBz0M/fedhiUZeDfCvxaCluJoVIkC6rOg+SfAdnKj5rmntEIs7/z5P1FsRadPTqknOfH7GfS9dtRlL8iruXiOG/97XhOyeK7YLU/uTdsFN/ZyC1FHqUE7HrE0o0rzSua+fPyHE9+U55g2VY/Dp/xpLBcQ0iohK/JtFhSAjnZRoI8ijj/cpCdvJaRq+bj77z5YnkMFVqrPhYZVMFzY/bzZ+h9rFdcAsBX5cWFIcsJ0vjb9fuEIoX2B6ZZZCSzbGTZxwylkDILqjaAZB5LSvDsRknAA8RtfZgi0/y+IaQ3q3t+6jC/N+mPMeTYO+Lv/KaEf7pdzD3zNibrIeVLqPgdJJNzuTIYAu+CwPFEdI22l9dkA6TOhfLfQTJzlBK4t4Hgh3j223H8+IPR/hqWfqwCyWTPdWsGwY+Az2AiukRY++2bIew4BX+C4Tx2UAZQ5jmQ2ENLKTT1e1hIL9b0/Myh3xv1Rxl67F3x/IviefjIJG7uvIL+w/0gsK1IiOUdL+wG1fkim65RiwMauJ73idrBkjlroXwf6NLBNx7cAgXPa9SBvgxKzoFey6XTXny/+QH2lD+Oe7AfCYkqWrQQ796sh2q1grM9nVTJd2ov8kz72NDg7qzv9aVDv9frj3D9sZm1v++KA5AxC3SnQDI77SvBrRVETIBLU+37XY8OcN+c51lgEMERbgo1v3V9nxvD+tmN8y9L1/H4+XkWObCh87sm76DVSXw5z51Pf4+2yIMg7F0TrjvJvcN300rzpPjwrlqIGnPyRQc+FR5+SAdluyFnCWj3gGTjqaTwQut1I+8cFLbst3kbT5Ub6detwUvlYdfvi6osmv01FSUqB1nq5cQHebPlY3bvr9xTS/fzr3CyQnC48UqJSw3gHQKr/Shwswb0nhj4K619mtjtYzovPTHb7rKT12zt/gBL/5B4a2EsBy8JByOFJHND9wymj9/Kqvxz1mNs7N8FF4oYPLUjR1KE99ZHjx1gysjd/JK1jTttbDi/d32f0U741DGpn7Akb589j9x2LprbLtU+PrDnbO34c9tjavAtB9P/otufr2Ae/a8kPsgbNd4FPgreL1rOcxdFYkk7ucU8l3Q5kPoBVG+zyrbqaAi8G/zHENE10okemgH5n4Bk2gc1cRD9MWji8O3fAa/yHCufCpC5C4q+BY5ZZTz3thD8EMn5icRVjhCfucAz1fRvMb/vVX/KvDE/lr1JIsBHqTByU6903r5nO20Cv4CcnXYyQmm5gtdn+fH1ymjKqoVDWcdmBbx+9y5u6XIYUl6xswPXanON9wdtESU57zWId0g+fpG43Mdc6rfD+Ojwcr3reVlhOh/+cBAQHH0L3xgODvhJtLOZ31VeVcTseZpifZX9XBq8UvTb1P70US09XxtGcaWGDx49wNRRu4UcVvoWFFY76KFybh53fd6HX/bE0zkxnx2z1+Mh5ZGcnEec9+sNe9/mJI+N0UtszAZk7oOi10Ay6UX+4yBsCkhq2N3F8r5lt2C27Pfmk3l+rNwbitFG120WWcSUW3Yzvuu4BslrTt93A/y4SHwYoxG+WeDGrCXRnM4UDoQSMn3a5vLaXbsY2uwDu3FeWq5gwZ+BfLIwiPMZ9nzq6D4XePrGnfSNuV986OI+5r1wPOU2r00pKdFIShSmZ6RD2BPNqGk3qE0vid92N8kmvcQsQz79eCH3jVwJFX9BxXGQi03JNlVWOUcVyprDQ/hxw3BO5Pbm1gea0LyFsJWEhQkZxGwv0euFi0xxMXQ/L7nc74qydGJ/eZB8k9xyXXAP1vX6wmGt3aA/ynUmeS20Kogcd6ue9Wf3WYwI62vX71R1Lh12P0qhXgQWqMDCn09rNoEZrZ5wuMY7hX/w4qXFov36mUw0+HBzpxXcOKIAgtuBbzOR8ErlBUo3IesaqqDkLOT/BammfazPIogbiwNsZApdRRZxP00g09Tv/oGd2drnW4d7WqU7yI3HPwAgInkwmXPFvlBcjEUPqRM/md5FY+b3fh2UboOyrVC6BeRy+3O7JYLPYMgz+We6OM59Fo6nzDTOg9X+/NJlBl31YcLgBlR56ZmctYBf8oT84K/1pUhjDWxNGryMJl7RDv5rMdvuIt3kx2XHIz9kgPK9kPMrVO+sIa95g++NtP9rM8dM/Hmg2pe8YZtE4hWb9TzfvZjg3Y9ZDrXTxwLKoWwT5P4GumP28cuqUPC7Bd9bv8CrIk/s3ytyoHQdFGw2tbe5JyRwa0ZyUXfiPEzOYn9j/67Lv8Xsz2Re16q1Ej+uDuTd74I5Z7OuKRQyd/Q/yysPnqCldJv4cFSaqFpYE0enw3Fr1JnvxGK8qspd9md6IzOQ13LXWz7d3+8Huvi3snvf5Z5VJGy/h1xdqZP3Xbd8ju8IthzwZGDT+bU/Wyd2A8teeYV4h/Onq+g3uLv93qpNh7SPTM/KtC5LHuAzEEIeJ6Jn5xr6txHS5kLZ7yCZEyRL4N4Ogh8idvMrpFIECL+v7GEbRBObcV7qUY7vrocsj8TWPmYrt8yYE8ZLv3YEoHNiPhtm/E6AW3atcsuh/Qaue3cI+WWCP//1te3c0u14g+QWW3nNjke29GEr8J5458pgiJ+HVgrhndWrLcdY/ZF1kDoHyn8CybS2eXSG0KfAox2c7tKg9232R7aTzzM2Q/Ec4LRVPndrAUH3c++xHSws+NPS3bShq4nyCHXYv5tsv4eLpuT2CrDoJS8nTuRNJ3ZgW72kmd6P8ya/3Nr89nLcCgm38duzxY+d3uKu6OEO1xhx6V1WFx4FGm4naoh8XlP/fuwRPQ/dsQnKdkLZPjBaeXjMT0gTI8yLOcno8lWs8DzD0k329jEvL2EfKy0V9rE2LU6yd7S13NLIsAF82e5FvIrKoEDsS8cU6YxNnk2GTuwxntVQ8Q4UFxfjW8dm/F8XSLJr1y569bJmW3777bdZuHAhp0+fdjimefPmTJgwgWnTplk+27lzJ3379iUzM5Pw8HA0Gg3z58/nzjvvtLT58ccfmThxIlVVVS5dt2ZwihkPPfQQqamprFmzptZAkuuuu46mTZvy1Vdf4QzTp0/ndSdh0vd5fMPEzweaMiCIKF1Ztsl7b7Jj63TVLDohBvR1vYcSExmPJjuf9nc9j0Krw6hRk/PlIMLd11nOvXAu3LPB8V7yCCKHUKpxw4NKoknDm3JoG8HKqExuqpGAoQQfUomhGjeUGPChlDiSUcZEcfet0figokubTnRo1cXungBktQLpAyPmkPuDFzuxfL6C6ecOiL55Ad6IaAAl4Gf62wC4Q1VoOK/6x+FXrqVn++6EhUSiLigm8cXZKPR6jCoVBS92JVizB1mWKMaP3/fAhFXFSDWmhAxcoAkl+BJBJuFkI0sSp5r1Z7GXgdeO7HQ4Bg0QhrAL5Zo+i4lpcL+PJLfDW3+Jpk1Lwb8btJ4MUTcK8tcW5SmwojkllUa2/BZE5KEs3PXQtuYaZEKKH2R7SVR6+7EpIIbX9h137IOb6bm6AxVAIchGieJuzdgYnsutKxyfVRVuJNEUX0qIIc3S7+lefkw/XUtWsTDT88oGzBxYjzBW+mfbjSkZyCKcPILRokGNDj+KiSGVkqZxbOsSSeSOXUgydMl0fqmzQVBiskkXx0fid0k4tcYVQUiFY/sCD7ggfLfI8Q1FH64m8mw63lpomef8GofDQa+AQ9V9eTh/OwCpqSJCtD6c2nWQuXMnEaw1MqL/TXZjFkBWSUiTZfAX7at0brz7U1sxL2yhRowhc0JYLWJuJITxQucgZoadrP9mTHhlVzhVsWIuXd/nejzcPe3uq+Y9Adyd26tB4/xUegsWnPIlwIBL/UaCldtwWHMAdKg4QwskZFpwBhUGMQb91Uw/dsHxAE/EedVANZAP6CA1ojtzvA2Oz9YDCDS1NyLmuAw0CeM3v2xuW4cDZOAszanCnSZcwMfk+n0wbDjLfXMcr+GNmHtqBDtQBiihqkks7xaF2Lf3MvVBbfoRD0F8HhHG9Z2jaCJ7ERsRzdA+N9T7LgBe/eBGvj/0FelEM3SQgXsnKOnTR5R9NQcHV1TA0aOwdi0s++xPDuXdyOhb9Hz4iXBcBUG+GE1SoSQJg7dCAbt2wbr7uzoft4GINUeLEO4rYW/nKAbclEm1ZEQhQ0IhHP4K3G30p4k3ww8dwGi6v0dP+fJVqxJcRbscd06EVGFOhrxjDvRJtW8ztyM8MBLL/jopvQuR5UZaNWlB84RW9Y7bU8UtmKUNRaNRM/6W++p9F2tLVNyQLc6lMsBNZ2HpIvt7+rQ7PD0czHzlgtXh3LPX9Qo0qUQzJzGM6d4H4EHEuDMCQe0gbDC4hQhja8F+SF8JwPQ32zqu50rEfbshtAGd6Tmp4KD3UJZXF9q/bwkIQIxTpemaleLz1BaRPNBZy4aAWhbZGuiaDk9dtJdbDCjIJoxKPKjEAy0a3KnCg0q8KEfXMpJZfd0btK6t2hVL6OEUJBk6ZYHCifRsu2cUK9vQZvIFwsMrIWIktJ4iqkWZs+iVpwinhspM2HYrVRkyyuf1qA2ui+XbmwfjUSaeU4s88HFiC65Qw0lTErQl1VP5oGAGTRIUfDdXSf/+JhJX5+gMp1SKn6XjBxCzeRtKI7TPBqWT2yt0h6RAMEgSlxS9OBWkELKRlwz/AZpRszATALJBIqe0JW+cj8ZgrHJZTp3+bhOmF16Ah4GmgOwO0ddD2ADwby8yRGiLIHMdnP2UZTn+jC0sQFt78hILJCSalPmR7w3FFKMwyow4B8t/tm9X6A6h/wG9EiRZYky1H2NPwq0rivlDHsljfEk2YaaO219YgYE2CUXMaB5M27Vx3Md8tjEAFTo0nmoGDxYltmUZkpNh0yYID9bR7LaeDVrPMwrDeeOcsFyPGzEOL08fu2Ns28uyxNISPybmiH4rDTJP7YUPa+xpMqLfeV7iWbX4cykV2Z1o1iyajRvrfsBGo5GtB7cy9feHOaxJQkZGKcP4IxBu4jqqlDC/IxS5i/OPd/djdgT4qYqRhqyH8BrOW04yamYnhRD4ep7rc6kVVE5V4OEO9P4BEkw6oVGHZeBWZonMrDvGgKyz10vaAI8g9i9nhUAMsLwsmJE5Yq6qDHDnMVjwh32zuR3hgVHi90glHPRWExaqg8TJ0OltkclENph+gKosE4GfBTvGgqxl5QKrbKRDRQaRVOKBDjU61Cgwmn7TUd5KSY8xZ9ApZBRGaJULx76078KJEGj7uPhdMsKNaQk8cLGamDMZtcrORgmOhYJOCZ92V7Kwg8GyR/34G9x1zL59hg9EmXw4JBnm7xTreTmejGchf3ArKnTobasimqDAQM+2yUyLaspNa2EVw5nAXHIIM1WqUdq1V6EjIkZNv1t7N0hOBSzPdg3DeISvSSEOsXk5zu+OCbm83jzC8i4WMp6H+BYDSod+qNCREGPglRYeln1Mi5oJfM9PjHe4hgI9SPBdtxfxDf/Woo99xBSeQziEGmoUnVVIelpGZZBR5ktQkB9HjgjCCcQ64yShO7IMI78ZwYrM1ZZB8cfPMNImd4deAS2egIv+Qg7xq9ZwR6UIeHNlPU/VQewlcS5Jhv6XYIs1L4AFI++AFc1BVkC0Cr7cLt7FUkYxkTkUEmDKN2//Lhr7vk+lt2BWuuvy2ulyNaPPKjjtbeJ5ZEjMh2CTB32FCo6HgkEpvvOvgm7VnRu0np/MD+X8eg8iDyQTWAlNCh2fE8CpYCg36X/JbXGql2QRRj5B6FDjTRnxXEKFgVOdezOrn9LlfhdXq9m6NJLIA8m46aFdLbzDJX/IM8VTnmrtnGcCIZPmE0QMqQQhEj+caN+GpJZ+RO7Y5ZL+LQPZzSIJPy90/JZ54O1ENkrxgxzTHKjwa8FP17v+vjMq1Tyzz5NVgcWUOi/yZYUMo05Dh5NNhB6qQewXPRG6udLJMUbIKGvDG6eFc1J9+7cZTuXzyUBXrAu7AaiA4jfB32pToWMmHHKS12ZxGxhn8tv30Gm4t8z1+Q2w/Zd4PA5cAqB5PvhW17wClGngtKkffp7wo+8NfH/wa1KJZUBfPfc9oKJPH2jaFEuG+LIyOHwYZmx7lzXaaZY95rtlMPGQ4zUG3QdbTAnHOpW0oLvB9ff9xfpHeXzel6jVwsHRFWy7/xY8168AILoEwh3zHJDrCcn+4ncfLzjXxDm3UY2G8zTDj2KiMQVM18ev+SM4ixysmVOc8GtmlOPJRRKIIp0Ak0GOhGhWNk9z2l6P0sK3NOeshW9Z2CLV6fwuxJ8swqnCHS/KiSEVD6pq5ZENKEghlhJ80aAllByCKKC0SRT33iTxR2Ca837XgLsOXvmrCW211USeTSe8TLyPmtAp4Eg4yEhsbx7ImwMNFll4zAn4qYYj/Hed4aGbQZIk/PDj6dWu86kYqLXfIDj0iyTgThXNOSumbgN5ZFmGpklqLhp1IAm5M/89x/n35HD4qqvQZTR6Nd/uCab1yUy8tNCqlrU23QcyfcQze+32hu1jqfnRzPk0jOmqA/Ao4nMD4BMD4UNF8LZRJ5JR5IgkCE7XNRD8lx/Cm6YcKIBKFXi9ZOVFWuTB6c8cD53fAe4fLX73kGHxHrhhrZJXeIOZvIACIwaUuLtLhIWJ55mdDdXVRuJiZJ66oS9rK/ewrpnzZ2SLQRdg6OFotJVhTA8+APcj+A/UENoTwgaJ5D+yHvL+gpSfKa7w5cZXvmRn1l0M7Kfnk0+VdOggOmU0YslGqFBY18TiiweZOHgdyy89g5evkgcfkhh3h4I2beyrxOt0cO4cPLv8VdZUvdkg+fyR435sCyvmZGj9/W6WBw8fCyc3sWE88oL9UbT4Kx21UezfnjrHc2d6Q7ovlKshq6QTp4IV9jyTL2LuabDyqVrTc48MZaV3jmXuVaPhHhbwK2YnKfNmKebyUzG/c+q2GQ0a5z0vqtmr01lOlfmB4x6wLQ4GTBC/K40wrrjh/HlD5FSA/8y8g2+PfkmVmz8PTjRw191Keva08rtmGAzCZ/H0ixL3bAAjEv/hfWbzFDKSg44hVk6ZZiPe5Fz36ZY+TfoLZq+2b3ndPbAl3syfwKuLbOZ3E0REpdnOZ3dT4jX6nFdQpRAEc3gpZH6IA2b1gGeGmXhhnRuvLbaxl3gATyN095q0hQwkxzD9Fxu7gbfpnprhqOOb1LPUbd2Zs8nGbhAAvABE1OiHWZ3bEsP07X5MP3McRgK32pzbIwT8Wgln1apMKD6JUQd+l5SUmTbzwArIe8/xdt7rA9OG1NJvCetepETMC1/T355AaCDXR8Y3aJyn5UdSnFVBmzZF4NcZ2k2DyOHCKdEWJq7m5x2juOvzn/Fy17PnLyVt20oYDGK8me0E5kRrBoPI4Bz3UQRZ1SJ4x00PJe+AxmB/+mlD4IPeYkw59NsWbmBJ+5+FWBNiYrj+tpAG9ftUfijnTPpYSDnEFTteCuBMEJSabI8fj2nY/AbsOB1bpBNJDqH4UkITLiABVfFN2NRHx4icVOh6PUSaIldsFXz3veDxl+XP6e+a9JIYRAR3KDZ6iSSSlJmTH+glXshpwjfl+RRTDLLM7NXwhLUAHyBkii+7gVEhZKPZu0Noeew8EjKdM53z5/kecNHEnyeHN0HtK+S1yFKILHVsb5TgoMntYkOCimnXWe0lDx+Az1fZt/+1NYwdK3hFP9mPD/db7f5GJKbwEbOZjKh9aV0UlOhRSAZ+7vY0hC+ys38X40tftnOK1nbr4UdMIaHvQkYPzbfc0zO7YaYTuThiKmT5iPsaWNyJVgShVBnqXc9lWSKnMpg3TnZ0mT8/WAVdTLYthRHGnoCff3O8p4dvFnykXgkUR/PayjDrXGoJTEGsobbrmpnjT4ph+k819BIJeAlogXW9NSBsRdPhoLaGPbQv8JDpOCdrZ9WWJkw2OXo2xr9FBqbzGm8wHQUGjDYXEQydltVtJ1IW9Ytl7mUTyjDWcpy2du/afPwXMTPYcevKK7p/V2k1TD7smv4tyxLFej/uOdqGKIPCpXXNaJRomRRDNZBKKt7VMiXvOI6PPE8Iec40l/DjiwNwx0pHv5Du7OUgnS3P6xQtacmZWvXQX7mdsfxqea4v8xavM52q+CZMHtmw9339X43US2z3jCbAq2LMWYaIETgDLIjht5apTvm1QvzJJgwtGgIoJJo0JGgwv9aQ922G7TgvwYfRLGUTQ6hphDOP2w/bvk/zqOe4aS3M514e53Mq8DRJvpeHT12bmkDFLgMx+1MaZTf4aQncWUP9y/KGiGfF75IMr/2ewGuJF+FmQK2EuDEQMxqCe4JXrOkiBsjZDJuHg6y321vL8CKbMKpxQ4/Kzl6iQk9AjA/P3KpukP4dfl5FjinMw10n5Ba10b4fLw+GmX3EWqvWq/HRGyhwE43c9fDaFiuPrJNgZl/BXcqSkK9lhXh2yNA5Ew584/hsB90HW+PFMfsj1XTx0kHMndDPFCRm0IqkbAqlNSjEZJtGtiG8Bq2FiOsdL3B0usXBXpah4wV3jhmqkCXxbpI/hpganMsdt8NvrUS/VUlD0S8UDvZVVdRbQQHg+ildGje/9QfgcYRcbgDc/YS/g5l3KD4OeftAE8bdO5s0aJy/lRzGK9psh3utDc3ylJwPFoKswijsrZP32Lc5EgYdTb7JCiO8stQkr0UgMmqZ++GMRzbA9ek+bKwqtfi3nPzMkddZ1gJG3WlzjcUmfawT4ll52FxDUoixYtRZrnEweygrvi3gtWYHYQyCj1FoIKwvhPQRyTMNlZC9DbI3NG5dm90w/xYCYWU3R9nZiEQGkRQQiBvVhJOFHyUQE8O7gd68kHoKPNXg7wse7qBRWZUSLwN46IUSotZysLw3y49muezPtKl7JEOHZyCb+Li+KbBpvr0O91Z/eHWQlb967TfT+45FyF228rmkEEkFDRWWd5FR1YY3TjTMbnD3vivLO1Rp3Xh3ho0+1gch39nuq2YYAPcYpr9po397IcZ6Cyfv2SQTBpxRUqQQc8lDBxVvOzbN9IbIZ61/L9nlaB97g5d5jTctfyvR05qT7KAvvj08HeSW/XRhIFuowh0DKiSMSMj8wh3cHH/QZbnFLK998qUTHrkJ8AqmeWV6RnkgT5c4FVbDH1kCJgG9sB9YBoQIsCCGu9v+DT9sEHvsWNP5nMjnD570YZ6qDIMpwGTrXOifbP+c9QpwfxkM9iIGklHYy35fjAMmjISFHcQxHnp3qpVWv73d30HPGiaBBR3gPhPHi2wKVpHEGtczDXZ+b98+2Q8SJou5JxlhdGoLQnyvjHxuxvR3mzBdvgATEXNbEwHxt4l107+D0L91pZCxCo6+BLKR1z8cxvcHhQ9C/z7CPta3r719rLRU2Me27ipnfU4TtvnWYpx1ggkHI5m7PON/J5BEq9Xi6enJr7/+yujRoy2fP/300xw+fJitW7c6HNO/f386derErFmzLJ8tXbqUsWPHUlFRgVqtJjY2lilTpjBlyhRLm48//phPPvmE5ORkl6574cIFmjZtysGDB+nUySbiZ+RI/P39mT9/Pps2bWLIkCEUFBQQEBBgadOhQwdGjRrlNFgEaq9I8sHMERQrxMzxLqnCp6QapVKJzsuAqeozUW5ehLu5k9O0C1mBESQXJZNSnAJAYG4ZAeUGCr2UGIIV+MuVNPHwJdbDE21lJJWFMpmlmWSVZbl0jZKAFpTqNA7H+JfrnbbPbdaVzIBwyz3FJeXzxn+skWsAX77Xl9IEN+I9vAn2DEZbGcmFlAyn91TkpaLMV1jyw73DifCJoOWmI7T6foXT5+oMOx/qT86A/pet387uiYR48t1lp+9Cb9Aj+cjIwRLechUJ7p4Mr9iOp74YRcyt0OcXxCpo44BkdkQtPmWNJi0EWv8gCGgzakQAmjOaoy3iqKwkqbSi1n4764ebjz/VpUUuv++6npPBYKDU183pNS5lnHL5XUTGDSU61Fo1qL5+49cMvJs7bw+Okc31HeOk/aLzkey74EVOsQYPHx98fQLxcXPDS60CSUJSSsiSEdmgR1ehxddTT/d7JFacW2Y3PnxKqlEpVRg8dcjBYt7XN19rG4PtY7qQ4BnNG+e+ZW7KclKqHIXyKE0Ad4f25u3Ioaj0ZRwMCuSgu8bpuHV2T6VeLclV+bs8v6NK3el5328otXqHe6kNR6KUXHhpEplShdN+4ws+cnW9Y7Cx47yh7Q0GA0ZfUPiAp1xNhJsn/u7+lAS04GxB/hW7p9rWnNrGVM6Jrkx74WlkWcHChRJ3322qllNLJbeXXoIZM0QGj6ys2h0Sa+Lo4bXs2POry/3O95B56JgTrcAJ/hPal/faPI7Rsxkvn/mC+akryKh29IYIU/tyZ2gv3o+6gb1FJ+h79jsAVJKSZ5vewzutnrSb36NTPmRF/iEMGFEgcebCIJot2OTSPZmxefJ1bLq5R53zIrOJn2Uuzb2QxI9pWy3R1K8mPkSMwRNKy9B5efBc6hzKDJUokGjpHszC5k+SXKFt0D7m51NIC7aJdxd7K3T+BLxirA7LAEXHYY2IYD+aBUm+E8nUc1nW89rWqRjPcN4/v5BFGes4Vnre7jkFqny4I6QHL0cMJAK53n3MWb/9d5bQfOFml99d4QM3E/D4dPsPne0Z2kKozoHyD5HlKqQWT0KXTwSBqTBJ+E6c38kD47OgcOIwURuMGhWK3/8AmyDmuvYx/1sfpLjCnddfh1dfdfEimZnix5V+myr8HJWV7M88wS3ufxCoqkAh1a1qHNRqONjiDZIry1ySUzVlSnqVzEHCiCL2Vuj2hZUENMtIshHy98M6odTJBXCvsg8/5Oys815ejxrBq2G9uP7iYjYXnUQvG1BJSnKu30BAcbWl33O0W3kw5VvLcfPjbqVjYFc+W+XLd988Zsq8LAK9u3eHkBCR5XPPHuGI2KkTPP/cLiZO7ERllYbISCUffQQjR4psSOYgPIUCqqthyxYIaX+Qg5kH691bbdeQ+vZj2/bhbhpG7fqJahNB2NmvJQf6/2j3vi9ocml6UuhMKhSMC2jLf+LuYMOFdFLyy9BWu6MpUeOnU6JQqDC4S+BhRCEZ8UeiSZgP3W4ZRftfB5Gvq8XyboO9zR8gWp2FqvokPkHxuMeNRPJNFBVJ3AJFEMX6fqIyhxkNnUtjgFGARwSMznDe5uh0u0w0AEezJM57DuIWn80okFGY9z63EHAPEdUCK6zMxpgUBb9XyyYztcTanp8TUaGAwiKM/n7cdPZVUqpzkYAH/Tz4JtRkPbg1R5zPxXtKCnyCzCpH2cjZOrhIqeWjdKuXz+9dP2AAcZYMSk8VLuCXot2mkAyJI60ep014H3tZuI4150jRKTqe/gIAtaTiwdhRfNF+mp18/mvFNsaaMkMrkHglZDjN3Xoy7Y17SE2NQZaVqNVw++0wfLioSpifDz/9JOZFp04w7/u1/Lwgj/dm3YHRKAEKfHzgzjshNlbMoe3bre2/+9O1uVRTD121zpfPP52M0ajAbGRLSLDO7zNnhBxkvqekEztYtiGO+fMm4jzKSKBTJ5l5368j6cQOMkoy+WbOHRw7OBhZrj04y/YaPy9vxa+L76q1LUBiooHcXAPl5RoWLZIZPbp+Ya24qpg2n7YkoyIbGZlAtS8PBg9DUSn2rqPGVFaVHLa0nxM7io4trrPTGWo+2/feH0JZgrtljXrkwCrOl4s9xkPhRumI7SjzCixjSvaWCDn+iKWiRbTal5Vtnmf+umZ88uXtlrU2LAzuvdf6vnfuhGXLoEOHxr3vUq+W7C8rdnmtjVR34Y59n3Ck9Gydz1SJxMW2U8mNSKjzOTm7RhP3XsS7dbI/YR16aG2yUV16SW6zruyRqi/PPTWCd2iwjt9QfR2cyi0HgwJZWpXpsv5t7neJtpR1eXuZk/IHa3J3AxCvCWNa07EM92lKjEJp6fel0mK6G+YSqswR+4WkhKhbIHKEcLyrzoMLc6FQRELUlI3q2r+dcQKt3LO4M9DRmc4gS6Too2mdkk2VKUtjhFswGdevdXhOn5as4emkhRY95KVWdxHfbJDLvGKd48P2XZje3+b9flz32l3IRolvv1PwwAN166E/HPmJe/64GxD62xstHmVa4gMO12h5eipnKsU6o0Bi95DZrNBmuzTOo928OHOyE+mXfMkpUaJw98TLIwBfjRvuKDCoVaCUUch6lAYZPw+JB++KQpVbw6hcD89U13z9p/i1+rjOhvItl4NHjowbyncFR3n9nFUGrw3HWz1BG48wxzWhnndxd9oafsnZZcma/0vnGURWaaC4CIOvD3cmvUuWthAJiNP4s7jlZNIq9FeUT20of76tMJsvkvZY8rEt6fIet6nb2+2tMSefsGS7jFL7kNz7K5S+Le0fYh3reU2O0JU9I6Qol7YVK0ToZ1h/6DIbAjqYsmLpAQmKjjaad3g1bzH5BuF96qX0oGzEDof3/WbBb7yR8gd6E88xK+w+Fn79AvsPtwAkBg4UmRBHjbIGYVRWwu+/w+bN8N2bVt24VF/OzoIjfHZmIefKUohRBzE5Yjj9wpvjp/K0PKvsqk2E6TYLvqX5Y9DhHVFh3KgHjMIwW3QU1nZj+m+v8frv0wkOFgEs4OjsbwtZhkmT4KuvZOLiJHbtEtycJNV+3MH0o3T5rgMAKknFw3Gj+bzdC3XK51/F3sNDHZ6mTF/BkowN/Jy+lnV5Vu+XAd6tuDuiF2NCeuBv1DodI1A3j+zynlGDd9iRkdSouffN92M5un9orfJ2585Gvl15uEH69+bs0/yYegSDLNaVNT0+ZVhobzu5pebe+lbb+wlL6HPF5NQzOwbz7jsT8fKC1asl+vQRbWobH0YjHD+6lvPHd/D+58PYs6cPZj0mNlboYz4+kJMDf/whdKCOnWTaTL2dH89bI+96+rfDy6gEnY48uYwjVVavgtcjBjMqfChJpRXoyo8x0nMlaslg1aedYGiWJ5tKKy3PrfCGLfgXVdmNjwczv2Z+9nb0puf/R+JTGGVfMkszuE6znKZuebVew+jdkuOhL5KUdJa80mRucl9GqLoUZR1cluzdgmOhL5GUdJac0lRu9VhCoKqi9mN8WnAs+DkCL7xPJKcFdx49Glo8DaH9hJMQWJLFYazmtgxYVm6NC00bupqoMsm+0l7qLH7L+wuDKb/n+lbP/S1bZX1j6paKLQRos5DCBsHA1SbnJpsgI7NToslW+e7y55m26F2Cgoykpirw8LAGkTh9rjK8tOlF3tv5HgbTWr2197f0N8bY9bvz2WkcKhfjylOhZkvbl5zux5fLXtIYfczVvdJV+3ej5DV/8FFWE+XpRbinO8XqBNx0+fTmJyQMKFXuEHcnNJkgnFkkBRiqIel72P8E1UYjrS7CJaNI3RChCWJLn29RFRZDYSGF7hX0PjMdLXoUSAz0SWBDl7eQfGp4gdWznjdEXpOrCxlw4Sd2l5xDLxtwV7iRdf1a/MxrQnAwfU5NYU/xaYzI+CrcWNX6P+RUQWZpJj/9OpSdm8bhKkdjfrZb1t7Fjo3jkGX7watU6Fn5zavcnP6eRb7oG9iR7X3m2PUjw72YqOMiU4sSiZH+LXmp2xMWPfRycLy2fEu4mxs37VhgWRva+yZyZMAvDs+2f9LrbLepOrer3atkVRqpLD/F7Z5/oKpjfZa9W3LMtHaan1NXz2Ru8XcMBDbIEnmGIE4ETyc4shk79vyKj+4o4wNFoFOt9kSfFhxs8yEHizJd5plsdePla7qxdtkjtZwcwEiXLjLff7eBpBM7SC3M4e0Zz5ObHYdsdL5QOeMVoXY/D2f7t7l9XWtOQ953Q2zy5jE1+dDvFOsFn+6ucKPyxl2ikc26lqHJJ2rvk5bjhxDL483utVtzis9EM/s7a6JchcLAkF6LeXbM10RGd8bYdJiDHXjuvHc4k9bZMp98ffKY98a9JMa0RNt7fJ3y19/td80xklOWwaSQ7QSrypyO9dP+T6CNvMluPTD343LyazX7YTum6vLjSinI5aOPHyf1UmuH9ckWZh559kd65iy80fJ5+/bwwAMiEapWK5JAzp8PzZo1jk912CvrWM8PF52ik43d4OG4W/ms3fN2eslvFTu4/ehbYmwhsTUmnj5uF5E8QmHIFuEHZdRbZREnPlN16ZWXQ/9ekpXE7+knLTrA7r7z6KkPt+t3z/OvsLc0CQA3Scn+LjPofvBVKm1tWrVgRdPxfFpwhI2FJzBgREKi4IbNdrJwpZcev6MT0ckGFMCZeBXN1HqM8feh6D1PnMigFbZTSarVrnQh8DGKqgsprsjATSkToAM/vQJZlsFbRvbQo5Gr8FUqOCQreDR1n+XdzGj1BM/73Wi5pxLPKkKOPYpW1qNEoq93HLMTH+ZscSUXsotJKyxBW+2Bd4WEb7VEqacbkoeMh1xFsFpFXLA/kWNv5nDOkQbNb//iEjqW/wbIKPxbQ+ePRRIHhcrqwGIjb9fHv9Z838GewUSoOzNyz0zOlafU+e6WJE5kqGc44cfeo8qoQ4FEn8CO9tVyg4N5I+dH3rjwo2XPnh8/kViVkT4sRIEBpUIJ0SOFvBY+GBRuwvH4/Ldw+Dnml8jcb0NDft3+JR6Ou9VuPX829wdmpa+1yCq/NH2E5lIqnaRVGGVQuAdBwr3Q5AHwbytOVHQMVnc28TVQVCXh7y6Lyj9tpkHrF0TyO6Ne2OMlSRxj4nQOVsHBxJdJ1tHg/dtVWbjYJ4Ey2fsf41Od6Rlb9OeZfekXSz9vCOlFFL5QXUWVWsEv+Vstc7m/dxyzmj1IcdkZG/ncw0Y+722Sz7WQNAf2PwEYG2w3aKjfXmPsY+b35125naEewm+7NvnOVpfOLU1hhPsyItUldfqSNElWc9Hk4C8hob9pn0Pl+nOqDJr/ZY0kGaVuwb1xYyzvuyAvgi/e+9qBB5IkA+OHzee5B4/byS2yDPM+/oD0rMQae6yMt2cpW76bgTRwbIPkFsdxLvNk0FaCNOV2cohRljiha0Fu6JMERza1yCEdFRvp5XXJ6bM1yiAHdONIp68aZf++kJJBrHEPN/mfqPU9AHxeGcqTabkWfmZOh1d5IHak3bp2QZlJ050TTO8LlCjQm9a4Jp5RJA1Z7iAjdDo7jcMmHV9pShUJwu4zrdkE++qKNbgQCRgf2pefcndZ9uMTA3+ldZWP5RqvlC7hnezllrV2S+ID+MR3uWL6WKyHJz4lVXQt+xEZCUW7V6Dty2JOy7I9j5K3D9b1YMvJAQx9Zz1Go5Jvv1MwcWLt9jFZFhyeMieTNUeWMHzvU3W+t0i1HydbPY6klfC74+3/nUASgB49etClSxe++OILy2etW7dm5MiRvPOOY7j8888/z4oVKzh50pp9/7HHHuPw4cPs3i0MvePGjaO0tJRVq6xpK4YPH46/vz8///yzS9eVZZnIyEimTJnCc889B4jAl9DQUGbOnMkjjzxCcXExISEh/PDDD4wdK7IdZWZmEh0dzapVqxg2bJhLz6CkpAQ/Pz+KL27FN76/q4/u3w9npTwPHIDOnRt/TmfOj5mZov67v7+94yWIv2t+9k+i7AIsbyp+H7gaIobZ77jOHFHNGLBSVC65hmuoB4ezDjPpz0nsz9hPy+CWzLllDt2iul3ei9Q3v1NSoEULkYbAVbi7C4+92NjLd5/XQEwMpKfDI4/Al1/W337RIuGo6eYG+/ZB27bCIKSqmajOBKNR/NT2fV0Y9csolp1ZVmcbPzc/Cp4vEMqDDfal7+PB5Q9yIvcEcX5xLBi9gL6xfS3fy7JMy89bci7/HDIyLYJacPqJ05bvq/XVBMwMoFJfiVJScmPzG1k24Kva9xiof59xYd8r05YR+n4olfrKOvsNcOChA3SObOCeWXIO/mwtiIDW06DjDJPCb2PArBmsCHDDAQj8G/tzA5FSnMJHuz4ipyKHZ3o9Q9fIrn//pFdSRmjs/p0HtJkLAe1du6fg4Aatge+/L4K/4uLg+++hXz/xeV0VSRoFWYYtN0LWOmswUmBXaDlFlIjUFsDpjyF3u/UYV8eUoUqQV6VnBQE4eL39mIU6x22pVyJvb3+bmTtn2p32w+s/5MnuT6JWCm1s88XNDF4w2PL9a/1fY3Qra0D5gyse5EDGAWFI9Y4geXIy58+q6dzZupWNHQuvvw4tbXyysrLg7bdh717h7HziBLRrJ6qOeHvX7izpVFFsjOxc85ga7W9bdBvLzizDIBtQSkpKppXgqfa0fL/gyALu++M+y99Lxizhtta31X69WpBVlkW3b7uRViICLXw1vgR4BJBcLEgCD5UHy+5YxnVNr7M/UDYHaxWIdcuoE8Ea+lJBYFYXClaiJBCItz+2trmkz4WSbyHnd4i6Gdq8IMarbeC2bZYmbRHoCsG7Key8G3TFgBH82kKHtwSpa8aF+bDnfgDS9RB3SWEhMerCyjE/c2PpRkEOhg2Cju9BUI13XZEhqpKY7686XxhPglyX4Sp1lcR8HEN+ZX69bR/r+hhf3PhFve1sIcsysZ/EWt5zq+BWnHzcvire06uf5sv9X6IzBTAlPXmBp+9LYPVqIU/cfjt88YUI1tDrhdOTwSDmw6lTMH06vPyyCNiqqhLyxRtvwJNPgqenOEaSRPsjR4Rs41AI1IW5lJIiZJyyMrHE9ekDb70FAwdaDzl5UtxLcrI4/NgxcQq9TZz00KHiXmVZBJZt3iyMeQcPiu+/+AIef7z+Z2s+ZudOsZbbJbBpAomJonrcwYNQXi7a798vfo4eFdUSq6pE4FrNDGBGo+hnYCC0G7WGmxYNr/d+WgS14NTjp0TZdFvUs+a8uPFF3t/1PnqjeEhHHz1Ku7B2lu8vFV0iYVYCACqFike7PMrdgZ/Sr594rp6eMGsW3HefdWyA6FdKCnz6qdj76rwnJ/fV2PZT1kxh1t5ZFhJVo9SgNQhn/SEJQ/h97O/4ujsh564EF/J38W+8p38xzLSqwxwQX4rKUam/A0aIugm6fQWeUabsbgrxuY2xDbCXjeqZS3YwVAmDaEUa4JzubZkby5kiYfDUKDVUvVTlcO+vbHqFmTtnWtbnNXevYVgz13jLxiAuDtLSYOJE+MZJdsWa2J68nf7zBCeqVqh5vNvjfHzDxw7tgt4LoqCyAIBQr1Cyn7Wxrl4b5/+V2J68nYnLJnKu8JzDd2Naj+Hbm7/Fz92vUefOKc8h+qNoy7ivC+vGr3OUVa8G6hm3BZUFhH8Qjs6oQ6VQcXe7u5k3ap6l6fGc47T7Uuy1CknB9AHTeWXAK1f0nqjIgBXNRIbKphOh+zdCrq/D4QdoEO8w4scRrDm/xrIHFz1f5DAOHlr+EPOOzLPIHRPzcpn7RTBGo9DRXnzRud5VV1BbnSg4CGu6AjJ0mQUtahj1avT7640P8+j3X+PpKXP+vERISN3cWVqa4PBABLvcfHP9XFtj5POLT18k3j/ero3OoCOpIImEgATcVC6kk/0XYcUKuOWWutvYyucW1DPON13cxJAFooKmUlIyY8gMnuvznF3zB5c/yPwj8y1jMHVKKtG+0S5fwwH1tB8yRHANI0eKwA9X8d578Pzz4veYGJFA6M47rZUjVCqhL3z2GSxfDuu2lOH7jq9l/tWGAPcAcv+TK5yhdKWCj6zMtPJGvi0gbAgoPaDgEOSI5D1v5MMbBdaAih0TdtAnto/dubt+05UDmSKI1lvjTdHzReI6pz+Bg1OoFwp3uPkMHJ4GKYus96TQQHAv0ARCZRrk/+V4zOmP4cxsoB5dX1KJ80oSdPkMmj9mn3QGTOuGeKdfFsHjuVZpbvkdy7m5xc12p0yYlcCloksAxPrFkjy5RirQhqK+MbjYV/Av7d8UThA1cXS6nWOiwajg979u54tD87mY4s6YMdC1K7RpIyhNjUZwj1qt0FvPnIH9qcd4OV3wokpJycv9X2b6wOmWcxZVFRE4MxAZGZVCxZ1t72TB6AV/r99XA/8GubMyC5Y3EcEinlEwaA34tjLtyTbj0OTIArCuDIZl1nI+G0hInH7iNM2Dmtff+G/icNZhOn1tdVT2UnvhrhJOfHqjnuJqa+KaT4Z9wtM9nwZg5UqxV9aHzp3FqzGjuFg4WZeVObZVKuGdd2B16GC2Jm/FKBtxV7lTOq0UlY1z0NJTS7l18a2Wv+fcMocHOj1gPdEV4HjbftGWE7nCEcxL7UXptFIHnS/sgzByykUG2xjfGFKmpAh98s92UH7RuhbWBvM66BULldlC3tM7eVBm9FsCMbdBeSr82cbUth4XJdtruNBvM/btg969rTxRbejaFf4yLe2vvCJkwrq8ppzKCFcDDeEEnLWvcUzMRzGklQp5UCkp0b/qmOTxYuFFmsxuYvn7uibXse4e+9TeDz4oAg9suU9vb2EDMVdDtkVqqrUSuy3WroXrnRRBuNz9dsDJmWLvr20cBveG6+tOTFYvruD6/9RT8Pnn1qRkAPHxEBAAGRnW4PROnQSHPmqUqYpGOPz8s+C1dTqxlpl97Kuq4Ntv4emnr2w/ZFkm+qNoMspEYq+2IW05NumYXZtn1j7Dp/s+RW/U08sddpl0H4ZsFgGQNRPvXgmfqXr6vSdtD73m9AKEfj1j8Aye7/u8pWmFrgK/d/3QG/UoJSWjWo5iydgl7EzZyaD5gyw6l5vSDY1SQ6nWWpprxuAZTOs3jYVHFnLvH/daPl86bimjWo6y/L3xwkaGLhwKiP34ixs+5tEQf0hfKZIe+rUFn0Rhz1J5ibW3KgeMWrHWVxVA80cbZFeSZZmOX3fkWPYxZGQivSP55IZPLPvM5kub+eIvqy1p470bGZwwuLbTuYb6xqC2CJYlgK5IcK99l5iqsNRQkm3kbaBu/rXmNWxwNv8sj/35GJsubrL7/JubvmFi54kWP5WHVzzM3MNz0Rv1KCQFuf/JJdAj0NK+w1cdOJp9FIAmAU04//BepOVNQF8ukukNWCGq7tgGTYFFXiswQMgFoYmoFCruaHsHC0cvtLunLt904WCm2LxCPEPIuncxio2DxJdB3cUccQsEJKutveZzMmPQWlFZ1kWbfKO47f9i6I16Ij6MIK/CMcGtLSQkUqekEqVWNlg+B/7es71S9rGiE7C6E8g2nGroADHGkCF7KxSYhC6zfHf0Nbi00CpzSirRL02gsG0UiwDlLilw0Cb2rmxaGV4ae0HjUOYhOn8j7kkpKbmr3V12euL998OPP9rLLGb4+Aj/OB8f62d1cUeSBN99J4Ix7dDQd5G1ETYNdf6dwg1uzQKNv/i74ACs6UadsrNvKzGGzHKzs3uq7b5yd8P6PnWfH9hZCX1NOTTVCjX/6f0f3h5inwx6fdJ6rv9BCHZKSUmcXxwXiy6K5EKSgooXK+y4RFmW8ZzhSZVe7OFdIrqQX5HPpeJLALQPa8+RR49Y2uuNegJnBlKqLUUpKRnSZAjzRs4jfla8xR4b5RNFs8BmlvPvTtuNzqhDQmJY02GsHl+jlO7l1scqs+HPVqAthuaToOunjsfXWDvjnrpEWkE0Ex9UumQfs4VRNrLgyAImLp+I0cYPpUdUD765+RvahwmOxRJvUE8gSSNcOf85PPPMM9xzzz107dqVXr168c0335CSksKjjz4KwLRp00hPT2fBArEgPProo3z22Wc888wzPPTQQ+zevZs5c+ZYAkRAVBbp378/M2fOZOTIkSxbtowNGzawY8cOl68rSRKTJ09mxowZJCYmkpiYyIwZM/D09OSuu0R2UD8/PyZOnMjUqVMJCgoiMDCQZ599lnbt2jF0aC2LQ12ocr1s2v9buOj0aTAY2LhxI+TlMSQ0FKULnpOWY4AhQ4a4dEyD4REFnjGCUE/5FSJvcBQSa4MmsN4mjenDVen3NVxVdAzvyK6Ju/7Zm4iNFZaCPBuhuj6H/AY6UF+DaygpsRJJdWUIM2PcOIiMhGefFXLS+PEwbJggacPDrcZ2g0GQ7YcOiVf9SF2JgGrBH3f8wfULr2f9hfWAEACbBDRhe8p2y99HHz3qEEQC0D2qO0cfO4rRaEThJPWeJElM6jqJyWsnA3Am/wyP//k4/u7+AFwoumAJ5jDIBh7t8uhVCT701njz5qA3eXb9s3W26xfbr+FBJAAHngZk8G0J7d8Qn9llwauFeKt0wYJ0GRHrF8snwz+5vCe9ku/PM05kmM5YDcffhOAeorSrjFD8vWKFgmyulFORIYIrfBIhpNeVuSfgP/8RTtmLFsG778Izzwjivm1boRx7eAgFurJSLMHZ2TBvnmtlhsFGRig9y5CqdSglgyAmu8yGpg9YZRjZAF5xGFZ3Z2OeIA+HGIxOK/M6IHszlJwSv3f93NHoXs+49QnszLtD32Vip4k8svIRfN18+eqmrwj3DrfvAxDrHUtKmXCyfH3b67y+zXn1wAc7PsjmjZtZuBAMhiGAkg8/FM+3prEqLEw4Pb/0kngHkgRz5ojnX5fTT6MclxoAc7/76fuxTBYBewbZwL70fQyMH2hptyNlByqFCr1Rjwce5O7I5Zsd33D//fej0WjqvIZWq2XevHkA3H///Vx46gKPrHyEuYfnUqItoURbAkCHsA6sHb+WYI9g1q0TximLzCkpwC1I/JhhG3jVaAwT5HnuDshcJxxBUIiMOrZZCmU9VBdBYCfIWAv6EsAICfdBz+8dDay+1uqAUSq4pckAlibVXQkp3CucG1vfAdwhHDOyNsDFecKopXQDjzBBpkkKMf5lHVSmg1skxN/ZoF57qD14rOtjvLX9rTrbSUi82O/FBp0bxN56W6vb+Pyvz9Eb9ZzOO01RVZFlbwXYkrzFYjBpE9KGtOMJrFwpvhs3TlQeMdu5zXPEvI0nJoqguBEjhNFLoYAlS4RjgLmN7bBs21YEFjQGDzwg1kZZhsmT4eOPxTVt0aKFcOL74w/R7rHHrIbRyEjhaDV6tPU4tRoWLxbGOYCCAnjO3teMRx+FqVNFUEdKilhXtm0z0Lr1Rtatg6lThyBJSmRZrOFvvSXuz9z/jAyYMMFASMhGNmwQc6l794bobzfQI6oHe9P31tpCQmLpuKXOHejrwY2JN/LODmtCkD1pe+wCSfakWbNd6416bmx+I0/eKQykGo0wNPfqZZVXbeXWmBiYaR8zeMXx8Q0fM779eG76+SayyrIspOWCUQu4p8M9V/dmruGqos7xn7cHUpeI36NHQr/frd9ZjN6XkVe5+EOdQSSgoInSgDnvrNagpUxbho+bj12rnPIcO4fQWL8rq3sXFYm5HR3tmh4a4xdj+d0oG8mtyHVoY5SNFFUVWf6O9Y0Vi6mZdzh1yvHENT+7xjv869Avrh/HHz/Oy5te5v1d1mjBlXeu5MbmjXMOsdUB7ml7D98f/d7ynWSSBW3nQzO/ZshJMuuS1v3ruNFAj0DGthnLz8d/Rm/Us+j4ImJ8Yyw8yY7UHUiIzOJG2WjvxHilcPg54aTiEQFdPhVy7GXmHVoFt2LDhQ0WuTKlOIV27u3s2lwqvmRx4FdUhPLjd0EYjfDEEyKIBJzrXY3WxfY/KfoZ1M15EEmNfj88+Bs8NJVM/uU72rTR8PzzcOON0KqV8zXRTJmCkFNdgSRJ3N7qdj7767Pa5fNL9vJ5zSASALVSTcuQlg6f/9tRXS34SEmq20m0MegZ3dOiKwMcyT7i0OZAxgHL9zG+MfZBJFcAzZqJqoynT4sgcze3+vfX1FSYNk38Hh2NpdKN+TiznuHtLTimIUMEd7l03FJGLRplOY+/mz96WU+ZVjgUKyUl2ydsF8EdAMffFlwYRhGs0eZF8SMphdOMTYWiPh7WIBIJiWM5x+wCSYyy0eIsLSHRJ6aPuE5VDhyZ5thJn2ZiAJQlWT8zVkHmekj+yfpZYFfotRD8bMb66VlwcLL1mLw9cGYW9TpCgyWbLwkTRBAJOPJZxVY5ZIin9awqhYoDmQfsAklKqkssQSQqhYphTa9cwK8FiY/BqfdExYq4O8E7wZRN09SPxEcg2uRtU5mJsjqfMcNbMSbIHVkW+umZM3D8uAgeqa4Wcp+bm/jx9obb+7VlwbrmnC04i0E2sD5pvV0gybbkbZY9WW/Uc2fbhvEg/69xZpbYj5UaGLpNOKtJkph3YHVkKT2HQVZaONs4r2Mkl2fVeep+Mf24dOASl7h0xWWjjuEdaR4oxghAua6ccl25QzuNpKF5UXPWrVtH//5DePxxpd3636ULTJgguIOjRwU3k55uoFUrwbeY+/HZZ2INdQaDQfBQd3xyM1uTRfblKn0VJ3JO0CG8g6Xd3vS9lj1CiZKA9ADW5bomRzbWJt89qjtn8s+gN+op15WTW5FLqFeo5fsKXYUliEQhKege1V18cWaWaX00PSiVN8TfLaonaYvg/HdQdFh8Z6wSY8YrFs5/BYZaHpQZ578XgSSHXzC1NV1DEwDxd4FfOyhPhgvfW31gbK/hIsxV22zh7Q233ire9+HDsGaNeH9m7j4pSQRO/vek3hVozPjQarWMqhhFNdXMYx46WYdRNjrYVasNwmNTiZLBDCaxMBGDwWC5hizDr786OmSWlcHGjc6dLxcvdpTDVCoR1OA0kORKwqCFk+9R5x5uquT6b8SxY4JrtuWe5861f46ffCL0HFkWnDJAUJCQ76JNYmhNXcfT00kQyRWAJEnc2upWvjrwFXqjnpN5JymtLrXjprYmb7XIzt0DIgCTfhjQ0T6IpD644DPVWPSI6kGEdwSZZeLeNl3cZBdIsjt1t6UPBtnA2DYi2XSf2D5cfPoiA+cP5HzBeaoN1ZY556HyYPXdqxkQPwCAUS1HWZIVqRVqNl7YaB9IcnGjZY+RJInb2t4FXiHQxJQQzmgQ9iN9uRjTKm8hAyg0oBgKbqHg5t+gfkuSxJPdn+ShFQ8BkFGWwdglY522DfcKZ1D8oAadv1E4/qaw16l8oOc8UwWWWoIdLgOaBzVnwz0bWHJyCU+tfop2Ye346bafCPYMtmv3WNfH+PagMAAZZSM3/XQTCQEicVaFrsISRALwRLcnkM59Kd6VpIAhm4T/Bjj6B5r+DlRCfw/YViWhN+odAlvKteUcyRK6qUqh4rbWt6E48baQ/7zixDUU7lZ5sC4k3AsRNRbrf5Evyb8BKoWK5Xcsp/f3vetsN63vNKJ8o4RMZJbPr9sOHpG1yuf/asgy/DUJS3IF9zCRUCVunKkiL3Y6PsYq4e9xcZ71HP7toNcCscabcfI9OPw8QTWGZ6m21CGQxDYQTyEp7HiuCxdg4UL7wEtblJcLWeThh62fvfSS4D+cHSPLYs91CCSpBbXKaydnmjgQx8hng8HAxj/mgH87hgwejHLfY6ZqFnVESZecEvPRNgjbFcgy/FXj/GGDodMH4jzVuXDoOUhfQXsbnyGjbCSpMMnhdEmFSRbu2SAb6B7VnZSSFPRGPUbZyNn8s3Z24JTiFEsQiVqhpn9cf0I8Q3hp00vIyBzNPspHuz+yvNOz+Wct79sgG3i488NE+ETQN6Yvmy6JNTC9NJ300nTHriLzVI+nHD6/7MjbKRKjArR1ksDJydpZWB6AUVYSE+OafcwWCknB/R3v55YWtzD+9/H8lfEXM4bMYGKniU59J+vDf1Ugybhx48jPz+eNN94gMzOTtm3bsmrVKuLi4gBR4SMlJcXSPiEhgVWrVjFlyhQ+//xzIiMjmT17NrfddpulTe/evfnll194+eWXeeWVV2jatCmLFi2iR48eLl8X4LnnnqOyspJJkyZRWFhIjx49WLduHT42YWsff/wxKpWKsWPHUllZyZAhQ5g3b17jSBVNQMOPuQanMBgMlgo1AwcOdDmgoqHHNBhKNxi2FzYPtxInraZCSD8hHNZ0RK3MhOKTENLXJUfUf22/r+H/J2Jjrzlo/Avw0EPw4YciC+zEicJYWJfR3GgUmbD37oX8fJHpZ+9eWL9eEOxVVVaDkKeniAnq108c5ySeo16svns1I38ZyZ/n/rQTAKN8ojjw8AECPesmhJwFkZhxd/u7LYEkAF8f+NoiWBlshHKVQsX1Ta8eqzm191TWX1jP2qS1gDCWtAxuyS/HRWnMcO9wVt29qq5T1I68XUIhiLvD8bvqPOeKP1hLz1+DcyiU0H85nHhLOKSvaG4iWIZBUA8RXOEVK8g6faXINFGZfkWDSMxISIAXXhA/IJxPSkrEXK2sFMS9h4co+mTODugq7GSEpkoRSNJzvrVCg5noMhEgBlnB7iJh/B9odDGQRGclAnAPtTe61wcbwjgxKJFN921yaGLbh7Hdx/LBvg/qPe1DnR/i+9nf06wZwEAmTFBaiPmaYpIkiZ9jx8T/Awb8O5Ku2PZbiRIDBhQoWHR8Ed4ab0u7NefXCEIaiaHxQ8m+JIx6Wq3WpUCSTFMVIK1Wi7e3N3NumUOMbwxvbBOBbNc3vZ7fxv6Gt8YbrVZ7dWVO91CIuVX81IfKTFgaBcgiO2nPOfYOcWbUIHd/uv4twr8fYcmO2MS/Cf7u/hzMEtmAzA75FnjFiazNVxBvDn6T7w59ZynN7KHywM/dj+yybItzxqRukxrt5DSq5Shm7Z0FCIJmwZEF9IkR875cV86xbJFpTIGC21rdxpdfinUoIABMuSFqLYGsUsHFi7Btm/j7hRfsg0hqQqms/Vx1ITlZGEBBBMt+bEp4X1M+Mg/RUaNEMMlOU8K60FARSBsQ4HjcrbfCIJMd5eOPrU6A/v4ikG+kTYEbPz/YsAFmzDBgMOxm9244c2YgRqOSwEAhg8XH2/c/LAxWrDDwzjuifWPm0oZ7N9Dxq44WQnBqr6l8c+AbC1E3f9R8WoW0qusUtaJndE983XwpqS5BpVCxO203D3V5yPL97tTdqBVqdEYd7kp3wioGsX+/+O7tt+2DSGqiMe/6cqBLZBdOTDpBv7n9yCvPY/296y3ZXq7h/ynOfy0CANU+0NvknHgFDZlcmIcIgqzNGcJIrFSGWqFCZzLkZJdnOwSSZJVnWYzdYB+4cSVwzz2iKtOcOcLJNzCwbj00yifKziBh3sdsUVhZaMnApJAUdDWE1V8Jdfx4+7+vVUL9V0Kj1PDede/RL7Yf65LWMa3vNCJ9Ixt9PltZ+PPnP2fdxXWWDL1tQtoQ7hPOhgsbxLUVGv4Y9wdLvhEBYv9GbvTm5jfz47EfAagyVPHuznctATF6o94i48X6xgrD9ZVGxmrBOzSZ4Ojwc5l4h5bBLe0qyaQUp9gZJQEuFF6w/O57+GVKdRLu7vDqqy5fpmEoOir6HXmjqEBl23cn/ZYkuLffQu565gZ2ZtzF1q2iMkRGhli2lEoh52m1Qk8PCBBZhLdsEdmIO3QQWf5rMzaajd+jWo7ik72fAEI+n3toLr1jhJNDua6cYzlW+fz21rdf5ofyz+LHH+0L05qDIe6+W9jNFy6ED8wUgG3gIdQbfOgJdA5sy768wxhkA/sz9ts1NTvIgeAVhyQMuUy9qh2ffCJ0mbVr4brrRGXGdu2sjrO2jpzmqrQ/iqUDSYKlS+vmhZVKK58xsuVI5o2cx/3L7gcgxCvEzkF5832baRPaRjQuT4HTHwJGIRMNXA1hA63yUQ29uoe7pX4bKoXKokOakVyUbHE6UEgK+sX2E1+c+dRU/c2EoB7Qc66o5AmQvBh2jrN+f/oDqxNHwr2ibc2KosE1eLsL80zHmGSmgM7Q6T3RH12pyLB6dra1vaSCDm86r6xbw4kgUQ3hSsgygMFo4ECGTYkERMZVM/RGPUObNCJZYUPRaaYIxDn6KqzuCPHjRSKd0P6g8RMBgx4RwllI7QcF+y3ZrSUJoqLET92QuDPzTl7fKpK57ErbRdsv2lo4+ozSDEtLT5Xn1en3/wK0xWJOyAZo8rDgpesYgwZZbeFsF984gl5/TsVocgxLDEyk2lBNSrHwxXBTurH41sV8NUuUf70astGi2xfR6ZtOdbZ5vtfz7Nu1D4D09IGkpFjvafJkYQMzV7wdMUI4Tt92m4HERCt/olAo+fbb2p3OQJxjROIInlknyGAJiT1pe+wCSXam7LToVu1C2nH0gHAadeVZNdYm3ym8E/MOz7P8fb7gvF0gSVKB1elLQqJzRGfQVwiHNrMu6ZUgshr7NDOthyYetGaGctkI5791XDNroiwJcrZD8s/WawR0EtdwCzatpQqRSX59n7rOVCc2brSvKtOzJ/z5p5Cd9Hrxzo8dExyfGe+9Z+8smJAgKpSMGCHsnl9+KSo//NvQmPGh1WoJNghHZzVqdOjQGrSWyj6WdqbkKAoU9KEPFGIXSHL+vLAr1YRKJWzEzgJJ9jrJU6PXWznUq4qMlSK5W13QlYr1sSHOmFcJL7wgZDG9XugEy5YJu54tnnxScOV33SWCpUAkWYqOvvKJy1zBLS1u4bO/PgOEM+qy08voFyfkuEp9JYczDwNiDEbHjYTCeWCshgtzocXT9vuYM58pbRF4N7midldJkhjXZhyz983GKBvZeHEjT6x6wiK37EnbY+Gu1Ao1IxJHWI6N8o1i5wM7GThvIKfyhF6hVqjZeO9GesVY79nHzYfB8YNZk7QGnVHHl/u/5PfT1iQ1ueW5lj2mR1QPQrxC7G/SnNzwMuP+jvcz6c9J9VZ0faTrI41KQNVgXPxB7ENNHxAZ/OuRtQHIA/ZtB/P22MCEM5IkMabNGMa0GVPrbXWK6IS3xtsSYL8nbQ/70oV8Yqyxb97RaiRs6AoYIe4u4VhfE0545DHesKVS7KsZpRl8vu9zgjxFMr7j2cctPi56o577YzvAMSGz0foFU0CR0vEaznjquDsc9ZhrviQO6BXTiwWjF3DvUlFJKNInkm6R3Vh2RiRxfKDjA6KCg7YYznxmks8fEQnGXRm38O8L0klfCbkmQ61bEAw/LGQ7qD1J+ukPrfp37Bjo/SN2iR0BQgcCEKSwcgKAZT7ZouZnAe5Wf+off6zbXmg0in3UHEhy8qSQFetCuWMce61wKq+VXYKs9bUfI0vsPlUG7GZgaxVKczUXWyjdRSCS7VrSiCBs0ldAkSkZiqQUyYdbvwDI4m9NILSbDukr8FFAjApS9cJ/zrx/2eJ8wXlUCpVlf7ih2Q38cuIXy/cnc0/acbYnc62VknVGHT2je9I7pjcvbrImuJy6bqrTW1dKSkvCjfmj5xP7cWyd1XKbBjRleOLweh/J34ZtcJ6st5Z+qwPj+/zAVxsfZc4cBY8+KvwEGiqvBXoENt5v0Ab/VYEkAJMmTWJSzVQCJpiz3NpiwIABHKynzuTtt9/O7bfXTYzXdV0QgsL06dOZPn16rW3c3d359NNP+bSxqVBtEdz975/jGv798IiA4QetGZH2TLBmQtb4mUoQVoqS0kVHwb8jtP7PP33X1/D/HQ00tgHXMn3+S/Dee4IYnTcP+vSBl18WvjRmAspsaDQ7Kaaniyw+IDKZDB8ufq4UlAolv9z+C73n9LYYtz1UHqy7Zx1h3mF/69zBnsHE+8VbyuQZZINdAIkZ/WP7WzPoXSX8OuZXWn3eivTSdA5nHbYYahSSgj/v+tPO0bthMAvSTpzN3IJFFgpnCqp3k0Ze7/8RFEpo9xq0ngY5WyBvryCyDr8oIvdlWTx2tR/4tYbAbkJZdiXrx2WEv7/4ufyQhUE59rb6mzYE/u2x0AUpS0zOSDbP7DISxq8NeI1P9n9i50RZE/1i+xHmZV17VCrheFKfPmiu/hQUVHubfwqxvrGcLzmPESNfHfiKrw585dBGRqZLZBe49PeuJUkSrw96nXj/eFKLU5nWbxpq5b/AilEfUn6z/t5jjnU+1wN3lTvr7llHz+96IiNTVF0kMvmafF/fv+59esb0vDL3XAe2T9hOq89boTfq0Rv1TO01lf+sF/pE7+jefDq88bpr39i+qCQVepNjzdNrnKc0M2KkZ9CNzFgiDGATJlid5erCTz9ZHeWeeab+9o0JYl282GpM/vpr1zKBLFok2hgMwik6IMA54WMOmqmoEIEkZoP13LkiA7UtzNf8z39ERSOwrjPffCMqTNW8L/M9/B14a7xZdscyOn3dyWKsqtCJLJOPdX3sb1XaUCqUDIwbyPKzy9Eb9Sw8utCSxRMgrSTNQjZ2j+rOD/PdUKnEc3vkkfrfwz8VTBLoEciJSSf+mYtfw78L2iJI/kWQxQn3CHL/ShqEypNFtqN6ECsX29kXcspzLKW+zcgstV7fR+PzN/QN1zBrlnDu/f136NsX3nxTVNJTqcTaaF7LzGtpcaGaIM8g8iryHO7XDLMDKwijQqT3la0meQ1XHze3uNkuO/vlgEKhYON9G2n7RVt0Rh1JhUl4qK0eOd/d8h2JQYmX9ZqXG2Naj+GepfdY9tDa9Jn7O95/dW7InMlX6cmV4h1aBlsrBkhIJBcn230vyzLpJemW7zXZvTAYhHN9SA0/m8sGhSnQ3lCJg7JQR79V/gkMSBRJB+qDLAtnsFdfhY4d4Y47RKBy586CqzPLvtnZIvv20aMwZWofO/nc7PhaE0aMV6fCwVXEZ59Z5XofH5EEp0sXa+XDV18VY+KjySn1Bx6CQ/DhkOuVHOyjRC8bOF9wnip9lcUp81z+OYtDpt6ot2QYvpLw8IAVK4Q+8/nn0L49NG8u9IyoKBGoLsuCn0hJEUH6p06J5zNwIHTtWv81bOXx+zrex9bkrcw9PJdzBdaMqTMGz7A4BQKQ9oc1y2WLKRA2qE7B3VsB7TRwRCucCmpWezHzwyC43L6xfUXClnNf2GfTHLDSOi8BvOLtL1RyWvzv0wy6f+1Ssgiy1lmvEdJPOEMrNCZnC39IGG8fSOIRKX5qopbgshs8YWGphAGZ3Wm77QJnt1zaYnFMBBicMNjxvFcCzR6CJg8ImTN7C6QshmPToTJDBMpgFP33bSEczs3ViRsASzCQCeaKMzURHxD/38Eh/RuQtwsMJm+nmlWyoE4nwI6+QXw47EOmrJ0CiKQo5wqtc/z3cb8T4Hl1E192jOjI872fZ+YuUYa0f2x/esf05t2dgizpGdWTF/u9aPl+5kxr8NyUKfDRR+I85n1SpRJJ0JYtE/YxM06fFgF5dUGWRVbyUM9QcipEVcdXNr/C/CPzxffI7E2zes9f3+R6cCymeNnRKaKTnRPVufxzlsBRwG6dNsgGOoV3Es7ZZqdP9zC44S9RZd3ZemiLrI0iSVZ9KD0DGwZasx37d4Drd4JkyhovmdZo27W6EXjvPSsfNnCgqD5iTi5j1idbtoT9+wX/WFoqktmYK2u0aAHbt1udt0JCYPZsIV/9G4NJLgeq9dUOgSTV+uo6j9mzx/nndQWG7NnjPDDr/HnBjXp6unK3lwnnvqo1C7gFpWcal9n7CiM5GVaZfAQDAgQP7eXlnBeOjRUyn5mDvv32f0cQCcCA+AEoJaXFDn/PH845ZiNGurW4A1QjYNtIOPy8eG8tnhbB+katWDe8YsEzWnwX2Bl0JWINu8LoHtXdEhBgkA18feBrp4kcInwiHLi1UK9Qtk/YTugHoRhlI7sn7hZ2txroGN6RNUlrLNewDay1RfvQq5fMSKVQMbHzRL7ab7UfKiQFsixb+uyudOfV/lcqc0MN6E1JCN3DXbO15wHPArrJdbe7DAlnxrUZx5xDcwAsCXFqoklAEyIqz1sz2Ld8xrEftfDIN3rB4zayxROrn3B6HwpJQVc5W5xT6S6q1tRM9lEXV+1svbzmS+IU97S/h62XtjLn0BwySjMsQSQtg1vy2QgRQEfuThv5/EnHk1yuIJ2r4beX/IvQBWU9dP/WNC7q0QGLTHq8Z6xI4iApa9W//ZWinrurgSQG2WBXkeS33+q3k9omHfntt/ptq387bj5zNXUnA7NB0nfW5wvg2wq6fgrhQ0QFo4NTRTKzxuL4W1h8b1o9K4JIbN9FDb6mixukGxQYZaNd0h4zzhect3DRPhofbm5u5e5VCpWDfn8i9wQKSWHZS3tF9yLaN5oQzxCnVeht0TG8Ixql0B2ifaN5qvtTzNonklvG+cUxqdsknt8gKoUpJSU/3/5z/c/jciB0gJBJKjPF++nzs73zkBN/ptldC8l4uohlawLp21ckUxw92joWzX6aZjmuoEAkY7sS+K8LJLmG/xFcczR3HZICIoeJHxBEeOl54Yhq1AoBT+0Pvs1FYMk1XMM/iZTGGduuZfr8d0ChsJbi+/hjePxxeOIJaNVKGKX9/QURmJoqsvqEhkI9sZqXHd4ab1bfvZroj0V29GV3LKN1SOvLcu5nez9bq4JtxszrZl6WazUEPm4+LBi9gCELRMbCgkqRKefFvi+KbFGNRWB3yNkMqUug7Uv23/1DGVz+56DUiFKvNcu9/n9AhxnOsyz+nazbfi1FgM6x6XBwishs6N8OkOyVLzOxbzQ0rGqJDTQqDW8NeosXNoryLS2DWvLO0HcYvWg0ILIDzR81364U+8CBriltsbFC8Tt+vPEVmq4UOoR34HzJ+XrbjWg2glW7/n5WA4AJnSZclvNcNSSbMmf4tbFmM7VFHeO8e1R3Hu36KF/u/5KCygJWnRPPsHVI66tTTtUJmgU244U+L/DW9rfQGXXM2D4DEMTylzd9+bcyRqkUKmL9YrlQ5Egm2UIhKTCmdrUYbe+/37V58fPPgjwZPvzKOQH++KOYp926iWCN+mA0CiO1wQBDhsBNN9XdXqWCHTusGWxGjBBVTWqD7euQZVHRxKbg6hVBm9A2vH/d+0xeO9kSRNI0oCkfXF9/1ab6EO1nrXajN+qdEo8gSMDffhNy6O23C+e/a7iGfz3y9ohsieC8wtTlztp26Sfs83M5R6wKbN3KbQMuzLB1VIzxvbLVSEDIRUuWiEyxH34Id94pAsY6dxZZ9n19xfqamiocfjw8IPahWEsgiTOjgu1nBtmAT2IbwTnYcpGZmaJEHwhlN6JGsMn/Vx7y/zmaBzXn1QGv8srmV6jUV/JXhsj6NjB+IOPbj0enqzvj5j8NhULB8GbDWX52ee1tJAUv9nux1u8vK7ybCgNx7jZQXBnewbY6mkqhsiTfMCO/Mp9qQ7Xle41BRPR7X8kYuehRcHE+JM0xGWG96zQYNqbfkiSqkTz4oKiIt2kTvPWWyJ6o14vqwDqdWD8TE0WQBEYVcf5xlmpztUEhKegR1aMxPf9X4tAh8WPGihX2QSQg9qKePWH6k3lwfz28thP0v2DgHZOPrlE2cv8f9xPiKZSUswVn7dvG9W/w+RsDtVpUXLn7bmFkPnlS/CQlCSdESRJ7atu20L27la6/7z4xdhrqaPjZiM/Yk7bHkpVyeLPh/KdPjaRnGWsASWQqbf+6S9HfAz3hhE4E6RzKPMSRrCMWPXXDhQ0oUGDEiAIF3aK6Qerv1izjmkDo/4fg52wdsRwcW0xOHJ0+cD3Jizky1zMaBq8VTtC2HFTN88i17B+1OGB1dIN5pYJ0yq/MJ+JD50GxwR7BBHsGu3bPlwMKpahCEnplxvGQJkNwV7lbKs3Uhoc7P3xFrv8/CbNTIoBHVN1BAU7wRPcn+Pbgt5zMPcnaC2stn49sMZIRiSPQarWX605dxmsDX2PhsYVklGawLWWbZZ2VkPjm5m/sKtNfuCD4k5gYmDHD+fmUSuw4XoDly+2rVDiD8AeSCPcOJ6dC6FW5Fbm1Oj0lBCSQTbbrHW0kOoR1sMuCbxs4AiKwxNaBu1NEJ9g9A4szW6cPRAIsVwLBLi60d26rE0bTJSTo8Y0IIql5jQaOT1tkZYlAURAV3L7/Xuz1NZ39zAEizzwjktRUm9R2f39R+TggwCojmIfSfff9uzj8ywmznFzfZ7bYs0c8R2eq0V9/OSbiKSwU+rwzyLJQ1TvVXWjo8qEqF7I24JLzZmMye19hbNli/f3ll4U9qjaHVrVaBJPr9TB27L9rDGuUGiJ9IkktqWVgmCAh0Se2j1grrt8Fh56HQ/+Bk+9D1I0Q0AF8moPCDfRlQvcsPAyVaXD97ivejzFtxjB+6XiLA2xtiRxGthjp9PMgzyAMr9bt4Tyt7zRLsGRdeHXAVQraMOHT4Z+y6twqi/69+u7VTF4z2aILLLx1od1+fEXhFgwVqSIATKqhxDjTvy+eB8VzwJWXYd4b+p4lkKQ2vNj3RajOt37g09RRl6iFR45Tg6dSQ4Wh7r7E+8Wj1BUDCnALdR64WRdXff5bUTXMFtd8SWrFrBtmseXSFgv3opSU/DrmV2uyGl2RtXEj5HOXcDX89mQjZK4RcmDoAIgZ7eLNmfTvju+YkjHU3n//Gl/VF0hilI2WQJLUVDhyxKG5A2z30UWL6g88+bsJ/MhoQCBJ+kos1hzPGBi6RfAcIPyDmz7Y+EASbbGoJIoszt3ujXrHYkc3WFkhYUQ894LKAgI9rM4xZ/LOWAIKO4R1INAzkKYBTUkqTMIoG+0qkICoSGIOJAnxDCHaV9iMJ3aaaLf3mYM0bYPla+57M6+byW+nfyOtJI3k4mS7iimTe06mW2Q315/N34HGH/othXW9IeVX8Z46vQ+agFoDYFXlqSxdFciyZcI+NmaM0Em6dLHaxwwGSEsTsrabm/j/SuBaIMk1XH1cczT/e1C6gX+bf/ouruEaruF/GP36iR+dTiy7hw6JzHRVVYJAjYuDxx4Tjj3/BKJ8oyh8vhCj0Uig5+ULtX2s62O8u/Nd0krSAJg5dCYpxSl8+deXgMis3jXShZR8VwCDEwbzSJdH+PqAUARaBbfilQGv/L2Tdp0Fq9oLYu3EO9D2ZXvHf1uHfACjzjE7xTVcgzP4tgSvGk6HDplMbMZSZRYuo82LUHJGVGpb2wMSHxFKsl8be+XWoIX8vcKBoMvHjerG5J6T+XD3h+RW5HI6/zQ7UnYAQll9qMtDJAQkkJFhJedGjXLN2WLqVGGkOnMGvvtOBO+proRWVl/gtvlvvZXcfqr7U/x29jfqgpfai1YhrVjF5Qkk+a+CrlRkckSG2LGO2TVdyC4/Y8gMFp9YTH6llRj+7ubv/tFMmtP6TWPu4bmkl6ZTWCUcDB7v9jjtw/5+FqvbW9/Oe7veq7NN29C2lJRY529UlGvVJLJNtvfu3Rvn6FQfioqsJOPYsa5d4/Bhq0/yHXe4dsz27dasIm+/Laakq2vC5MkNa99YPNnjSZafXc6mi5sA+OX2X/BU//1Ugc/0fIYv/vqi3nZP9XiKFSZfsNatQasVTgH14loCi2v4J2EbDOIZd2UMQrZI+4P6gkgAYmusSc4CSWz3qCYBVyeDnCSJ4LubboLiYrH+mvXQnByxzkVGwksvieC+aYcSOJx9GKNspKCyAFmW7YIfbftllI0iICY29tr8vgaX8Fyf51h4dCFn84VTolqh5tubv/1bAbZXE7OGz+LPc39anAN/G/sbn+37LWohpwABAABJREFUzJLBflLXSbip3K7OzXR8B7aMgMx1wvgZMdyxqqQt71AzGYELCPYMxs/Nj+LqYoyy0SGQxPZvnVFHeJhExkmR/fiKodN7QhetyoHd90Gfn4QjiJlTuQz9NsPTE+66S/yAcHgtKxPyklotMhTbyopjWo+p1xGpfVj7q+f0cxWwdKl4Bno93Hxz7RVfVCpoPyhY2KHqs13VQLc8DbaOSEtOLkFheqe2WWcVkoIE/4QG9+HvIjBQVP3q29f598uWWX+/4YbG6Vaeak+WjltKy89FlaCFoxdangEgeJqczYARom4xVSqqgfIUh6QMTVWgNz3DCn0FHb/u6PT6wZ7BQkfJ3mx1am77Eig9XAgOkcAjAqKdOPnVmizC5MDQdrq4Xn2JTCozRaBxYFd7HsHWAcvsfAX0q9TCrw/Uc98Q5+9CxoP/MgxNGMrKcytr/V5C4rGuj13FO/ovh8omclJXCuoamRnqzCYdj0qh4tubv6XP930sH7sr3Zk9fLZj+6sED7UHH1z3AXf9LjY/cyD8g50fpF1YO6fBLS+8UDd3UvO733+vO4jEFre1vo2jOUfrbTe+3Xg+XPOhayf9G/Bx8yHOP45LRZcwykbHQJKCc0KulSHII4hwz2DI3y++9G0B8Xe5JpfIRshY5WIQiQ2iboSg7g07xgXstRZ/4YEHhB2zNnFGrYZhw8SPGc8+KyqIO3PKVyisstb/GrROnI+dfWaLHTucB5GAqC5y8SI0syl8WldCQoVCUHNXLZAkcx0uOW7+S7F5s1ivPDxEIsj6OOGSEvF/dLRrlbavJka2GMlnf31WZ5vmQc1RmeWm4J5w3VYoPg05W6HgACR9D9UFImBXoRGOsEHdIe5O++zfVwgqhYr2Ye05nHXY8plSUiIjW4JLQASDNBa+7r4kBiY6rOW2iPKJItLXSeW7KwiVQsXL/V7m4ZUiuPfTvZ9anHYTAxO5tdWtV+9mWk4RWd8v/iBsyF4JjvK2rf4dBZwdbW83gCuScCbQM5CnezzNp3s/BYSsMiB+AHf/fjcAbUPaMqHjBEi3UcgM1XYmdKBOeW1AVBdWp9QdODW2zVirkqd3dMSv7xqkLxfBown31O1L8je4jf8leGm8+HXMr3T+RjhTzR4+m7ahba0N/pZ87iJXn5fXYF4DEMfk5bk21ouOWZM4xN3p3JfIiY4PEriHCJmzHvgr7Hft2gJJbKtamANJli+3ViasC+bAkKQkOOG8IOblg0FrCmh1UdEwVoncYQo1DForghFs17e/M9/M/g4Abaa5dK4OblZ+BkQFku5RQq6XZZlLxZcAwaWbEyJ3iuhkCSRZeXYl3b61BnSczDlpCcLsGNbRwr2/0v8VPt33KeU6kYXx6R5Pk1Oew0/HfwIg3j+eW1rcYndvbio33h3yLuOXCl/zn4+JCiTeGu+rl1DJjKCucMN++OtRkWQoZYmoIhPcW/g0KT1E9bTCA5CzC/RFSMP2MWqU8DfKzxf+Bmb7WGGhtcLc1KnCL+JKiTnXAkmu4Rqu4Rqu4fIhNtYxyydcy/T5Xwq1WmSla9u2/rZXG7YlCS8XFAoFz/R8hqnrpiJJEqfzTnMy9yRGkyD/XJ/nLvs1G4L3r3vfEkiycPRCS6m+RsOvNbR7HY6+DEdfgdJz0OlDcA8WztFmkkuhFlJo/gEI6fk3e3EN/7PQV1p/j7jBsexunVm3i12/jkIFfX4UZNWRF+HMbPGjCRGGLqUadOVQfEKUhQ1wLAXtKtxUbjzb+1lL2cv5R+YDItPcs72eBaC01No+JsY1Z4tOnWDCBJg/Xyh7oaG1B6E02jnelcBtc9C2Wi28MoGeROGmdKsz69jVyp76r4S2EAupEtjJ5axA4tgiQOxfs4fPthDFD3Z+kF4x/2x2Hk+1J58O/5RbFwty30fjwxuD3rgs557aa2q9gSTj241HYxNP5mqib/Pw9vConwhsDMyiK4jgBVfm4vr11oyVN97o2jHbton2TZuKCnCuQqEQFUmudBAJCIe3BaMW0OrzVtzS4pbLFljbNLAp3hpvp+SvGRqlhh7RPSwxby73t7EJLNzcRP3qiIhrgSfX8Pdg60xoQ65bcDkMQmboyoQBvSbUfqD2FVn5TIixmUMqhYrsMvuMuJW6Skv1IbVCTazf1R/ffn7Qv7/4qQ0xSTEoJSVG2YhBNlBUVUSAR4Dl+5zyHEsWXoAYvytfWeUa/negUWqYO3KuxWHyjUFv0CywWT1H/XsQ7x/P7a1v59eTvyLLMhklGexL32eZDw4VAq4kIoeLrJXpq2DnHdDta0i42zEg26gXBkt9uaMB3QW0Cm7FnvQ9GGSDQ4WzmoElt47Vsn+jMMht3Qp9+lwBecotCPr9CttuEw4Xq9pB29cg6mbQ+Nm3LT4BGWuh1TOX5dIKhchUVxum9p5abyDJve3vvSz38m/BgQNWx4BXXqnbiU4fGYuqEdx2UHAwHgtbUmniRgyywS6AxIwY35h/ZVBamY047vU3it63CG5B5UviGbir3O2/zN8DBpPcE3G9iTeqPzFDHw/Xrm3Z6/P3CqdmlQ80e9S1jPoYhVG/JupKFgHgHg5N7nPxGgqRQXvoVkcHKwcHLAOdJSVqxSPojHUryDWdJ/4XMGPIDLtAksW3L2bOoTmsvyBKDdzZ9k40qr/Ji/9/gn97LBlvLy2EllNrD2YCKEmDJFMZp2BRnap3TG8e6PQA3x/6HoDXB73+j+gJtrij7R18vOdjS/U4T7Unbw5606GdSiUSUTz4oOv7fXFxwzK8PtHtCV7b8lqdbWL9Yq/quO0S3oXkomQMsoEtl7bw5lbrs1mftN7qsBXeEYqOWte55k+a1mcXnNLKkkCbb/+ZZzR0/gTcw+Doq6YAwhpo+ayjLHgZsHeveMcGAzzngilPpxMygiyLSnVTpvy7nOyvFqr1TiqSOPnMjMrK+p0sjx+3DyTZv9+aRKcmJElUTLtqyFpvX0VHUkL7N6H5E1CVDdtvFY6x/1KsXy+Co/v2dS3Jjlot3tk/UDyqXkztPbXeQJJxbcY5fujXUvz8S/B0j6eZsGwCIIJI7mx3J0ezjnIsR4yjlsEtifBxXlnOVbw79F1uWyzKkgd5BLH5vs3c+NONlooubw1662+dv7G4t8O9vLL5FbLLs1l9frXl81f6v2IfUH6lkfg4nPlUyO7bb4dBa8AtxPk+Y7ZdX8VkM5O6TWLW3lkALDuzjDJtmYWzfKrHUyKJg0+i9YD0lZAw3t4hv47qH8+UlLP6h+ssTdUKNTKyXYWcqb2nQt5WEXRVnQs5O0RwlgsB7qT9AalLYPe9Ioir3XRTJn3ZKjNICmE/TV4sEkBeA50iOjF35FwuFV1yDIIP6IClsvjFBdDq2brl88ZUewluXJIM3N3Fsa4gcx2WfkTd6DyIxKk+bYSwQc7PWSORQ4DSvrq6K4EkZhvBmjWuBZKYsdmJ2HrZkbcLDJX1tzNDUgI6Eajj16re5g1C7g6TTGQQQT0110wnSTU61MhLdCTriIUzzyrNslQW1Rl1dAjvAICb0npQtaGa/Rn7nd6ObdIjT40nk7pN4qPdHwGgVqop1ZZa1s6X+r3k9Bx3truTd3a8w4ncExZfl5f7vWxXNaVRcDV5qxnBwRDbHq7bCbk7ReWenO1w5GX7+aD2h5C+EHO/HU8UFARDhoifq40Ga2g6nY4WLVqwcuVKWrdufSXu6Rr+13HN0fwaruF/G9eyfF7DfzHu7XAvz214Dr1Rz9LTSymuEg7u4d7h3NDshn/03nzcfMj9Ty5avfbyZRZp+xL4NIO/HhOZJC79JCKkw4YI5zZZL5SDzDWitOYN+y7Pda/hfw+2WbeDugNX2DEi8gbxU5kNuduF8lWdIzK1eERCxFBRRjW499+6zCNdHuGNrW9Qrisnr0LIrmNbjyUhQGQQtc1M15CErbNmCVF4+XIYPRpGjhRZzUaMEIYrEEEqf/4pSsV/8kkDb7yxmUby85nU1UpqXt/0et4Y9Aa95vSyOMG8NfifIaX/FdBXWH9X+TQ61cOdbe9kwrIJaA1aZg6deZlu7u9hVMtRlt9nDp152QI2Q71DGRA3gO3J25GRmdJzCt2junPHb3cA4Kny5InuT3DAJmvg/v2CHKnPwO/tLYZ5YWED5l8DKlRUXXQDRCVITxeLb+w38V8tWjiqs86g18POnYLI7Nu3YRlEOnQAn4b7WTYaUb5RlEwrueznvaHZDSw5uQSAQI9AOkd05mjWUXIqRDWBQfGCUPb1FYbPjAwXDfuNXQerq0VJhNpwrXLqNbgKTZD19+ITQiapmYX/7xqEzMjf4xisEn8X9PheVLU98S4cEdkPo1TWwukSkkNFkpqVPP5pB7HaEO0bbeegm1uRaxdIkluei0qhsjhfmsuiX8M1uIreMb25ufnNnMo9xdReU//p22kwHunyCItOLAJgwdEFlgxuw5oOu/rzus8i2PcwXPoRdt8Dpz+CmFGiOol7qOAdCo8IZ4myCzC04ZbbtqFt2Z+5H71RT3Jxst13KcUpdgblR8eHMf8jOHcOnnlGBPVC7bJno6u/hQ+FG4/DwSmQ+pvou0INvq2tfEuJaR/wb3fZAknqQ7BnMIPjB7Pl0hZkZKb2mkr3qO6MXTIWEBUoJ3WbdFXu5WrB7CTavr2oalUXVCoazW23DmnNgUwngZ026BtbS0mQfxi2+k5V1d/TMxwCSMzI2yucIGQjRAxzdFKoJTFDZ3dQShKGerw/hiQMEZxQsckbNW4cKGu5F2cIG+yYQbWuZBEATSY0gBcwCkeNHWOg1wJQuFmdrixNTNdP/xOib6FlcEuLE2JteLjLwy5e/78H7cLa0Tu6N7vTdiMjo1aqOZV3yrKOP9XjqX/4Dv/L4B0PseMg9Vc4/Qm0eBpkyT45im0wk3db4JDDaWYOnWkJJJncc/KVvut6IUkSs4fPptccoTu92v9VwrzDHNrp9SJo1KWqpiaY9w1XEegZSJRPFOml6QAEuAfg7+5PakmqxYlzVItRrp/wMkAv6y1BxDnlOby5zRpIYhugZpSNkLcbi5YYfp1zJ0BnlZkKD1uPA1EJYPhhkcxAUkLnD2BNjSRPCjcI6e2So1pDsXu3eN+JiZDgQvGv/HzxA3DnnYLeqQuXuxLyvwXOEkrVlWTq4EHnASFmqFRw7JhInGXG/v21zymDQbS/asjZYl9Fp8tsSHxU7MdKD+j+HazrcRVv6P/Yu+/4tqrzj+OfK8l7zzh7kr0TQgZJ2GGGhFEgEKDMsgqFllFaCm1pKWV0UGgp/RUKLbRQdiFsMoBASEgIBDLIInsnzvCQdH9/HGvZsjUs27L9ffPSiyvpXOlIkaVzzz3P80RvzRozLwomuVA0SchKS01VkkWLYvsebA498nswrMMwlmw1JcGvHHUlQ0qHcO3r1wJmMXwy/N5EcuGwC7n17VvZemArHtvD9Udczw9m/cD/HfzTST9t9HOc3u90ijKK2HloJzsP7WRPxR5/EEl2ajbnDjm30c8RjzRXGj+e+GOun3W9f46ua25XzhtyXvN2xJkKk56H9040c7CvDoCBt5jjgeBkPd5qU71w85vmN6qZ9C3qy1E9juL9te+z9cBWXlz+IjY2WSlZgfcqfzCUTIIdH8BXv4Xe3637QLWDz70ecDg5rgT6F/Xn651fA/Ds2c+yYucKbn3nViwsTut3GsWZxdBlGmR1hwPr4MtfmoCbiM/hNslA1vwTFn7fZNZf/YRZW1JypEkE4qmAnQtgzxLIG6xAkiAXD784/B1Z3aH7d0yVguW/g/4RxucQvtpHQ5pjXe6umsjr7N4muKi2ho6nOxwD3ipTTconTOBJfq1zv+WV5dRWXmkCDPz7pOdj2/Dhh9FXGARzrtZXzTaYL3lgQmybXTMv0sBgKpjtMcPtAT+sm8S1sbbONmOivIEmIVmweoKAerjAaTnw1BybX/HqFf7KVLUdVmgC5Kb3n84/l/4zYndOPuzkkOuXjLiE3374WwBe+OoFNpRvwMYm3ZUePtAUkxTx/hPu58R/mnV9BekFjZ8/iCV5q0/weePSI80FzHyY+yB4K82405nR5NXTYhXzFHhKSgqVlZVJmTVHWhEtNBcRkSRUlFnE2QPP5ukvnmZPxR7/7d8b9T2cjgQOzONUnBllBoBYdD/HZAJc85QpRb71PdgxP7RNRhczwSBSH8+BwHZKbvOVrs3oAN3OMpcmkJeex7VjruU3HwQW+99y5C3+7eDFFVu3Rr/IKDsbXngB/vY3uPVWeOklEzRi22axtG2bCX7LMotdYln8DpiJoLQ0syA6FkVFXNjtQh78+EEAFm9dTJWnyj8J3KegDyM7jmR/cLrS9sQVtLomXPnnKLPLW5ZF5U9i/LdpYpZlsf1H29m4byNDOgxJ6GPPHDqTOevmYFkWq3evpnt+dxyWAwuL6QOmk5GSwdixUFYGW7bAn/8MU6ZEftwBA8zE3iuvwD0NJ1U2YqxQkUMnwCwC2LPHTBRGClgpLzftgrPuNeSLL0xwBJhAErc7+hPT48c3nE25tbhj0h3+QJJqTzVvXPAGnR/o7L/fd7Jt0iTzvfnss1EG18WbcSlWsZT6lvalZIKZgK/eC6v+AqUT67apfUIoXjs/CT0BUTIBxv8zsFKjQyB1UaoFxU7Y7jHZ0n1BWz7BgSQe25O0gSRd87r6FxOC6Xffor4h132clpMOWXUXlYlE8vJ5L7d0F+J2VI+j6JHfg7V71rJwU2Bh+/dGf6/5O+PKhPFPQfdzYdlvYPuHsHsRLA3OGu4132Glk+N6iv7F/fF4zXfg1v1b+b/P/g9XzQLF11e+7j+hXJhRSEFmHg88YOJGFy0yi0v/+19THS54MZZve+NG6N49ztee1RUmPgcHN8GWt2HzG7DrU9j3tVkAkNkFel0MnafGFlHcSBcMvYB3176LhcXKXSvpktvFPz4/Y8AZIVkAW7sdO8yxOsDUqY0IDIrClD5TQgJJXA4Xtm2HBD7OGDKjaZ68kYLXjsyZY96rhC+Yrd4HOEwl5NT8mHbtllXMmv3bG2wzc+hMk0Hctzi0eFz4rPoH1odfqFw6ObaFOWACYohy/mvgbbDsHtjwklmQ0XOm+V7MG2jGcZU74NsXYN3T5r3qMpXp/af7A0mclpPu+d3ZW7GXnYfMyufCjELKssti63Mrcf7Q8/low0c4LAcvfv2iv7pUt9xuHN4pQkSY1DXoVlj/DFRsgdlTYdKL5vMe7jPvdde9DXNewnOH+T5r1izjDRjbZSx9i/qyevdqrh97fb3txo2L7fv/k0/qVk9ITYUjjjDzVitX1t3ntiNv47rXr/P3619n/ouC35hAdwuLn0z6SdSvKxHGdB7DS8tf8l+vr7rRiI4jzLkgywGubMjtG9qgocpMvv18v3PD7zHnBRqqNFI4IoZs1ZiEC1HwegNVZI6IMgbgs6B4qalTm6bacWtQ5albqiLcbT6Rqoe43bBqVehtn3zS8ALMDRsafsyEObTVLKD2yR8aCCKBhFfJSbTlywPbxx0X3Vjtggvg5z835562bTOBJcnkkhGXcMOsG7Asi32V+0hxpmBhYVkWJx12UkjCkGTlsBycM+gc/rTgT9jYvPXNW3y80WTNSnGkcGrfBhIWRcnpcHLB0Av44yd/xGt7+dtnfwPM78vZA8+uP5C7GVw28jLufP9OdlfsBuAnk37iPxZvVgXD4aQl8Ok1JpHDktvNJas7pJeYRfjlq0zQQ35iz39F45rDr+H9te8D+CtBXzT8IrJTswONBt0G758E+76CRTfCyAfqnyfwus2CZMzJoe8M+g53z70bC4u56+fy9Y6vsW0bL17OGlBz/tzhNMckC75n5iYW/xiG/6r+xem2B/atgPyBJpiky2mm2uzmN2DTq/DNY4G2rmzodJo5V9+Mcxut2sDbYN0zphrW+6fB5JcbHp9X7oCMGKsbNfW63Op9gBdy46gS1eGY0CASCBt4EhxI4rAc9VYkCdknPZ+1a2HXrrpPO2OGORf9r3+ZcX2wuXNDg0jS0027008348aTTza/pY2yc0HN324M8gYl/nvLUxUIBCqZWLdqaj1BQJYFGc5U9rsjn3f1rTU4re9pUXWpdnBI/+L+jO0ylvkb5rNqd2Bwee7gc8lJqz/7yQm9T/Bv33X0XWSkRFnmtj7xJC2s77yx5YCUbCA77G7JIK5f8Ouuu47f/OY3PPbYY7iaatZVpJmkpKRw1VVX+bebap9k015ft4hIJFeOupKnv3jaf93C4pIRl7Rgj5pBagH0u85cPBVQvhLcB8zBamqRmWjRQb80IMXl4qpuf6rZDlMFpNYC+xTLHWif/2JzdbNB9Y1zrj/ien8gycRuExleNtx/X1lZCk89dRV798JRR6Vw4YXRP5/DAZdfDpdcAh9/DK++Cu+/H6iuMHCgySx1zrj12P36YUW5+N0vLc08aPCKEF+mkaAsIym2zVX790N+Pim9ejEM/Fn0tuzfwqsrXvUvKjproJlwzMzM5JxzzvFvRxJr+6Qdc6YGnbjYvRg6npj4csMtqDizuEkCFk/rdxq8YrIczl4327+gyovXXwnF5YLvfc+c2Hr1VRMX1adPwyfELr7YTOwtW2YWAQ4bFiGoIsbJnkJ24aIaNynMnQunRTHXVV6TDCfaCia+LHJgAiUifdxTUlL4+9+v4uBBuO66lIiBJEn7txRkcOlgOmZ3ZPP+zZRXlTNv3Ty27DczuLlpuYztMhaAyy4zQSRbt5qTnyefHGERSDwZlzZvhjPPjC0IL5ZS39K+ONOg92Umq9i3/4VDv4W0koYXJnjd8S1c2DE/dNXLiN+GPlatgPhuLhNI4rW9bNq3KeS+rQe2hrZN1kCS3K4h18NVVvFl/+2Q3SEpkgJIcor1t7JZf1tjDSYHf+ZAy7K4avRV3PL2LXgxJyhLMks4pe8pTdjhCDqfai5Ve0wG0N2fBeYd0oqgw3GmQmocXA6XP+Orjc2lL18atp2zZnHEySfDf/5jDqG++AL69jVjsXPPNWNQ2zaLRJ95BvbvN5nJGyWzE/S60FySwKl9T8XCwsauMz6f3n96S3cvoRYvDmyPHNm0U1uXjbiMX839lf/69P7T2Ve5jze+eQOANGcaJ/Zu2WrH9RkzxgyLN2+GJ54wQ+KEc9ckIHFlxbzruJI+DQaSuBwuBncYDCv/gj87fvHY2BYrxxjcApgF0bU/VPVl1e92lvkOnP9dKF9hMg0vq5URwXKZQJhiM3/wg3E/4BdzfoGNCUj65LJP+OGbP+Spz5/Cxua6MdfF3udW4qyBZ3Hd69fhtb3MWhXIlnzB0AuU6DIeBcNg+L2w+GbY8papEjHoduh2psmC6lO5g5TVj3PViI9h7ON1xjrhAkhaet5h+bXL69yWkpLC6NFX8d3vgtudwoQJkb//g1/H5ZenhBxeZWSYqtLHHWeCSy64wIwRgp102EnYr5udPvz2Qz7ZEKjsPrLjSEqySrBtu9nGndP6TeP2d2+P2O6Uw06BpVeaxaJFY+o2aCiT9J6lgSCS4rGmKmYkRWPrLlht6DmCq6A3YPlyOFDzM3PEEVBVFbn6wmefBQKGDj+89SVqiefzkZmZyYG+B/jfiv9xCJPZptIdpiJJzW1u3DzMw/x00k/9z7F6tZm/rA4fmwSEBoa43ZEDRZotiGfHh6HXRz9Ud+FkEgeTHAwqlt61a/3tgl16Kdx1l/l3+NWvIifnae6kRVP7TeX6Wddj2zbvr32fFEcKlmXhtVvXccnZg87mD5/8AYCXlr/kD947sc+JDS52jcV5g8/j9x//HoD31pgqnjZ2iweqZ6ZkcsuEW7j1nVsBuGjYRS3XmYwOJpFD+Tew8RXY8CLsWggHvzXj7NQC6PYdE8zdzMEOp/c7nZLMErYfDBzTXD26ViXQjlOgyxmw4QX4+kE4uAFG3GfOO3qra/rsMN9Te5bAV/fDhH8BMH3AdH4+5+cAvLvmXVbtWoWNjdNyhs4D9b4ENr1u3p9lv4Y9n5sAlpIJoX05tAVWPWoSkE6pST6akgs9zjUX2wbPIZNZ35luEogkSaBxq1EwFEbcD5/dBFvfgddHmH+LbueAK2h8XrENVj9uqlYeP7vFuhtWdc0JUVeUJ0SDpRZG1Sw/6Dep3kCS6v3+OUEwgSTvLKr7WH/6E1x9tQluvfZaMw/oG6McOGDGOMH+9S8TbOxwmKSfc+bAoEFRdduvznht5ydArYFPWrGp6rJnKXgOhq6hsdwmKXC8543qU73HVISB+pNw1KNndglL93zbYJsURwr56fkApLpSyUvLY2/l3nrbZ7gyKMys+5m4ctSVzN8QmgD58pGXN/jclmWx6rpVLN6ymKn9pjbYNirxJC1sxeeN4/qUffzxx7zzzju8+eabDBkyhKys0Im/559/PiGdE2kOlmVRGmP4fTz7JJv2+rpFRCKZ1H0SvQp6sXq3OVo4qc9JdM2LclauIcGLQGJYANLsnOktko1DWjcrNZfStJoJsKpd/pK6frUW2FuHNlOaZAvs6xvndMzpSG5qLvuq9nHLhFtC7nO5LKZMKeUvfzGL3w8ejH4BuY/TaSoLjA8TfwPAojgyHYBZCN2xo1kt0wALqP2qzxp4Fn/4+A/Y2MxaNcuf8du36N/hcNC/f/QZRmJtn7RjzpQcc8Jz58ew/j8wOEw2wURll29DSrNKOaLLEczfMJ/dFbt5d+272NikOFKY0jtQeuTSS+EXvzAntk480UzKde5cN1jAts1EX8+egbmbm2+GN99suB/VbojltHsGFUzhDWZxIs8+6+L++yPv4ztJ3dDJ1GC+aiQARUWR21uWxZYtpVRWmtceTfuk/FsKYlkWp/c7nUcXPYrX9vKfZf8BzKTwKYed4l/8fdxx0KmTCb657jqTPTwvr/5gEq8XHPFkXFqxInTRbiJLfUv70+dy+Pp+cyb+vZPguNlm8WS4SX+vGw58Czk9Y3sO24YdH0HNQnE6n+pffFifXinwWZWF17bZvD80w2vtgIyEHAc1gdr92n4gdHHplv1b/CeQkjUYRpJDrL+VzfbbGmMlNb/0dLOSrls3Lh5+Mbe/e7s/qOqKUVe0TGbQ2lLzoft3zCVBhpUNi6pdaVbg3+6ss0yFu2uvhdmzAxffQjbfmpIRIxLWzaRRklXC+K7j+eDbD9hTsYd315jxeaozNSRzX1uweHFgkejo0U27MK5nQU8Glgxk2XaTqvuiYRexYucK3lr9FmCyMDoilThsSBPOKzoc8N3vwm9+A6+/DmvWmAWKDQVux1zdxTdHFFShJUQDFT6vG/Fd/rXmI8AEjcy5eA5/WfgXnvr8KQBOO6wm6n/3IrM42eGC3H51n6OhxcrhMr82VHU0q4dZTBUsUlb9zqfAqV+bBVvf/tdUJ6nYZhaGpeRAyZHQ7WxTORqzAGZ42XA+22LS5i/avIiPN36Mu6bqyrE9j637PG1EaVYpx/Q4hrfXvB0S6Hzu4HNbsFet3MAfmd/gBVebjNwfzYQFV0HhaLP4q2oX7FyAZXsoLRgVddr6ZJx3sCwLr7eU7TWHCMOHR/7+D34dn30WWj3ht781yX7AfF8+9RR8/nno/r0KetGnoA+rdq9ib+VeZn0zy5+Yx7eAqTnHnQNLB/qDRhsyuftkWLTHXCkYEdsitaqdge1Bt0e3b9HomoWw0T1FtNYFFZkYPz5yEAmYf2fbNj+XHVphAct4Ph8Oh4OU0hRWrlqJ7TWfjUpPmECSmttsbLaxjZyCHH8Q3zffhFbrCWf37sD2hg0NVyNpVts/CARt5g0OXzk2iQUHkkQzLwzQpYupxPjaa/D738Nhh8E114QPGKmuNkFYWbHH/MatR34P//h58/7NvLPmHby2FwvLBLq1EuO7jvcHCSzaHFi9XDu7emOM6TyGbrndWL9vPd/uMwt4izKKOLrH0Ql7jnhddfhV3PPBPZw/5PzEVLdsRFINAHJ6Q/8bzCVJpDhT+N7o7/GLOaYy6/gu4xlUWmtFumXBkc/ARxeaShXrn4X1z5ljhLJjwFkzXtvwsqlaUjDKv+uwDsPomtuVb/d9y5ItS/wJRY7uebR/MTdgjnmO/I8ZD67+G2yeBZv+B1k9TVUXRwoc2mjmmm1vyHPU6asrM3wAQaR/v2RZD5MMBtxoApw+uRL2rzZJBxZcA4WjAuPzXQsb/rdoSb5j6HoqGjZ4PO0MM1gL074gaArFwqq3IomvSrGFRW5aLp9/buYrfBVGTj7ZBJGAGc937QoPPghnn21uW7o0NLB1+HCYHhTPmJJipmnPPTdydbZgIeO1ih1QWStBRu4AOOED8znYvRjeOhLLfSCw5gageHz4qkGN4Q4aVKSVxFSddURh94iBJJ1yOoVcH9N5jH9uLCc1h045ndiyf4s/uGRYh/DzumcPPJtrXrvGX8mpT2EfxnWJvK6od2Fvehf2jtguKpGSFrax88ZxnTnIz8/nzCZJSSMiIiLSsizL4urRV/PDt34IwPdGf6/xDxrNIpAGFoCIJL3UQnCkgbcSts02J75ra8UL7Df/cDNV7iry0vPq3Hf++SaLhdttFl387GdmEqI+MS+2aAGn9zvdn93ItwimJLOEwzsf3pLdSg49zjOBJHuWmrLO2b2SOlNZsjhzwJn+rCG7Dpl6wsf2PDYkI1eXLvDnP5tKPevXm2yAt9wCV1wBOUGJuzZsMCe+5swxVUkefRTeecdUrHjsMXMirHYiPo8HtnuL6RRj1pDzeJr/cSrffgvvvgsTJzZcNcTXz3Alk8MJDiRJi/IcS1qaiRML3re1O6XvKfx54Z8BmLt+LmAqJZza91R/G4fDfL9eeaX5fEyaBLNmmQnf4JOf1dXm3+jFF+GMM+LoTFOX+5b2JbcfDPoJfPlLkynuzXGmWkink8z9vkys3ipY8ySseSr2zGKHNgYqYQH0u75uQG8t3VwmK7/XdrPjYOgE+LYD23A5XLi9bhyWo86kf7LomN0Rh+XAa3txOVx1AmB8ATIOy0HP/BiDc0SSQYyV1PwqKsy+3bpRmlXKtH7TeO6r5wC4dET4Kh1twfgu9UXlh+pfHBrcPmgQvPeeOff3n/+YwOQdO8yaiKIiOOkkOCdxa3+SypkDzuSDbz8AYHeFWe13fK/jyUptxpVjzWDpUvP/vLzoMzc3xrE9j2XFzhXYts2SrUtYsXMFFiar8uQek+N/4GaYV7zwQpOpGkzWzQ8+MIkyws1fuN3w7bcmuD9qzprPVvW+8PcHJyDxVfcEyO7FmOIjyHn1JsqrynF73RRlFrH94Ha8thcbO5Blt2KbWRyaPzL2hRbuCnBl198nMP366EKzoKcwTNKOaLLqW5apDlEwDIb+PGK3TuxzIku3LsXG5uMNH7N8p6m+kO5K54guR0T54lqnGUNm8Paat/3X+xX1Y0gHJT9qlD6Xm8WIq/4Ka54wn+Vt7wMO/IHp2X2g79UNPEjrEDxnEkvSn/Jy8/3mU1Rk5pt8cw6WZRbF33ijmQ8Odnr/03ngowewsXl3zbv+xDwttRi6OLM4JPN5bbmpuSZ5h6fmeyslxyxUjJUzHcqOi25+NKWgSeZRg38eu3SJbh9fwNDw4QnvTlLLSMkICTCq8lTVaVPlqQoJRMpICWRGX748tsCQtWsjt2m2ogB7l5lxAkDn0xKf3buJBc9Ju+tZsxvOn/8Mo0bB9u0miH7+fPjRj0x2dZ+qKpN5/aWX4IUXEtfnaJw54Ez/OaiN5RsBGNtlLCVZJc3bkUZwWA7OGXQODy14yF+NxOVwmUrtCWJZFjOHzeTuuXf7/zZnDJmRFBV4c9Ny2X3L7sgNo5GApBrJ6vKRl/sDSa4dc234Ro4UGP8v6HAMfHWfqWS44yPYPremgRWoGlAw3L+bZVmcPfBsHpj/gD+IBOCsAWfVfQ5nKox9DLpOD1QdObDGVG6BmsB/G3L7Q//vx/YitR4mdr2/CyXj4ZvHYPUTJtBg+1z8lTbB/Fv0S8JqlCk1J0Sr6vn7r32Mv/lNWGGqN+GpqrtiPczxd/6+9bAucGwSLpBkX+U+//diVmoWDsvBkiWhga+33hq6PsPlMucPe/Uy1z/7zIxHfMEkt98eONfo4/HAT38KM+ItBLWvVgSKIxWOeQtcNe9j3mAYchd89sPQdvlDoq+EGi1P0MFSjFVjjykbyD9Wz2uwzcCSgSHXrz/ien8gSVl2GV9f+zWjHx3Nws2mBPT1Y68P+zhZqVmcP+R8/rror4CpUNIiFUrb0XnjuEbGf//73xPdD5EW4/F4mDvXDLwmTpyIM4q0VPHsk2za6+sWEYnGRcMv8geSnHTYSY1/wHgWgQQtABFJdh6czD00E/Z/w8T013Ee3nCWzWQcUzTUp8yUTDJT6p519Hg8VFTM5fTT4X//m8gvf+lk9GiT2SLcS3K7TYa03rEkQYinZCZEXTYz3Oue2H0iuWm57KvcR1VNadPpA6bjqJmgrKqq4l//MiWTZ8yYQWqENG+xtk/Gz4df1zNhYc2ExseXmuzyEtHp/U7nR2/9KOS2MwbUXeV/2WWwdy/88Iewc6f5/89+BmPHmmxoO3aYk11er8ko/NvfmszRK1bA3/9uFordfDOceWYgoGv7drj/fvjoo27MbihrCNTJHDL1gIPUY22qqi0uuQSWLDH9CLeYyusNVFBZsMCcgIuUATHWE4Aej4dJk+ayfz9s2TIRl6vhv42k/lsKckzPY0h1plLlqWLlzpWAyRx0Yp8TQ9pdfjksXAh//avJ+tOrl/m3vuoq6NHDBNi8/77JJJSREWcgiUiiDb3LnChZ/TeTLW72qaZUeccpZpK+cofJRl21y2SAjdWepYFtZwaUTGowiASgWwr+CgV7K/eycNNCUpzmC+mLbV/4z1GVZJYkR/WCMJwOJ6VZpWzZvwULq04giS9Axmk56ZqbnFVVJDnE+lvZWn5bfa4YdYU/kKRnQdsNqkp1pfrHEg0Z3Wl02Ns7doTrrzeX9uL0/qdz45s3htwWbnze2u3da072D2mmteeTu0/mj5/8EQuLJVuW8OX2L/HUVOCY3L0RgSTNMK/Yrx98//vwxz/CF1+YwO2HHzaZ3aurzYIKh8Nc/vtf+MtfTLB91NJLzeLNqt0m22p2r7pt6klA4gAmdJvAG6vewMZm6dalLNmyxL9YZEK3CaahbzFEWhwLDw9+C+lh5lBq98m3cCunX7MsQD2257H8et6vAXh/3fv+hemTu08mNVwW1zZk+oDpXPHqFf5x6wVDL4iwh0QlbwCMegBG3Atb34MDa83fjisH8ofgyRvO3Hnz4Nv3W+3YyOPxsGXLXI46CubOnUhKSvTnvzdsAKdzIh6P2eeqq+rOAaWkmOC7p58Ovf3kw07m/o9MOduvdphFXUUZRYzoOCLkOaB5xp1jOo/hfyv/5+/HgOIBrNi1wn/sNLxsuGlYs+gZR5xZ5EuPMsEk0YhxoVq0ggOHoq3UUF5u/j9kSPjqDMkuns9HVVUV9mc2F3gv4J/8k2qqqXSHqUjirjTnAWyYyER2f7UbT38PTqeT1atj62c0gSTN9t4fWBvY7jIt8JveSgRXCikvN9PY0ejUyYzZjjnGzJM/9ZS5DBtmAq0rK80C2h07aqoxNrYaRIxO73e6f3G9T4sclzTydZ896GweWvCQ/64pvaeQm1arel0jzRgyg7vn3u2/fv6Q8xP6+EkhAUk1klXXvK7+5D0NfsYtywT/9r7MVKNY+0/z/eU+ACl5ZlF5zwshu0fIbmcMOIMH5j8QeBgsTu9/ev3P0/kUc6nYAZtehYqtNZUS80zFpvxhsUf6aT1MfHL7meRTw+6B7XNg/1ozPk8x4/O4/i2aQ0YnU+lr1wLz2QlX1SL4eNpyBAJJKrZAWmHD7YG8sirABJLY2PUGkvj4vncXLgwEhYwebZIE1ubxmODwv/0tUM3W7TZrOM44o27SUKfTzJuEe6z6hIzXyr7GGRwg1GMGZHYONHa4oMPReGwnc3eZJ5nYYQnO9FoV6CJVQo1G8L+VN8xcagPVZE7rfwZ8+GiDDz+h64SQ62O7jPVvr969mkp3pf94qfb9tV064lJ/IMmFwy5s8Hml8eKe4XK73bz//vt88803zJgxg5ycHDZt2kRubi7Z2dmRH0AkSXg8HmbPNgvAxo8fH3VARaz7JJv2+rpFRKJRnFnMi+e8SE5qTtIunhJJJh6Ph9nruwBdGF8wD+eepZA7sN6FjMk4poh3bDRnzmxGjIDXXx+P2+3krLNMZoubbjLVCXwnotxuUznh+edN9YSoRSqZCY0qmxnudbscLk7vdzpPfv6kv920ftP821VVVaxbt86/HU0gSSztk/Hz4ZfZGTqeBFvehO3zTMnhI/5ad5LMt6BkzT+hZxuc0I/RYUWH0bewLyt2rQDMJHZ9GbluugkOOwzuugsWLTIns4L/ZpxOM2c6YQJkZ5vM0ZMnmyCtTz+F73wHSkrMSbLKSli92gR1jBxJzFlDcoBrr4Pf/c48/gknwKuvmoyUwZOIHo95rq1bzd+62w3z5pl+NfTxDc6KeeBA5BOAHo+H0aPN38Zzz43HEWGxeFL/LQXJTMnk6B5H88Y3b3DIbc7+H9H5CAozQieSLQseecS89382BUz497/NpbZRSVjpW9opy2F+J3L6wLJ7oHqvWTy58uGgNjV/mxlxVP84tCmwXToxfFn42l2yCco/CqP/Gn5htR1czz0JFaQXsGX/Fqq91Tz31XN8s/sbwPTbVxa92lvdqrJYSvOL9bey2X5bExRMfmyvY7nn2HsY12VcgjuYfEozS9lQvqHBNkf3OLqZepP8ehX0YkDxAP+JWwuL0/omLmNusjh40Pw/2oV2jTWxuznZb2OzYOMCvi03WV1z03IZVDqoeTrRCPfdZ4JI3n/fBNFPmGACSaZONcde27fDk0+aY6wRsca/djgK/whk02vQ58rwC03qManbJN765i0sy2LhpoX+jNV5aXn0K+pnGrlr/sGjXdAcbMubkD84cp98mftdGfFl7o/R+K7jSXGkUO2tZtHmRf7bj+91fJM/d0vLT8/npD4n8cqKVwA4d/C5LdyjNsbhgo51P0eeqqrkHBvFwOPxsHv3bI46Cj74YDxVVbGd/3Y4xuPxOHG54IYbws/rWBacXasg95HdjiTDlcEh9yF/cOtpfU/zJ+Zp7nHnpSMu9QeSlGWXMfeSuYz/23h/IMmlI2uq1VkuoDLmRWRYTpO1vOPx9S8erM2uju05wgUdhhFcISPadZaVNfETeXmtN5Ak1s9HVVUV3j1eetCDFFJMIIknTCCJpxLLsrBsi6M4ii1fbsEz1cPevU72112/WUfwnOnatSb4qjrMP33gtUR+zIQ4ZMYOuLKgaFSrCyQpDJomnT/fnA4Kl+wonAEDTOKjO+4wQSQejxnrLVli7vd9fIYVNH81iJEdR9IhqwNbD2z13za139SYH6dRElAFY0LXCRRnFvsTm5wzKPGlLQeWDMRpOf2B6mM6j0n4c0jTqv5pA1+GtVkWFI02lyiM6zqOoowidh7aCZjPR1l2WeQd04uh18XR90uajsMJHY6GDi3dkSh1ONZUtXG7Ycd8KJnQ8G9rVlCCmy1vm/MljobPZaQ6U0l3plPhqcBreymvKq/TZl9FIJCkIL2AfftgQ9D04DXX1K0uAub6pZfCP/9pzi37kv2dfHL9/amujj2QxD9em7ILp+UKjIcH3GzmFILfM68bj+1g9q6jzD59qqkzwoumEmokzqCT0+7yuv0IV521ag9k96KwZFzI7/Z1Y66jf3F/rnntGv/uZw8KPVAqyiyiR34P1u5Zi8f2MG/9PA5Wm/mb4oxiuud1r7erYzqPwYGDoswiSrNK620niRHXysh169Zx4oknsn79eiorKzn++OPJycnh3nvvpaKigj/7zuiLiIiItFINZmmIVTyLQKKsJiCSlBb+AI59u6V70ax+/WuzAL6qCn7+c7PwfPp0s6B93z6z+HzTpjgWW0CLlMyc1n+aP5AkxZHCMT2PadbnT2pHPAb/GwjV5abc8K6FMPSX0DlodmnPEljyY6jYrkCSGmcOPNOfSXV0p9ENTmJPnWouH39sAgZWrDCZ1goLYcwYkxGyZ82cY5cu8NFHcOed8H//Zybytm83FwicCOvSJb5+/+pX8PbbpgLGJ5+YP8XvfQ+uvtr8fZeXmxNw999vglccDnMC+3//M4EkDckNSkq2cCGUlUV/4toXX9ZWhgqn9T2NN755w3+9vhOGDocJJrnwQrPQ7YUXTGYhp9O877Zt/l2uuqq5ei4SBcuCQbdCv+/D2n/Bij+aYBL3QZNZrHA09P8BdIqjEuKhzWbhj+2GDsdEtYCnIMrvmXRXHIswm1FwBrIt+7fw+qrXw7bbdWhXc3VJJHESFEzusBzccuQtTdrVZNGroFfEQJLDOx3eTL1pHc4aeJY/++/YLmPbZOCdL0N5tNnJG6s0q5Q+hX1YtWsVa/eu9VfMmNx9sn8hcTJLSTFzF+edBy+9ZBYnfvihuQRzOuNYcJs7ANJKoXIbbH4L+l4beZ+gih8Tuk0wi+Zs+GjjR/4mE7tPxPKtGrZrVn5Y9XSuocXKW9+FgVF8X/oz9zfPhyojJYPxXccze91sdlfs9t9+bK9jG/fAzZxtPF4zhszwB5L0KezTrM8tbcf+/aELsCPxLXofMcIkEgnH5aq7iCzVmcqU3lN4cfmL/ttOPqyBlWhNzFcJBeCb3d9g2zYrdq4I3F9Wc78zHTwHTKbz2lEY9S0iW/8fExQINVUxowwMdB8wEzfBz9PAQjVKoguGDv6dr2q4QJ2fL5CkucYIySpcRb8qTxUWdSNyoq1GUjuQJFKOimbJYeE+CNU1C02LxtQ/VkhiI0cGvp/efddUaY5Fly5m7vzee+Gxx+Ctt8xQICPDVCa55BKYUrIDDm/eahCWZXHGgDN45NNHAOhd0Ju+RX1j70NjJKAKhtPh5JxB5/CnBX8Cmi4YZkrvKby26jWGlw0PjIHbkgQl1WiPHJaDswaexV8W/gWA7wz6Tgv3SBIu0jFccx+/lR0Lvgobm16D4nENB5Lk9jPVQyu3m+Pvft+P6mly0nKoOFh/IEnwbYUZhXz5Zej9J5xQN4jEJz0dBg0yVVd9jjrKnGusXZEEzOMccURU3a5r35eBIJKcw0ylyNpqJzjO6V937JwIKTmB7T2fQ+fT6v7b1VMxFuCoHkfx3LLnsLHpntedIzoH3pTCjMKwv+OTuk9i/d71eG0v7619DzBJbSZ0m9Dg75llWXh+1lxRxxJXIMn111/P6NGjWbJkCUVBR9DTp0/nsssuS1jnRERERNqEcItAElRNQCTpWE7Y+g58dR/0vzH8pIG37R3wXXutyVZx++3mmH7fPnjiidA2LldyVp8N54TeJ/i3p/SZQporrQV7k2QyO8GkF+HdE8w/9u7PYPYpJpN8eilU7YUDa0zbgngih9qmaf2n+QNJzhp4VlT7HHFEdJNypaXw8MMmiOvhh+G118xPbno6dO9uAj9OOSW+fqelwaxZMG6cyWJTUWECxX73u7pte/Y0ZZI/+QT++lf48Y+hoCD8hCPAsJqK1LYNc+fG3sdZs+Ccc+qfBG1WjZzEPqXvKVz7+rUh1xsybpyZ3F2zxmRM3rXL/Ft16WIyBkUofCTSMlyZ0Ocyc0mUQ5vAt8CjeFxNNtmGjYryJz2qrHUtqENWB77d923EdoNKkj8DvEhYLRBM3poNLxvOnPVzAHMiMis1C7fHTUVN9YDMlEwc9Q3K2qlp/af5A0nOHBDjSrRWwpfhujn/6Y/teSyrdq3yB5GAOcneKM2YoCYjA1580WTkvOceU1U1eIFnejpccYWpxBoTyzJBs2v/CZtfh/JvIKtHvZVsgZBFFId3OhyXw4Xb62bp1qX+2yd1mxRo78uq6annfQperFx7MfS2eWaRqSsz/L7+11HTX1/QSrAEZNUP54TeJzB73Wz/9fz0fIZ2GBr34yUi63Zz8VVK+s5ALYST+H36qUn8EW3mfl/lhAkTGq5UcdhhdW87pe8pIYEkx/duuepB3fO6k5OaQ3lVORXuClbtWuXPUp7iSKF/cX/T0JUFVTth75fhA0LCLSJb+0/zPehIg4Jh0Xdq/2oTkFe7kmYDC9WikZER2N61q/4AoHBay1x9U6l0h6lIEuY2gG++ie4x3UE/kd98E3q9xRzcGNgumRASrNpapKeb+dC5c+G99+If3xYXm3Fc2LHcojC3NYOp/ab6A0la83HJ2QPP9geS5KXnNclz3Hv8vaQ4Urh90u1N8vgtLkFJNdqr6f2n+wNJpvef3vwdUGLVphPNMVxzH7+lFUH+MNizGL75Kwy6DaycBgZXNpQdb47Bt86O7rfY9pKfns/2gyZz4N6KvXWaHKg+4N8uzixmU1AB965dzXFAfdxuGDoU/vY3c92y4JhjGj5uiDdpIXuXBbY7TjGV/SIFtmZ2NGNuK8EngVNyTIWYA2vMXMiQ2B5/WIdhPLfsOZyWk1W7VtElN/Cm+IPVaxnXZRxPLnkSh+VgwcYFWFhYlsX4ruMb9VIkseIaHc+bN48PPviA1Fpn5rt3787GjRvr2UtERESkHdMiEGkvbI9Zz7j4Vji0BYb+3JQmtb01kwcWrHq4pXvZJG6+Gc4/32R1+vOfQzOgWRacdRb88pct179YZKdm+7dP75fACk1tRYejYPIrMP9iqNgK2GYx76GgGSrLGVoetp0b3SlQgrupPlPFxXDHHeaSSB07wvz5JlDlr381C6k8QfFwLpeZcJw82VQZWbjQVCq5/HKz8Ko++fkm280XX8C8ebFn9f3tb2HGjLheUmIlYBK7R36PkLuHlA6J6ql79gxUpxFplw5tqjmZ4DCVTaJYBdMvyvMC3fPrLymeDLrmdeXTzZ9GbFffyQsRaVsuHn4xf/jkD4CpqLTv1n38Ys4v+MWcX2Dbdsssokhywd+PCa3Km0R8C0srw6+HbBKTu0/2L94Jvq1RWiBBzejR8Nxz8O23ZhHo/v3maQYOjC2zf4iOJ8CaJ8AGFnwPjnmr/rZeN2x+AzqbAPOMlAyGlw3n002f+hdCg6lU4ucLAnHvp161Fys7XLDxZfC4YdlvYMgdDS/mcKSC56AJVqk97EpAVv1wju15LLcTWCx4XM/jGlfhJgFZt5tLVmoW9s+aI1W9tGUffginx/EzN3Fiw5USwiX1OKlPoMrk6I6jyU/Pj/2JE8SyLEZ2HOkPRAsOSBtUMogUZ80LKBwNBzfAzvnRP/iBteb/BcOir0YCsGO+qcaZYMHrT+fPhx49IiddSU01X2vxfB22JZWeMIEkYW4DU5HE6QydE40k2iomTe5QUOXC/KHU/RFvHY49Fj74wAwLP//cjMsaWuzqdkcfRAe0WDWIo3sc7d9uzcclR3Y7kpP6nMQ5g85psucYVDqIF897sckePyloPUXcju4Z+FvqWdACJ00iBQIpCCh+8RzDNcfxW+eTYe9SqNwJC2+Asf9Xf1vLAWXHwbp/QfUeWPUX6HNlw8EkloPCjMAERLiKJAerDwLgslzkp+ezbVMggd+RRzbcfYcDevUKjPkPO8x8TJtE5Q7wHcZ3OtnMi0QajjhSm650W4ejYM23sPPj6IJaggwrG4bH9uCxPazctZKueV1xWk4clqPeczFju4zFxsa2bVbuWunfHtcl/rmSuAUnRkzS6qwtJa5AEq/XiyfMEcKGDRvIyckJs4eIiIiIiLQLvS6FtY+ag86v7zcZyvpcBukdoWq3ub5nFdA2M+Z07gy//72pTLJ0KezebRaW9+1rTmK1JleNvoo/f/pnpvZtmjLcrV6nKTD1G/j6QVj5J7NIxCclH3qcD0N/0WLdSzYOy8HIjiP5avtX9Cvu19LdiVlZmal2cuut8KtfmZN2u3aZv+8hQ8zf/LBhsH073HefCSR54QW48Ub4zW/MY/hOYldXm9LIv/sdHH20mVtfuDAwlx4Nh8OcMHzoIbjmmtiDUBIqQZPYE7tNZO76ufQu6N1gKeNWLVLllnC3taNJSonDgfWAbcqcR8qgXcPhAKflxGM3vPojXAnyZNKnsE9U7fyZdkWkTQseXx5yH2JPxR7W7VkHmIWU+i6oy7Isju5xNEu3LY36O7W18QWSHDzYfM85qfukkOuZKZkMK4shW3t9WmhBVdeu5pIQXU6HtFKo3A5b3obFt8Gwu03ikeDFI7YNe5bAl7/2B5IAHNX9KD7dFAgiTXGkMKrjqMB+rmyz+GHvF9H3qcMxmNUcXvjqXugxA7J7h1/M4nXjX+lRuT18JbhGZtUPZ1SnUWSlZPkzrR7X67iEPr5IW/fhh/HNmUycGPsC7c65nf3bkSqtNofRnUYzb/08PLbH//3ptJwc3vnwQKOScbDhRajYBge+hawovvR9iXSyYkw+sCOGYJUYDB0aSPLy8ccm0VMkvny5Bw40b+WyZOKwHFR5qurcHu42MEEhsUzXud2wZUu8vYsg1vm1vR8EtiNVREtiRx8NP/uZ2b7pJnirgZhc2zZz0DEFkrRQNYg0V6B07hGdoyhPnmgJCqBxOpy8dv5rCe6cSPRSnamsuG4Fac4oy1E3BQUCtS+HXQVfPWDWhKz+O+T2hwE/DD3G99Ykwfrmbya5hM/SO6HbOZBaEP532VsNe76gKDNQaq68MjSQxGt7qXCb727LskwgyTbz21ddDWPGmKSfteok+DkcoYkyhg+P/JKrqyMHLDfMgtLJ0Y1FHE34t1wy0fybuffDjo+haEzU1dqGdQjMca3YuYLueeaYoNpbXe/81+DSwaS70qlwV7Cp3BxLOC0nozqNCtu+ySRjdZ8kElcgyfHHH8/vfvc7Hn30UcD8Me7fv5+f/exnnHzyyQntoIiIiIiItCLD74FDK2Hre4AXKrbAF7XLcCS4BGcSKi01GaJas4dPeZiHT2mb1WMSxpUJg283lwPrzWISVy7k9IntzFo7sfCKhS3dhUbr1s1UHKpPSYmpPHT99eb6gw/Cq6+agI8jjjABJPPnw7XXQl4e3HYb/PGPpu1vfmP2jWaBg9dr/n/LLaaqSe3vm+rq0KpIrcEZA85g7vq5bTdjeDQTlNAyk5TKwNN6+YIYs3vFtFtOSiZ7wmTwChZtZaCWMqhkUMQ2TsuJo72uChJpZzJTMumU08l/MnL93vWs3bMWt9cNwIDiAS3ZvaT17kXvtnQXmlRmplkYsHx58z1n59zOdMvrxvq96wETLO2qfTK+vQYXu7Jg5H3w0YXm+rJ7zNzR2L9DXs3fqOcQLLkdlv+hJmN4wIRuE7jvo/v810d3Gh2y8JD8IbD+P2Yx9KGtkNEhcp/SS6D3pbD6/0yVkTmnw8QXIbevWewCNRV2HaZCircmS/vuzwL3NzGXw8XRPY/m1RWvAnBsr1Y+2STSjFwuWLTIBAtkZUW/X3Gxmd+JR356Pnsq9nBinxPje4AEGlE2Ao/twWE5WLZ9GQ7Lgdf2hmYKLh4H1EwybXsPup/XcJURTwVU7zXbGZ3DZzA+sB72hvltO7geKrab794ESk+HwYNh8WITSBLNIWBmTR6Gr76KcaF9G2JhUekOU5HEXYmNjVUrTfbGjSY4JFobNgTmLxMqnvm104CzASeQGSZY6sB6kyk83Oc2iRxxBBQVwc6d8Pbb8NhjcMkldT/zXq+57Z574K67YnySFloE3qIVyFoogEakKRxWeFhLd0Hak8wuMOjHsPRngA2Lb4ENL8CYR83xOZhEDx9fbsaMfS6HTqfA5lnmd/eD78CkF4GM0PGn7YED62DJ7RSkF/qTYvmSK/j4qpEA2Njkp+ezdVvg/pEj6w8i8SkPOkUyYkTDgSeQgKR+uX2jTghmypbUklYMjnTwhhkHxXKOqCSoXMuXv4KjXo3QFa9/DqRTTify0vLYW7mXjeUbWb5zuT9pWXCQSTCXw8WYzmOYs26Ov/rd4NLBZKZE+14kSLJW90kScR0WPfjggxx99NEMHDiQiooKZsyYwcqVKykuLubpp59OdB9FRERERKS1cGXAUf+DT66ANf8wJ5JCMl5rMZ+0UU2QeVRap2uugRdfhDlzwOOBlSthypS67UaMCC2t/Pvfw/e+B126hJ+MrK4ObB95pHn8igo47ji44gp44IHAwohFi+C734VzzknoS2tSN4y9gRvG3tDS3Wg68UxQQtNPUioDT+tle00AI0BGJ5NuMsogxpKM/IiBJKM7jW5sD5vUiI7hy6QHy0qNYbWYiLR6g0oGhQSSrN6z2n+fKpK0T4cdZhbRrV8P+/aZaoLN4diex/L3xX8H4KgeR4XemczBxc2hxwWw5knY+q6ZK9r5Mbw2xCxAcWbAwQ0mIyZQe/5oQtcJIdcnd58c+tiFowLzTzvnQ6dTo8vyOfQuWPuUCWLZtxxeH2YWw/S9BlJyTeDukh/D2n9BaiF4q2D35yELKZraCb1O8AeS9C7o3SzPKdIWuN1mLuWhh0z2/mgDBoZEEVNf32NtvHEjB6oOUJxZHL5BM/IdM3ltL+v3rsdre0NuB8x3p+UC2w0rH4GeFzb8oAe+DWxndgavJ3QS68B6eKVf+MVtAGuegH43NJzx2FvdcDBLGBMmwBdfwJIlZkFgTk7D7QcNgm+/hc8+i+lp2hTLsvwL+YKFuw3M+xWL9evj6VUU4plfK8SsxbScdQOZGvrMBlcgTwKpqSYw5NprzfWrr4ZNm0ylbF/wiNcLhw6ZOeavv44jkKS9UhUFEZH4DLwFvv2vCRixPaYC3WtDA2M5b82JzYKa8eeIe2FTTfWmre+Z3+Axj0KX08xttge+ut8Ep+QOoCC9Nw7LYQJJqkIDSYIrlHhtLwXpBSzdFgh8HRZFcditWwPbI0dGPl5odM6qguHRt/VWQu3TPVnd4LTlJhAHzFilao8JIikZF/1j5/SB1CKo2gmb/gdb3oXSieHH4F4PVG6DDBNQaVkWw8uGM3vdbLy2l693fA2YYJGG5l8ndJ3AnHVz/NeP7HZkvW2lZcQVSNKpUycWL17M008/zaJFi/B6vVx66aWcf/75ZPhqRYu0Ei6Xi8suu8y/3VT7JJv2+rpFREQk8eqMERwOGPcE9L4cVjxkMktU7zUZEsqOwdXju1x21FiwrKQZU7TXsVE8ryE9PZ3TTz/dv53o9m3hfZX2zemEl1+GE04wmRDry77ncJhEZlOnwmuvmZN8555rtrOzQ8sjezywbp2LxYsv46GH4OyzXYwYYR7btuHRR+GJJ8zjHTjgS6DmYvbsy3jySf0tSQOUgaf1qtwRWCyZ0RHsarBqpcuqJxNsp6wSVu5teBVIz/yeieppkxhYMjBim+KMll+8Jckt1nGnxqnJbVDJIN5f+z5ur5t1e9b5g0ocloM+hX1auHfSEkaMCCwg+OwzmDSpeQpHTu4+2R9IUifYIVmDi5uLZcGRz8I7R8GepWYs48s2GsJRJwikJKuEnvk9WbNnDWAqlIQoHBXY3vWpyXQajYyOMOr3JiEKmECRpXeaS23OTKjaDZ6DsP8byGmejL/BVUisxn6Ii4tNYFKsn8P0dLOvtGltYWzk69OGDXDXXaZP991nFlXn5tb3O+BiyJDLuO46cLtdDBli5mHiyTicmZIZNrNuS7y3/Yr6keZMo9JTydYDZpWcw3IwtENQxSdnuqkAtXuRWfi35R0onVR/IEdF0ML6zC51q5FU7qg/iATg699Bv+833PEYg0gAxoyBP/3JbD/8cOTAodGj4a23TNWMvXtN1eDWJN45/VFHj+In7/2ECipw4qTKU7eccZWnCq/txcbmUR7lg0s+wOVysTnGmIrghZktrhATn5reIbbPbNWeJu5Y7C6/3FTAXrPGBMr97Gfwyivm9oICE/Bz//0mwGRE5PwbIiLSGsRzDBfP8Vu8leuPeQvemgj7VwXOV3irQ9v6fn/zBsKAH8JX9wE2VGyBOVPNb3RqoQmMqN7j3y0/Pd+/XeGuwGt7cdQkdNhftd9/n9f2kp+ez6ZN5pxp587Rje82bzZjfo8HBgxIQKBIEP94bdNruFbUTE7lDmwwaNplubms66Nmm4upG0lCYhJbWhb0vRq+uBvwwseXwnFzzPxIcMC3t9pUJFxyO4z9P//NIzuOZPa62QDsPLQTMMceKc76x/Hjuoxr8Lq0vLiP6DMyMrjkkku45JJLEtkfkWbncDjo3Llzk++TbNrr6xYREZHEq3eMUHqkuQB43WaSwLJwAMk2omivY6N4XoPL5WL48OFN1r4tvK8i2dnw9ttw553m5J1tBxYgeDxmMvK73zXX77zTBJ4AzJ8PgwfD00+bhW4+jz4KN97oYMCAznTubCZBn30Wpk83jw1QWQlr1wb3wkF5uWnfpJprEltEQgVnxszoVPf+BrJq9swqYHYDD+1yuHAk8qxJE3A5XP6y9vUpyy5rxh5JaxTruFPj1OTWv7g/bq8bp8PJ8p3L/QvjuuZ2Jc2V1sK9k5YQfBi6cCGMG2cyOTe1Sd0DA/lRnUY10LKdSs2DY9+Fj6+Ab58LZMIHzCpP2yxOPvyROrse3eNo1iw2gSTju44PvTOtCDI6w6GNsP5ZGPqL6PvU53LYvwaW/bqBRg5wZZn+Aez4CLJ6xLXgOVYDigdwx6Q7OLrn0Y1/sG7dTHUb3wIhn82bYc8es52fb7IUBPMtEpI2rS2MjXx96tTJZCH+/HPzcf/+900CDl/Wfh+3GzweB4880plNJgaVQYNMu3gCSSL1q6nah+N0OBlcOpiFmxdS4TbHhb0LetcNdOkyDXYvBryw4Go4eanJPFy7qpPXDVveDlzP7BZd5Sc/y3xHf/lrGPzT8FWdvG7YNgfKjonhceGIIwLbDz5oKjbUF1/hdkNpaSDYdOFCOPro5gk2TZR45/QHDB7AkveWAODESaU7fEUS27axsdlibaF7l+54vRa7d8fWx61bzXvqm7dsUSWYIUZmcn1fxSM1Ff75TzNvXF1t3t9PPzWX2hL5HSYiIi0o0jFcIo7fGlu5/vh5sPD7sO7p0GN833bHkwL7DbvbJL/a9BpQk4mvYqu51JKfnu+vqmdjc6j6kL8KeXAgia/tli1mu2/f6F721q3m2MDjSfwpS/94rXy/eRLbA3kDqF19NWQfy6Zzes1ByaFvm3a+od8N8NUD4DkAB9aaarFH/BW6nR1os2sRfHCOCfIJMqxD3XIvkSrcj+0yNuT6uK4KJEk2cQeSrFixgvfff59t27bhrZVe84477mh0x0REREREpA1pqFy9iEgblJkJ994L111nMsMtWmROoI4aBaedhj/AY8QImDED/v1vM1m5aZM5gT14MBQWmkxy33xT9/GnToX//hcuvhj27zf7+jgcZtHDqOZYt9Yck9giUtehTYHtzM5g1Tqp0EBWzdM6Debxle8AUJhRyOvnv86/v/g3D85/EBs74qR/sshNy2V3hVnNku5KJ82Zxv6q/f7gkt6FvVuyeyLSzPoX98fGxuP1sHzncv/tg0sHt2CvpCX16mXG5AcPwuzZcOONzfO8PfJ7+LdTnc0QudIapRbAxGdN5vu1/4Qt74K30iyq6HIG9L4EXHUz+k/oNoH/W2yyYBZmFNa5n6IjYMOLsG95TVb9yfXPR9XOAjrsbsgog89uMZXe/MGqNcEt6aUw+k/w3vHm+pqnoOeFDb9O2xt+oXSMLMvirqPvavTj+HXrpuMxafMsC37yEzjrLHP9H/8wlWCffNIsrvZ6TaDB9u1w0klQXh7Yt3Pn0CqxrdnhnQ5n4eaF/utjOo+p26jv1bDsVybbcPkKePdYmPwyuLLN96TtBSyz2G/Nk+Z7zfZCVtcYe1MTUfDlr00VlC7TQqM3bA/s+Ry+vDvmQJK+fc1l5UqzIPDHP4bf/75uO9/c2XvvBW57802YPLl9LLrPSMkIuV7pqRtIUuGuwK75t0p1pmJZFtu3119xuT7btpm/serqyG2bXHbN/zO6NO3zxJvJPUZHHAHPPQfTpgUWv9bmdEJWVswPLSIiyaqpj+EaW7k+vRgm/Av63wjfPg+7FgAWFI2BrmdA4cjAfo4UMx8w/xITeIIDf0AJ1FQvsaDf98nf4wlJJLW/an+DgSS+n+HS0uhfttdrfjMzMiK3j0vlDsxr9ED+sOgDsfcua6IO1UgrhCE/hcW3ATZU74V534GCkWacX7kDdnxsAoFqB5KU1Q0kCRdcEqwkqyTkes/8no1+CTFTYsQGxbWa669//StXXXUVxcXFlJWVhZTRtSxLgSTSqng8HubPnw/A2LFjcUYxSxDPPsmmvb5uERERSbxYxwjJOKZor2OjeF5DVVUVzz77LABnn302qRFSusbavi28ryLBunaFq69uuM0f/2iqkaxbZ07+eb0ma2Ywp9PDYYfN54MPAn8b06aZGI577zWBKBs3mhOIkybBd7/roXfv0PZNRguRIotnghLa1SSlxCi4Iklm15jSpw7KD2ThLK8s5/BOh/Py8pdxOVzY2AwuaR2Lrk8+7GSe+eIZHJaDm8ffzF1H30WP3/Vg3d51AJwz6JwW7qEku7ZwHCMBA0oGACZD4erdqwFwWA4GlgxsyW5JC3I4TDb6jz6C114zCxqjXUzQGJZl4f6pO3JDgbJjzSVKR3Y7suEGxUfAxhfNWuUlP4YpH9ff1qr1HW6ZhSp0nmoWSm96FSp3QVY3s/ClxwWmmkp2L9j/jcnKX/4NZPeo+1girVRbGBsF92nq1LEMGOBk+XIzz/Lss/DxxyaZR5cusHQpPPMM7N/vYcqU+ZSVwccfj6VTp8S/jpZ6b0d2HBlyfUTZiLqN0orgsKth+e9NMMf2efD6CJOluOxY81249in45m+QXoZ/sV96h9g6k5JvFqh5K2HumaYqyYAbISUPPJXmu3fh9yG3f8yv07Lg5pvhssvM9T/8wQQx3H+/CWRISTH/r642i++3bzfVhPfvh8cfh1/+suHH9z1Gsoh3Tv/NF99kBjN4FjNX76vgF8xXpcSJkwlM4IMPPiAjYyxQ9zn69IHu3eGdd+o+39atTVSNJJ75NV/XM7uYz3hT/G43NpN7jE47DebNg/PPhzVrzOfdV3HJ7TZzw//6V8wPKyIi0jhFo80lEme6CTzpfh6sfNgcX9tuE8jc5XQY8CMoGEbBV8+H7La/aj8d6ODfDpbtKmDfPrNdWmrOtUYaIm3ebNp1iHFYGw3/eO3bQ4y1LZyW08wnNLSP7WT+HlNqb6xzaZjRV4L1+wFs/B/s+DCQTGP3InMJVmvsNKB4QJ1q8eGCS2rrX9Sfr3d+TX56fki8QbMJlxhR1Vn94gok+eUvf8ndd9/NLbfckuj+iDQ7j8fD22+bMqyHH3541IsGY90n2bTX1y0iIiKJF+sYIRnHFO11bBTPa6iqqmLVqlX+7WgCSWJp3xbeV5FYFRbCG2/AuHGwe3d9meQ8DBz4Nm+/Hfq30aGDOTF+//1QVWVOHDocUFXl4de/1t9S0ohUuQVaZpJSGXhar8odZgLf9kBGp5h27ZpV5N+u9lZTXlXOtgPb/FlHu+W1jonxrrldcdRk+d52YBsAOw/uDNyfF2uGXGlv2sJxjASUZJaQk5pDeVU5Ww9sBcBre+lfHPtiRGk7Ro2CTz81C0B/9zv4xS/qX0jgW3yXCM76MkwquLhRDis8jIuGXsS0AdPCN+gxoyabJrDzE/j6Qej/g/BtVz8Bvb9b9/bsHiYr55Cfht+veAIcWGcWuSy5DY78T/h2thcqdkBGM0QviSRIWxgb1e7To486mTw5cP/69XDPPaH7pKR4GDPG7LNgweGUlDRNIElLvLcjOo5o8Lrf4J/A6sehag/gNd9zi8J9f9qAZSpLOWKsutXtbPjmr4HH+eLnsOweczxbuR3cB2J7vFrOP99UItm+3QQwPPAALFgAV15pgh0WLYKHHjJVS0aMgOHDzUL8rVtNpZqZM82cWjjJFEQC8c/pr1u9jr70JYUUqqjyB40EO+Q+BIADBxPdE3n77bc54ojDqR1I0qePeU9zcuCmm8z7HWzLFhPQkHDxzK+tPAY8eyElt6ZaWBN8VzU2k3scxo0zRU7eftsETe/ebRIaTZ9uqpa0xPpMERGRmHQ5zVy81eA5ZAJJgqp65qfnhzQPDh6pHUjiPRComhFtIMmmmqLvTRVIYsZreRzeG5yZRfVXTPXtYzt4e8cJAByetwDnwY2mGn1TcabCpBfhzXEmYYYd5uS05QRnaJmzNFcafYv68tWOQLW1SBVJAIZ2GMrXO79mYHELJv1RYsR6xRVIsnv3bs4+++xE90VEREREREREpF3q0we+/BIuvhhef90sYnM6zUlXy4Jrron8GBHitKSlJeMEpTLwtF7easAyJ1bSCiM2D5bpSiM/PZ89FXsA2Lp/K1v2b8HtNas8Wk0gSV5Xf5+3HdxGpbuS/dWBE0hdcxVIItKeWJZF/+L+LNi0IORk8oDiAS3YK2lpRx9tFo2CyU5+001meFN7MYHbDfv2mQDvJpWswcWthGVZPD798fobZHaBrtNhw0sm0GPRjWYxyqAfQ82YAYcLlt4JG14OH0gSSe+LYe0/zPb658yl6xkhi12wPeay9E4Y83DszyEiCXPkkfDgg3D99fW3qb3YuqgofLvWaHBpaLXJ4WXDwzdMLYBJL8A7x0CDVSRq3qxYg0gASiaaypqbXw8sUvNWwYG1tZ4ivkX+6enw29/CRRcFbps711zCOflk+PBDE0h6550mECXcgkO3G957D44/Pq5uJS3btqn01A0kCRdcsnNnnZu46SbzngPccQc88ggcOhS437cws7acHCgvj6fHQWKdX/sG8ACOFCJ8wFudtDQ45RRzERERabUcKTW/06FqB5KUV5WH3Qao2hdoG2012q0mD02TBJKEsiEtjuQge5ZCRsfQ+YZESyuEEz+FBVebKoSWE1OB0DbzKsUTwibQGN1ptD+QpENWB4oyIx9End7vdP6z7D+cOfDMBL8ISYS4AknOPvts3nzzTb73ve8luj8iIiIiIiIiIu1SaanJILdyJbz8ciCT3BlnQF4e/PrXLd1DaZOSMcBFIrPd+DPBxrHQpktuF38gybYD29hUHljl0VoqeXTJ7eKvorK5fDM7DgYW5aa70uucaBKRRlq/PnTx+1df1W1T+7ZmXvw+pHQICzYtCLmtX3G/Znt+ST6nnWYWBO/cCQcOwKmnmqzN6emBhaJuNxw8CNddB//8ZzN0SmOvpjXgh/DtfwPXl9wOa582wR7Y5r69y6Cgnqz8kZQeBdl9YP8q83gfnAtj/w49Z5pgFcsBniqYMxUqw6y8FZFmd911UFkJt95qgkaCq8A6nZCdHbiemQkZGc3fx6aS7krHwvIfNxVmNBAxWTrJfJ/NvwSzcKx2RmKHqehQuSPsQr+ILAeMfwreGBMh43Fm7I9dY+ZMU/H3mWdMgEhDvvtd+GlN8an1682Y4eWXzfXgMcInn8Bdd7XBQBJsqjxVdW4PF1yyY4dJeON7T3NyTMCOr1JLbi6ccw48/nhgn23b6j7nzTfDb34DTz1l/q2ajV0TTGq52lociYiISJuWlRJaCePM/5xJhssM1ssrQwNJyncFBvElJfVXmvPxemHXLrPdoUNiq9SGFU8gybbZUHa8P5a7yaTkwPgnYcjPYP2zcHADpBaaRB0FI8KWORvWYRhP8iQAIzuOjOppZgydwYyhMxLadUmcuAJJ+vTpw09/+lPmz5/PkCFDSKlVy/H73/9+QjonIiIiIiIiItLeHHaYyewXrKruuV0Rac+81eb/VhwLeIBeBb34ctuX2NhsO7CNrQe2+u9rNRVJgiqObNm/hW0HAitVOmV3wgpzgkNE4rR+PfTrBxUVDbe74ILQ6+nppvpCMy2a71/cP+R6YXphwwsmpc1LSYHLLzcZyj0emD8fjj3WLGDs08e0+eYbmDEDbC0sbBuKx0KXabDxlcAi5b1fmEsiWJYJVllQk2zR9sBHF8KKh6DsOKjaDeueMf+PN1hFRBLKsuBHPzLVSX77W3j1VaiuNovhZ8yAH/4wEEhYHMf6rmQ3oHgAy3YsozA9ijFRz5mQOwA+uRJ2Lwrc7kiH3peahfgrHzb/j0dqHkz5BD6aab6nLZdZ5G85zfdp3mA48pn4Hhvzb/3oo2bo+sEH9f+2z5gBZWUwdSq88ooJGHnzTZgyBX7/exg2zMzDPfmkqWbTt2/cXUpaXtsbNmikwl13vL9zpwmu8QWSjB8fGnDl8cAJJ4QGkvgKrfkUF8Pdd5vtCy4wFUw+/LBxryFq3prxQDwBUCIiIu1BcbGZw4s07xcsPb3JB88uR+iYM3j+v7bt2wPnAjp1ihwUUl4eGNt06GDGM1EFkkRKtOO77naH3l5fIMmB9SZQe2+YhD3r/g3DI2QY9LpN5dVEyOkDg26LqumwsmH+7RFlmvtoC+L6FD366KNkZ2cze/ZsZs+eHXKfZVkKJBERERERERERERFpKr6MmnGeJOie1x2Xw4Xb62bbgW3sPBjImN0lt0sietjkgiun7Di4I+REUo/8Hi3QI5E2bMeO2E4m+1RUmH1bKJBkQMmAZnleSW7XXgv33Re4/vHHZkHo0KFm0cDSpeb2ETrv3XaM+Sv8b5BZjEF9KekbkWq013dh2W/g4PpAsMrOT8xFRJLWuHHw/PMmQODAARNI4nKFJu5oi4Ek/Yv7s2zHMg4rOiy6HYpGw0kLzWK2vV+CM8NUK0nJgYU3mDaNWayWmgeTXoIdH8Hap2D/WkgvgW5nQ8cTG70QLisL3n0XbrkFHnrIBA35qmnk5cH998Oll5q2t9wCL7wQ2Hf2bBg+HAoLTbWyeIa/rUm4oJFKd/iKJMHGjjXvqy/fsMsFEycG7vd4zOLMYDNnBpJZV1fDZZc1YyCJvwxJmGQTacUmUMob5h87u1eT9kpERCRpdOtmEsEE/+hv3hyIDM3Ph44dQ/dphirEwYmkGuK0nGzbFhjzlZVF3qe6OrDdoUOUyUWiSbTjS7KTkgK33x64Pa3YPElw8qsD6+GVfkHjkFpBrwfWwPYPoWhM/WPkRAWRxGhYh0AgSXBQibRecX2S1qxZk+h+iIiIiIiIiIiIiEg0vG6zBiLOTLDd8rrhtb24HC6+3fcth9yHACjMKCTdlZ7AjjadoowiUp2pVHmqKK8qZ/P+zYA5cdQ9v3sL905EWkLtQJLBpYNbqCeSTDp3NtX+7r03sDDAtmHJkpbtlzSh9GKY9AK8NwU8hwLBHj6WE1xZ8T++MxUmPANvjmu4neWM/zlEpMmkpppLOCUlzduX5jC4dDDPf/08/Yr6xbZj3gBzCVGz8K2+lXbRLsq3LCgZby7hRJvp2afWQsaUFHjgAfjJT0zFkZ07oUcPOOUUSEsL7HbEEaY6yb//bYIffHbtCt+tJhdvhus4hQskqfZW17lt587Qpxw3zlQoCdalC5SWmu29e+t+RM49N7BuMiUFzj47ENDT5Hy/x3aY9y2rG5y2vCb4FDi0Gar2mM9rSYTfeRERkbakW7dmSwQTrVRXPYP2WlKcKVRUBAJJiooi7xM8tikpMYGxEcWbaAdqAkncoRXmK3eEHzcD/uQXX90Lk14M38S2oWIrZEQROZNgJVmBA6fgoBJpvVomJElERERERERERERE4mO7TVLNODNOdc3tiqdmUeX6vetDbm8tLMuiU3Yn1u5dC8DaPWtxWA4sy2pVr0NEEqdnQU9/tSWoG1gi7dddd8FLL8HKlaELRYPVXhAprVzJeJjyCcyZDuXLA8G3thty+sG4Jxv3+MVjYNSDsPD68PdbLkgtbNxziEiza4uBJHcdfRd3HX1XYh7MkWJiScIEGwChi/J9C/IhtkX5sWR69klPN1m0ay1+LCyEiy5q+On+9CdTwWT79vrHCFaYQhYJF2+G62+/hd6943rKaCuSbNsWCAyxLBNI4ghT2OuII2DDBhN4EszlgmHDQvfJzobDoiyS02gNBZKA+dxmNXLhbHGx+RzGsrg0Pb1tlkESERFJIIflwGvXV2nUSHel466pMpiWZsYZkQQHkqSmhh/bJJSvIknUal7zxldg21woHlf3XJBlwVcPwMh7E9bNePQp7NOizy+JEfWZxhtvvJFf/OIXZGVlceONNzbY9oEHHmh0x0Sai8vl4qKaGQRXVOGF8e2TbNrr6xYREZHEi3WMkIxjivY6NornNaSnpzNlyhT/dqLbt4X3VaQptIXvWhGJIJasq9u2m//HmQm2W83Xgsf2sKl8k/+uXgW96rZPYj3ye/gDSdbvXY/DcuD2uumap0ASiUy/rW2Py+GiV0EvVuxcASiQRALS0uCFF+Coo8xPbe2Foi6XWWwqbUzeADj1K9j6nrlYFnQ4FkonJWZVcL/vQ2oBfHwpeGs+VJbDLFTNGwjjnmr8c0jrEmk8H+62WpUUWlJbGBvFO8f74osXsWcPnHWWC7c7yozETdivZHxvARMkZ1P/gnxo/KL8eDI9V1SY/eL4W8rPh1mz4LjjYPfu8MEkNVPbTSuG1+1yu7no8cfN9qmnRrWPb47+vg/uo2K/eZ6wFUk8JkjIi5cNPTdw+6TbeeaZwGewVy/Iza37+NXVMGZM+ECSgQNDK8H4jB4d/msy4XyLLr3V/qI6CdetmwlmCv4N2LwZ9uwx2/n50LFj6D5J9P0vIiKSrFwOF1WeqgbbZKVk4TlkDvNzcqJ73OAxX0pK/e3i5XK7ueitx+FicFluSCsy8wUN7WO5uajz42bb5TJjF9sLs6fCiZ9AVk8zrrG95rEW/xi2vp34zkfp3uPuZdn2ZTgdyszSFkR91PnZZ59RXV3t366P1Szh+CKJ43A46NGjR5Pvk2za6+sWERGRxIt1jJCMY4r2OjaK5zW4XC7Gjh3bZO3bwvsq0hTawnetiDQg1qyr5wEn0nBGzQYywXbbt9Hf1BdI4rAcdM/r3qiX0dy653fHWmdhY7O5fDOemkWcqkgi0dBva9s0pHSIAkkkrP794ZNP4IwzYOFCs0jYts3igVGj4MlGFqiQJGVZUHaMuTSFnjOh40mw+m+wezE4M6HbWdBxSsRFItLGRDOeh6grKbSEtjA2ineOd/36HuzaZf45vA0nPG6WfiXjewsEFuQ3FEjSCg0bZsYIl14K770XuD0nB370o0Dxj2ThsG16rF1rrkS5Pss3R7952Wa8+82HvMpdd1FmdU21GcthQT706NEjJDaib996+uQIVBjZtSv0vlGjzJgruKtVVeb2Zgkk8VUl81QCTfjb3K1bUnyXi4iItCVpzrSIgSQ5qTn+CiPRxmAHVyRpikASh23TY+9ayKy5Ia0kYnV5h2XTI3OtuVJ8FGyfZ8bd1Xvg7ckw5C7oegZU7oRl98Dqv0PBiMR3Pko/mvCjFntuSbyoA0neCzpiCt4WERERERERERERkUaINeuqb3GTN75MsGXZZTgtJx7bw/aDprqJbdutrpJH19yuOCwHHtvDlgNbsDEVWlrb6xCRxBlQPMC/3S1PC7kkVLdusGABfPghvF2TtPGEE2DcuJbtl7Ry6cUw8JaW7oW0tHiqKECjKilI4viCR5xKptswq2aVXfX+lu1HE+jZE959F5Ytg8WLITPTVCnJzm7pniVWVkqWf7vCE6YiiS+QBIuMlAxsO1BUA6B3b/P34qgVj+F0mqBdqFuRZNQoU7EkNTVwW2qqqWDyVHMU7/It2qzYHHEBp4iIiCSXrJQsyqvKG2yTk5bjrzAS7Xg+OJCkyY4BgsdL6WWx7dvhWNj2fuD6oc3wyRXmItIENEqWds/j8bBw4UIARo0ahTOKX4d49kk27fV1i4iISOLFOkZIxjFFex0bxfMaqqqqeOmllwA4/fTTSQ0+A5SA9m3hfRVpCm3hu1ZEEshXej3OTLBOh5MOWR3YtH8T5ZXmRIyN3eoWXXfN64rH9mBhsf3A9sDtqkgiUdBva9sUXIXEoWoAEoZlwYQJ5iIiIgFtYWwU7xzv4MELqawEp3MUkPjX0RbeW6BmEb4NnoNQXQ4pOS3do4QbONBckpnH4WDhqFEAjPJ6o/rE+uboB24fyHu8hxt3nYokbq8br22iqhy2g5ztOcyd+wleb+Dvolcvs/Ay3BR/z57m/7t2mUATX4DW6NHh2w8fHkXHE8GZYf5/cEMzPaGIiIgkSlZqFhxouE1+en7SVSTxOBws7DMK9sCovIU404oi72M7WLi3ZoyX2QNnxymw5Z02Vw1QklPcgSQLFizg2WefZf369VRVhR5gPP/8843umEhz8Xg8vP766wAMHz486gmlWPdJNu31dYuIiEjixTpGSMYxRXsdG8XzGqqqqli2bBkAJ510UlSBJLG0bwvvq0hTaAvftSKSQP6KJA2XdW9I9/zubNq/iUpPpf+21hZI0iW3C2CCYPZV7gNMlrKctLa3oEkST7+tMSguhvT02DOtp6ebfZtRcCCJiIiIRK8tjI3ineM97jizj9M5nKYKJGnt7y0AKblg12Q1OLS5TQaStAYep5PXTzkFgOExBJIsW7aMAgpIJ5397Keq1nxClSdw3YmT1DWpvLfmdZzO4Xi95ln69Kl/gWZuLuTkmIokTmcgkKRXr/Dts7PNPk0usxvsXw0HNzbDk4mIiEgiRTPPX5hRGHNFkuDqar4xSyJ5nE5eH3oKbIfhuYtxOtMi72M7eX17zRjPY+Mc9Uf4X4QIZ0t1JCQx4vokPfPMM1x44YWccMIJvPXWW5xwwgmsXLmSLVu2MH369ET3UURERERERERERER8fBVJqvaA112TGTY2vQp68dGGj0Jua22BJMGVRw5WHwSgc27nluqOSNvVrRssXw47doTevnkz7NljtvPzoWPH0PuLi82+zahfcT8AMlMym/V5RUREpPVLlniNpJXZBbDN9sH1kNu3Rbsj8XFgVk4GB44AVLoDSSZs379zLX37hi68rK1LFxNI4pOWBiUl9bfv1ClyfxstqztYTjikQBIREZHWJj8tP2KbksySmANJggNjq6uj7Ey8iXaAuILVcw+Dob+EJbeGv99ygisrjr6I1BVXIMmvfvUrHnzwQa655hpycnL4/e9/T8+ePbnyyivpWPtEgYiIiIiIiIiIiIgkjhuwAGyo3AEZZTE/RHAQBoDL4aI0qzQh3WsuXfMCr8FTkxm3R36PFuqNSBvXrVuzB4XEIzs1G+8dTZBKUERERNq8hhbIC5ARFLR/YD14q8GR0nL9kbhYZjKhbiBJULVSrx1+PN29e8OP3aULrF+PfzFnpMOHZgkkyewMOMB9AKrLVUlHRESkFSnIKIjYpiSrhD01cRq+MUgkcQWSREq0E5xkx+2GmgqDAFhxHmgMvNmc//n6PsCBv1S95QRnFox5NL7HFaklrkCSb775hlNqSiWmpaVx4MABLMviBz/4Accccwx33XVXQjspIiIiIiIiIiIiIjX2EUhidWhzXIEktauPdMzuiCPeExotJC8tjwxXBofch/y3dc+LsLJFRNo8y7JaugsiIiLSCrndLd2DJJcZFEhyaCPUU7WiUeLJ9JyebvZrzeLNcF1UFPdTVntCV00GB5Z4qRtIUlpqulgft9sEhixcCN6a3Xv0qL+9x1O3oGGTyOwCds0f96FNkNKvGZ5UREREEqEoI/JYpyy7jPJGBJLEdAwQbaKdqqpagSRxlj60LBhxLxSPhc9/Cvu+MkEpPS6EIT+F7J7xPa5ILXEFkhQWFlJeXg5A586d+eKLLxgyZAh79uzh4MGDCe2giIiIiIiIiIiIiATZE7R9YB0UDIs5q1XtQJLWWMnDsiw653Rm1e5V/ttqV1oRERERERGJRrQLz9qttFL8mZAPbgQrruVGDYsl07NPcXGrqJzXoHgzXHeN//i32luNbdv+IOxKd2WD7SNVD/F6zT/F9u2B23r0ANs2ayBr83iaqSJJRhf8QU8H1kKuAklERERai5KskohtOmV3Yk3NsDTaoJDagST1jVcSpjEJvCwLup1pLu6D4EgFRxOMw6Vdi+sTNXHiRN566y2GDBnCd77zHa6//nreffdd3nrrLY499thE91FERERERERERESk7Yo1++juoO1Dm0x2TSs1pqesHUjSs6B1Zq/qUdAjNJAkT4EkIiIiItLM4q0m0BYqKbQhCiSJwOGE9FKo2AIHN0S3IM72xJ6BOdpMz21NvBmuY2QHVZKp9laT6jRzCZWehgNJIlUPcTqhpAR27Qrc1r07VFdDapjpCpermQJJMrsEtstXQYdjwJHSDE8sIiIijVWWFbkSe9e8rjhjrEjiDBqe7t1rgklSmnJ4EG9FktpcmYl5HJFa4gokeeihh6iomQS57bbbSElJYd68eZxxxhn89Kc/TWgHRURERERERERERNq0WLOuevbAypqEPhWbgdjTZdUOuGitlTy653UPud5aX4eIiIiItGKRxvPQdisptCHNEkiyeLFZQf/VV3Xv890WbSrllpDZxQSSlK+Mrr3tTdzCOUmI4ECSKk+VP5CkylMVtr2jJl6oLMI6Tl8gSXA8XY8egf3DPW6zfP0FB5Ls+Aj6XtMMTyoiIiKJ0Ck3ctRp9/zu/goj8VQk2brVVCRpWt66N6UVgyMdvGGSEWT3aOoOiYSIK5CksLDQv+1wOLj55pu5+eabE9Ypkebkcrk477zz/NtNtU+yaa+vW0RERBIv1jFCMo4p2uvYKJ7XkJ6ezqRJk/zbiW7fFt5XkabQFr5rRSSCWLKu2jasSgG7Gg5uAiv2v/O8tDwyUzI5WH3QPH1e61zAVjtwRBVJJFr6bRUREZGEauVVFNrC2CjeOd5XXjmPffvgrLNcWLHH6EfXr+OOgyuvxPXzn4M3zEIygAsuMO0dDs7r3RtSUnCNGhUo21A7+KT29eYITMrqDrsWQvkKqNoLqXkNt1flh4RrzJz+wk0LObjqoP/2Sncl2anZ/m0fDx4GHTOIlfOG4vWa5ygrM9VFGsrW3aFDaCBJ166hCzVrKyqKqvuNk1YMVs38yfYPI7f3ekz1HREREWlxQzsMDbk+97tzWbd3HRc8b8bNTstJfno+Tqc5ZVJeHt3jZmUFtrdsCa1Qkggul4vzju0EX/0Wl+UxwdV1OtENTlsOlSYZgevAJs7rvgnSy3CVTUhsh0QiiPqIft++fVE/aG5ublydEWkJDoeDvn37Nvk+yaa9vm4RERFJvFjHCMk4pmivY6N4XoPL5eLoo49usvZt4X0VaQpt4btWRBLIsiC9BA5tMpdoVjvVWgxhWRZdcrqwYtcKoBUHktQKHOmS26WeliKh9NsqIiIiEtAWxkbxzvFu3NiXLVtg9+7ELyLz9ysjA778Mrr2Xi99V9ZU/DjttPob1gSe+KWnm8o4TRlMktnFJDKwq2H7POh0oiqONLPGzOmvX7wez6pA6Z1KT2XYbS9eOvfozBfvBJ6ntDRytu68PKgMPIw/Bqo+2dnR9b9RLAvSO8ChDXBgDVRsNdfr1eQpyUVERCRKZdmhJdEOKzwMO2hAkpdugpp9gauVlbB/f+QxRlqaabN/v6lIkuhjAIfDQd+uebC+Zkxv11P6MKubuQCOwpH0VY4saSH1FBGsKz8/n4KCggYvvjYiIiIiIiIiIiIi0oQyOpv/718V5Q51s171LOjp326tgSTBgSMZrgwyUzJbsDciIiIiItLaOGpWzWzbFthulSoqYMeOpn2OjM74jy23zYm85v7At03bH4lJRkpGyPUqT1XYbV/bQ4cC14uLI/99ZGSYqiU+JSUNt2+2v7esoFWZG14Bb3X9bR3JUWFJREREIDs1G4cVGDDsr9rP/qr9/ut5aSaQJCMjUPQv2uFwcbH5/9atCelqXcHB1uEqkogkkahHwO+9915T9kOkxXg8HpYuXQrAkCFDcEYRYhjPPsmmvb5uERERSbxYxwjJOKZor2OjeF5DVVUVs2bNAuDEE08kNTU1oe3bwvsq0hTawnetiCRYVjfY9SmUr4LqfZASoUq0I6XOTd3zuvu3u+a2znRXwf3unNO5BXsirY1+W0VEREQC2sLYKN453iFDllJaCjt2DAES/zo8Hg9Lv/0Whg9nyOef4/Q2vJDM43CwdOhQgKjaN6vMzoGMyptnwYjf1N/WWw3bZkPPC+pvIzFrzJz+tj3bcOHCjRuASndQRZKgbQcONq/cjMcDDof5uygtDWT7rk9wNRKXy1QoSQrZfWDnJ+azu/EV6HNZ/W0PbYOM0ubrm4iIiNTLYTnITs1mX+U+oG4gSWFGIWCCV31D5q1boUePyI/dsSOsXds0gSQej4elq/bCvuEMyfkcp+2Obp8kO76S9iPqQJLJkyc3ZT9EWozH4+Gll14CYODAgVFPKMW6T7Jpr69bREREEi/WMUIyjina69gontdQVVXFZ599BsAxxxwTVSBJLO3bwvsq0hTawnetiCRYRkewXGBXw46PoexYsGJL5xlchSQnLSfRPWwWXfMCgSQ98nu0XEek1dFvq4iIiEhAWxgbxTvHO26c2ec//xlIUwWSvLR4MUybxsAvv4wcSOJ08tK0aQBRtW9WWYGqluz5HA5tNsem4ThSYPs8BZIkWGPn9FNJDQSSeIICSYK2nTj55N1PyMkBh8P8XXToELlvwRVMIlUjaVbFR8Dap8z2lrfrT8bhdcOWWdDzwubtn4iIiNQrNy233kCSoswiAEqDYkA3bTJBJZEqn3XuDJbVdIEkL839FpjGwOwvcXqjCyRJtuMraT/iLhS4e/du7rvvPi699FIuu+wy7r//fnbt2pXIvomIiIiIiIiIiIhIOBmdANts7/gokBW2PhXb69wUHEjSWmWnZvu3g4NKREREREREYrFjR0v3oBUoGG4SGvise9osvq/N9kLFDti9qNm6JrGr8lSF3Q7mi2MqLo78eMGBJEVFjelZgpVMwD9/4jkIS34Ctl23nfsAfPP3Zu2aiIiINKwgvcC/7QskcVgOHJbDX5EkOJBk2zZwR47boEMHU0Ft507wRDi10mhVu5v4CUQaJ65AktmzZ9OjRw/+8Ic/sHv3bnbt2sUf/vAHevbsyezZsxPdR8AErsycOZO8vDzy8vKYOXMme/bsaXAf27a588476dSpExkZGRx11FF8+eWXIW0qKyu57rrrKC4uJisri6lTp7Jhw4aYn3v9+vWcdtppZGVlUVxczPe//32qqgIHWmvXrsWyrDqXWbNmNep9ERERERERERERkXYooyP4SqJvfddke62Ptxq2f1Tn5rYQSBKsS26Xlu6CiIiIiIi0Unv2NMMistbOlQH5wwLXv/w1eA7VbWc5YPEt4YNMJGlUuivDbgfzBZIUFkZ+vOBAkmjaN1uxnbwh4MwIXF/5CJSvCP182jYs+TFU722mTomIiEg0fMEiEBpI4rSc5KflA3UDSaLRoYP5+bdt2N3UcR4VTVD2xGf9eli0KHD56qu6bb76KrTN+vVN1x9pleIKJLnmmms455xzWLNmDc8//zzPP/88q1ev5txzz+Waa65JdB8BmDFjBosXL2bWrFnMmjWLxYsXM3PmzAb3uffee3nggQd46KGHWLBgAWVlZRx//PGUl5f729xwww288MILPPPMM8ybN4/9+/dz6qmn4gmaIYj03B6Ph1NOOYUDBw4wb948nnnmGf773/9y00031enT22+/zebNm/2XY445JgHvjoiIiIiIiIiIiLQrGZ0D2zs+BPfB+ts6UmDnh3VubmsVPBRIIiIiIiIi8WqWRWRtQekksGoSGVTugKV3mgokPl437FkKax5vid5JDCo9lWG3a8vIMJdIDhwIbEdTkaTZArccTigeC1jmuu2GD84zn1+fdU/Dqr80U4dEREQkWsWZxVg1v+HlVeWUV5X7rxdkmGolwZXTtm0DpzPy43boEKhc0uRxFZXbwdsEA5/166FfPxg1KnC54IK67S64ILRNv34KJpEQrshN6vrmm2/473//izPoL87pdHLjjTfyj3/8I2Gd8/nqq6+YNWsW8+fP54gjjgDgr3/9K+PGjWP58uX069evzj62bfO73/2O22+/nTPOOAOAJ554gg4dOvCvf/2LK6+8kr179/K3v/2NJ598kuOOOw6Ap556iq5du/L2228zZcqUqJ77zTffZNmyZXz77bd06tQJgPvvv5+LL76Yu+++m9zcXH+/ioqKKCsrS/h7JCIiIiIiIiIiIu1I/tDAtrcatrwDnU4CR5gpX9sDOz+pc7Mv8CI/Pb+JOtk8XJYLt+1WIImIiIiIiDTK9u2hC9EkjJJxsPzBwPUVf4SSidB1mrleuR0+nBkaXCJJ6Vdzf8Xjix8H4OsdX/tv9y3O9IkmKATgYFB+i6IiE5xlWfW3b1YdjoVtc8z8CMDuz+C1IdD5NKjYApteb9n+iYiISFj56fk4HU68ttdfkQTAxvaf10hJgdxc2LcvtkASn4ULYcgQ8zhNonJHzRgkio7FYscOqKiIfb+KCrNvt7ZVsV7iF1dFkpEjR/JVmBI4X331FcOHD29sn+r46KOPyMvL8wdyAIwdO5a8vDw+/LBuJj2ANWvWsGXLFk444QT/bWlpaUyePNm/z8KFC6murg5p06lTJwYPHuxvE81zf/TRRwwePNgfRAIwZcoUKisrWbhwYUi/pk6dSmlpKRMmTOC5556L9y0RERERERERERGR9iyjA2QE5iP56rfhg0i8blj9BFTtqXNXqjMV+2c2u29p3Wl3M1JMalQFkoiIiIiISGNs2dLSPWgFSiaGXvdWw9zpMOcM+ORKeG0Y7FnSMn2TmLy39j3+tfRf/Gvpv/h006f+223skHbRBlcdOhTYLiwMZPmuT7MGmXQ6MRBE4lO5A1b/XUEkIiIiSSw/PR8LC4fl8AeS2LaN2+sOSZDlG69s2xbd4wYHyi5eHDn4pLo6pm6HqtwByRJcKxJGXBVJvv/973P99dezatUqxo4dC8D8+fP505/+xD333MPnn3/ubzt06ND6HiZqW7ZsobS0tM7tpaWlbKnnSN53e4fg0LGa6+vWrfO3SU1NpaCgoE4b3/7RPPeWLVvqPE9BQQGpqan+NtnZ2TzwwANMmDABh8PByy+/zDnnnMMTTzzBBeHKCdWorKyksjJQQnLfvn31thUREREREREREZF2pHg8fPsC4IHtc2HTLCg7rlZAiReW/gzSSlqql03uilFX8Lv5v6Nnfs+W7oqIiIiIiLRimzeDxxNdFuN2K6MM8gbC3mWht294oWX6I3Hz1lM1pnZFkry86B4vOJDEV5GkIa64VqzFqWCEScZxaFMzPqmIiIg0Vn56PjY2FpY/kMRTExwaHEjSsSOsXg0rVkT3uMHLvT/7DBwRSjI06vigcgdYzTnwEYlNXJ/O8847D4Cbb7457H2WZWHbNpZl4fF46rTxufPOO7nrrrsafK4FCxYAYIUJRfc9R0Nq3x/NPrXbRPPckdoUFxfzgx/8wH/f6NGj2b17N/fee2+DgSS//vWvI75H0jgul4uzzjrLv91U+ySb9vq6RUREJPFiHSMk45iivY6N4nkN6enp/oQC6enpCW/fFt5XkabQFr5rRaQJFB8B3z4fuL74FjhpEXg94HCC7YWvfwcHN7TpQJL7TriP+064r6W7Ia2MfltFREREAtrC2CjeOd7x48/ihhvA43GxYgV4vYkNJHG5XJx11FFw/fW4Glg/42/v8XDWf/7j305KXc6AfcvrVniQJteYOf0qTxWVCyojtvfg4ayzzuLKK83fRWZmdH0LypFLUVEzVxyJxHJAnyvgi5+buRIRERFpFfLT8/F4PbgcLvZX7ae8stxfPa12IIllwaZNsGcP5OeHfTi/zp0D20uWmEpqDQ2tIgWaBPOP1z66CJflqQkkafgBkvH4StqPuD5xa9asSciTX3vttZx77rkNtunRoweff/45W7durXPf9u3b61QC8SkrKwNMtZCOHTv6b9+2bZt/n7KyMqqqqti9e3dIVZJt27Yxfvx4f5tIz11WVsbHH38ccv/u3buprq6ut38AY8eO5bHHHqv3foDbbruNG2+80X993759dO3atcF9JDYOh4NBgwY1+T7Jpr2+bhEREUm8WMcIyTimaK9jo3heg8vlYsqUKU3Wvi28ryJNoS1814pIEygaAwQtgNjzObx7PBz5HKTmmSCSJbe1VO9Ekpp+W0VEREQC2sLYKN453lGjBrGsprjG0qWQktIE/Zo8GV5+GXbsCNyxebNZ5QZmpVvNuhYHMGjzZjjzTBPVEq30dCguTlS3G9brYvjyl5HbWSrtkmiNmdP3er14FkQO/rEcFoMGmb8LrxcyMqJ7nuBAksLCJKzs0+sSWBohka8+syIiIkmlIL0AGxuv7WV/1X72Vu4Nuc+ntNQEglRXm8CQSZMaDmrNzDRjnEOH4OBBU5Vk9Oj69zlwALKyouuzf7y2agcc8ELFjuj3EWkBcQWSdO/evd77oqn44VNcXExxFAey48aNY+/evXzyySeMGTMGgI8//pi9e/f6Az5q69mzJ2VlZbz11luMGDECgKqqKmbPns1vfvMbAEaNGkVKSgpvvfUW3/nOdwDYvHkzX3zxBffee2/Uzz1u3DjuvvtuNm/e7A9aefPNN0lLS2PUqFH1vq7PPvssJMglnLS0NNLS0iK+RyIiIiIiIiIiItLOFI0BKwXs6sBtW9+D/xaZUum2u+X6JiIiIiIi0grk55sF7x4PfP555PZeb2wZif26dTOXaK1YERp4AoHgk6DAE7/i4tgevzFyekPJRNjxQcPVHVT5Iak4ovzgOmuCKXyBIdFWJKmoCGyXlsb5d9KUsrpCp5Nh8xv1z5eoyo6IiEhS8VUd8dpeyqvK2Ve5r859YMYePosWwbhxkJpa/+Pu3w8dOsDateb622/D8OHhg8o9HvOYEyfG2Pm0UjiwzlQkEUlicQWSzJw5k0ceeYTs7OyQ29euXcvMmTOZO3duQjrnM2DAAE488UQuv/xy/vKXvwBwxRVXcOqpp9KvXz9/u/79+/PrX/+a6dOnY1kWN9xwA7/61a847LDDOOyww/jVr35FZmYmM2bMACAvL49LL72Um266iaKiIgoLC/nhD3/IkCFDOO6446J+7hNOOIGBAwcyc+ZMfvvb37Jr1y5++MMfcvnll5ObmwvAE088QUpKCiNGjMDhcPDKK6/whz/8wR/UIi3H6/Xy1VdfAebfO5qD53j2STbt9XWLiIhI4sU6RkjGMUV7HRvF8xrcbjfvvPMOAMcee2zE0qqxtm8L76tIU2gL37Ui0gSc6VAyHrbNgZpy7n4KIhFpkH5bRURERALawtioMXO8o0fDggUDWL3aQUWFKe5RH48ntgXyjXpvhw9Pivc2rD5XwvYG1gZZTig6vPn60040dk7fiRMPDQdLuCwXX375JT17wldfDSAz04FtN5zVG0xGb8sC226+4jgxG/kA/G9w+PssF5ROat7+iIiISIN8wSI2NuWV5ZRXlde5D0wgibvmlMgnn8APflD/Y3q9phLhiBGwfr25/t57cFsDxd0/+ST6QBL/eK28PwPshTiqdka/D8lzfCXtR1yftmXLljFkyBA++OAD/21PPPEEw4YNo0OHDgnrXLB//vOfDBkyhBNOOIETTjiBoUOH8uSTT4a0Wb58OXv3BkoX3Xzzzdxwww1cffXVjB49mo0bN/Lmm2+Sk5Pjb/Pggw8ybdo0vvOd7zBhwgQyMzN55ZVXcAbVWIz03E6nk//973+kp6czYcIEvvOd7zBt2jTuu+++kP798pe/ZPTo0Rx++OE888wz/N///R8/aOgbS5qF2+3mueee47nnnsPtju4Eezz7JJv2+rpFREQk8WIdIyTjmKK9jo3ieQ0VFRXMnz+f+fPnUxGcYixB7dvC+yrSFNrCd62INJEu01q6ByKtkn5bRURERALawtioMXO8J530HE6nG6/XZBu27fr3CZelOJH9Ssb3Nqzu50L+UBMwEo7thX7XN2+f2oHGzulnkBGxfbojneeee46zzzZ/FxkZJoAqkkOHAkFW0VYxaXa5fWHIHUDtqBgHOFJhYAMrSEVERKTZBQeL7K3cy4GqA2HvKy0NjOHnzWv4MX1j/pEjA4Gy77wD33xj7qutqgpefTX6PvvHa8t64yYNKrZHv0+yHwNImxRXRZKPP/6Yn/zkJxxzzDHcdNNNrFy5klmzZvH73/+eSy65JNF9BKCwsJCnnnqqwTZ2raN5y7K48847ufPOO+vdJz09nT/+8Y/88Y9/bNRzd+vWjVcb+La46KKLuOiiixp8DBEREREREREREZGYdD8PFt1EnYokdSiDlYiIiIiISCRz5sDhh8ceMNLuOJxwxN/gjTHh7oS+10LegGbvljTMqhNAUVeqMzXkemZmw8FVPr6KJAAZkeNVWs7AW+DQFlj5J1OFBBtS8mDic5DRNMmTRUREJD4FGQX+7fLKcg5WHwQg3ZVOijMwYO/cObDPhg2wcWPobcFcLvjsM5g2LRAs6/XCL38Jf/97aFu3Gx5+GILqG8TGssBbCQc3QmY9HRJpYXGdPXS5XNxzzz3ceuut3HPPPbz00ku8+eabTRZEIiIiIiIiIiIiIiJhZHSAsmPrzwLrF8WqDxERERERkXbKWXNINW9ew0EkW7Y0T39ahaLRMOoPmKVHvuVHFnSYDMN+2YIdk/o4I84d1A0kyciIPZAkLS2e3jUTRwoc/hBMfAF6XwL9fwAnL4UOR7d0z0RERKSW4Koj+yr3UeGuACA3LTek3aBBofu9+SZUV4d/zEOHYNkyGDEi9PannjIBKL7gEts2ASb339+IF+AbRO1Zair2iSShuAJJqquruemmm/jNb37Dbbfdxrhx45g+fTqvvfZaovsnIiIiIiIiIiIiIg3p9V2wPfXfbzmhKFyWWBEREREREQn24YeBxWO1VVfDJ580b3+SXr9r4dh3oWQ85A+FwXfA0W9BSk5L90zCcFiRl4mlOUOjQDIzo3vsioqgx0jmQBKfrtNgzF9gxG8hs1NL90ZERETCyHBl4HK4ADhQdQC7JmFWXlpeSLucHOjWLXD9oYfCB4e73fDXv5pxS6dOkJ8fet/ZZ8OBA+a6xwMXXwybNzfiBdhu8/+9X4DX3YgHEmk6cQWSjB49mpdffpn333+fu+++m/fff58f/OAHnHHGGVx99dWJ7qOIiIiIiIiIiIiI1Kfb2ZA7oP6qJLYHDrumefskIiIiIiLSiviCR3bvhueeC5/BOCUFnn++efvVKnSYDMfPhZOXwNA7wRG56oW0DJfTFbFNiit01WVGRnSPfeiQ+b9lQWpqw21FREREomFZFjmpJkD5QPUB/+2FGYV12o4cCY6aFfGLFsHs2SY4JJjDAQ8+6HtsGDMmUFEN4KOPYNQouOIKGDcOnn46QS9k71emKppIEoo7kGTx4sWMHTsWMH+st9xyC/Pnz2fOnDkJ7aCIiIiIiIiIiIiINMDhgsMfDl+VxHJCz4ugYHDz90tERERERKQVuu++uhmM3W5TjeTzz1umTyKJkOqMHOGR7kwPuZ6ZGbrAsj6HDoHXC+npkduKiIiIRCsv3VQfOeQ+5L+tOLO4TrthwwKBJAD33AOuoBhat9sEjK9dG7ht0qTQfQBWrTJVSz79NBG9r7Hn8+gGVLEoLo5v4JWebvYVqRE51DyMv/3tb2FvHz58OAsXLmxUh0REREREREREREQkRh2OgsOuhZUPBW6znJDZDYbf02LdEhERERERaQ2ys001EjCLxj74AI44IrD4zOWCe+9tuf6JJEI8gSQZGXUXWIZz6BDYdvQVTERERESiUZBewFrWht6WUVCn3dChoRVIZs2C3/0ObrjBXF+zJrDtc+SRgcqETWrPUvC6TVKwROnWDZYvhx07Qm/fvBn27DHb+fnQsWPo/cXFZl+RGjF9Kv/zn/8wbdo0UmtqEK5du5auXbvidJqylAcPHuShhx7i5ptvTnxPRZqI0+nk9NNP92831T7Jpr2+bhEREUm8WMcIyTimaK9jo3heQ2pqKiNGjPBvJ7p9W3hfRZpCW/iuFZFmMPoPkNMbPvsR2G4oPQomPgupdU+qiLR3+m0VERERCWgLY6PGzvG+/baTefMC933/+/D++4FF9P/7H7z4olmg1pT9Ssb3VpJHY+f0n1j1ROT2Kan06nU6DzwAHo+TzEyI5ql8FUkUSCIiIiKJVJRZVOe2/LT8OreNHFl33x/8wASIl5XBv/8N27eH3j9+POTmwr59CeosQeO16v04V/zc3OithN2LoXAkWHUjdJ2Wl9PHl0DJ+NiOAbp1U1CINJpl27YdbWOn08nmzZspLS0FIDc3l8WLF9OrVy8Atm7dSqdOnfA0S4hW+7Rv3z7y8vLYu3cvubm5Ld0dERERERERERERSTZejzkx4cps6Z6IiIiIiIi0CtdfD488AtXVgdtGjIBrr4WNG+EXvzD3jRgBixa1XD9Fwlq0CEaNCr1t4cI6Kyr7PdSPFTtXNPhQJ/U5icsyXuPMM831d9+Fo4+O3IXjj4e334Y+fWDlylg6H6T26wjzGkRERKR9Oee5c/jPl/8Jue0nE3/CL475Rchttg0lJbBzZ+THDB7Tf/e78NRTodVMGmofNduGZ3PBvd9cH/IzGPST+quSfHI1jHk4xicRqV+08QZRFB8MqB1zEkMMioiIiIiIiIiIiIg0B4dTQSQiIiIiIiIxOOKI0CASgM8+g0svhTvuqHufSGuU5kyL2CYzJZODBwPXs7Kie+wDB8z/09Pj6JiIiIhIPcJVH8lPr3ubZZkKI46YVsXDWWc1HEQCsT+mv0O5AwLXN82qP4jEUwG7Fa0uLaOeT6VI++H1elm1ahUAffr0wRHFt348+ySb9vq6RUREJPFiHSMk45iivY6N4nkNbrebuXPnAjBx4kRcroYPK2Nt3xbeV5Gm0Ba+a0VERJKJfltFREREAtrC2Kixc7yHH96HGHOxNkm/kvG9leTR2Dn9TEfkpBNZrix2b13BYYfBN9/0ISsrus+gL/gkIyOq5iIiIiJRKcgoiOo2gJNOgldfje3xjzsOsrNh//7623i90T9eyHgtbyiO3Z+B7YZdC6ByJ6QV1drBjXfTW6zaVQArVugYQJqdPm3S7rndbp5++mmefvpp3JFCCxuxT7Jpr69bREREEi/WMUIyjina69gontdQUVHBnDlzmDNnDhUVFQlv3xbeV5Gm0Ba+a0VERJKJfltFREREAtrC2Kixc7zdurnp2LHl+5WM760kj8bO6Wc5IpcXyXJlsWvX05x//tM4nW4yoyx4qkASERERaQrhqo+Euw1g6lSw7ciP6XQGttPS4Ac/qL/qiMsFRx0V+TF9QsZr2QPArolCsb2w/A/g9YTu4HDh/vohnl4xVscA0iJirkjyxhtvkJeXB5jIqXfeeYcvvvgCgD179iS0cyIiIiIiIiIiIiIiIiIiIiIiTcmyYPp0ePRR0NotaasyUiJHeWSnZofuE2VgyKFDsbUXERERiUYsgSSdO8OIEfDZZw0/pqdWLMdNN8Hvfw/79oVve8010fW1jtx+QFA5k5UPw6Afg22B5QCvG/Yth63vAePjfBKRxok5kOSiiy4KuX7llVeGXLcsq3E9EhERERERERERERERERERERFpRqefDg8/3NK9EGk60QSSZKWGVi1JT4/usSsra55DgSQiIiKSQLEEkgCceSZ8/nndYJFgnTqFXs/LgzvugB/+MPR2hwMuuAB6946+vyFy+4der9wBH82ECc+Y0inuA/DBOXE+uEhi1FOMJzyv1xvx4mnor09EREREREREREREREREREREJMlMngyZmQ23ccWcrlUkeUQTSJKTkhNyPdpAkoqKmudQIImIiIgkUEF6QVS3+cyYYWI06uNwwLRpdW+/8Ua45RaznZJiKhZOnWoqFsYtsws4Q4N0Wf8svHciLPkxvHUk7P2yEU8g0ngxBZKIiIiIiIiIiIiIiIiIiIiIiLQ1aWlmsVhDwSJud/P1RyTRsmovZAwjJy2+QBJfRZJo24uIiIhEI9aKJD17wkUX1T+mz86Gc8IUAbEsuOceePppuPZa+OMf4bnnzDFC3CwHFI6se/uWt2DZPbD3i0Y8uEhixB1Isnz5cq699lqOPfZYjjvuOK699lq+/vrrRPZNRERERERERERERERERERERKRZ3Hpr/cEiTieMGNG8/RFJpIzUKCqSBAWSRBsUYttQVVXzHBng9cbTOxEREZG6wgWN5KblNrjPT34SfjzicMCPfgQ5OXXv8zn3XHjgAbjmGjP+b7SiMWCprKEkr7gCSZ577jkGDx7MwoULGTZsGEOHDmXRokUMGTKEZ599NtF9FBERERERERERERERERERERFpUsOGwWmnhc9g7PHAlVc2f59EEiU7NTtim+CFmdEGklRUBLYVSCIiIiKJVDuQJCslC6ej4QiPXr3g7rtDb3M6YehQuP76BHcwkpLxYKusoSSvuMKcbr75Zm677TZ+/vOfh9z+s5/9jFtuuYWzzz47IZ0TaQ5Op5OTTjrJv91U+ySb9vq6RUREJPFiHSMk45iivY6N4nkNqampDBw40L+d6PZt4X0VaQpt4btWREQkmei3VURERCSgLYyNEjnHe9dd8PrrYFmm0oK5HyZNgsMPb9p+JeN7K8mjsXP6q9NXR2xfkFmAbZ/EG2+AZUX3HJWVge2MjMDfjYiIiEhj1Q4kiVSNxOfWW01w+I9+ZK6PHg1vvNFwNZJEqDNe63AMpuZD/ZG2TsvDSd0/h4G36BhAmp1l27EP3zMzM/n888/p06dPyO0rV65k2LBhHDx4MGEdlFD79u0jLy+PvXv3kpsb3ReiiIiIiIiIiIiIiIiIiIiIiERn1iyYOtUsiPd6YcwYs/BMyzQkKS1aBKNGhd62cCGMHBly018+/Qvf+9/3Gnyor6/5mn/+oR/33AMFBbB1a+Sn370bCgvN9t13ww9/CFHklaqr9usI8xpERESk/Un/ZTqVHhO5OqB4AMuuWRb1vrt3w7590LUrOBxN1cMI3hgPOz9quE3h4XDiJ83TH2kXoo03iKsiyVFHHcXcuXPrBJLMmzePiRMnxvOQIiIiIiIiIiIiIiIiIiIiIiIt7sQTYc4ceOUVyM+H732v6bMXizS12hm9UxwpAFR7q/23FaQX+CuKWFZ0j+sNSrCdnt6YHoqIiIjUlZOWQ+VBE0hSlFEU074FBebSojqfArs+AdtTfxvb3Xz9EQkSVyDJ1KlTueWWW1i4cCFjx44FYP78+Tz77LPcddddvPzyyyFtRZKZ1+tl/fr1AHTr1g1HFGGH8eyTbNrr6xYREZHEi3WMkIxjivY6NornNbjdbj799FMARo8ejcvV8GFlrO3bwvsq0hTawnetiIhIMtFvq4iIiEhAWxgbNcUc79ix5tKc/UrG91aSR2Pn9Ad1HxRy3w1jb2D3od089tlj/tsKMwqx7bV06waHDnUDIj+HL/AEICMjihciIiIiEoO8tDx2HNwBQGFmYQv3pmFhx2sdp8DnP6l/H9ti/f6OsHatjgGk2cX1abv66qvZsWMHDz/8MBdeeCEXXnghDz/8MNu3b+fqq69m2rRpTJs2jenTpye6vyIJ53a7eeKJJ3jiiSdwu6OL6otnn2TTXl+3iIiIJF6sY4RkHFO017FRPK+hoqKCN954gzfeeIOKioqEt28L76tIU2gL37UiIiLJRL+tIiIiIgFtYWyUrHO8beG9leTR2Dl9lx2a6Omuo+7i2jHX+q+7HC68Hi8pKU8wc+YTuFzRPUdwRZKMjOgrmYiIiIhEozAjEDxSkN7S5UUaFna8VjgKcvoB4QdJbtJ5YtkYHQNIi4grkMTr9UZ18XgaKMMjIiIiIiIiIiIiIiIiIiIiIiIiTS7dlR5yvdJTSaWn0n89zZkWcn+0ybBrVyRREm0RERFJpOLMYv92sgeShGVZMPBmwA5/v63gEWk5jR66R5NRVkRERERERERERERERERERERERFpGhisj5Hqlu5JKdyCQpHagSbSVRYIrkqSkqCKJiIiIJFZBRiB4JD89v+U60hg9zofUorq3W07oOKX5+yNSI65AEo/Hwy9+8Qs6d+5MdnY2q1evBuCnP/0pf/vb3xLaQREREREREREREREREREREREREYlfqjM15HqVp4oqT5X/epqr8RVJHA4FkoiIiEhi5aflB7ZbayCJMw1G3lfrRgc4UmDwHS3SJRGIM5Dk7rvv5vHHH+fee+8lNTVwkDFkyBAee+yxhHVOREREREREREREREREREREREREGifFmYLDCiwVq/RUUukJVCSpXbEknooklqVAEhEREUms4OCRVhtIAtDrYhj268B1ywGTX4GCYS3WJZG4Akn+8Y9/8Oijj3L++efjdDr9tw8dOpSvv/46YZ0TERERERERERERERERERERERGRxktzBqqOVLorqXQHAkkyUzJD2sZbkUREREQkkQoyCsJut0qDboWjZsHhD8OUT6DsuJbukbRzrnh22rhxI3369Klzu9frpbq6utGdEhERERERERERERERERERERERkcRJd6VzyH0IgCpPFVWeKv99tQNJ4q1IIiIiIpJIbaYiiU+nKS3dAxG/uAJJBg0axNy5c+nevXvI7c8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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#[15,17,19,22,27,45,49,60,68,72]\n", + "locs = [[250,500],\n", + " [210,460],\n", + " [200,450],\n", + " [90,340],\n", + " [235,460],\n", + " [50,300],\n", + " [65,315],\n", + " [170,420],\n", + " [120,410],\n", + " [75,325]]\n", + "for k,id_ in enumerate([15,17,19,22,27,45,49,60,68,72]):\n", + " \n", + " st = locs[k][0]\n", + " end = locs[k][1]\n", + "\n", + " nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}\n", + " start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + "\n", + " ntrack = 2\n", + " fig = plt.figure(figsize=(40,ntrack*5))\n", + " ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 17)\n", + "\n", + " for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "\n", + " ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 17)\n", + "\n", + " for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_][:15]):\n", + "\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + " ax1.set_xlim([st,end])\n", + " ax2.set_xlim([st,end])\n", + "\n", + "\n", + " plt.savefig(\"figures/evolution_from_scratch/EFS\"+str(k+1)+\"_deepexplainer_mut0_mut15_st\"+str(st)+\"_end\"+str(end)+\"_topic17.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "f10ae92f-c372-4a29-955e-3f0548136a29", + "metadata": {}, + "source": [ + "### Printing generated DNA sequences in nucleotide letters." + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "1ee1fb00-d921-483a-b0b7-3f933b0d6e00", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ">id15_mut15\n", + "CTGATTGTTTGAACCATTGTTACGATTTGGTAGCGAGGCCCATTTTTTAGAATTCGGGACCTCTTAGACAGGGTCCAAAGCATTTGAACTGATCGGTCTATCCGGTTATGACCGGTCTTAAACTCCGCTCACGAAAGTCACTGGGTCATAGCTGTATCTAACGTCCCCTGACGTTGTACGTTTCCGATTGTCGGTGAGCTTTAACAACAGCCAGTCGTGCAGAATTCGGAAAAAGACTTTGGGTATATCTAGCGAACAGAAATGAGTGACATTTCGTTACAACTAGTGTCGGGAACAATGCCCTCACTGAAGCTACATGAATAGGCCCTTTGTATTCGTGGGTGTGGTACCACGTGGCGTGCGTCTACCGTGGGGACAAAGAGCTCTTTTAATGGAAATTGCGCTTCCCACATCGCGAGGAGGATCTGTAAGGGTGAGCGAGACCGTGTTGGACACACCACACGTTTACGGTATGAGTCACGCGCAAAAAACAAAATTGC\n", + ">id17_mut15\n", + "GCCGAGTACTGTATTAACACGCAAACGGTATGTTGCTGAACTTTACCGTCAAACGCCTCTGGTTTTACGAGTCCACTGATGACGTACATACAGTCCGATCTTGGAAAGACTTCCTCGCTGTCTTGAGAAGATGCCGGTCTTATTTGCTTTGGGACTTTGGGCTCACGTAAGTAATCCTCAGTCCCTTTAATGTGCTCTTACGGATCTTCACAAGTGAGGTGCCGGTTCCATACCTACTGAAAGAGGCTATTCATTACCGCTCGCTGCCACGCATGGTCACGAGTTTCCCCCAGGCAGTATCAACAATGAAAGCATTGAACCGACCGAGAGTGCGGGAACAGGGTCGCGGGTGCGTGGGAAGGTAGGAAAGGGGTCGGCGGTACATTTTACTGAAAGAAGAGAAGGTCTTGGGGCCTTCCGCTAAGATAACTGCAAACGACAGGGCTCCGGCCCCAATTCCATGTTGGACCTTTATTATTTCTCGCTGCTAACGGTCTTGC\n", + ">id19_mut15\n", + "TATTGTATTGTCATAGGTGCCCGTTCCTCGTCCGCCCTGGGATACCGACACAAAATTAAGTTAAGTTAGCGATACCCCGATCCGTGTTTCCACTTCTGGCTAATATGGAGCTGGACGGCCGCCAATTCAAAGGCTACCAACCTTGAGACTCGGAAGACAGGTTACCGATACTAACGAATAACAGTGCGTAAAGTCCCGAGTACCATGTAGTTGATCACAAAAATACTAGAGCAAACGGCATCGGGTACTCCGCGTGATCCGCTTTGGACCGGCATAAAGGCGTCCATTGTCGACTGTGCCCCATGGCACTGCTGAAGCTTGGAAGTGGGGATTGGGGTCTTTAGTACACTGTTGGAACAATGCAGTCATTGTTCCTATTATATGGTTGTGTTAGGGACTTGCCGATTCTACATGACATATGGAGTAGACGGGCCTGCCTAATCATTTACATAATCATTTAGCTGGTGACTGAACTAAACTATTACACAGCACTTACGAAT\n", + ">id22_mut15\n", + "TGATATGTATTCACCCATGCCCTCACGTTCCTAAGTGGTGGGGTAGAGGGTCGCTGCCATATTACGTTGGGCAGAAGACTACGTCCAGAATGCTCATGAATGAGACTATTCAATGGTAGGACGCATCCATAGTCATTCGCACAGGAACAAAGGGATCATTGTGCGGGTATACAACAACAGAACCTTGTTTATCCACGTCAACACAAACACATTTGGGCCTGGACCAGTCGGTGTCAAGTGCCGGAGGGTATACCAAGGTTCAGATCTTGAACACGTGGTAACAGAATTTAGTTAAGTAGGGATTCTCCGTAACAATGCCCCCATTGTTGTTACTACGCAATCGATATTATGTAGCCTTACAGCAACCAGTAAGATTAATCCACTATCATAGTCTTAGCCCTCGATCAAGACTCTCGACTCCCGATCCAGCTATTGAATTAGCAATTAGCTGTCTATTGCTCGGACTATTTCGTATAAAGGAGCATACATATACAAACCCT\n", + ">id27_mut15\n", + "TCACGTGGCGGTAACCACAGTCCGCTAAATGGGCAAGGGTATGTCACGTTGACTGAAATAGCATCAAGGTTAATAGGTAGTTGGGTGCATCAGAGCGCCACGAGTTGTAAGCACCAATGATCCCATCATTCGGGAACACTGCAGAATCAGAAATGAGGAAGGTGCTCTCGGAGGGTATTGACAGTGATAACGAGTCCACTATTTAGGGGGTACGAATCTATGAGCTTGATAGAATCTGCCTGCAAATTTCCACAATCTCACATGATTCCATCTCATACGAGACAAAGTCCTCATTCAGCCGGAAAATGAAGTTCTCCCATGGATCTAGAACAGTAGCCCCTTATGAGTCTCATTGAAGGCGGATTCACATTACAAAGGGGCCTTTGTGTGAAACCAGGATTGCTCAATATGCATTCTCCTTTAGCTCAGGACCGCGAAGGTGGCCTGAGGGCTTTACAAGAATGCAGTGTTTGTTTACGAGCTAGTATCAACCATCTCAT\n", + ">id45_mut15\n", + "GAGTAACCTCCCGTGAAGAAAGTCTTGCCTCATGTCCAGTCTTCATTTCCATTTCGAATACAAGAATCCATTGTTTTATTGCCTCACATCTGAGTTAGACATTGCCTCAGGGATAGACTCCATAAACCCCTCCATGAAAAATCACTACCTCTGATCCTATACAATGGATGTATTGTTCGACACACAATCTTCAGTGTTCCCTTTATTTGCCGCAGGGCTGAATTTTGAGAAGCCGTAGCACGAACTCATGACTATATGCTAGAACGACGGCTACCGAATTAACACCTTCCCTTAGACTCGTTCTGCTGCGGACTCCTTGGTAGGGGTGCGCGCATACTAGAATTAGTAGGGCTTATCGGGAAAGTGATCTTCATGCGTCCAAAAAATATACTCATTGCGTAATGTATTGATTGGTTCACTCTAACTCTCGGGTTTCTGGAGCTAATCGCACTGCTCCCGTGATAGTCCAAATATAGCGATATTGGTGTACCGCTGCCACG\n", + ">id49_mut15\n", + "CTTTCATTATTGCATTTTTACATTTTTGAACGATGATAACTACTCGACTCCCTCGATTTTCCGAGCTCCTGTGGTGACCGCAAACTGATTTCGGCGGTCCGAAATTATGGGACTAGTACAATGAGCCTTTGTGTGGAGCAAACCTCCCGCATACTTATACTACAATAGTGATACATCACGCCCCAAGGCTAATGGACAGCCAATAGCTATTCCAGAGGGGAGTGCAGTATCGGGAAAACAATAGGGTCCTTTGTCCTTGCTTCCTAAGCTAAAGGACTGTAAGAGGTTCGGAGTTTGGACCTCGTGAAAATTGCAATGTCACCAGCCAGCTGAAGTTTCAGATGGGACTGATGGCTTTGTACTATGTGGCAACCTATACTTATACACCGCAGAAAGGAGCCCCACCTAAGTTTTACAGTCATGTGCGCGGATCGACCTCGAGTCGATGTCATTCCCGCAGCTTCTACAACTGAACTCTTGAAGACTCCTTGGGCTGGTCT\n", + ">id60_mut15\n", + "ATACGCACGACAAAGCCTCATCGATAGCAAAGGGAGAACGGATGAACTAAGGTGTCATCAGCGCCGTGGCAATCCCGCGAAAAACAACACAATATTTTAGGAACAAAACTATTGCGCCCTCAAGGTTCAAGTCGCATTTTGCTGATGGATAATATCCTACTTACTGGCAGCGAACACCGTACGAGGGTGGCTAGACTACTCAGGGTCTATAGAACATGAATGGGGCATTGTGTATTCAGCATGAATGGAAGCATTGTTCAGAGACATAGACACGCGCATAGGTCGTGTGACCGCTCCATTAAGCGGCTGTTTCGGCGACTGGGGTAATATCCATTTTTCTGGGAGCGTACTTCTATGAATCGGATCTGTGGTTTCTTTTCACACTCCTAAATCGAACGGGGTGACGTTCACATGGGTCATTCACTGTGCCTTTCCCGTGGAAGGTGACTTGGGAGGCTGCTTGGAGTTTGGGATCGTATTGCGGGATGCCTTGTACAGTG\n", + ">id68_mut15\n", + "AACCAAATACGAATGGTACTAGGGTGCTCACTTAGTGCACAACTTTAGTTTAAGACGATGTTTGACGGTTTACGCTGGGCCAGAACTCGGATGTTCAAGACTCCGGTTCCCTTTCACACGCATGCCCTCATTCATCAATCGTCCTCTTATATAAACAGGCAAATTCCGGGAACGAGCCCTAAGGCATTCTGTTAGTGAACAGCGCTTACAAAGCATGAATGACTGCTTTTATTAAAAGCTAATAGATGACTCAAAGTAAATCCGCGATGGGTGACTTGTGACATTCAGCAGGGTCATGGGGACTGGCCACATAATGCATAAGCCGTCTGAAAAAGGAGCCATTGTACTCGATGACCCACGGGGTCAAACACGAACAAGGCTCTCATTGTATAGCACAAAGACTACTTGGCTCCTTGACTCCTATCAACGTGGTATGCGTGCTAGTTGTCCATGATATCATTCCTAATGTAGAACGTATTGCGATCAGCACGGTTGTGTCT\n", + ">id72_mut15\n", + "ACGATAGAAGGATTAGTCTGCAAAGCCGTCAATTATACGCTTACGGGACGGCCATAAGGTCGTCGCGACCTAGGCACTCGAAGAAACAAACAGTCCATTCATAGCGTGGAAACCGGAAGCTCCCTTGGCATTTACACGCTACGTCTACCCTGAACTCCCACGTTCCTAAACATCACAAGACTCGCAAAGCAGTACTCCGCCGATGTTGTCCGACAATGGGAGCTATTGTTCGGACCTGCCCGACGGATGGCTTGCGCCTAACACAAGCGACGCAGGCCTTTTCCTCGAGTGACTGTAATAGCGGCCAATAGGCCGGCGCGGCATCGGTGGGACATCTCATCCGGTAGATGACTTATAGGGCCTGACGATATAATGGCAACAACCTACGAGCGAGTTAAGGACATCGCAATGGGGGGATCGCTGAGCAGATTGTTTATATGTGTGATATCCTACGCCAGTACACCTAAGAAGCGTATTAATGGGGCAGGTTTAGGGCTTGG\n" + ] + } + ], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}\n", + "\n", + "for id_ in [15,17,19,22,27,45,49,60,68,72]: \n", + "\n", + " start_x = np.copy(evolved_seq_4000_dict[\"X\"][id_:id_+1])\n", + "\n", + " for i, mut_ in enumerate(evolved_seq_4000_dict[\"mut_loc\"][id_]):\n", + " if i>=15:\n", + " break \n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "\n", + " print(\">id\"+str(id_)+\"_mut15\")\n", + "\n", + " for nuc in start_x[0]:\n", + " if nuc[0]==1:\n", + " print(\"A\",end=\"\")\n", + " if nuc[1]==1:\n", + " print(\"C\",end=\"\")\n", + " if nuc[2]==1:\n", + " print(\"G\",end=\"\")\n", + " if nuc[3]==1:\n", + " print(\"T\",end=\"\")\n", + " print(\"\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d8a97ffa-ba55-4a16-b989-dba42474558f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_EFS_Steps_Repressors.ipynb b/the_code/Human/MM_EFS_Steps_Repressors.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7a7b2b908dd53cd6efe75838009b6c7235b6c438 --- /dev/null +++ b/the_code/Human/MM_EFS_Steps_Repressors.ipynb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4598120fa020655092ccc2939a73da621e68591ad863015f054eb6c2491a2799 +size 11245818 diff --git a/the_code/Human/MM_EFS_TFModisco.ipynb b/the_code/Human/MM_EFS_TFModisco.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..c949a477d4eb8cd5ed44d410dcf1847e99537351 --- /dev/null +++ b/the_code/Human/MM_EFS_TFModisco.ipynb @@ -0,0 +1,1169 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3ffb42a0-c57c-4600-84b5-909c55c3424e", + "metadata": {}, + "source": [ + "# This notebook shows the TFModiscco experiments" + ] + }, + { + "cell_type": "markdown", + "id": "ed9a3498-74f0-426f-bbc7-f51ce1835a83", + "metadata": {}, + "source": [ + "\n", + "#### It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. \n", + "#### It consists of:\n", + "* Calculating contribution scores on synthetic sequences.\n", + "* Performing TFModisco on contribution scores.\n", + "* Plotting identified patterns.\n", + "* Saving trimmed patterns as txt file to be later used for motif analysis.\n", + "\t" + ] + }, + { + "cell_type": "markdown", + "id": "30a7d851-c414-4bdd-939a-bb558303892a", + "metadata": {}, + "source": [ + "#### Result files are saved to ./data/tfmodisco folder\n", + "#### Figures are saved to ./figures/tfmodisco folder" + ] + }, + { + "cell_type": "markdown", + "id": "af110d25-0692-43cd-804e-1e206151b5bd", + "metadata": {}, + "source": [ + "### General imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "e50ed967-f5e5-4faf-9d50-311006eb3335", + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "1ca78824-35d9-441d-9162-25dd071f01e6", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e0c9ecab-4cf4-4295-a620-9cf92d8c76ea", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "a3b2e959-2054-4f21-bcf2-a1526dcb4090", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "325274e9-40a9-431f-bf54-82fb680228f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "markdown", + "id": "829ed553-49ed-4545-aa61-bbecbe49196b", + "metadata": {}, + "source": [ + "### Loading the generated sequences via in silico evolution" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8fcc9fb7-3a25-423e-a01d-27d2a8653858", + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/deepmel2/MM_EFS_4000_withmut.pkl\", \"rb\")\n", + "random_seq_4000_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "b6c9e0c0-85ad-4998-8da4-4e5310a70edf", + "metadata": {}, + "source": [ + "### Calculating nucleotide contribution scores" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "e23130d1-541d-455a-95fb-a2030d716359", + "metadata": {}, + "outputs": [], + "source": [ + "# def my_print(text):\n", + "# sys.stdout.write(str(text))\n", + "# sys.stdout.flush()\n", + "\n", + "# for n_mut in [4]:\n", + "# my_print(\"n_mut: \" + str(n_mut) + \"\\n\")\n", + "# regions = np.copy(random_seq_4000_dict['X'])\n", + "\n", + "# for id_ in range(len((regions))):\n", + "# for i, mut_ in enumerate(random_seq_4000_dict[\"mut_loc\"][id_][:n_mut]):\n", + "# regions[id_][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "\n", + "# topic_for_tfmodisco = np.array([16])-1\n", + "\n", + "# shap_dict = {}\n", + "# tasks = []\n", + "# for topic__ in topic_for_tfmodisco:\n", + "# my_print(\"Topic_\" + str(topic__ + 1) + \"\\n\")\n", + "# task = \"Topic_\" + str(topic__ + 1)\n", + "# tasks.append(task)\n", + "# shap_dict[task] = {}\n", + "# for i in range(len(regions)):\n", + "# if i % 50 == 0:\n", + "# my_print(str(i) + \"_\")\n", + "# shap_values_, indexes_ = exp_dict[\"DeepFlyBrain\"].shap_values(\n", + "# regions[i:i + 1],\n", + "# output_rank_order=str(topic__),\n", + "# ranked_outputs=1,\n", + "# check_additivity=False)\n", + "# shap_dict[task][i] = [shap_values_]\n", + "\n", + "# from collections import OrderedDict\n", + "# task_to_scores = OrderedDict()\n", + "# task_to_hyp_scores = OrderedDict()\n", + " \n", + "# for task in tasks:\n", + "# task_to_scores[task] = [ (shap_dict[task][ids_][0][0]*(regions[ids_])).squeeze() for ids_ in shap_dict[task]]\n", + "# task_to_hyp_scores[task] = [shap_dict[task][ids_][0][0].squeeze() for ids_ in shap_dict[task]]\n", + "# onehot_data = regions\n", + "\n", + "# print(task_to_hyp_scores[tasks[0]][0].shape)\n", + "# print(onehot_data[0].shape)\n", + "# print(task_to_scores[tasks[0]][0].shape)\n", + "\n", + "# f = open(\"data/tfmodisco/MMEFS_M\"+str(n_mut)+\"_topic16_shapvalues.pkl\", \"wb\")\n", + "# pickle.dump(tasks, f)\n", + "# pickle.dump(task_to_scores, f)\n", + "# pickle.dump(task_to_hyp_scores, f)\n", + "# pickle.dump(onehot_data, f)\n", + "# f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "dff52a74-c958-4d31-ad52-89848f1bb45e", + "metadata": {}, + "source": [ + "### Importing TFModisco package" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "fca71f9e-0918-4b6c-81de-07e6535ece8c", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "TF-MoDISco is using the TensorFlow backend.\n" + ] + } + ], + "source": [ + "from __future__ import print_function, division\n", + "%matplotlib inline\n", + "try:\n", + " reload # Python 2.7\n", + "except NameError:\n", + " try:\n", + " from importlib import reload # Python 3.4+\n", + " except ImportError:\n", + " from imp import reload # Python 3.0 - 3.3\n", + "\n", + "import numpy as np\n", + "import modisco\n", + "import sys\n", + "import os\n", + "import pickle" + ] + }, + { + "cell_type": "markdown", + "id": "14c5e8bd-eaa6-4d91-9e0a-643c792e2e92", + "metadata": {}, + "source": [ + "### Loading the contribution scores calculated above" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "cd5f8e97-60bb-4fad-badf-a807599045ef", + "metadata": {}, + "outputs": [], + "source": [ + "tasks = {}\n", + "task_to_scores = {}\n", + "task_to_hyp_scores = {}\n", + "onehot_data = {}\n", + "for i in [4]:\n", + " f = open(\"data/tfmodisco/MMEFS_M4_topic16_shapvalues.pkl\", \"rb\")\n", + " tasks[i] = pickle.load(f)\n", + " task_to_scores[i] = pickle.load(f)\n", + " task_to_hyp_scores[i] = pickle.load(f)\n", + " onehot_data[i] = pickle.load(f)\n", + " f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "1f09edc5-17ff-429d-834b-2433ac9f0217", + "metadata": {}, + "source": [ + "### Visualizing the contribution scores" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "4286f966-f4cd-4b5b-99fc-dcf413b0eae7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import modisco.visualization\n", + "from modisco.visualization import viz_sequence\n", + "\n", + "n_mut = 4\n", + "viz_sequence.plot_weights(task_to_scores[n_mut]['Topic_16'][0], subticks_frequency=20)\n", + "viz_sequence.plot_weights(task_to_hyp_scores[n_mut]['Topic_16'][0], subticks_frequency=20)\n", + "viz_sequence.plot_weights(onehot_data[n_mut][0], subticks_frequency=20)" + ] + }, + { + "cell_type": "markdown", + "id": "4d49ee87-3805-4907-8fe0-01cefb37adbe", + "metadata": {}, + "source": [ + "### Importing TFModisco package" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "3bc5e297-4c45-4b92-97c5-287a211ec2c1", + "metadata": {}, + "outputs": [], + "source": [ + "import h5py\n", + "import numpy as np\n", + "%matplotlib inline\n", + "import modisco\n", + "import modisco.util\n", + "from importlib import reload" + ] + }, + { + "cell_type": "markdown", + "id": "a5f8684a-7739-4f56-a9d1-d710af684448", + "metadata": {}, + "source": [ + "### Running TFModisco" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "7de258cf-1269-4e1a-9690-47059835c217", + "metadata": {}, + "outputs": [], + "source": [ + "# tfmodisco_results = {}\n", + "# for n_mut in [4]:\n", + "# null_per_pos_scores = modisco.coordproducers.LaplaceNullDist(num_to_samp=5000)\n", + "# tfmodisco_results[n_mut] = modisco.tfmodisco_workflow.workflow.TfModiscoWorkflow(\n", + "# sliding_window_size=15,\n", + "# flank_size=5,\n", + "# target_seqlet_fdr=0.15,\n", + "# seqlets_to_patterns_factory=\n", + "# modisco.tfmodisco_workflow.seqlets_to_patterns.TfModiscoSeqletsToPatternsFactory(\n", + "# trim_to_window_size=15,\n", + "# initial_flank_to_add=5,\n", + "# final_flank_to_add=5,\n", + "# final_min_cluster_size=60,\n", + "# n_cores=16)\n", + "# )(\n", + "# task_names=tasks[n_mut],\n", + "# contrib_scores=task_to_scores[n_mut],\n", + "# hypothetical_contribs=task_to_hyp_scores[n_mut],\n", + "# one_hot=onehot_data[n_mut],\n", + "# null_per_pos_scores=null_per_pos_scores)\n", + "# grp = h5py.File(\"data/tfmodisco/MMEFS_M\"+str(n_mut)+\"_results.hdf5\", \"w\")\n", + "# tfmodisco_results[n_mut].save_hdf5(grp)\n", + "# grp.close()" + ] + }, + { + "cell_type": "markdown", + "id": "a640ebdf-814d-4608-a70b-c428c4695973", + "metadata": {}, + "source": [ + "### Plotting TFModisco patterns" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "32cf70b4-bc8c-4a12-a268-fba6280dcfbb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Metaclusters heatmap\n", + "metacluster_0\n", + "activity pattern: [1]\n", + "metacluster_0 pattern_0\n", + "total seqlets: 3201\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_1\n", + "total seqlets: 2134\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_2\n", + "total seqlets: 1972\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_3\n", + "total seqlets: 1778\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_4\n", + "total seqlets: 1059\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_5\n", + "total seqlets: 1018\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_6\n", + "total seqlets: 999\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_7\n", + "total seqlets: 551\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_8\n", + "total seqlets: 371\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_9\n", + "total seqlets: 208\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_10\n", + "total seqlets: 151\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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HhRBC/Hx8vOLjqOGfawO1XDvsWuYXzafCazra+GLNF+ys2Ul+Zn5KtmFj2UY+WP4BAJNWTWLNzjX0zu+dklhCpNLmzSZ59P77pqbJrl2mPyOHw3SKHepEWSlTu8TvN0mB1q1NjaNzzoFTToFu3WLXXVoKp58OS5Y0nEiy2WDECJNEOO20uvX4fHXPu91QXAxz58Ibb8CkSXs2Cth7y96L6i9Hozmz35lsq9jGw9Mfxmf5COgAby9+m6dOfyoq+SBiffopXHONad4Wz0EHwaOPmpHdlDIjugE4nfGXd7vN9+WYY8zn/vDD5vVNJQxLq0tZu3tt1Lxafy2HtT8sat6wTsPCfSiFzNoyC4/fg9vhbjyIEEKIPZZIDaUjgNVa67Vaay/wFlB/2ISxwKvamAG0Vkp1bOK1Y4FXgvdfAc7eu10RQgjxczdu5rhw4ghgQOEAzup3Fp5AXTMWu810rpsqf/v2b+F+mgJWgHu/vTdlsYRobjU18NJLph+jvn3h9783yYHSUtNcqaoKyspM0ibUh01FhZlXVWWW2bHD1Ca56SbT3KlXL3jhhboYFRUmUbRgQfxkkssF110H27ebBNH115v1ZGbWDSWfl2eGl3c6oXNn+MUvTIziYrP9nTsnt9+PzXiMSm9dhzztstrRo3UPxh40lgxHRni+zWZjwtIJSb6rB5affjIdo8dLJjmdMG6cSQCeeqrpUD2UTEpE6HP/859NwnPMmMaX/2rtV7jt0Qmhvm37RjWFBsjPzCc/I/oig9vh5odNPyS+cUIIIZKWSEKpMxDRwyGbg/MSWaax1xZqrbcBBG/bRyzXUyk1Xyn1rVLq2AS2UQghxM/cprJNzN06N/zYbXdz4SEXkufO49B2h4bnV/uqeWLmEynZhm0V23h90ev4LFOFwq/9TFg6gU1lm5p4pRAtq7IS7rrLNCm7+WZYs8bUNkq0yVg8VVVmHevWwR//aOb5fKamyaZNdTWNIp10knnuwQehoMAkEJpq1haSl2dqUF16qRlm/u9/N6O/NWXVjlUsLamrOG9TNs475DzA1FyJVOmt5LEfH0tsgw5AlZWmVlq8703r1vDDD/Cb35hEUqKfazzZ2WZ9E5rI7X2w7IOoiwwAx3U7Lu6yR3Q5IupxpbeST1Z8sucbKYQQokmJJJTijbepE1wmkdfWtw3oprUeDPwReEMplRezUUpdq5Sao5SaU1JS0sQqhRBC7Otenv9y1GO7zc6Z/c4E4KJDL4q6Sr2lYgsLixY2+zb86/t/YWkral7ACvD3aX9v9lhCNJdJk6BHD1NzJFTzKB6XyzQ5uuEGuOMO+Mc/zHTnnXDjjXDccaZpUjyhBMONN8K8eabj7fr+7//gk0+gfXvIzd3z/XG7Ta2Xm282CYymPDvn2ajRH7Od2Zxz0DmASS6N7jM6avkVO1awvHT5nm/gfuzf/47//XE6YfJkGDAg+T6QGpPVSMtDrXVMx9o5rhyO6XZM3OVP7HFi1O+EpS0+XPFhc2ymEEKIBiRybWEz0DXicReg/njODS3jauS125VSHbXW24LN44oBtNYewBO8P1cptQboB8yJDKi1fgF4AWDYsGFNJamEEOJnT2vNwOcGUu2rZuXvV0b1NfRzZ2nLjO4W0bQty5nFQQUHAXB639O5f9r94ec9fg/PzXmOZ898ttm2obS6lP/M+w/eQHTvsz7Lx6s/vcrfTvwbhTmFzRZPiL1lWSbB88orDfdj1KmTqVEydiwceqipceRymQRBqIaJ329qG3m9pobQ0qXw8cfwn/+YZkkhy5aZzpZra2Pj3H67SVI1liBIVnY2DBrU+DK+gI+X578crlUIENABRnYdGX584aEX8vnqz8M1XfyWn2dnP8vjYx5vvo3dD+zaBQ89FP+79MIL5vvTUMIxFWZtmRXTL5Iv4GNb5TZe++m1mOV31eyK6kcLYHPZZtbvXk+P1j1SualCCHHASiShNBvoq5TqCWwBLgZ+WW+Zj4EblVJvYTrlLgsmikoaee3HwBXAA8HbjwCUUu2AnVrrgFKqF6aj7+je+IQQ4gA0fsF4FhWbYeyfmPkENx91c8tuUDP6bsN3VPmi21ic2ffM8MnBYe0Pw+1wh5cJ6ACvLXqNcaPHNVuHqw//8HBU7aTW7tbs9uwGTDLvge8f4LHR0lRG7BssC664wnS4HS8B0KeP6fj4tNNMp8kZwW6E4iUEHA4zhfrCGTwYDjnE9HMzZYoZyW3FCvjDH+KP9nXmmfCXvzRvzZWQphIYE1dNjKlVeGKPE6OGkD+l1ylRyWqf5WP8gvE8fOrDuOyuZt3en7PnnjN9aNU3aJDpWL05k4WJuPebe6M+NwBPwMN9397X4GvqJ6D82s/9397PS2NfSsk2CiHEga7Jy9taaz9wIzAZWAa8o7VeopT6nVLqd8HFJmGSPquBF4HrG3tt8DUPAKcopVZhRoF7IDj/OOAnpdRCYALwO631zr3eUyGE+BnbXL6Zmz67Kfz4ril3sXrn6hbcoub11OynqPLWJZTyXHmce/C54cdKKU7ve3rUaxSKT1Y2T/8YZbVlPD376fDJS64rlysHX0muy7Tb8QQ8vDD3BXZU72iWeELsrSuvjJ9MUsrUFlq40CR6MjPrkknJCDU7GzPGNHG77jrT/MyKzt3gcsGLL6YmmZSIx2Y8FtXHTo4rh4sOvShqmVYZrTi8/eExr5X+daK9/3782mcPP5zemkkh0zZOizu/0lvZ4BTPpys/bThIhw7mjybdU4cOzfEWCSFEi0uovYTWepLWup/WurfW+h/Bec9prZ8L3tda6xuCzx+utZ7T2GuD83dorUdprfsGb3cG57+ntT5Uaz1Qaz1Eay2/9kKIA5rWmkveu4TagDnSVyg8AQ8XvnthzJX5n6NyTzmfrvwUHdHFXm2glpN6nhS13LkHnUueu65LvQpvBY/PaJ4mK4/PfDzqvfRbfv5y3F8I6LrL9RYWj/74aLPEE2JvTJxoOjOOl0waP97UFtrbTpND7Hazrt694z9/5ZVm1K6WsLl8MzM3z4ya5w14GdM3duiwiw+7OGq0twpvBY/NkBqHIR6PGd2tvowMOPbYxDpHb07FlcVU+xpox5nsuqqL8frjVK0DMxRhS2ipuEII0cz2nw44hBBiP/Wfef9h/rb5+C1/eJ6lLVbuWLlfjFb09uK3savos5VBhYPIdkVXeRjVa1RMc4bZW2ezpXzLXsWv8lbx8PSHqfGbMbIVirP6n0WbzDacf/D54b6qav21PDHzCco95XsVT4i9UVkJv/51/GZuTzwB552XmtpCkybFH0b+0ktbLqH04twXY+b1ye9DQVZBzPwz+50Z0+/c3G1z2bB7Q8q27+dk0aL4NdlGjIj/uafaM7Ofadb1vb7o9WZdnxBCCEMSSkIIsQ/bWLaRWybfEu47KMOREe7zo8pXxV+/+Ssrd6xM+XZMXj2Z+765L2okpeby+MzHo/pPyrBncNFhF8Usl+fOi2m2opRi/ILxexX/mdnPRNVOynHl8NuhvwXgmqHXkOWs6zhEo3ly5pN7FU+IvfHmm/FP8EeMgKuuSl1yZ2EDgyoOH56aeE3xW34emv5QVB87CoVlWZz91tkx0x1f3RGVlAfw+r38cfIf073p+6Tdu00Nt/p69Giemm7JenvJ2826vlcWvtKs6xNCCGG0wE+EEEKIRGituWTCJVG1cgYWDiTPnceUdVOwtEWtv5YL3r2AedfOw25r/jYJlra4/9v7ue/b+9BoJq6ayEcXf0TH3I7Nsv7F2xfH9gWl4OCCg1lRuiJm+RN7nMhP238Kj+gUqjV097F3x4zuk4hafy3//P6fUU0rnHYnJ/Q4AYCjux5NljMr3DdHta+aB394kJuPujmmBpUQ6fDaa1BVFTv/oYdS22lyvL51MjPT3xQq5OEfHo6psajRLN+xnOU7lie0DguLD5Z/gNfvxeWQzrnj2YNitVms3Nm8F0pmbJ7RrOsTQghhSA0lIYTYRz039zkWbl8Y7scny5nFo6c+ysOnPIzbbnpItbTFmp1reOTHR5o9fnFVMceNP46Hpj+ERmNXdhYULeDgpw/myzVfNkuMyz+8PHYUH7+HiyZcxPAXh8dMz855Nmp4cICS6hKenf3sHsV/ad5L+AJ163PYHFw+8PJw0xilFFcPvjpqJKiADvD83Of3KJ4Qe8PngxlxzotzclJfUyhe4sjna7mEUnP1f6TRPDT9oWZZ189Zq1agdez8DRvA74+dn0rT1k9r9v4BPQFP/OaNhYXNGidhLRVXCCGamSSUhBBiH7R+93pu++K2qKZgAwsHcnS3oxnYYSDHdT8unPSo8lVx3zf3sbw0savyifh2/bcc9NRBzNoyi2pfNRmODOzKjs/yUeYpY+xbY7n9y9tjmpAko9pbzfyi+THzNZoKb0XcKfL9iPTADw/End8YX8DHvd/eG7VOl93F1YOvjlru14N+HdXHU7Wvmr9P+zsef3QiTIhUKy+PX2OkT5/4NYiaU/v2sfP8fti8ObVx41lWsoyS6pJmW9+4GeOabV0/V4cfHv87NH16amu+xfPsnD27QNCUp2Y9FTuzqMhk0hKdGpPMeoqKUrKPQgiRbpJQEkKIfYylLS6ecHFUc44sZxaPnFpXC+mhUx4K11ICwk3f9raPo4AV4J6v72HM62PYVbsLn+Ujy5nFtUOv5esrvibbaZp51fhreGr2Uxz1n6PYWrF1j2L98/t/7tW2RtpUvomt5cltx6s/vUqNL7ozmo45HTms/WFR8/q17UeP1j2i5nkDXl5e8PIebasQe6qh5kdNnec2hzFjwBbnqHHixPTXYPnTl39q1vXtqNnB4uLFzbrOn5uMDDjssNj5NTXw449gpXFA0SUlS2Lm2ZSNnq17cnj7w5ucuuZ1xRbnFOen7XGGsRNCCLFXJKEkhBD7mGdmP8Pi4sVRQ9YP6jCIkV1Hhh8PKBzA8d2PD9dS0mjW7VrHgz88uMdxt1du59jxx/LIj4+ERzzLcmZxzZBrGHfaOEZ2G8lXl38VTipV+6pZuH0hhzx9CJNXT96j/WxOd0+9O+FlA1aAv0z9S0xn4NcMvYaAFYiZfjv0t2Q6MsPLVvmq+OvUv0Y1lxMi1Vq1ip9UWr4cXCnuAmjMmPgdfj/1FHgbGJE9FSzL2qPypim3fXFbs6/z5+acc8Dtjp1/662prwEX4gv4WLVzVcx8u7Iz77fz+Om6n5qcvr7iazKdmTHrmLttLjod2VfRbIoqili1I/b7IITYd0hCSQgh9iHrdq3j9q9uj0p0ZDmzeOSU2D6S6tdSqvJV8fdpf2dpydKk4z4z+xl6Pd6LmVtmhjuodtqcHNXlKPq37c/zc5/nuTnPsaBoAdcPvx63zcT1W37KPGWc9eZZnPHGGTGd5DZk8fbF7KrdlfR2NubNxW8mvOyfvvgT2yq3Rc2rDdRy51d34rzfGTPdMvmWcJItpLSmlD989odm2fYQS1t8uPxDSqqarzmP2H/Y7XDSSbHzPR74+msINP8gjGEnnBC/htLSpfDee+lLOExaPSkq2R5iUzZyXDlNTqGEeH1T10894JMN110Xv0+suXPho4+gujr2ueb24+YfcdqcMfMLsgpondE6oXX0atMLTexnWeOvadam4SI1tNZM2zCNs944i07/7kS/p/ox7IVhvLvkXbmII8Q+SO0PP57Dhg3Tc+bMaenNEEKIveK3/LR7uB27a3dHzXfb3RTmxO/As7iqOCaJk+3MpvTPpWQ4MpqM6fV7GfXqKL7f9H3Mcw6bI+6BPZjER/3OtAEyHZlMu3IawzoNazTuGa+fwaTVk5rcvmRN+uUkxvQd0+gyfstP5t8z8eu9b6djUzZq7qpplhGitlVs48IJF/L9xu/JdeXy3oXvcUrvU/Z6vWL/8uabcO21UFkZPf+gg8yJfyr7u3n2WbjttthR5nJzYd486N4dnPGLjGZz0YSLeGfJO1Hz3HY3t428jSsGXZHQOka9MoqN5Ruj5mU7s5l06SSO637cnm9cY0OipfJ4uxnj/vWv8MgjpqlbJLfbNH079NDU1oa77cvbeOzHx2KShmcfdDYfXPRBwusZ8dKImJHdMuwZ/HPUP7llxC17voEt9RkfAMo95by68FUemf4IpdWlVPmqcNgcaK0J6AA5rhzsys4Nw2/guuHX0SWvS0tvshAHDKXUXK113IN7SSgJIcQ+4ty3zuWDFYkfMDfmxB4nMvWKqY0uU1RZxJDnh8TU1AHTOXVkE694/JY/bifZCsWnv/yU0/ueHvd1WmvaPtQ2poaSQtEnv0/UiGoNKa0upbiqOOYq9FWDruKlsS81+to7v7pzjzrxbshNR97EuNHj9modHy3/iMs/vJxqXzUBK4BGk+nI5OrBV/PIqY/gdsRph5IsraG2CCpWg6c0OO2Amm1mqt0O3p1g+YEA6ABoC5S9brK5wV0AmYWQ2Rky2oO7rZmX0QHy+oEzLzZ2wAPly6B6M9QUmVhV66FqI9RsNdtieYMxQ3FtEXGdwbidIKsrZHeHzI4mZlZnaHUI2JtOoO4PvF6TPFq3Lva5226De+6B7PiVcPaa3w89e8bviLtTJ5PQatMmfrOpPVVdXZckK6sto8OjHWKS6BmODJZcv4RebXoltM47v7qTR358JGpQAYXi3IPPZcKFE/Z8Y/eDhFJFhfmMd+yIfa5tW5gyBfr2bb7EZVVV9Pe175N9Wb1zddQyGY4MHhj1ADcddVPC671ryl08+MODMaPFjegygulXT9/zDZaEUrNbXLyYf//4b95a/BZKKap91WQ6Msl0ZvLwKQ/TNa8rN0y6ga0VW6nyVeG2u1Eoju9xPLeNvI2Tep6EauxzEULsNUkoCSHEPm7quqmMenVUs67z/Qvf55yDz2kw3nnvnEeFpyLqSrDb7uaMvmdw9eCrEzpAW7FjBXdOuTPmBC/LkcXvhv2OB095EIfNEfXcrC2zOOmVk2KSUe2z21N0a1FCcZeVLGPYi8PCzfNCWrlbUfrn0piYIZZlkfGPDHxW81Wbd9gceO72YIvXHqgJ1b5qbph4A+8sfYdqXzUKhcPmwGFzUOOvIcuZRafcTnx08Ucc0u6QJFe+BbZPheLvoOQHqFpnTnjsbsAO2V0hpwe4g0mhzI5mcrc3yyi7SeqEkjz+KpMIqt4CtcXg3QHV26BqrZl/5kqTaAKo2Q7bv4atk6B0ukkc2TPMyZjlB5RJBGV2MEmhzA4mQeXMA5vLxNYBk2TyVUDNFpMMqykyt9VbzfM2R3TcA8SMGabpW/1aJAB33w133tn8SaXQif/cuXD88bG1lAAKCuDDD2HgwPj9LSWjttYkk849F775xsx7ds6zMaNfAnTJ68KmWzYlvO4Zm2dw6v9OpcJbETU/w5HBtlu3Jdy0KsZ+kFACU9vs2GPjN3Fzu+GJJ+Cyy8z9eE3kElFdbRKUV1wBHwSvoxRXFdP1sa54A9GdcuW585h82WSO6nJUwuv/ZMUnXPbBZZR7yqPmu+wudt++O24fSwmRhFKzqPRWcudXd/LS/JdimpMD4Saqoc7VNZoafw1ltWVRF5IUCpuycVa/sxg3ehzdW3dP2z4IcSBpLKEU/4hbCCFEozx+D0qphGrTNMXSFme9eVYzbFW0iydcTOVdlTjtdW1QAlaAv3z9F8bNGBdzEJflzOK6Ydfx8CkPJ3y1b0zfMYzsOpJRr46i0lvXBqfaX81zc59j6vqpfHzxx3Rt1TX83NOzn46JrVCc1e+shOMeVHAQWc6smISSpU2HvWf0OyPu6/71/b+aNZkEpqbWPd/cw/0n3Z/U6+Ztm8fYt8ZSWl1Krb8Wm7KRn5nP11d8zZ1f3cnU9VOp9lWzZucahr0wjAdPeZAbh9/Y9Hu07QtY8i8o/dHU7PEHP5fMTtDv99BlLOT2NrWGtGWSMja3uU1UwBusUeQ3CSA0OLKhZDrMvw12zjHr9AdP2F1toNMZ0PlMKBhhEleBGhMfG9hdjdcwCnjMRLDmkj3TJLVKpx9wySSAo46C22+Hhx6KPen/xz9g2TJ4+WXTNClzD8+bQ2prTa2oa66Bt9+GoUPN7QUXxCa0SktNIuKKK+CBB0wtltzc5ONZFowfb2pbRdaUeXzG4zHJJBs2zj3o3KRiDO80PO58u7Lz+k+vc8MRNyS30fuZIUPgtdfg0ktjP2OPB377W3j6aRg3Do480vStlZFgBcHycnA44Mkn4V//grKyuue+XPMlLrsrJqFU7atmUIdBSe3D8M7D8fhjm2VnODL4buN3nNr71KTWJ5rHprJNPD37aR764aG4/VyFVHoro44pGqIxzeE+XPEhH674kMsGXMatI25N+vsihNhzUkNJ7H+sAPjLwVsGvjLwlYPlAyxz8qItQIHNDtjMSZQjF1ytwNkqeIU8xZ1AiJ8tv+XnsRmPcedXd9LK3Yo3z39zrw9MH/3xUe786s6YREfHnI6ce3BiJ0qfrvyUDWUbouY5bU7uOvYu7j3hXgAqPBWc/OrJzNk2J6YZQJYzi+uHXc9DpzwUlbCwLNi1C4qLYfv2uqvKgYC5tdnMycGa2tncvfIkaq3oA0CFIsuZxcRfTuT4HsdT7aum4KGCmIRSnjuPN897s8FmcvFc+eGVvLLwlZiD0lN7ncrkX8UfBar/U/1ZuWNl1Dy7sjOww0AKMguajLmzZifziubFvH89WvVg7U1rE0qIWdriwe8f5P5p94ffB4fNQfus9ky/ejrdW3cnYAW47IPL+HjFx+GkWbYzmyM6H8Fb579F++z28Ve+fBwsvBsC9bIMh98Hh9wGWkECfWslzfLBtLNh+zfRsW1OOPx+6H+jKXudSWYXRKPuuy9+UgmgdWu44w7T0TJAXpyWiI2pCOYCn3vOJId27oyugPGf/8Af/hC/lhSYcuGXv4Srr4YjjjCJIpcrtqmU12vW4XRCURG8/jo884y5H6I1LChawNEvHx2TRM515fLxJR9zQo8Tktq/8985n/eWvRczv3eb3qz6/ao9a0Kzn9RQChk/Hm64oeHPGEzzywsugMsvN31o1dSY343QJmltPnebDaZPh//+Fz75BHbvjt3Ec98+lw+Wxzb77t2mN6v/sDpmflPyH8yPaVptUzauG3YdT53+VNLrA5rvve7QwfyoplthYfQfVxpY2mLK2ik8NP0hpm2YBhCVNMx0ZDK041D+Oeqf9G3bt8H1aF137LHbU8ojMx5kwjLTUbeF+U22KRsuu4s+bfpw+zG3c/4h58ftT7K62pRpO3ZE31ZU1MUIBMzk85nJ7zcfv9NpJofD1NAL3Tqdpslv27aQn19326aNWUaInzNp8ib2H9qCilVQvhzKV0DZUvO4erNJHAVqzJXw7O6Q3Q1cBeaExuYE5TDJI+UINuHwm5Og0K13t2mWUbXe9Odhd8FZq0wfIfuiQK3p/8S7M5g089ftV7gfkoCZr1Sw+YqjXn8owffD1RpcbcGdL8m0RkzfNJ1fffAriiqLqPXVYmGR5czixB4n8vyZz9M5r3PS61y1YxUDnxsYt7bQN1d8w/DO8a+k17e0ZCnDXhgWs55MRyYzfjODAYUD8Aa8nPfOeXj90Vd//QHoYz+RQ3fdzowZirVrTQJp507T8a/DUXdCYLOZGg92u5m0NgdZXi9Ut5mD56h7sZQPy6pLNrmcMP7aP3L+4NP438L/cf2k62OuPLrsLnbdvossZ+IdczTUpMFtd7Pplk20y24XNX/ahmmc/vrpMTUcWrtbU/rnUuy2pttuWNqi8OFCSmtKo+ZnO7P54KIPmuxEe/bW2Yx9cywlVSXhTsEVihxXDhcdehHZrrp2Slprpq6byvLS5VHLOm1O/nLcX/i/4/8vNsDUU6FoChCd8GLMQtPPUDK1kADe72Cas+2pIeOgzzXgSGFP0Qe4cePgrrtMwibeIV1GhhkO/owzTDO5Nm3MskrVNVeyLDO53abGyNSpMHGiaYoUmUyov/6pU02TtOpqc8LVkJwcU5Olf3847DBo187ErqyEJUtg5UqYPx/Wr4//eq3hNx//hv8u+G9MZ82ZjkzK7iiLqomZiLcXv801n1wT0+wt25nNt7/+lqGdhia1PmC/SygBfPcdnH22OdFu7DMGc0Ldu7eZsrLMyfju3bB8OWzd2vgmWtqi9QOtYz4PgMsHXs4rZ7+S9Laf8r9T+GrtVzHzu+Z1ZeMtG+O8IgGSUErazpqddHy0Y/hCTOht0hraqX4cW/4s1rrj2LbN1HIMBEwCvG1bU8MxdLxhs9UlcwIBc9yx276SeYV/oDhnStS6wfxevnjCRNpXnsK338K0abBli4nhcpkyacgQkwjt2tU02W3TxiTjs7PrYkZOWteVl6HJ6zV/H7t2meOm4mI488y9b/YrxL5EEkqpcu+95vJgS7jnHhM/3VrqB3BEG3jkdNjyiUmSKDv4a0wfIN0ugk5jILef6QfE8pmmGOhgAkUByjSTwGYea42psRRxqwPmNTanaXrhLTMJlpbiLTNNVkpnQMUKqFxv+g7xV5tkWVZn0zmtu51JemUUmv0PJc+Uo65TW4hIMvlNLS7LA7UlZp21xeApgYH/AnebltvnfdSO6h384bM/8MHyD6jx14RP6m3KRm2gFofNgcvu4r4T7uPmo25usP+e+gJWgKEvDGVR8aKoGi+hzia/vuLrpLbz7LfO5tOVn0adcIU6ul5y/ZKoE67Fi+H552HyZHMSl5lpDopqa6FLFxg+3BxoHX646Wy3XTtzpS072xzIhQ6qlDKTw2FONnbvNlf6iopg7VqYM8ecKM6aZeIOe2EYc7fNjdn2PekotcpbRf5D+THNIzIdmdx/4v3cOvLW6BhxRv1xKAfXDb+OJ8Y8kXDcP3/5Z8bNGBdTo2xIxyHMvTZ230JunXwr/57x74TjNOWgtgfxw1U/kJ8VUU5VbYKvx5jEuBVqUgbk9ILD/grdLjR/+46cxJJLe5tQGvok9L4amujgfe/i2uCXscPIp5vW5mSiqMj8DZSW1k3btpnnfD5zUmKFfnaCf0dQd54aOnFRinBi1u0254Ht25uTnsipY0dYswYuuQQ2bIjft1GkTp3q+jgKnfBUVZnkzsKF5oSrsX2sb/t2Uzvl++9N8ikVh5XV3hoKHi6IqZ0EMKbPGCZdmvyIkbtrd1P4SGFM+WFXdn414FeMP3t88hu6HyaUAEpK4PrrTZLR46n7zjYXrWH+tvkc99/jYi42ZDuzeXz041w95Oqk1/uv7/7FPd/cE1NWZ9gzWPn7lVFNsRO2n37GqeT3w1tvmQT1lCnmWMPlMrt0zDEwerS57doVWrUy5aTXG1s2ho43QofxoSlEa/Ocy2XKzEWLYNAgc3wT+b0dORJ++KGu1tHeNgtuDn7Lz/RN05mwdAITV03k0sMv5Rf9f8GQjkOwqeT7Zzxg+avqBh3xlplm977yuskbbGNrC15gDx0jhc4H0YDCnC9i7it78KK9z9x3BVuzOHLNrTPPtHBxF0BGu/12gBBJKO1LGvtBCAS/qPvySAUtkVAaCVwLOBVENm056FYY/KDpyyPZk5V9mb8aPh8OlatMPyG+KiBgEkajpkJun2DfI8HkV7J9n8Rjec376JTLKZEsbfHSvJe49Ytb8QQ8eANeXHYX7bLa8dXlX7GkeEl4ZC4wB74dcjrw6jmvMrLryCbX/9APD3Hft/fFnCRlOjKZduU0hnWKW243aFnJMoa8MCS2g2xnFrccdQt/P+nvLFoEN91kOvWNPMDKz4dbbjHDkefmmoO57Oy9r6ZdVWUO2Fq1gnW71nHIM4fEHaEp2RF8Qo76z1HM3DIzZn73Vt1Zd9O6cLOVWVtmceIrJ8a811nOLKZfNZ2BHQYmHHNZyTKGvjA0pjZYtjObzy79jGO7Hxs1v9Jbya8//HXc5jUKhdPuRNF4ue+3/DE1M4Bwn0sDCgfUzdQadsyCFY+b/pT8laaT7UCt6eeoYCS0PcJMrQ4GV76pQWT560ZaiyvYVNjmhrca6DvMng2BiIyGzQWDHoQ+15r1JtrkLdlE1i/TfyyzYYOpofP556Ypz/bt5ue7Y0dzwjJ0qBkNq1Mnc6W9VSvzt6VUXVK2/klR6GQplFCy281JT3m5ufq9YwcMHhz/BCgQMP3e/O1vZluaSiwlKyenrhlcPLNmwZ/+ZDrtDvWD1Bwxs7LgkS/i12zMceXw9OlPc/nAy/do/UOeH8L8ovkx8zMdmZTcVhJVYzAh+3myYckS+OMfTfIw1Axob2Rnm82rqoJ/TPsHf5v2t5gEX44rh+lXTefwwsOTXv/UdVM55+1zYmqxZjuzGTd6HL8Z8pvkN3o//4wj+QI+1u1ex8odK5m+aTpZziyGdRpG/7b96daqW0K1esE0Y73sstj5d94J//xnXeK8uZWVmdqZM2bU1casrjZl9NNPm3I6L6+udmeoVvWedDbv9ZopVLa3bt30a0qrS/l89ee8tfgtvl7/dczxiUKR587j9L6nc/4h53NKr1PIdUuz8ShlS2H5Y7BzrmmxEqgxxyhth0PX86DNYMjqYpJA9ixz3mT5THIoKpkUEkooBYWzmcFWHjanOU7yVwe7SGn8IFlrzebyzSwuXszi4sV8s+EbJq0yF0CO7XYsp/Y+lcPbH86h7Q+lZ+ueCf9NtQRJKKWK1qZmR/ky0wSrZpsZ/cazPVg7xGUO0h1Z5sttz4CTn4QdcTqZK2gFc16IbqqkreAIN8GsaqDKnPQHamDIo6aZUv3t8VeZkwd/pRkZx19p5kWuM7IvIR3MxipbRA2eyPt2cyLiyDGTM7fufiKdETfHD+C2L0zfHFqDFXEi2v0SOOqlYCIkN7jNCdjXr3z7KuCDjnWd1YZOzrK6wpnLgkmm8mBNqsym93tf39+9oLWmtLqU1hmtk27u0JRpG6bx209/y4bdG8KJgwx7BocXHs5LY1+ilbsVYJILl75/KeW15fi0Obp2292M7jOaJ0Y/QbfW3eKuf0XpCgY/Pzhu59Qn9DiBqVdM3aPtPuftc/hkxSdxm4W8PWoOl556CJWV0X9+hx5qrtY1Rwe+jblryl08+uOjcWsULfzdwkb7TmjIv3/8N3dPvTsmSZXtzOabX38TTsqNemUUU9fHvqc9Wvdg3U1xxl9vQv8n+7Ny58qY+Ud3PZrvr/o+/HjWllmc89Y57KzdGbWNGfYMBnYYyHsXvpdwM7/n5z7P3779W9xmjfefeD+3jLgl/pXMmu2wa5458No519x6dwSv3lWhbXYCOPDYs7FntMOZUYjN4UapYD9zod+PQK1pYuspNTUb68sohKPfNp1y715kDrRCHYK7C0yH3J3PgrZHQUaBqWUa+v2xZTT+mxLwmppV78Z2BLR1V0fWDtzKhg2mWc2uXaZWkM1mkhGhJpsOh5mcTvM9z8qKbsoQSuTUb9KgtTlRqKoySVi/38R4/HFz0hGI+FMbNgxmzzbLOxypOUlqitbw7bem36NvvjEnR6G+z5Jht5sTfo8HjjvO9Md00klNv27mTHjxRXj/fZNwqK1NLnZenol59NFw5ZVw0UVw5MvxEz8uu4vNt2yOad6aqId+eIi/fv1XPIHozptzXDk8NeYprhh0RXIrPECSDYsWwRtvwP/+Z/4WtG68n6UQpUyS0Os1NWCvvBLOO89c0Bj8/GAWFC2IeY3L7qLqrqqEa/5GKqsto93D7eIOxHBa79P4/LLPk17n/vYZW5bF4pLFfLv+W9bvXs/a3WtZtWMVS0qWNPlaGzYGFA6gX0E/uud1p3d+b07ocQJ98/tGjXq6fbvpy23KlLpytaYGunUz5coZZ5jr1aH+t2w2U2aHmtonw+s15UcgYN6yVq3MOpcuNcnuTZtg1aq6pm+WZcqc3Fxo21bTtkCTn6/Jb2vhdIHbqXC5FC6nDYdDYVl1NZv8fnO/uto0c9uxw9TmKyuDr2JbWmJZFu8ufZcJSycwY/MMtlVuw26z4w14sSs7GY4MRvUaxaHtDmXOljlM2zgtfDHJbXfjt/x0b9Wdo7seza8G/qrJJvYHhCUPwMI7zf3Q6LAAw5+BvsEOBAOe4NUaZ9OVNvbwnElrzbxt83h/2fvM3jqbTWWbKK4uZmfNzrivtCt73IuErdytaJfdji65XRjUcRBn9TuLE3ucuGd9+jUzSSilysd9oHKN+YLaHCbRA3BhVV1/Ef6aYBOtYOfPtj0cEcryBTOqlklgbZ8KO+ebE4Pa7eagPacndDm3rjmUu51JtNizTA0eW0Ywk6rqmoGFqvRpDeiIW8scvAdqTQer/irw7jIZX3smNTXmB2L3bjNVVZkCNXQbKmxv/VPDfwCPPqLDPxShq7JQ1+kemB8TpxPaZW2kj+tdeqjXyA0sRtsyUMqGsilU4QlQeBK0GWL23R3sNylQW9eMzUQxN5/0B09x4u/98RNNAsdfbpI9vjLzvtndhJvQEWpWZw/WGnJEzMN0hKuCNaw05jb0vutARLY8mBnXftMcrWo9unwlAU85+CpRVjW2jNbo/CPRWT3QGWaYb5XZHuVuC+7WqKh+kmzw2UCUpyTx/W2BK/2JqPJWsbh4MYuKFzFn6xwmr5nM+t3rw88rFGf2O5Ojux7NgMIBDCgcQKfcTkkXwlvLt3Lqa6fGPZhy2By47e6Y+RpNrb82pqNmgMsGXMb4seOjDoYDVoDBzw9mcfHimA6lMx2ZfH/V9wzpOCSp7Q5ZXrqcIc8PiTsMb/s1N1P53r+pro5+T267Df7+d/P3lioBK0DhI4XsqNkR81xhdiFFf9qzPh2Wly5n6AtDY67s2ZWdywdezstjX2Zh0UJGvDQi5j3JcGRwz/H3cMcxdyQdd9yMcdw15a4G+74a0nEI90+7n4d+eChuAui47sfx0cUf4XbEfp8aM37BeG6YeEPc2lGDOwzmnQveoWNuxybXU1ZbxmerP+O1n/7HnPVTydK1FNihjR3cStEmI49ju4xkZNcj6d/uMOw2Z90FBndBsM+1tg33jVS9xfxObZlomu3WbDG/RQpT3imnabKc0QEyO5jbrK7mN8vmNM/rYI0pfyVUb4KaIlj/WlSY+esHMeTuukRDqCnEoEGmqWWkyJpAe5LoCb1eKXPCcskl5qQhtM7qatP/xrhxMGqUaY4WagK2NydIgYCJ5/MlfuU7xOs1V+c/+wy+/NLUqtq1y/SrVL/2od9vkj9t2pgTvZNPhjFjYMQIk5RKltbmBG7iRHO7dCls3lz3foSa9AUC5r3q29d8bieeCKeeapJZACt3rGTQc4PilmkHFxzM0huWJr9xQUtLljL8xeFxm9INaD+AhdctTG6F+0uyQWuoWmea2ldvNH97NVvNVLs92GxEgSOLpVsHMG3pESxc3YMFq7qzalMHKmvc+AN2lNI47AEK88s5uPtWhvRfx4Ceazll4DTyMzaZ40zloOKkbyh4pH3MxQbYw88hQpd/d2FLRWw7zixnFmV3lCWfqGqBz3hz+Wa6NNY8L8G4JVUl3PvNvazYsYKlJUvZVrmtmbYwvq45HTi0oD/92vbjoZMfxGXPYtGc7cz6sYbVqxXLVmawpSiDkp1uvP4M2rZ30q2rpkOhRfv20L69ol37ugsBTqfCEewMOxAAvw98Ph1O7JSXwbYiTUmxZvt2G5u22Jgzp+EC12/5mb9tPt9u+JaJKycxY91CaqsdYNnBcoC2m/vaPO6Y3ZURXY7i6B5HMLzLUDq1KozplLt16+iytcpbxZR1U3h29rN8vmYPEphNuHrQ1Vxy+CUc2/3YpEcdLq4qZvaW2czYPIPPV3/O3G1z6ZTbiQsPvZARXUYwvPNwurfq3jzJDG2Z8zJ/tTlfDtTUq+gQ6oIkWNEh9GMbqugQ6rokVOHB5gxW2Mg0ZVLFSihbbPrXrdlm5ik7ZHVDZxSEB13S7gK0K99UyrBnBdfpQAUHalJfn4byxh6n1ufV8FKZYk7nK5m7bS6rd66O6Z+zubjtTnrldmRQu4M4ouNgLjvsIgryupka5zZ32lo27XVCSSk1GngcsAP/0Vo/UO95FXz+dKAa+LXWel5jr1VK5QNvAz2A9cCFWutdwefuBK4GAsAftNbxh+sJarGE0oonYNP7UL4C7SkB5UYrB/S/GTqPRrkLTB88zlxzkh9KGlihjGTEe7/kAVj24N5tz1mrzVDQUJcYSqTWToLZ2E/mncHZ//4IS9ux280Bqd1uOuQcH9HVQOhqrt8Pmb06YCuOXbfVvpDyFfFPIENXiUOFtMtl+p5YuxbWrYOirT6oXIezdjn5rnV0yF5FYeZKsp07yLBX4LZX4HJqHNn5KFdrLFuwiqPNVde/UCiJY/lAe7BZtaidM1ANNvWIkNUNzt7Q+DLhgrAJke0cQu+NBU89Za7kLFpkrqYoZd7v3/8eRo6w6NS+gsLWO8hz78DFThy6jIA/QMAfiOicO4C2gn0mBZNdyuZAKztK2XEvvgnlL4venIxC1Ll1n4s/4Gd56XLW7lrLlootlHvK2Vmzkw27N7B612rW7FrD7trdANixE8C8f3muPHrl96JPmz70bNOTNhltaJXRio45HenVpheHtDukwRpFASvAml1ruGvKXczaMouiyiL8lj/u8LJ2Zcdpd2JpK+6BaGiZXHcu/fL7ccuIWziz35nkuGKb9mmteXfpu1zy3iVxE0OZjswmf6xrfDV4rdjtKMgsYMoVU8LNkt5b+h7nv3s+ea48rFAfKhr8OkAP+5Fc5ZgSNbpIIGD+HkK1LMz2mtvIr1lo3uv+c1lpTcaGI5zDVIDHFyDvpY3U7srHG7GZubnw0UdmJKbQ33Vz+3LNl5z3znkxHa4qFNcMuYbnz3p+j9artabDIx0oro5NEmc5syi9rZQL3r2ASasmxXyH3HY3q/+wmi55XZKOW1xVTLfHusXUbFAoRvUcxcHtDubJWU/GfG/8lp/RfUbz1vlv7dEVd4B3l7zLrz/6Nc6IDvQ1mnJPOYXZhWy9dWvcmkrLSpbx8YqPmbB0Agu3L8Rpc1Ltr8Zpc9I6ozUXHnIhxdXFfLLiE/yWH7/2k+3MRqM5pdcpnHPQOZzV/yzyM/egbzl/NZQtwVu5jq3F89ixYzG1ZcvRVRtoa/NTYAOXTeG22bErG3ZA2UxZZZLjTpPAqlxrfkeDvH4nExddzFrn71m5xs26jVnsKnNS43Vy9HG5FBS6yMm1U1BgI6+VIjcHsnNMsiLDHbzWYwObqrtfv38jHbwiXRW8aFJRAVWVmsuvsKG16XB4xgzz+7RiRd2V70DAXB1v3970f9SunUmcFBbWXSwJ1ZpyOOqSK6GTI5/PJKSKisz6QiMtTjn23r3qv9GHg010pYR2+HCiUbjwUkAp3diIk0aqE915pxnrfQ9poIxWeHERwI4bD7lUNBrzltPgyZGxV3MdNgd3H3t3eBTLPdoerSl8pJCS6tiLLnZlZ9F1izi43cGJr/DnnFDSGta+DBvfhZLp5jgiVMZ0GgMdT4N2x5oEsC3D1Bi3/IR/YaIuroXuR3ZyU+/CpbKFj8s+WvEpl39wOeXe6KZpCsUNR9zAk2OeTPy9qOe8t8/j/eXvx8zPdeXy+WWfJ9Q8PXqjUv8Z76rZxdfrv2biyol8vuZztlVsY+vDmg5xzleLcmDsv4/gnIPP4eReJzO4w+AGm83MWz+Foa+cHH5sAzo5bOTYbXTJ7cDRBb0Z1P4wDu8wmLzsjsEL0lmmNrwt1Cepre4W2Fm9k4XFi1i4fRHTt8xiW1UxFd4KtlbWHfsPdMGC7hEb4sgxn3+rQ+HUur4TLQt2lXrYvs1PdbUO1wIKWCp4v+7WbtfBstPc2m2h+xq320a7QhsF7TNwuuo+rxpfDf/76X/cP+1+Npdv3pOPJobb7mZk15G8eNaL9GrTK5x8eWPRGzw9+2lmbZ4VHlQjJMPuItORwendRnJS5wG0cbjMsbq2zPsS+hsJ0xTV7OaLLQv5YutCLK2prXfM67Y5Ob7TIP44+DJO6zXKVCSwZ5pmWfYsNpRvZNLKSSwuXsycbXNYXro8pilohj2D2kB0bW+33U3/gv4M7TCUwwoP4+ReJ0c3sQ/ZMRs2fWianVWtNYMG+Suh9WDoeIr5/Xa3D16IygluX0a9bjsiL9KHWHXvh9bBLjpq6yo8+Mqh4Ci0zU1pdSmrd67m0R8f5et1X7OrdlfUcZ9LQa4yPajYAHvwNvK+XUFAm96UAhpQilYZ+YzpdwYXHfpLerbtT15OZ7yenZz96gnUenabSheWJ1yBpFv+QYzqMoyRXUfQq2AAytUquL9Z5qJcuKaUivhbMuXl1oot/LhpBt9s+JYlJUsJV/LQFhDAheKZX7xMr4IkfpeayV4llJSp874SOAXYDMwGLtFaL41Y5nTg95iE0pHA41rrIxt7rVLqIWCn1voBpdQdQBut9e1KqUOAN4EjgE7AV0A/rRs+02+phNI558CHH5r7LoeHgtxS2ubs4ON3d9Kjc0WwI7DQbaX54gdrM5l3XaG1BVZkwRH8cilQ2FDLH4nujyLE2QaGPW5qKFWtN7VZfGWQ09tkLB154Mo1HYa5WpuRz5ytzI93qOZK6Pbr0aYZQxOiE0qaDLeF3aY59zwY/9+6EyOtdTihZFkqfHCeqLqEkvmR+OorxRln1D0famIwerS56hop1HY53AdFqMmg5aWuqV+gbv8J1hxz5qFtGVHb6rBrLhq9hELXXHLcFWS5KsjL2Enb3J2MvaAtzswclN2OzeZA2R3BhI0THJkoe0bdZxm63TgBtendJve/qjaLnKvNZ+5w1DUVyMysGxrassz85mxSEQjAYY8dzfKq5DpGbg559vYMyD2BdTVzKfJsINDYCU0zaJ+Rx6GtuzKmyxBuG3geqyt2cOW0x5hfupqqiGZJNmUj25nNv0b9i/4F/RNa96crP+XZ2c/GJJYyHZlcOehKHjj5AX74wcaY66fUPRdsZnbQQfDVy8dEnbDX1NQNXxtZky/ymDaydh9AWW0532/+xpwUY06WQ1fPRnY6no/fbcU995gT49raun4whgyB3/zG1A7o1s1830IdXCZTs8Lnq2sa5HabBPNlk87i05Wfxiyb58rjrfPfYkzfMYmtPI6rP76a8fPHxySMclw53HP8Pfzl67/ENIkDOKLTEcy8Jrb/pUQdN/44vtv4Xcz8TEcm7134Hrz+Grz+RtRz7gCcsB5se3nesbQdbGgVOz/PA0df+Ve47z601iwrXcZ5b5/H8h3L9y5gPVcPupoHTnmAgqyCBpdZs3MNE5ZO4LuN37Fm5xq2Vm6NOYAF6JDdAYCiqtiLDHnuPDrldKJ3fm+O6XYM5x9yPn3y+9QtUFsM7xfGBs8fCqOjjwu0Bq9H4/OrqGZt9Zu4RTZ/q3/fZjNJV5uNhAfm8OJkJ/mUk0cAO34cUbeh+wqNAz+mAaI/+Iy578RHG3bRmt3YKspjhw+yfCZpZ3mjp4AH8gc2voHF0wkfwEcd5IaOR4IXZOzuYAIgODmymh4VtBlOvl+a9xKvPn8deKObLbkD8OLH0L2sgRcm6OXB8Eqct8hhwf++K6DT2iRq+P6cE0q7F8OkOP0UdRoDJ0xK/ELZHrjqo6sYv2B8zPxcVy4vnvUiFx120R6v+6lZT3Hbl7fF/AY4bU5uG3kb/xj1j+RWmILPuMZXw/9N/T/eW/Yem8o3xb2oZVM2HDYHdmVHowlYgQYvtmXYMxjaaSh3HnMnp/c9va6GyfJxMO+W0I4QPvc49C4YGPE+hOI3a5cKQJuhULPZJBu0BTk9YMSrJqkQ6tzYnllX1hCsxR+ZYNEaFv8dlv4zoZBf1mbwRZcb+XzN5ywrWRa3mZFd2ciwu3HZXdgjD3R09B2v5cMT8OIJ+CLfvbDW7lyO7jSU03udzNbV/2PhjjWYVgfBmjhKkd/5ZK4aeh3HdT0aZbPVla+hWsA6QF0ShZgofivA52u+4LVFbwZrxNjqltcWY/uexi8HX8P8ooXM2jKLqeunxj322luDCwdz3iHncUTnIxjWaRhtFt8Nq54NP69V8ELaCZ+gOp4a/eLQuVioNlJMH5IKPuqW0Hfrm2o4sZGBJFLl1CyYHBzY2dLmO2NTFnQ4GU76sm7B8H5G1rCK42fQPcneJpRGAPdqrU8LPr4TQGv9r4hlnge+0Vq/GXy8AjgBU/so7mtDy2ittymlOgZf37/++pVSk4Pr+LGhbWyphNIzz2heeEETIEBNjUVlJeyq8PJ/t2dw6il2lFImY+4El0vjdpuTK5dThQ9SUcEro8H72gpew4m4Qhoa7cDjMdPatdD1pfsY8kmCVyid1CU/Q5Ot3rzQ33ToNvK+L3g7ErjBrLLak0lxeXt2V7Vmd9d7qco/O9zcraamroZSqFPRyBEZIpM29Zu8RVaBB3MSW+Px8eHK99i1JZ+dmzpQvSOfmioneZmZ/PrSTDq0d9Cho6awEHJzNdk5kJUJmZkKd3AUCRU6KVCgbAptaSwdLn/NiUawr4eamuCINxVw8smxf/itW5smA8kI7XPkKD6NKS83o3AtWQI//WSaCWzfbr4LHTua9t5t2pgpP990+NqmjbkaHkoyhabQ0O6RJ0yh4VbLysy+lJSY27dmv8A620qobgvVBVDbBiwHE96107VNIZ1yO1GYXZhUf0V+y09xVTFbK7aGaxsFrAC7anexo3oHpdWlDNj9NbO2xo6OZe92HkN6/4Jjux1Lj9Y9Gq92G3NFByo8lczYMpPvN34ftx1z++z21PpreWzGY3gCnqiDuExHJn3y+zD5sskJNSGK9P3G7znzjTOp9FZGHbxkODLIdGRyz2Gv88ljoykpUWzZYt57mw0OPhj++1+zbKtW5nPOzKyrzRBKLIX+furf1k84hWr5+f11I7i1bWueDwRMx6pffw2TJpnvW+RobVqbvpV69zY1LDp2NEPrdukSPYyv1nXrLyoyNeo2bTK1KbZsMbXsSqt2Yd3aDovYH0CncvHZ8btx2zPD+xLZNCmR4/Mfd3zK35ZeRK0V22wl19GGKn95TGy3yuFXbZ/k2NxfM2gQDIhzwa0pby1+i2s/uTam1pVN2XipT39+zbLYFw1/Fvr+Lv4KGxr0IIlhngNWgBmbZ/Du0nd5Z8k7lHnKqPHVhE867MqOQtGzTU/65Pch29l4p8Ml1SWsKF1BcVUxKMJ/Iy6bCxQc2u5QfjXgV5zacww/LF/Noh1zmVvyHct3L2SXpzShbU5Wvrsd/VsPZFi7YzgsfwgntmqDs+JH/L7tBGq3UV61jJqadeS3PZys7A5kuPNwuVrhdObgdOZgd+SinLkoh+mDTkX0HWhb/wa2Da8ntiEZHSGvL1H9EWoLBvzNXIUF6g6UFbRtpBnrzgXBO/EOruvV8ph5jekTq76xG00zwvoaG0wj1UOIN8fJd9ly6DUEdibQSU9za9cGFr2P1gq9+SM8/hq82sJvWVho/DjwHXoXfu3Hb/np18iFh7U71+BQDpx2Jw6bI5wgcDvMiaxCRf3Gaa3xWT68AS87qnewtWIrNb4aPAEP1b5qqn3V1PhrqPJWccvIPzYY95lZT5PlzApPod+h/Mx8uuR1wWl34rQ5sSsbrHkRNk6A0unBqxEO8zl1PhM6jYZ2x5i+0mwuc0U+3DdRvZoFSsHifyZ00q81FK6DkjjnR1nOLBZdt4hebXo1uZ6GzNw8k1NfOzVuMvuggoNYdkOccroxzfCd9lt+5m6dy5drv+SD5R+wuHhxg7Ws94ZDOch153Jyr5M5q99Z9OFkrj1rF307rqF3+9V0bbuB9nnF9OlaypAR7cP9vipHVrD2SEbdiFb2rIgaSjaUssEPvwRfggfE7wGRFcUcQBbgbmCyYw58MjLNwbvNZqohha6QWRYEglPo4vy55WadEUZvgVXe2ORPQfvh/GrArzjn4HOSrqXst/x8v/F73lz8JlPWTolJADrtTn7s7Ce/Zm3dTHumSRr9Yo1pNl5fIPT3FOcq/JJ/JdyK5f4dNu7bGX3EowCXzYFGcXhBX47tNIRhhYfRIatdxM9NnO+1gt21FcwrXsoPW+cxp3gxgUAAr+XDqveOHjTvddZ/dg5d226ie8EG8nN20iqzjJtvKOeQg/zBGlgBwv0yAuGBhSJrNIa2Y9G9pkJGE95ccAK/nDsSdvaBGvO7q5Tpe++233bh0HaHxnQtEDoXakqlt5Kfin9iR3VpxLG1pqiyiBVbtvHKZb+nT+Fq+hSupmvbTRTkltC703bOOZvg348rmCB1Bbu9yazriziyOZ+ywezrg12qJELBLxPYgWa2twml84HRWuvfBB//CjhSa31jxDKfAg9orb8PPp4C3I5JKMV9rVJqt9a6dcQ6dmmt2yilngJmaK1fC85/CfhMaz2hoW1sqYSSui+BKzWWgoAb/Bngd2OyRjbQoQxS8HHovrJAaXOLNvdDt3YPODzmj6bDT0lt67aHiV9VNhs63pbYOtwKBrigwA4ZCjJtkKmgtSuHTvn9gwcqmWQ4M3HbnLjtThw2J3abE5vNJNjC/5Sie9lsulXMbjJuVQBy1jaygAYCLvBlgTcbfNnBts+2elPovbcH3+eGpgC4qsBZzT0zd3Lvt3WhfDioIJcaMvHgxoObWjLCtz7lQrmc4fFQtc1k07Symftao7QpyZS2sOkA+ANojwcV8OPGQwa1DL83NrkSl6XMfvuyo/fVskc8tps3KbR/tkD0vioLXJXgrMHbdhDOtguiQ1gK74hPCXQ4PdwUI1QN2e+PPfkPP17xFHrVsyhl9lUpC6XMkwpz324L4LT7yHDV0Oqg01HabwpUX7n5ISk4Gtofa1ZozzA17uwZwckdrDpqJ5wZVTbTFHVlYtXj/7BgME9mzw8mUeuyfMqmubjXMYw/5kbcDgfhfq+CV5jqMrFEXOSLLEsVG6tKOG3y/aws3xo1gldAW3S0w9b5hA+uNFBNFrtpTSU5VJNFFdnh2yqy8Ssntkw3KsONpexom5mw2dA2B8oKgBVABSebDqA9XqzqWuzaH1xLFae+txgV1YeYBkcOeuwmNm5xs3Chjc1bFEVFpr+VLVsURUWK0h2mvzSfz3wnQIc7MNZamc/TbipOtGkDhe01nTqZmk4dOnm5Y9ot4I79sXzy9pHceMSNMfOTUeuv5bYvbovpn0lrzTszv8PK2lb3eQW1zsxl4y0b92rElBpfDV0f6xpu9hmOi+a3mV05csNpbNvViR0VbdhS2pYdlW1xtT+c/gM74M5QZGRAVpYiK8s0wcrOgqzgyHr1a8gopcPNrywNVsA8rq3VVFVqqqssaqr9vLn4A37s9qu6jbHM74uyaQ5tdwh/PvrPXHDoBWQ4khvWdmvFVp6d/SxPz346fGJmaSucqFK7eqMDdnDUBn+3jKxsGNqrB7/o/wtO6nkSAwsHJjyKScAKsHD7Qqaum8rHKz6O6jMNTOLO7XCzckds5+j7oub4HQb4Sz5cnGPKDbsKniwoaH/Us7jbjwgnyJSy1SUpImrl6sgybPljqBWPJRR3fi0Mjve1udgPDX2mzXDy/cUzL3Bq69/GPjFkHBx0U/wXNZac/eJ3sLjpC3IvrTqI35Bczb7m+oyT1dxxFdDbCd0d0N0JhXbo7IBODnO/nTuL/My2ZGUWYHMXYHPno2xObMrU2tbY0TYHBI9zLMuP1gG09mPf9B7Kqmsq7LGgcLGiLDP2+9BtN6wfF/dUN2G1DujyR9gRp7s3uwXYICt4PBuaMmzmWqzbZiPHmUm2M4OM4HHtS7/b1GCsP/3X1PDSaCytgzWJLAKWH7/lw2P5qAn4yN1SwMvu6ESWCv5/SLtD+O3Q33LhoRdSmBOn9mUDtNbM2DyDlxe8zNuL3w6PiBhZgymnYjCVj8Ymo085Bb74IuFQoYCQaNcae6K5aoJ9c4ZJSoeO4QjWFjnuA9NyI+aYLuJ4MirBr2D5v82UgH9efhd3BYIJ1QxMois7eN8VMWW7ICcTsjPBHZzCybPgAYAjePUuEFGtNmDBEcvAFZ2JfWbGLzhq0Mcx2+McMZ6D+1+WXFP7n+6NKiu1hlU+qIyTy7htWT+mLhhrzikCLvBlgi+bYX17cMLgrlh+O9py4LQ7cNqcOO0O3C4bbpcdhz10bmgu+ptPQGGh0VbwG6w1Fhqvz8LjtfD6AvgCfsorA/TIPoQtW+oujof6CRw50lyUDR2XZmXVDciRkRE+VYupjVy/5rLWpkJHbW1dxYnSUvjzn828UKUJMBddV6+OHqwDor/Okcs3NS/0vkfeprK/08bsbULpAuC0ekmhI7TWv49YZiLwr3oJpT8DvRp6bSMJpaeBH+sllCZprd+rt13XYgaTp1u3bkM3bNiQ+DvSTLwBL/HeP6VU0h2jxeML+OJWe/UGvHgCHmr9teHpq7VfUVxVTLmnnEpvJVW+Kqq8oamaKl8lVb5qMhyZVHjKyXZlk+XIItuVQ5Yzi2xnNlnObLJd2eS6cslz5TKy69F0yetKliuDTGcGGQ43GY6MuH1zOO3O+KMLJSFUfTdmvg4kPApSWDNc6QfTjj30flb7qllavJQp66aw27Obck85Vd4qKr2VZhlvFYvuL6VDnEH8tucohtzXkRxXDjnOnPD73DqjNd1bd2ds/7Fku7KDn0MWNmVjV+0uSqtLKa0uZXHxYp6a9RTlnnJq/bVxq+wmQqGw2+xkO7Npm9mWe0+4l4KsgvDUIacDmc4kh/lqpvd6d/t+rC/JYgPdKaWAMlpRRiv8+e2w8gtQ+W2wtc6D7BxsWZm4suy4sxzYneYESdnMhFLBglmDpYMVByy0pfHWBPBUB/BXedDV1Rze8X+cc3zsyZQa+T9cveKMcduUelVWtTYd98Xjtik4a2XdgiGhJiSh45hQsqrPEVAcp8ZH+wKYeCmsfDyxbYwcBSPEkQsXxl69BRr8fK32HfBPuh7b0vuw2wJNt4QY+YZJFNaX0ztqdC+tFZalsQ08B1USW6tMt8vH++65qA2vRO9WvatlNpuFTVl4ljlRB8WO8GP/xQocef2a2OimhWrc1Xfs0U5mz4osE80H6vHEPxjY29YkodcvW27xrwd9UbXVAHr2hJOOd0d91ULJ35HndsC1K/Yz9rQp5Mf3i6K2zdIWAXzheaFbpaBvTzfdu8fftniTs1sHVJzvli4sxLuhqMn3IxTX170Q2/bYPrQcFtiTOO+IRwPeOLkSraCqUwG75v/Izpqd7KrZxU/bf2L8gvHsrt1Nla8Kj98T08dWU2zKhttufmvz3Ll0yu3ErUf9kfzMfNpktSU/M59sZza1/loqvZVUeCsorS7lvwv+S1ltGbtqd5nfJV9l+PcpsjNrl82B3/KHT5+yHBnkunLIdGWT7cwhy5VN64w25LlbcdWQq2mb2db8brlyyPKX4/QUhXPnoX67lM2FzZGBRqO1Dn7HNFpbdBx6CfbS2BoMVn4Gtidjm6HGs21XB75afx22QX+Nmp+dbfqlihLs2NV8d8y2KHT4sVlER9QEMs0fiXpsTib9fj99+5bidNjCF8QiP6fQlLCVT8LKp8z+a03o1Da86cHNt4Cafn8jq/fZMbVy7TZ70n2vuVf9C/eauq5PAxr8cf4uAsD2rzrimbjNVFJXUOaGtW0goCBgC07B+5YCv6qbF9pSuzaJGqcy16/sVnAKzs/ww8Glptmv0ua2r60dtpIkmhY2E+tesPUNnjD63NT4Mqn2ZFFz8iq8Vla4hUBoOPhAAEae1wF3A+Xld++YY57IWvfMuQE8peiAD5uuxWmrBqsae0YOzuP+Gx6mPjPDVMbJyXZhi/i+GvFqLtZxrHoE55q6RIfWxKkPbNg/74p6reGkWKS6epEqaoqcF5oL1FsqNC+ooiK2qW5jmunYMtGmyXHVyzVFtXPT9e7X8/p/aliwPCOmm4IRI0xLh8jfzsZ+h71tCpn+fuz+xjtmUMr0OTvg/Xvp/VqC+6zi3K8/r/5Xsf5jwGcD/ac/4XrokcTiNqd77jGfc6IivlvmF8NmvrHtO2Bt3ByVXKp/LBVlD75b5u2r/5cS/bcU/28qQrJ/S81EmrwJsZ/TWodPLHbW7KQwu5C2WW2TT8S1kLFj4ePgBRWFhQM/GsX8RU4OOyx6WdM3V3DZiII+Xt9CkbWnoO5KQ6gpoA0flC83w6D7a0wno/4a0/eII5hY02aromooqdAZZr3yc9Zv9/kqq0lrrquEe3NQtzd+4YJBwaYEkQeHo/4JXY4Ozg99pqEjtMirkxHW/wc2vJRQWK/fybQtv2Vr5yfZvbuuaWl5uWlCGBq1xu2ua5qYmWlOkp3Ouu925AFN5NWy0NWz0OiaoRqDXi/c5b0X9wMt8F4ff7wZrz7dsrPNm5Bue9hcLGAF8AQ8ZDoyG2/GK4RIqbNGl/Pp5LyY+WvXmiS8EOJnoKWOL5NNZP3M7W1CyYHpWHsUsAXTsfYvtdZLIpY5A7iRuk65n9BaH9HYa5VSDwM7Ijrlztda/1kpdSjwBnWdck8B+u6LnXILIZrHDz/A5MlmtKRVq8wVlspKGDYMTjrJXIUuLDQjJIWqrGZm1nWOG3nyDbEjNYWmUJXVmhoz7d5t1n9AkR9eIYQQgqlT4dNPzTFDaATHykoYPBj69avrTzA0qEVoCnfMT/TFrMj+QiObqXg8Jtkf6jLA54MLL6wbkEMIIfZ1e5VQCq7gdGAcpou0l7XW/1BK/Q5Aa/2cMpfYngJGA9XAlVrrOQ29Nji/LfAO0A3YCFygtd4ZfO5u4CrAD9ysta43llc0SSgJsX/z+00CqLq6borsZDzeaE12e/wRmpQytUKysszUps3eNTUSQgghhBBCiP3VXieU9nWSUBJCCCGEEEIIIYRoXo0llFLUNb8QQgghhBBCCCGE2F9JQkkIIYQQQgghhBBCJEUSSkIIIYQQQgghhBAiKZJQEkIIIYQQQgghhBBJkYSSEEIIIYQQQgghhEiKJJSEEEIIIYQQQgghRFIkoSSEEEIIIYQQQgghkiIJJSGEEEIIIYQQQgiRFEkoCSGEEEIIIYQQQoikSEJJCCGEEEIIIYQQQiRFEkpCCCGEEEIIIYQQIimSUBJCCCGEEEIIIYQQSZGEkhBCCCGEEEIIIYRIitJat/Q27DWlVAmwoQVCFwClLRC3JWNLXIm7v8WWuBJ3f4stcSXu/hZb4krc/S22xJW4+1tsibt/x+2utW4X74n9IqHUUpRSc7TWww6k2BJX4u5vsSWuxN3fYktcibu/xZa4End/iy1xJe7+Flvi7t9xGyNN3oQQQgghhBBCCCFEUiShJIQQQgghhBBCCCGSIgmlvfPCARhb4krc/S22xJW4+1tsiStx97fYElfi7m+xJa7E3d9iS9z9O26DpA8lIYQQQgghhBBCCJEUqaEkhBBCCCGEEEIIIZIiCaU9pJQarZRaoZRarZS6I41xX1ZKFSulFqcxZlel1NdKqWVKqSVKqZvSGDtDKTVLKbUwGPu+NMa2K6XmK6U+TVfMYNz1SqlFSqkFSqk5aYzbWik1QSm1PPhZj0hDzP7B/QxN5Uqpm1MdNxj7luB3arFS6k2lVEaa4t4UjLkk1fsar7xQSuUrpb5USq0K3rZJU9wLgvtsKaVSMjpFA3EfDn6nf1JKfaCUap2muPcHYy5QSn2hlOrU3HEbih3x3J+UUlopVZCOuEqpe5VSWyL+nk9PR9zg/N8Hf5OXKKUeSkdcpdTbEfu6Xim1IE1xBymlZoR+I5RSR6Qp7kCl1I/B36dPlFJ5KYgb93gj1eVWI3FTWm41Ejcd5VZDsVNadjUUN+L5lJRbjexvSsutxvY3leVWI/ub0nKrkbjpKLcaip3Ssks1cK6ShnKrobipLrcaipvScquRuKkusxo9F01VmdVY7FSXW0nTWsuU5ATYgTVAL8AFLAQOSVPs44AhwOI07m9HYEjwfi6wMo37q4Cc4H0nMBM4Kk2x/wi8AXyarvc6GHc9UJDOmMG4rwC/Cd53Aa3THN8OFAHd0xCrM7AOyAw+fgf4dRriHgYsBrIAB/AV0DeF8WLKC+Ah4I7g/TuAB9MU92CgP/ANMCyN+3sq4AjefzCN+5sXcf8PwHPp2ufg/K7AZGBDKsqTBvb5XuBPqdjPJuKeGPxbcgcft0/X+xzx/KPAX9O0v18AY4L3Twe+SVPc2cDxwftXAfenIG7c441Ul1uNxE1pudVI3HSUWw3FTmnZ1VDc4OOUlVuN7G9Ky61G4qa03GrsfY5YptnLrUb2Nx3lVkOxU1p20cC5ShrKrYbiprrcaihuSsutRuKmusxq8Fw0lWVWE/uc0nIr2UlqKO2ZI4DVWuu1Wmsv8BYwNh2BtdbTgJ3piBURc5vWel7wfgWwDHNCno7YWmtdGXzoDE4p7/hLKdUFOAP4T6pj7QuCV2uOA14C0Fp7tda707wZo4A1WusNaYrnADKVUg5MgmdrGmIeDMzQWldrrf3At8A5qQrWQHkxFpM8JHh7djriaq2Xaa1XNHesBOJ+EXyvAWYAXdIUtzziYTYpKrca+U14DPhzC8RNqQbiXgc8oLX2BJcpTlNcAJRSCrgQeDNNcTUQusLeihSUXQ3E7Q9MC97/EjgvBXEbOt5IabnVUNxUl1uNxE1HudVQ7JSWXU0cU6as3GqpY9lG4qa03Gpqf1NVbjUSNx3lVkOxU1p2NXKukupyK27cNJRbDcVNabnVSNxUl1mNnYum+lirRc6DkyUJpT3TGdgU8XgzaUqwtDSlVA9gMCZDmq6Y9mCV3GLgS611OmKPwxQQVhpi1aeBL5RSc5VS16YpZi+gBBivTDO//yilstMUO+RiUnBCFo/WegvwCLAR2AaUaa2/SEPoxcBxSqm2SqkszFW6rmmIG6lQa70NzMEX0D7N8VvSVcBn6QqmlPqHUmoTcCnw1zTG/QWwRWu9MF0xI9wYrHr+cnNX729EP+BYpdRMpdS3SqnhaYobciywXWu9Kk3xbgYeDn63HgHuTFPcxcAvgvcvIMVlV73jjbSVWy1xnNNE3JSXW/Vjp6vsioybznIrznudlnKrXty0lVsNfLdSXm7Vi3szaSy36sVOednVwLlKysutFjpHSiRuSsqthuKmusyKFzddZVYj73VLHG/FJQmlPaPizNvnsoXNTSmVA7wH3FwvG5xSWuuA1noQJtN9hFLqsFTGU0qdCRRrreemMk4jjtZaDwHGADcopY5LQ0wHpnnDs1rrwUAVpnpuWiilXJgf+3fTFK8N5spRT6ATkK2UuizVcbXWyzDVgL8EPsc0l/U3+iLRLJRSd2Pe69fTFVNrfbfWumsw5o3piBlMVN5NGhNYEZ4FegODMInaR9MU1wG0wVQDvw14J3j1PV0uIU3J8KDrgFuC361bCNYsTYOrML9JczHNSbypCtRSxxv7Wtx0lFvxYqej7IqMi9nHtJRbcfY3LeVWnLhpKbca+U6ntNyKEzdt5Vac2Ckvu9J9rrIvx01ludVQ3FSXWXHiDiBNZVYD+9xSx1txSUJpz2wmOrvdhfQ0l2kxSiknpnB+XWv9fktsgzZNsL4BRqc41NHAL5RS6zHNGU9SSr2W4phhWuutwdti4ANME8tU2wxsjsh6T8AkmNJlDDBPa709TfFOBtZprUu01j7gfWBkOgJrrV/SWg/RWh+HaVKSrloNIduVUh0BgrfN3jxoX6OUugI4E7hUa90Syf83SEHzoAb0xiRKFwbLsC7APKVUh1QH1lpvDx74WMCLpKfsAlN+vR+sGj4LU7O02TvHjCfYZPZc4O10xAu6AlNmgUnCp+V91lov11qfqrUeijkRXZOKOA0cb6S83Gqp45yG4qaj3Epgn1NSdsWJm5ZyK97+pqPcauB9Tnm51ch3K6XlVgNx01JuNfAZp6XsCsbaTd25StqOt9J4jtRo3HQdbzWyvyk93oqIG7oonbZjrch9bsHjrbgkobRnZgN9lVI9gzUrLgY+buFtSpngFZOXgGVa63+nOXY7FRwlQCmViUkELE9lTK31nVrrLlrrHpjPdqrWOuW1VwCUUtlKqdzQfUwHdykf0U9rXQRsUkr1D84aBSxNddwI6b7CvxE4SimVFfx+j8K0tU85pVT74G03zAFdOvcbTFl1RfD+FcBHaY6fVkqp0cDtwC+01tVpjNs34uEvSHG5FaK1XqS1bq+17hEswzZjOiktSnXs0IFz0DmkoewK+hA4KbgN/TCDCpSmKfbJwHKt9eY0xQNzAev44P2TSFNSOqLssgH/BzyXghgNHW+ktNxqqeOchuKmo9xqJHZKy654cdNRbjWyvykttxr5bn1ICsutJr7TKSu3Gomb8nKrkc84pWVXI+cqqS630n6O1FjcVJdbjcRNdZkVL+78dBxrNbLPLXW8FZ/eB3oG/zlOmL5PVmKy3HenMe6bmKptPsyX9+o0xDwG06TvJ2BBcDo9Tfs7AJgfjL2YFIyi00T8E0jjKG+YvowWBqclaf5uDQLmBN/rD4E2aYqbBewAWqX5s70P86OzGPgfwZFW0hD3O0yybiEwKsWxYsoLoC0wBXMwNwXIT1Pcc4L3PcB2YHKa4q7G9HkXKruafbS1BuK+F/xu/QR8gunsNi2fcb3n15OakUfi7fP/gEXBff4Y6JimuC7gteD7PQ84KV3vM/Bf4Hep+Gwb2d9jgLnBMmQmMDRNcW/CHPesBB4AVArixj3eSHW51UjclJZbjcRNR7nVUOyUll0Nxa23TLOXW43sb0rLrUbiprTcaux9JoXlViP7m45yq6HYKS27aOBchdSXWw3FTXW51VDclJZbjcRNdZnV5LkoqTvWamifU368lcykghslhBBCCCGEEEIIIURCpMmbEEIIIYQQQgghhEiKJJSEEEIIIYQQQgghRFIkoSSEEEIIIYQQQgghkiIJJSGEEEIIIYQQQgiRFEkoCSGEEEIIIYQQQoikSEJJCCGEEEIIIYQQQiRFEkpCCCGEEEIIIYQQIimSUBJCCCGEEEIIIYQQSfl/ttntVDxGU4kAAAAASUVORK5CYII=\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_11\n", + "total seqlets: 141\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_0 pattern_12\n", + "total seqlets: 105\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n"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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1\n", + "activity pattern: [-1]\n", + "metacluster_1 pattern_0\n", + "total seqlets: 1074\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_1\n", + "total seqlets: 342\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_2\n", + "total seqlets: 333\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_3\n", + "total seqlets: 265\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_4\n", + "total seqlets: 156\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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rHXOTXX017L03jBy5EyTJf6UEWnrym7SwLwzzzjvwzDPwySdGcPL54mG0EyYYEXvffc21UVJi8l3l5cUTqUeLDIARnrSG+nqorjbX6JYtsHQpzJkDs2aJ2CQIgiAIgiDs2kjS8B2Nvk4a3rwFFv4RVj1iwlJCDQm2nFB0iAlZKTocMoaDp9AISToEqEh7FKAj9rUZMDv8EKqHxg1QPduIWaUfwvlJSpqn4XgrKuDWW+Hpp82gL5q/yeWC737XDKJHjDDVt3y+3g+YW1rM5PdvR4hefyWG34UIBuGzz4wnzrvvGr0vGgoWCJh1fL54NcGhQ2H4cONZ4nabKZrnq67OiFMbNhiBcsMG48ECxnslUcRMitbQUgr1q4wQW78SahdA/XJo2gihJiPYogEr8qqNuKuc4CmAzJGQvQfk7GHE3szR5n0X10pdnREwqqrMVF1tXisrjdBWV2e8bEIhMykVD/NyOo1QUlJiXvPz41Nenjmnv/xlR9GpsBCmTTNJ9vtaxA2/uSeO+oUdF5y+2pyfnvBMz8S8Z764kF+++SzV1cabK8o++8BvfgMnnhj3+MrI6H7et2SEw8aG05nCin+CIAiCIAiCkEY6SxougtOORl+JEVrD8vtg7i/i3klR/ENhj1/CyO+a9ZwZvcuRom3jQeXwmPxOPaGPxZetW+Ghh0z4z/z5RliybePlkpMDBxwAkybBfvuZQXNxsRlk5+QYc7YdN6tUfGBZW2sG8mVlJrRmxgwTavPNN20HqP1xzN8mWlvhzjvhb38zwklDQ9yrJC/PJIY//XQ48kgTutTSYgb4TmdbL6dEot5NgYD5anw+Y+frr8119K9/JWlISzlseRfWvwRlU81vzPKY11AjRlSKoBzgzjX5z5QLsCPegs1GtE3E8pjfkdYx8VZrU21x5kz46ivzft06Iwb5fEb4GTUKhgyB7GzzuaDAePbl5MRDvbSOh3lVVRlRqqrKCFN1dUZsW7PG/G6Ki+H//s9Mzc3tmmjB974Hf/6zsZ+dvX3fZZT6yCmY99jPOKzgXjrkcdrvHzD2hz3ro3ogOD3w4dX89Ol7aAq0VX9++lO44w4jZKY8YbogCIIgCIIg7MSI4PRtE5xm3mS8msLtsmgPPRsOeswIQ5Zru5rYp6RQfAkEYNEiIwxN/8pm8aIgZaWaqmqLmjonCo3HHcJhhUFr/H4zmHa6AA2hMIRD0NwCoAiFnbQGnChLk5sdprDAprjY4uPPeujiJILTdvHll3DBBUYkSfS8KSiAe++Fc88133lvBZBEmpraJYov+xTm/xYqvza/n0SPQcsFhYdCwQGQOwGyd4eMEeDOBx00wqzWca9Bywl2CJo3R7yiFkLtYiidCk3rqTxRc++98N//GsHUtk17nE447TT4wQ+McJqXZ+ZrbZZFPbi2hW0b8SkQMEJUNCl+YnLwL76As84ywl4y4emUU+C660zy/JycbXsQhkJmXx6PsTt/Pjz8sPFUO2T0VKb+7mwItvOSzJsEx38BTn/SfSalB4LTmfe8yhuzT0PrtqrSjBkmfK433kyCIAiCIAiC8G1ABKcdWXCyg9BaCa3lkLdX5+vNuDFeLU45zQDMUwCeIhMKF31tXANTj4FwuxFi4SFwzPvGo2lHIRXiS6gJqmZDxVdQPg1qFpjQJstlPEwsF9o7iIbQQMoah1HWMJy6QDFhK4uQ7SYYcmFZ4LCCOFUAh64j17OF4ox1FGdtIMPaYkQCHTLf3QUN5nvpz2PexVm3DiZO7OhNNnKkyYXj86U4OXz9Svj8AqhfFvFgiqJg4Akw5joYdAKEAyaXmWM7SiFq21y7ykF9RTnj9hlGdXU8PBRMCNzChcZrqS+Fta5oaIB77jFeZVp37tGXn28Emv32MwJUVpb5XizLCGJNTUZgmjnTfGebN7fd3uNqoeWpAR29vgAOexEGn97989qDHE7LNo/jkDu+pMUuaCNk7r47vPyyCcnszDtOEARBEARBEAQRnHYMwSkcgJp5UPE1VH5jch81rDXCkMNjRKRrGqHG7rhtvg/eucyE7Oiw2aa10ngDBGogUGXm6aDJwaSckTxMCez/AIy9Jh1H2n36UnypmgWL/wobXzPnM9xiQpecWTD8AiMMFBxgql6FW+PnRzkioUydDGbDrWY/OhLqYzlNeFTjBiNqjfxuz9q5iwpOWps8Qlu2mBCt+nojTtTXt52CwXhuIa3NQD5a3cvjMUJFVpapGBd9/+qrJlSyfSXChx6CK65IsRhQ9jF8eroRg0j4bXqLjRCSN8mIuKrvXGFKS03OqUCg7fzx441oo7URndJJUxM8+6zxSJo929jvcThpJ/j9xuOqec69MO/XHT0zvQPg5LngGQBWL7/sJN5PDS0Z/Le2gT/9yQh8waAJswQ4/HA480yTx2nMmHiVQ6WMJ5nH07UXVDhs9hW93qPeZ4sWwf779+5QBEEQBEEQBGFHQASn/hKctIatn8CiO82r5Y2LQt4SKDkOBhwJhQeaZMGWB+wWsCNJhpUFWEmSd9vGIyIammNFBJaGlbDyIVjzRDtPDGDExbD/g+DqYe33HlV8suDi8LZXi9KF+DLtM208jRxtEx0XFppku7FNtYYZPzTHbLdEzgvm3O19F4z7YWSEvoPUvN8FBKfVq+HDD02Y25IlxgOpstKIRNFKZoMGmVxAQ4fGKwU6HPGcQk5nvIR8KNT2tabGCFcbNpi8WV99ZTxj2iexvuoq+Pvfjd2UEKyH10cYQTcRVzacthLcOUZ8TAFffQU33QQLFpjPUU+n8ePN/EsuMecxEDDeXb318GpqMvvKzd32utXV8PbbJnH7N9/AsmVmvttt2hn9HhMv52jCco8nnktq1CjjEXXYYSZMcHBJAN4YaTwI25M1Bk78xgjIvck511m43cWaUAjmzjXH9d57RtyrqDCCmFJGFBs0yHiaDRhgpuLiuBdU9Bijx9fQYH4bW7fGpy1bzKvDYa5zQRAEQRAEQdjZEcGpPwSnlnIT2ta4tm2uF+8AI/wMOsmEZLn6uNyTHYYPjzQeP3ZL22X7/RNGX9GzsLoeVnzi4rbXVG2tGbgtWmTKga9caUqEV1bC7M0lFNNRzCp3FHPE2FK0NoPXYNDsJ1pZDIyAkZcH44dv4M2rRqBo5xmWv5/J/eLYwWq4dyU4bf3CeKdZkQpmzgwTJunK6Xq7NPHVV3Dhheb7UyouAB1/PPzhDyYhe9QzxOvtfTXAaMXB1la48kojAjS201FvvRVuu80IWT2uGLgtNr4OX36vY5jXmGth37+lJTx13Tp46SUjgsyaZbyfoqFqxcWw225GuBk71nweMCBebS6al8yy4knxbdsIIdXV5jdYUWHC21asgFWr4L15JUbl6wEa2MgQ5rMXaxhJC16a8dGIHxsHmTTgpQUvLQxiM3szj1GsxtH+N1tWBiyDj0/sGBIMkDESjn4H/EO2/9wn689+CNQmX72BDJayO2UUs5UBbGUAGxnCBoawmUFUUkAIFyEc2DiwsbCwcRDGQRg3AQawlYFsZhgbGMymyF62ckzps7iK87fvOARBEARBEARhB0EEp/4QnKZfBWse7xjadvS7UHxMapN2h5rgy+9C6fsdPZ0GngT73gMZw0w42bYqy/XIwwn0RZpp00y402efxQfI0VCUffYx0377GW+NwkIzQM7ONqJBIGAGx9FLMzpgdjqNwFFTYxJHb95sBuAL5oV5/prjoHJG21AcywNHvg5FhxsvlO56RfTWo8sOQd1SqF0E1fPMa0sZtFZAoBquqko+uM11wOOjzPWiQ0aktIPxcD5nJrhyTd4u7wA47HnjadMJUZGupsa8BoNGbAiHO07R0LZEj7LEyeczni+//S08+WS8RHyU116DM84w+09VkmWt4cUX4ZprzDWS6O00fLhJXn3xxeZ6CgaN19P2tiUaKqbLppE16+SOv6HBp8MhT6fXWzDcAnXLCFSuZO3yapYvbmTL5jBVNU62VmZQWp1LeW0BFQ1F1DTm0NTqxdYObNvC1hagsSwbS2ksFSbT20ReZg0FGeUMyK1iYEENRXlN/PTNO1FbeyY49RnFxabDWPc8TL88uehkuWCPW2H8z0z/1ZNk4tBjwSmlRI9XEARBEARBEHZiRHDqD8FpzdPwzdUQbhcHNOYaI/hEcwF1l54OVi8Kwea3Ye4txssq3BwPNwPIHg9Dz4Jh55n36Ej+Jwsc/uQCjW2b49EheCmvw+L35x/PdS++T1lZvHIWmAS8v/0tnH228YBxOk1YXG8Jh404kJMVhHUvwOI7oWFNZGHkvGfvDuNugOJjIWu0OUYd7jx3Uw8FNi7WJin5igdh8xRTaSz6vYYajbBXcADk7gX5+4KvBNwF4M41Xhp2GEiIP1IKsMzAOtwMwVporYKWraaSWfUc7Io5rN59LrNnm2paS5YYAa683HgWjR0LQ4bEw3+iol5urlkeFfGighIY8+FwW1Gqvj7uCbN1K2zaZPb52msmxM3tNs21LJPr5uyz4aCDjG2fr23uGisSGdp+ioqLiZNtm2Uul/GSamgwVdDAiGdPPw2PP27Cn7xes9yOXNqDBsERR8CECTBunPH+GTzYnAPLinv5KBU/9qoqE+q0Zg0sX25CxKZNg+XLNfq9w6FqhhH+EjnseRh0ihECu0tPvQVP+ArWPgsbXoGWUpOQXClwZJicZPn7muvKPwy8RWZ5uAUTcqsxvkfJiH4BFlg+I262lELjehh4fM/aCKkJE116L8z7VXLRCYzYOu4GGHU5+AabPsnhT57jKdxqzovlghc66Xgu7kE7d4GwWEEQBEEQBEHoK0Rw6q8cTpvfMUlw65YYb5Wot1PWOBj/Uxh8hskDE24x4ofT1/m+tkcIATMAKv8CVj9qQoSigkv7cDtPkRFkMkdB5hjz2ek1eafsgNkuWAsNq6B+lclJlcCijXuw/69n0Bxs63Fw+OHw7rtGPEhLouPaJeZ4y6aa5OyNGxI8nBT4h0LG8EiFv0KT/Nk/xLxXDrOe1hFPo7CpHti0Eeb+Mrm9QadA6UeABjsS7+fMgrHXwR4/N4NgO2iEid4mPNY2hBq56LsennvBHRN1oj/jL76AQw6J59Hxevs2oXZrazxMLtASZsWCraxaWsvqla2sXadYtdbHxi0+6hudBEMuMrK95OS5KShykJercbtt3C4jOEbz3YRC8SkQVAQCFpVVUF0ZoqYqQFN9C153kOUbBnZoT3U1fP45fPCBmTZu1DQ3g89r43BoQiFFc4uFbRuBIHoNOp3xPDvBoDl/Sml8XhuXS2PbZjunE5prquGzM03lw/bJrEdeBvv9I6KOdaNsXE9/w86M+O8VzHV1xGtQdEjkmurbZOXbTaoEmI1vwJeXRM5BqPP1MoabXHjZ4yF/HyPoWo6IV9hyU6yhej6Uf2bOWzJ2cMGptdV4K0Y9FmtrjadfVCCOehdGhWSn03iN5ubGJ693h4jMFQRBEARBEHYxRHDq7yp11fNN9bTSD6B6jvFqcXjMk3dXFuTuCTkTjDeMb4jxgvEWgTvfiCXKYQaWOmxEB7s17vXy0bHJbSYbQGmNrl1C69r3CZTNRtUvwR1Yi0tXE8aHjQOLABZBFGEspRM2VWgsbJzYeHBRj0pYPnvNPhz6+y9oCbQVzU44AV55JZ53Ju3YYWhcY7w3WsuhtYJA4yZWbvqULeWzydEtFLg8FPpyyXT5UNFk7MqKnHeHERNq5nX0csGKfC8Jg2HlhLM2GoEpRTl+XnoJ/vxn49lk28bTSGs47zy44AKTuDs/P57/KhoCl+hZlPgZ4uPkxHDGqNeQUmYA6wlvwrnmAROqWT0/4iHjNCLeoJNNqGj2bqaamNNvzpcdxA6HaWqChgYVGxybSWFZuk3YZFaWxucDZTniQmGo0YgtoQZTGbB6DtQtM8Jn61ZTrdGdD95imh0j2FgzlvWVw1lfOZT1ZYUsX51FfaOLQMgiELAIhS0cDo3baeN2hfF5w4we3sCIQVUMK9jIsMJ1DM1dSba1Bo56y5yQlQ/CgtuNx01iTjblhIEnmqT8g042bbaDkXDVTjxuEgm3wvPdzPiduxecMs9c0z0RL3sbJhpqhpYtpjJmdApUmjx1rVvhwIc6391n5yf88CO/l6iHleU2Qq+nKCIAR0Rgd4HpA11Z5nf7xYXmemsv+PUlyfpLO9j2eFsrTQL5MVd1vp+5vzbXrIrkYYv2IdF5Dn/8WN3mVbvy2bTFwaJFsHgxLFwIS5ea/F319cZb1O833nojRkBBgfnNO51xAdXliv/eYwJuwAhU69YZ773qatMPr1plcn0JgiAIgiAIQl8gglN/C04RGhth5QpN6doyWsoWomuXYrVuIUNtIsu1mWz3VnK8lWR5a/G7GlHKxtYWGgutFUoZyUcpG60tmoKZ+FwNOKx2yXe9xdQeW8pnn8H06WYAs2KFCYuqrzdVxMaNMxXEiopg8MAgYwauozhjFX57NS5Vj0MFcRDAogUbNzZuwtpNSHtpcQynMjCaVaWjWLsxg4oKE5J0xhlw441m0FOfkGf50EPh9783r83NJr+OsxeFphKJDsa6w8qqlfz9q7/z2LzHzLbBeLhjpjsTp3JywwE3cP0B11OSWbLtHb5SYkS/xNAlywPnbI2E6/Uga3ZPvV9Q6MNeZsOyDaxb2UBpqaas3EVtoITy2kIq6gtoJY+QygaHn4xMJ1nZDpwuhbIUlgKUMpoRCltrtA1a68gEjY02DfVhWptacepGLp/8K07d46mOTTniNRhyRg/avp3HbLlM2FgoEtZZcCDs+3fIn2REGB0iFo7o8Gy/90+4NZ47y50bn29HQjdXPmC85xxeU8ku8fv3DY54CY6CrLFGTPaWmDZZrohgHDDCVf1yk+Nr6d+TtyN/fyN0Wu5IHiltwjNHXwVDzzYiXLgJUOZ4O8vH1tPzfNhLUPYRlE6F5o3GU8idBwUHGfvZ44zI6MkHVx6M3AvKtnbcT/EA2LgmHiYaC+VzmHMQrIdgDbRWQ/MmEyaYTKSNVvuc/VPjsdTXwpOnEA540Bxv1SzTltYKwAEDDjNhuf5h4Btk8qftfT5srezkeFeb71jbxKqJ6rD5/gLVZr8t5dC0gcWhG3jkyUyeftoIQx6P6R+9XjjnHDj1VNhrLxMm6nKZZVFPpmgoa/Q1MVw0MTQ1Gj4arWJYVmaq6nVFOGz+VzU2mnDVQIB2QnHbKbENiVM0ZNfvN31+RoY5RvGyEgRBEARB2LUQwamfBKfSUpgyBZ5/3uS8qa83N98OB+y/v0mePWmSEYAGDjRPrj2eSILnsEZrG22H0XYIbYdRlhNlOcykLJSlYoOUqOgzY0bcntdrbGptqln9+c9wbMQhKhSKlynvTXWvcNiEdQWDJmwjFILXX4f77zdtCYeNuNTYaJYfdJBJGH7ggTBmjJmXnW3WaW3tWE4dzADF7TaDrqYmE05SXm5y+MycCffd13n7bG3z7sp3ufPzO5m5eSZhO0zQDuJ3+Tlw8IH8YL8f8Kdpf2JN9Roag414nV601pw45kRuOfQWDh5yMKqzEVLdcph2rgkzjObOATMY3+NWGHWZESm6EgOi9FhwgpgnVjTk6vgvoejgyIEHAR3xsugD1zI7bNq3/kXY8h5UTjeCgcNrwhKLj4MBh0POHhHvlByzzA5ExJskOYXe3M14yHQXh79tTrSxN8D+/zKDeYfXCBndobceP2Bsln0Cm94wCesb10OwBu3wYmOB3Yqjg0dcMhyY66bdufEWw9mlxqtmy3smpK9yBjSsNCKn5TKeQZmjwT8Y7RsYCRcdgXL6It5hLlARoQsdSUIfnQLw8QnJm6QcEcEkmrnfDRdGwkXDQXCkIzY2CVHhafl/YMs7gIoIcfY2NkzAkWGEyczRMPJ7Rvhb+HtwZkeqEUaOed+/w+4/gkBtRCz09qmL5ttTwpx7niPmkRTl0ktNwYVAwFTi7GvCYXjrLeNBNX++yVlWXW365yOPNGJUUZF5GFFQYPrmzEzzfysaktde8IK40BV9DQbN/6WGBjPV1pr/Pd19OCAIgiAIgrDTom2TkqV+OdSvNA8cm0tNhJLlNPfnDnfkAXnkQbnDb7z7LRexqIBoxA06/kAz+lAz+vA23GQelutQJG9p5L0dBG+hefDtLTIpc7LHmYfjKXj6l1LBSSl1EvAPzMjpf1rru9otV5HlpwBNwPe11rO72lYplQ88D4wA1gLna62rI8tuBa4EwsBNWuv3ttXG/hCcXnwRLrvM3JQnlnK/9lr461/Njb/P1/el3B95xJSQb88tt8Bddxm7fZnXpyu0NqEcc+fCggXwzTewfr1J0lxbq2lqAqfLBkcAlyfEwCIXuTkOnE4HTocVS2QdDEa3MQOx1sjYNyvLCFarV3e0va5mHde/fT0frP6AsB0mHBFlHMqB2+FmQtEECvwFsfW3NGxhSfkSwjqMHUmu7lAOPE4P5+9xPnefcDf5/k5KmFfNgiX3GK+QQJURP8ItpoPI3894hRTsDzl7mlAaV3Y8pFKH2okxkQ7Achovqee6GNzn7wf1KyLCjwcGHGXyCvkHG08Md57pvByRkaIdiCeOT7S56E+w+K7OrLTFkQEXRELKgvXQtAmaN8dCjuyWCqprltJQu4JA8xZabY3t8OFyZuCwHDgsJ36XH5/Lh8fhxWU5cSirbb+34dV4Pqwo7nzY5y8mL1rlDCNU2SFzrEWHQ85EyBoF3oGRcKW8yHn2RkS5hA76tWHblQ+tOdjMjM0zeHXJq6yuXk1FUwVVLVVsqttEfaAeFzDcBaNdMMoFu7ugyAkewGOB21hHObwohxdteWnwlODLn8hBu11MbuF+KG9Rl/8EmgJNzN4yk01bZ7G1ciGbqxazvnwBznAjOZYpdjjAAZkWOAGHgiyXj3xfAdnePDI82WR5csnPGYW1+tG24YHR79eTb86Pwxfx9mqBib+BoedAzvi4aAWRcDF3cm+++bfDwju6dYptW/HN2iPZuPvH1NQYEaSqyrxmZ8dDLl0u897lDDEi80t2y3iTYtdMctQKfKoMGxeaaAensQgQxkODHkFVeALrWo5haf1p1LQOJByG8b5nOG/4NebaUCpekXDsD2HP2801FG4GVPw4uxJwu3nMT0z7Htc8/CAtwbYhyLfcYrxBoe//N4Dph/faq+P8iRPNsigmr1nf2e3r/QmCIAiCkBq0NmOtxsZ4levOpmQeztHJ5UqBd3Ns/KJ27BuLWKEgFU+3gd02hYMdNGMZiKQpcfXcSUDbkTzRkfGd5ep+ZfY+JmWCk1LKASwHjgc2AjOAi7TWixPWOQW4ESM4HQj8Q2t9YFfbKqX+AlRpre9SSv0SyNNa36KU2gN4FjgAGAR8CIzTWidxQYjTH4LT735nPIpa242bH3oIrrjCCCmpGFBobXL8PPEEfPqpseNymfmTJ8N3vgNHH22eZOfkxHN9REMjYNuVxKJ2EiuJNTaagWEyalpqmL5hOgvLFzJr8yxmbZnFiqoVYFvQnA9NhdBYBEE/aAfYTtzKz6j8EYwrGs3o/BGMLRrJviNHMmCARVGR6cCS9TMLyhbws/d/xvur3+/zc3v1fldz62G3MiJ3RGxeZaXxtoom9G2uLsfTNJvM8CKKnd+Q51iGV1XgsWpxqUZsXNjahW15UZ58lDvHeCFFOwc7DDqMHWyA1ko8dlmbXFkxrregJtq5AJmRyQd4k7x63ODPApcbXA5wWGZyRt4HwxAKQ9iGUCQT8aFl4G1n210E5xqvpNZQK4/OfZTXlr7G/LL51LTU0BzqWFXMZbnI9+WjtaaiuSIm6EVRKPwuP4X+QiaVTOJ7e3+PM3c7E0dinqKSEhMPlIgXyGo3ZQI5keO2MKqLU5njdDrA5TTHH7YhGDLHHQxBWJveqZ1uolZ0PPXp4Du+3zHaczhb7WWsbVzIavsTtuolfW7nqOFHsd+g/RhfOJ7dC3dn4oCJ5HhzjGdVxXRoWG0qPzauMZ5VgWq05UI7s1HuHGxPEdqdj/YUoB0+UC4shxsV8bBSSqHsECr6pMUOwrxbOwhd59z7Iq/MOLdD+9asMXmL2hPtr9r0AXbIVNuzA5E8eW4jGLnjFTUT/+XFttXaPH0qnwY1842I27jOhMBZbvANQWcOR3uLwV2A9pWgvSWRpO0OlOVCKUfkeB2gQygdjhRniIR6fnhEh2N4e+7J/GPe23z6qelDAwHjLTphAnz/+yakLnrsra2mmW53z7yEWlrabut0wuol1Sydt5WVSxtZusxBWbmLymoXhSWZDBiUQWa2i+wcJ5nZFllZFjk5pm/PitQ9sCywlHnvcERuOqMhdxEvp9ZW84Cgrg7qajUNDTa//k3/3AAJgiAIwo6E1iYKZs0aWLvWjCOqq020itPZtgBINDzd4zGextHliVN0n4nextEH9s3N8XyuLS3GXlWVsVVfHy+ec9hhJr9jbq7xdC4oMO+zsoyns8eTXFRKJkK1thrv5vp6Mzaqqgxx1emf4bfXQMNac28ZqDL3gtm7m4fKDm8k/20kB67Tb947PIAjXl05Gt3RxuNHE/P4CTWa1BuhRgg1UjfgB6zdlMn69aaid22taVNLS7zadvQ8x3LWetpW4o7eb0bPdfv0BeFw/B4uOm9y1r8Y4fuYIs8SclwbcDuaCGs3jP8ZVtGBKF8xeArMONDhjTzQdEQEqHbOAQv/D7X4T92/wBKdA9JIKgWng4HbtdYnRj7fCqC1vjNhnQeBT7TWz0Y+LwOOwngvJd02uo7WeotSamBk+93a718p9V5kH1911c7+EJy0hjfeMOXbP/jAfHY6zcU4frxJ8Hz00TB6dDzBc3Rg0J0S8okXu2XFBxMVFWZsDmDbmsUr6/lw9mo+m7ORzVs0laUZ1G7NpqEyi0BDFjmeHAbkeygeYJGfb+Fw2Dhd2kxOjdNlBhOhoCIUskynFbKor4fyck1VFQSDirw8WLTIiEtzS+cye8tsnpj7BPO2zuvzc3vzgTdzwOAD2KdkH8YVjMPWNq8ve507p93JkooltIZasSM/VgsLp+XkO+O+w0UTL8Lv2vZorbqlmkfmPMIX678gkBAW5bJcOJSDQ4cdyi8P+yW3X3osX3wRH/G6XKbD2rwZ8vI67jcYsAm31KBbKlCtFRCsjg9MdYh4CJwDrRzgyER7ilDeIixvPk63Mx7Vk0yASTGVPnjmkEy+uPY7fLPpG9bXro95jvU1LsvFmPwxHDTkIA4ZeghXnvJrVJqPF0AdeysoG+qGGGFUKzKz4NnHMxibP5aReSNxO3qmHGutqWiqYHnlcjbVbyLaDzeHmtlUt4mNdRt5YNYDSbd1hmFkNexdBntshd0qYUBjzC8uKbaCjdmwrAAWDoAFxbA+N/m6Rc2KsjvDVLdUs6pqFcsrl3PDOzdQ01LTsS1AjmX0PAfGmyrqVeXAzFdASBt31Oirz5XBTw75BfsMnMywwokMyB7K1q2K114zHpBbSsNsKg2yalM1WZkO9t/XTZbfSVamg8ICB1kZFpkZFpmZiowMFbn5MsnnlQWW0ihLmT4yIUG9bUNzs6ax0YTmNjcramvh5pshEA6wsW4ja2vWcvdXd/Plhi+pbalFo1GR4yxwQIEFHhU55uhx0/YcRI8zrAFl4XNn8XhhCxm0e/rgyoED/0djg+abOdksWp7JzAWFLFkzgHWbfFRUurEsGDjQZtgwzdAhMHiIRX4BuJwKd+SGyONRuFzmprG1VRMIQKAVgkFNbZ1m80bNho2K9evBH17OgjsnJDRCAdrkGzttedv26TBaQyiksLWV9KYyHO78yabDAZYyFSNBwdbPjDek1vFQWztgCmVYzkg/GO1P7MgDzGj+r/a08whtg53gUhWZooU3QkbIx+E2HqRWxIM0ZyLkJXH9EgRBEIQ+5ic/gb9H0ndGhYxw2KQkOf30tusmphpJFJi6Q+K2SpkUJDff3HG9n/8c/vKXnh9Htyn/Ej44NPYxclcAhYfACV90XH9bbtHdTI1R3ZhL/tXVsc/RXebkGIGvPXbC7UOHh5pdEB2XQ3wMP3y4uaeN4nKGGZBby8Y1NRBsMPcj0SnYgA41EQ5rk7tZExObzH2oTrgnit7XKNyLfoEK1XVsUDQtR5pJpeB0LnCS1vqqyOfvAQdqrW9IWOct4C6t9eeRz1OBWzCCU9JtlVI1WuvchH1Ua63zlFL/BqZrrZ+KzH8YeEdr/VJX7ewPwWn6xukc/HA0n44F1SOhcpyZqsZA5VioGwatWahQBgXZPgYOcDNoaIjcPBunU+Nya1OFKKJyh0LGGSMUgmBAEQopqiocbNnkYHNZgKr6JnA1wk+3kRW2MzRgGw+jNpMVBisUn1QYrI7Xzv6D9mfG5hkd5rssFy6Hiz0K92DfgfsyYcAEBmQMQHUxTA7YAVZUrmBB2QJmbZnF5vrNAB0EDp/Tx4jcESypMN4fWe4srIg7YiAc4MTRJ3LvSfcyPHd4j0/H/LL5XPPWNcwvm48rMjAJ6zANAaMa72afzZbAUoJ2sE1S3ewMFxOzD2Ny/gkcNvQIRg4owuczTya83vhTgsQOLfoPpK6lgembv+CjtR/wyfoPaQo2Ee13tA0WTpz4WNEwu0fHom/vfJnqYll7DtfDCGxc32H+3mVw8ko4ci3ktfSoaWzOgo9HwFvjYE1uu7YB7hB8NrLz7fO8eRT5i8j35ZPpzsTv9vP6RW90uv4JTxxPY7CR6uZqypvKqWqu6uB1FeXrDTdR+/BiGsloM7mGluAuzkNnZqMzMtA+P9rtQXk8ONwWDrejzResLAudxF1QaY0dDhNutQkHjOpsBVq45ovLUFvTL7CN/bGDlTldi4huy43b4cblcOG0nDgsR5vfskZja5tgOEjQDhIIBwiEu5PPajvRgFagLTMRea/sdlPqmtBTCiyo7CT1lN/pZ1juMIZmDidbDcJvD8QbKoHWHFobfLQ0eGhu8GCHHMbtPRimsXoFLU3raMamVoepIkTAXQfeGvDWmldPLU5vNecPqGOcCya6YaTLhGHmOD1kjrwAZ+ZwLG+xSZDuzos8afRHQnM9mJwC0ZsdCxb/BbWke3epXzRDRZJLq/Ckzzlk6CGd58pLxvzb24QuttrwUTMEktzSNC8/hZkrDuowf9K5NzJkaG7S3Sf1hOuEkB0inFCpNOYprB1sXO+ivNwU7Fj4/ru0hDy0BH0UFGfiy/RSWKgoGTM69j/ACIjx/wddPXSKtrO11TxZjeYCi/4vchAg27GKAZkbKcyqJD+jkixfHZnuGkoKm3C7EnJBOLxmspwk3szGfzRRgwlPXXWk+EE4SCzPBA5zneho2G3kKbQVCUWNPljRkX1GC0FEhT8iKjXtbCeGgNshY9dujaxjgYKmFj+rSoewbutAqhoLqG7MpbYln8ZgIUHbE3s4Z9vmfioxpUF77+725xjM+W1pMec6ui+tNTnuMgZmr6EkewN5/mpyM2rIyainID+M32dHrutI/g3liJxnd7vzmzCyaRNiH/nHH241x9vm/Nsmb0eoLjJCwvSDDnc8h5+GSCB3/DuO/Ybb242uG21D1G5zxK4VueDKI5VYE9qvlCms4PTHxd1o/hHLFfn+Ix7LsWXtjjca8h7LNxiIh5qEm42XbaDODM6ivzeH31TGdfrjeSOj+49dW46E6ynqGdH+uooI3NGCHtGK0No213K4BZrLoGlt5DqO7sI2hUU8BbQJZ4l+x4nnxyxsd44jRO3agfi52TTF/MaInE/lMIVCDrjfPJhs//3F6Ok/Ot1mcF//3iVsLQ0QCLkJhl1mCrnguM9QTneHfH3bEy6d+BuL9n3j1h7GpnUN1Ldk0Rzw0RL00hzwEdr/Udw+f+yURW23v3eOLu/MXpT2D+t/9869LCv+A1SNhcox0DAQgAsvcHLKZDNm2b1w97Ye99s6o1qzqX4Ts7fMZs6WOTQEzZihtqWWlVUrWVG1gmMDk8hZnsXa8uGsqxhBVWMeTa0ZlAzN4dQDJ1Nc4KW4GIqLjYeR328mny/uidPe8ybx2DbVbWJzw6bIgyhoaYXWFijb9CW3ffS+GYeWT4Cq0dCcj1fnc+IR+Qwc4KUgz0FJsUVBgRFmoh5OiXkcow/4HJYJGLBtnfAwStPSEvdwqq1VVFfBfXcuY3jhOoYVrGdQ3iYKsyoZVlLB6WfnRjzGo78dl7nGYx5PkZCFRO+mr68yRWe2gW0r3ppzKivLxrCidAyrt46mpimH+pYcDj15PCUl5tjy8403l99vjtfni1dXTzzPDkf8Gkz8LYRCxpMsWmylqQk2bjQ5M+vr41NjI9x+O+y+u/n/Ez2/0fGh2x33rGo/Jf4GEqdoqpnWVvM/qq7O5EnuD1IpOJ0HnNhONDpAa31jwjpTgDvbCU6/AEZ1tm0XgtN9wFftBKe3tdYvJ2nb1cDVAMOGDdtv3bp1vTrWnlLbUsuT8580N6N2mJAdYm7pXNbVriNoB2Pzw3aYkA4RskOEQppgswcVyCHU7APbiUO5cODCwmXcKi2F02HhdILb38Lugwex59CRuByO2OAv25NNrjeXAl9BG++LDHcGg7IGkePJ6dnNfYTGQCNbGrZQ3RyXhUN2iOqWaiqbKhmVNyqpt0euN5cx+WO2y2ai7aUVSzsVBpKR58tjTP6Y7bYJ5h/H4vLFbSraRWkKNrGschnTN07n601fs6JyBcFobps+RGExJGMEexbsx0GDD2Fk/nBq7M0QGdhrrZm+cTp1gTq0js+ztW0mbF6+6Qvy6zq2rSrbxfn/OgKlFBYWlrLMe2Wxd/HeFGcWo1AopSjwFXDRnhf1rPGdeWIVFxt/4m4QtsPc89U9lDeVs7VxK2WNZXyz6Ruqmqs63WbLX6EkSTGz0gwY+PPk2/icPg4ZegglmSUMyBjAgIwB/GDfH7TJ9bVN+uB4t4s+sju3dC6lDaXk+/LbiEhOy8nYgrFkujO3u4ktoRaWVy6nNdTW06e2tZbKpko0mgJfATnenJhtpRRF/iJKMkvwONvFO3bjmLXWVDVXsal+Uxu7reFWKpsqaQg04Ha4GZw9OCYqRxmcPZiBmQO3u98K22HW1Kxp01+C8WTbULuBjXUb2Vy/iS31W9hYt545pfNpCfdQrd0GTmAfDwx1wiAnDHSCw5XJyoEXsrJ6Jcsrl8fE/CgK8CnIsMCvjEeXIhJGR8Kk4invbSLhdJH3nwyBonb354O+2octhXMiJ8eNCntQgMcXZlBGCb/Z9xecNOQonJYdG/CpqP4AmAG7eVWRZ35NoWYeXfYSdy/4H2E7jLLNj77RNl5mFuBdcyxNI6eaXdjxRrmcFtfvfz13HH0H2Z5O4sG7oCnYxJ3T7uSvX/6VkB0XnKIPRQpen0blnMNi863IeH3dOpOUvT2JT1ah7U1mexLFkMSn15YFrH4Cpl9mZjoziRUBGHkp7P/viLFgJIdgmDbeYtEb+ugOOwhOCULIG2M6L/rg8Bvxyg5D0aFwTEKqzVAjsaIWid5nieJLbCDdTuhCw+uj2thdWTqasT9daQ7XaQYM4bBJG7A4ltwhflMeDsfPVTSfZbKn2e1Fp/aVGV1WC/43E3KwKVdkJw64oN39gh313oscR7LjfW3wdhQOwQgtWhsR5vSV4BsYsRk0YSWx7zcyYGsvdJHwI+viPHfJBU1G3GlPO+W2zXl8ZRi6eSuWZWMpMymleyZeHPEGevBpNDVFwnfr4gO7xLwziQ8EwyGNXvcC1sYXjAemFTb2rfh7j7OVbF8dA3LKGJQX+f8Z+y2FoegIOHpKvB3BeuLemdELqZ2wF50fE7miFxfwRttzbduKyb+eSWWDufewtYWtFdnZTqZ8VBITHBKv2fav7b6IuD1oYzrmOAGEbZvhvzwTsjreM3z/5D158LQHe+zRnciS8iVc89Y1Se+nZ/3tDiha3GH+/fdmcu4e51KUUbTddssaynhp8UtJ7X749Wber793u/e9vZyUPZQP6jYQvWq8kf+1WrmwHR4u3/tyrtnnegZ5xtLUZASMcDhyLYTtNmKHbYO9/H+w+j98SS1P2FtZqJtwR37YTbGYDxhqweV7nMLqplqW125hVcNWKluThF5pIOiDQKZxPIg+0OswOUCF6fiAzybPaTPKHWK3zAbG+Zu58tQqbGce4XD8Nxn1km4votg27H50Ca7Kjn1isKCYpR+XbrOviP4+xuV/iTNc07GD9xTSXqANh8GaeBKqouP4wi4soOLxS1Hrn4z1GZayUeg2/ZjH1WpMnVNhxOgk2Lb5n9TcbKaWFhh2QAnOTo537julbUTGZK8eDzHnhtzcngvBfYGE1PVTlTrh20XYDvPmsjd5b9V7zC2dy8b6jWxt3JrUu2NQ5iC2Nm4llPBkHEwI4ICMAQzOHsweRXtw7MhjOWePc3o10P+2EAgHqGiqMKJUQxkrqlbw9cavCesw+w3cj/FF42NCUpG/CJ8ryQ2y0H/cfjvccUf67f7ud8b2DkZ9az1bGrawpX4LWxq28J0jriKruqOK2lyQw1czXmFQ1iAGZg4k25PdY5HMtm1WVa9iUfkiNtRuYG3NWhZtXcQXG7+IeXQmY88BezJ50GRG541meO5wRuSOYPKgyXidyatyLi5fzKNzH+XROY/SFGiiORzP+WYpC7flZmzBWEoyS7r0gA3ZIdbVrmNtzdqYR10Ur8PLsJxhXDv5Wi7e82JcDhf/m/0//vrlX2kNtVIfqG+zrsvh4rYjbuPiiRd36ym2rW1eXfIqv/3kt7QEW9qIhJnuTJyWk5sOuImT829k6luFlG+sJCO0CHd4Ex69lWHF5YwaXEm2vz7yRNXC47FwuBxYrgyUOyNWoUZFc1YogKhbgB0ZKBoPDB1qRgcbCAdaCQZtdN0qslu/xAh00QSkyhSUOPCBiJin0eFWGurDVFdpAhGP6bCtIoMBRdg2r/bKx3GsfxSHFcahwuY1YfK5m8nPrMLnbgEs4x3XUkqsCk/OHnDIM4RtqG7IpbI2k6oaJ1UVYZqbw4RDNuEwhELa2I0MRsIb38cqexeHFcbpCLWx6bRCeFyt5GdUYVlhbn/lD2wKH8+GDebpsttt9Ognn9DkZDSSn1lJtrcCL5U4wpXYwSbsYAjbDhsvmsTQdjsc9yixnBFBzIGynFhOBw6nG+3KI6jy8Fa9B41rjfdN00Z0sJ7Kaj9bcn9KRWAsFQ0lVNQXUF6TyeZSL1U1ToIhBw6HZWRTDVpHXmsWgB3EIoS2QzgIgA6jw61gB3A7AxRnl1GSu4UzJr/B8CHNeKnAohUsD8pywIH/NUVKLC+4stGWh4a6INVVYWqqbaqrTe6Shsb492xvfBu9+d3YubWUTYankbyMavIyqsn115CXUU2Wr55Q2MmqreNZ7r6NZau8bNjspazCS2VDHgUDi/Bm+MjIcpOR7cTrdeD3W+Tmmaf4Ho+KiHw68vDUiEux6yzyGg5p6uo1NdVQXx+mtTlIZXkrhx3YwIplIWbM8bNuo5fqWhcOl4u99nYycYJm9GjNoEGQl6/IzoLMLMjIULgjP4H2A7T2njq2bQZ9jY2a+oh4ZZd/zdGei7GCNcazKloNN28S+vDXaG0OUteUQV2jh7qaEHW1NoGATTikE4QuFfEAAXvd61hbXm0jdCUKXm5HgGx/HRmeBsb/fFmHvqew0OT6SRVhO8xlr17OMwufRrer/upx+Ni/8BjunvwaDuVs4+HR/t9NsqHlhsYVXPn1gdQHqzssc1keTht1Lu+tfZPGSHiQFXm04VRuNDb7Z57Fafm3MNyzdyx0qb2HU3vbq1tm8WbVXcxufAtQ2DqIjR07Nr+Vw2l5v+TRK3+JL3I7WNNSw/0z7mfW5lmsql5JQ3MlgZZKnHYLWZZ5EOMk/gDG0e5BjIr01ZmeHDLcWRT4ixiVN4YTx57MiLzRKKffeKq5sqgOBnln7Wc8u/B5pq6ZmjQHqtmb2ub/dK1N6FV7HMpBSWYJ5004j3PGn8PBQw5O+n8uZIeYXzqfFVUrWF+7ntXVq5lbOpfpm6Z3alOhOGzoYexVshcjckcwPGc44wrGseeAPbGSxP1tqd+StI35vvzk9wxdHXO7i8zWNqUNyR+uNgWbSKZ35PnyKPQX9tru2pq1hO2O7tv5vnyyPB3LDTuUI/m9Rg/sgvnOkjlhWMqkkukPUik4OTGJv48FNmESf1+stV6UsM53gBuIJw3/p9b6gK62VUr9FahMSBqer7X+hVJqAvAM8aThU4GxO2LScEGIUt5Yzryyecwtncun6z7lreVvxZYdOfxIjhl5DPsO3Je9i/dmSPaQXnmCCYKwi9LDm5E+IwVee7a2eWzuY1zz1jVtvIN6S4GvgKmXTmXvkr07LAvbYd5a/ha//fi3zN86v89sRhmdN5o/HvNHzhl/Di6HC+bcAkv+Eg/tieauOvAh422ktfH2iXm+RD1QnMRD1KCtp0RCGFD09bVhHTxRtKeYdftsYvqn5Sxd3MyqVRbrNriprHajlYuiYg95hS6KijRFhZqCAvM1Z2WZnGjRBKrR5LShMIRD8ddgEGpqNKWlkcIZFRbl5ZqHHrJYs0YxbZrNN18FWLsOSkst6uodjBxlsdeeJh/ZwBIoLoEBAxT5BYrMTHA4lMn7Fcv/FU9Cb0dqWthhTWMTVFZqyss1ZVtgSyn84mchcu3ZsPVTwqXT0PXroLUUR7gWnb07Om9/tH8o+IegfMUobyHKU2DKT0cEpfg5j4QBxkKqIuFV7+xlci8msKFhbz7yzOWdd+Dzz03opGVBUZHm0ENh//1h7FgYPBjy81UsAS/Ec6tEB8+JP+HEEI5oOoW6OiMWVVRoJk0Cny/ivVBTw6K59SyYF2TeAgcLlvhYvdZPRbWH5hYnLpfN0KFhRgzXDBmi8PlVrOKny2Xyv4H5TkNBTSBovuOWFs2mTZq1axXrN1i0tpqwQFub69LhMMcAsGVLYu7QuNdCbysiR0WNH/wAHnus4/KpU+GYY3pnoysCAfjkE5g/H77+KsTyZSEqqxTNzQ72mGAxYSKMGQPDhupI+JGKJ1j2qjbhR9HvtL23XDQstrFBR8KPNJWVcMp3LDIyur4XjCaFDgYhY0wJVpIwfLuomIqFpUnDcxLDscz1YL6zR+Y+zE1v30RTqK1HkN/l56QxJ/HCuS/0KMRsTfUaDvjfATFP5ihep5fijGLe++577Fa4G2E7zOfrP+eZBc/w3MLnqAvUddtGd8n15HLRnhdx8Z4XG/GlaT1s/RSq50P1bGjeAoEa4zlYfLSp+OwfivYPNuGTzixwZqCdflBOVGK/EfEeVET7jkgf/dZ4E4raHs8AOMd8Z4FwgN989Buemv8Umxs2d1y3hziUg30G7sPtR97Od8Z9p3c764N7gEA4QOYffARVwsOhoMnOYis4cSVcOQdOWAWebqaG1cCMwfD43vDsntDsNM9mmqOR4RHGNHpYmRH3cPeEwBWGoAMmbIWrZ8E5S6CwowNcp3ZnDWpr19LQ6AadYHdylY+Z+UZEtBJ0IZcN182A26Z132Yim7Lgd0fBE5MgHA21U3HbFyyA5yb2z4PUlAlOkZ2fAtyL8a5/RGv9f0qpawG01g8oM3r+N3AS0ARcrrWe2dm2kfkFwAvAMGA9cJ7Wuiqy7DbgCiAE/Ehr/c622iiCk7CjYdt20icAgiB8S+iHxP9Az4WiFAtdVU1VPDH/CZ5Z8AxzS+fiUA5awi34nD48Tg837n8jR408isfnPs4Li14grMME7SAZrgzCdpjjRh3HhRMv5IKJF3T7qd7rS1/nZ+//jJXVKzssc1kusjxZOFV8X2Edpj5Qn9RbdWj2UO487k4u2fOSNvMbZv6MmkV3GwHJ6Y2FPTkn3UnJxB8bISPcSqxUcjSkTTnjITlg5i34PSz6Y5v919tQm+TG/OXPL+NXT96HtjJwOo3Hj9YmSe1vfmNCzpojD9IdjnjOiO2lpcUMeN96Cy6+2FQ0jOY6AiMWPPSQaUc4HM9j2FcEyxfg+mAvMxC0WyN5cDCDxWM/glAz6GC7XFFd0M1ktKU1xQy8vhSv1xxvlL33hrlzzfFHBbu+JhiEV16B//4Xpk0z5zQcNvlBJkyASy4xFad2283kJmltNdu0Fz8SExB3CNGJTNFKxDU18MILsGKFOb7ly03S3ZYWOOEEOOssGDLEdC/5+fF8M9FqT9AxbAboIIRYlmlrS0t8emXmNJ5d8RBVVUbgbG6CQBDcTifHe27j8AljGD3a2M7ONoJPRoax73QmD0FJPN4XFj/P2yveMt5WoXi+1NXvncjSF7/b4fz//e/wox/1/ffaK/q4n56zZQ6nPHMKVU1VbYrneBwejhx+JL858jexfKldsbVxK1e8fgU1LTVtxCa/y8/xo47nqbOfSurBH7JDPDLnEe6bcR+Lyxdj23a8GJCyUCiKM4op8BfgtJyE7FDMwz3R69XCwrIs9hywJzcecCOX7X1Z23vvN3eD+uUd7LcpXd9d5t/eJrfgNumkkpjWmkXli3ht6Ws8s+AZVlevRqMJhk1ajHEF46hsrowJeH6XH1vbHD3iaC7e82JOHnNyz1JBbIs+urbqW+uZtn4a7658l7dXvB07rr6m0F/IcSOP49Rxp3L0yKMpzihmTukcPlrzEa8vfZ3pG6cnBBn2HUX+Io4bFbE74miclpOn5j/Fv775F1sbt9IcbI7ZdVkuFIqTxp7EuePPTeoJ1Z6q5iqeW/gcn679lLAOx8L3HcqB2+FmRO4IbjzwRi6aeBG53tw+P77ukFLBaWdABCdBEARhh0IEpw6UN5bz3MLnuH/m/ayrWUcgHIiFCiilcFpOFIqDhx7MDyf/kFPHndqr0Njq5moenvMwf/vybzQGG2kINMRu3q7c50puOewW/v3Nv/nn1/8kGA4S0iEy3Zm4HW5uPvBmrpt8Xae5Re745A5u//R2ALwON1bEvSGswxyUW8L9u09mj4xsYh41yoqXgY7lA0rMBWO2bwq18ufln/PXlV9Fwg7Nd9AcDqGBrK9uo/69P5KdHS+HDXD33UZ0qq83g+xoie2+wLbhvffg/PON8OFwGIEJ4JxzjOCUkWHaE/WmSEyOvj1EPUOC1avI+uowCFSbRM2hSMhk/n5w+KvgKzaiE5jlDm/X13Q3BafWoJvz//kiHy49PZawt6nJVKj917/guONMHo2ouOd09k7ci4p4oRCcfLKpCtyYEGHr8cBXX8G4ceb89kZE7AnhsCkz3tAQn+rr4+/P/mEJvrqO57Mpu5gn/1KatCpzNEeR32/Eo28aX+S3C87vsA+FYkTOKN4/awHBJl8sh1NdnTlPifmb2r9GS82vDc7gztIjCeqO4UwZoSHs5zuX6nIPpaVQVw+tAcjwK44feCHHTdybceNMKfns7HhiZ6/XfAedJdiOCl/zyubywuLnIrmlIt5KkYrVfzz1JgZlD+r+F5GCfrq6uZqDHz6YZZUdw/tclmubVZ81mvrW+qSiwp+O+RO/POyX3fLo11ozr2wezy98nqcWPEVVc1UsJ6NDORiTP4aV1SsJ2SEUCrfDzYCMAXx3r+9ywYQLmDhgYud2GtaaCqq1C6Eq6uFUbbwfiw43eX4yhoF/CLhyzXxXphGLLAdtk1lHHxREPZxsYt6S4Wbj0Rqsh2CtCTse9f1tHjtAaUMpU5ZP4ekFT/PZus9iQkOhv5Azdz+T8/c4nyNHHNmr/FpdkqJ7gEVbF3HfjPt4d+W7bKrfFBPUoteLQzko9BdSnFGMy+GK5XBNfPATFR/zffkcNeIortjnCk4ac1KXdutb63ls7mO8tPglFmxdQE1LDZay2hSlGuAfwKi8UWR7s9lYt5E11WtiIY8Kk+fWUhYlmSUcPeJoLt/nco4acVQnp0gzt3Quf/zsj7yy9JXtPl+dcdU+V/Hjg3/MHkV79Pm+e4oITiI4CYIgCMJOI3Qtq1jGo3Mf5X+z/0dVcxW7F+7OdZOv48KJF/YqgWwywnaYt1e8zZ8+/xPzSucRCAdwKAchHTJPz8MhPE4PuxXsxm1H3MaZu5+5TW+q6D7v/PxO5pbOJWSHYkUlooOi40Ydxw0H3EC+L3+bbbS1zdsr3uYfX/+D1lArreF4iECWOwuPw8OPDvoRBw85mL9+8XdqaowHSl2dEUJaWywcS89jt8BFjB7lYPhwKCoyl0NhoZn8/vhAPBbaZhHLq1TbUsvDS+5mcfUcQiEjgESTcQdbXCz7w4tsWO/giy9gzhxYudIkSa+qMvsZNsx4wURtlpSYwXpubtxuYihfokgQCpnXujpz+ZaVQUWFeX3yScxAsfxzqPjaeCw0roXWSuNJljEKMoeDb7AZQPpKTNlod17Eo8wRnyxHPAl3NLdTtDJey1YjRrWUoVu2ct66KjbVbaKpCeobIh45zWBVTiTzk//gUE4KCkxIXXGxOd8DBpj3bjex8MVoiFu02lEwCFua1vHPdT+gKVRvhKaIGBFoctFw/0eEg22vv2h+n9bWvvUg6zV9NFj93+z/cdM7N3XIc+Nz+rhw4oU8csYjPW5abUstu/17N8oa2/aHCkWuN5cHTn2Ai1++uEN1ZIBcTz6vH78EV2BALGF5ba357hKTlENywamRMu6qH08THXMaWTj45NLPOXxkx+qanZIiUSBkhzjhyRP4eO3H272PRBSKB059gKv3u3q797GkfAkvLHqBJ+Y/werq1bH54/LH8b29v8f5E85nXMG4vmiu8UAN1hshO1hvRKM9ToHyJEVrivJgzlPxfiQWJp1QudHpi+VwwlPUs8zO/VWUJk0PnbbUb+HjtR8zZfkUPlj9AeVNyROW+V1+Dh16KKfvdjrHjjyW3Qt371UqkuZgM19t/IoPVn3Am8vfZFH5oqTrZbgyOHz44Zw+7nSOHXUsY/PH9thuXUsdd3x2B88tfI7S+lKUUoR1GIcy1Z73Ltk7lgezMdjINxu/YVH5IlMIChuHcqC1ZmjOUC7b+zJuPfzWTnNm9gciOIngJAiCIAg7jeDUXzfXS8qX8Lev/sazC56lOdSMx+Hh7PFn84tDf8Gkkknbtc/llcu558t7eHD2g33bWExI379O/henjjsVh+VgWcUyfvzej3lv1XsdEslmujPJ8+Zx51F3c0TROdRUW1RVRfL3hOLCUvspZDUwpeoe3qj8C7YOE9Btqyn6HBlcsNul3HfG3fjdnXucaW28cqKhUROOK8Fd1fE7bskt5t1HS9sIUO0FKY/HhG4VFBgvmC7v+7Vt8rK0VkKgMjJg7DjQpzAHZtwPWGbA2EaMckbmucCTj+3K4+w3ruetFVM6CBJ+l59L9ryEh057KHbMFRVGkEgUzxJfQ6F4zqZmXcvVs/ahtGVdh+TNCsXvJ77EZw+ezWefGaEq6k02ciRceSVcfrkRoKLeVb0JY4xWUgITotZjz6k+HKz+Z+Z/+Ol7P+0gOvldfh474zHOm3Bet/eltea0Z0/jw9UfthFvwVRW/urKr9i9cHfeWfEO5754bocKZy7LxeRBk5l2+bQe5TMCI0Yf8sghzN4yu0MOO5/Tx8vnv8zJY0/u0T5TLQrc/dXd/OrDXxG0g7E+xamc7DNwH44ecXSbdZtDzTw5/0lqW2rbrFucWcwH3/uA8UXje92eLv+P7SICzLfd7prqNXy89mP+O+u/VDRXcM1+13DsyGPZq3ivHv/mekJ9az2fr/+cFxa9wMzNM7ly3ys5ZuQxTBwwsVthpN1lS/0WHp/3OPfNuI/q5mqagk24HC6cysl+g/Zj5uaZBO0gtrbxOr0MyhzEDQfcwHf3+m7fhkz2ISI4ieAkCIIgCDsP/XVzDSkTu0obSvnJez/hlSWvEAwHY/kcoi76Q3OGku/NjyU8bQm1sKF2Aw2BhtjAzcJCo9m9cHfuPuHuTgemFU0VPDnvSf759T9ZW7u2w3KFwuVwbfMGOmSHkiZ2VygOGXoIPzroR5w27jQ8zu1QNHbyAZStbX7+/s95YNYDHQQJv8vPH4/+Iz8++Mc9alowHOTox49m5uaZHYSQDFcGL533EkNzhrK5fjONjfDNN7BkCSxdCptX59G4YjI+n6kMN3YsDBpkptGjTYJrv9+IT9Ek0a5I9GY0XC8QgAUVs9naUMnmzbB5U1wgLF05kC3zJvboePr6O/73N//mlg9u6ZDQOsOZwbzr5jEyb2S39nP/jPv5xQe/6CBe5Xhy+PLKL9uEp3yw6gPOfP7MpN/xTQfcxJ3H3UlP+PkHP+f+Gfcn3d9rF7zG8aOP79H+gLT8ljbWbeSUp09hVdWq2Pn3u/z87OCfccfRJndRbUstBz98MCurVsY8On1OH9fvfz13HXdX3wkF2/Is2Qn6j36zu7M8dPqWoLXmm03fcP/M+3lp0UsE7SBBO4jH4cHlcPG9vb7HNftdk7QYyo6GCE4iOAmCIAjCzkN/Ck4ptq215vP1n/PnL/7M1DVT0VrTGm4lw5XBsJxh/OX4v/DGsjd4av5TtIZasbHJcGVQ5C/i54f+nEv3vjRpot3ObN33zX3c9cVdbKrf1Ou2A0weOJm7T7ibI0Yc0bsd7ewDtwj3z7ifn73/s6ThXs+f+zyn7XZat/ajteby1y/nhUUvtNmXQznI8eYw9dKpTCqZxFGPHcWn6z4ly53VRjAM2kF+fejtnFX8czZtIhZWaarbxcMQ6+ri4XvRcK+o59jmYfeydvSvcOBGWaZaIMqmRdezR9YhzL3xi1hlu26Rgu/471/9nZ+8/5Pt2rYrXJaL2dfMZuKAjqLax2s+5tRnT+0gEvmcPh4+/WGOGdm9cnnvr3qfq9+8mpZwWy9Bv8vPlIundJoHZpuk6bcUCAe48e0beWrBU7Fz4Xf5+fXhv+aGA27gsEcPY2nFUgLhAJay8Lv8PH3W05y+++l91gZABKfe2BXBaYelOdjMK0te4ZG5j3DD/jfwnXHfSV1urhQggpMIToIgCIKw87ALC06JbK7fzH9m/Id/f/NvQjpEQ6ChTVJSS1kcO/JYfnHoLzhi+BG9ylXRFGzi5cUv84+v/8Gi8kXY2iYQDpDhymBM/hj+dsLfWFW9itum3kZzqJmmYJOpgGTbnDz2ZG484EaOHHFk34UV7OwDtwSmLJ/COc+fQ6vd1itJoRiVN6pbye3LG8tjVbYSGZ4znGmXT2NozlAA6lrruOSVS/h4zcc0BhvbrOt3+bn9qNv5+SE/7/Ex3Dv9Xn419VdJQ9aOHH4kz5zzTM+rH6XoOz71mVOZsmLKdm+fjBfPe5Fz9zi30+XT1k3jqMeOSlrhyuv0RpL4d45G0xJq6TDfwuLTyz/lsGGH9bzRUdL8W3p6/tNc/dbVNAeb0Wh8Th9F/iLKGstoDbfic/oYkj2Edy55h9H5o/vcvghOabQrCN1EBCcRnARBEARh5+FbIjhFCYaDvLr01ViS8Ux3JjcecCPX7389g7MH97m9lVUreWjWQ/xv9v8I2sE2QpetbXwuM2C86cCbuGTPS7onNPTXk/Nombh00+6J/TMLnuGSVy7pUxOZrkwWX784JjZF0Vpz34z7koaFbY/o9Pfpf48JjYn4nD7+dOyfuPnAm7dP7Ezhb+nkp07m3VXvdpjvd/lxWcndsJqCTbFQr0SeO+c5Lph4wTZtPjjzQa6dcm3PG9sF/z3tv1y171W920k/9FmLti7ipKdOorypnNZwKwqFRuN3+Tl93Ok8csYjvaoi2iUiOKXPriB0ExGcRHASBEEQhP5jZ3Lj768b+35IlB62w7y36j3++fU/eX/V+7gdbi6bdBk/nPzDHuWMWFy+mGP+MoFwklN39hL499vg2k5NKKzgZyfAU3slWajBF4ZAktQwJ66Ex15jG34nXfPOGLjqdAgnceq642O4Zmbb6+Hz9Z9z1GNHdUgkbimLTHdmUi+YsA7TEGjoMH9I9hCWXL+ky/DJOVvmcOKTJ1Le3LGik9/lx+fc9oA/6s3WngJvAe997z32G7RffOYO9ju+5q1reHzu423yXfmcPh449QEK/YVt1p26eir3zbivzbpep5cXz3uRU8ed2u2mPDrnUa5444oO852Ws9OKUS2hlqS50B474zEum3RZt213Sj/1WXWtdVz08kW8v+p9QnYIv8vPPSfew9X7Xt0rb8xtsisITjvYb0kQeosITiI4CYIgCEL/sTPdXH/bnmD3gdBV31rPz75XzCO7NxNqJ/74AzCpFKY8A7kdI4q6pMENZ14IXw2BpnapLJxhOH8RbMo2ywPOtsszAvCHj+DH03tmM8qaXNjrOmhonw9dm31//no+kxZVdthuQ+0GTnjqBNZUr4mJGy7LxcQBE/nnyf/EacUbuqV+C5e+dmkbwcnj8HDRxIt4+PSHsaxthy9urNvI5IcmU9bYd7+vIn8RM6+eybCcYbF5//fZ//HWE7/usG5OKzz1ChR21Kx6xC3HwWfDO87PbYHXnwN3KPlv4I5P7uAvX/4lJpo5LSd7F+/N9Kumx8718srl7PPgPm2EtUxXJh9d9hH7D96/x239dO2nnPrMqTQE49+b1+nlz8f9mdPGtc3Z9dqy1/jV1F+1CafLdGcy5eIpHDG8l3nQouzEfcd2IYLT9iOCk5AiRHASwUkQBEEQhO7wbROc+tDu1xu/5uJXLqa0obTN4N5luSjJKOHDSz/sdk6X9bXrOf7J49lQu4GAHYjN9zv9FPgLePrspzl8+OG0hlo57dnT+GLDF0mTOk+9dCoHDz24R8fREmph0gOTWFG1AlvHXbMUihxPDtOumJY0uXSU1lArF718Ee+teq9NcuWLJ17MQ6c9hFKK2pZaJj04ifW162M2fE4f/zj5H/xg3x/0qL22bXPRyxfx4uIX2+SAUihyvblke7I7bFPXWkdNS02H9c/a/SxePO/FDmLXNW9dwyPfPNRBUPSE4JfT4PZPe9TkNiwvgL2vhZYkkXCFjbD+6QH4NnU+OP/NR7/hnun3tDnXNx94M3869k+0hFrY6z97sbJqZexYM1wZTL10KgcOOXC72zyvdB5HPnYkta21sXkZrgxmXj2T3Qt3B2BJ+RIm/3dym+syx5PDp9//tG+rTu0CfUef2e1P29+ScbUgJEMEJxGcBEEQBEHoDjviIGonshsMB/nzF3/mdx//LmmC5W0lV46ZpqNtC4tbD7+V3xzxGzzOuOtRMBzk7OfP5qO1H3UQnQp8BSy5fglFGUXdPoZLX72Ulxa/1CankUKR583jiyu/iAkKXWFrm1s+vIX7Z9zfRgj5/dG/56YDbuKox49i5uaZBMJGTMtwZfDSeS9x0tiTut3O9szZModTnz2VquaqmEeN3+Xnd0f+jl8c+ovYevd8dQ+//ujXsePzODzkefN46+K32obQJVDdXM2If4ygrrWuw7JcTy6lPytt8530hCtfv5In5j1BSLcNO8twZfDYmY91mcw7yq0f3so/v/ln7Fz7nD6mXDyFZxY+w9Pzn44da4Yrg/e/9z6HDD1ku9qayMKtCzn8kcOpba1Fo1EohucOZ+F1C9FoJtw/gQ21G2LLcrw5fH7550wYMKHXttuwi/QdfWK3p7bF00gQ+gQRnERwEgRBEIRvH/01mICeDyh2xMFbL+x+tOYjznjujKT5iVyWC4eVJPESJq9UssTOPqePl85/iVPGnpJ0u5Ad4oKXLmDK8ilt8vQ4lIMh2UO4fv/ru1Vh75tN3/Dq0lfbtEGhKPAX8OUVXzK2YOw295HIf2b+h5++99OY4OF1eDloyEF8velrmkPNOJSDHG8OUy+dyqSSST3adzLqWuv43ivf48M1H7YRuqKiU3uxye/yc9SIo3jm7GfI8eZ0ue8HZz3IT9/7aYfqeJnuTO475T4u3fvSHre3qrmKIfcM6ZCwXKE4YPABfHXlV93KB6S15hcf/qKNwJfhzMDGbiM2vfvdd3tXEa4dS8qXcOgjh8a8xbxOL6eMOQWN5p2V79ASaol5mn155ZfdEit3GhFkR+yzemo7lbmmtsW3ZBwufDsQwUkEJ0EQBEH49tGfgwnou4HPTig4gQn1+sn7P+GBmQ8QskOxZNouy8Xhww7nrPFnxTyeNJopy6cwdc3UmNhjKQun5eTySZfz71P+3Sb/UTLCdpiJ909kaeXSDsssrE5FriganTS5s6Usll6/tMdiU5S3V7zNeS+e18H7yu1wMzhrMJ9+/9MOleh6g9aaB2Y+wE/f/2kbYenoEUfz0ZqPYvN8Th93HXcXNx5wY7dEnbAdZsL9E1hWuazDsjH5Y1h+w/IeJ4v+07Q/8cfP/thBcPI6vcz8wcweeQNprfnp+z/lwVkP0hRswqEcsWvO7/LzziXv9F3epASWVy7n4IcPpqalBlvbuC03SqlY9bZ8Xz5fXflV96+fnUUE2RH7rJ7a3lnOtSDs4IjgJIKTIAiCIHz7EA+nHcJuRVMFP5zyQ6asmNLG6+bwYYfz8vkv47AcXPzyxR1yHh078lgeOu0hSjJLum0rZIfY/d+7s6p6VZ+03VIWX1zxBQcNOahX+5m9ZTbHPXFczBPG5/Sxd8nevHvJu9v0LNpe5pbO5dRnTqWiqaKN15fH4SHPl8dbF3UeQtcZX274kuOeOK6DQJThymDKxVM4csSR3d5XMByk5O4Sqpqr2sz3ODx8f9L3eeDUB3rUNjCi003v3sQjcx6hNdRKWIfxu/y8eeGbHDPqmB7vr7usqlrFQQ8fRFVzVSwnl6UsCnwFTL9qOqPyRnVrP7a2eXO8A53kZ7nvFhhW23F+T2hxwgejkldePGATDKr7lglOO4s3mSDs4IjgJIKTIAiCIAg7Mjvi4K2P7X64+kO+9+r3qG2ppTnUjNfpZVDWIDwOD2tr1sbmZbmzePSMR/nOuO9slx3bttn3oX2ZXza/TS4oC4txheNwO9qVvNOwumY1jYHGNut7HB6+vPJL9h2473a1oz3ratZxyMOHsLlhM+dPOJ8nz3qyY1v6mLrWOi599VI+WP0BTcGmmKfT02c/vd1C17kvnMsby97oEPp47Mhj+fDSD7u9n2cXPMvVb13dIewy25PNuh+tI9ebu13t01rzwyk/5IFZD2Api3cveZfjRx+/XfvqCWuq13DQwwextXErAMUZxUy/ajojckd0ex8Lty5kz//sSUYrOBJ+flpBbjOs/ic4O6ZG6zY3nwT/27fjPhrc8KvZGfzhzY4hsJ2ys1dsAxF+BKGPEMFJBCdBEARBEHZkdvbBWzcHbs3BZn7z8W+4f8b9scTWSilsbeNz+rhinyu467i7yHRn9qo5WmtufvdmHpnzSCznkEM5GFcwjjnXzGmT4Pquz+/iD5/9IeZd5bJcDM4ezPQrp1OcWdyrdsTorxLymHMRzb9057F3cuOB3Quh64zN9ZsZ+6+xHUIEPQ4P86+d361KhFpr9vzPnh3CH/1OP/eedC8/2K9nlfra0I/nen3teibePxGlFAuvW7hdoZJXvnElzy54NqkX2V9P+CvXTb5uu9q2rmYd4+8b32G/AIOyBrHshmU9+931VZ+1M4U+C4KQFBGcRHASBEEQBGFHZlcYvPWgnQvKFnDxyxezqHwRYHIAPXvOsz0O8eq6OR0TSfucPi6YcAGPnvkoAJ+t+4yTnjopNgh3WS6G5w7nyyu+7FFlu23SXx5sXQmQvRBgfvzuj7n363uTLutNJcICXwFbf761WwneO2VHO9c9PM8toRYm3j+R1dWrO5yjHE8OG368gSxPVo+bd87z5/DGsjc6VAP0OX18fsXnPffk2xX6LBDBSRD6gM4Ep1705IIgCIIgCEKnlJSYgVR3p67oyX6sfrq9K+6ZJ9CexXsy99q5/P7o33Pb4bex+PrFfSo2gfGc+stxf+EnB/0Ev8sPQHOomRcWv8AT856gtKGUM587MyY2uR1uxuSP4eurvu5bsak/6crbrReecL8/+vedikK6m3/JuPPYO3snNvUnnZ3PHp5nr9PLmxe9ic/l67AsEA5w1+d39bhpc7bM4Z2V73QQm/wuP3845g99Fja6XfSw79hlbAvCtwDxcBIEQRAEQUgFO4mn0beFP3z2B+76/K42nk6j8kaxrGIZIR3C4/AwrmAc0y6flpok3jtijq5e2v79J7/nd5/+bru3b8+QrCFs+MmG3u9oRzzX22H3v7P+y4/f+3EsJDSKz+lj1U2rGJg1sFv70Vpz8MMH8/Wmr9vMd1kuDht2GFMvnbp9IZb9dZ4FQdjhkJA6EZwEQRAEQUgnIjjtcPz1y79y+ye3x0Qnh3IQ1mE8Dg8TBkzgk8s+2a5QpW6xI4ogfWA778951LTU9GofUeZcPYdJAyf1fkc74rneDrtaa858/kzeXfEuATsQm++yXHxn7He4+8S7u7WfT9d+yvVvX98hd1O+L59lNyyj0F9oZuzg+d8EQdhxEcFJBCdBEARBENKJDN52SP759T+5deqtNAWbcCgHLoeLvYv3ZuqlU8lwZ6TO8I4ogvSB7amrp3L8k8e3CZFTKHK9uficHUPCbGxKGzpen2fsdgavXfhar9oSb8AOeK63025tSy3FfyumNdzaYZnf5d92+KGGxmBj0hDG9777HieMPiE+Q0RyQRC2k84EJ2d/NEYQBEEQBGGXR0SfHZKbDrwJj8PDtVOuJazDHDzoYN7/7vtJ8+UI2+bYUcfyk4N/wv0z7o950Gg0Q7KHMP+6+R3W/8f0f/Crj37VpsLdkOwhvHDeC2lr885EjjeH+79zP1e+cWWHZe2rBPaEAwcf2FZsEgRBSAE7aUY+QRAEQRAEQdg+rpl8DfeccA8njTmJD773gYhNveT2o27vcA5XVa/im03ftJkXtsPc9cVdbYQSv8vPf0/7L26HOy1t3Rm5Yp8rOH7U8X22P5/Txyff/6Tjgv5KoC2JuwVhl0UEJ0EQBEEQBOFbx48P/jHvXPIOXqe3v5uy05PpzuTfJ/+bDFc8JLE52Mz/Tfu/Nuu9tfwtGgINsc8O5eDgIQdz0piT0tbWnZW3L3mbXE9u0mUuy5V0ShZup1B8dOlHya/70lIT2pbuSbxBBWGXRQQnQRAEQRAEQRB6xYUTL2RswVgUJg+QRvP+qvfZWLcxts7vP/t9G8HJ7XDz4KkPpr2tOyNOy8nSG5aS681tMz/DlcETZz1B4DeBNtPGn2zsICr5XX5ePv9lDhp6UBpbLgjCt5leCU5KqXyl1AdKqRWR17xO1jtJKbVMKbVSKfXL7myvlLo1sv4ypdSJkXl+pdQUpdRSpdQipdRdvWm/IAiCIAiCIOxUlJSY5M7dnbZFT/ZVUtLFbhSPnvFoG5HD1jb3Tr8XgDlb5rC0Ymlsmc/p4/oDrmd0/ujtPhXfNoozi3nh3BfaJGNvDDZy87s30xpqm1T8tqm3EbJDsc8+p4+LJl7EWePPSlt7BUEQeuvh9EtgqtZ6LDA18rkNSikHcB9wMrAHcJFSao+uto8svxCYAJwE3B/ZD8DftNa7A/sAhyqlTu7lMQiCIAiCIAhCz+hL4acn++mPyodRtmF7UskkLphwAR6HB4BAOMCDMx+kMdDIn6b9iZZQS2xdn8vH7UfensrW7pIcP/p4rp18LX6XPzavMdDIv775V+zz8srlPLXgKQLhAGDC6AZlDeLfp/w77e0VBOHbTW8FpzOAxyPvHwfOTLLOAcBKrfVqrXUAeC6yXVfbnwE8p7Vu1VqvAVYCB2itm7TWHwNE9jUbGNLLYxAEQRAEQRCEntGfwk9/0Y3kzn874W+4HK7YZ43mn1//k7eWv4WtbcCEgf375H+T4c7obDdCF/z5uD8zKm8Ujsjz+MZgI3d8egfVzdUA3PzOzTGxCYy49+ZFb0q+MkEQ0k5vBadirfUWgMjrgCTrDAY2JHzeGJnX1fZdbQOAUioXOA3jGSUIgiAIgiAI3w76I7FzN5M7F/gLuPPYO2MJxBuDxrtJowHjbbNb4W5cOPHClJ6iXRmXw8UbF77RJrQuZIe449M7+HLDl3y2/rOYuOd3+fnHSf9gfNH4/mquIAjfYrYpOCmlPlRKLUwynbGtbaO7SDJP92YbpZQTeBb4p9Z6dac7UepqpdRMpdTM8vLybjVWEARBEARBELaJlJDvlGsnX0tJZjzfU2OwkdawyTHkdXp55PRHUN3JL9Xf9FfYZBe5sqKMzBvJw2c8HAutawm18ODMB7ny9StpCjYB4HF4OH7U8Vy5z5W9PhWCIAjbwzYFJ631cVrriUmm14EypdRAgMjr1iS72AgMTfg8BNgced/Z9l1tA/AQsEJrfe822v6Q1nqy1npyUVHRtg5VEARBEARBELqHlJDvFKfl5JEzHmmTZwiMAHLRxIvYu2TvfmpZD+mvsMlu2j1/wvmcM/6cWKhcIBxgZfXK2PI8bx5PnPXEziHuCYKwS9LbkLo3gMsi7y8DXk+yzgxgrFJqpFLKjUkG/sY2tn8DuFAp5VFKjQTGAt8AKKX+COQAP+pl2wVBEARBEARBSAFHDD+C40Yeh9Nyxua5HC7+cvxfer6z/vI02gl44NQHKM4oRqGwsdHaBIX4nD5ev+h1sj3Z/dxCQRC+zfRWcLoLOF4ptQI4PvIZpdQgpdTbAFrrEHAD8B6wBHhBa72oq+0jy18AFgPvAtdrrcNKqSHAbZhqd7OVUnOVUlf18hgEQRAEQRAEQehj7vvOfbgdbjQap+XkzmPvpMBf0PMdfRsTtHcTv8vPmxe92SafU4Yrg98e+VsOGHxAP7ZMEAQBVFQF39WZPHmynjlzZn83QxAEQRAEQRC+Nfz+09/zu09+x9Dsoay5eQ0Oy9Hznewk3kZ9RnFxj0Mn75txHze8fQMAhw07jE+//ymW6q1vgSAIQvdQSs3SWk9uP196IUEQBEEQBEEQUsIvDv0Few7Yk/u/c//2iU39zU6Sp+uHk3/IfgP3w+Pw8NJ5L4nYJAjCDoFz26sIgiAIgiAIgiD0HK/Ty/zr5vduJ8XF/RNWtxNUBIyilGL6VdPRWuNyuPq7OYIgCIAIToIgCIIgCIIg7MjsBJX5dgQSE7QLgiDsCIivpSAIgiAIgiAIgiAIgtCniOAkCIIgCIIgCIIgCIIg9CkiOAmCIAiCIAiCIAiCIAh9ighOgiAIgiAIgiAIgiAIQp8igpMgCIIgCIIgCIIgCILQp4jgJAiCIAiCIAiCIAiCIPQpIjgJgiAIgiAIgiAIgiAIfYoIToIgCIIgCIIgCIIgCEKforTW/d2GtKCUKgfW9YPpQqBC7O6ydvvTttgVu7uS3f60LXbF7q5mW+yK3V3NttgVu7uabbErdnc128O11kXtZ35rBKf+Qik1U2s9Wezumnb707bYFbu7kt3+tC12xe6uZlvsit1dzbbYFbu7mm2xK3Z3RdvJkJA6QRAEQRAEQRAEQRAEoU8RwUkQBEEQBEEQBEEQBEHoU0RwSj0Pid1d2m5/2ha7YndXstuftsWu2N3VbItdsbur2Ra7YndXsy12xe6uaLsDksNJEARBEARBEARBEARB6FPEw0kQBEEQBEEQBEEQBEHoU0RwShFKqZOUUsuUUiuVUr9Mo91HlFJblVIL02UzYneoUupjpdQSpdQipdTNabLrVUp9o5SaF7F7RzrsJth3KKXmKKXeSqPNtUqpBUqpuUqpmWm0m6uUekkptTTyPR+cJru7RY41OtUppX6UJts/jlxXC5VSzyqlvGmye3PE5qJUHmuy/kIpla+U+kAptSLympcmu+dFjtdWSqWsskYntv8aua7nK6VeVUrlpsnuHyI25yql3ldKDUqH3YRlP1NKaaVUYTrsKqVuV0ptSvgtn5IOu5H5N0b+Jy9SSv0lHXaVUs8nHOtapdTcvrbbhe1JSqnp0f8TSqkD0mR3b6XUV5H/UW8qpbL72GbSe4009Vud2U5p39WF3ZT2W13YTWm/1ZndhOUp6be6ON6U9ltdHW8a+q3OjjmlfVcXdlPab3VhN9X9VtKxSqr7rS7sprrP6sxuOu61OrOd6n6ry/FoCvutzo435fdbPUJrLVMfT4ADWAWMAtzAPGCPNNk+AtgXWJjmYx4I7Bt5nwUsT8cxAwrIjLx3AV8DB6XxuH8CPAO8lUaba4HCdH6/EbuPA1dF3ruB3H5ogwMoBYanwdZgYA3gi3x+Afh+GuxOBBYCfsAJfAiMTZGtDv0F8Bfgl5H3vwT+nCa744HdgE+AySk8v8lsnwA4I+//nMZjzk54fxPwQDrsRuYPBd4D1qWiP+nkeG8Hfpaq77YLu0dHfkeeyOcB6TrPCcvvBn6bxmN+Hzg58v4U4JM02Z0BHBl5fwXwhz62mfReI039Vme2U9p3dWE3pf1WF3ZT2m91ZjfyOWX9VhfHm9J+qwu76ei3tnnvnoq+q4tjTmm/1YXdVPdbSccqqe63urCb6j6rM7vpuNfqzHaq+61Ox6Mp7rc6O96U9ls9ncTDKTUcAKzUWq/WWgeA54Az0mFYa/0ZUJUOW+3sbtFaz468rweWYAbsqbartdYNkY+uyJSWxGRKqSHAd4D/pcNefxJ52nME8DCA1jqgta7ph6YcC6zSWq9Lkz0n4FNKOTEC0OY02BwPTNdaN2mtQ8CnwFmpMNRJf3EGRlwk8npmOuxqrZdorZf1ta1u2n4/cq4BpgND0mS3LuFjBinou7r4n/B34BepsLkNuymlE7vXAXdprVsj62xNk10AlFIKOB94tq/tdmFbA9Gn9DmkoO/qxO5uwGeR9x8A5/Sxzc7uNdLRbyW1neq+qwu7Ke23urCb0n5rG/eTKeu3+vE+tjO76ei3ujzmVPVdXdhNab/Vhd1U91udjVVS2m91ZjcNfVZndtNxr9WZ7VT3W12NR1PZb/XbOLgniOCUGgYDGxI+byQN/7R2FJRSI4B9MCprOuw5Iu6+W4EPtNZpsQvci+lA7DTZi6KB95VSs5RSV6fJ5iigHHhUmRDC/ymlMtJkO5ELSdGgrT1a603A34D1wBagVmv9fhpMLwSOUEoVKKX8mKd8Q9NgN0qx1noLmJszYEAabe8IXAG8ky5jSqn/U0ptAC4Bfpsmm6cDm7TW89Jhrx03RNzaH+nr8IEuGAccrpT6Win1qVJq/zTZjXI4UKa1XpFGmz8C/hq5tv4G3JomuwuB0yPvzyOFfVe7e4209lvpvs/pht2U9lvt7aar30q0m85+K8l5Tku/1c5uWvutTq6tlPdd7ez+iDT1W+3sprzf6mSskvJ+q7/GSN2wm7I+qzPbqe63ktlNR7/Vxbnuj/utpIjglBpUknk7nNqYCpRSmcDLwI/aqckpQ2sd1lpPwijlByilJqbaplLqVGCr1npWqm0l4VCt9b7AycD1Sqkj0mDTiQmd+I/Weh+gEeP+mzaUUm7MDcGLabKXh3n6NBIYBGQopb6barta6yUYV+MPgHcxIbmhLjcS+gSl1G2Yc/10umxqrW/TWg+N2Lwh1fYiIuZtpEncasd/gNHAJIyIe3ea7DqBPIyb+c+BFyJP7tPFRaRJKE/gOuDHkWvrx0S8U9PAFZj/S7MwISuBVBjpj3uN/rbdmd1U91vJ7Kaj30q0izm+tPRbSY43Lf1WErtp67e6uKZT2nclsZuWfiuJ3ZT3W/0xVtlR7aa6z+rMdqr7rSR29yIN/VYnx9tf91tJEcEpNWykrTo+hPSE4vQrSikXpgN/Wmv9SrrtaxPi9QlwUhrMHQqcrpRaiwmZPEYp9VQa7KK13hx53Qq8ignhTDUbgY0JqvlLGAEqnZwMzNZal6XJ3nHAGq11udY6CLwCHJIOw1rrh7XW+2qtj8CErKTTM6JMKTUQIPLa5278OyJKqcuAU4FLtNb98YDgGfrYjb8TRmNE1HmR/msIMFspVZJqw1rrssiNkQ38l/T0XWD6r1ciruffYLxS+zxRejIi4bhnA8+nw14Cl2H6LDAifVrOtdZ6qdb6BK31fpiB6qq+ttHJvUZa+q3+us/pzG6q+61uHG9K+q0kdtPSbyU73nT0W52c57T0W11cWyntuzqxm/J+q5PvOOX9VpR2Y5W03W+leYzUqd103mt1ccwpvd9KsBt9aJ2W+63E4+3H+62kiOCUGmYAY5VSIyNeGRcCb/Rzm1JK5KnLw8ASrfU9abRbpCJVDpRSPoxIsDTVdrXWt2qth2itR2C+34+01in3flFKZSilsqLvMQn4Ul6RUGtdCmxQSu0WmXUssDjVdtuRbi+B9cBBSil/5Po+FhPvn3KUUgMir8MwN3zpPO43MDd9RF5fT6PtfkEpdRJwC3C61ropjXbHJnw8nfT0XQu01gO01iMi/ddGTBLV0lTbjt5YRziLNPRdEV4Djom0YRym6EFFmmwfByzVWm9Mk70om4EjI++PIU2idULfZQG/Bh7o4/13dq+R8n6rH+9zktpNdb/Vhd2U9lvJ7Kaj3+rieFPab3VxXb1GivutbVzTKeu7urCb0n6ri+841f1WZ2OVlPZb/TVG6sxuOu61urCd6n4rmd05aei3Ojve/rrfSo7eATKX74oTJu/KcoxKflsa7T6LcZ0LYi7sK9Nk9zBM2OB8YG5kOiUNdvcC5kTsLiRFVYC20YajSFOVOkwupXmRaVGar61JwMzIuX4NyEujbT9QCeSk+bu9A/NPaSHwJJFqMWmwOw0j6M0Djk2hnQ79BVAATMXc6E0F8tNk96zI+1agDHgvjce8EpN3L9p3paJaXDK7L0eurfnAm5iEvCm32275WlJTpS7Z8T4JLIgc7xvAwDTZdQNPRc71bOCYdJ1n4DHg2lRcy9s45sOAWZE+5GtgvzTZvRlz77McuAtQfWwz6b1GmvqtzmyntO/qwm5K+60u7Ka03+rMbrt1+rzf6uJ4U9pvdWE3Hf1Wp+eaFPZdXRxzSvutLuymut9KOlYhxf1WF3ZT3Wd1Zjcd91qd2U51v7XN8Sip6bc6O96U32/1ZFKRRgmCIAiCIAiCIAiCIAhCnyAhdYIgCIIgCIIgCIIgCEKfIoKTIAiCIAiCIAiCIAiC0KeI4CQIgiAIgiAIgiAIgiD0KSI4CYIgCIIgCIIgCIIgCH2KCE6CIAiCIAiCIAiCIAhCnyKCkyAIgiAIgiAIgiAIgtCniOAkCIIgCIIgCIIgCIIg9CkiOAmCIAiCIAiCIAiCIAh9yv8DipN1KB4mydsAAAAASUVORK5CYII=\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_5\n", + "total seqlets: 152\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_6\n", + "total seqlets: 104\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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u33abeI51dHTvy09/Cj/6kayn7J7EKhxWVcm5EGs1NSISBQIiQvZ8DIfjYlEsN1js0esVgbK0VNqqVfB//yehlYlC6rRp4lV3xhnxsM7h+C3HEtjn9ldErb0Stj4jVSgbPpZCAZ3V8rs0bvESinT2/XnjBpc/Kur00DYyyuDsyq6Xra3wwgsSpvrSSyISZWbGc5vFQu9ycuJhqrFE6R5PPDS1s1Pyp23eLCJxMBgf//KzW9jyh9FSUTMx95y/HM5YL+OSe9fKszQcqOCkgpOiKIqiKIqiDIkrroC77+4thPzlL3DRRWmuetayQTwHtjwF29+V2aLjhkgoKkJFJ3m+YsgcJyErLr+EqRhXPAwn2AStm6Btc3SymoQLZa7U1iY5cGJJuxctktC/xkYRA7xemdAXFkrLz5fm88WFp5jQ1Nkpn2tokIl/ba2IDIGArJ+TI+8n5p0ZN07yOOXn72DyrnwiaGyU7/PFF+GDDySfVnW1iBazZsE++0i+sDFjoLxcPOpKS7vn5kp8DIfl3IqFqYbDUjWxulqSzVdUiEDygx/I+fPYY/DnP8O778YTy7e2iqA5axYceKB4802dKrYLC8VjsaMjLqhaGxdTXS55v709nidszRrZxw8/hPc3jpKFA8UFFAOjos0PeKLNC4SAYLQFgBqgMtoStamqKjlwidgItG2B5lXUV2xgzaogmzdF2FzhYV1FLqs3j2Jj9Si21ZfQHvATjrgIR1xErAtDBMeJ4HLCuJwwBVmNjC6qYvKoSvaYUMWEMe1MGNvO8aN/BYEGsAluir4SOGOtPPcMwk1xgF6ZcRy4sHey9FSjgpMKToqiKIqiKIoyJIqKpOx5IsaI90Iq8xntEGuhZR20bsS2bqK+diG1Ve8Sbl5FVrCBYhd4HYMD0cTjUQ8n4wIcCcHLKJVcKImTQ4ArHGjYccbzCIZmcqijsKvVU0AQD2FcXc2V8MpNiALqEz5RRy5NOFiqFldz899LuOsuOcYxTxSXC849Fy6/XCrjxUSGrKyheT7FErOHQiJkfJJzOFkb9zADOR5ud3fvsoFup65OBJrNm0WvaGqSVlcn4mBDgwhGLS1xkSfmyRZ77jjxym0FBdKKi+X1vHmSZN/rleMf83a78Ub49rfjApDfP7whbrEw10QiERFQ582TcLMPPpB9bmiwGAM+XwSXEyESkd9OUZHBl2FwHIPLZQiHLZGIpbPDUltrMViMYwiHHToDDtZCfr6hxjVIwWm4KCuLlnJ8Bzb8B2regqaV0Ri5aE6onKmQtw/k7gW5e0JGsYTvefKj+ZR8XQm7jSGayDsioWyhZgjEkn5vg/pF0LwKZt8Oy34tIYM2LCFvkU7x2hp3riRIz58pIni4AzAiiruS/AgHLTjRJZSnExWcVHBSFEVRFEVRlCFx8MHiqdBz6rBkiSQGd7mSfy7VbG3eyivrX+F/q/7HS+teoq69DtszrCaKyxj2KJjKyXucxolTT+LQcYf2X0J81AhOkisraWiARx+V3Duvvy4ih98vwkEwKN4n++8vOWjGjhWPmFGjxKEjMzN5lbraWvF42bJFvGoqKsRba/Hi7iFWI0V9PaxdC+vXSx+3bZNKetu2ibdOR4fsW8yTzOORfXS5RMCJCW+hkHiMxbx9QqG4YNTeLp5kJSXitffBB/DEE7BggYhMkYjYOOAACZecPBkmTRJvo1GjRHxN9FyLHWNrux/vSETsNjbKabRli+zLnXfC6tXxvsX43//g1FPle0ibx2CgQbwE6xZAzdvQuAQ6a7GhDpoCJVQ2jaGqoYzKprFUtYwnYPMJRXyErJtQ2IXbFcZtQridTrymgbLsTYzKrWBUfiWjcreQ492OcWfA+U1RkXeA9KcUDka/2PAf+Og7EGyWwgOxELeyY6Uy3qhjINSeUB1vJ9XzSFCEKG9e9HUYtr8NdfNF7Kr/WLyrsCJ2+0qwMS9M/xhMzrSoyOWV951ow4pgFQlAOPr49gV990MFp/SjgpOiKIqiKIqy2xBqh+bV0TLatVJaO9gEgUZJpGvDEmJmiCaS9SWZ8EXzGtkeXjw2IpObcAeSE8XF0vVjOfgr19DW4cHa+KRs8mR46ikRO1JaUj1KbVstVz93NU+teorGzsZh2eaEvAl8Z+53+Pqcr+NN5mEwUIZrkhwjEhTvrfZt0F5JXXUri5Z6+XhpFhs2Z7CpMp+t2wupbsinrimH5jY/blcYlyuCAYyx8ZRVGMkfZQ2BgJsMX5D87BZK8hopL6xnbFk9f33quB59jojt1k2SN6utAjpqIFAnXh2BBjnnCEM4GE1+7AKicV6WhLLuEcm1Y1wykfbkgTcfvAW8t2I/7n/hIP732hS2VPrJ8EuurWnTJJnzqafClCniIRTLtRMTaoyJH/bE57HEzj2fu1wiFhkjucfuuqt3Eunf/U6S34PsRuYw6BCJtLWJyPXss5JLaO1aEacyMkTYOvJI2HdfEbti4Wx5ebIPwWD3xNWx/Yvte2LzemX9hgbYvl3ExZNPRrxxVt4O6++VRNsuv4gkNgQ506RSXPEhkhfNXx4VT4yMB7afUK1YPjSsjEPtW6H2AxG0PnP34A7ScPyW6hbAC3NFnEmk/EQ48sno+Zh690xrJVfUxx9LFc7Fiy1b19XgdG7BSz1+Vx3FOfVMGVfH+LLtlOZsI8vbJGKeK4TLCWMt0dA+EfpaAnkcPPpR/J623vYyyjAJeavShQpOKjgpiqIoiqIon3TeOFsS7NqwTBSNIxP9I5+C4oNkEgVyF9yGiSfRjSbM7jaRiz238Ucbe53wOeMCl5eVqzycdrqhslLCiWK4XHDllfCtb4l3jTEySd8ZQiHx9OiMtDJ/+xs8u+ZZnln9DOsb1hPpKZABbseNx/HgcfWIQbLxB2stwUiQYDhAhO7bcBkXjnGYPXo2Z00/i2MnH8vs8tmYwcRkDcckubMOPv4hVL0OreviQmHGKJh6mYgBOdPAkxsVBgNd37O1UF/v0NEBobAhFJRHl8vicsDttng8UFAQiYfPGZfkv3K8EOqEqpdh6/9g2wviieG4JewnZ08oOQRyp0vFMH+55KTxRpUQwtFH20PATEjWbhw5P21QBKuOGkJNW/FMPLkrjCzG6NHiERSrEpYKpkwRj6Zgj0jKWBW3nuFnw06gHra/j21aTf22GjaubZWE4bUZVDePoqJuDJu3l1NZX0JHMAOf34fXL6KdiR5PYxxwDEQiWCtuVpYI2DCtTQFsOEBORitjiqqYWLKR669ajHfDH8V+LOk+BiZ9CWb+VPKeWSteNsNFsHlwOYtgeH5L7dvg6X0kP1ui6JSzB5zwrpzbnkEkRBtEaJu1Du9NDnP33fDQQyKS+nxybuXkwGc/C4ccIl50Y8dKbraOjnhIKHQXD2Wb3YVGEA8/n088AysqYP58uPTSge/ScKKCkwpOiqIoiqIoShqwVsJ5WlvjrbOze6hNzxYru51Y2SwxZMfvlzCb0o8Px13/VjTkwi+TexuCk+ZB3gzpQKhVvJu6RCMn6nkSm/gjj0tugqW/GPiOubIIn9vCo4/CDTdISFY43D259R57wHHHwWmnSeWr8nKZFLW3d/fEiB2n2FQkVllr+3YRAV57DZ57Dt6o/B/ZX/oCwUiISNgSiU26Iobc1lkUbbyUktqzyPHmkpEhQldenkzgsrLiYVax5nJJnys71/JB+/18EPwHLVTFtRIA6+CEM9ny7W2UFPejdlgrk/Zgo3j65O3Z97pVr8v3YBwReRIfY7mkPLlQvxBeO0XeS/QmmXghHPJveR4JyWR5IAw2/4s7p3u1r5ypcPw70ZLtZuil2/vhN7+Bv/1NzqdY4ulQCL75TbjgAilVHw7Lbwrke/T5Bp/fKFZdLDapb22Fv/5VBIE1a+Q3Fg7L9k8+Gc4/H2bOFPHL5YonzE78jcZ+p7HnsdC6xMfY7zt2jrcs/if566+FQK38hmNV2KZdDtO/BVmTokJiiC7B1/Emz+/THzFPxUjU+2zlH2DZzRJalsj+vxbbwykyJeuOle941ap49b36enmM5cMCOZ7/uq9vwen6n8i5mVjtMRKJj7nt7XEPuHxfJSdPvYOjxv4Fj9OBYyJ4TJsIn2PPgCmXQMEs8BWJl1csv5vjjRYZSPj9D/C3FIkYzrrtMV5ZeWa3JOteL9x/v3jshULp8QhNJykVnIwxJwG/R/LJ/81ae3OP9030/VOANuDL1toF/X3WGFMI/BeYCGwAzrfW1kff+yFwCRAGvmWtfX5HfVTBSVEURVEURRkOrIVHHpEQiSVLJCSmoUEmO7Hwn9GjRWwpLJSJRWamTKYzMrpPUGMT1sS717EWCskEub1dtt3cDAcdBBk+Cx3V0LwSOqpoad7IttolNDVvhlATHuPG5XhwOQa/Jxu3Nwe3OwfjuHGiXhGxR5fjxsFIsl9jcIyDd9UdmHCShD6+UjgnPuFavlySHz/+uFRvy8iQfscEgxi5uTBxolRaiwkFjiMCQDAoItP69ZKnJzY1iZUYt1Zy5lRVyTEMhWTi/9Wvwne/CxMmdBcjjIkLEoNJpB0IxHP+WCsJxvNca6FhEdQthMbF4jHRUS0iQfZk8I8Bf6l4H/mK4cBvQE19742XFsPaD6KeP1EPoFji4XC7hKYF6qFzO3RUwpgzoWl5NLfOh9BeJeKEOxeKDoT8fSBzPNZfDt4C8TLy5IIrKypkOXEh68kpmM7qgR8IV5aUc4+Rtw+c8rF4qbizo8LlABiU0CVVtWpr4c03RfxZvlx+VzU1kncpM1PyJ40eLY/FxfIYS6wda7FE4bFzK9ba2+UcqqmRx61bpa1fLz1obBSbq1aJ/dWro+dkZYTmlgguBwoKHEaNgvIxITKzIrg9EXxeFz6Pg8djcDmGcMgQDBrCYUMgIL/fWJW4ujoJp/vthZdz8dw/yfFMrI54+CMw7mw51sYNbn8KjnUS5t4L484buL1B2l1dOZUTfvUC25on4XLJ9xQOi5h3333yXcZyk8V+f7nTR+FU9962LSsjuKmy11gJ8ST6ieGT2dlRgdtGJMSubr4kEK//CFo2yu/PlQHuLMieBP6xWE82eHIxviLx5PPkRcPv3BD1HiMSlPDSjspeon1tcyHF36jt1ffp02HFisEd4k8SKROcjDEuYBVwPFABfAh83lq7LGGdU4ArEcHpYOD31tqD+/usMeY3QJ219mZjzLVAgbX2B8aYGcB/gIOA0cBLwB7W9hdQqoKToiiKoiiKMjy0tXVP6hsree/3y3uJJOaaGWpoUOIk6jsvXs3v3//90Da0E1w+53LuPPXOPt9vbxcBbsMGacuXw8qVkiS5piZevj0mtkF8shhLaJ2TI4LClCkwY4Y8vvIKPPCAvNfWFj+ed98teXZaW+XzPt/wVVmLRCC88q94PvoaXV5hsRC8mT+HfX4sz8OBqDfEMGZMtxEwDp2hTrY0b2FT4yYeXf4o9y++n4aOejJNhHwH8h0ocEGBAxkGXEbu3nc9JjyPIHfpw1aee1wZ3FoUJNv0mD75SmD/X8HmRyXBcahNPJqMGwrnQOkRULC/TMx9xSJ2dYX1xcLooifqU9NhoELXI8CjO16tAx81lFBPASHcXS2Mq9tri8FDsGtJrCpgrBVQTwk1+OikpmodG4Pb2di4kQ0NG/jei9/rvxMhL3TmQCAHAllgHbCu6KMDJgxOGEwEXJ3ga+ZLB36WY6fPZWLBBCbkTWBMzmjc7RUiKFa9Bg1LJN9RYDs4GRK6mDMNMseBfxTWF62a5i0QTzhcCcKiCzOYYw0imEY649+Zyw/73QRTvyZJrgcqLA5QcPp440z2/9HHgHgfxkTjI4+El1+WdZqb47/tZEngB0LMyykUigtX+fn9f6azrZqVW95gTeUHrNn2AZu2L8QJNFLkgnI35DrgACX+AkozCynIKCTPX0SmNwfjeMQzat0/uguHwP0ffp1v3vtnQiHx3oqN32efDd/7niT7j1UNHK7QzfZ2ETh3tM+pIpWC01zgRmvtidHXPwSw1v4qYZ2/AK9Za/8Tfb0SOArxXkr62dg61tptxpjy6Oen99y+Meb56Dbe7a+fKjghA4gNihuuDcUfbSh+xwXi8dfyosdGYv90icdjY8St17jjj92eDyL2XVEURVGUTxzBoAgDa9fKxXVjo4RKtLWJB0rM2yTmgeByxS+0Y94uPfNVQPc72LGKT7GL6mAwLlSEgwFsqIPKLZ1kZnRSVNBJfk6ArMwQo0eHOPjAMBneqEcJEbm8MdFsyonGEunWEQMm9r4IDI17ns+a7YWsYzIbmMh2iqmijGBeMTmTS/AU5eIrzMKX78eT5cOb5SY7x5Cd6+B2GxwXOI7BcRlcbrlMi0Rs12M4DOFghKZGS2tzhEBrkFBrJ9WjTuY+8xFjm2BMtBW0gy8E0+phWq200rZ4hqb+sEBNJqwqgjWFsLoQOtxQ74etObAlFypy4YIl8I+GI6Vc2iCJYKingABegngI4iGCE30mLZcmMuhM+vnt65v5cHk2770n1dQ2bRIvlWBQQvgmTBDvqdJSSbJcXCyeZX5/d6ErFp4Y84RIfGxuFk+amAdMsH49Pz77Ztj+gZQ5tyEJs8nbGyZ8TjyNMidI4mt3ZvQkjYZBdbuWjrL0Zlj+6wEdL7N60Id4WLjE9wwFtSdTXS3eOJ0tTeS713LS4Zsoz6+gOGMDhf5tZLob8DmNeEyTVInzZuKYcHRq4AbHwUS9QWwkGvIZiRDBwdU4H2ND3exaXynmnOTCRSgSoqmzicaORho7G6lvr+foycf0ux8fb1tIri+XvIw8cn25uPsIP5z229Gsad7W53ay3D6KfLnkerPI8WaS7cnC5/JGQyEh9gsLRcK0BNtoCbbRHGiltqOBhs7mPrcLYC99GrAS/rrk51RGvLza0sn81lZqgx00hEI0BDvwhFsocMDbQ1B0J7x2gDx/IYX+YvL8hRRlljG5aA/23PgXTKipu+GMMjjqWVjyM8kF52REw+46JZyy7Gip3FZyGORMF++fcEc0vI/ovrui46ODjKeWeHJ44OGCpPtcf7JlyZJ4SN2WLbBpaxu1jZ34/eD3ucjwufD7XGRnG/JyHbKzDR63weUCt8vgchncbkM4bLuq/MV+xx0dhqYm+R8UC53817/i9jtDnTy58klueecWlm9fTmugNWlFS8c4eBwPxhjCkTDBSLDXOiB538qyyzhk7CHccsItTMib0C3nWzgsw+W//gXvvCMeczERLTdXqnvOmCGhx3vuKV6gZWWyjuPIerH9i92wcLlkvyIR2ceqKtnuypXilbd0Kbz0Ur+nXspIpeB0LnCStfbS6OsvAgdba7+ZsM7/gJuttW9FX78M/AARnJJ+1hjTYK3NT9hGvbW2wBhzB/Cetfa+6PK/A89aax/ur58jIThVtlRy1XNX4XP5pLl9VLVU0RxoJtOTSZYniyxvFpmeTDLdmfLoycTr9uJxJCg5EAnQGeqkPdhOW7Ctq7UGW2kNtNIebKcws5CCjAI6w510hjsh1Ma/gkluE2RPgTPWpHSf+9KW0pkq7NFH4Zxzei//8pfhkktETY7lUejLhR26X/gmxmU7jlw4+/3SMjLi7ryxUqhtbXS50cZaTHGPbatndYlEEqttxIiVWvV6YU37BzxdeRfF/hKKM4spyykhLyuDjAwozy1hTO4YxuSM6b/Ubw8iNkJ1azVbmrawpXkLHaEOIjZCQ0cDNa01bG/bjt+dybdn/oqmprjreawlJnuMxVQnHsvE/eiLxDueMRwHXLaVw7clCXTOnQ6npdE3dd6VsOqO3suPeh5GnzCspq64Al54If46dmzuuEP+MaWK8298lHnb3oO6qdCR37X8V79wc8Yhe7JH0R59Xrj1R8RGWFe/jqXVS2WcitISaGFt3VqC4SAVzRVkuDPwuTL48x0ZkLdJrtc7cyGQQ35mDtd+O4csbxZ+tx+vy0uGOwOX48JaSyAckHEw1ElroJXmQDMtgRaaA800dTbRGmxldPZoPC4PHaEOOkIdOB3FLH9vXEJPDdtatpGX5eEz06dEl8QmmrHJqXwZjnEk6ayFZP9LTXRyaoEcr/Q7dl1jcJiVdxItLTIubNsmvyNr49VwjIFZs7r/tmS7AxtTk31Omu06nyKR+Lji8YDXa8jOltLPg7mrmEif1xVvnovZ9lzPXsJxr0HeXr2XDwsW1t4NFY/Jy/YqaIqOGXv/CEqPFFMuv7TEzw2JhH4Hm+TObyQIbVth80MidkSrMoGRxKXlJ0bt2R7bGEgfEteNfsGhdqkoFVsebpf3HF+80pDLE08M281u4nnel70e60eFmw8/thx04lG9PnHOOZaHHx7495ns9Nnhfav7Tddn2wN+WjqyabXj6Dh6frf/wbH/w7GcH4m/kZ6JWPureuV2y29m9pkecpq6T5zTwXGel3k52HvCvXatVIzrxY4O4EAv0iIh8cIItdLaEuTIwwN4XEEy/SGKigw+n2XqFMsN11u6JqHlx/a9vW0v9+xorEMJr6OzrFv+Abfe0+emOvBRT0FXC+AlgkMYV9KWfKm0TNoooB6TUcu3/nwg9aEm6tvrCHfU4gRqKXFBngN50cdcR7yMRnkzyPHlkuHLw+POxG0cXI4Lt+PChTwPR8KEiRCKhAlHwoRshCMCS8igu6fRO8/7KHimE1ePrya3E8padm6EbPGKkJiIBRoy4DNbuhuMhTW2JomujBHzJBnoaZSYmyzG0XeM47XaioFtANh2C4zqo0+VWVC+AyelGM9MKecoegtOzvGv4ys7YsD9AWDRjbDkp90WhSwEkxyXeR1wTa3DKptNU2dT7xVSwNjcsew/an+ZN2SVUZpVSllmIWWdWyhuXUF5xzoK2jfi6azEGE88f5HjjVYUzIOMUgmrdfnjjgUxJ4ZwO3RWYzuqoW4hJuGcthZOq/Ky3jeFzU2baQm09NPTncfjeBiTO4bxeeP5yv5f4cW1L/LelvfY0LAhacGB4SLLk8U+pftwxIQj+NJ+X2Kf0n26vR8Oizi0dq2IQxUVIhhVV4vYXV8vN2tiglls7ufx0FWhMJYPLCNDwgXz8qCgQMKOY4L7r37VRwdTTF+C0xAvJ7tvO8myZG4xydYZyGeHYk9WNOZrwNcAxo8fv4PNDj8vv93Ag+f9N/rK4ve2k5/ZwMWfb+BXP2uRhG2hVmnhNrlIhLgLo7XIV+QGmwmmMHqHLXYIEpWL6I/a7QdXBr946lESHSENkNVSzSEf/QbHhnEAlzE4WLpSSEZdM40xGOS/gDGGgqrnya/eYZosAP7f6Y+wIXR2Vxdjquwbb3R3c451e9apo/DW9b6jESgs4+PnKvv859XzH9uvv7SEZ1dPRaZ/Dg4eXIR5420X++zryPVK7LrFRO+mRhXi7kkie1zym/ijY8AVVZpD0R/85y+EJ5/sfUouWQJ77z2gQzYk5r/zBk98+PfUGeiLpefw64d6L77tNrj66hTaDXvgzVPjd1diX5onF2rnJXjoJXwXM06Gmrre2yophKfOgbV/HZjtos/AiVEHyjl/kNYXNgJjy6GmOu4MGGtlJRK4nViphVhcQUIS0aiYM2+e5BDoyQEHQElJj4WRIEwdA7U1cT96E30sLYLXX5X1urwPXfHnxiUXFZ48cFy0TP8TTO59a+SHC6WlCs/yCwk+9bvoKxP9IRq+dbmfH33fH1vaNewlvoaE1xC/y2Y8YEzvfxAJc+pf37OYe2/fr1d/vn4TXHdFH50dNUquEHpSViaJGgZAVRXM3Xcde45eQY6/mVx/E7n+Jmbt28RF5/iiV+Kx8yS6Z44LTOzOapJ/hV2z5+gOxqoGRYLRO+7R1R4a4JU4ckd1tAvGumGcRx5zDXgd8EbfDwMBK63DQmUIKkKwOfpYH722WzEmm+mZvcv34iuS3Ak96e84v/CNXhf2fbHPJhdLO+MXvgYocUFBzb/Za9QSZpfPZu+SvdmzeE8y3FG/9oMOkqQyPSnw0/mTdlYFYWkAFnTCkk5oiEBNmG5TxudHwwnJNP9zakTsGQyLbhzw/iYSCHnYXDuOLXVj2FbyU2rdR1NXJ4e1slJyDoVCInJmZ8dLhXdrkXZsqJ1IxEIkjLURIpEI7S0hWpqDdLa24InUMGrUAvju+VA/BQLZ0ZCTbB5pz6H0/GIKM/PJ9uSQ48vF78rG5/jJ8Hjxedx4PQ6G2PWH/DnGwWKJ2AgWi41WXgqGInQEQnSGgnSE22gPtvLan3pfLJSVQeXlgz5kg8JcMzixqa9J8mAmyACHLHmNQ7cd0xXGF7smeustmazEro9iE/q9i8rw1Cb3HgkWlbF8Ue/licmPY9z71hh+V5sQtnMxeAC/L5exOWOZVDCJ9ZnFfPujAvL9+RRkFHBpYQ6Zdb09PVryvPz8wWOpD0NdGDaFYEMQmiL08nFygPAJR8ItfU8RMoDyaAOGZZyuaKzg2d+N67V8TdAh05tJoUdu+OZn5JPjyyHTnYnf4yfDnYETTTQcsRE6Qh1y4zjURnNnMw0dDdS311PXUUdboK1XtTyArXespzynvNfyPhnE/mYDe/S1nZ92/99ikeS75qeQ1e4nv62QvGAxmbaQzEgJXicbl9uF43ZikwnAYI2lzdVEi6mjxamjwVVFnWsbISeQxChcWpCFJzMu4GUbORdKp1zIuPK5FPrlWBf4C8jz5dH8TTd9+Q8Fl/+Od1b+kYaw/P+pi8DGIGwPy/abLTRGoDEMqxq3cfJ7E+C+jdJ/H/LPzXdk1xSsq2W4IMMrExqvL+o6Fx0oY49mfPSuq/wo3dbiPr8KMrt/x5tDMK8jAjSR58tjYv5ESrNKcYzDvqX7ctCYg5hVPotJBZO6zqUdfcftwXYWVy9mwbYFvL3pbWraaugIdbC5aTObGjdR0VRBRdOORT0HKHSFKXV1UOaCUheUumoY5ZZrgAwDHhM9LCYuqoWQa4DNQagMQ3WPtj0cgOblAGR6MinyF5Hny2N83nimF01nUsEkJuRNYFzeOHxuX799DEfCbGve1hUGubpuNWvq1lDfUU9jRyP1HfVsaNjAhoYN5PnyCIQDTCucxrTC+B3b4sxiTp12KsdOPpbSrNL4xgfwW4rYCB9XfsyL617k9Y2vE450F4yXVC/B9/NfwR33d1vuAqZG24k7/CZiOws2kEQAaYm2ZMPZdc27VEZyDalLIfWr36Pz9a/gc7WQ7dmOY0KEI14oORTP4XcDEXFj9GTJozEJYW4JIW5J9bQE0SlJMkCbUYY5u5JgOEhrsJU1dWtYVrOM+vZ6WoOtXT/GuvY66jvq+e+Vb1Cc5C5dba6HS/9yKgX+AhnoMwrI8maRn5HPpPxJzBw1kyxPFl6Xt5sL4YCIhMHvll2JzakSn1dupdvE3HERn5jHJudydXzkkSJq5fibGFe4meLcBopyGrnrjy0UF7SL6h6r1hIJYCNhwjY66U48xl0uOUTFJxOd18X2LYSLECZaPvaxp/PYtGIzBZnbyfY2kuWtJ9vbyNS9i8kbOxXHnYHxZOB4czBuP7j9GHemuKcad3Q/Enc81peou3+snHGoHRsVJW24E9vZiNt0iEjZWY1tWsXGSAYrgoaNQWiwLho8JWwKBFlZu5I1dWtYcVNj0gvdmhyHL/7xeKYWTqUks4S8jDzKssqYUjCFvUv37uYlZa2o8Mk8nHp6i8XueB167ih89b0H7s6CMt5+OD5K9uUFFfP0mDt3kLkZhqOcqo3ArV+El+6HMqAUuVLLdMEeJ0LBRMgsgMwS8BdJdQ93liTcdPvpOl+7VBKHqDsMkkXBio1IMEGAboHOZvjXWrjpV3LxMxUoidovBfKBXCA/B4rHQFYJeEpkEusrkrtRxhsvcxw7z2Ou/rHHcIckKO3cDsEaaK6BU98CfynWWqpbq1lZu5Lvv/h9NjZupL69nmAk2OfdIUk5m/zYGgwel4dcXy7j88bz48N/zEFjDqI8pxzHOPzxj+LV1ZNbbpGksN3orIOGxdC4BGo/kASQrZsSQhnC8WMdC+/15EkYRNHBULg/5O0rlXccd98XFwOhHJgNzELODQ8QAOqRrIQfAUl0z/BYWP3zJNsrPYJJJ7zQ/8VWMpfIHnkUQhbWJPcAZ4ILuKCNznCnXIw2bmbRtgX4WlZS2LKcSe0rKQrVkm3bySBIp3URBoy1eE0ET38/LSBkPFjjwe04mEjUbctXCKcuwQxGaBmO3zDw/I1f4LH5/2ZlEawshm2DrMw8GEpbYHotTN8Op6yGz37uJ/CTH8VFv67/8dHQrq7HaNvjMKhOInSVFsOqN+n6X9Tt0ETFxehYs2qtjz/8fQyvvmZYtSrqvu8Sz8gzzoSjj4bJkw2FhXLzJRZ2EOnxs+55+JMdcseJzr28EuaWkSFzsEQCoQDbWrZR215LU0cTjZ2NVLdWS66Uc35LfmNHr+02F2Txnxd/S1lWWVdYTGFGIaNzRuN1d/9HEIlICeiaGtmPtjYJjbIWbrxRvJFi3hSxRNIHnZn8ZleouIz17/RORhv7nxYIiJd0LAnxEUfI9nrSEmhhe9t2mjqbaO5sprGzkS1NW7omQOvq1+F1e/G6vEzMm8jEfGml2aXkenPJ9eWS482hLLsMj2uQZbhSyHOrnua2d2+hurWa6rbt1LTXE4ykxsOr0JdLqT+fUn8Bh46ayS9P/dvgK3Qpg2b19GJW21o25sHGfHhtArzfW3PbaS5eCFPqYEIjTGiAfW0JhRsHkYNod+DGG+Gng7+RsNPccIPYRoST5TXLWVi5kPUN66ltq6Who4FNjZtYVbeKiqaKfoXyg28azx5FezAudxx5GXkU+4uZXDiZWaNmsUfRHoOfG6aCXeA4f1pIZUidG0n8fSywBbnEvtBauzRhnVOBbxJPGn67tfag/j5rjLkFqE1IGl5orf2+MWZv4H7iScNfBqbtkknDK56EN86U58YdLyc69iyYe098PRuOlsNMLF8bc1tP+KEuvRmWdysA2DeuLPjcINwVh+nCnp99H/5zi3wz5UAhkAcUl8CoaZBbCjmlkFkIvnxJgOfJB08O8ZjgBGGpq5JHBIgKceEABBuiFT3qoKMRNv9TJs2ANS5w/FhcOJ9r6N3HSDDhjn+yiXNPl+4oSRLyfdhhWBWwjHbTbRLmOuEdJhdMpjSrtPdg22Wzx/LFP+12B7shDKuD0JnQjQjiPZDrwEkTj4TjX5PvJ9Qsk/BAvQgWoZa4eBFsEcHtpl9CZvQWtuOAK6F9+csJwkhM+DKIrB4CHEkg6M6OiirZ0UooVt6zQKQjbjNmP9whtW792TIjcUWFQ3f06v8LF8WPQ6L9xDhwl5+wK5MHNi8Uoc7xxatJuLPZo2Qmc8Yc2Ps4D+KcXrl9JfO29h4fMgPbmbP0anpdTmeMpvDMZeRl5PXYbixOw+n5CWHRjd2+44iVu1zJzsIxuePxerKhZXU0uWNUKJp2OYw/Bwpni2dSuCNq18hrx7dzFWQyyuDsHd/9behoYG3dWtbUreHUIy4hu7731UigpJCmDSsp8hft3EWHjcD292HTg7DpIeiskXMgEpD9HxRO1JtGxGdKDoOLlg5OcMoAzgIOB/zIKZxsHtQh5qgDXgReoOvLfmccHHoJZLg8eLrGOksEy/TsIt49+ut4Xb6oYBgdF10ecGVGE4YmesoZeP9SGReR8+q0rfBae3c35jDQZuG/o+D8r1sZBysehw3/gW3Py7YiIfktg3gQFs8VoS57ckIC0zJwZcfF/0ThtLMW2rfAqydJmfBErnDEFSgJEQzbKKeaUhrJo5E8msilkTwayKOWIlrIiQa8OIRxY7DRgJkIboLk0UgRddFPN5JLkzwvdFO+4lWKi+PDQiQSYXH1Yj7c+iEbG+QO6bKaZSyoXNC9YxaonwwbjoKqfaAjnwJ/EcUFXiZPDXDw4e2ceshkZpfPwtXjd3fDqzfw89d/1mtfHQv/70P41cuQnfxm/w55cg+47AyoSeJBlfHI32hfckmv5S+/DMccE9WmdoE5ADB81x6fFLu7OYlh+DVtNVS1VLG0ZikLti1gS9MWvC4vB445kP1H7c/Y3LGUZpVSkimpAXYlYU1JjrWWuvY6NjZuZGPDRjY2buS9ivd4Ye0L1HfUd623Z/GenDT1JGYUz2BCviTJHp83Hr9nkBXQlF0DHS+VAZIywSm68VOA3yGeYndba39hjPkGgLX2z0ZmGncAJyGemV+x1s7r67PR5UXAg8B4YBNwnrW2LvredcBXEe+9q621z+6ojyOaNDwShvYKKaUaaJRJQSyULtIZzRLZKRfrx94GtUlk5KJseP1H8rxLk4pOOGxMQInI5MTxwn8b4edpDuAsBn4f65srLhhkTYAzN8TXiwTjHkr9MYgSn7+ohTfCedhIMOrlIO41WcWzOHbiURwx9iD2GXUAjidXJmuONzo59yaEoERvYy7+GSz9OUEr4RKvt8Eb7RIukogx4kGwrg8vglRyZhY8nj8GWrdAQXRhCJj0eZjxTfHmyCiMlsiNxkh0iWyx/SW5p0T8BTw5tXfVi3oHQpHudksOg0P/JN4ivoK4XRuJnp9humbaA0ni9OS0bnbrw3DoMsPyjFi/ISMErqgjWEEHXDofPr9EkqQOhCYfPLon3DUHNuTLtiIGOjxgo90Y3wDt+X5qaO/6XJbLg8EStBGOKhrPNyfN4qRR03G7fHSFp8UEsZ7eTcYBG2FDSzV3r3mDv6x+jeZgBy7j0BkOEowKVgUO1E1J0un8feGURcQq2AyYRTcOPBxnsGI1pO5iJNAIq+6EFb+V33WoDejj3oIrU/IAubPjuQXCHSK2tm2B1g192xmgyAbA5sfg/cui4/cgxC5XppTPPuQ+KD4Iay0/evlH3P7B7bQFu5+0me5Mzp1xLvecdc+QhLofv/Jjbnvvtt7b9ch27z7jblzVr8J7l4hon1hZxVcMU78OEy+E7KnieefyR0WuQXB/kn5fDjTCZsbyPCcyn1l8xCzWM5FaivESYOLYEFOmOpSPdRg1xsXEKS7GjHfh95teZa+hd9nr1pYIG9eH2bw+zLaKCFsrwtz3WBYlpQP/vVhreea1Gn79G8P8d3IIBzw4jqG9rfs2YsmIjYFDD4VrroHjjov/HBo6Grj9nLHcul8rYQNtCaKkPwDZQbjncfGEGihbc+DSM+D1Cd2354qAJwzHrIfL3srllaLDWXzwZSxbCttrJdojPx8On3wQxxxUzowZUF4uy3JyZF8Sq/okyzEYC7Fbun0RGxvX44o6KHd0indTW4uLK088beA7E9toXwxm7NgZL8WdYRDhWYqiKLsEOl4qKSKlgtMngU9MlbpPsoocDnDLU+dSXb9KPBCCzSJyOB6KRx3GsZOO44Cxh+DKLBdBxJUR9VjxdglEXcIPwOMTukSHujC80gbzOqWka0/GumD91Kt4r+I9lm9fntIEfEW+HGYUTmJu+X6cNfUE5k6/gKC1bGkWd/lrX7qWiqYK6jvqCYQDhIbgbu4yLrwuL7m+XMpzyvnBoT9gdvlsxuaOlTtE86+BlbfJyu4swMiEfO4/pXJKjFArkVCIlhYIBF2ErZtw2CEcgXDYEA4bQmGDXflHXGtvx+WEcZmwPEab2xUi09tGhreTtggsi92Rd3x0JQscczp7H/XP+N2rUJt8912JbF09PKeiM5clN8HSm7q6WxfuW8CbnZlJ5alreG7Nczy07CGeXbNDnXlIHDb+MM6fcT6nTDuFKYVT6Ah18Namt3hixRM8sfIJtjZvJdy/Q+WQyHBncOi4Qzl3xrmcNPUkylpXEd78KGx7Edo2yqTfGLx5++AtPwbKj4esiVLC2OWDcGfCMU+k55gi73eEOuTcNE7cMyrUhjejEO9gwxaGe9yyEVhxGyy+IerV2N5jBSMiZ/Fn5LFwlohGoTZE2Ez0Uox6fmEkWfRzs5PbvHAH/Wyvgne+ANvfERFmqLj8MOFCyQXm9nPbe7dx3cvX0R7qvo+ZnkxuPu5mrjzoykFt/pFlj/DFx76YdHtXHHgFvz7u15j5V8Hav/fej2mXw/6/FrHOtZM1epMITg+8ez4/ee6/VFSIg2OsdPzpp8Nll4lYY62ELcUqmHmG6PQQSxQdiQyuPPDixSIcvf22iCiDIStLqsz8/vciQMVoC7bxtwV/42ev/4y69rpeYac+l488Xx6O048oZmU7zYHmXp93O27Om3EeNxx5A9OLp/P2prc544EzqGuXWE7HOPhdfrAOneFOpmTO5rCMbzC+4zSa6jKoqpJjHqscB/Hwupjw1OGqZkP2/azKvYsOVzUGNxFCREx718+t2JlK1R3NONUjMJGJJTNKNzqBUhTlk4YKTkqKUMFJBae0cN3L1/HsmmdZVrOsWyUqkBwuANmeDPK9meS4ffiSXWBbiGBpDXXSFOygIdhOIJJ8gj8qI4/ZJdP40bG3csiEI7uWr61by+3v386HWz9kXf06mjqbek3AQC70c3w5NHQ0JBWGMj2Z5PvymVY0jYPHHsz3D/k+RZlFgzkkskvWUttey6bGTczY91gyaht6rRMuLcFUVsaTA+6ISJiajVt4/81a1qwOsWGjmw2bM6ip89HSkUlmbha5+T6yc9wUFVuKiqCkWO5mu93gjnoJuF3xEpuJLRCQnLm1tbC91tBQb9nsvMyi2SdhsXgdN36XF7BYG8FtHG6dcQRfGjsdl3HRVaHG5YuKJdHb4YmCUzT3SHs4wP+teotfrXwDt3GiAaWW1nCQsLV4jcPGK1cwqiCe7K8j1ME/PvoH/1z0T5ZWL6U10IoxhrAN4+DgOA7TCqexZ9GeeFweVtauZOX2lQQiASJWUssbY/C6vEwrnMb5e5/PFQddQX5Gfr+H/a1Nb/Gz13/GW5veSnpOxXIVxSpNRmyEYCSY9PxycJiYP5EL9rmAG466oZvQM/uu2SzYJuE9si0RY13G4TvTDuPaCdPJDtZAe6WEUjpu8BREq1Al5DkzUcEvmjdqa0crP1iziAeqK+KyjLVdYYOX7vcl/nrWvTs4+Xru9DCOW20V8Oa5kqOppyDizoJpV8Ce10iOLMc3PJ430L/g1F4Fzx8k1Zns4AXkXjgZUDQHjn8TgH8v/jeXPXlZr/Mpw5XBU59/iqMnHT2gzS6qWsShdx/aazt+t5+bjrmJa+ZeAzXvwivH9T62o0+Gwx5Knry7PwboibqmcgrTvtM7C/7cuVIqeKTp6JA8QI8+Ks935t9tZqYITg8+2F3s6gx1cuWzV3L3R3cnFa0d4yQd/621fYrce5fszb1n3cvs0d2F1IiNsLByIc+sfoaHlz3Mx1UfD32H+sBgOG7ycV0i+fi88TqRURRFUZRPKSo4jZTg9Cm9+IrYCGvq1nDvwnu59d1bCYSHmKgiCVMLp3LXaXdxQPkBOxQHEgmGJYH2oqpFLNi2gOfXPs+S6iVd7x885mCOnXQss8pnMbNsJpMLJvfKyTEsDMPk/M474Wc/kwpDGRkyQQoE4Npr4ZJLYMIEWRYOizmXS1I3DdZbIBKR7QaD8W3VRdZz54d3ctf8u7DYbqVNfS4f+Rn5XDbrMvYbtd+Ot28jvL7xdf758T8JhAPdzpNsbzaZnky+/Zlvc+msSynO7D/ZcGVLJc+veZ6Hlj3EqxtepTPUGZ+kRQxE3Bg8ePAzp/wgzt7rLE7a43imFk/qdmd/MATDQd6teJcnVz7JYyseo6KpglA41FVxJsuTRWtQQmS9Li9ux81RE47i3BnncuLUExmdM7rf/fnr/L9y+we30xnqpDkQr8fic/lwO24uP/Byzt7zbNyuHRccbQm0cPdHd/Pg0gcJRUJdx8YxDn63n/Kccr53yPe49NSf4FQNIXGnC8nZVgIUATnEEwiFgVagFtgefUw2JEwpht+4xUOy5wR78ldh1v+Jt9JgRZFEBis4DbfYFMPlh8/FRZ/n1jzHqfefmjQhu+nlpZacZAnbDYZ7z7qXL+73RVmw+VF49+LuYXQg3k0H3BLNNTgIBig4BUNuvvin+3j8o8/hcsW9mzIzZTw75xwZb9xu8RQaLiKR7qW3k1FVBSecICWKB+vV1Bder/wb3rSp93uhSIjfv/d77vjgDipbKumI5iHLcGUwLm8cPzv6Z0zKn0RHqIO/LvgrDy97uOsGjs/lw8Hh/H3O57rDr2Na0bTeBpKwuXEzd354J48uf5SNjRsJR8JYa7vquvrcPvYo2oMpBeLVuapulZSPjkSIEMFlXFhryfJmMaNkBl+c+UW+sv9XyPQO8nxRFEVRFGW3RAUnFZxGnIiNsLp2NfO2zuPdind5c9ObLKpKUosXERsOH384R044kgPHHMis8lmDEpcGQygSwu3seMI+bAyD4HTRRXD//VLxsiVh3hhLCtvUJOKSf5jzM4ZC8dwpnaFOHl72MF947AvDawTI8+Xxn3P+w4lTT+zX4ysYhLVrYcUKaRUVsG0bVFVFqKjqYHttiLYWNzaYASaas9wxGGO6QkViZZ99PvH+ys9HvMFKJMfJ//1f8sqi1sLWrWJ32zbxBFu/pZkFqypZsaGBmu1AWwHuSDY+VyZeJwMXHowxkrPdJccyJ0fslZWJvbIyKC6WNnkyTJka5s1tz3Pti9eyuGbxsB/rz+75WX542A+ZM3qO5Asa6JjlB2YA+wAzEaEpiIhLDiI2xSpORnP+d73nBRqBpcAiYBnQDDw8DdrX9xZ29rwGZv5s54SmGIMRnNqr4IWDJQfUcIpNMXrkjvrbgr9x2VOXDauJnx75U64/6vr4gnAnPLs/tKyTMNwYjg+Oe10ShHtSU0q3urWazds6efFFeOZpWLUKaraDnwIynGxmzpRKanvsAVOmiHBeXg4FBfFwr0gk3oCu35IxUNVUS2NbG/X1cgpvroANG+DH383tneA/yqJFEspXXy/j23ASKyvfF9ZaXt3wKte9fB2LqhfRHmzHGIPP5ePsPc/mlQ2v0NjZSFuwrasa7A8P+yH/78D/R7Z36N+RtZaVtSt5dvWzPLTsIeZvm5/0ppBjHLI8WRw3+TjO3utsTphyQvfS0YqiKIqiKFFUcPqkhNR9yojYCKtqV/FexXssq1nGCVNOYFb5LAr9hSPdtYEzAqKiBdYXHci7v/+A116DpUtF/KitFY+nQw6RCdv4aIRDcTEUFsrELSMjXiI61mITo0hEPJliz5uboa5OWnW1CDrXX9+7P/9d8l+uf+161tStwWC6vGdcxsWY3DHsX7Z/153wxo5G5m2dR117Xbf1DIYDyg/gtyf+lsPGH5Z0vyMReOkl+O9/JcfKunXxonvhMMyYAfvsI23aNBGNioriiXE9HtnXWLqPWKnrlhbxFqurk9LaGzfKRHTZMnjtNbFdVwdPPQVvvim216+PlwR3u0UcmjxZjnlZGYweLY9FReKx4XLJ+jGRKxiUSW5NjWjDW7fKabRunYhob70ln0/knc3vcM3z1zBv6zwstssbJuahMKlgEjneeM332rZaNjTGvRRAJpFux83JU0/mthNvY1LBpEGceBZq3oIVv4Otz0j+tVAzvfNGDQJ3tuSeypokxRV6et6MPUsSbQ9GbBpEwYEuegpOkTA8f6CE9qVCbOrD7pMrn+SsB87q5a0UC9VMRigSSuoZ9ZfT/sLXZn+t9wc6tsOCb8PmR3rnx5p4kYh7GeXiZTYc4lMkSG1TBaP+sAdel7ebx5a1lnxfCffuv4ENG+JhvDU18tjQIK2pSXIyxQSmmEdiLNF1OHsTNZ/fA8dK6K5BfuvWhJlaNIkVVy7r1a1ly+Dgg7uL9sPNQC+xPtzyIT959Se8sfENOsOdXd9ntjebHG8ONx51IxfvdzE+9yBDSAdAe7AdZ/QYfNvre71ny8owu9jNK0VRFEVRdj1UcFLBSUkVu5gXW0+hqK5OhI1YWFw4nDBJC8cFptgkLuZJkNgyM0U4KSyUpLh9hZ81djRy78f3css7t9DQ0UBroBW348btuLnkgEvY3r6dx1c8TmeoE2MMGe4MphRM4fuHfp/zZpzX52TKWvjjHyWMsK2t+wTx2GPhRz+Cww6TcBiXK7lH0mBpa5NjtmkT/OQn8Nxzcmxao0UkCwrg61+Hr341HsII4lU2lETH1so2OjtFxMrsJ1IlGA7y5Mon+c07v2Fx1WJCkRDBSJBMTyZzx87lCzO/wM1v3UxFUwWtwVYy3Blg4fgpx/Odud/hiAlHDK76mbWw5X8w/1sS7hZqY6dEpsFw6lLImzG4z/TlxdQfPQWnRTfC8lt2LkH4UOwCa+rWcNQ9R1HVUkUoKnb53X6+Pvvr3HDUDd3WvWv+Xdz42o1deZsMhryMPF750iscUH5A/7Zr58Gin0D1a2C8UbEvKlxlTYCyY6D8RCg4ADJKwZ0DkXboykeWeJxtfFks4XjndmjdCJUvYatepXzhcqpae4+Vfref5VcsZ0L+hP772w/3LryXbz77zW4hvjEu3OdC/n3Ov7stq66GmTMHN3RPmiQitjEypq5evWNBaTCXWG1t8OjLG/nto6/x0fJG/E37UBKeRbg1j2BQjnVsPB49GiZOlBsLe+0lwtn48f070PbLJzx/pKIoiqIoI4sKTio4KUrasNby2obXuOWdW3hl/StdibMNpktUOm/GeVwz9xr2H7X/Drf3r3/BN74Rz/sS4/vfhxtu6F+c2RlWrIA5c+IiU4yDD4ZXX5V5WKpsD5RVtav4wwd/4J6F92Ct7coZBeId4Xf7uergq7hs9mVDC4dp3QTvfknEiXBr8nWMA/n7QelRMOZUKNhPchQ5XroqKEY6oWmVCFcJlQl3yAWd0e0Mgp0VnBqWSN6mXtXxkpCzB4z7LEy4AHKmSY6pcCfUfwQb7octT0n+p4HYTaCmtYYj7zmSdfXruvL3ZLoz+cdZ/+D8vc8H4PUNr3Pyv0/uEpvcjptRWaN466tvDU68CXdC1WtQ+QJsewGaVoLLG61CGZbjYMOybxnlkDWOiCuf1kA27YEsPK4Amd4WfK5W2de2Cgg2yrZd/miVQPhO7qXc/v7tXSJajGxvNneecidf2u9LA+9zDz730Od4cNmDvZbneHN46LyHOHHqifHdDcPhh8O8eSIq98fJJ8PXvgZHHilCcGz9WGjxO+/AP/4hCcKThc/1d4llLcyfD/feC08/LR6kfn+8wt5AMEYE9lBIhO6DDoKLL4YLL9xx7qpeG+qvo4qiKIqiKP2ggpMKTooyImxt3sqfPvwTt713G36Pnx8f/mO+vP+X+8ypkoxHHoEvfrF3Qt8rroBbb41W20tBGq633oLjj497L8X47Gclh1bGTlaOH07ag+08vOxhbn7rZlbUruCoCUfxvUO/xwlTThh45cOe1M6Timahlt5JvAFKj4R9fgLFcyXszHikelx/hAPw30GEBZ2xDrIHEfYHQwipc+DC6P7ZCDx7gITS9efF5SuGA++E0aeJ4OZKcjKEWmXbq+6Ahd9Pvp1+quM1dzZz4n0nsrByYZeolOnJ5O2vvk2eL4/9/7I/TZ1N0h2XhFS+8eU3KMkqGcA+90M4IOGNbRXQuhnaNtNSXcEb72TzxoJJvLhwLks3TSdiHVxOCGsdgmE3Zfk1HLrnPI6fs5AjDqxmz32zxFMqcyxkjmV+W4gj7z2qmyga43N7f44Hzn1gyF0uvaWUmraaXsuzPFnU/6C+WzjiTTfBr37VW8BO5Igj4A9/kDDZHXlMNjdL+N/VV8MTT3R/L9klVn09/O53cNdd8tlYgYfhIjtbtjsoVHBSFEVRFGUnUMFJBSdFGVFiY82gQrkSePBBCW2rqJC7/7EJ2n77wQ9+AGecIa+DQfE68g7SKSaRcDju1fTYY/C978mkMHESd+yx8MMfiqdEW5vkkhqOJO0x27m5Q9/GsCTC3/ocvHlucq+m3L3g4L+JJ9NQEnkPxgNp8ldgzh+GJ2H4QNjwAHxwaVQs6oOxZ8Pcf0iibdcAxLNQKzzYh2rRj+AEkpz/3AfP5ZUNr9AWFIWk2F9MljeLzU2bidgIfrefmWUzefGLL5Ljy+l3e4OlpgZ++1u44w7xmGlp6T8RNsjvz1r5bd50kxQyMEbGgFG3jqK6rXcVxJLMEqq/N4TqiMCGhg3sdededIQ6er13wd4X8J9z/9P1urpaQtH6q0Z3/fXiPTnYanktLfDAA+KNGRufEi+x2trg178WkTwS6S1kxygtFS/KQw+VfHx5eSJuu1wy9rW3Szjfq6/C++/DkiW9BStbtmuFeiuKoiiKsnujgpMKToqyW7BgATz6qCTzXrQIAgGZjAWDktdkr72kTZ4s6bVKS+OJw2MJxmNJw2PJu5uaxEOhulrmaBs3wvLl0hYvlvVefhnuuQfefRc2b45Pqo2B/feXROX77ScVtoqLJcdTbm58vVgD+YzLJbabm6GxUXJtVVbCRx9JMuMHhu7ssfO0rIOnZyYXmyZcIGKT4x9kzE4C/QpOhl6eRbN+C1O/lnrRyVp4egY0reh7nQmfl/13DzKWcjDV8XoQjoS59KlLeWjpQ7QGW3GMg4NDyIbI9GRy1MSjePT8R4c1oXRzswit//xnPL/YUMjKgrFj4U9/gqOPhmuev4Y/vP+HXmF1Ge4MVlyxYkh5nPrK35TjzeHB8x7kpKkndS37+tfldxzoXZQNjwf+8x848cSh54FrbYWFC+GUU2Rcif3mV66U7VZXJxe75s6F735XBOycHBGWsrP7zpcXsxUOy7i2fLns19/+JstVcFIURVEUJZ2o4KSCk6LslmzfLrmWVq6UeU5lJWzbJp4Z27fHK1wFg3GRKSYUxcSnWKLx/HwRp0pLpRx7eblMAnvmaWpvl5LuK1aIOLRhg8ztampEOGpsjHuCeDwyIYwlZLdW8q0EgzLpDQbFMyo3V+wXF4v9Rx5J/7EEpDrbc3OgcZGElyUy9Wsw67bBiy096U9w8uTF8/8ksu9PYa/vSl4h1064r/Uk2AyeqFdQzdvw6ol9ezeN/xx85u6h7f9OCE4g3kHXvXIdv3//97QF2zAY/B4/5804j7+f8XdcTj/KxCBZvFgEk5qagecS2hF+v3j4zNs6j6Pu6R1WtzN5nPrK35TpyaThBw1d4XQbNogY3Zd4dv/9cOaZO5+XraND8kMdfbT8vp9+Gj73Odn/npdchx4Kd94JU6fKMRqqhgsy5lgrHmk33LDj9RVFURRFUYaLvgSnFGQ9URRFSR/FxVKh7rDD0mfT7xdvpv3263+99nZpsUqA4XDcuykmQOXk7Nwkc9jZ+j9oWdNbbMrda/Bi06BzKQHHvw1vnAHt27on7V58A6z5M+xzA0z6gvTPM8TwsXAAbFA8uRb/FA5/OGrjZ32LTXl7w2f+vvNi2xAxxvDLY39JWVYZVz9/NRbLNw/8Jjcfd/OQw1R7Yi38/e9w1VX95zcaCjGvntnls8n0ZPYSnFoCLTy7+tkhCU6vbng16fLT9zi9W+6mH/yg7yThV14Jp58+PEUAMjLggAMkdG7RIjj//N7H03Ek3PCqq4av8EDMK+t73xue7SmKoiiKouwsKjgpiqKkCL9/ePI6pZW1/5Ak4T054BZwBpklfbBiE0D+3nDqMvjo+7D2LoiEJCE5iAj14TdgwTUw9kwoORxK5kLudBGgIiFJ4G0cwERFs6hLm9sPnbVQ9xHUvAlbn4GGRXG7Leug+o3kfTJuOOIxqbg2kowaxVVVVVzVteA30oYpjOn668U7ZrjFpkSMMVy070Xc8cEdvcLqXtnwyqC3t7FhI82B3hmyc7w5XLzfxV2v29okoXey5NyTJ0sS8cHmbOqPrCy46CLYd9/kx/OvfxWvp1RUuRzpypmKoiiKoigxVHBSFEVR4lS+2HuZKwNGHZs+VyyXD+b8Hva6BpbcBBv+LaJPKCoshNtg43+kAWAgezLk7wPubOmvcUO4AyKd0LYZ6j9OLqTFWHdv8kp8AHteAxnlUSFrBOkrJ88w5Or53e8GLja53TBzpnj4ZWVJiOiWLZLfbPv2HX/+opkX8beP/tYr51JTZxObGjcxPm/8gPv9+sbXcZvelzJhG+bYycd2vX7mGSkkkCxE8P/+b+eKDPTFc89JmFtPzjlHxKbhFLgURVEURVF2RVRwUhRFUQQbETGnJ75S8R4avjRBAyNrAhz8V0kavu052HA/bHsBjAuw0fA3K61lrbSBEKsuF+6ArImybPMjEmbXE1cG7HMdeIaYRfoTwLPPwo9+1H/lNpCcRDfeKBXUOjriYaGx5PsZGZJ8/89/hj/8QfKnJWN2+Wz8bn8vwcntuHl9w+t8cb8vDrjvz6x+hpZgb1XntD1Ow5uQ6+sf/+heZTLGfvvBCSdIrrXh5s47kwtOP/6xik2KoiiKonw6UMFJURRFEYwjnkE9Qp0INYMzhBl5Rtkgw+r68CDy5MD486RFglJFrmEx1C+E7e9B43II1knfjUu2Y4iWBgxLMw5kTYKC/aHoYCiYCfn7QkYpBBqgeXVy2xO/1He/dgOqqiTHUH9i0+zZUq1u/Ph4niBfHwXxRo+Ga6+VfEm33y5heqEep5Mxhgv3vZA7PriDcIJXWUughWdWPzMowemV9b3D8HK8OXx5vy93vW5rg1f6iNa7/noRylLBunXJl++7b2rsKYqiKIqi7Gqo4KQoiqLEyd8X6j/qvixQD82r5L3BcHYKyqM7HulH/r7wmWt6hJNFa92XFsPa9yXnlCuh9RUSV/WKrBsJ9HjDwD4/3q29m66+uv9KdFddBb/85eDyAsXW/da34KSTJBn3li3d17lo34v4+0d/7+Xl1FcC8GRsatyUNH9Tz3C6d9+VkLme1el8PulfqiJF+/Ka6uzUPEuKoiiKonw6UMFJURRFiTPlEknY3TO0bslN8Jm7wb0LxQL1lbuoervkdBooFU9AqKn38pLDwJs3tL59AvjgA0mk3Vfltn/8A849d+jiSFYW7LMPLF4MhxzS/b05o+fgSeI1t71tO1c9exW5vtwdbn9R1SLCkd55t06YfEK3cLply5KLaiec0Pe+DwfHHy+eYZEeBR8ff1xyOLnSHaKqKIqiKIqSZlRwUhRFUeJM+Dx8fB30nMdvehAmXADlJ4J7N3PP2PZC8uVjTgfXIPf10VFDq86XZiIR+MpX+g6l+/Wv4bzzdj7XkMcDeXnw5pvdlxtjmJA/gfrK+m7LwzbM7R/cvlM2Z5XP6vZ6wYLkgtM550jfUsXll8ODD/ZOxP6Tn4jXV05O6mwriqIoiqLsCuy+iSkURVGUweMrhLn/TC60vP052PZ8NFn3MBMaQHm0VBAJQmdN8vfGnQXOIO/LfALEJoDXX4dNm5K/d9ZZcMUVw5fY2nGSCzvfOuhbw2OgB9+e++1urxcuTL7erFnJlw8Xc+bAGWeA3999+bp1cPbZ0Nra2/tJURRFURRld0IFJ0VRFKU7Y8+AKV8FVw/FIRKEN8+BxT8V0SnckfzzgyESglA7rLt357c1FNo2S/6mnviKIXNc+vuTJv78ZxE8epKZCX/96/BXUUuWz+ji/S7GYIbVzticsWR7u+fc6it59+RBRF0OBWMkLHHSJMkhlchLL4kgtWFD8kp2QyUY7O1RpSiKoiiKMlKo4KQoiqL0ZvbtMOMHSTydLCy/BZ6cDGvvFtEp0Chi1ECJhOUz4U7Y+jQ8ux/Mu3xYuz9gWtYl92IqOlD6txvS1gZPPSVF/Hpyww3pS2jtOA4zy2YO6zYvOeCSbq+thaYk6bmKitKTQykjA956Cw49tPdxXbEC9tgDvvlN2LhR+hnombd+gDQ3S3jkP/8JM2bsfL8VRVEURVGGA83hpCiKovTGGNj3J5A9BT78uogvNkFU6qiGeVfAR9+F4s9A2TEw+lTImxH1fEqiZrgyoXW9hOVVvgjVb0GwIV17lJyWdUmq0yFJxx1v7+W7AY89llxsyc6GK6/sHQKWSr518Le45MlLdrziAPnuod/t9joUkpC+nqFr+fniDZSRxLltuCkoEI+mn/8cbr5Z7IajOdLCYbj3XmlHHCHt2GMl3M/tlnUdR74vY2T9SESENL8f1q+HN96Q9uyzUFub+v1RFEVRFEUZKCo4KYqiKH0z6UIYdSws+DZUPC6eTDYUfz/cDlWvSlv0E3B8kLcXuLOlop1xJPwu1AZNKyHUu4z9iNK0UvahJzl7gjuNyksaefzx5GFcZ58tAk06+fJ+X+bSJy/FJhMoB8mYnDG9wuligk1PwcntTu7hlSocR7zHLr4Yrr1WqgNa2z2ZeUw4uukmeT1hAuy/P+TmirjkdosXU3u7hOJ99FHyZOiKoiiKoii7Cio4KYqiKP3jL4ND7xdxZuUfYH0031IoiWoR6YT6hYPbviuL3mXx0kRLHwl+8nbfuKSPPkq+/Ior0l85zXEc9i3bl0VVi7otNxhyfblJPxOxEZoDvYXLnuF0ILmjwklOrWBQPIbSzcSJ8MADkrD9vvvg73+HbdtEfOrokRJt40ZpA8VxxEst3aKhoiiKoihKXxibzlt8I8icOXPsvHnzRrobiqIon3zCnVDxBGx+VDybgk3geCSUzu4gl5NxgytDZtiOC4oPhbFnwoQLwDvIGvX9KQYD/d/26smw7bney09dOjTR6f5BqhgXDuJ/8DDsbygkuYSCPb4mj0eSiCdL7p1qXt/wOif9+yQ6QnHFxeN4uOv0uyjOLO61/qvrX+WP8/7YbX2f46Pxh4343L5u61or4Wg9D09BgQg9vu6rjwgrVsDLL8Mrr8B770FNjYT6OY6IZYGAeGhFIrLM44l/T7Hvcd994Zhj4PDDJSRvV9gvRVEURVE+PRhj5ltr5/Rcrh5OiqIoyuBw+WDC+dIAWjdD7QfQuhGaV0PzSsnxFEskbtzgLYCcaZA7HbImQOEsyNljZNxMEkmWvwlEQNsNWbNGxIiegtP06RKqNRKC0xETjiDLk9VdQHL78DgeTtvjtF7r37/4/m7rApw+/fReYhPI6ZWfD/X13ZfX10s42q4gzOy5p7QrrpDXLS1QUQFbtsDWrSJABYMiOHk8UkFw9GgYM0ZaWZkIUYqiKIqiKLsaKjgpiqIoO0fWOGmfRGykjzeGOIPPKIOOqgGunH6VYPXq5OLEvvumvStdGGP4/D6f50/z/kTYSvxbS6CFZ9c8y0UzL+q1/ivrX+n2Osebw8X7X9zn9qdMgWQOzuvWSY6kXY3s7LgIpSiKoiiK8klGBSdFURTl00tfleh2FBrYF2dXDr0vaaCtLXn03Zgx6a1O15OLZl7EPR/fQ0sgnhfs5fUv91qvoqmCxo7GbsvCkTDHTz6+z20fcEBywWnePJg5U72DFEVRFEVRUoVeZimKoiifXpw+YqqCu1g1vWEiEEguOHm9Iyu8HDzmYHyu7t9FQ0cDW5q2dFv2+obXcbu63ys7edrJScPpYuy/f3Ix7aGHklfrUxRFURRFUYaHnbq8NMYUGmNeNMasjj4W9LHeScaYlcaYNcaYawfyeWPMD6PrrzTGnBhdlmmMedoYs8IYs9QYc/PO9F9RFEX5lJPROyk1AE2r0tuPNOHxJE+bFQpJjqCRIhZW5zKurmUex8PrG1/vtt4za57p5gWV483h4v36DqcD2Hvv5LmpXnlFvZsURVEURVFSyc5eal0LvGytnQa8HH3dDWOMC7gTOBmYAXzeGDOjv89H378A2Bs4CfhjdDsAt1pr9wQOAA41xpy8k/ugKIqifFrJnQEmiRrRuCSe9Hw3IiMjueC0fbsk0R5JLpp5EX5P3BWpOdDMs2ue7bbOK+u6528KRUKcMOWEfrc7d64Iaj0JheCJJ5K/pyiKoiiKouw8Oys4nQncG31+L3BWknUOAtZYa9dZawPAA9HP9ff5M4EHrLWd1tr1wBrgIGttm7X2VYDothYAY3dyHxRFUZRPKzlTwJUk3qplHYTa0t+fFDNhQvKQuiVLIBxOf38SSRZW9/K6eB6niqYKGjoaur1/0tST+g2nAwkXPOWU5O/97GcSZqgoiqIoiqIMPzsrOJVZa7cBRB9Lk6wzBtic8Loiuqy/z/f3GQCMMfnA6YhnlKIoiqIMnuzJyZc3LoWE8K7dhb32gvb23suXLoXMzPT3JxFjDBfsc0G3sLq69jq2Nm8FeudvyvHm8OX9vzygbX/pS5CT03v5qlXw8MOpEZ1GMkRRURRFURRlV2CHgpMx5iVjzJIk7cwdfTa2iSTLktxfHfhnjDFu4D/A7dbadX1uxJivGWPmGWPm1dTUDKiziqIoyqeI7EkQTuLJ1LgUbIpjrUaNkvi2gbb+GOA2MvyGssi2Xh9vbYWNG1O0n4Pgon27h9V5XV5e3yB5nJ5b81y3/E0DCaeLccIJfYfO/fCHqRGcOjqGf5uKoiiKoiifJHYoOFlrj7PW7pOkPQFUGWPKAaKP1Uk2UQGMS3g9Ftgafd7X5/v7DMBdwGpr7e920Pe7rLVzrLVzSkpKdrSriqIoyqcNTy64MpK/V/liam1XVaV2+32wb2Rh0uV/+Qu0jXAU4cFjD8br8na9Tszj9PL67g7NJ009iQx3H99dD3w+uOCC5MnDt26Fb3xDRLfhorUVbtayJoqiKIqifMrZ2ZC6J4FYeZiLgSeSrPMhMM0YM8kY40WSgT+5g88/CVxgjPEZYyYB04APAIwxNwF5wNU72XdFURRFgcLZyZdvfgyCzentSxo4mWeThs/dd9/IV21zjMMFe3cPq3tp3UtsadpCXXtd17LBhNPF+MUvwO1O/t6//w133z08olN7u1TAu+mmnd+WoiiKoijKJ5mdvbS8GTjeGLMaOD76GmPMaGPMMwDW2hDwTeB5YDnwoLV2aX+fj77/ILAMeA64wlobNsaMBa5Dqt0tMMYsNMZcupP7oCiKonyaGXdO8sThW5/eLfM4XcADSROEV1bC00+PfBLtL8z8Qrewurr2Oh5f8Xg3z6fBhNPFKC+Hyy+XSn3JuPpquPfenROdWlvhxRfh/POTJ2dXFEVRFEX5NGHsp+SKaM6cOXbevHkj3Q1FURSlL0aNGpkws72L4CftyXM5HfgnmPJVcLy939tZdpSXKYUcfZTltdd6Ly8vh9WrISsr7V3qImIjlNxS0uXRlOPNYb+y/Xhr81td65y151k89rnHBr3thgYYNw5aWvpe52tfg9tukzA81yD0xtZW+dxPfhJf9im5xFIURVEU5VOOMWa+tXZOz+Uj7DyvKIqiKFFGKKcRS2vB3YfCsuw3EEniDjQclJWlZrsDsHv55cmrtm3bBj//+fDmMxosjnH43N6f6wqraw40M3/b/K73c7w5fHm/Lw9p2/n58Ktf9S+o3XUXHHywhMW1tu642lxLC8ybJ4nJE8UmRVEURVGUTzsqOCmKoihK+UnJl7euh6qXIRwcXnuhVolhszb9rbKS00/vO7TsN7+Bt96SXETDxWAFrC/M/AKZnniiqfZQvDOhSIgTp5445L5ccQUccYR4MPXFkiUiIB11FPzxj7BmDXR2irjU3CzPN2+WvE9nngkHHgjvvDPkLimKoiiKouyWqOCkKIqiKBMvAnd28vc+/H9ghzmxUaBxeLc3SDIy4M47k3v6WAuf/SwsXz48olNrq+Q0GgyfGfsZ3E7yDN8nTDlhwNXpkmEMPPCAhA/uKEn6vHlw5ZUwbRqUlMC++8J++0n05/jxcMkl4gmlKIqiKIqi9EYFJ0VRFEUpPx68Bcnfa6uABd+FUD+JfwZDqA3e/tzwbGsnOPdc2Hvv5Kmk2tvh8MPhqaeGHl4XCEBdHZxyCjzzzOA+2zOsLsZQqtMlIzcXXn0V8vIGXpmvuRk2bID16yUXlKIoiqIoitI/KjgpiqIouwYjmNMI48DeP+o7l9OaP0PlKxIKtzOEWmH5rVDz1o7XTTHGSEhYX6F1bW3wuc/BVVeJ6NSWJKd6MiIRWf/dd2GvveCNN4bWv55hdQDBSJCTpvYR/jhIJk6E+fPFU6m/8Lqh4k7uoKUoiqIoivKpQQUnRVEUZddgBHMaATDpYqCfynFvnStCUWiAyktPQi2w+k+w+IahfT4F7L03/PSnkJnZ9zp//zuMHg033SSePc3NvcWnUEje6+yUELPjjpP8R9XVQ+/b3HFze4XVnTjlxJ0Kp+vJpEnw8ccwd27/x2Cw+P2w557Dtz1FURRFUZRPIio4KYqiKAqA2w/TrgCnD3eXSBBePx2qX4fgIMPrQq2w6k/w0fd2vp/DzHe/Kzmb+hNcmpqkultRERx6KFxzDdxzDzz2GPz3v3DrrXDhhZIX6fjj4b33dr5fsbA6ExUBhyucrie5ufDSS3D55eLt5fEMfVuOI9s491z44IPh66OiKIqiKMonEWOtHek+pIU5c+bYefPmjXQ3FEVRlF2Zju3w5GQINfe/3uSvwOzfiTjl6iceK9QKwUZ492KofKn7exfuOv9/QyE44wx47bXhrU6XyFAuN97e9DZH3XMUIRsiw51B3ffr8Hv8w9+5KJs3w3XXwUMPQTAI4fDAPmeMCE3HHAO33CKhhIqiKIqiKJ8WjDHzrbVzei5XDydFURRFiZFRDAf8H7j6yOUUY90/RJhaeTu0bpIwu0AjBJog0ADhDmhYCot/Ck9O6S027WK43fD443DBBcMbWrazzB03tyuP0wmTT0ip2AQwbhz885+wZAlccYVUp/N6xQsqMSeT2w05OfLeuHHw1a/CO+/A//6nYpOiKIqiKEoM9XBSFEVRlERsBF44BOrmgw0N7DNZkyBvBrgyxKupfgF07CCB0S7k4ZTI/ffDZZeJp9NwXSJkZg692t1Fj1zE/Uvu59HzH+Wze312eDo0CBoa4M03YeVKaGmRpOjZ2TB5MhxxBJSWpr1LiqIoiqIouxR9eThpDRVFURRFScQ4cPjD8L8ZOw6ti9G6XtpuwIUXwuzZcP75sHbt0IUikOTZxsD11w99GxfscwFPrHxi2KrTDZb8fDj9dGmKoiiKoijKwNGQOkVRFEXpSeZYOPQ/4EptCNeuyvTpsHAhPP00HHaYCEcu18A/n50NeXmSD2nrVvjBD4bel9Onn07Lj1pSHk6nKIqiKIqiDC/q4aQoiqIoyRhzKhzyb3jnIginKJP2LowxcOSREk62cCE8+ii88AJ8/LHkMHK5JOTOSBE52tpg1Cg4/HA46SSp1OZXjUhRFEVRFOVTi+ZwUhRFUZT+2PQIvPvF4RWd3DlwftPwbS+NhMOwfDlUV0ueJ48HsrJgxgwoKBjp3imKoiiKoijpRnM4KYqiKMpQGH+OPL77JYgEBp5IPBlOBrgz4ZgXhqdvI4DLBfvsM9K9UBRFURRFUXZ1NIeToiiKouyI8efA6Suh7BhwZQ5tGy4/TPoinLkeCmcPb/8URVEURVEUZRdDPZwURVEUZSBkjoVjnofNT8AHl0G4A8JtYMN9f8bxgvFA5hg45D4oOjB9/VUURVEURVGUEUQFJ0VRFEUZDOPOhDGnQe37sPlR2PQwdFSC4wHjgI1I6F3OVJjweRh7FuTtHc+urSiKoiiKoiifAlRwUhRFUZTB4rig5BBps26FjhoI1InXkzsLfMXgzR/pXiqKoiiKoijKiKGCk6IoiqLsLBkl0hRFURRFURRFATRpuKIoiqIoiqIoiqIoijLMqOCkKIqiKIqiKIqiKIqiDCsqOCmKoiiKoiiKoiiKoijDigpOiqIoiqIoiqIoiqIoyrCigpOiKIqiKIqiKIqiKIoyrKjgpCiKoiiKoiiKoiiKogwrKjgpiqIoiqIoiqIoiqIow4oKToqiKIqiKIqiKIqiKMqwooKToiiKoiiKoiiKoiiKMqyo4KQoiqIoiqIoiqIoiqIMK8ZaO9J9SAvGmBpg4wiYLga2q93d1u5I2la7and3sjuSttWu2t3dbKtdtbu72Va7and3s6121e7uZnuCtbak58JPjeA0Uhhj5llr56jd3dPuSNpWu2p3d7I7krbVrtrd3WyrXbW7u9lWu2p3d7OtdtXu7mg7GRpSpyiKoiiKoiiKoiiKogwrKjgpiqIoiqIoiqIoiqIow4oKTqnnLrW7W9sdSdtqV+3uTnZH0rbaVbu7m221q3Z3N9tqV+3ubrbVrtrdHW33QnM4KYqiKIqiKIqiKIqiKMOKejgpiqIoiqIoiqIoiqIow4oKTinCGHOSMWalMWaNMebaNNq92xhTbYxZki6bUbvjjDGvGmOWG2OWGmOuSpPdDGPMB8aYj6N2f5oOuwn2XcaYj4wx/0ujzQ3GmMXGmIXGmHlptJtvjHnYGLMi+j3PTZPd6dF9jbUmY8zVabL97eh5tcQY8x9jTEaa7F4Vtbk0lfuabLwwxhQaY140xqyOPhakye550f2NGGNSVlmjD9u3RM/rRcaYx4wx+Wmy+/OozYXGmBeMMaPTYTfhve8aY6wxpjgddo0xNxpjtiT8lk9Jh93o8iuj/5OXGmN+kw67xpj/JuzrBmPMwuG224/t/Y0x78X+TxhjDkqT3f2MMe9G/0c9ZYzJHWabSa810jRu9WU7pWNXP3ZTOm71Yzel41ZfdhPeT8m41c/+pnTc6m9/0zBu9bXPKR27+rGb0nGrH7upHreSzlVSPW71YzfVY1ZfdtNxrdWX7VSPW/3OR1M4bvW1vym/3hoU1lptw9wAF7AWmAx4gY+BGWmyfQQwC1iS5n0uB2ZFn+cAq9Kxz4ABsqPPPcD7wGfSuN/XAPcD/0ujzQ1AcTq/36jde4FLo8+9QP4I9MEFVAIT0mBrDLAe8EdfPwh8OQ129wGWAJmAG3gJmJYiW73GC+A3wLXR59cCv06T3b2A6cBrwJwUHt9ktk8A3NHnv07jPucmPP8W8Od02I0uHwc8D2xMxXjSx/7eCHw3Vd9tP3aPjv6OfNHXpek6zgnv/x9wfRr3+QXg5OjzU4DX0mT3Q+DI6POvAj8fZptJrzXSNG71ZTulY1c/dlM6bvVjN6XjVl92o69TNm71s78pHbf6sZuOcWuH1+6pGLv62eeUjlv92E31uJV0rpLqcasfu6kes/qym45rrb5sp3rc6nM+muJxq6/9Tem4NdimHk6p4SBgjbV2nbU2ADwAnJkOw9baN4C6dNjqYXebtXZB9HkzsByZsKfarrXWtkRfeqItLYnJjDFjgVOBv6XD3kgSvdtzBPB3AGttwFrbMAJdORZYa63dmCZ7bsBvjHEjAtDWNNjcC3jPWttmrQ0BrwOfTYWhPsaLMxFxkejjWemwa61dbq1dOdy2Bmj7heixBngPGJsmu00JL7NIwdjVz/+E24Dvp8LmDuymlD7s/j/gZmttZ3Sd6jTZBcAYY4Dzgf8Mt91+bFsgdpc+jxSMXX3YnQ68EX3+InDOMNvs61ojHeNWUtupHrv6sZvScasfuykdt3ZwPZmycWsEr2P7spuOcavffU7V2NWP3ZSOW/3YTfW41ddcJaXjVl920zBm9WU3HddafdlO9bjV33w0lePWiM2DB4MKTqlhDLA54XUFafintatgjJkIHICorOmw54q6+1YDL1pr02IX+B0ygETSZC+GBV4wxsw3xnwtTTYnAzXAP4yEEP7NGJOVJtuJXECKJm09sdZuAW4FNgHbgEZr7QtpML0EOMIYU2SMyUTu8o1Lg90YZdbabSAXZ0BpGm3vCnwVeDZdxowxvzDGbAYuAq5Pk80zgC3W2o/TYa8H34y6td893OED/bAHcLgx5n1jzOvGmAPTZDfG4UCVtXZ1Gm1eDdwSPbduBX6YJrtLgDOiz88jhWNXj2uNtI5b6b7OGYDdlI5bPe2ma9xKtJvOcSvJcU7LuNXDblrHrT7OrZSPXT3sXk2axq0edlM+bvUxV0n5uDVSc6QB2E3ZmNWX7VSPW8nspmPc6udYj8T1VlJUcEoNJsmyXU5tTAXGmGzgEeDqHmpyyrDWhq21+yNK+UHGmH1SbdMYcxpQba2dn2pbSTjUWjsLOBm4whhzRBpsupHQiT9Zaw8AWhH337RhjPEiFwQPpcleAXL3aRIwGsgyxnwh1XattcsRV+MXgeeQkNxQvx9ShgVjzHXIsf53umxaa6+z1o6L2vxmqu1FRczrSJO41YM/AVOA/RER9//SZNcNFCBu5t8DHozeuU8XnydNQnkC/w/4dvTc+jZR79Q08FXk/9J8JGQlkAojI3GtMdK2+7Kb6nErmd10jFuJdpH9S8u4lWR/0zJuJbGbtnGrn3M6pWNXErtpGbeS2E35uDUSc5Vd1W6qx6y+bKd63EpidyZpGLf62N+Rut5KigpOqaGC7ur4WNITijOiGGM8yAD+b2vto+m2byXE6zXgpDSYOxQ4wxizAQmZPMYYc18a7GKt3Rp9rAYeQ0I4U00FUJGgmj+MCFDp5GRggbW2Kk32jgPWW2trrLVB4FHgkHQYttb+3Vo7y1p7BBKykk7PiCpjTDlA9HHY3fh3RYwxFwOnARdZa0fiBsH9DLMbfx9MQUTUj6Pj11hggTFmVKoNW2urohdGEeCvpGfsAhm/Ho26nn+AeKUOe6L0ZETDcc8G/psOewlcjIxZICJ9Wo61tXaFtfYEa+1sZKK6drht9HGtkZZxa6Suc/qym+pxawD7m5JxK4ndtIxbyfY3HeNWH8c5LeNWP+dWSseuPuymfNzq4ztO+bgVo8dcJW3XW2meI/VpN53XWv3sc0qvtxLsxm5ap+V6K3F/R/B6KykqOKWGD4FpxphJUa+MC4AnR7hPKSV61+XvwHJr7W/TaLfERKscGGP8iEiwItV2rbU/tNaOtdZORL7fV6y1Kfd+McZkGWNyYs+RBHwpr0hora0ENhtjpkcXHQssS7XdHqTbS2AT8BljTGb0/D4WifdPOcaY0ujjeOSCL537/SRy0Uf08Yk02h4RjDEnAT8AzrDWtqXR7rSEl2eQnrFrsbW21Fo7MTp+VSBJVCtTbTt2YR3ls6Rh7IryOHBMtA97IEUPtqfJ9nHACmttRZrsxdgKHBl9fgxpEq0Txi4H+DHw52Hefl/XGikft0bwOiep3VSPW/3YTem4lcxuOsatfvY3peNWP+fV46R43NrBOZ2ysasfuykdt/r5jlM9bvU1V0npuDVSc6S+7KbjWqsf26ket5LZ/SgN41Zf+ztS11vJsbtA5vLdsSF5V1YhKvl1abT7H8R1Loic2Jekye5hSNjgImBhtJ2SBrszgY+idpeQoipAO+jDUaSpSh2SS+njaFua5nNrf2Be9Fg/DhSk0XYmUAvkpfm7/SnyT2kJ8C+i1WLSYPdNRND7GDg2hXZ6jRdAEfAycqH3MlCYJrufjT7vBKqA59O4z2uQvHuxsSsV1eKS2X0kem4tAp5CEvKm3G6P9zeQmip1yfb3X8Di6P4+CZSnya4XuC96rBcAx6TrOAP3AN9Ixbm8g30+DJgfHUPeB2anye5VyLXPKuBmwAyzzaTXGmkat/qyndKxqx+7KR23+rGb0nGrL7s91hn2cauf/U3puNWP3XSMW30ea1I4dvWzzykdt/qxm+pxK+lchRSPW/3YTfWY1ZfddFxr9WU71ePWDuejpGbc6mt/U369NZhmop1SFEVRFEVRFEVRFEVRlGFBQ+oURVEURVEURVEURVGUYUUFJ0VRFEVRFEVRFEVRFGVYUcFJURRFURRFURRFURRFGVZUcFIURVEURVEURVEURVGGFRWcFEVRFEVRFEVRFEVRlGFFBSdFURRFURRFURRFURRlWFHBSVEURVEURVEURVEURRlWVHBSFEVRFEVRFEVRFEVRhpX/D4Rn0TNRTBjBAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_7\n", + "total seqlets: 97\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_8\n", + "total seqlets: 91\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "metacluster_1 pattern_9\n", + "total seqlets: 77\n", + "Topic 16 actual importance scores:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from collections import Counter\n", + "import numpy as np\n", + "\n", + "from modisco.visualization import viz_sequence\n", + "reload(viz_sequence)\n", + "from matplotlib import pyplot as plt\n", + "\n", + "import modisco.affinitymat.core\n", + "reload(modisco.affinitymat.core)\n", + "import modisco.cluster.phenograph.core\n", + "reload(modisco.cluster.phenograph.core)\n", + "import modisco.cluster.phenograph.cluster\n", + "reload(modisco.cluster.phenograph.cluster)\n", + "import modisco.cluster.core\n", + "reload(modisco.cluster.core)\n", + "import modisco.aggregator\n", + "reload(modisco.aggregator)\n", + "\n", + "n_mut = 4\n", + "hdf5_results = h5py.File(\"data/tfmodisco/MMEFS_M4_results.hdf5\",\"r\")\n", + "\n", + "print(\"Metaclusters heatmap\")\n", + "#import seaborn as sns\n", + "activity_patterns = np.array(hdf5_results['metaclustering_results']['attribute_vectors'])[\n", + " np.array(\n", + " [x[0] for x in sorted(\n", + " enumerate(hdf5_results['metaclustering_results']['metacluster_indices']),\n", + " key=lambda x: x[1])])]\n", + "#sns.heatmap(activity_patterns, center=0)\n", + "plt.show()\n", + "\n", + "metacluster_names = [\n", + " x.decode(\"utf-8\") for x in \n", + " list(hdf5_results[\"metaclustering_results\"]\n", + " [\"all_metacluster_names\"][:])]\n", + "\n", + "all_patterns = []\n", + "background = np.mean(onehot_data[n_mut], axis=(0,1))\n", + "\n", + "for metacluster_name in metacluster_names:\n", + " print(metacluster_name)\n", + " metacluster_grp = (hdf5_results[\"metacluster_idx_to_submetacluster_results\"]\n", + " [metacluster_name])\n", + " print(\"activity pattern:\",metacluster_grp[\"activity_pattern\"][:])\n", + " all_pattern_names = [x.decode(\"utf-8\") for x in \n", + " list(metacluster_grp[\"seqlets_to_patterns_result\"]\n", + " [\"patterns\"][\"all_pattern_names\"][:])]\n", + " if (len(all_pattern_names)==0):\n", + " print(\"No motifs found for this activity pattern\")\n", + " for pattern_name in all_pattern_names:\n", + " print(metacluster_name, pattern_name)\n", + " all_patterns.append((metacluster_name, pattern_name))\n", + " pattern = metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][pattern_name]\n", + " print(\"total seqlets:\",len(pattern[\"seqlets_and_alnmts\"][\"seqlets\"]))\n", + " print(\"Topic 16 actual importance scores:\")\n", + " viz_sequence.plot_weights(pattern[\"Topic_16_contrib_scores\"][\"fwd\"]) \n", + "hdf5_results.close()" + ] + }, + { + "cell_type": "markdown", + "id": "9815f06f-e033-43ec-ab3c-88c7a8054eef", + "metadata": {}, + "source": [ + "### Saving TFModisco patterns as text to be later used by ClusterBuster" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ccc7ed01-356e-4708-b5fa-166c137a0c1e", + "metadata": {}, + "outputs": [], + "source": [ + "def get_ic_trimming_indices(ppm, background, threshold, pseudocount=0.001):\n", + " \"\"\"Return tuple of indices to trim to if ppm is trimmed by info content.\n", + " The ppm will be trimmed from the left and from the right until a position\n", + " that meets the information content specified by threshold is found. A\n", + " base of 2 is used for the infromation content.\n", + " Arguments:\n", + " threshold: the minimum information content.\n", + " remaining arguments same as for compute_per_position_ic\n", + " Returns:\n", + " (start_idx, end_idx). start_idx is inclusive, end_idx is exclusive.\n", + " \"\"\"\n", + " per_position_ic = compute_per_position_ic(\n", + " ppm=ppm, background=background, pseudocount=pseudocount)\n", + " passing_positions = np.where(per_position_ic >= threshold)\n", + " return (passing_positions[0][0], passing_positions[0][-1]+1)\n", + "\n", + "def compute_per_position_ic(ppm, background, pseudocount):\n", + " \"\"\"Compute information content at each position of ppm.\n", + " Arguments:\n", + " ppm: should have dimensions of length x alphabet. Entries along the\n", + " alphabet axis should sum to 1.\n", + " background: the background base frequencies\n", + " pseudocount: pseudocount to be added to the probabilities of the ppm\n", + " to prevent overflow/underflow.\n", + " Returns:\n", + " total information content at each positon of the ppm.\n", + " \"\"\"\n", + " assert len(ppm.shape)==2\n", + " assert ppm.shape[1]==len(background),\\\n", + " \"Make sure the letter axis is the second axis\"\n", + " assert (np.max(np.abs(np.sum(ppm, axis=1)-1.0)) < 1e-7),(\n", + " \"Probabilities don't sum to 1 along axis 1 in \"\n", + " +str(ppm)+\"\\n\"+str(np.sum(ppm, axis=1)))\n", + " alphabet_len = len(background)\n", + " ic = ((np.log((ppm+pseudocount)/(1 + pseudocount*alphabet_len))/np.log(2))\n", + " *ppm - (np.log(background)*background/np.log(2))[None,:])\n", + " return np.sum(ic,axis=1)\n", + "\n", + "import h5py\n", + "n_mut = 4\n", + "hdf5_results = h5py.File(\"data/tfmodisco/MMEFS_M4_results.hdf5\",\"r\")\n", + "\n", + "metacluster_names = [x.decode(\"utf-8\") for x in list(hdf5_results[\"metaclustering_results\"][\"all_metacluster_names\"][:])]\n", + "\n", + "motif_dict = {}\n", + "with open(\"data/tfmodisco/selected_patterns.txt\", 'w') as fw_pattern:\n", + " for metacluster_name in metacluster_names:\n", + " motif_dict[metacluster_name] = {}\n", + " metacluster_grp = (hdf5_results[\"metacluster_idx_to_submetacluster_results\"][metacluster_name])\n", + " pattern_names = [x.decode(\"utf-8\") for x in list(metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][\"all_pattern_names\"][:])]\n", + "\n", + " background = np.mean(onehot_data[n_mut], axis=(0,1))\n", + " for pattern_name in pattern_names:\n", + " pattern = metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][pattern_name]\n", + " pattern_array = np.array(pattern[\"sequence\"][\"fwd\"])\n", + " start, end = get_ic_trimming_indices(pattern_array, background=np.mean(onehot_data[n_mut], axis=(0,1)), threshold=0.1)\n", + " print(f'{metacluster_name}_{pattern_name}',file=fw_pattern)\n", + " with open(f'data/tfmodisco/motifs/MMEFS_M{n_mut}_{metacluster_name}_{pattern_name}.cb', 'w') as fw:\n", + " print(f'>{metacluster_name}_{pattern_name}',file=fw)\n", + " for i in pattern_array[start:end,:]*100:\n", + " print(*i,file=fw)\n", + "hdf5_results.close()" + ] + }, + { + "cell_type": "markdown", + "id": "9d2040e9-a016-4db9-b153-8f0d058654ac", + "metadata": {}, + "source": [ + "### Plotting TFModisco trimmed patterns " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "cb9bdbdb-576b-42d3-9d1e-1c6ac6618fa8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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H8MEZJstGIIIITX891O2E2cdD9aYYNEAIIYSI3PLlcO21Xbs/bWiAH/8YPvkk9u0SIpbiNDB2Z3DbL5RS7yulhjr1foQQQvQOSik3Jvv7VGACcIVSakKHzaYC44OP64HHI9h3OjBPaz0emBd8DXAJkKa1PgY4EfiRUmp0fN6diDevF772NZg7N3TmvBYNDaZ8ykknQUVF/Nsneqj6vbD4e5Fn3OjIXw+fXge1O2PaLNE9ErwhhI1AwHSKvfRS7NJT1debiMmf/zyOARxaQ8n7MGcKvFYAiy6DNXfC5kdh09/hi9/Ch1+Fl3Ng8fehekucGiKEEEJYW7MGbryxe9fX+no4//xuXqMrV8H8aeCLMjJd+6CpDOZ+GRrLu9EAIYQQInLl5XDBBd279jU0mKwd+/bFrl1CxFIcB8bu11ofq7U+Hvgf8H9xfitCCCF6n5OBrVrr7VprLzATmNZhm2nAM8GM80uBAUqpwjD7TgNa8qPNAC4KPtdAllLKA2QAXqA6Pm9NxNsvfwmffhpdELbXC7t3mwx6kWTcE31MwGf6Nf3dnHnub4D5F8qE7yQiwRtC2Pjd7+DVV2NfV6y+Hp5+Gh54ILbHBaDyC3hnAiz8FlQsA90MzdWA/9A2gSbw1Zifu2bCu8fCwkvMjGMhhBAizqqrYerU7me0aqkFes01XQyI9FbCR+d3PTIdDc1VsGAaBPzhNxdCCCG6we+Hiy6CqqruH6umxpQFtUrTLEQSiMvAmNa67WBXFmZATAghhIjGMGBPm9d7g8si2SbUvoO11iUAwZ+DgstfBeqAEmA38IDW+oBVw5RS1yulViilVpSVlUX7vkSczZoF//lP1/rCvF5Ytgzuuy/27RI93LZ/m6zA2te942g/1G6DzY/Hpl2i2yR4QwgLb78NDz8c+8CNFvX18Mc/wvz5MTqgDsCGB+D9L0H1xshnEGsf+Buh6G14+3DYvzBGDRJCCCGsXXONSfcYiwxUjY3wzjumBEtUdAAWfBu8ln0ekQt4TeDkKik7K4QQIr7uvBO++MJ03naXz2dSMP/ud90/VjtaQ9V6U3N571tw4HNzzRUiOvEaGEMpdbdSag/wXSTzhhBCiOgpi2Udezfstolk345OxszKHAqMAX6llDrMakOt9ZNa68la68kFBQVhDiuctGsXfO973Rtrqqsz9wOLF8euXaKHC/hgzR/BH2U2YTv+elh7Z2yOJbpNgjeE6GDrVrjyyu7PCA6nocHMnCoq6uaBAs1m1u/q27ueHinQBE3l8NHXYMsT3WyQEEIIYW3VKnjvPRN0ESv19fCb30S505o7oeJTE3zRXf562PwYFP2v+8cSQgghLJSXw/33R1YbO1L19fDYYyaLVbd5K2Hlz+G1gfDeSbDk+7DkKvjgDHhlACy5BuqLY3Ai0UfEbWBMa/17rfUI4HngZsuTy8xlIYQQ9vYCI9q8Hg50/JJjt02ofUuDGaQI/twfXH4l8J7WullrvR9YBEyOwfsQDrr88thMEm5ogIsvjk0wt+gFdr8CvtrYHjMQww5b0S0SvCFEG1rDpZfGL+NGR7W18P3vd+MA/ib4+Buwb15sIuz8DfDZr2DTI90/lhBCCNHBrbdCU1PsjxtVwGVDCWy4rxvlUiz462HZj2J3PCGEEKKNe+6JT41rvx/uuKObB9n6NLw5Crb802S08teb0p3N1aYz0VcDO1+At8ebmVySiUOEF6+BsbZeAL5tdXKZuSyEECKE5cB4pdQYpVQqcDkwq8M2s4CrlHEKUBUshRJq31nA1cHnVwNvBZ/vBs4OHisLOAXYGK83J2Jv0SJYvdp8746Fujp45pnYHEv0YFrDqt/HPngj1scTXSbBG0K08cwzsHlzfDrGrPh8pl5ZlwT8MP8bULaw6xk3rPjr4YvpsOnR2B1TCCFEn7d6NSxYEJ9rbFQzkdf8ydRyjLXm6vDbCCGEEFEqK4PHH49t1qoWXm83On8Dflj2Y1j5MxOgEWqWlm4295nr7oMFF4MvzmkuRU8Xl4ExpdT4NvtfiAx+CSGEiJLW2ofJ3DQH2AC8rLVep5S6QSl1Q3Cz2cB2YCvwFHBjqH2D+9wLnKuU2gKcG3wN8BiQDazFXOP+o7VeHd93KWJp+vTYThSuq4M//CF2xxM9VPE70CQZ4nozT6IbIESyqKyEn/0stqloI9Hl831xC5Qtjm3gRgt/vTn+gKNh8FmxP74QQog+J15ZN6JSXwQ7/hubcikdSXS6SDCl1PnAQ4AbeFprfW+H9Sq4/utAPXCN1vqzUPsqpfKAl4DRwE7gUq11ZXDdscA/gX5AADhJay05NoWIsbvvju/kgi7NAtQBWHARlH4YXSYrfx3smwtzT4fzFoE7vQsnF72d1tqnlGoZ3HID/24ZGAuufwIzMPZ1zMBYPXBtqH2Dh75XKXUE5pq1C7gBIYToiYYMgdLS7h1j8GDYty827eljtNazMdehtsueaPNcAzdFum9weQVwjsXyWuCSbjZZJMjy5fDZZ7E/bq10P/VtWsMXv5V+yF5OgjeECPr1r+Mzmykudr0CW56Ibcr3jvwNpkPu62sga0TYzYUQQgg7q1fD/PnOZbayb8gfzUxhIXoZpZQbMyvrXEzK+OVKqVla6/VtNpsKjA8+pgCPA1PC7DsdmKe1vlcpNT34+lallAd4Dvi+1nqVUiofaHbkzQrRh5SWwpNPxjf4sUs1s1f9PvrAjRb+BqjeAEuuhdNeAKW60ADR28VpYMyyTIoQQvQ43Q3ciNUxhBAh/e53UZb5jZAEb/Rx++dD7Y5Et0LEmZRNEQJYsQJefDEJZgRHomYbLL0mvoEbLXy18PHX438eIYQQvdr06Ulwja3bDbueN6nbheh9Tga2aq23a629wExgWodtpgHPaGMpMEApVRhm32nAjODzGcBFwefnAau11qvAzBTTOh71iITo2+66KwkCHzva9TJserh796P+BiiaBRvuj127hBBCCCGESBKrV8OiRSZJghAxtenvJqOh6NUkeEMI4IYb4hMFGXNam8CNgEMjYNovUXxCCCG6Zf16+PjjJBh8WnWbZN0QvdkwYE+b13uDyyLZJtS+g7XWJQDBn4OCyw8HtFJqjlLqM6XULTF5F0KIVuXl8K9/JUHwY1uVX8DSa2MzkcBfD2tuh+L3un8sIYQQQgghksjvfpdk3+NF7+BrgJI5iW6FcIAEb4g+b8UK2LAh0a2I0J5X4cDnJqjCKRLFJ4QQohv++U9oTnSyi7rdsOcVybohejOrugMd5/jYbRPJvh15gNOB7wZ/XqyU6lSjWSl1vVJqhVJqRVlZWZhDCiHaevHFJKsoogPwyeWxzQDpb4DF3zOdkEIIIYQQQvQCpaXwwQdJMIlJ9D7Fs0GlJLoVwgESvCH6vDvvhMbGRLciAs3VsOxHEkwhhBCix/D74dlnwedLcEO2/UtyVYrebi8wos3r4UBxhNuE2rc0WFqF4M/9bY41X2tdrrWuB2YDkzo2Smv9pNZ6stZ6ckFBQZfemBB91eOPQ70DlTIjtvtVaNgb++P6G2Hzw7E/rhBCCCGEEAnw8svgdie6FaJX2vYv8NUkuhXCARK8Ifq03bvh/fd7SBTk57eamUlCCCFED7FgQRIEbmgN255yruSYEImxHBivlBqjlEoFLgdmddhmFnCVMk4BqoKlUELtOwu4Ovj8auCt4PM5wLFKqUyllAc4E1gfrzcnRF+zZQvsSKbqlYFmWPlz8MVhIoG/DtbeFfvjCiGEEEIIkQBPPplkQdiid/A3QumHUeygYPg0OP1lOH8FfPlVGPEtrJOvimTjSXQDhEikBx/sfuDGwIEweTLk5EBVFSxfDpWVsWlfq8rVsGOG+YAWQggheoinn4ba2gQ3omKZyV4lRC+mtfYppW7GBFW4gX9rrdcppW4Irn8Ckx3j68BWoB64NtS+wUPfC7yslLoO2A1cEtynUin1ICbwQwOztdbvOPNuhej9ZsxIsgkG256O77VUJzrSUwghhBBCiO7btQu2bk10K0SvVPoRuNIim5yWORxOmwkDjoWUHLMs70QYch4cdQt8cinU745ve0W3SPCG6LOamuDf/wavt2v7X3AB3H8/jBljyq4oZSb3ZmTAxo3wq1/BvHkxauzqP4BfZgwLIYToOZqb4c03o69W8p3vwDXXwPHHm2N88AH885+wYkUXG7L1KQl+FH2C1no2JkCj7bIn2jzXwE2R7htcXgGcY7PPc8Bz3WiyEMLGM89Ed5/qcsF118ENN8Axx5hlGzaY6+c//2nKmHWZrx6++F18y3fKdVoIIYQQQvQCr70W3fbjx8ONN8LUqabUysKFpnzi8uXxaZ/owXa/GlnJlJxx8LUV4M4Ad2r7dSk5kDcJLlgDc6ZA9cb4tFV0m5RNEX3WrI6JpCN0zDGwejW8+CIcdRSkp8OAAdC/v/mZlgbHHWcGrJYvNxfgbqnbBSXvA8k09UoIIYQIbeFC8EQRJjx6NCxebAIrL7gAhg0zy669Fj7+GP7xD8jMjLIRAT/seQV0NKNWCkZdAWfPhW/th4tL4PRXYPDZUZ5cCCGEiN7mzVBeHvn2Rx0Fn39uskpOmgQpKeZx7LFw333m3vXYY7vRoA0PQqCLMx6EEEIIIYToQ55/3kz0DcflgltugS++gJtvhiOOgHHj4OqrTR/YY4+ZScJCAGZmXNEsTOLTENwZcNa74MnuHLjRwpUC7iz4yrvgyYp5U0VsSPCG6LMefBBqIghUa+uEE8xg1MSJpkxKKNnZZvulS+HII7veTtb/JcpBJyGEECLxXnop8pIpxx5rBpdOOqnz9dXthqwscwP7xRfmecTKl0SX+iPncDh/OZz8JAz5KqQXQMYQGPkdOHMWnP4qpOVH0QAhhBAiOq+9FnnJlAkT4NNPzf1pdnbn9dnZ5l500SKT0SpqzdWw/l7wS9FuIYQQQgghQjlwANaujWzbZ5+F//s/M0mp7cQnl8ssu+aa6CdFiV6sah34GsJvN+VfkDEUXO7Q27nckDYITpkRm/aJmJPgDdEn7dhhBoCiceKJJuqxf39zEY2E222ycSxaZGZERc17ELb/B3RzF3YWQgghEkPryAef8vJgzhwTlBHqpjQzE4YPh5kzo2jI7pdMuvdI5E6C81fCgOMhxWIEzJMFwy6AC9ZB+qAoGiGEEEJE7tlnTYnPcHJzYe5cc/10h+iba+kAnjMHCgqibMyul0FFuY8QQgghhBB90Lvvmqzs4dxwA0ybFnpyUmamCcJ+6KHYtU/0YGWLCJt1Y9QVMPxC8ESYttiTCYVfg8Ou7XbzROxJ8Ibok156KbqJuCedBB99BP36RX8ul+tQAMfEiVHuvOMZutVbNvTrcMYs+HY5XOGHK3xw4XY4+Z9mdrEQQggRB6tWRZYm0u2Gt982A1CRBEZmZMBZZ8Ftt0XQCK3NoBMRZK9KHwxfmWNuXEJFp7vTISXXpCB0pUTQCCGEECJy+/bB9u3ht2u5fubnR3b9bLknffddU1IlYpseAl9dFDsIIYQQQgjRN738cvhM7yefDH/9a2RZZVuy0F52WWzaJ3qw/R+Hzoao3DDpr9GXQUnJhuPvAyUpXpKNBG+IPunVVyObzQQmffvs2eHLpITicpmMHe+9F1n0JWAGnTY+2LUUtYPPhq+vgdNmwvBvmhTvymU+xLPHmGi6qV/AaS9B1ujojy+EEEKEMH8++COImbjvPlMyJeJrIyYF/G9/C1/9apgNq9ZGNuDkSoWz3oPUfuZaGY47FfodYVIRCiGEEDG0aFFk18Q//cmUQYnm+pmaambvPfBAhDtUbYTabZGfQAghhOjNBg9OjmMIIZLW4sWh16elwaxZJqtGpLKy4OmnYdiw7rVN9HBlYX65Rl4CHosswpFwp8PoK7u2r4gbCd4QfU5tLaxZE/n2998fWSRkOC6XmVn8xz9GuEP5Umgqj/5ER/4SzpwFA46GFJuIE1cKeDJgxMXw9VWQd2L05xGiF1NKna+U2qSU2qqUmm6xXimlHg6uX62UmhRuX6VUnlJqrlJqS/Bnbpt1xyqlliil1iml1iil0uP/LoWIn7lzw2feGD4cbrzRBGNEKzMT/vGPMBuVzgciqNty4iPQ73ATxBEpTxaM+BaMvS7yfYQQQogw5s8PP1tv4ED4+c+7do+alQU//CEMHRrBxtuegoAv+pO40sz9Zf5JXe9AFEIIIZLNvn1mop3VoyO77fbtc77dQghH7NsX/nv8D34QXeBGi5QU+MMfutYu0Qs010BDSehtjr3bfiwwnJQcOPYupF5mcpHgDdHnfPQRpEc4LHrSSfD975s07bGQlQU/+xkcdVQEG2/6O/gaojvBhOlw7J8iT4/kSoGUfnDOR5A/JbpzCdFLKaXcwGPAVGACcIVSakKHzaYC44OP64HHI9h3OjBPaz0emBd8jVLKAzwH3KC1ngicBTTH6/0J4YSlS8Nvc8cdkaV6tzNkiKkRamvfXPCHuY5mHwZjvh95Pci2PFlwwl9MhLoQQggRA/PmhS/v+fvfd+/66XLB7beH2UhrU8JTR/GVNGMYfPkNuOQgnD0PvjLXlO885yOTsUoIIYRIlCFDQKnuPYYMSfS7EEIksU8/DZ0Vz+Mx38G7kt09Lc2MUUnynj7qwEozEdvO0AsgvaB750gdAMMv6t4xRExJ8Iboc958M3wUJJgL6vPPRx7oEam0NHjuOfO935avHva+RUQzhlsc/X9w9G3R17UCE1139gdQcFr0+wrR+5wMbNVab9dae4GZQMch4mnAM9pYCgxQShWG2XcaMCP4fAZwUfD5ecBqrfUqAK11hdY6goITQiSn4mKoC1OtZPhwuOKK6NK9d5STY7Jj2SoPk1IQ4Lg/d6+uo0qFcTd0fX8hhBAiqKkJtmwJvc2gQXD99d27R01Lg+99z1yLbR1YET4Asq3xN8M3N8Gwr5ugxtT+5uFOg4Ivw/mfmWuuEEIIkQilpclxDCFEr7Vokcn4bqe7E4RdLlNCWPRB5Z+CP0R642Nu73rWjRYpOeY4ImnEPXhDUs+LZPPOO+FnMwH88pdQWNi9WU1W3G44/HC4LlSm9f3zTUdXpA77AUz4TdcCN1qkZMNZ70HWmK4fQ4jeYRiwp83rvcFlkWwTat/BWusSgODPQcHlhwNaKTVHKfWZUuqWmLwLIRJk6VJIDVOB5PbbY3N9tc2+UV9s0gqGknM4DLsQ3Cldb0BKNhzzR3DHKEWXEEKIPuvzz8N36N52W2yuny4X/OlPITbY+XzoDsK2xv4QTrjX3ItalSBzuU2Gq8N/YtL5CiGEEEII0cvMmwcBm3m4bjfcfXfXsm60SE835Q/z87t+DNFDlX4IAa/1uoxCGHB0bM6TMx4yR8bmWKLb4hq8IannRbLZuhWqq8Nvl5Fh0tFmx6lEb3Y23HOPuXBb2vtW+EGnFumD4cS/x6aesDsdvvRc948jRM9mlRenY8iX3TaR7NuRBzgd+G7w58VKqXM6NUqp65VSK5RSK8rKysIcUojEWbAgdIarwsLuZ91okZMDf/mLxYryJeGDII+/F1zdyLrRwuWBw2/u/nGEEEL0aYsWmewbdgYMgP/3/2KTGTItDS6/3GTy6ERrE7wRSSK4wecE70UjmESQkg1H/gzGXBVtc4UQPchbG99izN9lUpAQQoi+w++Hdevs13/ta5DVjTm3bV17bWyOI6IQi9Jb3SnXdWCFfdtGfCey+7aIaBh1WYyOJbor3pk3JPW8SCpz5kS23VVXhSlrEgOpqfCd79is3DuL8OO9QVOetp7h1BUuDww4FsZ8PzbHE6Jn2guMaPN6OFAc4Tah9i0NXt8I/tzf5ljztdblWut6YDYwiQ601k9qrSdrrScXFHSzjp0QcTRvXugMV9//fmyvsUOHwnHHdVi4/+PQQZDZh0Hh+eDqRtaNFp5smPj72BxLCCFEnzV3bujgje98x3QMx0ogYIIpO6laD74ISqb0OwrOeMNk1YiUJwtOehwGnRn5PkKIHmVjxUZ2V+9OdDOEEEIIx2zYACkhuoSuuy42k4QzM00wt3BYospmlZZCQwn4QtSmHvuD7mXjb8uTaTL8i6QQ7+CNpEw9L7OX+66XX4aGMP1QSpl0tN1JYxWJfv3gj3+0WFGzDZoPRnaQYd+AwWdFV2IlnJRsmPwopA2M3TGF6FmWA+OVUmOUUqnA5cCsDtvMAq4Klv46BagKXo9C7TsLuDr4/GrgreDzOcCxSqnMYAapM4H18XpzQsST1wubN4fe5vrru1fns6PUVLjmmg4L980jZBDkYdfEPkqzcGpsjyeEEKLP0Bo+/TT0NjfeGNvMkFlZcMMNFivKFhLRRILTXgB3FzoKPZlw2kwJehSilyqvKyegAzT5QkSjCSGEEL3I0qX2k5gyMmDq1NiUPgQYMQLGj4/NsUQPULHcfuwvNc8E1MdS9ujYHk90WbyDN5Iy9bzMXu6bmppg2bLw233lK9C/f/zbA+ZiO6nj/PqSOVj/+nfgyYYp/4lNuZSOXGlw0hOxP64QPYDW2gfcjAmq2AC8rLVep5S6QSnV0sU9G9gObAWeAm4MtW9wn3uBc5VSW4Bzg6/RWlcCD2ICP74APtNavxPv9ylEPHzxReh07hMmHMr6FyupqSZjVit/I9RsDb3T2P9nSoXFrBH9YbzVCJgQQggR3p49obNuDB8ORx4Z+/OOHGnR+Vv8HvjrQ+847BuQPbbrvdCebBj3o67tK4RIavvq9pmftfsS3BIhejC/10zuCzXbWiSMUup8pdQmpdRWpdR0i/VKKfVwcP1qpdSkcPsqpfKUUnOVUluCP3PbrDtWKbVEKbVOKbVGKRXDzgwRCx99BHU2f67nnmsmOsWKywXf/nbsjtdnVCyHz2+B9ybD60PhjWHw/mmw+o9QtSHRrbNXvRF8NvdmQ8+HQIyDZQPNsT2e6LIYFPoOqTup51ND7FuqlCrUWpfYpZ4HUEq1pJ6fF4P3Inq45cvNAE9jY+jtfv7z2NUgCyc9HW6+ucPCXS+F7ywDOPIX0aWojYY7DYZOhQHHwcFV8TmHEElMaz0bE6DRdtkTbZ5r4KZI9w0urwA6BRQG1z0HPNeNJguRFJYsCX1Teskl4InDt892xzywEjwZ0Gxzw5F/cnwCHwd/JfbHFEII0ScsXhz6+njxxabMSawpZdH5W/ZJmJ1ccOLDkNKNVJUp2XDsnbD9PzIwJUQvU1xtum5LaksYNWBUglsjRA+jNay/F9b9GdCgAzDmGpj8kGSsShJKKTfwGGZS1l5guVJqlta6bQbdqcD44GMK8DgwJcy+04F5Wut7g0Ed04Fbgxl6nwO+r7VepZTKB2R0NcksXWq/7rLLYpvhPT0dvvvd2B3Pabt2wcKFpv+wrMxkJpk8GU45xfyMaZJcraH0Q1j1Ozi41kz2os1NVUMxVCyDDfdDwZfhuLsg/6QYNiAGDq4D7bNeN+I7kNIvtufrzj2eiKl4Z96Q1PMiaaxebT+O0yI/30RDxiqNVTgeD1x6aZsF/iaoCJMvF0xmjCN/Gb/gDQBXKhz9h/gdXwghRK+zYEHoIMnvfhfSYljpq0W7Mixli4M3ZDZGXhbbrBstAjGcSiGEEKJP+ewzqK21X3/VVfGZYJCRAd//fpsFdbvDTyQY/b3YlNh0pcBRv+n+cYQQSWV/nZlfV1JTkuCWCNHDBHyw+EpYexf4ak1wo78BdsyAD86C5upD2w4e3P3zxeIYfdPJwFat9XattReYCUzrsM004BltLAUGBCcgh9p3GjAj+HwGcFHw+XnAaq31KjATw7TW/ji9N9EFWsPevdbrlIJvfCP2Y03jxsX2eE5YsgTOP99kE/zxj+Ef/4BXXoFnnoFbbjHZ8MeNg+eeCz+GF5GAD5ZcBfOnmQANfz3tAjdaaJ/5rN0313zWfvF7+xo4iVCz0X7dwC851w7huLgOUUvqeZFMli+HhobQ21x4YYwuDlHwtQ2cK1toX8OqrdHfBeWOW5sAcHlg2Nchc3h8zyOEEKLX2BjinmLECJP2PR5S2k5CKl8cOpBi9BXxmbUU62h3IYQQfcaaNfZ9hLm5cPTR8Tv3YYe1ebF/IagQKUCUG064PzYzsjxZcNSvIWVA948lhEga5Q3lgMm8IYSIwvq/wN5ZnYMo/fUmu+SyGw8t27fPfHGwenRkt90+KW3URcOAPW1e7w0ui2SbUPsODk5oJvhzUHD54YBWSs1RSn2mlLolJu9CxExZmX1wxjHHxOecsSzDEm91dSZo46tfhfffNxO+OgatNzaa7bZvN4EdI0fCunXWx4uIrx4+ngp7Xgd/pFn+tPm83fR3WHoNBJIkRqpul/XytHxIHeBoU4Sz4l02RVLPi6SxcmX4bb7zndimsYpEu/PtnWWiq8OZ+DuHUhgpGH9j+M2EEEIIYM8e+3XnnNMhYDFeqjfZr+s/QVIACiGESDpbttivO+00aGoyKZLjod2x930Avhr7jQvPj232Kq1NUOWWx2N3TCFEQlU1VgFQVF2U4JYI0YPU7YF1d9tnvwo0wd7XoWwJFJzqbNtER1ZFHTpGzdhtE8m+HXmA04GTgHpgnlJqpdZ6XqeGKXU9cD3AyJEjwxxWxMq2bSbDrFUW2ilTwB2H+bfZcagEHA/79sHZZ8OOHaGz9LZVW2sCOU45BWbNMhk5otJ0AD48B6o3hs7Ka8dfD7tfhcZSOOPN+GTujZQCmsqt1+WdZDKGRDIRXPRIDhWHECKxtIatW0Nv43bDmWc605622kVmFr1t6hmGkn8SpDuU2s6dDuNvCL+dEEKIPq+mJnSGq698xaEAyfoQESSDzsS6vyS5NDbCp5/C44/D7bfDHXfA00/D5587nyFMCCFEfGkNRSHGOL/85fh20La7Npd+GHrjw2+ObaaplGw4/KexO54QIqG8fi8NPnNDsP3g9gS3RogeZNn14ctw+htgydWmFIBIpL3AiDavhwPFEW4Tat/SYGkVgj/3tznWfK11uda6HjPReZJVw7TWT2qtJ2utJxcUFET9xkTXbN8OfpskDV/5SnxKH8a6DEs8bNgAxx1nxuQiDdxoobUJ4rjgApgxI/z2rfyN8P4pULW+a4Ebrceph/0L4MPzwo/VxVM+4LIJzhh4qslkKHqtuGfeECIZhOoMa3HSSQ7NCLbjb4J6mwJpbR3+U2cj/uJdnkUIIUSvsG0bZGZCdbX1+jPOcKAR3oPmempnyFeT+uZm+3Z48EH4z3/A4zGBGi0BMVlZ5gZdKbjxRvjpT6GwMD7tqK+H55+Ht94ymcsOHDDL8/Nh8mS46CK48sr4zQIXQoi+pLw8dFnlc8+Nz4y9Fq2dv00V0BgihXpqHgw+K/YNyBphMmMJIXq8fbWHPkN2V+1OYEuE6EHKFpuyZTqCTumGYtj5HBx2TdybJWwtB8YrpcYARcDlwJUdtpkF3KyUmglMAaq01iVKqbIQ+84CrgbuDf58K7h8DnCLUioT8AJnAn+L15sT0du2zfShWDntNGfbkiw2bjRZR2prQ9/nhNPQYPq/6utNOZWwPr/FjK+FC4aLhL8BDnwGmx7p/rG6qgBT9tkqOGjw2fEpCS2SRg+I0RKi+9auhdTU0Nt8/euQkeFMeyxVbwR3mAa4UmDEt8HlYNxVLGdWCSGE6LVCZbjq1w+GDnWgEbXbwBPiWjowOe+cq6th2jSYOBGefNLcmFZXt89kUldnsptUV8Pf/gaHHQY/+IFJdx8rpaUwfToMHgy/+AW8845Jc+n1mkdJCbz9NvzsZ2abP/zB1HcVQgjRddu22QfDeTxw1FEONaRsUehJAsMvgkAc0j8pD4zqOOYhhOiJSmpKLJ93xaR/TmJLRYiaUkL0FpsesS+X0pG/DjY+GN/2iJC01j7gZkxQxQbgZa31OqXUDUqplvTVs4HtwFbgKeDGUPsG97kXOFcptQU4N/garXUl8CAmaOQL4DOt9Tvxfp8icqtXQ8AiOUNODgwZ4nx7Eq2pyfRvdTdwo0V9Pfz61xFsuH8BbHvaBF3Eir8OVv02dseL1iDssy3lHu9kS0QCSOYN0SesWWMfAdni298OH+ARVwfXELbM3cBTg5GDiYwyEUIIIToLNdvgpJPMurhfZ2u22t8dpg+G1P5xbkD0tm2Dc84xQRKRBmK0bDdzJnz2GcyZY4IpumP+fPjmN02QRrh21Naanw88AI88ArNnw5e+1L3zCyFEX7V1q32q5WOPNZ/LjmQ6qvwcmuvs14/9AaTEof6ZOw3GXBX74wohHFdSW4JbufFrPxUNFV0+TrO/mc/3fc6Gsg2Mzx8fwxYKkWSaa6HoLcL2B7dVI0FNiaa1no0J0Gi77Ik2zzVwU6T7BpdXAOfY7PMc8Fw3miziaPNm6+WO9YMlmd/8BvbsiU3gRotQJZoBaK6BTy6NbeBGi1DZfeNtMNbBfVmjTVpe0atJ5g3RJyxdGrpGfF4ejB3rXHssHfgcfCE6ywCGfTOp070LIYTou9assS8/dtpppqRK3NVstZ+1NPDUxN50WfjoI5g0ydzYdiWDRkMDrF8PRx8NX3zR9Xb8978wdarJ7BFNOxoboarKpPR/8cWun18IIfqyzZvtgx9PPdVk33BE5RdY5+QFUvpD3uT4nTstL37HFkI4piXbhkJR663FZzdbNIyW8iv76kKUchKiN9jzevTlqrXFFH8hRMLs2WO9/NRTHeoHSyIffABPPx1BsEWUwgaCLP8xeKtie9JWCfzMHQGWwX054+OTEVEkFQneEH1CuAGN004zAxAJVbGUsJHWI77lbMkUIYQQIkIbNtivO/dch2YbHFwN2mbgadCZ4Ml2oBGR+de/4IILTBkUqxSbkWpuhvJy811mdqf5O6FpDbfeCjfd1L2b6/p6+H//D/74x9jOrhBCiL7ALtUymOunY52+VSEu5AWnx2cmWyuZOSZEb1BUU4Q/+F08zZ3G/rr9XT4OHAriEKLX2vQQ+Gqj2yfgjU9bhBBRa2gwk2CsnHpq38q6UVEBl14a+8CNsMqXwZ43IJDowb04sMuwmz0GXCmONkU4T4I3RK/n99tHQLY49tgkiISsDtFZBpBRCBlDnWmLEEIIEaVdu+zXHXecQ40IdS0dcg64opzVFCdLl8JPfhLbm9r6enOjvHVr5Pv84Afw2GPhS8tFev4HHoAbb+z+sYQQoi/ZtMl+3QknONQIraF+t/36wWfFNwDSk+ibcZFslFLnK6U2KaW2KqWmW6xXSqmHg+tXK6UmhdtXKXW/UmpjcPs3lFIDHHo7fcaOyh2tz1PcKa2ZOKJVXFNsflYXx6RdQiSl+mKoWpfoVgghumHnTvsxpfF9rOrX738PdWGSysfFF9PjHGSeQP1sluccDu4MR5sinCfBG6LX274d0tJCb3PKKZCSyGA1b2X4SOvCr0k6JCGEEEmpqQkOHrReN2BA+OtwzNSFGHjKSY475wMH4JvfjM9shIYG+PrXI9v2xRfh5Zdje3NdXw/PPANvvhm7YwohRG+3d6/1cqVgyBCHGtFUHjoNe+H5kgFSOEYp5QYeA6YCE4ArlFITOmw2FRgffFwPPB7BvnOBo7XWxwKbgd/G+a30OburDn0XVyhKarsWvFFUbTJv7KzaGYtmCZGc9s2VmdNC9HA7d4LLZoR1aB+ag7t3L8yYAV6nEwMd+DyybPY9lV1fav+JoGRov7eT/2HR6xUVgTvMRNtjj3WmLbYOrgV3mNlGI74DKTnOtEcIIYSIwo4dkGET9D12rENpE3115mElrYBkuJnTGi65xJRKiYdAwH4QsK0dO+D662OTcaOj+nq46qrYH1cIIXqjmhr78p2FheDzOdWQzeBOt17nTod+hzvUECEAOBnYqrXerrX2AjOBaR22mQY8o42lwAClVGGofbXW72utW/6qlgLDnXgzfUlx7aFMGc2B5tYMGtHaXW2CQLq6vxA9wt43oy+ZIoRIKgcOmKzvHfXv37dKpvzxj9b/DqGMGwcnnQQTJkC6zW1IWGv/BP6myLZN6Q9H/Qam7YLLGuDSOvjGZhj7w+TMYqEAu/i+nHFOtkQkiARviF6vrCx0LfmUFNMxllAH14SvWTjoy860RQghhIhSSYl9oOTYsQ41onan/Q1XzrjIb+ji6C9/gU8/je9shHCBMs3NMG1afANqHK9xKoQQPVR5uX12qnHjHJy9VrMFAjaRIvkng08+2IWjhgFti9/uDS6LZJtI9gX4AfCu1cmVUtcrpVYopVaUlZVF2fS+rby+vPV5Q3NDl4Mvth3YBsD+uv0xaZcQDB6cHMdooTWUfmSzUsFRt8BX3ofj/2IfXCmESLjKSutg68MO6zv9ImVl8MILpq8pnJwcuPlm2L0bvvgC3n8fliwxx3j44Sj7D+uLofhdIMTAX4uj/wgXF8Mxf4SskeZz1ZMJ/cbDpL/Ct0pNEEcyyQDsAvkzEj2YKZwgeS9Fr7d/f+iLxxFHmItpQsumVCwPXZsrfTC4+lC4phBCiB6lstL0P1kZO9a+BmhMNZXbpw3MGQcqTBquOFu9Gu64I/E38L//PWzbFv2siGg4NlNcCCF6uMpK++DHcePA41SPTdUG8NukYyr4cnLORhO9mbJY1vGbpt02YfdVSv0e0x3+vNXJtdZPAk8CTJ48OfGp23oIf8BPrddkEVBKEdABdlTu6NKxWsqvVDZWxqx9oo/bt89+nerwsWF3YxtLdTusS2O7M+Gs/0HeSZCSDQWnwbBvwodnQ0PXyhAJIeLn4EFTRrgjxyYxJYFHHolsu1NPhdmzzf1Ndnbn9ddfD9ddB3fdBffcE8EBtzwWfhvlhlP+CyMuMsEaVloy3Z/4N8gaBatvi+DkDsgC/HTOvpEyAJSU3OoLJPOG6PVKS+1T0QIcfbRzbbF1YGXo9QOOAX+INyGEEEIkkN1sAzClyRwJkPSGiCDJORw8WQ40wt5Pfxr6+4gTPvsMHn00PuVShBBCRK+ysvOYUYvDD3co+BGg8nNsy4sVfg3cMpFAOGovMKLN6+FAxxQOdtuE3FcpdTXwDeC7WjsxQtt37K/bT2qHz4pdVbu6dKySWjNI7fV7qWmq6XbbhEg6+xdaTzw4/h7IP8UEboAZbMwZC6c+62z7hBARKS217oY67DD70sK9SVOTyZgRrq/rO9+BuXNhwADrwA0w2QgzM+F3v4N//cs+wB0w/+hbnoBAiAy7yg1nzYYRF4PH5qRtebLgyJ/BlH91XhfLzEuRygK0xY1i1igI9JG0Ln2cBG+IXm/PntDrjz8eshI7ngONYaKnBxwjafKEEEIkrcpK+yxXRx7pUCO8B0DbpJMYcJx9Vg4HLFgAy5c7M4krlF/8IvEBJEIIIQ4Jlbnq2GPB5dSlq3qz/bp+RzjUCCFaLQfGK6XGKKVSgcuBWR22mQVcpYxTgCqtdUmofZVS5wO3AhdqrSWUNcZKaktagzcC2qQwL6npWqaAAw0HAHArd5dLrwiR1PZ9AL7a9sv6T4Sx/w88HUZ8XSkwcAoM+4Zz7RNCRGS/TXWviRMhtQ/EPn/wQfh+rssvh//+N/Lxt+xsuOwyeOWVEBtVfg6BMPUlj/4DDDwtuolcnmwYeSmMuar98n37zBuN9BFKpMdYMg/69eu8f1pe4jsXhSMkeEP0ekVFodcfe2yYSD4nNFeHXp8/RYI3hBBCJK2KCvvgjZEjHWqEt9L+5q3f4Q41wtrPfhZ9tosTToD77jO1Q597Dv70J1PqrasWL4YVK+QerzdTSp2vlNqklNqqlJpusV4ppR4Orl+tlJoUbl+lVJ5Saq5SakvwZ26HY45UStUqpX4d33cnRO904IB95qrDnbp06QA02AyOulIhNc+hhghhaK19wM3AHGAD8LLWep1S6gal1A3BzWYD24GtwFPAjaH2De7zKJADzFVKfaGUesKp99QXlNSUoIJVazzK1Hwqqy+L+ji13lp8AfPB6HF5KKoJ06knRE90YEXnZSf+HVxp1tt7smFyBCUChBCOKi+3Xj50qLPtSJQXXoCaEAmyxoyBp56KfuJ0Vhacey5ce63NBnteA3+IrBu5k+Co30BKF2Zsp2TD5Echc0T4beOp+SCWmRFTBmBdJVD0Nk5VUBUiYUpLQ68fMsSZdtjy1dnPFG6Re4IzbRFCCCG6wK6EcGqqdaB4XDRVgLaJIMkc7lAjOvvkE9iyJfLtr7kGpk+H4cNN2khP8Nu61wu/+hVs3Ah33glvvhldO3796+gDSCZMgO9+F0aPNkEfO3fCs8/Cpk3RHUfEn1LKDTwGnItJGb9cKTVLa72+zWZTgfHBxxTgcWBKmH2nA/O01vcGgzqmY2Ytt/gb8G58350QvVdlpfl8tzJokEONaK4ytVusgvuyx4K/HlxOXcyFMLTWszEBGm2XPdHmuQZuinTf4PJxMW6maKO4ppjmQDMe5SHNk4av2Ud1UzUBHcAVRQa84ppi0j3p1HprUSjJvCF6H62hdkf7ZemDoOB0cIWYXZiaayb3VXwa3/YJISJ24ID18txc6+W9ic8Hb79tP0HI7YY33oD0Ls5Hzs6GRx6BhQth69YOK3fNtO//c6fDGa93byK0Ox1OfwXePxXb0pLx5q2EgMWYYeoAUxJG9HqSeUP0enYRkC0GDnSmHbYay8AV4mKiXJA12rHmCCGEENEqs5lUl59vamA6osEmLbM73X4GkwNuuw3q6sJvl55ubmwfecRk2MjKOhS4ASYQJjMTJk0ymTj+8Y/IM4d98YV5RGraNFi50pR6+c1v4MorTRDHb34Dn30Gy5bBBRdEfjzhiJOBrVrr7VprLzATmNZhm2nAM9pYCgxQShWG2XcaMCP4fAZwUcvBlFIXYWY9t8xoFkJEqbzcPvOGY3Wymw6YDBtWcsabzBxCCBFGcU0xDc0NpHpSyU41teVT3CmU14fplOugqLoId3BQojnQTFG1ZN4QvUz9ns4lPcd8P/z11p0B438cv3YJIaJWVWW9vC8EbyxaFHr9738PY8e279eKVno6vP66iTNvVbcb6kMEdh7xC0gb2L3Sya4UU8pq1KVdP0Z3eQ9aZxdOHWDaJ3o9Cd4QvZ7dRbTFgAGONMNeUxm4QlzFsseGr+ElhBBCJFBFhfXy3Fz7QamYa7KJIEnNg4BTESTtbdhgAh3CKSw0wRLnnWdmF4STlQVXXQUffQT9+4ff/q67IguicblM8Mhzz5kgkcxMSGlzT9gSQHLSSfDSS/DAAx1uokUiDQP2tHm9N7gskm1C7TtYa10CEPw5CEAplYXJwHFHqEYppa5XSq1QSq0os4vyEqIPs8tclZXlYJkr7wH72Vv9DjeDRUIIEcaOgzvQaDwuD/3TzRfUVHcqJTU2AdY2imuK8Qez0/q1nx0Hd4TZQ4gepmp956DJ8TeBJzP0fi4PjPxOQicmCCHaq662Xp6T42w7EuHFF+0nKuXlwS23RNa/FYrbbTLBXnRRm4VFb9t3RLkzYcKt4OlCuZSOUrLhuHtJWImSpgPW2UVScyV4o4+Q4A3Rq/l8oVOEu1xmECKhGveHXp8zDrRTI19CCCFE9CorrZfn5jo4+NRkM6svNRcCibmOPvcc+MNURsvMhMWLYfz46L6TZGWZIIp580Jn4CgpgXfegUCYiVyZmfDee6ZsS6QBJDfcAG+91fU0mCKmrHoUOv712W0Tyb4d3QH8TWtdG2ojrfWTWuvJWuvJBQUFYQ4pRN9jF9OUl2dfTiXmmmzyPQMMOB7cMkgkRE+wYOcCDjYeTNj5d1XtAkChKMgsaH1eUhtd8Mbe6r00+hpbX2+v3B67RgqRDKrWgb/h0OvMEZAeYU3vgM+UVxFCJAW74IWsGMQOJDOt4dVX7fuZbr3VjLvFQk4O/PWvbRbseLb9Z2hbh10b25IiafkwLEFpZ5tsxgzTB3cvq0gc+QI+6r1R1msWtpLzf1mIGKmoMPXi7eTnO9gpZqdxf+jgjLRBUsdKCCFEUkuKVJFemwiS1FwSVaPymWfCf8/4979h8OD2GS4ilZ4ORx4Jf/6z/TavvRb+plkpeP99OP306GZGZGXBOefA//4X+T4ibvYCI9q8Hg50zCVqt02ofUuDpVUI/mzpQZgC/EUptRP4OfA7pdTN3X4XQvRAe/fCY4/BT35iSkx973vw05/CE0+YALpQkiJzlbfCPlV7/wkONUII0V1nP3M2z69+PmHnb8mwEdABhuYMBUwnfrSZN3Ye3ImvTeC1lE0RvU7FsvYZlod8NfJJe54sGDo1Pu0SQkTF77fOcOpy9f4JLqtW2Wd3zcqCG2+MbQnIgQODT/xeqPzMZisFE6ebjBmxkpIDE34Xu+NFo7nGenla8k6Kuf2j28m9rw/UDHJINyoOCZH8ysrMYEhjo/X6ggIzqOJYPWErTfvBHyKXeXqBpMQTQgiR1Gpt5t7n5obOChFTzTYRJKl5JCLN4bp1cCDEZGYwWS6+8Y3ufQ/JyoKbbjIZON5/v/P6//43dBYygOnT4bjjutaOzEyYMgV+/nP4+9+j31/EzHJgvFJqDFAEXA5c2WGbWcDNSqmZmOCLKq11iVKqLMS+s4CrgXuDP98C0Fp/ueWgSqnbgVqt9aNxem9CJJ3du2HmTJgxA7ZtM520DR0mgGVmms/Gww83n/eXXQbDOhQzSo7MVQcgYJGSFyBzuEONEEJ0x8HGg/i1n93VuxPWhrJ6k0qoOdDMqP6jUCgafY1RZ97YfrB9po3SutKYtVGIpFC5qv3rwq+ZAcJIuDxmeyFEwjU0mP6ujgHX/fpBc3PoCcU93dKl9llmr7oq9udrLUNTvR5c6db3LoPOgJQI6gpHK/e42B8zEnZBfWl5zrYjCp/t+wxvwEtJTQmFOYWJbk6PJ5k3RK/W2Bh6tmlBgYOdYnbqi0NHWGcMBXeq/XohhBAigbS2Dw7Iy+taRokusYtKT81NSErBF14wN+x2Ro2CRx+NTTrNrCx46SXo3+E+tbwc1qwJve9JJ8Ftt3WvFml2Ntx9twkAEYmhtfYBNwNzgA3Ay1rrdUqpG5RSNwQ3mw1sB7YCTwE3hto3uM+9wLlKqS3AucHXQvRZfj/cc4/JevTHP8L69WbWWcfADTDXxqYm8zl8220miONvf2ufXtiuTnZurn0p55jzVkDAZjJBLGeuCSHiZkvFlnY/nRbQAaoaTSC11+9leL/hpHnS8Gs/Ow7uiOpYe6v3tnt9sPEgAbvsQEL0RA3tf8cpOC26/XMOj11bhBBd5vdbjzsNGBC6L6g3WLjQ+v4H4Prru9e/FFLlF9hm1h15GbijqEWc7LRNdIw7kbPQQ/ti3xcALNm7JLEN6SUk84bo1cKlmi0ocLBTzE79ntDrM0c60w4hhBCiCxoazA2rVa3L3FxIdSL+UGv7mpepueByNghSa1MyJdQN+/33xzawJTUVfvc7U1u0xVtvmXPYlW5JT4c33zSzw7srPR1mzYLx45OgJF0fpbWejQnQaLvsiTbPNXBTpPsGl1cA54Q57+1daK4QPc6mTXDJJSbThl1npZ2W7f/wB3j+eXj5ZTjsMPvrRF6eg5mrGvZh2QmqPJIBUogeYssBE7Sx9cDWhJy/or4Cj8uD3+8n1Z3KoKxBpLhSaKSRnZU7ozpWaa3JtOHCRYAAHpeH8vpyBmUNikPLhXCYv6n9fWvKAFMuO6pjNMgkPyGSgN9vPa6UkWHdP9abfPqp9fJBg0yQe9yULwWfTerfkd8GVxxuoDwJCggJ2ARv4NRNYnRqmmpas63N3zmfbx31rQS3qOeTzBuiV7NL39QiLS0JgjcawqSQzJAUQ0I4TSl1vlJqk1Jqq1JqusV6pZR6OLh+tVJqUrh9lVJ5Sqm5SqktwZ+5HY45UilVq5T6dXzfnRCx5fPZX0uHDAmdAStmdADb6Pu0fHA5lf7DCFcyZcIEuOCC2Aa2ZGbCzTebm+UW//0v1NXZ73PzzSalZyy4XGaw8Yc/jM3xhBAimTzxBJxwgvl8D1eKKpS6OvjiCzjmGFNyxa5jd8AABzNXNe6zXp6aG7q8pxAiaWws3wh0zlrhlJLaElKDg8k5qTnkZ+bjCma+K64pjvg4WmsONh4EaD1emictqmMIkdQaisHVZtb0wCngj/KLhcMTE4QQ1uyCN9zuJMj0HkderykhaeXCC8NPpu6W8qXWy/sf3buybgBgM7DpSCdr9JYXL299Pm/HvAS2pPdIzv9pIWIk3MXC7U6C4I2m8tDr0wucaYcQAgCllBt4DJgKTACuUEpN6LDZVGB88HE98HgE+04H5mmtxwPzgq/b+hvwbszfkBBxZnfDCibzhiO0H9uvtWmDHC+b8sorobNu3H57fDKSKAW/+pV5XlUFy5bZb5uVZWaAxzKdZXY23HmnycIhhBC9xX/+A7/8pcmeEYtZdH6/CQD58Y/tMxWlpjqYeaOxzHp5Wh7oXp7zWYheoiVN9cHGgzT5nA+6KqkpaQ3W6J/en7yMPHQwsHp//f6Ij1NeX47HZZJEZ6SYAW6Foqi6KMYtFiJB6ovA1SYRev7J4ImyjqYneVPmC9GXBALWfWFJOrYeM2vXmuwiVq66Ko4lU3QAqjdZrxt+UfvP1t4gYDOwqZIz88ai3YtQKFy42FyxGa9fUvJ2V9w/SmT2skikcMEbHk8SBG8EwnyQpeY50w4hRIuTga1a6+1aay8wE5jWYZtpwDPaWAoMUEoVhtl3GjAj+HwGcFHLwZRSFwHbgXXxeUtCxE+o4A2PU/dOOkQj3M6nfH//ffvgjeHD4RvfiM+/TUYG3Hijef7OO6EDRH74w/gMDKakmBt2IYToDWbNgptuir5MSiQaGqCx0Xqdo5MMvDapolLzgpmthBDJriXzhkazvXK74+cvqS3BFxxkyMvIIz8jH38w3ffBxoPoCKcgF9cUk+Yx3937p/fHhYvmQLNk3hC9R0Nx+yn5/SY4niVSdJ+Mdwmwz/je2zNvfPaZ9ZhbejqcfHIcT1y30z5wYeS3wd3bZhHZ/RJ18Sbx9SHwgorwEX1n4fvb3zeBu8oE4H5e8nnX2ilaxTV4Q2Yvi0QLVzYlKTJv6DCN9OQ40w4hRIthwJ42r/cGl0WyTah9B2utSwCCPwcBKKWygFuBO2LUfiEcZTfbABycNaz92N7AOBx9rzWsWWO//vLL43sj3zIr/N13odamFKjbDb/9rcm+EWvZ2SajhxBC9HQffwxXXBGfwI1w3G4HZ+01V1kvl0kEQvQIWmv2VJtbUI/Lw+aKzY63obimmEafiUYblDmI/Mz81hmXLuVqLYUSTlFNESr4nT4/I580TxoNzQ0JKwcjRMw1FEGgTeRm1sjEtUV0iYx3iRZaW/eFJXysKc4WLbIuI3nccfaB6TFx4HOb4A0F/Y6M44kTxC5QJdxYop3G0ig2ji6AX2vdLlijydfE4j2LozqG6Cze3QEye1mIcMJ94Dqc6l0IYTkC3HGo1W6bSPbt6A7gb1prm2HW4AmVul4ptUIptaKszCa9tRAJkDyZN2yul8rZ4I0dO0IHZ/zgB5AZx1Kc/fqZn0uW2G9zzjnxLW3S0gYhhOipNm+Gb37TumPSCY5OMrBLyZuWn7RpeYUQh5TVl6G1RqEI6ABbDmxxvA27Du7CH+zbGpI9hJzUHALBzD1p7jRKaksiOk5xTTHNAZO+rjC7kBR3ChrNtspt8Wm4EE6r290+A3PG0MS1RXSVjHcJwD7DRqg+st7giy+sl594osnEGjc1W8BvcXOWfRjoMOn3eyLb4I3ky4zYMXC4yd/E+9vfT1Breo94jwrL7GWRUOEGjfz+JEhj1ROCN4YMMd86kvUxZEii/4VE77IXGNHm9XCgY55Wu21C7VsavFkj+LOl+O8U4C9KqZ3Az4HfKaVu7tgorfWTWuvJWuvJBQUFXXhbQsRH0gRv2GXecDh4Y/ly+4wjo0bB6NHxb0NTE+zebb/+u9+NYx1S4hucIoQQ8eb3w2WXJS5wA5yulW3TAZjSz/FrqBAiepsrNpPuMVG5AR3gi31fON6GHQd3tD4vzClEKUVWqknx5lKuiMue7KnaQ0NzAx6Xh2H9hrVm4dh5cGfM2yxEQtRubf86bWBi2iG6Q8a7BBA6eKM327/fevnpp8e5L6h+j3WQRu4JEOiF/+ixzrwRR0v2dp49tmzvsgS0pHeJ9514wmYvqxDhbUqp6zEpqxg5UtKT9Wbh0rX7fMkQvBEqWk7R5TpWsVQaTVqlBEj29omeZjkwXik1BigCLgeu7LDNLOBmpdRMTPBFlda6RClVFmLfWcDVwL3Bn28BaK2/3HJQpdTtQK3W+tE4vTchYi7UjIKAUwHhIac1dKMRrw+JMrWgi8Wf+m3LlVx6qTPfO9asMZk1mps7r3O54KKL4jsw6FjQjhBCxMHDD8OWLdFfwwYNgvx88zlfXm4eXWVVRzpu7O5HlSc5JhIIIULaUrEFX5sMOuvKnJ+YXVRTBJgsGwWZZqJBv7R+VDdV49d+Smoiy7yxvXI7Gk2aO43hOcNN7XSIOPhDiKTX0Obe0pUG7jimQxTxkpTjXSBjXk7rq5k3DhywXj5lSpxPXLfLenneZPDEcXZSotgF0QcsOvoS7MMdH1LXXNduWb2vnj1VexjRf4TNXiKceHetdmf2cmqIfUuVUoXBgbKOs5e/o5T6CzAACCilGjsOgmmtnwSeBJg8eXKih+5FHPX4zBsuD2bQSdLVCuEUrbUvmPliDuaP799a63VKqRuC658AZgNfB7YC9cC1ofYNHvpe4GWl1HXAbuASB9+WEHFjd8MKTs44cGHb59GdCPyoAjcAAsyfb//vcc01zmSlWLnS/t/+9NOT4LuPEEIkqX374LbbIs+6cfjhcMUV8P3vw7Bh4A1mQk9NhT17YMYMmDkTtkWZ8d/vN8EjjmTgsA3ecJMUEwmEECGtL19PXXNdQrNUlNWZsp4p7hTyM/MByE3PZW/1Xhp9jRGXTWlpu9vlZuSAkTT7zQBFWb2UDRW9hK9NlH/GUPA3gqsXDjr2bkk53gUy5uU0u74wr7f3Bm80NFhPEkpJgRHxHqNvsPkuUXAauHrh2JnLZmCz+aCjzYjE/F3zOy1LcaWwZO8SCd7ohngHb8jsZZFQ4TJvNDYmwQBGqKu5DhCzDrOoZw8L0XdprWdjAjTaLnuizXMN3BTpvsHlFcA5Yc57exeaK0RChQrecGzmsHKHyGTlXEpBf8DFxo3W69LSYNw4Z9qxcKH9wOOVV0JWljPtEEKInuaXv4zs2pWWBvfcAz/6kbkOpqWZ5eltJtCOH28CQX73O3joIfjjH607O60kTfBGb+15FqIXWbVvVbvXtd5aar21ZKdGPyB88CC8+io8/7zJHpSdbTK2fe97JkDNitaaysZKANzKTX6GCd4YmGnKQfgCPnYdtJkt20FxrRnDVCjGDBhDk78JgPrmerx+L6nu1KjfkxBJpW3wRuZQ6xIAItnJeJcAzPd0q76wqioTzNAb7dtn7nfq2idZoLDQlO+N6/u2G9fK6qVZZlxp1subupHeMQ6qGqssM6zVemuZv3M+l068NAGt6h3iGrwhs5dFooXLvFFengTBG4TokdP+2KWqlcANIYQQcZAUmTeUG/vMG851iG3ffxgej7lp7ej4480shVQH+pyXLrVf981vSlkTIYSwsn49vPnmoewZdo4/3mw3cGD4bEotwRw//SlccokZBF0XQUUDn8/B0mN25cWUiy5PJOjSxAEXXJl8NZyFSHabKzYDtJYYyUzJZOuBrRw/5PiIj6E13H+/CTJzu9sPyqxaZZZ/73vw6KPtg9QAqpqqcAX7tTSavIw8AAZlDWrdJtJsIC0ZPPzaz+DswaS6U2n0NZLhyaCkpoRRA0ZF/J6ESEq+NhH2GcOkPFkPJONdokV6unXQ98GDzvT7JMK+fdb9SYWFDkze8lZaL0/Ni/OJEyStwHp5437r5QmyrGgZGSkZNDe1n6Wg0Xy488MEtap3iHvXrcxeFomUkRG602v/fodmM4WiwqQH0QH5Mi+EECJufD7YsQM2boRNm8wsgcZGc33MyIAhQ+Coo8yjoKDzJFy72QZgjuMIFSqCxKlGQNGBYbaBESed5Mzsi6Ym2L3bel2/fmawUQghRGcPPhg+cOPYY2HBApPBKJr7yKwsOOwwWLQITjkF2yxNLaqqTJYOZzp+bd6IDhC+DLuNLk0ccCxaRYheI6ADFNeYbBXp7nSa/E1ordlcsTni4I2aGrj4YhP8a/XdvaHB/HzhBZPd7f33YVSbGIqSmhLSPGl4vV78AX9r2ZShOUNbt9lbszdsO5r9za310pv9zQzMHEi/tH40+hrxuDwU1xRL8Ibo+fwNh55nDrOfWS2Smox3CTD9Oykpne8ffD7zPT6tF/5579tn3fU2ZEicE/b5vdZ9e8oDnow4njiB0gdiYrw6BLc3lZtJanZlVRz2ye5PqPPWWa7bdmAbjb5G0j3plutFaMnxPyxEnBQUhE5NW1aWBGmswn3QSvCGEEKIGNLazPqdOdM8du0yN5Vut3X9yowMM3jU2Gi2OeEEuPZaM3s4Pz905o39TgWEKze2gz6N+00DHUj9Xlw51DZo9Kyzws/QjoXdu83/p9X3n0mTTDmV3joLRAghuqq21gxMhsoYNXYsfPxx9IEbLVwuyMkxg5+TJsGePfbbVlY6WXrMLnjDnwxpKoUQIRRVF+FxeWgONJObkUtVUxX1zfWt2TjC8fvNd/pFi6wzx7XV0ABbt8KZZ8LOnYeWF9cU4wp+jjT7m1vLpgzOGozH5cEX8FFaGz6gq6S2hHRPOvXN9TT7mxmQPoDc9Fz21+1HoymqKYroPQmRtLRuP/iYOQrcvXB0V4g+JCvLOvi7rq53Bm+UlFj3NRUWxnmMrWk/uNPB36E+cPog8DeBx4HONqelDgB3avugPwDvQQh4kyZ44/3t7+PX5iY6xWV+CQLBspwZKRmsLF7JaSNPS1j7ejIZERZJZXXpalYWrYzZ8fLzQ9+AHjiQBAMY4QIzAmHuoIUQQogIVFXB7bfDiBEwZYpJjbxtmxkcqquD6mrrm7CGBrNvU5MZ+F+0CH7+c1P3+tRT4Z137AeY9u93aPBJubD9WuutcOxaWnKw0DbbyJQpjjSBkhITUGPlxBM7p7oWQggBzz0XOiBjwAD45BMTfNGdzI0ulznWokWQnW2/XWWlg3EToYI3upp5QwjhiC0HtpDqNp1aw3KGkeJKwa/9fL7v84j2/+UvTcaNcIEbLQIBM+u2rZLaktZOe5/20S+tHwD5mfmkBQemKxttUp23UVxT3Nrpn5maiUu5KMg0KcObfE2tGUaE6LE63pPmjE1MO4QQMZOTY728utrZdjilpW+wo8LCOPc1NVVYByukD4ZAiJnbPVnKAJNZpKPmg46Whw4loAOs2req9XVmSibD+g1rfd3oa2TxnsWJaFqvIMEbIqmc9+x5nP3s2egY9VS53SYC0k4gYAaiEsrqQ7gt70FHmiGEEKJ3amw0gRrDh8Nf/gJFRebaFy41fCi1teaGbelS+OEPrWteghl8irQzuFuUsk+V6K107GZuZ/koywAYt9vczDqhpMS+ZNyZZ0rwhhAiSbTk1k30Y8gQtDbXxzrrbK8APPGECbqwu95Fw+Mxkwweesh+mwMHun+eiNkGb/iCpVOEEMlqc8VmvH7zpX58/nh0MOBqY1mY2kzARx/B009H3yfW8bt9SU0JjT4TvZyVkoUKZrvLz8jH7TIRxQEdoKapJuRxi6qLWvsC+6f1B2Bw9mBzTn8Tu6p2RddQIZJNcw242kxNTxmQsKYIIWKjf3/r5VVVzrbDKT6fdX/TsGHdC3APS/sAi2y66YPotcHmqbnW92negyRLucmN5Rtbs68BeP1eJhdObvd67va5iWharyDBGyJpLCtaRmldKdVN1czbMS9mx7W7iLY4eDBmp+oaT4gpV2AiC4UQQogueOcdE7Rxxx0m4KKhIfw+0aqttZ897Gjad4/NlAdvZXD2cPztLBtjuXzQIIeCWDCzIe0Cc0480Zk2CCFEWKXhU+g7orSUJUtCl/n6ylfgG9+IbfBbZiZcfjn062e9vrLSPotS7Nl0CzVXBTtKhRDJat3+dTT4Gkh1p3L0oKNbgyjCBTr4/XDdddaBG8cfDw8+CLNnm+COr3wldPXBXVW78AVngLZk3QCTeUMFB1rSPemU1JaEbFNxTTFNfvOFOS8jD4ChOUNb128/sD3k/kIkPV9t+5njSZLyXgjRdbm51ssdDcR2kNVkJXCgRIxdpglXL6xN0yJ1gPXyJJrovWTPkk7Lvjzqy6R7Dt04LytaFrOJ+n2NfEsQSePPC//c+vyuBXfx1cO+GpPjDhxoZhnbKSszKeQTJn0wVK21X9+YJB2bQgghegy/36RBjmY2XX4+HHUUjB5tbrwCAaipgc2bzcOuHAiYVJGVFtmQHU37ntIfGvd1Xu517q55T8Vwy+WFhSagItOBMpx79lgHiihlgkiEEEK099//2l8r3W5zLQ2VzbGr0tNN+bE5czqvq6x0sLyn3eBR0wHHgh+FEF2zqtSkqk73pDM+b3xr53hzoJkDDQdagyA6mjmzc9BaZiY89RRMm2Y+f1JSzD3FpZfC2rVw8cXWcXc7D+5sfZ6bcWgUKz8jv7XmuVu5Kakp4fD8w23fy66qXa3BGwVZplzK0JyhuJUbv/azu2p36H8M0SNVV8OSJSb71eDBcMopTgYvOizQYea4SrHdVAjRMwwcaL08VGB4T2Y3KSkl3h9ndgHlLg+WGTl6g5QB1lkQG4raZ3FKoA+2f0Bd86H0lYflHsbRg44mzZ3WGlDs9XvZVbWL0QNGJ6iVPZcEb4ikUFRdxJxtptdKoVhWtIzNFZtD3thFavDg0Os71ut0XMaw0OsbQkSeOKU/kMzpvsL9JwshRB9SW2s6XZcuDR24kZIC55wDV10FF1xgAjYaGkxnWcvsOr/fPM/MhL174dlnTWfv+vXtj2WX5coqoCNuUq07p/FW4tTNXGnVEMvlQ4daLo6LHTusl+fnm1kSsUj5H08+H+zaBVu2mMe6dea7WlOTCQRKSzOX/YkTYfx48xg92oHOAiFEr/Xee/aBhhddBAUF8TmvywVjrBM2UVXl4OdaSn9oKO683MHgRyFE12w9sBUw/Wgj+o9gYOZASmpLSPeks6ViC1OGT7Hc784725eKSk2FhQvhyCPbBxu73SZI+8QTYdUqOPbYzgNSe6v3tj7Pz8hvfZ6XkdeakSOgA2Ezb2yr3Nb6vDDb1BscmDmQNE8a9c317KtNdOediKXt2+H//g9ee+1QsGLLd/2f/AR+8xvIsKmK2XMFaHdfKpk3hOjx7CbIrF9v+tN6WzCa3T1TXEumgH3mDdWLP0dTc62DVhqKweVUlH9on+z+pN3r44ccz8SCia2BGwAel4cle5ZI8EYX9OLfbtGT/P3Tv7dG5AM0+5v5y6K/8PSFT3f72MPCxEasWgVf+1oCL6aZ1rN0W9XtNlF2drWInfAP4MpuTJ0OlWOzhaRPEkKIbvP7TeDGokWhI+J/+EO46y5zg5WTc+hGK1Sqw9Gj4ZZbTEaPzZvh5pth8WKzLs8mbsLRtO9p+dbLmw44FpVeWW+dM7Ow0LlBuL17rZcPGWKyfyRjJ2h5uUnNPXOmqb/udpsgk6Ym+4wvaWnm4febx5e/DFdcYQKRJMOIECJSpQwKOTPullvMdTJehg831+COtaO1NgGV8cj40Ynd9dN7ILH3oEKIkHwBH2X1ZYDpQxvebziFOYWU1JYQ0AG2HLAO3li/HnZ3SGLx3/92DtxoKzXVpIZ//3046aT26/bXHfoQHZR16EtYfmZ+ayaNJn8TJTWhgzfaZtYozDHBG/kZ+XiCA9wVDVJSuLf48EMTHFlXZ65/bb/v19TAvffCK6/A3LnmHqbX6DiDWoI3hOjx7Poetm0zn3F2JRJ7Krt+LbtyKjGjbDoWu5ol8PUhUWa7d8GVDmckTO0PAYuayDoATWWQ4eAsMQuVDZWU1h36N0xzpzF56GQGZQ3C4/K0fges8dbw8a6PueKYKxLV1B5L7sRFwtU31/PEiifw+g99GPm0jxfWvEBlQ/en7IYribJqVfsZB47LGBK6PlfTfvCHyFUvhBBCBP3ylybjhl3gxplnmqwG995rOmD7948uQj4tzQwkHXec6bx97z2TJtIuVWRlpYMzh9NtpkZ7Kx2LSvf5rTvghg1zLmjCLqNYYWHyxUkuXGiCLoYNg5tugnffNZ23dXVm1nmoUj1NTSbNcl2d2W7uXPjpT2HkSJgyxXQKCyFEOB/xFdvyJEccAUcfHd/z5+baB046lr0qzeb62VSRNCl5hRCd7Ty4kzS3+QBp9DdSmF3ImAEmnU+dt46N5Rst9/vXv0ymsxZf/SpceGH48n6pqTB2LPzsZ+2Xt82IMWfrHMY8NIYxD43hiEePaJ2k5fV7eW/reyGP33KcFFcKQ7LMiP3AzIGoYKYCv/ZT01QTupEi6c2cCd/4hgnS6Bi42KKhATZuhGOOcbZtcac7ZN7ozTPGhegj8vKsSx1u22b/GdeT2d03xT14wy7Yza6cSjhRBW6AyZzkMHc6tlmE63Y52hQrnxZ9SkbKoY7ONE8aRw86GqUU4/LGtdv2ox0fOd28XkGCN0TCPbPqmda6nB09ufLJbh9/8GBTT9jOmjXdPkX3pA8KPajUuB8C8b4CCiGE6OlmzICnn7YvlXLrrfDOO2YQv7uziF0uE8Rx1lmwYYN99arKSgfSJ7ZIL7ReHmhyLAgyELB+s3l5zv072A32FRYmT8rOuXNN+u2pU+GTT0xGkNra7h+3ttYEdSxbZgYhhBAinNlMpcZmLPBnP4t/qancXPtzbN8e33O3Sre5iHsrQ08yEEIk1JaKLa1ZKfqn9cftcjM+bzwAGs3n+z633O+559oPsvz975Fn+cnOhj/84dDrfbX70Bzqz6v2VrPz4M7WR1urSleFPHZFvcmskeZOY2CmiQwfmDmwNQAkw5NBUU0SlBUWXbZxI1x3nQnOCMfnc7gEpyM69n2HyVL8+hB4Qdk8kuTGTog+LjfXesLS9u2hM9v2VB6PdYL1uH9e2wW7BZrp/Nnai3hsImurNjjbDgsLdi2g1nuoI8/r9zKxYCIAkwontdt258Gd1DeHqOstLEnwhkgorTV/Xvhn6po7p75o8DVw/+L7W2tkdlVBgX1UIJjU7wlNIZ4+KHQ62oYSevVFSAghRLfV1JjawHaBG3/6E9x2W+zTr6elmawbgwdb38BpDaXRBrR3uTH59sGQ9Xvifnp/wIW26YBzLPsI7WdStjVkSOI7Dyoq4JvfhIsvhs8+i2/ms4RmVRNChGcX9eewD1zn2667/PLQ95GxkJtrH9y3dm18z90qoxDLASTtNwGQQoiktLlic2tN8cHZ5jN11IBRZHhMB9em8k2d9ikqMpnLWnz1qyZrWTTafmatKY18NlR1U7XtupqmGvzB1Odul7td8EZzcDKTS7korimOrrEiaTQ0mPKGkQRutPA7nKE+7pSLdv274WaMh5wZ3gun9AvRA9kFYu/f7+BEJgelp1u/3z17zKScuHF5sBwfayqP40mTQMoA6+VV68Gf2Pu0D7Z/0BpgC+Z72pBskzntxMITSfccmk2fkZLBiuIVjrexp+uFHyGiJ5m7fS6VjfaheV6/lzc2vNGtcwwaZD2g1MLnMzewCZNW0LnuYVtV68CdhAXqRcL87N2fcd8n9yW6GUKIJPLAA/aD9t/5jimnkp0dv/OHSvu+bVv8zttOWp59eveazp3Xsebze3Ap6+u5k8Ebdp2c2dnxH4QMZfFiOPxwU24nVGCFUqbsyZ/+ZMrybN9uOnl9PvNoaICdO81x7r4bTjutd3aKCNHr7dtnIvyifYQS5bFK92kOpFgHkRxxhDOf3Xl59uvWr49ukKvL0vLtM2w0xyAtkhAiLtbsX9NaT3xkfxOBMbzfcFLc5sNrb/XeTlluFy1q/9l2zTXRZ+Rre09hV5rFSlOIQYbimuJ2nfwtwRu5GbmtJZb92k9RtWTe6KnuvRdKSpKvjKOzOty06N4WnSJE3zN8uP3nWkmJs21xwuDB1n1/+/aFLnvbbSn9rT8zG0t7dwmqrNHWy+t2RJ9h2C7bYhf4A37W7G8fwHtY7mGo4CDsxEETW0v7ATT6Glm8Z3HMzt9XSFenSKg7F9zZLr1Oiiul9UYToMZbw50L7uzWOYYNsx/QarF6dbdO0T3pg0KXRfFWgl/SCgmjsqGSR5c9yp8W/KnbWWmEEL1DZSX89a/WAzxDhsB//xv7jBsdhUr77tjM4dRcUDbpYytXQSC+nWNK2fdEOtlJaVdXNZGBG++8A+eeCwcO2M/GGD4c/vEPOHjQBGZMnw5f+xqMGWNmd7jd5pGeDqNGmeP95jcwe7bZ51//gtGjHXxTQvRkQ4aYSKlEPoYMSfS/Atu325fXPPvs0BMAYiU31z7obutWUwoq7lJDBD/W73WgAUJ0ppQ6Xym1SSm1VSk13WK9Uko9HFy/Wik1Kdy+SqlLlFLrlFIBpdRkp95LvLTNejEu19QWH95veOsypRSlde1n7n/0UftSdWee2b02bD2wNeJtAyEmLRXXFOMOfo/3a39r8IbH5WkN6mj0NUrmjR6qosJMNrC6Xx01ynzvf/BB+MEPor9vfXX9q/xj2T9i09B465h1WUpkC9HjHXaYfbC1YxOZHGRXjrekxL4vKibSB1sHKzSWgtvmhq436H+U9fLa7WErb3XyrX1wpe786IL1ZetbS/e1mDTkUKmUiQUTW7PDgZmgP2fbnC6dqy+T4A2RMBvLN7KyeGW7ZS6L8iHbKrexrGhZl88zZkz4tE2ffhrn1E6hpOZDIMzJqyKfzSB6t8dXPE6AAPXN9by6/tVEN0cIkQRmzbIfYLrjDusbq1jLzbU/z8aN9uVcYio1F9u7l5otcQ+E9Lh8BLT1V+tmB/vlki1445NP4NJL7X8H8vJMgNHmzabDtl8/84hkxntKitk2Jwe+9z0zS/3FF03WNSFECI7Vs0ruNuzcaf+ZeeGF8Q98BPMZaHeN2LbNmWs4qXn2ZTyrnIrAFOIQpZQbeAyYCkwArlBKTeiw2VRgfPBxPfB4BPuuBb4FLIj3e3DC9oPbATMJ6rDcwwATvNHkM1Ffae40NldsbrfP8uWHgorz8kyZ4e7YXbU7qu0P1B+wXF5UU9RaNsXr87YGbwD0T+sPgC/ga33Pomd56KHO11uPB558EjZsgNtvh1/8wmxXWmruHSL1m7m/Yfq8TvFdyUm5aZf2XyZkCdHj9e9v39eycmVyln/SWnfKzBWpIUOs75/27YtzRlRPpnWGDX8j6F4cCNfvKOsMiVUbEpqpf/GexQTa/CKkudM4ceiJra8LsgraTdAHWFm8ssu/d32VBG+IhLnvk/ta0x+2GJs7lkmFk9ota2hu4M8L/9zl87jdJpI7lFWrHEpJa8XlNhegUCqWxjl8UfQEXr+XBxY/0Pr69o9vl4ueEILZs9vPoGuRnw/f/779rOJYys+3X7d1q0MBkmkD7cuQ1WyNe1pal0ujrGpwksAA0TYScblYtw6mTrUP3DjrLNiyBS6/HDIy7EvvRCI11Rzj4otNIMj553f9WEKIvmHnTvt7wFNPdaYNeXn2n8+7dpnPtbhLC1G7pXJVwuspRyXgh4Z9UL3Z1II+uA6qN5kMIjLDuSc5Gdiqtd6utfYCM4FpHbaZBjyjjaXAAKVUYah9tdYbtNbxr6XngEZfI5UNpgRxuie9NeNGfkZ+axBEc6CZLRVb2u1X3CZxxamndr8fbHd1dMEbq/dbp70tqi6isdnM0PRrP/3S+rWuy83IbX2+o3JHF1opEsnnM0EZbdPpu90wbx5ceWX7e4DsbBM4+e9/w69+Ff7Y1U3V7Dq4ixpvTadApaTkyWx/T9qbBxyF6EOGD7devmgR1NQ425ZwAjpAv3v7ccVrV3Rp/yFDrPu3iou7158TkdRc6+XeyjifOIGyDwO3xT9soAlqE/ed6IPtH1DvO9TRl+ZJ4+hBR7fbZnze+Hav/drP9koJwo1GLy4IJJLZgYYDzFw3s/WmEiDdnc41x1/DgPQBrCldQ12zKYiu0czZNoei6iKG9RvWpfMdf7wZPLKzaJEzg1u2UgeAL0Q94crPwV8HriiLkYpeZebamTQHmnHhIkCAvdV7Wbh7IWeMOiPRTROiR9Iaiopg0yYzgFxba25C3G5z01FYCEceCePHQ2aYGLtE+ugj6+VnnmnejxMDP6NG2ad2d2zmcNYY++watVu7lkoxfbBJwxghlyuAP9A5Nnr/ftNxaVdaJpZcLut4Tyezf4D5+7rySqirs15/8cXw7LOxn9melmYer0pyKiFEGBs3WpfXzMpy7rqvFAwdagJJOmpuNqnmB8euPLG11Dz7AMeaLWZGm1WnYSJ5K+HASqhYDqUfQ+02aCqH5hpwpwZn5rXJxqX9EGgEd6bJfJk1AgrOgIFTIG8yZA5N1DsR1oYBe9q83gtMiWCbYRHu2+NtO7CNzJRMarw1uJSLEf1HAKZUSn5GPqV1pdQ317O+bH3rPlpDefmhY5x5psle1h0lNSVRbb+hbANnjT6r0/KtB7bi0+YDOSMlg73Vh0o2Zadktz7fdXBX1xoqEmbBgs5BivfeCyeeaH8fkJUFf/qTyZIcyrtb3kUHg+ff2PAGt55+awxaHEeenPaBhP5EzSIUQsTSuHGmX7GjTz9N8HiThTlb51DrrWXWpll4/V5S3dGlaM3Ls75/qqoyk3biGsCRVgCN+zovry+GjF76XT57jH2k//4F0O8IZ9sTtGjPonavm3xNTChonyTvhMIT+Hzf562vXcrF4j2LGZs31pE29gYSvCES4okVT6A6pjZXcMnES8hKyeLmd29ut0przd+X/p37z7u/S+c75RSTVt5u5uvBg2aW5jHHdOnw3ZczPnQ94YNrgG5m3ohyAEokF601d8y/g1pvLa5g0qS65jrumH8H866al+DWCdEzaA1r18Irr5jHjh1moDs11VwffD6T0tDlMo+Wm476elMW5NRTTSaLqVPNrCDAhJ0nMPV7BXlUUQx0vkM677zud8hGasgQ+3SQjs0c9mSApx80W0TdN1XYZ+UI5VsWN4YtXuhcoiXN00S9t/PX6+JiM9ssO7vTqphzu61vpp3O/vHSSyZwx+o+8ytfiU/gRltOlDsQQvRsm20m6Y4aZWajR1K+KRbGjbMO3gATYBL34I20EGU8azbbl1RxWtVG2P0SbH8GGvaYVMG+hs4zl63qYbfw1ZpH/S4oWwwp2eD3QkoOjLoMJj8S3/cgImVVB6/jNwq7bSLZN/TJlboeU4qFkSNHRrOrY7Yc2IIK1k1sDjS3Zt4AKMwppLTO3J98se+L1uWVle1LLU6e3P0A66qmqqi233rAelbV25vfbn1e563jqMcO1XhvWzN9a2WIWVkiKT37bPtg7pNPhh//OPx39cxMeO21MMde/Wy758kfvJHVPliyToKRhOgNjj7aZMTt2PdRWmoybyRTAMefPzHZ7Rt8Dbyy7hW+e+x3o9pfKVMq5oBFFbTVq01gaNxkFELVms7LKz6FvEnJc88SS9lj7AP9yhbCqMvNfYyDyuvLqWioaLfM7XIzOKv9TeuJhSfy4poXafCZ9td6a/lo50d8/7jvx7V9Wpv+1+Zm8zwlxfRJ25UbT2a98De6lxkyxPxmJfNjyJCo3lKzv5m/Lvlr6x9ui5H9RjJ6wGgKsgo4dvCx7dY1+Zt4YuUT1Dd3rV790UeHHzh67TX7WcNxl38KIf8cqzaYWULd8a19cKW2f4ik9uGODymt7TxAvHjP4p6RHlKIBCorg1tvNTNbTz0V7rvPDIY0NZnBmaoq87O52WQs8PnMQHdNjXn4/WaW2ttvw3XXwcCBcPbZ8O67JDRwA6CafqRgnVJh/Pg415xso2XmsJXmZlP/0hFZITrYq+OfJTsv27qOd0mJdUBFPNj9n9fUOBfA0dwMP/mJddaNnBx4/XUJrhBCJN5um2z/o0c7W7Hy2GPt182d68Bnd0p/bMe2a7cntJ4y/kbY8iS8NQbemwTr/gx1283M5ebqbqacD5hjBBqhqQw2Px6zZotu2wuMaPN6OFAc4TaR7BuS1vpJrfVkrfXkgoKCaHZ1zNrStdR5zRethuYGKuorWLt/LWv3ryUv/VAppI3lG1ufHzxogtZbxOK7WJMvuk40u8wZlY2Hgq81mrrmutZH24y9AR3AF3DoS7XoNr/f9LW2vab+7W+RB/aHyoLV5Gti3g4zkcmlXGw9sDXqTDCOUwpcbf4Ia7aB/D4L0eMdfrj959WyZc62JZQtFVtYUbwCVzDIoSWQI1oDB1ovnz8/zv1emSOsl1d8Cj6blK89nSfLfkywIjG/XEv3LiXd0z4iaVzuuNag4hYTCyZ2yuwyf+f8mLalrMxMHLvhBhM4NGqU+Y6Rk2N+TwcNMsFGqakwbJgZE7jmGvjXv+wnTyQTCd5IdgkeFIpIlG18bcNreP3te6DS3GlcffzVra9/cPwPyEzp8MGk4dlVz9IVxxwTPjBj9uwEBm/kHm8+jO0EmqB+j/160evdMf+O1lJCbfn8Pu5ZeE8CWiRE8qusNEEbo0aZOrv79pnB5O4MgtTUmGvFRx/BJZfErq1dFcCFshlwcSpwo8XYEJnvPvnEoUb0P8p+3b4P4t45NmSAdYdhcbFzUd52M8VLStrXmo6nxYvt/85uv739wIEQIgHinsqhZ7Sh0qY88ujRzn5OHXmkfYfvokUmA1hcKQUZNuVJA17wVlivCyW9m/+/OgBbn4Q3hsFnv4S6nWbWWccMIcoF/SfAmKvh5CfhgvVwSTVc1gBX+Mzjska4pAYu3AGnvQjjfwz5J7UfQAPAJoWYSITlwHil1BilVCpwOTCrwzazgKuUcQpQpbUuiXDfHu8/X/ynNahBozlrxlmc9u/TOO3fp/HJnkNfvItri1uDHZqb238fjUV5KL9dySUbu6uto+aa/ZEHYm0qjzwg+64Fd/HCmhci3l7E1po17WeiT5xoylpHep8aKmvhRzs/ItWdikLhVm48Lk+7DC5Jq21AZEOxlE4Rohc47DD7Ernz5jnXDxPOg0sexBfwtWbD33lwJ8uLlkd9nNGjrZevWGFfNjcmskZhOZxd+QVRJlnrWTJt7tOqN4NyokZ1ewt3LaS2qbbdshMKT+i03cRBEztN3t9TvYdab22nbaOxaxfccguMGQPDh8MPfwj//Kcp07Z7t+mz9/vN996WLNs+n+mXXboUZsyAn/0MJkwwXRLXXQerVnWrSXEjwRvCcXctuKvTH6lLubh04qWtry8+6mL8gfY3gbXNtdy98G60XZ2nEAoLw98crFzp/EBXqwHHEPYis+dNicjuo9aXrWdF8QrLdT7tY+a6mZTXl1uuF6Iv0hoefRRGjICHHzZZNeIRnBfXm5IIZVOLz6YKXlGRs20JVXrsww+htnvfzyMz4NhgnXsLZQviHo0/Mt860LKkJM61P9vIy7NeXlLi3Ezy//3P+u8jJcWkSY7FYIEQohv27TMXy2gfoUR7LMdSMtmzmxk2ZIizn1Njx9oH3i1f7lBbcg63X9eVzFWhsj6G07gfPjgLVv4SvAfA3+GColww/CI4dzFcWgfnLTHlTsb90ARxpuSAO910Zio3uNNMeZTs0Sa18An3w1fmwqU1Jthj3PXdz3IpYkpr7QNuBuYAG4CXtdbrlFI3KKVuCG42G9gObAWeAm4MtS+AUupipdRe4FTgHaXUHAffVkwV17ZPJlLdVN366DhZ6tO9nwKdP8a7G1h8sPFg1PsU13ROguIL+NBRDLqsLl0d0XbVTdXc/vHt/PTdn3apH1F03/Ll7e8/brkldiXJXlz7IjVNNWSmZOJ2ualrruOZVc/E5uDx5GlzvWkoal9GRQjRI40dawaKrSxdGp/+yGj712q9tTyz+pl22asafY3ct+i+qM99xhnWwSorV8Y5AD57jPXk56oN5rt/NLobaO6knPE2KzQctCgjE2cfbP+AAIcu7umedCYPndxpu4GZA0lzt+8IzUjJYFlR1zKGfPQRfPWrZuLDQw+ZzBktWbOjVVdnxgr27zfBHF/6UpeaFHcSvCEctXTvUnYc3NFpeWFOIePyxrW+HpI9hKMKOs+erWysZO72uVGfVymTPj6UQMAMLjktEMB8CPvDXMmLZvXeFFAipLsX3N2uA0ZZlPF95FOpzywEQHU1TJ0K06ebL2PhItwzM83sn8sug1//Gn7/e7Pvj38M55xjonhDSvDM4UHsJ0VZd/i8/37XvsR21ZFH2qfAXbIk/LhfTOSMt0/vXr4k+hu6KB1WsN1yeUVF92uKR8qumt2+fc5l/5g1y0S6d/SlLzlXuqUvUkqdr5TapJTaqpSabrFeKaUeDq5frZSaFG5fpVSeUmquUmpL8GducPm5SqmVSqk1wZ9nO/MuhYgdu4A2p+tSjxtn3+FbV2df3iWmck8Ai3sMAErmhL9XjZUDK+F/R0L50s5BGyiTYePiYjh1BhScaq7rKf2iq/XsyYLU/ibzRv+j4IQH4FulcMztsXwnopu01rO11odrrcdqre8OLntCa/1E8LnWWt8UXH+M1npFqH2Dy9/QWg/XWqdprQdrrb/m/DuLjUZf5NN4F+5eCJhB87bfx7ub1WdNafQDBlYBH1sqtkR1jEgzbzz12VP4tZ+Khgo+3JGAzj7BggXtf8+mTo1N8EZAB3hr41toNE2+JtzBmcfLi5dT3VTd/RPEU9uBx/oiE5AohOjRhg617+eIV0BDtBOQZ6ya0Wk8IaADvLPlHfbX7Y/qWCeeaB1cXlwMB6wrCcdG7vHWy7UP6qzLstmyCzRPRv0nYnuftvdNU2bSIb6Aj3Vl69otS3OnMbFgouX24/PaD8jWN9ezaPeiqM65c6cpXf7Nbx7KZGP395aeDiedZPrzL7wQpk2Dc8815VL697fex+93INNlF8k3BOGoPy/8Mw3N7dPlpLpTufq4qztta1U6pdZby10L7urSuU88Mfw2r7/u7EAXBM/n8kCWTd2uFuWLwS15xvua0tpSXt/4ert0pB63h6yUQzd8jb5GHvr0oag6cITojXbtMnXjP/44dFaMYcPgpz+Fzz4ztZ8//hiefBLuvhvuuAPuvBMeeABefRU2bTJp1f/9bxPh22kAPsGzl5XWfOk863yyH31kn7oxHsaOtb8pXb/eobbkjMP2pqapwjziaET+HssMG1o7V09xhM3XCSezf5TYlJs++eTIa1yL6Cil3MBjwFRgAnCFUmpCh82mAuODj+uBxyPYdzowT2s9HpgXfA1QDnxTa30McDXQtdqGQiSQXfCG06Wdhg8PHdj28ccOZE7qf6R99on9C53rFJx3LngrQXeIZknLh3PmweRHzUy5lH6xO2dKjsnMcdSvY3dMIeKouLpz9opQPi/5HIB+/doHinW3o3pTRfsgCrdyk5mS2enRVpOvcyBYpJk0Wmyt3Bp2G3/Az18W/aV1oOrOBXdGdQ4RG4sXH3o+cKD5HYyFZUXLCGhzYRw1YBQnDzsZMANI7219LzYniRdPm3v3hmJwOXSDJoSIG7cbBg2yXuf1mkC2WKuIomtLa81fPvlLazl21WFWzxMrnojq3JMm2U+Ue/FF+6D0but3JARsTlz0Tu/NWN/vcOuMIwBFbzv6vteUriG1w/hko6+RiYOsgzdOHNp+QNYX8EU1MX/GDDj6aPM3ZNXP73bDlClw222mbM/BgzB3Lrzyitn3v/+Fl16C2bOhtBQ2bIC//MUEdzg9YaMrJHhDOGZv9V7mbpvbKR2iW7m5bOJlnbb/9oRvdyqdArCieAUbyzdGff6TTgo/YDBrlrMDXdDmfAOOD71hoBnKFofeRvQ6D336UKcUn4OzOs/09wf8UstV9GmVlSZ135499ikJR4wwX942b4Z77oETTjAzf/r3Nx1Jqanmi5/HY6LIBww49POqq+C112DHDrj0UucyGETim9+0vr7t2WMGfOzSwsfauHH25woEYHV0/bJdkz0W/CF6oss+sV8XA4W5JbYBEouiCy7vMrv6owcOOPcdx+5mPTMzdqmSRScnA1u11tu11l5gJjCtwzbTgGeCs5WXAgOUUoVh9p0GzAg+nwFcBKC1/lxr3TJ6tA5IV0pJ77PoUeyu5VaZg+LJ5QqdyOvjj+Nbeqy2FlM2xWVzkahYFvfMVa18FjOmUwbA+Z/BwC+ZIIt4sesUFSLJzN81P6rt1+5fC5jB87afb6tWde/zrn9af9LbfDacN/Y8/v61v3d6tE2ZneLu/EVwQ/mGqM67uyp8OqK3Nr1FfXM9rmBWg2VFyyLO2CFiQ+v2maNOOsmkKI+Fl9e9TH2zuec7Z8w5TB03lVR3KjXeGp5f/XxsThIvqW1qXDZXYTvxQCQ1yXgoOpo0yX7dCy/EdrJwc7MZkI7Uhzs+5EDjoZQYLlzkpJqsdY2+Rv6+9O80+yOPuBg0CLJsvja/8kr4DMhd5vJA1mjrdXtes8ja10vkhZiRXrUO/DG6uEbgwx0f0tQhI6NLudhSsYVFuxd1evRP69+pdMqK4hURlbO7/36TFbuurvP31cxMuP12qKoyWadvu81M3E9LM338ubmmL3/AgEPP09JMxuhf/ML07x88CP/6FxQUdOdfJL4keEM45sElD7arh9RiUNYgjhh4RKflQ3OGcnh+59q7Xr+X+z6Jvh7XsceGHzCorIR333WuJnxzMzzfcl8x8BSTujWU3S9L6ZQ4aGgwacz+8x/zYX/VVSYCb+JEk36+f3/IzjYXhqwsM8g7cCAccQR8+ctw+eWmdudjj8HChebDPybtam7gkWWPtLsoprpTueb4a5h2xLR26c5qm2v50/w/SS1X0TM0lpl02Dtnwrp7YMm1sPA7MH8aLPgWLLoCPr8Vtj4JJXOhekvISGKvF772NZMEw+rz2+WC//s/2LjRlEfJzIy+frzbbf72R4yAp5+Gdevg8BDl4Z30jW/Yr/v1r50rUzFiROhanh984EAgSUpO6Lr1+z6A5vhdR4cOKLYdDFy4ML6Dby2GD7fPsLFvX/zPD/az1quq4lPvVQAwDNjT5vXe4LJItgm172CtdQlA8KfVnKJvA59rrTv97yqlrldKrVBKrSgrK4vi7QgRf3blrBLxOXXYYfbrPvnEgeC7nMPts2sEmqBmc5wbEKQtRpJPfxnSB4Fb4sOEAFOOOBp7qs0lXinIazNu3N3AsNK60tZx51R3KueNPY8fnvjDTo/8zPzWfZr8Te1KwgJsP2BddtBOJMEbd8y/g1pvLW7lJjslm2Z/M/d+cm9U5xHdU1nZPq3/lCn2g33R0Frz0tqX8Gs/Oak5nHPYOXx51JdJ95hAornb53b6HUsqHQcevSGmz6cntkSrsCYZD4WVr37Vfib/O+/EdhJLY6PJFBypez65h1rvoQv+Vw/7arvPSV/Ax5sb34yqDccfb718+fI4Zt4AyJ9ivbx8Mb12qLvfBDOp287ul0Ovj6EHlz7Y6Rrb5G/ighcusHw8vuLxTsEeDb4G3t/2fsjz3HGHCc6wCvqcNs0Eh/7614fG6aLJMuzxmLG+tDS48kozSfNnP4t8fyf10t9okWzqvHU8ufLJTn/cKa4UrjruKtv9rj3+WjI87acT+7WfmetmcqAhuiJakydHNoD10EOh0+3HktdrBvwBGHAMuMOkBil+D/mz7b49e+Cf/zQDnsOHmw/5s8+Gn/zElE149ln48EOT5r+0FKqrze9EQ4NJLVpTY9KTbd5sOlNfeslEA/761+aYgwaZ4I4zz4Q//9nMNu9KTMV/V/23UzCGW7m58pgrufr4q8lObT/zrKKhgjnb5nTnn0YESRR9jDUdgN2vmSCN14fCmyPgo/Nh2fWw+v9gx39NlHTRLNj7BuyaCRvuh5W/gE8ugfdOgFdy4IOzYONDcHBtuz+q66+HtWutP+P79TM18X7zGxOwEYuyETk5JnBj5cruHysWRo0yQSlWA+br15vPJyeCBjweyM+3X2+X5i7mQpUh2/9RXNOmjMjfY/tdY/lyZ4JDCwvtgyeWLYv/+QHGjLFe/sknzgUT9UFWv9gdv33YbRPJvtYnVWoicB/wI6v1WusntdaTtdaTC5J5SoPok+yCNyornf+sOuYY+3W7dsH+6EpRR6W2FlOWRNn8gwCUzElMKuKcw6HgNOcyfwjRA0RbZqSuTeDy0KGHli9e3L17o73Ve1tLt6a6U8nPsL4RyE3PbX2e7kmntLa03fqdVTujOm+4vsBlRcvYesCUVhnabyg+7cOnfcxcN5OK+i6UUGwogT2vm8kFS66Bpf8P1t8P+xeAz7nZrj1Nx5KNZ50Vm8HLjeUbOdh0EDCT+04bcRqTCie1/i6muFP4aMdH3T9RvOSMbX+9bQwRXf+tfXClPvQQyUIyHopOpkyx74epqDD9QbFSXw+ffhrZtjsP7mTR7kNpYHNSc7j2hGs5feTprctqvDX8+ZM/R9WGM86wvpfS2gSWxG3i1sBTrcfPdACK3zU/exuX25SMsbPzOcdKXJbUdK6RHNABqpqqLB91NpPnXln/iu05PvkE7rvPurzfbbeZifD5+bEJCE1PN8e5667uHyse4j4KLANg3RQqf2qyiKCNM1bNsFye4k7h8qMvt93v2xO+3VrHsC2FiroeV2oqfOlL4bdbsMCkFnfC9u1t0sgPOMbMagqlfjc02hSSFyGtXGkGb8eMMYOuv/yliXwtKjJfKFoCNLqjsdEcp7nZfDFbsMBECn7pS9GPFQZ0gLsW3NXpIjckewhHDDyCs8ec3akEUa23lts/vr17b0JIFH2saA1li0w2jTeGwtJrTZBGY4n5rGuuAl8NaLtv9NqUv2iuMhmH/I2wfz6s+i3MOQVmmSmqq1fDyy9bR+OmpJhad6ecYrLnxJLbHftjdsddd7Wf2dTW7bebrBfdrWsdiVAzh+fPt7+Zjal+R9mvq9kKTeVxO/WI/D22/w/r18cmeCicwkL734UFC+KYwrKNb3/b+v/6s8/if+4+bC/QNnJpOFAc4Tah9i0NdjQS/Nk6hKyUGg68AVyltd4Wg/cghKPsSmru3Bm71O6ROv740FnBXnghPgElPp9Jb4xSkBki+LH0I/A5EAna0eCvEGEsmRB9xqaK6Mp/BHSAeq+5ETjhhEPLS0tNVrSu2lG5o/W5W7nbZdhoq+3yFFcKJbXt+7T2VO3puEtIDWECJu5acBcNzQ2kudP4wfE/4KuHfRUw/Yj/WP6PyE9UOh/mnQ1vHWbuZTfcDztmwPZ/werbYP434fVB8NmvoL7jVy4bTRVw4DOoWAF1u7s2yycJHDwI//ufyUD77W/Dt75l0pC/8QaUB2+1Skra35OEClKMxmsbXsMXDCbsl9aPYf2GkepOZUKB6Xapaaph5tqZsTlZPGQMbT/wWBc+k4xIOkmZ8RAk62EiHX986PuHJ580Ywbd5fXCM89Evv1DSx/C3yazndfv5fxx53P1ce0nhW6u2MyqfasiPu5JJ9kPnj/0UOzvW1rHbHJPsM9cv2tmYu5XnDD4K9iW2Spf6kjwxrr96zqNRXXVhzs+tFze0GAy3Fv9Lf3+9zB9emyCNjpKpv79tuIavCEDYDGwb5/5Mt+dRyS6c/wwObgDOsA9n9xjGWmVl5HX+gXbysj+Izkst/NIUIOvgb8u+WtU9bgALrkkslT5f/pTbGuRWamuNgNqrTKGEtGf5MaHpHRKhJqb4bnn4KijTETo3/5mOmMbG8MPYo4cabJo/PCHcPPNJqvG735nAkB++lMz0/+SS8yx7Wbtgfmy0pWgkHc2v0N1U/tvdanuVK49/loAPC4PFx95cbvSKWBm4UTzZUtYkij67tDaZNl4ezx89DUoetsEa/hi9KHqbzB1DOt2Aubv0W4w+tlnTfkju9SFvcmwYabDzO4ad9llpixYrDNwBALtP+NOOME+WK2pyQRwxEO791VwGrhC/AntfAHilEpXKTjuOOt1fr8z2VoKC+1nOaxc6Uw5gKlTrYM3AgG4805nMsH0QcuB8UqpMUqpVOByYFaHbWYBVwWD508BqoIdg6H2nYW5ryL48y0ApdQA4B3gt1rrRQjRAw3r2M0etHOn8+Npp5xiH3gHZgZbPII36uvb1MzuHyL4sWxR+CyR8RBo7vp/xutD4AUV3WOAMhfzRD6GDIntv6HodSoaos8esXD3QsBkHG3bQf3JJ11vR0s5lhZ2mTcGZx2a8KXRnWZtRvt+fCGyAO2p2sPc7XPRaFzKxeVHX841x11DTmoODb4Gy3TfnTTXwqIr4eOvm8C1QCM0V9MukCzgNct8tbD5Ufhf51LQreqLYMVP4Y0RZlLDvLPhw6/C/46EV/NN2dADPSPCee9eU39+6FD47nfhr3+F1183QRsPPwzXXGNKaV51lZlk0bZGfawGW55f/Xzr/+EZo85oXX7+2PNxKzcazRsb37CcCJgUMoe1z7xRs613zhTv3ZIy4yFI1sNESk8PPZnpjTdikwTW7zeBIJFoaG7g6c+eprlNSY0vjfgS2anZfOPwb7S7Hjb5mrh/8f0Rt+OMM+z7ltavNxN3Ypl5tvXfbsAx4LMZ1Cl+p8cGRYZVcBp4cuzXb34k7uOFz695PmbHsiuBN3OmCRDt6NhjzbhcPAI3klm8K6e2DmIBKKVaBrHWt9mmdQAMWKqUahkAGx1i32nAWcH9ZwAfA7dqrT9vc9zWATC7aEThjDc2vGGZmtCt3Jw16iwW71kccv+zRp/FtsptnW6wGpobeGbVM1w36bqI2/K1r5mMC+E8/zw8+GDEh+2ShgZ48802C5SCvBOhbGHoHXc+CydIrc5wXn8dbrjB/DuHGiRSCk480UTInnSSSXM2fry51jc3m5n7LpcJ0HC7zRcPv988fD6zLi3NpDNeuRKWLoVVq8zP7sxuvn3+7e3q0YH5m2mbqebq467mzY1vUuM9NCju9Xu5e+HdvHzJy10/ubCKhO9YVC+aKPqWfdtF0Suloo6iT3q1O2Dx9+Dgqsi+NPY7Cgq+BGkF4MmGlP6HOseaa8xxypeagA0LS5ea1INW382nToULLuhbX+zuvNP8e3zySefPH68XvvMdU8fvz382n2fdzQJRW2u+VF944aGMCmecYYJm7AIgn3sOTjvNlJ6JJU/bb7QDv2SCN+yyWe1+CQ6/GdzxSQNy1lkmhWXbzsoW//63mXUW6/ff1siR9gN8n39uP9M8liZNMiXErK6/Dz1kfg8zM0MPVIroaK19SqmbgTmAG/i31nqdUuqG4PongNnA14GtQD1wbah9g4e+F3hZKXUdsBu4JLj8ZmAc8Ael1B+Cy87TWsexuEPiVTZUkuJO6VS6TvRM48aZsmsd7drlTKaktiZMCJ1e+PPPzQz5WM8K8npN6QTAzGTb+zZgcQFrroKK5TDo9M7r4qnkXXA9Fn47K42l4bfpqBtZCGKmtAvtFn1K20Fpt3Jz1uizOm2zpWILu6tNx7jH5eFg40HAfA9v+x31uefgvPOi+25aX2++x7UNwvBrv23mjcLswtbnzf5mimvaZ6kIl0nDSk1TDTlpnRv91yV/bf33KcwuZHz+eIb1G9Y68csX8PHS2pf4/nHftz5wfTG8fyo07beZxaroNM4a8JpHR34vfP4r2Pa0GZxv2abttv4G2PsmlLxn7mHO+SD0G0+gV181wRnNzeba0XFWbCBwaFb5iy+awMC2ZVI8MRiBWLd/HZsrNgPmd7+ouoir3jCluItrilFKgTalgt7e9DbTjuw4BycJZAxrH6xxYIUJAkrpl7g2iWh1J+Nhaoh9S5VShcH+Qsl42AOdeSZsskmOVVcHDzwAt94a2cRiKz4fvPcebN0a2fbPr3m+XaaE7NRsrjrOfGbmZuRywpAT+LTI1F/xaz+vbXiNhxseJi8jL+yxc3LMGMqCBdbrf/tbM4EsFvcujY0mYOXnPwdSsk35qeqNnTcMeE1A5ZG/BE8Cgs7jKf9k0CEmsW96GCbcGtcmzNk6J2bH8ms/u6t2M7L/yHbLn3nGehL0X//aNyZmdhTv4A0ZABNc+9a1ljdjfu3nzU1v8vbmt0PuH9ABy8j4Bl8DN82+KargjTFjYMCA8Glwm5rgj380aejjkTanttZkcOgUgTjyUvPF3WagEgBvJRT9D4ZfDK54/wn3PPv3ww9+AB99FDq7xsiRcN11ZtZAWpoZQIrk/9rttq7TOX68eUybZm5kPR5zs/qPf0Q/03pl8Uo2lnf+EjI0Zyjj88e3vj5z9JmdtvFrP29vfpvimmKG5gzttF5EJNFR9OfZrL8ek6GKkSNHWm2SWLtegqXXmeALbdHpD5CaC6O/C8OnQX7LJV2ZOuZtP89aOrf8TeYLd802U2t95/PmMzLolVesg6SUgkceSd60Z/HidpvAtRNOMLOGrYIHHnrIdLzdc49JcetyRf8FuLraXL9uu83cQDW3uX849dTQg0+zZsHTT0d3vkisW2cC8QDIPd78Htqp/AK8B8xNXxyccooJGrJKifnmm/Doo3E5bauUFPN9Z/Pmzuvq6syY0IgQmfFjweWCp56Cb36z87W4udkMEixZAv37x7cdfY3WejYmQKPtsifaPNfATZHuG1xeAZxjsfwuIEkrg8ZHUXURox8azaj+o9h08ybcrhCp10SPcOSR5jtDxyDQ/ftDZ9aLB7fbzChatsx+m6eeMqliY9Vx5fXCf/7T5v3nngApWcEZ5ha2/xtyj4OUOEYgdtRQYuo4j7oCPH0oIlcIGxX1FbjUoejXMblj+OCqzgP+j3z6CL+Z+xua/E24lKs1YGL0aNP/0dIn9tZbpmxwNMEbLZ8Z5Q2HShF6/V7bzBtDsofgVm782k+Dr4GimqJ26ztm0khzd46ea/Y3E+BQB9ra/Ws5dcSp7bap9dby1Mqn8Pq9pLhSuHTipVQ2VAImQ8P72983pWbn3873jv2eGehvy1sJc78EDcXtS3sOOA4m/haGXQDuTHOv2lQGmx6CLf+E5oOd33R9MXw81ZRsDJvKXJs+wP02I2BJ4NZbzT1MpGU4W+4HWwI23O7YzDi/c/6drb8Hfu1nadFSlhYt7Xz+gI87F9yZpMEbQ9v/TpQvBSV9uz1Ma9ZCoAiTtfDKDtvMAm4OTkaeQjDjoVKqLMS+LRkP76UvZTzUGhr3Q/UGqNligpn8TYcC41yp5uFOM5O+csZDvyMhfXBsPlhi6MwzTfCa3WSmv//djAd1lddrSkdEQmvdKRN+s7+ZC4+4sPX11cddzZr9a6hvNh/uCsVTK5/i1tMjCwK4+moz5mE12P7JJ2Zy6ymndP++yu+Hu+8OBm8AjLoS1t1lHTi5+WE48hfdO2EyyhwBrhT7McPmKtj8OBxxs+ljj4P15evDbxSFF9a8wPTTp7e+bm5uM6mgjcxMOP30vjn5K95vOdEDYJZppKT+l3NmbZr1/9k76/imzvaNf0+0SYUKtMXdbfgYMGRjwowBG2PuruzHO/bOfWxj7nsnzF2Y4GPIgMGGu0MppdBSl9g5vz/upGkaaVKBbsv1+RxoknOenCTnPHLf131dPqoAVVFsL6bAVhByC3W8zWXjf6sjywKdc054Y/srr8D+/XUr8QSyiNm4USqT/dDszPAa2fhE8IrifzFWrxYCxbx5wReVLVuKVNnWreLP2aQJJCTUXZLXYpFkVGysSEX+9pu3Ij1cPLr4UcocvoOxWW+usEzxwKAzML7reJ/gDcgE7fnl9Swd889GbVj0oY7NdrPnqQmLvkHLH+54W3yAXSWBiRtx7WHwRzA2E054GtJPlcC/MV4S6FWJaIpOJpumRrJIa9QVOt0Gp/4GYzZCKyn8/umnwH300KFyb/8bER8v5LXmzQPbVgBkZkr/1KOHqHXs2CEkmPz8wBVURUVS7VteDvPnw803S/uvveZL3ADpY0NVKxcVwYIFtfqIAdt8881KT+hNEB9Cuhhg51tQgyq/cDBgQHD5yNzcyMeESKGqcNJJwV//9tvQBJu6wqhRch6Bquy2bBECR1FRYJJRbaGqUWuWKOoWqqYy/svxOFUnu/N28+TSJ4/3KUVRB2jfPrga0ea6jU2FhdGjQwc3P/ywbpWAHQ744INKTzQZEjrJeOB7CRrWJwLZnq26WYiXkUoBx6RVv09VNARSYVoNzjuKfw12HN1BjMEblG+R0CLgfi0SWmA2yP1kd9lZly3WqooCF17o7Ws0De6+O/x5U0mJkMEdLkdFsgfkcaOYwDdQsiW54lwA9uTtqfjb7rL7WMEmxyTz3GnP+W19mvap2MdisAS0xLjmh2sodUupO1QHz694nqbTm9J0elN+3ev1Vt+dt5tXVwZgU6+4WghjHuKGtQWctgJO+x1ajpekoaKTtaulKfR4AM7PhBOewSeEXZ4DcwZBwWZwVQlMWZpLEUOToRDfyfe1UBW1xxHTpwcmbgweLPLmy5eL6uA338CppwZuQ1XrJuny846fw953zaE11e90PGBM8A1Kl+zxJQtF0eChaZoTUSGcA2wBvvQoHnpUDxFS/G5E8fAd4OZQx7qPeRoYrSjKDmC0+zH4Kh6udW+BCpkbPpxlcHA2bH4Wll4EP3WHL+Pgh9aweCz8dSesnQrr74cND8GmJ+T/9ffL83/dKfv90Ba+jJXjl06U9lzHP08yaFDo+EZhYWREuMpwucSGeMuW8Pb/PeN3sot91dx6pfXyUdUY22UsLtV7wmXOMqYvn+7zXCicc45/TLAyrryydqrkIPOT//s/yMmp9GTLsaAEWZOUH4bdMxrE9VCnUBQh2ofC1mfrzYar1F5KubOWP2YVzNoxy+dxfn7guULbtsfG/rkhor7JG9EE2L8cd86+s97f475fw6QcunHeeeFVFaiqeDjWdpCpCrsdLgui0Eh8e7ENqA756yB/Q52e198dW7ZIoqiwMLhc/E03SSD2rLMkUFvfcksGg5BC+lQztlbG/oL9zN0510fWDEBRFCb1nOS3/+W9LyfW6FuFZnPZePPPN/1sV6IIGxUsekVRTAgTfmaVfWYClyuCE3Gz6Ks51sOih38Si37rS7D6rsDsX8UAPR+GMRug9URR0ahp1aROL8cmdodB75F/4mr27g2866mn/jvl1Dxo2VIY7gMHhpZj3LNHLFQ6dRJvzgkThNT28svw7rvw1lvw7LNw662SUGrcWP7/5JPgi01FkfcNhbffDqxKUVMYjaIm4oP00YSc5u75sO5OoOpbp4e263nvveCVGHWBoiKRxA52Dp9/XrNgQU0wYwakpAQmza5cKfYqO3cGrtSoKUpKxPJgUFWtvyiiqAWeXPIkGw5vqPBSf2rJU6zMDCGRUI8oKRELjcWLYe5cUTT66itJmvz8s5Dsli4VovKxIGr9ndGmTWBFPYAffwy+pqgvDBsWevzYs0d+97ogvamqkAl9SCrmZIhpGvQY7HmQ/Wu9BQUBqUhWqjBYVAfMHwE73xECR7jVFeMOwcVa4C0YXkey2ZFsoRBpW5oGhw6F9/mi+Fdie+521Er3QPuk9gH3q0rq2HjY6xF1/fW+a6VvvhE7yuoUap1OOHJEFGqzS7KJqVTZaTVa/YpKPEixpmCoRNav7HN+qPgQFqOXRdcmqQ23DrzVbxvZdmTFPka9kaxir2ULgN1p5+stvgsCu8uOzWXD5rL5qXs8+NuDvieZNVc2TxVvbBs44y9I7itr0ECqt4ZYMFih400w5At5TnXBb2PEtqlyQj65H4ycC+fsgJGzYfiPcOZqOHsrtBhL4PrF44+VK+GBB3zXDsOHi1Xn3LlwwQVSVT1wIIwbJyTxTZsk5gbeNYDHlrg22Je/j2JH+DEuVVP5ZYefqNzxh6KAuUre/WiEcr1RHHdomvaLpmmdNE1rr2naE+7n3vSoHmqCW9yv99Q07c9Qx7qfz9U07RRN0zq6/z/qfv5xTdNiNU07odL297GqVJ1wYKaQLr5Jht8nwrr7xM620E1yU22iHKDaILaV9L1NhkDqCPk/uS/EtpY+2lEgSquuMjl+/5fSXgDVpmONdu2qJ6o9+2zNyNg2m1iRhIunlz7to7phNVq5ovcVPvs0jW9Kx+SOPs+VOcv4aftPYb1HkyZSFBYMO3fC7bfXvLCmvFyUGHyKtQAa9QgdW97wUGhV+78r0kYFJ62AEFf2fAx1TLIA/OZYdYHVh3wr2/T6wPeGy/XvVN2A+idvRBNg/2LsyN3Bnvw91e9YSxwuOcwfB/4Ie//hw8MnZKxdK/LudZXkKCmBZ56pxpus+TmEtXBbd59IiUVBURGcfHLoZOAzz8gWFxc8SNsQ8Nyy53zkQD1oldCKdknt/J4/ufXJ/nKfbry/5v06P79/A6Is+ghwdA2su9e/oghAb4FTfoWu/yekjbqs1DTGsTe/Z1CCxmmnBVed+LcgMVFY+f/5jwRnq/MYzsoSRYxXX4U77oBrr4UbbxR59g8/lABduAn20aNDq2/8/HPdJevtdkla5udXeSHt5NC2KKUHIOObwDKLdYC+fYO/9vXX9bvwsNuhf//g7/HHH/WjdhEIzZrBkiXB7VF27pTF/oMPQl5e7dQyiotFIebJJ8UK4XhUzUfxz8SqzFU8ueRJnwrjMmcZYz8fS5Gt/phYmiZqfR9+KFXRw4ZJgCwxEUaMgHPPlerpyy6TPvvqq4V4PmECnH22qABZLEJQOPtsePRRSaocrFpK8S9GmzbBCS7z51efyKxrDBpU/XtOmVI3lUdlZVLF5of0UaEP3P5q/a5BT10k6ln6KuxTzSlk4QUjIWcpOEuF1BFFFP8ybM3ZWpHA1iv6kOQNh8t7j1SOzfXtC8lV7OzHjZP1QLD+xeWS+fspp0j/kVWUhUHvXWAkmBOCnnOKJcVHXaMy8SKzMNOH2NHEGrjALi02rWI/m9NGZqGv9cpDvz0UUI0jGPLL85m3a573idWTvWtaQyycsgBMyeGtYY1xXhXdXW9LMtGjoqEzC1Hj1EWSdDFYwJQomyEWEjrD4A/hnO0iid6AoKoyt6g8Ll16qazl+veX2FrV9UZ8PHTrJhbCZ5/tqyZVW/LGc8uei/iYF1e8WLs3rS806ub7+OCcMOx1oojibwbVCdtehW9TYdmlcOAHuc4dhdJH6i1CXuv9lJDbxu6HiWVwxmp5PPwnOPk7+X/kXCHUTSyV/UbNleNanC/tNBDlIkUJHQsCsSq77rrIYmLFxaJ6tW5dePtnFmayYLev5K1LdTG2y1i/fS/vfbmPolexvZinlj4V9rldfnlwJUOQ4qXffou8OFpV5Tu6uKohEcgX3XKcqGEFgu2IqENHqtrX0NF4sMwjQmHtFLDnhk+2D3O/H7b+EF57EaDYXuxDrm3UKHDseseOBueQdMxQr+SNaALs340bf7qx+p3qCDf/fHPY+8bGwgknhN/2vfcKOaC29ikul1QpPFmdynKLsWAIQxok+1c4tOCfJwNVA7z5phBsgjFXr7tOZP7ryhqlvlBoK+TdNe9id/kmE816M1f3uTrgMXqdngu6XeBX5VLiKOGJJU+ELXUWhS+iLPowoDqEMR+Izawzw6lLILl/vfmTl9kMQSdvCcFjh/8q6HTw0EOSxD7vPFlQ1QdpoOpCbfDg0OQNl8s7ttYWLpck/v3QeHD1AbD190t1XD1gzJjgC9iCAnjnnbpX9gJZ1D/2GHTvHrx9TRMCSX0SOConQzt2hF9/lWBuIDsApxOefx6aNhWy0bp1kjgoLAx9jqoq+5SXS4XfffdJG08+eeyr5aP456LIVsR5n59HWQCbpbyyPK6ZeU2dvp/dDr/8IsmSJk2kmvWWW+CFF0RNIydH7pnCQulLCgrkb8/mea6gQPoDp1OUaH7+WcgbV10lFWFRCNq2Db5+WLHi2Kt4JSaKelMobNgg5MzaqKqoKvz5p1RU+yH91NBr0ay59VvJFtsSzlwD7a72J3AA5K6C+cNhVh/Y+TYUbhcipr0gvACtq1z2jSKKvynWHlpb8bfFaKFlo8AJ/9TYVJ+4QkF5gdfTXhGCdmWln6IiIZCtWOEf/yoqgr17RV1h9255rqryRWJMYtBzTrGm+CiL5pR6tc8PFvkyCpvGBVb/aWxtjNldVW1z2dhfuN/n9U83fOrzONmSTKo11WdLMCf4kEgqrFPyN0Lxbu/BHW6AmPTAahvBYIyTvmXtVG9fpOgk6Zg2yq3eEcQXyxgvSh+nrQj//Y4Bvv4aH6XL4cNFmTGUQpQHsbEwebJvsqW25NGNR7zqMUadkfFdx3PrgFt9tit7X4ke7/e8I3dH7d60vpAyEJ+UTPb8eisqiCKK44LcP+HHjrBuqii3OSsFf1IGwNCvYXwunPgBdJ0CTUcLgU1nlD7RQ3KrvBnj5XVrS1Fa7ToFTnwfJhyFYd/KJFpRjv1WZfJ+4YWhyQwAn30GH30UHoGjvBz++gvuvz/8r/+Vla/4KXq3T2pP84TmfvuO6zrO77n12evZciQ8f5Zx46pXErn4YvkM4RJWnE4p7jn1VLEeDohWF4idWTAc+B4yf643u+TjgiZDq88DOgpFASzc9VqYxMGlGUvDay9CVFbI0uvhzDP993G54Lvv/p3WKRHMRGsGTdN+QQgalZ97s9LfGnBLuMe6n88FTgnw/OPA47U85SjqACX2EhbuXXjM3m/1odUcLj5Malx4XJ0JE2D9+vASJ6WlUsW9eLEkHmqS+HK5pCr49NPDYJunDRf5r3Cw8no4Z2eDkAY7XnC5YNq04OooBoMkcsJZYB5vvP3X2wGfVxSFiT0mBj3u8t6X8+WmLymy+2ZCSxwl/LDth4ATsSiiqDV2z4DSIBGY3o9Boy7VM4JrAZMp+AIhmrj1Rdu2EnzbsEEqdhculO+vNioHOp30qzqdKHRURr9+1VcOf/wxPPVUeDZmwWC3+wcVKxCTKtVy5SGkx0v2wf7PofXFdT6OTpgQWtJy2jSRrK5rOJ1iefPyy/K7b98eeL9PP4WJE+uP6FRW5vvb9ukj864xYySRHGjMttngjTdkS0kRBZdevaB3b2jfXpKoOp3M3XbtEpLHhg0wbx4cbvh0tyj+prh25rUcLTta8digM2DWmSl1lFLuKueXHb/wyfpPuKTXJbV6n5wcIWi89pqMbUVFwcc4RZH7u1cvIXjExMimqnJ/lJfLfbZunRDHPXC56tay6p8AvV4IMr/+6v+a3S4yvSNH+r9Wnzj5ZLEnC4UpU4R4UZ2qVjAEVd0AaDIsdPWi5oLV/wcDXpcgen1Ab4IBr0Cbi+Gv26FgszsAWemmKNoOf94qf+tMkNhTSMOpJ0sluz4GdBa5YVzlsr4uOQCHF0pCIYoo/qbYlrut4m+9oqdlQmDyhl6nJzEmkdwyyXpYjVZ2Hd1Fz7SegCg2PfqobyIlJ0f6vDPPlNc7doTsbHj/fZlzVw6aHyw66KPs0djaOOg5p1hSfPYtshfhUl3odXoyizKxOb0NB0osedrXVyI/7DzqlbP96+Bf5JR5CSFtEtuw5w5/FeBSRynJ05KxuRMfc3fPJa8sj6R9X/gq+XS+Q+xQIsWud33b6fEwND4xvLZ0BjAH/w6PB156yXt9WK2i3hXKkrMq2rXzJRouXw4dOtTsXMqd5aw44CW3KIrCp+M/xaT3l9v8ecfPHCmVCVBWcRYHiw7SLL5Zzd64vpDYUwg9noR23hoaqnVOFFFEjEMLYPF5/qRavRWGfiV5D12Mm9BWi5ihTg8mt8Rn83Mh+zjFvrOzfR6ec06IeXYl3HabkCK7dw9e/OR0Sj7p/PPDLyouLC9k+vLpPooGCgoFtgIGvDMg4DFVlavKnGVc+f2V/HFd9Ur3LVuKQuT8+cHXr0VFohz54Yfy/YQqri0vF7LfiBGQkRHijVOHibpLKKy8Ds5cK7aM/4TcmcEihWqHfwu9X/56+PM26P9K6IJKZ4ms68JAfll+wOctBktQRfjKsLvsfhZ2AGuy1nBu53MrHl9xBcye7R+vnjJFihJDFQr+E1Hv5I0o/p34z7z/+DH86hu3z7qdzy/4PKx9J04MUqkbBOvXy0C0eLEkOiIhcLhcwhYcPLgauxQPDLGQ1Adyw7CCKT8Mf90J/V4KLQ//D8aRI6GZm336/D3sE5yqk2m/T/OR5PagTWIb2iS2CXrskJZDAvrLFtuLefi3h6PkjSjqB7vfA1eAmy++I3S8pWYBrwiQmhqcpLFqlSS1/q2eeMHQs6dMggsK4McfJRC7dCmYzRqKAiUlSlClA7NZkoMOh/SpF1wgsrlDhvirKcTESLBu27bAbYGMjf/9r5AMakrgCKq64UGTIWKNEgrrH4RWF9XsBEKgZUsJTm7aFPj1Q4eEpHDzzdVXZYSL4mKpxvAQI4YMCU7eWLRIkrj1Rd44csT/d23TRuzoHn4YXnxRrqVgleO5ufD557JFEcXxwicbPuGnHT9VJHmsRiv3DrmXH3f8yKrMVWholDhKuOGnGxjccnBAe7vq4HTC008L0VjTAhPLk5Nh7FhZSwwaJMk0p1P6QINB+mDPeOdyyeZ0Sl/sUaZZtkz6+1mzai9b/k/DeefJ9xPou58+XQiJx1LR65RT4PvvQ69vNm2SAOkZZ0S+znE4pLL+z2D8hdiWUsUWqgpr36fQ8+H6I2940GQwnLEKjiyHzU9B1jwhajirsJBUOxz9S7adb9XvOUURxXGEpmkcKDxQ8dipOmmR0CLo/ulx6RXkDUVR2J67vYK8YTKJgumll/r2N5omClC/+JXR+SKzMNNHlSo1NnghVYo1pWIsBVEWPVxymKbxTdlfsL/iNbPeHLSdxtbGPqoZGQXejM4TS56gzCHnYtKZuLL3lQHbsBqtnNL2FH7ZKR9OQeGNP9/gv7alYs0EkhQxJYX45CGw8y1vpWtMKnT7P5HzDxcBiAjHC4cOSZW0B2PHRk4YTE/3JfQvXiwJyJoo4v6651dMehPlThmbujXuFpC4ATCs1TC+3fotICSmmdtmcmP/Y6cMHRYadfd9rKmw91Nof01kii9RRNHQYMuFRef5xwqNiXD6CrC2qp8ir2DKRscBrVqJfezu3aH3czpFWeL992X+X7VvLC6WmNoFF0heKVxMmTfFL0muoZFZlElmUWaQo/yx8uBK9hfsp1WjVtXu+8ADsp4KtX5xOkWB44YbJG7VqJG3IAyE4KHTwYwZEissqE4oT2eEVhfC3o+EXB4IjkKY3Q9G/Srk7uquPcffwGalzSRRIgwUj6+M3e9LjvGEpyuRpdxQXUJsX/8Q7HwzeBtuZBVlBSRoJJgTKJganqLhO3+9w51z7vTLe23N2erz+KyzxFp51SpfJd7sbLl+vvji71GgXVeIpjWiqHNomsaP238M+rpBZ2B46+E12swhWHLz98wP2+OyVSvxaIwEGzbA0KGS7AiX7ehyiZfZiSeGSdyoOMELpWMNB7vfg4JN1bMN/6FQ1dC+VwZD9fJdDQEfr/84IHHDpDdxVsez2HJkS9Bte+52Tmt/mk8ww4MdR3eweN/iY/ERovg3wV4gAfJAaH1RcN/BOkTLlsGT/rNm1Y0lR32gpCQ0qQFEpemMM+Dcc0XB4eKL4Y47JOH9zTfwxx+QmVlz24tGjSRQu2AB7D+cj/PKQSRPvIcHHtA491yp+h00SBKFI0aIh+W0afDll7BliyTW335b9gtkgwEwalT1noQff1xz9Q+bTb6LgKobHqSPDiy5XhmlB2DHa/WySLvmmtDEjMcfD64aFSlUVaol364k4DRmTPB7RNPEXqU26ivBUFQkBI1AMJkkSb1hA0yaJMllYxhW4pHCaDz2dgdR/LOwJ28PN/x4g8/czKw3c/dJd/Pqma/6+AKXO8sZ+/nYgJUkobBtmyjLPP20JDeqkgcGDZIkfmam9P/XXiskvJgYCe55Al4xMXJvmUzS58TFif1GTIz8P2SISJd/+KFX4SMKL0aODJ6QmjWrfiyuQuGkk8Jbu1x9tawzI7X2LCyUOUBINBkW+nVNFUUMRz0MIgHPZzAMnymy2INniM2oKUls+owJQB0G7GPS6q6tKKIIEzO3ziTx6UTyy/ND7pdVnOVTtFHuLA+qVAHQulHrir9LHaVsz/Vl9Z53Hpx9duREYoMB9uT7KlsEszsBiDHEoFe896lRb6ywXamsoGHSm4IqeDS2NsZVKTlzqFjU9TILM5m1c1ZF8Zhep+eiHsGJ2VeecCXxJpkglznLmL58OlpBJbZ16ghR7okUxXuhtFKJcKuJ4fvNN0AIwd/7+KabIicyms2+a5FVq2puR/3phk8ptAlxT6foOL3D6UH3Pb3D6ViNsgYsdZQyY92Mmr1pfSK+o7+k/c63wldhrivUhc1EdX5vUfy7sOU5LxmuMno8ANbW9arO25Bw0UXhxTny8oQcd/nlQphzOqWf3L5d7M0GDIA9/kJSIfHBug9qcsoBcfus28Pab+hQybWFg7fekn3HjRM74e++E8LG5MlSpHfLLWEQNzzoNkWI3aFgz4N5J8HhRaI0Ecg62eUAZylkfBnmGx9HNDsr8D0WCNtfFavJw78JMd9ZLP8fWQKzB8DW6WE1s/zA8oCEyY7JHcM+7e6p3THq/G+KqnYsiiJKwYEUNn7+Wa4bjz1sXaKuYrN1jSidM4o6x4oDK3zkhStDp+i4od8NvDrm1Rq1/eDCB5n2+zQf704PbC4bc3fN5YwOZ4TV1uTJIiccSYJv0yYhYnz4IXTrFpwxrqoShF21SrylQyaXAqHZmbD+gfD3/32SVCUZG/3rWNpNmgRPHoJU+Tb06ntVVbnhpxsCXtd2l503/3wzqKWKBy7NFVDtptxZzoQvJ3B4SlRTPoo6RMFmqSIK5MvacnzNAl41wKmnildkVcyff/zve7sdVq+GJUtg7lzYsUPUCOx2CZDuUNJI07L9jjtEGnPnBm7TZJJknKJIO3a7JO+2bYPGNVDZ1TSN6365nLKUVexlFelnteeHh26IvKEAGD5cyBmhxlinU/xA58yJTIJXVWWRe8cd1eyYOjy8BtdOhZRB4r0a7rVbVQI0AC64ILR1Sn6+LDxmzYrs8wdCWZmQNSpX1J9xRmgLoQ8/FOuaukZZmShmfPhh8H3at5fXn3hCts8/FzKSzVZzVQCDwZt8mDBBqj+iiKImcKpOxn4+1qeiONYYy7TR07AYLQxoPoBRbUcxe+dsXJoLl+ZiV94u7ltwH9NGTwvrPbZtE3JGYaF/oj45WeyPRo+Wa1qnqz0ZSa+X8QIkAROFF927B39NVUU2/r77at9PB0Nxse+aslMnSXZVF0DKzRVrz+XLw68+Ki2VseFQCEcxAJqdAVlzwBXiJA7+ItYlib2PXbWjwQItx0LLsagq7NuaReaGvyg/9AdWx2YSDBkkxRwi0ZqL2WjDoJPgrEvV4XAZyS9NJq8sjQJHC0r0ndCnDiK9W3/a92qL0RSVq4/i+OHJpU9SYCvgjVVvcO+w4JPHHbk7MOvNFeoDFqPFh0xYFR2SvR4VTtXJ2uy1Pq8riiRMBg2CzZvDn4MlJsL+gv3edlBIjwudwI03x1fECRUUsoqyoClkFHoJDzpFF5K8UTle4mnrhRUv+BRxpcWm0blx56DnMabjGJ927C47LrvDGxw3N5Zq3kiRt0aO8yTkO94QWqq8gWPdOi/JOzU18uI3D3r2FCIISDy1JvMZl+pi5raZFY/jTHGMaDMi6P5DWw1FV6lWdXXWavLL80mMSYz8zesLehPEpEOZV0mHvDWirlwTaZKaIts/HnFc2ojin4O8taDa/J9PHwUhxqs6QVra8bke0/yJvxdcIGuIcMfV776TTadzO/7VsFDr/TXvB8wt1BQ/bv8Rp+rEUE2uSVHg2WdF6T6U+oYHmiZx2/nza3mCjbpBYq/q1etdZfDbmZAyELrdK3k3TzxbZ4B9X8DmZ6BwSy1P6BjA2hxiW8s6LBwU7YBfT5UYvrmxqOOEWuMFwKK9iyi2+5P2+zXrF3Yb3Zp0C1i0nF2cLRZ2Fq/qWdu2Ujx44YX+a+K5c6UA5v33oW/f2g+ZxcVSLHPllbKubmj4d2V5ozgmeHzx45QEqWCNNcZySc+ae0JP7D6R6cunBxyIiu3FPLbosbDJG2efXbPknifYOnKkDEw9e/p2JFaryNBOmSKSUTVCQhcwJ4dP+yrZA3NPhNHL3FVIEd7azgZKLwsDRqOwMl96KXBlXFmZSB5PmdJwZZVe//P1kJOrYPdTuDhSeoTFexdzcpuTa9VOFFFUINREz9io5u1+mw7l4S+2zku5iB/jPvNTDygqElWBhx46tvd9bq7YkXzyiZA2zGZJRlf2h27eXIJfj7c8RNu2In/fqhU0bSpJugQ9lFWSv3c6haiQmSmM++3bxfdxxw5h5h89WjPiBsAHaz9gwZ4F6BQdqqYyee5khrcZTpfGXWr9XZxyiu/nDoalS6V/njYt/El3WZmokxwNzBP1IqEzmBKhrJoxTnPBonPhrA0Q06z6yYGrHI4G05v3okWL0NYpIPLB06bJd1DTRUdxMdx6q6iiVEZcnFRALFgQ+LjyciE4RPLdV4eiIrjnnvCDFC1bimT366/L9fzdtxpffeli734dJqOK0eDC7tBRbtOjafK7KIqK2eTCbFJxOnXY7AZatnQxfoKeceMUBg4MTeqMIorqcP+v97Pz6E6fZFCKJYWrTriq4vGLZ7xIzzd64nJKZK3UUcorK19hTMcxDG8Tmjh2+LBXza8qcaN9e7G0iIurP/WYf5tPbHXQ6cQec9aswK+//bZI99YXql4DiiKBqtdfrz5wu2GDVOp9+GH1852SEiHuBLVLqYwmQyGAop8fPAUEumPjK5OVBTNnyuddvRp0uqYYDGdTXHx2iGpujWCfJS5Ovu/ycujcWZTOpk6tXjksiijqEpuPbGZV5ioAnl32LHefdHdQO4jtudtxqN5JVhNrk5Btt01qi0lvqog1bD682W8fs1kC4aecIhLvoUJQZrMQAefPh3G/ZVU8H2OIIcWaEvJcGpkbVRAuHKqjQnnjUJGXTaahBSVvNDI38lG4UjWVrKIs3vjzjYrPZ9QZubz35SHPI9YUy8i2I5m9czYgcUSbqmDw3PeBko6VEc561dIM4iK3UmtIWL3aq5LRo4f0kzWZl4wcKckQz7p261axN40EKw6s8Hlc5ihjcIvBQffv0riLT2GTWW9m1o5ZTOo5KbI3rm8k9vAlbwCsuw8GvhPYFjuM4oEoojjuSOwJ2Qv9+9LsRZLriLTQK5IY4fM6uDgC6e1QE75aSnj37g1JSeERGSqjpupEHtz/6/21a6AKVE3lqSVP8cDw6itjxoyB1q2FDHpM0fMhWHpBeH1k7kpYcr5YRMakiUJW+SF/JaSGjvbXwIaHQttcVoWrzFchLAIs2LPAr2DYarTSN71v2G0kxiQSZ4ojr9zXA8hitPBH5h9++dyzzoKffpL8bdW56e7dUjB4yimiaNynj8xTYmOrt3hzuSSGGhMDu3ZJQdsnnzRc1f4GXo8exd8N+/L38eveX4O+btAZGNRiUI3b79akG0kxwf0n1xxaw6bDIbIklWA0wnXXRe4T7MHChZKAS0kRucnLLoNzzpHBeciQWhA3QCYQne+MzB+zaCfMGSgMukhkm50lIh31N8bkyaE758cek4BEpJOmY4UHFz5Y7+9x488NzOMzir83DLEQQOkFAHtOzduNgLgBMG7A10HlW19+WZQu6lpKLRDsdpnwtWoFt90mAU2bTRJzLpdMOmfMkITdjh3y97PPSt91zjmysEtNlUpbq1UmkTExMvFs1AjatJFx5dJLhZDyyisiF1dQIFVRNcHOozu5ddatlDpKKyyXyhxlnPf5edicYbAuqkHjxqGrmSvj9delyiAcvmJJiSharV8fRsOKAq0ngRIGodGRD7+OBmdRYEUZD5ylcp0uOi+ME6jeOgVkjPrzz5rJ9JWUSCJrRhA14CuuCE3MeOcduS5rGyQAudYPHoSPPgpjZ9UFOX/A9tfgz9vQLRzFgMw2PNk7hh1PxFP+cWM2PdObr24bz7OT/o/HLniYB85/jPvOe4JHJzzCMxf9hy9uvYD10/pS9nFjdj8Vz7P9zAzOboV+4QhYdQtse6XhrsCiaLBYvG8xL//xMqWViM2xxlhePvNln4qjDskduKTnJT4JtjJnGeO/HB9UgdCDZ58VolPVy9NqFeKfx/IkimOHSZOC95U5ORIUqg+bqeLiwApNEyeGr/Tx7bdCZC8uDqy25HDIWHH33WH2zwAJXcOrGC/aLuNhJIUAESafbDYZ47p3lyqsyZNlnV1eLuNm9ZamwQPzxcVyLzocsHEjPPJIlLgRxbHHY4seqwiIO1QHn20IICvoxuaczT5Viy0SWoRsu0VCCx9ljn0F+wLul5oqJNqrr5bxpyrJT6+XPmnECClm6tkTckq9az6DzkCKJTR5I9mSXPF3uaOcg0UHAcgty6143qk6g5I3FEUhzuTtqGMMMWSXZDN0l5OBB2DgARiyy8G1Yx+t1ubhoamzOTGDiuNKSysNyGVZofu0cNarMelQh5XPxwOV1RMjtUupjEGDfMmFL78cub3pl5u+9CloapHQgkYxwQtGdIqO/s28UiFF9iI+Xv9xZG96LJB+qth/Vca+z9222AHYm47CY3NeNUFtrVei9iv/HHSdAkqASoqNj0JpJjgjTJJHFCNsOFZViiJjak1zTjXBxsMbOVh8sM7bfW75c2Htpyjw6qv1p1YYFE3PAGvLyI5xFkPxLimG/rsRN0Dsyo9RqMvusvvZ7oEQZrunhhn0daNTSie/50rsJSzZtyTg/iNHwu+/yxow0HW1YIHYfTdqBOefD88/L0VtLpes78rKZL1ot8t6cd8+Kcy47DKZ+3bvLorRDTlsGFXeiKJO8fyK53EFmmQiE+gLul/g49EZKRRF4fLel/Pcsud8Kg48cKgOpv0+jQ/PD6HVXQl33ikDS21QXCyVs3WOtlcI6zoSlOyFOQNg1Dxh+xuDmN2DLAZUGxz4AZZfUatTPd5ITRU23pgxgZNfqioVbNOni1/4MZ9IhMC8XfP8WIf1gS05W9iTt4e2SW3r/b2i+BcgsSe4giT4930JCd2PiZel0eDkhRdkUVSVnGWzSYBxzRoh1dUXNm8WFYi8PP/+55RTRPo+KUmSQh5Bh0h9pStDr/dNMEVauQTgcDk477PzKHP4LlI0NDIKMpgybwovn/lyzU/Sjcsuk+qqsjDWQtdeKxPuUaMCJ9A8lhoPPwxffRXBSbS6UPyDnWFk3Qq3ws/d4cT3ofFgMFjBM2dRnULq2PMhrJkSXnuI12l1FduaJjL2H34o41i4KhglJUK+uPvu4Pucc44QVYPB4YBzz4U//qi9Sk15ubxf0EpxRzFk/ihByewFgA40R8BqAb1ip02LeNp0LWW0OQt0uV4Ja9Uhm61UJmGlBaKeAlJJUJohpFRdDHS+rXYfKop/FfLK8hj/5XgfuxQQosa5nc/12/+JUU/w6YZPfZ4rthdzybeX8MvFv6AEyAI7HPDGG4GVia66Skh81VWLRFH3uOACuPnm4K8//zxcf72sIerKlk1V4cABUR+quh4dPDgyEsGMGUJUf+MNmZN41AhjYqTg4IYbRLUrbCgKtLkEtr9Svafy4d+EMDfg1eoJH84S8UIPA06nkDsffljum2DkGatV5kJ9+sBJJ8HAgdCsmRRqGAzyUZxOaePoUa+l3erVYq+ZV2kZFo5iWKT46CP5rU0mOSejUc65dWvZoko4/25kFWXx/bbv0dBQUCi2F/Pwooe5vPflAceQdYd8Wdvtk9qHbL9lQssKkjaIpWpBeUHAxLfJJATx5c0nkrN8DKYtV5CfL9fr2WfLeqtPH7ecu+qi0OZNJOsUXbXKG5VVQlRUduftpshWhEvzThztLntQ8gaI+obnfXWKjtzSXOa8FzlJ4sQDsPzdSk9YAU+N2YHvoM8zEbfpA4OVarMqQavJdXBxDfXy6xCVVexqamkI0idX7ls/+UTG1HDhdGp8sekLHzW0UW1HVXvcmR3OZPmB5RWqLAv2LMDmtGE2NKBOt8kwIW9UVShYfjmc/oeMqTqjVIa7ymBZzVWsg+J42UwEQkM5jyhqh5gmMOxbWDIeXJWCdPajMOsEGPYdND4R9GFOqmPSIi7yaii45BIh7R8rfL7xc3ToUKuQWDomd6Rv0+oVEjRN47ut3/nl20rtpew8utPHii0YRo4UVcAZM8KLA9YJFAVOmAbLLv73KBTFtoL49kL2q2esyVqDxWjBYfO9LsocZXRvEhl5o3+z/vyR6Wtx49JczNs9jydOeSLgMSecIISMZ57x2j5XvbZsNlnzLlwoSsCKInH32FjpZkpKJF5fF0VrxxrR0FAUdYZiezHvrn43IKkCpGrt0p6X1vp9LupxES//8XLA93GqTr7a/BUvnP5CtYtHEPn6s86Sit8GdwPHNIamp0uiIxI6XWkG/NQVWo6Hvs+JjYpi9CZSHUXCgs1ZBqv/D/JrWLbdwDB8uCT0LrhAOvGqrDmnE+64Az79VHyxWras2wBsMBQWCsMvmK3BLb/cUr8nUAk3/HQDcy+be8zeL4p/MAyx0PgkOLzQ/7V9X0DPh4/ZqUyYIJWSW7f69+P79sGpp4oSRn0kxHJz4cwzxdKkap8zfrwsWBqiXdO9C+5lT/6eiio/naLDbDBT6iilzFnG/1b/j3M6ncPo9qNr9T5jx4YvNW+3i4rV2LFCeNHrJYjs+U137ZLK6IglGFP6R+ZbXZYJC0+T8bft5eKJqTqFbLDrPchbHdHbN20qDPCvvgqtAmOzSaX11Klw//2SzAl2vdrtEkS9+WYhfIRCYqL4QIbybty0Cf7zn9rZpxQXw+23i7KMH0ozYePjsPsD+S2cVcrt9FZIGwnNxkByH4htI16cqs2tJOauxqoQDFTdN5wmqir6GLDlQMk+yFsHWb/AoQVhE2yiiAJAVVVOePMEn0piAAWFIlsRvd4MzJSLM8VR7iyv6E9tLhtzds7h2pnX8u557/rtn5MTfM1xxhnH1uY8Ci9iYiQx+cYbgZNUdrsQwRctqjsSeHm5tBmI8KbTwbhx0seHu0bNypIx1ENmUBRRqaqx8mCbi2HX2+FJmO35APRm6POc9PP6KskxDwFyy3TY8HC1ze3cKZ9/167AxPz4eAmI33kntGsn+3hIEYFgMskWGytrQA/BxWIR8sZbb0kV1sEwihX37IGVK+X/zZtFheBHXRqpqn9iIVtJqyAFeQqLPX+7XLJmTUgQm7X27aX6q317UVozRjB1ieLvi+nLp6NpGhaDheYJzdl5dCc5pTnM2TUnoB3wjqPeiZZO0VWbSGmR0MLHntVitLDj6A4fVYLKWLJvCX/ZvoS+X/L7qx05qeVJAfc7UnoEk95EuVOYYhpatcobaXFpPo/3FezjYNFBLAYLRXbv3NBqDN7JJlmSyCgUJppLc1Wod9Qam4ATADNQegBy/4DUIBZo4SQSw0keBW2jYQQmmzXz/p2bW3NVoiZNxJbKo5pYXg4vvAD/93/hrZPLylXa7MpF774sdBpccdu7EGCOVRnnNYa3L4Zy93oqsdxGebuWmPcfrtkHqQ8k9wE1gOR90Xb4pRcMnwmJveSaXHwe5K2t+3M4dCj4a1V/9GClyenpdUO8SEurfp8o/h5odjqcsgCWTAB7npfE4SyGhaMlltj9XlGfUe1iYRGs0HdckGv004Yvldapk2w1VcuNBA6Xg9dXve5H3Ig3xfPB2A+CjudVcc3Ma/hg7Qc+hDlFUXh++fO8ftbrYbXxwgtCKt+z5xgqGjQ/Bxr1gKN/VU88/6egw42wdqovSaoesCxjWUB1ZovRQpIlskrJPul9iDXG+qhpAWw4vAGX6kKvC+x/bDaL5fNNN8ma7YUXJIYaTMlL02R9GK66cUOOwUTJG1HUGT5Y+0HI13WKLuzBIhR6pvYkwZzgd6N7oKDwxp9vcP/J4fl83X+/eBzXRK683tHlLsj+tQYJCA0yvoYD30JSX2gyBOI6yKQofy0cXiIqHf8wjBkj1cMXXgj79wcOVv7xB3TrBiefLImmMWMkSBsb61tdUBsUF0tba9fCSy/BN98EDgTvyN3hE4Cpb8zfPZ9ie7GP3GgUUdQY7a+Boyv9g1Ol+2HTk7IYC0dyu5bQ6cRCpE8fyM/3f331arElmTkTOnSom0mZwyGJnFtvlSrOQAuSu+9umMSNhXsW8vqq1ysqy816M9f1vY45u+ZU9EdlzjImfj2Rbbduo0lsaC/tUGjbVgJ/u3eHf8z338OPP0r1bO/eMiFfskTIOTWCopPq4R1vRraIy5ojWx3gwQeFJBpO/uvpp2HOHElITZgg15ongeNwyNgyY4ZIDm/3Vy4MCI/NTKgE3uuvC5l1+PDIr9uSElmcv/9+lRdUl/hwbp0uFWOq3TdA2exM6HgLpJ8iSj6GOKi8WIuEdGNJly15ALSeKISOw/UhixbFPxWXf385+wv3+z2vobE7P4JOzH3Me2vfY3y38YzpOMbntdjY4H3BwYPyWlR5oxoEqxKtZdD/ttskGBSswvjPP4U09/rrtSdwlJbClVfChg3B97nmGvj668jtWkpLYcWKWp2eILkf6GPDr2Db+ZYoOvZ7CVqcAy4HoLn740Xw5y1i81kNfvxRVKvKy/2JK1arKHHccou85pnTNQqunh8QHns6kJzTf/4j248/+u9rt8O8ebKe++UXIeYbDEK88NzLaUhiwaP63ratKEOaTHCeUeaqnrljQYEEs/fvFwJHXp5sGzbADz/IZ7zqqsg+TxR/TxTZinjzzzexuWyY9WbuOvEups6fSpG9iIcWPuRH3nCpLg4Ve5NYFoOFlo1Cy4Snx6X7kDc0TWN77vaA5A2X6uLqmVdXPL5m5jVsunlTQOXcrKIsTDoT5ci8zqk6qy2eahbfzOdxVlEWmUWZPu3Hm0Iox+Kr3lHuKCezKLNulANWAJdVerxlOiT1A2OAhWPVRGKgBGJZpvR9f2MMGCD9ns0m419tip6uvloI/Z6Y67PPiuqixRK63dJS+PYbPSvejDwR1yUHdvkJSR6JuJ16hc4ISX2ELFQVpRkwqw9i/dWA9dwhMgIINGx9+ijqDo0HwXm7xcp04yPyu3uKOHKWwaJzJF7YbAyknAjJfSGhM5ibgKtU4gdVoeik8MNWC6vmY4xp06Swq75t3L/d8m3AImedouPEFieG3c6kHpP4atNXPqRKh+pgxroZPDP6mbDyCTExMqcdOLBu1TdCxqkUBYZ+CT93Ozbe2Q0B7a+CdWFWy9UCc3fNxRZAeTuQBUp16J7aPSBBw6AzsPnIZnqm9Qx5fOPGMp+45x5Zl339tcQi8/MlblpaGkIJ2A2dTtZbmiZrupEjpWhgwoSIP84xQTQ0FEWdQNVUnlr6VEhCxfiu44MyqCKBoihc0usSXlzxIk7Vv0Muc5bx/PLnuWfIPRj11Qf+TzhBqpP++KMBziFTh4tfZnH1ga6A0FQ4+qds/xL06CFJqmeeEX9qTfNKB1fG4sWyJSRI5Xz//iJR3K2bdOJlZb6BvUCw22Vg8HjYbd8ulVirVsngsd8/B+CD63+6vuYftAbQ0JgydwpvnP3GMX3fKP6haDNJkrJ56/CrENr8NKSOgCaDIyNw1FASsU0bSXiPHBmYiJeRIff4VVeJzFpMTM1IHE6n3Pdz5kiQf+dOSEkJnFj56CPxg25IDN6jZUe54KsLfCwBDDoDj4x8hHM7n8v5X5xfMY6X2EuY9M0k5l02L6Bsc7i47jpRRgnUDweDyyWEjSWBbQ8jR/trRDXDdXwWcV26yLU5d271CwkQq58rrpDk1OmnSwJIVaWqes6cyGXdzz9fyIrVYexYIYacc074121xsaiKXF9lODPq7fDraZC7yt8WxZQMJ30CTYZ6rWnqKsCt04HJncVrWjvlmCj+PZi1YxafbPikztsd+/lYcqbkkBDjNYtPSJDxKJAazquvSsV9lLwRGlk71jD8g+EVhMNuTbqx8IqFpMam1qrdDh2ECBpKqWjGDAkaPfJIzQmaJSVC8KzOAmzIEElsRUreqDMoiihQbXtJLK7CQfkh+H2iJKQSuoraY+HWsL2kl20fzEXPBp7L9esnBM/k5Lq3wPTY2Z1/vve57Gx47jlRY9HrpbKrcqwgNhZOO03WkX37igVKaqqXpOGZOnkSk5rm3QwGmYvm58scdfNmGd/nzQudA4vin4V3Vr9TodrUpXEXLu99OZPnTAZg45GNrM5a7SNznlGYgUlvqoiBGXQGWiS0CPkeep2eBHNChU1rib2EbTnbgp5PVlEWBp0MQhkFGXyw9gOu7nO1375ZxVk+6wOb01at8kYTaxNMelMFmeRI6REOFh30sU1JjEkM2UbTuKYVfzs1J3vy9tRd4njxeMicKWTvzB/FPqXluJoVI5QfhoLNkoz8m6J3b6l0tdlkDfz557KWrskcZcIESbR4UFIiVjxLlwYfSx0O+Wlvugn+3ibP1aDlOFHUqGqdUoGGFqSOIooIoDNC18nQ6VbpX3e9JwWqejM4S4UgvP8r2SqOMUN8BzA2Ap0J9CZw2aUQxFEgROCg90vDw2mniepbjYuRwsRTS5+i2O67aFBQGNtlbEASZjAMbz3cZ1yu3NaH6z7k5gEhfCYroUcPib3ed1/dEFeMRsnfhURsK+j/Kqy6tX7UKGIamDqQIRa63g2bp4W91qoJqtqceNCvab+I2+rWpJuffTdIXnlZxjIhb4Sh5qQHznFvAPtoxfLyweymLZvpxnY6cYQmODGioWDEQSL5dGQHXdXNtCvewwBW0ZUtKN8D3wOXI++bWruYQl0jGhqKok4we+dsH8/LqogzxXFpr9pbpngwqcck3lj1RkDyBggr8OvNXzOp56Sw2nvzTUncHzM/rnChKGI/sOrGqPx3BDAYhIl3/fXw4ovi3appgeWUCgvhiy9k8yAlRQg9vXuLtY7VKovKmBgvYaOkRKSvN2wQCbSIfKSRAMfKAyuDvp4Uk8R5nc+LrFGEoPH5xs8DsiIBft7+M5qm1SoZG0UUgCRch3wuvpVVJ4qaC347E4Z+JVKIgaqWAqEWkogDB4ot0sUXBw76u1zwv/8JqeKKK6Tap1cvIRXExgYPRJWWSsDK5RJW78svw8aN3tdnzpTAvd3uS1B44w059sUXZaFxvFU4NE3jkm8u8ZUlNliZOnQqyZZkRrcfTY/UHqzMXImGhl21s+LACl5d9Sq3Dbytxu97ySVSJXtckdhbbDhKq2HU1SOef16SguGQNzwoLpaKt9qicWMJmn7+eegiBIdD7p8HHpAAa6hqOFWVOdPjj0s1SVVMPfdpN3Gjys1oiIUx68Gc8revSIzin4FiWzHnfR75fCscOFQHQ98fyvqb1vs8/+ijYhNVdazasAGeeALuvbdhEf8aErYc2cKIGSM4Wna04rkduTvo82YfFl21KCwv5lC45x4h0IQiTEyfLmP6PfdERiJQVZknPPyw2HRUB0WRauUXXpA5xnFBh+tgx2tuFY0IoDogf331+1VCUVkcY575hdIA6/FevcTDOD50UX6tYTTK7/TEE/Dkk7J+rEqYPPtsIVeOGCGvxcX5qjeGsm+pisaNZevTB849V47dWcOajSj+XnCqTp5a+hSljlKsRivX9b2OOFMcp7Q7hV92/EK5s5xHFz3K9xd9X3HM9tztGCupkrk0V7XkDRD1DQ95Q0Vl7aG1fvvkl+dzz/x7KHGUYHbbHpU4Spg8ZzITuk0gwZzgs39WUZZPha9O0WExWkKeR4o1xYe8UVBewIGCAz5B/OrUO5onNPd5vDsvMmWskOj3AmTN9pK9/7gGjAmiEGeowaC8403o+3zwdXCkRQv2fCjYAoWboWS/JD1Vm8ynDXEQ1w4adYOELnWifjlkiK/60bvvioVlTeYnzZtLP1dZFWrtWqlG/+or6TMr96NlZRJfO+UUd4y2LtRVoGHacjQ9DTY+9rdKRkcRRcTQm6DVBNmcJWJxmr9BLC4KNkqfpuhwokPRHOgLt0lM0Ye8pAgpWGcQYoejwP99GlpyHZnPT5smcbG6JmR75ptrD60NqOodb47nkp6XRNSmUW/krI5n8dVmX5Z5iaOEab9P46b+N4WdT7j9djhwQFQLa6N2b7FIQdTMmWHs3PYK2Ps5ZC8ErY4WUHoLtL0SBoZnG3NM0fkO2PxMvTV/oPCAT/GfB1aD1YdgHC4SzAnEm+N91vIApY5S5u+Zzw39b6jReN+a/bSmDuK9aWkNrrI/St6Iok7w6KJH/Rh+VTGs9bA6e79gHkkeFNuLeXTxo1zU46KwBpXevUW69v33I6sOPiZofSH8dQcQJW9EisaNJbHkkayfMQN++00CY8XFwT2kc3MlQLhwYd2cR0KC/3OfbPgk6LVpMVh4ZMQj3DaoZgnTRjGNeG3lawHZskfLj7Jw70JGtR1Vo7ajiMIHCZ1g4Duw8roABA4nLDkfOt4EJzwji6x6Ttaedx7Mny/2D8XFgaXPbTaRRX/7bSFqjRolijv9+omCh9ksCfaCAiFmrV8vUrGrVgWew510EuzdC1OnCjHE5fImWWbMkL7n4oslGdS/v4wxJpO3yrMmcLmEQGYwyCKocePqj3l79dss2b/ERzrZbDAzefDkisevjnmVk98/uWJyXuIoYeq8qYxqM4ruqd1rdK4tW8r3u2ZNjQ6vGygKdLwRNjwa2Ff4GKBLFwlQfvllcEn++sR99wkRJBwFycceg0WLhAR58snynOd6LSuTr/PXXyWx9fvvgdu468wX/IkbAO2uBlNSlLgRRYPBPfPvCThf0qFjcMvBmA3msNrJLs5mS84WH39ggK05W5m9c7aP/P2pp4rywvTp/oGsJ5+U/v3JJ2WsaGgqHK7UJugPB5AdPwYJkd/3/86Zn5xZQUI0KAYURcGhOjhUcoj+b/dn7mVzGdh8YI3f4+yzoWlT2FGNq+Gjj4qa0ldfhacEUVIChw8LkW716vDP56qrhDR63JDQSaof80P4u9QRZiy+Aqfqf8HrdCKLeyxIsE6nVEj+8Yd/TCA1FT7+WAo+PMnLUAqNkcJDTOnRo+7ajKLh4qtNX1HulIvMpbqY0E20mq/pcw1L9i2hyF7EnF1z2Je/j9aJrQHYm7+Xcmc5sUa5GcocZTSPbx74DSqhTWIb9uTvQa/ocWkuduXt8tvn3vn3YnPa0Ct6xncdj1N18vWWr7G5bDy48EFePONFn/0PFh2k3OG9SWJN1d+gyZZk9Io3Q2/QGdiSu8VnDE6LDT2WpMWm+RBAMosyq33fsBHbCno/Aevukzms6oAl46D9DdDjv5IsNFZikLns7uRiEGR8Df1fCv565aKFQIUKmgpZc2HX/yTR6SwBg0VsCc3JomSnM0o1enm22+JKJ+d+fibE1K5y1GQSO+IZM2Tt+ccfQr4YOjT8vq+y/eNjj4nKX+UK7DlzZH386KPymqLIGv6NN2QeVDFH+ifbciT2FrJNtFgvin8LDLHQ4lzZ3Ch3lPHY7BtZufVDOhrhnHYjOa3NyehVh8RvdDESP9Cb5fj4TkJUs7YI3Ac0MJxzjiyV6pq84Sm0efb3ZyvmFJXhVJ2MaDMi4nYv6XkJs3fO9in8AlHyjSSfoChik9W+PUyeXLOCaasVRo+WQqSwxh5FgZM+gh87uQNvtRwPFD2YU6Hv9Nq1U18wJUqsc/trdU8CjEljecZyjDpjhU2eBwa9ocYx4s4pnVl+wF/q8vf9QYKL/3I0sHBQFH9HbDy8kfXZwStrPDJNHvnFuoCiKEzqOYnXVr6GM4iHfUZBBssPLOeklieF1ebTT8NnnzVA8obOCN3ugQ0PB06ERFEtTCaYOFE2h0OSTd99B7NmSdLVbPYuFGu7zouNlaqB0lJReho2zN83S9M0Hlv0WFDykaqpXND9ghqfw2W9LuPd1e8GbL/EUcIjix6JkjeiqDu0vUSsD5ZdEliqbccbsP9r6Pp/MqkEqWKqJwweDFu2wAUXSIIklERfbm71suXhIClJqmgnT5Zx5LPPYN8+6XuKikTd6c03JXjVt694CLdtC506QatWkihKSpJ+yOWSfkhRZNPrZVw6cgQyM2H3bkkq7dghUrMZGdX3W9tytjF59mRKnd4xJNYYy9OnPo3V6M049W/Wn1PbncovO36pCKSWOcs49/Nz2XTzJmIMNctS3HQT3HVX/ft8hkS7K2Hjo8fxBKTiYubM40Pe6NJF7o2FC8Mb5zzWYs2byxjWwl3YmZEh90xWVk3PJAhrMhx8m14DWyUdXByB3EkU/yrM3jGb99e+70e4iDHEcHP/m5l+evhBGlVT6fZaN7bl+srRO1QHk76exNZbt5IW501KPfKI9IlvvulP4HjpJUlWv/SSVPcrSt0liYuKZFyJ1HYiryyPxxY/xpu3F+NUjThVJxoaMYYY9IqeqUNv5S57SVgJvJrgm83fcNl3l1WQC816M/2a9cPusrM+ez12l50CWwEjZ4zkiwlfcHans2v0Pnq9VBefcUb1FWIrVkDHjqLAcfXVQgjV6YTspmneAGV2tih/Pfdc5AoanTsLiW7evOCk83pH5zvgrzvrPbH0+vybKbH5l3SPHi3EhmBKUHWJ55+XBGXV395ikTll48aybowiitpAVVVu/OnGiuIng87A2C/GymuaWvF8ubOcS7+9lCVXi4/gpB6TME+eAgWieNuiEGIfql4G4fVEWNTa+7i3IwsqqZ5vObKFGetmYHPZsBgsTB06Fafq5KcdP1HqKOXtv97m5gE3+3ib78nfg1ppTtfI3Kja86hqq2I2mNmeu93nuabxTQmFxtbGPuSN7JI6UGOojM53wNE1QrxwlQqBYucbsPNNaHYmtLpQKrtVGxRuh50BZJT0VjnWngdr/wu9HgtfhdKDzJ9h5Q3gKJS+N7EHtL8Wmp4Osa2FNFJJ+QS9Wc61eDdkfFdr4oYHU6bIutYznl14oRQ2pKV5SRnB4CmG8BQZnHKK2JOtW+e73/btcNFFMv4eV6uw4wVFgQ7XS+V0VH0jin8h1mStYdyX48guzqbMCfOBGRv/oHXGIb6b+B2dG3c+3qdYayiK5Jyuuqru+jiLReKPuaW5fLv1W7/1LMAZHc7AqK+msw6A09qf5lP05UGxvZinlj4VcT7hxhulUG7CBBlPwl3TWK1y7LPPRrgOiGkCo5fCguGiWhWKaBkKOhNYmsPoxUKebKjo+h/YUceqILoYGHeIhT/f7EfiASEQd2vSrUZND2g2ICB5I7c0l5zSHBrXldpWTdAAFbqOwRI4in86nl76dMBO3YN4czyX9bqszt/34p4XE2MMHsksdZTyxOInwm4vIUEY3sda2j6s4GmnW3xZ/lHUGEajBMJfekkWiqWlUlH/zjtw191Oug3Zib7FahJS84iL19DppOrRZJJgnckkbeh08ts1ayZSvqefDjffLBYtv/4qdiwZGWLjMG6c7znM3TWXnLKcoOfYvUl30uPSa/wZ+zXtV1GREwirMlex5ciWGrcfRRR+aHk+nPyD15eyKmxHYO098E0q/HEd7J4BJRngsslk2lEsxA/VIc85SyRY5ShyVxFFhrQ0UQ749FNo167++vWqQavOnUUOfds2IYa99x7ccIMkdzzJnM2bRaHjwQdFKaR3b6nmNJmkT0lKkvNv3FjGJbNZzr9NG5GvveYasWL55Rchn1SWmA0Em9PGuZ+d6yd1l2RJCuhh/fzpz/ss8DQ0soqyuGv2XTX6jkAkdo9F0iUkLE2h7VWBr89jhObN5bevjepKbfDss5EngDMzZbycMkW2l18Oj7jx7E9TJHhdFbveB1tuzTw5IyZuQK3IIlH8o3G45DCTvpkUUAbUoDPwwPAHImpPp+h4/azXA86/ShwlXPj1hT5BNUUR5Y2ZM6FJE/97c8cOGDNGxpVnnhHJWYdDEiHhEuFUVeajRUVCGli3Du68MzIb1xJ7CY8uepSWL7TkjVVvUOYsQ6/Tk2JNoZG5EaqmUuIo4amlT9Hi+Ra8uvLVkOvCmuDFFS/6EDd0io70uHR+ufgX5lw6hybWJihI1V2po5QLv7qQt/4Mw5ckCIYNE8KAKYzhorxciDitW0v18NSpUl38+ONC6jjhBJmHPPlkza1PnnnmOBMGWl14TN4mtziwXUL79sdOgebttwOTds47zzsniyKK2uKFFS9QaPdaDpc4SlhxYAUrDqyosC/0YGnGUvbk7QEkrnbF4kKuWAdXrINT9oT3fm3yqTjminVwwmavVLWmaVz343UVFbs9UnvQM60nfZr2oXOKJMzsLjs3/nSjT5v78vf5PE62JFd7HinWFB+VDQWFg4UHffapTkmksbWxj3pHQXlBwIRVjaEoMPh9aHdFlXmsBgd/gRVXijXo4rGw9j9Q7K9igr7SRH/bi3DwJwhStBMUSy+AskxJ5g/7Fk5bLmqWCZ3dNimxUm3r2fQWeS6xpxR+1RG6dBG7UU/fl5cHJ54IBw8GtiT2oKhI1qlDhnifUxQhrAZbB7lc/0LihgftrwFqoB7QAC0ioogiXLhUF48tfowh7w1hb/5eypxlGHVGzHozpY5StuVuo89bfXj5j5fR/k5qOkEwbpwQvesKOp0USL3111sV66DKSDAlcGnPS2vUtsVoCarYsXT/Ur85QDg44wzJvZxzjqx7QxEAY2Oha1f45BNZL9colpjYHc5YI+osNYkB6i3QqDuc+Ze00ZBhSYPWl4ASOVEnIBQDtJKC4oV7A0vSx5niSIxJrFHzJ6SfEDBmEmOMYcWBFaK2pWmRbaEQSTuhlL6OE6LKG1HUCkdKjvDNlm8Cyg17oGpqjWSaqsOAZgMw680UB7ET0dD4de+vPlKT1WHiRElSrFoVmS99TWE0eiXJQ8JghUHvySIuqr5RpzAYoH1HB78Vv8sH++6jfEw5Lkcpdn0MBr2Bx066n2t73YZZZ8XplESpwSAL2OqqDYLh4UUPB7UZshqtXNP3mlp8IlGmubTXpby88mWcqr8yjUN18MSSJ/h43Me1ep8oovBB09Fwzg5Yeb1IvAbqq1Qb7P9SNgBzY2g8GMxNJOBksAqBw1kiVUZ566BgU41OR1HEP/zss0Up4J57RL3C6ay9d3x8vLQxcWLwfdLTYcJ4jQln7IHcP6FkD8WHsziwr4QDB+BAlpWMw4lsz+rIvpy2lDvMOFxGnC4DTpcRnU7FoHNg0Dsx6h0kxebTIW0b7dMzaZFeSIumDlq21pPWMhm0x0EJvKI585Mz2ZW3yycQrFf0tE9qz9U/+JM3QAKne/K8FXVlzjLeWf0O7ZLaMWXIlIi/r7g4uPdeSWbVxuuy1uj5IOz54DiegCSArrpKbNpqIhsZDoKRlfr2heHDReq/viu4n/15Ck/esRCOLAdXpYC1qxR+6QmDP4S0URIYD3c1Hqk3eBRRBIGmaVz41YUBFcpijbE8ePKDNQpGjGo7ij7pffg943efPtehOvjr4F+8uOJFH6sqkErUXbuEXPXCCxIzqEzOyMiAhx6SLTZWLBV695bkycCBEgT0EItVVQgeDoeoP/3+O/z1l5A2tm2LbG1jd9l54883eGjhQ9hd9grihNVo5YJuF/DamNekKvy7S1mybwkljhJKKWXq/Kk8vvhxnjvtOSb1mIReVw3DMARUTWXynMm8s/odH5JNvCmehVcspFGMVHr/esWv9H+7f0VVUJmzjMlzJ7OvYB9PjHoibF/mynjnHakQjmS+sHWrbHWNXr2EeD5nTv313SG/ImM8dLsXNj1Rr+vQxvE5HC70T0Tt3Bme5VednENjuR+r4sCBBkBCjeIfg0cWPRLR/tf9eB3zL58vD+qiGrFSVeEjvz3C7xlemeoNhzcQ/5QUDXniCC7NxcK9C3lq6VPcO/ReQGxTKqOJtYnP4/JySfCXlsr9qyhQ7ErB5vR2qnaXndyy3IrHMYYYv3aqorHV1yvSqDdypOSIj7JVraHoYMDr0PwcWHap2JKEqzwUkwZ9n5f1sKcAYdklMOAtaHMJ6PT+SaRAHbuH5Dz0a0gfJevkcKH3ssxKSkQ1aMsWKSBYv17Ww2lpEs/S66Vv0zSZI6gqHD0qNqNduggB8aST4OuvZTzUNCF2d+ggahlPPAGJiV7VSE2T3/6hh+CDD6SdyjjxRLGNe/7547wmbGiIbS3qKkf/DP8YU4qv9U4DwsGDYju7dy/cHuD1zp1l3tqsmVxnHTpIoUr//vJcFP987M7bzfgvxrP96HafNcbXF3xNoa2Qq364ijJnGWXOMv674L98tfkrvpjwBc3i/74XiE4nSkannFL7OJDVCq++CvEJLl5Y8ULAYgSby8bpHU6v8Xtc3vtylmUs81NdUDWVF/94kRdOfyHiNrt2he+/l3Xqiy+KGvquXV4F4tRUGXPuuEPI9LV2xIltCWeshgWjoGh7+AVEeis0GQonf9+wFTcqo9cjEmd31oHMr94MvR+j3FnOrqMBFkbgo8YWKbqndg8YIyi2F7Nk35IaK2j+U6H8E9hrtUH//v21P/+MYIL0d0Q4vV0Nr4MnFj/BQ789FJK8cXGPi/lk/CeB39NZDPajIiloO+r++yg4y9yyRqr8r3l05PU+221rvuP17YtRg3hY6RQdd514F8+d9lzYn2nvXgmKFhZWu2utkZwsi6iwVXkWngmH5kMQq5h6xcW16CvCuAYzD2ioqhAjDAYvScJkqls/4cpwqS4+2/gZU+ZNochWFDCIbzVaMelNPDriUW7ofwMmfe2qttdnr+fE/50YcHIFIgO97859tQ5ArM5azcnvnxzUmiXGEMPeO/bWbaCjnqEoyl+apvU/3ufRENDgx67Di2HtVJGd1Zz122dF0Ddt3ixEjo8+kkB8TIwEokItnirLyzudorJz2WXyv1+SXNMgf72QVw78APlrvWOXq8z9PShgbQnW5qIGYWkqUnxxbcEQL1ZZiptbqznET7n8EBTvgfIsKHNvJXtFnSTEd/DU4qf478L/hv39hIMNN26gR1rkhuzFxRKMCVWlVVuENZX583bY+Xb9ytJWc03a7UKk2Lq17omiZrMsdOfNC/z65s0SGKsv4khlaKoKGx6DLdNEyrnqd552CnS6GZqNEcUdQ5wEtWuCQF7hHtRm/lIHiI5dXjSUsev55c/zwMIHKHX4Zw4aWxuTcVdGjW2i1h5ay0nvnhRwnmcxWFh+zXJ6p/cOeGxpKXzxhQTjNm6U+7k++kydLnjfY3fauWvOXcxYNwO7y47DLcuuU3QYdUYmdJ1AlyZdKvbXNI3Vh1bz8/afK6xUAEx6E1ajldsG3sbDwx9GF2Hm2+6yM+nrSczeNdvnd7IYLMy7bB5DWg3x2X/hnoWc9elZPt+71WhlbOexfDD2gxpJBn/+uahdHYsEU3Xj18aNQtapr77baq1G0cVZCt+3kDV7PeG1uTdzz+fT/KxTFEWCvM2b1z+BYuVKIcoE+p5ffx0uv/zYq3QeL0THLi/qcuz68+CfDHhnQMVjnaLzsTAEQINih5csoFf0lPy3BLOhGumXqjGXajqWwvJCkp5JClu5QqfoKJxaSKwplht+vIF5u2WyabPBQMcUShbdxK5dcPiwKEo1by73i0d9sKRUZWXXUyjWS8WuTgdqwr6K9483xfP2OW9zUY+Lgp7D7rzd9HqjV0WMI8GcwG9X/Eafpn0CHxAoDhVJ7NNlx7n3E3L+mkqK4wg6gxW9xw5atcuarelp0G0qpPT3tr/wDDi8yHfuG9sGej4MrS9yW55ooDND7gqYPzzw+19QENpuNIil4Lp9J/DgijXMmgWNGknF92WXQffuQqoPJVtvMsn6NyND1m5Wq4xBJ53kPydRFHm+WTM55tAhWLLEd45R9et2uWDoUCGVhEOQjI2tRpGjtr9xsHaOdRt7PoJVN4dHFNKZoPNd0Ofp+jmXGrRx4AC89hp8/LEQhJKTZd7y0fx04ivZGzkbp7H790Pk54vK3JYtcn2tXCnXRHrNBYjdpxwduyqjoay9PNA0jf+t/h93zrmTcmd5Rf8fZ4pjzqVzKmzv5+ycw/gvx1f09UadkRhDDO+e+26tLMb9ECpXUU/50qeflqKmmloKWywwdqyoDH+/9Xsu/+7ygLYWo9uNZu5lc2t8ngXlBaQ+lxpQUTHOFEfhS1aU7MM1bt8DJ3rKsGDGhokwiAfZ2ZHJSILkGLe9BJuflphsMHVnQ5yQJXs+BO2vA894X1Mc6+sr43u3nXktFq96Kwx6F9pcxLKMZZz5yZkU2vwTpLcMuIVXx7xao7cotheTPC25Is5QGX2b9uWv6/+KvNHjcC/XJUKNXVHyRgMbyOoF9Uje2JC9gU82BCBmgBAubLnc0KYvbbU8yFsDRTuEnOGRwlfczHOdHnBTtTWnyBOZGgE62Uc+CELmUAENHEVklhXyWr4LtUIiSnMTPVTpZHVmxp/xLQPanRbR55o7VwbD+kxuWCxir3HiiREcVHoAfux87NU3YtLCYnU7HGJFkpkp42l2tiz6Hn4rnSRb8AqRQ6TR3irtV1UscjqFlZ2YKNVQ6enQqpVs6elCfDnrrPCkjT3QNI3vtn7H5DmTySnNqZgQGhQDFqOFyYMn89qq1yiyFWFzyYI71hiL1Whl2qnTuKz3ZRhqOIhf+NWFfLPlm6BBkv7N+rPqulU1arsyNE2j6fSmQX1gY/QxTB48mSdOCd9a6HgjuhDz4m8zdhVuh60vwJ4PJbjlKq1bIsctOsivWRlqFulsoStb6cJ6erGBnhQRjx0TelyYsNGSDPrxF93YQme20YWt/guK7GxonAL7PoM1UyTgojoqBesUaDwI0k+H5meJ9B6aO2inyBioNwdVzqiA6gRXuZcAoreAPQdy/hDbmirYcmQL3V/v7lP9XRdIMCdw9D9Ha1RN/eSTUqFVX4mwsKYy5Ufgh9Y1s+0IB2GOl3v3Qs+edSsPrCgyTm7dKgGzYHjiCXjqqZoHDMJFxe9Rlg2bnxLSjGIAZ5Xggs4MqScLiSOpjxCZLOlyzat2KmSEFUX+rhg/Nfcc0gifh5gERMkbDQYNYexad2gdg98dHJBcEWuM5dUxr3LlCVfW6j3GfTGOH7f9iDPAeNcyoSVbb93qn6yrgvx8UVr4+mtRBMzMFMKhTif3brjEL5NJ1hyeBEm7dpKcfrVKrEXTNO7/9X6m/T4tJCm/JjDrzTw7+lluG3RbWPvvL9hPj9d7BAxEGnXGoOOPS3UFDAIlxSSx+ZbNNbIkvOuu4FYadYlwxq9zzpEKtbom/SkKjBwJCxZUs+OOt2DN3TWyswsHxeWxtLgtg4LSJL/XevSAZcskiVffBI6vvhKFrEDJzXPOkWpyvV5U2OrjXIqKpO3jjejY5UVdjl0XfnUhX2/+Gg0Nq9HKIyMeYVzXcX773TX7LmZunwnI2PTymS8HtDv0QYTJ2olfTeTLzV9WPDbrzX4EEZvTVhEPAW9hlqbJ+HTzzaK0EBMDl14qfva9e8upOBxeRQbP6SiK7FtcDPOWHebqDa0rLFsamRvx9YVfc2q7U4Oec6GtkMbPNK7o6xPMCXwy7pPgVZq1SOyrmsrnGz9n8pzJZJdkYwS6m+GSTmdyVd9rSWncVxQTAr2HowjmDILi3f7kZb0VYlJl/lp+BBz5wU+i38vQ/ipJKAVCEPJyzBVl2F0xaJqoXNxxR+37qzVrRPY+Pz98VSqjMfC+eXliDbd+fejx1WqVcfjxx0O8yT+FvOGyw8z2UHag+n0NcXDuLrmO6uNcImzjiy/g2muFyGUyyRzzoovkcWxsaOszp1PmtWZz3RTtRccuXzSEtZcHmw5vYvRHo8kuyfaJhxsUA/2b9yfe5Dv5yS/PZ3XWap91iU7R0bpRaxZesTBshfWQOA4JX1WFU08VhcRIFYEVRawaN22S/vHcz85l7q65fmO3w+Xg7dOe5NI2g6QQzFEocUpHkYw5NncRtbNI4pJapVybonPHJnUMW7+aNcWF7rWXOxajQInTTvFLFmKO1nNAKRDS0iKytsgpzeHHbT/ywboP2JT1F0+17cT4mBKSbBkoqhPQJLaa3Bc6XC92kbUlbXhwPAgFK66FfZ/WLN6pt0DL8XDSRwA8+/uz3P/r/dhV3wvVarTy8hkv10o1vskzTcgpy/F73qw3U/zf4shzblHyxj8XDWkgqzfUI3nDB65yODATDnwHuaugZL/4MYI7YecCFIhvD416QHxHSOwtMkamZPFqNCYIy01zuQcQDSoSTxrewUKRBIDOIAw6ZxHY84UYUpYllc+F26BwC4xZX6OP8+ijMG1a/QTrrFZp+9Zba3Dw5mdhw8PHjsCht8BE//dSVWFI//47LF0qTOl9+7yBZZdLJuuOKjHUxEQZa9PTpSLDbPYqbeh0Mnl3ueT//HwvCeTwYd+2PAt/o1H8v8OBpmnM3TWXO+fcSUZBho8qhdVopV/Tfnwx4Quaxjclvzyfa2dey6yds3wq/mKNsSRZkph+2nQmdJuArrqEayVkFWXR7qV2lLvKA75uNVqZftp0bux/Y8DXI8WUeVN4acVLAQPZINUt2f+XjcX495ABiy7EvPjbjV0uO+SuhKw5kPkDWsEWnOjR6U3oNdXdn1UZh3Rmr+yrqwyMiZA+WiRs00dJsKLWOnp1gBbAq23AluNfKdP8bOj7IsQ0AV0M1FK5J1yoqkrjZxuTV14/FbLndjqXHyb9EPFx9am+oSgRyMmvvhu2vw5q4L64xjDEwYXhf7jffxfyYVFR7aXwjUYhbCxYIFV1oaCqUvG2alX9SdGbTP5SyThLxS9835dwaI43SBBsPhOTLnNGcxMJcOtMgCJBcNUBtlzxGi/Lwq//qIwoeaPB4HiPXaqm0u6lduwrCOzT2y6pHdtv3e5LDlAd7gBXrlxztlwJdqn2SuqA7jWOogednr0leXT96WHKXf7zL52i4+gLZhrlRxZQcaJnJx3YRHc20IO/6EchjSgjhnJisGNGh4oZm/uZctI5xEBW0p1NdGcTzTjodUSuVLX0297fuO2X29iSs8WPuKGgkBiTSJwpLqCfcmVoaBTYCiiyFfkRBw2KgUEtBvHymS/Tt2nfoG2szlrNoP8NCmj7VxuY9Cb+uu6viJWjNE2qlb/7rv4IHNWqXrhRX8pJFouMR32CFK5XQHXCD22gLLNuT6AS/th/BqMemxXwuz7hBPjhByEpWkNzn2oMu13Gr507Jdn5668yTlYeKw0GCbpfdRWcdpo8drlkXWquRhihKpxOua40TY5duVLIIe+9V6cfq0aIjl1e1NXYlVmYSYdXOlSQFcx6M4enHCbB7K+sMG/XPMZ/Ob6CxNYyoSV779wbOvYQQbL2UPEh2r3UroLIaNKZePe8d/2IhSX2Eq6deW1F4N5qsLLnzj08ek8qH3wgfVe3brBokdyXkdybaw+tZfgHwysqOhPMCSy6chEnpJ8Q9BhN0zA+ZqwYqywGCy+e8SLX97s+8AE1SOyrqsp7a97jscWPkVWchUN10DqhNf2a9ePbrd+ioGDSm5jUYxKPjXyMFo1aBG7Ing9LxgvR3hVBgsuYKOqLHqJcr8egy2SZMxurkDiCKG/c9sHL/G+JECZ79ZJ+pXVr6eMsltB9lcsl/ZKqimpHZRw9KiSd336TeX6w9YuiyPv07StKHIHgcMAtt4gipqr6JjFjY+Vnev99uPDC4Oda8WZV8XckbwAcWgCLzg0d6zXEwgnPiHphfZ5LmG3s3CnXmGdu4plPWI5TiDE6dvnieK+9PLhvwX08ufTJOmtPQeHZ0c9y90l317Kh45Pwzc2VeW12tn/OJBgURci9K1aI/QjAnrw9bMxaBfkbxXapaDuUH8bkKubUuBj0Sb0goRvEtQFrK7f6b7rEV/SWKur2Orf/lTtGo7nILspi5cGVEo91FIAtT+KetiOcPvw1TJYIFDCO4Xe9O2833235jo/Xf8zmnM04VacvYUhnQK/oOKXVYCZ2v4gzO4+jSVyEah7h4HhcX65y+LmHKDVHUpCh6EUR+uwtYmcOjP5wNPP3zPfbNcGcwJxL53Bii0iq0X0x9L2hPrZ9HsSb4ll05aLgimrBECVv/HPRUAayekV9kzcKtsLmaeKtpOj9KyoNsdByAnS8EZJ6g+oOcuot9ZfIUp2SJFAILTMYApomi4kZM+o2WBcWezwUVCfMHQx562RRV5/Qx0L3e6DHA4AEmH77TRZY333n9casGkRMTBRFkT59RL69Qwfx5E5I8JI6VNXNwamyVVbd8CwGjUYJiJWXC0v/0CEJbq1cKcmnTZuq/yjfbP6GB397kD15e/yqLc16M1OHTOWSXpf4+WLP2jGLexfcS7mz3CegbTFYaBLbhAdPfpCrTrgqLDnoKfOm8Mofr/hUr1Q9j4y7MmgSG9rrNVysPbSWoe8NDWqdEmuMZfpp07mh/w118n71jehCzIu/69hVYi/hzb/e5JklTxDryKOdSeGspt2Z2PZEmsUkSDJdZxTihqWZLDJi3ZupkX+D6em1932uDczAywrEBRhDO9wEfZ+NzKO4jvDSipe4a85dAVU3ki3JYbOYSx2lFNv9pSH0ip7VN6ymV1qviM+tvtQ3wk1+AZJ8/b5V3ZMgY9vCebsjOmTvXvE9PXhQxriawGqVBfzs2ZLUCgdZWXJMuOTHSJGUJAHeoNBUyFsLR/+SIEP+RijaCWUH3QpsMcLHqLDQ81SD4FMNIoEGvBZCVRGmEkp9Ijp2edEQxq4nlzxJRkGG75OuEig/wvUtOtNHOwQFG6H8sFQnqTa3OpJRxidjIyGcmxJlLeMhbaBVBLpwFPHpob0sKcgHzW0S77mGdQZeeMxKTO4x8GcMhbQ0/lr9M7fPvp21h9b6WchYjVZaJbTi+4u+p3PjzhE1vTJzJed/cT5Hy45WJClBAq0xhhhGtR3F9NOm+7W7+chmer/RO6BiiUFnINYY3nha4igJSP4w6oxsvHljxB69Tiece66sgeqaOGG1wplnSgV7OBg/Hn76KfJKvWAwGmHUKBk/wsL+r2HFlXWvvqF3SxR3m8Ivv0iyrrzcX2XEYoEHH4TbbpN1Yl0pVJSWyjr0++9h0iTv8zt2wHPPwZdfynVgt/t/9926QZcu0LatjKtdukiSNClJihP0ei/B1FNhnJEhapWbN8Pu3eL3XdlCoCGE6BrC2KUoyhnAS4Ae+J+maU9XeV1xvz4GKAWu1DRtdahjFUVJBr4A2gB7gQs1TQvJdq6rseuu2Xfx+p+vV0iQn9ruVOZdFtjnzqk6SZ6WXEHeiDPF8fn4zzmr01nB3yCCZO2kryfxzZZvcKgOjDojV/e5mjfPfjPgvtfOvJYZa2fg1JyY9CYmdp/I8v98yM6d8vrNN4u6Q6TkpZ+3/8zF315cQd6wGq1su3UbLRKCkCHcSHw6kQKbTGAVFO4bdh+PjXos8M4RJvZ/3/87Q98fGt4HcGN81/F8PO7jwHZrmioy7ZuedBOWgwwiilHmEi3Hw5CPIX8D/HUn5CyT89VboNV4aHoGJPZyK37oARXQy1zlS98xMmukxpdfwvz5Ei8zGEQVpVMn6asSEiTGZjJJX1teLnG6fftg2zbYsEES8YGwfr0Uu82dK8ca3c5kHqLbsGHw0ENuleFq1ut7ac0b3MgPjKUUK2lkcz1vM4nPiMM91oSSyf8nkTcAFp0HB2cFj/UmdIUxG6q3mjxGn2f7dklCe+ZHK1bIdVZf1tfV4ViOXcd6jFIU5V7gGsAF3K5p2pzqzvF4r72K7cXc9PNNfLrhUz/1aQWFWFNstQWRqqZSYi/xi23pFB039b+J5057rsZ2l8cz4ZudLX3lvn3Vz+t1OsmzLFki884KbHsF1vxHilycRVQUtHS7B7r+nxSQaaok4+tKTQLE8lYf4aBfj9+1qqp8tukzvtz4JcsyllFgK0DTNJyaE6POSII5gbM7nU3P1J4s3b+Uubvm4lAdOFQHZr0Zp+qkRXwLhrYeyrV9r2VEmxG1Op8KHK/rq/SA5A3LssPLGyoGIfScvlzmFwhZNmlaUsV8qzKMOiM5/8kJSD4OF3fNuYsXV7zo97zFYOG5057j5gHVEBSrIkre+OfieA9kxwT1Sd449CssOkcSboFsIJqeBkO/ATQwNgD9zwihaXD77cL4rgt5casV7r5bFjq1Qvlh+Lm7MB7rC7oYqW4f/hOqpvDFF3LuxcWyVb1kUlKElDJxolialJbK543EziQSqKr3NwkVuPt43cfcMuuWgB5dADp0xBhjQk4YNU2jzFkW1OrErDfz9KlPc+eJdwZto8ReQvpz6T7+tVUxqPkgVly7IujrkULTNFq80IKDRQeD7tM8vjn779ofkYLI8UJDCCI2FPzdxq6jZUd5YfkLvPjHi6iaSqmjFB06FEVBQ8OsN3NC+gk8PupxRrYZ6UeiqlNU13Yk42HBVpjdN3Ag7tRFYgVREwSpogoOHVwsGY5Nhzcx8J2BlDp9E3EGxcDYrmP56oKvwm7V5rTR6oVWHC719bJUUGjVqBVbbtkSsXJPfahv6HRiA1Ct5HtlbH0B1j0QWSVcKOgtMOJnSBsZ8aHFxeJF/fvvkZNarFY59t13Ix9vf/5ZEmR1TaSxWGDmTDj10hqSq6xAqnuzICEtg3sDcCIhKydQDhwBsoFAP2VNPFHrGNGxy4sGM3ZpKmQvhO2vQPYiqVDRm0TNT3OIvVVyf0gZ4LXyMTYSUpFH+SXInLACisFrDekskTl7wVapiur5YM3Ouw6DEjf+dCNv/fUWCgoGncFn3NUrem4ZeAtPjHoCk6KvJK+b6/7fvdlyvXZeqtNr66UzUOxycfOGhXyTtR1nxXeloIGbWKHw2MhHue/k+wFYsm8JZ316lp9Vik7R0TKhJa+Ped1PEjgYypxl3PjTjWQVZaHi+zvVtFLIZhO1hTVr6s5yKjYWBg+GX37xJr6qQ16eJN3qireakiJ+803C5Y1rmqxBC7fUzQl4YG4MYzMqVDv37BGiyvbtgb/v2FghWdx1lxQJlJUJSSIuiLNAVZSVyW9qtYq641tvwTvvyPca6FZSVVi7VqyMvvlGkpqKIslqTZP2aqpkpSjyefR6qb602epPFSuy8zq+Y5eiKHpgOzAaOACsAiZpmra50j5jgNuQxNgg4CVN0waFOlZRlGeAo5qmPa0oylQgSdO0e0KdS12MXYW2QppOb1pBlIs3xfPOOe8wscfEoMdc/cPVzFg3oyIG0a9pP/68PsR5hJmsXZW5iuEfDK8oaIkxxLDxpo20T24fcP9tOdvo81afiv0tBgvPtlvP/Td3oKxM5uEvvABXXCEJqLi46i06XC54bfk73Lv4zorvRK/oKbq3qNq1ResXW7O/YH/F40k9JvHp+E8D7xxmYn9rzlbumHUHv+79FafqRIcOk97EBd0voE1iG599y53l/LD1B3bn7capOTEoBhrFNOKZ0c9wRe8rfNS7souzWZ21muW756DueJVxVhfdzaAoBnQ6PXrNhRLbGpqdCV3ulsIFJFm5v2A/q3d8Q+PDc2hdtJYUVx4mnJRrCgoaen0MOr1ZZN81JybN5tXH+iEWvvTtPDXgEOlk0BIbZmyYsWOqZBlqx4wNE3YaUUB7dhFz72TxWgwCDdhNOzJpjoqOdA7Rie3oKidZU1Olo60NQsnk/9PIG2VZMKufzBt9km46UV45dbEURR6LcwmzjY8+gptu8o6rb70F558vhKDqLMZUVeICfzfblGM9RimK0g34DBgINAPmA500LXRp/fFcey3LWMb4L8eTX57vQ+aO0cfQMaUjv135G8mWEF6vlZBVlMWQ94aQWZRZQYAEGY/S4tL4buJ3IVWbguI4J3zz8+Gaa4REHSwmExsrdruffQZt2lR58dfT4fAif3uu0/+A5AFSVBAJaSOiOKQ3BhkW6vi7drgcLN63mKeXPh1QHaK2uHPQnVza61L6Nu1b8/j08by+yrJh/jAozQxdtKa3SsHT6KVgbVbx9L78fXR9rWtAq9mkmCSO3hOqUqt6fLD2A26bdVvAYsHzu5zPtxO/jazBKHnjn4sGE0SsT9QneWPpRFHcCIbTV0rgs7aIOJFVGREOKFWgaaKS8dRTtau2slikjTvuqHkbPshdBfNH1I99iqIHa0sYswFVH8eECcKqDxQ8UxSxgLnlFq88YkPA5iObOeOjM8goygi6j17RB/XNDgSX6grpA54Yk8icS+cwsPlAv9de+eMV7l1wb0gVjBdOf4Hr+l0X9vmEg3vn38v05dODWqfEmeL4bPxnwX1iGxCOdxCxIeHvMnZlFmby1NKneG/Ne2holDvLMelNxBhieGTEI8zaMYulGUsrgnaxxlhaN2rN46Me57wu59UPqaguyRuqCxYMh9w//RdMjU+EkfNksaSPMBIRxL84JC6W77fH6z3YlbfL7+UYQwxbb9kasTfoJ+s/4YafbvDruywGC5N6TuLdc9+N+FQ//RSuu67uSANxcZJQ69AhgoM0DRafL/YdQayswoY+Frr/F3r8t8ZNqCo884yMp06nEDpCIS5OgmOPPy4ewzVdT959N7z5Zt39Fj7qYg3B1giO+2ItOnZ50SDGrkMLYNmlYnPlLKGiQklnhM53QZc7wJBAvRHPVWfNK5/qMCgxe+dsthyplIB3lUlwp/QAg03lnEg2lOwR9RGdSb4fvdVtddnIbXUZB+Zked4juYvmtZJxFjM/axsbCo8I0d9VLsqImhM0FwNHf8uQjufy5aYvuer7q/xIhwCNrY3ZcNMG0uPSI/p8BwoP0OuNXgHtw6xGK5+N/4xzO58bUZsul/TRjz8urIq2pAABAABJREFUCYmadi06nSQpnnhC1oVhiPf5YM0asb6qbb9ttYotyKBBER6Yt16quepqDaq3wPCZkH6qz9Mul4xPDz4oCeFg46LZDD16iOLj4MGyNWsmhBijUW4bh0O23Fz480+x/Fy9Gtat8yeThvO7apq0tWePbNt3OZi9fD9/ri/CnpuO0ZWITjOhqjpcLnfhvFuFw2CQc27eXOYt3btD+/YSkG/bVp7Xh788rTcc77FLUZTBwMOapp3ufnwvgKZpT1Xa5y3gN03TPnM/3gaMQCqWAx7r2UfTtCxFUZq6jw8pL1QXY9ezvz/LAwsfqFDgNOvN5P4nl1iDSYhwqr0KEQ4WZa7m7O9voNi9TjLpTdyhbaFlXBP02GjVwk7jZAc6xYVO56L/SF9VoTW/bfV5rGngVHVc+ucp7CjzxkgGNjqB70e9TNP04GPMyd/fwpIsrx1x35QOzBvxKk+91IzPfmxDTp6FFs1VhgwzMHCgjmHDhBxmNsvmscWw2eDAAVEy+jjjv2xK9RIDTDoD5TeKx4bPbVjlnuz/1RWsydle8XhwWg9+H/8ObH8F1W6j1G6mLO1SypLOpHUb/8+0eZOGokjfq9NJP/HShvuZsexJPPHxYfvggx8gtszEUZJxYMSJoWJT0Pi551GmnZ6DXa+hALF2jZu2xrLmytP5cduPQeMvRqCJHvQK5LqgVAOdomdU87M5IbU/z61+IOjvkKiDriZobQCzAkYF7BqUa7DLAVvtUKLB7pMvpHSvO04b14Y2520k1uRW5ghCdlA1le2523Gp7niXvQBDwUYsRRth2yvENjmRFGsydJsqhV5NqsS8jqxE0zSOlOVR7k6uFjtK2VWQiVGnx+AqRoeOJjGNaJQ2mPiENiRZfRO3h4uzKSwvJK88j6NlRzHqjZTYS+iR0oG2cSlCnq1sr625oFEANa38bZU+qwYozJyfz933NgUFyh1OPp2RTqNEGYAVoGdPX4Loho32imtP8fyrqeT/di6qy0XOUTvdTz6XJm37VigsJbQZ5dNG4d6FFX8rUBHbmP5FCRt3mCjJ2Y0hReGUIZ3Q9FYMZpGqt5DLOc7racR+9NhxYcZOLDMNH4ClNwoKB7KWsdf+KaVqOctKN3CUYmwuG+UuOw7Nifaw71difcyMWWciRm9mUEovOjdqTZKpEVe3Px9bSRkHd+33XAp0Hj0Ru5ZAWpU+YdNGrcLyWq+XeycxUZLL+/bByy/LOr+gAJo00TjxROjdW6FLFxnnGjWSMdDplH127YKtW2HdOo0VK2D//tqvHY8heeOYjlFV21cUZY67jeWhzvN4rL3sLjv3LbiP11a95pf4tRgs9Gvaj9mXzvb2SWEiryyPETNGsD13uw8ZxNPufcPuI/vreykokPtMVeV6VhS48kq59jwK3x6171NHB7/mFsz3Dj6BeEyethUFGjn+wOLaDQocyIBt20GnQPP2TYhtZEXToEN7aNtWq1AQ0TT5W9VUFv+exKPPtWbl6gTMZhUFKCvX0b1zKf93y0EmjcsJvAxUHVC8GzK+FhKHpsq6TQOS+4jldONBohBrTpbiAg/x3gfuxn/sBLYIyHYXFLoLGjx9slplIq15+2triLVcaThKqfJl/7BjNh9s+Iw5exZic9pQK00SYvRmdDo9o9udyiltTyXJklRtqwcKDzB752yWZSxDp+gq5mlCk9RItiQzrss4zkq9mfiSPhWK8RXv6Vaw8lxXla+vocOCX19LFvsvOCr/xp5ry26H/fu9jz3rIb1eFLQ8a4yOHb3vXdGGaiM99wnS855DQ4de88Z0XYoVBY3spDvJSnkQTRfj895/5MzljhVnYvVZqGq4NOib1p1F57/h2VsuH03ByyCtvi9fc2Qbg7++lpgqxRlO1UXLuFS2XPyZPJH7BxyYiY+1Dwq0vQzaXBz4y6uKvwH3IUreCIEGEUSsb9QneePoalhwigT8qiauQKrWhv8EBgvow6DgB0NNElmVUQd+58uXw9ixUFgYmbS5xSIL1x9/FDm5OsWBH+H3i+qWwKHowZwKp6+A2Fa8955I0wYLEE6dCvffLxP2hoDdebv5z7z/8POOn7E5bf6e227Z5Wv6XkOrhFYRt3+49DDvrX6P3LLcgAtyq9HK4BaDef705yssBVyqixYvtOBQcfAJiVlvJnNyJinWlIjPKRQ2ZG/gxHdP9JPDroz+Tfuz6vpVdfq+9YHjHURsSGjoY9fS/Ut5eunTzNs9D03TKu6VGEMMI9qM4MGTH6yYSC/YvYD7f72fUmdpBYvearSSYErg9kG3c8egO7Ca6tDcvC7JGyB2DWumwp4P3AHXSv2COQV6PAjtrxGih94cnrxgTQiLF2vc+NONfLjuw4DWUNf0uYbXznotsjaRyq9Or3QKSAipaQIMhHDw6ae1l6C3WuGTT2R8jhiOYvilJ5Tswy8yHC50ZkgbASNmBa/8sufJ72k/CvYCqWJ3FIgXti3XXVnlBJ0Zu9PEl/P78fSHZ7JtfxrWGLknFEDVFMrtRvp02s9/r5jF2UPXo9c5RLZSZ4KYJnLNGRuJVV0Y0DSRun7ggdr/FhaLEFBuvdX9xPG2NYLQlXrHCNGxy4vjPnaV58D3zSVJVhUD34E2l8iapQHCpbrQ60OQPmqylrPlwp6PYfur0g8aLNKfqDYwJUklcOPBkHIixLUTwoZqk7HOnQxB0bulu3W4IzdUBOo8JA40d7DFrUZiy4GiHZA6jOnLpvPAwgcCVvVYjVaWX7O8RhZdAH8e/JPhHwwPOAeusSQrYnVxwQViexUpgSI2VoJrX34p/9cU774r6pA1JXDExkpRwW231fAEMr6DZZcEtwAIF3or9H4cutwVdBe7Hb76SsaXbdsk+F5X6idVERMT2Vi4O283r/zxCv9b8z/QoNhRjIKCUWdEp9MxtNVQppw0hVPbnfq3UDmsjOM9dimKMgE4Q9O0a92PLwMGaZp2a6V9fgKe1jRtqfvxAuAeJDEW8FhFUfI1TUus1Eaepml+0X1FUa4Hrgdo1apVv3379tXq8zzx20O8ueo1d9LEzoVNmjO915lui8i2Uu1oiJV+UpG+3uWyMeqbq9ldkAGaCytOtjWvpCZaNcZVed6Vlgav47eecGlwygHIdOfnDeZkPrxoNgOaD/BvAyAlFl4u4Y9yuOKQCJ8BfJgGgz3DpT6GrJPLWLFC+sVdu2DnTrEHKisDZ1kBijMPg85FfEwRrRvvpVP6DoxNNmLu92HFW3UZ8joT+94U/Etc/zBsfISlZbCgUt/3+GQbTqfIzz3yiBC+xN+3DFq0hexKiajUJrBvI2K95950JnLyLMzqcBuzC09kC11pNbQ1Lbsl0KajgbatVZo1U4ixSP9j0MtI53QKKawgX+PAAfh25Wq+T/Oy4WL0MZzU6iR6pfaiY0pHzJXWgHaXnZ1Hd7Lx8EaW7l/qQ15sPut3cg6koDlNXHmFwpP3pWI1ylo4pk06ymHv76OlpVG2O4uj5UcptheiaWId9ub8S3g3w0u2MemMjGpzMmd3OJ3Uux+HAu91VJpoYuF4Oz+UQH4lsarTLDA3RH+Y9Syku/viQ7HQdErg/U6MgW4mSNdDp/hU2qb2JiU2nbiYRFqc/R76XGlETYmncMmTqJoLVXWiuew4HQWU2Qv5/aMi/tzTn8OFTTCkn8iYC9rhcMja45zr04nJ934n9qQ0Vny3D03VUFUoL1MpLXWxdO5zvPjuI97vruq0qer9E2j9oLrg80pzsTPXQVKlOUrVNubeCBsfoSoevuQhHsb/eR8oQDekN8sG1uC9AYHz727K9/FZQQ8P6/cpj+dd+33MzbyHTZugXTshQ3bsCC1awPCL0jHmyudxNUkja/UhXC6vFXZuLhzK0jir33wsebMgdwVoLvbazmTVrn7sy23Ltn1N2L47jqxsIw6ngsuloNdrGA0aTdMcdG5fTKdWR2idsodxt52F3lC7sfIYkjeO6RilKMqrwApN0z52P/8uMEvTtJDGe8dj7fXZhs+4+NuL0St6dIqhInevotLKdjoD9nyDy26qINEZDBLTiY+XeVhlcl1Ve/VytYTP9WeSqaxA8Wj8aKApDlBUzvphJj1abiTRkk9KfA7JcXmkJBQxfGwfIZ3rYtz5KYsUWA28FXIK/D9Ek2TY+L387UNO0GQdpJbLGONyk9On3ggRCgUEQglWttMJFR1t2UMy/iR0P+QdhsQmbim4LCjeKYSO0gNQtAtK90nM0lEsMSdDnNh/6sxCzlcMokCpGGRd5yGSqnY3Wc4lipWV4pwFLkiMzC3Yp0+qjFDjRyB039gdNXWT3/NNSuH2P+DcbWCsRiAzEIpM8HEv+F9fKKuy5FaAspl/sedAX7/jSktDFDEHi4dFEKO655XlPHP7YL/n77vPXTAVDsqyIXOm2F/acoTI03I8tDgPLE0DHqJpGsvf0+H3VepMdJ14MPLc1fqH/cbDtTYoDvBbtU7tR8vBr0HxHolR2I6IA4HLJvFOnVHuX30MKEa5fruHENHb97VXNVVTEVtmJzhKxG7IE99wlcu9rToldovijrE2BmsrUWON7wSWtMg+exiIkjdC4LgHEesCLrvcfLYcSQY4SyWZ7yqTvzuGUcm/9CL3H3rvIkbRyYDmqazSW8QnS291D3ZWeewsh0NzYd/n7iq2MnxmlSgiI97hOmgyBGLS5bxQwvfdqpXyBnVC3gAhbjz/PEyfLuNiqMBRbKxMQu69VxIZ9UZuODgLloyvffAMZLCOSRfihrU5IJ/1vvtkch4Ir7wiSbjj5WnoQWZhJvf/ej+fb/ocp+oM6HVtNVq5pOclvHjGixUL4JrAqTp55LdHmL58esBgs07RYdabOa39aTw7+lk2Ht7I5d9fHlAOyoPBLQaz7JplNT6nYNA0jZYvtCSzKDPoPlajlSVXLaFvU/+JSEPC8Q4iNiQ01LHrk/WfcOecO8kp9bd0UlCwGCwB1W40NGxOW0BClILCuZ3P5Z1z3qFJbLi63iFQ1+QND0oyYP1DcOBb94LHJRM/kEVQcj+xUUkbBYm93cx3vTuI65Ixl0pMYjkZN3vdPabqTH5+xh780v9nJnw1IWgCbN+d+2hsbVyjjzZ752wmfDkhoHJQgjmBLbdsoVl8swBHBofNBv36SbVNVU/7cGG1ioLHiy/W7HgACrfD7H4yf4kUih4szeCsjTJXAshbJ+Py4cWQt1YqFxQDGOLFiiyxNyT3lUWSKVnkb/VWWYCodneyU4IDZWWwfoOO7EMSvGjWXKNHd81tj+KOZCh6uS5Uu8ytnEWSkE3qE5HyxcyZIkFfm0Tg11/DGWfU7PgK/M0Z84EQHbu8OO5jl6MYfmgt66WqSmpdp0DPhySoF4EqG1Arq6tgyC/PZ8WBFSzZt4R5u+ex5tAaMqY5Awa9suMUJr06gtPbn86QVkPo17Rf9ZZW29+A1ZNl7KlMAjenwMD/QbMzpF8xxLnHp7rHlLlTmL58uh/RGoRc8cWELzin8zneJJyzxL0VV/q7xK3k4QnEuAMz7jH1q70ruGLxy5S5/Ak7Cgr3D7ufR0dF7mfpdMoa6I03NDIypLVg5H6LRT5CmzayJrzxxrpRVrjpJpEqj5TIYLWKJcmMGRENE/5Y9yBsnV7zIgK9RQKHgz8M+0Sys+Gnn+Djj2HlSvlejUapQlMjDNR67EpACCLdusEll8D//V/o41yqi1k7Z/HM78+w6uAqXKoLh+og1hhL84TmdEzuyK97fsXmsqFqKnGmOOJN8dx14l1c0/easCXCjzeO99ilKMoFwOlVklsDNU27rdI+PwNPVUmM/QdoF+zYcMkblVEnY9eicyDzJ/k76QQ4c03o/YOOKwqcuVoC2JqKm97rHtOq3EeLz3MHn6vgG2qfZFKA4SfBbzWPX7jQ8dc1r6O78QYURWJnOp3cyx7FmsrwVDmD93+dDhJXDKBl3Gp5vuN1KANfq+AXyoEhPoMbHTro2L1bnrjoIpGnV9XIas/27RPrGE0TUsett0q/7+nv+4xJx3RUflNHchob5h3yqZJ1ueRz9ekTwgoxTIsQTdNYn72eTzd8yjPLngn/QwDDWw3nvyf/lxFtRqBX9BwsOsh7a99j/u75HCg8QEZBRkA1WpPeRMuElrRMaMl5Xc7jwu4X0pQylB8rSSNOLA9dyBDkuk+5IYejxZIomjRJCgCiqD2mT/cd8zyXUuV7rVoU7YQfK7FRPdaxwRpZ/3BAQgsATYbD6N/CfOPAOIbkjWM6RimK8hqwvAp54xdN074JcG51Sj6MFN9+7+SG24vIywOLm4zhcMDZZ8OLTyeSnKyg00k8yDN30+m8ii4ewkblzUPeEGUDjbzy/AoiUcXUXytnzY/NsFftEs0ptD9tDv2a9Qt+0j52mO4GNjwCGx+reLZYhTklvtkuD1o3PoG0U75Dp+hQ3INLsb0Yg86AUWdErxPVb4PO4Ca16GTfSveI5lZAUjUVl+bCqTpF/ds9z3SpLqxGKzqdrmI/i8FCWofeFQQBFzoO0ox9tCabNA6TSjZp7KclmbQgm1ScejMJjc2Y4wyYzE70RgWdUUFvUNAZwOUAl0NDdag4HQpOu56SPDsl+XasWglNyaKFsp8btgwlJsmIS3XhVB1kFOxnX8F+bM4y7C4HdtWO3WXH4XJU/G9T7ThcdhR06HV6THqjbHs+xOgqxaSIopRJgRgFUnTQzSwuunpFXHTLcjpiH7ndT6XCbA48ZncYmo4h139ccaaksX3xoWr7uorXj/5AUtl3mMwSq9OA3NJcYpIHY07qiculoWrgcimobvKg5u4HPbl3TVNQFAXLge+wHpyJ4qZGKEollRf39afTqShoOBUXro2Xk/z8OxX7qCi40KOhoKKr+N+zVZy4oqB54oae60zRoVS+3jVN3tNzg0FFS8/ff5SCMrPfd33mmZXuTVVDUVwompMTx7fGlOev3GJPSmXl11vxTLxEr8y9KYqEvVHQ3ATm4Qcr54k9xSH453Y9zDBFF5wok6iD1yJZJNbOvaGmiJI3QuC4BxHDgaYJY+7on2KVUbgFSvZD+SHxHVbtwtJP6CoJd0tTqZYyJ4M5HQbdCkdCsPXSmsC+rfgmidzBL9UdDHOVur2Nc6DczXhy5Mv//V6S99I0yFkBB3+BI0shf50E1PQWadMjTay3QqOuEN8REjoLeykmTZhM5mSpGDXEeWXmPTcjGhWJLUXnlt4tBnsh/BjYn7MCdUTe8KCkRCp9Z84Uj/riYq/8W6NGImV73nmysDgmpIbshbB4nDuAGViesVrorfKbjJzlw7wrLIQBA6SKwh6gUDE+HubPl4BXuD7DdY37FtzHM8uewaW6AgaATToTsaZYPhv/Gad3OL3O3ndV5irGfTmOnNIcP9k2DxQUOqVI1bpBZ/C9nt39r1Nz8UH3IVzSrD0yeBmE1KQz+lYq6mNksasY3PtVTvbqvAOypiH3sPz/+KY5PLppLnq/4Lu8v11VebbzQCa37uo9N71V7kljgsiGm5uIlU5sS7lfj0P12PEOIjYkNKSxS9M0ftv7G/9d8F9WZK6ot/cx6UxMHTqVO0+8Myz5u6CoL/JG5eMLNok0f/YCGbftR91jmiJJJmc54JKx29IUYprK/war+343usdjN+vdngulB6E8S9j0VZDthM4HG1Fg868asBgs3DPkHh4a8VAtPpLGwP8N5K+Df/n1sUadkf7N+rP06qURV5Xu3w+9eolsaqTwyKSvWCHjb62Q8wcsPE3sAcJV4NCZ5Dc7dYn0ix58bg5c1d9lMvSdXssTrV+sXg2nnSZVkuGSOKxWSX4tWCBerLVGlLzxj0aDGLtK9sFfd8DB2W4CXaWLvclQ6HwnNB/jXQMZYqsnmtdQLckDTdP4Zss3fLrhU5ZnLK9Qd/PItXoQo48hyZJEo5hGqKpKfnk+eeV5PsRHHTpUVMx6M83imzGs9TCu7Xstw1oN8763szQoEZCBb0G7q2tu7RIBnlj8BEv3LwVUUSVyFsvv4SzhgoQYrm6kylrXEAuxrWSsjEmVzdxE1rs6k5yrYhTSjWKUxjVHhRrWW1vm8n3GKrfcul0KH1RRGBlldjLlyj3VVtBomkZGYQabDm9i05FNrMxcyayds4SYndca/daJxG65CfvRdFx2Iwo6rFZo00bhiiuELNGyZci3iBiaJhXmzz8fWZ99443w3HO1JG54TmDJOMiaGzmBQ2+BxJ4yhuorZSkjUGzSgH20Zg19+Iu+bKUrB2hONmnk0phyYiQQiIIOFSN2kskjlcM0J5P27KQ/f9GX1XRiO3pPbVl2NqSm+r3fpsObeG7Zc3y79VscLkcFWdasNxNjiOHmATczss1IdIqOfQX7eOWPV9iSs8XHJkPVVE5qeRLX972eST0n+QTtGxqO99j1T7NNIW8tbHsVsubIvL7LndB4CMR3cJN5G8m9oLnjcN+3CDKuHJ+gcoPGzz2hYKP83fEWGPBq8H3XPxwwcTxvw6m8seQBFm05Gb0e7rlHSOZt2kBSksS5FEUSjarqTVrodJKULCyEnBzo2jXEeQbS3Q+EulCuq1LVuzxjOT9s+4GP1n3EweKDfrtf1usyxnUdx5gOYzAZgjFH/GF32kPvr2lCaC/cImtZZ5F77DbLmK2zgjGWCjn0VTcLwdYPCq6JKgUFkJcn8dfSUlFEdjjkd6ic3K2a9FUUicsOGiSEvygEW7P30PXNdhWPjY5EOrjGMtA6iU6prWncWOK9erfIWpEzl3mZ3zD34Gfk2gOrfjQxGDi1SRuu7TCMHk0HyPzKmOSeq+lR0bE4YwVvb/iC1Yc3kWcT77L0mDiy7ikK2GYkiNqm+OJ4rL3eeQeuv17iNSaTW4HJCf/5j9gPAuTne/tQg0H2qwmx2eWSPIXTCWV2O/1ntCOjKBMFhViDO+msgUtzMSqtE6/0nUCb2GRAlWIrBfcawoCX9af5EABdqsYHe5bzf2u+w1VBmtSwq05sqgsdCi+e9iy3Db67tl9djT7/zymX83PBEOZyGhm0xIwNIw6699Iz/DQzvfsb6dhRITVVbI4sFu93Vilf72u3UYko6fmNjEaxGszLg6wsOOEEDau14c5jo6gDPPywSJodY9z5aDe+jcnC4fIofkp+y6Q3cnKTdpzdrDsjW/QntVF7r+CAR2xA8TDA3Pmy2f3AdoSjLvitDH4pgV9LoazKFMygwHALfJweJW80ODSIIGIobH4WNj8lRAXF6K4M9TCGFOjxALQcBwldJAilqZUSveFPuiOG5nLL6jrE9xjp6PPy4MgR6dCLi8FWmIuhbDsxju3EOrfQSNtAjHIEs5KHWSnApCvCoNhwaSZcGNHwjNaae5zUyY2nczOyNJebmun2CdMARcGsFPow1Xxwi85X/6+uvwqgmDjKicFCGXHUQMc1SJAoIpRlw+8TheTjjOQcFEkqdpkMPR8OGKzNzYX//hc+/NDrV1oVo0aJZFO/fjI58yiP1DeKi+HtcfFssAavmk4ug/uWyP91jVIjTBsC+xsF32dsKxhcuQvWW5HJokiQ6Xo/RuPe93tf11R3NU2lAcMjS60YIiZOaJrGkdIjlZLBlejJAIqO5LhmGPQNeyV7vIOIDQkNYexSNZWZ22by3wX/ZX/Bfj9VBqvBSqeUTnw87mO6NgkVyfKFU3Uyffl0Hlv0GHaX3aeyx+KWs7+277VMHTrVX+1B09xkw3xJxLtKfKtznSXQ/srQJ7D1ZXxYwD6MYNW7wDPEBt6MjcCY6Fu5bc+ThGFZFrbivRzIXsXRI6txFe8i3lVMEwPE6IyY9XoMis7NnXarKng2g1WUkfLX+9iUaRqMOGjk9zI1YBVUojmRA5MPiKeopsl8wuFOklVMhN3S9h4CZwWR03MOOlZmb2HEd9dR5vSXYTLqjDw68lGmDp0a+rsNgI0bYfhwWcCHWzVrsQhRYN488XmsExRug/kj5LupTsnKEAvxnWHUPCGdVsaR38WT8chSCSQ7S6SS35QITc8Q1Y2kPpJ8NCW5E8PGSrKUni+h0pxm09OwZVr4n0VngYtqVgldVCQBl6efloBoUZAYWny8JAH/+1+4+uo6JG9GyRv/aDSEsasCtlzY+wlk/gxH/5KEgt4i96GrDBI6SXV0QhdRzIlJE1UKU6Io6ehjqKyUA3jHDEUn976jEL73z9iXqLBq6EKW7l/K3F1zWZ21OqCyUV1BQSHJksSg5oM4vf3pnNRiMP12PYkue77/miG5H4ycI/2SMcIONmISiyLfccEm6Sc1p3z35hRRbGx+nryOJvNiT2WNh9AcKTRVxk+XA1lPK15itGcXTWPRvkV8v/V7VmetJqMwg6OlRym0FwZsMsWSgoJCTpm/4hhAvCmeFEsKLRJacEL6CZzX5TxGtR1VpxYaH30kFd42W3ClRJNJthdeEMXEOoOmwl93wq53wydw6K2i7HLSp/4V2A2FzFBRIacxY90M7p1/L4dKgssbe6osAzYVhBRq1Bm5tNelvDrm1VopQtYXjvfYpSiKAdgOnAJkAquAizVN21Rpn7OAW4ExwCDgZU3TBoY6VlGUZ4FcTdOeVhRlKpCsadp/Qp1LnY9dqsutnHtY+szyIzDgRshx9zON42HZNKDS+l9nFunm1JOlf44iNFSHEBVVW6XCFvfmURn2FL/ozG5FYPley8uF93D4sITpcnOFIOBRBPEoZFSuFLdYJJw3avHD6B+vZaIjNrb23lAhJNn35u/l3dXvsq9gH7cOvJUBzQY0aCJZFPUHu8vOt1u+5bst3/HV5q+CjlfBcGrb07ig+3gMOgPfb/2en3f8jKpFFntPMMUztvM5XNvvRoa1Hlb9AdXgGJI3jukYpShKd+BTYCDQDFgAdNS0AAGgSjheay9Vhd27Ye1a2LMHMjOlcOfoUek/GzWSrs5ikS0hQezmGzWSPtVolHyCp4/19L0euyqXy0uaKyyUHER5Ocz4UNTRnlryFGsOrfGJJ+oUHXpFz7BWwzir01kVscVQ2J67nU82fEJBeQH2SgU6caY4dIqOm/vfzK0Db6V5QvP6+ipD4pxzYO5c/xzN4sUwbJh8J8dbJT2KKCLFzqM7WZaxjOUZy1mWsYytOVt97r+6gl7R0Tm5PYObn8jgVkM5seUQuqd2r/P3CQfHlbyhKMoZwEuIys3/NE17usrrivv1MUApcKWmaatDHasoSjLwBcJW3AtcqGlanvu1e4FrECWj2zVNmxPq/BpUELEqNFUqOEGCWVVhiIMLiyolWGoRBKqhLclvm0/mlCd/RdUkSeUJDHm8yc48UyQHK8Pl8g62qgqq0wmOAhTHUdnsuShqeZUEkjs4WjmRpejRFBOaKRnNmIxmTAJTEoreJMxgnXvAb9EAPNerQ115smua2Nesu088oULKwOuF4NNkKJzwlARrq8G+ffDee0LiyM6W37hqpVdcHJx0kkwUhg2TBFujRl5WPMgkzGyunvWuqhKEtNvlo+n13utr1y6Ry12yBN75sYH/xu2ACWY4pZ+o6NiOSAJV5/aVSx0BnW4WIpQxUZQuPOozOqM7seeUfqAiUQDe5J77/01Pwean/d4+LOhjYWINbAOOIY5lEDE6dlWPE948gXXZ69ApOqwGK5qmuJnbsuyflDydfsq1lJboKqpjHA65741GrywuBM7JFih7+dl4JVnKnyhu6TdNA1Vx4FLK0aPn49RLGRRbSpJhG1YyMFIIKJDYCzrfhmJpKoFOU5L3nmrZMXh/kZYKB/a4Hyhutr0nmKUTcpumuhPtNrEJi0kNWaFcbC9mWcYy5u+ez6wds9iWuw2X5qoIbJh0Jp+JqFFnxKQ3cWKLEzm709kMbz2cXmm9AtrNyHeicfanZ7Enb6fbc9NWiQjg5JG0BC5IaykqEcZE7/dhbgymFDAnScLSU/HkIYh55hQe0pemcsfi6czLWIUv4cMFqpML+9zAw6fUrP/ZuxdGjBDyZ3XVw7GxMHIkfPVV3S1ENU2jwFZAdv5uUne/SWLGx4CCUjURZYiX/0+YBh2uD89awVnKwSNr2J65hEO5mykrO4RqP4qr/CjO8mysaikpej0WcwJmUyJGgwWDTo9Op0eviLymXtFjUERmU6fTo3PLTMYYYkjKnoWiVsnWGeLgdquvx3eEcKJnJucymzNYwjCOIJZFqRxmGEsYwy+czU/eSuVAqAkxNUre+EejIYxdIDmR/ftl8wT9HMU5xKlbSNJvJc20niTTXmINR7Dqc4nR5xOjK0Kv2HFiRtWM3mSazoCm6NzCZU4UzQWuMhRc6BQHeux+l/XYQyZ+KPINQCjuKq4kYwznNWnBBcnJjIwzE6PXA+7kkjFeCBV6M5J00rlfcyeh0Mi3lzH78B4+P7ideTn7KXPJGrLq3fNIy9Y82LwplGaImqNidBMDNflszc6ANpdAyiCwtqhk8aV3z01N/mvP2tpcetDjfuj1WPX7BUKE57DOpjC30zT+zPqTdYfWsTd/b4VSQn3BpDfRulFreqf1ZkDzAYxqO4r+zWrXReTlCZnuk0/8X9M0mDhRSHmNa+aeVj12fyCKNh7yUyB41j09HoRu/wnc39dFxXltkZZG0b4dfLj+Q55b9hwHCw/6BQw9hKi02LSg87MKaJBvyyerKAtVU32SY3pFxvLLe1/OHYPuoHPjkAIQxxQNYexSFGUM8CKypnpP07QnFEW5EUDTtDfd67FXgTOQ9dhVmqb9GexY9/MpwJdAK2A/cIGmaQG8Rbw4JmNXuKoMUUQRRRT1AFVVmbd7Hr9s+471u39BLcsgThELA8+WYIyjZ3ofeqb3ZUibEeg9xSWxLSXOoCj8tvc3Pt3wKb/t/Y0dR3cEfK++6X0Z0WYE1/a9NqIin3BwjGOGx3SMUhTlPuBqwAncqWnarOrOsaGsvaqDlp6OEmD+p6amkbvxUAWJozJpzvN3MHurbTnbmPTNJNYcWlPn5ztj7Awmdp+I2RDCBuoY4KWXYOpUyZOUlHjtiO+9F+68U/IzDofkX+oqdqaq3oLdKKI4FnCqTn7Z8QuzdswSK9mCDLJLsv2KF2MMMbSIb8Gh4kMUO3zzWzp0NIltQstGLemd1pvT25/OOZ3OIcbYMNhNx428oSiKHmETjgYOIGzCSZqmba60zxjgNrxMxJc0TRsU6lhFUZ4BjlZiIiZpmnaPoijdgM/wMhHnA51CMREb/EBWdkgqWQ7NF6lFV5m70kuT5Iw5WZLvqcOh8WBJzpiTAcWdvHFSofek6CslotzBPk+F2A+takzeGPnEoorHHlksz+A5Zoy/H6EfeUOtu7WpRxrPM4B7pJ1q3Wh1aGiLa00T+5p9X8DhhaLKoTMi8l8uqRhuehq0vxoadavRW2zfDr/+KizPVauEe2K1uuXKyny/EpNJ8jdpad4tPR2aNZNjKidzHQ7ZnE6pdsjKkhhe5S0/3//j1hr1/TtXlZvSATGAFbAARsBUZfM8Z1bAHAMxFjBb3LNVN0NKr5MvTqeAwR08dLpA1dzlIe4bzKXC4ANgDpJoM6fC+AZMgOGYsuijY1c1sNngvLtns21fPocPCznLcw937qzwxLUjaZeWSlKSsOhjYrz3tYc1Hw40TWPpgd84XJotxbaVZPt0LhsXbbnSu7PO5LWr6H4f9H7c+5pqdysaeNScQgTaI04++cqqFdoKmTp/KjO3zSSzKDOCdkLDoDPQtXFXJg+ezKW9LhUbJpDqva8ThaxnTBBCicc+q9Nt0P9l+due765Y9iTdaqBLGQgeGXpDeKs3VVOxOW2UO8spc5ZR6ijlaNlRMo/m8O3/OvDV2x3Q66G0xLsKVxSN+HgFsxneegvGjg3eZWuaRqGtkJzSHHJKc/hy05csP7Cco2VHKbIXUWwvpsReElClxINmejg3Di6MgzZG6U43ORR+LIthmSsJ1ZRAiiWFU9udylkdz6KxtTGNrY2JM8Vx66xbeX3V65F8g3WOO0+8kxeu+Oz4J8BSU2D7ErxWYGZJOuvMbqsDY8UP6VSd5JTmkB7fNGhzdqcNU32qytUTosRDL4732AW+fYenqkvT4Nxz4YsvfPetvF4BUDQHiuMoOsdR0BxC1NBcKEgZroabXI4eTWdBM6WgGRqhofPKzuo12PY02v5vRHECxW2V5YLYdug7Xo+SOgzi24uKjlpeaT2Hm1zn6b+rKESB7OdWA9E0FZfH/sVDtFJ0oBjRGazoPGNh+RFRDcpdBUcWQ+F2sOei6S2AHg0dxLZAiW2FYkpyK5CkyLrTki5KCm45bGFxuoT05yiU8bTsoI9ntA/SR0POcjlOp5cxTB8DbS6GFudCyokytrnKvcUMit7dnwToDyIcw98qgBnrjThd/raTqcUwejeclAG9s8EUoYKqQwfr02BFC5jXDg4GEDIxqHDhRrhzYx1UWiMeyH/Rjx2I/3w7djOAVaGJdh4UFkB8aLUVm9NGVnEWB4sOcrDoIPvy97E0YylL9y2lkV7h8TQLZxtyidEcoDOioIiamM4IrSZAr8ertaiJGHVI+tt5dCdPLnmSTzZ8gqqpOFXfAhqLwcJp7U7lhVOfoG18ups06yY2eSxoK/9f8TfYXA5eXvc5j658G6fqpNzlJYToFR2qpjGg6QncN2QK53YZ556rHb9q+IZA3mgoqLOxy01OKiOGPbRlP60qthIlDldMLC6TBdUoySCdvRy9oxx9eQlxWiGtyKBVYhGtl39O27YSe4siiiiiqDE0DXL/gN0fwpElUmSWOhxSBqDFd0ZzkzIUnZCWFcWjhu2EWX3B7lYdCxJLLLIVMX/3fJ5f/jwp1hRuH3Q7Q1sNrdf1XHTs8kVDWHuFhXos4DhYeJC75tzFLzt+odxVXjG3MygGLEYLI9uMpFWjVgCUO8tZcWAFW3K2VMSL9O51V/uk9tx38n1c3vvyWp1PXaOsTKyE58+HP/8UxZNDh6QoqksXsRpu00byMM2aQdOm8rfF8v/s3XecXHW9//HXZ2a2b3ojCQkJISBVhEi5IkWKgCVYUMCCXK/IFX62a0G9FlSuXL0qFgTxihdsiFiI0oxRkA4hQiAQSCFld5NNssn2OjPf3x/fmd3ZzczszO603X0/85jHzJxzvme+s9mdM+d8P9/PJ3ZddUhATPx6bfwcOBz2ZY4bG/34TEOD3//3vlfsdy4TmXOObS3bWLNjDU81PMWqV1bxZP2T/euPmXMMZx98NifOP5Hj5h7H4mmLc5r5MteKGbxR8jXASv1A9oc/+A/geH3FKmtkamgL1YF6JgXrOfawBg6YXEdFdAcVbhdltBCkm0AwQKC8hkB5LVYxBVfuZ9g6i9cFDu2XxWLQTNrowGxac33Ylv/z2TCSiZUlccBeprOHmbQxiXZqaWMS3VTSRVX/fV9FLdHayfRWTqancgqBqgqClWWEqsqwUCCWUcNiKSINF4gHnpjvVzSKxS4MWjR2gTASJdwdJtzVR7S7l/KuVsq6WyjrbOWKzZ+hZs6krH/2kWiE7nA3NRXD5wLv7O2gMlQ58g+CfNeRqsQHCETwl+qTJHJJyYDtj4Lb7YOHIt2xlMPxGd59UDGdzu5ynn9pGs+un0F9Yw1bG2rZvqOGHbur2bOvkpa2CiIRo6Ii4i9cx/TXV0t4ORj83S0ahd6+IH3hALXVfcyY2s2cGV3Mm9PJQfPb+M5Pj/YnGn1tAzPOo70DNxcGZwxcRIunzkx4vuDNw/8s6u5O8TOyhDeT+JnqAyx27q7gvr/PYs/ecrq6g3R2BWjrKKOjs4yOrjKmTC/jkEPLCASMQCBAqDxIWVmAUGggAOl97x/+4t1f7o+n+B34uSU+jwdO9fYODpKJp54LhweCqV5+2c9Eranxt3iK/KoqP2vv3HP99adCUv3KAcU+du3bB9Nj1SIqKvzvaVeX//358pf9Rxr436uenoHMOfHf55Fei05Mk+gcVFV20t68jq59z9PX8hKRzgY27XiUQE8TtRWTqK2aSXXFNKoqp1FRMY3yUA2hshosNAkrn4oFK8AC+Jgbf6wJPHVFilq7ye2NwMMn3MXKTSu5f9P9bG3emjKlWzxV43CpaaMuSiQaSZq6NBQIEQqEOH7u8bz50Ddz+kGncsLm6wjsftQPlIWqB1LDzzkdXvNtP2s6VBMrxxQ/ANjADOr+95+QxWvtV5LWhE7lyK3wQi4y2XXMhA3nw/PvgpZFYBGYuwaO/C0sXgVl+Z0RPVrnbqtk/aRuDmyF+W0wvxWm9IA5mNwDh+z1t8XN2Q8E9gRhy1TYOB02zIC2cn9oa66E+klQP9nfP7HEx03sp2ouvG3/Otf9Us14HkF2sKiLsrdrL7s6drGrYxe7O3Zzx7o7uGfjPXT2pU6vsuNbcECS8cudNTD308nbVIWqOPHAE/nw8R9mVvUsZtfMZnbNbGZUzxgIcioiBR4OKPaxC/yFpjVrYONGn3kjnmp3wQL44hd9LeAZMwZq3FdWDgSnl5X5Y1liLXXwx76hz8Efp+Lft+IlLbq7HEuejJ8vBCBxUP3oa+DoL40sq2KWQQs/e/Bf+cOOn7Jvn/8ZtLX52IHaWl8G0VwPs6s3MatmB7UVe6myvZTTRHl0J2XhnQT6dhPoa+ovAWgklOSzWMCHBXGBClz5TEL7HtnvXLK+8xienv0s+/Y5yrvXUxNeR1VkK1PsJWbXbqE22EBVYDflwV6CVTOxyulEK+biKudAxSysbBK+TvWQW3+ZwHDsnMCfFwRe/DoWGfwB4wD7xAzY1ZT5zzrXPor/axyqfDq8M02/cviZHY6G2dm+sz8oo6GtgV899yse2f5IVvuJW1IGS8v8ed22MKwb8v1g4eSFfPLkTzJv0rz+29xJc6kMjWD2Uw4v+P/i4S9xzSPfjmVHSyizgOPAqYfwPyd+gNfOOdqXTyqb7DOXBeMBibHMIv1/t4nBVRA/R9zbuYevPPQN7t54f0IfB85JXzPrEO68+L79S8oUmAbABuTi2LVzJ9x0yLf4Wce7aGAebzyjlwsvDvHq40PMOzDA9Ok+g2F8chPE5mfEfp327nU01EU57PCAasyLSG689AN4+qNAwE8CfUdihuAk30HTfde8pDQmNOrYNVgpnHtlpADZN51z/O2Vv/GNh7/BI9sfIeqi9EZ6qS6rZtncZZyy8BS+/+T36Yv00RPpoba8lopgBR878WNcsewKZtXMykk/CiUc9hkmd+/2E2Pjt56eweMA8Vtvr19WVjaQVT9+/TY+NlFT4yfmzp7tM66Hin+pRWSQ9t52aspqxlw5uHTHrnz/mc0Htic8r2P/SxPJtpk/TNs5zrkdALFBsHhO5vnA40n2NWb9+2e307ghsVbynNjN6+z0g6lpRSNYpCs28N7pZzQNuhiRUPux/0LhkPqPx30jNqsqyajbJw8AGjFgBnuZQdqsk9ATuxXIkT/+Oi+M4li/oyb5QELczhqY+18jzxd1UOvFbJ38a/jKiHeRcrAjbmcQ5n5sZPueHYTGB/8l9QZz3gBnrqIaOOFofwU/lc5OaGwM0NjoIzfjNesiEQg/8iGiPa2EgmFCgTDBQIRQMEx5qJfZk3cxZ0ojM2qbCASS/Gf+ev9Fg2RyIjFnTvpZynPmwPzzh99PEnfcCR/7ROr1t90G73vfMDv59PD9O+ecEXVP9qdj1zCmTfMXFnftgpde8sE+u3f7C5MvvgjLl/sv8uXlA0E/oZAfBKup8YNj8SxNQ9MeJtYTjl/AjNe0jJdfiQcg/Xhuus/eZgb/V+TH7OrZ7Lp9edJ18yfN5z1Hv4dLjr6EY+Yck/UXyJ5wDys3r+S2Z2/jzy//ma5wF+FomHA0zCPbH+kfVPn+ed/n/71zhc+u0fxcLA3+LujaAS9+G3r3+gsxFohlPQhCoBLKaiE0OTZ7OZaCP/4dIFgBx1w7ENQZD3hzUXjp+v1q23/cGY9OclQFoNL8rSkCvWVTmXzI+5lWOY0pFVOYVDGJqlAVlaFKqsqqqAhW7Bf4GHE+eLJ701fo3nonnVFoddASgX1RaIvCpIC/dTvoivr79X/6OU888zqIDJ7Ns2gR/PPJGqZUTBn1l3jnHPu699HVt39a+O5wN5MqJjG7JstSIZDRBYsK4LDYLZ1j/zvEEX0RgvjETeXm76uDezjm3osIECVkRnmwjIpgBaFAkLJAiMCd7yJgISwQJBDrj8X+zb33FObuy3wQb8FmaMggOMUwzIyABTCMhZ8FM4uVkACHIx5oHoo9Hpp2vivcxQNbHuCBLQ/st3/35dK4kFggJwAbnXObAczsdmA58ELCNsuB25z/oT5uZlNjwYSL0rRdjg9OBLgVeAD4bGz57c65HuAVM9sY60PKwMNS8LF9X4Hb9g9M69scouuyKjqppgt/vzv2uIsqoj5/wKD7/sfBMnCOQDRMgCiGi60deBwkQjWdVNNJuHEToZ5nYM/jsOsf0LENevfB81+Fbb+F6ctg6pFQvdBntiib6geKy2p9WaRAGf3nbPGA5Cz9958+zUs7Bi8rL4dDDoGLLwb/iXNE7Jbwc4oFUPalKHvm3OCPs/jjSGDgwl/cgnj3MeDw2A2OPRb+mSzDcTRMMNwB4Q6fbSp+Hy+1SdQH+lvi+WysHFhZLSx+pw9kDNXGzmuD2G9q4btJAiQmLYW3vJzqx5c+cOJHZBVI8+cO2N0C3RbCRcP+8zoAtaEOjn7+ewTNF48LYAQDIQJmBANlBB75FgTKCVgI4p+bsfuyhy6mfPvtGfdh8QvTqCvbl3ab2h6Y2g21vVDdB1VhqOyDocM7Dh9suKcMOmO3KZXQWgEutvG21m18/P6P7/caC9oCdM+eRTjaR3N7Ly7YCYH0v9/pPuXtmvTH/OqyasqD5f23GxfOZcOCIQGGgXL/+3Jhmt+HWBDTQMaNWM+cg3XXwgv98d9MB74PfD/lGEAd3Dmj5MtZSnbe9z5Y1flpHL5G/YoVZft9XqYzZ44xZ06OsuaJiIDP3j35MP891EVhw01w0EV+XbyEXH9p1XQfVqU7m1kkzsw48+AzOfPgM9nSvIXvP/F9frLmJzjn+Me2f/DQtocwjIpQBcvmLuNzr/8cbz3srSUxGWQkQiF/ulLoSZcixVRbPvwE/LEm359AyY7uQ8+vU22TSduRvB5mdjlwOcDChQuH2WVxvecH1/Pdx7/bX/M8aCGClBPuC9LTDZO+XEGAMiwauxEiEC2DaBkBV07QyikPlFMWCBEKlhG0oB97if+Ineu/aBZ1fpZvxEVwRIm6KFEX6b9IHrIQvdFeeiI9ROgmYj0smn4gL9ftHF203XC1bUcweyjRvOunsae9mSqDygBUGVSZsS/qiDionPIqJldOo7a8lpqyGmrKq6ktq+2/mPPjFeWUhyooD5YTTBhgCkcj9Eb8z+PqnX+nZ/ejdEahIwrtLnYfhTYH3VGoCvgLcd1R6HL+1u2goq0eKmugewr0TIndT44NPkV4zeEzOOfk+cyomsG0qmlMrZjKtKppTKucRnVZNWZGy5Uw3Dzx56NhWnta2de1j33d+9jXtY/mnmYaOxrZ2b6T1u5WqsqqaOluoaWnhdaeVlp6Wmjr7aByYxcLQwMDchWxn2WFQeWOv1H9fDVTKqdSGarwA3KhCiqCFZQFQpQHQ4QCZQQDIYIWIhAI9g/WGGAhw0LGW4+/myo3sqgeB9i5q6GvPXnmjS23+wtvg1rE7l3s/skbGJR22tz+mz/0bth+R9b9++hM+Mi9p9N49N/p6vIlJobe/+53g8sIxW/9s2++ubN/9o1Z8uBjF6tzney8Kt4m2WweM1+GYNhAsIlDx64M2DVfYc411zAHODVH+4xiGC7pDySZH7W2+GnCSeQyJZpzLmkWjPi6VAEBo+1DRaiCNx/6Zt586JvT9sG+cg2cmOPI4niyogx9qK2VD6X4v0grhzOHaf0KPJAkEu45fPapLPl5sP53EgaOENPTNWpry/6FIHUA4Zzs08uv+UzqFCjx428upPud3Jbm76JQfZiASjLwsNSOXXzlKwPpoRKUxW4pi0bk8rMKgINhwdsHLwp3+SCOvmZ/39sMHduh7zmfWSkaHihJ0j9YHBswXnCh30cgALHyLf3ZFl/6rg90SLD+h6fTff5OWlr8x1Zr60AGjjvu8N9N+/oGvpfGs7fFAy7j3yvjg4/RIePr8T/x+PfMxKDM+Ayu1lafere52Qdmxm8dHfB//+fbxvfv+xAiGp1CIDCl/ztssuCRoX2IP078nh0PGDW3hwvPeZHKQLP/+UcSbpv/z//8/B5iLxD7eT/6zdSZUVZfleL/PLnHu+DafRBPjVhdVk3IQkRchKp7vs7kisnUltf6W0UttWW1VIYqqYifbwV9jdBwNExPuIeeSA/d4T7ao2/sLxXW1ttGa08rXX1dmBlRF6Wjb+B34tXbv8dTt32aAyheua3vnwAfOz/qy32C/4NMELBA0ltjbQdz2vc/DjTW+p9l1EX7A//it/hxo7Ovc1A2qP9pW8Kb39/nM7D1tfm/u/ht250DmSdd1J8rRmN/j/0lagMMZHmM9al6Piz7YfxdDHTQDP75WQi37v/DyLAUnYwd//mffvLK2rU++9O3vgXvehfMn+9nwfbFKjcN/XoU/0wrKxvIdigikhMzlsGb10P7ZmhaDa0vweqP+okfZr5EXtlk+rN1L3rfwPegaJcvuxfpgdf9otjvRErNcOM82cjmukGG52WLpi7iO2/8Dte+4Vpuf/52vvzAl9nZvpNLjr6ET/3Lpzhq9lGj6LCISO7k+6t/HZCYNuJAYGi+5lTblKdp22hmcxNSz+/K4vVwzt0M3Aw+hVQ2b6jQvv3Gb/PtN3672N3Ir1EEZmRi5cfTzyKSsa9gyZAWvh1f9j17IUo8lYIk0rErEykGwEYj21CHQs3xSMwEsP/KEujDNdfkt/RWPuXyO0COfycTk53nXQ5/DoWq5VjyfxcTT0kGHpbcsWuk8ny+AkCoyt+Yl9v9vvprSRdX4jNijSBGLGcOPbR4r+1VAq/J7S4Xvzerzb8euxXdrcOlAcyvj8ZuWftc8sVzgDSJKdOrmOFv+bb0ivy/hpSE006DJ5/0mQqffRY2bIAf/tDfd3b6sqSVlbHkt7GvcfFgs64un/q8ttZn7JyUfUVgEZHUag/2N5EJpqqsistecxkfOPYDOOcIBAp1hVFEJDP5Dt54ClhqZouBeuAi4JIh26wAroql5z0RaIkNbO1O03YFcClwXez+roTlvzKz7+Cvei0FnszXmxMRkXFJxy4RERlrSjLwUERERLxZs+Css/xNRERkXCpE0HsOmeUuM6iISC7lNaTMORcGrgLuB14E7nDOrTOzK8wsPs3gHmAzsBH4CfCRdG1jba4DzjazDcDZsefE1t+Br898H3Clcy6DitsiIiKejl0iIjIG9Qcemlk5PnhwxZBtVgDvN+8kYoGHw7SNBx7C/oGHF5lZRSxgUYGHIiIiIiIiIiIio5T3ionOuXvwg1yJy25KeOyAKzNtG1veBJyZos21wLWj6LKIiExwOnaJiMhY4pwLm1k8eDAI3BIPPIytvwl/bDofH3jYCVyWrm1s19cBd5jZB4FtwIWxNuvMLB54GEaBhyIiIiIiIiIiIqOW9+ANERERERERyS8FHoqIiIiIiIiIiIxteS2bIiIiIiIiIiIiIiIiIiIiIiLpKXhDREREREREREREREREREREpIgUvCEiIiIiIiIiIiIiIiIiIiJSRAreEBERERERERERERERERERESkiBW+IiIiIiIiIiIiIiIiIiIiIFJGCN0RERERERERERERERERERESKSMEbIiIiIiIiIiIiIiIiIiIiIkWk4A0RERERERERERERERERERGRIlLwhoiIiIiIiIiIiIiIiIiIiEgRKXhDREREREREREREREREREREpIgUvCEiIiIiIiIiIiIiIiIiIiJSRAreEBERERERERERERERERERESkiBW+IiIiIiIiIiIiIiIiIJGFm081spZltiN1PS7HduWb2kpltNLOrM2lvZp+Lbf+Smb0xtqzazO42s/Vmts7Mrsv/uxQRkVKg4A0RERERERERERERERGR5K4GVjnnlgKrYs8HMbMgcANwHnAEcLGZHZGufWz9RcCRwLnAj2L7Afgf59yrgNcArzOz8/L15kREpHQoeENEREREREREREREREQkueXArbHHtwIXJNnmBGCjc26zc64XuD3WLl375cDtzrke59wrwEbgBOdcp3Pu7wCxfa0BDszpOxIRkZKk4A0RERERERERERERERGR5OY453YAxO5nJ9lmPrA94XldbFm69unaAGBmU4G34DN2iIjIOBcqdgdEREREREREREREREREisXM/gockGTVFzLdRZJlbjRtzCwE/Br4vnNuc8qdmF0OXA6wcOHC4XsqIiIlS8EbIiIiIiIiIiIiIiIiMmE5585Ktc7MGs1srnNuh5nNBXYl2awOWJDw/ECgIfY4Vft0bQBuBjY4564fpu83x7Zl2bJlwwWMiIhICVPZFBEREREREREREREREZHkVgCXxh5fCtyVZJungKVmttjMyoGLYu3StV8BXGRmFWa2GFgKPAlgZl8HpgAfz+1bERGRUqbgDREREREREREREREREZHkrgPONrMNwNmx55jZPDO7B8A5FwauAu4HXgTucM6tS9c+tv4O4AXgPuBK51zEzA7El2s5AlhjZs+Y2b8V5q2KiEgxmXMTO4OSme0Gtha7H2nMBPYUuxMiJU5/JxPDQc65WcXuRCkokWOX/u6k1Oh3UkqRjl0xOnaJpKTfSyk1OnbF5PDYpb/z/NDPNX/0s80P/VzzR8euBEU899LvuOSLfrckn4r1+5Xy2DXhgzdKnZmtds4tK3Y/REqZ/k5ECk9/d1Jq9DspIsPR54SUIv1eiox/+jvPD/1c80c/2/zQz1XGO/2OS77od0vyqRR/v1Q2RURERERERERERERERERERKSIFLwhIiIiIiIiIiIiIiIiIiIiUkQK3ih9Nxe7AyJjgP5ORApPf3dSavQ7KSLD0eeElCL9XoqMf/o7zw/9XPNHP9v80M9Vxjv9jku+6HdL8qnkfr/MOVfsPoiIiIiIiIiIiIiIiIiIiIhMWMq8ISIiIiIiIiIiIiIiIiIiIlJECt4QERERERERERERERERERERKSIFb5QwMzvXzF4ys41mdnWx+yNSisxsi5k9Z2bPmNnqYvdHZCLQ8UlKjY4FIjIcHbuk1OjYJTL+6diTP/oMzR0zu8XMdpnZ8wnLppvZSjPbELufVsw+jkUpfq5fMbP62O/tM2Z2fjH7KJIrOt5JPumYL7kylr7zmHOu2H2QJMwsCLwMnA3UAU8BFzvnXihqx0RKjJltAZY55/YUuy8iE4GOT1KKdCwQkXR07JJSpGOXyPimY09+6TM0d8zsVKAduM05d1Rs2TeBvc6562IDsdOcc58tZj/HmhQ/168A7c65/ylm30RyScc7yTcd8yVXxtJ3HmXeKF0nABudc5udc73A7cDyIvdJRERExycRERlrdOwSEZFC07FHxgTn3D+AvUMWLwdujT2+FbigkH0aD1L8XEXGIx3vRGRMGEvfeRS8UbrmA9sTntfFlonIYA74i5k9bWaXF7szIhOAjk9SinQsEJF0dOySUqRjl8j4pmNPfukzNL/mOOd2AMTuZxe5P+PJVWa2Npa6vSRSs4uMko53km865ks+leR3nlCxOyApWZJlqnEjsr/XOecazGw2sNLM1sci6EQkP3R8klKkY4GIpKNjl5QiHbtExjcde/JLn6EyFt0IfA3/WfA14NvAvxa1RyKjp+Od5JuO+TLhKPNG6aoDFiQ8PxBoKFJfREqWc64hdr8L+AM+VZuI5I+OT1JydCwQkWHo2CUlR8cukXFPx5480mdo3jWa2VyA2P2uIvdnXHDONTrnIs65KPAT9Hsr44OOd5JXOuZLnpXkdx4Fb5Sup4ClZrbYzMqBi4AVRe6TSEkxsxozmxR/DJwDPF/cXomMezo+SUnRsUBEMqBjl5QUHbtEJgQde/JEn6EFsQK4NPb4UuCuIvZl3IgPDsW8Df3eyvig453kjY75UgAl+Z1HZVNKlHMubGZXAfcDQeAW59y6IndLpNTMAf5gZuA/z37lnLuvuF0SGd90fJISpGOBiKSlY5eUIB27RMY5HXvySp+hOWRmvwZOB2aaWR3wZeA64A4z+yCwDbiweD0cm1L8XE83s2PxJSW2AB8uVv9EckXHO8kzHfMlZ8bSdx5zTuWnRERERERERERERERERERERIpFZVNEREREREREREREREREREREikjBGyIiIiIiIiIiIiIiIiIiIiJFpOANERERERERERERERERERERkSJS8IaIiIiIiIiIiIiIiIiIiIhIESl4Q0RERERERERERERERERERKSIFLwhIiIiIiIiIiIiIiIiIiIiUkQK3hAREREREREREREREREREREpIgVviIiIiIiIiIiIiIiIiIiIiBSRgjdEREREREREREREREREREREikjBGyIiIiIiIiIiIiIiIiIiIiJFpOANERERERERERERERERERERkSJS8IaIiIiIiIiIiIiIiIiIiIhIESl4Q0REZAgzO9fMXjKzjWZ2dZL1Zmbfj61fa2bHDdfWzKab2Uoz2xC7nxZbXmZmt5rZc2b2opl9rjDvUkREREREREREREREREqFgjdEREQSmFkQuAE4DzgCuNjMjhiy2XnA0tjtcuDGDNpeDaxyzi0FVsWeA1wIVDjnjgaOBz5sZovy8+5ERERERERERERERESkFIWK3YFimzlzplu0aFGxuyEiIsN4+umn9zjnZhXgpU4ANjrnNgOY2e3AcuCFhG2WA7c55xzwuJlNNbO5wKI0bZcDp8fa3wo8AHwWcECNmYWAKqAXaE3XQR27RETGhgIeu0qejl0iImODjl0DdOwSERkbdOwaTMcvEZHSl+7YlffgDTM7F/geEAT+1zl33ZD1Flt/PtAJfMA5tyZdWzObDvwGP0i2BXiXc26fmb0H+HTC7o8BjnPOPZOqf4sWLWL16tWjf6MiIpJXZra1QC81H9ie8LwOODGDbeYP03aOc24HgHNuh5nNji2/Ex/YsQOoBj7hnNs7tFNmdjk+ywcLFy7UsUtEZAwo4LGr5Om8S0RkbNCxa4COXSIiY4OOXYPp+CUiUvrSHbvyWjal0KnnnXO/dM4d65w7FngfsCVd4IaIiEgSlmSZy3CbTNoOdQIQAeYBi4H/MLOD99uJczc755Y555bNmqXJBCIiIiIiIiIiIiIiIuNJXoM3SEg975zrBeLp4xP1p553zj0OxFPPp2u7HJ9yntj9BUle+2Lg1zl9NyIiMhHUAQsSnh8INGS4Tbq2jbHjG7H7XbHllwD3Oef6nHO7gEeAZTl4HyIiIiIiIiIiIiIiIjJG5Dt4I1Va+Uy2Sdd2UOp5YDb7ezcpgjfM7HIzW21mq3fv3p3hWxERkQniKWCpmS02s3LgImDFkG1WAO837ySgJXY8Std2BXBp7PGlwF2xx9uAN8T2VQOcBKzP15sTERERERERERERERGR0pPv4I1Cp573OzQ7Eeh0zj2fbL1Sz4uISCrOuTBwFXA/8CJwh3NunZldYWZXxDa7B9gMbAR+AnwkXdtYm+uAs81sA3B27Dn4EmG1wPP44I+fOefW5vddiojIeGNm55rZS2a20cyuTrLezOz7sfVrzey44dqa2XQzW2lmG2L302LLy8zsVjN7zsxeNLPPFeZdioiIiIiIiIiIjF+hPO9/NKnny9O0bTSzuc65HUNSz8ddhEqmiIjICDnn7sEHaCQuuynhsQOuzLRtbHkTcGaS5e3AhaPssoiITGBmFsQHA56NP796ysxWOOdeSNjsPGBp7HYicCNw4jBtrwZWOeeuiwV1XA18Fn/cqnDOHW1m1cALZvZr59yWQrxfERERERERERGR8SjfmTcKnXoeMwvgLybenq83JSIiIiIiUkJOADY65zY753rx50LLh2yzHLjNeY8DU2OB8OnaLgdujT2+Fbgg9tgBNWYWAqqAXqA1P29NRERERERERERkYshr8EYRUs8DnArUOec25/O9iYiIiIiIlIj5wPaE53WxZZlsk67tnFhgPbH72bHldwIdwA5gG/A/zrm9o38bIiIiIiIiIiIiE1e+y6YUNPV8bN0DwEkj77GIiIiIiMiYYkmWuQy3yaTtUCcAEWAeMA14yMz+OjSA3swuBy4HWLhw4TC7FBERERERERERmdjyXTZFRERERERE8qsOWJDw/ECgIcNt0rVtjJVWIXa/K7b8EuA+51yfc24X8AiwbGinnHM3O+eWOeeWzZo1a0RvTEREREREREREZKJQ8IaIiIiIiMjY9hSw1MwWm1k5cBGwYsg2K4D3m3cS0BIrhZKu7Qrg0tjjS4G7Yo+3AW+I7asGn/lwfb7enIiIiIiIiIiIyESQ97IpIiIiIiIikj/OubCZXQXcDwSBW5xz68zsitj6m/DlKM8HNgKdwGXp2sZ2fR1wh5l9EB+wcWFs+Q3Az4Dn8WVXfuacW5v/dyoiIiIiIiIiIjJ+KXhDRERERERkjHPO3YMP0EhcdlPCYwdcmWnb2PIm4Mwky9sZCOQQEREZETM7F/gePnjwf51z1w1Zb7H15+MDDz/gnFuTrq2ZfQ1YDkTx5b4+4JxriK37HPBBIAJ81Dl3f97fpIiIiIiISBZUNkVEREREREREREQKxsyC+ExO5wFHABeb2RFDNjsPWBq7XQ7cmEHbbznnjnHOHQv8GfhSrM0R+NJgRwLnAj+K7UdERERERKRkKHhDRERERERERERECukEYKNzbrNzrhe4HZ8xI9Fy4DbnPQ5MNbO56do651oT2tcALmFftzvnepxzr+DLiJ2QrzcnIiIiIiIyEgreEBERERERERERkUKaD2xPeF4XW5bJNmnbmtm1ZrYdeA+xzBsZvh5mdrmZrTaz1bt3787qDYmIiIiIiIyWgjdERERERERERESkkCzJMpfhNmnbOue+4JxbAPwSuCqL18M5d7NzbplzbtmsWbOSdlxERERERCRfFLwhIiIiIiIiIiIihVQHLEh4fiDQkOE2mbQF+BXwjixeT0REREREpKgUvCEiIiIiIiIiIiKF9BSw1MwWm1k5cBGwYsg2K4D3m3cS0OKc25GurZktTWj/VmB9wr4uMrMKM1sMLAWezNebExERERERGYlQsTsgIiIiIiIiIiIiE4dzLmxmVwH3A0HgFufcOjO7Irb+JuAe4HxgI9AJXJaubWzX15nZYUAU2ArE97fOzO4AXgDCwJXOuUhh3q2IiIiIiEhmFLwhIiIiIiIiIiIiBeWcuwcfoJG47KaExw64MtO2seXvSLJ5fN21wLUj7a+IiIiIiEi+qWyKiIiIiIiIiIiIiIiIiIiISBHlPXjDzM41s5fMbKOZXZ1kvZnZ92Pr15rZccO1NbPpZrbSzDbE7qclrDvGzB4zs3Vm9pyZVeb7PYqIiIiIiIiIiIiIiIiIiIiMVF6DN8wsCNwAnAccAVxsZkcM2ew8YGnsdjlwYwZtrwZWOeeWAqtizzGzEPAL4Arn3JHA6UBfvt6fiIiIiIiIiIiIiIiIiIiIyGiF8rz/E4CNzrnNAGZ2O7AceCFhm+XAbbE6lo+b2VQzmwssStN2OT4wA+BW4AHgs8A5wFrn3LMAzrmmfL45kRGJ9ELHK9DXCtE+sBCEqqH2YH8vIiKSK31t0LYRcDDpECibXOweiYiIiIiIiIwtBxwAjY2j28ecObBzZ276IyIFs2cP3HsvPP88RCKwZAmcdx4sWlTsnonIeJXv4I35wPaE53XAiRlsM3+YtnOcczsAnHM7zGx2bPmhgDOz+4FZwO3OuW8O7ZSZXY7P8sHChQtH8LZEstDyAmy7E3b9A1pfhO5GCFaBBQe2cVGIdEH5VJh0KMw8CRa8w99b3qsbiYjIeLPrIXjuy7D7UQhW+GWRbphxIhz9ZTjgzOL2T0REREpPLgamMqHBKxERGWtycXwsxDFWRHJm40b48Ifh4YehvBza2/3yqir45Cd9EMdPfgInn1zcforI+JPv4A1LssxluE0mbYcKAacArwU6gVVm9rRzbtWgnTh3M3AzwLJly4bbp0j2WjfA5lvglZ9D7z5wYYj2DqwPtydv17PH3/Y8ARt/4gM8Fl4ISz4IM4fGPYmIiAwR7oTVH4Wtv/JBgQDRnoH1ux+CB98KB14AJ9wEZZOK0k0REREpQYUaVNLglYiIiIiUKOfgv/4Lrr0Went9to3ehKGdrtjltnXr4Mwz4Z3vhP/9Xx/gISKSC/kO3qgDFiQ8PxBoyHCb8jRtG81sbizrxlxgV8K+HnTO7QEws3uA44BBwRsiedOyHp79POy4F6IRcH0j3FEEwm3+4eafwpZfwtSj4TXfgtmvz1l3RURkHAl3wF/PgJbnfJaNVCKdsP130PwcnPOwSqmIiIiIiIiIiMiEF4nAhz4Ed9wxEKSRTlcX3HknbNoE990HkzRHSkRyIN/1GJ4ClprZYjMrBy4CVgzZZgXwfvNOAlpiJVHStV0BXBp7fClwV+zx/cAxZlZtZiHgNOCFfL05kX4d2+HBC+C+10D9Cj9oNuLAjSFc1A+0NT0Bfz8X7jsB9q7Jzb5FRGR8iHRnFrgRF+2BtpfhL6f4oA8REREZN/Z07GFf175id0NEREREZMxwDi65BH7zG+jI4lJZVxc8/TSccgr09Ay/vYjIcPIavOGcCwNX4YMqXgTucM6tM7MrzOyK2Gb3AJuBjcBPgI+kaxtrcx1wtpltAM6OPcc5tw/4Dj7w4xlgjXPu7ny+R5ngnINNP4W7D4eGP8eCNiL5e71IJ+x9ClaeAs98HiK9w7cREZGi6euDVavgIx+Bc8+Ft70NbrwRGobmIRutpz8JLc9nFrgRF+2Btg3w5L/nuDMiIiJSTKffejpv+83bit0NEREREZEx44c/hLvvhs7O7Nv29MCGDXDFFcNvKyIynHyXTcE5dw8+QCNx2U0Jjx1wZaZtY8ubgDNTtPkF8ItRdFkkM1074NH3wJ4nIVLgWcuRLnjpe7D9TjjlTph2TGFfX0REhnXvvfCBD0B3N7S3QzTql//lL/DJT/po/u98B6ZMGeUL7VgJr9zqjw3Zinb7Eip174QD3zrKjoiIiEgpaOluwbBid0NEREREZEx44gn47GczK5WSSleXL7dy2mn+eqCIyEjlu2yKyPjU9BT8+QjY9XDhAzfiIp3QthH+cjJsvaM4fRARkf1EInDZZfDOd8KuXdDaOhC4AT6Cv7sbfvUrWLIE1q4dxYv1NMEj7/bHhBF3uBMeex907RxFR0RERKRUtPe209zTXOxuiIiIiIw7Znaumb1kZhvN7Ook683Mvh9bv9bMjhuurZlNN7OVZrYhdj8tYd0xZvaYma0zs+fMrDL/73Ji2bMH3vzm0QVuxHV2wpVXwnPPjX5fIjJxKXhDJFt1K+Cvp0NfM7i+InfG+UG3xz8A677hy7iIiEjR9PX5oI077hg+zWJ3NzQ1+ZqYTz01whd84t8gnIMgwnAXPPq+0e9HREREiq6zr5O2nrZid0NERETy4YADwGx0twMOKPa7GJPMLAjcAJwHHAFcbGZHDNnsPGBp7HY5cGMGba8GVjnnlgKrYs8xsxA+y/wVzrkjgdOBYg9IjDtXXAEtLbnbX1cXvP3tgydyiYhkQ8EbItlY/z145KLRzXDOh0gXPP91eOKDEA0XuzciIhPWFVf4sijZ1Mdsa4Mzz4StW7N8sdaXYcd9EO3NsmESrg/2PAL7nh39vkRERKRo+iJ99EZ76ewrsXNWERERyY3GxtLYx8R0ArDRObfZOdcL3A4sH7LNcuA25z0OTDWzucO0XQ7cGnt8K3BB7PE5wFrn3LMAzrkm51wkT+9tQnrpJbj7bj8ZK1ecg5074Y9/zN0+RWRiUfCGSKZe+CY8+3kfKFGKIp2w9Tfw6HuK3RMRkQnp97+H22/PLnAjrrMT3vrWLE8Wn/96bgP2oj3w3DW525+IiIgU3M52XwatL9qnAA4peXlKPf8tM1sf2/4PZjY1tnyRmXWZ2TOx200FeZMiIjKezAe2Jzyviy3LZJt0bec453YAxO5nx5YfCjgzu9/M1pjZZ3LyLqTf5z6X28CNuPZ2+PSnc79fEZkYFLwhkolNP/MDWqWWcWOoSCfU/7nYvRARmXC2boVLLx1Z4AZAJAIbN8LnP59hg65G2PZbcDkM3nBRaLg3d/sTERGRgmtoa0j6WKTU5DH1/ErgKOfcMcDLwOcS9rfJOXds7HZFft6ZiIiMY5Zk2dA65qm2yaTtUCHgFOA9sfu3mdmZSTtmdrmZrTaz1bt37x5mtwKwfj3cd5+/JpcPu3blZ78iMv4peENkOHV/gtVXln7gRtxY6adICcvTDLDpZrbSzDbE7qclrDvGzB4zs3Vm9pyZVeb/XUquRCJwwQW+puVodHbCDTfA3/6Wwcbrvzu6F0tJBTlFRETGsvq2+oHHrfVpthQpuryknnfO/cW5/gjnx4EDC/FmRERkQqgDFiQ8PxAYGi2bapt0bRtjxzdi9/Fh/zrgQefcHudcJ3APcBxJOOduds4tc84tmzVrVtZvbCL63OegNweViFNpb8/fvkVkfFPwhkg6ex6HRy4q3VIpIpJzeZwBdjWwyjm3FFgVe46ZhYBfAFc4544ETgfykLBP8uX3v/dZM3IRqd/VBf/+78NsFO6ADTdAtHv0LzhUNI9nrSIiIpJ3yrwhY0i+Us8n+lcgMbXcYjP7p5k9aGavH2nHRURkwnoKWGpmi82sHLgIWDFkmxXA+2MTv04CWmKlUNK1XQFcGnt8KXBX7PH9wDFmVh27fnga8EK+3txEsn493H9//rJuiIiMRqjYHRApWT1N8OBblMlCZOLpn8UFYGbxWVyJJ0f9M8CAx80sPgNsUZq2y/GBGQC3Ag8AnwXOAdY6554FcM415fPNSW4550ud5DKavmG4cZaN/+tLnIiIiIgMsbVla//jxCwcIiUor6nnzewLQBj4ZWzRDmChc67JzI4H/mhmRzrnWoe0uxwfoM/ChQuHfRMiIjJxOOfCZnYVPqgiCNzinFtnZlfE1t+Ez45xPrAR6AQuS9c2tuvrgDvM7IPANuDCWJt9ZvYdfOCHA+5xzt1dmHc7vl19dX6zboiIjIaCN0SScVF46ELoax1+WxEZb5LN4joxg21SzQCLt50Ti7THObfDzGbHlh8KODO7H5gF3O6c++bQTukiYmm67z7YuTO3+0wbCOKisO6/FFgoIiIiSW3eu7n/8ZbmLcXriMjwRpN6vjxdWzO7FHgzcGYs4B7nXA/QE3v8tJltwp+LrU58QefczcDNAMuWLRsaTCIiY9EBB0BjY7F7IeOEc+4efIBG4rKbEh474MpM28aWNwFnpmjzC3zGXsmR7dvHVtaNJ56A226Du++Gujo/kWzqVDjzTHjXu+Btb4NgsNi9FJFcUtkUkWRe+CY0Pan08SITU15ngCURAk4B3hO7f5uZ7XfCptqVpelznytwDcs9j6uUl4iIiKS0rXVb/+PN+zan2VKk6PKSet7MzsVnOHyrc64/4tnMZsXKXGJmB+NLYOqPRGQiUOCGiCT4xRgJhVm/3gdovOENcNNNsHWrDziJRmHvXvjtb+Gyy+CQQ+Ce/UKCRAogGoG2TdDyAnTleHbjBKfgDZGh9jwJz38VIh3F7omIFMdoZoCla9sYK61C7H5Xwr4edM7tiV1cvAc4LgfvQ/LsoYdg48YCv+jWX0NYWTdEZH9mdq6ZvWRmG83s6iTrzcy+H1u/1syOG66tmU03s5VmtiF2Py1h3TFm9piZrTOz58ysMv/vUkSGs6NtR//j7a3b02wpUlzOuTAQTx//InBHPPV8PP08/txoMz71/E+Aj6RrG2vzQ2ASsNLMnjGz+GzoU4G1ZvYscCdwhXNub77fp4iIiJSWm2+G7u5i9yK9O+6A44+HBx6Azk4fsJFMezts2QIXXgif+MTYySYiY5hzUPcnWHUm/HYS3PNquP8kuGsR/P4AeOxfoa3QF8zHH5VNEUkU7YNHLtKsZpGJrX8WF1CPn8V1yZBtVgBXmdnt+LIoLbFSKLvTtF0BXIqvY3kpcFds+f3AZ8ysGugFTgO+m683J7nz+c9DRyHj/JyDrbcDOhMTkcFiM4lvAM7GBwU+ZWYrnHMvJGx2Hn6W8VL8setG4MRh2l4NrHLOXRcL6rga+KyZhfCpe9/nnHvWzGYAfQV5syKSVlNXU//jXe270mwpUnx5Sj1/SIrtfwf8bjT9FRERkbFt7VrYVeJfka+5Br75TR+0kanOTh+U8s9/+pIwFRX5659MYHufhsc+AB2vQDjJRfHuRthyG2z7NSy4EF77QyibXPBujgd5z7xRyBlgZrbIzLpikfWJ0fUimVl3nf+AEZEJK48zwK4DzjazDfgBsutibfYB38EHjTwDrHHO3Z3v9ymj8+yz8PTTBX7RvU9DpMSnBohIsZwAbHTObXbO9QK3A8uHbLMcuM15jwNTY5mg0rVdDtwae3wrcEHs8TnAWufcs+BrNDvnFFkmUmQdvR2Eo+H+53u79+LHvkVERERE5P/+D/pGMO2gthZOO82XMclnNev//d/sAzfiOjvhySfhPe/x879EcmrTLbDy9dDyfPLAjTgX8devt90Bdx8FLesL18dxJK+ZNwo9Ayy2v03OuWPz+b5knGrfAi98I39ZN6YdC/PfDDNOhqlHQsUsCJT5D7PefdC6HpqegoZ7YPdD4FLkwhKRvMvTDLAm4MwUbX6Bn8EsY8Qtt4zsZG9Utv8uu+CNKUfCYR+HuecABo2r4KXvwb5n8tRBESmi+UBifYQ6/LnVcNvMH6btHOfcDoBYhqnZseWHAs7M7gdmAbc7576ZizciUizRKNx9N9x2mw/QNPMXaN//fjj99GL3LjMNbQ1Uhipp720HIGhB9nXvY3rV9CL3TERERESkuJyDX/86u+t5c+bAjTfC+edDV2zYqLLST+q67DJ48cXc9e8vf4GPfnTgdUaiqwvuuw+uvhr++79z1zeZ4NZ+GV78n+zGTqM90FkH978Wzvw7zFiWv/6NQ/kum9I/iwsgll5+OZAYvNE/Awx43MziM8AWpWm7HDg91v5W4AEGgjdERuapK3zZlFwqnwav+gQs+RCEaiFQDsHyIRuVQdVcf5t1KiyNTezf+htYdy10bM1tn0REZFScg1/+EsLh4bfNqe2/A5fJixoc/h9w9DUQqIBA0C9e9D5Y+C544Tp/fFGQoMh4YkmWDZ1rk2qbTNoOFQJOAV4LdAKrzOxp59yqQS9odjlwOcDChQuH2aVI8bz8Mlx8sb9vbx9Y/sorvt70614HP/sZzJtXvD5mor6tnqAF+5+XB8upb61X8IaIiIiITHgvvgitrZlv/653+UwY5eW+DEliKZJly2D1arjuOvja10bft+eeg7e/fXSBG3EdHfDDH8LSpfBv/zb6/ckEt/GnscCNEaSDwUG4Hf52Npz3NNQenPPujVf5Dt4o9AwwgMVm9k+gFfhP59xDo34XMv7tehh2PZThoFgGQjVw5BfhsKsAg1B1Zu0CQQjEakAtvhQWvdcP1j3zWehqyE3fCqitzV/w3LwZduyA3l4/o628HKZMgYMP9rc5c/zMNhGRseDxx6Gnp8Av2tWYeTDfST+FhRfuf+wJBCFQDUd8BqYeDQ+/K/f9FJFiqQMWJDw/EBj65THVNuVp2jaa2dzYOddcIF4duA540Dm3B8DM7gGOAwYFbzjnbgZuBli2bJkSt0pJevJJOOssf5EzOiSu0Tm//G9/g2OPhccegyVLitLNjDS0NRBJqGAUsAANbQ0cPefoIvZKRMaK3zz/G4KBIO884p3F7oqIiEjO/f73mU/EOuccH7xdnWJYJxj06z7zGV+u5NvfHnm/olF497v9eUeudHb6LB7nn1/6AehSwhruh6f/3+irFYRbYeVpcP4zUDEjJ10b7/IdvFHoGWA7gIXOuSYzOx74o5kd6ZwbFE+nGWDF5ZwfyN+4ETZtgg0boL4eumOZ4CsrYe5cOPRQf2FsyRKYPz/Pg/v//NQII8eSmHECnPoHKJsGoaqR7yeeoeOgd8GBb4XH/9UHcpQo5/z/6cqV8Ic/wBNP+EjR+Becvj6IxK4jBgJQVubve3r88kMPhQsugHPPhRNP9OtFRErRz3+efSR8IOBrYnZ0DJ7Rm7Ed9/vsTdHe9NstvNBn1wjVpN4mVAtzz4ODL4PNPxtBZ0SkBD0FLDWzxUA9cBFwyZBtVgBXxTIangi0xIIydqdpuwK4FLgudn9XbPn9wGfMrBroBU4DvpuvNyeSL8884+tWD3dsDoehqcmfp/zzn7BgQfrti6WutY7u8ECJtXA0TH1bfRF7JCJjyTce/gZlgTIFb4iIyLj085/7yaXDWbIEfvvb1IEbiWpr4atf9ecVq1YNu3lSv/wlbNs2srbphMPwH//hS8WIZK3lBXjoHaMP3ACf/bm7Ef52Frxx9UCWaEkp38EbBZ0B5pzrAXpij582s034esyrE19QM8AKb88ef/C66y64/34f+VdR4Q8gnZ1+4D+RmT84hkL+gFpRAWef7Qf3zzoLZs9O+jIjs+shaH5+9PuxIBz1JTj8U5ln2shEoNzfTr4VFr4DnrjcpxoqETt3ws03w49+5DNtgP8/jUuViqy7e/Dzdet8muIf/MD/n19wAXzyk/Da1+al2yIiI+Ic3HnnQDDacCZPhm99Cy66yB/TQiH/effpT2d5Urf9zuE/+2sWw4k/TR+4EVdWC8t+AHseg9b1WXREREqRcy5sZlfhgyqCwC3OuXVmdkVs/U3APcD5wEZ8qZPL0rWN7fo64A4z+yCwDbgw1mafmX0HHzTigHucc3cX5t2K5EZ7O7zlLZkHVUaj0NICb3ubD1QPluD1pi3NWwhHB6YTdvV1Ud+q4A0RyUxbTxuhQL4vFYuIiBTerl2wZcvw29XWwl//CjUZXFqLq672WT2OPdZnIc9GZyd8/OO5zboR19fnx+NEsuacn0yeqwnvAK4P2jbApp/A0ityt99xKpDn/ffPADOzcvwsrhVDtlkBvN+8k4jNABumbXwGGCTMADOzWWa+wKuZHQwsBTbn7+1JOtGoz8Jw9tlw4IHwoQ/5KL+9e/3AfUuLPygNDdyAgfS0LS1+dnNzs492vOIKWLgQTj8d7r13/7S2I7LmPyAyyqNjqBbOeQJe9cncBm4Meo0amH8BvOVlP0BXZI89Bm96EyxaBN/4BjQ2+i8bnaP4PO/r88Ee3d2+tvQZZ8Bhh8Ett/h1IiLF9sILmX/OnXaaz0j0vvf5II7qal826jWv8SdPN988uF5mWnseG2YDg9NWQDCLjE+BSjjtzz74UETGPOfcPc65Q51zS5xz18aW3RQL3MB5V8bWH+2cW52ubWx5k3PuTOfc0tj93oR1v3DOHemcO8o595lCvleRXLj8cj/JIBvhMKxfD9dck58+jdbmfYMvf0SJsmnfpiL1RkTGmo7eDtp7S2eykMi4M2dOsXsgMmE99pjP+D6c66/3f6rZBmpXV/vJXtn6xjf2n+SaS/nct4xjdXdBy/MMXwwjS+EOeOazud3nOJXX4A3nXBiIz+J6EbgjPgMsPgsMPwNsM34G2E+Aj6RrG2tzHXC2mW0Azo49BzgVWGtmzwJ3AlckXmCUwujt9dkTDjwQ3v52H6nY0zOQlWE02tr8vh580NcBmzfP1xPr6RnhDhsfhJZ1w2+XTqAC3vAXmHKEn8mcT6EqqJgFZz8MlcX5wr9xI5x3ns+Acu+9/mefjy8B0agP4Hn5ZV+f7eCDYcWK5ME+IiKFsmJFZvUxjz4a7r7bl0qpShJPUVMD73kP/O//ZvCi3buhL0Uao7j5b4aagyCbmXKBIFTO9qVWREREJpDf/c4HUo7kPKajA/7nf3z2jVJT11q337ItzVsK3xERGZM6+jro7MvhDEuR8ca55LdMt9u5s/B9FhEAHnpo+Ix7Bx4Il1yS/DrecEIhXxb+zDMzb1Nf78e2RjMZdjgaS5GsRXrgqX/3gRb5MFxJcAHyn3mjoDPAnHO/i83+erVz7jjn3J/y/f5kgHP+AtjixfC5z8GOHZmnoB2Jtjaf7eHLX4aDDvKRjVkfjJ778uhS/1gATv09TH21D6wohEAIKmbCWf+AsimFeU18Rox//3c/ILlyZfJyN/nS0QF1df7L0wknwNq1hXldEZGhfv3r4QMGJ0/2wW3DnexVV/sSUZddNsyL7l09fEaNY74KZZOG2VESZZPg6BKdPiwiIpIHkQh87GOju0ja1eVLPJaaxo7G/ZbVt2VRNqVQM4I181ikJPVEeugKj66ueWN7I3988Y+56ZCIiEiOrFw5fBb3r34VAqMYMa2t9UHemfrkJzObICZSUOu/M/wkwtGIKB1MJvIevCETw8svw8kn+1nEDQ35qdGVSkeHD+L4wAfguONgXaaJNNq3wJ5RTpc66Wcw+7T8lUpJJVgONQvhDX+FYAb5vkbpiSd8+ZL/+z8/Oy0SyftLJtXRAU8/DSed5KNSc1I2R0QkQ62tPlX6cH79a5g+PbMTvtpan63qmGPSbLTnyfTRzjNPgkmHDP9iqVTNhTlvGHl7ERGRMeSPf/TlOUfrmWdGv49ccs7R3N283/LdHbsz38nOnalnC6ebYTy4I8PfNPNYpOREohH6on30RnqJupFfbPndi7/j3Xe+O4c9ExERGZ2+vuGv5y1YABddlEV54xQOOcRnLB/O5s0+u69KxUtJ6WqE578+ugnvkhMK3pBRcQ5uuQVe8xp46qnCBm0M1dEBzz7rMzPceGMGWSFevgEYxej/a74JC94OoZqR72M0gpW+VMupK8CyLMKWoUjE13M+4wx/fa0UaqQ552e6ffnLcPrpPnBHRKQQVq8ePpvGu98Np56aXYrFqqph6mLuegBcmlD8o78CgVEEESr7hoiITBDOwX/+Z24yRHaNbnJ6zjV1NRFMcl7Y1ttGOKopfSKSXlNXEwCO5IFgmdrbuZe+qEaiRESkdDz77PBBGaPNuhGXafaNH/1IE1OlBP3z0+mvQUvBKHhDRqy1Fd7xDvjoR33K2VI42Djn+/LpT8Ob3gT79qXYMNILm24eeX2lJR+EpR+BUO2I+5oToWqY9S+w7Iac77qtzQdtfPObpXdhEnywzuOPw+GHF7snIjJRPPFE+s9DM/jGN/yJWjYCATjgADj//BQb7HsmdePag2HW60d/hjn9NTDlyNHtQ0REpMStWgXbt+dmX6VWP7qhrYHyYDkAgYRLPRXBChrbFfEuIunt6tiV9HG2mrqbcDg6+zRjU2TE+tph7z+hp6nYPREpDb3N0Pw8ND8H3Xuybv7YY+kzXEyblpusG3FLlsCJJ6Ze39sLN9/s70VKRvdu2HbHyMdMJacUvCEjsnUrHHUU3HNPcbNtpNLR4S/MHXFEig3q/jDyq23VB8Jx1xcv48ZQoRpY/F6YfWrOdtnYCK99LTz55OhqQedbX1+aAB0RkRz761/Tn+y96U0wc+bI9j1pkg/82E9nQ/pagAddDJaDr3NWBovfN/r9iIiIlLD//M/SPH/NhYa2BgKx7wShYIiyQBkAZcEyGtoaitk1ERkDchW8ES/VpKAxkRFwDtZ+CX4/G1adDn+YD49d5ichJpozZ/SvlYt9iORT+yvw1FXwhwX+b+Ivr4O/nAJ/nA+/n+v/NlpeyGhXK1emzyh+4YUQzmGygcpK+OAHU6//4x9z91oiObPpp7m5xiw5of8Jydq6dXDccdDQAD09xe5Nar29sCvV+eb670K4bWQ7PvnnECgfcb/yIlQD//IrCGaRpz+FDRvg2GN93bVS/v8VESm0NWvSr//GN3wQxkgdfDCcdtqQhXufhmCaY87Bl/oyWqMVLIdF7x39fkRERHKsuRm+8hU48kh/IbSyEo4+Gr7+dZ8tMFNr1sBzz+Wrl8VX31rfX6ogaEFCgdDAurb6YnVLJC0zO9fMXjKzjWZ2dZL1Zmbfj61fa2bHDdfWzL5lZutj2//BzKYmrPtcbPuXzOyNeX+DY0g86GLo42zFgzZGEwAiMiFFw/Doe+HFb0OkC/paIdoD234Dq86AvoQvPTt3+kCPZLehUm23c2fh3ptINnqa4KF3wp+PgI03Q1cdRPsg3Opv0V7o3glbfg73LYNVZ0Nn+u+6jz+e/iWvuCL7LLrphEK+rHIolHz9D36Q3XmMGVxyCTzwALS0+BKQa9fCF74ANSUyv1jGOBeFl673xx8pCQrekKw8+iicfLLPdhCJFLs3w0tayqV7d/oU9OkcdDFMX5Z+IK1YyqfBq68d1S5eeQVOOskHvaSbXS4iMtHU16eP0j/jDFi0aHSvUV2dJPtG0xPQl2KKcM0iqJo/uhdNVD5FpVNERKRkRKNwyy3++HrddfDCCz64vKcHnn8err0WDjoIfvWrzJIq/uxn4zs4vb6tnq4+f7HNzAgGggD0RnqVeUNKkpkFgRuA84AjgIvNbGj+1POApbHb5cCNGbRdCRzlnDsGeBn4XKzNEcBFwJHAucCPYvsRcpd5I962sUOZN0Sy8tL3oe6PEBmSAjnS5Sd1PP3xYvRKpLAa7ocVh0D9nyDaDS7NAIWL+L+PXQ/An18FW36ddLOdO6G1NfVu5s2DV71qdN1O5cwz91+2axc89VTm+3jta/25z49/7Cd8TZ7sAzaOPho+/3nYtg3eq7lYMlo7/wrhEaTgr5jly3nPOx9mvBZi2R9l9BS8IRl78kk45xwfFVhq9X2zUncXBFKEPaYTrIZlP4CyHIZh5lKoGg75MEw6ZETNd+2CU07xM9uSBr2IiExgTz4J5Wni9j75ydFH6QcCPvPR4sUJC3c9AKSIlpz/5tG94FAWyv0+RURERsA5X3f6ox/1s8uSBV10d/tJBZdf7tMSpztHjUbh178eGxMQRmrj3o04/A8h6gZO6LrD3Wxr2VasbomkcwKw0Tm32TnXC9wOLB+yzXLgNuc9Dkw1s7np2jrn/uKciyc/fxw4MGFftzvnepxzrwAbY/sRYEf7jv7Howm82Nu11+9DZVNEMte9G5770v6BG3HRHtj6a9i3trD9EimkLbfDQ2+DvmafXSNTLgzhdnji3+DF7+y3+vHHoaIidfPly/MzFlJT489nhrrjDghmGDr6L/8Cf/+7Dy5Jds2xuhqmT4cbb4TPfGZ0/ZUJbsON2VUqqJgBx38Plm+B01bAv/wS3rASLtgOi9+v8is5oJ+gZGTDBh+4MS7qA2/+GYRH8EaO+s/cpKbPp0A5LPtR1s3a2nzk5u7dCtwQEUnmkUd8WsJkqqvhrLNy91qDTu6a09TvXPhuH7iXK8FKv08REZEiu/pquPvuzM4/OzrgN7/xmThSeeKJ8Z11A2Br89b+x32RvkEBHJv2bipGl0SGMx/YnvC8LrYsk20yaQvwr8C9WbzehFXXWpf0cbZaeloAlU0RycqaT/myEOlEuuGJYaJVRcaqTT+DJ/51dCUbIp2w9ouwbnBK23Xr0p9TvP/9+Sk9EgzCBRfsv/ymm6AzgwQHRx4J997r+xYYZhS3tha+9CX/XkSy1tcODfdlvv2Sy2H5VljyIX9dunyqv5VNgco5sOyH8NbNMDlPKW0mCAVvyLAaG+HUU7Orw1WyevfB3tXZt6s+EA77GIRKvIhYIASzTs6qSSQC55/vS6aoVIqISHJ//3vq4LY3vxl6s5gUkE5VFfzrv8aeRHp8Pc9kgpUwY1luXjTRlKGZqkVERArrxz+GH/4ws4uacZ2d8F//Bb/4RfL1v/41dGVwLbiyEr78ZfjrX+H+++HjH898Zlyx1bcNrvXdGx74crK1ZevQzUVKgSVZNnRUMtU2w7Y1sy8AYeCXWbweZna5ma02s9W7d+9O0mR8SvwMGWnwhnOOjl4/QqaMPyIZankBtv82g0wDDlpfhPo/F6RbIgWz6VZYfdXoAjfiIp3w/Nfh+f/qX7R2berse7W18JrXjP5lUxkadLFzJ2zcOHy7hQvhwQezy/BbU+MzcJx/fnZ9FKHuj5lXKlj0Hjj+O36cNFSVfJuySVC1AM56CKoX5qybE42CNySt7m444wzYs2ecZGSoW+GzU2Tr0I/BWCmFGsoub//nPw9r1oz/mWgiIiMVifhI/VTe+15fczJX5s2LPejYCsEUX4Snv9YHd+RaLk6WRURERuivf4VPfCK7wI24ri5fQuWRR/Zf97vfDV8y5YwzYNMm+PSnfX3qc86Br33N15g+9tjs+1NouzsHBpknlU8aNEy9s31nEXokMqw6YEHC8wOBhgy3SdvWzC4F3gy8x7n+aeqZvB7OuZudc8ucc8tmzZqV1RsayxLLnIy0bEpzdzNR/MXDba0K3pASMmdOaewjmQ0/Hj7rRly4A176bn76IVIM7Zth9UdSlwwaiUgnrPs6NPkJvOvXp970xBMzC/AeqbKywc8ffDB9Sea4X/wCpkwZPuPGUNXVPmh9ypTs2skEt/HHvvTQcOadDyfcnNkE90DAZ+M4+2GomDjfp3Mpw3AamaiuuAK2bIFweNhNx4btd2b2QZQoUA5LL4dgmuJoY9Rf/pL9rLZshEJw0klw8skwbZq/hULQ3OxrV7/wgp/Nvm9ffl5fRCQXNm70J1zJgtxCIT/Ak0v9l5c7tqQOHJyxLD/HpVyWYREREclCXx984AOju4Da1eX3sWHDwLKNG4c/3zjzTLjrrv1TJtfWwqGHwkMP+fOadMGcxdQX6aO9d+A8d2rVVMyMfd3+je/p3FOsromk8xSw1MwWA/XARcAlQ7ZZAVxlZrcDJwItzrkdZrY7VVszOxf4LHCac65zyL5+ZWbfAeYBS4En8/buMvTw1oc5/1fn0/q5FBn3CmRv197+xyP9zEgM+tjRtmPUfRLJmZ1pghhtSFKeQpYliUbgldvAZXHhffej+euPSCG5KDz8LojmaWLSw++E5VvYliaW8HWv8wEP+VI1ZD7WvfcOn93+3HN9NpDQCEduy8rgmmt8BkGRYUV6oCmDr8NTj4FT7sjuunEg5MuonPUA3HMMuGFmU8ggCt6QlG6/HX772/xGHx5xBBx/PEyaNJAGqqPDH8TWrPGznHLGOdj1j+zbLXh7DjtROnbtgne/O/eBG4cfDmedBe94B5xwgi8lUFW1f1RpNOr/nysrfcmWu+6C++6DRx/NXfkBEZFc2LgxdbT7616X+5JT/QNHHVtSz8CZfbovnZJrI8lOJSIikgM/+YkP8h6tHUPGC/88THbxefPgzjtT17oOBPxF3bvv9rWn09XMLpbGjkYqQ5V09vmTuxlVMzAGgjd6I7109nVSXaYgTSkdzrmwmV0F3A8EgVucc+vM7IrY+puAe4DzgY1AJ3BZuraxXf8QqABWmh+Ufdw5d0Vs33cAL+DLqVzpXPGvIr/S/AptvW10h7upDOXh+32Gmrubkz7Oxq6OXRiGwyloTCQTu/6e/WDWWMkMLTKcl74HLevzN6DbvYvOTmhPM4/37LMzy4SRKytXpl8fCsFNN2VXLmWoqir40Ifg+9+HzZtHvh+ZIPY87q8vD1e666RbIJAiO3Q6wXJfOuWQD8OGH42sjxOUgjckqW3b/Id8rgf2Z870A/sXXODT0JaV+ZiKUGggmjAcHsj0EYn41Ll//KO/bxxZ5kav9UUf0Zytwz8NZTnMh18iLrsstxceTzjB16deutQHrcejVodGmMYFAgMpvF71KliyxGd6cQ4++1n46U+HT20sIlIImzenLi11zjmpB3tGrW1D6tSRM5bl6UVFREQKr73dl3PMxfnJ0H388Y+pJyQEg7BixfAz7gIBmD0bbrvNB6mXmvrWesoCA3mZZ9fMxsx4pfkVAKrKqmhoa+CQ6YcUq4siSTnn7sEHaCQuuynhsQOuzLRtbHnKX3Tn3LXAtSPtbz7saPcRZ3WtdUX7G+2N9NKTUJKxs6+TSDRCMJDdIHFjeyNBCxJxkf7gMRFJY0OGqeoT5bK8hEixtG6AZ7+Q39K9kS42b/ZjE8myXZj5DBeF0tAATU3pt/nwh2HGjNG/VlmZz7Z+/vmj35eMczv/CuFhjisL3gGTDsu+jk9cWS0c+w3Y8ivoax7ZPiagEf60M2dm55rZS2a20cyuTrLezOz7sfVrzey44dqa2XQzW2lmG2L304bsc6GZtZvZp/L77sYn5+Cii3KbcePww315jO3b/QD/u9/tS2jU1vqsG1VV/qBSVuYfT5rkb1OnwjvfCT/6kS/f8sgjcPTRI+xE498hVnszY1OOgMmvGuELlq777oMHHsjNbPFFi3zWjL/9DY45xg9ijiTdWFmZD+aYOhX+5398quNzzx19/0RERmv9+tTBG2eeOfJUhsNqeTH58rIpUD4zTy8qIiJSeNddl5/se87BP/+Zev273uXLomQy466qygdt/su/5K5/udLQ1oBjIM373ElzmV0zu/950II0tDUUo2siMoz61nrAB28Uy57OPVQklGQsD5bT1DXMCFMSjR2N/Z9F3eFu+iI5TlEoMp6Eu6Dhz0ABy7SIlAIXhUfyVC5liE2b9q+MFHfooYWtkvTgg+nPOcrL4dprR5d1I66sDE491We8F0mr/k/pS3cFKuC1N/gAjNGwMnh1ScVPl7y8Bm+YWRC4ATgPOAK42MyOGLLZefg6k0uBy4EbM2h7NbDKObcUWBV7nui7wL05f0MTxJ13wtq1ucl6MGOGT3+7ejW8/vW+RMbkESSxmDzZtz3xRHj8cT/jac6cLHdStyL7aM5DPwYJM5jGg+5un3VjtFlVamvh+uvhhRfgvPN80MZIg++GmjQJFi/2ZXseftiX1xERKZYXXki+3GwUAYWZaN+UfPn04zTbRkRExo1du+A738lPuc66uvQB61//uj/3yFR1NXzta6PvV67Vt9XTGxmIfplXO4+5tXP7n0ddtH+AWERKSzxDzvaW7UXrw66OXZQFB659lQXK2NWxK+v97GzfSSSW/r4iWDGifYhMGHseVdlSmZjq/ghtG30QR55t3OjHQpI5+eTCBm/ce2/yDCBx73hH6kCTkaiogE98Inf7k3Eo3OmrFaRz+KcglIOIolAVHPwBmHTo6Pc1QeQ788YJwEbn3GbnXC9wO7B8yDbLgduc9zgw1czmDtN2OXBr7PGtwAXxnZnZBcBmIF7rUrLQ3u5LV4w2XW15OXz60z5bxnvf6y9yBXNQki8Y9Pt617t85OQXvuCDOoblnP9SnI1QDSx+z7gL3vja16C1dXT7mDMHnn4aLr98IGtKPtTWwkknwRNPwBvfmJ/XEBEZziuvJF9+yCEQzee5ZmeKGbLTXwvBEdQZFBERKUE335y/C6dPPpn6XOVNb4JZs7LbXyDgz0+OOmr0fculbS3b6A77K9MVwQpm18xm/qT5GP4KcHe4W5k3REpUPGijmJk3dnfsxmL/AAIWYHfH7qz3s7Vla//jsuDIAkBEJowdf4FwDutZi4wFzsEzn8++XNAIrVuXOrvfGWdkF8Q9Wn/9a/r1n/rUyCY9pxIKwdvfntt9yjiz51EIphlcDZTDEZ/x46S5ECiHIz+fm31NAPkO3pgPJIaO18WWZbJNurZznHM7AGL3swHMrAb4LHBNjvo/4XzpS6Of8TRtms+O8aUv+cH3jIIrslRR4TM9fO5zPohg5nDZ4zu2Zh/NOfc8iKZJGTQG1dXBd787uqwbS5fCM8/4cilVBRg7DAb979Hvfw+XXpr/1xMRSeQc7NiRfN2JJ+YxSj/cBZEUF3JmnQIJaY1FRETGKufghhtSz4gbrUce8RMUkrn22pFdsC0vh2tK7IrDpn0D2brKg+XMrJ7JrJpZVIT894W+aF//7H4ZRst6eOS98Pu58JsauHM63H00bL4NInmo7SMT3s6OnQC83PRy0fqwq2MXERchFAgRCoSIuuiIAi8SA1AMo7GjMZfdFBlf6v8ELkXa62AVTDnSl0wVGU92/AW6ChesmCqTLhS2pEh9Pezbl3r9wQfDq16V+9eNRODd7879fmWc2LES+tIEES54e25fLxCChRdCqIBRU2NYvqq0xyVL9DN0mCPVNpm0Heoa4LvOuXZLk2PIzC7Hl2hh4cKFw+xy4ti0CW66aXTBG/Pnwz/+4e8rCjCuVFPjZz7/859wyimwdWuKDfc9A5blr/u886BsfH2QfPWroyuHc8IJ8Je/+GCKXGRSyUZ1tb+wu2CBT28sIlIIu3enTlv4+tf741BedGyBYDWEk+RUnLw0Ty8qIiJSWA8+mDq4Ipn4OUim5zQPPJA8S9ZRR/nzyJEIheD882H69JG1z4dtLdv6HwcswMzqmZgZZYEyuvGRMa/sU/BGWnvXwD8/DXseg2jfQO3nSCf07oPVV8KaT8ARV8OrPj7uMnRK8ezt3AsMDsIqtF0du+iN9BI0/yHbF+1jd2f2mTca2weCNcLR8KDnIpIg3AVtG5Kvm/FaOP3e2HEmAI9e4gM9RMaD576UfcaZOWfAoR+F2kVAwAd/bLgR6u9muOHCVJl0wY8xFMrDD/tsgKkC1t/3vtyVo09UWwsf/nDu9yvjRMOfgTQn1od/CspynLrFRWHRe3K7z3Eq35k36oDEj8EDgaG5OlNtk65tY6y0CrH7eDj4icA3zWwL8HHg82Z21dBOOeduds4tc84tm5VtntRx7ItfTF8PeDiHHgpr1vgDXyECN+LKy+GAA3wGjpTpa/euyf6LwdxzwPL9J1I49fXw85+nThU2nPPPh7/9DaZMKXzgRlxNDXz2s/DjH+e2BpyISCqvvJL6mHbqqfk5uQJ88EaqD7qqeXl6URERkcK6+ebMSna+6U2+ZnVPj7+9+CKcfXb6NpFI6tl2l1wyutKPfX1wwQUjb59rO9t39j92OGZWz2Rm9UwCCeez21u3J2sqAPX3wMrXQ+PfIdI1ELiRKNwOvXvhuS/D38+FSJ7SxciE0trTSm/UX6QpZtmUHe076I30ErAAgUCA7nD3oM+VTDV1NfU/7on0KPOGSCp7V0Ooev/l04+HM/8OFTP8gFlZLbzu17DgHYXvo0iutbwIzc9lvv2Cd8BbXoZTV8CBb4Vpx8K0Y2De+fAvv4ILtsOSD6ZsHo0aTU3J1+UrW3wqzz+f/pzn3/4tf/054oj87FfGuL621EGEANULYUoefnnKauHQj+R+v+NQvkemnwKWmtliMysHLgJWDNlmBfB+804CWmKlUNK1XQHECyhcCtwF4Jx7vXNukXNuEXA98F/OuR/m7+2NH1u2wB/+AOERVglZtgyeeAJmzBjdRbCRCoV8uZZHHoHXvS7JBnseIW0U2VCVB0DFcLVYxpavfjX5rLNMLFsGv/1tHmeYZ6G2Ft7zHmXfEJHC2Lw5eWkUM1iyJI8v3N2YPIVqsNqnUBURERnjenvhrrvSlyCrrfXneLff7o+7waC/vepVvqzi3/6WupTjSy+lPjd9//v9JICRmjTJX2QtFXs69/Q/DkfD/cEbLmE2ogZRU9j6W3j4nT7DxrDJXvHBHXseg7+eAX2Fqdcu49f2lu0EYpdmR1KmJGf9iAV3mVl/0Nf2luwDvpq7m/1+MMLRMPWt9Tnro8i4svuRJEGABif93/7n+6EaOOHH/l5Kgpmda2YvmdlGM7s6yXozs+/H1q81s+OGa2tm081spZltiN1PG7LPhWbWbmafyu+7y6P13/XZzTJx9Ffh5Fth0lI/2Dt0gm3ZJKieD8ddDyf8hGRJ/Fu7JqecgLpkyeiyz2fr6adTj8ssWeLHtfJlpONBMs41r/XXmFNZ/N6MTo1GpHaEKTAnmLwGbzjnwsBVwP3Ai8Adzrl1ZnaFmV0R2+weYDOwEfgJ8JF0bWNtrgPONrMNwNmx5zIK11wz8nIahx/uL5pNnVq8jAzgZz9Pngz33w/HHjtkZfPa7HY253SIjp96to2NcNttI8u6MWsW3HuvL1tSKmpq4OMfh7e+tdg9EZHxbtMm6Ozcf/m8eaPLVjWs3ubkJ7U1B/lBAxERkTFu5cr054+hENxzDxx3nA/iGKq2Fk46Cf74x+SZsJ58MnlgyKGH+nPX0TruuOG3KYSO3g7C0YFZGD3hHmZUz2BG1YxBy/d27cWli5SZiF75OTx+afbfrSJdvjTrytf5WWsiI7S9dTtlQR9l1h3uprMvyYlHATS0+kTHzrn+z4mGtqGJk9Pr6O0g6mIjRLExtMSSTiKSoPHv+193XvxeqFmUPAt0sBKO+lJBuibpmVkQuAE4DzgCuNjMhk5PPw9YGrtdDtyYQdurgVXOuaXAqtjzRN8F7s35GyqUcAds+UXy7GaDGLz2RnjVJzILWCqrhUUXw+t/BxYatGpfx7SUgdwjLZ84Ui++mHrdGWekD2YfrVKYjCslqHU9RNP8PR78rxDK0+RBpdTPSN5rQjjn7nHOHeqcW+Kcuza27Cbn3E2xx845d2Vs/dHOudXp2saWNznnznTOLY3d703yul9xzv1Pvt/feFBf72cyjWQQatIkuO++0joIVFX5YIP+iMXeFuhryW4n887LfT2nIvrpT0fWLhCAP/3JB8WUmupq+OUv8zzzXUQmvBdfTB7cuHjxyMtQZaS3OXkQYe1iXx9QRERkjPvFL6Atzbj3rbf6AIl0KYSrqnzmxRtv3H/ds88mT0/85jfn5npRqprV6Tyz4xnWNKwZ/YsnaGhroDI08EMKWIDqsmpmVM+gJ9wzaPm+7n05fe0xrXUDPPnhkQfFRruh9WV4+uM57ZZMLHWtdf3BElVlVUXLVLGr02f9iLhIfwDGzo7syqbs6thFRdDXm4y/p/o2Zd4QSaolSV23o7/iB6KTCdXAoVdCoIB1yiWVE4CNzrnNzrle4HZg+ZBtlgO3xca9HgemmtncYdouB26NPb4VuCC+MzO7AD/5OT6xeezZsRIsg3Ttx38PFr8v9d9CMqEamHsOnHLHoMX7OqalzbxRqImqkYgff0vlTW9KHqguklf71kIkRS2fipk+s02+BAtYs2gMy3vwhpS+G28ceXTf7bf7zAzJZjoVSyDgZ1L9/vexi3Ltm7JPMX/AMAWUx5BoFL7//ZFdXPzMZ+DII0eXUjifKiv9/7OISL7s2JF8+cEH5znbVHeKtMk1iyBQoh/KIiIiWfj731OvW77cZ9nLZJJATY0vq3jmmYOXr0txefud78zNxdpJk7Jvc8nvL+GS318y+hdP0NDWQNAGvpRMqvAdqy6r7i9/AFAZqsx6Jv245aLwyMUQ7Rl+23Si3bD117npk0xIW5u30hsL2A5asL98SaHt7fRz4nojvfTFsv81dTZltY/GjkZCAT/rOV6yaXfn7hz2UmSciPZB95DgqKlHQ+Wc9O1cBOa/KX/9kkzNBxI/rOtiyzLZJl3bOc65HQCx+9kAZlYDfBa4ZriOmdnlZrbazFbv3l1in7/bfgvh1vTbzD4VlnxwZCWCQjUw92xYeGH/or0d01MGbB99dOryirm2bVv6sZXTTitMP0QG2ZdmQsHs0yEyyvMkGbUSGnKXYohE4KaboGcEf4sf/CCcemrqGsPFVFkJy5bB//t/QMfW7OozVc2Hsql56lnh/f3vyVP+D+eYY+CLXyztyM9QyA+giuSa6ldK3L4UE1TzHqXfuyf58kmHQqiE6liJiIiMQH09tKRIjhgMwg9+kN15SE0N/OhHgzNqbN6cfNtXvzrz/aYzkgkMDW0N7GhPERk6QvVt9QOlCoCplVP7H0+uGEihaFjRZvWXnJdv8KmCc5HNTOXsZBRebnq5/3HERdjeUpzgjZYe/4EcsEB/1oz4skw1tjf2B22UBfyI2N6u/RIli0jbpv1nHR98GQSGGUkumwxL/z1//ZJMJQsHGDrykGqbTNoOdQ3wXedc+3Adc87d7Jxb5pxbNmvWrOE2LxwXhYa7028TqoHX3T66612hWjjhJ1A5G/CZN1JNWD788JG/TLbWr/djGMksXVq6k2ZlnGt9OfW6eedB2QhmKkhOKXhjgvvrX0eW9n3RIrj++tIe2K+thW98A+jY4mfEZGrmyclT1Y9R3/1u+nTEqfzyl+lTFJeKUv4dlLFJ9SslUXNz8uVHHZXnzBs9KWa6TT4sjy8qIiJSGA89lHq227/9W0IJzCzMmwcXXzzwPFn2rEMO8ZkJi6Gzr5OWnhZae1rp6E2RonYE6lvr6QoPBBDMqJrR/zgxkCMcDSvzBvjJHc9cnTpNsEgBvdL8Sv/jzr7OomTe6OrrIhyreV5bXktVmZ+h1R3upi+SeX3lxo5GwtEwoUCIipAv7dDe2z4ouExEgNYXwYYMySx+f2YZNmedAmVT8tMvyVQdsCDh+YHA0C9YqbZJ17YxVlqF2H08HeuJwDfNbAvwceDzZnbVqN9FIe192meOSee47+bmdztYCSf56jP7OqYRDiffbO7c0b9Uptavh64Usb6nn164foj0i3RDb5oMa3PP2f84JQWn/4EJ7vrrRzaw/6tfjY2B/YoKfBRZNsEYtYuzL7NSolpbYeXK7Nudey4cdFBplcMRKSDVr5R+qY6RS5fm+YV7U6T8qCih2RMiIiIjdP/9yY+xFRU+AH8kAdq1tfCd7/jgyuZm6Esy5njCCcUL3niu8bn+x2sb1+Zsv1uat/QPvALMqRlIuz6zemb/465wF3WtdTl73TFrzX+MvlyKSI7Utw1kw4m6KBuaNhS8D7s7d1MZ8hf4astrqS3zH8AVwQr2dKbIBphEY3sjXX1dlAfKqS7zM6fLAmVZl18RGfda1kE4IUXy5MMgUJFZ20iPLy0hxfQUsNTMFptZOXARsGLINiuA98ey9p4EtMRKoaRruwK4NPb4UuAuAOfc651zi5xzi4Drgf9yzv0wf28vD+r+mL4Ew+TDYdF7cpNlNljhg5xmn86+jmkpJy2PpPzhSK1Zk3ry9LnnZlYmUiSnWl+GYIq/t8oDoGJm8nVSUBqancCamtLXGU7ltNN8XbBU6Z5KSTAItL6UXaNJh0FwfOSruu++WABLlr71rcJ+iREpMSVZv7Kka1eOYx0pJmUuWJB8ec70pagFWj45+XIRmfBU8kvGklWrki+/4ILRZbaqqvIXQV95JXl5z1NOKV7mvn/u/GfSx6O1ed/g+jBzJw1MJZxdM7v/cdRF99t2wunY5tN2Dzf7U6QAnHP7BUds2rep4P3Y3bGbYMB/8E6umNxfbqksWMaujl3pmg6yrXUbDkcwEGRy7JylPFie1T5EJoSm1eAS0gHMecPgum/phGph7rn56ZdkxDkXBq4C7gdeBO5wzq0zsyvM7IrYZvfgJ2htBH4CfCRd21ib64CzzWwDcHbs+fiw9Tfg0mRyOuZrmWWeyVSoGo79BnvaZqbMvJHsPCFf1qaJ2c5VOUeRrLSuT71uzunjqirBWKbgjQns7rtTp6pN57//e4yVqujYkt32kw/NSzeK4Ve/yj6zyjnn+LI4IhNYSdavLNnaleNYNAo9SSYHmBUgwK0vxYd3SMEbIrI/lfySsWT3bmhsTL7u4x+HyaM41E2e7PfxyivJ1592WvGyCz687eGkj0draJmFeZPm9T+eWzs4J3RiiYYJad11EM0wcGP68XDgBT5tcPkI6vhIRvIUeHihma0zs6iZLUtYvsjMuszsmdjtpvy/w9Raelr2O1Osb61PvnEe7erYhcVOY6dVTmNKpU9bb1hWgRfbW/xnUcACTKua1v+4sSPFB77IRNXy/ODnB5wFoQyn3geCPthDiso5d49z7lDn3BLn3LWxZTc5526KPXbOuStj6492zq1O1za2vMk5d6Zzbmnsfm+S1/2Kc+5/CvEec6azHjrTZH6rXgDzzodADmcJWwCmHs3OzqGnw15NDbjhrtTmUKrzErMCTAwTSaZlHYRTzFaccaIPFJSiGwO5EyRffv1raE87VLi/k0+Go47KT3/ypne/7zrp1RyUn34UWF/fyEqmfOtbYyw4RyT3RlO/sjxN20Yzm+uc25GkfuU7zeybwFQgambdYy4N4jjU2uqDHIemN5w8GcLh0c0MHlY4xQE604s6IjLR9JftAjCzeNmuFxK26S/5BTxuZvGSX4vStF0OnB5rfyvwAD5bVGLJrxRn/SLJPfywL8E59Pg6dy4ce+zo93/KKXDDDdDdPXh5IACHHDL6/Y/UE/VP9D9+sv7JnO03cXC1MlTJrOqBIN95k+ZhGC42QtzQNvQr7QTS1w6v/F/6mZ8YHPRuOOarPmVwPENHoBxeuQ3WXZt+AEKykhA8eDb+/OopM1vhnEs8diUGHp6IDzw8cZi2zwNvB36c5GU3OeeOzdNbysr2lu1UhCro7e2lLFBGX7SPXZ2Fz1Kxq2MXkVhQ0/Sq6fRF/d9I1EXZ3Zl5xscd7TsAcLj+rD9RF6WxXcEbIoN07Rj8fMZJ2bWfdHDu+iKSbw33goWAFGVTDv1/mWeeyUaggt2R45KumjbNn4eMZFJztsLh1ONvBx7ox2/Kx0cCeBlL9j4NpKglOv14HwAlRaf/hQmqpwceeCD7dv/934VNK5UTiXUEM1E5e/htxoB//CP70jZnnQUH6xxARPUrBYB9+5KfzE2dmrpeZU44B5Hu5OtCY+0gLCIFUpIlv0SSefrp5Bcx3/lOiOSgmkVfH7zwwv7H6vnz/bpi6I30srV5a//zbS3b6Amnqf2dIecc+7r39T8vC5Qxs3qgRvGsmllUhir7n0/o8gVbbwdLE3lrQXjd7XDCT2DSUiibBOVT/S1UDQf/K5z/HEx7TaF6PBH0Bx4653qBePBgov7AQ+fc40A88DBlW+fci865LOvnFl5dax0WG7CqKvPf8XsjvXT0FjYmcnfnbrpj5x6zamb1f4b0RHqy+syIl4CJRCPMnzS/fx/KvCGSINID0YRz/bKpUDEz5ebJ99GV0y6J5NXuRyCS4rgWKIelH4ZgZfL1oxEI0dQxJ+mqadNIWU4l1/buTV3S/lWvKt65iUxw7WlKaU5aWrh+SFoK3pigHnww+6i+ZcvguOOKl2Z2RCK9g+sIDqd8OsmrHow999+ffWaVL39ZWTdEVL9S4pqbk2fXmDrVl1TJm3BH8ijnYDW4fL6wiIxhJVnyy8wuN7PVZrZ69+7MZ+/K+LZmTfLj6Hvf69MYj9akSfBSkmHbxYuLd4H0hd0vDAqiqAxVsm73ujQtMrO3ay/BhICEgAUGBW/MrJ5JKCENdVtvG+Foga5Wl5r1306d2SxQBqeugPlvgrIUJ8TBch/IcdaDMPNf8tbNCSZfgYfpLDazf5rZg2b2+mQbFOrYtb11O+FomIAFmFzh60VVhiqpay1sdpf6tvr+z4XZNbOZU+MHu3ojvexo25Gu6SDN3c397eZPnk8oEMp6HyLjXtcOCCRMyJixLPtgDCtAugCRXGl6IvW6OafntX5Jc3PyfU+fXriyKU1NqTN8HH64z0YoUnCpKhUEKqBiRmH7IimpbMoE9Yc/ZD+wf+21Y/CA0tfiozijGc5qqjnIz3YOpgiJHENWrsxucHHyZHjta/PXH5GxxDl3Dz5AI3HZTQmPHXBlpm1jy5uAM4d53a+MoLuSJ83NybM3Tp2a5xO9cJsfRIgMGVwpnwrRXr9ORGSwkiz55Zy7GbgZYNmyZQWsLCylbP36/ZeVlcGrX52719izZ/9lBx+c55JnaazZsYZoQgBmxEVYs2MNx81Nns45U/Vt9VSEKuiJ+PNdh9sveCOQEBBaEaygsb2R+ZMzGeMeRzoboD1FwXGA13zbDyCEqoffV9kkOONe+NOh0K2MAqNU6MDDHcBC51yTmR0P/NHMjnTOtQ7aSYGOXVuat9DZ10l1WTWzqmdR11pH0IJsb93OYTMPy9fL7md7i4+BCQVCzKiaQTgaJmhBIi6ScSBJb6SX7rDPJhCJRphTO4fyYDnhaJitLVuHaS0ygXTtgEAI4pnGpp+Q2bEnUbbbixRLNALtm1KvP/AdEMrfLNLevuRf/KdNy0+llmSamlJPhD722DE41ibjQ19b8uWTD/UBhbruXBLGUg4FyaFVq7If2D/ttOJd7BqxvpbsPmxqDspfXwoonio4G+edt39daBGRiay5OXmQRt5P9KJhkl6PLpsyUHtdRGQwlfySMcE5qK/ff/lxx+X2XKS1df9lS5bkJrPHSDy2/TE6+gZSRnf2dfLY9sdGvd+GtsExWuFIeL/gDZcwnl0WLNuvzYSw414/WJbMjBNgyQezGwwLVMBJ/5eTrk1wowk8zKTtIM65nlhAPc65p4FNwKEj6nkObGjaAPigibm1cwEIR8P9wRSFsrN9JwDlwXKmVk5lauVUyoM+VW99W5IP7CR2d+ymIjYJqrKskhlVM/qz/tS3ZrYPkQmhq4FBcWZTXqVBMhm/2jelzxSz4G0QyN9gU6pyjFOnFm6Ma8+e1JO/jjmmMH0QGSQaTp3xafKrCpeWRoal4I0JqKsLtmzJrs0b3wg9oy/JW3i9zenr2g5VPj277UvUs8+mrqeWyiWXwJQp+emPiMhY1Nyc/GQv/yd60eTRIWWTVDZFRJJSyS8ZK+rrkx9DTz89+/OXdJJlmTzyyOKVAH207tH9lj1Wl5vgjcQyKN2RbmZUD6S6nVk9k75I335tJpytv/Fl6YYKlMPrfpP9LOZgBcw+BRZemJv+TVz5CjxMysxmmfkLPmZ2MLAUf1wsileafTYYwzho6kGELERXXxfbWwsbvLGrwyfVClmoP3gjHngRXzecxo5GyoJ+gK62vJZpldOwWDB6pvsQmRC6GnyJ77hxMolQJKnmZ1OPs0w5EkJVydflSKqJyxUVhc28EU5RsXDOnML0QWSQ3r2pqw5MOQJCRZrtIPtR2ZQJaPVqqKrKrt7vRRf57BtjTqqatqkEysHGfkzTo49m9/9bVgZnnZW//oxbzkHnNmh5AVrWQdNT0LzWBw1F+/zN9fnfKSv30fTBCqhZDDNeC1OPgalH+qhGHRhFSk5fX/KTvalTU9eszAkXIWnmjXEQXCjjR12dvxDR2elnss+eDQccUOxeTWwq+SVjwcsvQ3m5n1CQ6E1vyl3aYOf8Z9NQS5fmZv/ZikQjbNy7cb/lG/duJBwN9w+SjkRdax1dfQM/zFAgRGVo4Ac5o2pGf0kV8KUNMp1JP25EemH3Q8nXHXI5VMxMvm44oVpYdgNs/8PI+zbBOefCZhYPHgwCt8QDD2Prb8Ifm87HBx52ApelawtgZm8DfgDMAu42s2ecc28ETgW+amZhfNGCK5xzKYp+5188kCriIiyYsoCKUAUdfR283PRyQfuxt8v/CMyMaVXTCEfD/eWWmrqaMtpHY3tjf7DGlIopTKua1p/1J9N9iEwInXUQTUg1VjWveH0Rybe9a1KPzcx/K1h+hyZTZd4IBgsbvNHbm3zdmBxrk7GvpymWESdJ2stJh6XOVigFl/f/CTM7F/ge/mTqf51z1w1Zb7H15+NPxD7gnFuTrq2ZTQd+AywCtgDvcs7tM7MTiNWlxI96fMU5pzPpIR59NLuUtMGgz7wxJmWbXj5QVrijdx499lh2/8ennZZdsMeEFe6A+j/7C3T7/gkdW/1gaqDMp5uKpvg2BkDCTK/O7f4CYqjGB3aEO6F8Gkw+DGafAYsu8pGOIlJUqU70Jk/2A095E03xwgrekCKKRuHJJ+G3v4Xf/MZfhCgv91+bnPMZ2ubN85m83vEOX791HHylEpEce+ml5Bcwjz8+d6+R6jxoXpHGR15uepnyYDm9kd7+AdGoi1IRquClPS9x5OwjR7zvTfs2DSqLMql80qD1FaEKygJl/QEc3eHugpdkKLrdD/tA+qEXKC0IR30RykZRaz1YCQe9e1Tdm+jyFHj4B2C/a4HOud8Bvxtll3PCOceezj0A9IR7WDJtCcFY6vhX9r1S0H609vg6Uw7H1Mqpg7L5tHS3ZLSfxo7G/nZTK6cyrXIakdg5TUtPC845TF8MRaB9SLKfkQYQiowFux8GUqS/WPgO/z0qj1Jl3ggECnetYufO1Jk3ilXOUSa4nj2pJ69XKh1MKclr8EYsHeEN+BS7dcBTZrbCOfdCwmbn4VMVLgVOBG4EThym7dXAKufcdWZ2dez5Z4HngWWxCPy5wLNm9qdYKmCJ+dvfUkf8JfO616U+yJS8bNPLB8oYD9WE1q0bfptE73oX1I7imtW4FumGhvtg8y2wY6X/HQm3DdlmJDt2g6OPe3bD7t3Q9CSs/zZUzoaD/xUWXQKTlozmHYjICEWjyUv9xQes8/jKJM+8UfrHp54eePhhH0S4d6+fWT11qh8wO/tsOOwwDeiPRatWwfve58sQdHUNfC8cOkD6yivwzW/C9df7LBy//CWceGLBuysiJez55/fPujF3bm5fo7k5eXaPYl0gXbNjTf/jiliK2q5wV/+60QRvbNm3ZdDzaVXT9ttmUsUkejoHsm9s2rdpxK83JtX9ESJJSqbMf8voBw3KJsGR/zm6fciEtK97X38wQ9RFWTh5YX/mirq2uoL1o6Ovoz8ALOqi/cEb0di1tL5oH93h7kEZfZLZ1bGrP0hsZvVMplVNoy/qZwgZRmtPK1MqVadXhK6E0mUW8McRkfGqJc0AxeTD8/7yqYI3Cpl5oyFFtcIpU/x1lfyWZBZJoqcp+cVugMpZhe3LSEUjPhiy5TnYtxZa1/vJ0a4XApVQPgWmvhqmHgVTjoKquWPyYnS+M2+cAGx0zm0GMLPbgeVAYvDGcuC2WDT942Y2NRZ4sShN2+XA6bH2twIPAJ91ziUmR60EUvwWTmwvvpjd9u985xiOBMw2eMNChRsc+/0B0N2Yl11v2dACZJ576w1v0JeFQaIR2LkSNt0CDXf7WVnxgI1oFilNRvTavUAvdGyBddfCuv/yNTAP+RAcdBFUz8/v64tIv0gk+ffZUL6/PaXKGlWimTd6e+HWW+EXv4AnnvD1Qzs6BmcuqaqCq6/23yfe9Ca4/HI4+eTi9Vkys28fXHkl3HVX8hIEyfT1+dumTXDGGXDZZT6gY8x+lxSRnHr++f2XHXqoP5ZUV+fmNZqb9z9Wh0J5LnmWxuN1j9Pe64O2DesfsG3vbefxusd536vfN+J9N7QPviI8s2r/GbzTKqf1z/AH2NaybcSvNyY1/i35d6vDPw1lOchXXbNg9PuQCaeutY6KYAW9kV4mV0xmTu2c/swVuzt2F6wfuzt2UxGsIBwN0xfp6w/eiPelMlTJ7o7dLJiS/vd8e+v2/jazamYxuWIy4Yh/XhGqYFfHLgVviAD0tQ48rpgNkR4I5egLkEgp6WuHvrbk66oXUohhu1Tj02aFG8dtTDH0M3OmP/+pqChMP0T69eyBVLkOyqcXti/Z6Gv3QfkbboK9T0KgIpbRviP5uV6gHIJV/jgbCMK8N8GSf4M5b/DPx4B8Dz/MBxJzctbhs2sMt838YdrOcc7tAHDO7TCz2fGNzOxE4BbgIOB9ybJumNnlwOUACxcuzP5djWHRqE/XlI23va0AA1X5km0ghgtnH/AxUnkK3GjumEJ3X3YziA48MC9dGXucg4Z7YfWV/kAW7qCoMWDR2Ay5tpdg7Rf9bckH4ehroKKED6Yi40Sq4I38B7ulOItMdeY5nKyDBQNwSWYphe69Fz70IT9Q1hGb1NrTs/928dnPnZ0+0OOOO3wmjh/+UMegUvXww/DWt/r/s2T/p5no6oKf/Qx+9zv4y1/gmGNy20cRGXt2JxmTPOyw3AZWNDf7dMiJpkzxn2VVVbl7nUw9sv2R/sfd4e5BpQMe3f7oqPa9q2PXoOeza2fvt83M6pls2Luh/3lDW4opgOORi0Lbxv2XV8yA6Tmq1RPQVXfJ3vaW7f1llKZVTWNWzaz+zBV90T7aetqYVJH/Gfm7OnYRitU274309gdv9EZ8ut5QIMSujl3DBm8kBoUdUHMAAQtQWVZJZ18nQQvS2NHI0hlL8/dGRMaKcEImqKp5EFUNaxmnunf6DGeJWafjph0L0fyneR96PhCX6lpfPjQ1JV8+Y0bqUs0iedWzJzZ5OIlcBLbn2r5nYe2XYMdfIBAa+EwZ7vgZ7R14n1Fg22/9uJ8FYfH74Kj/9JnvS1i+h+STjT4M/WhMtU0mbfffwLkngCPN7HDgVjO71znXPWSbm4GbAZYtWzahsnPU1fkLY30ZfjcsL/dpr8esbIM3on2krMU2Rry881Cqyrvo6yrPaPt58/RlAYC9/4Sn/h2an0+eVrfYIrGRz43/C5t/Bu9K8uVXRHIqVdmUvAdvpMqwkSojx3CyDhYc/ji4davPqPDkkwNBG5lyzgcE3HOPn2199dXwhS8oA1QpeeIJOPfc7P9vk+nq8rdTT/UDqiIysSX7HDjqqNxm50n2GlOn+nPgQgdvOOd4cc9A6supVVMJEGBPl8+Esb5pPVEX7R/EzUY4Gu7P6BE3r3beftvNqRlcu7ipK8VV5PGoY0vy71Vz3+gD5YM5CLwIjNWZLlJM21u39wdIzKqeRU1ZTX/ZlKpQFXWtdRw+K/8p5RMDwMqD5YQCIUKBkA8ycz5b0O7O4TOB7GjbAfhgj5nVPgNQbXktnX2dOOdobM/P5CWRMWdQ8MZclDRcxq3uxtTXtqa9piAZZ1JdY0p1rS8fUk2EmTGjMK8v41TXDtjzGLS+7I8r0R4I1UL5VJi+DKYfl7o8ZPfOFJk3rLQyQXXvgjWfgu13QqQbcKMctnUDmfU3/hg231Ly42v5PsusAxLDsw8Ehk7zSLVNeZq2jWY2N5Z1Yy4weLoJ4Jx70cw6gKOA1aN6F+PIyy9nN6tpyRI/wDK5BIOuMpJtivlob+Eyb+TJ9qbs0rbmOk3xmNOxHdb8BzT8eeBAUMqi3WM9vkhkzEiVSjHvJ3kWIPlnUWn88T//vB+Ib20dXfBfvLzGf/83PPUU/OlPueujjNwzz8BZZ+UmcCNRa+vw24jI+Jfss+DYY3P7Gs3N+9e4njo1dd3rfHql+RWCCeeki6cuJmADwRtBC7J532YOmX5I1vve2b6TymAlnWFf18ow5k3aP3hj7qS5g573hHvo6uuiqqwIaUgKbd9aXxp1qAUXlubMMpkwtjZvpSvsJ2jMrZ2LmTG5YjJNXU0ELMD21u0FCd7Y3bmbvtjMxeqygYtC1WXVtPa0EnGR/TL8JN1PrNRLebCcaVXTAJhcMZldHbvoi/bR2KHgDREgdt0xpmoeBIpU000k37obU188m/26gvzul0LmjVTXzKZOTd0/kf1EI75kyCs/hz2P+hJcgQo/ATlxol+gIra8CyYthblnw6FXwaSEc83eluSvUT7VT2wv9sw652D9d30GehdOnSVkNBKzcpSwfH9EPAUsNbPFZlYOXASsGLLNCuD95p0EtMRKoqRruwK4NPb4UuAugNi2odjjg4DDgC15e3dj0MaNfqA+U0uXFuciV86UTSKrwfhoX+GO3nnS1D6DcCTzuKxDDy1e/eeiiobh2S/Anw/zB79IFyUfuCEiBZXq+2o439kdLUjSz6ORZt7Ioaeegte9zg+M5SprU2cnrFqVm33J6LzwApx2GrTnIfh8jH+9EpEciEYHymglWrw4t6/T2Zk8eKMYn0NrdqwZlFXjqNlHcdTso/qfByzAmh1rRrTvhrYGyoIDJ3KVocr+Ge+J5k2aRyDh0k9VWdXEKZ2y75nBs5zBB8kecFZRuiMS9/Lel/sfHzjZ1xCcXuVLo4ajYepa6wrSj8b2RnrCflpwYpmW2vJawAd7xQMz0tnbvRfwmTemVfrgjfh9d7hbmTckqb4++NWvYPlyOOMM+MAH4PHHi92rPIsOCd4IToBASpmYuhvBpUj9PvnIgnQhVXBEOFz84I2ysuSTxfLmgAMGZqgV6zam0/sXSaQHNtwMdy2Exz8A9XdBz26faSPcuv914v7lfdD6Arx8A9xzNDzwJtj7tN8madYNfFnJYpfyCnfAg2/1ZVIinZkHWASrofpAqFnsj63JgvfHoLy+C+dc2MyuAu4HgsAtzrl1ZnZFbP1NwD3A+cBGoBO4LF3b2K6vA+4wsw8C24ALY8tPAa42s3jti4845/bk8z2ONTt3Jr9glsqhhxanLnDOlE3JLpNGb1NJDI6NRlPbDHrCmZVMATjyyNymKR4Tunf5A0HzcwPlSEREhggEkp9M5b3UlAWTx5JFihsV/OCD8KY35T4jA2T33UTyo6sLzjsP2tqK3RMRGa9aWiAU2n8ywdSpuX2dZLPppkwpzuy2J+qf6C9tUh4s5+jZRxMMBKkIVtAT6aG9t50n65/kXUe+K+t917fW4xK+MJQFypIGb8ysnklFqKJ/ln/QgtS31bNk+pIRvqsxZM+jwJAvbtOOo1SymcnE9cq+VwD/9xjPmDOzeiYb9m6gs6+TbS3bCtKP+rZ6IrFrYJMrBrLRTK6YTENbA33RPhra0wd7RaKR/s85w/ozb8yo9jnhHY6tLVvz0X0Zw377W/jwh/0gavz8wwzuvBMOPhh+9zs/oZADDoDGHAT/zJnjL4oXk4sOHoiadHD25b5FxoquxsGZZhJVTC9IF1JNyGptLcCkrJhUk6KDwQIHb+Tic3Q89GEs2fobePLffSBGeIQzrFwYImFouA8aH4Dpx0N5ir+/QHlxKxL0NMFfT4e2jYMDHZOpmg+LLoZ5b4IpR0D5NB+44pw/rgbKobMemtfCtt/6idsj/RkWUd5DUJxz9+ADNBKX3ZTw2AFXZto2trwJODPJ8p8DPx9ll8e1HTuy2/6YY6AiB2Vgi6ZsanYRYx1j/4RyZ8scItHMU2m8+tV57Ewp2vOEjzbsa00dATxaFvQHjUCFr6McDcciHzvG5IFCZKIKBpMP9OQ/80aKsil9LdmXA8uRLVvgLW/JT+CGlIZPfQp2785+BkowWICAJhEZF5qaoLx8cPCGWe4nCySrY12sTIOPbHukP8CiMlTJYTMPwzAqQ5X0RHpwOB7e9vCI9t3Q1kBvQmCnmaUM3igLlvUHb0RddOJk3mh+bv9l015N/pPQiqS3o91fnKsIVTC7ZjYwUOLI4Xi56eWUbXMpMcPH9MqBi/nxrBkA21u2p93H3q69lAXK+j/T4m1nV89O+joi118Pn//8/gH8zvnzzXXr4LWv9dkZj8/VYF8pDBqGO8DKBq5FVh1Y3P6I5FPHVpJe1wpWFWxWfCjFy+zdW/zMGwUP3pCxI9INT33EB29EOnO006jf157HUm9SpOvNAIQ74S8n+8+NdNk25pwJx14HU4/ygSahgZJ/+5Viql3kb3POgBN/Ag33wDOf9cEhY8T4yB8iGcs2yPjIwmSxyp/yKdnVL2rfAsHKvHWnEHY071/nOJ0DJ9K5wvY/wqPvyeGBD5+OafpxMOVImHEiTD3Sp2eKhoFoLGLRYlF/IQh3QdsG2LsG9q2Blheg6Ukf3CEiJSVVlH5Hhw/gSHUiOGqBiuTRzn3NRamJ29vrM250ZvHROXMmLFrkB+na2mD9ep8WV0rTU0/Bz36WWQaUI46Ad7wD3vtePysuHrzx4ovw85/D738Pmzblv88iMvbs3bv/sXXKFH9MzWVp3WSZN4pxgdQ5x3O7BoIHoi7K0ulLCViASHTgSu663etwzmFZdnBry1a6wwOzkhwuZfCGMbDv7nA39a31Wb3WmOScTys81PQToKy28P0RiXHO0dTZBPgyI/HgjQWTF/RvE8/MkW872wcuEk6vHgjemFE1o//xjrb0s8AaOxopD5bTE+khEo30Z96YUzsn6etk6qP3fJTPvf5z/UEtMj5cfz184QvpzzuiUZ+t6/TTYVwlBQy3++uCkdiJcXAsz5YUGUZniqC9ytl+cDqQ/+9ikyYlX75vX95ful+qIJFiZASUMaBtEzxwPnRuz0+2+FQlUyB1Ce98cw4e+4B/z6nGcWuXwAk/hpknQSjLEgJlsQ+C+W+FuefCxp/A2i9CuPS/YSh4Y4LZPXypykFyXX+44AJl/otxptk3+popyodUDu1rnzb8RgnGdGaVbLz0Ax9dl4sDX/VCOOjdsORDUD3f/36FavzvWlyqAdbycpixzN/CHT7II1AG9X+CzT+DnavSH0hFpGBSlU1pbvYBDXkL3ihLEXjY2+JTvxXYV77iM28Ml11h7ly48kp45zt94Eb8glwg4Gc8P/II3HYb/PKXqVNHSuFFo76+9HCBG9OmwQ03wFvf6n/3E78/hEJw9NFwzTX+9+XWW+HTn85xphYXhX3/hB0roeMVn0ErUOFTPs462UfgFyj9qoiMTFPT/sumT/fH1Fyek5RK8EZDW8OgII2uvi4WT1uMYYOCLiLRCHWtdSyYsiDZblJa3bB60PPOvk5+sfYXTKoYfKW6saNx0Ov1RftYvWNw23GprzlWim7IF5iZJxSlOyJxTV1NBGKlEgxjVs0sAOZNmkcoECIcDVPXVphMFbs7By4SJmbKSAwE29WxK+0+Gtsb+99Pb6S3P/PGzOqZ/e9nT2d2Fa3rW+v5wVM/4NUHvJoPHvfBrNpK6XrhheQZN1IZd1kfwx2DZzYXYWKGSMF0pwj8q5xTsOve01NcHti3L7eB4+mkCtJIdr4iE1zz87DyddDXTlFKPBYr88aGH0HD3anLLM1/C/zLr/yE+8AoLsQHQv52yOWw4G3wt7NHvq8CUfDGBJPsglk6teNhQkqwBqLNmW/f3Qg1B+WtO/nWF8nuz7pYKYQL6qUfwDNXjy5ww0Jw8GVw2P+DSYf4GJ/QKHM8J0YKLrgQ5p7nrypv/x2s+wa0FSZVqogkV1ub/ISuuTnPpVOC5bHBhiFf1l3YB3wFCxfA8eyzfnZUugts5eXwH//hZ1AlDuoPHYg76yw48UT44hfhgx+Ehx7KW7clC7/5DWwdpmrcOefA7bf70gaVaRKUxUsfXHopvP3tcMEF8Pjjo+icc7DjPn8y1/gAYD5T1dDgpk3/65fXLIaFF8KrPqFADpES1NKyf/DejBm5L72U7EJoMdISr9mxZlC5khnVMyiPHcNn1szsn4leFixjzY41WQdvPFH/xKDn4WiYbz36raTbuiETFFZtXpXVa41JXY0+yG/oMWPSocXpj0hMXWsdFcEKeiI9hKPh/swbs2tmUxGsIBwNs7sjy5lXI7S3a2//43gQSbwvcU1d6S8k7urYRTR23hKJRvoDyKZVTqM8WE44Gqa5uzmrfj207aH+ewVvjA99fT57X/cwZewTjbuBzXhm3rgClY4QKYqevcmXV85JvjwPZs1KvnzfvsKNh6QKElHpWRmkbSOsPNVPUspG7RL/NxUI+XGv1pd9ye2RSJYBOhu/P8CPq2YsAG95Cf756dRjdks+BMdfP7g8ymiFqiAwH974ZO72mSf6ljDBZBrdHFeoKMS8qpgey6iRoY6tYzp4I+IUvDHIrn+MPuPGgcth2Q1+Nny+UuwGAlA+2T9e9F5Y+G7Y8gt49vPQk90sFRHJjalTk0fJNzcXIHNEqCp5nZFIR0GDNz72sfQX2GbPhn/8A+bPh5oMMtdNmuRv994LP/whXH117voqI/P1r6ef1Xb22fCHP0B1FudK1dX+tnIlvOENvixL1pqfhyc/DPue9b/36cTTHba9BC9+C166Ho75Khx6lWa0iZSQcHj/gZhUM+JGI9mxuxgZn55qeIr23vb+50umLRn0OB680dHbwVMNT7H8Vcuz2n9PeP+yi0ODNFJp7cnywuBY1LPLl65MVDlHBcal6La3bO8fv+2J9DCr2o8uzaqeRSg2ozDqorT2tDK5YnLe+uGco63Hf4cqD5YPKpUys3omIQsRduFhPy8aOxrpifjPo8qyyv4sHNOqpvW/n3A0TFdfF1VlmU2AWblpJQD/2PqP7N6UlKwf/xi2bRuHARnZGDowpvMUGc9ciizolXMK9rs/e3by5S0tfhJSIaTKvJHsvCiv5syBxmwG1vPUB9lfbzOsekNmQRfBSlj8fjjoYph+vD/XSaw4EKqGrh1+8tOGH0FTFgEKLsygAMNsZRW4ARCFtV9OXTFhzhm5D9yICwShfEru95tjqq40wWQT1Tduam/VLMpu+9aX8tKNQrEsy76M6xOnju3w4FtHHrgx47Vw7tNw8i98eZRC1UYOhPzA7eL3wfItcOQX/MFZRApqWooqVM3/n73zDo+i3P74Z7Zl00hCS+gdpBcpFgQUKWLBrtfey9Wr/q79Wq/da7leu9ixYUcUFFCaAiK9twChpZCQ3rfM74+zSbbMbEl2QwL7eZ55CLszs7PJ7rzve873fE9hI7y4Sed+Y28879gNG+Cvv/THiU6dYNUqabEWqlNXfLy0WHnnnWgO5Ujy11/+XTfGjAlduOFOQgL8+isMHhzCQfZyWH4tzB0JeX8GFm5446ySftLrH4EfukHO4tCOjxIlSsTQWotaLOEfB7RapBwJa+Lf9/5eW40OMDB1YO3Pg1IH1f7sUB38vjd0OyqHdzuQEKh26PQTPpqoPOT7R7emwrHw3qM0aQ4UH/D4DiZYZCLdNr5trQDLarKKyCMEMjKkbV2/fjI/P+UUcU6r8tV5ASLiMrosss0GM8nW5Nrnkq3JWEyS2VJRKavWn48dLDlY+35q3guI84biSgJYTdaA7Vfc+XXPr/KeCjNqBSZRmi/V1dJasbxc+/lhw8Tpr3NnjSfDlexrEklDL/HGkbKojxKlMdCbp5oTG811JlVHs+t0huYC1BD0CqOrqhpZXJ6dLfPiULZAhHq+7OzIv8/mhqrCkvNk3eKvVYoxTvJD52XD0BchdZx8l0zxYEmu2wwWKUrvegWMXyDuEqmnBXktR8AOZv932m2UYtvDKd9FRrjRjDha0vNRgiSUQcFiOUp60rc4LrT9i7c364CO0RCal79WYfdRgb0CFk6UBE6oKCY4/n8wfiGkDGk80YY3RqsMwv0fhLPTIXlQ4GOiRIkSNpKTtcfBgoJGEDiadars6mt/Vw8efVQ/2NuqlST+27Wrf8VCQgJcdhm89Vb9rzFKw3j+eX1Xtnbt4Mcfg3NU8UdCgjhwtAimcLS6QHp87pvhEl42YCLqKIOKg7DojPqfI0qUKGFFS0BhikDs1mBoGuKNDYc21P5sNVkZ2LZOvDGg7QCspjpx9sZDG0M6d0NbKqioOI+Kxb4fKnN8qz6tbSHEYocokUVRlMmKomxXFCVdURQfTzZFeNX1/AZFUYYFOlZRlIsURdmsKIpTUZThXud70LX/dkVRJkX23Wmzp3APlXbJGrWIaYHiumG1iW+DwymBc4NiYH9xcOINmw2uuw769oVXX4WtW0XI8ccfcNNNkJYGCxf6Hneo7FCtQMNoMPqIN2qEHTHGGHLL9e85+wr31f6cFFNXxZgSm1IrRjEajOSUBVeRmV+RX+tMZDFaWH5geVDHRWm6fPON9rry1FMhPR0WLZJWjtu2wdy5sg6pxV/CUYumnDSMtk2JciyhlwhWNFTWESIlxbedbw3+3EfDid5aJz//KC+ojRIc+7+FwyulCEmPpH5w1mbJD1mSRLQRCINRckqtRsDYWTD8zcCON85qX9fCSKN3nxj2klz/MU50lnCMEcrY6HAcJdWwib1cvW793ATdKdsjCYNGtKUPJxZTaGqMo1K8oaqw/GppgROqajCmDYz7WUQ/TWWQMMWDMRYmLoO/bpF2KlGiRIk4ycliZehNYWFkkk0emJO1H68ujPALC7t2SeBML6/zzTeyEG7o7yEhAa64An77rWHniRI62dkwZ47+3/izz8AaBtMng0H+zgFFOuUHYf4pIrhwhlFE25C2aVGiRAkrWgKKSLTp1HLeqKxs3ABpblmuR6V6jDGGXi171f6/V8texBhjahO45bZyckpzSE0IrjJ4fc76Bl9jRmEG3Vt2b/B5Ik1RkSShlywRMWBGhlRxG40iMBwxQiq2Tz5ZnJ5q//aVOb5jgLVttNK5CaEoihF4A5gAHABWKooyS1XVLW67nQH0cm2jgLeAUQGO3QScD7zj9Xr9gEuB/kB74FdFUXqrauOWGu48vLP255axdb2j2sS1qW0/YnPaOFB8IOC5CgrgjDNg40btKuISl2nFmWfC//4HN95Y91xGYQY2hwSEKm2VfL/te9ZmrwVgd8Hu2tZMdqedvYV76ZrcVfMaMksya392F4CkWFNqxSgAOaXBiTeW7luK1WSl2lGNzWlj4Z6FTOwxMahjozRNnnsOSr3qqi65BD74wNfh79RTYe1aGD1ahB1HNwEmJt+l+bGhN8BlR6BKOkqUYPFuE1SDYqKx6slbtpR28Vrj4+HD0KZN5K9Bz8X08OGjJO8Wpf7Yy2Hlrf7dZrtcBqOmgSG2/lWEpnjofhW0PQUWToKKTO39qgsav52XVnul+C7QYWq0tRhR8cYxRyjfcZstMsG0Rie+KxhDEG/kLZf9mymtE/NC2r+xbMIalZ1vQeac0BM2iT3h9MVgad30xDuKQQbbkW/LdUaJEiXiJCdLcsCboiJ99X7YsOj0bCk/GOEXFl58UVu4AnDzzTB8ePh+B/Hx8N574TlXlOD55BP956ZOlWRYuPrAxsbKOXUpzYC5o6A6X9syMUqUKEcFWgHKSAgqtMQbjdLyzI212WuJMcXUJmLtTju9W/Wufb5Xq17Y3Pr7Wk1W1mavZXLPyUGdf/OhzQ2+xvU565u0eCMzUxJ+770ngffSUl/BYXExzJolog6DQaq1n34aLrgAjOUagUlrqtgJR2kqjATSVVXdDaAoygxgKuAu3pgKTFdVVQX+VBQlWVGUdkBXvWNVVd3qesz79aYCM1RVrQL2KIqS7rqGRrV2yCjKqP25TVxd5ijeEl/bZqTCVsHeQj+97RBB3MSJ0upQa83iTkUF3HWXp3hjwZ4Ftfeoamc1n2zQnhxWOapYsGcBY7uO1Xze3VGjVWyr2p9TYlNqxSEOpyNo541f9/xa2yrFqTr5Of1nnj392aCOjdL0OHgQduzwfGzIEHj/fe2kptkMrVvLff24EI2UmzyKAQ/BRqB1j65wAxrkUBglSmOgK94w4OFAEwp+BU2+pKybjMH+BZDs81x6euPcY/QEInl5jVAUFqVps/EJ/62xu14OI6eFp3WIKR5a9IGJy+HHPuDUSAgeCfGGFn3uiIrtXUTbphxjhBqE10vcNCviu4S2f0UWVB2OzLU0Au2TddRzOuzeHaELOVLYy2D9g/5Vi1ok9oJJKyEmtekJN9wxxUPfu4/0VUSJckxgtWonmqqqGmF8jGmt/XjRFnBGtsJGVcVZQ+s9JiaKsCMhzN2kwuHwECU0vvlGX8D56qvh/xvrtl+xV8DCyVCdFxVuRIlylKMlqnBEYEhLTPQtQigsbNzqtlWZqyi3ldf+v8pRReekzrX/79SiE9VurTrLbeWszlwd9Pl35u8MvFMAtuZtbfA5IkFlJdx6K/ToAe+8I0nn4mL/LV0rKsT+Oj0drr8eOnWCrEyN4g1rarMu1DgK6QC49wY54HosmH2CObY+rxdxtuVuq/15c+5mBrw5oHZzupJdKipz0uf4Pc9jj8GWLYGFGzWUl3v+P9i2LIH2zSuvKyBKsiZRWFlIYWUhTtVZK1KrsFXUtkIJxLxd82rbrYDcq2pcQKI0P376yTNBabHAt9+KuFsPo1ESns8/H/nra1y80jARXtdHiXJE0Uu+Ou3UW3wUgnADICW+QPe59ev9zy3DRVqa9uOHDzdCUViUpkvZftjxqn7hcdsx4RNu1GAwgzUNet6o/f1UnRKfO9K0O6Np5+Yakah44xgjRaeQV49gF4FNmsQeod94sufrK0SbOG1a5GIyBv+HW7eucSYrjcaON1wTwRAwJcJp8+VfQzNQ9pnCnFGLEuVYQHVCeSaU7ILi7VC6GypyApb86lkcRrxlboyOPL9sNzjKtZ8LE1sO9vMJ7tZw222RSX6Fy+EhSnBUVsr4r8Xpp4c+X2wQf90M5fuCm3cZY6HdRBjwCAx7BYY8Dz1vhoSmWzkeJUqUOvTEG+F230hO1nbeaExXyd/3/o7dbU2SGp+K0W2dYTQYSUuoi+banDaW7F0S9PkzCjMafI3p+U3Pj373bqnI/vhjGavqE48oLYWsLPhjiYYNrzGMAdAo4UBrVul9R9DbJ5hj6/N6KIpyk6IoqxRFWZWbmxvglKHhdDqpdNSpZ4uritmcu7l2c7h1cNmWt03rFAAsWwYvv+wryAiFrJKsBu/rdDopqKxLjn2z5RtSX0wl9cVU2r3UrlaE4cTJd1u/C/g6ZdVl7MrfBUCsSbL7VpOVlZkrg75WH0p2QcbnkP4u7PkMinc2bh+tY5xPPxVxXQ3XXgtt2wZ2ho6Ph5tuiuy1NTqK15uOCtejHM3oiTfUCEz+dUiJL8Cpat9sdu70vDdFig46EtGKiuhQdEyz+0P9GJi5BYyZGV7hRg1GCyT2AYOOcsheHP7XDAVjrORyowDRtinHHKH28jp4EHr1Crxfk8bcQuznqw4Ff0zmz9DxfLC0iNx1RYhWiYeJMVVjdwSXCdu6VSYriYkRvrDGwF4Gm58OMbGpwCnfQkzb5iHciBIlSmBUFfJXw8FZkPcnFO+Qnn4Gk2sBqQBqneI/riO0OA5anwQdp0JS/9qsT0KCVHt6s2cPdAnR2CkkrK0BI+BVjVOaIYvdCPLjmrM0K6GtVrj/fj8OClGaDcuWyd9TKyn2r3814t/4wI+w/9vAbc6S+sPxr0CbU8BRKSLGmjHbVibfV1sxbHlORJzRQGiUKE0SLfFERQSKe5KTfR8rLBQr9sZibfZaj//3bOnb9rBXy14cKD6ge4w/9hb5b6fQWOcIJ/Pnw/nnSzI6HMUFBjTEG03BCjiKOweATm7/7wh4W4nq7WMJ4tj6vB6qqk4DpgEMHz48rKmV7Ye3B71vpV3bIk1VxZ2moffPrNLgxRuZpdq/2gMlBzz+71AdOHQsldzvd3r8eeBPYs2x2KpsdE/pTnp+OpX2ShZnLGZ059FBXy+OKtjxGmx5AewloJhkDaUYZZ5oShBH0z53Rd14Ikh5Oaz00t08/HDwDn9HRStvdxQjHnqxUAvPokRpTniLlWpQbY1WMJsSX4DNoT33S0+PjAOgN23aSLGSVuylpARatoz8NURpYqgqpL8DTh1XscHPgiGC9sRx7SQ+rvX5r8qH2PaRe+1AxLYDR3W0zaWLqHjjGKNt29D23779KBBvACQPhJzfgt//0KJma8/TOiEPoyH4BcCOHY0zWWkUdrwZ+uJn0JPQ5iQw+fFsjBIlSvMgf60E6Q7MBKdNgnaqW+DeoRHEB3HhKN0N2b/B5mfAnAidLoQ+/yApqQ+ZGrHKLVtg3LhIvAkXlmQZh7yT2mUZEU88fLn8Uqo01hAXX3wUBtCOUX7+WbvKpGtXOOGEwJVwYcFWAsuv8i+4NLcQh40ul0hlgMHoG2A3u5QmpjgY9BQcdzesuA6yf43YpUeJ0qSpLoDCjVCwAYo2S9JKVaX1XlJfWRclDwJriAvDMGA2+zpi5OeH/3VSUnzXNyUljddXuqiyiPwKzzc2KHWQz36D0wazMGNh7f8LKwspqCggJTaw/VGw7Qf8sa9wX4PPES7++APOPTc4F4H27UWgY7fDgQP6xxgUjcSAXiJBj6B7qxvgsqNlUd2orAR6KYrSDTgIXApc5rXPLOB2RVFmAKOAIlVVsxRFyQ3iWG9mAZ8rivIy0B7oBfwVtncTBGuy1wS9r1N14nQ6MXhNzH79FXbt8t0/LQ3++U+46ioR4m7bBi+8AF99pX1+93Yngcgt03Yg2ZobfPul0urSgPsszFhIWXUZJoOJEzueyIHiAxRVFfFz+s88NOahIC92Gfx+gQh79eaZjgrY+CRsfRlO+QbanhL0+4gSPOvWSVuAmrXl2LGQlBT88UedO6MpzrMQQ9WJT0SJcjSg57xRdRjUaiDyvXNT4guotmvfSHbtapy2Ja1a6Ys3Cguj4o1jksN/ga1I+7mkftD9msjmqWJao21Gh3w/jySKiXq3VYIQ1m41NO01XFS8cYzRPkTh1Lp1cMYZR0Gyps1oEWQEW61ceUi2+M6B921idGu7B1UN3tN+xw6pvm322Mtg81OhuW60HA7H3SXB7ChRojRfDq+CdfdD3nIRbNR3olejenaUQ/rbsPt9kpO1S9q2bRM774jdP83JrkmrFxUH9e3twkBpZTybD/bXfO6yy44Sl6YozJqlLdycMqURW6nteB2cfvzwrWlw+hKI7wTGIL9o5gTZxvwAa/4p1QxRohwLVObB3i/EeaZst7SGcFaJU407hhj5PjkqRbzR61bodqU4UDUCycm+4rD8/PCLKmoS++6oqiSP9NqhhZN12etqK8cB4sxx9G/jO7b2a92POHMc5bby2v3WZa/j1G6nBnyNkqqSBl9nbnl420HUl1274Mwz/Qs3Jk6Eu+6CE0+UQLvNle+yWiEjA374QVpIuLe1szk1PljOEBNlQQf/Qhg8K7Ige4GIDHN+g8psKUBQDOIG0PJ46fWcOlbWq5HoV9dEUFXVrijK7cBcxHLuA1VVNyuKcovr+beBOcAUIB0oB671dyyAoijnAa8BbYDZiqKsU1V1kuvcXwFbADtwm6pG2NLOi82HNoe0//7i/XRJ9rT7e/RRXxHuiBHwyy8i2qhJRg0fDu+/D5dcIvN4b3F2mS14v3i9e04o7ZeqHYH7IP2882ccqoMkSxLju41n+obpAKzOWo3D6fBoP6XJ/pmw7LLArm4AjjLZFk6GSxrBO/8YZN26uvs1wB13HOMujqZEz4Iz73lalChHE3qt6ipzGs15w2yyEx9TRkmlr7N6dnbj5Ltat9Z/nX37oHu0A+yxR/o0/fv/wMciGvMFwNJK/ztYGbwrW0Swl4LSgILFkIQb0CChSCMQcfGGoiiTgf8hi6n3VFV9zut5xfX8FGQhdo2qqmv8HasoSkvgS6ArkAFcrKpqgaIoE4DnEPvEauBeVVUXRPo9NifattVX+2mxbZssCls0v+4hnrQcJgl6Wwh9m7LmQvfrI1d+ak2txw0lMD1T06moDj4qefjwUeK8sesDcIb4Rob+BwxRx40oUZotVYfhz2vFMcNRQeA21yGgOsDhoFUr7af37ImweCOuo3Z1qOqE6sMyhgRLCOPNzuxexFoqsFV4VieYzTBmTPAvGSVCqKq4rxRvk3ZAhRugbI/LZUYVt5aY1pA8GFr0gcRe0nLEzU3M6YTdu7VPf/75jRRQtZdLixM9wWVCd5jwhywq6+OEZoqDYS9BbBps/HfDrjVKlKZMZS6suRv2fSXVbTXfKadOJY+zqk6oWL4fNj4hW9p4GPdTxC+3ZUvf3s6HD4e/sjYpSXu9W1TUOOKN1VmrPdodmA1merfq7bNfr1a9MLu5aVXYK1iTtSYo8UYwSdBA1IhGjiR2O0yeDKU6BfknnggffSRFKO42+7FuS7jeveEf/4Dbb4fPPoM77xQhiM2uEfjzJxqMNKV7YMNjsO9rsSq2e71p1SFVeDkLIHepOK3FdYQhz0OHs49aEYeqqnMQgYb7Y2+7/awCtwV7rOvx74HvdY55Gni6AZfcIEIROwCsylzlId7Yvx/WenVY6t0bFizQbkWRkCDfsW+/hbPO8nyuyq5j161BpU6SIaMwI+hzOALoZKod1WzK3VT78yldTiHWFEu1oxqzwcyGnA0MbTdU/wQH5wQv3PC4sCN/LzxaWb7cs73P2LGN5PDXVDHFebZ3LA/cSihKlGaLtQ2Ua7Toq8xBt+o/AnRqtZ8tOgVKmZniPhpJWrXyXf/UsHq1xNmO6ftiM6KgooDNhzYzuksIbdy0yJytXWBuiof2Z9e1CI4UMa31nZ+Kd0p+LdLXoEdFpuvaovk6iLB4Q1EUI/AGMAHpLblSUZRZqqpucdvtDMSqsBdigfgWMCrAsQ8Av6mq+pyiKA+4/n8/kAecrapqpqIoAxAFfodIvsfmRrdu+j3Otdi5U3+AaVakDA69nUbmz9D5ErBESLlyfohWt58HN7GJi6mgRWwx+WU6GUcN9u6Ffv1Cu5wmx94ZUjURLC2HQ6tR0RlSlCjNldxlsPhscd3R6xMIIlxIGw8t+kHKUIhrL44WThuU74OCtVC0Raofqwt8DtdrHbZ7d4RvHwnd9BMMZftCE2/ojTca40p6Tk9NDcwpp8jcITY6f258nDbI/QP2fQP7v5V2IwazKPX1PvsHZtZVuqh2SD0VulwG7c8gM7clZrNvVbrRKEmyRmGnnzZnpkQYvxBi2jZswWiKh773QqlGwChKlOaO6oTtr8GGh+S75G8c9IfTlYzLmhu+a/NDq1ba7UzCXfVmNoubh/ead/9+aNcuvK+lxRt/veEhriiqKmLSp5M097W5OUFUO6p5/a/Xufuku/2e3+l0ooZBsGoL1YUiArzxBmRlabs+3XsvPP54cIKbGjHt5ZfD6aeLk5Rmj/PqfAmW6ll5RwJ7Bay8FfZ+KWOyag9c5FUjtCreBssuFzeqU76GlCGNccVRIsjuAh0FrQ6bczdzARfU/v/bbz3XIDEx8NNP/ufocXGSNL/lFs/HA4kpPPbVKZTZX7w/6HMAlFeXE2fR/lKvzlyN1WSl2lGNoii0T2xP3zZ9+fPAn9icNpbsXaIv3ijbD0sv9RVuxHeF3rdDhzNFFFydL7G+Ha9J28woEWXFirqfW7bUFhgdUygGWcfVrPNLdzX+mBQlSmMRq2P/XpkT8VbA7vRpt11XvLFtW+OIN/TcTTdtkqLpqMNt8+Cyby/jl12/sPLGlQxvP7x+J7GX6bcm6Xhe4wgXYlqCXiFA8RbJrxmOYCV/3p/QbuKRe/0mRKSzliOBdFVVd6uqWg3MAKZ67TMVmK4KfwLJiqK0C3DsVOBj188fA+cCqKq6VlXVms70mwGroiiN0L2q+dC7d2hijJ07j5KWGnGdQ58MZ/0Sek/cJkL3tqEtQn/8MXhBT5PEUQ35q0M7ZsjzYDgaPtxRohyD7PsGFpwuwTethJUhBnr9HaZsgqkZMOIt6P8gdJgiQe/kAdByKHScCv0fgZHvwnlZMHmV2Me7jRe9e2sHQ/fsiXD1rrWdvnijcGPEXnZndk/KNdybRoxonGrlKG7YK2Db/6Rn4+Kp0sqnMkeqA21F/pO1qgPsJbI5KiBzDqy8Bb5vT8ZPz2hWuQ8d6ivoiAiOStj0tH6V4wkfQkyb8Cj9TfEw4o2GnydKlKaErRQWToL1DwUWMBrjpHI/rpMIo/RQG+PLL4kbrTWHt/1/ONAas7ZvD//raLG3yFc0ZnPaNDdv9hXvC3j+XQW7wnKdgIdDSGOTlwcPP6z993/tNWkNEercIzYWOnWCP/8EU2yy7w6VhxrXpr50D/w8WNxxnJX1+67ZS6E0HeadHP7ri9LoHCgOrdJ+x+EdHv//8ENPJ4N//EOcaQKJ4BIS4IUX6v5vD7G4SUXFqZF9Olh8MKTzeL8fdxbvXVx7T+rTqg+KonBCxxNQUKi0VzIn3cdkpY7lV3kKNwwWGPAYnLkZ+twBLY6TKvAWfUTMMWUjDHoieGtyexlk/gK7PoQ9n0L+mqOk0q3+5OfDjBnw9NPw1FPwySdw6JDnPnvdhsPBgz0/u8cs7u0gK7KirVOaKYqiTFYUZbuiKOmuwmLv5xVFUV51Pb9BUZRhgY5VFKWloijzFUXZ6fo3xfX4BEVRViuKstH172mN8y4biF4r+qo8MDZeum5gpw26hVe//SaOupGkdWv9nMu2bUeJG/oxwLL9y/hl1y8AXPndlbqi1oAUbhYXJi26XArmRhBNGMz6DrdFWwmrq3V92POJFK1Fibh4owPgLsM+gK8Tht4+/o5NVVU1C8D1b1uN174AWKuqqk80S1GUmxRFWaUoyqrc3KbR57Wx6NHDfy9ZbwoKfPtiNksUBdqEaGnkqIA9H+sr0ZowAzuFltj79ttm/nc+vCK0iV+LPtA66roRJUqzJGeRb3CuFkVEG+dlikArub8ER8wt9MV4BiNYkuQe0vJ4GP4GnLtfJs2IY5VWoruiQuzXI4bBKFZ2WuT+Icm7CLB+72DsTt8qiMGDpZI5SiPgdMC2V+D79pKcrc4XEUZD+8LaS8FZxZ4NOzUDBH36NOz0QZM1X9siEqDDOdB+MpjCWGkQ6X6hUaI0JlX5MO8EOPSHtuOcwSIVO2N/gvOy4aJCOGsrnLkFLsyDC/LgtN+g6xUibmpkWrTQDlAW+BpfNRitCrbNmyMvWM8tyw2pmt0bp+okp9R/q7MNORvqfX5vtuRuCbxThHjoIe2/x513wrXX1r9C22iUY8+7rIO4rblTeSh0R876krMI5gyW6v5Q2zhoEW3tcFRQVBXaAsLdqSMnx1OEZrGIACrYlnfuAo89BXtCug6AgyW+Qo3MkkyNPfXZflhfRffzzp9rXYtGdhgJwPHtjifeIm9w+f7lqFqCibwVcPgvN3GUAmO+h373SoLEu8LbYJLHj7sbxv7ov2irYAP8eip80xKWXgKr/yFOOr+OhW9SYPX/HXMJhq1bxea/XTu46SYR2j36KPz979C5MwwfLq0ASks9q82HDj1KigMbitFtnVORKS6LUZoVbm7xZwD9gL8piuLtZ+3uNH8T4jQf6Ngap/lewG+u/0Od0/xA4Grgkwi9tfAS18l3HgYS17A33pymd7udumLg5csjnw/RW/+AjOlRd9umj91p56rvrwJAQWF/8X7eWvVW/U5WuEFiflqkDK7nFdYDk45IpGRHnYvvkWLvjPCsnY4CIp251Orz4D3T1tsnmGO1X1RR+gPPAzdrPa+q6jRVVYerqjq8TZs2wZzyqMFqheTk0I5ZvDgil9L4dDwn9JvP9lcbrRItnJzcZ2lIPetXrWqkattIkTUvtIlfavMQKUc5ckRV9E2Uws3SKkVrEhfTGib8IaKNmJZgrmfE35wIse3EjWPMLLp3119orVpVv5cImrhO2o/nryKw33b92JbZV/PxvtoPNwmW7lvK3PTGsfyPOGV7Ye5wWP8w2Ar9twMzWiGpvzjIdLsaul8roqNWo8DSUvew3TmdNYW83bs3krvK3i9FjOKDAse/Ev6E8pHq1RklSrhx2mHhZCjZWdfupAbFIOLFC3LhxI/EHj42VRJWpgQZEw0WiGkFaaeJI835h2DAI40qcFIU7SRjenr4XyspyfexPXsiX/U7c9vMBp/j+23f+31+W962Br9GDRtzIufm5Y+qKvj0U1/xRs+e8MwzwSej9TAYICapra/AvzKHRqkmO7wKFp3pEl8GI+ZpvN7vUY4sVfbQskT7iurceJYvlzYpNVx8sdxXg8U9QbQ9L3QrIi3XjILK0NR36fnaN3yn6mRVliyu4s3xjGg/AoBBqYNQXN8Pp+rUdu5Ye6/n+nDQk9B2TOA5pSkO2pwEg5/TuCAbrLzdJZhcLI6ItmJx4LCXymYrgp1vww9d4aAfV5CjBFUV0d2wYbB0qdy/S0pEoKGqItaoqoI1a6Tl5k03eX5eTz45Kt4APOPSFZlE7//NkqjTfDBY2+qvMypCE/41hB5td+m6U61eHXnxhKJI6xQtjpqi6aOcV/58hazSLAAURaHMVsYDvz4QUHCvScEanSKMmNDaYzcUS4r2444KqC5svOswacTuVTuse1DmWqHSmL/DRiDS4o0DgHvmoSPgfXfW28ffsTmuAQ/Xv7XGbIqidAS+B65SVTV8fqJHEd27h7b/F19AcXFkrqVRST019GNKdkDR5vBfS4Q5qdeykPZXVfjhh2Zs1ZU9LzSRTbszjki1YZTmQVRF30RRVen5bdeY5Ma0gTPWinNGfUUb3pgTIO10unTRT/T89luEF1qJvbUfL9oSsbZPBWXaE/jOOo6XR5odh3dw6sencsZnZ7DiwIrAB4QRp+oMOQDvl5xFMHuQtMXRE2206AsDHoWztsFFJTBxGZzwMQx/HY5/FUa8A6f+Iu4zF+TBCR9Au8keFYVbDvbV7Lnarx+YNApjworqhMwftZ/rOFXfbSZKlCjixFO0xbelVnxXmLJZxIvmFsFZrZpbSNKq731wzi5IbrwqnxYal7dmjX4v6PrSrp3vY3v2RN7lfv7u+Q0+x2+7f/P7fHpB+NQu/qrgI8ns2dptHqZN03Y8qw+m+LbazhuhtlMNlfJMWDjRv1NGQg9JME9eBZdUwGVO+Jtd3N9O/Bg6nE00oXf0YXfaUUMUD7mLI/78UxLkNdxzj/Y9NRj2FIbuvKElvCizhdb3SqutFMCmQ5swuOarRoORQamDADiu9XFU2OsWY7/v+93zwPJMcd2o+b2mDIHj/k87GaCFKR563+b5mKNaCgZ2f+AShfj5mzkrxSXvjwuDe71miqrCzTfDK69IiwF/Y7aqyvr5u+881xbHHx/xy2weuH82K7JEXBuludEkneahibnNW1PF6UiLwysb7TJ6pqXrtkaprITdoXWerxe9dUJ70DivH6X+HCw+yGOLHqPc5jmvr3ZU8/c5fw/9hBVZ2o8n9mpct4mEbvrPlei3uPNLfYQTevO13R9A9kJpJx0K52fDZarv1kyJtHhjJdBLUZRuiqJYgEuBWV77zAKuclUxnwAUuQYof8fOQhJcuP79AUBRlGRgNvCgqqpLI/i+mjUnnxxat4iff/ZUSzdbEnv72iUGw5b/iMK+GdGn3faQA5NffukZCGhWlGkHAHRpG2ILnSjHGlEVfVPkwPfS79s7eGaMhfELIUajurKhmGKxWLSrdwFWrIhwBW9SP+0Eg+qQyusIYHNoj5ON4sgQIgUVBYz/eDw2l9XsGZ+dwf6i/QGOCg+qqnLx1xcT90wcs3fMbvgJ8/5yVegWa1fothwurQ4mr4L+/5L2XwaTJGAtSSI2MieApQVYkuW7ENMKul4Fo7+EqfvEnUMxkleqLZDo1avhbyMgh1fqZ06HPCvON1HqTdQ16ijm0BLY8bqvsCt5IJyxBhJ71k+8aE4Qt6mJf4TnOoNAywVy61YoCy3/F5B+3rJbJDga6arfFQcbLiQMdI69hSGuffxQn9YJ4eCtt6Ri251Ro2DEiDAKCWNT8Zk3VhwU56pIoTol6avXRiGuI4z+CqZshH73i/C45noUozzf7So46TMRVnU4O3LXGqXR2ZYbumtOpb0u47R4cV3S3GxumDNeRlFG6McU+h5jD7ENkV6blcUZi2vPVW4rp3/b/gBYjBY6JEpes8xWxs/pP3seePBHT5HWkOdC/46771/zHT60JLQkylFu733nnfD556G14a6q8pz2H2PG1/q4i2yrcusXp45ypGmSTvPQxNzmrRrzsBryljda65RWCYf9ulQtXBh+Ebk3w4bpP7d8eeRfv9njdEDpHsicCxmfw64Pxflq+6vScnjHm5D+Huz5BPZ9C/lrw9Zq+uafbq5t6QbUtm+zOW38kv4LizIWhXZCvfmCOaHhrZJDoeXx6ArF89fU75z1EU4MegKMOgXWyy6Dymzf4pVjiIjW16mqalcU5XZgLmAEPlBVdbOiKLe4nn8bmANMAdKBcuBaf8e6Tv0c8JWiKNcD+4CLXI/fDvQEHlEU5RHXYxNVVa115ogivQk/+CB4N43CQti06ShQSSsKtB0HB38I7bgDM0GdFokrihgGg8rQoWJlGCwLFoSvyqlRUZ1QdTj4/RO6R5XtUQKhpYQfFcQ+eir6mmM9VPSKooSsoj9mUVVYdae268aAR0QxbIzc97pzZ8jP93189eoIixoSuomtqlaLidzfIamv/x7N9cDu1J4a6tlMHilsDhtTPp/CoXKZ4ikoFFcVc9r001h781oSLGFyYNFAVVVun3M7s7bPwqk6ufibi5l16SzGdx9fvxMWb4eFE7QrdI1WOP516HopGGJDU9+CtAwxuCrxh78G/e6n+intDGl9KzdD4sD32ovVxF4Q10TtXZoJbs5PE5CxZ6WiKLNUVd3itpu7a9QoxDVqVIBja1yjnnOJOh4A7qfONSpTUZQByJrNu+IsSrhYe6/vPcLSUkRd5qSGjQWKIfgK5TCQmgqbvYwNt28PvwNg795ig+wusjx8OPKtIvUSk6FQY8urx4HiAz6PmQwmrCb/CcsKWwUOL4Hg/uLGET2643TC77/7Pn7zzWEW18S0lXZD7jgqxX0jLkK3q4wvoGS7titk6mlwyrdS6R8oWWdOlO3kL2D3h7D6/5plO9conuSW52JQDDhdwXmryUqrWF8v9aySLJyuFomqqroSBQob3bocDRgg97f6xnAOFh8MyzHOEBMNeq/7n6X/qRWq2J12kp6rU8873HrD/7DNK56X8XmdsNFolXYpoY6J7vtveQFyl/rOV42x4ubb4jhwVsGhP6BwfWiv00yZMwfef99XuBEfDxMmwIknyhJl5UqYOxeKiur2cU9ImqMaBcF9/FGdstbXs6+3prrafUVpYjTEad7i59gcRVHaueKFzd9p3poqLai0KFyv/1yYURTo0AF26fzWFi+Gyy+PXDzEboeBAyV2qCWAmzcPLrtMv2jsmKMyF3IWQt4KKFwrhWsV2ZLLMZil2ElVAadL7KACBhnLFQO1XgWOclnjJnSFpAFSEJU6DpIHBd1zbt6ueSzMWFgrLk2wJNA6rnWtmLXcVs7VM69m5z92Ygk2Jq0nevV2CwyF79LqMVYo8vvRijcf/kuE6I1RXNXtatj6khRrehey2Uulfd3pS6StuKkJVhVGmEibI6Oq6hxEoOH+2NtuP6vAbd7H6R3revww4BMhV1X1KeCpBl7yUc+JJ4Zu8/7ZZ6Lqb4qVtyHR+ULI+S20nkmqXdR8x/1fZKt0wszEifDXX2ALci5UXS0LrbPPbnpJOr9U5ckAF2wwK65zo00QozRbjrSKfqLO8zchLVrofKR6WKSlQc4RCB60A55BlrnuWNOgz50Rn8D17g3r1vk+XlYGWVnQpUuEXji+m37wMXcpdL087JNpg6IdgG1KlQCqqnLTjzexIXsD1Y5qFBQMBgN2p50DxQe44KsL+Pnyn2utl8PNfb/ex0frP8LmtKGgUG4r55wZ5/DL5b9wSpdTQjuZ0w4LJ2lX6FpawoQ/IL5LeD7j5kRI7I1NR9Qe8ZYpIFWMWuN1h3OI2sM3mFrnJwBFUWqcn9zFG7WuUcCfiqLUuEZ19XPsVGCc6/iPgUXA/aqqrnU7b61rVFR8GAHy/oLCTb6Pn/yFCLMidK+LFIMGiWjcnR07wu+I0b27JDW9HbLWrxcnykhQWl0achW6FnanneLKYlpYtaPIrWJbsRNPB67xXcdz1ZCr/J731RWv+rh6aCWOI82ePTLmuMckTCa46KIwj0XWNtLSwJvCDZERb9jLYbWO2LjrFTDy7dBbd5riofu1EmhecHp4rjPKEaOoqogEcwLF1VJJdcvwW/jvpP/67Hfc68fVtjQyG80UVBZgrG5JtVvh4fDhDfu+ZJdmh3xMZqlnbjK/XEPdHoCcMt+1pNPp5ECJpyhN717qUB2sOLCCUR1d9RFFboqW1PHS8sQYG/J1AVCSDpv+7SncUEzQ924pGHDaJSaoOmSrPAR/XgO5jede1diUlsJVV/kmHG++GV54QdaIiYki3igulljiE0/ASy+JKNN9Ddms4oyRxNuqvjJXX7xxvtf39PPoeqmJUOsWDxxE3OIv89pnFnC7a101CpfTvKIouX6OrXGaf46jwWne2lY//l6wAUz1vFfXg5499cUby5ZFVlxWWgrHHaf/GkuWRN4ZsEmjqlCwFnZ/LG5aFQfBEOMrKnDYIVSxv60QCtbJtu8bca+9WMcdz4tKeyXXzLzGo11KnDmO/03+H5d/dzml1ZJbzCvP4z9L/8PDYx4O7pr05igOnd4+QV1sfeL0eikM4NCiholJQsFogVN/hjmDtYUklYfg52Fw4kfQfkroa6lmTvOK9EQJC2lpoasJZ3k3u2mudDi7flY7O17TtjFvwkyZEnq7m8ceC13Yc8RxVITWt/gYVOlFCZmGqOj9HZvjSpJRHxV9k7A/PBLCDYABaEtgOp2v80R46d9fP9j0RyRjdQld9ces/JVBq8VDwWzUXlwHKwRsDP634n98teUryl02m7GmWBJc7QIq7ZUs3beU++bfF5HXfnzR47y58k2ffpfltnLO+OwM/jr4V2gn3PkWVObh2w4oTtoBJXQP77hlMMp2pCjVaeja9bJGDd4cpTTJ3stNqu9yc2Xby74VwK1GQZuTw98urBHo39+3ICAvD4+kZDjo1k3bzWPBgsi5b/y4/cewnWvWdv0FeF5Fnsf/jYqRsV3HctnAy/xuJ3Q8wedcWonUSLNxo++8qnfvCAhFjVYwaETD85ZFRsy/9QVtd6m2Y2HkO/UPNprixdr4xE8adn1Rjjj7i/ZT5ZCh0mQw0T6hveZ+bePrhlqrycr+ov1kZXkmd045RZwP6ou7Y4aCQoo1hbbxbT22ZGsyih9x7Za8LbrP6VFS5RuYX5CxQGNPfaZvmC4/2Ms8BdBdLgFTA4Tt6x7wXHsZrTD+VxFumOKlVaExRubm5kRI7AGn/gI9bqj/azZx3n7bUwSpKPDhh/DiiyLaSEqqMwZs0UI+k48+CjNnehoGNopIvLkQ18lzbKrw77YVpemhqqodcX+fC2wFvqpxmq9xm0eKkXcjTvPvAn/3d6zrmOeACYqi7EQcEZ9zPe7uNL/OtWmtyZoWBrN83rWwl0B1QejntKbW61IG+TFb2L9f1iKRwmoV8UalTm4+Px8Ohm6G1fxx2qX9yY+9YP4psPMNKNsj47B7Ej+mjcyle94CI96BSX/BeZlwQS5cWAgXFcOFh+H8HDh7J5zyPfR/CDqeK+2Ga0QIzsqQirmfWvIURVV1VlJx5jgeOuUhzup9Fi1jW9Y+Xm4r59nfn9VsLaeJ3nqg/ICIVhoTLfffmmuxFTbedSR0k3bPusKWcvjjYlh4hjgX24obt8XMESQ6fTpGOfHE0AQZu3ZJzq5bt8D7NmksSRLszNXwafVHRRZsfRH63tNsFF7HHx+6cnTDBrGwPf30ZqSKV52hFesazDRadW+9bKuCxQCXNS9BUTMiqqJvagwCtOawnc5rlHtyjx6SaPLuzQ7w229wzjkSvAo7/mwmi7eDoyrsVvdWi/aK8tAhSGg8V31d5qbP5V+//YsKu0QR483xPH3a03RK6sRV319Fma2MMlsZb616i4GpA7l68NVhe+0Xlr7AC8teqBVuxJpiuWLQFXy+8fPa1z19+uksuXYJQ9KGBD5hdRGsf6jO6tmdkW9JK5EIJGb17LUjLtBxVItbljeKCZIHRvjFjwmapGuUqqrTgGkAw4cPj7za7mjk0GJ8/hwDHtFOSh8JbMViZeusBlSxtLWmybpLgz59tNcoy5fDpEnhu6wuXXxdNwD+/FMq4JKTw/daNczdNTds55q3ax5XDL5C87ncMk8hVIwphtZxrQOeMy0hDZNiwu7mgBSoRUsk2LhR3MvcGRipYSChOxR5OdcUrBeXDJ3PqAehWNZve8U3CGpOgjHfN1yIaYqH9mc27BxRjji7C3fXijdijDEeIg132ifWiToUFA4UHyAua7BHMvzEExt2LXHmus9kYkwii69ZzMBUzy/i2qy1jPt4HMVV4hQS6yW03XF4R8ivW6lRWfr5xs9DOse89HnyQ+luCfTXJHlajQi9xWANZfvh4Gy3oi0Fxv4ELUf4//6a4uH4V2QsPMqw2eD55z1dN156SVyS/AmH4uPh1FPh+uvFxRki37KsWRHbTuZKNc5QZRnA2CN5RVHqQdRpPkhaDpOEvBZ5f0LHqaGdz9uNxh0/zjQ1bvLe888aZsyAu+6KjAPHihUwdqyv65w7v/wijkbNJhfTUHIWw4rrZQ2pFQ9LGQrdrqpzG3ZUyn0z0Hza2hYSe0KHM2WurxhEEJG7BHa9DwdmBnV56fnpvLz85dq4I4BBMXD90OsxKAYeH/s4d/x8B6U2EYNUO6u5YdYN/HrVr4FPnjwI9n8HqlcArjK78QvHLcnaMTqA7PnyN2gs2p8Bg56EDY9oi+FB8rmz+0G7SdDjRmg3WVrZaX02nE7XZ0ttdgX57kSdN45Rpk4NPQnz739rJ66aHd2vrV+ya8tzcuNvJigKnHtu6IXZDzzQzNw3DBZXr7MgsZfTGJX6QIR7Ux4bCsMjQVRF3wTRE0YkdG+Ul+/eXf9e+vPP4V/g1Qa3FIMEd/TInB12tXH3NtpekjtCj82Gna25W7nwqws9FlBdkrtw+8jbOe+48zix44mYDKJLLreVc+tPt7J0X3j0UG/89QaPL368VrgRb47n8XGP89aZb9GndZ/a1y2pLmHcR+PYkhtEJWKmT7xGSB4EnS6MmBOFnnijsDAiL1dHTYDdm4RuDbOIjFJDk3SNitJAKg9BtbctvSL9ehvbRUdVoXgnpL8HSy6AH7rBl7HwTSv45XiYdzLMGw2/DIdv28CMWJjZFRafC+nTRHSoqvTurb3WmD1buw90fbFatd0mV66E2AgZ/WzN3erzmIKC2WD2u2lVtm/N8z0XSCuBkmrPRbnJYApKvNE6rjUWk+cgkFcewVJDHTIzfV1RevVqmIuALi1H+D52+K/gxZHnZ8Nlquemh1ZgcOC/w1dFZ24CKtooDSL9cHrtzyaDiTbx2m6KnVrUDcnVjmr2F4vzhrs7TdeuDbsW97YpdqedZGuyzz7J1mQczrrPdXaZZ9Is0ZKIxVB3TxmcOphbjr/FZzO6OaWaFd+F0/xd80O69j2FrkSgrdSzdVhDRO3b/otHjKXHDVL4FYzwyhQPo96r/2s3UWbO9KwUHzVKkovB3Kvj46W1j7uWRssN65gktr1ncKFoi4jco0Q5Gml9kv48aO+XjSZ8GzHCf37kq6/0nTEaQmkpTHeZRfkriJ47V/aNFJFqg7xsGfz1F2zeHGTOUFVh/cOwaAqU7vIVbrSfAmesgwlLoPdt0gLRaBWRQShCaINZRNrmRGnLkXa6uOCdHzhPo6oq1/5wba3YFsQF7R8j/0G8RQbAywZehslY54lgd9pZfmC5X+fEWlIG6cf6Sho58JrYS/+5zJ8bX5ja924Y/ob/9neqU67t9/Phuzaw+GxYczekvysi3Kz5cPAn2P5fWPl3+HUcfBt4ndxUiTpvHKOceSb8/e+hHfPZZ6K6jkh1cWPScSqsvDX04xyVctwJHzWbwMnFF8O330rvyWBZt04G31NPbSaKT0tLUdkFi62IRnPeiNJsiarodUhNPXKtU7Sorw4rJFccA/3OdGhW7wJkZ8PevVJJHC7KysSCFoBWI6F8v/aO+7+DDlODqxwNksGdN/DrpgmoXvreDRtg4sT6F7M1lMPlhxk/fTxltrrFXawpls/P/xyjK4H5/tT36ftG39oe2RX2Cs78/EzW3bKOrsld6/3aH679kHvn31srGjEZTAxtN5R7TroHg2Lg+0u+Z8CbA2qTacVVxYz+YDQrblhBr1Z+FkMHZmr3dOx3f0TtElN1nEZ37oSRIyP2slCy0zPAXkNi72athG9CRF2jjkYKN0nwwt3GvUXv0ITLDaXqMOz+CLa/6qrMUXwDbVoWtKoNyvfKlu1KzFmSaXvuQc3g6ZIl4a/M7dgRCrwcmXNzZW0UiQ50NdXp7txz0j08OvZRv8c9veRpnl/6PKrbxEbrXAA5pTlYjdba1mEgApFgxRs1YsMaquxVVNgqiDU3XusqrTlVYmKE1p6tR8K+GZ4VXJU5ULZPvkvhxPt7ENcZet4YbdsZpZaMoozan1VUXeeNdontMBvM2Jw2Ku2VZBRm0N6tvZTZ3PDuie7CLZvDpivesLm5AOaVeYq9iqqKMBlNVDurMSkmLht4Gfed7Nu68Ltt33GoTLSfVc4qnKoTg9ucMLPUU2tqNvgKPNyvw6E62J2/m+7e88dA7XSDXQNaWsKwF0OL+xl01NHNmM8/r0smKgp89JFn655AtGnjuXa02SJT1d7siG3n6a6Zv1Jcm4xH32coShRShkjyXStun/VLo7WJ6NfP/zpj9WoRb4Q752Uy1TnfDxwImzZp77dkSWj311ApKXGLMQZJZiakJKUSW6Q9buYoqUyZIj87nTK/t1gk3tSrF0yeDKedJu+7dixYczekv6PRrkOBIc9B77+H3V24FrOGql+Db7Z8w5qsNR7t5QD+74T/q/05xhTDfSfdx1O/P1Vb4FVuK+eGWTew5849tSIPTZIHScsYLbJ/g6QBjTcepAyFvOXaz+UsOjJzmx7Xiqhk8dmyfvOX87OXQe4fsh2lRJ03jlFSU6Fnz9COsdvhkUeOAveNmJbSM7Y+7P8W8pY2G1X0qafWLwh6333NyH3DFAvGEAJiBetl4hglSpTQyc6WhFEomz+CPcc4HSvFkm31ex8hueI4SUqCtn68UGbMCO890yOo1Xas/j0ra37Y22r0ab+d2Bjf0ueNGyNbCeCPakc1kz+bTF55Xm1iK9YUy43DbmRw2uDa/TondeaJcU8Qb65bKJVWl3Lax6dp9tcOhi82fcFtc27zcPuIN8fzzUXf1AadOyd15sOpH9baT6uoFFUVcdIHJ7G3cK/+ybN1LBXbTYpoRX3fvtoJss2bI9w6pTJHe5Ga2Cs6LoeBqGvUUYq9FB+lojUV1DCrHLSoLoCVt8H3HWDDo1C+TwJt3sINU4IkqVscBy36QnwXMHlFPh3lslVkoijQSaP99caNEuAMJ3rr3aVhkhu53zPtTju7CjwNaBIsCQxOHUyCJcHvNjB1IAkWz0DlnsI92By+N+WDJQc9Kr0AnKozaPGGt8uH1WQls8TbpCeyaCXvqiO1vE4e5Gqb6cW+ryOwpvf6rva4Tlu0GOWYxdvtok2ctoqsTVwbYkwyx1dR2Zm/E5utrnLWam242K2osq6Pu0N1+NyDAJKsSR73ofxKTyeo7NJsKu1SqmwxWUixpmi+VouYuoSJ2WCmoKJOVZdZkunhzJEWn8Zzpz/ns53U8aTafawmKxtyNrjWQW7fu0BOucGuAbtcElgI4k0EWh0eSZxO+NVtqTJsGHToEJqQPzXVU2SUm6u/7zGFNa2uZQpA/uqoyC/K0UvKYP0WCNUFUKztNBduDAYYNEj/eVUVgVq456N//gl5Lt3jsGH+XVDXrAnva7sTrHAuPV3ax7RvLw7EbR3ZKKiaW5qaTVERFBVJrtBuFxfFPXtg3jz4179g9GgRxJx5Jiyfsw7S39YQbgAj346scCNISqpKuGX2LbWCDACTYuKS/pf4uKX9fYRvVXxpdSmPLXrM/4vEdULXTX3Px77tVCJJymD9nFpltriAHgnajoZz0qVtizGWY1nCcOy+8yj87W8QE+L64uOPm1FS3x/H/dM3qBgsy68JzenhCBITA5dcEnoV09q18PvvEQyihRt/bQW8cVaJbXOUKFGaD+3P0J5Q7v9e7HIbgRNO0H/uiy/CVy3sdMKPP7o90HK4vtrZUQ6HFofnhV30StuJ2ej7ZubP119oRhKn08mod0exNmutR8WdU3WSWZLJ3779m8e2MnOlRyWfQ3Wwt2gvA94cQLU9tEHtsYWPceV3V3oIN4yKkRHtR/DArw9w7cxra7efdvxEWkJabfDZqTrJK8+j7xt9WZW5yvfkqirBCm9iWon1cgTp3l36vXqzZ492NXTYcFZrt/mJaRUVb4QJVVXnqKraW1XVHqqqPu167O0a5yhVuM31/EBVVVf5O9b1+GFVVcerqtrL9W++6/GnVFWNV1V1iNt2hFb3RzGKER/HOL1KHT2+S5Me0AE3twXDgR+lLcquD2Tu7B5ki2kNnc6HEW/DObvhgsNw5maYtAIm/QlTNsGFeXDOHhg5TdpAWT11Pf36+V6m0ym2u+FkwADtRNPXX4fmTKiH+z1ze9722mRrDQbF4N+ByUWvlr1QFF9RxbY8X5GqltDC5rQFLd7wriIzGUyNLt7Qqmo8dChCY1DyQLBrnPjgLM/kWSTocX10fAsCRVEmK4qyXVGUdEVRHtB4XlEU5VXX8xsURRkW6FhFUVoqijJfUZSdrn9TXI93VRSlwk10+Lb360UKp+r0EC1U2at026a0jW/rIWjYU7AHu71OF2+1NswC3e60e7j3xJpife5BIPcw9/taaXWpxz3kQPGB2v8bFSMpsdriDXdXD4vRQk5ZnYji972/YzXVfU8m95zMP0/8p892w7AbagXaVfYqfsv4TYSDbrbmlB8I8jcQgM4XRXw+3tRZt85TeDFlSuhrwdRUz1YpqzSWRMckxhjP2IatOMItl6NEOYLEtAKjn/tpxufa87QIMGGC//zIRx+F1wWwuBjedptlDBrk313jnXciUzDtdMIcnY69IHOL77+XmOfAgfDmm5CVJfm/hhRwVVbK8eXl8vo5C57Ubpeb0B26XnnEhRsAD/72oIdwA8BkNPHwmId99k2yJnHD0BuwuLlkVNgreHPlm5qtNGtRFEgaqP1c0WYoP1iva68XLY7TFrnXsPujI9fiOKYVjJoGk1ZC6xNl3FQi0ETEqmNN3ESItk05hjn3XHjmmdCOqa6Gf/8bnn0WEo78PbX+dDwndCV9DZXZ0j5l5DvNYkH3j3/Al1+G3kP62mth27Yjk6wLhdJSSGg5LLS+YJk/Q1I/MERvgVGiNAvaTUCzR8qB72HYfxvlEk47TRYcWomF7dulm0z37g1/nZISWTReconrgZQh/qvIdn8sE9kgLQAD0TM1nSqbr7IzJyf87WGC4ZwZ57AuZ53P41WOKr7Z+k1Q53CqTvYV72PEuyNYf+v6oI55cvGTPLHkCZ/HHaqDX/foOGZoUGGv4IT3TmDdLesY0HaA2zMqmp9pxawtcAhECK2Auu08AYP9ZyDZ4/GtWxtuwe0XZzWaFQbRxFaUY4T8fEmG5OXJWFJRIcEyqxViY8XKdtAgqXSq/S7GtMLnXlGaHtr3JuiEgOv7uf1VWPeAb5VcfFcY8rysoxxVIoSvUUZoWbsmdJXkdeeLJVGR+QusuxeAoUNFqOjwcryfPh2OP77hlsXFxdCihVS4JST4CjV++SX0IgYt3IUha7PX+jxfYaugV8sgxButelFh8/x9q6rK2uy1DEz1DO4dLD5ItZdjRJW9Sjdp6k7ruNY+xzpVJwdLGjFIiMwl4uI816cbN0qQODbc3VvMiWBJgSovbVn+qsi2H0rsKa8bxS+KohiBNxBnpwPASkVRZqmqusVttzOAXq5tFPAWMCrAsQ8Av6mq+pxL1PEAcL/rfLtUVR0S+XfnSU5pDhajpVYUbDQYa13bvGkT38ajjVJmSaZHwslma1grw8Plh7EYLbWuGf7svePN8bX7mQwmCisLaRnbEoD9RXWtHQ2KQdd5o1VsK4/9ckpz6NdGVHzzd8+vbT0Ya4plVMdRmucYlDqotlWiisq8XfNg8qt4CBz3fiEuuw1pc2ywQGs/qv1jhK1eeaeLLgp93ExNleRdDUuXSvV1JFsDNBti20lLyRry/oTOGrZkUaIcDST3129rcPBHGBjAqSBMnHIKvPaavoB7yxbYsQOGDAnP6zmd8MMPdf8/6ST/QuXvvoO33grPa7tTWgrvvQcXXuj73MqVkv/Zuzc4oUZSUt08Pj5exDDl5bJlZkJGhv6xnVvuRjMGltTfFSuqxyIgpJbYNRjgMt+2vbO2z+KtVW/5CN0TLYncPe9uzTNV2Cpq2zbXPmav4NSPTyXzn5kY9CZrvW6G1Vu1W49uexmGhti6zZpaPxFgsh9nHIA906HvPaGfN5wk94cJv0PBOtj9Iez5RNouazmU+kMxi1DFmia//66XQVzHSF112IhmLo9h+veX4GB6emjHvfuuCDiaNQYz9LoFtv23fi4aGZ+JzfdxdzdsYdgIDB0q1sTbQzSbyMqC664Tt5X4JqpRqayEhQvh7AFnwcHZYA9Sonpogfz9LSE2fIsSJcqRIaE7xHaQhJU7VYdh89Mw4OHQxHT1mNiOHOnfzv2dd+DRR8Nzv3S3qMUUK7Z6ZXu0dz4wUywGw0T7lEwSrSVU2nwXTl99Bfff33iivscWPMbsnbPDdr4NhzZw1fdXMf286X73e+XPV3h00aNhe12H6mDoO0PZdts2erTsIQ8qBgkOO73cQKoL6icuDeHz3LV1BlV23+jrhg0RFm9oOQhA6C4CNYS0UNdeoEeJEilUVZzsfvkFFi+Wn4uKJDHtdNZtIAm4mq2qSu6xAwfCmDEw4bQhjLNXeH5zKg9BdSHEpoX/wre/Cuse9AziKAZxLRz4b1lDGczBi0cUQ918u8OZ0G4iIGNqfLxv8PT778MTtKwZp0aO1HYSzM+XVlHDhvk+FyxOJ8yeXSe2XL5/OaXVngG4GFNMUKKKZGsyMaYYbNV1DlOltlL+PPAnVw2+ymPffUX7ahOpNcSaYzEFIUpPsab4Cj8cVY3uvDFwoO+cauPGCAg3akgZDNnzPR9TnZD+LvT5R2TaHSQNrP/4dmwxEkhXVXU3gKIoM4CpgLt4YyowXVVVFfhTUZRkRVHaAV39HDsVGOc6/mNgEXXijSPCgeIDmI3mWvFGUox+LKJtfFuPZMDhisMYE1QMBhkNKipCd1d1J7c8F7PBTCVyL3Fva+JNYkwihysOAxBjjOFQ2aFa8UZmad29Q0XVvd+5O4w4VaeH88avu+sWPmajmUGp2r72/dr086iG3VOwh1JbGQkJXaHY5VJ0cBYc/4ruewmKNqdISyVjpG5IzYP0dChzdUlLTobevUM/R0KCp8ho3TqJ4YVVvJGaKlUG7v9vDiQN9BRvZP8K7aaAuYkGX6NEaQitT4LcZWgWchRvg9I9kDzA97kwM2pUYJe3e+6BmTMbXrBcWgpPPukpYEtIkHvp5s3ax5SUiNjjoosaNsZ7U1kpTrru2O3wz3+KqMPf76RtW5g8WYrZxo2Ddu18i4NVVeJIZrOIS//6C+bOhd9+g/VutVPbMo9jWLeNknh3p2C9vttwwDdXH9ci38+h3Wnnkm8u8RFugMyZZm2fFdIr5JTlcOvsW3nn7He0d+h0obQn1WLXe9D33tDyjedn6z/3uZ8gnyVJCjT0CqJLd8mWrOMU0lgoCrQcKtuw/1K6ezGHN/+CpXglieoWrIZ8qmyxOFUFUEBRMSoOLKYqSh0dKDUPQk0+gbThUzG36X9k30uIRNumHOPcdZe2dbY/qqokqV8zkW/K+FUN9vLtTRUSGx8XEYet6f8i7r67fgnFb7+VSUuorh2NgdMpQfCrrwbSTvNNgPkjZ7HvZCFKlChNm+Gva7dO2faSTPZDsXI7PxsuU303Pwwa5Lnw8ubttxtewFlWBs8/r2HV6K/6y1EhybZAPZ6DRFFg6vE/aCbxP/rIt0o6Umw6tIknf39S87lYUyxx5ji/W6xJO+D6yYZPWLRnke7rLtu/jPvn+8b2FRR6pPSgb+u+Abe28W1RvEQKdqedyZ9N9ugvTpLGosFZBUUbda8vHKQlZ+Nw+kYDVFWSzBHDYJFErjeO8vq5jYS0UG+At3iU5kdamtzMIr2l+YoncnJEyNepk4gvHn9cev7m5oqIoKYncFlZnftGWZk8VlQk40xxsVSnPv88nHuBFSWxh+973PNpZCxM1z3g24d4+Jsw4DHpx+7PVjUQBnNtT3e9yrPCwobfhxwO+Okn+bl9e31BwHvvNcwKuKRERO41LNu/zGefzi06B32+LkldfB5bum+pz2O7Cnb5POYv8eqO0WAk1uz5C6l2VLOnUEcgGiEGDPD9+x8+HHqxQdB0Ol97DrnzjfqNP8GQPKD285nP1FIAAQAASURBVB7FLx2A/W7/P+B6LJh9/B2bqqpqFoDrX/feTd0URVmrKMpiRVFOafhbCI79xfs9/l8jgNCiTVwbD5GWUTFiiiut7VlfVdUw541DZYc82gy6tzXxxv05g2Igtyy39v/uPzucDl3njbT4uvGy2lHNoTJxwimoKCCrNKv2uQpbhZdTXR2x5lhS41M9/r98/3LoeK5UUwJUZEFphu57Ccoau+Xx0e8usGlTnch04MD6t7Xq2rXu53Xrwi/SK92XjvHfBpTHYW9BBmT7SWA1JVoe72n/nrNAU+MeJcpRQeqp/ltibHkWbBHoF+JFcrLm8s2D336DnTv97xMMNpu2IP3MM/0LM155JbxtBMvLxW3EvdVaeTlMmgTvv6//WqecIi6JGRnw+uuSe+nSRQTyycmeW0qK/BsfL/9OnAhPPw1//CFz+xtuEOemJ79/VFukUb4PdrwG9iOXX7v+h+t9xPENZdqaaewt3Kv9pCWptqjBB9UBK65rvN9H+zO143Q1bH2pUb6f/nA6JT7y8MPQf6CRVv1PY/DV/6HXrQtpcU0OyTcUMOKRPxnzxCJOe3o+ox9fwqAH1hF7TTmtr8+g3y2zGHDpv0js1J8xY+B//4vgujPMRMUbxziXX16/Xpk//CBBsYj2Rm8gNa4MusR3gjYnN+xFVt4KWXOP6AATDH/7W/2raa+/XgZrmy3gro1KRYWoPwsKEMtBr17afnFWwcbHwNaAiG2UKFEal/aToOUw30ml0wYLJ0ugLoK9Mi0W6NlT//niYukN2ZBxUVVlYeRD2zHaSYcatv+PcEZ7zh/xnaZl/e7dkoQMZx9QLXLLcjl9+ukedtEgoo2nT3uanf/YyY7bd/jddv5jJx+e86GmiGPql1PZle+b/FqduZpJn0yi2ksMGGeO480z3yT9jnS23LYl4JZ1dxajO4/G7JXk3F+0n7Efja2rzO50gfbiddeHER2fFAX6tNNeqcyc2bBkpl9McdquImV7m/w8KkozI6c+FTgNe52SEqnU6tYN/vMfOHhQRBk182eTSdqB/P3v8PXXEsxavRrWrIFly2Rdde+9EiirEdY7nS5nio7ngcHLGWDbi8EnnUPp4+otCOl8MXS7IuxOgy1aeCZ03HnlFX0742AoL4dXX637/9Ch2vt9+23DqtoMhjqnLKfqZNvhbT779G3TN+jz1bQQcGf74e0+FWD7ivb57NfSqp8E9kar2n9PQeOKN1q0gDZtfB9/880IjUHtp2h/X8oyIOc3cEZAmZrQvWFip2MHrQmstxxab59gjvUmC+isqupQ4J/A54qi+KifFEW5SVGUVYqirMrNzfU5SX3YX7SfKnud62vbeP34RYwpxqOHeowpBmOLQx6ONYcOaRwYJIfKDnncW/zdQ9wFGaqq1govAAorC2t/tjlsuoKU1nGtMbkS1e5uP0v3L8VqqrNhSLYm+xWjubtylFWXsTBjocyn3d1ztr2sP4/2FvBrYW4R/e4iLd5qaEgF+siRdT8XFMh8KZzM3Daz9rP86YZPw3vySJLc33N9X5IeXQ9FOXpJHeff9XzfN6A2TtLhlCAkm/fc07D5aI3rhlZscMIE/8W1K1ZIC5NwMm1a3c9FRXDyybB8uXahbufOImCZMwemTBHBXX3aWVqtdU4j//2v5JW6D+kL/R7Ujm2uux82/lvug6EIq0NZ5+qw8/BOpm/w785bXyZ8MkH/yV636ouaDi2R70WYivT80m6if3HVvi85UurC0lIRH3XsCGecIcUtW7bUFcWUlUkcvawqga0H+7Fu71BW7R7Bhn2D2ZXTE7vDjMMhc4/iYhE///47PPigxAiGDz8ibyskouKNY5zkZLkZ1yexf9NNDQusRZqyMunb5ZdBT/pPiAVEhaWXwOGVEU0aNpSEBLjvvvqp3KuqRJFZWlo/oU8kKCuDW24R5X4t7c/wrxT0Jv3d0Nw6okSJcuQ5cTqYNCyG7SUwd7iI6SKY9B4zxv/zL75Y/3NXVMAbb+gEtFoO96zM8aYqT3o8h+meNq7fIqp01taPPqptQR8uquxVTPp0EvkV+R6PKyj0atWLB0Y/QIcWHYLarhl6DeO6jvMRUZRWlzJ++ngPF4yNORs57ePTKPX6/FiMFsZ2GcvNx98c9HswKAa+vuhr4r1sb6scVWzP28746eOpsFVAh7O0/67p08BWGPTr1Ydzh8/UbAM0e3Z4LTo9SOiuPU6X7Iy6YUVp1mzaBH371gn4au6fRqO01Fi1Suauv/0GL7wg/YZPPlladgwdCieeKFVYTz4Js2aJ+8SOHXDnna7gXp87fRdrlTmw6UntPrnehOQ25f64AiPeCq0tWQhMnKi9Bp07t2HJnUOHJChTw/jx1Fare+/344/1E6iXl0vFTs2xuwt2Y/QSpxkVI0PShgR9zsGpg2uTmzWYDCbS8z1bxrlXqdfQOq510K+j1dZASxASaa691rcN24wZEVpvxnfWD+6uf6h+bVQDEar983dpYmsccIvUIH3EOAB0cvt/R8C7j4/ePv6OzXG1VsH17yEAVVWrVFU97Pp5NbAL8GkIoarqNFVVh6uqOryNltKoHuwp3EOVo+6z1i6hnd/9vUUM9vj9Hi5/q1bV/1pyy3I9Wii1imulu2+r2LrnbE4bueUiZrE5bLUtYGqeS4zRzvCkxKZgMdV9J2ruOb/u/pWSqrobvp7rRg0ndTqp9j7pUB38nP6zyynDbZza9R4UbwFHPROB5npkqY5C3MX6sbH1LwY78UTPOOTixeG9z7+9StqHKihMWzMNtaFWmI1Fi774OAPu/hAcERiPokQ50hit/otnndWw6ZlGcTY/7bTAzuQLFsharL73Kj3XDdB3H3Tn5pvD43ZfViYxSnex59VXw9at2tdw2mmyrj3lFN+2Vw0hIUEcT776Chj4iCsXF4uPIGDrC7BgIuQslBxbMHk2vXVuAGdld87+4mzd56wma1Cbu+DWnZ35O5m5bab2ydtNkpYlevx1IxRtiozbpjttRnu2TPXGUdnoziilpSKiSksToUVWlsQHwlVIWOOAunp1eM4XSaLijSj83/+F3joFRLhx5plNs31KeTmcc47Yr/qlzUmQMqRhL6baYdEUKFgdXAD1CHHnnfVPyBw4IEHmw4ePvANHebl8Zj/1FtX3us23KtEfjeG+EQYFaJQoUdxI6Abjf9VOJNnL4Pfz4M+rpZI/ArZuNYsYPXJzYfp0dIUPgdAVfyQP9D+ZBtj8TNgqR2MtlZyg06llwwZJQNb3PeohimmVq2dezba8bdicnoON1WTls/M/87B4DoZ3z37XZyHlVJ1kl2Zz9hdnY3fa2Za3jTEfjqG42leR2iKmBZ+d/xlKiBHL1IRUvrjwCx/nj0pHJRtyNjD508lUJR4nCyVvNwrVDssuD01lH+J4M2nQXM25X1aW/H0jkjxL7K0dkCzZIQGdKFHCRWP1O09NZdEi6Z+cmekZBJs0Saqmpk0Txw2LBZKS/K+5YmJEWG82Q69e8NRTcl5iU6HL3+ps4WvY8jzk/hm5ipxWw8HgRzjYQE4/XbuSy+mEO+6on4CjtFTcTdwZNUr/9/744/Vf2/z3v3U/r81a6zM+xZnj6N3KJyesS+9WvYkze16oQTGwNmutx2OHy30XuGkJATyg3WgT55uIzilrJLcaN665xjcoXFQEDzwQIfeNTucDGovhwg0imgz39yjUQGvQrcCaSDVF+FgJ9FIUpZuiKBbgUsC7sfgs4CpFOAEocrVC8XfsLOBq189XAz8AKIrSRlFk4qUoSnegF7A7cm+vjp2HPX3YOyV10tlTcBdNVDuqqYjZ4yGgXrTIf0tHf2SXZnsISfy5gLSJr7tnVNorySmVz2pueS4xbo4XseZY3Xl6ijXFQ+B2oPgAAPN2zat12lNQOLHjiX6ve3DqYOIsdffJLblbqHJUw8An3NaHKiw5F2xF9WuLFCg+5FdodfSIq9xFjxUV9W8POnSop1Dv1VfDF0M+VHaIVZmiYlIUhbzyPDbkbAjPySNNQnffcWL3R7IOjBLlaKTrZf4F4elvgxr5AssT/Q8ztVx3Xf1cdcvKRHyhNz7HxcFxx/k/x9Kl4iTf0PxLRQU891zd/7/+GubP147lTZ0qRQSJidqi93BQK5rp+0+YuFzycd6OD3nLYMHpMLs/bH5KXImcNrAVQ3UROIO8RwYpNFi2fxkZhRk+j1sMFi4feDkvTXwpqO3liS/rzqUemP8ADq1YrWKAEz50CVk0cNrgt9Ol2CmSDhzmBEjs5X+fzU83mrjwl1/EofPNN+X75G/OEBcn7hkXXwz33y/OHC+9BM8+K/GEs8+G/v0jWKDWCEQuGhOl2TB6tNgYrV0beF9vVq+Gu+6S4FVDrPTCSWmp9EBa5tt2WJuhL8rA4N3fORQcFTB/DPS9FwY+JkmIEBNMkaZFC7j7brFyrs8EZOtWWXgtXgwdOogFVmNTVgaXXlrXx9qDlEHQdixkzwt+kZ7+rlQzGrtGJjh9foj9Nj+PNrmMEiUgLYfBmB9g8VTXfdsrkrT/O9j/vVjo9rpVRHqOShF3abTQwF4uk+IgKiRHjgyc1P73v+U+FROClqy0FF5+2dOe1gNjjCiyS/003yzdBTteh95/D0uV9F13yRivlUC5/nqpRAjlPfqjokIWins6PsuPO370qOIDaZdy28jbAlbjadGhRQeeHf8sD/72IGVulRxVjipWZ63mlh9v4btt31FYVehzbKwplm8v/lazSjkYJveczLVDruWDtR9Q6Racq7RX8vu+37ny+yv5avIbMGeQrzjn0BL48xpZzAXz99Qbb3TGlVE9Vug6qDz7LIwbF4F5XUxr7blR1WF5/1EBR5RwEUq/cz1hVhBZiv374dyBvpaz//qXbIGqugLh8R0c/LSMb7YitwdVWHI2jPkRWp8I5obf+z2wtAwt8fVdWpAJaANc5mD0aP3A5nffwWOPwYABwVd9OZ2wcaO093Ln+OO1bYFB1jd//CFCkmBfp6oKPvwQ8t0MolYcXFHXEsuFoighize824WVVpfy18G/uGTAJQCU28o9quVraN+ifdCvoyX0KKgoQFXVkIWKDaFnT9k2bfJ8/J13RIDTp0/Dg8dlZW7fw45TpSLfrqEKWv8gdL5I2nuFi5Kd4KgGnUq8KIKqqnZFUW4H5iLqmg9UVd2sKMotruffBuYAU4B0oBy41t+xrlM/B3ylKMr1wD7gItfjY4AnFEWxAw7gFlVVPe3eIkRGUUbtz2aDOaDzRtv4tmzN2wrI3PEw23G4xf5XrZJ7aH3iMvuL99f+bMDg173HPRmhotYem1Oag9lorp23J1j0J44psSkewo5DZYcoqy7zcBZKtCQytJ1OnysXg1IHYXdL3FhNVlZlruLk7tfAhofrkjUVWfDbOBg7C2Laarf+0hNp2Itda0OdG5Dfce7oEVe1cjNjaYigbvBgz7F+yRIR6gVrw19d7evSVMOXm77EaDASo8agGBSqHdV8uO5DXpn8Sv0vuLEwmKT9c3ndd5HibVB+AFr0OXLXFSVKpGg/BVbepv+8vQz+vA5O+jRirn8gwolg5pfr18MNN8B77wW/pisthbffFpGEP848U9Yg/lwE/vEP2Ly5/nPh0lIp4nXP/9x4o36rlE8/bfjaNSRSBsPk1XBwlhSiFW6Q9XeNG17ZHnl88zMSy03sBUl9IWmAOBMndJPHjRaJMTmqpfVOVYEUVxesD3gJdqedq76/ykPMWkOcJY73z3mfGFPwQc828W24ftb1PmvCAyUHeGvVW9w+8nbfg1oNl9j1vq+0nZTtJfDLCHHD7HJx5L4bHc6G4u36jrj2MlhzFwx/M+ztVGuoKeD48EP9tTtAp05wxRVwwQUSK6iZY8TGes4XKitlMxikhe0ff4j7y4wZTdOIQI+IZ5cVRZmsKMp2RVHSFUV5QON5RVGUV13Pb1AUZVigYxVFaakoynxFUXa6/k1xPd5KUZSFiqKUKoqi1TU+ig7PPVf/m/R774VXPd0Qysrg/ffFxjZo2pwILYfS8P5NKmz9D8w7Ccr2hc9OyFEF1YVhOdX//R+aNunBcvCgBEA3bvR/Iw03Docs8MaP1xFu1DDk+dDdNxZMiPaWjBKluZE2HiatgLiOOiplFfZ/AwvGwzct4Y+LYd19sHMaZM6F7AWQ+bOIHdbcDUumwjfJAV+2Z0/94FENWVlw0UXB3yOrqkQ8+e9/B9ix/RkEnLatfxCKd0rAMRABXDrOOQda6rS/zs0VZXM4xgGHQ2wcr31iIQ8teIhym+9Jk6xJPDHuCc8HnTYoPwj5q+HgT7Drfdj+Omx7Bba+JBXpW1+Eba/w9xYq3eJ82+2U28p5f9373PtrBY8vxGf77NMKxnQdK8ndem4vT32TJ3+u9Dn3YwtVrn5hPiT2hH73a7dw2/c1LP2buMjU1/pZB7PJzogR2s8tWybjfbhxqgrE6VSZHvyp6fRmixIlSG691TehceGF4RFu+BDbDkZ/7TvmOSph0STY+nydGDFcFG0NbV4donNA69ZiharHbbeFJjivrJRjvElOBn9dDx5+OLTXcTg8q9gA/tj3h4/wotxWTs+WPYM+b8+WPX3Eiyoqv++r6wGTWZLp4+hkUkwBk8DudGjRwecxRVEorCwM+hzh4tlnfb8rTidMnixrv4YMC2Vl8NFHbg+0OUm/otlRCX9cFN41YdHmhhWHHEOoqjpHVdXeqqr2UFX1addjb7uEG6jCba7nB6qqusrfsa7HD6uqOl5V1V6uf/Ndj3+rqmp/VVUHq6o6TFXVHxvrfdY4VgDEmGL8ul0AtE/0FGXtLNhObzc92Jo19XPQBbmX1GAxWWgZqzPpB1rGtvRwsTtYLJPEQ2WHUNxiaEkxGq0tXaRYUzzukYfLD7Pi4ApizXX3M6fqZFDqIL/X3TmpM043UWGlvZIle5dI8mbU+57z6aLN8GMf2PhvqMoXl9zqQte/BVLRq0XBusbpMd/EcRdPbthQvxbMIJ/RkSM9H3viieAFIQ4/S9a3Vr1Fua0cRVFwOB3YnXamr5+uXeHcFEnq7/vYhkf9CIsiELdMS2vQWhdF8T+ZixKlhth2EN/F/z4HZkLmLxFtE2EwwHnnBdcKasYMePfd4PJdlZUiqrz//sD7TpgQePzOyJC2yvXJtdlssHs3fPGF5+N68+p33w1fYVZIKIqIqyetgDO3wIBHIGWYFNaZW9S1GHZWSfuQfV+Lg/riM2F2P/ixB8zsBN93gFnd4MfeMG8UrPw7pL+j/7ou19r//vlfskt9iz5iTbHce9K9IQk3AM7ve75P62SAMlsZD/z6gOZrATDsZf/FhM4qWHEdrLhB5jGhOMgHOx6mTQgsDNnzKZTvrZ+rWQCcTrjqKv/CjWHDpOXp9u3Szvv44+Vzm5Qkm3es3mqVOECLFvJ9mzgRXnkFcnIkb9wu+OXzESWizhsuO8I3gAlIP8qViqLMUlV1i9tuZyBWhb2AUcBbwKgAxz4A/Kaq6nMuUccDwP1AJfAIMMC1RQmSCROgSxfYsiXwvlo89JB8+J95ppGVem6UlYm9sHcwLSiGvgS/nRaeAEvhepjdF/reA33vEwVgfZRxjkpRHe6ZDhseafh1ITezl14SEUd9xTZFRdI64JtvIlSZ60VFhbToGTtWbtB+qXHfyJpH0FUPZRnw+/kw9sfwVltFiRIlsiT3h7O2weq7YM8nEpDXCso7KiB7vmwNRFHgrLM02jZ5MX9+3b020D2yuFgWjwETFB2nipWq3be1Ry2qA5acA2du0q8Wq8HpP1NlMMCTT0oiTCu4Nn8+/POf4hhS38CxzSbtuE49Faryu/PPE/6psVMJV3ToReymxyB3qVQjVedLUNVorXNNcjrq3FUUo2yqA1QnRmcV37cq4R2jxTUyOMVuUTGC0cqDv0ZOwBfjgHt0ncAK5Z8Bj0qrn71f+s5DDv4oC9MRb0PqqbKoC5NT1IUXSoBBK2l5662yMArnnK6yEuKS+kubFG/2fQUdzgGLfuA/SpSmRH4+/PqrZ1LBYJBqq4ithdpNgOPuhm0ve94rVCdsehJ2fwxDnoGO58l4aIwHg3dbJqckroJwm6J8nyS/UoZErH3KpEkivNcaA//4QwIsd94ZeCwtK5MxS89J8uST9avgVq6EDz4Qe+RAf7vSUum7e+BA3WOqqrI5d7PPvvHmeL+V6D77W+JJtCRSUFng8fiW3C21rhiZJZkYvf6mMaYYv1Xz3qTFp2EymDyq12OMMWSWZNbbaaq+nHmmBN7++MPzM3DwoKw3Fy2S9WuozgJlZfDll1K1WCvoMZilsm3vF9pVZXnLYeEZMG6O/4qyYAOmhRuC+55FOSZwOB0eAimjYvRoR6JFpxaegteMwgxGj5ZKXJDWUjk5UoEYKu4JBJPBRLI1WXffZGsyZoO51vUnu0yOzSnLweH2XfJ3jpTYFI+EemFVIeuz11Npr6wVfVQ5quiR0sPvdSuKQt/WfdmZvxOjYqTaUc3yA8vlyY5nQ7crZV1YM0aqdtj2omyJPcWFoypXnHH0OLQ46gaHFC3Excm4V1QksbhB/rU1ulx+uTg61iRkPvoI7rsPunf373pVViZJxbvu8n0uPT+dPYV7ABk/2ye2Z+OhjdiddpbsXcKp3U6t38U2JqmnQc4Cz2rrfV+Jo3PKMN9fTiTadOeEoW1aEOdwOqVoxWYTJ4GYmOAdz6IcRXS5FDY/Kw4Jevx1I5ydHtH78KWXwrffSiwuEHffLW71Y8bor0fKylyOjOcGJzw+8cTg2hA/+KAkrE88MfiYm8Mh69TJk32NJLXieikp8t4i1SolaBK6wYCHZLNXQN5SOLwKtWAdjvwtULYXg1pBtTMW1amgoqKgAqrLjFlBVRRAQVHAZLBhVGw4LO0xJvfC0GoIJA+CtuMgvhMHiw/y+KLHNYvHFEXhthF+XGJ0MBlMPDzmYR749QEP11+Q9ne3zbmNby/+1vdAaxs4+QspOvTXLnvvDBE4dbsGBj5a13LG7GVl5bTLeGGMhZyFwV1865OCEE2p4o4zfkFYHUCcTpknzJqlLdyIixPTgEsvlTVhQ1qg1HyHb75Z1v7BiK2ONJFumzISSFdVdTeAoigzgKmAu0RgKjBdVVUV+FNRlGRFUdoBXf0cOxUY5zr+Y2ARcL+qqmXAH4qiBF/iEgWQhNR//gOXXFL/pP6rr4pL8QcfNL6Ao7xcAjMff1zPE7QeBWmnSyW2v0lEsDgqYdNTUgHc+zboeQtY24qQw98ExGmTY51VsOczqaKryGr49bhx/fXw+uvinlHfvpVVVVKVfemlolaLiwv/37y6WizEpk2TftRFRQEPEYY8LwtufwOeNzkLROE+8PGI2T9FiRIlApjiYNQ06P8ArH8EDnwnSfxw3MdrcKmya7joIplUBlroPfaYLLTGjtVe5Nlsksw+6ywRMASkzWhtGz1vyvfD7xfCKd+6xA1eqzCnXcaZZZcFPNXf/gb33KNfGfXOO3Jvfv/90AUcVVXiUnLyyZCZCdCFlya9JE8e+kOU8lnzRKyy0+IKVjkhrrNYbrYaKdVKce0lEGtJFjGG0wY1izhk8YZioqei8EJ1oQRsK7JEQJC3AvJXQurh8ASuQiXV9dlSFBj5rlxb9gJfAUf5AVh8FiT1E6FHh7Pk72iK0xfp1CRo/XDllfqLlYULpdfkmWeGp01aTQX0bWdMFSGV97Vl/xa6tbw1NYRK/yhRwsuGDfLdcA+89e/fCIGvQU8AKmz7r8a9Yh8su0ICNe2nQKtRssapaVlUXQB5f8l976COlZ0x1nMO/cdFMGUDGILwN6/Hd/Lyy6WqrUSjkwWIK0a3btKHWW+tUVYGn30mPW71OP98uafpvc4//ymBy3799P+GFRWwYIGso9w5UHxAs8q3a3JX/QvSoWtyVwqyPcUbqqqyr2gfXZK7cLD4oEfVOYDRYKRVbCuCpVVcK2KMMR7iDYNi4GDJQfq31agCjiCKIom5IUN8hYTbtkHfviK6GTkyOIv9msTQbbfB9OkaOxz3f9J+SK9gI/d3+O1UGDNTKv7cg6G1hRVBBhzK9sp8I9F/MjrKsUFOWQ4Wo6XWXUdFDei80S6xHRajpVY0kVmayckny/2uZm7+9ttSSBXqPDy/oq5TjFExBhRvuIvG8sqlz2NOaQ6V9rpAv7/7UIo1BZuXM9SlAy5lwD+egIJCADoVg/HhwCHqnxJhs5vupb+6HP7m+s/w12Qcyprn+z0vSZctEI5KOLwS2o7Wfj7Usc5RBfmrZH2T9YvM652VMlc3WqVFWeppkDpOWqBZkoM/dwTp18/z/19/LQnM+qwLzjpLhJg12Gxid758uf5nt8ad8YEHtMUb09dPrx0PJ/WYRM+WPdmWt43S6lLeW/Ne8xBvtDkJDFbfNf6K62DCMiCuTuFgL4c/r2/0S6wP+fnw228iqF2+XARnubmScDMYJFHncIgr2oABcMIJ0qL7gguigo6jno5TYdtLYPcTr6sucBVY/hSx+Py4cf5blrjjdEpM5IorxAkDpJIfZA2iKLIGefbZ4M8ZGytF1H6dxZHvydlnw9KlMicO5v5bUiIC6CyNVJJWDuiUU2T+HI6YT0MpLJR7x5IlsWzefDq7dp1OVpZct9UKiTFFdEjaSUpcHjHmKmJMVVhM1RgNDqpsMVTbLVTZYyivjiOzuAeHSjtisxmorBRX4c6dpW3O9Olw8083a7aitBgtXDfkOpKs9Ssqum7odTz424M+j9ucNn5J/4VFGYsY13Wc74EdzhLnkU1P+S8sd1RC+tsSL23RW0QXqaeJK7XBIg5N+Ssh9w/I+1O+T8FgipWCjcN/+d/v8F+w4noY9UHwBdAB3D+mTZPCMS3hRmqqOAOnpdW/aFCLmBjZ/MUPmgqRFm90ANwauHEAcdcItE+HAMemqqqaBaCqapaiKP5XPV4oinITcBNA586dQzn0qGbKFAk6rlpVf4vSr76Sidr330fekaGGsjIRncye3cATjXhDbBXDaU1uLxXr9i3PQ2JvuRm3GgXJA8UyzGCWBEz1YSjcJDfYrLmyWIwQBgN88olMkEOxCPZGVcWC6/vvpbr8oYdkMt7QAd/plITm/PmywNu7N8QT1LhvZP+qb42rxbaXwJICx90V0f56UaJEiQAJ3eHkz6A0Q/qZ7/0CyjNlJRWKkMsUL/fkhB7Q9XLocR3EetqAjh8fnEpeVSVQddNN4k7hdEriwWaT49esEQGc1qJKE6NFAjw5CwLvmz0fZvcXAUdSX8AovwunDUp3w5LzpIdkAMxmaedy7736ws4ZM0S4OX26qPaDGfvLyiSJdvPNXsKVwyth1R1Sreq+YDFbYfBT0P06SaSoNjAm+FaUg3/HEWsb2ZL6SeudrlcACmSHOGHx57FZX1WkwQhjfoD1D8P2V7Q/t0VbYOmlYh/ZZjS0PUV6hbboK0kmFBF/lu4Ry+f81X5fMiVFxEiff65tSXzjjbBjh9gPNiSQ5nBAXp4IgW67foq2CMlRAbunQ/drwBikPeX5OraTnze0DV6UKIHR+k7Y7Y0QdFYUuR8m9hJLWGe173zXUQH7v5UtVGJaSWKphrIMqQI65RtxN/LnwFGP7+To0YGrZ66+WoI6l1wiQZaa/e12EXtPnw63a7QQdmfSJP9jt90uY/aaNTKOedvDl5XJeH3FFb7Hrslag9lo9ml50r9N6EKI/m36szbb0z7EZDSxJmsNXZK7kFmS6ZEsBVBQQnLeaB3X2se9w+60e7RRaEx695ZWQ8895zvXKCiA00+XoPnTT0sluKp6zjXsdklkWyxitfvcc57OKB60HCaW3cVb9S8ofxX80Bk6TIW+d0u7L0clZM6BrS9ARQi/p13viugymOBmVJB4VLO/aL/HfcLutNMmzr/zRpu4Nh7ijfyKfEaMUHE66+6p77wjIrdgsdulja53m6RA4g339ig1xx4sOeghAvPnJJJkTcLmFmezmqyU2cqYsLpQ9xg92pfIVkde3Y8Gs6x/Vt0Juz+ov7Puvq/kfqH13fUe6/TGuNylsO5f4upjinUVaWkJ8XdD/lpJxjgq4NyDsl45wgwe7LnkmTNH3DLqE+/r0EHu9Rs31j22YQNcc42Iu70TMjabrB0mTNAeu1VV5f2171PtqCbRksjZfc6mc1JnXlnxCsVVxczcPpNKeyVWUxPIRvqj5fHaa77CjTDvBDhtvqzxVAcsOTf4CuojxJo1UsAyf76MyeXl0LWrFGsMHiyJ05gY+Zvu3SufgQ0bYPFiEehedNGRfgdRIk7KULC0DtwC6NBiWHA6nDYXjInBLbBCaCtkscj95Ycfgj6ETz8VscWZZ8rc1GIR57hZs+rXcvbGG+Wzrycsr6GiAk47Df76S9o86MXbqqpkXXT66bDTj7mUN/HxwbWQiRT79klu6fPPRbhttWoXyqkqtGmTRFK34XTtLr+L2Ni6tWFlpfwOCgthzx4o2g1qSd3aIjdXttWr4ap/z2NhxkKPOUwNBsXA/aPrb8cQZ47jzlF38tLyl3zWbOW2cq6eeTU7/7HTox1dLf0egMpsSH8viPmLCsXbZdv9Yb2v14OeN4vrZqDv0t4vwdIKhv4nuPyZXf9Dnl2Yyr33a8ebU1NhxQr5WwdqX15fGit33RAiLd7Q+vp7R7X19gnm2Hqhquo0YBrA8OHDw3LOowFFkYDH8OENS+r/+qso9z77TCwcg6mSqQ8lJZIwuvxysbttMHEdReW2+anI9BIs2SE2x02AQYPEHuiDDxr2twYZIJ99VqqmnnlGKnmrqmQBFmz1odMpf0+rFdavF4vbvwKI/fxywgcwe4BY64fChoelSur4V6ItVKJEaY4kdJWk1uCnoGwvh3Z8yB/rXqG/2UmvGBMGW5GrpYbB1afPIZPOhB4i/Go1Etqf6SPYcCc+XipAf/9ddxcPpk0TS8ZzzpGKkvx8+PlnmYSGTJdLRT0dTCCyfD/MHSnWgKnjAAUO/Q4Fa0J6yZtvlvv7+vX6ws5Fi6BHDxHc1Qj5zGbP4F5JiUy4t22TlhzLl3ueY3j3lfDrON/31moknPar/N3CfV/2thc80igGaXnQbhIsvUQEoFrzEdUOhxbJ1kDuu0/aoGnNBQoKRKz0++911SWh4nTKeU49VeYLWNtAi+NEoOPNpieh21X1e6EoURqZoUMlQObO1q3iRtQoQYDuV4tY+a+bpbImHK0fralS5fbrWLCVUNuCMOsXmD0QTv4ckgaEtQrOaBRRxnvv6fe1t9tl3fLii9KSbNgwCeCtXCmOGcEEKFNSpGJt/Xr9fQ4cgF69pFXLRRfJa6iqXOPrr0tCQiuJtCpzFaVVnm5CJoOJwWmDA1+YF4PTBvPl5i89KtRLq0tZlbmK8/qex57CPT7V607VGbJ4Q/EKtVTYKzhYXI/Ic5h46CFYt07mR1pVV7Nny9anjySBxo6F1q3ls7F5MyxZIlVZwdhfM/Ax6Rntz51KdcKB72ULhZqWbTXs/kjEG8GgJX6KihGPGvYX7/f4f6W9MmDblLbxbTEqdUIro2IkpWMuyclta78nhw9L0uPyy4PrV19dDU6lmipH3c3MqTpJseq3TEqxpqC6hWLLqstwOB3sK9rnsV9qQqr3obUYFANWk7VWvGJUjOSU5hARy2TFACNeg84Xwl83o1YcBEcVirszo2IWsXBsu7rWhN+lQdUheX7vDBj8TP1evzxTqlIPLakbm+P6SOuzdpMlYW+Kp1Z0XbxdHIBzFkrCsgkIN0BypaefLsVaIC4K+/dL1XJ9hKoPPCDrSndHx6+/FneNd9+VqlqHQz7HixbJuJ+towldnbWaokqx5q1yVDG+23hSYlNqhU5GxcicnXM4v+/5oV9oY2K0yrqoaKPvc0WbYWZniG0vwj5nENUj9SE1tcEOlM62adz+dxHiVFZKvOS228QxJSFBxur4eBGO1WCzyXhvMkmc4JVXGnQJUZoLigL97oO194EjQN7l8AqYdxKMXyTOgHrrD3uZFGAtmhLSpVx3nTjqBRJPuFNYKLmuzz4L6aU0mTw5+MLpwkIYOFBauPzrX3WFYSBxHFWFmTNlXRTq13nfvsD7RIKNG0V8Om+e/L/SpXOoWV/36AFnnCFrsr59ZS1XUSHjhNksOSct0Ul1dV1sKzZW7jUHDkjx2I8/wuKllVwz8xrNdikGxcBZvc6iY4uODXpvd466k5eXa+f/8srz+M/S//DwGA3lraLAsFdkPbHz7dAKEcNBpwukOCQYdr4p4sIBj0hxmZYYxVYq72HhZN3T3Dn9f7oFFjNmQPv2TaClzxEm0uKNA4B7B8aOgHepgt4+Fj/H5iiK0s7lutEOOBTWqz6G6dcPbrhBJs+VlYH312PdOrE/u/xymYRZreFrq1FeLoGze+8VsUl9XUI06XuPKPT99cA8SnjhBVHPZ2TUv1DYnbw8qTC/7TZx9Zg8Wfq99eghA6ei1FXKOZ2yWSyyeKsZRBcskMRmg4ltJ/2Kfzs19MFu17tQvEUqoE2Jodu4R4kS5YjjcDp4Ye0XPLH4P7Vq5xYxLXj/rE+5oM9Z4kBhsEjQzp9Tgw7XXisBLL12It4cPizj1YcNFUR3OAdW/SO0Ywo3aCfKg8RgkL7xQ4ZoJ1RqsNnqEmuDBslCq39/WTAVFEhVwbx5EqDT4upTPtJOPvb7V9MTWUSa1LEwdZ8kfTY8LONYuHscu9oBDRhQ57qmxYYNErhdsCD0hLTTKYns0aOl+qGWLpdJoNo7CFlxUILlXS8L3n0jSpQjRGIinHeeiJ/cRRxXXilVWeG09dQloatUpGXNh42Pi9uOogTRr9aFwSJJrsTeMOBh6OwqeZy8CuaPERF0zfe0bA/MO1HaTA54FFqNkApig0W/JaSjSqzhA3DTTVLNFqh155YtMrbUl8sug+3b/a9xi4pkjP/f/0Qk4nCI2HDHDv1jluxdghPPBWmcOY7erXqHfI29WvYi1hyLraouyehUnSzZtwSA3QW7fY6pdlSHLN5wqJ5KGafqZFfBrpCvN1woiiSgJ02CP//ULy7Yvl22Dz5owIt1ugBW3xn+cRUkueB+3soc2PqiOHhEnR2PaQ4UH/CowDQbzAFdAdrEt/EQTcSYYjhYcoDLL2/LK6/I3BskkXPBBYHFG+Xl8j074+I8YowxHi4ggZw33KtTY0wx5Ffke7j1mBRTQCeRBEuCR9uYnLKcsCSOa9sQ+jw+lqrJa5n6RhrnJbXm5o7dRZhoThSL8XaTpE2J4lIidL4Q0t8Vh7+qXJmDD3oqdMHinIHyOqpN3CFHvSdidMXoO14aY2Q8TRkibZ2qckN++8FSXQ27d4vgcedOEdSXlEhstcZBt2NHEWf07i1ixr/9TVwUSkslZnjNNdJaMdjYbmlp3frhwgtF6O+9fl68WF5vyBAR5W3fLiIRf7y/5v3az1LHFh1rhVAndDyBRRmLKKku4e1Vbzd98QZAx3PEDUrLNVi1S0u8SKKnkAHfzKhO4PjmG+Hzj2XsbtVKCvFSU/1/TsxmSHJ1JYiPh0ceCfG6ozRful0Ja+8Jbt+iLfBDV3HnHPAQmBKorfVWnfId2fIfaSFhC7bXuhCKeCISWCxyX/z0U30BuztVVVIwO22aOOePGSPj/urVIn7evj3wOWqcb9xZvjw8OaFgsdlE2PXhh3It7n8DgwGuv17c3bt0kcfc19TBFIdbLJ4uDRaLiL979JAx7MW/XuSZ5drzjhhjDI+O1RFdqypUHZY1cVkGVOXLWthpk/FedUpsWTHTxmDm0i7DmL57OQ6vdpfltnKeWPwENw67UVv0qigw7GVoeyosu1xipGoQH5D64NUiHEuSzI+yfg7u+C3PQcZnInbtdL78PhRD3Qdq46Ow8x1d8WG13cysNefUzmfdOf98MRc41oUbEHnxxkqgl6Io3YCDwKWAd5P1WcDtiqLMQNqiFLlEGbl+jp0FXA085/o3BKOjKIF4+mkZPBoi3gD5rn76KXz3nais775bHq9vMLMmafT66/Dkk8EnzULCYIKTv4T5Jze+wq2RiY0VwcTIkf4TcqFis0mV7u+/SxVVcjKMGCFVuwkJsjAsK5Nt61bYFak4YetRcPxrsPqO0KsRc5dKy4ERb8mi3mCNNl+MEqUe2Gzgb671/vtSbWEyyb0hPh7atq3b6iP623xoMxd/czEZhRlU2CswKSZUVIqqirhq1g2832UsH0z9gLSElvV+X+edJ+4RjU5sqrT8KFgbeN8w0qsXvPWWvOdA44WqSmWzv+pmLWYs/xu3n/GR7/16+8vQ7nTtgKc/vksLwX7cAJdFaEFUX4wW6HUT9LgWMr6QgET+Kmlb4Md2UPtcsYAK1jQRRvS+Qz5LLh55RJKaeonTlSvFOeP776XiIZjvZWmp2Ieed55GIKHT+bDp39oHrrsPOp0XFW9EaRa8+qo4DrqL0hYulBYer78uiZBGmT62myBbeSbs+YTc7e+QUHkAq8GA4n3fdFYBLsFGhzOh+7WQ2MNzn8SecOYmWHU7HJjpEoO4gjDZv8qmGMVSvu04mStb24LRtchzlENVHmTODcohaNgwqbiN2JrAxcUXi3tGMKxbJ1swbDzkWzGrqiq9WvYK+tpq6NWqF6pGBHVjjryGd/U+gM1h85t49aZ1XGuP9gU17CkM3E4tkpjNIui/805phROO9almwM9gkoTs6rsCV32GijHOVxSy5TnoeZOMxUp0PXmssit/l0dv9WB6qbeNb+vzXd1ftJ+//W0Yb75ZJ97IyZGiqS+/1J+jORySo739dlh+5iGPFi7VjuqA4g336zAbzBwqO8ShsrrBz2Ky+HXvABHS55aLOMHmsMnxYUgc++PRRY8zt6iYuUXFtBz5Py7q76cvQ00hV8173fEadLkEkodI25NgsRVLQrFFH5i0Ur77/lqOgSR8DGZfwbqjUlwXC9ZCSbqIn8v2irhStUuySDGIk0hMGxF1tugDCT2h1UiKTcOY8ZWJDz6QlhYxMRKP7dBB2lm0by+JLYdDhBzLlokbRl6eJOL37JG5TE3sdeVKePttuOWWwOuBsjKpBK9pN2axwOOPi+uf1v092DHX7rTz2cbPcKpOFBTGdhlb6wJzatdTWb5/OVWOKhZnLKagooCUWP+fyyNO2gT5rNmCsY5qeuzd65k/+OYb+XwF4wTkTriKPaM0A8yJ0O1q2PW+JL0D4SiXKv+db0nb2LiOgEHaS+QsCq1duhsWi7g6TJ9+5EQct98u35lAAnZ38vLkmqdPD/31tNalTqcUYd1/f+TdIx0OcerfuNFXqN2xo+QP+/aNzHWYTCIYm9p/MtVox9N6tuzJwDb9IG+FtDwr3ibiutKMutiiMcZlz+gag1FdQiJV5i0up+dnDQrtWpqw4xRnGEOMfPbNKVjj0mgdE+Cm1/FsmLIBFp8lrx+2NYtB3sNx98DgJ3yf7nWruHoGG3Ms3w/Lr4QNj0DyQHmPVXmSVwvQ1WDx1rFYTNVU2nznWHff3TxamjQGERVvqKpqVxTldmAuYAQ+UFV1s6Iot7iefxuYA0wB0oFy4Fp/x7pO/RzwlaIo1wP7gNoZuKIoGUALwKIoyrnARFVVt0TyfR5tJCbKIHDxxQ1vqQEyMX/0UUn8nHeeKAtPOEGU3/5aa9TYqMXEiHL3m28kcaDbwzZctBwqqrH1D4c/oNPE6N8f3nhD3DLCKeBwp7BQ1PpHhJ7Xi9VaxmehCzgqc+D388XWcsTbYmcYRpvoKFGOFkpKRO29YYOotrdskQVFYaGMIZmkkoZvEj3PlMqbb8piwW6X8xQWynN2uwQADAaZYLdqJcGkln70FjaHjSeXPMmLy16k0l6JikqcOY4L+13IrvxdrMlaQ7mtnF93/0rv13rz+pTXuXLQlSj1aPCYnAwnniiWro1O92th3bZGFxhedZWI8j7/PDLjxdIdo8UxadVtomSvmegfWgKzeoodX7crkEoLJcz34yNYchEIgxm6XyWbrQSy5sHBWdILuXSPJImMVsAgvxpVreunHddJArhpE6DjVAnoanD22eLAsXKlfuBi1Sro2VPEs7ffLt9RrcqH4mKZ1z3zjDh82bViKS16QeuTIGcBPh0Rq/Jg2RUw+qto+7IoTZ5WrWDuXBE3lZbWfd4//FCSJO+/L5U+cXH1E3GUlIgTRMdgnVvj2vPfEgv/3ChJ+PO7jubTCY8Ra8DV/8MqVcCx7QM3N45pKW1SDq+CdQ9IEAelzklDdcDhlbJtfSH0N+fFXXeJ2D+U4GWodO0qVVzBVKYFTXyOpu1uua2cHi17aBzgnx4pPTTPV2mvJKski0OlvvZVceY4jAajz+N6eCdia8gs9jZIbXwsFokZnH46XH21xAu0qrGCIT5eLKY16XGdiCIL1rgCr2Gi/wOw/hHPGIKjQqy8J/wedd84htmZ7+ns2iq2VcBjWse19mhvUu2oZn/xfs4ZIWsi9/vl7NniwPHss77FUpWVIvA4/XT5+VDZIZ/WSf5cQBIsCTicdSJng2LgUNkh8ivqLFONijFgktxd3FFpryS71I9wIwysyVrDa3+9hgEDTpzc8OMNjOs6Tr9dTUI3cZc6OAdwyr1hwUQYvwCS+gc/L1Xt4ko1drYIukK4P9eSsxA2PSVjr9EKLfpBm5NEYJI8wCUIiRFRiNMmwkx7mThwZf8GXS9l2setuesumX84nVLNfOutkhirsdm3WOR5VZU5jN1eV5n9/fci7njwQRF616z/7r1X1sKXXKKfWCkrE3HrtdfWiTdAnLbeeENcP+pb6f3y8pcpqZakkorKF5u+4KvNXwHiIlXznal2VnP3vLv5YGpDrJoagdYnSGKvmXLggHyOasQbPXuGLtyIcgzS/1+w56M6sVxQqBIbCiM33CC5pogUBwfB8OFynw2mBWQ4GDJE8mveTh/PPis5wD59PF0rws3rr8OmTb7xxJgYifempUXeaWF4++EMbz/c88GqfDjwA+z9Ar6+SwQYzmptxwhzoswX4ruK67vBUudm6bTJZishtSyDpxP3QNk+V7ixyrXlgTM9uHhmQleYvAb2TBeXTVtR/Z0DFZPMGdJOh0FPiuOXFu3PqJc7NWUZsoXA/E2nU1Lp+3uIj4fjjw/9Eo5WIu28gaqqcxCBhvtjb7v9rAK3BXus6/HDwHidY7o24HKjuDjrLJmMf/lleAQcAFlZ8OabspnNIuA44wwYN04SADX9qsrKZOBcskTaeixf7ttTOuL0uROy5sqiKVK9BZsI11wDS5dGLiF3xBnxhgTmCjYEp+r1Jn81zB0BHc6G4a+BpaUsoOszmEWJcpSwb5+0xPrpJ2m9FBcnQZ7KSkmMjB0rk63hw6EoLRtTqzpbzKoqV7BIhYWu8ymKjAtms9z/CwqkknnLFllc/PWXf+HGmqw1XPz1xWSVZtVWkcWaYnls7GPce9K92J12rpl5DTO3z6TcVo6t2sbfZ/+dD9Z+wCfnfUKnpE76J9fhhhskod3oC71OF8Daexv5RYVp02Qx99FHERovUsfClI3S9zn9LchZDDhF9b3qNtmSBoizUpuTIbEPxKaBpZUsfhxVLktBFc7a7kpOKrKQMlqleu2rJiTCS0truFV0DJBcKhY3CmAHyoBiEF10OjAbuMvzuJwcsbdBfk0ffCDfV39zvqoqqZZ74QURfFx1lYg+LBZ5btUqqbyaM0e+w34Z8hz8OlZbWJk5G7b9F46702WNGiVK4/Pkk3W2q3FxEow+7jgJsLnrHoYMkSDUlCniHFGTTFu/Xr5TJ50klSOjR4sLXVVVnROdO06njCdGowTUVq+G116DH34IzkrXqTq58+c7+WCdJCmMipE5B1Zx/Pd3sPDqhdq2rMHQajiM/1VcPXa9D3s/h9JdYIxFtVegBJpbK6a6+3IN3hatSKL+oYfqd4mhcN114r7RUIfJWtqtJcYU45FgBRFIBGqJoEWMKYaU2BTyyvM8HrearKzJWkN+pW9/yRYxLUJ6DYNiIM4SR2m15wTmUHnT6UR7wQUwapR8Dz/5ROaNwf7NEhLEev+pp+DSS3V2Ugxw8hcwZ1D4xLDWVOh9O2x9CSq8VEgFa+H3C+GUb6IOHMcoVpMVo2JEURRUVWVw2uCAx1iMFjokdiCrNAuAKnsVZoMZRZFk+v/9n6eA49VXZe303/9C9+4uB0QzfPWVCOSKXI7yuWW5Hq2T4sxxfsXsiqJgNVtrhWVO1UlOWU5tAh3kvhLIeaNlXN1iTkWtdUuIBNWOai7++mIq7BXSosZgpdJeyXU/XMePl/2of+CQ50X8UHNfsJfCr2Og/yPS1sRpk8SNapd9bDoLweSBYG0TunDDaZf1zp5PZY6cPBBGf+NKEJm1XQiNViARYlpDfBdoN5nHnozjxRdlXp+WJu0PO3euczcIlByLjZU2cAA33wzPPVe39lNVWQcvWwYvvyyP1Qi6S0pkHvPII/J59BaFm83w7bcSJwg2zuz90Xx1xase/3dvR+TNjE0zmr54wxgDHc+V1pFNuaBAh+HDPee0//mPJIKjThpR/BLfCTqeD/u+qrdzRjg46SQJiRwp8QbIOvHuuyMrYK/hiy+kiNf7tRwOGD9e2lh17SpjQCT45BPt93naaRIvbvQWGcU7RCi572sRNngLI+I6icNkx3Nd43oqoLpcKRW5fysGwCiDleqoa+fjtLncg2PFWal8vxRiZf3sKooIEqMFet4gRXwHf5BC89I9Ihixl+BTDOVOTXtTRxV0uVTapCb29P96BpOsZ7b8J6j2pw3hUFEqquo7T2rXTvLAUSGgEHHxRpTmyxtvyI07IyP8/a/cW2s0SRRFAjo/HReC7Xrz5e23ITNTrJ7DJdZpMhjMMO5nmD9aLCbrK8Y5+KNsLYdDt6ug6+UyqBnj61dN4Y6tNLCVZpQoTYDcXAng/PyzTPBrqiHtdvj736USp0UL+X98vG9yCgJPyJOSZOvaVdo6XXSRfuKqsLKQC7+8kMX7Fnv0YjYZTEw9bioOp4Pn/ngOgP5t+5Ndms2SfUuwO+2U2cr4fd/v9Hi1B1cMuoJpZ0/DFML38IILxLWo0YlrLxU6hxY3+ksriqjlW7aUYF24BByKIp+b2v90mCKbqkqf0/yVkLtMrAsrs1F3fwy7P0FVYnCqBlTViYIdQ0xLFJMVxWCUe6rqQHXYUZ021MrDOFUFEwqK9wJHI5HYbKgCDWObwAwa5GFV3a8f3HMPvPRS4L9rbq6IPT5oSCy01XBpuaC3cN3wsCyK+z8QrVSOEjayskQMsXy5uEXt3g3bNdyhsknlscekGtVoFJtVs1mCCE6nJED695cAVEKC2EOvWiXz6UcflbGxJjC1bJlsIMHBUaPEualDBznWYJB98/Lgzz9ly8gI7X1V2iu58KsLWZixkHJbOVaTFafqpNJeyc78nQx+ezCLrlnEca2Pq/8vL649DHxENlspJQfn8sb8m0h1FnNRp8EkOIolSAUy97amSWuWFr0l2NXmZDDriwwSEyXZ/uCDkQ1eXnll8K1TgsJSSml1KRZjXZmaU3UyssNI+U91AZTsgtLdshVtEgve8gMuwaHdFbSusdk1McpYwVwkGVojQiypLianeK885kV9LOFbxLTwEW+UVJXgcDpCcvGIJB07wjvvSEvXV15Ref+zQnIPJBEfZ8DhkO+iotQJnoxG+X7deaeIqQK63ST2hIH/ho3/brjbZkwbON81po54C5b9zdcqOOsXmHcynPoLmJOhHuKeKM2Xby/+lqrO7Wv7bMXYZ4A6I+Bxuwxgc/tKxr71KGTfzFVXidOG9/3y11/FcaZzZ1lP7dnjm5Q6VHbIo4VLoiVwE/kES0KteKPaUU1GYQZmg7lWuKaiBrwXtYnzdLzYX+TbBipcPL7ocbJKszAoBiZ0n8Cm3E3sK9rHgowFfLvlWy7od4H2gUn9oO+9IsKquS84KmHDQ7DtRUnitDhOHsv9Q9YmWjhd93V/BNPi8dT5cn8Jwb5LNcbx7LN16/R//1sEqKEmxUyuZXF8vMx3zj/fc43wwQcwY4a4j40aJfuvWiWuuyV+3Nb79hUxyIMPBreWdBcB5JXncbDkYNDvocJewYoDKxjVcVTQxxwRet4ozor1rag+gsTEiPPPxIlyr3ntNfksPPmkLOWDsb2vuY9FBR/HGAMfhwPfg+PIiTcURQpTrr76yAk4Lr9c4jCNQZcu8h29/Xbf+29ursRfv/pKWpuEu2VFebm4Vta4QbmTkVE35jQKTps4S+58U8Zr1e6mnVNEKHHc/0lrUafD1yVDr51z7TrNS3UQ01K2pP7SSlGpx1rLYIRO57Mtth9Pz70Vcv7kjq7DGaYUYqw4IE4hqrMuT9VyKKRNkjV4y+NDa//W82bY8nzo1xgiJoP2d9/hCGwSeiwRzRZG0SUuThJ0xx/fOArAJoclGcbNhvljQm+50cwwGqW32Nix0muy6mgzG7G2gcmrxLI2f3XDKqzyV8m2+k4ZBLteIRaWCT0QO+kqsbDUGhidjroggDFOFutFW2D/t7JFidLEGTsW0tM9LaxNJqkQ7tgxMgtuvXO+s+odbptzm0flWA1Op5OvNn9Va6HqjnsveafqxKk6+XDdh3y1+Stm/W0Wp3U7LajrslrF4v3JJ4+Aa9HAf8PiMwP2EIwEiiLvuVUrCRpXVwdXFa5HXBykpGi313I4Fdbv7s+qVf35889rWLlS9AZFRSotYovo0iabdinZtG2RRbuUbFomVWK12DEZHZiN1dgdJmwOM9U2E4UlFrLy23KoJI3swjT25bYjt7gliYkG8vLgiNTA+uvzrYe/VUwDlbaPPirVcNu3N+xvGjRDnocFE/TnWJufkl62x/9Penkbo45XUUKnvFyqjF57TWy6jUbPe3bXmGx69RJXjeOOk4r92FiYZpBK/+Ji2LFDjt22TSqXd+6UzT2oZTbDP/4h1ahffCFCjg0b6hylQHJ2P/4oWzDExQX+Wh8uP8zpn5zOtrxtVNoriTXFcnH/i7mk/yVc8NUFVNgrOFR2iJHvjmTO5XMY3Xl0aL9ADQ5WFHHKD/eSUSgWO3fkb2f2ZbMZ02VMg857yy1SrRnJdWe7dmIL/PnnOm2dQmXLBRTc72Y1pKqQv4q4zDkwq4eINIxWedxRIcFBxehqa3Wc2PAbLBJsc9rAXsJM427Ky7IAZ12ltaqS0eY4YowxHklXQL8FgB9axrYks8SzTYrFaCGnLIf2ie3r85uIGAnJleweeh3Z5i/AFsuV7T9imPUiKiuV2v7Vw4eL00DIgb7j/intNYu31rUcCxVjHJz0Wd3/O5wFrUZJYtf7nIXr4ae+UvnW6xZ5TEug6LTV/3qiNEmMBiNxdgVCNAI1O2WrQz7kMTGScLr9du175j4/phZZpVme4o2YwOKNFjEtOFQmwpMqRxV7CvZgMVpqxRsOpyOg80ZaQprH/7PLItM2ZV32Ol758xUq7BXEmmJ5fsLzbDq0iRt/vJHS6lKun3U9Y7uOpXVca+0TDHgUcn5zxY3cqk6rC1zuCEFQtFGEesmDpWpWC7/CDQVQ4fBfkHoqGHSyaBoCEAVoFZdJdlE7QNbu1dUNq2ieNElanrz7rufnrbxcEvezZ4d2vjvukH8feEC/eMxgEHH/b7/VPfbUkqdCeyFEyPPzFT+HfFyj0naMxBAJMXvcRAoQTjxRhMrXXSfuP//7nzh1XnaZFLz07y+tdmocWBVF7mGFhbB5s7St+PzzIJwboxxdtOglrufbXz2iOZdzz4XU1CMn3khIEGH54483Tu7t2mvlde67z/f+W1oqAuhzzpGC7qQkicfWp/2n+zkNBnFuXrJEvvver7t1q8xp7r3Xt/Vb2HE6JM9XuMFzjAdphTL6a1mj1Qg2wqlpN5jAklSvQ7fnbefB3x7k5/SfqbJXoaLy3abNGAwG7j/5X9w56k4SLQnhUT3EtZf1zIFZ9XOwD5LuqbuwmKqotnuKXfbuDb+JQHMmKt6I4pc+feDrr2XCddQ5MgRDy+PhlO/g9/PCZ6naRImJgXnzRGmZkXEUCjjMidKvdNlVompv8ORQlaCce9WwNU2qNZL6i7WlMU5EHE67vJ6tGEp2QOFm+TcalIvSjHA6fYUbIJPr7t0bz+KurLqMu+fdzbTV01A1LOLEV0H16x5Xu4/7eW1lTPxkIs+f/jx3nXBXUJWnt90mlcKNTtsxkvgp3nYEXly46y5pnXHLLRKsCVXAYrGI8Oehh8QmssYSz24Xtf/bb8PKlfK5cjjk/DExUtk1YoTC6NHJ9OyZTOvWx5GcLOeqrKwTHdQEhkAWizEx8v/CQjh8WBYES5eK8Kghi1FvvvhCXsdkqqvYb9VKLIvT0hphMdoATCYR7Q4fLr8j74qIsNPmJEibINaReuPhrvfEvnr4a5A6ztVTVOdmYyupq/yPcszjdEobn//7P5nTugfDhg2TCqsLLpBgXXm53DPi432rfpxOOdbhkO9vRYVUNn/8sfbrxsZK8Pq668TVbsECcfr44w8RRplM+pVFTmdd+7ETT5RWK2P86CH2FOxhzEdjOFR6iGpnNTHGGIa2G8q7Z7+L2Wjm+QnP88CvD1BuK6ekuoSJn0zko3M/4uL+F4f2y3Rja+5Wxn40lvyKfFRUjIqR0upSzvjsDD4971PO63tevc9tNovN+jXXNDx46U9M+uijMs6ERbyBIm1LnA7Y/j+pzLaVuIQargEpeSC0P0t6CCd0lVZfjkpdm2iTwUILg1kSciU74cBMODibLJtN03nDOyEaDN4V8ABmo5nMkswmJd7YX7SfyZ9NZk/BHgyKAae5go8KryOn19dMv3I6seYG+jobjHD6QgnilqSHbg9sjIVR70G7CXWPKYq0R5k9ACqy8JmQ2gph7T2w+RnofBG0OwNajxQRh9MuDi1ZP0vANMrRhT/RrnewPYio9dVXS8JzyZLQYjf7iz0dLwKJLgCSYjyTDRlFGR73I5vTFtB5o3Vca0yKCbvr3ufdHioc2Bw2LvhShIsKCqM7jaZji460S2hHUkwSpdWllNvKuWbmNfx02U/aJzEY4dR5sHBS6IU/itnV974KlpwLU9YDCdpVutZUfQFHQjeozJVz9LwR+twFid3BXl43F/bTxvfrOy/izFf+oKxMEmKxsSKUcDqDK7aw22W+k+im63n5ZfmcTZ8e/Bjtb91zxx3Siu7mm0VcUpM4NRikSKJXL0nq93RzeF9xYEXtz2aDmUsGXOIzBpZXl/P2qrdxusqoN+RsCO5ijySKQSq9t/8v+ERZu0ni5NREGDhQ1u5//QVvvQWzZonY59NP5XNjNotAOiZG/p+bK5+zmBiZhycG1pBFORoZ+G9pWVG664hdgsEg98mrroqcgCNQG5I77pCWZ41VOH377bIGvuYaudd7TzlmzZJig9NOk1jdaafJGtViCfxe7HZ5H7Gx4v718ssyV6n53c6eLW0Ny8o8402PPy7u/F98Ia+TmBjeOF0N1Ztew1K40TcnZLTChD9kbG5Czujuog2bw4ZDdRBripV1keqktLqUZ39/lueXPs/9J98vIo4gRLkBOf4VyJwDjsjF184aOptnfnjIR7zhdMIvv4jjl5ab97GGoh7jUpbhw4erq1atOtKX0eT54AO5uTdHAUdYPuIZM2DFdc1HwGFNrbNuDZGiIlHWb9jQfP7eIf2NVRV2vA7r7m8+f089Lju27t+KoqxWVXX4kb6OpsCRGrt+/BEuuUR+dr8/jB8P06ZBmzYSbAm3kMPplIn7gj0LuOzbyyiqKvLobxtjjKFXy17Mv3J+0BWomw9tZvz08RRUFni4d8Sb4+mR0oMZF86gb5u+Ac/zr3/JQivYXuzBEvC+tu9r+PO6yNirhjiGzJsnC86MDM8qc28MBqksqKqCqVNFfd+uXd3zM2ZIorW01PMcgweL28fEifJ7tlrD0//QZpNgUZKG+N3plGr7VaukjcHWrdJyITcXNual+bRZAMhRUumVIL+3mhh8zb92u1y72SxOI23aSKuyli19TuOfCDpv1LBrlwg5CwrCq3g3GjWSpVX58GNPqWYMRMvh0OkC6DhV2jGodgl2OiohZwHs/x72f6PvSHOExszo2FVHY41d1dUyVs2f7xkEGzpUKgF79JCgUH3HKqdT7lEteqdBTvB9i5wopNOTw7SiglgqiMWJwfVTBS0opg/bsXiXZufkSM8VN77Y+AXX/XAdVQ6pvFFQSLYm888T/onVXJck+m7rd6zKXIXNJWwyGUxc0u8Spp83HUOIEbHl+5cz+dPJFFcXAzJepiWksbdoL3annVhTLC9MfIHbRtS/p5iqSgJg8+Z6nwJFgREjYMUK/X2mToWffmq4SC0mBioP74XfL4CirZ6BwB7Xw8AnREBuiNGvvg6EXc75wcYZ3PHzHZTZPO9xd594Ny9OfDGkU17+7eV8vulzj8daxLRg+rnTmXrc1OBOEuHxaHHGYqbOmEppdSkO1YHVaAWFWoeZTkmdmHvFXLomd23wa2Ergd/GS7W8dxWeHsY4OHkGdDxb+/niHTB3JNiKGn593jTCeBYdu+polLGrHuINgPx8KbjKC1IHERcHw18fy5J9S2ofm9JzCrMv92+dMPGTiczfXWeTN6DNAPYW7aWkWvpjKCjYH7VrCsxqeGfVO/xz3j9r269YTVYqHvITj6nH72TcR+NYvLeutaTZYEZxncepOj3abN5/0v08N+E5/ZM5KmHFjeKQ6i9uZIgRQcWoaSLG+nmIiDIcFWBJgSH/kZa7zmowJWi33P3c671eWg05i2DvDNTs+VCeidPcGjVlOEpSHxSTBcUYi2KKxWkvA0clyo7XUGrGIGsqe4/P5h//kHWa2SyJtAsvlCrzPn1kDaaqdeOg2SxuYxkZIsz/8kvfNteqCk88Ac8/L+s5vTFUUWS9duON8L8v/c+VbJj4jvP5iospIoku7OVm3mEkK+t2yskhL8FAx5c71rq9xJnjKH6gWLPgousrXdlbtLd2vxU3rGBA2wG611B70d5vNlQaco7infDz4OBilMZ4OOVbaD8pMtcS6jnStP/GBSSzkYFsZCBb6UsZcVRixUol8ZTRl20MYgMD2EQKhZrz3dAvOTp2udMscl4F62DeSZGNzweIb6kq9O4txWqRID4+sDDkhx+khUqkBBxWq2+OZ8MGEVLs2+f/dU0mGDIETj5ZYnL9+8v5rFaJ8VRWypaTI2POkiVSvFCkMQVWVRF13Hqr7Oft5GsywYQJ4vZ0+ul1bRLr6wBSc22xseKcGbf0FLonarTuTT0Vxsz02+azMdmet51//fYv5qTPqRVtWIwWYk2xfDD1A6b0msIDvz7AtNXTqLDLHzbOFIfBYOCBkx/gjlF3NFzEsf5h2PbfiDnjqCq0vfUQeSW+Mfx+/UQQ2JSL38KJv7ErKt5oDgNZE6Fmkt7o9vANJGwf8e01Cf8m/AswxkkFz4kfNeg0VVV1Qe+m/veu6UEeMnkrYPFZkuRpriKOqHjjmOVIjl35+fD666Kgdjhkq1kEjBkjE+2JE6WfrdlcZ49pMEiyrMYBwZvqatm3ZuJuNsuWkQFzFxexsvU/+GbLN7UT0xrizHGM6TyG7y75LqgKTFWt642eXZrFuI/Hsa9wH5VuwXoFhRhTDA+OfpAHRz+I2U+7hsOHoVOn8IrdYmODuPc6HTCzQ+BeyaFiSYHbLSElJGvIpB3zmMg3XMhyTqScWOyYsVJJKw5zNj9yDrM4hd+x4lki+D1TuTz2eyoqPD8cF18MH34on5tIq66Li6Uq4LvvJGgJ8lmtsXrs00dcKfr3h27dpFVQWpo4a8TFyT4111jz3SgpkYB6Zibs3w+7d8siedUq/5bWuvhJlm3aqGI01l1HbKxY1MbFhe6euHWrVP5rLbjrg8EgghXNotOcRdLWLKTKRpOrSrk6+OOi4o0jTmONXTfcIN9l9/vyWWeJQCw2NoxVPDrB6rCTmurx5XlkwSM89buv7ZNJp0rI4XT4uE0d1+o41t+yHospOEHBj9t/5NJvLqXcJSSINcXyw6U/0K9NPwa+NZCCShFgxZnjuGPkHTwz/pnahFmorFsnwcH6rkESEqTys68f/eW6dXDSSQ0fu1sllZL3fg+oPlzntIECY36QIKB3j+QG8OTiJ3ls0WMef0uzwcwz45/hnpNCa5Z93/z7eGHZCx6PxZpieWniS9w64tbgThIh8Yaqqrz858s8suCR2jlfvDmehVcvZG32Wu765S4q7BUYFSPxlni+u/g7xncfX+/Xq8VeIW6bh353jSs678EYL8LBMd9B2un+z1mwDhZMhOoiUMPouBgVbzQqTVm8AbB2rQjpi4v9t72Lj5cinS2n9WVbXp1731WDruLj83TspFz87du/MWNTXcuQdgntyK/I90ikl/3Lf8bpq81fceOsG2sFgAbFQNm/yrCa9HrHh/Y7+WbLN1z09UV+9/Fm5+076dmqp9991NxlFC+9ivjyDIymOBRntdwDFLMIiTtfAsNegJhWcoCtVOKGuz6Q51U7xLSGNqdA6mnioGhuIS20HGXi7rHsCo/X3H2CyuefSzJv82bokFbJhJMPMLL/Xvp12UeC+RBmkw2z0Y7NbqLabqGouh0bd3dhxabOvPt5F4xG+f0dPixixW+/lZYWBw7UiSuSkjxdDsvKZFxMSRFnTT0R5I4d4r64dKmnBX5srKznhw6Fd94RAX5Y5kqpqbzx4yPcN/++WvHPxB4TmXvFXM3db59zO2+tegun6sRsMHPHqDsCixyPtHgD4K+bYfd0/y5QigFanwynL/Y/DjcB8UbIeM1360N07PKk2eS81j8C214Of77FaIXOl8KJHwbcdeZMuPLK8LtvxMbCPfdITs0fqgonnCAJ60ikahMSJDbljcMB770n7kw18atI4v7etmyBp5+W373JVOd2WYPBII6Z/fuLC9OAAeLK1LGjjF8Oh4g7auLNBoMUC2Vni0Bk82Zpe7prl8T3CgvhjWtu5e+TPhSHLHesaXBOunY7w0BotDALjAEu8520zU2fy73z72Vr3laPNbzZYKZ3q95c0v8S4i1117i3cC8fr/+YMltZrUC1Rrg6pecU3pjyBu1b1NNV0V4OMzvLOjdCPDP7aZ6e+S/Ndf8zz0iRYCTaszc1ouINPzSbgawJoKpil/TOO00/oe9OWD/iO9+FNXc2zWS/MU4qvI5/RSb0DcTpFFv8999vun/vuDjo+v/s3XecXFX9//HXmbZ9s5u2m94IaRBaSEB6L6IUAcFC0a+Igr2Byg9UUOyCIk2RooIUgVATCB0JEEII6XVTtyTb++zMnN8fZ2Z3trfZlryfecxjZu/ce+fMZOaee8/5nM+Z3IvReQ2VsOpm2PBnl6a2D+fy6hMK3thvDYa6KxJxv70333Rp4Zcvd53TSUnuxNta13E8bJhl5EjD6NFuIMWIEW4dv9+dXDc0uFtZGRQVxW6WykpDkZtambrZf6fhzKvaLMfVR3yNHxx0G2tWe9m922VHyMtzZdm922VKKC93J/GxE3tjmu5NUhX2knOxk15rtt9YW8U7VyxjwaTDOvwsvvENlxY0UdNNdSl4A2DDHa5xsL1MA93lTXHzPB90fWL21w3f4k/8hWuItJjR79FH4fzz259mIBGqq132lF//2n1H4j/7E05wF7LHHtt0PtGbeT/DYdcg4Pe3jiIPBl1j6Nq1Lsjj44/dd7m01DXIV1XBurJcctrI+lEayOGKMwsIBpt+U8Ggu/jetct9/9PS3NzRw4a5ERHZnWTJ/vhjN+dpSUnvzgPS0twF9gsvuKCXNq2+FVb9om8DZBW8MeD6o+7avdtl1ojPhpSa6uqGzIEcSNNeA3s3L1Rufv1mbnjthlbL0/3p7U73ZbFUBauI2OZDZA8cfiAfXv0hqf6Oh7Tcu/xevvXCt5pG9fhT+eUpv+RbC74FwPu73ueE+09o9vyFsy7k7+f+vd2Aks688ELPpu1MSYHnn4cTT+x83eOPd9PZ9PRa0e+Hv113F5fN+V7zY9f4c+Hoh1zGjQS68qkruf+j+5stS/On8Zez/8IVh17RrX39/n+/5/ol1zdmZIn58bE/5pZTbunaTvogeKOmoYbLnryMFza90NhBl+pP5fnPPc8Jk08A4Lf/+y03vXZT4/MpvhRuPOFGfnjMD3scMBRT21DLY2/8kNNr/0dO1RqMx+um4zJeFzToTYaDboBpX+p6427dXnj9U9G5tRNQx/Uiw2Z3qO5qMtiDN8Bd95x8sqvrWo6e9Xrdtdf3vgc/+xnk/j6Houqixue//4nv89vTfktHvvXit7j93dsb/07zpzXLAjQ6dTSFP+i44+LlLS9z4aMXUl7vIoNT/amsvWYtE4dNbHuDbnwmDeEGJv1xEvnV+Y3LMgIZeE3zejEYCTYeOwBOnnIySy5b0u5+X8t7je8t+h7LC5Yz3AOnp3m5YuaZnDDlVJJHHA4jP9F+evWqrfDxL2D3M9BQhfX4IVSF6WBuz1DYy/ce+Sv3vnoV4bDrsLr7bpeRKjZyuKPsg7W17no0a2b7nekWKCSHrUyhlhSCBPASxk8DoyliGptJIhpsNmqUu5huRzmZvMRpbGEqETxMYhuns5gRlDSt1FE2hW78H8+9cy4fF30MuO/O70//PVfPu7rNdV/Y+AKXPHEJFfUuUGhEygiKflDUYWaYQRG8ESyFpyZBqIPeU28KnLkchs3s27L01T56up8uv5zqrniDod2wSyINbrq5qs1xwdAJkDTadch34Zy8r7JvpKW59pi2sr22lKjg8rbK8POfw3e/2/46waALovjd72DVKtculqj2TY/HlSE5mcY23nj19e6abOFCF7S4e3fT9Cx1dW0P2DWmacBffLtyW0GsscwdXi+k+UvYdecBLjNei2vjxms4TzJ0MICvlZbZs7oqrn3q1a2v8sUnv8iuyl1trurB0+F1TsRG2pxWHODUqafy6IWPdjq9XZvyHob3vpK4Nud4vnQazq9k1iwXYNOSxwMPPeQyZu7rARwd1V2DZxIfGfSMcSOtc3LcRd9QmVIjoaZ/BdInwZsX9M2Bq6e8KXDorTDjGwnbpcfj5p0+7TT4whdcx01i5oZOjJQUNz/mrR1kuuyUPwMO+7X73Jb/AHY9HU2VOwSCIpJzBroEsp/zeODg2fUcPH4dXz97NVRsoGHvarbn1VO0x09RSSpFJRnsqRzJjvLZ7Mwbz/srswmFfYQiPsIRLxHrwecJ4fOG8HnCpCdXM254AUdMXkduxg5GZ5czekQ1o0fUM/OrDXg8HsJhFyiyZImbxuWh38E/Qu6kPTY1xcSJ7jZnjhsIMm6cC/RKS3NBAF6vO6lvaICqqnS2bl3C7t0uQrugwHWY797tLi4W3Nj5Z3H99W56sURISXEjmbpk6pWwIpGBFgamfw1y/tQ/o8njfJ/f8Yj5HJXJo5qdX3z3uy7jxdSpbrRAotXXu8CM9eubn9ckJbnOwyOPTOzrer3NL9w3bnTZAB580H3vYhepkYgbRXnGGa4Mkye79MZpaQVU1bnvb3y7lwFajpk0pmlkXTjsLpR37oSPPuo8cANcQ/HGjfD//p/LtlNX1722No/HfY4/+Qn84AedBODMjgYh9cWIG9mvbN/usjzFB2+MHz/050uN2AjfX/x97lp2V7PlAU+AHx37I06cfGKH2++t3stXnmka8QywvXw7C/62gFcue6XNKccikQhn/PMMlmxd0tgYZDCk+FJ46KOHeOijhxrXzU3PJa8sD4ulpqGGh1Y+xEtbXmLV11YxPLW780PBWWe5qbW+852uB4+lpLiRY10J3ADXITZvXs+D01JT4bzzPLCxxRPdbXTu4mitrTtbL/N5fIxIGdG91wNGpI4g4A20Ct7YVNJH+aK74K3tb3Hqg6c2juSPMRjOe+S8ZsvCkabPuDZUy3VLruO2d29jxVdXMDq9+ynXq4JV/OW9v3DrW7dSXl+Ox3g4ZdQUfn3Ipzg0eyLGlwppEyH3tO7Pg508Ek57Ez6+yaUeJtL1qVkAMO5af/hhrkE5vb0oyKHLGHMmcBvgBf5mrb21xfMm+vzZQA1whbV2eUfbGmOGA/8BJgN5wMXW2tLoc9cDXwbCwDettW0P3x9srIWCl6B8tQsMaKiEpFHgz2CCN5mPnxrJf16czW/unsX6Lel4vRYDXHzODr5z5RoOm74Z1lRTXteUVs1rvIxMGdnpS49OHY3BNNYF8dNXAmQmdx4dmZ2c3SpzUGFVYfvBG93wyzd/SXnQvS+D4fRpp/PiF15stV44Embynyazs9IdUJfuXMrC9Qv59IxPN1vvP6v+wy/e+AXr964nZENkJ2Uza/RsHtnxNv95/3lSVrzKVYdfxY+Pm9X+lJ3pU2iYfzev5l3CU8vvYO/2hZySAlP8MCFtBLlpIxmWNhZPSq7L1DTqWN5YNoN7X/U0XpMsWuQGPng87ny+MykpTdcS7TFALoVtTgHZSnHHo22HUcGFPNHxPubO7XU2ha2lW9lY0lTZWms5bepp7a5//KTjm31H68P1vLX9LY6fdHyvytHnAtmufXL599u+HvImw9QvdR64ITLUePxw8mJYdBTU70lAAIcB/zA45eUuB1Mb49r0zjgjcf1daWkuGKIrgRvgpia58EJ47LHETctsjJuq9xuddBcFAi7r7cUXu7axp5927a3Llrm21kjEUlsLkUjngQrJyTaalckwebK7rvvkJ137VluSktxzp5wCt93mBiBt3eoGNG3Z4jJ0rF3r2stiwR+xTBux6b+Mce1NHo9r+8rIcG0ABx7oMnYccIBrU5w6dThkLoPXzoHqbc2PtTufhmdnwYJ7Xb0cCXUti2JyTo8zIm8o3sCPl/yYhesXtrouMxhS/ankpOW0O0gjXm2olvzK/FaBHEu2LGHiHydy/XHX880F3yQ90I0GzkmXwJpfQdnHXd+mK7xpcPDP8PvhX/+Ck05q/buLRFx/5F/+ApdfnvgAjlDItQcP9sAQZd4YKlGIg8wDD7j5qQZ7AEeXRy93V+lKeOVkd8EcSWAK1G7zuBP4jubbTYD8fLjoIhcF2lfzr3VVUpI7sD72mBtdklClH8H7X3f34UEUnBPjSXYNhgf/DGZ1EDK7j1IUfZMBrbuqt0Pev2HLfa7h0BttIQrXQ+5JMGI+jFgA6VMhZawbmRiujUY1d+Gcw3jc3MFYdwJcnQclK2iY9i0efNB1BNfUuJOsWAT2zJlwwQXw6U+7DmdrXWBGbKqWzhq7IpGmaVusdduEw+6Yd9xxXftY7r3XdTL15hhpjMtMsGpV5w1vjTbeDR9+r/cBhd40mPszmPW97m+boNG35eXw5z/Db37jdllZ2bT5ySe7E/ZTT4WRI913IDaSMNC1rP9AU4BPKOS+F88/D5dd1vr/7XOfc/+nfTnH4je/6V7D2uajGm67Db785aZsGX2ZdaSrPvrIfU4bNrj/m47O/1JT3e/n8MPd+eL06d14oQ13wIc/SHyGs34aqdwW1V1N+qPuqqyEsWObp7z1eFwg0sSJA/h76kXmjfpQPZc8cQmLNy9uNmI41Z/Kdcdcxw0ntM7E0ZYVBSs45r5jmu3D7/EzKnUUr13xGtNHNP1Yg6Egc++ay/ri9V3ad3tSfCms+voqpmZP7dH2P/mJy4zU2TVnSgrccIMLpuyOu+5yqYy7W3enpropts44pQaeOQDq9rjU+DHHPALjzuladoYujtY6MA82tkgSOCxpGC98/gWOnnB01wsPPLvhWb7w3y80joCPOWrcUbzzf+90bScJzLxx29Lb+Paib3drm7b4PD7euvItFoxf0KX1y+vK+dPSP/G7d35HOBKmPlyPz/gwxlAfrifdn05uei63nnor5886v+NR211RXwJrf4ddf3t0yoQajG09OsIC+DLcSNSRR2MOvRVGzu/da3dTf9VdxhgvsAE4DdgJvA9caq1dE7fO2cA3cMEbC4DbrLULOtrWGPMboMRae6sx5jog21r7I2PMbOBhYD4wFngZONDa9nuKBk3mjT3vwEufaPo7PqNYLKVgVG2tuw0b1jx4sbahloxfZRCOvt0UXwp/POOPfHXeVzss3h3v3cH3X/p+q6CNmCPHHsl7X3mvw31sKd3C3DvnNmbsGJY0jH9e8E/OOfCctjfo4qj/VUWrmH/v/MbsTym+FN758jsckntIm+v/c+U/+dpzX6Mq6E4UspOz2fTNTQxPGc4beW9wwgMndPg+Wrpw1oU8cP4DjVmswpEwN79xM7e9e1vjlGLgOmFiGUviO1WGJQ3j6nlXc/PJN1NW4mPePDflYnU1/PCHcOON7lo1YcHkicqE0I+ZHX7++s/55Zu/bAzuG5U6iqIftDF8O85hdx/GioIVgJui5/MHf54Hz3+w12XpUCL2YSPw/jWw9cHmnYreVBh1LBz/FPjabiiI2Ag7ynewvng9px9wRrPnympLyUrO6l5ZlHljyBtyfV41u2DxUVBb2IvM2B4IZMFpb/co0OnWW+Hmm3vf95GcDJ/6FPznP92bwra62gWXb97s2jR7Kz3dTYE1e3YbT1oLtbugYr3LelKxASo3Qn0xNJRCsJxQfS3LN85gzc6Z5JUcwNr8uWwunEJJ5TAawj6sNfi9IVKS6pk8agczx6xl2qg1TBu9iaNmfkTWsLCbKsyfBUnD4dIVvRooFsFQQyoN+AkSoAE/ETz4aSBAED8NJFHflEGqLYWFMCILNt0dzf5a1zrjUdIIGH8BTPyMm/YMXP+f8brjcReCKQjVwqNtNyhuCMKPUz/DcxufoyHc0HheBhDwBkjxpfD3T/+dz8z+TOevE6e2oZYfvfwj/rb8b21OOe41Xq479rruBXGULIeXjk1cG53xuf6CT65ygVu438mVV7Z/zX/aaa5tMT3dBeb0Rizb8scfuzbOjS0HYgwATZvSgSFXkQ0iS5a4iMDq6sRUKInk87lGtYcfdim/+0TdHlh6pZurfSA6+r2pkD4NjnsMMmf0+ctFIu5A+b3vuU6m/p5Kxet1HXRXXOFOpIZ3fxBf1+1eBKt+7uYfNb6BDeQwXtc57klyKXrnXO8i8vdDuhBrMmB110c/hbW/d0N24kcNzv05HPhN99iX2ngCligFuyMsONpDSUnzDrnRo93UTief3NSRP1CsddN7vPhiz9MLpqa6OS7bvLDq6IVfPR0K3+j5fOrG54JuTnuzZ9NuJTh1ek2NO8dYvNiNOMvLcxe/1rqT+fR0N4fy5MkuG9j48a5TduzYpnSIsewq4bAL1igocCmlt29312qxDBSFhW56n7Ky5mUYP94935URbD0RCxJqmdEqFnQaifR8apa+lJfn0mk+9BCsXNk8k0047LKEfPGLLpBqbA+n1mT74/DO5W4e0t6OuvGlQdYhcPrbvdtPL6juatJfddddd7nz1fhz1SlT3HElN7dvftOd6mHwRl2ojuP/cTwf5H/QbNqTFF8K5886n3+e/0+MMVjr6sfiYncrKXF1USjUlD7W64XlVc/y660XE4w0tYwYDGmBNN644g0OG3MY9aF6Tv/n6byx7Y1W5ems87rl1CwAw5OH89HXPmJ85vgOt23Piy/XcPVXkije6201D3V6usuudf/9bp7o7rLWjQRbsqTtlLxtSUlxAXZ//nN0Qc1uePtiKFnR/Jph0iVwyC3RbHmedjtbupp5I2szlLf4eNMD6Sy/anmzwJuuWLpzKWf+88xWwRsTh01k27e3dW0nCaj7rbX86q1f8bPXfkYwbkCEx3iYPXI2E4ZN6HD7jwo+oqC6oNn3Lt2fzmMXP8aZB5zZ7naFVYX89u3fcueyO4nYCHXhOlJ9qRwx9gjuPuduNpVs4v8W/h8V9RXUhetI86cxPGU4N55wI5cdchn+dlIpx6YUXLeuabTgtm1uIEQk4s5lsrNh4tgaDhm3lAOz3mBW9gsMD+ThM/WErY+6cBabK49jXflprNlzLGu3TWzsyG1ocA2N/XF+0I/BG0cDN1lrz4j+fT2AtfZXcevcDbxmrX04+vd64ERcVo02t42tY63NN8aMiW4/o+X+jTGLovtoN2opEXXXzg//h39FdApIaxjxyb/hSR7e+FvxZDdvzwmXbnDvPT7w3YZpuPgwkobVwxhgxkyYciQMHw8ZuZCW4zpIPD7XqbDlAchr3lm9vQGm5RlC0f0GjJ87FlzH+RM6HhXz2LaX+Nay3xKMtN3wN88/m1tG38icsy5uM2U5QHl9KYc/kkMouo8kbzK/Ou4OPjfzSzQ0uPoqNoK2vh5mz2l+jPl4pW3MKgfRe0+IT784l83la6Ofl+HUqaey+IuL230voUiISX+axO7K3YALYjxh0glUN1Tz7q53idgIHrwkeZM4fcKFjE1pynZjLdRHank9/1m2VW0gbEN48JLqS+Oz43/IW2u2sDX5cYKeivZevl0p3nSOG3E+8zI/ycbXj2LREzlUlQUYP95w9tmGo45yHXoTJ7priFiq+Fg2yfp6d8x5913Lp2d+jqKtj7gdp03mgPM+buqkaaczPRwJs2bPmqbAHo+fGRkjIX8RLL3cfbe8yXDCc9Hz6xYXrGXxcxmbxvtntrxGeiCdrORMvN4kxmSMY2TWgRhvoM3ggPpQPTsqdlAVrKI+VE9hVSFXP/Nl8mv2Nq72hRln89DpNxMKGYJBQyTizoOsbRoq8puP7uI3H91LKBogN6ZuAicMO4SIjbA5nEddapAIljCWiI2w8ft5zYoy8/fT8BoPHuNlevpkJqSOxQdcWrUUH2HqGurJPeyLZE88CWMMxhgyxp3YbB8VO19tzFhjjAcP7uD9639XsnqDj9q9G/GO8HLqMTPAm4o/Kc19dNYyN/wg8+0dgMVDhFXmQv7n+QGZKSMwGNbkvclLxf+k0OSx3bSeRzr/t5AbPSUpSIMxP2h6Ls0zjIMy5jEhZTpHZ52GP5jO9g1FBEhmJBP40rdmM2xkRrvBGzvKd1Bc67KyVAWrmDVyFiNSW2QBsxEXsJjSRmaa0pWu/cH43PHKn+naOBMw/beuu5obkn1etQWw+BNQV9D9zmJPwGXcOP1/kHFAj17eWpcp4rXXet6u5/G4tqqPP+7ZYKCCAtfetWdP72KdUlLguedcVoNGFRvcYLydT7pADXCfW6TBBSxkHwZZB7k2lMwDITDCZZ/wpQHeuDaaNgpmvK4t2HghVOMGmDWUQVWey9xQ/jGcv7jfs/y2kpPTlBEqEnIZNzb/DYpeA+N3bd3NgoeMG5iYPhnSprjAg2GzIXWC66vx+gGva4+NNEBDBZSvg8r1sOEvrV5+UTWctdt9gumB9MYp3qyFYLiBw7NP4erc+whVjKS42H0PCgrctX4o5K7pYzG7keglUCz7CLj7ktR3eH/KRYS8FWA9jW8j4qkjYupJMyO564B8Ro3wMWKEy/I1ZkwHAx+3Pw7vXJaAAA4DSSPhrBWQ2rzB8PHHXTBFewEcPp/rh/5//8+dCxnTvd9XRYU7d3rtNbjlFng72kQ4GEIjFLzRgSFZkQ0ihYXuh/PhhwOfkSEmNdWlyn/ySdeY1+e2/Qfe/UobB/e+YtxF05yfwOzruhbtl0A1NW5U9G9/6yqHRKXyak8sReQJJ7hpXA7o2flXz9TtgR1PwKZ7XXpS40n8aOA2GfClu9eb9FmYcjmMPCohFzNDmS7EmgxI3WUtPOyl1Um6Lw0urmpzkw51sbMC4Lw/PMlzH36SUKR5Y/lrr7k5If2JjRXpsfJylwWkJ5lh09Lc1GRXXdWDF67bA88c6C6MesKXAeesa3Xy3GV9MO99vGDQpUn86CM3X2gsCCM/36VNLC1tysRhjKs3jKGxES8ScQ2bSUmu02TkSHdhMmGCO+k/7zwX5b1+ffNzmREj3Cjur33NNYomJXUtZXFXVFe76X++8hX3XuLnFF2wwGXlOP98d3EWiSTmtUMhoqkuYdgfb3Jz4PVCHUlUkEkNqaRRzTDKCdDJeVBlZdeGDlZuhmXXQtEbPZtGJRb0ePgfYMpl/X6uFE91V5P+rLvuuQe+/W0aO4TAjdK4/nr4+tfdMSI9vWedoJWVrt7p1m+yh8EbERvhoscuorK+Eos7764oB0/FZEYv+wsb1gYoKXHHlIwMVwdNnOjKlpTkyhmI9o8Eg+62JvAPNqU+TH1dU4ew1wuLvv9r5k2bymkPncaqolXNRuuk+dJ45//eYebIjkewVQermf+3+Wwu2UwE15rkwcPw1OG8fsXrzB7VeXRiKBLi/V3v8+KmF3lszWOs3bsWwl6yt3yV4VuvonrHdFL8yRw5z8OFF7rMW72ZFqesDI4+2nV6dRbAkZIC8+e74MJmWZ9sBDbeA2t/6xqbIw1N14XDZsOYs2Hc2a6xL3mMa/SMtNUiHL3O+0/zL1fIQtImaBkaE/AGKPheQbfnMN5UsonD7j6sceR5TKo/leofd/Givpd1f3WwmkueuIRXtr7SKqPMz078Gd//xPc73Uc4Eub8/5zPy1tebvZ9TfGlcN2x13HD8Tc0mx/648KPufjxi1m3d12n++7IhbMu5KELHiLZ5/6f1q93DYkvvtgUfJmZ6c7pLrzQpWmOZdmytinINJbyOf68JRJpuo9Emjq0fT73u+6v7EH9GLxxIXCmtfb/on9/EVhgrb02bp1ngVuttW9F/14C/AgXvNHmtsaYMmttVtw+Sq212caYvwBLrbX/jC7/O/CCtfbxFuW6CrgKYOLEiUds29bFoKZ2LLr3cc5Iu6hpweda/EZyc5s6M3JyYPHVsKr1eVrBVU0dsj0R9ML1V0NJdBomfxh++QqM7ORUqygNfnoSNESPtW+MPIKKMesBi8cDNx13OV+b/ammTIuN7RaGWEd+xIY55bnryKssAiwNe6ew69alGBNhVMYeCvPyIVjmbg0VsOAbsDcaBDEyE9693e0rtu9ImDo8HPPCzymuryZivfg8qfz6iCcY6zuI+noIf+1aTLCeiCf6g8scBr/6Fe+WPsdft37DdaoDpe+cT/2UpwCLzw9fPPYkbjvzNjKS2h/euXD9Qn708o8as5FECmeyfbsB447Ul30mh+8c9R0OzT3UbdDy/7iggNVFq/nj0j+ys8L9hxhjeHFT3HQvdZmw+wjYOwsqxkHpFKiYCLXDIeLDWC/WhMATgrQ9MGwbZG3lK1c8y73b3fmWBwh4kzh3+hlcNONTnHPq90kqbgrcq89O4ic31nN/BZRF3FxCAOenwZMtvmuxFO4p/hRW/7yE0VXuvRamG6b+yEttONSqO2+MF3J8kGFgeCCF3PRcMgPppPtT+O7XPyS93NWV1VkB/n7fiUQiFhsNqAiG66lpqOPP74Qo97sypyR7eOnrD3LMxGPa/b8BWL93Pec9ch510QEnB+1N5llf+8f+joIdYvxAMD5W8oz3YMSRTX938Xd80+dv5Ca6cB3mA4YD5UCLU4bDLjmFFTOXNP6d5k9j1qhZTMicQE5aDmkBl/krYiMU1xZTWFXIppJNbCnd0izzS1uGJQ0jIymD5TfmM6rSfSOKMjzM+mkWZXVlrQJ1Hz7hu1ySnQZ73nC/3axDIW2S6/idfw3sacpAw+iRsGlp9DyoAYJ7XRBsxQaY+W0IdHF+iXbouqu5IdvnFaqGZd+CbQ93vS3AmwZjToMFf3cZHnqhvNwNqCooaOoc7460NNfWc+CBPS/DmjUuML2ysvN125Ka6gY0fPGL0QUV6+HNC12GDRuOyyJv3HTMM78F6dPd9YkvLeED8lyjXHWXp7FpprPUJYnq2440QPF7bkBvwUvY6m1Qvwdr/FgCQBhPpAbT6oqsg6LRFM4YU9IA/9x9BGv8t/DBB7B5E5RXgMdAui+bBePnM2+e+/5MnOjaL7Oy3LVFamrz64WWt1iQqzFQF6rlnd1vgYkQDkFt9Nq/qgqqypL55qdP6N6UIWt/Dyv/X++mOfZlwBlL3fVxG5YscZn/q6s7vi6fNQtOP91dZ82Z49pBYoPgGl8qeu1UXOwCNZ56Cl56qXV7/WAIjVDwRgeGbEU2iEQirjP/5z9v3kDa37xe10B53XXw05/289zWtQWw/Huw478uZW4b6U97z7jOiBFHwry/uEjIAVRU5BrGb7vNNUT19ISiPamp7rt1wQXw3e/CEUckdv/dVrMbtj/qAjmqNrr/i0iod5VWjPG5bAWxEcbjz3cnT6NPGNAOp8FGF2JNBqzu2vYYvPd/7uwmVEVjIMf4c2HOj2HYwV0/2e9G8Mbld97Pf969mPqG5qNWn3jCRcUPyCjqdixfDiee2L1jYmqqO0H9xz+6l1Kxmd0vuIux7h6TvKlw9IMuHWBPJSp4I77Bq5tCeAkSIISPMF5C+PASxkeo8dZuYEFhIXbUaF591WV2eucddz4Rm0rH63Uj3Y491gUSzp7tLqDS093zDQ3tv02Px3Wger2ug3DPHvjgA3jzTbj7brfOli3uu/z66250xu7dbpukJDdi44ADXBaLadPcBdykSe474/M1vxnTNPouFHK3YNAFuWza5DqX8vNd9oxXX+3ChxoJud95qArSOhj9XLIi2pDucfexxx5v9N7vAhJ96d2v04redAGyNTujjQwdRYwadzFogzDj2y7ItStzlPYx1V1N+rvu2rrVze+7ZEnT9Fjgft8nneTm9D3iCNex6ublbdo21pEKrpPe43GBY6tXuwDxhQtd4Fgz1rog39jvJlQNDVWuoWpMO3Ozb38C99vxNv/9GI871/Sns7c8k3sfHMWf70yjrNzg9xuqquCYY+CSS9yxafJk1zhRW9u84SbWMQxNncHxjTvJye5YsX07ZI3P5/j7j2d7+XaC4abWkhRfCk9+9knOaJGCuz07yndwyF2HtEoXnx5I58UvvMgnJnyi2fqRSIRX817l2Q3P8vq211m9Z3Wz189JyyHFl0JeeV7jMq/xcuCIAzl+0vGcMuUUzp91Pj5Pz3u1y8rcd2LjxvYHJKSluanUnnqqk0xfpR/Bjidhx+OuodSbEj1A1zcFbCSPhrTJ0UCzgOvwtA1uSs6qra2CMXeFYHoe1LaoazzGQ8MNDd2ezqOsroyc3+U0+5zBfa6V11eS4u/CiVUv6v5tZds4+cGT2Va2rVma4FR/Kt856jvcfOKNECx3n0Oo2h3/bSR6H/fYGIKRCGc8812WFq6mLu79eI2X06acxH8/+zTlwQpueeMW7lp2V+Mo7Bifx0eqL7VZkEe8cCTcapoDcGn7bz75Zq449Aqu/VqAe+9tvt3NN7tpf4aqfgzeuAg4o0UAxnxr7Tfi1nkO+FWL4I0fAlPb27aD4I07gHdaBG88b619or0yqs2wteB71xPYdKv7I2kUfKaDKSxW3tRmB3Zdg59kvzs3D9lkPGe+jWfE4QBYG3HHzMbRvbHfX/R3uvAATL17TfP5pt/mnXfC1Vd3//2sX++mrayvd0GSY8Y0BVCfcUUuyWVN1yd1WTksur+g8RAY60TxeOCMMzoI7OzGFBT1oXqW7lzKncvuJK8sj82lm9kbl3ki3uSsyUweNpmDcw7mh8f8kLEZYzEYlucv594P7uXu5Xd356PgsJzD+NlJP+PIcUeyeMMzbCndzEMfP8KW8q4HMM0dOZOLZnySAzJyuWRzXBTEpeGOByS10z7wg3//hifX/YBw2HXY/PWvTec51nYciBs75wE3uG8wTEc5mIQiIVYWruSm127imQ3PuIUWCKZBKBkivqYbBkwYPCFm5RzI7878FSeNyyBl0cFNOzzlNcg5odVUTo06bAPywOd6l3WxP6+7jDFnArcBXuBv1tpbWzxvos+fDdQAV1hrl3e0rTFmOPAfXHBiHnCxtbY0+tz1wJdxMVbftNYu6qyMQ6X+stYde6uq3C2W1TOp4g1G77qe5NoPgQge2zyKKUIAa/w0JE1jz9hbqMk+B4/H/c7T0lx7TUpKz9rY8vLceX9hYdezzccGByxa5ALDe+u99+DMM13bYnf62lJS3MCwZvXhi/Pc9Bctg7dyT4OTXhzcg0X7IHijtNRlPV692mXJ27rVdeqXlrq2u+xsl/F91MgIU8bkM2lEHhOHb2V02haGsZpkivCaBjwE8dCAIUyEgLtZPyFSqDTTKWmYwe7yyWwvnsLmwsnsLkrj3XfdtXdSUvPsLqNHu++bta7dYiAzS7fr/W+4KdR7NMAqFU56AUYf3+FqxcVwzTXwzDNNbRudSU527aTDhjW15RYWusF/7WWEixkMoREK3ujAUKnIhoK8PDdS9OWXO5+XONFSU+H44+Evf3GdGwOmaquLQtvxePQqroc5tuIZn+v4GHkUHPobGDG42v/DYXdictttrjPK53MnXd2dSscYFylXV+c6qr76VZcuKSur+2Wy1kXclZa6Bti6OvedrKtzt/p6dyBvaGh+Hww2NWxHIk0dYJFI04hurxdSfaWM9K9lpH81owMrGBNYRrZvIwFPFQ2R1GibgsVYCyZ2jPVEKwSDx4TwmiAVoQnsaTiY3fXzKQ7NYU9wDiXBKYQj3sYyQFNaer+/qSH+u9/t/ucy1KkDrMmA1l2REBQsga33w9533LyUsY6JwHDIOhiGHeTml8w40KWSSx4VTcUXBmKN7tEvuMt529Rx9XDrzt2qujTO+vULLN95XLM0+KmpLnnA177mfqsZGYlNJd3TqSs++sh18ldWdh6pn5bmouFjjVC9suFO+PD73RidkAoH3wSz2xha1B2DIHijV+LTJuK+S8uWwdKlLrvLsmWWwkIXCZ8UiODxRlwdEfKQmellzBh3cRc7TsdGyoZCLlijsNBSUx0h4I9gDITCHurqPYRC7XQUhd1FxubNbnqX8nIoLomwcks+H28tYFt+NcGqNEwwk1RfBmm+DJK8KRg8jR21sWmEsrNdBpFRo9zF4PDhMCKrlktOe4+kunVQttKNvqjb4zoNsw52c8QGst3vNjnHPT78yuajpmJGj4TN78b9pm1Tp1ps7tBgOQRLXEPdgdeAP5OGBneBvHu3CygpLnadp4WFLji0trYp20lammXqiLUcNHIRR4x6gkkZ74P1EMGLIYLXNFDRMJqPi8/ho+JPsWbPCewtz6C62n01/X7X2TpQVHc1Gai6a+tWN63GAw+475ff784P4y/ks7Nhxgx3wZ+U5H5HsWkCN21yv8kYYyB7WD3Fr97oOuorN7jfULjGBQ1lHwrJuS71rC/dTZcxcSYUtujcyslxP4DGHqDobyjS4H4/4Tp2ba/jkGMmUV1tGrPdZWa6ILOJE109mIh6r6yujBl/mcGe6j3NOqlT/an84qRf8N2ju3fi+e7OdznpgZNazbXr8/h488o3OXDEgSzZsoTH1jzGY2se6/0bABaMW8DV867mtKmnMS6zRfrFcBCCxRAsdce6UKW7b6iM1pkeGkJefvu3g/nFHYfj90WorA4Alsy0Bizwxx+/w5cu2hCdxsC6QFV/Bsz7avt1VwAYBYyO3sYA44GRuCG83ujN4tJqhIE6oAjYCRS4x+9bOPVzGVQEm0eGZgQyqLi+++n5rbX4fuFrNXo2PZDOR1d/xNTsqZ3vpBd1/8f5H/LFJy7Chmrc5x8Ogg3xqZHj+MXskzApudEsJaPd78g/zAW6twx0su6Dqw1Wc9nz32FD6Za4II8Qfhvm0Ekn88DHD2OtbQwUSfImkepP5R/n/oOzp53beM0Y6yxoeWuI1HPPxhv595bbCYbrGn8jPuMjM2kY3z34NwTfu4LHHvWwaZNrNE9NddO3nn8+zJ3rfu7GuONK7NgT/xHGdwTHf3zGuACyQMDVkyNaZKbvK5o2pYnaDDthrRvBG65z7V/hOhrPBxvvTdw1n3G/48o8eOUk93v1+F2n74gjo+uZaAajUNNrrP4lrPlVq5f/65Jvs23kHyksdHX5YYe5c/Dk5KbfYnxAY3wQY21tUzvRFzbdhP+XvctKx403wk03tf1cN4I32tXyWqnFNUxbgqEg9390P4+veZyXtrzU5joHjz6Yz8z6DF85/CuMzew8E2MwHGR7+Xa2lW1j2vBpjM8c33YApbVQvRVqC129G65z//fY6HGauA5D66ZNbDOTZO879aW1cBj+9z+XNWrZMlc/TZ5sGTPGBQWPmxAhaxj4/BDwGYzHEA5BOGyoqXHXcXl5EXZMOoNtJSuhoRyfN8BlM87iMwd/AU/6ZNc+5M9sqrufnkxNTSF3l8PiuCaL01PhO9lDJ3jDGOMFNgCn4c7Y3gcutdauiVvnbOAbuOCNBcBt1toFHW1rjPkNUGKtvdUYcx2Qba39kTFmNvAwMB8YC7wMHGhtx3OMDnT9VVUFK1bAhg2uk3zDBtc+UlrqjteTJrnrmuxsdziLzzCQkeGO4x4PJNevIb1qMWkVi/HX5wGWUGA81RmnUp1xKjXJRzRmMq2sdLfSUjeNZGGhmyKhJ9dLe/a44O6tWzufOj452QVuvP56N6dB7sTu3W7A2ubNnWe8T0lx5XjmGRfk38zmf8Cya6J1dtyAmEA2HPckjFzg6mtfN+ah6MaAvCY9+J0nMHjj0Ufd4I7SUvd51dW5vqCMDPfcvHlNfVOxbHmxTJa9ueaO9T2FQm4g1fe/7wI44suQlOT6NU87zQWRxgIXPB5XhlgbRU+FQk3Tqlrbs/42rIV1f4CVN3Q9M73xu6xKJ70Iw7s+MnvpUndK9frrTYPUEi01dXDMJDGgwRuDPRJxoCuyfdE777jovk2b3AGoJymmusLjcQe5iRNdhP0JJ/TN6/RI9XbY+hBsfQBqdrhl4W7ML2L84A24Bt9Jn4Opl0P2IX1T1jgRG6E6WE1VsIqqYBWVwcrGx1XBKirrKymqLmJnxU62V2xnR/kOdlbsbJzvkLAXdh9JIO9TeDd/knDJRBqqMvEFwvh8NjqiyUSncfRQX+shNc0ybpzl6KMMn/60h5NOcg3n3XH22fDCC82X+Xyuco0FXcTX9R980H6QT2xu8PjRifEX+B1qKMdbtQbTUIKJ1LtGjEi9u1DxJGE9SeBJJpI6jUjq5OiFa9viU13Fj5yMnTjsjxRF32RQ1V3hoOu4qtoMlZuiHcGFhGoLqaveTbi+GBOuJpkIfo8f600CTwDjTcLgiTb21bvR8pEQ7U4/lZzDGyML+MEP3AVgcrKbsw7cSedpp7ljwTHHuMaGYLB5qumUlLYzMoVCrq4KhZo6en0+d3H0+us9G70FbvvPf96N4mrrZNDncyffv/mNCz7pdeBGzMa7YPl3Oz+R9qbA3F/ArO+1v059MVRvc9ml6gpdY1qwFOqKoL7U/Z9ZCyc+3f4+3rvG3dvYqLnogTRc50amRxrcsdCbAskj3ei9QJZr6EnJdR2g6VPB20bYeSKna6kthD1vQfFSN1K6epvrjLUNkH4ANnUSFZEDKKicSH7FRArKcykozmZHfjIlZX5CIQ8NDR6CDSZ6cRXB543g90cYmxNk7OhacocXkzssn9yMbeRkbCftmF93OMKhKljF4s2LeXjVw7y46UXCkXBjR2iqL5WakGtBSIp+NvPHzeeLc7/IOQeew5iMMe2/12XfaHPuTY56AKZe1vT5JexL6ZSUuMxor73mzhFjGUlGjYIvfckF4R54oPs9x0YbhMOtO7GINOAJl7vvjyeA9aZjfZmNxY6JXeTGLrQT/Ha6THVXk36tu2zEBVVXb3PHrGAxNJSzaZOPj9aPYu2WUXywbgKrt45le342Hk8Eny+Cp42+lXDEUB/0kTOikpmTCjl85naOmL6Zz077WtOK3mhD12dbHPAjsbotPmARwMDTU6C+g9HKwP82HM3Jt7xCfahpKO/06a7xMxxOXKbBiI3w05+dQPB/bzVbPq0Url5Gq3SvXfHSVFjU4nzbAos/MYrVZm+zDnC/153cHj/peM484EwOHH5gu5kQAHZU7OClzS+xeMtiguEgoUiIUKRpSNpRwyex5KCDSa3ZBtVbIFTrOg/m3+1SeSePco2VjZkvwu7/CUtVleXFRV6Wf+jB54Wjj45w8klhkpJiJ+Y+V2+F613gwaQ5fR54+NRMuPx8Q0VS87ptfOZ4dnxnR4/2OezWYVTUNw/8GJY0jGcufYbjJh3X+Q56Uwev/b0LNo2Xcwqc8nJ0+0hCRgB+sHs5F/3nUmpqw9TVQ0P03DBlzzEsKL2NiaOzGDnS9YfGOg0yMppPaxKbVzochrWlH/GrlV+npL6wWXBHoGE0a773NtnZhvJyl8Fl82bX4L5rF+TlWTZvq6esPERqGmQPj5CZYfB5vQS8Xvx+Hz6vwUYMkYhxCe6iQaDFxa6B2edz5Xzkke5fK/dEP3aA+XCdWKcAu3CdWJ+z1q6OW+eTwLU0dYDdbq2d39G2xpjfAsVxHWDDrbU/NMbMAf5NUwfYEmB6Rx1gg+q6a19krbvGqM1vyrgTLIsL+qCpDm0MAjHuuO1Lh7Fnu7azweCmm3o9LSEnnOAuQnujnSCS2oZant3wLD9e8mOKa4u54fgbuPTgS8lNz+3d68mQ9Mc/ukFhsc7AWGBhdwawWAt/WPp7blt6Gzsqms5HDOD3+PEaT/Qc0p31hSJhGlocbg8ZcQD/7xPf4YLDru513a/Aw+YGuv465BBYubL18tmzXTAHNLW591X29Da/zzYWQBZ/a5HhLdp21dAAf7w9lZ/9yk33UVPTfGdJSRaPx3LF52v41S+qGDbM0njl1Bhw7HVtXD0UDsO//+06/GMBh7GObI/HBY2EQm7K0B/9yAW/tKkqz01Fs/k+qNnuroPC9S6YI2UMTLgQRh8HWYdA6nhX7kiQxizheMDji14LGXhqQg+CN2g9dVxnEhi8ceONbuaAzMzmgzlyc92YCnCDpxI5ZXJLoZA7r6+qctk/PvzQZePdtMmVobTUvaURI1zGqNxc93jEiKbrlVj2Xa+3dSbecLipb6uhwX1fCgpcMFJxsbvt3NnLU43C113AZbA4mpW7LcZNB5pzChx1n7v+7oGtW10mmfvvd3/HBl/3VCzT/4gRrg4cDIOjByx4YyhEIg50RbYve/999+N66ilXmXQWpdhVKSnuR3bOOa7iWrCgbxvkrbVUN1RTXldOeX15q/uyujK2lW9jw94NbC7dzPby7YRtGL/HT0OkgWl+D1eOHMaJqT4O9NUzPFJNxHijHffGdcxjMZEgNjkXM2w2ZuTRMOF8V2F2881tKd3CT1/5abPAi8r6ysa/axpqmjVu9rmwFyrGQ9UYCAfAesAbhOQyyMqDQOdfDI/xkOpPJT2QTkYgg4ykjMbH6YF0Ku//N88/52k2YsnrbQreaNlp8957roOoZWCRx9NUybVMLR1/62uxssYHbsSyfsQ6o/ZHiqJvMtjqrkgkwkeFH/Hurnd5a9tbvLX9LbZVbGu2TrI3mWC4Dg/gNa53cFTqCA4bO4/jJp7IEePmc/T4Ywj4O88Nt3ev6wBetMjNXRffERyJuN9xVpY7yY2/paa634/f35Rxp7rancjG3yoqmn5vZWU9/1yshf/8B26/3QWN+f2ubJmZLl3/j3/sIqoTrngZvP1ZF3wQajF/iy/DXTge8wiM+kTrbXc8DRtuh9IV7iTcmwwY1zA64QIYfrjLxuBNjgbdhGDC9NYjygFyRsOOjdF4jdjBM/4gGh155/E3H0nbVYkI3qgrcikk64pcgEhDpStj+lQ4+SV30RqqcWX1BNw6ve1QioTdBbKv9QSTy/OX8/v//Z7FWxZTUlOCx3gI2RAm+m902mgOHHEgo9NGUxmsZGPxRraVb2ucG9prvFhrSQukceTYI7l2/rWcO+NcPPEtFtU7YOfT7v+4bIVrLG+oAF8mTPqsmyIldSKkjMH6M105fangSYn+X0UbzWP3q36BWfWLTt/2ix+dwVm/eRGvt3nGgy9+ER58MPrR9DDbzWCmuqtJv9RdDVXw/Fw30tOb5hqYbAROe7MpEDpU3dhRD2CtYXe+h/JyD/X1hvpoJrakJEgKWFJTLRPGu2Asx7jjgC/ddTJVbITa3UTqiyksXUdB+XbC4TosEULhOpI8Afz+NHy+NDweLx7jwWM8TNrxIL5I5yNW/v7al/jJwr9TXd00l+u8ea4OOessV59FIq6BqbvpVRsamq7R8vJcA2tZmWu02rvX7S8zs6lhKJaK+Jvfavv4++9/uc80PgC6vr5plE84DA3vXcK0Nf9ptl12LZyYB/5IGzvtQMTA0vGws0UjZVYOnP7l6B/eFNfI6E2Bz8Q1MIajgdaxQAHjbTquYeDpSV1skOziCLJe1Fl/ff+vfG/x96gLNR8McPDog1n5tTZaxbtgwh8nsLNiZ7NlGYEM7v3UvXz2oM92voPe1MF1RbDlARc0Wfoh1O9xn/+0qyB7rguwSRnj6iVfmsteE5tehugF2cc/g9U3d/gyv3vuu/zg378nEGia4uwLX4CHHnLP19a673Nvrq2sdd/v+AbejcUbuWvZXby5/U22lW1jb81eIi3mxx6RMoKahppW2WlS/amMTh3N7FGzOWv6WXz1iK82Bjf1p34OPDwb+BPu8uA+a+0txpirAay1d0UDD/8CnIkLPLzSWrusvW2jy0cAjwITge3ARdbakuhzPwG+BISAb1trWwwDaW6wXXeJiCTCjh3w29+6Ufr5u0N8/2s7OOP4nUwbs4tM/25S/NV4sNhIEGtD7rTZ48V4fICXYNhPdSiHEePHYVPGsnDXKi579upWgaHtmZA5gcVfWMzMUTMT9p768brrQuDMFtN2LbDWXhu3zrPArS2m/PoRLnijzW07mPLrL8DSFlN+vWCtfbyjcg50/fWtv/2b2x/aBPmHw96ZUJ0DDakEkkNcfrnl0EMN48Z5yM0xjBhuSEs1pKQYkpNde36sDT4SHQMU3yZv4pojDNF2cw8Eo9cdtbWWmhpL5urLGVn5r7YL2I0ggsJCN3Xmv/7lptqKRGD8eDeF5YUXugzi7dr6EHz/Mvhvl1+uTQ34eJ8jWcTprOBQwviYwlbO5EWO5w0yaK8THZ6cCRdc4h57jZdcv5+DkiwzvQ3MTYLZAcskH4zwWrxAAxDyD4ekkRDIwhvIxpuUhQlkYXzpmFj7HR6wYawNQ6SeSH0poWApyQWL8bQYmPdyDZy5C3IyxjIqdRSj0kaRnZRNWlIa2cnZjE0fy9jMsYzLHMe49HGkJ7kpcHM7GpgE7CrfSVF1EbsqdrG7ajc7y3eyt3YvJbUl1IXq2FO9h6KaIvZU72HWqFk8dc47vP++y+ywdKkLti4qcte/Y8e6KW8mTnSBEzk5rpN/+HAXPJ2e3jS4Nv5mTPNM7vEZ3cvLmzLB7N3rArtvCN/UabCnBWpIpYThFDOCWlII422cJjr2OHaL4Gm2xEeo1d/DKGc4JSwZNpnPlb/X9vesoYtTjEXCsO3fsO6PUL66qe3Yhtx9zsku0/Pww9rcfEf5Dib+aWIXXij2eh4oOBQ2nw5rPgNFB7nX8dW5Dyuc5PocrQdMBDwh8DaANRBKAX8NjP8fzP4vTH0Jsrfh9/gJ3tCLSJAEGcjgjUEfiTjQFdmQ1PidsXF/t9Up4xQXw6OPenj8CcP/3jEEArGUQF0LSvD7LSkprpNtwXzLhRdaPntxhFFtBmyZ5vfGUF5fSUltSZuBF+V15ZTWlfKPFf+gpLaka++/lwww3gcZHggYaLBu/uLtDa71oCNZydl86ZAvkZWcTWbSMLKShzEs2d1npQxjWNIwPsj/gIseu6jD/fjC4I1AIAzJYciog5xqGFUNw+ohLQjpDe4+rcV9dxtVY0IGagJQHYBqf/P7Kj9UJsGeVChMh7JkqPNB0OsaZYOdVBqvLsnlxDebp4usJZkShlNDKnUkN95qSSFIgCABGvA3uw8SIOxPxqakEvYnE/KnEA6kEPKn4A14MX4v3oAPb8D16lrjwTamx3C1tW3rsY24KVSsBRvBQ9PjpqgQMDZCpCFMOBgm0hAiEgxjgw0EGmrwBqvxNdThCdZhamv4yt5fkTa8j8JABylF0TcZ6LqrLlTHB7s/4LW81/jpqz9N+P4vnn0xVxx6BUeNP4rslGy3sIMpNUJ42cw08hlDAbkUkMtOxpHHFHYyjiJyaMAfd9rqwUuk8a8k6hlNIePZyRTyGMeu6F4KOPZ7R+H5/W97/Z6qSWUvI0minhwKOx3FvOcr1zPq3tapgbvMC8wFjgGmRJdtB94CPqL9Cud64CBcJ30k7mLrU5sgY5rr6IpF3HdFt1IpdjOFYiKCN2p2wlMTXeeQDTdlLBk2G85e6ZaFat2IPm9K5/vr5vu1l4ZYVbSKJ9c9yUMfPcSm0k1d3Lbr0vxpXH7I5Vw05yKOnXhsq7TG5XXl/Ovjf/Hq1lfYXbqZ+rq9NARLMaFqMjyQ7gFfNODKg5s+JnqZjjf6OAyk+tJICaSRHsgkN2MsXwsvIxBpHqC5Iv9k3k1fwptvwvLlLvq/rAymTHHBuAcd5DLn5OS4AKzYBXJsaoj4TFSx//74TuLYlDWVlS4Iq7zcXSSffXbCP9YuU93VpF/qrlA1JU/NICu4m4jxEjY+rLUETlmCGTkfjAcTaYimY48/3sQdT9bc6m6duLnUzyvpx7J6z2qKqjvOoNFdyb5kZoyYwaxRs7j1lFuZkDmpMWjxtddg7VrXMJma6gKSp0xxjUyzZrnMHLFGz9jNmKZRKsGg23br1ubz/L7Txv9cu4fSturkaPr2ltu0OlT/u41jd1uNp+3V+11IEw/w6uXHc9LTb8I4IAvIAFKB4WmQOxpGjYZhmZCeAcmZEEh15+2xg0zhPdDiGNaWm564kcicm5q97+OOc597jLVw0snt11mvvdr2Bx3b58Ltf+NPW7/iGqNijOXyQy/j/vPu77SMbTnn3+fw/Mbnm2U4yWgIUDarRbZI44NL28iK1ts6uOUIdT+Qhvs/ir8l0VTp+Lzgj0bX+ryuNT8UdrdwGC62bpuoD/MO5YYnfs37O0+nrMz9LqZNc+mSFyxwjbKx0YoNDa2zPXUkFsiUlAQFFXt5YsO/eWXrK7y7610Kqjr/fnaVz+NjxogZnDDpBE6bdhrnzTwvYfvuSH8Gbwx2A33dJSLSJ4JlsPGvsOVBbNVm7OhTYPIlkH2Ym74sabjLm2wj0BiAGG3/fGpi4zWvTc7BXNBU7zWEG1i8eTF3LruT5zY+1+wlv3Tol/jKEV9hwbgFHWZY66l+vO66CDijRQDGfGvtN+LWeQ74VYvgjR8CU9vbtoPgjTuAd1oEbzxvrX2ijbJdBVwFMHHixCO2bdvWcpV+c9eyu/je4u9hrRtoYrE0hEPYunSoz4RgurvVZzQ9DqZz62IvaUEvJhAg4vFio7fKJC+/P9aLMYZwJESEMBEbdveEaQiHokEcEUygGpNUzZUHT+fMzb/kvHUtCucBTvtcNDodwLqGDmxc11KsfZ/moyxTlkPqim59FlXt9KWknrsJk5zT9pMTpmHaGCRlc0bDi1/GtDGVWHuerYILCwxBC7aNvrt4AQPDPJDtgSwPZHnd42wvJMW1C3mjgTNh3Cl5GAhZKItEb2EojT6utF5m5BzG+7u7fz6V/1vIbWdqi4I0GNONWaAXjFvA0p1nths4UUcSpWRTRhalZDfe6klqFSwRf7OYDp51twwqG/c4t/xNfJmtB3N1qKNpprt4fRyzdN1Wjv/8KxBpcF9v1y1F0AfXXnQQB08fjo2474kxBhc/EP19RJc1/QVeW0u23YLXNFBvMygzUxp/O7EtTTj6yLj7ivoC/t+2TxGxkcZbOBLu9PsZ+z5YoIThbGUKW5hKPmMo9gf4xfE+N2jcVwfDtkP2lsbB47FBNB7jwWu8ZKdks+u7uzp8vf4wkMEbgz4ScX+7EFu78EhmVXXj/X62PqEpCBsa4N13XWTbmjXulpfnGu5jozC9XtdYP2mSa4A86CDXuHLUUc0bwbrK/KxnJ4Re4yXNn0Z6IJ30pHRS/akk+5LdzZtMki+JZF8ySd4kvJ6u5/cKR8LUh+upC9VRH6qnLlxHXcjdahpqqA5WUxmspDpY3Tgvb3d8KRP+3k6936aTl0Duyd17kY4qjLZ0sxLprgX3LuC93W1HDCZKRycLbenuCUR32Rv7IQXIIKMo+iYDVXf9ffnf+ePSP7Ju77pmxyeDwe/14zEe5oyaw6G5hzJ9xHQCnvYP2hEbYVv5Nj4u/JgVhSuoDla7k7UWx72JwyZywcwL+OMVD/d5WvK2mJu6t357x4puHxNu6rgjp5UEncjf896fue/Vb3JEEhybDAcEIMcL2T4PKZkHwvDDiaROwKZOxCSPwiSNwASyMf5hGG8SxEXgG+OBZ2dhOpkWoJnupFBM1LQpkTCUfwxFb0Lha1C1BWp3Q0O5m7Zl5NGQNhFSxrmsI8mjoiMQhtGYPj+WNeTZOZ1OgxBzRxn8oiaHwmr3/xbLruHz+DDGcFjuYVw7/1pOnXpql88zPir4iDuX3cmzG57Fa7zUheqajfZN9ady7IRjWbxlcdc/nwS68VW4qUV6RgtUk9bsAjn2uIbUNi99I3gI48VgWz3riQZm+WkgizKyKOO4ksdJyW4vf2jf2t/rroFoQIyd++d6YbIfRnthhBcyPe42PmU4OanZjEjOJCkwjEAgE6/Hi9d48BiXGcM1CoabGhJsmFl7X8Bvm0ZmmI1Nr5nkTSInLYfR6aM5PPdwDh9zOAfnHExuWm6HjdO1oVpWF61mZeFKlu5cyo6KHRRVF1FaV9q4ziuXvcJJU05qtW1JiZs+paioKQVq0Y1/YXdNFoXkNDUy+ZKJHHZEY2rVQMBNVxQ/mmjECJgzx40kKy9vuoVCrsM7fgpCY9w+/P7mh+H4DHixmZdi0z/U1zcdlr951FX4bQUQiQYyR2DqFeAfRtPggJYp8uNsud9NTdmJ+P+fjvS63m6jvm6zCupFMEpDfZC7vvrNZju2GA6+7DY8PpeVobEBLdYuBs2bvsrXQNmqxj8jNoI1kWZlza8o4wR+Hd2fxWIwHg/jr3jD1XeNDEw5FIr2tC7siFS4vQspN0ceA6e/1fl6HQQKdUk0SKSULHYy3jXsMaKxvtnjyaEycxyR7OGkZifjTwuA1wfe6JwpXo9rYwyHseEwhEPYYIjasnrqS6tJKcsnkv4hK29+n7CneWTsAdkH8JnZn+HUqaeSlZzV6fux1rK+eD0vbHyBhRsWUhVsGkFpMMweNbvHwTrdpeCNJvtbm6GI7CdW3QIrowNxknPhgvymE7i2dDRIoZ1r+LK6Mu5fcT+jUkdx0ZyLCPTxFEcKmm9uUNRfiZhOqrfamUpKBodIJMKOih1sKd1CcW0xe2v2srdmL5tKNvFh/oes2bOGkG09+iw3PZe5o+cyN2cuYzPGMiJlBCNSR5CTnsPMkTNJD6QPwLuRPpfAaXQGi47qri4Om+z5a7exrOUn2N46Xdm2J6/XshGxk13uW/IP/BHrfvV1zn9jT+efJsDtU2DE6PafNy2iEuNP9OJzWUUf+w0cCxwbW2d09AZwUD4c1M6J4E6gw2Rg7Xv2tcsofi0aGdbJm7YYpn7uaIzP07xxrMX5q7Vgo2nTWx0TjGnnONH662mNcRkZWqxmgJaBVe6jbr1jg218Xy5lWAPB355BIBCESL3rlCJ+7rboLRK9D9dB/stN/5fE/r/iXqvx7+iy5ffHFbTFe2v1NqPb5C9yqcLy2klX1gvneCeRPOl4krxJBLyBZrfYsvK6cqobqknyJZHiSyEzKZOMQAapgdTGwJy2tkvyJuH3+tl8pYfNXSyPtZaQDfFiqJ5gONh4qw/XUx+uJxgKUhuqpTpYTVWwior6CqobqqkP1WOtZVzmuMb1W24fDAf7/IJHVHe1Z3LWZL4w9wutlvs9fk6cfCKHjTkMTw+nlNhSuoVFmxZRXl/e6rkx6WOg4I/d22EvR+zGLH35Evw2RLLXR5LHi8/jAhN84z9Nmj+ZNF9KNJ119L/s6rYbPHIBu/kfsPV+IhZqLFRHoC66WQQIWvd3nYXb/jySxZUBvDYFXyQVG/ZTXFlJ8neT8Fg/fpNMsi+FJE8qXgL4v3QiAU8Av8+HFx/hSIQIsU4Zi/3pldEOyBA22hFpiZDmzyBsQwQjdQRtHRNy0thANhuDhkcbPBgM5XXl0ak7NpBiNpDtNS4CPxqF7zcGDxDweDA2Eu1Qj4vEt55oFL4lbA0RLPfmWLJaflXaG3HQnpyc9v+Pu8PjhexD3W3GN5o/F66HYAnUF7tbsBhqdkB1nksH2FifRh/P+i6ufowFdXhdlpIPfwSh5ilkZ6Zn8e25325VnCRvEufNPI8p2VNaPdeZU6aewilTT6GsrozHVj9GcW1xq3VqG2rZXrGdadnTOGD4AeSk5TR2Lk8cNpFDcg5hxsgZrTJ0dKYuVMfqotWsKFjBnhrXoReOhNlVuYtNJZvYXLqZ+85t4C9n1+CNTh1RH6qnKliFMQ0Y9mJMsQthMQaP8bDpl9XkVLU+hBamw7Tr07DYZiN5rLX4PD6yU7IJR8KEbZhwJMzfCl7mguwLuv15DjGDsu6y1t4D3AOuAbGTfSZERwGuoUiI2oZaFzDdUM2e6j1sqy6kOlhNTnoOOWk5DEseRqrfnR8meZPaDb5I1JuZPWo2F83pIGveTTfBz1oHWg8HjurKC4RwE+F05sYbmd4vDZv39G7znBPh6Ps7Xa3L/z83tr04t6v7aGf7VnoRyO5PCvCN++/q8fbOQdFbZ67tfBVoe7q0vtDbAQA33QQ33UQ2kA0cnIAitXZlO50Ty4BHOt+8sBCiI9hmRm/faXPF9+HGyeqAEBGR3pt+tcuqufUhqNkOr30KJn/OTTOYnOOCam0YiMsa3Kb223+ykrP49lHf7ovSD7T3genGmCnALuAS4HMt1lkIXGuMeQQ3XWV5NChjTwfbLgQuB26N3j8dt/zfxpg/4KarnA707QjGRImeh4m0x+PxMClrEpOyJg10UaS/9UVwV3ezOg3y4K6+Dt7YCUyI+3s8sLuL6wQ62LbQGDMmLhIx1nLQldcbkEbEweLkmRfCAxcOdDH61Sdbnj7JwBlzBnzinwnf7Q3Rm0iCqO5qR6xjuC9MzZ7K1478WuJ2mKBsPwtO7UKje1eNPh6O/gceID16a8+/E/eq+64+zOjUyJsEKWPcrTemX91q0SnRW1/ISs7iK0d8pd3nf3ZS4ke/JPuSOWLsERwx9ojE7fT6thfnQAczuu63BmXdNdj4PD4ykjLISMoAXN0z6KnRU2Tw0+9URESGkqQRMPdn7haud4MTanZByQfuPlSDC9wIuduUy6KDE3wu46TH6zJ2TL18oN9Jv7PWhowx1wKLcLNI3GetXW2MuTr6/F3A88DZwCagBriyo22ju74VeNQY82XcpLcXRbdZbYx5FFiDC8u+xtoepOoWERlMdP3Uqb4O3lAkooiIDDWqu0REZKhR3SUiIiIiIt3jTYLMGe4mXWKtfR4XoBG/7K64xxa4pqvbRpcX0874DmvtLcAtvSiyiIgMMX0avKFIRBERGWpUd4mIyFCjuktERERERERERGToM7bdOcv2D/PmzbPLli0b6GKIiEgnjDEfWGvnDXQ5BgPVXSIiQ4Pqriaqu0REhgbVXU1Ud4mIDA2qu5pT/SUiMvh1VHd5+rswIiIiIiIiIiIiIiIiIiIiItJEwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiLSL4wxw40xLxljNkbvs9tZ70xjzHpjzCZjzHVd2d4Yc310/fXGmDPilr8WXbYiehvdt+9SRERERESk+xS8ISIiIiIiIiIiIv3lOmCJtXY6sCT6dzPGGC9wB3AWMBu41Bgzu6Pto89fAswBzgT+Gt1PzOettYdGb0V989ZERERERER6TsEbIiIiIiIiIiIi0l/OBR6IPn4AOK+NdeYDm6y1W6y1QeCR6HYdbX8u8Ii1tt5auxXYFN2PiIiIiIjIkKDgDREREREREREREekvOdbafIDofVtTmIwDdsT9vTO6rKPtO9oG4B/RKVNuMMaY3r8NERERERGRxPINdAFERERERERERERk32GMeRnIbeOpn3R1F20ss73Y5vPW2l3GmAzgCeCLwIOtdmDMVcBVABMnTuxiUUVERERERBJDwRsiIiIiIiIiIiKSMNbaU9t7zhhTaIwZY63NN8aMAYraWG0nMCHu7/HA7ujj9rZvdxtr7a7ofaUx5t+46VRaBW9Ya+8B7gGYN29eZ8EiIiIiIiIiCdVn06YYY4YbY14yxmyM3me3s96Zxpj1xphNxpjrurK9Meb66PrrjTFnxC2/xRizwxhT1VfvS0RERERERERERHpsIXB59PHlwNNtrPM+MN0YM8UYEwAuiW7X0fYLgUuMMUnGmCnAdOA9Y4zPGDMSwBjjB84BViX4PYmIiIiIiPRanwVvANcBS6y104El0b+bMcZ4gTuAs4DZwKXGmNkdbR99/hJgDnAm8NfofgCewUXOi4iIiIiIiIiIyOBzK3CaMWYjcFr0b4wxY40xzwNYa0PAtcAiYC3wqLV2dUfbR59/FFgDvAhcY60NA0nAImPMSmAFsAu4tx/ep4iIiIiISLf05bQp5wInRh8/ALwG/KjFOvOBTdbaLQDGmEei263pYPtzgUestfXAVmPMpuh+3rHWLo3upy/ej4iIiIiIiIiIiPSCtbYYOKWN5buBs+P+fh54vqvbR5+7BbilxbJq4IjelVpERERERKTv9WXmjRxrbT5A9H50G+uMA3bE/b0zuqyj7TvaRkRERERERERERERERERERGRI6VXmDWPMy0BuG0/9pKu7aGOZ7YNtmu/AmKuAqwAmTpzYnU1FREREREREREREREREREREEqpXwRvW2lPbe84YU2iMGWOtzTfGjAGK2lhtJzAh7u/xwO7o4/a272ibrpb7HuAegHnz5nUr8ENEREREREREREREREREREQkkfpy2pSFwOXRx5cDT7exzvvAdGPMFGNMALgkul1H2y8ELjHGJBljpgDTgff6oPwiIiIiIiIiIiIiIiIiIiIifa4vgzduBU4zxmwETov+jTFmrDHmeQBrbQi4FlgErAUetdau7mj76POPAmuAF4FrrLXh6L5/Y4zZCaQaY3YaY27qw/cnIiIiIiIiIiIiIiIiIiIi0mvG2v171hBjzB5g20CXo5+NBPYOdCFERLppkrV21EAXYjAYwLpL9Yf0JX2/pK8M5HdLdVdUP9ZdOpYI6Hsgjr4HPaO6KyqBdZe+i31Dn2vf0WfbN/S59h3VXXEGSZ+Xvu8y2Og7KYNNu3XXfh+8sT8yxiyz1s4b6HKIiMjQovpD+pK+X9JX9N3av+j/W0DfA3H0PZDBQt/FvqHPte/os+0b+lxlf6Lvuww2+k7KUNKX06aIiIiIiIiIiIiIiIiIiIiISCcUvCEiIiIiIiIiIiIiIiIiIiIygBS8sX+6Z6ALICIiQ5LqD+lL+n5JX9F3a/+i/28BfQ/E0fdABgt9F/uGPte+o8+2b+hzlf2Jvu8y2Og7KUOGsdYOdBlERERERERERERERERERERE9lvKvCEiIiIiIiIiIiIiIiIiIiIygBS8ISIiIiIiIiIiIiIiIiIiIjKAFLyxHzHGnGmMWW+M2WSMuW6gyyMiIkOH6hDpS8aYPGPMx8aYFcaYZQNdHhm6jDH3GWOKjDGr4pYNN8a8ZIzZGL3PHsgySt9RXSWgOmV/peO/DEaql/qOjvWJo+Nn32jnc73JGLMr+r1dYYw5eyDLKNIXVPfJYKNzBhmKFLyxnzDGeIE7gLOA2cClxpjZA1sqEREZClSHSD85yVp7qLV23kAXRIa0+4EzWyy7DlhirZ0OLIn+LfsY1VXSguqU/c/96Pgvg4jqpX6hY31i3I+On33hflp/rgB/jH5vD7XWPt/PZRLpU6r7ZBDTOYMMKQre2H/MBzZZa7dYa4PAI8C5A1wmEREZGlSHiMiQYK19Ayhpsfhc4IHo4weA8/qzTNJvVFeJ7Md0/JdBSPWSDAk6fvaNdj5XkX2d6j4RkQRQ8Mb+YxywI+7vndFlIiIinVEdIn3NAouNMR8YY64a6MLIPifHWpsPEL0fPcDlkb6hukpiVKdIjI7/MpBUL/UtHev7lo6ffedaY8zK6LQqmo5G9jWq+2Qw0jmDDDm+gS6A9BvTxjLb76UQEZGhSHWI9LVjrLW7jTGjgZeMMeuiI5VERLpKdZXEqE4RkcFA9VLf0rFehqI7gV/gjgW/AH4PfGlASySSWKr7ZDDSOYMMOcq8sf/YCUyI+3s8sHuAyiIiIkOL6hDpU9ba3dH7IuBJXKpNkUQpNMaMAYjeFw1weaRvqK4SQHWKNKPjvwwk1Ut9SMf6PqfjZx+w1hZaa8PW2ghwL/reyr5HdZ8MOjpnkKFIwRv7j/eB6caYKcaYAHAJsHCAyyQiIkOD6hDpM8aYNGNMRuwxcDqwamBLJfuYhcDl0ceXA08PYFmk76iuEtUp0pKO/zKQVC/1ER3r+4WOn30gFhATdT763sq+R3WfDCo6Z5ChStOm7CestSFjzLXAIsAL3GetXT3AxRIRkSFAdYj0sRzgSWMMuHPTf1trXxzYIslQZYx5GDgRGGmM2QncCNwKPGqM+TKwHbho4EoofUV1lUSpTtlP6fgvg43qpT6lY30C6fjZN9r5XE80xhyKm0YiD/jqQJVPpC+o7pNBSOcMMiQZazXllIiIiIiIiIiIiIiIiIiIiMhA0bQpIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA0jBGyIiIiIiIiIiIiIiIiIiIiIDSMEbIiIiIiIiIiIiIiIiIiIiIgNIwRsiIiIiIiIiIiIiIiIiIiIiA8g30AUYaCNHjrSTJ08e6GKIiEgnPvjgg73W2lEDXY7BQHWXiMjQoLqrieouEZGhQXVXE9VdIiJDg+qu5lR/iYgMfh3VXft98MbkyZNZtmzZQBdDREQ6YYzZNtBlGCxUd4mIDA2qu5qo7hIRGRpUdzVR3SUiMjSo7mpO9ZeIyODXUd2laVNEREREREREREREREREREREBpCCN0REREREREREREREREREREQGkII3RERERERERERERERERERERAaQgjdEREREREREREREREREREREBpCCN0RERERERERERKRfGWPONMasN8ZsMsZc18bzxhhze/T5lcaYwzvb1hgz3BjzkjFmY/Q+O7p8hDHmVWNMlTHmL/3zDkVERERERLpHwRsiIiIiIiIiIiLSb4wxXuAO4CxgNnCpMWZ2i9XOAqZHb1cBd3Zh2+uAJdba6cCS6N8AdcANwPf76j2JiIiIiIj0loI3REREREREREREpD/NBzZZa7dYa4PAI8C5LdY5F3jQOkuBLGPMmE62PRd4IPr4AeA8AGtttbX2LVwQh4iIiIiIyKCk4A0RERERERERERHpT+OAHXF/74wu68o6HW2bY63NB4jej+5OoYwxVxljlhljlu3Zs6c7m4qIiIiIiPSagjdERERERERERESkP5k2ltkurtOVbXvEWnuPtXaetXbeqFGjErFLERERERGRLlPwhoiISAvGmDONMeuNMZuMMde18bwxxtwefX6lMebwzrY1xgw3xrxkjNkYvc+OLvcbYx4wxnxsjFlrjLm+f96liIiIiIjIgNkJTIj7ezywu4vrdLRtYXRqFaL3RQkss4iIiIiISJ9S8IaIiEgcY4wXuAM4C5gNXGqMmd1itbOA6dHbVcCdXdj2OmCJtXY6sCT6N8BFQJK19mDgCOCrxpjJffPuREREREREBoX3genGmCnGmABwCbCwxToLgcuiwfNHAeXRqVA62nYhcHn08eXA0339RkRERERERBLFN9AFEBERGWTmA5ustVsAjDGPAOcCa+LWORd40FprgaXGmKzoqK7JHWx7LnBidPsHgNeAH+HS+6YZY3xAChAEKvrw/YmIiIiIiAwoa23IGHMtsAjwAvdZa1cbY66OPn8X8DxwNrAJqAGu7Gjb6K5vBR41xnwZ2I4LlgfAGJMHZAIBY8x5wOnW2vjrPBERERERkQGVkOANY8yZwG24C6a/WWtvbfG8iT5/Nu5i6wpr7fKOtjXGXATcBMwC5ltrl0WXTwbWAuuju19qrb06+twRwP24zq/ngW9FO9ZERES6ahywI+7vncCCLqwzrpNtc6KjxLDW5htjRkeXP44L7MgHUoHvWGtLEvA+REREREREBi1r7fO49rv4ZXfFPbbANV3dNrq8GDilnW0m96K4IiIiIiIifa7X06b0YXr5VcAFwBttvOxma+2h0dvVccvvjO4/9lpn9vb9iYjIfse0saxlIGB763Rl25bmA2FgLDAF+J4xZmqrQhlzlTFmmTFm2Z49ezrZpYiIiIiIiIiIiIiIiAwlvQ7eIC69vLU2CMRSxMdrTC9vrV0KxNLLt7uttXattXY9XRTdX6a19p1oZP6DwHm9fXMiIrLf2QlMiPt7PLC7i+t0tG1htK6K1VlF0eWfA1601jZYa4uAt4F5LQtlrb3HWjvPWjtv1KhRPXpjIiIiIiIiIiIiIiIiMjglInijvdTxXVmnK9u2ZYox5kNjzOvGmOPiXmNnD/YlIiIS731gujFmijEmAFwCLGyxzkLgMuMcBZRHp0TpaNuFwOXRx5cDT0cfbwdOju4rDTgKWNdXb05EREREREREREREREQGH18C9tHf6eXzgYnW2mJjzBHAU8aYOd3ZlzHmKtz0KkycOLGTlxMRkf2JtTZkjLkWWAR4gfustauNMVdHn78LN7fy2cAmoAa4sqNto7u+FXjUGPNlXMDGRdHldwD/wE0XZoB/WGtX9v07FRERERERERERERERkcEiEcEbvUkvH+jCts1Ya+uB+ujjD4wxm4EDo68xviv7stbeA9wDMG/evM6CRUREZD9jrX0eF6ARv+yuuMcWuKar20aXFwOntLG8iqZADhEREREREREREREREdkPJWLalL5KL98mY8woY4w3+ngqMB3YEt1fpTHmKGOMAS6jKSW9iIiIiIiIiIiIiIiIiIiIyKDU6+ANa20IiKWIXws8GksvH0sxjxuBvAWXXv5e4OsdbQtgjDnfGLMTOBp4zhizKLqv44GVxpiPgMeBq621JdHnvgb8Lfo6m4EXevv+REREREREBjtjzJnGmPXGmE3GmOvaeN4YY26PPr/SGHN4Z9saY4YbY14yxmyM3mdHl/uNMQ8YYz42xqw1xlzfP+9SRERERERERERk35WIaVP6Kr38k8CTbSx/AniinX0tAw7qTtlFRERERESGsmhmwjuA03DTSb5vjFlorV0Tt9pZuKyF04EFwJ3Agk62vQ5YYq29NRrUcR3wI9x0X0nW2oONManAGmPMw9bavP54vyIiIiIiIgPBGHMmcBvgBf5mrb21xfMm+vzZQA1whbV2eUfbGmOGA/8BJgN5wMXW2lJjzGTcoOf10d0vtdZejYiI7NMSMW2KiIiIiIiIDJz5wCZr7RZrbRB4BDi3xTrnAg9aZymQZYwZ08m25wIPRB8/AJwXfWyBNGOMD0gBgkBF37w1ERERERGRgRcX+H4WMBu41Bgzu8Vq8UHzV+GC5jvbNhY0Px1YEv07ZrO19tDoTYEbIiL7gYRk3hAREREREZEBMw7YEff3Tlx2jc7WGdfJtjnW2nwAa22+MWZ0dPnjuMCOfCAV+E7cVJYiIiIiItIDDQ1QUeFu5eXuVl8P4TBEIu4+/nHLZZEIeDzu5vU23cc/jl+WlASZmTBsWNO93z/Qn8Kg1hj4DmCMiQW+x2c8bAyaB5YaY2JB85M72PZc4MTo9g8Ar+EyHoqIyH5IwRsiIiIisv/KzYXCwv5/3ZwcKCjo/9eVfZVpY5nt4jpd2bal+UAYGAtkA28aY16ONUQ2vqAxV+FGmzFx4sROdjkwqqpg0SLXQD5nDhx5JJi2PhERERERkR6oqoJ162DNGti1C3budLf8fBecUVXlbklJMHw4jB0Lo0a5QIpYUEVWFowc6R4nJbUOyIg99niagjhaBneEwxAKQWUlFBdDSYl7HAsS2bsXHn7Yvba0q7+D5gGmGGM+xGU6/Km19s1evwsR6TlroXYXVGyAUCVEgmB84E2B9CmQPg086nqX3tE3SET2P4nsqFPnm4jI0DYQgRsD+bqyr9oJTIj7ezywu4vrBDrYttAYMybagDgGKIou/xzworW2ASgyxrwNzAOaBW9Ya+8B7gGYN29eZwEh/Sochp/+FG67DXw+17AN7tTu4Ydh/vyBLZ+IiIiIDF35+e5cc+FCKCuD1FR3vllb685DAaZNg29/G446CmbOdBkv6uvdesa4QAyfzy339UEvTjgMwaAL6IhEXH9kVlbiX2cf099B8/nARGttsTHmCOApY8wca22rKSuHQuC87DtKS+Htt2HtWvjgA/j4YygqctmDrHXHrREj3ACJefNg1iw45hgYPbrzfQ864XooWALbHoG970DNDjAe8AQA2/QrNgZsGMJ1kJwLWQfDpEtg3DmQNHwg34EMQQreEJH9TyI7zNT5JiIiIgPvfWC6MWYKsAu4BBdgEW8hcG00Pe8CoDwalLGng20XApcDt0bvn44u3w6cbIz5J27alKOAP/XRe0u46mo4/XRYscI1oMfbsgVOPBHuugsuu2wgSiciIjL4RGyE0tpSspKz8Hq8A10ckUHv+efhvvuifXnWZXlr6aKL4NprXRCFN/qzSkrqvzJ6vZCS0n+vt4/o16B5a209UB99/IExZjNwILCsZcEGc+C87Bvy8+Hpp+H+++HDDyE52V1PNzS0vX5xMWzYAM884wLY6uthxgy4/HK44AKYPLk/S99N1kL+Yth4BxS8DMbvsmzEx1uFa9vdnNqd7rbnTXjvKsg+BA64CiZ/Abz9eKCXIUvBGyIiIiIiIkOYtTZkjLkWWAR4gfustauNMVdHn78LeB44G9gE1ABXdrRtdNe3Ao8aY76MC9i4KLr8DuAfwCrcCLJ/WGtX9v077b1IBC68EJYvh7q6tteprYWrr4Zx4+CUU/q3fCIiIgOhIdzAzoqdbCvfxraybWwt28q6vetYUbCC9cXrW60/OWsyh485nFkjZzElawqTsiYxadgkJg6bSJJPnRIiX/qSG2n+zDPw/vtudHpREQQCLouGMXDHHfD66269I46AQw5xo9KHD4e0NLduQ4O7hcOuLzFe/FR/scexYBFovn5b23q9bnS83+9eo7ravbZ0qF+D5o0xo4ASa23YGDMVmE6LbIcifW3VKpdJaNEilxGopsYtDwa7tn0o1BTAtnIl/OQn7nb00fDLX7rsQ4OGjcDOhbDiOhd8EaqOPtFBoEZHQlXuvvg9KF8NH/4A5twA078KvtSEFFn2TQreEBERERERGeKstc/jAjTil90V99gC13R12+jyYqBV+IK1toqmQI4h5eab4Y032g/ciKmthfPPdw3t48b1T9lERPY3xpgzgdtwwYN/s9be2uJ5E33+bFzg4RXW2uUdbWuMGQ78B5gM5AEXW2tLo89dD3wZCAPftNYu6uO3OGjUNNTw1ra3eHTNo2wu2cz2iu2U1JZQH6onGA4StuF2tzUYMpMyCXgDhCIhKuoryCvLI68sr831PcZDwBsgyZtEVnIWEzInMHX4VM6Zfg5nHHAGmUmZffQuRQYPY+ATn3C3mGDQJfAtKmq6lZW5Ts31690UBCUlbllZeYSKyjDGQGqKJS3dkJFhSUsHr8fg8ZjovQevx+D1Wrw+8HldoEcoZBoDPiKRpmlRIhHX8VpZ6W41NW55WhpkZsLSpQP1iQ0NAxA0fzzwc2NMCFd3XW2tLemHtyrCihXwwx/CW2+541e4/VOFboldi7/2mhsscfDB8NvfwnHHJWb/PVb4Giz9EtTvaQq6SKRQNVANK2+AVTfBIb+C6Ve7KVhEWjC2ZdjlfmbevHl22bJWWaZEZF9m2ppicIDl5EBBwUCXYlAzxnxgrZ030OUYDFR3iSTQQNYJ+/l5+P5AdVeTwVB3bdvmRja2nCqlPX4/fPKT8OSTfVsukYFQE6zhlAdP4e0vv41HDYYSp7/qLmOMF9gAnIZLMf8+cKm1dk3cOmcD38B1gi0AbrPWLuhoW2PMb3CjlG81xlwHZFtrf2SMmQ08DMwHxgIvAwda237UwmCou7qruKaYf678JxtLNrJ+73ryyvIoqMqnqqG68437SYo3QG5KNpMyRnNg1kQOzJrIhQecwqTMCeDxgcfv0pN7/OBNbrp5kkFTtkhP2AjYcPRmcWnvW6anaGtZVOM1Y9x9m8u87jvchXo1Eomwbu86/rfzf6zZs4aCqgK2l29nV8Uu9tTsobqD3+zotNFU1FdQF6qLK7rH3SJevD7DiNRscjNGMzlrEmMzxjJx2ESOHHckR40/ivRAeqflG2p03dXcUKy/ZPCorYXrroN773WBFv3RdJWa6gZP3HEHDBvW96/XTEMlfPBt2PZwx1OhJJo3DbLmwDEPQ/rU/ntdGTQ6qruUeUNEZDAoLBzoEoiIiHToWy98ixkjZ/D1I78+0EUR6ZGvf739+Xjb0tAAixe7kUbHHtt35RIZCPlV+SzdtZTimmJGpY0a6OLI/mk+sMlauwUgml7+XGBN3DrnAg9Gs0ctNcZkGWPG4LJqtLftucCJ0e0fAF4DfhRd/oi1th7YaozZFC3DO334HvtdddE7vP7Wt6m3EAAOBA70A/64lVLHM37S2RyWexizRs5i9qjZCT0OlNaWsnbvWtbuWcvKwpVsLt2Mpe2en50hS1FJPicmT2bSyCMSVgbZx6z5Laz4YcfrzL8HDvhK288ZTzSgwt/2832kPlRPXlkeW0q3sKV0C+v2rmP1ntV8XPgxe2v39ni/RdVFzRcYwESACHhDhIGi2nyKavNZWfRRm/s4PPdwZoycwZxRc5g2fBrTsqcxNXsqw1OGYwbjoDcR6RdvvQWXXOKyAHV10EMi1NTAE0/ACy/AAw/AOef00wsXvAJvXwKhSgh3kp4z0cLVUPIBPHcwHHILzPjW4Bx0LANCwRsiIiIiItKp/6z+D7NHzVbwhgxJr7zi0rKGQt3brqYGrrwS1q1z84KL7Cvyq/Ib7xW8IQNkHLAj7u+duOwana0zrpNtc6y1+QDW2nxjzOi4fS1tsc0+NzHWxNGH8t/DT4NIdCJ6G3aPw3XuFqmHzDkw+1KXjcBEoHotVK/DZQ7wRDNfRDNgePwum4Dxtcg0EH1sDKz9A6z/Y2MZsoFPRG9dUR2Co765iQlJqzpcb8EuuPH1rn8WvXHjifD+2I7XmTAR7knu/WsZWnfUGGOIz5Zt6zKg6CCoHQ4RL/hrYfgmyNoKnkGazS/kh5LpUD4RQkngCUFqMYxaA8kV3drVN3yj+f1k9zj2blt+at5wLSbS0DREvHEFE92q6ZO2zZa34+OfY1bf3K1yxquNQNrmDl8Bv8ePtZbc9FxmjZrFobmHMnPETGaMnMGo1FE9DqKoC9WxqWQT6/euZ9WeVXxU8BFby7ZSF6rDWkuECMsLlrO8YHmrbX996q/54TGdBMqIyD7HWrjpJjd9SX8GbcSrq3O3z34WPv95+OtfwdeXPdjrb4cV1/Vvto2WbBjCNfDRT2DvO3D0g+BNGrjyyKCh4A0REREREelUZX0lBVWa4kuGpu99zwVi9ERBATz1FHzmMwktksiAKqxymf8KqgqYmzN3gEsj+6m2eiVb9nO2t05Xtu3J62GMuQq4CmDixImd7HIQSh0PJy/u/X4iYRg7rvMsoTmjYccmmHsTjUEdJi64o9nfcY8bMyFAacVO1myeTMehG/DSDD8n/b9St4+W34Lo/+RRF04hUFrU1ubNBLNHs/S+56B8TYtnLBEb4ZZt/0eYSIf7mOKDGeEAtj5I2ECY6M1AhYGqLgZ9tpWVxIaB7cfB+1+DvBOgdgT4Yycy0aCDiA+sF0aug0P/AXP/BaklAAzzQJoBrwEvze8/vSlAgTdIyOBuHmgwUGfg7WyIGIh4PESiJbPRMlrAdhRLYIFdR8JHX4T150LlGBdkYiLEB1DQkAKBKsyE/+E57B/4pr+AN1BLlgcOSwKfAb9xnRaxx7O8Faw5YiWRQFZ0T7bxc9tbU0RNqJpITYTIijeanrURF6hgG0tPJBLhM2dfRkpJWYf/J7XDs3jq+fvwTHsSF/Rh8Hi8YAzGeDG4764xHnJSx5LkS8bgwXhMs2Ccks8Mw9PJDCqp/lR8nk66aHJz3W8xCRgNZOGipLKif48E0vxw5GEQCYHHx8EmOu3QmAkw/WJIHUetP5twcg6R1Ingz2zzpZLUaSiy36mvd8ESL7wwcIEb8Wpq4F//gvXr4ZlnILPtw1XPRUKw7BrY+s+BDdyIF66BXc/A4k/ASYsgeeRAl0gGmII3RERERESkQ9ZaakO17K3peXpfkYGycaPLnNFTVVVw++0K3pB9S35lfrP7Lot1IPWVnBwXMSX7g53AhLi/xwO7u7hOoINtC40xY6JZN8YAsZ78rrwe1tp7gHsA5s2bN0hTGvQDj7drv/XCIvBn9OqlxmWMI9mfRE1Dx1GWPq+X6UdWMCZjTPsrlXTt+BQAjgeg9TTjOyt2EvhzErWhjjt09njSqfhxRUKnmGhogDvugFtvhepqd2tMwFEfaHujgsNIfeMwwq/ezqmnwh/+AAcemLAidaqhAf7+dzdiu6rKjZoOh6NPBtuZpqRuOHbjOaQWnEPDQvj8F+FnP4MxHfzXtm9S91bvJHADIKWkjEsXnN+TwjR3003ujfWEF3fEmgpciJsDKQtoACLR5/3Re3BPFL/X9r4iQBBSYvFIAaAc2ISbbGoLsB0IAZWVkK4ADpH9xZ49cPrpLlBiMARuxNTUwLvvwiGHwKuvwuTJCdpxqAZe+6Q7XoZ7OLqjr4RroWwVPD8XTnsDMg4Y6BLJAOok9lNERERERPZ3hdWFWCwV9d1LcSwyGNx7b1wnQg+9+25iyiIyWOyucn3WselTuqwvAzf6Y/8ymLwPTDfGTDHGBIBLgIUt1lkIXGaco4Dy6JQoHW27ELg8+vhy4Om45ZcYY5KMMVOA6UA7PZ3Sn4wxzBgxo9P1krxJbC7d3Ofl2VyymYC3nUCJODNHzExo4MaiRXDAAfDTn7pDYVVVXOBGJ2pq3MjpF15wHV3XXANlZQkrWpusdSOjJ0yA73/flbm6unvnXJWVLtjjgQdg2jT41rfcsn3GTTe5D6qrt1AtbH8SXvs0/DMZfp0JV6W4OYhG4obhpgBpQDJxgRud8ETXT43efMAI3GRT/5cCt2bCQ0nwypmQnp7gD0FEBquiIpg3D1avHlyBGzH19bBjBxxxRIJ2GA7Cq2fB3qWDL3AjxgahrsBl4JD9moI3RERERESkQ3lleQDUh+upClYNbGFEuiEchr/9zY0K7Y0E9s2IDApbS7cCTcd3kf5mrQ0B1wKLgLXAo9ba1caYq40xV0dXex43JnwTcC/w9Y62jW5zK3CaMWYjcFr0b6LPP4obZ/4icI21tpehfZIo88fN73SdsA2zuaQfgjdKNxOKhDpdb8H4BQl5vfp6uOwyuOAC2L7dBUD0VCTigiHuu88FgvRV8OnevXDWWXDVVU1BG70RDLqOw7vvdllD/ve/xJRzSLAW8hfDG5+Bx4fDO5fBroUQqYNQRd+n9A/XQkMFROoh/0X4b27fvp6IDAplZXDssZCf3/tr5b4UDicoGDESgjfOg5L33fF1ULMQLBnoQsgAS0jwhjHmTGPMemPMJmPMdW08b4wxt0efX2mMObyzbY0xFxljVhtjIsaYeXHLTzPGfGCM+Th6f3Lcc69F97UiehudiPcnIiIiIrI/i+/c21a2beAKItJNixdDqPP+l07VDfb2HZFu2lG+A1Dwhgwsa+3z1toDrbXTrLW3RJfdZa29K/rYWmuviT5/sLV2WUfbRpcXW2tPsdZOj96XxD13S3T9GdbaF/rzvUrH5o+bT5o/rcN1qoPVbCzZ2Odl2VC8odMpXNL8aRw59shev9aOHXD44fD44y57RqLU1UFxMZx0Evz1r13P4NEVr74K06fDK68ktszgAlkKCuDUU+EnP0lsuQcda2HbY/DMgfDmZ2Dnf10gRaibqUeMD1LGQfbhMPJoGHWcux9+BKROAE87U9e0p04ZsET2ddXVcOKJsG3b4A7ciIlEOl+nQzYC//siFL3e9wFxiaL44v2er7c7MMZ4gTtw0ew7gfeNMQuttWviVjsLl45wOi4h153Agk62XQVcANzd4iX3Ap+y1u42xhyEi7IfF/f85+Mv5kREREREpHdiI7TBdfTNGT1nAEsj0nW3376Ppd8WSZCC6gIAdlfuHuCSiIjA3Jy5eD0dzwFhsawqWtXnZVlVtApLx1EDHuNhbs7cXr3OmjVu1HNFRe+nd2tPbS384Aewdq07J+ptJrFHHoEvfanv0+vX1sKf/gQbN7qpWfzdjD8Y9Apfh/evhpodEOpi2hLjhWFzYMR8GH0ijJwPyTngS4NwnRtV3vJ76/GBJ8VND1BX5Eacv31pot+NiAwhoRCceSasX++yHu0XPrrBZTQarFOliLSh18EbwHxgk7V2C4Ax5hHgXFwawphzgQettRZYaozJMsaMASa3t621dm10WbMXs9Z+GPfnaiDZGJNkra1PwHsREREREZEW1u1d1/hYo7RlqNi7140OFZHW9tbsBaCoumiASyIiAnNGzek02wW4rBh9bWNx59k9akO1zB41u8evsW4dHHNMglLBd6Kmxk2jYgzcdlvPAzj+9Cf48Y/7PnAjpqYGnn3WZeF4/nlI6zgxy9AQCcGK62DjX7s2+tv4IPdkmHoljPtUdCS2B/zpzdfzdfLheDLAnwEZ0xS8IbKf+9GPYPny/Siz5O5FsP6PQyfjhkhUIoI3xgE74v7eicuu0dk647q4bUc+A3zYInDjH8aYMPAEcHM0YKQZY8xVwFUAEydO7MbLiYiIiIjsf+IbyvsjXbVIIrzwghupWa8wf5FmwpEwFfUVAJTWlQ5waUREIMWfQk5aDrsqd3W43o6KHR0+nwg7K3d2us6Y9DEk+ZJ6tP8NG+ATn+ifwI2Ymhr4+9/B54M//KH72//9724ak/4K3IiprYV334VPfxqWLOnf10642nx4/VwoX915J2JgOMz8Hsy41iXT8KeD8fRLMUVk37VwIdx5Z/8fywdM9XZ462IFbsiQlIhav6143ZYBE+2t05Vt235RY+YAvwa+Grf489bag4HjorcvtrWttfYea+08a+28UaNGdeXlRERERET2W9vLt2Oip+5r964d4NKIdM2TT0JV1UCXQmTw2VuzF5/HjeWJ2AiV9ZpbSEQGXlemIakL1fXpMausroyGcEOn6x2ae2iP9l9RAaec0r+BGzE1NXB3y8nJu+DVV+Eb33DbD4T6eli6dGBeO2EqN8NzB0Hphx2n7TdemPMTOG8bzPwO+DMhkKnADRHptS1b4POf348CN8JBeO2TEO7i1FQig0wiav6dwIS4v8cDLSdNbW+drmzbijFmPPAkcJm1dnNsubV2V/S+Evg3bkoXERERERHpIWstRTVFjcEbW0u3DnCJRDpn7T4wQlOkj+RX5RPwBgBI9iWTX5U/wCUSEYFjJhzTGFjWnhRfCptLN3e4Tm9sLtlMij+lw3X8Hj+fmPCJbu87EoELL4Q9e9x5ykDobgDGunVw7rkD39k3UIEjCdFQCa+cCsFSsKH210sZA6cvhTnXgy8dfB1/D0VEuqqhAc4+e4gfS7tr5U+hakt0uimRoScRwRvvA9ONMVOMMQHgEmBhi3UWApcZ5yig3Fqb38VtmzHGZAHPAddba9+OW+4zxoyMPvYD5wCrEvD+RERERET2W4XVha4hPZozT518MhR8/LHrJBGR1gqqCvBER/F6jZf8Sh3XRWTgHZJ7CKn+1A7XMcawuaQPgzdKN9PGDNzNpPhTOCTnkG7v++c/h7ffHjrTue3ZAyedpCxmvWIj8OYFbsqUjpKNZx0Mn1wNWYeAL63fiici+4df/hJ27NiPro9LV8CGv3Sc6UhkkOs4nLkLrLUhY8y1wCLAC9xnrV1tjLk6+vxdwPPA2cAmoAa4sqNtAYwx5wN/BkYBzxljVlhrzwCuBQ4AbjDG3BAtxulANbAoGrjhBV4G7u3t+xMRERERGWwKC+G+++C//3Uj4sJhGD0aPvlJuOwyWLAgca+VV5ZHwBsgGA4CLl11VbCK9EB64l5EJMGWLIFQB4MbYy66CH7wA8jNddv87GeQl5fgwtQWuEb7lFw3qlJkgOVX5hOKuB9IxEYoqCoY4BKJiMAhOYd0OmVJbUNtn2be2FSyidqGjtNMBENBDsntXvDG8uXwm98MfAaLrrLWZQkpLh64LCH7hLyHYc87EOkgYidpJJz8EgSye/96/82FusLe70dE9hnr1sGvf90/9U9uLmRmgjEu8G/37gGoQyJhePtSCNf13Wskj4ZhcyBzJqRNAV8qRIJQswsq1kHFWpf1Q6QXeh28AWCtfR4XoBG/7K64xxa4pqvbRpc/iZsapeXym4Gb2ynKEV0vtYiIiIjI0FJfD7/4BfzhD27URPzIvW3b4K674P774dhj3eMpU3r/mnllec1GIKb4UthWto05o+f0fucifeT556Gug/YarxfuuMPN+5sejUP6whfgvPNcENT//peAQhS8Ah98Gyo3gDcJwvWQcQAc/kcYc1oCXkCkZ3ZX7qYu5H4g9eF6ZVQSkUFhfOb4TtdpiDSwqqjvEi2vKlpFqKOpLQCvx8uY9K4HY4ZCcMklQydwA+CRR+CDD1yqfemFdX+AcHXH6xzzH/AnIHADFLghIs1Y6wb39EXGJ68Xjj8ePvtZl6Vp4kT3erF6w+dztx073LX1I4/Ayy9DMJj4sjSz8U6o3kGH2Y56Im0yTP4cTLkM0ia54BBPwAVuxITrIVwLHj+EqmHbo5D3Tyh+N7Flkf1CIqZNERER2acYY840xqw3xmwyxlzXxvPGGHN79PmVxpjDO9vWGDPcGPOSMWZj9D477rm5xph3jDGrjTEfG2OS+/5diiTWfR/ex/q96we6GPu0oiI4+mgXuFFb2/YFeCTi5jFdsgQOPRReeaX3r7u1dCs1DU3pJo0x5JXl9X7HIn3EWni3k/aR3//eBWukxyWQ8fkgKwsWL4YDDuhFASJhWHE9vH4OlH/sRls2VLj78tXwxnmw/AcQ6UJqEJE+kFeeh402aAbDQXZU7BjgEomIuHPMGSNmdLreur3r+qwMXdn3zJEzMcZ0eZ+33gq7dvWmVP2rpAS+9jWo7iTmQDpRsQEq1nS8Tvo0GHkUeAP9UyYR2a/861+wZk1ip0sZMcLVa6Wl8OST8H//BwceCMnJkJLiMm9kZkJqKgQCMG2aGzDx73+7be66C8aNS1x5mqkvho+u7zxorjsyZ8Kxj8Mn18BBN0DmDPAmQyCreeAGuAEbgSw3/VXyaJh+NZz8Mpz5AeRq8IZ0j4I3RERE4hhjvMAdwFnAbOBSY8zsFqudBUyP3q4C7uzCttcBS6y104El0b8xxviAfwJXW2vnACcCGt8iQ87Xn/s69y7XjHV9ZfdumDsXVq3q2qi9cBgqKuCcc+Cxx3r32uv2riNsw41/B8NBBW/IoLZ+fccNVAcfDF/5CqS1M6V4UpLLYNMj1sJbF8H6292om7aEa2DjX10Qh3KRywDYVrat2d9bS7cOUElEpE/k5rqc5b29dVUiXis3F4D54+d3+nJ9eR66vXx7p+ssGNf1+Qm3boVf/tIFVw8V3/52x9nLuuOgg+DUU+H88+Gss1wgevL+MlSl4KXO15l6JZiEJEYXEWmmvh6+853EBeIlJcHvfgfbt8M3vwkZGTBsmMvA0RmPx62bmgpXXAEbN8Lf/+6CPBJq1c2JGyDhSYIjbneBF+M/Db4UF7TRrX34wJ8Oww+H4/4Lp74BKWMTUz7Z5yl4Q0REpLn5wCZr7RZrbRB4BDi3xTrnAg9aZymQZYwZ08m25wIPRB8/AJwXfXw6sNJa+xGAtbbY2rheUhlYiWr47GHj5VARioSoD9ezo1wjd/tCdTWccoqbc7q7qYtra93F8Xvv9fz1NxRvaPZ3XaiOjSUbe75DkT729tvtP2cMPPRQxx0HPh8ccghcfHEPXnzrQ5C/2AVodCRcA4Wvwea/9+BFRHpnd+XuZn/vrNg5QCURkT5ROASnToiWef7Y+aT524mujCqpLaEhnPjxDvWhesrqyjpcJ82fxpHjjuzyPr/73aE19cjKlfD4471LsX/ooa6Dr6AA3nnHBZL/4x9u1PULL7jMHk8+CZ/+tBuVvc8KlroU+h3JPFBZN4ag/s7WG31+ojGmyhjz/b59d7KvuPvuxE3XdfjhsG4dXH21C8BISen5vpKS3PaXXuqCOE48MTFlpLYANt0NkQREH2YfBuesg2lfctk1PP7e79OfDiMWuP1OuqT3+5N9noI3REREmhsHxPdA74wu68o6HW2bY63NB4jej44uPxCwxphFxpjlxpgftlUoY8xVxphlxphle/bs6cHbkh4ZqIbPIdbgGhvBu7l08wCXZN8TicCFF0JenpsvuydqauDMM90IiZ5oawTi2r1re7YzkX7w3nvtjzD63Odc6lZPJ1fC6elw553d7FSoyoNlX+96mtZwNXzwLajUsVP6156a5ueShdVD67xDRAZeBMNeRrCbMWxjIluYwnYmkE8uZQzr8Uzzc3Pm4vV0PIw32ZfMtvJtHa7TE3lleaT4O+6R8hgPc3Pmdml/K1bAokU9P4eP8XphwQL46lfdtG9//jPccIMLfkh0zP/Xv97zrBvz5sGmTfDmm25Udk6OO5/KynIjrmP3KSlw3nkumLakBL7xjQS+gcHEkwSmkyHpoQSnZEnOScBO1F3Ukf7O1hvnj8ALCX9Dsk+qqYEbb+x91g2vF266yR3XJ05sP3NlT6SkwOjR8OyzcMcdCcjK9PGNkIixkLN/DKe9BWkT3fQnieQNgD8DFtwLxz8F3tRON5H9l/JyiYiINNdWftiWbU/trdOVbVvyAccCRwI1wBJjzAfW2iXNdmLtPcA9APPmzVOOdRlUYpkZNHI38f7f/4M33uh96uKKCpe9Y80a8Hdj0IC1lqKaolbLlWJfBrMPPmj/uR/8wHUkdIXPB5/6FDzxRBdWjoThzQsg3M0fa6QO3jgfzlru0qqK9DFrLaW1pc2WFdcUD1BpRKRP5OQkJBi8hhQ+4Aje40jWMZOtTGUX4yhiNOUMw0cIL2EMFrBYDBZDGB8WQzYl5FDIRHYwhS0czCoW8C5zWI2PFh0s0fLOGT2HmoaOO7R9Hh+bSzZzwPADev0e420u3YzHdNxxXRuqZfaolv20bbvuut6dw48b50Y5X3ONCzr1+Zo6zkIh1ykXCLjsFr/7nQsU6WjauM4sXgwfftj9Gd28XvjpT+GHP3Qjsrsqli7/l790weqf/azL1rHPyDgAvCkQqmx/nd3PwYTzwZ+guQMu2Jc+wEGrMeMugDEmlnF3Tdw6jdl6gaXGmFi23skdbHsubhplcNl6XwN+FF3vPGALkKAJMGRf9+c/QzDYu334fC6w4thju3ds7660NJct9qij4LjjejjNWPUOlwEz0ss3PfcXMOM7LttGX/KlQ+7pcNKL8MqpvS+37JPUOiQi+58ENWTIPmsnMCHu7/HA7i6uE+hg20JjzBhrbX70oi3WG7oTeN1auxfAGPM8cDgu0l5kSIhNoVFcW4y1FtOdObIH2kDVCTmdj4ravh3+8IfEpLoMhyE/H+66q3uj2wqrC/F5fIRazBuaX5Xf+0KJ9JENG9pePn26u3VVZqYbOdql4I2Nf4WKDd0f7WMjULUZ1v8JZikLsvS9ivqKVstqQ7UEw0ECSt0usm/oYQ/43r3w3HPwyivw1lvuXDQ11QUgtNUJFO6kWbmIXIrI5WMOAdy+PB63r5kz4aST4OST4fTTm0bcpvpTGZ02utX0TvGC4WCfZPzbXLKZYLjjDpTc9FySfZ0PD1650gVgdzcQAtxndPPN8O1vu+ne2hqN7PO5LBbgPsMjj4Q9e+Css9o/D+rMd7/b/U6zyZPdFCjTp/e8cy89HY4+2qXkv/xyePrpnu1n0Bl7Np2O5dn5NCz4W78URxKmrYy7C7qwTnvZemPbNsvWa4wZDWCMScMFcZwG6GJBOlVVBbfc0sMgiChj4D//cYEbicy20Z7UVJg1ywUhnnJKDwJPVv0CIr1MczXr+zDzO4nPttEeXwoMP8Jl4Hj9U4nJGiL7FOXBEpH9T0GBu4Ju79ZSd9aVfcH7wHRjzBRjTAC4BFjYYp2FwGXReSyPAsqjF1kdbbsQuDz6+HIg1iSxCJhrjEk1xviAE2gesS8y6H1c9DEAoUiow4bWQamzOqE7x/3u7KcLjeqJniO7utqNiuuOvLK8Njvz6kJ1VAWrElQykcTZs6f9edqvusqNDu2O+fNh7NhOVoqEYfUvuz5dSkvhGlj9655tK9JN+VX5JPmSmi1L9iVTUKXRutJ/jDHDjTEvGWM2Ru+z21nvTGPMemPMJmPMdV3Z3hhzfXT99caYM+KW32KM2WGM0QlMnIoKeOAB10EzfrzL8vDgg7Bli8vu8P/ZO+/wuIrzbd+zRV2ybLnIltywDQaDTXGhd0IPAUInkISEQCD5kQ5JSCPF6SEJ5QNCAiGEkISAAROK6QSDjXu3ZMu2erPqSto23x+zWm05288W2XNf1167O2dmzqy0e8rM8z5vT0/q0bvDOBxqUcnpVOKG3/8err8exo0Lrrdg0oKo/Qy4B9jWvs2cQQWwtX0rg+7oVhlHVx4dV1933RX5eiQaY8fCG28o8WhhYfw28qWlSkjx0UcqJUmibNwIuxM01psyRaWqO+qo1Bf37HYlRnnySeXCcUBgzYeZN4KIInLyOmH1l8CtDRVGEZl26/0h8FspZcxzl063rAGVkioVFyaAP/0Jzj03M8KNYQoL4dhjlYAvoXt2Vy/UPQEyhcmzWZ+Ho36QOeHGMLYimHgqnPgkxocHzcGMFm9oNBqNRhOAlNIN3I4SVWwFnpZSbhZC3CKEuMVXbTnKsrAGeBj4YrS2vjZLgXOEEDtRivmlvjb7gd+ghB/rgDVSyhfT/Tk1GjPZ1LLJ/3rYhUOTGmvWwPLlqefIDiVRMUhdVx3SQLRSaCtkT5f5ucY1mlTZvFlN/IRitcJNN0F+fvi2aEipbFyj0vgCuFNcC/SmmBtJo4mT5r5mrCJ4RtRusdPUqx2VNBnlTmCFlHIOynHwztAKQggrcB9wPnAEcI0Q4oho7X3brwbmAecB9/v6AXgeZXevAVatggsvVPnmb78d3ntPiQ36M7iGLCX09oa7zJ049URsMVKJbW7dHHV7MsTq02axcWL1iTH7qalR7iWJLp4dfbRKcbhkSXILZhaLcrF44gmVRiWRxa8//jExsUlZGbz1FpSXJy6MjUZR0YiY6IDg8K8qEUc0dj8OtY9qAcfoIRW33mhtW3wuvYS49S4BfiGEqAPuAL4thLjdaGBSyoeklAullAsnTJiQ4MfSHAhICT//eWrn8t/+Fq64IrPCjWGKilTqlL//Xbl/xMXux0lpmXvalXDc7zIv3BjGVqycmhb/v+zsX5Oz6LQpGo1Gkwpm2e3HYZ+vyRxSyuUogUZg2YMBryVwW7xtfeUdwFkR2jwBPJHCkDWarLKraxcCgRCCnR07OX3G6dke0qhGSrj11tRyZEci0RQsu/fvNsw7LoSgrquOeRPnmTQyTaoIIc4D7gWswCNSyqUh24Vv+wWAA/i0lHJNtLZCiHHAP1D5meuAK32iQ4QQ84H/B5QBXmCRlDLrCoTNm40XH047TS1qJEphIXz+8yofe0Q23ZO6eCPV9hpNnDT1NuGVwSuKEqmdNzSZ5hLgdN/rx4A3UbbwgSwGaqSUuwCEEE/52m2J0v4S4Ckp5RCwWwhR4+vnfSnlSl8/6fg8o4Z161QKvTVr1HWhlPEv2gsBU6dCVZV6TJmipjIKCpRzgtOpFoyamqChARobVeqVRAPAj648mmJ7Md1D3RHrpCNtyq6uXVG3F9mL4nLeeOyxxIUbxxyj0qyUlCTWzojiYrjlFvW/uuqq2PUHB+Fvf1NpFuPBbof//lc5tdjtqY3ViKIilb7n+ONh61bz+88oJYfAiX+H964CT5QbsTV3KPHGYV9WkdiaXMbvuAs0oASD14bUWQbc7jtvLcHn1iuEaIvSdtitdykBbr1SylOGOxVC/ADok1L+MU2fTTPKeftt6OhIvv33vgef+5w556JkKS5WKcAefliNJSpSwpafJ++AOekMOP7P2T/u2ktgxrUw0AQbv5/dsWhyBi3e0Gg0mlSIZntvNCmkU61oNJoDDKfHSYejAyEEXulla/ton2HLPi+9pBagc+GUsa19Gx6D3JtOj5O6rrrMD0hjSEB08jmoiK5VQohlUsrANFznA3N8jyXAA8CSGG2HI5uX+uzq7wS+5Uvz9QTwKSnleiFEBWBikp/k+egjY+HThRcmHz1UWQmTJ0fYuH8ddOvjnmb00NTXxJAneKXW5XHR1KedNzQZZZIv7SS+Ba2JBnWqgH0B7+tR569o7auAlSFtqkwd+Silqwu+8AV4/nl1noznOtNuh9NPVwLIs85S6TFAObkJodysQtN6SKlEIcNub/n5StCxahWsWKFSgnz0UfT9zp80H6cneq6Wpr4mpJSmiXG80ktLX/TAHKfHyfxJ86PWkRIefTSxVDMVFUoMYeZiWXGxuvb5v/+De++NXvdf/0ogwhkl9FiwIP6ULslQUqKcPY46ypx4qaxSfTEccadvgTFcFA+A9ML6u6D1TTjpKbDkZWcx0T0ANgMLO40fKaXb53zxMkr4/uiwW69v+4OogK4LUG69DuAz0dr6ul4KPC2EuAnYC1yRwY+lOUBIxXXjzDPhm9/MjuNGKCUlSnz4xhvqnBOR1jfBuT+5ndjL4KSnsy/cGMZWDId/HRqeh87V2R6NJgfQ4g2NRqPRaDSaA43urbD3X9DyOvT7UlsUTYVJZ8LUS2Fs9EnHRNi9fzeF9kK/O8P65vWm9X0wIqWaZM2kZXU0AtPgWIXVH6096B5MS8SjJmmiRScPcwnwuM89aqUQotxnyTsjSttIkc0fAzZIKdeD310qJ4i0IHTJJWBL8u7X5YJzzomwcfPPdMqTg5zeXnjtNdizR9nIn3UWTJ+e7VFFZm/33rBF0QH3AA09DVkakeZARQjxGlBpsOk78XZhUBZLcpBMm+AOhLgZuBlg2rRpiTTNWTZsUFGsHR2xXTaEUIKNz3wGLr1UuTEUF8d/DhVCOScEUlAA550HZ5wx4s7x+OPqsdkgU8nUsqnhhSFYhIWW/hYqS4y+YonT1NuEzWLD5Y2sRbUKK1NKp0TtZ80a6I5sGBLep1UJasaMib9NvBQXK+ewjz6Cd9+NXO83v4G+OA3APvlJ9V0K/R+bjcWi/iZ/+hNcdFF695URjrwbvEOw7bfRHTiaXoZnp8G8b8NhXwJEZhYW3T5RSe0jyv1DE5VMu/UG1PlBEsPVHCQ0NCixQzJBQKWlKlVJLgg3hikpgQceUGnImiJpzLf+OnkHy4X3Zy9VSiSsBXDKv+D5w9Q5Q3NQk0IyII1Go9FoNBpNTtHyFrx2Ovz3ONj0I6VC79+tHm1vw+YfwyvHwysnQfNrplg77OjYgUWMXFLu6NyRcp8HMx9+GOXGNAvs6d7jf221WLFbRryRt7RtMWqiyQ5G0cmhkcaR6kRrGxTZDAxHNh8KSCHEy0KINUKIb5ryKVJESpVnPpSKCmXtnSylpUr8EYazG+qfU9GSmoOOoSG46y6YMAE+/Wn41rfgy1+GuXPVAuW+fTG7yAq7u3b7X4uAde7Aco3GDKSUZ0spjzR4PAe0+ASE+J5bDbqoBwJX8auBRt/rSO2jtYl33A9JKRdKKRdOmDAhkaY5yWOPwQknqBQm0YQbQsCVV8KuXfDcc3DddWrhZMyY5MWPoeTnq3NqZSXccYe67n37bVi8OHQsgkMrDo3aV541j9pO84TEtftrybPmRa1zWMVhMZ0+Hn00sdSHv/oVzJ+v/jbpoKgIli1TKW6M2LEj/tQk5eXw0EOZs9PPy1NCoosvzsz+0ooQsOAncMqzYB8Dwhq5rrtXuXD8pwo2fAe6NivBhzvB/Jex8Awq0UbPdtj4Q3h2Knz0f+buQ6PRZIwnn0y+7R/+oM7PuUZ+fpTP5epT85rJMPljMPUTuec0JCyQP16dLzQHPVq8odFoNBqNRjPa8Xrgg5vhzQuh9S01uSPd4fWkW21r/x+89Qn43/UQJbosHnZ07GDQPTJD2dzX7Hdn0CTO73+vrKZzASklbf3BScoDJ7V379cLfTlEPJHGkeokE6VsA04GrvM9XyqECIsUE0LcLIRYLYRY3ZZowvskaGkxzjF/8smJLaQYccopBoWNLylba81Bx+bNcNhh6pg9NAQ9PSPR5IODKsL58MPVommuEeiwYbOMrMju7d4bXweTJpk9pMz2r8kVlgE3+l7fCDxnUGcVMEcIMVMIkQdc7WsXrf0y4GohRL4QYiYqVdiHaRj/qOD+++GLXwRHhEwNw8ydCxs3KpeDGTPUAo4lzTPGeXlKWHDKKSqqNpQl1UvCCwPwer2musDVdtbi9hrcPyUwJo9HLTJ5wjMOGnLRRfD5z6c/0rmkBF580Tg1yv33xz/epUuhMMPrXMXF8Mgj6RO3ZJwpH4MLN8O4hbEjvl3dsO13sPxIeH4ubLxbLVQOdap7eme3El/EE5DhdozUd3ZDy5tKsLF8PrwwF7b+ApydZnxCjUaTJRIVDw5zwgnKVSnTx/d4yMuDhQvh8ssNNja+mNy9uCUPljyae64bw9iKYc6tUBpdxKo58DFFOy2EOA+4F5Wr6xEp5dKQ7cK3/QJUnq9PSynXRGsrhLgC+AFwOLBYSrk6oL+7gJsAD/BlKeXLvvLjgL8AhSj7qf/z2VRpNBqNRqPRHJi4++HtT0Db/yLn0DXC0w/1z8KKM+H0F1W+xyTY2LoRp8fpd9/Is+axr3sf08tz2DM+R+nthWeeMV58zgat/a1YLVa/fbTb4yYvb+TmuLEvoUBWTXqJJ9I4Up28KG1bhBCTpZRNBpHNb0kp2wGEEMuBY4EVgTuUUj4EPASwcOHCtN+X7dmjJvdDJ63OPDP1KFHD9nVPqOhIzUFFe7ty1oimR3K71ePWW5UW4bzzMje+WLT0t/hf59vycTnVMb65rzm+DprjqBcpMl1Pz2hGWAo8LYS4CdgLXAEghJiCmhu8QErpFkLcDryMmjN8VEq5OVp7KeVmIcTTqNRfbuA2KaXH1/cvgGuBIiFEvW8/P8jMx808770HX/96bFHwlVeqBZ/CwvQLNiJhJF5YNGURf9vwN/pdxrkEHS4HOzt2Gm5Lhh0dO/xpII0othezaMqiqH289Vb8Qoi8POVikQmLersdZs+G66+Hv/51pNzrhT//WaWHi8WcOXDDDSoFTqYpKoKvfjXz+00bRVXwsffVwuPqL8FQe2zbf8delR5g66/V+8IpMPYYKKpWj5JD1LMlD4QdpEsFaQw0Qm8tOPbBQAPsXwuO+vR/Ro1Gk1Hq6tQjUSwWdR7IpXQpoQynTwmj9tHk7sXnfk05IOUyljxY8nC2R6HJMimLN4QQVuA+4BzUJN4qIcQyKWWgj/L5KLX7HGAJ8ACwJEbbTcBlwP8L2d8RKLX9PGAK8JoQ4lDfzdgDqLyUK1HijfOAl1L9jBqNRqPRaDQ5yUCLEl/07QJvEhJ7jwM6VsFLx8LZb6oJnwTZ1Lop6L3dYmdn504t3kiCf/87MVvqOXPg5z+HRYvUpGxDA/zoR8rq2gzquurIt+b7nVUkMshVZdA9SL+zn+K8HL7TP3jwRycDDaj7pWtD6iwDbhdCPIW6J+v2iTLaorQdjmxeSnBk88vAN4UQRYATOA34bbo+XLw0NBivDZ91lsopnwpOZ0g0kmcIWgxChSMhrCDjXNHR5CxuN1x4IXR1xVd/YEAtjK5ZoxbOcoHOgZHI2hJ7CX1OtWDU7mjP1pA0ByFSyg4gzLFJStmICvwafr8cNb8XV3vftp8AYX7TUspvAjmR5ivdNDYqV4dYwo2vfQ1++MPcXLRZMGkBVkvkk7cXLxtbN5q2v42tG5FRjMcswsKCygVR+/jTn6Avxhr8MHfckVmL+pIS+O1v1f3GMFu3xi82ufdedb+RDUpK4Nvfzs6+04YQUHURTLkAGp6H9XdD3051IeuNkt9omIFG9dBoNBrgH/9Irt3nPx85rVYuUVQUUuDqVa7DiVIwCY78Tu66bgxjscG4Y7M9Ck2WMUNTvRiokVLuklI6gaeA0IzAlwCPS8VKoNwXuRWxrZRyq5Ryu8H+LgGeklIOSSl3AzXAYl9/ZVLK931uG48DnzDh82k0Gs0Bw3dWfIdLn7o028PQaDRm4HbAK0ugd0dywo1hvEPQXwf/XQyunoSb13XVBb13epymRsEdTDz8cHwTvuXlanJ43TqVA7q6WkV2H3ssPPGEKj/uuNTHU9dVFyTWGFMwhiH3yGRioa2QPd17Ut+RJmWklG5gODp5K/C0L/r4FiHELb5qy4FdqPunh4EvRmvra7MUOEcIsRMluF/qa7Mf+A1KNLIOWCOlfDHdnzMWDQ0qhUUohxySet9hzhtt74EljlWMWZ+HT+6Hq13wyS5lgaoZtXz5y7BpU3xRysP098M558S/oJdOBt2DQanOxhaO9b/uGerRac80mgOE739fObpF4+yzleg3F4UbAPMmzovqhAGws9O8e46azpqo2wfcAxwx4YiI2wcH4dln4zMYKiuD7343dVewRCkoUKKRYd58Mz7Hv2nT4PTTExOZm022XGHSjrBA9SVw4Qa4YBMc+V3lomEtzHxqPmEHa+gKqUajGQ386U+Jp0yx2+FnP8uskDBZwq5VGl5I7hh56JdUUMVowJbhiwRNzmHGZVcVsC/gfT0qkitWnao42xrtb6VBXy7f69ByjUaj0fhYWb+Sre1bsz0MjUZjBqtug8EWkNFzM8eF9IBzP6y8CU75Z9zNBt2DdA12BZUNuAfY3LbZuIEmIm1t8NFHsesVFqqJ1rlzjXM/l5TAUUepOqeeCmvXJj+m3V27GXCNhGxOKJpA79DISoBFWKjrqos6ka3JHEbRyVLKBwNeS+C2eNv6yqNFNj8BPJHCkE1nz55w8UZ1tTmpiMKcOxpfBFeU1Xh7GZz6LIxbBHbfxEveGDj6FzD9Gnjr4+DqSn1gmozx0kvw2GPgSCBDGajvX3OzSqESaFefDZr7mimwFeBwObBgYWLxRP+9gd1qp93RzsTiidkdpEajSYmBAXjyyeiOCvn58M9/GkSy5hBF9iImFk+ksTeyu8C+7n0RtyVKfU/0VBKVJZUU2CLnDHnllfhdvr761dQdwZKhuBi+9a2R9y+9FNudBeDmmyNnw8oUufxdNY3SWUq8ceR3oWc77P0XNL8G+9eoFCjC7ksRYFIKMlupmksQNhi7ACrPhqmfNKdvjUaTMfbtU49Eueyy7JyLTGHvPxNPmWKxw6G3gTUL+b80miQwQ7xhdPkWehURqU48bePdX9x9CSFuRqVXYdq0aTF2p9FoNAcO7Y72iDljNRrNKKJ+Gex9GjwpOG6E4h2ExrC126jUdtZSZC+i1xl807ShZYN54zpI+Ne/Yt84WyzwzDMqXYqRcCOwXkkJvPaacuBIJvcpwLb2bbgDxEFTSqewf3A/rf2tAAx5hsKcVzSabFJbG1525JGJuSTETf1zQBRVyJJHYfwJ4ZND9hKoWAwnPq4EHJpRgZTwla8kLtwYZnBQHedzQbxhs6hpoHxbPhOKJpBnzcPpcZJnzaOpt0mLNzSaUc4zz8R2KfjEJ0aHk8H8ifOjijcG3AP0DvVSmp9a2HD3YDdOjzNqnQWToqdMWbEiPoel0lIl3siWGGH4fkNKePfd2PUtFrjlFuXaockgZYcpa/8jv6P+WY566PgQ2v8HXRvB0aACOVxdSnxhyVMuHqFICV4nSBfYy6FgAhRWwZh5MOEkdU1aPD376hyNRpM0K1Yk54x0553KCWrUISW0vJF4u6mXGR8nNZocxQzxRj0wNeB9NRB6ZR2pTl4cbePdX73vdcy+pJQPAQ8BLFy40CS5qkaj0eQ++wf3B1klazSaUchAE7z/KfAkuYIUjQT73NGxA2Ggn41lO6wJ56mnYi8K3ncfnHJK/JO9ZWXw9ttq8bon8Yw47OjYEfR+6piptPS3+MUbg+5B/b/W5BR7DLL4zJunHGtMZbAVHFHCm6ZfDVPOixzVY82HiWfAzBtg9+MmD06TDl58EeqjB2XHxG2CUVaqNPU2+V/bLDYqSyr94g2BoKmviQVEX6DUaDS5zeuvxxYRfP7zo2PB5qRpJ/HarteCxMSBFNoK2bV/FwsqUztu1e6vpdBeiGvIWO1ps9g4aepJUft44434UqZcf312hTPD1vM7d8Ynbj33XGWtr8kiQkDxVPWYdnnwNumFoU4YbALPkHLS8LrBYhsRdRRWQv54vWip0RygLFuWeHrG+fNVUNCopGe7EqUlyhF3KXdMjWaUYMZZexUwRwgxUwiRB1wNLAupswy4QSiOB7qllE1xtg1lGXC1ECJfCDETmAN86OuvVwhxvBBCADcAz5nw+TQajeaAoWeoB6fHidubA7PHGo0mcaSEd68EdxqEG0mwo2MHDoOxtDna9HEmATweWLUqep3jjoMbbkgsL7nNBuPHw/e+l9y49nQHr4TPGDODKSVTgsq2tG1JrnONJg00N4eXLVkS3akmKdo/iCzMKJgEix8CW4wfq70EFt6noh81OY2U8I1vQH+K5nU5Id7oa/JHl1uEhcrSSqy+vM9ur5vmPoMfkQYG22HP07D5p7D119D2nrKw12hykM7O2HUmT07/OMxgwaQFFOVFVi0LBLX7DWy3EqS2sxYZRXlRZC+KKhBxuWD79vj29YUvJHY9ny7efju+el/5yugQ+hy0CAsUjIfyo6BiIYw/HiaerJ4rFsLY+VAwUQs3NJoDFCmVeDBRvva1NNwjZ4qWFSScPqp8AZTOTstwNJp0kbLzhpTSLYS4HXgZsAKPSik3CyFu8W1/EJU/+QKgBnAAn4nWFkAIcSnwB2AC8KIQYp2U8lxf308DWwA3cJuUcjiT463AX4BC4CXfQ6PRaDQ+HC61yNra38qU0ikxams0mpyj6b+wf62KqMkBNrRsMBRp5Fvz2dO1h1njZmVhVKOPDRti21zef39ydsWFhXDrrXDvvYnlQZVS0tbfNtKPrZAppVOYOmZqUL3d+3cnPiiNJg1ICR0d4eUL0mEi0LkaIqWhO+wrKp9uPFjscPjXYc1XzBubxnSWL0/ddSNXaOhp8LvwSSRTS0eO6YPuwSBnDg3g7IJ134Zdj6roZXe/ima25CsB16L7YOontd28JqcoKYldJ1UxWqZYULkAtyfyfc+Ae4DaztTFGzWdNQy4BiJud3qcUdOmbNigFsGcMQKBp02DQw9NdpTmsnx5bNe/igrl+qfRaDSa3GT79sRThJaXwxVXJJdqJSeofw48kc/Zhhz+NXX9rtGMIkz5iUopl6MEGoFlDwa8lsBt8bb1lf8H+E+ENj8BfmJQvho4MpGxazQazcHCgGsAly9CrKm3SYs3NJrRhpSw5qtq4SBH2Ny22bDcZrGxs3OnFm/EyVtvRb/hvvBCOOKI5C2WbTb49a/hyivjb9Pa34rVYvWfN+xWO5Ullcwon4EFC168ADT2xcp4qNFkhp4eY7vy6dPTsLPWtwFPeLm1AA79YmRXjrD6+TDrc7Dhuzl1bNcE861vJW5FnKvs6trlf+32uplePh2PLxbGIz3UddVlaWQ5SMtb8PbHweME75B6gLJp9jrB3QsrPwPbfgtnvKLcdDSaHGD+fCX4HYySLfWf/1RpxeJNxZctppZNRUaJrnV5XWxq25Tyfja1boqYmgWUU1G0+ZP334/PXenaa5MZnflIqe4/YnHaaTA0lJyAXKPRaDTpZ8UK8HoTa/OZzyTeJmeQEtr+l1gbe7kSW1tGq1pFc7CiPbM0Go3mIKGpr8nwtUajicKkSbmz38YXwZFI6K+ACSfBjGthxnUw8VRVZiKBaTUsAVasQ54hdnbsNHVfBzIvvhh5gt1igfvuiy+KMhJ5eUoAcswx8bep66oj3zoSmSAQVJZUMrlkMgX2kRncQfcg/U696KzJPg0N4YsL5eVp2lnXeuPyGdcn19/MG5MfiyatbN8Ou3bFrjdaqO8euY5wepzMHDsTl2dEPVjXXZeFUeUg+9fDWxeBqwe8UVbA3f3QuQbevFCnUdHkDJ/6lLGYMZC//GV0GMYIITi0IrpVxba2bSnvZ1tH9D7mVsxFRPmDrVgBA3EEAX/+88oVL9s0NMR23QD42MegtDT949FoNBpNcsR7/gnky1/OjfRdSdG/m4RTplRdAFJfp2tGH1pupNFoNAcJjb2Nhq81Gk0UmhPM/R5tFjTWLGosNnwf3HGE/tpK4JDPwhHfBHvIbJvbAVt/BbUPqwWJFOh39tPnHBmPN0C6P+geNCUK7mDA61XRepE4/3wYOzb1/eTnw7e/rewx46Guqw6vHPmfur1uKksqae1vxR6QEqLQVsie7j0cMeGI1Aep0aRAQ0O4O01VlYoYNTWf72BrZJeMed8JP+7Gwl4C874NO+9PfWwa03nsMfAYmKyMVkIF3FWlVTg9Iz7/jT36HoG+3fDaGfFdc4Fy5OhcDe9dCyf/A4SOkdJkl8pKleritdci12lrg5/9DL75zdQEwplg0ZRFrG+JIJoEavfXppzGb1dndJXe4qrFUbevXBl7H/PmZS8uIJRdu9S1UTR3FoBzzkne+U+j0Wg06Wf16sTqV1aqx6ilc61y0Ejk/mzKhWAvS9uQNJp0ocUbGo1Gc5AQmMNaizc0mlFG5xroiSOqrHg6nP0m5E8Am4GU3l4G838Ic78KK06H3uTdMWo6ayiyF9Ez5BOBCMi35DPkUbbiG1s2Jt33wcSWLdG333EHlJlwn2m1KveNMWPiq7+7a3dQ7u9B9yCTSiZR2R98p28RFuq66rR4Q5N1OjrC7V+rqtJgCdu5FqyFKm1CIOVHQcH45Pq0l8G441Ifm8ZUpIRHHwWnM3bdyZNVip6uLtiWehB42mh3tPtfl9hLsFqsFNgKGHCr432rozVbQ8sNXD3w6qng7k6snccBjcth3Z1wzC/SMzaNJgF++EN4773o0bj33APHHw9nnJEbbhCRKLJHz+3SMdDBUQ8cFdUZIxpSSvpd0V3koo2hvR06O2Pv55prwG6PXS8T7N0bW5hYXg7V1RkZjkaj0WiSYGAAmhI01j7jDHVvM2rTYXV+BK4E81lWnpOesWg0aUbrZzUajeYgIVCwUbu/Nosj0Wg0CbP5Z9Ftu0Et/J2/BgqrjYUbw9iKoWASnLsKxp+Q9JB2dOxABriJjMkfQ75tJLxdH2fi4623Ii8uT5wIJ59s3r48HjVxHA/b2rcF5f7Os+ZRYCugsqQSV4A1/JBniLquOvMGqdEkSW9v+EJEVRXYzA5X6PxIuRiFMvVyEEmuyljyVR5eTU6xYQP0xZgbLC+Hhx6C2lp46SUV/bZ2Lcyfn5EhJoTH66HX2et/X1aglIGl+SNuMfsH9ged2w86NvwAhtpBJqH68jhgxx/NHpFGkxQnnqjEGUXRdQ9cfjk8+yz053AGvKMrj45Zp9+lHAGTecQSbgAcO/nYiNs++CC+RbBzz1WpDHOBurrYaVNOOSVxK36NRqPRZI6NG2Of50O56CJzgoOyRts7QALX6cUzo8+PajQ5jBZvaDQazUHCvp59/td7u/ZmcSQajSYhPEPQ+EL0hYTS2XDWm5A3TlkIxsJihbwxcOarMObIpIa1o2MHDtfIrN/E4olB2zscHUFW7Bpjli+PPDF6xRXm2vWXlMAXvhBf3R0dO4Lejy1UuVsmFk9k0D0iJBp0D1LTWWPaGDWaZOntBbc7uKyqKg3RxK1vG+fMnX4NWJPMz2LNg+lXpTYujek880x01405c5Ro4/rr1fesvFzlj54/X6XD+tznMjbUuGhztJFnHVk5HFswNuh5mECBx0FFXx3UPBhbLBsN75Bpw9FoUuWrX1Wua9GEBYODcO218JWvqMX8eJyG0kE08chFh16UuYFE4MJDL4y47b33Ygv9LBY4MrlbrrSwfXtsZ7Kzz879lDoajUZzMLN2bfj9byzOGe0mFF0JpmeuPIuExB4aTQ6hxRsajUZzkLBrv8rjKhA09um0KRrNqKF5BYgoYVoWO5z6nLLxTxRLIZz2HFgT90xc37IejxxRFswsn4nLM7KgWWgvTDn/9MHA+sgpvLn5ZrUQaCaHHRZfvT3de4LeD4tz8m35FNiCvy9b2mLkftFoMkBvb/ii0+zZKmWQqXStCy/LH6/SVqVC4eTU2mtM529/A5eBTgegtBRefVWlogoVCFksKgru3ntV9Huu0NzXTJ5l5HpifJFK8zOucJy/LN+WH5Rq8aDio/8Db4R/eLwk49ih0aQJIeDxx+H882NH5j78sLpG/Pe/lag4UyIOh0MJH371q8h1JhRPwCKyN31tFVbKC8ojbt+8ObYQ4ogjIp9PskFtHAaJxx2XhmsojUaj0ZjGypWxXZQCOeQQ8+eXMspgu3K6S4TqS8CmlYia0YkWb2g0Gs1BwrDzhhAiKN+1RqPJcfY8Ce4oUbALfqIWDS1JzK5ZLFBQCcf+NuGmoQv2R048Mshpwyqs7OzcmfiYDiLcbmhpMd5WURG/0CIRYk0ug8r93dbfFlQ2pXSK/3XgQh+gRTqanMAo3/zMmSbvxOtWKRVCqTw79Yj7VBeNNabS3Az19ZG3//OfKrVVtIWtoiJ4/nmYnCO6nKbeJoQQ/veVJZWAWhgdxiqsNPUdhOKN9pXQ/CrIBMMXNZocp6BACTJ+9rPYTlT19cqF44gj4P77oa0NenoSj+qNxeCgWmzavh2+/33lkvWDH0RvE+oQlEkqCiuibt8bh6np8cer265cYd++2HWmTk3/ODQajUaTPBs3Jlb/rLPimw/KWfp3Jx54NvHU9IxFo8kAOXTpqNFoNJp00tzXDCjnjZ6hHjxeE734NRpNevB6oH4ZECH//LiFMOe21HI42opg5qcSvqnZ2z0yU1loK2Tm2JmMKRjjLxt0D7KzQ4s3olFXB/kRsiyceqqa3DabeCItWvtbsYaIgaaPGXEVCE2Ro92cNLmAkXijstLknQw0gsXgRzv5Y2DLcYDzAAEAAElEQVRPMXmwvTS19hpTef/9yMfnCy5QjhrxpOQpKYFf/tLcsSVLU18Tbu/IKuyweGP4GcArvf57hoOKj+4AT4QcZpq0IIQYJ4R4VQix0/dsuDovhDhPCLFdCFEjhLgznvZCiLt89bcLIc71lRUJIV4UQmwTQmwWQixN/6fMDYSAL38ZXn9dic5iuXDU1ak0KpMmwbnnwoMPwrZtyo2ju1ulOJERbk1C8XiUM1Zvr3L0+PBDJSRZsADmzlWOGz09sfuZP2l+fDtMAwsmLYi6vTmOQ+aZZ+ZOtLOUSpgTi4kTY9fRaA5WIp2bArYLIcTvfds3CCGOjdU20nlNCLFYCLHO91gvhLg0M59Sk+vEI8QL5JJLRnk6rP66+C9AwJciWsSsptHkKnEkRddoNBrNgUDnwMiqRp41jzZHW9BkrUajyUHa34u+/djfgiXxlCdh2Irh2N/Bf4+NWRWgZ6iHQfeIssButVNdVk1lcaX/WDPkGWJja4KhAAcZ27dHjto+5xxly58N6rrqyLfm+//HVmFl2php/u1VpVWsaVrjfz/oHqTf2U9xXo7MSmsOSrq6wstMn5zq36NSVYXqX8efYPKONNnmnXeUlb8Rv/pV/MfnvDy47DLlArM7yyZFjb2NDLiVQMFmsTGpeBIAk0smIxBIJEOeoYMvbUpvDXRtyPYoDkbuBFZIKZf6Fq/uBL4VWEEIYQXuA84B6oFVQohlUsotkdoLIY4ArgbmAVOA14QQh/q6/JWU8g0hRB6wQghxvpTypQx81pzg+ONhzx747W/hJz9R0bcDUTRLUipL9pUr1fu8PDj6aCW8mDoVZs2C6dPVIr/Npq5pPR4YGoLGRiUC2bVL7XP1anXdm8iaSyAnTj2RN+reSK5xipw07aSI26SEjo44+ojcRcbZvz/2/6G8XIl+NBpNODHOTcOcD8zxPZYADwBLkjmvAZuAhVJKtxBiMrBeCPG8lNou7GDG44nv/BPIkiXpGUvG6KsDTwIRTmPnEzEQTqMZBWjxhkaj0RwEDLoHGXKP2HnnWfNo6m3S4g2NJtfZ84/IOR0rlsC4Y8zz4C2dDZPOjKvqzo6dFNoLcQ2N2PxXl1UzdcxUtrSPzFlsat1kztgOULZvj+yuce652bNXruuqwytH/DQLbAVMLhnx/Z9ePj2ofqGtkD3dezhiwhEZG6NGE0p3d3hZrOjihOnfAzJEuSFsUHyIyTvSZJsVK4xthS+4AKqrE+vLaoUf/Qg+9SlzxpYsgcf2PGuePwXW+KLx5NuUYM/pcfpTLR407LhPpUTSZJpLgNN9rx8D3iREvAEsBmqklLsAhBBP+dptidL+EuApKeUQsFsIUQMsllK+D7wBIKV0CiHWAAn+mkc/BQVw111w661w773w61+rRfp43C+cTuWc8eGH6R9nKOfPPp+fvPOTzO8YuODQCyJu6+qKLXIoLk6DE1gK7N2rvgdOZ+Q606ape5RIDlQazUFOtHPTMJcAj0spJbBSCFHuE17MiNLW8LwmpQycECpAr0ZrUCLJ/HyVhiwe7HYlzBvV9GwFmUCq0eIZYDV7QkCjyRw6bYpGo9EcBDT1NlFgG4nOFwgae7XNvUaT8+x7JnyhcJgjvweWODzb48VWrPqMgx0dO5ABIVtOj5Pqsmpmj5sdVG/X/l3mje8AZN0644nT8vLEFwfNZHfXbgZcI6GYNostSOw3rWwaNsuIBtwiLNR11WVyiBpNGEYLTwUmGBMF0V8H7pAw5bK54E1DjiNN1nC5VIoAI5YuTdwVKS8PLr88u8d1CE53ZrPYqCiqAGBc4TjsFrt/2+79WbYIySReN+x6NPZE8Nhj4YxX4BP18PFaWLA09VRJmklSyiYA37NRkoYqIFBNVO8ri9Y+WhsAhBDlwMXAitQ+wuilvBy+/31ob4cnnlBW6gUF2XF9EyL2fk+ozp7D1XGVx0Xc1tAQW+AwLITIFdraYgtOpk1L3iVFozkIiHmeiVInmfMaQoglQojNwEbglkiuG0KIm4UQq4UQq9viyY+kGbXU1SlBRrxUV+fWuSgpenYkVn/MPLBo7wLN6EWLNzQajeYgoKmvKWihzeV10dR3kFkiazSjjaFOcHYabyuqhsozzLVmEBaoWBRX1e0d2+l39vvfuzwuxheNZ2b5zKAFoK7BrqD0KppgNkbIKnPyydFtrNPNtvZtuAPmgyQySLxRWVIZJAgc8gxp8YYm64SmuBBCLZqbSs82wnKmjDsWnUv3wGL9euPFuDlzVJqAZLn++uTbmkFDb4P/tUBQUajEGxWFFVjEyPVEfU99xseWNVreiL5CacmDk/8F57wDk86CoiooOQQO+5IScky/OnNjHYUIIV4TQmwyeFwSbxcGZbGWlKO2EULYgL8Dvx+OfDYY90Gz+JWXBxdfDM8+q4QcjzwCF10E48er42BZmflOcHa76tduV2lXbrwRli2L3sZisVBgNVuRGZtCWyGWKH+AhobYf5+qKmMnp2zhdMYWZkydmoZrKI3mwCGec1OkOsmc15BSfiClnAcsAu4SQhgeEKWUD0kpF0opF06YMCFWt5pRTF2dSp0SLzNngnu0G805EnQHLJ2TnnFoNBlCS480Go3mIKCxt9Fvk2wVVgZcAzT0NMRodfAihDgPuBewAo9IKZeGbBe+7RcADuDTUso10doKIcYB/0DZJNYBV0op9wf0OQ1llfgDKeWv0vn5NKOE/WvBWgheA2uGqZelJxxKxDc7u755PV5GZiHHFY7DIixUl1VTYCvA5VQRrEX2Imo7a5k3cZ75Yz0A2BXBmOSUU6CkJLNjCWRHR3BEg8vjChNvWIXV/37QPUhNZ03GxqfRGNHfH/y+uFhNUJm6+NBr8D0ff7xyLtIcMLz/vnLfCOXGG1UKlGQoLISbb05tXKnS1j+yCO2VXn/alOHnYVr6WzI6rqxS+wi4+yJsFHDyP6HybLCFWC4Pv1/yJ3D1QOPytA5ztCKlPDvSNiFEixBispSyyWcl32pQrR6YGvC+Ghi2j4zUPlobgIeAnVLK30UZ90O+eixcuPCg8R8oLoYrr1QPgJYWlSLlvffgjTdUuo2ODrWtoECJFjwedUvi9apni0WJJy0W9XC7R9JvVFTAYYfBWWfBCSfAcccldr07vXw62zu2m//BozCzfGbU7Q0NsRfDqqrAlkOz70bnt1CKinJrzBpNjhHrPBOtTl6UtjHPi1LKrUKIfuBIYHVKn0Izqmlrg6Gh2PWGmTHjADiuu+LI8RZI0dTYdTSaHGa0/2Q1Go1GEwdNvU04PU6sworFYkF6Jbu7DiJL5AQQQliB+4BzUDdcq4QQy6SUgfkrzwfm+B5LgAeAJTHa3gmskFIuFULc6XsfmNf5t8BL6f10mlFF50fgiWC/MPPG8IUEM4gzom1be7Cf/PDCfnVZdVD0rhCCnZ07tXjDgO7uyPlJjzsu+QVCM9jTvSfo/ZBniPFF4/3vK0sqkSEBQlvatqDRZJPQ31NpaRrEG0bRPhVL4ha+abKH260EPiUlsY+vr75qbCt8/fWx7fGjMWlS8m1TRUrJ/kG/Zhi31+1Pm1JRVIHbO7L62DHQkfHxZQWvBxpeIGLA68I/QOWZ0a+3bEVw8tPw2unQqddQEmQZcCOw1Pf8nEGdVcAcIcRMoAG4Grg2RvtlwJNCiN8AU1D3ax8CCCF+DIwBPpeGz3PAMWmScuW4+OKRMilVmrLGRiVcaGlRTg4ulxJy2GzKUaOgAKZMUcKFyZOVGCBVFk9ZnHHxxuLqxVG319dHvp4fprpaCfhyBZcrdgyA3W6+44pGcwAR7dw0zDLgdiHEU6g5w26fKKMtSlvD85qv7j4ppVsIMR04DBUQpjmI6eyMT4w3zCGH5Na5KCk8/bHrDCMskD8+dj2NJocxRbyRyQhlIcR1wDcCup8PHCulXCeEeBOYDAyvdHxMSmmk3tdoNJqDir09exnyDFFgLUD4XPq0xX1EFgM1wza6vputS1CuGMNcAjwupZTASiFEuU8ZPyNK20uA033tHwPexCfeEEJ8AtgFJHAlqjngaX3L2HUjf7zK3ZhF9vbsDXo/bcw0QIk3XN6RO8gB1wA7O3ZmdGyjhdpaNZHdYxA8cOihmR/PMFLKoOhsgJK8EqyWkdXOypJKnJ7g7+bu/VoQqMkuobaxw+IN05ASBg3s84uqTdyJxkz6++Gxx2DpUrXAZrerSc7DD4fvfhc++UnjXNEbNoSXzZoFqbpPiyxm1+ke6vbfA4AS5Q07blQUVgSduwfdgwy5h8i3paBUGQ10rQcRQckz/ng45NPxuerYiuGkv8MLh4HModwIuc9S4GkhxE3AXuAKACHEFNTc4AW+harbgZdRc4aPSik3R2svpdwshHgadf/lBm6TUnqEENXAd4BtwBo1TckfpZSPZOjzHhAIAWPGqMfhh2d236fPPJ2/bvxrRvd51oyzom6vrY0thJg1K7ui7FDiFW/k0pg1mlwi0rlJCHGLb/uDwHLUOlgNai3sM9Ha+ro2PK8BJwN3CiFcgBf4opSyPQMfVZPDtCa44nnEEaP8uO5xgjeBm/uCyeAdAov2LtCMXlL+9mY6QllK+Tfgb759HwU8J6VcF7Cv66SUOuRBozkI6R3q5Zmtz3Dj0Tdmeyg5x/Cims1q80fWNfU2ZXNIuUwVEBhaW486d8WqUxWj7SQpZROAT3E/EUAIUYwScZwDfN2kz6A5EOhcY1xedbESdVizs6jS4egIitAFmD1uNgCTSycz6B4JV3Z5XaxvWZ/R8Y0W2tqMF/KsVqisDC/PFK39rVgt1qCFvIrCiqA6FUUVuDzBYR6NfaFOsRpNZgldiCgpMTnH/FCHiuAJ3I+wQN64iE002UFK+OlP4Wc/U++HU+o4fZqzLVvgC1+A226D3/0ObrghuG2jweHs/PNTH1c2o92a+5rJt+X705rZLXbyrMqWpiy/LOi8XmgrpLmvmenl07My1ozR8oaxSBZg8f9TqevipWASzPwM7PqTOWM7CJBSdgBhK+NSykbUgtfw++WoRbC42vu2/QT4SUhZPZBFCZUmVS6ac1HG93nBnAuibt+7N+pmAGZGz7ySceLJvClEdgWHGk2uY3Ru8ok2hl9L4LZ42/rKI50X/wpkVrmmyXnaDGIKojF7dnrGkTFc3WDJB6+BPaIRJTPAm4A1iUaTg5hhguaPUJZSOoHhKONA/BHKUsqVwHCEcrS2l6Aik/E9f8Jg39cAfzfhM2g0mgOAd/a8w6ef+3TYoqIG9nUrPYFA+P8+bY4Er/QOHoymKUKnOCLViadtKD8EfiuljJRwW+1QiJuFEKuFEKvbEr1K14w+XD1qodCIaVeCvTSz4wlgZ+dOCm0jCxr51nx/Pug8ax4lecHJqze3bkYTTmen8cLyjBmJ5S41m7quOvJDhEGTSoK9/i3CQml+8Hdw0D1Iv1ObB2myR+jvyfScvs79YAmxaSicoiJ6NDmDxwOf/rQSb/T3jwg3Qunthf374ZZb4J57RhazmpuNvzsf+5g5tv/Zoqm3CWuAy0TguVoIQZF95MPZLDaa+g4CkXfD88a/32lXQvHMxNIh2Uvh2F/G59Sh0WiSYmLJxKD0jOnGIiyMK4ou0Iznmr2qyqQBmYTdHluYMZwGR6PRaDS5SWdnYvVz7VyUMM6uxFw0Cqt0alPNqMeMb3Ck6ON46kRrGxShDEw02PdVhIs3/iyEWCeEuNuXriUMvQBmLlf+80oe+uihbA9Do6Guuw6Avd1xhD8cZDT3NwPglV68PjvfnqEe/2tNEPXA1ID31UBoDGakOtHatviEi/ieh03ulgC/EELUAXcA3/bZKAYhpXxISrlQSrlwQqq+3Zrcp3Nt5Bzr447L7FhC2NmxE493ZDYv35pPddlI2oBJxcEL/cPHZk0wHR3GOUoPO8zkVA8JUtdVF3ZuqC4NTwsR6sZRaCtkT/eetI5No4lGaCSp6bnaXd3hE0DF03VETw4xOAgXXgj/+hc4HPG1GRhQaVW++EUlAKqpgby88HpLQj3YRhlNfU1Bx/YxBWOCtpfll/lfSyTNfc0ZG1tW8HqgY5XxtqN/npxI1pIHsz6X2rg0Gk1UxhaMzdi+Qq91jTC6lg+lvDz1sZhJvOINU93LNBqNRmMq+/cnVr+gID3jyBhG9+LRsBagDdc0ox0zprQyHaGsOhRiCeCQUm4KKL5OSnkUcIrv8SmjtnoBzFxeqnmJl2tezvYwNBp27d8FQE1nTZZHknt0OFQEv9vrptiuIsLsVjvtDp0m0YBVwBwhxEwhRB5wNbAspM4y4AahOB7o9gkNo7VdBgzn9LkReA5ASnmKlHKGlHIG8Dvgp1LKP6bv42lGBb07jfM55o0De1l4eQbZ1r6NftdIKLMQIki8UVUWrOHtc/ZpRwYD2tuNo/UOOyy7N9a7u3Yz4BoIKpsxdkZYvcqS4NwuFmGhrqsujSPTaKITusiQFvFG6O1r0TTMuaXWmMHVV8Nbb8Uv3BjG4YDHH4fvfAdqa8MFdJMmQVl2T70p09TbFJTWbFxhcDR5eUG5/7XL4zrw0yt2bQBhkPh7/AmQPz65Pm3FMPerqY1Lo9FE5aiJR2VsX/MnzY9ZJx7BtdXgUJNN7PbYdYaGtPOGRqPR5DKDcWYPGcZ0V8pM43WRkBjDYk+svkaTg5gx05TpCOVhribEdUNK2eB77gWeRKVl0aQRKSUDrgH29eyLXVmjSTPb2rYBWrwRypB7iAG3Wohzepz+SLs8ax6NvQZJvQ9ypJRu4HbgZWAr8LSUcrMQ4hYhxC2+asuBXUAN8DDwxWhtfW2WAucIIXYC5/jeazTGDDSBZyC8fOwxxuUZZH3LemSA1tbpcQaJN2aNnRVUv9BWqI/LBjQ1GeecnjMnu+KNbe3bcMuRmeg8a56h80bg/xxgyDOkxRtZRghxnhBiuxCiRghxp8F2IYT4vW/7BiHEsbHaCiHGCSFeFULs9D2PDelzmhCiTwjx9fR+utiE/p5MXyxx9YTvpHg6BKSR0mSPp56CV19NfCJzGIcD7r0XduwIF3+ccEJ201mZwd7uvbgCXGLGFwYLFALfD7gHaOhtyNjYskLLG8auOXNuBWsKv+m86CkWNBpNapw47cSM7evkqSfHrBOP80YuijdiOW80NY3+855Go9EcyCQqsDM9sCHTyAQ/sLDrtCmaUY8Z3+CMRigDCCEswBXAUwFlNiHEeN9rO3AREOjKoUkDnQOdeKTnwI/M0YwKhhcHt7RtyfJIcovmvmYKbGolsMhe5LcaFQj9242AlHK5lPJQKeUsKeVPfGUPSikf9L2WUsrbfNuPklKujtbWV94hpTxLSjnH9xyWoVBK+QMp5a8y8Rk1OU5/HWDgVTvu2NQWFUxge8f2oPdDniEmlYykSpk9bjY2MSLrFwh2du7M2PhGC80RHOknT87sOELZ0bEj6H2+NT/MZQNgRvmMoPeD7kEt0skiQggrcB9wPnAEcI0Q4oiQaucDc3yPm4EH4mh7J7BCSjkHWOF7H8hvgZdM/0BJELoQYSSOSglXNxAyaVQ8wxfVo8kmTU1w882JO26EMjAAGzaEf3dOPhlKSlLrO9uEpjALPa5PLA7OUrt7/+50Dym7NL8G3hCljyUPpl4GlhRWWq35qY1Lo9FE5fzZ52dsXxfMuSBmndHovDFmTOxrpL1703AdpdFoNBrTSDS11ah33khUvGGJQ6mo0eQ4Kf9spZRuIcRwlLEVeHQ4Qtm3/UFUhPIFqAhlB/CZaG19XS8FnhZC3ATsRYk1hjkVqJdS7gooywde9gk3rMBrqGhoTRqp3V8LQMdAR5ZHotFAQ5+KENvYsjHLI8ktGnsbsVnU4b4sv4wJRSpdlMvr0s4bGk2u0r/XuHzCKVldGJBSUt9TH1Q2Jn+M/xgDypGhwF5An7MPAIfLESYI0EBbm3F5tjP67eneE/TeIiyG4o2q0iryrfkMeUbC8rR4MqssBmqG74+EEE8BlwCB/5RLgMellBJYKYQo9zkczojS9hLgdF/7x4A3gW/56n0C5UKVE3mRQudmTM/V7uwOT2dVoFNwZhsp4dprlfDCDHYaaA2PPTb3Ft8SJfTcPaV0StD7ytLg4/zengjXIQcKPVvDyyadYZyyLhG0mEujSSsnVp+IVVjxRFjEmVY2jWOnHGu4LZTVjavDjo3D2ISNhVMWxuwjHoFDrq0dTZsW2zFk717I11o0jUaj0eQKCZ9MvZApEeIzlTDYkqbOLXCtzmN2sGKK5kpKuRwl0AgsezDgtQRui7etr7wDOCtCmzeB40PK+oHjEhy6JkVqO5V4Y8A9QJ+zj5K8UR6SpBm19Dn7/AuFu7p2xah9cNHUN+KuUV5Q7o+QH3QNavGGRpOrDEb4bZbMyOgwQmlzhCsOJhVPCnpfXVaNNSCPvFu6Wd+yPu1jG210RNC9VlRkdhyBSClp6w/+H3ul11C8UVlSGSbeOOAjtXObKiAwj2E9sCSOOlUx2k7yOSYipWwSQkwEEEIUo0Qc5wBZT5kCGRBvuLrB6wwuyxtrXFeTMV5+GVatii/6OR4aDU6/s2aFl402WvpGJhTzrHmMLwpOm1JZXIlFWPBK9cM5oN35pBccBmlhKs8GW3Hmx6PRaOLGYrFwxIQj2NhqHLBTWVLJf676T1x9LXxoYUTxxpETj8QSh8e8PQ69llnnJ7OorIwt3mhpie+zaTQazcHMT9/+KT9+58e8eO2LnDHzjIzuO9E0KB7PKBejiwQH73Vh6GacDtIm3ICMfQZNTqIT/2hSItAGfdd+vWCuyR61nbV+m/7mvmb/xKNGOW84PWqxYXzReH+knRev/t1qNLnKYLtxef5E4/IMsaNjB/khzh9Tx0wNel9dVh0WDbelVTsyhNLVZVxeXp7JUQTT2t+KNcQufsgzFFG8IUJWyxv7tCAwixiFooTGmkSqE0/bUH4I/FZK2Rd1UELcLIRYLYRY3RbJbsYkQsUbieYBjslQG2F/lrxyk3eiSQQp4Vvfgn4TvV+M+qoMPwSOOjoHRrL12S12KoqClYIVRRVB5/cD2lmzf6+xQ8aUC8Ay2j2lNZoDnyVVodrUEUId5KIRre6S6sj7CCQeG3rTr0dSxGKBceOi15EystBco9FoNPCL937BD976AQPuAS76+0W8tuu1jO4/GfHGqCZh8YZT5//SjHq0eEOTEptaN/lfD7twaDTZoKazxm/bn2fNo6HHIJrqIKW+p55Bt8rpPLF4IhOLJ/r/VolMbmg0mgwhJTj3G2/LcpT3zo6duEMsxWeNDQ5JriqtYsAV7F+vjzXh9PYal5eVZXYcgdR11YWJc7zSS1l++KAqSyrDRDqD7kH6nTmRQeNgpB4IVFJVA6Fqmkh1orVt8aVWwffc6itfAvxCCFEH3AF825cOMwgp5UNSyoVSyoUT0pwTKHQCy+Uy2ap8yEBUZ8viD1bDO+9AbYxbUJsNrrwSXnoJVq6EZ56Bc8+N/N0IjTSePDn3oqYTZcA14BdyA1gtVsYVBq/cVRRWYA8QNPQO9eLxjvZZ3gj0bAsXb9hKoGR2dsaj0WgSYlHVIorsRYbb2h3tYfcqRjg9TvYPGN9vFduLWTRlUVxjicedwnQnMBOYMiV2nXpjUxKNRqM56PnJ2z/hh2/9EJdX2Rg5XA4ueeoS/lvz34yNIdHUVqP9fgZbcWJijEw6b2g0aUKLNzQpsa19m/917X4t3tBkj52dO/2TknaLnZrOmiyPyFw8Hnj2WfjYx+Coo+CEE+A3v4GenthtA901JpdMpqJwJLJOp03RaHIQd4RVfVtJ1pMmb23fSr9rZHHebrFzyNhDguoU2gspsBUElQ24B+gZiuOAdRBhZFdssUBBQXh5pqjrqgtzriovKA9z2AAl3hhyDwWVFdoKtVAne6wC5gghZgoh8oCrgWUhdZYBNwjF8UC3LyVKtLbLgBt9r28EngOQUp4ipZwhpZwB/A74qZTyj+n7eLEJ/Zr29SUekRSVoc7wMrtOGZlNfvpTcDgibz/3XGhuhocfhvPOgyVL4NJL4Z//hN274eijw9uELsTNng1OZ3i9tNO9Fbb+Ct65Ap4/FP5RDH/Pg6fy4OkyWL4AVn4Wdv4/GGiO2lVLf0vQeVkgqCgMdt4YVzgu6Fhvt9ppd0RwARvt9GwHz2Bw2YSTwBPly6TRaHKGBZMW+INRQimwFbC3e2/MPvZ07aHQVmi4zSqsLKhcENdY4nHeiGfOJtMcckjsOlu0caJGo9GE8f03vs9P3/0pDlfwdaPD5eCyf1zG89ufz8g4EnVszcr9jJnYy0EmoEBxdqlUiRrNKEaLNzQpsa9nHxahvkabWzdneTSag5lNrZvw+hSVLo/rgBITvfEGVFXBpz4Fr74KmzapyMG771bRgEuXRhef7utWaewtWKgsqaSiqMJvi9/mSK+FuUajSQJXj7Gdd2Fl+GJDhlnfsj7ofYGtICxtCsCEouAI+yJ7ETs7dobVO5gxOm6XlcXOQZ1OdnftDnNNGV803rBuSV74orVFWKjrqkvH0DQxkFK6gduBl4GtwNNSys1CiFuEELf4qi0HdgE1wMPAF6O19bVZCpwjhNgJnON7n5OELrr39pqc19c7FF5mLTZxB5pE2LsX3nor8jXwpz6lXDYqKsIdjUpLYepU5dxx+unB20K/M4ccksH80K4+2PIrWDYb/nscrP8u7PsX9O5UwgLpUlFk7l7o2gC7/gxrvgrPzYCXj4e6Jw3/IE29TUEpsbzSG+68UVSBDEgLlGfNo6mvKW0fNavsXxv+e65YokSyGo0m5zly4pFhi2bD2Cy2uFyBa/fXhqUKHMbhdjBvwry4xhJP5HNDDprCHnZY7DqvvhrZKVCj0WgONqSUfHvFt/nV+7+KeA4acA9w1b+u4j9b/5P28cRKfxVKc3Std+6TV+5z04iT/joQeulbM7rR32BN0gy4Buhz9iF8abK3tGlZtiZ5Bgbgr3+F73wHvvc9FRGXyAJW4PfP4XYEucKMZv75T7jwQmhpURGkgTgc6nHPPXDrrZHtOJv71BVavi2f8UXjGV803v+77R7sDouy1mg0WcbrBgwcNvLGgcyuhfmOjh1B7y3CQnVZdVi9qrKqoPdSSnZ2avFGIEbHbJstu9bK29q34Q6JZphcMtmwrhCCsYXBaXyGPENavJFFpJTLpZSHSilnSSl/4it7UEr5oO+1lFLe5tt+lJRydbS2vvIOKeVZUso5vucw+wkp5Q+klL/KxGeMRlGIg3pvb3x25nFjdPy1ZtEq5yDnn/+MvO2yy+CBB8K/E4FYLFBSAi+8AAsXjpSHOrhMmJABRyTphdo/w7NTYeP3oK8WPAPGgqFQPA5Vr+MD+PBmQ4euUBGG0+OkoijceSMw1YBA0NSbJfFGZaX6HOl6vP238H2OOw4iRPJrNJrcojivOKK42OlxxhXIU9tZy5DH+Bg7qXgShXZjV45QqsNvg8LYvTuurjLKIYdEP0cCvP12fM4iGo1Gc6AjpeSbr36Tez+4N6JwY5gB9wDXPXMd/9wc5WbFBMYbnwYjEivVZM5jK0lsPrR/D1jjO5drNLmKFm9okmZ31+4gm0Ftk61JhqEh+MY3YOJE+OIXlf3xPffATTepsp/8RKUMiUXo929Dy4Y0jThzPP003HijErZEw+FQwpdPf9p4e/uAsjy2WWxUFFVQUVjhF2zYLDY6HB0mjlqj0aSMdBunRzFy48ggUsqwVEtur5uq0qqwujPHzgx673A5woQfBzNSGkeLW62JpfE0G6P/kZGzyjChE+eD7sEDLm2ZZvRQHGKC4XCY7JhgNFmko3myxhNPwKCBGVVlJTz6aPj3IRKFhfDvf48INEKPwRMmmCwCCmWgGf67CFZ/CVxdSrSRLO5+w+Km3iZ/eklQi5tjC4LFdxWFFUF13F63XwCecVpa0tt/sYHl8pgj0rtPjUZjKvMnzjcsH3APsL19e8z2W9u3Mug2djScP8m4byNmzYqd1bK2Nr45rUwybVrsc9uePdBvfFrRaDSagwYpJXf89w7uX32/oXBDGAReDbgHuPHZG/n7xr+nbVyTJiVWf8uW7AYKpYwQiQVOuPsggkhToxktaA2tJmlqO2uD8uK2O9pxe90Rc09qNKF0dcHHPqbSgIQKFIbtGX/6U3j3XWV7XBhBMDnoHqR7sDuobLRHeDc0KAFLLOHGMA6Hmnh+/PHgcqfH6b+4tAgLFYUVVBRV4PJZjeXb8mnqa2JC8YTQLjUaTbaI5Lwhsnt+beprwiqCV0IH3ANMKZ0SVnfOuDlYsPjTWXmkh3XN6zIxzFFBpJvmbIs3jM6dvYO9/G2DQZQyxhMVHzZ8aPq4NJp4KDHIeDA0FPn6MWG0eCNn6OhQE5BG/O1vif3PLRYVufab3yghuTtkXT/RidGE6N4Kr53qy8lsICgonQ1TL4cZ10LBZLAVKZcOjwN6dsDux6B+GQxFT4NY31MftEhZYCsISxdQZA8OwR50Dx64aVPCvh8CiiILFTUaTe5x4tQTWbF7BR6Dc/PG1o0x20dK+2wTNk6cemLc45g6VZ1zHFECsevr1byO0XVKtpg+PT5ByVtvweWXp388Go1Gk4tIKblt+W08tv4xQ+FGkb2Iu0+5m3veuSds+4B7gJuW3YTL6+KGBTeYPrZx45QIL17X8tpaJXyP5bqU09hK1H1QvAw2gX1O+saj0aQZvcquSZqazpqwSaC93Xs5ZOwhWRyVZrTQ2QnHHQeNjeB0Rq7ncKgbxhNPhLVrjevs3r+bQnuhP42PRNLU24SUMkhgNFqQEq65xjiaMBpGEwbNfc0U2ApwuBxIJOOLxjOucBxDbqU+FQgaexsTii7RaDTpJtLqfZLHs2cqYTCRKFYLXBs+m7ejYwd51jwG3COqsmJ7Mfm28GTPU8umUmgvpN81Eq61tX1rQsNOiIEmaH9fPQaawe0Aa75KNTN+CYw/EUoOiR0alyGkVEMJFWpkc3her5d2R3tY+fKa5by6+1XDNkYRi1q8ockWZWXhZQMDZoo3QlVXYuTHrMkoy5dDXl74PcTHPgaLF6ttiVBUpBzs7r4buoP14ExIl77Z0QCvnKTcNkLP+5POhEX3QdE0QIAt5EtsL4WCSTD2aFj4R2h9Fz66HXqMo823dwSXF9gK+N++/4XVy7fm+1OneKQnruj1UYcAQi9biqqynpZOo9EkxtGVR1OcV0zPUE/Ytl37d8Vsv6vLuE5RXhFHVx4d9ziqqmKnFmloCBcGZpvZs+MTb7z0Epx7bm4JTzQajSYTSCm5+YWbeXLjkxGFG388/4985pjPsKNzB09teiporgyUgOOWF27B5XFx07E3mTq+igp1zxOveKOuTt07jWrxRsF4GGqNv37fLijV4g3N6EWLNzRJs6VtC06PE7vFjkd6sFls1HbWavGGJiZSwvXXxxZuDDMwANujzB3WdNZg8UU+FtgKGHAPIISgtb+VSSXpDJdLD08+CWvWmHOD39TbhN2XasHlcVFRVIHNYiPfls+gexC31529fNYajcYYYcNQwGEUlRsPCQk3AIxtIXZ27MTlCb4znFg80bBudVl1mBPXvu59CY4jBj07YfPPoPEFcPWAJR/cvYT97XY/phZdhRUmngZHfgfGH2/uWBIkksOGx5O9deAtbcZh7EOeoYg5wY0YdnbSaDLNmDHhZQ6HikoyhxTVVnEJ6YzFc5pgnnwS+vrCy3/+8+QXmGw2JRZ//vng8oqK5PqLiscJb14Qfs6yFcMJT8Dks1VkWSzspep50ulw3lrY+gvDaq/vfj3offdgNxf87YKweqET08trlscew2ijEPAQnEC4dA54ncBons0efQghxgH/AGYAdcCVUsr9BvXOA+4FrMAjUsqlsdoLIe4CbkL9t78spXzZV/5fYDJqLvQd4DYptXJnNLKgcoFfbBZKY29j1EAeKWXEORCXx8WCSQviHkdVVWzXvIYG5fKUS1itsHAhvPNO9Hpvvpl7Y9doNJp045VePvvcZ/nnln8aCjcKbYVcOvdSPnPMZwB44MIHWFm/kh0dO8IcoQbcA3zppS/h8rq4ZeEtpo1xxozY4sFAdu82OaVoNiiZBd0R7BeN6N4Ck89N33g0mjSjL8E0SbO5TdkMCiGwYMHpcVK7vzbp/k7986kc9/+OM2t4mhzmz3+Gt9+OT7gxTLT0ITs7d/qjf8sLygEVOVbTWZPCKLODxwN33mlebtHG3kakb1J4yDNERaGagS7LV+GpA+4BGnsbzdmZRqMxh0jpx5IVb5jElvYtONzBN67VZdWGdavLqvGGRKm7PC46BzpTH0jHanjjAnhpPtT9VdnFe4fA3YOh6MXdp6wV3b3Q+CKsOAteOg4almctR4kQxuu+2RRvfNDwgWl9tfYlEA2h0ZjE2LHhZcNp+Mwh5NZZehP7wcYlpBvNiYgzg8ejFpNCOe44mJNCYJXdrhbhQjH6XqXMhruhtyb4vG4fA+d+qCYY4xFuBGKxKXeOw79muDnQBQvAi5fuoe6whww5h/YOmfoDyg1KUcv5geRPIGl3M00q3AmskFLOAVb43gchhLAC9wHnA0cA1wghjojW3rf9amAecB5wv68fUAKPBcCRwATgijR9Nk2amT5meti9RiBtjsjppJr7msNSRwUS6f7GiKoqlaItGnv3QkFB3F1mjAsvjO1UVVsLe/ZkZjwajUaTC3i8Hq5/5vqIwg2BoLqsmocvfthflm/L58VrXwxLQzjMgHuAr738Nf7wwR9MG+eMGYkFfe7da6IjZbYoO4KErtl7a5Qrr0YzStHiDU3S1HXVAeqkVmBXbgepWKvu2r+LvT17TRqdJldpboYvf9k8cQKofKVOj5NCWyGVJZUAuL3uUSneeP556OoKL7dY4KqrYP16tRBRXw933WUcZRpIU18TTo9SyQw7bgCU55cDSk28u2u3iZ9Ao9GkjLAZ2PMDrl6yubiwvnl9WFkkt62qsqqwlBoF9gJ2duxMfgCeIfjg8/DaadD0X/AMJiFokUrIsX8NvHel6itLGK35ut3ZE29saNlgWl8rG1aa1pdGEy9GDhuNZupThcFCT5SFI0162L7dOMrsjjtSXxwzmgA13Vp4qAN2/DEkX7OAU/6t0nuFpkhJhAiij0jR6bEYvoc4oCjBQLxRAT6nQk1GuQR4zPf6MeATBnUWAzVSyl1SSifwlK9dtPaXAE9JKYeklLuBGl8/SCmHc2zYgDwi5yrU5DhCCOaMM1bsFdgKqO2MHFhWu7+WfGt42keAwyoOSyj17rhx4I1xKdDTA+3hmQmzzhlnQL7xnyGI3/zG2O1KozmYEUKcJ4TYLoSoEUIYiQ+FEOL3vu0bhBDHxmorhBgnhHhVCLHT9zzWV36OEOIjIcRG3/OZmfmUBx8er4er/301z21/zlC4ASpdyvLrllNoD75mnzl2Jn+77G8URriWd7gd3LniTn7z/m9MGevUqYmlWx8cPACO5aWzwJrAvVJfrc9dT6MZnWjxhiYpPF6PX8kukf60DBtbNybdZ7ujna6BLmSWomA1yeF2q+i3v/8d/v1vZcMVjXvuiT8fW7wMW73brXZmjZ2FQOBwOdjRscPcHWWAn/0s/GIqPx9eeAEeeQTmz1d20FVV8N3vwubNSm0bifqeev8Camleqb+8omjEA3pYiKXRaHIEa6Fx7vWBJogw0ZgJQgVxVmFl9rjZhnXL8sv86ayG8UovOzuTFG/01sLyBVD3N9+ClwnXCu5+aDfPbSJRjCyIe3tV9Hc22N6RvAA3lLVNa03rS6OJl7Fjw8VPsa5LE8JIvKHX/TLOunXh/2eLBT7+8fRYAZtuF7/114Q5rMz6PIxfAlbzQ7Od7uQnLCUSb6xVyXQwKY1pL0sBS8gXKL8iq9dXBzGTpJRNAL5no1x8VUBg3r16X1m09tHaIIR4GWgFeoF/GQ1MCHGzEGK1EGJ1W1tkBwdNdllUtciw3CM9UV2BaztrI4raFlctTmgMQsSXnu399xPqNiMcc0x8brhPPaVTp2g0gcRwhRrmfGCO73Ez8EAcbSM5UrUDF0spjwJuBP6apo92UOP2urn86ctZvnN5ROFGoa2Qxy99POI82MWHXcytC2+N6MDhcDm4+427+fm7P095vHY7lJcn1mZ9eDzW6KJ4RmKC6/b3ExN7aDQ5hr780iRFfU89eVblrzcmf4zfYjXZtCntjnaGPEO4pZv6nnrTxqlJHx0dcPvtKg/0JZfAF74An/0sHHEEHH00PP20cZtHHzW+QTzvPHjvPSXscDrhlVfg5JPjG8uurl3+17PHzabAVoBEmhpFnAn27YMNIUMWAv77XzjttPAc3kVFam5z1arIc5y79o/8bcYUjNh0TCwemRvTaVM0mhwjf5yxo4Rzv3LlyAJe6Q07VtgsNhp7G3l689OGj9Ab1j5nH6sbVye+88aX4aWjoW8neKLk0EoGmT0VvlHkuNudWEoxMzHTrWpr+1bT+tJo4qW0NFz8VFtromjYSLzhNVmRrInJhx+GC52XLDGnb4+BbtL0Bau6J5Rz1DDCBgvuSTxVSpxs69iWUvv63izcmzc3q7RmsR5GxGrz78egtDi4TcHkCOIsTaoIIV4TQmwyeFwSu7XqwqAslmouahsp5bnAZCAfMIxellI+JKVcKKVcOGHChDiHqsk0S6qWUGQLXyBzOB1Rr2t3dOwwXJgrshclLN6A+PRmK1aY6z5rBna7mruLRV8f/Oc/xudIjeYgJZor1DCXAI9LxUqgXAgxOUZbQ0cpKeVaKeXwZMxmoEAIoVWnJuLyuPjEU5/gldpXIjtu2Iq46ZibuOzwy6L29fNzfs4RE47AFiEdssPl4Edv/4h73r4n5XEbpXyMxn/+Ez0tfc5TPMM40C0Srh7o2xW7nkaTo5gyFZFhq6gZQogBIcQ63+PBgDbH+Sykanz704lL00Tt/lq/28bE4okMuVWSx8bexqScMza3bva/3tS6yZxBatLG++/D3Lnw0EPKArKnR0UL9/QoG6716+Ezn4GrrwZHwDXPAw+ER8oJAb/6FfzrX3DiiWoxy26Hs85SooWvfjX6WFweFx2ODkBZ+84dPxe7VX03R5vzxgsvhE8Q33YbLFwY2bLZZoOyMvhrBN31vu6RoKNxhSMhIcPpZQBa+1uTHrNGo0kDwgK2MoMNUt18ZIEP6j/AE3KTNOQZ4s/r/sznln3O8NE91B3Wz1Obnkpsxy1vwjuXgbvvgEtPUFxsXJ4tK8uW/hbT+hpt51/NgUFpabgoqqEhMTvZqBhNwOkcuhnnf/8LX7e/7DJzcjgbmUyYOqMw1AGDIcfaiaeCJX3z74H32clwwN2bewbCJ30LJ2dnLAcBUsqzpZRHGjyeA1p8C1n4no1uSuuBqQHvq4HhBaxI7aO1GR7XILCM8MU2zShi/qT52Kzh52YvXja2RHYF3tS6yR+AFojNYmP+pPkJj2P69Nh1Vq7MTfHDRRfF5/r3+99nf8EvWwJ3jcaAqA5PMeok4ygVyOXAWinlkNHAtHNU4jg9Ti7++8W8vvt1BtzGBzqrsHLo+EP5zbmxU57YLDaev+b5IPfrUBwuB0vfXcr33vhe0uMGOPzwxOqvWGGcJnLUUDJDpVNOhIbnIckUkhpNtklZvJEFqyiAWinl0b7HLQHlD/j6H97Xeal+Po0xu/bvwuVRkWYzxszwL+gIhD+dSiIETgodcBNEBxj/+Y8SVrS3R49kdDjgueeUFeMwDz4YfsP3y18q147QRSyLRZX96Efwf/8XeT97uvdQYFMWwy6Pi7nj5/q3ZSVSLAWeeCJY7DJlCixdGu64EUpeHpxwAlxxRfi2xr6ReaoJRSNRQ1NKpyB8QUldgzpdkUaTcxSMNy4fys4N+Dt73zEsd7gc9Dp7DR9eA7FF50Bn/Dvt3gpvXexLkxIFYYPqS2HR/XDRNrhqEK5xw9VDcMleOPEJOOTTaYtqTpZIFpddXZkcxQiRIkySYW/3XtP60mjiJZJ4w7TFEvuY8DL3aE8cPLqQErZsCS+/7DJzUk4ZuWyYeoncsSrcunfiqWAQOW4WqYrptrebl1IrJzCK1rOXZ3wYGkCJJ270vb4ReM6gzipgjhBiphAiD7ja1y5a+2XA1UKIfCHETNTc4IdCiJIAsYcNuABIzZpGk1WOnHhkxOvXaOkAd3QaHxcdLgfzJs5LeBxz58YW+m3YoNLh5hqnnx6f+PHDD6Exy4ato3rBUXOgEY8rVKQ6yThKqQ6FmAf8HPhCpDraOSoxhtxDXPC3C3h7z9sRhRsAJXklvHDNC/5g0VhUllTyzFXPUGiLfIB1uBz8+v1fc+drdyY9J3/CCVCQQNbFzZtNvrfJNBY7FE9LrE3TKyplskYzCjHDe9tv9wQghBi2ewqcVvFbRQErhRDDVlEzorS9BDjd1/4x4E3gW5EG4euvTEr5vu/94yh7qZdM+IyaELa3b8fhizSbNW4Wa5vX0upopcBWQG1nbVBKhnj4sPFD/+uV9StNHavGPNavh+uvj19xPzgIe33rN9u2wf79wdtPOw1uvTWyqwQoAcdPf6rUoUbUdtb6rcjK8suYNmYaTo+S5Lu9bjoHOoMcJ3KVvj746KPgsu98x9hW34iSEiWECWXYlQSC3TYqCisosBUw4B7AZrHROdBJRVFFMkPXaDTpoKASeneGlzsaoOywjA9nbdNaU/pxeV14vV4ssXzonV2w4qzoN1nWAph9M8z7rspVbytRriXDCCsUT4Xi66Dq47DwD7Djftj6SxhqN+XzpMK4cSqlQygdHTBnTmbH4vV6DcU2ydIzlB2HGM3BzYQJ4YsnDQ1gNSsbQr6BqC5LbkgHKw0N4e4Y+fkwdapx/UQxEoCYGint3B/uIlV2eGK5mxNkd9fulNoHpmA8IJCe8P9BBFtrTdpZCjwthLgJ2AtcASCEmAI8IqW8QErpFkLcDrwMWIFHpZSbo7WXUm4WQjyNmld0A7dJKT1CiGJgmc9q3gq8DvidfDWjj5K8EsYXjqe5vzls276efQYtFJFSNU8snhiW9jEeTjppxJU2Eh4PbN0aX5qSTLJoUfwOZbffDs88Ezu4KB0MDalAsuuuy/y+NRoDYjo8RamTF6VtixBispSyKdSRSghRDfwHuEFKmVzOek0QXYNdHPqHQ2l3tBu6MQ0jEJQXlHPuE+cmvI/SvFIG3YMR+3e4HPzivV/w1p63eO8z78WeJwvhmGPUvVC8x3Ep4a234OKLE9pNblGxGPoS+Am0v6fmDkcrXwSuO4iSS0yapFJoagBzxBtGdk+hWWcTsYoabhtkFSWECFQDzBRCrAV6gO9KKd/x9VUf0leCmZ808bKxVVkQ2iw2ppdPZ2LJRFodrXikh9r9tZww9YSE+lvTuMb/en3LelPHqjGHzk742MeCnSHiYfgC4t//Dp78tNng73+PLtwYpqAAnnzSeFtNZw1DPsusicUTmVg80e8KMywmGleV++KNN99UF1xDPvevwkK48cbEojPGhXxMl8dFv2tk4XNK6RT/6/FF4/2ilzxrHo29jVq8odHkEkURVqI6VsLE08CS2dzsm9rMc8Xa2r41dlTbujvVIlekm+iyw+H0FyF/AtjjmEG0+ywrD/2SEny8eyU0v5rQuM1mYgSdazbcTbe0GYSyp4DLG8WaS6NJE1VV4QvtDQ2JRSNFxVC8EZ4eSpM+9u5VjnOBQvJ589T9yRgDY5REMRL6GKVSSRphNCGbwA6eqQxPuxKGBa4d+SEEplBMhgPOSUl6CLu2EJm9pgrD3Q8tb0Hrm+r/K1HHm0mnwqQzR65hDjCklB3AWQbljShXjOH3y4Hl8bb3bfsJ8JOQshZgUWqj1uQaR006iuZd4ZP8DpeDfmc/xXnBFq+9Q70Muo1XuRZMWpDUGJYsGZnHicarr6pzlhlOUWaRnw/nn69cc2Px6quwdq1Kd2yaMDZOPB74xje0eEOTM/hdoYAGlCvUtSF1lgG3+wKVlwDdvvWttihthx2llhLgKCWEKAdeBO6SUr6Xzg92sNDh6GDmvTPpdfbGrCuR7Onek7axSCQr61dy9P87mnVfWJeQgOPooxNfp1m2DM44IztCPFOYcBLUP6tSIcaDZxC6N8G449I6rLRxsE03tJiXzvlAIOW0KWTeKqoJmCalPAb4KvCkEKIskb50/q/UqemsAdTieFVpFdWl1QA4nA52dhhECkdBSknt/hHF3N7uvXi8OZgM8iDn61+H7hROGE88EXxDe+218V8oWCwwY4bxti1tW/w339Vl1VgtVsryywD13Rr+ruY6q1dDf0CA+ZVXJj5ZHJp6pqW/hQKfujTPmheUNqWiqAKLbwLZIiw09TUlNW6NRpMmSmZieGnTsSorNv1mLt68veft6BX2b4Ddj4M3QvjAtKvgvFVQNC0+4UYgtkLIK4dTn4X59yTW1mQiiTeyITL/oOED0/ts7TNKXa/RpI+qqvCoo76+6Gn+EiJvrErTFIhzv3FdTVpobg63+j3mGPMWkYz66TPzlJtvYA/TuS7+3M0xhRsQKgaJFn0eDweceMNoiihWvoNAnqmEJ0WMR5xfyNZ34ZUT4V/j4L1rYOuv1PVP3eOw/bfwvxvg3+PhpYXQlF3BqUaTq5w49USsBgKsQluhoXNQ7f5aQ3cNm7BxQnViQWjDTJ6sUrfF4qmn4hN5ZJo77oh/bu7mmzP/Gfr74Wc/gyY9ZaXJEaSUbmDYFWor8LTP9ekWIcQtvmrLgV1ADfAwKn4+Yltfm6XAOUKIncA5vvf46s8G7hZCrPM9ErM81/hp7Wtl+u+mxyXcyCQbWzdy1ANH4U1gMaCsLDyQMxYrVhinihw1jD0mcdfC+ufiv99KhoJJ6etbc1Bjxk81FauoaG1bAvJR+q2ipJRDPoU9UsqPgFrgUF9f1THGga+dzv+VAlJKGnobALAKK1NKp3DI2EMA8OL1u3LEy3Bfw+RZ84LEHJrss2WL8Y2mEHDppUqB39QEu3ap1B2HHBJcr7s73Br+rrviu8EdJlSYMEzg9234ezipRJ00+1397OxMTEyULd59Nzha9PbbE/v7QPjFV2NvIzarz13DkhfkrFFRWOG3bXN73TT2ZjmBqUajCaZwClgMrHc612TF3rvPad7q1UdNH0XeKCWs/KxSxxsx9XI4/lGwFafmPmIrgsPugAU/Tb6PFJkyxbi8thaczsyOZUPLBtP7XNmg0+BpMktxsXE0q1F6oqTIGwOWvOCyoQ7jupq00NISLsZZssS8yDGja+/OTnP6BqBiUXiUWNvb4E3fQb/dkVqasOa+A8y2VlgJE8cmEjiShIAmjP698NYl8Ma50P6++v+7ewgWlkhV5nXC/o/g7U/AirOhd3QEJmg0meKYymPC3DUAhBCG84q1nbWGGq6ivCKOmXxM0uNYvDh2nTVrUguIShennRb/3NO2bfC73wUHHqWb5mZYOryEXVmpJiJTfcSLGfuqrIy9H82oQ0q5XEp5qJRyls/tCSnlg1LKB32vpZTyNt/2o6SUq6O19ZV3SCnPklLO8T13+sp/LKUsllIeHfDQkRJJ0NjTyMx7Zwa5VOcSW9q3MPe+ubi97rjbJJqOa/duk8XpmaZ8PrgTtBtpfAnS6Q57WTNcK+N/aDRxYoZ4w28VJYTIQ9k9LQupswy4QSiOx2cVFaPtsFUUBFtFTRBCyaqFEIcAc4Bdvv56hRDHCyEEcMNwmwOJ1v5W7PfYaerNnuS4c6DTnxfdIz1MKZ3CjPIZ2H2qtx0dOxLqb1PrJvKsaiJUILBarGxqNc+eXZM63/xmuHBj3Dil1nzsMTj7bHU/MnMmfPnLsGEDfPrTI3XXrQtOj7JwIVRXkxCRVKHD0RRWYfWLN4adYLzSm5YFqXSwIWCYQsCRR6beZ+BxwmqxUlEYIN4oqvBfDA66B7N6TNFoNAYUTwdrXni5Yy+xTcrMZdA96D/vm0HUc3zDC9C7HcPPWLEITnhcCS/MwF4Ch33ZnL6SYMIE49RY27cHpwTIBNs7tpve59qmtab3qdHEosIgA9xas76K9jHh6RUcDSbn1dBEo6kp3F3lsMPM67+iIlwA1J6a9iEYeykUTQ/ZwUoYMnMnwaQ6Od3j7DFpJDmCsBEm3pAZdP1seRNenAeNy8GTwMSzx6HSqixfAPXPp2t0Gs2oY/6k+YaLXIPuQSXUCKGmswaHwaKPy+Ni/qT5SY/j7LPjS3n7yCO5574hBHzpS/GnmfvRj9T52B3/2mLS9PfDNdcE7Gs02qmPxjFrNAcgLX0tzPrDLMNzQC6xs3Mnc/84N+45uDPPTCzlOqhzUabnnEzDXqLmSxOhc3WcAmyNJrdIOXRTSukWQgzbPVmBR4etonzbH0RZRV2AsopyAJ+J1tbX9VLgaSHETcBe4Apf+anAj4QQbsAD3DKsRARuBf4CFAIv+R4HFO/ufRe31827e9/linlXxG6QBmr311JgK8DpcTLoHmRK6RSmlE4h35aPy+lK2Jp1Y8tGHC4HNosNi7DQ7+xnQ8sGLjv8sjR9Ak0iNDfDa68Fz0sXF8PKlTBtWvgFQl6eevzxj6reffepCIPAidarroLCwtTH5vF6aOlXJ99CeyFVpVUAzBw7E3arOtvat6W+ozTT1aUew8yaZc6N8Ou7X6dnSE24dg91c9W/rsLmi9iXSBwudcHqkR6W7VjGXafclfpONRqNOYw9BjwRInG7NsH44+Pvq2BSSjcq7+97P+m2RhhNpPrZ8QfjtDAWO5z8b/OEG8PYItg6ZYDhRcLQCdzt2xMLCDODdKQY29q+1fQ+NZpYTJkC9fXBZatWwRVXmHDtaR8DIkRN3F8H3gGwZO9YcjCxZ0942pRJJrrUjh2r7mMC3T1Mz7I65xbY8L2AhXsJa74KJ/4VbDEsRJI4n7s8qUWZDblzbJUxVYQ1/CTrypBApX6ZSo+SiGgjEOlRbd+7Cq7K7YUHjSZTzCifYbjA5fQ42dy2Oax8c9vmiBHNU8umGpbHwwknqLmxWMKMJ56Ab3wj6d2kjc9+Fn74w/jqDg3B6aerIK1x49Jnv+9wqHGtWpWe/jUazcFD12AXZz1+Fk53bLc7i7Awo3xGSueESGxu3UzHQIffCTsSe7r2cN0z1/HEpU9gjeE4e9ZZ8OMfJyYMvO8++MpX4q+fc0y5AHbeB4kEmW1ZCsf+RonpNZpRgim+21LK5SiBRmDZgwGvJXBbvG195R3AWQbl/wb+HaGv1YAJ8eq5y2u7XgNgxe4V2RNvdNYifbNmVmGlNL+UqrIqf55Jh8tBn7OPkrz4/Gs/aPgAl9flzzvp9Dj5oN783Oua5HjyyfCbsX/8QzlnRFN2FhfDL34BGzfC228HX0Sccoo5uakbehvIs+bh9rqxCitVZUq8ccjYQ7AJG27pTjnPcybYuVMtKAxPFB99dHAKlWQJTU0QLZ9foo45Go0mzRRNUc4bXoP0IfXPQvkCsMW5EnlZBMvzJ+NTCLy377349hMnXUNdxhuGOqD1beNth30F8saaOo5sM26c8bmwtjbYrSoTDAshzWRnx+hIW6Y5sJg+HT78MLhs82Z1HWqKeCMUx570WrBqgthncFk/frx5/Y8dG35cbm5WInbTFqfm3AqbfqTCUIapfxb2/BOmXxldVGh0Po9yLvd6vTEnh2PhyaQrRSaw5oc76AxmwIFw77/h/U+Fp81JBjP60GgOEIQQzB47m01t4c5+W9q2hJVtbTMWFx9acSgiBfX0McfEF8VcUwN798LcuUnvKi1MmqQEGS+/HF/9hgZV//33E0/3Gw/9/UpM8vTT5vet0WgOLjoHOjn50ZOp3V+LN0Zqu3xrPmcfcjbPX/N8SueESPQ5+5h3/zz2de+Leo3ulm6WbV/G1f++mqcufyqqgCOZNYTGRnjjDTjvvPQJ8NLKlPNh92OJCbDrnoTjfpe2IaWNMUAOplxLG2ZGZhwAjMaf50HNK7WvAPBq7atZG8POzp1++9XhNAxTSqf4J3YKbYX+VBbxsK55nf/1sGJ+Y+tGk0arSZUHHgi+Cb30UpUTM54J8KIiJf74KFhDwLx55oytprPGn67HIz1+542q0ioK7Mrz0eFy0DsUWbSQCzQ3BweAHXecEr+kSn1PfexKPvqcoznhnUZzgFJ+lHH5vmfIZOqUwPO0Gbi9brxGaQb2PBW+oAJKtHHU95Q94gHE+PHhEeQATqfJNv1xMOzEZCZ7uveY3qdGE4vZs8OD6jdtit8KPCp5Y8Kje/r3GB+3NGnByAWjrMy8/seNC//+dHYGO3GkjK0IjvoBWEMu9lfdAm3vgYk5uPf27DWln67BLlP6yQnyxoX/ZgeaEovcS5TurfD+DfGJLoQl3OFHo9FEZXHVYsPyuq66sLJI16dLqpakNIb8fHUNEg//7/8pV4lc4ytfSUyIsXkzXHyx+Z+lv1+lZ/7lL83tV6PRHHx0ODo4/pHjqd1fizOSs20A44vG8+TlT6ZFuAFQklfCf6/7L4X22IsqDpeD5TuXc/nTl0d0jAIlPD/ppMTH8otfqOPtqGTCKYmLmT0O2PVn8IwyV8H7UROH6XokQzrH0xwh+PAgRd8VjiJ6hnrY260mYPb17KN7MDuyq02tm/wii0klSg01uWQyg24VHSyEiG6JHoDH6/F/pkHXoN/Wtbmv2d+fJnvs3KkU9cMIAb/5DZQksH5WVgatrSPvp041T9VZ21nr/84Mugf9zhuBTjBF9qKExETZoKUlOE3KSSeBzQRfpM6BztiVfIRZKldWqn94qo/KytQ/iEZzsDLhVAwv1Xp3wlDmVvc3t4ZbDqfKupZ14YU1jxhbiU+7KvmbihzmkEOCU4oFUmN+FpOIeL3euPOpJsJw2q4gzDq36HORJgJTp4YLNdrazFl8d4kxKm1BIP17wWpCLkBNXDhD5lxLSsw9PYwdG95fc3NiNsRxcdgdMOEksATYGHqd8Ob5vvRhDogySRsvm1rCI9GT6qfVnH5ygvyK8LKh9vRN5Hqc8PYl0SeYJ50Bx/8FLmuFq13qcXkHnPikiizUaDRRWVy1mCKD1IodAx1BC14uj8twjqTIXsSiqkUpj+P00+Or9/jj2b21iSS2OOec6O66Rrz1FlxzDfT2mnOt1d8Pf/sb3H576n1pNJqDm7b+NhY/spi6rrq4hBtF9iJeuu4lyvJNVIYbcPiEw3nooof8DvTRcLgcvLrrVS556pKoqRA/8YnEXSbfegs6OhJrkzPYS6D0sMTbbb83vYJtjcZktHhjFPH+vvf9yrxCeyH/2/e/rIxje8d2/+upY1T+r9L8Uv9i+aB7MO7F8l37d5FnzQOgrKCM8UXK97bIXsT29u3RmmoywDvvBAstPv5xqDCY74qGxRIsTDj2WPOi17a1b8PhVneeNovNn6qnqrRqxOJXKoeOXKalJXgB70iTkj8NuONXoUpkcCR8i0kW+mb1k2GEEOcJIbYLIWqEEHcabBdCiN/7tm8QQhwbq60QYpwQ4lUhxE7f81hf+TlCiI+EEBt9z2dm5lNqcp6KxWCLoJare1ItCGSA+t74XXzi5Z097wQXSAk9xjbGHHr7Aee6Acp5I5JQb80aZdOfCYwspc3AZZRKIlvnhFF6LtIkTlUV2O3h5dtNuK1weCaAN2SB1zNgLDozokBbgKZKqCVwXp45qQaHGTs2+L4FlJjO9EU2IeCUf6rvhAg4EUgvrL8LXloAjcvBMwjOCAEbXndMq+DA+/ZUiJRmYFSSPz580naoI33pjzb9GBwNGDqmlcyCs16HU5fBzE9BwYQR5438cTDjGjjpH/CxlTDGJOtKjeYAZEHlAmzW8IvqfGs++7pH8m3t6d5DgS3cistmsbFg0oKUx3HWWfE5V3R2hjvcZpJI9xgWC9x9d+IusMuWKXfdtWuhL0lD16Eh2L8frrgCvvCFA1K3r9FoMkhLXwuLH1nM3u69xvMSIRTZi/jj+X/kqEkR3G9N5rr513HVvKsojCMVssPl4I3db3Dx3y+OKEI588xw98B4+PnPkz9uZ53qT4AwuPGPRm8NdK5Oy3A0mnSgxRujiNd3v+5PbdDn7OONujeyMo5hpwyAWWNn+V8Pp1BxepxsbosvSndT6yZ/3q6q0iqmjZkWtE2TXV57LdhC6447Es9n2dISHAG5cKE5KUEANrRs8L8e/v6BSuMz7NzicDtyXryxd+/IxHN+vnn2z9Fs1Yyo664zZ8ejHCGEFbgPOB84ArhGCHFESLXzgTm+x83AA3G0vRNYIaWcA6zwvQdoBy6WUh4F3Aj8NU0fTTPaGHcsyAg3mnufBpkZ8Ua/03wvxTVNa0J2EiH1QGEVlBxi+v5zhRkzjMvfey9zN9HNfc1YDCza86x5TBszLa6HwHimoG9otM4EaEYrVVXG5a+8krp4uKAoD2wGF2kDcVp7XtYM18rgRw7z+q7XWfjQwoSvJxNhwDWATGCFJlSoYbOZ77wR6u5RW2tS2p1Q7GVw7odQOhusITvorVFuDf+qgJWfgT1PQ8cq6NkO3Zuh/X2ofQTe+njUXdTuj88NMxa5fi+VEHkVyuUkkKF2iJEDPSmc+2Hbr40FXuNPgPPXKNtne0nkVCn2Uhi3UAk4Ks8xf4wazQHAkROPNEwBaLPYgo6DtZ212CzhIg+Hy8G8iakLpM47L/5rjaVLMyfUDsThgD/8IfL2W2+F8vLE+923D44/Hu65R+0jXmGK263ued58Ew49FF56KfF9azQaTSBNvU0sengR9T31cd3HFNoKuWzuZXzmmM9kYHQjPHDhA8won+EPho7GgHuAt/e8zflPnM+QO9wt7rDDkjt2//WvyYk+coJpV4AlQfEGwJal4Oo1fzwaTRrQ4o1RxH9r/uu3tfZKLy/VZP6qdsA14BeQ5FvzmT5mun9bZemIJXW8UZwbWjb4F4XmjJvDoRWHAkqcYmiprsko74QERi9cmHgfzc3BkcUnnGBOShAInkisLBn5/gU6wbi97iCRRy4SmFamoCA84i8Zkkk7tLFlY+o7PjBYDNRIKXdJKZ3AU8AlIXUuAR6XipVAuRBicoy2lwCP+V4/BnwCQEq5VkrZ6CvfDBQIIRI0LNUckBRNNRY0AOxfq+z600y/sx9pFC2aImECza6NYDCZyrhjwiPdDyDmRZgnfustFVGeCToGOii2h6sqLz70YvbcsSeux8yxM8Pal+aVsrcn/d9RjSaQmTON0xG9+WbqOdlbW4GiKeEbug9Mwfm3X/82HzV9xFObnkpL/x/Uf0DRT4t4bN1jsStHwOzI3OLi8D47O8119wiicBKc9xFUfRysBtbJHgfU/wfeuwpeXgwvzIUXj4RXToRVt0LrW1G7Dwy6SIU93XtM6ScnyBsbLt7oqw12QDGLbb/D0HFj4ulw5qtKwGN07ROKxaoEHqc+C1UXmztGjeYAoCSvJCiYZxiX1xWU0rl2fy1DBimSJhZPjMu+PhbFxUrAEQ8dHSolcb/5GvmouFxKOBIJu12JO5IJuJISfvELmDsXvv995XrmcIRfl3k80NMDXV3wpz/Bueeqv1t75rKCajSaA5T6nnoWPbyIxt7GuIQbFmGhuqyahy5+KAOjCybfls/y65bHff4ZcA/wfv37nPPXcxhwBSvkhIAbbjB2oIxGfz/8+teZPxclQ9g9fvlR6ro+URqXK0G8N103eBqNeWjxxihhyD3Eto5tAP7oxu3t25NaoE2F3V27/ZZOedY8ppSOTGBOLZvqf13XVRdXfx80fOBPb3HEhCOYN2EeNmFDIvmw/kPzBq5JmL6+YJfxQw9Nrp9AYQIkpwQ1QkpJY1+j//308ulB24dT8ABsbc9tq9/ACL/8fHMmiDe3xud+E8i29m2p7/jAoArYF/C+3lcWT51obSdJKZsAfM8TDfZ9ObBWShk2qySEuFkIsVoIsbqtrS2Bj6MZtQgBlWdH3r7xh2lXjL+z953YlZJgd9fu4IKuDeA2WFkdMx8MclgfKBxzjLGgsaVFLRhmgt1du8Nu/gFmlM+Iu49AAeUwFmGJ+3pQozGLceOM8/2+/37ieYAD8Xrh9deBknChEq3vqPQWZvBF1LE/XY/K8N+qEeub1/Nhg7oXu2vFXXhMntzySi+feU5Ft33tla/F7fAUerz0eIJTPKaKEMYug42N4WWmYSuCk/8BZ7wMZXMjp0uLl4D0PBVFwYuZVmHl7Jln87UTvhbxcdr007CETBNNKJqQ2phyCYsVrCEHg/46sJqsm3b1wbbfqNRKgRRWKRGGLYmVUVsRnPgklM4xZYgazYGEkdW9w+UISh+1tX2r4Rzq/InzTRvHzTfH76S6dKmx4DRd9PXBXXcp4UQ0PvEJFcWdbDT2vn3wy18qEcdRR6l9/upX8Oc/K2HIj34EF1+sUjLfcgv8LzsZwTUazQHGnq49LHp4Ec19zSOp1GNQZCvipeteotCewo1iCswon8GTlz8ZV/oUUAKO1Y2rOfvxs8Mcp669NnHxBsDPfjY6UqeEOVsJATNvSDx1CsAHNx3QQWKaA4c0hBdo0sGqxlUU2ApwepyU5JXQ6+yl0F7Ihw0fcur0UxPuT0rJpf+4lLtOvosl1UviblfbWYvwXcFbhCVIvBGYQqXd0Y7b6za0JAxkY6uK9C+2FzN73GwK7YUU2gvpdfaypT09Odg18bFvn3KBGD45nnhictFtTmewHaRZtsPbO7YH5Xp7YccLlP1s5C653zUyCZzrzhuBThsFBebYZ8abuigQs6yVDwCMpilCv/2R6sTT1ninQswDfg58zGi7lPIh4CGAhQsX5rbXusY8ZlwPzSvAbSDS2PcvOPZXylI7TXzU+JFhuc1iiytCQEpJrzN87GFlgy0gDSIjxh0LlgxZUGSBuXOhqMh4EnXFCvjUp9I/hm3t23CH/O3zrHlUl1XH3YdR3SHPkBZvaLLCoYfCqlXBZX19sG0bzE9yfaa3F55/Hm78zlxoeCF44/41SrwRmvoiGbpT7yIqgcrsKHx7xbeRSASCrsEuntn6DFfMu8K0Yfx57Z/9rhD9rn7uefselp4dJRTYhzXEjGpgwDxHv2GmTlXRwIHs3AmzZ5u7nzAmngwXboaG52Hn/4OW18GSr9w3jM6PoLZb80F6lXXw7C/A+JF7+/0D+4OqF9mL+Pxxn+fKeVdGHMZj6x5jdePqoHupjoGO1D5brmEvDU5lIr0w0ATF0yK3SZS6vxnfPJ/0ZLh4JBGshXDyv5Jvr9EcoJw09STe2P1G2ILd8JwjGAe4WIWVE6eeaNo4zj47/nkzhwO+9CV46CEoSVG3FwuPB5qa1L5iIQQ8/jgsWhR/+pNI7NoFv/tdan1oNBpNLNr621j08CLaHe1xO8cW2Yt4/NLHmTVuVuzK0fC6wNkFzk6VMm+oE1xdyulNekF61LOwKGddYVVzXHnlkDeOiyoP5YvHfJr71/6FAXfsg+6Ae4CVDSs587Ezef+m9/3rdEceqVJAJuo2OTiohHR//Wv6z0XJ0tcH3/kO/P73IRtmXAvb7wVPgvlRuzaoa/UZ10OcwhmNJhto8cYo4a26txhwDSAQzB0/l9WNqxlwDfBW3VtJiTdeqnmJ57Y/R+9QLytuXBF3u5rOGgZdShru9rqDxBvTxkwj35rPkGeIAlsBe7v3csjYyHnqh9xDNPepHNE2i42ZY2dSaCv0n3S6BrvoHeqlND99i1KayNTXB0eynXWWcSRaLNzu4JvXfJOCml7f/XrQe6fHGSTmCMQjPXQ6OhlXNM6cnZtMYESD12tOvrmdHTsTbrOve1/sSgcH9cDUgPfVQGjMZaQ6eVHatgghJkspm3wpVvy+NEKIauA/wA1SSq2i0Yww5bxwe+9hpBfWfgMWP6LstNNAvi0fm8UWZjl58aEXc/3862O290ovV/3zKrwhueSllHilF8twjncj1w1IqzAlFzjssMiCvf/+Fy65JP7ovWTZ0bEjrCzfmm/ophGJGWNmhJUNugeD0psBMGlS3IvHpjJpUuw6BwBCiPOAewEr8IiUcmnIduHbfgHgAD4tpVwTra0QYhzwD2AGUAdcKaXcL4Q4B1iKOu85gW9IKYMvzrLEokXh4g2AZ55RgqlkUhIVFPicN342Sy2eBkbT719nnPJilLK1bStv1L3hf9/n7OPOFXfyySM+6b9PS4XuwW7ltuETBwx5hvj9B7/n5uNujnrvCOHuKQMD6l7DTAHHYYfBxpBMgh98oO6F0p7OSlig+hL1cPXw11c+y949L/Ktw8/G1rd7JELMVgJjjoTxi6F8AUw8xTDnc31PfdB7i7AYphYIpKKoIiwAw6z0KzlD/gQlGg2kZ6vJ4o0nwBPiKDPpTBh7LFhT+CJZrMYOQBrNQc7RlUdTnFdMz1CwIjo0bUooxXnFHF15tGnjsNvhiivgL3+JLyjn739XKUMuvzy5VCXx4nDA+efH7/I6b54SlvzhD6kLODQajSbdjCkYw4VzLowrVcowJ0w9gUsPvzR2xaFO6K2Bvhro2aEW/nu2wWAruPvUfJ01XzlADM9vSS/gDVgQGY71E76QP0tAXQ9LPS5spUM0eCwqlZ+1AOxjVFoQeynYytRzQGDT9PLpQfdmQsCnP62cj5wRphAj8eyz8OGHcPLJmUvfGy8ej1qjuv9+A/HGmHmQX5FcftS134Cpl2rxhian0eKNUcLymuW4vC5K80pZUrWEbe3b6HX2srxmOXefdndCfUkpufO1OwF4o+4Ndu3fFXOibJj/1f8Pp28RyeFy8OLOF7H7JooCI/290sum1k1R+93esZ1Cm3LZcHldzCyfSaG9kCG3mpQqshexuW0zx1cfn9Dn05hDfX2wI8TJJyfXT2jUgRnCBIA1TWsSqv/uvnf5+GEfN2fnJhNoazY4aI798679uxJuc0Dls06NVcAcIcRMoAG4Grg2pM4y4HYhxFPAEqDbJ8poi9J2GXAjarHrRuA5ACFEOfAicJeU8r10fjDNKMRWDBNOhJY3jLfv+Ycv0vak1BYDIrC5dXPYDXChrZCPzfoYlx1+WVx9jC0cGxa1m2/Np76nnmljTFwoCeSZyvCFmYhY4Nrs5LucNSvyhOjbbydnexmLwcFgFyyjY79FWBISb1SVVfkFvIFsaQtxUWtuTmisUS8akrEDO4ARQliB+4BzUALDVUKIZVLKwH/C+cAc32MJ8ACwJEbbO4EVUsqlQog7fe+/BbQDF0spG4UQRwIvE55iLCscc4xytAmdw1m+HL72teQmpGpqYP9+oHi6mjQLFG+4elSkVWH8v5mIjCG97htxCJm++/p3wwTRrf2tPL/jeVOupb+94tthtvVOj5NbXriFVz71StS2RllfurrizgYTF/Pnw3/+E7zA9d576lidycnMdpeTz619HqfHSe+hC1h68UsJ99HSH3welMiwVCqhjCsMF7s39TUlvO+cZsw86N4UXNbxkUpVJ6zGbYYpmBTf9UWHgYJswc/MEdse4MJWjSYZFkxaYLho19jbiPRdMzb1hh/L3B43CyoXmDqWz34Wnn46fhv6z39eXbvMnZuea3+HA666CmoTDBH54Q/hiSe0eEOj0eQ+edY8/vyJP6fe0WAbtL8PrW9D86tKtCHdSkwhJbj7AQNlnmcQSD4Plg1YOh5f307fowdoVGnzhAD3oBJrl8yByefAxPD1sk99Cn7zm+TGcP31sH177ok3hoaUwNFQfCgEzLkFNv04PFVhLFzd8L/r4ZR/J5fOUKPJACZmiNWkC4/XE7RQfc4h5/gtoNY2rU1IVQgqf/2u/bsQCIQQ/OitH8Xd9uWal/2vJZJvvvpNvvLyV/jKy1/h8fWP+yftB9wD/GPTP6L2tal1ZMJkyD1EdVk1E4om+D+bx+sJqqPJLE1NwTdp45I0rbDZgtdezMrpGbYgFIPhvN25SKAbyeBguCV0MuzrSdxFo7W/deSNWVHKozDaWUrpBm5HLURtBZ6WUm4WQtwihLjFV205sAuoAR5GZamP2NbXZilwjhBiJ2qBbDgi+nZgNnC3EGKd7zEx3Z9TM4qYeYOKso3Ee1cH23+byKa28POw3WpPKKXGpJLw44Ddag92CLJFiFo3ShcTD3ELN8Dw5jtD5OfD+PHG2+rr1bnYbAKjAKWUtPW3hdeR3oTEG5UlleRbw621du/fndQYNUmxGKiRUu6SUjqBp4BLQupcAjwuFSuBcp8TVLS2lwCP+V4/BnwCQEq5Vko57Cy1GSgQQpjkr5YaRx5p7MSwalXsPO9G9PXBH//oe1M83RdJFcL+tYl3bMT9qInBWI9IxGoXQ0BV21nL8prleKQHu8VOSZ469/Q5+7jztTv9C2DJsqVtC39e92eGPENYhZXjJh9Hkb0Ij/Tw3r73eKU2unhjmoHery38EJYSs2cr8U8gH34Y7vqRbr7+ytdxe9wIBL//4PdJHU87BzqD3ru9bkNxRiAVhRV4Q77jHY4DLG3KuGPD82N3rgZXHCutlzXDtTL4YYQl5HBYvgDK5yU33gMUIcQ4IcSrQoidvuexEeqdJ4TYLoSo8YkIY7YXQtzlq79dCHGuQZ/LhBB6sukAYnr5dDxeYzF2u6Odlv4WrJbwiRaJZGrZVINWyXPCCYmlC3Y6lStGvGKPROjrg1/9Cl5KXP9HQYGKxg49J2o0Gs0Bw0AT1DwC71wJz0yBZ6vhf5+C7b9VDhseh3LWcPX45qYyPXfkUft19ahxuPuhax1s/TX877qw2ocdBkcdldyemprg1lvTcy5Klr4++PGPYUu0JaBZNycf2NP0Mux7JrITsEaTZbR4YxSwoWWD37p00D3IObPO8btT5FnzWN+8PqH+7nrtLr9NrVd6+cfmf9DQ0xBX28Dct6BEGsOP0GjLrW1bo/a1rnkdfU51RqgoqsBqsSKE8C8W9Lv6E3ZX0JiHwxG8wJOs8tJuDxZvDA1FrpsIYVbsMdjYsjF2pSxRHbAGOjBgjvNGMilQhn+PgJrcT2TBIMlFglxFSrlcSnmolHKWlPInvrIHpZQP+l5LKeVtvu1HSSlXR2vrK++QUp4lpZzje+70lf9YSlkspTw64NEaOibNQUzVxSqPZiQGW+F/1/qiAMwl0mJRIuINI3cNp8fJzs4A8UbBJGUPGUrn2uif/QDg8MMjb/vTn8yPdmsMSALV2t9qOJE95BlKWLxhlE6hsS8045QmjVQBgSf/esKdMCLVidZ2kpSyCcD3bCQuvBxYK6U06SovNY44IrJz6h//mLirqtWqbM0BJd4wiuppfhXiyFGc63zvje/h8uUMtllsfOboz1BgUytQe7v3xhRXRENKyU3LbvK7buRZ87j/gvv9ghCHy8Hnln3Ov38jpk0LFzmbfak5e3a46U9PT3rEdJFY37yepzc/jRcvQghcXhe3vnhrQn0MuAbC/pZOjzNm2pRxhePCnFd6nb0RF0VHJWVzwy2S295WUZVmESo+nXZ5uGBEM+zsNAdY4XsfRIAz1PnAEcA1QogjorX3bb8amAecB9zv62e4z8uAHFqa0JiBRViYM25OWHmBrYDa/bXUdtYaCo0PrTjUlJRgQWOxKOv6RFw0GhpUusR+E2/nHA54/334wQ+S72PRInj88cwLGDUajSZtOBqV+OHFo+C5mfDRHbDvnzDY5BNI9BiL9WNhL1Ni3UlnwuTzoOrjMPVymH6NCsiafo16X/VxtX3SmVA+H2zJOKp5laDDgLvuSi7tPcDf/gbPP2/uuShZHA746CP4xS9iVCwYD9UfH0lDkygffgG6t/rcUzSa3EKLN0YBb+952++uUV1WTaG9kKljlDLc5XXxzt534u5rdeNq1rWsA6Asv4x8az5SSpa+uzR6Q8DpdoZF4USjrrsu6vYPGj7wu2wEKt1nlM/wv17VYGA3qskIofnRkrVvnDAheAK0N8kg6lC6BrsSqr+lPTGnjkxSXT3y9/V4zJkc7hzsjF0phNCJWo3mQOD57c/zQf0H2R5GauRXwNijo9dpfAnW3mmqYnzQPWh4rB12y4qX2eNmh5UNuAeC0q1RfpSx+0bX+rSIUnKJCy4IdmAKxL9gbBIDA0oQMkxdV53hRLZXehmTPybufitLKvHI8IW9Qfcg/c4D+/+XQxitPIQqLiPViaet8U6FmAf8HPhChO03CyFWCyFWt5ltkRCBsjL1MOIvf0lMJOv1wn//C93DqUxsxcYLvE2vgsFvYDSxt3svz2x7xv9bnl4+na+e8FX/9n5XP9967VtJu288u+1ZNrZs9N//LZqyiMXVi7n2qGv9gQqdA53c+8G9EfuorAw/Xq5bF8FGN0lmzTJ2Cnwn/lvulJBS8tlln2UgQAzk9rp5Z+87vL779bj7ae5r9gtvAvsuskcPoR5bODbsniDPmkebIzO/34xQNjd8Un6oQ0VfmkbI72TaVWlJbzfKMXR2CiFhZyhf+VNSyiEp5W6UU+JiACFECfBV4MemfhJNTrCoalFYmVd6qe2spXZ/reG16uKqxWkZy6c/bewCFo133oELL1TpwFwpatf7++Hf/4aLL0490+Dll8N3v5t9B450pJTRaDQHCVLCvv/AyyfAskNgw90qhZ53CDwJzFfkjYPJ58KcL8Kxv4UzXoGLd8KV/XB5G5z9lkrDcdLf4YTHYMmfYPGDsPCP6nnJn1T5SX9X9c5+Gz7ZAVf2wsU74PSX4Jhfw+xboPIcsJcn/FEvuii11Cef+hS8+WbiAQ9mMjgImzcrV6q47vMO/wZYkhRhewbg9TOhbzd4ciIWRaPxo8Ubo4CXal7yRygdM/kYAI6tPBZQk+LLdy6Pu6/vvP4dBlwD5FvzuemYmxBCMOQZ4k9r/xTTDnV10+qo20PpHYq+Sh/ozDF3/Fz/68PHj4Sg7ujckdA+NeYROrHtTdIZrLIy+ES7erU5E6yuBCOxjfKb5gqTJgVPRK81wXlbBKzDCASTSyYzrWxa0MPIHjRVO2yNJpdYvmM5H3/q45z6l1PZ3r4928NJjSPujJ46BWDnH+G9q5TYIZbYMg5BRG1nreEij0d6YkbuBnJI+SHkGSxYbGjeMPKm/CgwSgO3f1249fgBxumnR7653r1b3bSahRDw2GMj7+u66gyFuWPyxyQUhVhZUul3hQuk0FbInu49SY1VkzD1QOCJvRoItT6JVCda2xZfahV8z35nKCFENfAf4AYppWEmdSnlQ1LKhVLKhRMmTEj4QyXL3LnG5c3NsHJl/P309cF994UUlh0WXrF7E8jR7RL0o7d+5HdXKLIXcdui25hePp0jJhzhr1PTWcNbe95KuO8B1wC3vHiL38WxxF7C3afdDcC3TvqWX7zR7+rnB2/+gJY+49RXkyaFL96sXm1udNi4ccYpDF97zTwRejSe3vy0/5ql2F5MWb5SIg07k8SbMrWpr8n/dx2mJK8k5rHdZrGFiT7yrHk5fS+VMCUzjaPrml5J/qY3GvYyKJlhfr+jn3icnZJxhorW5h7g14D2xz4AWVy1OOzepd/VT01nDTs6doQJiovsRSyaEi74MIN582BxErqQt95S6d+2bk3+3OZwwFe+AjfcYJ7z7V13KRFHthw4hFCBYRqNRpMQUkLDC/DCYfD+DdCx0ifYiNMxsXg6HPJZOPFv8Il6uLQRTnoKjvklzL0DJp8DpbNVIJIlD/LGQF55wGOMug60l6pno+0Wu5rrK50DU86Dw78Kx/4aTn4aLmuBS/bACX+FQz4NRbHTfNlscMcdyR+vPR647DKVctRsF9h4GBqCXbvgrLMS2H/FQvW/ShZXD7x2Cgw0QhQXSI0m02jxRo4jpeR/+/4HqEmTE6pPAOCEqSf4F0JW1q+Ma8F1S9sW3tnzDhKJEIIvL/my31ZQIvn1+7+O2v79fe8nNHa3dOONMPnR5+zzR/NahTVoUnDu+Ln+KNBB96BhLnZN+gmNagt14oiXysrg6LUPP0w9f1ptp+H6QFQcrtydn5k0KXiS+N13zbvJBsi35bP2C2vZ85U9QY+9X9kbNLlht9jpHuqO0pNGM3pY1bCKK/51BQKB0+Pk1L+cOroXHqouji3eAHVj+spJ0PK6uiENVI57nMrWv+VNWHFGzK52du40XOQZVzguoYX96rJqQ3eHmv0B6a+KpxtHrTvqod84dcuBwjHHRD/H/va35i0YvvdesLvT7q7dDLjC74gnFCU2O1qaZ+zLaREW6rrqEupLkzSrgDlCiJlCiDyUZfyykDrLgBuE4nig27fgFa3tMuBG3+sbgecAhBDlwIvAXVLK99L4uZJiUZS1mJ/+NP5r0c5OeD3U7GDCyRialTQuT8/CbwZo6m3ibxv/5hdHe7werj7yagBuW3QbxfZiQC2C3flaWGaDmCx9d2lQer7xReM5a+ZZAMypmMPx1cf7t7m8Lr7y8lcM+6msDI8gXrcuPM1JqlQbmEu99FLqUb+xjuUOl4PbX7rdL3KxWWx879Tv+f/+rf2tPLDqgbj21dTbFDZHMCwEiUVpfvAxXSBo6hvF11ChWOwqXVsozS+Hpzsxg9I5B0RapWQQQrwmhNhk8LgkdmvVhUFZrMkvwzZCiKOB2VLK/8TcaRZcozSps2DSgjDRmld62dC6gU2tm/zOT8PYLDYWVC5I23h+8Yvk3CoaGtR1zFNPKSFGvC4cvb3Q2gqnnQYPP5z4fqMhhHLvO+20zDtwWK1QUaEiwTUajSZuWt6A5UfBe1dD705wx3kDWDQV5n1HOWpcuAWOuxdmXAtFVWDNV6ILI9dYM7EVqf1Y86B4Gsy8Ho77PVy0HS7aBkd8CwqnRGz+BUNPzPhxOpXrxZYtxo6E6cLpVOfAU05JYg7sqB/EN2caiaEOePUkcLYbB5ZpNFnAFPGGEOI8IcR2IUSNEMIoT6UQQvzet32DEOLYWG2FEOOEEK8KIXb6nsf6ys8RQnwkhNjoez4zoM2bvr7W+R5Gyv1Rxc7OnX5rvwJbAfMnzQdg/qT5FPrytHqll+0dsSOKv//G9xnyLeIcVnEY08unc+vCWym2FzPoHuT3H/w+qlvG+pb1CY9/a/tWw/ItbVsotKvxF9mLOGTsIf5tM8tnkm9TizyFtsJgW3VNxhg7NljAkayYoKQkeEJ1zRrjaLZEeHvP2wm3kcictW6fMiV4rn/dutTUrR6vh17nyG/Z6XEyrnCcYd3ASdx8Wz6NvaFBuhrN6KOms4Zz/noODpcDiy/vYedAJ6f95TR6hozzQuY8FivM+zZYi2PX7VoPr58Dz8+FLUthz1Ow5x+w9Rew/Egl3OiInZZsR8cOw4X9ypLKhIZeXVbt/z8E0trfOhJBLCzKxtxwIPeB68BNTW6zKQFHJJ55JnXrZFCL1T/7WXDZtvZtuGX4jWllaWL/YyEE5QXlYeVDniEt3sgQUko3cDvwMrAVeFpKuVkIcYsQ4hZfteXALpSF/MPAF6O19bVZCpwjhNgJnON7j6/+bODuXLz3Wrw4cq7fV19V1uSxhMn9/XDjjQZ24xVLjCeG6v6enoXfDPCTd34S5MJz0tSTGF80HoBPHvHJILeHja0bExL17+vexy//90u/kLrYXsx3Tv1OkAjw7lPvpiRP/U2dHifPbnuWDxs+DOtr9uzwCcSaGvOt1JcsCS9rbYUdKZpCxhrnT9/5qf9+pcBawP8t+T8+f9zn/QuO/a5+vv36t2M6ZoJy3nB6g7/kYwvHxjXO8vzyoPdur5vmvua42o4ajBx0ml5Rk/JmUzrHfIXRKEFKebaU8kiDx3NEcXYKIBlnqEhtTgCOE0LUAe8Chwoh3oww7qy4RmlS48iJRxoG7exo38GOjvADuMPlYN6EeWkbz+LFcOyxsesZ4XTC5z6n+vjLX5SIo7s7/J6gr09dr2zcCF/8Ikybphyp0oHdDi+8AFdckTkBR14eTJ2q3GnnzMnMPjWaeMjwWliFEOINIUSfEOKPmfmEoxgpYeOP4M2LoHtz/Gl4y4+CM16Gi7cr8cawo4Y9BUGAmdhLwVaormGP/B58PHJg64QJSsBRkGQmEVDrEmecodxgMyHgcDqhrQ1OOkkFUCTMtE9CQYrTEQNNKhjO2alTqGhygpTFG0IIK3AfcD5wBHCNEOKIkGrnA3N8j5uBB+JoeyewQko5B1jhew/QDlwspTwKFf3115B9XSelPNr3MLr5G1W8s+cdf/qDIfdQkHhjOJXKcL1o1HXV8cLOF/BKL8X2Ym5deCsAV8670j8ZJ5HctyrUF3iEwDQn8fLePuNAvHf3vMugS43f5XWxpmkND6x6gAdWPcCqxlV+6+1+V39SC/Wa1KmuDhZv7NyZXD9CwPjxI+9raxPP/RlKoil8hnm/PjH3mExx6KHBYo3161O7wGrtbw2Kcs+z5mG3Gs8Wjy0YmcS1CMvodibQaFDf/1P/fKpfpCEQ2C123F43e7v3cu4T54blch81zPqcsmKMF8de2PgDeO8aFW2w4W7o2xV38w0tGwxTVE0fk5gdYXVZtWE/+dZ89nbvHSmYdRNYDWYC9zyV+KKHUURtDhMtL+ngIHz966m5b3g8atJzxYrgcqOJbIBpZdMS3seE4vDFjUH3IDWdNQa1NelASrlcSnmolHKWlPInvrIHpZQP+l5LKeVtvu1HSSlXR2vrK++QUp4lpZzje+70lf9YSlkccN+VU/deJ58cXfR0883Rtw8OqgWKt41uQ8Ydi2Hgd/NrYEnxIjcLtPW38ejaR/3nxtK8Ur646Iv+7WX5ZXxs1sf87wdcAwm5bxz/yPEMBLgO9Lv6+eKLXyTvnjz/47wnzgty5hhwD3D6X04PSxFSXg5lIeYRXq+KCjOTM8+EYgOt5KOPppaiJVoarL3de/nN+78Z+VsJuG3xbZTklfDZoz+L3aKu5V0eF9987Zsx99XQ0xA0XwD4BTmxGFcULPoedA+OmnuEb38bfvADuPdeePll2LMngiHOxNNBhNwfufugeYVB5RQpqk4+D/eBjaGzUwgJO0P5yq8WQuQLIWai5iE/lFI+IKWcIqWcAZwM7JBSnm7yZ9JkkdL8UsPUjvt69lHfUx9WPqFoAsV5cQjjU+CXv0xN6LB5s7pmmTgRrrsO7rkH/vEPJe5+8EH4v/9TLh3z58MTT5jr4GqE1Qp//jN87WvpT6FSVKQ+15o1AY5Yk0bXPR4wOsesiUoW1sIGgbuBr6frMx0wuAfgnctgy8/BE6cDd9E0OHXZ/2fvvMPbqs4//jlXy/IecezsnUAGISGQhBFm2KtsKKtQWlbpYJdRKKMUyi5l/NhQNpQZwiYQZoDsvaedxPEe2uf3xytZkiXb8kocOJ/nuY+kq3uv7pXse855z/f9vnDot1B0MNjcIpLoztjTwdZy3/L668Hq4MxvTQ1Mngzvvde5ZSqbUlsL33wDEyZImdN2oSwYf2/H3DdAnH/fGylj+59xEplh56AznDf2AlZorVdprX3AS0BTC8TjgGfDAcNvgdywMr6lfY8DIlW5nwGOB9Baz9ZaR5T2C4E0pdTPthj69BXTG21THTYHRRnS6euZ0bPRnaLOX8f0ldNbPM7F713cGJDzBrx4g16e+OkJ3lzyJgNzBwKiOv/7jL83m5W8urLttuWzS2YnXf/UnKcaM4E8AQ8Pfv8gl394OZd/eDl3f3N3o0NIIBTg6TlPt+kza7w1O01wqTvTt2/8XNmHH7Y/83dsjBOl1rBkScfOramDRqYzk16ZvRKWSGkhAAur22aMOZ2SIRFhy5aOqVpLakvixBrN2dlDfBA3GAr+vCyRDb84an21HPD0AWyt34pGY1M2JvSe0Og84w16mVs6l9NfOz0uw3inwe6G3W4Ge9cGGSM053wVKbmWKsWZxQkTSCBWxcu3xSgDB5yevHSKrxwW3Na2gdMJpXCGTly6KQce2LJo75lnpG1oL14vXHJJ4vq1VWuTbj8gt+31Qntl9kq6ftHWTp5VNRhSoH//5JPvETZskEneZEGoQEAyXC+9tJmds4ZBEkEaIS+semqny9K55uNr4kQSvqCPDGcGn67+tHGZ3Hdyo+ujRvPdxu+YsWZGq8e+/9v72VSb6OrmD/kTlqY0BBr4/TuJnr+77Zb4OS++2Lk1mSdPTr7+pZfa7yBYUyMTbc1xyXuX4A/XWLaUxXEjjqNnhmSP/WXyX7BZ8sHeoJcX57/IvM3zWvy8ZGP3yPFao2nprKAOtisW0BWEQlIC7NJLYbOKnxArpYh//ANuvhmuvhpOPRVGjhTRz5lnwvTpMePZogOTB+aX/0fqXncmlksc1AxNSerspJTqrZSaBu1zhgq//wqwCJgOXKJ1sg6m4efI6J6jE9bV+mrjRIQRIslxXcmkSbD33h2fQKurk8mzW26B006DE0+Eiy4SUeHitufZdQil4O9/h2nTJFGracnlzsDthquugm+/FVfgRkpLJai4My3tnok0dGO291xYndZ6JiLiMDSH1vDJQVDyQerCjcJ94ci50PtwEUT8jPprBQUi8Ouo0K6qCk46Cc49F6qrW3evbAuBgLRvV14JBxzQCbfLPsdI2ZuO4t0GM46GWb8Hf03ysX97CaT4t2kw0DnijT7A+pjXG8LrUtmmpX2LwjWYCT8mizScCMzWWsdGyJ4K2/beoJopyL4z1a/8aNVHjc8L3AX830//x2M/PsZjPz5Gflo0I+bjlR83e4y5pXN5f8X7jRNVIUJc+8m1XDb9Mi6bflmcnXVDoIHfvv3bpMep8la1+fybC9g3Df54Ah4aAg00BBoSJnjaWsbhuJeOo9+9/XZea/xuQt++8Q3yzJntV1lOmRJvEzxzZsdKgsf+thmODP59xL/ZdPmmhOXMMWc2bue0O6n0VLb/Q7uYPfaIf/3ZZ+3/jpr+zySzso8QG8T1BD2mbIphp8Uf9HPUC0exqmJV4yRUmj2NV05+hRdPfJF0h6Q8NQQamL5yOn/+4M878nTbz9DfgT21mvUdZW1l4sS+y+ZqFH2misPmSCoi8wa9LC+PEW+k9YDC/ZIfZMnd4K9s0+fuTEyY0LJoLxQSK+Tadgj/vV54802xU45Fa83WusR+sNvupndW8/VTm6N/TnK3jtUV3WPCz/DLY79mbicRHnhAAkV1dRI4Anm+fr3YnJeVNbOjsiBrePL3Ft8NO5E4cGX5Sp6c82SceCKkQ5z22mmc8PIJjcs/v/pn3MSXN+jlxFdObPHYnoCHKz7qWILgk3OeTMiW3m+/RAHFW291bGzRlOHDk5TLATZvFjeWYDumgS0LXn01+XtfrP2CT9d82ljGKs2exrX7Xtv4/qC8Qew/YP9GR05PwMNv3/4tOtlJholztgrTOzO1e3syMV6yPsH2RGuZuBw+HA4/XIQwxboUhW5cehGN+Hq9EmyurxfhzAsvwCmnQJ9ItKlgTwgmaXhLpkOoE6PSIPeEVPWjbxTDC6qV5ecxsdCCs9MmrfWRMdu1yRkq/N5t4e1HaK3fT/LZa7TWibP8hp2effrtg03F/4+4bK44Z1IAm7Kxd7+9t8s5PfBA1wgcdjQHHCAOvccfLyL0jgpUQMouDxsmbe3f/tbxkssGQxexI+fCDM2x9iWomg/BFBXdvY+CA6eDMxesTq7B2E24+urOu4++9hqMGCHzFfX17RsPRQiFJLb1448izG9J4N4mlII97uu8hLc1L4gLx8b3xNWlvSIOHZJktIpwiWuDIUU6Q7yRTCDRdGja3Dap7Jv8Q5UaBfwTiE3H+XW4nMp+4eWsZPvuLPUrZ22cFSeY2FC9gT9N/1Pjsr462tZX+6r5bsN3SY9zzpvnxL0O6RD1/vrGxdskO+y1Ra9R74tXgYVCoQTb2lSIm5SJIeImkgreoJdQitG4tZVr+XzN5wR1kPu+vS/lzzAk0qtXfBD0u+/ab/e4xx7x+/7vfx2z21q6bWnjc7tlp0920z6yMCR/SOPA3RPwdOvs3332iR/QP/BA27+jiEVmSU1J3P9rxHUgGb2yosHZQCiwwwOzBkN70Fpz1v/OYtbGWY1tWoYjg3sPu5d+Of04cNCBnD76dNLsYm1Q76/n8Z8e5+5v7t6Rp90+bC6Y8oZYOXYhdb46anyJdTpcdhd9s/sm2aNlIs5hsXgCHhZsWRC/csQfktschnzw5Ump1yvdyXA6YcyYlrf58EMRP9a3Uajf0CBlV5qypW5LYyZ3LA6bg+LM4rZ9CFJOx0oytEiWdW8wbA+OOKL1vuvDD0sf7MknpcTCX/8qAaS1rXWHCpuZ8KlbA1u/6FwlQRfSdJwI4opR5a1KWJqyrWEbbyx+o9lj3/jZjQnjR7uyk+nMbHZxJikNdsHbF8S9Hj9eJndiWb4cKipautK2YVmw++7J37vmmrbb0tfXSxmPqiS5EL6Aj6NeOIp6f/TmrlBcMu0S9n1y38ZlY83GRvGGRvPjph+56fObmv3Mpo6DdmVP2XmjOLO48bMi7Mh7+cqV8rufeqo8r61te8BYaxFxNObu2FyQmyTrXodgwa2da5McqAWdYrDXszmFjXaO+4vBsCPYvXj3hFIoGp3gupjhzGD34t23yzntuqs44HWkfEp3JTdXXKl+/FGEdWlpbReqKCXt+oAB8PTT4tQ7YUJXnK3B0GnskLmwVNiZEpY7FX8t/HBp6vEiWzpMfma7udruKHJy4MYbW3akbAulpXKv33dfiU95PG2bu6ivl/jUN9/AkUeKO9Wq1Cs7p0bxVMgbB6qTVCv1G+DLX8H7u8G6V8Q5w1eV2njfXyNi8a1fwYxj4P3doezrzjkvwy+CzijKuwGI9aPpCzQd2Te3jbOFfTcrpXpprUvCtlKNZtFKqb7A/4CztdYrI+u11hvDjzVKqRcQK6pnO3BtO5Rn58WfelAHk1r9xW4/se/EuHUbqzcyd/PcuHVNVeiRY0fQaK786EoeOuqhxnXlDeVYymoc8NgtO6ePPj3hOGX1ZXy06qPGQJ0jiXJxadnShHWtMWvTrIRrS8YNn92ARqNQ3PXVXfxp0p/IdrUxQ1mHoGY5bPtebq71m8J2WyFp3F0F0GNvKNgLckc3r87UGqoWQelHsOEtCeYG6sUS3pYGjizoOUWUnj33B2dO286zi7HZZCLph3A19KoqKCmRAVVbGTcu3sr400/leFnNV/NokfVVUeFSSIfok5VcvNEnqw9p9rRGsVDCJGE3YuJEmbyLBIM//1wCjG35jiL9ho01G2nwR7/wlgK1vTJ7xf1vr6rs7F6TwdD1XP3x1byz7J3GNtJu2Rnfazy/HR91krrv8Pt4b9l7lAZkMqPeX88Nn95A36y+nDr61B1y3u2mxyTY5Qpxo0jVDrKNrChfQbojPamLVXvEG/1y+rGsfFnC+gTb9z7HSEZ7xWwSYhjbvoNvz4NJT4ml5c+Mk06SutYtOXCceCJ8/71kpDkT5zgTqKuDQw+V9rspayrX4LK5EhzPFKpd4o1eWb1Ic6TFTUCCiHTqfHVdXlPcYGjKwQcnd09oyty58PvE6hwt02MSrH4egkmiVQtugcJ9wOpgvd0uZkP1Br5a/1WHjnHxexdzwq4nJKzfVr+Nh394OG5dmj2Nl058iVE9RzV7vLK6MvZ/Zv/Gcp8An635jCVlS9ilxy6AjCuS2fU+/zz86U8tl6Bqjdi+99Spcr8NNMlfmD0bvv5ayl2lmsmmNfzrX8nfO+fNc6j1xQsF6vx1rf42IULc8sUt/HHiH8lPTxRqb2vYFvfaaXdSkF6Q0vn2SO+B0+aMS/JI5tS0PXj3XTj9dAn2JouRDhwobePxx4u1fnq6tKPV1RJUfuUVWNDcELDPMZIB11RYsewh2PUKcHTS/3DtKgnctlKb3GAwdJyxxWMThIPeoDdBkOYP+hlbNJbtxS23iMihrSLsnYWRI8UdaeVKKWX21FOwcaMIObzeeNGjzSYTiaGQCDdOOgnOPju5s5bB0E3Z7nNhqaK1fgx4DGDChAndt25sZ7NlBrQl6XjoBV2eENVd+NOfJGFhdScaos6eLeKLXr3guOOkpMrYsXJf9/nk3h4ZhzscsixeDM8+C2+8AWvWdN65JKCUxAyn7Za6C0sq1KyAr88EywlFB0G/E6FgAmQOBlsGEAQs0AGoWweV82HjW7DxXfB1YpaB4RdFZ4g3ZgHDlFKDgI3AacAZTbZ5G7hUKfUSMBGoCjdEW1vY923gHKRu5TnAWwBKqVzgPeBarXVjREMpZQdytdZlSikHcDTQfC2RnYAPVnzQpu0/XPFhwrpHfngEu2VvHLyMLRrLaaNPS9huRfkKnpv3XGOg7M0lb/LgkQ9iKcmgXFW5ikxnZuMkzoCcATz7q0RdzMbqjQx7cFjj51V6KxO2mb5iepuuC+CDlR+0Kt5YW7mWVxeJF62lLII6yL3f3MvfDvhb6x8QCsoNdfHdMmEUEbgEmsm4WfeabBPywvEbxeo9Qu0amHsdbHpPbtg6mNyStQGoXgprXoKQBzKHwOE/dKsJqUMPlQY5ktn0zjtwwQVtV9IXFkJxMayLce+9+24ZwDbNnGuOSDC12lsdJ2LyBDzNOm/0ye6D3Yre5lZWrEy6XXdgzz0T1912G/zzn6l9R8GgZGRPnSoW9Tpm0jOZ9XGEAncBLpur8TvdWL2xzeduMLRIKCCd3KqF0eB1sE4U8Tok9zxbhgS003pCzmjIGZlywPzGT2/kge8eiJtgcCgHf5n8F77Z8E3cttdPuZ7LP7y8cduGQANnv3k2lrI4edTJnXfN24Mxf4NN70LlPGlnOpO0InHOSjLU9wf97RJvDM4bzCerP0lYv6qiiWBMKZj0JHw4OflAa90roOww8TGw3J3jz9tNOO00uPnmlrepr5cJwzlzoKio5QBnfb1YxM+alfz9NZVrErIQQVyY2iPeKM4sjmtzI7jtbtZWrWVk4cg2H9Ng6AhDhkjfsaETYzaN5E9InjcHIv5e/z8J6LTUr29BlN8Sfj80Z+z70EPRAFmPHtC/vyy5uXJ7jaW5UplNJ7hi0U0ahs11m/l01accNPiguPVXfnQl/mD8hPjIwpEct0vTcuDxDM0fyvG7HM/ri15vTC7wh/xc8M4FfHHuFyil6NtXBBpNf9d//1vqOneEWLHPPvuIEKA6SSXOq66CL79MLYutvl4c9ZI5g6yuWM1LC19q//miOf7l4/niN1/ErQ+GggmCELtlp8Cdmngj352fIN6o8FSgtaaZyrRdwv/+B7/+deJvnZEhv/W550qpT62TZ7Tvvjv8+c/yG/73vyKg2RI7DVJ0ULgsWxPxhg7ArEtg7/92joCjZnnnZf8ZDIYWGZg7kGAofmyUrL8LzZf86wrS0kTUcOihXdQv6SYMGQLXXy9LSYkI0xcsEFFHfb2Iz4uLYfRoGDVKBOlGsGHYCdmuc2GGFPBupU3OZFnDutX8S1ficIhooivan5ISKXkSKXvSq5eUVsnKkrFnXR0sWwYbNqSWVNFpZA3tuoS3kE/KLJbEzG9aTll0IPkc4M+M8nKZh9Ja2nDLksdkz7fj0PFnSYfFG1rrgFLqUuADwAY8qbVeqJS6MPz+I8A04EhgBVAP/KalfcOHvgN4RSl1PrAOiMyqXAoMBW5QSt0QXncoUAd8EBZu2BDhxv919Pp2JAkTGq2wujJeQlfrq+W+7+5rFFJkObO497B7OXDQgQn7BkNBXl/8eqN4o9pXzZtL3mzMpFpVsSqupm5zTgdFmUVxQZ56f31CtmV7Mry+3fBtq9tc/9n1BIIB3HY3/pCfhkAD//r6X/xp0p/ISWvB1WLjNPj+9+CvjIo18idAj8kS0MnbPWqjFfJC9WIo/VQygLd8ERVuBH0w7wZY9qDUwArXLMaeCb2PlGO5e4HlgkCNiERKPxZ3DpDjdrOOw377SSA0ErS88044//y2HSMQALtdMqbuuScaG3vsMalhmSoVFdL4ryxfGZcNrpQiy5ncnqJ3Vu+4gfqWui0EQ8GkNvE7GptN7L1feSW67okn4NprUxNveL1w+eUwbx6sqVoT915saZSmFKQX4LA5GsUbm+tSseo1GFqgdhVseBs2fyZK4/oNYk2Nkk6sDpDcFdImAg7LJi5FzjzI3kWs6fscI45HTXp9V390NXd+fWfioRSc++a5SU+vaX14X9DHKa+dwmvqNU4ceWK7LnmHYNlgvzdg2ujOKyViS4cjfoLsESz78vYEBwWQ7ytV2/VYhuYPjROTRiirL8Mf9OOwxUxF5o2FgWfC6udE3NiUtS9A5Vw44D1w9fjZWF0OHCgBz4ULW95u61axqXzhBQl8Nm0j6upkUP6738G0ac0fZ3Xl6jiXpgiegCdpmZvWaE7wYSmLNZVrjHjDsEM48kh45pkuCBbljGp5MnbWRdL3b6lv709SQ6MJGzeKG9v774uguqRE3Os2UUQR8X22LVYRt98ufe/6+qi2zeOR5rNnTzlGQYGUxpq5bmbc/nbLzh/2+kOLE/wz1s7gs9WfEQiPcyxl8fAPD8eJN+aUzuGlBS/FjQkznZncMOWGhOMl46/7/pV3l73b2AaFdIjZJbN5d9m7HDPiGJSSDK+mv+vGjTB9OhxzjIw92kpEZHH99fJ64sTmnZBmz5YMtgsvbLmfHghIsPKWW5K/f8LLia4ldsue1CkzQtOSp1+u+5LFWxeza+Gujeu21G2JE2eDiHJaKqUYS0F6QWMSRwRLWVR5q8hNy03pGB3lhx/gzDMTg8yTJsHrr4sgqbUSBC6XLJmZcNll0i6ee27MBgV7Nh9g3fg2lH0Fhft1fIxet1oCugaDocuxlMXQ/KEs3Npyh3pY/rDtKkYD6b9fcAE8/vjP14Ejll69ZDnkkB19JgZD57ID5sJQSq0BsgGnUup44FCtdfetDb69cRbQvLI+CbWrRUhv3w7uG28Up1gWrz1YcEbryVz77ivzMi+80LLTa0cpKUnu+rpDGH09rP2vxKi7mpBPlm6Izye/SWWlLBUV0efl5XC5u4ichtT/PkspYmDvaHhe6+iYPOKSGArJOsuS8VpmJmRni0tifr4kmRQVSVwiN1fW5+bKMn58+8byP1c65avQWk9DGqXYdY/EPNfAJanuG16/DTg4yfpbgVubOZU9Uj/r7s3K8pVxpUxSIaiDLN+2nGEFwwB4eNbDcRPXDpuD/Qfun3Rfm2XjrN3O4uEfHiYQClDrq+Wvn/yVX+3yK5RSLN+2vLH0BMCA3OS1M+yWnSxnVmNdZLfdzaqKVYwpihZy/7HkxzZdF8Dc0rktvr+mcg2vLXqNgA5g0zYOGngQH676UNw3vr2Xmw64qZkDXw9L7o2q8PocDePvhbQiyexN1oin94XCKRLoidyY/bXw6VSZTIpkCveYDOPvkTpbQY+IOGJFA4FTYLfbZCJz+SOw8La2fSnbgX33jbclXr9eMqBOOik1u3aQ/e12OPlkyQaMiDfq68Wi+sknW89aq6+Hs86CGTPEPSN28rXAXdDsoLtPVp84O3inzcnGmo3bNcOiLZx6qgTna2rktdcr39snn7QcnKyrg7vugvnz5XVJTbSnlGZPo0d6j2b2DH9/MR3ciobtn1Vn+BlQtxaWPQxrXwwr3nV8MDyQSp3voDhyRJo+71aZpS77Gpb9B06JT319eNbDyYUbiKNGS2XGknHyqyfzzfnfpFSiq9uQORAOmAafHx0WH3ZgdtKeIWKQ7BGAtLuRyblYctJy2iWA65vdlzR7WkImsNvhZnXlaoYXDI/fYdw/ZeLE4yXpdVUthHdHwrALYdRfpYSZPROaTDY14q/dKSTfv/udiPZaC+iuXg2TJ8Nhh8F998HQoTIwqq4WoeW997Y+KF9StiTpb+ywOXA72h7EKM4sThDngEw0rqlc0+bjGQydwTHHiDVrMveEDqEUFB0CG95I/n6gTmrjHvRpWJgYM+wOhTNyvkwuGPR4RDz9+ONiKetwQG2tBDMOOkjcdxaOLKV2gAQ90tIk8yUrBCuV3AssC7ZtE+HAqlVS5uPzzyVAAvDwDw8nuGiMKBjBPYfd0+Jln1N9DsMeGEYgKP/rIR3i3eXvsrpiNYPyBqG15ry3zktogzMcGRwz/JgWjx1hbPFYRhaO5IdNPzSuq/PX8bt3f8fqIatJs6dxyinJf9frrpP7YnsCPqGQOANGxBvZ2VJC8sdmhq5XXy3OeRMnNl+qJVK6KlmW26Kti1hUFh9zd1gObjvothbvwe8ue5dPVn/SeL+1lMW1n1zLm6e92bhNSW1JnDgb5LdKtWxKMgGPy+aipKZku4g3PB4RXjVtC085JbWxYzIiQo7nn49ZaXNJ+dLSj5Lv9MWv4NBvRExsa8Z6MhUBbcgPZd9A0QFtPW2DwdAO9uy9Z6vijT37JLE+3Q7cfTd89x389FOi6Y/BYNh52J5zYeH3BnbgdH/+9JzSfCwoGSv/Tyb32Q7ijS4TbkBb3Ebuu0/KEXaleKNbYXPCvq/CR/t2bvmUbojPJw4nixeL09WCBbBkCaxdK2INl0vGx5FyNsGg9EF8PriF0qTHVCoquMjNlXnAiJvGxLCzhlJyrFBIHoNBSV6oqYkKRWpqZEkm6rHbJdZht8txtZZEFUMUo2PZTkQmm1OdEH15wctxr+2WnXRH4uxtvb8+LlD+0oKXuGH/G/AGvNw+M5o1a1d2zt7t7IQMmljOG3ceT85+svF4G6o38NGqjzh0yKHM3zK/UQiiUAzJG9LscQozChvFG0opVlasjBNvtKcsw5b6lsu83fDpDY1BxIMGHcRlEy/jmw3fUOOr4e6v7+bPk/6c6L6x4ol44caYv8Ouf5bJn9awuaIBHK3h8yOhco4EYpUN9rgfBp8r9dOUlTzYE5vBM+IyGHJe65+7ncnMFDeI//0vuu7KK+HYY1MTbzQ0RO1ux49P3OeVV6RG8dFHNy9OqKuDRx+FL8JuwMu3LY/LFG7J2j3blR33P+ewHKwoX9FtxRuHHpo4gP/2W3Eouemm5IHKujrZ5tYYSdvW+mhNaoflaDGDsiC9ICF4X+2tbtmtxmCIUL0UZl8NJR8AoeRKY2e+OBjl7Q6F+0LuaHF4sJzS0wv5IOiVmoBbZ0L5j1AxR7IUQUqCBGriDrlwy0IunnZx0lPKdGa22NaBuE3FChJBrMf3f3p/Si4vIc+dl9r1dwd6ToHDvoOPD5A6ik3rtreGsoEjBw7+VBwvwjSdUIpQnNH2chogYrpkmcSWsli+bXmieMOZBwd9DB9Oan5iJFgPS+4Rx6s+x0GvQ6HoQMgYIGKOUAA8W2DrlzIxs+7Vdp379uS002RCMFU++AB23VX+lWw2GSilyrJty5Kuz09LLTO7KUUZRXGCyQiegIcV5SvadUyDoaMcdlgXTo70+xWUfth8mcVts2DaGAkaZY9AssG0lBKbeVLSLKAZi6dwxhAJdkQmrgcMEMe6iRNF2JuVlVgxKplYoahIlj32kL525P7gCXi47cvb4tyV0h3pXLTnRa1ect/svowuGh0nrAiEAvzt87/x7K+e5aUFLyXcW9Id6Vy1z1VtEv7dMOUGznzjTGp80fa/2lvNXV/dxQ3738BBB8ULzCMsXgz/+Q9cdFHbJvhra6UMR2Vl/PqzzoJFi5KLL0IhOP54+PRTsX2PdeBoaJDf6thjJWjWFK01F7x9QVxpGbtl5zfjfsOV+1zZ4rmePPJkBt4/sHHMHtIhPlr5ETPXzWTf/vsCIuRuWv4mEAqk7LyR785PSCSxlEVJbUmcw0dX8eCDMsaJZe+92y/ciCVh/6G/g7JvE/qagAR6PzkQDvkSMvqDI8btMRSQPuzifyX/IOWI75OtfVHcPVsrw5JW1MVBfoPh58/EvhN5ZdErSV0EQdqliX12jGDfbpdyxKNGSZ7CjqA11yKDwWDY6XDmwLh/wU9/Sk1Y668WF/ZJT3U7F/SuIitL2p8DDvh5l++KI3887P5PmHOtJAv+DNBaBBozZ8LHH8t82aZN0rYrJTGEpnHBSFzBZpOSk0OGwODBMHw49OsnThj5+SLSyMqS8VJamsRR/P5oiZRUsSzp77hcsm99vQg4qqvF7aO8HEpLRXCyapVcz6pVieM/gxFvbDdu/eJWbvniFlb9cVVKteJjSxdYWJwy8hROG31awnavLHqFF+e/SFAHUSi21knv/6k5T8UFg5x2J78Z95sWP3Ns0Vjy3fmNE1p1/jr++slfOXTIoSzdtrRxO7fDTZ/s5GVTAHpn9m4M0nsCHlaWr2x8T2sd55pgKYtr9rkGlz1e3BAIBbj1i1sbJ5W11s2Wu1hdsZrXFovrRpYziz/s9QemDp7auG1QB7nnm3u4+cCYQvJBH/z056hwo/dRsOtf2me9vvpZKP8pmmU+8hoRbrTlWPb0bttZ+P3vpTGIuEFs2iSBzP/+t+VBXyAg9sW//72IN5SCc84R943YYOtZZ4mI4+CDk1u/P/+8CEYizN8yPy5TuCUhhlKKAncBJbUi7/OH/KwoX8FBgw5qdp8dSWamiFleekkatwj/+pcEkx94IFrTOdKAvvWWfK+R7YOhIDXeaPDRUlaLWXYF7oK4e0WaPY2S2hIj3jC0TCgoweoFN0vguqlTVMYgGHYRDD5HhAHBBsk8tjWTmgqQOUjEHYHasEuRTSbFlt4vJVjCbKrZxIHPJJb/ctqcXDD+Ag4elDRRIYFHf3iUz9Z8hi9GcBLUQQ557hC+Ou8r0uwtnGt3I2dXOHIufHKQiF5SrbFoucRN6pDP5TGGdVXrku7SL6dfu06xb3bf5K4MAS/Ly5cn3yl3NOz/jjiLtFSnMuSH9a/JspPTs6dk1b//ftv207ptwg2AtVVJZhQREW57cNldpNnTkgbKF201jq6GHUNGBpxwgtSZD6WemJQaxVNbt0etWwMf7AXFh8h9tmGTiMl04sks3DCSI++cRn3MIU89VSasXS4JtjTn8NAa7pikssd/ejyu7wfSfzx99OkpHevSPS/l0vcvbXRSCoQCvLroVW4/+Hau/eRaAqFAXEnDkA5xwfgL5IWvCurXiWNX3TqoXSnfSTBiNavBcnC0cpCpAmi7E4UFyiKgQ/xj5j+4et+rcbmc7L+/CNiact11IqoYPDhR5JIMr1eyoJ98MvG944+Ha65pft/KShHHnH22ZFPn5Un//NlnRYjXXObQW0vfYu7muXECartl58q9WxZugJQpPXb4sby2+LXG5Ir6QD3nv3U+iy5ZhM2yUVJbgj8U/xt7g94WBd2xFKQXNJZTjRDSIUprk2dmdSY+n5SZiXXdsNvh1Vc7LtxISu+jouVOk55QhYiwBpwmrmDu3vL/W/qJxBOqlyTfz+aKd55b/z8Yf1/r53NCku/4he7vHGYwdCd2K9oNu9V8uNtu2dmtaLfteEbxFBbChx9KmeLaZvSfXUV6usScDAaD4WfHkPMksad6qZS9b411r4iIY99Xwglm3a/Eemez117wz3+K2+svZqJ8+KWw+VMomZ56rLSbobWU7Xz0UXj5ZRlvWlZ8H6ImiQ59/Hhx7pw0CXbfXYQaPp/EDh0OiRG0NF6OOBd2BJtNkrlzcxPf83qjTjBudxe4pf4MMOKN7UBFQwX/mPkP/CE/l067NM7StDk+WhW17sx0ZXLa6NM4ZkSi1aylLN5e+jbV3mo0unG/5+Y9R1AHyXZlo7WmKKOocXCycaOUn5g+XWx06uvlHzctTREaezG2ETfjsjmxbJqfSn5iS92WuEkch+Wgd1bvZs99YO5AvlgnNgm+oC/OrnBjzUYRVYTjlW67m9sOTl4u5N/f/5sKTwUgE8orK1YmZuYCN3wWdd2wKRtTh4hw4/xx5/PAdw/QEGjg7m/u5i+T/xKdkK5aEH+QIee3T7gBsPjuqHova7jYt3dTIUZ7OPjgxGy+N98UJ4ibbkou4PB4xBpp6tT4zsCf/yz1oWPx+eBXv4KLL4a//lVu5kqJndLf/tbE2hZYvHVx3Ouh+UNbPP/izOJG8Ua9v57FZYtb3H5Hc9VVYgPdVAX7+OPiYnLBBTB2rHw///d/kmEYS1l9GQ6bg2BAJtM1ulXnjdja2ZayKKkpYZceu3TaNRl+ZgQ9UiaqfHai9VzmEBh3F/Q6PN51qDmr6aZYNlHMR+h9DBQdBA3yP1zlqWLKU1MobyiP282u7OzTbx8ePOLBlB2uDht6GMMeGMam2k2N6wKhAIu3LuaEl0/gndPfaVd5kB2GuxgOnwULbpMBq9bNK8tt6YASgc2YG8CRHfd2tbc6zuEoltbuuc3RJ7tPUlcGb9DL/M3zm9+x6EDY7zX48uTw31tnz752P/74R1HRJxt8dRZa60bBb1Na6uO1Rl5aXlLxxuqK1e0+psHQUS65RPqunR6gchdB1jAp49QiuvmyDDH8b9av8Pjj28srrujcDFlf0MfNM25OcJ+aMmBKyq4MJ+x6Ahe+d2HcumAoyC0zbuHFE1+MCsO0hvoNDPevJ2vGEVAxW8R2tjTpI4S84niYMUDcliwHoCBYjxVo4PNB+fxUHXZfVBp0kAIVxOmvAlshZ5wBX32VOPEVGVt89ZUIo1sKSPl8Mmb59a+Tvz9ggCxLlyZ/P3KZzzwji93eupDOE/Bw4bsXJvwGk/tOTrmNvWbfa3h3+btx99uNNRt5fPbj/H6P31NSU5LQjtste0LCRHNku7ITBJfeoDeuNGNX8d13iVXOzjpLssC6BLsb+p0Ia19IKqoStDhnrH1R/nab3S6Gpm5j3q2w5gUYdJbYOBsMhi5jTM8xzY5lQOJCo3uO3o5nlMjuu8Nnn4loe3sJONLTRZT49NPb5/MMBoNhu6IsmPqllL0r+7blBKAIJdPhgz1hr/8Tl4aIg3pn0s1c1S69VNqf99//hZRQUQomPwfvjYL69XSo3PQOYPaa3TlluMwDeTzxyb7JGDoUzj9fEn2zskSkESvASMVJf3vRVBzSo8eOO5fuihFvbAeu/vhqfEEfCsVHKz/iy7Vfst+A/Zrdvt5fH2cvHQgFmlWF71a0W1zm1MqKldT6annjlDfiMmNc3v5ceim8/roEqCK1kxNYchWq6EhUusbjhT6FaajLsuIy+TW6xcD+4LzBKFRjJlFstuWCLQtw2pyN9XdbOk6/7H6N4g2bZWPBlgUJ4o1ZG2fx8sKXCegAlrLYtXBX7ph5ByAuC5Fz8Aa9XDrtUp474TnZ0Z4VnynuqxDr0xbU+bxR3Hpj2+foxEDNTo7dLrWfb7ghPgPqrrtgzhzJLEtPFyVdKCR/W++/D7/5TWK2Wb9+Yh/8xhvxgU2txZHjP/8R+6ZgUBw+khGbKeyyuVotgdI/pz+zS2c3vm5xkrAbsNtuooT94otES6pt2+COO1ref1PNJpw2Z+MkaTAUpEd6861fmj0Nm7I1Zu4FdZBNNc18+QZDKAhfnCClTZoKN3ruD/u/K0INy9E5n2dZYGWBIwtvwMuhzx3K+ur1CVbeaY40nj/h+ZSFGyB2ua+c/ApTn5saVxO+IdDAjLUzuOi9i3j06EfbdMztQSAgFuxLl8KGDWI3t3mzdOS3bMlg27bbaai9nl/t9iSnT3yKXXotQhECFBpYWjqSV2edyWuzL8CZkUVBgbg99Ool9vr5+TDhmOW4HW783visXYflYHDe4Hadd5o9DbfD3ZipHcv8La3cl3sfAUfMlhJlDRs7v15lWlHnHq+DTJ0q2fVdKd7YUrcFm2VLyMwGGJAzoN3H7ZnRk401ieXxYkVSBsP2ZtIkcUToqHgjadb/wDNh/k2pZXe1wtQxH3H729fS4IuOR555BkaO7DwBx7Nzn02Y0MpyZnHRhNZLpjRu78risCGH8dbStxrX+UN+np33LDcfeDOT++wFy/4Ni+8EX6WMuUJecPeBPsdA32MgdyykFcokeNBLsiDacGVnuM0N/rBbx6b3YdN7sh8i0LjwwoTdAElQmDxZEhZyc5OXlfF4YP16mDJF2tHm+P3vxc0jFXvhVByQ7vr6rrhyMCAl367b77rWdw4zrtc4RhSMiBvj1PnruOqjqzh11KmsrlydUBYx05lCadAwlrJId6THtdm+oI911clduTqTjz9O/K7PPLMLxRsAI/4I699ILcifinADoPfRsPa/8esW3gIDz2j7+RkMhjaR5coiz53Hlrrk5Zd7pPcgw9kVVj5tY8IE+OQTSZiqq2ubJXlbSU+HY46B555LzZXKYDAYdkoc2XDghzD7SljxaGp9u+ql8PEU6LE3jL9HHGCVo/PEtslc1Vqiix3XlJK2YLfdYN26tju47pQ4MuHAD+CDiRDYeewd3v3pSE558FUaWjH7jHD66ZLo63B0L5GGof0Y8UYXs2DLAp6f93xjWZP6QD3nv30+iy9Z3GxG77cbvo2bNAnpULMT1E1LsLgdbr7d8C2HDD6EoswiAgG4/XaZ8A0Go+UqcnLgiCPgkEOgf3/5h25ogCVLLD7+eDe++krKvm7YCFsDi0h3pDcGmXxBH32ymi+b0je7L26HuzETaE3lmsb35m+eH5ch1NIk0PCC4czbMg+AOl8d8zbP44RdT4jb5uRXT46r9/vthm/5dsO3je9HglaBUIDn5z/PrQfdyoDcAZA9TKyLa5YDGhb8HfqdAM7cZs8nJZWk5WhdodmiCMSCM1qR0HUSPl/UKslmiyrxks1TXnyx/A3VN+nzfPQR9O4tNYhHj5b3P/yw5QDo7bdLjbVknQOtJYjaHA3+Bqq90UbWZXO1+LcIMCR/SNzr2DI+3ZV77oF9921fDbqS2vga196gt8WyKSDBjYiTgTfgbXQqMRgSWPsSbPkicfK8x95wwHvtdzBqhZAOccprpzB/y/wEG+8MRwYPHflQu9wC9um/D+eNO48nZz8ZJ+Co99fz3/n/pX9Of66fcn2Hz78jbN0qgrfPPoPvv5d7ZMQ+PyNDahQOHSrZW717iwCjoCCd/PxLycy8lDorhBWsQqEJ2nLoFbJx/inwq3IRhG3ZImK5FSvknr50Kdw1eXlcibMIafa0lEq/NUdhemFS8UZKrgzZw+Co+fD9RWJvGWygw4p5e4ZMIB76VceO08lYFtx5p2REdJWV5ZrKNbhsrgQ3FJuytSqKbIk+WX3iJhMjeAIe6nx13SJQbvjloZT8P910U8eyi5JmufQ7QcYRncDEod/z1O9+w++efQWPR/rp//63WKQ+8wwUF8u1tEfIEQxCZXWAGz67IcHxIaRDHDnsyGb31To6jlRKxgwX7nERn67+NE6EENIhHvv8Gm7kBykXE3F/chXC5KfFSSkUAkeT+0BLJdUAXPmy5IyC4Zc0rs7KkoyiJ54Q69imLFoE48ZJ2cHDD5ePdjrlb8Bmk1I6f/lL6/asp58u1sKdQmYJt35xa0Jfpoe7R5vLOt4w5QbO+t9Zcb9nvb+e6z+9PmlZrBxX20oiZjuzE9rsNRVr2nSM9jBnTuLvOX58F39owQRI7xOODXQSg8+GjW9JOcAIdWthyd2wy5+7rM9sMBiEMT3H8MnqT5K+tyNLpjRlr71kjHfooTLu83ZcC5qA2y2liG+80Qg3DAbDLwDLBnvcA0UHwA9/AF95fH+sOcq+hg8nQc5IGHweDDoTbBmS6NvaeGUnIyND3F732EPmcDq9vGh3JGcXOPhj+ORACOwcNWOe/uI3NPhSH/zfdlsXlZk07DCMeKML0Vpz/tvn4wl4yHRk0iurF8vLl7OpZhOP/fRYsxlOn6/5nDpf9CYyLH9Ys5m/SimGFwxn7ua5ANT76vl8zeccMvgQamthn31g5croJPBhh8nE8ODBEoBraiV7+OHw299K5/6rr+BPf5LJ7tjP9wf9LU4G987qjSMm67qsvoxAKIDdsvPdxu/isjxHFY5q9jijeo7ijcVvECJEUAf5bsN3Cd9T08BU0wyjppz5xpl8ed6X8mLK/+CDSaJSqVsLM46F/d8Gy5m87EkqNldbZ0q95payzls8Rue2llpL4HLGDPjhB1i+XCb+tmyR3z87WwKwgYA4sWgt9Tf79IEhQ0Stl5kpGcCPPCKWtU0FHFrL38pXKc59DRkiAdB//rPtk1KrKlbFCYmUUvTJblm8MSBnAC6bq7E0yKbaTWitu102fSzjx8Nll8GDDyZ+3y1hWeK8EWtzrLUmo2mQvAm5abmN4g1/yB8nuDIY4lh4S/JSHBMf79Ig9H3f3MfbS98W9wa7u3G9RjOp7yTO2u0suRkFasCzVaypI4/ereDZAoEG0H5xWdIBUHawHNyVr3jTbmNbyI6KiO+UIhiSSa4pA6YwZcCULru25li8WEpNff65TDJF7gU9e0oW8O9/L/fr+nrJKE5Pby4YZwF5CWsHDYo+D4Wkn+D3S/t/xzdLEyb3QDJxOyLe6Jvdl9WViUKNCk8FnoCHNHsrA2JbGkx+CoZdCPNuhK1fRH/PlFFSNiZrCOx2K/Q5qm0XsZ046yy49Vbpw3UFayrXNDouxZJmT6NXVq92H3dAbnLXDrfdzdqqtYwsHNnuYxsMHeGcc6QcX3tRSoTvCWQPh4yBUN05ZflOnfwqh9wk5/rCC9JHnzVLRHojRsjkzuGHy+viYrn3NzTEB9wiAgu7XSaCNm6Er7+Gdz+roH5Sfdw4DeDCCRdSUeZi1ixYvVpEfIsXy/PSUhE7KBVtY0Ih0Opg1KXFkONBKXk/GAxxTuWrYHmI1sjsBUctkMCnzQUdMSi0HAljrCuuEPv3ZOINEIeqE04QceMxx0gCw9atUoqwsjK1jy0uhv32k+zoDmdF+zM4eBX4mjRbV3+1BvXnts2oHavg5GNhfVzlswAjP3uWT05MHB/luRP7Ai2R685NcE3aUL2hTcdoD8kmLrdL5ti4f8HXZ3ReMLd4qvz9NxWEzL8Zeh8JOaNN+RSDoQvZu9/efL7m8wTHRpuysXffvXfQWSVn111h4UI49VT48svOE287HBLLe+UV6TsYDAbDL4q+x0Lvo2Ddy+LE4a9OTcRRtQhmXyFL7lgoPgh6HQYFE2UsEgrIvFFnOQ7vIHr1kjHihAni6NuV7k/dhoI94YBp8NkRqbmy7GB+s/+TTJt7ZMoCjr/+FR5/XOIAseVIDDsvRrzRhbyx+A0WblmIRmNZFvccdg+nv346tb5arv7oak4bdVrSIMr7y9+PG2BM6D2hxc/Zq89ejeKNgA7w/or3ueXAWzn7bFi2LD676IgjZDIepBPfFJtNglogFrLffAOPzVsZl5mZm5aL1YK7RO+s3nEiijR7Guuq1jE4bzBzSuc0rnfb3QwrGNbscQbnDSbdGbVrbWqr/odpf4h77ba7cTYJgGh0nFPDzPUzqfRUkpuWK0rKA6bBjKPFynfrl/DWAMmEGXaJWCoFfVKL2bKJzVVkcvDVJplLtnS56W/9Ctb/D/qdBM1NQm2HWme1tXDLLfDUUzKxl5Ymv+c554iqsk8fscbXWgKwSslvX10t1vsLF0rpk8jfCkjg89134eWX2yYoSMZf/yq1x+fObb1WVwSnE1aUr4gXEoX8rTpv9MnqEyfesCkbpbWlHZqc2h78/e+Sbb9iReodKJdLxBux7jaZzsxWhSr57nxWVaxqfG3EG4ak6BBUL0tcn9YTMgclru9Ejt/1+PiM/ZAf6tdi1a7hxHQP6p2hUBeuXWhziTDD5pZMXXsOuPLA1QMsl9Q2V5aUgNFB3KF6ZowZz8dl60TgEawPizw0aIuxOcVdem3JqKiAPfeUe23s/3+fPtF7gjusYemMCQ3Lildnz908N+nEfir33JYYlDeIL9d9mbDe7XCzqmJV6hP7PSbCQR+IveWCW2HTNAjUy+A5UEuCI4c9M/pF9twXRl0vj90Ymw0efljKAnS2+4bDAasrVyetBW637BRntv9vvn9OfxyWI6Eci6Us1lSuMeINww6juFhczT79tH2BqfR0+MMfmnlz9A3w/e9SCwamQEGBOG488AD8+KOc89tvi6jiPw9pnnhc43CECIU0GouePS3cboXDIf1qvx/KyzU11UGcDghphcdrYbf3oP5NqWmoNcyfL44er/0O/l0q4wWPRwQjffuKyO/AA+UxPz8aAPJ4YNs2O6tXL2P1HBF5bNwI6W4fAx5LI+4enDsmbDucYvQolTKVMU6FQ4bIhNQ777Q8pti0CR59NLVTSMY//9l+V7w4vNlMeypF39tWsGl46q1k79Rw4+FbE9YWphe26fgF7sRkjc11XV+vuyBJjkhZmbiFdil9joHskVD+A51SC1spGHs7fPub+HuDDsBnh8EhX0j/+WeWyWkwdBfGFY8jw5kRFw8EyHBmMK7XuB10Vs2TnQ3Tpolw87LLpL3pSJvjdsNRR8H994uA0WAwGH6RWDYpWdf/FFj9PCy+C+pWh8s6ptAnr5wry5J75XXGQCjYCzIHy7xS9ghI7y/xxpBXYpUoWVTk0ZLnWofL7+nwgDS8WE6JZXnLoK7rSxTGMnCgOHBMmiRzQt1ZwNFZZUTpOQX2ew2+PKl7Czhs6Rx1xmi+OiOdU0+V8bbX2/KY96WXJPHjvPPg3HOjSdtGyLHzYsQbXUSDv4GL37uYOn8dLpuLS/e8lKOGHUVeWh61vlr8IT/XfnItjxz9SNx+/qC/sVQIQLojnYl9Jrb4WXv23pP/zv9v44Ttgi0LeOGlAB9+aG+0Br7hBjjyyLZZ59hscmNcuHVhnLVrz4yeLe7XO6s33kA0ZcZu2VlZvpIBOQNYVxVthBw2B4Nym5/wG5Q7CJuKpmeV1pY2ZuauqljF8vJoFovDcvD6Ka+T7cpOOM7VH1/NV+vFFsJlc3H313dzy0G3hC9mXzh+nWTALH9EJvPm3yyLuxfk7wl5Y8GRC8omKs3qRYkn6+oBDRukEf7hUsjeVRpwR5LawrG1zrqgjtmSJZIdVlcng72TThLVHYi9cEs2iXl5sowcmVyZ/+ijUkM6mZ1tcyRrXG02ESaMGwdVVa3bczkc0KOHiDdihUSegKfVSaY+2X3ixAtOm5OVFSu7vXjD6ZRA9D77SGZgayIXtxuefBKmV6yKE0+lYpHcNJi7vrqF2jWGXzDhQUeT7CWCHnmvraQ0QSMMBn6PggPeh4W3Qdm3IsIIeqDaB2nFMOBUsWQv2EtcFZQdgt6oK4OyhctahQdQkYGSDjFEBxkCYodopUHIAzUroOwbyB3e9mvrIBFBXWR8FyEUioruupIlZUuSrvcEPB26dw7NG4qlrARhiKUslm9bzsgxB7Vcd6sl8oGhHhgO5ABOwA/UAStrYRlQCvBBeIlh82axNOlmTJ0q7eRXX3XuINpul984kMSxRKM7JN4ozizGZXfh98V3ErxBb5uEgVqLEDWrhW3+9S/p09hs0fJveXniSBNZCgrkeg0GgHvvhYkT2z4ZYllSmuqAA5rZoP9J8MMlzbzZfizfVvbs+Sl7HvQFV4/+AurWEfA2UFI9gHXlQ1hXtSvrK4fSEMzDG0jD63dgtwVxOXw4VB2FGZvon7OE/nlL6Z+3guyMOtD1LFps49RTYdWqaAnFnBwRap91lgTvgkFZ35yzUzAoAsNgUP73lIKZM53gPgk2viPtKMCWLyXgmbt78nFRU1LqF8S3IbfdBh980AnCihYYPx4mT5YSZt05qAnSu6nyViWsL8osatNxCjMSxR4Rp76u5KCD4K234oWLH38sSQi2jji3tIZSsNej8NE+ieUB20pa+LvudwL89OdEYZe3TGpuH/iBCJxS+d8wGAxtYrei3QiGEoMogVCgW5VNiUUp+PWv4fjjpW178EFZV1PT6q6AxJAsC3bbTfbda68uPV2DwWDYebDsMORcWaqXwupnYfV/wbslHGRLsbZm3RpZmqIscPcRYa6zIOwY6IxZHCLsCPliFr84BdeuhoZNdIp4uB3ssoskbx90kJRWTnW+Z3thWTKf9f77nXjQ3kfAge/D58eE++ndrG6MzQ1jb4Nd/sQ4JDl/zhx47DFJzvf55HupTZI7snIlXHedLLvvLr/rpEkSW+zfX35fv1/G8G73ji2n5vVGXT7dbpn/KmxbvsHPHhPO7CL+MfMfjY4RSin+MPEPKKW4br/ruPzDy6nz1/HM3Ge4dK9LGd1zdON+P5X8hMvmahRL2C17qwOLMUVjsFvRnzLNlsYdd9dTVydChmHDpL5hexVqi7fG2wC3lnVbkF4QV7bBH/KzqmIVA3MH4rQ5G7Mxg6Egg/JaEG/kDYoTjaQ70llatpSxxWP56yd/jfuMw4YcxhHDknkZw43738hJr5xEja8Gb9DLvd/ey+V7Xy7uGwCObBh/N4z5G6x7FUo+hrKv0Q2b8GyaTtrmz1GRSb7Gib8Y0orgkM/hw70lEOOvgg8nwvBLYbe/SyfA7pbGuhUCQRvffQXz5okIY/VquSG7XCJeyMuLTlLYbBIwjQRXy8okW/vbb+U5SJbhiy+2b+IiK8mMicMhjeXRR8s5tubAkZ4Od9+d/L0BA+Cnn8QRZPNmuc5kpKWJNfSnn8JVXy2I+5vIdGbisLVsU9Ynq09cBnAgFGBF+Qr27d+9s65B7LF/+kky/UpLk3egIg3c66+L4ObRZ+JLCaVikdx0om5L3ZYOnbfhZ4pSUHQwlH5E3KDCXw2bP4XiQ9pmG9hmByINM0+KBsD9fhHZTXgIeh0uIg1HkxtXe20MrUzI2x1ydkxgLzdXsq2vukruuXa7dMpLSiRz6rzz4OKLpeNdXy8/TUZG+yc1gkGZJNFa7tuxQstYMp2ZCQ5XbaFfTj/cdndCSZYGf4MIMtsr3AAoB74PL22lqKjbzsY99JAMtDprUtLtlpJ4n29L4qKDiIg7Kt6IFd5G8AQ8rChfkbC+uloyA+bOhe++k8ctWyRIrRSsp4giEv8uKpxFfPllVNDk80kfqKJCBnx+v6zz+aQfsXp1t9TnGLYzY8aIOOHZZ2kUuKeCyyVC6GaNzCwH7HK5iAs7Ounr6gkb3oI510LtKhk/BGols2vY77H3Opx+eWPp58hhn0jQD038+CR8P1M2yerXQSkRueULnnzKxqWXyvVHbntHHimZvpHAWCrYbInbHnooEHgG5l0Pyx8WAWWwAT6aAsMugpHXiCMWWhyRktEOh8KRI+HCC0Vk3lF3wJa4804RyHfkfpyWBuQUday9a4XKfoVYKlG80SuzbeLLZNv7gj4a/A24He4ke3QOBx6YKFL997/htNM6MeOuOfLHQZ9jYf0b4sLWHmzp0WQNZcFe/wdfnpiY2ReoEaHIoDNh/H3y/2oP11UHSSoJ1LZw4zEYDC0xKG9QXMwwQkiHGJCTvMxfdyEjA26/XUqovfuu3AO/+05uB3a7jN20lnbbsqTt69ULzjxTymAPHryjr8BgMBi6MdkjZGJ87G3iLrzhbSj5ALZ9J+MmZbXdUVGHoH69LDshu+4q8zyHHipuj10pim8LLpe0b599Ji4hnUrPKXD4D/DJQSLiScWJZXtgz4B9Xk4o8bz77vCf/0iMcPVqcUz5+GOYMUNcJtPSpE8QKYkNIviYMyd6DMsSh83Bg8XBcvhwcXguLBSnzdxcGeNnZsrxAgE5VqTfkSqWJXOITqcco65OYnzV1VKiZ9s2ifstWyZik1WrZGnqPm0w4o0u4fsN33PbF7cRCqu2MhwZnPzKyQAEdZCGgNwBPQEPhzxzCJsu34QVljl9sfaLxvIOIBMaseKOZIzuOTquTIIn6GHFkujkyu67d0w1t7oivj59S4ILkAza3LRctjVsA6DeX8/SbUvpmdETmxUN6HsCnhYHTb2zeifYbi/YsoBMZyZvLX2rsbRMljOLS/e6tNnjHDzo4LgJ/pAOcddXd3HbwbfFb+jIhiHnw5Dz+X7j9xz37EEMs+rYo6AXN+93DdnOLBFhOLIleyytR/z+h/8IM0+ByjlSK3fp/bD8P1ITrdehUtvWWSABmaAHKuPLwNz5zpXc+ub14JDst4cekkYzEJDFsuSmF6k5bVkS2Iosfr883n033HOP3PAqKmD9epmX6qxgV0GBNBDXXw/33SfrmgbAs7JkwPnuu1KmpTkGDpRG5JxzpMHROlrnOFLW56STJBibng6Ltsa7nqRi/1ucWRzn1lHvr2dp2dJW9+sWBOrpn7uen6Zt4obbi3jmjWHYbCG8Pht2WwiNYt89SrjrxpXsvlce+AawqSa+NnUq31HvrHgfze2RVWfYSRnzN9g6MzEA/e15cNh3kNYLWhFUdYimA6j93oD8CdFAd2ezAyXIQ4eKQ1FVlZSZ+vJLUcOvXCkd9ieekDZh6FCxtB80SAY1xcVRx4Hs7Gh7oZR0uEOhaId561YRhpWUSOd/9WpYtr4c/++SdxqKMtqWtduUvtl948SmEfwhP/M2z5PGqgsntJqlqGPX1ZXstpu0g6++2rbJ5ubIyJDSZc88tjbp+96gt83W+rEUZxbHuT/FEmnDy8vhkUdkMnzDBhGUeDwitBgzBk4+WVynxo8HZ59SAlnydxtrEamAZ5ocX6moJaTXK5+zZIn83xjhhiHCHXeIsDnV/6e0NDj/fMlIapFhF8LCWzt2csoFmQPh61/LWAIgrRD2eUGcpSJijAgpt30OyB7BhsphXHppfDDuuOPgv/9tmztji9jdIooffC4suR/WvyZB0JVPyrgoayj0PBAKJkDWCMjoJ+5Z9nQJeh6/UeyNQwERxf8vNcHBP/4hbg2rV3cs4ONooQuzxx4ipvv88/Z/hmUhDW8qNDdp38qHl2xdhOvxSXGCd4flaNU9sym9MnthYTXGNEDKoZbWlrYaD+gIgwbJ/9vs2dF1s2eLmPXII6Nl47qM8XdDyfvtC6DY3JLJF0vvw6HfifK/kCDu0rD6OVj7MhTuC72PhtyRgCVZoZvehS0z2nsl3R6lVD7wMjAQWAOcorWuSLLd4cD9gA14XGt9R2v7K6WuBc4HgsBlWusPwus/B3oBkR/jUK21yVz4GWIpiyH5QxJiSMPyh7VaVra74HLBiSfKojWsWydC5/JyiRG63ZKsN3r0dhC3GQwGw8+R7OEw8gpZtJaSKlu/gtJPYcvnUL9Byi9bdpnc76hQv7NJ67xYVmGhxE7OPBOmT+/88r1tJSNDYkLvvCPzZF1C9jA4ci7MOBoq5kFwB160LQ3s2XDQR5DXfCKhUiK+GDwYzj5b1vn9sHw5LF4sMeOFC+X52rUilHC5RPyplCQ7/fCD/NZeb7Mfg1Ii4sjLE1GHyxV1vo08xsaZYx+rquRzKiulv9IcdrvEte12GYd32e+8E2PEG13AMS8dExfk2NawjZnrZybddnP9Zq755BrunHonANNWTIsLtOSm5ZLlajkFKtOZSYG7oLEGrS/ow+msgToJ7lVXtz9hIxgKsqU+Opa1KVuLpU4i9Mzo2SjeAJi/eT45rhzqfNGbYLYrG5e9+aJLlrLokd6D0loJcNX6apmzeQ5vL3sbfzAaTLFZNg4ZfEizx7FZNs4fdz73f3e/ZAsFGrj/u/u5Yu8rkroSvLnkTX79xq+p99ezGcU3JRt55b1bmHHuDIbmD23+otN7w9QvYeO78OMfwVMitv1bZ8oy78bm9wXe+vE4GnzpBDwiajj2WGko09Kad86IzbKOBLKuu072uf12eT1ypAgtzj9fboJeb/PWSB6PvG+zyQ03e3hx0ok0G/AP4GL68ixn8TS/YSuFOPCzBz9ycc1/OLxmOs4J4d+psFBmCZOQD7wDrKcvj/J75rIbNoLs5fmeC3icwufL4HnZdvUd8UWQW3OBASnPk+nMbKx1qtEySdgdCXrF1WDty1D6iSg/nXn0yBrOwxf14o4LBvLWV5PYUpFNptvDIXsuYGiPBeAphRmrwFPC1rr46HsqFsmF6YW4bK5G4VhIh6jx1rR67zH8AincG8bcBPNvihdweErF/nnqlzJ4aOqAkYx2ZNcmsPUryBktThltoQ0lW8CCM1qpW9QVFMv9Nwc4J7yA5FOXUsxSzwjW04/yrfls+6aAEnoxjyK2Ukg5+dSSQQgbISxCWGiIeRUkg3ry2UYhZfRkMwMpYQLbqOizlPtiHMBi6Zvdt0OX1De7b0LJlAgLtixIfUIrQkudm5+RXPvRR0XouGRJx8S46elSWiAjQ7O1LnmbnOnMjBPatpXizOKkfzsAq8pXc+21IvxUKjqB7PdLH+Vvf5NBoWUln0h2tsH0JT1dlr59Wyh1YfhFkpcnGawXXdS6S4NS0ne+NRVNhqsA+p8Ka/4bLdfVJmyQsytUzJV6yREmPyuTuu11kophxSorYUwxfnxUMN2p5I6BSY/DxMfkmjZ/Jn3c2lXSz131pEx0K1u09rOyIaOMgNzDI3WimwrCkgQpXS4RPE6e3LFMsdaEAffcA3vv3b7PSE8XN8yupqSmBEvFD/KcNif57vw2HSffnY/L7mpMPAFxBS2pLelS8YZSYvd/6KHx/6PnnCOOhAMHtq09aEoo1Io2N70PHPihZOG1pQ625YKcUbD384nv7fUIlH0drrGepB8U8omL3eZPU/+8nwfXAJ9ore9QSl0Tfn117AZKKRvwEDAV2ADMUkq9rbVe1Nz+SqmRwGnAKKA38LFSarjWjbUff621/mF7XKBhx7JX770SxBt79dk5a4koJe61A7q3aYjBYDDsvCgFmYNlGXQWfj/U1QbxbFtHsHIFoeoV2GoXkeadj9u/Aofehg0vQZwEtQOtI27tISwCKBWKOrmHnRJ1uIyz1hYh7GgsFGCpIJbyY8NHUKXhUwV47MPwpI0hmLErKmcYjryhpOX3JT3D1qLgvCOkpUni0FNPwR//KPNELU2+dwWWJWO7G2+Eyy/v4rKJIM6QU2fC0gdh7l9lLN60XHhXY3PDgNNgj/tTi6c3weGQ+b+RIxPf83t8lK4rp7KsnsptHiq2+aisCFBZEaS8QrNlq52tZQ7Kyp1UVLuoqnVTU++mzpNGTY2L2hrNhvUapcIL0ecAaPm71hq0lthzSFtobWG3AmSnN5DpbiAnw0NudgMFOT56FPgp6umnIF+Tm2uRl28nN99BboELqYVtiGDEG53Mv7//d5tLDvzr63/x133/SnZaNt9vjPf7Ht1zNFrLvPfGjRLAiNQmijgtOBzQ2z6azTG20qERr2L/4SICAcWnn0pWbWZm25OIN9ZsxGlzNtoNptnT6JPd+oR53+y+LC6LlltZWbESh83R6JYR2aY1BuQMaBRvaDQzVs/gx9IfGyd/7Jad88ed3+pEw2/H/5YHv3+w8bU36OWur+/i9oNvj9vu3m/v5bpPrqMh0ECGI4M/TfoT9357L6W1pezx2B5M//V0Jveb3PwHKQV9j5Glbh2BTR+wduGD9KiZT5ZNoSwHSlmSTaZDYtXV91jodRifn7AHH39m56WXND/O8tOnt8Xe+1iMHasZPkwzYKCioEBht4mYw2ZTBIMaf9jCqGyrZs0azdKlipv/buO3v5Ug5osvStD59ttFlTdsmCQZDxwomoqIhVFlpWSrbd4Ma9bAokVQ3Yp6vx8buI5/cB3/aHnDZoQbTY91Kzc0+77PBuX12yDmbzjVwGFhemGjeAMQe/7uxvr/wXfny99GoAYG/hqG/0FKN4S8oEPkWC7OPsAZDXSHDhMXFzTY3ITq11F9765xh23qqpGMgvQCHDZHo3gjzZ5GSW2JEW8YkjPySvm7W/SPeNW5pxTe3QUGnQW73Sb1u20tNDwnNDNR/0ILE/LOAvl/iDhwzL4CSqbDqL9Cj71FAKWsTq4dHg2y+/1i7VZaKurliJK4oiJq+/Z0C0f6/e+jz2N1B8GgCOf8fnHM6NkTbmzGgUIBvSilF20UOqTI8wUQqgGSaCuH5A3p0LH7ZPWJmwSKZU3lmg4d++eM2w0ffSQuHFvamRvqdktZhPHjYXPtFmyWLcHdDGjz5F5TCtwFzYo31n0ziQfeTnQ8uOACEXR0VcZge0rHGX7enH22ZJs88UTLAo6MDCnbl3IGyNjbpNxCIMXi9LHY3bDLn2DWxfHrt82Cgj1TE2+0Ikyc7HeS61xOva1/o4vNc8+JxXpeXic5GhQnF34n4ADya6EHkIVoNmxIIxcMLz6gDNgGxBpvNSPCHjsWbroJbr65feVT3G54+umWt9l9dxFwXH552z7D5YKJE+GG5oc6nUZJbUncmBtkzFzgLmhmj+QUpBckuGVpNCU1JR0+x9bYZx8pBzltWrTNqKuTsjUffig2v5nt6OpFnCn7tBbO6DER9nstXO4kBaWOsovo46CP4t1xItjT4eBPpMyqZ0s7BV4/S44DDgg/fwb4nCbiDWAvYIXWehWAUuql8H6LWtj/OOAlrbUXWK2UWhE+zjddcxmG7speffbi5YUvN44/0u3pO614w2AwGAwdw+cT58/162UpLZW5trVrZd5s82aJ70XKTsicmw2bbRA22yAsa2pjHC8tTcYO7rQgPbIrKcypoDCnnB7ZFeSll5PpqsRh86NUCLsVxLKChEI2AiEboZANf8hBrTeXivp8yqry2FqVx9bqfLZV51DfYKOhIeqKoHXU0SAYlHOLuLPX1HS+uEEpKdV8+OEybv722+3nwpGRIQ58L74o81fbDWXBLn+UObqvzoCq+VEnzK7Eli4O//u8CEUHtO8YQa8kSNQsg5qVULsCqpdD/TrwlOII1NLPSqOfssl1ZgAZGvoEZQ4q5COu7Ko9SwQkjmy0PZugLZeQlUMQJyFtJ6jthLSNYEjERzYVwFJBbMqPZYUfQ7XYgpVYwWoptR5ZYpNUlENiHJHzAtimQZeHkzoMYMQbnUowFOTOmXc2vrYpGxN6T6BXVqLd63cbvqOktqRxu3u+uYebDryJE3Y5gXnr1lK2DWqqYd6Hf+bgZ8QGb8gQuXHl54sVut0uN2u/H87y/5ngCh8erzQywdGLqVkoN3G/H044QWokut1tu6kv3rwyLmhjt+wpTQY3defYVLMpYZJgWEHrd+ERPUbw3cbvGl+vrFzJYWvsBP0yMeAKBvjjv+6G6rtbPM5w4I+HwOzGMu4BRn/wEITFG4FQgFNePYVpy6fhDXpxWk6u3fdaJvadyIItC5i+YjrV3moOfPpAbj/kdv4y+S8tfl5Ih3hp1Uz+8sENjY4oDjR909P5+/43cNrY87A7s6M3J8Cx5QuOcN/FEUd8DEc5YfC5+IpPpqRuOBu25FFVHmLb5kBYuKMJBBR2u8bhULK4HAweGGT/idvQxeMp2ryZi4CLgCAWG+jLugX9ZaE/q+nPElz4cWIngAsvRZSyO2uQLdahV8xDNec1nizjublM51QDuS2wKawjyHRKpM4X9KU8kdgvpx8bazZit+yEdKhRENRtWP1f+P534ewuJYG/gknRCWhbkllUZcn6mPfKrBwRSQUkYJuqRXKBuwBbTMNoUzY21WxieIFROxqaYcwNYgv95Yng2xbt1OogrHoaVj0jHc8h58vfckb/cPBbSf0+lUTQEWiI78gl44QS2PAmrH1FHI185TKx9dmRQFDETrm7Qd54yBwk2bmuHuDMlc8FuU8dvw6wwuehwV8Lvgp4O77tqve6eezT3/HpSzLRt3mzDNLy8uD442UiZs89RWyRnS1trJ5ehEpyvwv1LOKf/4y+jr2FxtYD9Pmgthb0f5Ifp6tZWgB1SeYIbcrGkPyOiTeyXFnYLXvS+tM1vhrq/fWkO4znbzKKiuCTTySrvK6ubcYi6emStXDccfJ6TeUaXDZXXEmxxs/pYGkcm2Ujy5lFlbcq4T2/qwRLS8ZJLKWl0YDEDqxUZPiFce+9Min83/8mTsLbbFIC8J13kmevNEt6H5j0JHxzTtsy9m3psOejMOgMCVT8+CcRSQbrYM7V4lgx/l7IGiZtqT2jXU4cLoePL26YwknPrWHJErmXrFghAbKHHxZbdq9Xrr2t/4uhkIw7U3Y69QObw0tb2W23Zp2arrpKfr8bbmibO0Z6Ojz/PPzqV61ve+GFYjP76qupfYZS0KOHiOq7PHMMKK0tTXp/L0hvm3gj352f4ODhD/q32zjq+eelnxXrOrVlC0yYIL/vlVdKAkJWClrz+nr5HV59FS65RPpZrdL7CNjzYZh1UaOQPim2dOlnHvKlPDZHxgAps/rRvlIPvUN1tX82jWWR1roEQGtdopRKNnDtA8QWkN8ATGxl/z7At032iZXsPKWUCgKvA7dq/TOyazPEMbZ4LA6bo1G8YbfZGVs0dgeflcFgMBi6Eq1FkPHNN1Lu8MsvRaRRWysxO7s9PoEqwoABUsa1Xz/o318SYPv2lfLEPXpIn9PlkthdKBQpc28jFCogFIrvZ8fG+2Kfx/Y4mvY+IiWPbTb5jMicn9crrvplZSIyWb9ekm/XrevasUXv3pJE9NprcMUVUrIrpT50O8jMlPHYLbdIYsEOiwtlDoJDv5aEjLnXQkNJYvnuzsCeIeKFUX+F4ZeI0DsVdAgqZsPG9ySRsWalxORt6YCCkKeZMUYIMgZB1nAZk2QOlthCRn8Zv9gyxP3DskPIL4sOotBh8YCKccWEpjG9qFOmDj+NGTcpmyxW2Dox5IVAvSS8NJRC7UoRntStk+dGuBFHp4g3mqtBGfO+Cr9/JFAPnKu1/qmlfdtZv3IPJOnVDUwD/rg9B2KP/PgI5Z7yxtc90nvw1XlfJXWF+H7j9xz4zIHU++sJ6AD/+uZfnLf7Bcy8/DnKyiTAMHUqvPO5PHc4ZMKouZvXuHFH8WeOAmTip6EBZp0qgfr6enFR2HNPUa4NGSJKtpZuhIGAHOedmSsJBKOTLCEdSk28kTcIu7ITCGeVaK0prYkGehSKUYWjWj3OqMJRcRM91d5q3p2Wj7W57amnd3zcZEWRpJeV15cz4qERlNWXRd9T8I+ZUTeJiPDEG/Jy+YeX8+nqT3n3jHcTPiMUCvHoj49y+5e3s6V+C/6gn7y0PC7a8yIe//Fx1taXcf6H13LFjDu5Yp8r+Mukv2BFfohZF0PVQnlesAdMuB+nDjFAWQwYEfmEGI/YSHadF1lqkcy0tUCTeJ2NEANYxwDWpf6FQYvB0TbR0jFSFIEM0JrXbz6d6pdeblx33K03grflcjQAT+TBV/2irwf96jet7rNdWf9aNMjvKoCig1suB9BMZmWJF5zB6M/vtDlTyrJrGswN6dB2yarrznSXdq1bUzABjl0Bq56FBTeL+CFYH7U/3/yZLCCTTNm7irgiZ7QoiyMijmC9dNxqVkDFnJY/03JQ3+Nk1tWfzOYQVG3Zhq1mPmne+eSEZpNetoEM+ywyHdPJcFThtNUR1E6CIScaK9xhDCt7QwHJfNQBFBqb5cOu4v/1Ppo/lT8/f1/cKdTXSw3If/+7mXNs5n5nAbmtfqnS1qelNX+cZmmtPlqK3aE5Lx6DXpbYvrkdbvpl90uyR9soTC9kffX6hPVuu5sV5SvYraj52o6/dEaPlqyHQw4Rp5dUSqi43TJJ/bvfRdetqVzTbPmajpbGAWlTkok3MkZ8y9/u38C9N/ejqio68H/nHTj4YCnxduih0od1ODrHiSMQkAlqUzvzF0ooKBkntauhbq0I/rzl4N2CzbOVx04u56D8vbnmqcsoq8rDbg/g8Tk5dPy3/OeSO+nr88NXBeAqhLSe4MiFEZe2/Jn9T4J1r8KGtyV40hqWC3odKsINgEFnyjFWPy/lRcq+grJv4cPJEvDoMQny9wgHWwaCuxc486VtO3ZVuA0OiSjRsxmmj4/7uIGFa/n+exFr3HuvBAD9fmnXLrxQ/gePPhrGjZPAZU6OiFyCwWgzopQECtPSxMVg/Xr48Ud49114K9W2q7k2qxOG7pdfLkHWCy5IrTRORga89x5MmZL6Zzz2GMydK2Ps1u7FGRkS+MzNTf34HWFt5doEkWRIh9rsrFTgLkA3KVnTEGhgY83GDp9jKrjd8PHHMGkSbNoUzT4MBKTM1oMPSqzj3HMlzuHxRAPekZrLLhcsXSqOKq+/Ln+rLaG1ZFxu3izGkV7vOTgz9mJU7e/I0bOx8GEhP3iADECzyn4Fa93XYH3jJitLxJbNljVwF8PhP8DnR0PlnLZn9NkzIHMoHNj9hwkRlFIfA8VJ3rou1UMkWdfajaKlfX6ttd6olMpCxBtnAc8mHECp3wG/A+jfv3+Kp2robozpOYYGf1RlV++vZ3TP0TvwjAwGg8HQVSxeLEkrH30kc1p2u4jLY4l1kBgxAk4+WcY/48bJuCDiauF202JpEsvaPg6fLpcs2dkiJNl9d1nv93esVGSqKCXf0YknwltvwTXXSL+8vl762h09dkaGjDdvvx1OP73l73y7oRT0PxH6nQCb3oc514ibhQ61nnDYIjYRadjSYMzfJNkxmWNfU0JB2PA/SWIs/SB8Hr54kUZT58+0Iuh1OPQ/BXrsJXGMYL0MdmxpyZOEG0/T1fL7HcWyh5MrC0VEUri3xOeDDdu/XM1OQIdvM63UoIxwBDAsvEwEHgYmdkH9yoeRAda3iHjjcOD9jl5jKpQ3lHPtx9dS55dWIN2RzlX7XNVsOY+9+uzFkLwhzN8yHxBxwGXTL8Nm+19jzCqShRh5niqRbQ85RNRxv/613FSXLJHGaOpUOOkkaZx69ZIGLZLt6HLBsmViUfrSSzC7x1LYJxr18ga8KYk3emf1Js2RRq1PIvNOm5MQIQL+QOP3k4prwqDcQaQ70htLXqQ70pn1/etMLOgH9RuhYVN4wtArN9CRVyQeZNHdRLNTwpZAlhMsB2UL72efD++ME27YLTuOJtlsafY0GvwNjQGsacun8ft3fs9/jvpP42/87fpvmfxkYkmVCk8Ft38ZLc/iC/rYXL+ZKz+6kis/upLpv57OYUMPgwPeCwdqX4Lyn+Cj/aDvcZA3Hu3uDWmF4clOUay1OE33H+CMJH80WidX7fhracxCV1bUsshbDps+gJrl8l0HfeH9m1H+LLkPUdnpaMZgKBi2hlXgygN3H8gbKxO4Vuq3IKUUx930Etz0UksbJV4vMDi8dFt2vQpKPpS/YW8ZzL8RRl4rv0MbGsxNgfBXEP7pbZYtpSy7AndBXJDXE/CwqWZTW6/iZ0M3a9e6N5YDhp4PQ86DLV/I/Wv9G9FgdDD8GPJD5TxZ2sFXS/fmjvf+xuyrJKDudsutaN99CzjttAPYY/IB9O4tau2IjaA3AJ5QEOUrR/nLIORH6WBYrBEU/bCyoZUNLBfa2QPtyENZFna7DBoOPxHePRi+/x5mfK5ZvERTUaF4+mlYtTLE+D3Epr1vX0VBviIrW9T46engcilCoWhbrnX8xJdlRR9DIU19vQwka2qgukqzx4QdIzVfWrY06fpQKEAfamHr13KvCvpA+6P3d8IuJhqiNT1jUAo09Ha5STZ34g96WL7qLXazNYQHC26wZ4aXjDa1Fz9nRo2CBQvg/PPFOt7jSd5HzMgQR5hnn4V9941/b3Xl6rhAdiwDcwd2+ByLM4pZVbEqYb2lLHY9YD7rzu/HBx/A44/D11/L5O+SJdI31Rr22EOCEnvuKQGVwkKZ9MzJiWafNP1/soVLytXXy8Tbtm0SVPjhB5lgff31Dl+WYWehcj6sfAI2vivCDeWAnJFQuI/0PfPHQ3p/CWjY3Zw21captwdZuiREVZWdYcMU+QX7gdpf2i5fpfSB69ZA1WIJliRzj4pl4v9Jm+jZTKtzjI5smPRU/DpbGgz9rSw6BNVLYdv3UL0M6lZB6Sd4VjxBoKGUdOR8VHhp7IfrYPi+aRGX+ZJWhGWJ+8All0iQ8733xBVi7lx45x3Nxx9pUBqPR+ox9+snbZvDIYf2+yX7a8MGsNlCuFwara1wALEVIWFXokONWTxnHFPPoLecXH1jAT/MTsMfUAQC0XNzOkNYCg49uI47btrGrruGoCFDLGJTyHxyucQN6fzzJUCcTCSSni73r1dfhV13TXy/q0hWhswf8rerbEowlNgVTXZ/7yp69pS/y9NOgxkz4gPuZWVS+uiJJ6R92HdfaSsyMiSYXV0tzqPJ9ESBgLw3fTr89JM40GzbBoMGiRPNwIFSWqVfP8juuSsb+n5Bpe97smun4fbMI2SlU5t5EJXuo/BaxbjrpM2ZM0ce77qrhUQZZy5M/VKCsLMulnF4sK6ZjcPY0qVvtMeDMPD01u9B3Qit9SHNvaeU2qyU6hV2zegFJMvQ2QDEqof7ApGBanP7N7uP1npj+LFGKfUCUk4lQbyhtX4MeAxgwoQJxpljJyXLlUWeO6+xtHWP9B5kODN28FkZDAaDobOZOVMSQiKlRVrj3HNFjK21OODubDgc21foYFniUHj88eJk8uKLMsbxemVe0ZeioZzdLvFcpUSEfcYZMk+5PdwJ24xS6N5HUJk/mYot31FU8RXp619D1a0Bm1PmvVp00rOBI0PmxRyZIqQYcJokY6Tal69dBV/8Sh5TcQDJGg6Tn4O83SSW4YixKLSyU/vMHYFlBysFO8VfIJ0RCW+pBmWE44Bnwy4Y3yqlcsODq4Et7Num+pVKqTVAttb6m/CxngWOZzuJN67++OqEGt+/Hf/bFve5YcoNnP/2+dT4agiEAnyy5kOmffwFrtIpvP662DsNHy5BhJEjxTFj+HApm2K3S+MSCWL7fBLAX7sWli+XDJPXX4cjjoCVK+Hvf4dHH5X9PvpIFpAAR2GhBKAaGiT7KhJ8siywnTWf2DYvpDXffi7pi5HJKMtKnDjYUN0Hnz+6Z4Pfg03F/LmF7Hg3D6K6WtSDzTEoL97CvofyM3HmfuETTINxd8KIP0Q3KLoTYl05inqKki2CUiLcsKWxonwF+z+1P1vrtwIi0JgyYArTzpiWVHRTWlvK2EfGsrVuKxrN8/OfZ03VGu485E6u/eRaPl39aeO2dmXnyGFHM7rHmMZ5rMhXtLx8GW8v/x+BkB+N5rgXj2OvPpO477AHGDfqOrYM/C23f3EbMxa/jW3OjeToBnrbIUOBQ4FdSZlom4KgVricmeSnF3JZ2mbskcCPssP748FfAyP+CAV7RUUZPXvAlhiXkZ6FEpiOZOoFvaLG2zQN5oYTYiwnHDkPssMWICEfFD0dXwqlqEhqdevILGVALlw5oBkRU5tZ85IEz33lUmKhx0RpLCPZ9E3Z8DaNk4ihYLRh1UHZvmaFqBNdPaSm17CLpAHuIN6AlypvFcl8X0M6lGBBTOFkOGo+fPdbmRhdcp8oKgedBX2Pl+xKkPNHw9FLovtaTnhFAhAlAQjE/C8qVMrOG/5gNG3QH/KzrqqNLi0/L7pFu0Y3rMv89dcS5A4Gpc3weERs0L+/Ij9/f4LB/QmF/kOetYhCaxb5ag6F1vdkqyU4qCWIG93sxI7Gwo9CU8MQtoXGUxaaQIXejbu/2o+Pf7ThdMpnR9TzZ54pAf1QSNpBpaRtjA6+bEBheGk7wYZKjqrK46gRQMQByXJSY42hYtIPVFbKRHFFhdgWVlRAQ32IYCBIMBiSupQBEWeEQoqQDsscLLBsGrtNiYjDUtjsFg6nndxcyM1VjB4jbXNTQqEQVd4qan211PpqqffXs61+G4e2ci0/bvqRDGcGmc5MMhwZ5Lhyos5PMVzcqy9fepcnrM8qnsgeI84AV8c61FcfGOL5ec8nrLeUxYRdz4bc5tJVf37M2zyPnzbNotZTRY2vilpvDU/Mex6P34Mn6CMYChBoTsM1DigaB19dCasOBV8mqBBoBX1m4ZnwJFvHvc6vvrZzdMmBDMntT6YjgyxnJp+ueK/RGS0Wp83ZKc4bzR3DG/Ty0cqPCIWC1Pet4Zjr6uhbOptPFy6iYu0A1IaBNKwdw/eb+vDtsgIefiYPvNkQsoHdC1aA9HRNRobCZpMBfkhDMKgI+KGqCnTQQgedELTjcgfIzPKRk+cH8jp8XYadgM+PEsenUEDEZY4cmSTNHALoaPmsJijLxi4jk/RVLYeIp9MKRXjc++jUAi2ObDj4U/jscPBsSe7AYUuT/ucB77dcakFZkLMr5OyK1poZa2dwzcfXMG9zBQ2BEBaQaXfQO6Mnfz/gBn6160nYbWkxTlPNtLm1a6DsW3b1/Miu42ZzxdAV4N1Clbc3a+r2YXXVONZsG8qStb0or8rA63fg9TtQFjjtflzFPo6cWMeI/iUMLFjGoJzZDMycCbqLrU4r58OGd8QutmaZjAnyxkH+BHD3hvS+8n06spg82c4Xn1SxZGk9d9+fwQ+zHdTWKrKzQxy0v58/XlxH374BCGoRfTSUinC9z1Gtu1kBBQXw5pvw9tvwpz/JONrlkn6KZcGll0r2X7K2vCvZULMhYZ034CXP3bb7YL47H28wMbssmXtWV5KVJa4uL70Ef/6zuDY1rbtdVSUipFRwuUTs63RKXzYQgIsuEke1iCNUWlrTQL5CtNoTG9dkI4rrWEKhqAMIiIBkzRoRdJSVST+xvBwqKhT19Sfgsh/Jfn2fZ2z+KwzO/JKgdqC17KxUCJvys7ZuEnMrTmbmhrOp+zCT9HSJ4dx0U2rX2815GzgHuCP8+FaSbWYBw5RSg4CNiOD9jFb2fxt4QSl1D/IzDQO+V0rZgVytdZlSygEcDTT1ZzX8zBjdc3RjrG5MzzE7+GwMBoPB0BVkZEh8QKnUxBsRJ9NgUObKduryrYF68G6TZFBvmTz3V4mTQcTp2F8jSXZBD1ICQ0PEnVhZ4bkbe/i92MReuwiILQdYDpRyMqWnYsof4T+XWfy0qJDPvuvHT4t6Mm9ZAas3ZOPx2rFZkjwQDCmcjhADetcwevg29hi1hSkTNjJpt1JstiCgYVl4DinkjzpKhAIyd6ODUXdnHYC9HumUryykQ2yt20pJbQklNSWU1JawqWYTqytXs7ZyLSsrViYVxAP0ssHUvEwmZhcyzhlikKonXQVxAJbNiWVPx5a9C1bBXuFx/CjI3iWl8WUCc6+X8W+rpnNhprwJ2cPDycApuHoYuj2dId5oqQZlS9v0aWXfttav9IefN13f5VR6KnnipyexazdOXGjl54C8s5nxYTZ+vwQEItm1EP1f1aFfQfBi3Jas8AU8DP7jofR728ukmOPrdVAxI48N9KUBN34c1OOgCgdBbDjx4cCPGz9j8HMgZfSxbYB100FVk+fZzL0X1HHdSel88m1fPpg5kI++GcTWCjc6GGRLKXIPUOCwwGG3M7hfFUfsu5JF7MeHc6L1z++8ancOn9z6zWaKbyKbPj6PGp/MsP20fjELy+Zi19mgwUM9BdZg5syJ7pOsoaz2D6be10CGTRQeFT4Pc4KDGO5QbN0aYt2HG9jw+WJKynJZV5JNxWEbyMiwYVlSh0nXb4JzVqC0H6V9+L0ePFWVFGau5N+73YHXUYddZ+BQLgqsfpwceoPnn7OhlAR2IhZY8psVc22vT7l21SQUFqGA5sOVH/Lhu+kwPDLmdzC+7xheO/m1BOFJLCU1JZz22ml8s+EbQoT4duPXHPvyke2wodVADVDD5eE1e7pgljcAzKbAgsElj7P/oLXs1WcvhhcMx5r3adwRvEseZN4zffnGA181wHq/VGDpZ4fLc+HAdOhv95E951p0vxMhawjK1RO1doHUxFLh3tGCW1AvJP/b8GsRngAw8CzYOyG5JTW+Pj36vOcU2PPB+PeLrogKSoqKxMFkwc0Jh8n/ancqes5J8gF/AhKbRHVz8uva3zuIGa7VzZ5uSQYUxwQXSzOg199bDmgX2uDIdC9HZSxj/LYbKJ5zA04FDY48VPoAlDNXOk06iA7UoevWkaXlJ6gOQZ3fBX5poGuppzgzmUttPDmuHFDhR8Qd5oHvH+CB7x+IblRXgLOuN1P36U9iQQU46JmDWF+1nvXV6+MCvXccfAdX73t1q+fQzegu7Vq3Y+qzU6nvFRPjVECGnXxvNkM8QxiSN4TCjEJ6pvekMKOQbNdElJIWzRGsI8O3FVvIj0378ftqqPJWsM1bR5mnhnV1W/hx23oW1VfjDS4EFgLPyefso1j87xBz5kgm/aJFMklyxRUyMTJihFgI9u4tjlIFBSJ0zMmJunRErLQjWfoRS+3YJZK1X14uQfZtpXaO6Q95NsldzlDg1j4y7OvIyF1K33xXdFBjOVBWzKDGis7W6EiJink3oRbe0voXHQD3P8HThjy/pvebWEozYML/TUjpOEfMuZ5LhqZhWSHSnQ1kpdWQkVbH4EEjcJR9KRtF6hVGBnE2l1j/q8hgT0UnOJfcB0vvazz+r8JLUz4v6cfA+wemdrFhWvp6mrtvJ+Wm5Efq6sJ7JzwxlpUplD5plt6z4eQz5ItoyANtg7RKsAUIArVBqG2Apxe9EbdbH18ubldMuxzGo4MMzuu4T9XIwpG4bC5c9vgZS0/Aw33f3cd9392XuFNEYzUuyQH9aVBXCPWF1AfSqA/ZIGSX61UhUEGwgmAFIK0CMrZCWgUeS+MByoAqTyU5aaZ2ys+emuWAEuEGiFgjd4wEqxwpCM+aKUsXjwVnBAkEZCK2okIEhbW1stTUyISw3b4rdrWISVxAP/UmEMKuvAS1C43FBv9RfOt/Cv87mQSDMlmcmSklS5qitWb6iulc88k1rCxfSZ2/jnRHOpP6TKJ/Tn/eWfYOS6rWc977f+GyT27klgNv4eyxZ+NMFiBa+6r0jWtXSpAu2AB9j4XJT0P+BHIsO2ODHsaiJOBjOZoXrEQsW4NTAC2OSWHhRjAIq1ZJEsH69dJmr1kjbh2VlfB9M9/uOedES7RE2uaIUNLphH8cczv79hUXvhA2FEHU8U3EBKFwIDAceNxld/i/iLlJ7G88K7w05XXgjSTrm+HY8LKevqz1DCCbakazAOt2Dbcn2aGmRn7sLmJLbaJ5gcvuwt5GB6sMRwbJKtDuiNKKSomV8kkniWvTXXeJo0YoFC2n0hIOh/z9ZGTAscfCU0/JWD9yeZG64pHElPYG8COJNWedJTXWI25xAwdKDe/99oPiYtnO54NAIA2tfwv8lrqQH1vNAlSgErRGO3LwZI2hh+XkYOAQFU3gibhPtScG3M24A3hFKXU+sA44GUAp1RspPXmk1jqglLoU+ABRZT+ptV7Y0v5a64VKqVcQ8XwAuERrHVRKZQAfhIUbNkS48X/b62INO4Z9+u3TKN7Yp98+O/hsDAaDwdAVjBsnCc333CPlPVaskD6Y15u8r/jOO9C/Pxx+OBxwABx4oJS983qjpVMSxbzdg0gCt2PJ33Cv+Hv8mxERvw6J8CEUoNGF8cAPodfUxAOG/OHtYupkxsX1bOEYYPx8hgL22BX2ODG6TuuIE4cNraW/7XRaKJWHJNQMbf7CQrFijVBUtNF4PlarHWB/0M/X67/mx5IfWVm+knXV69hYvZEKTwV1vjoaAg14A178odYDcQpFvjufvLQ8bJYNrTXlnnI2N5TzbFkZz5aVtbD3CuzWdFw2F26HmwxHBnlpefTK6kX/nP4MyRvC7sW7M2XAlIS4WRx9j4cNb0qidaybZnMse0gS3SElN8kOkVLspD1IvMUgqGQD8jYdQKmTgcO0jDpRSp0F7KW1/kPMNu8B/9Bazwy//gS4CqlkkHRfpVSl1jo35hgVWus8pdRDwDda6+fD659ASqSsC3/GIeH1+wFXaa2PSXLOsfUr91i7dm2HvgOAoZMfZUjfeeRllLPbiG38cepYMlzZ4QkNp9QWsjnDAa2wV7oOsrKqhIUVa0T9pv1M9K+kyLtOAmH2LNjnv7J95Aa5yyGwZZs871kA75wEKx5t+eRchXBikyCO1mzerFmxQiarvJ+fg5tNZLjqGNV3IVnu2shmlNX0oNaTSb0vnYa93iOUPpBgUEQpE48rxlkR/Uf15eTxzY1noYhRxQV9rC63c+6b0Wjkvbf14E8n7p3Sd/vdhu/YXCefUV9r55PHD+TtN9xUVcE+e2suvEhq4RYVyc3b6426gsQSEdCkpcm5p+/yJbgrALHo/ujx/VLKSFq2bRlLyqLOB47KUThqhshPqmXCMBJwDAZh/FHFOMvl/H35Rfz4btS7NdLeWBYsqf6Rre4vGVowCKUUuWm5TOwzMXoTLy5OcLrQJSWsrFjJoq1iCFDlqWJlxUo+X/M5P5X8SI0vBUulJBTbYA8X2G1OVrlHsKRsCYGQnxwL8m2QZ0GmJREPu5JHmzjiE9AQBF4ulm0BVvotspwZhLRG9dyP/IkPNja49qGTUDFOIDo/HfVg8gLVe960iDmrhpLtrmaPMVV8OK0+rCSN1PqK1AyJRLQIr1Mw80QpsQNcN38Kb9cUYtN2Kl3rKR6QidOWhtNy4VAuXrjmdfKqxVK+PDuNU247HH+gFp/2EdRBhqaPIKD95G5zUK6/JcvmwqP99Bo8nAH5Aylw5ZDtzCDT7kaFf2RfKEDdxjep3fIpJQHYGIAeNqjXIm75usSBv8LP5gwozZTkaY08plsw0AZFdplscyrJNg5oqAiALgNdB7YQHL30UPbZ8CEAOV4Yn2J8dUkPKImJI7902hhqh9vw1qzBFaikh8NF78xiemcWcsrv5uGqjDoN+fLS+OnVEwjpEAEdIhj0YREioGF44Sj65fSXLNS0Yqn1nDEI7O7UTiwGpdSPWuvUZqA7QHdp17TWcUb/XdF2tZXXFr3GC/NfoKSmlI3Vm9hcV4qvQzX/kqOwyHMW0cPVi0JXb0bnT+ShRQFstyaKsSL4sVNFTuPiDwscQ1gEsTUukdeRNRahmHfltQtv45FuefsMPCpIUAcJ6RDrqtaxctsSXARxEMRJECchXOHFhjRACo3T5iAUCmBTFnbLhsOyS/uARrbQKGw8kltGjhXfEX+6Pptlgy5pdMpIs6fhDXjJT88nPy2fnLQcclw5ZLuySbOnNd5rkqG1piHQQLW3mipvFdWeasobytnWsI10Rzr1/vpGJ49egcn0rj02YTyUmSlimNhSFZHnexxdhLNiS+PtFgALfPk9mf36anSk34NCY6GUQuvwxuEPKqup5m8zr0ErPyEChPBTxhKqrbVY9iA6/P2HkEdNiPV3+pMKVkozoP9VLixlYWFDKSv83E6+s5ihmWOxKTt25cCm7Kh5PamqsaPCA8MGHWBjQx0nHDAJt8sZ/ptUjdd87eXnkFVdmfC5Ndm5/OPOx0DL/0RsN8RC7vmxY+Gz5n5O4etPSCMaHhPLhj0gMwsc4VogdjvYLFmssOVE5HuO/FBDN8Cw1ASg87f0ZfUiN4Mr4h1WbEUD2GX8yeGmM/JjxlxFcwNl+1dg+7rxpV/D0mbcI4fn7oLzwFejWRShgPQVrTSiA3TkcxufNzmPCCsfh1VPpnLJULgfTP0itW07me3VdoU/63DgfuSv6XGt9R1N3lfh948E6oFztdY/tbSvUiofeBlxlloDnKK1rgi/dy1wPtL1u0xr/UFL5zdhwgT9ww8/dMq1JsVXBetfk6BF5TwpNWDPkHqvvQ+D3LHg7iXlmIKesEtcDO+MAG8y137hzR+O44LH/w8vhdTVSTDv1lvhvPPkX8PhkABVZGK2cTxSswJ7yRuo+rXo9P4Eep0AWcMaxyaRyViPR0ptRP7NAqEA1358LQ/NeghvwEsoHLCxlMXA3IEUpourVI2vhuXblhMIBdDo8P3O4pgRx/D4MY+Tn54vByz/CabvSVzgZ5c/w7h/peYokgLTp8PDD8PHH0e/k6OOEpvdPfcUbbVlga1vMdaW+GBPqGcRNctknBQ7jot11aqsCJJlrcHZsBhqV+Gt20hp+WICyobdcmCzu7EsB05HJjZHFpYtXUrKWDYsZSd9wY2opjWBE1BwRgrBsWT3wzbEVrQWUcqWLSIaraqKLtXVcMWVydv1u/8ln2G3yymEQjK2tSxppy/a6Mav491eCtML2XJl83/bzZFzR05j+dII2a5sqq6pSti2ylPF/C3zmVs6l5nrZnLvuS8ltNFl2XYefPOvjOs1jrFFYxmQOyDRkTAFNlRv4PWZc3n+RS8/fJUDZbug6oqxO8BuWWit8PtFzDtsmIgmTjlFSnIpJf+fX38N778Ps2eLyKiiQkqm7LqrBPP79tX06aspLASHQ+OwK+x2hd0OWisCARqX+noRKK1fL8d6IKx/z8gQl5CDDpIyOxB1j4vcL1IVYIRCUcdVEEeSrmR7tl3dnS5vuwxdyhuL3+DEV2Rm6c1T3+S4XY7bwWdkMBi6CjPuiueX3H55POIa/PXXIqhdtUqEv1VVIuqw26N9K69X+uUOhySE9esnfcFevaSM3oAB0SQxt1vmldLSokm/kTmySIJYbInXllAqOldlt9PoLhoIyDl5PLLU14tTSEmJCFQ2bpTnub6Z/OeP98mconerOG74qsRhXIfESUOFhRco6Pcr6HeixOftGeGxcroIPmxpMn+pwvtY9rAgPhgVgujwfAuQND4Te9EL/wGL/9nRnzGB2f40Vu75HCU1JWyo3sDqytWsq1pHaW0p2xq2UdvOebAdiduWTo6rgMK0Ynpn9qN/9iD6ZfejV2YvBuUNYHJuDmkL/4ja+gXKcobLp7QwVk3vL791/1OlZGywIezEkdG5FjNdJt4AzujiTLpuRkttV2eINyYDN2mtDwu/vhZAa/2PmG0eBT7XWr8Yfr0UsY4f2Ny+kW1i6ld+rrUe0fT4SqkPgJuQRu0zrfUu4fWnh/f/fUvn32kNWazjwC5XwPi7Wt5+3k1JHQEo3B+mft7x86leCuvfgLp1UL9BLHOcPcCZI5lnEy+DrZXhz8yD/yixnU1KCwGsVINW9Zvg0f6SHamACVfDqPPCDUJEyRdzLBWeuY6bNAjx3vQ0jj6lFxGrkK+/hsmTW/4qWkJrCahEsuQijaPPB+OOjBdd/PBOqdjbR+easNthzJhW6ow1/Y5a+p9rKtBoL0VFjQV+y+vL+X7T98zfPJ/3lr/HjLUz4jY9ddSpTBkwhTE9x7Bnnz1Js7dsq1Trq2V1xWqWlC3hveXv4Q/6OXLYkYzqOYpBuYNMZuvPAX8NvBpTz2jMzTDmxuhrrUWZG9tZeGtgM4125ykmt6N4o1u0a5EyYMnojoMwrTW1vlpKa0spqS2htLaU5duWc/GxfyevKnEmt6Egh6++f41emb0oziwmz53XrgC+oQu46Sa4uXmhTJfxt7/9bHzADYYI27HtsgHLgKmIg9Ms4HSt9aKYbY4E/oAEEScC92utJ7a0r1LqTqBca32HUuoaIE9rfbVSaiTwIlLmqzeSwTxc6+Zq/WyntivSl7YDvcJnVoj4WWUBmUC2E3r0gcxccDrA5gi7Jtkg6Jc+TsAPHi94F4AlfffHPzuPCx5/ApDAncMhLgAnnxz9eL9f4/VG3CNan5WNuEG5XNHxRCAU4KUFL3HBOxfgCSQpudJG/nHwP7hkz0vIUiH4eIrUzA3WSyAudzfY+7+QOUhe2zOaF3LMuyn5+DX2en4dP86ZPFmCpp3lEvDC/Bf49Ru/7viBmsFpc+K93ivBykBN2GK4NiwW90jWkw5np/U9KvEAG94JP4mx3IyMaZVFRbWbv9y8C9/PzmbFahegGDFCc/fdiuJiRc+eUlLU5QLVuxjVZFwY6llE7fLSxkNHAr4R54iKmgaKH8gi2OTfcFj+MJb9YVmbv4/+9/ZPKJOiUCy6eBELty7kp5KfuH1mMnuRtnHo4EM5YdcT2K1oN8YUjSHTGVWU+wI+3lz6Ju8vf595m+exuGwxDYGGxIME7eJCFXSS6U5jZL8+jOu7K8eOOJbDhxyetFRchNLaUt5a8hZzS+fz/fKV/Lh8PdT1hKBLnJ5il6CD4uwiBuf3Z0B+H/boM5YRPYdgt8tvV1QkAf/ly+H772HJsgDfL9jKhk0B8nOcFPVIIz/HSU6mg/xcG0VFirQ0jd2uG/WaygpPAgREhOLxKLZs0VRWKurrJX7xzDMd/tpbxIg3onTHcZchdVaWr2Tog5Lpu/qPqxmYO3DHnpDBYOgyzLgrHtN+JeL3i/hh/XoZMm7eLEKIdevEIXDzZhFLRMpEe71R4WyknxZxaYv0xV0uGRu63SLEdzrj++mRx4iwI1bg4fNJv87jiX4mxLsQRsTCIMd2uUQ84nbD6nNuSh67swFOwAU4ws+dyBg5drE1ee2IWZcWtq6zu8DhBLszPOhQ4bm8mEeVZJ0VzjwNRS5GRy88FPMY0rDHanC2Lp7f86exrHAF8Qf9BAmIrkQ3WYjqTAoLHBQ5BtPHOZI+acPpmzmIATmDGJDTn6wMB87wJUV+28bcKVv8bw3x84HNPUZ+u0AowMaaDaypXM3qylWsqlzB4m0LWVW5El/QGzflGXkemS7UGmzKjk056OUazMe/fUvKcAZ9sHUmbHhL3Dg8JeJ8qbUIeJIJOmzpUv41axhk7yrPMwdJcq09S8a4Ohg9mYjYJ+wo3SnooMRYXmlDEq8Rb0Tf6wTxhh1pdA5GalDOAs6IsTJEKXUUcCnRBusBrfVeLe2rlLoL2BbTYOVrra9SSo0CXiDaYH0CDAvbIM5CGsbvEDeOB7XW01o6/05ryCrmwLZZ0FAiYglXT3HdiFiKO3LDtrO2qFAhYgWk/aKMC/lg2EXg6Dob1UbaIijojEmcIuCemNf7vgL9T25u62aDg1rDx+v/wn+X3M0XX0iGzJFHwv77i21+cbEkrDqdUcVirCV+Q4NY4W/aBIfM7ITrAvnwGTNa3y4VIuk5HSVGvJGMUCiEUqrFTG3DL5hQgAVvPMSPP/hZv9HJ2sphZPfbnbTMDNIy0khzW+TkWrjC/2eWTaGDXnQwRDCo8XpDVJYH8NQ34KmuxuvahZoaUSv37Qt77SVZbW1lOw7Euk271tw57lSDsJbuM11dl8JgMBh2MEZ4GKWr267NtZvJGzwS59bmBOkdY2MWPL93JusvPY8Va+v5culC6qtd4MsEXybOUC6ZVgGZjlyy0tJwO51YiOODhQ2bZScYCoQdhOTRoVxkOwpwOeykuWH/Y9Zzy1c3UtlQiSco0Tun5cTtcHP7Qbdz4KADWzzHJWVLuOLDKyipLWmc4HbZXNgsG5dPvpw/T/wTeXVLxbVmywyoWwPKKfV488ZBzkjIGi5BHXcvGctGgjjhkihR55wgvBJvx/r+nMN5ZOn7zTpvFIer+UUELrE0DXrFro84b7z401tc/t6vGbKhjsHl0KcaXEHYpQx22wxDy8HeStei2gnze8K8YnFqqnXB6lxYlQ/9M2Ha2CY7jL9HHEqaksQVsaXxF8DixTBypDzPyJAA8sEHw7RwxMLnk+8m8t1Fgr8tEQxGSnBAlbeSEQ8X4AtFg3caOHaXX/HGqW2oBRPmyP8eyYcrP4wbM+rqHgQzE6+zML2QUYWj2KXHLgzJH0KGIyPxXHWQjdUbWV6+nPlb5rNsW3JBySdnf8KMNTN45OMP2OL8rs3n3RSFYkq/yRw++GD27bc3Lns6P22ey4x1M3l3+bR2u1XGctCggzh40MFM7DORqc9NRadam1oD2oKQTR61TawXrSCNZcFUKC7P5fChh/P+r9/v8Dm3hBFvRNmpxl2GBEI6hOPvDizLwne9z8TADIafMWbcFc8vrv3qoiQkDfhxUEcGdWRQT3rS5xGnX40ihJXw3Ao/Ez/a+Oc2guGjyJJOfcJzJ0lKfbRSjlFrjSfgEQdebzXV3mrq/fV4A158QR++oA9v0Is34KXGV0OVR7ar8lRR6ankpVNebvP3ddE7F5Ltym50C850ZuKyuxpL6zotJ067k0xnJlnOrMZtW0smhpbHRUpFhReR59XVzW/flKZltWMFIS2RzPm/tcSFiBAkIuyJXVLGVwHVy6V0bPUSqJgtyfyezRCsC5c0tYfFE+EEhFgsB7h7gzNf3Fgc2ZLwb488zwFXAbjywZkHKlxONTK3HXF00SEgHBsg7NLir5Hz824Ts4BADSx9IPVrM+KNRtpW+DQJzdWgVEpdGH7/EURIcSSwArGK+k1L+4YP3ab6leF9LgKeBtzA++Fl+5C3uyzdiba4OLR0Rykq6poJtlBAFF6B+nDJi4hFtoZBZ8LgsyFS0wqpWaxsbqY685gaPl2txfJq0yZZZs+WwJXfH32M3LAjSjqnUy4pcP1N2H+hGb4tZR4ZDGXldsac/MfG1/ffD5ddFn0/eSckvpMl2+QhWoSdi27WrhkMBoPBkAp9gNgU+Q2IuLC1bfq0sm+R1roEIBxI7BlzrG+THCuOJiW/2nA5bWfK01NYdknrwo2Su0go51CaAb2uTOVTauHHcOChQBaXHwrroWcdZPkg0wfptdG51qCCOifUOqHGBVsyYWs6hJJ0xz+cnkbAZcdus5Npk0DcKSNP4d7D7yXblZ24QxN2LdyVY0Ycw73f3MvtM28nEIqWhrn/u/s54/Vl5D0UE4SzgAI/FP0ABT9ABuJQkht+zEIysCwkeyqSyhQCfEj4OSYp54iJP3HEnTIOW71a6k2vXw8LF8J770lGW2WlZKXl50fLRkSCbEpFXEuiQbOKCllcLujd+zhWPF7besmIZOPgsLgiH9g/vCTgLefhJwqwK8i1ZOmz/BV6huxYaBz2dOyOLCy7G2v2c2BFypZJWp317W+xVj3R/O8D+KdNYcWgGcydK5l/GzdK6R2IltJwOETckZkZTUiw2aIBvWAwas3s90vctr4eAoFc3qvcgz33mCUbKlnSplwFVatoLInVmCZmNRnnK1h6Dyy7D4B3AM/g+Gt49vMjuPyhu7BUSErAacWTz2Rz1OHyh2DFHDLym8aLcXRMZpmW7DMd9ducv/A+Tnr+YPwatAsyNCh7OuP7TOCUkacwdchUCtwFzX7HACU1Jby/4n1eWfgKi8sWQ6COHzd8zewNX2MHLEvht2cT1EG01rjtbvpm9+WwIYex/8D9GVU4Stzg9t0HyrbFH7xHASXvv8ZX679i+orpzN08l6AO8v3G75m1cRYOy8FVtWMJzJtD32ooqgWblvvC0HIYWAnOhF5+uLZ3DHUOWJUni9cOXhuUZImIbMrL02H5TcatzGBIAUtZ5LvzsZRlhBsGg6Gz6Jbjrl88N93UJX0jRdi4QinyqGzbzl2YsHb7l7dz3d1dW0fvvozEcXNLlGbAIz8+0mXn89PvjmX3x96mklw8pDUuXlx4dBoef3gJr39OOQhgl7LaNic6zY12paHT3Khw7ZuA3UXQ7iLoSAO7A8thoew2LIcsMqAhLFhQaBWZqyRehREZ9MRaaGiZ61Th5wqNDj/X/iChQJCQP0QoEAR/AFvAi+X3yqPPw9K8RTx41ONt/p6cCvra6+hnh352KLJBjgX5NiiwQZ4F2Zaf7Ia1ZFlrybDArSBNSV0mv5bJidgxWntQgE2FzV9UsrmkJKQVdeATf350WLwBEHa3mNZk3SMxzzVwSar7htdvQzKXk+1zG3BbkvU/AKPbcu6GHYhlBytLVF3tRCnIzZUlksVkMBg6RkEBvPKK2FyvXAlvvy2B5fx8qfOXmwt5eRJcjliJaR0NJHu9Uru7ogLOPXdHX0376C7tWrejs0o7RWhLAC2FjFaDwWD4BZPshtp0rN3cNqns257PQ2v9GPAYSPZXK8fsEEsvXZrahn9LXFVMxwIT3Qm7ZefKfa7kyn2aUaP8+6WuPwc7DBsmyw6hvf0FVz4XXdyBv4TCyTCp5QCbHdgF2GWX9n9My3zfsd0n3CsLokJu6p9x0ZlwUdtjiDGoJs/jLXQP3OtStg0aH+0jai2ZYTZ3OHNsM9SUhJM+Yg4X+dlWPU3BmmcZDVyZiZRKasobdni9qsnK5eHl3y2f/rZtjBh8IAcA1zW3zd/+AB/Mbvk4rZABjAkvBoOhY/TL7mcSmAwGQ2fSLcddsH2F8784ioraFg8t6tpJ6ONGHIcn4MFlc5FmT2t0t4h97rQ5sVm2xn1cNhfpjnTSHem4He7oc7s7brtGbkxajKNZeiKT/7EEQgEa/A00BBqo99fHLb5gtMR2MBRsdALxBDx4A96E5zm7n4t69C3y2vRNtYH2xLy7MFZdWluK+5t8dFj0kezRE/Dw5bovJSe+yfub0GyMrNOiyND+xOMA4dch0lSIbAU5NgtXyIelwKYUlgI78mhDRXM7lCXVbxBhi0hUZPFjUaft1GGjHotRPcdSlFmEQqoBJHu85aBbcHbJt7lz0iniDUM3xUxyGQyGdqCU1G+PreHelFixRjAYtfqKZAaapBaDwWAwGLYrG4B+Ma/7AptS3MbZwr6blVK9Yux7t7Th8wwGg6FtOLKg92Ht37/4QNj7mZa3OaP9hzcYDDsfP/7+xx19CgaD4edFtx13bU/h/C+ObjbPNqrnKP7e8+87+jRaxWlz4rQ5ySFnR59K63Sz37g4s5h/Tv3njj4Nww7ESI8NBoPB0GYi5YhcLrG+drvlud1uhBs/a0pL4wv/bc+lm3WiDQaDoZsxCximlBqklHICpwFvN9nmbeBsJUwCqsLWvC3t+zZwTvj5OcBbMetPU0q5lFKDgGF0OOXfYDAYDAaDoXNRSpmSKQaDoTMx4y6DwWAwdDnGecNgMBgMBoPBYDAYdmK01gGl1KXAB0i1gye11guVUheG338EKel1JLACqAd+09K+4UPfAbyilDofWAecHN5noVLqFWARUhL1Eq11U5dUg8FgMBgMBoPBYPjZYMZdBoPBYNgeGPGGwWAwGAwGg8FgMOzkaK2nIYHC2HWPxDzXwCWp7htevw04uJl9bgNu68ApGwwGg8FgMBgMBsNOhRl3GQwGg6GrMWVTDAaDwWAwGAwGg8FgMBgMBoPBYDAYDAaDwWAwGHYgRrxhMBgMBoPBYDAYDAaDwWAwGAwGg8FgMBgMBoPBsAMx4g2DwWAwGAwGg8FgMBgMBoPBYDAYDAaDwWAwGAyGHYgRbxgMBoPBYDAYDAaDwWAwGAwGg8FgMBgMBoPBYDDsQIx4w2AwGAwGg8FgMBgMBoPBYDAYDAaDwWAwGAwGg2EHYsQbBoPBYDAYDAaDwWAwGAwGg8FgMBgMBoPBYDAYDDsQI94wGAwGg8FgMBgMBoPBYDAYDNsFpVS+UuojpdTy8GNeM9sdrpRaqpRaoZS6JpX9lVLXhrdfqpQ6LGa9Uyn1mFJqmVJqiVLqxK69SoPBYDAYDAaDwWBoO0a8YTAYDAaDwWAwGAwGg8FgMBi2F9cAn2ithwGfhF/HoZSyAQ8BRwAjgdOVUiNb2j/8/mnAKOBw4D/h4wBcB2zRWg8PH29GF12bwWAwGAwGg8FgMLQbI94wGAwGg8FgMBgMBoPBYDAYDNuL44Bnws+fAY5Pss1ewAqt9SqttQ94KbxfS/sfB7yktfZqrVcDK8LHATgP+AeA1jqktS7rtKsxGAwGg8FgMBgMhk7CiDcMBoPBYDAYDAaDwWAwGAwGw/aiSGtdAhB+7Jlkmz7A+pjXG8LrWto/6T5Kqdzw61uUUj8ppV5VShV1ypUYDAaDwWAwGAwGQyfSIfHG9q5RqZRKV0q9F65NuVApdUfM9ucqpbYqpeaEl9925NoMBoPBYDAYDAaDwWAwGAwGQ9tRSn2slFqQZDmu9b3lEEnW6XbuYwf6Al9prccD3wD/aua8f6eU+kEp9cPWrVtTPFWDwWAwGAwGg8Fg6Bw66ryxI2pU/ktrvQswDthHKXVEzMe9rLXePbw83sFrMxgMBoPBYDAYDAaDwWAwGAxtRGt9iNZ6dJLlLWCzUqoXQPhxS5JDbAD6xbzuC2wKP29u/+b22QbUA/8Lr38VGN/MeT+mtZ6gtZ5QWFjYxqs2GAwGg8FgMBgMho7RUfHGdq1RqbWu11p/BhA+1k/IQMxgMBgMBoPBYDAYDAaDwWAwdH/eBs4JPz8HeCvJNrOAYUqpQUopJ5Lk9XYr+78NnKaUcimlBgHDgO+11hp4BzggvN3BwKLOuxyDwWAwGAwGg8Fg6Bw6Kt7YrjUqYw8arld5DOLYEeFEpdQ8pdRrSqlYpX0cxgLRYDAYDAaDwWAwGAwGTDJOOgABAABJREFUg8Fg2CHcAUxVSi0HpoZfo5TqrZSaBqC1DgCXAh8Ai4FXtNYLW9o//P4riDBjOnCJ1joY3udq4Cal1DzgLODyLr9Kg8FgMBgMBoPBYGgj9tY2UEp9DBQneeu6FD+jM2tURs7JDrwIPKC1XhVe/Q7wotbaq5S6EHHyOCjZwbXWjwGPAUyYMKG1czEYDAaDwWAwGAwGg8FgMBgMnYDWehviftF0/SbgyJjX04Bpqe4ffu824LYk69cCU9p/1gaDwWAwGAwGg8HQ9bQq3tBaH9Lce0qpzUqpXlrrko7UqEyyf0v7gAgvlmut74s5z20x7/8f8M+Wr8xgMBgMBoPBYDAYDAaDwWAwGAwGg8FgMBgMBoNhx9PRsinbtUYlgFLqViAH+FPsh4TFHxGORSwVDQaDwWAwGAwGg8FgMBgMBoPBYDAYDAaDwWAwGLo1HRVvbNcalUqpvki5lpHAT0qpOUqp34aPdZlSaqFSai5wGXBuB6/NYDAYDAaDwWAwGAwGg8FgMBgMBoPB8AtGKZWvlPpIKbU8/JjXzHaHK6WWKqVWKKWuSWV/pdS14e2XKqUOi1l/m1JqvVKqtmuvzmAwGAzdiVbLprTE9q5RqbXeAKhmtr8WuLYNp28wGAwGg8FgMBgMBoPBYDAYDAaDwWAwtMQ1wCda6zvCooxrgKtjN1BK2YCHkETlDcAspdTbWutFze2vlBqJuNWPAnoDHyulhmutg8A7wL+B5dvnEg0Gg8HQHeio84bBYDAYDAaDwWAwGAwGg8FgMBgMBoPB8HPlOOCZ8PNngOOTbLMXsEJrvUpr7QNeCu/X0v7HAf/P3n3HR1WlDRz/nemThFBD6IICAiJdsGJXwIJ1bWtd17W3fde1l11d6+ruqliXBbuorKLCIkXs9CK9txBKgJCeTDvvH2cmM5OZJJNkUgjPl898Zrhz22TKvefc5zzPR1rrMq31ZmBDcD1oredqrXcm+XUIIYRo4iR4QwghhBBCCCGEEEIIIYQQQoj4MkOBFMH79nHm6Qxsj/h/VnBaVctXtYwQQohDUJ3KpjQHixYt2quU2pqEVbUD9iZhPaJ68rduOPK3bjjyt67eYY29A01FEo9dNSWfU1Gf5PMl6ktjfrbk2BXUQMcu+R1p/uQ9bv7kPW58cuwKasR2V13J90iIpkG+iw0nKccupdRMoEOcpx5KdBVxpul6WCZ2JUrdBNwU/G+hUmptTddxEJPvmhDiYFTpseuQD97QWmckYz1KqYVa62HJWJeomvytG478rRuO/K1FTSTr2FVT8jkV9Uk+X6K+yGeraWiIY5e8182fvMfNn7zHoilprHZXXcn3SIimQb6LBx+t9RmVPaeU2q2U6qi13qmU6gjsiTNbFtA14v9dgOzg48qWr2qZmuz7m8CbNV2uOZDvmhCiuZGyKUIIIYQQQgghhBBCCCGEEELENwW4Nvj4WuCLOPMsAHoppXoopRzA5cHlqlp+CnC5UsqplOoB9ALm18P+CyGEOEhI8IYQQgghhBBCCCGEEEIIIYQQ8T0DnKmUWg+cGfw/SqlOSqmpAFprH3A7MB1YDUzSWq+savng85OAVcD/gNu01v7gup9TSmUBKUqpLKXU4w3ySoUQQjSqQ75sShIdkimpGon8rRuO/K0bjvytxcFAPqeiPsnnS9QX+WwdOuS9bv7kPW7+5D0Wou7keyRE0yDfxWZEa70POD3O9GxgTMT/pwJTE10++NxTwFNxpt8H3Ff7vT5kyHdNCNGsKK11Y++DEEIIIYQQQgghhBBCCCGEEEIIIcQhS8qmCCGEEEIIIYQQQgghhBBCCCGEEEI0IgneSAKl1Cil1Fql1Aal1P2NvT/NmVJqi1JquVJqqVJqYWPvT3OilBqvlNqjlFoRMa2NUmqGUmp98L51Y+5jc1HJ3/pxpdSO4Gd7qVJqTFXrEKKhybFO1Cc5votkkfOZQ5Mco5o/OU40T/KbLURyyfFQiKZDzl2EaBhy7BNCNEcSvFFHSikr8CowGugHXKGU6te4e9Xsnaq1HqS1HtbYO9LMTABGVZh2PzBLa90LmBX8v6i7CcT+rQFeCn62BwXrIwrRJMixTjQQOb6LZJiAnM8cUuQYdUiR40TzMwH5zRYiKeR4KESTJOcuQtQjOfYJIZorCd6ou+HABq31Jq21B/gIGNvI+yREjWmtvwf2V5g8FpgYfDwRuKAh96m5quRvLURTJsc6IcRBQc5nDklyjBLiICW/2UIklRwPhRBCHGrk2CeEaJYkeKPuOgPbI/6fFZwm6ocGvlFKLVJK3dTYO3MIyNRa7wQI3rdv5P1p7m5XSv0aTB8s6YFFUyLHOlHf5Pgu6pOczzRvcow6NMhx4tAhv9lC1I4cD4VoWuTcRYj6J8c+IUSzZGvsHWgGVJxpusH34tBxgtY6WynVHpihlFoTHK0jxMHuNeCvmN+PvwJ/B25o1D0SIkyOdaK+yfFdCFFbcow6NMhxQgghqibHQyGaFjl3EaL+ybFPCNEsSeaNussCukb8vwuQ3Uj70uxprbOD93uA/2JSY4n6s1sp1REgeL+nkfen2dJa79Za+7XWAeAt5LMtmhY51ol6Jcd3Uc/kfKZ5k2PUIUCOE4cU+c0WonbkeChEEyLnLkI0CDn2CSGaJQneqLsFQC+lVA+llAO4HJjSyPvULCmlUpVSLUKPgbOAFY27V83eFODa4ONrgS8acV+atVAHZdCFyGdbNC1yrBP1Ro7vogHI+UzzJseoZk6OE4cc+c0WonbkeChEEyHnLkI0GDn2CSGaJSmbUkdaa59S6nZgOmAFxmutVzbybjVXmcB/lVJgPrsfaK3/17i71HwopT4ETgHaKaWygMeAZ4BJSqnfAduASxtvD5uPSv7WpyilBmFSu20B/tBY+ydERXKsE/VMju8iaeR85tAjx6hDghwnmin5zRYieeR4KESTIucuQjQAOfYJIZorpbWUgBJCCCGEEEIIIYQQQgghhBBCCCGEaCxSNkUIIYQQQgghhBBCCCGEEEIIIYQQohFJ8IYQQgghhBBCCCGEEEIIIYQQQgghRCOS4A0hhBBCCCGEEEIIIYQQQgghhBBCiEYkwRtCCCGEEEIIIYQQQgghhBBCCCGEEI1IgjeEEEIIIYQQQgghhBBCCCGEEEIIIRqRBG8IIYQQQgghhBBCCCGEEEIIIYQQQjQiCd4QQgghhBBCCCGEEEIIIYQQQgghhGhEErwhhBBCCCGEEEIIIYQQQgghhBBCCNGIJHhDCCGEEEIIIYQQQgghhBBCCCGEEKIRSfCGEEIIIYQQQgghhBBCCCGEEEIIIUQjkuANIYQQQgghhBBCCCGEEEIIIYQQQohGJMEbQgghhBBCCCGEEEIIIYQQQgghhBCNSII3hBBCCCGEEEIIIYQQQgghhBBCCCEakQRvCCGEEEIIIYQQQgghhBBCCCGEEEI0IgneEEIIIYQQQgghhBBCCCGEEEIIIYRoRLbG3oHG1q5dO929e/fG3g0hhBDVWLRo0V6tdUZj70dTIMcuIYQ4OMixK0yOXUIIcXCQY1eYHLuEEOLgIMeuaHL8EkKIpq+qY9chH7zRvXt3Fi5c2Ni7IYQQohpKqa2NvQ9NhRy7hBDi4CDHrjA5dgkhxMFBjl1hcuwSQoiDgxy7osnxSwghmr6qjl1SNkUIIYQQQgghhBBCCCGEEEIIIYQQohFJ8IYQQgghhBBCCCGEEKJeKKVGKaXWKqU2KKXuj/O8Ukr9K/j8r0qpIdUtq5Rqo5SaoZRaH7xvHfHcA8H51yqlzo6YPic4bWnw1r4+X7cQQoiDlxy7hBBCNBYJ3hBCCCGEEEIIIYQQQiSdUsoKvAqMBvoBVyil+lWYbTTQK3i7CXgtgWXvB2ZprXsBs4L/J/j85cBRwChgXHA9IVdprQcFb3uS/XqFEEIc/OTYJYQQojFJ8IYQQgghhBBCCCGEEKI+DAc2aK03aa09wEfA2ArzjAXe0cZcoJVSqmM1y44FJgYfTwQuiJj+kda6TGu9GdgQXI8QQgiRKDl2CSGEaDQSvCGEEEIIIYQQQgghhKgPnYHtEf/PCk5LZJ6qls3UWu8ECN6H0shXt73/BNPOP6KUUhV3Vil1k1JqoVJqYU5OTiKvTwghRPNzUB27hBBCNC8SvCGEEEIIIYQQQgghhKgP8S4y6QTnSWTZmmzvKq310cBJwdvVMTNq/abWepjWelhGRkY1mxJCCNFMHVTHLpDgQyGEaE4keEMIIYQQQgghhBBCCFEfsoCuEf/vAmQnOE9Vy+4OpqcneL+nuu1prXcE7wuAD5CU9EIIIeI76I5dEnwohBDNhwRvCCGEEEIIIYQQQggh6sMCoJdSqodSygFcDkypMM8U4BplHAvkBdPJV7XsFODa4ONrgS8ipl+ulHIqpXoAvYD5SimbUqodgFLKDpwLrKiPFyyEEOKgJ8cuIYQQjUaCN4QQQgghhBDiIKeUGqWUWquU2qCUuj/O80op9a/g878qpYZUt6xSqo1SaoZSan3wvnVw+plKqUVKqeXB+9Ma5lUKIYQ42GitfcDtwHRgNTBJa71SKXWzUurm4GxTgU3ABuAt4Naqlg0u8wxwplJqPXBm8P8En58ErAL+B9ymtfYDTmC6UupXYCmwI7gtIYQQIoocu4QQQjQmW2PvgBBCCCGEEEKI2lNKWYFXMR2AWcACpdQUrfWqiNlGY0Zw9QJGAK8BI6pZ9n5gltb6mWBQx/3An4G9wHla62ylVH9Mx2TnhnitQgghDj5a66mYi1yR016PeKyB2xJdNjh9H3B6Jcs8BTxVYVoRMLSm+y6EEOLQJMcuIYQQjUUybwghhBBCCCHEwW04sEFrvUlr7QE+AsZWmGcs8I425gKtgnWWq1p2LDAx+HgicAGA1nqJ1jpUt3kl4FJKOevptQkhhBBCCCGEEEIIcUiQ4A0hhBBCCCGEOLh1BrZH/D+L2EwYlc1T1bKZwbrNBO/bx9n2xcASrXVZrfdeCCGEEEIIIYQQQgghZVOEEEIIIYQQ4iCn4kzTCc6TyLLxN6rUUcCzwFmVPH8TcBNAt27dElmlEEIIIYQQQgghhBCHLMm8IYQQQgghhBAHtyyga8T/uwDZCc5T1bK7g6VVCN7vCc2klOoC/Be4Rmu9Md5Oaa3f1FoP01oPy8jIqPGLalRaQ9l+KNkJAV9j740QQgghhBBCCCGEOARI8IYQQgghhBBCHNwWAL2UUj2UUg7gcmBKhXmmANco41ggL1gKpaplpwDXBh9fC3wBoJRqBXwNPKC1/qkeX1fj2D0Hvj4K/tsRphwBn7aBNS+B39PYeyaEEEIIIYQQQgghmjEJ3hBCCCGEEEKIg5jW2gfcDkwHVgOTtNYrlVI3K6VuDs42FdgEbADeAm6tatngMs8AZyql1gNnBv9PcP6ewCNKqaXBW/v6fp31Tmv4+WqYcw7kr4aAB/wl4CuAXx+BL3uaTBxCCCGEEEIIIYQQQtQDW2PvgBBCCCGEEEKIutFaT8UEaEROez3isQZuS3TZ4PR9wOlxpj8JPFnHXW56ltwH2yeDvzj2OV8R+Mtg5ikwaiHYWzT47gkhhBBCCCGEEEKI5q3eM28opUYppdYqpTYope6P87xSSv0r+PyvSqkh1S2rlGqjlJqhlFofvG8dnG5XSk1USi1XSq1WSj1Q369PCCGEEEIIIcRBbv2bsH5c/MCNEO2Doq0mM4cQQgghhBBCCCGEEElWr8EbSikr8CowGugHXKGU6ldhttFAr+DtJuC1BJa9H5ilte4FzAr+H+BSwKm1PhoYCvxBKdW9fl6dEEIIIYQQQoiDXtk+WHJv1YEbIYEyyF1c//skhBBCCCGEEEIIIQ459Z15YziwQWu9SWvtAT4CxlaYZyzwjjbmAq2UUh2rWXYsMDH4eCJwQfCxBlKVUjbADXiA/Pp5aUIIIYQQQgghmhqtoaQEPJ4EF1j2CAR8iW/AV1Sr/RJCCCGEEEIIIYQQoir1HbzRGdge8f+s4LRE5qlq2Uyt9U6A4H374PRPgSJgJ7ANeEFrvb/iTimlblJKLVRKLczJyanN6xJCCCGEEEII0YTMmwc33AAtW0KLFuB2Q9eu8PjjsH17JQsVboLNE0xGDSGEEEIIIYQQQgghGlF9B2+oONN0gvMksmxFwwE/0AnoAfxRKXV4zEq0flNrPUxrPSwjI6OaVQohhGiOlFKjlFJrlVIblFL3x3leKaX+FXz+V6XUkOqWVUq1UUrNUEqtD963jnjugeD8a5VSZ0dMH6qUWh587l9KqXjHPyGEEEJUorQU/vAHOO00mDgRCgrA74dAALKy4JlnoG9feOedOAsv/ysEEk3RIYQQQgghhBBCCCFE/anv4I0soGvE/7sA2QnOU9Wyu4OlVQje7wlOvxL4n9baq7XeA/wEDEvC6xBCCNGMKKWswKvAaKAfcIVSql+F2UYDvYK3m4DXElj2fmCW1roXMCv4f4LPXw4cBYwCxgXXQ3C9N0Vsa1SyX68QQgjRXOXmwqBB8O67UFxsAjYqKiuDoiK45RaTmaOcrwi2fQza31C7K4QQQgghhDgIyKAvIYQQjcVWz+tfAPRSSvUAdmAuXF1ZYZ4pwO1KqY+AEUCe1nqnUiqnimWnANcCzwTvvwhO3wacppR6D0gBjgX+UU+vTTQRa3LW0L11d1w2V2PvihDi4DEc2KC13gQQPAaNBVZFzDMWeEdrrYG5SqlWwYDB7lUsOxY4Jbj8RGAO8Ofg9I+01mXAZqXUBmC4UmoLkK61/iW4rneAC4Bp9fKqG4LW4CsEbx548sy9Nw88B8xFMu0HAqADZl5lAWU19xYnOFqBvSU4WgbvW4EtHSzWqrcLZp2hbXkOgCcXvAfMfmif2bYObltZwtu22MHeymzL0Qocrc3/7S3MPAABP/gKwJsP3gLwF4O/NHwLeCJGbiuznNYmj5iueCVRBaercJ6x0N/DYjc3qxOsLrC4wOIApcLr0f7gdkuCt1II+MKvCR3MYRa818HEZaridlX472Gxme1Z3eGbzQ22Fua9iHgPtDYXQfPyYm+FheHR7n5/8CVZzM1qBYcD0tNNSYOKN4cjgc+WvzT4HkR8trz55hbwhF+PDgRfb/CzpWzm/bSlhz9boc+ZNcXMW5WAH3z5sZ9pb57ZJx0AAmY+FXz/CX6+bKmxn2l7S7ClJbjdgojXHLEPviKzzfLPdbzvU+i1podfsz0drNX9sSvwFkBJdvC2y5SXCHjN9yrgN58fZTP3Fhe4O4K7E6R0Mq8/AVqbz8/evbBvn7kvKgKfz3yW4t2HPlc2W+y93Q5t2kC7dtC2rXlst9fsZYumz+uF0aNh82bwJJA8o7gYJk2C8eODE7b/13xnKlI26HkT9LvP/B5mT4WlD0DprqTuvxBCCFEbXi/s2WMCGPPy4MCB8Pn4gQNmusdjzsktwWZJIBAOcAzdW4JNHaXC51V+v3nsckHr1tCqVfh8PfS4TRvIyDDzCyGaiIAXCjaG222le8CzH0p3m8dluab9pqxgSwm2C1ODPwTBNqxSQPCLrQMEOxTC7c2AJ9guLTCPlTLtaVc7cGWCqz042pj2oKsjpHU30w5CEQO3zsQMMl6glJqitY7sN4wc9DUCMzhrRDXLhgZ9PRMM6rgf+HOFQV+dgJlKqd5aaz/hQV9zgamYQV8HTb+h1qa9tm2byZhYWgolJeHHDodpw4e6R7QOH7dCfUpVHW+0rrprJfL4Zwl+zCO35fOZY6bLFb653ea+Wzfo0aP6rhshEqZ1RD+xjr4P9d9WVP4BjPwghj7ISj6gzVS9Bm9orX1KqduB6Zgj/3it9Uql1M3B51/HHHDGABuAYuD6qpYNrvoZYJJS6neYgI1Lg9NfBf4DrMB8kv+jtf61Pl+jaFxev5e+4/ry9nlv87shv2vs3RFCHDw6A9sj/p+FaWhVN0/napbN1FrvBAgGIoZaqZ0xjayK6/IGH1ecHkMpdROmsUa3bt2qeGkNpGAj5C6FAyvgwFIo2AAlO8yFZasTUg6D1K6Q0sVcxLWmmIv/FqcJRrC4zMllwGMuBPs9oD1QtNl0LBTvgKLtULzFBGFcuBPcmWa+vBVwYHl4+4UbTIeEv9QEIKR0hdTDzL2jVfDCsj14cTkYHBHwmIAH7Qs+9oNnHxRvh8KtUJJl9iueFr3hvLWV/20CfrNegi3OiifjhE6ug4+/6G72P5Kyg/aG/29xmP0+eyG07BNnm8EL6aFOlajtVRQ8qZ9yBJTtiX3alQkX7WLrVli0CFauhCVLYMMGyM42ncEuF3TvDl26mFvHjtCihWl02+3gdJrGrsViOpc9HtMoz8uDHTvMxfkdO8xt2zZzn5UFHToAZfth3zzIWwW5SyB/LRRnQdle06EUem/dnSGls+kcsjjCfyNr8D7gM58pvwd0qVmvNw9Kdpr1FW+Hoq1w/gZwdzDv24GlcGAlHPjV3Ao3Q+lO8BWbz1JKd/O5dnc2n0eLHZQDrHbz2balhDu1AiXmvnSPCfaJ2u628Ha1Np/p3GXB79Mys92SnSZww9nWfJ9SupjX6+pgtlP+mt3hAJ+ANxxI5Csy6yjbE9z2DrPd4m1w4Q6z7Ui+EvP33jsXcn6Aoi1Qstt0+Gm/uYCtLMEArNBnOyJopLzBaAnP5y813z9HW3B3QJ86k01Zrfj+e/jpJ1i/3rz/ubmms2bwYNMx0rEjZGaaz0PnzuZCgc0W7rQJ3UKdMH5/+FZSYgI/du+GdevMhY2HH5bAjebqpptg+fLEAjdCiooi/rPhLRNwGMnqgjN+hPQjwZ5mph12BXS9CGaMNN9RIYQQNaKUGgX8E9O/97bW+pkKz6vg82MwfYPXaa0XV7WsUqoN8DEmuH4L8ButdW7wuQeA32FKK9+ptZ4enD4UmAC4Mf2RdwWD9ZustWth1ixz7rRggTlvLi2F1FQ48UQYONBkoOraFYYMMefkqamQkmLOn3y+6ItgUCG2u8LNZjPn70VF5lZQAD17JhBoLYRoePlrYc1LsOcHKFxv2qTKavoFul4EmSdDj6tNG9KeFmwveiOyzlXomwj1FSgV25cR9X8VDNx3BK+uW+MHRB/cZNBXkkydfYBzH3g/7nNt2sBbL3Xk7CPOJtWR2MCP6pT5ypi5aSZbDmypdJ45W+aQXZhNujOd9NR0WjpbYrfYCegA7VLakZGaQWtXawp9rcne3orWrtakOdJIJOlJQAfIL8sntySX3NLc8vs9hXvYV7IPl81FsbeYvLI88svyyS/Lp5O9H8vW5xDwuEDbwG+DgI3svD2k2NPo1KodDosTm8WGTdmxWx1YsGJVNqzKgtViQSkLNouVQPnBnuj91aCD/yi/B6fVVf7a/fgJBPw47Q7+MPRmSkvNeURRkelrCQ2kAXNeoZQ572jd2kwPnWtEnldEnmXFO+OK3MXQ/KGbUqbvJ3JQWGiwjsNh+h1TUsx96Jaa2kCxDPNvhg1vxH+u759g8HPxnwsNNEs2bz5Mzqz8+QuzTV98lepyShznj6616VP0FUOgFOaMgbKc8LYszuAAQicc9ZC5flA+II9g36IKz6+q2MXQYMWo1xKaOTTYMRSoGHxssQX3wRUcQBl87AgOfGtk9Z15A631VEyDKHLa6xGPNXBbossGp+8DTo8zvZBwIIc4BCzfsxyAJbuWNPKeCCEOMvFO4yoe/iubJ5FlE91ewuvSWr8JvAkwbNiwxulgLN0Lq5+HLR+YQAdlNxeIbS7ofD4M+Tu0Hmgu1PpLgwEMluAJkD2xs+fJHWIDGQC+6gMdzoTsr4MnuQGzbXdn0xnRaRSk9zUX8kNZAbAEt2shKtNGiPYHb9rcf9EjNphB2aFFT7M+f7HZprcA9s0PXjC3hzstLE6Ky5wsWOxizVo7W7dbWL9esWWrhaIi8BftR3lzsFt9dGy1kyMyN3J4+40c1m4kw4+Yz2Httob/RKEobGULnrj6QVtNpo2AaSl5vZq9exU5ey3s3WslZ48iZ0+A3XsU+/aZhpPXC769KyBvBTaLD5vVh93moU1qLpktf0NGeg4ZLXJo12IvGek5OG2lvPTJPbz/R9i1yzSIiotNMMZ558Gzz8LQoaaBHWrEhUbm1aRDt7jY7BuY5ayWAI7tb8O0N0wgg9UV/Az5of0pMPhOyDzVBJYEPMH3V4UzlCQq3ufr66Og4yjY8WXoj28u5qZ0MRdsu/0GWvQyARP+kmAjwmoaGJYET6XjbXfq0dB5LGR9bhoxKPP5cmVA10vN57pl34i/RcB8HqzuxDLRVLZdgGmD4KJdJnhl68ew7RMTrGJxBb8/ZWZ/0vtAxzMh7XBIO8IEzrg7gbNdMHuHNZwVRgfM6yjbC8XZ8P355jfA74OSHSxf25qRFys8mEVCF9CPOw5+/tl8pkpKTGPc5UpOsIXW5nPqdtd9XaLp+e47k0WjuDj2OasVOnUyQR2743wFANO5sW9u7PQTPzPfPVtKxAqd5nhy+izz/SnOil1OCCFEXDJ6uW769w9fKIl0003wwgvVL1+boAun09zatIl9TutwYHZpqXns9Ua0PYL3oSx8EH3xJnRBJlLkKOjI0dChizZ2e/hiTeixwxEeIe1wyKDTQ44nD3bPNu0Zb4G5OFS2H7y5JuuDMyM4cCM4eMTqjLhA4w4GOYQCFyID0YkIUgiEHwd84cyXgTLwBwegBMrMgAFfMRRsMn0jjjbmZk83gfjtT4YWR9TP32H187Dx3+H/B4KN7LQj4LgJsfNbrdW3nytrQ1bJAlc2uzKEMugrSfoOzmXgtRNZsW8Jfm0OaAoLFmzko7hykh0fHnq7TuS41Cs5OuVM7KRFZd4IZcwIUSq6XKY3UMrq0tnMLfqIlSWzsGLHjweNJoAPTaB8u10cR3OAzRR48sMr8NnB0wLKWoA3BXwu8DvNvc/cq4ALB6m47E6cNjsOmx0LFiwWK0pbUCiUMvcQCo/wE9AB81gH8Ot0ynxeyrx2Sv2peFFgc2Kf9SDePT3j/v0mfABXXJHc96Q6a9dCnzjjxsBkN83Jif8cAT/4i4jKfBx6HJU5NiIjcihrbWS/bejemlLe76aeqPpAb7PYcNvcpNhTcNvdpNjMvdPmxD53AfZSL3Y/WICAAo8FvFbwuuyUDTqaYl8xJd4SSrwlFHuLKfGV4K+ivOqVmd15/5i7zP5X5GwHu783rxkIZ2YOHlsG/AZycuOvOKM1fH4ObHmvytdbkVfD/NLKn29fsJdebXvFf7JDhyo6TjCjq765GVY8ETV5lw82eitZBjihqr64K+t4aaNWxyo4mI5X9R68IUR9mpc1L+peCCESlAV0jfh/FyA7wXkcVSy7WynVMdgA6wiEIgEqW1dW8HFV+9E0aG0CKHz54Q4BSkynx8V7zTR7i/D8lrSq11fTkyzvAdj+SfS0IS9Cr1vMvtkizgiru6Bek21rL5y7Ks50DdqH9pXyy08+3v/QxsxvnWzeasftCuD1KkpKI0auANAueIMVWUczYwXYbAHcLo3Pp3A4NCOGlXHxRR5uvKUlFkuwwRfQbN5Qxi8/lTD3AViwqIy1G5zkF9hwOgLYbH5cTk2bNoqWra2kp1vIyFC0agWuFLC2GQwMLo+Qz8uDDTma/J0B8g4E2L9fU1qq8PoslJRasNvDgRWlwRP/5ctNNoTIi+Bp1bzFVUlJqTBh+ZOw8m/hbCehEjRD/gG9b8ME4gQbRJYErurX5D327IetH0RPa3c8nPWTyUYR9dmqZts12W7ZXtg0ATMgNLR+p8ky4y+rsN1qet1r+n0q3Q3zb4HNE4JDMSP+7p3PN+UiMk8JBxHZUikvIVQltyk71KKXuTAeodiTwoHilqSnR19sT083n63CQtOXmJKSvBTcSkngRnMVCMDvfx8buJGWBn/7G1xzTbiMzs6d8Nxz8PrrFVaS85PpvC4veQV0uxTaj4wO3AhRFlN66JjX4btzk/6ahBCiGZPRy3Xw78mb+O/MnaxYbjKWBbQJYHjve8i7qzcnDslg4EBTxqRVKxPM4PeHAykSzSuyu2gXm/M2YlHhka3KAmWlcNdVR7J6cbuYZTp3NtnzGorXa9onXq+5FRTA/v3hsnqhrGyRJRwrCyCJJzKApGJ2ktCI33ijfyNvLpeZXloK+flmH73e8D7Fu9c6vO5491arGdmcnm7OlesSqOLxmHOjgoLogButw4ExNpvZTqdOST6XDvgiSkLmmzZP+QW9UImOyPKmNlPG054eLPHhDK9r2YOwflz87VR1QShe5FBIrS4EKTh5inmYeWp4sqNNuF/Cs8+knqwPh11uglX2LzXZ4UqyzT6VZMP/RkC74dDuOBOM78oMlu9MNfsWykaKjv671CoZUcVSsc2CDPpKksPb9GDpbfMp9ZUyL2seszfP5uv1X7No5yIAfJj+iNWls1ldOhuS8HXxEb6KfXT7oxndczRnHH4Gx3c9nlRHKr17Q8H66GWcTvP79803muOPj/9D6/fr8mNOxWDE6rNKmP+Eft/tFca4lZWZ9q3PF33zemHNmvDxIvJYFwjAgLM6YN8f/7fL2yaTZdOjS39WdQwJBcmUlpp2Nf4yUnxrSNcrcesdpFp20sqZxfaJ+3CQh9NlxZGahs2VitXhwmJPRdtbmd9sR1uT8UdZzcA3ZQlmRg4GZ4QCOwKhLMLBrEC+IvO76c1HeQ8Q8BQR8JbyjP9klq76jgInFDgg3wk7WkBOsG/SF/BR4CmgwFMQ87qcXeBoB/S0Q0cbdLFBDzt0tIJTebGpxWgH+DQUadjhg01eyPbBTj/s3weF+yCtDFp4oEUZnL1xC+xqBY8/XvkftDKVBW6Enjv+XXOrgT35OzjvxZ7kqvBn3+0BR7DL0ftib9oXwQ1L4MrlcEQVuxBj924YaAI39qbAZ33hraGwoj24gocRvwUKHZT/Yjm9MC31LE696ibzngZKo8uPr3nJlJMuF+pDDx5Pjvs/2Bvdr1iuXUuo5BSgek3mp7FaErwhDmrfbvkWgFV7V6G1Tih1lRBCAAuAXkqpHsAOzMisKyvMMwW4PdhBOALICwZl5FSx7BTgWkx5r2uBLyKmf6CUehEz+qsXMF9r7VdKFSiljgXmAdcAL9fLK06Gln1NqZJARFit9plprQaGy5Y0lBa9zAl+vItsSRP/gvWu3Ypx4+y8+aadoiLTwApF/Xu9iV959vksFAQz9peUwjezU/hpXgo33WYyX7z8Mrz2mqK01IXN5qKgwDSmTj0VTj4ZTjnFSp8+Vlq3Ng29UMebxRIuMxE5gCgQCKUyVChlxWaz4nSagI41a+C++0yJFPM6wvs5YwZce63pgEyvj8xx7Y4Pl7SJLGGwZw70uMoENWhnMNtDPbCmmtEBIWV7TbkTq9uMHEg000WNt+ukvHQPmPvtk6HzueDJDzZ0EwmaqIVN/4kuDZR6GIycYjr27DWIzEmwk3NEz/kUjU9hXvdivv3WZE3Yvh1++MF0XgweDMOGmTI83bpB+/ZmREeb1gFa2rbgKFmNxbcPK2UoXYolUIpWNgLKFby58bsOp9jel/0FLdi3z4wG2bkTbr+9Fn8f0aR9/rl5byP17Wt+q9q0ib7Q0KMHPP88XHwxnH++yfACwK7Z4I34vbHYYei/qv78W2ymY75txUF3QgghqnBQjV5uaiOXp5Tcx+dtPsNxmgO3zV1+sagwAO/rAClFH7D/23M5cMCUjsvJMcc6l8scD0PZzKq6Hrs55RN+bHsDSofPebUGv7UYrby0GHwRuIeD8oO2gNcN3lT2W1ry9JsD0AELOmABbTVjqa02nDYbTqfCbrdgsyosyly4UgosSqGUIlSxJqB18HVpAlrj84PHE8Dj0ZT5fPj8Pv46fRwlQ581O+d1Q2k6+B0oCwzs3ZZu6d3okNaBlq6WtHS2NKnwXek4KgmC9gV85enq88ryyCvNY3fRbrbnbSenOAd/wI9f+8kvy6fIa9oJl/W7nGeHf8iKFSa4fdUqcz6ye7cJRG7b1pzHtmkTPI+NuG/VyqRyDwV/OBzhtlpoBHlk4InHY9qYeXkmQGXvXnP9f/9+eOYZs754AgFT9nL5cnOuvXGjKX+ZlRXeT5fLnH9XzHYS+Tnx+83FO5fLBAZ16QKHH25K6HTrZkaBl2d18eRBwTrIXweFm8zjwk2mjeArMlkptN9kGEzpZu4twaxmodKmyha8ZuM3F/AiS5x6ck1J1dKdZrotxYzGPuM7k3XDWxAdFLL0oYhA+Mj09ApOfhL2VSiZF9JS1eJikIbvzoudXFUASVUjnNumwr+K4j9XmYyT4cw5wd3R5u9Vkm1S03tyzS3nRyjbZ8pilu2Bi2ZAbiV1B9s44YvLCF/gUuH7rP/GLy/rbB877eAng76SzGVzcXL3kzm5+8k8ceoT5Jfm897y9/h01acs272M3JJcrBYr/oAfjcaqrGitaZfajsNbHU6X9C4opcguyGZT7iZ2F+1GocqzI9gsNvwBPy2dLemb0ZeL+l7EdYOuo11KbPBhixbRGT1CZViVgsJChdcbHcQXurfZVPnjQAB0WS6WglWQvxJL/mrw5aH8JYAVbXOBMxOd3p9A+lGmBLPVVR6Up7XpnwsFDIayXtVYJYEbAPaC3Qzrvd78Bjvbmt/fROz+nmOzLjKlh61uzNX5YIbllkeZviN3pvnt9pdSHmekrKhQduLa9mVV6GOyBm9/HpQJf0nwwntxNuyYgt41G71vPqpkBwGrK5gx1oNVx0lpFo/FZV5LV7McLXqZ/suOZ0LH0TXrO6tnndM7s/exIpbvXs6szbP4Ys0XzM+eT54vHMyxxQGPnmZuCoVFWbBarOXZYiqj0aasTvC7GaksGGFgt9gZkNGX83qfx1lHnMWIziNw2mrzgQ7ae1MVz+XBpQdPEEZtqSZe2rHeDRs2TC9cuLCxd0PUUtcXu5JVYNreG+/cyOGtD2/kPRJC1Bel1CKt9bAkrm8M8A/MOeB4rfVTSqmbwZT3CtZdfgWTSrcYuF5rvbCyZYPT2wKTgG7ANuBSrfX+4HMPATcAPuBurfW04PRhhOsuTwPuqK7ucqMduwJ+2DkNtrwPO742nSoWhzmBdXWErhdDxgnQsp8Z1WFLg0C4zIcRJx+ueRAxiyV40dxrOhjy10LuEtjwOpTsBCzmQruyQoczTPaNjBNMZLevxKzL4qhdUIevyGw3tA8VMi0UFJig6tdeMw21sjj9FiHdu8Pxx5v71FRz83hMh1leHixcCIsWhbNbRPr73+Ghh8yfJ3Ib111nOutCtRyTUVoiks8Hq1fDJ5/ARx/B5s2mwy40KuCMM2DECFNPu2tX05HndpvX4A9Gc1d3aqmU6eiz2yE31/RbbdgAF4zeb8ribH7PlDIIZb3QGloNgHbHQpthJuWsu6NJQ6isZsRWqJZhVB1eCKe/Dd5CZXTK9kPpLijaDO1PNWVDNr8L+34JZrmwmgZo26EmE0XbYaaR5mxnng+VdIncTujFRf0RIj/XwZInvkLTEE3vDQdWmGCNrR9D4YbgCDOHCYLKOMmUIWo9GFK7me+Uo3V4ZELUa67wBy6vXWwxHaO+QtNJV5wNC2+DvNXEjI464wfIOI4a1978oIaBs3E6Mn2+YKd0jqZ05xLs+2aQVjqPVupX0q3b8GsHAW1FqQCKAAo/Cj9gQWMlgAW0Ba0UdlWMR7ck19+bAttQSlqcxMBzL0FZatlxUEfJPnYdzJJ57DrhBFNuJyQzE3791VwgqeytLimBb7+Fc88NBtt93R/yVoZnOPwGGPrP6jtgdAD2/mKOO0II0QzVQ7vrUuBsrfWNwf9fDQzXWt8RMc/XwNNa6x+D/58F3AccXtmySqkDWutWEevI1Vq3Vkq9CvyitX4vOP3fmBIp24LbOCM4/STgPq11nCuvRlPoM/T6vby28DUenv0w3oCXUl9048Ftc3PD4Bt48ewXcdQw0LnUV8ptX9/GRys/otgbnc7KbXPjsDp45oxnuHHIjdgqZDcs85Wxu2g3uwt3k1eaR5G3iCJvETlFOews2MnOwp28dP1HtMmLvUB8oJWLpyfdSccWHclIySDNkUaqPZV0ZzqZaZlkpmbiskcPCnh21ms8O/8x8r255Wn3G4rCQpqtNa6JC8hZ3wOXKzwiGmDkSBOYDCbgQutweyeZfD7TnozMYqi1SW//+efw5ZcmED+UxS5U5jKkTRsThNGli2nLtWkTzhhisYRL4OTnm2CP7dvN/Z494SaHxWLaf4WbfjBtqO3/NW0bm9ucI/lLoe1w6HyeaUOl9QwHawRKI/oGIsqUlLddQilPAsFmVLC98+WRseVNwbSPLtoVO70q1Q36a4jrJLIP9aIejl02YB1wOmbg1gLgSq31yoh5zgFuB8ZgAgv/pbUeXtWySqnngX0RJb/aaK3vU0odBXyAyVbVCZgF9AoO+loA3IEZ9DUVeFlrPbWq/W8Kx6+a8vg9LMpexOzNs/lq/Vcs3bUUhaLUVxpzwRhMMEhAB+jfvj/n9DqH03qcxojOI3Dba54yKFRytaDA9NmVlZlbaWn0va+0mI76K3oE/k1bPRcLpfhxY8GLjdh6nhqFD9O+tFJMGe3JVuexxXINB6zH4XRZcLlM0MaJMx9H/eWJmHXUmAM4DTge0zsd+tm1AfnAEkzvc1U/n4OAPxEsN+UMBuEFV9R2OJwdzILvzae8xG9NgjZ+fTymBEe1rKlwWSXBd2DKaG350PTtFW4M9hfGqbGaDLYWpi/88irqlFSlgX6DfQEfL897mQnLJrAqZxW+QHLPnxSKw1oexrlHnsszpz9DqiM1iStvfsepeKo6dknwxkF4IBNGXmkeGc9n4Av4sFvtTBg7gSuObuACYEKIBiMXwMKaxLFLaxNIkb/aBFcUrDePi7PAW4D2FpKVk8GaPcNYs/cYFm/sx4YdXSjxOPH4bHi8drRW2G0+HHYvTruHjm32M6TnGvp1WEKfjAX07LAeh8tpgkDOW2u2m7/OpLrfvwj2L4SiLSbAw+IwqUlTu0FKZ3B3htTDCDgy2LUvnc1Zrdm+K41SjwOf34bN6iPFWUa3TgX06JRL+zYFqNKdULwdSnZA8Q4o2gYXhQc0/PKLuehXXBw/4OLww+HCC+Gss2D4cNNh5/OZoI3IMhChgIyyMtPxtXEjzJplRox//bUJgrDZYmtbDxgACxbUrm51bXm9Zv/WroWtW/zs376ZQO467IE9uFQOLR07ad9iB53b7KRdWg5pzjxsFj8Wix+L8qOURmsLAW3BH7Di8Tk5UNKGPXmZ7MjtxN7izhT5Miklg8ef7QTp/cAVHBXhOQD5aziQvYM1K4pYt8bD7j0Wdu91k52Tzp4DLcnJb0NuYSvyi9PwBWz4A5bg9hQWpVEqgEUFsFn8pLmLaZ12gHYt9tO+1QE6ZeSR2a6YjBE30LOnqeeZmeFDFW2G/FWQvx6dv5adW/aybbuDnFw3Oblp7MlvS3b+Eew40IOdue0oLEnBHzCvzx+wotBYrQGsFj82i49WaYV0bL2HLq020LHFFjJaHiCjdSEZY9/l8MOhdeuID0ZxlvkuFW2Fws2U5W5n63Ybm7ensWlHa9Zt78TK7X3YtKsre/Nb4wvY8PnNdrVWZptWP1aLnxbuIg7LyKZPl3X07bqFwzvv4/CuBRzV5hsc/qzoUhEAIz+HjqOi0xEnokbphePUltQa9nwPG96C7K+CwSme2P2rLVsL+E0lqRYbgBy7wpJ17MrKMqM+IwPbfv4Zhg6t/vexqAj++ld45sli+LRVdCapMcuhVf/EdqJiSSUhhGhG6uEC2HHA41rrs4P/fwBAa/10xDxvAHO01h8G/78WUxKle2XLhuaJGL08R2t9ZMX1K6WmA48DW4BvtdZ9gtOvCC7/h8r2vUm0u4LySvN44rsneH3h65T5yghEBOLaLXZau1tzzYBraONuk9D69hbvZcKyCeSX5Ud15luVFYfVwZ0j7uShkx6ihbNFFWupRlUd7/XQH+0PmEwZuaW5HCg9QG5JLscNv4iUfbHngmXtWrN82Te0crWitas1LV0tYwJUKvrHm3v5zye72LLFtAmdTvMS27aFe/+QyQmDMjj8cDOiO1S6JpRaH2IzXcTLeAFQUFbItvwtUcuFyrS0TW3FYa274PWaLI0vvGAGBvj90edG7dvDqFGmbXrSSSbZQ2jwQSi4xOmMLVcYyvrh8YTnczhM1o/58+F//4ORzt9z2YgPTDCGjggIT+8LZ/0S3OGU6suZRqpt7fqqMlzEk8SLQR6/h/yy+O2MFHsKKfZKBpPUcB+01uwv2R/34rXNYqOVq1Uiu1unfTgY1Ee7SwZ9NS6v38vinYuZs2UOX637irlZc9FoBncczLm9zuW0HqcxvPPwuo3uT4TWsHO6KdW0c0YwY2xsaY6EKUvwN9IJ3a80pYLTj0zCfgZgw9uw7H4zyKnSwAWL6UPtdikMeQFcsZlzftr2E7dPu930y/hKwV8S7KfxgvZyUUs3j7RvCSmdwNnG9Mc62oCjlbl3tjWPrSnBMinBUinl96GyKcHSKTrAB2v/x/NLPwB0MPuS3wSMaD9oP3ee+gLXD74+9uXsXwTLHoLd3wWXrWKUXYgzwwwSc7Q0g6csLiAQLulRuseUovJVkwmpNkGE0Gi/wWW+MubtmMeMjTP4ct2XrMpZhcvmotBTiEVZUCiOan8UqY5UFmUvwq/9+AI+Uuwp+AI+OrfozKieoxjdczQjDxtJS1fLKrc35dhW5Hjy4j6X6oVLV4I1iS+1zAqfHGXu4+maD2cVZppU102EBG9UoTkcyA5VMzfN5OJJF1NQVoBGc8uwWxh3Tq2LHQkhmji5ABbWFI9d+/bBf/8LX31l0rRu3246gux2HYxQT2x0vtWqSU0FrRXFxabTqXdvM4qoRWX9hgGfSQvqyaVgfwHf/WDj6xmt+N93HcnalYbd5sdh8xHQikBAlRcNtVg0Smk8Xjv+gIXDOhdw3mnZjD4jjxNP8ONu2RJa9gel+Pe/4Y47ItLtRzjySHj6adM5ppTJVFFTgYCJ7i8qggcegDlzYMeO6ACOli3NSKqMDEhriMx8xVmmrMDubyHnByjeFoyit5oGlivTZI9wdTANH3dHSOliGn4WV7hRFmpweQvM+1S8A1Y+FduQdGagL9rDokXm/Z4zB5YtMx2jbrfpSGzf3gRZHHmkKYXQsaMZcd+2rUkd7HSGa0OH0g57vXDggPmM7tljMn1s2WICUtauNSPxMzPNLmRlmYvA335r7jdsMOsIXRBOTzcj1dq0MfuSkWH2oV27cM3rUKrjsjKzrV27TPrqPXtMppGtW81z69aFtxvi9cKPP5ogns8/N/vpdpvX4/HEfv7S081rdjjMZy9U//vAgXAZHzD7FSoj4bLksmP8CGye7OhSMfZ0OOY16HJBMEtIPUcJaW1GRfz6sEnp64szgkJZzGi9VgOgzRDIOB7cnYJplh3hQA9fIeQuMxlb1r9psgJFqm2DOgnk2BWWrGPXk0/CU0+Fg+jGjoV3363iGFFBURGkFs6B78eakUJgUnifuybxgAxfcT2X7BJCiMYjo5fDmmK7a8uBLZw68VS2HNgS93mFqraksNY67oVggN5tezP7mtl0To+pKFNzDRy8UaN9cAK7V5nHKV3AXv2JxONzHueJ78xIYZvFjtMSLmPjC3gYYLmCoYWP4dt7GKWl5rw8EDDtw5SUcDr8UJawyCAOraFMHWCR40WWuF9EaQugTKZ65SFgMSc+XYrPYdyJX3H77aaUSnGFJtXJJ8M//2naS15v4udHiSouBsfc87HlzIptz7UZCqMWmvMrew1rbdYweOOrQpg0C4gT731MNtwxv2abr8yadvDMiTE5CwHY0QJmHwFKg7PCwAuLhpenwvVLqSYZfdV2pcFvLoW5XcAasRN+C3it0LYYctyPoh6v4Qh2Cd5o9pri8atWqiozBKZTpT4vxO6dBwtuMeWgqruQXxvKaoJBul0Ox/2n9uvxFsKPv4E93yWebULZzbHv1P9B22Oinvp5+8+M/M/I8pI0FblsLjbeuZFOLTqZCQFfuHyVr6g8ICPuPcF7ZQVMQIcn4KfDf84ht5KAOLvFzrhzxnHjkBvDE0t2wi/Xmf7K8tItcTgzTLaQtsdA+5Gm7LctJbhMMGMtluDygfDvn81tgjg+7xp/vQC3AvFjEyqlgTxakk0ndtCZbDqxiw6U4MKLHQ8OynCiseDAE5ziwYGX1uTSiWw6s4NOZNOBXdiIeI9q+H0o9hbz07af+GbjN3y57kvW7VsXdX6Y6RtG37LraX3gVNpYutO2pZv+/eG44+CII6o7zdP0+D8b21oEcHvjz/PbX+H1r+p2nAwJKLjoMphRSWGGEjsM3gmLvpDgjYNGszmQHYKe/P5JnvjuifJaS/0y+rHy1pXVLyiEOChJQyysqRy7ysrgs8/MiJ8lS8zF66I4bRm32wRg9OljslOkppppFou5+FZSAtnZsGaNKdmxb1/sOqo6XdEaZs82ARQ//GA6xwoKatffYLGYwIjSUjjnHJg8Gd55B265JbZjDEwJlT/9yVw8t9VgYFFVCgvN3+Sxx2DiRHMyHPq7Ohxw2WVwzz3Qr5/ZT4slXD+5tgoKTMei2w2OAz/Cir+abAgWW/iiujMDev7eXNxv1T9YK9JnGlxWZ0yJmSrFKbXx7g9X8ZeZ75GdbT5boTIsAwfCn/9s3g+bzQQxuN21rAUa5PWa99NqNR2p06aZ0fhLl5q/cUFwEEWXLnDVVSYwZ9CgcIkYrc2+OJ3Vp0MuKzP7HKqfmpJiOlo7dgzPs3Ur/O1v8MEH4fc7Mviib1845RTznvfta75HHTua99zvD8+rlJlms5ltbNtmvlerVpmRcj/9FBxF5/fBxvGw9M/mffQVUN7QTT8SDrvClEFq0duMsAATMGGrQWSSLzgyQymzbN4K06ELULgZfrrClI3xV/jRUDbofC4ceaepJRrwAAGTgae6ki6+EphUyQX1mo7KSxI5doUl69g1ZIg55oSsWwe9eiW+fEkJuLePgyX/F/58H3k3DHxKAjKEEAIZvRypqbS74pmwZAK3Tb2NYl9sI8VuseOyuWKCOLTWlPhK4qbNTnOk8dZ5b3F5/8uTt5PJDt54/HF4og4p5S3ASEwoUFeiU8lnAd8Cc4D416rQwOIN3/PW6vf5YPkHABR4wqOvrcqKRVkY3nk4l/S7hMzUzPgrqqDQU8hX675i+sbpBHQAb0RmsDR7Gj7tY1TPUdw67FYCG07jwgutMUHdSsH778P555u2Yb0K+GHbx6ac6u454Qtf/mJTJrLTaDOiu9XRkNLVtBPLy06GSlkqs0xoBHboPL/8Ip8OZvUI/d8fLgmpLDw4/R6em/sq/jhtYJcXlrwBffbW/aWOvB5+OCz+cy1L4K8L0njsLDtl/rKY0kOp9lRO6X4K71z4TsIZcSJNWTOFqz+/mmJvccx31m1zc0r3U3jx7Bfp065PjdctwRvNX1M+ftVIdZ9VqJ/Pa+FmWHgH7J4dbjPWt9oOOineATNPNveBWpTxsLphxL+he3RG+6smX8Vnqz6jzB+bycJpdXLrMbfy4tkv1nx7cUxYOoHbp95OkTe2U1mhGJA5gMV/WIwlVJJl+xfwyzXmuFNZKbUOZ0Df+6D9SSYTiS21ZhmhQqoqFVxF8EYurZjPcH7ieJYwhG10ZTcd2E8bFBonZVgI4MNKKS78VN25qAjgpAxHMGrRh41SXKRRSHv20IlspuwcTssOtc8Qmleax7Q1M/nmy5Z8987JZGfZsdvDfaRg+swDATOA7sEH4frro8u5RcopyuGs985i7d61lPhiv0cp9hQeOukhHjzpwVrvc8gdU+9g/NLxMcfi0HaO6XQMU66YQrqzhsGl9UyCN6rQbA5kh6BTJ57KnC1zUCg0GrvFTuGDhTWu8SmEODhIQyyssY9dWsPHH8Odd5qLYIUVBsxnZMBFF8GVV5oLza1amQvlSsWWEAkpKjIX1N1uc795M0ydai5m//pr/LaY1ma09aOPmoCPivtRV0rBihVwzDGxgRsWiwnsOOOM+u0cKyiATz6B6dNNRoY9e8xJcSidbf/+cNRR5u/cpQt06mQyQrRpY0ZZWSzmplT4In9hIezfb9a1c6fJNrF6tcmYclrHv/Pcbx+NjdQ/8m4Y9DfTY1mTUgEJjqB6Y9bvuee9lyjxRP8x77/fvL8OR/zPTV15PDBmDMybF/35cThgwgS44ILaZ1NJRFER3Hab+T6FUiuHHHUU3HST+R65XOZ9rKxBVJ1QsIrTabKKjB4dfMJXAnvmQNbnsONrU0va6g7XM7U4TNaL1O4mHWZKN0g73HTC2twm0EJZzbwBvwnEKNoOhZtMppaSbPP4wAozz5Uads4yGQ8CJdFplpUVDr8BBj5p0lbWdLReSGUNawneaHTJOHZ5POa3zRMcZTlypMnUk17Tj8v8W2DD6+H/j14CrQfVad+EEKK5kGNXWGO3u6qjteaLtV9w29TbyCvNK7/o4ba56Zzema+v/JrebXsDsHLPSs754Bx2F+2m1Gcu7qTaU2nrbstr577G6J6jq83YUWNNIfNGyJ4f4JdrzfluZaOnrakm1ftxEyDz1CpX5/V7mbZhGjd8cQP7SuKMPkiS8eeP55J+l5SXr+nZ05S1rOjSS2H8+AbK0Bgp4AuWUV0H+Wsgbw0UbjRZHD37zUVPiwNSDzPlTV2dzN/YYjNtCYvNjP4OZW0MeINtC18wXX5EBseSYGlTzwFKlZOeO9uwo2BHzC5ZlZWL+l7EpEsn1emlLd65mJP+c1KlF4Leu/A9Lux7ISXeEv4575889f1TeAIePP5wOhCrsuK0Obl24LX0apNYtLEn4OGzVZ+xdNfSqEAeMN/Z/u378/Lolzmm8zGVrCEBErzR7DX141fCGiN4Y9unJqNDIBR01oBq2m/hyYVpQ0wJ6Lrsq9UNJ34Cnc8pn7SveB89/tkjKkgxUoo9hZ1/3Fnni+Faa3r8swdb87bGfd5tczPvxnkcnXm0mbDsYVjzUuUZRjJOghFvm+zACWTVqlZVwRtQ/p75fDBzJnz6qenD3b3b9HEXFYUHp4GZdsQR0Lmz6cPt3Nn8v3t3k3HZZjO3UD+uz2cGhWVlmeP/9u0mU3N2thmwlR2u9l3nr8LPP5vzifz8xPrYU1PNgLYJE0xG1HjKfGVc/d+r+Xr91/GPp7YUXjv3Na4ZeE2t9/v5n57n8e8er/R4fc2Aa3hlzCtYLfXQsVxHVR27kjRGVIiGpbVm8c7FUdNcNhe/7v6VYZ3kPE0IIepLXp658Pvrr7FZNkaMMBfaTzvNnGBGBjW0rLoMXtS8TiccfbRJ9Xr77dEnoiHr15sMFOvWxc/2EWKzweDBcMIJJlNBy5bmAnhRkSktkZVlsnWsWBGd6QDMSe9NN8XPuPHEE/UfuAHmIuUNN5gbmJPnVatg+XJTUiMry/x9VqwwASwHDpjXFhm0EWrrhlL6hsqJpKSYwJq2bU3Ax1FHwUOnVdIAGvikaczVk/2FbYmXKC8jw+xzfQRuAHz/vclGUVphcMJFF8GFF9Zf0AaYhtxxx5kAmsjt2+0mi8wtt5jH1WX2SITdHv4OlgdugAnA6DTa3MA0/PctgP2LKNiVxY5tRWRv0OzYnUJWTiqbc1qxdW86pd4yvH4/Xp8df8CKzerDZvXhsHlxO1rQvV063dul0qV9Bp07tKBz50F0OiyN1L3zTOBGxWwbFjuMnGJGRNjqe6igOJgtXmy+l6HgjVNPreX3NHdZ+LGyQcujkrJ/QgghRENSSnFBnwsY02sM4xaM49FvH8Ub8FLiK2FT7iYGvzGY1895nRJfCfdMv6e8U9tlc+G0Onn69Kf5/dDfY6vNSNSDyfo3YfHd1Y+e9hdBcRHMOQcGPw+9b6t0VrvVzvlHns/e+/aycf9GHpr1ENM3TTelnbUmQACFwqIsdG3ZleGdhtPK3QqAEm8Ji3cuZs3eNeXzAtgsNhxWB8d2Ppa/nPoXTuh2Qsx2K8v26PHEn17vLDZodZS5VSbgNQEY3Y6EPTNjn2/XEha+aQK7LeE0+iirCei2twjeB28WJy6leH/Ld4x+f3TMaF6/9vPlui/ZcmAL3Vt1r/VLe2jWQ5R4Yz8zNouNkYeN5MK+FwLgtru5/8T7uXnYzVwz+Rq+XP9l1L4Ue4t5beFrKFS1F4601pWWKXBYHUy+bDJnHXFWrV+TEKIKWsPS+2Hdy4ln23C0gXYjIL2fKcuRdoTJTKsDJlDwwK+QuwTyVsK++eb3MFl8JTDrdBPcVtcgE3+JKbty+mzzeoC2KW158ewXuft/d8fNiAHwxsI3+NMJf6rTpqdtmMa+4vhBkC6bixuH3BgO3Fj/RuWBG8oKg56FXrc0aEbNPXtMH95//mP6WiOzVHi9Jqjy9NNNZqyTT4auXc1AyFBG31Cp5OoMH27uTWlys7zTaR4vXmwGtdRWIGCySr/2Wvxy4ZUJ9cdfeSWcd54J4qjYP+O0Ofn4ko958ocnefqHp2OO2cW+Ym7+6mY6pnXkzCPOrPG+f7jiQx6b81jczB5um5sXznyBW465pcbrbQok80ZziUI8xGw9sJW+r/alxFdSnnnDbXPz/JnPc9vwyhtXQoiDl0TRhzXWsevAAXOyuHVrbOfQn/8MjzwSLodSnz75BK67zpywVgy4ADMC+7rrzMnjwIFmXx2O+Bf4iotNFLPNBgsXmhIpH3wQPlkNnQhHysw0mUHc9RfLUHNV1AH1Z2Syd/kubDbTILBaqyizsuk9WHBTeMRTyGFXwPDXAZWcyPUKAgETEPOPf5gGSKixY7GYBs7DD5uAnpISE4hQ2wwUkcrKTODLyJGQkxP9PmdkwC+/mPsaj+hP0Lnnmmh8X4UMj59/DmeemZzXmKjCQvjuOxPMMmuWCRAKZcIJlWYpLdX4/YqMDDM6wO0274XVal6Dz2cabtnZpmSLzaZxuRRWa3j5ko97YivdFLsDp34DGSfUrIFdw7rYknmj8SXj2PXyy3DffeGAp7lzTeBgjX3WHspyzOMWvWDUYrA39FBVIYRomuTYFXaw9RkeKD3AY3Me461Fb+ENePEFfNgtdpRSePwebBYbdoud24ffzsMjH67/1NFNIfPGr4/D6ucrH6FbGWsK9L4dBj9bo8XW7VvH+CXj+ffif1PmL6PQU4hFWbBb7YzsNpJ2Ke2YvGYy/oAfb8BLC0cLAjrAb476DX8Y+geGdx5eZQaUn34ybYV4F1deew2uuSacta/JqYfPw7X/vZZJqyaVZ5MJsVvs/HbAbxk/dnyt1rs6ZzVD3xwa92JQmiONdbevo2OLjnGWhKU7l3Lpp5eyYf+GmOcsykILR4uYgCmNpsRbEnd7VmXlrhF38fyZz2NJ1hsrmTeavYPt+FWphsq8oQPw05Ww48vqjxe2VOh6ERzxexOw4S8z2UOtldT29RWFSw5/Uk1/Wk36LX7+LWz/zJSlShZ7KzhvHbgyAAjoAEPfGMqy3cvQxO5ba1drdv3frjplwh/65tCYQdoh7VLasfmuzaQ50mD/IpgxsvL357h3oeuFyR8QVEXmjddm/oE/TXodrze2n7xNG3jySVNWpKwsnB25vhQX164f0e83/edffRV/8GKiXC5T4nbGjMr3Y/LqyVzx6RV4ArERpwpF5/TOOCv7HsVR4i1hZ+HOuJ9Nl9XFV1d+xemHn57w+hqDlE2pQrM5kB1iPln5Cb+b8jsKPAXlwRsAF/e9mE9/82kj750Qoj5IQyyssY5d99xjOoQqBjP85S9w770NUFsXE1xx883xO6tatYKnnjKBG1rXbn9CQQMvv2yCCez22Mwet90Gzz3XsBfXq5XMzpf8dbD6BdjynsmIECqhYXWZ2sWdz4d2x5vGnL/YrFtZTTrc6k6ydcA0LANeQAfrHdugYD206o/HA1OmwKRJppRJdrb5O4d2f/BgUypm4EDo0QPatTMNopYtTTS7zRbOLBLKPuL3m/cwPx9yc01gQVYWLFlighTefx/+/nd45RWzjcJCsz2LxUSO3367CVqy2UxjzOWq3Uj/QMB8br1eExQUqhMZqW1b85odDVABLhAwZYfGjYOlS81rKiw005UKZ6w5/XTo1csELbVsSXmjNN5HSinz2mw287fevRvWrDEBIWXbvmX8teeDr0LuxQ5nwEmTax4UVF3qyookeKPRJePYdddd8K9/mcdWq/nM1vj76C+FSWnh0UmdzoHj3wNHqzrtmxBCNBdy7Ao7WPsMN+du5u7/3c3MzTPLs224bW7O6XUOL579Il1bdm2YHWns4I2tH8HcGxIfQV2RNQWGjYMjrq3xogEd4Put3/PGwjf4Yu0XKKXK34vQhYkTup3Abcfcxjm9zsFpS/xixfz55mLQ1q2xbdUhQ+Cll0xwa2lp8i8WFRSYNnKtMp/Vw+fhQOkBDv/n4eSW5sY857K52HTnpkqDLKpyyaRL+HzN5zFZMFLtqbx49ovcNPSmatexYf8G/jj9j8zYNINSXykajULhsrl4/sznufWYW1FKsT1vOxdPupiVOSvLPyMp9pTy7Di/G/K75GfHkeCNZu9gPX7FaKjgjSWhjBtVXL1WVuh5Ewz8WzAzUC0GNiVYgqNa27+An6+seWBidZTdlA079X/lf/vlu5cz4u0RlQazvTL6Fa4dVPPjJMD8HfM5deKpcctdpNpTeefCd7io70VmwvcXQtYXEOdCPT1vhiHPg62WAzJqOjgImPD9tdz2n1cp9sR2Pg8ZYkoWVzaQsKnwek2ZlBkz6ha4EeJymT7b2bPN+Uc8Hyz/gN9O/m3cgItksSgL066adlBkqpLgjSo0mwPZIebOaXfy8vyXAaKCNzq16MSOe2PrHQohDn7SEAtrjGOX1uYiesXyEikp5mJ4Q2Sh+OgjUz4kXuDG6NHmIrzbnZwT4+JieOEFEwxSMXr6uedMOrkmpT46X7yFsG8u7PkRdn8L+avAk2dKbaDCtYudbcGZAc524O4A7k5gcQbrF1vD9Yq9eVC8w4x2L82Bsr2mcVQSrItz6YGYXSgqMqVx1q6F1atNbcddu0ymjP37TRmfggKT9cFqNR2TofqQoWwQoWAOpUzARHq6CfjIyDABCe++a7ZVWgpTp5oG1syZppakw2HWWVZmSsscfbSpRZmZaVIddupkpqenh7ettQkY8fvNPu7ebepRZmWFgxlWrDDz7tkT/XrtdhO80a5dzd+umpgzB37/e1OyJbLDt21bMzLgyivD+5OM73ZREdg2voxz1Z8gUCH6a+Df4KgHar5SCd446CTj2DV6NPzvf+ZxqEOkxtlxCjbAtEHhevd97jWfwxqM8BBCiOZMjl1hB3WfYWWZ+TIzzQl1Q2jM4I0Dy2H6sXW/sGV1w5k/QpshtV6F7pCJ2r0n9ok6vBeBgElP/uyzJojDao2+8NKihSlnetppJhi7SxfTFiopMW0ki8Wc6ysVLrcZajf5fKYtY7WatkBpqdnNH34wQdkzZlSa9LFq9fR5mLx6Mlf/9+qYi38Oq4Obht7Ey6NfrtH6Nudupt+4fjHZPCzKwpAOQ5j/+/lVZkepaMnOJdz5vztZvHNx+T6m2lMZ0XkEl/W/jD9+80dKvCX4tR+X1YXNauPBEx/k7mPvxm2vp44WCd5o9g7q41ekhgje2PYZ/HJN1ceLNkPNoBNHm7plbExG8EbJbviqN3jza78fVbGmwtB/QM8byyfdOe1O3l78dtwAjsNaHsbmuzbX6HcxZMz7Y/jfhv/FXMi3KisndTuJ2dfONust3Qufd4VAvCwjCi7MMn2RtVXT/iWg463Z7MqLHxy4cCEMHVr73WkIPp/JCPz99zUrlVIdp9OUQf/xx8oDOBZmL+SE8Sfg8Se/5luqPZVlNy/jiDZHJH3d9aGqY1czL2oomqs5W+bEnZ5TlENuSS6t3a0bdoeEEKKZ0zp+Hd1Ky28k2e7dcNNN8U8or74aXn89uZkwUlKgWzfToVXxdW/dWvt0dAcVe5rJitDhDOBxM81baLJklAdg5MCJD8O+OPUvW1lhYg9QoZrFNpO9w5UJKZ2h1QCTvcOZYe4DPhPwESE11WSAGDw4zv516AD7InoNg1ksAumZ7F2xqzyYw2qtPAhhe952XE/2whtZdzQDuAJO7HoSb50whxUrwkEjWVkmW8ecOSYw48CBcK3Jilk0LBZQ6dn4b+kDjiKwAB3NTZ0KPfbcReHEF6M6Wb1eUybmq6/Ma3fWw7Xkb7+Fc86J/S6NHAlff22CSpI9MiA1FUhrad7fisEbJTvMRfSaprZ0ZdZgZERTzBstamPbtvDjoUMTqw0bo2yf+T0KaT1IAjeEEEI0P5VdXa/NVfcqSjTWWi0u8iQc7FC2H2afnZwRyf4S+HYUnLOyPI18TcUN3IA6/U0tFjOw4YYbTPD3l1+a2y+/mLaqUvDNN/DFF+Fl7Hbo2NEEcnTtagK3Q4HvFotpi3i9Jjh++3bT9tmxI7rd4HI1TJbAmrio70W8uehNZm+eHdWu8/g9/Hvxv3n85Mdpm9I24fX95bu/4Av4YqY7rU7ev/j9Gl+gHNxxMD9c/wNztszh9qm3s+XAFoq8RXy/9XvmbJ1DQAewW+w4rA5uPeZWHh75MK1crRLfQFP4fjZkUJgQyXRgRfWBGz2uhWPG1azMa31aeDvECaJIGn8RLLo7Knjjb6f/jQ+WfxA3eGNfyT6mbZjGmF5jarSZDfs38O2Wb+NmYHBYHYwfOz78e1u40bTZ4wVvpHYDe8sabTsZMtL3sDsvEx2nv2njRjjqqKaddeOZZ0xQZjIDN8D0ka5da7IYT5wYf55hnYax494dnDT+JDbmbow6dluVlbYpbblpyE3YrfaYZUu8Jby28DXyy/KjPjt2i52BmQP59rpvTZmdZkCCN8RBx+v3snbf2rjPue1uFmQvOChS4giRsIAPCjdBwToTVasD5gJoandIP7J2adqEqCGLBY49Fn7+OXp6To5J23rssaYzqL7cdFNs1g+AUaOSH7gRuW5fbJ8Nn3wCzz+f/O0dFOxp0KZCJMW+e+LPe8AP56+vv32ppIPKkrOb9u0TW0VmWiYum4uyirWAgPk75pHSIYuLendJaF2hAI7Q6DWAf837lPtn+ijxRUd2KGXh+DNyuORs+O1vTYBQKEjol1+gZ0/45z/h4ovNZ7DGmQUqUVwMjz0Wv3H26qtmNF696TIWFtwcO33zuzDgqZqv7yLpHDwU7dsXfpyeXsvjjmd/9P9bHV2nfRJCCCGavWRfGK6tRPdj7vXg2Vf9fInyHICfr4LTvkneOpOoUyf4wx/MDcxggxUrTODF1q2wfj1s3myCPHbtMtn3li417ZbQDUx7JnQLZRJs0wZ694bDDjOlFLt3N8EfTc34sePp/o/uMdNLfCUc9o/DSHcm1qDyaz97imKDbRSKe469h95te9d6H0/pfgrLb1nOF2u/4K5pd5FdmE0gEMBlc3FF/yu47cinObAjk3nfmUyMAwYkeK7bFL6fTWEfRNNWH0FGIXUJBvzluqoDN468CwY+1XQCN3J/heyvQXurn7cudHRnaJojjdfPfZ3LPr2MgI7u3yr0FDL2o7G0S6lZCtm80ryYDEdgfm/vGH4HPVr3iJpa+b4Gqn4+ETUaHGRMuvMyhj+ygGJvC/zRFba48Ub4+GMzSKohSozX1IoV8Le/JT9wI6SsDD79tPLgDYB2Ke1YedtK7p95P68ueLU8M5Vf+8kvy2du1lym/XZaVNmwUl8px//7eEp8JVGBG26bmydOeYL/O/7/apUBpqmS4A0Rw+cz6XIWLYK5c82XOZRSOyUF+vY1tROHDoVTT234iOuVOStxWp1x0+qUeEuYmzVXgjfEwS9vNWz7BLZ8EI4uVbbgCYkGLOa8xFdsoks7nQPdrzR16axNbBiEaDZefhlOOim2Dt6ll5oyE4cfXj9BFLt2wfTpZhRQpLQ0eOed+suA0aEDHHMM/PRTdBbGPXtMSZV7722aJ+EicQ6rgztH3MnzPz1PqT+60aiUYvLqydw54s6E1qVUbBaACUsnxB2Z4LQ6+fOJf6Z/e9OZ+vTT8PbbZh1FRZCbC9dcYzpgR4+GCy4w6Y4zMkyQh9drRsilpMTPfFNSYhpLFovJOFJcDIsXm8bT0qVmWsVG2syZ0KNHPX6mHS2hzz2w5h/RnSPefJh1Gpwxu1FGS4iDS2RAndttvgc1VrYPIuuXp3av624JIYQQojoK6Af0D96HTvtygVXAcmBNEraTuxR2zYBAElNxay/k/AR750G7Eclbbz057DBzi1Lxwmmwbe1rl8n673ehtQkUCGXicLtNZo5410A8fg8HunUxIzkqSPGCwx+7TLXibEgDeZWMWrYFIK11ONtDpxaduKTfJXy44sOYeYu8RRR542SKrAGrxcpDJz1Up3WAaWNe0OcCzut9HuMWjGPyz0vosOwlvnixJR8WhzMvBgKmPTdoEDz4IJx3Xvx238SlE7njAeKMW4cOhfDdBOhUUOfdZvwguGcUBOJ8HtI8sOmf0ACVdMXBLFmBG+nAEUBPoBvgBOyY37QyYBuwAdgIVFVVZPdu2D0H8qs48GSebsprNpXADYCFd4A/zsi2ZAuUweQOUYNmLupzES0cLcgry4uZ3RfwsaswOQNsLMoS+3ub3hv8sYOuACjeDmV7wNa99hutxeCgPsDyS81gwx9/NAMOQxl5CwpgzBg47jh44gk48UTTl+d218+11Px8s95EMn14vaYfP94AyWSqeO0gHouy8NyZz9G/fX9u+eoWin1moVJfKT9n/czvvvgdEy6YgFIKf8DPRR9fxOq9q6OuC6faU/nw4g8578jz6uulNBoJ3hDlFi+GceNg0iRzzlxaGj9F/vr1MG2a+bHx++Gii+CWW8yPUUOYlzUPfyB+S8Ab8DJr0ywePfnRhtkZIZJJB2DHl7D0ASjaai4shNLLxxv+H+LZB1vehazPAW0ujvW5BxytGmCnxaFkyBCYMgXGjjUXfkMnpbt3myCHf/7TlDDROnkBFT6fueBss5nOi0iXXRa/FEYyvfWWCVaseNL5+OPQvz+ceWY9ZysQ9e62Y27j+Z9jU6mU+EqYsHRCwsEbFe0u3M2qnFVxnzs682j6t+8PmH7Uf/7TNOgmT4b33jPZNxwO8z2bPNncwHTYdeligix69DDpjkPlVazWcNDGnj2waZMZYbdlS2ygxtixplZ15Of6//7PzP/Xv5rvcMskx1EEAmAZ8CQUboasL6IDOHIXw4yT4MRPTJ3SZGaU8peabFWiWYgMpAul+K6xsn0QSstpa9G0OuOEEEKIpigzs/YX3hRwOjAWc3XXSXRFuwzMhbizgSJgMvA98a9GJ7IPi+6pnwtb/mKTRv7sX5K/7oZQyd/Otnc3ffvWbFV3TbuLN27IwR6na7Z9Eax5BVKTMCj87lEw7hiwVPgs+C3Qogz2TtRExs6/c+E7fL7m87jB83X11rlvkeJI3jljSbGVRa/dwdyPTd96aKBKxYtp8+ebTI1t2phR3MceG/386YefTmaJlW1pfjwVrvJsscEp18KiN6FFHWKZ/ncE3H4OlMTJAuL0wTXLwNk2wdSX4tBVl+NIb2AMcCTmOOLFHEvildAciAnisAMlwFpgKrCuwny7dsHiMaZESDwpXWDkZ02rrbh7DuxfSPwDZD2okInCYrHwxeVfcMrEU+p1s8+e8SzprgrZkhytoOuFsO3j4MDWCpY9AsNfr3k53jo67DAz2HDRIpMV+qOPTB9FUZH5bf/lFzjrLBMcedxxcPzx5v+9eoVLl5WWmnktFvP/UDZfpUw/Wujm85lpDodZX16eyaT144/w3XdmMP6OHdXv85NPmnK0uoE+Rom4ZuA1HNH6CM754BwKPAUEdIBibzGfrv6U7q268/gpj3Pz1zfz3dbvyrO12JSN1u7WzLxmJgMyBzTyK6gfSjeld6kRDBs2TC9cuLCxd6NRrV4N99xjahxFRoglymIxUV3HHAP/+IeJCq5Pl396OR+v/Lj8/woVlSanhaMFeffnNasUOeIQsGsmzLsJynLAV1i3dVndgII+90L/R5pNJg6l1CKt9bDG3o+moLGPXWvXmowACxeGMzOFtGljMgb87nfmZLSkxJxUJjqav6wsvExxMXz4ITz0EBTG+VrMnm0yQNW3994zrzde1PAjj8ADD4RHKSVDYWEtAkKqO+bV5/leVds+SLZ72aeX8emqT2PSPzqtTrbevZXMtMwa797rC1/nj9/8sTz1X0iaI40PL/6QzbmbWbJrScxy7VLa8fhJT7FogZ1ffjHnaWvXmiCMnBzzWXM4zPlaqFRLKL2xxRJu5HkHvoEvcx4+PzjskJoC6S2hfas0fnnsJebNtXLLLSYoF8IBHmlppjF54YVw8smmj6WkxKy/qmwfIX6/md/nC58j7tgB335ranIT8MPyx2HN300N8Yo6nwdHPQCtBpkgRnstoqP8HlMLVfth49vQ9081X0eSyLErLBnHrvbtw4M877vPdDzUuHTKskdg5ZPmcUo3U8O+Np8zIYRopuTYFdbY7a46aaxz9EgHlsOPl5vBKZVdIKvImmpG2J7woSkTWxN758Ks06tOgV8X1hS4rBYZHJrCe5HEfVi7dy3HvHUMBZ7YlA5um5trB17La+e+VtM9jDI3ay6nTTwtbiBGij2lPD16RdPWT2PMB2PqtO2Kjso4ihW3rkja+hYtgnPPhQMHajby2e2Gu+8257+R7bFCTyFjPxzL3B1zY9qeTquT4Z2HM+uaWditNa83uGTnEk76z0lxM5e4bW5eHfMq1w++vsbrrQ9y7Ip2UB+/wLTpt02CFU9CSRb46pA9x5YK7i7Q/2Ho9hvTT57zM3x7VuXrPf49M68lyfWhP6im7+7KSn6PtYavj4L81cndn+rE2Z9TJ5zKnK1z6mVzHdM6kv3H7PhPHlgB00dUfowf+i844oYGD+CI5PHAvHnwzTcmu+2yZeb32mo1z1X8zU9NhY4doXNnc2vRwvS72e1mOa/X9K15PCZQIzvb3HJyYge2uFwm40dVli0zQST1VS6lopqe4mw5sIVTJ57KzoKdlAUzraTYUzjz8DOZsWlG+THOZXPRq00vZlw9o1b9tU1JVccuCd442A9kdVBWBn/8I4wfb34AKtZmqimlzI/EJZfAa6/VX9rtri91JSs/K7zdCsEbbpublbeurFAXS4gmypMHC2+H7Z/Fv4hVF9YUU7PtxEnQ9uBvv0hDLKypHLtmzjTZAhYsMCeiFYMb2rQxpbb69IGBA2HwYJMtwOk0J6JKhU9Ed+2CX3+FJUvCF6s3b656+5s3m5q7DWHCBLjttvgBHL17m1qBY8aEj4U1FQiYoI2CAhMQMn58DVcgwRt12u7SXUs5YfwJMZ1dqfZU/n7W3/nDsD/UePeOfftY5u2YFzO9Q1oHdty7g2FvDosbvJFiT+HdC9/lor4XxTwXCJiG2ubNpuHm8YTLqAQC4cCOIrWLuzZ3x6tj00q6bC6y782mtbs1ABs2wNSpJsPN4sVmHoslHICRnm6+Z507m3raXbqYEklpaWZbNpvZvtdrUjVu2gRZWSZgIzvbBJ0UFpp9i8rolvsr/HItFKyP35mf0s2UAmt7DLQdAel9QFnip8BWFhO4WLITcpdAzi9mRMqeOSaAo7IOkAYgx66wZBy7evQwnymAO+6AZ5+tRQamhXfAulfM4xY9YdQisCdWB10IIQ4FcuwKayrtrlpp7ICBHVPhx0trGUihzMWXk7+EzFMSX2z6CNg3vxbbqwFXZs3Tqzf2e1EP+/Djth85+92zy1OcR3Lb3My4egYndDuhxusFKPOV0fuV3mzL2xbzXIo9hasHXM3r575e6fKnv3M6szfPjpmuUFhU5VHofh3bMW5RFrLvzU7axaGffzaB8hUHwSQqJQV+8xv497+jAzj8AT+3T72dd359J6ZNm2JL4YI+F/DeRe/VaKDjtrxtDHp9ELmluVHTFYo0RxpfXvElJ3c/uXYvpB4k89illGoDfAx0B7YAv9Fa58aZbxTwT0wOiLe11s9Ut7xS6gHgd4AfuFNrPT04fSgwAZNbYipwl9ZaK6WuA54HQmPqX9Fav13dazioj1/bPoN5vzclq+o6wDGSLQ2UHUa8afoNVj0bXU4zJLWHCfC31TLV7+QOMVkrElZZ30XWl/Dzlcn9e9Ryf/JL82nzXJu4v5l1tfzm5fTP7F/5DFs/hrnXV3INRUHf++DoRxskY8ofptzId9t+jPuc1WLl3QvfZVDmENatM33cO3bA9u2wcSNs3Wr6wffuNddoXa7wQKzyV6PCh+fQgK3i024m0G0OVgtYbWCzm8FadjvYbRa+vP49hnQcEnefAgHTR7+uYhaaelSbU5z8snzO//B8FmQviDmeQTiY46NLPsJlO/iz7FZ17JKyKYeotWvh/PNN53qyIq20Nuv69FOYMwe+/NJcrEum/LJ8dhdWffCzWWzM3zFfgjdE05e7FGafBd4CM0I42fzFULQZZo6E/o9Bv/uqv8ArRA2ccYa57doFn31mOhB+/dVcSLNYTAq3n34yt9pISzPrKSiIf8LXUJHCANddZ4JQzj3XBHBEbnvdOhO42KOHObaefbZJZ+p0movfKSnRWTlC9WtD9Q7XrTOBMDNnmrJkgUAtgjdEnQzqMIgj2x4ZE0xR5C3iP0v/U+PgjX3F+1i6a2nM9BR7Cn8+4c9YlIVXx7zKGe+eEdMYKfYW8+xPz8YN3giVTenSpertPz7ndSxbMd1Bkdu3pTCy+0iOGndUzDLWC6x8/c77dPKOZNEik0Zx82Zz277dpOw9cCBcqqJiwzKUAcRz9Jv4T3oc1Q6sg01gV4rVNCxnbnyHM444wyzQegCMWQJ7foTVz8HO6WBxgS9YmLZ4G2yeaG4h7k7mZnWaebXPpMX2FZkgkEBssIpoXrp2DQdvrF8f/h2tkVDJFACLI+kXTfLyTEDU+++bNKklJWY/HQ4T3H7CCSb99ahRUnZLCCFEM7XpHVhwcx0GqGhzgWrOGDjuHeh2SfWL7JoNB1bWcns1UNsLcs3Mid1O5N9j/83vpvwupj1T4ivh8s8uZ/0d62t1YeWRbx9hb/HemOkuq4uTup3Eq2NerXL5aVdNo88rfdh8IHo0SGtXa7bcvQVHnOy0T//4NM/++CylESV33DY3n176adICN376yfQV1DZwA0xfxKRJZgDmhAnhAA6rxcpr575G34y+/N83/4c34ny32FfMRys/4qftP3F468MT2o4v4GP+jvnlI59DFIoOqR2Yc/0cerftXfsX0vTdD8zSWj+jlLo/+P8/R86glLICrwJnAlnAAqXUFK31qsqWV0r1Ay4HjgI6ATOVUr211n7gNeAmYC4meGMUMC24uY+11rfX70tuArwFMP8PsWVWkyUU+PDLtSazU2XBB0feDpY6XDatj+PE6ucaPnCjEumudF4Z8wq3T709JoDDoixc3PfiSn/7tdZ8suqTmN8Wq7LyuyG/qzpwA+Cwy6B4B/z6cJxzDA2rn4Vd0+GY16FVf9NvZIlXX6cO/KWgNT9vns7aA1lxZ7EqK1PXT2VIxyH06WP6kytTUmL61cvKTB+yzxc9QMtmMzerVTPwk4mU+UvxY7r7PEBx8KWnkEJWflalwRuff24GWDV16c50Zl4zkzum3hETkJhiS+GPx/2RJ0554pCouiDBG4egadPg0kvNCV99BHiXlJhO/uOPh//8x0QEJ8vC7IW47W68ZZUXTyz0FPLDth+4rP9lyduwEMmW9SX8dHn9pfOM5C+BFX+BvJVw7L+Tn/JNHPI6dDBZKW67zVyg2rjRZM9YvdqkBF250kQVa20u5IYu+oaiiCPr92VmwpFHwpAhcPTR5gR3wgR4883YDFFTp0LPnrVImV9Lxx5rLhr+5S/wyivhIIyQzZvhn/80NzAXGU84wdRATEkx6e/KykwWgrw8U3Zm8eIK2QhEo3l45MNc9/l1Mel/l+xawr7ifbRNaZvwur5Y+wU2iy2mQQpww+AbADiu63GMPGwkMzbOiGnwLt+9nHX71tWqQ8wf8PPK/Ffibtttd3PZUZcxZ8uc8jqRkR6b8yhzrptDr17x1x0IQG5uuFHp9ZrvZXlj0hZg0HuPsLdkDxrwBW8AdmUnIzUjdqXtTzQ3b6EpIbbtU9PY9hwwGaS0P5yZoyTb3Kqi7GaETMBngjtaxgaqNFeVjfyKeF4Fnx+DaeNfp7VeXNWylY0aU0q1BT4FjgEmNFRn4hFHmFKPYEYu1jhwA8xnI8TiJFk1g7//Hh580GSjcjpjU5aWlJjbF1+Ysl8ejzmufPONCewQQgghmoW1L8PSPycns6i/BH65Brz5JhV6ZbSGRXclXppFJMXl/S9nU+4mnvrhqZgAjv3F+3lo9kP8/ay/12idS3Yu4ZX5r8SUS7FZbPRs25PJl03GWs2FOIfVwYcXf8ipE0+NWo/H7+HjlR9z45Abo+Yv9hbz0tyXogI3HFYHo3uNZkzv5JRgmT+/7oEbIcXFZvCM1Wr63SPdOeJOijxFPDj7wajpAR1ga95WtuZtrdO2XTYXv9z4C4e1OqxO6zkIjAVOCT6eCMyhQvAGMBzYoLXeBKCU+ii43Koqlh8LfKS1LgM2K6U2AMOVUluAdK31L8F1vQNcQDh4o/nbOxe+v9D0A9THAMdI/mKTeaMyHUc3rb7zoq2wr2llUbl52M3M2DiDr9Z9hSciO6rD6uCI1kfw9BlPx13ug+Uf8Pnaz2P6q3q17cW4MeMS23jfe02G8R8uAW9ebHbW3KXwzbHQegj0/SN0vQj8ZWbgRm2zqXiDjXsdgPWvwbpXGBHYQWUFtfzaz6+7f01o1W63GQxYnZyivVTVd6G1ZlCHQZU8Z0p+xytJ3hTZLDZeO/c1js48mnun30uZvwy3zc2/x/6bi3pfTl6eKUETyn6dmpq8UuZNSTN8SaIqH31k6o03xGjl4mIzUjk3F/5Q82zjcf2y/RdKvFXvvEYzZ8uc5Gywnlz52ZWs37eeBTctaOxdEY1h3Wuw5I/JL5NSFX+xKc1SuBHOqmUaBCES4HCYNGx9+wYndOgAu2Ojzn3tMtnwwy6cTnORy+GAli3jB2L4fPDee7EXwt59F265peGCN8CMkn7uOVN27LXX4K23TCBGSYm5sB1p+3Zz3K2p+io7Jqo29sixOG3OmOANh9XBlLVTalTLd+LSiTF1gW0WG1cPuJp0Z7g8w79G/YsBrw/A74sO3vAFfPxr3r94ZcwrNX4dX6//Go8/NiIo1Z7K82c9zzUDr+Ev3/0lZiQamNrSWflZdEmPn9rDYoG2VcSwzNg4i9I4QYlWZWV0z9EM7FBFSjZ7GnS9wNzANI47d4ec/Nh5W1ng7XagrKZTxeoy2Tha9DGN+Jb9oWU/SO1mSqocAqoZ+RUyGugVvI3AjO4aUZtRY0Ap8AjQP3hrEL17m0a5z2fK9GRlmTI+NRP5Y53AaI1K095a4Eo/ZWVw553mmBRqY3k85vty7LHQq5fpkCkuNtkP588PH8+++04CN4QQQjQj+xYkL3AjxF9iSs22HQGtKgnKzfkJirYkb5siYQ+c+AAb9m/gwxUfRgWHF/uKeXney6TYUujeqntC6/IH/Dwy55GYwA2AdintmHXNLFLsiaXCH9FlBNcOvJYJyyaU71eht5BHv32U6wddHxUA8saiN/BFBvdighTeOPeNhLZVnZISuPDC5ARuhIQycJx/vll3pAdOeoBebXvxm09+E1VmPMRusVdZPsbr9xIgEDO9c4vOrLp1FemuQ6LcYKbWeieA1nqnUqp9nHk6A9sj/p+FaWNVtXxnTGaNyGU6A97g44rTQy5WSo0E1gH3aK0jt1tOKXUTJnsH3bp1q/ZFNhnbPjHZMBqyn7wy1hRIO6Kx9yLa+tchzneysY07ZxzTN06PCt4o9ZXyyvxXeGjkQ6Q5otNMaq15bM5jFHqiIwjcNjfvXfhetYF5UdqPhPPWwYLbIGsy+L3EpJ7NXQw/X2Xe09YDoM1QyDjRnE+kdAFfMeFgCEVUYISymmCPgvXmHGPvL7B/EeSvLs/YcqwLPixJiVvaA2DN3jWJv54EbNi/AZfNFXegFoBSiq7pXeM+9803B0fWjYqu7HUre5eO4KX/zqFPye+499VW/HaPCV60Bj8ufr/pj+/a1ZRrP/54GDTIDKasTVnzpkSCNw4hb79tOhYbMs18SQnce6/pXP3Tn+q+vlmbZ0WlfqvMun3r8Pq92K1NKEoyyB/w8/mazyn1lbK3eC/tUto19i6JhrR1UsMHboRUF1ksRH2IE7gBYNu7u8q0cZFCJUgqBm8sWwYffghXXlnL0dd1kJkJjz8Ojz1mLsS9954pe7Jxo9kXn890qFTH4QiXV3G5zGu9KLZahmgAVouVPx3/J5747omoxlehp5AJSyckHLyRV5rH3B1zY6bbLDb+dHz0yVCvtr24esDVvLPsnagGmDfgZcLSCTx35nMJd1CGPPvTszEBKACZaZlcM+AaLMrCP0f9kys+uyImwATgrUVv8cSpT9RomyEvzX0ppiEOYLfaeeGsF2q2MnsLyNkf/7kDAbhYUlZXUNXIr5CxwDtaaw3MVUq1Ukp1xGTVqNGoMa11EfCjUqpnPb+uKP37m0xG+cGYnpkz4cYbo2t+VytyFFXAQ7UBHJWmvQ1QWgojR8KKFeE21oABcN99cN55ZoSLxWI6Fvx+83+/36Qsfe45WJPc/hwhhBCi8XgL4fsL6qevw18C358P52+M//z6100ZPdHglFK8ed6bTFs/jV2+XVHPeQNenvrhKdz2xBrrXr+30j7fGVfPoH1qvOvnlXv+rOf5bPVnUUElBZ4CPln1CZf3vxww2Tie/P7JqPZfqj2VV8a8krT+2gceMAMbk6242AzQrBi8AXBJv0tY8oclnP3e2ewr2RcVnKJQ3DXiLjqnd45ZbvLqyfy8/WcCESNT7BY75/Y6l09/8ymWGp10N21KqZlAhzhPPZToKuJMqy6lX2XLVLWuL4EPtdZlSqmbMW2y0+KtXGv9JvAmwLBhw+oh33o92DoJ5l5Xu2OHuyO4Mk02xUCZabeV7Kzb/qR2M5k/4pRXahQBP2x4Iza7RMIUpB1uBrsUbUtq6ZXMtEyeOeMZ7p95f1TfUoAAby9+m7uPvTtq/lmbZ7GzIPr9cdlcXDXgKoZ2GlrzHXC0ghPeh/z1sOKvJgjIYo09H/AXm8wue+fCumDZLasL0vuCPT04GMhtsmr4S0xZlLIcKFhnplVikNP081WmrpmOKtqwf0NM1t5Ifdr2qbSUyKOP1i7rRrt2cOutcOKJ0Lq16ZdfvNhknN4eN4Ss7gIBk6n05Zdh+nRwOodSXDyUuRExlhUzc0O47PNXX5n+db8fLr/c7P/gwdFlnw8WErxxiJg1q+EDN0KKi83FrboGb2itWbxzccz01u7W5JXmRf14uWwulu9ZXmmNp8Y0e/Ps8ijyD5Z/wJ0j7mzkPRINZtfs2p+QJktTiGIWooYsFhOAeOWVsQERd91lSqz06dPwARxgTv5GjDA3AJ3ZAbUn9kLfXmsmJxyxC6vVZArp2NGUfDn8cOjWzSzfNX6AtGhAvx/yex6e/XDM9B+3/cgfp/8Rp81Z7TpW7FmBjlOXbljHYRzRJnYEx1OnPcX7y9+PGSSglOLjFR/XKOPHxv0b454rpdhTeO2c18pHMpzb+1wOb304y/csj5qvzF/GuIXjeOyUx6ocjRVPTlEOszfPjplut9i5tN+l9GpbSS0WkSxVjfyqap7O1SybyKizSiV79NcJJ5j0mCGzZpkGeXpNBgCqCsEbtWzFa23KQ0YGbjz4IDz0kOksqKpv+5pr4LLLzPxCCNGcVVZ+K858NSrfFXzuAeB3mLOoO7XW04PThwITADcwFbhLa62VUtcBzwM7gpt9RWv9dpJf8qFr/k3gqSTwNhkKN5lsWBdFBwjgKzGjbpNUBk3UnM1iY8nNSzjspcOiRmCDyY5c2ajkRL065lX6t695orc0RxoTL5jIJZ9cUr4PhZ5CHpz1IL856jdYlIWJyyZS5gsH0VuVlSEdh/Dbo39bp30OWbDAlICtr/74qtY7sMNANt65kYsnXcwP234o/xt4Ah7eXvI2S/+wlK4tw50Qr8x/hQXZC6ICaFJsKbx5/ptcdfRV9fMCGpHW+ozKnlNK7VZKdQy2fzoCe+LMlgVE9uJ0AUJj2ytbvrJlsoKPY9altd4XMf0t4NlqX9zBoqb95I7WcPi10OkcUxLD5ga/h/L4F6vDXHjfvwiyv4ZNE8FTw8gpi8M09OrClVnFAIAqNx47ac+30WU/E5XSBQY/D53ODU4ImCCX/NWw7EHITk5FnluG3cK4BeNYvXd1+bRibzF/++Fv3D789qjghke+fSRmAJHL5uKFM2s40Kei9F5w/Dsw5EXI+hw2vwP75pnX64sd2ASYz0mtB7hawZbCUW5flce3Ym8xhZ7CmAwktbV231qKPJUHqh7X9bi401evhuXL4z5VqV694OGH4dJLzf8j+9uPP94ERMycaQY1Lo7tgqyVsjJ4/nkTGFJaGg42iSxXngiPJ1yefMIEkxE7M9O8nuuuO7iCOCR44xCwfr2Jwm2MwI2QZGw7Kz8rbhrwXm16sTpnNfmecFptX8DHvKx5TTJ4Y9xCU79LoXh1wasSvHGo2L/YjBSR4AkhamXsWDjtNJPqzRNxKCgqMhHA06ebtGhpyTknBsyJYk3XFy9wA6Cdfzdr1yZhp0S9au1uTY/WPVi3b13U9AABXpz7Yp3WfWHfOEOigIzUDP58wp959qdnYzJ+PPfzczUK3nh5/sv4A9FRIArFwMyBnHXEWeFpSvHy6JcZ88GYmMZmma+MGRtncHbPsxPeLsD4JePjRvlbLVaePj1+vVORVImM/KrNSK86SfborzZtTMM7NMpj2rQaZt0AtDU1/IIDZSRUOiWOr5ecw+zZ4XbOCy+YUpEpCSTLsVrNfE89VatNCyHEwaSy8lvlalO+SynVD7gcOAroBMxUSvXWWvsxZcFuwqSmnwqMAkJXKT7WWt9evy/5ELT1E8j6wlwMqU/xLoZlfQ6qAbu3bwWuSmLPf22uImRmwq5d1c/XgDqkdWDBTQsY9PqguKU6bMpW5SlXxbIlIXeNuItbj7m11vs1utdozj7i7KjSkjnFOXy17ivG9BrDY98+FnUx0Wlz8s6F71Q6erkmPB4TrFuf/fHVXdRKdaQy9aqp3DP9Ht5e/HZ52y+vNI+RE0ay5A9LaOVqxRdrvuC+GfeVDzZUKFo4WzD1yqmc0O2E+nsBTdcU4FrgmeD9F3HmWQD0Ukr1wAQFXg5cWc3yU4APlFIvYo5dvYD5Wmu/UqpAKXUsMA+4BngZIBQEElz+fCB8lfxglrcGvh+bWD95i17Q73447ApAgy2iwWWtMIrL6oYOZ0C742HAUzCphnWJ/cV1L71aMciwLjb+u/IAhHiUFfo/DH3vMxknLRWy0rceBCd+Ysqczb0OiuqWHcJqsfLuhe9y0n9Oiip5VeIr4ZOVn3DF0VcAsHTXUn7d/WvUsqn2VF4d8yotXS3rtA/lXO2g543m5s2HndNhzw+Q8yPkrwGU+XsEfCa7ivZTWJrKr9sGkFvUGqU0nVplc1SXldhtPhPIY3GYv6m/1Hy2Wg+EjJMg8xTc7UfS8Z9HsD0/fgqKFHsKm3I3MSBzQFJe3vI9y+MeXwHS7GkM7zw87nMvvhjdj16dM86A//7XDEixxTm9cgbHtJ1zjumnv+02mDgx8fXHM2sWXHutyVKVSBbrRPn95rrBpk1wxx0mm0eygk0aggRvNHMHDsDppye3rl5jmbdjXkwqIpvFxojOI1iVsypqeomvhG+3fMstx9zSkLtYrfyyfP634X+AuXCyPW87K/es5Kj2ldTtFM1DyU6Ydbqk8RSijt5/H045BVatiu6kKC42aevvvBOefNJcyEvk4lllCgtNGZM774R33qnzbouDzEtnv8Q5H5yT1HValZW7R9xd6fP/d/z/8Y+5/4gJpNiUu4kXf3mRXm2qz1rh8Xt4Y9EbMamGnVYn484ZFzP/yd1PZlCHQfyy/ZeoBmCBp4CX5r5Uo+ANrTUvz385KiVxaNs3Dr4xbkpekXRVjfyqbh5HFcsmMuqsQZ15phlBEQiYtJ1//7vJ8Jfo777HmoFT2UF7zblZFalOq3Lfh8+Vt7GOOAJuuaXmx57UGvYlCiHEQShu+a0K81RV+quy5ccCH2mty4DNSqkNwHCl1BYgXWv9S3Bd7wAXEA7eEMlWshvm/c5c8GoM61+v2YUtAHsr6DTaXNxTytSyz56WWOaQvFrtZXJVUpq0sQ3IHMDUq6Yy9qOxMYPv2qa05d7j7o2b3W/OljnM2DgjKmuH3WLniqOv4B+j/lHn/Xrj3Dc44l9HlO9ToaeQB2Y+QEFZAfll4YGAKfYUnjjlCbq36l7nbYIZkdwU3qpQ2cx+7fpxz/R7KPGV4Nd+dhbsZNR7o3jhzBe4cvKV5RdeHVYHmamZfHvtt3EzRx4ingEmKaV+B2wDLgVQSnXCZIcao7X2KaVuB6ZjskaN11qvrGp5rfVKpdQkzPHNB9wWDDoEuIVw1qhphI9bdyqlzg/Ovx+4rt5edUPRAfjp8gT6yRX0+zP0fyR+IEJVbLXsFCzcXLPt1Cd/GWRNqdkyx46HrhdX/fptqSYA4ex5MG1wnUvNDO00lN8O+C3vLnuX0mAQZ6GnkEe/fZTL+1+OUorH5zxOiTcc3GFRFo5ufzRX9L+iTtuulD0dul1qbmA+c4WboGAj2VvzeOPdTvxncj927U3H7SwDNEpBIGCh1OugT/c93HH1Cq685ACpbTNMiRV3bJWlwR0GVxq8AabUSbKCN9btXVfpc0qZQVsVFRSYvvR4ZUbiufRS09eSSL+GxWL6M159FTIyzGCWmtq92/SjTJ+e3KCNeIqKYOnS+t1GstV78EZlqQ8jnlfB58cAxcB1WuvFVS1bTdrEAcAbQDoQAI7RWtdz6HfT5POZWsu7d5vOzYPdD9t+iKmjnmJP4aRuJ/Hqgldj5v95+88NtWsJ+2TlJ1iVtfz/voCPtxa/lZTGiGiitIaff5vUmnJCHKrS0+GHH0wU8LJl0SNYtDap1d55B37/e/i//zNRwqHRzdUJXYDbvx+eecZEDRcVSfDGoWhMrzG0cLSgwFPDTuAqXN7/8irrA6fYU7h+0PUx2T08fg/3z7w/oTrRXr83JngCoFurbgzqMCjuMv8a9a+YERJgOlB3F+4mMy2z2u2COUfLK4vtybZarDx2ymMJrUPUWVUjv0KmALcHL4qNAPKCQRk5VSybyKizBnXDDTBpUjiN5t//bkZRJPJb7/HA2k1tGWB1gM8LZXtrtQ97C9qycU+4M/v5501JLCGEEDESKb9Vm/JdnTGZNSKX6Qx4g48rTg+5WCk1ElgH3KO1julxT3bJrzrr0CH5V4BrmlWgqkwPyx8PZrJqBJ482De3+vnKKeh1Cwx6FgiYizsAPa4xI62XPQzr/lVljfukage0MrtFPiZENtE8ZcnM+53E7B+jeo7im99+w+j3R0e1MQo9hWg0/3f8/0XNv3H/Rh799tGowI0UewqXH3U5b5+fnKpGGakZvDLmFW79+tbyLBtbDmzhj9/8MSrrRveW3bnn2HuSss2dO+Gll6LL/TW2Pwz7A0e0OYILP7qQIm8RZf4ylu1axmnvnFY+AMBtczMgcwDTrppGa3frRt7jxhMsVXJ6nOnZmGtYof9PxWR4Smj54HNPATH597TWC4GY+kBa6weAB2qw+03f+tehcANV/uC5O8PIyZDer/aBGLWh/bB/CWTEL0HRoLKnmawPiRr4t2DgRgIjBCxWcLSBM36AL3vWfh+Dnj/zeT5Z+Ul58AbArqJdzNw0k95tezN94/SoQUNOq5OJF05MSpajhCgL+709ufv+nkyaZCaFBgV6i2MvkS/f0Il7n+/E3c/Co4/CvfdCvOb+Cd1OYNqGaTGDqABKvCVs2L8haS+hqiCREl8JfTP6xkyfMsX0iyfixhtNv3ptBqQ8/ji0bm1KyCZq2TKTdCA/H7yxf756UdeKSA2tjjmAqhaR+nA00A+4IpjaMNJoTIqoXpjG0WsJLBtKm9gLmBX8P0opG/AecLPW+ihMdH4DvfVNz0svmTQwNUmL05TN2TwnJjWQP+BnQIcBZKRmxMy/p2gPB0oPNNDeJeaVBa9ENQy8AS8Tl06sND2gaAY2vwN754GW97ipUEq1UUrNUEqtD97HbZEqpUYppdYqpTYEU/RWu7xS6oHg/GuVUmdHTB+qlFoefO5fwcBFlFLXKaVylFJLg7cb6/O1NwepqfDtt+binTvO9ezcXHjuOdOXdMIJcN99MHWqme73m5vHY4IafT7IyYHJk+Huu2HoUOjWDcaNax4Zq0TtVexUrKtEgjSfPv1pk064Am/AS35ZfrW3igEYIRPGTqh0m0M7DeWU7qdgidMkeOK7J5iXNS+h26PfPhoTYOu0Orn32Htpl9Ku2tcu6k5r7QNCI79WA5OCI7tuVkrdHJxtKrAJ2ICpl3xrVcsGl3kGOFMptR6Tzr48ED84uvlF4DqlVFacdl69OP54E8wXUlAAV1xR/UiNQADy8uDvr7aN7gQrqrwTpDIrtvfHbQ9/5447ToI3hBCHLqXUTKXUiji3sYmuIs606rpXa1MK7Eugu9Z6ADATk8kjdmat39RaD9NaD8vIiO1ranBNYeh+ZftQvAM2T4BAI3U87vjKpDRPhNUNZ881gRv2tHDgBoC9hbnYNeCvMGpR1Re+6prd/Ujg/4B/A88B9wVvfwPGAw8BA6ltVbeGU8Xn8uTuJ/PGeW+QYg9fASryFvHEnCdYv299+bSADnDFZ1dQ5g8H/zitTo7tfCxvnPdGUi/qXT3gagZ1GFQ+oK7YV8ze4nAQr9vm5sNLPsRqqcGF0io8+2zTHEh5xuFnMO/382if2h67xU6pv7S8TzrFnsKFfS/kh+t/OKQDN0Q9K9kJS++rOutGancYvQhaDza/1w0tazL4GimbVKTNExPPLNXrVjjyzsQCN0IsdkjpUrt9q6ClqyWvnvMqqfbw9gs9hTw25zGe/vHpqPK+bpubO4bfQe+2vZOy7URMmgQ9epj7srLqS06BGSxSXAx/+Qv06QO//ho7z+AOgysdbOUNeGNKxdRWbkluTEarSF3Tu+Kwxp4PffhheNBLVfr3r13gRkhqKtx1F5x1VvXzgimTcsIJsG9f4oEbDgcMHgzXXWfKz/7jH+b69+OPmxJlffrUvKRuU1ffmTeqSn0YMhZ4R2utgblKqVbBlLzdq1i2srSJZwG/aq2XQXmU4yEpK8t8cOs73UxD8QV8rNm3JmZ6mb+Mw1sfTt92fdlVGB3x7ba7WZi9kDMOP6OhdrNKm3M3s2Zv7Gvwaz8zN81kVM9RjbBXol4VZ8PC28GfhKvAVjek9zEdDMpmTt6Kt9c5tdkhSuouH+RcLnjlFbjqKlMTb+fO2JNRrWH5cnN7NSI5k91uli8pMcEbQsTz4EkP8sR3TxBIwqi7oR2HJhTA4LA5eOyUx3jk20fqvM2QIR2GcFzXqkeMPH3600zbEJ1JvMxfxusLX+eD5R9Uuw2Njko3HOLxe7jvhPtqtsOiTuKN/NJavx7xWAO3JbpscHpVo8a612F3a00pU1f1r38Nj2b85huTcemFF+J3OHi95nf/jDMgrbQtUVdE8lZBes06jgI6uleguXUSCCFETWitK+10UUolUn6rqtJflS1f2TJZwccx66rQR/gW8Gy1L05UbfnjEEgwF3eklv3AFUw/XpIdrEVfC5snJpjlVMGJH0PLo8FWRUY7exq0OBJOmgzfVlJCcBxwZS2Gbm77FJbeD6W7oi9aOivM1w8YkGYCSvo/Dj1/H5UZ4+HZD/PJf2MG7QMwagP8838137V4/tsH7q/km90lH75516TJrszVA65m0/5NPPfzc+WlIcv8ZVzx2RXM//18LMrC6wtfZ1XOqvI2l81io0frHky5YkpM2ey6Ukrx7oXv0n9cf4orXJR129zcNvy2pKW2P3AA3nqr6Q6m7JfRj19v+ZUz3jmD1Tmr8Ws/bpubB098kAdPerDhRsKLQ9P8m0w5kMq42sNZP4OjnckOUZ8szviZo9a/Af0frd9tV0dr2D0nsXlbD4HBz9cuQ4m14kGo9q7ofwUvz3uZ+dnzy3/Xl+xcwuKdi6MyU6Q703n8lMeTtt2qaG3Kaz/9dHT25pooLoZNm8wgks8+g7MjTg8GdhhIma/yz/PqnNW122gFG3M34ra78ZbFj3QY1mlYzDSvF2bPrn7dNht88onpK6+L1FRToqVnTzNopjLffAMXXpjYdWuXCy64wASGDB1qlrFYoEWL8DyBgLkmoJQJ8JgxA15+GWbObJpBlDVR38EbVaU+rGqeztUsW1naxN6AVkpNBzIw9S+fS8YLOdj8/vdN9ySxNlbuWYnD6oiJMOvUohM2i42hnYYyZ0t0Zo5ibzG/bP+lyQRvjF8yPu5FoAJPAeMWjJPgjeZo4e1Vn5BWx94KOp8LPa6G9iOD64roJLC6oGgbbH4Xtn9a+w6PQ4/UXW4mjjsO1qwxJ35PPQULF5rMGlVF7Xq9iUX1OpPXfhEHIZvFxu8H/563Fr9FgPCxW6EY1mlY3FrNuaW5bNi/IepYr1C8ce4bCW/3wRMf5Jkfn4nK0lUXky+bXO08AzsMpFt6N7blb4uartFxS6EkakyvMbRwtqh+RiFq4ZZb4G9/i5722muwbp0ZXeJwmCCOUMalVavgkktg2zbo06lNdDr03MXQ+Zwa1Tbu02kNpb5w78avv8KppyaeklQIIQ4hiZTfqqr0V2XLTwE+UEq9iAmc7wXM11r7lVIFSqljgXnANcDLAKEgkODy52OyTTVvbYBumL9Qd0y4i5twb7APKAC2BW/ZwFZMCY/qlO2DLe+BTnDIpC0Vuv8W+v0ZnBnh7KQWu8ngsepp2PoRRKRcr5KvCPZ8n9i8A5+E9qdWHbhRvp9uyDghsfUmIuCHRXfDpvHgT3CEna/Q3BbfA7tmwPHvmv6foC2twRPnnGNbS7hjPvTcX8ddVnD7GMhOj/OkBpcPVPt4FZCiPXryo2zYv4HJqydT7CsmoAOs2buGcQvGMfbIsdw3476odk8bdxu+vfZbUh01GDleAz1a9+DxUx7nie+eiNnuX0/9a9K2M25czVOz2+3mYlbv3ibD6J498PnnsHVr0nYrSvvU9sy7cR7nvH8u3y/J5vr2E1n95nCG3GUujvl8Zj/atDHnuCNHwvDh0RfMhKixwi2wc2bl2amVBU6dAc4GCNyAyktG+Qpg9QvmeNWQJVsiFWxIPKvViDejjhGNRSnFhAsmMPiNweWZYcv8ZVEZjVLsKYw/f3xCpYHryuczpUA++aT2gRuRiorM7/S//mXWC+a31G13R2WQirQlb0vdNwxs2L8BXcmBxWl1cnzX42Om//ijObZU99ofeQS6dk3OgJS0NNMvc2XFAr5Ba9YkFrjhdJoSLPfeawIwQseelnGyn1ks0ZlZzz3XHLO8Xvjzn2H8+IOvXEpIfQdvJJL6sDapDitjA04EjgGKgVlKqUVa61lRG2xq9SuT7Jtv4PvvkzOiuHt3OOoo88VQykRNrVkDG5JXrikh83bMixv40K+dyc58dPujSbWnUugNR9z7Aj5mbZ7FIycnbwRrbWmteWvxW5WmN/pm4zfklebR0lXX/IuiydjzI+ycnnhHRiRbKgx5ydRdDZSF03nGOxFL7w39H4Kj7jcnwT9fCQeSk5KrGTvo6i6LylksMGqUua1bBx98AF98AStXms6GRNPhud3mpLa0FIYMgbFjTWYPceh64ewXeG/5e1Edey2cLXjopIcY2yc2C/glky5h3b515f9XKM7pfQ5DOw1NeJsWi4V/n/9vrvjsiqiAVIWijbsNTltsVJHWmp2F0VmYFIrf9PsNh7U6LKHtfnjJh5wwPnmd1ArFexe9l7T1CVFR69amk+Gvf40uczVrFnTsaDqZhw41v/8zZphjQkh2bqfoC0P5a0xaXEcl5+GuTCiNTg3eqfVOOrTcxda93QGT9ePnn2ufZlQIIZqxZ4BJSqnfYcIDLgVQSnUC3tZaj9Fa+5RSofJdVmB8hfJdMcsHS4NNwgTX+4DbghkPAW4BJmDCFKYRDpq/Uyl1fnD+/cB19faqkykzs2alUzphhiKchAne8AIO4hdrBzP07XDAEzHvTuB7TFjNXuJvf92rsdMq0+5YOGWaySIaLwV+em8Y+i8zcnj2mZC7tPp17v3FjBiON2o6UtdL4Mi7apZKvibzVsWTB9+PhX0LEg/ciOQvhuyv4X/D4bTp4O7IQyc9xNuL32Z3Uex74nfaefY/1/LW+W/Vabe/Xvsl+ZOvhAplEcFkOZ742M9YXhtU7XqUUowfO56teVuZv2M+Zf4yirxF/HnGn3n313cp9YXPx1o4WjDn2jl0SOtQp32vzj3H3cN/lv6H1XtXo9G4bW7ev+h9XLbkXPgMBEwq90QvFLZoAbfeasq92u3mXNJqNcs//bTp4//LX0xZ9GRavx7+8hc3Cz6fiUvDO0pVmlr/l1/Cr6lHD3jgAdNXIiUDRY1teAOoYij8kXdB2uE1Cqqvk07nmRIpOk4GqdXPQ/ergvtT35dQ49jzHQnVz+pygckYFWeAUWM4st2R3DH8Dl5Z8ArF3mI0OpxdSdkYedhIxvQeU+/7EQjAeeeZa6TJrExQUmKyQOTmwp/+ZKb1y+jHz9t/jjt/Xmkepb7SOh9j1u1bV+kgL5fNxaAOg2KmT55cfcmUAQNMX0ay+jFcLjj/fBgzxpQwj1RWZp6r7vh4+ukwcSK0amWyedRGKJjjH/8wWVuvvjq6T+hgUd/f6qpSH1Y3T7VpE8FEzhOdNvE7rfVerXUxJvXvkIo71eTqVyZRIGBO+uryo9Shg/kRWrnSjFJ77z0TMTVuHLz7LixbZi6Q/elP0CU5ZbGq9e3mb8vT7IUoVPkFkb7t+mKJEx62eOfiSqPSGtKP236schStzWJj0spJDbhHol4F/DD3hto1zjNPh/M3mhNEqzO6DmtlrC7TuZDeF876BQY82XAnuk1Uc6u7DCbwUCm1UCm1MCcnp5pdOTT17m1Khi1ZAqWtO5CXrygtU2jCt92WDnTqBN26mfnPOgvuvhv+/ncT9JGXZzon7r/fRB6LQ1eaI43rB1+PPeL3NL8sn3d/fTdmXo/fE1N6JMWewoMnPljj7V7W/zIu7HNhTKrgYzodw457d8Tc7j/x/qh60mCi/9+56J2Et3l81+Pp265vjfe1Mr8d8FtauVolbX1CxHPvveZ6VsUmgN9vUmQ++6xprFdspOeXtIweeZu/jipdtMukR6+QIv3JSx8u70xYtsx0jhRVfrofV03nF0KIg43Wep/W+nStda/g/f7g9Gyt9ZiI+aZqrf+fvbOOj6Nc2/A16xutJ3V3dzdKaSkVpFjRgx5cD3KwAh8cnEMLpThFDi5VaKHu3lJ3S9tIkza2Sdbm++PdyGZndjeb3U1S5upvfs2Ove+sjLzP/dxPO1mWW8uy/FKg7T3LXvKs316W5d/KzN8ky3IXz7J7PWXDkGX5SVmWO8uy3F2W5ZGyLNcM68rUVJEy6G9yuyFlLsxpB2/FwNUmSEYIMWJRF26Upey6zYCbLDDdAr/1hfIuCy477H07OJeMplfABX+CqZaycKMYY7zItr5wZRCdBdJWeJcfUUJnhn4zwyfGqAi5B2FBNzizLrSxoWJcBZCzB+Z3hazNWI1WPp74MbFG32NyuB18veNrsgoqZ70xdflU8hSEG2a9meu6XacYJFLDqDcyf8p8miU2K3m+KXQVsuXUFlyegKnVYGXutXPpWD98zyNqGHQGvrniGwDcspvJnSYzvMXwsO1/4cLghRstW8K+ffDss8LhIj6+1MXNahXT+PGwcqW47w0H27eLgGa3bsKtLi9PIj9fXbgBIjk0J0dkMe/fD/fdB40aiezzcGSza/xNcLuEeEPNTSKmKXR70f91Itz0eBkklQukqwCWXhT4OhMuyjs3nJwXuAy7zgh93ovuexYEU0dMJd7ka9NjMpj4aELlxIXB8uqr4twZTuFGMTYbPPecSN4AGNx0sKI7L4hxwSNnj1S6zZ3pO1XLOtscNrondfeZ/9NPgcuG/Pe/lS+XUp7YWFHqvLyxzcMPQ0qKfxeMF18UY/ONG4cu3ChLXBx07w4bNsA111R+f9Em0uKNEutDSZJMCOvDOeXWmQPcKAkGANmejGZ/2xbbJoK3beJCoJskSTGSJBmA4QgV/t+Gb74Rz3WhEBcnMpaPHBH28506iRvFWrWEWikhQfwdEwNt24oA2f794gdVq1b4jkGJNSm+6rU4UxxdGnQBoEO9DhQ4fO8YnW4nx7OP+8yPNjM3zSTfrn7BzXfk8+6Gd6PYI42IkvIzFJ4OvF5ZdCYY8DkMny0yPEOxZdPpxHYdHoRL9og6sn9TZFm+0DNgV36ajboAsCyhCggrXHfZU2YFRN1l1RT981l4GAl06crZaQ3caZw8KexH9+0Tgytvvy0s+EeMCP9Nq0bN5pGBj3hZPAL8dvA3HyetJUeWoJe812ua0JQBTQaE1O5bY97yEo3IyCw9upRTud4aaFmWeXPNm14C11hjLO+MfQeT3lShNn+48gfF+UadkRhjjOJU/pgB9JKeDyd8WKG2NTRCwWgU2YhxFRyrMpmA2BalM3IPhHTfNWXQ/+jSxbM/4OabxbNYsIKM/Hz4UPupaGhoaGhUltQlQiSw+hrI3S+EAsFarfvDVQjuQsjaCD+Xc0M4vVA5U7k8be+GgV9UTDwRbBDq9O+B+9DuHiHgiDb2bPhjGNhOBHYGCQbZCfZMWDwKbCcZ3248/Rr3U7wXB3hvQwVcUcqx+dRm9p5R1jWZDWZeH/16hfcZb45n2c3LSsTdbtld4jIYY4jhwwkfhlVAEYjuyd2Z0nUKscZYHu7wLjNmwFVXQY8e0LUrXHCBcLtYvjxw4Ks8b7wRONMZoGNH2LhR6KL8ZTzr9WL5Cy+IcfhQKSyEm24SpWcXLBCvXUH8hJXIy4MzZ+Df/xYJLyuCrF6k8Tfn9O/g9mMT3+stMTYeTeLbQJNJ6u3mH4Nl48CRG9l+OAsg73Dpa1mGjCB+WO3uA1MQSZ9Rxmq08tmkz7ySjGKNsTw3/DmaJEQ+E3zdOl+HznBTUCAcmwH6NOqjKKgE4UB1MKvyJQz2nFGv9JdoTqS2tbbXvP374dw5//vs1k2UwwpHuZTy1KsnhILF/PknfP65uuBPkuDjj+Ghh8Ij2iiLTieuox9/LFw4ahIRFW/IsuwEiq0P9wDfe6wN/ylJ0j89qy0ADgMHEYGru/1t69nmFWC0JEkHgNGe18iyfBZ4CyH82AZskWV5fiSPsTpRVCQUTKGcmPr0EeVQLr1UBK6C+ZHExAhxx0UXiRPCkCEVbzcYcotyOZ2rHAgvzhKNN8cTZ/J9wDPoDKw/uT4yHQsSm8PGL3t/8bI/B9CV+/ntz9oflpO5RjVg1yuiPmmwSHoY+jM0uzI8GSGGWIhrCaNXiRtRjfKoCQDLEoqAcA5wjSRJZk+95uK6y6eBXEmSBkiSJCHqLs+GEvFHMX+PussaGjWIFrVaMLTZUKQyBjoGnYHFh70q8vHl9i/JtZc+0MeZ4nhq2FNIajVUA9C8VnNu7307ljLlsiRJYuammV7rrTy+kqxC78y6ZonNuKrzVRVus3ODzjzY/0GvNgHqx9Zn/737OXDfAa9pyx1bfNxBrAbxkB4u22ENjUC0bi0GoIO1+TQaoX59ILFL6UyXDQoqrn7X6WR+/11khZhMYgD89tvh8sth9WrxbJaTUzow7nKJ14WFsGyZsBINVxalhoaGhsbfEEcerLoalk+A7J2RzQ4uVz6Mo1+BM0Awq3ZPUQYllMSUQLidgcvFGmKhy7PRz0iWZVHO1p5FYPPOCuLMh+UTAfh44seKYu0CZwFvrX2LImdoopEXVrygmBwXa4zl7TFvh+yu1yi+EUtuXFIS4JKRiTHG8PiQx7m+2/Uh7bMy3NXga/osymNgrwQefRR++EG4UuzcCUuXisDf+PFCnDB9enClyc+dg1WrAq/XqZPI2K5du9RpIxCxscLa/tVXg1u/LIcOiczjH34QgbOKClLUyM+HzExRwlZDIyCHPla/bphqQ+PxobtI/5wM/5OUp0D0ex/MfhLkzqyBRQOh4FRwblMVxZknSqQs7Fs6L++wrxNHeSQDdHkGDNXLdaOYi9tezPDmQpTnlt0kxSXx8MDIP/yePRtcaY5wkJMj/u+R3MMn7ldMobMwLPE+f8npXZO6+sybPdu/wwUIQWCkEhjj44U5QDEPPeTfBeWll4QzRriFG2WJjQ3tGlqVRLwYkpL1oSzLM2VZnun5W5Zl+R7P8q6yLG/yt61nvj/bxK88NohdZFl+LNLHV534+uuKCzckSdSqW75cDDxarYG3KY/FIgZBFy6El18O/sYzWDad2oTV6Nsxm8NGu7rtSl63rdPWZ508ex6rjgdx5xxBftnzi0/WbowhxmeeW3bz6dZPo9k1jUhwbqewtAwaCQZ+CUkjwjuoIenAkACjVwvrOY2yKAoAJUlqJEnSAghZQLgLKK67/Du+dZc/RggVD+Fdd3mXJEnbgfupKXWXNTT+Rjw19CmvjIHcoly++uurktdOt5M5+72N5fSSPiQBRVmmDp+KQV8qjih0FvLuhndxlslWeX3N616WxjHGGGaOnxmyaGTqCO82QZSKOZZ9jEbxjbymJUeX+Ig3miQ04bpu14XUtoZGqAweLAbZk5PB7Ce5NiYGBg3y1Ayv09PbIvfY/0LKUq5VS+xv5MjSgYZFi4SovUEDuOMOYan6n/8IS+xbbhHPTSNHalmKGhoaGhqVIPcgzO8EKXMCl+QwJkLTydD1BRgxH8bvg0nHYdIxuGQ3DPsFujwtAmf6IAYF3U44FSBPTh8jXEUjIdwAOLcjcIZ2h4eh3L1qVNg3DdKWhcdxozyyE3KEK0ar2q14aMBDxCi8x07ZyTc7v6nw7o9nH2fRoUWKQahWtVtxc4+bK7zPsnRN6srsa2YjIeGW3VzR8QqeHvoMNhucPg0nTohgWLjEBUpkZ8ONN4pExOXLhahWKcjndAqHiVOnREnVTp0895B+WLTI/70ogMEAv/wi7iErmu0cGyuyhkeMCH6b2bOFo8jBg5ELZmqlUzSCInOj+rKWNwTn5qRGeYFhRTDVhgsWgd5P1Dh7F8zrBMe+A6dNlICpLE4bOHJg6xOw7GJvAWb6MpQrcJehySQx9l+N+XDChyUOUV9e9qXP+FG4kWW4+mpxno8Gds/wQevarX3ceUvWcdnZmb6zUu3k2fO83HbLopN0DG462Gf+t9+K65saSUlCeBfuOG5ZWrYU/69dC4cPq683dCg88EBkhRvFRKONcFK9f+EaFeLttysu3njjDXjqqeCz1fwREwP33w+fhll/sDZlraLqu25MXS9RR8+GPX3WKbYZr0re3fiuT61Ih9uB2eB9R2932floy0eq9as0agh73gS3I/j1+86AJhMiU4NVpwdTHSHgsDQIvP7fBK3usoaGRkUY1nwYSXFJJa9lZObsn1MiolhxbIWXM4dFb+GB/g9UuGxJeWpba/Pc8Oe87Bedbidz980FIC0vjT8O/VGyTCfpGNhkIMOaDwu5zURLoo9YxeawMW39NJ91/7vuv+Q7Sm88Y42xTLt4mmqtTw2NSNKvnyiFdfPNooxKQoJ4MC+emjSBV16BJUuEqIKEDmAoE6A69n3g7CYVatWC334TJVCaNRNieItFBB+++05kkfz730Lk/tNPIhBQvE7r1uE4eg0NDQ2NvxVZW+C33mBLEWVNlJB00Pxa4cZ5eRr0/wS6/BsajYOEdhDbFGKbQWJHaHIpdHkOBn4Fk7OU91eWjJUEHE7uOwNMdSt6ZMGTsQpkP+Muhljo+K/IjLP4I3MTbH8ysKCmMrhsJWVsnh72NPHmeJ9V8ux5PL/8eeRAabfleH3167gUgpJWg5VZl84Ky33+qFajePOiNxkSexNNN39G48YSCQninqhDB2G1npAgSnysXh04c7giHD8uyqJ8/33FBAc2Gxw4IAJM332nvt4PP0BuAEOaJ58UyZOhEhsrSp4HM47//fdw7bXi3jOSghgNjYA48/0LLNreE/3zdVkSO8Ggr/wLGB3ZsO5m+L03pC8FV4Eod1JRHDliuwPvw69N4YBCmauTC8AVIMjX8REwVr+SKYDIqpAkmiQ2xfmcC3kqDGo2WGSRS5JYHgGmTROuRvaK52RUCr1OT+va6g/2uzJ2qS4LhkNZh7zG6MoSZ4qjV8NeXvPcbtgVoMm77qpUl4Ki2NXjhRfUr7kJCWKMJByx6fORKpAga0SCvXuFDVpFuOMOuPPO8CqOYmPhiitgzx4xQBoOlhxZgkMhGF7WdQOERZHVYKWg3IVzf+Z+HC4HRn2I1luV4GTOSbae3uozv02dNnRt0JXvd3/vNb/QWciKYysY0WJElHqoEVbs2XD8O5ENEQwdH4MW10fW4kxnAGsSjFom6uAG2zcNDQ0NDUCUK3l66NPc/9v95DmEGFMn6Vh+dDmjWo3iq7++8hZpSnBPv/AUUryv3328vub1EpFErj2X19a8xmUdL+ODzR94iUZMehPTL55e6Tbv738/r61+rUTZ75bdzN43m+zCbBItiQBsPb2VlJwUr+3a1W3HmNZjKt2+hkZAkpMhzXfwLwGYCUzHwHKGc4zmGHDSg210y/8L6X6ExxXAiV3etrdnt4gBOKNvACQYJAmmTBHTgQPw88/w1Vewe7fIqjQYRAan2y1qy954oyhXWZyNoqGhoaGhERT5J2DJheDMUV+n6eXQ6y0hniguGaIPYAegM4ApMbg+HPvWf4mWegOg2eTIuW4AnF7k376+yWWRa1sNRx4sHy/uJyKNJwhqNVr5aMJHTP5+MvZyDmInc05y7U/X0qp2q6B2WeQsYuammTjLjRnpJT1Tuk5RTJgLhR9/hE+ff4iDB2GDuzTIVjaw43CI+6iffxbjzHfdJUQPpkpo43fvhmHDhKV+qEIGmw3+8Q/IyIB77/Ve5nYLR2p/dOwoXDwqG6RKTITXXxcuHGosXiz6WhGRSlISDBgghM5Go0gQ3b0btm4NrmyMhoYq53YIRyala5feIkp/VzVNL4Xe02Hzff7P4zl7YcloiGkCza+B1rdBXCvhpCFJwsGj2G3dZRf7kvTCLSpjhSgfc3Ke+nVUlj3OG36IaQK1e4RwkFFC4Vm9QstD4OxZkaBe0cT2cNGvcT/2nFF2Yj9y7kil9u2v7IrT7aRHcg+veYcPB3bUuOOO0CowVAS9Ho4dEyVj1YSY995b89wwookm3jhP+OCDit1IXXihcOqIhKopNhaefloMXP70U+X3t/n0ZsX5vRv29nrdsV5HTHqTj3jDrDezM31n2B40KsKs7bO8AisABp2ByzteTpcGXfjt4G/k2ktl2fn2fN7f9L4m3qipHJlFQFuzYhI6QtfnIjugUYzOJEqndH0O/nom8u1paGhonGdc2/VaHvj9gZLXefY8vt7xNSNbjuTnPT+XWAvrJB0T20+kQWx43I7MBjPvjH2H2+bcViLg2Ja6jb0Ze5m+fjqFnkFro87IVZ2vomP9jpVuM8YYw/9d8H889sdjJW3qJT1f7/iau/veDcD0DdO96mjHGGOYfvH0kMu1aGhUiACDPUacXMhi//to2hl+bgIFZURIB94XwlpDkKMYdwPX+X7n2wKPeyYZyHfHUuC0EoONGGxI24BtQHHJ37Q0jx2IhoaGhoaGHxy5sHikyNpVwpgAg76BBsNKRRvhRpbh+I+An+h3z7cin0F9Zo3/5e3uDVmQGTK7X1P/bCLIhPYTiDPHkVXg7ZricDv4bpcfm4ggcckuXhz5YqX3U1AgEgh/+sl/3fti3G7hGJGXJ2rU//gjzJsHzZtXvO3iEnc5Yfh4Cgrg8cchM1OUxitm06bALiFffVWaiVwZYmKEM8knnyiXcjl4EC67LLj3uXlz4RA3aZIQhRQVCdGxTgcul5gsFti5E958U7h5uMJQMULjb8bZrepuSYldhPAhWAFhJGlzqxBGrJos+uTvWmdLgT1viElvhYT2wsEjprkQpMguIdDI3Q/ZuyH/CATjtp5/LLAIsPm14bUlOg946aWqPTcNbDKQH3b/oFjeJNOWWanE8gNZB1TLprhlNy1qtfCat327f/FGu3bC8SIaLFmi3hejER59VHPd8Ifma3we4HDAZ5+J/4Ohc2ehXo7kDyM2FmbNEhbGlSElJ4VCp6+aPtYYS7ekbl7zOtbvqLiuS3ax/uT6ynUkBGRZ5v1N75cEVoqxGqxc0vYSRrcaTVE5e2YZmTn75pBvryKZoEboyLJ4WA/GHlPSwdAfQBcg+yWcGONEzdda3QKvq6GhoaHhhcVg4Z6+92D2ZC26ZTc/7/mZlcdWepU7sxgsPDnkybC2fVXnq2ia2LTktcvt4tE/HvW6hzDoDLx64atha/P2Xrd7WTDnO/J5e93b4m97Pt/u/BaXpyathETfRn0Z3My3zqaGRkRISgq8TjD7SL7Qe97+d/E7QFeeIGrpSkAc+dTnDLHYlCW+4TgeDQ0NDY3znw13imCRrBCdsDaCcdsh+YLICTcAsjaB248feb0BUDvCYw75xz1BNRWsjaB298j2oTyFGbD3zei4bijw45U/RmzfN3e/mYbxDSu1j/37RbmSH34ITlBQnoIC4QDRtSvMmVOxbXNyYNy48Ag3irHZhKCkrNPGnDlC+KDGsGEiYKYLUyTGahXByvI4HDBmjBC9+KNpU/F57Nkjyg4mJQmRRmKiGNO3WkUpwsREMJuhd2+ROJqSIhw9znckSaojSdIfkiQd8PxfW2W9sZIk7ZMk6aAkSU8Es70kSU961t8nSdKYMvNfkiTphCRJeeXaMEuS9J1nm/WSJLWIwCFHluzd6ufH2j1Aqkb55Y3GwLi/IL5t8EJEVwGc3QZH/we7/wM7noOdL4jrwsm5kHcoOOEGCJcSXYAgf+vbo5MMWkNITYUZM6DQjyFXICqbh9QjuQcGnfL32Gq0ciz7WMj73pm+s6Rsc3na123vk0S1ebN/B5KJE8N3LQrE0qXqfbniCiEW1FBHE2+cB/z+e/CWb3o9zJ4dHTua2FjRVmVUxetT1mNUuGDpdXo61vPOLq0fU1/xJGlz2Fh6dGnonQiRTac2cbbgrM98l+yib+O+1I2pS8tavrZgBp2Bn/f8HI0uaoSTtCWi/l0wtLpNKHF1ATyswo3OAgM+j26bGhoaGucJ9/e/3+uhyC27eXvt2yXuFAAd6nbwsSysLDpJx/uXvF9S49Lhdng5d1kNVh4e+DDJceGrG2rUG3nzojeJKzP4fzr3NJtPbeb7Xd+jl0qvXxaDhXfGvhO2tjU0ApKaKkSzSlN51NZLTYWGF4GhTFZu0RnY/ap/K/iyhCs5TBNvaGhoaGgEIns3pPwCboXosCEORi0Fa2OR7RtJUmb7L1fS+RnQRdiHO2O1/8BW0yuCD5KFi7+eq3iJWr0FGk+ENv+EtndD08ne9yUVYGTLkQxsMjCkbf1h1pv5aOJHldrH/PnQs6ewca9MYM3thtxcuPZa+Ne/gt/uttvg3LnQ21WjoED0pZgffvCfVPl//yfEEOFCp4Phw6F9e+/5//1v6a2yGmPHCieNSy8VIo1gy9HEx4vqhdOmwdy54vV5zBPAYlmW2wKLPa+9kCRJD7wHXAx0Aq6VJKmTv+09y68BOgNjgRme/QDMBZTSYG8Fzsqy3AZ4Gwhf1ka0cPhRE8U0BmM1q5sQ1xIu2Qk93gBjonDWiDTFQpGcPf4FirEtxXumUUKorhvDh8Ovv4pri9MpzuFnzsD06UJsVxG6JnWlwKEsUNJLer+lTwKxO2O36rIBTQb4zFu92n+s+NprI18ypZhVq9SXTZhw3l9HKo0m3jgPmD5dnGSC4aGHxPhgtNRV8fHeNnIVZfWJ1d515D0UOAp8rMElSVIUQwCsPbE29E6EyAebP/Ap4QIwvPnwEpHJ5R0v9xGc5NnzeHfju1HpY7UiOVnIHGvalOwJlh37LrjBfmMt6PV6ZLNh1NDphHJYQ0NDQ6PCNIxvyMVtLkYniZuofHs+vx/6vcR5I84Ux9PDno5I2yNajKB/4/4lbZd1+zDpTTwxxGcsqdJc0+Ua6sfWL3ld6Cxk+obpvL3ubfI8gy96Sc/oVqPpnhzl7EYNjXDQYJhv9vCeN4SIQyWzxYsZBC8iwc+6qamVPhQNDQ0NjfOczQ+CS8XxYuiPokxqoEzdcJC+TF2kENMUkkdGfsAxazM4/QyCtro5uhnJhRlw5HP/jiRlSWgPfd+HyzNg0JfQ6y3o+QYM+AQuT4NBX0Gd3oH3U455187zKdtcWT6Z9IlqJnEwbN8OV10lnCrC5fBvs4kM6/feC7zu//4nxCP+HDEqQ7G7RVoaHD2qvl7btsK5ItwYDGKcv5j0dHj+ef/uJi++KErXJCSEnvEcFwejRgk3lDZtQttHDWASMMvz9yzgUoV1+gEHZVk+LMuyHfjWs52/7ScB38qyXCTL8hHgoGc/yLK8Tpbl0wH68iMwSqpp9Ur9uVTrq5lwoxidAdr9Ey5NgfYPCQFHJPpqiAdLMvT/VLw+u9W/GDD5gugLFKsxZ8+KElL2IC/BIJwnTpwQIrQJE8Q5TacT58S6deGOO2DrVtiwAToGWZk4xhjjNX5WliJXUaXEG2quHbHGWPo19tV77dypvq9atURVhmiQlyfcmtQYrJn3BkQTb9Rw0tNhxYrg1k1OhqlTw6v0DURsLNx/P7RuHdr2S48sLakjX5YYYwy1LLV85ndLVrZnTM1LJacoerUni5xFfLfzO6/gCoiT6uUdLy95fUnbS7Aq1NXenrqdE9knIt7PipCen87wz4ZzOlfpPjIMBKhfXm0p7vfp30Hhu+pDhwdBisKgihpVIRrR0NCoWVRUTOePUMRw1ZgnhzyJxSAyGt24sZcZRLcarExsPzFibb877t2Ssi3FxBpj+c+o/xBnCv+5XSfpeGfsO8R6smBcsotvd37r9dBp1Bt546I3wt62hkZUiGkMsS2857kK4M/homZ9eQFHsI4cGhoaGhoa4SRnH2SsQrG0V9IoqDcYFMaV/PJzMvxPUp7UkGVh565Gs8nhi9D74+x29WXmepAYpahEMXveDP64W98KYzeL/41xYEwQn53BWvp3s2vgwuXQpWKi8DoxdfjPhf/xcsgD0KGjXZ12TO44WXEa3ny44jYDGg/guq7XVagPZUlPh9GjQyuTEgibLbD7xvHjcOedkWm/mGKnjZUrRWkRNe67LzLW8EYjXH996euHH/bv/vHss0LsEY4y6lYrNGokMrwbn58mAEnFQgrP/w0U1mkMlB28T/HM87e9v23UKNlGlmUnonhj3aCPpDrgbxzc7edLGyyWUJwMgwyLGuOgx0tCxNH7bajTV5RB11fih2SIF2KQppNhyHdw6XFofpVY5u86C9BonDa2X4Z3K5j//Oyz8M030KSJSDpX0puaTOI82bu3EHCMHRvcvtVceAudhX7dM/xR4Cggu1DZ6V2v0/u0mZXlv2zW2LGREzSWJyVF/dpYfA3R8I9WVaaG8+WXwYvaX365auoIGY3w5psV387ldrHnzB7FZW3qKEt7+zTsw4+7f/QKpoAQe2w8uZFRrUZVvCMhMP/AfJ96UyCOaWyb0jN+/yb9FWtWSZLE59s+55nhz0S0n8EiyzJX/XAVK46vYPIPk1n5j5Ul2b8aQMFpKEwPvJ5kgPb3VXxgRUNDQyOaVJWYrgaI+Po27kur2q3Yme4tZbcarDw66FH0ESyH1al+J67odAXf7fwOh2eAo461Drf3vj1ibY5vN55WtVuxI10MILhld0nbRp2RKztdSdu6mqOTRg2m9W2w41nvGsz5x2BhX+jzLiSNBNkFRVmw6e6q66eGhoaGxt+X04tQTRTpMy20IE5hCPfdBafV3T8AWt4YHceLPD/Zq/WHirIuej+R9HDizIf974I7QD0QSQ+9p0Grm0qt8dXQ6UEXC52egJ3/V6HuPDboMX478Burjq/CJQsPeTduTuWeYsudW4g1+bZ9wawLStYtJs4cx4LrFlSo7bIUFcGYMSIjOlIUKLvTA0JLc8UV/tcJJ1u3qgfL9Hq4+ebgS5NUlGJr/F274Oef1bPPr7wSHn88PMKNYnQ6qFMH/vwzfPuMJpIk/QkoZZA8FewuFOYFUnJFdBtJku4A7gBo1qxZgN1GEX9lUZw5QsBRGfeoy6PgZGiuA21uF1NBGhz/AVL/hHN/gS0FdCZx/pZBiC0lMUmSuC5JBohvDbV7QNPLoeEY5VJn+Uf996PB8HAfWY3F6YS33gruXG82w9dfi2tTsOdBnU4kwf/0kxB9BIpvDmk6hEWHFinG+orH1CrKkXNHiDHGlJRNLovNYaNT/U5e8/76CywW9WvBJZcI56VoUFCgHreuVUv00ViF+c01AS36WsP58cfgTlBt2sA11/hXAkcKo1GorSvKroxdGPXKv2A1JVvH+h0VnSxsDhvrUtZVvBMh8u6GdxVPqvVj69MkoUnJa4POwJBmQ3zWK3QWMnPzTORoZC0EwVvr3mLjqY0AbEvdxutrXq/iHlUzUpeIm7RANLlU3KxpaGhoaNRYnh76tKLTxR2974h4269d+FqJdbFRZ2T6xdMrZWUcCEmSmHbxNC/3jWJXMb1Oz8ujXq7YDjVXF43qRospyrazeYdh2TiY3Rzmd4E5LeDkvKh3T0NDQ0NDg5NzReCnPLEtfB2kIsnZLerjHpYGkNAhOv0oOKm+LGmkyGiOFifnQzCJTYO/CU64UZaKrOtBkiQ+mfgJJr335yQj8+nWT33W33dmH2tTvMtMxxpjefOiN6ltrV3h9ou55RbYt08E1qqCuXNh715wuQKvGw7WrlU3Xxk4sFRgEQniPV/3Dz9Ud91ITobPPguvcKMYgwGaNw//fqOBLMsXyrLcRWGaDaRJktQQwPO/UsZeCtC0zOsmwCnP32rb+9tGjZJtJEkyAIlAlsoxfSjLch9ZlvvUr69cwqFKsCSjGobM3lXzHA5bdocO98GI2XDpEZjigGvy4aocuEeCfh9Avw9h4Ocw7FfhrHFVLozbDgNnQZNJysKNwjP+nUhiWwrHDg1AVCMI9jz/7bcwblxoFQliYkRJqn/+0/96PRv2JMaofKI9fPZwxRsGDmYdVEwQB2gc37jEGbiYrVv9O2v07RtSN0LC32djMETHrK2mo4k3ajAuF2zbFty6Tz1VNa4bxYQiGtlwcoNP2REAi8FCz+Seitt0rNexJCO0LA63g8VHFle8EyGQkZ/BmhNrfObrJB2T2k/ymX9lpysVT+zZhdmsP7k+In2sCFtPb+WZJc9gcwivQZvDxvPLnmfzqc1V3LNqxKl5/muuFtP5SWGFqaGhoaFRY7m84+VeA6J6Sc+1Xa5VLOcWbhrGN+TBAQ8C0L5u+4iWaSlmRIsRdE/u7lVD26w3c1vP27wEqUGhubpoVDdiGkF9P8VWC9NF9lMU6wq73SLg8Nlnwgq7TRtISoLatUUN3kaNoH9/ePpp+P33yGa1amhoaGhUA86sVZ6fNDK6de8zN6gH2BpP9C03Fin8JcQkXxi8PXE4OPRp4LGgNncIm/sQxBih0LpOax7o/4DXOGO+I5+XVr6Ey+0dSXl51cs4XN5jqC1qteCWnreE3P6CBfDrr9FzvSiPLMMjj/i3jQ83O/wkVE+aJEqKRxKXC774Ql0s8847kc1utp6fseQ5wE2ev28CZiussxFoK0lSS0mSTMA1nu38bT8HuEaSJLMkSS2BtsCGCvRlMrBEri7ZnsFSuycYVKLmZ7cFlxBZnfA3vnAmWyQItLgGml4GSSOEwDFQcgpA7j5lUUcxSSOie92v5nz5ZXDn+jvugAsvrNy5KjYW3ngDunVTX6dHcg+fagDFpOen+1yDg+Fg1kEKncruXr0a9vKZt22bunhDr4eWLSvchZCxWNQFGjZb1caqawqaeKMGs317cDdfVquwR6tKGxp9CC7iS48sLREMlMWkN9GxfkfFbZomNlW0JgLYcnpLVJwsvvrrK8WSInGmOCa0n+Azf0ybMYoilUJnIR9s+iAifQyWfHs+E7+dSIHT+6mrwFnAxG8nklsUhGDh70BqEB6BiV2il4mioaGhUVOpAa4MRr2RhwY8hMEzcGzUG3ls8GOhHnGFeXLIk7Sq1Yq3x76tqsAPN9PGThOKfs9tlF6n57kRz0WlbQ2NoHAWKNcH3vov+OtZ2DcNTv0uHDXKD5p0ebZyNYuD5dwOyNkPTuXi65mZQpBRqxb06SPqo3/9NRw6BLm5Ihblcoka8hs2wCuvwNVXC2HHmTOR776GhoaGRhXgdoFTJTJRp090696nrwRUAg8tb4heX9SCfHqLsKSPFo48SF/mf51a3aDX21ETbhTzzPBniCv3eeQ78pm9rzT+nJGfwfe7vvcqmWI1WJl16ayQyyQXFcHtt4ugTFXxyy9w+nTFt7NYhINE27ZCMBss2dliUuOKKyIfoFq6VD3DuV8/GD8+cmVbzmNeAUZLknQAGO15jSRJjSRJWgAgy7ITuBdYCOwBvpdleZe/7T3Lvwd2A78D98iy+BFKkvSaJEkpQIwkSSmSJE317OsToK4kSQeBh4EnInrkkaB2D5BV1EW2FE2QUEzOXv9CyEaXRPe6X41xuUQ5k0Chvi5dRGmVUBw3ymO1wrx56oK85LhkH+erYkx6Eyk5KRVuc2f6TkVBiElvYnBT3ySU48fV99WunX9XjnBTu7a6I1RmpvoyjVI08UYNZtWq4L7kl18eWYu2SLH6xGrF+XannY71lMUbOklH04SmisvsLjsnck6ErX9qzNg4w0fsAEKMMbTZUJ/5zRKbUdda12e+S3bx/e7vVdV10eCOeXdwxqY8Gpxly+K2ubeFr7GkpPDtK5p0qhucvVvbu2ueklhDQ+Nvh8PlIM+Ez1QQpgEnl+S77+KpygjBleGuPnche/71btib9vXaR6BjCiQnE29J4NCDh7mw9eiolQXp3ag3I1qMwI24oXx4wMPUi6kX0TY1NPwiy5CxGtbfAT8nwQ/xsGgwJJZ5vK1jhtyDcGYdHJgJa66DBd3gOwsUZpSulzQc6vanUo/G9mw4+j9YexP81gsSywmrEiVYNAR+7w0/JMKPdeH3PrDuFmRnAR98AC1aiDq6ubnCtfAf/xC23xkZkJMDJ0+K01VBAezeDf/9LwwYIJ4H62k/Rw0NjWqKJEl1JEn6Q5KkA57/FcOikiSNlSRpnyRJByVJeiKY7SVJetKz/j5JksaUmf+SJEknJEnKK9eGWZKk7zzbrJckqUUEDjm8yA6QVLKhDJUQHloqOv6ig7Pb1RfX6RN6XyqKmqV8nb5CzBktTs7zP8ajM8OI+ZX7nEIkxhjDhxM+LCl9CJBnz2Pqsqklr6etn1YizAbhrHdNl2vo3ah3yO2+9RacO1exbcxmuOQSkRl9992i5Hdlqj088wzkV6ACQ/fu8NVXwsls507YvFmIP7ZsEYmQgYQXO3eqZ3M3aRKd6o0ffijuH5V44YXIlEs535FlOVOW5VGyLLf1/J/lmX9KluVxZdZbIMtyO1mWW8uy/FKg7T3LXvKs316W5d/KzH9MluUmsizrPP9P9cwvlGX5SlmW28iy3E+W5dDqL1Qlsc3xOuGU59SCmhm8CjfndoLLj/qtwbDo9aWas3Jl4HUsFiG2CJc7kE4nnrs/9a1CVoJazNKoM3Iw62CF29ydsVtxvtVgpUdyD5/5/oY3u3ePbqmSRo38Cwe3bo1eX2oqmjlJDWbBAigMIq7/wAOlNfBqCnn2PE7lKpd8kySJ5Dj1u98uDbpw6Owhn/lGnZH1KetpltgsbP0sz460HZzKU+5374a9sRqVrxYT20/kg80f+Dhw6CU9c/fN5crOV4a9r4H4due3/Lr3V1XxSKGrkHn75/H1X19zXbfrKt9gamrl9wHB2ZBB+K5WBz+EzQ8FXq/xeNBpp1wNDY3qzYhZI9jwBEjlT5Ey/DUTOlQyu/vmS+GbrqArt3+nDtzPV27f0aRuTF0ubnMx8w7M4+lhT0evYbUnsSiUBXnzojf57eBvmPXmkJxG0vPTeWO08pDNFXtgQMWTELzIN8KrQ5SFRkOPQeQLzGhEjaytsOpKKEwVQZq6faHHq8KSfHJtT+DGDSWlfmRhsa43Q/5xOPo1WMpFBfq+K8QUrgoEfSxJkL0Htv8bTv0mAjg6g7CO3/qgcF2LayksgiWdyChz5Ar3j+wdkLoYTvzE879/yuuviyxVoxGmToV//Us0UXawvWzwoGNHaN8ebroJTgWqkq2hoaFRtTwBLJZl+RWPKOMJ4PGyK0iSpAfeQ2QnpwAbJUmaI8vybrXtJUnqhLCo7ww0Av6UJKmdJ4N5LvAucKBcX24Fzsqy3EaSpGuAV4GrI3PYYUJnBlklpb4oU1xbQnFJuLyC4y+FZ+DXxsrL4loBIQTdfk6GwhDuYdUCWw2Ggj6K9RsOfeK/ZEq7+8BUAQuHMDOx/UR6N+rN6uOrS9w1Dp09xLqUdfRI7sG0DdModJWO95n0Jt646I2Q28vOhpdfDt51o3dvePBBuOwykUFtMIjhPIdDBHvWr4fp00VmdbCsXQvHjgW3bkKCKO/Sr58QkJQXafTsCR9/DDNmwIQJsG6d8n7++ks9sXLcOHVHjHCyaJHy/Fq1YPjwyLevoREQSRJu1GdVorX7p0Gji0FXwwJY4SZri/oyQxyYEqPXl2rOV18FLpnywANCbBHOampWqxAc9usn3DDL07VBV9afXO8zP8+ex1NLnmLW9lkVam9b6jbF+bn2XLond/eZ78+Rs0+f8DiQBIskQa9esGyZ8vI//hDlYM3m6PWppqFFEmsosixuSgPRsqWwB6ppbDq1CavRiqPI9w64Ra0Wfm3C+zTqw7z987ys/0Cc1FYdXxVRIcSHWz7E7vS1MrLoLVzZSb3die0n8vWOr8kpyvGan2vP5b2N70VdvHH03FFun3O7T9kaq8Hq5Spic9i4c96dDGw6kFa1W0W1j9WG03/4V8UCWBv6Bgk0NDQ0qiHxpnicCg82caY4Ni+eSYdKivVW/Lc5ruzjPobL8aZ4oIaU4kpOhrQ05ha/nnqx+D8pKXxCxOpGcjId09I8wosieCZBzK/AMS87uoz/DgCHQvLo2qawyk/2QjD80RpeHwSFCmUCl7U1aOKN84XUP2H5JHHvJemh3wfQ4lrQWUDn+XKZ/NSKjG8NnRTER4mdoPkUOPa/IAQckqhb3Oe9UsGHpIPur0Pr24QlsFFh4FHSg7mOmOr2gaZXMP/MJ7z2Wmld+I8/FvbawWRI6nRCoN9ewfgnK0tYpqanC21XeroIpjidIqnNaBSZSPXri59xUhI0biz+j1I1Jg0Njb8Pk4ARnr9nAcsoJ94A+gEHi7OJJUn61rPdbj/bTwK+lWW5CDjisZPvB6yVZXmdZz9KfZnq+ftH4F1JkiQ5GvV1Q0WSwNwAitJ9l2WsEtedaARzbCdEWRK3Qi332r3UBSb+CEW44Y/ki0DFrjzsOHIhw0/aryEeuj4b9XIpZZEkiU8mfkK397uVjOMVOAp4YfkLXNrhUlxlysjFGmN546I3qGOtE3J7r70m7jMC9wueew4efVTci5Qvs12cIT18uBB43H67cOMIxtHj//4vOPFIkyawfLnICrZY1NdL8Dzy/Pkn3HCDKMlSnnXrSu/jynPxxZEPlGVmqrd/5ZXBfSYaGlGh8QTI3g1uhboNGavBfk75GervRG55zWkZEtqLJAWtBhIuF/z4o/+83MREeOop9RInlSE2VogL+/f3XWY2KCsRXLKL9SfXKwo7QkGWZUU3XH/XykGDwitkCYYLLxTVI5SuRV9+Cf/+d3T7U9PQyqbUUA4eDO4G7Lbbov+jDAfrUtZR4FC+++ya1NXvtp3qd/KyBixGRmbZsWXh6J4iTreTL7d/iVOhhptOp2Nsm7Gq2w5rPkzV4WJdyjrS8iKfUVuM0+1k0reTsJWrxx1jjOHtMW9jNXhnMhQ4C5j4zUQcrr9poarcfYHXSbpAeZBDQ0NDo5oxquUozHrfh418ez470ndUat9Ot1PVVavIFcXCi5WlCt0vqowwHPOgpoPQm5VHR/e2ryuevCsx/TXzeRwmX2WIXtIz+vJ/Bd1PjWrOxntKRbOtbxPCDUNsqXAjGPQqo/R9Z4h6zLoAqR+GOBj8Pay9wdMXGQZ9Da1uAYM1+EFHYwJPP2cuGXC/7DJR7jKUAaaiImHfOm4c1K0rnDn+7/+EnWxsrBioGTcOrroKrr1WZJAOGybEGlu2wNtvi+CJJtzQ0NCIAEmyLJ8G8PzfQGGdxkDZGrcpnnn+tve3jRol28iy7ASyAZ8atpIk3SFJ0iZJkjZlZGSUXxx9kkcpz09frn5NCzeFqZQ6WpWjXn/QV4OAW2Kn6LV1cj7o/IhF290TmiNKmGlTpw3397+/ZBxPRmbJkSVMXTaVfEdpbZHmtZpzW6/QyyLn5YlyboHcoevVE/cmjzwi7k/KCzfKExcnRBx79wohhz8yM2Hx4sAmux07wrZt0KyZf+FGWWJjRZb3fff5Ltu0SX27nj2D239l8Fe2ZcqU6GZZa2j4pXWAc8yOqeAIYKVwPiPLykLNYhLah/6w9nMy/E9Sn2oYa9YErrLz0EOBy15Vhk6dYMgQ3/ljWo/xnRkB4s2+9115ef6vgc0iV4xAlSFD1K9Rx47BkiVaxSR/aM4bNZRVq4I7X197bc20nll8ZDEOhTqWRp2R3g3937F3rNexpCZ7efae2YvT7cQQgfIViw4t8il7UozFYKFDvQ6q28YYY+iZ3FNRfaeTdHz515c8OujRsPXVH08veZqDWQe9jkUn6RjUZBB39rmTX/f9yh+H/ihxNnHLbo6cO8KTi5+slMVijcV2MvA6jSeAMSHyfdHQ0Dh/8Lg7hI0gH/IGNgPzdRJF5e4dZGQ2nfIzMhUEh88exmKwkGf3fSBvX7c9UDlxiEb1pklCE2KNsYpi1ZyiHLILs0m0hJ45ui5lnY/rGkCsKZbhzTW/4L8lfu3YdTCl3PdFb4KRv8NvvaHgpK8Dh6QTDh8jFogMY6nM80SDYaAgHg/Ul907CwFxwh09OrQB9hUrhFtHQYEQ98+YIQbrCwvFQEmgZ8HRo0WWaqLmwquhoREikiT9CSjVtn0q2F0ozAvkhhGxbWRZ/hD4EKBPnz5V78rReDycnOdbosN+Fk7/Do0uiXyJ1oJUcKtkkNUfWvVZYzpTdEuUpP4BTpUgo84kXL6q0HWjLM8Of5ZPt35a4r7hdDs5Yyv1VbcarMy6dBa6SohNfvop8FfAYhHW6W3bVixx3GIR09KlwvJ9/37l9ebMEYG6Ij85AVYr/PabELpWlJgYeOUV2LxZBA6LOXFCeX2TSTh7RJqdO9WPuXPnyLevoRE0sU2hbj9116LDn0Lbfwo3p4oI888XnHmoiiQBEjuLJIJQCLfTVRXzyy/+S6ZYLEK8oSYaCAdxcfDii77zL2p9UeQaLUOner6C1fR08eyvlvBfq1Zk+6TEkCHivcpVMVqeOhVGjIiMQ8r5QNXLgDVCYuFCyM/3v06tWsL+tiay+dRmxflWo5VO9f2r6dvUaUOhQ1nubdab2Zm+s9L9U+K9je+Ra1c+E13c5mK/pV4AJneajMXgK/sucBYwY+OMsPQxEMuPLmfa+mk+5VLMejPTx00H4J2x72DUe2cY2Bw2ZmycwZIjS6LSz2qDyw6O7MDrqWXKaGhoaKhRRS4OvU6DzaA8Rr3nzJ5K7Xt3xm7FQUEJieHNh+PQoTiFC7X9u2teokGNZVDTQYrzrUYruzJ2VWrfas4wBY4CBjQZUKl9a1Qj+r4Hek9NkUMfw9H/gTMf3BW1axciZVmGjAxRV/2bb+Dl1xN4evUWFh57ELvLis0RT4EzjiJnDHuyLuDVvzbx7LtD+HTuAGFTXyzg2PY4OP34dKsMmNWOPVvy97Fj6rbX/vj4Y1HbNj9fZHjecosYsKpVKzgRv9GoCTc0NDQqhyzLF8qy3EVhmg2kSZLUEMDzv1JaaQrQtMzrJkCxXZva9v62UaNkG0mSDEAikBXscVYZyReKklxKbHkEFBKfwk7BafWyYokdI99+IOJaBlH2TAF/2cj+yFilvqzhRaJUWjUhxhjDhxM+LHEodsmukmQts97M1Z2vpk+jPpVqY8YM/4E0gK+/FqW9Q3X8j40Vzhpqwacvvww8Tj5tmigZFyoxMfDzz6XlVEC9zQ4dQruvqygbNyo7nsTFafd3GtWQDg+LslJqrLleuazK34GiTP8OkLV7VgtHp+rA8uX+HSauvz46mtJ+/XznmQ1mjP6cucLEoGa+Y2tpaepuI8VlU6ONXi9Ko6iJMzZtEuMZga7ff1e0X3wNxZ8tWzGDB0fnRjHcnMw5WaIIL4/L7aJjPf8Phka9kaS4JOXtZRfrU8JTW6osZwvOsvjwYsVl8aZ4LutwWcB9XNzmYvQqD3hp+WlsS91WmS4GJNOWyRXfX+Hz3ht1RiZ3mlziHNKubjumdJ3iY6tf4Cxg8veTvRT85z0FKYFtSmOalgYZNDQ0NKo5MQ5orqJJS8tLw+4KvQTUrvRd5Nt978jjTHHkFOVgegYsT3tPpmfgo14hN1nC/LZgVtn/g5dHUI6v4cVFrS/yKb8G4HQ5KyWuLXIWkZqXqrisUXyjSjl6aFQzki+E0asgrjXorbDxn7D4AjjyBRSmi6xgR46omTx+H0w+K6YrSwXWsgxLdo1k3DgRAOjUSVhhS5KoTf7gv+IZ+eDL6C87TMzITzEPmYnxklW0ueMP7n6iI9ddBw0bm3GP3gC1uooMqCNfwpLRkLYUXEWi/bJiDovys8kdF3yA1STWmz4dTp8WNXwrwrPPioyWmBiRDfrPf8KpU+I58Nw5/xbmdrtYRxss0dDQiCBzgJs8f98EzFZYZyPQVpKklpIkmYBrPNv5234OcI0kSWZJkloCbYENFejLZGCJLAcqslANsDQQdvNKQZ28Q7D7FSFkjCT5R0HJ4VZnAn01SJeMbytcsSpKqNnIeUfUl7X6R7VzXp3UfhK9GvbyGXM06U28OebNSu37xAn46y//6zz9NFx0kbhXCRWdTggv5s3zLbeSn+/thqHEuHHCnboyfQAhiPjkk9LXamKU7t2jU47ulIpkrX37mhkT0DjPaXyJt3theXL3C1FipK9pkd5/KNgz/Qv/EqqBULIa4HbD7t3+17nzzuiUjFIr/dU4PvLZ9OPajPOZl5amLmpp0CBwabNIccst/q+H//qXSGSp6DhIKFTVexAqWtmUGkqq8vi0FyNH1kzLmQ0nN2DSmxRtte0uOy1qtQi4jw71OnAy17echc1hY9nRZdzZ585wdLWEb3d9i16nB4WTTJGziFGtAjsvdKrfCZPe5FV3shi7085Hmz/ivUveC0d3fZBlmSk/TVF0DjHoDLx64ate816+4GW+3fGtz7r59nyu+fEa/rjhj4BOI+cFeUf933SCCC647YAm4NA4D6iiUh4AJCUFd/ELN+E85hpyXhx2FA7V8Z1vNVo5kHmAzg1C81/ddGqTYlkLh9tB+3rtiTHF+Dg/Afz5xFXcfuV3IbVZzKo/n4TVr+KWvJ9kdOiIv+uhSu1bI3gGNx2sWLrO5rSx+bSy61ow7M/cj9VgVbyPGdliZMj71aim1OkJEw7AmbVCtJHyK2y4HfQxuHQmsDZGH9vEE+Ryi8G5/BSEDa3MWwse4snvX8HhLL205OcrPDeZkiFuckm2gw6RsdK+vZigIYzZAKcWwN63RX9WXCZEJYmdRSCpVlch3Oj3kbgfLDgF2Tvh4IcAPH3pS/y+/WK2p/TDZhOBjd9+E5eeeD9JacU4ncKSe+VKIdz47TeZPxc56NZFwhJjoHs3F127uGnYEKxWiZhYcSkqsIHNJnPmDOzaJbF9h56DB7W8Dg0NjYjwCvC9JEm3AseBKwEkSWoEfCzL8jhZlp2SJN0LLAT0wKeyLO/yt70sy7skSfoe2A04gXtkWdxoSpL0GjAFiJEkKcXTzlTgE+BLSZIOIhw3ron84YeJrlPh0KeAQkbyzhcgsZMo12qI0LiD7bjyfEsSuAtBV8WDj/FtxfU3Wuit4FRwPNGZoeHY6PUjSCRJ4pOJn9B9ZveShK1YYyyvj36dOlaFB78K8MUX/pd37QpPPll50QQIR7EePeC+++C//y2dv3ChEFGolQ+xWoUzRzjGyC0WGDtWTL//Lu4NlYJBvXsHdy9XWdQCUQkJ/jPTNTSqBJ0R+kwTAnw1AcXBmRDTBDo8GJnyU8582PcOdP53+PddGYoy1ccMJR3ERKEOUw1g/3510QQIkV+XLtHpi5rLZb/G/TiafTSibQ9v4VsaOC0NHCpmbElJ6uVUIk1MDNxzD7zzjvI1y+GASy6BDRugTh3/n29lKCwU359u3SKz/0igiTdqIDZbcCqhMWPUrXKqM6tOrCK3SLn8SOOExkIkEYA+jfqw5MgSZIWSp6tPrK50H8vz4vIXFQNOAAnmBF5Z9UpQ+0mOS+Zs4Vmf+U7ZycdbPub10a8TYwr/w/iMTTNYfWK1T0a1xWDhvn730TC+odf8pLgkHh74MG+ufdPLqcPutrMuZR3T1k/jgQEPhL2f1Y78o+p1X4uJaxFY4KGhUVOoolIeVdp2VR5zFTH8GPwwII48u7f3rU7SsefMnpDFGzszlJ0VzHozo1qO4tXVryou350RQFYfBNtStyneE8SZ4+jbuG+l968RHF2Tuqq6t2w6GYStnApqrh1xprigBLQaNRBJgvqDxNRvJrtOb2LG0kc4fWoFbUyZ1DHsYXTzIXRP7onBGA+N60B8e0hoR8eEZhh/1WMyC4vv5cuF5Wl2thjcD2Tn7XKJ57H4eEBngCYTxeTIg8wNZKatZcf+b9AfXUxjA9S3JBBrMKPTmUSGcqzHlc1lw2Rw8NuzNzF+5h527IBDh6BjR5gyBR55RFhuFxaKbFO9XgzCO50iUFBUJIIVL7wAu1dtpbftJXq3X8LTbe3Q5FJcdQaT6e5Jmq01aVkJFBTqcLp0yDLEx7kxm2SGDsznn9cco75hG8g3ala8GhoaYUeW5UzA52Isy/IpYFyZ1wuABcFu71n2EvCSwvzHgMcU5hfiEX/UOMx1oOuzsON5cCmMPa29AQZ+CY3GgzHMwS5nPthU0vutydEp2xKIWl1BrxJFiQSyihtho7HV4/1QoG3dttzb715eX/M6LtlF81rNub337ZXapyzDzJn+x6g/+SS8Vu2xsfDii8I1rZivvoJc5WFkQASNgiklFyxxcfDWW0K8oWbN3ysM7pHBoBaMq4nxAI2/CS2ugwMzIXOdumPSX0+LcmEdHw2vgMNpgz1vwI6p1VO8ISs4XIFw9XY7xLPk35xNm/znxV12WdWJFIoZ2XIk3+/+PmL7N+vNiklRZ86oX4+TkqpW0Pfcc/Ddd3D0qPLyo0fFmMyKFaKvoZZYU8Nmgx07YPRoyMkJ774jiXYpr4GcOCEGFv3VE7RYoF276PUpnCw9slQxwALCnSIYujToQqwp1ifwBJCal0pOUQ4J5vDYGC48uJDTeadVl58pOKMakKoIdred/6z6Dy9e8GKl91WWnek7eWzRY9gU6nSb9CaeGvaU4naPD3mc6Rum+5RZyXfk8+TiJxnZciTdkmqQlC0U8g4rD5yUJa515LJfNDT+boTLuaKGOGBUFf1PCkem8uTb89mZvpPJnSZXeJ9u2c3xbOWMvd6NetMtqZuqCPJY9rEKt1eefZn7FOc7XA56Jves9P41gsOgM9A1qSubTvkKNfZn7Q95v9tStyne87ncLgY19a0Fer4iSdJY4B1E1vLHsiy/Um655Fk+DrABN8uyvMXftpIk1QG+A1oAR4GrZFk+61n2JHArwnvuflmWF0b4EH1YcngJLyx/gdUnVuOUnRglI13ju7IldQv/zlhGvHkz9/a7l0cGXl+SWTpuPKSni8GD336D224Tl4UePaB9ezcdOsokN5QxmyQsZh06nYTdLkqM5OQIm9YDB+Cjj7z7siljL88vf5t5++eV62UOZr2ZO3vfyaODHqVpYlOvpXWBNTfC99/DY4/B2bPwzTciQ9RkEv3q2FFkrDidkJUlslJOnBDbP3Hpm7DoaeHsYU2Gi/eC3oJeH0cDnY4GQFefd6440mACagM9KvMxaGhoaGhEg47/gsyNcGo+uMrVQ3A7YPU10Oaf0OtNYb1eWTGD0yaCZ2tvhKJ05XUsyQhnqyomMUpptsW4VKIjLW8GU/Ut1zd1xFTe3/Q+efY8Zk36HF1hGhSdESXfkEVg0JgoAoVBJM5t3izuW9S4+GJxD6MmcAgVgwGef1787XAIMasaFgs89VT4nambNBH3aIcOKS9PUq6YF3bURClqLiQaGlWOJMGgL2B+F99rWVl2TIX0FTDke1GmsjLXNFehECKuugrSloS+n0hSlOlx7lbA2rDaCgOjzapV/mOit94anZIp/pjYbiJ3zb8rYvtvnthccb7dri7QSEqqWlGf1Qpz5kD//uolvY4eFdfVb7+FgQPD9znabELkee+96s4k1RVNvFEDOXEisH1Mnz7ihxBulVKkcbldqhm2OklH30bBZcd2qt8JHcpPB1ajlU2nNnFBywtC7mdZnl36bFj2Ewzvb3o/rOKNAkcBE7+ZqCjciDXG8vyI51VFLnGmOF4a9RKP//G4T6mXAmcBE76ZwJ579hBjPI+FC9m7QEVoVEJiJy2LUUNDo0bRLlOILcrjkl2KQfdgOJF9AoPO4OO6YNQZubDlhViNVhrFN1IUeBQ6CyslupRlmVO5ytmCkiTRLLFZSPvVCI0xrcew9fRWnxI6DpeD9Px0GsQ2qPA+N5zcoCj8NelNtKzVMuS+1iQkSdID7wGjgRRgoyRJc2RZLntjfTHQ1jP1B94H+gfY9glgsSzLr0iS9ITn9eOSJHVC2M13BhoBf0qS1K7Ysj7SbDq5ib4f+z4XOGQHW1K3ACAjk1OUw8srX+bllS8zvu14vpn8DXGmOGJjRe3Va6638fHWj/nz8J/8tmcbP6TVh5Q4cJnE5DSjw0C3xh3o3rgjl3Yax5AhiUyZIgZGZNz8d91/eWTRI377W+QqYtqGaUzbMA0JiTW3rGFA0wFQeAYyViAVpHJ1x3SunGdi2cZWLN/UjEVrWrB9bwN27ZDZu9vt0R1KyDIUFulp1KCAIb1OctWojR5Rohv0FjDVEs5wapGSn5OhUMlVSoL+H4llRefAlCCsjSWDsIE3WAGdpxazKEGD7BYZc648cDlEkE92gD1bWOlbkqDeQEhoG+xHq6GhoaGhhiTBoK/gj8FwbodykOfgTFFOrNvz0OIGMc9QwXIijjzR1t53YM+r4MgRjlFKWJKFC1VVE9uiqnsgaDC0qnugTt5RYk78wt6uHTHmHaTByqGAJAQbZfU3bqcIElobQWJHqNsfml4Gtbr5JEH8/rt/kcDbb0cmiGaxwD/+If5eudJ/QOr66yNjwR4fL8qV79mjvLxu3fC3qYRV5eedmho563kNjUoT1wq6PAM7/89/UmTaEpjbFvrOFKXBJF3FRByuIvG8cnKuKNVi96M2q2qKMsCtckI1RemEUgNYtUp9Wb161aMkRqOERugkneK4ajjo37i/4nx/woS4uKp3ZOraFf7zH/j3v4WgQomsLFFKduJE+PhjcY0L9T4iNxdOnoQbbhCOLTWRanCHrVFRTpwIbP/TqlX4lc3RYHfGblEWRWHY12qwUs9aj8NnDwfcj0ln8hEUFGOz21h1bFVYxBtOt5ONpzZWej/BklmQyaGsQ7Su0zos+7t3wb2k5qUqLos3x3N337v9bn9Hrzv4z8r/KL7XGfkZ3DXvLmZdNissfa2W5AeRDR4Xns9KQ0NDI1roZOiW1I31J9f7LNuVsUthi8DsztiNUWf0mW81WhnYdCAAfRr2URRvWI1WDmQeoHej3iG1nZqXiqTittKpXifVZRqRYVjzYUzfMJ2cIm+vQovBws70nSHdn+0+oyz87d+4/9/p8+0HHJRl+TCAJEnfApOAsm/OJOALWVjrrJMkqZYkSQ0Rrhpq204CRni2nwUsAx73zP9WluUi4IgkSQc9fVgbwWNkW+o2Hvz9QVYcWwGADh1GvZEJ7SbQtq63QKDQWcjCQwvZf2Y/TtnJggMLSH4jmQf6P0BqXioLDiwgNb/MfbAeaHTCp003sA3YlgezNkCiOZFL2l5Ct6RuvLfxPVJyUkRfJB1xxjj6NOpDosU76/ZU7im2nN6C0+1ERmbgpwMZ2GQgX8fs40xBllipwXDajPqFC7rW5oJb4HnA7RYZndnZQphvMIDZ4ibbuIO42iJoZ3c/yP6sfjQ+9iHW/EMwuzW6FlMgaQQkdCytjyy7PGILNeGxDOtvE39edlq4eFQUWRaZbS6byNh220UQ6OxOxAOeR/Thg2e+pBNiEckAehPoLMLBTh+DLOlJTxcDPcVOKHZP3NJkKp1iYqBBgwAmW64iKEwVIhPZKd4bySACWJYGYK4bWHztdopB1qIzIsglu0r7b6othCsBBpfdbpGxnJ4uLG5dnmdgg6H0OBITAxyLI0cch7tIvN+uItEXnUm0rzMLUY+5vv8sarcDCjPAnlnmePTieMx1wNxAfCb+3o/CNPH5ux2ez94u3hOdSQiBdCaROWmup3xQxftw2oQIyO0RA8myCA5LRvG/ziw+J3/uhi67cAooyirzGetFP0x1xfZKAWdZBmce2M+J/4u3LRYqIXneF73n2Mwiy95YS7w/riKxnasAnAXgLizzu5MRZxQQ7jeS532QxGckGUv7CaJttxNwiu1Lfj5lf0Nl3sfifuk832W9BfRWYTeuJROcP+jNMHIRLB4JuQeUs5YLU2HDnbDjBWh+NbS8CRLai3UlAxjLjIIXf+dljwAwawsc+RyO/wj2rDLrqWgzrQ3F96yqMYbHWbdSWJJCs/dXFVWGgbwjcHgWHP0KCk4C0Li8a4hbxUXEdkxMqYtFmQFDrPg+tboZ6oiaIAsXqo9P9+8PjRqF6TgUKL6MrF2rHgQC4boRHx+5PqiJVxKi9JXs1EmIaMrf3h06FN5SMRoaYafT45CxSgg01NyMQAguVl8N1sbQ4QHhMIUM6LyvZ8U48hD3WzohaNz735LzX7WmQKU8GXieTTQ1ltMpHDDVGD5cPB+Gs1RXqNS21CazIDMi+1YrDexPvKHXVw8T6vvvF2VrFy70f+2eMwdatIBrr4UHHyyNdQf6bPPzxbGuXw/TpsGvv4pn7pqKJt6ogRw/rm4vU0yzZurq2+rM9PXTVW3T8x35PL74cZ5c8mRQ+yqf0VmMU3YybcM0nh1ReceMd9a9o1riJVI8ufhJvr+y8nWz/m/5/zFr+yzF90kv6Wlbpy23zbkt4H7a1GlDal6qz34KnAV8veNrWtZqydSRUyvd32qJKwgfwpgmke+HRoXwZwFfbr2wWchLkvQScCNQW5bluDJtmIEvgN5AJnC1LMtHw3zIGhoVZlTLUWw6tcnn3H4y5yQut0sILSvA7ozdPmW2QDhA9WnUB4ChzYcy/8B8isqdW2VZ5kBW6OKNA1kHMOvNFDp9BwSGNBsS0j41Qqd/4/4UOHy/C0WuopDEG/n2fLIKsnzmm/VmLmp9Ucj9rIE0BsoqD1IQ7hqB1mkcYNskWZZPA8iyfFqSpGJrlMbAOoV9eSFJ0h3AHQDNmlXe5WZtylpO5Z6iTZ02AAxsOpB3xr5DLUst1W3+OPQH//rjXyXPGD/u/rGkTE89az2aJDThhu43MLnTZLGfNm0gI0NsXL8+BXt2MG//PD7Z+glHzh0hNS+V/+38HzvSd2AxWGhTpw16nZ5HBj7CLT1vQacSJM235/Ps0meZu38uAGdsZ7jZ3YIVp8T3V3diBYat9bg4uQPXNO1FHUucJyCmA0nCmbGapcfX8nkunHWXat3rSJDleRypa4qlvSGDewy7uAo9hgPvi8C+pCsJ/roT2pOWX5vUvFQ6S9mYJHC5dfT475e0St5P3bhMbjY9w7AOzT11lT0ZboYYSpw3Un6FlF8ocMO+MoNEcedasfNEV3IKEsiPu4DEnjcDHpcSWT0DVJLAlboatz0HvZyH0+5kQ9q17N8PKSni2bdxY2jbFlq3FqIGi6V08KawUEwZGXDwoJh+/hnq13OLQGTaEhF8ytkrxA6xzSC+fakFs87oEZ0UimDluR0imDl+rxgsPbsVUpdC+jLhvOe0QWxz4bBnTBABT51ZCA1cRcKWOfcA5HrKQY37i4Mn6rJ4sRis2rwZzp2Dhg2hSxdxPGazOB5ZLj2eU6dEmZ6MDNi1C+qZDkDqIkhf5elHnjiWhI6lAVRDjPiMXAXieBw5kHtQHPuoJeJ4MjeJY0nzHI+r0Pt4dCYxlT2e7D2Qd0gIFEb+AelLS/shGSG2CcS1gfg2QryiM4t1ZXepqKTglOhL/iHo8rz4XDJWQd5RiG8NcS3E9rGtRD91Ro/7iySEDK5Cccx5RyHvIHR6AgzxkLUZ0paKKWcPuPIhpqXIGC/7Gbsdpe9J9m6wHQckkf1ZlCECk12eFcIOS7IoHWCI8QiKdJ5+eEQYshvmtBbblUGWwT5ZxlYkBg9tNiHKcbtLJxCDjzod6BYPRWdPJ8Zso2ndFHJs8exPbcepDos5k5PIuXOl+zCZRBfcbiBzA5LbBm4nkttOUUE+BmcqsfIx6ox6g/r1haV/+/ZgqgYDtRphxlwHxqyHtf+Ak3PUs5YLTsLet8Rkqi3OFQkdIKGd+G3IMjiyIXefOEdk7wVnrvK+1MQbhpiqFwcVnyuqmrp9xblOX8GoUSSEG/knYPtTcPwHwK1uxR8MskO4a7nyYf97cOgTqNcf98glbNmivtkddwghYqQovgdYsUJdQNKtm8jEjhSnVGKt8fHRCxb17ClKwpQvI+ByieTP1lo+mUZ1RdLB0J/gjyFwbqe660QxBSdh62Ow7Ulxz1q3HzQYIco86c3i/GtLEfe4mevFvV50TCHDQ4Fyci3guS+uYfb6EWD3bvHMZFe5pA0aVPUlU4rpntSdJUcjU6JnQrsJivP9iTcMhuoh3pAkUS726quF8NCfgMNmg08+EVOHDjBmjCin0ru3GBswGj3PXnY4ckSUll2/HubOhdOno3dMkUQTb9RA9u0LfBPYrl3VW+GEwh+H//C7XE3YUVEyCzJxu93oKmlP8va6t8PSn4owe+/sSu9j48mNPLPsGdXlLtnFyuMrWXl8ZaXacckunl/xPGPajCnJrD6vkIMolFUdslA0yqNoAV92hQhYyM8F3gXKa4RvBc7KstxGkqRrgFeBqyNz2BoVJS0WXhiunCN89S4YHoT5jj+yzfDiMLCVG2t0SZCSCOkKiVs9UuGjuZVrF+CGy2CvwkBW4xz44QcY1HQQcaY4souyvZab9CaOnDtSEjgNls2nN/uUTAFoFN+IOJN4uuqZ3BOLweIj3sh35LPvzL4KtVeWA5kHcCjUB403xdOvcb+Q96sRGomWRBonNObouaNe8wudhWw4uaHC+9udsZsYY4yPk4dJb/q7iXOUHsXLn77U1glm21DaQ5blD4EPAfr06VNpxfNdfe7irj4Vqx87uvVotrXeFvwGKRlefyfEJXFrr1u5tdetFWq3PLGmWN4c8yZvjnnTa/7O9J18uuVT3l7/Nna3zOxTu5l9StlNpiyd6nXiPxf+h7FtxrInYw9P/PkEvx/6nTV2WLNlPtdtmR9Uv8a1GccD/R9k54SL2OuOBVnPF7vsPFX4E70TxiHLHscPc6mzo053I+5kePSvC9mTuw4deorkAlx/3A5J2wEHTSyLmHtBD3ok9/Dbfnp+Oo//8TiFTYXALmPDSDZ/eDsul2jzs89g9GghZtDpRCBITQTicolBHrcbEvMWwK93iMCkzgjt74c+0yCupQjgy56vfklQ3i2mue2EYwPA3PYikF+QApIJ2t0Dfd8TVvJOm2dbHaAXrhbF7gwlgf10DqS24d7+f7Fy/0h0Orj0UpEB1KZNaUKGwSCOqfi4XC4xORzimM2uFEybb4Yza8QKza+FEfNF34oz6dUCqGUzuue2EwHcogwxANz+Qeg3Uwg/yh6PpEc4Q5Q9njal78v8jqKEQq3OMOxXsNQXDhF6s/+gZdm+nF4k+mCqDZenCqcM2aVc3kEtK333a2LA3p4l9tXhIXE8MY09xyOJ4yg+ruLP2PPZlJCViSzD2firSS+4iswUyMyE7LMuIRoB3G4Zd+oypPQl6GQ7Ohy4HZdg1tvIyK3LfbNmlOyu4AqoXVtMAeksnrcPHYJ6/ZxkZulJiHfx4Yc6brlFCFjz8yWFwKT3/YskiQHMSAZKNaoZegsM+QaOfAkb7/aUugiQuXxmTel5pKKoWX9L1UA0YaotgnYVLQ8TbuoOCM15I5w4cmHrv+DILHC7ghuzqhBuIRZKW8q+d4ciScpjhiYTXHVVdMp2bN2qvmzyZHFujBRpKrqbpCQRTIqG80XXruoBubVroWXLmunMXdVUs6Svm4HXgWL7iHdlWf44nMdbZegtMGop/DlciC0CCThA3C+e2yGmQ59Evo/Rouy9aXnM9StWLuY85eBB/wKEYcOqz/luSLMhERFv6CQddWLqKC5TE7WAeN6sLu+NwSAEHPfdB7Nm+RdwFLN3r5jeeSfy/atORDy8r3YRK7Nc8iwfB9iAm2VZ3uJv20AXUEmSmiFsfqfKsvxGJI+vKjgcuGoIbSoWU6k2pOSmRK2tTac20a9J6EGb1LxUTuZG33bL7raz4MACxrUdF9r2TjsjPh8R3k4FYNQXo8h6PAuLoRr4VoUThWCgD1INVFGd/6hZwJfFn/18hS3kZVle59mPUl+mev7+EXhXkiTJY2mv4eGloTCjr+98gxt+/B76+nEXDIYvusGTF/rOLzRArhkcCoNOa5rCtg8q1+6vHeDdflCkMKBkdIJD4fSxPRle+wNq+xmbDcTJePixExQqtLunPugaNKB/k/6KThkGnYE9GXsqLN7YnrZdcX7Z4HqP5B6KIk237GZb6rYKtVeW3Rm7FfcryzK9GvYKeb8aoTOyxUg+2/aZz/ytqX5GX1XYmb4Tl9s3o6bIVUTPhj1D6l8NJQVoWuZ1E6D82VFtHZOfbdMkSWrocd1oCBSPKgXTXvVl6lR4/vng1lUbIXruObGfStKlQRfeGvsWr45+lS+2f8EPu39g4aGFiut2qNeByR0nc1uv22heq3nJ/O7J3fnt+t/4cvuXPLjwQc4WnC1xB6xtqU3dmLqcsZ3hXOE5cUhI1LXWZfrF07mm6zUA3Nz9Zr7b9R0FTlEO8bOMf/L0tYcw6pWjHosPL2bfurUUusX51Wqw0vKar9hzZjcyMinA5K/2MKPb1hIxQvGAUbEThyTBjGPPszDjK1yI6LR+zvVIeSKLtndvGD9eiDGCCYDo9R5r9JPzYdVVIsAk6WDCSeEoUVxmo3zmmpo4wHFWTADDvoaGY0sHTk3epXHU9nHt9G/YcqwnsgzXXQeff16aZKEWUPJJwtj9rXCVwA2mOjCgzEC10kDuX1Nhp8L323FOTAAXrhRZ4hU8nhJcNuFYEddCCCXKb++vH0CJcEaW4chXoo653gL2bGRZ5ly2jtxcHU6nhHy6GQanGYupkHrxZ9DrioPIssc9Axi3Q5SrLA7eBnk8r879F1+tuoF9aZ3p0B6mv+umUSPo0kUiNlYHmHA6i7+zY5CkMUhSqViiqAju+f5FaK4vKWvS9/1B/DpxZUnQsvh7X7xdsXvGxb/2Yk+WuD9yn22OtesjSPkGisywJCuWSx3XYNAZ0Ou9XTvKcvjcQZafWIxOJ77/fZv0oH8T5TrYGucpLW8Qv5/dr8G+d0RQK5jgV0XQW5XLs0D1yAQ21fGIFKpYvJE0UrkcU7TI3ATLJwpBW7DfAUOcOHca4wBJfM75R6EosNX76h3tVSuxXXJJdJwnzp4VTlZqXHddZAUUalnODRqUlkKLNO3bq7tzf/45TJwYvRIu5xnVKekL4DtZlu+NyJFWNcZ4uHAFrJgIZzYIl5+/I0W+bqIlWCNYg6oGceqUukBBkqBz5+j2xx/j243nhRUvhH2/9WPqqy7zl8hf7ARYXdDrYcYMUfrr8cfF56rmovV3JqJ3lQEuYsVcDLT1TP2B94H+oVwAy+zzbeC3SB5bVZIShL6hSQ2s1JCel47THb1f6Q+7f6iUeOPpxU+HsTcV49mlz4Ys3hj95WhszvA4mARLgbOAUbNGsfrW1VFtN+IEJd6oJrJGjbKoWcCXJWIW8mrtyLLslCQpG6gLnCm/Yrit50Nh3HWwS+E+sUE+rPgMrJU8hd90KSxr4Ts/3wjZFnCWE1Ho3PBNl8qLN2b0g1MKAxpWP6rlPU1MFDlyMBtCHw1a9PN1FO34n8/8OGMcTeo1Ye+Zvb59iklgw47vGdNmTMjtrt/zM6bZ/6CwnFMBwAVdJqA/PYd6iIBfWr53oMPmsLE7YzcT2ivb9CkhyzJHzh7xmR9rjGVki5ElrxMtidS11iU139cucm+m73sRLGrCEYfbQdu6bUPer0boXNDyAn7Y/QN5dm9/30NZh5BlWUnopsqW01vId/gO8HSs1xGTvhoEFKLHRqCtJEktEVlZ1wBTyq0zB7jXI0jsD2R7rmMZfradA9wEvOL5f3aZ+f+TJOktxMBjW6Di1ilVxdSpYRFehBOj3lji8FHgKICGDbFmlrofuRrUQ5+2x+8+buh+Azd0v4Gd6Tt54s8nmH9gPmcLz5JdlI3bkzU9sf1E/jPqP3Sq38lr2/fHv8+alDUczDqIW3aTVZDFzE0zua//fT7tuNwu7ph3R4kwLsYYw4sjX2R8u/H0mNmjRPx32r4fS/sVDGs+TLG/Z2xnuPLtz0qEG7HGWGZ85uLUMonp02HNGlG7+MYboW9faNZUJtaYiTPnJLIzX2SayzLojUiGWAwJjcl31OXsUR0tyzYkV+IGRR8rBpFPzofk0aKESAUyqy/v+zO7TnbG4bayZo3IGGvcWGQlBxtQKmh0I9asjZAyRzx/rLgcuj0vyh+4CsR7oDMJxwxJB12fhS5PeYK4TnH8bjss6Caysl02SP0T6vQSLiQVtfhHEkHK03/C7BacibuelMKBpOa1JPVcMmlnzBTZ9Tic/0aSnsRocBMX6yK5bh7JiadoGLOPZsOvJUY+xrEd+1n8P5nFq/az+2B9UrMSwRhPs2YQH+fGYgG9fhUFBWCz6UhN05GVYaN7iz0seWokkuwQx5a1RbiquF3CBSVIflh/FTtTuhIbC23aiu8bCKcXm8e8Q6cr1XDJshj4lGUh3NDpYESPlvxwKkZc0yTYn7+BWg0zqRtTt6SdYsFS8ban8k5wKHsPbsTvMrZBOoUXPIBB0iFJBmZlSuR+mMpA96Pk5YltTKbS7WUZnBTyetEIbGQCEi6KmNB2ErOn/FzBz1OjxmOqBT1ehg4Pw+6X4fAsT7migtAt43UmkYhiqgVt/wl/PYeyKVclcg4sSeEpGWKqre4MEk0S2ldd24e/hI3/VC+hU4wlCZpMghY3CPckQyw4Cyj9HCVxTXA7RHmqY9/B7lcUd/XHjgtVs2VvvTU6goGtW4XjUHa277KWLSE5ObLtq4k34uMj225ZzGYRAzh61HfZ0qXRE5Gch1SnpK/zH2McXLBYlGba9pi4P41omfpq+B47fMfnSrBG+GRWQ0hJEffoSrRtW73Od70bhlb2ORD+EtBMfoa/isXo1Y177xUiw9tug9Wrg3PhqAzWGmaQH2lJsL+LWDGTgC88WcbrJEmq5cnqauFnW9ULqCRJlwKHgfNWppfj51xeTH11EVa15btd30W1vcVHFldq+292fhOmnlScLae3YHfaMRkqFpT4cNOHrDi+IkK98s+alDW8u+Fd7u13PgmFg7jqhfumO1AWXFDoYEo1uqOJAJIk/Qko3d0+FewuFOaFxUI+1G3CbT0fCil19Byv5fvdOWuFVc1gdBDOUGrkmOGbrsouFwYnmNy+4g23DhZN6gwLd4bcrtPtZPt/4sHp+wTgtpoZ0XyYYkkvi8HC5tObGdR0UMhtLzu6THG+3W3ntp638eyyZ30cI2x2G2tT1lZKvLHq+Cpyi3zrWceZ4riy05Ulrwc0GcDsfd6luhxuB5tObapQe2n5aSiZyUiS5JMd2iO5B78f+t1n3ePZxyvUZlkOZCklrkDbOm3RaQK7KmFw08GKbhl6Sc+JnBM0SwxeoLbx1EafeRISo1uNrlQfaxoeAeC9wEKEa+GnsizvkiTpn57lM4EFCLfDgwjHw3/429az61eA7yVJuhU4Dlzp2WaXJEnfI57NnMA9nowxjTBgNVoh0zsSoU/30XWq0qVBF+ZNmcfujN08/sfjzDswj8s6XMbLo16mQ70OittYDBbmT5lP5/c6Y5ft5DvyeXDhg3y05SP05YLhmbZMTuYIB0IJiUFNB/HQgIeQJIknhzzJK6tfweawYXPYeHLxk6y+RVnA/drq10pEJQadgcHNBnPjgIkwAJ54zEH2oTVk71uE9dyfWLcdxbIjBzmxK5K5CZI+ptRlwVkIbhsUniAuZycGZzzyiC+Qtj4isofnd4W2d0GLKRDfTmQkyy6E+4MEEw54RrM8wT+9RQwaG+KF9fzeN+HI55C2RLhv1BsItXuQRwtOnDRRWGTA0egkeoMOk9FFw2QndWNOI2X/xb87beDq/1h55RVR17dbNxg6FPr3h549XPRoe5w6xoMYpVwMOjsg4XCbsMu1SC9sx5Y9jdi+vQFvvPEdFJyGtGVwZi1nlz7Blh112Jvaie0n+rLtSFsyzsbjcOpxu3UYDS5iLEW0bZJKr5Zb6ZS8hS43HKGj9A7SgfdEMC5lNjQaC/WHQK2uyNbGnDkjkZ/norD9McwWiZhYAw0ayEiFqZC9EzLWkN/6eb74QpR/2bhBBklm8EA3nbtAjx4SvVrpMJvBapVwuaCwUKaoUOb4cSs/La7H9u3deFKW+de/mnP4cHPMZrjsMnjtYejVS9SqLixUHmA0GkGS4ti7ty9Sp8Ow/Sk4+j/YdA8c/hyaXg4NhkB8W5AM2IucOOxunMP2YzBIGE06TGaD+A7k7GdTzxWk1+3Dli1w4gS8/LLIYHY64d/Tk4kvI2LNi0vi3adSS/pVWCgmt/FSHJbbvX5LS48uZXKnySXzih03il04lh5bjEFvEIbpgIzMpxM/5a4Fd5Xc+83Ofo6X755Mi1otFH8/T/w5Fcf6LJzOQiQkGic05vPLziP7cI2KY6kHvd6Cnm9C5kY49i0c/x4KU0WpIyRw5lFyriumuPSS7Bbnvthm0OI6aHY1JHYSX94dzysLQdx+1O6BuNxXsO2XnxtBoUIRc5OyfXh0kcCo4EAUDQ5/CRvvVHdHAajdE3q+AfUHCVGfMa50mVK0R2+G2j0gvr2qeGPVvqGqzQ0eHGTfK8nmzequE5dfHv7huPKoZQlHo1xMWW64AV591Tcj3e0W5efuvhss55kRchSoTklfAFdIkjQM2A88JMvyCaWVqkPSV8hIErS/F5IvhBWXgu1EYEFaKOhjRNm96oa/R2lzDQz0RYAjvjlhJfTpU73ECTqdjkRzok8p6soyts1Y1WWBnDeq0/tTlmbNYNEimDMHbr9dXNdzfYesQ0aSIDZWCB2/+ip8+40GkRZv+LuI+VuncYBtFS+AkiTFIkQco4FH1TpVoy9kBFaRxcVVnxpGFeG3g9E1S9lzxn/mmj9WH18ddfeKssjIvLXuLZ4Y8kTQ25wrPMd9v/tmzpVFL+krlUVe5CzC5edm4+GFD3Nd1+uobQ2mAHANQBdE8UzZ5akbHSbCkZlSfrDmPESWZYUiGAJJktQs4Mvizw4+nBbyxdukSJJkABIBP155VctdN0znX3/8yyfLPd+iY8F79zN67Nsh73vZvjlYf7kBh4IbxCWdJ7HmxBpstgyfZfsz91PgKBCBrhDYkbYDo85IIb7ijaHNh3Jzj5tZl7KOXLv3nWOhs5AVx1aELN5Iz0/njE05ENc9qTuTO03m6aW+Dk9O2cniw4uZOmJqSO0CLD2ytMROvywOl8NLFDKq5SgWHlpIYTlhy470HRVqb0/GHswGM4Uu7/043U461uvoNW9Y82EsPrIYRzlnI6fbSVZBFnWsFRucdctuTucqDPJCpYQ3GpWjRa0WmPQmn9I8Br2Bnek7KyTe2Je5z2devDme4S2GV7qfNQ1ZlhcgBBpl580s87cM3BPstp75mcAolW1eAl6qRJc1Ikyn+p2Y+/BGSAP4BZLWQKp6sKxNnTbc2+9e3lr3FiDOoYHO+ZIk8cnET0qyBJ8Y8gSfbv2Uo9lHAVifsp4rv7+S+rHeg452l51Z22bh9LhiGCQDn036zFNG40vYfB+JMiTqTNDjAWh6hbB2dxdilN2UCC+QPBnXMsxtDxQQZygQwfzLTot62KmLydi/mS2/vsmhlHrsSe3OzpPdSDtXB4fTiMutw6h3YTYV0TrpBF0bb6Rt8kHaTnmPXr1uwdT6Fs6dyee3n04y72MdO/fFcexUAvkFJqymIozGQkxGcLqgqEiiyGFCr29E0+R42rfqxjdzZT76SAL7OQoOzqFw37eYC3ZgcaTi3GXG6TYiWZNEsEyWMToLMRZm0FZfRAedi8t7N0a2b8ZpaMhP667lnXeuZetWkW1rNsu0aSPRua+wna1dWwzcFRTAoUOwd28SX6/tRlrazRx4BKSkJ6DLE1CQhpy1hW3rzrDiqyJ+W3GGdbtqU+gwYdA70UkysizhdLkx6N3063iGi4facOpG8OrnMna7hNkM/31H4uqrJQoLhWBDOTjk+ZyAvDz44QeYPFn0MS4ONmyARo3E38UEciXp1QugAfT/CHfvmWxZfoCVS86yboOJIylWTmXk4ZBqYTJbiI0VDh6FhRJ5+TochXYsunwa1Y+nZZNhfPSzzNixChG+V7yfu+Ly0nhC8fE7nr3fjGbe/nkA5BTlMH//fC/xRnlm75td4j4lIXFph0u5sceN7M/az1tr36LAWUChs5BxX4/j+RHP+2Thnsg+wdtr38buCZzHm+NZetPS8+c5W6NySBLU6yem3m8JZ4W8g5CzF7L3QNEZT6Df47JgbQgJHYWbT1wrUHQu01GiNiqLK8wlWvyhJk4w1wnvmEsomOsJt4pol01JW+5fuGFpAP0/9ZR0sYjB4oq8VQblZ2yH00BqtnImePPm/rN/w8nKleoW+hMmRD7DVk28YTBEXjhSlptugjdUisa/9JIIhmniDV9qUNLXXOAbWZaLPML8WcAFSitWh6SvSpPYAcb9BQdmCvGYM9cjPKwkhjghzO70hHCUqnb4Gas3RtHOpxpz3E9OV6dO3s8S1YEbut3Auxvf9Zk/oe0EZl87W2ELwcmck7Sd3tZnDNWkM3F156tVt/N37S0srF7OJEpMnAgXXwwLFsA77wgXTklSd1sJRGysOOaJE4XDx5Ah0b02h4NI31UGc0FSWyeUi9nzwNuyLOf5s5iq6ReyQD80q1XcQEbrZjlcbDgZXaflQmchhc5CLIaK38HO3T8XHboSm9PyFGd8Viajd9nRZT4n6bIsObIkaPGGLMvc+MuNfn9BFr2F5Tcvp1FC6HXUUvNSGfrpUL/9vu7n65g/Zf75YQMnBSHecLvEOIdGdULNAr4s/uznw2khX7yvtcBkYImsZFFQTbiq81U8tPAhn/lu2c3c/XN5uxLijfn75yu6QcSb4rmz9500jm/MB5s/8BGIWY1WNp3axNDm6pk//lh5fKWPUABE6ZIbut3AuLbjKFIYlLS77Px24LcKiejKsvr4asx6M3aX92iT1WDlhm430LxWc+rH1OdEjm9CxdbUrRUuLVGMy+1SFS+2qNWCBrGlCSX9m/THpDP5CFuOnjtaofZ3Z+xWfA871+/sk83dq2EvrEYrjiLvz8RisHAg80CF67ifzDmJUWf0+YxjjbEMaDKgQvvSCB/FriuLDi3yml/gKGBH2o6gS8NlFWRhs/uKaQudhQxsMjAsfdXQqPGkpSn/rcKbY95k4cGF7Dqzq2SeTtIheR7P3bLbSwD4xWVfeAmujHojL13wEtf9ch0ALtnFj3t+DNju5M6TaRTfCLb8Cw68L0qVxLeBMRtFcLG4tEf5oKKaK11hGmfPSXz5ZTc++KAbBw+KwEWLFmJwb8h46NoVatUSQRa7XQwI7trVnC2HBvPZLxKbnhLzHnkEFi6MxWhsh9UqXCJeGAcdOkDTpgYsFvGMrtOJ/0+fhgMHYOlSMz/+WI9Y4zlYcy+c+AmrZMAq6aD1ldDsKkyJnTBZkkT2erHtv2QQgchfG0PRGWLlIxz86GIufH0dmZlCADFiBDzzDAweLFFQII6h/IBlUZEQSBiNEjk5kJRUumz+kiQefvhiTp7E444h5terB82amTGbxXuSkiK+Nku2dmf17u7Y7aVZW/fdB9ddJzKMgy0BExcHu3eXBtuSkqB169CylIuK4IUXYPp0PbLcgcaNRab13U9D9+7CSt/hALdbj9vtiVnqwWi0kJPTkG3bGrJggRjYqyy397qd5UeXl4h9lVzEipFlmaVHlpa8jjPFcVvP2wB4ceSL/LDrB/Zn7cctu9lzZg83/XoTxnJJA3n2PK+xiFmTZtGmTpvKH4jG+YnBCrW6iilUJJ3yeJLjrEe0EMTYSGVRSxQy1RZlXqoSayOPC0kU/bhzDsDyCerCjfqDYfhcUf4rzKUEU7OTsRgLsdl9T6CDBkWvbv3mzerLunWLfPtq4/PRTqhs3RpatYJdu3yXZWXBk0/CK69Uv8BmVVNTkr48YvpiPgJe9bf+eYHeBB3uF04cpxbAzheFIFvSiRKGwWKIFffXtbpCl2eg0bjqW97cX/kvKcrCwGqKnxwEWrWqfoH5/k368/n2z33KBe/P2u93PPXQ2UOKCXBWo5WkuCSVrYRDoRrp6dG7NlcGoxEmTRJTairMmgWzZ4vrW1GReOYsLPQVblosYpnNJp7vu3aFa6+Fq6+ObimzcBPpX34wFyS1dUx+tlW7APYHJkuS9BpQC3BLklQoy7KvxKkGE0i8YTRWXxscf2QVRD/ZfN7+eX4zYpSQZZkvtn+hKtwAGNxsMAtvWFipvt234D5mbJpRYiVcnpXHV5JTlEOCOXAhyU+3fsqSI0tKMnPKY9FbuKvvXfRr0q9SfW6S0IT7+9/P9A3TfbJpQdjtrzi2gg83f8idfe6sVFvVgmAGKNxFRPUBXiMYFC3gJUlqBHwsy/K4cFvIe65LU4AYSZJSPO1MBT4BvvTUucxCiESqLXVj6jKo6SCWHl3qs+xEzgky8jN8MmuDZf6B+YpuEACjW48m1hTLl3996eOAUZe6ISIAAQAASURBVOAoYPmx5SGLN3478JuPswSI0iXj242nlqUWvRr2Yl3KOp91Np3ehFt2hyTUW3xksc8NPIig2GUdLwPg0g6X8t7G93yuAzIyh88epnWd1hVud1fGLkx6k4+YwqAzcEXHK7zmdU/qrngu10k6TuaepElCk6Da3JK6xec9lpAY2XKkz7o9G/ZU/DzcspsDWRUXbxzIOoBRbxS/yDLoJJ3fWpEakWdM6zEsP7rc67vocDtYf3J90PvYlb4Lq9GKvcj7/qZ+TH3qxtQNW181NCJKcnJQogpAfUQqKcn/aFYF2XznZnp92Iu9Z/YiITGq1SgWXr+QY+eO0fG9jhQ4C4gxxvDqha9yXdfrfLaf0m0K/1n1H3ZmlJY1KysAAbzEmDGGGOG6AZC9q9QiObalt3CjAizeeSFX3lsqYHjwQXj0UUhMFM/TMTHK1rKFhcI9w2KBP/8UAz42m3jrX3kF/vlPMfBVPgBSHKjR60XWcfPmIrvn6QcPwbyhYM8Ugb3m10L/j8UAbVnbeqXniiLh0HX6bDJ9/vU7OZ5SIo8+ClOnlooO1IQTwplD/F287pkzwl595UrI94x9Dx0Kd9wBI0cK8UbZkiUWC2Rnw4oV8OmnovSL1SpEEf/7n8hs7tlTWLMHExRyucR7uHcvLFkChw/D+PEwc6Yo/epwiAE2f4Gv/HzIzBT9PnNGfD4PPCBKnuh03tnFagktdevCqFEiyBgOxrYZ63W/ll2YzdFzRxVLnuzO2I3TXXpjotfpGdZ8GCDEjetvX0/yG8kl18cCZwFGs7Hk91PkKvIai7i5x81c2vHS8ByIhoYaOpNnbKMcBami1EpUxBsqY3D62KoPbFkbElRZ3XCy4U71bPQGI2DEPBG4jAAnMpti1PsmQIA4tyYEHqasNLIsglFKJCVFp669mkV9VWQ333UXPPaYuCaWZ+ZMuOceaNvWv61+qOTnh0cIWc2oNklfxTEwz8uJQOhW4jUNSQeNx4sp5wCcWQ1pK+DMKsg7KlzrJB0iB1z2lP8qgtjmUH8oJA2DeoMhoW0VH0gQ+BVvVFPBSZQ546eKaHUsrtAjuYfX828xKTkpfrc7dPaQYpJh5wad/W5Xq5Z49itSuF1LS6t58eLkZHj8cTGBOIbt24WQIzdXXHv0evFcX7u2EG126yae988XIn136+8iVswc4F5Jkr5FiC+yPaKMDD/bKl4AZVkuidxIkjQVyDvfhBsQnHjDXcOqImw7vU01aBdJ5uydU2HxxtqUteQo2PoXYzFYmNyxYvtUYkL7CXzx1xeqbeklPT/u/pFbet7idz/7zuzj/t/vL6mdq4RBb+DZ4c9Wqr/FPDXsKd7f9L7q8nxHPg8vepihzYfSqX6nsLRZZQST3VFwCky1It4VjeBRs4CXZfkUMK7M67BZyMuy/BjwmML8Qjzij5rCnb3vZNOpTT4iCrPezJIjS7i6i7qFmxopOSmKJUR0ko6ru1yNQWdgcFPlwrkOt4PfD/7O08N8S4wEQpZl1qasVVzWrUG3khIdN3W/ib/S/vI5j+okHbvSd9E1qeJZbIsOLVK87rWo1aJEFHFph0uZtX2Wz3VAL+lZf3J9SOKN9SnrFctbWQ1WJraf6DXPbDDTuk5r9p7Z6zXfpDexO2N30OKNrae3+syLN8czpOkQn/kNYhsQa4z1cSTJt+f79CMY9mfu99kXCGeGGn8NquEMaTYEs97sIyTanrY96H3sTN+p+PkWB8E0NDRCw2wwM+/aeXSb2Y08ex6rjq9i2dFlvL32bRxuB2a9mVEtR3FPX8UqPAAsuWkJraa1Is+eh4REh3oduKHbDYAQof9x6A8cbgcGnYEF1y3AUGw133cGrL4WsndA6h+w7lbo/baoT43saxt8eTnRiiOXPXt0TLw9tiSAMWeOECYEIy6wWMRks8E115QKHKZNg3/8o2K24xYLsPYeKEwVfU++EPp/BIYY5Q1UXERmrbwRm92KLAtxxf/9X/BOF2Wx2+Gii2DnTiGSaNQIvv4a+vb1DrqU37fFAldeKWxs9+6Fhg3hrbfE+zpihBgkGzhQZDj17CkGz0wmsR+3Wwwg2u1w8iRs2gQb9pxi/HNzaX8drFsHm1Z1oG3b4XTsKLbv2VNkz8XEiOCbwSA+j+0Zm9matoljx+Dg1mTOZEygsEAMZj/xhFi/ooQruGfSm7i84+V8vePrEmHv4sOLubXXrT7r/nH4D1xucS+ml/Rc3+16LyeyWpZa7L5nN30+7MPZwrMYdUYGNRnECyNfIMOWwRXfCbGtWW/mmi7XlAqfNDQiibmOsK4vT2GquiNG2FEZ6NTpqz7d1too+gKSzPUoCkYSOsDwORETbgCkZDXBLSu/5+ESxQUiO1td6NezpxAiRrpUiJoQwumMfpDs+uvhKZViHy4XjBkjgl61w1xdKz8fPvpIiGTPM6pT0tf9kiRN9KyfBdwc8aOvjiS0FVOrm8VrVyHkHxfuQ64iIeTQWyG2WUjC7yrHr3ijikuDVQPsdmVxWjENG0avL8HSvm57xeQ0h8vB2YKzquUO957Z6zP+LCEFLP2clCSewdTEG5EQ70WTpCTxLHvRRVXdk+gR0Y9M7SLmqc9VXIN5ASJYdhCwAf/wt61n14oXQA1BtO3ZwsF3u76rknZXHF9R4W1mbpqpmIlcjE7SMbbN2Mp0C4ChzYYqnuCLyXfkM33DdL/ijSJnERO/mUiBQ72/McYYnhn2DLUstSrT3RISzAm8MPIFnl7yNPkOZSuzAkcBE7+ZyM67d4ZUtqbaENMYzgUIMuUdhkQtQKhx/jCh/QScs3291nLtuczdPzck8cbiw4sx6o0+QVyrwVpiI63X6Rnfbjzf7PzGZ/stp7fgcrt8SnAE4si5I4pqZqvByo3dbyx5Pan9JB78/UGf9dxuN6uOr6qweCPPnsfRc0d95pv1Zq7vdn3J6yHNhigGpnPtuaw4toIpXcvrYQOz9OhSRTGfjEyfRn185o9sMdJHNFHgKGBX+i5GtVTUMPlwMOugz7xCR6Gqi0a3pG4sP7bcp3/bUrcF1V5ZdmXsUrxmN6/VXDhyaFQZPZJ7kOfwzRY8fPYwgz8ZHFRZngNZB3w+X52ko3/jijm0aGhUKWF0zAgnLWu35MvLvuS6n6/D5rBxw883kFWQhdPtJCk+ia8u/8rv77R+bH1+uuonLvvuMmwOG4fPHubKTlfSJKEJr61+DYfbQYwxhscGPcbwFsNLtjvikFne4A4wbocza+h+eB49T/ws7I5r94A6vSCmqQhKGWIACZw2lhxfw/GsfZB3lCVzh+J2vwBIGI3CHaKi5OV527F26hRioN+WQklwLaap31XVqJ+QgVHvwOEyk58v+hWKeOORR4T4wuEQAa0VK4RDSLADeXFxIiCm18Obb4qpoEBkP6WkiK9yxwuSic8XApSz5iRuuyQVo1FkQDVvLgZWY+p+wn2/vSgEO/VBvkzm9KJ8jh7RcfKk2Nfq1XD2rDhWl0sc77eNLqVQdwZdvIRzkETy2dWc29sDm02Ub/nmG7FebGxwx+RwiP6HK0P8lh638O3Ob3HLbvId+Tyz9Bl+O/ibz3rLjy0vsUHWSTr+0eMfPuu0qt2KFf9YwYCPB5DvyGfFsRXYHDamrZ+GU3ZiMVgY3nw4n076NDyd19AIhCUZ8o/5zi84jXLV6wigFtiS9FWflWyMB12UoyIuhSiWpBOlUiIo3AAh3ihyKI/lJSdHtOkSTp+mpMRXefr0iY4ThD/xRrRJTITXXoOHHy4VnpblxAnhirJ8efgs5PPz4bffRJvnm3ijmiV9PQk8WYHu/z3QWyChXVX3Ioxozhv+SEsrFdgrUa9edPsTDEa9kWaJzTh09pDXfIvRwqGzh+hj9R2DBfgr7S+feXGmOPo0VF6/mKQk9bhwWlpoz48aVUvE7yyVLmIe0Ubx3zKgmLITygWwzDpTQ+hujaC4lq4aDkfVi84ryp+H/6ySdgPZFJWnwFHAT7t/Ui1lAkIM0a5u5W8erEYrvRv2Vs0KB6HEO3L2CC1rt1Rc/vDChzmRc8Kvq0msMZYH+j9Q6f6W5e6+d/PKqldUxRsyMqdyT/HAbw/wwYQPwtp2VEnoKGrv+SN7d/WuqaehUUFijDGMbzeeH3f/6HNuWXhoIbIsBxV0Lcuve39VLCESZ4qjX+PSck7XdrmWefvn+bh+6HV6dqbvpHty9wq1u/LYSnT4/jbdsptLO1xa8rphfEPa1GnDrgzvIrI2p43fDv7GXX3vqlC761LWYTVacRR5C0d0ks7LDcqkNzGo6SCWHFnis4/y4oZgWX1iteL8US1HKYpfmic295lnd9t5eNHDPLLokaDaVLoGuXGTHKc8sjek2RBWHV/l4xCyL3NfUO2VRemhB/D6XmlUDSa9CZPepChUXZOyJuT9umV3WO7DNDQ0hAPUzd1v5vPtn3M67zQu2YXVYGX+lPlBlW68qPVFXNL2Eubsm4PT5WTq8qkMbjq4RJiYHJfMv4f+22ubj7Z8xGurXysReOt1ek798y9i7WlQcFKIIU4tAEeOKEOCzP6CIsavm49O0gMS+XUOYdE9CxhxOGD6dLjllooFcho0gMmT4ddfxSDh3XfD0qUiOFIRhwdHxxcwbrxeZAUe+waaXQUNhoBBwQakvIuIhxsmw0d/wV9/CbHBsGGipIvJFHwAJicHPvlEbA8iwNOwYcUzsPTlbhWsVhEk61M8lnhXqXNI7aI0fvrJdx9tjo1g9jdvlDiLxRnjyHDvp3fvDvTurdL/ohxmvZaG0+0AGeKt8Tw+YwXm4/F8+AGs3GqhU6fG9OsH/fsLR5AOHcQgr8kkjtPphMIiN3vTjnDwAKxbD7s2J7JsQXhGe4c0H+JVDuV03ml+2qPwBpTBJbvokdRDcVmXBl34/srvmfz9ZGxOG5d9dxlFriJkWaZ5YnN+uuqnkEr3RRtJkuoA3wEtgKPAVbIsn1VYbyzwDiJ562NZll8JtL0kSU8CtwIu4H5Zlhd65r8E3AjUlmU5rkwbNwOvI9x9Ad6VZfnjcB7veUtME4/TQzkKU0W2c1RQE29Ug1RSnREUniujTvMpYEmq+PiTivOTGofTWmF3+X7uBkN0SqaAEAyqBamGDROu1JFG7Rp67lzk21bi1luFsHL/fuXlW7fC4MGwYIEIdFbGmcRmE+VYHn+85lnxa2hUT/yMo1b2R2ZJqtA5vpRqcF3zcO6c+jnXYKi+pZv6NOrjI96QZZmDWQcVE+hAJCmVR5ZleiT38NtWUpJ6NQabreZVatCoTr9AjaAJ5KzhcNQ8943yAbFo4ZJdnM49HXhFD3P2zUEX4M0d13ZchQOXalzZ6Uq/zhSyLPPpVuVsmwX7F/DZts/8uoTEGmN586I3MRvC+7Bt0pv479j/EmtUv3IWOAv4asdXzN03N6xtB01BKthOikyRwnQoygJ3BeXx8W2EJZs/8g6JwVoNjfOI23vdTpzJN+iQb8/3uSkNhCzLLDnqK04w6U3c2vNWr/Ppha0uVHSicLldrDq+qkLtgihdopT53yyxGU0TvbNjb+h2g+L5ePWJ1cgVfJBaemQp+XZfcVsdax061OvgNe/qzlcTY/SNEh3KOkSRU8ELzw+5RbmK17w4UxxXdlI2MVNzxwAhygjmnxK1Lep+rX0b9SXW5Hv9SMlJqfB7fSjL9/toNVgVS7ZoRJ+uDSpecigYxrQeE5H9amj8HXl77Nu0qt0Kl+xCQuKtMW9VSCz5/iXvYzaYccpOftj1A88sfYZ8Rz5Wg5VvrvjGxwXp8cGPU8tSi3xHPvmOfJxuJzN2/yoED82vho6PQN/3YNCXMOQ7GPI9T58zY5ch32XH5rLTs319NqzX06KFEDfcf79wZli/XtjInjsn6uSWT4goKhI27Lm5YvryS1E/3myG48eF+8bUqbBvn3jmzskR69tswp69oEBsl50t9pWWBjPmXg5DfwFjoggwLhsH6++AM+vBZQd7tphcdlF6wO0U1s/2bHDkgqsQU+YiVq4UQRmLRQRlmjUTWa5r1og2i4+r7JSXJ/p5/Di89JL3gOfFF4dWZiQcDGgywPt+ToJNpzb53Wbr6a1YjaXPXYXOQh5a+BCPHuzB/lE9kB5sxWtfbuWSS8Rx//e/MHasKOXSpg00aSL+b3n9Gwz+uhO3bOjBh/pubBnQRTFrOxQMOgPdkyomJB7SdIjf8YVxbcfx0gUvEWOMIbsoG5vDRqIlkcU3Lla8V6qmPAEslmW5LbDY89oLSZL0wHvAxUAn4FpJkjr5296z/BqgMzAWmOHZD8BcQE2p+50syz08kybcCJbYFsrzi7KiJ55QfQyoxACoJSn0bcsiGapHwk63F33LiwVDBYN6B9PaKM5v2FBcD6NBaqp6IKpFi+j0Qe06WlX29Ho9fPqp/+v7jh3ifmbxYnG9rCgFBeL+5+qr4dFHA5d219DQCBJ/15DKlie7PBWmyCFM1ecH7vA1TS6hXj3lUiHVgcFNB/uMJdscNg5k+go0QIyRn8w56TPf7rbTpo7ytbeYBg38vw9VJSzUCJ1qIE/WqCh6vf8TVk0Tb9iddr8Cg0jz3a7veHDAg0Gt++6GdxWzw4uJN8VzaftLw9MxYGybsTy99GnV5UWuIj7a8hEvjHzBK8CZmpfKlJ+nBHxfG8Y35Lpu14Wtv2W5qvNVTF021W+mtM1h4/pfrmfPPXtoFN+o8o06bdCgLqRn+l8vEZjTCqFqlcUku8HtEGIMYyKYa4O5PsQ0gzo9IaGTKH8S06TU2ia2BehM/sUZ+UfFfjU0ziMuaHmBaqbfH4f+CHhDWZad6TtL6n6XRS/puanHTV7zrEYrI1qMYOGhhV7zC5wF/H7wd+7pp2jkpYqSe4VJb/IqXVLMFZ2u4Pnlz/vMtzlsHM8+TvNavg4Vaiw8tNDHVcIgGbi267U+617c5mIe+M3XHclqsLI9bXuFHCQ2ndqk6Phhd9kZ00Y52D2s2bCg918RBjYZqLqsZ8OeOFy+501ZlsmwZdAgtkFQbbjcLtLyfQcijXojPRv2DL6zGhFjbJuxbDy1Maz7TDQnBhTaamicdyQni0hBMKiJzJOSFEu4mPQm5l07j7bT2zKgyQDu7H1nhbpWN6YuM8bN4M55d1LoLCS7MBuLwcLNPW5WvIYlWhKZdeksrvrxKmwOGzaHjZdXvMy9fe/1Ct4Xc/jsYebun1tyXbUYLHx9+dccyJrHm/NktmyFxfNq88fcYSxeLJwzWreGpk1FML92beHMUFgIe06msD1jM5mZ4q3Ytqgzzz3Xhnvvha+/hi++gLffhvffFyVEGjcWpUCSkkSGr9MpBsWOHhWlP86eFUGOBx4YIwZNj30Phz6GEz/ByXmgj4GYRhDXCmKbC/tn2S2eLfIOQ+4RKDxNur2AL1o8T/Nr4clJcGx7c7Z/cyVffSVKhZhMItusaVPRL71e2MgfLtxIesxyZBmKchIxO25BmBpU7eCdUW+kX+N+rDgmSpjm2fNYc2KN4v1XMRtPbfRyamoU34jUvNSSZ3OrwYqt7mruvdj/9X3E5wtYfsyOE6HY6NK4OyZTZY+olCeGPME1P10T9PrPDn824DoPDniQnRk7+XTrp+glPX/c8AeNExpXppvRZhIwwvP3LGAZ8Hi5dfoBB2VZPgwgSdK3nu12+9l+EvCtLMtFwBFJkg569rNWluV1nv1E4nj+nsQ0EWMf7vJqJ1kE/mOi8J2UdMoCjsoEtVQcj1T5Ph6cSmOClciKDjkjuhzWhmCNTs2Sk2eVP+8mTfyPV4eT1FT1IFW07PMbqQxjZmRUztWiMgweDFOmiPuWApWhytxcGD8eRo6El18WQkeTyb9bSV6eSP6fPl24e2RlRab/Ghp/WyIp3jgPcDrVH2NNpurrKtEjuQdmvdnrOcYlu1RdgjNsGYr3r61rtw5YKrx2bf+CutRU8dyqUXPQxBs1kEDqXX82QtURpTqw0eT3g78HJd44nXs6YIChyFXEBS0vCFPPoEO9DmIgyqFS0AvId+Sz6vgqhjYfCgi78Cu+v0K1ZEkxscZYZoybETGrVZ2k4/1L3mfCNxP89sXmsHH5d5ez+pbVAS9CXsgy5O6H1D8hZTac3Qb2s/BuDMjFD9R+HqDVBBcum5gKy2SnH/9eDKa67WJANbYFNBwNiV3U664Wk3eketh4amiEEb1Oz/XdrmfmppleIoQCZwG/7P2lQmVE/jj8h4+QAYT7hVLpg+u7Xc/qE6t9hHTFDhjBDtJm5GeQYcvwmW/QGbii4xU+89vUaUOD2AYcy/au9WzUGVl5fGXQ4g2Hy8GO9B0+8y1GC1d1uspnftPEpiTFJfm0a3fbWZ+yvkLijbUpaylw+J77WtVuRb0Y5REunU5HgjmhxNo8XIxrO051WdOEporXJovBwoHMA0GLN45nH8esN3tZmIO47nRL6laxDmtEhJu638SLK14M6z77N1Z3i9HQ0AiN5h36Y09zACvhFp2q0EONKV2n8OGWD1lxbAVu2U0tSy1eG/2a6vqXtLuEsa3HMmf/HJxuJzanjX/M/gcXtrrQZ92Pt3xc4kRl1pt5athTFDoLmfTtJOJMcegkHY6uDmb/3zyauS7g0CE4dAh274aNG0WQyeEAk9nNql7DcbZMR99ahx0bT/55OT9c9R116wr3jvvvF+sePQrN+iVj3pwGm0U/zlmSePDqVOLiRECkXTto21YIRQDxLNHqRjG5CiH3oHiW6XkTZG4V69Q2wg9DQWcWIvLWwyGhPfOP7+Dff/67xM1Kh45TKy6gjrUuJ08KJ5C9e4V+p6BADG5arbDTfD12DqOTQIcb/YlLoFBEmh55RNSpryr3jSs6XsHGkxtLkg0COagtO7qsxK1DJ+mY1GESm05tYs0JUWarwFnA0qNLubffvar7kGWZralbS15b9BavcnXh4MpOV3L9L9eX3HtISBh0pc+CTrez5HO0GCyMauW3GrDYhyTx8R3z+SQNwAXP9a7wb7CKSZJl+TSALMunJUlSupFrDJwo8zoFKL6gq23fGFhXbptgFARXSJI0DNgPPCTL8olAG2gghAE6s4J4A8jaHB3xhpqlvFxBB9VKdUFlzMrtDDw2pEZFBSS/Ngfbcd/59YeKz0cfedVAkUPZvbdRo+iV8T5+HEXnJEkKvqRYZWnWTHl+8bW4qsbmZ8yA7dth2zb/YpqlS2HgQOjdW9y7jBkDPXqUBkL1ejh5ElasgD/+gJ9+Cs2tQ0NDIxj8iTeqqTIhijj9XOoNhupbvqlbUjfFuN7eM3sV1z+YdVCxvHAwY7+SJEqXnfUpTijYtAm6V8wkUKOK0SKKNRCz2f/NktstBBzRUhpXltn7Zldp+xtPBpfx+eVfXwYMCnao24FES2I4ugWIgZqxbcby9Y6vVdexOWzM3DSzRLwxY8MM1p5Yq2pVX0y3pG6Mbj26Yh1y2jylRk6JqTAd3EXiYdntAp1B1PrUx4C1ESPjG9E7qQsrUzao9sfpdrLh5AamrZ/GQwMf8t++qwhOzYej30Lan+I1srcQwxHeACMgjtFdRtKfuw/yDoA+Vgg9/JF7MPz90dCoBvyjxz/4fNvnPuKs1SdW43K7ghZj/bznZ5+bUqvBqprZe0nbSxRLpxQ6CzmWfYwWtVoE1e7qE6uxGCw++0o0J9KpfifFba7tci1vrn0TRxk3nVx7LosOLfKbLVqWLae3YNabfdo16oz0bqRc6P2yDpcxfcN0L5FLobOQxUcWc1//+4JqF2Dx4cVefQchVpnc0X/gonfD3iw9ujTodoJBrUwLiGtf5/qd2XBqg9d8p9vJgawDDG42OKg2DmQd8AqYFNMwrqFiKRqN6NO6Tmv0kl5RwBUqkzpMCtu+NDRqDJEO4pZ39QjW5cODJEl8cekXtJ7WGpfs4ovLvlAsv1aW98e/zy9v/AIIh6jvdn3H3P3e5RZlWfZyGpQkiccHP45BZ+Dqzlcze+9sCl3iHuOBhfey6+5dtG+v/Dz31V//Y/W8NOyOfJAhzhjHGxf5CkyMRiHK4Jz3e1CrMI3PPw/0TnjQW6BWFzFllhGMnnXAqMU+q1+c2Afd4ucpconnkQRzAmtOrGFC+wk0aSIynUeV0wDk2fN449UjuN1O3LIokfbIm3/x2h2NKCgQgZiXXoKnnqqYgCM/Pzw1pUe3Gs2/pX+XvN6Xuc/v/ePm05tL/o4zxXFJ20toWaslW05vKbmPXJ+y3m+bKTkpXs5eOp2Oi9tcXJnD8EGn0/HvIf/mlVWvYHfbMeqMnHrkFCa9iTx7Hs3/2xyH24FFb+H/Rv5f0PuVKvkbjDSSJP0JKKX8PxXsLhTmBRqGD2WbucA3siwXSZL0T4STh0/2jSRJdwB3ADRTi87+3bAkq2cFpy+HhmNAH95yvD6otS+7RGArGmVL1BJzZAcQpeCaWiKSpYFwR4kCTrfy+xATEz0n6KNHlefXrSsEC9EQTiQnC7GkksNFdnbVuW8YjfD770KUceJE4NImmzeL6XmP0WixC0dBQfXNZtfQOO9QEwdC4NjD34CaKt5ItCRSy1LLJ3nweI6CCBNR+tldTqwTY4xhQJMBQbVXp466eGP9erjmmvA8y2lEB028UQNJTobMAFUhTp2qOeINJdv6aJJVGNjrTZZlZmyc4RNgLItRZ+SKTr7Z2pXlsg6XMXf/XNWsZ7fs5pe9v2Bz2IgxxjCs+TCeHPKk331KksStPW9VX8HtgpzdohZz2jI4s0Y4UbidYrBR0nvKjNhLH5SRAZ2Q+ekMJQ+NX5iL+Li2jFtnAlNtiGsB1iYiM8NQOmjr17Ekey/sfQuO/U+04cz1e3zeB6sXVsSJnSChgyiJoo8Bg9XjpuEUD7+uAo845QRk74acPcLJQw3ZLfphTAggGJEhYyU0Cu/AoIZGVdOrYS8SzYk+4g0JiT8P/0mvhr0C7sPusisK6Fxul2IJEYDa1tr0SOrhE9jX6/SsOr4qaPHGkiNLyC3yPpfoJT1Xdb5KVah3ZecrmbZhmo8AYtGhRaqWd+X5btd3iteSyzteruqENLH9RD7d9qnPdSBQkKIssix7BT6KsRgsTGg/we+2Y9uMDat4w6gzUiemjt91hjQbwsZTG72EfzaHjd0Zu4NuZ3/m/pJAV1l6N1QWyWhUDU0Smvg4y1SGKV2nhG1fGhoa4aN5h/440zzRg6kXB3QOaBDbgPv63ce0DdNK5vlzIwSYdemsEtHeRxM+Yvmx5aTmiTaOZx/nl72/cHnHy322s7vsPLLokZJ7mhhjDDMnzKxQSbRIkhyXTJs6bdiVsQsQwoylR5f6vX6vT1nvVSrN7rLzwBX9aVwADzwgAjIvvwzLlsG770L79mJQNCHBd1+5uSIYl5IC990HixZV/pg61OuASW8qec9NehN7z+ylc4POPuueKzxHpq10AKTQWcjQZkNpltiMp5aUagPS89PJLsxWTabYcHKDl6jTYrDQoV6Hyh9MOW7ucTOvrXkN3MJZbXfGboY2H8qq46tKPhMZOWLlS6sCWZZ9bXE8SJKUJklSQ49rRkMgXWG1FKBpmddNgFOev9W297eNWj/LjqR9BLyqst6HwIcAffr0qabhgChjTVa3bc/aIsZTqky84YyieEMluGY/5ynDG4VofSARSyhUsHSL06UcTjAao+e8cfq08vzkZOHIYfWttBZ2GjQoFTmU58yZqrWnr1MHVq+Gvn1FX5RcStSw2yu2voaGRhjwJ94oPBO9flRT/F1bqqtwo5huSd1YfMRboG9z2Miz5/kkNOzL3Ee+3Xuc3aAz0CO5R1BtJSUJl0kltm3zL4LRqH5o4o0aSPPmsGuX/3WOHoVuNcQRPMvmXzwRb4onOS70uo159jxS81JVnR8kJE5kn6BpYlPF5QBbU7cq2uuXxWww+7WBD5VRrUb5FY2ACFr+uvdXpnSdQrfkbnRLDuHDL0iFY9/B0S/h3E7hoCHL4CpX8kSxvmcxLqHhcDmFHTDQXAcv1gOwA2lABjj3wNkiMMRCg6HQ6h+QrODblHsQNvxTiEfcjsB2mOa60GAk1OoMdfoJwUZMY9EX2Q2GGHFc/nDmex66rWK7vINiMOLsVvF/5ga8EnqsjQO7faTMhvrDwKhJGzXOHyRJYljzYXy761uv+fmOfMZ/M17R8aA8btmNXcF6t7a1tt/z/g3db2Bb2jYv94o8ex7vb3rfK6PSHz/s/sHnumDSm7iqs2/pkmJ6JvcssWYvS1p+GkM+HRJUyZZ8e76iy8DQZkNVtxncbLCi20hWQRaZtkzqxtQN2G5KToqikEFCok+jPn63vabLNTz+Z/nS5KHTslbLgOv0a9yPOFMcufZSgY2MzPa07UG3szN9p8/106Q3lThVaVQPLmh5AZ9t+yws+zLpTdSy1ArLvjQ0NMJMCM4Bb495m/kH5nP47GFkZMx6c4nY0eawMXvfbNyyG72kZ0zrMV7X8HhzPD9f9TPDPx+Ow+0g35HPdT9dx8iWI32u10fPHi0RB+jQcVHri7iua/UKrF/f7XqmLptKkasIt+xm0SH/Corlx5Zjs5eKXbondae2tTa33w49e/4/e+cdH0dxt/HvXJPuVG3ZVnWXi+Tebdx7ARcMNh3TQ4dUIJCEUBIghAABAgTIS++92WAbA+7dxr3JvVf1q/P+MaeTTlcl3Z0ke7+fz1p3u7Mzs2fpdmfm+T0/uPxytfC1eDH07q3mGIYMgXHjIDdXLXqVl6t5he++g59/DjwRWBuEEIxtP5YPNn6gdkhYeXClX/HG6kOrvYQo3dO7Yzaa6ZTWCYvR4hH1mI1mVh5cGTAVSfW0e5NyJ4Wdbq8mtG3SlvZN2rPx2EZK7aXM2TmHoa2H8s32bzzC4V6Zveo0x9HI+AKYBTzm/unPenUF0EEI0RY4AFwKXB7i/C+Ad4QQTwFZQAfAW91djQoRiPvtFGBzLa/p3COhjWeOx4dTa1SATNQJIFqwnVGBRWGMP+uMwQK+QyrlTBtBJ7mgGFP8Cy2Kdqi5rNpQw9Qtzt/736/TxU68YfX3/4ASb8RqIS89PfD1HjwIXXxvaTElKws2bICLL4alS6E0SsH7sfo/19A4qzGY/d9fAKwNy3GtPgjmpuRwNOzvoSGthrBg9wKvuWCzwczOkzvpUW09bP2R9T5z1aX2Urq16BZWW9lBstht2FB/KTM1aocm3miEdOoE33wTvMy2bbHpS10ptZf6RG1XxaQz8Zfhf+G35/221m1sO7GNPi/1odjuX3SQFJfEioMrgoo3Xlr1UkgBBRBWpHlNSY1PpWPTjmw4tiFgmWJbMc8tf67m0abWk7DvE9jxEpz+RSn4KywYXYGeGOqKq1LsYLMqYcPh+TCzigDCUQK/PAjbnq909wiEIQFaTof2N0JaP5VKxZDgPXAPJdioXl8F+jho2kdtjlJ3ehgbFLwFBa/DqbXK1aMwxJzPkXkB07NqaDRmftX3Vz7iDVDpLSpyfdeGqZ2Cpz0Y3ma4XzHDkn1LWHc49OK+RPqN3i13lAe1ohNC0CmtE5uO+7o/VBUZ1IZgaURMehNtU9uy+bj3d43NZaPtM20x6UPb41qdVr/3sc5pnQM6flTQKqVVRFNbjGwzMmSZXpm9/PZ36b6l3PntnWG14y8tm0CErVjXiA0zu8yMmHgjr1leROrR0NBoGOh0On669ic6PdeJYlsxRr2RMe3GcF2v67j5q5sx6AzYnDZyknP45JJPfM4f1HIQA3MG8vPenwEod5bz7Y5vg7YpkTw38bmoXE9dmJ43nYd+fMjzftuJbZTZyzAb/YcWz94xG4db+G42mLmq+1XM2zVPuXglwJNfGLFunMizT+tZtUo5e378MbxdPVunoRxj3mz0yRJDN+iQmQ6cF5FrmtppKt9u/5YiWxHF9mIW71/MrJ6zfMqtOLCCMrsao5p0JqZ3Vu4pQggm5k7kzfVvAlBmL2P5geUBxRs/7v7RMxmaZEpiWudpEbkOf9zc92bumXuPR2T0yKhH+Hr710gkicbEgOkBz1IeAz4QQlwP7AVmAAghsoBXpJSTpJQOIcTtwBxAD7wmpdwY7Hwp5UYhxAfAJsAB3CalelgVQjyBEn9YhBD73e08CNwphJjiLn8SuCbqV3+2oI8DS0soKfA9Zj8DthNgzoxuHwKJM2wnlaNqLIjPgJLdvvvLDhKzSZ/0kVC0HZ8sQccWqSCkGBBoEc3hiJ1wIlD0cFJS7BbxWrQInJJk2TIYNQr04WWTjRpNmsD33yu3rb/9zb9LSF2Ijw++WKihoREmpqZQEsCRtDSosdg5gTHI0o7d3rDFG70ze5NgSvByUxZCsOPkDh/xxrYTvou6LRJakGAKLyC4Sxf45BP/96ayMhU/kZNTs/5r1B+aeKMR0ratejgqD6IlKChQitqGrqZadXCVVxRNdeKN8eQ3z69TG+2atPPkOvZHsa2YRXsX+bXQBWUx+84v7/jkm6rOqDajQi6A1ZbpedPZemKrj1V/VVYfWs2BwgNkJ4fx1FyyF355CHa/DTq9EkvUJ1XToBTvgu+GgP104FyeoNKVdPsr5N6oXDWMSWp/tGwqDVX+mDreptotLoBD38HheeAK8gdZtENFqRgi4LxRQztLDY1oMqLNCOL0cX4dHerCX4b/Jejxbi26YdQZfb4TJTKoIDAUbVPbhvwev6nPTdw95+5at+GP7KRsLKbgN+x+Wf18xBtQd9HIgJwBYZXLSspiX+G+OrVVwYV5F4Ys065JO7/3vEJbIf9e/u9at211WmnfpH2tz9eIPOPajYtYXePbj49YXRoaGg2DrKQs/jX+X9w9+26KbcU8MP8Bxrcfz+vrXsfmtGE2mHn/4veJM/i36//uqu9o8ngTL0FgkinJ47hgdVi9nmOen/R8eOOpGNMxrSNpljT2F+4HKl0m/LlJOVwOr3RuEsmINiPo/mJ3z7XbnXb+O/m//PzzFTidKhLr559VZG5REZSUqLmEPa2eYlPzh9EbTOiFkz1S4nQVotfVfTVqTLsxXrbAr699nUV7F/mU23Nmj+eZwCmdjGpXmW7zws4X8vmWzym0FWJ32ZlfMJ/7hvqmEHVJlyftDKj/90Aij0gws8tMfvfd7wDYenwrO0/u5GCRmni3u+wB5x7ORtypSnw+bCnlQWBSlfffAD5hSoHOdx97FHjUz/4/AH/ws/8+IHiOWY3ApPX3L94AOPANtLtGzS9FC0OiEmpUx3YSqGW6kJqS0ApOLPXdX3owNilTQKXk3f0uOKo5wDpL4cQSaD406ilkGrJ4w2CIrXgjUHqRNWuguBhS/Gfyiik6HTzwAAwbBtdfr5y3Suo4DRwXpz7na66Bf/4zIt3U0Di3iWse+Fj5EeWsVJPg1LMMgyHw/aWkJLi4o77pmdHTJ8Cx1F7KjpM7fMr6m3etSQBa796QkACFAUzi167VxBuNiRgkBNSINC1bgilEkO3evY0jP93S/Usptwde9Ha4HOQ1r1sUpUFnIDMxcASAS7qYv3t+wOPfbv8WEUJBn2hK5KL8i2rdx1Cc3/F84g3BB4JCCN5Y90bwiqwnYPmt8FUnKHhTCQ7CFW7ENYOs8yH/PhjwCoyaCxdsgelH4KITcPEpuOg4XHgAJq6BYV9A76eU0CFtAOjCyH96ZgvM7qceSoIJN9peDVP3QO6vlCCiQrgRK3RG1W5qV8gYE5495+HvwRWBCYXph+FyGXzT0IghkzsGzrdeG9IT0slKzgpZblirYRFtF1SO8lDc0veWiLd7VferQpa5vf/tEW8X4M4B4blYBEvrUlPGthsbsoxBZyAuCnmzBYLWqa0jXq9G7dHpdDSJb+KzXy/0pMSl+N0sRv9ip3D+ljQ0NBof1/e6nu7p3dELPUXWIq77/Dpc0oXZYObantcGFSLGG+JZdeMqzAYVjWw2mLm+9/UsvHYhX172pUfEEW+I55a+t3BLv8jf5yPFpV0vxSDUuKPMXsZPe37yW27d4XVerlwtk1vSLb0b3Vt0p8hWRKG1kDJHGZ9u+RRQUcE9esDtt8Nbb8Hnn8PcufDFF2Do/jEOyilxFFJiL2FMuzEREW6AiiLT6SqnpKxOKxuPbfTZqqY6cUonfTL7eN6PajvKK1Bj9aHVftvaenwrxioT3h2bdYxqmq0WCS08aenMRjMvrXrJ838yqu0okuOSo9a2hkbUaDE0sLPDnndCpNiNACbf50UAbKei225VEtv5328/HXXBhIcWwwMHD636TeD0NhEkkHjjzJnITHuFQyDHi1g6XaSkBO7HunX177pRnWHDlFP3Rx9Bz55qga+mQhezWYk7b79dpVb7z38afuCohkajID5IOj3bCeU0fg5jMgUWb5w6pURqDZWWyb5u/9XF9qBSY1cXeRh0Bs7LCd/1sEcP5UQSiO++i14KLY3I04B/rTUC0apV6DKrVysVbENnfsF8bK7AKhO7006rlDAuOAShBCCbj23G6fL/xP38iudDRjbbnXbGtY9c5Gh1+mT2Cen8Ue4o5z8r/4MMdCfb/zl83gZ2vaYGczKEukcXBzlTYejHSqAxbT+c9xZ0/yu0vx4yRkNyJ4hvAXFNwZQKcWlgzoImPSFnMnT+NfT8B4yco9KiXLAFev1THa+O9QR8N8g98A5yrb3/BX2fV+0ZYmMJGZTUruGV2/4fFQmhoXGW8dDIh0IXqgE39bkprHJ3D7w7ou0C3DXgrpBlTAZTRO5LVQknNVi/7H6eBZtIYdKb6JDWIayyUzpNiUibiaZEr4WaYLRrEmBytA40NTeNeJ0adeeuAXdhqCaETDIlMffquX63WT1mocd7NjTNnEbX9DDvyRoaGo0KIQRvT3+bOEMcxfZivt/1PTanjZS4FP4x7h8hz89vkc+LF7xIgjGBMkcZr6x+hVYprfhw44dIKdEJHblNc3l24rMxuJraMyN/hsdhxO6y8+nmT9l2YpvP9vHmjz1uIkadkSu6XQHAbf1vI8FY6QQ4d9fcwGNHoMRWwoajlak7k0xJERe3dGnepUblm1uae90vUuJTSDOned6fLD9JxpMZZD+V7bWd99p5Xu5sQ1oOqXvnQ3Bz35tJNCVSZC3i082fUmQrIsmUFPazroZGg6NpHxABQluP/hReUEtdiEvzv996EkSMVsktOYEFLP5cQaKBKRVaXuz//+LUajj4DTginBujGgkBTGX3RcaoMSwC3b5iaZ0vRGBnjV27Aotc6hMhYMIE5QwyZw7ccQfk56uo9eRk9X8bH68WSi0WlYbGbFbpVyZOhCeegIMH4cknIT29vq9GQ+MswhIk9Zj1RPCU8ucAwZyOAE6fjllXakxFCu7qVHdX3nlyp0/wdoIxgd6ZvcNuq2XL4PfBL79s2ClmNLxpgI8RGqFo2RKsIcR2Bw8qu1NzA1jbDsaKgyuCHm+Z0jIiqUj6Zvbl+53fe3LcVseoN7Lp2Ca6pXfz2n+i9ETAiKaqZCVlkZEYRCFZR/Q6PSPbjOSr7V8FLXey7CQrD66kX3a/yp0uB6y9B7a/GJ54oGlfyPsdZF+gzjVVGYnUJgraYAbcv4jJnSCxLeTepCITdr4K2/6tHkI2/s0dIRDEOaLrX1S6kkikH4kUQgcthqkBcjCO/gTWY2BMjE2/NDRiRF7zPFLiUjhjPROR+u4dfG9Y5SZ1mIRO6EIK28KlhaUFyfHhRUHO6jGLh396OCLtNo1vSjNLs7DKds/oHjCitDYMyhkUdtlpnaehF3qcVQaMBmFgYoeJAS38nlrylE8am5n5M8Nu87yW5/lNFVMXamI3qBE7RrcbzVNLn/LKAVpsL6Zzs84kmnzvmw//+DBOvCcvRrQZEe1uamho1CNtm7TlkVGPcN/c+7A6rZgNZt656J2ATjzVuar7VXy8+WPm7JiD0+Xknrn38Ma6N7A6rViMFj675DMfEVlDo29WX8qqLMitOryKvi/39SlXai/13K/tLjtj2o8BlPjjzm8rHbec0smGoxt8xsAV/LjnR+IN8dicaqZUJ3SMaTcmYtcDKr3IuiPrwi4/MXeiz77OzTpzqPiQ5/2RktApJgfmDAy7zdoytdNUbvzyRiSSXad3Aeoz93cNGhqNgtTugeeUpEPNibSaEb32TQHGTLaToAthTxwpzFlu0YQfccTp9ZAR2mEwIvR6HPZ/Ck4/4bVLrobxKyC5Y9Qs9tu0UYv/1dm/P7RTdKQI5GoRy9QtAO3bw0k/uh0plYAjv26ZwKPK4MFqA5WafeVK2L4dyspU5LbFAqmp0L+/CiQ9lxb8hBBNgfeBNsBuYKaU0sfmRwgxAXgG0AOvSCkfC3W+EOI+4HrACdwppZwjhLAAHwLt3fu/lFLe6y4fB7wB9AFOAJdIKXdH4bI16pP4dHUv8xfkbD1O0PWSc4C0tMDpsgCOHoXmQTLP1DeDcgax5rD3jXPPmT1e73ee2ukjrLc6rTWaxxQCOnXyf48G5Zh09Ci01gyJGwWa80YjpFmzwLZsVfnxx+j3pS4cLj7sZYHqj64tIhNB2bVFV7+T/xVIKVl2YJnP/nd+eQd9CAW/TuiY1nlaXbsYkul504NeAyj3jZdWvVS5w3YKvh8SnnAjtRuM+RHGLFAqfkOCt3AjUuhMSsBgyYG8P8DUvdDtr8qZIpD1I6goi/zfNyzhRgU5U0EfxsTxpsfBHmUrUQ2NeiBQqoIkU1LAtAf+0lF1aNoBiym8RRidThfRhfhLu14adtnfDPpNxNqdkR/+BOfV3a+OWLsA1/W6LuyycYY4n3uyUzpp37Q9D418yGe7f+j9nqjfCpLjkpnRJfzrnZA7Ieyy4aIt8DdM+mb19UmjZzFa2HRsk9/y1e0lLUZLWOl4NDQ0Gjd3DbiL9k3aA3Bx/sWMbDsy7HOFELw+7XWS4pI87ht2px2L0cK/J/6b9k3bR6vbEUMndJ7rr6DIVuSzVRVa6oSOQdlKrNnE3MTrM7M77czZOSdge19u/ZIiq3Kg1As9V3S7IuICl1/1+VWdy1/b89oat3tF9ytqfE5NSYpL8tybXNKFQDCt8zSPe4qGRqPDYFHihUAUvAX2AEnWI0FcAAc9e2H0XT8qMGcFXsE+PB+cMcpfbclRaYR1ftIrO8tg/igoOxidFCouJ7nt/Nd7/Hjs3CYCtRNscS8aDAicuY0VweMVGxTx8TBkCFx7Ldx6K9x1F9x4I8yYoRb5ziXhhpt7gXlSyg7APPd7L4QQeuB5YCKQD1wmhMgPdr77+KVAF2AC8IK7HoAnpZSdgV7AYCFEhdrzeuCUlDIX+BfweKQvVqMBYEoL7G5lPRa71FwNFCGUmCwQBw/GrCu1on92f591vTPlZyizV4pBt53YRonNOwDOqDPWOGB8UIg4vY8+iv29UqN2nNt/9Y0UIZSAIxTffQfFDXideNn+ZUEnLvRC75XPti6ESptSYi9hwe4FPvufW/EcpY7goodEYyKTO06uS/fCYnzueOz+VPVVcEon7214D6vDqlwzFlwAp9aEEG4I6P4wjFsKzQYrcUSE8hiHxGBWEwDNB4eOlMiaBBGKsI846aPDK7f7rXNyxKNx9vO30X/zyiMOKqf8zX1u5u3pb/ts/5rwL5/J/3hDPC+c/0KN2r2lb+Ssu38/+Pdhl02NTyUzMYilYZTavbH3jRFps4LLu11eo/Ij2470csOSSFYeXOm37PaT2zFXS21V7iinf3b/sNublDupRv0Lh2mdpkW8To26E2+IJzct12uf0+X0suuvwO60s79ov9c+ndAxuNXgqPZRQ+OsJyNDPaf62/zhr1xG9JwIQf2tr/3rEeSD8Mb0N2vcXmp8Kh/P/BizwYxLunDhYmSbkYEX/yPxmQihwoPDrSdQOfe1XturZkKFri26eqUru6XvLSSZkgAVyfXRpo8Cnvvlti89zpVxhjhu7BPZ5xCANEsaySZv5zOjzujZqop99ULPea18cz5f1u2yGrWZnpAeM5eVG3vf6ElVk2hK5IZeN8SkXQ2NqJHWL/CxQ7OjO2djaor/aWwZHZGCP8xZ4AowL3diuRJOxIoef4OkDuAvtWb5UfimOxz9MbIBRI4SKN5Om6K/Ee9HNwL+XSiiQSDxRllZbJ03+vWDxABxdl99BWciY1CqEXumAq+7X78OTPNTpj+wQ0q5S0ppA95znxfs/KnAe1JKq5SyANgB9JdSlkopfwBw17UayPFT10fAaCG0yeWzjri0wOsxxQXhBY2e5QRz1ti9O2bdqBU9M3r6BDFajBYKThd43q8/sh4X3s9R+c3zqemfe79+gdObAXzyCZSGYc6vUf80bF9QjYDk5sLhw8HL/PxzbPpSWxbtW+SJ5PFHgjGhxjlwA9EprROl9uDfSov2LfJ6b3PaOFJ8JGTaFpPBFNaCgcsFW7bAunXKSnDXLrXt2wdHjqgvTadTlRMCdDo1z5eUBJmZ0LJlFsk98zluULaygb63yx3lHC4+TOudT8Optf7ttjydbwLDPoUmfZSIor4Ix8pRGMBPpH6d+CQDykPb6gZHB5c5VN7TUO4mjhIoeBPaXQf6GHlJamjEgKS4JCZ3nMynWz71TPKXOcrYW7iX8zue71P+tTWvYdKbsFeZ+Eo2JTO6bZhCKDfX9LyGm7+62SvCFNT9I5BT0anyUx777wpaJLQgJznHb/lA/GPsP7j5q5sprjIZZtKZKPpjkd8FgRs+v4H/rfuf176+mX1rFOlrMVlIM6dxouxEjfrqj+yk7BovXAxpOYTX1rzmldpi24ltfstuPuab7qSpuSlNzQEi5vxgMVkw6oxevyd1pWt6ZBy9NCLPmLZj2Hxss+c7pMRewupDq30cYnac3EG8Id7Lvc3pcpLfvAF7EmtoNAaO1PWZOEJ1hMB4rMo9sBbtDWs9jFv73co/l/yTJGMSb1z4RsAJsV22IxS69SE6Cd2OhB6NSGBjC3DoKt9b7JWTcC0LwRLGbe1IApyusjDW4egRdMAd/e/gj/P+GLoCN9WdKibkTvBKObfq0CoW7l3ok1/5cPFhjpUe87xvZm5Gj/Qe6k1GRviffaBBa3q6Z0Ljd+f9jod/ehi7y45BGDj828MY9Wp82ObpNpwsVyuBgZzeDDoDGYkZHC4OMUHiZkrHKeH1PQKMzx3v+bz1Oj3DWg+LWdsaGlEhczwc/Nb/3IfLBluehvx73OlzI4i9BE4sVal8/Qkkyo9BYgxcWs0ZgefYTq6K/HUHw2CG0XPhmx7uea1qigV7IfwwAdpcDr3+CYbE2qfxdZSCdKp0x1v+Scuk8ZhMKtVGdfbsUV/x0SZQepbDh2MbM9W9e+D2vvuOgCIXjQZPupTyEICU8pAQooWfMtnAvirv9wMVXiyBzs8GllY7J7tqpUKIVGAyKh2LVztSSocQ4gyQBhyv3aVpNEji0gIfc9lU6hRzdIXyPtTkmb+m1OKLOtv4I1vw/yy9c6dK92SMTrawOpPXPI9yh/dNUwjBjpM7PHNZW45v8T6O4LyWvsL1UPTsqdYVA7F0afDjGg0HTbzRSBk/HpYtU19Kgdi6VQkBGio/FPzgmaD3hwtXSMeMcDEbzTQ1N/WagKrOgcIDFNuKPQt+Jr2J43847jW55Q+90KP3o4wsLISFC2HRIpg7F9avV8pwIZQSPFx7orIylYtq3Trg65WY4h3ExYHNBnFx0KcPjB4NAwcqu744k8B46FvY8XJwMYHOCKPmQkoXNQCuT5I6gssavMzheRAihU2NqbNwA8CttskYA3vfD11849+h7dWAJt7QOLu4qc9NfL/re4pslaK873d9j5TSZ1Hksy2fUWKvtIIz6oxc2+vaGquJDToDV3W/itfXve51P+mR3oNF1y/yKS+lpMnjTbzEGxajhYdGPFSjdgEu6HgBtmoTd3GGONYfWU/fLN/88/N3z/d6bzFamNVzVo3bvTj/Yu/0WG6qO59UxZ/4oaauGwADcgb4CF9OlJ6gzF6G2eg9Ubnh6AYfu7/a5JfPSc7xUqLXheS45NCFNOqNEW1G8H/r/s9LHLTigK/X8IajG3wiFnpl9AopttXQ0NCo4B9Xv8WTRwAK4Zl8v1ERDpeDbreCcIFegk0P/5wDt/o3nPLwVne4cTLEOcEloMQEcQ4wusAhYHQBfPlu8DpKjdD2bjC4h6FlBnhrXgqXoNwbWia3ZF/hvmBVAGrCr7rTg0lvIr95PisOrvBc54S3JvgIOm1Om9c9f1DLQZXPaREW+kzqMIknFj+B3WbHbDSzt3AvPTN6cqzkmEckm2RKYmrnqYFq49oe1/LYoseQSASCrKQsjwCk0FrIqbJTnmN3Dryz7v0PE5PexPS86bz9y9tc2f1Kv/MGGhqNiuwpsPKOwMe3Pwf5f4hCwy44tiiwY2vRdkhsE4V2q6EzQmJb1V517GeUiMSS7XssWsS3UKmP5wwAexHgZ/5y9zuw5wNodw10ulO5dUhn6JTEznLlpGI9DjtfUcIchxrr5zTdH/C0efOgd+/op08JZL516FBsF+/y8tS8rT8KC2HjRvV5aDQ8hBBzAX+/SfeHW4WffaF8X4KeI4QwAO8Cz0opd9W0HSHETcBNAK1atQrRFY0GhSktuHtV0Y7YizdiIMyvCa3s2yGAeGPtWhUYnZIS0y6FjUlv8pnfLHeUs+PkDs/76uO7RFOi3/nlUAS7L4FaL/7kE7j88tilOtOoHdosZyNl+HAwhyHoXrCgYQo4XNLFhmO+VthVKbeXk9s0N2iZmtCpWaegxy1GC6sOrvLaZ9AZMOlNQbeqEzDl5fDppzBxIrRoAZddBo8/DsuXq2PFxVBUVIe8UlKHrcxE0WkT1lIThadM/DDXxEN/MTF9qomM5iZuvN4I6/8c2gWiz3OQ3Kn+hRugHj5azgyc2w2gdK9KO+IoCVymPmk1AwxJocuV7oUtTzXc69DQqCWj2432EV+UO8p9nBlc0uWTpsqgM3BNz2tq1e6lXS8lKc77b2/14dU4XU6fsrtO7fIRMjhdzqCLAYFIiU/xSe1ld9n5ac9PPmVPlZ3iYJF3Akany8mFnS+scbt/Hv5nTNUmLZNMSXx7xbecvOekz/bxzI899ugVGHVG7h3ik7I1JDnJOT6pUBJMCWw9sdWn7MqDK73s/swGc42dVaB2go9AdG2uuW40ZM5reZ5K+1YFf79b646s83LdMOgMjM8dH/X+aWic9UQiTDYWobYRQFSdiAwwKWnQGRiZfz6lcYLCeCg3wqs39lZe7EG2V389HKsRCuOhOA6ykrOxm/QUxUGZCRb1aBKyjjU7FmJMTKYoDoriIN6cSP4nlbaaT4570nNvjzfEs+fuPci/SORfJNlJlYuGl3W9DJPBd6Gzetq5EnsJZ6xnvLYyh/eM328H/bbGn3O49MrshXR73Luky5OSbdWhVR5HEKvTysg2IwPWcdfAuzxijURTIk+MfYKCuwoouKuAUW1GeUS+bVLb0LVFbJ8HKtLyBEzPo6HRmDCnq3mkQFhPwPYXwBFk1aCmOEpg0+Mq4CeQWPf0+si1F4pmQwIfOzQH/IxDo0pyJ5i4VolXdAFsHqRDCTC+6Q5ftINVv4Ydr8KJFUqcYS9Wn7PtFJz+RQk+1t4H3/aCz1vDhoc9wg1Q4g1rgPirn36KTQrv1q397z92TAW6xYq4OOWWHIj33vPvUKJR/0gpx0gpu/rZPgeOCCEyAdw/j/qpYj/Qssr7HKBi4ifQ+cHOAXgZ2C6lfNpfO25xRwrgN0GRlPJlKWVfKWXf5sFyTGg0POLSgrunn1oTu740UNpSENAxYuXKhu90VH0O2ea0eVIFF1mLfLIGSCQ9M3rWuJ24OAil3XrySQLexyNFYWHoMhrB0cQbjZR+/YIrqCp44YXYPDTXlC3Ht6AP4aKQnpiOKYKpJap/QVanzFHG0v1Lg5YJxOrVcMUVkJYGs2bB7NnqC7CwUKVCiTY2m2qrpASWfb8Vivzb2HtIyoW2V4ZW2seSHg+HTp+y4lblwNEQhQ85U8J3Btn4N3dUhIbG2YNBZ+Cyrpd5fbdLKZm7a65XuV+O/OLjupSdnE3nZp1r1e7ItiOxO70FGUad0fMAXJWFexf6ROx3aNqBjMTaqddn9ZjlyWMOSqwye8dsn3KL9y32caZo26Qt2ck1j8rKSsryOc/usvPL0V9INCX6bGsPr/VZgOmY1rFG6UuqUl31LaVk07FNPuU2Htvo9d6gM9RKiDG23dganxOIoa2HRqwujciTnphOanyq174yexknSr3TBC3bv8zrO8RitDC0lfZ/q6FRZw4fDikqCLmFyuvZyLhvyH1YjJWpJTcc3cCxksBOjoXWQpbsX+J5n2hK5NcDf+31rFDmKONA4YGg7S47sMxLzGbQGbwEBxNyJ2B1quNGnZFFe5Xb2LGSYx6nyeS4ZC7rdpnf+mf1mFUjt6IEYwL9svsBcOvXt9LtFjzbh2FkrLLqYdyVlef0vBk2VVlP0Akdw1sPB5SQ5Oe9Sqiy4sAKzyRmbtNcUuIDh9KlJ6bTMlmthRTZili4d6HnWMUYXyd0tRLO1pVR512BfBB6Z/UJHCquodGYaHMV6IOskGz8e/AFqJriLIetFdkDAgS1F25WAoRY0GIo6APMpRW8Ac56mK9KbAOT1qugIn2IlMhlh2Dnf2H5DTCnP3zcHD5Mgg8S4aOmSuCx+ArY+nTAucVmSccDznUuXQqWGGRlbtXKf8SwyxX7efBevQIf+/rrOgTwhUFDDNg8S/gCqLBKnQV87qfMCqCDEKKtEMIEXOo+L9j5XwCXCiHihBBtgQ7AcgAhxCMoYcbdQfpyMTBfVqheNc4eTKkQLGXw6V8a5npIDMnmYMBg9hMnGr5YYHCrwcRVC6LeeFTNne48tdNr3AlgdVjpmNaxVm1deCHogyxT/fILbAuxfFhXbBF8FDxX0cQbjZT4eOgU3EgCgO+/j+5DYm1ZfmB5yDK1XcgLRPf07l4TZ9WxOW0+tvahWLsWRo2CIUOUmrq0VDlr1AS9HnJyoH9/Vde4cTB2LIwcqQYALVrULA3YNcNeA1eI//TcmyOfgqSuJLSCEd8EF5RIB/x8IWx5RuXcDPZQEw7xEYwO1Bmh422gC0Pi7yyDxZera9DQOIu4rtd1XjnTyxxlfLL5E68yc3bO8RJbmA1mn3zsNcGkN/ks8DtcDs/Ef/W2q6ZridPHcWX3K2vd9tTOU3FU+75dun8p1cfR8wvmezkFxOnjAuZtD4eL8i7yEsmUO8qZt2ue37LzCuZ59dGoMzIjf0at2x7ddrSXsLLYVuwjlHG4HD5OI+WOcrqnd69xe1M71dwVJRCTO06OWF0a0WFIK+9IRrPR7CMEqv6+zF5G/+z+Ue+bhobGucd5Lc/zEkwadUY+2/JZwPJfb/va6x6ZGp/KHf3v8EqzZtKbPClLAjG/YL5HnAEwvv14L3ez5Lhk+mUpMUWRrYi5BUoou3jfYs9zmM1hC+h4pdNViiUqSDAmeISfFoP3xGHVVGvzCuaxIR3P9nrPoJcCQEETWNSq8pztTWF3m1SvMhfmXegZqy/ZpwQwC/YswOFyYNAZmNZpWsh2pnWe5nk++nHPj4AS1BwpUe4qicZELuh4QegOR5hwnF40NBoVrS4KnhjAdhKWzorMIpOjFBZeAg73WEoGUAwUbVfzRbEgrX/gSbpjPysxY31gSIDz3oARX0FKt6gGawljAh06+D92+nRstJyZmYGjrE+c8L8/WgwaFNh6ftOm6C4oNsSAzbOEx4CxQojtwFj3e4QQWUKIbwCklA7gdmAOsBn4QEq5Mdj57uMfAJuA2cBtUkqnECIHla4lH1gthFgrhKjIffcqkCaE2AH8Bqi5japGw0fowJga+HjhlrqvgzRysjgYNM3HyhDpLeubnhk9vebMAXaf2Q3AzpM7feaS2zZp65PaMlymTw8tpHzwwZqvY4ZLcTH87W/RqftcQhNvNGImTCCgVVAFLhe8/HL0bXBqyoLdC7wW0KojECGdMmpKXrO8kDlmVx4I71v+yBGVF+q881RqmrKy8NTOmZlK+fbPfyrhx6lT6v9myxaYMwc+/hjefx8++EDlnvrhB9i9WynVjh2DhQvhL39R4o5AOby65vwCMsTNPHtyw0iXUp304TBqnko/IgLcnKQL1t8PX3d1u3CUgbOWv+DTD8PlMvhWEzrciv9UhH448gMUNOA0MBoataBfVj+S45K99i3ev9hLPPDZls+8FiRc0uW1KFAbrux+pVdqkDJHmV8HjIqJ/Ap0Qsf0vOm1bjcjMYMOad6zVi7p8kkVM2fnHFxVclfqhI6L8i6qdbtTOk3xUWQvO7DMp5yUktWHVnvtizPEMblT7UUMg1oO8kqdIpE+i1AFpwp8nLM6pnWslZtWU0tTv4MVk95Eclyy3y0+QCTgoJxBNW5fI7aMaz/O63e7qo0kKKFGRVR5BW1S25BgakBOYhoaGmcNQggeGPoAiaZEQLlC/N/a/wtY/vV1r3vEmgnGBO4dci8mg8lLmFZsLWbxvsVB2616X00yJfl9Vrm6x9UescP8gvmen0VWNQM3vM1wH9evqrww6QWMbtfDCjHri+e/yIvnv8jEDhM9IgijzsgTY5/wnFc95UjB4PyQjix7lszGmFRl8JpgIW+O9/PJ2HZjcboXZXef3o3VYWXNIWUPbTaYmdhhYpBPTDG542TP/WD7ie3YnXZWHVzl+RxsLhuDWw0OWY+GhkYIEtuCJSt4mf2fw96P6haw4iiFna/CkSoi9UBzP0XbQRc5596gJHcOvIAmXbD3w9inTqlK+kiYtA6GfAhJnZQTR7AUxWGjU3N1cc2h99OMHh1Yw/Ltt9EPJMzICBxVvG9fdNuuTs+ewRfJnn5aBftFAy0lS3SQUp6QUo6WUnZw/zzp3n9QSjmpSrlvpJQdpZTtpZSPhjrffexRd/lOUspv3fv2SymFlDJPStnTvb3iPlYupZwhpcyVUvaXUu6K3SehEVOS2gU+VrgluOvVOUBXNgRd41ywoOGtgValR3oPyuzezsgnSk9gc9rYfnK7z7EKsX5tGDAgtJb0yy/h+PFaNxEUlwteeik6dZ9LaOKNRszIkZCYGLrcK680PBu1qjam/kgwJdAtvVtE28xrnufzJVidUkepT7RwdRYvhrw8+OgjJdoI9UXYsiX84Q+wYwfs3An/+x/cdRf06AGpqWqwkZCgXlffUlLAbFYK7mbNYPBguP9+Je44cgSWL4frrvMWcljiwsinow88kVcrPsmAd0QdN/eoq9kAuGATZE0KbvdYUgALJsLXXWDzE1B6QNlkOuvRk8mSBRmjCVvAsep2lWNUc+DQOEsQQnB9r+u9FulNOhMrDqhFiHJHOasOrfI6p0dGD7KSQkz+haCqfXgFi/Yt8lItHys5xvFS76fS5gnNfcQXNeXq7lf7KKer3uPK7GVsP7Hd63iaJY1OzcKwzwrAoJaDfBw/zljP+Fi57zmzx6ecTuhqlTOxgj6ZfXzyMG45tsXr/ebjm33EkiPajKh1m+PbjffZ16V5FxbMWuB3G93ON9K4e4vu6EIpXjXqnfNanudl5V/mKGPlwUph7ZbjW3yES6PajopZ/zQ0NM49ZnaZia7KtMnyg8v5afdPrD281mtbsn+JR0QBSkB5TY9rAJiRP8MjtHDh4oeCHwK2d7z0OKfLT3veW51WxrQb41NuSqcpnnv8gcIDnC4/zfe7vkciSTQlhnQW69y8s0eIYXVaOVJ8hCu6X8EV3a9gx8kdHiHF5E6TvVJa9c3s6yWqDDV2BvU8Yq+y0Gl32mmd2tqrTOvU1jSJbwIoscaPu3/0PG/YXXYGZA8I2c6gloOwuceC8YZ4NhzdwNL9Sz1zAAOyB0Q0LauGxjlNmytCiyVW3ArW47UTMrgcULof1vzOe3+guayyQ7Fzl9XplYAjENFOnRJOCl4hIGsiXLAZxi+FLvdCQju18GdIDvOzEkqsYUhQgo0ONyu33AsPQe4NQeekX301vFTfdSEjI/B87MKFsUlhXcGQIcFFFK++WjNH5XApK4N//zvy9WpoaNQTqUHcaq3HYucw1UDJ5gBxQWKRly5t2IK2JuYmJMUlee0zG83sOb2H9UfW46jy/2s2mOsUgKbXw3jfqVQvpITf/hZKIvzIUlICjz4aPdHiuYQ2i92IOe+88B6Gd+5UNm0NhVJ7KXvO7AlaRiDIa5YX0XZT41ODRh+BiuRdtt83ehnUF9rzz8OYMcoxwx7C3GLYMCX02LpVuWW0b6+EGCkpwXNOhcJoVMKOuDjo108puA8fVmKSTp3gZHHT0JWUhZ5kqxHlkbB/raIwsuTA8M9hxNeQ2E4NGANRUgDr/wyf5cDcYbD+TyrCo3Cbyo3qKAHb6fDdOVwuNRi2namdHVn+H8K3p3TZYcEkOLNR9VUjJgghmgohvhdCbHf/bBKg3AQhxFYhxA4hxL3hnC+EuM9dfqsQYnyV/Y8KIfYJIYqrtXGNEOKY2xKxqi1io2VWz1k+i69zds4BlA12VaFDojGRm/vcXOc2k+KSfCb1rQ4ru0/v9rxfuHehlyODQWfg0i6X1rntC/MuRFQRbJXYS5i9s9L1Y8XBFcQbq7QrDFzatW7tGnQGH7vzeEO8j/vGsv3LfFwrxrcfX6M899VJMCWQk5zjte9w8WGvVDgbj270EngkmZIY2mpordsc036MT17II8VH6JXZy+92qOiQTx3aAn/jIL95Ps5qE/yrDlYKvjYc3eDlYpNkStL+bzU0NKJKnCGOkW1Het47XA4mvD2B4f833Gsb/fpoL4FCv+x+HheI8e3He8QQABuOeX+XVWXFgRVez0q5TXNpavYd32UkZpDbNBdQk34/FPzAjpM7AOVadH6H80Ne2239bvOISuYVzMMlXRRZi9h8fDOgvmOrP6flN8/3EtEVWYs8golA7Dq1y+u5ICc5x++zyMQOExEIHC4HX2z7wvM5DMgegFEfOmrcpDdxXs55ADilkxUHV/DD7h+wu+yYDeY6pY3T0NCoRutLQwsAnKUwdziUHaiZW6qzHEp2w7xR4Kr2/ZLQKvB5ZQfCb6OutBhOwKCdYwvBfiaKjdfAIVYISO0G3R+CqTvh/E0w8DXo9lfIuRCSOkJcC2XVb0yBuGaQ0AYyJ0KX+6D/izBuCUw/Av2ehxZDlHgFlSokUD77FSvgTDQ/ApR4I1CE9YoVsU0nkpgIvXsHPn7yJHz4Yeh55JoiJfznP5GtU0NDox5p0it4OvYTDTwvSJQRKKejQCxeXLc1t1jQrYV3sLpe6Nlxcodn/FWBUW+sU+AdwCWXQFKQJTWATz+NrGOJywUFBSrrgEbd0cQbjZjUVMjODlkMgMcei14Oo3Co2vbqQ6t9oiarU+Yoo3OzIEr2WpLbJDfo8WJrMYv2LfJ77JZblINGKMFMx47w44/w9dfKoshsDp1jqi4kJak8j1OmwJo1kNF7EhhCWLLseCk8tX59kz4CJm+HIe9D82HqASaYRdipNcqFY+EM+KoTvG+Br/Jg0aWw7j4oeBMOfAWH58LRhcr14vgSOLIADs6B/Z/Bln+qCJF5o+Ajv2v6wWk+VA14w8VZBvNGQ/Gu2qd/0agp9wLzpJQdgHn4yRcphNADzwMTUTknLxNC5Ac73338UqALMAF4wV0PwJdA/wD9eb+6LWJjJrdpLm1S23je2112T374b3d8S4mtxOvYRfm1Tx9Slar24QB6nd7LAWN+wXyKbJXfe/GGeGZ2mVnndnOb5tIioYXXvp/2/OR5XTVyFNQi0Mz8urc7s8tMj407QImtxMeG/ee9P3tdc5IpiYvzL65z20Nbewsx4o3xngUjgJWHVno5fjhcDgbmDKx1e70yevm4mxwtPerjKlJBwekCr/dJpiT6Zwf689NoSOiEjt6Z3jOfO07t8LjorDm8xpOSANR3yHktz4tpHxsiDUmUqKFxNvLQyIe83pc5yii0FnptZQ7vQeIjox7xvG6d2ppmlsrxgV7ofVKsVbBk/xLPs5JBZ+DivMD37au6X0WcPo5iWzEfbPzAE6jQM70nTcyhxzEX51/suZdKJOuPrGfB7gWee65ep/cRyOU1z/MSnsQb4tl3Jrg//Zbj3g5dXVp08VtucsfJJMUlUeoo5ac9P1FsK8ZsMNcoxd3F+RdjMVootZfy4+4fvRzfJuRO8H9SRoZa4Ky++cNfOSFUHRoa5xIp+ZDi/2/Zi5Ld8G1POP1LeI6jjhI1T/Ntb/9ijOR8330VnFgeuv5IkTk+yLybVAFG0Zhzc5TC5qdqf35iW2h1EXS9H4Z9ApO3wkVHYMYpmHEaLjoGUwtg5DfQ41Foc7kSf/j5TszMhORk3yYqeOml6EZAN20aODXL6tUq8C2WXHKJmpsNxMMPRzaVjM0Gr78OJ05Erk4NjXOKQM9/4WyhqG29N/45+LrHga/O+eDP4cMDCzQcDvjii4aXgaAqg1sN9hKxW51WdpzcwZ7T3oHuZfYyuqcHcWIJg3HjwhNlXHNN5NyyysthxozYul+dzWjijUbOuHEQjgv4xx/DwQibLdSEwsLK18v2L6PcEfxGkxKXEpX85aEUay5c/LDb18b25ZfhzTdD2/3MmKEGCYMHK+V1LB3ajUYlFOlz4UyQIb4h935AjdT69YnQKbvHsT/ClF3Q9UFlI6YzgjGZ4F9jEkr3waE5sOVfsORq+HEyzB8Lc4fCnP7w3XkwbyQsmAA/XQhr/wC734JTq9XEQY37KyD/nvDdNwAcRfD9UOXAYdfWQGLAVOB19+vXgWl+yvQHdkgpd0kpbcB77vOCnT8VeE9KaZVSFgA73PUgpVwqpfS1AzhLuaXvLV4ivc3HN1NsK+aLrV94RZ6Objua5LggMz41YHLHyV6L+cW2Yr7f9b3nfYWVeAUmvclnkbi2XN7tck/eeIAz5Wc8NuLf7PjGq19xhjj6ZvWtc5sTcid4uV04pZN5BfO8yizYvcDrvdVpZWy7sXVue0TrEV7CER06Nh2rtPj65cgvXuWNeiOtUoJEyYWgZ0ZPn1Qtcfo4n8ENKHevqoIVAJd0Rez/WiP6jGs/zssxxiVdHCpWX5/LD3hPyicYfZ1gzlEamihR41wl2CSoPxrJQnj39O5kJ4UZNQE0NTdlSKshXvumdprqmagTQvh8n1Uwv2C+51nJbDBzfsfADhrT86ajEzpcUo1hy+xlmA1mrupxVVj9TIlPYWx79Vxgd9qZs2MOn2/9nCJrEQZhYFaPWT5p0No1aec1ljfoDCFdNXedqkzNrhf6gPmbR7YZ6al7+4ntOKUTIQTj2o8L63oAxueO9wj+ftrzk0cIkxKfQvum7f2fdCQCLpKRqOMsJdYCQyGERQjxtRBiixBioxDisSrl44QQ77vPWSaEaBPFSz/76faX0IFDALZT8P1g2PmqEh/4m/OwF6tt2wsqkMYRQPjQpDsQYNXm0Hexm0/JGBN83m3327WbTwqFdMHWpyNfby0ZPDjwsddfD51mui6UlioBhz/27Yv9wtEFFwRf092xAz7/PHKCFpsNHnkkdDkNDY0ANMRnt02nfR2nqnLkh+DHzwEGDoSEIEsub75ZvwHsoeiT2YdEY+WzU7mjnHVH1vnMYzY1N/VJsVJTUlKgR4/Q5Y4fh+uvr3v6lOJieOgh2LIldFmN8NDEG42ca69VC/ahkBLuuCO2tnEVFBXBr39d+X5ewbyQ1qod0jpEpS+9Mn2jd6uz8ehGL8vuFSvg7rtDCzeeeAL+9z91A6lPi6b4pCTInkrAAS2oQeTCmeFFPjQkLFnQ5R6YtA4uOgmD34OOt0JCWxAGNXFgSCbotUea+HTffW2vDpyLNRC2kzC7L6x/QP3/BIgoD4lDE3+EQXqFkML9s4WfMtlA1TDC/e59wc4Pdk4wLhJCrBdCfCSEaBmokBDiJiHESiHEymPHjoVRbf1xaddLvb5H4w3xfL39a6/J+yRTEr/q+6uItZmemE6ntE5e+yrECyW2Eq+2BYKL8i5CRCjx7Iz8GV451E16Ewv3LsTpcrL28FrPfp3QRazdzKRMn0XrX4784omGtTvtPlG9ndI6hRWJG4oBOQO89H8l9hKPeENKyd4ze73K987sXadrTolPIc2c5rXPoDOw/eR2n7I7Tu7AbPD+/nW4HFF7rtCIPENbDfUSf8Xp49hwdAPgG72tuW540ESJGg2DSE2CNsDJ1KfGPeVJkyYQNLc0p01qG9qktqFFQguvY38f/Xef84e3Hu4RFRTbirnhixtI/nuyz1bVBbLUXkqfzD4B+9QhrYPH0eNoyVHsLjsu6WJqp6kBz6nOLX1vIcmUhNVp5aPNH/HN9m+QSEwGE9f3ut6nvEFnICspy/Pe6XL63PerUyFoBbAYLXRp7j9aPyU+hQ5N1f263B1VGG+I93m+C0a7Ju1IjU9V7RYfJE4fh0CElUZGI2rUh8DwSSllZ6AXMFgIMdG9/3rglJQyF/gX8HikL/acImuSO6AmDFw2WHUnfJIOa++B0+uh7AiUHVYOqqt/DZ+0UME0MshcSFJHMASwtj3m30U3KuhNkD058HGXXV1TJMUkjhLY+GiUU7LUjLFjA89J79sH330XWbeJqthswRelNm6MTruByM1VDtnBuPXWyEQ3FxfD739fv0GaGhoaUeAkwe+Bp9eq9Y9zmL59g4vg5s0DQwP+iHpm9PQKagSVpaD6PGaPjDBUF2Fw2WXBXaEq+OQT+Oyz2gs4yspg/Xr4xz9qd76Gf6Iu3giknq9yXAghnnUfXy+E6B3q3EDKeyHEWCHEKiHEL+6fZ30S7AEDAiuNq/P997BkSeRz7AXD6YRt21RuvwpWHFgR8rzeGdGJkM1rlue1wOYPo97oyTPldMLUqaEfrn/1K5VWJZjyL6b0egKMISIgDs2BXx6KTDSAPwFDtDEmKkeOvv+GqbtgZgmMX4ZrwKucbvkAx02TOCM7Uepsgd0Vj0vqsDrMlNiSKbKmUFSeQqF7KypPociaQqk9EbvLhEvqKHclU+RqxUnRl+OpN1Le7QUYvQCmH4XLZeU2/bBv3wwW6PdCzdw3AJCw9Rn4uhucXKVsNl1h/sHazoDtNCy5poZtnp0IIeYKITb42cKdzfa30hwqbqQ253wJtJFSdgfmUrl45luRlC9LKftKKfs2b948RLX1S4uEFl7uEsW2Yv635n9e4jmXdAW2r64lV/W4ivgqFoNHSo5wovQEyw4s81iJAySaErm066URa7dnRk+v+ottxczdNZf1R9Z7OXIkGBMi2u5FeRdhqDJw0wmdR7Cx/sh6r8/bpDdFLNd752adcVQZUFbklQfYV7gPfZX81wadgdFtR9e5zerOWVanle0nfMUb209s9xGKdGjawcuWUKNh0z+7P2X2ygevMkcZG45uoNBayBlr5WR1vCE+Ik4yZwkNTZTooTEJDzU0gjGz60y6tugKqBQj/bL6UXBXAQV3FTCyzUiPu1fb1Lbc2PtGn/PHth/r5QBmd9kpshX5bFVpZmnm43xRnUu7XopBZ/DU3TqlNS1TAmqBfRjXfpznvrnu8DpOlZ8CIDMxk27p3fyek9+sMm1Bqb2U3ad3B6zf4XJwuvy0571Ektc8L2D5aZ2neT07jW03tsYC0MmdJiMQGISBIlsRSXFJTOs8rUZ1aESUmAoMpZSlUsofANx1rQZy/NT1ETBaRErNfS4idND9kRq6jhbD9hfgmx7waQZ8mqlSpOx8RaWUDUVSh8D2BkXbiKnDbLtr3MFDAdjzPhRuAWcEJmGlC6zHG5TrBqj50mD29H/4gxJZRJriYnjgARg2LPAi3ezZ4dnFR5Jp04I7MJ86VffoZodDCVNeeqn2dWhoaDRQJGAO4iwqXXByZcy6Q3o9rPcEIz2d5s2Dp+yy2+Grr2KTOqU2Dh9tUtv4iDf2nN7jNd4xCAODWwaxtqoBF9cgc/ZVV8G779b8HlVSAj//DKNGNeyUNY2RqM5kh1DPVzAR6ODebgL+E8a5gZT7x4HJUspuwCzgzShdWoNBCLj99vDcNwBuvDE6D86BsFrh6qsr3x8pPuIzKVUdi8ESMXVZdfKa54V0/ZBSsmz/MgDmzg3tVtKrFzz1lEqT0mBIaAnDPgvt/rD5cVh6rdvpoQ6egtMPewsa/G1R4MgRpQr8zW9g2EgTOV3yicu9mOwJD5J7w9fk3LyFpjcewXRVGfGzymh71w4G/flnRj/yHeMf+4bzn/iSiY9/zdi/z2bkw3Ppfs8amv/qCPorHSRec4b0m/bQ9uYVtL/sZZJ630Jyh+F07duciy+GZ5+FlSuD2EC2vNidA7YWc0ElBfDdQJg/BrY+C6UH1SSHvUi5pTjLVQSH7Yx6v/9zWHYDfJYD+z6uwyd69iClHCOl7Opn+xw4IoTIBHD/POqniv1A1ZnvHKAiriHQ+cHOCdTPE1LKiimF/wKBwysbGTf3vdmTWsMlXSzcu9Dz/S8QXJR/UUgxXU25sPOFXg+88YZ4Fu1bxI+7f6TUVuk05JROhrYaGrF2hRDMzJ/pES1IJHN3zeWnPT95pTZxSRfDWg+LWLuTO032Eo0IITz3r6X7l3qlazHpTVzQ8YKItKsTOrq18F7Q2XhUhTZtPrYZg75yBs1itETEHWFY62FeiznljnI2HNvgU27biW0+KVY0d4bGRYIpgTapbTzvbU4byw4sY+PRjV6OHAadwSctwdlMIxIlehduRMJDDY1QPDDsAZJMyr52fsF8yuxl2J12vtr2FaBEmn8c+ke/YoPU+FTPueEyuWOQqG43M/JneMSaeqHniu5X1KgNg87AFd2uQC/06IQOKSVmgzmoO1rfrL7o3FNJLlyewAd/HCg8QJwhzvO+zF5GbtPcgOUn5E7wPNtYDJYauYhUMKXjFJLiknBKJxJJuaOcEW1G1LgejYhRbwJDIUQqMBk1b+h1jpTSAZwBvO3dNGpG26vAmBK79pJygzvIxnJRK2N0iJTFEn6aAs4IBEw5y+CHiWouqAGRnQ09ewY+vm0bvPNO5FKFVHDsGPz3vyoCO1AQ3ccfR8/1IxDTp4eeG/70U/jhh9oLS6xWuPzy6Kak0dDQqEdSqi+dVmP/l7G7Fxw+rL5sGsp2WAXQ9g4R8/3886Ed9CNBMLFeIIQQdGza0WvfqfJTXgFMFpMlYqmfW7aEIWFOm0mp1o6ffTZ8AUdxMXzxBUyaFHvB5LlAtMMQg6nnK5gKvCEVS4FU92JYjZX3Uso1UsqKhbKNQLwQonKm4Czl6qvDVzXt2QN/+lNs0qcUF8PTT8OmTZX7lh9Y7jV54w+j3khes8DROHUhMzEzZJkSewk/7vkRUF/2oVR0f/5zePZDMSd9BPT4G+gDWEpWsPdDmN0PCjcpcUAD5vhx+L//UwOi9HRo3RpmzYJnnlEKvwMH1OCstBTOnFG/gxU3DrvTxKHTWfyyrzsrdvVnyfbzWLh1KIu3DWbZjoGsKujLziO5nClNBQROp3JcKSxUm8Ohfhc2blSDwHvuUYrCgHE6QsCA10Bfh1+OE8thze/gs2yYMxBW3gZrfg9r71WWowtnwEdN4KdpsO+j6ORUPTv5AiXww/3zcz9lVgAdhBBthRAmlCXvFyHO/wK41J1LuS1KlOg/obmbChGImylA4NnvRsa0ztO8xAMl9srfzwRTgt+o1LrSvml70hMqleHFtmJ+2P0Ds3fM9nKKmJg7EaPe6K+KWnNJ10u8Fpb3F+7nq21feWy/ASZ1mIRBFzn/voE5A70U28W2Ys/964fdP1DmqHz41wu9j3tFXRjVdpSXm8W+wn04XU42HdvkyVcPapGmqgtLbemd2dtLqAIqTUx11h1Z5/V7l2BMYGDOwDq3rxFbRrUd5UlBALD28Fo2HN3g9X9rd9oDRoWfjTQWUaKGxtnMhZ0v9Dw/mPQm5uycw497fvTcD3VCF1Q8MabtmBq1d1u/20KW6ZPVxyNulEguyruoRm0A3ND7BuIN8diddqxOKy7p4spuVwYs36VFFxJMlatlO0/uDFh2z5k9XuLL9IT0oOLdAdkDPMEWVqeV0e1q7t41os0Iyh3lHjeSbi26eQTFGtGhIQoMhRAG4F3gWSnlrnDOqXKu5hoVLjoD9Hwc9DGyoTUmBU6bAnBoNjijuHrgqhIMpjNCTgiRXdkhNW9Tl5TFjhJYcRsUNsypgttuCy5Y+MMfIiveKClR7hUOh1rAC1T3hg21i4quC0OHhhcwedVVsH17zT+X0lIl3Ni1K3RZDQ2NRkrT3gRdsj36g/e9KFrIhmuhMH588LW4n39Wa6DRpLwcXn65ducObOk9R6kTOuxVnNdtTltE52/vuadmQed//KPKMHDggFoT80dREZw8CQ89BFdcobIXaESeaIs3wrHaDVSmNsr7qlwErKkS0XzWkpEBg2vgpPOvf6k8RnWxaQtFaalSEj/wgPf+RfsWUWwNrhwpc5QFtVKtC0IIr2jOQCzcuxCbDebMCV4uJUXdMGqjtIsJne9W6TtCCTgKN8M33WHpdVC0C+yF4IqxRD0ARUVKsDFggFL133GHUqofPaqEGYWFgcVLGRlKXXjNNfC3vykl4IIFsHixcs1Ytw7WrIFly9SNfe5ceO015eQxZQrk5wd+GCgvD2MgmNoF8n4f+vMPhzMboeBNZTG69RnY9T84/H1sHtjOPh4DxgohtgNj3e8RQmQJIb4BTyTW7cAclKDiAynlxmDnu49/AGwCZgO3SalW1oUQTwgh9gMWIcR+IcSD7rruFEJsFEKsA+4EronqlceQRFMi49uP93ss3hAfNTeEy7pd5lkkcEkXs7fPZt2RdZ7jSaYkruhWs6jUcKhuaRdviGfx/sVRbdegMzCi9QivfT/v+RmAJfuXeO2fkDuhxrbjwRjccrDXQohRb2TPmT2sOrTKy+EqIzGD5Lgwc2EHoVdmLy9RCMDOU76LRZuObfJ6rxO6iCnWNWLHqLajvH6/dp/ezcpDK71cVbqld4uoGKqR02BEiRrnOJGy1m1oFr1ujHojvxn4G8wGM4W2Qt5c9yZvrX+LYlsxJr2Jm/ve7JWyrDrB3CyqY9AZ6JnZM2Q5ndBxYd6FAKSZ08hvHiJazw+9MnqRZknDhRpU9c3qS2ZS4KCH6oEW+wv3Byy798xeL6Fpp2adgvbFqDcyMFtNaLZMaUmLBH9TPcFJMCXQPb07Lvek88X5gf2CZ++Yzb/749kOhTGx6RLweo/Kc/7TF+wNdT4gRjRQgeHLwHYp5dP+2nGLO1JQGearX4/mGlUT2lyu5j6qpE6MKpZWgY8dXRjdiOQq4ngA2l4DhhCuSofnwqbHaxds4yhR6VcKAmZXrXemTw++aHPqlEonEoko6JISNaf9ww/qfXo6WIJMt73/fmzdN+LiYOZM0If4Uzh9GgYNgl9+CZ2mu4KSEpWm5osvQpfV0NBoxCTnB09HdnJ1+CnW64I9BpHftWT69NBlHnggusHrLhf84x+1O3dA9gASjIH/j/VCT3ZSjbLVBmX0aLWGWRPefFO5dlx5pVpDKytT11xeDlu2wK23qnW3f/xDc4KKJtEeYoajag9UptY2vUKILsDjgN/ZkbNRRX/nnZBUAxfW669Xi9aRtq4DtaC+Y4d6YK3+xzu/YL5nUigQJr2JZpZmke+Ym+pW7/7YV7iP/YdLQz5wd+vWCCyB2s2CcYshPhN0IYxo9n0EX+bCgvNh1+tKxGE/AyFSzUSDwkJ48EHIzFSCjeXLlYI90I23QwcluvjuOygoUP8vu3bBl1/Cv/+tVIaTJ8Pw4WqQ1KcPdO+uLB7791cij9Gj4dprldDjjTdgyRIl0DhxAlavhldfhQsuCD9NEQBdH4CEVtQqfYpGVHCnKhktpezg/nnSvf+glHJSlXLfSCk7SinbSykfDXW++9ij7vKdpJTfVtn/BylljpRS5/75oHv/fVLKLlLKHlLKkVLKLTH5EGLETX1u8rEIN+qMXNPjGi/XhkgyI3+GV0TnjpM7vN7bnDbG5/oXldQFvU7P5I6TPW4BxbZiLxGDzWljXPtxEW93RpcZJBqrLHKf2c3BwoMcK6l8vkkyJdUqEjcYA3IGYHVU3gCNOiObj232EsoAEUtr0SKhhc/g5kTpCZ9UaHvOeMvryx3ltVrI0qhfzmt5nlfkgVFnZPHeSjGUXugZ1y7yf0+NmIYkStQ4l4mUta7bErchcnPfmz2ODt/u+JZPt3yKRCIQ3DXgrqDnjm03ljh95XisqbkpA3MGMjBnIAOyB3g5Do1tNzbsPl3a5VJAOYvVRqgphODmPjd73t/a79ag5TumdfRy9zpRdsIjlKjO7tO7PcI7gQjLjWt6npqRndh+YsiygZiRP8PzemJu4Hou//hyfjcefj8WfjMeHgvjsWVVJtx8gTrn92PhromwtHuTWvfVQ0aGcm/0t/nDX7mMjLr3I/LEXGAohHgEJcy4O0hfLgbmS6lNOdcZoYOhH0cmaCUckoMEe51YrtxAooWumnNQxqjQ82wAGx6ClXfWzIHDUQob/w7Lrq9ZH2NMQoKaJwvGjz/C735XtyDCsjIVjPXnP3vv7xZkivf996Nrne9PtPKb3ygRRyiKi9X85M8/q9eBgtKKi5XYY/x4FXCmoaFxlpOST/AlUAkFb0VfwNGAlzHatFFu7MH47DPYH1hfXifKy9Ua0aFDtTu/Z0ZP9LrKRUdZ7f87r1leRIPvhID77w+cZiwQUqp1tX79lFDSYFBrYnl58NZbYI+BhuhcJ9rijXCsdgOVqY3yHiFEDvApcLWU0q9/59moop80KUj6Bj84HHD++XDwYGRVyE6nsswZM8ZXGOKSLn456mtxXp32TdpHrkN+6JfVz8u61R8Wo4VV+38J+ZkaI+u6Hz2a9IALNkHONNCbCX4HlnBsISy/AT5qCj9OUwPNIwuUmMNZBrbTanOU+Ob4dNlV+hXbabeDhw1K9vm0EgiXCx5/XLlsPPGEGtwFEmx07KjKHDwIa9fCI4/A2LHqJm4yqRtKaqqyhqqJO0pcnFIkJierG1PTptCrl3LweOstFTnwww9w6aVhVKYzwpAP3Z+7hsa5hb+FB6PeyDU9r4lamz0zenpFvep1ei/HhsGtBnulN4kkl3W7jKQ4JVaRSKrOBQ9rPcwn7UckmJA7wWuR22K08P7G973asjqtjG0f/iJQOLRIaOHlqFHmKGPj0Y3sOlXp4WoxWhjZZmTE2uye3t3rvdlopuBUged9obXQy5kBoHVq64inyNGIPjnJOV5iHb1O7+W0kmBKYHib4fXRtQZJQxIlamg0GGqyEB6onJ+F8DRLGhflXYRe6BEI7E47AsG49uPITg4eIaXT6bis62UekYbZYGbJ9UtYcv0SXp78ssdxKDkumXsG3xP2pQ5vM5yUuJSgDhOhuKrHVYASx03rPC1oWbPRTFNzU897o87IkeIjfstuOb7FI+xIMCWEFUhR8cxSF9FrhWDDbDD7PD9UJb95PjY9WI3g0MPamcNCiou2ffsWhoRErEZ1HkYj3ZcUBGwjbI74/wxjXkfkianA0D0neD+QD6wWQqwVQtzgrutVIE0IsQP4DXBvdC/9HMKSAwNfi66Ao2JOpWkvEAEEGtIBB7+JXh8OV1s91xmh6/3hpY3Z9RrMHwPWk8FTFjtKVMTzoktg46OByzUgbr45dEDhf/6j5tNqI+AoK4Pdu/0HCQ4bFni+b+nS6Abc+XPN6NED2rYN//zx41Ug2Zw56v3p02orKlILg/fcA1lZsGhRJHuuoaHRYEnpou5lwSh4Pcopwhyw573o1R8Brr02eOoUgNtvj07mAYcD/vrX2p+f3zzfZ+6yKtFI/XzttXVfx9TkzrEn2uKNYOr5Cr4ArhaKgcAZdyqUGivvhRCpwNfAfVLKc+qxxmhUC8s1+SMsLISRI2HfvsgokcvK1FzByJHgz9Bk24lt6MOwUeyR0aPunQlCXvO8kAto5Y5ytpQsCZmrcPduJRJoFJhSYch7yoWj+RD3oDqEOkU64egCNWCcNxI+TIHP28K80bDkKlj9W/jlQfjlr7DhUfV6/Z9g5W3w88UwZwB8lAafB7G1rEJREUycqPJlFRcHtg/s1EkpKNesgbvuUu4cFksNHTFqgU6nRB1xcTBiBLz0UpgnpnaFwe9oAg6Ncw6j3silXS/1+u7PSMygS4suUWtTCMHF+Rd7nD0cLodH3JBgTAiaw72ujGk3xscJAlQKmau6XxWVNjMSM2iZUql1tTqszN4xm1Jb5Y29c7POpManRrztAdkDPK9tThuL9y/G6aoU9OmEjgE5A/ydWiuGtBri9bukF3q2n9zueb/j5A4s1XJg98/qH7H2NWJL1dRKJbYSr7+tMnuZ1++fhoaGhg9RXAi/Z/A9mPQmSh2llDvKMRvN/HHoH8OqclrnaR6h59GSo5wpPwPA8gPLPelFbE4bg1oOCrubpuxWnL7vDJM7T6m180JOcg6ZiZl0T+8elsi1Y1rHyvb1Jh/nqwp2nNzhea1DF1Z61E5dRyAfhGn5F9b6erq26IpJZ6Jri65BI9eGtR7m5QZX9bkiEJuObaLEVjkTnGZJIyW+hl7E5xCxFhhKKfdLKYWUMk9K2dO9veI+Vi6lnCGlzJVS9pdSVqqONepOq4vdAUMhVlNqg94Mbd3TwGkDwBDke6rgTRVIFGnshVDwhu/+3JuU+0g4HF+i5sdW3QWnNyp3jarBUcW7Ye198FlLOPBVBDsfXUaMUMFPobj5ZvjTn2o2B11SAl9/rSJ//Z03cKAK2PKHlMrSPVppww9WD091c++9gfvkj+XLVVBmhw4qhfPMmUqUkpMDL7wQfmoVDQ2NswCdHpqGmMc6tQZsx6PXB1c57Phv9OqPADNnhi4zbx58/nlkv0OLi5Uo5MSJ2tcRb4gnKynL77FEUyL9syM/jxkfD3/8Y/BUYxoNj6iKNwKp54UQNwshKnw5vwF2ATuA/wK3BjvXfY5f5b27fC7wJ7e6fq0QouZJUhspd90VOq9edfbuhfx8eO+9uj3MFhcrG51OnWDrVv9llu1f5mUF6484fRy9MnrVviNhkNcsz2txyR82p41FR2bTsWPQYhQUqNQcjYomPWHsT2rLOl9ZPBpqMKooPwKnVquB5I6XYMMjbtHGA0rEselxNVg+Mg8Kt4AjvARjRWWJ9Oyp7BSDDeTuuEOlMDn/fHXDqU/xTDiDUw85U6H307GzEtXQaCBc1+s6j2DOqDPyqz7h53uvLZd2vdRv/kC7y86UTlOi1m68Id6v04TNaeOCjiG8ZOvAxXkXY3DbA1udVlYcXIHDrdQ36Uxc0uWSqLQ7ut1oL5eT1YdWe723O+10aR45oU6/rH4kmCr/X8scZWw/UbnIsv3Edi+7QbPBHLG0LRqxZ1z7cZgN6rvDKZ1ei2/ZydnaQpmGhka90S29G11bdAWU01brlNZhR0iNajvK4whmNppZeXAlAAt2L/BEYJ3X8jyvlG8hqSoyqa1oJSODg787xOqb14SVfqNPZh/Pa5d0see0f/HGvsJKB8ZSRymdm3UO2RURgesRmZlY/2xj+U0rgl5P/+z+HscTgGMlx7A7g3sArz281ut5o29m6FQwGhrnDP1fAlMaEfVbF3owZ0Gff6n3zQaAI8hKzKE56pxIIwz+XT0MFsi/J/y5HkcJ7PoffNMVvu6q0hb/OBm+7Q1ftIVt/wb76Yh2PdrodMoVNxzBwr/+pcQehw+roMJAFBerucG774YZMwLPWY8cGdxd4+WXQ/epNhQVBY68vuSS0BHh/jhwQKVR+f575S4cKJWKRvQRQjQVQnwvhNju/uk3P5oQYoIQYqsQYocQ4t5wzhdC3Ocuv1UIMd69zyKE+FoIsUUIsVEI8ViV8tcIIY5VWeu6AY2zm+zJoVNybfmXup9Eg7LDcHJldOqOEG3bQsuWocvdcIMaTkTi+7SsTK1/vv563evqndHb736BoGdGz7o34Idbb1UO8xqNh2g7b/hVz0spX5RSvuh+LaWUt7mPd5NSrgx2rnt/IOX+I1LKhCrq+p5SyqPV+3S20q4dXH11zRezy8vh+uvhiivUg3P1dCfBsFrVA/VNN6mH00DpLQB+3PMjxfbgC/nxhvio56Zvk9rGb2R0dVYcXMEdd4TOB/XEE8Gvu8HStA+M+BIuOgb9XoQWw2su5Iggf/7sSQ4eDD7oevhh+PvfK/NsNTo63AR5f6h/AUd8ev22r3FOMSB7gEdI4XA5uKLbFVFvc0irIT45AwG6Nu9KmiUtqm1f1f0qkkzenrE9M3rSxByBXOgBmNxpsmeRG+BU+SnPa6PeyPkdzo9KuwNzBnotLh0qPuR1f81vnu+Vx7Gu9Mrs5bWgYnPaWH9kvef91hNbvawHjXojvTKjKwjViB6DWw72iJIArzREkUzHo6GhoVEb7h96v+d1uK4bAElxSR5hY5m9jGUHlgGweN9iQKUcuziv9ulPak11kUQI0URu01wM7rQFxbZinlj0BLM+m+W9fTqLQ0WVyaDj9HFeQomoEub19M3q6/XsEm+Mp+B08BQom49v9rw26U1aGi8NjaoYE1WgUHxG4NQmNUEYwZwDo3+odPQwJEBCm8DnuGyw9wMIEbRVI1wu2P85OANEGnX+NehDLLT5o6QAji9WqYuLttWtj/XMpZdCs2bhlV2xAlq1giuvhG+/VfOApaVqbtVmg/Xr4be/Vc4Tr7wSvC6LBYYODXz8zBl47rnIu1cUFcH77/s/ZjTC/feHnk/WaNDcC8yTUnYA5uEnzZYQQg88D0xEpeq6TAiRH+x89/FLgS7ABOAFdz0AT0opOwO9gMFCiIlVmnu/upuUxllM+gjQhVjgK3gzfNenmuAohs1PRb7eKDBrlnJHD0ZZmQoArus9wOWCo0eVGCQSDGk1xK9Yv9xRHpbYvTYkJMB//6u5bzQmoi7e0IgtDz9cc/eNCj7/XDln/P3vypGj4qG5OnZ7Ze69f/4TunSBd98NXf9Pe34KWcbmtJHXLLSVal3Q6/RkJwXPRwzKonvE+YdxhhjvvfmmsmFqtDZ2xiRoewWMWQAXHlRCjvY3QlJHNVA2JIMuQraXhkQlXNAnQLPzoMsDMGouB4baeWner4IKh9q3h9/85iwY/HT7M7S7JrycqJFGZwJLS5h+OPZta5yzCCG4rtd1gLKwDpUPPhIYdAYmdZjktc9sMHN1j6uj3vakDpOwVsk9aTFauLp7dNsdkD3AY7VeHaPeGDTXe13omdGTMnvlzc8lXZS5o+AEgpFtI7vA3jK5pZe1OcCGYxs8r9cdWef1OZTaS6N27RrRp1t6t4BpiEa1HVUPPdLQ0GhUpEdArBykjgs6XkCCMYE4fRwzu4Th21uFGfkziNPHYXfZmVcwj1J7qcehwiVdTMidUKdux4I4fZzH5UsiWX14NW+se8N7W/+Gl5g2lAtnfZCdlI1RV5l7Vid0bDsReAFVSsmBogOe9/GGePpmac4bGhpeJLaDiWvUz1CRw8HQxUNKHkxcDQnVwmszQjwL7ngZnBGcpHOWKOfZQBgs0POx+pnnaSDodEokEe6cnd2uIpgnTVLpiXNz1fxys2bQo4dyzDh1KnQ9AFddFdz14/HHCTm3WxOKi+EPfwhe5003NdKgM40KpgIV8fWvA9P8lOkP7JBS7pJS2oD33OcFO38q8J6U0iqlLEA50feXUpZKKX8AcNe1GsiJ6BVpeBOJsUKkqehTk54ggzvBYTsFBW+DswZR2OHgcsDuNyNbZ5S45BJlsBeKTZtU2q6apOyqitOp1kLPP7/2dVSnZ0ZPryC8ClqltMKoN/o5IzLMnAmjRimRoUbDRxNvnGW0aKEWuM2+f/thcfgwPPQQtG4NgwfDs8/CTz/BunVK+fzzz/Cf/yhbuqwspSTeuzeMig1lAfPgVsUlXeQkR//ZJL9FaHePOEMcW0uW8eijoQcfV1yhPodGK+CoIK6pEnIMeBkmb4WZhTBqDvR6AjreDlmTILUbxLVQURTCqAbjerN7i1fvhV6JNCytVD7SVjMh/14lDJm0DmYWwbhF0ONhyBjN9p2GkI4xI0aofJWNHiGg73PQ5Y/qM4sVejOkdleTKBoaMWZWD5Wf+MpuV8aszcu7Xu7lgCGRTOs8LertpsSneE3iO13OqLer1+kDLmZPzJ0YNNd7XYg3xNO2SVvP+6qLMkmmJIa0jGzKEiGETxqWglOV0bFbjm3xOpaZmInFqEnKGysGnYFu6d189jtdTga3HFwPPdLQ0IgZGRnqmdnfVp1g5aSs23Y4sOBZr9Pzz3H/5LHRj9UsxQlK6FkxKbfm0BrWHFrjuV81NTf1urc2VMa1H1fjc1qnto5CT+qGEMJL6FnuKGfr8QB5YIEDRQfQV0nHUGYvi3raVw2NRok5HSasgKZ9aydo0CdAiyEwbomap6pOxmgwJPnur+D4UijdF/h4TSk/CkdDBKS1u04JVqKRsqWRcP750K+fEnLUBKtVBQju3asWyGrKBRf4Dz6s4NQplX4lEq7JdruaI3/nneDlLBZ44YWzIADt3CVdSnkIwP2zhZ8y2UDVL5r97n3Bzg92DgBCiFRgMsqxo4KLhBDrhRAfCSECJosQQtwkhFgphFh57NixEJd4jnP4cN3HCpHeKsYeOoO6f4Zi3X0QIJCrVtiLYe29yn2jEZCbCx07hlf2rbdUCq7i4pqlULFaVUqrvn1h48ba9dMfPTJ6eILfqhILUfj//qe5bzQWNPHGWch990Xm4XD9evj972H4cOjZUymfhw2Du+6CVatqWFnmmrAWUFqltIraIlNV+mb29YnerU6xtZhF+xbx61/DmDHB8xWWlECfPiovYYNIoRJswrMmm8EMzQdB5zuh33Mw8hs4/xe4+Chc7oDr7XCjFW4qg5vL4KZyuMEKs5xwaSlcuBcmLIOhH0Cvx6DdlZDcQY3kqrSTPLI3TkfwO+ehQ2dRvkchoOsf4by33ClUovxVrLdA9hQYuwjiopsyQkPDH52adeKFSS9wfe/rY9bm2PZjsTltnlQL2UnZMVs0qBCrOKWTdk3axcRtZEb+DB8r8iRTEhflXRTVdke0GeF5XTW61ua0MSBnQMTbG9JqiJdI5HT5acodKtKguki0T2afiLevEVvGtx/vtUgGyqK+TWqb+umQhoZGbAiRsiNmdYTgV31/xd2D7q7xed3Tu3u+28ocZXy38zvKHeUIBFM6TolwL6NDbZ6popW/ua4Maz3MMzdgc9pYe2RtwLLbTmzzEuukWdJIiU+JTEei7BajoRFzjMkqhUrvp9wurGEEr+gt6rz+/4GR3ylHC380GwyuEFHJq+9WC1F1xV4Mq38NftJyeqEzwIiv6j9Nbj3z3/+GtrGPNE2bqjnrYLz6qgpIDJaqORxKS9UCYDjBZZddBgMHag4cDRUhxFwhxAY/29TQZ6sq/OwL9ZsR9BwhhAF4F3hWSrnLvftLoI2Usjswl0pHD9+KpHxZStlXStm3efPmIbqi0aDJuiB06hTrcdjwKNhLItOm9RjsbFxZeR5+OLjzUlW++QYGDFDpT8IJwC4uhpUroXt32LGjbv2sTjNLM0+K8QriDfEMyhkU2Yb8td0MXnst+gIOTSBSdzTxxllIQoLKCdig/kCyl3rloQ9E1xZda1avyw4le+DYYjg8Dw7OhgNfwb5PYe+HsPtd9XPfZ2r/wTlweB5d4o3EhYiQcuFifsF8hFDqvMxMgrpDlJTA1Knwl7+o13UdENSGkhI4fpyYTFYCUAYUA4XAaffPEiDEGLo6PVlL65Lg8sVvv4WCAnA4atPRBkrL6coJI7V7dOw1hVFFo/R/CQa/CzWMCtTQiCS39LuFNEvsxEMWo4WhrYfiQqm+ruweO9ePKZ0qF16u6n5VTNoc3368T4oJq9PKmHZjotrusFbDvBxOKrCYLGQlZUW8vf7Z/b1EKhajhZ0nd3Kq7JTX9Zv0Joa2DpL8WKNRMKz1MBJM3vfHATkDYiL01dDQ0IgWQgjG544H1P3q6+1fY3PaSIpLYmrncNcL6h9LoEXVAAzMGRilntSNAdkDvJ4tNhzZELDs1uNbvZ43+mX1i1xHIhEBGsQtRkOjXhA66HATTNsL3f4K8RnKsbUiPa8+Xok1dHFgzoEef4Ope6HtVcG90C1ZKgVwMA59B0WB0yCFTekeOPBleGUTWsF570TXZbWBi0Nyc+H552M/J3311aFdqK+8sm4BdyUlcM01KrgsHISAN94IHgxYVxrU3H8jQ0o5RkrZ1c/2OXBECJEJ4P551E8V+4GqLhg5wEH360DnBzsH4GVgu5Ty6Sr9PCGlrFhl+C+gRamcC2SMCi/12JanVGqvumIvhhW3RNbJIwZccAE0aRJ++U2bID8f/vY3JeIoLPQ+7nCo7/qNG+GOO1RQ+5kzke1zBV1aeDsLx+nj6JUZG0e/6dNh/Pjga511QacL3xVFIzCa9vMsZepUpe796acGsti9f1BY1qp3Dbir8o10QdkhKN2v7A5L90HRTijaDiV7ofwwOArVgE9XLVGTlFQKV90DvioDv9EOFxeY7ZS4UOk/dPHKZUKf4P6ptjGdLgSUgm/FCpgyBdauDZ7f6qmn4O23lfLviitUV6Jtk1dUpNp54gnVfoTSb8UMHZL/41qGmVcGVD5KqSwY586FVq1qnxqowZHcESashK3PwPo/A66652YVOvWAlz4KBrwC5oyIdFVDo7FxVfermLtrLkDUHSiqkpGYQauUVuw9s5fpedNj0mZ6YjptUtqw7WTlBGV+8/zIRYMGYEDOAJx+BncRXcyoQq/MXrhkpQ2TEILtJ7dTYi/BbDRjtyr1YLwhnt6ZvaPSB43YMSB7AGX2yntinD6O8e3H12OPNDQ0NCLD9M7T+Xb7txTbitl8fDOgUnYMbz28nnsWPjnJOV7PHaEY225sFHtTe/pk9fESZBScLghYdsPRDR6LY5PexLDWw6LePw2NswJTE8j/PeT9DsoOwIkVar5PCDBnQdN+SpBRE5qdBwc+D15m1V0wcjYYajkpZy+GlXeFLleVnAsg91ew42VwRnh2ThcPmRMiW2cUuPZaWLNGuV0Emz+tC9XdLC68EH73u+DnnDwJ06bB7Nk1n6ctKVHX89lnNTsvKwueflq5WJdEKDi+Kq1aRb5ODQC+AGYBj7l/+vuyWQF0EEK0BQ4AlwKXhzj/C+AdIcRTQBbQAVgOIIR4BEgBbqjaiBAisyIFCzAF2ByB69No6DTpFdphCsBlhZV3wIBXwRimBYVPHQ44tQYOzand+fWITgd//asSWoT7HXvqFDzyiBJwjBunBCAZGSot1t69Ki3WunXR7TfA4JaDWbR3ked9qb2UHukhbKQiyCuvQNeuSsTijLBmJzERPvwwsnWei2jijbOY116Dbt1qly8w4uwfxNeXfx28jNMGJ1fBxsfh4DdwciUglUWUlOAqB5efJIbOUqjhF0wa8IFnPduBso8oBo6pRW9dnNJ8DFpYeU6aEsP8/vfw0kvBByBHjsBNN8EDDyibvJtvVg/UQkROdFBcrAYrK1fCiy/Cp59Gb1AUC/qyivfeg8svV9fhz4Jw/37o1Qv++U+ldtfpYm/HGBV0esj7DbS/Tok4Nv9T7XfU8I9X75bzZ4yB7o9Ck+7By2tonOVc0PECQKUPqbGzUx0Z124c7298n07NOsWszYvyL+KJRU/glE5MehMz82dGvc32Tdp7pTEBMOlMjG47Oirt5TbNxeGqVKWW2cvYfmI7JbYSL1FHmb2swdqza4RPSnwK2cnZ7D69G1ALZUNaDanfTmloaGhEgDHtxmB1WnFJl0ek1juzN2Zj41Go98joUSPxRiyfiWpCdlI2Rp2RclQathJ7CUXWIpLifKP61x2pnMmNN8THJC+1hsZZhRBgyVFbXckcB4e/Cx78cmwhnFwNzQaptCY1weWEws1wZF7N+9brH3D0Jzizwf88Zm0QBohvAYMCZkxoUPzrXyod99Kl0XEmTqkWo5CdreYLly4Nft7ChTBkCMybB8nJ4aU0KS2FBx+EJ5+sXV+vuw7+9z/Vt0gukJnN8MEHkatPw4vHgA+EENcDe4EZAEKILOAVKeUkKaVDCHE7MAfQA69JKTcGO19KuVEI8QGwCbUgcZuU0imEyAHuB7YAq91Ok89JKV8B7hRCTHGXPwlcE/3L16h3dAZo2geOLwpddu8H0GoGZE2snVjRfgYWx86tONJcdRX8+c81F8i5XErMN3t2dPoVir5ZfUk0JVLiTnuTGp8a9QC8qjRtqoLVBw1SjlKRMAAQQt2fFy5UTlwadUNLm3IW07q1UgQ3aIcCeyHseAXmjoQPk2HBBPjlz3DsJ7coo0zdQByFlQOeuGZKfZg9BTrepgZFwz6HievgwoNw0TG4+BTMKISZxernxSfV/gsPqjQVQz+Fno9Dh1sg+wJI7QGmpqp+l1W1Zy/06a5er5wtXn8dUlNDf7ZHj8Izz0BeHvTsCffeC19+qfaXl8Pp08p6qbzc//kulxoknDmjNpsN9uxRaVzuvFMJQoYOVU4fXsKNxpjrNj2dKVNg2TI16Aqkgi8rg1tvVTeA//1PiVjOnIm8QjAYJSWqH7/8EuGKTanQ7S8cHruG+elX4cy6QLnAGBKVlaioNqqs2K8zqdQr3R+B8zfD8C814YaGBtDU3JTMxEwGZMc+zcLLk1/mzL1R8tYLwJROU4jTK0WbUWf0iFeiiRDCRyQRb4xnUMvo5GnUCR0d0yq99+wuO+uOrGPria2U2CpHak3MTUiNTw2v0owMNcIIdwtGTerJ0FyRwmFkm5EASCRWp1UT5WhonAtEYizTwMdDaZY02jVp53kfb4iPiegykgzIHhB22fgKkXkDRAhB9/TKsZPFaGHbCf+ilO0nt3tel9nLKl2+gj1L+DaoPRdoaESCFkOV62goFl+u5vhqiqMIFtbye1lngNHzlWgkEmlO9GZIzoPxS2sfWR1j9Hr4/HN1O9brI1u3xQJz/ASI/+UvKto3FGvXqjnavXt9LfOrUlqqtlmzai/cAPUV/+GHKh13OGKRcDCb4d//VkGbGpHHnapktJSyg/vnSff+g1LKSVXKfSOl7CilbC+lfDTU+e5jj7rLd5JSfuvet19KKaSUeVLKnu7tFfex+6SUXaSUPaSUI6WUW2L3SWjUK22uCP8esvhyJVZ01NDN214E80ZC6d6a96+BYDCoQN9wvv8bEj0zenoFoVUdj8SK7Gwl4GjVCozG0OWDIYQShCxbBl26hC6vERrNeeMsZ9QolUrjnnsamCvDqXWw5V9KGYiuMjeXy48cu0lPlf4haxKkDVCDIKe7nM4INcy1izlT1Sld4Kxw8xCgj1P1Hl+inD+OzA9YxcUXw4QJymLp3/9WIotAAowKtm9X27PPqvctWkD79pCTo74o27RRgpC4OCVEsNuVg8fevXDggNq2bg3TSSVSuW7DXez0Z5NRS7p0gZ07lXPMn/6kRBL+lJMHD8IttygRy4gRKlfXhRcq5bzVqgaHCQnKnaMuWK2qDxUuH6tWKfusr75SQpoIXjo2p42nljzFXxb8BZvTRmZiJv89/x0mZXZCFG6Bwq1KzORyqN/7xHaQ3FltptgpMzU0GhMHfnOgXtqNtVgEvFOVmPSmmLmNjGk3hmX7l+FCDTpK7aVRTVlyXsvz+OVopXpu47GNFFoLkVR+Iddogf/IkQj2rgbUV7ugFogi1X5NftfT02v8jDKq7Sj+t/Z/uKSLvGZ5mPRRSsqpoaHRcIjUWKaBc3Hexfzt578hkeiEjgm5Dd8Kvyo1cdnKTMqMYk/qzsCcgSzet1gJBR1WnlrylE/OaYfLwbGSY573KXEpJMclqzeRuKfW53OBhkZjJKWrEjU4QoTalu6HHyYqMUW4EcmOUvjxAijZXfv+mVJg1DxY/RvY+UrtU6joLZB1Ppz3RqXbaiOhIvr2/PNhxw4CpkkOF4NBLc598gn06eN7fPx4aNJEBXmFYt8+6NhRpce+7z41F2lzxwzqdOr1v/4FL78Mx4/Xrd+ghBvLl8OAAXWPcDab4bnnlKOHhobGWUyrGbD61+GVddlhwUQYvxySclWgZygcJepedzrS0amx5+KLlfvG1q313ZPwadeknXIWliAQnNfyvHrpR3q6uj+NGqXu1bVZQzabVdaCH3+Edu1Cl9cID028cQ5w++1KVfzuu/Un4PA4VNhOw4pbYf/nSqghA9glJHWEzr+GVhernI46g/cgJRIDFqFzCz+qiD/08ZA1AVoMA4KvyicmwmOPqZyKjz+uUpfodMFV21U5elRtGr6YTCrVzLXXqpySzzyjBlZOZ+VgqgK7Hb7/Xm233KIGRO3bK2eOTp2ge3fo0EGJZHQ6VV7Kyg3UupNOpzaTSeXB3L0bNm6EDRvUjWvHDti1K7RIp7Z8u/1bbvzyRk6Vn/LkXD5UfIhLPrmS3pm9+e/k/9Kp5YXRaVxD4yymPkQU9YVep2dU21F8tf0rJnWYFLNrH5QzCIvJQrFNzZK1TmmNxRiBCLMADMwZyNvr36bYrtrbfXq3l+uGQWdgaKuhUWv/rKARCVYGtxzseT22/dhI9kZDQ0OjXjm/4/k8+vOjSCRmg5nOzTrXd5dqRPf07hh1RuzufNwDsgcwMXcioETpjy16DJd0oRd6LulySX12NSTxhniPCNTqtPLehvf4YFM1L3qJl1DUUNMUDBoaGpFFCGg1E3a8FHhusYITy2HZjTDgv6EFHI4SWHkHHAvDqj4UOj30fUa5B6+81R2I5gp5mge9Bbr+CfLvqZlgugHRsqVK9/zb36r5vdoKOCwW6NpVuXkEMioSQi3e3X13ePb5TqdKQf3pp2qxqXVrNSd44gSsWRN5h9+qAo7Dh33nN8PBbIYXXlCppDU0NM5y4ptBWn849nN45R0lMHcEjPgKkvMDOzU5ytS63OKrVIqvswCdTq19Dh5cd6FgrNAJHblNc9l4bCMCQZ9MP6rEGJGWpgKWH31UrXPabOHfA81muPpqla3AEr2p4HMSbbR5jvCf/8DmzbB6dfQWnwMRF6cW0zm5CuaPUzcSfw4boAYm3R+EDrcphWB9TYjUwM2jWTP4xz/gb3+D775TquzvvlNWQ2G5ZEQIIRqfPVQo4uJUipRbb1W/vx98oFLG7NmjbgwlJb43kkOH1LZwoW99TZooNw6TqXKrEITYbErYceyY+hkrtp/Yzk1f3sTyg8sptfuqq0rsJSzat4heL/Xi+t7X88jIR2Ka/0xDQ6NxcVH+RXy1/SsuyrsoZm32z+5Pmb1ydBRt4UTvzN5ewpQiaxHljsqHG4vRouWgP4tok9oGi8FCqaOUEa1H1Hd3NDQ0NCJGv6x+xBniKHeUx1R0GSl0OjXhuPn4ZgCaxDfhLyP+AsDGoxv59/J/U2QrIsGUwIg2I+qxp6GZ2mkqj/7scTvHhQuXK/gCq/asoaHRAGhzORS8qVKchGLPu8pxt8+zar7RnW7Sg8sGThus+S3s+l9k+9n+GkjrA788BAe+crcXYHJWZwJ0Kqis24PQPDrpKGOJyaRci8eMgSuvVHNu1gDTwtXR6SA+Hu66Cx5+OHQKllmz4IEHwhNvVGXXLrVFm4wMJQyZNQvmzw8/yNJkUnO+770HYzU9u4bGuUPuTXBqDTjCsBQCsB6DOQOg5UXQ73nlUCX0anNa1b1v5yuw/gGw1yKlWAOmVy8VaP3HP9b8HlBfDMgewMZjG5HIek8RbDCo9GOXXKLut598ou65/j5Ls1kFRY8YAX/9K/TvH/PunhPUMaGARmPBaFTOBP37V3HBiAHx8cp6buEPZ2DBBWA7GVi4YUiCCzYp4YbBUn/CjVpiNCorwM8/VwKAF19UX3Y5OepYcnLkchuCEjYkJ6u6O3aEG29UORRPngx9bmMkL0/dQLZvV4G7772n0gH17as+C4tFWTIGU/idOgX796sB2ZYtsH69ctfYvl0JQg4eDCzcMBjU513xmWdmwowZtb+eImsRd8++mx4v9uCnvT95hBsGnYHU+FRu73c7ZoP6Y3VJF2WOMl5Z/Qqtn27Na2te88qJpqGhoVHB+PbjSU9IZ3S78K3M60oTcxOaJzTHJV3ohC7qCzR5zfK8xBpmoxmnq1LJZ3VY6ZXRy9+pGo0QIQQdm3UEYFDLxj95raGhoVGBXqenf5aa6bqwc+N02Kuam7ngdIHn9d4ze9EJNd1kd9rJa54X877VhNpEuo1pNyYKPdHQ0KgRzQYpV91w2fV/8GUu7P9URR7bC9XmLIP9X8BXHWHHy9Hpa2o3GPohTN2tnDSa9HYvqhnUpouDlG7Q8Q6YvAVGzTkrhBtVmToVtm1TKZJbtlTzd4HEGElJarvhBli0SAXMhRJugJqv+/vfG3ZwW9Om8MUX8NJLSswRrK8mk5pbv+QSNXepCTc0NM4xcqaBrEWepX0fwyeZMHe4St+15g+w+HL4uBmsuvOsE25UcMcdMGyYWiuKNglhZmILxsCcgQDE6eNoldKq7hVGgM6d4e23lSv9888rV428POVO1bGjSlHzr3+pQOtvv9WEG9Gkca2Oa9QJi0UJOGbMgLlzo59CxWJRf7xffw2Wgv+A7VTwE3r+HeJagCGG6pIokZgIl1+uNoDTp5U13uLFyhFi3z6VMqWoqNIBogIpvd0QpVSKdIdDOUdkZECbNkrZNmiQUhXGUpDTEGjSBCZOVNujjyr3jAMHKtObVAgzdu9xse/oGVxWC06bCaNRYDQq5T5Ufs4VKVScTvVZ6/XqBpycrGyjOneGbt1U+pXcXOUkk5RUu767pIs31r3Br+f8mnJHuXe0uMFCp2ad+Pryr8lMyuTSrpcy5d0pFNmKsLvsnvJ3fnsnTy5+ktemvua5yWtoaGiAyil/+HeHY97uoJxBfLz5Y1zSxYCcAVFty6g30ia1DdtPbgfA5XJh0Bk8tu1mo5n0xPSo9kEjtvTO6M3W41tpam5a313R0NDQiCjj2o/jp70/MartqPruSq3om9WXT7d8is1p41DxIc/+PWf2eFJBuqSLlskt66uLYaHT6UgyJVFkC98686L82LmcaWhoBEDooPUlsPPV0KlTKig/CosuA51RpWxGQNFWcMXIgtWcrhyHuz/onogqVT8NlpoJURopmZlw//0qMnrNGnjlFVi2TKWgtttVUFb79nD99TBunBJj1JSrrlJRw8VhBqrXB0IoF5LLLlPRzW+/reaMjx9Xc5Z6vZqHPP98lVY6M7O+e6yhoVEvGBMh50LY8z41SrsFgIRTa9V2jiAEvPOOWsuJZrZgkwmGDKl7PRVuGznJOQ3OhTE9XblEzZpV3z05d9HEG+cYJpN6KPzjH5VlXbRyQFks6g/7mWfcD9rWE4EdNypIbBdZ4cYnGVBex2/pW4Ezde9KKjDOvVXFgZ4jZekcKMumkGTsGLFjRIcLAw6M2EnjBNkcoBnHEceB48AG4KsgDR45Ai1a1L3jjQS9Hlq1Utso97znqoOrmPLeFGxFBxEIOjXN4+0LvqQJ7bBaweVSYg0h1Pl6vRJrNGkSPXXmigMruPbza9l9ejcldm/PKYvRwjU9ruHpCU9j1KvR6eBWg9l02yYmvzuZjcc2etw5SuwlbD6+mVGvj+L8jufz7IRnyUzSRnIaGhr1x+i2o/l488fE6ePomNYx6u0NzBnoEW+UO8q98s53a9Et6u1HjEgOzhrYQC+S/HPcP7lvyH313Q0NDQ2NiHND7xtoldKq0aZFzGuWh9lgxua0UWIrodxRTrwhnp2ndlLmUJMNrVJaNbjJSH90a9GNxfsXh1VWJ3TkJOdU7khPr/sMcfrZKTwVQjQF3gfaALuBmVJKn8geIcQE4BlAD7wipXws1PlCiPuA6wEncKeUco4QwgJ8CLR37/9SSnmvu/w1wD+AA+5mn5NSvhLpa9aIMe1vhIK3wVlDj3SXHc5sjE6fwkUIMEQgdLcRIgT07g0vvBD5ug0G+OwzGDgwevPekUKvV0GWFc6+druaq4yLO6uHdxoaGjWh011w4AtwNJJcIPVMaip8+SUMHx69e0BqKrz7bt3r6dqiK6DGVBoa1Tn7Jb0aPuj18PjjytYmLS2yC9Umk1JJf/ihegD3KKRbTlN2gMHY+PfI3oTqKtyAiAg3gmHASTYH6c8KxjCPicxmCl9yAV8zgTmMZj49WUdzjlOjZ/azdOInHFzSxWMLH2Po/4ZysOggOnRIJNtObWHou9348cz/0amTJD9fqdi7dlXWTx07KleTaAg3thzfwsS3JjL0f0PZeGyjj3Aj3hDPg8Mf5JZ+t7D1xFY2HN3g2Y6VHuPlyS9zYecLiauWk7XMUcZnmz+j3bPtuOvbuyiyhh8ppqGhoRFJKtw22jZp67FJjybntTyvMrUULhwuZSOpQ8eQVhGQv2s0KFLNqeSm5dZ3NzQ0NDQiTnpiOlf1uKq+u1Fr8prnee7BZqOZvWf2ArDl2BZPmYpJyYbO8DbDwy7b3NLce8fhw5V2jrXdDsfeOS1G3AvMk1J2AOa533shhNADzwMTgXzgMiFEfrDz3ccvBboAE4AX3PUAPCml7Az0AgYLISZWae59KWVP96YJN84GmvaBOM2dTcOb7t3hoYciY2sfCF0Uhr1Go0qTogk3NDQ0PKT1V271GmHTrx/897+Rd6vX6VTg7/ffq591xWw0E2+Ip3OzznWvTOOsQxNvnMMMH67y5d14o/oiq40VXQUGg6rjyith61aYNKlageaDodPdoA/y1HzsZ1gyS6VXcTQQaXTjDIA6Z8Ubh4oOMfS1oTz808OeSC+JBJSoo9Reym3f3MZFH1zEmfIoK3OAYlsxE96aQN7zeczeORur09d9RiDQCz2P/PwIg18b7Hcb/n/D+XLbl34XRB3SQbmjnGeXP0vq46n8af6fcLlqaqOmoaGhUTe6teiGQHgs/6JN78zeHpeiqiTGJdI/W0u4qKGhoaGhEQtap7T2pEfRC71HvLHr9C4ADDoDfbP61lv/asLF+Rd7vdcJHQadAYPOgN6jCVAMbx2+0EODqcDr7tevA9P8lOkP7JBS7pJS2oD33OcFO38q8J6U0iqlLAB2AP2llKVSyh8A3HWtBqrYpGicdQgBHW4BfXx990SjgfGb30DPnmrOOhqcaymsNTQ06gkhoPNvQG+p7540Kq64Ar7+GhITI1OfyaRc39euVQLBSFFwVwEPjXwochVqnDVo4o1znCZNVPqUrVvh0kvVg2dSUvjnJyYqRfC0afDLL/Dqq0F0Az0ehT7/UpaAIsCT876P4bPWsOt/4CwH2xmQtVyIjo+AgOEF6h5BU7GFSyTaOnujdgLy1dav6Px8Z5YfWO5JLwIqHYm5SjqeUnsp32z/hk7PdWLp/qVR68+jPz1KymMpzNk5J2g5iaTEXkKhtTDkVhZC1OSSLh75+RGaPNGE73Z8F8nL0dDQ0AiKUW9kaKuhTO00NXThCNCtRTev7/oK7E47vTJ6xaQPGhoaGhoa5zp6nd6TPsThcrDn9B5AiepBjcXym+cHPL8h0SujF4nGytndX/X5FYX3FlJ4byHzZ80nyaQmSpJMSdza79b66mZjJF1KeQjA/dNf6Gg2sK/K+/3ufcHOD3YOAEKIVGAyyrGjgouEEOuFEB8JIVrW6oo0Gh5ttYTsGr7odMoZ2hKF9U6LBZ5/PvL1amhoaPil/XWgj1Ke97OYkSNh6VJo3lyJL2qLxaLEgGvWKAFHJMlIzMBs1NSAGr5ESXuq0dgojNtIwszn6DZoM0PLH2fDd31Zu0bPiRPqy6nCrk1KlSsqJUV9YV1zDUydGqaCTQjIvRGyJsKaP8D+TwEdOKstvjiKYOVtsOb3kDkWWl8OGaOUulA6QJ8Ynjfd9DAEDO9oPnSNnXJHOXfNvou31r1FqaPyd0kgSI1PZeF1CzlReoKJb0/0pCuxOq0cKTnCqNdHcc/ge3hg2APodfpATdSI7Se2c9OXN7Fw70JcAYRHFX1LjkuuVRsSybGSY5Q7yj3OIlUptBZywbsX8Ku+v+KRkY802hzaGhoajYsfr/0xZm2ZjWaykrI8Eb4VCCFolRLhkZSGhoaGhoZGQPKb51NwuoBSeykFpwuwO+2csSqXQ6fL2WhyOAsh6JHRg0X7FgGw4egGz0Tq3jN7PeOuckc5vTI1oWhVhBBzgQw/h+4Ptwo/+0JFwAQ9RwhhAN4FnpVS7nLv/hJ4V0ppFULcjHLyGOVTsRA3ATcBtIr0DL1GdLBkQesrYPeb4LLVd280GhCZmfDee3DRRWo+OxJYLDB9Olx9dWTq09DQ0AiJwQI9HoPVvwFnSejyGh66dIGNG+GOO+CLL2p2L9Drlejj3nvhnnvqJgDR0KgpmnjjHOZA4QHe/uVtXl71MoeKD1FuVwvBm01jcQ5xcuGNF3JF55toUT6E0hIdUiqRRocONXPn8MGSA4PfUelRdr0OW5+GsiNK3OGs8u3pLIX9n6sNwNIKWgyF5DxI7ggJbcGSDXHNQDrBaaVyrC7UJip2Se9jmp3iWcHmY5uZ/O5kDhYd9HKl0AkdaeY0Fl+/mNymuQDMu3oeY98cS5GtyFOuzFHGE4uf4OvtX/PJJZ94osZqQ5G1iD/98CdeXvUyVqfVr3DDoDOQZEri80s/Z2jrobVuC0BKyTPLnuGP8/7o15HD7rLzyupXeHPdmzw1/imu6XmN37Qr5yJCiKbA+0AbYDcwU0p5yk+5CcAzgB54RUr5WKjzhRD3AdcDTuBOKeUcIYQF+BBo797/pZSyIldzHPAG0Ac4AVwipdwdhcvW0Djr6JvZ10e8kd8sH6ElCNbQ0NDQ0PAlIwOOHAm/fKD7aXq6l9Nj36y+zN4xG6d0svn4ZvYX7sdsMFNiL8HqtNK+afs6djx2DG89nKX7l+KUTraf3O7Zv+nYJkpsaqK8maVZrUX4ZytSyjGBjgkhjgghMqWUh4QQmcBRP8X2A1VdMHKAg+7Xgc4Pdg7Ay8B2KeXTVfp5osrx/wKPB7iel93n07dv3xrYqGrUKz0ehj3v1HcvNBogEycq6/zJk6GkjmueFgtcfz0880zg26SGhoZGVGh/HWx8BEo18UZNad5cCfl+/lkJMVavBpcLbAH0nhaLOj5lCjz+OLRpE9PuamgAmnjjnONM+Rk+2vQRL656kV+O/IIQgnJHOQBmgxmb04bNacPqtPLOL+/wxdYvMOqNXN3jaq7teS3d0yOY0MnUBDrfrbbiAjg0Gw58A8cWgssKQg+O4srypXth99v+64pLA0tLiM8AnQl0RtAZVHoW6QCXHVwOVW/ZISjdp8QjGo0SKSUvrnqR3333O8rsZV7uE3qhp0VCC5Zcv4TWqa09+wfkDOCna39ixP+NoNBa6Dmn1F7KmsNryH8+nzcufINpnafVqC8u6eKNdW/w6zm/ptxR7vl7qo7FYKFzs858dflXZCZl1vyiqyGE4O6Bd9M/uz+T351MkbUIu8vuVaaiP3d+eydPLn6S16a+xsCcgXVu+yzgXmCelPIxIcS97vf3VC0ghNADzwNjURODK4QQX0gpNwU6XwiRD1wKdAGygLlCiI7uKp+UUv4ghDAB84QQE6WU36KEHqeklLlCiEtRE4iXRPn6NTTOCoa2HsrX27/G6rR69g1pNaQee6ShoaGhodGAqYlwowb1dGneBYvRQpGtiF0nd7HnzB4MOjXVlJGY4XndGOif3Z8EUwKF1kKOlxzH7rRj1BtZc3iNZ/zYL6tfPfey0fEFMAt4zP3zcz9lVgAdhBBtgQOoMdXlIc7/AnhHCPEUauzVAVgOIIR4BEgBbqjaSIUIxP12CrA5Aten0VAwZyq33+0vqbm/aKDTQm4bKyNHwk8/wahRUFSkFuVqisUC998Pf/xj5Pun0bCIddCXe/9sIBO1XvczcJuU0qkFfWl40Bmgz7Ow5EpwRFvAcXYGgA4dCosWQUGBEnMsWABr10JxsRLkNWsG/fvD6NFwySWQmlrPHdY4p2k8o2iNWmN1WPl2x7e8tOolfij4AYPO4EkfASoPbV6zPP4++u90ad6FJxY/wcurXgbwuBQ8t/w5Xl71Ms0tzbmpz01c2f3KyNqSJ7aFDreoTUooKYCjP8Pp9VC0DYr3KNGF/VSlOAOU24bLCtYTaos08emRr1OjTpwsO8kVH1/Bz3t/ptTunXLHIAxkJmWy5PolZCdn+5zbM6Mni65bxND/DeV0+WnPBJzD5aDIVsQVn1zBjPwZvHD+C1iMoZNirj28lis/uZItx7fglM6A5SxGC9f0uIanJzyNUW8MWqfTqQaShYXqwcHlUpvTWflaSpU5SK+HBN15fDxyE3csmczOwo2UVU9DBJTYS9h8fDPnvXoe0/Om8+IFL9LM0izk9Z3FTAVGuF+/DiygmngD6A/sqLDYFUK85z5vU5DzpwLvSSmtQIEQYgfQX0q5BPgBQEppE0KsRkWGVfTlQffrj4DnhBBCSqlFeGlohKBXRi/iDfEe8UaSKYn+2f3ruVcaGhoaGhrnFnnNK9Oi7C/az57Te3C4HOpYI0mZUkGfrD7YnCoEL94Yz65Tu+jUrBNbj28FwKQ3Maz1sPrsYmPkMeADIcT1wF5gBoAQIgu10DVJSukQQtwOzEEtgL0mpdwY7Hwp5UYhxAeo8ZmDykWuHFS6li3Aarcj23NSyleAO4UQU9zlTwLXRP/yNWJK1z/DjleiV7+ITLpdjfqhd2+1SHf55bB+ffguHHFxSrjx2mswbVo0e6jRgIhp0JeU0okSeBQKdeP6CHW/ew8t6EujKjlTIbG9WjOLJvq46NZfz7RtC/fdpzYNjYaKJt44S3G4HLyy+hU+3Pghi/YtQid0ntQKVqcVgcCoM9K5WWeu7nE1ec3zsLvsrD2ylnHtxzEoZxCfbf2Mz7Z8hpQSq9OKw+Vgz5k9PLjgQR5c8CAtU1pyfofz+fXAX9O2SdvQnaqpTas/BJBSBmllkAY0BVoA6YAJ9Rutr7LpABdKy1qxOQArcARluHkCNWw/ARTinVn1SJRvhP4o3kVl2hed2nD/NFhAnwC6hjVg3Ly5UlCg0ymlYsVrk0ml20lMVGKDuvDM0mf47Xe/DSyUECo1yYjXRwStJykuiTPWM1RfHy+1l/LGujd4d8O7vD39bS7OvzhoPasPrcbutNO+iX8rYAlIl45Zrf9C57JL+fczsGuXchk+dQrOnFFCjeJiNWgsKwO7HYxGMBjU51X1szQYKj9flwscjgphRzpSLMYx+D5E+y8qEwQJ7/8PvQ7mrN7I7n4naNb2nBZvpFdEXLntd1v4KZMN7Kvyfj8wIMT52cDSaud4qYiEEKnAZJQy36sd96TlGdS32/HaXZqGxrlDz4yeXiI+l3TRO7N3zStKT49cNLKGhoaGhkY0qMlYOsY+7h2advDcj0+VnWLXqV2U2ksRCPpm9Y1pX+pKdlI2Rp2RcsrRCR3bTmyjQ1oH9hfuByDeEN/orqm+cacqGe1n/0FgUpX33wDfhHu++9ijwKPV9u1HTaj4K38foE3Tn83EpUGnu2HLU+Dy74paa3RxkHtzZOvUiDlt2qio6zfegD/9Sc3NlZSoOc3qJCSo/ddeC488okVgn2PENOgLWCKlLHSXN6BWOSp+K7WgL41KhIABr8LcYeD0TaMeEfRmaHt1dOrW0NAIG028cZbx2ZbPeOSnR1h9aLVXKonq6IQOvU7PzlM7+cuCvwQtVxE1U0FFaoZdp3bx7+X/5t/L/02T+CZc2+ta/jTsT6TGp0bkWvwigdPubWf0mvHQvbtXPl/vvkgoP6pSsJQdVM4gZQegZK9KyWIvBEcR2IvBWQopAs6EeK5K1cOCyYAE6QTpUpvLqupylqsUMMKgFJB6s9oMiWBIAGMyGFNg4GtgSvHbxJkzsHs3HDxYue3aBcePq2PFxWorLYVVIp10GXyS8LghnSuuqPxIKlwinE5VR2Gh+mm3K/FBXByYzWpLSFCijqQk+OgjaNLEfxultlJGvj6S5QeXB+2Lw+Wg4HRB8M84BBKJzWljxoczmNZpGh/P/Bidzr9V2HW9ruO6Xtepth2wdCl8/z2sXAlbtsD+/Uo08WSc+9elXOVSS0+HDh2gUydo2VK9btFCDQSTk9XnkZiolP3x8UrEUeG4UfFoLkTlBmC1Gigr+wclJf/wOHecOQMnT6r/3z17YO9e9brvY3X6iBoFQoi5QIafQ/eHW4WffaEGRkHPEUIYgHeBZysGdzVpRwhxE3ATQKtWEXQ+0tBopKTEp5BmTuNwyWEkEofLQYe0DjWvKNB9PtpoSZI1NDQ0NMKlAYsM4wxxNE9ozuHiw5j0JtYeXotEkmhKpGuLrvXdvRohhKB7encW7VtEuaOcrSe20rOwJwadAbvLTpm9jF6Zveq7mxoaGsHocg9se1YFckUSoYeuD0S4Uo36QAiYNQuuvhp++AE+/xx+/FHNmblcam5u4EAYNw5mzlTzcxrnHPUS9CWEmIMSc3yLEmp4taMFfWkAkNYXOv8OtvxTrTlFmvgW0Ptfka9XQ0OjRmjijbOA/YX7eXv927y06iX2nNmDSwYeoeiFHpPehNs6MqjAowKD3oBBb8DhcngsRKtzqvwUTy15iueXPc/0/Onc0PsGhrcejr6qQ0SkFkfCXeyIpADVWQ7Hl8LheXD0J5XWpfwwoAe9CRDgsoHeAkntVRqY5E6Q0Ea9js+AfUlu5wwz6OOVal86QTqUQKN6n0XFP24HDp3RrY6wqv44y1R+M3uhEo8U71LCkZLdYEpBSuWI8cMPMHu2EhMcPKhEFGaz+hjtdlVlbi60a6csBFu3Vq9zcqA49TAuixIRxMUpFw2nU51XISaIAxZU7bao/GkwKBcJKcFqVeKFsjKlaj9+XAkKKoQFgYQbqw6uYvBrgz22+LHks62fkfaPNNbfvJ6WKS39lpkzB557DubPVyKL0lL1GVWlbVuYPFkN+vLz1T6rVQk7zGb1GYUilGtJhSCmaVPfYy5XpatHXd1PGgtSyjGBjgkhjlTkOxZCZKI8eKqzH6j6n54DHHS/DnR+sHMAXga2Symf9tPOfre4IwXlBeTvml5210Hfvn01hb2GBsp9Y/bO2UgkHZp2QCfOzrycZw3pWjo6DQ0NjUaPn+/yvGZ5HvHGthPbABAI8pvnx7p3dWZ46+Es3b8Um9PG2sNr6ZXRC5PeRJmjjOYJzUmOS67vLmpoaATDmAw9H4c1v4/copbeAt0fgjg/Ey4ajRYhYNQotWmcezTEoC8p5XghRDzwNjAK+L4m7WhBX+cQ3f4M+z+DMxuJqFpRb4ahn4LBHLk6NTQ0aoUm3miknC4/zYcbP+TFVS+y8ehGBIJyp68lYLw+HiEE1/e6nvuG3kdWUlad2nW4HHy06SPun38/R4uPUmwv9jpudVl5b8N7fLXtKww6A1f1uIpre15Lj/QeHsFIo+L4clj9azi5UgkuHKVKbOHBDqldIfdXkDleKROdZUpsoTcrwUUwhA4IY+XeUx7QGZTLhj+c5Zw+YeVPd8Drr6tF+4qF+6pYLHD77TB9OnTpokQVoAQa8fHBu6DThSc2qI7BoJw2KujUCQYP9t+/Ct7+5W1u+uKmgMINHTqS4pLol90Pg6jd15nVaWXp/qWUO8r9ipnOlJ+h+3+68+HMDxnTzlsPcPfd8N//KsFGIP7v/2DGDDUoNFd57jHH8BlIp/P+7DX4ApiFyp88C/jcT5kVQAchRFvgACon5eUhzv8CeEcI8RQqd2UHYDmAEOIRlDDjhgB9WQJcDMzXrA81NMJnWOthzN45G4BBLQfVc28aGdpXzVmDEKIp8D7QBtiNypd8yk+5Cai0XXrgFSnlY6HOF0Lch8qz7ATulFLOEUJYgA+B9u79X0op743eFWpoaESMKH3398nqw4LdC3BJF4eKDwFQ5iijU1qnqLQXTfpn9yfBlEChtZCNRzey7cQ2TxBL30wtZYqGRqOgwy0q8OrAF3W3ldfFQ+ZY6PybyPRNQ0OjQdBAg76QUpYLIb5ApUv5Hi3oS8MfOgOM+BK+7aUc4COB3gy9noSmmsuchkZDQBNvNEIe+ekR/vrjX3G4HOiEDrPBjAASdRZ3CYmQ4EJyV+dx/KbzSNIMBtj/DjhtyiHCZQWXU4kHhAF0ekBHpXCz6v298rUBwaXAJcOv4Jsj27lv43x2lZxCeIlAJdJZTonDxbPLnuXZZc/SPiGNDZPuJ96UpEQQFe4TBos75UcSGBMhrpna3xCwnoTvBlS+d/lxHUntBhNWKOeMimhffVxs+ucPfTy/uiOeTz5RaTwC8f330LNnpQgjrh677E9YUGQt4oYvb+CrbV9R6vCvjDAbzPTN6sucK+dgNtZNCXG89DhDXhtCwekCH3cZieS09TRT3p3CTX1u4omxT2DSmwBYuFC5WQRjwgQlXDGZ6tRFjcjyGPCBEOJ6YC8wA0AIkYVazJrktiK8HZiDWuR6TUq5Mdj5UsqNQogPUPktHcBtUkqnECIHpdzfAqx2C9mek1K+ArwKvOnOc3kSJRLR0NAIk96ZvT2vB+Vo4g2Nc5Z7gXlSyseEEPe633vlZBZC6IHngbGoCcAVQogvpJSbAp0vhMhH3Ze6oESJc4UQHd1VPiml/EEIYQLmCSEmSim/jcG1amhoNEC6tehGgimBUnupRxDfJL5Jncdp9UGf/2fvvuOkKPL/j79qwuYlw5KTIEFFUcSMAVTEgDnemX/mdGeC0/ueWc4706lnxtMzYFZUEAT1FBUVxUDOGZbM5t0J9fujZndmd2cjO+wC7+fj0Y+Z6e6qru6Z6d6d+vSnOh5Q9j/hkq1L+C37NwqDhSR5kxjSbUgjt05EasUYOOQ/MPEAyJ3vst7WiwfSOsOhr2vIQ5Hdyw696csYkwFkRoI9fMAI4OsKdemmLykvvRsM/QI+O8xlZ98e3jTocwPseU3DtE1EtlvCgzequsMrZrmJLB8BFAAXW2t/rq5sXe8OS/Au7nAnetbQvUtrsAF3Yg4XuAAM46U0k1ZS93M44YCbyUzKcGmOvGkuKMJ4IRyM/OMSckEH1lJzVq/yDHBiPxhxpOXb1d+zdOvy6BITGeqjdLgP48VrPKT0Oz8a4ACUlEBurstaUDoVF1c9BQJuOIraXkKeeSamvab8Y+xza1294XD5oT5SkpszxHMaWeFJGEJ4iZP9IXcxrPwAOo5w0fy+dBf5uD3eaw9F9R/T+I9dRjDJ/xrh1Bbk5cW/ueof/4Cnn3ZBG8Y0rawMM9bMYOQbI9lcuDluNhlwgRuHdz2cj877iGTf9keetElrw/TLpzPkpSEs2LQgbqaPwmAhz//8PJMXT+bDcz+kd+veTJgAV14JEya4jCU5OZXr3mcfGDUKzjgD2rVzn+W0tMYL5giFdp+hU6pird0EDI0zfw3uWlT6egIwobblI8vuB+6vMG8V8dMcYq0tIhL8ISJ1FzvufGwgh8huZiRwVOT5y8CXVAjewI2dvMhauwTAGDMuUm5ONeVHAuOstcXA0kig4WBr7XfAFwDW2hJjzM+4u8ZEJFGysiC7/v8jltWRIP3a9MNjPIRsCK9x/2zs2XrPGko1TZ0yO5HkTaIoWERBoICf1/0MQIovhUEdlXlDZKfhTYFjJsEn+0Bga/3q8GXAMZPdjWcisjvZ0Td9pQPjjTHJkbo+B0p7NnTTl1St5b4w5CP46uT6B3B406DbObDvAw3bNhHZLgkN3qjhDq9SJ+CiDHsDBwFPAwc15N1h1tY7xLpJGhhcycCkyA83ycZlrTAmEogRcsN6DLoRWu4dLWTDLrggHJsmIDbAwgN43Cxrykc5YGDWvTD7vkptMcBhkak6C9f1osOQYRTY9oTDLitESYkLkvB63bTffjBxoltmjMvIYIxbx++PBlnYe7IwNfxwFW6XxXnnxV9WMYCjdFseT7QtxkAg4MXnew9PzixYO9mlW9z0QzRbSbjEjZ/59WnuH7q2h0K7o6DFvpC5B6R2AG86hIsix93GHHOvC/Lw+CNBNw3npP0nsPKJLkxukcvEiTB5svudLyXFHcPCQnj7bTf17QtHHw0HHeSed+0KrVu7eoqKXEBL6XEqPT6lwS21uekgHHZBN8FgNECmlM/nhg4pKnLt694jzIPTHuT+r+6nMFh1Wss0fxpDewzl3bPfxe+tx/gtVWiR0oJvLv2GY145hlnrZ1EUrBw4UhAoYP6m+ez37H48OeJJLt73Yt5/35CXB1OmwLvvwqRJsHmzC9AwBrZsgZtvdlOXLjBwoBsyZt99YY89oHNnaNvWHdOSkuixKg26Kf1sQvTzCtHl1kaHxynl8UTfJ4/HtWHtWli+HH77Df7ylwY7bCIijapdejtSfakUBYvo37Z/YzdHpLFkWWvXAkTu1moXZ51OwMqY16tw/3tVV74TML1CmU6xlRpjWgAn4wLuRSRR1q1r7BZUq2+bvhQGyv8Pd0CHAxqpNdvHGMOAdgOYtnIaaf40Fm5aCEBhoLBc0KiI7ATSOsOxX8GUo10AR21/HjYe8DWHoVMgo0dCmygiTU8j3PSVDRxYxfq66Uuq1/5oOG46fH4sFG9yN3zXljcVBtwHfW9ShimRJibRmTequ8Or1EjglUi6p+nGmBaRscC6V1O2TneH4dJK7TqO+gjuugvuvRuaW2iZ40Y7SwZSI49vDgQ/kGogMx2aN4NmzSCzmevFT02BpBTwp4AvBfypLpggNmrCeCjLpOHxQLfbXBBIOAzYaNaOcORx/Viw8TvdS4JJrNvWvty81FTXwVzaIZ2WVnUGiOJi16kdDoNdsA5razFcbxXL45WLDeIozb5RNpRIi73d1O/PbqiZvCWQv9Q95i6EnIVQuBK2/A7Z/3PBM6VBGSYZUrMgua3LyuFLA0+qO+alQ8b4W4A3CfC6MgPuiQnECUcCbwogsA2CeRAshCVjq931zNQ8zjjDZXsAF0ywaBEsWeKmOXNgxQpYswZefx2efdbts8/nAjRatID27d1HJi3NvVelU0YGZGa6KTbgxeOJvkehkHu+bVs0u0phoZtKs6xs3ux+gywshGA4xMB/HcF3q6r/qqb50zh5z5N57fTX8HoaPn1EZnIm/7v4fxz/3+OZsXZG3ACOsA1TECjg0g8vZdKiSYw7cxwZGXDqqW4Ct0+LF8P8+bBwISxY4F6vWOGCPD76yB0zv98d89Jgi4wMd7xLj3lmpnsPUlOjx7o0mCMUigbEBAIu60dOTvRY5+e7qagoGvgUCLhJwRsisivpkNmBzYWbGzSgT6SpMcZMAdrHWXRHbauIM6+mv6arLRNJ6fsG8K/S/9kqVWDMFcAVAF27dq1dS0Vkp5OZnElGUgZbirZgsaT50xiQNSCxG23fvm7ZSKr6QTorq1JwzJBuQ/hu1XeEw2HygnkAtE1vS7PkZvVtrYg0lhb7wIhfXABH4Rr3+1p1vGmQ0g6GfelS0ouIiDR1LfaGE2fB9Eth3WcQKqLaf/d96eBvCYe8DO2P2WHNFJHaS3TwRnV3eFW3Tqcaytb77jDYRX5EvOsuN22v2vzgEefHjPierHLJXoC9Lfq6pAQ2box27Ofnu8ePPqo8XEppJ3Vp53NsFgiPh3KBHBWDOqytPGRK7KMx0WCD0swFsdlALrnEdaSX8XihWW83VSVYEAmyyINAXvR5xdeBnMhjbkywRiRzivHGZEPxRrN9JLWB9EzwNYNgnDE6SqWUT4nbqhUMHuymuE0OQl5e1VNubvR5To4LvNiwoXwAQSgUDf4ofW+8Xhd4kJXlAhEyMqqavDz82+H0bdO36n0Cerfuze2H3Y4nZvidhpbmT2PKhVO4+393sy6v+s99n9Z94s5PTYW993ZTPNa6z3xpwEVODuQcfxY5y0Pk0Kxs2kZzgngJ4SWEj2BqJqELLizLWpOUFD3e7dq5z2qLFi7go6opM3M7D5CISBMzpOsQVuasrHlFkZ2YtXZYVcuMMdnGmA6R/4s6AOvjrLYK6BLzujOwJvK8qvLVlQF4DlhorX2smnY/F1mPQYMGaWxmkV1Y71a9+WHNDwD4PD76te2X2A1u7zAy1dQzuNNg0pPSyS3Oxe/xU2JLGNRBQ6aI7LTSOsOJs2H+4zDrbsADwdzy6/gy3G9ze98Jff8M3u0foldERGSHSW4NR34Im3+GmbfChmluCLFwwHVGePwuk3xKFux9B/S81N3MLSJNUqK/nbW5w6uqdRr87rCyGfoRMaqR0q8mJUHHjo2y6cTzpUXGw4yXsbqB9Lu5Qavz+Vynf4sWDVptnfyj/UONt/EKkn3JPDC0luO83XUX3H13neo3QEZkqtPXoBB44aI6bSuuv/2tYYK/RESagJdOfamxm1A/WVkN1/FUn23LrmQ8cBFubOWLgA/jrPMj0NsY0wNYjRtq8vwayo8HXjfGPIL7k6U38AOAMeY+XO6/yxOwPyKyExrYYWBZ8EZhoJB+bRIcvJFAB3Q8gJJQCRZLmDBJ3iSGdBvS2M0Ske3hTYL+t0Kvy2HNp7DibciZD4Qhc0/oehZ0PMF1fomIiOysWu0PQ6e67BsbvoHcRe5m4eQ20G4IpHZo7BaKSC0kOnijpru1qlsnqZqy9b07TESkYTVUFhwREdm9NFIAreySxgBvGWMuA1YQGRPZGNMReMFaO8JaGzTGXAdMArzAWGvt7OrKW2tnG2Pewg1bGQSutdaGjDGdccO1zAN+Ni6t3ZPW2hd20P6KSBO0X/v98ODBWktqUiotU1tWvXJdhjxphPG3O2V2IsmbRFGwCGstKf4UDuwUdyh6EdnZJLWE7ue5SUREZFflTYH2Q90kIjudRAdvVHeHV6nxwHXGmHG4YVG2RYIyNlRTts53h4mIiIiIiOxqrLWbgEq/yFhr1wAjYl5PACbUtnxk2f3A/RXmrSJ+xkMR2Y31a9OPMG4s0j1a7lH9yo2VeaqWjDEMaDeAaSunAS6TyMD2Axu5VSIiIiIiIrI7SGjwRlV3eBljroosfwb3A+IIYBFQAFxSXdlI1XW6OyyR+ygiIiIiIiIisjvr1zY6TMp+7fdrvIY0kCHdhjBt5TTCNkxWRhaZyZmN3SQRERERERHZDSQ680bcO7wiQRulzy1wbW3LRubX6e4wERERERERERFJjLZpbUnxplAUKmL/Dvs3dnO22+BOgwGwWAZ1GNTIrREREREREZHdhaexGyAiIiIiIiIiIjsvYwwdMjsAbgiVnUZWVtzZgzpGAzaO7H7kjmqNiIiIiIiI7OYUvCEiIiIiIiIiIttlj5Z7AOWHUEkoa7d/WrcubtUdMzuS6ksFygdySN0YY1oZYz4zxiyMPLasYr3hxpj5xphFxphRtSlvjBkdWX++Meb4mPmfGmN+NcbMNsY8Y4zxRuYnG2PejJT53hjTPYG7LiIiIiIiUi8K3hARERERERERke2yZ+s98RgPHTI6NHZTtpsxhm7NuwEwsP3ARm7NTm0UMNVa2xuYGnldTiS44ingBKA/cJ4xpn915SPLzwX2AoYD/y4N0gDOttbuC+wNtAXOisy/DNhire0FPAr8vYH3VUREREREZLspeENERERERERERLbL4V0PZ2D7gRhjGrspDaJf236k+lLJTM5s7KbszEYCL0eevwycGmedwcAia+0Sa20JMC5SrrryI4Fx1tpia+1SYFGkHqy1OZF1fEASYOPU9Q4w1OwqH1YREREREdllKHhDRERERERERES2y3n7nMeMK2bUvGJW1vZvrCHqqMFNB9/E3UfdnfDt7OKyrLVrASKP7eKs0wlYGfN6VWRedeWrK4MxZhKwHsjFBWqUK2OtDQLbgNb13TEREdk1NbEhvy42xmwwxvwSmS5P5L6LiEjToOANERERERERERHZMdatA2u3b1q3LuHNHNJtCLcedmvCt7OzM8ZMMcbMijONrLm0qyLOPBtnXq3LWGuPBzoAycAxddmOMeYKY8wMY8yMDRs21NAMERHZBTWlIb8A3rTW7heZXmjYXRURkaZIwRsiIiIiIiIiIiJSZ9baYdbaveNMHwLZxpgOAJHH9XGqWAV0iXndGVgTeV5V+erKlLarCBhPdAiWsjLGGB/QHNgcZ3+es9YOstYOatu2be0OgoiI7Eqa0pBfIiKyG1LwhoiIiIiIiIiIiDS08cBFkecXAR/GWedHoLcxpocxJgl3V/L4GsqPB841xiQbY3oAvYEfjDEZMcEePmAEMC9OXWcCn1tr1TkmIiIVNaUhvwDOMMb8Zox5xxgTG7goIiK7KAVviIiIiIiIiIiISEMbAxxrjFkIHBt5jTGmozFmAoC1NghcB0wC5gJvWWtnV1c+svwtYA7wKXCttTYEpAPjjTG/Ab/iOsGeidT1ItDaGLMI+DNx0uCLiMjuYSca8usjoLu1dgAwhWhGj8qVa9gvEZFdhq+xGyAiIiIiIiIiIiK7FmvtJmBonPlrcFkxSl9PACbUtnxk2f3A/RXmZQMHVrF+EXBWHZovIiK7KGvtsKqWGWOyjTEdrLVrt2fIrzjlazXklzGmdMivzyLXwVLPA3+vZp+eA54DGDRokDJLiYjsxJR5Q0RERERERERERERERHZ3TWbIr9L5EafgMlSJiMguTpk3REREREREREREREREZHc3BnjLGHMZsIJI1iZjTEfgBWvtCGtt0BhTOuSXFxhbYcivSuWttbONMaVDfgWJDPlljCkd8is5UtfnRIf8usEYc0pk/c3AxQnedxERaQIUvCEiIiIiIiIiIiIiIiK7tSY25NdoYHQdmi8iIrsADZsiIiIiIiIiIiIiIiIiIiIi0ogUvCEiIrsVY0wrY8xnxpiFkceWVaw33Bgz3xizyBgzqjbljTGjI+vPN8YcH5mXZoz5xBgzzxgz2xgzJmb9i40xG4wxv0SmyxO57yIiIiIiIiIiIiIiItI0KXhDRER2N6OAqdba3sDUyOtyjDFe4CngBKA/cJ4xpn915SPLzwX2AoYD/47UA/BPa21fYCBwmDHmhJjNvWmt3S8yvdDA+yoiIiIiIiIiIiIiIiI7AQVviIjI7mYk8HLk+cvAqXHWGQwsstYusdaWAOMi5aorPxIYZ60tttYuBRYBg621BdbaLwAidf0MdG7QPRIREREREREREREREZGdmoI3RERkd5NlrV0LEHlsF2edTsDKmNerIvOqK19dGQCMMS2Ak3EZO0qdYYz5zRjzjjGmS732SERERERERERERERERHZqvsZugIiISEMzxkwB2sdZdEdtq4gzz25PGWOMD3gD+Je1dklk9kfAG9baYmPMVbhMHsfErdyYK4ArALp27VpDU0RERERERERERERERGRnouANERHZ5Vhrh1W1zBiTbYzpYK1da4zpAKyPs9oqIDYLRmdgTeR5VeWrKwPwHLDQWvtYTDs3xSx/Hvh7Nfv0XKQOBg0aVFMgiYiIiIiIiIiIiIiIiOxENGyKiIjsbsYDF0WeXwR8GGedH4Hexpgexpgk4NxIuerKjwfONcYkG2N6AL2BHwCMMfcBzYGbYjcSCf4odQowt/67JSIiIiIiIiIiIiIiIjsrY+3uffOuMWYDsLyx21EPbYCNjd0IEdF3cQfqZq1tu72VGGNaA28BXYEVwFnW2s3GmI7AC9baEZH1RgCPAV5grLX2/urKR5bdAVwKBIGbrLUTjTGdgZXAPKA40ownrbUvGGMexAVtBIHNwNXW2nm12IfGunbp8y6JpM+XJEpjfrYa5Nq1K2jAa5fOFYmh45o4OraJoeOaOLp2RTSR3wz1WZemSJ9LaWp07YrRRK5fsXTOkF2RPteyvaq8du32wRs7K2PMDGvtoMZuh8juTt9F2Z3o8y6JpM+XJIo+W7sWvZ+JoeOaODq2iaHjKrsLfdalKdLnUkTqQucM2RXpcy2JpGFTRERERERERERERERERERERBqRgjdEREREREREREREREREREREGpGCN3ZezzV2A0QE0HdRdi/6vEsi6fMliaLP1q5F72di6Lgmjo5tYui4yu5Cn3VpivS5FJG60DlDdkX6XEvCGGttY7dBREREREREREREREREREREZLelzBsiIiIiIiIiIiIiIiIiIiIijUjBGzsZY8xwY8x8Y8wiY8yoxm6PyO7KGLPMGPO7MeYXY8yMxm6PSKLp+iOJpHOqNBRjzFhjzHpjzKyYea2MMZ8ZYxZGHls2ZhulfnQdShydgxuGzj+JU8WxvcsYszryuf3FGDOiMdsokgi69klTo78ZRKQudB2TXZGuhbIjaNiUnYgxxgssAI4FVgE/AudZa+c0asNEdkPGmGXAIGvtxsZui0ii6fojiaZzqjQUY8wQIA94xVq7d2TeQ8Bma+2YyA9GLa21tzdmO6VudB1KLJ2DG4bOP4lTxbG9C8iz1v6zMdsmkii69klTpL8ZRKS2dB2TXZWuhbIjKPPGzmUwsMhau8RaWwKMA0Y2cptERGTXp+uPiOwUrLVfAZsrzB4JvBx5/jJw6o5skzQIXYekydP5J3GqOLYiuzpd+0REZGem65iISD0peGPn0glYGfN6VWSeiOx4FphsjPnJGHNFYzdGJMF0/ZFE0zlVEinLWrsWIPLYrpHbI3Wn61Bi6RycODr/JNZ1xpjfIsOqaEga2dXo2idNkf5mEJHa0nVMdlW6FkrC+Rq7AVInJs48jXsj0jgOs9auMca0Az4zxsyL3BEmsivS9UcSTedUEamOrkOJpXOw7IyeBu7FnQvuBR4GLm3UFok0LF37pCnS3wwiUlu6jsmuStdCSThl3ti5rAK6xLzuDKxppLaI7NastWsij+uB93Gp4ER2Vbr+SELpnCoJlm2M6QAQeVzfyO2RutN1KIF0Dk4onX8SxFqbba0NWWvDwPPocyu7Hl37pMnR3wwiUge6jskuSddC2REUvLFz+RHobYzpYYxJAs4Fxjdym0R2O8aYdGNMZulz4DhgVuO2SiShdP2RhNE5VXaA8cBFkecXAR82YlukfnQdShCdgxNO558EKQ2KiTgNfW5l16NrnzQp+ptBROpI1zHZ5ehaKDuKhk3ZiVhrg8aY64BJgBcYa62d3cjNEtkdZQHvG2PAnUdft9Z+2rhNEkkcXX8kwXROlQZjjHkDOApoY4xZBfwNGAO8ZYy5DFgBnNV4LZT60HUooXQObiA6/yROFcf2KGPMfrj028uAKxurfSKJoGufNEH6m0FEak3XMdlF6VooO4SxVsNMiYiIiIiIiIiIiIiIiIiIiDQWDZsiIiIiIiIiIiIiIiIiIiIi0ogUvCEiIiIiIiIiIiIiIiIiIiLSiBS8ISIiIiIiIiIiIiIiIiIiItKIFLwhIiIiIiIiIiIiIiIiIiIi0ogUvCEiIiIiIiIiIiIiIiIiIiLSiBS8ISIiIiIiIiIiIiIiIiIiItKIFLwhIiIiIiIiIiIiIiIiIiIi0ogUvCEiIiIiIiIiIiIiIiIiIiLSiBS8ISIiIiIiIiIiIiIiIiIiItKIFLwhIiIiIiIiIiIiIiIiIiIi0ogUvCEiIiIiIiIiIiIiIiIiIiLSiBS8ISIiIiIiIiIiIiIiIiIiItKIFLwhIiIiIiIiIiIiIiIiIiIi0ogUvCEiIiIiIiIiIiIiIiIiIiLSiBS8ISIiIiIiIiIiIiIiIiIiItKIfInegDFmOPA44AVesNaOqbDcRJaPAAqAi621P1dX1hjTCngT6A4sA8621m4xxhwLjAGSgBLgVmvt59W1r02bNrZ79+4Nsq8iIpI4P/3000ZrbdvGbkdToGuXiMjOQdeuKF27RER2Drp2iYiIiIiINJ6EBm8YY7zAU8CxwCrgR2PMeGvtnJjVTgB6R6aDgKeBg2ooOwqYaq0dY4wZFXl9O7ARONlau8YYszcwCehUXRu7d+/OjBkzGm6nRUQkIYwxyxu7DU2Frl0iIjuHHXntSlDQ/D+Ak3GB8YuBS6y1W40x3YG5wPxI9dOttVdV1z5du0REdg76v0tERERERKTxJHrYlMHAImvtEmttCTAOGFlhnZHAK9aZDrQwxnSooexI4OXI85eBUwGstTOttWsi82cDKcaY5ATtm4iIiIiISKOLCXw/AegPnGeM6V9htdig+StwQfM1lf0M2NtaOwBYAIyOqW+xtXa/yFRt4IaIiIiIiIiIiIjULNHBG52AlTGvV1E5E0ZV61RXNstauxYg8tguzrbPAGZaa4srLjDGXGGMmWGMmbFhw4Y67I6IiIiIiEiTk5CgeWvtZGttMFJ+OtB5R+yMiIiIiIiIiIjI7ijRwRsmzjxby3VqUzb+Ro3ZC/g7cGW85dba56y1g6y1g9q21TCeIiK7I2PMcGPMfGPMosgQXBWXG2PMvyLLfzPG7F9TWWNMK2PMZ8aYhZHHljHLRkfWn2+MOT5m/peReb9EpngBiSIiItVJVNB8rEuBiTGvexhjZhpj/meMOaK+DRcREREREREREREn0cEbq4AuMa87A2tquU51ZbMjd4kReVxfupIxpjPwPnChtXZxA+yDiIjsYhKYXn4UMNVa2xuYGnlNZPm5wF7AcODfkXpKXRCTen49IiIidZPQoHljzB1AEHgtMmst0NVaOxD4M/C6MaZZpUYp46GIiIiIiIiIiEitJTp440egtzGmhzEmCddxNb7COuOBCyN3OB8MbIsMhVJd2fHARZHnFwEfAhhjWgCfAKOttd8kcL9ERGTnlpD08pHHlyPPXwZOjZk/zlpbbK1dCiyK1CMiItIQEhU0jzHmIuAkXKChBYhczzZFnv8ELAb2rNgoZTwUERERERERERGpvYQGb0TGR74OmATMBd6y1s42xlxljLkqstoEYAmuI+t54JrqykbKjAGONcYsBI6NvCayfi/gr0o/LyIi1UhUevmsSAAikcfSa1BN23spcs36qzEm3h3QIiIi1UlI0LwxZjhwO3CKtbagtCJjTNvSDFLGmJ64LFVLEruLIiIiIiIiIiIiuzZfojdgrZ2AC9CInfdMzHMLXFvbspH5m4ChcebfB9y3nU0WEZFdX0LTy9dxexdYa1cbYzKBd4E/Aq9UqsCYK3DDt9C1a9caNiciIrsTa23QGFMa+O4FxpYGzUeWP4P7v2oELmi+ALikurKRqp8EkoHPIrGF0621VwFDgHuMMUEgBFxlrd28Y/ZWRERERERERERk15Tw4A0REZEmaHvSyydVUzbbGNPBWrs2MsTK+pq2Z61dHXnMNca8jhtOpVLwhrX2OeA5gEGDBtUULCIiIruZBAXN96pi/XdxAYciIiIiIiIiIiLSQBI6bIqIiEgTlZD08pHHiyLPLwI+jJl/rjEm2RjTA5de/gdjjM8Y0wbAGOMHTgJmJWKHRUREREREREREREREpOlS5g0REdntJDC9/BjgLWPMZcAK4KxImdnGmLeAOUAQuNZaGzLGpAOTIoEbXmAK8Hzij4CIiIiIiIiIiIiIiIg0JQreEBGR3VKC0stvAoZWUeZ+4P4K8/KBA+radhEREREREREREREREdm1aNgUERERERERERERERERERERkUak4A0RERERERERERERERERERGRRqTgDREREREREREREREREREREZFGpOANERERERERERERERERERERkUak4A0RERERERERERERERERERGRRuRr7AaIiEgTFyyE/GUQKgA8kNQc0rqBx9vYLRMRERERERERERERERHZJSh4Q0REygvkwaoPYekrsPVXKN4E3lQwxi0Ph8CWQFoXaHsE9LzYPSqYQ0RERERERERERERERKReFLwhIiJOwWqYeRusfBc8SRDMjS6LfV4qbwnkLYOV74Hxwl6joP/tO6y5IiIiIiIiIiIiIiIiIrsKBW+IiOwCgkGYPRs2bYJwGDIyYJ99ID29FoVDJTDrHpj3CISDYAMQLq7llsPRwI7f71XwhoiIiIiIiIiIiIiIiEg9KHhDRGQnlZsLzzwDb78Nv/0GSUng8bhl1kJhIXTvDiecAH/6k3teSdEG+OJ4yJkPocLKyz1+yBoKGT3A38wFdwRyYPOPsOWX8uuG8ht2B0VERERERERERERERER2EwreEBHZyeTmwkMPwWOPuSwbBQVufnGcZBkLF8KyZfDcc3DKKfDAA7DHHpGFhdnw6QFQtN5l2yhjoN2RsMcl0Pl0sCEXxOHxu6gQGwAslGyFxWNh2auQuzCRuywiIiIiIiIiIiIiIiKyS1PwhojITmTOHBg+HDZsgKKi2pUJBNz07rvwySeQlweEA/C/EysHbqR2giM/hMw9wZsGHm+cGpPcgy8D+t8G/W6BxS/AzFu2d/dERERERGrWvj1kZ9e9XFYWrFvX8O0REREREREREWkACt4QEdlJvP02XHyxGw7F2rqXD4Ugv3Rkk59vhW1zywdutNwfhk4Fbzp4/bWr1JviHve4DNocVvdGNSJjzHDgccALvGCtHVNhuYksHwEUABdba3+urqwxphXwJtAdWAacba3dElk2GrgMCAE3WGsnReYfAPwHSAUmADdaW593WGQnZy3kL4PNP0HBKshfCYVrAAvG585LvgzwNwfjB+MBYwAPEI6cGMNgwxDMhZIcF6hmgy6DUFJLSO8CqZ2hWV9oNdBlFNpNbd3qAgLXrHH9n5s3w8aNLotTMAgpKZCW5g6xMdFhucAd6nDkkBcUuGBCrxeSk6FVK2jd2vWPduwI/fq51yIiDao+gRvbU05EREREREREZAdQ8IaIyE7ggw/gootc4EZVPB7XWeb1ug64KjNzFKyCxc9BKKay5nvBsC/Bn1m/BvrSocVe9SvbCIwxXuAp4FhgFfCjMWa8tXZOzGonAL0j00HA08BBNZQdBUy11o4xxoyKvL7dGNMfOBfYC+gITDHG7GmtDUXqvQKYjgveGA5MTOwRqFpurrshdetWN+XkQEmJ66gNhdwjgC/yF0Tp69Jwk9KOXmOiZTwe97n0eFy59HRo2RJatIh28spubtXH8NUpLiDM+IGwOye1OgCCeRAOuvWMFzxJLnCDSPCG8cQEblgXvGEDkTLWLfdlRgI95L//hT/9yX2309LA74cpU6B7d8jIcNeZYOnhNtHDVvrc2uj3PfZ56Xdbh1lERERERERERESkfhS8ISLSxM2cCRdcED9ww++HP/wBrrgC9t032pHm98OSJfDOO/DYY7BpU0yhWfe6u9BjDX7WDZOyPUqzcOwcBgOLrLVLAIwx44CRQGzwxkjglUgWjOnGmBbGmA64rBpVlR0JHBUp/zLwJXB7ZP44a20xsNQYswgYbIxZBjSz1n4XqesV4FQaKXjjm+9CHH58NoSi2Qi2bkqieUrzOtUTDAfZUril3Dyvx0ur1Fa1rqOoyAWNBIMuAMTnc1NyMiQllV93W9E2SkIlZa+NMbRObY2pYy9yXkkehYHyX7TWaa3xGE8VJZqo2WNgwRPuubWQ1AqOmYwLZDBA6XGpeHyMWyeumN56gBVvw5y/R4oZ8KbCiF9dIFd9GE8kC4aNNMNEAzaIPf6R4Iyy5hr4/W6YdU/19XvT4Zy8+MushVBR5LwYydxROpUGfxAJEikNGvH4I0EkdfiMlW0nEMkIYiP1+CNBK9vxOQsHXUCeDUI4FIm08IHH587tMe1cuaaETYXbSGsOQQMhD+zRJ4OMlFTy8tx3zhj3ffP7XdBV6VS2uTAEQkE25m8hEIBQ0O1Oh6Q00pNq9xkIh102qNLvuLUuyMvrdVk/kpPrfziCQZcRJBSK7k9p3Wlp0eAzERERERERERERkaZEP12KiDRhxcVw0kmuE6qi4493d1CnpEBmnIQZffvCn//s7rB+8EF44AGw1sKyNyAc7egmayi02Bc83sTtSNPTCVgZ83oVLrtGTet0qqFslrV2LYC1dq0xpl1MXdPj1BWIPK84vxJjzBW4DB107dq1ml2rP9t2Fty8X7l5LSL986m0IN3bgjRfJqnedLxeT1l/cNCWUBjKJT+YQ05gEwFbQjx5t1jSI/26hYXwyy8wYwb89husWOGGb9iwwWX8CAbd5zopyXW0BgIuoCM/333mW7aEdu2gY6cw3x7ek7ySXLyRz3AoHOKOI+7gb0f9rdb7vnjzYvZ5eh9sTPBCUbCI8eeO5+Q+J1dfuH37ymnYs7JcCpPasGEo2QolmyGQC4EcNwVz4abrIRh2vc5+LzRvBnfcgYtcKE2J4HF1GK/LnrP+q8hwIxHGQFrHmtudlQWTr4JZd1fZ1EXBpHKBMr7u59L7qNfrHCizZMsSioLR9ECe5J70PbcY8lfAtLNh0/cw+WC3j5l9oPUgwAsnvwWbK0Sytc6AL+6JCb6wMO8RCMWcOG0Qpg6D4o0ugGLP68Gf4YZSSWrhhmPxpYEnpXywRln5MGWBHaFCCOa7jCBtDqkcuJa/HNZPg5y5kLsA8pa696N4Q6QeT0zdNhokktQKUjtAejfI3BMG3OPaVLr9bXNhy8+w+WfIW+zqLNrgPjehYvCnu/Z7UlxbQ4WRqdh9LpJbQ0oWLboWwG0/U2L8GLxYC60fTGbYimm0Cu5NUpL7uGVmQvPmLmgjNvghFIKCUA7PBg9jEwtdAA0QMkWM6DmST/74AdbCypXuOz53rntcvtwNzVJc7IZWadHCBWikpLggEZ/PBWyVlLjzQ2GhCzwsLHTt+PxzVy4cdsGJM2e6YV9++QVWr4YtW9x5onVrF6CRmhoN9rLWLSsudvXl5bm2lA7zMnGiO6eIiIiIiIiIiIiINCYFb4iINGGPPOI6siu66y649VbXQVWd0uWjRsFRR8FtVy2I3rVeqk+kE3P3Eq+nuWLKgarWqU3Z2m6v1nVZa58DngMYNGhQTdurl8N77UvBXwqYv2k+czbM4Y6pd7Bs2zIACtlKYWgrhKqtopzrD7yek/qcRP+2/emU2YlAAJ55Bp5/HmbNcp22xsD++8Phh7upSxdo29Z11pZmkrE22nkcDLrvxPr1sGgRfPWVh4EHXsMj0x+hIBDtrP/7N3/nykFX0j6jfa3aeuOnN1ISKiEUk5Wma/OuHNPjmJoLVwzcqGperDUT4dPLoGgtNAPCXjjyHcjoAek9Iak5+FLh/XMjWRpKv7ex399IAIDxwIfdoCiyzZQsOL8WH5GKbczOhgF3uSmOvJI8+j2YiQdIjnxyA6ve5ja7B3cfeSflM3eUPo+sOOtemH0/AC9sg+s2QGkClQBQZGHZ/oPpdvL3cHxsnFMFm1+uPG9THuzz1/Lz9r03+vyHq2DRs5A91b1O7Qh9ro1ff+lQK0Q+eDHtjqvtkXDsl7BxOix5CVa+74JujM+9b60PhLaHQ2YvyOwNaV1csIjxumNjQy4QpGCVGzZm629uAlj6Xzj8LZj9IGyYFs2a0rwvtD0CevwRWgxwwR6eJFeXDcVkJvFGp/faQ+5CyF3IJWH4pnkKHxR4ot8ZTxHf9jmCby/7ln5t+1W9v7jPweFjh7B14wJCoRIwkOpLZY9We3PfoU/ywAPwr3+5YVn8fjccyyWXwO23Q48ebmiVgoLokEtQPoGJjfnoJie7oI7sbBfYNXo0vP56JGmJBwYMcNmnDj0UunVz17zCwsp12wpfB4/HrZuXB8uW7TqBG8aY4cDjgBd4wVo7psJyE1k+AigALrbW/lxdWWPMP4CTgRJgMXCJtXZrZNlo4DLcleEGa+2kRO+jiIiIiIiIiIjIrkzBGyIiTVR2Ntx3X+WsG//3f3DzzTUHbsTKyHAd4+OemgHbKsQLtD1s+xu781kFdIl53RlYU8t1kqopm22M6RDJutEBWF9DXasiz6trxw6V6k9lv/b7sV/7/Th/n/PL5peESli4aSFzNszh+CMuptmW8h/M4jYt2bp0Lu3S28XNwvDDD9EsMvn5LhDj8svhb39zHatpaa6jtyY+n0sY0b6967gdMQL8SXcxafEkZq6bSTAy1EbIhrjts9t45bRXaqxz+qrpfLHsi3KBG6m+VD4+7+NaDwFRV6vXfsN3gbWum7QoBYyPPZK6MbD1vm6FcEnMUB6xx9PAnAdhjuuTXRmA74vK190rsI39EtDmjKQMnh/5Etd8cg25wUj2CxviH989wjE9j+XI7kdWXXjf+2Df+5i9fjY3vjCYYltAcWRRmj+N+474C92OuCMBrQYGPwP7P+oyVJRshuJNsGo8BAvBlkSGSAnCwX+GjTnRcm2awfRH4eCXXHYJAy7gIujKePzQdgj871RY95nLcoF1QRoHPA5ZR7usF94U8NYwBkjmHi7bSqzi9fDliRDKd6/bD4MDn4WUttGhVmIZD1DFl6h4fdnTVA+81q6IF/o+z40Tb6Qg6L7LW4u3csBzB3DNgdfQNq1t3GpKQiU8+9OzrMtbV/Z9SfWlcsGAC3hqxFN0ap9EXp7LkgMuaONf/3Lf8dihSpo1q/5wVJSfDwMHuqwcocjX9L33XAaqlJTyQ7rU5jxSqkUL2G+/urWlqTLGeIGngGNx15YfjTHjrbWxw4GdAPSOTAcBTwMH1VD2M2C0tTZojPk7MBq43RjTHzgX2AvoCEwxxuxpbcVx2URERERERERERKS2Eh68kaA7wFoBbwLdgWXA2dbaLcaY1sA7wIHAf6y11yV6/0REEuWRR1yWgVjHHQe33UbZ0BN1kZIC3TrlwtYK/Sr+FvVu407sR6C3MaYHsBrXAXV+hXXGA9cZY8bhOrm2RYIyNlRTdjxwETAm8vhhzPzXjTGP4Dq5egM/WGtDxphcY8zBwPfAhcATCdnj7ZTkTWKvdnuxV7u9YMvZlZYnb9xCVkZWleXPO8/dOV/q/PPh/vvd53J7uPJePjj3A/o91Y+cYtcBXhIq4Z057zDq8FH0b9u/yvLWWq76+KpyWTvS/ek8dOxD7JO1z/Y1rhrP5Xi5L9tDhj8tkikhRPDFg1l44l/omJwaCd4occMZeZJxkQNh9+hvDvs+SNiGOObTR1lblIs3Et9RGApyYMd9+SZB7b54v4uxWK795FoKIwEchcFCTn/zdOZdN4+26fE7/QHyS/I58fUTyx3rNH8aow8fzR2JCtwo5UsFXydIizsqkbPx8gqvc2CPS6tePxyAj/tD/jIX0AHQ9Vw4+EX3nnm8lQMsYr3XPpotpSqlgRsAR01wQRs1qU29wOX7X84+7fbh0LGHEo5k6ygMFvLwdw/jwRM3L1C4YuYm4M4hd/KXI/4CuCwbc+dGly1f7gI5QqG6B2zE8npdgIbHEw3eKChwWTXC4fLBG7uxwcAia+0SgMi1ayQQG7wxEnjFWmuB6caYFpFAw+5VlbXWTo4pPx04M6aucdbaYmCpMWZRpA3fJWoHRUREREREREREdnUJDd5I4B1go4Cp1toxxphRkde3A0XAX4G9I5OIyE7JWnjpJXeXcSm/H8aOrV/gRqnkVD+VeuRsgFpdDmrVIeiB85v+TbeRO4ivAybhAgTHWmtnG2Ouiix/BpiACyxchAsuvKS6spGqxwBvGWMuA1YAZ0XKzDbGvIXrRAsC18bcnXw18B8gFZgYmXY5Bx8Ma9e6IQ0Afv0Viotdx2tdsshUpWNmR14//XXOfPtMioLutv+iYBGnvHEKVw+6uspyv6//nbkbor3NXuPlyO5HVlumIdx62K28OPNFVueuLpvn9/gZtWxxrbKFALz66yusLSkiPxQ9UaT50njulBcbvL2xLtnvEsLhMFd9fBXBSNDClqIt9Hy8J33a9Kmy3JItS9hatLXstc/j4/bDbufOIXcmtL0JU7ASClZEAzcAel0Gvgb4QJfyJLlAHoCFz8Ael7kAjtoEcVRfMQAHdT6IpTcuZdBzg9hYsBEbM2pTm7Q2+Iy7Nlgsmwo2UWKjnzW/x897Z7/HSX1OKpv3/ffwxRfw8MMwbRpMnQo9e7rAw4MOgn33dQEeWZE4r1DIXe9KhzkxJhqk4fW6YU1WrYKFC91QS0895a6N+flwzTXw6KNw9tlwxBFuSJY2bVywSMXAx1jGuCwgSUmwcSMsXuwyU+0COgErY16vwv1vVdM6nWpZFuBSXAB9aV2xYxyV1lWOMeYK4AqArl271rQPIiIiIiIiIiIiu7VEZ95IyB1gkcejIuVfBr4EbrfW5gPTjDG9ErxfIiIJ9e230U7uUldcAc2bb2fFGb3A43Oj05faNhda7V9z2Vrcye0yA+wcrLUTcAEasfOeiXlugWtrWzYyfxMwtIoy9wP3x5k/g90g4PCll2D//eHee11n7axZ0LUr3HILnHOO63gtHSLI74fUVNfJWlEo5L4bwaDr4E1OdhPAiXueyD7t9uHHNT8CrsN58ZbFjJoyKu5QLgCBcKDca2str572apXrN5SMpAw+Ou8jDht7WFkGi0A4wDtz3mH04aPp17ZfteWLgkXcMvkW8gPRzAzp/nQeGvYQew0Y6sZdqo+a9jsrC9at47L9L+PrFV/z8q8vA+5Y5wXy+GntT7Xe1BFdj+D/jvy/+rWzKUjvDq0OgC0z3RA3ALPuc/O8qdVn3QA4fV31ywvXwqwHYPELLojj55thwRPQ8zLoeDxk9gLji2zbRN47D5yyBLCRjC7WfeHABZWUbIYtv0KH48o207V5V7Jvyeahbx/i7i/vpjBYiDEGj/Hw/f/7nnbp7Rj+6nC+W/UdhF22lOP2OI7/nvZfMpIyyjXZ44GhQ91krQvYmjcP5s93QRg//wzr18PLk9vTOhD9jG70ZXHcPusIhaKZNVJSIDMT2rWDtu0DXL6gA7nNcuBGsEDIeujs/zuzZ9/IpEmwaRPk5LhhwpKSXFtSU1094bALFlvT4m2W7nsxYU/AVWLAY71k77+SNmltqn8/mr54X15by3VqLGuMuQMXfPhaHbaHtfY54DmAQYMGVVouIiIiIiIiIiIiUYkO3kjUHWBZ1tq1AJEU9u0astEiIo3t3XejHdmlbrzRdUptl9aDIVghKmT5OGjWB3zbkdJDpAbzt/xOy2N+ZMzhsGAB/P47LJ8+kPvvH8iDD7ohFfr1c7EBrVpBhw7QqZML5PD5XBaaoiL4ftUPLM6dRV4ebN0K69bBjPcPKQt2+Pyiz2n9UGtKYrJRBG0wTpdifM+e/CwtU1tGZ7Rvn7BAiIFZWdz73r387cu/lQVhFIeKuX7i9Uy5cEq1ZR///vFygRtJ3iSO6HoEVx94Nbfvcy1TRpZf/5KZcN2PtW96sRcuPA0WtSo//6HPssuik/5z6n8Ih8P89/f/llvHYCoFv1QcbuPIrkfy+UWf175BTZHxwDFT4Pe7XVAFwPr/wfg9YK87oNu5kNwaQsUuU0ZNGTlCxS4Qw+NzQ7KkdoADn4D9/wmbfnR1b5hGeN4TbJz2JKs2tWdV3n6sKtifZRs6syW3GcXBJAKhJIwJk+wrIclXTOc2m+jSchGdU3+gc7P5dG63mYwLyweOGGO4/bDbObTzoYwcN5K8kjw25G/goOcPonfr3vyw+geKgkWk+lIZM3QM1w2+rsYAJ2OgY0c3HXNMxYXlv1Ntgtn8/HPVdVnrY7+ZY7h+4vUUB4vLMoR8Zv/CXVeW8PKht1Y+nKHoZAy8Pe8NrvzkMsIx18BkbzJ/PfJOWqW2qlR+J7QK6BLzujOwppbrJFVX1hhzEXASMDQS2Fjb7YmIiIiIiIiIiEgdJDp4I6F3gNWX0veKSFM3fXo0jTxA376uA2y7+VKh1UDY9EN03oKnYK/RQA3BGylZtcy+IVLZcz89x5M/PkmqLxWP8WBbWMxww09vz6BZSV+ys10gxrp17m79Vatg0SLX8RoMuiCObWm/MLHD0ZiWYFoZ6BqmZJ9CXvn1Lzw4zCU1yUjKYOIFExn2yrByQ0BkJmWS4otmQgjbMJsLN5db54ReJ3D5/peXb3hVgRsdgSygLdAh8rotkIIbTMeD+6sljMt0kwNkA6sjjxuBldn8+ZA/8+H8D5m2YhoWS9iG+WLZFxzx0hG0Tm0dd9OBUIBJiycRstEUOmn+NF474zWMMbQzGfzSPo+wJ1pmblvokAdnzI1TYQUWOP8MmNAbiiKjcxgLmcXQukIn9yunv8JhXQ/jz5P/TEHARZy1Sm3F/Ovm0zqtNYWBQvZ+em+WblmKxZLmT+PmQ27mnqPvqbkhOwNfGgz8O/S5Hla8C8teha2/we/3wO93gb+FO+emdXGZOprtCcltXCYNjBsSJZALuQshb7EbimXr71CwCs5xwTkhkvluweF8/PHhTJoEs2e7IUWSkizNmoVp2xbatPHSuTM0T3fBTtZCIOCyUcxdYNm4IcyGDYbiEkNhoWHV8dGhS2Id0e0I5lw7h1PeOIXZG2azNm8t2fnZeIyHtmlt+fj8jxncafAOPMCOMYbL97+cw7ocxklvnMTqnNUUh4opCBRwx9Q7+HzJ5xzTo2KESNRPa37i3XnvEgy78VT8Hj8tU1vy4bkfcnDng3fUbiTaj0BvY0wP3JnmXOD8CuuMB66LZDQ8CNgWCYTfUFVZY8xw3PCUR1prCyrU9box5hHcGbA3EPPHhYiIiIiIiIiIiNRVooM3EnUHWLYxpkPkx8YOwPq6NErpe0WkqZs3r/zrQw6JZr7fbgPug69Pg2Dkrv1QAcy8HfZ/BPzVpPaIl+L/9cQOLSG7jkeOf4TVuauZtHhSWcYIg2HE68cz65pZdOmSWW35zYWb6f/UcIL5kb5D6wIWzun3R+47pnwgwDE9juG101/j8o8uLwsoSPGlsOJPK8oCOG6ZfAtP/fgURcEi/B4/gzsN5uPzP6684awsF8DhB/YFjgD644IzwoDPQItOrmM+o4d79LcAb7IbtiJUCEXrIG8ZrP4IbDBad3JbjDG8cMoL9HmyT9nssA0zbcW02h3YiPuPub8se8DNk3PpMvstLvnwkrL9L/TDhX9Io+tFX3JgpwOrrevOqXfw6fePURQp6/f4ycrI4quLv6LHgz0qrX/loCsJE+aWybdQECggtySXs98+mykXTuHKj69kTe6assCNmw66adcJ3IiV1hn63uimUAls+RlyFkDBCjjyfthcVH795sAzKWC84PGCLwNSO0JGT+h6NqR3I1hczL+fTeavf3Xn/4ICN0TQuefCWWfBYYcZMjK8FBW5YD+fz02lCTHCYRfAEQ4bfD4vKSmwfDlMnBg/cKNU+4z2fHvZt9z52S188NPjdPeHGNSuD7cf8icySxbC8qUuk4g3FdK7QXoPFxi4A/Rr249ZV8/i8LGH8/M6l6ojEA7w6eJPmbR4UtxsINbackFaAFkZWfx+9e+0SGmxI5q9Q1hrg8aY64BJuBCysdba2caYqyLLn8EN9zUCWAQUAJdUVzZS9ZNAMvBZ5PhOt9ZeFan7LdyQlkHgWmtt7KBsIiIiIiIiIiIiUkfGNlhvYJzKjfEBC4ChuLu4fgTOj/kxEGPMicB1uB8SDwL+Za0dXF1ZY8w/gE3W2jHGmFFAK2vtbTF1XgwMstZeV1MbBw0aZGfMmNEwOywi0gByc6F1a9fpVuqJJ+Caa8DjqbpcrVkLE/eFrbNxvc8R+z8Cva6o2/Ap8YI3zk/MdcUY85O1dlBCKt/JNPq1q6rhEmr4myIUDnHJh5fwzpx3KIwMXZDkSeKQLofw4ikvVjkMQygc4vz3zufXdb8SCLsvRpo/jYv2vYinRjxVZbk/vPcH3pv7HoXBQtL8adw55E5GHz6aldtW0ufJPmVtaJHSgnnXziMrI06PtrWw6FmYeQvggWAuGB90PgV6XAxZR7nhM8IB1xHvS3OP5XYgMhzGOy0q1x/5vjz0zUPcPuX2ao9fVQ7pfAjfXvZtpfnTVkzj+P8eT0EwerO8x3jo07oPSd6kuHVtKdzCypyVZZ3dHjwMyBrA1Ium1ji0xL9//De3Tr6VgmABaf40TtnzFMYvGE9BwL2+8aAbeWDoA1VXsD1D1NQkK8uldalOvM9RQ/ydXI/vS2EhDB4MS5dCfiTObuhQeO01SE/fviG0QiGXuaOc/JWw9lNY+xnkzoP8VRDMIWD8hKwl2ZuMwVKWHM8Y92jDLgDQl+ECWI79GpJaVt5oRQ1wrG+dfCsPf/dw2WfVYGiR0sJlrIlUv61oGxsLNpZb56z+Z/HGGW/gaZALas107Ypq9GuX7FpqGLqpWgn8DURkV6Brl4iIiIiISONJaPAGgDFmBPAY0bu47o+9A8y4HpcngeFE7gCz1s6oqmxkfmvgLaArsAI4y1q7ObJsGdAMl7ljK3CctXZOVe3Tj4gisiO8/tvrBMNBLtzvwhrXXbUK+vRxd1mXmjwZjj22ARuUswA+PQCCeeXn73kj7PcAeFNch3RNFLzRKBr92lXP4A23iuXcd87lrTlvlZuf5E2qMqCgOFhcFrRR6soDruTpE5+uMnADIL8kn/7/7s/KbS4YId2fzvKblnPVJ1fxwbwPCIaDpPpSGX/eeIb1HBansWH4cgSsnwahSA96eg846iNI6wr+6rOFVFLD92XI2CF8s/IbwpGgKr/HzwEdDii3jws2LWBT4aay161SWrH65tXlhoSJNXnRZE54/QTCNhx3eU3apbdj0fWLyEyu3b4++cOT3D7l9rKMH+ACba4ffD0PDn2w2verpo44C8yjL19wNLPZi9/Zh9V0IogPD2Gas5V+zGVffuVAZnAEX5NEzOemps9nEwreeOEFuPHG8teB/HxIS9v+5pQJ5MLiF2Hhv13whvG6z3lyG2g/DJrvDS32gszekNLBZZMxHve9CJe4YbRyF8E350WvJSlZ8bM0VdRAx3rZ1mWMHDeSRZsXlQUJXXPgNTw07CGe+OEJRk0ZRWGwkBRfCu3S2/HxeR+zT9Y+dd7O9tC1K6rRr12ya1HwhkjC6NolIiIiIiLSeBIevNHU6UdEEUm0BZsW0P+p/lgsv1/9O/3b9q92/WXLYO+9o3dbA3z5JRx5ZAM3bPXHMO1sN6xDrBb7wj5/gw7DwQbA36xy2XDQ3W39dvPKyxS8kXCNfu3ajuANgHA4zKFjD+X71d/Xa/NDewxlyoVTarXu79m/c9ALB1EYLCTZm8wpfU7h4wUfl2XjuGbQNfzjuH/EL7ziHfju4mjgBriO6aQ2bqiL6rzX3nVu1yTm+1ISKmHgswOZt3EeYRsm3Z/OmGFjuG6wSyT267pfOeTFQ8oyhmQkZTD7mtl0bd612k3Myp7FIWMPIb8kH4vFYEjzp9G7dW9MJEVBcai4bLvgMhTs32F/pl8+HZ+nbqPsPfH9E9w+5fayTvMbBt/AmGFjqg/cgCozb6ygC//gVt7ibPLIwAKFVJ0hyEeANAooIYkj+R+38RBHZ4/DtGtX/fabUPDGtGlw/PHlgzd++AH693eZN7bbhm/g6zMgkBO9BnQ6Cfa5C5rv5YIzvBm1S/cUG5R0DbCtAdoXTxXZUwKhAKOnjubpGU+XBXAc0OEAZqyZUfY9P7XPqTx38nOkJzXEwasbXbuiGv3aJbsWBW+IJIyuXSIiIiIiIo1HwRv6EVFEEqg4WMyApwewYPMCAHq27Mnsa2ZXeZc8wJo10KuXS5tfasIEOOGEBDRw+Zsw/VIXiFGRN8115u1xKWT0cmnxbdDdYb3+a1j6H9cBWJGCNxIuodeuHTh0xdlvn80H8z4oy6qR7E3m2sHX0iK5BQCbCjfx9I9PUxIuAcDn8fHHAX9k7Mixddrs0z8+za2f3Up+IL8sWMFjPOzdbm9mXDGj6uCExS/BjOvKfz/OygV/LcasqFXwhgfOD5Xf5ObF7PvMvuQHXMBI8+TmrPzTSjKTMznipSP4ZsU3WCxp/jRePvVlzux/Zs1twWUhGTluJN+t+q6sg/vs/mczduRYthRtYcDTA1iTuwaLJdWXyoPDHuTGg26sVd3x/Ov7f3HjpzdyQdaDdF52O199ZfB4YNgwuOAC6N275jpWr4abb4YPP3RDfQQCNZeJJz0d8vJqXq8pBW8AvPwy3HADFBe7yeeD0aPh1ltd0aQkSKn6UhJXbi4kbfuW5G+OjflcGxj0BPS8uOZhs2r6XF9QTdlkoCPQCZc7ryfQFvBFJgOEIlM+sBJYghs8cTWwCQhXfcw+W/wZZ799NnmBPILhYFmQ0nMnP8f5+5xf/X4lkK5dUfq/SxqUgjdEEkbXLhERERERkcaj4A39iCgiCXTdhOsYO3Ns2Z3yqb5ULhhwAc+f/HyVZQoLoVkzCAaj8x580HXYeWu42b9eNv4AX42M3IEdJ4ijrhS8kXAJvXbVtTPEAK2BdKAE18FaUs36Ff7u+Nf3/2L01NEUBArwGi97tt6Tn6/8mWA4yICnB7Bs67KygIInRjzBZQMvq1v7cEO1nPTGSUxdMpWSUAkWW7usFaFimDAAClZGsxO0GwJHvOc6ub117DmvpVd/e5WrPr6K/EA+qb5Ubjr4Job2GMop406hIFBAii+Fs/c6m5dPfblO9YbCIa74+ArGzRpXFsBxxxF38P7c9/k1+1cC4QBp/jReO/01Tu176nbtQ34+3HRzCa+94icQMGXnM7/fBSH86U/wf/8Hycnxy7/5Jlx+ORQVlT8Xgitz5JFw4onQuTNkZrr1Nm92WYomTqwcf1SrP3ebWPAGwJYt8Nhj8MYbsHy5C9bIz4dBg+CII9xj9+7QqRO0aeMCOkqTZYRCLmhl/XpYuRIWLYJvvoHLex7LEb1jMte0ORSOmeQC9GoSb+ifWBUzb7QCDgOOwgVqFOPOGcmABzdUS0oWeJJdNptQCQS2uQkgiDufeIFz10Jq+2o3vy5vHWe8dQbfrvyWPq378Mn5n7BHqz1q3q8E0rUrSv93SYNS8IZIwujaJSIiIiIi0ngUvKEfEUUkQSYsmMBZ75zlOlu9KVgsxaFi0vxpvHHGG5zS55Qqy3boUD47/LnnwrPPuqCOhAgVw/zH4Pd7I6/zq129SilZbliJBNCPiFFNIvNGMjAEOBnIwN0tb3Adsl8BE4D1FcpkZ0OcoSvGzhzLdROuozBYSKovldP6nkZuSS6fLf6MolARqb5Uxo4cy7l7n1vv3dpatJU+T/Zhff56PMbD22e9zen9Tq+5YLAQZt4KS150nT3hYkhuDb2vhZ4XQWpHCBWBx1991oLSoYasdUEfG7+DrKOqXP3st8/mo/kfURQqIsWbQsdmHVmyZQkA3Zp3Y861c0jzp9XxKLhAljHTxnDf1/dRECjAZ3x4PV5KQiU0S27GpD9M4qDOB9W53lhbtsB++7mggaKi+OukpUGPHm4okLQKuzFmDNx7b/khQwBGjoTrr4dDD4WSEsjIqBzQlpvrAkSWL4dXX4VHH3XBDjtb8MaCTQsY/upwQjaamSXD14Jb209i9vftmTfP7eO6dS5opTQoxhgXvBF2o98QaDuDopPOA28JXg94ffBylxzOaZWPsZFUJpl7wgkzwVeLz1ONGWUi2WS2zoZfR8Paz9zscOSD0GIf6HwatDkYmvd3359wAMr204AnyQVLje8JJZujVdfm+hLv/FXFcCs7iq5dUfq/S6qUyKxf8ezmv4GI1ETXLhERERERkcaj4A39iCgiCbA2dy39nurHtmJ39/DgToNJ8iaVDXnQLKkZc66dQ6dmneKWHzYMpk6Nvu7QAZYsqXuK/Dor2QIr3oaFz2C3zSHsScJrA65zuoyJdFJ7IFwCHY+HPS6HDsOhquEnGoB+RIxq9GvXqo/h23PBEj/Qx/jdHfU9L4JBT7k76mvw5qw3ueTDSygMFuL3+PEYjwt28qUx7sxxnNzn5O1u9vRV0znkxUM4ve/pvHvOu3UrnLsYlr0GS19xmTg8KS4YI7kVtNgX0rtDZm9o3g/8zVwwhw27junC1bBtLuQtgfylsPlnMB44p7DqzRXn0vd9y/muAADttElEQVTJvqzJW4PP48NgCIQDpPpSmX75dAZkDdiuY/HG729w2fjLKAq673bHzI787+L/bXeWgmDQZcWYMcMFWFQnJQWOPx7efz8a3/Dss/DnP5cP3MjKgnHjXJaJjFokhyhVUOACN847D6ZMqXn9phS8sTZ3LT0f70lRzLk32ZvMTQffxJhhY8qtGw7Dxo0ucCUQcJPH4wI6Lv5iKN+t+7zc+ge06MiPXUKYkq0uGAmgw3Fw2FsucMKXWq/dLLPqI/jm3Ei2msg+djkD9n0A0jq5bXj8NdcTL8tHTZmdtiPLSaLo2hXV6Ncuabq2J4tGfezmv4GI1ETXLhERERERkcaj4A39iCgiDSxswxw+9nB+XP0jQRsk1ZfK15d8jd/r5+AXDqYwWIjP42Ng+4F8d9l3eON0bN91FzzwgOuEKzV9Ohy0fTfE18n/TbyGr35/mvsPOJ/DmrWAQJ7rcE5pA833cXdNN99r+zv6akk/IkY16rVr0fPw043RYUSq401z2SWOeLdWQ4x8vOBjznnnHAoCruc+zZ/Gh+d8yLA9hm1no6nXHfmz18/moBcOwhL9WynNn8a3F3xM79BqyFkIOfMgdwHkL4OiDS6DgPG4CcCGmJAb4pxsCFvjOqiMhwxfKov/vIaMpKqjEX5a8xNHvHQEhcFCvMZLsi+ZB4c+yA0H3bA9R6LMV8u/Ytgrw+iUsic3pH3Hu29ksnUrHHIIXHcd7Ltv3eu89lr4z38qZ82oSloajBoFf/0rLFjgMnYUxny09t4bvvjCZR1KSqp7e8C1Ja1ngu7qrk1Wh3oGFPzjm39w9//uJj8QDZDKSMog+5bsWmVdWbBpAfs+s29ZgA64z+8H53zAsV0Pgu//H6z+yH1mwyWQ0g56XAQ9L4GMnpHvuMdl5IgXmBcORbLJhNz3u2AVbJsTE7gRMeBe6Pun6jPTxKPgjV2O/u+SKil4Q6RJ0bVLRERERESk8Sh4Qz8iikgDu//r+3ng6wfckAQeHyf1Pon3z30fgHPeOYf3575PIBwgzZ/GrYfeyl1H3VWpjnnzYP/9y3dinnYavPwyZGYmfh8mLpzIqeNOpSRcQpovjWmXTmNgh4GJ33A19CNiVKNdu2bdB7MfdB22teVNdYE+w/5Xq87bqUumctx/j8Pj8fDlRV9yWNfDtqPBMerRqZtXkkffJ/uyOnd12Tyv8TK813A+Pv/j+HWFA2AD7tF4CFpDz6f6szJnVdlqPo+Pw7ocxhcXfYGpocPq79/8nVFTRgEwrMcwJv9xco1l6mL+wgDDj/Oxfr0pC7jweiE5Ge680wVW1HZzb7wBl19e+8CNUqmpMH483H8/fPVVdMiPpCQX0NGtW93qiyuRHYM1/S1dz4CCQChA7yd6s3zb8rJ56f50/nncP7lq0FU1NuvSDy/lv7/+l6ANAu5zN6znMCZeMDG6Us5CWPISLH8DCtdGhyzxZUCzPpDRAzL2gGZ9I0EcSS7QI1QIOQsgb7HLKJO7AEq2QmonKFgRrb/7H2DwM7UL3KhxSBYUvLGT0/9dUiUFb4g0Kbp2iYiIiIiINB4Fb+hHRBFpQNNWTOPYV44tS3Wf7E1m2iXT6NbC9T6uzlnNIS8eUrY8xZvChAsmcHSPoyvV1bs3LFpUft6MGTBwoEuJnyjLty5nwNMDyCnJKZvXPqM9c6+dS4uUFonbcA0a6kdEY0wr4E2gO7AMONtauyXOesOBxwEv8IK1dkxN5Y0xo4HLgBBwg7V2UmT+AcB/gFRgAnCjtdYaYy4G/gGURgc8aa19oaZ9aJRrV/YX8OVJdQvcKOVJge7nwcFja163YoaM2mQ2qI16durGZr8oleZP44uLvmBwp8E1bvbZGc9y8+Sby2VPaJHSgvnXzaddersay4dtmL3+vRfLti5j/BHr+ODN5ixYAD16wIUXwmGH1b/P67vvYPhwyMuLBkzESkuDk0+G11+v+ZxTUgKdO8OGDfVrS7du7m0vihmh6e674eabIb2OCRviqsVBCuBjLv2YTx/m0Yds2lOCn2RK6MYy+jKfPsynF4soV1uCgjcAPl/6OSe/cXJZNhqATpmdWPGnFXhM1W/KpoJNdH60c/msG7405l43l67Nu8YvVLAaNn7rhgjaNsdllclfDiWbXFtLM8rYsJsAkltDWhcX3NGsP/x+Z/k6D3gc+tQyU0yNwRseOD9UfR0K3mjS9H+XVEnBGyJNiq5dIiIiIiIijUfBG/oRUUQayKqcVXR7rBthG+0F9Rovfq+/3HqBUICQjXZAefCw5MYlZQEepR57DO64o/xd7HvtBd9/X//OzLw8yKh6lAaKg8Xs/9z+zNs4j7AN4/f4CYQDJHuTObzr4Uz+4+RqOwwTqQGDNx4CNltrxxhjRgEtrbW3V1jHCywAjgVWAT8C51lr51RV3hjTH3gDGAx0BKYAe1prQ8aYH4Abgem44I1/WWsnRoI3Bllrr6vLPuzwa1fJNvioFxRvrH8d3lQ4pxaBH/E6cBrib5Xt6NR9cNqD3P/V/WUBGAbDAR0P4IfLf6g2C0Z+ST6dH+3M1qKtZfPSfGm8d857HN/r+Fo3PSe/hKuv9PLB+16KilyghcfjMlYMGwavvVb3c0JurgsA2bSp+vXS0mDMGLj++urXe/ppuPVWyM+vfr2qJCWB31++/MaN0Lp1/eqrJN6wOUAQL+M5hf/yByZzPF7cubmANEJEhwpJopgUCgniJ5VCzuBd/sCrHJ79LqZdDUE42xlQcPLrJzNx0cSy60aaP42nT3yaY3seW2WZR757hCd/eLIsUDDVl8pth90WN9NTlSoFUrWDFfPB+MDjd1PF68Ene8O22dHXHU+Ew9+s+5Ap9aXgjSZN/3dJlXZk8EZ9gkKruIYkZFsiTYCuXSIiIiIiIo1HwRv6EVFEGkA4HKbzo51Zm7e2XuXbpbVj7c1r8cTc3l5Q4O5G31ihv/zUU+HVV+veWZuX5zp5r7yy6nUu/fBSxs0aR2GwkFRfKmOGjeEvU/9CfiCfNH8aow8fzZ1D7qy6ggRqwOCN+cBR1tq1xpgOwJfW2j4V1jkEuMtae3zk9WgAa+2DVZWPXSdSZhJwFy47xxfW2r6R+edFyl+50wRvfH0mrP4YwsXbV09KFpxeQydGEwzeCNswR7x0BN+v+r6sAz3Fm8IDQx+odliXF35+gVd+fYXiUHFZmcv3v5wnRjxR62avXw9HHQXLlpUfRqlUSorrU/rqK+jSpdbVctVVbhim2EwXVUlPh/nzoVOn+MuLi92ymgJB6qJLFzd8VFpaw9UZKxiE//4X/vIXFzCSm1u38qXBM3l5tVh5OwMKVuWsouujXbFE1zcYUnwpVZaJzRQDLgvUtlHbSPYl12qbbiP1+C5u+A4+PxZCMVE4PS+GQU+CJzWxaaNAwRtNnP7vkirVN3gj3nc7tq6G+u5vT3DJbv57i+ycdO0SERERERFpPI1z+7SIyC7mnv/dUylwI8WbQvPk5nGnip1u6wvWc8fnd5Sbl5YGTzxROUjjgw/gnHNcZ2MwWLv25efD44/D1VdXvc4rv7zCm7PfpDBYSJI3iTP7n8n1g69nYIeBeIyHgkABD3z9AF8s/aJ2G226sqy1awEij/Fum+8ErIx5vSoyr7ryVZXpFHkery6AM4wxvxlj3jHGVNn9boy5whgzwxgzY0N9x6aoj3VTYM3E7Q/cgBqGRGi6PMbDO2e9Q2zAa1GoiJsn38xx/z0u7nTsK8fy/M/PlwVuAPi9fh4+/uFab9daOO88WLgwfuAGuOCLFSvgjDPiD30Szw8/wCuv1C5wA1xwxiWXVL382WdrX1dtJSdDqIYRMuprwQLYZx+XTWTduviBGz16wH77wSGHwIAB0KFD+eXhcCRLSPv2rlOvuqkqNZVr3x6Azs06c0yPY8oVtVgKg4VVThWNOnxU3QI36qvtIXDsV+BvCZ7I9pb8B6YcBes+hVARBHJq/2ENFUMgFwp3znOHJE44HGbszLHs7jciiIiIiIiIiIjIrsVX8yoiIlKdBZsW8NC3D5Wbl5mUybgzxlXZWVYSKuG8d89jW/G2snmPf/84F+57If3a9iubd8458PDD8OuvEAhEy3/yietYfP55OPhgN+SAr8IZvbRzceNGd5f95MlV78Pv2b9z9YSrKQi4YS38Hj8PH/cwxhieO+k5DnjugLJOwdPfPJ1Z18yiU7MqbsNvAowxU4D2cRbdEWde3CrizKuph6iqMtXV9RHwhrW22BhzFfAycEyc9bHWPgc8B+7u5Rra0jCshZ9vhlAthjvZxXXI7MBfh/yVu7+6u2yexZb7Dtfk7bPeJsmbVOv1X3nFDZNUU5BWOAyzZ8OTT8INN1S/biAA559fdTBIPMEgfPstvPuuCxKJFQrB3XfXf7iUWElJUFLinq9YUfmc1hAmTXL7UFBQ/mZovx+OPBLOPRdOO80FjwSDbh1jXNuys+GNN+Cdd+DnnyMF65NGv7Zi6n7v7Pdo+VDLcsNy1VbLlJZ1Gy5le7XaH06eB3P/CQufBgxsngFfnghJLaHDcGg5EFodAM37QXIbNwSLtUDYBXjkLYUtv8KWn2DDN7DpBzhfnfQStaVoC5eNv4wz+p1B85Tmjd0cERERERERERGRBqHgDRGRQA7kLICc+ZAzD4o3us6jcBEYH3hTwJcJmXtAsz6QuSekdQbjoSRUwilvnEJRMHrbebo/nceGP8aIPUdUu9mnRjzFlR9fSX7A9XoWBYs4Zdwp/H7172WZOYyB8ePdXeIVhyRYsgSGDnV3hV9wARx/vBtmxeNxARtffgnvvQcTJlSfsXld3jqOfvnossCNJG8SZ+11FtNXTS9b58huRzJ16VQC4QA5JTkM+c8QZl09i1R/ah0O9I5jrR1W1TJjTLYxpkPMsCfr46y2CojNgtEZWBN5XlX5qsqsijyvVJe1NvZdfR74e407tyOt/x/kLq5+nbSu0Ov/QWYvKNkKy9+E9V/uiNbtcHcdfRdvzXmLuRvnlpufkZSBiYnRCdtw2fe61EX7XsTxvY6v9bZWr4brrqt9UERBAYweDSeeCHvsUfV6b77psk3UVX4+3HRT5eCNqVPLB5Ztj9jgjZIS+OwzOOEEF1jREH74AU4/3R2rWGec4QLhPB7IyACvN3757t3h5pvd+5Kd7YLr+Dn+uhWV4GcmA5lLPwpII590wnhIo4B08unGcg7iezKI/4Y3S2nG34f+ndum3FY2fIrBsGfrPfF7owcorySP5VuXl1vnvXPeq10jG8DizYujWahanwItjmef0Gqar3gdNn0HwXxYMwFWfRgnKMxQGte2JABrQh53/bUWwl72LtpKi5QWO2xfpGnLznPBTdn52QreEBERERERERGRXYaCN0Rk95O7CFa8AyvehrxFECwAbxpgIZhHlQkWvCkuDXw4ADYAqZ242XssK7atKOsoA2iX3o6L9r2oxmact8953P2/u1m4eSHg7uJfnbOaGz+9kWdPerZsvQ4d4PPP4bDDIC+vcj2//eam22+vy0FwwuEwA54ewKbCaAxBIBTgvbnv8d7cmA4/C4Gw66EN2zBLtixh8POD+f2a3+u+0cY3HrgIGBN5/DDOOj8CvY0xPYDVwLnA+TWUHw+8box5BOgI9AZ+sNaGjDG5xpiDge+BC4EnAEqDQCLlTwHKRwU0tln3QqiK6AFfOhzyCnQ4AYwHvJEsM90vgKINMO0M2PLLDmvqjjLjihn0fbIvK3PcCDkpvhSu3P9K/t8B/69snWsnXMsXS78gTBi/x88RXY/gpZEv1Wk7f/xj3YciKSqCs8+Gn36qep1HH61/loytWyvPe+65+MOO1EdGRvlz3LXXwrx5DRO8sWYNHHdc+cANnw9eesll2qg4PFVVkpLclJkJX38N9MyqMvvGDA7gTc7mM45jLv1IoYgQXkJ4COIDDF6CeAnhI0QhqXRlOUP5nFP5gOHZL5dL23PLYbfw2dLP+Hzp5wTDQfxePyfueSIPHxcdimfIS0NYtnUZAKm+VG486EaO6n5UXQ7Vdjn/vfOZuXYmaf40AEI2RK+Wvfjpyp/wGA8Ub4acubBtDmyeCTlzXLBkqBhsCLxJLCmBfX79Bb/H5+I5jJdtJSEenjmWPx/y5x22L9K0rc9fX/a4Z+s9G7k1IiIiIiIiIiIiDcPs7uMEDxo0yM6YMaOxmyEiiWbDLiPAnDGQuzByJ2+RS9Xe7ihoPRhaDYRme0F6Z/CkgMfnOpPCQSjeBLkLYMtM2PobrJnIxI3ZnL4hpVLWjbfPepsTep9QuQ3hENigq9OGwXiYsvRLRr59VlnWC3CdwW+d+RYn9zm5XPHffnN3oW/aBMXF9TsMxrghFkqd+NqJTFg0oX6VATcddBOPDn+03uXrwhjzk7V2UAPU0xp4C+gKrADOstZuNsZ0BF6w1o6IrDcCeAzwAmOttfdXVz6y7A7gUiAI3GStnRiZPwj4D5AKTASut9ZaY8yDuKCNILAZuNpaO6+mfdgh1668JfDxXu57UlFyWxj2JaT3AF8V2VcCefB2ZuX5NQ19YOKMMtMQf6vEq7eedc/ZMIcDnz+w7Hub7k9n5Z9W0jK1JTPXzuSwsYdRGHTjkrRNa8uC6xfUKWPAzJlw+OGVM0TURkZG1cEUCxbAvvvWPSikVMXzR2EhtGpVc33nnOPOXeEwvP8+fPRR/PXefx/+8IfywSWXXQb/+hekpdWvzeDqu+IKePvt8llCPv3UHefaBm7URjgMr74K998Pq1a5YxOu+0gnVb6Py7Yuo/9T/cs+X+n+dNbdso6MpAzmbphbNsQVuM/e8puW1z9DUj2+i79n/84hLx5SLvNMuj+dvw/7O9cOvrbGTVprOWzsYXy/+vuyIWJ8Hh/92/bn+8u/L8tKVac216LdidRQ165dQUNeu96a9RbnvHsO7579Lqf3O71B6pRGVNV3tybxvtuxdTXUd7++7WvINojsQLp2iYiIiIiINB5l3hCRXV/JNvj6dNj4fTSLQGon2Puv0OMPLjjDl+YCOSoyXpdDP62jm9oNcWnfD/Tz0QcXEF7/MUneJLeutRzapifD87+Fr1+EomyXgSCQB/50wLjMHb5UNxxLOMCwUCFHpcKUYNkGCYeK+XDu25WCNwYMgNmz3Z31335b97vn09OhZcvo66+Xf82niz8tt47XeElPit+Taa0lrySvXJaRJ354gqsGXUWfNn3q1phGFBmqZGic+WuAETGvJwCVIluqKh9Zdj9wf5z5M4C948wfDYyuQ/N3nGXjiJuFxpMEx06DjO7ueVX8GYlqWaPr37Y//zz2n9z62a3kB/IJhUPc/b+7eWz4Y1w74dqygK5UXyrvn/N+nYd6+Oc/6x9gES87T6mnn4ZQqH71QuX+p8mTXRaKqtraty+88Qb06uWCEQDOOgt++cUFaSxfXn79kSPh6KPdUCyFLv6AF190iS1efx2Sk9326iI/3x3P998vH7hx+ukum1FDBm789psLVFm5svL5uVkzOOIIN7zVgAFuux6PC9BZssQFknzxRXRIm6rex+4tunPLobfw8HcPlwUPvTTzJa4/6Hoe+PoBSkJu3Jl0fzrPnvTsDh/aap+sfXj7rLc5460zyoJI8gP53D7ldk7teyqdmnWqtvzLv77Mb9m/lQVuALRObc1nf/ys5sAN2a1k50eGTcmLn/lGRERERERERERkZ6TMG8q8IbJrCxXBx/2hcA2EI+kqWu4Hx0x1ncvVdT7XxFrYMA3m/hPWfeYCPfBAuyOg/TBoczBk9ISkVi57gQ1Hej9jz7vGDTlhvC54pGi9G9Yl68hqNztxIowa5Tr9Cgurv7M7I8N1ev7tb3D55ZCaCuvy1tH/qf5sKdpStl6KL4Vfrvyl2kCML5d9yYmvn1jWaWgwdGvRjVlXz6oy6KOh6A6wqB1y7fp4LzekQUUDH4beV7phU2ryepw7VXeBzBuumGXEayP4fNnnlIRKSPGl8MLJL3DFx1dQECggzZ/Gnw/+M/cec2+d6t2yBTp2rH/whmtb5XklJdC2LeTk1L/einWffbbLZhFP+/Ywa5YLGPN4yi8LhWDtWth7b9i2rXzdxcVwzDHw88/lj0G7dvDkk3DKKW5+Zmblekvl57tly5fDlVfCV1+5oI8SF9eA1+u237Zt3fe/Kh99BOeeWz5bijEumOP//g969nTtzshw268oJ8e1ceNG+Pe/3fA2pQEsFRUFi+j+WPeyzuv26e2ZeeVMevyrB0XBIjzGw6GdD+WrS77CbM/d4tvxXfzX9/9i1JRRZQEcXuNlYIeBPHLcI1W2aUvhFs5555yyMgAZ/gy+/3/f079t//q3uQ7tTgRdu6Ia8tp1x9Q7eGDaA/ztyL9x11F3NUid0oiUeUOkSdG1S0REREREpPEo84aI7NoWRzJglAZuePww7CvX8Wyq6PmrrZm3wMJnIFQIWMjsBUO/AH8z8KaDJ6aHzlPLLARpndxUDWNgxAg3DMHXX7tOw0mTYN686PJgEDp3dp2gw4fDaadF71gPhoOc8sYp5JZEc/KneFO4bOBlNWbQOKr7URzV7SgmL5lMMBzEYlmXt44L37+Qd85+Z/s6CqXpKFwHeYsqz29zMPS+ymWq2c0ZY3jtjNfY84k92VS4iWAoyFWfXEVBoACv8dK3dd96dSi++OL29RFV5aOPGrb/KByGCVWMuJSc7LJyNGsWP8DC63WBE+PHu0wbscFnpWX/8Af3WBoMsX69CxZJTXXntTPPdOe2Fi3cuS0YdMERP/0E48a5tq1aFa23NHAD4MAD657BozoffADnn18+2KJ3b3j3XejRI5p1JDm56jqaNXOPnTvDHXfAn/5U9bopvhReOOUFzn3nXPID+eQF8rhu4nVlcYHJ3mReHPlio56PbzjoBsbPG8/UZVMBCNkQM9bMYPhrw/HHy3KFy9ARDAfLzfvvaf+tfeCGYIwZDjyOG+7rBWvtmArLTWT5CKAAuNha+3N1ZY0xZwF3Af2AwZFMUhhjugNzgfmR6qdba69K5P7FWr7Npe5ZsW3FjtqkiIiIiIiIiIhIwil4Q0R2bXlLIBRzK7S/ucu2UZvAjffau8CP2srsA6kdKMumsT11XwNsq3oxbisMiUz/AEJ4KCCNID7SySdpRQD+g5ti3PreFczeMLtcJ1mSL4n7jrmv+g1GPHXiU/R/qn9Z+aJgEZ8u/pSnfnyK6wZfV6s6pIlbNR6MHygpP/+AfylwI0ar1Fa8e/a7nPDaCRQGC8krcWNdpPpTef/c9/F64qRYqEY4DI88UnXGhe3x9NOQm1vzerU1Z07VQSZ33w177AH++H30gAtkOOAAuP56ePzx8svS0+G99+C119zyQCA6DElhIXzyiZvqa//9Gy54IzsbLrqo/Hu2997w3Xcu0CRelo2apKfXPJzLSXuexIEdD+TrFV+TV5LH+/PeJ2zDpPpSuXrQ1ezZes+6b7iBTbhgAln/zGJr8dayeaVZm2rj3L3O5dR+pzZ8w3ZRxhgv8BRwLLAK+NEYM95aG5tC6QSgd2Q6CHgaOKiGsrOA04Fn42x2sbV2vwTtUrVW56wGYFXOqhrWFBERERERERER2Xls523nIiJNXLfzwJsafV28EdZMhEBezWVrG7jhSQZfJqyZAFOHwbqpECyAYD6UbHWPtppxTRqIlzCZ5NGSrSQRiLvO3Dbw2G/PAdAsuRnNkpuR5k/joWEPES5owa+/uiFZXnwR7rkHLr4YRo50mT6OOw6OPx6uvaA7nVffgC+cRjLNSDXNCIYsN336J9Zs2RJ3u7KTWfYahPLLz2tzMDTv1zjtacKO7H4k1w2+jqTIEExp/jTGnjKWrs271rmuzz9v2ACLUiUl8M03DVvnt9/GH66pdWu47jpIq0WMT3q6G84pNbXyMmNc9o21a+Ghh9wwLOnptQ+6MMZls0hJcVMsj6fhspv85S/lAzfS0uDjj91jfQI36uL5U54nyesOSDhyjUnzp3HP0ffUXLh9e3cQqpviqalM+/Zlqyb5kph9zWxSfdE32GBontycvdruVTb1a9MPr/GWW+fAjgfyxplvNEyb69jundhgYJG1dom1tgQYB4yssM5I4BXrTAdaGGM6VFfWWjvXWjufJiY7z/2Nti5vXSO3REREREREREREpOEo84aI7NpaD4J9H4RfR0eGNwG+Ph32fxR6XwEY8KbEL5uSVbsAjlNXQfbn2PVfE1r/Pears/GEcgml7UE4ow8msycmrQvGn+K25U3B7P8ENlQMoSIIFeH5bTQmFBNQMjYLTq+hQ6KqjqpqxkboY8O8O+8DrLVs2gy//AI/TU/jzseO54ZtrpOzZUt313zr1q4/a6+9oHlz12kaDruO4NXZ9/DDpkPZvC1Abg6sXQeB/DQ8V7Ss+XhJ02bDsOn7yvP7jwaPsm7Ec/8x9/PR/I+Yt2kep/U9jRO6ncWvv7rvU+/e8YcOieeNN6IZJhrSd9+5729RUcPVOWVKdEiTWH/5S+33F1y7rr0W/jlxHB0eLj9WSM+WPZl2yTSuucZw9dXw++/w4YduCJglS2DrVpfBw+Nxp71AAEyvyQRPvpikJIs3BZonwbbHv4BVfcvqnTULiosrB3XUVSgE77zjtlvqwguhTZu6HYP66tWqFzccdAOPfvcoJeES0v3pPDXiKdKTakjbAS5lSCJUqLdjs47Mv24++z6zL1uKtmCxBEIBnhzxJEd1PwqAqz++mqVblxIKhkj2JjOk2xAmXjBxx7U50XXvOJ2AlTGvV+Gya9S0Tqdalo2nhzFmJpAD3Gmt/bquja6vjYUb3WPBxh21SRERERERERERkYRT8IaI7Pr63ggtB8A350UyYuTCzzfBvH9Cz0ugxx8hvYcL7rAhl6nDmxwNnrAhV86G4J1ocEJxIInPZx/DW5+14euvz2bVqrNp2RJOPBEG7lvM3i030T5zE20yN5Lu24g3uBmPLcQE8/AQIowXi5cwyZTs/wq5xa3ZmNuGVRvaMOyktglJjeQxHg7MOJ1bb3WdoF6v6yzu1w8euN+1vXVrdye5Ma5jNd5d8eFwEoWFp7jOUuPWWbBgV7l5eTeXuxiMDyiOzvOmQYfjdkyPdH20b1//zteaUjBkZcG66gOp/F4/75/zPv/vxX+x5JEnaH2eCwwIhdwhu/RSuO8+yMioug5r3XeymtirevvoI8irRbKhupg2rfK8li3hqqvinzOqkp4Od94Jj32Vx7aibRQGo2ksthVtY9nWZfRo2QNjYMAAN/31r255cbF7a0pKwOeDFi3gxi9f5b+/raUQKAwAAfD3fh9/9igCAfdef/ttw2TeWLHCvcexzjyz5iFPGtL/Hfl/PP/z82wu3Mxe7fbi7L3O3nEbr6Uuzbsw+Y+TOfI/R1IQKKAgWMAF713AousX8fv633n515cpChbhNV66tejG++fUfcghAdxoahVVPKNUtU5tyla0Fuhqrd1kjDkA+MAYs5e1NqfcBo25ArgCoGvXumckqsq2Ije23NairQ1WpzSirKy6X8ezshLTFhERERERERGRRqTgDRHZPWQdDaeuhrWfwoInIPtLCOTAnIdg1r3gSYKMntCsD2T0An8GeFLABl12jIJVkFs+a/iJ//iEL+ceRdi6Dtcjj4Qvv3TBEKmpyXg8HYGOVTaptBvcC/iBVKAd0D8R+x+xciXss4+7Y770bvF774U//9ndwV6a5j85ufp6PJ7KHZR7793w7ZVGsGUmmApBGh2Og1BJ1VlqGlsj35EfCsFT9/Tlpxf/TVGROx+UlESXP/ccvPoqvPaaG3oont9/b9jMGLHGj48/xEmsSy+Fu+5yASY//ugySFS16xs3wqZNleefc07N24nHGDimxzFUvGXf7/Uzc91MerTsEbdccjJ061Z+3verK2eNOfCYNfzyvSk755WUwG23wT//WX1ATU1CocpBIDWdOxtamj+NR49/lEs/vJSXRr6EqW1USn06SmtbbxyDOg7i1dNe5YL3LqAwWMiWwi3c8fkdfDj/w7KAneYpzfn8ws9rlzlE4lkFdIl53RlYU8t1kmpRthxrbTGRKD9r7U/GmMXAnsCMCus9BzwHMGjQoAYJTysMFBIMBwEoDhVTHCwm2beDv3zSsOIFSVY8nyUiulFEREREREREpIlR8IaI7NIKCmDcOFi7FjZs8LJhw4lkZZ1Ip/aFdE//mqzkubRL+o3Wvt/IzFmCL2cRFj8WD+5GVIshDIQAg8GLB3er9Un7f8RPSw8k6GlOKASLF8OkSTBkiAvgCIVcMERysstgUZPiYjeFw+4O8jI2DEXr3VS8AYo2QHE1acJn3gZ4wHhdJ3zp5Mvks/EHU1J8EIFA9K7mm2+u253ysovb9CMEK6Rp6HYeJDVrnPbsBG64Af7zH5exJp7CQjedfjpMnQoHH1x5nU8+KT/8RjwdO8JDD8Gee8LSpXD77bBsWfVlcnJg+fKqlycnu7affHI0IOuoo2DOHBg5Mn6Gje++c5lFYgNUAK6+un7BEM2awc2X9uDnX9PLZd7IK85jxpoZnN7v9FrVEwgFWLplabl5qb5U/nBcfzKnwWefRYNLnn/eZQnp27f+w6d06VI588aECTBo0PYPyVJr7dtzYXY2FwL8bS83rxbZYmpcngCn9TuNvw75K/d9fR8FgQKe+P4JfF73r0iaP42pF06lU7NO27cRLzAA6I0LI+iAi44EKMGFI8wHFgCzgXoEGzVhPwK9jTE9gNXAucD5FdYZD1xnjBmHGxZlm7V2rTFmQy3KlmOMaQtsttaGjDE9cUd9SYPuURXW568n2ZdMYbCQFF8KGwo20LlZ5x2xaRERERERERERkYRKePCGMWY48Dju59QXrLVjKiw3keUjgALgYmvtz9WVNca0At4EugPLgLOttVsiy0YDl+F6Wm+w1k5K8C6KSBM2bx5cdln5ee7GvVTguMgUI1gAgVwIl7jJeF1WDm8KJLUsdxfgTefDDf+Bn3+G77+H2bPhH/9wd3SnpECrVtChg+twbd8+GsSRlORS/AcCbioudh27a9fC6tWwYQN8+p8psOJtWDsJClZDSjvofJrLINK8HyS3gax7IXt9+fZntYN97gJMpK0GPD63L4EcRp69jTsf98DWaEfzDTfAo4+6Nu2wDkdpujZMo1K2/I4nNEzd1wAX1GO8ioYY48IPDAT6Ar2A9rh7zQ0QBDYAi3GdujOA/NpV+/jjLvihoKDmdQsKYPhwd87o2bP8sg8/rBwMEWvkSHjlFRdo5ffDwIEwYgRceSW8/nrV5b75Jn6gRamHHoJTToG0tOi8pCR3/powwQWKVOzn/+oryM0tP699e7dufQ0ZYhiaM5Q3Z79ZNi9MmK+Wf1XrOuZtnEeyL5lASTQKxhjD0J5DGfYE7Ldf9H0Kh12g3ccfw/771y/oJBiE445zmU1Kbwh/8cXoNWCHiJc9I5GZaLbTqMNHMWfDHN6b9x7FwWKKgkWk+lIZd8Y49mu/X/WFq8sWkoX7T+Iw3OkrBSqNPZYOtMSdA4oj630FTADmNt1jVlvW2qAx5jpgEu5/p7HW2tnGmKsiy5/B7e0IYBHu/65LqisLYIw5DXgCaAt8Yoz5xVp7PDAEuMcYE8T933WVtXbzjtjX7PxsfB73b6zP4yM7L1vBGyIiIiIiIiIisktIaPCGMcYLPAUci0vT+6MxZry1dk7Maifg7tTqjbsD7GngoBrKjgKmWmvHGGNGRV7fbozpj7tTbC/cWAVTjDF7Wmsr3Be5awiFXIr1wkLXKVPaERwIuGWlHQnWun6viplmjYn2hxnjOm79/uiUkuI6iZKSGqbfTHagkm0Q2OoCEUIF7tGGXAYHG4pMxLyx8dIQR5ZZ654aL+Bxw4iEi91zYyLBDcngS4/WXaq0bLn6Tcy2bWR4Bi/8Yyz84/kGPQwA+wMbDz2ZNd8uZSst2EoLXvO2INSyDbZlK2zzFoRSM7CpqfjSksDjBY8H6/G652F33Ew4jLFhQkUBwoXFeAvz8OTlcP5JOQz6+/0MirNtC+TQjGKSCeAniI8gPgL4CeGNvAriJ1D2PI0CMvz58HmFygbcA3tUiEJZV0Vn03vtoSj+stbAgvsy+fvSHB5+2H3Xx451nY8XX+wyAwwYUH7Yh9Jgk9KPSzjszjPBoJuXkgJ5efDtt+7ufdnJbZtd/nV6j8rDqNS77oappk46AKfg/sII4+K2KvLhBgzoAhwMXAzMwd2j/lXVnbqffAKjR1edcSOe3FyX2eK336IZdoqLYebMqsscdpgbciV2qCKfzwUcPPccbN4Mn34av+yUKe77Gc/AgXD55eUDN2IlJ7sMFRW/1z/9VPlvilNPrZyFoi5KSuCkPU/ik4WfkFcSbfCs9bNqXcfMdTMrXc6Svcn0btUb0xrefBPOPjv6fuXmwtFHu+xDd93lzm21CeLYts3t60UXueCXyZOjda5f74aPef/9qo/r7swYw9iRY1m4eWHZEDf3Hn0vJ/epxcUjXraQYCHMuhvm/8sFKdbmT34vUPrejPDBSUnQrl2t96Eps9ZOwAVoxM57Jua5Ba6tbdnI/PeB9+PMfxd4dzubXC/r86OBqwZT7rWIiIiIiIiIiMjOLNGZNwYDi6y1SwAiKXpH4rpESo0EXon8mDjdGNPCGNMBl1WjqrIjgaMi5V8GvgRuj8wfFxmDeakxZlGkDd8lcB/jWr/edYbG6trVBUOEw9EJXAdIdUP4xgZYeDxw3u3TyPb+WLa8VWt46eE9GN5rOEneWozNAGwu3MyH8z5ka9HWcvOnfdSTbRvTSA63wuChSxc47vC2tErqgNd441cWw1rLlpL1bC5ZR5gw1lryg9vIC23jyHanAjBxIsyf7zqrAgGXmeCkk1wnSjjs9rE02CQcjgafxE6lxy89HTIzo1PLltC6tZu/0wWc2DCUbI0ZFmODG7ogHHQBEzYYee6G78DjiwyL4Ys897nMEBunw+z7ytd9fgONEf1hT8iPSUmf2QtOXtgwdZ//AZx0avR1s37Q+ZRyq9i2h5BLJutoTw7NygIhzEfP4PNZfD5L88wQ7bNKyEgPYwxsKcqh16tnsvW4CreJV7D2H9C+wp3269Khw63x1/cYD5fsdwkXnfICjLkv7joGaA7xP4w1jNv90qd/pO3mrzjEs40W4VzszNGwYTre9kMxzfaE5Lbgbwb+jEhQjsX1WoZrrDsjJZd774U773RDInz6qRvK4fHH4bHHXDBGp07Qtq27+759e9cJ6fe7710o5DqLN2yAjRtdf9rGjS6YLBisdtPS1JUGfMVqNdCde2pSTdDQDlHxcx/Ig9/+DxY94wLObC3HRyjNmLAfcEBalZ26hYVw4YV1C9wA9x1avx7++ld44gk3b/r0qrNjpKXBW2+VD9yIlZ4Or74KvXrB1q2Vl3/+efTvjVgej8vYUV2AQVKSCzQ56SSXoaLUokWV1x05suo21kazZnB096MJVvisFQWLWJe3jvYZ7Wus47uV35EXKB+pcnT3ozGRc/BJJ8FTT8G110bft3DYZUwqHTrmj390w9oUFZX/m8MYNwzWxInuuE2e7LJ4fPQR3HMP/O1v0awekye7QLjXX3d/99V1WKrSQNxdNfjD7/Uz8YKJ7PXvvRjccTB/PuTP9ato2zz4fBiUbIZQHb+IpWwQQkF3/jp9xw8lI/WzPn89wZA7VwTDQQVvSOJVl/mnpnIiIiIiIiIiInWQ6OCNTsDKmNercPe+1rROpxrKZllr1wJExmku7VnpBEyPU1c5xpgrgCsAunbtWofdqb0xH3zIoyvOAxPtMemwrRX/PvHfjOwzsqwjoTpzN8zlkg8v4Zd1v5TNM8bQ98xhFJf8zNbQGgA2A6eN82Lw0Dm5P91T9qW5tz3GY8qSG2AgHA6RHVjCksKf2RhYCYSxkVtUDYYuyXuzIvn3SkfsmTjj3dfZ6gPoMeVUNm1ydwAnJ8PLL7s7Xr3eaIaPUMh1/oZj+p9LH2ODN7xe15EcCrkOmIwM1xFVrfbty//oVpsx4WujYr21qdta2PANrP3UDYuRv9x1IGQdA20Ohsw+kNrJDY2R1AI8/kighgeXB7y0kz4yjd/DBXuU8reAg1+MdsQufRWMvyyZBuEQDL4GNsbcBt+mObx3LKx8p8pmL/B2YWn30W6b4RIIlbDPvOfpmNocV7l1wSUHXl1t3b8Xw5oKfcHHx3T6FRSnMr1kOD98ejBffw3LlrlAga2UgIGOrYpp3z5MRobB5zPwmCUYhNxcS3a2hzXZyWAtLdO30KLVErZenIvXeGmX3o4kbxKp/lR6t+pNl2ZdaJPWhtZprZk4MhNPTI71QDjAlsIt3F64iey8bJZsWcLybcsxGLYWb2Vr0VbW5K6p+j2OVfEH31r8kPv86sV8t2pF9BB6N9Bu4Qu09b5AWy+08UJLD/iNIdmXQrLHS5LXR5Lx4vN4KA61pDgUpDgc5LrMQjJivh/2gzTMBYZkYGhkAvep2kZz1pR0ZE1OR9bM7cgaOrKV5gRIIo9kPIRIooQOlLAvG3BruKkDayFvQ/3GH5CmoSjbDREUjIlkajXIBQnVpmxTsW0OTB3mMhDVt1MX3Pmzik7dxx5zHfz1UVzshtcoDd74+uuqh1355z+jGTqqkp4OzzwD555bfr61sGBB/DInneSCtGqSkeHaUBq8EQ7Hv7wdVPGvu3ro1KwTrVJblTu3JvuSmbl2Jif0rnnonu9WlY/VzfBnVMrocMklbniX005zQaOl7+GGDS4L0dix7ngOGgTNm7u/T/Lz3fIZM+JnF7nlFhdsce+90aCQSZPc0Dh33OGCRYJB97dPcnL8tgeDbjspKS4g5JZb3LVvV9UytSVrbq7lNTSeTT/C1KEuyDVe9rA2B0Ovq6DV/i7Q0VoI5MDG72DRs7ClQqqbpnT+khqty1tHcbgYcAFe2fl6/yTBqvq/LvZ/+hqCp0VEREREREREaiPRwRvxIhQq/qpR1Tq1KVuf7WGtfQ54DmDQoEEJ+ZXlnouH0vXnB7j/6/vJL8mnMFjI2ry1nPPOOfRs0ZOLB1xOy5Q2rq+7rF3usSRYzMeL3+fL5VMJWDdue5LHjV3yh70vZPTho+nZqjtLty7hjd/f4M4v7iRMCAixvPhXlhf/Wut2+jw+3jjjDYb2GErL1JZl80tCJfya/StfLP2CldtWsrFgI8u3LWfx5sX8evf6ShkKsjMMJz68Pz1a9qBtWls6Znbk0C6HckjnQ0j1p/LhpG2c+vtjkOWCLqwX5iQ357RWfywbs7qgIBq4UZUlWxcxaanrQfJ4XNr4PVp359S+p9a8sxUDLBpqTPj6jDe/ZgL87yRcIEZkh8/YBMmtoqlGqlKbu9sDW6HL6dWvs/GCCq+3wRFvV1vkvvcv5L+fPUhKAJKDlI2AMuE1OGxlNQU3boMhLnDjkYPhzmMgKdIBlp8EQS+8Gj6drCPe5c473fABKSmug/Pww11q+qOOgl69/DRrBsGgn5KSyp8Vjyc6xEdODixcmMUXX2QxalQj/5hajyChby/7tuz5/I3zeemXl/hl3S+syV3DD5sXURgs7ZC2QOXO6a7NutKleRd6tuzJR71O4Mz+Z+L3+gEw58ffpgFaRKb+dW7xzsMY0wp4E5fhaRlwtrV2S5z1hgOP45Lsv2CtHVNTeWPMaOAyIATcYK2dFJl/P3Ah0NJamxGzjWTgFeAAYBNwjrV2WQPvcu0VrnNZfGK1PSwybNIO4gf6RqZ9gZa4dyAArAV+BeYBi6sov3E6fH5spFO3Ak8SdDoJel/rOnW9ae58GyqEvCWw4N+wuMLwTXHOt1u3wgMPVB1wURuBQPT5t9/Gz1qTleWGM6opc0NKCpxyigsWWLIkOn/t2qqvqX/6k8tYVRudO8N++8Evv7g6fb7y7e/SpeqghLo6fo/jeemXl8peFwYK+XntzzUGb4RtmPmb5pebF7RBju5+dKV1DzvMZQ/5xz/g0Uejw9CVys+H//2v5rbGxqmNHg29e7thaIqK3PVr2za47Ta37IADYOhQl92jVy93vDwet252thuCZ/Jk91moazaX3U7e0kjgRoWMWr5M2PNa6H2Ny0TmTXXDn8Vq3h96/AHeUpDhzmxVzirCNozHeAjZEKtzVjd2k0RERERERERERBpEooM3VuFGkC/VGah4m11V6yRVUzbbGNMhknWjA1CaK7c229shMpIyuOngm7j2wGt5c9ab/PGDPwIuKGLepnmM+uKWOtV30X4X8eDQB2md1rpsXs+WPbljyB3cMeQOguEg36/6ngkLJ/DevPeYt3Fe3HoO73o4Z/Y7k+G9hrNn6z2rzACS5E3iwI4HcmDHAysvvK1ymaw8y4wrZlTZ/t77ryb95DspCBSA8RHC8OCvPt6c/x+ubfkRnkAzit0NdPgin8qKw6YsDHzOC/kjCeLyyltChAnRP/l4jr/x1DqnJW9UbQ+DPjfC6o8hf4W70/2HK6DrOdB6MKS0BU+yS/UfDlAuBqlWd3XVlIakfsaOHMte7fbi7i/vJjdYTDgSeDLsihT+edw/OaP/GVWWDYaD3D7ldt6f+z6FwUIKgRRfCi2TMhl70is8+afhTHvYdZqBu+v5lVfc0B3p6S7bSimfz3VWVqdVK3cn+AEHbOdONwF92vRhzLAxleZvyN/A3I1z+Xr51/Rp3Yd9svZhj1Z7lAVESZVGAVOttWOMMaMir2+PXcEY44X/z955x0lRpH/4qUmbA0vYJWdQMkgQRcwkA4rh1Lsz53Tm7M98xtNTz5wTKmZUTIAYUJAMknNml7BsDhPq90fN7k7cnZ1A8n349Genq6verm52u6e7vvV9eQ44HnNvmaWUmqi1XhKuvVKqB3AW0BNoBUxWSnXTWruBL4H/AYF5hi4CCrXWXZRSZwGPAn9LzGFHQGV+8DUmtU384mcBRWG2OYDjgFMwSqIkjGjDlxygG+ACioEPgFnANq/AonRdaOFGUnPo+29ofxbgMTPxfbHYoUk/GPBksHgjBA88EHuKIN/28+eHrnPFFZHHs1rh2mvhuuvqyhYtMiKBQIeQ1q1NapBISUqCq682woRVq4xIzldgcNhh8UuZNKbrGD5e8jEl1WZg3ulx8vP6n7mTO+ttt6ZwDRblf+/LSsqifXZ7VuxcEfS9qF9ePx54oB033mhcUN55B5YtM8daUeEvTqnBkbsWa8tFOJ1w8MFGjLF6V08653QG4PTTTdm995qYYO5pbjf88YdZHn44svOwX32n2ZN4nPDTyf7uQAAZ3eCYH8zfuq2ek2fxppoT9ms2FhnFsFVZ8WgPG4o2NNBCEARBEARBEARBEARBEPYPlE6gvadSygaswLjyb8YMsZyjtV7sU+cE4GpgDCYtyjNa68H1tVVKPQ7s9Bk4y9Fa36KU6gmMBwZjBs6mAF29A2chGThwoJ49O7zoIF54PB4enf4oL855ka0lW3F6nNgtdjIcGZzX7zyapTbjvUXvsXLnSpweJ0nWJOxWO+MOGsd/Rv6HZqnNGrW/XRW7SG3bieSddaNkOjcXFY80IeFcIRr4Xcovzeeyry7jhzU/GBEHYLfYyUnJ4bHjH6s3n/2klZN4YdYLVHuMcMOmbCTbk3lq5FNc1P+iiNLQhOx3PH7/ozwftThLoWydEXFUFUDldqjYambAj/0MdgWMuuWkwKRzvT4zGrAYkYerzAg+UltDr7vAlha8r4b6HWGf1xSu4eT3T2bx9sV+5TaLDbvFHrJNlbsKj/afAn7JgEt4cuSTzJuZzogR/gOMS5aYwTFBqEEpNUdrPTAOcZYDR/kIAKdprbsH1BkK3Ku1Huldvx1Aa/1wuPa+dbxtvvPG+N0nbmmA80ZtHe99bxvQXDdwc07YvWvlizD3Bv9UI6fvBkdWw23HR3AdBjgnxKFt/gZ+O9sMzLobYWdhS4fklnDyCnBXw7cDoHipSe1UQ85AOOobI9iwOhqOGeo4fPq8c6dxmoiHO4LWZnA/OztY/GC1QkGBEaJFSkkJtGhR17fHH4e77oLqav96991nHCEaEsH5UlZmxHTPPgv/+led0A5MypbLLos8Vn3sKN9B6ydbU+2u63SLtBbk31S/49RHiz/iookX1Yo+AP7R+x+8M+4djnrzKGZsmkGSzdiDeLSHVhmtWH61v1NHQQHMnAnLlxtBTUGBOXdJSdCho+aj1h2opBC7TYGCKlcVfXL7cP2h19fGUEpxQtcTsLoz+OADI0L0/VMtC9Ac1GDvNhVrVj5Op/n9GjIEXrpxDFnJDfztxfodZH9jwd2w7En/60STAXDcj2CNJIeelwb+zuNJvO5dBwLxuncNfHkgc7bOIc2eRpmzjCGthzDj4hkNNxT2LwKvb5Fe1/ZkKhNJmyIcoMi9SxAEQRAEQRAEYe+R0KlnWmuXUupq4DvM/NnXveKLy73bXwQmYYQbq4By4IL62npDPwJMUEpdBGwAzvC2WayUmgAswczLvao+4caexGKxcPsRt3P7Ebcza/Ms7p12L1PXTaWwspD/zvgvVosVt8dNsi2ZDtkduP/o+zm9x+lRz6DPScmBnf7Tm1W80oRESW56Lp+f9TmTVk5i7PtjcWkXTo+T/LJ8zvv8PKzKGlKE4fa40QHZb3q16MW3//iW3PTchPb5rH8k82uLqrqEPBpOWwqPTIaUhmYZe4/lxw5w9Rgo8hkks3ng229yOGjZTrCnQ3YvswSyK8Tgwq4KGPJi2N2WVpeyrH872LWrtqxZOXTY3UB/ffoMsDsZVgUMGuaVQpuUXDpt28bCyxdy8ZcX+9nbuzwuXJ6Gp1/bLDZePOFFLhpwEWDs+Fu2NNlFagYdn3gCnn7aDGDKDGQhzuRqrbcCeAUYLULUaQ34JgPahBEY1te+NTAjoE3rBvpSux/vfa8IaArsCKyolLoUuBSgXbt2DYSNkvIt/sINZTHXqEShPbDoPlj6uP9+I8VVCqWrzOclj5p0Cr7CjeaHw9HfNSxmawTvvFN/ZqvGsmgRpKaaVE++nHxynRNVYzjrrLrPM2YECzcALrmkccINMO4RJ59s3CkCBQiDQph0RUuz1Ga0zmjN2t1ra8sKKwrZXbmb7OTssO3+2PwHpdV1jisZjgxO6HYCAFcOupI5W+dQXFV3kjcWbWTVrlV0yelSW9aihUlrctJJwfEX5i/i3dd2UOEsp8J7TtPsaczfNp+Lv7wYqze1kNPj5NIBl/L06Ke58EK48ELjIrZ8OUyfDgsXGpFNcbER7GRmgidnGRNyxmCxOkixmvxJHzvLGbP8dc7te24UZ/EAxVkKy57yF27Ys+Hob4PddIQDmu3l2wFItadS5iyjoKyggRaCIAiCIAiCIAiCIAiCsH+QcN9grfUkjEDDt+xFn88auCrStt7ynRhHjlBtHgIeiqHLCWdQ60F8/fevWbVrFQ/9/BBvL3gbl8fF0DZDeeDoBzim4zGROUnsp4zpOoaNN2zk+LePZ/H2xbXCDI/20CylGekOM1CotSa/LB+3p05/Y1VW7jziTu47+r490tcLlqewMLuKlTng8tr3vzQAJvSAZ7+BAfUYmZTZ4f4j4cuuUOWd7G1zg1XDdb9DVpWFsuq6ETCrxUqyrZGjaUCFs8LP0WLSykn87XQj3MisNLqTaitcOwMe+BHsnjCBfPiyG/xznPH1UECpA9wW+PtCeHe6qWOxWHh97Os8fOzDXPLlJUxZO4VyZzkpthQObn4w3//je9buXsuId0ZQXFWMR3tItiVz82E3c+fwO3H4zIDPyDADmM8+ayzltYZ334UvvjADX2PHQt++ZiCzqspst1rNUjPJ1uMxg4tutxlYTUoyg5YLFsARRzT6tAr7OUqpyUAoO5/6cy/4hAhR1tCUyoS20Vq/DLwMZvZyA3Gjo3qX/3pSM+NoUV8agmjRGqafA5u/jE64URcIPskFT6X/oG5Scxg+Ma7CDa3hmWegvBHmIA2xYEHoFB2XXGIG9htDRoa/A0aodCydO0NWBEYqgWRmwrhx8MYbwds6dGh8vPoY3WU0L8x+ofb7QYo9hfnb5nNUh6PCtvl1469+Qs9qd3Vt/XEHj+Oab67xE3d4tIfxi8bzf0f+X0R9enfhuzjd/v9ROSk5nNjtRF6f9zrlPr97by14i/+M/E+tANdiMU5S4dykbvz+FdRMD+XuEvB+5clKyuL0HqdH1Le/DKtfI+jyOPglEW78BSmsKAQgMymT7eXb2VWxq4EWgiAIgiAIgiAIgiAIgrB/IEmf9yJdcrrwxuXf8EZ+zWj675D7d2M/cICTl57HoisXMWvzLM755By2lm6lzFlGaXUplx1yGZcdchnHvXMcHu1Bo0mxpXBu33N5YsQTteKOPcHIWYUs1ppvVn3D+Z+fz/by7VQ5YJsDzvhb4+PdOPxWbjn8Foqrimn1dEesD6WjfMYhvvgAxqyMIJBX3PP8QLh2DLUxPMqIMyZb/8mtrZawbMcyypxGIPLkkXbeGNWEi/tfHNaxpNJVyYTFE1iYvxCnxwxSpdpSaeJI5d/H/psL7r4gKFd8bnouE8+eyJfLv+SCLy6gzFnGovxFdHu2GxWuCipcFaTZ0+jWtBvjTxvPQc0OCrnvf8+4kx29dvC3d0xagq1bbCTNvZ533+3CU0+ZQ27dGvLyjHV/8+aQnm4EHFob8caOsl387niQsqoyysuhrBzwWKgY+t9au3zhr4HW+rhw25RS+Uqplj5pT0JN2d0EtPVZbwNs8X4O176+NuGoabPJmzYlC9h7o1CeAJsGeyboht10omL+LV7hRhglRJN+0GI4NDscbKlQtRMKpkH+j1C23r9uVQFYA0QaA581aVXiyMKF0JCJVW4u3H+/SXtRUWHEDq++aq5Rofj99+AULHY7HHVUdH3s39/8dLth48bg7SNHRhe3pu3DD/uXJSc3XmTSEMd1Oo5X5r5Sex8qrSrlum+vo1vTbmHbzN7sn4oh3ZFem47NZrFx5xF3cseUO2rviVXuKl6f93pE4g2tNW8veLu2P2BcN+4+8m5O6nYSb85/06++R3v4fvX3jOk6psHYbo+bN+a94Rc71Z7KHUfcQao9tcH2fylWv+p/vUhtC61PAmsD9/dP86By77rPCfHD7XHX/h03S2nG6sLVlFSX4NEeLCrCtDmCIAiCIAiCIAiCIAiCsI8i4o29TeAo0F5ObbKnGdR6EEuuWsJj0x/joV8eospdxX9+/w+P//Y4To+TZFsynTM7M/608QxuPXiv9FEpxZiuY9h24zYe/OVBHpv+mHG7wINCYbPY6Na0GxlJGbg9btbtXseO8h1oNMo7qX5w68G8N+49Oud0BqBJshFRjP9zPOXOuoGIsy7I4M8r/6RdVsMpEeZsmcNNbxyB21U36pdiS+HuI+/m2GG3M0trflj9AyPfMyN1To+TgrIC/v3rvxt1/FcOupIHj3mwQfHDSd1PYs2/1nDDdzcwftF4CivNrMg0exqPHv8oVwy8IuxLdZfHxTervmH+tvm1M6cVipwhHzLr1Vl0yO5ISYnRNdUsu3ebwUmn0wg7qi27mVB4ONvdq3Djqo3RMqMVRVX30cIWKjOG8BdlInAeJgXXecAXIerMAroqpToCm4GzgHMaaD8RGK+UehJoBXQF/oiwL78DpwNTvY5UewdPgAWEstKweUgUbPwMVjwfWrjRchQMeAJS25v9+7p+tD3NlE0IMajt9snlkdIa2pwMPg4/YWnEwO5774V2yajhmmuMuMFmM+4/AL16wa23mlQcS5YEt5k1K7hs2DDjHBRNyqiqKrPvVavMz8D+nnqqSdMSDVarufb60qmTcSKJp4DjkFaH+IkZPHhYkL+ABfkLIo7RLLWZ3/pF/S/izin+xjvby7ezZPsSejTvUW+sOVvn+Ll2gBGEnNvnXJJsSZzf73xem/ca1W4jfiqpLuG5P56LSLwxde3UoHRjNouNqwaFNKX76+KuhpIV/mUdzzWpnRpChBsHFDsrduKwOnB73DRLa4bNYsOqrBRWFNI0tene7p4gCIIgCIIgCIIgCIIgxIRMTxL2OnarnTuH38miKxYxuPVgnB4nVe4qkqxJ3DbsNpZetXSvCTd8sVgs/N+R/0fJ7SV8dc5X9GjWg1R7Kk6Pk9WFq2mV3op1u9exu3I3DquDVHsqtx5+Kztu2cGMi2fUCjfACEJePullzu1zLmn2utni5c5yThh/Qu0AUDgKKwo5YfwJVPgIN1Ltqdx31H3cPuz22n2M6DIC991u7h5+NznJOTgsZiDTYXHQPqs9dx5xJw8f+zDD2w2vtXe3WWw4rA5O6X4K+Tfm8/iIxyNyraiqglWLMzlsx6scv2Q11hf/RD1SgvO+Eq499CpsVgt2uxk0zMuD44+H++6Dr76CbVtszLhoJlcNuopUmxlV1GgKKws59LVD2Vi8gcxM6NYNhg+HM8+ESy+FK66Aa6+F8y4t5i3LcHaxpla4kWpPZVSXUSy9agkt0kS4IfjxCHC8UmolcLx3HaVUK6XUJACttQu4GvgOWApM0Fovrq+9d/sEYAnwLXCV1trtjf2YUmoTkKqU2qSUutcb6zWgqVJqFXADcFtCj7whtDugoBFfE5JDO/oExXOVwcyLg4UbFjsMeQ2O+BiyeoI9PThdS6iyULQ52VjyREKEA7s16ZzCiTf++U945BFIS6sTboBxCOrUCaZNg5Yt/dt4PLB6dXCs0aNNnGhI95qNLF1al1aqBqXg0EOjiwsmXnGxf1mXLuFdRaKlXVY77BZ7TDHGdh/rt57mSOPKQVeS5OPS4PK4eG/hew3GenvB21S6KmvXU2wp3DD0htp7493D7w4SJ05ZO6U2tUN9PDfrOUqqS2rXU+2p3D7sdtIc8Uv3c0BQ9CdYAr6L5B3fsOuGcMBRUFaA3WLHbrXTNLUpDqsDh9VBQVkoEy1BEARBEARBEARBEARB2L8Q5439lby86Fw6vOk2wmKxRD8K01Ds3Nx6U8J0zunMb3euReXXzECtAP4Pcp9rOJVMos5HiD4rpRjddTSjuozi21XfctP3N7GqcBWfLfuU5lbo6Ejmkr7ncvGAC8lOzQWqzYzRgBngSimeP+F5rBYrL895GafHiVu7WVKwhE5PdwqbXgRg3rZ5foNCdoudB45+gBuG3hBU12KxcP/R93PvUffy4Z8fctMPN1FUWcTG4o08NeMpspOy2VGxA4Ui1Z7Kv4b8i1sPv5Ws5KwGT191NXz+OfznPzB3rhFmuN1QVtYSMKOUvjIUl8ssFRXmv+vHH80AZXU1rFtn59kxz3JUh6M4+5OzcXqceLSHgrIC2v+3PUnWJFSI/y+tNdXu6lrHDgCLsnDvkfdy02E3hWwj/LXRWu8Ejg1RvgUY47M+CZgUaXvvtoeAh0KU3wLcEqK8EjijEd1PLIED5o1JmTIuwpRfC+4Cd0CeEEsSHDcNsvuYFCmxkntsfOL4sGwZFBWF3jZsGLz4Yv2OFtnZMHUqDBhQlyaloCBYYAFw4onGvSMaauJt3GhEdb707Bm5piUUqalQVuZf1rFjdA4hDdE3ty+zt85uuGIYLj3k0qCyG4bewDN/PFO7Xu2u5s0Fb/LgMQ+GvVd4tIfxi8bjDhA2XT346trPLTNacl7f83hj/hu14kubxcb7f77PlYOuDNvHosoivlv9nV+ZzWLjmsHXNHyAfzUqC4JdNjK77p2+CHuV/NJ8LMqCUormqc2xWWwoFPll+Rzc/OC93T1BEARBEARBEARBEARBiAkRb+yvNEao0Ak4EegJ2IGdwHTgGyBgYCdq4UbNeF89dvKR9FmFqhPJsTZQp4xUFtOThfRhIb0pIotyUqkmiSQqSaOcZuygLwvow0IOYhkOnOHjuitRhQsYrTYyasBgSreW4qjYiEVZsFktqOLxMG28d5TMAx4XpLaGJv2h2WGQ0x9yj0YpC8+OfpbfNv7GvG3zAGMPv7lkM5tLNjd83F5OOeiUkMINXyzKwtm9z+aMnmfw5vw3uX3K7ews30l5dTlJpd0Y0/Qazuj+T1roLPI3mDGRcLoHjwdeeAHuvtvMQi/1uskXF8OgQTBwIAwdCkOGQOvWYLebAUWXywz8LVkC06fD7Nnwyy+mXa530v5pPU7jS8eXnPj+iX5W8lXuKlJCzLivclf5CTcUimdHP1vvgJkgCGGwBKQZcVcRV5OuygJY9mSweOOwd+Mn3ABIbRufOD789FPocqvVpFNpKBWJ3Q7t2sFNN8EDD5iyDRtMeYXP6UhOhs6dQ8doDOvWBYs3DjkktphOpxHb+dK8ub/TSLw4rcdpUYs3bBabn9tVDbnpuRzT4RgmrarTZG0t2UrrJ1vjCJNip8pdxa6KXX5lJ3Y7kZyUHL+y/zvy/3hj/hu162XOMu6Zdg87y3eG7efsLbNxe+pEIQ6rg1sPv1VcN0KhQ30/tUbWNjk3AocdMSPcXygoK8CjPViUhby0PBSqVuwrCIIgCIIgCIIgCIIgCPs7It7YX8nNbVjUkAycAwwDfAdWWgFjgRHAC8Ain23Nm8P27ZH1wY4RhRwFNPGW7QJ+BL4GAidsR+OMESkB56OEdD7kTCZwJovoww6akUo5LqyUkx4miId0SlFABSm0ZjPztrasPTQACufDsmdgw4egbKBdKHc5GQAK466RkmdmkSsLeKqgaie4C6FsnVk2fWZiJefCuG0opZh9yWwGvzqYOVvnNPrQz+hxBhPOmBBxfZvFxkX9LyZv27nc+MA61i5qhXKn8mOShanaCDZcLvNz8GCTnuT0080AJZiZ4mPHwsKFUO7NeuBwwGWXwW23QUaGqRtqINNmMwOTRxwBhx1mRB9JSSadgC8ju4xk641bOXH8iczbNo9qdzUWZSHVnso9R95DZlImTo+Tx6Y/xrrd63B6nDisDtpktOGLs7+gV4tejT6PgiAA1oA/3KrtYE2OX/y1IVJUtDkVWo2Kr1OGp/7UU340OLBrBnW//bbumufL+edDTk5weShSU+GWW+C552DXLuOOEUivXkbM4QitJYiYlSuDyw45xFyjo2X3bnPNrqzLIBKUCiZeXDzgYm6fcntUbXs27xl221WDr/ITb2g0W0u3Nir+tUOuDSprldGKrjldWbx9cW3ZjvId/N+0/4s4brW7misGXlFXEK2rGMTshrbP4QjhBla5FVIiSNcUqSuQsF+QX5ZPlbuKZFsyrTJboTEObPmlCXzOEP4aVBfB3Btg5x+Q0RkOeQbS2u3tXgmCIAiCIAiCIAiC8BdDxBv7Kw29cHdXwXdDoHiZERAE4vAud6bCoa9B+7Mat//8n+C3c6B6N7h9RrOaA2enwvnN4PDx0PzwxsWNFu/5WLcO7rkHJkwwAoIae3erFVp1zaJPH2NZ36ePSddht5tZxMXFMHu2hfnzM1m4ENavh/W6A03yvPHLNsCM82HHTHM+a+zT0ztB29OhxRHQpJ8ZBHT7bFcWM5PdVQafNPXvs89gocViYdYls7j1h1v536z/UeGqQKHo3KQzCy5fQIo9he1l2zn4uYPZVWlmACdbk3lyxJNcMfgKGsOXX8LNN8OmTQ7KyroBxjDFdzCuhqlTYeZMuPFG+Pe/4ZRTYPhwWL3aCDzAjC398Qc0aQLp4XQxIbBaIcs7FjNiRPD2ZqnN+P2i33lpzkvc8N0NVLgqKK4q5umZT/PLBb/w90//zqbiTTg9TlJsKVw56EoeOe4RbBa5rAlC1KS2BmUH7bVRcld4U6fE6e9q9cv+rhsWBwx6DmyNuHhEwq7ZxuUoVE6SQCIc2P311+Cy5GR49NHGXftsNrj3Xrj2WuO8EXjt7dcv+pQpvqxfH1w2aFBsMXftMvdN3z43bx5bzHA0S21Gsi2ZSleIm1MDjDtoXNhtY7qOITs5m92Vu6PqV4u0FgxrNyzktjdPeZNBr0R/ko/rdBxNUnwko4kUvSYydiLI7gOuAPXUth8hqzdYInTgEA4ItpZspdpdjc1io21mW9weN1XuKraVikhHiIHCBTB1BDiLzLNe8VLYNgUO/xBaj2m4vSAIgiAIgiAIgiAIQpyQUc4DEa3h9/OhZEVo4YYv7nKYcRFkdDepPCJh+3SYNsZftBEYs3yDeQF23DRoGuNoUQRobWzoH37YiApqhAW9ehmhwumng9tt6qWl1blI+DJ6tBF72GxG0PH6694NmybC9HPAU1knymg6GPr/B3IOMQINq4+1icUeFNtvexiUUjx6/KPYrDaenvk05c5yNpds5vKvL+eNsW8wbsI4SqpLAEixpfD06Ke5ZMAlEZ+jqiq4/HIjbAk1ezwcZWVmueIKI4zZurXu/GZmmrQneXlmQC9awo2vKqW4fODlDGo1iDHjx7C7cjcbizfS7dluuLV5WZ/uSOe9U9/j5INOjr4DgiAYknPN9crlkwOruhBS4mCvULLauA/50u70+As3APKnQucLwZIZl3AbNtSJAX05++zGpwxJToaLL4Y77zRCuMA0JEOGmPtUrITSeB50UGwxCwuDr9dNm4auGw+OaHcEP6z5odHtLh5wcb3bHzj6Aa755pqo+vTE8U+E3Taw1UC65XRjxa4VUcV+59R3omr3l8CeYa5D5RvqyjZ8AF0vBYukmfkrsaHY/A443U7aZbfD6XH6lQtCo3GVm2fbKp/UO9oNrlKYfiacsBTS4p+OTRAEQRAEQRAEQRAEIRSS4PlAZNmTsHmi/+zm+nCXw48joCKCWZil62DaCeGFG0FxR0L55sj6ESVaG2eIRx81s4FdLiPOeP994xrx978bq/qMDCM2CCXcACPayMoyg2ZNmsA11wD5P8P0s8BdVifc6HAOHDsVmh8GtpSIhBmRopTi38f+mxsOvYFUeyoVrgo+WfoJ4z4cx7xt82pdJv435n+NEm5s2WIcRz78sHHCDV/Ky42zSZWPHuiSS6Bt29iEG5FwSKtDWHrVUoa2GYrNYqPUWYpbu+mS04UFly8Q4YYgxIuUPFABF8nKgtB1G8v26SbdlC9dLjODsg3xaR6MV3VLSHzKt3wD7sY7NoTjl19Cu2H861+Nc92owe2GM8+EFSHG+IcMaXy8QLQ2Lhm+5ORASkpscUtLg8siTRkTDXcPv5vMpDoBjt1ip/quavQ9unZ59LhHsfuIJns270mrzFb1xr1y4JWkBqTpsVlspNpT/RZrwN9CZlIm/+z7z3pjvzvu3aAyh9VBsi3ZbwlkdJfR5KXnBZULPrQ91bj11LDzDyheAdqz9/ok7HE2F5vnCrfHTZuMNjjdRryxqXjT3uyWsD8z9yYjVA2Fu8q4TQqCIAiCIAiCIAiCIOwhRLyRSPLyTM7x+pZQNNRGKRM7FDtnw8K7IxNX+FK9G345tf46zhKYeiy4SiKP6yyGqccFW13HkY8+gpdfrhMlWCxGpHDSSUa0EU6s0RAOu4ZZl/uLYHKPhcGvgC3NOG7UR0SDjaF54JgHuOWwW0i1p1LuLGfiiomUO8tJsaXw4gkvcmH/CyOOtWsXHH44LF8OFfXoeXJzoUsXaFX/mJcfzZo1ftZ5tOSk5DD1vKncfNjNWJSFU7ufyoLLF9CpSac90wFB+CuQnBc8ELp7YXxiF843s1hrsKZC00Mja1sZgbjQ6qNM0C5YcIf//mLg+++DhQsdOkC3btHFS0+Hq64yjh6+KAVdu0YX05edO4Pvfb17138PiAS3O7gsIwLtTbQMaTOEKledYjDZlszSHUv96vyy4ZfamfdWZeWkbic1GNdisfDWqW+R7qhT3mQ4Mii5vYSyO8oou6OM3bfuJsVe9zuV7kjn/dPebzD2oNaDuLD/hX6CktFdRlNxZ0XtMumcSX77Tnek8+HpHwYHy81tcH9Rk8jYieKgGwl6dPn9n5GLlYUDgvwycz9ItidjtVhrxVAFpXESGgoN4vHAjz/Ciy/C229Dwf586otXwto3w19HtAsK5+3RLgmCIAiCIAiCIAiC8NdGxBuJZG/kKp97fXQvsbXL5Pqtj9n/Mi4ajZnhqN3GrWPezY3vU4Q8+qi/nf3o0TByZBxs5yu3Qeka/7Lu10DAbN3w7WP7/7/nqHu4fdjtJFmMOiLFlsLLJ77Muf3OjTiGywUnnmicN0INug0cCJ98Ajt2GFeNuXNh5UooKoJvvoFjjqk//qRJoVMJJAqLsnDvUfdScUcFH5zxQcjZy4IgxEByLngC8nhsnw6uOPyh7/rDfz3r4PgOumYG5ARZ/RrkT4vNgcNjckTNmBG86cwzow8LcPDBJg2VL23ahL5WN5ZNm4KFdQcdBA5H6PqREqpv0QokI8FhddA3r2/tutaauVvn+tXxXU9zpHF85+Mjin3qQaeSZq/7ouDyuJi+YXrt+tS1U1E+bi45KTmM6jIqotj3HnkvVkvdiflu9XcUVRbVrr8w+wXKqs3fVIothZsPu5mMpBAqmG3bjI1KIpZQeXX2ddLaQusTQPnYfRUthtlXx3aNSqDAWIg/O8t3AtQKoNIc5u94R8WOvdanvxKffWbmEIwdCzfcYISI7drBaadBcTGRTV5ozMSERLPimdp7fVji8R1IEARBEARBEARBEAQhQkS8sS9gBwYCNwDPAi8B/wNuAw4DIh2f3v4b7JrbcL1w1OfWUboGNrwPnqrwdcLhqYQ1r0ffrwbYvt1/vXnzOAVWVkD7l3ln90ZEckOzWhv+87tr+F3cMfwOLO4U/qmn8tzl/6BzZzMIN3Ys/PqrGYMJx7//DQsWQHXAWGzz5jB5MkybBqecAk2bQnKymUGdmmrSy4waBV98AfPmQceOdW19bfd/+QWuu27PCjgAHLYYRyAFQQhNUk5diqgaCuc1PLARCaXr/NezejTsYNQYBj7j774B8OvfYNec6AZe3JVQsRWtYePG4M3nnBNbGpKysmA3j3btwNmI20w4Nm0KNvdq395c32PB4wm+51gS/E1ybPexOKzmml/qLGXGpjolTWl1KdvL6r4EVLoqGdpmaERxrRYrdw2/q1bAUeYs460Fb9Vuf2P+G5RUG6exNHsa9xx5D5YIf1/bZrXlrJ5n1bpvWJWVj5Z8VNvnL1d8ifZ+v7BarFx36HURxRWAQc8b9zNf1rwJMy9u/N+5x2Nc5X49I27dExKL1priqmIAspKyAGpTK/kKpITEcMcdJh3l9u1QUmLcnEpLTUrFr7+GXr2IfvJCIic9hMNVDqvfAB2HG68gCIIgCIIgCIIgCEKcEPFGImnIkloBY4GXgcuAQ4AcIB1oAvQGLgReBP6JEXnUEOoF19wbGp8uJZBPw8x6mndr44QLgXjiMJU4DKNGgd3n3Pz0U/2ChohJbgFN+vmXLX448sGBcdvgHF3P0vA5cbvBNv3/yHimjPceOZQZM2DNGpMCZeJEc+w9e8J33wW33bIFHnmkLp1MDQMGwJIlcMQRxp2kvoG39HRjtT9/PowYYcqef95/wPLVV+GCC8wk3uLihk9LINXVwX0UBGEvoSyQ1s6/bPeiyB2H6iPQ0cORA5Y4CrGaHw4H32zSsdTgLofJRxoXDlc5uKvDt6/tpxucpVDwC0zqxfbtZozXl6Qk45wRC6WlRjTnS7t28RFDbNkSLAKJRzqWwPMAiRdvHNfpOJKsdTYiv2/8vfbzwvyFfqlNerXo5bfeEBf0uwDlVbl4tIePlnyEy+OiylXFlyu+rK1nt9j5e++/N6rf9x19X637RpmzjGf/eBaAj5d8jE3ZAOO6cePQG2sHn4UISG4BwyYEC7XWfwA/DDNOQe5KcNXj6uMqN3UKfoRvB8KWSYnt8x5EKTVKKbVcKbVKKXVbiO1KKfWMd/tCpdSAhtoqpc5QSi1WSnmUUgMD4t3urb9cKTUysUdnxE81wqfs5Gy/ny6Pi3KnfKFMFK++Ck8/HT79VlUVbN68Z/sUM+s/DJ/GVBAEQRAEQRAEQRAEYS8h4o1EUp/ddfEq+KovnJ0KDiDcuFgKRrRxQgp81BF2zTPtW7Twr5f/kxlgi5VQqT6KlsKWr4NnYzcG7QwvDImRu+82jhE1797WrjVCg9LSONjPD3kVbHV56SmcCz+dbF78xyJmiYDqahg3Dh56CIqKVEh3i7IyWLoUTj0VXnvNf9u//mXSpvjSvTtMnQrNmkVun2+1GieOTz+Fww+H8883ea7btKlLTfPRR9C2LZx7Lnz7rZmRV10Nu3eb/4eKCqisNP0tLjaz9aqrYdkyePZZ6NOnsWdHEISEkTPIf91dAUVL4hA4UFXXiAGTSJ2Mev0fNB3sP7Cr3TDnX/DtAGOPXrULnMX+biLaY8pcZbD+PfhxJPw4ApzFrFwZLLIYODD8AFakFBWBzeZf1q5dbG4evrEDHZc6dIg9biihRihBRzwZ0HIATp/77fKdy/F407fN2TKHaq8gx2axcXK3kxsVO82RxtWDrq5NwaW15qd1P/H96u+xKiO8SLGlcONhN5JkS6ovVBDtstrxt55/q3XfWLlzJat2reJ/f/yPUqexXLEoC9cfen2j4gpAy+Oh/xP+Qi2AwvlGwDGxCyz5N5RvMX//7kqzaA+UrYNF98AX7WHqcVCyYm8cQUJQSlmB54DRQA/gbKVUj4Bqo4Gu3uVS4IUI2v4JjAN+DthfD+AsoCcwCnjeGydhFJQV1Iq5mqY09fuZbEumoKwgkbv/y7JoEVx7bcNi60TfD+LO2jfBVdpgNUEQBEEQBEEQBEEQhD2JreEqQtwpnA8/HOHNsR3hWy53BZSthe8Ph+FfQMvj/Lcvuid2141wzLs5unQpgYQShsSBtm1h5kw47DAoLDSChRkz4NBD4T//geHDjbAjcPCtPsrKjGghObs3HPMD/HSSsdb2VEH+VPi6B/R5ANqdbkQc1vTIph87y8zM9l1zoMWwsNXKy2HMGPjjj8gGCCsq4JprzPHfdJOxzP/qK/+Z10lJxqEjIyOCExCCtDT40jsRecgQ4wDyzjvw2GMmpYDTadKsfPGFqZOdDX37QufO5tzbbEbAUVQECxfCihVxENcIghB/mh8Om78wg501rHsXMrqBLQZlQaDLRnWh9/oZwaD4uG0R7sMKR38Lv4yD/Gn+98Xi5eZ+Nv9WyD0GcgZ63T/sULUdSlbC5i/9jxtzrQoUwh15ZOwii+Li4Am/Xbv6O0lFy+7dwX1u2TL2uFZrcJ8TPVhns9gY0noIP63/qXZ99a7VdG3alekbp1PpMv9fKbYUju98fKPjX3fodfx35n8BM6v/zQVvUlpdWpsyBeCqQVdF1ff7jrqPDxd/iNPjxK3dPPX7UyzevhgwA803DL2BrOSsqGL/5el2JTiyYeYl5juyrzisYjP8+aBZlA0cWUb47CyKTYi87zMYWKW1XgOglPoA4/Hnq74bC7yttdbADKVUtlKqJdAhXFut9VJvWeD+xgIfaK2rgLVKqVXePvweWDFeFJQVYLOYx9fmaSZPYvNU89NmsVFQVkCH7A6J2v1flksuMd/hfenQAYYOhR07jKg78J6zz+OqgB0zg8uTW0DTIVC02KQNFQRBEARBEARBEARB2MOIeGNPU7oWJh8T/Swfdzn8cgqc6dO+sgB2zAjbJCbKt8C2yWa24j5Mly4mtcctt8Ann5jBpMWLTVqRtm3hnHPMYFufPsa0pKLCf8DJajXihk2bYN48mDwZPvwQdu0Cmh0KJ62CudfD+vdNg7L18Pu5MPtqaDXaDAI2OxyyeoA9A7TLjCMoq3EdKVlpXhDunAnbfjDtzwmd20VrOPlkI0gJfFFaHxUVcM890KSJcb4I5MYbjeNGLBb3voOVdjtceKFZ5s6F77+HX381/w/5+eb8zp5tBChut1m3Ws1is5nz7fEYN5BDD42+T4IgxJmcAUZo4Sti2PQ59L4vtripbaFiS9168ZLEDKRak+DIL2HRvbD0CZOuxXc/2mPua9smRxRuyRKCnI9Gj47cvSgcRUXBZfFIbQLee1cAzZrFHtcaYk79nhiwG9t9LDM3z6TSVYlFWZi7dS5dm3blj81/1NapdlczqNWgeqKEJjc9lzN7nMn4ReNxaRefLvkUj1dYa7fYOb/f+TRJaRJVv9tnt+eMHmfwwZ8fUO2u5o35b6C9ed2sysqNQ2+MKq7gpcM5kN3HfB8rXgHuEBZl2gVVO+uPY01LTP/2PK2BjT7rm4AhEdRpHWHbUPvzfQCpieWHUupSjMsH7dq1C9zcKPLL8mvTpuSmGUemFmnGjVCjyS9NjFD8r8zPP8Off9alpHQ44M034ZRTjHBba3MfOPFEI57fb9gx3Xxf8J2g0Go0HP6BOSiLHebdAiuf23t9FARBEARBEARBEAThL4mIN/YklTuM44YzxIhNY3AFvJxeN964OSSCte/ELxfwlcDfo4zVUB9yc2m1bRvvvmvSjLzwgsnNXFVl3CgefdQsYFwgOnWC1FQjQKiqMqk91qypG4SyWOpSggBm1uahr0Pff8Pq12Hl/6CqEFCw4ROTM7m2rzbvTHILeCoD0qsok4alnoGCt96C339vnHCjhvJyky6lRQv/9tnZcMcdAccUBeHcSwYMMEsNZWXGYnn58rqUKS6XaZ+cDDk50K+fmbUXi5hEEKJBKZUDfIiZabwOOFNrXRii3ijgacAKvKq1fqSh9kqp24GLADdwrdb6O2/5Q8C5QBOtdbrPPs4HHgdqMsX/T2v9ajyPt9Fk9zUzUn0pWWWEgukdoo/bZIARsNVQtMQ/vUk8URbocz90PA9mXmz263GagdzIAoAtDZLzmD8/eGuvXrF3sbg42LWibdvY44K57/mSFSdzh1DijaIik0YrkRzb6Vhs08xX1tLqUmZtmcUpB53CpuJNtXUGthqI3RqdbckdR9zBhCUTcLlcePCgvCl9rBYrtx5+a0x9v//o+/loyUc4PU4qXZVoNCm2FK479Dpx3YgH2b1g1BxY+xYsut+4vLkradDZTtmMSC21LfR9cI90dQ8Q6styJPmqdIRto9kfWuuXgZcBBg4c2FDMeikoK8DpdmJTNpqlGkVa87TmWJUVt8ctaVMSwKOP1gkYU1ONy0bPnkbQ7SvqnjwZzj4b+HKvdLPxbPnOOCLWkNYBhn1k7v019H8Uiv6Egp/2ePcEQRAEQRAEQRAEQfjrIuKNPcmMC8zgV6SpUiJl9atey+gwWBxw8C3Q7QojGiheZhwjds1uOPaqF4Is5IOwpkLWwWaWUvHS8H2JUbNSL/l1M+3at4dHHjEijsWLjYhgzhzIX7GYVtZp9MibS78O82iWsQObxY3TbWPL7tbMWTuA1Tv6sZURdO7Tjv79Q+wnJQ963WGWim0mBU7hfNj+KzvWr+fN70fx0pRL2bY7D7e2kpWymzMO/YSrRr9D9x7JJh1BziHQpF/Iw9iyxaQ/aSindH1UVMDWrf5lp59eN2NuT5CWZtw0xFFD2Ee5DZiitX5EKXWbd91vhFYpZQWeA47HzCaepZSaqLVeEq69UqoHcBbQE2gFTFZKddNauzHDGf8DVoboz4da66sTcqTRYE+HlFZQvt6/fMlj0P8xsz0akpube1DN7HhXGRTONe5GiSKjMxz3I+z+09wr17yFdlezZntXflval50lTfBoC5kpJQzsuoQ+7RZhUU5ocwp0vQKaD2Pltf4h09NjF8KBEW8Eulbk5MQeF4LFG61aGaFiUgQZauojVNqtwH0lgl4t6tQyGs0vG35h8fbFJNuScVY7SbImcXL3k6OO371Zd4a1HcaUtVNq07AoFCM6jaB9dvuY+t4huwPjDh7HhMUTcHuMA4xFWbjpsJtiiiv4oBR0Ot+ItQrnwerXoOBn43qmLEaoAXXirYxuJnVS54sgu+de63YC2AT4SsDaAFsirOOIoG00+4sr20q3UemqJMWeUuuI0yS5CQ6rg0pXJfllDTtvfPjnh2QlZzGqy6hEdvWAoKQEpkypW7/vPujdO3TasLQ0eO89oGuu33NZxOTmRt3PqNj2PUZn62Xo22AJuEna0uDw9+Hz2BxjBEEQBEEQBEEQBEEQGoOIN/YUm76C/KkmhUY4sntDy9Em1251oUmvsfOP8PXBpDUpWRV+e+bBcOxksGWB3Tva1GwIHPcTrHsX/rgsfNuipVAZIv9GLQo6XQAD/kPt5Dvthjn/gnXv0fCEvQboDgwAsoFKzPz234Cq8E18sVqhT/ed9OFp/p72JgzZCXhCilHaNd3AoZ1/N0IU7YH0TtDlMtDXhHf9SMmDlFFU5oziiifg/feNi0SFj3alojqVF6dew6s/X0Pv3vDxx+FnVmsN//hHdI4bvng8xtLYN85ll5kBR0EQABgLHOX9/BYwjQDxBjAYWKW1XgOglPrA225JPe3HAh9orauAtUqpVd44v2utZ3jjJOJ44k+702H50/5OFWvfgv6PRBfPWeKduRogXlz5ImT1il4QEinZvVib81/u+e9TfPmlh6oqjdXiptppAa2w2TxYrAq3x8rwI+D+BywMNk787N7tH6pLFyOwi9XNoqjIWM77EmpALNrYvmRmBrt8REOTJiYNli87G8hIEQ8sysKwtsP4dvW3ACzZvoS5W+fi9qbDcVgdHNfpuJj2ce9R9/L7pt8p887ETrGncM9R98TWcS8PHP0Any79FLfHjVVZ+deQf5GdnB2X2IIPSpm0TzleKzDtMamanKVmm80rTNtfrsONZxbQVSnVEePmdBZwTkCdicDV3nvaEKBIa71VKbU9graBTATGK6WexAgWuwINPLjExsaijWg0VmWlSbJXvJHSBJvFRoWrgo1FGxuIAJd9dRnZydmsu25dIrt6QDBxonmmqKqCdu3gyivrv0/Z7cC2baE3Bv7d7UlVeSBaG3FXDVk9jbjeEuLViC3NCDoFQRAEQRAEQRAEQRD2ECLe2BO4q2HWZeAOY6fQ/HAY+o6ZlawcYHWAxwU9bgVXOcy8CLZ8Hbrtps9BhfAxB3DkwLFTIDk3OK2KLdXkCq9PvLF+Qj0W8wqOnAgtjgoedBv0ArQZC7+e4V+eRcPuGwo4HDgVI9pwADVdrwT+gRkm/RLY7dMucIaXqwKWPQlLHjbn0hOh4qPm/6h4CSy4HQ66tt7qmzfDyJEm5UpVmF04nWaZM8fMVvvqKxg2LLjetGnwxx/BM7Gjwde5QymzX0EQasnVWm8F8A5atQhRpzXgOwq0CTPQVV/71sCMgDatI+jPaUqp4cAK4HqtdcjRJ6XUpcClAO3aJXgWaLvTYdXL4CqpK3OXw+JHoNed/rbikVCxxYg30rtAqY/gcMOH0P/xhIo38vPhppuMeM7lUrhcNffMuq9A1T7X3e++h19+hUGD4NlnTVotX7p1i8/Yb2Gh//XeagVbnL6VFRf7r2dmxiduTk6w4CSaCdbRMPagsfy8/mfKXeW4PW6mrJlCudPc7NzaTd/cvjHFP6ztYXTI7sDi7YsB6Nm8JwNaDmigVWR0atKJUw86lff/fB+rxSquG3sKZYHUBOf02YfQWruUUlcD32HSfb2utV6slLrcu/1FYBIwBlgFlAMX1NcWQCl1KvAs0Bz4Wik1X2s90ht7AkbU6AKu8jpNJYxFBYsAcLqd/LDmB9btXsfynctxup1+28OxpnANRVVFFFcVU1hRWOveIYTmm2+M+wbAzTeHTp3lS7j0ivscZevwy/rT/XqwhEm7Zc80z+SCIAiCIAiCIAiCIAh7CEvDVYSYWfM6VIdRLfR7FI7+HtI7mhmBVocpt9jAngEpuTDsw/Cx178fWhSiLHDU10bAESjcqMHWwGDZunfAUx2m3w9D7tGhB9zs6dBqdHD585iZTuEWVxVMGwdXp0EekIz/b2iydxlth1eaQuGfdW1b+Iy9Fq+Ar3vC4oeMLX8o4UZaR2gyAJoPMylMUloF13GXw6d5YU6OScfSuzcsW+bvthEOt9vMhh4xAt5+O3j7HXfU5ZSOFd8BwY4dgwfbBOFARyk1WSn1Z4hlbKQhQpQ1NE00mjZfAh201n2AyRgnj5BorV/WWg/UWg9s3rx5A2FjpOng0PeOZU8YIYZuhI2Dqxymn2U+d7kErD6jO+5K49bkLA3dNkZmz4aePeGDD4wbUaTiuPJy+PlnGDIkWKjRvTukpsbet0DHiowMqA5zy20sgYKTjIz4CE6ys4P7GG6Sdbw5puMxtc41dqud6Run1247rM1hWC0NjCo2gFKK+4++v3bd93M8ePCYBwE4u9fZMmAsJAyt9SStdTetdWet9UPeshe9wg204Srv9t5a69n1tfWWf6a1bqO1TtJa52qtR/pse8hbv7vW+ptEH9+C/AUAVLoreX3e69wx9Q7enP8mlV5Xvblb59bb/qPFHwEm/dKXK75MbGcPAGbOND+VgvPPjz311j5D4YK6dErKAu3/Fl68AQdaeiVBEARBEARBEARBEPZxRLyRaLSGpY+DO8SofJ8HoNtVxgWjPsLNcNYe2BXmJWWHvxsremuUb9kqd0B5GOvh1idCt6vrn3nd2FnZzhKYegxs/Sb0ufJFO6F6J3x/KBT86r9t+2/w7UAzo8odoKhoMsCkeBmXDycsMq4kR34Jx06Dk1aZJZDK0FOKi4qM40ZhYbCFfENUVMDll/uXzZ8PCxfW3+6YY2DyZNi6FTZsgBdfNMKMhmjXLj5uHoKwP6G1Pk5r3SvE8gWQr5RqCeD9WRAixCbAN8lRG2CL93O49vW1CdfPnd40KwCvAIdEfpQJRFmg9UnB5R4n/HxqyPRTIXGVGQekwvlmvcM/CNK4rH8ftv9iHJOiwRVa+DF+PAwfbkQS0VwDtTbXa4fDv7xHj/g4ZASKNzIz43etLg/QdGZkNDxjOhKs1uDBu+3bIxMwxkrXnK44vALX0qpStpSYP61kWzIndz85LvsY230safY0spOzGdl5ZMMNGkGnJp2Yc8kcnhn9TFzjCsJfiWp3nXrMrd24PK7a9EmB20Px1oI6feSb89+Me/8OJKqrYf1687lr173bl7iza675fgLQdAhBKd0C8STUUEYQBEEQBEEQBEEQBMGPhIk3lFI5SqkflFIrvT9DTjNUSo1SSi1XSq1SSt0WSXul1O3e+suVUiN9yh9SSm1USiVmCm807JwFFSEEAB3Pg4Oub7zIwZfi5aGn0iob9HssNhv6Hb+BJYT3rbLAwOdi63cgHhdMPhJ2zg4WXNSHqxR+HGnOMUDpGvhxtNfm32eye85AOHkNHPcTdLsGkluY/juyvUsW2FIgo3NEu9Ua/vY32LUr8q4GEjjQ9cQTZlZ4KDIz4bff4PPP4dhjIS8P2raFCy6AxYvhvvvq31e8bPgF4QBiInCe9/N5wBch6swCuiqlOiqlHMBZ3nb1tZ8InKWUSlJKdQS6An/U15EaEYiXk4GljTyWxNHhHLBlBJcXLYZZlxtHjfpwlUH+j7D433Vlqa2g6xXB95dfzzDpVBor4HCVwYaPgoq//BIuvrhhUYHNFizOCFXHF1+jp1jYvdt/PSur8WLAcAQed2ZmfMQbAOkBXy3qSxsWT5RSHNXhKAA8PgNtVmXlmI7HxGUfVouVT8/4lE/O+KTW5SOeDGg1gMykOOWwEYS/IJ4GXJ/c9WRt2VS8iTWFa3BYHdgtdn7b+BslVSVh6//VWbKkLg3KkCHm+eeAYdcswPu7kns0WBqY7JDA1G6CIAiCIAiCIAiCIAiBJNJ54zZgita6KzDFu+6HUsoKPAeMBnoAZyuletTX3rv9LKAnMAp43hsHjP384IQdUTQs/2+wICGlJQz8X+wCiO3TQxvydzq/4ZQoDZH/o1cEEUCHf5hULPHkzweNECVUepOGcJfDL+PMIOKUY4NnYHe90og20juaF2/1WeJGyBNPwC+/xG+wqrgYPvkEPCHeRzdrZiyL+/c3M6d9cTggJQVuuAGefz68Jf6emBEtCPsZjwDHK6VWAsd711FKtVJKTQLQWruAq4HvMIKKCVrrxfW1926fACwBvgWu0tqMJCmlHlNKbQJSlVKblFL3emNdq5RarJRaAFwLnJ/QI28MeSPAmhJ629p34NfTTboTd4iLobMU1r4LP48NTrHS+55gVyhXGXw3BLZMijyFiqvM3D9mXOhXvGwZnH12+Gvf8cfDhAmQn2+u4+Xl5jr83Xfwz38GixwCr61Nm0bWvYYITGeVmRm/wbHA+1NGRsMilUjJDNAerFoVP2FIQ5zU7STS7Oa7k/Z+AbIoCz2a96ivWaMY0XUEx3SKjxhEEIT4UV7dgGDQS7UrtPvGJ0s+waIsaK1xWB04rA4mrZwUzy4eUCxcWHdPGj48+Dlkv6Z8Q93nVidE71QpCIIgCIIgCIIgCIKQABIp3hgL1HjTvgWcEqLOYGCV1nqN1roa+MDbrr72Y4EPtNZVWuu1wCpvHLTWM7TWW+N8HNHjroSNnxJkxTrgKbDGYRRl2+TQKUZ63xv7DKFtkwlShsTD0SOQXfNg6WNGhBEt5Zvgk1yoLMDvXB98C/R/rOG0NI1gyxa4555gS/pY+O47sIfQlCgFX38NnTrVzXwLRXo6nHsuXH996O0rVtTfXhD+anhTlRyrte7q/bnLW75Faz3Gp94krXU3rXVnrfVDDbX3bnvIW7+71vobn/JbtNZttNYW7897veW3a617aq37aq2P1lov2yMnIRIsVjj4JrCGuYZu+Qa+7gErXzBCCo/TOClt/QF+Osm4c4SaJW3PNA5OgXHdFUYQMvMiKFsPzmLwBAzCuSrMvrZPN4K9JY/4h3DDSSeFvkb37Anz5sGnn8IZZxgHDYvFCA8yMmDECCOE27DBpMWqIVBYl50d+nQ0lsC4aXE0tAoUgTRpEj+BReDxr1tnhIR7gmM6HhM0s/7IDkcmxCVDEIR9i2U7I7s9rti5ImT5mwvepMJVQbPUZmg0JdUlvL3g7Xh28YBi9+46keFhh+3VrsSfGldMZYGc/nu3L4IgCIIgCIIgCIIgCAEkUryRWyOk8P4MZTTeGtjos77JW1Zf+/ra7FvsmBk8kye1HbQ+GSxxEG9s/yW4rNmhZmAsFtxVUBLixWerUSa9SLxwVxrXjMakSgkbq9RfAJLe2czujmd6F+DWW8Hlqr9ORgYccQQcfTS0juA3c8IEKAlhcnLNNdCjR2SzpdPS4IEHoEsXs+4r1ti+PXiGtyAIQkR0vcwMboSjfCPMvR4mpMPHTeDDJPhxBBRMqz9ux79Dx3+GFoZsmABfdDQCkD8fMmKQgl9h00RYcBt8dyj8MAx2zgxq+sYbsHVrsHhh7FjjYtSnT3DaD1/S06FVKyPwuOsuUxaYyiQrq/5Di5TAuJY4fiMLPP54CkNatfJfr66GwsL4xa+P9tnt/dKOpNpTOanbSXtm54Ig7FVW7lwZUb3lO5cHleWX5rN0u8lKdmzHYxnc2hg1Tl07lQqnWNSFoqKi7j4V6Li0X6M94NxtPqe0Di0yFQRBEARBEARBEARB2IvENFSglJqslPozxDK24dYmRIiyhkzDo2njH0CpS5VSs5VSs7dv396Ypo1j2xSTzsOXrlfUPxAWKZU7oGpHcHmnC8LPko6UXXPAEsKqoeuVsQtDfFn5ktctIwEc8nRkAplP82C8qlvqYf16+Pjj8EKIzp3hgw+MFf/EiWbwb+VKmD4djgnjwO52G+eNQNq2hX//u/5BxkCSkuDDD+s++/Ljj5HHEQRBqMWeCQfdCNYI7HtcZY0bBBn4HOQeFSY1i4aCn+HP+40YZPIRJgXL8meg6M+Q4crL4ZZboCzAkOqkk+C994yAIVKBRGoq3HYbjBmTOIeMwLjxcsbQOli8EU9hSJ8+walk1q6NX/yGOK7TcbWftdYc2/HYPbdzQRD2Gqt2rYqo3urC1UFlny/7HKvFSrojnZFdRnJC1xNIsiZht9r5fvX38e7qAUFlZZ1gPfC5Yr+magcor+VhWjvjGiYIgiAIgiAIgiAIgrAPEdPrfK31cVrrXiGWL4B8pVRLAO/PUKP0m4C2PuttgC3ez+Ha19cm0n6/rLUeqLUe2Lx588Y0bRxbvgLtY9OgrGYWczzy6u6aHWIwTUHb043VfSwU/AKeSv8yWxrkHh1bXF/cVWZQLpZ0KeFIagZ5x4LF1nDdyvyIwz74YPBM6RpGjDB2/Kefbuzjs7PNkpJirIYnToS77w5uN2tW6Hj33BM6lUp9WK3QrZvJS10RMInwpZeguLhx8QRBEAA4+AawJSDZvcUKw7+AzpfELjrEXOeqqvzLunSB8eOjE1ykpcFRRwULIRp7bQ5HKOeNeGT/CBSFQPyEIQDduwefz99+C39/jDcndj0RCxY82kOqPZVOTTrtmR0LgrBX2Vi0seFKwPqi9UFlb85/k3JnOW6Pm+Hth3Nk+yNxWB2UVJfwzsJ34t3VAwLf+1HgfXC/pmJLXfrS1LYk1ohUEARBEARBEARBEASh8STybcVE4Dzv5/OAL0LUmQV0VUp1VEo5gLO87eprPxE4SymVpJTqCHQF/khA/2PDXQVFi/3Lcg4xAo54ULLC7MMv/gCwxGFUacfv4Kn2L2s1BtzVoetHw7r3wFMVfrs9Cw6+CU7ZBGdVw5klcPj7kN234djNhwWfmxiprDQzt0O5bowdC599ZtKlhBsgS0szM8JfeMG//LPPzGxxX3Jy4JxzIkuXEkh6OjzyCAwc6F/+/fdQWtr4eIIgCNgzYdhHYRwyGkEo9w6LDQY+DYe+Ada0yBw+/GKmQYrJ4/HSS8HX01deMSK6aLHZ/AetLJb4DWIFCjVCOWZEg8cTHNsWgZYxUrp0Cb7X/fTTnrvHHN3xaDwYhcoxHY9BxUPxIgjCPs/mks2R1Sv2r7ejbAdzts4BwG61szB/IVtKtlDhMkrnr1Z8RZUrvs8NBwIpKXX3juo4PgLudco3U2vkmdouvilBBUEQBEEQBEEQBEEQ4kAixRuPAMcrpVYCx3vXUUq1UkpNAtBau4Crge+ApcAErfXi+tp7t08AlgDfAldprd3e2I8ppTYBqUqpTUqpexN4fPVTuhosAQ4buUcHl4UiMJVHqHQeRYuDxQ/Nh8dHvFEcnCuaNqeCI04pU7SGxf82FvuhyDkExq6F3vdCamtzTLZ04yoy4jfo90j98VNaxuc8+PDNN6EHv7p0gXffNRb7DZGeDv/8J/ztb3VlkyYFz1a++OLYBvD69oXLL/dPueJywRVXxD64JgIQQfiLknskdLooNgGHo1n4be3PhFM3elO0pDXg9GE125Pz4JD/wth1rF1rUlv5ctRRRsgWi+uEx5M48UZgKpNQjhnREErLEM9Z0507Bzuc/P77nrPVz0vPo3mqcU07qdtJe2angiDsdSIWbwTUu23KbTi9qTHKneX849N/cN7n56G9F8YqdxWP//Z4fDt7AJCcXHf/3Llz7/YlrlRsrkuVktE17s+MgiAIgiAIgiAIgiAIsZIw8YbWeqfW+litdVfvz13e8i1a6zE+9SZprbtprTtrrR9qqL1320Pe+t211t/4lN+itW6jtbZ4f96bqONrkLL1oAJOb+uTIkuZEkkqj91/Bpe1HNH4WcuhKN8QXNbiyNjj1rBzJlRuC70t91g4dho4mphULb5YbGBLhW5X1x/fVQY6Qv/25NwGKpj/w9deg5IS/y1WK3z9deNmdaelwauvQocOZqBu5crgOpdcEpkYJBxWK5x6avBA4MSJ8PPPwSlVIsXphNXBacQFQfirMOBxSGldlyu+MVhTYfin9ddxNIG+D8K4LcaJo8vlkN4FbJlGNGLPgiYDoMctcMQncMpG6HIxWOxMmBAsULjjDn8RWzSEcseIF4kSb4QSmMQzpUmLFsHx8/OhqCh++2iIIW2GAMaFQxCEvwb5pZGlOgys98mST2o/uzwuiqqKKKoqwu3zrPDa3Nfi08kDiKZN69KE/fJL/O5Re52yjeD2PgxldN67fREEQRAEQRAEQRAEQQhBHI20BT/K1genHsnqFb/4pWuCy5odGp/Y2uW/ntQMkprGJzbA+g/AFUJBkNIahn8G9gZG2wJFHYHsnBl66nEoxoURkfhQVgZTpgSXX3ghtGrV+FndSUnw3//C2rXBbVu1gjZtGhcvVPykJLjtNpNCxTeNwJlnwsyZxjGkMbOknU7YsQNGjoRtDZ8yQRAORKzJMHIGTD4aSlaCpzKydrZ0OPJLaDoosvr2TGh3mlki5Mcf/d0gMjLgiCMibh4Wq9X/duJ2B4suoiXQzSleAotQt794ijeUMveqtWv9y3/7zQgHo8Xjifzcjug0gpmbZtImM8YbpiAI+w3VPukbrcqK1VL3JdrtcdeKMSpddfemLcVb2F21u8HY64rWUemqJNkWBxH8AUL//nWff/nFuAdmZe29/sSNqh2AV4GY2n6vdkUQBEEQBEEQBEEQBCEUiUyb8temdHXdrB4w6VIaEh00hqrt/utp7cHiiE/sQPeOZoeBO8JBukjY8BEQOH1LwbAPwRKHl6bFy6Fye8P1IuSbb+pmntVgt8NDD0U3q9tuh+OPhwULgsUbJ5wQv0G2m28O7l9ZGRx2GPz0U+QpUMrK4M8/4ZBDzOxqQRD+wiQ1NQKO5ocbN436UDZw5Jh0V7lHJbRbS5b4rx97bHBqj2gIFG9A/K7RgUKFQHenaFEquM8uV+i60dK1a3DZ55/HdgyNaXvNkGsouLkg+p0JgrDfkZlk0jcmWZN49LhHyb8pv3b597H/JsnrbpidlF3bZtKqSVi8j7sKRbusdnVLZrvaehZlYdraaeF37nFB/k8w/3aYcTEsvBd2zgJ9oNhRBNOtG1R79TIzZwY/C+23+KYdTW6x9/ohCIIgCIIgCIIgCIIQBhFvJIriFf7raW39xRyxEihyaHaoebEYDwJfRLY4ysycjgfFy6G6MLi843nQpC9Y4/RmcNaV4IxQndAA338fPKh0xhkmF3S0OBwwZ44RRvhy9tkmtUo8SE6GV14JTsFSXAyjRpmUAoWF4QfMysrMtieegMGDYevW+PRLEIT9HFsqHP0t9HsMUtoE3x+sqWbpfAmMWQTZvRPaHacz+PrUp098rqU2W7DIItrUU4EEuh8VF0duGtUQgXEiFetFypAhweLDL7+MbXDvgBkYFAQhIRRWmucHh9VBq4xWZCdn1y6tMlph9z5D7KqszbTJJ0s/weMVjI/qMor1162vW65fT7+8fn51Q7JtCnzRHn46CZY8Bmteg8UPwZRj4OuesGtuYg54L2O1Gqc+gPXroTKOOv69iq8zZjzSjQqCIAiCIAiCIAiCIMQZEW8kClfASElKK9Bx9C23BPitZx4cP2cPV4CioPlQsDQyN0g4Nn4WLA5RVuj3cOwCEeVzTrZ+Czv/CJ2epZH8/HNw2eWXG1v+aLHZjMV8YP7oQw6JPmYoTj4ZrrgiWMChNTz7LLRsaba/956xwC8ogA0b4NNP4frrjTX+vffGf9a2IAj7ORYbdL8KTlkPwz6GrldC29Og0wXQ/zGTkmrw85DaKuFd2bLFCOJ8GTQoOC1JNGRmBosU4uWQkZ3tv15cHJ8+Q7DgpLAwvtfxI44IFscUFsLcGMYwv/02tj4JgnDgorWmuKoYMC4ZTVKa+G1vktwEqzIX66KqIrTWVDgr+HHtjwCk2FIY03VMUNwxXcZgVVY82sPHSz/GE/iMsuQx+OlkqNgCrhJqnQO1yzzrFS+HH4bF92D3EE6nEXkPG2aeE+x2yMuDCy4w7oAAQ4fW1X/uOf9UjPstPul3gp6nBUEQBEEQBEEQBEEQ9gHkjUWi8J3VAyZtSlzjO/3Xs3tHJrD4NA8qG8p9of1X0zvGKS6wfry/XS1Am1PiIzyxOMDtMzr104lw5FfQbEh08V1lVLnTWLPGvzgnxwwMxsrKlf7reXnBA5Dx4LHHYN06k/4l8KVrVZURbrz3Xvz3KwjCXwBlgVYjzbKXqKwMFlg0axaf2Dk5wbF37zbCt1hp2tR/PZ7ijeRkf7eNkhIzUBev+EOGhHYgeeEF6N278eLG4mJ46SUYNy4+/RME4cCiqKoIq8WK25u3qklygHjDR8yhUJRWlzJl7RQcVgdV7iqsFitHtj8yKO7RHY/mf7P+R3FVMS6Pi5mbZjK0rVexsOwZWHQfuOtTLOj4OivuIWbPhtNOg507/V0A8/Phrbfgww/hb38zIvAJE8w95Jln4IYb6o9bXh4sGN/nqHkOVVYzoUDJXBZBEARBEARBEARBEPYt5G1FotABAojGeKEn5zZQQQULIDK7RxY7EoGFLxY7OJo2XC/SuMXLgst63gb2GGwsahj6NlhT6tbdFfDjCFj6JLjK/Wda1YerwqRcmX01CxdCSor/5lNOic8M5sKA7DF9+ybGkthigQ8+gEsuif2FarxSugjC3kQplaOU+kEptdL7s0mYeqOUUsuVUquUUrdF0l4pdbu3/nKl1EhvWapS6mul1DKl1GKl1CM+9ZOUUh9628xUSnVI4KEfkATebiHYeSJacnKCy3bujE/sQIFJaWn8UocE3rdKSuLrvJGZaZyZAvn00+jiVVTAlCmx9UkQhAOX/NJ8HFajcHZrd0jnjRrXjCRbEvll+by94G1Kqo1Vktaani16BsUd2mYoFU4jvqhwVvD+n++bDbsXwYLb/IUbWT1MurCh70DfhyC1TbwPc48weTIcdZRx2gtM3wjmnlpRYQQcY8aAVy/Djh1w332h29SwXzhz1EyAULZgN0hBEARBEARBEARBEIR9ABFvJAprgIVCpMIBMHbz5+jwy0HXB6dgSW0Xe59DkdYhvjPKAh1IkppBVq/4xG53GvS4Faw+CgXthkX/B98OgGVPQPlmY3PsDhC/uMqNaKNoman/VXdY8yYzZ5rZyr6ceCKkx5jhxekMFmr065e42Wo2G/z3v/DOO6bvSY00grHbzWDg448npHuCsKe5DZiite4KTPGu+6GUsgLPAaOBHsDZSqke9bX3bj8L6AmMAp73xgF4Qmt9ENAfOFwpNdpbfhFQqLXuAjwFPBrvgz3QcTiCU1AVFcUndtOmdQNXNWzfHp/Y2dn+Yg2PB6ob8VWhPgKFdsXFwecoVo4MnsROeTk8/HD9g3uBlJTAHXcEn2dBEIQaCsoKatOiuDyukM4bLo9RqFmVlc3Fm/lu1Xe12we3HowlhMNCmiONLjldACMK+eDPD9AeD8y4ENzeL+rWZOj3KIycBQffCB3/AQffDCcug4Nu2K+cG5YtMyJ032t0kyZwwglw5plw6KF15RUV5nlh7Ng6QeRTT8GkSf7OTmCu37t3mzj7Pt6bobIQ5DZZw6d5MF4FLHFKISoIgiAIgiAIgiAIgtAA+8/bpv0Na8C016qC+L3cC3S5sGeCNc5pWWrI6BosFIknrU8ETxynA/e+Bwb8J/j8Fy+HBXfC523g+8NhwR3w50Ow/FlYdD/MvwW+7gFfHwxLnzC5rYFFi4Kt4YcMib2bBQXBAopevRKTNsWXceNgzRq49lozuNeQk0ZKirHfP/98WL4crrgisf0ThD3EWOAt7+e3gFNC1BkMrNJar9FaVwMfeNvV134s8IHWukprvRZYBQzWWpdrrX8E8MaaC7QJEetj4FilGmPVJOTlmRRQvsybFx+xQk5OsKBi3brY44Jxrwh02ojXrOVAgWFJSWiHklg45pjQQsZnnmmcy0dpKbz9dvz6JQjCgUd+WX6ts0aVq4rs5Gy/7dnJ2VR5hdkazbIdy6j2VOOwOrAqK2f1OstULJwPMy6CT1vChAyYkMGZlo1YUdgtNkqqSyhf/5HXKVADyqRg7HY12FLrnuUsdpOSsc/9MOjFPXIOYsXtNgKNmvuMzQbXXQfr15v0ia+8At9/D3/8YQTlNdx2W90zi8tlYjz5pIlTVGSEIEuWwMCBpu0+j/LeeLUr/LN5SEdJcekQBEEQBEEQBEEQBGHPEKfs50IQ6Z3818s2BAsKoqUyYNpvSmszO8ySgJH/9I7Bbhmx4AqYqtXh72CP0cYikK6XQ9NB8Pv5ULYWXAFTgHcvNEsErF3rv56dbWZix0p+vhm08xWGtG4de9xIaN4cHnsM7rzTWNz/8AP89BNs21Y3uNe0KQwbBiNGwKmnmsFRQTiAyNVabwXQWm9VSrUIUac1sNFnfRNQI90K1741MCOgjd9ftlIqGzgJeDpwP1prl1KqCGgK7Iju0P56pKYakUVBQV3ZwoVmQCkjxoxcWVnB7ktLlhjBQawOTJmZYA2YyLtjR+hULdHE9qWkJPaYgRx2WGiBTFkZ3H+/WRoSCJaWws03xzeliyD8lVFKjcLcX6zAq1rrRwK2K+/2MUA5cL7Wem59bZVSOcCHQAdgHXCm1rrQm+ZrKbDcG36G1vryRBxXQVkBTm+6C7vVjt3qr3xLtiVjURY82oPTbeoV3lpYK/jILPwDvuwO5ZtM6kkfYfo9mXBDhhUsNmzpnUjd9End80q3q6HZECPcCIUtDTqcE+ejTQyvvGIE3Fobsfivv8LBBwffyw45BKZPhwsvNOt9+hix3nff1V2r77kHHn0Uevc2963Vq/fsscREzfOyxwlK3DQEQRAEQRAEQRAEQdj3EPFGosjoakQPHu90YFcpeKrNTK1YqQoY00vKSVzOXkezxLl6KAs0H5aY2DmHwJiFsPFTmH8bVGw2L2o9EXjSW1PM+WzSl02b/Df1719nIxwL+fkQOLd+TwsksrLgggvMUoPLZQYTZd6/sL+jlJoMhPqrujPSECHKGvIuqLeNUsoGvA88o7Ve09j9KKUuBS4FaNcuQamy9lO6d/cXb/z4Y7CrRTRYLMaByNcRY8WK+IgNsrLqrOhrWL8eunWLT2xfCguDhSKx0qWLGQAM5Rby1FMwZgwcfrhxbwpFeTl89ZWZ8S0IQuz4pPs6HiMenKWUmqi1XuJTbTTQ1bsMAV4AhjTQtiZV2CNKqdu867d6463WWvdL9LFtLdlKpcukMUmzh1aFpdnTKKoqotJVybbSbaQ7vKqEFc/DvJvq0kAqG7QaDemdAY0qWUnmtsmgK6F0CVRvNfUcTaDvQ2BrQKlna0Clto/w3HN16VKeeQZ69AgtsLNYjCjytdf82/bu7S8ELC+HmTMT2+eE4JvaVLtFwCEIgiAIgiAIgiAIwj6HiDcSRVp7I3rw+Hi5l66B7N6xx3bu9l93NAlZLS6k5CUul3NGV5MypaF3Zp/mhbGvNfyrAD4pBZ5sU1t2Zs8zeXLkk9DuNLMUr4B178OWr6BklXHjsCZhxk094K7i5p123i9xm5d61hTYspmdm0qBupe27drFZwBsxw5jX+xLPBw9YsUmVwThAEFrfVy4bUqpfKVUS69rRkugIES1TUBbn/U2wBbv53Dt62sD8DKwUmv93xD72eQVd2QBu8Ic08veGAwcODDOSTD2b4YOhd9+q7uubtkCy5b5W79HS2ZmsHgjVgFfTdxAVq6E44+PPXZ2tv/6li1GhBJPlDKpuN54Izgli9bGtWnRImjZMjglWFWVmal9/vnx7ZMg/MWpTfcFoJSqSfflK94YC7yttdbADKVUtvc+1qGetmOBo7zt3wKmUSfe2CNsKN5Q+zkzKcTFE8hIyqCoqgiNZmOx1zhrzZsw72Yj3LDYode90O0KwFLnwKCdxoVh+dMmpaLbK/RudULCjmdPs327ub+Acdb4xz8adkbyFd61bw8ffABnnFF/eq94iCYTjkXEG4IgCIIgCIIgCIIg7NskaFReIDXErOjNXxuxQqw4i/3XHTmJe/GUHCqbQJxo0p+I8gfXI9zAG2GbGzaXbK5dXpj9AlUuH+FMZjfocw+MmgVnFMJp22H0PBg5E0YvoHrcdp4rgs3V1WyuKGJz6Ta2lmyjqsx/tKtVq/gMgFVXB9vNhxrIEwQhIUwEzvN+Pg/4IkSdWUBXpVRHpZQDOMvbrr72E4GzlFJJSqmOmJnNfwAopR7ECDOuq6cvpwNTvYNqQiM488xgh4cnnzRpOWKlbVv/9W3b4uNOlJkZLHpYtcoIG2IlUAxYXh6fuIGcfXb49DElJTBkiHHXKCsz6WecTtOX99+HI49MTJ8E4S9MqHRfgUn5wtWpr61fqjDA9+Ggo1JqnlLqJ6XUEbEfQmg2F2+u/ZyVnBWyTlZSXfmm4k1QXQizrgR3uRFlH/8rHHSdEb07ssCWYhZ7JiQ1hR63QpfL6lKqtD0V7DHm3tpHmDSpTlhx0UWRCRADxepjxsCzz4Z/DkpNhb59Y+vnHsFXvFFduPf6IQiCIAiCIAiCIAiCEAYRbySKjC7gqvAv2zbZOD7EiitgNMrRxP9FVDxJap6YuAA5g8DagBVxBFyTDfaAgTSH1cG0ddPCN3Jkmf+jrIMhozM/b56NPSCljaM6F7vNP3CnTvFxp3C5ggftxPVCEPYYjwDHK6VWYiziHwFQSrVSSk0C0Fq7gKuB74ClwASt9eL62nu3T8DMVP4WuEpr7VZKtcGka+kBzFVKzVdKXeyN9RrQVCm1CrgBY0cvNJIBA4JFBO+9Z1JUxUqfPsFl69bFHrdJEyNm8GXjRqisjD12Tk5w2fbtsccN5Mgjg+9lvuTnw2mnwXHHwd13w513wmGHmXRdhTJmJgjxJpI0XOHqRJMqbCvQTmvdH3P/Gq+UCpIiK6UuVUrNVkrN3h7lhWhb6bbazzkpIS5wAeVbS7fCqlfqNh76BmT1Altq+J3Y0qB4GXgqAQW5x0bV132R99+vEzOOGxf9M8eFF8K0aca9IznZpOjKzDTLv/5lHLD2eXzT3JRvCV9PEARBEARBEARBEARhLyHDxYnCngFpHaB0ZV3Zjt+MZW+seALybSQ19aYASQBJoV+QxoVmQ0xi5Rjp5oA+DvjDZwZvSVUJE5ZMYGSXkRHFmLB4AiXVJX5lXTP7sNpmobq6rixwBna0hBJvxOFUCIIQAVrrnUDQqIzWegswxmd9EjAp0vbebQ8BDwWUbSL0wBha60rgjEZ0XwiBUnDuufDf/9YJIjweuPhi+PprMyM4GkpLoXdvM0vZ1yViyhTo1i2263ZuLn73F4ANG+oXQ0RKVpaZZe0rDtm8GTp0iD22L3a7sdF/661gNylfZswwiyAICaWh1F311XHU0zZkqjCtdRVQ5f08Rym1GugGzPbdYTxSfu2s2Fn7uVlKs5B1mqXWlReWb4clj5t0KSmtoc3Jxn2jIWpSU6a2js8z2z7CnDnm50EHNZwuxY+8vCAV5GDMf/A62rO8sjtplDGEmdgfdsHDmPotgp0bS3PSSd/lVZDk5kZzGPEhtS0ou0mXU7YWcvrvvb4IgiAIgiAIgiAIgiCEQIaLE0mrUfiN17krYMOEOKROCRghsSXQ0tcWuzNGWJJbxi3UzU0gw1F3HjSaz5d9TiTZB7TWfLbsM7TPBMMMRwaX9r8yyBo/EpvhSAhluS+JEgRBEKLnhhuCZxNPmwaPPBJd+pSKCvjpJyPSCEzJMmWKSQsSCzabEVn4sn59fO4z2dngCDDkWrs29rihuPji6MUxgiDElfrSfdUwEThXGQ4FirypUBqdKkwp1Vwpk7dRKdUJkypsTSIObHfl7trPLdJCp3RsnlbnFpjnLvQ6aABdLiGMfjKYGodEWwboOKS63Eeo8JpBdu5sBOQRU499VQfWM5LvGcZ07PgEDSPMOOiOLNS9sHz7MpN/bG+R0hqs3pt68Yr6lYeCIAiCIAiCIAiCIAh7ARFvJJKWI4JzJS9/GjwxJnnXAS+ZVAINVJS14TrREkdXj7HpYFH+v87V7mrmbZvXYNuF+QupcPqnuFFKcWyHkUEii3ilNrHZggUc8u5QEAQhevLy4PrrISVgcvUDD8Dzz0N5eeSxSkuN8OP00414I3Cw69dfgwUd0dAyQMOYn9/IgbUwtGkTfL9auTIx95mhQ4NFKIIg7HnCpftSSl2ulLrcW20SRmCxCngFuLK+tt42IVOFAcOBhUqpBcDHwOVa613xPq5KVyXVbmNTpFBhxRu5aXWigXSq0DXPMFk96gbrG0J73Q2VNbyq+tM8GK8ClgQ+L8WBGpen1NTQAvJEs2DbAjaXbgbghdkv7PkO+JLaGmqeGcvWgqei/vqCIAiCIAiCIAiCIAh7GBFvJJLmw8AdkLy+cD7s/jPGEZTAfBuJFG8k6ldExdXVw67g8oGX47DWTTWuclXx2dLPGmz72bLPal8KAzisDi4dcCmpSY6g97bxGFQDM6gWaLcfaJ8vCIIgNI7bbw/tXHHrrXDhhcYtoz4RR3W12f7kk3DCCVBZCe3b+6dMAdi+HXbsiK2vVVWh05gsXRpbXDDijcCvGevXN07AEilKwaOPQnoCjboEQYgMrfUkrXU3rXVnbxovtNYvaq1f9H7WWuurvNt7a61n19fWW75Ta32s1rqr9+cub/knWuueWuu+WusBWusvE3FMBWUFJNuM+MJhdZCTElr8nZOSU/scoJS9zn3P4wxZHwgWYpSuNuWu0vAC9spQbhT7tgLb7s0AU1m5d5z+npv1HGDEN6/Pe93vuWuPk9KqTqRTvjH070fyXkzrIgiCIAiCIAiCIAjCXx4RbyQSRzY0Ozy4/I9L66x8G0uNna8vjXkL1+iXURFOz2ps3KScuNsRXznoSiw+v9JOj5P3/3y/wXbvL3ofp8+LO4uycNXgq7DZgk9tZZT/bYGkpgaLN3bvjk9sQRCEvyrp6fD++8HuGwAffgitW8Pjj8OmTeZ6vnu3WcrKYNcuePtt6N4d7rmn7vpvs0GLEBO9v/4a3O7o++p0mn0F8vvvsTtktGkTfL9asiS2/tbHWWdBkyaJiS0Iwl+bgrICbF6hut1ip0lK6ItNk+Qm2C1GpbATR53TYcFP4AyT5yqkEAOo2JxYcfwepuaeuHlz8PNHoqlwVvDeovewYMFqMYKYL5cnROcTGSmtTCpTgLKNoScqjNsG52izCIIgCIIgCIIgCIIg7GEOnLdS+yoH3wi7ZoPL56Xh7oWw4jnodiXY0iKP5SqHLV8HlzdGBDGunhzDW3+AX88AZ5FP7AhHkOqLCzDnOpMypgZratzFG+2y2jGw1UB+3fhrbdn6ovXc+sOtZCWH9nQvripmdeFqv7L+ef3pkN2BQh3stLF+fXz62qJF8MvT7dvNwKIgCIIQPaNGwR13wMMPBztNlJTAvfeapUUL6NLFXIs3b4a1a8PH7NULtmzxL3v3XSNayMyMrp9lZdCpk0m/4iu0mDXLbMvICN+2ITIzg+8xS5YY4WAisFrhscfg4otN36MhrRFfhwRB+OtQUFaA8orJLRYLTZLDiDdSmtSKA9a5rJQlNSWjYj2sfRf6PxE6eHJuaAGHxwk7Z0KLI+NyDHub7t3ht99g3rxGOm/k5pp8Xo0h11/Q//GSj7EoC2mONBxWBzsrdvLkjCc5rcdpjYsbL2wpYEkCdzmUrY88pY4gCIIgCIIgCIIgCMIeQsQbiablKLA4gssX3GZyMOceDbYIRlPcVVC0BH47N3hbfXbAjSGUPbCO0zRdd4DnvAphaxEHRnUd5SfecHlcPP7b47UvfQPR3n++jOg8AoDs7ODZz2vXmtnSNfbD0ZKbGxx761bo1y+2uIIgCALceacZb3r99fCpQgoKzBIJo0bBzz/7iyymTzf3g2iorq5z+XA4/OMuWBCf22PTpv6Ckxp3kdwEucGfeSbcdlv04o2DD45vfwRBODDIL83H5TFqaoWq13mj5vu+W7uZ2/QEjtz2jhHQL7of+twTnLKxRnw+PsRzwoaPIWdQ8HNaOMHHPsw558D8+eZ++PXXRngYkQPHthDifBVwrhq4YT014ylKq0vJcGRwZs8zeWn2S8zdOpd1u9fRIbtDpIcQX5KaQ/l687tRkQ9pbfdOPwRBEARBEARBEARBEEIgaVMSjcUK3a4yM3x80R745TTYOcvkVa4PVxmUrISpx9VZAPttL4nPSE8o8YY7TnlCgsQT8U71Yn6Vbx56c5BQQ6PxhPkXKNxQKO4Ydof5rIJt4LdsiU/qlNxcM3jny4YNsccVBEEQzPX72Wfhv/8NnUIlUmqcKoYPDxbteTzw6qtQFeK23BBuN7z8MrRrF7xt2TJISgoubyytWgWXLV4ce9xwWCzmfERzvlNT4cUX498nQRD2f/LL8ql0mS/fHu0hOzk7ZL3s5Oza7/WVrkpmW9uB1XtBWvYELHvGPFNFmpdq81ehyyNNqVG+CRY/DD8Mh6/7wKR+MHUErHoVqovqbxtnTjyx7rDfeCO8qDHerNi5gqU7lgIwustoTjv4NNKT0tFa88qcV/ZMJ0KR0rLuc/6UvdcPQRAEQRAEQRAEQRCEEIh4Y09w0PWh3Tc8VTDlaJh/l0mJEpiP2VVmcvIu+y98098/nYkvVTtDizoai8VBkKiiujD2uADWgOPXruCZW+HwfUkadjEOIQ6bg6M7HB11N4e3H47DVtfXFi38t2/YYAbdYiUnJ3jG9rx50c9YFgRBEIK55BKYMgU6d4b09Ibr15CWZq7Tr3jHlvr2De2y8cILkY8D1uDxmBnQq1ZB27bB4g+XCxYtalzMUHTsGFw2Y0Z87mHhOO44uOeexqVnSU2F556DQw5JXL8EQdh/2VS8CbfXCdDlcdWbNqXGocPlcbGxZCsc832d28bCO+HHUbB5ohGnO4vN4q4IveOydbDmLXCF2R6O/Gnw3VCY2AX+vB+2/wJFi2D3Atj2A8y9Dj7Ng5/Ggie+KSTD0b49tPTqFSZPhl9+aViMHo9nkudnPY/b4ybDkcEZPc/giPZHUO2upspdxYtzXsTtSeANqT6yfKyetn4P1cV7px+CIAiCIAiCIAiCIAghEPHGnsCRDX0fAmuohO4aVjwNn7eBOdfClm9h5xzYNhXm3QJfdIKFdxmxQziqC+OTOsWRHezgUbUj9rgAloApy+4KkzolAfx31H+jbvvUyKf81tu08d8+b17jBqXCYbFARoZ/2YIFZtBOEARBiB9Dh8KKFfDmm9CpEyQnB19/wVzba0QbDz0Emzcbq3kAm80IOAJZvx7eeadx7huVlXDtteZzTg5YQ5heff55dI4eUCfO6NIleNv8+YkXCd5yC4weHZkDR2oqXHABnH9+YvskCML+y8bijbWfq9xV9aZNqXbX2dptLNoITfrCcT+BI8c8i2z/FX45FT5pAd8NNssnzYOD2bzPbPNvhqoCiFRksPgRmDYGds4wwnqtofVJ0PVK6HIZtDjSCPY9lcbZw7LnMpief37dM8w558D27eEFHKWl8Mgjse2vrLqM52Y9h9PjpLS6lOdnPc9J408izW7ObVFlEc/Pej62nURL0yFg9Z6M/CnBkwwEQRAEQRAEQRAEQRD2IgkTbyilcpRSPyilVnp/hnzTppQapZRarpRapZS6LZL2SqnbvfWXK6VGestSlVJfK6WWKaUWK6VifOUUZ7peCekdCE4f4qW6ENa8CdNGw3cDYeqxsPJ5qAyRazio7S7QcZi55MgBHSACqSyIPS54Z735HHvVrmBBR5zondubbjnd/MpyUnIY1naY39I0palfnc5NOtO/ZX+/ssCZy8XFkB+nNNfNmvmvL1oUH2GIIAiC4I/FAqedBqtXw8qV8NJLcPHFxkp+9Gj4+9/hySdhzhzYsQP+9S8j8vBlzBgj4gjk7rsjd7NwuWDqVJg926wrBQcdFFzv+++jF2+UejOxtW8fLKD444/g9C/xRil4913o1cuIYcKRlgbDhpnUNoIgCOGwWWw4rA5SbClkJ2eTbEsOWS/Vnkq6I50UWwoOqwOrxauMyxkAJyyBbteCPQtsGSblZPFys7jK8HtGSWph6oDZNvkoKJwDzoA0l64AJdyi++HPB4xA3Z4NQ16F03fC0Heg/+Mw4Ek4ciKcVgC97o7cgTBO3HwzZGebz7t3w4ABMH68SaFSVWVcoUpLoaAALrwQHnwwtv3dO+3eWicUjebHdT/y/Zrv2VmxEwC3dnPPtHti20m0NOlbJ5ypLICSFYnbV16e+b9uzJKXl7j+CIIgCIIgCIIgCIKwz5PI6T63AVO01o94RRm3Abf6VlBKWYHngOOBTcAspdRErfWScO2VUj2As4CeQCtgslKqZqT+Ca31j0opBzBFKTVaa/1NAo8xcixWGPaRmeHlKm24fmOIV2oTRxPwmbEGRCYeiYSUlibvtLsmybI2VsWO0LPnYuXFE1/k5A9OprTanOtKVyVTz5uK3WpGrVweF00erdt3uiOdl058KShOv35m8KvCxzF5xgxjdR8rffqYgcQaysrMoGHLluHbCIIgCLHRpg2cfbZZGsORR8J//mNEfL4UFMDDD8OttzacmqWyEq6/3r9s6FCYO9e/rEbcEQ0O7wTidu3MZ9/71/r15l4TiStGKEpKQruWBJKcDL//Ds8+C3feacaiahw/0tPN+tNPm5nge3j8UhCE/Yzx48azq1sb2L6D9OoKuDX0RUMBGxxQ6r0G5pV/DGcG1LUC/YABQBYmW2QRMFvDAu96/iKongnTzzLPLWXr4Lsh0Ol8OOgG8+xSmQ8LA4QHSx426VhS28CIGZDUFKyhhSb0uBVajojibERPSgp88AGMHGnuCzt2wEUXGeHiyJFGULdxo6nTUEqVSHhpTvBzVSCFlYUs2LaAvnkhrK0SSXZv44BSw9InYOBzYI/gBtdYolH9x2umgCAIgiAIgiAIgiAI+yWJTJsyFnjL+/kt4JQQdQYDq7TWa7TW1cAH3nb1tR8LfKC1rtJarwVWAYO11uVa6x8BvLHmAgFJL/YyWQfDkV8ZEUNMBPy3Ve8CFYf/Sqsj2L63age4o5z+60tybojYu2KPG4ajOhxFVlJW7bpVWZm+cXrt+u8bf0f5zLLLcGRwdMejg+IMHhw80/rLL80AVqwcdljdIFsNkyebmW+CIAjCvsWhh4IzTIayhx4y1+/y8tDbwWw76yxYtcq/fNCgYNGH1jBpUnT3g59/Nj979oTq6uDt06Y1PmYNoZxHwmG1wnXXwdq1dUKNiy6CF14wIpILLhDhhiAIDZNkS6Ll2h20LIWMENc0XzKqoWWpWZRHB1dwA3OAV4AngP8ArwLzMcINgNxcaHMStDmlLrUGGIfESX3g87bw7UDY8rV/7JoUlkd/a557wgk3wKRlaXJI/QeTAI44wrgd+Qr4Fi82Ao4HHjDpxWqEG7G4NK3fvb5WQA/mOSsrKat2sfg8t74+7/XodxQttjRI8kmXs34Cdb8AgiAIgiAIgiAIgiAIe5dEijdytdZbAbw/W4So0xrY6LO+yVtWX/v62gCglMoGTgKmhOqYUupSpdRspdTs7du3N+aYYif3SBj6dvQCDmsq5AS87CvfFAdBiBdbwAhS+cY4iTfyCEoZU7El9rhhUEpxw9AbSLWZl67lznI+XvJx7faPl3xMmdNMA06xpXD9odf7vUisoVev4NlnX3wRH9v5/v2Dbfk/+ig+whBBEMKzL6X1Ukqdr5TarpSa710uTuSxC9GTlGRSrIRCayPMWLy4Lm1JDR6PEW7ceit8/XVw2379QosYXnihzq0iUoqL4X//M5/btjX9CuTzz4PdQyJlVxSayxYtjGjjjTfg1VfhH/+AJokx3RIE4UAlN3fP73PoW5B7jL+Aoz60G3KPhdR2wYL1UNhCP7tVV8OSJTBzJvz6K8yaBevWhRfzud0mHdgnnxhhxqOPwuOPw/PPw5QpEPioe+ml8M47xmkjKSl0zLQ0k1YlWl6a81Kt22Feeh7Ftxez+7bdtctdR9yF3Zs+c8LiCXj0XlCuNx1Y99lTBfNuDZEapx5FZqRE87u7N37fBUEQBEEQBEEQBEHYZ4hJvKGUmqyU+jPEMrbh1iZEiLKGpr3U20YpZQPeB57RWq8JFUBr/bLWeqDWemDz5s1DVUks7U43KVTs2aAiVAEoqxFWDHreCEB8cZUF512OFnum/3rJKuIyEyklD7x5j2vZOTOhNhPn9zu/9mWgW7v5eMnHaO9I1kdLPqrd5tEeLux/YcgYdjt06+ZfVlxsXqbGSt++wcKQKVPCv0gVBCFu1KTl6ooR+d0WWMEnrddooAdwtjdtV9j2AWm9RgHPe+OASet1ENAfOFwp5SsD+FBr3c+7vBrnYxXiyPnnQ2Zm6G1VVcad44YboLDQCDaqqkwKlMMPrxNVBHLwwf6pTWr4+WfYubNx/auqMo4dYAQhXboE1/n+++juM263cZ4SBEHY42zbZtRovksggdujHQCvaWexwfBPTaoUawpYAuzyrMnGwaHLlWD3uv11vaLRqTecTvjsMzjlFJPuKi3NOGRceCFcdZURvPXsCamp5n5RVAQuF3z4oUm7lZJiBOF3320coObOhT/+MILw884zqcKys027Gk47zQhCLrnECOySksx+HQ4j2njzTZP6KhrcHjcvzXmJanc1FmXhlO6nBNU5ufvJJNnMjajUWcq0ddOi21kstD4ZrGl166tehF2z69KbuipMepxYieZ3d1uc0pYKgiAIgiAIgiAIgrBf0ggD7GC01seF26aUyldKtdRab1VKtQQKQlTbBLT1WW8D1NgxhGtfXxuAl4GVWuv/Nu5o9jCtT4CTVsKM8yB/GniqQbtCVLSYmVlZvWDYBEhrB0seB2Xzr1+2ARzZsffLkQ2+OpCSVWCLcMZZfSTngidAqbBzlnlB5ggzEhYjOSk5nHzQyXy85GM82kNJdQlLti/BarFSVGXeYCoUJ3Y7kaapTcPGGT7czKb25cUXYcgQyIgyNbLTCc2amRexvrb25eXmhevw4dHFBTPrO9CCXxAEP8YCR3k/vwVMA24NqFOb1gtAKVWT1mtJPe1r03oBa5VSNWm9fgdq03oppfa9tF5CRIwYUb/m0OOBV16B118343+VlQ27VTgcxiVj7drgbY89ZpZIrunl5WbWtW//DjkE/vzTv9727bBmjRkEbAxlZfDpp3D55Y1rJwiCsFcINwDua3UUaiA9Ly/YDqk5cBgwCEgDioAZlfA7cPDzcJ33Ip3SslFd/PprIwqsqoLOneHee+HYY6FVK/N84PGYdFVKmev2hAnmntK7txEJ5uUZR6Nx48BiMW1quq61ec7Ytg2eeQayuudBfp0YoRnwrHfJpwUVVSm0oIDUuRVwhrdSfr5RdzSC71Z/h9NtUsik2dM4rcdpQXX6t+yP1attLasu4+kZT3NMx2MatZ+YyTsWCLihTz0eet9rJlrs+B1mX7tn+1RDnv//VcTk5orwQxAEQRAEQRAEQRAOABKZNmUicJ7383nAFyHqzAK6KqU6KqUcmBnLExtoPxE4SymVpJTqCHQF/gBQSj0IZAHXxfdQEkRyMzjqaxjxm5nVldLKiDIsyeano6mZwXXMZBjxuxFuACTlBM/+Kl4Wnz4lBTiRuErAHWJKcGOxJgfnfi6cDyFSlcSTGw69gRSvLbHb4+bzZZ/z+bLPcXvcAKTaU7lx6I31xhgxIlik8dlnsaU3cXl1N336BG97+unoLe0BrNaG6wjCX5x9La3XaUqphUqpj5VSvuJEYR8jKQn+/veGr7NuN2zZEnmakf79Q5e/844ZkIsEpeDll/3LBg8OTs8F8OyzweldGqK62rhDCYIgHNCEGjTfjnkSvQu4HrgX+BYj4igHSrwX1MpQcxW8fJoH41Xt8uVNJ3HGuHJ27IDrrjOufueeC+3bG+e/tDTz/JGSYq7jPXoYocfQobB5s3HjmDsXzj7bCPxSU43DRlaWWbKzjTiwXTu4774wx+UllwI6sJ5UAp75onAveWrGU5RUm4ckp8fJ8PbBinSLsnBC1xMA0Gi+W/0dO8sDrKZCCWtWvgBr34Pdi4IdHRtLekdwBOTw0i5YeBd8dRDMuMA8BwuCIAiCIAiCIAiCIOxhEjly/ghwvFJqJXC8dx2lVCul1CQArbULuBr4DlgKTNBaL66vvXf7BMzs52+Bq7TWbqVUG+BOjL39XKXUfKXUxQk8vvjRpC/0fxRO2QRn7IZT1sPphXDadhj0P2h2qP8MsLSOYAlIt7J7YewvsQCyegSXla2PPS5ARnf/9ZKVkeWEjoHBrQeTl54HQJW7ivGLxvPeoveoclcB0CKtBYe2ObTeGKNG1YktavB44JZbGj/4BWYA7PPPzefTTzcvZX354gt/N47Gxn7//ejaCsKBxH6U1utLoIPWug8wGePkETq4UpcqpWYrpWZvD0xiL+wxrrgi/umtDj88dMzSUjMTu6F7TVmZcd3YscO/vFcvM3gXyHvvNU7oV1lpHKcSmOlMEARh36CxgoUNQM1j2aqXwBlmwD8gBcfVb/6PiupU+vSB224zYg1bA49FU6YY8bjHA88/b8Qd9ggycKalEV0amUa20VqzbMcyrMqKVVk5octoHNt+gPl3wveHwUdN4IMU+CCJ84s+xQrYlKLaXcWqLb96U4ZMgR9Hw0dZZkpGDdk2WPkizL3RxJqQCpU7wnUlMtqeZlKT7muESrUSKGYJtV1cNwRBEARBEARBEAThgCBh4g2t9U6t9bFa667en7u85Vu01mN86k3SWnfTWnfWWj/UUHvvtoe89btrrb/xlm3SWiut9cFa637e5dVEHV9CUMrkTk5uAfb0YMveGjK6gMfpX1a8FFxloes3hsyDwRqQJqVwfuxxAZofFlCgoeDn+MQOg1KKmw+7mTS7yWm8atcqVuxcAXhdNw67ERXuPHtJTobRo4PLx4+HVauChR0NUVkJN91kPp94YvC7OLcbHnzQDMY1lpq2gvBXR2t9nNa6V4jlC7xpuQBiSesVon2j03p573VV3tVXgEPqOaaXtdYDtdYDmzdvHq6akGD69oUBA8LfoqPhyCNDiywA/vMfWLnSXN9D4fEYl4977gne1ru3uecEUlxshILhYgaidbCrhyAIwgFJqIHzQHy3FWrofKYRAWz9Fiq2gifExTXZXwiRbDcX54qKyO8nzZrV1V21yrRN2HFFIQZQSrH62tUU37KD4lPuYYKaDNPPhlWvQFIz6HEzDH0LDn+f4494mpLjzqWo30GUdktlSNMO8N1g+HmseT7schGsWwiuSqgugfwdcPwvcOpGOGEJHPKscbGMhS6XBrtZCoIgCIIgCIIgCIIg7GUSm7NCSAypbcATYM2w43ewxmEqcEbXYFeP/KngjMJiIpCmQ8CW7l+27r3wM9TixDm9z8GjvdOFFSjv5HiP9nBun3MjinHhhcGpU7SGk05qnMiivNzYG2/xDud27Bg6lfSLL0Zut+8b+403YO3axrUThL8g+0xarxoRiJeTMS5Uwj7Os8+GTkcSLf361S/OOPNMM0gXyvmiogLOOAOczuBtTZp4Z1yH4OmnIxv483hg9mzYuLHhuoIgCHuEUOKIDR/D1u+hdE3o7Ymk9z11IoBpo6F6B7gDntXGbYNz6gQT7175D9KTS1i5Ei65xHyPLy+vfzdHHw2nnmpSpFxwAcycaZyZ6hOSl5c3UuQRIw40qT8eS+rSR7BYbDDwGTh1PQx9Bw6+BdqfCW3HQddLSRn8HKlj/iB1xE/w69/MhIGk5jB2LfR5ELJ7m+dbezo4ssCeaZ5T09pC5wtj72x2L8g8KLK6yVE4lwiCIAiCIAiCIAiCIESBiDf2R5Ql+AVSxdb4iCAyuga7emyfHp8pxk36B5dt+Tr2GU/uENOKfchIyuCsXmdhs9iodldT5a7Coiyc2fNMMpIy6m1bw/HHhx5Y27TJDJpFIuAoKzODZZMm+ZefdlqwfX1VlYnb0EtcXwoL6xw9BEGol30prde1SqnFSqkFwLXA+Yk9dCEe9OsHI0c2LvVIIL6iCqsVDgs0p/Jh1SoYMsSI82ruCxUV5h40fDgsWBC+7cEHhy6fMQN+/TW06MOXykq4+ur66wiCICSc4uUw71aY2Bk+TDZpNGrISTXpNta+C7+cabZX7sH0Ylk9oNs1YE0z4pGve8Gmz8BdAdXF5tnKXQXVRbVNBnWezbS7jqJfP/jsM+jSxTgoTZ0K+fl1zx3V1bBmjalz+eXw5psmzYrFAiefDMceC889B3/8Abt3m2t2ebkRin/zDfzf/0HnznvuVDDzEuMIqd1w7DRofzZYU4z4IjBdpj3dCPu3/QBl60C74KivwJFj3CjrI3CyQbT0uDV4ckHQvpKM+EYQBEEQBEEQBEEQBGEP0EBmXWGfJb0zVGz2L9vxO7Q5Oba4qa2DxRslK80LuFjJ7A6eKv+yqp1QuACaDY4+rg4xFTmA6w69jg8Xf4jLY6amJduSuf7Q6yPehcMBF10EL71kXqL68sMPRtzx1Vfhc0+Xl8Mtt5j81IGMGwevvmpyWPsyc6Z5GXvlleFnTtdQVlY3M1sQhPrRWu8Ejg1RvgXwS+sFTApRL2R777aHgIcCyjYBIRVwWuvbgdsb0X1hH+GJJ+DbbyNPPRJIz57+66ecAtOnh7+OL1li2lxyCXTrZoQcL7/csHhw1CiYNSu0SOOii2D58tD3LTCxX3oJFi5s8HAEQRASg8cNc66DNa+BJRl6/x90/AeckQIelxG1K6t5VtEesFiN60VSzp7tZ79HjKBg2VNQtQOmn2VEAa1PhNS2RphQvNyvySEd5zLvjxIWTJvLhx94+H1yc956pRW7SjKxWd1YlMajLbg9Fto0207frpuxWgdy991GsP3FF+Y55LXXjKDD7TZiQK2NG0eTJtCjB/zzn3voHHhcsH68+b/o8HdI7xSZM2TF1rpnxNT2wSIPgE/zoDI/oNAC58T4jNrmVJh7I7jqcZkM1Z89gNZGuDN3rhFp+mbGPO00SE83S9OmRlQ6YAC0b9+4ORcej3nmXLDA7Ku01LTPygKbrS6W1uYZuKjIlDVtagRHgweHF4kKgiAIgiAIgiAIghAdIt7YX8nuDdt/9i/b+h3kHQe21OjjKguk5EF5gD/6zlmQF3KsMnIsNsjsAbsDpggvecTkP7ZH5oIRxK450OKIeqv0ye1D5yadWVSwCIAO2R3ol9evUbu5/XZ45ZXQ237/HXr1MnXO8yZT0BqSkuD77+GBB4ztfCiGDjX1AsUbYAQfNhtceml4AUdpqbFQ/u23Rh2OIAiCEAOdOxshxWuvNc4lCYzl/Qsv+JeNGQM331x/u6oq+N//Grevo482QpNQ4o0tW8x95vHHg+8xTqcZpLnrrsbtTxAEIa7MuwXWvG5SRo6eC2ntjZNDfeyNJ1yloO+D0Pxw4xBSugrtqUat/yB8G0syfNKcvuld6HvLFdBqJKRlUFFWSVmpxuXUOJIUmVkWbPYmULTF2HPcfz8pmHxuZ3lDaaCUdCqdyVhxk0IFKTsq4WfMcneJGelP6DmwUKtVdVeFrxdSiOHlzweh113GlaNBGhbwN4jVAcMmwNTjjFNK0PY0OOSZ2PfTCLZuNffmL74wKTZPPx2OOQbcL+di3Z6Pzs1l/HgjpigthT//hF9+gSOOaJxwY+lSI/iw2+Hii+HJJ83zaI0IyGLxF2+43UbskZQEKQ38CQqCIAiCIAiCIAiCED2SNmV/JatH8IvLgp+Iy0usjC7BZZsmgquRo1O+OL2zmTr83VjP+rL5C3AWRx930b0RVb35sJtDfo6Uli3h3HPNC6tQbN0K114LzZsb+/ujjoK8PBg7NrxwA8zLsX/9C5KTQ2+/4Qa44w4ziFYj8NDavKxbvtzYJU+e3OjDEQRBEGLkySdh0KDw94VQpKQYx4wBA/zLO3Y09494M2iQsdEPxwsvwK23+gtQyspg0SLTVhydBGH/QSk1Sim1XCm1Sil1W4jtSin1jHf7QqXUgIbaKqVylFI/KKVWen828dl2u7f+cqXUyIQc1O4F4C43LhYZXUMLNz7Ng/EqYIkhr5WXeVvnceSbR7LNR9y2OyuZdbvXhW/UajR/DhrPNeooHt5RzZxK2GnNxpXWCZoeCgOegnEFkHMIoCGlJYz6A7peap7BLHZSMtJp1jKDvHaZ5ORmYEtOA2uyaXPffeZBwHfBSCYyKKU5O8jRu0jRFf510tPNz8odsHsRbP0huO/rJ8DGT2HTlyZtZukacDXiJqAs0P06sKbCpk9h16zGPT9aU2HpozD/VqjebdLM1IhAxm2DczSc5Yo8XqQ0Pwy6XGb2H9ifZodCpwv8irXWLNuxjMemP+ZX/mfBn2jv/0e0bNgAXbvChx+aFJq//26EHMccA9aCbaA1ats2kpKM42PLlsYB8o47Gv8dwmYzvxYejxGHut0am1f45PEYsYbv4vEYMYdF3iAJgiAIgiAIgiAIQkIR5439lczuxprXd4ZQ0WIjZmgob284nKVmllOTQyB/GmYOl5dNn0L/R6Lvb43dbJtTYNE9/tu0x7ykG/RihLOsvHjcULIC8qdGVP2Mnmdw0cSLAPhbz79Fvh8fHnwQ3n23/jrV1bB4cePiXnopPPRQ+O3PPGOs6888E/r2NQNx338PP/8cvo0gCIKQWGw2+PJLOOQQYzfeUAqV1FRjdf/3v4fefvrp8PTT0adiCUVSEvTuDXPmhK/z3HNmgOi22yAnB6ZNg0ceMbb7giDsHyilrMBzwPHAJmCWUmqi1nqJT7XRQFfvMgR4ARjSQNvbgCla60e8oo7bgFuVUj0wxg89gVbAZKVUN63jkWvRh74PwY+zwFkCMy6CQc+bZ4cGnxmiF7R/suQTzv/ifEqrjfi89S0WUu2p3vVKeLojLdJa8M3fv2FAS6N/8Xg83PXjXbw27zUKygoASLenc+fOUmA3sJsuTSzc3yqXs5Obg7IDqi7dS6g0kPWlCtHapBpxhcidVbrG1FMWUDbY9DmsehnK1kGfB6HZUMjuA7m5kO+Nn5sL7c80/XCVmdQvKa0iS3viS/9HoehP2P4LTBsDPW6Dg7ypKpUVbGlGiOFxmv183KSu7dHfwtzr0WvegHXvoZr0h5wB0HQQ2DON+0rRUv/9rRsPVbvMdkIIJ9a9V1esXdQ6gzhLqFbJLKl2M7tK8fr8GRxZZeX/shTKkoRdaTydLsI+4AlQiuKqYqasmcL5n59PcXXdpINz0yCvDLalQe8XegMmPec7p77DcZ2OIzs5u1Gnr6jIOF85nUbEoVRkAtFwkwDqo2uHUgomP8HiXxeycENPHrt5DPkVnXGSSWaWDWWxGKGGBo/WuJ2akmInKZad3P94a9LSG2HzAeZ31lkElQXmp7PMmy5HmZ3gMZ+VMj+1Aluyced05EByCyNiEgRBEARBEARBEIQDHBXr7JD9nYEDB+rZ9dki7KtUF8EnzUEH+KAPeAq6XWWEHY3FXWleiGz6En77B7gC3DBOWGwcP6Jh1xzvDDPgszZQsTm4zrHTzMynSPvuKoNv+kPJSjMTKwIumXgJbo+b1095PbJ9hODFF+HGGxtvkx9I4J/exRfD22+HtraPNbYgHAgopeZorQfu7X7sC+y3964DlM2bTd73wsLwThWpqUaA9/rr4W3N58yB4cPjf3/597/NZO3q6tjihootCEL97Kl7l1JqKHCv1nqkd/12AK31wz51XgKmaa3f964vB44COoRrW1NHa71VKdXS2757YHyl1HfeGL+H62PU966S1WZQf+t3kNIa8o5HtT0FsnqBLcW4+nmqjKj983Z17UI9H/hcgNes1jgcRrdgt8O63eu4+Yeb+XjJxxF1y4KFi/pchbWwGx9vfZwdrg0RteudfTj/aHspJ+gv6F71Ne6Utji6X4pqNQoyugFeMccXnaCqwK/t6mozzG3tfD4dhr2OUspY/fmKMLZto7S6lG2l2wBo++MRJFVtw5PWBcvYlaaeu9Ir7rCbcxIgFNEaplYoUkdOp9xZTou0FmQlZdGuSXu//qzcsYId5TtwepxoremQ3YH2We1g/Ycw/zZ09U7QFlRmZyPCSG1rnvWqC6FwHmz9nrnre3LIHX8C8PHHcNpxy4z4Y/uvsON3qNpphBvKZsQfVdvNeg3ZfWHM/Lr1mvORmwvP43dcPxQ0Z0TR9rD/N3lW6O6AjS5YU88zWbem3eiY3ZF0hxERlVWXsW73OpbtXOZXb+lVS7FNP4vUogW0tFlQ57iDvwRozebizVS4KnC6nayb34GrL09h61Y46yzNP/8J/fsrkpPNc6KvA4bdbtwY58zRjBihzOQGd5lxLHFXmncFGvyFLV6BROF8+GUcYIF+D0OPW8xmj9MIbZTXYiNcmptOF+JscSLlnlzKyq1UVyujKdLmp1JgURqLBdIsm2m2dJxp1/ch6HkHbjfs2mW+m7hcZlHKHJPNZr43ZWZ6T5f2GBcXd6X5O9cuc0y1oqca0YfFCI6sKSYtkXaZNp6qut8ZrX3OhzLaEWWFrd/DjhmgrLhbn0lZVQqlZVacToXHo/B4TWwsCiwWjdUKaalu0lMqcBROM2lnLane86hBaWrFQnj/D7S3n8pm9lkrWrGCrvYKuQL75xWzWBw+qYmUOTbt8grA8O6vZle+7Wzmb86SZN71RCjIkucuQRAEQRAEQRCEvYeIN/bnAbAvOkDZev+y7D4w4jfzYquxbJ9u8jRX7YTPWvm/FAPoeiX0e7Rx7hhgZsrNuRYOfcOsz7kBlj8DBEzMS86Dk5Z7Z041gKsM5t8OK5416xGKN+KB1vC3v5nZ1vVZ0UcSx5f16+Ggg2KLGS62IBwIyEvEOvbre9cBSkWFEUg884xJh1VaagZW0tPNAMQbb8CoUQ3H6dHD5KGPhcB7wPz5cMQRpk+xIvcXQWgce1C8cTowSmt9sXf9n8AQrfXVPnW+Ah7RWv/qXZ8C3IoRb4Rsq5TarbXO9olRqLVuopT6HzBDa/2ut/w14ButtZ/yQSl1KXApQLt27Q5Zvz7g2aUBvvgCTjnFfP5pcjHDu02B3X+agf/iZeAqMYPNFrtxHyxdawZqk3P5//buPD6q8uz/+OeamexhJ+yyCRUF3EDcFUUFccG6YmvFpS5VK+rTX9X2afGpP/rDtfqodV+oChbFhVILCrUqrQq4oYAIKiA7YZE1JDNz/f44ExKSyQphSPJ9v17zmpkz933Pfc6czD055zr3FT9nFTNmwKuvwrvvBoF289a3o3VsNRsy2nLZ4FVs3QqrVsGaNcChz7L+8N/gHqd9szzuOuZZjuhwBE2bBjMbhELB+dDJi97g1ndGsj26HeIh8he3g6z15OTC9ScMZ9TAUWSnZe8SRPD9glmMnDKSj1d8vHOigaWblpJhcHQmHJkJvdJh//Qw+2U3JzOSRTiUTlGsgC1F2+gS38iaGHReDGlmhC3EiAPP4tETbw0COCyRJmbRE6xc8CSHLYWtcdji0MzgsEzolwF9cptzUF5v2jfrQnZOe8KRHEKhNHK/uotQtGSQKHRYE4XcEKTvfzlZ/e4L+t25F7Y6CCjxtm1g6YJSn5bzwQdhnh9bxMx3V9DvxM4cf8g3HNJ5Np3S3iV3x2xCvhU8hlsmheldydg6i5lrsjj2ubvBjbOO78Y5J3XGPEKIMJFwcY6OYKM5QdqSaCzGDV90Zb+MGK3D0DazCR1y8miZ2YTstFwioQhhC3FV4b/JoeR/2hcWHMrPogthTW8GHt6Z8/qdSL8O/Wh+ylmwbh0AW9u24NOxd/H+kvf5ZsM3zM+fz39/dSH9u39Ek5bNOeTi+wiFMkpOjhf7+hH860fYlhgnH9gA/72+5OWwhWmd3Zov/pBP3ubg/+A1uUb7/2PES828smn/4P7b6PnMTZ/Ahx8aM2eWBGuEQomJVzzOjk2fQ0E+o8+9k66tVrDqh3asO3wG0WjJBQHF5aEkbiS28FlCO1bQJLKS9n360yZjHi2aFZKVk4mFM2HQ/ZC/GVo3hUc8+DtLuPQv9/D8Z6cCsGJhG9o3aZ/0b7c4vUxhrJDY9gLmjl/Mq1N7kL+tC0cc15wDeoXZf39o2wbS0iEScTzuRGNB+rZl38Ph60+kmX/Bmk3t2HDcArZuDVK8FK9PcVag4mCW+Ce3kRP9ktzwStb80IZN3e4k0qb/znLhJNmU4ktexXds4KGxvXj/q2PJy0t8H1TD0i8+4+SzCojGI1x4aQ9+cWXzIDbDSm3vRKBJQXQH24q24u4c9ml7CqNpfLf5WJYf+A6rVgWzrhR/x8QTMRyhENiiPxPdvIIWkYW8/NGFuBsDf3Yuhx1Wqkzi/eLxkrQ2XrAejwfvvWR1W159NVj/m2+GY4+tet30f5eIiIiIiEjqKHijPp8A+2AEfPeX8svPWhjkTK6Jos0w8xo4dlzwPNnsGOkt4JxlEMkuX78y0a3BFTsXJg765M+Ef56cfJrfNifAiX+vPEAkujW4muujK0uW7cXgDQgOKPXtC4sX1+5EVnZ20EZZv/sd3H//nr/qWqQh0EHEEvV67GrgVq+GKVPgiy+C7/oTTghu6enVqz92LNxww+4FWpQdA+JxaNECNm1KXn532haRyu3F4I0LgMFlAjAGuPsvS5X5O/D/ygRv/BroXlHdSoI3HgE+KBO88aa7T6yoj7UZu959F4YNC046/ulPcPrpJSejw+Fdv5OKT3oCLFsGZ50VzIh09NHw61/DMccEaanKpqYKh4M2r7sumAUPghkBWpTK6BGPl5xQLT5RXHyStEKlZ1io4MszGo+yfNNy1m5dy5IfljD4uMvI3RAMADtat+DrL9+lXW47WmW1IhQK8exnz3Ld5OsoiBWQFkpjYNeBDOo2aGd7BdECHpr5EOu3rydsYbo078L0S6fTpXmXpO9foW0r4fUOweNe/wWH31u+zJw74Mv/2XWVfxqs5wknBJ9ddRRv073mjjuCaMuaGDUqqFdDKzev5MEPH+Su/9wFQJMQtAlDukE6kGZQ5FAIXNXvOob3u5EDHu3N5liMCMZpXY/n1bMeISOSXhKgA/zw5d2c8u4TfLYDokD7yU+xcnbwv/EeGacr2XfPemQkk/P/l1A8k7RwiP8+6AWOa/3jXYIIovEixsy/knfXvkJRfAfxLy6EieMBmDgRzj23et04oN98vl69iewc+HpWJzo27Zi0XCwe49NVnxKLx5j/aRqXnx2kM5oxo3qBCgC//S28/DJkZcETT0CrVsHyrke3I5IfzDwSbd2WpR+t2vld88rHU7lt/hCIhwmHQjxyxkNc0/+acm1/svITThp7EtuLtlNUCPu/+jnffdWLfodHmfpWhCZNgs1cUFD8HVa8/X1n0M7dr73GqLmXAE6TrCzGXfAXzvzRmeXe699L/835E85n446NGMa9p93LdUdcV72NUIr+7xIREREREUkdBW/U5xNg3/4FZl8P0TJneDpfAEc+HeSHra7tK+H1/eDiRIL7f/8ElowvX+6w+6DnL4Ipiqsjug2+ug/m/L4kwMIdJveCzV8nr9P8EBg0PZjSM1IqiCMeDWYDmX8vfDFq1zp7OXgDYNEiOO644OBuTVKdZGfDiy+WXEVYWlER9OkDX1ewaarbfrLAEJH6TgcRS9TrsUsqVVAAeXl7NngDYPhwmDBh90/qNPKfjSI1prQpJfbk2FUcTBGPB8EYxQEYoVAQuHHQQcHv4Z//HB58MPh9XB3uwW/7lSuDwI+NG0vSOZQO3giHg+fp6XDqqRUE6FUjeKPSOhXUm/z1ZM4af1aVTeWk5bDqV6t2pvbYG+bPD8aaGTOgUyfo3Dm479IFcnKC7RQKBakyiopgxQpYujQIrmlw3IP0L9+9AOtm4tmd8Ka9iDfrA9kdsXAmFsrAPIrFd8C25bDhc6bnHstFr/+c9duDaTuaZTTjiI5HEAlFANgR3cGHyz9ke9F2DKNTs048dNRkln/al5Urg309Nzc44X/pr9uRtSkIPNjerC2THl9FPB5cKFBUBD/7WfC5lFPJvlsYK+TOd+/kjzP+uMuMIRVpmdWSJ05/lqsn3cDW7TuIx8P0j1/PTzrfygE9I7RpE+wXaWmwZNN33PbB5Xy7aT6xuMHGLvyQO5OwZxC2CCOaPcuxLS7YuX6hEGyNbeAPC8/mm22fsMO3gYeYctr35HoHNmxIzFISh8GXtSNzY7AtCpq3Zepzq3aunnsQGJaZWcW2KLM9YvEY//Pu/3DPv++hIFZA2ML069CPXq177SyTvzWft759i2g8SnoonRM7nca8cZeyfMtyunWD1+4/iUPaHbLzMym9uVdsWc6kha9gIScjHRauX8gTHz9B1KMYRsuslrTMbAUYDvywYyP529bgOGGLcO6B5/HI0IfIy8mr8nMqv9r6v0tERERERCRVFLxRn0+AbV4Ebx4CsbLTNBictQiadK9eO0WbYdZ1sPiFkiCIb56F2b8McuaWlt4Czvm++mlZijbDax2DqVZLB1h8OzYReFJBlEEkF7pfBr1ugaz2Qa7aZa/DvLthU5L55FMQvAHB7LpnnBFcYV3VbBlpadC8Obz1Fhx6aMXl5syBo44KpuCvje7d4ZtvaldXZF+mg4gl6vXYJVW65RZ4+OGaBQYWC4eDE41lvfdeMF7tbuqURv6zUaTG9mLwRgT4GhgELAdmAT9x97mlypwB3AAMBY4E/tfdB1RW18zuAda5+xgzuw1o6e6/NrPewDhgANABmA70dPcy81qU2Ftj1+zZcOKJwW/zRx+Fyy+HjIw6fMPazOQAQSerOz1FscQMEB9+/yHD/jqMddvWYRjXHXEd7yx+h7lr5xK2MKf3OJ2JF03cecI/ldyDcak4lUc8HvxfFIkEt2SpLBqEmdfCt8+ChYLZK0MZQXqfcKmd8dV2ULC6TMUQ63+8lo73d6QgWnk+zXY57fh25Lc8+NGD/Hba7eDQvABe+yuckCRD0bOHwi/OhKLErDFv/r05g2dvKF+wGoFHE+ZOYMRrIyiIBX3MjGSSm5bL+oL1O4M6ujfvzn+u/A8tslrw+OzH+f07v2fjjo2VrlOxYzuewN2njeHdpf/iN9N/U606ffL6MO68cfRt27fydapkvWpT7/nPn+fS1y+tsqmzf3Q2rw9/nb6P9mV+/nxCREi3LEblzSVte0fC4eDtYjEojBdw79ZDWB//jjgxMiyHJSOX8f7ytzn/5fOrfK8HBj/AyKNGVm8dk9D/XSIiIiIiIqmj4I36fALMHV5utksO2p06nQNHP195+pFiW7+HSV3B4yVBEJu+hn8cliQwBOh7Bxz4f6pOnxLdCl+OhnmJC/5KB1jECoOgjsL8qvtXHSkK3oDgQOSttwYHh8Ph8ifGMjODj2rgQHj++eCK6qrce29wbLam6VNyc4Mr3Q45pGb1ROoDHUQsUa/HLqnS4sVw4IHBLBw1lZWVfOxwh/32g+XLy79WE438Z6NIje3NscvMhgIPAGHgGXcfbWbXArj7Y2ZmwMPAEGAbcLm7z66obmJ5K2AC0BlYClzg7usTr/0WuIIgc8NN7v6Pyvq3t8Yu9+B39H33BVfmP/YYnHce7NgBTZqUT3cSiwW/3zMyKrjyfh+1pXAL5084n7e+eQsn+HLOCGfw1FlPcckhl6S4d8K8e2HO7yCUDsdPhDbHBRckhNJKLoSoIHiDnwQxUC/OeZFrJ1/LlqIttM5qzdairWyPbqdVViteOPcFhvQYAsC6bev4rys78WLPAqJhwCE9FtyKFUQgGgIM0org9hmQGQ8COczhkjnQbWPyVflXV3gvkXnngHy4KL8trFpF3OM8PPNhbpl6C7FScVvdm3dn/PnjGdBxwC7tbN6xmTPHn8mMpTN2Bni0zGrJ1sKt7IjtACA3PZfRJ4/mxiNv3Flv1vJZXPDyBSz9YSmOk5edR7fm3Zi5YiYAaaE0Lj/0ch4941FCFeUzqsPgDYAlG5dw8SsXM3PFTGIe46KDLmLi/InEPEabnDaMP288J3U7CYC1W9dy9NNHs2TjEuLEaZ/bnpuOuolwqdQ4478cz2erPqMoXkSzjGbMuGIGfdr0ASDucZ7+9Glu/MeNFEQLSA+lUxgvJGQh/njyH7nl6FtIC6dVb/0qXG393yUiIiIiIpIqCt6o7yfApp8Kq6clf+3EydD25MpTnES3wT9Phfz/BM9LpzZ5pQUU/VC+TigNTv03ND941yuHSovtgHUzYfpJUHwgp2yAxYJH4LNby8/uURspDN4otnVrkCf3z38OpmuORqFlS7jkErjiCujQoWbtPfRQEBRSnRk4zKBZM/jXvxS4IQ2XDiKWqPdjl1Tp8svhpZdqFsCRng5Dh8JrryV//a67ggvEaxMUUqyR/2wUqTGNXSX29tg1e3Ywi9Hf/hbM8HDiiXDkkdCqVRDE4Q6bN0N+PnzwQTBDUf4eiivfW+Ie57Zpt3HPf+4B4MMrP+TITkemuFdSbNPqNUydMIdZHxYyf3FbLLcLrdo1IS8vTDjNCIeNWMyJFTn5+THyV27B01vRqxcMGACDB8NWW8nwicN5b8l7AJzb61yeHvY0zTObl3u/x2c/zi/+/oudwTzJpIfTeefSd+jdpjc/GtWStVlxzCFvG3z6GLQvcyHCtG5w9k9ge2ISl9MXwZvTguCNYkt/WMqgsYNYtGERo04cxW+O/w3p4WS5hAIF0QIen/04N029aeeyYzodw/2D7690/5327TQufe1SVm5ZuXPZNf2u4a5T7qJZZjMA3J1NOzYBEAlFyElPBMokCcIoihWxrSiIeM2MZJIRSXJsowZBH+7Ogx89yM1Tb9657KLeF/H02U+X9CMhf1s+ne7vtDNopTKzrppF/w7lh5H8bfmMnDKScV+M4/jOxzPuvHF0atqpyvaqQ2OXiIiIiIhI6ih4o76fAPvmGZh9Y/IAiHA2nP4p5HaHZFPmRrfCxyPhm6dLlpUOgvjwCvj2OUh28CejFQz9AjLyyrcdj8L2FfDmwbsGf5QNsIgVwt8Pgi17IMfHPhC8URdefBGuuirICx2rYBLqrKzgAPSMGdCz597tn8jepIOIJer92CVV2rwZevSANWuqX6d5c1i0KDgxmczatcHsGzuqPk+QVCRSu1QuIo2Zxq4SqRq73IPzzN99F9xWrAi+B82CoLeOHYO0g926QZs25c/V1gfvLX6P7i2777ETt7L7nnwSbrop2Mf+/Gc499wgeLJ4vwuFglkbY7EglUxhYbCvNm2aLF7Aue+D+2iZ1ZIrDrui0veNxWM8+cmTjJwyksJY4c7lbXPa8uywZzm95+k7l+Vvy2fIC0P4eOXHAIQsRIvMFliiA9F4lI0FG3eW/+WAX/KnwX8iHCqf68bbtcNWJ2YRabtrcEdFalOnMFbI9tbNabZxe9J6M5fP5MinjiSS+N/5yUlw2efl21mbDYdeC/nZUBiBQ1fCnLbBayd/B289D8m+CsYeAlcOC46QGPDNi63psmjtLmWK2rQmbe26Ktfrm/XfcMSTR7CxYCMhCzGkxxCaZTTjr3P/SsxjZIQzeG34a5ze4/Sk9QFo1w5quA2rQ2OXiIiIiIhI6ih4o76fACvIh9c7Qrww+evZnWDg3yGne0kKlXg0KD/3jzB39K7lSwdBrJoO7/04eVoWgOzOcNRT0PqYIFAEgjQrq9+FmVfD9jJzsycLsNgwB946CmLVmF6iIuEsuKiG+UXqka++gtGj4ZVXgoN827cHB/oyM4N80b/6FVx3XXDSTqQh00HEEvV+7JJqeecdOOOM6s3AlJ0N48bBsGGVlxs6FP5RaWKDilWUkkVEKqaxq4TGLmlMLrkkmJUxEoH164NZGbOyyqftKS0er/z1mli3bR2Xv345f1v4N35/wu+5/fjbyYyUzwu0rXAbBzx8AMs2L6u0veG9hzP+/PEVF6hNWpI6SGUSi8e4ctKVTJg7ge3R7WSEM3h46MM7U44AFMWKuOpvV7Fo/SLcndY5rRnz+jauH7iF7WmQUwj3T4GrP9n1bb5vCgfeAFvTIbMITlgCb05rQ3hlmdQ3NVivDds3cMwzx7Bw3UKyIlk0z2rO8k3LaZ7ZnA+u/IADWh9Q622xOzR2iYiIiIiIpI6CNxrCQcQpR8D6ytbBoNvP4ICbIK0JbPgcPv0VbF1cvmjpAIt4NEidEt1SvlxpbU+CtoMAh5Vvwdr3k5eraHaML/8vzB1T+/QpOV1g2OLa1a1H1qyB118PLqzJyID994ezzgqu3BJpDPbUQUQzawn8FegKLAYudPcNScoNAR4EwsBT7j6mqvpmdjtwJRADbnT3qYnlU4D2QAR4H7je3WNmlgH8BegHrAMucvfFVa1Dgxi7pFquugpeeKHyVCcZGcF48PLLVbc3bRqcc06Q6qumDj8cPv645vVEGjOdACuhsUsak1gs+N/t6aeDYPyjjgpSofTtG0yWkJ4eBOIXFQWzbqxeDXPmBLN1pMLjsx/n5qk3UxAtYEDHASxav4j129fTIqsFU346hSM6HlF5A/tI8Ebw1LnijSt47vPnqmwqLZTG4psW06FJB+58707+8K8/EPUoIUIc1v6wXdK/fLnmSzYXbsYwDso7iFlXzSIrLUmK2hqu18aCjRz7zLHMWzsPgJZZLfnwyg/p2aoa02oqeENERERERKTBUfBGQziIuOhJ+Pjm2gc/lFY2wOKjq+HbZ8AryNmxO20Xi8fg7WOCWTjilZydSiacDae+Dy0P3/3+icg+bQ8Gb9wNrHf3MWZ2G9DC3W8tUyYMfA2cCiwDZgEXu/u8iuqb2UHAeGAA0AGYBvwoEaTR1N03WTAP9SvAy+7+kpldBxzs7tea2XDgx+5+UVXr0CDGLqmW7dvhpz+FqVOTz3qRnQ3HHRfMztSkSdXtucOgQfD++8FVwNWVlRXU6dev+nVERCfAStPYJY1ZUREsWRIE5BcWltzS00tubdoEAfqpSt0zY+kMhr44lM2Fwcybfdv0ZeolU2nfpH3Vlfeh4I1iF064kInzJxInTlYki0PbHcqqLatYsnEJjtM0oymfXvMp3Vp0SzTjHPjIgSxYt2BnGyEL7XzNE+lkwxZmwQ0L2L/l/ntsvX4o+IGDHz2YddvX8dm1n9GjZY8q69T2varXrMYuERERERGRVNlDk3JKSnW+ALwGZ2Bqouc1ECo/veoeFQrDoH9C66NL0q9UySDSNKinwA0RqZlhwNjE47HAOUnKDAAWufu37l4IvJSoV1n9YcBL7r7D3b8DFiXawd03JcpEgHTAk7T1CjDILFWH7GVflJUFEycG6bMyMyEnJ1ienR3MuHHbbTBlSvUCNyA4xv/cczWbtSkrC664QoEbIiIitZWWBj16wDHHwMCBcNppcOaZwf3AgcHyHj1SF7gBcFzn45h73VwyI5n0bdOXWVfNSh640a5d0NHSt7LKvt6uXd2vQBkTLpzAi+e9SFYki8JYkGZ22aZlhENhTup6Eiv+a8XOwI2gy8aca+fQJ68PkVCE9FA6F/a+kFEnjiItlAZAViSL9y57r+LAjVpqltmMxXftYMtvt9LjoOP2aNsiIiIiIiJSvyh4oyFIbw7tBgF1cKSnxeGQVY0rbXZXJAdOngodz4ZwTuVlQ+mQkQdDZkLrI+u+byLS0LR195UAifs2Scp0BL4v9XxZYlll9Surg5lNBdYAmwkCNXap4+5R4AegVW1XTBoms2Aa9RUr4KGHYNQoeOABWLYMfve7mp/o6dwZ7rwzCACpjiZNYMyYmvZaRERE6pv9mu3H9t9uZ84v5pARyUh1d3Y7UGR4n+G8MfwNIqEIHyz7gKJ4EeceeC5TfzaV7LTyP4TSI+nMvGomvfN6E/MYk76axOSvJxP1KDlpOcy4YgbHdD6mTlbVVq8OHhTfi4iIiIiISKOk4I2G4uA7IVwHM2SYweH3BsEVdS2UBseOgyOfgma9E7NwlDo4E8mBSBM4YCSc8QU0PaDu+yQi9ZKZTTOzL5PchlVdO2giybKq5iGutI67DwbaAxnAyTV9HzO72sxmm9nstWvXVtEVaYhatIDLL4c77oCrroLWrWvf1siR0LUrhKr4JZidDc8+C7m5tX8vERERaUBWrQrSc9TkBjUPwjCDPfCb99T9T2XGFTMAGNJjCOPPG08kFKmwfFZaFtMvnU6HJh3YFt3GrBWzSAulMfHCiRzeXrN+ioiIiIiISN2q+D9WqV9aHg55x8GqaVR9frGGOp4N2V1g07w9224yZtB1eHDL/wiWT4aCVUGKlBYHQ+cLIZJV9/0QkXrN3U+p6DUzW21m7d19pZm1J5gNo6xlwH6lnncCViQeV1S/sjrF/Sows0kE6VLeLlVnmZlFgGbA+grW6QngCYD+/fvv4S96aWzCYZg6FU45BZYsgYKC8mWysoIZN4YO3fv9ExERESEvLwgW2U39O/THR1X/53Or7Fa8d/l79H6kN9ui23jsjMcY3GNw+YLt2lU9U0bZQJW2bffIOomIiIiIiEjDpJk3GpLD7t3N2TcqmHfdDPo9UHU6k8qEqzk3e2mtj4RD7oQjn4R+90H3EQrcEJE9YRIwIvF4BPBGkjKzgJ5m1s3M0oHhiXqV1Z8EDDezDDPrBvQEZppZbiLIg0SAxlDgqyRtnQ/8090VmCF7RadO8MkncNppwQwb4XCwPDcXmjaFyZPhl79MbR9FRESkAajNbB3uKQ1y6Nq8K+9e9i7PDXuOyw67LHmh2qQ4qW1alN1MISMiIiIiIiL1Q50Fb5hZSzN728wWJu5bVFBuiJktMLNFZnZbdeqb2e2J8gvMbHCp5VPM7HMzm2tmj5lZuK7Wb5/U4mBoexK1/lgrC/xodwo07VW7drFgZhARkX3DGOBUM1sInJp4jpl1MLM3Adw9CtwATAXmAxPcfW5l9ROvTwDmAVOA6909BuQAk8xsDvA5wUwdjyXaehpoZWaLgFuAneOgyN6QnQ1vvAEffAC33w7XXw+PPAIrVsDJJ1ddX0RERKSh6t+xPyMOHVFxgbZta95oberA3g0UERERERERkZSxurrA18zuBta7+5hEUEYLd7+1TJkw8DXBya9lBFc6X+zu8yqqb2YHAeOBAUAHYBrwI3ePmVlTd99kZga8Arzs7i9V1s/+/fv77Nmz9+zKp9IPX8GUfhDbVrN6oXRodyoMnFxxmY1fwNSjat52JBcGz4JmtQ3+EBEBM/vY3funuh/7ggY3domINFAau0po7BIRoXqpVpIJhSAer1mdWqZo0dglIiIiIiKSOnWZNmUYMDbxeCxwTpIyA4BF7v6tuxcCLyXqVVZ/GPCSu+9w9++ARYl2cPdNiTIRIB1ofFPPN+sFRzxewzQlBpnt4NhxlRdr3heOGQfhGqQuCWfBcS8rcENEREREREREpDby8upV2hkRERERERGpnboM3mjr7isBEvdtkpTpCHxf6vmyxLLK6ldWBzObSjAl/WaC2Tcan+6XQM9rqh/AEcmFQdMhrWnVZfcbBn3+u3pth7Ph4NHQYUj1+iEiIiIiIiIi0lCtWlXzIAwFYoiIiIiIiDQauxW8YWbTzOzLJLdhVdcOmkiyrKrZMiqt4+6DgfZABpA0W7uZXW1ms81s9tq1a6vZ1Xrm0Hug9VFVB1mEs+D4V6FJj+q3fdDt0OPqymfgCGfBAb+EXjdVv10REREREREREREREREREZFGaLeCN9z9FHfvk+T2BrDazNoDJO7XJGliGbBfqeedgBWJxxXVr6xOcb8KgEmUpGAp2+8n3L2/u/fPy8urySrXH6EwnDQFet+eCLII7/p6OAea9oLT/gPtT6lZ22bQ709wynvQ9MCg/UiT4BbOhGZ9g3YPHROUFRERERERERERERERERERkQpF6rDtScAIYEzi/o0kZWYBPc2sG7AcGA78pIr6k4BxZnY/0AHoCcw0s1ygibuvNLMIMBR4vy5WrN4IpQUpTrpcDAsfgxWTIboFmhwAXS+BbpdAaDd2gVb94cx5sPkbWDcrCNRoNQByu+25dRAREREREREREREREREREWng6jJ4YwwwwcyuBJYCFwCYWQfgKXcf6u5RM7sBmEowNcQz7j63svruPtfMJgDzgChwvbvHzCwHmGRmGYm2/gk8VofrV3802R8Ovye41VX7Tfavm7ZFREREREREREREREREREQauDoL3nD3dcCgJMtXEMyKUfz8TeDN6tZPvDYaGF1m2WrgiN3rtYiIiIiIiIiIiIiIiIiIiMjeFUp1B0RERERERKR2zKylmb1tZgsT9y0qKDfEzBaY2SIzu6069c3s9kT5BWY2uNTyfyWWfZa4tanbtRQREREREREREWn4FLwhIiIiIiJSf90GTHf3nsD0xPNdmFkYeAQ4HTgIuNjMDqqsfuL14UBvYAjw50Q7xX7q7ocmbmvqZtVEREREREREREQaDwVviIiIiIiI1F/DgLGJx2OBc5KUGQAscvdv3b0QeClRr7L6w4CX3H2Hu38HLEq0IyIiIiIiIiIiInVAwRsiIiIiIiL1V1t3XwmQuE+WwqQj8H2p58sSyyqrX1kdgGcTKVN+Z2a2+6shIiIiIiIiIiLSuEVS3QERERERERGpmJlNA9oleem31W0iyTLfjTo/dfflZtYEmAj8DPhLuQbMrgauBujcuXM1uyoiIiIiIiIiItI4aeYNERFpVMyspZm9bWYLE/ctKig3xMwWmNkiM7utOvXN7PZE+QVmNrjU8ilm9rmZzTWzx8wsnFh+mZmtTVy5/JmZ/bwu111EROondz/F3fskub0BrDaz9gCJ+zVJmlgG7FfqeSdgReJxRfUrrOPuyxP3m4FxVJBOxd2fcPf+7t4/Ly+v5isuIiIiIiIiIiLSiCh4Q0REGpvbgOnu3hOYnni+i0RwxSPA6cBBwMVmdlBl9ROvDwd6A0OAPxcHaQAXuvshQB8gD7ig1Nv91d0PTdye2rOrKiIijcAkYETi8QjgjSRlZgE9zaybmaUTjFeTqqg/CRhuZhlm1g3oCcw0s4iZtQYwszTgTODLPbxOIiIiIiIiIiIijY6CN0REpLEZBoxNPB4LnJOkzABgkbt/6+6FwEuJepXVHwa85O473P07YFGiHdx9U6JMBEin6qnqRUREqmsMcKqZLQROTTzHzDqY2ZsA7h4FbgCmAvOBCe4+t7L6idcnAPOAKcD17h4DMoCpZjYH+AxYDjy5F9ZTRERERERERESkQYukugMiIiJ7WVt3Xwng7ivNrE2SMh2B70s9XwYcWUX9jsCHZep0LH5iZlMJgjn+AbxSqtx5ZnYC8DVws7uXfl8REZFKufs6YFCS5SuAoaWevwm8Wd36iddGA6PLLNsK9Nu9XouIiIiIiIiIiEhZmnlDREQaHDObZmZfJrkNq7p20ESSZVXNllFpHXcfDLQnuGL55MTivwFd3f1gYBolM3qUb9zsajObbWaz165dW0VXREREREREREREREREpD7RzBsiItLguPspFb1mZqvNrH1i1oz2wJokxZYB+5V63glYkXhcUf3K6hT3q8DMJhGkWHk7cbVzsSeBuypZpyeAJwD69++vtCsiIiIiIiIiIiIiIiINiGbeEBGRxmYSMCLxeATwRpIys4CeZtbNzNKB4Yl6ldWfBAw3swwz6wb0BGaaWW4iyAMzixBMYf9V4nn7Uu95NjB/D6yfiIiIiIiIiIiIiIiI1DOaeUNERBqbMcAEM7sSWApcAGBmHYCn3H2ou0fN7AZgKhAGnnH3uZXVd/e5ZjYBmAdEgevdPWZmOcAkM8tItPVP4LFEWzea2dmJ8uuBy+p43UVERERERERERERERGQfpOANERFpVBKpSgYlWb6CYFaM4udvAm9Wt37itdHA6DLLVgNHVFD+duD2GnRfREREREREREREREREGiClTRERERERERERERERERERERFJIQVviIiIiIiIiIiIiIiIiIiIiKSQgjdEREREREREREREREREREREUsjcPdV9SCkzWwssqaPmWwP5ddS27B36DBsGfY4NQxd3z0t1J/YFGrukCvoMGwZ9jg2Dxq6E3Ri79LdQQtuihLbFrrQ9SmhblKjtttDYJSIiIiIikiKNPnijLpnZbHfvn+p+SO3pM2wY9DmKVJ/+Xuo/fYYNgz5HkYD+FkpoW5TQttiVtkcJbYsS2hYiIiIiIiL1j9KmiIiIiIiIiIiIiIiIiIiIiKSQgjdEREREREREREREREREREREUkjBG3XriVR3QHabPsOGQZ+jSPXp76X+02fYMOhzFAnob6GEtkUJbYtdaXuU0LYooW0hIiIiIiJSz5i7p7oPIiIiIiIiIiIiIiIiIiIiIo2WZt4QERERERERERERERERERERSSEFb9QBMxtiZgvMbJGZ3Zbq/kjtmNliM/vCzD4zs9mp7o9Uj5k9Y2ZrzOzLUstamtnbZrYwcd8ilX0U2Rdp7GoYNHbVTxq7RMrTuLSrxvz9ru/IEhVsizvMbHli3/jMzIamso97i5ntZ2bvmNl8M5trZiMTyxvrvlHR9miU+4eIiIiIiEh9pbQpe5iZhYGvgVOBZcAs4GJ3n5fSjkmNmdlioL+756e6L1J9ZnYCsAX4i7v3SSy7G1jv7mMSB/9buPutqeynyL5EY1fDobGrftLYJbIrjUvlNebvd31HlqhgW9wBbHH3e1PZt73NzNoD7d39EzNrAnwMnANcRuPcNyraHhfSCPcPERERERGR+kozb+x5A4BF7v6tuxcCLwHDUtwnkUbD3d8D1pdZPAwYm3g8luAgloiU0NglkkIau0TK0bgkO+k7skQF26JRcveV7v5J4vFmYD7Qkca7b1S0PURERERERKQeUfDGntcR+L7U82XoH+b6yoG3zOxjM7s61Z2R3dLW3VdCcFALaJPi/ojsazR2NRwauxoOjV3SmGlcKk/f77vSd+SubjCzOYm0Ko0iTUhpZtYVOAz4CO0bZbcHNPL9Q0REREREpD5R8MaeZ0mWKTdN/XSsux8OnA5cn5iiVkSkIdLY1XBo7BKRhkDjUnn6fpeKPArsDxwKrATuS2lv9jIzywUmAje5+6ZU9yfVkmyPRr1/iIiIiIiI1DcK3tjzlgH7lXreCViRor7IbnD3FYn7NcBrBNM3S/20OpEDuDgX8JoU90dkX6Oxq4HQ2NWgaOySxkzjUhn6fi9H35EJ7r7a3WPuHgeepBHtG2aWRhCo8KK7v5pY3Gj3jWTbozHvHyIiIiIiIvWRgjf2vFlATzPrZmbpwHBgUor7JDVkZjlm1qT4MXAa8GVqeyW7YRIwIvF4BPBGCvsisi/S2NUAaOxqcDR2SWOmcakUfb8npe/IhOJAhYQf00j2DTMz4GlgvrvfX+qlRrlvVLQ9Guv+ISIiIiIiUl+Ze2OffXbPM7OhwANAGHjG3UentkdSU2bWneCKNoAIME6fY/1gZuOBgUBrYDUwCngdmAB0BpYCF7j7+hR1UWSfpLGr/tPYVX9p7BIpT+NSicb+/a7vyBIVbIuBBCkxHFgMXOPuK1PSwb3IzI4D3ge+AOKJxb8BPqJx7hsVbY+LaYT7h4iIiIiISH2l4A0RERERERERERERERERERGRFFLaFBEREREREREREREREREREZEUUvCGiIiIiIiIiIiIiIiIiIiISAopeENEREREREREREREREREREQkhRS8ISIiIiIiIiIiIiIiIiIiIpJCCt4QERERERERERERERERERERSSEFb4iIiIiIiIiIiIiIiIiIiIikkII3RERERERERERERERERERERFJIwRsiIiIiIiIiIiIiIiIiIiIiKfT/ARd/Psr6GKeaAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(30,15))\n", + "\n", + "hdf5_results = h5py.File(\"data/tfmodisco/MMEFS_M4_results.hdf5\",\"r\")\n", + "\n", + "metacluster_names = [x.decode(\"utf-8\") for x in list(hdf5_results[\"metaclustering_results\"][\"all_metacluster_names\"][:])]\n", + "\n", + "motif_dict = {}\n", + "track_no = 1\n", + "for metacluster_name in metacluster_names:\n", + " \n", + " motif_dict[metacluster_name] = {}\n", + " metacluster_grp = (hdf5_results[\"metacluster_idx_to_submetacluster_results\"][metacluster_name])\n", + " pattern_names = [x.decode(\"utf-8\") for x in list(metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][\"all_pattern_names\"][:])]\n", + "\n", + " background = np.mean(onehot_data[n_mut], axis=(0,1))\n", + " for pattern_name in pattern_names:\n", + " pattern = metacluster_grp[\"seqlets_to_patterns_result\"][\"patterns\"][pattern_name]\n", + " pattern_array = np.array(pattern[\"sequence\"][\"fwd\"])\n", + " pattern_cont_score = np.array(pattern[\"Topic_16_contrib_scores\"][\"fwd\"])\n", + " start, end = get_ic_trimming_indices(pattern_array, background=np.mean(onehot_data[n_mut], axis=(0,1)), threshold=0.1)\n", + " pattern_array[start:end,:]*100\n", + " \n", + " _, ax1 = utils.plot_weights(pattern_cont_score[start:end,:],\n", + " fig, 5, 5, track_no,\n", + " title=\"\", subticks_frequency=5, ylab=\"\")\n", + " track_no += 1\n", + "\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/tfmodisco/M4_patterns.pdf\",transparent=True)\n", + "\n", + "hdf5_results.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7ae99857-1eed-40b3-a391-bf8a788e5471", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "72eaf7af-cc6c-44af-8a3f-3321982d6324", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_Enformer_Experiments.ipynb b/the_code/Human/MM_Enformer_Experiments.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6177180b4ded796f3311e5fccd8771f5992f6fa3 --- /dev/null +++ b/the_code/Human/MM_Enformer_Experiments.ipynb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1d6b52758c7782ae23fd6125661267cebc695844b018ba5533f2c7661fb50815 +size 10916359 diff --git a/the_code/Human/MM_Enhance_Rescue.ipynb b/the_code/Human/MM_Enhance_Rescue.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..8cbdb09393ca3dbc0a584822651fb54a70f9e140 --- /dev/null +++ b/the_code/Human/MM_Enhance_Rescue.ipynb @@ -0,0 +1,424 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d7e7a0a5-88a4-4cbc-940d-dd632ba1dc9e", + "metadata": {}, + "source": [ + "## This notebook shows the near-enhancer and enhancing active enhancer experiments.\n", + "#### Luciferase values are in ./data/enhance_rescue/luciferase folder\n", + "#### Figures are saved to ./figures/enhance_rescue folder" + ] + }, + { + "cell_type": "markdown", + "id": "e2a87214-dfef-40c2-8b8a-16bc14e0f376", + "metadata": {}, + "source": [ + "### General imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "d9131ce0-69f4-420e-80af-53e290feac19", + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "f8a77c65-2e03-4a16-9194-50f5ada48e3d", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "126d6f8d-72bf-48ea-a210-e1a5bd9fe10a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "82318fae-9720-45ae-b0ce-6e90f4263566", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "dc4aed56-8ae7-4cae-a859-4684bf78316b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4b16c2d7-6faf-4be8-abc1-4122cf6024fa", + "metadata": {}, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "id": "cd559c88-7874-4e25-98b6-fb5df1be9b25", + "metadata": {}, + "source": [ + "### Loading fasta file and calculating prediction scores" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c4dff6c5-46b1-4f1f-b128-cff4805dc21e", + "metadata": {}, + "outputs": [], + "source": [ + "resc_X, resc_id = utils.prepare_data(\"data/enhance_rescue/regions.fa\")\n", + "rescue_dict = {}\n", + "rescue_dict[\"X\"] = resc_X\n", + "rescue_dict[\"ids\"] = resc_id\n", + "rescue_dict[\"prediction_deepmel\"] = model_dict[\"deepmel\"].predict([rescue_dict[\"X\"],rescue_dict[\"X\"][:,::-1,::-1]])\n", + "rescue_dict[\"prediction_deepmel2\"] = model_dict[\"deepmel2\"].predict([rescue_dict[\"X\"],rescue_dict[\"X\"][:,::-1,::-1]])\n", + "rescue_dict[\"prediction_deepmel2_g\"] = model_dict[\"deepmel2_gabpa\"].predict([rescue_dict[\"X\"],rescue_dict[\"X\"][:,::-1,::-1]])" + ] + }, + { + "cell_type": "markdown", + "id": "ed8e111e-edf4-4f7f-864f-5589c01014c2", + "metadata": {}, + "source": [ + "### Loading luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1b72fbd0-a4f9-4d57-9235-bce5bc7b0c3b", + "metadata": {}, + "outputs": [], + "source": [ + "rescue_dict[\"values\"] = []\n", + "with open(\"data/enhance_rescue/luciferase.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " rescue_dict[\"values\"].append(sep[1:])\n", + "rescue_dict[\"values\"] = np.array(rescue_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "markdown", + "id": "beefb9e8-bfab-4b33-a6c0-f0b2dc2cdc2a", + "metadata": {}, + "source": [ + "### Plotting luciferase values versus prediction scores for the rescue of near-enhancer sequence" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "22adb230-4db5-4b74-9bbd-b503049b435f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "mean = np.mean(np.log2(rescue_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(rescue_dict[\"values\"]),axis=1)\n", + "\n", + "plt.errorbar(rescue_dict[\"prediction_deepmel\"][:,3][0:6],mean[0:6],yerr=std[0:6],linestyle=\"None\", color=\"black\",fmt=\"o\",capsize=5)\n", + "plt.ylim(0,4)\n", + "plt.xlim(0,0.4)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "plt.xlabel(\"Prediction score\")\n", + "\n", + "plt.savefig(\"figures/enhance_rescue/rescue_prediction_vs_luciferase.pdf\",transparent=True,dpi=300)\n" + ] + }, + { + "cell_type": "markdown", + "id": "5c4131a0-66f1-4e2e-84ea-cbdc18996112", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores together with in silico saturation mutagenesis values" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "11eea078-0f01-4648-b733-d503eedecae3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "st = 230\n", + "end = 340\n", + "\n", + "ntrack = 4\n", + "fig = plt.figure(figsize=(17.6,ntrack*5))\n", + "\n", + "start_x = np.copy(rescue_dict[\"X\"][0:1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 4)\n", + "start_x = np.copy(rescue_dict[\"X\"][5:6])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 4)\n", + "start_x = np.copy(rescue_dict[\"X\"][1:2])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=start_x, class_no = 4)\n", + "ax4 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=start_x, class_no = 4)\n", + "\n", + "\n", + "for i, mut_ in enumerate([\"254_\",\"277_\",\"327_\",\"330_\"]):\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "ax3.set_xlim([st,end])\n", + "ax4.set_xlim([st,end])\n", + "\n", + "min_ = np.min([ax1.get_ylim()[0],ax2.get_ylim()[0],ax3.get_ylim()[0] ])\n", + "max_ = np.max([ax1.get_ylim()[1],ax2.get_ylim()[1],ax3.get_ylim()[1] ])\n", + "ax1.set_ylim([min_, max_])\n", + "ax2.set_ylim([min_, max_])\n", + "ax3.set_ylim([min_, max_])\n", + "\n", + "plt.savefig(\"figures/enhance_rescue/rescue_deepexplainer_humMut0_humMut4_dog_st230_end340.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "db8d3dc6-d926-49aa-853a-1bbb034a6569", + "metadata": {}, + "source": [ + "### Plotting luciferase values versus prediction scores for the activity-enhanced sequence" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "39715d49-1ff3-4ecf-bd30-8452626ecba8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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9nYULFyojI0ObNm0y1X/ChAkXfcYKAABPcttDlUePHtW8efNM98/KytLgwYP17rvvKiQkxNRnRo8erdzcXPtfVlZWacsFAMBlpZ4R6HKlp6fryJEjatasmb2tsLBQa9eu1YwZM1RQUCB/f3+HzwQHBys4ONjbpQIAIMmHoXn77bdr27ZtDm1/+ctf1KBBAz377LMlAhMAAF/zWWiGhoaqUaNGDm0VKlRQlSpVSrQDAGAFpkPzUu+XO3bs2OXWAgCApZkOzfDw8Euuf/TRRy+rmNWrV1/W5wEA8CTToTl37lxP1gEAgOXxHi8AAEwyFZoDBgww/Uxkamqq5s+ff1lFAQBgRaYuz0ZGRqpRo0a69dZb1aVLFyUkJCg6OlohISH6/ffftWPHDq1fv14LFy5UjRo19Oabb3q6bgAAvM70+zSPHDmi2bNna+HChfr+++8d1oWGhqpDhw564okn1LFjR48U6gzv0wQASN7LA5dfQi2dfbxk//79OnnypKpWrao6derIZrN5or6LIjQBAJL38qBUkxtUqlRJlSpVcnMpAABYG6NnAQAwidAEAMAkQhMAAJMITQAATHI5NJOTk7V//35P1AIAgKW5HJr/+c9/VKdOHd1+++1asGCBTp065Ym6AACwHJdDMz09XRkZGWrcuLGGDh2qqKgoPfnkk9q0aZMn6gMAwDJKdU+zcePGmjJlirKzszVnzhxlZ2erZcuWuuGGGzRt2jTl5ua6u04AAHzusgYCFRUV6fTp0yooKJBhGIqIiNDMmTMVGxur1NRUd9UIAIAllCo009PT9fTTTysqKkpDhw5VkyZNtHPnTq1Zs0Y//PCDxo0bp0GDBrm7VgAAfMrluWcbN26snTt3qmPHjnr88cd17733yt/f36HPL7/8ourVq6uoqMitxZ6PuWcBAJKF5569//771a9fP9WoUeOCfSIjIz0emAAAeJvLl2cNw1DlypVLtJ88eVLPP/+8W4oCAMCKXL486+/vr5ycHFWrVs2h/bffflO1atVUWFjo1gIvhsuzAADJe3lQqjNNZ+/O/PbbbxUREeGWogAAsCLT9zQrV64sm80mm82mevXqOQRnYWGh8vPzNWDAAI8UCQCAFZgOzalTp8owDPXr10/jx49XeHi4fV1QUJDi4+OVmJjokSIBALAC06HZp08fSVKtWrV06623KjAw0GNFAQBgRaZCMy8vz35jtUmTJjp58qROnjzptC8DcgAAVypToVm5cmX7iNlKlSo5HQhUPEDIm6NnAQDwJlOhuWrVKvvI2FWrVjkNTQAArnQuP6dpJTynCQCQLPycZu3atTV27Fjt2rXLE/UAAGBZLofm008/rU8//VTXXXedmjVrpqlTpyonJ8cTtQEAYCkuh+awYcO0adMm/fDDD7rnnns0c+ZM1axZUx07dtQ777zjiRoBALAEt9zT3Lhxo5588kl99913zD0LAPA6y74a7FzffPONFixYoNTUVOXm5qpHjx7uqgsAAMtxOTR3796t+fPna8GCBdq3b5/atWuniRMnKikpSaGhoZ6oEQAAS3A5NBs0aKCEhAQNHDhQDzzwgK655hpP1AUAgOW4HJo//PCD6tWr54laAACwNJdHzxKYAICrlakzzYiICO3evVtVq1a1v1fzQo4ePeq24gAAsBJToTllyhT7IJ8pU6Yw9ywA4KrE3LMAgDLPsnPP+vv768iRIyXaf/vtN/n7+7ulKAAArMjl0LzQiWlBQYGCgoIuuyAAAKzK9CMn06dPlyTZbDa99dZbqlixon1dYWGh1q5dqwYNGri/QgAALMJ0aE6ZMkXS2TPNN954w+FSbFBQkOLj4/XGG2+4v0IAACzCdGhmZmZKktq1a6e0tDRVrlzZY0UBAGBFLs8I9MUXX3iiDgAALM/lgUA9evTQxIkTS7S//PLLuv/++91SFAAAVuRyaK5Zs0adO3cu0X7XXXdp7dq1Lm1r5syZaty4scLCwhQWFqbExER98sknrpYEAIBXuBya+fn5Th8tCQwMVF5enkvbiomJ0cSJE7V582Zt3rxZ7du3V9euXbV9+3ZXywIAwONcDs1GjRopNTW1RPvChQvVsGFDl7Z177336u6771a9evVUr149vfjii6pYsaI2btzoalkAAHicywOBxo4dq+7du2vv3r1q3769JGnlypV67733tGjRolIXUlhYqEWLFunEiRNKTEx02qegoEAFBQX2ZVfPbAEAuBwuh2aXLl30wQcf6KWXXtLixYtVrlw5NW7cWCtWrFDbtm1dLmDbtm1KTEzUqVOnVLFiRS1duvSCZ6wTJkzQ+PHjXf4OAADcwecTtp8+fVoHDhzQsWPHtGTJEr311ltas2aN0+B0dqYZGxvLhO0AcJXz1oTtPg/N83Xo0EF16tRRSkrKJfvylhMAgOS9PHD58mxhYaGmTJmi999/XwcOHNDp06cd1l/uS6gNw3A4mwQAwCpcHj07fvx4/etf/1LPnj2Vm5urYcOGKSkpSX5+fkpOTnZpW//v//0/rVu3Tvv27dO2bds0ZswYrV69Wg899JCrZQEA4HEun2nOnz9fs2bNUufOnTV+/Hg9+OCDqlOnjho3bqyNGzdq0KBBprf1888/65FHHlFOTo7Cw8PVuHFjffrpp7rjjjtcLQsAAI9zOTQPHz6sG264QZJUsWJF5ebmSpLuuecejR071qVtzZ4929WvBwDAZ1y+PBsTE6OcnBxJUt26dfX5559LkjZt2qTg4GD3VgcAgIW4HJr33XefVq5cKUkaPHiwxo4dq2uvvVaPPvqo+vXr5/YCAQCwist+5OTrr7/Wl19+qbp166pLly7uqssUHjkBUNbl5OTYr965IioqSlFRUR6oqGyy7CMn52vevLmaN2/ujloA4KqTkpJSqpnOxo0b5/ITC7h8lx2aAIDS69+/v8NVulWrVmny5Mn65Zdf7G3VqlXTiBEj7PN9S+Is00csNyOQK7g8C+BKkpaWph49euj8fy3bbDZJ0uLFi5WUlOSL0izPW3ng8kAgAID7FRYWavDgwSUCU5K9bciQISosLPR2aTgHoQkAFrBu3TodPHjwgusNw1BWVpbWrVvnxapwvlKF5rFjx/TWW29p9OjR9rlmMzIylJ2d7dbiAOBqYXYEbWlG2sJ9XB4I9N1336lDhw4KDw/Xvn379PjjjysiIkJLly7V/v379c4773iiTgC4opkd2MMAIN9y+Uxz2LBh6tu3r/bs2aOQkBB7e6dOnbR27Vq3FgcAV4vWrVsrJibGPujnfDabTbGxsWrdurWXK8O5XA7NTZs2qX///iXaa9SoocOHD7ulKAC42vj7+2vatGmSVCI4i5enTp0qf39/r9eG/3E5NENCQpSXl1eifdeuXYqMjHRLUQBwtcjJyVFGRoYyMjIUHx+vyZMnq2rVqg59qlWrpsmTJys+Pt7el3ubvuHyPc2uXbvq+eef1/vvvy/p7H8BHThwQKNGjVL37t3dXiAAXMnMzAj0888/a8SIEQ5tzAjkGy5PbpCXl6e7775b27dv1/HjxxUdHa3Dhw8rMTFRy5YtU4UKFTxVq9NamNwAQFnG3LPu4a08KPWMQKtWrVJGRoaKiorUtGlTdejQwd21XRKhCQCQysCE7e3bt7fPg3js2DF31QMAgGW5PBBo0qRJSk1NtS/37NlTVapUUY0aNfTtt9+6tTgAAKzE5dBMSUlRbGysJGn58uVavny5PvnkE3Xq1KnEjWoAAK4kLl+ezcnJsYfmxx9/rJ49e6pjx46Kj4/nvZoAgCuay2ealStXVlZWliTp008/tQ8AMgyD2fcBAFc0l880k5KS1Lt3b1177bX67bff1KlTJ0nS1q1bVbduXbcXCACAVbgcmlOmTFF8fLyysrI0efJkVaxYUdLZy7ZPPfWU2wsEAMAqSv2cphXwnCYAQCoDz2nu2LFDBw4c0OnTpx3au3TpctlFAbAWZq0BznI5NH/66Sfdd9992rZtm2w2m4pPVItn4WcwEHDlMTM/qjPMj4orjcuhOXjwYNWqVUsrVqxQ7dq19c033+i3337T8OHD9c9//tMTNQLwsf79+5e4inTy5Em1atVKkrR+/XqVK1euxOc4y8SVxuXQ/Oqrr7Rq1SpFRkbKz89Pfn5+atWqlSZMmKBBgwZpy5YtnqgTgA85u8x67isC8/Ly1KJFC971iCuey89pFhYW2kfMVq1aVYcOHZIkxcXFadeuXe6tDoAlpaWlqWHDhvblu+++W/Hx8UpLS/NhVYDnuRyajRo10nfffSdJat68uSZPnqwvv/xSzz//vGrXru32AgFYS1pamnr06KHs7GyH9uzsbPXo0YPgxBXN5UdOPvvsM504cUJJSUn66aefdM899+iHH35QlSpVlJqaan/ziTfwyAngXYWFhYqPj9fBgwedrrfZbIqJiVFmZiaXauFVln+f5rmOHj2qypUr20fQeguhCXjX6tWr1a5du0v2++KLL3Tbbbd5viDg/3grD1y6PPvnn38qICBA33//vUN7RESE1wMTgPeZfVazNM90AmWBS6EZEBCguLg4nsUErlJmHyHhURNcqVweCPTcc89p9OjROnr0qCfqAWBhrVu3VkxMzAWvLNlsNsXGxqp169ZergzwDpef05w+fbp+/PFHRUdHKy4uThUqVHBYn5GR4bbiAFiLv7+/pk2bph49ejjMCCb9b1awqVOnMggIVyyXQ7Nbt24eKANAWZGUlKTFixdr0KBBDo+dxMTEaOrUqUpKSvJhdYBn8ZYTAKVS/P8/SVq2bJk6duzIGSZ8xtJvOTl27JgWL16svXv3asSIEYqIiFBGRoaqV6+uGjVquLtGAD7m7C0nJ0+etP9zWFiYvv322xKf4y0nuNK4HJrfffedOnTooPDwcO3bt0+PP/64IiIitHTpUu3fv1/vvPOOJ+oE4EOXestJ8cTt5+MtJ7jSuByaw4YNU9++fTV58mSFhoba2zt16qTevXu7tTgA1uDsLSdmcJaJK43Loblp0yalpKSUaK9Ro4YOHz7slqIAWAuXWYGzXH5OMyQkxOGVQMV27dqlyMhItxQFAIAVuRyaXbt21fPPP68zZ85IOvts1oEDBzRq1Ch1797d7QUCAGAVLofmP//5T/3yyy+qVq2aTp48qbZt26pu3boKDQ3Viy++6IkaAQCwBJfvaYaFhWn9+vVatWqVMjIyVFRUpKZNm6pDhw6eqA8AAMswNblBRESEdu/erapVq6pfv36aNm2aw8hZX2FyAwCAZLFXg50+fdo++GfevHk6deqUxwoCAMCqTF2eTUxMVLdu3dSsWTMZhqFBgwapXLlyTvvOmTPH9JdPmDBBaWlp+uGHH1SuXDndeuutmjRpkurXr296GwAAeIupM813331Xd999t/Lz82Wz2ZSbm6vff//d6Z8r1qxZo4EDB2rjxo1avny5/vzzT3Xs2FEnTpwo1c4AAOBJLk/YXqtWLW3evFlVqlRxezHFo3LXrFmjNm3aXLI/9zQBAJKFJ2zPzMz0RB2SpNzcXElnBx45U1BQoIKCAvuys0kWAADwFFOhOX36dD3xxBMKCQnR9OnTL9p30KBBpSrEMAwNGzZMrVq1UqNGjZz2mTBhwkUnjQYAwJNMXZ4995JsrVq1Lrwxm00//fRTqQoZOHCg/vvf/2r9+vWKiYlx2sfZmWZsbCyXZwHgKmepy7PnXpL1xOXZZ555Rh999JHWrl17wcCUpODgYAUHB7v9+wEAMKNUL6F2F8Mw9Mwzz2jp0qVavXr1Rc9iAQDwNZfnnu3Ro4cmTpxYov3ll1/W/fff79K2Bg4cqHfffVcLFixQaGioDh8+rMOHDzu8ER4AAKtw+ZGTyMhIrVq1SjfccIND+7Zt29ShQwf9/PPP5r/cZnPaPnfuXPXt2/eSn+eREwCAZLF7mufKz89XUFBQifbAwECXHwFxMa8BAPAply/PNmrUSKmpqSXaFy5cqIYNG7qlKAAArMjlM82xY8eqe/fu2rt3r9q3by9JWrlypd577z0tWrTI7QUCAGAVLodmly5d9MEHH+ill17S4sWLVa5cOTVu3FgrVqxQ27ZtPVEjAACW4PJAICthIBAAQLLY+zQBAEApLs/6+fld8FERSSosLLysggAAsCqXQ3Pp0qUOy2fOnNGWLVs0b948JlMHAFzR3HZPc8GCBUpNTdWHH37ojs2Zwj1NAIBUBu9pNm/eXCtWrHDX5gAAsBy3hObJkyf16quvXvQNJQAAlHUu39OsXLmyw0AgwzB0/PhxlS9fXv/+97/dWhwAAFbicmhOnTrVYdnPz0+RkZFq3ry5Kleu7K66AACwHJdDs0+fPk7bs7KyNHz4cM2ZM+eyiwIAwIrcNhDo6NGjmjdvnrs2BwCA5TAjEAAAJhGaAACYRGgCAGCS6YFASUlJF11/7Nixy60FAABLMx2a4eHhl1z/6KOPXnZBAABYlenQnDt3rifrAADA8rinCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYBKhCQCASYQmAAAmEZoAAJhEaAIAYJJPQ3Pt2rW69957FR0dLZvNpg8++MCX5QAAcFE+Dc0TJ07oxhtv1IwZM3xZBgAApgT48ss7deqkTp06+bIEAABM82louqqgoEAFBQX25by8PB9WAwC42pSpgUATJkxQeHi4/S82NtbXJQEAriJlKjRHjx6t3Nxc+19WVpavSwIAXEXK1OXZ4OBgBQcH+7oMAMBVqkydaQIA4Es+PdPMz8/Xjz/+aF/OzMzU1q1bFRERoZo1a/qwMgAASvJpaG7evFnt2rWzLw8bNkyS1KdPH7399ts+qgoAAOd8Gpq33XabDMPwZQkAAJjGPU0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEAMInQBADAJEITAACTfB6ar7/+umrVqqWQkBA1a9ZM69at83VJAAA45dPQTE1N1ZAhQzRmzBht2bJFrVu3VqdOnXTgwAFflgUAgFM2wzAMX3158+bN1bRpU82cOdPedt1116lbt26aMGHCJT+fl5en8PBw5ebmKiwszJOlAgAszFt54LMzzdOnTys9PV0dO3Z0aO/YsaM2bNjgo6oAALiwAF998a+//qrCwkJVr17dob169eo6fPiw088UFBSooKDAvpybmyvp7H9hAACuXsU54OmLpz4LzWI2m81h2TCMEm3FJkyYoPHjx5doj42N9UhtAICy5bffflN4eLjHtu+z0Kxatar8/f1LnFUeOXKkxNlnsdGjR2vYsGH25WPHjikuLk4HDhzw6I/kSXl5eYqNjVVWVlaZvC9L/b5X1vehrNcvlf19KOv1S2evPNasWVMREREe/R6fhWZQUJCaNWum5cuX67777rO3L1++XF27dnX6meDgYAUHB5doDw8PL7MHulhYWFiZ3gfq972yvg9lvX6p7O9DWa9fkvz8PDtUx6eXZ4cNG6ZHHnlECQkJSkxM1JtvvqkDBw5owIABviwLAACnfBqavXr10m+//abnn39eOTk5atSokZYtW6a4uDhflgUAgFM+Hwj01FNP6amnnirVZ4ODgzVu3Dinl2zLirK+D9Tve2V9H8p6/VLZ34eyXr/kvX3w6eQGAACUJT6fexYAgLKC0AQAwCRCEwAAkwhNAABMslxouvp+zTVr1qhZs2YKCQlR7dq19cYbb5Tos2TJEjVs2FDBwcFq2LChli5d6qny3V7/22+/LZvNVuLv1KlTPq8/JydHvXv3Vv369eXn56chQ4Y47efN319y/z5Y+RikpaXpjjvuUGRkpMLCwpSYmKjPPvusRD8rHwMz+2DlY7B+/Xq1bNlSVapUUbly5dSgQQNNmTKlRD8rHwMz+2DlY3CuL7/8UgEBAbrppptKrHPLMTAsZOHChUZgYKAxa9YsY8eOHcbgwYONChUqGPv373fa/6effjLKly9vDB482NixY4cxa9YsIzAw0Fi8eLG9z4YNGwx/f3/jpZdeMnbu3Gm89NJLRkBAgLFx48YyUf/cuXONsLAwIycnx+HPE1ytPzMz0xg0aJAxb94846abbjIGDx5coo83f39P7YOVj8HgwYONSZMmGd98842xe/duY/To0UZgYKCRkZFh72P1Y2BmH6x8DDIyMowFCxYY33//vZGZmWn8+9//NsqXL2+kpKTY+1j9GJjZBysfg2LHjh0zateubXTs2NG48cYbHda56xhYKjRvueUWY8CAAQ5tDRo0MEaNGuW0/8iRI40GDRo4tPXv399o0aKFfblnz57GXXfd5dDnzjvvNB544AE3Vf0/nqh/7ty5Rnh4uNtrdcbV+s/Vtm1bp4Hjzd/fMDyzD2XlGBRr2LChMX78ePtyWToGxc7fh7J2DO677z7j4Ycfti+XxWNw/j6UhWPQq1cv47nnnjPGjRtXIjTddQwsc3m2NO/X/Oqrr0r0v/POO7V582adOXPmon3c/c5OT9UvSfn5+YqLi1NMTIzuuecebdmyxa21l7Z+M7z1+0uefUdrWTkGRUVFOn78uMOk1WXtGDjbB6nsHIMtW7Zow4YNatu2rb2trB0DZ/sgWfsYzJ07V3v37tW4ceOcrnfXMbBMaJbm/ZqHDx922v/PP//Ur7/+etE+F9pmaXmq/gYNGujtt9/WRx99pPfee08hISFq2bKl9uzZ4/P6zfDW7y95bh/K0jF45ZVXdOLECfXs2dPeVtaOgbN9KAvHICYmRsHBwUpISNDAgQP117/+1b6urByDi+2DlY/Bnj17NGrUKM2fP18BAc4nunPXMfD5NHrnc+X9mhfqf367q9u8HO6uv0WLFmrRooV9fcuWLdW0aVO9+uqrmj59urvKvmg9l/tbefP398T3lZVj8N577yk5OVkffvihqlWr5pZtlpa796EsHIN169YpPz9fGzdu1KhRo1S3bl09+OCDl7XNy+HufbDqMSgsLFTv3r01fvx41atXzy3bvBjLhGZp3q95zTXXOO0fEBCgKlWqXLTPhbZZWp6q/3x+fn66+eab3f5fd6Wp3wxv/f6S5/bhfFY8BqmpqXrssce0aNEidejQwWFdWTkGF9uH81nxGNSqVUuSdMMNN+jnn39WcnKyPXDKyjG42D6czyrH4Pjx49q8ebO2bNmip59+WtLZS/yGYSggIECff/652rdv77ZjYJnLs+e+X/Ncy5cv16233ur0M4mJiSX6f/7550pISFBgYOBF+1xom6XlqfrPZxiGtm7dqqioKPcU/n9KU78Z3vr9Jc/tw/msdgzee+899e3bVwsWLFDnzp1LrC8Lx+BS+3A+qx0DZ/UVFBTYl8vCMTjf+fvgbL0VjkFYWJi2bdumrVu32v8GDBig+vXra+vWrWrevLkkNx4Dl4YNeVjxMOPZs2cbO3bsMIYMGWJUqFDB2Ldvn2EYhjFq1CjjkUcesfcvfmRj6NChxo4dO4zZs2eXeGTjyy+/NPz9/Y2JEycaO3fuNCZOnOjxR07cWX9ycrLx6aefGnv37jW2bNli/OUvfzECAgKMr7/+2uf1G4ZhbNmyxdiyZYvRrFkzo3fv3saWLVuM7du329d78/f31D5Y+RgsWLDACAgIMF577TWHxwCOHTtm72P1Y2BmH6x8DGbMmGF89NFHxu7du43du3cbc+bMMcLCwowxY8bY+1j9GJjZBysfg/M5Gz3rrmNgqdA0DMN47bXXjLi4OCMoKMho2rSpsWbNGvu6Pn36GG3btnXov3r1aqNJkyZGUFCQER8fb8ycObPENhctWmTUr1/fCAwMNBo0aGAsWbKkzNQ/ZMgQo2bNmkZQUJARGRlpdOzY0diwYYNl6pdU4i8uLs6hjzd/f0/sg5WPQdu2bZ3W36dPH4dtWvkYmNkHKx+D6dOnG9dff71Rvnx5IywszGjSpInx+uuvG4WFhQ7btPIxMLMPVj4G53MWmobhnmPAq8EAADDJMvc0AQCwOkITAACTCE0AAEwiNAEAMInQBADAJEITAACTCE0AAEwiNAEPSE5OdnhzfN++fdWtW7fL2qY7tgHg8hCauGr07dtXNptNNptNgYGBql27tv72t7/pxIkTHv/uadOm6e233zbVd9++fbLZbNq6dWuptwHAMyzzlhPAG+666y7NnTtXZ86c0bp16/TXv/5VJ06c0MyZM0v0PXPmzAUnzndVeHi4JbZhNadPn1ZQUJCvywBM40wTV5Xg4GBdc801io2NVe/evfXQQw/pgw8+kPS/S6pz5sxR7dq1FRwcLMMwlJubqyeeeELVqlVTWFiY2rdvr2+//dZhuxMnTlT16tUVGhqqxx57TKdOnXJYf/6l1aKiIk2aNEl169ZVcHCwatasqRdffFHS/17P1KRJE9lsNt12221Ot1FQUKBBgwapWrVqCgkJUatWrbRp0yb7+tWrV8tms2nlypVKSEhQ+fLldeutt2rXrl0X/H1Onz6tp59+WlFRUQoJCVF8fLwmTJhgX3/s2DE98cQTql69ukJCQtSoUSN9/PHH9vVLlizR9ddfr+DgYMXHx+uVV15x2H58fLxeeOEF9e3bV+Hh4Xr88cclSRs2bFCbNm1Urlw5xcbGatCgQV65AgC4itDEVa1cuXI6c+aMffnHH3/U+++/ryVLltgvj3bu3FmHDx/WsmXLlJ6erqZNm+r222/X0aNHJUnvv/++xo0bpxdffFGbN29WVFSUXn/99Yt+7+jRozVp0iSNHTtWO3bs0IIFC+zv9fvmm28kSStWrFBOTo7S0tKcbmPkyJFasmSJ5s2bp4yMDNWtW1d33nmnva5iY8aM0SuvvKLNmzcrICBA/fr1u2Bd06dP10cffaT3339fu3bt0rvvvqv4+HhJZ4O+U6dO2rBhg959913t2LFDEydOlL+/vyQpPT1dPXv21AMPPKBt27YpOTlZY8eOLXFJ+eWXX1ajRo2Unp6usWPHatu2bbrzzjuVlJSk7777TqmpqVq/fr393YiApbg8xTtQRvXp08fo2rWrffnrr782qlSpYvTs2dMwjLNvRggMDDSOHDli77Ny5UojLCzMOHXqlMO26tSpY6SkpBiGYRiJiYnGgAEDHNY3b97c4S0L5353Xl6eERwcbMyaNctpnZmZmYYkY8uWLResPz8/3wgMDDTmz59vX3/69GkjOjramDx5smEYhvHFF18YkowVK1bY+/z3v/81JBknT550+t3PPPOM0b59e6OoqKjEus8++8zw8/Mzdu3a5fSzvXv3Nu644w6HthEjRhgNGza0L8fFxRndunVz6PPII48YTzzxhEPbunXrDD8/vwvWCfgKZ5q4qnz88ceqWLGiQkJClJiYqDZt2ujVV1+1r4+Li1NkZKR9OT09Xfn5+apSpYoqVqxo/8vMzNTevXslSTt37lRiYqLD95y/fK6dO3eqoKBAt99+e6n3Y+/evTpz5oxatmxpbwsMDNQtt9yinTt3OvRt3Lix/Z+LXxh85MgRp9vt27evtm7dqvr162vQoEH6/PPP7eu2bt2qmJgY1atX74L7dW49ktSyZUvt2bNHhYWF9raEhASHPunp6Xr77bcdft8777xTRUVFyszMvNjPAHgdA4FwVWnXrp1mzpypwMBARUdHlxjoU6FCBYfloqIiRUVFafXq1SW2ValSpVLVUK5cuVJ97lzG/73Rz2azlWg/v+3cfSxeV1RU5HS7TZs2VWZmpj755BOtWLFCPXv2VIcOHbR48eJL1u3suw0nbx509hv3799fgwYNKtG3Zs2aF/1OwNs408RVpUKFCqpbt67i4uJMjYxt2rSpDh8+rICAANWtW9fhr2rVqpKk6667Ths3bnT43PnL57r22mtVrlw5rVy50un64tGk556dna9u3boKCgrS+vXr7W1nzpzR5s2bdd11111yvy4mLCxMvXr10qxZs5SamqolS5bo6NGjaty4sQ4ePKjdu3c7/VzDhg0d6pHODvCpV6+e/b6nM02bNtX27dtL/L7F+whYCWeawEV06NBBiYmJ6tatmyZNmqT69evr0KFDWrZsmbp166aEhAQNHjxYffr0UUJCglq1aqX58+dr+/btql27ttNthoSE6Nlnn9XIkSMVFBSkli1b6pdfftH27dv12GOPqVq1aipXrpw+/fRTxcTEKCQkpMTjJhUqVNCTTz6pESNGKCIiQjVr1tTkyZP1xx9/6LHHHiv1/k6ZMkVRUVG66aab5Ofnp0WLFumaa65RpUqV1LZtW7Vp00bdu3fXv/71L9WtW1c//PCDbDab7rrrLg0fPlw333yz/vGPf6hXr1766quvNGPGjEsOinr22WfVokULDRw4UI8//rgqVKignTt3avny5Q6XzgEr4EwTuAibzaZly5apTZs26tevn+rVq6cHHnhA+/bts4927dWrl/7+97/r2WefVbNmzbR//349+eSTF93u2LFjNXz4cP3973/Xddddp169etnvMwYEBGj69OlKSUlRdHS0unbt6nQbEydOVPfu3fXII4+oadOm+vHHH/XZZ5+pcuXKpd7fihUratKkSUpISNDNN9+sffv2admyZfLzO/uviiVLlujmm2/Wgw8+qIYNG2rkyJH2M+KmTZvq/fff18KFC9WoUSP9/e9/1/PPP6++ffte9DsbN26sNWvWaM+ePWrdurWaNGmisWPH2u+/AlZiM5zddAAAACVwpgkAgEmEJgAAJhGaAACYRGgCAGASoQkAgEmEJgAAJhGaAACYRGgCAGASoQkAgEmEJgAAJhGaAACYRGgCAGDS/wfdgeROXbP3CAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "mean = np.mean(np.log2(rescue_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(rescue_dict[\"values\"]),axis=1)\n", + "\n", + "plt.errorbar(rescue_dict[\"prediction_deepmel\"][:,3][[6,7,8,9]],mean[[6,7,8,9]],yerr=std[[6,7,8,9]],linestyle=\"None\", color=\"black\",fmt=\"o\",capsize=5)\n", + "plt.ylim(0,6.5)\n", + "plt.xlim(0,0.4)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "plt.xlabel(\"Prediction score\")\n", + "\n", + "plt.savefig(\"figures/enhance_rescue/enhance_prediction_vs_luciferase.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "c1bab6b3-d127-4d21-9c5a-28033fdf42f4", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores together with in silico saturation mutagenesis values" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "06d7eadd-91c8-4e9f-8259-277b2378c150", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "st = 170\n", + "end = 350\n", + "\n", + "ntrack = 5\n", + "fig = plt.figure(figsize=(28.8,ntrack*5))\n", + "\n", + "start_x = np.copy(rescue_dict[\"X\"][9:10])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 4)\n", + "start_x = np.copy(rescue_dict[\"X\"][7:8])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 4)\n", + "start_x = np.copy(rescue_dict[\"X\"][8:9])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=start_x, class_no = 4)\n", + "start_x = np.copy(rescue_dict[\"X\"][6:7])\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=start_x, class_no = 4)\n", + "ax5 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel\"], fig=fig, ntrack=ntrack, track_no=5, seq_onehot=start_x, class_no = 4)\n", + "\n", + "for i, mut_ in enumerate([\"316_\",\"184_\"]):\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax1.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + " ax4.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax4.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "for i, mut_ in enumerate([\"184_\"]):\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "for i, mut_ in enumerate([\"316_\"]):\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "ax3.set_xlim([st,end])\n", + "ax4.set_xlim([st,end])\n", + "ax5.set_xlim([st,end])\n", + "\n", + "min_ = np.min([ax1.get_ylim()[0],ax2.get_ylim()[0],ax3.get_ylim()[0],ax4.get_ylim()[0] ])\n", + "max_ = np.max([ax1.get_ylim()[1],ax2.get_ylim()[1],ax3.get_ylim()[1],ax4.get_ylim()[1] ])\n", + "ax1.set_ylim([min_, max_])\n", + "ax2.set_ylim([min_, max_])\n", + "ax3.set_ylim([min_, max_])\n", + "ax4.set_ylim([min_, max_])\n", + "\n", + "plt.savefig(\"figures/enhance_rescue/enhance_deepexplainer_dogwt_dogSox_dogMitf_dogAll_st170_end350.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f57d040a-2243-4d16-884d-1361dcfc652e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_GAN.ipynb b/the_code/Human/MM_GAN.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..a14342557288b216b61d1477b5bcbdcc83bc84a0 --- /dev/null +++ b/the_code/Human/MM_GAN.ipynb @@ -0,0 +1,630 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ffc1b380-41d9-4451-ac90-01923f9da5bc", + "metadata": {}, + "source": [ + "# This notebook shows how to load and analyse GAN generated sequences.\n", + "#### GAN generated sequences are provided in ./data/gan/generated_seqs folder.\n", + "#### Background sequences are provided in ./data/gan/background_seqs folder.\n", + "#### Genomic sequences are provided in ./data/gan folder\n", + "#### It consists of:\n", + "* Reading GAN generated, genomic, and background sequences.\n", + "* Scoring generated sequences with the DeepMEL model.\n", + "* Visualising prediction scores on gan generated sequences at different training steps.\n", + "* Comparing GC content of GAN generated and background sequences.\n", + "* Visializing the luciferase results and contribution score plots.\n", + "#### Luciferase values are in ./data/luciferase folder\n", + "#### Intermediate files are saved to ./data/gan folder\n", + "#### Figures are saved to ./figures/gan folder" + ] + }, + { + "cell_type": "markdown", + "id": "1bddf7a6-e658-4486-a8ed-2351efdbaea5", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c2637bcf-5ea3-48f5-94da-449cb525577d", + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "05f9a531-2cab-4927-a0b0-7a465263c4dd", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c7010635-3387-4580-a881-d9e661e79872", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "d403a2b7-2c1c-4228-955b-7d604759f5ef", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "e9297d98-5daa-4206-a55e-f8f0f4dca1c7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a0091038-3a89-4658-8731-25f2b1737a91", + "metadata": {}, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "id": "9106c41b-665f-4e6d-a485-c0aeea677add", + "metadata": {}, + "source": [ + "### Reading GAN generated, genomic, and background sequences and calculating prediction scores" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "0c2e78a0-0e0d-4656-b55e-d8c1d83ee898", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# data_dict = {}\n", + "# data_dict[\"MMgan\"] = {}\n", + "# for iter_ in range(0,161000,10000):\n", + "# data_dict[\"MMgan\"][iter_] = {}\n", + "# data_dict[\"MMgan\"][iter_][\"seq\"], data_dict[\"MMgan\"][iter_][\"ids\"]= utils.prepare_data(\"data/gan/generated_seqs/generated_3968_iter_\"+str(iter_)+\".fa\")\n", + "# data_dict[\"MMgan\"][iter_][\"pred\"] = model_dict[\"deepmel2\"].predict([data_dict[\"MMgan\"][iter_][\"seq\"],data_dict[\"MMgan\"][iter_][\"seq\"][:,::-1,::-1]])\n", + "# data_dict[\"MMgan\"][iter_][\"pred_deepmel\"] = model_dict[\"deepmel\"].predict([data_dict[\"MMgan\"][iter_][\"seq\"],data_dict[\"MMgan\"][iter_][\"seq\"][:,::-1,::-1]])\n", + " \n", + "# data_dict[\"original\"] = {}\n", + "# data_dict[\"original\"][\"seq\"], data_dict[\"original\"][\"ids\"] = utils.prepare_data(\"data/gan/Genomic_MEL_regions.fa\")\n", + "# data_dict[\"original\"][\"pred\"] = model_dict[\"deepmel2\"].predict([data_dict[\"original\"][\"seq\"],data_dict[\"original\"][\"seq\"][:,::-1,::-1]])\n", + "# data_dict[\"original\"][\"pred_deepmel\"] = model_dict[\"deepmel\"].predict([data_dict[\"original\"][\"seq\"],data_dict[\"original\"][\"seq\"][:,::-1,::-1]])\n", + "\n", + "# data_dict[\"bg\"] = {}\n", + "# for order in [0,1,2,3,4]:\n", + "# data_dict[\"bg\"][order] = {}\n", + "# data_dict[\"bg\"][order][\"seq\"], data_dict[\"bg\"][order][\"ids\"] = utils.prepare_data(\"data/gan/background_seqs/Genomic_MEL_regions.bg_o\"+str(order)+\".fa\")\n", + "# data_dict[\"bg\"][order][\"pred\"] = model_dict[\"deepmel2\"].predict([data_dict[\"bg\"][order][\"seq\"],data_dict[\"bg\"][order][\"seq\"][:,::-1,::-1]])\n", + "# data_dict[\"bg\"][order][\"pred_deepmel\"] = model_dict[\"deepmel\"].predict([data_dict[\"bg\"][order][\"seq\"],data_dict[\"bg\"][order][\"seq\"][:,::-1,::-1]])\n", + "\n", + "# import pickle \n", + "# with open('data/gan/GAN_data_dict.pkl', 'wb') as f:\n", + "# pickle.dump(data_dict, f)\n", + "\n", + "import pickle \n", + "with open('data/gan/GAN_data_dict.pkl', 'rb') as f:\n", + " data_dict = pickle.load(f)" + ] + }, + { + "cell_type": "markdown", + "id": "f91e15d7-ccb8-4ba5-8579-e99f10364dfc", + "metadata": {}, + "source": [ + "### Plotting prediction scores of the GAN generated sequences at different iterations as well as background sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "7852b39c-83c9-47e7-8655-e59d22491d5b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3968\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8,5))\n", + "print(len(data_dict[\"bg\"][0][\"pred\"]))\n", + "th = 0.15\n", + "for k,i in enumerate(range(0,161000,10000)):\n", + " plt.bar(k,np.sum(data_dict[\"MMgan\"][i][\"pred_deepmel\"][:,3]>th)/3968*100,color=\"C0\")\n", + "\n", + "\n", + "for k,i in enumerate(range(5)):\n", + " plt.bar(k+19,np.sum(data_dict[\"bg\"][i][\"pred_deepmel\"][:,3]>th)/3968*100,color=\"gray\")\n", + "\n", + "_ = plt.xticks(range(23),range(23))\n", + "\n", + "plt.xlabel(\"Position (bp)\")\n", + "plt.ylabel(\"Correctly predicted sequences (%)\")\n", + "\n", + "plt.savefig(\"figures/gan/prediction_percentage_bar.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "6a602d99-8787-43fe-b5ba-9eab03e0c051", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "c = \"C0\"\n", + "_ = plt.boxplot([data_dict[\"MMgan\"][key][\"pred_deepmel\"][:,3] for key in data_dict[\"MMgan\"]],notch=True,showfliers=False, whis=[5,95],\n", + " positions=list(range(0,17)),\n", + " boxprops=dict(color=c),\n", + " capprops=dict(color=c),\n", + " whiskerprops=dict(color=c),\n", + " flierprops=dict(color=c, markeredgecolor=c),\n", + " medianprops=dict(color=c),\n", + " )\n", + "c = 'red'\n", + "_ = plt.boxplot(data_dict[\"original\"][\"pred_deepmel\"][:,3],notch=True,showfliers=False, whis=[5,95],\n", + " positions=list(range(18,19)),\n", + " boxprops=dict(color=c),\n", + " capprops=dict(color=c),\n", + " whiskerprops=dict(color=c),\n", + " flierprops=dict(color=c, markeredgecolor=c),\n", + " medianprops=dict(color=c),\n", + " )\n", + "c = 'grey'\n", + "_ = plt.boxplot([data_dict[\"bg\"][key][\"pred_deepmel\"][:,3] for key in data_dict[\"bg\"]],notch=True,showfliers=False, whis=[5,95],\n", + " positions=list(range(20,25)),\n", + " boxprops=dict(color=c),\n", + " capprops=dict(color=c),\n", + " whiskerprops=dict(color=c),\n", + " flierprops=dict(color=c, markeredgecolor=c),\n", + " medianprops=dict(color=c),\n", + " )\n", + "_ = plt.xticks(range(25),list(range(0,17))+[\"\",\"Ori\",\"\"]+list(range(5)))\n", + "plt.savefig(\"figures/gan/prediction_distribution_bar.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "0a49188b-1436-44fc-897a-fe23e05238df", + "metadata": {}, + "source": [ + "### Smoothed plotting of GC-content comparison of Genomic and GAN generated and background sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "356d3bf2-c04c-4514-8f95-67fa1dae41a4", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def smooth(y, box_pts):\n", + " box = np.ones(box_pts)/box_pts\n", + " y_smooth = np.convolve(y, box, mode='valid')\n", + " return y_smooth\n", + "\n", + "plt.figure(figsize=(6,5))\n", + "plt.plot((np.mean(data_dict[\"original\"][\"seq\"][:,:,1] + data_dict[\"original\"][\"seq\"][:,:,2],axis=0)),color=\"C3\",linewidth=0.2)\n", + "plt.plot((np.mean(data_dict[\"MMgan\"][160000][\"seq\"][:,:,1] + data_dict[\"MMgan\"][160000][\"seq\"][:,:,2],axis=0)),color=\"C0\",linewidth=0.2)\n", + "plt.plot((np.mean(data_dict[\"bg\"][4][\"seq\"][:,:,1] + data_dict[\"bg\"][4][\"seq\"][:,:,2],axis=0)),color=\"gray\",linewidth=0.2)\n", + "\n", + "smt_val = 10\n", + "plt.plot(range(5,496),smooth(np.mean(data_dict[\"original\"][\"seq\"][:,:,1] + data_dict[\"original\"][\"seq\"][:,:,2],axis=0),smt_val),label=\"Genomic\",color=\"C3\")\n", + "plt.plot(range(5,496),smooth(np.mean(data_dict[\"MMgan\"][160000][\"seq\"][:,:,1] + data_dict[\"MMgan\"][160000][\"seq\"][:,:,2],axis=0),smt_val),label=\"GAN (160kth iteration)\",color=\"C0\")\n", + "plt.plot(range(5,496),smooth(np.mean(data_dict[\"bg\"][4][\"seq\"][:,:,1] + data_dict[\"bg\"][4][\"seq\"][:,:,2],axis=0),smt_val),label=\"Background model (5th order)\",color=\"gray\")\n", + "plt.legend()\n", + "\n", + "plt.xlabel(\"Position (bp)\")\n", + "plt.ylabel(\"Average GC-content\")\n", + "\n", + "plt.savefig(\"figures/gan/GC_content_Genomic_Gan_Background.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "c6369a85-cfa8-4307-b9fc-3a2dc6fd6019", + "metadata": {}, + "source": [ + "### Loading and plotting luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "7d9b415e-8ca9-44a5-ac1b-60927b6e033a", + "metadata": {}, + "outputs": [], + "source": [ + "luciferase_dict = {\"ids\":[],\"values\":[]}\n", + "with open(\"data/luciferase/GANall_IRF4_TYR_MLANA.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " luciferase_dict[\"ids\"].append(sep[0])\n", + " luciferase_dict[\"values\"].append(sep[1:])\n", + "luciferase_dict[\"values\"] = np.array(luciferase_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "b74a0306-eda1-4c53-b893-9d4f1ee96fc4", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "mean = np.mean(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "\n", + "index = np.argsort(mean)[::-1]\n", + "temp = sorted(mean)[::-1]\n", + "res = [temp.index(i) for i in mean]\n", + "\n", + "plt.bar(res[:10],mean[:10],color=\"C0\",label=\"GAN generated\",yerr=std[:10],capsize=3)\n", + "plt.bar(res[10:],mean[10:],color=\"red\",label=\"Genomic\",yerr=std[10:],capsize=3)\n", + "plt.legend()\n", + "\n", + "for i in range(13):\n", + " for k in np.log2(luciferase_dict[\"values\"][i]):\n", + " plt.scatter(res[i],k,color=\"black\",zorder=10,s=8)\n", + " \n", + "plt.ylim(-0.15,7.5)\n", + "_ = plt.xticks(range(13),np.array(luciferase_dict[\"ids\"])[index],rotation=90)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "plt.savefig(\"figures/gan/GAN_selected_regions_luciferase_withdot.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "03042895-c95d-4d39-a64b-f5964dae0487", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores and in silico saturation mutagenesis values on the GAN-generated sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "9bde7de7-7ff5-4cd7-b09b-c0efe69635d3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 530_MMgan_160000 MM-GG-1\n", + "# 807_MMgan_160000 MM-GG-2\n", + "# 1015_MMgan_160000 MM-GG-3\n", + "# 1751_MMgan_160000 MM-GG-4\n", + "# 1747_MMgan_160000 MM-GG-5\n", + "# 1931_MMgan_160000 MM-GG-6\n", + "# 2113_MMgan_160000 MM-GG-7\n", + "# 2376_MMgan_160000 MM-GG-8\n", + "# 3045_MMgan_160000 MM-GG-9\n", + "# 3271_MMgan_160000 MM-GG-10\n", + "\n", + "region = '530_MMgan_160000' \n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(37.6,ntrack*5))\n", + "seq_onehot = np.copy(data_dict[\"MMgan\"][160000][\"seq\"][np.array(data_dict[\"MMgan\"][160000][\"ids\"])==region])\n", + "\n", + "st = 130\n", + "end = 365\n", + "\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=seq_onehot, class_no = 16)\n", + "ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=seq_onehot, class_no = 16)\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/gan/530_MMgan_160000_GG1_st130_end365_deepexplainer_topic16.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "d8c5620c-22ba-4a7a-90ac-c643f92e1c71", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "locs = [[120,370],\n", + " [100,390],\n", + " [130,380],\n", + " [160,460],\n", + " [110,410],\n", + " [200,450],\n", + " [150,400],\n", + " [150,400],\n", + " [110,370],\n", + " [35,315]]\n", + "for k,region in enumerate([\"530_MMgan_160000\",\"807_MMgan_160000\",\"1015_MMgan_160000\",\"1751_MMgan_160000\",\"1747_MMgan_160000\",\n", + " \"1931_MMgan_160000\",\"2113_MMgan_160000\",\"2376_MMgan_160000\",\"3045_MMgan_160000\",\"3271_MMgan_160000\"]):\n", + " \n", + " st = locs[k][0]\n", + " end = locs[k][1]\n", + "\n", + " ntrack = 2\n", + " fig = plt.figure(figsize=(40,ntrack*5))\n", + " \n", + " seq_onehot = np.copy(data_dict[\"MMgan\"][160000][\"seq\"][np.array(data_dict[\"MMgan\"][160000][\"ids\"])==region])\n", + " ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=seq_onehot, class_no = 16)\n", + " ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=seq_onehot, class_no = 16)\n", + "\n", + " ax1.set_xlim([st,end])\n", + " ax2.set_xlim([st,end])\n", + "\n", + "\n", + " plt.savefig(\"figures/gan/\"+region+\"_\"+\"GG\"+str(k+1)+\"_deepexplainer_st\"+str(st)+\"_end\"+str(end)+\"_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "961c6734-d488-484b-bcde-132a1a18933f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_IRF4_Experiments.ipynb b/the_code/Human/MM_IRF4_Experiments.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..cba62883b49e2064459d0ce9f8c8e39061c9d817 --- /dev/null +++ b/the_code/Human/MM_IRF4_Experiments.ipynb @@ -0,0 +1,700 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6d54e01f-9de9-47b4-b716-09ea7a184a72", + "metadata": {}, + "source": [ + "# This notebook shows the experiments performed on IRF4 enhancer." + ] + }, + { + "cell_type": "markdown", + "id": "a70647de-e11b-4396-b115-c29ac14b5b6b", + "metadata": {}, + "source": [ + "#### It consists of:\n", + "* Loading the IRF4 enhancer sequence with different motif modifications.\n", + "* Loading saturation mutagenesis assay performed on IRF4 enhancer by Kircher et al.\n", + "* Showing individual mutations generating repressor binding sites on IRF4 enhancer.\n", + "* Plotting the findings. \n" + ] + }, + { + "cell_type": "markdown", + "id": "d325cfac-ea26-409f-b5f2-83288d6883ea", + "metadata": {}, + "source": [ + "#### In vitro saturation mutagenesis assay value file is in ./data/irf4/\n", + "#### Luciferase values are in ./data/luciferase folder\n", + "#### Figures are saved to ./figures/irf4 folder" + ] + }, + { + "cell_type": "markdown", + "id": "a913e9af-ccf8-40f1-915b-6af5dd96629c", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "d9131ce0-69f4-420e-80af-53e290feac19", + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "c918b9b5-d6e3-40a8-840a-aedbe94ee388", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "126d6f8d-72bf-48ea-a210-e1a5bd9fe10a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "fa930a37-d9e2-42c7-9b3f-c2193c0607bb", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "dc4aed56-8ae7-4cae-a859-4684bf78316b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4b16c2d7-6faf-4be8-abc1-4122cf6024fa", + "metadata": {}, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "id": "0276e054-6123-4015-813c-e5d87466a801", + "metadata": {}, + "source": [ + "### Loading the IRF4 enhancer sequence with different motif modifications." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "8d9491fa-4638-4c25-ba5d-f5ff4643fb2c", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "irf4_onehot = {}\n", + "irf4_onehot[\"more_ZEB2\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGGTGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTACCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACCTTGGTAGGTAAAAGAAGGTAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACCTAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACCTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_ZEB2\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCGGATCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCGGATTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_MITF\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATAATGTAAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCAATATAACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"no_SOX10\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGGATGACAGCTTGTGTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAGGTATCTCCATGTGCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")\n", + "irf4_onehot[\"wild-type\"] = utils.one_hot_encode_along_row_axis(\"GCTGCCATTGGTGTGGATTTTAAGTTGGGGAGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGT\")" + ] + }, + { + "cell_type": "markdown", + "id": "676e99bb-fe2f-4606-9fde-23296ca70d88", + "metadata": {}, + "source": [ + "### Loading saturation mutagenesis assay performed on IRF4 enhancer by Kircher et al." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "7b335354-0e6b-4317-a6bc-e49ecdb92ab3", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def get_irf4_in_vitro_mpra_values(shift=396106, pval=0.00001):\n", + " irf4_pos = []\n", + " irf4_score = []\n", + " irf4_pvalue = []\n", + " with open('data/irf4/GRCh37_IRF4.tsv','r') as irf4file:\n", + " for line in irf4file:\n", + " irf4_pos.append(int(line.strip().split('\\t')[1]))\n", + " irf4_score.append(float(line.strip().split('\\t')[7]))\n", + " irf4_pvalue.append(float(line.strip().split('\\t')[8]))\n", + "\n", + " irf4 = {}\n", + " with open('data/irf4/GRCh37_IRF4.tsv','r') as irf4file:\n", + " for line in irf4file:\n", + " splitted_line=line.strip().split('\\t')\n", + " if int(splitted_line[1]) not in irf4:\n", + " irf4[int(splitted_line[1])]= {'A':[], 'C':[], 'G':[], 'T':[]}\n", + " #if splitted_line[3]=='-':\n", + " # irf4[int(splitted_line[1])][splitted_line[2]]=[float(splitted_line[7]),float(splitted_line[8])]\n", + " if splitted_line[3]!='-' and int(splitted_line[4])>=10:\n", + " irf4[int(splitted_line[1])][splitted_line[3]]=[float(splitted_line[7]),float(splitted_line[8])]\n", + "\n", + " array_={'A':np.empty(500),'C':np.empty(500),'G':np.empty(500),'T':np.empty(500)}\n", + " array_['A'][:]=np.nan\n", + " array_['C'][:]=np.nan\n", + " array_['T'][:]=np.nan\n", + " array_['G'][:]=np.nan\n", + " for i in range(500):\n", + " if i+shift in irf4:\n", + " for key in irf4[i+shift]:\n", + " if irf4[i+shift][key]!=[]:\n", + " if irf4[i+shift][key][1]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8,8))\n", + "ax = fig.add_subplot()\n", + "\n", + "ax.scatter(np.array(kircher_mpra),np.array(deepmel2_mpra),linewidths=0)\n", + "import scipy\n", + "scipy.stats.spearmanr(np.array(kircher_mpra),np.array(deepmel2_mpra),axis=None)\n", + "\n", + "ax.set_title(scipy.stats.spearmanr(np.array(kircher_mpra),np.array(deepmel2_mpra),axis=None))\n", + "ax.set_xlabel(\"In vitro mutagenesis assay\\n(Log2FC)\")\n", + "ax.set_ylabel(\"In silico mutagenesis assay\\n(Delta score)\")\n", + "ax.axvline(x=0,linestyle='--',color='gray')\n", + "ax.axhline(y=0,linestyle='--',color='gray')\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_scatter_insilicoMPRA_vs_invitroMPRA.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "5e78ef46-8b0f-4bba-af60-a6a23f8382b6", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores and in silico / in vitro saturation mutagenesis values of IRF4 enhancer" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "3b110fa6-7248-4ba4-be26-4a5ec55a2069", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ntrack = 3\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "\n", + "st = 50\n", + "end = 350\n", + "\n", + "start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 16)\n", + "ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 16)\n", + "\n", + "\n", + "ax3 = fig.add_subplot(ntrack,1,3)\n", + "ax3.set_ylabel('Kircher et al.\\nMPRA')\n", + "ax3.scatter(range(500),irf4_kircher_array['A'],label='A',color='green')\n", + "ax3.scatter(range(500),irf4_kircher_array['C'],label='C',color='blue')\n", + "ax3.scatter(range(500),irf4_kircher_array['G'],label='G',color='orange')\n", + "ax3.scatter(range(500),irf4_kircher_array['T'],label='T',color='red')\n", + "ax3.set_xlim((0,500))\n", + "#ax.axvline(x=185,linestyle='-',color='blue')\n", + "ax3.legend()\n", + "ax3.axhline(y=0,linestyle='--',color='gray')\n", + "ax3.set_xticks(np.arange(0, end-st+1, 10))\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "_ = ax3.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_DX_insilicoMPRA_invitroMPRA.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "3bba9260-1582-4628-9e52-9feb776b433f", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores after applying the repressor creating mutations" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ba577d3b-6e7f-419f-96cd-c14f9ff3151b", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ntrack = 14\n", + "fig = plt.figure(figsize=(4,ntrack*5))\n", + "\n", + "for track,mut_ in enumerate([\"71_G\",\"85_G\",\"119_A\",\"145_C\",\"146_G\",\"160_T\",\"196_C\",\"198_A\",\"202_A\",\"215_T\",\"222_A\",\"233_C\",\"270_C\",\"326_C\"]):\n", + " start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + " st = int(mut_.split(\"_\")[0])-12\n", + " end = int(mut_.split(\"_\")[0])+13\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "\n", + " ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=track+1, seq_onehot=start_x, class_no = 16)\n", + " ax1.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_DX_ZEB2_creating_muts.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "531352f8-11dc-4763-9690-46a72c07da23", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores for the IRF4 enhancer sequence with different motif modifications." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "61ecb79c-107a-4ced-ab49-7dcc76c91bd2", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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9jUrXmqTQnFS7k7lPGbl+uKDyeDrppLHVt7Uly5cLJAMAMO6m6joPa0MAmOpWb15dt7+mY4pMRt7UF0auVqspFAoN7IZpad0dSaGl9p5qkhxwRlKtJMWm2n6xOdnvpOS29zSuRwAAGCcz+l3H5ubm/PM//3P+/u//Pv/8z/+cb3/72/nRj34kiAxMmFKplEsuuSSXXHJJSqXSuNdP1j0AAAAAgOlhXefYw8hd5a4R601G3naVSvKv/1obfDGUcjn5zW8mt6dR6+q3CHTeAZMXNh5vHR3J6tUj1wEAwBhN1XUe1oYAMNU9uunRuv01m6dGGHlt59re7dG+1wp11v1fXxC5eedk/1OGeF+1kDzl1ElvDQAAxtuMDiN3d3fnb/7mb/KRj3wky5YtyxFHHJFXv/rVueKKKxrdGgAAAAAAwHZb37l+VHUbuzb2bo8mjDyaGoZ2/fXJI48MX9PUNDm9jFnXmiRbUtTznjpyfbUyoe0AAAAAMDMMDB9PlcnI5Wq5d3tgYBpGZe1v+7b3+NOkefbgmkJTsvdrJq8nAACYIDM6jHzYYYflO9/5Tq666qp86EMfylVXXZWzzjorr3nNa3LaaadN2H0vuOCC7Lfffmlra8uhhx6aa665Ztj6q6++Ooceemja2trypCc9KZ/73OcG1Xzzm9/MgQcemFmzZuXAAw/M5ZdfXnf+vPPOy7Of/ezMnTs3u+++e/78z/88y5cvH9fvCwAAAAAAmFpGG0be1L2pd7u73D1ifXdl5JptUu7a+sjgGeLyy5Pm5uFryuXhzzdM12NJtZQ0z01mLRq5vjLGb2TRoqStbdt6AwAAAGDaGjh1+NHNjQ/+dpQ66vZXb1rdoE6Ytro3JB0r+/YXH5MM9d56oZAsODiZtevk9QYAABNgxoeRf/WrX+Xwww9PkhQKhbz73e/O9ddfn5///OcTcs9LL70073znO/Pe9743t956a4466qi87GUvS3t7+5D199xzT4499tgcddRRufXWW/Oe97wnZ5xxRr75zW/21lx33XU58cQTc/LJJ+e2227LySefnBNOOCE33HBDb83VV1+d008/Pddff32uvPLKlEqlHHPMMdm4ceNQtwUAAAAAAGaADV0bRlXXP4zckMnImx5Ivn9ocums5JsLkwd/ML6vP0VUq8k3vpGUSo3uZBt1bBnpPGef0dUXxzjiecmSZPny5Oab+74uvri+5uKLt34OAAAAgGmnXClnY3dtPXMhhSRTYwrxwB6mQkCaaWbDnfX7e748KbZsvX7h4RPbDwAATLARnss+vX3xi18c8vgzn/nM3HzzzRNyz49//ON5y1vekre+9a1JkvPPPz8//OEP89nPfjbnnXfeoPrPfe5zWbJkSc4///wkydKlS3PTTTflYx/7WI477rje1zj66KOzbNmyJMmyZcty9dVX5/zzz88ll1ySJPnBD+oX7XzpS1/K7rvvnptvvjnPe97zJuR7BQAAAAAAGmu0YeTNpc2926OZejya6cmjtu53yY+fl3Stqe13rUuuOjY5/EvJk944fveZAn73u+S++xrdxXboeqz262gndBS24bnHS5bUvrZm6dLkkEPG/roAAAAATEn9pyI3F5vTXenOY5sfa2BHNQPDx1MhIM000/NwxyRp2yPZed+t11a6k12fNeEtAQDARJqRk5G//vWvp6ur74n99957b8rlcu/+pk2b8slPfnLc79vV1ZWbb745xxxzTN3xY445Jr/85S+HvOa6664bVP+Sl7wkN910U7q7u4et2dprJsm6dbUf3HfddZSLRQAAAAAAgGln1GHk7r4wcrlSHqayplQZp9G+1Wpy41/XQq7VntesJKkmN74t6Vg9PveZIn7xi0Z3sJ16wsituzS2DwAAAABmjDWb1/RutzTVpsb2Dyg3yupNq4fdhxF19vs9s+sID1gstiTznj6x/QAAwASbkWHk173udVm7dm3v/jOe8Yzc1+8x9I8//njvlOHxtHr16pTL5eyxxx51x/fYY4+sWrVqyGtWrVo1ZH2pVMrq1auHrdnaa1ar1Zx99tn5kz/5kxx00EFb7bezszPr16+v+wIAAAAAAKaPbZmMPJqg8biFkVd8J3n450l1iAB0pSv5/WfG5z5TxC9/mTQ31x+bNy954QuTffZpTE9j0r3ls6JWD7sFAAAAYHys6egLI89qmpUkWd+5PtVqtVEtJRk8CXngpGQYUeejSQq17QV/lIz0vvrO+094SwAAMJGaRy6Zfgb+cDrZP6wWCoVB9x94bKT6gcfH8ppvf/vb8+tf/zrXXnvtsH2ed955+cAHPjBsDTA2TU1NednLXta7Pd71k3UPAAAAAGB62Ni1cVR1HaWO3u1KtTJifXmo8PBYVavJre9O7dm4Q9yzWq6FlZ/x/u2/1xTxy18mpX7rzRYvTn72s+SAA5KOjuRVr0p+9KPG9Tes0uZaQDypTUaulJLijPwoEQAAttlUXedhbQgAU1nPZORCCmlrbktSe49yQ9eGzJ01t2F9mYzMdutcnRSak2p3Mn9pkhEyC1smgwMAwHRlBcE4WrRoUZqamgZNLH744YcHTTbu8YQnPGHI+ubm5ixcuHDYmqFe8x3veEe+853v5Oc//3me+MQnDtvvsmXLcvbZZ/fur1+/Pnvvvfew1wDDa2pqyh//8R9PWP1k3QMAAAAAmB42dW8aVV3/MPJoHuI6msDyiNbcmjy+fPiaQnH77zNFdHQkd95Zf+zSS5MnPam23dKSfOc7U3hCclffhJq07pKMx+8BAACYYabqOg9rQwCYytZ2rE1SG8w0u2V23fFGhpEHTkI2GZkx6+r3e2bBwUlR2BgAgJlt5qzwmAJaW1tz6KGH5sorr6w7fuWVV+bII48c8pojjjhiUP2PfvSjHHbYYWlpaRm2pv9rVqvVvP3tb8+3vvWt/PSnP81+++03Yr+zZs3KvHnz6r4AAAAAAIDpY2P36CYjd5Y7e7erI01nyOgCyyO6979qUyGGvdE4TGCeIm6/PSn3+3YOPzw56qhaCDlJmppqX2ec0Zj+RjQwjAwAAAAA42BNR99k5DmtcwYdb5SBk5Af3vhwgzph2up8NMmWhzrOPWDk+kppQtsBAICJNmMnI//whz/M/PnzkySVSiU/+clP8tvf/jZJsnbt2gm779lnn52TTz45hx12WI444ohceOGFaW9vz6mnnpqkNo14xYoVueiii5Ikp556aj796U/n7LPPzimnnJLrrrsuX/ziF3PJJZf0vuaZZ56Z5z3vefnIRz6SV73qVfn2t7+dH//4x7n22mt7a04//fT813/9V7797W9n7ty5vZOU58+fn5122mnCvl+gXqVSSXt7e5JkyZIlKRaHf+bDWOsn6x4AAAAAwPSwuXvzqOo6S2MMI4+iZliVcnLPfybVHWdx1W231e8vW5Z0d/eFkZOkubkWRv7BDya3t1GpCyPvOqOmVgMAwHiZqus8rA0BYCpbs3lNmgpNKVfL2bl15xRSSDXVrNnc2DDywEnID28QRp5uWj/Ymu5Kd6rvH4eHa26LjodrD9yc/cSkefbI9dv7vjsAADTYjA0jv/GNb6zb/+u//uu6/UKhMCH3PfHEE/Poo4/m3HPPzcqVK3PQQQfliiuuyD777JMkWblyZe8bv0my33775YorrshZZ52Vz3zmM9lzzz3zqU99Kscdd1xvzZFHHpmvfe1red/73pdzzjkn+++/fy699NI85znP6a357Gc/myR5wQteUNfPl770pbzpTW+akO8VGKxUKuUrX/lKktrDB1pbW8e1frLuAQAAAABMD6P9vGOiPhfZqsduTDp3rMV7v/pVLXjc3Z3st1/yylcOXbfTTskrXjGprY1O/zDyrF2T4oz9GBEAALbZVF3nYW0IAFNZ/wnIc1vnplgoplwtN34y8sb6ycgDw8lMfd2V7iS1h3HOap41+Q10bHkPfKc9R1dfbBm5BgAAprAZuYqgUqk09P6nnXZaTjvttCHPffnLXx507PnPf35uueWWYV/z+OOPz/HHH7/V89WqJyUBAAAAAMCO5uDdD86lhUtTqVYyq2lWvvLnX+k9d87PzskfHvtDCinkwN0OTFI/IXkklUpl26dpPXRVUmiqTYXYQdx6ay2InCQvfnFSqSRb+8d3+OGT19eodT3Wtz1rUeP6AAAAAGBGWbN5TapbJsLOmzWv9uDEaho+GXnVxlVJ0jupeW3H2lSr1cl/sCPbbdWGVdlnwT6Tf+POLYF276cCALCD2MYVJAAAAAAAADRaZ7kzTYWmJMlOLTvlxINO7P3aa95eSZJqqilVSkmSzd2bR/3aHaWObW/soZ8l1QEPj33y/0te/PPksE8nTTtt+2tPUffe27f9vOcl5a3ksJuakkMOmZSWxqa8OcmWhZatuza0FQAAAABmjrWda3uHLi1oW5AkKRaKWduxtnFNJVm9qRYkbS7WZnt1V7qzsXtjI1tiGz34+IONuXH3lkD9rIWNuT8AAEyyGTkZub/ly5fn3/7t33LHHXekUCjkaU97Wt7+9rfnaU97WqNbAwAAAAAA2C79A8MtxZa6c21Nbb3bPSHk8oBJxR/60w/l6P2PTpJ8/87v5/1Xvb/3XHele9uaqlaTR69Ptkw7SZIc9L7kGR+sbe92ZLLw2cmPjty215+iHn20b/tFL0paWrZeO2fOxPczZv3D4627NK6P/hYtStrako4xBuPb2mrXAgAAANBwj256tHcy8oK2BSlXymkuNmdNR2MnI/dMZm5tau19L/TRTY9m59adG9kW26AhYeRyR+0rqU1GrpSS4oyPZgAAsIOb0ZORL7vsshx00EG5+eab80d/9Ed5xjOekVtuuSUHH3xwvvGNbzS6PQAAAAAAgO1SF0Zuqk+/zmqe1bu9qXtTkmRzqX4y8tLdlubZez07z97r2Vm6aOlWX3tMNtyddK/v25/9xOSgf+jbLzQlC/842e+N2/b6U9Dmzcmm2j/iLF5c+xpOpTL8+YaoltM7GbllbkNb6bVkSbJ8eXLzzX1fF188uO7ii+trli+vXQsAAABAw/VMIE6SXXfaNdUt/+sJA4+nZT9elsMuPGzEuu5y3xTktua+hzr275WpbWNX3xTrlRtWTn4Dnf2eTtm6sP5hjwAAMEPN6MfvvOtd78qyZcty7rnn1h1///vfn3e/+9157Wtf26DOAAAAAAAAtl//wHBrU2vdudam1hRSSDXV3jDywIBx/8By/+2hakftsZvq9w86J70h1x7VSvKMc5NrXrNt95hiHn64b/uP/mjk+nI5KU61RwZXy0mhkKS5FhifKpYsGTlYvHRpcsghk9MPAAAAAGPy2ObHercXzV6UJKlUKxMyGfmff/HPva9fLGz9Dbj+Pc1umZ3HNj+Waqp5dPOjW72GqaV/ALkhk5H7h5FnLZz8+wMAQANMtWUO42rVqlV5wxveMOj4SSedlFWrVjWgIwAAAAAAgPHTUepIZcvEhaHCyD0L7nqCxQMDxv2vGXj9NoeRH70xKWyZ0jz7icn+b0mKA56PWygmOy1O9nrFtt1jinnoob7tZz4zKZWGr29pGf58Q1TLtV+HWaQJAADAju2hDQ/lLy77i/yi/Rdjuq6jI7nttuT3v0+q1QlqDpiy1nWu691eOLsW2qxUK3WB4PH2yMZHhj3ffwLy3Na5KRQKg44ztfUPIDcmjNzv98qsRYPfAwcAgBloRv+t9wUveEGuueaaPPnJT647fu211+aoo45qUFfATNbU1JQXv/jFvdvjXT9Z9wAAAAAApoeOUkeqqa3indVUP9m4tam1toiummwube6tH1gz1PZQtaP26P8m1e7a9p7HZtBU5B7VarLHn27bPaaYsU5GnpK2hNqn1FRkAACYYqbqOg9rQ5gs313+3Vz6f5fmNw/9Jv93+v+N6pqrr07e8Iakvb22/7KXJf/+78lee01go8CUUa1Ws6FrQ+/+brN3691+dNPETSF+YP0D2WPnPbZ6vmcCciGF7Dxr5yRJsVCc0J4YXysf75uMvOLxFZPfQFe/3yttu3vIIwAAO4QZHUZ+5StfmXe/+925+eabc/jhhydJrr/++nzjG9/IBz7wgXznO9+pqwXYXk1NTXnuc587YfWTdQ8AAAAAYHroLHX2TkZuaaoft9tSbKmrSyYpjLzh7r7tJxxTC7kOtRCr2JTscui23WOK6T8Z+cADk+bp+AlctZykIIwMAADDmKrrPKwNYbKs3lybAtlRHt17Bv/zP8nLX570z8hfeWXyrGclv/tdsuuuE9ElMJU83vV47/uXbU1tWdC2oPdcTyB4Ijyw/oEcuufW33vsmYBcLBQzf9b8VKqVNBebJ7Qnxlf/acjt69onv4GutX3bbbtP/v0BAKABpuNSiFE77bTTkiQXXHBBLrjggiHPJUmhUEi5XJ7U3gAAAAAAALZXz8TjZCuTkbdMJe4sT1IYuVpNOreMCS4Uk8UvTorDfBzV3Db2e0xBDz9cCyCXSskeWx+4MrVVt3xWJowMAADAVjy4vhb8WtexbsTalSuTk09OisWk//LMUilZsyY555zkM5+ZqE6BqWLN5jW927NbZ2fn1p1799d2rB3Xe23q3tS7/cD6B4at7ZmAXCgUegPS1Wq1N6TM1LdyQ99k5Ic2PDRM5QSplpIUklST1oWTf38AAGiAGR1GrlQqjW4B2MFUKpWsXFl7g2Px4sUpFoeY9rEd9ZN1DwAAAABgeui/wG5W8+Awco9tmYzcP+g8at1rk0p3bXvuAUnL/OHrK6Xhw8rTxEMPJYVa7nv6TnUyGRkAAEY0Vdd5WBvCNittSn77weSuL9Z+Llzy2uSZ/5y0Lhiy/MENtTDyaCaHnnlmsn59MtQyzlIpue667WkcmC7WdPSFkee0zMnc1rm9++s714/rvVasX9G7PWIYefOjaS42p1qtZtedam/oVaoVk5Gnkf6Tkdd1rktnqXPQe+QTqtI/jLxg8u4LAAANtMO869jRsQ1P7wcYo1KplC984Qv5whe+kFKpNO71k3UPAAAAAGB66B9GbhswZbh/uLir3JVkEiYjb+6bRpGFzx779dPUww/XpjzNn5+0tDS6m21U3bI6vDDMx4cb25PHbklW/E9yz1drX49YPQ4AwI5jqq7zsDaEbdL5aHLFwcntH006H0m6Hkvu+kLy3acmG+8f8pL+Qb/h3H13ctll9RORB5KZhx1D/+nH82bNq5uM3F3p3rb3ILeifwD5gceHDyOv3rQ6hRRSrpazcHZtqm011Ty88eFx64eJdf/6+j+r+k9KnhTVcu0JlYXmpDhd3xQGAICxmf6Pmh9GuVzOhz/84Xzuc5/LQw89lN///vd50pOelHPOOSf77rtv3vKWtzS6RQAAAAAAgG3Wf7HerKatT0buKnelWq1mc/fmrdZMSBi53JUMeN06M2AqcpKsXFmb9LTHHmO4qL09Wb168AutXZssWJAsXlx/btGiZMmS7ex0GD2jnVMd+vzG9uS7BySVIX5fHP3LZLcjJqw1AAAAxlmlnPzidcnG+5L0G11cLSdda5Jb/y75k68NumykcF+P88+vhY2HCyMPNTEZmHnWbO6bjDxv1rzMap6V5mJzSpVS7/nFcxdv7fIx6R9Gvm/tfcPWPrr50VS2PJxv99m79x4XRp4+Bk6/Xvn4yuy7YN/Ja6C65Q+5QtPk3RMAABpsZqzw2IoPfehD+cpXvpKPfvSjOeWUU3qPH3zwwfnEJz4hjAwAAAAAAExrm0u1cHEhhUFh4tam1lS3BEurqQ45aWRCw8i7HDJ8EHkGWbnl29599+HrerW3JwcckHSM4Z9xW1uyfPnEBZJ7Fs1VtrJSvHP10EHkJNlwtzAyAADAdPKHC5JVVw59rlpKHr9zyFMrH+/7uX9dx7rMb5s/qGbz5uQLXxg+iAzsONZ09IWRe/6bMbtldtZ3ru89PyFh5HXDh5Ef2fhIylvCpE/Y+Qm9xx/d9Oi49MK2W7Mmufvu2rMZ99ln63UPbXiobv/Bxx+c4M4GqJaTFISRAQDYoRQb3cBEuuiii3LhhRfm9a9/fZqa+v6i/4xnPCO/+93vGtgZAAAAAADA9usJDBcLxSHDyANrO0odKRaKQ9b03y6ksO1h5J7FV3MmcIrvFPPwloEpo56MvHr12ILISa1+4CTl8VRoSlLtm+gBAADAzFTuTH77TyMUDR5bXK6Ue4N7SXL/+vuHvPJHP6oFkgd60pPG8BAvYMZYs3lNmgpNKRaKmTdrXpJkTsucuvPjpf9/l1ZtWJVqtbrV2v4TkPfYue9Nvf7haSZXZ2dy3nnJXnslhx2W7Ltv8rrXJQ88MLh2Y9fGbOzeWHesMWHkCCMDALBDmdFh5BUrVuTJT37yoOOVSiXd3d0N6AgAAACYKN3dyYMPJhs3jlw7Y5Q7k99/JvnfU5Pb3pdsmuQPWAGAhussdSZJCoWtTEbut+CuJ4xcSKGuZqjtYqG4HZORt3z8NGvHWGFcrSbr1tW2d989qQxerz099CyaE0YGAACY2e75StL58Mh1A6zasKpuv31d+5B13/1u0tzct794cS2gfNddtc9xzjsvaZLbgh3Gmo41KRaKKRaK2bll5yTJzq07150fL/ev6wsjd5W78ujmrU857h9G3n327mku1v7D1VHqyObuIZ6owISqVpM3vSl573vrH2hx2WXJEUfUpiX3t3LDykGvMdSxCWUyMgAAO6AZHUZ++tOfnmuuuWbQ8W984xt51rOe1YCOAAAAgPFWKiWf/3xtMcteeyXz5ydnnDGxQ+OmhEdvSr771OSmdyR3/Udy+z8n39k/+cNnG90ZADCJuspdvdtDhZEr1b5kbGepc9Bk5FlNs4bcLhS2cTJyx8raIqyWBcmAfmaqSqUvgLzHHrW/n05LhWKSaoaafgUAAMAMcsfHk34PKhutgZOQ+4f+elSryfe/3/ezcaGQfP3ryQteUNtvakre9a7k7LPHfHtgmlrbsTZJUkghc2fNTZLeCcn9z4+He9fdW7f/wPohRupu0T8EPb9tft205uFCzEyM885Lvva12p8j/ZVKycqVyVln1R8fagpywyYjF4cJI29sTx67JVnxP8k9X619PXLd5PQHAAAToHnkkunr/e9/f04++eSsWLEilUol3/rWt7J8+fJcdNFF+d73vtfo9gAAAIDtVK0mp5ySfPnLtQUtSVIuJxdckHzve8nNNye77NLQFifGhnuTn70k6V6XpJpUu2vHq+XkxtOSnfdPFh/TyA4BgEnSE0YuZCuTkTN4MnJ/LU0tdfU9CtnGMPKmB5JUkp0Wj/3aaap/+Hj36TwM2mRkAACAmW/tb5PHl9cfK7Yke72q9usD307Km4a8dGD4eGA4OUnuvrs2/bjH296W/MmfDLhdMfmnf0ruvHObvgNgmlm1YVVKlVKaCk2pVqt5YP0DmdVceyhiIYWsfHz8ptmuWL+ibv+B9Q/kmU945qC6cqWcxzsf792f3zY/c2fNzbrOdUmSRzc9mifOe+K49cXw7rsvef/7t36+XE5+/ev6Y0MFj4cLn0+I3uT0Vh7wsbE9+e4BSWWI99mP/mWy2xET1hoAAEyUGR1GfsUrXpFLL700H/7wh1MoFPIP//APOeSQQ/Ld7343Rx99dKPbA2agpqamPP/5z+/dHu/6yboHAABMFx/6UC2InNQ/JblcTtrbk3e+M/nKVxrR2QSqlJOrX5l0r99KUKSQ3PY+YWQA2AFUq9URJyP3NzCM3FRoqpuS3Fys/9hoc/fmsTe1acuCvx0ojFzu91eytra+h+RMO4Wm2l+qq9N1tDMAAEy8qbrOw9oQRm3Fd7b8/Lflh9k5+yQv+H4yf2ltf+P9ydUvH/LSQZORhwgj//jHtZ+Lq9Vkzpzkox+tbQ/8WblQMB0ZdhRX33d1qqmmVC3lU//7qXzqfz/Ve66aar5/5/fzd8/9u+2+T0epo27acbL1cOqajjW9D3EsFoqZ0zIn82fNzwOp1ZuMPLk+8IGRawb+ObLy8ZUppJBqqikWiqlUK0P+uTShRnq4Y+fqoYPISbLhbmFkAACmpRkdRk6Sl7zkJXnJS17S6DaAHURTU1Ne8IIXTFj9ZN0DAACmgz/8IfnHf9z6+XI5+e1vJ62dsWlvT1avrj+2cmWydm1te8GCZPGAAM+iRcmSJcm9X03W/WaYF68Ocw4AmEm6K911k49bii115/tPPU4Gh5EH1hcKhbQUW9Jd6e6tH7OOh2q/7kBh5P6TkZubp3kYOdXaV2lT0jy70R0BAMCUM1XXeVgbwqituCKpVmrbhWJy5H8lc5/cd36nxclR30yue8OgSwdORr537b2Daq6/Pmlqqv2s/MpX1gLJQ2lpSQ4/fFu/CWA62dQ99LT1Hms71o7LfcYyKffRTX1h49kts1MoFLJL2y69x1ZvWj3UZUyAe++tPVy8Uhm+rjrgI/D+/75nt8zOhq4NWbVh1fg3OJxic5JqUvFwRwAAdhwzPoy8du3aXHbZZbn77rvzt3/7t9l1111zyy23ZI899shee+3V6PYAAACAbbRs2chBj4EfSk4J7e3JAQckHWMM97S1JXf8OrntPUkKGTZ0bJodAOwQBoaFRzMZeXNpc6pb/pLU3DT4Y6LmYnNvyHnMYeRqJSlvWVy40+LaIqzijP8oalAYedrqNyU73WuFkQEAAGaarnXJo9en9/OFpe9OFh1e//NgsTnZeb/kgDMHXX7fuvvq9u9dc++gmrvu6vs5+S//sra9tZ+Vi8WhjwMzS1e5a9jz6zvXj/gamzbVnuu8YEGycOHQNUMFj7cWRu4fNp7bOjdJsstOtTByIYW6sDIT66KLBn/mP3t2cuCByQMPJKu2ki9euWFl74M6F7QtyIauDVnfuT6dpc7Map41wV1vMdJkZAAAmIFm9Ns5v/71r/PUpz41H/nIR/Iv//IvWbtlutDll1+eZcuWNbY5YEaqVqt5+OGH8/DDD/cu6BvP+sm6BwAATHW/+U3yzW/WBz+mjdWrxx5ETmrX3HtZsnlFTD8GAJL6MHI11VGFkTtKHamkNmZi4GTkpG+acrVaTUd5rGHkfouudlrcN2lphiv3+7abmqbzZOSW9P49s2tNQ1sBAICpaqqu87A2hFF56Gd9P7sXZyVP//v6IHKPQlOy5PhBh+9Ze0/tdGo/+K7csHLQ77e776792tqavPjFwz+0a6QpmMDMUK4MH9Tc2LVxq+c2bEj+4R+SPfZInvzkZLfdkhNPTH7/+8G1A6e3J0NPcE+SRzf3hY3nzZqXJJnfNj9NhaY0FZtMRp5EX/1q/furxx5b+7Pkxhtrz/j+p38a+rr71/f9+95t9m692ys3rJyoVgcrNCWpCiMDALBDmc7PZx/R2WefnTe96U356Ec/mrlz5/Yef9nLXpa//Mu/bGBnwEzV3d2dz372s0mSZcuWpbW1dVzrJ+seAAAw1X3hC7UFLP3DyE9/evKCFyT33JNccUXDWptYa79T+1Cz5wPNWYuSg9+fLH5p8vidyW3vTdbc0tgeJ0FXV/KNbyS/+12y667J61+f7L57o7sCgMlXF0aujiGMvCUkPPB80hdQrlQrY5+MXOn3l7OWBdM4lTs2AycjT9tvu3VB33an6S8AADCUqbrOw9qQHVR7e+0BqP2tXJmsXVsbH7p4cf25TdcmheakWkr2ennSMm+YFx/8w21P0K+1qTWd5c50V7rzyKZHsvuc2hv0pVLt9kly+OFJW9vw7Q8XVAZmhkql0ju9dms2dg8dRt6wITnmmOSGG/oeXlCtJt/6VvLDHya//GVtem6PB9Y/kEIKqaaapkJTytXyoInuPfpPPl7QtiBJMq91XopbHtDQP6zMxLnrrvpg+UEH1R5I3vPXmJaW5L3vTR55JPn5z+uv7R8+33Punrl11a1JkgcffzD7Lth3gjvfwmRkAAB2QDP67Zwbb7wxn//85wcd32uvvbJq1aoGdAQAAABsr0ol+a//qg99/OM/JuecU9suFpNrr01e+tKGtDdxZifZ9L/JlkmGad45OfoXyc5PSorNyZx9kie8KLnyqKTS1chOJ9RPfpKcfHJtQVNLS+1J2X//98n73lf7mrbhHwDYBtsyGXlzaXPvfs8U5KGuqaaaju6xTkbu9xe0YnOGWrjMFosW1VZld4zhn3FbW+26idK6S9925+raZOuhJmQBAADQeO3tyQEHjO3nyrc1JUdt+Vl9n79IKt1JcfB7A0PpLHX2hvPmtM5J5+bOJLUwWE8YecWKvsDgC1+YdHfX3scHdlyPdTw2Yk1nqXPQsWo1efWrk//938FT1EulWlD5bW9Lrr667/gD6x/o3Z43a17WdKzJqsdXpVqtpjDgA8RfrfpVb3B5Q9eGfP6mz+fuNXenXC2nWq3mtw//dmzfKNvku9+tfbZfqSSzZyf//d9JU1PtWH8f+1jy5jfXH3t448NJkmKhmD123qM3gL7y8UmejFytJiknlXJSbJq8e2+j9vZk1arkiU9M9tyz0d0AADAdzegVBG1tbVm/fv2g48uXL89uu+3WgI4AAACA7XXDDfUP+j/ppOT97699KNnzweQRRyT/8R+N6W/CPDPpDSInyRFf6QsiJ1sWDBWS5/13MmvXSW9vMvzgB8nLXpY89FBtv7u79uF0V1fyD/+QfOITje0PACZb/4V6o5mM3FnuzKbuTVs9n9QHlDeVNg06P6z+YeTCjH4ebp2mfmvMSqUt689GsmRJsnx5cvPNfV8XX1xfc/HF9eeXL69dN1HqwsiPmegBAAAwla1ePbYgcpIsKtd+di80J4tfOnwQecDDqVY8vqJ3e5e2XVLY8gCy9nXtvcfv6zeA9GlP8/BQILl37b0j1pQqpUHHLr44+fGPaw8lHkq5nGwa8Nbl/evv753CvHCnhUmSjnJH1nasHXT9DStu6K39v0f+L2/7n7flB3f9IJVqbZLzr1b9asS+2X7f+U7f9l/+ZbLfflt/iMUpp/Rtb+ja0DtRe96seVm006IUC8UUC8U8+PiDE9jxAIWmpGfyd/e6ybvvNvjVr2oPc99nn+Q5z6mFkY8/PvnDHxrdGQAA082MDiO/6lWvyrnnnpvu7u4kSaFQSHt7e/7+7/8+xx13XIO7AwAAALbF5ZcnzVuyLfvtl3zhC4OfiN3UlJxwQvKa10x+fxPmsCTZknTZ89hk79f0BZF7FJuTWQuTJ5862d1NuAceSI47rhbwGfjvu8fA/A4AzHTbNBm5u28y8qymWYNes/81/YPLo1IZEEbeQVYdN/f7K1m5PMowclILFh9ySN/X0qX155curT8/kUHkJGnt90CbrjVj+EYAAACYFvbY8uui5yQtO4/p0vvX3Z8kKaSQhbMXplAopFgo5v719/fW3HtvX/3++9f/vAzsmHr+2zGcSuo/+Fu/PnnnO0d+a3FgULl/8Hnx3MW92/0nJvdY07Gmbr8nmNyjJ+jKxLrttr7PfU89detvRzY3J899bt9+/+nHu+60axbNXpRKtZKmQtPkhpGLzekNI3c9Onn3HaOrrkqOPLIW8O9RrSbf/nYtmLx8ecNaAwBgGprRb/d87GMfy7HHHpvdd989mzdvzvOf//ysWrUqRxxxRD70oQ81uj0AAABgG1xxRS2QmiRve1steFwc4nFrlUryxjdObm8T6ilJsuVT9aecllS6h55aUGxJ9nz5ZHY24arV2r/rrq7hMzE7SN4JAHr1DyMng8PH/feLhWItjFzqF0ZuHhxGbmtq690ecxi5/2TkYnOSIf5w3tiedK6ubW9emXStTXZ+UrLbEWO71xTSf3F1afAgl+mj/2TkrjX+cgUAADCTNCVZsGV7l0OSannLRMfR6QkdFwvF7DFnj97QV/+g4b331n5GLpVqD5MFGG0wdFPXpsxunZ0k+eIXkzUDnpM3e3btuX0rViSrVg39Gv1Dx3vN2yuFFFJNNQ+sfyAH73FwXe36jvXD9tNd7h5V3zNae3uyenX9sZUrk7VrkwULksWL688tWjSmhyk+/njy2GO17f33Tw49dPj6/r8fVm7oCyPvNnu3LJy9MOVqedC5Cdc8r2+745Fk7lMm796jtHx5bSJyd/fgB36XSrXw///7f8nVVzemPwAApp8ZHUaeN29err322vzsZz/LzTffnEqlkkMOOSQvfvGLG90aAAAAsA0qleTOO2vbra3JKads/cn6xWKy996T19uEaknSkw1p2z3Z82VJYYgEdo8BQaTp7qqrku99b+Q6w/sA2NGMJYxcSCEdpY66gPGQk5Gb+67pP0V5dPqFV4f6g3lje/LdA5JKx+BzR/9y2gaSm/qt3R7TZOSppmVukmKSStL12OBF6bMWJcW2of/9tS6YhAYBAADYZovS92P7zk9KKuX6H2hHcP+6+9O05efEPefumSSpVCtDTkZua0sWLhyHnoFpb9WGrSSHB7hv3X1ZutvSVKvJZz5T//7am96UfPzjyS671N57++IXk9NPr7++q9yVxzbXkq1zWuZk8c6L01xsTnele8jJyBu6NwzbT0+wdYfV3p4ccEDSMcT7gFvT1lZLvo4ykNzzmX+SvOIVtX+3o/1jqX/Iffc5u2fhTrU/dMrV8pD/vifMrH5/2HU8lFQrw3+GP8nK5drD28vlwUHk/jWbx/oxAAAAO7Sp8zfecVapVPIf//EfefnLX553vOMd+cpXvpJrr702Dz74YKrTdhUIAAAA7NhWrEg6O2vbL3xh7aHLw+meKQ+t3j19i4T2emWGnDLYX3UrnyZOUx/7WH3ofO+9awsRbr89+Z//SZ73vMb1BgCNNKYwcqEWRu5/zVCTkfsHlAe+/ogK/f7ArpYGp3I7Vw8dZE2SDXeP7V5TSP+/p3R0TOMwcqG4JZCcLZORB3yMOGdJ8orlyREXD752p8WDjwEAADB17N5ve+f9k+LY5tjcv/7+FAqFlKvl7DN/nyRJNdXcs/ae3pq77qpNWdxnn/FoGJgJHtr40Kjq2te1J0luvrn235IeJ5xQCx/vsuWhzU1NyVvfWjvW38rHV6aa2ptyC2cvzG6zd0s11bQUW4YMp47mfc+NXRtH1fuMtHr12ILISa1+4CTlYfzhD33bf/ZnI9f3Dyo/+PiDKRaKaS40Z9HsRVk4uy8UfP+6+4e4eoL0DyN3PppMsRD7V76S3HBD7c/m4Yx0HgAA+puRk5Gr1Wpe+cpX5oorrsgf/dEf5eCDD061Ws0dd9yRN73pTfnWt76V//7v/250m8AM1NTUlCOOOKJ3e7zrJ+seAAAwVf3+933br351LWzc0rL1+uHONcyiRbUnQ4/lA9z+2Y4n/nntg8zCMG/rjHERUSPdckvyqU8l3/xm7anLBxyQ/L//l/z1X9f+Ma1alfzgB31Pa95vv+T662uLDlpakic/OXnpS5PXva7+Q2sA2BFsy2TkzlJn77GhJiP3Dyh3ljsHnR9WcUAYOdM1lTs2/d92feSRxvUxLlrmJ93ramHkocxZksxfOrk9AQDAFDJV13lYG8KIdk/tx/RCknlPHfPkxvvW3ZdSpZZW2nfBvn3H197Xu/3oo7Vf9903AEmS1ZtGF07tCQx/9au1B/+VSsnSpcnFQzwTr1hM3vCG+vfh+k9p32POHtltzm4pVUppLjbXnetRrowcGr1rzV15xh7PGFX/jN2dd9beVy2Xk2c8Y/RTkZNa+LypULtg4U4LeycjJ8mqjaObxj0uZi3q2+5cPaWeUlmpJB/6UFIo9LW1337JmWfWPo//1a9qn9GvXNnQNgEAmIamz8rUMfjyl7+cn//85/nJT36SP/3TP60799Of/jR//ud/nosuuihveMMbGtQhMFM1NTXlmGOOmbD6yboHAABMVcuX931g9oIXTNGwcY9KKVl1ZbLmV0mxNVl8TLLg4GTJkto30v/J0HfckZx0Uv31F19c+5Q9SR79cvLIBUnKyS7PmlZh462pVpPPfz55+9tr/057nrh8xx3JWWcl//mfyfe+V1t00GOXXZKrruoLIie1XyuVWt3pp0/6twEADTUwjNzSVP+Xo5Zi/X5HqaMuYNzW3DboNfsf267JyJXtCyP/09X/lB/f8+Nc9aartvk1JktTU9/fUR96qH5S8rQza9dkU/vWw8gAALCDm6rrPKwNYUS7JymntmJ0zthHF9+zpm8C8pN3fXLv9iObHukN/HV11Y7tvXftZ+RCYftaBqa/xzY/Nqq6lRtqicjvfa/vM8N3v7v2a3GIZydUq8mb39y333/68RN2fkJ2m71bkqRUKfVOXe5RqVR6pygP55419wgjT6A//KH258Ts2cnuu4/t2gc3PJhKtZJCoZBFsxdl0ey+UPD6zvXpKHUM+d73uOs/Gbnr0cEP+pi1KCm2JZUh3mdvXTChrf3858ndd/ftP+c5yU9+krS21j5ff/GLk1NOSZ773AltAwCAGWg6L4fYqksuuSTvec97BgWRk+SFL3xh/v7v/z5f/epXhZEBAABgmvn972vhjnJ5ij9Zf8UVyfVvSjofqYVyqpXk1r9NFh6e/MnXa4HkJUuGf42lS5NDDqltX/+ZZHWh9mHl7D0nvP3J8PnPJ2972+DjPU9mvu225K1vrU1G7pmK/M53JnvtNfjJ2MVi7bq//dsJbRkAppyxTEbuqe8q11YGF1IYdD6pn5bcUztq/R+YUuke27UDnHPVOUmSNZvXZJeddtmu15pohUIyf36ydm3y8MNDL5CcNmbVFmpm84ON7QMAAIDhLVqUtLUlHaN8kNic1KYit+2RNI09oNU/6Lfn3D0zf9b8rOtcl0q1kpWPr8ze8/dO95a3Anbaqfa+/jYP6d7Yntz95eSBbyeljcn8pyf7nZw88ZVjnugMNNa6jnWjqnto40Pp7OwLT+62W/L612/9oX+FQu3hxT0eWP9AmgpNKRQK2X3O7tltzm695+5de2/dtUNNSh7KwOsYX8uX903AHqsH1j+QcrWcVJOFsxcOev941YZV2XfBvuPT6HCaZtceSl7pqk1GHvhA8TlLklcsTx6+JrluwIPJd1o8oa194Qt9U8YPPDC58spk1qy+/081Nyfz5tVCy29844S2AgDADDMj35n59a9/nZe+9KVbPf+yl70st9122yR2BOwoqtVq1q5dm7Vr16ZaHfnpeWOtn6x7AADAVHXHHUl3d7LPPrWn9k5Jd3w8ufrPks5Ha/vVUpItadrHbkp+8fqxv+a6O2qvs/OTR66dBm66KXnHO4avKZVqQeTf/Ka2P3t2bWLy1hYvNTUlT3nK+PYJAFNdZ7kzxX6LcIcLI1dTTUd3vzByYegwcmtTawqpjS4acxi5/2TkztV9TxnZDresvGW7X2My7LZlfeNDDzW2j+02a2FtYffmB5PyGCdjAwDADmCqrvOwNmQHtGRJLcl18819XxdfXF9z8cV95171Z7U30mc/ccy32tC1IY93Pd67v9uc3eqmUPYE+3rCyC0t2/GWwL3/lXzvaclvz03W3JI8vjxZ8Z3kmlcnP31J0rF6G18YaIRNpU11+02Fpt6v/tZ3rM/vf9/3gOITThj5gX89E5STWji1WCimkEJ2m71b72TkpG/qco8719w5qt5XPL5iVHVsm+XLa79uy+e7//fw//VuX33v1fnXX/5r3Xvdk/aecqGQtCyobfesDRhozpJk/jYkrrdDV1dy2WV9/x/5l3+pPb9kYLi/paUW6j/llEltDwCAaW5GTkZ+7LHHsscee2z1/B577JE1a9ZMYkfAjqK7uzuf/OQnkyTLli1L6wjpiLHWT9Y9AABg0rS3J6sHLBxZubI2Vi5JFixIFvc9FfiO2w5K0pqnPnWyGhyjB76T3Po3W3Yqg89XS0l50+DjI3l8y6ex8w7Y5tamikqlNvF44EKkZz0rWbiwtiaq522bTZtqH5YmyWtek8ydO/xrd3fXPjQFgB1FR6mjNzicjBBGrlbrFv9tbTJya1NrioViytVySpVS/j97Zx0e1bX14XckLlgCBHfX4hQoFUq99Nbdb/Wruxt1N+rKrRdKqUBpkeLuBCfEjbiNnfP9sUYzk2QmJCG0+32ewDln9rGZI3uvtX5rOTQHJmOQpYy8gwirsiDY9aqRW57rnl6buZYTe5xYr+00JUlJsGePVEY+qglvBZgADcoONHmgnEKhUCgUCoVC0dxprnEeKjbkX0qXLvJXE/37wzHHyHRlHJTo9aqKnFbsqSIaGx5LuCmcpNgk9hXuAyC1OJXxnce7xcjh4fUUI+95D9behJRw9tqA7lRT5S6C1dfAcT/XY+MKheJI0K1lN3Yf2g1Ar9a9uGHEDe7PHv7rYayaFaPBSK/Wvdi2zbPeBRfU/RzxFlamlaRh1+wYDAYSYxJ9KiNX2CoosZQQHxEPQEphSlDHnlWaVXcjRb3QNCgokOnevUU0W1MV7EAcqvQIf7/e9jUGgwG75lGnr0hbwX/6/6ehDrd2ItqAJbdmMfIRYNcusFhketgwOO20mtuGhcFZZzXJYSkUCoVCoVAo/iH8I8XIDocDcy2jEpPJhN07JZZCoVAoFAqFQqFQKBSKpic1Ffr2hargKq7pQAYynu/bFxyOmqvkHhGqcmHFpfgFyfgRQKRcG7oGVqc3Nq4PaDYw1k9x+9bqt1hycAk/XPBDvdZvCH79FTZv9sz37QuzZsGAATJvtcILL8Djj/teGpdeWrcjWgmRFQqFQvFvo8pehcFgcHc9qouLzUbPi1PTNSpsXmLk2ioje22zyl5FTHhMcAfkqgRhK4LKLF9xcgisy1znnl6bubZe22hqkpKkWstRXxk5vJVnuniH9D/rKSpXKBQKhUKhUCgUCkUzQrMCOhhCN6S7Kh8D7orISXFJ7iqkLrGyq6JpXdVMA5KzBNbe4pypwceiO8TeoFAojhpKLCWAJEYc0nYI94y/x/3Zi8tfJK8iD5PBRImlhO3bxddns4mAMhQ/cEpRCjo6uq6TGJ1Ii4gWmI1mt0A1vSSdAYkD3NPB4J0w8V9HQoKU0g3Sjw9I+4SEGj/WdTEfA+7kFQDdu3veH8GQXZbtM+/QHX6vjZSilOA3eLhEtoWSZKjKrrttE+Hti7/uOpXQW6FQKBQKhULRsPwjxci6rnPVVVcRERER8HOLK92PQqFQKBQKhUKhUCgUiiNHfn5IDkwbYWiI17l372YoRt72NDgqcXs724yGodOh7fGyPPVb2HR/6NvVvLyxsd3rWU5AuG3ebQDklef5ZARvSl58UX43hwPGjIH58yE62vN5eDg88gj06AH33CPiY7td2oaSEVuhUCgUin8DdVVGNhgM7qA7HZ1ya7nns1oqI3tvMyQxMkBUe6cYOTP4darhLUZelb6q3ttpStq1kz5OUVHolTyaFeGtcSfPKdsrgd40p063QqFQKBQKhUKhUCjqhWYDdAhgC3BTngqWfBH8WosgtgckjvOpIto2pi1V9ipaR7XGiKiOXaIv11jYW2QWFA4rrLrKd1lYS+h0poxT81fCoTWyXHeEuHGFonly8683M2PdDFZeu5KxncYe6cNpNAoqJOGy0WAkNiLW57PY8FjyKvLQ0SmsKiR/m/gPk5IgPj60/WzK3uSevnrO1Vzz8zU+lXLn7JzjFiNnlgZnt/Suvvuvo0sXKa+bn+9ZlpwMl13mmZ85E/r398wnJMh6TnRdElJ/8gksWiRhAV26wPnnw3//61ktKiq0JBZbc7bW2SajJCP4DR4ukW0BI5SnyPustvdsE7Fli4iP7Xb5yeoSIjermAuFQqFQKBQKRbPnaA2FqJUrr7yyzjZXXHFFExyJQqFQKBQKhUKhUCgUiobCisdxFxfnyZxcH2btmMWGrA08c+IzDXBkQGUO7P3AEwTT9WIY9xlglEpyxljofgW0PwnW3xXatjWvpGqmSDDUp6SAVEN0sSx1Gef0P6de2zkckpNh2TKZDg+Hb76BmBh/sY7BIJWQn3kGcnNF3NOqlf/2FApF/bFaYfFiWLAACgqgbVs45RSYMOHoCjoY+9FYVmesRntMk0qujUHhFsj4GUp2SmX6hHHQ8UyISmqc/SkU3jgssOc9OPgNFKwHNGgxCLqcD31vp8rum9glkLg4zBjmDrzzFiPX1L76sur7qJPoTnK/HEalojUZa9zTmaWZRzSRSrC0bSsBdroOhYWQ2LwPt2bCW3n6tCW75LmnUCgUCoVCoVAogsNeAVnzIOsPsBZAZDtIOgVaH3ekj0wRBLt2wezZsHatjO2GDIFp06Q65z8Dp+2spoSn5akwty9o1ewAU1bw1bav3LNrMtYQNT3Kp8ms5Fm8c/o7brGTzRaiD+fA5yLictH5PzB+JhgjAQ0MJshaAMsuCGGjCkXz5tvt3wIwf+/8f7QYuchSBIgYOS48zuezuAiZd2gOiqqK2LxZKuQOHBjaPiptlT5+0ECVcncd2uWetjqsQW3XW8z8r6RLFx9xsR/9+8MxxwT8qLAQLr8cfv3Vk6Qa4OBBeO01eO89T9vw8NDeGcl5yXW2yavIC36Dh0tEgryndBuU7YMW/etep5HZuFHexT17QosWdbdvLPeaQqFQKBQKheKfyT9SjPzpp58e6UNQKBQKhUKhUCgUCoVC0cB4i5HDw0PLkFydc78/F4Dbxt5G25i2h3tosGeGR7TRargEyYCvcNgYBlEdYeSboW3b2yFuDAfq5w30dsweKTHy8uWe6ZtuEv91Tb+jpkFFhfw/eHDTHJ+LzZslS/e8eR6R5umnw/XXS1VuheJoZ9EiuO462L/fNxnA889LkOWXX8r/RwOrM1YDkJyf7K5q0GBUZsO62yDtewkkAcAA+z8D4//BMa9A71tUlIai8SjcDEvPkwAmwB1BV7QZirdC2k9U6aN9VgkoRjaFUWmvBKDCXuHzWYQpwq999WUhi5GjOoLBHFiMHJEggcTVA5sBwlsCoOs6q9NX+3y0LnMdp/Y+NbTjaGLatZNKEwA5OUe5GNlF8Tb1jFMoFAqFQqFQKIIl4xdYcwNUZsqYSNfEPrz7bYjuB1x0pI9QUQOlpfDQQ/DOOzIEcml1f/4ZnnwS/u//4I03/gHDI2MYYACtBhGeJT/weL1sf51VRIuqigB8xMhB+3A0O2x7Ro4NHXrdCKNnOO8hA+C0y7U7Hk5ZB6uuCXLDCkXzpqBSKgavTF95hI/EC3s5ZM6DnIWSVCOiLSRNgfZTIIAdMRhKLCXu6dhw38rILSJEJamjk1eeT2qqLB84UMSrwSZO3ZKzpc42B4sOuqc7xHXAZDDh0B3EhsUy5+I57s/u+eMeNmZvdLdThE5pKUydChs2yLyjWkF7hwPKyjzzoYqR9xburbON6/5qEsLbeKaLtkBcbzAeWXnGRrmEjxpfn0KhUCgUCoXi6OIfKUZWKBQKhUKhUCgUCoVC8c+juhi5voE/3lmsF6cs5oKBDZBJP2u+R4w8yhkkE8jJaDSHXklTt3mtHxb4xMtTJVAIRPhjLYLYHpA4zt1kWeoy9/Tig4tDO4YGYvVqET7qOtx7b+1tDQZIT5fpwYNDCzqoLzYb3HMPvPWW7MslKMrPh927JVP3iy/CHXf8AwLPFP9aPv0Urr3WEwxor5bYf/t2ESqvWeO/bnOj1FLqnl6csrhhxchlKbBgAlRly7xeLVpGs8K+T6HPrQ23T4XCm8LN8OdxYC/Dr4wHSF8DnSq7Bd3r85oqI7uotFX6fNYolZGjkgADOCrBVgZhXkGGMV3gzF3SbylOhpWXVVtPKiHnV+b7bPJoECO39cpvs3Mn9Ovnm/DhqCG8tWe6aLs8/wyN3AlTKBQKheIfQFERbNsmSdX69z+KE5MoFIr6sfsdWHcr4DS46E6Di6tKo3fFV0WzorgYTjpJRDu67ls02CWeWrnyH2IPNjodK5qt7rbVqKvCpMVhATxi5IKCEMTIeUuhwqlAjOkOI16TaUO1DRjNENMV+t4W5IYViuaLt1ByRdqKI3gkXhz8DtbfBlU5YAgDHIARdr8JMd1g7GfQ7riQNml1WN22RR3drzJyy8iW7un80hI052uzb9/Q/IKbczbX2SarzJM48VDlIYwGIw7dQevo1pzQ/QT3Zz1a9WBT9iZ0dPIr8gNtSlELug5XXSVCZNd71GiETp0gNlZ8vyUlvutUFyvXxcHig3W2KbOW1dmmwYho4/EhlSQT0J7fhOTkwKFDMj10qPi/w8JqX0ehUCgUCoVCoQiFw6ghpFAoFAqFQqFQKBQKhULRdBjR3NP6YfjwNmZtdE8vOrDocA5JcFihYL1MtzseEsbUnu24egBNXRi8tqXZ8XNglqfC3L4wb4T8LTlDhD0LxkOeJ5u6txh5c/Zmyq3loR1HA7B8uQgfx46Fjh1rD0ayWPALOmhMLBY45xwRIuu6v0DTbpe/L7/8hwSeKf6VzJ4tQmRdr/mecjga/35rKLyfawsPLAx+RWuxVHdI+Qay/5RqDz6fF8KfkyToyluE7Koe4+bIBpQo/sFYC2HRVBEiu67BqCTocCp0PEOC/wDQqLJXoet1iJFNnkgjb2Gxjt54YmTXcVty/D+P6QKtj4EW/QOuvi5znd+ytZlrQzuGI0C7dp7pzXXHPzZfIr2UU44KKNp25I5FoVAoFIqjgHXrYNIkaNMGJk6E446TJCUjRogdRKFQ/AtI+cYpRAa8bNiYojzT1ZOcKZoFDgeccYYIkb3tYZGREB3t2+4fgcu25agIedW6RF06OkVVRURGynxKSggbz1vhSYI15MnaE2IZzdD5nBA2rlA0T7xt26XWUrLLso/cweg6bH0all8IVbnOZTZJqOFKrlGeChvuCnnThZWF7mlN14iL8BUjx4bHYnLe84VlnmdTbGwICQ2Anfk762zjLSw+VHHInbzaWxANUq3ZZJRjyi3PDf4gFAD89hvMmuV5dw4YIMmqDx6UZLh5efDAA75Cc5vN4xMOhsySzDrb2OqReKPeRCTg7gMWbnG+b48caWme6WHDQruXFAqFQqFQKBSKYDgac7IrFApFs8VoNDJy5Ej3dEO3b6p9KBQKhUKhUCgUTUJCgkT1VAUncAnH6p52CVXr08X1FqzN3zc/9A1Up3Cjp3px9yukqkBDOhmNXoIgzSpBAd5aOEs+aDV8h2X73dWRF6Z4ztuhO1idsdon03djU14Ou3bJ9JgxdWc0t1g80zExje8ovf12+P13j9A9OhqmToXWrSE3F+bNE2e4QnG0cugQXH21Zz4yEh56CP7v/yA+HgoL4bnn4I03Di/hQ1OyOGWxe/qvA3+h6zqG2rIFlB2ADXdD+hx8goMNZuh2KQx/ESLbwvq7oDLTEyjc4XQY+aZUnNfskLMI1t3cKOekUACw+WF5v+sOuT773g5Dn/YEsmt22PECZP6CxWFB0z3Xc13iYlelIgBdr1mM7F1tuX6VkZ3HVLpfqhqFkIzFW4wcYYrA4rCwKn1VaMdwBPCujLxpU91VkZttRYqY7r7zOX+JcNzof60oFAqFQvFvxmqFO+6A994Tm0X14PnNm2W8tWHDETk8hULRiPjEYFgPwZrrEYOtDuZYEVP2vgVMEZIAbceLGLe9zMi2B6DL+c0mlkQhiSmXL/fYwkaPhg8/hCFDZH7/frjxRsj/pxTGNIYDBiivu6KkN5qmuUV7tbE+cz1du57Ili0iOguavKUieozqCN0uqV2MDE57ibrGFUc3fx/822d+6cGlnD/w/CNzMLvfgq2POWecD8SojhDRGqryoCobsfWF7jgorPIVI8eGx/p8HhceJzZ9HUrKPXbLiIjQEgPvL9xfZ5sSi6ccb055jtv+WV2MHB8Rj8HpiPU+fkXd2O1w552e8dHVV8P77/u2CQ+H6dPhrLNg/HhZZrWG5pfKq8gLql1RVZHf79soRLTxTBdurLldE+EdetG7d/AVxhUKhUKhUCgUimBRYmSFQqFoQMxmM6effnqjtW+qfSgUCoVCoVAoFE1Cly6iTvWO5ElOhssu8203cyb07094pQEmyKJQnZLe/HXgL/f0gaIDZJZm0iGuQ/02BpC/EjACGrQ9ruGzHfuIkS3Ux9mfVpxGZqlvluhlqcuaVIy8fr0nMHf06Lp/P28xckRE44qR//7b1xnuqpDcsaNn2Z49EnhWqOIOFEcpjzwCZWVy7w0eDHPnQqdOniCENm3gxRfhmmvgvvuO7LEGy4L9C9zTRVVFbM/bzqC2gwI3Tn4VNj2APEOrqQR0O6TMhNI9cMxrcOAzWW4ww7FfQZfzQXMKk41maDcZTt8Oya808BkpFEgV2j3vAbpcgycuhMRjfYNsjWYY+AB0vYTKuf/nIxwOC9AP8V5mdXiSu9RWGdm72nLIYuTIJM90wVpodxwYgheyrs5Y7Z7u1rIbuw7tIq8i7/D7bI2Mtxg5mMrIzVYbYI6CyPbOQFMgZwn0C73yjUKhUCgU/2R0HW64AT7/XKYDVcz8x1TRVCgUfvjEYKy6FhyVgA6tR8BxcyXRmUtMaY6BwY9j7nElp2+4CyYFF7vRFLEk/3Zyc8Ve5hr+Tp8ulRq9k0t06QJ//AFz5hyZY2xwIhIBA1gLwVYKYXF1rgKwvyy4yqCbsjfRvfuJmM2QlRVkEi5dk8rI6E77QRCKqSNccVKhaAgWpSzymV+a2jhi5HEfj2NV+irsj9rd1X59KNktCTxdxPWGEW9Bh6meZQe/9W0TAkVVRT7zceH+lZFdwt9yL8eg2RyaGDm9JL3ONt6Vcr0rHreObO3TrkVkC/d0qaUUh+YI/N0p/Fi8WPypIH6o998P/B4wGmH4cM/8oUOh+f2DFYlvzdnKxK4Tg99wfYlI8EyXp0iF8ci2NTZvbLzFyFFRIayYmuqfgSUrC4qKoGVLSEry/SwhQTpLCoVCoVAoFIp/HUqMrFAoFAqFQqFQKBQKheLI0aVL3U6q/v3hmGMI90q8n5tbPzGy1WFlaepSn2WLDizi0iGXhr4xF/krxSMe3gZiu9fdPlS8xcgVadRHjLw8bbnfsupZ1xubnTs90xMm1F0t0DvoqzHFOq4AYpNJAoUffRSeeso/aLh7d/jrL3jmmcY7FoWisSgshA8+kPsqPl6EyB07+mdDNxolS/orR4HGtsRSwuYcX7Xf4pTFgcXIez+EjdWCpeL7QlhLqT5btk8qqjgqYefLEvSoO2DodOh8rrT3DjZyBTwOuL/hTkihcJEy03kN2mHw4/5CZBcGE8R0ptJW6bPYbPR/wUaYItzTPmLkICsjV9or/drUSpRXUNKhdSFV1NV1nTUZawAwYGB4++HsPrQbHZ11mes4q+9ZoR1LExITI1Xnq6ogLQ3y8iAxseb2zboiRXwfjxg592/QbCrYW6FQKBQKLz74AD77zDM/ejS8/DKMGiXjqm3bJMlTQcERO0SFQtEUWA7B/k8BXWwMk+aI2LO6mNJghOguMPzVI3GUihr45BOodA53L70UHnpIpr1t0S4b9tlnN+2xNRqxPUB3ivHKD0LLGpL6VWP9oQNBtduZv5MBXcW2ruuQkQHdutWxUslOsJfKdMKxoFlDsiMoFEcjZdYyNmVvAsT+paP7JFJuKHRdZ1X6KgBWpq9kQpcJ/o3W3uyZ7nI+jP+ff5vO/4FOZ8H6O0M+hsJKX9GoX2XkCC9xsskjRg41KXVOWU5Q7bLLsmkf255DlYdklwYT8ZHxPm3iI+LRdHFS6ugUVhWSEJ3gty2FP3/+Ke9Oux3eeaf2thERnrZ79tTtN/bG5rDV3YjgKygfNrE9feczf4dulxwxe6p3wu/wYF+pqanQt6+vkrkuIiMl8bwSJCsUCoVCoVD862iuedcVCoXiqETXdcrLyykvL/epHtJQ7ZtqHwqFQqFQKBQKRXPEbBafFohfq86M+gFYm7HWr7rfwgMLD+/AireLaK3N2MPbTk0YTWB2OudLdtcrEGdZ6jL3dHyEONVXpK3ArtlrWqXenPj5iUz5Yorf8ooKEd2EhflWHK6JCI9uCovFV5zckGzdKkJphwMmTRIhMvgLhMxmCXy4X2kPFUchf/7puYcef1zuwZoCO8LCRJDc3FmWuswdEORi0YFF/g0LNsLamzzz7Y6HU9bBGTth6io4ay+cuBjajJKbPHO+PNNbDoH+9wQWgbqoxc5SXCzvqs2b4eBBVRVNEQIZv4kQObaHCN5ruwaNZirsFe7ZMGMYhgAlQ8LNnr6DdwWQRquMHNXeM12wNqRVDxYfpNhSDECHuA4MSByAyWjCbDSzLnNdaMdxBEjwiktcuFCC6WoilLiuJie+n1TmBrAVQfocESQrFAqFQqEgLQ3uussz/+67sHo1jB0rdqvwcBgyRMZhL7985I5ToVA0Hu4YjAO/e8ZOQ5+GyHYQIEEUgG4wUW5IbFaxJP92fvtNTDutWsFbbzWe/blZEdvDM12yC7RqBquIBDBG+q22rTTfb1kgDhQdoFs3z3e5b18QKx3yGuu3naSEyIp/BSvTVrpt2y6Ra3Jesp9w93DZkbfDPT07ebZ/g7L9kPOX2CLj+8K4LyShRnUBpTEMDOEw/MWQj6F6BVsf8TFSKdlt5/cSI1dVhfZcDrZS7sasjei6TnGV2B+NBiMtIlr4tGkR0QKH7nk+Hqo4FPyB/MuZP1/soSNHwsSJtfvyDQbo3Fmm9+ypX2Jqk8HE9cdcz6prV7Hq2lX8fNHPPp9X9yE1GhGtJWm5i6z5RzSxo7ePO+j7KD8/dIN1VZV/JWWFQqFQKBQKxb8CJUZWKBSKBsRms/Hyyy/z8ssvY7PVHZwVavum2odCoVAoFAqFQtFc6eGMldm9W5yUobIoxSNUc1UO/GP/H4d3UPZy+T+2hwjYGoM4pzKwdHe9VvcWXA9uOxiQKoebszfXtEq9KKwsZGHKQv488Kfbke+islJ+s0j/WKaAeLerqqpfJexg+O03j4P7vfdqFw3V55pTKJoD8+eL+Dg2Fv7v/+rOMN+Y1cgbCm/hcZQ5CoC/DvzlG1yia7DyMs/84CfgxIXQcqjvxhLHw9Q1kDAW7CWyrN9ddT/Tjb5ZC3Qdli2DCy6A1q2hXz8YNkwqwHTvLhWni4pCOk3Fv42qXCjeKtPdLgXqfvF4V0YOVBUZfCsjV09EEkxl5JDFyOYYMEXLdEW6/AWJt+B4YOJA+iX0w67ZcWgOd8Xk5ox3EYi//675eepwwKZNTXJI9SO2F3hdA+z9wDeArrH6vAqFQqFQHAV88IGn0tSDD8JNztxH3oH2rjHX5MlNemhHB5YCKNgAuUuhcBPYSo70ESkUIeOOwfh2HzaiwBwHvW6sUYjsXueVV5tVLMm/mbIyWLlSbDlXXAHx8UeHPeyw8RYjl+33H9vFdIEzd8G4mT6LUyp9n9VhxjD3nzc5ZTk+lZD375fqprViKwKMIoBs0T+o01Aojnb+Pvg3RmcCwv4J/d3VkZenLa9z3YMHYfZs+Owz+O47WLu2Zv/Z7J0eAfL3O773T1SR+Ttu++Oo9+Q+rCkxotEEpqg6j686hZWFGLxsnNUrI8eGx3qEv2aPGDkvLzS/oPc+YsJi6BDbgQ6xHUiMTvRpZ9NslFnLfBI2+omRI33n8yuU2DIYCgokOSvASSfV7m910b+/+F737g1+P2XWMirtYhPXdI1h7YcxptMYxnQaw5SenmTZRoORzNLMUE7h8GgxwDOdvQAaISF4sHgn/G7WCTEVCoVCoVAoFEctdYSdKRQKhUKhUCgUCoVCoVA0HwYOlCq2u3bVb/0F+xe4p3u37k1yfjLpJemkFKXQrWW3+m3U4fTimaJE+GYw+bcpTwVLPlRmgbVIgn4SxwW/jxYDoGgLlO7x/8xVrUAL4E0Mb0lRVRE783cC4tQf3XE0qzNWo+kay1KXMaLDiOCPow5+2PGDe3pW8iyuHn61e95mE4dysBWtvR2lKSkNdIAB+OUXCWgYOFCc3nVRn4rcCsWRRNfh118l8OP44/851/Cf+/90Tw9uN5g1GWsothSzPXc7g9tJ0gUOrYNiZ/WHTufA4MdlunpwsCtwMqq9PMN1DTqeHlLm+qwsOPtsCf4ym/2zzaelwb33wg8/SLCropmQmuqfuT8rS1TjLVtCUpLvZwkJvmrThibbc13T4dTaqyI7cQVeAYSZAl+z3mJkTdfcAY5QsxjZm5DFyCAVwcoPyHTm79DjqqDuqbUZazEbzRgw0D+xP30T+gJSxXl1xmp0XQ9Y/bm5MGyYPAdsNqmMXFswu6uCYrMkrrdvUHr2n5C90FmlykwwQnmFQqFQKP6p/PijJBbp3x+eeqr2tg0lbNuyBT78EObNk66q2Sxd1YsvhiuvhLZtG2Y/jYauQ84i2PMepM+W6nsujBHQ9WLo+3/QarjKBKc4+tDt0P7kWoXIiubHokUekdSppx7ZY2lSojs5bV8OESMHum5juviJgpOiEzAajGi6RqQ5kvvG3+f+7MstX3KgSMb/bWPa+oiR166Fa6+t45jsFWL/MEUG9q2Av38FQvexHCEqKmDjRs/7u21bsR2o192/m0Upi9xJNcd0GsPS1KWYDCb+Pvg3Z/Q5w6+9wyGJdd99VxKPVhfp9ukDDzwAV13le219v+N793RaSRpbcrYwtL1Xos6MX2SF6K7QbnLdB16PSq+FVYWYjCZ3gsS48GqVkb0rJRvthEc4sFpM7NgRvC/DoTmosFcAUin38eMe595j7wWkqnHCSwnutgWVBRyq9FQ61nSN+Ih4n+1Vn/dur6iZJUs81+aUKcE95/r0gQULxH9itUK4v6naj6zSLPe0jk6bKE9F4khzJJHmSKrsVZgMJp+2jU7LQZC/CnSbvLNSv4Mu5x+RCsneCb+Li2tup1AoFAqFQqFQ1BdlCVUoFAqFQqFQKBQKhUJx1NCnD5hMohsqKZGKBcFSZa9iZZoowMJN4UzoMoHdh3bj0B0sOrDIRzgbEq4qnDUJhspTYW5ff7HwlBXBB8vE9QEMUi3Gki8CZBeuagWWfChO9q0CGpXEyrSVbsHRkHZDGNpuKHbNjtFgZGnqUm4fe3twxxAEX2z+wjO95Quf7zQiQpzQFkugNf0xGkXzlZ8PW7c2joCyqMhTAePUUyWgw1RDvJNCcbSydy9kZ8v01KnBB3Q0Z4qritmcIyn2Y8NjGd9pPBsyN8jzPGWRR4ycPgsMThP4mA8k0LKmoEaArAXSpuVQ3+dsHaSnw7hxnu85KkoEARMnStBHRoZUqlizJvhnoKIJSE2Fvn1DKw0QGSkZURpLkJy3HAxhYI6CNqODEiN7C4WrVyRyEWGO8Jk3GAzuSih1iZGNBmP9xMgt+kN5CqBLJYhe1we12oL9C9zBibquk17sqapcVFXE9tztDGo3KPTjaSjKUiBtFlRlgcMKYXHQZgwkTQVTOMOGiRAZJIHOn3/Cccf592OsVpgzB25vuG5YwxLXu9oCHZadDyf8AbE9YceLR+SwFAqFQqE40hw4AMnJMn311aFVa6sPa9bAjTeKiMls9q0ulp0tlcfefVe6qM12nFeZA0vOgoI1Mj7Tq1UI0yyQMhOKNsOpG/zX12xQshtsxbJ+ZCLEdFMqLkXzImmqXKtHQGxyNFNUWQRAy6iWTb7vRYtknGY0ypjtX2MTNpohqgNUpEH+yqDsDgCZFfnuqqNdW3TlyeOfdH+2v2g/qcWpOHQHGaUZtGwJMTFQXg5//RVEYg7NChjAWMOLrCb/CoTmY2lCdB1WrYJPP4WvvpLvwpsuXeCuu+C229Tr7N+IxW5hTcYaQOxuU3pM4aUVL+HQHSw8sNCvfWGhJMFculSeVa7+p8Hgmd6zB95+W/qnLg4WHWRLzhafbc3eOdsjRrZXQs5C8XF2ONWZbLnhS8QXVRX5VC32ER9TrVKyATp0LyVlZ0u2bw/+/sgpz3GLux26g8QYTzXkVlGt3MkUzEYz6SXpHKrwiIsdusOvEnL1SsmqMnJwpKfLM1/XYcKE4N6tvXrJGEfXJTF1nz51r1O92nGb6DY+8y0jW5Jdlo2ma2SWNWFl5Pj+vmOdna9Ct0s8801YKTnO6zbbtAmGDAlivJiQIP6PUP0lCcH70hQKhUKhUCgU/xyUGFmhUCgUCoVCoVAoFArFUUPfvr4Cj5Ejg68ysyp9FTZNVh6UOIgRSSP4aMNHmAwmFqUchhjZ5Ewv7KgkYJU4S37gQJmy/aGJkV0OzKLt0HaCr6Aupov8BWBZ6jJ3hcHh7Ye7RXqarrEkZUmDVRhMLU5lWdoy9/ySlCVklGTQMb4jIOI8TRMfpqYF97sNGyYinq1bD/vwArJrl6d66eFUwNB1nbCnwzAajFgftTbMwSkUDUROjmd64sRmHKCOBJ0sXQrbtkFZmSQx6NQJTjnFN/nE0tSl7iQLw9oNY3jScOy6JFlYdGARt425TaJXDn7rrFA0JThxcZXzy0oYG3TwVWUlnHaaCAHsdrjzTnj6aXnm6bo86+x2uOkmERI8+STNrxrvv5X8/NACa0Da5+c33u9hLZJrr8WA2oXzXljsHoV7TZWRI82RPvOuADyoW4xswFA/MXKb0ZA1XwT+mfPAWgzhLWpdxa7Z2Zi90T3/5po3eXPNmz5tPt/8OS+d/FLox3M46LoIZPbMkGBtjGA0IY8hXZ4zYS2gz60MHfKUfO7kuefgpJN8N2e3wwcfyC3fbInr7amW5cJaAPNGHrljUigUCoWiGTBnjvTxNQ3OPbdxEqe5+OknuPBCSZwG0LEjXHqpdEXtdhEof/sttGrVjMd5FZnwxziozJD52B7Q67/Q6Wwwx0r/N+172Puh73q6DvkrIOUr+bMV+X4e1xf63gq9b24U0YxCETKJE5QQOUQsdgutXmwl049YAo5NG5O8PHmWDx3qWz3wX0FcHxEjF23xT3xaA/uLM3A4x4dJcb52q7bRbTEajDh0B+kl6RgM0Lmz+G/275dql50717xtBxGY0J2i5ADU5F+B0HwsTURlJdxwA3z5pSeRiNks72ubTSpUpqbCzJnNOEGZolFZm7nW7avs3rI7ozqOcn+2KXsT5dZyYsJjALleJk6U+wlgwAC5vi69VMzIVquI/t99V8zL3vy08yf3tAEDOjrf7/ieJyY/IQuLt3vuuw6nN5oYubCy0G3Lh2riY/wrJSf1yiV9b0t27Ah+H+kl6T7zidEeMbLRYKRlREsKqgrcbauLi2urjGwymHzEy4qaqaiQsVJERPDjk969PaL6Zcuge/e6x1h+YuSoNn7z2WXZ7vdSk9GiP3hd6xSsh+3PwsCHxMZqK2myQ+nd2zNu3bxZ3kN10qWLOM69fVfJyXCZVxL0mTOhf3/PvPJdKRQKhUKhUPxrUWJkhUKhUCgUCoVCoVAoFEcN3hmRf/sNjjmmdlGrt+h14YGFmI1iChnVcRTDk4ajo+PQHczfN7/+olxTlPxvyZPKAo1BvNeJZ8wVMXKQfLf9O3eFwZyyHP7c/6c78CC/Mp/VGasZ22nsYR/i11u/9pnX0flm2zfcPf5uAGJjPcLfvXuDy249dCgsWSJBS5WVIu6rD0NmDGFr7lZKHyz1CXQoK/O06dq1/hUwlqYuxaE7cOgOVqStYHzn8fXb0BFm/36YOxcOHhS9XXQ09OwJZ54pglDF0Yl35Y2WLY/YYdTKjh3w5pvw3XdS6cFo9GTQdzgk+OSyy+DDD+U+XXRgkTvJwsgOIxnefjggSRYWpixE0zWMpXudVVmBzv8JrkKR3fllhcU7qygHeMGUp0oQZGUWWIv4+ucxbN3aC4CHH4ZnnvFfxRU8M3w4fPFMM6zGq2g+OMoBhwgzaqLaNWi1V7g/qil4O9wU7n73V6d61eTqy+pdGbn1KI+Q1V4KO56Doc/63lfVqkEsTF9b52aXpS6rs02DYq+AlZdLNWSMgEECnduMlqpNVTnSN7Mcgqw/GDTpGXegF8DChbBhg1SfMJtlucEAr74KbdrUtuMjjClcKiCX7j7SR6JQKBQKRbNiyxYZq/ToIX+NxeLFcP75Mh5KSIBPPpEkSJrm6WeYzfDWW1JxscGoypP3v70cjBFSPTOuV/3KNmoOWDQVKjNF3DL8Jeh/j+/YLKo9xD0oAfq735Fl1iJYdTWk/+SppByRAFFJ0n8sT4HSXbDvM+hza8Oct0JxuITVkHjJNX4DaEoxzFHA19s8tuTvtn/HZUMuq6V1NXQd0A9LNFdeLs/Y+Pi62/7jiOsFuX+DboP0udD9sjptZqmlonI0GowkxVYTI8e0ddsbym3llFhK6NUrnl275Kf67jupAFyTuMwUHiXvCUeF0x539JaprqyUpKdLl8r8yJHw3/9KcpHoaFmWkQEffwwrVhy541QcWX7f8ztGjOjo9GnTh/yKfBKjE8mryMOhO/hr/1+c1e8sAC6/XITIDgc89BBMny6idtf9FB4uSfBOPRVWr/bdzw87fnBP92nTh12HdrEjbwf7C/fTo1UPsde5iO/baP7NwqpCHJrYCI0GI1FmX0efd6Vkk8FEqy4Z6Hofysul0m4wvqnqgtO2MW195hNjEimoKsCu2UkrSeNQpa+4uHolZO9KyUaD0a+9IjAWiwwbIvzNzTXSu7dneu5cuOaa2tvbbJBVluWTbDMh2jepRrvYdmzP2w5AenFTipEH+i/b/DBUpEtSJtd4pwmIiJCq07t3ixg52MTudOlSux+qf38JzlAoFAqFQqFQ/OtRYmSFQqFQKBQKhUKhUCgUjYau60Q/G40BA+UPlR92BV5vAeusWfDEE7W39xYjf7nlS7coN604jVnJs9ztcstzWZa6jIldJ4Z+UDGdJVDz0JrQ1w2WOC9vbPpsOObloFYrsZaxt3Cve37WzlnM3jnbR4z00YaPGkSM/PnmzwMuc4mRhw71LA82u/XgwZ5K2Nu31y0+D0RGSQZbc6W08oy1M7j32Hvdn3lrAQ+nAsYLy15wT7+4/EV+uuin+m+sibHbJXj5gw8kqMVo9BVl2+1w881SmXbu3CCzZyuaFa5Adahf/Hhj8957EpCo63K9DR0q11vr1nKPrlrlqZDuujY/3/y5+3m+LG0ZqSWpbqFliaWEn3f+zLQ2rT07aXtckBWKnF9WTcGs5akwt69PNZZ3Xl+H0agzbJghoBDZm7AwiLc1w2q8RxO6DlXZUmUXHcLiIKpj/S7uhAR5+IcqDE8Iosp2vXGKXXUt8McBrkGLV+GgWsXIBgO6s8yEAUOt61RfVr/KyNUq6O56C/rdAxGtPfdYtSDHOfuX1LnZnfk7Qz+W+uKwwOLTINcZRdzzWhj0qPT9NAegOasHa5D5K+x5j+ho6ePs2+fZzIUXiqCoY0d5Jl9+uVRBatZiZIBWw6Fsn291ZIVCoVAo/uWUlooYpGPHxtuHrssYSdOgbVtYuVJEGK6kTd5ERcHVVx/mDisy4cDnkDYbCtZB9QQ20V2gx9Uw+LHQhH+Zv0DxNpk+5lXoe4dMVx+bufqEfW+Dqlz4c7InIUq3i6HndVJ11rVveyWk/QhZC0I4SYWikQk0Jq0+ftPCgIdlOn81dKiHHfofgq7rvLj8Rff8i8tf5NLBl9bsO7AWQdZ8yPgVsn4HSwGgSdKEloOg49nQ8QxoNSxo+4CrCmNztJU1OrE9cNvADn4FPWt/kWg65FRIRVGTweQn8msb09ZtpwPxvfTrN5B588TW9803cPfdNW+/3NaKGDR5/RRth1ZD6nNWzYK77hIhsqZ5khZ6C0dB+hAPPSTC5SYhNdW3yiVICd2iIslcmeQrLldVLhuf99a9h+a8B3/f+zu93+rt8/krK1/hrH5nsXOn+GRAqmhPny7T1f1qrvkRIzzL8srzWJ62HJDKw6f2OpW9BXvR0ZmdPFv8dl4JDt1Jl6vjnVTDmRiR2B4hVSTPr8h3+ySjzFF+z3rvBMJGg5GYjik4nKaov/+WBD11+RLTS9J9xKmJMYk+n7eLbceuQ7sASClMIb8i36d9bZWRdXS/SsqKwERFyfs1lOdb586eKvILFoipvjZ/bViYVEY2GUzu369NtK+RNTE60f37ZpVlBdpM4xCVBBFtJGmlN3tmNN0xeDFypNiot2w5IrtXKBQKhUKhUPzDUeGDCoVCoVAoFAqFQqFQKBqNH5N/dAtY5uyaw7R+0w5re61ayV9hoQjTkpOlwGRNAlWXcDK3LJeUohT38j/2/8GC/b5Bi++te69+YuSE8ZCzGEr3grUQwluFvo26CIuTKjCWfCjbLwFrrUeCsfYqAV/vmu8zrwUQNy09uPSwD29rzlaS85MB6JfQD7tmZ2/BXrbmbiU5L5n+if0ZPFicxDYbrFkDV11V93YHD/ZMf/edVBWtDYfDv7rxC8s9QuHnlj3HLaNvITpMyhC4qhFA/YN/kvOS+W3vb+75n3f9zJ5De+jdpnctayEe+fKDYC2QqkDmaAniMMfU70DqQUYGnHUWbNwohzNyJJx9NkycKJWsi4th0SL46SfIyVFC5KOVGK9LyrsaeHNg+nR45BGZnjIFZsyQatx2u6d6aFgYlJTAl19KuwOFB3wqEazPXM/6zPU+SRY+3/w50yZe79lRmKe6gg/Vg6lckaj2ssBVWCz5PiLQTSlD2ZAiUV433ugfXBiIMHUfhY7mgIw5kDkPMn+DygzfzyMSocOp0HEadDxdKroGQ5cuUnHaOyAzOVnKcLuYOVOy/bto7IBMc6yILGzFgT+vdg0CWL20InVVRnbhfb8EI0autNXjJRnZFiKToMoZ8OWogFVXwcQfRIBiMEHK/3xWWZW9tc7NFlmK0DQNY6jZSerD/k+kWhQ6jHgT+v6f5zlhNAHO54TBCB1Ok8QHwLhxcPCgPMsA9u6Vd+zkyXKJbd7c+IfeILQZCanfH+mjUCgUCoWiWWG1SncgPMguZyAqKmD5chlvZ2RIBbHISOjaFU44QcYVW53dotdfFyFybeOMw+oW7fsY1t0GjipAFyFfuxPEtqVVQcF6yF4o/fAhT4S27Z2vS58vrhf0uzO4dVZdC6V7pCLyhO+h8zkyHvAWQZujoOuF0O2S0I5HoWhMbAEMLgHGb27KUoB/rxh54YGFblsywNbcrfx98G+O63acb0Ndg91vw6YHwFEpz4bIRGh/AhjD5Tsu2ACFm2Dfh3DmHjAFV44xJkbsyM3NVtYktBrmSTqVsxCqcsS2UkPCiRwH2J3tdfSAYmRv0krSmDx5IC8786muWwfr18OQIf7vM02DuStGcZFLi5i7BFr0k9/3KCMnRyoeaxrcdBPupIWB3uFms69votFITRUHWqiJ+HbtUoLkRqLKXkVBVUGtbTblbALgnXfkWomMpM4kmODrv5m7ey46OgYMTOgygYldJ/L66tcBqZh89/i7weSl+Az0vgqQFNHNlBVBC5IPVXhs+THh/v6vuHBf231Y+93u6a++gkvq6PLZbCJG9hanJkb7ipHbx7Z3i1MzSjM4VHHIp713JWSAmLAYd3uH5vA5h6bGnVzyKMieERMjflq7XXw68fF1r2M2y+Nm/34oL5cEFpdeWvP4p6hIxMgO53sp3BTu9vm6aBPVxv37llpLqbRVEhVWg+C+oWk9ShKoVE/wdAQYOhS+/VZ8vZs3i8+9trGj3a78wAqFQqFQKBSK4FFdR4VCoWhAjEYjQ53lvoIJiAu1fVPtQ6FQKBQKhUKhaAjsmp37/7zfPX/fgvs4o88ZmI2HZ44YMsSTXf7NN8UhH3D/dhG9jh8PH2/82O/YqvN36t8yUVumePDPFl+WCLpze7nLRIziLRKOSABjpL/DPrxlrefpR+sRkL1AgrD2vAPjvqhzlTkH6q4wuL9of2jHEYD/bf0fJqdw79Rep2LX7Ly79l33Z8+c8Azh4TBsGKxdK1V9ghme9O4t7TRN9GDPP197++q++KzSLN5f/757vrCqkPfXvc+d4yQINtaTcJ29e6WSYXUxc128svIVn3kdnddWvca7p7/r31izwcFvIPN3yP4TLHnVTsAErY6BzufCgHtDqzgUIqWlMHo05OZCYqIIPU8+WQI3zGb5LjUNJk2Cp5+GP/5ooB1rDqlwZC0AzS4Z9+N6SrbwowhXkIqxEX+jhqKVV36ENWugV6+6BbP1IsRn5/70cB5/bCBg4Lrr4P33PRq/6gEP8fESxAdSzd0bPUBQx8r0lWC61bNAs/q1qTWYqmBDUPffst0TMBg0DAZjrQEyPjTLarzNmIKNsPJyKN4uQcfx/aDrBRDTFTCKMDn7T8hbDqPfC16I7KJLl9qDK/v3h2OOOaxTCInIRMAARVtFEGKqpQwE4NDBu0cTUUPQtasysut2cQWxuT4L1N6belVGBmg7UarWuYKcM3+FP8ZBx7OgeAek/eDTfE9RalCbXXxwMSd0P6F+xxQsmg22PyvTHc8UITLUXDbLGCZicqTv+T9fnTXZ2RJMd1TR9jjc1bIUCoVCoVAAYkcwGmVMHSo7dsCDD8Jvv3kCvTt0kO5+ZSVkZsJTT0kQv9kM7dpJJbhQ7RRBs/EBSHYmcOt6MRzzilTz0uxiezIYpI/jqITUH2rfVnXKDkDuYpnuc6v0rapXRK5O4Wappgww4nXodJZMB0rEV9e2FIpGxmg0MrR/V0ifgxENDq0W4X0t16YRjaFxm5zr95SFuiZjo7zl8r+jQuwRYS0wtjiGoQN7gzm60WJJjhQvrXjJb9nLK1/2FSM7qmDZBZAxFzBAz+uhzy3QaqjvirYSSP8ZDn4btBAZoHVreZ5v2xZccrl/FG0nSVVpzSLX4Mb7YNznNTZP9TI82DV7nWLk1OJULp4k7y9XddMrr5SEmN7Y7bB7N7z6UV8uujdefsv8FZ7xt4ua/CsQuo+lEXnnHTnf8HB48kmxc9amHWy097s3+fmh2SBB2ufnKzFyI/Hd9u/qbFNiKaG4soRPPonHbpe8iaGK199e87Y7MWGEKYK9BXvdn63KWCVJhM1eDrKygxDTzTdBZ61JNfYHLUYuqipyT3tXQQ60zKE7sMcdIDpaEvjMn+/xYdV0P4WFSUV2lzg1whThJ3pOjE50i1OLLcXklOf4fF69MrLBYCA6LJoyaxk6Otnl2UGda0OTnJfMgHcHYDQYsT9qb/aC5D59PD6ev/6CM88MTtw6ebK4l+x28RPVlMza4YBZsyDdkO720bWMbOnXrnql5OyybLq36h78iRwOCWOdvnxH0+yvFoYM8byHP/gA3nqr9vZKiKxQKBQKhUKhCAXVfVQoFIoGxGw2M23atEZr31T7UCgUCoVCoVA0ILouwrtDa+DQWihJBnu5OHTDWkoW+jajIWEcRP6zhEafbPyE/YUeoeuegj18uflLrh5+9WFtd9o0ESMDfPEF3H23VI/xDhjSdfl77z0RhPy86+c6t5tRkoGWkoKxf//QAjSigQ9dG/kZOp7h+3lMFzhzF+QuhZVe1RajkgiJTtMgy6kIPfgt9L0DWg72DXKrVvl4Xc6OOjdr1+xsz93OwLYDQzser/VnrJ3hdvSXW8slW7hz/p217/DU5KcwGo2MHw+bNsGWLZKFedCg2oNu4uKgWzfJiJ2VJcKeiy4KHBym65Ld2Vt4+dKKl7A6RIRoNpqxa3aeXfYsN468kaiwKAYMEOeq3Q6//ipi3FDILsvm880SqBUfHo+GRpm1jI83fsyTk58kMcYr+3rOYlh1NZSnQHgb6DBVRD7x/T2VPPKWQ85fItwaeH/AfTYUL74owqiICFi9Gjp2lOXe363R6BGNn3A4mq+qfNj3AWQtkGeho8K/TUx3ucaPeSlwRdpmxKGKQyS8JM/rgvsKaBXVCNXQG5ABA0TMW1IiwTtXXhnkirWJi6snZcjKgnPPlZJeQfIEn2GgL23bhvHmm3UnKHB9/vve3+vcdk55DjZjFO7LuWw/RHf1DWKvLZjq0BqwldZcUdlJUXlLTAYHsfHG4APCmmM13uZK5nxYcgagQ7vjYfT7ENdbAnk0ZxSNwQjDnofKPElucLTT7njY+aqIhnMWQ/spgcUXTizVtPgR5lrEyPWsjKyj11+M3O54/8q6hZvkrxoOHaqc72wDBvom9KVfQj9AKjPP3zff3Ta7rAkCANN/hop0mR70qIhy6kqo4/z82GM9gXdHNa2Gy33lqEdl7H8IF/9wMd9s/4bvzvuO8weef6QPR6FQKBTNgISE+onXXnsN7rtPpseNg5tvhilToI1XnHx2tozZbr1V7BRnnVW7iOmwKFgPyS/K9JBnYNDDHptS9T6PKSr0KsTlBz3TSVMDCzTLU2VcBlCZBdueFntAZHvo9d9mbxtQ/Lsxm81MO+9y+PF2sDmkAl6Pq2pfx+hgWvufZEY7GTbcA3s/BHuJXO8thkBEaxnzlqdhLn+JadGd4czdYAouvO9oiA3Zmb/TPb7rFNcJh+4gqyyLX3f/yp5De+jdprez4auQ8YuIZifNhg6nBh5ohcVLtfTO54Z0HJMmiSjHZoMVK2DChCYShzYHTJFil87+E9DgwBfi0+h0jucd4JXMNc3mu3ptYuQwYxhpxWnExcGoUbBqlSzfvh0eegheekkSYGqaCKQuvxx03QCJEyBznthCqo+/a/KvQOg+lkbkxx/lvKZNE+Fks0AlRWx2/Ljjx6DafbzqeyoqrgXEx6lpwSX4BcgsyWRjtkf9P2fXHObsmuPTZvrS6cw84x15/+gOyPwN2h1XfVMNQrGl2D1dvQoy+IqRNV2joOoQQ4fK88Nuh5dflkTFgfrFdrs8X1KKU9zi1NZRrf3aJUYn+thD00o84mWAFhEt/NaJD4+nzFoGQF55nt/njY2ma1z787Xu6W+2fcPFgy9u8uMIhWOPlfGRzQZ//glnnx3cemedBZ98ItOrVsn7+eabfd/LNhscOCAV6DMvSHMvbxPln+i4TVQbn983szSz6cTI7afA1ieaZl91MNQrf8vMmfDcczVXq9Y0yMuThFgKhUKhUCgUCkUwKDGyQqFQKBQKhUKhUCgUjYGuS7DM1sdEcGGOE8Fxq+EQ3hrQoDxdxKUp/4Mzth/pI/Yn1ArB4BZMVdgqeGThIwAYMYJBnKUPL3yYiwdfTKS59kp/tTFtGtwphW2pqIAzzoD168UR73JMGgwSvLltm8xvy9vmXt+IEZNT2KOju6sk6+is2zKP0aFmiq8AsoH2wIEvYeh0ydbvXVUzpgu06F/DBoKk41mw1lkaVLPC39Pg1E0ScGU0O6vWePap6VDsdJQDRJmj3NnAHZqDwqpC92dbc7bWW4w8Y+0MSqwl7vmPNvpWLS2qKuLDDR9yw8gbGDMG3nhDlk+fDt/VkgTebof0dPm933hDgpOmT4cLLwwceGEwSGbn+50a3tzyXHd15nBTOOf0O4dvt3/LoYpDfLThI/5vzP8REyMZtxcuhN9/rzsrdHXeXvM2mq5hNBi5cNCF2DU7n2/+3F0Z+vHJj0vDzHmw+FTACL1vgmEviMhRs4oQGSTgI2kqGJ+F/LWhHUiI5OR4Ar/uuks0jnUFstQrI7auQfIrsPVxqbSROAmGPSv/x/WUQBdbCeSvgty/oWhzsw821nWd6+Ze556/4Zcb+Pa8b5t1RnqTCaZOlYzxCxYEGbiUmgp9+4ZeOSNI7Jj4H5ehYeK220KrPrP70G6f+ZoElosL85jiqvKSNhvahaCo1x3yfu50tm/wY7VKLOFmKzpgDVB4uVaaWzXe5oitTBI46Bp0PgcmfOcJOjaY/COEI/2DzI5K2k6WCtC6HbLmQdIU38+rXYNV1eKwAwmLQYKBvQmlMrKma1Q56itGPgECVC8PxE4r2Lz6ZE8c9wQXDrrQfbzRz0ZTZa8izBjG+sz1XDI4REFMqJTtk2vNGA5tRgVu4xLQVGaBtUiWxfZg8OBxJCVJt/moxmiWgPDsP6nzdzRGyvX5D2Jd5jq+2S7lrC+ZdQkndD/Br7KKQqFQKP59TJkCb74JZWVS7eukk+oeL//yi4y9QewOLrFx9fXat4dLLhG7RlmZBIo7HMELT0Ji3e1iQ2oxCAY+KMsMtewo1LG6dzITUwAbYHkqzO0bOEFU52k17696/yu2R9BV+RSKBsdogqRTIe0HZwU8X9tsrdVcN94j9oo2o2HgQ5LIyexbxZHKbMhdEvgeOop5bdVrmAwmdHQuGXwJds3O66tfx4CBN1a/wdunvS2JobY+DejQ/26xmULNGRqMYSE/p048UTan61Kx/thjD++8jjo6nOYc6zlZ/V+5XjudKfNFW90fpdnBaDC6hX7VxcjeCTl1XSetRERip54Ka9d6qjK+/LLk57vlFigogMcfhz17YPhwZOyZNR+qsuHA59D9Ct9EFg3hX2lkCgrk/27dmlG1bZUUsdlxsPhg3Y2AHdmeSsYREaElqHl55cs+83oAm868vfMgvAUkjIe8ZSJGPsZ3vYaoSu7QHJTbyt3zLSL9Rb8mo4lIU6Tb/phfkc/VF3mSGcyYAddfL/eW933lSmzw6quQOjTVvdwnSbDXMofmEadmlWa5n2kAcRH+Iun4yHgyyzIBKKgsCOp8G5KPNnzEyvSV7vlbfruFqb2mBhRbNxeiokQ8//ffkmQpmHGMzSZjKpeIGeCeeySB0/Dh4gaw2WT8NG2a5EvIKfNUtq7+TgJIiE7w+X0zSzMP99SCp81oMMeCvazuto1M+/bQvbuIuEtKxC/8xBOBk68YjVKV+rHHmvwwFYojh8Mi8QmFmyRGoWSX05ZhlPibVkOg5VBIHC+2k8OJBajKlf51ZabEhxjM8i5tMVDsGrXZYxQKhUKhaKYoMbJCoVA0ILquY3NaRsLCwuoMRg61fVPtQ/HPRNd1dF3H2ChRCwqFQqFQNC9SilIY+9FYhrcfzm+X/tb0fSBdF9Ho3vchIhFGvQs9rgVTuGR19640YjCCpdBdza+qSsRiGzZITMD27eIg0jRxxHXpAoMHS2zAKadAjx6NdA71FaJFRsKuXbyZ+hX5FRLgMK3/NOyanZ93/Ux2WTbvrHmHu8ffXe9D69ZNvoNt2+Sr3rVLvosPP4R+/aC0FB59VISpw4dDcVUx5VaPs/uE7icwptMYAKrsVbyy8hX3ZzvIZXSomeIBdpkgCQki23gvjPu83udXI9EdoPVIqV6DDhVp8NfxMGqGOEGqcmHzw+7myVawap6yBZ+c/QkXDboIEGFRzLMxVNmrMBvNrM1cy0WDL6rXYbkEvy60atWZAd5a8xY3jLyBSZM8QV7ffw8rV8LIkYEDc8xmeOEFuOkmCSYA+a3PPRd++slXUKnr8O678O23HjHyvQvuxeqwYsDA+E7jOSbpGL7d/i06Oo8tfowrhl5Bi8gWnH66iJH37ZMKwcccU3ugkCuQKKcsh+eXPe8+33WZ69DR3fPPLH2GW0bfQoLJACuvAIzQ40p5HrhEYEYvAZjBhFtT2XpYzQfQAOzY4Slge+WVjRTYDLBtuiRkMMfB5J8g6WRfATZIoGXHM6HTWVCfypuhVO+Fww6m+nTTp/y08yf3/Pc7vueMLWdwxdAr6r3NpuDUU+Wey8+X///zn9qvc0dOPqZGEiIDFNIKDYl46N07eP9tQWWBT/DS+QPOZ3K3yYA8z+/+Q94tBgxsLdjHlA6nScX69Nkw6h3fjdUWTAWw+23oUq2qTrVKLO1bZuPQwqiokODJnj0b8X76t5H8MlTlSOKG0e/LsloqBDf3RAZBExYLCWMhb7lUJhr8hAQ9uAIRql2D1cXIEaaaKyN7E0plZE3X6l8ZOb6PBFMU76AuMeu6aoXV+yb0dU8bDAZ6te7Fttxt2DQbqzNW1+94QkG3A4bAVfygVgGNYcoKzjtvHDNmSKDcUU274yFnoSRpqIkWg2HyL3J9/kMotZRy/veeSsh2zc7Vc65mzkVzlH1dcfjoGrjGacYwFWymUBxlnHiip8DgrFlw8sm1ty8pgWuvlXHC5ZeLEBlqFjCHhYkIOSdHxm/1SgxWF/YKyF8u031ukfd89WdR9arFoQp/w1t5bSsNojr49tkt+TWPxUwx/qJO1zEF6n9NWaEEyYomxx2DkXgyYQe/xWA5BAe/hS7necYQrvGbJR+Kk9FXXIZNl8/C9AoMA+6D4S9IvyDAuEOPbIet3RlgtTZaLElTsyt/Fx+s/8A9//HGjwGPPfndte9y59g76Zn3u9jZDSYY+Ejg/lINyaGCfR60aiV26bVr4YsvRBjbKM/cBuDW325l5paZfDbtM6b1m9YwG+10Nmy4wzNvK4K/z5IxvDEcCj1VVdPsYPISIydG+wr9osOiiTRHUmWvwq7bOVgkYstzzpHv1Zu5c+XPj8RjPePOrU9C14tFpNHMruHaiHCaZKqqmpl9UCVFbDZousaBwgMAmA1mLh9yOdNPnO7+/OQvT2Zb3jYMGEi1bHEvT00Vf1iw1duDqb58qPIQqcWpdOl4ptghS5JFJBXf35Ocs9p7zKcyeZBVyYuqinzmA1UgBogKi3KLkQsqC7jwYklKreuSpOfEE+V53bq19JftdrnPLr4Y9h/QyO2V695WUqz/sVWvjJxb7mkfHRaNMcB7pmVkS/d0saUYXdeb7L2aVZrl9nVEmCKwOCwUVhVy9x938+nZnzbIPioqxM++axfs3g2FhR7/Z0KChAj07QsDB3qeb8Fw8smwbJn4XGfOlATTtfmijEaIiZH15s2TBBZWqySSvu8+8W3t2SMi2X37YMioUirtkvjIgCGgGNk7maDRYCSrrAkzRhrNUh054+fa7anQ6MkdDQb473/h4YflGfLCCzB2rMRUeD9PNA0+/xzmzFFiZMW/BGuRJFPf/ZYkDmh/IrQZI4UBIlrLvVuRIe/F1B+hxxWh90l1XRJL7f1AEu7YSyGuL8T3BXO0jAHLD0LRNohsD6dvhRr8e0cVTRy3ARLzsn+/7MJul3dO69aSjKFZJAdSKBSKfzDN1IymUCgURyc2m43nnnsOgAcffJDw8MDVSOrbvqn2ofjnYbFbGPb+MHbm7+Te8ffywkkvNDvno0KhUCj+4TiqJMt67t9QuhfK9kvgmzEc0CTYP6wVxPeWjLHtToQWA+oVaJBRksHETyeSU57DvH3zuOePe3j55Jeb9t23510RIpui4IQFzgAO5xDcGGAoHt6Sigpx8Lz/vjiALrhAnKiDBkFcnBhKy8rEdrtwoQiWr7666U4pFPaXpvLwwofdjt31mevd0zo69/95P+cNOI+uLbvWex9XXw13e+mZly0Th2jbtuIwtXgJWpamLvVxMj808SGO7368e/6bbd+QUZqByWBiTsVGrqorUzz4Z4uPzIJNZ8j0gS9EdNntUt91tDqcjsHQ42qnGNlJ0RZYcKwErHkJjwGWVYm21XXmg9sOdn9mNBgZkDiADVkbsGt2Fh9cXK/DsTqs7Dq0y2e7JmdwqUN3uAOUduTtwOaw0bFjGOedB7NnizPg/PPhjz+gTx9PsJdLZHzXXSIOnjFDxOfbt8tnv/wi2a9ff12Ef2Vl8Mor8OSTMGyYbGNX/i6+2PyF+7gWH1zsc45FVUXc+MuNfH3e15x2mqfS9o03wpo14h8K9MjQNI8T45bfbsHh5UjemL3Rp61ds3Pb77fx1eBjJVjDYISRb9UcUHsYwXOh4i2MarQgu7zlUhEZYOynnqq0xgBjUtdz0RwV2j7qkzTBmTChPo6tPYf2cMtvtwAewZ/FYeGmX29iYpeJdG/VPeRtNhXeAfJ33y3BBrGxgQOY7HYoNifQJtTEDBER8OOPHkdiLc/O2CoDOCvOFBUFH0z198G/feb/b/T/MbHrRPf8m6vf5GDxQQwGAwsPLOSucReLELkyC/Z/Bt0uCy6YCiPkLoYDM6HrRb7vbq9KLGceM5dwswWrPYJ335VnkaKBKN4G6NBqOETUUIn0n1oVrcOpkL8SrIWw/g4Y95nv517XoJ8Y2RycGLmuz6ovq7RV+rUJmu5XwKYHqVuMbCLMaHBXR+7durfP54PaDiI5LxmH7mBD1gYcmgNTbQL1wyUyScYothK51qI7+b6/axPQlO3nnHPG8dZbte+iuQa6+9DuBNAfqqWBSYLG/0FCZJBg/5SiFAB6turJvsJ9zN09l/fXv8+NI288sgenOLpwVEHmPKmWWJws1S9Ags4wgKNcHo+RiZBwLLSbDIkTISymlo0qFIojSVSUjKfmzpWA7bvugl69an6vr1sHuU6tw/33+yZWq4ljj5XqVbNnwzvvhBb8HxT2Cs90WDwQpOgXghf+thwC5niwl8C+jyAhhH566e7A9tOa+l9l+/8Z4wDFUYVPDEbPMMINNql23OE0STLlEt/HdHH3lW16GM/tk0SSD45eQPgwWb+mBEg2m43nXpAqldXjPDRdw6E5CDOF+a/TjGNDbv3tVp/5Q5WHfOZ1dG797VZ+HzZBvkNzTGB7YUM8p4DTT5eksNnZ8MAD8OabNbcN5vndGLy/7n3eWSsJ9s759hyWX7Oc8Z3HH/6GY7uJL65gnSd5LkDxdr+maTZ8KooGrEIZlUB6aTqAeyw1aJAkj929W76/Wkk4Vuw6ZQckCeu6W2DMx05b+tGRgG7AAEhPFzHdG28c6aNRNEeS85IpsZYAYNftjOs8jqQ4jyhnTKcx7Dy0E7tmZ3nmYiZM1Fm5wsCnn0ql2GCwOqw+wssIUwRRYfIcdWgOSq2l7s8WHVjEld1Og033yYLV18PJK3w36PUeqw+FVYXuaZPBFLACMUBseKy7bXFVMe3awZQp8OefIk5NS4PRo+GRR+CEE0R09OyzsHgxDBqbh91pTzQZTAGfUd7Vks1GM8WWYvd8XHjgY/KuQKzpGsWWYh+BcmNyy2+3UGaVyrp3jr2TjzZ+RH5FPp9t+ozLh1zOCd1PqPe2ly8X/+rcuVI599RTJTnH4MEy1qmokIRKf/4piaKXLg1t+yefLOJXkOv21FNFfxbI/6Np8PHHIpi94gr49VfPZ+XlktCielILW4Tn+jYbzbSJ8vcdeC8zGUxNWxkZIGkqpP9Ue5tWI2HSj41uU73iCnjIadq12STh9+efi0gc5P764ANJmjV0aKMeikLRPLAWwYIJYqdNOglGfwQxnaWgBAZPUmTNJv6g+vRD7RWw9D8iQm45VBLVdzpHClcEomjbP0eI3ARxG5WVEo4wa5bEEoWFyfMrNlY2V1EhxSs2bYLOnWHJEmj0YfEREGErFApFc+BoCHVQKI4Iy1KXMWfnHG4dfethBcgrFApFY7EmfQ0Gg4FRHUfV2q7UUsrZ35zNzvydALy04iXsmp2XT345YHZHhUKhUCgaFF2HHS/A9ukSONL7Fhj4ELQe7m+4tZfDoTWQOKHmCmR1kFOWw3GfHUd6Sbp72aurXiUqLIpnTnjmcM4kNHa+Jv/3uEqC7wKpGr0ENMX55Zxy7ams2RjHlCliPI2KEiecdzBjq1ZiMB00yFeI2yh06SKG31BFuQkJXDTvPJ/quAeLD/qs4tAdXPLjJSy/dnm9D++KK8SZWemljdE0CRyqzqIDizAbzW5n9LD2w3w+H9VxFFm7snDoDhamLES7sBPGuoy/gbLFZ50EuYskW+qKy6BkJwx81ONYsBX7bydUul0Cmx6Q7KneVBMiA/xdAUaDCYfuwGw006dNH5/Pj2l/DFtytmDX7GzO3ky5tZyY8NCC3n/f87uP0Pvc/ufSPrY9AJmlmfyYLBnYdXT+2PcHp/c5nXvukcqsABkZMH48vPYaXHKJBNju2QMPPihBt8OHS7s774RrrvHs95dfxCmdmAjFxb7ic4Br5lxDXXy34zs+tH5I796xjBkD69eLU+KWW8Tx6soA7sJmk4CzRx6BF16y+1THrYkfdvzAzL4DMRpMkpzAHOD7rS147sTFsk7hRqkqaS8Fhx3Q5LliMIMpEmK7Q5ux0GqIM5C4dnr29FSonjcPrr++EQRRuUvFSWeK8q8u66KJRdh1ousiPAtQdaPCWsGkzya5q4OO6DACXddZmb6SClsFEz+dyN7b9hJpjjwSR14nHTvCmWfC77/LfXfRReKkM5t9r3O7XYI87nytC1/U9Q4I8Pyv03HmfHZGIY/QzZulqv1//xvceVR/ng9t7xsdMarDKNJK0tB0jSUHl+D4zxeYXMka1t8OCePlfvGuUhQw2MP5Dlt7o4g+Wzmf967rwrn/VjFFXDzua/638ko+/9zAAw9AmzZHicCwuWOKAoySlTwQ/+SqaD2uhm3PgKMSDnwOrYZBvzvkunOJMpzJMCxe+l4DhqArI9f1WfVlFbYKvzZB0/Vi2HR/7W3i+rGqJBybJlVfkmKT/Pok/dr0k+RCOlTaK9l9aDf9E/sH2lrD0OVcWH+bXIPbn4VRM3w/r626enhLJk6UGIOiopp3cVRUTW4zGmJ7isgnoKDcIRW1/kE8uvBRvtgiSW2izdGc0usUd/D/rb/dSqe4TpzR94wjeYiKo4V9n0hSCYMR+t4JI6532gcC2ORL9jj7KI3ciagtMApUcJRC4cRqFXtTVZXYG8LCJKDR9XfhhfDTTxK4fe65nqRm1Suu2O1iS3ARHh6ckO222+Czz6CgAD79FK67roHHGBGtwRQNjgo4tBa6nO/7eR1JV4Lqb5ujofd/xUZ68GsY9jyEt/Y852rrS2X8LPuJ6eb7zKxpnfCWdR+PQtGYdDgdcn6RpCPLL4CJs8Xu4O3j0Kp1/hPGU2PCJpe9zMvH4U1ueS4j3h9Bemk6Vw69kg/O/KDWMV9zwWK3sDBloXveiBGj86Ho0BxuG/OC/QuwjzkHs+6Q5FCV2RDZNqTkUMHaBa6+Gp57Tp7nb70ltuirr5Z5l2jKJUJetUrs2E3JF5u/4MZffZMhnfzlySy5agkjOow4/B30vxeWnV9ns/120Jy/T7gpnNjwWL827WLbucXImWWZ7gqi993na9evEaMJBj0Kq5wZePd/BlU5cOw3Qdm7mwN33CG21927ReR3yimqGpvCl78P/o0Bg/t5V922PaTdELdvtcJWwVlXHGDZ0h7s2CFJfU84ofY+ocMBCw8sxOblL5xz0Rym9poKgK7rtHu5HXkVeZiNZn7Z/QtXDr1ChFLF2+DQakmsccyrvnZI8H2P5QObk8G7yHENgpuioh3uaYPBUKPw13t5qbUUXde5/XYD8+d72qSmBvYj2CI970ujwehXvR18K7obMPgkXqxJIN0iogUmp48VIL8iv0nEyA//9TCzd852z7+04iUfn/vUL6eSc08OraNbB1q9Vt54Q55VbdvKeOaUUzxJmE0med85HLLsuutkjBNqIo4RI+D440XEnJMDZ50lPuG2bT3Xr90u05984vEPnX22XDrZ2bLfmrBF+lY59q6CHGiZpmtNWxkZoNNZklSjpsrIBrPYnpsguWOHDvgkCbdYxD/4yCOSVGv7dhH7NylKtKc4kqy8UmJ4Wh8Dk+YGLihxuImQ/z4bshdKteUTF/qPDasT34h+rn8YK1bIe6WwUBJevPSSxL3UxP79TSREbsLk+QqFQhEIu93jyzAaJfaywROcBkCFRTUC7777Li+99BJZWVkMHDiQ119/nYkTJ9bYfsmSJdx1111s376dDh06cN9993Hjjb7GxB9//JFHH32Uffv20bNnT6ZPn84555xzWPs9YmRlyV/1ZTUNJpKS/Jc1IhW2Ch5Z+AivrRLxwMsrX+bd097lhpE3KNHeUYCmSXbp8nJxFLuCxcPC5K9VK7nMDrcoXkWFPLStVo9BJizs8LerUARDdlk2t/1+G9/vEAXHJYMu4bVTXguY3fFA4QFO++o0txC5XUw7cspzeG3Va+wr2MdX535Vo+AkoySDN1e/SZ82fbhy2JWYGzsQSqFQ/DvRdajKhvKDIkTVrE5BnUEqJ5rCIbwVxPSA8KPD2ayoxpobYN+HUhn4xMUSHGYw+XacvI25lgIwrquXiGRX/i4mfDqB/ApxXozpMIbt+dsps5Yxfel0duXv4vsLvm+Q06obp5fMYHROV+soVhPQfDbvNlatP5+ICPj5Z4/DryYHX5MFMHTpErSwzEV6STrrstbVuemV6SvJKs3yyfodCm3aSLWCJ5+sPau+yQR/7P/DLVzrGNeRVlGtfNoc0/4Y5u6aC0CJpYQtOVv8BMtBMexZmD/aM7/tGdj1FiSOB1uZVIo9XMJbwqCHg6owuLgSt5O8T5s+fpUyBrcb7HZgO3QHqzNWh5xN+8stX7qd8TFhMXx17lfufqPNYaPF8y2otFdiNpqZuXUmp/c5ndGj4YwzRARrt4uY+Jpr4KabIDpanAfVufRSCQzbv18c4SCvEFd1IW8KKwtZk7mmzmPXdI2ZW2Zy48gbee89z2X84YcikHzvPY8YGsS5cfPNYrCblTzLpyry2I5j3dfVoYpD7v3bNBuryyoYp9tFSJy/ClqP8HU41RY8t3CKVEfrehH0vhHievkncqjMkoy5CWOCTuTQowdcfjn873/wxBMyHRlZeyBLdXF2nYTFSeUKR6Vc/+Zo36DBhqhgEkzShECC2ehs2D5Tvjd7mfQ1Itt7nIGaTfokFZlSxSmmByev+Y3sMk+2gxVpvhUCMkozOO1/p7HwyoU0V15/Xe47kP/79pVAy7O9NGQzZ8K990riizrfAYGSMoTAc8/B1KlSKezrryWgv7bAFpvNGZDqfJ53ie9CfIRv/3B40nB3oE6ZtYxNBQcYMfgp2PyQBLAuPBFGvQcdT3f2OY24hcfeJBwrwVf2cpg/BvrcAkOf9SQUqPTYNm86aQafL72KwkLJ+r9oEcTF+d8vrkDWWbPgP/8J9dv6F9L5P5AyUyr0ZC+EthODe8ZZCxr/2BqbqCQY/LjnXb/hTkifA2M+gjinV90qL8sqr8vXYDDUGIAebgr3SR5S/bO6lh2WGDmmM7SfAjmLJOFDAGxhLdmSv8E9PyBxgF+bvgl93fc/wNrMtY0rRg6Lh753iBB5/2fQ7VLp03lXODtzlyTf8KmsDkQlYTbD//0fTJ8euK9qNELv3v7Lmx0Gg/RBNt5PwL5nWDy0O77JDytYcnJgyxZJdrN/v8eGr+vOvC4Geb+Eh8OwYVDS6m+eWeZJYlVhr3ALkUH6zOd+fy459+Q0WTUcxVHKztfl+R2RACevgpiutdtCrEUy3ZgJNeoTGAUqOErxr2DtWpgzRxKUORwSmtCzp9goIiLkXWGxSGKnAwcgJga6dpXqhzt2SCXjt96CiROlra7Lu2XbNqk6FRMjvuv334fnn687oH/4cNnmqlUSXDlihAy9AlUTc73TQsJglGSRWx6F3W9D39ulDxqMUDgU4W/vmyH5FakSv/g0OHERECX7cfWlLPlSkci7P6VrsPYWOO5npwKijv5XVNPFkigUARn+PMxzlvLL+gN+6Qsj3pBxrYvM33zXKdkZuMqWt71MCwOcpQXzV0OHiSxJWcI5357jrh75+ebP2ZKzhR8u+IEerXo0/Lk1IN9u/9ZHTHVm3zPd4rCc8hzm7hb7vEN3MKvczAWRbaEqFzbcBcd+5buxBnpOdekiSTGffFIeN9dcI3ab996TxH4goWy33y5inQ0bat1cg/LwXw/z7LJnAanqeGL3E/lj/x+U28o59pNj+frcrzmn/zl1bKUOOv8HYns5k0/V7GRJ9RrKt4lqI4nCqpEUlwROc5nVYSW/Ip/EmEQuuQTuu89fc+SN2ybd7VIZg5ftFwFX5u8wK0kqTEa0gZwjZHfV7FKtuWy/JB1wWMR2rNud9uRwMEYwZUgn+vc9ll17zNxyi4EVK6Bdu5pt6keq2rbiyLHk4BKMBiMO3YEBAwMTB/p8PrTdUPdz0mgwYuw3l/btbyc3V5L5Llsm4sFAfhy7Xf5mJc9yJ/M0YGBcZ88Y02AwMLnbZGYlz8Ku2fl1z69UOSxEjvlQbOAgiWQKN0lSvvi+nh2U7pb/84F7AFs1W1gNFPYArnDuH0PAZAYA8ZEeO7+ma5RZyzjllDjGj5fEP7Ul9LNGecTIOrpPFWQX3sts1ZI7t4psVb05IGJk1+8F4vvr1bpXzQfSAOSW5/L8sud9ljmqCVrtup2zvjmLZdcsC2nb69eLEBngu+9kvAHyHPIWanlfX/WJgzUYpKKyy3W0YgX06yfjoAsvlDHW/v3ybv3rL48fNiJC3sd1Ja7VYjxVjh26g4ToBL823sscusMniX2TEJUEXS6E1O8C28N1uyTwbCIef1zEyN7s3St/TU4DiPZ0XWfOzjkcKD7A1cOuVjZaRWgUrJN+ZrvJgSsVB5kIOacsh625WxnfeTzRYdGedtZCyP5TpvveJhWPq4/7XDZhqL/guTlS37iNIG3Oe/fC5MnSh/74YyleUdd7qlu3oI9eoVD8CymsLOSOeXewKGURt425jdvG3HZUJPtLSxPb1bp1kJcH8fESAxgfL31qTZOuVn6++McbE6UqamC+/fZb7rjjDt59912OPfZY3n//fU499VR27NhBlwAvzAMHDnDaaadx/fXXM3PmTJYvX87NN99MYmIi554rVWNWrlzJhRdeyNNPP80555zD7NmzueCCC1i2bBljxoyp134blFDFxf/7n4w4g+XxxyUy1oW9UoIHdbt0CnWH04FvEiNfWAvpwNWDt9a8xROLnqCgSoLWXMaZm3+7mZdXvswHZ3zAiT1OrNe2/7U0ciarQ4fkkvrjDwn07N5dnMPdukFsrDxU7XYoLZXs0QcOyOEUFMhD94QTxDFcW0B1drbsY9UqMYh06iSOhw4dZKwbFib7sFp9A+EfekiCd08+WYwqSqjcMJSWSjBASor8jlar/M7e368riMzhkEppHTvK79a7d2BH/dGCXbNzx7w7eH/9+z7Bl19t+4rvdnzHzSNv5pWpr7jFH8sOLmPiZ75JKXLKc9zTP+/+mVYvtCL9rnQfIXNqcSrPLXuO99a951526++38u5p73LZkMv8RCwg90BhoWSKdzjkT9fFSGkyyb3SqtVhCqd0TaoJOiye5z8GzzvAHCN/6mZTNBKarvH3wb+Z/vd0MkszuXPcnZw34Lyjx7BpLYSKdHHcW7wD9B2A0RONa46F6E4Q2Q4iEwNXazlcylJg7weQ8Su0HCiVluL7SWC9KVqctujiyHUdd4uBdW1V0YDklOVQWFVInzZ9gkrIU2mrZHvudnq27ukn8iTrd/k/6WSI9HcGNVRVu8LKQvq9089n2erM1T7zPyT/wHnfnccPF/wQ9HbrTZ9bJUhm/2fQ+yaI61OrgMZstAMGn+zDRyuPL37cndnbaDDy0Zkf0SJS0mMXVBbw37n/RUfHgIEnlzzJe2e8V8cWa+auuyTYs6CgZkGyxVjA9tztgDjvR3UY5ddmeNJwtzPXaDCy8MDC+omR24ySagLJL+MWa9iKJWimIelzmwQEVOUjz3F/0iJ6kOnYD0iw0jHt/QWDg9t6xMgmg4llqctCEiOXWEqYu3suDt2B0WDkhO4n+CSwCTOFMbnbZObvm49ds/NT8k+UWcuIDY9lxgwYMkSEyK7fzmLxr3Ds6tqFh0uG7LpyrhmN8MbqN3Bonu9l4w0bGdR2kHt+1Aej2JSzCYBnlz7LtcOvZdiwMB5+GJ5xak/WrIGRIyXgt3VrGett3CifDRuu8/yy5zEajGi6RruYdiy/drn7eenQHLR/pT35FfmYDCbu3PYnq/pMg4y5sOJSmLoawloGF+Q78H4Y8rSIJr2fIdWdVJYCOFQtkYPmkG26+s66Lvs0mMAYwfTpZr77TsbVxx8vWdCTkvwrsrueSZmZEmztQtd1tudt56MNH2E0GLnumOt8xWPdLpN7oSINVl0JE3/0z6ZfE6GICUMRzFoKYOl/IHeJVB4d8Yb0d8CZ2V+DslTP/i15YC1ieUkpy/PeqPNQFqUsYlX6KsZ2Ghv88TchPXrACy/IsxPESD1tGrRvLwkecnPFWA1OMXIjM2WK2GWWLBGHYX6+CPdc15zr/ncJ4VdvzSc5PxmQZ/XIDiP9tjms/TCf5/milEWMGHsPZP4K+SulX7nkDEicAN0vFyF6VR7sqvb7DnwIVlwiYnXdAbvehL0fiajSUQXlnuCVMb3W8Ni9WTz1UhJbtsjldt99UkknKsqzye3b4eWXRZCgxMhB0Pkc6HimBGyvvgaO/0MSMuBUD/7ThQj97oKD30HRZrkGcxfD3N4SfGswS3UgoKpaZeRaxcg1lJQIRoxcaa/0axMSw1+G34fV8KGB7W1OwepYBUCYMYz+Cf4i475tPAGQYcYw1mWu44qhVxzecdVFvzukOnVlFiyaCiPegp5XA7p09aI7QVzNiuK77pJEEKWl/p9pGtxySyMdd0PT/UoRx+vVOtwGs7xP6+mPaUwWLICHH5aKVHfdBeefD9dfX7NtsrwcwiLsDHr3ujq3bXVYuWPeHXw27bOGPWjFP4v8FYABWgzwJJLwpoFsIYp6oNlkXGAv8/I1a/JMM5g8iRHNccrX8C9A16Wy8ezZcNppkpysQwdZbrP5tzeZ5E/XJYD+mGOgrEwSmk2aJJXFxoyRNps3S1DQsGHw5ptw7bUSIjF5suyrJgGSK4nRO+/AhAmSIPu44yR4/7rrZIxht8vlaTbLuO6zz+Cx62uJ2QB/v7x2PIS3A1seLJoiFYHiesr94CMU3gErL/esF0p/O7Y7DHsONj0ABeth/igY9pIkhzIYIbqj7Kt6xViArHmw8GSpiBnVzmMXielSa/9LoTgixHSH4S9KIhIQ28PSc6Wab3gbsOSC5RDg1RnNmie+gx5XOd9DtfthrBW5nP7lFP7c/6d7Wef4zqSVpLExeyN93urD7WNv57nJzzX46TUEuq7z4vIXMWJEQ6NTfCdmXzjbLWrVdI2Or3Ykuywbo8HI9FVvcP7UVzGsvFSqq8f1gsFPyHvb9SyoJTlUKDzwAPzwA+zcKc/XX36RuKOOHeV5nJ4uNmvvpJWNzUvLX3ILkUGEVH/s/8M9b3FY+M93/2HFNSt8hIYhYzDC0Omw/MIam1hj+nDIsQeXvyNQgnyQpPiuGDuAtJI0EmMSiYiQkL9bb63lMFxdLmMYjPsCFng5ARwVkD474HqNiuaAg9/AnhlgK5JkoQljoe1xcm8bw6TvqDvEn12ZjaE8hXfeMXDyKQbS08W/8PHHcOqp0ndwJVkND5f3+9dfS/9AESRHeSVNXddZeGCh23bdtWVXv8IRQ9oN8Zlflr6YmTNv55RTxA86dqwkvbvqKkl24+pPaprYQT77wsFfw2e578NBbQf5JfOc1HUSP+wQP3mlvZI/9//JGX3OcPo2XwJ0SSj46yBJyhfeWuJL8n2TswZLYZTvfE2VkavH3BRWFRIXEccHH8DQoQFXcWOPSnf7pe2aPeBzqk1UG5+q1LXt20X17+5Q5aHaD6QBeGLxE2heySHaxbTD5EzMU2oppdQqRsYVaSvYkrPF75qpjfJyz3SbNo073B02TOJmp0+X+dJSsYMGsoV6x0RcdZUksU1N9Twzq2MJz3T7ZzVdo02Uf2XkuPA4n6rWacVNXfoX6H8XHPzKf7nBLHEzsV39P2skBg6USsiu5CtHKw7Nwfc7vue2328jr0KcmXfNv4sHjn2AO8beQbvYdkf4CBVHBW3GQMbPkP2X+HtdfToXNSWRL9sPieNIzkvmxRUv8tmmz9wfPTrpUW4ZdYtcg+Y4+bOXQ+Fm6HaJ73YaIll7c6YRE52npnpsda6EGnW9y5ok8U99RNgWi7T3Xqcx+rWaQwoEWfLk2nZYAc3zMnBd++YYGUdHthUNVnOyiTssULYPKjKkT+qoch63jrswjMEotkVzNER3Ft9tdEcKLKV8tfUrHl74MAYMPHvis1w86GL/uNbDRbOL3dKtaTN66drCG+T7zCzNZEXaCoa0G0Lv1r0DJghTBE9RZREvr3iZ6cumu5fdu+Benlv6HNNPmM51I66rf/G+Rh63PvusSCt79pRHy0hnyJTd7h83azLJGKBFi5DPImiUGLmBefXVV7n22mu57joJWHj99deZP38+M2bM4Lnn/I2+7733Hl26dOH1118HoH///qxbt46XX37ZLUZ+/fXXmTJlCg8++CAADz74IEuWLOH111/n66+/rtd+G5T335eRSrDcdZek2nJR20tX16HsXZg/Vl4Qva4HU5QE6obFyUO6MktelLoDylOkak1kIpTslYwxCaOhx5VO0Zr3aMqAS8RWarNw9S838GPyjz6H6i3221+4n5O+PIkXT3qRu8bd5R7oNza5Zbn8deAvVqSt4P317xMTFkORpYjLBl/G8d2O57hux9GzdYBAhuZAA2SyqovjjpNgzptugnfflWU1ZYCuT2bokhIJ1q2shBkzwFW03PXArt5ZrayEF1+U6Wef9c0cVyele0Avc3ZK7B6hpSu4zYD8Y/OythTtgOhW0gk0RwXc7D+Jm2+W36FXL3EGHbUinbSfoHibdO5jujgHtWHObFtG988OGmgW0OxsKcpmwu+PU2q3BNykXbPz5po3+Xzz5yy7ZhmarnHmN2fWeSg2zcYpM0/hj8v/oMRSwriPxpFb4V9erspexTU/X8M1P1/DnWPu5MqOz3P3neFkZkpWwuHDReDfpo0YvV2B4w6HPAKysiQZQFaWiPtbtIDbbhMBSo1kLZDMt/YyyRQW2V6CgCLaOLPLhouwwZIP5WmShTayPRh0cTxGtYf+90uQwtFGqIk+kpL8lx1pajsHOPzz0OySRbI8RQZuEYlitHVVs/NG1zzZiQ1hktQkLB4SxkNc9zp39dvu3/jvL/8lozTDZ/n1c6/n+rnXExsey+VDLue1qa8RYW5+AbisvxN2vS4O0gk/iKjXO6ihMstT2a0yC6yH5PuMaodDc5BWlMLW3K3MTp6NxWFhQpcJHNv5WHq17kV0eHTAXdbJolOgdJfc2yOcwo/qL+rKLDEiuLIAFm4SkZ+iUcguzeaVla+wIm0FK9J9nYmd4zszqeskrh52tTsxj6ZrfLThI37e9TN/7PvDL4PwCd1OYHK3ydw7/l4ie98s1QhTf4Ae10DLQf6iukCEIEQrtZQydeZUn2VtY9q6DQPezrkfk3/k3bXvcvOom4Pefr3oewcUboUDn8JfJ8LQ50T0ZDTL+Ue2h9O2wqGVsPIKrpn8Cb9uOp35W07lpJMMzJkjSVUCVSLVnLbB5tgXSs5L5tONn6KjYzaaObvv2Vw9/GqfNr/s/oVfd/+KXbfz4YYPuXvc3fRuU78gwthYCew84QT5TgI50MZetIStJfKBAQPHJPkbt4e3940k+uvAX9w17q56HRNDn4PCjVLFsZZqAhgjZWxbH8xRMHEW/DnZKQrxP/Fl8ccD+93zg9sN9mvjvUzTNZakLIHjgj+MWcmzsDqsgARSTO051a/N1J5Tmb9vPgBVjip+2vkTlw25jE6dJPP2qac6919DxcARIzzzEybAY4/BU08FPh6TCXoNKuaVla+4Be+D2g7yE5Zfe8y13Pb7bejopJWk8b+t/+OqYVfx5JNSPe/DDz3HtHat/37K2yxlT7Yok81GM5cOvtQncYPJaOLiQRczY90M7Jqd1RlrWHPCr4wuOwBFW+CX/lLxsttlUqmjtuC5cKcTPdiKwi0GiWAovo8kGIlMBFOk9JcqMiXwsTIDKjLpFJnIX/8bzJlXjWbjhij69TNx6aVwzjnyXUdGimFy0SIJzE5OhlWrdGZumcmzy55lZ/5On12/tuo1APon9OeRSY9w8aCLMUyaA39Okoqef50kgZmtnfdgVBKcvk2CWFZWE5M1lpiwcJMIkQEG3O8RIoM8n8tT4bfBPt9tsQMuSsUdqJIQlcC8y+a5+31Vtiqm/m8qBZUFGDFy4Q8Xsu2mbcRFBA6qOdLccYd0y196ybMsO1v+XDSV78JgkOpj554rSeZuu03G/OefD2eeKePLykpYuhS+/x5Sov4GpzHdgIHhSf5RoNXv94UHFnLP+Htg0hz4YyyU7gM0yFsmf4EwRkp/5YQ/4a/jpbq37pDgx5JdAds/8ZiNEpuIDlNTJajmoYdkrBwVJRXUtmyR5qNUlzZ4Rn8If0+TKtW/D4U+/ycVA1oNlediTBdo0YiVcY8kxjA4fp48Q0v3Oiso6J5EFE58xMgNWBk5opq4tNJ2mGLkVkOg53Ww/xOnzdOJwQRRSawzeIIE7Zqdvgl9/TbRp00f97RNs7EqfdXhHVMwRLSBKcukP19+ANZcB1sfleuwzSgwRsChAJ0FJy1bSnKCxx7z7aeazWITqyvJSrMhMlFEx/s+xqd/azBB7+apqL7hBrFF3n67fP91ERMDjyx8gj2FnhTR00+Y7pOo583Vb/Lttm/R0Ph88+ecN+A8CdhVKALR42pInysJgw5+B10vaHBbSMgEExgFh1WholliOQQrr5SgpfYnOW0zEfKMN7WScUBFuiT6qMiEqkwJGAxrAYfWyHur22XQSd3v/0RKSjwVoi68UITIIGOV2ny8BoME/MyZI0mpjUYJ+Jk3T/68MZkkUdGGDSIwPvtsqWx3220SpO9t37PbJTnajz/CK6/IOOm000TwfPvtMsY4+2xJFGazSfLmv/6S7TymhRizAfDMLTDoNyjZA7857Qmdz4F2J0hfO6YLlOwObZvV6X+fBApufUK29fdZENVRAvDD4iQZafpc33X63QM7X4Hcv2FOZ2g/BTqf5xQuWyFzXsBdKRRHlL63iz8r+UXPsqpc+QuIAVZfD3krYPBjEiwLItI/IxnylsNyj139+HmPse7QDp8tpJV4hDUO3cGrK1+ltLyUjnRsqLNqMBalLGJ7niQMNRvNYjf0MkAZDUYuHnQxb615C7tmZ0vOFpYaOjJp6HPiX9r+rCR67HktdDpb4sdiujiTlh0eEREi4ps4UcYQDoc8Y1NSfNsFqkTaGCzYt4AH/3rQPR9ljnJXeNTRySrNcourpn0zjVXXraJ7q7r93TXS9QLIXgD7PsHPn2EwkdlqHDqed0GHuA4BN9M2pi0GPL9pWnGa2xdz883w66/yXgskLrvnHq+ZhLEw5iNYdRVegTOBORwfS13kLXPa6g1wxk6xt1fHz8dexPHDNjJnzijOO0+63WecIYUTLrpIkj/abJKw5McfJZxOiZHFt5RXkceeQ3tILU6lf2J/urfs7k5yDDRJ/GFjc6DogFs8ZzQYGZE0wq9Nq6hWtI9tT3ZZNpqusfjgYmZdqPP99wYuvFD6hLfeCvffL761xEQRti9eDAcPQp+TVrkFs2HGMI7vdrzfPiZ2mei2EZqNZmYnzxbbxtBn5Z114DNpqNulL1adBODVCBj+o8ePU0vsb2HKj7BVkitoulZjZeS48Di3wBQkCXmXFl0YOBBee036zoEwGiGhZxrZRrM7XiEx2r8ysslookVkC4qqinzXNxhrFKS0iGzhY0/Nr6ilxHsDsDJtpbtoiNlo5sqhV/LRWR+5Pz9UcYhOr3Wiyl6FyWji6jlXs+a6NUHHMI8bJ0lhv/hCnknz50vijUCxCFDz8mB56ilJ6PHFFzULYE0meQ+7CAuTxMljx8rtHmi9YROyyC02ua+VNtH+YmSDwUCLyBYUVIqNJbss269No9N6BLQ7Xu4jb3u4bocBDzT54Tz4oIwdly8P7JM3GCTeotGph2jP2iqeh3a+ySufvhJwk88vf57nlz9Pl/guLL1mKV1aNI/nvqKZMu4zWDBJhMKLT5d+Z2x3T5K0AEnkdR1mZ+zg3C8CO9Cf/vtpnv77aaLDoll73VoGHD8PFp4EO1+VWJD+9ziT2NhrzwhwOHZhXffafjWdjFsYeXSLF8eMkQT7ixfL+GLWLE9ylkBjNZtNljfJaYciwm6Kfu2BmbD2ZrG7TfheYoXj+ohY14VrLFORKdoVU3TgMU9DEkpMvGaF9KugYhf0+i+Mft9/ewHGY3aDiafWfsJLK16iyu77Hd/y2y3c8tstRJojeXDCgzw88eHQtWD7P4eD38p098vlOw1vDRGtJXa9Mkdir3VNYo8qM8QOai+DymyI7QJ97wxcmd0Lu2bnxeUv8svuX1iZvtLv82HthjGhywSePfHZZhuXFDKNrTdAvteXVrzEQ389FPDzgqoCbvrtJm767SZ+u+Q3Tul1SmjC7ya4vz/6SHwIU6d6hMjQdDar6igxcgNitVpZv349DzzgO1g4+eSTWbEicHawlStXcvLJJ/ssmzp1Kh9//DE2m42wsDBWrlzJnXfe6dfGJWCuz34BLBYLFq+SQyUlJQDYvm6FNuRqjGNm+K9UmSUPQ0seWA6x+MfVTE58F54BTnUKjKsPDt57Gvp0B2shjopCTJWPSSfruJ+lukV1uidAN2Qflbmw6xNZ3uMqcUp5U54Kf4z36fglZ/Slf0dnYOAlNXTcXC8gSx4FxSkM+u5GsryaTmw9jCFhnaGqCk3XWGRJZqclE4D7/ryPBb9+wIKIvYG3HQCjZsDR17kD7/N2ZT9ISIDEMI+wuiqfvp/fwG5Dud+2iixFAMzcOpOZW2e6l08qHsKSkc6oxvMKRLBXxz7cQc7DX4b+d9f6PVGVT+r6Zaz/I5u8Qx2IOvYJDOFmDCYTYQYb2B1gMoBJFAB2q5XIrN38xxHCAxVYd10fRn7ZFVoOlo4/SFke1wA0zghxzhGxtZDTe/dk+/ZT+ftvyMvVSWxr8Ok8euuaXP+XfRJLbGS5dPKHv+T7PQHEOiDBBJY8YsoPMbbfEBZtHMTixR4xsrcIWdNk2wZDNUHId7Fw0jxoH2Ck7vpuvY0dvw+HvtfBqHdrbg9g9axz64zRJPW8mLt6X0OLsDjPd5WQQFFkGa/s/5KcykN05CTPMQ28vc7zpiqfn79JZ8bMIUSFm7jzleOJcvVDNR00Dd2l55eF2G12xmY4jcFBXucrv/2YcV0WiUPh5JU1HxOAJY+tq/oC3YiNDSy+cSfs8boGQvm9qcpn+jsDefuVdiSRxYY1xVC1G2xZULwXKvIgMgyiYsAYBWHtcejxmHIflm1NSxcHYU2/X/V7b+iz0CtAtQ3v39uSx/2zZ/Bi3hz3x+HGMMa0HEQLLRysVopMVtaU7cKq2ym2FDN4xmBiANcTJNYUxe9j36Z7ZYSkywT+1LZzVap00Ddmb2TyswPZHlaTM9SX11a/xuvrytH/kvXvuKPudTp3hoce60OheQ8JI1tzztCnGGIfB/N97+/txlTezlwADgsXWguYnLgDWg6Rjnt1ylPFOOD1Dpi030h7TSMhvg/XDnmMEckZkLfJZx+zLKtZkL+evZVZnJ87kP8O+Vk+835nuK6Ratego/wQ3fpNYGLnpTxyXyYD+hWDWRO/nF2HyAhPhIrlEFiKWLl6N+O6LQv6Ot+0eBvDfrgHZtX9vboo+zgmpOt88Y8rmdzhneDPu3Avpk3OdMXn5kugVnWqXedp1z9C579Sgj6HVW1Gs3zysURrFVz3+ATCoqMAh5Q/t9vAHAZ6qWQetpVCVQakfyErT10LbfyrolU/pme++44Mw+9ggVFDHuOaLv2BQs+zM85IcVQZj6b8gM1eQYmllK+KN9d57GXWMmasm8GMdTNYYB/HSf1XSqXfqav9G1e7vzct3sYw3elhDfX9Pex5EdHUcd55m+aQGIWIkwI9o/a8D9s8QUqFdmh9oObz/Wqbf/bOCfYWLDMXAyIMMRtMmDA63xE6djQcuobmNHhNN/Xi7s5hRGT8it77Fgxxvfyzvnsdl6bDnQfNWO12iO/DXce8QO/YLn59hAX2zczKWQ6ahXHpXbhisDPRTDDXeVkeprXOZ00jvccO6/ce+hwMDOCUqPZ7u95jXcwHWb0kBSz7wJYGZYVgrYLoSBnE6kZwVJJpMdBxyzeBf2wnLqHe/7b+D4DOWgRpxsDJMVwsTFnIwpSFPLb4MUiZxDXbPuLB856lV9VICWhLOg3aTRKDTFQHOG2LZFleewMAZVUxxC45I+jn2pT/Pcxax0H3/j8f9iRXdD7DfY3YY3Um7HuCdaUHcKBxyy//x9OjzyGJLF5/TWfSmINgTYXCXVB+ECJNEBUJhnAwt4XwTqxc8Qvjui4O+vdessTIRRc/w6Wj+vPCPe9hWn0NbLwH2oyDNsPl3HWHVBfBQFR4FT9eNY3Xf7ubN9bcT+fOLTntNJ0zTocBAyE+3kB4uGQOzsvTWbhQZ7DhOS7t9AjW/DB29dvE9v1R7EmNoLygCluFDS3cjDHMjtngIMJYRqcW2fx34NlQBIx4DdpOkuP16kMSh4hcrIVgLWLltj8Z13WJ73lXpzgZCuS87/jqfrdj1q7ZuanFSRJt6bWPG6NHMUeXvo2mayTNGQ7V32OB9pHlvC/S58CW7+U8Tl3PxBj439MtufzRblJZWjNiMmo4NCPXTd1OeMzbIMNdHLqD4RVxfsfUIVanlTmGQns5mq7xf3ty4StD0Octv/cgkshi8SKIj38aqlpC0Q9yvxlcXj0jYILO91O25zVi53QN+rx9+qnrASIh6RnIfMSZXVFzbl+DFueyNKvMHarj0B0MLonyO++EOEgwx5JvL0NHp8uu7dz0lAEiWnP6kEc5o90kv2ftJsMB3s9aCA4L83J2ugYE6OicVJXkt4+TDJFuhzDAf/6+HOZeDt0v56R+d7DovRim3dWdgtIwZx4mA2aTht1h5MrjN/HuGU/BO7Pdv/cTZ4Expz1PvN8Bs1Hz+b3H9ctkwMQ7+Da9zL2/axNP9jumiyLacicG7M5rtfdf18OvV2NsOZj3b/iM3tFteezdJKx2o+TT1A0YjRq6biAuykrs2Nvd27drdi40D/Xbx4V6N97ySnD2n/596eB4n5ce+pbjBnwE6/4P1t0B8f2hRR+nYTrT3f6DhdcxpMNWxhrulkRGXS+V/k5YYEOyphkwGnVpO+Ae/wblqbBwik/fueQQjC+B5IeO444ls/h+QSvef9/Axx/K9+rC9XtMuvgxjE89Hfha9SI5P5lLZ13KpbMupctz++kZ9iOvPvQhw5gF80ZAdFfpK8X1FDFGeRo+gWWFwIwRcOp6cgvMbN4dxaYNGhnpOhaDibAoB63irAzpksGgDvvo2+L/ZL2a7ExVeVCwQd4ZFVl8s/p6zh72JVHLL5Fgz3YnQljgABiA61Nak64VuI/vxT63MCLbAHkZ7t/7+W6X89/kN9DQSC1OxfhOO1HRdr9cqmpCYNuG81l78Qvj+Wb5CSQkeCoT14bD5sD0vdn/vGvpU5QsfZb4tB0YWg7mhQs/o6sxgfte70iV1f86bxlj4Z6pM+Gr62W73v2Wmr7bqnzKFt3gPy6pTrXneeyW7/l9goE3BqXy3KftSE4O49npGk895S3wl3u8/ZV/eb4D3cHwcv/neVKsTmtzDAXO5/nmRy7jmMs2MHgwfP7xRxD2MRTM9CQAcyV+wwCYWJL7EhfdeYHzeW4kvtNHkPUEWHZWe56bAAe0uwTH7h8xvdGVV0dezvAnn+LZT9qz62Ak5aUaixe7zkPHaJBzuWHUo/DVc7K4Jtul1zumKfqpO1bs5Jp7xmB0aDz4+ki69XB+5sr0YXAagNxObJ0ei1oRE8J1vnj9ASb3+cT/vGsZf3fqfTydTa/z9Tvf07PF+1KdI/kVqS4f00nGEBWe4Os7t7enau8IiGjNf4Y9zZTEsX7HlGxK482MP8BhoW1WG57s57S3BHmd9xg4kZaV+VxxuZc9JC8P8vcAf0GUDq3HQtwUMBhYPP9bJnd9Mfjf23ne0k+FSePfBv15KP0z4DVYFTcSWAeAptkJLyj2vS+c5x1ettH9Pg7TzNiMdudWjBg3bvL9/RISMMf6Huum2GzpG9W73wIYLwXTarBtlURymMAYD22fZ+2OOe43gY5O30Kj3/0dEwftwlqQY5Ox5wtFa2G6wc+OfOhACR8u6kVGeQw9upRy3el7iTPn8d7m5WzWvwELxHa9kJcG3+d33sTB3TveoMJWCpqF3+/+jtaWAq696lNuOf9NKP7FKTB43eu3qIbXewzg/imw/c8kvl3SHh0DJqNG58RyZt/xI9oiG6bs/8p6wbzHarq/A/0WzmuqxnFoLfsIeJ0Xng76XCDXc+5tH4C9pSxe8CCTOz8vyw7nudaA5/3oleU88Mqx/PhjO0aP1jnnHIiKqtlhvCl7E88ulQzYRmBYi348GD0Vw/Z8973UJ+p45hpnUabJeHjt+69yxogz/c+7hucalbnw+xU+47GSMiNLFmms3hhOsR6HbjYQF1HKiB6pHN9/B2FVHxKfvcvnOs9ILuGnBTGk5MVQoZuJibfTp1MJZ4/axpyDi1mv/w8s0Kr7JTw70On3qXadP7DzbYotRaBZeJONhBXZKWp7A1uNd7JtbxSZB21UFVuwY0YPN2IKsxFuqCA2vIRebWZz4ei3gj7vpniP+Y/HAK0CMv+A0k0QCUTHgKkFRI+BqEH0mNCellV5nutcs0D2UiheA5RCZDjEtITwHhA9isWLlgZ+ntd03hWFTH3gZ565+BHG2C/CsGeGCGfanyR2kIhEOG2z0xYijqeznppJzr42TDnuG555NB1s2WApBt0kTqnICAiPkPdxVQ5LNvbhovuvlvP+q5T4sGSw7IbSbKgohkij05cRIQF1pkjKMr6tu7/WAUhy2lO//V81e+rZvtdUNXtqlbWCyKoNYIGIdpN4bOgTtA5v4XcNvn/gWzaV7AHNgiErCz08HSJac/bQJzml7Xi/99g240HeyfwTHBbsWUbMMX+DBdr3vIrH+t0qASFe+9BjdZ7Y/QG5VXl0NRzigfhk2db4r6B1tYQ25anw+wifsdLjyf3JjU32nHd0B8jd4HPeZdEV3Lf/a3SHBautkp+K1nMc0LXdJK7rdysD43r6HFNZVCXvpXzHzrIUfi/aRtevZlG1vTUjhlfy4VsHwLLX6YcqAqMudqnIKECS2i3ZMZKL7r2o2nVeCVl/QMlGr+u8JcSMhciBONZMwFRgcffXSsqMrFxqZ9WGcArKwrGZTETH2uiTlMPEvjv5LucHsqMXggVGD3mcq7uc5fd7l0aV82DKdzjslVRYy4mu2ggWMLedwPPHPE+MOcrv9/445QfWFe8EzUJUZi6VEQchojXnDZvOiYmj/X7vXaZ0Xs+YDw4L7bMSeLzfT/JZkPbUgOOSGuyKLarymfnIIR54+xzuv78zRUU6554LHTvW/M4oL7MT83kYFMHkEa+x9Zsp3PRcZxati3ePn8Ezlu7TIY/Sr0/j7aR1nHXLf7nr99f54osovvxCp1UrnYGDjERFSTKwbVs1iksMXHvm3/DOZMYVwfqPV/LAjL7MXtSSygr46itwGWNMRg1dNxIfXUV5/IvEPIOnfx4o2cB7T0O3lmAtYvp3x/L2I/3oEXERy2fPgKIfYd+HTjGaw/nssLr35dAMmIy6jOuDfJ6fdfEA0lfrDB58Jp+/GQ2HPgTLHqjIgv2feh2YfGdLkidx0TPfkEQWS+f1I6b8FahKFvFxxm94NG6e36esKobYeSOCtiM/+e1Msg3zar3Oy6IreODAtzjslRi0Kt5lnZ891ZqZz+8LI1h0oBt6GIztk8a00VuJMhxi5ba/QrIj18dvEMp1Xi+/YPVxidOMTG4uHFoKUTshKgKiR0HsRDAYOevGcNLXWmX8/ZmrfbYkl2IzRDogriPETIDI/mzalMywqMtDOu8pJ7VnYIutnH1WCcefEimRdpoODpxZBMJkmeUQ2AqhcBWkrHDbFQGy8sz8Pt/Izt1GyjUzETEOklpXcvKwXQxO2sPW1T+Smt6F/KS70VsPQDebMekOTNjRw8PBZMDgsGC3eWJ5jo3dxIB+Zj7/9AJoZ4Cc10G3Oi9X3XmN62Dw2J+uefIjPnvubcz7PpR7L6YXJIySRECaHYp9kwBuPrQHACMGbux6LoMM7aFcbKC/W7Ywt2QDAJ9t+YyHccYufBcLl1nr/r2boL/21I93uQ/Drtm5wDTEb8x3vqMzr3nZUy/p04m2tpO5///ac+Fxz0uSwXW3wdrbICxG7IrWEp/vqfp4zOEQEeyaTeEU2cKJjrPTI6mMiyduooU5G9IehyJoP+I1ls84gZue68ysha3cdmfwPM+Hdc/k+MeHsNjoFPoZzEQaw4k0hGHUZSxbpduo0m1YdTmPM8tG8/PwNXJsQVzn+/K2c8bsu+WSBtpGtGb75O9pU2xzf7frklIYt+sx7GjkVuQy85nreXSE02ZWH7vDJMB0DZjXgX2T73rhvUjVxgOfg/OY2lnMAe0ObYvT3AU/JkXB2X9Ngx+BkxZhCIvn87vNTNnZjS0H4tAxYDToaLqBG0/fynltV9Mj+hRaVuY6++eDoePLkPEo6FXI/QNue1zUMTyxPZGcsPnwStca+6ll0RXcv/8bNEcVdlsVHxWuoyPQK64np3Y8lTGtBhNXaoWiIhwt49iuHWRR/hrWle4j25LN74ZjGNNjAyS/LJW5o6sJsav52F3X4GlFsO6T1dzzVl/mrYwnMwNeftn1DXpsndERVso+ad24z/N6jL/v+vRRKs0HIKI15w57hpMSx/j93jtN6bzh7K8NMhVyi207FIHj+EXsSGvLnrRI9u60kZmuYw2LxhAO0eYyuiXk0attBqdwqf9x1MJ7mcdxQwjxh8XhMPyhKiZ91pVW7SZx16D76RzV3ueZY49x8G7KNySXHmBpyW6GlZooD8+ifURrzhryBKe2O9bvvLcaD/Ju5p9U2EqpyICEFmvc45JH+90iSWu99qHFajy1+0NyqvLYWeGV+F7XGaolBryXjglrx29IXODNUUUY3jUyrQiWf5zMo+8mMX9VPFWV8MMPnv6Q2ST+Qb27x+dv02xMcHTwe9YOinUQY4ygXLNg1+zMv/MkjpnmtJ9/egskxkLe+87EiDjfY67Aywg2Fd7MsNavwsEzarYzecX+Fqbv9fFVxuUUBjzvuEO56M6gv4dawdAfh7nf3/93LFjvaMu9r3fEZNR9/IInDkulddfFbMq3uXefmF4A5Rv8xiVtiKCo2qHqukZ8qTXgMcWX7MLhei+lTOL+YVN4nQ2e8Rg4+0bzISoFoltAi9MgQhJllG2aFNL9femXt7l97A7Nwf0tz/A5rjZxRm5pfwKvp8/DrtnZlLER0zfB+4nCqvJ584RnGV0wmZdXPESPHh05/TSd006D0aMhLt7gHpeUlOisXKGTuelvnjneKWoP0q7omHcNpgIrxu6X8/Etd9Azqj1PfdBergFNfDGud+vAzjn8dMud8M7X7t97CPDds/Fc8EB3rDYDDq/f+87/bCTLvBS7V6L8Nql5UBrg99bDcMn6vrX2Ccnv32D2VOt/QdsEFHvsqYm3QnoMiz8NzZ4ayK4IkLq9lK9/jSfH2grNbCAxrpDzxm2jb7sUSnJnuu2K4eM+Y/7zBs67oxO/rU10f6eu3+LyE5K5pPsc+OrBkM67wcYl3nTA/QzZkbmFgV/cF7hdNVJLUun6elf+NI7lxJ6rDs+uCJC9AQr/hsgiiI6DyAEQM5ZyIrn3z+PQ7Q6I78PNw55icHxvv2fIXOs6fstbA5qF0emduHrwbP/zDsGODJC7p5h5iyJYl9URPQwGd83mtOE76NQiw/176y0Gc7DbV6zdHs2uHQ4qCi1UWM1YjSYiou1ERzqICSulU9xqrhjr1KUEOR5z3d/efsE9m8r5aUEMWUVRWI0m4lrYGNXzIKcN20yk/hfk/EV+Rht29FjB3rQIUrPDwWYFq8QzGcwOjAYNe1kJEbHJZPS4HCxgajuBF2qwM32U8j3ri3eBZuHionAmdV8e0u997dXfc9cpr3LjBV9jnNsLEidJxeSWg0Q8PPJtuc73vodV14jYC+x9ts5rsMJWwcAZA4la+jijdv7OQ+dMZ6r+KOx8DTqdI0l74/vBsd9ITFbBGtj7gcfesuSMoMdj7ljCTmfDpJ+cflyvDBINEJ/aKPf3Yfi/Y6ry+f6yF3nbMI23V95O166tueACnSlTpMBBbKyBiAjRAJaW6qxepbNiw8fYE/9bZ3/tyd0fkluV5+Mvofvl6H3vIDU7nHWr7GzaaqK4Mgy7yURkjJ3uiXmM7L6PitLlnNjv4+DP+0AyphB1NafeEckfn3aluzGMEe0mM7LlAHrY4zCVSpxXuqmQTfaDLCveRYa1gE9j2nJ++1JJ3pU4PvBGq41lyqpCiz/3jtsrGL+Jtduj2bwnmtK8KiqKrFRiJjzKQXSknWhzGT0T0rg45YLgY+IjAGdYAa38k/gEOofn9nfmIUda4LZeVNmreHzx4zy++HFKO4d23nmLniIxar9o2rpd7Lvh8lRYNNU3JssOfVJgMpDUbhI3959C76ptPtdgVbSVGSnfsrMshT+KtmOrqiSjjrjcTTmb2JSzibfXvg0pk2j/2TdOP1El8eE7xZ5amg0VheInio4BQyToNjBG02PaI7SsOiT9llvzwHIACnZA2QHAIv6x6Dgwt4GwTkz/+hTe/sDp919nA0sKWA9CYbKziGgYRMWCKQbCOuMwdsG0/dqQ4lPTXv+IzgsP1njOfvQDbgVrfhg7ey5nV0YbdqdGUlFUBVYbjqgYqW2mlWOwlhIbk8mDnc4OevOnfXUaj7Y28JRRhyLIH7uJtTti2LInyn2dVxnMhEU5iI5wEG0uZXD4RqaFeH+X3FRF/JddKYkYy/aEz0g+EEnKXjvWMgsOgxktzIQx3I5JdxBpLOPGY3fzlXUgn3wynJYt4YordLp3B6MxsD+j0mILuLyhUGLkBiQ/Px+Hw0G7du18lrdr145s7/IiXmRnZwdsb7fbyc/PJykpqcY2rm3WZ78Azz33HE8GyI4bZtIwdjkncHbufZ/4PLjDysdBR6AVnqwdCQkicKiqgnAzWB4FZ59GdxjFNgjSgavePjISSufBvNfd+/jw8au4vvtnsOhBGDoXOnSBlgkQGQ9aicf44SS7uL1HjFyRUafoppUOvUshsUzsJ08sgWk7NwGb3M114NmJ8N1Ambe2KfLfZi0YdAMUysOInvGQs0GyNfznPyKyCg+HV86DYo+4p9QGOPVscRbofQiSyiDaBhYT5MbA3taQHyNt2mrRkA+UAtsOAAfq3AfdXSdYQ+BUtRf1afdvZXv6IE47DX69K/Aq3titSdDeeUwnLZag6TqOadja7fA2wFaghg6EFy+MhvvPaMXSXybySbt+HEroi6NXX+K6tMYUHY4hPEyEs1YblmILUZZCHr7c6RiKd2bQqp6JItwML9khQS7XhffA/i+6s+Lb8TzxbS8quw9E79Gd+A5xGCLCMYSZZXBps1FWUErkMV4HGN+v9u9WCwOXMygL0FdCz50STOkK9tR12PMW7HN21L3W+Qyw7fuCp/Z94bv9vZ7JMMJ42CVGTgHiokGvdg0CmE1whwNayuwjMzazNWMIPXrAxAB66urYrXb4kJCu8+Ex4XAAKA8TA1odx/T3ZbCh5TGsXjSGx1v3I2xAH4ydOxLTLgZTZBiGMHE46jYb1nIb4fYKbj0u+N8bYPuKmcyY9ATTTpoDB+Il2337iTD0DKmkaoqSCgb2cshbhp69xvMllO0LSuj3/VvncH7H2bD1IxiRCS3bQEw8RMRKUFHeXMj72d0+KU+uo/550LUIPpljI6lso88uMuLgmrMhtQXsTISh5VBWKs+1V/6oZMKjvilVrwQKx8Knw2S+e2sT24E++TA6A16dD4kVvqfxR094fDJsbg+WYZ/xTW4hB9Z05+kBQ4kf3JWwpASi2sRgjjRhMJnAAJrdgWZ1YLBb+Z99D6kmoKqAD1beyp0r4TivvuOuNvD48VDhfPbN3nUm72X0ZlrCHNhyLHTuBW3awv+zd9/hURV9G8e/Z3fTKxAgCRB6b9KrFBVEKSpg7/ooKhawPrZX7F0sqNhF7A3sKOpjQQEpIkV6L6FDQkjfPe8fk2zappJGcn+49mKzO7tnzs4pc+bMbya0Lrj8C5wDUjzwuzvreJawjpd/v4j6RyEq2fwObgfEh0JioJLcCgABAABJREFUYM4yL3fmzLzjlXsbybd94LHY/o5tZmUeucr3aMsp8aZB4rexYKfTLTbAvJ49Km8x22DK+r5wEtCdnIE+itmXQgNLt537JfUr1XrnOX8fXFJwcBAosJ3XH+UPQ4EGJ0KPZ4vdvwOS0ril81TzR9fpBb8fYPkUWJ2zjG9njOD0unNg503Q/kQIDTcXQX5BZl/a+yXkCuT/PDWcvy2zPbyy7AEa3v4AI9fnfL3HggvPhzmtwG1ltQVnrXfHPXDxP3DGWvDPddpcUR+m94T/NYc0P0wgMphOhb7k+51S1veF7MlAczf0ZJdFYCDMvgYOPFvwuywfdTUfy/i/D15k6JFfOCfmDei8EJq3hvrREFovK8g7FaKvhfQEOPghrnzDYDo8EJhpHhaQ7oBUP8jINShEdiAymJvtGXYmRV3G3L38BKxHxnNnm8ewGrWFJmHQthU0bAqBwaZjpTsJXCdCxjzWZdg8n5EJNjgPrWP+B2fx12vg7875zu3hMP46SPIHjwMGWz4udUq6nWfXU4spi27RZdi/y1re+WYm88rfOLTuYX65ZQZtu2wCxyXQegzUudiMqm85TMNH2n5zrPrtLAJzXXAGp8OoddBve845IN0JS2PMOWBd9rEwM81bT+2/DU7ZZM5RWd1p2BoJvzSF71pjNpqjDWiyeDutFm+ChkC7D6Hhh+Z5PcAv64OZQAvACaFJR03dKKRk9ZYu6U1ISQcS4MRtcPGU+4D7vOvmAj6KgPHnmHWyPRYXhz/NbSOfNsvfHQMxI6DzYAgenxXs54DMI3B4BRxaRreY+aUq770LxzOBjkxZdD+cCzQBWhyElt9Ao29Mw5kHSAb2AJkNCTq6hzvnPsYdPM4C+vL3rG4sndWe92nHYSJw4yKANJqylQ78S/Rlizhrxuf8sPc0xl0QyBlnwMXn2TSJA6czbyPD/v02q1Zkmrr25wCTfW9T+XR7K992nvv6LXu9V1zkvebrndSC3SmmLKKTYOj91xYYuH64BSdfBPuyrmVCW+c7jxWzDAB+zlqPe8w1wzlAPxrzIPfwN91p6NnDbTzJ4O9/Y+6hBvw+1OTJaUP3cyeba5RcLOCcUTC/sfl7SJ8VpVpvb3lzvzn/ZWsJDPKYbTsD+McDv3sgZAahj5VuvVf9+R4TmG2WkftSqS5wJub67rAHvgHWfMYZfRrwx5Cc9e567o0F1htg7ChY0BhSXPB21B6cbrCTD7L/rcmM+qRg+m9OhFeHmr7RnVObEe7YDwmmztVmyrgC6TsAQy6Fg0Hm7+DlZG2DM4GZDATWE8l7XMinjCOJMDq7l3MlbzLgpz+wugfDRrzlbWH27rF04mnPzaykM/U9e5nAq4xZ9SULX2rAZ8Oy19vm/CefhqNP58lTFDDhdPg9zvzdZ08mzAJYgUUPbgPOpxEfch4/MJz91CPGs5sRzOH85A94ZlND3E3MMhoehV5TLi2w3v0sOOli2J81qNNZ6TNN2T2IOd80B9q5oe1KCF9pXksD9gE74Ze/TmPXnkb0jVwIrd6Apm+Y40j9GAgNgeA4yEyF9GSoux+PbTHrxbMYV/9zWHsCtOyUlbYO+AX6bD8J/h8wCxrwK+9Tj1cI5XtO5SvPaDbRgqMEE0YSbdzrGMOXbEjbzW9Zn+22Cy5YAUO2gCtrH8+0TJ3o/U6wLKsqdHnaDKak3Q93AUFAK6D1Vmi5FUIxB+g0zM2XXUCPQDIWZTJz9sU8d4+T5XQhJgZ6dHPTqYtNVIhFRobNpk3wyWddSEnOZPMjN5iFlbCdac0Ld3OeKxVaLoUmZ5p2rdaNICrOBHi4ekJmCqQnQeBaOnnqsjblICRA7BG4+IH7wZO3Pe1yB3x6AezO6lMasjwlz3ZenNY97wdOIjOz2KQA3k45eda7mDpF8GzybOcTgbFE8wHnM4cR3u38dL7l/KQPWLuoJ3TO+nB2vaWY3zY0+1qrlMdzx+c2k2nCTVj8SX8+cZ/NcjqTQATBpBDn2cZZzCJw9ULuicZ7XOt27iSfx/PxWcc1gLO2/ssULjTNTL2zEjUE+mFuUIQCCTastuFPD3utNUzglbzHcwtz3O3hgcaYOstaNywA3L/j7JUGn4PFTC5hJhcDvzCENz1XsJWmpBBEPQ4w2P6Vq9yvsdbVoWCh5m9PzfU7lameGli69pb/Lb2OhVtuAmD02ILZ8+mh0m3nfhP7Qf4BlYusnzuZwD1Mcd8P12Aqmy2Azh5ofRBCD5qySQZ2woG0+jzfbje2B6zkg/z+5URWvJQ7TMF49Ex4r4t5Pjaxb84bJdzOL0m5z2wfuVd7EHAZ5piWBKR+Af/eCS+A32UnQtN8mSiyvLPWm/vzVtfaAL095nrCAWxyw2LonbKLoWfAgaPm3HzBGx/D9o8L/P6nRsCAcXDEHwIDo0kN2AEJcPImD0wp2AZrAZNOhZ+z2o9LW18rtN7iBMYD7YGDbnj3EBy8iDP71mfBYLz7d4ezJ/qst4wZDQuzmt5O3IP3uJa9kLe5lOuZRgqBOPHgxskDLzfnbS7nidt+Ykuw+Z3cWz7i/qs+IjjfhWtiADxzJzg9po3g/9LeNuvwNubhB3TLKou6WX8nAzuA1cDpgbAyNU891Q94FwetmMJPnExTz1amxk8m+pI9ZMY1hUezFl7C81iB69BiysLndWhZtnMwx4zzgBjgB+CP+4H78bvxRFNPya20x7VyXu/LW8OFJ/uxZHYP/rmwK/c62nC4cUciWjXAERxkpl3xuLHT0kg7lIJf2jZ6nwwpWe2pU99agzW5Z55Vqgs83gteydqmu4f5uKFcVLsieK9j5jCH++nNX/TBgxMXGQQH2VgWJCdHk0FH4pqcysaet8IssFnBezzDNCaykCFYeHCRU3HIwMUEetFo8qPsCDdtOe5N7zNx4vs0yrcvbY2AxyeD0w1uy2LQd+fyyKK72B3Vmeuug8Gn2JzdFaKi8h5B09NtNm6AHZ+8Vqr1roz2ljzXY1cDZwEdMcdlN2bUzqNkjT3yCtgNuST1GpP+d8x9rI6YHdYDuMIg0w/2HwErAyzwSx1YyvV2MnDrPfR97C8IBzr8AjG/mHpIA0y7ipW1vGaAAx4Y+jgn/HcFtBwP7W8zQeiuoJzlZXciS4mH38ayd+doXjv5T0YN+wYOR0OzC6DpADP7jl+EaUuyPXBkI/zQGzzppa6vzUoNZ2mu9tSo/z7AmLU5WXJbcO4F8GNL89zhsfBkl/fu3/h07Uk89DPUS8n6XYC3T4BZuatDfuBwA8kHWffBDYzId7sLYMYweLWf+cmaZjRgU6rZzj0b3qbFE29z8fK86d8+AR44MyuNAxq9dBEXN3oXFoyC9j0gpglE1DP3ZHxcK73p3MyOFHNOemvJA4y66AEaHM27jJcGwPRTzHnFts16z8pa72d3/5Y38QYKeND9DlfcPRM6BELAldB0ONS50gS5WM6cNryjO2HeOPZuT2cCCWa7vRyznXc1v1/B7Xw6eBri/DEN+3P4lgM8QAaL6YkHJ5GhGbRobpqGD6+xWbe5PTCUFvfc7f1tX/v7frpdez8n5OtqcMdIcxy0LcC2sB0mPfHz8L93IE//kDf9Pw3h6gnmuccBoU5IssGRfJCP/nctq6eZ6+ps6U445ypY1cBsU+N91deKOYYU2M6LOYZc2B7OGzqZFbM68/dN3Zh6U0d2hHcgomUUBAWb68SMDKy0VI7sSKCp33Ye6YG3fa0t8BMwhxF87R7FInphY9HFvZzT+I6z/l6M7dwKs2A4r7KCV9lIS37mJP53aChbf49jL8GEcJQxbOIkfma0+0/vOaMF/fgY2EcUM7mYuQzjAPXwI51YTzzn8DFnbFuKf3TWjtZnCLTs7nv/TrsXTAwdqza+xwR+Ndfsp2dtS+2B7m5znRyUBunAQRs2gp0SDVdlHRxKeDzv/tfdfMnDprqWfX3VDBjiMR3MgzB1qe0e+Bv2prXJuR4bkZW+PtDfk3P9lom5hlsHJDUkdMKeUpX3u6nBbLBMfe/1pffT76r7abefPO4bDi9nbXqWA17ytmWZCvrvDORsPmEP0fhhrrGepykRdOLTJjcz8KY/S3U9lnKgL2RXOypoOy/9fUEf1yXhwM2YumVS1sP1AewEPmhC92WX5JR3D0xZTwDiyDlOJWPOxWsh5e9hpm5ZivWe+2DWk2F/+O5Q671HOyknGPhn8Hxu8dY9L/I8N7KcLoCNX667WG4c3E53mtc7yOYD/2d+g0L6EGdLT0/n0ay6/B8MxH9FRk45RgJ9McfpMEyb7TJgcRJMMkne3HolrrMzzD2SNkCbDdBkgxlcwpP1++72M9fBQKc9ZpD8R362OX39p3nyci3wxAB4r7OZP4C8XceMKq6v9T/anENZ9w0aHoUeUy4ukMU++dtTM7LaU1/APOoBJ9imvSoyydT1UoHdwCbgxEBYYa7HjtwzmNe4imeZxHbivPsqQCYubn62E7c1fZ/7cx3PG2BiZ39nIJ95xjGfvnhw0sO9hDOZzanz/8XR4YD3ezLsTDLcmb4uXb0CMhyl6sfV2IYeR+Fo1nXJs98fpN6dJ+f5zp7A1N7wWla/pC6h+Tp1QNnaHQAGYnpJOzHtXj+spWvzBzj5TNiXtZiuc76CBV8VWGSb1tDlJFNH6F8XWJj1295jTgD1gUW4eIpb+YrRBNvJ3MwznP7Nd7C8CZek7Ch4HRoODMD0mwgEdrjhD2DlUt6+J4itbnM8f2PpA5xy2QPEJeTN01ND4OVBWW1DtgVOc8jaeWQjv66ZljfxjoI/43f3n0afekuh1WsQ/Rq0rA8tW0KdWFN2zgzwGwYZSaavl4X3/N2BPnwLxBPNTC7mZ07iIHVxkUGsJ55xfMZZO5cQWJn9PEpw/Z3ohmkWZGa1r33/3XWsfQH88nUrvOM8+LqN+VnHhcHwH1rx1A+38BEnENk0khEjYNBQD92iICzczNyUmAhbt7Zn9goLoksXjBxZLx2ewuxLvvrQ5Du3rsu02Oyx2Qymfh7/G+FpeNuBMh1wOBAyc/V3WJV9vzr1INMX3si41TBkc07b4soG8Eb3nD4SbT2xrE01+6q9/m0y33ibB/+XN993nQyPD8wa49GCnslmDAXLtuk/Yzpsnl5gXU/tAzu6meenhADzgc+hJ+35DthCU16zr+IvenOIOoRwlJbujVzOW6QvW8fNdfG2r514/n8h6b95vt8JXDwS/sxqxzlryyqmcIE5f2efx+pi2s87Y+pfh23z/p+ppPReAVdkpStBO9OYNPg0GTISzW/V5N2HYcPDBda7fX/onNVme3Ku9c5uX7sFGElbHvfcwQo608Czh4m8xOlLv+XLwPqsPjFnvWPHXQYJBRbBkDEQEmvuZUUHwf6s41qHObNhwewC6Zu3hq4nmTbCo9sbcFH++waRmONoK8x5+yiwf4a5OPi5CaGPlm7/HuiJJSzVrMeQLTatp5xVIE83h8HP55v+bw6PBdmTI5Xw/B3yBUz8+l+u4yX+phuLZvfi39lt+Yz2HKAe6fgTQBoN2Es71tDh5G0561vCdkXnj3jvGziZyb3A+bTkA85nLqeQTAht3Gs5i9mctWUWrr8D8twHBhgFbCSaKdzH33SngWcPd/Eo/T+fz+w99fl3YE55xxRS3ieOyem2NbTPSvOkKtpT6wNnY+pnvwD/mwZMK3V7KpDTP4LJrKYdj/Ff3ssa3MGBOVB7aMS9b3bhP02+56We9+ZpPw8Cvga+51Re8lzLLhrRwr2JG3iBgT/NYwHDSrV/QzldlxSx3nWyYrECM+CE3XD/LzB8Y96P7w6FW4bDwsawsS4MaJLVp7Ys7YpDMa9fiLmnaJPT3uICMmDWsrq8HOnG5QbPoXU0uu88OudrBgKYfoHpf2gBJzpcBROUsB0ZJpNCII9wF49zBxn4e+u2GcRh0Yu7m8zg+s77uOvb5/mYc2nSvQFnngn9LvLQrp1FULCZeTw9HZKTYeUKm42/5Kr8lPB6LHv/dvMerxDKq1zNP5yIk0zvNmjy1ZEQBvHfkel89PtUDod3ZtIkOO1cmwtaQGBg/jt34HbbPPnTX0yfn9POFHnnQB76OW+6NVFwzXVZn3HA1Kalb0e+KLUj182eDl9h9vWmv0DcL+a+hz+m3JOBfeBvN4Qmpt2h6264eglMWGyOP9mO+MMDg+GbNrC6PgRsbcPQnf/j1GlzzX2ltvugyatmn8/uI+fG9JFoawbrL218yfrEFrTuuglS9xT4LU2CY++fWtH7d1muQyO+hvt+Xs49PMSCo31Z+kp3fn2lNa/ShkPU9Z7H6rOPNqxjw5XvMScsq7624W0cr77Nvfn21ylD4MHBOfW1l5fDkc9DeYHGTCOaeGKJjITePTJp1syMf7Y/Eb7/pS1rXhnEB9fnawwtyXpn12tP+aVEcTVzMg8DsNGTwcb4uXwcP7fgMnO5cnEP3Ov7c17Dj+HX9tCyHTSMgbAo8PMHpx+kp0G9C+HAB4Cn1P3P3R4HL7x6E68uv5pD0R0YNw4G9PfQvTuEhVkEBJr5p5KTYf16m+XLe5r2je4lX+9nJ09kUvMXocn10OFFaNbK9HkOqQNOF9jJUP8qyEiAw58S4g7xfvbELXDDQhi4Pac+bwO/xcG03jCvmXmttOv9+OdPMDT9F0bGfACL9kJMHNSNgqAIcB8pcJ9hc4bFHtvmIyjxfYOmGZg+pcCwDTB6nemXm70e28Phu1Ywuz2ku4CjDZjacxLnnf6xCS6LOwOaDjLl618PXIHmPlHiBvjfyeBJ5/KMaO4d8ZDp0Lc5yAyi2/YkCBkG/hEmPiLjCBxZC/v/ZNXaE7i3yStcN2K6ad+q2whiToXOA829KFcouFPMtfHB+dj7fspzHiuJ+lP9TdxECeMNViZ05IFH7+WbPWcy/oIAzj0XrrjYJia24DkmI8Nm27bu3PmuOR503Q03z4eLluftS5LhgPuHwJdtYEU09E5z8tSMm3ht5VUkN27LuHHQf4CH7t0twsLMreaMTDNPxfp1NitW9ISnrivx/m3b8L9vRvLwgv9jfURPrr3OwbBhNmNuKHiPFmD3bpsDy7Zy29HubJjVir8e6M1bD7RnU1BHQlvH4AgLhoBA04CYmkrq/iMEp28t0e9fVpZtF9eEKiW1a9cuGjVqxJ9//km/fjkn1YcffpiZM2eyZs2aAp9p06YNl19+OXfeeaf3tT/++IOBAwcSHx9PdHQ0/v7+zJgxg/PPzxlB4b333uPKK68kNTW1TMsFfM6M3KRJE9599TYS3AfZnTVja2hiKpFHM3G73Xjq2DgiLYKtNGKCg4kMimRvdBcWWjbbErZ5v6vuviTqHHXjDs7AztoZWgSFExcUzJGQduxzRbL18FbvZ7LTHwpx4o5yEGmnEGqn0iwolHCrCymHbOKPxOfJU1hiGk6nE3dEJkSYZTQJDqJBcDCJrjiOZEYU+Ezk0UwOh7ggEsKcaTQKDiE6OJCYeifSpMFQ8ihiJg8AIlpBaBvfn8k3ey/ph4mfPZ+YN7/1WRa+HLpiNHUmTik+T9nL2LkFz7XP4UgvYc9V4J9GTjbdfR3xVnIh5Q2OSLzl/ffKEXz316n4h1lcdnljgoP8cbud+LssHJaFw2kGnrU9NhkZNmEhNhEd1/LP3r/LrbwzQtw4wkz+GwWEEB0QSEJYc5Ls0MLLOxzC7DRv+sQ6bTmS4e9NH7MjgWufm5fnt/nkxhNIbuRHTEAwkYGRJIQ1Z33iEe/3515G7jzF+IeyJ6UtGf5hxNSHPUeL3gYDySAptQeWXyQx9R0F0nvXO9yNIzJrGUGh7ElsS5ozlOfT32Fj6vYiy7m1f0Nu52LC/9nG2M8+x1XC3s1JhPBzw8YsvOgMUoOCcTmDsCx/QjJsgtNsMgNsHIE2tm0T4XQRGxlG9w0LaTT19RJ9P8DmPi1ovnBTidMD/HHVIPYOHlTi8j4S1opEO6iE5R1Er8h11PHbjV1/ENaJn0FglBn525EVdZWvww92Osv3uNhY51riUwvuS7nLO3tfssK7kZRRcJv1Vd7e41TUIJrUH5L3xyhilJgij1FQLse15baTjUeSiy2LYDuNmIBg6jYfxh3bZvPzgcXFlnPzgHrMbn4eBDUqchnOOjbBjnTv8d8/rDPTDqzgjW1fFLuMZxqdxjX1e7G6fkNmpcZ7j1FNNx7ggdu+8aZ7+YmBxLeIoEVQOCelryAueSU4A+HcFN9fvHxKnov5FTstNtS/3rt9FLYN7m8c6t1u9zXpSHx082KPndnn1vSU2DzHzpIc1/Y268JCP7tE6+1rGfnLIv92nt58ELvrxBVYh7DENFxOV4E6QssAB6FH0nAfzcCvThMyLRs/lx8Bth/+bsj0c4CVgtN9hEDSCHRYbPfvy6bte3zmydd5LMMvgJt2/83G1H2AmcE3JiAKl22Bx81hTzKJnpxyvbvhYB5sPwErrG3eMi5i3ytsvyhq/94b3SXPb5W/LJ548mSSmgeWqCx8rXdkUCQJfs1Zf9D3eexwiIukcNOC1CoslMahobRs2JemdbuXeL1zHz88toekzGT27t7Irr0biXKFExNRh/DIQJyWo8THkPx5mudJ5r5NH3iz0yq4CZ0DmkB6OjY2v6Wu5aA7CQB/HMxtfTmhzbqXeP/2VU8trCyy6y0B9QcWmf5YllGW8m4cHMDQoD9wWDb0eglaX2saE7JnnT66Db5qm2cENsCMFN/yWXMxX8ryLpAeynTOyF3eLVOh7+2f4SxFvRYwswB/PhtiYgrmK3+eUlaRkfIuTk8yji73Qae7AYdpFMoelOnoNhOInHW+X5rmx9J2D7I1JanE5V3csTN7vaNDo4kJiyEgLJK0I4cLL+9wcIRBsJ1GJPUYf9dXZLqdTJtmMXGiGeXf6aRQtg0r/vmejavmlfj8nd5uELvrl/x4HhcUTIvAfjQL6JZ34UVsU0vr1WVpoL/P816mOxMrzMaOsrz7XlRwFOkpsWzatqvY+nn2uTW26Sk0btD/mPNU1HqXtrxp3owDgXa5rbevZXRp0oOWoXElWu/MtAPUW/44iW5zLowNqM/O4XMK7N+jtz7JtweXeWe739bneZo0GFDi37ao40H+7Ty73pJYpy3rDh6osPIu9vxdgcvIXu8j4QE+jwlbdq0u8fk7IyiG5BSKrTuHOtJoGBSMI6yLz7aTqlzvcGcz7nv0KjZtbkjfvh4ef9zhnX0nM9O0mVqWuWEKpt02nqUsjV9abu0O5VE3Kst2XtJ2h+yy2NuyB7vrxpS43lKW9pZ9rXoSXye6xNclRbX5VdXxvLj9u7Tn42M9f2eX975WPVlgpZW5PbW48u4yO5l2rxd9IzI3Nw6+uXAMu3oMZH9yMgkZyTgIICTNQ0iazdFAFwTbBHnSqevnR0xkJLG927F5zZ+lWu/yvg7NLovs8pjv2sUHO7/HndXpYW7flziFFt7z2I6AQzRbdRNuPDhx0CekEc/3u4O/gwLKfP3dMmAfl9T9Cyvf/SC3bbHH3YC1UfcS0a0fs1bPKnF5l3a9T+0wqvDzPfisnxdZp6+E+tqx1lt87d8r/x7ErPdvo2AIugenw0O/+/sz37MUt21Gtfpn8Id0yT1jQVQUS+z19FxoBrlw4eD8oK6c1WhkuZ2/j+VYW9h1aHb6ouqpJb0nU9LrUF/rTfNmLE3dUmH3icqy3sW2ZeVrRy7yHAM+21OX1qtbqnaHwweaMfWZMcyb3wWHw824cU7Gj4dhw6BOVh+gI0fg55/h779h7Jnf8+/ShTz2wkj+WdYD8BAW5mDMGDODWUiI6dD944/w3XdQb+RUdna6xTuTzlsn3MdlTcbk2c5fS/iOq1c/Zxa2+Gr4+hUCAz3ExzuIjMwZI7UwmZmwfN/SPMe16tDekp4cQ/PDP9OGP7EBR0gTMzNE7EgzQJvtNrMQL70F8LB8r4uAel1p41iCBwtnzMlmVo+YUyEwK4LnyCb4pn3WzKCwNN2fWTET2JacUKL1LunxPMKZQvfwNIYG/WGCUEevg9AWBX/85VMKzrwG2FEDsU6aY9qsbRtyd3BMiYfdP3tny1iaCktb38PWDEp0PLecwdy98lfWH93l/coQZyAO2wLbJo0M0u2c0QKnRA/lhKjunP/vi6Tkb3/y4Yb6fVmQupelR7aY87PlYO/wH6mbkO7d9+xQi6arb2R7mgn+CXME0MA/ki2p+3DjIcDhxy0tLiYszYbkoyQGWDwd/xnpdiYOLFoH1OOtNteyO6Xw4xp1bYiwvNdKy9zJ3LF7EQBOHExueSFPdpjk3ZeSgtNp8u/1HM5MxoFFY79w/ujxEE/vmc+zm9/3ua7ZmvnXZU7zobT1fIZtW1jD55mAOo8bHFmNOoW04S3fDY7IrnQIWI4NOP3DIfZ0aDQSgpuYmTT3/Q4rHgA8LNgeyY0f/saiZZ0JDnZz3XVOLrwQOnfO23508KA5jrwzZxW/tuzD0UzTCau+f10mNjsbZ0oqHE1mE3t58+CvgDnbjgpvS6rTn58OrfS2Edze8lKaucPgaBLukGAej/+YnWkHsLEJdvjxfMtLmbD+Tdx4sIDYwPoMCzsBK9X0WVicsZkVue57Ptf4dAa2H5mnHlJce2pxxxww++uR5gFlvi7Jf685d3pf7WuOmD4+0xd1PVbSZZSkTlFe9bX8bVnHeh1aHtdjxeUpf3kfcNvctOwbMmw3Dhy0DW3KA22vwUo8AkcS2eo4wK273jPnEiwGhzbj6ZZXsuVoKvFH4vlxXhtmv38rYGPb+RtiPZzWcQdfb2iNIy2d0lgc52LZGw+x1eG77bk8tvMjIe1YnJRQpuuxpOQtXBk1nzrOZPJPtOG2LdLr9GF97BRvu3NExj+cX3cJYBdID1l9SsI68E+nJ1h6OL5E+3eLACed9v9GUOZBnK0uxa/zXVjY5MzWaMHqp2FN3kEJ/7ehPle/8wsbNnYAbE4+2WL06Jz6V2oq/PUXfP01LF8O27enk5jo5N13HYwdm5P5/HWkzMxMvvpqFokJu6kbtLfQfh65t9uGIdFkHG2Ew8+PRnXTCu1Lkj99RHAdLu41AFfug3ch9dTM1EPM2uLhkL8/21sns+1I9amvlfa+QVnbU5f9u4tnpk7iwL5GWaNnWDgcEBZmOkJnZAUj9uzh5o3XfyzV/ZIObcd7rxkS04+wLz2B9buWs+PgFuo5Q2lfpzENIkOJdIbgyEwoUz+uIu915Svvwq5LoOrbHUral6Qk5z1f5b3fmcqUrOO1EwfjY07mtRPuNXk6cIDdAYl0Xn0HaZg6YcfABvzV6wlWYPHwujdYeWQjG5PzRiBHuELoEtKYc+p05qrIjqy1AkrcrljSNvrizt8VcTwv7fX3osMOntowy/t9r3S5m6uDT/SW9wLHRvqtuw8AJxb9dk1g8YznsBxOpk1zcsUVph3f4zHBGrll9782Dfvxed8s5+3c4WnBff9+ym8H/6Y4s1qcT//owdy8dTbv7ZxTbPruwY15J+5M7j+wiE/2LSw2PcB5dToxo/Md+EfkG6iymPVebjuZt2tjtWo/L+r+pq92piKP/1W03sfa3+HQ0e38J+pP6ruSCtR1bBt21LmQfd1uznPvqiT7d5G/lY885W+zrQ73iYrt31IF94HLct+/OranZi/jy5+a8Pbb/8GybGyP784hPXtk8sbrP/ms51TkfcGynMeKW+9j7XtSmn49GUdXMCr4WwKsTJyW79CanQEtabzSRERbWJwc1Yu5/V7OcwzxhELkiv9wJGt2xEZ+YXwx+FFmp+0u9fXYpr2Hefa569i5rS227fCZp86d3Gzb7ubIERcPP+zgv/81dV6n08zlkl/2eXr5vqVFHqd89V/buz2Qh54ey/r1pi9lYKDFyJHQs6c5x+/dC7Nnw9pcgxm+8w5cXHAsogLS3ekMfrUfi/Yuw40HBw5mnHA/jdP8ISEBOyKCm7e/yvKkTXiw8bMcvNnrNlIbtipTeZe03aHIe1dQ6vOYrzpko7lbaTvjx+J/pCyF9aEvz/6plbF/l/Y6tLTnsTr+fjyQtoUfD6/0fmeEK5QAXGB7SMNNgjtnlMQzI9pzHjdy1b0Xk3Q0iOHDHUyZAn375qxz7raBI0dg1izoNGxpqe4Dl7Z+3rvuaBq62jN9y2f8dnApiw6vYmfqPiwsbGwiHcH0jWhFt9Cm3NZgAHXsjFL3y3X7NSApw1mi/ufR/sHc+vx0Vm5uy5gxFh98YGKvfdX/ofBjTnHrXRX9eo41nshXTJsrtBPP7V/GOzvy7j/51XEG83XLC+kXO7Tw/upQsE6Y+D5kzMcO74A1dA6ENDET7uWelDTffaKj6RDsBzQeg9V/ppmoL/dn8vWZBdOWhzMYR9/XoOl5Jp3tNve0kndA6j4ziei8s0sWV3OM/VPvuXoqO3c2ZOJEmDatyJ82RymuQ+20w/S8+Ur+3hjN2HEW775r+qnZduHbudsNK/aXfDtP39KDe297HLBZutSiW7fi79F6PLByecn6/jYKCCHU4+Tkyd+SkJBAeHh4CX+oklMwcjlKT08nODiYTz75hLPOyhmZ6qabbmLZsmX8+uuvBT4zaNAgunXrxnPPPed9bdasWZxzzjkkJyfj5+dHXFwckydPZvLknJEBpk6dyrPPPsvWrVvLtFxfEhMTiYiIqLCNrdbzdQCLj4fDhyEyMm9DMpi/879WlPyjcZREYKCp9cfFFZ+2JpkyBXzMCl6k++4zn6uGlu9ezvMLn+eNZW/kef0/3f7DjX1upHPDzmXbPqD020hpt3OHw5wZfaWHY983SrvewZjZnQH6v2dmEshv+RQfHX6ccMYmCKll+1IZeDwezvzoTL5alzNabnhAOIlpid6/OzfozLzL5xEeWPZz0cq9K3nk90f4YOUHBd67qc9N3DPoHqKCo3x8EjNKeY9c0/YsWQLdc12gJG0xHXqObgdsE+TnDMrq5GWZoUwzEiDjEOw4ABd8BaXsdFDqfa8sx7VJk/K29KxeDRddlPP3u+9C+/Y5f0dF1Yjzxf6j+6n/VP1i053T8Rw+Gv9RJeTIh+K2wVrs6q+u5rWlPmbgyefj8R9zdsezC75R2t/2WNP7+sy2bTkXsFC++54nE77pZEYla3k19HnFXKF6MswxKnmH72BkgGF/Qn0foxRWhcqot8w7H7Z9ZDp7DptX8P3CArcHf206eELJyrsCZWZCq1awdSvehhWPx7zu7+87PfhuEBHJdvYnZzNr9SxvkM6eW/fQIKSB933btmnwZAP2p5jjWIs6Ldh440af3yVSWrYNgwfDn3+aGzo//WRukhZ13PJ4fN9ErZVUh6xdiivvotpnoHzaIstDOW+3h1IO0eK5FhxOO4yFRbPIZlzUJaeu/eOmH1mwYwE2NhYW/1zzj2k3K6vkXfBNBzO1B75us1jQ/Vlod2PZlyElsnYtdOpEoTPMOxwQd85UtrW/FY9t2iI/OfsTxncYnyfdBys+4ILPTXughcVzI57jhj43VGjepYYp5rh22WXmsr9ePfj8cxgwwGy3+es7bndO0/ngwTB/vrn5fN99cMcd5povI8O8ZtvmBnhyMjzx4h4eTInFY3twWk7GdxjPh+M/zPPd4z4axxdrv8Btu3GsGY/nw08ICDDBz+3bm87hfn6+b3ZnZprXCwyCVR3aW5ZMgrXPARZ0ugc6/Z9pt7XtnADP/X/BD33yfo8jAPq9A03PKdhB4+BSmJNvuSOWQHZnlvI8j3ncsPV92DQDMg5DozFmOaGtILCByVfqXkjZadp/EtfCP3ebNug2E6FnIb0tlk/Jdz+j9PcyDqUcot4T9bxB7oW5tOulvH3m2wCs2LOCk985mX3JOYNCBvsFczTDdO5yWS7uHnQ3U4ZM4aOVH3HeZ+d5v2fGmTO4pOsl3r//2f0PJ7xygsm95eT2AbdzVferaPVCK+8xvTBOy8mmmzYRF1H6du3zPj2Pj1Z95M1/5wadcTnNzronaQ87j+z0pv3l0l8Y3Gyw9+/le5bzyuJXeGnxSwB0rN+R+4fcz6g2owhwBZjy+6Yz4IF+M6HZ+Wb7s5xmuy2sXSq3lv+BHs+BK9hsE9lB6Lm28yteeYMZ8y4nOtpi3jxo2rTw66fsTqq/bP2Zk9852XeiXKJDotl00yYyPBk0e7YZh1IPFfuZby/4ltNan8ZrS17j6q+vLjb9JV0uYcZZMwq+Udy+V1z7K9TY+x+Vrjpeh5bgnPHe8ve4aFa+bcKHcP9wNk/aTN2gut6v7tcvZ0IOX07ruI1vN5ZD23ZFnCuL+0xh6W0b/jfcDOqRawCKPMLbw9A55vyy9zf46eSstMV0R3MEwui1Oeel0q63J8PMvGJ7zPKS4yFtn3lkJpHpCaTLqLNYtzGI+vXhgw9gyBBzzPPLdcrP/nvfPqhfP2e1jx6FQ4dMcbrd5pHd6dDpNHWyunUhNLTojoLVQnWor1WCQ4egVy9z3yQzE7p0MbfEL7ww577Jb7/B1KmwfTssLn4M9WOjflwV6u6f7uaReY8Um85luVg1cRVt6rUp8F6GO4MMdwbB/sEVkcXilUe9pZzPx26Pm/5v9OevXX95XwtwBmBlDf6Q5k7zXhvUC6pH6Mt72LbVycSJ8MILZV5shflr5188+ceTfLr60zyvt67bmlv63cJV3a/CkauS/NQfT/Hg7w96+zAFuYJIyTSD+Po5/Lj8hMt5eeTLOBwOPLaHTi91YvX+1UXmoVODTvxzzT84rEIq43L8+f0c2PF54XWjOt3gtKV5X6uMc2V1rJ9LufrqKzjjDFMnBWjXDm67zQSCOhywYgU8/bRpU1y6tOjvqhDVpE6YR0nzdGQDfNct6/oia98Obmza5jzpcHg5ZJoJMnpvt1icCjY2Qa4gEu9MxJVrcMAVe1bQZXoXAFwOFzf0voFnTn2m6Hz5yFNGhmkb/usvcy0C5rqjfn1zPbJ3r3m9VSvYkDW75po1pvpZJsXkKTHRXBOvXWvyMWUKTJ4MwcE518kOh7leWrYMzj/f1Ms7d4Ynn4T+/Yvvr7Q7aTctnmvhPfcW5Y0xb3BFvVNqRhtQRceX+FId29cq4DyW6cmkxXMt2J5Y9KRvzSKa8ce5G+jV08mePeZezuuv+75/k+f7i3n/uFDK69bDRFCHwwDMnFlwsziuVGI8UaYnky/Xfsn//e//WLVvlff1h4Y+xH+6/4eGoQ1L/Z0AzI6D5O3QbjJ0f8Z3muVTCsa9OIPgnCOAlTPRERR9b6LnC9D6upKnz93PtpzdcQc89ZRp9/n4Y2idNft7RkZOPSmb01n05D6+JCSYwy+UfFCN0tq6Fbp1M4f6Z54x7Ve2bdbB5cp7Lye7XdJXn+CiVHR86PF++KtW/P396dGjB3Pnzs0TFDx37lzOOOMMn5/p168fX331VZ7XfvjhB3r27IlfVut3v379mDt3bp5g5B9++IH+/fuXeblSBSq6Q19cnKnl5678QdEV0upYqa4MEybAmDF5XytJh8xqqkt0F14/43UeG/YYz/z5DA6Hg8l9J1MvuF5OouK2DyifbaQqOq6Wp2RgIdAHWP8yRJ9iOvrknhm59QRonLX9HN0BmYkQ3laByCXkcDj48vwvWbt/LRd8fgFL45d6G/EbhjTk47M/ZlDTQce8nE4NOvH+uPd5evjT3DTnJn7f9jvX9byOm/vdTIh/SN7Evi6cc8v/d1SUmSWjJKK3gVX0iEblorTHtfh4GDcOnn228O/Mf5VYQ258RoVEsXPyTobMGML6g+sBaFO3DRsObfB2XpvUdxJTT51aeZkqyzZ4nJdDWb06+lXij8Tz9fqvAXPDr2dsT+bvmA+YjoH3D7k/JxC5uv22JWm8OZZ9z+GCkSthy3uw4wv4ridEdoKIjhDWClwh0P8dM8KbOw0S10P6AWh7U/UJRIbKqbeEtQJsM8BE2gEzwlvuDse+7AfW7IM9WXdt8m8/vl6rwG3K5TI/0+uvw2efmcaVgQPN/23bmhmyAgNNo39qqmnAOHQIrr++QrIjNcSIliP49N+cDhmLdi5iZJuchsGdR3Z6A5FdDhejWo+q9DxKzXX4MPz+u3l+3XU5HTuLokBkkUIc7+0zZVQnqA6T+k5iyq9TsLHZfHgzj8571NtZMsOT4U17SotTji0QGeDfx7I6nxTWwd6GDa9AkzPVblTBbrqp6Pc9Hgg42N173e9yuFh3YF2BdOsOrMPlcJHpycTGpnuMOutJ+fn+e5iRFVP3+uvQJysm1ldHlew60Pvvwx9/mOeffQZnnplT//HLdwkbHAxTbmvIX++dyg8bf8Btu5mzYQ5ujxtnVjBupieTuZvm4rbdOC0nI89I58E7TWewYcOgd29zXdm1KzRqZK4pXS5zTZmUBCtXmkv1SZPK9ac5dgn/wtqsXu8nPA7tb82JCMoODDq6DY6sL/jZzv8HcVkDE+RuFzi6DRKK7lBerhxO0+ac3e6cngDJ20wnkqSNJtjKzgDLz9yrCG8NfV6DFffB+lfAGWKCkvOfb7LvZ6TEQ/pBCG9X6nNSnaA67L9tP6fMPIW/d5tZxZpGNGVrwlaTdcvBlMFTuHfwvd7PdG7YmT237uGtZW9x5ZdXYmN7A5HP6XAO00dNp06QmQ58bPuxNAhpwN6je3HgYPri6TSLbOb9rjeWvoEDBx48eGwP1/a8liYRTXjrjLe4dPalOT9hVgeY3AHKM8+aWaZAZICnhz/Nx6s+xs76t3zvcp/pukV3yxOIDNClYRdeHPkiz454Fo/tMQHIuYW3hTM2w+onYfk9sOFVcz8qsrNps3IGwSm/Qupu8KTBwWWmU+yOz8HOhHY3Q/dcM39md3jNtZ1/v3w4b/12BWCOJY0bF339lH1MOan5SVzf63qmLcoJcPdz+OG23d7f1s/hxy+X/UKQXxBBBPHV+V9x4lsnFhmwfl7H8zit9WkAXNXjKhbvWsyrS18FTJtuxwYdWbt/rbe+1q9xP946463CM1yYknaeq6H3P6RkLuxyIc8tfI5FuxYVme6ds97xBiKnp8PZZ+d0AM8WGGj2reRk8/du/0q6J1+ZNs+E3cXM0JS42nQ8PG0Z/HGBCQ7OPiY0uwjaTYKAKHM++vt2M+gzmI6KafvLfr3k8Mt7/g6ol+ftl56H1etMfebnn00nfShYj8r+u27dnNcsywQZh4aWLWtSNS67DLZsMfvqLbeYjqn5g8/794dBg8yAiBVO/bgq1L2D7+X5v54nKT2pyHSXd7vcZyAygJ/TDz9nMfcHK0o1rbc4HU6eHfEs/d/MmXU0zZ3mM+09g+7h0y+d7NgOGzea9hfbLn1H74rUu1FvPjnnE7YnbOf2ubez8dBGHjrpIYa1GIblYySJWwfcysTeE3not4d4ZN4j3mCoCzpfwLOnPkv9kJyB7x2Wg5XXrmTitxOZvmQ6AIGuQGzb9v5mE3tOZNrIkk7VJceFfX/C9k+KTpOZYq7P1CYs5WjLFrgga14dpxNeew0uvdTUe7LrOm3bmgDQ336rsmwen2yPuY7JDkQOiILO90Pra3ICrvb8Aj8NBeCcUJslaRa2DSmZKfyz+x96xOYEUP6+7XfvjKWZnkzGth9bpmw9+SQsWJATVHX66fDii9Csmfl7714TDLxqlan7PvOMKf9p00ydF8z2kX1+zh5kMnsQzNLeZ3/hBRPs7HSa2Y9HjMj5jvzBUZ06wT//QFoaLFxogpNnzzbXzhEROemyT8VJSVCnDtx3XzRPD3+a6769rsi8tKrTygQiV8O6VJlUxn3d/AHPRfWhzO5bnOa7Duh1HPy2LoeLTTdt4qwPz/L2N60TWAcbm8OphwEY02YMs86dxfPPO9i927QhTJ+e9fliIu2O+0DkMogkgXt4gIe5h0cfsWjTxqJ375wgSjDHBtvOuTaoTtcHeVRiPJHL4WJs+7GMbT+W1ftWsztpNyc2PTHPYBZl0uUh+GsCbHkfGgyGxlmxg550vIHGLf8DsadnzZD8A6x/ydx3OLrdDLxRUYMm+dctPk0ZPf64Kb4vvoAHHzQDCoaEmMNPdp9Zt9scxg4dMv8//XTJg3kjIuCJJ+Cuu0y8ekwMnHKKec9XwHNhgzwXpWlTM1DeG2/ADz/AJ5+Y8R06dDDrERgIAQHmNJeaCps3m/Usbfx8RaqFh8CKdfPNN3PxxRfTs2dP+vXrx6uvvsq2bdu45pprALjzzjvZuXMn77zzDgDXXHMN06ZN4+abb+aqq65i/vz5vPHGG3zwQc5MjjfddBODBg3i8ccf54wzzuCLL77gxx9/ZN68eSVertQScXHVqhJXbdXQDplRwVE8ckoRo37Wxu2jLMFMtg3273DgY/iyNcSeCvVPhHo9wS8CnMEmmCsz2QQiJ++A5sfz0D5Vo21UWxZcuYDb597OC3+9QL8m/fjmgm8IDyjfkVdiwmL4+OyPC09Q0YGB1XUggG3bjoMhuitObHgsy69dzjmfnMNX675i3cGcDsifnv0p4zqMq7zMVPQ2WAN9dcFX3Pe/+3jgtwfI8GSweJcZttzCYvZ5sxnTNquBoCy/bUCA6d2bvT9VdfByWThc0OJS8wDIPApJm8x5y5MGWBBQ38z802AQBDeFwHpFfmWVqOh6S5f7TSellQ/Ad92h072mMSYw6wZySJyZkSFtv2mI2bgSrvg/SLu86O+t5P01IMDMijxxoqnC7N0L69aZBvwjR0xDip+fSRcTY2bdyr7JIOLLqa1O9T53OVws2pU3GHnRzpxOmpmezDzpRY5VaKg5bKal5YyoLCJZqtsgO2VVCetxz6B7eGr+U96OqJmeTByWAzvXHSELizfPeLNU31tAyh4TaFzY7BfZEv81nfJzz/Yl5erHH02QZ3ECDnXzPrdtu9Bg5OxtxYGDE6JPKK9sivDee6bDRZcuMHp08ekzMuCee0yd6PTTYWwJ+6xdfsLlfLfhOwAS0hK44ssriAk17Rw7E3dyJP0IAG7bzeUnXE6Xdmb0ejDNlatWwc6dsGuXaVLJzDR1tMBAc/O9Wl5X/nO36SwR2tKM/p4/c4WNzO7wh/Z3FOxoUdRI7inxBV+rCP4R4N/ZBKcWpfGZcGAB7P3VzA6dtNmcb1zBpt3Dtk0gc/ohsFwweFaZslM3uC5/XfUXV391NW8te8sbiOxyuJhz4RxOblFwJl3Lsrii2xUMaTaEXq/14mDKQd4f+z7ndz4/Tzo/px9j241l+pLpePAwf8d8Br89uMD3AXSL6UaTiCYAXNL1EuoF1WP0B6OxsQnzD8PGJjEtEYfl4JsLvmFEqxFlWl+ARuGNmNxvMs/ML2Q2AczMy99e+G2h7xcZ2BLcCHo8ax6ZySaQL2kTHFxiBhHMHiTXGWhmyU5cDdhmAN0uDxX8vnzb7dLN3XE6MggO8WOw75+zUC+c/gJxEXHc/uPtAMRFxLHx0EYA6gbVZdFVi2hRp4U3/YC4Afzv0v8xbOYwMjwZOHDQPba7t932mh7X8PKol/Ms45XRr9ClYReu/+56bGy2J2z3BiJf1f0qXhn1is/gEJHy8ueVfzL07aHM22763IxsNZJftv7iHTjh9dGvc0a7nIH/33wTNm3K+Xzr1vD882YwD6cT5s0zncDdbmrWPXl3Ovx9W8nSelJh7bOQsgtzvGoI/d81gy3YHnO+DW5sjntzehTzZcfO4zF1KYCrrzazxhV3WKm2nWOlRDZvhi+/NM8vv9wEIkPB4PPszuK9e1dSxmrSMaGaCXQF8v2F3zNkxhBvPWJEyxGs2rfKO/NZ14ZdeXX0q1WYy+NTvyb9uL739Uz7ywTROi0nPWN7smLvCpIzzAgcJ8adyKS+k7j4Cxg/Hr77DkaNMpOEZc/QCeZ4bFk5x+DUVHN9WdmaRDThg/EfFJ8QCPIL4uGTH+acjufw9J9Pc06ncxjVxvfgvA6Hg5dHvczAuIFcNOsiUjNzriM/HPch53Y6t1zyL9WEbZtrb8tZdLvwkTVqE5ZyN3WqOYbadk4gssORN6A0u94zYEDV5PG4teE1OJjVDyK0JZz6l5nQIHeboSvM+/SsELhtf9Z9BMvB79t+zxOM/OvWX3FYDty2m7pBdenXuPSTQ2zZYoKNstthZ86ECy/MO0BWVJRpc1640Ax8efXVJuD3iSfMvfamTaFNGwgKyglmSk7OuRX33XclD8o6csQER3s8pq592mlFX1+5XCatv78J3soO4CqJa3tdy9aErTz+x+MA1Auqx4lNT2T2mtkAtKnXhiVXL4HdB0v+pQKvvFJ0BFv+/m6VEWVbSfe/XQ4XX57/JY/Ne4y7fr6LQ6mHvO89fsrj3D7AtIF6ssa4zH9srfHK0Mf9QWD83j28MzeGq64y97N69zb3v0JDzeC5aWmQkmIGLTp0CN5+u5LWpzSqKJ6off32tK/fvviEJdHiEmhwImx8HVY8CEtvgai+ULcn+EeamBfbDe7krPtbTujxAiydBN/3hhMeg7izwS/rPBcSB6NWm8FtU+Ih/TDEfw9bP4Bld4J/HWh6PmCZgVODG5k6b+pe0/6Xshsyj0BoiwqfHKlFC9Mem19mptn+HA5zHipre99tt5l7sx9+aIKfr70WOnaEzp3Ndh4UZAawzN7OU1Lgo49Kt4yQELjxRvMAE2y8bZs5Z6elmX0rPNycxzt3zhmQpLpQMHI5O/fcczlw4AAPPPAA8fHxdOrUiW+//ZamTZsCEB8fz7Zt27zpmzdvzrfffsvkyZN58cUXiY2N5fnnn2fcuJwgmP79+/Phhx9yzz33cO+999KyZUs++ugj+mQPm16C5YpI5UhPT+fRRx8FzOAD/sVcrZU2fWUto0Yp082dHsAkM/vA4RVwdCvs/tlUrjwZplHRFQIhTSGqOva+Oj74Of2YOmIqU0dU4gy0VaE63mDUKMwEugL5/NzPueKLK5i53PS4/P6i7xnecngV50xKYsqQKaS503j8j8e9N5c/PvvjnEDkskpLM3dJC3OsgaZVse+5QorvuFobWQ4z+1Hra2H756bRZM1U87p/HfALBSwTzJ1+GA4HVftzvWVBw4bmIVJWjcMb07ZeW9YeWIvb42bBjgV53v9r51/e2QL9HH4MblrKHs0iRfDzM2OCjBkDjzxiZqu5+GLTuOpyFTwM55/VpNapKcGpUryaMoBRJa2H0+Hk/bHvc8aHZ2Bj47Ac3Df4Pp6Z/wwJaQkA3Df4PhqHNy7LWuRY90LxgcjZjnW2LynS1KnmJmLuTjitW5vNbflys+kBODPDaR7ZnM2HN+O23fy7798C37Vq3yrcWeXasm5LQvxDKmMVpJZITjadWXLP/FCUpUtztt877jDbeElumI9uO9o78wbAe8vf884Y68513LKwOL316Xk+GxlZws6K1a0ecnCJ6fQQO9L3tXvaft+BxQ5/MyNxaVTgSO5l4nBC/QHmkV/2QBzl1J7hcrh4Y8wbNAxpyGN/PAbAgisX5Ols6UuLOi04cPuBItNc3/t670xiRbn8hLyDxI1sM5KXR77MNd9c4z3PA7w66tVjCkTO9vTwp9l8aDOz1pgg7sl9JvP2P297O6zNuWgO0aHRx7wcXMFQt4d5FObv20zdI+5scAYUfD/fdh4elIjHdpKcbGaXCQ4uXSe6W/vfypaELby06CVvILK/0585F87JE4icbXCzwbw/7n3O/uRsPHi8gcgjW49k2um+Z4Kb2HsiCWkJ3P3z3d7yO7fjubw88uWyByJX1gCxctxzOVx8c+E39HqtF+sOrOObDd9433vs5Me4svuV3r8zM+HRR83h1LZh8GAz60ZISM65uW9fE5CcHfxaY2z7BNL25vztCjUDfba4wgx6sepRWPVwzvub3gJscy/9xM+gXla0Z3Ynfqvyon0PHjQd5sHMguvxlG+wcXXt51Gb+4a8/nrOjEvZgchFqY0zWNVE/eP68+H4Dxn3seln+e++f72ByM0im/H75b9XZfaKVs3rLc+PeJ59R/fx0aqPcNtuGoU1YuHOhQB0atCJuRfPBaBePTP7/G+/wccfmzb9w4dNQHK9eqaTdmZmTqdqPz+T/njQNbor74x9p0RpL+xyIQ1DGzJs5jAAfr7kZ4Y2H1qR2ZOqcHBxTsBibo4A0y6Ru71YbcJSjjIz4d13zf9nnmmCQYuiQXZKaUPWwCUOPxj8lQnIyj9TZa52ipb+0CK8MZsSd+CxPTzw6wN8tCor+siGxfGLve2wo9uMxlna9kfMgFjZ9zxuvz3vrNjZstt5evY0/7dpY9JmO3rUtEknJ5vucIGBpn0o+1Ean30GCVlNb//3fyXrLn0swZyPnvwo+5L38ebfb3Ig5YA3ELl+cH1+vexXQv1DIS60Wtelqp2iZoD19Tv5uiFRnr9tJd//tiyLO0+8k3rB9Zjw9QTADESXu/1n/Hh4+GGzirfeamYbL24W8czMGnJtWYY+7l2Bp7Oa4FNSzG2hpCRzzElJMbOdBwebY1SbNuWfZckltDl0fdg83Gkm7iX9kAlAzkw27XGBDSGkuYl7CW0BTcbC1vdh8zvw938hNM4MyOEKNffOMpMg47C5/1a3F5z2txmE8K9r4e/bIWY4RA00A+u6QsGdaj5zeAUkb4MBJRsIqiK4XOW3X7ZsCXffbR62bWYyzr2d+/ub7TwoCJo0OfblhYSY2ZGPFzXh8FftXHfddVx33XU+33vbx7AOgwcPZunSpUV+5/jx4xk/fnyZlysiImXgHwENBgIDqzonUlFqc1BudQySrmQuh4u3z3ybM9udSfPI5nSL6Vb8h8pbbd4Gj4FlWTx68qMs3rWYnzb/xAunvcD4DvnqyqX9bVevLtiIVZzUVPP9pSkP7XvVS2B9aD3BPMC0GmQcNg0ktm06d/rXNa3oA7epEVtqhYFNBrL2wFpsbH7Y+AN1Hq/jfS8pPYlMTyYAHep3UICOlLvTT4dvv4VJk+CSS8wsQ+ecY25QdOpkGnAzM81MJ0uWmNngn3iiqnNdBWpKcKrULvv3F73N+lKW+jYmEO/GPjfy3MLn8Ngeluxa4g1wGdR0EP83+P9Kl4/8bBs2zSgYjOwKMaPlV9asmcKePWb0/tzxdi+/DFddZToHZGaa88Tdd5v3+zTqw7aEbbhtd4GZkW3bZsPBDYCZ8adPoz6IlKcuXWDWLBNkvG8f1K1bdMfAg7kmdmjWrOSdCANdgbSNasua/WsAE4Ds9jF4QscGHfF3liE45XishwREgSOwYEByZhLsmgPRJ5vOhtlC4sxI7mn7c0Z+h0oZyb1cVcCgapZl8egpj3Jxl4uJDIokNiy2XL63Y4OOtIhswabDmwpNE+AM4LqeBe+DT+g5gS2Ht3gDpO858Z48nciO1fRR0/nf5v9xOO0w0xZN8w6MOKHHBE5pUYppXY6VJ8387wzKmWE0t3zb+YUD3uORL+9id0IsEyZYvPde6TrPWZbF8yOeZ3vCdr5a9xUAn5/zOb0a9Sr08+M7jOfRkx/lzp/uBKBzg858OP7DIjvd3jnwTtbsX8PM5TNpGNKQmWfNLFMn3TzU/iolFB4QzrcXfEvX6V29MyKf1+k874w42b78MmeAkPr1TSByaGjec7PLZfavRx6prNxXko2vAQ7AY44/Q76FqH45HfMbjckbjJx9rGo1AaL6V+kAn7k71x85Uv7ByFK92Da8+qrpLz92rKlrS+0xtv1Yrul5DdMXT2dbojlgOy0nn579KWEBYcV8uopV43qLZVlMHzWd37b+RnxSPJ+v+RwwA9R8NP4jAlwBudKawToGZ41f6/HArl3mkT0jVVCQubatyfvnKS1OIenOJADdP6upNr0FlssEHgMEN4Yez0OTs0z/giW3wIaXqjaPUiP98ENOW+HVV9eg4LfqIGU3HMqK32hzI4S3Ldjm4kPTsGg2Je4A4FDqoQKDvGdrU69sEXhffGHqti1awAMPFH1pVdh1TkiIeZSHXbvMNhccXDlVF8uyePH0F/ln9z8siV/iff2L877IOzBgNa5LVTtVNANsdXN1j6vpGdMTLOge0z3Pe3Fx8M03Zibv55+H3bthypScQNrMzKyuhE5Tv83IMH1bzjij8tejugkKgu7di08nlcAZAPV6Fp8uOBba32oeABlJcHSzmbjHdoPlB0ExZubj7PNin9eh18uQsBqOrDOPhBXgSTfp/cIgogPEnVMjJ/mzLJ1y8lN1VERERGo3NUrUag7Lwdj2Y6s2E9oGy8SyLH685MeiE5Xmt42KMp1jSxMgERhoPic1h2WZmZF90b4qtUSreq28z21sDqce9pnumGeUFCnE8OGwahX8/jt8/72ZJeHJJ03QTrbgYOjcGYYNK/ksgSLHrZoygFEl17fvH3I/7614j/3J+/l63deA6Yh6TDPtZTu4BFJ25H2t3S3Q9UHTQX/jW7DwimNbhpTI55/n/fuxx3ICkcF0jrnrLrP7/PIL9Ijtwcf/fgxAQloCB5IPUC+4HgB7j+71BqHY2MXO9ClSWrfeama02L7dzF4ye3bRHQdzdxTbswdiY0te57mx941c923Rgxff3Pfmkn1ZfpU4uESJ1elmgoZ3fQPdnoT8h3lfwcWbZ8KeH2Hhf+DUvyCwQd4ZT0LicmYv8rhLP4NyDdehQYdy/87nTnuO0R+MBsDf4c+Ms2Zw1093sfnwZgDuOvEuHIVE0j588sPsTtqNw3LwwNAHyjVfDUIa8PKolzn/s/O9gcixYbE8OezJcl1OsUKamg6yB/4qODsPFNjOI9MP8/E7hxg6thEffWSum6ZONdXG7I5zlmUCRfz9zf8//ggjck0o7XQ4+XD8h1zz9TX0iu3FyDYji83mHQPu4Jt137B873K+u/A7M1NNESzLYsaZM3h+xPME+QXh5/QrMr1IeWtZtyVfnPcFp8w0gwu8OebNAtcLP/9sZnHMyIAHH8w7I3JuDkfOzFU1wtGtsPfXnL/7vWMCjHOfEwvMFpb1XpcHq7zDYXAwDBgACxbACy/AFbpEK1/b8g3eunp1wTT5X6vAtork5JzsnHaa2V/9dEqpVZ4Z/gy/bvmV1fvNdvfU8Kd0XV8OIgMjeX/c+wydkTPD79PDn6ZD/aKvBxwOaNzYPGobBSHXYLYHtn2SE4jsCoWhcyGspfnbGQgtL1cwslSIb74xbYh16pj7qLovWo52fZPzvPnFFGxYBI5uM4FXuVzX+Wz+t3NxsV9/Y58bS52l+HhYvtw8v/TSY5thuLz4+5u2pPT0yltmoCuQ2efNpslUM9Xk9JHT6dfkOBooUopWhfe/u8cWHjXbty9s2gSPP24GvPrgAzOgTt++0LSpOf4eOQLLlpnB89u2VTCy1BB+oRDZufh0Dj+o08U8pNZTMLKIiIiIiEhNCfIQETlG1/S8xjuLUVGu6KYefFJxLAsGDTKPbNk3OF0u3WRXvaUWqgmDolTydhsRGMGzpz7LRbMuwoMHgJv73VxsZ8kSiZ9jOtlnzzTa8j/Q/alcC+947MuQEvngg5znZ5wBt9/uO91TT5nggx4xPfDYHu/rX6/7ms4NzY3VpfFLva97bA89YtRpWcpXcDC8954J9Pv+e9N55bnnTJAMmOBAyAlOjow0h8H9+00A4XvvlXxZE3pM4J7/3cPBFDNlysReE/HYHl5e/DIA9YPrc2nXS8u2ItVxMLcTHoWdX8OR9bBmqhnJPX8AVO7gYtsNsafBz6fAoWXwTUfofC+0uLzgAGW2x8yOsmkGNLy96KCbSgy4qYlGtRlFr9heLN61mHRPOikZKd5A5IiACG7rf1uhn3VYDt46860Ky9u5Hc/lg5Uf8OXaLwF4+4y3K3+WvY53wa+jYe9vEP89NDwp74zekHc7BwY0Nx3jrr0WPvrIzKrTuzcMHGhm9HC5TDVswQL44w9z3MkdjAwQ7BfMO2e9U+JsWpbF71f8XqpVsyyLyKDIUn1GxKscAiJPbnEyafeYGX39nf4FPj5vnglsjIkxdcqiZiCr1sGPxf1W+f9O/wrTEd+Guj0gbnzxy7DdENUXAnxMe3l0mxkwIcFHGVWQF1+Ebt1MR/777jPB5EUNalfcDPKSZds20+O6uPrgRRfl/Tsw0LQLVED9KCkp53lYmNoOa6MgvyA+O+czOrzUgVD/UG7qc1NVZ6nGGNJsCOd0OIeP//2YAGcAE3tNrOosiVSNfX+auky2/u9CWKu8g7OUYDZVkbLYv9/UVdu1q2b1nGo2QE2Z7PgCcEJQNNTpWvD9o9vgq7bgyVv3HRvbHqflxJ11n8hpOXFYDty223sPomlE02IHafNlzpyc52PGVI8yb9/eXEu53Wbg14EDK2d27sbhjVl93Wrik+IZ0mxIxS9QKlc1vf/doAE8/bQZAHnVKli82LSx7txp2ocCA83syf/9L/TqVdW5FRGpOgpGFhERERERgdI3cm3bBktzOqwflw3rIiL5RAZGUi+oHgdSDhSaxsLizLZnVl6mRDDxJAEBVZ2LaqSa3pwTKVIlb7cXdL6Au3++m60JWwH4v8H/Vz5fvPOrnEDk8LbQ8/m87/uarVDKXUqKCZyybfP3vfcWHljgdpuZaLtEn5Dn9cu+uKzQ7+/a0EfHI5H8ShnUM6BJFCtWxHH99WZGk0GDTDPBkCHm8GhZZoyGX36B6GgTNHPjjfDhhzBxogkiLKqTV3YAjcPh4MbeN/Lgbw8CYNs2GZ4MnJYTG5tJfScVOsNssarjoCgRHaDtDbD2eVh2B2QmQad7TSdg286ZwdGTYYI30xNNkNSpC2H107DqIVh6C/z9X3Ncj2hv0qUdNLPQph+CjA4w6I2ig24qMeCmpprcdzIXfH4BANOXTPe+fm3PawnyC6qqbGFZFq+MeoUv135JlwZdGNZyWOVnInYk1B8I++fD/Eth8FcmOBAKdnj3ZHrrIx06wK+/moDjuXPN8+eeg6NHsz5qQfPmcNJJJhA5e8ZkkeNCOQZE+gpCBjPb6sqV5vnZZx/Hgaol+a3y/04TnDDICWRC+9tzzqPFiR6e5zgEFNqBn/3AX79Dg6y/y3mgj65d4aGH4O674eGHTefhxx83x0Yw1wmWZcr1wAEzcMN115X462uv/ftLNzBNttRU89kKqBuF5RojJDHRlO1xu79KmbWv3x77Pruqs1HxSju4RDlcj80cO5PJ/SbTum5rLFUWpbba+SVYLjMzcr3e0FjTIErlSUsz7X7V6j5pNRygpkwS1wJuiD7Fd6NI2v6C1zGAIzORka1H8tW6rwBoU68NI1uP5NWlr5KYlgiYQeDLYsEC0wZcrx6ccEKZvqLcnXaaCUheu9bci/m9BOPQZWSUz4Bd7eq3o139dsf+RSKl5Odn9sHqsh+KiFQ36hUjIiIiIiJSWjWlYV1ExIfhLYfzwUoz1WCQK4jmkc2JT4rnUOohADo16FT24AUREZFKYlkWM8+aycj3R3LHwDvKNAJ9AemH4MCinL+7PgJWdZ7+rOZau9Z0wALo2RN6FDGRsZ8fnHgiOBx18sxWUBiXw0V4YHg55lZqpLIE9QQG0mztWr7+Oo7ly+GHH8zj229NsJNtQ1CQ2abHj4crr4QXXoCNG2HYMHj5ZbjkkpzgCssy+4Ftm0D8Dz6ACy80i7q468VM+XUKAF+t+wq37fZu+xd1yZev0qqOg6J0fwYcgbD6CVj5MGx6y3QMjh0JwY3NIBKHV5jOw8m7YPg8E1DV8b8mkHnfH7DnZ9j9sznOezLAFWJmn40+GXY3gtQxpctTBQbc1FTjOowjak4U+5P3s2TXEsAMhnVtr2urOGcQHRpdtcEtlgUDPoCfT4XENfBDf2h1NTQ7H6L65wQkZybDrm/Mttz7Ze/H+/Y1j3vvzUqWaR4BAcdB8HEVBNzIcaISAiIXLzbnXYB+/XIGwjnulOW3apK14v51oMlZJQtEBtOJ38o3QpCvDvz7gVuBjEmFf1c53F+56y7o1Amuugq+/hq++w4aNzaDwURGmp9l6VJYssTMoqxg5BKIijJlUdptKjDQfLYCBAWZ2av27jWD/lxxRYUsRqTqlfE69FjvTfs7/enbuG+ZPy9SIxz62wQiA7S5oeQDtYiUg/Bw0/Z36FBV5ySXajhATZlkJpn/A+ub9kOr5GE1/x34X75c9yUACWkJ3NL/Fp6a/xRgzp039L4hJ3Ep2jYStzbD46lDq1YV3GBTijw5gPtvaMI519Vn3jxz3TRtmmmb9jV4ptsNW7dCq1YVk3URERGpegpGFhERERERKa2a0rAuIuLD/w3+P28wso3N8muX0+f1PiyJN53B7xl0T1VmT0REpMRObHoiiXcmlt8XHloGZEUg+NeFRqM1E3IVyd0v5vzzix9lPztwJCY0hh1HdhT53Y3CGpVDDqXGK0u7QK42gS5doEsXuPVW81b2Npo/KPCPP2DUKPjrL7j0UnjgATMz45AhpiPioUNmttNPP4X69XOCkVvUaUG/xv2Yv2M+2xO3e79vUNNBxEVUcptEZQQSWg7o9hg0HgMrHzCBmOumwfpXciWyTcfhBoPzftYVAjHDzaMwR5aWLj9SJtkdNe/75T5v8PyZ7c6s/G22ugpubGb0XnYHrH/ZPDZMB1cYBDYwnWaTd5r/IzsX+VUuV9EzrVcbVRRwI8eJSgiInD/fDADi8cCgQcfJfuNLaX8rC8iuEjcaXaoO+QQ3KtkoB0eAjJJ/LVDm+ytjxsDQofDllyYg+dtvYcaMnPddLlO+F1xgylpjMBYjLs4cZ3PX7wDi4+HwYfM8MhJiYvK+X4GDRVgWTJgAjzxiynn/fjOTXLUfcEOktI7xOlREjkHCv+Z/ZzDEjVcgslSqNm3M/8uWwb59pg1QClFcO2T+19KzzquWE++9n9wCoswAiPkHVwptQZ+oPtQPrs++5H3sOrKLWatnma/CYkSrEYT4h+TkqRRtG0f5Ag9jCAkpYj2PVRnaW8YFBHH9ZXuY9nYYL79stsdbboHRo8HfPyfdxo3w9tvw44/mmlpERERqpuO1qVxEpFpyOBy0bt3a+7y801fWMkRERKQY1XDkdxGR8tK2Xltiw2LZdWQXqZmpLN+znOV7lgPm5tkpLU6p4hyKiIhUkSMbc57HnV1wxi+pNKtXm6CBzEw477yiA5EhpxN6pwadig1G7tKwSznlUmq0srQLFNEmUFigRFQUzJsHTz1lZpvYuNE8f+KJnGAZyzKzTXTvnvezl59wOfN3zC/wWqWq7EDC+v1h6BzISILdc+HAX5CRaIKoAuqZ2Rrr9Sn995ZzeUvhru5xNff9cp/375v63FSFuamG/EKh14vQ6V4z0/e2T2H/AlNHcTjBL9LMCN7sAjPKwfEehaWAGylKJQRErl9vzrUNG0Js7DHnuOoU91vl/53St8OmM83zOieAnQGWf97PHt0GCT469jsCCr5WWAf+ShQWZgZtufBCcw2xfz8kJZnTdd26EBxcuu+rrv08vJ9JScHxzz9mCj0o/8Fg4uKq3XH2yivhoYfM6W/SJHj33aLTu905P4+IiEiRMlMgJd48jx0BzsCqzY/UOuefD/fea56/8w7ceGPx7eEVrjr2mSpJOyTkbYt8BmhIVvuhj8phSByMXgtp+81xIP0whLaA+v1wAGd3OJuXF7+Mjc3stbOxsLCxGd9+fM53lLJtI5BULNykplZgZbUM7S2OtBSev349Lbt257bbzOCZ48eba62OHSEgAPbsgTVrzL2bzkWPkyciIiLHOQUji4iUI5fLxQUXXFBh6StrGSIiIlKMajjyu4hIebEsi1GtR/HG32/gtt3MWjOLDI+ZqqR7THfqBtWt4hyKiIhUkaRNYPmZzviNRmUF+VR1pmqnf/81gZj165csMCS77/7Q5kOZs3FOkWlPan5SOeRQarzSBvVAmdsEXC7473/hjjtg8WL47DPYsgWSkyEkxMyOMn48dOqU93PndDyHid9O9NblA52BjGs/rtTLPyZVFUjoFwpNzjKP8lCJ5V3bRYdGM6DxAP7Y8QdgZvMWH4KiodXV5iFSm1VwQGRysqlzNmtWYYsom9LO9gXmvJR/5JLCbN8Cm7Ke1+lmroFyO7oNvmrrO7jYk1bwtdwd+MF04o/bAAG3Q1p6yfIE5Ra44HJBdPSxfkf17Ofhcrm4YODAWjmrfNOmMG4czJoF771nqmfPP2+CjnMH62Rmmm1g3jwYPLjKsitSNhokSaRqHFmPd8bU6GHgydDMyFKpWraE3r1Nu+ALL8DVV5tBVQobr6ZSxiarjn2mytIOeRhoAOz7E6xCftCQOPPw4az2Z/HS4pcAWLRzETY2TsvJqDajSpePXEJJwomHXbsqMBi5jHUKq34UkybBmDGmzj1zphnEa8GCnGT+/ub9a68t91yLiIhINaJgZBERERERkbKohiO/i4iUl1NbncqrS1/FwuKXLb8AZlbkY7lxJiIictxL2gS4weEPDU82MxBKlVixwgSGtGtXus+Naz+OO368w/t3vaB62NgcTDnofW1s+7HllU2p6Sq5XcCyoFcv8yiJiMAIzmp3Fh//+zEA4zqMIywgrAJzWI5yB1CVNMCqostC7UCV5pb+t/DHx39wYecLsY73mX3l2CjgRqpYSoqpc5Z21twKVZbZvqB0waaHloPlAjsT6nQtGMmQtr/wWY6PboeQZgU78ufvwN8IWHeWBvqoCLV4Vvk33oCVK01AxIsvwk8/wfXXw2WXmUF83G7z2tSpsG8fLFlS1TkWKSUNkiRSNRLX5DyP6Og7EPnoNkjw0X4hUk7+8x8zE+3WrTB2LHzzjQlGduWLAsnMNK9XSnNKTWgrWwa0Bg7/Aym7IKgEI5/mMrjpYML9w0lMT+RQ6iHva3WC6uQkKmXbRkdW4cHBhg2wfTs0aVKqLJXMMdYpWrQws3Xfcw+sW2dmRE5Ly5klOew4aYIWERGRslMwsoiIiIiIiIiI5HFy85NxWA48toeVe1cCYGNzastTqzhnIiIiVShxDdgeqNMZXEFVnZtaKzMTNmXN1Na+vQkQKWwWiPxa1m1Jo7BG7DyyE4CPz/6YTE8mp75r6jhNI5oSF3Gcd6ASyeXSEy71BiNf2vXSys9AWQIJoWAAVXHv14DZ/CTHWe3Pwr7PrupsSHWggBupYm63+d9Z0WMQFTfTcf5BOkp7XoXSBZum7DD/BzYE/zpFp81v91yoP6DwWcVyqwnBC1KthIfDr7/CsGFmAKu1a00w8vXXQ0AApKebmQIBevas2ryKlJmOnSKVL3FtzkAt4e0Lvn90G3zVtuBgLSnxlZM/qRWuuAI+/NDUdX78EU48ER56yNR7clu8GN5+G6ZPr5JsVq2ytEMuAc7Ner7tM2h9TalmPvdz+nFW+7OY8c8M72tndzw7b6JStm2cvjmQW8ebi9AvvoAJE8CvIiZjL4c6hWWZsbLati2nPImIiMhxQ8HIIiLlKD09naeeegqAW2+9FX9//3JNX1nLEBERERGR2i0iMII+jfowf8d87yi+Yf5h9GpUwmnYREREaqKjm83/oS2rNh+13ObNJiAZTDByZiaUpsmzT+M+zF4zG9u2WXdgHZmeTCwsLMuiT+M+FZNpkSoyvOVw7/OTmp9U+RkobSDh6tXFByL7UkNm8xMRHxRwI1UoKMgMepOSUoELKclMx2U5Nx4Ld6qJ2AxpVvrP7p4LXR8q9yxVN9W1n0d6ejpPffst3HUXtz75JP4ZGcV+pqZp0ADmz4cZM+CZZ2DDBjNjoMdj/s/IMDO1VfZuJSIix7HEtYANfuEQGFXw/bT9BQORAdIPV3TOpBZxOuGjj0wQ8vr1Zpbk4cOhSxfo2tVct6xebV7v1q2qc1tFimuHhIJtkbYNm0dDejysehhaXAqWs/DBlTwZBYKVz2qXNxj5jLZn+M5bCds22nWDRo1g504TgH799SX6mIiIiEilUjCyiEg5yyjlDZ3Spq+sZYiIiIiISO12euvTmb9jvvfvU1ueisuhpiQREaml0g9DRqJ5HtrCZ6cTjm6DhNUFPirl6+DBnOcdO5Z+VoCeMT35Ys0XOB1ObzCy0+HEY3voGaPpsaRmcTlcbLrRTCXudFT0tI6FUCChiIgcp4KCzExP+fuyl6v9+8s203FpBQaamcJKwp0GeMAZWMqFOODgYkjdDwF1i54d2eOGqqqblJPq2s8jw+0u3WhNULrt4zgQHAzXXgvXXGNmDvzrLxN/EhwMLVrA+PEQElLVuRQRkePGkTVguyFcU39K1YqKgt9+gwsvhLlzzUAry5ebRzbn8V3FPnZlaYd0XAxrnobUPfDnhTDoC9/XK54Mc48ooF6el3MPBtk0oikxYTEcC8uCM86AV1+FP/6Ad9+F884z5e1LRkYFzZwsIiIiUgT1IBURERERERERkQJGtBrBvf+7N8/fIiIitVbSppznvmZGProNvmrrexaMlPiKy1ctlJaW87xJE9M5pzS6x3THbbtx227WHlhLhjuDTE+m9z2RmqZ5neZVnYWSi4oywTClDcqqYQE0IiJSPURHm7rm2rVw9Gg1C158911o3z7n76Jm+wJznixpp3xPGmCDM6CUmfKADfxzJ/R5reikx3kg8nFh3ry8EQvZ24iv7SMtzQTGZ0fer843yFb+v0uzPVUhy4Jhw8xDRESkzDKSzP9hbao2HyJA/frwww+wdCk88gh8/rmZ3DfbySfDgw9WXf6OSx3vgk1vmVnOd34Nv5wOPV+A0FYmANmyzMC0u76Dja/D4C/zfDzILwiX5SLTzmR0m9HlkqWLLoKXXjLPr70WevWCVq0KBptnZkJCgppFRUREpPIpGFlERERERERERArIH4xzaqtTqygnIiIi1UDuYOSw1gVnRU7b7zsQGcysylJu0tNzngeUNj4C6BHbw/v8373/egORQcHIIlUuLs5EfOWfgrI8A6xERERKqE8f07kbYMECGDoUHEVM9lup2reH7hVVd81aSY/b99sBUeAILHj9k/3apjeh6fnQYBA4fHRL82TC7h8g9vTyzbbkdcIJJZsheds2aNu26MFgLroo79+BgabOpvqXiIjUBp6sxkj/OmaGZEuDqkjV694dPv3UDJq0fz94PFCvHoSHV3XOjkP+EdD3bfh1pPk7/nv4ugM0uwDC25nBmvb8Ant/hTrdfH7F1T2u5qXFL3FB5wvKJUv9+sEll8B770FSEvTsCXffDbfckjMLsscDb7wBH30EP/9cLosVERERKTEFI4uIiIiIiIiISAEOy0HfRn1ZsHMBAI3DG1dxjkRERKpQ2n7AAmwTjCxVJncwsp9f4ekKExUcRUxoDPFJ8WxN2Op9vUl4E+oE1SmHHIrIMYmLU2CLiEh1tG1b3sEiasjMqUXp2zfn+Z9/wqBBFRCMHBVlAjuLCgTNLzCwYqe+cgYCjqwZkn0IiYPRa801Ukq8GXwptAXs+w2W3Qm2B/44F/q8Do3PMH9bDhPc7HDClndhw2sKRq4u9u8v3fYHJv3+/cf9Pi4iIlIi2XUiR4CZgtaq2uyI5BYSYh5yjBqdDr1egkUTARvsTNj8TsF0hQxG8OLIF3lx5IvlmqWnn4bvvzfV7qQkuPNOePVVE4judMLy5bBmDXTzHR8tIiIiUqEUjCwiIiIiIiIiIj4NaTaEBTsXEBMaU3xiERGRmsyTjrenWVDDKs1KbWfbOc+tMnb+692oN1+s/QIbO89rIiIiIuJDLZ05NSYGYmNh1y747ju4994KWEhcnPmdcgd6A8THw+HDEBlpMpJbRQd6OwNMRTvjSOFpQuLMI7e63WH9dEjebgKVfzsTGp8JbSdBYH1I3gn/PgZ7fi50RjERERGRaseTYf53+EOutsQi7QdWboZDS83f+Qfu8fVaDRjMR+S41vpaCIyBv67ONTitx7xnuUyAcnj7SstOVBT89BMMGQKHDoHbDZs3m0duTk3WLiIiIlVAwcgiIiIiIiIiIuLTJV0v4fW/X+eBoQ9UdVZERESqlifDdMi3/Aod/V4qR0BAzvPcsySXRs/Ynnyx9osCr4mIiIiID7V45tQTT4RPP4X5882jVy9wFdLTyu0uY0fwuLjq9Tu5QgAHHFkLtrvk1z/OABjwIfw4yMyGjA07ZptHfrqmEhERkeNG9miIhQQiB0SBIxA8WfXl/cCtQMa9QBGj2dTAwXxEjntNzoToU2DTW7DrO0j81wxEEDXAvNdoTKVmp2NHWLAALrsM5s0z16KZmea97OctWlRqlkREREQABSOLiJQry7Jo2rSp93l5p6+sZYiIiIiIiAC0r9+efbftq+psiIiIVL3smZEd/lWdk1rPP1cRpKWV7Tt6xPQo0WsiIiIiUrsNGACffGKe33IL/Pln4WlrzIxU4e3MrF/uDEjaAmEtS/7ZqD4w+Gv4daQJSLbdBdNYruP+uqq69vMoU9+QqCgT/FSaAQcCA83nREREagNnVr3Fk0ZOYHIuIXEweq2ZSTUlHpb+nRWIXEo1ZDAfkeOeXyi0vcE8qoGWLeG33+Cbb2DWLFi4EDwe6N4dxoyBceOqOociIiJSGykYWUSkHPn5+XHZZZdVWPrKWoaIiIiIiIiIiIjk4snABCP7VXVOar3cMyPv2AFt25pJq0uje0z3Er0mIiIiIrXbeefBbbeZQXDmz4fHHoP//td32m+/hdNPr9z8VYjILnhn/ju4BEKagaMUkdYxw2DE37DwSjiw0MyCbDnA4wY80HAI9J1R/vmuRNW1n0eZ+obExZlZGPfvz/t6fDwcPgyRkRATk/e9qCgFSomISO2RPYiKJ93UaXwJiTMPgD0xFDkjsohIKVkWjBplHiIiIiLVgYKRRUREREREREREREREjkVAFDgCweNjNqnQFpWfnxqsTp2c56tWwaBBeWdLLomGoQ1pENKAvUf3AhAbFku94HrlmEsRERERqQnq14err4aXXgK3G+680wyIM3Uq+GWNU+TxwMMPw+zZNSUYuXPO84QV0OQsoJTTPkd2hOHz4fA/sGsOpB+EwIYQOxLCyzCakFSsuDgFF4uIiBTGkTUyYsruwoORRUREREREahEFI4uIiIiIiIiIiIiIiBTF4QfYWTMk+xASB6PXQtp+SImH9MPm9dAWUL9fZeWyVmjRAlwuyMyE1avN87Lo06gPX637yvtcRERERMSXO+6A114zwcgAL74IH34Ip51m6qI//AC7dkG3blWbz3ITUA8CGkDaXtj3R9a1UBlYFtQ5wTxEREREjlf+dc3/iWuqNh8iIiIiIiLVhIKRRUTKUXp6Os899xwAN910E/7FTMlR2vSVtQwRERERERERERHJxeGPCUZOLzxNSJx5SIVyuaB5c1i/HtasAUcZJyTpEdPDG4zcI6ZHOeZQREREpIaJioLAQEhNLflnAgPN52qARo3gySfhhhtyXjtwAN59t+ryVOHqdoP472Hvr5CyC4JiqzpH1Up17eehviEiIiIVIKI9HFgIRzaA7ak+syNv2wb79+f8vXp13vfz/x0VBXFquxYRERERkWOnYGQRkXKWnJxcoekraxkiIiIiIiIiIiKSxeEHtg12OthusJxVnaNarXNn2LixYJ+60ugR28PncxERERHJJy4O1q7NG+wAEB8Phw9DZCTExOR9r4YFO0ycCH/9ZQKQbdt3mrIOklMtRXaF3T+DnQHrX4bOUwq/BvJklH325ONYde3nob4hIiIi5Sy8HeABTyYk74SQJkWnL8tAPlC6wXy2bYO2bYtexkUXFfz+tWtrVB1dRERERESqhoKRRUREREREREREREREiuLwBzzmecpuCG5Updmp7Tp0gC+/hL17YfduiI4uOr1tg2XlfS33bMjdY7pXQC5FREREapC4uFoduGBZ8MYbULcuPPccuFyQmWneczrB7YZTT63aPJarqD4mEBlg7QvQ/g5whRSsVAPg6zURERGRGiK8rZkRGSDhXwhuXEidKEtxA/nAsQ/ms39/6YOdU1PN52pxnV5ERERERMqHgpFFRERERERERERERESKElA/5/mR9QpGrmLt2+cEf3z4oZmpzq+Iydg8HhMkkltMWE6HvwYhDSoglyIiIiJSk/j5wbPPwhlnwKuvwty5pp45YABcdRWMHl3VOSxHsaeDKwwyj0BGAiyaAP1m4jPweO3z0P7mSs+iiIiISKUIa5vz/PByiD4JrCIaIqHWD+QjIiIiIiI1m6OqMyAiIiIiIiIiIiIiIlKthbbIeX5kPXjSqy4vQvv2Oc8//LDoQGQoGIicrVWdVrSt19b3myIiIiIiPgwdCh98YCaWO3gQvvoKxowpeoK8444zEJpdCFbWHBdb3odF15rnngzzAFgxBba8WyVZFBEREakUoc1z6kS7vgZHMQ2RIiIiIiIiNZxmRhYRERERERERERERESlK7mDkpI1orNeq1batCfawbVi4EJYtg86dfQcdZ2TAggVw4okF31t/4/oKz6uIiIiIyHGp9QTYMD3n7w2vwt5fodnFJghn60dwaCnU6VZ1eRQRERGpaA4XhDQ1bcL75kHaAQioV3h6T4YClkVEREREpEZTbxkREREREREREREREZGi+EeAX4R5nrTJdEKTKhMcDP37gyPrLtdDDxU++7GfH8yYUXl5ExERERGpEeqcANHDcmYCBEhcC8vvgWV3mEBkERERkdogohNgge2BjW+AJ7PwtApEFhERERGRGk7ByCIi5ciyLGJjY4mNjcWyrHJPX1nLEBERERERERERkXxCm5v/j2wsWXrbU3F5Ec4/38yMDPDZZ/Dss+Dx8ZP/97+wVHESIiIiIiKl1/NFsNS1LL/q2s9DfUNEREQqSFRvyD63rn+p8PqRx13ytmMREREREZHjlGXb2V01pLZLTEwkIiKChIQEwsPDqzo7IiIiIiIiIiIiIiLVx7zzYdvH4HDC+MPgCi46vSdTMyhXoN27ITY2JyDZ4YA33oDLLjN/u90wdSrcdht066aAZBERERGRMln9DPx9S+Hv1+kOpy2pvPyIiIiIVLaENfBN+5y/O/0fdLm/YDpPBiy8Cvq9XbH5WboUevQo/eeWLIHu3cs/PyIiIiIiUq1UdHyohq8UEREREREREREREREpTlgLsJymU9nuH02wcVEUiFyhoqNh2DBwOs3fHg9cfjl07AjjxkHbtiYQWUREREREjkG7ydDhzqw/fMy222h0pWZHREREpNJFtIOwNjl/r3wQtn8Otsf8nd1O/NcEOLy84vMTFQWBgaX7TGCg+ZyIiIiIiMgxUk8YERERERERERERERGR4oS2ADvDPN/5NTQaVXT6tAMQUK/i81WL3Xwz/PBD3tf+/dc8RERERESkHFgWnPAIRHSAFfdD0gbzelCsCVJuc13V5k9ERESkMjQ9H1Y9BLYbsOGP86H1NdD8Ukg/DP8+BrvnQp1uFZ+XuDhYuxb278/7enw8HD4MkZEQE5P3vago8zkREREREZFjZNm2bVd1JqR6qOhpuEVqg4yMDF588UUAJk6ciJ+fX7mmr6xliIiIiIiIiIiISD57foGfhprn/nVg7B5wFNLW5smELe9Bi0srLXu1kW2b2ZF/+QXc7sLT9ewJixZVWrZERERERGom2wNHNpognLCWhV8P1XDVtZ+H+oaIiIhUoKNb4YvmQDFd7ut0g9OWVkqWREREREREfKno+FBHuX+jiEgtZts2CQkJJCQkUJKxHkqbvrKWISIiIiIiIiIiIvnUOQHvbZX0Q7BjNngyfKd1uGDnV5WUsdrLsuD5501QclFp1AdfRERERKQcWA4Ibw0R7WptIDJU334e6hsiIiJSgUKaQtNzwXJWdU5ERERERESqlIKRRUREREREREREREREiuMfCfX6AJb5e9mdJhg5fydv2w3rp0PSpsrOYa3UoQO89Vbh7zsc8OSTlZcfERERERERERERqYFOeIxiu90rWFlERERERGo4BSOLiIiIiIiIiIiIiIiURONRZjYwgKSNsOg6M/VuNk8mHNkIS2+umvzVUpdcAq+8AoGB4HSCy2WCkMPD4aOPYMCAqs6hiIiIiIiIiIiIHNdCmkLHu6o6FyIiIiIiIlVKwcgiIiIiIiIiIiIiIiIlEXOamfk42+YZsPh6yEwyf++bB/8bAe6UqslfLXb11bB1K9x7L1xxBTzyiPl73LiqzpmIiIiIiIiIiIjUCJ3/D5qeT8Hu91kDVna+v7JzJCIiIiIiUqlcVZ0BERERERERERERERGR40KdEyC4CSRvz3lt3Yuw4TVwhUL6wSrLmkCDBnDffVWdCxEREREREREREamRLAf0fdu0Ea99Fjzp5vXAaOgxFRqdXpW5ExERERERqXAKRhYRERERERERERERESkJy4IWl8Oqh8D25LzuSVcgsoiIiIiIiIiIiEhN5/SHbo9D2xvhwEJwBED0yeAMrOqciYiIiIiIVDgFI4uIlCPLsqhfv773eXmnr6xliIiIiIiIiIiISCHaXA//PgF2atHpLGfl5EdEREREREQqTXXt56G+ISIiIpUsuBEEj63qXIiIiIiIiFQqy7Ztu6ozIdVDYmIiERERJCQkEB4eXtXZERERERERERERERGpnpbcDOueB9tdeJp6veHUhZWXJxERERERERERERERERERERGptSo6PtRR7t8oIiIiIiIiIiIiIiJSk3W4A/zCKfw2iwXNL63MHImIiIiIiIiIiIiIiIiIiIiIVBgFI4uIiIiIiIiIiIiIiJRGUEM48TPALvie5YSGQ6DVhMrOlYiIiIiIiIiIiIiIiIiIiIhIhXBVdQZERGqSjIwMXnvtNQCuuuoq/Pz8yjV9ZS1DREREREREREREitFwKPSbCYuuBXcy4AA7AxqeDP3fA4ezqnMoIiIiIiIi5ay69vNQ3xARERERERERERGpaApGFhEpR7Zts2/fPu/z8k5fWcsQERERERERERGREmh+IcQMg42vQ3oC1O8PjcaAZVV1zkRERERERKQCVNd+HuobIiIiIiIiIiIiIhVNwcgiIiIiIiIiIiIiIiJlFdgAOt5V1bkQEREREREREREREREREREREakwjqrOgIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIVE8KRhYREREREREREREREREREREREREREREREREREREREZ8UjCwiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIj4pGFlERERERERERERERERERERERERERERERERERERERHxyVXUGRERqEsuyiIiI8D4v7/SVtQwRERERERERERERERERERERyau69vNQ3xARERERERERERGpaJZt23ZVZ0Kqh8TERCIiIkhISCA8PLyqsyMiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIixajo+FBHuX+jiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIjUCApGFhERERERERERERERERERERERERERERERERERERERn1xVnQERkZokIyODt99+G4DLLrsMPz+/ck1fWcsQERERERERERERERERERERkbyqaz8P9Q0RERERERERERGRiqaZkcvRoUOHuPjii4mIiCAiIoKLL76Yw4cPF/kZ27aZMmUKsbGxBAUFMWTIEFatWpUnTVpaGjfccANRUVGEhIQwZswYduzY4X1/y5YtXHnllTRv3pygoCBatmzJfffdR3p6ekWspogUwbZtdu3axa5du7Btu9zTV9YyRERERERERERERERERERERCSv6trPQ31DREREREREREREpKIpGLkcXXDBBSxbtow5c+YwZ84cli1bxsUXX1zkZ5544gmeeeYZpk2bxqJFi4iOjmbYsGEcOXLEm2bSpEnMmjWLDz/8kHnz5pGUlMSoUaNwu90ArFmzBo/HwyuvvMKqVauYOnUq06dP56677qrQ9RURERERERERERERERERERERERERERERERERERGRms1V1RmoKVavXs2cOXNYsGABffr0AeC1116jX79+rF27lrZt2xb4jG3bPPvss9x9992MHTsWgBkzZtCwYUPef/99JkyYQEJCAm+88QYzZ87klFNOAeDdd9+lSZMm/Pjjj5x66qmMGDGCESNGeL+3RYsWrF27lpdffpmnnnqqEtZeRERERERERERERERERERERERERERERERERERERGoizYxcTubPn09ERIQ3EBmgb9++RERE8Oeff/r8zObNm9m9ezfDhw/3vhYQEMDgwYO9n1myZAkZGRl50sTGxtKpU6dCvxcgISGBunXrFpnntLQ0EhMT8zxERERERERERERERERERERERERERERERERERERERLIpGLmc7N69mwYNGhR4vUGDBuzevbvQzwA0bNgwz+sNGzb0vrd79278/f2pU6dOoWny27hxIy+88ALXXHNNkXl+9NFHiYiI8D6aNGlSZHoRERERERERERERERERERERERERERERERERERERqV0UjFyMKVOmYFlWkY/FixcDYFlWgc/btu3z9dzyv1+SzxSWZteuXYwYMYKzzz6b//znP0V+x5133klCQoL3sX379iLTi4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiEjt4qrqDFR3119/Peedd16RaZo1a8by5cvZs2dPgff27dtXYObjbNHR0YCZ/TgmJsb7+t69e72fiY6OJj09nUOHDuWZHXnv3r30798/z/ft2rWLoUOH0q9fP1599dVi1y0gIICAgIBi04lI6QQHB1do+spahoiIiIiIiIiIiIiIiIiIiIjkVV37eahviIiIiIiIiIiIiFQky7Ztu6ozUROsXr2aDh06sHDhQnr37g3AwoUL6du3L2vWrKFt27YFPmPbNrGxsUyePJnbb78dgPT0dBo0aMDjjz/OhAkTSEhIoH79+rz77rucc845AMTHx9O4cWO+/fZbTj31VAB27tzJ0KFD6dGjB++++y5Op7PU65CYmEhERAQJCQmEh4eX9acQERERERERERERERERERERERERERERERERERERkUpS0fGhjnL/xlqqffv2jBgxgquuuooFCxawYMECrrrqKkaNGpUnELldu3bMmjULAMuymDRpEo888gizZs1i5cqVXHbZZQQHB3PBBRcAEBERwZVXXsktt9zCTz/9xN9//81FF11E586dOeWUUwAzI/KQIUNo0qQJTz31FPv27WP37t3s3r278n8IEREREREREREREREREREREREREREREREREREREakxXFWdgZrkvffe48Ybb2T48OEAjBkzhmnTpuVJs3btWhISErx/33777aSkpHDddddx6NAh+vTpww8//EBYWJg3zdSpU3G5XJxzzjmkpKRw8skn8/bbb3tnP/7hhx/YsGEDGzZsoHHjxnmWp4mvRURERERERERERERERERERERERERERERERERERKSsLFvRqpKloqfhFqkNMjIyeO+99wC48MIL8fPzK9f0lbUMEREREREREREREREREREREcmruvbzUN8QERERERERERERqej4UM2MLCJSjmzbZuvWrd7n5Z2+spYhIiIiIiIiIiIiIiIiIiIiInlV134e6hsiIiIiIiIiIiIiFc1R1RkQEREREREREREREREREREREREREREREREREREREZHqScHIIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLik4KRRURERERERERERERERERERERERERERERERERERETEJwUji4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiITwpGFhERERERERERERERERERERERERERERERERERERERn1xVnQERkZrGz8+vQtNX1jJEREREREREREREREREREREJK/q2s9DfUNERERERERERESkIlm2bdtVnQmpHhITE4mIiCAhIYHw8PCqzo6IiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIFKOi40Md5f6NIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiJSIygYWUREREREREREREREREREREREREREREREREREREREfHJVdQZERGqSzMxMPv74YwDOOeccXK6iD7OlTV9ZyxARERERERERERERERERERGRvKprPw/1DREREREREREREZGKplZHEZFy5PF4WL9+vfd5eaevrGWIiIiIiIiIiIiIiIiIiIiISF7VtZ+H+oaIiIiIiIiIiIhIRXNUdQZERERERERERERERERERERERERERERERERERERERKR6UjCyiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIj4pGBkERERERERERERERERERERERERERERERERERERERHxScHIIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLik4KRRURERERERERERERERERERERERERERERERERERETEJ1dVZ0CqD9u2AUhMTKzinIgcv9LT00lNTQXMvuTv71+u6StrGSIiIiIiIiIiIiIiIiIiIiKSV3Xt56G+ISIiIiIiIiIiIpIdF5odJ1reLLuivlmOO5s2baJly5ZVnQ0RERERERERERERERERERERERERERERERERERERKaWNGzfSokWLcv9ezYwsXnXr1gVg27ZtREREVHFupKIlJibSpEkTtm/fTnh4eFVnRyqYyrt2UXnXLirv2kXlXbuovGsXlXftovKuXVTetYvKu3ZRedcuKu/aReVdu6i8axeVd+2i8q5dVN61i8q7dlF51y4q79pF5V27qLxrF5V37aLyrl1U3rWLyrt2UXnXLirv2kXlXbskJCQQFxfnjRMtbwpGFi+HwwFARESEDi61SHh4uMq7FlF51y4q79pF5V27qLxrF5V37aLyrl1U3rWLyrt2UXnXLirv2kXlXbuovGsXlXftovKuXVTetYvKu3ZRedcuKu/aReVdu6i8axeVd+2i8q5dVN61i8q7dlF51y4q79pF5V27qLxrl+w40XL/3gr5VhEREREREREREREREREREREREREREREREREREREROe4pGFlERERERERERERERERERERERERERERERERERERERHxSMLJ4BQQEcN999xEQEFDVWZFKoPKuXVTetYvKu3ZRedcuKu/aReVdu6i8axeVd+2i8q5dVN61i8q7dlF51y4q79pF5V27qLxrF5V37aLyrl1U3rWLyrt2UXnXLirv2kXlXbuovGsXlXftovKuXVTetYvKu3ZRedcuKu/apaLL27Jt266QbxYRERERERERERERERERERERERERERERERERERERkeOaZkYWERERERERERERERERERERERERERERERERERERERGfFIwsIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiI+KRhZRERERERERERERERERERERERERERERERERERERER8UjCyiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIj4pGDkWmbKlClYlpXnER0d7X3ftm2mTJlCbGwsQUFBDBkyhFWrVlVhjuVY7dy5k4suuoh69eoRHBzMCSecwJIlS7zvq8xrjmbNmhXYvy3LYuLEiYDKuqbJzMzknnvuoXnz5gQFBdGiRQseeOABPB6PN43KvGY5cuQIkyZNomnTpgQFBdG/f38WLVrkfV/lffz67bffGD16NLGxsViWxezZs/O8X5KyTUtL44YbbiAqKoqQkBDGjBnDjh07KnEtpKSKK+/PP/+cU089laioKCzLYtmyZQW+Q+V9/CiqvDMyMrjjjjvo3LkzISEhxMbGcskll7Br164836HyPn4Ut39PmTKFdu3aERISQp06dTjllFNYuHBhnjQq7+NHceWd24QJE7Asi2effTbP6yrv40dx5X3ZZZcVuBbv27dvnjQq7+NHSfbv1atXM2bMGCIiIggLC6Nv375s27bN+77K+/hRXHn7amuzLIsnn3zSm0blffworryTkpK4/vrrady4MUFBQbRv356XX345TxqV9/GjuPLes2cPl112GbGxsQQHBzNixAjWr1+fJ43K+/jx6KOP0qtXL8LCwmjQoAFnnnkma9euzZNGbWw1R0nKW21sNUdx5a02tpqlJPu32thqjpKUd25qYzu+laS81cZWc5R0/1YbW81QkvJWG1vNUZLyVhtbzVGS8lYbW83x8ssv06VLF8LDwwkPD6dfv35899133vfVtlazFFfealurWYoqb7Wt1TzF7d9qW6tZiivv3NS2dvwrrrwrs21Nwci1UMeOHYmPj/c+VqxY4X3viSee4JlnnmHatGksWrSI6Ohohg0bxpEjR6owx1JWhw4dYsCAAfj5+fHdd9/x77//8vTTTxMZGelNozKvORYtWpRn3547dy4AZ599NqCyrmkef/xxpk+fzrRp01i9ejVPPPEETz75JC+88II3jcq8ZvnPf/7D3LlzmTlzJitWrGD48OGccsop7Ny5E1B5H8+OHj1K165dmTZtms/3S1K2kyZNYtasWXz44YfMmzePpKQkRo0ahdvtrqzVkBIqrryPHj3KgAEDeOyxxwr9DpX38aOo8k5OTmbp0qXce++9LF26lM8//5x169YxZsyYPOlU3seP4vbvNm3aMG3aNFasWMG8efNo1qwZw4cPZ9++fd40Ku/jR3HlnW327NksXLiQ2NjYAu+pvI8fJSnvESNG5Lkm//bbb/O8r/I+fhRX3hs3bmTgwIG0a9eOX375hX/++Yd7772XwMBAbxqV9/GjuPLOvV/Hx8fz5ptvYlkW48aN86ZReR8/iivvyZMnM2fOHN59911Wr17N5MmTueGGG/jiiy+8aVTex4+iytu2bc4880w2bdrEF198wd9//03Tpk055ZRTOHr0qDedyvv48euvvzJx4kQWLFjA3LlzyczM5P/Zu+/4qKr8/+PvmUwKSSCUAAlVmgiCSHEV7AVRLHzFgg1xLftz2V2xu6gr6hZ114INlbWyYkdX17IKCAiKKL25gBAIkIQkkB6STLm/P24ymUkmmZIymeH15JFH7tw5994zOZOQfO75nM+5557rNZ7E2KJHIONNjC16+BtvYmzRJZDvb2Js0SOQ8a5BjC3yBTrexNiiQyDjTYwtegQy3sTYokcg402MLXr4G29ibNGlV69eeuyxx7R69WqtXr1aZ511liZNmuROOCa2Fl38jTextejS2HgTW4s+/r6/ia1FF3/jXYPYWnQIZLxbLbZm4Igya9YsY8SIET6fc7lcRlpamvHYY4+591VUVBgpKSnGSy+91Eo9RHO69957jVNOOaXB5xnz6DZjxgxjwIABhsvlYqyj0AUXXGDccMMNXvsmT55sXHvttYZh8P0dbcrLy42YmBjjs88+89o/YsQI4/7772e8o4gk4+OPP3Y/DmRsCwsLjdjYWOPdd991t9m/f79htVqN//73v63WdwSv7nh7ysjIMCQZ69at89rPeEeuxsa7xo8//mhIMvbs2WMYBuMdyQIZ76KiIkOSsWjRIsMwGO9I1tB479u3z+jZs6exefNmo2/fvsbTTz/tfo7xjly+xnvatGnGpEmTGjyG8Y5cvsZ7ypQp7r+9fWG8I1cg/39PmjTJOOuss9yPGe/I5Wu8jz32WOORRx7x2jdq1CjjgQceMAyD8Y5kdcd727ZthiRj8+bN7n0Oh8Po3Lmz8c9//tMwDMY70uXm5hqSjGXLlhmGQYwt2tUdb0/E2KJPY+Ndgxhb9AhkvImxRY+GxpsYW3TyNd7E2KKXr/Emxha9Avn/mxhb9PA13sTYolfd8SbGFv06depkvPLKK8TWjhA14+2J2Fr08jXeNYitRZ/GxpvYWvSpO97E1qKb53i3ZmyNyshHoB07dqhHjx7q16+frrzySu3atUuSlJGRoZycHJ177rnutvHx8Tr99NP1/fffh6u7aIJPP/1UY8aM0eWXX65u3bpp5MiR+uc//+l+njGPXlVVVXrrrbd0ww03yGKxMNZR6JRTTtHixYu1fft2SdKGDRu0YsUKTZw4URLf39HG4XDI6XR6rQIsSe3atdOKFSsY7ygWyNiuWbNGdrvdq02PHj00bNgwxj8KMd7RraioSBaLRR07dpTEeEezqqoqzZ07VykpKRoxYoQkxjvauFwuTZ06VXfffbeOPfbYes8z3tFn6dKl6tatm44++mjdfPPNys3NdT/HeEcPl8ulzz//XEcffbQmTJigbt266cQTT9S///1vdxvGO3odOHBAn3/+uW688Ub3PsY7upxyyin69NNPtX//fhmGoSVLlmj79u2aMGGCJMY7mlRWVkqSV6wtJiZGcXFxWrFihSTGO9IVFRVJkjp37iyJGFu0qzvegWC8I1cg402MLXr4G29ibNHF13gTY4teDX1/E2OLTnXHmxhbdPP3/zcxtujia7yJsUWvuuNNjC16OZ1OvfvuuyorK9PYsWOJrUW5uuMdCMY7cgUy3sTWooe/8Sa2Fl18jTextejV0Pd3a8XWSEY+wpx44omaN2+evvrqK/3zn/9UTk6Oxo0bp4MHDyonJ0eS1L17d69junfv7n4OkWXXrl168cUXNWjQIH311Ve65ZZbdOutt2revHmSxJhHsX//+98qLCzU9ddfL4mxjkb33nuvrrrqKh1zzDGKjY3VyJEjddttt+mqq66SxJhHm/bt22vs2LH685//rKysLDmdTr311ltatWqVsrOzGe8oFsjY5uTkKC4uTp06dWqwDaIH4x29Kioq9Mc//lFXX321OnToIInxjkafffaZkpOTlZCQoKeffloLFy5UamqqJMY72jz++OOy2Wy69dZbfT7PeEeX888/X/Pnz9c333yjJ598Uj/99JPOOuss9yQMxjt65ObmqrS0VI899pjOO+88ff3117rkkks0efJkLVu2TBLjHc3efPNNtW/fXpMnT3bvY7yjy7PPPquhQ4eqV69eiouL03nnnac5c+bolFNOkcR4R5NjjjlGffv21cyZM1VQUKCqqio99thjysnJUXZ2tiTGO5IZhqE77rhDp5xyioYNGyaJGFs08zXegWC8I1Mg402MLXo0Nt7E2KJPQ+NNjC06NTTexNiik6/xJsYWvQL5fY0YW/RoaLyJsUUnX+NNjC36bNq0ScnJyYqPj9ctt9yijz/+WEOHDiW2FqUaGu9AMN6RJ9DxJrYWHfyNN7G16NLYeBNbiz6NjXdrxtZszfNyECnOP/989/bw4cM1duxYDRgwQG+++aZOOukkSZLFYvE6xjCMevsQGVwul8aMGaO//e1vkqSRI0dqy5YtevHFF3Xddde52zHm0efVV1/V+eefrx49enjtZ6yjx3vvvae33npLb7/9to499litX79et912m3r06KFp06a52zHm0eNf//qXbrjhBvXs2VMxMTEaNWqUrr76aq1du9bdhvGOXqGMLeN/ZGG8I5vdbteVV14pl8ulOXPm+G3PeEeuM888U+vXr1d+fr7++c9/6oorrtCqVavUrVu3Bo9hvCPPmjVr9Mwzz2jt2rVBjx3jHZmmTJni3h42bJjGjBmjvn376vPPP/eaUFUX4x15XC6XJGnSpEm6/fbbJUnHH3+8vv/+e7300ks6/fTTGzyW8Y58r732mq655hqvKg8NYbwj07PPPqsffvhBn376qfr27atvv/1W06dPV3p6us4555wGj2O8I09sbKwWLFigG2+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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ntrack = 5\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "\n", + "st = 50\n", + "end = 350\n", + "\n", + "start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + "muts = [\"67_G\",\"69_A\",\"243_G\",\"245_A\"]\n", + "for i, mut_ in enumerate(muts):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=start_x, class_no = 16)\n", + "for i, mut_ in enumerate(muts):\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax2.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "\n", + "start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + "muts = [\"173_G\",\"184_G\",\"185_T\",\"186_G\",\"283_G\",\"294_G\",\"295_T\",\"296_G\",]\n", + "for i, mut_ in enumerate(muts):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=start_x, class_no = 16)\n", + "for i, mut_ in enumerate(muts):\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax3.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "\n", + "start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + "muts = [\"126_A\",\"131_A\",\"252_A\",\"257_A\"]\n", + "for i, mut_ in enumerate(muts):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=start_x, class_no = 16)\n", + "for i, mut_ in enumerate(muts):\n", + " ax4.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax4.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "\n", + "start_x = np.copy(irf4_onehot[\"wild-type\"])\n", + "muts = [\"85_G\",\"119_A\",\"196_C\",\"202_A\",\"215_T\",\"270_C\",\"326_C\"]\n", + "for i, mut_ in enumerate(muts):\n", + " start_x[0][int(mut_.split(\"_\")[0]),:] = np.array(nuc_to_onehot[mut_.split(\"_\")[1]], dtype='int8')\n", + "ax5 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=start_x, class_no = 16)\n", + "ax6 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=5, seq_onehot=start_x, class_no = 16)\n", + "for i, mut_ in enumerate(muts):\n", + " ax5.axvline(x=int(mut_.split(\"_\")[0]),linestyle=\"--\",color=\"gray\")\n", + " ax5.axvline(x=int(mut_.split(\"_\")[0])+1,linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax2.set_xlim([st,end])\n", + "ax3.set_xlim([st,end])\n", + "ax4.set_xlim([st,end])\n", + "ax5.set_xlim([st,end])\n", + "_ = ax6.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_noZeb_noSox_noMitf_moreZeb.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "9d09d832-621c-4b43-8083-d13156cd96db", + "metadata": {}, + "source": [ + "### Loading luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "1f293846-4b93-43eb-958f-b13faa2d6322", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "luciferase_dict = {\"ids\":[],\"values\":[]}\n", + "with open(\"data/luciferase/IRF4.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " luciferase_dict[\"ids\"].append(sep[0])\n", + " luciferase_dict[\"values\"].append(sep[1:])\n", + "luciferase_dict[\"values\"] = np.array(luciferase_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "markdown", + "id": "3eaaad22-3d90-400e-b1d7-40b8201568f4", + "metadata": {}, + "source": [ + "### Plotting luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "fd12cf67-c8f0-4de4-b06c-9da969751794", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(4,5))\n", + "plt.title(\"IRF4\")\n", + "\n", + "mean = np.mean(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "\n", + "index = np.argsort(mean)[::-1]\n", + "temp = sorted(mean)[::-1]\n", + "res = [temp.index(i) for i in mean]\n", + "\n", + "plt.bar(range(len(mean)),mean,color=\"green\",label=\"\",yerr=std,capsize=3)\n", + "\n", + "for i in (range(len(mean))):\n", + " for k in np.log2(luciferase_dict[\"values\"][i]):\n", + " plt.scatter(i,k,color=\"black\",zorder=10,s=8)\n", + "\n", + "_ = plt.xticks(range(len(mean)),np.array(luciferase_dict[\"ids\"]),rotation=45)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_mutations_luciferase.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "9bd7f9e7-78f9-48d7-b46f-3654b0a3049b", + "metadata": {}, + "source": [ + "### Calculating and plotting prediction scores for the IRF4 enhancer sequence with different motif modifications." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "6c88aac3-337e-4caa-b5c4-288c1b91807e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(4,5))\n", + "\n", + "topic=16\n", + "topic=topic-1\n", + "pred = []\n", + "\n", + "start_x = np.copy(irf4_onehot['wild-type'])\n", + "pred.append(model_dict[\"deepmel2\"].predict([start_x,start_x[:,::-1,::-1]])[0,topic])\n", + "\n", + "start_x = np.copy(irf4_onehot['more_ZEB2'])\n", + "pred.append(model_dict[\"deepmel2\"].predict([start_x,start_x[:,::-1,::-1]])[0,topic])\n", + "\n", + "start_x = np.copy(irf4_onehot['no_MITF'])\n", + "pred.append(model_dict[\"deepmel2\"].predict([start_x,start_x[:,::-1,::-1]])[0,topic])\n", + "\n", + "start_x = np.copy(irf4_onehot['no_SOX10'])\n", + "pred.append(model_dict[\"deepmel2\"].predict([start_x,start_x[:,::-1,::-1]])[0,topic])\n", + "\n", + "start_x = np.copy(irf4_onehot['no_ZEB2'])\n", + "pred.append(model_dict[\"deepmel2\"].predict([start_x,start_x[:,::-1,::-1]])[0,topic])\n", + "\n", + "_ = plt.bar(range(5),pred)\n", + "plt.title(\"IRF4\")\n", + "plt.xticks(range(5),['WT',\"Repr\",\"No MITF\",\"No SOX10\",\"No ZEB2\"],rotation=45)\n", + "plt.ylabel(\"Prediction Score\")\n", + "\n", + "plt.savefig(\"figures/irf4/IRF4_mutations_prediction.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "40ac5fb0-2841-4ec9-ba3e-e80aa762b558", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_Lenti_ATAC.ipynb b/the_code/Human/MM_Lenti_ATAC.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..935c7dcfb2dd7d869a1acd91732ce0903466ebda --- /dev/null +++ b/the_code/Human/MM_Lenti_ATAC.ipynb @@ -0,0 +1,328 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "49aab365-5580-4d5d-b237-0acc3394fee9", + "metadata": {}, + "source": [ + "# This notebook shows the experiments related to ATAC-seq on synthetic enhancer integrated cell lines." + ] + }, + { + "cell_type": "markdown", + "id": "3936b70b-d2ef-4cb7-8ba2-27bfb3d44ca8", + "metadata": {}, + "source": [ + "#### Processed ATAC-seq data is in data/lenti_atac_chip folder.\n", + "#### It consist of:\n", + "* Reading ATAC-seq files and calculating the coverage on the enhancers\n", + "#### Figures are saved to ./figures/lenti_atac_chip folder" + ] + }, + { + "cell_type": "markdown", + "id": "96a8e08a-272f-4752-94cb-31309ea0dd2e", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "9a5e24c7-455c-48c8-a57d-04bb65a5b525", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pyBigWig\n", + "import pyranges as pr\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.patches as mpatches\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "970d9765-e904-4eb8-898b-aa1f495fde9c", + "metadata": {}, + "source": [ + "### Loading the gtf file of the integrated cassette that harbors the synthetic enhancer" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fc6d8ecc-100b-4d31-ae1f-e3db68b7f2ea", + "metadata": {}, + "outputs": [], + "source": [ + "pr_gtf = pr.read_gtf(\"data/lenti_atac_chip/MMEFS.gtf\")" + ] + }, + { + "cell_type": "markdown", + "id": "9663a133-41f7-4c94-9c6c-2157b7e0020b", + "metadata": {}, + "source": [ + "### Loading the ATAC-seq bigwig files and calculating the coverage on integrated synthetic sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "12c6e246-42b8-48e5-9e42-f071ad7dbd5f", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "evolved_all_MM001_bw = pyBigWig.open(\"data/lenti_atac_chip/OmniATAC_MM001_EFS_enhancers_lenti.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "evolved_all_MM099_bw = pyBigWig.open(\"data/lenti_atac_chip/OmniATAC_MM099_EFS_enhancers_lenti.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "\n", + "MMEFS_MM001_values = {}\n", + "MMEFS_MM099_values = {}\n", + "for i in range(1,11):\n", + " MMEFS_MM001_values[i] = evolved_all_MM001_bw.values(\"MM-EFS-\"+str(i), 1, 4397)\n", + " MMEFS_MM099_values[i] = evolved_all_MM099_bw.values(\"MM-EFS-\"+str(i), 1, 4397)" + ] + }, + { + "cell_type": "markdown", + "id": "0b4c84c0-3da7-41a2-9062-59541af7b5ee", + "metadata": {}, + "source": [ + "### Plotting the ATAC-seq coverage on integrated synthetic sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "90d7cd0a-b927-49ce-932b-6c4af37a521b", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 11\n", + "fig = plt.figure(figsize=(10,0.8*n_tracks))\n", + "start = 1\n", + "end = 4397\n", + "for i, EFS in enumerate([4,1,8,2,5,9,10,6,3,7]):\n", + " ax = fig.add_subplot(n_tracks,2,i*2+1)\n", + " ax.fill_between(np.linspace(start, end, num=len(MMEFS_MM001_values[EFS])),0,MMEFS_MM001_values[EFS]) \n", + " ax.set_title(\"MMEFS-\"+str(EFS))\n", + " ax.margins(x=0)\n", + " if i!=9:\n", + " ax.set_xticks([])\n", + " \n", + "for i, EFS in enumerate([4,1,8,2,5,9,10,6,3,7]):\n", + " ax = fig.add_subplot(n_tracks,2,i*2+2)\n", + " ax.fill_between(np.linspace(start, end, num=len(MMEFS_MM099_values[EFS])),0,MMEFS_MM099_values[EFS]) \n", + " ax.set_title(\"MMEFS-\"+str(EFS))\n", + " ax.margins(x=0)\n", + " if i!=9:\n", + " ax.set_xticks([])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "for ax_no in [21,22]:\n", + " ax = fig.add_subplot(n_tracks,2,ax_no)\n", + " gtf_region_intersect = pr_gtf.intersect(pr_gtf)\n", + " genes_in_window = set(gtf_region_intersect.gene_name)\n", + " n_genes_in_window = len(genes_in_window)\n", + " for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.5, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " ax.text(gene_start, 2, part[\"gene_id\"], fontsize=5)\n", + "\n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([1, 4397])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0)\n", + "\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/lenti_atac_chip/MMEFS_all_MM001_MM099_ATAC.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "3bd661c1-7fd9-401e-8527-c451ac34f13a", + "metadata": {}, + "source": [ + "### Loading the ATAC-seq bigwig files and calculating the coverage on integrated synthetic sequences that are at random state, evolved state, or repressed state" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c25e74d9-5683-49f2-8fe0-75d936e7fe3c", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "repressed_bw = pyBigWig.open(\"data/lenti_atac_chip/OmniATAC_MM001_pool_1_enhancers_repressed_seq.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "random_bw = pyBigWig.open(\"data/lenti_atac_chip/OmniATAC_MM001_pool_2_enhancers_random_seq.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "evolved_bw = pyBigWig.open(\"data/lenti_atac_chip/OmniATAC_MM001_pool_3_enhancers_evolved_seq.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "\n", + "repressed_values = {}\n", + "for i in [4,1,8]:\n", + " repressed_values[i] = repressed_bw.values(\"MM-EFS-\"+str(i)+\"_repr\", 1, 4397)\n", + "random_values = {}\n", + "for i in [4,1,8]:\n", + " random_values[i] = random_bw.values(\"MM-EFS-\"+str(i)+\"_rand\", 1, 4397)\n", + "evolved_values = {}\n", + "for i in [4,1,8]:\n", + " evolved_values[i] = evolved_bw.values(\"MM-EFS-\"+str(i), 1, 4397)" + ] + }, + { + "cell_type": "markdown", + "id": "b4db32c9-8d1a-4270-9bc3-a4c7c49c53ab", + "metadata": {}, + "source": [ + "### Plotting the ATAC-seq coverage on integrated synthetic sequences that are at random state, evolved state, or repressed statev" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a2d2690e-b359-4615-bdd0-9831f51bf8c2", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 4\n", + "fig = plt.figure(figsize=(15,1*n_tracks))\n", + "start = 1\n", + "end = 4397\n", + "\n", + "for i, EFS in enumerate([4,1,8]):\n", + " ax = fig.add_subplot(n_tracks,3,i+1)\n", + " ax.fill_between(np.linspace(start, end, num=len(random_values[EFS])),0,random_values[EFS]) \n", + " ax.set_title(\"MMEFS-\"+str(EFS)+\"-Random\")\n", + " ax.margins(x=0)\n", + " ax.set_xticks([])\n", + " \n", + "for i, EFS in enumerate([4,1,8]):\n", + " ax = fig.add_subplot(n_tracks,3,3+i+1)\n", + " ax.fill_between(np.linspace(start, end, num=len(evolved_values[EFS])),0,evolved_values[EFS]) \n", + " ax.set_title(\"MMEFS-\"+str(EFS)+\"-Evolved\")\n", + " ax.margins(x=0)\n", + " ax.set_xticks([])\n", + " \n", + "for i, EFS in enumerate([4,1,8]):\n", + " ax = fig.add_subplot(n_tracks,3,6+i+1)\n", + " ax.fill_between(np.linspace(start, end, num=len(repressed_values[EFS])),0,repressed_values[EFS]) \n", + " ax.set_title(\"MMEFS-\"+str(EFS)+\"-Repressed\")\n", + " ax.margins(x=0)\n", + " \n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "for ax_no in [10,11,12]:\n", + " ax = fig.add_subplot(n_tracks,3,ax_no)\n", + " gtf_region_intersect = pr_gtf.intersect(pr_gtf)\n", + " genes_in_window = set(gtf_region_intersect.gene_name)\n", + " n_genes_in_window = len(genes_in_window)\n", + " for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.5, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " ax.text(gene_start, 2, part[\"gene_id\"], fontsize=5)\n", + "\n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([start, end])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0)\n", + " \n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/lenti_atac_chip/MMEFS_Rand_Evolved_Repr_EFS4-1-8_MM001_ATAC.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7890c7ff-e384-4ab8-ab8e-673af0da31c5", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "20230504_pycistopic.sif", + "language": "python", + "name": "cistopic_20230504" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_Motif_Implanting.ipynb b/the_code/Human/MM_Motif_Implanting.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..e2cca0b85f510460d76ee89e378e225f3db3aef2 --- /dev/null +++ b/the_code/Human/MM_Motif_Implanting.ipynb @@ -0,0 +1,1643 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# This notebook shows how to design synthetic sequences by using motif implantation.\n", + "#### It consists of:\n", + "* Performing motif implantation experiments.\n", + "* Visualising motif distance preference experiments.\n", + "* Replacing motifs on synthetic sequences with weaker ones from IRF4 enhancer.\n", + "* Cutting and shortening designed sequences.\n", + "#### Luciferase values are in ./data/motif_embedding folder\n", + "#### Intermediate files are saved to ./data/motif_embedding folder\n", + "#### Figures are saved to ./figures/motif_embedding" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading the models and initializing shap.DeepExplainer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Defining the TF patterns that are going to be implanted" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "patterns_dict = {}\n", + "patterns_dict[\"sox10\"] = utils.one_hot_encode_along_row_axis(\"AACAATGGGCCCATTGTT\")\n", + "patterns_dict[\"tfap2\"] = utils.one_hot_encode_along_row_axis(\"GCCTGAGGC\")\n", + "patterns_dict[\"mitf\"] = utils.one_hot_encode_along_row_axis(\"GTCACGTGAC\")\n", + "patterns_dict[\"runx\"] = utils.one_hot_encode_along_row_axis(\"AACCACA\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generating random sequences and implanting the motifs to the best location selected by highest model prediction score " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# irf4_onehot = utils.one_hot_encode_along_row_axis(\"AGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGTGCTTCCTATCTCAGCCTCTCCTGCACTCCT\")\n", + "# shuffled_regions = []\n", + "# for i in range(2000):\n", + "# np.random.shuffle(irf4_onehot[0])\n", + "# shuffled_regions.append(np.copy(irf4_onehot[0]))\n", + "# shuffled_regions = np.array(shuffled_regions)\n", + "# pred_2000 = model_dict[\"deepmel2\"].predict([shuffled_regions,shuffled_regions[:,::-1,::-1]])[:,15]\n", + "# pred_1834 = pred_2000[pred_2000<0.05]\n", + "# shuffled_regions_1834 = shuffled_regions[pred_2000<0.05]\n", + "\n", + "# motif_embedding_dict = {}\n", + "# motif_embedding_dict[\"0\"] = {}\n", + "# motif_embedding_dict[\"0\"][\"regions\"] = np.copy(shuffled_regions_1834)\n", + "# motif_embedding_dict[\"s\"] = utils.add_pattern_to_best_location(patterns_dict[\"sox10\"], motif_embedding_dict[\"0\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"m\"] = utils.add_pattern_to_best_location(patterns_dict[\"mitf\"], motif_embedding_dict[\"0\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"t\"] = utils.add_pattern_to_best_location(patterns_dict[\"tfap2\"], motif_embedding_dict[\"0\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"r\"] = utils.add_pattern_to_best_location(patterns_dict[\"runx\"], motif_embedding_dict[\"0\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# motif_embedding_dict[\"ss\"] = utils.add_pattern_to_best_location(patterns_dict[\"sox10\"], motif_embedding_dict[\"s\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"sm\"] = utils.add_pattern_to_best_location(patterns_dict[\"mitf\"], motif_embedding_dict[\"s\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"ms\"] = utils.add_pattern_to_best_location(patterns_dict[\"sox10\"], motif_embedding_dict[\"m\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# motif_embedding_dict[\"ssm\"] = utils.add_pattern_to_best_location(patterns_dict[\"mitf\"], motif_embedding_dict[\"ss\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"ssmm\"] = utils.add_pattern_to_best_location(patterns_dict[\"mitf\"], motif_embedding_dict[\"ssm\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# motif_embedding_dict[\"ssmmt\"] = utils.add_pattern_to_best_location(patterns_dict[\"tfap2\"], motif_embedding_dict[\"ssmm\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"ssmmtt\"] = utils.add_pattern_to_best_location(patterns_dict[\"tfap2\"], motif_embedding_dict[\"ssmmt\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# motif_embedding_dict[\"smt\"] = utils.add_pattern_to_best_location(patterns_dict[\"tfap2\"], motif_embedding_dict[\"sm\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"smtr\"] = utils.add_pattern_to_best_location(patterns_dict[\"runx\"], motif_embedding_dict[\"smt\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# motif_embedding_dict[\"smts\"] = utils.add_pattern_to_best_location(patterns_dict[\"sox10\"], motif_embedding_dict[\"smt\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"smtsm\"] = utils.add_pattern_to_best_location(patterns_dict[\"mitf\"], motif_embedding_dict[\"smts\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "# motif_embedding_dict[\"smtsmt\"] = utils.add_pattern_to_best_location(patterns_dict[\"tfap2\"], motif_embedding_dict[\"smtsm\"][\"regions\"], model_dict[\"deepmel2\"], class_no=16)\n", + "\n", + "# for key in motif_embedding_dict:\n", + "# motif_embedding_dict[key][\"prediction\"] = model_dict[\"deepmel2\"].predict([motif_embedding_dict[key][\"regions\"],motif_embedding_dict[key][\"regions\"][:,::-1,::-1]])\n", + " \n", + "# import pickle\n", + "# f = open(\"data/motif_embedding/motif_embedding_smtr.pkl\", \"wb\")\n", + "# pickle.dump(motif_embedding_dict,f)\n", + "# f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "f = open(\"data/motif_embedding/motif_embedding_smtr.pkl\", \"rb\")\n", + "motif_embedding_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['0', 's', 'm', 't', 'r', 'ss', 'sm', 'ms', 'ssm', 'ssmm', 'ssmmt', 'ssmmtt', 'smt', 'smtr', 'smts', 'smtsm', 'smtsmt'])" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "motif_embedding_dict.keys()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the prediction scores after each motif implantation steps" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Prediction score')" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(7,4))\n", + "\n", + "Topic = 16\n", + "_ = plt.boxplot([motif_embedding_dict[key][\"prediction\"][:,Topic-1] for key in ['0', 't', 'm', 's', 'sm','smt', 'smts', 'smtsm', 'smtsmt']] ,notch=True,showfliers=False, whis=[5,95])\n", + "plt.ylim([-0.05,1.05])\n", + "\n", + "_ = plt.xticks(range(1,10),[\"Random\",\"TFAP2\",\"MITF\",\"SOX10\",\"S,M\",\"S,M,T\",\"S,M,T,S\",\"S,M,T,S,M\",\"S,M,T,S,M,T\"],rotation=90)\n", + "\n", + "plt.ylabel(\"Prediction score\")\n", + "#plt.savefig(\"/Users/u0110091/PycharmProjects/EnhancerDesign/figures/boxplot_withdouble.pdf\",transparent=True,dpi=300)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting the implantation location of a TF motif relative to another TF motif." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "a = plt.hist(motif_embedding_dict[\"sm\"][\"locations\"]-motif_embedding_dict[\"s\"][\"locations\"],bins=401,range=(-200.5,200.5),color=\"gray\")\n", + "plt.xlabel(\"Location of MITF relative to SOX10\")\n", + "plt.ylabel(\"Number of sequences\")\n", + "plt.ylim([0,24])\n", + "plt.savefig(\"figures/motif_embedding/mitf_sox10_distance.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "a = plt.hist(motif_embedding_dict[\"smt\"][\"locations\"]-motif_embedding_dict[\"s\"][\"locations\"],bins=401,range=(-200.5,200.5),color=\"gray\")\n", + "plt.xlabel(\"Location of TFAP2 relative to SOX10\")\n", + "plt.ylabel(\"Number of sequences\")\n", + "plt.ylim([0,24])\n", + "plt.savefig(\"figures/motif_embedding/tfap2_sox10_distance.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "a = plt.hist(motif_embedding_dict[\"smts\"][\"locations\"]-motif_embedding_dict[\"s\"][\"locations\"],bins=601,range=(-300.5,300.5),color=\"gray\")\n", + "plt.xlabel(\"Location of second SOX10 relative to first SOX10\")\n", + "plt.ylabel(\"Number of sequences\")\n", + "plt.ylim([0,24])\n", + "plt.savefig(\"figures/motif_embedding/secondSox10_firstSox10_distance.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Function that implant motifs to every possible positions on given sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "def add_pattern_to_every(pattern, regions, model, topic):\n", + " pattern_added_regions = np.zeros(regions.shape,dtype=\"int\")\n", + " pattern_locations = np.zeros(regions.shape[0],dtype=\"int\")\n", + " for r, region in enumerate(regions):\n", + " tmp_array = np.zeros((regions.shape[1]-pattern.shape[1]+1,regions.shape[1],regions.shape[2]))\n", + " for nt in range(tmp_array.shape[0]):\n", + " tmp_array[nt] = np.copy(region)\n", + " tmp_array[nt,nt:nt+pattern.shape[1],:] = pattern[0]\n", + " prediction = model.predict([tmp_array,tmp_array[:,::-1,::-1]])[:,topic-1]\n", + " return {\"tmp_array\":tmp_array, \"prediction\":prediction}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading flanking sequences in the vector around the tested enhancers and defining the TF patterns that are going to be implanted" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sox10 18\n", + "tfap2 9\n", + "mitf 10\n", + "runx 7\n" + ] + } + ], + "source": [ + "upstream_seq = utils.one_hot_encode_along_row_axis(\"ctcaaggatcttgccgctattgagatccagttcgatatagcccactcttgcacccagttgatcttcagcatcttttactttcaccagcgtttcggggtgtgcaaaaacaggcaagcaaaatgccgcaaagaagggaatgagtgcgacacgaaaatgttggatgctcatactcgtcctttttcaatattattgaagcatttatcagggttactagtacgtctctcaaggataagtaagtaatattaaggtacgggaggtattggacaggccgcaataaaatatctttattttcattacatctgtgtgttggttttttgtgtgaatcgatagtactaacatacgctctccatcaaaacaaaacgaaacaaaacaaactagcaaaataggctgtccccagtgcaagtgcaggtgccagaacatttctctggcctaactggccggtacctgagctcccgtcgacgaattctgcagatatcCAAGTTTGTACAAAAAAGCAGGCT\")\n", + "downstream_seq = utils.one_hot_encode_along_row_axis(\"ACCCAGCTTTCTTGTACAAAGTGGgataaacccgctgatcagcctcgactgtgctcgaggatatcaagatctggcctcggcggccaagcttagacactagagggtatataatggaagctcgacttccagcttggcaatccggtactgttggtaaagccaccatggaagatgccaaaaacattaagaagggcccagcgccattctacccactcgaagacgggaccgccggcgagcagctgcacaaagccatgaagcgctacgccctggtgcccggcaccatcgcctttaccgacgcacatatcgaggtggacattacctacgccgagtacttcgagatgagcgttcggctggcagaagctatgaagcgctatgggctgaatacaaaccatcggatcgtggtgtgcagcgagaatagcttgcagttcttcatgcccgtgttgggtgccctgttcatcggtgtggctgtggccccagctaacgacatctacaacgagcgcgag\")\n", + "\n", + "patterns_dict = {}\n", + "patterns_dict[\"sox10\"] = utils.one_hot_encode_along_row_axis(\"AACAATGGGCCCATTGTT\")\n", + "patterns_dict[\"tfap2\"] = utils.one_hot_encode_along_row_axis(\"GCCTGAGGC\")\n", + "patterns_dict[\"mitf\"] = utils.one_hot_encode_along_row_axis(\"GTCACGTGAC\")\n", + "patterns_dict[\"runx\"] = utils.one_hot_encode_along_row_axis(\"AACCACA\")\n", + "\n", + "patterns_dict_irf4 = {}\n", + "patterns_dict_irf4[\"sox1\"] = utils.one_hot_encode_along_row_axis(\"GTGAATGACAGCTTTGTT\")\n", + "patterns_dict_irf4[\"sox2\"] = utils.one_hot_encode_along_row_axis(\"TACAAGTATCTCCATTGT\")\n", + "patterns_dict_irf4[\"mitf1\"] = utils.one_hot_encode_along_row_axis(\"ATCATGTGAA\")\n", + "patterns_dict_irf4[\"mitf2\"] = utils.one_hot_encode_along_row_axis(\"GCCATATGAC\")\n", + "patterns_dict_irf4[\"tfap1\"] = utils.one_hot_encode_along_row_axis(\"TCTTCAGGC\")\n", + "patterns_dict_irf4[\"tfap2\"] = utils.one_hot_encode_along_row_axis(\"CCCTGTGGT\")\n", + "\n", + "for key in patterns_dict:\n", + " print(key,len(patterns_dict[key][0]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Selecting 2 sequences where the motifs are implanted on the upstream side of the sequence" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 10, 12, 16])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.where([np.logical_and(\n", + " motif_embedding_dict[\"smt\"][\"locations\"]>120,\n", + " np.logical_and(motif_embedding_dict[\"smt\"][\"locations\"]<200,\n", + " np.logical_and(motif_embedding_dict[\"s\"][\"locations\"]<150,\n", + " motif_embedding_dict[\"sm\"][\"locations\"]<100)))])[1][:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Selected IDs: 1 12\n" + ] + } + ], + "source": [ + "print(\"Selected IDs:\",*[1,12])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores for:\n", + "* The initial random sequence\n", + "* The SOX, MITF, TFAP motifs implanted once on the random sequence\n", + "* The SOX, MITF, TFAP motifs implanted twice on the random sequence\n", + "* Strong SOX, MITF, TFAP motifs are replaced with weak ones\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 1\n", + "\n", + "ntrack = 4\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"0\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict_smtsmt[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "onehot_[0,motif_embedding_dict[\"smts\"][\"locations\"][ori_index]:motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox2\"].shape[1],:] = patterns_dict_irf4[\"sox2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"s\"][\"locations\"][ori_index]:motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox1\"].shape[1],:] = patterns_dict_irf4[\"sox1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf1\"].shape[1],:] = patterns_dict_irf4[\"mitf1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"sm\"][\"locations\"][ori_index]:motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf2\"].shape[1],:] = patterns_dict_irf4[\"mitf2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap2\"].shape[1],:] = patterns_dict_irf4[\"tfap2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap1\"].shape[1],:] = patterns_dict_irf4[\"tfap1\"][0]\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "\n", + "for ax_ in [ax1,ax2,ax3,ax4]:\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + "\n", + "plt.savefig(\"figures/motif_embedding/ME1_rand_single_double_irf4_st0_end500_deepexplainer_topic16.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores for the cut sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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w4MGSpC1btqiysjKw/5AhQzRv3jxNnTpVDzzwgAYMGKD77rtPEydODOxz7LHH6tlnn9Utt9yiW2+9VcOGDdPcuXN19NFHB/b561//qltvvVVXXXWVtm3bpgEDBuiXv/ylfv/737fdlwcAAECr+QfnGzwNWTk+CwgDAAAAyFcFFQyQpKuuukpXXXVV1NeefPLJiG0nnniili1bFveYF1xwgS644IKYr3fp0kWzZs3SrFmzUmkqAAAA8owpM6vHJzMAAAAAQL4qqDJBAAAAQGv4a4H6zOzUBHV73SHPCQYAAAAAyBcEAwAAAFA0PD6PpOwFA5p9oYP/4QsKAwAAAECuEAwAAABA0fAPzpMZAAAAAKDYGKZpZrdwKiRJtbW16tatm2pqatS1a9dcNwcAAKAo3fbubZr+/nSN7D1SX1z1RcaP3/HOjiGLE5994Nn690//nfHPQYFYtkwaMyb19y1dKh15ZObbAwAAgHYnlXFnMgMAAABQNPyZAf5yQZkWftxGb2NWPgcAAAAAUkUwAAAAAEWjyZO9YIBpmnL7QssE+T8PAAAAAHLNlesGoDB4PB699NJLkqTzzz9fLhf/dNozzjcAIJ9k8rrkzwwIr+2fCfYAgyFDpkw1esgMaFcqK6Xq6tBtW7ZIu3dbj7t3l/r3D762enVbtSwr6BMCABAf18rCVoznr/1/Q2SEz+fTqlWrJEnnnntujluDbON8AwDySSavS/7B+Wws7Gs/pmEYMk2TBYTbk8pKafhwqbF4Ajz0CQEAiI9rZWErxvNHmSAAAAAUjWxmBoQEA2SEfB7agerqogoEAAAAoP0hGAAAAICi4a/h3+zLfmZA+DYAAAAAyCWCAQAAACgagWBAlssEOQxHyOcBAAAAQK4RDAAAAEDR8JftaatggNuX+XJEAAAAAJAOggEAAAAoGtmcqR81GJCFtQkAAAAAIB0EAwAAAFA0srmgr/3YTsMpiWAA0lBeLvXqletWAAAAoB0yTNM0c92IYlBbW6tu3bqppqZGXbt2zXVzUmaaptxu62a2pKQksCge2ifONwAgn2TyunTEQ0doxdYV1nFvy2w3+JNNn+joR4+WJHUr66aaphqVOcvUeEtjRj8HObJsmTRmTHrvffppacQI6/Hq1dIll0R/TbICAYMGpd/ODKJPCABAfFwrC1t7OX+pjDu72qhNKHCGYai0tDTXzUAb4XwDAPJJJq9L2cwMsJcJCmQGsGYAJGuw/8gjU38tx+gTAgAQH9fKwlaM548yQQAAACgajZ7szdIPWTPAYXWzfaZPXp83a58JAAAAAMkiMwBJ8Xg8+s9//iNJOvvss+Vy8U+nPeN8AwDySSavS20RDDBkyGUE2+j2ueV0OOO+11+5s1BTk9E+0ScEACA+rpWFrRjPH5kBSIrP59PKlSu1cuVK+Xy+XDcHWcb5BgDkk0xel5o8bVQmyDb4b98ei2O6Q87p8QMGQFujTwgAQHxcKwtbMZ4/ggEAAAAoGm2xZoBhGHI5grOKkg1AmMrsgsYAAAAAYEcwAAAAAEXDPjCf6Vr+9gwAezAgUWYAawoAAAAAaAsEAwAAAFA0PKYn8DjTWQIhawakEAzI5joGAAAAAOBHMAAAAABFKdOD8PasgxJnSeBxomBAg6cho+0AAAAAgGgIBgAAAKAoZToY0OxtlsNwyJQpl5F8ZkCDm2AAAAAAgOwjGAAAAICilI1ggCFDPtMnlzOFYACZAQAAAADagCvxLoBUUlKi66+/PvAY7RvnGwCQTzJ1XfL4PCHPsxIMMAzJlEocJTJkyJRJZgAKFn1CAADi41pZ2Irx/BEMQFIMw1CnTp1y3Qy0Ec43ACCfZOq6ZK/pL2UnGOCXygLCZAYgX9EnBAAgPq6Vha0Yzx9lggAAAFAUwgf/sxkMKHGUWFkCYs0AAAAAAPkh5WCA2+3W0KFDtWrVqmy0B3nK4/Ho1Vdf1auvviqPx5P4DShonG8AQD7J1HWpLYIBpmlKUsiaAU3eplhvkURmAPIXfUIAAOLjWlnYivH8pRwMKCkpUVNTU2CmE4qDz+fTkiVLtGTJEvl8vlw3B1nG+QYA5JNMXZfaMjOg1FEqQ2QGoLDRJwQAID6ulYWtGM9fWmWCfv3rX+vuu+8umogJAAAACl+bZAYomBmQdJkgMgMAAAAAtIG0FhD++OOP9fbbb+vNN9/U6NGjIxZaePHFFzPSOAAAACBTsh0MsJcDKnWUBh6TGQAAAAAgH6QVDOjevbsmTpyY6bYAAAAAWdOWawaUulIoE0RmAAAAAIA2kFYw4Iknnsh0OwAAAICsassyQSWOEkmSISOlzACPzyOXI60uOgAAAADEldaaAZK12vJbb72lv/3tb9qzZ48kafPmzdq7d2/GGgcAAABkSlsuIFzmLJMpUw7DkVJmACWDAAAAAGRLWtOONmzYoB/84AeqrKxUU1OTTjvtNHXp0kX33HOPGhsb9dBDD2W6nQAAAECrtOWaASXOEsmUDCO1zIAGT4O6lHXJaLsAAAAAQEozGHDttddq7NixWrlypXr27BnYfv755+uKK67IWOOQP0pKSnTttdcGHqN943wDAPJJpq5L2Q4G2I8XyAwQmQEoXPQJAQCIj2tlYSvG85dWMGDRokX64IMPVFpaGrJ98ODB2rRpU0YahvxiGIa6d++e62agjXC+AQD5JFPXpaxnBnhCMwP86wfYt0cTnhkAROXeK624QfI2SUf8r1TWI+sfSZ8QAID4uFYWtmI8f2kFA3w+n7xeb8T27777Tl26kNYMAACA/NOWZYLKnGXymT45DSeZAWg905TeP0/a+q71fNdy6QdLJCPtJeAAAABQhNLqPZ522mmaNWtW4LlhGNq7d69uu+02nXnmmZlqW1QPPvighgwZovLyco0ZM0YLFy6Mu/+CBQs0ZswYlZeXa+jQoVHXM3jhhRc0cuRIlZWVaeTIkXrppZci9tm0aZMuueQS9ezZUx07dtThhx+upUuXZux75Tuv16s333xTb775ZtRAENoXzjcAIJ9k6rrUmmBAfb10333Sv/4Vex/7oH+5qzzq9mhCggFkBiCa7QulrW9L8ll/di2Xvnsl6x9LnxAAgPi4Vha2Yjx/aQUD/vznP2vBggUaOXKkGhsb9dOf/lT777+/Nm3apLvvvjvTbQyYO3eurrvuOt18881avny5xo8frzPOOEOVlZVR91+3bp3OPPNMjR8/XsuXL9dNN92ka665Ri+88EJgn8WLF2vSpEmaPHmyVq5cqcmTJ+uiiy7Sxx9/HNhn165dOu6441RSUqLXXntNq1at0v/93/8VVRqJ1+vV4sWLtXjx4qL54ShmnG8AQD7J1HUp3WCAxyOdfrp07bXS+edLf/5z9P3s5YBKnVY5TVNmwmBAvbs+8JjMAET1+R2S4bRtcEifT7cyBrKIPiEAAPFxrSxsxXj+0ioTNGDAAK1YsULPPPOMli1bJp/Pp8svv1wXX3yxOnTokOk2Btx77726/PLLA4sUz5o1S2+88YZmz56tGTNmROz/0EMPadCgQYEshhEjRmjJkiWaOXOmJk6cGDjGaaedpoqKCklSRUWFFixYoFmzZumZZ56RJN19993ab7/99MQTTwSOvf/++2ftewIAACDz0g0GPPectGhR8PlNN0mXXir17Bm6X0iZIFeZJMk0EwcD6prrAo/JDECEhq1S1VthG1uyA/aul7oMyUWrAAAAUIDSLjLZoUMH/eIXv9D999+vBx98UFdccUVWAwHNzc1aunSpJkyYELJ9woQJ+vDDD6O+Z/HixRH7n3766VqyZIncbnfcfezHfOWVVzR27FhdeOGF6tOnj4444gg98sgjmfhaAAAAaCPpBAN8Pmn6dMlh6zU3N1slg8K5ve7A4zJnSzBAppp9ZAagFba/H+MFQ9q1rE2bAgAAgMKWVmaAJK1du1bvvfeetm3bJp/PF/La73//+1Y3LFx1dbW8Xq/69u0bsr1v376qqqqK+p6qqqqo+3s8HlVXV6t///4x97Ef89tvv9Xs2bM1bdo03XTTTfrkk090zTXXqKysTJdeemnUz25qalJTU3B2WG1tbUrfFwAAAJkVPvhvH4SP5YMPpDVrQrf5fNL990t/+INkGMHt0dYMSCYzICQYQGYAwm19TzJKJNMdut1wSDs+lXSUVF0d+tqWLdLu3dbj7t2l/v1DX+/VSxo0KDvtBQAAQN5KKxjwyCOP6H/+53/Uq1cv9evXT4btLsgwjKwEA+zHtzNNM2Jbov3Dtyc6ps/n09ixY3XXXXdJko444gh98cUXmj17dsxgwIwZM3T77bcn8Y0AAADQFtIJBrzzjuR0SuElRHfulL79Vho2LLjN7QsO1gaCAawZgNaqeisyECBJpldavVC6/C9SY/KLYUuSysutKBcBAQAAgKKSVpmgP/7xj7rzzjtVVVWlFStWaPny5YE/y5ZlJ1W1V69ecjqdEVkA27Zti5jZ79evX7+o+7tcLvVsKfIaax/7Mfv376+RI0eG7DNixIiYCxdL1toDNTU1gT8bN25M/CUBAACQNY3e0AHTZGbhv/22lQkQzjCkJUtCt0UrEySFLiwcjX2tgWTXMUAO9OplDaKnqrzcem86GrdLe9bGfn3HjtQDAZL1nvBsAgAAALR7aQUDdu3apQsvvDDTbYmrtLRUY8aM0fz580O2z58/X8cee2zU94wbNy5i/zfffFNjx45VSUlJ3H3sxzzuuOO0Jiw/fO3atRo8eHDM9paVlalr164hfwAAAJA74QPtiWbhNzZKH30ktSSWhnA4IoMBHp8n8Li8JDhonGiA3/46ZYLy2KBB1mz6pUuDf55+OnK/p58O3ac1M/C3xVovAAAAAEhdWmWCLrzwQr355puaMmVKptsT17Rp0zR58mSNHTtW48aN08MPP6zKyspAOyoqKrRp0ybNmTNHkjRlyhTdf//9mjZtmq688kotXrxYjz32mJ555pnAMa+99lqdcMIJuvvuu3Xuuefq5Zdf1ltvvaVFixYF9pk6daqOPfZY3XXXXbrooov0ySef6OGHH9bDDz/cpt8/l0pKSvQ///M/gcdo3zjfAIB8kqnrUvjgf6JB+o8/ltxRqrNIVtmgTz4JPjdNM1AmyJChUmdp4LVEmQEhwQDKBOW3QYMSD+yPGCEdeWRmPm/n0ujrBfgZzsx8Tgz0CQEAiI9rZWErxvOXVjDggAMO0K233qqPPvpIo0ePjvjLuuaaazLSuHCTJk3Sjh07NH36dG3ZskWjRo3SvHnzAjP0t2zZElK6Z8iQIZo3b56mTp2qBx54QAMGDNB9992niRMnBvY59thj9eyzz+qWW27RrbfeqmHDhmnu3Lk6+uijA/scddRReumll1RRUaHp06dryJAhmjVrli6++OKsfM98ZBiG+vTpk+tmoI1wvgEA+SRT16XwgXZ7eZ5o3n03+noBfnv2BB/bswKcDqdKHMH+cbzPCV9gmMwAhKhdba0NEEu81zKAPiEAAPFxrSxsxXj+0goGPPzww+rcubMWLFigBQsWhLxmGEbWggGSdNVVV+mqq66K+tqTTz4Zse3EE09MuI7BBRdcoAsuuCDuPmeffbbOPvvspNsJAACA/FLvCV0wONGM/Y8+ir5eQDT2AX2X4ZLLEexmxwsGuH1u+czgh5AZgBA1X0hK8h8hAAAAkEBawYB169Zluh3Ic16vVwsXLpQkjR8/Xk5ndlOSkVucbwBAPsnUdck/0G7IkCkzYWbAF19EXy/Az2XrSduP5XQ4VeK0ZQbECTqED/6TGYAAn0fam9v7LvqEAADEx7WysBXj+UsrGIDi4/V6A1kgxx57bFH8cBQzzjcAIJ9k6rrkH2g3DCOiPE/Evg3Spk2J2hV8bD9WibMkpExQ3M/xEAxADHXrJdOTcLdsok8IAEB8XCsLWzGev6SDAdOmTdMdd9yhTp06adq0aXH3vffee1vdMAAAACCT/Av1OgyHfKZPHp9HXp9XTkdkp/+rr+JnBUihr9sH/J2GM6RMUNxgQHhmAGWC4Fe7JtctAAAAQDuTdDBg+fLlcrvdgcexGIbR+lYBAAAAGeYv1+MwHMFt3iZ1dHSM2PfLL1M7dkhmgKMkpEyQ2+eO+b7wTIB6d32MPVF0ar+UDGfWFwkGAABA8Ug6GPDuu+9GfQwAAAAUAn9df3swoNHTqI4l0YMBLpfkSbJKS0hmgCP9zIC65rrkPhDtX+0aSUy0AgAAQOY4Eu8CAAAAFD5/ZoDTCJYF8pcOCrdmTeIyQXbx1gxwe5PPDKhzEwxAi9rVOV8zAAAAAO1L2gsIf/rpp/rnP/+pyspKNTeHznZ68cUXW90wAAAAIJP8A/b2WfuxggH//W/oAsHJHtt/fPtnxC0TxJoBiGXv+ly3AAAAAO1MWpkBzz77rI477jitWrVKL730ktxut1atWqV33nlH3bp1y3QbAQAAgFbx+DzyttRety8YHC0YYJrWAsKpiLdmgMcXe3Z3xJoBHtYMgCTTJzVuzXUrAAAA0M6klRlw11136c9//rOuvvpqdenSRX/5y180ZMgQ/fKXv1T//v0z3UbkAZfLpSuuuCLwGO0b5xsAkE8ycV3ylwiSEmcG7NwpNUZPGIjJHgwodZaGlAnymT55fd6QIIRfeCZArEwFFJmmasmMnVHSVugTAgAQH9fKwlaM5y+tb/nNN9/orLPOkiSVlZWprq5OhmFo6tSpOvnkk3X77bdntJHIPYfDoX333TfXzUAb4XwDAPJJJq5L9kH2RMGA775L/fjhwQb7Z0hWsKCDo0PE+8IzAwgGQJJUn8Y/wiygTwgAQHxcKwtbMZ6/tMoE9ejRQ3v27JEk7bvvvvr8888lSbt371Z9PanNAAAAyC/2QfYSR4kMGRHb/TZuTP34EZkBtjJB4a/bhWcG2IMKKGKxggGuLlJJ9zZtCgAAANqPtDIDxo8fr/nz52v06NG66KKLdO211+qdd97R/Pnzdcopp2S6jcgDXq9XH330kSTpmGOOkdMZmeaO9oPzDQDIJ5m4LoUEA2wD9bEyAwzDWjsgWSFrBjhL5DAcMmTIlBnxul14ZkCTt0mmacowjOQ/HO1Pw2ZJhiTbP8Luh0mnvS8ZJdK7E6Tti7LeDPqEAADEx7WysBXj+UsrGHD//fersaWQakVFhUpKSrRo0SL96Ec/0q233prRBiI/eL1evfXWW5Kko446qih+OIoZ5xsAkE8ycV2KyAwwDJmmGTMY4HJJ7rCS7YceKlVXS5s3Rx4/PDNAssoFuX3uiNftwjMDJCsgUO4qT/id0I41bpUMV+i6AWNmSc6OVqTqqAeleYdmvRn0CQEAiI9rZWErxvOXVjCgR48egccOh0M33HCDbrjhhow1CgAAAMikVMoEbd4cmRVw1VXSAw9INTXSuHHS6tWhr0cLBjgdzsTBAE9kMKDB3UAwoNg1bg19vs8RUt+Tgs+7j5b6nSrtSKOmFQAAAIpW0sGA2trapA/atWvXtBoDAAAAZIN/0N+QkbBMUFWV5PEEn3frJt19t/W4Y0fpjjukCy4IfU9ImSCHdXyXEexqN3mjrwUQLTOgwdOgfbRP/C+E9q1xq2Ta/hEOOFPyeST/wtQ+t7Xti7/lpn0AAAAoSEkHA7p3756wdqm/vqnX6211wwAAAIBMsQ/6+2fuGzKiBgM2bQp9/otfSB06WI9LSqTzz5f23z90n2ZvsxyGQ6ZpBoINLqdLcgdfjyZWZgCKXP0mhawX0Pf7VnkgP0eJ1O8USQQDAAAAkLykgwHvvvtuNtsBAAAAZE0gM8AwVOoslc/0yWE4YmYG2J1xRuTxTj1VWro0+LzZ22yVHjKstQIkyWk4Q16PJmowIMo2FJkG2z9CR4nU+zjJCKth222UtYYAAAAAkKSkgwEnnnhiNtsBAAAAZI29TFCps1SmrIzW8GCAaUo7dwafl5RIxx8v2dcS83ql738/SjDAMCQzWCbIXo4olQWEyQyAmrYHH/cYKzmjrCFhOKRuB0ta3mbNAgAAQGFLawFhSdq1a5cee+wxrV69WoZhaMSIEfr5z38esrgwAAAAkA/CMwPCt/vt2hW6XsDYscESQX4lJVZmwMyZwW1N3qaIzAD7mgEpBQPIDChungbJWx98vs/hkumzBv/tfG6p46A2bRoAAAAKW1rBgAULFuicc85Rt27dNHbsWEnSfffdp+nTp+uVV14hi6Adcrlc+tnPfhZ4jPaN8w0AyCeZuC7ZB/3LXGXWAzMyGBBeIujEE63gQPjH9ukj7bdf8HnUBYSdiYMBde66iG1kBhS5xq2hz7sOtxYPtgWxAjr0z2pT6BMCABAf18rCVoznL61vefXVV2vSpEmaPXu2nC05016vV1dddZWuvvpqff755xltJHLP4XBo//CV8tBucb4BAPkkE9elRk+jNXNfUpnTCgaYMiOCAVvDxmFHjYp9zAMOCD72D/YbMgLlgfxBAfvr4aIGA8gMKG4RwYARkiPKbZujROowMKtNoU8IAEB8XCsLWzGeP0fiXSJ98803+s1vfhMIBEiS0+nUtGnT9M0332SscQAAAEAmNHoa5TAcMk1T5S6r/noywYDRoyOzAiQrW8B+32Af7PeXCUomGFDvro/YRmZAkQsPBnQ7JLJEkF+WMwMAAADQvqQVDDjyyCO1evXqiO2rV6/W4Ycf3to2IQ95vV598skn+uSTT+T1enPdHGQZ5xsAkE8ycV1q9DTKMAyZMoOZAWZkMKCqSnK09JANQzrwwOjHM83YwYB0FhB22AZ7w9uEItO4LfjYWR5/wN8VZWHhDKJPCABAfFwrC1sxnr+0ygRdc801uvbaa/X111/rmGOOkSR99NFHeuCBB/SnP/1Jn332WWDfQw89NDMtRU55vV699tprkqTDDz88JCsE7Q/nGwCQTzJxXfKXCUomM8DplHw+ad99IxcP9ispkYYNCz5v9jbLlClDRtTMgCZPU9Tj+EsCuRwuNXubZcigTFCxc9dKhlMyvVKXA2NnBbQB+oQAAMTHtbKwFeP5SysY8JOf/ESSdMMNN0R9zTCsGy3DMIomqgIAAID85R/0NxUMBti3+23fbs36l6SDD45/zMGDg4+bvc2B/m9gzYAkMgP8n+8PBkiUCSp6njqpZX0Lddo//r69eknl5VJjitkk5eXWewEAAFBU0goGrFu3LtPtAAAAALKm0dMoU9Yof4eS4HT/8Jr9e/daWQGSNHy49dgRY2J2p07Bx83eZvlMnxyGI5ARUOoslWQtKpwoGOA0rFlIhkFmQNHz1lk1qkxJHQdKpi92dsDA/tKaNVJ1dXDb6tXSJZeE7vf009KIEcHnvXpJgwZlvOkAAADIb2kFAwbbp0GF8c+IAgAAAPJFo6dRZsuUf3tmQLxgwODB1kLBpaWJj+8vE2TKDJYJaskMcBiOmMEAf/kge0khMgOKnKdOLXErqeN+ks8jOeP8Ixw0KPHA/ogR0pFHZqyJAAAAKExpFaCcPHmy9u7dG7F9/fr1OuGEE1rdKAAAACCTGr3RMwPCZ+Hv2RN8PHBg7KyAcNX11sxsr8+rN799UzfOv1Hf7vpWkuQzfaptqo14j8/0ye1zS5JKXcHBXjIDipynToFoQMeB8dcMMNKa2wUAAIAilVYwYNWqVRo9erQ++OCDwLannnpKhx12mPr27ZuxxgEAAACZYM8M6OjqGNgePgvfHgwYPFhyxRlrtS+N9cW2LyRZaxIs3LBQf/7oz1q3a11wW+XCqG3yK3VYwQDTNMkMKHaeeqs0kCR1GCA54vwjJCMbAAAAKUhrKsnHH3+sW265RSeffLJ+85vf6KuvvtLrr7+uv/zlL/rFL36R6TYCAAAArdLgboiaGRC+gLA9+XW//eIf0+eTnFapf3lMT2C71/TKa3pD9vWXAwpvkx+ZAQjw1EmyBQMAAACADEkrGOByufSnP/1JZWVluuOOO+RyubRgwQKNGzcu0+1DnnC5XPrJT34SeIz2jfMNAMgnmbgu2QfeO5YEMwOavKGD9HV1wce9e8c/pn1Sttfnjb2jFHXNAPugv38dA1MmwYBi57GVlCrvk7t2iD4hAACJcK0sbMV4/tL6lm63W7/73e/0wAMPqKKiQosWLdL555+vxx9/XGeeeWam24g84HA4dNBBB+W6GWgjnG8AQD7JxHWp3hNcKDgkGBA2Y7+hZRy+c2epvFxx2e8XfP6yLjH41wYI+Sx3ZDAgfDuKkLulVpXhkEq757Qp9AkBAIiPa2VhK8bzl1YwYOzYsaqvr9d7772nY445RqZp6p577tGPfvQj/eIXv9CDDz6Y6XYCAAAAabMPsHcq6RR4HJ4Z4A8G9OuX2vETBQOSzQyQpDp3XcS+KCKelvNf2lMynLltCwAAANqVtBYQHjt2rFasWKFjjjlGkmQYhm688UZ99NFHev/99zPaQOQHr9erFStWaMWKFfJ646fBo/BxvgEA+SQT1yX7wLs9M8A+SO/zSY0tSwj07Zva8VubGdDBFVzHoK6ZYEBR8wcDylP8R5gF9AkBAIiPa2VhK8bzl1ZmwGOPPRZ1++GHH66lS5e2qkHIT16vVy+//LIkaeTIkXI6maXUnnG+AQD5JBPXJftCwfZggMfnkdfnldPhDGQFSKkHA/yLE8fi8XkitvkDFIaMkMyAend9xL4oIv6SVnkSDKBPCABAbFwrC1sxnr+UMgOee+45NTcHZ0+tX78+JGpSX1+vv/zlL5lrHQAAAJAB9rUBylxlKnGUBF9rKRVkXzy4Xz8rUyBZppkgGOCNEgxoyQwwDEMdSoKZAQQDipyvJSrVIffBAAAAALQvKQUDfvKTn2j37t2B54ceeqg2bNgQeL5nzx5VVFRkrHEAAABAJtjXBih1lsrlCCbI+rMG7MGAvn0lT+T4fUyJMgOilgmyZwY4g5kB9iwGFBnTlPz/Vl1dpQTlpwAAAIBUpBQMCJ/xlGgGFAAAAJAP7JkBpc5SlTiDmQHRggG9e2f286OWCbJlBthLF9nXN0CR8TZI/sCSqxPBAAAAAGRUWgsIAwAAAIXEvlBwqbM0pEyQPxiwd29w/86dJcPI3OcnWjPAvoCwPXCBIuOxRaRcnSQRDAAAAEDmEAwAAABAu+bxeeQ1g+tclTpLVeosDTyPlhnQqZOU7PphviQWF4iVGeAwrO64fR0De0kjFJnwYACJ2AAAAMiglIMBb7zxhl555RW98sor8vl8evvttwPP33jjjWy0McSDDz6oIUOGqLy8XGPGjNHChQvj7r9gwQKNGTNG5eXlGjp0qB566KGIfV544QWNHDlSZWVlGjlypF566aWYx5sxY4YMw9B1113X2q8CAACANhBeg7/EURJSJshfrsceDOjcWXIk2VOu9yRe8NcejAh8rqdBhqz0gzJXWWAdA4/PI68vcn8UgYjMAAAAACBzXIl3CfWzn/0s5Pkvf/nLkOdGJvOpw8ydO1fXXXedHnzwQR133HH629/+pjPOOEOrVq3SoEGDIvZft26dzjzzTF155ZV6+umn9cEHH+iqq65S7969NXHiREnS4sWLNWnSJN1xxx06//zz9dJLL+miiy7SokWLdPTRR4cc79NPP9XDDz+sQw89NGvfMV+5XC5dcMEFgcdo3zjfAIB80trrkj0Y4DAccjqcCTMDunRJ/vh7m/cm3Cda9oA/M8CUqTJnmUqdpYHSQQ2eBnUu7Zx8I9A+hAcDsnhvlQz6hAAAxMe1srAV4/lL6VsmkwKdTffee68uv/xyXXHFFZKkWbNm6Y033tDs2bM1Y8aMiP0feughDRo0SLNmzZIkjRgxQkuWLNHMmTMDwYBZs2bptNNOU0VFhSSpoqJCCxYs0KxZs/TMM88EjrV3715dfPHFeuSRR/THP/4xy980/zgcDh1yyCG5bgbaCOcbAJBPWntdsgcD/KV4ypxlEa+nGwyoa65LuE+szABJMk1TZa6ykABFg5tgQFHyhgcDclvVlT4hAADxca0sbMV4/gpmzYDm5mYtXbpUEyZMCNk+YcIEffjhh1Hfs3jx4oj9Tz/9dC1ZskRutzvuPuHHvPrqq3XWWWfp1FNPTaq9TU1Nqq2tDfkDAACAthctGBArM8BfGqhTChVa6tyJgwFmlOLv/vJEPtMXsY6BP1CAImMvOeXqLBlJLlwBAAAAJCHt/Ic1a9bor3/9q1avXi3DMHTwwQfrV7/6lQ4++OBMti+gurpaXq9Xffv2Ddnet29fVVVVRX1PVVVV1P09Ho+qq6vVv3//mPvYj/nss89q2bJl+vTTT5Nu74wZM3T77bcnvX++8/l8Wr16tSQrw8KRbBFdFCTONwAgn7T2uhQSDGhZK6DMFT0zwOGQfL4UgwFJZAb4zChlgjwNMlv+85cJCrzmJhhQlELKBKWQnpIl9AkBAIiPa2VhK8bzl9Y3fP755zVq1CgtXbpUhx12mA499FAtW7ZMo0eP1j//+c9MtzFE+JoEpmnGXacg2v7h2+Mdc+PGjbr22mv19NNPq7y8POl2VlRUqKamJvBn48aNSb83H3k8Hj3//PN6/vnn5fF4ct0cZBnnGwCQT1p7XYoaDIhRJsjfLezQIfnjJ5UZYEbJDPA0BLaXucpU7ioPeQ1FyB4MKMl9mSj6hAAAxMe1srAV4/lLKzPghhtuUEVFhaZPnx6y/bbbbtONN96oCy+8MCONs+vVq5ecTmdEFsC2bdsiZvb79evXL+r+LpdLPXv2jLuP/5hLly7Vtm3bNGbMmMDrXq9X77//vu6//341NTXJ6YxM3y0rK1NZWVnEdgAAALStaGWC7APv0dYMSCkYkERmQKwyQf6MgVJnaUi2ApkBRcpTJ2u+ls8qEwQAAABkUFqZAVVVVbr00ksjtl9yySUxS/a0VmlpqcaMGaP58+eHbJ8/f76OPfbYqO8ZN25cxP5vvvmmxo4dq5KSkrj7+I95yimn6L///a9WrFgR+DN27FhdfPHFWrFiRdRAAAAAAPKHPRjgL8XjH3g3ZIQEA0xTKimRXClMmal31yfeKcb7/EGCMieZAZC1gLB/0WBXx9y2BQAAAO1OWpkBJ510khYuXKgDDjggZPuiRYs0fvz4jDQsmmnTpmny5MkaO3asxo0bp4cffliVlZWaMmWKJKs0z6ZNmzRnzhxJ0pQpU3T//fdr2rRpuvLKK7V48WI99thjeuaZZwLHvPbaa3XCCSfo7rvv1rnnnquXX35Zb731lhYtWiRJ6tKli0aNGhXSjk6dOqlnz54R2wEAAJB/ogUDSp2lMmTIYThCggE+n9S1a2rHTzcYYC8vVOYqCyldRGZAkfLUSWqpVeUkGAAAAIDMSisYcM455+jGG2/U0qVLdcwxx0iSPvroI/3zn//U7bffrldeeSVk30yZNGmSduzYoenTp2vLli0aNWqU5s2bp8GDB0uStmzZosrKysD+Q4YM0bx58zR16lQ98MADGjBggO677z5NnDgxsM+xxx6rZ599VrfccotuvfVWDRs2THPnztXRRx+dsXYDAAAgd+zBAH9GQKmzVA7DIcMwIoIBqSweLKU/i98+4F/mLFOHkmBtInubUUQ8dVYswJTkTKFWFQAAAJCEtIIBV111lSTpwQcf1IMPPhj1NclamNfr9baiedE/2/4Zdk8++WTEthNPPFHLli2Le8wLLrhAF1xwQdJteO+995LeFwAAALkVEgxwBoMBhmGElAmqrbX2STkYkOQs/iZPU8i6APaMglJnKWWCIHnqrUCA4ZCcrD8GAACAzEorGODz+TLdDgAAACArogYDHKURr+/ZYz3PVmbA3ua9MYMBZa6yQLaCz/RRJqhY+ZolmZQIAgAAQFakFQywa2xsVHl5eeIdUdCcTqfOPffcwGO0b5xvAEA+ae11qdHTGBhkt5cJMlpqs/uDAQ0t4++pBgOSLemz171XPdUz6vvKnNaaAf51DMgMKFY+SabkSvEfYZbQJwQAID6ulYWtGM9fWsEAr9eru+66Sw899JC2bt2qtWvXaujQobr11lu1//776/LLL890O5FjTqdThx9+eK6bgTbC+QYA5JPWXpcaPY2BgX97MECSTJmBQXl/dctsBQPqmutCnoevZVDmLAuULiIzoEiZLRnYeZIZQJ8QAID4uFYWtmI8f4503nTnnXfqySef1D333KPS0mCK9ejRo/Xoo49mrHEAAABAazV6GmUYLcEAZ1gwwDTV6LUG5f2VMLO1ZkC8YECps1RlLiszwJBBZkCx8gcD8iQzAAAAAO1LWsGAOXPm6OGHH9bFF18ckkJx6KGH6ssvv8xY45A/fD6f1q5dq7Vr17JmRBHgfAMA8klrr0vf1X4nr8+a9v/hxg814f9N0HNfPCePzyOv6VVlTaUkyTSt/VMNBjR5m5Lar84dGgywv6/MWRYIUEjJBxjQ3rT8I3TlR2YAfUIAAOLjWlnYivH8pRUM2LRpkw444ICI7T6fT263u9WNQv7xeDx65pln9Mwzz8jj8eS6OcgyzjcAIJ+09rq0ZPMSmS2DrFvrtmr+t/P17e5vA9u+3G5NZrFnBqRyL5BsmSD7gsFur1s+M/gh/jJBfmQGFCnTZ0WljFYv7ZYR9AkBAIiPa2VhK8bzl1Yw4JBDDtHChQsjtv/zn//UEUcc0epGAQAAAJnS7G2O/7rPet0fACgtDWYJJKPJk1xmgD0YED7Y7y8TJFnrGJAZUKT8ASIjrds0AAAAIK60ppzcdtttmjx5sjZt2iSfz6cXX3xRa9as0Zw5c/Sf//wn020EAAAA0paojI/HZ80C8gcDDCPFYECSZYJCggFhg/1lTiszwJQp0zTJDChaPkkmwQAAAABkRVq9zB/+8IeaO3eu5s2bJ8Mw9Pvf/16rV6/Wv//9b5122mmZbiMAAACQtkSZAeHBAEeKPeREx/erb46fGVDqLJVpmvKZPoIBxSoQhTJy2gwAAAC0T2kXozz99NN1+umnZ7ItAAAAQMa5vfHXtPIvLpztYIB9gN+eGVDiKJFhGCpzlcln+mTKDMkiQDEhMwAAAADZk3Yvc/fu3Xr00Ud10003aefOnZKkZcuWadOmTRlrHAAAANBaiQbr/Qv5+idlOxyplQlKKxhge+xyWPNz/GWCJKmuuS75BqD9CCwqTTAAAAAAmZdWZsBnn32mU089Vd26ddP69et1xRVXqEePHnrppZe0YcMGzZkzJ9PtBAAAANKSKDPAbBn59wcAjBQrtCQbDGh0NwYe2zMDSp2lIf+XlL3MAJ9XaqqWyvuk/kWRfSwgDAAAgCxKKxgwbdo0XXbZZbrnnnvUpUuXwPYzzjhDP/3pTzPWOOQPp9OpM844I/AY7RvnGwCQT1p7XXL74gcDfLIGYNMtE5To+H6xMgP8QYAyV1lgW1aCATuXSm+fIrlrpI4DpVPflzoPyfznoBXSjEhlCX1CAADi41pZ2Irx/KUVDPj000/1t7/9LWL7vvvuq6qqqlY3CvnH6XTqe9/7Xq6bgTbC+QYA5JPWXpe8pjep/dIOBiTIPPBr9ETPDPCZPs37ap4+3/Z5YFttU21qjUhk53LprZMlb0v5oYYqaf54acIHUqfBmf2sLNuzR3r9dcnrlSZMkHr0yHWLMijwbzU/MgPoEwIAEB/XysJWjOcvrWBAeXm5amsjb1DWrFmj3r17t7pRAAAAQKb4FwhOxB4MSGXNgGQzA+zBgI83fRx4vKNhh876x1kh+1btzeAEG9OUPr7CCgT4B5tNj9S4VVp2vTT+n5n7rCyrqZFOPVVassR6fvDB0oIFUp8+uW1XxlAmCAAAAFmUVi/z3HPP1fTp0+V2Wzc+hmGosrJSv/vd7zRx4sSMNhD5wefzaf369Vq/fr18/jtltFucbwBAPmntdclnJn5Po6cxZAHhVCSbGdDkaQo83rp3a9x9k81mSMrWt6Vdy2yzzluYHmnjC9Le9Zn7rCzyeKTTTpOWLw9u++or6YQTpMbG2O8rKIF/q3HKBNVVSjuXSZteldb9Xdq+OGvNoU8IAEB8XCsLWzGev7SCATNnztT27dvVp08fNTQ06MQTT9QBBxygLl266M4778x0G5EHPB6PnnrqKT311FPyeDy5bg6yjPMNAMgnrb0uJRMMqG2sTXsB4X277ht43MHVQQf2ODDwx27oPkMDj+vcdal9SGv89w7JiFED1XBK3z7Zdm1phblzpU8/tcoD+Xm90tq10r/+Fft9X38tjRollZdLxx4rbduW9aamL5ARECM1pa5S+vdw6fUx0oKzpcWXSPOPzVpAgD4hAADxca0sbMV4/tIqE9S1a1ctWrRI7777rpYuXSqfz6cjjzxSp556aqbbBwAAALSKGWtg1aamqUaGYdWaSaVEkCT16tAr8Pi4Qcdp/uT5geeld5TK7XPLaTjVtbxrYHsyCwT7fD45Uk1TCLfna2n7+7FfNz3S5nnSoX9o3edkmc8n3X67lbURPmnLNKXHHpN+/OPI961eLZ14orRrl5VZ8Mkn0vHHW6WF+vdvm7anxB8MiBXAaqqWfFHSIPZ+K/Uel712AQAAoF1IORjg8/n05JNP6sUXX9T69etlGIaGDBmifv36yTRNGalOpQIAAAByzAoGWI9TzRBu8gbL/5Q6S0NeczqccvvcMgxDzd7mwPZkggF7m/eGBBDSsuk/spKB43wpM/9nQb38slUSKJYdOyK3maZ06aXSzp3BbAKvV1q3Tpo6VXr22ey0tVUCGRzFkaYOAACAtpXSVCPTNHXOOefoiiuu0KZNmzR69Ggdcsgh2rBhgy677DKdf/752WonAAAAkDW1TbWBtQJMM7VSQfaFgcODAS6HNffGUGgwoMHdkPC4uxp3Jd+IWL77V+J9jLSShdvUP/4hOWNUOpKir/Pw+uvWQsPesKUSPB7pueekb77JbBszo+UfXqrpKQAAAEASUgoGPPnkk3r//ff19ttva/ny5XrmmWf07LPPauXKlXrrrbf0zjvvaM6cOdlqKwAAAJAS+0B9PHua9rQ6M8CQERj897M/DwkGeJIIBjS0MhjQXCNtX6SEs8zzPDOguVmaNy9yUN8uWumgW26JHUBwOqWHH85cGzMmUZkgAAAAoBVSCgY888wzuummm/T9738/4rWTTz5Zv/vd7/T3v/89Y40DAAAAWmN34+6k9tvTtCcwuzzlYICnJRhgGCpxlIS8FisY4H9PPLubdqfWkHBVb0lmnBH0ArFggVSfuKpSiM8+k5Ytix1A8Hikt99ufdsyLrCAMMEAAAAAZF5KwYDPPvtMP/jBD2K+fsYZZ2jlypWtbhQAAACQCTWNNUntt6c5/WCAf5A/lcwA+zoDsSTb9piqP5SMksT75blXXpFcKVYy+te/4pcVklI/z23DsP6QGQAAAIAsSKlbvXPnTvXt2zfm63379tWuXRmobYq843Q6deqppwYeo33jfAMA8klrrku1TbVJ7be3eW9ImaB01gyIlhlgf55yMKCptcGAxZLpbt0x8sBrr1kz+VPx/PPxywpJiYMFORHIDMiPNQPoEwIAEB/XysJWjOcvpWCA1+uVK860HKfTKU+qPXUUBKfTqeOOOy7XzUAb4XwDAPJJa65LyQYD6prrQhYQToV9kD88M8DpsG4qTJkh+zV7mpVIsm2PyueVdi4P3eYokb73qNT3JGnDXGnFDekfv43s2pX6Qr/r10uff554v0TBgtxwKJ8yA+gTAgAQH9fKwlaM5y+lYIBpmrrssstUVlYW9fWmpsQznAAAAIC2knQwwF2Xdpkgt8+afW/IUIkzNDOg1FEqyepHhwQDfImDAXua9qTWELu6dZIvbPHkcf9PGnSBZDilkb+11hNYWZH+Z7SBTz+N3OZ0SpMmWaWDnn3WWmDY7vXXrcyOVIM6eYEFhAEAAJBFKQUDfvaznyXc59JLL027MchfPp9PW7ZskST1799fDkdKy02gwHC+AQD5pDXXpT3NyQ2o17nr0i4TZB/kjygT1BIcMGWGlAZyexOX79nbvDf5RoTbHTY1fp/DpcGTQreN+I20Zlb6n9EGli+3Bv/9s/idTunpp6Uf/9h6/uMfS+efH/qeDz+09ivMhGWjJZKRH2kL9AkBAIiPa2VhK8bzl1Iw4IknnshWO5DnPB6PHn30UUlSRUWFSktLc9wiZBPnGwCQT1pzXUp2QL3eXR/IDPB6UwsG2Af2Yy0g7DN9IUEDfzZBPK0KBtR8LhkuyWwZER9+reRzW6WCAhzSgVOk716JfZydS6VNr0quTtLQn0tlPdJvUxr++9/Q55dfbmUF+E2YIE2bZmUD+L3/fmQgYMQI6YgjpEWLpMrK7LW31QyHtVyAtz7XLZFEnxAAgES4Vha2Yjx/7T/cAQAAgHbLuN2QcXvskft0ggH19VIqk4LsA/sRZYKcwRuKJk8wM8DrSzzzu85dl3wjwu3+PFgnp7yvtP/FYYEASQ6ndNCvI7f7ffuk9MYx0ufTpeU3SK+PkWpWp9+mNCxbFswKMAzphhtCy/84HNJ111klgySppkbasCH0GKedZh3n73+3Mg0OO6xNmp4ewyEZkjytOPcAACB/mD6pdq3Vh/IVZNoi2hmCAQAAACh4nhg3V8kGAxrcDYEAQF2K47D2z46VGSCFBgN8SdSEr2tuxYDwrmWSWkbRB/84WIs+XFlPqdexkds3/Uf66OdWZoHpleST6jdK88dL7lasZZACt1v66qvg8zPPlIYNCw3UGIbUp490+unW8/BMgq5dpRdflEpKgs9ffjm1YE+b8p8nggEAABS+5t3Se2dJ/xkuvTpSeuskqXFbrluFIpev3WAAAAAgadvrtkfdnuzs+kZPY2CAeG8K1XlM0wwJBoSvGWDPDGj0Bhf0TSYYUO9Os1SMzyvt/Tb4vPdxsVfT9bmt9QTsvI3Sp1cr4lbB9EruXdJXD6fXrhStWRNa7ufaa6OvA+D1SpdcYj1euTK0xNMvfyl16GCtISBZGQSDB0s/+lH22t06hvXHkx9lggAAQJo8ddLrR0lV84PbdnwkvXa41LQrZ80CCAYAAACg4G3ZuyXq9vrm5AZVGz2NgQHjVDID7CWCTJlJlwkyFWNw3ibtYEDzjtAFaPucIDliLBVmOKV9jgjdtuYvVhaAogQsTJ+04Zn02pUi+yz/0lLpxBOD5YDsnE5p+HDr8cqVwYH/0lLp+usjswA8HqmiIjttbjVHqSRD8pIZAABAQfv8j9bkDHufzPRamQFr789du1D0CAYAAACg4FXtrYq6PdkB9UZPo/zrhaUSDAgZ4DfNiDJB9mCAfQHhZDR4GlLaP6DRliXRcT9rzYBYDIfUdUTwuemTvvyLFC9YEavkUIZt3Bgc2D/ySCmZ9dyWLQtmD0ycaJUQCl8M2uWyjjd6dGbbmxGuTtb/TZ+U4r8XAACQJ2q+lFbPVPSJFV7pu3+1dYuAgBhThAAAAID81ugJlt2JGQxIstxKk7dJ3btYj1MJBoQP8IeXCbJnCjR5rcCBz5e4RJBk+36VlVJ1deiLW7ZIu3dL3btL/fuHvuayFdrvMTbxB9mzGbYtkBqjZ1kEmG2z+N22bdasfq9XOu446//+4EA4t9t67YsvgttOPdXaXhJlfWSPRzr66Oy0u1WcHYOPvQ2SM4kICAAAyC9f3hv/9TaaWAFEQzAASXE6nTrxxBMDj9G+cb4BAPkk1nVp696tgcexggFJVOOxdjNNdWllMMBn+qIuIGzIkCkzsO/uxt1JHbvR02gFAoYPlxobE7/B7/gS6X9aHncfZa0L4IgyIh7Nt3Mkw9VmA/7xbN8u+eMmRx8de9kDyQoE7N4d+td08snRAwGSlS0wZkzGmpo5rk4K/KP11kvqlsvW0CcEACCBiGulp15a/4/4fSl76SDkVDH2dQgGIClOp1MnnXRSrpuBNsL5BgDkk1jXJXsAIFYwYHTf0XrxyxflM30qd5Vr9lmzA6/dvuB2rd+9XoYMjeo7Sr7O1kz0dIMB0dYMKHGUyDAMmaapZo+1767G5BaNa/I2WRkBqQQCJKncLWshWlPqNqrlcRz+YIG3WaqcmxeBAMnKDPC23CuPGRN9vQA/h8Pa369vX2n//WPv73RKhx6akWZmlquTVSJIyotFhOkTAgAQX8S1cv2/WPungBRjX4dgAAAAAApSMsGAZm+znIZTPtOnTiWddNnhlwVee3TZo1q/e70kyePzqEun1gUDJMXMDJCkZl+KwQDbegQp6SpZS4N5pR5HxF482M9omQW142OrNE2e2LzZ+n95uTR4cOL97cGA730v8f4dOqTXrqxydVKgvrBnb06bAgAA0vDtk1bfitn/yFMEA5AU0zS1fbu1GF3v3r1lhK/EhuzyNFg3hGU926S2HOcbAJBPYl2X7AGA72q/i/pe+7oC4bP2y13l1vFlqtHdqH6drPIxjY1WeRpHEpfchGsGtGQGyJTcXrckqaaxJvGBoxw7aV0kKxvAkDoPTby/v2+x9Z3Im9fuh0oHXS017ZC+uFPytN1Mt5ZTrpEjY68VYGcPBhx2WOz1AvKafwFhSfLsyV07WtAnBAAgvpBr5T6dZWx9j0BAASnGvg4rViApbrdbs2fP1uzZs+V2u3PdnOLhbZJWVEjPdZZe7CO9eoi0a0XWP5bzDQDIJ7GuS/ZgwOY9m6O+1x4MKA1bjLXMVRZ4XO+uVyfbOGyylXkiggHhZYKcJYHMALfPanuyawakHQzoKkleqaxHcNZ/MrYvCpaokaS+35dO/0ga+gtp5A3S6Z9IJd3Ta1OKTFPascN6fMghyb1n61YrmCNZwYBE93J52cWxBwPcuQ8G0CcEACC+kGtl1SLJDLteujpJB0+TRtzQZv0oJK8Y+zoFFwx48MEHNWTIEJWXl2vMmDFauHBh3P0XLFigMWPGqLy8XEOHDtVDDz0Usc8LL7ygkSNHqqysTCNHjtRLL70U8vqMGTN01FFHqUuXLurTp4/OO+88rVmzJqPfC4jg80hvnyytuluBdPE9X0mvHyVtmZ/TpgEAkA/swYDt9duj7tPoaZTZsiBrRDDAaQsGeKxggH+R2oYkq+UkUybIz58ZUNtUm9Sx/cGDlHWTJFMq6538e0xTqv5YgcVrDaf0vUckR6lVZshwSl2GSyNvTK9NKaqrk5pb/mr79ZM8SSxjsG1bcF2BsWPjrzEgJZdt0OZCMgPqQoMzklTWS3KUR76vtHtWmwUAAJJQvTh0IkZ5X2syxRH/Kx1+l3TGcqnT/jlrHiAVWDBg7ty5uu6663TzzTdr+fLlGj9+vM444wxVVlZG3X/dunU688wzNX78eC1fvlw33XSTrrnmGr3wwguBfRYvXqxJkyZp8uTJWrlypSZPnqyLLrpIH3/8cWCfBQsW6Oqrr9ZHH32k+fPny+PxaMKECapLpaAskKov7rIuJP6bcslKNTN90oeXSM27c9UyAADywpa9WwKP6931qmuO7Js1ehplmtGDAaXOUjlaSuQ0uBtCggHJdvOSKRPk5/F5ZJqm9jSFzvg2ZMhhOAJtse+flm4t/08lGLDnq9CyNEN/YZUYst/QOpzSwVOlsj7ptSsF222xnd69rbJNifjLBDmd0qBBifdPpgxUm3N2DD721EWWGeg0SPrhGmnc06HbO/TPftsAAEB81R+FBvIPu0vqcpBVktFwSh33lcbMylnzAKnA1gy49957dfnll+uKK66QJM2aNUtvvPGGZs+erRkzZkTs/9BDD2nQoEGaNWuWJGnEiBFasmSJZs6cqYkTJwaOcdppp6miokKSVFFRoQULFmjWrFl65plnJEmvv/56yHGfeOIJ9enTR0uXLtUJJ5yQra+LYrb7v9J/b1dIICDAJzXvkFbPlA77Y1u3DACAvBG+TsDWuq0aWhpaI7/R0yhfy02ZPRNAsoIB/hI+DR4rGOBtGXtNNxgQLzPAlCmv6dWQfYaE7HPGgWeoc2lnSdLSzUv17a5vZcpUj/IeyTUiXJeW/5enEAzYEZwII8PZ0scwJYXV2jEc0rBfpNeuFNjr//fpk7jkj/89Ho+1f14O9CcjPDMgWl+w0yCp24g2axIAAEjSDluWZbdR0tDLQtd9dJRIA8+VvnslF60DJBVQZkBzc7OWLl2qCRMmhGyfMGGCPvzww6jvWbx4ccT+p59+upYsWRKoAxVrn1jHlKSaGmvRtx490rxBAxJZfW/8hYJNr7T59divAwBQBOyZAVJo2SC/Bk9DoEyQfY0AqSUY0DLK3OhpDFkzYO/e5NrQ5G0KeR5tzQC7Zm9zxIz/v539N829YK7mXjBX5ww/JxBACM8USIohyf89ynpHlpmJZccSyWhpa8+jpfI+0fsijhKp36mptytF9syAPn0Sl/yRpM2brcyOPtlPXMieiDJBuWsKAABIkcfWgTzsrugLCfs80vBr265NQJiCyQyorq6W1+tV3759Q7b37dtXVVWRN36SVFVVFXV/j8ej6upq9e/fP+Y+sY5pmqamTZum448/XqNGjYrZ3qamJjU1BW8Oa2uTqw0LqGGrtP5pyUxQGqAIVjgHACAW0zRVXV8dsi1aMKDeXR94HC8zoMnTFBIM2JPk2q2pZAb492/whC5IYG+X/XH4fknpqOB0n/Le1k1oMkGFuvXBvkf/060bVUeMW4Wy7E+IsWcGDBiQXLfH331vN8EAb11EYgYAACgArs7SgB9YkyjCOVzSPoe2fZuAFgWTGeBnhN0JmKYZsS3R/uHbUznmr371K3322WeBEkKxzJgxQ926dQv82W+//eLuDwR884gCCwbHEy3CDABAkahpqokYiI+aGeAODqiXu0IXXrWvIdDkjQwGmEnMyk5mzQDTNr27ydMU0iYpNGMhpE2e0KyDpHS1H7h3cl9CkuorFZiGvu9Z8QMIvuz3QbZvD2YD9E6y2lF1S2yo3QQDPHUiGgAAQAExWjovfU+OHgjwS7Z/BmRBwWQG9OrVS06nM2LG/rZt2yJm9vv169cv6v4ul0s9e/aMu0+0Y/7617/WK6+8ovfff18DBw6M296KigpNmzYt8Ly2tragAwJOp1Pjxo0LPEYWrX8m+ZT+LOF8AwDySbTrUrSB/1hlgvyiZQb4hWcG1NVZ6wckKk8TEQxIokxQg6dBhoxAkMDejjJXWWB7eAmipNjWn1VZ7+SyAiSpfrP1f2e51P2w5N+XJdu3B7MBWrrtcTU3B0s79eljnbt0uzA/ff6nKi8p1+PnPp7eAVrD2SH42FMXuoBzDtAnBAAgvsC1smq+nEbLWE7/0yWfO3ZAwPQGAwfIqWLs6xTMv7zS0lKNGTNG8+fP1/nnnx/YPn/+fJ177rlR3zNu3Dj9+9//Dtn25ptvauzYsSopKQnsM3/+fE2dOjVkn2OPPTbw3DRN/frXv9ZLL72k9957T0OGhC76Fk1ZWZnKysoS7lconE5nxNoKyIK6DVLtqtBtHQdJR9wjdRwoffO49G32b0w53wCAfBLtupR0MKBlFr4hQ6Wu0pDX7IPwzd7miGCAL4nYfDJlgkzb7K9mb7Ma3A1yGA55W7L8QoIBzrLA/m6fW94e+8hZXi41NiZujCTZ72HK+8Yu9WPn80pNLdPq9zki8Xsc2b9R2rXLmjTXqZOUTJc6fMHh1gQDnvnCygDOSTDAcEiOcsnXKLlrcx6UoU8IAEB8gWvle3+VNrdM5Oh7UvzMgDh9re3bpVmzpO++k4YPl665RurcOaNNhk0x9nUKJhggSdOmTdPkyZM1duxYjRs3Tg8//LAqKys1ZcoUSdZs/E2bNmnOnDmSpClTpuj+++/XtGnTdOWVV2rx4sV67LHHQkr8XHvttTrhhBN0991369xzz9XLL7+st956S4sWLQrsc/XVV+sf//iHXn75ZXXp0iWQSdCtWzd16GCbvYOsamqS5s2z0vaPOkoaMSLXLcqCqrdDn3caIp250pqlZ7ik3sdJ3UZIy3+bm/YBAJAnog38b9mzJWJbo8caRHcYjpBBdyl0EN5relXWwSN/93jnzuTa0extDpnln6hMkD8zwB8McDlcIQsF2zMDJKlxQB91WrMmWANHklavli65JPj86aeDHaP6ZVLlldbj8ujZsxGatitQorDn0S2z1XI7M8rjSW0x4PAFh9NdWsnMh7R9ZwcrGNC4LfG+AAAgP9RtsP7v6ix1HZ7WIZ57Trr8cqmhwerL+HxWYOC556STTspYS1HkCioYMGnSJO3YsUPTp0/Xli1bNGrUKM2bN0+DBw+WJG3ZskWVlZWB/YcMGaJ58+Zp6tSpeuCBBzRgwADdd999mjhxYmCfY489Vs8++6xuueUW3XrrrRo2bJjmzp2ro48+OrDP7NmzJUknhf3kPfHEE7rsssuy94XziGmaqqmpkWQFQeKt05AN8+ZJU6ZIGzdazw1DuvJK6f/+r51FSLe+aw36+xfwO/pRKxBgH1g4eJpU+bzka45+jAzI9fkGAMAu2nUpWjDguz3fRWzzl9oxDCNqMMA+8F5S1ix/93jrVsmRxKTsZm+zDMMIDCInmxkQ+Myw4EGps1Q+W7nABk+DOg0aJA0aFLsRI0ZIRx5pPa7aLfm7w84ks1QbNgcfdx9llSvMcTDA27IsQa9eye1vT5zo0yf9rAD7otT17np1LOkYZ+8scXWQ3Lukxq1t/9lh6BMCABBf4FpZs0fdTENGj7Fp9aM++EC6+GJrQoRddbV0zjnS55/H7w4iPcXY1ymoYIAkXXXVVbrqqquivvbkk09GbDvxxBO1bNmyuMe84IILdMEFF8R8PS9mCOWY2+3WX/7yF0lWBkZpaWmCd2TOu+9av/jsp8E0pccekzZtkl5+Of0bvlYxTWnTf6TPp0v1m6zI72F/tGbvp3u8qjeDgYAhk6V+J0fZzycd86S0eHLaTU8kl+cbAIBw0a5LVXurAjPyy5xlavI2Rc0MsC/CW+qIEgywdTCcZY3yF92vqkq8XoAUzAzwi7ZmQLTMgFj7h69rEL7YcEKmbXHfZG9E7cGADvvmRQ1bf2ZAslU37TfOAwYkF8iJZt3udYHH63ev18jeI9M7UGv4FxHOg2AAfUIAAOILXisvU8WwO1Xa/ZCWiRXJd0Z27bLGvaKVqDRNK1Pg2mull17KXLthKca+Tm6LUAIJbNggnXuu9csv/Jei12tlDDz4YA4aZprS4suk98+Rdi2TGrdI2xdK84+XPrstvWPu/TY0HXz41OgLCTtcUreDpR5j0vscAADaAXtmQJeyLpKkHQ07QmbVS7bMACXODHCUBQfetyY5DuvPDPCLViYofP8Gd0PUxYMlq0yQnT1wkJTWBgM6DUq/xk4Geb1WdyvZCR/2YEDXrul/7rpd66I+blP+YEBTdfS+IAAAyF8d9pV8nsT72fzf/0m7d8der8rjscbHgEwgGIC8dsstVgQ01i9E05T+3/9r2zZJklbeLK2f09KIlsb5b74/ny5tfCH1Y9Z+GXzcabDU44jYkWSfW+p3auqfAQBAO7F5z+bAgHqP8h6SJI/Po10Nu0L2sy/wGy0YYA8eeNSokpax+2SDAU2eppDMgGhlgsLb0+BpCGQkRAQDWp0ZYLv5TGbxYEmq3ywZLV+8vF9qn5cl/syAZLIzpGBZISn590Szfvf6qI/blMsKbsn0Ss27c9MGAACQng4DUppYsX27FQyINe7llwdzNdBOEAxA3vr8c+nvf4+sl5Zz2z+QVs2Iv88Xd6d+3LoNkn8wYeB5oTP7wjlKCAYAAIraptpNgcd9OgVXmbVnDHh8npDB/ngLCEvWYsPl5S3HiVySICp7sEGKXibIrsnbpEZPY6Bd4YP/0dqUkmQyA+oqpZ3LrD+bXpW2vS/JZ/Uvynqk9nlZ4h/cTyczoDXBAHuZIPvjNlXSJfi4iUWEAQAoKB33C133MYFHHpGak1gSkgrmyJTcFwQFYvjTn6wbwETBgDYNFpimtHSadXMdb7A+HXUbWhYPdkv9TpNMSfEiv6XdM/v5AAAUkKq64Gh9/y79A+sHVO2t0iF9DpEUOZCeTDCgY0dpzx5p505rQDreYLTXGxkMSCYzoN5dn8UyQfZpZVHm/dRVSv8eLvmiBBk6DEjts7LI379LNhhgzwxozVpS3+z6JvA4d2WCOss6dz6pYYvU9eDctAMAAKSu035J72qa0uOPh2YFuFzSL34hjRplLSo8d24W2oiiRjAAeam2Vnr++dCB/vJy6bLLpL59rUWDV6zIQcM2vyrt/CTxfmYaEYq6DZJ8VqCh70mSI8GdbIoL0gAA0F54fV7tbtwtSepU0kk9O/SUw3DIa3pDMgPswQBTZtLBAMm6Odu5U+rdO3Y7fL4omQFJrBlQ564LPC93lYe83uoyQfZsgGgTF5qqowcCpLwKBvhvipNdCDhTmQFf7fgq8HjtzrXpH6g1XJ2sPp7ps9Zz8HmSL/mUrMpKqbo6dNuWLVbB4u7dpf79rW15l6ILAECeS6Hk4pdfSt8E5yGoQwdp4ULpyCMlt1v69a+liy+Wzjsv881E8SIYgLw0b57U1BR8PnCg9OGH0r77WjeHv/+9VFEh3XNPGzds7QORWQEd+kudh0k1q6Tmnekfe++31nG7HxpcOC4eggEAgCK1vX57oMxOt/Ju6tGhhxwt18SYwQAzuWBA587B55s3xw8GGIY1uG9fhDipzIDm+sDz8GBAeJtSzgxIFAyIJ4+CAf4B/WTHou0z6pINIEQcw/Rp055g+akNu3O0Up+zo/WPy5RU/13mFxGurJSGD5cakyhBVVIi3Xyz9XjjRmnYsMy2BQCA9sTZMbTcXwL//rfVb/H3Yx54QDr8cKsbUNrSJTz7bOmmm6RXX818cwtac4309d+k6sWSs1waNEkaeA7jZEkgGICkOBwOjR07NvA42/71L+sm0OOxfgG+9JLUr5/1S9L/8TNmSJ99lvwCf8lYv156803rF/H3v2/dJwU0Vktb3pBsN/wa/QfpkJusenCeOmnZb6xfRumoW2/9v/OQ5PbP0Awxt9tKO5s3z/rep54q/fjHbXu+AQCIJ7wfYh/w79mhp3p06CGf6ZPDcLQ6M8AeDPj2W2n06NiDyy6X1OxLbc2AZm+z6j3BYEB4WaCIMkEpZwbY+gepZip26Jc3kw38wQBvkvEMe2mgZN8TbvOezfL4gn9ne5r3aHfjbnUv757eAdNlnxRS/13mswKqq5MLBEhy+Hwa+4mVFes480yCAQAAhHE4HBq7X41Uu1aOjn1Teu/LLwfXAjjvPOnnP4/cxzCk22+3+qVoUfW29P55kqdekmn1XTc8K+1zuPT9t6Tynkkfqq3HO/MBwQAkxeVy6ayzzmqTz2pulv7zn+BMsN//XjriiMj6r6YpPfusdM45rf/MujppyhRrwWLTDK7Sfu650hNPWNnS2vSKQgIBB/1aGn1b8Lmrk/S9h6zarvUbU2uAt9lK25ekToOtmXyxFv3LoK++kk47Tdqwwfr7NU0rMHDLLS69/fZZOuSQrDcBAICEwvsh9gH/3h17q0eHHvK2zIK3ryWQTmZA167B5999F5yYEEuzt1mmGTszIFqZoHp3MBjQwdUh5PWIMkGpZgY4WpEZ4CjLq2CAYSSfGWAvDZRuZZv1u9dH3XZ4v8PTO2C6XJ2CXc76jTk9Hy6vV2fNm2c9ueOOnLUDAIB85XK5dNbwKqnyNanD0Um/r7FR+uijYDDguuusPky0coder3ThhZlpb8HbMl9acLZVRlEtKRX+Pu/uz6VPrpROeDHpw7XleGe+yH1PHwizdKk1OC9JZWXS1VdHXwjO6ZS6dJFa+zNbUyOdcor0zDPBX8Kmaf3597+lK69s2XHjC8EB+l7HSGP+HHkw0ycd94zUYd/UGlG/UYG7vo6DJF+GFyeO4ssvpXHjrIEOybq4+FPTqqut4AgAAPloy54tkiRDhnp16qUeHXpIkrymV5v3bA7sl25mgH9SwMaNiUvONHubAyWLHIYjUK7Izx4ccBgONXub1egOtitizQBbZoDDcLRuzQBfiqPiDpdCJj7kkNNpnYe2zAyItmBwThYRdnVS4Oa2LkeligAAQExmeHfJ9FgbwyaBxPPNN8ExmCFDpBNPjL3uUUmJ9IMfpNfWguDzShv/Jb13tvTakdLCC6WqdyL/opt2Sh/8WPK5Fegr2Zme1CfnFiGCAUiKaZqqq6tTXV1dyOy3bFizJvj4Rz9qmZUfR2ujo1dcIS1ZEv3G0eu1Zs3L2yxVzQ9GG0dWRK/fajisX/6Df5xaI+w3ep0GZz0rwOORfvxja4246N/blM/XNucbAIBEwvshVXur5HK45HK41KO8RyAYIEmbaoM138MH0hMFAxo8DercORgA+Oqr+IvRut1Ssye4ZoAzyvXbXibIkKFmb3Ngtr/DcESUBbK3yZCRxpoB9inye1J8b/I3sNnmH9xPJzMg7WDA7ijBgCjbsq6kS7DPWZujRYxbmJLqOnZUXceO9AkBAEWtvl7685+tinlOp7TPPtLUqdKGDabqGk3VeTrITKEAy9dfBx//6EeJ+y/l5fFfL1jNu6W3T5IWni9teV3atVz67iXpnVOkRZMkr21B0eXXS+4axZ28kmJmbFuOd+YLygQhKW63WzNnzpQkVVRUqDRevnwrffWVFfV0u62B/lhpUpJ1sz4kyRL70bzwgvT88/H38XhkLe7rc1sbOu4n7Xt27JRtR4k08Dxrcbbq6tDXtmyxRuC7d5f69w9u3/1+8HGXYaEp/inw+rxy3eFS7469te2322Lu93//Z623EOv3XEmJWxMmzNTMmdk/3wAAJBLeD6naWyVD1vT9Hh1CgwFb64KLCdkzA6T4wQCH4VCjp1E9elj9C6/XyqKLZ9Om0M9wRrl+2zMDDMMKBjS13NQYMiLaZC8T1OrMgIatofUPE4mXGVBXaZU0bNhi3bR1Hir1Hpda21LgLxO0a1dy+9szA9zu9D4zajAgF5kBZX2Cj731UkOVtZ5DDrhLSjTzhhskSRVer+gRAgCK0bZt0plnSsuWWc9N0xra+etfpaefdutXvxolaZQqBnyU9LXyq6+s/ovXa60XkIjbbY2VtSvuvdL846Xalk63fyDf//+NL0hLe1gluWvXSN8+kfkmtOF4Z74gGIC8s3at9cuwvNxKg4o3I0+y9o1WRqimsUYljhJ1LO0Y9X1ut3TttdaNZsLg3x5busKgC5UwhX7LDmv14SQXZ9MESZNl5ep0HJzce6L4audXkqTt9dtj7lNTY5V8Df/O/sGP8PgFAAD5pmpvlbymV4aMiGDA7sbdcnvdKnGWpBQMMGSo0dOovn2DKdvffBO7n+H1Wq83eoOfEb5egBS6ZoAhQ02eJjV5WoIBhhGxRkDEAsKpZgbYj9e0zUqXTnrGf4ygQV2l9O/hki+sX3Pah1kLCPjLBG2P3aUJYe8vJhtACPf1jq8jtn27Ower9ZWHLT5Y84W1LdmgDgAAyJj6emn8eKvfFz6O4vVKe/faNhhxBrDCJlZ8/d9T5HD0k8NhlXCO1t+0a3eBAEla/hupZrWilvyRrO07PrEervmr9fdrtqSNdhoiHf4nazKuZ4+09n7pizvboNGFjzJByDurVlk34UccIXXokHj/aPdF9e56db+7uzrN6BTzfS+8YM3o8/8y79DBWqx43TqrRvCMGQouIli7NjjTbtAFinmz7LetKvlAgCQ5ZcUXDJdU1iPR3jGtrFqZcJ+nnrIuZn4DB0qvvirt2GHdcL/7rpX2BgBAVKYpufdI3hSucxm2ac8m+UyfvKZXPTr00D4d9gl5fVudlR2XTmZAv37BNG23u6VcYBRer7R+vQID+1KMYIAz9M6t0dMYWOzYUJRgQPgCwqlmBpT2tH3Y9iRmPNiYHkXt4zRVRwYCJCtzMks6dbL6eDt3Jlf2x34DvXlzMKCTim93Wd/HsP0dfL0zMkCQdR3CggG1q4MZqgAAoE1df71V0idWfyR0e5wMy38Pl14fYy1+u/gSrV2ySm63qSFDEgcC2qWqd6SvH1bsQICNt0la9/+CgYCOA6XTFkr7nS85S6WyntKoW6Rxc2JX8UAAmQHIK6YpfdtyX3nQQcm9J9rCfv/d+t+E73v44WBKVlmZ9PLL0sknB38JX3+99P3vS7/5jVoyAwzJWS71PDrxL5cogwFx+X/xhw0ApGrl1mAwYEf9DvXs2DNin0ceCT7u1096/30rIOB3/PHSm29Kjz/eqqYAANobT7305b3S149I9ZXWtt4nSAdfK+33ozZtin2A9ptd3+itb99SiaNE7pYB0zXVa7Rv131TCgZICmQG2H3+ubT//pH9jdJSawJB037xgwHh2+rd9SHPw9tgDx6YMlPPDCjvHXzctD21G6IcDDjv3i29+KIVWOne3UqTHzpU6t3yNUzTymrskWCuROfOwcdbt1plHlPJ8nZ73aqqq5Ik9erYS/XuetW561RZUynTNGW05az88MyA2jWp9y3j6dXLSsFNZeKKJPWM7FcCANCeffihNHt2Cm+I1ZeKMrHiy80HSzJ0wAFpN6+wrbzJmnTrLwnkKJMGXyR1PkDatULa9Erwtc2vSp7alv1KpJPflsr7hC7YbDilQRdJqfadixDBAOSVzZuD9yUHHig1N6d2I+e3vGp54LHX542o4bt+vfTee8HJck89FRoIkKx08zFjpHvvlbR7lRWB7HxwdqKM/hK9rVy4z/69V25dqZOHnBz6+nJrUMPvlVesQIA93czlSnzDDQAoMnu/lRacE5nGu32RtP19aeSN0mEz2qyMiX1dgDsXRqYDv7/hfZ089OSMBANWrbLKFkbrj6xbJzX3bw48t5cEirUtPBgQXhbIYTjkcrjk8XlkmmkEA1ydrJspX5MVDEhlEDlWZkAW+HzS3XdLf/iDlYHhclkTNH7zG2niROnYY4OLB2/fnrhv0sdWZn9b7GWTYtpYu1E+0/q33b9Lf9U21apud50aPY3aXr9dfTr1SXCEDHJ1siag+LNvdq3MbP9z0CBpzZrQ2pCrV0uXXBJ8/vTT0ogR1kl47TVr2377Za4NAAAUgD/8weqj+PskBx8s3XCDdNxx1rjSrFnSW2/Z3uDzJHXcxuYyVe221gM64IDYZSnbrZ3LpB0fB593GiKdukDqtJ8VUHGUWAGBt0+xXt/4r2DgYMilUpcDo993GA5pyCWR2xGC3AlkhmlKu/8rbX3PKqmTpq++Cj4+6KD0fxku27IseMydX0W8/vLLwd8bY8dKkyZF/yyXS/re92TNyJKkrkmmK6TK/9lRBhEC6iqtX5ibXpXW/d36s31xyC727x2tZNDrrwe/59lnS0cdFb3uXLusRQcASE/TTumtk1quheFpvC3Pt7zVZoGAHfU7Eu6zvma9JGtw32EbRE0mGNAvbJ3WDz6IHghoaLD6Lf7FgKXECwhLkWV/wssCScEAgs/0pV4mSJJKW0bOG5MsuO/nc7fJefR6pQsukG66yZr4YZpWQMBf2udf/5L+/vfgpI2qqsTH7Nkz2PRt2xKvORXOvlDwwK4DNbDLwKivtZkyW4bHjk8kb3PsfdMxaJB05JHBPyNGhL4+YoS1/fDDM/u5AAAUiK+/lubPDwYCjjlG+vRTK3Z+0EHWhNJ586Srr7a9yUwuGLBu+xCZLUOyBx6YXEnEduXrh4PrK3QaLJ22SOrQ0gn3j4t1O8QKELi6SDuXBrMERlYo/jqerLGUCMEAtI5pSmsfkF4eLM07VHr7+9J/hkv/Plja8FzKh/vmm+DjkSPTDwZ8sumTwOPlW5ZHvL5iRTDd/3e/s25AY/HU75aad1pPugzPTgq9/3dVrFlfUerLafEl0vxjAwGBHfU7AjWSpdCSQX6ffRZ8/NvfBi9qAABEZZrSBz+WGjYnuLlJo0B7mr7c/mXCfTbVbpLUEgxQcsEAU6YaPY3q3Tt0PHzhwsj6816vtGiRdR1t9ibIDIhT9seUGZEZYH+PKTMikyAp/lJBTVGCAWW9JEd59Pc1bQ+ukZRFN91kDfjH4vVKdXXB51VViW+SXS6pWzfr8bZt0ctIxrNutzXg73K4NKDzAA3sNjDwb8f/Wpsqt0WlfE3W7Dmz7X7OAAAodn/7W3BM6sADpbfftqrs+SdP+ice3H237U1JZnTuqguud3XggUU2IdPnltbNCd5bHDHT6ruG96MdJVLXg61MgD0tk457jZO6DIufMZnJ0ortFH9DSIrD4dBhhx0WeCzJqh28cKK05fXIN+xZK30wySoncOhtSX/O3r3WzZvPZ9WLTYfb69YX278IPF+2ZZl+MvonIfssXWrdwPfqJZ17bvzZY65G2+J4XYen16hE/Pd2sQZaYi3cJ1mlG3qPixj8X7J5ScSuS5daN9NDhkgnnBC7OVHPNwCg+Gx8QaqaH7qt1zFS35OtRYQ3vig1bMrsZ/o8UvWHUt1GqaSr1PckORwdAteltbsSZyD6ywg1ehqtWu8tk4fiBgNMKxjgH1TevdvaXlNjBdPtE6RN07ohlBRYp0BKvGaAaZpqtC28bJpmRJvC21Xnrot4PaEO/aXdn0XPDOg0SPrhGqtvUbPamlzg17Al9c9K0TvvSPfcE7ndnoIvhQ7mb9uWXPp8797WeUunTND63esDwZx+nftpb/NeOR1OGaah9bvXp37A1uq4r7RziQL/eLe+Y/3s+W9+22h9B/qEAIBiNXducDLCjBnWgH30sSOHRvXdI2fDt3I0bU7q2M2eYF9v//3bLME2P9SslrwtQZPuo6VBF8Te1+GSeowNjpUNuihYRihDirGvQzAASXG5XDrvvPOCG3xe6YOfSFvejPGOlhuXTa+kFAxobrZu/srKpA4d0mvr6urV8tjqtC3dsjTkdY9H+rJlUuG55yYxc8xjuwnvNjK5XzqpLszmL9Hbihu78LJAa3askdvrDswubGwMZl6cfXb8m+qI8w0AKD6mKX32e1mJpD7J2UE69mlrsWCfx7prGfNn6dOrrTImreXzSmv+In1+h+TeHdxuuOTaf7LOO/NeqbS7bpx/Y8JD7WywMvoSrRlgn8nvM32B/fv0CQYDJCtF/JBDQmeCvfee9dieGRBtYN/+Gf7sA/vzaGWC7Mepb04jM6CsjzXDP1pmgGQFBDoNitzekNwNbEx1lVLlc9LWd63+U9fh0r7nSgN+IBkOmaZ03XVW/8N/cz15snTzzdLw4dLOndIjj0i//33ozfb2JKsd9e9vlW5KJxiwbtc6+UyffKZP/bv0197mvfKZPhmGkZsyQeV9rfR5s6VvuOV1abStT53Bm+B48qFP6PNJGzdav5IGDky9BBQAAKnavdu69kjWOgETJ8bet7TUpR8d2SDjm/9IzV6rnE2CTEt7MKAssiuYktWrrYzL1autYx1/vDXm07Nn646bNbtWBB8feFXiwf3aVcHHPcYGywtlSD70ddpacYQ8kHmr/1fa9G+FlAVwlFireYf80otXxytSc8v9dDqLBvvZ6+ZL1gx50wy2Y+3aYFmgI45IolSOz1ajtSzJlXX9C7MtXRr88/TTofs8/XTwtV9da90ZtyYYEJYZ4PF59GV1sJTCqlXBMgeHHhpZ8gAAgBBbXpdqWxYMdpRYNTsHnmu95nC1XO8d0vcekoZd3rrP8tRZpQaX/yY0ECBZM4HWz7GyESVV1lQmPFxNY42kxMEAwzACM/ftA/UDBoQe79FHgwF0r1f6/HPp45Y1z9ze4LU7UZkgn+lTk6cp5Hm0MkH2AEH6ZYIckmdv6KSGRNLNDPB5pVV3S/8+UFp+o7T5NWnbAumbx6UFZ0lvHift+UZvvin997/W36HDId17rzRnjpUeL1mLBF9/vfTuu9YNrH/CRrJrAPTvb70nnWDAVzu/ktf0ypSp/p37q1/nfvKaXnl8Hn2z65vEB8i08rCVrKs/kqo/tv6uTZ8VeGnntm6VrrrKyvjYf38rs7VnT+nnPw8O0AAAkA0rVgQf/8//xC8tLUlmhwGSTOsa3ZR4fSt7MCDd8a+dO6Wf/cwqsX3rrdI//iE9+aR02WXWkNScOcH1l/LKruWSUWLdSwyZnHiCQ83nwQDAPocWWRpFdjCvAkkxTVPult9+JZ4dMv77BwUG+h1l0uF/koZfY6Uu+9zWTMLVUXLAE3C3rFvXmnpp4WsE7Gneo8qaSg3uPliStNI2Zn7EEUn84rUHAxwp/JYeNMj6E4t/YTZJ+nKBVC2rJqzPk1aNM39ZIEOGzJZzs3LrSo3uO1pS6HoBRx4Z/+845HyXlFglFgAAxeXbp6xOuumVDv6N1GNMZH1O//XhgF+m/zneZmnBuVZpoBhMn1fuxjqpuTmwHkA8/rr84cGAqPX5HSWBjEL/wPuAAaGz19eutW6wLrnE2n7LLcH3hwQDnJEX14gFhMNqySbMDPCkkxnQW4F+Ws0qqedRyb3PUye590olnZP/LNMnfXyFtO4pRUwC8ad071wiffQL3XPPgsDf6y9/KU2dar1sz9J0OqWjjpL+8Afp/POlXbusBfySydru08d6/65dVp8ylf7kt7uCZSH7de6nzs3Bv4Ovd36d/IEypbxvZPnIZdOkU96W5Eyrn52OXPUJX31V+ulPrbUj7OtF1NZa82k++MCaAZnu+mIAgAJXWSlVV4du27LFmtLfvbs1Q8CuV6/44zNhli0LlrA+77zE4yee0v6S11CJIRkNm62JsnF4fMH+YToZb9u2SccdJ61rSV4MX1upvl6aNUu69NLUj511O5damY9dR0iuTon33/251d/sMMAqIZphxTj+RTAASXG73ZoxY4YkqeIHu1TqvznpNEQ66T9WGrh/gMBRIh12lzTgLOmzW1P6HP8vsNZ07D/ZHFmqYNmWZYFgwGefWb/I3W5rhnxCyQQD6iqt2ruSNauuebfUeajUe1xyjXaUtiwKZ0qNVVLHgcm9r4Xb69aaHWskST069NCOhh0yZGhl1UpdcqhVC9j/vb1eK3Ic93j2811RodLWpGoAAArT9oVWIKCkmzTqlvgLdaWYCRhi1QyrHnpgkkGpNHiS1HE/63r63Uty11VrxpIzpCUztLPHzoSH9JpWh6LR0xgIkEsxyvg4SwID9P5gQL9+1g2g/cbqiiuswce1a6WXXw5ut68ZkEwwIFG2giSVu4IL/Ibvn5Ty3sGB5F0rpH0OS35CQ2OVVHJA6Db/osPh6xeVdrf6euuejH9M06PmxmYtXGj9ne6zj7XYnmlGn9xVUiKdeKI1I3zXLiubIBl9+ljHNE2rXFCi/o6/ZOLuht3a0RCcxffhxg9D/t431m5Us6dZpa427A916K+In6vqD6VXDrAmjdRtaJNm5KJP+Npr1sCL1xt9RqPHI3XuTCAAAIpWZaVVXzDZssySVcZ5zZqkAwLLlll9lG7dEr/F7XZrxrMbJd2simF3qnTveqn7oaF957C+lMsRDPgnrFYRpqFBOvlkKxAQHgTIe6ZpZQZIUo8jknvPnq8k+az1BbKgGMe/CAYgdd88Islr/WI77hmpy4GR9dAMw1rk7JDfpXRo/89cc3P8/WLxmb5A7fyuZV1V21QrQ4aWVy3X+SPOlyRt3mxFdwcPtm4kErPdpUa7I6mrlP49PPoCv6d9mFxAwD6Db+/6lIMBX1Z/GZjVeECPA7Rj0w6ZMrW8KpglUV1tfe8DDrCugwAAxNSwJVg//oArJWeCC0e69cvrNkpf3KXANbDHGGnc/5O6jbAyDQ2ndPgM6aNfSy2VWnY17Erq0FV7q9TobQwpFZiopr8/KDBwYOTNVVOTdNddodtM+QKBh/Bj+TkMhxyGQz7Tqs/X7Ant5ETLVmh1MKCsd/BxzecJ69aGqN8odQkLBvgXHd62MHTB4ebd0hczgs9LukqH3y0NulBydpT2fi0tvVba+q5WfHNAIMX+6quljh3jZ3l7PFZQZu1aa/bbzp1WGaF4+vQJ3lAvWWKVH4o3k8/nswaUF1UuCtl+/fzrQ/czfVpetVxHDzw6fgMyKVZfMNMLdueZykrpwgtDAwFHHikdc4z172XpUumjj3LbRgBAjlVXpxYIkKz9q6uTDgZ88ol1LTr88NSbp4bNVsUHe78zrC9V4gpOJklUgijcH/5gTVDxl34+6CDp//5PGj3a+pr//rd0W/JLd7atug1WGUtJ2ucIa/Jtogkr/sWGuxxgTaKNO0EJySAYgNT53NZqE0MulXrFuSlyuKT+p6eUvlW6va9M3wA1N6eXlvP1zq8DN/LD9hmm5VXLZcrU0s3BRYSbmqybi/32S/Kg9l9MvihRiqbq6IEASdr7bXLBgE6Dg4/rvpV8R6c0sOJfL8BpODWq9yh9vMkqZGwPBvi/d9++UQ8BAEBQtW20rf8PFBIYz6T/3mZlH0hS35Olk98MjgD6r4OuztLRj0jvWIPOe5v3JnXoL7Z9oUZPY2AQXoqdGeDX4Lb6EPvtl9zaOqYj9O4t2vEl6/rsb0eTtynktWhlgjIaDNj93xSDAd9FL1nYaZAVpLFbPbOllJRH6nOCdNxzUlnP4Hu7jpBOeUf6+hEtnlkbSLf/+c8Tz+p2uYIZGj6fVebxpJPiBxD62DLyV66ULr44/mf4AwXLqpbF31HSp5s/zY9gQDt33XXBPmvXrtKMGdKUKcHXHQ6rBvKTT+aqhQCA9s7rlb5pmYRy5JHBTMKkNWyK3mGx9aVKncGxpVQmw37zjbXmkr+f+tvfSn/8Y2i57QMOkCZNsoIGecc/2UiS9jkyucWA/X1nZ4eWxZkJBrQWwQCkznBKckuj/5A4Krf+W2nEIUlHbUt1nUz9rxobXan/wlVw8WCn4dShfQ8NDIZ/uvnTwD6NjdYvzqRnx4cEA9Jf4DeuTrbodN0GpVpuYWXVSpU4SuQ1vTq498Hq2aGndjTs0M6GnaraW6V+nful/r0BAMWr+qOWzrnPyvTLRqfb55E2PGd16l1dpGP/YV3+wgehE3y2o+V10zRDSgI1eZvU4G4I2RZt5r59AN8/8D4wyXFY0xF69xatTJAkOR3OQDkht88dkimQqExQs7dZpmmmVr+03BYM2LEktVlUe75S0v2Q3Sus/3fYVzrhZamkS2jgwX8uh12uxRvXyTCsBWCHDk3u8L17W31Bn0/69FPp+ONjz/R3uyODAcn2I1dtX5Vwn8+2fpZwn4wq7xtcs6NILFokvfSS9bhTJyu7Y8iQyPUifvpT6Ywz2r59AIAsiTeBVIpcA2D16qw2xz92IlklB/2ZhEmrq0w4ubPUFexDfvedNYCfTFfvHtuSQT/7WehzP6fTWv9q1qwk25uI6ZM2viht/0Bq3mVN1Ol6kDT051bfLxVe29hgp8HJ9U99/mBAuWL2Uf2luxOU7d6wQdq40TrHPXpIhxxSnOsREwxA6kyf1G146Gz2WHbuTil9q1TN8skh02uV80l69n6L5VuWBwbFD+l9SGBQfHv9dm3du1V9O/dVU8vvkaTLgNmDAY1bpS7DUmtUMsr7Wqupm24rGGCEXThi1eqVpNLuWlG1IjDIMGyfYTqwx4HascmqffvZ1s/Ur3O/1L83AKB4VX9ozfbuNjK5hb3SsXOp5K2zHo/8rVTeK6kZ7P7rncvh0p0n36kbjrtBkvRd7Xfa78/BjkO9uz6wBoBkBQ2cjsjj2wfj/bP2k+1/mEZoMCBWZoB93QC3NzQYkKhMkM/0ye1zxzx2VPbMAM8eqWa11P2Q5N6745PksxP9g9VjZln/TmKdP8Oh95cPlddrlXtJln1w/4MPpBtuiL2vyxW6vz+9P97Nuz9J9Zud3yRsy1c7vkq4T0YZDqt/aJ9B1849+6x1Hj0eawBjyJDoiyq6XNa6EwCAdiCd+v/pKC+3FhFOgr0pnTtHBqUT2rkk4S5dO9QGHq9day0GnGisxjSlV16xrpO9e0v3328FKqK1z+nMwERQn1eqnCv99w/WZBGjRNZgvGHdJ3z2e+nQ6dJBv05+RN0eDIiSHSspck3OaBU6wvePVrrbVrb744+lO+6QXn01dJc+faQbb0yu6e0JwQCkwZR6n5CVWl0D9Z1MWcf88ktrZl4qUbpPN38aGCQ4sOeBOqjnQVr83WJJVsmcHxzwg8CMsqQXaSmxLSxQs0rqeVT6tZFjMRzWyuj1G6xfZOFfOlatXknq0D8kvf2AHgdoeK/hgWyIlVUrNWHYhFavxwAAKCL+Acie34u9ymtrbX07OJg87MqkS9l4WhbG9fg86tEhWETe/tiQoaq9VYGyP1L0rAApLBjgsYIB9vI08dgzAwwZMT/Dvt3j88iwlV2KViaozFUWEjBocDekFgwo6So5OwWDLdvfl7oemNwiwjs+Sf5zTK8VMBp0QdzdmpulLVus7zxunDWLP14tf79+/YL9tQ8/jL+vYYSWQtyzR/riC+nQQ6Pv7/FYiwOefLK0eW/iAfeNtRsTNzjTOg7Or2DAihWho/PxZm1K1qBLkrWZJesG3eOx6jP/4hfxB1+iBQkAAAUonfr/fk8/LY1oKWG4erV0ySXRX5NSuibZm1NenkYwoHaN5N4Td9b80D7fBh5/9VVymQdffy1VVVmPf/ObxG1Lpq8Vk7dJev88acvrUssYncywShnuGunbOdLwayLe/l3td9rRsEOH9T0s9AX7wH60fmm8NTm9TYpaujRW6e6932pP+ThddJH0+uvR+w7btkkVFdJNN0W+1p7RjUJ6+pyQlVpdB2lt4PGaNdKJJyY/k900zUCZIEk6sMeBGtFrhD7d/GngtR8c8AOVlVk3jE1NcQ5m19m2iN6etcpa3eTOQ61gQO2X0V+PVqtX0tZ6qxyQ39B9hmrYPsNkGIZM0wysJ1BenuL3BgAUL/+snbJeLdf7LHQZt8y3JhZ0OUjq0C+tQ9gDAB1cHVTiKJHb55bL4bKCAZ5gMMAVXn6ohX0w3p8Z4HRa94vr18f//JBggGHE/Ax7RoLHFzobIVpmQKmzNCRg0OBpUDd1i98YO8OwBul3tpRJrHpHOvB/kntv8y5p7zdS5yQzIfuf3vJvJPZdbH0wQUP77598bGnEiOASEtXV1s1yrDT63bulbt2sOvO1LZPt3n1XOvjg6H1JwwgGA3bU70jYlm1125JrdCZ1G2GdQzPZGSxZdvzxqa1yWF5udeiTGHxZvz748/aTn1hZHSkPvgAAisuIEVZR/1Rfa3Hfx/fpzoV3avEvFmtoj2ANQ3s/wzRTnBfjL6td/ZHU75SYY2adyuvVq8t2Ve/pra+/Ti4Y8NZbVjtMUzr33CwGxk1T+vASacubLRt8Vn/vgP/PKg3prpG++5f0zePWa1H4s3W/m/qd9u26b/CF1qzJ6W1IaQyyodGp00+3skUla8LB6NHS979vdVEqK63yhMmsE9be0MVCUhwOh0YO7aWRnb+QQ2bys+N79UopN2movpWj5ZdJstFRvw01G1TTVBN4PrDrQA3ZZ4h8Pp98pk9LNlupWv7o6a5dSR64pHMw3b52TWQt40zpPMQabKnfaC3el6Sn18wLPHYYDh358JGavWS2PD6PvKZX//ryX5KksjLre4eX4ovG4XBo5MiRGjlypBzciQFA8fEHA5zlitXJV12ltHOZtOlVad3fpe2Lkz++z2uVIpJpLRxsxu+F+69LvQb3ClkDICQbwDDUrdwaMDdlRgQDYtXztw/GN3uDNyWjRye+8fOFZwbE+Ax7ZoA3rAZ8tBn/Zc6ykDUC0lpEuMcRwSDOppetUodmWJ1VX4x69JtfS36dpH4TEi4x0BA8DerQIflB3tGjQ58/8kj0GzaPx7qZMwzpMNsEtFdfjT2pxOm0Sg9JkYs6R1Pnrkuu0ZnUdbhSXUcq0xwOh0b276+RX3whR/i/n0QaG5PreEqaPz/483bGGa2czQgAQBKuff1abavbptlLZodstw9hNTREdp/CBcZP+ruDg6xb307Yvx3ef40ka8Z/MubPt/pQ/3979x3fVNUGcPyX0b3ogA6gbMregoCyRIYMRUURFwpuBdzixIk4UVFQRF4VEVw4QJkqiGxK2duyW2b3yrrvH6dJmqYjBUpp+3z59EOb3CT35tx7z35OdLQa7FBu9n0CR34AbCo8eP8N0HsR1B4KEV0gqi90mgrXHYKa3d1efiTNOZtyzrY5rk8aCny51jKWbzP/83gmMcAjEzuxbp0aYNCiBSxYAFu3qgWYX3sNvv1WdQg88ICe48erV/tX9ThKcd6MRiPD+zRgePT3GPWW4uMH2xsG7I0D1n9g9RzYtMn5M3u262tmz3Y857NpDdFR6oa5d2/ZOgM+3fipy981Jtfghb9ewIYNDY1f9/wKqFFjer0KQ+RxqCD7iPyMPe7P2eP5F8W7hocfgOsaDElLPK6E/3nEGY/OptnYe2YvSZlJjseyzFmk56YTFqaOe+/e0kMFGY1Ghg8fzvDhwzGeZ3fzwYPqRnv11dCpk4oVPGwYfP01ZGae11sLIYQoL/ZRN5qNImfE2afwLuoIKwarEHZLu3neIWDNdo4GCu9c6iKp9nwptGMoFpyZd8HOAIBQXxVI3GKzkJSZ5NKIXlyYnYIzA2yazTFyv3nz0kdcaXpnI7JOp8NYzAyKgjMGrDarS4dGkWGCDD6uMwMKhDvyWEgr5/dqM8PuD3Dr2Cm8hoK9gpW02LNBHzo9RPZ0f59CCjbg6/Wej66rUUOFCrKbMaP4Msy8eer/Dh2cDclLl6qoAdZCp5fZrCqEhw5BSo5no0Nsmg2T5SLHWgxuVuELCBuNRoZ36sTw77/H6HHBuezWrVPl/lq13DuBhBBCVGFlHEDqUIY1AIpScMbf7G2z0Qq0+Pv5ObdLTXUvRxTmaD+5MgyjfT2p43+UOpA0LnoPRqONA6UvXQTA9u1qX3r39mz7c2Izw5bn1e/eodB3BYTmj7SwH49Or358akKH99ze4ptt3zh+n5Uwy/XJgp0BWYdK7TBxkbrN403/3dONmd81xmaDVq1UuMn+/fN3weAsK9asCVOmGOnT58K0f1UW1eMoxYVRMD5YURXEkmJ7FVi4w02h6VvNW8GxZNiyxbPdssedXX2k5GCyVs3KodRDtGxZD4tF9e7u3+9hj2pwc9XAkfkf2CyuN3V7PP+802qBvoIx/f2i3d+rOAGxzmngSYuh0d0evWynB4veLdy3kNatb3HM7N67V90Qz5mmqSla1lww+oPex61mv369imO3apV73GWDAX7+GZo0URmaLGosxAVw+LD7CEx7POcLEMtZVDOG/FqQNYeyxuYsNr8vyFIgboxXUNGjfAovHmZKJTl5nUss/cKdARH+Eew7qxZ6PZp+1LEGABS/ZkDhMD25llwCvQOJiys9IorbmgHFzAwo2Blg02yunQFFhAkq/FjBGQ4eq9EKl1HlBz6D1i85W+M1K+QVCo9jr5Cd+EvFZS1uYTc7Y6DzXClBwUp1To4qE3g64KN9exXnVdPU7WzGDHjwQWdHjdmsOgJO5tfp27Z1Tbc33lADEAry8oI331S/H0477PLc5L6TaR/VHlBly4krJjqeO5J+hEZhHoZPuhCC4y7eZ1Ww9HR1XsRVn0MWQojqQ9PUmkTJS1U4Qk1TAycje0Gd7iqkXMF6TOH4/3BeawAU5Zutzgbr5MxkEpITaB+t8n8fH1VWMJvdl8spUY1WOAZepG5VszJ9I4vdvEnUPjRNR24ubN6syjAlDUy3D6aMiVEDWz3ar5LqiOBeT8xcBeb85zp9rMICFdepodO7NeZrmubSAbDr9C62JG+hbVR+h4JfjHPjs/FQ60rQedgglH2k1LUY7L5adQdGgw1vHz2//goBAUV/X/ZmrJtv9mwXqgrpDBCeM/g7fy+qUlpSbC9PGwdQlYAVK9T9KSFBLfzmyaIou07vKvW95++eT+e24x3TvDZtUrFnS72JBsepSrNmg5MroFYv11FwAbHq53wUnBlwfKFnlXDgWNapUrdZnrice9vc4vh70yb1PZdpCrY1D078CUd+gsM/ODMIAN8oiL0J6l4PNa/gy68NjBnjnE7XoQPcdJNaENpiUR09c+ZAYKB0BIhqSLPB6XUqzuKxX1Uh0ZY/4yr8Mqh7A9QeAj5hpb6Vw+HD6qIuy+JbZYjlLKohewNv1qHyCY9XMAa6zohbh0MxAwyST4NBZyy2M6BWQC3ntpnJLuFfipsZ4Gt0HY1m7wzwZLBAwc4AKL7DoWAnQeHOgKL2q/Bj5zwzoKC8M7D+Xrh8lroP2ayw9YVCL8rfL0sW7JkCzR4vOf0NJYzks3fm5CThl54BjADg1Ck1qs3TzoA2bVSMXHsD/9tvqwpbeLiqwGVlqRmI/v7O7QuaOxdef13Vc728VDlk3ToVIqh9e0hMTXTZfnDTwbSo2QKAYJ9gl86AxNTEi9sZENjQuch2SfS+aqZqebGP2izrAo9lGLWZmak6AwIDz2H/hBBCXJpMKbBjEhz8BnKOqzzNMftUg20vQY12MGB96XUSD9YA8JSmacyIn+Hy2KyEWY7OAL1eDZ7cvFn9eBw5Jryz69+7P4C2rxUb575x5H6sVlUGnj9fzYwr6bPs2bCfn4dx7s+ljvgA0BXwC4PY4aXXAwo9vzl5M3vP7HV57OutXzs7AwLqgTEILBmQsrnoRYRLkrYdIgq1LdqjdeTXG/LM3sxdMwKLVc/IG6FBg9LftkzrQlQB0hkgHM6cgcWLVXzVv/6CjAx1QQQGQo8eJlq2XA1MZEKj1/HOOaYu4nK4Wpo2dU7D+uEHdRMu6YaYlaV6+U5nlx6T9K/Evxg9eLzj7y1bPOwBDIrD0cN7+AeILId5WaHtUI0hmqqEH/8dag8ucZp+uhXMhRYiLEp8Ujwtr3IuNrN1q3tHe0Emk4lJkyYBMGHCBLxT1qgZD9lH8xttNDV13eAPlnTI2K/iyh2dz7ycA9x1lwFNU2k3dy60bKkq8fbTZeRIeOst+OMPj78dIQA18nPRInWf2rlTNR74+qqOpoED4ZprVHnnks3Ik5fD2rsh+7C6ljQLeAWrjj/TGXXdH/sN/OtBu+VwNs319cWN9N+1q+yNNPZYztIZcFGYTKoj9vRpdT8MCFD3yNq1S39thQiOU/f202vL5/2NBQYYWLPdFykuNMDAZPNi0oHnCAAMTMKMBS+9F35G11HpYX5hGPVGLDYLZ7LPuIzIL64zwL5Yr72B3h5ayJMRyoU7A4pbQLhgJ4FWKAZ8cWGCCjqnmQG+NVXlKK9A+SjxK/V3ze7qfnNmnetr7PclgB1vQuP71T3KflMtXOYoLtZroc4cXw2CfK8hIzeYdetg7FjPD6PwSP+jR6F7d5g2TQ0oGDtW9Wu2V/V3WrZ0nZFosajp9CtWqLxixw616J7jK0lJdJltEh3ovLdGB7nOqEpMce04KHd6L5UfZP1X/DZBcdBnyfkPSimGyWRi0qxZ8MwzTBg4EG/7CJoLPGrTPkClHCMRiUoiM1PNFNE0CApSi4ILISqhMxtgxbWQd1KV8wIbqkFPQU0AHWQlqoGGOp1noQkvoM3Jmx2DSb0N3pisJr7a8hVvX/22Y3bmZZepKAbbtpU+iMGl/aRNHN45+eGl90yBuLHgW8u1EyRfk6h9jt/nz4dXXil5v33yi4d5eR7Wd0+fLlsdUQd0BgxA7I1lWqzX7ustzumYXnovzDYzX235isl9J2PQG9SOh7WHkytVZ0BhhRr23ZzdBGGdXM8Ze7SOk//AmttYvLU/6TlqHbHbby99FoVb+1c1GLEqnQGC3Fx49VXVOGu/SCIjVeVLp4MjR+C331TlyuHkCtXrqbvwN+0mTZwVuK+/LvmGaDarRsGWvXa4Va6LsvXkVoKCoG5ddVxLl6rjLlVwU+fvR36ATh+e042xRN6hahRfWn4ctG0Toc7QEl+yuNBadnqd3hFjuOAChYkpiQQEQL16Kob/H3/Au+96uF//fQHxDwI6CGoKzZ9QGYN3qHObnONw+HtMB5fw6INeaJpaH+Cvv5wZVlGzEOwx24QozdGjMG6cKiRpmrpPRUSoNvHcXPj7b/jzT5gyRS0+7uPetlaxNA12vQ0JT6t7R3AzaHyvGm3hX0dtYzNB8p9waC7si1cx08rawC8uKWYzfPUV/PSTOj+LSs64OLj1VnjuuTKMOroYIrqqxuKc45CTDH5Rrs8XV1D3dK0cQ4G1hzL/oyyLpFrzO+dDfENcFtkF1RlQMB+0WZ3DpopqdIf8zgCdzhEr1t4ZEB4OoaGQUkJIeZ2x0MyA4hYQLuZxKD5MUMFyzTnNDACI6AbHFuCyVsDx39VPUYLjIG2H+t2cCluehcs+VvcwzeoaMhLAkqk6BArPECjUmaPTQdcma1i6vS9r1pRhQSigc2f3xw4cgH79it7e11e1R+/Y4Xzsv/9U+bJ2bTVIrmDnwsHUgxh0BmyaDS+9FzV8azieiwxwTu330ntxMPVgmfb9gqjRUjWYFHeNGP3LrSPATbt2JU/pPI9Rm4GBqqHFHrWg3GmaOteTl6m1ulLiVfgynSE/dEVvtUBiVD/wLcdZFwJNU3WyRYtUHWX3btfnGzZUgz2uvVZ17JVlTTkhRAU5swGW9VT1G/86cPmXao0hmxWwolqdddD2dUjdedF374vNXzh+7xzTmVVHVpGWl8aCvQu4ocUNgMrOZsxQ96jdu9UCtB41wNfsBkcOqMEV1hxV/+v6pfP5Am/SKNIZ8nn7djULoU2bou9zZrOzrnDqlIchgso6s88XsGfzNa9UM0nL0O5lsVn4eqvqDNCho0e9HixPXM6p7FMsT1xOv0b5hbfQjioMd8Ze97A/JYXhBjU4t+nD7h8eEOtY63NfchMMegsGo1HyjWJcStVOUQGSk6FbNxU31WCAZ55Ro+WPHlWx3v/5RzUeby7cYXdypXvv7QVaSLdjR+f98fBhWLKk+Ji9Xl7w44+qZ9cTZ7JVbNwOHdSNNCHB2dNbHE0DAuo7QybknYZD8zxe4LdMoq92joxM3Qo7J7tODS8Ujy2jUL3whuY3cEvrW7il9S20rNnS0SBispnQNM1x3Lt2wYYNpS+EA8DGcYAGsTfANVuh4SjXjgBQcd+aPMicoz+QlL928aefqnynpFBE1WRtFs+Z0+HE33BkPhz+Xi3Cnb7XZfRAdbRsmRpB/euvaiHJd99VBbKkJHUuJyaqAtGXX6pK4iXXEQAqJFDC0+r3RmPUtdT0YWdHAKgpklF9VQiP2OfKvyPgPBfdEiVLSFDn7ZgxsHy5Wjz9jTfUeim//646Ce66S83C++23S6wjAFRngD3/OfWP+4hwe0G962zXxz1dK8fgrUaIgQpBdw4jwuyLBRcU5hfm0ojuEo7HWPLMALuCiw4XHORcFJuu7DMDivr8wnwMPi4L2Z3TzACAiC5lmypVo63rDI19n6jZTFn/qbiua2533V6zqTKhrfQCRfem/6LXaSQmqtmonmrYUHX8lkWPHu7lj9xc1YlQuEz5X8p/mPPLdDX9a7p0MPkYfQj2UcOSbZrNLaTQRRHczDVNCivpuUokMlKdqlu2qHUlylXaTljeG35vDfGPqxlQYZ3UYJc6Q1Tn58E5kPAMeAWU/n7inG3fDl26qAFCH32krs/77lOhvd54Ax56SPU//f67mhFUEQ06+87sY8amGWSZskrfWAih6q6bxqmOgMBGMGCTaiAHFWpZ763KffYyU3CTi7p7eZY8R4M1wK1tbgVU4/XMzTMdj3fo4KyGf/ONh2F5QIV9LdiGk/gVbByrytKaDfZ+7Hgq0DeLti2d62hNnVr8fc7LS9UX9Ho1EM6j4l1srJo+uWmT82f2bPftZs9Wz/1VIHSDMbD4Nb3OxqufYwsh8RvVsA8sPbCUMzmqkNc+uj1Dmg5Bhw6DzsBXW75yvkdYezXARLOp76dw21pALIR1cDTuuzi5UkWsKGHh4fScYPQ6GyEh0hFQnKpRehTn7MEHVWN4VJQajdGyZdE3lYYNC/yhM8Kp1flT+gvFzb8AC+nWqqVGga1fr26+jz6q7ksGg2tjic0Gn3yiRgEfSTuCHj02bOjQEX9fvKPiPSthFu+teQ8NjUxTJtnmbNq182fhQvUe774L//tf8fujaaDTGyFmEBydr4575yRVYdAMrj2lHoTsKVFkb9hdYDX2ba9A2GWqk0CzuU3H32YCL70Rs81CgFcA826c56jEfh7/Off8dg8A2eZsjmUco127Ovz6q/O45871YJ90BghqDN2/BXTF9wzrvfh4uhGdDnr1umDh/DyTd0ZNF8s+CrY8NWPFJwxC26uOnCJO6ss+u4xtJ7dx9LGjRPhXYINo5n+w50O1aHT6HtTIP50qHNkzRa8QqHMddJnpulZFNXDiBFx3nWoYGDBALRJpX9CpoBo1VMivksJfVRibBTY/Cegh6iro/Gnx29oLxfU7lT0+s4+P6h21hw8qHMLhAi+6JYq3aRN07arutT16qDymQQPVyGE0qluS2axmBGiah/fiiy2sE2rMiE11TsYOd9+mwAiccxI9APZ/BqfXgNWkOgjsSpsiDEXeu8P8wrAUkxcXOzNAr2YG2PsNCnYGdOigOs+LG5RgpexrBhRk0BnQF5Gvehu8L8zMgFo9S483X1B4Jzg0x/Wx/2apn+IkLYHIq1wfKyL9ujZZg9Wm7nE//QSjRpU8YMBmc6513KuX6jTzaBADzjBCnrAvOA3uYYEAogKiSM9Lx6pZ2Xdmn9vz5S60g/uMjILKkr6XsD594P331e8rVsDVV5dTBf7wD7D6VlWujugG7Sardc0KN3hYsiBpqUcLZItzs2wZDB6sZqZfcYW6Zlu1Ute+PVyU0ajuA0eOuC5EfrGYrWaaTlUzxJclLmPejfMu/k4IUUaaBseOwf79qiqh16uQWy1bXqSwW0lLVNkOoMO7KtxgSYM+LnKIoN/2/kZ6XjoArWq24qaWN/HgwgfR0Fh8YDFJGUlEB0U74vfbbDBzJrz8sof5Uq2euM3m2/uRKvPq9Gq2QAHXDUpj+25/rFaYNQuGD4e+fV0HTlqtarClvXMiMVENnPWoKhcb6/l6DKYUsE9WKCqMZzFregFw9WreW/OeKtdq0CSsiWOmq1Wz8t2O73iv/3tqfa/Qds7X7ZsGTR/y4EBwLli8czJ0/KDYzbyNJjRNR15esZtUe5faODRxES1frkJuWCxqJEazZs5KV4k0i1rs49DcsvXglcH11zv3Y/duuPNOtW/2gqHFAhs3wmOPqb/jk+Mdaw/WCa5Du6h2tKzVkpa1WnJl7JWOCrWGxtYTW+nd2/les2er6eNFxSi1WCDNHrK77g3OClfaTlhzZ/7NKP+OfCEqY7V6ut5sbXnwV3/45wbYNBZW3eiyeXyuc82AhqENXUazNQ5r7LLtluQtXHWV8zi//151EhfVwOHyXWgWaP2KR1PEjhzRoWmqM6fcY75m7Fc97PPrwI8RsPI62DsVDn4LBz5XiyT+2hAWtlKNTAXM2TaHjUkbybPmcef8O11GXwIqZ42Pd/1ZuFANCfjmG/V74ecPHy7b/tvMqoH41yYqAwxpCd2+hmsPw0gbjDDBzdnQ9x9o9hjknKh2HQEATz+tCrG1asF336mKYHGNR2VaEPtiOvwDZB4AbNDhHc86Des3Kn0Uh30Eh/1n714YNEgV5Dp0cB/SbC/k2X+kI6BcWCwwerSqOHTposID2b9qLy9n3mYf3WMwwIgRFbe/xfIKVCOSAY78qDouPRj9XSaRffKnUOeqUB0FyxT2AQYDNrnPPshXM6Cm22OFFxQuqPBCwXYlzQzo1av4jgAAvdf5zQworpPAx+jjiGEP5zEzIPxyVQn3VGgHylY90KnO7ML5UxEzR7o0WocuP1zR22+XraF3yBDPOwJAdR57MttGQ+NQ2iFAjQisE1zHbZvawc6FPf5LLSF2f3mJ7FnKBlVj9mCvXs6Gj0WLyulDso/B2lFqtGqjMXD1PxBxedEjH40BUHtQOe2IyMxU9TuzGYYOVR1A9kXb9Xo1G8Db23kdx8SUw054MPN20qpJjt+/2/EdfyX+VQ47IsT5y81VDcn9+6swh3XrwrBh8MADcM89avZ0SIjqeDOZSn+/83JojrqvBjcrdQ3EivDAggccv28/tZ3wt8Id7UU2zcaYX8cAzrCDOp1at+6jj4pv43ApowQ2At8o941seW4dAQBD+qc6Xq9parBQcrLzPW02NYD3scdUp459hsKCBSWXUc+JMcgZCvxsvHvjYKEwkAUdP7mJZYnLsGk2bNiYt2MeDyx0ftdmm5kX/3pR/RHcTOWzoEL2eRp5w142PvC5ytOLeU1Y4FmsNgMZGWpwoXAnMwMutiNHCgXfrzj/+5+qiLVooRrfy2zrS1C3iJGCF8B116lGQLsfflBtXK+/rmYxzJsHEyc6b37rj653VJqbR7g2gDUJd04706Fjc9Jm7u9xOfXqwaFD6iY7eLAKixQc7KyIWCxqYZaxY9XaBdS+xnVhvcPfwbogaP+2CpuTk5w/+vc8eAWpxpHkZTjj+2pqYZ1CNA0S8jNyvU5Ps4hmLs83Cm3k+N2gM7DlxBYmXDGIRo3UNHmbTX2nq1dDWJjrcWdn46rWlUVn4lmHnQsT5iShs/UB/Mo3qo2mwdbn1cKGRn9oNFpV6EKau1fmso+psDsFRpseOHvAMWMC4Pf9v/PR+o8Y2yV/NcPDh1UQ77KGaPH1VY23njawbn5aLSjkEw69/lCjMW0W58hwUKPRanZTFdUqMvKvLHJzVegfgKeeUpXCS2aa3+HDakGmgopb3Pf0SnXvMAZCjTZFv5/9WspJAlOqeiywIXToWvw+nEds5qoqJUV1IO/Zo0Lc5eaqW4avr1ozpWlTlQWHukeXuWC++06FudDp1Cgi+xoXJblkzuvCovqoWJ6aRXW+9lpwYd8/sheqJ1+DrS+ofLaggNhiY6Eb9UbC/cLdHi/YGWCfMWhXVGx+cA/TU7AzoGcJ7bA6HdSpZ3IMoNLQim/cL2G9gtK2N+gM5z4zQG+A2kPVAA6tlI5IvS8ENlDhyk4s9yzf0ekhbTsc/QVirnFfzK3A4JBg/wxa1NnJzmMt2bdPx8cfqxmqRZ3/FosqMjdooP4eNEh9356WL8LDVYPHqlWlTOv3P+1Ib6PeSEyQe4tj7eDaGHQGrJqVszlnyTZn4+/l77ZdufGLhoAG+esGFMEYVPTjlUxgoAqn9u+/qo7y4osqO72gIdTiHwVrnmqo6ThFnb8lDXS5xBqwqpK331aNXUFB8Nln6rGS8srzyic1G5z6F5IWQep2FYo15xiQP8JU76VmQddoCzWvUJ1A/rWJT4rnlRWui9fdPv92dj600xE+TIhLwR9/wN13q2uqd281y+bKK1070SwW5zijcl8bNe+sKkME1Ct+m8J1n8CGapZWOUtISuB0zukSt1n631JsNht6vZ5Ro1S7lKaptqjrrlMdLQUHoVmthToJdDqod7MKB1Ra2Qto3yaHqCiVfgBnz6pZUs88o/5fvVrNnMvLU3WasDC1zdtvq46ekpS2cK4bvRFiBqi1pQ7NhfaFFtgsYebui1t/LfXtv9vxHdMHT1f33QZ3wP4Z6jva/ATU7A6+ka55b+FBdAY/1aFizYU/+0C/NeBVw9mGkr99/zaL0VAzFL7+Wq09eKkOHDyVdYrP4z9nWLNhNKvZrPQXXCAyM+BiK0uQ1HKWmqpuXGUeaREUB+jVSNctE9RjheN1nefowaZNVRtXwY7I33+H9u1VG9v48c4FxqzGNA6nq1HZXnov4iLiXN6rUWgjx4g/g95AfFI8Op26cdorGLt2qenJB5zrt3D0qFqczrEAnVcw1BnmOnL/wEyYHwM/x8KvDeDUyvM6bgAa3onLQn/FOGaB9PzNDDqDS+M/qMprwZGIW5K3uB33gQOqoWPbNufr9u9XlW4XtiKGD9iniC3qqH5WDKZu0Db0Oitr15Z9PQCrVYVisC8aPWYM3HKLM/TLY4+pGHq75r8DO95QPcn91kCH9yCkRdGjuvxrq4w4n8lqYvj3w8k2q96OIG9VgX58yeNsTspfd+L06XOL1Z6b6944XJykpbDnfUBT4Zfs0+SKGlGq06vHi2lIKlc2M2QeVHH5ji2Eo7+q/0/9mx+SqXw7KAou2lmv3iXUYGrvMOrY0fVn8GB1sg4e7Pr4x9NUSay4hrWC19KKwSrE2prbYGk3R/xFUTyTCb74QoXliYiAhx9WlZ3ISFWAbtNG5RuJifDOO6oQXZ7271f3v9BQNcqxUq+N0uRBZyXm+ELYkT9CsmCL7PmEx/MJz7//6dXinbve9bjjU4euyFkALp0BhRr5PG2QL9gZEBHhHK1amF4PsQ2d8481TSt2BkBxjf6ebK/T6c59ZgBA7SGlV0aD4tRI/oBYtTaQRx0B3s7tNo5VlbMS4rcCPNLvI8fp8/zzamJd4RH/ZjOkp6tFte0iI6FTp7Itf3DDDaVvk+3tbGDX0IgOdA8TFB0Y7XIuVcgiwlF9nSP1CtIZVGziKsI+oyMtDR55pBzWUjm5Sl0Lda8vutwIzljIheIgiwtr61aVlXTqpO6z5bZuzrGF8FtTtZBp6jZVl+u/Fm7KghG5cIsJbjwD3eeqwTcN7wT/2uRachn540is+fe465pdp94u4xiPLn60nHZWiLJbs0Y1UJ84oUau//mnGuhZuI3HaFQDYkaOdD6Wnq7WZHvrLbj/ftX20bWrmtl65ZWqHv7ss/D552oCsscD/ryCAD2Yzhb9fFF1n4tU73nuz+dK3cZsM/PlFjUi7a67nHXQs2dVGML//lPfhdnsHEB67bWF3qThKI86AkDd/0aNcq3rpqXBhAlqZuSkSc7mCZ1O5ZUGgxr49OKLxaeLpp3j0oP1b1Plu5xjkPynxzN3fzq0zvW4dHr0Or3L7NuU3BR2ndql/mh8r/M7yj4KS7qrwZzg/MyMva77Ft3f2R6XsV/d20/+rf625sGRHwBoWCuRyxquQ6/X+OqrS7cj4GTWSRp92Ihn/3yW5p80d343F0FlrqJWTuHuo9gqSlSUyhT27lUVsZIa2vR6PU2aqBH2+jYvwZr8GQG734Pck9B5uloIBgCdWgj1PI0fD3fcUfp2uaEJjt8tNgtNwlwXoPEx+hATFMOxjGNYbBY2HN8AqMbml192jhjbssU50NZgUGGIbDbVAeEQ9zAc+d51B6y5kH2k7AdYnLo3gs+jkHeyxM22FGifN9vMNApz7QzQ6/TEhsRyIOUAVs3KxqSNgApf8dJLOOKn7d7tjChiMKiFvIxGPZd3rkuXen+hR1OLurR6wbXiVMQUsYf7TeXO6V+xcqVq2G/fvvSGsJMn1f7MmQO1a6upwr17q4KKv796fU6OahjesCabZjlPq4GkbV+D4ObuI7oKzVYoONJg+HfDHYtN1w+pT6eYTvyw6wcsNgtXf3012x/cTlRERNljtUPZFmM9vVZlYl5BqoJflOJGipf3iIlTq+HQt3D8D7WPNbuqRiKjP+h9VJpbstTIqqzDcNXycuuoCAtzxmncu9cZP7pUZRm1D+UfO/8QYECFV0tepsKBFWwALGG6JZn/XZRRMpVVaqq6Z/zzj4ovnZioktJiUeeLTqd+7OfOxWiYDwxUn5eZqToqyn30Fep4DxxQ4w1yc11nRNhHEDVufA4F4ZDmqiH5+B+qsL7lWTUQoN1bal0WUOfo+Wj9Mqwcqn7f8qyaQdPkPtXZaA89o2no0Qjx2cuGPOeiwKV1BhQMs6PX6YttkC+pMwDUubV/v/vUcKsVasea0G3ToeX/Ky5MkNFQ9OPFdVAUnMWgQ3fuMwMAovupMlpRHft2/nWcszDqXAsGfxUrtjjBLaDX7/DvCDi7AbIPq5CG3b8tNELLtaX/ziu/5PlfpnL6jBfp6WpNjWnTVHnPfn/ftk015BeewXPDDWpEY3EV28Ll2GuvVSPBSqKFHHT8brFZiAp0n9YfFRjlci4dTD1Ii5otSn7jC61WTzgww/1xzZa/vkf5cakDlPNK56NHq0Vjs7NVubBVKzUi02ZzncFqNKpZwzfeWPL7uXGcl+aie5aKi4V89WrJiy8wX1+VBFnluSbvwW9h9W2qnNrrdzXa1WZ2n/Fh8FUhK4IaO54bOHsge87sASDYJ5gsU5ZjttkXm7+gXkg9Xuz5ouMt0tJU3WfTJjWQzGpV5629jm0vzzZqpBoT27dXdfFzkZ2tiro5OSq/N5nUslG+vqruVK+e+ltUD/feq+6LN92kBsRAyeU9o1E1Io8fryLfXn65yl8feADq11chWQ0G1VaQlqY6GzZsUOOdPO6Qj+qr6pNnNsDZzVCjteugt+LqPuVc79E0jS0ntjj+9jf6u4ScPJx22FHGXHloJXe1v4vwcLj9dvjqK/U9Jyer6/fWW+Gyy9Qsxi++gJMn9cTFNeHKK/PzytB2qqyUvosSw/npfcEngvvvV4OWPPHEE/Dtt+r3yZPVLEr7eWDPK81mlYavvqq2KZPag50j8NePgYEJqnxuT8MiZu4eNUNKnrMNsH1Ue0eEjjxLHr/s+QVQZdqF+xbSvGZz9R1FdIMz61TnQ/ZhWNBUddgHNoaUBDVDoaB6I+Doz86/03bCn1er/bWZXTpgRvX4ko2Jndm2TZUtJkwo/hy22fTUq9ckPzzdxRkzn5SRRM//9STDlOF4rPsX3Vl510pa1WpV7p9f6WYGfPLJJzRo0ABfX186duzIP//8U+L2K1asoGPHjvj6+tKwYUOmT5/uts2PP/5IixYt8PHxoUWLFsyfP/+8P7dYdeue2+vO0eojq+n7VV/G/jGW1NxUl+fGjVOFksRE+PjjkmOxGo1GRo4cyciRIzHWv0FVPOwNwwdnw8LWakTff1/CjtfdYtufi5Ej1eDb0q7FrKB4x4gtDc0lLJBdwRA6O07twGw1ExmpFicu+P6apgpx69cXM628Vg+14KHOgxal/Bt7mRm8odk4Srs8t+iiMRRonC88MwAgLiLO0RN7MPUg2eZsIiLg8cfdv9ddu1RHAIDFYuSff+9mZJ9IjAZNpW3uKddeYfsUsQJu6fottUOPAhr33acKqyXFsUtIgNat1WiDCRNg50547TW1YE7jxmpEQ61aqlDbrh3ceVs2Ol1+Zuob6f6GRcxWsI80eGPR/fy61zl17WDaQX7Y9YPj7zM5Z7jiiytUS2JpsdrBPV57WUIEeYeqDM+SqTrOCo+krIiR4tZcWH8fLO2uCm49foEhu6HLF2rNgsb3Q8O7oPED0PwJ6D4H+q2CYyeKX1/hPNdW8PFxhpB46y3IyPAgZnRZR+137Ki2L8uaD56cIwXPj5kbIbCdumdufgrQuTaQFXEtOXjX8Hy/qqEnn1QhJZo3V7PHaueH9jYaVSO8l5fz94s1Qv+669RnmUxqJE+JIUrylSUWut2OHSqMXbt2MHCgqojs36/uu/YGgbw8VeH79ddzHBkE0OY111HiB2bCT5Hwezv4tTGsvuUc3zhf7cFQ80qVr9pMsOF+WN5XzRTIPakWVt/9Hka9haCQOcxhDhYsWG3W0jsDCsyy06ErsTOg4GK9hTsDevUqOkastzdE1DI51uvRtOLDBHnpvVxGRjnew1h6mCA4jzUDQN1HGo0pfiQ0OmhYYPSF0R8a3F7C9qjGtcB6avE2ex6WvEyNwE38WuVtNjPkHHV5ma93Hq9OSHL8nZurRt3VqaPiHLdurW7LBw+6f+SYMSU3cBWu4NWrpzoEirv2DQZo0jnRpSxV1ALC0YHRjtHBOnQkphQTrqc8FbtugAbhHcv1o13qAOV8I42KUmFA7Wn57LOq4XRvgYGBR47AVVepin2Z1R6qBpEcnF10+as4xY1uFeds2DCVP65dqzr0L3jca4CEZwCbGn0aM0A9VrgjwD4T5PjvcOg7OLWGaRum8fehvx2bpOelq7AhBfKUiX9PZN+ZfRw4oEbuhoWpxT2bNlUNb998oxrrvvtO/f/NNyoc0pAhqp5Tlo6AvDz12htuUI2Po0erRdh37oTjx9Xo7qNHVUfqnDmqjl940Uyz1cw3W7/hu+3fYTmfGX3iknPmjLqW6tXzrMy5cSO0bavizU+dqq6/hx5Sj4WEOMOy+vur8VNDh6rwOGWaWdvgDgioD+gh/jFA86zuU871nvXH1nMs45jj7ykDpnBw/EHHz8jWIx2DOn7Y9YOjPPj8865tJzk5qv3ivvtU28Xx46r9ZN26Qnllk/tL3qGg5o5ZmfXqqQb90mbC63SqM8I+k0DT1H706QP79qk6RU6OSt+4OFi6tKzfEqoc2OwxQAdZh+DPvmA6o/LMgvlmgXvJNxmgL1AQ+/aGb5l34zzm3TiPn0f8TJtIFSpXQ2NWwizne7R9w7WeYTOr9QN2vK5mJRfuSAlqArE3uZdRrTluMzFu6fYtNSMs6PUqDe1NwQXzG5tN/aSmGlm48OKUdQA2Ht9I2+lt2Xd2HwDd6nQD1MyJLp934efdP5f7PlSqmQHz5s1j/PjxfPLJJ3Tv3p1PP/2UgQMHsnPnTmKLaIRLTEzkmmuu4Z577mH27Nn8+++/PPjgg9SsWZMb8ucOr1mzhptvvplXX32VYcOGMX/+fG666SZWrVpFly5dzulzLwX/Hv6XF/56gb8OqkWOlicu56P1H/FijxcZ12UcYf5htGqleo+nTlUNsVFRqkfZbHbvTXZ5TKeDy2fB4s6qARFNxTG1hwy6QAwGFQdt6NDitzEawbveZpcKduGZAQBx4XGsPLQSs82MxWZh56mdtI1qy8SJaiHdw4eLb4xx6z1s/xb83rbkna/RBnr+Vmys41I1eQD2fKga4IsJGbTFqx4aztVQCi8YDOq7WKpfitlmxqbZ2HFyB5fVvowXXlDrLhw8WPxx6/VAywmq4ceSAUsuhyvnQ1h7dZO2TxHLO61Gia+9Ey+jhQ/uGMfwD39g82Y1xfDbb1VjVcGbrj3jevttNTMgJETFxIOSG+y8A8NVh8ypf2H3+1DnOrBpRYfXKeCEBV7d8EWJ2wAcSDnA7K2zua3NbaU37J9PvPaGd6r1ArIOwpo7oMfP7usFFJKeHcQvm65l3dJorL5qfYuQEDWo3V5os1rVT2qqmsao06mCW4MGqoBQeEC8i5P/wP78oK3d56j4xKDexN6AlpOkfuy/J+6Hvk9BXhlWoSrj2gqvvKIqUOnp6l7w009qtKhe796hZTaDznKRMrbY2JKPofD5EfsxLL1CjXD4qz90n6dGVms257V08h/V6VOQX0mJJtLzB6AUXPekojVsqGadPfus6gxo21Z1EBQ3A89iUYX2oDKE/f7oI1XZr10blixRp5vFou6rhfNveyP2OX8/oW2g1Yuw/WXnY5oFUre4b3suneA6HXSZCYvagzW/knFiuSpjFJJsVde3BVWZKKozIMg7CL1O7zKSW31MyZ0BBRXuDOjXT91z7ecbqO/z+uvBpjM5yiAlzgzQG9Hr9I5GZTtPZgYA5zczAKD5k7DPfUCM2rkgqFMopk7riapRv6jZATqjGskFENFZdRDvegfQwJQC6+5WP8W4547T/PBHLH//7SyDJCWpn4IK3+PDw1XomHffdS+7GI2qr7ewl1+GX34pej+MRqjZJBHdLp2jrlnczADHa/RGElMroDPAv47r6DkA9BDcVMW/r0LGj1cNqJs3q3Reu1aFtggIUOdERv4AOpeZu55q94ZaED33JKy+Fa74Xs2asTcQF5EfaxocT4ll3z7nJEP7WjD2EAz2uoLF4lyjpl49NQasvEPTVVbDh6u1IZYuVQsJL1mi8k/7jL7CrFYwnCziRmFPFHCf/WkxAnrnjOHCipgJkmmDicdLX1hIQ+PR357jzwe/w2RSnVNPP11yfO6gINWYX5ZBp0ePqrAtx46pjrLvvlNlCZPJWRa2zzqw2dzLAdnmbGbGz2TsorHOB3+EaYOmMardKHyNcoJWdtdfD598ourcTzyh6kkllfkWL1blmZAQ1YgMpc8kKDO9Edq/owaInvzbWffxrenajnDib1h7p/N15Vzv+SLhC4x6o6NDbEDjAS7PD2g8gG+2fQNApimTn3f/zIhWI2jQQI3aHzvW7S1duJXzG98Hez6AzETc23R04B/j0l703HNqcI/9Wi7q/e2zJt95BxYtglOn1H3nr7/UWqCF11eKLGL8pEdaT4QTf6lyx9lN8HM9aHQ3NHkI/KLUoMZDcwD1ebPSwZb/wdGB0TQNb+rydtc0voadp3Y62uK2ntiqOggie6qwpPumF/EdFWKvZ3T8QM1atmSUuHloUC4/zD5L72si0TQ1yPCzz9T33LevGmBy9Khaj+GLL9T3dzEkJCdw2QzXEI+rj652/J5tzmbYvGF8d+N3DG9ZPmu0QiXrDHjvvfcYPXo0Y8aMAWDKlCksXryYadOmMWnSJLftp0+fTmxsLFOmTAGgefPmbNy4kXfeecfRGTBlyhSuvvpqJkxQDdkTJkxgxYoVTJkyhW/z596U9XMr0tYTW+nyeRe3iqzdKytf4ZWVr3BPh3uYMmAKb77pz+nTahTBiBGqUHbLLWrUQo0a6jUZGWpRmg0bVOMtADVawZU/wt+DUTFbSrhwz3WEPGo/xo+HDz5wvyEaDKpyrqu7DmuaqhgZdAbq1XBfqKZJeBOXCnh8Ujxto9ri5wdz56qwNHl57pVLvb6Im3qN1tDxQ9j0SDF7rVPPn2tHAKiR491mqylPbm9vhFo92LTjoKOxw0vvRe3g2m6bNgpt5DL6Y8uJLVxW+zJ8fdVx9+qlRuUVe9w+4dDvX5WBZx9VjTMxA6DO9WphSYM/eIWo6Vn5buj8E7OnH2TUww3Yt09V1tq0UTEH69RRDbZbtqjPDw1VUxEzM1UB5pZbSg6rYbXpoPvPGJZ2VqPX/7waOn2opphpGvhGwaBtkHdGxZdbcwc2DW5NBlP+aAQ9eubcMIc6wXUANZLz/oX3s+vULmzYuG/BfXSt09Ut7NIF5RWkOgCW9YRjC2BpD9XJFHG5et4vBgZth9NrYM3tpGcHUeeRo2TkBjN1qsZDDznfymRyrTTZK6hlnt0W1Eitw2DNU5lr04fcp1Lv+9S1QfA0nixvcV5CQ1VBZ+hQNU21SROVkQ8dqipU9uszMVE1+PzzTyw/7tnjGiZo1y41K8Bu9mzVempX3mGCQC0E3WM+rBqh1mD4rQnE3gB1b4CwDmrqpdGvfPehCnr+eVixAtatU7+/8oozryh877bf5y7G2hOPP67iic6YoUbyXXedWtitTx91z7PbvVuN2l+8GJYv9/z9//1XHWf9+s5TubjK2gXpJGn9ohqpf2wBxU51DoqDPkvOLe8LbqIWUv+zL2AtNl59sgWXsfVFdQbodDpCfEJIyU1xfby0mQH5J45ep3crQwUGqnVrXnnFOerOYlGViV/O5s8MyP9ailsDoNiFhT1Y1FhDO7+ZAQCB9dVIvYNfF/p+ddD8cfAKcN3eLwravKoWdCsqzZs/5fy97STIPp5fKSxlCoreF4N/BN99p2YAHDlS9KAEe1iNwh5/XHWG5eU508KeB951l/v2bduqEci//ur6OXq9GhCzJeeASzmpyDUDCswWsNgsFTMzAFS4xr8HFnjAlh/CsdJN9C6Rl5eqd/To4QxlCu7hZM7p3uYVrMpfK6+FpCWwoBm0fFYNLrE3QgXEQnAcAHuON6XZkypUzP/+pxqtPVGwg6BUphQ1CjInWQ0SMAapspfey30msmZVM6j0PqjOtzPgFQbRVztDt1USOh3MnKnyxw0b1KygceNUfbRNG9frf8cOtRj4fUmfqh4+T9UDXvVV329gQ2fIU81W7ACcp07D6QKz6RfcsoAr613p+HvSP5OY/O9kNDQW7luI0WIFDI7G1LKsa+KJPXtUYxWo78ZehilcVyo8SOZszlmun3c9Kw6tKPJ9H1j4AA8sfIBrGl/DnBvmEOIbcmF3XJyzX35R57zJpKonRqNzlqu9s8zeEZmXp8YetWqlZob06qUGevburd6rcD3Ry0uVRYOCVP3788/VrLuiBoPaWSxFD8IqVewN0PUrWHu3qvv82gBiBkHscHWP1ZXQUVcOcsw5zNk2x5HnNw1vSt0Q16gd/Rv1R4cK/WjQGZi5eSYjWo0AVJnhzz9V+hTVUG80Qs2ahR40eMNl0+CvfkXskQYtnnJ5JCZGDYIrbs0jvV41XIMaCPX339CtmwrnZB/8U3jfzjnijd4IvRbkr7eyA2x5sG+a+ikkIQ/25A/8NOqNDGwy0DFr1u7qRlfz5r9vAqrN7ustX/N2v/zGxfZvqcGeaduLX7Oq7k3Q4W1nPaPrl/DPjahyZ+EEMUBEF+j+LVcGRDJvnhr0bDCoyBTDi2lfv9D376IkpiQyeE4Ro1eKMOqXUcSGxNKlTpdy2ZdK0xlgMpnYtGkTz9iHD+fr168fq1evLvI1a9asoV8/1wuvf//+zJw5E7PZjJeXF2vWrOHRRx9128begXAunwuQl5dHXoH5een5w8kefjOE+i3v5uVmD6oL5NQp1WgVEYEt0Mazez7hdO4ZsJmY+YiK8f7VVypOWWk6v96IDRbPYvfOiJ/BV5tnkBsOs5vD0AlLePKLnvzxhzeLF2mqo9Jfh14PmRka3t55PPHke7z4go0/JvejXWsjM2ZEQux0OPIM2M4COtBpqODYVvCqy6ZTo+lYYyL8Ug9GmIsueOWeUtMz805B7mn4/TZIBRqPgSYP8M5ISIqPZt7KaPQ6GzZNj15vI9jPxI9Pf8lVafscbxXrG4kxYav6w/7dBulpYjrqaDj31cFdq++G3++Gy6bROaIzf0/3p98DjUjLNubfQHXodRp+XhY+vm8J/To05fTmDDp2UI070A38RkL2HEAPOlv+cQNRz7Bp4RE6+ubfTTw87uiGfYgmiXvGqJh9EAb+YyBrZv53a1P/e9cnx28s/6Vc53irur6R6DcnuB13I7Mz7p2vDsasuQf+uAcum0aniM6s+NSPq+9vTGqW63EH+2czZNB7vPiCjj8m96Nrx9l8+PxHkL5ANQYd/T1/f+wK5DIpMDK1Ic2+2MYTH8Ty96Ygtm9TC4XZm3EMehtWm54mDc38dnNLxs39gNtu7c+sWXquH6bRq7cq/Pj6qnPQZIKMDI11a+G992vw36pFPDHwXR68eQ780R5CWkF4Z9VJZQxQFaWz8YCOT8/qWZ5jBWwY0PFA/eHcbGoCu5zX3oz6o+l26jFA9cQmT7+RRvUTVIzevn+7px1A2i44C+Sd4puFC/nr9EdggphGd/NC3L2qQajA9Z0XYGLi3hmcyj0NNhMLH/mNuIAf+OCFmbTle1jSFXwiIbwLBDdSFcCsI4AOX+9cmsXsZsN/nUlIcM2lvL1dFweyZ/i5Wbn4/pLf6thnGURdpX63x9OPiICaXmqEf/45eNtHP3Jvl9fobh2L4fhClenWulJ1FICK411nKKTtgDV3sCm9Ax3fiYcMoP86dZ4Xbnj/4iOoHwqmFEy5p3l098vk/a8eBDfl6Q6TaRIY6/yeAIL0LDBt4ueTq8FmYnRQCl0z/2Pn6FAm7N7D/34LZ9IkPW+/ZcNg1BMUlB8jPceGxaqnc4ccWFXP/bgLahAB9XEcd/zcqXSos9Y1vQuuOxBohYj86zvvFJuWJdDRkJ8nlOn6rsvjD8/l1r5vQdZaNetm/6xC15Ly986e9GqxAhZ1gpHF9LgUOAdzU5LxTRhV8nEX2qfHZz1DmvEo+IQzot2r9K3ZxS0ttusPMeXYIrCaiD0exYst5rsfdzHnVG7WcR778W5MeUBwU57sMIm4wPpun/GraQO/nlwLNhNeyRrmwHgwweWtn2dMvWFquwL3tTS/TJ74bw6aNQ+jLZcND5/ixfkv885bd/D110aGDdMYMABiY3UEBjpHkh47prFju8aV5ivpUHu1x+n96W8/suHsDDBBrYZ38kaLsa77FBGBFqjxxK4PSTOlgs3E57pNfFYPhj75IY/Nu4effvJl/nwNby+NOnX1eHmpad0pZ61YrAam3PUczHkD0Lmmt32/Cu3TOw+n4pOYw+x/b2fIEAPjx2t07gxBQUWXYnNyNK7tvt81H7NmQvK/kL4JSAdfI/gFg1ct8GvLkoTLufORMKJJYv06MAY+B6FBkDIHNH2B81YHOl+IeR7+Vw9SQWs0hl3GR9l7yIeD+8wcPqSRlWfEZtTh5WejVlAq9SOSWb6lPsv+rkkMSWzaFAB1P4ek58F0uMBnqGMy2QIITRvPk9h4m7cxYybs4AlIjXdJC4KgBkZSCn0HVpsZ7zOpKlxZoXPQOyPBMWCgr5+Nhzc8Aksfcd7XgEdapjLF9wrSc7xAB9dfcZhWx37j++S1WAs0JhsPHwXN/TOMyYfcZisA+OZZ1T4VOs99NGdcFINJzxdZs2DOLI+v737XteH0VnOBcguQdh3Y1gD7nN9t0NVgGsiSzw9z5z1ezvQ2Alp38O4LJvsccz1ggOiX4UgW0S2SnOWW+8dCRBCc/iy/TmbLTzp7mbA+BDSDxEUwpR5hAzex4XMDtzzbgGXrgzHqbVhsqnxns+mIDs3ky3G/w8cjVJnwsmkQ0ZlawMKJVq55vgMmTY8GGPQaPz73O3UTk8n8+wMCD29Xnaxd1IHPHJlCv4R2bD4UitWmR6fTGNTlGK/3/JUGCRsdX6EOHbX2HgX9CZdzKtrX2QqtofGj9SeYo1MNi21ecU8LUPfnJJUWf3+3gl51Z+B2fRfe3n4/TztLg+a9iCaJ6dOgs32SzElAawC6Q+pvrzpwpjHk7CJ+wRj3+1oJn1GWfMyUmcw7X28Eax5PNHwb7zbPeHTcX8zIxXR4AzV8bYx4ZhAYjPkhEvNXXLSlg5aOY60xUwps+hBSIeKyaaz8qCtj367Lt4vDHOcHgNGg8vuucYnc99IVWA3HwSec69o8z+DIHm7X3kb2Mz1pOVhNnNzViQ1TJxAX8C1/zvsUfdqPsOFB2PCIamDwraVmPmUcACAlyzlCvF27og/ZzZbn0a16HVIh76p4tu33Y+8hH/busnIy2YZZr8foayPI30KTqGS6xP5Im6hP1GtHFtOZZp+Zab++hzbLv74bM2N6Ohz9Cc7sUGu6kA2+XuAXCIYQ8K7L5wnHWJun8rGoRnfxWvOH1fsWysee3j2Vs3lnHfmYlgL/BU1gl3Y3ew75cirJjN5mwaYzgpcOndGCzpKF0ZJOy6g53Nx5Op7mY2QfJ3rR3awaZOTj9n/z8pwuTJ5s5J23NWrUgJjaOnQ6SErSOHtGo01bPV0HLaTNaziv78JlToDpr0LTBmBKYcm6MF58ogHPDnuDIbyJbv+nUPtatY6Kb6Qa0HTlD6oRauck1ufCtDQADT06rgxvz6DMaPh7jeOcesa/MZ8YfEm35oB3NuOfbkP8dx/y5BO92bxZz623anTpAqGh7vlxTo7Gyg2JfL+6EZjAq9aVvNNhEgFGP7d87OPEb9mctheb2corw/swZcETDBgQznPPaQwcCDExRef3NpvGY9Mf4YNTH5d+rgK/7/+dGpNroNkn1reb7NZAWdQ5WOx9rZj0di2nLi16zbRCnxH/fdnK5yT/Basnq3JIv3UcOenH9gN+7Nhq5fBhyDP6o/eGAO9MmkYl07L2YR40jyLcBo2D47i1xWP0iujkcg+xBsJX2StYlbKN1en7eSLtcka3XnCOx+1Zfey6624FVLipu4ufZOeUtIQ7Mq9h5vLRTFr/IX36+NCksUa3bhqt2+gJDVWdqseOaWxJsJGSamDL4w0YP/d97r9vCF99ZeD66zX69LGvGaBzrBmQnq7x778QdvQlap78kf0HG3OiwVSsRh+sBiPeeis6qwXNoEdnVMPZzdk5mDLSmfx+FNG05MtPZ9O65mTISYDD38Oh7/PbjFzFH2pDh0UdyyUfI+8UC3YvJNOUCYABHUNrdHErE9YM0tM2IJaErENYNSu90pbBxzpIBd3ATXw/AR7S1+Wzn2oWKrfoadvwON0v/5znnzOw+O2r+fhDY37+HQ7+d0HWrPzW5vxjD7sTUuqQuay1S7nl+vrw7j3+PPl5HHqdhsWmx2CwYdRr/O/xZbROWgQrp0AqNO2/jnUz/Rk1sT6rEgId+SNoGPQaNk3Hbb22wZz8qBYelluef7ctMz8OV+Xz9VPB+C2c/Rps2fm93fYXGQAbX5uaAbsANWiiv76J63cbEUH3ABM+OiN5mgWrZmXu6CtYfjTeWU6t+RFkPgKWLQXqAPllyOCBLNn9Jnf28CKa+Pxyaj2oPRmOTVAdvI46gwZeURA92VEvuaHxGFZ/8TgvfxbNH6tDXMoUOp0GGkSGpXLtkA944xUzTzR8B+/bCsRaK+76Pv0fvtseVH/fcKboTvkC9zVTVjJdZt/DKZ3qOTHqDKy+YhaXmWs5zsEjPim03fM0qZZsss3ZvPrewyzotNH9PC/uHnLqcNHpW4RK0xlw+vRprFYrkYXmuURGRpKcnFzka5KTk4vc3mKxcPr0aaKjo4vdxv6e5/K5AJMmTeLlIkYuzLaBtv8L6r73BffEuz73weUweQDobWAr0Laa6OEApIYY2QC0SYbOx+CdJRBSKF7gX/XhhT6wOxyyA4E/QfcT3Ew/bgJ20ZyF2iBWaj04mxmKDT1hpNDVthprflzbf7kC73gz2EOU+gGdgU4aBAFnrbAe2HSE3F7/wqj87ewnbsEFWn19IWMRLJri3Mk/gZ8APgc+xwDMBe6iHx9qY0kjhCtsq3gm801Cnk5j8IRIjlpPQCpccfg4PO0eO7VFDbhsOFh14KsHttg/4wEALgMOEsznjOFXhqChp5+2hAfyphH+cgDdjt7BRF6HeJzHDWrEyRAbhAPHrfALcPJ1cq++uszHfR8vMZGX7YddMGHhOg0CgB0a/LIfX+t1DHE57qPwlPtxNy/luDsCBwliBve4HPc9eZ8xXXsIgzE/vdeaYTDgBbQCOtkgAvAFcoHjNtgDxAVDRjr8BB1ozZ/AUWozh5GsoAdnCcMbM9G2JIYxn2uPb8Z3xz7+2HcNKdTg76W92L20Ge/RgP9oSCaqJc9oMxHDcRqQSKbfQO7I+4kHf54GC/K/nwbb1U8E4I2KIZEOnIAO3hF0iFTfk7dV48W35kH2PJfvqSvw0DWwRk0WoFO3/JkO3mHuaQfgbYRtt0H+TOUVR+oy037N7v+ChSu/4InV4J3fsZ1jhDevgB0FbiMv8SkTs16GZwAfoBHQ5AQ0+hUCUXlfHnAWvJPNrB/dgz1/12Pd5114+YtGmJu0gPr1CYwKROfthc7LC6xWNLOZ7DM5+JuSedpePwrPb0mwx9O3n4M/3w9nnOdg43+fo8eqVeAPNPsDav8BNVHfa7Av+PhCbg5k5UELyDX7qOcigE6d3b8rX1+IOQBJ6jPWZMMnuSqv1qXsJfuDYcz5yfWcNRng/nGQFAg2HfQ3An9C2E8pfEot3sePv+nF79Zr2G1tRkZeEL7kUoej9Gcxvc/udr5ZeDH7VOjaaxnp7ZreBb8ne3q/bVHHCeTu7wpx+S8u6/U9FfUTCLQD2tmgBio3zgaSgf3g3dXZuOhQ8DMKnYO2PF91Hnl43GZN3WbSNdBnn+H7vx9ky3Son+r8uHQfGHo/HApRedLIjK6QgmqYs3e6JiWp+cn2KT3v3ghpasronzaYZlN5Gil78Z18A1MLrQGlAU89DPvCQNNBLaMPJ/LAYIOv419j4J2vUbvQDNB3esMX+YP0fAwwfQvMih/NxzzM34d7sfODFvz4QRwHaEQ2/mjo8CObRvxHx7onafnqxjKl9+fHQ9gIGDSwHviSUeO/pOkZ131KiIL37geDFawG+Hwr8BMMZiyDGMt+GrNY689fpl6cPBCJCW9qk0FbttCfxQSEFDGbr+B+FdqnOsCXdeDD9eNYu+ByEha04mtaQ+3aGEODsPn6g16PLicLa2oGNUij29HNKh8zo/KqJqi2Xa8ICGkJBh1YjsHZP8Cazul993Mfkeq8LTggpT7QwwYNUO+VoMGqHAh5ltNtwnll4QvM5RZCm9Zi0CDo0V+jb2MN/wAdXkbIztY4exbWrtOz6he4j4nqM+xZmBHohMpnagJZmsq7NuRhGGvEALRLAmwQed1tqjOykN5DITQKLDqIDIAzmSr9bv3sWzj+rdv2g0KgxzDI9IbLI4C1Kv143nngYcAqWjCOD6ivHeSjlY/AylyGt4lkcX8wp6kyV993XoTMF90+465Y2Npf5cehtSJINZ2GVHj4px0w3j3/buUF1w+DgzXAx6YH+2QmD+9r3bY9V3S5xQe4FYgB9mvw3RKwLeF02MPcR7h7egP0RZXz8mzwkw0Sn4W607iPu93LLbWAy4GW+Z+VZIWNQPxBePIE7Ld/tx2JABajYylX87XtNvbThHDbGW7kB4af/p7AF2uo+2SBcgtAb2AxV/IWT2HGyDjrh1zz8h/wRV18Ox2B+VDwwEOBPwnkcd5lF824XFvHG2uexWuohWF3NmFtZCqkQliOhtdll7ulRTDQ/W6VlwPq2gFneJ5SygjeOe7vWfL93I/7eEp9tw8Uel0gcDeqPDbzMKR2gbp1aflqfthID8stZcrHbF6YLc+hClieH/fA2lFEt0qG8Mug8Wfu38HWia6zDaFAHeABIoA5wFi68KPtBtbQFRs6LrNu5Hp+InjbHjo0PoHBClr2GdK/eJTBP7h/zK+9YdaVqonAery+s/w1OP+QmgKtrFA/EXwT1YzHDOAIXJ53kJ19m7N1WRsWdmnBgrhmeDWKxSsyDN8gbzAa0Bn0aGYrNpOF7FNZDGuzmrQ/OvD+X4/y0/NxRDXwZ8AA6NbPRscQCAxSoeEyMzS27WjO8n/acLd5L/2Cl0H69RDdEIJDwT8YDF6qR/v0b3B6geOYum17jomdXod+wB4d1OwM9a+GGneo2Q9GfzBnqhvTyT+Zk/k7f9lU3mrdP4urn5tFz0Ou39OixvD2bfnbmIKp8/NLfLT7EZp0Ceehh2DYUC1/lLJ7I3RKisaWT6a6f/kl5GP29Pb6ycJ4ruAR9GyiI0ttV7P6bDdSztZAQ0dH0ujCOgad3kpc463q3K9TTw2HLuoczHvBcQ6ePnELA042ZeinC+BLoNlJqD1D/dRCvZeGqjc0hWZe0C0LctNAr2lM+jwejrren0OASZfBF+3VS29suJO3W/Xl5N6arJ/dmfWzOzCLlujCQ7EFBGPz9UdvysWYm4XpZArWPj/x8xWqLVSX9A+GiVcw9Q/Xr21VLDxyl9rGpgezZT0Tct4mIbEdW8a05W1akRzclMDYUDQfPzRvH3R5uehzs0lLPEv4oNPQCmJToc0JeHspNCs0AHtrJDzTF7bVgqMFJwV4BbunI7jNDi7yvlZCeruWU4t4bRGfUdbyOUDWEn9m/jqaT54PZg/N6NAB+vez0bilRnCwDotFIz0dNu+P47MfLWwbNAqAv9P28Pma+4rerwICDUWMZPf4uD2rj8257Bf2bmhO5mdN+d+ROAyhwRiD/fEJMKLT6xxxoWxWjbxMM439t9N5hZX7fv2Me5jBZtqzaX9H4vd3YCFNySIAA1ZqkEobtnJF3UM0CD/IL7uHkUYwf//Ti93/NONjGnKARmQSiA093qj6dyMOsDjmejYff4WbboJ5r5b6NZGdDanv55fv7F9rDVSjS0tUxqoDMoFEID2Slrfl1+HKIx8DrrBA1yzIy7++r5v5NRz52m3fR3eG/7VT13dvP2AdjnKLEfgUuJvOTLfdz27iCLedYRRfck3iQt7WnsHL26LaTx4wu75xW6C/pur4fwLrvoS6fxZZbnkM6E8LXtOe4xD1aG7dxUvWV4h98whsD1N5V345tRGwAh2LGMB86zC20QpfculpW8nNzKPFd5nQIX8fPMy/922cy33sUulnH5DgiyoPNs1Pv2xUGW8RDGyQxopeQKoqb181eQLkuIYQ9wHuHgTr8oNZDDm2gYlc51pO1QFtgF42VXg7aYVlwN4/OB32XtHl1BpAf9S5YNJgNfDvMYgZqc63/HbFLnzO70ACbfnY9hAHqU8W/kRqJ+nHEm7NmM37uicwa4WmXXl6fafthFpX4KbAfc0b6HcWduWpQ71/o5XLXrrDZfO6wLyG8OxVqi2khdmrTPXvtfvcw6wWR6dpRU1yufQcP36c2rVrs3r1arp27ep4/PXXX+frr79m9+7dbq9p2rQpd911lyMEEMC///7LFVdcQVJSElFRUXh7e/Pll19yyy23OLb55ptvGD16NLm5uef0uVD0zIC6deuie0aH5qthQM/10X0IthggL5cUg4X5KavR8kciXOZfmw8bj+FYtoWkjCSSM1XHQ2B6LjWyLFitVmzBoA8Cfy2PaB9/avjWIDr2KupGdnfdmQIjzQjK78E2pYApla2agQMZ2UV+RmqAEYIhSMvD12bhcO4AAFo1tHAiy3X7oPQ8DAYDqQFGMoN9ARVjNTooGhrU54yvxqHUQxxOUz1VYacyCc2ykhJgwBqhp4aWQ0O/YGL9/DHlxJCTopXpuGPq9aVOrW4X/Ljtn6GP7kKG2dtt+4t53BnBPm6f0aZuRxoFxl5S6e0TVIO8jNRSP6O2TwBRPr6kh8YV+d2WlN7poXHsPXvGsX3hzyjT95Q/Aoe8047vKT48jHhfb7e0C0rPw2gwYvU3o0WoylBDv2Dq+Prxz8lsXtkzl9Lo0TEtdghdwrrwX2ZOmdLbJ6gGB4/vKvK4zQFW9Pkxx+3f7anGnUgKjXIcR70DZ3jlyYWO17719lVkNvAlUMulvl8gwbo2RZ6DRaV346BA6gQGklknjpNBoR6d53V9/Xh153pWnd2FVbOiA7b3+p4WuUGO3vBP8/7i/iMznftYuz/9a/Vk1fED53zcxe1TcccdfTSNBz5Y5ZJu349tx+k6gY7POFm/Dck1Y8v1+qZBfeJzDzrev+BnFD4HY/38yQhoxiljDY+P26Bvzh0bp5CdHyvXV+9NY58Y9PkxGQ5aTpNuU6FJdMC39W+ix8pMor8o1KJfDKsOmj8bwH9eOVix4W/w5US/pQSmZDnSe6VuDz33qVqFAR39ghrzR4aa7WXQ6Rld9zo+bfuc43o94ZtB/R1jydXMGNDT0q8ms5o8xKFsk8f3c3OrviVeFwDT3rqCpIYhNPQL5nDWSV7auTx/H/U813Q0L8fd73IPefz4Z3x4+Gcs+XGzZtW7ixCv2mW6r51q3Im1ujxH2hXer4L7VNo5VdRxG6I6EWf5nTq6Xdj0/uibPwqNRkNgA9eEyzwIC+LAZmLrSS8O1LifpNzsIj+j4DlrSm3Hy2/eRXqGH2+8oefpp9VINHvossLs5detCYtZtfb7Uu/nkQHRnD6pemwnDById8E3LeF+TkhjCHSNW1p45PC55pX2+0GJZZCCn2HfJyh5v4rYp+LyJU/va/ZjOJ/8uyzbX6h8rKQywrmU14r6jBLTrwxlhNAsKxarBV2Qhhahc6RFhH8EGQHN2JiZ5vH9vLTr2/69Or7bNl2LLHMWV24pS55R3zuEI/HqXI0eGM2RzCMeHXcdbx+8s42cPXManxrReHv54G30wsdmxNuqoRly0Oly0NDww4yf0chx3678d+SER+ldy9uPmzPXk2FVeVi0TwTH+y12u/auSnyNv1J3OoII/NViAikmwwU7zwvfz1cnXMerXz1CQAD8738GtbaITf0YDM4wBAXvj1sTFnNgx6rij7sGBBny8NflEePvR1xAGrHaFmyBceh7/gwhzdTaUzq9+sk6rM7Z7GPwz43syTPR5hCYUOEZuoe2ZUX3GY7vSgsPp9POR9iScQArGl7/PoN56SSCgiAlxbPwepoGm5Pjmb9rfrnlY4Xzb0/Oc0+vJXu5tlHk5dQL64CLUu7nWzWDx+XUmt4+vGw6yJKUrY5z8qbovsQSAjk5mH29mXVqCenWbHRAqMGPOU0eItviW673tZLyPavVii0U9DXAX5dHtL8/NfxqcDKqDet02oVL7xrO8zza3x9Tgx4kh8Z6XF4LMdXksfHPcvCQGozw0Uc6GjTIn4hkc42lbg+pmn3kANPXfsLjO9+jNIsa38HVQY3YjpdLeheuN5RWZzjf+tj55JXnWv9+7YvJ/LO1CwMGqDBunijtvnYx8zH79g19u1Lfp73rjl6g6zvKO4itqaqVuqj2k+KOu35M8yLzmAuZ3iXVjYsrt5hyYvjv8PFya28p7p5zMcupBc/zWt6BrE/rCUBEraOcyFI9I6Vd32lBDcjUAj2+rzWvM4S6tXqXfg6C47tK+nmNx/Xvt7mHp5hBWloawcHFdO7mqzSdASaTCX9/f77//nuGDRvmeHzcuHEkJCSwYsUKt9f06NGD9u3b88EHHzgesy8QnJ2djZeXF7GxsTz66KMuoYLef/99pkyZwqFDh87pc4uSnp5OSEgIhgkGrD7FxMHK52v05fhjxwn1Cy1xu4vJZDI51keYMGEC3sUFdRdVgqT3uZm/az53zL+DTLOaguhj8MGm2TDb1MiAYJ9gvr/xe/o1Lipu4EUQH6+CNNtt2nTuiyCfo+MZx2n6UVOyzCrsgp/RzxH3W0MjOTPZEUrjspjLWDN6DQZ9OQd5nzixbDFoAV56Sb2ukvtj3x9cM+eaUreb3HcyT3V/quhVPu2L9xVeuA/43byTQYucce6e6PoE1zW7zvH3i3+/yIrEFVix4mv0JXFcIm+sfIOPNnzk2MagMzjiTlptVkfoM4POwPYHt9MsolnZDrqwwtcFuFwbNs1Gi49bsO/sPmyajdjgWA6OP+jYJ4vNQvS70ZzOPo1ep6dtZFs23bvJLVbmee/X+V6v8U/C7nfVFNb+GyGgroqdbGdvPErb5bqQ9YBNaupyKV5/Xa3bEBLiXMvxQpJ8SYiKcSlfe7f+eCvf7fzOEQP62GPHiAmKcTxv02wETwp2lDnaRrYl4f6EctufjAx1D9Q0+PRTFYv7nOM1F+fE37A8vyFh0A61Xou+0L280KK4AO+mwBMFBjXXDa6Lv5e/eokpi6MZRx3PTWjwE18/N4yjR9VxjB6tOgQ0zblYPajGVZf11QqGcIFLY82mS1CuJZcGHzRwaWQrzsZ7NtIxxn322CWpvOsZpZTX+vSBlSvhyith2TLn+empTcc38cG6D/h6q3O0+As9XuCeDve4xpYva72hcJ3hEqiPnYuMDDhwAI4fV+W8nBznYA+bTX3XOp26R4SEqPVALsY6XZeKSzmvFKVzSb/XX8fbbC7lFfkuRptAGerfaRmZ1OjV06POgEoTJsjb25uOHTuydOlSl0b5pUuXcu211xb5mq5du/Lbb7+5PLZkyRI6deqEV/4KKV27dmXp0qUunQFLliyhW7du5/y5JVl02yIG/TgIk80EQExgDFbNyoksNb3X1+jL+jHrL6mOACGEZ4Y1H8bZpmd5beVrvLLyFfKsztlBb/R5g6e6P1X+DduXuJigGO7tcC/vr1OrH+VYcjiWcazIbd/p987F+b7uu0+tSFyQPYOFIhu53f6upAY2Gci313/LqF9GOc7XK2Ov5J/D/wAqhvYrvV9RHQGgjrsMxz5Qa0/chtfYc0YtwPjOmnd4Z807RW57b4d7iQqM4tU+rzJ903RHJ5pVsxa5JunwFsPPvyPAA3qdnhd6vMBt81WDxuH0w3T4tAPBvqqAlZKTwuls1fhh02y81POl8+8IuNBSd8Du/O/9sk/Bv457R0ARjUeAikHpgauvVvFts7Jg1iy1mKvZrCqKRX0dZnPxi8QKIYQnBjUdxJztcxx/rzu6jmHNnfW13ad3OzoCDDoD18aVve5WFvbGME1T97hyYQxw/p53GoKaFr9tAeNrwMQ0fzLN2QAcST9S5HZhfmG8fvt1vHwLLFoEa9bArSqEOREREBrqHFVtNqtZXseOQSyHee2HOHS5ReQjdoXj+/v6qhVyq1mHgK/Rl7Wj19Ls42aOBev9jH74eflxNuesY7vJfSdXno6AS8CuXWrGTefO59YI3TGmI18N+4oPB37IgbMHaBPZBi9DEavqllRvqMJ1hqAgtXaKx+unCFFZrVrlOq25oq/vMtS/dflr1Xqi0nQGADz22GPcfvvtdOrUia5du/LZZ59x+PBh7r//fkD1wB07doyvvvoKgPvvv5+pU6fy2GOPcc8997BmzRpmzpzJt98648WOGzeOHj16MHnyZK699lp++eUXli1bxqpVqzz+3LLoXKczWx/YSteZXUnJTeF45nHHc7UCarFuzDrq16h/jt+QEKKieRm8eLn3y1zT5Br6fNkHg97AyrtW0i6qXUXv2iXjnX7v8MOuHxwVUW+DNyE+IZzOPu0Y9X1zi5vpUa/HxdmhMjZwVzUjWo+gZa2W9PxfT1JyUxwdAQadgYUjF9K/cf9zfm+dTscLPV/gtp9uK3k7dDx35XMAhPiGMPv62dz8w82O5zvHdOZw2mGSs9QoutjgWL65/ptz3q+yurnVzYz6ZZRj9GnCiYQit/Mx+DAkbshF2y+PZR10/h5xedGLrBXHHru1FJ07w7Zt8PTT8OCD8PnnMGQI9OqlFqTz91fl6pwcSE9XDUwHDsALL5TlQIQQwql/o/7o0KGhYdQbWXt0rUtnwNqjax2/WzUrg5oOKtf9CQiAH36AW25R90J/f7jjDtUwaTKpBvT8cN9oWqFR9Z4Kvww6fwYbHoCV18NlU6Hujeq+bjODbxRcsw3yzqieifxFSQ3BTfkuNdVlNqAxPy+wFFgE/dcRv6LT6fDyUvfwIZ5maYeBItZsEEWrV6Me+x7ZR+cZnUnKTCLHkuOYqQHw7Q3fMqLViArcw0tAUTNNCivw2C19avP+nEi++w7GjoXIyKLDFNppWtGDFWr41ii5E6as9YbDh9VsgCL2uci/q+mMGSEuGe3aqVimVVyl6gy4+eabOXPmDK+88gpJSUm0atWK33//nXr16gGQlJTE4cPOWJwNGjTg999/59FHH+Xjjz8mJiaGDz/8kBtuuMGxTbdu3Zg7dy7PP/88L7zwAo0aNWLevHl06dLF488tq7iIOJbdsYxuM7s5RmIGeQfx151/SUeAEFVElzpdyHouq2J3orRCdAUVPvV6PZvu3USzj5txNucsJquJ29vczntrVbzOnvV6MufGOaW8i7iQWke2ZtXdq2j5SUvHY0tuX0KfBn3O+71vbX0rr/z9CnvP7gUgwCuAmv41OZJ+RI36B0a1G0WtwFqO19zU8iaOpB3hiaVPAGDQGxwdAaG+oay/Zz36izik3Kg3MrLVSL7a+pXjMS+9Gi1mn8EAcG/He9HrLsGh7gXXBTi9GuoMc+0QCIiFIXvUKFNQswFMqRDYEGp2xVP16sHcuWqNrXXr1IDPX3+FQ4dUJ4DVCl5eUKsWNGgA7dsXXxkXQojShPuH07l2Z9YdW4fFZuH3fb+7NPjP3zUfg86AVbNSw6cGnWI6lfs+DRsGCQnw4YfwxBOqU6BvX+jWTQ0qDAhQ98jMTNi6FY4ehfnzy/ghje+BmlfAgc9h85Ow/j6o1QtC24AxCAx+YMkCSwac2QCWTOi3moE14Z2r33HkrV3rdCXLnEV8kmqo/HTwp3SP7V7CB5cgNlbd9AuWO6HkEZXVvNGzTnAdlt+xnMtnXk56Xjpncs4A8H7/96UjoPBiwcUpMNvkXQDDFKYcGkvXrjoefxxGjFCdAkXZu1d9RLny5DhkxowQogJUmjUDKjv7mgEFYzetPLSSnv9Ti1SsH7Oey2pfVpG7WCKz2cw336hRmLfeeqsjzJKomiS9qwBPC9EFXeTC58+7f2bYPDWCz0vvhdlmxt/Ln50P7qRejXPrbBXnZ2vyVl5e8TJ3tbuLwXGDL9j7Hko9RJOPmmC2mTHqjcwcOpM7f74TgLjwOHY8uMMtJJRNs3HVV1fx98G/XR7/7ZbfGNz0PPattJjGUGRc48yoMCLfiSQ7P8TCwMYDMVvNLEtcBqg1QU49cQpv4zmOJCnvWMubn4Zdb4N3Dei/AQLru4YKKih/3Q4uoY4NyZeEqBiX+rU3+pfRfJHwRanbdandhbVj1pa63YVktUJioipa7dmj1gg0mVSnaFAQNG0KLVuqW/t5dYqaUiFjP2TsA3OamiGg91ZrxAQ1gcAm4KXCC1ltVrrN7Mb64+td3qJ3/d4sv2P5pRfmrhpYfWQ13b9QnTBPdH2Ct/u9XcF7dI4uZCz8otYH8NC++duZubYlv/yiZiDGxalBCMHBKrRVejr895+atVggGET5ONfjqCTrCAinSz2vFCWrKulXVLtzcaQz4CIpLlFOZJ5Ah85lRKQQQpy3StAZAHDH/DtcFuqaOXQmd7e/+6J9vrh4nl76NG+tfguAxqGN2Z+yH4CFIxdyTZOiFzE+mn6UFh+3IMOUAcD9ne5n2qBp574T53JdgOPa+DDpZ8YvGg/A9c2vJz0vnaX/LQXO89y9GNerzQJrbodDc8EYCE0fgkZjIKix63aaFdJ2wtFfodVznu+PEEJUgO92fOcSVq4447uM5/0B71+EPbr07Tm9h9bTWjtmtvkZ/dj10C4ZiFGBVhxcwYGUA4xqN+rSnGHoiQvZGXCe5TV72chigf371QzFvDwVmisgQL11dPRFmJlYSepjQoiqQToDLkFlSRQhhLggCo80hktuunZqbiqhk9WC6R2jO7Lhng0yKq2KSs1Npf6U+qTlpTke61W/F3/e8WeJaf7Dzh8Y/v1wALKezXKJqVtm51m5zI6OoM57dUjJTcGoM2LVrGhoRAdGc3D8QbwN5zgr4GKOHEteDttfhZP/ADbwiYCQVqD3UWElUreCJR3CLoMB60t9OyGEqEg2mw2v17yw2Wc0FePguIPS2F3Au6vfdYQL+nTwp9zb8d4K3iNR6ZT3jMaS6jFwydRlSlUJ6mNCiKpBOgMuQdIZIIQQRftm6zd8sfkLZgyZQcOwhhW9O6IcfbD2A8YvHu/4O/7eeNpHty/1dbtO7aKGbw2igy7AQs/nWbl8c9WbTFg+weXpjwZ+xMOdHz6/fbrYI8csWSqW9Ok1kHsCrHlg8AX/OhDRDcI6gMHn3N5bCCEuouYfN2f36d3FPh/kHUT6hPSLuEeXPqvNSoMpDfAx+rD3kb0yEEOUjYx4F0KIS450BlyCKntngMlk4oMPPgBg3LhxeFeD1bWrM0lvIUR5MFlN+LymGpj7NuzL0tuXVvAelV16Xjp13qvjCF0U7hfOkUeP4Ofld35vLCPHSiT5khAVozJce9M3TueBhQ8AUNO/Jh9f8zGTVk1ic/JmdOgY22UsUwZMqdidFKIqkVj4QrioDHmlKF5VSb+ytDsbL9I+iSogOzu7ondBXESS3kKIC83b4M3kvpN5d/W7fND/g4renXMS7BPM+MvH8+rKVwF4qvtT598RAKphvxo17p8LyZeEqBiX+rV3W5vbeOSPR7DYLJzKPkXv+r25d4EKe6OhcU+Heyp4D4WoYiIi1Ej/ss4MiIgov30SooJd6nmlKFl1Sz/pDBBCCCHERfNU96d4qvtTFb0b52Vcl3GOzoAHOj1QwXsjhBDVW6B3IL3q9WJ54nI0NH7Z8wupuakAxATF0KJmi4rdQSGqmthYFfJHZjQKIUSlJJ0BQgghhBBlEO4fTvy98Rj0BoJ8gip6d4QQotobEjeE5YnL0aFjwd4FAOjRc23ctRIPX4jyIDMahRCi0tJX9A4IIYQQQlQ27aPb0yayTUXvhhBCCOCaJteg5f/bmLQRABs2BjUZVMF7JoQQQghxaZHOACGEEEIIIYQQlVbjsMY0DG0IwPH044Bap6Z3g94VuVtCCCGEEJcc6QwQQgghhBBCCFGpXRt3LaBmBAD0qd8Hfy//itwlIYQQQohLjqwZIDyi0+mIiYlx/C6qNklvIYQQlxLJl4SoGJXp2hvUZBDvr33f8feQuCEVuDdCCCGqi8qUVwp31TH9dJqmaRW9E9VBeno6ISEhpKWlERwcXNG7I4QQQgghhBBVhslqwuc1H8ffieMSqV+jfsXtkBBCCCHERVKWdmcJEySEEEIIIYQQolLzNnjTqlYrx9/SESCEEEII4U46A4QQQgghhBBCVHp96vcBIDYktoL3RAghhBDi0iRrBgiPmM1mPv74YwAeeughvLy8KniPRHmS9BZCCHEpkXxJiIpR2a69+zvdz+/7f2dSn0kVvStCCCGqicqWVwpX1TH9pDNAeETTNNLS0hy/i6pN0lsIIcSlRPIlISpGZbv2mtdszr5H9lX0bgghhKhGKlteKVxVx/STMEFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBVnrOgdEJWDTqejZs2ajt9F1SbpLYQQ4lIi+ZIQFUOuPSGEEKJkkldWbtUx/XSapmkVvRPVQXp6OiEhIaSlpREcHFzRuyOEEEIIIYQQQgghhBCikitLu7OECRJCCCGEEEIIIYQQQgghqjjpDBBCCCGEEEIIIYQQQgghqjhZM0B4xGw2M2PGDADuuecevLy8KniPRHmS9BZCCHEpkXxJiIoh154QQghRMskrK7fqmH7SGSA8omkap06dcvwuqjZJbyGEEJcSyZeEqBhy7QkhhBAlk7yycquO6SdhgoQQQgghhBBCCCGEEEKIKk46A4QQQgghhBBCCCGEEEKIKk46A4QQQgghhBBCCCGEEEKIKk46A4QQQgghhBBCCCGEEEKIKk46A4QQQgghhBBCCCGEEEKIKs5Y0TsgKgedTkdISIjjd1G1SXoLIYS4lEi+JETFkGtPCCGEKJnklZVbdUw/naZpWkXvRHWQnp5OSEgIaWlpBAcHV/TuCCGEEEIIIYQQQgghhKjkytLuLGGChBBCCCGEEEIIIYQQQogqTjoDhBBCCCGEEEIIIYQQQogqTtYMEB4xm83873//A2DUqFF4eXlV7A6JciXpLYQQ4lIi+ZIQFUOuPSGEEKJkkldWbtUx/aQzQHhE0zSOHz/u+F1UbZLeQgghLiWSLwlRMeTaE0IIIUomeWXlVh3TT8IECSGEEEIIIYQQQgghhBBVXKXpDEhJSeH2228nJCSEkJAQbr/9dlJTU0t8jaZpTJw4kZiYGPz8/OjVqxc7duxw2SYvL49HHnmEiIgIAgICGDp0KEePHnU8f/DgQUaPHk2DBg3w8/OjUaNGvPTSS5hMpvI4TCGEEEIIIYQQQgghhBDigqs0nQEjR44kISGBRYsWsWjRIhISErj99ttLfM1bb73Fe++9x9SpU9mwYQNRUVFcffXVZGRkOLYZP3488+fPZ+7cuaxatYrMzEwGDx6M1WoFYPfu3dhsNj799FN27NjB+++/z/Tp03n22WfL9XiFEEIIIYQQQgghhBBCiAulUqwZsGvXLhYtWsTatWvp0qULADNmzKBr167s2bOHuLg4t9domsaUKVN47rnnuP766wH48ssviYyMZM6cOdx3332kpaUxc+ZMvv76a/r27QvA7NmzqVu3LsuWLaN///4MGDCAAQMGON63YcOG7Nmzh2nTpvHOO+9chKMXQgghhBBCCCGEEEIIIc5PpZgZsGbNGkJCQhwdAQCXX345ISEhrF69usjXJCYmkpycTL9+/RyP+fj40LNnT8drNm3ahNlsdtkmJiaGVq1aFfu+AGlpaYSFhZ3vYQkhhBBCCCGEEEIIIYQQF0WlmBmQnJxMrVq13B6vVasWycnJxb4GIDIy0uXxyMhIDh065NjG29ub0NBQt22Ke98DBw7w0Ucf8e6775a4z3l5eeTl5Tn+Tk9PL3H7ysDf37+id0FcRJLeQgghLiWSLwlRMeTaE0IIIUomeWXlVt3Sr0I7AyZOnMjLL79c4jYbNmwAQKfTuT2naVqRjxdU+HlPXlPcNsePH2fAgAEMHz6cMWPGlPgekyZNKvXYKhNvb2+efPLJit4NcZFIegshhLiUSL4kRMWQa08IIYQomeSVlVt1TL8K7Qx4+OGHGTFiRInb1K9fn61bt3LixAm3506dOuU28t8uKioKUKP/o6OjHY+fPHnS8ZqoqChMJhMpKSkuswNOnjxJt27dXN7v+PHj9O7dm65du/LZZ5+VemwTJkzgsccec/ydnp5O3bp1S32dEEIIIYQQQgghhBBCCHGhVWhnQEREBBEREaVu17VrV9LS0li/fj2dO3cGYN26daSlpbk12ts1aNCAqKgoli5dSvv27QEwmUysWLGCyZMnA9CxY0e8vLxYunQpN910EwBJSUls376dt956y/Fex44do3fv3nTs2JFZs2ah15e+1IKPjw8+Pj6lbieEEEIIIYQQQgghhBBClLdKsWZA8+bNGTBgAPfccw+ffvopAPfeey+DBw8mLi7OsV2zZs2YNGkSw4YNQ6fTMX78eN544w2aNGlCkyZNeOONN/D392fkyJEAhISEMHr0aB5//HHCw8MJCwvjiSeeoHXr1vTt2xdQMwJ69epFbGws77zzDqdOnXJ8nn32QXVgNpv55ptvALj11lvx8vKq4D0S5UnSWwghxKVE8iUhKoZce0IIIUTJJK+s3Kpj+lWKzgCAb775hrFjx9KvXz8Ahg4dytSpU1222bNnD2lpaY6/n3rqKXJycnjwwQdJSUmhS5cuLFmyhKCgIMc277//PkajkZtuuomcnByuuuoq/ve//2EwGABYsmQJ+/fvZ//+/dSpU8fl8zRNK6/DveRomuZYeLk6HXd1JekthBDiUiL5khAVQ649IYQQomSSV1Zu1TH9Kk1nQFhYGLNnzy5xm8KJptPpmDhxIhMnTiz2Nb6+vnz00Ud89NFHRT4/atQoRo0aVdbdFUIIIYQQQgghhBBCCCEuGaUHvxdCCCGEEEIIIYQQQgghRKUmnQFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBUnnQFCCCGEEEIIIYQQQgghRBVXaRYQFhXPy8urondBXESS3kIIIS4lki8JUTHk2hNCCCFKJnll5Vbd0k+naZpW0TtRHaSnpxMSEkJaWhrBwcEVvTtCCCGEEEIIIYQQQgghKrmytDtLmCAhhBBCCCGEEEIIIYQQooqTzgAhhBBCCCGEEEIIIYQQooqTNQOERywWC9999x0AN910E0ajnDpVmaS3EEKIS4nkS0JUDLn2hBBCiJJJXlm5Vcf0q/pHKC4Im83Gvn37HL+Lqk3SWwghxKVE8iUhKoZce0IIIUTJJK+s3Kpj+kmYICGEEEIIIYQQQgghhBCiipPOACGEEEIIIYQQQgghhBCiipPOACGEEEIIIYQQQgghhBCiipPOACGEEEIIIYQQQgghhBCiipPOACGEEEIIIYQQQgghhBCiijNW9A5UF5qmAZCenl7Be3JuTCYTubm5gDoGb2/vCt4jUZ4kvYUQQlxKJF8SomLItSeEEEKUTPLKyq2qpJ+9vdne/lwSnebJVuK8HT16lLp161b0bgghhBBCCCGEEEIIIYSoYo4cOUKdOnVK3EY6Ay4Sm83G8ePHCQoKQqfTlbp9eno6devW5ciRIwQHB1+EPRQVSdK7epH0rl4kvasXSe/qRdK7epH0rl4kvasXSe/qRdK7epH0rl6qa3prmkZGRgYxMTHo9SWvCiBhgi4SvV5fas9MUYKDg6vVyVvdSXpXL5Le1Yukd/Ui6V29SHpXL5Le1Yukd/Ui6V29SHpXL5Le1Ut1TO+QkBCPtpMFhIUQQgghhBBCCCGEEEKIKk46A4QQQgghhBBCCCGEEEKIKk46Ay5RPj4+vPTSS/j4+FT0roiLQNK7epH0rl4kvasXSe/qRdK7epH0rl4kvasXSe/qRdK7epH0rl4kvUsnCwgLIYQQQgghhBBCCCGEEFWczAwQQgghhBBCCCGEEEIIIao46QwQQgghhBBCCCGEEEIIIao46QwQQgghhBBCDyS38wAADPRJREFUCCGEEEIIIao46QwQQgghhBBCCCGEEEIIIao46QyoQNOmTaNNmzYEBwcTHBxM165d+eOPPxzPa5rGxIkTiYmJwc/Pj169erFjx44K3GNxIU2aNAmdTsf48eMdj0maVx0TJ05Ep9O5/ERFRTmel7Sueo4dO8Ztt91GeHg4/v7+tGvXjk2bNjmelzSvOurXr+92fet0Oh566CFA0rqqsVgsPP/88zRo0AA/Pz8aNmzIK6+8gs1mc2wjaV61ZGRkMH78eOrVq4efnx/dunVjw4YNjuclvSuvlStXMmTIEGJiYtDpdPz8888uz3uStnl5eTzyyCNEREQQEBDA0KFDOXr06EU8CuGp0tL7p59+on///kRERKDT6UhISHB7D0nvyqOk9DabzTz99NO0bt2agIAAYmJiuOOOOzh+/LjLe0h6Vx6lXd8TJ06kWbNmBAQEEBoaSt++fVm3bp3LNpLelUdp6V3Qfffdh06nY8qUKS6PS3o7SWdABapTpw5vvvkmGzduZOPGjfTp04drr73WUeB86623eO+995g6dSobNmwgKiqKq6++moyMjArec3G+NmzYwGeffUabNm1cHpc0r1patmxJUlKS42fbtm2O5yStq5aUlBS6d++Ol5cXf/zxBzt37uTdd9+lRo0ajm0kzauODRs2uFzbS5cuBWD48OGApHVVM3nyZKZPn87UqVPZtWsXb731Fm+//TYfffSRYxtJ86plzJgxLF26lK+//ppt27bRr18/+vbty7FjxwBJ78osKyuLtm3bMnXq1CKf9yRtx48fz/z585k7dy6rVq0iMzOTwYMHY7VaL9ZhCA+Vlt5ZWVl0796dN998s9j3kPSuPEpK7+zsbOLj43nhhReIj4/np59+Yu/evQwdOtRlO0nvyqO067tp06ZMnTqVbdu2sWrVKurXr0+/fv04deqUYxtJ78qjtPS2+/nnn1m3bh0xMTFuz0l6F6CJS0poaKj2+eefazabTYuKitLefPNNx3O5ublaSEiINn369ArcQ3G+MjIytCZNmmhLly7VevbsqY0bN07TNE3SvIp56aWXtLZt2xb5nKR11fP0009rV1xxRbHPS5pXbePGjdMaNWqk2Ww2SesqaNCgQdrdd9/t8tj111+v3XbbbZqmyfVd1WRnZ2sGg0FbsGCBy+Nt27bVnnvuOUnvKgTQ5s+f7/jbk7RNTU3VvLy8tLlz5zq2OXbsmKbX67VFixZdtH0XZVc4vQtKTEzUAG3z5s0uj0t6V14lpbfd+vXrNUA7dOiQpmmS3pWZJ+mdlpamAdqyZcs0TZP0rsyKS++jR49qtWvX1rZv367Vq1dPe//99x3PSXq7kpkBlwir1crcuXPJysqia9euJCYmkpycTL9+/Rzb+Pj40LNnT1avXl2BeyrO10MPPcSgQYPo27evy+OS5lXPvn37iImJoUGDBowYMYL//vsPkLSuin799Vc6derE8OHDqVWrFu3bt2fGjBmO5yXNqy6TycTs2bO5++670el0ktZV0BVXXMHy5cvZu3cvAFu2bGHVqlVcc801gFzfVY3FYsFqteLr6+vyuJ+fH6tWrZL0rsI8SdtNmzZhNptdtomJiaFVq1aS/lWQpHfVlpaWhk6nc8zklfSuukwmE5999hkhISG0bdsWkPSuamw2G7fffjtPPvkkLVu2dHte0tuVsaJ3oLrbtm0bXbt2JTc3l8DAQObPn0+LFi0cJ2NkZKTL9pGRkRw6dKgidlVcAHPnziU+Pt4l7qxdcnIyIGleVXTp0oWvvvqKpk2bcuLECV577TW6devGjh07JK2roP/++49p06bx2GOP8eyzz7J+/XrGjh2Lj48Pd9xxh6R5Ffbzzz+TmprKqFGjALmXV0VPP/00aWlpNGvWDIPBgNVq5fXXX+eWW24BJM2rmqCgILp27cqrr75K8+bNiYyM5Ntvv2XdunU0adJE0rsK8yRtk5OT8fb2JjQ01G0b++tF1SHpXXXl5ubyzDPPMHLkSIKDgwFJ76powYIFjBgxguzsbKKjo1m6dCkRERGApHdVM3nyZIxGI2PHji3yeUlvV9IZUMHi4uJISEggNTWVH3/8kTvvvJMVK1Y4ntfpdC7ba5rm9pioHI4cOcK4ceNYsmSJ22izgiTNq4aBAwc6fm/dujVdu3alUaNGfPnll1x++eWApHVVYrPZ6NSpE2+88QYA7du3Z8eOHUybNo077rjDsZ2kedUzc+ZMBg4c6BaXUtK66pg3bx6zZ89mzpw5tGzZkoSEBMaPH09MTAx33nmnYztJ86rj66+/5u6776Z27doYDAY6dOjAyJEjiY+Pd2wj6V11nUvaSvpXL5LelZvZbGbEiBHYbDY++eSTUreX9K68evfuTUJCAqdPn2bGjBncdNNNrFu3jlq1ahX7GknvymfTpk188MEHxMfHlzntqmt6S5igCubt7U3jxo3p1KkTkyZNom3btnzwwQdERUUBuPVQnTx50m20iqgcNm3axMmTJ+nYsSNGoxGj0ciKFSv48MMPMRqNjnSVNK+aAgICaN26Nfv27ZPruwqKjo6mRYsWLo81b96cw4cPA0iaV1GHDh1i2bJljBkzxvGYpHXV8+STT/LMM88wYsQIWrduze23386jjz7KpEmTAEnzqqhRo0asWLGCzMxMjhw5wvr16zGbzTRo0EDSuwrzJG2joqIwmUykpKQUu42oOiS9qx6z2cxNN91EYmIiS5cudcwKAEnvqiggIIDGjRtz+eWXM3PmTIxGIzNnzgQkvauSf/75h5MnTxIbG+toazt06BCPP/449evXByS9C5POgEuMpmnk5eU5KhtLly51PGcymVixYgXdunWrwD0U5+qqq65i27ZtJCQkOH46derErbfeSkJCAg0bNpQ0r8Ly8vLYtWsX0dHRcn1XQd27d2fPnj0uj+3du5d69eoBSJpXUbNmzaJWrVoMGjTI8ZikddWTnZ2NXu9aZDYYDNhsNkDSvCoLCAggOjqalJQUFi9ezLXXXivpXYV5krYdO3bEy8vLZZukpCS2b98u6V8FSXpXLfaOgH379rFs2TLCw8Ndnpf0rvrs7W0g6V2V3H777WzdutWlrS0mJoYnn3ySxYsXA5LehUmYoAr07LPPMnDgQOrWrUtGRgZz587l77//ZtGiReh0OsaPH88bb7xBkyZNaNKkCW+88Qb+/v6MHDmyonddnIOgoCBatWrl8lhAQADh4eGOxyXNq44nnniCIUOGEBsby8mTJ3nttddIT0/nzjvvlOu7Cnr00Ufp1q0bb7zxBjfddBPr16/ns88+47PPPgOQNK+CbDYbs2bN4s4778RodBanJK2rniFDhvD6668TGxtLy5Yt2bx5M++99x533303IGleFS1evBhN04iLi2P//v08+eSTxMXFcdddd0l6V3KZmZns37/f8XdiYiIJCQmEhYURGxtbatqGhIQwevRoHn/8ccLDwwkLC+OJJ56gdevW9O3bt6IOSxSjtPQ+e/Yshw8f5vjx4wCOgR1RUVFERUVJelcyJaV3TEwMN954I/Hx8SxYsACr1eqYBRQWFoa3t7ekdyVTUnqHh4fz+uuvM3ToUKKjozlz5gyffPIJR48eZfjw4YDczyub0u7nhTv3vLy8iIqKIi4uDpD0dqOJCnP33Xdr9erV07y9vbWaNWtqV111lbZkyRLH8zabTXvppZe0qKgozcfHR+vRo4e2bdu2CtxjcaH17NlTGzdunONvSfOq4+abb9aio6M1Ly8vLSYmRrv++uu1HTt2OJ6XtK56fvvtN61Vq1aaj4+P1qxZM+2zzz5zeV7SvGpZvHixBmh79uxxe07SumpJT0/Xxo0bp8XGxmq+vr5aw4YNteeee07Ly8tzbCNpXrXMmzdPa9iwoebt7a1FRUVpDz30kJaamup4XtK78vrrr780wO3nzjvv1DTNs7TNycnRHn74YS0sLEzz8/PTBg8erB0+fLgCjkaUprT0njVrVpHPv/TSS473kPSuPEpK78TExCKfA7S//vrL8R6S3pVHSemdk5OjDRs2TIuJidG8vb216OhobejQodr69etd3kPSu/Io7X5eWL169bT333/f5TFJbyedpmlaufY2CCGEEEIIIYQQQgghhBCiQsmaAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFSedAUIIIYQQQgghhBBCCCFEFfd/yjVmvS/xTX4AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 1\n", + "st = 29\n", + "end = 145\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME1_cut_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Moving MITF and TFAP motifs as close as possible to SOX motif" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TGTTGTCACGTGACGGCGAACAATGGGCCCATTGTTTGGCCTGAGGCTCTG" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 1\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][63:63+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_tfap[\"tmp_array\"][97:97+1])\n", + "st = 63 - 4\n", + "end = 97 + 9 + 4\n", + "\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=63,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=63+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=97,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=97+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME1_shortened_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)\n", + "\n", + "for nuc in onehot_[0][st:end]:\n", + " if nuc[0]==1:\n", + " print(\"A\",end=\"\")\n", + " if nuc[1]==1:\n", + " print(\"C\",end=\"\")\n", + " if nuc[2]==1:\n", + " print(\"G\",end=\"\")\n", + " if nuc[3]==1:\n", + " print(\"T\",end=\"\")\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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VzjjjjLztbW/L5z//+SSyLpv99tuv/UvECxYsyMyZM/PXv/41kyZNSiLvWvRyPqsi79rSVda9Ieva01Pe6mnl0VPWamnl0lXe6mnlszHHbbW02tdV3upp5dObta2WVh5d5a2eVj7drW21tHJ5Od8DknVt6Srr3pB17ekpb3W08ugpa3W0cukqb3W08tmY47Y6Wu3rKm91tPLpzdpWRyuPrvJWRyuf7ta2Olp5bI5zrMi7dvSU99q1a3t8DHnXjt7mrZ5W+3qbtXpaOfSU92233aaeVhKbctxWT6tdPeW97bbbqqeVxMasbfW02tdT3s8//7x6Wkn0Zm2rp5XXxp7DdnNmrXlFCQ0YMCD77bdfbr755g7bb7755hx44IFVmhV94cUTaq6b/erVq3P77bfLvgYVRZEzzjgj119/fX7961+3H/BfJO/yK4oiq1atknXJHH744XnwwQcze/bs9sv++++fd7zjHZk9e3Z22mkneZfYqlWr8sgjj2TcuHHWdskcdNBBmTNnTodtjz76aCZOnJjEcbusrrzyyowePTpvfOMb27fJulxeeOGFNDR0LJ3069evvVu4vMtpyJAhGTduXBYvXpxf/vKXOfbYY2VdYr3Jdr/99kv//v07jFmwYEEeeugh+ZeQvMvjxQ80PvbYY7nllluy7bbbdtgv6/J7sbaWyLssTjrppDzwwAMd6mrNzc354Ac/mF/+8pdJZF12f/3rX/PEE09k3LhxSeRdFgMGDMirX/3qbmtrsi6nK664Ivvtt1+mTp3aYbu8y6GlpSUtLS3d1tZkXU5NTU3Zbrvt8thjj+Xee+/Nsccem0TetWRzfFZF3rWhp6x7Q9a1ozd5q6eVw6aubbW02tRT3upp5bEpa1strXb1lLd6WnlszNpWS6t9PeWtnlYeG7O21dLKaWO+ByTr2rbu39I9kXXtWzdvdbRy62ltq6OVy4t5qqOVX3drWx2tfF7MWx2t/Dpb2+po5fVi3upo5dfZ2lZHq32b4xwr8q4dPeXdr1+/Hh9D3rWjN3mrp5XDpq5t9bTa1FPep5xyinpaSWzK2lZPq1095T1w4ED1tJLYmLWtnlb7esp77dq16mklsTFrWz2tfDb2HLabNeuCUrr22muL/v37F1dccUXxhz/8oTj77LOLIUOGFH/+85+rPTVepuXLlxf3339/cf/99xdJiksvvbS4//77i3nz5hVFURSf+cxniqampuL6668vHnzwweLtb397MW7cuGLZsmVVnjkb61/+5V+Kpqam4rbbbisWLFjQfnnhhRfax8i7PM4///ziN7/5TTF37tzigQceKD760Y8WDQ0NxU033VQUhazL7pBDDinOOuus9tvyLo/zzjuvuO2224rHH3+8uPPOO4ujjz66GDp0aPtrMlmXx9133100NjYWn/rUp4rHHnus+N73vldss802xTXXXNM+Rt7lsnbt2mLChAnFhz/84Q32ybo8Tj755GL77bcvfvrTnxZz584trr/++mLUqFHFhz70ofYx8i6PmTNnFr/4xS+Kxx9/vLjpppuKqVOnFq95zWuK1atXF0Uh61q2OWop//zP/1yMHz++uOWWW4r77ruvOOyww4qpU6cWa9asqdavRRd6yvuvf/1rcf/99xc/+9nPiiTFtddeW9x///3FggUL2h9D3rWhu6xbWlqKY445phg/fnwxe/bsDrW1VatWtT+GrGtHd3k/99xzxfnnn1/893//d/HnP/+5mDVrVnHqqacWAwcOLB566KH2x5B3bejpeXx9EydOLL74xS922Cbr2tFd3suXLy/OO++84ne/+10xd+7c4tZbby2mT59ebL/99l6n1aCe1vb1119f9O/fv/j2t79dPPbYY8VXv/rVol+/fsVvf/vb9seQde3ozXP50qVLi2222ab4xje+0eljyLs29JT1IYccUuyxxx7FrbfeWjz++OPFlVdeWQwaNKj4+te/3v4Ysq4dPeX9gx/8oLj11luLP/3pT8WNN95YTJw4sTjuuOM6PIa8a8Pm+qyKvLd+vclaLa08espbPa08espaLa1cevNcvj71tNrUU9ZqaeXSm7WtnlYOvX0eV0srh97krZ5WDr3JWi2tPDbH94BkXRt6ylodrVy6y1sdrVy6y1odrXx6ei5fnzpa7eoua3W08ulpbaujlUdvnsfV0cqjp7zV0cqjp6zV0cptU86xIu/atX7e6mnltm7e6mnltm7W6mnlt/5z+frU08pj3azV08pv/bWtnlZenT2Pq6eV1/p5q6eV1/pZq6eVx+Y4h+3mylrzihL72te+VkycOLEYMGBAse+++xa33357tafEZnDrrbcWSTa4nHzyyUVRFEVra2vx8Y9/vBg7dmwxcODA4rWvfW3x4IMPVnfSbJLOck5SXHnlle1j5F0e7373u9ufs7fbbrvi8MMP7/CBCVmX2/ov/OVdHm9729uKcePGFf379y+am5uL4447rnj44Yfb98u6XH7yk58Ue+65ZzFw4MBiypQpxbe//e0O++VdLr/85S+LJMWcOXM22Cfr8li2bFlx1llnFRMmTCgGDRpU7LTTTsUFF1zQ4cMQ8i6P6667rthpp52KAQMGFGPHji1OP/30YsmSJe37ZV27NkctZcWKFcUZZ5xRjBw5shg8eHBx9NFHF/Pnz6/Cb0NPesr7yiuv7HT/xz/+8fbHkHdt6C7ruXPndllbu/XWW9sfQ9a1o7u8V6xYUbzlLW8pmpubiwEDBhTjxo0rjjnmmOLuu+/u8Bjyrg09PY+vr7MPNcq6dnSX9wsvvFDMmDGj2G677Yr+/fsXEyZMKE4++eQNspR3bejN2r7iiiuKXXbZpRg0aFAxderU4sYbb+zwGLKuHb3J+1vf+lYxePDgDn93r0vetaGnrBcsWFCccsopRXNzczFo0KBi8uTJxRe+8IWitbW1/TFkXTt6yvvLX/5yMX78+Pbj9oUXXtihjloU8q4Vm+uzKvLe+vUma7W08ugpb/W08ugpa7W0cunNc/n61NNqU09Zq6WVS2/Xtnpa7ett1mpp5dCbvNXTyqE3Waullcfm+B6QrGtDT1mro5VLd3mro5VLd1mro5VPT8/l61NHq13dZa2OVj69WdvqaOXQm6zV0cqjp7zV0cqjp6zV0cptU86xIu/atX7e6mnltm7e6mnltm7W6mnltynNK+Rdm9bNWj2t/Dpb2+pp5dRZ1upp5bV+3upp5bV+1upp5bE5zmG7ubKuFEVRBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgLrUUO0JAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAUD2aVwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANQxzSsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADqmOYVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdUzzCgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgDqmeQUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAd07wCAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACgjmleAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAUMc0rwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAKhjmlcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADUMc0rAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA6pjmFQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHXs/wem1kmnhto3TwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 12\n", + "\n", + "ntrack = 4\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"0\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict_smtsmt[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "onehot_[0,motif_embedding_dict[\"smts\"][\"locations\"][ori_index]:motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox2\"].shape[1],:] = patterns_dict_irf4[\"sox2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"s\"][\"locations\"][ori_index]:motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox1\"].shape[1],:] = patterns_dict_irf4[\"sox1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf1\"].shape[1],:] = patterns_dict_irf4[\"mitf1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"sm\"][\"locations\"][ori_index]:motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf2\"].shape[1],:] = patterns_dict_irf4[\"mitf2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap2\"].shape[1],:] = patterns_dict_irf4[\"tfap2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap1\"].shape[1],:] = patterns_dict_irf4[\"tfap1\"][0]\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "\n", + "for ax_ in [ax1,ax2,ax3,ax4]:\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + "\n", + "plt.savefig(\"figures/motif_embedding/ME2_rand_single_double_irf4_st0_end500_deepexplainer_topic16.pdf\",transparent=True)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 12\n", + "st = 37\n", + "end = 156\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding//ME2_cut_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TTTTGTCACGTGACTGGTTCACTACCGGAACAATGGGCCCATTGTTCTTCGGCCTGAGGCGCTT" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 12\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][64:64+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_tfap[\"tmp_array\"][111:111+1])\n", + "st = 64 - 4\n", + "end = 111 + 9 + 4\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=64,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=64+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=111,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=111+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME2_shortened_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)\n", + "\n", + "\n", + "for nuc in onehot_[0][st:end]:\n", + " if nuc[0]==1:\n", + " print(\"A\",end=\"\")\n", + " if nuc[1]==1:\n", + " print(\"C\",end=\"\")\n", + " if nuc[2]==1:\n", + " print(\"G\",end=\"\")\n", + " if nuc[3]==1:\n", + " print(\"T\",end=\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Selecting 2 sequences where the motifs are implanted on the upstream side of the sequence" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5, 7, 8, 11, 17, 20, 25, 37, 45, 47, 50, 51, 54, 58, 60])" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.where([np.logical_and(\n", + " motif_embedding_dict[\"smt\"][\"locations\"]>260,\n", + " np.logical_and(motif_embedding_dict[\"smt\"][\"locations\"]<360,\n", + " np.logical_and(motif_embedding_dict[\"sm\"][\"locations\"]>400,\n", + " motif_embedding_dict[\"s\"][\"locations\"]>330)))])[1][:15]" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Selected IDs: 17 58\n" + ] + } + ], + "source": [ + "print(\"Selected IDs:\",*[17,58])" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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XXnop73jHO7jooosGa7eSJEmSJEmDKplMcvPNN3PzzTeTTCaHezgaRB5rSZKkoeHrLmnoeb+TJEmSpJHLc7bRy2MnSZIkSZIkaTh5jXJ08/hJI99A3U/rWuoAKC4ozsxrH16xbVv0u6wMJk3q/baXVC4hFaYAWFq5lO898j1e3PwiqTBFKkyxpHJJh3UaWrIBFW3hFSEhYRjmBVtoN5KozrYLxgzfOFr5HClJkiTt2nzNv3vxeEuSNHoUDNaGjzjiCK6++mrKy8sBCIKAL3/5y5x55pl88IMfHKzdSpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkjRjpME1DIgqLKC0opYoqQsIO4RU7dkS/99mnb9tfWrmUdJgG4PlNz/PSlpdIh+nMvFe3vdphnYZkx/CKtv5tY9VupqUKCCFeCrFBK08mSZIkSZIkSRrBBu3q8K9+9atO5x966KEsXrx4sHYrSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZI0YtS11GXaZYVlmXZ1c3Vev5rWLIv99uvb9puSTZl2SEgyncxb3pxs7rBOY6Ix024fXpE7Xu1GEtUQpqBw8nCPRJIkSZIkSZI0TGIDvcE///nPtLS0ZKZXr15NKpXKTDc0NPCTn/xkoHcrSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZI04tQ012TaYwrHZNo7Gndk2mEItbVRe/r0aLq3mlMdwylytaRa8qbDMMxbpy28oo3hFbuplh1ACEXjh3skkiRJkiRJkqRhMuDhFe973/uoqqrKTL/+9a9nzZo1mena2loWLFgw0LuVJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEkacXLDK8aVjMu0q5uqM+2GBkgmo/aECdl2b7QkW7pf3i68ojnVTDpMZ6bbh1fUttT2fufadbRsj34XGl4hSZIkSZIkSburAQ+vCNvFdbefliRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ2l3UNmfDIMYVZ8MralqyoRZVVdn+e+wBfSnd1Jxq7nZ5IpXIm65vqc+bbh9eUddS1/uda9fRUhX9NrxCkiRJkiRJknZbAx5eIUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpEhNcxRSERAwtmhsZn5uSERueMWECX3bfiKd6HZ5MkzmTTckGvKm24dXtF+u3USiNUylaMKwDkOSJEmSJEmSNHwKhnsAkiRJkiRJo0k8Huess87KtLXr8lhLkiQNDV93SUPP+50kSZIkjVyes41eHjtJkiRJkiRJw8lrlKObx08a+QbiftoWXhELYowpGkNJvISmVBP1LfWZPu3DK/qyq0Sq+/CKVDqVN12fqM+bLooXGV4hSLaGqRSOhzCEIBjW4fgcKUmSJO3afM2/e/F4S5I0egxKeMV9993H+PHjAUin0/zzn//k3//+NwBVue+QSJIkSZIkjTLxeJyjjjpquIehIeCxliRJGhq+7pKGnvc7SZIkSRq5PGcbvTx2kiRJkiRJkoaT1yhHN4+fNPINxP00N7yirLCMksIovCKRTtCcbKa4oDgvvGKPPfoWXpEKU90uT4fpvOlllcsy7YCAc24+hx1NOzLzqpqq0G4mnYB0S9QuHA9hCoJBKVHWaz5HSpIkSbs2X/PvXjzekiSNHoNyZfjDH/5w3vQnP/nJvOlgmNOUJUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmShkJNcw2xIAZAeVE5ZQVlVFGVWTalYEpeeMXkyX3bfvtwivZCwrzpdTXr8pbdtfyuDttLp9PEYrG+DUSjVzqRbReNhx7+T0mSJEmSJEmSdk0DHl6RTnvBWZIkSZIk7brS6TQVFRUAzJ492w9e7sI81pIkSUPD113S0PN+J0mSJEkjl+dso5fHTpIkSZIkSdJw8hrl6Obxk0a+gbif1jTXEA/ihISUFZZRWliat2xKeRReEQQQhrDHHn3bfhiGPXfKUdVU1fOYW2qYUDKhbwPpSbIRmrdCyXSIFw3strVzcsMqCscP3zhy+BwpSZIk7dp8zb978XhLkjR6+CwtSZIkSZLUB8lkkhtuuIEbbriBZDI53MPRIPJYS5IkDQ1fd0lDz/udJEmSJI1cnrONXh47SZIkSZIkScPJa5Sjm8dPGvkG4n5a01wDRCETZYVllBeVd1i2YwcUFETzxvcxOyCk5/CKVDqVaVc3V/fYv7Khsm+D6EnFbXDbJPjrHLhjJmx5bGC3r50TZv9/UDg+SlIZZj5HSpIkSbs2X/PvXjzekiSNHoMaXrFs2TI+85nP8OY3v5nTTjuNz3zmMyxdunQwdylJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkjRitAVUpMIU5YXljCka02FZVVW2/9ixvd92Op3uVb+qpuwO2vbZnW0N23o/iJ4s+xk89k5INUXTLTvgnyfDur8N3D60k3L+H8VLGOTyZJIkSZIkSZKkEWrQrg7feuutHHLIISxevJg3vOENvP71r+fZZ59l/vz53HLLLYO1W0mSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpBGjtqWWVJgCoKywjLFFY/OWAdTVRdMlJVBU1PttNyQbetVve+P27D6ba/vUf6fUr4Hnvtg6Ebb+TkOYhqc+AYn6gdmPdk46lW0HMQiC4RuLJEmSJEmSJGnYFAzWhr/0pS+xYMECvvOd7+TN/+Y3v8mXv/xl3vWudw3WriVJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkkaE6uZq0mEagPKicsYUjSEgICSkprkGgHQawhD22KNv2+5tyMSOxh2Zdl2iruftNg1QeMXiSyBMdbIghOZKWHE9HPj5gdnXCLR6Nfz4x1E4ydlnw3nnDfeIupLONoP44O2mogIqK/PnbdwIVVVRe8IEmDEjaieTgzcOSZIkSZIkSVKnBi28YtOmTXzoQx/qMP+DH/wgP/rRjwZrt5IkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSSNGbnBEWWEZZYVlxIIY6TCdCa9IteY7TJjQ/213268p26++pb7H/lWNVX0bSKcbeRnW/aWbDmlY8/tdNrzi7rvhfe+DxsYomOQ3v4GLL4b/9/+gsHC4R9dOXsBIDAgGfh8VFTB3LjQ19a5/YSF87WtRe+1a2G+/gR+TJEmSJEmSJClPbLA2fPLJJ/Poo492mP/YY49xwgknDNZuJUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSRozqpupMOze8Ih6LZ8Ir0ulo+dixfdt2bihFd6qaqzLtXoVXNFX12KdHq26AIN59n3Sq++Wj1IoVcP75UFcHyWQ2nOSaa6Lwis6k0il+89xvWLp16dANtE2YzrZjcQgGIbyisrL3wRXtbds2sGORJEmSJEmSJHWqYLA2fM455/DlL3+ZxYsXc8wxxwDw5JNPcsstt/Dtb3+bv/3tb3l9JUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSdjVtARUA5YXllBeWAxAQZJalUhCGEO8h66G9qsaqXvXLDdBoTDb23L+5usc+3UonYeVvIewpnGIQQhKGWRjCf/5n9pi2X/bf/w3vex/stVf+so11G/no3z7K2KKx1CyoYUjlHac+/ieUJEmSJEmSJO0yBi284qKLLgLgmmuu4Zprrul0GUAQBKRSu2bytSRJkiRJ2vXE43FOO+20TFu7Lo+1JEnS0PB1lzT0vN9JkiRJ0sjlOdvo5bGTJEmSJEmSNJy8Rjm6efykkW8g7qe1LbWZdllhGWWFZZnp3PCKaB9923ZvQyZqmrJhCL0Jr8gN3OiXTf+E5q296Jjeuf2MQHfdBQ8+2PXyVAp+8hO48sr8+RtqNgDQkmoZxNF1ITe8IjYyno/i6TSn3X9/1P6P/xjm0UiSJEkaaF4X2714vCVJGj0GLbwind713hCQJEmSJEmKx+Mcf/zxwz0MDQGPtSRJ0tDwdZc09LzfSZIkSdLI5Tnb6OWxkyRJkiRJkjScvEY5unn8pJFvIO6n9Yn6TLu8qJzyonJCQiAbEpFOQxhCLNa3bfc6vKIlG0bRlGzqsX9tc22Pfbq18e8QFECY3LntjELXXBOFkKRSnS9PJmHhwo7zN9RG4RXNqeZBHF0XwpyaYUEXRUTrK6C5Mmo3boSWKhizL0w5dlCGFE+lOP7xx6OJvt4xJEmSJI14XhfbvXi8JUkaPQYtvCJXU1MTJSUlQ7ErSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkEaE52UwynQ1wKCsso6ywjHSYJgxDaluikIhUKgqviHeRG9CVtvCLnrTtp21MPalrqevbQNrbeG/H4IrJx8Aeh8GWhVD98s5tf4Rauxbuuy86lt3pbPmGug2DM6jeCIJsu7PB1VfAnXMh3UnwyemPD1qAhSRJkiRJkiRpaA1alHAqleK73/0us2bNYsyYMaxcuRKAb3zjG/zqV78arN1KkiRJkiQNqnQ6zfr161m/fj3pdHq4h6NB5LGWJEkaGr7ukoae9ztJkiRJGrk8Zxu9PHaSJEmSJEmShpPXKEc3j5808u3s/bR9uEReeAUhVY1VrfuJlsf6WBWqtrm2505AfXN9pt2c6jm8oj5R32OfLrXsgJpl+fPmXgKn/wuO/Dm8ZTHs9c7+b38Yvfoq/PKX8LvfQX0nf6Lf/rZ3x7Cz/0obaoczvCInNSVMdVzeXNl5cAVA3cpBGVI6CFg/cybrZ84k3VMaiCRJkqRRx+tiuxePtyRJo8eghVd8//vf57e//S0//OEPKSoqysyfP38+119//WDtVpIkSZIkaVAlk0muv/56rr/+epLJ5HAPR4PIYy1JkjQ0fN0lDT3vd5IkSZI0cnnONnp57CRJkiRJkiQNJ69Rjm4eP2nk29n7afvwitKCUsoLyzPTO5p2AJBKQRhCPE6f1Lb0Lrwit19LsqXH/vUtOxFeUfl0/vSE+XDY/0LQWvIqVgjH/haKp/R/H0MsnYYf/QgOOQQ++Un40IfgoIPgscfy+912W3Qs+2N9zfpMOxzysIaccmThyHg+ShYUcP1//ifX/+d/kuzvH1WSJEnSiOV1sd2Lx1uSpNFj0MIrbrzxRn75y1/ygQ98gHjOuyGvf/3rWbp06WDtVpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkadB95R9fIfh2wE+e+kmXfXLDK0riJQRBQFlhWWZedXM1EIUjAMT6WBWqtyETDcmGTDvZi3CCxmRj3waSa9uTEBRkp994JYQ54QNBDGLFMP+/+7+PIXbVVfClL0EikZ23fj2cfjqsWhVNb90KL7yQv14sBh/8IFx6Kcyc2f0+csMr2kJNhkyQk5oSpod235IkSZIkSZKkEWPQwivWr1/P/vvv32F+Op0mkXv1XZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkaZR5YXOUVLBk65Iu+yzasCjTbkm3cNgvDuOL938xM29t9VogG1qR7mNuQF1LXa/65YZcpNKpbnpGdiq8ovKJbFjF1JNhxhkQK8zvEyuA/T8FpbO63k6YhqYtkOxdQMdgee45+PKXO85PpSCZhK98JZp+5JH85SUlcN998LvfwZVXwosvwlFHdb2fipqKTHtD7YYBGHkfBDnlyMIUhOHQ7l+SJEmSJEmSNCIMWnjFwQcfzKOPPtph/i233MIb3/jGwdqtJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEnSoKtpqgGgsqGyyz5t4RQA6TDNc5ue47Udr2XmJdIJIAqvCIK+h1c0JBp61S83jCId9ryTpmRT3wbSJgyj8Apaww/mvAdab2MHQQDTTu182dZ/wV3z4PZp8Oex8MxnIFHTvzHtpIsv7jrLIZmE11oP5+OPQ0FBdtkXvwintt68WAwmTIiCLHL75MoNrFhfs37nB94XQTzbDtNkjp8kSZIkSZIkabfSxSXsnffNb36TCy64gPXr15NOp7n99ttZtmwZN954I3fddddg7VaSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJGnQba7fDMCmuk1d9tnWuK3H7SRSCeLxQgBSqb6NYebYmZl2QMDE0omZ6R1NOzJBFTPHZPuFvQgmaE42920gbRI1+SETs94GscKu+095U8d5FbfCY+/KCVQI4bVrYdP98JZnoXBM/8bWD08/DU880bu+CxdGYRYAe+4JX/taFFrRJh6H/feHiy6CRx/NX7c52UxtS21men3tUIdX5Aw0TGF4hSRJkqTdQSoF//53dC538MFQUjLcI5IkSRp+sZ679M/ZZ5/Nn/70J+655x6CIOC///u/WbJkCXfeeSenn376YO1WkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkgZfohY23g+b/gHJhuEejaRh0BZasbFuY5d9tjdu79V2YjEIAkin+zaGSWWTKGwNh5gxdgaVX6rM/Bww8QAACmOFTCqbBEAY9i6UoN/hFY0bsu1xc6Fsz677BnGYeGj+vJpX4YkPA0FriEKrMA11K+Hf3+vfuPrpxz+GgoLu+4QhNDbCCy9k533961FYRXtBAN/9LhQX589vH4CyoXYDQyrIGWyYim7UQJs8uf+VYCdNGtixSJIkSdrtLVoERxwBhx4a/Z47F+65Z7hHJUmSNPx6uCS+c84880zOPPPMwdyFJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJA2t1TfD4s9D89ZounQWHHkN7HnO8I5L0pCqT9QDsLG26/CK6ubqHrezqW4T8fheBAGkUj12z9OQyIbnFMfzExGKC6LpdJimMdnYoX93WtItfRtIm8b12faUN0UhCEHQdf/W4I2MJz8C6Wagk/CEMAWb7gd+0L+x9dGOHXDrrb07Js8/D8lk1I7F4F3vgsLCjv2CAMaNiwqj5lpfuz5/uiZ/etAFsWw7WQf0MUWlN2bPhmXLoLIyO2/JEvjgB/P73XQTzJsX/UHvvTeat9deAz8eSZIkSbutRYvguOPyAyTXrYP/+A944AE47bThG5skSdJwG9TwiqqqKm699VZWrlzJF7/4RSZOnMizzz7LtGnTmDVr1mDuWpIkSZIkaVDE43FOOumkTFu7Lo+1JEnS0PB1lzT0vN9JkiRJ0sjlOdvo5bGTJEmSJEmSNJy8RjkMVt4AT14I5BRjb9wIj7wd3vwwTDup15vy+EkjX1f30zDMhiu0BUN0pqa5psd9bKzbSNum+xpe0ZhozIylpKAkb1lpYSkQhVe0hVZsrd/aq+0m08m+DaRNw4Zse9IxECYh6CTFoU06CbHWUlhbHoXKx7vffm7IwiC7666Ox6OsLCpiun07PPZYdn5FRbZ91FEwcWLX200k4MQT8+e1D6tYV7uun6PupyDnOShRHYWODIbZs6Of7sybB4cdRjyV4qSG6P+tz5GSJEnSrme4rott3QrnnBMFV+Se86XTUeDgN75heMVg8DqoJEmjx6BdhX/xxRc54IADuOKKK/jRj35EVVUVAHfccQcLFiwYrN0CcM0117DPPvtQUlLC4YcfzqOPPtpt/4ULF3L44YdTUlLCvvvuy3XXXdehz2233cZBBx1EcXExBx10EHfccUfe8ssvv5wjjzySsWPHMnXqVM4991yWLVuW1+fCCy8kCIK8n2OOOWbnb7AkSZIkSRoy8Xick08+mZNPPtk3QXZxHmtJkqSh4esuaeh5v5MkSZKkkctzttHLYydJkiRJkiRpOHmNcohtWwRPfaJ1IrewdxoI4IWv9mlzHj9p5OvqflrVVJXXryXV0un6tS21Pe5jS/0WYq3VoNLpvo2vIdlAmmilDuEVBVF4RUiYCa+obKzs1XZT6T6maLRpXA9BaxjFlDdBrJvgCiAvCOjf380PUehM2Mc/0E64917IfWh+wxvglVfgr3+FRx+FO+6AktY/+bp12b5veUsUUNGVwsKO4RUbajfkTVdUVzC0csqRJaqjiq3DzOdISZIkadc2XK/5v/lN2LKl8/DIMIRkP7McR5X6Cqi4BdbfBammIdml53iSJI0egxZecdlll3HhhReyfPlySkqyb2icddZZPPLII4O1W/70pz9xySWX8LWvfY3nnnuOE044gbPOOouKis4vxK9atYq3vvWtnHDCCTz33HN89atf5XOf+xy33XZbps8TTzzBe97zHi644AJeeOEFLrjgAt797nfz1FNPZfosXLiQiy++mCeffJIHHniAZDLJGWecQX19fd7+3vKWt7Bx48bMzz333DM4fwhJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJAycMYdFngK4Kp4eQ7rx4vaRdT/twgfU16zvtV99S3+n8XFvrtxKPR3kB9T13z9OYaCQddh5ekTtd11IHQEDvQgliQT/LUzVuAIIohGLc63qxo9aClXWrYNMDEPYzNGOAhSHcf3+2mGlxMdx6K8yale1z9tnw7W9H7XXryASQnHhifuhFZ6ZNy59eX5v//6er/0+DJl5MJkikpbrnEBFJkiRJGoXWrYP/+7/OgyvadLds1Eu1wPNfgb/tD4+9GxaeDXe+Dtb9dbhHJkmSRpCCwdrwM888wy9+8YsO82fNmsWmTZsGa7f8+Mc/5mMf+xgf//jHAbjqqqu47777uPbaa7n88ss79L/uuuuYPXs2V111FQDz5s1j0aJFXHnllZx//vmZbZx++uksWLAAgAULFrBw4UKuuuoqbr75ZgD+/ve/5233N7/5DVOnTmXx4sWcmBNxXVxczPTp0wf8dkuSJEmSpKERhiFbt24FYMqUKQRB7z6kqdHHYy1JkjQ0fN0lDT3vd5IkSZI0cnnONnp57CRJkiRJkiQNp8G6RtnSEhXe7qn49m5l0wOw7anu+/Sx6LrXmKWRr6v7afvwiorqCvbZY58O6zckGnrcR2VjZSb4YMeOvo2vLZQCOg+vCAgICTMhGvFY/gP7Xe+7iyNmHgHA1U9dzRX/uoJUmKIwVti3gbRp2ABhEkpn9C0AoeIWIEZeQNC4A2H2u6BpC6z8zZAGBL38Mmzblp3+5jdhn33ynxfjcfjiF+Gll6ICqKlUNO+YY7JBFr3VPrxie+N2EqkEhfF+Hoe+CmIQL4NUPSSqRkR4hc+RkiRJ0q5tOF7z//CHUVjhbikM4amPw+rfk3fu3bABHjkPTnsYpp7Y1doDsHvP8SRJGi36GW3ds5KSEmpqajrMX7ZsGVOmTBmUfba0tLB48WLOOOOMvPlnnHEGjz/+eKfrPPHEEx36n3nmmSxatIhEItFtn662CVBdXQ3AxIkT8+Y//PDDTJ06lQMOOIBPfOITbNmypdvb1NzcTE1NTd6PJEmSJEkaPolEgmuvvZZrr702c+1AuyaPtSRJ0tDwdZc09LzfSZIkSdLI5Tnb6OWxkyRJkiRJkjScBvoa5SOPREW3i4uhqAg+/GFYvXrnx7lLeOnbA17M22vM0sjX1f20s/CKzjQmGnvcx/bG7cTjEARQVdW38dUn6jPt0sLSvGXFBcWZYpBtIRptIRZtZo6dybQx05g2ZhpTyrO1oZpTzX0bSGZAa4AQSmf2bb11f43Wa7PPh+GtL8Ih/w1HXhO1iyf1b0z98OCD0fEAmDwZvvSlzgOd0mn47Gej58p0Gg4+GEpLO/Zrr/1D/trqtXnTISGb6zf3b/D9VTg2+t1SPbT77YLPkZIkSdKubahf8zc3ww03RMGDu6UlP4LVvyMvuAKy0899eVB37zmeJEmjx6CFV7z97W/nO9/5TubFQBAEVFRU8JWvfIXzzz9/UPZZWVlJKpVi2rRpefOnTZvGpk2bOl1n06ZNnfZPJpNUVlZ226erbYZhyGWXXcab3vQmDjnkkMz8s846i9///vc8+OCD/O///i/PPPMMp556Ks3NXb9Jc/nllzN+/PjMz1577dX1H0CSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEnqp//7PzjpJFi0KJpOp+EPf4D582Hp0uEd27CrXQGVj0PYrrpdyTQontL5OpJ2ab0Nr+hNCERVY1Um8KC+vm+FNNvCKAICSgpK8pYVx4uJBVGZqUx4RSI/vCJ3nZKCEtJhVLQyFaZoSbVARQU8+2z+z913w+9/H/1uv6yu9e/Ql/CKRA1se4pMeMW4A+GoX0BQALECCGIwZj846v96v82dtHhxNqzi/POzQRbtFRTAEUfAunXR9D779G777YMw2v7/FMYKM/PW16zvy5B3XuH46HdiZIRXSJIkSdJA+sc/oKYmf96HPgQrV8L69VFoYWFh5+uOeo2b4MVvdtMh7HjdU5Ik7bYKBmvDV155JW9961uZOnUqjY2NnHTSSWzatIljjz2W73//+4O1W4BM0nebMAw7zOupf/v5fdnmZz7zGV588UUee+yxvPnvec97Mu1DDjmEI444gjlz5nD33Xfzjne8o9NtLViwgMsuuywzXVNTY4CFJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSBtRdd8EnPxm1c4umJ5PQ2AgXXwz//OfwjG1EqLgFgni2iFvRRDjyWpjz7mh6xW9g8eeGb3yShlxvwysS6USP26purmaPPbLTtbUwYULvxtEWShEEAcXx4rxlxfFiAqI6SY3Jxrz+bdqHV4RtARJA44plFL3hKGhq6t1gAuAGIA6UzYIwHQVP9GTTgzlFMgM47g/Rerk1nmIFsNd5sOPZ3o1lJ61YET0HArzvfRCGXfdNpWDLlqi9555R+FOsh5uduzwMQzbXbwagrLCM6uYoPGJ97RCHVxRNiH4bXiFJkiRpF3T33VEAYdu53uc+Bz/5SfYc7vLLYc4cuP764R3noPj3dyHs4fpEmByasUiSpBFv0MIrxo0bx2OPPcZDDz3E4sWLSafTHHbYYZx22mmDtUsmT55MPB5n06ZNefO3bNnCtGnTOl1n+vTpnfYvKChg0qRJ3fbpbJuf/exn+dvf/sYjjzzCnnvu2e14Z8yYwZw5c1i+fHmXfYqLiykuLu5yuSRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkrQz6uvhYx/renkqFRVS362t+2tUhB3IFFaf/ubs8n0ugIJSeOWHwzI8SUNvVdWqvOk11Ws67ZdKpzqdn6u2uZYJE7LhQdXVvQ+vaExEoRSxIEZxQbvwipzppmQUQFHfUp/Xp314Ra7mTet7H1wBMJYouAKgdGZU+DIo6nm9Tf+AoCDqP+1kmPjGzvuFadjnwt6PZyesaj28ZWVw/PEQj3fdd+PGqNgpROEVySQU9eJmt6lprskcnwklE6huriYgYEPthn6Ovp+KJka/WwyvkCRJkrRrCUP429+ywRWHHgpXXhm128IFYzG46CJYuXJYhjh4mrbCa7/MCY2UJEnqXi8iqfsunU7z61//mre97W189rOf5YYbbuCxxx5jw4YNhN3FR++koqIiDj/8cB544IG8+Q888ADHHXdcp+sce+yxHfrff//9HHHEERQWFnbbJ3ebYRjymc98httvv50HH3yQffbZp8fxbtu2jbVr1zJjxoxe3T5JkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRpoP3wh1BZGRVx60pbYbfdUvM22PYU0PoHmvdFmHkmxAqyfWIFMOe9sOe5wzFCScOgLawiFkRlnFbu6Ly6ZUjPNZfqEnVMmJANQNixo/fjaEw2ZtrF8XbhFfGO4RUNiYa8Pt2FV7St02vjc9qls4Cgd+tV/zsKrgDY+4OQTnTeL4jB2P36NqZ+SCZh06aofcIJUFDQff+2vgCzZmULn/bW+tr1mfak0kkABEHA+pr1Xa0yOIr2gCAOiU7CK4onQ6yk43yAogmDOixJkiRJ2llLlsD6nFOsX/4Sgk5OWdNp+PrXh25cQ2L1HzoGV0w9GY76BRx6RRQ+KUmSlGPAwyvCMOScc87h4x//OOvXr2f+/PkcfPDBrFmzhgsvvJDzzjtvoHeZ57LLLuP666/n17/+NUuWLOHSSy+loqKCT33qUwAsWLCAD33oQ5n+n/rUp1izZg2XXXYZS5Ys4de//jW/+tWv+OIXv5jp8/nPf57777+fK664gqVLl3LFFVfwj3/8g0suuSTT5+KLL+amm27iD3/4A2PHjmXTpk1s2rSJxsbojZ26ujq++MUv8sQTT7B69Woefvhhzj77bCZPnjzofxNJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiSpM9XVUXhFW8F0dWLj/WSCKwrGwOu/3Xm/MIS5nx+yYUkaPsl0ki31WwAoihcBsK5mHWG7FKCWZEuvtteQaGDChOz0tm29H0tbwERA0CF8Ine6JdVCOkxTn6gnHsQ77dN+/dxgjF7JDXkomwVBD6kPbWpfi34HcZj9LogVdt03PfhpSuvXZ58XTzoJEl1kabRZty7bnjOn57CLDvtrDakICJhaPhWIannlhloMiaLxQAwSNR2Xlc+Gs5fBWxbDsTflLyudMSTDkyRJkqT+euKJbPugg+DIIzs/d4vFyDs/3yWs+VP+9Pxvw2kPwb4fgQMvg3Neg0lHDs/YJEnSiNTHS9w9++1vf8sjjzzCP//5T0455ZS8ZQ8++CDnnnsuN954Y16AxEB6z3vew7Zt2/jOd77Dxo0bOeSQQ7jnnnuYM2cOABs3bqSioiLTf5999uGee+7h0ksv5ec//zkzZ87k6quv5vzzz8/0Oe644/jjH//I17/+db7xjW+w33778ac//Ymjjz460+faa68F4OSTT84bz29+8xsuvPBC4vE4L730EjfeeCNVVVXMmDGDU045hT/96U+MHTt2UP4WkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUnduvhmam/PnveUt8P73Q00N/PSnsGzZ8IxtxNjxHASFECZg9rshVtJ5vyBoLfwtaVe3oXYD6TBKNxhTNIamZBONyUaqm6uZUDIh029T/aZeba99eMX27ZBKQTze5SpAFHDQnMo+iBfHi/OWFxcUE5IN1GhKNlHfUk8QBJlMnuKC7DodwisSfQyvyB1v6czocbEn6QQ0bozak46Gwh7qMQWxvo2pH1avzrZf97qoeGl3Nm6MbmoYwuzZfd/fhtoNAMRjcaaPmQ5ASMi6mnXdrTbwCsdDQBQQkmqEeGn+8vLZ0Y8kSZIkjTIrVkBhYRROeMEF0e/CLnITu1s26jRtgW1PkrkIsOe5MP+/o3ZbcGQaOPGv8PgHh2GAkiRpJBrw8Iqbb76Zr371qx2CKwBOPfVUvvKVr/D73/9+0MIrAC666CIuuuiiTpf99re/7TDvpJNO4tlnn+12m+985zt55zvf2eXy9onn7ZWWlnLfffd120eSJEmSJI188XicY489NtPWrstjLUmSNDR83SUNPe93kiRJkjRyec42ennsJEmSJEmSJA2nnb1GedNN2YLbAFdeCV/4AiST0bxPfQrOOScqzN2Vykq4+26or4fDDoOjj+5dvfJRo/Y1CJNRe58PQZiGoIu/dToJsd6XdPEaszTydXY/raiuyCyfUDKByobKzPzc8IqNtd08eOZoSjblhVdUVfUuvCKRTmRCNCA/iAKiMIvc2kiNiUYaEg0ERA/ShbFCYjlhEO3DK5qSTb0af0ZuyEOsl5U+G9YSVcoEZpwZhVl0t+4whFf0dByamqKAi1QKZszo+/7W166nIFZAGIbMGjcrMz/3/9mQKByffUGQqOsYXjHEfI6UJEmSdm1D+Zp/xQpIt556nnde9+EUu0xwBcD6O8kEVxSOg2N/13ptM+fcOlYAxVPgoC8P6lA8x5MkafQY8PCKF198kR/+8IddLj/rrLO4+uqrB3q3kiRJkiRJQyIej3PGGWcM9zA0BDzWkiRJQ8PXXdLQ834nSZIkSSOX52yjl8dOkiRJkiRJ0nDamWuUGzfC449n61R/7GNRcAVAQWtVklQK/vxn+PCHO66fTMKXvww/+xm0tGRDMA47LArFmDevX8MaPmEaErVQUJZfOL1mKRBGRb2nHA+xboqr9SG4ArzGLI0Gnd1P20IFYkGMSaWTWMlK0qSpqK7g9dNen+m3qW5Tr/bRkmrpEF7RG42Jxkw7JKQ43i68oqCYkGx4RUOigfpEfWa6KF6U1799eEVjspE+yX0I7G14Rd3KbHuPN3QdDjSE1qyJngeTSZgzp+f+iUT0HDh2LBQX99y/vfU16wFIhSlmj5+dmb+xrnfhJwOmaDyEqaidqIaSKUO7/3Z8jpQkSZJ2bUP5mn/p0ug65+zZMHfukOxyZNi8MDrPDlOwzwXRdc/OQiFjBTD9zYM6FM/xJEkaPQY8vGL79u1Mmzaty+XTpk1jx44dA71bSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSX1wxx3Z9pQpcM01UfhEEGTnx+NRIe5vfSt/3aYmeNe74O67s+EXbb9feAGOOQYefRRe/3pGvuZtsORKWP4LSOyICq7P+QAc9GUYNxfqV0X9pp/e53AKSbumiuoK4kGcdJhmWvk0giAgCINMqEWbiaUT86ZPnH0i44rHAbCkcgkrd6wkJKS8oJw99sj227Ej/7G4K7nhEmEYUlzQLrwiXkw6TOf1b0g0ZAItegqvaEo29TyIXLn1L4NePl7Wrcq2x87tvIjmEFu9OvpdXk5eqEhXksnod1FR9/26sr52Pcl0tJHpY6ZTXlhOfaKehkQDtc21jC0e278N91XheGgLO2lYC2P3H5r9SpIkSdIgW9V66vmmNw3vOIZc9SvZkML9P9V93xDoxbUISZK06xvwq/SpVIqCgq7fNIjH4yTbrrRLkiRJkiSNMmEYUlVVRVVVFWHbp+m1S/JYS5IkDQ1fd0lDz/udJEmSJI1cnrONXh47SZIkSZIkScNpZ65RPvEExFqrj3zyk1FQRWfF0gsK4JBD8uctWAD33JMNrMiVSkFdHVxySZ+GMzxqX4O/HwlLfhQFVwCkE7D6Jvj74bD2L5BqLd6+x6GQbhnQ3XuNWRr5OruftoVUhITMHDuTVJgiHot3CK9oSDTkTV9/zvXc+f47ufP9d3LB6y+goDUQJ0WKMWOyj8lVVdFjck9ytx8SUhxvF17RLsyiIdFAfaI+E2jRPqyi/fSOMXEoyZ/XrdwxdxX2U18B25+NftbfDevuzAZdlM/p/b4G0YoVUSDFnF4OJ5GInj+7Kb3VrTXVazLtyWWT2aM0m2SyoXZD/zbaH4Xjs+26ldHz4TDq6jkyDOHxx+HjH4cTT4TzzoM//xlaBvYpWpIkSdIgG6rrYtu3Q21t1N5//+gcbrcQhlC7LGqP2RcmHNJ9YGRvUjR3ajheB5UkabTo56XuroVhyIUXXkhxcXGny5ubmwd6l5IkSZIkSUMmkUjwk5/8BIAFCxZQVFQ0zCPSYPFYS5IkDQ1fd0lDz/udJEmSJI1cnrONXh47SZIkSZIkScNpZ65RvvRSFDQB8KlPdV8oPZGAwsKo/dBDcNVV3W87nc4WhRuxmirh/uOhZTuEqfxlYRJSaXhhQXbe2P2Bbgq89YPXmKWRr7P76ZrqNaRaHzf2nrA3AKl0qkN4RW1L/gNheVF5XrstRCIKoQgZMyagpga2bMkGWXSnMdGYaafDdIewivZhFo2JRupbsuEV7fvnhlfEghhbJpXAsmVQWZnttGQJfPCD2embboJ586J23eOw7rNRu7NClPUVcOdcSDd1XFY8BQpKu7qpQ6qqKvq99969699W+LTtebKv1tesz7Qnl01mStkU1tWsi5bVrmfu5Ln923Bf5YZX1K8emn12o7P7XnMzfOIT8LvfRWEhyWT0+uUvf4n+G95/P+y558CNoa4u+pk4EXyKliRJkgbWUF0XW7Ei295vv0HZxcjUvA2SdVF7z3Oj659BNxeAuwu2GABeB5UkafQY8PCKD3/4wz32+dCHPjTQu5UkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZLUS2EIr74atY88EmbN6r5/W0HuMITPfz4qqp5OZ5fPnAkTJkQ1ztsCMVKpDpsZOcIQnvwItGzrGFyRkYZ0c3Zy3IEQG/ByLZJGoVU7VmXa++6xLwAhIauqVuX1q2muyZsuKyzLa7eFSCTTSZpTzYwbV0JNDaxc2btxRKEXWe3DKtqHUzQkGqhrqctMl8RL8vvnrB8LYtH2Z8+Ofroybx4cdljU3rQd1rXOD5Md+zZXdh5cATBm3673McTawihmzYqeLoKg+/7J1pta0I+niFQ6xbbGbZnpyWWTmT5memZ6Q+2Gvm+0v4pywivqVkOsn2kcgySRgDPOgMcei6bb/u5trzeWL4cLLohCtnbWQw/BFVfAAw9Er3fGjIkyW77+9Z5fM0mSJEkaWXLDK+bO7X/w4KhT+2q2PfGI1hPc4RuOJEkaPQb83dDf/OY3A71JSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSX0VhlD5BFT8GRo3Qsl0mP0umHI8GzYENDZG3c45JyoI3ZvCbQ8+CC+9lJ2ePBluuAHe+tZoesMG+Mxn4I47Bv7mDKh1f4UNd3WcHyuEdCI7nWqEoBDCxIgqrC5peK2tWZtpz500N9NeU7Umr19Ncw3xIE6qNSSnfXhFSJjXd489Sli3rvfhFY3JxrzpkoKSbqcbk43UttRmlxd23T8goL6lvncDyayUU9Kqs/CK7oygx9iWluh3SUkUXBCPd9+/bXl/Qps212/OhJjEghgTSiYwpXwK8SDa6Pqa9X3faH8V5oRX1K8euv320n//Nzz6aPTypjPJJNT38b9se2EIl18ehVTkBnXV1cH118Of/wz33ANHH71z+5EkSZI0dFasiMIGk0nYb7/hHs0Qyg2vGH+wobySJKnXfNUgSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIk7WqatsC/PgCb/xEVEw/TEMTg1ath6kksTdwB7AHA/PlRgebeuPbabLG3KVPg4YfhgAOyy6dPh1tvhQ98AJYtG/BbNTDCEF76VvT3aC0Yzp7nwRu+D+PnQdNWWHIlLPkRpFuANBRPgsKxwzlqSSNETXMNdS11ABTECth/4v6ZZZvrN5NMJyloLQhZ01xDLIiRClPEgzhF8aJM3/LC8g7bnThxKgDV1VBTA+PGdT+WhkRD3nRxQXH+dDx/uiHRkBdIUVpQ2u367bffo1hOClJuEFBvlM2CdHJEFNNMtA69sLDroIRcbeFPiT7eZMgPpxhfPJ5YEGNy6WRiQfTEvL7W8AqARYvgBz/ouV+yj5kp7f3kJ/C1r0Xt9mEkySRUVcGll8Ljj+/cfiRJkiQNnW3bIAigrCwK4h3Rko1R4O6mB6Mw3QmHwpx3Q8nUvm+r5tVsKO/Y/XvuL0mS1KqXbxtLkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJGhUaNsC9h8KWh6LpMAmkW38DW//F0nt/RxBEk4ccAvF4z5vdsgX+8pdsYejf/Q5e97oozKJNWwjGTTfBnDkDcFsGw7anoOqFbHDF6z4NJ94O4+ZG0yVT4NAfwNG/iqqWh2kYs9/wjVfSiLK2em2mPbF0ImVFZZQVlgGQDtNsrN2YWV7TXJNplxSU5G2nbZ3cvpMmkXlsXrWq57E0JhrzptuHVbQPo2hMNGaCNzobQyyIUdgaQBESUp+op0+CnCeEVGPX/ToTKwbSfVtnkLQ9z/U2vKLtebA/wQmvbns10y4vLOeFTS+QSCVIh2kS6UTe8kFXOBZo/Q/YsB5SzUO37x5861v5rzeOOw7uuQe2boXnnoOPfnTn9/Gvf8EXvtB9n3R65wMyJEmSJA2ttqDBvfYa3nH0aMN98Ne94LF3w4pfwcobYPHn4I5Z8Op1vTtBzVX7KoQpKJkOBWU995ckSWpleIUkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZK0q0g1wcJzoGlrVJysM2GSpaunU1AQFYLubcjEY49BqnWTb3oTnHlmVNi7vVgsKu786U/37yYMuld/li2wPv10OPKaqB3klGIJAtj3w1A+GwiheNKQD1PSyFRRXZFpTy2fCsDkssmdLs8NrygtLM3bTnlRed50TXMNe+yRDRNatiz7mNuZMISGREPevPZhFblhFgEBDYkGGpPZUIn24RUARfEiIAriaL/9HsVy0gXq12ZDgnq1biH0sQ7nYEm3DjvWywpdbSEXbQVR++LOV+/MtNfVruPQXxzKT5/5KanW5/BHKx7t+0b7K4hBvO3/RAh1K4du3z14+OFsaMS73x1Nn346TJ4Mr389/OpX8LOf9f6YtZdOw6c+lQ2PAZg4Ef7zP6PgjLe9LXvfNLxCkiRJGl1aWqLfJSXd9xtWr/0SHn4LNO+IpsNEaxBxGP1e8cv8E5beqFsBpGHcAQM9WkmStIsr6LmLJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpFHh5cthx3NATsHwMfvB2P2jgmW1rwGwdO1sEgmYOzcKsOiN556L+iaTcNllUZHuzsIrIJp/2mk7d1MGRRjChntai78FcNiPIZ3ML7jeJohB8ZSoHSsa0mFKGrkqqisICAgJmTFmBgDTx0zPhFZUVFdwPMcDUSBFWwhBaUF+eEX74Iia5homTMjWoly6NAqvaCuY314ySV4QBeSHVUB+mEUsiNGYbMwEUgQElBR0rNxZFC+iPlFPOkxTn6jv6s/QuXjObWzcED3WBr18/Ozqcba+AporW7e5EVqqYMy+MOXYvo2tD9qeF3sbUtAWXlFb2/0x68za6rXdLm9KNvV+YwOhcCykWo971Ysw9nWdP0cOsYKC6HXHm94EN98czWsLqmj7/elPd/26pCd33w3//nd2+owz4LbboKwsOqaFhfD88/DWt/b7JkiSJEkaJolEdM5WNFIv7218AJ5uSwHuQwhkT1Kt55Nj9ov+AH0Nv5AkSbut4b8iLEmSJEmSNIrEYjGOOOKITFu7Lo+1JEnS0PB1lzT0vN9JkiRJ0sjlOdvo5bGTJEmSJEmSNJzyrlG2bIdXfkimyFnxJDjuDzDjjOwKmx6Ef72XqvqxABx4YO/39eyzUQHnqVPhnHN6Ls6dTmcLSo8YjeuhZUfUnnEGTDik+/7pluh30E017LbC6v0oqu41ZqkP6lbCmj/B5ocgURsV1Z/1NtjrPIj1s2J9L7S/ny7esJhYECMMQ5LpJHcuu5OAqABkjBiLNiziffPfB0SBFOkwekxuH1bRfrq2uZYJE6J6kgCvvNJ9Yc14HBoSDcSCWGYfuWEVkB9mEQQBDYmGTBhCLIh1Gl6RO6+2ubbrAXSmdGa23bgB6EthzLDjrPoKuHMupDsJcDj98UELsGgLr0gkevc81hZekU7Dli0wY0bv97WlYUu3y9NhmmQ6ScFQBUgUT4KmTVF7+yLY651Ds99OtN33fvtbaGmJEQTw059Gf+fOgrdiMbjwwv7t6/LLo/tUKgXnngu33prdZtv/gYMPhkWL4MMf7t8+JEmSJOUbqutiLS3DE14RhvDww3DnnfDaa1BSAiecAO94B8ya1dopUQuPfzB/xdJZMOV4iBfDjheiYMH+aLuuWTAGwjQEfUhaHAReB5UkafQwvEKSJEmSJKkPCgoK+I//+I/hHoaGgMdakiRpaPi6Sxp63u8kSZIkaeTynG308thJkiRJkiRJGk551yhf+BqEiahdPgdOexRKp+evMPUEOOs5mv8r6jdlSu/3tWhRVHTtuON6Dq6A1j4VFVBZmZ25cSNUVUXtCRM6VviePBlmz+79oPpq++Js+3WfhnSi+6L3rQXhiXVxg7sqrN7LoupeY5Z6IZ2El/8H/v3d1vtkGP1sXwSrfwfjDoTj/wh7vGFQdt/+fvqPVf8gFaYAeGj1Qzy0+qHsUElz/4r7M9M7mnZk2mOKxuRtt7ywPNMOCKhprmHChKh4PsCLPdSmjMWgMdGYH14RbxdekRNmERBQ11xHMp2MpoOg0/CK3HXqWuq6H0R7heMhVgzpZmhY37dQkXRLx6yL5srOgysgCjMZpPCKtoKmiQQEvcjfmDYtClQAWLu2b+EV2xq29dhn6dalHDKth7ClgTJ2f6h+BQih8qmun/+GQEFBAYcf/h+87W3R9BlnwKGHdr9Of+qfrloFTzwRtceOhV/+Mjru7bdVWBi9brr00r7vQ5IkSVJHQ3VdrO21fdt521B47TX42MfgkUei8L1kMhrHrbfCf/0X/PjH8OlPQ7Ds6ujcty2MeM574KjrobD1GkKYhleugLV39H0QbeEV8eLW7Q9veIXXQSVJGj0Mr5AkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZJGuzANr14DrQXVOfr6KLiifeHwWCGUTKU5FvUrKooKt/VU7HnrVtiyJWq/8Y1RQe/CHmqSB2srYO5caOqi8HhnSkpg2bLBC7DY/iwEBRAmYdrJPRdWbysEn050vryrwuo5RdXDEP76V/j97+Ghh6ChAWbNgv/4D/jMZ2D//ft/c6RdXjoFT3wI1vyRKLQiRxiFMFC7HJ7+JJz55JAMqbKhstvlm+s3Z9pVTVWZdvvwirLCskw7HotT01zD/jOixwyApUuhpgbGjet8P4kENCQaCHISH3KDJ6BjmEVNc02mHdB5eEXuvD6HVwQBlEyDhgpo3NC3ddMJOqZXDI+257dt23oXhjBrVra9ejUcfnjvQp6gd3/jF7e8OHThFeV7tz5PJmDHs9HrimD4Cpw+80y2/ZnP9Pz6o6AfVdWezHno+NznYOLEro97YSG89a1934ckSZKk4VNUFJ2utrTs3HbCMCQMQwggFnR9svjii3DSSVDXerqXbL180Rae0dwMv/oVXPSJGnjlh2SCK95wORz8lWyYLkAQg4O+DDP7cSLSdj0zVtR1n/qK6Ppm40ZoqYIx+w5aUKQkSRo9+pERLEmSJEmStPsKw5D6+nrq6+ujN5O0y/JYS5IkDQ1fd0lDz/udJEmSJI1cnrONXh47SZIkSZIkScMpc41y0wuELVXRzJlnwfTTug5miBXSnIyKkxcXZwundee557LtN76xd8W8qazsW3AFRP0ruy8Mv1O2L4oKcZfvDYXje+7fVtwt3b/qdps2wcknw3nnwR13RIXQGxvhtdfg5z+HefNCfvzjeurqvMYsdeq5/+oYXFE4DkpnRgX2IbpPp5ODNoT27wU1JBq67V/dXJ1p54ZFjC0em9evvKg80w4IqGmuYd99c/cL//oXpFId95FOw5Il0JhszJvfPqyifZhFbaI2b7qz8IrSgtJMuz5R33HnPSnbK/rduL7jsuLJEOu4TwCSDYyUklilrX+C1at713/PPbPtdes6P2ZdSXQVjpRjaeXS3m9wZ5XvnQ3CStZD9RDuu50wDHnmmXrGjasHQk48sefgrP546qlou4WFcNllPQePJHo+ZJIkSZJ6Yag+e1lYODDhFT97+mfEvxvn1BtO7bLPhg1wyilQW5sNrQAYMyY/bC8MgXV/g2TrdYOpJ0bBFRAFVuQKYjBhft8H3LadsIuT1PoKuHMu/P1wWPg2eOKD8MBxsPWJvG7zfjaP4NsBS7Yu6fsYcvhZW0mSRo9+ZARLkiRJkiTtvhKJBFdeeSUACxYsoKiom2RxjWoea0mSpKHh6y5p6Hm/kyRJkqSRy3O20ctjJ0mSJEmSJGk45V2j3K+QoiABB38tKuQe67q0SBCEQEBv64StWBEVeQtDOPLIngs7j1jbngZCmHhY7/q3FYJPNfd5V2vWwEknwfrW+u3ti5knk1BYmKC29kr+93+9xix1sPUJWPb/stNj9oOjfgHT3xxNJxvhxa/Dsp8AvUjh6afcx9kv/NcXSHVV9LFVSypbDbOupQ6AWBCjvLA8r19uSATQIbwC4LHH4PTTO+4jlYJnn4WGqflBGu3DKHKn02Ga2uZehFcUZsfVU1BHp8r3gm1xaNzQybLZcPYyaK6E6iVRYcw29WsgNjKeXObMif6+a9b0rv/Mmdn2unW9DHgCKht6F9a0csfK3m1wIJTvTd79ad1fYNzc/NcUgxgWkyuRSBCPX8lll8Ef/rCA8eMH5znysceiQIojjoCJE3vuPxgBGpIkSdLuaKg+e9m22Zqa7vv15J+r/gnA0+uf7rLPpz8N1dXZ64Af/CD8+McwZUoURHnffXDRRa2dtz4aBXOGSTjsx91fzw1iUFHRMfR340aoqoraEybAjBnZZW3Be+kWIOi4zeZKSHcSPFy3EqYcm5lcui0KNfz7ir8zb8q8Lm97T/ysrSRJo4fhFZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSdKuICiAghKYfGxU0KwbxcVRwbLm5t4V2W5sjPoVFMD06QMx2MFz80s387UHv8a9H7iXuZPnZhekk1FRNoCJh0eF22I9FEmLFQEBNKzt0xhaWmKc/a4ouCLZWuP7sMPgHe+AsWOjWnPXXw8N/agLL+0WwjQsuhiCOIQp2PsDcPSv8h/bCkrhjVfCPh+CxZ8fkmG9UvlKr/qtr1nPzLEzqW+pByBGjLLCsrw+8VicwlghiXSCMAypaalh/HgYPz4qdAnw4IPw/e933H5hITzzDDSd0UiYk0JUXFCc1684np1Oh2nqE/WZ6ZCw0/CK3HH2K7yidBYQg+ZtUfBPPH9MlM+OftqrG8KAhh7MmROFNG3aBC0t2UKnXSkuhj32gB07ovCKgl5U9kqn4bmNz/VqPBXVFb3qNyDG7J0/veaPcMjX8ud1E441WA7rZeZUXzU3wwsvRO1jjokKzI7agC5JkiRJnSpuPS1dty66Ttebc7bOPLz6YQAak40kUgkK4/nJdg88AH/7W9QuLY3ap50Wnf9BdG31tNNgyRL43veAzQ9FwRVTToiuVXanogLmzoWmTsImunIlMIPo3LyHa8VdqWnOJn7c99p9XHrMpf3ajiRJGl3698pBkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ0sgSJmHyMb0qRtZWtK2lpXfhFc3NEARR4bWR7pK/X8KqqlVct+i6/AWpnOJuZbPpVemVoklRKEjdqqiYfi/96P/m8e9/RwXxJk2C//u/qND8l74En/oUXHEFrFwJF17Y601Ku5fKJ2HHc1FwxYT5cPSvozCZWH5hSIIAxh8M878zJMN6ftPzveq3eONimpJNpMIUAEEQUF5Y3qFfaWH0oJoKU5mCkPvsk13+5JOwahXk5FMAsHUrPP00NCQbSJN9bCpuFxQRj8WJtT4nhITUNddlloVhF+EVBdnwiuZkc29ubrsbNRPaxrTjuY6D70r9qr7va5DsvXcUYhCGUQhRb+y5Z/R7bS+zjlIpeHnry73qu7l+c+82OhDK986frv431CyFdCo7L9WP/xf9kPtf541vjF6zDLQXXsiGTB19dLaorCRJkqRdx6xZ0TlYKhUFWPTHprpNVDdXZ6afWv9Uhz7/+7/Z66xXXw2nnBK1c6+9FhZG12W/+ZVtULs8mjn91Ch0tzuVlX0LrgBo22TTpn6HVzy46sG8dktqEE7MJEnSiGN4hSRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkrSrmHIcpBM9dmsLr9iwoXebbQuvKC7uuW/G5MlQ0rEwerdKSqL1+ikdptnSsAWAe1+7N39hbnhFvKTzom31FbD92ehn/d2QqI6K56eboXFTr8awtWYy3756PmEY/b3+/vcopCIWiwrUFRVBPA4TJsDPfta/2ynt8jbeB0E8ah95XfQAFASd940VwLQTh2RYSyqX9Krfi5tfzIRRtCkrLOvQr7QgCq8ICdnRuAOAuXPzC1v++tdRgc02yST89rfRvMZEI+mcYJ3igo4P0kXxoky7PlGfaafDdKfhFSWFJQREf+tEOkGypwKaHW7UzOhxE6DycQh7fk6KdlYDLdX584onQ6yL55GiCX0bVx/MmZMNMVi5snf5G3vvHf0XffHF/OPVlYICel30M5XuxQYHStEEKBiTP+/ZyyDWen8MQ1h+7ZAMJbcu6+TJXT8E7IzNObkgxx8fPU9LkiRJ2rXst1/2HG/58t5nLOa6f8X9edN/f+3vedNNTfDww9F+3vQm+PjHo+t/nQkCiG17LDtjyon9DpfoVlt+Zc2r/d5E7vXVRDrBE2uf2MlBSZKk0cDwCkmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJGlXMfHIbMH3brQVgV66tHebbSu2luxLDfPZs2HZMli8OPq56aaOfW66Kbt88eKo/+zZ2eVVL8PTn4bbp8MfS+BPZfCXOfDC16FhXYfNLdqwKNNetm0Z1U05hdDTOUXCY0Udi8LVV8Cdc+Hvh0c/C98Ga24GWqvb1XZS6K2Twur3PP9WEolo29/+NrzxjVGR8vZiVn6RurbhHgjTMPHwKJQn1kNF+SEq7r9y+8pe9VtauZTaltq8eeVF5R365QZaVDdHj1f77Zdf4PKXv4Tq6igQIZ2GhoZs8E1dS12mXzyIE+uk2GVhzt+uIdGQaYeEnYdXFJTkbSd3nV4pm5VtVz4ZPd72Vn27v2/5bDh7GbxlMRzb7jmkdEb+dO1r8O/vwTOfgac/Bc8vgM0L+1WVdO+9s+2VK3v33LfXXtFjfUNDFGDRkyCAgIBYaxmweBBn3aXrWH/ZetZftp73Hvxe4q3P5wWxTp5EBlPZ7PzpDffCv78fBYysvQ1W/25IhtHcnG2Xlg7O82ZjY7Y9adLAb1+SJEnS8Ntvv2x7+XJI9DJjMde9y/NDcu9efnfe9L/+lT2H+eIXez6PjNe8CEFB9DPl2MEJr9gIJIG61/q1ehiG3PXqXXnz2od2SJKkXdMQX5GWJEmSJEmSJEmSJEmSJEmSpFGsogIqK/PnbdwIVVVRe8IEmJFTJGXy5PwCW5IkaXiFIdQshabNkE5A0QSYMB/iHQu0SZIkSZI0ahVP6lWxs3nz4B//gDVrosJqxcXd9y8piYqmNzX1cTyzZ3d/rXzePDjssI7za1+Dpz4OWxZGRdzCnIpvDRXwyg9g1U1wzqt5hdHvWHJH3mbuWX4P75v/vmginnMj080QpvKDPporId3NDax9tbWIfk4h9rbC6lsehSc+CMCdz55NPA5TpkTF6uI9Z4lIytWyA7YvBkKYfgakk9BT8f7YEN3Rgt52C6hprslMp8N0XlBFm9xAi7awnX33zS+kuWULvOtdcN99UeDBBz8YvW05aRLUJ+oz/QrjnQd8FMWzj1mNyca8ZZ2GV8RLCIIAWjMf6lvqGVc8rptb207pzJzBP9L79QBqXoXxr88/nuWzo5+ubLgXlv4YNv2j9TG97TkwjJ4rpp4Cp97f8/+hHHPmZNvPPAMf+1jP68yalc3JWLgQDj4YirrJ7aithQ21G4jH4qTTafYo3YNZ47LBH7PHzyYWxEiFKTbVber12AfE+HnRtfS28CaAF78e/Qyh3NyRoJf3vb7KDa/o7nhJkiRJGmG6+zxvu8/y7tMcEASHEoYBK1b0PRgvlU5x72tReEVRvIiWVAvPb3qeLfVbmFo+FYD778+G1552WudBtnmSddGJTulMiJf2PIjJk6MLtH25OLuR6DpGqgkaN+Sfr0M2lLf99dCiCUAUDLyhdgMQXecIicIsLj/t8t6PQZIkjUqGV0iSJEmSJEmSJEmSJEmSJElSb1RUwNy5ffviV0kJLFtmgEU/pVKwfTvU1UFpaVSAp7DzmjuSJHWvaQus+h289suoyGSugnFw4Odh/rd6VdhTkiRJkqQRr6uQxvqKKJwBoHEjB06eRCJxNBAVbTvooO43W1ISFZFuaIgulZcMZhbkjhfgn6dAorXwexCH2e+EsftDOgVVz8OGv0PxxPwgCeCWV27Jm759ye054RU5g042QJjOD6/oSe1rZIui5yifHRX6BlqShdz7wlmkUgFvfevgFduWdmlbHiOTnDDzrBF13S6W8xhw7J7H8vCFD2emD73uUJZULiFGjCDoZXhFYTa8oralFojekmzvoYdg3LiowGZDQ3Z+fUs2vCI3pCJXcU5wT1My/73OTsMrCkoIclI6cgMyeiW3GGbTZtjxYhQi3JsHxG1PRY/3vRGG8PxX4ZXLs4/lsUIo3zsKPWpYB4kqSFT3KbgCYPx4GDMmep/ywQd7V9h0zz0h2Zqz9MADcMklXfdNJOCJJ2B97XpSYQqASaWT8vpMLptMOozCI6qbq2lKNnV6vAbFuLnR3zRM99x3EOUGazU2RiFaAx0IlfvfMjcsQ5IkSdII1sfP85YAU9nEZqaxdGkvgiXaeXbjs1Q3twZOTtiXpduWAvDAigf4wOs/ELUfiM4J3/QmKC/vclNZqcbo0ke847WCjLbruY0bIVUFj/8Bwpy0xSVLooTLXDfdFIUFA9QuhPWXRe3qJVAyI/8kqJNQXgBKo+CPv7/298ysPcftydqatfx767/ZWLuRGWOz4SCdefVVWLo0Oq8uL4f994fXva7bVSRJ0ghieIUkSZIkSVIfxGIx3vCGN2Ta2nV5rCVJkoaGr7ukoef9TpIkaQSrqIDKyvx5GzdCVVXUnjABZrT7ksfkyRbEl4ZSZWXfgisg6l9Z2av76pCes7V/zBlBjzdhCM88A3/4Q/Qdum3bsstKS+Fd74L3vx/e/OZ2XyBMp2DrI7D5IWipjr5gVzQRZpwJk44a1Opgnm9L0gi35s/wxIch3UKm4F2sOCpilqyDZE1U7PL13xnWYUqSJEmS1F+xWIw3zJsN6/5GjHTrOXA79RVw51xIZ69zH9j4JuBRAF56CQ44oPvCbZMmRUWjAV5+GQ4/fABvRK6G9fDgGVFwRZiGg78KB34hCqpItwBBdF5fvwZWXJ+36pKtS1ixYwUAZYVlNCQauHv53dmC37Gcot91r0Xb6ostD/dYAP2J5cfS0BJVqDv77Ohv1t2lY68xS51oznkfa9JRwx5ekXs/vX3D7QAEBOw5bs+8wIg9x+3JksolpEmzaseqvPCKkDAvqKLN2OKxmXZdSx2QrTHZXmdvVTYkskkWXYVXFBVk57ekWogFsUwoQlfhFV3to1cKSqMAi8YN0fSGu6KAn6AXKfUb74PDfty7/Sy/Blb+OmqXzoK5n4P9Pw6F46N56SSsvR023NO38beaMyd6vluxAtavh1mzuu6bSEThFW0efLD7oKfCQnjkEViz95rMsZg2Zlpen8llkzPBFgAbajew7x779uu29NnYuRAmhmZf3Sgri/H889F9b9y42KCES5SWZtvNzfnTkiRJkgZXv6+L9ePzvK/jVTYzjYULo3O4wl6corb5+2t/JxbECMOQo2cdzdJtSwkIuG/FfZnwis2bo77HHBOFWPQYkNF2vtfVNY9OrucCcPrjMOXYrrc7bx4cdljUri7LCa94BaaeAEG7awc5obzt3b387kz76D2PZv2S9aTDNPevuJ8PH/rhDv0rK6PP/f72t/DCCx23d/DBMS644A3Mnet1UEmSRjrDKyRJkiRJkvqgoKCAc889d7iHoSHgsZYkSRoavu6Shp73O0mSpBGqogLmzu17UfySEli2zAALaRcxZOds/XnM6eTxZtUqeOIJqKmBeBwmToSTTopyLvpr0yZ473th4cLoi3vJJBQXw9ix0NAQ/fzhD/DQQ/Dqq61f7mvcDC9/D1bfDC3bICggW2wshJe+CROPhDP+FRUzGwSeb0vSCLb8Onjm00AAxZNg34/A/p+Asa+LlidqYNVNsPXRYR2mJEmSJEk7o6CggHPf8ia466PRjERtlBScG+rbXNmh0NmBM5dm2i+8AOef3/1+WuvIAVEI8fz5UNR5nfSd88LXoWV7FFxx7A2w9weyRdxiOTssmw2v/27eqncsvYOAgJCQ+VPn89T6p2hMNvKPlf/gbQe8DWJxKN0TGtfB9sU9BlF0sG0RNG+LrjN0YVPV9Ez7pJN6LlTnNWapE8k6IBbd9+PFnfepr4ge2xo3QktVNG/Mvt0XcOyn3PvpR674SDQvVsDU8ql5/aaPmU48iJMKU6yuXp0XXgFRqE57Y4rGZNpNySZS6RSTJsWZOBG2b+95bI2Jxky7uIu/VWlBthp/+/CKztYpLsifV99S3/NA2pvyJlh7W1SMc+VvYd6XOvbpLImg+pUo9KJ0Zs/7aAuumHQUnHIfFIzJf1yPFcBe58Hsd/Z9/MD++8Mrr0TDvOUWuPjiroubFhbCoYdmp5ua4P774a1v7fx5IJWCf/0L1k9cD0RhKNPKO4ZX5BrS8IpxBw7NfnpQVFTAP/95LrW1MG7c4LzuKMu5W65bBxMmDPw+JEmSJHVuKK+LHcCrPBk/nvr6GI8+Gl23i8d7t+7dy+/OnEefM/ccbnjxBkLCzPxYEKO+9dR53LhsAHC3ClpPRlKNnS/v5HouAHUre3/tY8y+QAxIw6b7Ye5ne7ce0fWGR9Y8AkA8iHPW/mdx6yu3Egti3PvavR3CKx5+GN75TtixIzqPLiiIMjTGjYO6Onj2WXjllQJuueVcFi3q9TAkSdIwMbxCkiRJkiRJkiRJkiRJkqRR5qYXbmJtzVoWnLBguIcioKUlKqZeUBB9oT0W68dGKiv7HlwB0TqVlYMbXlFREe2jzcaNUFUVtSdMgBkz8vtPnmyYhnZdkydHIQ59DX3YmTQHoqI0998ffXGrtjb6stykSXDyyXD88f0o0NGfx5zWx5vKstlcfTXceissWdKxWxDAeefBn/7URTGu5m2tX6hLRl+8K9srU0Bm+fLoy4BbtkS38f3vhwsugFNOyX5B8Lnn4MYbYfHi6E/L5oXw6DuiwuNhEsbNhb3Oh/K9gRBqlkHFrdGyToIr0ml48cVony0tUF4O8+bB9OkdukqSRqMtj7UGVwATD4OT74XiiWRDjoDCcVGYxes+NSxDlCRJkiRpwBSOy7Z3PA9TT4Cg+wvIk8dWMq60mprG8dxxB/zP/3S/i7lzo2vSLS3w/PM9hzL0S8sOWHNzdF33gIthnwu67psbztHqllduISQqhv6W/d/CU+ufIhbEuGPJHVF4BcDko2HtBtj+bMdtFk+GWEnnheGCWBSosfZ22PfCLgOT65qzhejHju16+JK60xpq0Mn9HIiCK+6c2/l99fTHByXAAqAh0UBVU1XrCMMO4RXTyqcRC2KkwhSb6jZR3VSdCdSBzsMrygrLMoEXALUttUwomcD8+VHge08akznhFQWdh1fkzk+mk8SDbHXOkoKSDv1LCkoyY4bodvfZ5GOi9+kAapfDa9fB/p9qFxrUSXgFRIHDB17Wc8BQEIfSGa3BFWOjgKL2diLc/oADovcpk8no/c9LLum679atMGVKFHjx2mvRvO99D845p2PfZBKuuQaqqkO21G8BojCU9mEV7afX16zv923psz1eD0FB9Hw8zA47LLovPPPM4Gx/772z7ccei477oIRzSZIkSRo4/fg8734FawjD6DrDLbdEn8HtSiKRDS/c0biDp9c/DUCMGGfsfwbTyqexuX4z2xu38/ym5zlsxmGZwIpef5cg3ho02bQ5Cn4Mepmk0RfxIiibBQ1rYdM/oqCMeGnP6wEL1yykJdUCwEFTDuJNs98EQDpMc+9r95JKp4i3noffeSe84x3RZ3KnTIGvfQ0++EHYY4/s9mpq4Oab4a9/HdibKEmSBofhFZIkSZIkSX0QhiGJRAKAwsJCgq4+/KpRz2MtSZI0NHzdJQ0973eSJI1+lQ2VXPCXqEDLMXsewyn7nDLMI9r9JBJw331RIfm774aVK7PLiorgxBPhrLPg3HNh332HYEDtq8e3hUsMRLBERUVUhaivhfqXLTPAQrum2bOj/9+5gS5LlkTfsMp1001RAgL06X7X/pztrrsCvve9qAhHGGa/CBf1he98Jyqc8dJL7YpnhGmoejEq2N2yIyooUlAG4+dHxcr66e5Hx3HBt6MvkKXTcNRR8B//AXvuCakUvPoq/O1vsHp1u4JlW/8F6/4C6++GmnaPWQVjYPrpJKe8hTPf+nG2bIkxbhzcdRcce2y03XjO9/He8Aa48soobILNC+HB06Mv7Y3dD469CSYfFQVj0PotwCAOh/0vbH0i7293xx1w221wzz3ZPJ5cBx8MH/gAfPnLvfsioefbkjRCvfKDqLhW6Uw49Z9QUN75F713onhZB2EIta9Fz8XJumh/RRNg0jFQsnOBVpIkSZIkdSUMQxKxCVA4g8KWjQSVj8O8L/S4XhDAgTOX8PSKY1i6NLrkPXdu19dFwzC6fvrcc1HIcG+un+YWeuuVVb+DdFQUjQMvi655B72r+La2ei3Pb3oegNKCUt53yPv49sJvkw7T3L70dn5x9i8oiBXAxCOi69ZNm6FpC5TkFJ8vnw1nL4uCmKuXwBM57wG01Vhf+ZsoDLMLQU4x9rCLuuy5Rs015nQCtj0dFbqrWQrJhui6SvEUmHoiTDsVSqcN9yi1qygoB9LRm1LpRMdreM2VnQdXANStHPDwirb76aptqzLzkukk08rz/89PLZ9KOkxnlq+vXU88FieZjgIAyovKO2y7vLA8ut+3Pl7UNNcwoWQCxx8P//pXFHTQnaZk9u9QHO88vCI3oCIdpnsXXpHzAFafqO9+EJ2ZdAyZ9+wAXvoO7PuRqB0riN7Ta9qcv04Qj977W30THPSlnvcRpuCAz0bvOXYWXLGTTj4ZfvSjqP3kk/Dii9HbwO2f19Jp+POf4eKLo3VWr46O2zPPwG9/G72d3Pb+aToNtbXwzW/CnnMrSaQTme10F14RC2Ksrx3C8Ip4CYw/BKqeH7p9diIMQ44+OsHTT8OyZYU0NASUdcyA2Snz5kF5OdTXR8f5k58c2O1LkqQeVFTkfx4PBvZzsJJGtE6vi6VaoPJx2PQAbHwAGjdE1wvjJTDuQJhxBkw/HZYuhW3bshtr/3ne3M/yAgc8tRepi6Lrbn/8I/zkJ10H1+We9/3m+d9kAh4nl0/mhudvYPqY6Zkwwl8s+gW/OPsXlJdH53t1dV1nceYZsx+ECUgmoOol2OPQXqzUD+MPisIrUk1RyOSc9/bqs1LXP3s9sdbrspNKJ/FYxWOUxEtoSjVR01zDXa/exdsPfDvbt8N73xt93veQQ+Cf/4wevtufO48bBx/5SMi73pWgpWWEXweVJEmGV0iSJEmSJPVFIpHg8ssvB2DBggUUdfUulEY9j7UkSdLQ8HWXNPS830mSNPp975HvZdpfuP8LLPrPRZkvBWjwPfQQfOITsGJFVFhg772j6UmTosIDS5bAI4/A8uXw6U/3YcOTJ0ehD30JiWjTvmh+d/oaLFFZ2fcxNTVF6/nlQO2qZs/u+f/3vHlw2GF93nTuOdvy5Qv4/e+LiMWiUJzzzouCcaZNix5vli2DO+9sF1xRvRT+/V3YcBckaoAgKthNAKSi4i1BHOIn9/kx5+bCD/GBS/cD4JRT4De/if4MiWwtFWKxqHjLiy+2zmjcDE//J6z/WzSOkmlRQZrxB0VffGveBpsfhg338Kc79mLV6uj57K67omCMIGgXgkG2ENqUyWm4/+LoNk2YD6ctjAI6ICp2096kIwBYswbe/354/PHoi3GHHAJnngnz50d/xx07YOHCKKDojjtgwYLe/X0835akEahmGWy4O2rP+0JU7K6z54iBsm0RvPpT2Hhfx4JrbaaeCqf+fWDDMiRJkiRJo8sgFWRMJBJc/oMfAJ9kwf4/oGjr4x07FU+GWEmHYu+H7Pkyz645imQyxs9+Bj/9adf7KSyEI4+Mrk0vXhwV5549u/sQiz4FVwBsuCf6PeVNMKZvSfG/XPzLTPvASQeyumo144rHUdNcQ1VTFX9d+lfOP+h8mHhYdH0ZouDlfT6Yf75ePjv66aC1CHvlE1D9Cox9Xafn+WNK6jLtmprovcTujPhrzM3b4aVvw4r/g1Rj9F5DyTQoHBcVn29YD69dB2V7wdnLoYvi+VKfFO2RbVe9CHu8sddBNoMh935aSCEJojfJppZPzes3tXwqqbbHF2BD7QYCsoUYywo7Vt0vKyzL61PTXAPA8cf3HFwREtKcas5MdxZEAVGgT/v1ulunpKAkE8IB0JBo6H4gnZn4xug9wrD1RjRvhYfOhBP/Ej0n1a+BRZ/JX6ftb1f1ElTcAnue1/113VgR7P+fg3bt94QTIB6PCnACXHhhFEiRK5GIPiNyww1ReMVxx8H112eXL1gAb3lL9JQeBNHP5z4XPfVPK9mQ6ZcKU92GV8SDOBtqNzCkphwH1S9HxVSHSSKRoKzscr78Zfj+9xfw1FNFnHBCx/eRd0YsFr0//fDD8NRTvSwyK0mSutaXax8bN8L550NzM73Wyedgt9Zv5e7ld3PW/mcxbYyhitJokndd7CtfoWj9n+C5L0bnkEEcSmdG1/LiJZCohspnYNM/oezq6DrUnDldb7zdZ3lPmQPBxVHYbFUV3HhjdJ7X/vwikYCXX4ZDD42mf7HoF5llW+q38Nl7Pwtkz61v/vfN/OLsXzBhAmzaBC+80MtrolNPyLY3P9z62dqc64JdXM+laEIvNp5jwuujv1mYhOXXwT4X9Gq1vy77a+bawMNrHubhNQ/nLb/qyat4+4Fv56c/jT6OXFgI990He+zR3Tlbgp/+dARfB5UkSRmGV0iSJEmSJEmSJEmSJEmSRq31Net5fvPznL7v6RTFd/0Prq/asYqfP/PzzPRzm57jlpdv4T2HvGcYRzU0GhONHHTNQRww6QDu++B9wzKGa6+NCg0EQVRE/sorYd99IZ2OChW0FVlPJODBB6F0azdfwIOOX8J78EEozinksmRJx2CKm26KvkjT1fKe9DVYoj+hGiUl0XrSAGtujr7Q9fTTUThCbW30BbLS0uhucdRRcMQRMGbMcI90YNx6K4wfH4VEnHde9NiS+2W2Y46JbnMYAmEaXv4fePGbUdGeyUfDnPfBjDNhzD7RF/haqmHzQ1HRr6qXoi/wtj1G9fB4U1sf4zPnzCesCjj/fPjzn1v3S+dfsJs3D6hfC38/HFp2RMXFjrwOZpwerZhuLW4SBPD67xA2V/Ptr6SIxeDNb44KuvSkYNNfokIpAEf8rOeC5LFCKirgDW+A+no46KDoi4eHH54t+hOLRe1PfCL6/fvf9zwOSdIItu4v0XNgrAj2+/jgBVck6uDZS2DFr6JCbNNOhplfhmmnRkUcwxTUrYBND0D1EoMrJEmSJGl3VlEBc+f2/X2XvgSTQ3QdtmkT1C6HMftli72Xz4azl0FzZXSO+kR0XfjkeQ/z64UfA6Lrpv/zP9G19ng8f7OJBDz5JLzxjdF7Y2EIP/sZXHFF10NJpWDLlo6ZHN1qqgTCaOxdqa+IbkfjRmipiq5DTzmWnz6dTd54bvNzvOX3b8lb7XuPfq81vOLw7Mzl18B+H+nd2ArKIVkftf/1fnjL09Efoq3KdWsxt1l7rM+s8uCDcO65/QjxGCm2PAKPvhNatkPpLDjov2Dm22DM3tk+yUbY8jBsesjgCg2cycdn2+vvhglvGNbwiq60L4zbfnpzXX7QbXlheYdttJ9X21wLwLHH9rz/MEjkhUx0FV7Rfn4Y9hxekRtwUd9S3/Ng2ouXwKSjoDInUGnrv+Cv+0bPSXUrINXuOTFWDOnWwsVPfxKmnNharLP1SSnntgLRdroq2tnFc0VfjB0bvZ/4zDPRw/1zz8F3vwvf+lb0WZF0Opp/wQXZ909POCF/G5s2wfz58L3vwZQp8POfR88NAImS7PNFOkx3CK8YXzKeWBAjHaZJh2nW165nSE06Onqe7EmsJDpOQ+Daa+GUU7rv0/699d447jh49NHoZdfy5dHngdq/FsqVTA5sgIYk7Y621m9lS/0WDppyEIHJQbuO/lz76KtOPgd75P8dyZrqNUwtn8qmL2watf+nHl3zKGOLx3Lo9EOHeyhK1kPTZkg1R587KZ4MReOHe1S7vicvhPV/jD5/M/fzcMBnYWy7a4RhCrYthtW/6/N1qEmTos8Zt4USXnYZnHYa7Lln9vV9Oh19XvlrX4O774Z0Os1rO17LH0LO+TJAbUsta6vXcsope/Haa7BwYS/PS8r3geIpUVDHlkfgwEvaLW+9nrvl0cy1XABK+3KxFZj1Nljyo6hd+ThsvD/6XFM3n6V6ZN1ikunuEzWf3vA0TU3w4x9Hf7cPfximTzcQUJKkXYWXPyVJkiRJkiRJkiRJkiRJo1JTsok9/9+eAHxg/ge46R03DfOIBt9X//nVzJcA2r6c/l8P/BfnHnguxQW7dhGQy+6/jNVVq1ldtZpbXr6Fdx38rp3bYEXfgiWWVxTz+c8dRBgGfO1rUTGCVCpaFotFP20KC+HU/Qep+NC8eXDYYVF7Z4IlUi2w8V6ofBK2L4Ydz0dftArTEC+KigFNOhL2OAxe+BfUta7fU6BG27j6UkBJ6sGGDVGhrF/9KvrvvtdecPTR0V00FoNt2+DXv46KfCxduvP7a0m18OYb3szE0on85b1/GbYvsqbT8LvfwVlnRdPtv8SW99iz9Gp48RtRMZej/w/2uSAKiMgtjl00PvoC2p7nQOMmKJvZ68ebH34DqmqgrAyuaa1N0l2hjsJC4PGLW4Mr9oG3PJv9kmAQRI8zOaobxrF8TfR3/tCHevmlvVU3ATGYdARMfVMPnSOf+UwUXLH33rBoUfbLhrlFRYqKsvP6mg8kSRphmrdFxexKpkFBWed9drZ4WRjCv94DG/4OZXvCcb+HqSdCuiUqXtCmdAZMPm5EFteTJEmSJA2hysq+F2/sazA5AK2FvV/5IRz1y/xF5bOjnxznHP43CgpCksmAujp417vg3nvzV0smo2F897vRNfu2At3XXQcLFsAee+S/X9YmHodf/CIq8t1rmevyYefL6yvgzrmQzv9bLj/yT1Q3V3e76Rc3v0g6nSZWPAlKZ0LjBti+CDY+EAVS9hQ6OeXEKKAyTELVC7Dos3DUL6BdIbej93+KsSU1aXAQlQABAABJREFU1DaN4847o7/pqNS0FRa+HRI1sNc74Lgbo+KB7f9OBaUw4wyYedbwjFO7ptJpMP4QqP43bLof5v93/vLiyVHB/HQnj6tdhRkMkMKgkEQYhbVPLZ+atyx3Oh7E2dqwNS9coqyw47XKssKyvMKXNc01QPTY+rrXRYX0uxLGG/OmuwuvCAgy++kp8CJ3XiyIUZ/oR3gFRI8N256Kiou2SdZmQ+rbm3gEVD4BpKP3Gh95O7zpFijfK1q+od0TVNBF+awunis4/fE+B1icdRYsXpz9jMi3vw2vvQYXXxy9V/2lL0UfpXjjG6Pl++0Xvae9dm12G5WV8KlPddx2ojQ/jKJ9eEUsiDG+eDw7mnaQClNUVFX0aew7bfLRPfcZOxdOvb/D64vBcvvtsHp19Dfu6j3r7t7L7srRR0evdwAuvzz6fEJ3wi5epkiSeqcp2cTUK6PXTf/vzP/HJcdcMrwD0sDpz7WPvmr7HGyrP7/8Z9ZUrwFgS/0Wbv73zbx//vsHbn81y6NrB1UvQPUrkKgFwijgcuwBsMehUejXuLk7VbH93uX38tY/vBWAJRcv4cDJBw7M+NU7qWZYe1t0zlH5ZBS2RwgEZK5Rle0Fk46JPoO553nQSTihdtLa26CgCE79J0w5jujv304Qj4JpJx/Vr12ccw48+2x0jldbG123e/BBKC3Nvs7/8IejrxUA3PnqnXnn0F35+TM/58wzf8C110bnFo89Biee2MP5SRBE1yTX3g4b7oHGzVAyJf/zReWzYfy8LjfRK5OPg8IJkKiKpv/1Pjjr+ejzTG0BFrnn7cB1/76tx802JBr4179XU1OzNxD9LXNzfiVJ0uhmeIUkSZIkSZK0GwnD6MOwr7wSFW+qqIDm5ujNv/Jy2H//qA7RoYdGifbaPdXWwquvwqZN0NISvSE+dmz0/2PWrM6/VCRJkiRJkjQcLr3v0kz79y/9nvMOPI/zDzp/GEc0uBZtWMQfX/4jEBU7OH6v47lj6R2srVnLdYuu4/PHfH7oBxWGUPVSVCyiegnUrYRUIxBCvDQqWD5uHuzxxuhLE/0s1PqXpX/hukXXZaY/+rePctSso5gzYU7/xl3R92CJz3MXIQcwf35hprhOt4Xbq4eg+NDs2VHYRW4IR/twifbBEpP2gMa/wF++GxXpnXYaTD8VDrwsOl5BDJp3wI5nYdszsOwncNbi6Hh2JTdQQxpg998P554bXa9+73vhv/8bDjggWtZWHKTtvrh9e/TlsZ0RhiEX33Mxj619DIAr/nUFX3nTV3Zuo/100klw9tm96Fj7GjzfOsb534S9PxC1Oyuw1fYls5KpHZd14/77ozCNc86Bqb1ZddM/Yf2dUfvI66Lgim4KftXVZ7+pNn58L4IrAJo2AekobKcrOQXJH32skDvvPAOIAjgKCnreT3+KmkiSRpBYcVQ/IN3c+fKBKF626sboy+NBHE78C0x4feu+84OaCGIGV0gjTH1LPb9c/EtOnHMih888fLiHI0mSpN3FzgST90WsCEjAqhvgoC9B+T7Z68OdGF9Wwxmn1HDfg+NJpeCBB6KC3D//efR2YCwWfcb8rW+Nvntw+OGw776walUUGPzZz0ZvSbUvTJZMwpNPwt139zG8omQaEIsKQnamubLTYvVXPH1Nj5tOh2lufvlmPjD/AzD7XfDqz6LCbM99Ec58BtIpiHVzcXjqiVFAfJvXfhm9Tzr3s9F2XvoOAAXxFP/xxru49Zn3ce+9AS0t2fDkUWXx56Ii8+V7wbE3RkEBXVWfC7yorkEw861QszQKM6j6N4w7MPt4Vj4bzl4GWx6FJ9olkpfOGNRh5QZNTCuflrcsdzoWxNjRGIUOtOkyvCLsGF4BcPLJ0eNtMtlhNQCCovzwitLCzt8wLS4oJgiCzH5yb0NvwisaEg2dD6Ans86Bl77V+/7TT4XKx7PT256Cuw6MipY2bYGqF/P7N26AdKLje5FdPFdQt7LP4RVvf3sUWJHr97+PfjoTBNF73G0FS7uTKNlAQayAZGsIUvvwCoBJZZPY0bQDgLU1azssH1RjXwcFY6Pngq4UlA1ZcEVBATQ2wiWXwF/+0nmfZBLuuKPvwVHHHBMduzCEG2+Eyy6DAw+M9tleKgW//jV88pN9vQXqj5qa6LuOK1ZErz3DEIqLowCTAw6IvgdrcVxp9PnsPZ/NtC+971KOnHkkx88+fhhHpAHTn2sfxcVw220wo/V1fE+fg508OfM52811m/nkndGTcltY26fv/jSn7H0KM8buxHlBGMK6v8C/vxd9nrZ8H5h2Ckw7NSosTwAt26PzlFW/gznv3qknpIrqCt532/sy0+f+8VwW/+diyou6DkdIh2lef+3reXnryzzxsSc4Zs9j+r3/3d6aP8Piz0efSZx6Mhz0X62BJPMgXhSFltathG1PwuZHYPb53X+ueleXaoYdz0Xn6zVLoXEjpFuicMHCcVGQy7gDYY/DoKSP1zUBDl4QnQN29zmb7q7f9eCcc+Ab38hOL1oU1dG46KLoM8j/939RYGFbQOG9r93b+YbaeXzt43z1/OhaajodnROeckr366RSEJ9yIlTcBmEzvPgNOPqX3a/UH7EC2Ou86PEqTEaPXw+dCcf+FiYdFV3XXHt73iqLtnRxbbadu5c8CHwUgDFjrEUiSdKuxPAKSZIkSZIkaTewbRtcfTVcfz3s2AGnngpnnBG92Tl2bPSmZl1d9AG+a6+FP/5xuEesoZRKwT33wB/+AP/4R1SI6fjjYeLEKNSkpSX6stGyZVBdDS++GH0OSJIkSZIkaTj94aU/ZMIM2r7E/eG/fJg3TH8D+0/cf5hHN/DS6TTn/zkbzLHXuL1IpBOZ6S/940ucN+88Zo8fmi+Dk6iDV6+GV6+F5q0w/c1R0YiJh0PRBKIvZVVB00bY/CDMfme/C7Wuq1nHhX+5EMge67qWOt5z63t47KOPUdBNoZ0uVfY9WOIpjiFJIe94R/SFkh4Lmg9V8aHZs7sPu8gNlghDWHQxLL8OyvaEtyyGiYdFhRyCePYYjQUmHgr7fxKSdbv3F6w0JBKp6PGsMJ5fUGT5cjj//CiI+xvfiApbpdPZ5e3vh3vsQRROkxvoArBxI1RVRe0JE7Jfcm2T82XWnz39M65/9vrMogX/XMC8yfN4+4Fv79+N2wlveENUWKOzYhh51t4OYQIKxkRFyDp7vM0JcaClKpo3Zt9eF2ZpaK1FM2ZMx+JjndrxQvS4EiuKCsx0JmdMe1TXAu+Nbs5aSCR6EWBROD76najqevs5BcmXPPgJ4HSCIODUUw2mkKTdwph9oy9cN26Cmldh7H75RRQHonjZqz+Lfs9+Z3Q+1Jn2z8N9eA6WRqWdfE0+FOpb6nnzjW/mqfVPAbD4Pxdz2AxDGSVJknYHYRhyx9I72KN0D07Zu4fKYYOhP8Hk/Xm9vNc7Yd3vo/eAnvwInPpPSJMfYJHOr6b9wXdt554Hxmemf/EL+Oc/o8LPtbVREeeamqhoWxBExdy+9KXomvHNN0fBDL/+dbZId2Eh/OtfUeDF3Ll9Gz57ngsb7obti6DqZRg/L//ad/HkKESh3Xn9i1X/n72zjpOq/P74+05uN2zCAksuHdLdYICF2IWKiV0Y2IWK3QqCCgaKAtJd0t21AbvLdk/e+/vjzOzsbC/G1+/3tx9fIzszz9z73CfPc87nnHO2TpffkLRBkle0uksSuYMEQ18zBgYtBAwSBF2tIuJ44wFiO3OWCxafuV5eFXBx14XM3XwNWVnw4oti56gueFu5mPV/CsW2Yjp81IG0wjT+mPQHnaM6/7kLpi6Q4HUtJ0ubVDQQuPUe0KD7aMDfg+iRcOh1+XvbnTB8rff3/k1ljfiH4dBkfTDpTQSYAry+a+TfyFNOdZBvzff6vqrgs/4mf68EF+WTVwwfLoEzq62L4kkqoaBUmYgCwKw3o1N0qJpa6bvaklcoKBTbiquvRE0I7QJBiVBwCKjDYtd4CCiviG7XDWcJpK+oury9AFJ+giaXV05g8RehSxdP0qa6rtc33QTvvVd7OaffGa/3VSWvaOzfmOM5xwHIKM5A0zSUfypSv6KDuEsgaZ53n3gKQMA/x9NyyxkLFsAjj8AbbwiHwL2/qiosXQpvv13/5BWNGgk/4Zdf5D7XXSeyUFCQt+3a6YQNG2DmzIbkFX8ndu8WX9j580UWHTwYmjcXX1i9Xnxhly4V0XrdOqFc/SXQVJHzFL0kSf8L5lp+PuzbJ2vIyZPi3+twyHMEB8tztWgBnTq5eC8N+FvgdEpg6v37xY/61CkZWw6HnGUiIqQfEhKgb1+Ij/9P1/h/G7N2z+LzXcLPcicbuOz7y9h35z4a+zf+D9fuL0ZNdrN/gc2s3ig6Kef0opNQfFr4pZpT5DBzIzkPBrSA/Tsgv9yZ/c/qPsrzYMtB0zTuWHgHedY8AC5uczG/HvmVAmsBt/12G79d/dv5yU2aBjsfhCMzwLeJ6ApiL5TvnLZyOgoVFNdZ+U/YSG1OG5fNu8zr7HAk+wh3LrqTWeNnVfkMmqYxZckUDmQeAGDIrCFsu20bHRp3qP/z1gKnUx7DbpdH9fWVPfl/JnlU8k+wcaIkXhgwXwL8V0yQpzNAUGsIaA7Nb/jP1fVvQGGhyL379skeeeyY6AA1TeSV6GhJ7JCQACP7HKMdr6NL/k70YzFjJNlHeE9Jeue0SOK7vH1wZiEMWnB+lWo5uWYeLPwpPVTHjpIE7ehRz2fnzlWffPdY9rGyv1uHtebdMe+WvZ++aTqrTq9C1VSO5xwnMFCjVy+FLVvghx9g1SoYMKB6PqxeD8ReJMlTAE58Ds2vg4h+fypBR5Vodh2c/MrzvuAQLO0lyXkchZ62BWwapBRlAJLQclybcdzU5aay72/85UbyLHnoFT1nnHvKPj98GHr0qAP/143du71J0v/Ne2QD/lY4HHDmDGRmyt86Hfj5SVLD4ODaf9+ABjSgAQ04PzQkr2hAAxrQgAY0oBpoGiQlwenTEkOgtFSUZz4+8vL3F7JUfeMF1Bv/CceN0gywZIgiSLWIcU3vIy9jMPjHn3dAiQY0oAENaEADGtCABjSgAf88Tp+WJBUpKXDrrTB9uhACbDYxyOj1cgZyB3uqNQBSA/7jcKpCSNf/BQbnjAxxCNq5E8aPh2XLxKGo7F5OIY+4SbyFhQ2JKxrQgAY0oAENaEADGtCABjTgH4emQUkK5OyEgoMSMN5pAdUqhHi9r7wCEoT0HdDirycpN6AB/zJsSdnCzQtuBsRx7Y5ud/DB9g8othczZs4Ytt22jRDfkP9sJf9ivLj+RZLzk8ve78nYw96MvWXvbU4bE3+cyKZbN/39lbFmw6pRkLtLnCV6fwXmMFBt4rjj5hRomjiut5p83reyOWyM+HpEmUPWJa0vYd+5fRzLOcYfZ/7g1gW3MuvSWVX/2GkFW46smU4LoAn3QecDIX71TixhRILr22x1dLiqS/Ah8HbC+7udKpLmwrGPpJ+GLpc9A7wdrCoG1vVvDo37/n11+qfwv+YE+j+EOXvncP3P1wPwx6Q/6Bnbs+y7Dz6QaRof73EKqy6oE4CSkiykrnomp8HHB44cYZn9MFOWiANYiDmEYnsxdtXO1T9dzZZJW+gU2al+160BO9N28vSqp7mkzSXc0aPqiBbnztXRbuMsBXRg8PMOyO1GhSQOXhixqU6Oe82byxK2fXsd10C9WXhnqh1UZ2X5tEKd/IHh7cNZfWgw771nZHJdto7GgyBtGaSvhJIz4BvtzWurEJDc11gKKGia8AEDAipfsgENaEAD6gtN8wRKMhj+hxzz/+XIy5Pgl9u2ia3b6fRwH0D6wWKB+LgJfDDsfkxKgQS461khwls1gS4lIV8dYS/wXEtTK3Osq9uH67gH/89C06AkGaw5Hs46ioezbo4A39iGSfXfiOQ/J5P/E+ewYlsxY78dW5a4AmDQzEGsvWmtdwKLhnNkAxrQgH8S9gI4tw6yt0L2NldQJFeARHcWSUcJGAMgajiEXQChXaGaoLQNaEADGtCAqmFxWLj9t9uZvXc2AC8PfZnH+z/+zwV/dqM+icnPF4mPQMrX8nfmRljeTwIt+kaJTU9n8pxpXbjsojxCQyWYrhvHj8Mrr1R9i5tugqee8oj/s2bBjh1wyy0QFia89B9+EN/seiN+Iuy4H5zFcOg16PO19/f+TeHiI3BuPWwW21uxCntyTgOgV/Tc1/M+Xhz2YtlPLvn2ElaeXgnA6tOr5cOg1rK3ZqwRu2bGKljWC9o9ChG9oegU7JvmfW+9LyTcBsc+kACdNWB05yX4+qiUWnS88goMGwb9+1dOruzm7P9ZZJVkMWrOKE7nnQag6yddWX3jagY1G3R+F9Q0zzPqzVQKOl+d3iMLaP8VhJazqzScpxpwvmg8UOzaxachcwPsehS6TZfkMrr/vANUuG94pX3EpDcRaAqk0FaIhlYp6YOvwbfSdfyMfmV/6xW9V/KKiy+W2BbF1eSOUIyeZDqKomDWV+30Y9abUah6sTEbKv+mYkKLEntJpTJ1gqJAwq2w6xFqTV6h85EkxM1vgFNfV5MsodINJBFR0wneH/8V+l/3HRR4+GG4++66/6ZbNwlEv29fzQkvrOZUHOWSJVWVvCIqIKossLfNaSPXkkuYb1h9HuHPIf5qOP1NNV8qEDv2H6tKly4eu8D06aLCe+EFCTybmyscg2nTpO3PB48+Cj/+KH/v2SNBV3/+We4L4n/55ZcyFjr89XGhG4DMl2eekcRfzZrBhx/ChRdK8FunU/pA04Q78qf8YDVNEqWlL4fMzRK4N6AFGANF3tOcYr+wZMordiw06geN+otMXYfLf/+9jMlt22DoUEnAMWCABFb19RU5uqBAxto330CvXn/ief6b8Tfr4ouK4NlnZe6GhEiSmmHDYPJkCXZrMgmHpLAQNm+GrVvh0kvr/xjZ2bB8ufx+82YZn0FBMlYVRcZvSYns56NGSX/36iWJc/6/YVPKJm777TZA5J7rOl7HrL2zOFd8jnFzx7H2xrWYDKbzu/i/zbZzPnazv8BmZrHIeLNYwGqVNbR8zLR6nz+dFjj4OpycKckqYi+GyMGyLhoCQG8S/bUtF7K2QMZq6PWZ2H2rw1+h+wAeXf4oC45IcHyT3oSP3gez3ozVaWXRsUXcv+R+3hnzTv0vfOJzSVxhCIBhKyRhgRv6Ksbnn7SR3r7zGXak7QBgUPwgTuaeJKUghdl7Z9OxcUce6fdIpZ8+t/Y53t/6ftl7i8PC0FlD+WPSHzQPbV6pfF3hdEpiqN9/l/WspATi4iQ2hZ+fZz3LyhJ+Y48eEsdi0CApl5Qk085ikZfT6Rl/wcEit/2n4hSoqnDAnU6pg8EAOIph0zVSoNNzEDdO/q6KVw3/U4k7MzPh/vtFf9ehA1xzDUyZAq1aiayi10t7FRXBH39A+t51JCaNRdHs0OVVaH2vnMtVu/BWFZ1Hl9R0wl9/Zv8LeLBuKAo88ADceWcdbmsrZl3yOgCMOiOjW45mVMtRZd8fzznOylOic0wrSuNo9lHuuKMNmzfL99dcI/JBbKy3TtDNdfr8c5g0qRm0uBFOzZZz8Oox0H0GtLxN2heEk/RnETlYxm7RaSTTsfshT1UquqkULE4bAKqmcm3Ha7mkzSVl3w9tPpQFhxfg1JysyvyW/v1nsHmzwttvw80316NO/fvXXYH8D/JKGvCfR34+/PQTLF4s3PXoaDmbBwfLfmS3i2x9+rSsZytWNMTBaUADGtCAvwP/eSvM34APP/yQN954g7S0NNq3b8+MGTMYMGBAteXXrl3Lgw8+yIEDB4iJieHRRx9lcgWPp59++omnn36aEydOkJCQwEsvvcSlFTRMtd1X0zSee+45Pv30U3Jzc+nVqxcffPAB7du3/2sboAENaEADGnDeKCqCjz6ChQtF59y7N3TuLM7PoaGiiLVYpNzu3fDdd/Dmm3/+sLL97HZO5p7kkjaXeBvxz1cpaTbLiau8wrwmRXoQYPldSFWOYghuL4QgcyOXElgnChtbPpSehfZPukhGHtiddnan76ZVeCtCfELqV98GNKABDWhAAxrQgAY0oAF/DqoTbNkSiE21iUFSMYhRXGfm+usbk5KiMGYMfPKJ52emctyI8skJypC7R5w58g9AaboQ74zBYjhWdGI4Vm2SAM/gB+E9IMz1qoJI3YA/D03T+O3ob4ybK8SHZwc9y2P9HsPXeP7tPXSo2GivugrmzhVDd3lUdIwJDETGXOZ6yNoE+YfBnidnSEOga3woUsZZIskR/ZpCSAd5hfWodKZsQAMa0ID/VqgqnDkjBGObTYgOTqfssSaTkDmbNhWiVgMa0IAGNKABDWiAG04nHD0Khw/LeSw7W2QHd1JJtzOIqkLbhHxGxrxAVOlsdAFNoOmVENEPghPl7K2YRA+gWiVgQt5+SUTfkLiiAX8VanLigsr2538ooMS5onMMnDkQu4uIr6HxwfYPyr4/nnucXl/04sg9R/72uvxTcKpO3tj0Rtl7xfUfiPOe0xUwZHPqZpLzk2ka/Df3w54nJXFFUBsYOB/cwQ105ZSOFRMgFAeBLdb7OjWNJ4DoaMYuv57D2YfLPpp/eL5Xka/3fk2P2B7c2/NecXw7NUf0mqVpEsQ8JBFM4S7+g+LhPxQchNlDwRIMga2hUV84lVljYomxzxn4epHGrFkKU6eK7qxWJ77agg/BX+aEVyfkHxD9sU+k9F9F/K8G1v0POYE2oGZYHBamLJnCpzs+Lfus1+e9+GDsB9zZ404URcFqlc//iSQDS1LXMHb5TWiugCkGvQF/xZ88Sx6ljlJ6fNqDPZP30K5Ruz91H6fq5M3Nb/LYiscAWHx8MatPr+ajCz8i1DfUq+xPP0lQhmbNagm6ENpV5EJLpjgAh3X3dp6skMTBC0Un6zS/n3gCfvtNeHPffgsTJtRSp6jh4pCoOeDou9DmvqoTa5TDM5c9z4oXRnD4MHz8sTgG1rTOOlrcjeHga2Kn2P0Y9J3jCegJlQLSDOuwEl9TCaU2X15+WeHFF2tOhgKeQDJJSbB3r8jyyckezqD7djqdOOVGuGLJHD8ujrYNSeP/87Db4dgxeZ04If2kaXLmcvedokhAiA4dxPk2IqIhVnoDKqO0FBYtgk2bZDyBxznfvSbYbBLUJDVVxlH79hIcqX//BlvBX4WcHHEe/+YbCe5z991w113QuHHlsk4nnDjhj6H4Xjj8igQ6a3I5RI/07ElVBLoE5CxRV4R2lf00faXwKComr6huH67jHvw/hcLjEuQjY50EKQjpKDwCU6js2WgS+MSWAyWp0HFaA7/gX4ozBWe48ecbOZB5gNdGvMZ1na5DV3Hs1xcGDfI2QFEK5B+RILrmMFfgdneSTCc4Cj0+DyGdILSLBDQE9mXsY2faTsa3HU+wT3CVtzlXdI5hXw9jf+Z+ALpFdmNnxk6KbEX0/7I/313+HePajms4RzagAf/L+LcFL7MXwZ4n4NjHENYV2j4Mre8BnyoEHBC9p7nRvyJIbwMa0IAG/LchrTCNcXPHse3strLPnlz1JHsz9vLluC//FB/7X4nAVtDsWkj6TmTpnB3wW0uIGy/fFZ2A5B+9fmI2a7zwAtxzT91uER4uAe3eeMPDedi/Hx58sHLZ2nSxlWAMgBY3wfGPJWhbSCdo97B34kj/phDs0dkvKQaby4bs1JwMaT7EKxj80BZDWZO0Bqfm5Ej2EY5lH6NVeCvo+Dykl0vknrcPNl9fc/3aPy51qyV5RVhQKS8/l88Dj4XicMBFF8HTT4t+Q6cT/YXBIOLI/fdDx46uH+7e7a1grkleiY6G6GhO5Z5i+NfDOZl3suwrDY2hs4Yy94q5XNn+ypqfqSooCoT3Fr+BpLnQZor391XpPbKAhwF7PaLUnc956t8m1zWg3tA0CSx36pToVa1W0bEqioeLHRoKCQlGQrq/B2svlB8eflPGZK8vPGvAXxHA8TwRGRBZ5ecRfhEU2goBsLmCPYIE1NVXwe3yN/qX/a1TdF7JK3x94eqrYeZMTzJlNwwG6NqrhP3lflsx6YQb1X2uV/QYqjhjlC+voVFsryZ7Rl3Q7Fqx59XUV6HdhYPi3xQSH4eTX9V+XcUga3HWFthxH/R437NXVKP/TcqKZ+VSsf0lJ0sMkcaNpS11OtnTHA7IyJB/O3eGrl0l0HhQkARPrA4VbYN33ik67Oqg04ESklz23qw3e+1dbkT4RqDX6cuSXJwtPPvPJq+IGgGGIHAUVPGlClEj/7GqPPus7KdufP+9vNyJAGpKFFIXXHCBJEpYulT6//Rp6f/OnWVr2bNHtps/BU2D0jNQeEz05rZc8cNzyxWKXgaHMVj0oIEtwSfqv9uAqTqEa5azAwoOC7fBFOziFLjKKICjmI9/GsSL02/E31/schERMk9BuFoVfR3PC4UnRN7L2iwyZ5dXIaSGGHBOm/Bya+E8uKGqErD3668lOcHx4xKs2G6XdaJiV/bt6+3r+3dCVeHgQVkDjxyB9HQPJ0dVPfbz4mJZ87p3F2pbmzbedVRVT4xho/E85H03/kJdvKZ510lRZC0fNEj6YNIkeP99T/uXH0tBQRAZKfGlrrsOlJS6y5olpQpPfZXAO18F0amTJNCZNk2uWRVKS6Ut/5Kx/F+I5PxkBs0cVLanOTUns/bOKvt+S+oWhnw9hI23bCz7LC9PePduzo6qehLZuHkfOh209UvmsifaoLOd/3jSNI0Fhxew4tQK7r7g7j/NE/unsGMH/PKL/Gu3C5ehZUvZH81m+cxikfY7dUqGcffuElutX79atpjSdFg9EvIOSGD1Cz4W/bTm9OangXRKRO/Kn/9N2J22m+mbp5e9tzltfH/we68y7259l+s7X0+PmB71u3jmBln3QzpI4suqUJ4nnXz8vM8lD219gVkHPPNgbdJar+8fXfEo8SHxTGjvSdZ2y4Jb+Gq3yMt+Rj96xfZi9enVZJZk0vWTrqy5cQ1dorvUuy4HD8rZY98+uPde2cual8uDUZ6aB6LXyMiQ+BUffSTyU/fuwpWJjJQx6OMjfK30dOHTtKmCuvxXw+mUhEJr18ozORyydDdqJHNCr5czaHExlGRm8clY15kttCtUTPj3FyZM+MfhTiSh2kFzbZKKEXQmTifr6dtXzuWPPSaJw6qSVUwmSVI7coSKrvAiFEcpdJgKbe73FHTP+b8yycexj6Djs94cnL+AB1seN98Mzz0nY7imc8TapLVl+5ZdtdMztqfX9z1je5bxjnWKjiXHl3Dv9W149105P2RkiDw1bZroTd0yQEoK3Hab+JRNmgR0eFr8IEBidGy9Hc4ugpixwptIW1qv56sSik5k3w0Tai26pFSPQQGH65xS8bl7xfbil8O/AJJQ99p7TrJhQwL79smacNttf0JGbMB/HzRN1hrVVmG9kTWnvufZFSsk8UthIbz8suxHfn4iAzqdnjn7p5MaNqABDWhAA2rF/9wyO2/ePO6//34+/PBD+vXrxyeffMKYMWM4ePAgTaswJJ46dYqxY8dy2223MWfOHDZu3Mhdd91Fo0aNuPzyywHYvHkzV111FS+88AKXXnopP//8MxMmTGDDhg30cqWrrct9X3/9dd566y1mzpxJ69atefHFFxkxYgRHjhwhMDDwn2ukBjSgAQ34fwarVZSm6ekeAzF4iFBuw0lmpigS8vPh9deF+ANSvqKRR1VhzJgKn6t2UW5Ys+XwpDo8DkiKXpSuxiAwNwaDpCBen7SeJ1Y+wcYUj8J8+ojp3NHjDgJMf8Lj2mr1trjWhM7AfYCfLwz4UbK9a5rr8OcKSFucApZzoDsrAWlzdpYpaopsRXy+83MeWPpA2SUf6P0AD/R+gCbBTco+O3kS1q+Xfx0OafPAQO9ADpomRharVb5r3FiUlxdcIIH+GtAANzIyREF89KgQkXQ6GSNms0dhpWkyloqKZDwFBzloE3earm3OEOabLk5Lil4U/2WacR3gBFOIBNf1ayKE//9mQ359kJZWmS1Rh2AxlT77b8P/1+duQAMacN7Q6XQkJiaW/d2A/138q/u6OAlOzoLs7ULS828GAc3ANwb0vnL+UB3i0F96lvz0sahqJJGRdZRrCk/AlpslOUGbB8Sw6xvlXaYoSRJmuA3HmlOMxyEdxbhryZDvwXUAUyk7Y4DIXL5x4BcNphCsVuFyWSxyZnAnUDAY5Nzg7y/OLcZ/hq/yr8SW1C08vOxhrzPkc2uf44OtH/Di0Be5rdtt9R6rmibEO6cTerrsxbWS3jI3w5aboPg0dH4Fen4k59yyizpd5IIcsKTL+PBvDsFthVyaugAsWXLu1BldlsFybBXVLoEE/eNFLvdvDlUQryvhXxpMswEN+J9Gfecd/NfPPacTFi+W4HwZGZCYKMHMWrYU4lpgoOgmbDbRSRw6JAH97rvvnyOS/zfiXy13NaAB/6NomHf1g6ZJcMsTJ+DsWSgoqGzfUBT51+GAqChxMIqLk23vv9WxZP9+IWonJXkcOkJCvB00NU1I5CUl4rgUFiZ7Yny8fFZY6AkIqmme65jNEBMjtqDw8PMnozpUB1tStoACveN6V+lA+29Cfj689hp88IE4M95zD9x4Y/Xq5tJiO4ZF7TDkZ6C0nQLd3pIzk1KODV6R3A3i3PdvJsA3oHpomuh9Co9B6Vk5UytKOQfNcguO6gDfSPCLA99Ycbb+q+fAvzRAn6ZpXDrv0rLEFdXhaPZR3v3jXe7rdd9fcs+9GXuxOqx0j+leOYiA0wrn1kH+frBkg04RorXe1zVfFcDl/OEolj40hYljcUgnCIivtQ6z986myFZU9v66TteRECqBGUsdpUzfNB2n5kSHjmlrpvHluC/r/6D1Ce5xLlX+dTsRV0RVjjo/AfMrF60JG5+9mZXKylrLPbb8MW5q1JjA7beLM3efr6HpZfKlavds2MXJopuypItetVUFhxifnZUvXi6xxOtfwM+tpFluvRVmz5Yi1ekt3Q69/yqE9XAFuE+XPSOkU90C3NfXqachWEy9UWov5adDPzHl9ymUOkp5auBT3NL1FqIComr/cU0oOQs526DoNDiKZD4YfBGdvauMBqilMmjN4bKvBLSAoDaomg6bTfQibt6VXi9yocl0/mN8fdJ6xs8dT44lB4Bw33AKbYXYnDbuXnw37/3xHqtvWs2VV0bxyScin/78M1x8cS1OJk2byl5UfvwdOlRjYhqA3EAjF37XpcyBDMSZqjzsqp0+X/Th3CPnMOnPT9mzPmk9N/x8A6fzTwPgZ/CjxFHCvAPzWHxsMc8OfpYpF0yhbdtEli0Dh0PHVVeJTio8vOpnV1XQxV4MsRfD2cWw+QYYuUW4am75oEISBy+YQupU9z594IorpB/uvFPqM2qUjIuK9bLbwRjUBto/AftfhL3PQEQfCO8JKLImVxEsZkDbDYzqtITl+0dxzz0KeXnw5JMy/tw8v7LrG2HNxkCGd3wWdj4Ap78RB6cLPnSta+XukbEWttxATGgar1z1BPfPnsH06RL0fMyY6tdrux2++w5eeEF4bY88ApddJmeeqs56DoeOefMSMRqhdWvdeTlEqZrKypMruWvxXSTnJdM8tDnvj32foc2H/vmA0P9mqHbhXjqKRWbSXAuOopczkN4s41hfdVClqrB9O7z0EqxeLU5s48eLc3VVZzCrVZyj4+MbHNn+LVBV4ZuePCkiREGBR69QPvmjW+cQEyO6mLg4+fuvpvz9/rs4LJeUSECT11+XseLWB7mdIRXF48Rd0WG/Tsg7IEFyik97LmAMdMnc5TZuR7HMm1wNCs1yNgxKBL2pToEM/5sxYoTEbrziCpg3r+p9yA29XhIJYZkCSbMkqMa68dDtbWh5u6ejfGMkaKcbucCeQ1A+7n1NNjDjjaBbKPbwXQ9D93fk3F7bPlzHPfh/Bsc+gu33SWKQAfMhvIdweFWHa73Xuc5s50QvYgz24qz/T0B1yH5nq8bfQDHInPeJFM7+vxC5pbm8tuE1Xtv0WtlnN/5yI6+uf5U3R73JmFZjzk8mL1gCmW/D8Yeg6+vQ+j7XuaUGlFtot5/dztOrnmbJiSXy3QJ4asBTTOk9hQi/iLKf5JTkEPNWTFkSUICdGR5dQKmjlPHzxvPNZd9wTXD/erRMAxrQgP8a/Bv13ltugpT5klx3xAZvOcKNiomCKwT6sVrFLufmXqqqt/4mKOg8dDg1+Vn8j8qaDWhAA/63MWvPLCb9OqksyFioTyhWh5USRwlzD8xl0bFFrLxhJRfEXlD/i/+LuJSVOEFd35CgZrYcj63y9Dc1XuOOO+Cdd0Qv43RWXaa8fvSZZ+DHHyWwc3XlwaPTqRc6PS9675IU2PUI5B8SvXNgyyqLzy8Cg6IvC6jWr2k/r+8HNB1Qdh7QKTp+Pvwzj/Z7VPbVNlPgyHuI30MN0PnIWd83WhJOHZ5R/W8C28LQpdzrE8q8n0VnWVQkAQE//1xsHoGBEqju229FxxwWlsiImAPo+vWrHKG+Ojz7LPOuaMfEnyZW+bWKyoQfJ3Dx3ov59epf63bN8uj5CSzuBNlbYd+z0OkFj8xSk/3h78RfJNdZHBYKLAU0DqgmcVh94bRC/gHR75VmSKBBXUWbkuLSgbv0Un5NXK+4/xe+zNnZMv5//FF4dn36eBJLBwSI/OoOPJ2XJ13dqRMQMhbir4akeYAqetTFnSCojdjECo/9I/XX6XS0aN2C347+VmZXjAmMqbJsVEAUp/JOATIP3agugUTFhAXlk1cA3HCDtF1FOBxwQZ9SZu/yfGauJiGs2VD159XZPr2SV2h/MnmFb6QkITr4OtWumx2min0PIKiV9HnyvOoTBQW2hcG/wR+TJLjw0Q/k3NTpRUlsojllnrmSnFjtJu744mO+3tCeESPgrbckCbXnGb0Dt7tR3pb42GMwdWrdEyTcdJPYFJKTq94nVRVU/7PgWvJDfUOrvE6EXwRKuSC6ZwrO0KFxh7pV4q+A3gTxE+DkTI8dDwAFwrqDX9Xz4K9CeRln1CgdN9wg6sXy8kVpaYUq/wnu7vvvQ5cuctZ232PPHnn9qXuUnIFDb8KpWRLYu9l10HiQcJgqzkPVLnwP/7g6J0z41yLpe7GfqDbo+Jwkrq7BRnL6Z9DpNCIilL9P1bD+cklY1vx66P1V1ZO6Fn1MTTh1SoKrgvANYlxTpDqO2T/lb/TRR/D88+KrO3WqJNeJrDoHEyC85+3bhSOXni46prAw2cP9/Lz37cJCKRNYlEZQcRrhEdC9GyQkgJJew/koLa1eWWc0YLPam4WvB5NaIPJ0WJg8h7+/p43tdglIvnq1iIAAr75aOx/AaKTesubjvMN7dKVNG2kvqHl98K3C/OFUnWxM2civR35lePPhDGsxDKO+ZmdqTdNIyk/CrDcTHfif0csdOQLr1smYB9k/g4Iq+xuUlkpz+vtrfKhdVHY2rw6bUjbx/f4fsO66kunTITdXePfDhglvx51wpTyKiiB1k3eM8/pA0zSWn1zO/Uvu51DWIQA+2PYB13S4hmmDp0niw/NBXexmFXhs9dEZaBpcdRX88AOMHg2ffSa8CRD/xoq8BXff1IvPkLZU1kzw8LIUxbuxS9M8L1uefBbUGsLPQ89SR2iaxpSlU2ovCEz5fQobbtmAkp5ed713UZDIk4XHXEmXQr1191XxpF8H2n8FoZ3kfR14i8dNRbz106Ban+GmX25iVMIogn2CmfL7lLLEFQAl9hJWn15d9j7fmk/XT7uS8VCG57zrKJH+sZzz6Ik01ZP4TZEkTZeNG8Kxkz7cfrvCO+9UrkfFcbN6NYwbJ+eS+fMlCZg7GZx7vIGMufKxI/5OHDwonJJDhyQhw3ffyb5VkeMDrsRYSgz82hSt9CzK6TkQM9r7gn9xwoS/DZoKGWvgzELhiBtDwaeRyOqGAI9+QrWBvZD130eQliaxdqdOla9qiuOh16ngLAVUVwJ2Da9EHzUl+egwzXVvi4w3vb9L/nWvIxo6u5XEGBVs+ejQ4OCrEDUMGg2QIoryl/Bgy8NsluR4d95ZfRmdDpYcX4JBZyjbvyomcegU2cnr+8XHFjOl9xS++gp69JA5UVICjz4Kb78tMRVLSmSMWq3iXwZAQHPo/KIkfnQjdYG8/ko0uQJCu0HenhrP27/lOHFoom+J8I0gLijOq0jP2J6orqQ9OkVHXsyPDBnyGOvWSZtmZ8Pjj3snm3KvBTqdjoCARJpGlKDbuNEjPP2Fe2QD/kZomsQiSl0g51xTqKwLfnEu7rprMVHt4rtQnOry6XGCOUzmdUTPGgW3K6+U88i0aZ54sODhkP4lOA/bzrHCKNafiOHUKZnbVcVSBZnjFgtEaWnEm9KIjZWYFL6+tdyjwebegAY04F+I/znXirfeeotbb72VSZMmATBjxgyWLl3KRx99xCuvvFKp/Mcff0zTpk2ZMWMGAO3atWP79u1Mnz69LHnFjBkzGDFiBE888QQATzzxBGvXrmXGjBl89913dbqvpmnMmDGDqVOnctll4hQ7a9YsIiMj+fbbb7njjjv+1nZpQAP+P8BmEyHNahUFgTtDLngOLXq9HBZ9fOTf/wf2e4GmSZCEouNCLDIEeidUcCsANADVJeCr4uynAT7hENIVfBv9554BRDGZt1eUeWguLZBataFNU9m4PZzxtw2goMjI3HkKw4aJ0F6dgmTBAlFWgzgoug8nVRl5dDrX56dmC7FItUHHZ4Qc4hslQSYUgxyqrJnSpgVJUJqGFt6Lj5P3c9fiu6qsx8PLH+bh5Q/TJbILq25cRWh9HTfS0uDyy2Uy1AXtAR8kYGzsWPlMUUBxPXhxMixsW0lhk9FvIb1/uYfTeacrXfLtLW/z9pa3MeqMrLpxFR8+3p/vvhMjwIoVnnLlgxW5b/vfFsBJ0zTsTjsmw/9w9MF/WUCJ114TpVRCghjuQkLk8/KZ0d3Q60GnlsDyAZC7E6InQ8IbroDO5QZbxcBO1mxw2oQIU1f8G4n59U3K8M03wrSpK0KAZy6CYd1FKaT3k31FZ3Yphso5y6oO0GyAAewFQrozhUFYF9B0oGjlMogrniA+OpMowA0B4pB3nsEfasQnn0j2ovrg2WdFs/V34XwSapT3zK74mwbnkPPHv3BunzwpQRLz873XvqpkW03zkDZ9faXKzZvXbMzTNDEA5OQIUcRmk5f7OzfcvtvugPJ+fqJMDQ2Vv/9y/Iv6wmAwcOWVV/4t127Avwv/VF+XlMh2dOKEzKGYGJlHfn5yflUUT9ANux0oTuIyfTMAtIELUOIukQuVd1h0EzyMQeC08eoTh7j0zsbMmaMwYoQQUdxBfSpCVYGkH9Blrpffd69CPqjmnABA48HQ82MI7eIduK68zFVylj82FvPMB1GcyQxh8mRZn+LiJNBRcLDnTOZ0ShulpkpgqhMn5FwRHw8PPugh7v1XQtNcwQhsLlnIlcQBEJlIB4qREtXJNfOvY8GRqg3LWaVZTF40mQeXPcieyXuINrckI0PWcqtV+tqdRFDTPAFj3ev6xIlChnznHcmD2KqVlK92fBz/Al3hUSEXt3uwcqGSM7Awserx0fpe6PFu5c/dY9b9ty0PTBEQ0r5y2arwDzsVO1QHR7OPsjF5Iz8f/hkFhQntJ9A7rjctw1qi1+nRNPjjD6lacbGnPd06qvKBjt2El/IEybAw6Ny5IZnjfwKqKoFuDhyQvomLE12i+1WeLOUmjNjt0q85OSKa9OkjBuT/KjiK4fS3sl4b/OXMpjfJuUwxlhu0qpADUs/A8CfBWnOw2Eowm+GnnyoTjf8qPUPefsjdIwQ6Q4BrLS2n63IvhiBJdDRVgp2pKpoxiFRdCLsLc1hwZAEKCuPbjqdLVBdiAmNQFIW335YAdbGxMkaCg711WxXRq9e/MEjpvxANMvZ5QNPE8cdpBdXqkSW8BqTOo6vRu/U1DWiA4B+bd2nLIOVnsBdCxAVgCBI9nzFI7CjWLLDlAqo4WFmzXYEofUVODmwJ8RO99bn/MObNk+QCTiesWiVBCmuFW4+Ri7zcn/0nE+Zqquhm7fmy7zutco6ULz3lFB1ocNG1rVi0LJiLL9b49VfPJucmale07SQnw6WXiu7q4YeFXBsQIOfcqmw/hYXgX5CGLiUNUsp9UYd2Ou1j5a0tb7Hm9Br2ndvn9XWHxh0YHD+YB/s8SHxwc5Yvl3OkzSa6K3eCxPLnHffz2Gwi34UUJGPMzyIkRByjQ0qrr9PhU2beW9CUMwWB9OkjyTiCg+W5fXzkXm5ibUmJjKfPPxd93fLltSdo9DVZwJEhfRTcUT4sH1y8JnL3iE3nTYJXNZXM4kzSi9KJCYwRx9eKws6/SF8HQP5hcYyxnJMAEQZfWWd0Zo9uQqHcWdyOiomCPAcFJWZKiccW3AunKvulW93uluV0OtHVuHWh/v51c5pQVQmwWlwsjlduJ6Dy6ny37ie4eBExp65G5yyEQb9BixsrX7CiY09gy7/Vqeffii92fcGm1E1l7y9pcwn9m3iCCX65+0uOZh1FReWxFY8xrPkw2jeuo46hHDKKMnh367usObXG634gDgZDmg3h3p73kmBPhZWD5WwxaBFEDfUUdMtpJWlgSYPSc2DPk+/q4ZRVai/l8RWPo6CgodEsuBkzx8/0CmCdUZTBnH1zcKgOZu6eySPNr6OdI8T7QjWts/XlGsQBUwG2wd5nodNzroCjuuplz6HAbTOgscuJpBb+Q569kKvWTUQpkeeO8I3gnTHvlCUrOltwlgeXPYiGhtVhZdPmxxhFgegm3YkrwLN2FifDog6V1816rJkRETB3rjg1/fQT7NsnpsYxYyrrcY4flyDH995bp0v/c2gyHtpPhQMvweqx0HcORI+QpB9of01g3X9CX5e5GTLXSRJd/6YyBxWDK2lMuTGoafIsqh2WvwyZGTIm/OMhw/df4eDy65FfmbxwMmlF3nvr1FVTmbpqKkHmIO7teS/PD3m+foHrNRXWjJU9MnIYDFtRuUwF3WzyKRvPf9yfU2mNGDQImjUTvX3jxmJvdO9/Dod0b2amyDkFBbB5sywrN98sv6sJi44u4qLvLvL6LLs02+v94ezDtHu/HZtu3cT06e146CGRzV9+WQJnGY2yt7r3a1Utx/Nq2rT2viuXmMahOrhizig0l6CrU3SMaTmGAJN4OmeWZLLq1CpAgsRMXjiZLy75orKMVAM0TePLXV8y6bdJXp+XOErK/i60FfLwsofZdmYbX132FR06+LJ8uQTAaNdO+DJXXAEtWnh+73TCli2wYoXCs49+AiuGiMPsokQJytLsatH3VZEoogy+dZfTPv1U+n3dOnF4vuoqsTOMHi3TGISD98svsHEjfP7Jk5CzC84uFP5O67sg4TYIcQVS8W9aFizGjfn3X8a4WemsXBfE1KkiQ0+cCJdcIuOxqEhsRd9+K3LUzh1T5Hx54CVJ/p6+HJpeJefJgOauM6Znf7t7xAfssD7D7O/DuegiCfRz551yjimvy8vPl0Qd7nPgF1/ALbfU3D4Gg4Frr71S9tW9e72/rEVeTg9QGPPNGPZk7PFKonIk+wgjZo9Ap+joHNmZJdctobH/XxRE6z+J4mTY8QAUHoW48RDRC3yixGFWHyRyfEmqS4Y6I/YnY4AE8075CUzh0OoOCO1c7S0uv1y2pEcekaBANcFsFj5avXH6O3HCc9pEBjEGypwzBIhuzpIF9lzZZ0vOgD0HTI1EX6czyG9ixpzHjf8e7Enfw8bkjXy3/zs2pGwAoEtkF27sciN94vpwQcwF/0gi1E8+gbvvFvlq/XoYOfJvv2Wt+PJLSWo9dKisG24oSvXne69twq3TdXO0vezCirxdPRKyNkmgor6zy/3WFSzAvW8riiuYQB58swbeqCJaWXX4m3lv2dky306eFLtzs2YeXYmfn8dO6nTK0SM3V+SK0lKRrRs1EsfTmuaj3WWaMrtirNVpO/ZpBMPXyj5Zega23w37pkGzayGsq9jCsrZ4yq8C7rmuuqtVjTcmQNwCOPqh2Ku6vCbJGaD6fdjgLwnGnCWyV6kVdf0gjvqKyLBuHqUhAKoJcPevxpmFMg9COroSV2iuoAQ1c9b/jJ7rX4FTs+HIOzL/2z/pSkQaIy+dwaUbz5R5XpwkOoRGfaDxvytxglN1Mm3NNF5c/2KV3x/KPsTYb8di0pvYd+c+WjdtXS+ZnAVXgD0LWtwvwcKqQkXdWFBrfj6XymXfX1Zl8RfXv8iL618kLjCObbdvI9AUyLi547wSV1SH2369jTY3r6P7nwgmpGoqZwvPsjt9N8dzjtM9ujuJjRIJ8w2r11miAQ1owP8DaG7eYDWydgV7UKnNh0e/e539RYm0aBvM8OFyXo6KEvucOxiUO0BfTo4rBuDZNPYtS8PHBwYPhp49qfmsWl//kr/bx6IB/904Hx+Zf6PPy7/NRtqAOmPu/rnc9MtNXp/lWnK93hfaChnw1QDW3rSWXnG96n7x87GJwN+WHKkSJ8gQBYMWwgrXGaMmediVlMFgEP3rgAGV7dtyD+9q+/mJ/WyAywRYXQKL86IqmcPEvrFisJwFTn4JJ7+CxgMlEaXmEJsRYNPg12LKEle0CW9DmG+Y1+UuiL2gLJCcpmn8ePBHSV4B0OVVCfCXv7+adtJLUvhBv3gCq3d6AdJXQP7BCoG8EbtVo77g3xQ9ojcfMgSOHpU2Onasqq3WwPbtV/Lpov6iFHejlrPIepK54eeram3O347+xrQ103h20LP1O5cEt5UEFltvhwOviB6l0/OSsNqt97BmSXKRzddBBDAd6DjHYwP4lwSeU1WVnw/9xLLjy/hq91fYVQ8Pum+TvoxsMZIbOt9A89DmgMhU+fmeYGN2ezkacjn+lKJAdMbjhKW/JoGtR/4BPhEVb1/5bBvQ4m/lfZw+LfP57Fnx2QkMlOXHratz+5W4uVOlpfJ5SYnYY2JjJQhpVQGWzxcTJ4qdZ/x4scNA9b6RTZoIf6vsu16fS9LTzA2UJcLOP1D1jdyJZv5iGAwG2g1qxw1HRVFs0BmI8o+qsmxsUGwZz6M8fKtJ2Fk+eYWGVil5Rf/+okrZs8ez1ur1Yjts0aYEdslnCkq1SSrqm9SifPIKVVMpsZdUWa7O6PCU2PMsGXglsFD0ENIF4sZ5l7/gA7HDlJ6tem1u+6Dwpwb+AqtHQ/Y2SQ6YMh8a9YewbrIe50rjHEhtz6z1Yvx76SXvxBVQfayL8qaRRx6B336DbduqzjE0pUL8ZB8fsTEMGVK5rF4P195g5WuHRy4pn4i1PCL8IsqCggKcKTxTZbm/FW2mSPIKL2iQ+PjffuuKMs6HH4rP1vHjVcseev2fi1vSrJnwPceMqdp9X+ok21e9sGeqJK4I7wmDF1VdpuJeYa1n4O+sLZA0V/bm0O5gCnLZF4LEHmLNEv6a5oCSdEm27NNYON7OYuHTxF/918Z02PmAzOPEJ8TGWxEVuCs3DlOZ+eVozpwx8swzkmzBbvckkK+I6vxka4TJlSjG6uKqaA5pHzeq4+fW0WYREyP72NmzIgcOG1a9v6Yb5/Uc9ThvZ+Xquesusa9//33d5PN77hGxbdAgWLPG87nN5pGBwCNPmEzAtE/g3XrG7rj/fri+nG2gBtnx3tfi+OD7xvT4Q9bi2uo0erT4ABQVyXr84IO1t7XdDvXpChMSiMHhkFdd1x+n6uTFdS/yy5Ff2J2+u+zzNze/CUCHRh0YmTCSl4a+hI9R9uTU/FQ+2/kZq06vYkPyBq/rXdTqIoY2H8qkbpMIMAVy9KgMh/x81/1c62V532I3VFVkRXdctpAQsdnWxJUeP15idY0dC4vKLWkVY/+491dFgbc2v82ZZR7+/6VtL6V7dHdA5J9PdnzCmQLZ42758nWK35aBum6d58xZHQICoO3I80sUMa9gMxOfj6/yut/u/5Zv93+Lv9GfvXfupUVoiyrL1YjauGzlbWb1RF6eJK4A4da5E1dAzYlxlPR66LksZpGvNTsk/yC2vIpJmI99Avsrzn09jDvpOUP/xZizdw7rktaVvZ86YCq3dPWQu2bvmc20tdMA2JS6ia92f8UtC5LrHl9IB3zYBjgKq4ZB/x8keZ5qr54nHQG0bQSxNfRnuf4utZcy/rML0KFDRcXH4MMT/Z8oOzOkF6Xz1hZRHlgdVm759RZu7HQj7271+On7GHwINAUC4NSc5JTmlH13ydyL2dAmHkPGKtm/Or8CAc3A1E24S+Ad/6E4iUbBuRwjumx41LZmbtggZ8jISElcAeVi85WDovz9SSvcWLRIpn5goCcpg7sOVT+LEYYuQ1naUxImGvyhy+sSJ0O1ia/1X5gw4W/Dllvh1EyI6A8j13s+V+2Uxa0oTRMOW2kavfsohAY7KCw28MEH4gtWU3+rGNA6v4F+9wOw7zkI7y3cD9Xu7edUFZLmwKjt0qbg2qhdvPXSNChNx2DJ5MrheRCYAEcyRKZdOQxaTZYEskFtKuihDsDmciSuevBgy+P222HxYnlVPFsYDLIfLjy6sCwxRaApkJZh3ol1zQYznSI7sTNtJ6qmsjZpLaX2Ujp18uXHH4XH6N4fqxLfvGSHdo/Is52aDRX0CV74M3oPRRH/gaW9xMewYoJJRc/Z4B4czJ4jt1J09G7Su5I+sXt09zK9h6ZpLD6+iMW/PsaFFwrnb+pUSZ529dWyPoSGilyydCl8+62BkJAr2bmzlrr+iT3yX4u8A+IDYckEcyM5eylGz7oszm/yp2pz7bkmcFrEXyIgQfi2Neh39+8X/XNenmc9Li+TueFORKcooi80GKSfEhMl1km12PkQHHkbQjrDmB0evz3VDrjiOpSmCSeq9KyM15IwsEaCBfElTdldo62wSURbCgp8OXRIQVVlfta0H5VPPFonnIdtZxy/8CvduPBCWLjQ+97l47956Zem1TO24YMPwrXXen9WT5uqpmkUWgtRFIVAc2Dd711HqJpKRlEGx3KOEekfSXxIfOVkvfW0qeb5xZBOFHl5nhhJ7uQgVcW7MxqFXxwcpBEUYKVxuAW9Ui5uU9lhRLiXSak+fPy5H6lnDSQmKoSHy/khMFDmiLu/3LzWwkKNaG0JPrYjGPUWouPDiIoxYjAaXMmgys1TTQXVRl6ejv3HG5GZpUf1iULziUc1BJVdu/z5yP1sfn5yBgsMFDk+Jlp1+XxXXP8Vkb0b4kQ04D+E/6nkFTabjR07dvD4495K7ZEjR7Jp06Yqf7N582ZGVvBmGDVqFF988QV2ux2j0cjmzZt5oHy6JVcZd8KLutz31KlTpKene93LbDYzaNAgNm3aVG3yCqvVirWcQ3BBQUGV5arDlp0b6fubkAmqWH68PlNc/99m6EqH2P3oW05E3+dT17flSrqEfKxZYM1m3a/7GWB8E/J0KGP+8JTLypJXgAKBrt/b88jNziEk51nIA6XryxA1wrt8RAQE4FF22/JYtmEHrSN2E9y6H6FDpkl9tHL1smSCLVMcUe25/LHyJL3DPpTvrqlC8C6vtLZmYs/PQL/iRqlTx6c8Bq0a6jRy6/usNGTU2q7ymcK79OaeVptls5lYhZN3hTphyaLkl0n4FFtQ2j0oDoS11Ckl6Suahp2E6JEwZGmt95j9eT43PDMBqKxQrA5Zr0cQZstGaXUHtJxUa51Wrd/FkKD5ENAMZcAP3uWh0vg4cDidRP1L0hf95shhsYZ7FOUXE3TVY0DdlIwAy16+g2FNP0f1jUF36WnXpxXHuLudsliyZSNj979ctwZy4bDamlbGo9DkMpQOT1T/3K522rZvLz2b/SDGjStyKl+wQt/t3r+XfpsexR8o1ZnwNwbgr/fFpCrgVLHrNEo0K0XOEsyKngDFxqlmLvLE4N8rZ/Ysfw/X+Fv32wH661+XvhizDc4mAUnVzu38nByCsl1zu/MLnnvUMD5GbXuHI/osVJ2JiIBmxPk0JloLIMAGhZqFs+SR6swm114EmspPAWFcEHFKDMUj1lf/DK522rY7iKxcE/7+EiynNoweDU9O+IK35l/DyJG+vPSSxvDh4O9f/QEtY9MXRCo7ocll0LSCZaY4GRZ38lI6nXFA3Kna6wKwO2M3Ya+H8Z1jJBPaLIewrtIXmkrFGmnRGsSrYM1i1+GDdHnVCkWgDPgRAuLh8GGU6zyGGu2jF6B1M+kLSzJL1h1gTPfFsP4KtPZTIbQTSlVJQVzocjCQPccuqvZ7N+yqnQFfDSBw63JgeFmSATcqZqIFT7KZQc/5EUwp7UMT6d/ydvqEdsCQmy+ebUCuuZQl9t0cKDrJ9sKT3J3SiasbLQJTGMow1xpY03pztIiO98nevXcvdOxY6+PQfJqZ04qt9oIuTEm9m+2rJuJn1vPa1xfIwdYrolP50hoZyZmMukysACdPChGoNozuuo7NhzpzyaUm3v/YB3dCWnfsHTfcvo3bv/uUIY7JMldH/+E5iFQzt4uPn8T/gbdR6hGHUnGtqfffL5lea8Pbnz/JDxmvMNAJCYkPMyHuQoKMAV51Oqo/y8/ZO0gqPcOC5ZcBD+DjA76+rgfGO2mRG6oKOkeRJK4ACbhhDPAuVIXheNuJHnQP3S7tNGShOD3X0E7Y8rB+9iI+v9UxkAuQ+nYccY1TIXIIDFtVuUCFNW372hTOblqADxYG3zUZY2C45yFVFRy54ugMEnzMnk/hU+8S9Hthneu04rbRDH0B8I1FGfxLpbUDvNePcykLiPRbCKf2w7hqFrfy+0tRMmxzGXqqM8xX2I9um/cJ31llzXfqTJh0RkzoQZX2d+DEjhOb5sBPMdLd2orlUfuk7y54XxRtUON+dNA5n3YvAHEXo3R8pvrnbh4CtjzW7khlYMRz8NLLKKPLnTOqGR/Z584SoX9F3l+eWbXit8Jzn7ntSWJXJlfdplVg/aB+9A/biPJz3cqXGs2Y37K65N9nIe6iWttpwLYZbNRn13BVb4y3dmOZeScGwK4zY9aZMOuN6FTQVCdOVKw4sKp2fHVGLKqd/GYKBp0Dpcc70OZuuZA7gU5EBDQyutopC6xZXPrVU2zUJ+FEh8kUQpDBn0DMGJwqDk2lSLFQoJZiUe2YdHruDArl5lyN5OSmnGs2A4spEodiRK/aUaw2NKMOjBoKKk5rKYo1j8t3jsRvYd2VjKsnD2dQ7AoISEAZMNe7XaHS+Ni4248Hp7enY/heXnguj6g4HegBh1OCAPuawezjYoBmcfSEmXY3PAmIQ3zjOsSjmPhcV+axu87PkLj3Pg7OfwedrnrCeEXodCqapmPaNPE7qg03vj6Ur0tX17lOnawt2H34ZJ3HOMCul7rSueluaHE9Sp+v5MPyCZkCVIjQlY2n92a14dXnYmlqSmbT6rNgSwFHGhTmQGkRBPiBjz+ggFoKaCgnPkPLBaXrK5zVj+FEqpnTR2ycTXFgNQWimMGsFBIXlkWzsLMsKHgeP9MpCGjGxO5v0CagWaXxsYOTLMzaDE4LKVvH8/sXVxDFWTZuUMTpXrND2kooOAT+evAPAUMj8O+DTQ2lRd8ookjj6aeEHIymQcY2yPsD/F1aS50/+HUFUyvWL3+OAU0lmJoybFn17QRgzWL+Al/uvasV0Zxl2TKF0BAn2FMgczsUngZ/I/gHgS4AzK1QjS3otWIYnVWNlo37c3Gbu+kQ1NJrvcn3KeanM0s4WnyadflH8P36S1bvG07//mKQqg07Fi2na+4oAJRxR8TQUv45KjwDpelMf/wIQWo2g69oR+sLXIZBu91jTdUKZV+154OjgCXLUxnV/AcIboty0f5a2+n7bwqZ+KicD+py3t6+XewHIJcMD6/lB7YQsmbHEeGbipb5hyd5hc7gUUIf/RAOeJzFx/rA6nt68+iPbzBxYn/ee1fjssth1CiIjFTw9xf5vLgYTpzQOLFnAm2yFtOr5Xq0rXdC4uMoAVUTb9wosfriZy6FRv0853k3qpC5fvr2NZatGU98vJDYakN8POx8ox9Dozdz2/3XoPT9GgAtqfq5vW7BXgYY3vCcbd2oZt/Oyy5h/KM9aRdykLvvLqV9FwMYFLA7we4AH7No/jXNFWS3gHErZnJOn0mUOZz+za/jgtB2NC5RyrIjphnz2OY8yab8Q5yxZPOcFs1FTXaIAfzSs2JELE/+riAH7k3dRefFT9TeQECJvYRW77WCafJMzzxTNzvW8LYLGKr9xDO/vkDnzvFceaXGRRfCoMEKwcFCNnM4hDxy5IhG8oG7aJmxnc7KHrTdU6HNfSh1TfxWFVlW0+DYx7D/+bKPdp3uQueg3dJ37rMtVC+TnzkNDkul83JNuPXmCLZ8FU9jvZkuTS+jW3Bb4m1+6PIL0DSNc6YC9jpT2FRwlDxHIY3yQ/ndsKfa6y0+vtj7g3OJ8KE4QqSmiuNGbbj++Z7M0cqN1eU1l+9qbcku8/HaL1wOL+2fSn5GAE0v6EXiEFd/OOwe1rwOkUc0B6hOvt9zD1uMC+io6ujU9l4Gh3cnukQnXs2A1dfBVvUEGwuOcbwkBS3fyOIEIRAqg+aDe42qQa7b8f1HdIvdDM2uQun3jXd5qDy3f9vPgDCJMqVcY/dYyatZ+wvPpRGw/1Yp32+WBKGpoU75mflcc404cP3wgwSDqw2bvv2O3uq1EAnKhBwwBskeUE2dNEsmPrNvQA/YAJ2iR4cOHQp6FByoqKg4NRWjokdDY3bRhSgpRqyhvQjucSMOTYfisMtLUWS9MgjBQ7VbKExax3Xtb5fnvvS0BEGpoZ1IW4ZyxHWQr0qvDt5nF87hdDqpD5//QEJbEpMPo1xUu17JjWbTdOSiUoqCUW/GqBjQawqKpqGhuc6ETvSKaOeLE1xKjHaPQtfXqn8GAGsm36z6neuOv1Pt/T/f9bn3ByeG42tawLlzfmzbqjF8hFI2BMvrutw6Lp0O9nx8I52DvpY+GJ9CJVSoU1HqETbN+o3crFD0XR9GFxqPpujROUVeUcwmND0oqg3VYUWzlpBgvZVOsTsh4WaU3p/JtWqYR2t/3snAxjNAZ0a5urj68gDWLDJPp9L49G3yfsBPog+t7jlcZ9uJXz1EqCGDyIAWXNLleboGt6kk/65xHmRt7i6SStIJ3TuCOXMfAg32HmuEvpxjQUU9F0BJQQlxm4Q0ofT5Elrc4P0cVaw3G+bOoV+TZRAzEmXI4lqfe/PCLfT2k/1JuTLT46BQ3TyyZjGgXzMSQw5w881F9OpvAL0ig8Nm92TW1jRx8rDls3rtQYY0/x0a9UFxkwJrqNPRFT/QxvClOJBMKHQR+8rpuyqMJ0dJBs/Mux2Tw4ohohf3dHuV4PK6N5cOYOHZ5ewoOAROC53PhjCu5S8Q2gFl7O5a67R3/QE62h+Rdrpwtyf4ZHXtZMnk8ksjiNGOc+nlVoaM9gG9ztVODulkHxOYzGW6icWrUhjb/Dvwj0cZf6L2dtpxjFb54v2ljFoPEX1qHR/HfnmJlo2OQJu7RTdR3T1c5e+a+xEL7Jvw0RQCAlsQ7xtNLEEE2xQsmp0MpYBkZxYp1hzMio6mxXG862vHgJ2Ey5/FENnFNcDxsJKsmfKy5YItlz2Lv6dT9E5ocYOM81rqtPaX3Qxs9BYoBpRryukzqumLkyePcd3a+xjghMaxY7m+3RQam8O8xkeJr4U5Kb+SWprG6ryDhOWXohoy6RIQT9/EBxka3h1DTh5kid7I6ufgd/tudhQcYWfhSd71sdAmJFX23zYVPPKKk2HNhV7nhAKbgR4pDtqo0CqiFwPjr6BL6iIMeQWQk4MWGsppXQZrsrZwoPAke0tSedfaiaEtVkH0MJShS2sdH9sWraenv8v2Vwdb8qYl8VitbfHxqdoW6dZLl3d2OXn9SFqs3F+5cDXY0bEbXR8V50hl3FFxSi7/HFWsN/0GtCHBfJDrrslmxEgNDJqcW+xO8PWR84sG2LLAmo/u7Az5ffw14Ja5qntuWyaW/FAgGJPRo4cHbzNH+ff79sHu3fLZ5MkSaLAmBAbC0csupfWKP2ouWA7fdI/muovTaiyz/9x+9p/bz/vb3oes1vD+EUCSTtUludjmFx+n9/Ov1dkuMtvnRT60TCUmRpzLakN8PGxfcYDdp9vzwgsqDz2oEBxSuX3LyJLGQH4pXE6n4ltpsf1utOLT0Ow6lMCEaslmxwsCaJVRBMf61u0hgE7OAPbqi+pc/qniC3n++KI66+sceh1XJPxIQuAJbrxNT4duPmDQu8as3ZMpTkPWQXsB61ZtY2Cz5RA1GMUdaLuGuZ22/EVijBvrbHc5fMBGuxEXy1trzc45bmx5ZxKHd6RR6Nsdc5c70XQGcNjROVznEgMuJpaGarOwbHkun/7am6Agj+NXjdi7FZxi19EaD658xtXUSufn6/ZFs9gnDQ0FvTGIAIMfAZjQO1VUNEqwUaRZKFVt+CgGOuX2o/vuwQSqhdw9rS3B4SbAATaryCsmE1AADpd+zGkh9bFGxBlSoPl1KG2n1GpH+XljFsdufx+f4DA6TpwsKlWLHc1mFyuiDjC6VhbNTvLZLbxWPJFBKrSMv4yLm00kwT9O+jo7G8LDOa0/x2/pKzlalMzyvAOk2vKEdwk094vjh4QnMObklY2PSyJupX2WcEksDgvzvhrF8PTmnMuKQ+n5BqreiGa1o3M7D7n6TlFUnFYLx/PWMlW5s+buytjL3oy9vPPHO1zkD7/FADofNJ9I775zJwo6/omXvu7jFXfw/FeDiWI727e52LP2MxJYpTDJpWsNBl0w+LbnjeNrySjOQJpQ4a6YS1B27kQrt2/fYerMTHWm9AkaxvtuhLWpNT5HeWzr3o0eqrXO+hUtFfo8s5FXrp3KYO0FSJ4HTSdCzFgU/yYiP4/ZCRmrYLsoAFef68Og4AdAPwBl+Opa+Q9Xf/M4Z0rSy757v92DTLC1LqcjasThqCF8nr4GJyp3n07i88KBDO64Hm3LrZD4KEpFXWUFLDs0gOFqPwjrgjJme9V1yjsI2VInzq1n5PGX2Xt7PA/8sZEFG2O58koNs0mjcxcdERGytB0+DGlnVTp20nGFIZbIwDTo+BRKp2nV3+PsObBm8fvcVYxuMlPsTeOO1FqnQ38coW2x8BuV0ZtFB1fhN1rpOcjeXiZL9Lz4OkY1MfPwTZ8QsnokWkhniBqGEtpVnND7fgNZG+GwOL2tOTiIgerFYG6EckVarXVKWbeDJs766ev2P9WcxHXNoOUtKL1cvMUa5N/idfcTYMyGhEl10gGcO5VCxOmHpJ0G/SiB0nfu9G6nZuFl4w9rFjd+/gjRhnR8A1pwdffXaR0QX+ls+4d2jCXZW8m15jHWt4CRJQfQcqGw/zb2nQjg8GkfirNKseSVYlH0GP1UfExOfA2F6AK3Mdn0WK1tU2At4KX1L/HS+pfoPX8R+iMBXDQqmUcfyAItH6wl4FBBp4gsaPaRddyaTWnaVvyNSMDm8tCcsrdUsCcsWXUbX3wjRKuVK2utGgB3PNMes+EgMa0iGdvtNeKz26Md8W6nfbpk5mdto8Cex9HUbBbp95b9PtbcmElNx2G2OKCkmExdIZ9kr6REtZFnzaPbR53IC9eReONgHlvzBffeG8cLL2gMHqzRo4eOmBiRn7KyYMcOldwcuKvvJEbEzYTQjihjd9U6Zm//8XVW5Yr9UkHhudZ3MLXVLZ7+DlaYFOlgVsYGnKh8tfsrnktZRmzIWejwhPDlapnbo2c+yzLdybLv4n2jGRbQEZ1VuEj7HalsKRF977wD8yhJWsICn3z23BDMk3s38+nCtjz2mMLUJ1ViYnVERspR+tQpKCqU9eb3r0vRpXzB9Ce+pE/b2Shbb0PbdjdKWFcJ2qIzQlGym14kc7vtOlgxEuXKc7WvgfkHCVn1EMuH6nmr5Vqem9OHefN0/PSjiqLTERIiNua8PNApUqeh3VLJ3/ssz07pxMW930M58i7akQ9kPQlpJ3UqOUv5k4dvcSmLRzTilXYnmf51FKdO6Xn9NZVXXvHIwHqdilNV6NJZJUaXQTSX8vmMcLpEv4pSkop2eAbK4Te9n8V1j9J8JzM7RjAq6AUenP8YM2camf21SlCwQmKigskkKvCDB1QcDoXe7Q6w42hrPvvMRKeOGj0u8G6lig5PlmIL5rtj6mXfbvSMkSxdzQcRVVPZlb6LyOmRjC3ujE/oHjraIaH941wbf5noicvZUfJ9i/kkbRXF9nx2FZ5inpJM0ummJAc+SI7/CEpVEzqHHZ3DhurjJ3E4nKXgKMVZnEfaqfWknAwjonkTRt46DE3TUFSn8BlAhLGy53ayecVRHn9LdDB14iRnboTU+fL3hfsqf1+cLM6R5fQGU/Y0pcQ/mVhTKIO6vsLgk3bIWuK13hzWn2Fe5hYK7fkkdr2Qc2l3smiRL5eO1+jT1/v85Xb+Kd9/45/3I5FSfMO6cHOXl4j1bVxp7V9k38X2/IMklaTzVbic5+n4HLSpYPQsToY1F3s9w/qz8TxoSWKECpHNJnJD696EpG330sfkmYuYnfIr6ZYMlucdQHlvMVpqKbfckMYdt6SDPQOKM+VMpSjg7ws+vhK8xlHMvVsP8KtuOwGqQmhIR9oExBOnBRBiAYvmIEOXzwlnBsdK09EDIcVBbNEfq7ardmfsZvfS3V6fdVB92a8rrfY3FTHO1oEFprrrSnx++AGn8woCAqBTp8rfV5VUuuDbCwg8tR0tchDZzWew45Afp4/aKc0tpdSmx6HXYQ5w4msoItCUx+A2vxBt/YbjJxNIbfkDmfl+lDjNGDUbms2KZtSjGFXQVJylxbQzldCtiS8bNvTgqac07rkHoqJqkXa+dX3f+h7o8Z44mZZ31i4vr1jSKchIJUgPqjHcO2yx5pSHPv6p174NUBLtg88LePwNKvKFv3gPmoWUccBW7N7FsDk6CO+BMtqVrKGG8/aKlQZuvCGRaM6w4MdzxDRKBlsqFGVBUZ7wafz8AQOopazb0o3XX7/Dq59qwwvThuHUrSKwUQgDe7xJi7xOaEu9512KKYsv09eCauH2m3SsnHUrs2dfSl4e3HevRu8+EBBQdX+kp2tceMFpSM3l1lu+5M7xr0PhStnbDs/wdshF9oplcX0Y/sJm2a+GLq6VS3nohJ7hd4+jd/SVfPXqWwRnrEJbegGYIlAa9ZWgT5oT8g967XmsHAJDV0DUsMoVr2B3ef2TRN57Q0+fJhuY+3UGODKhJBMciI7dzyUHooDlHGnpKtF8DIAyZAHEXOjd31XoyV97IhVj/jl6DI5kwPg2UmebRaL9oIFSAkoROIrAUUB2ajIHNuWSea4Ruj4zUPVGVEWP3mlDsdvL7Jeg4bRZMJfeTOPiHPooS9G23gVt70cJal3j+Bh3MJS8Y31p7RtJz5aT6B/WmcBCa5m9Os9cwnrHEbYXHOFwyRlGF3TBuaMLBqeOnrfei9Hscptz84L0yAsNNCeqw8YQu3CHlF4fQcvbam2nvE1vE3xqJ+n64ZyKfJfTaWYyU60oDhuaokc16dAZnSiaimLL56I2b9Gi0W6IuxTir/J+wOJkWNzZa6+wafBcshGj3Y6xUR/u6/YqAQa/SradX88uY1fBYXBaOHP6DJrPUeLMEQzp+hIDw7tV2r/cMnmOLQdLqkJM4BqwQHzru7mp1U1Srpws4Qxw8s6ZpRTacym05fPWuar98irC5rTR5v02fGIZzaT2SyGoJcrFh2uVNU86riAwbyaNk+aihXSB+AkoFQM5lgt6U6hC0Ik6VYnUwlSi34ymrS2Uw6bcss8/6ziViT49IFvaKc2cT8+jz5DnLKHEUcKt70xkZ0e5iTJ8uegeK563K5wjY7+8hbR6EO9nlFzCvR1/A70vykQX57uGdZnC47DiXsgDur4BkYOx2RW2brSzY7eeIn0wihmCzXn0bn2KLnHHuejZsWTudTJiBLz8sqv25w5BznqgAPxNEBAOpgTw7cb0VZ9SopsJFmjf9WWuiKng9xegUOBbwttnfpexW+zgmTDR4Sp9Z0Lz67yfo4p5VLDhdYKS96FF9EHt+i7J6SaO7LNx7KhGYakBh0GHyV+lcWAObSJT6BS3goDcbziTHMvphN84mxtEZr4JvWoDixXVpEMxauhQcZYW4qed44Yel6KgofR8XwKa1FKn2++NpORAOj27Z3Hv/SoYdLJuOFRZuH18xH6paWDNYM7mo5x0zgULtGr/MNc0u6pSO9n97cw4u5QSez44LUx1bMKQa6Uk/gGOKLdy+LQvWWcsWHItWE0BaCYFs1KIWV9EiDmPxTvDOLHeh5at4LtvXTrEc3sh9w8gX/rOPwQMkeDbhXX7WnLNHYFEkcb381yJDzUNMjZB3nbhkPoHgz4c/PuBIZS0P8YRHXwWOjyJ0vn56segq52mTI1j43cBxMTCgl9c4ynzLGSvBjKE1xoQDsam4Nebhfu3sDPrQbBAWPNruTfxfu92cq1pM07OId+WA04LD6l7CMjOQYu/CqXdwwCUpObw63JfUnP8sOn0hDWyMqLTERIikkHbDSk/oRUHl9kTtMwsVq/Tsy8lhELVRECInbZN8hnR6TCpZzJp+opFfK7c/ga1yFAl6R/jNzseLfZitPbPkJRm4vBeG0ePaBRZjTgNCiZ/ldiQLNpFJ9Mx+hfMOQspyQrgZNvNnDxjJiXDhL3QgrPEgmrSozM50StOdI4igk1XoRT6c92Qb9Av64PW9hGIHIxiDqty7UjOasr7yyRj7vOv1s2fcv2sL+m/4lYuXeD6YF7N5cv8DV4o529QSzu9MsfAoS6ziWvfnAtvuQDQUFTVlTQXNMVj3tI0lfSdv3KZ+Qbpi2ErPAGL0tNFueCrQojrB657aMnPouSpaG0e5qTxBnYf8SUj2Yol10KpMRDNCL76Qnz0RUT4Z9M/4VVis7ahBXcss7mnHipk9UYTaXm+WBU9vkEOEmKKGJx4lBMnj9Pdz+VPOXiBJJuCanmLqjWHcXtfpLNqxy+iF5O6PF/J5q75a/x8dgn7Co9xrPgMRQueJnVVM1okwLzvHGIbyDoIBceBUvD3Ab9ASexojGPhwQy+ynuBznaIaTWJW1pNQq/ovepk9bfxcdoq8mzZ7C08zQxDEXEhqdD+MZQuL7kGTvVze8VnvzPM71vwiUIZ8pv3M0Ol5162CUY/f4+rL2sdfnK5mzsTsTSzboWBl3mC97mbVoHbWb3SCfZUyDrkaqcSVzsFCC/eGEtqZiBxGZNcvkTvengiNfjIbN+5hsyTRgpDx6BvdSWaXo/icKCz29DK8fFwWlFtpdjO/MI1J6fVXecTAM6XFFKSm3Aq/BUy6EWBxYxOtaPYrGi+fmhG0DlKUO0lUJJD29CX6Nd8LTQZjzLwR7lODX23YfFh+gUL/0GZWCRBi8r/poIsYSvMoXnbwURzlqeeVhh3sdM1BndL2/obxN9AMYOpCZhaMPGJFhxf56DnBRoffqiIP0PGdsjbBRSBv9mzH/m0Z8v2M/QOkzVKuTzNo5uugf/QvO0gwm0ZPPigwtUuV3qRV9aAv9MVYT0I/HqCqSk3P62wb4lG+0SNWTNVsKdB1n4oOOYZH/5BoAsBUxMe2bqUt4o9HdfavymPJFyPsdgChUXkGYt5Lv1ncp3FWJ1WBnzZl7wIE765Fmh5B+fCJpf5iqQmObEYA9FMYFKKiArKpo1+H70ctnpxKfe3TCTx2UOwrhnK2O2S4LQW245txf2YzmWjNbsepe19FBbr2LXVzp59OgpLDahGHT6BDlpFpdOj2XHe+r0ta7+PoFFjjcWL9BD7CUrqw6DlAlqZv6kYXoPQom5DOTAdZsRDz0/pHtaVBdODuOj+liiAU5V+UxSNmLBCPr7pN0pmPoPvmZNoTS6je/snWPOxP6PvaUlhsR6nJuUNehWHU8eD4zfT2/kN6pwPwRiIMiG3dnvTqRJ69+9NNDm8/85n9G4+AwqXS/3PrYVza+U3rt+uKYEi1xs9MCSgA9qO7V5rmjlAoYd/M7YUHkdDY9svPYi5/QxRpIndNvwdFOsjKKXb0DQdiqKiuWtpaExu4Aw6BBiIZgcvvij+GIS+jJJ/A2i5KIrmqpMChig0v9sp+rYngae20ajxADZ88A63Pt+MX9aElrWN68nR6zRMBif3DZqBulLsR8pV+RIwseL4KGdTXXtqAyNXvIQrDCGNTWHM6jKN4GIn5OehBQfzcsZcFmVtRQOeW/scJ5d9SahPCqG+0Vzc/XW6BbettPbvUU7zS/YO8m15pOzuzaaP72FQ/Exmvf4GpvQVaOkrwRiCEtFTgjiqNrTc3e5RRVGAP35nrkeJfAPaPVDreWrFnN8Y1vQHCO+GMnqrFKrhfLRr/V66uOW6OvjSWyyZ+O1+HmY1pzpsStnEppRNZcFNjS9asDvMjBtXN15Q8WGXX5ZP48qJK9wJyyrwPiw5YM4Hrdk1KG0fKJvbe/cpFJQacRp0+AY5aBmZTvf4E8w4NZddhs30NvjSseNUxkUNwi+3qKydNH/YzFFW5h3kYNEpDi+4lT0r7iIuDlKqoDBXhYHtTlB8OI/xl2pMeKwQtiej5h6FgtOATXTS/kGgDwVDNOs2nmRg07dA74cysUAuUkPfje7uz5pVvdm2zUjSaY34ZkpZ0DG3u3T5IG+KAqMuOEbW9gJGjNR4+YWXUCyvoxT8iqbpURSXvOkeYboA7j/RhXcd6+FIzX5QbgQoUBCOnLc7Pe9JOp2VxcE9dhYebY1i1hjX8wito1JIytjo6VrVQaNCZ6X1hgCFRrm5Vcaf8VN1Ut51D7dc56d4/LSdqoNPkj9He+lzSHwMmopTwzd3ltLlzr5oOp2o7NCYO+V7Tu9fV+63dkxZuVXWyZR7CKeLy6JoCppr3TKrVFknsyHD86xofFmwAnWODqXrq5D4cK3716T7m7P7VzOtWsO337hKGh9AKX0GsLnWWT3owtCCHmPt18lce5OJaNL4/ntXrIWIV1BS7gCt1FXeFUfBfzCarS+dI5Mwncvittumc8f4DyH/Z9AscG4DSuaGcvWHjk32cfugd/hy/V088ICRV1/V6N0b9Prq9f3OrJ3o5nWX8dF7JvqQ9nz7pImBt7TiTJYZVdPh1i5PGHiUibHrsHz5HOa0VLRmE1HaPsSgQJh2fTDTZrdCUTQ0TUGnaHRunskDg97h69Oe+0U6favsu/CSI2VJWROKmnLTgUmoByZJXI2oYbX2xb6f3qZD1C6Pv0Et9u23v2jL9JdiaGo6y6aNimdsOC9BUX6W50AHAYPRzjUj88RGGp2RA6oy8Adocmmtddr2/Sf0iN0I8Veg9J9ba53IWAM7vkDLBb9RW9jwgYnLHmnJ+l2BLvux9IVOgfDAUqbdMptpr0+WwJiRg3iy26sYdYZK54SZyfNJKkkFp4VbtZPEZSWhhfdm5AXvseS9ICY82pzCUj2qpgAKOp2KquronpDOsH6PMe31r8ECzdo/yo3NrvS0lWselfpZeT11IagW2pDKCHs4EYZDaEk/QtNLPXFdNA1Q4dhHsP+FsjZYdbgfg1tvqrO/QcbKF4jSb4LIodD3Ae8GLU6G37ztlwCOHNDnA63vojDyIo5vPsbxgzaSTqlYjIGoRtFbxYZm0bLRGRbmfozRZyuYwxje7XX6hXWuNGaPG9L55txGUC20ykpkbGgxoae/QQvrDrEXo5RPjlEh4HkisOHeJjwy9x1efHEcCxYoXHM1jB4DzZop4iatk6RL2dkaO3domE5MYUz0B3X2N9hvvZM9q2K4etBc0ce0ngJRQ1DccUUqQFUV1u3qRc6i17HGXoq5xUjZqBwOdA7hRioGBU2vgWpFtVmY+8BM3p3Tg08+upKdOw3ceqvG0KHQokXlNSc1VWP5ghRuuacpAElJdcvrlX5jD6KWn629IBAO3NP0XT5Oncw77xhp0UKje3fvulRMKNU0pgTw49w5DbsNjCb5Uq8XfkjF5AQAO+wr6PoC0p5dX6+Vc7phTyb9mr0DB99BmVgsvrY1yL/RcRrQmOxsKCjQCAry1Kl8zBl3nVq2hLXPX8GDM+7g4YeGsXSpwrXXwtChEBfn/fxOJ+zbp7H95z+4xS1rDlsugclrkDVfLikg8ItpvLLkcTp29OGJJzRGjKh8fTdycjQGvhvBASWnxj7bn7mf/Zn7eWvLW3QvSWCHX82GkYXHFrLw2EIeXPYgnOkOn20ve666BPL9/bXbGBD7BQS3Q+kpPI4q/bdBfDDPtAGa4+/v7W9QfmyAhxu/I207jywT/p4OhY5BLfkh4XF02Tll9xgVdTs9C54BoNhvH53b/s6ew2N4/32N5s2927R8gGD38x3fcYAWhySAlDJyjcQoq+EsUlyUSuBXt9XeOECxvZiEdxP4ICKc0VmBJJ1pQ3arD7BixmGxY9AcaIoOjC6dkqbitJbgyDvBzV1EllOG/CayZi17ZPGaZ+F0Osd1N3I29H7SskxYi+3oVTuaokMzKuiMKjhLcBbl8uj4DD5dOpYnnghF0zQuuaTmeGmZZ3KIuLd+3KY7u3/G5Iveo7N2A1rqAmg6ASKHoLh1P63ukCSTm8VOtOFIX/q22gw/N0O5qgAMfpWfu5wOwFF0Dv3Wm6Sden0CLW+tsZ0y808y+ef7yoZeI1MoTwaMxnfr0bLx9JhfPB8bg0m35wPw+9efcVPCFtF7D10C5vCaY7LZ8mh79VXcOfh97pwwC/PCdmhRI6FRP+Hj+cbAwPmQsRYOCYd1+aH+DFMvhvDuEterFt3HjfOe50CBJyHfW+3uZ3LA2HKyRAyl0cP4NG01TlTmH5rPb4eEb6VDId43mr2D5uKfV1wm38wuXMmNB6YDsO3MVgx+rjN29FiPz58bVcR/WDQ5kAe/fIuZv91Enz4GpkzRGDy4ao6M0wljx2qcWjGP2RsnMHasjqef1ujRA4zG6sfgG8+Pp5gFYPBjUPe3GBzRvZIscc6cx0dpK0G14HPOl0ebyIBVRqyExoOkXDW2v2sGFLOpu5lfdlzENdfA009rtGtXM8fnxXdbs/DdJTx/9TRGaJ+jnJqDFnOhxPwLbg+9v5RYpzlb4fQ3pOVGEhl8DlZfjDL4F4i9qMY6Yc1ixw8f0i1mCzSbKPE1y5eHSvrfV36az077z3SwQ7uuL3Nl9PBKHME0cy4zM9ZRaMujtX0fN4cAljQ0exGKO8aaohO+sOYQvYSLe9QKWP9AEx6Y8xmPPjKSJb/D1dfA8OEQH+/dXg4H7Nyp8emn98Fef5666kWaLeuFFj1WZLuooS7fgT1gSYO8fbDjXo9sofdFM/h55oObw4ybD/VS2b2umf4BR3Y9xB1Xt+e2cW+jHH0f7eiHYsMI6yxB8O0FaFkytreduIAezbfD4h4olyaBX2yN6w3WLNQlk9DlWCVGRvPrmf2Qjv77WnHgdECZfkGnaIQHlnDfpV/Q/4jnvN4zqC3s3OHx43CN2T6EswcdTlR6m6z4fOqHlgsXD/iBxe905KZpzUnPMgKa6xzp0Z0O63ycDo2NmDOzuHWSxuTb70IJVVByZ5XpKAE09Cg40SIu5Ped0Yz+uVmd/Q12bFe5ZFwXojnLzJmKJHOMegMl9V7RL7jO2wAYm7GkIKHsOoqm0UtpUumsGhCg0Mo3kqOl6WhoDCvagP8sheWjw3mh9V5mfBNJaqqet95UeeONivxfHRcPOog6R9YlZfgyOcPUskcqm11rdvup0NmbRwdU4ls9MO8L5tlW46dBQGArWvjHEqcFEWLTYXX5AJ9WMzltycSEjoCScAasuYNQJYdbH44ntrmvzB27TXyfzW6fqyLh6jtKuOf57hw80ZIuA+K46b5m0o6qOAgqcowEBTRV9IOR+64jxnc3NLkcBvxY/TMAWDMpzkzDd911YgPrNA1i20DyjhptYB0veQqAzz6rnAehKmz6bh69i8VAo4zMAlNIjXEysGZJP1kz0SyZKL6uxK6K3sN1LLfeAJz6pAnN19VRQQms7xDEfT3e4Zt515GUZODuuzWGDIGYmMrruc2mcfgwXLvAQIyqkhDagQHNJtIjOBFzfpHwzMLCSNafY13mH+wtOkH2mSSW2Otu29GAbN9wKIXg4Orl34pxJs6aPiPqBSDhFpTWd9Z6Pjr21o+0rpz1ulr80K0JEy6pe7sCZfGI5syp2/i49rWBfGupQwAwFzqWtmDP0brHiSvFh1CEj7xkicvuUguSZw6nqWklBLeHC/cDFZJnVJhH330SxKtv9iEoCGbPrkOlrDnw01i57ICfocn4Kiruvd5cdHNPNu5txdChdfPDsWYewby8rbwZXAJ6X0DnnUy0wj32fP8enZv8ATFjq06KWjFm9aKFdPF7X+bm1Y5ay2PJwvrrzRgL7cLXqciFqmK92bB+I/2ClkCIh5NRE9dg577TdI9x+XhcWQDGCglWqqhTzo/3EmLNRWl9FyTcXGudrtg6i/mG47X2gRvXWgbwdex6WWf7fyvnmvL3qCLmbNzOaZyljsEZgavWf8y8lXfQtKnofGrDsW17aXWss7wZtU0ShlVEhfFBSHvI2gzHP6PQFkrguDo6hNUBiqbVlRry78fZs2eJjY1l48aN9O3rccJ/+eWXmTVrFkeOHKn0m9atW3PTTTfx5JNPln22adMm+vXrx9mzZ4mOjsZkMjFz5kyuueaasjLffvstN998M1artU73dV/zzJkzxMTElJW5/fbbSUpKYunSKhINANOmTeO5KiLM5efnExQUVGubzFnwGdfvvr3WcuWhueYJ/eZWJkYD7J3mpfDdndSZLtv3wPy6XT+lUSxNBpypc3kA3LEzen7mSZhQQ51WHxjEkPZCOKgy4EiF8qU2M76/WetVJ2Va3csC3J82jrcHLqg+eUWFOgHwE/WqU9GHfgQEl0DsJTBoQeUCFe7x6apJ3PGFBLGq80pwuVK/vruMepVfP6gfA8I31vk3Fsz4IoqP6dPhoYdq/03JJ774BVokW5s76FJ57J3m1U4zjiXwAHVktbug7aVez711ag96Jm6X4OiXpVcuUKFO85KbMtGaXOfrG4FVh/vSP3QTdBsBvW4EnRNMPmDwlQCnKd9AsidQzc5TXem2c1ednyMtNJLoIRl/6zy6/MA9vNNxPrG+Trj4EwhoDIrqSel86gs4/WVZebvDwIIPx3H4j7YUJHQlsGsCPk0jCYr0xeynR2fQgaKg2p3YSp2oVhuTd0VSOD+AdQxkJ93Yo3SmuFkHIuL9wceM3mRAtdhwlljJPJqLj182k1tPZ2zMcug9HJq2grAo8AsHZwEcekoIeS4UOCHY5YPcJB+eXQO37MLrsHwsDCZfBGubgVNXbl2Ovxr6fVs5W5/JAG84JPMusObQQAa3cxEM3Gtg+d9UKA8w7dpnmRb2HLQDmgItzJDQDoIauRyZrFCaCTapbPP9cNoMZjtcdAReWwHRxZ7rlerhzb7wSQ/I8YNrA+DehT1Zv2YAZ0LaY+rcDmOLJoTF+mL0MaAzSh867Sol+XaU0iIeb1Q9Aagq5P/hT9DvxbUXdGF1s8EMPS1O53VdA5XnalZCVkSjt1PJzI+tM6nnyLYjtO3Zpn51clVp5kzJgF0btr0xlgu2/F7nuZodEEK4NQ/qkbyikekcWbZG3HyzZJ6vDb1eiGOreqbuNwCOb2rB0mWjOOmTiK5jewytmhMcF4hPgAG9Uea20+bEWuwAi4XgBc9zR6tPoUUgdOwBzVrLXPUNA2c+HH1elEQurDk4iMGH1tZvz3sfIZ6M2CBra1oaXHaZOO2ZTPDmFZD/bVnxLJ9wIqKzIXIYuIMulcfeaV5r/6ajvenb2uUsWgf5BoBcV50G/gL+TbzrBBIY6n4nhMjbkhh3wOn+kiSolvVm6d4RhKTl0ytkD4yZAqGR4tDiEyx7i04Pyd9C6tyyKuVnBxEcXgCJT0CXKpJDVXiOmON60rS6H9AG5ndibdLe85M1+/8ITS+v9bn3p7Snw9YDdb7HicjmJLzlUkJfZfVWDrixd5p3/7n7LvExiJ9Qa99tsfakd+RW+c2YHfJh+d9UKJ9nDSLkQMHfum/3dUSyqRwxrS7QIqj+GaqYR0oV+pCa0HXpp+zafBtdusCuXXX80QeK1Gn4ajAG1VondlKvdt19bSe6jN0rCouLj1Yu4FYQlKbBusvIK/Lliqk/kpoZx/VTwpg4OQQQcqWmAYqLrKmKAluv07jgazPZtSQpL4+Bmb3546PVoCms3mCkew/FS0FaPiOt25BvNsuG9P33cOWVVVy0Alq9YOa4WveEUL3z27M54UC9xgduUaLfdxA/sda5/cCcN7mn8wckdMqBtpMk0WJwogSXV/RieLVmufriUtDspMyOY8aS+/mBKzE0b8rw4dCnD0RFqgQESDsVFsHZszo2Hj3IrID26Fykl8sOSTDsiuh7K/wRKw5a2g/zePbgQabxHLQERgPdADOSuFxFBEm9/F2c1pw3Hr1ByocClwAXIH+XL68gQUQckeCep4mPQZdXa22ne2e9S/iybKa1fg7GAF0Asx6C2kJQB9AHyJ5achpyd5GhmYg6nFXnvgbKlNxXXw3ffltLWWDN+y8xOEwMJ3WVf8tQXWDuvdOqXpcb9ZWAErWsy4uSxnLRZ6LkrYtcV1wMH/d5iJP7WhA+tDPRF8ThFxWEf6gJs68OnV5Y15pTw25TUR1O9k16gWnNp4tVOM5HInY0bQ5BMWA0CcnWlgfWPMj5FdDK9AwnaMESRnOIduynPadojg0zOlT8KKEth+nbJAVryjmmRT8HrYE4oE04tEyEwMbiiIsFSs9B8UZA46I3fmVy+Mdc1HQldOsjMld4tJyPHAVwdJqXzJVTFMp3H17NiT0JBA7qTlBiLH4xoQRGmDCadXJm0zScDhVbqQY2GzeYIjxk8NgLa+2LnWpXuu2u+9k2u38o4Xe6nNRrCtyesxPWXQaaDaX6OC5V4uGUibwxdK6QWi6vYn7sneY1/o6W6miTKotHs1z49DcYcdL7J2kBcM3lsDMaCnzgis++Z8mZ0QwaqmfuAt+y4KcK3mu5oojd0/fQQ5jeeBt1vsI2LmANgzlKaw6QyFlicShGFM1JIEW04yA9m6RjTclgWtPnZQzGAomR0CwR/MMk4KizFCznoGQToPHmPQ/wUOe3obkPdOwCzdtARAz4hYHeCM4iMeDYcuHMLNYc7M/gQ+vqJ9e9AxQCgxeDb2St46O+ssTAotasC/Ds14oGehV0rqGiKuDQ4TnkWwK58dt3yUxuRP/rmtN/YiwODKjo0OsVFL0iyaIcGk6HhskM16zyJ9Vcd5V916IEdgXUT2/lXme3bYMeVdgnKiLqeRMZWt0PhZ0KW7Gnm2tiVLUu+/jAL5Mhe0blH/f6HBJurXU/2n6yOz1a7Kj+HhXKn8uPoHFwVp3r5FR1fDT9Tg7vaYtP9/a0Gd0cn0aB+IaY8fXXodPrUHSgOqXvivKdhCTdzZjE2XWuk1ODeti7BK6+mzoVXqyCT1ERa2Y8zmDja3U+J6CDtTsHMChkPQyeAE07QlAE+IaAwSwEpZS5Xmc8spB5FzVcgkTWMu82n+pJn6+31kvPUN+zyKJNIxnbcpmsScMfFiKI0SAER/c5NcWjB331aGueUKqQxWuAZZeJ5QtGsJNupAe3hU4dCWzRiIBQEzqTHkUnegl7qYPs04Vcc8EN9GuzEfybw7iTlS+4d5rX2v/Zqlu5/YvPgXro7t1nl65vQNTQWvvigD6R9oEHocgfRqyrtfyJguYkdHadbesoQ9V3j+w8byl7Do2U/UmtvXxueg6hq8K961TX9abDM9DpuVrXm3WH+zOw7Ybq73E+smYFWaJsHjW5DDpMrbUvfjh1OVcO/UlICFeVVL7+3mle/bDLAt3K6Sab5MGrK6CR66ca8GMifFZuTyjTSceNh4E/19pOaw8NYFC79efXTpdniVxUSzsVlgYQ6FsEEb1h5OZa67TleE96t9xafZ2qGh/uvuj5KYR3r7Uvopx6MuqhtxpamMjKbge961QRe6dVfRbp8ookr6+lTnuVjnQK3geFJmknqHHt/6G4MRPM5+r8DOeDXhte5LXgZQyK2w39r4DIphAYDj4h4MiDfQ962VEOFvrSPr20XvcoG7NunWMt42Pl/qEM67BK3tRB16qqCju+6M6qNUM5F9kR/y6tMbeIJSjaDx9/PYpBh6IoqHZV7E0WK/dGRUnfxV0MHafV2ndrcgYxuHsF+3ad51E2VBW4psI82r2uM10G7oHwnjCqioQRFZ5b02D75z1Yt2YgqUGJGDsnYmzRhNBYP4w+enRGPZqqodqdFOc7UEoKSdzzAAe2tCc3vguhPVvh2yySgMZ++Prr0RkU2SPtKnarimazcykJhNnyIbgd9J1Tazt9mN+Gu/2F92F0wCVHoW8yBLmKF5hgUxPhztsMgM2Xh394jnPHGtP84g50G9cUm2LCJ9CIyaygN8h5W3XI2bO40Em3491o/urxOssrZ5tGMzvwepIPxhN7SXeC20ThFxlEQJhRzrZ60a2pTg2bRQW7nQlLw9j5czc204ejShvyWnTDr01TAhuZ0ZmNKHodqs2Bo8RG5okC1u6P4NbSd3nWfQZrBiT4Q0xr8PUXY7C9GKyFoBxnW2Zjeub/vXP7G1sfronZXGdZ02Y0YIpzHcLquke60fYh6Da91rn97pJ76KVspVfjIzD8TggJh4BQMLtsFqnzvGTZtNwoWtx3EovqyxdfwC231P7cbrvco4/Ca1XESK+IX9//kXH3XoGPj5DKak1GrGl83Hwykzt8CgkRkNgF4hMgJBrMgaA3SFKJotOQ+hXgrLfMdU9hT97rVmGPLI8qHFDKMHo7hHWvtS+Ua+W6w4fD8lqSMgK8POtxpp6uQ4OWQ7wNSm1yBP9yAYytoh2eHAZfdHW9+ewM5/JjmDAB5tUSkAtg0fKfuGiTOIqhwdij0DcVQl2PXGSErbGwqDVYXPr31958mEe7ToemBmjXFlonQqNYsUcajOAshuIkOPsN4GTkK0vpu38T0yKfg4uAnghZUmeGgHaSrEyzQdFRsOfxTVYsD547A1YwOWH3xxBeYcvUgKE3wkGXH1hGM2Setr5HyJm1rLMbivvRP2qjyER1mNuqqvD8M8+ITjoI0Rc3QXRFUYAJ6SQnoqcu7/zY5j7o/k6t4+mmw/H8riaBFdpnwspZVHKqSA+AXpPAYpD3d05/Vtq1LaLXbBkACYkSNM/sI7rT0kywbfe+UPxVwperpU6AF6crhTiWM4KljGQH3SnBHwMOGpHJcFZwcZPd9H/Vtf5cchICmtd6D5vDiMlgh8aDxUZVS/mNR/vQr7VL/quj/Dvt2mel70B0wC2BeMS+4uPqLycQJn+fzY0mJjRNEhdfdLjWOu063YWuAburH09V2XZCkDHb7U2IHFzrmH1wzXQmRP1A72YpMPBGCA4H/1AwB4kOIHWevFw4nt6CllEn69xODg2M5fQ3OhUuPgJd0mUcqgpsaAqrWnjKzAv15+BHD/PN4Wvx7diKyy6D7t2hQ3sNPz95bLsDrBY4eQrWbdvNM8XdAIgshMnb4fJDMs9B5vXGpvB2bzgQKbH6kkIDCQorrNnpptyeOvmLD+mfvYHrEr6FNs2gbQeIjYeASNH5aKWil7XmQtocCkv9mPXejZzYk0DAgG6Ed4nDLyaEwHATJh8dil4nZ3eHis2qodocXJcZ6lWF+FxIyAW9JuapU6FwspzIelFpS7YajoMVWmXDwu8gpMLWc6ARXHI1FLnM6xkngfnSJjvozib6spWebKcHhQSgocOPEjqyjxFNDnPXqy5OcNyl4iBay5idcjiBueoJsEJ8Hmz4ytMPbmT7Qp9JkG921cm9z1x0BIJa13qPa7YorHTpfy85Ah8tAkMFHcjXneHREfKcVwbA++V4iDmEsoyR/M4YttCbIgLQ4ySCLIazgvFNdrAspZ1nbvsia2F7hBMWgNgVrcBZIBmS+jYlvnGyR29VzzXQgplVDGUB41jHQAoIQo+TcLIZxVKubLKF31K6eOpkQNacjkAHZP8oX6dTwAAjrLeX3cOKid8Zwzdcyx46U0ggvpSQwAmu4Ts6R2Xwa3pPzz0AEoDervv4Iw1aCBwBciLB5OE5OtDzB71YyiiWMpJ0orFjxI8SOrGXMfzOdU/8ROEeA2sWD2YvnTgT0h5H2w5ENA9E72MUTqHDiWqzk3fWQlDxcd6+bvh58R8MTrj8INy/BRqXU/1k+MPbvWB+Ijj10NoZzFF9ftn3oSXQ8Rz4uc4ymf6wtzHYXfsjx0bBN0sAiQEaGUmtcMu/998Pb79de/l3Hvud+1+XYE510ms6bfwydALjoxdA587Qtgc0joOARmD0FU7X/se89AYV5V9fOwRZxVajIWtGkdnz/R3B8PLKUFYvHMJeOnE2JBF7246EJwRj9DOhNxvQnBqqzU5hlgXVcoyP+wzzXECD1tkQUyhvbXo4Fi7t68Y3v13GNS3nQ0Is9LwYGjWBwDA5i9hzYe/9Xs/w+LF4XqMOXicuNDPAgrMd6HTBfuhwjzj/h3TwJNqFSmt/9HE96fXQW3UobM7+wFNl7xsVQ3ShrM0Ksu6lB0B6YPXXqA1dCWAXRXUuH6/ombWiH+vXD6CgaUf8OrfEFB9NcLQfZl89OqMOTdPQHCqWYhXNYuHKXV14cfFUfuFS4nrFMWoUdO+u0TIBfP3EVGCxQkE+7N6j8Ovnq1mweQgDBsC6dXWolKMUbYIfe37uzGb6cID2JDfqTmj7aHxCfNH7GFEUBafFRmluKYb8bF67ZhQRMdnQ5AoYUAVJZO80L33M/bPfokvSHm5qNQsSGkNiJ2jSzMUDMINaKo5P1lxI/w7ZaV2or568+Q3QZ1ata/9nqybR0/gHnXscgnYTJXF9SCdJeKb38fBpSs7A+sspLjXy5bu3cHxPSwIHdCGyu8gS/mHmMv6DooiuxGFTsdlKuT2lMcV6sb3GFMKR98C3gi13/ET4rbXwaW4Khi83wNn50axjINu4gB1KD3ybRaIPDkDv54PqcKKVlFCUVkQrvzPEpmzx3isCgH7IfhGK7EfFwDEgI5JzFzpoHJQtwUPH7Kq1nRbvHsPWN8rtR5FIZKVEoAUerk8xkASUNians52wyFxo+wB0q8LhtML4+GX7JVzUeRGGJkOgx4fibG/w85SvwDM7lNqcdrFHzm98DFoEsWNrrVOnx/ewL6UTo0fD779XLl4RZ87AZ3HPMi36eWiDnCFbBYhdLyAEzL5yfrZkl3HW66v76DBvCfsPjSI2FlJTay/vsDkw/Og63NehnYos/jz/6jPMOnYj3UZHcvvtYnePjtYwGCrzzEtLNZ575BSDjt/NmOjl0HsENG1Zo7/BxlLoX67undPgqwUQUE5l9n17eGoolQ/JdURnazR7zGkomsyrzxfArRU4lQ+PEH8A8L5PTAG8shJu2ONdPssPbh4H65tCvi/YW+gx6J2eZLO1zKPZ66/j9OfxPN36JZk3cXro0AKi24BvgHCV7IUuLspGVE1D7zqzRRXCQ5tFhiovY58NhHvGwpKWUGqEK7P0rPWRPfLyQ/BhFT68y1vA9ZdKu/Qv6spPA1wNU8d5VN8xu92nLd2bHJa9/YqcesnkaxjEazzGGgZjwRcdTnSuvcGJDg097ZoUMCHlLVmfTMBYoA+iM9GQtUmjLDGZZoOwJAP5mgOdBuElkPamhxvjxtwOcPUVIr+G2sM51zG7Xu3ET7Bjfjc+5E5+5ApMESGMGAEdO2gEBqiYzcKpy8nTsWGDQmjJb6ze2Y+4tmF8+im0bg1hVZhG3LBYwGe+Ur86udHtLVmbK6LCOnvhoTAW69PdsSn55De4fYenuKrIWPquo4wnnAY+XXgT7++6h8L4Dtx8q54LLpBnDgkFk1FoGTYbFBXByZMKS/pMk76LRPigPZA9TFPAHC2BWZzFktwMeGfRVHK/NXj0daOB/khUuvIcUp2r3zMiIdrFIb34mCQ9rGUMTrvuSaZpLh+AlsAIhKdqRnRJ5cYTFhh0IoJ1piwMTnDo4ei70KpCPLb9jaHjXZSVKe+Tl04kH3A373Ev+YSgx4GChtMVQuISfmXee9diXl0C86GAQGZxI+8whRO0LJsXKjpU9DQhmUd7f8I9975cv/HhGrMfcDc/cTm6kGBGjoS2bVSCAjVMJum3zGw9q1fDFW2eYcGyi8gM7M69U/T07w+tWmmEhlZeuIuKNNatU9h64TSm+T3nkR9aAHFxcr7w8xW9vSUP9ElowE/vXc6ePzpT0rIT0QNa4t80Ar8IX3wD9CJz6YRz6rCrFObYSSi8kaGRv9XP36BtQb3ayW0feOsteKCKaVQRf0y9ll5vfFsvHtGmQX14fe0jrDcNZ9i4QPr3hx7dNRpHSk5XRYFSi8QPOHpU4fpfFJgP+QQxnYf5jqs5QUsADNhR0FDR4cSAgso71zzCvZa36sxbPBkKCVM873WqjPFI1/HHahA/wZxyYtuz055lWqfnYAjQGYjuIftlsIuHrfdxJZcshMx1XLl0HT+W821tmif7WJDLRTnTD35IhMwAzz3KbOgXHhA+fC1z2zLXhM9vdef2b2jTjwFHhE9Tb25Tz48lAXMt+t/Wbx/h6ZgXuH7oHOisQGwfCUgW2hkMgaD3c7VTEWRtYt/WM3Rc8UOd+66QAIKQA//KlRKwsjbseXMAnX02QIERRm2RD2viZBy8ggnf/kBgoPivJCRUe2kP3EkQu8+ANlNq7bvNx3rTp5WrLnXgGhRb/Hjj1kfEF2A4sob7BUL0CPBpIj4zKGDPFxtVwWGmjXf5J3RFZInWiJ7PtwkEtBafeUchFOwDez5rDw1lULtVda4TlLNZKMjeNQjRbYLn6KuTqpEbybR7JjOt5XMwDNkfI5q4/D86usaHDziKhb9+bg0PrT7NHOcBsEJCDvz+DQRXcPM/FgZjr4UCl27p4KEw3lr0IPOYgL1pK0aOFF+RuFiVwEDxpSkqgnOZOo4ehWdDFdFB1tHfYH12fwb0qIGXVs1+ZJ1v4ktu4QPu5iCJ6PQ62ieqxDdR0ekgNxd27jEQGgq3pD3KNMcb3g/q52rfvsh5OA/YBKwDekdAUFaleZRME57jWZYzAjNWJvE59/Iefk0i4IKUSuUzaMzHTOYbrqEEf3qwnfuZwWDWcuy1VrSKOwY+UXBZWp34wgufvsj7TB8MDHX1faBrjOQBuyGpJIJBPbLKbMkfLJI1syJeGgDv9pK/S79dwYNn13vfQ4/Mj+GI3bMQWCuvlJCefJE2xrs8iDw0HtE1aK42XQRENamyndYykO+4mpUMo4gAmpLEWH7nDj7hxL1t6NfbpbCqwzzaXaxjVJIKVvBxwOJvxLZaHjY9XHQN7HHphs8FeH/fJhPaZovsrwJHI+BQ+bzoS6fz7OZCz3NHI3r+9ohPugmRBwuAk0BJJFzikjUn2oW3UVeZvNk10Peb2n3pDw5kcGLd20nTQFfO9tcxAzqnQ1yBjJdSAxyOEPufW898zRez+TblOnr0EO59bZg9ywZv3sL1rb6BxARo3RFimkJgJBh9xG/ClgslSZA6SxrtJ7DMN5fN7UO0w2DU0aG9zG2DXiMnV8eO3XqCgiDl1vopA/oWt2TwrzeRcSKW9jd0J7BZOL4R/gSEGDAYdSh6BTRQnWL70+x2Dt/5OlNHvSJrRavGED0KIvqCfzPhMuiMYC+CwqOQ/QeHN22lbfQhj49MHc62Od+FsnzhCPbRkazI9pDYntDmQZgDXLp7VeyQpfk2lKICfOZ/V3netUT2jY7IHMwAdgCrYeDDwawvZ0epDZF6SN+F11y1Y+Be3uNTbkcpS/ejcTfvc0/iG4wed5Yiu4yf51d7nwndeKsPvN5P5lUTn1BStVywythbNqdy+eNhMPBmcLq62W0jrYi1DGQK72DHyFs8yCiWkdQumpHj0shziJ127o8wsApzxPYYuPQqWRdijI04q8sEK1yzD96uIuyRxQCjr/WsCWU20gnFop+sDzehPCKBSa5/TwJfAIXwdsg08vO0yr8JAK5G+rsE+BXZw5o0YVrKLd7lfRD9b388+t8i4BCQFokjIIPcnyNYyyD20oljvh1xtOlARDN/dGYTepMBp82B02Ij61QRFyV8wU3K65X6ogh/HucVfuNi/CnhSV7mWr5BaVL12g+wkAt5glcoJJBLmc9rPI7daGfgM0ZSLXawVq+3WtUcrr1MdA69ijvza3+Xgq6+uo8B8yWxRC1ztefTfzD25OLKfaFH4ggNBPYDXwOlcKJTTxIeqyd3240LPpLko/W0V4PM1R+4kk+5nWO0IowcrmMOt/IFT12l8km73DKdw/ovoX+y961tegh9TM5vqgLqPir13Vmi+YJb+Y6J5BFKa45yC18ykblEP62Qq7Oh0+Sclv1aZbXtungYdLNH9/H8C0/xdOKLwtFp4gsd20JMS/ALEb9QtQRKzkLeMiif/qblHXKmqqWdPlh2F+2L9jM4ahsMnABRzcQ3yCcEHPmw7wEvnTSA5XszXy64ha+5nj2mnvTtr2fIEGgSpxLg75J/i0X+3XnkHN/FROLKfcPAJFg9q3K3PjgKZvQW+cK5/S5eXBHC1DYvu57bCB1aQXQrMAdI49iLXGeRDZT3hT1HIxYzlv104DBtOUwbSvFDRYcJK81Iol+TZJ549q56+RvM33Ype2d0En1MO2RfSQCiIiEwRAyMzhKw5oMpneyiMCImix706FFo1ariE1eBX1vCrBNkzw9jGSPZRVdO0Zwk37ZYA8Iw+hqxWxyYivOJLT5Mp84pvLDnPuA8ztt19DcgGjJ+asyaxYPZR0dSgjvgbNuBiOb+6H1ca6DdiWq1k3umhAT9Fm4yPcqSJaM5omuHo20HdG1aEto0ELO/Eb1JDxo47U4shXaU4mKeHtZc7tX9XWhz719+tgVImxPF77+P4ZCSiK11B/RtWxEaH4Q5wIjOKLpD1e7EWmRHKy7hmdxmMB/OEMNSRrGfDhynJadMbVD9A9GbDdhLbAQUZ9DSeZTLJy3giiHz6lUnfoKS+b6sYyBb6ckf9KI4Ih7fxgHg64uiKGilFqzZRUQZs/nu1oFlP+2bBFcehMRy7sYnQmB+O1ghqixGlCaw3Fd0RCYHDDslMoXbfpTlJ/7F65q5LlDUiKGzvuNcZmNufrQxF10XjFp2uHb/o0gQZUXDYIBWq8wuX/p+0OPdWseTFgBbf5FYUmdDEstiSVX0N3DanZTkOyiynGBmSG8cLp7Hj9//H3v3HSZVdT5w/DuzfRd2F1hgWXoTUIqIitiwIGLvJhpNNP7UxIpoNEaNaOwlauya2GtMNNagGHsHsYuIqNSlwy5t68zvjwsLu2xn2Tbfz/PMs7Mzd+aemXfuveeee855YbdNxjttcOaBwTgngJ9+gAX/6cvbjGY6g1jebSjhAf1p3z2NuKR4wglxRIpLKS0sYfncNfROeYVLjjur6thVOB5tep6QvQomfBjc4jbZBpelBNebXukfjN/uc8+3/LhwECecULuJb7955xO2mzey1mWaPn8gv77mET5dOYLLJ4Y5++xgguRqk229tjeFd37M+y/sxjR24JvQYFb02p5O/TMJpwRjFCLFJUQLilg+ZzXdw9O47fTj69S3aeKl6+t1HYGhBH2FOwHd0yAtLTiGFa6ClDwI16Jfa8U2yqJEkhOLav09FUdhp68gd333mIlvwe8rdAsG+PsOwXXVKHBFyZ78bqfan0fCJvXZOILz4N4EfW17EJyHAJQQXIsJb7LiXifAro/WuA/8/Xd9eDbyY9ButQLeeXDzPoVLU4N+0qsTg3OFhESIFAa/0/88BTtXmLIrCvz6CHhtfXvklf86jdMH3Ae928Lw3YLr1e06r59zKx++u6zc/A8A/BtWPJvJ/9iXT9iZ2fRkZadtWJfRmaS0BEpLokTWriN14U9s22ERN+30SxY+25m3Gc3nbM9XCcNJGtiXtE6phJKTCMeFiRQUUbRqHeH8FXx20I5MTw06fCWWwuuPlK+n5SXBHr8NriERgv1X7MCk/tPqNt/MNPj52Z68w558zWBmttme5O36kd45hVBSIuH4MKUFxZSsKWTJd8v4KLcXZxTfGsQ7c328exHUD9oTtImWEJyPdIXvFm3DwMTv69ZPev0hkpEPBH37a/h9dJuZyHw2abuPlr9uGw2tvw65wapsbvrH8Zw/7K/QLQSD+sM2AyGrR1DnSkiC4nxYOxcWPwtEyupcC+jCJMaVHSNnxW1DaVo6cYlxFK0tJnPdQraJzmBG6nAOXvvP4HvqRXBdK4fg+nN7yua+oQjoBBFC3HHBmZwz9A7omQLbDoG+/aB9d0hMWz/HxKqg/1HuE0Ck/Hlk3PoYbOhz2o5gDFUhkAvMgrc6jWGvPV4Plq/Dcbtivb+YeG5lPPdyGqXEcxT/5nKugD4Z7HHM/LL9zXkfwR/fYzP/3A7OOSDYBs/uAJdOKb+O1aTxD07hOY7ge7YhmQL25X/8isfZq/uPm5/bsv6zjybY78YR9LF9D1jYnaK/LKzTeIPH3z+emXf133wd7YCj13/HhcDrwe3L7Toz7pBFlK4/bj/xb9j7580/93n7wxNDgvtfDYJOL1Ouj/HLHMSjnMC3bMdq2pDKGgYyg1/xOH12XcbIM9cPOqrzeeQ9QeKkir6cWK5vU78fEpm16Ri1GhxQ3J1Xtp1bvkybqmTM1YZrpM88A0cfXfM6Jp72CgcVX85OXefCfmdDWltIzQjGjYXjg7Fvc58sW37Z6nZ0eHVFneZdGd/3FmbMGsCg0Z045uJ+FEfiKIkG8x+EwyHCccEcJ9FoMEdZydSzGNvvgfKfu4bt6IbfXcCFw24Ktv9BfWCbQdCpFyS33Th/zKb7mxUE+/EeR8N2F9d87tIO+B8sf7ZduePR0g7bUJDeicTURCLFQR/BNotmsV3Xudx80m9r/yUB0XYE+/HOewdjF2uq/7aFD58dxXtv705u++1IGjaQ+F7dad81uWwu1UhplEhJUP8Nr13NRbuv3/nXcrzB2kUppK5dF/TRHPVgjWW6Pq8/f0yrY2el9XOW/O1vcPbZNS++zVWJzCyt/UX93fOG8G7fr2p93C4ujWefv73B18sGc/xJSVxzS8r6RMdRwuEQEA3Op6LRsnPlF6/6I7/e8cagH+thP29eiC8nltsXLFjRhQfu+i3zpnen55EjaDegE8md2tK2XSLxiSHi4oM+yRvGAIdKCmj/8rHsk/UmDN8Ddjwm6NiTmrF+7ua4YDvdZFt94v3juOnxC+icFuZP9/Umo2MiJZEwoXBwsN7wGUKsP+df8xPDF66/ILr/J8E19Bo+R5lBFwZzu9Sw/IvTDuKQHV6GUDwcV0kMK3v/So6R1Tqybsu/fsg+jPll7cf316dMoYm1Xxbg9BV7cM/cd7fqOrKuCebmHTECplZy3lLRx/9+gZGFhwX/1HZOio6jYb+3al2m/Px8MjIyapXfoFUmr/jggw8YNWpU2eNXX301jz76KN99991mr9lmm204+eSTufjii8see//999l9993Jzc0lOzubxMREHn74YY477riyZR5//HFOOeUUCgoKarXeigkxNjj11FOZO3cukyZNqvQzFRYWUli4sQdEfn4+3bt3r3XyCiDYUefmln9syZKNWWLaEgwYKFoBRSv5MhrHrFVryV2Vy8LVCwFok19A5poSSktLibSDcCakhgrpkppKZkomeQm9mbl8Vdnym76mOK2U8PrBKl2T0shOSiavbW9WR9tUuo6VafGQDm2jhZss34s10TQWrlrA4tULCYfDtF1VQOa6CKWlpUTbQSgdUkKFdE5OIj05k5Vxvfl+5er17x8qX6b0UsKZ68uUmkZ2ajJ5Cb1ZXVz7MnXJ2YPuXfeu/HsFaBuGtutbAWrx3W5JmVKjhXRJSiXUcXil32vb/ELi4uLqvI5KY5e5DatLkhquTA3y+6h6+dLSUiLpEG7LxjJl71zpZ6jue+rSYQ+6d6oi3vXZjiqUKTM5k7y2vZmZv6pOZeqStQcLCpawrDiPOWsXMmvxd0TWrKZ3+770bNeJLErIIURiyer6bduJfZi5LH+rbdtdcvagc5fdeWvpVGasmc30VT/x5dJvCZWWEEeYIW16MCijCwMT2rJHShYJoTi+jMbx3oJZlZepst94Yh9WF6XVukz57QawqjixTr/Zql6TuaaE0owSyAj2Qd1TU+iUmkpO+1F067xfrX9P0zq0Z1pyIrNXzmZOXtDK1n7JatrmFxIfF09pajHRrGAdfVLS6ZGSyqq0gSyJz9zsNe3WlFa6fNG6HNatiFb5+1iVnsTq9GQy4tbRPa0tI/scTM/2O1T+GaDO+8DKYtGh+2hmhRM56fOJLCxcRpTNqyyJoXj2Su/H7V33Z11iJ35cvW6r7m+69NiX7p13q/lzr//MxSVhPl6Xwvvz5rC8YBXhcAKpq0tJW1dCXFwcJSlRQqnB99QxIZmOCfGsSc+kIBpl6bpclhQsJByqYR9YzX65yv1N5jbMXLG81tt2fmpPVoXTy60jY+Va2q6LsColTGlmuPx2lNaTVaH0WpcpIymDVR235coFr/Lu8gojnyqY2PVAzmg/lNz49Fr9njasI9xlZLXbdmXban58D1aVZNT6GLm411AWduxR6Xa3Ii2O0qwwmdF1tIkW0CulDemhoZVud1Xt+7ukJlAYn0VBSRJrKWF1cT7xoThSiqKkFZYSSS6C5ODkMDMhTIeUNJb3P5TP1q2rtEwlpSWE2kaJZoXKypTUcfdK9x3V7W+q23+sTIuHTGgbV1ir/XJlx6O4lP706n4QvVO7sba0gFUla1i86EeWLJ1Dm3ASXTI7kJGeSJu4ZOJLVtVrf1Nd7Cr7nrJSsyhal8OPcxY03DGywve0OHsoC9vVrUyr0gYydXVe2fKbvqZesWuA+i8Z/Yik9iO/ZDX5JWtZVLSM+QtnkrhqHT0ysuiQ2YaMuGRSI+ugaCW5//mQLg+8UuU+oKIVvz2EzDMuJ7dgKfMKFjFv3SJmLp5O3qqltAkn0z89h+6Z7chJzKR7KMwNT27LHx/Zl759YcYMiIureR3TcqcxLXdaw23bFX4fQ9ospHfyF0GChAO/3nyiwS8nbtaY8uXCELPan0Vuwdpa7We3HXA03TrtWv59G/i4XW19qIrj0WbH1RrKVFWdqGIsqvqNd5mXx+9vK38F6Jlztmdt1wS6Jyewd4cPgsk3dn0Ceh23cVZ32OziQVEkgWtnXQLArbdeyF//msLJJwcT7JaWQkKFZCHFxRAXF2XcA3vx5oL3KYmWEiLEt3s9w8CCNmWf+53QDEbP/AsAcYQ4sf32nNfjKEqW/5PhiV8SIURcYnqQ/TZ7TDBgtbQAFv0PZj0ARPlycQIF7fdleNzrhCklLiEt6CSccxC06RN8pmVT4LMLgQjTihKZNuBKZq9bzZy8OfSctYwr/1C+d+PdN+xObp+M4LtNTmbAsql0Lf6KSEp3woMvhd4nlB8MX+E7W7EikYfb/ZrzZv6d6uyd3p87uo6jOCm77vW6CnWiivF+5pztWdqtzfrlk4hrG09hNJGSxGSiSanEhaIkl0RJLglRmBhHKL6A+NLVUFzAc19vD8DFV19NYnHtG9PfP3VPFo/es/bntnWs19VUv1mZFs/q9GQA+rVtQ7c2bShO6cLadTTYtl3xPCErLYvilC7MWtwwda7KypT5fj7bPPpmreOwIRZf7NC/Vsft3imF9EubRjhaTPzuDxPuvBcQXAQIhODb62H6xoE8keUh5g78B3/66Z9My/+O71b/XG79cYQYmJrDqLQeTOy8OzkJbfmK+Dqd2zZUu0R9z23ruvymv78Nv4+MrCGV/v7q+5uta528sjrUzu0PoQ29uOPnf/LWsql8k/8jS4tXEiZEhCipoUQGt+nGkNTuXNplb3qGwoQy+weD7bYwFg153CajX53K9Oj0Hvy0soTCcJSENolEo/EkFUZJiaxPWJUYgsQo8dEiUgmT1T6d4aNzuOK9q3h58bssLlpBRanhRHold+SOnkeyW1J7vu7Yqdxxu+Lx5YYb92V17+R6Hbc31CXyU3vy/Zo1Zd9r9fv+zc9VKy7/8Lk7sbZrUr3bHDOTMzfbLmoqU8U6dmm0lIJFCyhaupC0jl1JSI8nVLSsLHbXvjmUL2a3ITUzwh6jcygpiYMiiItEiRKCcAjCEUJhSAiFaJ8Rz/YfXE/XW+7fLGZVqfH4lRmcu2w4ZyvqM5qFmd3rdB5Zsqoza1aFK21niCSXEM0Mlt/wPeV02pVuPccQiURYU7qW/JI1LFw4i7XLF9EpLp0OGem0yUgkuXRN7faBle1ns/ake8e9yn8ZDbhtx6X3p7DDQH5eML1WZYqs7sH9L59EcSSBI4/NomPnJEpKwoRK1w8MDIWJhqOEohES40K0SQszaPKldYo1wE8j+9D74x9rvXxtfx8bvteUjBH8d80SLvru9hrf+/5uRzJ/3lAAsjrNY9Gajde1qt339x3BwvZdar2/qdhuWmP9txav2XT5gQlFDFs6mcTIGkK73E+o5y839OfeOHrg66vh2/UTYSyFyAUQrsNEDABfdI3jx0vOIDe0+XlhZb/xz0OZnP/jM6wurSTZRQXHtxvK/w09gVnp7er0PVXctqvbB3ZNCtOjzXfEUUBCvxNI7vtLQkTKDdQJzbqP8KyNv+lPC8J8Nuia2p+71OL4sum+v8eaCEMuf4O44tJaRiFQnBTHlIeuZVrCUr5fM5svl05nTeEqiqKlDGnTne0yutI3uRMHtOlJ20gBX0Wi/LR6NUtWL2TpumXEhUO0WVNE27URVqXGEWobJS1cQOfkZDomJ5L63xVs89j7dSpTbbftooQErr0kOLf9pvP7PLOo+tnFh6R04R89DmVo5934sLiAX3x6UaX1gg36JWXxeK+j2CG1C9+SWGX9t7LzhHYZI/gsmsjl39/Dz2sXUFBJAszuSR04ocMOnNdhBHOzu1db94Cafx+blqkhrtsWDx5DbrvsLTpGVrcd9UopZkjqG0HTxW5PBZNtV/TlxHLtSlW1KVV7Lbma9tw6XzOr5BhZn++pT/IoeiUNp5wGvm67qm0/ZuSvLFdXSV1dTFxcXKX1lequizRUW1p+uwF8v3xZpdtRZedTfTvvUvW1vEq+p2rPK2Cza2AA0zq057mC3Fq1SfdLhN4rviFaVEJS/1+QlDWMMBHC0QihaJRoCBLmP0PCvH+WvdcXC0P8uMlvtqrzhE3r2NXV47fkWvKGWPxn2vl880MPsrvDr07IJhoJEykJBxPlRkPrJ0xZn1g4BOlpkN5uKj99916D9cmoeL694brtiqJ85hcsZlHhMn5YOJ1l+QtJDSfRv202Xdtl0jkhg2yihArnMa9kBosLSkjOHkYkLkyYCAklURIiEAqtovuSuwmz8Zj4aQF81vePzC6Nr9X59tKf9uOnmR1YXbyGXv07ESmNI1wISaUQDoWJJEAoPkqUKCmE6dQ+mZF7ZHLbx7dyy4+PU1xx8Mt6CaE4zuy8Bxd23JkuWcPr9Ju946UdufP17enYtZRrrmlPmzZxlJaGiAuHNib6ZH2iz1JIToowsN1SwosWVr6OeuxvKmtL6xb/I/1K3iIaiiOuz69hmzMgc1jQ4XyDNXOCGVojhcFInKH/Dq4p1KJM1bWrN9b1por7p9XdBrC4bbuG2/fX4xpHxe0oecBudS5TtXWJSrbtJf12rPSY15DXbavrJ1Kb6yg1/WbT03qwrvcwphX8vNXKlPPEHAb+vRZZbzZRsf23pvrN4i7DKm3LqKpModI+3Dzzv7y8uJJRRhWckrkzr/zlVRYuz+Dss0PcdhuUlAQD+DckhN9UNBo8n7C0Dv07C36GNTcHy+z1cnDNqKIvJ9bp+uKWXE/YcIzs3Gd/Hs+bzo2zah6Ne1qnXflzp93o2nGHqvflW3D9cqvVNet4/bKqNukq3x/KraNo3XKunRLM5jm4TwmL1jTstR2A7DbZdGnbBXr3qtO2Xde+BvUpU1LbzHJtaZu+ZkuuWWz6/oWrVjZYnXzTMmUntuXLlcGA8y4HdGHu6rm12t9U+/ur8PugaAXFhct4bF0up3x3byW96sobkNSJU1dezAXXjwdqn7zilZff4dvPvmHZurXEpyYSicSTUhgluThKXFyY0kQIJUUhGqVNKI4u7drQY6cO/PTdBw1W/41rFyU1XESbcCGdU1Lpnr03r6xdyQXTb62x/L/vtAd/6jSS5Qntq+67XUmZ1nQazI25b/LfJR/UuI5buh3Aru1HMn9tSd36pSX35prc93hzWfWjT/Zu258ncjqQHfkoSDJzyPfl64obfDlxs31/0fIQb3SfyEdr5/Htqp/5YsW3FJcUsSZSyODUbgxN70H/1Gx+kTGADtGSOl9vqs95ZLWv2cK+K/lLBnLaTddTWBTPQw/FceKJQV+NcLjy/kHFxTB6NHz4IbVOcgfw5eevMuubys/x6tUnuR7tULWtY1fVt6liXbOmtrTj8v9DUmRd5YmzqkiA+OVCmJX6C3JpU6vj9tTMzlzyc9AmEAJO6XE4v0vfF1auBOD96EzOnf9I2fMntt+eCT2OqbRvSYMdj4aOYllytEH7Utb5eLRJX8peaXHsmfxR0B449EoYfNnGL3zD9YevrthsXzCtIMy0atrWK15HSc9fS2R1ASUJSSRkdiMOSCopIXH9bHnR+HWEQmsJl64lOVTEC+8eyL0vHUpaRgGXX55F27bxRCJhiEKIEKHwhuIFgy5TkqOEeJsfp1e9HVX8jffutDMFiR343ZdX89WqWawozqeiDvFt2CmtO3/ruj8Jeb15aU423y5bTHaPLEIkEI3EkxSBpOIo0UQgIUooGiUlFEendsn0Hh7lp+/er9X1hO+/24M/3H0JSUlBcoysrM2KU6nq9h8VjxUdU1J4pzSeP81+npJaJCPaP70f9ww8m5fXzuesr2+ocflLcsby64xBnDT/FT7M3zh4OT0+jQTiIBKhgGLWRDaOZftlu8E8NORCkjK2K/9m1ez76zMGoq7tDNW2g1ZSplofv6De/RZrXa+roq21Ntc4Vi7rxW23HMw7H2xPKFTKIYfEceihsN9+QQLdaBTmzoVXX4UvvoBzznqVZd88w47Rp0gLrSEclxRMYpZzYJCsNpwIed/Ah7+GaCmnLoKH8oO5VwA+3P0hdmk3pNxx+5i5t/Dc0k8pXT+b9L9GXcaKrB61vm779BNHcd/fD6BTp1Luvz+Ogw8OjttFFS4JhUJBn8wOHWDtWjj9dLjnHmqlYv/fqsq04Rg5ZvVntC+dAz2Ogd3/ufkbfjmx3H52eSkcMxfeqOW13h3fe4ypr/+KPn2izJgRIj4+6HNaWZtB2So/m0Tct9cziLeJAnHdD4O+p0DHPSAxY+OCyz+DV0dCtJgvFyeQ1+5gdox7haRQIeEQkNQRuh4ctCtGimDJh7A0uAZZ2z6kq3onbdJPOkLXwlfYKemzoF9rKArtd4TO+0BC22DSmwX/hbyveX41HL6+2SMuFOaividx9aAzy9U1z19wH3+b8x9K1v+e/tHzJNoldOPtqenceefZlJYkEI1W3uk7HC5h2LB4HnrgVf7z4pvccuu5rFyezYYsGqFQMGfW2rXB9w1Rdtghyv0vfV6r/uEbfrOPP3osDzw4ls6dS7n77mCbi4sL6pWbjs6Oi4Nlyzaec730Ehx0UK1+IjXWNevSflPVue2SfjvyUaiw1u2/dW3fmz93IMtzk1i2dg0lCVEgkZSCKGnFwcQS0ZQQoaQoISKkxyXQJ1rE3ldcTriwdhPG3MkZnMWdZHeO8N77Yfr23Ti3RWWKi2H6N6/y76dyufmOo1i7No1OncKceCKMHRsknd2QLOedd4L95jffRLnnrteqjEVl55ErMvtyzeI3eaeG8VAAd3c/kCPTltCpdAqRjCGE93gmSBgcLV3fdz0Ma+etT9Y0H947ltJIEY8siuPUVdGy/W5V2oSTeKTXkfTosxufpSTVWO8vv23XfgxEfcbkVezjA9W0pSWnMarkB7qv/ZZI+mDCe/47mMwlUhIcHEJxFRLpHQ3RIr5cFM+sdr+vsh100zJlxadx9b/PZ8GSjozaI5Ff/rIdJSVxREtDG7v5hILJUMLhKKEopLUBun7HC9//p1bb0fv/OZK/3380HTvC4sU1/jyAmo9fFWNX2bWd6vo29UhOoc/yr+hVNIVIai/CI/4aHCPCCcH3SyT4bld+C+8dA9Eivl4cR3ZWZ7LCCyhN6UbcdhcHfRSSOpQv/CbXtGo6vlTWh6NkxVqGlj5Fj/j5RKJBd0g6jIT0gUEs8qbDso8ByF0dpkubCJGkLoR3fzyYVCgaXT8BbwjWzA1+H+ty4b1jgwxdKxNh2LOVX2erUA+c8k0K4678JavWpnDddWEmTNikTb/CWJGS9T/LLxZXPvaoIa+j/DBjKJdc8muWLs9g1Kgol1wSZsyYYF+2qYKCIq6//lqg8vblyvpu1+ZctaH6P1Q8HjX0+fbQ7iPo26ZH+S+lhjp5dePW6/M9bUmbdKfENnySNzr4fe1awpzVtTtu17U/zcLkLK5Z8Ba3/1xzw9jpHXfjz513ZWlCu1pdh930+kNl7SsN1W5Vn7H0dT1nq8+4jNr2+9hQr/th6VD+dOVvWLY8nd13h0svDbH33pXXcX7+GXokzufLGe/w28+v4LP8GVXGLSkUz2P9fs2BaV35IZRS67bWnskl9G8zlZRoPmx7IaFhVwXt0pGi4PwR1h8rvipLqAwwrTCB53J+x5y1eVvcf6+hrjdVuz+ooU06d9VCXnj6PL76dG+ilD9xS0go4JJLgonBLj7gABLj4zd//0p+T8BWbSfPTkomp+eYhh2PsgVtJbUdb9sY+9mKv49eOYMqXb6+Y64a4hgZl96fXn0PKv+bbeB2q+r2mbUdS19T7Gq7769PmXokpjPjs2FA7ccb/BBdyfkrgzpkfCiOi/qdxFUDzyh3jHy7+Ev2+vTCYBnC/LbNzozLHlNj7Das429rv+KtwoVl52vf7f1vBrTpVW47unrFc1z+87/Llrm923F0Te5b775NW7qfrdgmHSrsynm3XMHMH7vzy19GueeeMBkZwXk1bLzWFokEt8RE2Of+3Xkn9yNK14+VnjPmZbqtDpf9ZkvaRMn++vcsK1kd/Ebi2/Dythcye23RVmv7qNhPpCGOR5uWqXNyBg+9cDzLV6YwZIdkdhnVnkgkDkohtP60nnAIQsF5ZHwI0tuGad/xCz6Y8sxW29/U6Xy7nvNk1LVMde0r1xjzZNR2v7zp567uc2xJmbbaONIG6G/V69NwvcZvVzXWrLLfU63rK1tQJ68udg1xbefgK3/By1P7c+CB8HIlCacqU9s5S/qkpPPVG/vz15t/A8DXX0fZbruNo60qzhYa2vgUX37+Ku999Eytt+26fk917XOalZbF6m4DmFKav9XapOva36qmOtSWtEtsSZ/kuvZbrGsfn5q2o4aY/6Gu9d/EHrvz25kP8tO6BdQknjAP9DyCMe+uq9N8RNXtn2rbR7C6eRD6FsAuF/6buKLKxz5UZmqPeD7/x1XMDtfuulxGcjtm5CUw/qu/Vzr33qYOyxzCdTl7U5SUXav2my253lTX8U019UnesHyftLbMXjwQqHu7ZnXnIk113K52ztl6jMlrir5NdW5rbduXLyNR3vv+jRqP2/Xta1vT8aiyuVQ7tt+V+fFZTFn5Dd+t/pkvl3/L6sLVFEZLgr6Umd3pk9yJg9v2pn0kn/nFX7OkoIiETtsSSkoPxlyVRkkojQKr6bb4DsJs3PY/nJ3GjKTfklucTF7RakLhBFJXl5BeGKU0EiGaFiKUGiU5WkT7+ETaJqawLiOdOavns2TdQuLig+FoDTH+bUvmyVjVth/50ZRaz5NR03jKphi306H7aH4MJ/GH6bfx45p5rKpkTH33pA4c0W4wf+w4ktzsng3at6mpxhI1xnjbxp4nrjZlqrZvfwPMN15j/aYB5m6u8Xw7s8L8ndV8hk3LVNvP3ShzoNexr0FDlGlQn0Madq74Sj5Drefj3IrXmyr+PjoNOIReO55CbcVs8oqioiJSU1N55plnOOKII8oeP/fcc/n88895++23N3vNnnvuyfDhw7ntttvKHnvuuec49thjWbt2LQkJCfTo0YPzzjuP8847r2yZW265hVtvvZXZs2fXar0//vgjffv2Zdq0aQwfvnHHfthhh5GZmcnDDz9cq89Yl+BKktSalERK+Hzh58xcNpPdeuxGj4weNb9ILdKytct4ZeYr3PvpvXRM68g5O5/D7j12JyEuoeYXS2rZKku8l5sbDETOzIRNEgECwf8VH6uFdeuCzv8rVgRvHYmwPttq8PyGjjSZmbD99tUPDGswkdKgoaF4ZdAgHymGaCQYeFK0PBiIUrQ8KGTnvSCrkkypKm/iRLjiihoXA4KR7ecAOwFdD4Kd7oa07sFz0Sis+Rle2rbS5BVffnkx//53FaOeKpi9cjYD7hhAYWkhIUL0bd+X0T1Hlz3/35n/JXd1LlGitE9uz8xzZtL+8wnwUzAAn20vgqFXBJ19I8VBVttoBFZMg1d33nyFPY6Fne8JklxEioNBJQBLP4HXRm5cbtynsGEQ77RpwWisTX36Keyw/vmp58D3d0BqtyBrb1KHje8LGwcC5U2HD0/YbB3RaJRvl3zLo18+yuyVs/n1sF8zutdoUhMqJL+oq7rEG+Dyy4PX1KCoqIhrrw0GbmzWoXjD/gkadB+lGlR3rICtF4toFIgGAwTXLYSCRcGtaGUwIK6yDNZSK1YSKWHW8ll0TOtI+5T2my8wZ87GiyoA06fDCZscFx57DAYN2vj/o4/CrbfWrRDx8cGov9qKiwtmNKitWh4rytlKx6Mt0kh1bDUD9TlGhsMbT4Rqs3w9fx/RaJRP5n/CnVPu5NEvN05iec7Iczh9xOls23Hb8vWuiy8msaqZBWpSsT67aV22NstX9pqK321N+7SK31OkeP05XmlQf1+XC4VLgvO9OXNgzB+hlhMxlElODrIy9qh9G+mMpTPY66G9WLhmY4eHpLgkCkuDiYfCoTDn7HwOt4y7pebPDOU/d24uHHUUFBZSazV9hnW5G2+V1blqE7u67pfremyBesWiThpi2970NZssX1RSwrX//S8QbHcJCQl8mvsp9316H/dPCxKH7N93fyaMmsA+vfchvrKJEYHVRat566e3eGfOO4zrN45du+9Kcnxy/T9zFZatXcba4rV0S++2SXK5TT5fXX6z0PyOeXPmwIABUFBQ+9ds+P3ldAi2k6IVQZLLaCS4FS4J2pMKVwT7IduU1NxV3Pff/RbcWH0y1M00Rh07Fmxo49sQizZ9oOOoRi3CvPx5vDjjRSJEOGSbQ1rnteGfHoMPTwzaV/d5PZhwjvUTU0GNba1Sq9RU7b+18PDnD3P1u1czc/nMzZ7bIXsHrtn3Gvbsuj+ZmcHg/dtvhzPPrHkSynrJ+xaWfwqrfggmaQsnQlwSxKUGo1EL86A4b30n5+UQToL+pzfKvvyHZT9w5TtXljv/3+DYbY/lsj0vY3DnwVu9HK1Bg7WVqNE1duwKSgq46u2ruGvqXawoKJ9kcqcuOzF+l/EcP/R4IOgrMXt2cAq6fHlwChoKBfupaJSypF4QTHh39NGVT/rfHKwtWsvdU+/m5g9vJnd1+WPHH3f7I2ePPJuctjlbtI53fn6HGz64gZdnlh8gnBiXyFk7ncVloy8jMzlzi9YRjUb5aN5H3D317rJ954lDT+T3O/6eXbrtErSBFC6DmXfD7KcgrVcwoWTmUGjTCxLSg34D6xbBunnBBKerfwomC+5+RExdw3z0Ufj1r4P7q1cHExTXZNWqoElxxoyguhEXF2wDqanlJ3iAYHtJSYFTTgmaEVu0uralLbwOVv4LskbBbk9C2vrzs0hJ0J/m5cFBsr2K9vug1vWPaDTKic+dyONfPV7jsn3b9eXrM77eKm2QzV7+DJj3H1j5DSRlQXIWJLRb33cnHoryoWhp0A9tzTwoWQUph0G058b3qOkaR1bW1mvvbkAFJQXMy59Hj4weJMY1wLG2DtcT1pLCjaNf5sGf96ZPHzj5ZNhpp+BrS62k+9OKFcEmt+22dS/WCzNe4LCnDqt2mdE9R/Pmb94sazePRCK8MOMFbvv4Nt6a/VbZcttmbctFu1/EsdsdW7b9FJQU0O2v3Vi2blm169il6y68f8r7hEMNfXKjStXiGthRR8HzzweJKv75T9h99+BctOJEymWP5X0L/x0eXK/ssPP6/XnP8n0Kl02FV4O6w1eFMHT9HELx4Xgm7DKB6/e7vux9C0oKaHd9OwpKCogLxbFnzz154zdvVP85NvkMr78eJNqAILnGttvWfHydOROeeQamToXu3SE7O/j82dlB3TUxMbjMV1wc1HXXroVf75cbJIzcoC7XeaMRKFkDJas3uc67MLj2EooL6miRQkraDmLQ07/mh+U/VFv+U3c4laGz7+Pss4NVfPIJdOsWlDcU2vzzRyJBF5eEOQ/Cx78N4rTni5Czf7CfD6+vqFfVhrihb2la96A/bJexQCj4LIRg5ZcwaZP41KUPKcCUM4I6KkD3o2CHvwZ1hEhJsN5QuGwd0SjsMBe+KgpTGo3QKa0T8yfML7v2WFRaROebOrOyYCVxoTh2ytmJD075gA8/DLHXXsH3EInA8OEwYQLsuWcQ759/hjvuCLaBwYPhhRdgxx2D7kqlpbDHHnDWWXDkkcH3W1oK//1v0GazZEnwMWvr2WeD7S4Ugu+/h549N9/eNhWNwoUXBolWBg+GG24IjhXJ1VRfSkpaQT2zvir2M4Mq+zb99ooePPhCFjvuCFOmlD+PrcpnnwW/DYDf/Cb43WyY5H3Tc94NSWiXLYOOHev3USbPmszNH97Mq7NeLfd4emI6Z+18Fn/a40+k5X0Jk9dPbnTgl5Cx3cbrAlBlgjiA5SOf4MzPXuCpb57a7LmkuCROGnYStx5wa+V15dps283J6p/ghT7B/b0nQfbY8sGu5nti9EvBeIBmIBIJjl0zZsD8+Rt/c6mpm7e5bNgP/N//Vdgf1Cd21fWf+uZa+OJPkNwJxn0GyR03HwtQ6XcbhszBMPaDoE26DuMHaiwTBO3Zr+8VJNSKRmDA2TBwQlBn2WD5tPLHL4Bx0yBzSCWJ4bfs93H22cH+Yttt4Ztvaly8USxZEnyFCxYEVZqHHqr6+GH7csvW2PH7ctGXTHxrIs9999xmzx064FAuH305O3RppONFa+gDVkeLFwfbdm5u0L75wAPV1w0ru/a4tngt785+l39/+2+G5wznsAGHbVn7+Lc3wOcXQXwbOHbV5s/XZj/b0uoelbjtNhg/vvLnEhKKuOQS97NSY6vPMbK4tJguN3cpawMd1nkYn//u83LLXPz6xdz04U2URII+5J+e9mmdjn1PfvUkxz97fNn/fz/k75yyQ/lJ4vZ/dH8m/ziZKFHiw/Esv3A5bZPa1nodm2ng/ey55wb13379gvOX2pxvv/XzW+z9cDBBXzgU5rp9r+MPu/2h7PlXf3iVcY+PA4Jk17eNu42zR55dr/LVWys4HkmNrhn332tuIpGgPr9kSXA9cPXqjY9v2I9uGNrToQOMHFn7foSRCHz4YdCmvXhx8PrMzOCWnh60K4XDQbt3cfHG5tUzz6y+7VpqbpatXUaXm7tQHKk+U/zTRz/Nsdsd2/zGSm/JOLAN/TLqUF95ZeYr3D3lbl6a+VK5x/+85585bcRpdE3vWtdP0OzYrhlbWnS8m8GYqwbXEPu0ZmpN0RryCvPo0qbL5uOSJSmG1SW/Qavq0pSYmMiIESOYPHlyuSQSkydP5rDDKu+wO2rUKF588cVyj7322mvsuOOOJKw/Ex81ahSTJ08ul7zitddeY9ddd631env37k12djaTJ08uS15RVFTE22+/zfXXb+zAKUmSKhcfjmfHnB3ZMWfHpi6KtrIOqR04cdiJnDjsxKYuiqTG1kgXp1NSgoFDPXvWvGyjCccFA4qTs5q6JK3H6afDoYeWf6ymDhKZRRD9BmbcGgyACIUhqSMQB31Pg9LVQY+B1YtgVvCSzz8P2uC7rr+WV9XkHaWl0DOzJycMPYF/fPYPokT5YfkPzFoevFHFTPcX7HoB7Vd/Bz+tT3a5873Q99SNvb7CCRsvaOR/X2FtIej1K9j10WDwxoblIXjNqs0nVqqVaBR+uBeIwsDzgoHwtR3osS64EBwKhdiu03ZcN+a6+pWhKtXFu6qLzXW1/fbBqEc1rabqyBQKAaFgv5DWfWOCGylGxYfjGZA1oPIna3NxuuJAoqQkeOml8tt3dcftDZOk12WC8fj4YPaGytbRUMeKxjge1VWMdgCNSc041qFQiJHdRjKy20juPPBOZiybwZBOQ0iKT9ryN68sWc6mKv5fWLhxFoLKnq/ssZoS7FTcp1WcNDucUH7AdmIGMDC43wP4/qiqJ2KAyvcf9Zg8akDWAHIvyOX5757nuH8fx7qSdWWJK34z7Dfcsv8ttEtpFyx87701T9JU8XM39EwaKV2C2wa5ueVnEKlN7A4/vG775dLSzU/qtkIs6mRrbttFRUFv9vVCoVBZG/y9B99LlGitJqJqk9iGgwcczMEDDt465VyvQ2oHOtCh8ifr85ttTRPcx6cFt9SW39FYMa7ivv+8feCXvy+/TG0GQGnLpfXYOBlpE+mW3o3f7/T7mhdsqSIl8Mmpwf3tLoGOu29sf4JatbVKrVIzPrf9zfa/4dfDfs2rs17lgMcPACCnbQ7P/eI5du66McH4Rx8Fg/rHj4evv4Zf/jIYQ9a2kjkHioqCiRa32aaOhcnYNrg1Q/069OORIx7hbwf8javeuYqnv36aA7c5kKv3uZqsVK+DSltDcnwyV+17FVfsfQX//Oaf/GHyH+iU1on7D7mfETnlB7ampMDAgcGtpUtNTOX8Xc9nwqgJvPHTG9w/7X4O6n8Qxw05rsoEnHW1Z6892bPXnszJm8OEVycwLXcal+15GScMPYGEuIYZ7R8KhRjVfRSjuo/i4cMfLnusnKQOMPjS4BYphYKFsHYuLP8copskzg0nBImMOuwIab2DAZEx5IgjgokY7roLxo6Fv/41mCB4w+QPGxK0bDoZRFwc7LVXcIsp9WlLu+ocGNEfvr46mMQ7LhFScoIJS7c5Z+PE3utyIVIE2/2pTgNyQ6EQdx14F//85p81Tkrw5FFPxmbiCoD0AbDtRZU/F40GMQjFbexbVJ/rti1kUHFyfDL92vdruDesw3XeVODyLl24vAvk5QV1+hkz4J13golkNtzC4eCWmAh9+9Yvsd2hAw5l3SXrOP+187lryl3lnuud2Zt/HfuvzSZRC4fDHD7ocA4fdDizV87m+RnPs0/vfRjcafMkcsnxySy8YCFHPn0kL34fjKvLSMpgddFqSqOlAJy505ncceAddSu46m7Ta541XAP71+uZPPtsH0IheOqpYLIjqHwyooQEgv3DlDODfoTpg2DM25S1QW3apzB/RtnrhiTB7snwQUGIkkgJj3/5OKcMP6WsnvLGT29QUBLsW0qjpYzfZXzlk8xW8RmWT80EgrpKjx612zb694c//an8YyUlwbn1hqQVcXHBZ46PD7a90BU1HPOqu3YUCkNC2+C2QSVtpvHAzLNncsP7N3DR65vvo9slt+OxIx/jwP4HAkGikXvvhYMPhj59YOjQYFLsrKygvh4KBbvtlSuhYEUuv0w5I3ijoX+BLuszfmyauKKqNsRoKbTbHvZ9I7iGFIrb+Lm21JIPNyau2PaPsP21m/RT3bwuHgrBNR3gwAXBMovXLCb7puyy/gIFxQWsLFgJBL+na/a9hiVLQhx66MbLt488Ar/6VfkkLR07BvMWX3cdnHNOcGl46dJgf3vHHUHdsLh442XsuDjYf//gu3/llbp95Nmzg7/JycEkjjUJheDGG+EvfwkStHz/PbzxRpA8rWKStVAoSLbSsSOcd16MJrDo0aPWdY8r74QVYfjPf4KuY5ddBkOGVN13u6QkSFgRCgUJTR54oOr33vDdt29ft+Jvar+++7Ff3/34ccWPTHh1AtOXTGfiXhM5drtjiduw7aZkQygBiMCKLyBjcO1mBQXap/fiyaOf5K6D7uK6967jhg9uAOCafa7h3F3OJTVhk0xaNfWnqfhYc0tiltwZkrODpEELJkGX/csnXapO4hYEsYGFw7DzzsGt2Vj6cfC33faQWpeJzSOw21NBsuQ6jh+ola+vDhJXEAoSbfX8Re1eV9djWy1/H/vvHxyzZ8+GyZODxFtFRVUPJagskVhDu+++IHFFejrcf3+w64jJ44Ya3NDOQ3n2F8+yaPUi/vDaH3hx5ouM7TOWW8bdssUJgussBvuA/f3vwalUmzbBdg7Vb9uVnT+lJqSyf7/92b/f/g1TqE57BYkrStfBT49B7xOC43AovuY6SzM6Dm+JZcvg0kubuhSSGkJCXAInbX8St350K6XRUr5Y9AWL1yymU1qnsmVenvkyJZESQoQYmDWQ4dnD67SOA/sfSHw4npJICfHheN6b+1655BWlkVLen/t+Wb/sMb3HbFniiq2gXbugTSU/P5h8PTm55rrm6J6j2bnrzkyZP4VINMJV71zFp7mflj3/4bwPCREiSpSM5Az+b4f/28qfQlKDaMb995qbcDhIsJ2dvXXee7fdgpvUmnVI7cDaS9YyftJ47pxyJwDxoXhKosG48R2yd+Cfx/yTvu37Bi9obvuoHj2CzgK1TNANbFFb/IH9D+TA/gcyP38+D3z2AAM6DOCobY/aeP1BUuNpBmOuVHtpiWmkJabVvKAkqUqt7rL0hAkTOPHEE9lxxx0ZNWoU9913H3PmzOF3v/sdEGTWmj9/Po888ggAv/vd77jjjjuYMGECp556Kh9++CH/+Mc/ePLJJ8ve89xzz2XPPffk+uuv57DDDuP555/n9ddf57333qv1ekOhEOPHj+eaa66hf//+9O/fn2uuuYbU1FSOP/54JEmSJElSA6r3xcddal6kqAg+CDJ4h8PBwKeTTw4mQNhtN8jIKL/4smXw1VfBhAd3HXgXT379JGuL1wKbJ60A6JTaiYt2uwgm7xoMGmy/A/Q7rfxC1Q30iG8DO9wSDAjcdEBGVa+py8CQuJRgooHCZXUb7LG1OyA3t4vNkqS6CYWCA2pdOt18/32jdeqpNY9HUo3aJrVtuOS09Zl0qTbqkmCnISbNrsNEDA3hsIGHMW/CPA5/6nBmLJvBg4c9WDZZSpn6JAOsLvFDQ+yXY3BgalMKhUKEqHlyjGajPr/Z5nbMbuROy1KLYP1arVlxHpSur8emD4JK2omr1Eome5BaolAoxLh+4yi5rIS8wjzaJbfbbILx4cODSWuXLIGpU+HDD4NJ8eLjg4mkSks3TmJbWBhMUnn++VVPsNdSZSZnctPYm7hp7E1NXRQpZsSF4zhuyHEcN+S4pi5KowqFQuzbZ1/27bPvVltHj4we/OvYf221999gs6QVlQnHBckrTWC5mTZtgkmKzz8/yNd6zz1wxhnBZDs5OUEzb2IirFsXNCn/+CP07BlMeLy1J5dsdurblraVz9HTk9P59LRP2f3B3ckvzAfgt8N/y8OfP0xptJRwKMwjhz/CTl132qrlaLFCoWACQdVPPX/jGRkwbFhw21qS45O588A72a/Pfhzx9BEAnDD0BO468K4aJzjrmdmTc0aeU+0y8eF4XjjuBW758BYmvDaBvMK8suee+8VzHD7w8C3+DKpBHa953serhOjF2LFh9tyzFu+/6E1Y/FZwf8f1iUhqMeH0aenwXkHQZjV/9XwG3Dmg0rdvm9iWg/ofBFf+pdaJIg6gDXv3+oK35/ThmGPguecgNTWYIK+ySfGqmig6Pr6GSfTqkJgG2KJj3YW7XciePfdkv0f3Y3XRagBGdBnBC8e9UG7C3+23h7vX530oLQ0S4CxbFoR/9ergO0hODia76tZ9OsxYH5cex27eX7NwaeX9RzcY9UjQl7RivAuXQl4lk9jX1peXBv1a2/aHYVcHj1Xsp1phHeNSIS0+hTUl6wBYtm5ZpW+dkZTB3r335rrrYMWK4Pt4+OEgOSiUr7dtaEvJzoZTT4UD11/yvuqqoB5YcflN/x83rm4f+Ygj4OabYeFCmDAhSJRW3STlJSVB209ycpBgZkOSGW25bt2CfcYPPwQJQe65J+if3a5dkDw2bn0er5KSICnIhv7bEMStpKTmyTcbop2uT7s+/OeX/6n8yTa9Yez78O6R8NFvYMVn0OckyNgu2JbSesAhM4LtCGDtfMj7FjrtWZYgrl1KO67f73om7jURgJSElPLrqM2xBcr3sWhuScziU+HAr+CT02DGbbBiGvQ5BbL3gdRum39PedNh5VfQ7bA6JdJrluqaeATq1ncge1+Y/zwsmwKrZgYJMDc9Vmz63a7LhdxX4fvbg+dSulSaqKhSS4HvlsCiaZWXedP/S/Ng1h1B8qUB46HHMZu/35o5lR+/3j4UdnsCOu4WjJ2IlgTJFg+eDgWLgWjwWYpWQJu+tf59HHwwTJsGF18MBx0E++4bJLQYPTqoMqSkBPv6goLgmDV9Ohx2WK3eut7Wrg32campMdiWoUbRuU1nHjnykaYtRGvoA1ZHRUXB39pMEt5osnaGg76Gz/4In5wKP9wLXQ+BTnsEx42EdDhgGqxdAKt/Co7TBYtg0AUt/zi83tVXB23JklqH3wz7DTd/eHPZ/6c8fwrbdtwWgDXFa/hq8Vcbn9skgWttZSRnsHevvfnfT/+jJFLCmz+9We75rxd/zZriNQBEohGO2vao+n6UreaSS2D5crj9dhg1Cm66KagDbzg2lQa5jsudM4dCIX653S/5ZP4nAOQX5fPMt8+UPR/ZkOwU2KfXPpufu0qSJBFcr77jwDvYu9feHP3M0WWJK36/4++5ddytJMZVkU22uajruNA5c4KGxw3q0f7bNb0rl42+rI4FlaQaOLZVklSN5nIJq8H84he/YNmyZVx55ZXk5uYyePBgXnnlFXr27AlAbm4uc+bMKVu+d+/evPLKK5x33nnceeed5OTk8Le//Y2jjtrY2Lvrrrvy1FNPcemll3LZZZfRt29fnn76aUZu0nOspvUCXHjhhaxbt44zzjiDFStWMHLkSF577TXatm1eGZElSZIkSVLtfP11MAjq3XfhrbfgoYdg7tzguWg0GCDQq1cwSHn33SExPpGXj3uZfR/ZlwgR4kJx3LL/LZwzKRgonBSXxP9+8z/ClMKyj4M36vNbiBRDeJNRBtUNPMzaBZKzNn+8qtcUrazdhw2FYOf74P1fwvQbodNo6LIfREqCgSgVBwKtyw2SXLTt32o6IEuSaqGxLk438mTvkmJYfRLsNHPtU9rzzsnvVL1Ac5wsPAYHpqoOmuNvtj6s30hS7EhsD6ndYd0CmPcf6Hls+ecra2stWglt+tjWKjUDceE42qdUn0imY0c44IDgJkmSGk/v3hsnK95UcXFwS04OJpeMac24LW1I5yG8dsJr7P7g7pRESnj8y8cpjQYzIt114F38auivmriELYyDiluVwwcezsLzF7KycCUDOlSeRGBLnDfqPLqld+PYfwVtFB+e8iG7dNulwdejLZdPOlHCZFXSPbDyF3wHhIJrnp32qHUChGPawkmLQ0RqSLq6Z889iQvH1SlRRFtgUocUrvoH3HlnMBn9MccECQWGDYO0tCDx1Jo1kJcX9MucPj1Ytk4a+Zi3S7dd+O7M7zjkyUPIaZvDv479F8nxyVUuHxcHffsGt0otbwcz1t9fMydoT9x0wvCkLAgnV94ntOtBkDm4/GNVJCoBgvbH2lgzGxa9Edzf7uJgkvGKiSsqWUcoBJcP/yUXTnmw2re/dt9riUbhvvuCxBVjx5afW78y8fHwyCPB3/bt4cILg/VVp671wV694JNP4OST4ZZbgsSlJ54YTFLeq1f5ZdetgzffDOYduvTSuq1HtdevX3CryYsvbtw1de3ajCaE7rATHPoTLPwfLHgZPvk9FC6B5E5B0oZwMpSug5K1weOZw2DQhM3epsqJP5curTlxRUUFBcHrmlNdMDkL9nw2SECQ+yos/wzmPRfssyLFQfK2aEmQUCe5M7QfEXy3LVl9Eo9AcOD89783HveqSxTBbtBjAsz5K0weDUMuh17HBRORQ5AAYkOCEAjGAfz0CBSvgu9uhqF/Kf/elV3T+mkm/PYiKDy5dp/hYOAXQHwibPdHoMKOvKpj2LDrYMXn8MbYILFG9n7QbhjEt4W4ZChZA8X5sOyjYFL1fSZXXZ5KDB4c7EfWroWPP4ZZs4Kved68IETRaJBgKzs7WLa0dOsmqj7iCLjxRpg/H/7xDzjppNaXGFtqzu1WW8vRR8MNN8DixXDrrXDOOc2k/TKtJ+z+JJQWwvKpkP89LHgV1s4J6inRUgglBMfg9AHQ/fBgLFsrsGpVkHRww0Ttklq+IZ2H0CaxTVnC0Vd+eIVXZ70KlE+wECXK0dseXa91HDnoSCb/GNQ3Z+fN5uT/nExqQipAueQYAIdsc0i91rE1JSTA3/4Gp50Gjz8etK8sWADDhwdtd2lpwfFpzRpYsiRo/3jtNTh35Ln86Y0/UVAS1NWj0SihUIhotHyb4u0H3N4UH0uSJLUgR217FJ+d/hlnvXIWB29zMH/c/Y9NXaSGV9/23+aWfFpS6+XYVklSFZpLd5sGdcYZZ3BGZaMOgIceemizx0aPHs20TTPRVeLoo4/m6KOrb2Subr0QZA2eOHEiEydOrPZ9JEmSJElSyxAKwXbbBbfa2qv3Xlyy5yX85Z2/UBot5c4pG0dV3jruVgZ3GhwMltggPpXNBmFUN/Bwk05zNb5mKfBjMaxY3y5ScbDKZo/1g23+Cj9fCW/uD92OhD6/gQ47Q0rnYABKWg8oLQjKsXaek6lJUizy4rSkxlCfSZcKC4MB25UtD07U1JzF4MBUSZLUioVCMPoFeHUXmP00tO0LQyauz4gcFzy/oa0VNk9uLEmSJKlOEhKCm5q/kd1Gct/B9/HbF35LYWkhAKeNOI3Tdzy9iUvWQnndtlXp3KYzndt03mrvf8x2x5DfLx+Atkltt9p6VEFl1zyruX459KruTH0hynvvhSgoCOYqqVZcMhAN2p0ixRBX4VppFf0Qk8MwpttOvDbvk7LHwqEw0WiU6CYJLW4bd1twp47X8hKBK6+EP/8Z3n8/mOh/8mS4/fYgYUVJSXDs7toVBg6E3XcPkhk0i0lcq9E1vSvTTq9+jGqttdseuh4aTGw/5XQ44DOIsDGBRWWThb/3CyhdE0zgXrFNsYpEJUCQOLc21i3cpHzDN2+zrGYd5w/Ymwd/+ojvln5HlCi/GfYbikuLeeLrJwgRYlj2MH6/0+9591346afgNaeeGiQgq64et2YN/OtfwW/mlFO23m8kJwdefRV+/BGefRamToUHHgj+D4eDMhYUBJvsdtvBbrtt/UnMVbPevTfef++9IJFFs0lgEY6HnP2D2walhUGCgGgxhBPXT8CfWPf3zsoKDhB1SWCRnEztMyM1suRO0PvE4KbKFRbCwQdX/Xxlk5199j9Y/Tx8NRGmngUddw2SVsSnB4mJilfC2vlBEpU9n4M39oNvrg3qFNv9KRjfECkKJi5P6wEpXYEotN8B1kzZPGFWdboEL6XdsGAS9M0+XxXHl9RusN1FwTFv1SxYNTO4rVu4cTtKyoLev4b0geuvw9WQ4agSqamw997BrSntuCM8/DD86ldw1llBEosJE6BNm+A4GFk/hKQeH1FSExo8GJ55Bg4/HC66KJjH8uKLoWPHYLsuKQmWC4eDekxN9eMGF5cEHXcLbjHiX/8qX42Kj4ff/x7OPjuIyS23QCVTFklq5sb2Gcuz3z0LBAkrIpWMv81KzaJnZs96vf8+vfcp9/+jXz5KeH2duCRSUvZ4elL6Vm3j3VKDB8O11wa3aDRIrjR7dpCsYkPytu7dgzY7gHA4zEW7XcQVb18BQGJcIocPPJy3fn6LRWsWAXDoNoeSk57TVB9JkiS1INtnb897v32vqYshSZIkqYLm0tVGkiRJkiQpZlyyxyU8+fWT/LD8B2YsmwHAqG6jOG3EacEC8WmQkBkM/Fj6MfSqMGiksoGHPz0Cc56BpR8E/yd3Lj/wY9PXrMuFn36A314IhSdXX9jKBqx8+xlE3od5z8OU38G6BUF5E9pApAQKF0M4CbofA/2dQECSJElbiZMuSZIkqaVqtz3s8xp8dAp8fVWQxKL3b6Dj7tB+eDCxYKQEVn0PS96H5Z/BLn9v6lJLkiRJ0lZ38vCTeWXmK/xr+r8AuP2A25u4RFLsMGlFE6nDNc+/3A3/fCOYNG7CBLjrruonyC/pMJr4UDxES2DG32DQhCB56gYV+xRuSGLQpg+3hzsw6M5BZZP5XbbnZbzx0xu8NyeYNGZMnzH0bd+3vp8aCCYBHT06uKmCUAh2eRAmjYD8mTBpJxhxO2Svnzk7UgTJ2ZDSZWMSiXAClBK0K1Jh5uoqEpUA0KZP7coUt0m2lJK1m08CXs06wun9uOfgexj9UBDsj+d9TEFpsFyUKPcefG/w+MfB7zkhAQ47rOaJeRct2jih7z77bP1kEX36wAUXlH8suj4/THNPrhKLBg+G3/wGHnsMzjkHxoyBlJTqf1clJU2Y4CIuafMkQ/VRWWIkqDY5EllZ9r9pDuoTu9xcOOqoIIFFXaT2g4G3wY63QdEKyPsWVv0ApQVAFOJSoG0/yNgOEjNh/ynw2QXwzdXw/Z3QZVyQqCJ9myBJRPEqWPklLJsKRUur/xwVP8OCSyD/teB9KlPV8WXD8SucABkDg1srd9xxMGgQXHopTJwI118Pu+4KO+wA3boFx8EVK+Crr4LlJLUMBx0E330Hf/kL3HFHkNRv2LAgaU3XrsG2nZcHn38eJFV4++2mLnHr9swzQd1+Q1Kg22+H007b+NjddwfnBevWNW05JdXN1fteXZa8oiq/Hvbrer//Nh22ITUhlbXFawEojZZSGi3dbLk9euxR73U0tlAIOncObtX58+g/8+TXT/L9su8pLC3kiIFH8M9v/glASnwKDx7+YCOUVpIkqQWoT/sv2H4vSZKkJmfyCkmSJEmSpDoIh8P079+/7H59JMUn8eBhD7LHgxs7nD1w2AOEN002MfgS+OxCmHU/DPoDpHaD8CZNOWk9gtsGnfaCxe9CwUKYcibs8S+IRjZPYLHhNSU/QeiP9So/canQ+xToe0rwf9EKWDMHSguDASCJGZDWq/y6W6CGiLUkSZJqZr1Lanxud5IkNQOd9oSDv4N5z8LcZ+GHe+HLSzdfLrHd5gmOJUmtmudsLZexk6SG8cRRT/CHhX+gb7u+JMZVMYGpJMWgzp3hgQfgF7+A++6Dn3+GW26BAQOCyfM3TOK/YWL26XP7MmTg+TD9Rvj6L5BzYDCxc8UEFhv6FEZKIRw8tw1w4tATefTLR4lGo6QlpPH9su+JEgXg5rE3N86HjmVJ7eHAr4LYzfgbvLEPpPWGrJ0hcyiEk6BkDaz4DJZ+HCQpCcXBgldg2FXl32vTRCWwMVlJmz7QcVTtytOmD8S3gZLV8POj0GEnyiXJqGEdewJ799qbN39+k++WfVf2sgP7HcjOXXcGgrl5wmFo377mxBVQfsLY1NTafYyGFgqVz+Gh5uWvf4XXX4eFC2H4cPj732HvvYOJh0tLg9hFIpCYGPx9+eUgcUqLV4fESGpm6hO777+vfaII2Hyys8R20HG34FaV9sNh3/9B3nRY9CYsmwI/PgCFyyBSHCQ4SusBWaOg42jo3r32nyM6CFa9HiTPiJSUHy8BlSfbqsvxq5XZfnt46SWYPz9I+jRlCnz2Gbz7blAXTE2FgQPDpKX1p0sX2yhbItuYY1PfvvDQQ0GihGnTYOpU+OKL4H5pKSQnB8ks9thj8xxyajirVsHkyRsTV5x6Kvzudxuf37BJTpgQ5sor+zNwoNup1Ji25Bg5MGsgo7qN4qN5HwHwi+1+wZDOQ7jkjUuAIMnC5XtevkXl27PHnkyaNanaZcbvMn6L1tEchUNh/rznnznhuaBv240f3FjWfnjOyHNon9K+KYsnSZLUvNh2Xy3bxWKL8ZYkqeUIRaPRaFMXQrWXn59PRkYGeXl5pKenN3VxJEmSJEnSFhhy1xC+XvI1v9zulzx59JPlnywtgBf7B4Ms2vaDvV6BtJ5AaPOkEJHiIFHFglfg3aOCx7rsD7s8CCnZwfOh9QM5oiVBgonCZbBoTdWDVaB2A1YkSZIkSZIkSQ2jYAmsnRu0D4cTISkraBd29glJkiRJkiSt9/nncNppwWTFcXHQs2cwGXuXLsEkm7Nnw5tvBv9P/XA1vD4aVnweTCw9ZCL0/x0ktA36HEYjQcKDUAhWfgXf3wU73w3AtNxpjLhvBADbddyOb5Z8A8Du3Xfn3d++2zQfPlYVLg8mC1/yHix+J+hXGikMYpraEzqPDiYf//yiYPk9X4CcAzafALwm06bBiBHlH/v0U9hhh+D+V1fCV1cEfVAPmRn0Tw1Xk2UiUlzu+Y/mfcSof5SfbHzaadMY3mU4AFdcAVdfHXRdXby45uLOmxfMjw7wr38FSQfi6/iR1fotXw5nnAFPPx38Pnr1gjFjgp91UlIwSfEHH8Abb0C3bsG+VVIjWv4ZTFp/nBn5D+h9YvXHFklS8zRnzsbxadOnwwknlH/+scdg0KCN/zfDsWnPPAPHHhvcb9MmSICWlrb5cpFIUIfMyGjc8knaMs9/9zyHP304ALt225Vx/cYx8e2JhAhx2ojTuOugu7bo/V/94VXGPT6u7P8dc3ZkxboVzFoxC4A2iW1YdfGqLVpHmZrabxpZSaSEfn/rx+y82YQIESVKYlwic8bPoXObzk1SJqDZfU+SJEmSJElSc1GX/AZ2xZIkSZIkSWoiH5/6McvXLadzWiWdsOKSYa9J8Ob+sOoHeHkw9P899DgaOozcmMBizWyY869gQOLo52Gvl+GDX8HCyfB8D+i4J3Q9aGPiizWzYcHLUJwP+3/c7Dr7SpIkSZIkSVLMSu4Y3CRJkiRJkqQqbL89fPwxvP8+/O9/8Oqr8PjjUFAQPJ+WBqNGwZFHQiSuDeGx78PnF8OM2+DzP8IXl0DWSGi3fZBAtXAZLHojSIiQOaRsPTt02YGRXUfy8fyPyxJXAIzfZXyjfl4BSe2hx1HBrSrRKMx9DpZPgY9Ogr0nQfsdgPDmyXEjJUEf1LnzNk4wC8EksxVt+ljmkZDwVyhZnxRl70nQtl+w7nDcJu9fGqxzzVxo26fs4V267cK4vuOYNGsSAIcPPLwscQUE89eWlMCyZbBkCXSsoam0S5fglpsbbANHVfP1KHa1bw9PPQUTJsCzz8KkSXDvvcHPdoP4eNh1VzjmmGAy4nC46corxZz2wyF7LCz6X5AgqetBkNi+6gQWkZK6J2eSJG1dc+bAgAEbT0orUzGZRXIyzJjRrMa0TZ0KCQlQXAy/+hWkpFS+XDhs4gqpJTqw/4G0S27HioIVfDz/Y4pKi4hEIwCcvP3JW/z++/fbn37t+vHDih8AuHbfa/nXt/9i9meziUajjB85vv5vvmmCIKi5/QYaNUlQfDieS/e8lFNfPJUowcn26SNOb9rEFZIkSZIkSZIaRCga3bSLjZq7umQmkSRJkiRJrUDhcvj0XPj5cSAKoTgIJ0FiBpQWQNGKYBBh5jA4YNrG13x3C8z9N+Rv6Hi2YfDh+qagbkfCnv9u5A8jSZIkSZIkSZIkSZIkSZIaWun6fAFVTrqe/z3Mew7mvQhLPwQiG59LbA9dD4buxwSTRq9PdvDU109x3L+PK1ssu002c8+bS7yTRjdPq38Mkkqsyw36lQ44F/qcDBnbblymtAjmvwifPgXHv1T9BLMVJSfD1Gfg2xODBBbhBOj9G+h1HHTcPVhntBQWvws/PwErv4T9Pyr3Fp8u+JQd798RgK9+/xWDOw0ue27OHOjVK0gqcN11cP75QVKB6lx1FVx+efCTnTcvSHgRF1f18iYmEMDKlbBoERQWQmoq5OQEfyU1kWVTYfJuECmGtB6wx7NBAqZI8cYkFhvur50Hqd2atrySpPKmTYMRI+r+uk8/hR12aPjy1NPhh8MLLwTnI1OmBEWr6tyhtLT68w5JzdP4SeO57ePbAAgRIkqU/u37M+OsGYQqJv6sh4tfv5gbP7gRgEv3vJQnv36S75d9D8DUU6cyIqce+8raJAiqTCMnCSoqLSL5quSy5BVzz5tLt/QmrrdXdnxqZsceSZIkSZIkqSnUJb+ByStaGJNXSJIkSZLUtIqKirjpppsAuOCCC0hMTGycFRcshvkvwdznggF9JWsgLglSukL3w6Hb0ZDev2zQaJk1s2Hxe1CSH/SgTciATrtDWs/GKXcL1mSxliRJijHWu6TG53YnSZIkSc2X52wtl7GTJElSi1GyBopWQGkhxKdBcqcg8UAFRaVFdP1rV5auXQrA1ftczZ/2+FNjl1Z1sS4X3j8eFr8FoXiIlkCbPpCcDZEiyJ8BJatg+SA4e3rd3//TT2FAFnzwK1jyHoTigoQVoTiIS4XStRv/zxwKB0zb7C0Oe/IwEuMSeebYZzZ7bswYeOutIInFt99CQsLm3WI3tWBBMA9jaSnsthv8739BwovKJpKNRIJutE4yK0nN0MI34J1DobQgOI50GAm9fhUkYArFwaofYPaTUJwH46Y2dWmbNdsoWzbjpxaplSSv6NcPZs2Crl2DxHhVcTuVmkZDbHufL/yc4fcOL/fY9WOu58LdLmyQMn4872N2+ccuAOzWfTfen/s+ANlp2Sw4f0H9EmTUdx8Ljb6fPevls7hz6p10SOnA0guXNtp6q2TyCkmSpBbF8+3YYrwlSWpadclvEN9IZZIkSZIkSWo1iouLG3+lyZ2g72+DW12k9YTeJqqoryaJtSRJUgyy3iU1Prc7SZIkSWq+PGdruYydJEmSWoT4tOBWg8S4RM7a6Swmvj0RgFN3OHUrF0xbLKUL7PM6LHoDfn4C5v4LVv8Y3DbI2A7SjgauqN860nrAmHcg72uY/XSwnjWzg6QYhKFNX+h1PPQ8odKXP3/c81W+9WmnBQkoZs2CX/8anngiSDgR3jy3CqWlwXIXXgjXXgvvvw977w2PPQZ9+kBxcZCoorQ0SIKRmxssd8cd9fvYkqStKHsfOOBz+OR0WPQmLJsCyz4uv8yGxEiqkW2ULZvxU4uTlQXJyVBQUPvXJCcHr2smSkpg9uzg/oEHBonvKjsH2cDtVGoaW7rtbZ+9Pdt13I5vlnwDQIgQJwytvO2iPnbquhMdUzuyZO0SPpn/SdnjR217VP0SV0D99rHQJPvZG/a7gQP7H8gOXUwOIUmSpPrxfDu2GG9JkloGk1dIkiRJkiRJkiRJkiRJkiRJkiRJkiSpnNN3PJ2Jb08kNSGVjmkdm7o4qo1wHHTZL7jtfA/kz4DifAgnQnInaNML5syB5OvrP8FsKASZQ4LbsKuCDBORomAd9Z2QETjySNh3X3jrLXj6aVi3Dm6+Gfr1g6KiYJm4uOD+XXcFy3z0UfBxHn8cPvwwWHa//eCoo6BdO8jPhxdegJdegmHD6l00SdLW1rYf7Ps/WDsPfn4S5r8ABYshGoGk9tDlAOhzUlOXUpJUUY8eMGMGLF268bHcXFi5MrifmQldupR/TVZW8LpmYvbsIIEFwHbbBfcTE5u2TJK2jlOGn8KE1yYAMKbPGHLa5jTYe4dDYY4adBT3fHoPxZGNk7AeMfCI+r9pZftYaJb72dTEVA7c5sBGXackSZIkSZKkrcvkFZIkSZIkSZIkSZIkSZIkSZIkSZIkSSonu0020cujTV0M1VdcErQbuvnj9Zn8sLqJD0OhYF1bKD4ennkG9tgDvvsuSDrx4otwwAEwahQkJQUTyz7+eFDMESMgHIZHHoGePeHGG6G0FF57LbhtKhwOEl9Ikpq51G6w7R+CmySpZejRo1klo6irGTM23h80CBISmq4skrauXw39VVnyilOGn9Lg73/EoCO459N7yv5vm9iWPXvuuWVv2sL3sZIkSZIkSZJaLpNXSJIkSZIkSZIkSZIkSZIkSZIkSZIkSbGimU5+2K4dvPsu/OpX8N//BgknXnkluG0QDgd/O3TY+P/VV8N558EDD8Dtt8O8eRuX79QJzjwTTj+98T6HJEmSpJZhxozgnCISCZJXhEJNXSJJW0untE5l9w8beFiDv/9evfYiLSGNNcVrytaREGdGnEYxZ075JK3Tp2++TMXHqkvUKkmSJEmSJMnkFZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKaXrt2QbKKr76CW26Bxx6D4uKNz2+/PVx0ERx5ZPnXZWXBhRfCH/4Aa9ZAfj60bQtt2jgBrSRJkqTKff99kLwiIQG6dm3q0kja2qKXR7faeyfGJXLIgEN46uunADhi4BFbbV3axJw5MGAAFBRUv9wJJ5T/Pzk5yGBkAgtJkiRJkiSpUuGmLoAkSZIkSZIkSZIkSZIkSZIkSZIkSZIkbTBkCDzwQJCEYt48mDULVqyAqVPh2GMhPr7y14VCQcKKnJwgeYWJKyRJkiRVZcUKiESgX78giYUkbYlNE1bs33f/JixJDFm6tObEFZUpKAheK0mSJEmSJKlSVXTNkiRJkiRJUmVCoRA9e/Ysu6/Wy1hLkiQ1DutdUuNzu5MkSZKk5stztpbL2EmSJEnS1pGcDF27NnUpJElq/myjbNmMn9Q0ioqC5BU5OTUv63YqNY2WtO2N6zeu7H5aYloTlkSSJElqOVpSnV9bznhLktRyhKLRaLSpC6Hay8/PJyMjg7y8PNLT05u6OJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIktSgHHgj//S8cdBC89FJTl0ZSa7CyYCXx4XjaJLZp6qLEhmnTYMSI+r32009hhx0atjySJEmSJElSM1aX/AbxjVQmSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkJldYGPxNTGzackhqPTKTM5u6CLElKwuSk6GgoG6vS04OXitJkiRJkiSpUiavkCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJMaOkJPgbF9e05ZAk1VOPHjBjBixdWv7x3FxYuTK4n5kJXbqUfz4rK3itJEmSJEmSpEqZvEKSJEmSJKkOioqKuO222wA499xzSUxMbOISaWsx1pIkSY3DepfU+NzuJEmSJKn58pyt5TJ2kiRJkiRJkpqSbZQtm/GTmkZSUvC3qKjmZd1Opabhtqca9ehhIgpJkqQWzDp/bDHekiS1HCavkCRJkiRJqqO1a9c2dRHUSIy1JElS47DeJTU+tztJkiRJar48Z2u5jJ0kSZIkSZKkpmQbZctm/KTGl5IS/K1N8gpwO5WaitueJEmS1LpZ548txluSpJYh3NQFkCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJaiyJiRAKwapVTV0SSZIkSZIkSZKk5sPkFZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkKWYkJ0M4DDNnNnVJJEmSJEmSJEmSmg+TV0iSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpJjRqxeEQrB4Maxa1dSlkSRJkiRJkiRJah5MXiFJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkmLGgAFQUhLcnzmzacsiSZIkSZIkSZLUXJi8QpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkxYxtttl4/5tvNiaykCRJkiRJkiRJimXxTV0ASZIkSZKkliQUCpGTk1N2X62XsZYkSWoc1rukxud2J0mSJEnNl+dsLZexkyRJkiRJktSUbKNs2Yyf1DQGDNh4f8YMiEarXtbtVGoabnuSJElS62adP7YYb0mSWo5QNFrdZRM1N/n5+WRkZJCXl0d6enpTF0eSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpBanQwdYvhxGj4a33mrq0kiSJEmSJEmSJG0ddclvEG6kMkmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJDULAwYEf997D1asaNqySJIkSZIkSZIkNQcmr5AkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSTFlu+0gPh5KS+Hpp6G4uOplS0oar1ySJEmSJEmSJElNJb6pCyBJkiRJktSSFBcXc+eddwJw5plnkpCQ0MQl0tZirCVJkhqH9S6p8bndSZIkSVLz5Tlby2XsJEmSJEmSJDUl2yhbNuMnNZ1BgyASCe7fcw/87neVL+d2KjUNtz1JkiSpdbPOH1uMtyRJLYfJKyRJkiRJkuogGo2Sl5dXdl+tl7GWJElqHNa7pMbndidJkiRJzZfnbC2XsZMkSZIkSZLUlGyjbNmMn9R09t8fzj8/uP/FF/D66zB6NFScO7G42O1UagoeIyVJkqTWzTp/bDHekiS1HOGmLoAkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSVJj2nZb6NVr4//HHw9Ll0JJycbHSkpg/vxGL5okSZIkSZIkSVKTMHmFJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmKKaEQ/OIXEBcX/L9kCRx0EOTmblxmzhw46qimKZ8kSZIkSZIkSVJja1XJK1asWMGJJ55IRkYGGRkZnHjiiaxcubLa10SjUSZOnEhOTg4pKSnstddefPPNN+WWKSws5OyzzyYrK4u0tDQOPfRQ5s2bV/b8zz//zCmnnELv3r1JSUmhb9++XH755RQVFZV7n1AotNntnnvuabDPL0mSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSauf446G0dOP/n30G/frBoYcGiSwGDIDvvmu68kmSJEmSJEmSJDWmVpW84vjjj+fzzz9n0qRJTJo0ic8//5wTTzyx2tfccMMN/PWvf+WOO+5gypQpZGdns99++7Fq1aqyZcaPH89zzz3HU089xXvvvcfq1as5+OCDKV1/1em7774jEolw77338s0333DLLbdwzz338Kc//Wmz9T344IPk5uaW3X7zm9807JcgSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZJqNHQojBgBcXEbHysqghdfhFdegZKSpiubJEmSJEmSJElSY4tv6gI0lOnTpzNp0iQ++ugjRo4cCcD999/PqFGjmDFjBgMGDNjsNdFolFtvvZVLLrmEI488EoCHH36Yzp0788QTT3D66aeTl5fHP/7xDx599FHGjBkDwGOPPUb37t15/fXX2X///Rk3bhzjxo0re98+ffowY8YM7r77bm666aZy68zMzCQ7O3trfQ2SJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJKmWrr8e1k8tJEmSJEmSJEmSFNPCTV2AhvLhhx+SkZFRlrgCYJdddiEjI4MPPvig0tf89NNPLFy4kLFjx5Y9lpSUxOjRo8te8+mnn1JcXFxumZycHAYPHlzl+wLk5eXRvn37zR4/66yzyMrKYqedduKee+4hEolU+7kKCwvJz88vd5MkSZIkSU0nFArRsWNHOnbsSCgUauriaCsy1pIkSY3DepfU+NzuJEmSJKn58pyt5TJ2kiRJkiRJkpqSbZQtm/GTmt6++8LYsRAXV9USIVatcjuVGpvHSEmSJKl1s84fW4y3JEktRygajUabuhAN4ZprruGhhx7i+++/L/f4Nttsw8knn8zFF1+82Ws++OADdtttN+bPn09OTk7Z46eddhqzZ8/m1Vdf5YknnuDkk0+msLCw3GvHjh1L7969uffeezd731mzZrHDDjtw880383//939lj1911VXsu+++pKSk8L///Y8///nPXHzxxVx66aVVfq6JEydyxRVXbPZ4Xl4e6enpVX8hkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiSpRj//DDvuCCtXQmlp+efi4mCffeC115qiZJIkSZIkSZIkSVsmPz+fjIyMWuU3CDdSmept4sSJhEKham9Tp04FqDRrVjQarTGbVsXna/OaqpZZsGAB48aN45hjjimXuALg0ksvZdSoUWy//facf/75XHnlldx4443Vrufiiy8mLy+v7DZ37txql5ckSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSbXXqxdMmgRJSUGyig3i4iA1Fe66q8mKJkmSJEmSJEmS1Gjim7oANTnrrLP45S9/We0yvXr14ssvv2TRokWbPbdkyRI6d+5c6euys7MBWLhwIV26dCl7fPHixWWvyc7OpqioiBUrVtCuXbtyy+y6667l3m/BggXsvffejBo1ivvuu6/Gz7bLLruQn5/PokWLqixjUlISSUlJNb6XJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmqnx13hO+/h8sug2efhVAIfvELuOIKqGJ6IEmSJEmSJEmSpFal2SevyMrKIisrq8blRo0aRV5eHp988gk777wzAB9//DF5eXmbJZnYoHfv3mRnZzN58mSGDx8OQFFREW+//TbXX389ACNGjCAhIYHJkydz7LHHApCbm8vXX3/NDTfcUPZe8+fPZ++992bEiBE8+OCDhMPhGsv82WefkZycTGZmZo3LSpIkSZKk5qG4uJj7778fgFNPPZWEhIQmLpG2FmMtSZLUOKx3SY3P7U6SJEmSmi/P2VouYydJkiRJkiSpKdlG2bIZP6l56doVHngguG1QXFzMXXe5nUqNzWOkJEmS1LpZ548txluSpJaj2SevqK1BgwYxbtw4Tj31VO69914ATjvtNA4++GAGDBhQttzAgQO59tprOeKIIwiFQowfP55rrrmG/v37079/f6655hpSU1M5/vjjAcjIyOCUU07h/PPPp0OHDrRv354LLriAIUOGMGbMGAAWLFjAXnvtRY8ePbjppptYsmRJ2fqys7MBePHFF1m4cCGjRo0iJSWFN998k0suuYTTTjuNpKSkxvqaJEmSJEnSFopGo2Xn/tFotIlLo63JWEuSJDUO611S43O7kyRJkqTmy3O2lsvYSZIkSZIkSWpKtlG2bMZPav7cTqWm4bYnSZIktW7W+WOL8ZYkqeVoNckrAB5//HHOOeccxo4dC8Chhx7KHXfcUW6ZGTNmkJeXV/b/hRdeyLp16zjjjDNYsWIFI0eO5LXXXqNt27Zly9xyyy3Ex8dz7LHHsm7dOvbdd18eeugh4uLiAHjttdf44Ycf+OGHH+jWrVu59W2oDCUkJHDXXXcxYcIEIpEIffr04corr+TMM8/cKt+FJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElSbbSq5BXt27fnscceq3aZipm1QqEQEydOZOLEiVW+Jjk5mdtvv53bb7+90udPOukkTjrppGrXO27cOMaNG1ftMpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSY0t3NQFkCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUtMxeYUkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSVIMM3mFJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElSDItv6gJIkiRJkiS1JKFQiIyMjLL7ar2MtSRJUuOw3iU1Prc7SZIkSWq+PGdruYydJEmSJEmSpKZkG2XLZvyk5s/tVGoabnuSJElS62adP7YYb0mSWo5QNBqNNnUhVHv5+flkZGSQl5dHenp6UxdHkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiQ1Q3XJbxBupDJJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiSpGTJ5hSRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUgyLb+oCSJIkSZIktSTFxcU89NBDAJx00kkkJCQ0bYG01RhrSZKkxmG9S2p8bneSJEmS1Hx5ztZyGTtJkiRJkiRJTck2ypbN+EnNn9up1DTc9iRJkqTWzTp/bDHekiS1HCavkCRJkiRJqoNoNMqCBQvK7qv1MtaSJEmNw3qX1Pjc7iRJkiSp+fKcreUydpIkSZIkSZKakm2ULZvxk5o/t1OpabjtSZIkSa2bdf7YYrwlSWo5wk1dAEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJDUdk1dIkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiTFMJNXSJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkxTCTV0iSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJMUwk1dIkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiTFsPimLoAkSZIkSVJLk5qa2tRFUCMx1pIkSY3DepfU+NzuJEmSJKn58pyt5TJ2kiRJkiRJkpqSbZQtm/GTmj+3U6lpuO1JkiRJrZt1/thivCVJahlC0Wg02tSFUO3l5+eTkZFBXl4e6enpTV0cSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZLUDNUlv0G4kcokSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkZsjkFZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSTEsvqkLIEmSJEmS1JIUFxfz+OOPA/CrX/2KhISEJi6RthZjLUmS1Disd0mNz+1OkiRJkpovz9laLmMnSZIkSZIkqSnZRtmyGT+p+XM7lZqG254kSZLUulnnjy3GW5KklsPkFZIkSZIkSXUQjUaZPXt22X21XsZakiSpcVjvkhqf250kSZIkNV+es7Vcxk6SJEmSJElSU7KNsmUzflLz53YqNQ23PUmSJKl1s84fW4y3JEktR7ipCyBJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkqSmY/IKSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkGGbyCkmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpBhm8gpJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkqQYZvIKSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkGBbf1AWQJEmSJElqaRISEpq6CGokxlqSJKlxWO+SGp/bnSRJkiQ1X56ztVzGTpIkSZIkSVJTso2yZTN+UvPndio1Dbc9SZIkqXWzzh9bjLckSS1DKBqNRpu6EKq9/Px8MjIyyMvLIz09vamLI0mSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSmqG65DcIN1KZJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS1AyZvEKSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJCmGxTd1ASRJkiRJklqSkpIS/vnPfwJw7LHHEh9v80prZawlSZIah/UuqfG53UmSJElS8+U5W8tl7CRJkiRJkiQ1JdsoWzbjJzV/bqdS03DbkyRJklo36/yxxXhLktRyeJSWJEmSJEmqg0gkwsyZM8vuq/Uy1pIkSY3DepfU+NzuJEmSJKn58pyt5TJ2kiRJkiRJkpqSbZQtm/GTmj+3U6lpuO1JkiRJrZt1/thivCVJajnCTV2AhrRixQpOPPFEMjIyyMjI4MQTT2TlypXVviYajTJx4kRycnJISUlhr7324ptvvim3TGFhIWeffTZZWVmkpaVx6KGHMm/evHLL9OrVi1AoVO72xz/+sdwyc+bM4ZBDDiEtLY2srCzOOeccioqKGuSzS5IkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIk1UerSl5x/PHH8/nnnzNp0iQmTZrE559/zoknnljta2644Qb++te/cscddzBlyhSys7PZb7/9WLVqVdky48eP57nnnuOpp57ivffeY/Xq1Rx88MGUlpaWe68rr7yS3Nzcstull15a9lxpaSkHHXQQa9as4b333uOpp57i3//+N+eff37DfgmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEl1EN/UBWgo06dPZ9KkSXz00UeMHDkSgPvvv59Ro0YxY8YMBgwYsNlrotEot956K5dccglHHnkkAA8//DCdO3fmiSee4PTTTycvL49//OMfPProo4wZMwaAxx57jO7du/P666+z//77l71f27Ztyc7OrrR8r732Gt9++y1z584lJycHgJtvvpmTTjqJq6++mvT09Ab9PiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkmoj3NQFaCgffvghGRkZZYkrAHbZZRcyMjL44IMPKn3NTz/9xMKFCxk7dmzZY0lJSYwePbrsNZ9++inFxcXllsnJyWHw4MGbve/1119Phw4d2H777bn66qspKioqV77BgweXJa4A2H///SksLOTTTz+t8nMVFhaSn59f7iZJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJktRQ4pu6AA1l4cKFdOrUabPHO3XqxMKFC6t8DUDnzp3LPd65c2dmz55dtkxiYiLt2rXbbJlN3/fcc89lhx12oF27dnzyySdcfPHF/PTTT/z9738ve5+K62nXrh2JiYlVlg/g2muv5YorrqjyeUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpC3R7JNXTJw4scbkDVOmTAEgFApt9lw0Gq308U1VfL42r6m4zHnnnVd2f+jQobRr146jjz6a66+/ng4dOtS7fBdffDETJkwo+z8vL48ePXqQn59fbfkkSZIkSdLWUVRUREFBAQD5+fkkJiY2cYm0tRhrSZKkxmG9S2p8bneSJEmS1Hx5ztZyGTtJkiRJkiRJTck2ypbN+EnNn9up1DTc9iRJkqTWzTp/bDHekiQ1rQ15DaLRaI3LhqK1WaoJLV26lKVLl1a7TK9evXjiiSeYMGECK1euLPdcZmYmt9xyCyeffPJmr/vxxx/p27cv06ZNY/jw4WWPH3bYYWRmZvLwww/zxhtvsO+++7J8+XLatWtXtsywYcM4/PDDq0ysMX/+fLp168ZHH33EyJEj+fOf/8zzzz/PF198UbbMihUraN++PW+88QZ77713bb4O5s2bR/fu3Wu1rCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJim1z586lW7du1S4T30hlqbesrCyysrJqXG7UqFHk5eXxySefsPPOOwPw8ccfk5eXx6677lrpa3r37k12djaTJ08uS15RVFTE22+/zfXXXw/AiBEjSEhIYPLkyRx77LEA5Obm8vXXX3PDDTdUWZ7PPvsMgC5dupSV7+qrryY3N7fssddee42kpCRGjBhRm68CgJycHObOnUvbtm0JhUI1Lp+fn0/37geHRhMAAQAASURBVN2ZO3cu6enptV6PWh5jHVuMd+ww1rHFeMcOYx1bjHfsMNaxxXjHDmMdW4x37DDWscV4xw5jHVuMd+ww1rHFeMcOYx1bjHfsMNaxxXjHFuMdO4x1bDHescNYxxbjHTuMdWwx3rHDWMcW4x07jHVsMd6xw1jHFuMdO4x1bDHescNYxxbjHTuMdWwx3rHDWMcW4x07jHVsMd6xw1jHFuMdO4x1bDHescNYxxbjHTvqE+toNMqqVavIycmpcdlmn7yitgYNGsS4ceM49dRTuffeewE47bTTOPjggxkwYEDZcgMHDuTaa6/liCOOIBQKMX78eK655hr69+9P//79ueaaa0hNTeX4448HICMjg1NOOYXzzz+fDh060L59ey644AKGDBnCmDFjAPjwww/56KOP2HvvvcnIyGDKlCmcd955HHroofTo0QOAsWPHsu2223LiiSdy4403snz5ci644AJOPfXUOm3E4XC4xowklUlPT3dnESOMdWwx3rHDWMcW4x07jHVsMd6xw1jHFuMdO4x1bDHescNYxxbjHTuMdWwx3rHDWMcW4x07jHVsMd6xw1jHFuMdW4x37DDWscV4xw5jHVuMd+ww1rHFeMcOYx1bjHfsMNaxxXjHDmMdW4x37DDWscV4xw5jHVuMd+ww1rHFeMcOYx1bjHfsMNaxxXjHDmMdW4x37DDWscV4xw5jHVuMd+yoa6wzMjJqtVyrSV4B8Pjjj3POOecwduxYAA499FDuuOOOcsvMmDGDvLy8sv8vvPBC1q1bxxlnnMGKFSsYOXIkr732Gm3bti1b5pZbbiE+Pp5jjz2WdevWse+++/LQQw8RFxcHQFJSEk8//TRXXHEFhYWF9OzZk1NPPZULL7yw7D3i4uJ4+eWXOeOMM9htt91ISUnh+OOP56abbtqaX4kkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSVK1WlXyivbt2/PYY49Vu0w0Gi33fygUYuLEiUycOLHK1yQnJ3P77bdz++23V/r8DjvswEcffVRj+Xr06MFLL71U43KSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmNJdzUBdDWlZSUxOWXX05SUlJTF0VbmbGOLcY7dhjr2GK8Y4exji3GO3YY69hivGOHsY4txjt2GOvYYrxjh7GOLcY7dhjr2GK8Y4exji3GO3YY69hivGOL8Y4dxjq2GO/YYaxji/GOHcY6thjv2GGsY4vxjh3GOrYY79hhrGOL8Y4dxjq2GO/YYaxji/GOHcY6thjv2GGsY4vxjh3GOrYY79hhrGOL8Y4dxjq2GO/YYaxji/GOHVs71qFoNBrdKu8sSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkZi/c1AWQJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElS0zF5hSRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUgwzeYUkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSVIMM3mFJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElSDDN5RSt211130bt3b5KTkxkxYgTvvvtuUxdJDeCdd97hkEMOIScnh1AoxH/+859yz0ejUSZOnEhOTg4pKSnstddefPPNN01TWG2Ra6+9lp122om2bdvSqVMnDj/8cGbMmFFuGePdetx9990MHTqU9PR00tPTGTVqFP/973/LnjfWrde1115LKBRi/PjxZY8Z79Zj4sSJhEKhcrfs7Oyy54116zJ//nxOOOEEOnToQGpqKttvvz2ffvpp2fPGu/Xo1avXZtt2KBTizDPPBIx1a1JSUsKll15K7969SUlJoU+fPlx55ZVEIpGyZYx367Fq1SrGjx9Pz549SUlJYdddd2XKlCllzxvrlqsh2lIKCws5++yzycrKIi0tjUMPPZR58+Y14qdQbdUU72effZb999+frKwsQqEQn3/++WbvYbxbhupiXVxczEUXXcSQIUNIS0sjJyeHX//61yxYsKDcexjrlqOmbXvixIkMHDiQtLQ02rVrx5gxY/j444/LLWO8W4aaYr2p008/nVAoxK233lrucWPdctQU75NOOmmzc+9ddtml3DLGu2WozbY9ffp0Dj30UDIyMmjbti277LILc+bMKXveWLccNcW7sna1UCjEjTfeWLaM8W4Zaor16tWrOeuss+jWrRspKSkMGjSIu+++u9wyxrrlqCneixYt4qSTTiInJ4fU1FTGjRvHzJkzyy1jvFuGhuqrYrybv9rE2ra01qOmeNue1nrUZtu2La31qE28N2V7WstVm1jbltZ61Hbbtj2t5atNrG1Laz1qE2/b01qH2sTatrTWoyHGARnrlqGmWNuO1rpUF2/b0VqXmrZt29Fal5rivSnb0Vq2mmJtO1rrUptt23a01qGmWNuO1rrUFG/b0VqPmmJtO1rrVd85Vox3y1RZvG1Pa70qxtv2tNarsm3b9rTWq7J4b8r2tNajsljbntZ6VbVt257W+lQWa9vTWq/K4m17WutUWaxtT2s9GmIO24aKtckrWqmnn36a8ePHc8kll/DZZ5+xxx57cMABB5Sr+KllWrNmDcOGDeOOO+6o9PkbbriBv/71r9xxxx1MmTKF7Oxs9ttvP1atWtXIJdWWevvttznzzDP56KOPmDx5MiUlJYwdO5Y1a9aULWO8W49u3bpx3XXXMXXqVKZOnco+++zDYYcdVlYBMNat05QpU7jvvvsYOnRouceNd+uy3XbbkZubW3b76quvyp4z1q3HihUr2G233UhISOC///0v3377LTfffDOZmZllyxjv1mPKlCnltuvJkycDcMwxxwDGujW5/vrrueeee7jjjjuYPn06N9xwAzfeeCO333572TLGu/X4v//7PyZPnsyjjz7KV199xdixYxkzZgzz588HjHVL1hBtKePHj+e5557jqaee4r333mP16tUcfPDBlJaWNtbHUC3VFO81a9aw2267cd1111X5Hsa7Zagu1mvXrmXatGlcdtllTJs2jWeffZbvv/+eQw89tNxyxrrlqGnb3mabbbjjjjv46quveO+99+jVqxdjx45lyZIlZcsY75ahplhv8J///IePP/6YnJyczZ4z1i1HbeI9bty4cufgr7zySrnnjXfLUFOsZ82axe67787AgQN56623+OKLL7jssstITk4uW8ZYtxw1xXvTbTo3N5cHHniAUCjEUUcdVbaM8W4Zaor1eeedx6RJk3jssceYPn065513HmeffTbPP/982TLGuuWoLt7RaJTDDz+cH3/8keeff57PPvuMnj17MmbMmHL9G4x3y9BQfVWMd/NXm1jbltZ61BRv29Naj9ps27altR61ifcGtqe1bLWNtW1prUNt4m17WutQm1jbltZ61Cbetqe1DjXF2ra01qUhxgEZ65ahpljbjta6VBdv29Fal5q2bdvRWpea4r2B7WgtX21ibTta61FTvG1Haz1qirXtaK1LTfG2Ha31qC7WtqO1Xlsyx4rxbnmqirftaa1TZfG2Pa11qmrbtj2tdaoq3hvYntZ6VBdr29Nan6ribXta61NVrG1Pa52qirftaa1PZbG2Pa312dI5bBss1lG1SjvvvHP0d7/7XbnHBg4cGP3jH//YRCXS1gBEn3vuubL/I5FINDs7O3rdddeVPVZQUBDNyMiI3nPPPU1QQjWkxYsXR4Ho22+/HY1GjXcsaNeuXfTvf/+7sW6lVq1aFe3fv3908uTJ0dGjR0fPPffcaDTqtt3aXH755dFhw4ZV+pyxbl0uuuii6O67717l88a7dTv33HOjffv2jUYiEWPdyhx00EHR3/72t+UeO/LII6MnnHBCNBp1225N1q5dG42Li4u+9NJL5R4fNmxY9JJLLjHWrUh92lJWrlwZTUhIiD711FNly8yfPz8aDoejkyZNarSyq+4qxntTP/30/+zdeZxcVZ03/m/1HpaEgUBIgIQAgokwKokLCMOjSBgQ5ZHdBfBh+Q2iAyTqYBCGARcGBzGiLKKIMijgiAujIASFCBJZkgCyCIxEwpKAYSBbb1XV9/dHTKeX6i10d9W99X6/Xnlx69ape0/zyUnfe/rc/i5NIiJZsmRJt/3yTqf+st7ggQceSCIiee6555IkkXWaDSbvVatWJRGR3HnnnUmSyDut+sr6hRdeSHbYYYfkscceS6ZMmZJ8/etf73xP1ulVKu8TTzwxOfzww/v8jLzTqVTWxx57bOe9dimyTq/BfN8+/PDDk/e9732dr+WdTqWyfstb3pJceOGF3fbtvffeybnnnpskiazTrGfeTz31VBIRyWOPPda5r1AoJFtvvXXyne98J0kSeafZpqxVkXc69cy6K3Np2dNf3huYT8uGwWRtLi07+srbfFr2lMraXFp2lcrbfFo2Deb7trm07CiVt/m0bOqZtbm07BvKc0CyTrcNWXdlHi27SuW9gXm0bOkva/No2dMzb/No2dU1a/No2dc1b/No2dbf923zaNnTNW/zaNm2IWvzaNn0Rn7HirzTp6+8uzKflh2DyXsD82npNpSszael30B5m0/Ljv6yNp+WPf3lbT4tW4byfdt8Wvr1l7f5tGzpK2vzadnyRn+H7XBmXTO0UhekQXt7eyxatChmzZrVbf+sWbPivvvuK1OvGA1Lly6NFStWdMu+sbExDjjgANlnwKpVqyIiYuutt44IeWdZsViMG2+8MdatWxf77LOPrDPqU5/6VHzgAx+I97///d32yzt7nnnmmZg0aVJMnTo1jjvuuHj22WcjQtZZc8stt8TMmTPj6KOPju222y7e/va3x3e+853O9+WdXe3t7XH99dfHSSedFLlcTtYZs99++8VvfvObePrppyMi4pFHHol77703Dj300IgwtrOkUChEsVjsVu09ImLMmDFx7733yjrDBpPtokWLIp/Pd2szadKk2HPPPeWfQfLOrlWrVkUul4utttoqImSdZe3t7XH11VfHuHHj4q1vfWtEyDtLOjo64vjjj4/Pfe5z8Za3vKXX+7LOnrvvvju222672H333ePUU0+NV155pfM9eWdDR0dH/OpXv4rdd989Dj744Nhuu+3iXe96V/z85z/vbCPr7Hr55ZfjV7/6VZx88smd++SdHfvtt1/ccsst8eKLL0aSJHHXXXfF008/HQcffHBEyDpL2traIiK6za3V1tZGQ0ND3HvvvREh7zTblLUq8k6nnlkPhqzTazB5m0/LhoGyNpeWLaXyNp+WTX2NbXNp2dQzb/Np2TXQ921zadlSKm/zadnUM2tzadm1Kc8ByTqdemY9GLJOr8HkbR4tGwbK2jxatpTK2zxaNvU1ts2jZVPPvM2jZddA37fNo2VLqbzNo2VTz6zNo2XTG/kdK/JOn77yHgx5p89Q8jaflm6Dzdp8Wjb0l7f5tGwZaGybT8uWvvI2n5Y9g/2+bT4tG/rL23xatvSVtfm07Hkjv8N2OLOuG4avhQqzcuXKKBaLMWHChG77J0yYECtWrChTrxgNG/Itlf1zzz1Xji4xTJIkiTlz5sR+++0Xe+65Z0TIO4v++Mc/xj777BOtra2xxRZbxM9+9rOYPn165zd3WWfHjTfeGIsXL44HH3yw13vGdra8613viuuuuy523333ePnll+NLX/pS7LvvvvH444/LOmOeffbZuPLKK2POnDlxzjnnxAMPPBBnnHFGNDY2xgknnCDvDPv5z38er7/+enziE5+ICP+OZ83ZZ58dq1atije/+c1RW1sbxWIxvvzlL8dHPvKRiJB3lmy55Zaxzz77xBe/+MWYNm1aTJgwIW644Ya4//77401vepOsM2ww2a5YsSIaGhri7/7u73q1MdeWPfLOptbW1vj85z8fH/3oR2Ps2LERIess+uUvfxnHHXdcNDc3x8SJE2P+/Pkxfvz4iJB3llx88cVRV1cXZ5xxRsn3ZZ0thxxySBx99NExZcqUWLp0aZx33nnxvve9LxYtWhSNjY3yzohXXnkl1q5dG//+7/8eX/rSl+Liiy+OX//613HEEUfEXXfdFQcccICsM+wHP/hBbLnllnHEEUd07pN3dlx22WVx6qmnxo477hh1dXVRU1MT3/3ud2O//faLCFlnyZvf/OaYMmVKzJ07N7797W/H5ptvHpdeemmsWLEili9fHhHyTqtNXasi7/QplfVgyDqdBpO3+bRs6C9rc2nZ01fe5tOyp6+szaVlU6m8zadl02Cu0cylZUdfeZtPy55SWZtLy5438hyQrNOlr6wHQ9bpM9i8zaOl30BZm0fLlv7yNo+WLf1lbR4te/rKe8WKFebRMmaw12jm0bKhv7zNo2VLX1nn83nzaBnzRn/HirzTpb+8B0Pe6TKUvM2npdtgsjaflh0D5W0+LTsGytp8Wrb0l7d1adkylGs082npN1De5tOyo7+srUvLljf6O2yHM2vFKzIsl8t1e50kSa99ZJPss+fTn/50PProo50Vq7qSd3bsscce8fDDD8frr78eN998c5x44omxYMGCzvdlnQ3PP/98nHnmmXHHHXd0q0zXk7yz4ZBDDunc3muvvWKfffaJXXfdNX7wgx/Eu9/97oiQdVZ0dHTEzJkz4ytf+UpERLz97W+Pxx9/PK688so44YQTOtvJO3uuueaaOOSQQ2LSpEnd9ss6G2666aa4/vrr40c/+lG85S1viYcffjjOOuusmDRpUpx44omd7eSdDf/5n/8ZJ510Uuywww5RW1sbe++9d3z0ox+NxYsXd7aRdXZtSrbyry7yTq98Ph/HHXdcdHR0xBVXXDFge1mn13vf+954+OGHY+XKlfGd73wnjjnmmLj//vtju+226/Mz8k6XRYsWxTe+8Y1YvHjxkHOTdTode+yxndt77rlnzJw5M6ZMmRK/+tWvui2C6kne6dLR0REREYcffnjMnj07IiLe9ra3xX333RdXXXVVHHDAAX1+Vtbp973vfS8+9rGP9fvzkg3knT6XXXZZ/OEPf4hbbrklpkyZEr/73e/i9NNPj4kTJ8b73//+Pj8n6/Spr6+Pm2++OU4++eTYeuuto7a2Nt7//vd3+zlZX+Rd2YZ7rYq8K1d/WW8KWVe2gfI2n5Yd/WVtLi17SuVtPi2b+hrb5tKyqVTe5tOyaTDX5ObSsqOvvM2nZU+prM2lZc9IPAck68rUV9aDLWBRiqwr12DyNo+WDQNlbR4tW/rKu6WlxTxaxvQ3ts2jZU9feW+11VYRYR4tSwZ7TW4eLRv6y9s8Wrb0l7V5tOwYyd+xIu/KM9i8N4W8K89Q8jaflm6Dzdp8WjYMlLd1adkxmLFtPi07BsrburTsGOo1ufm0dBtM3ubTsmGgrK1Ly5aR+h22m5J1zZBakwrjx4+P2traXpVMXnnllV5VUciW7bffPiJC9hnzz//8z3HLLbfEXXfdFTvuuGPnfnlnT0NDQ+y2224xc+bMuOiii+Ktb31rfOMb35B1xixatCheeeWVmDFjRtTV1UVdXV0sWLAgLrvssqirq+vMVN7ZtPnmm8dee+0VzzzzjLGdMRMnTuy1yG3atGmxbNmyiPB9O6uee+65uPPOO+OUU07p3CfrbPnc5z4Xn//85+O4446LvfbaK44//viYPXt2XHTRRREh76zZddddY8GCBbF27dp4/vnn44EHHoh8Ph9Tp06VdYYNJtvtt98+2tvb47XXXuuzDdkh72zJ5/NxzDHHxNKlS2P+/PkxduzYzvdknT2bb7557LbbbvHud787rrnmmqirq4trrrkmIuSdFffcc0+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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 17\n", + "\n", + "ntrack = 4\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"0\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict_smtsmt[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "onehot_[0,motif_embedding_dict[\"smts\"][\"locations\"][ori_index]:motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox2\"].shape[1],:] = patterns_dict_irf4[\"sox2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"s\"][\"locations\"][ori_index]:motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox1\"].shape[1],:] = patterns_dict_irf4[\"sox1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf1\"].shape[1],:] = patterns_dict_irf4[\"mitf1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"sm\"][\"locations\"][ori_index]:motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf2\"].shape[1],:] = patterns_dict_irf4[\"mitf2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap2\"].shape[1],:] = patterns_dict_irf4[\"tfap2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap1\"].shape[1],:] = patterns_dict_irf4[\"tfap1\"][0]\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "\n", + "for ax_ in [ax1,ax2,ax3,ax4]:\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + "\n", + "plt.savefig(\"figures/motif_embedding/ME3_rand_single_double_irf4_st0_end500_deepexplainer_topic16.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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TvQAAAAAAoFOJO0D07rvvRp0GAADZKdEA0T/+YZWUi2XpUuncc63pQIDIaAoQ2ZySJK/plcfnkcMWeQpS7w5mC/nbtzRmEXJIxeeZ7gEAAAAAAJ0OYxABAJCjql3VUaej2blTWrUqdoDIMKQlS4KPo2UQNV/WnH8MIknKs+dJknymT26vu8W+IQfUbJREljoAAAAAAKkUdwZRcytXrtQ///lPlZSUyOUKLxfz8ssvt7ljAAAgvRLJIFqxouVt+XzS5yFJHv5sIJthU749PxDwkawAUbe8bhHbCB1vKLR9vac+LMCEHFTzrWQ4JJNgIQAAAAAAqZJUBtELL7yg7373u1q3bp1eeeUVud1urVu3Tu+884569OiR6j4CAIA0SCRAtHq15GjltpL6YHxHDZ4GGU0ZH3n2vPCAT0gpubD13fUym1KU8h35rbZHDqn+VjK9me4FAAAAAACdSlIZRPfcc4/+/Oc/69prr1VRUZEeeOABjRgxQj/72c80YMCAVPcRWcLhcOjKK68MTCO7sP+A7JDKYzWRANHKlZI3gevzDZ4G2QzrPpTmAaJYJeZCM4jy7cEAUWjpOeSo6g2SfJHz84ulxvJ26waflQAAAEDu4Pw/t+Tq/k7qlW7atEnf+973JEn5+fmqra2VYRi68cYbNWXKFN11110p7SSyg81m06BBgzLdDSSJ/Qdkh1Qeq6FBoarGqpjtTFP6+OPY4w/5hZ4/1XvqZRjBDKLQgE9LASJT1pMUOArC5iPH1ZZEzjtpoTRwulT2tvTOqe3SDT4rAQAAgNzB+X9uydX9nVSJuV69eqm62hrMetCgQVq7dq0kqaKiQnV13OULAEA2CA0QVTZWxmy3datUFTt+FODxBKf9JeZMmXFnENW6agPThc7CwDQl5nKcp07yVIfPG/ZjKzgkSf1PkUZc2v79AgAAAAAgyyWVQTRp0iQtXrxY48aN0wUXXKDrr79e77zzjhYvXqxTTjkl1X1ElvB6vfrwww8lSccee6zsdnuGe4REsP+A7JDKYzU0a6i6sTpmu9WrE992IAhkWuMJxZMRVOsOBogK7AWBABMZRDmubkfkvPGzJdMnGTbr3/Gzpc1Pp70rfFYCAAAAuYPz/9ySq/s7qQDRX//6VzU0WBd+Zs2aJafTqeXLl+ucc87R7bffntIOInt4vV4tWbJEknT00UfnzEHUWbD/gOyQymM1NEDU0hhEn35qlY8LzRBqjT9A5JNPefa8sABRrAyiOlcwC7nAGWzPGEQ5rn57+OMeY6Suw4KPDZtUOEA6YHzau8JnJQAAAJA7OP/PLbm6v5MKEPXq1SswbbPZdPPNN+vmm29OWacAAED6hWYNhWbvNPfNN5LPl9i2693WeEKmaZWYy3e0PgZRnScYCCp0FMpm2OQ1vZSYy3V1zQJEg86UfB7JFnIa6/NY83e80b59AwAAAAAgi8UdIKqKZ/CBJt27d0+qMwAAoP1Uu4IBopaydNavTzxA1OBtkGmagTGI8u2tB4iaj0FkGIZkxi5JhxxRt10yHJLZlMI26AdW1lAowyYNPosAEQAAAAAACYg7QNSzZ0/rQk0LTNOUYRjyer1t7hgAAEiv0LJyLq9LHp9HDlv4qYFpSps2Jb7tBk+DfKYVVcqz5ynPniebbPLJFzMjKDRw1MXRRYas8w4yiHJc3Xap6W9Bhl3qNSF6gKjn4eFZRQAAAAAAoEVxf4t+991309kPAADQzpoHXmpdtepR0CNs3t69Um2U6nM33yxNmCD95S/S8uWRy+vcdTJlSpLy7fnKd+QHMoJiZRCFBYicXSRJhgzGIMp1dduC2UNFB0sh2WhhbE6p64j26xcAAAAAAFku7gDR5MmT09kPAADQjrw+rxq84YGaGldNRICopCRy3fPPl+691yo7N3mydOihUkVFeJvQoE6ePU95tjwZhiG77HEFiAqdhZIkm2GjxFyuq9kiNQUbdcD4ltt2PyTNnQEAAAAAoPNIug7H/v379fjjj2v9+vUyDEOjR4/WT3/6U/Xq1SuV/QMAAGkQLSsntOScX/MAUX6+NG+eFRyy2aTevaW775auuy68XWh2kr/EnCFDMqKPKWSaphq9jZIkp82pAkeBTJlWgIgSc7mtfkdw+oAjJJ9LsuVFtvO5pCICRAAAAAAAxMvWepNIy5Yt0/Dhw/Xggw9q//792rdvnx588EGNGDFCy5YtS3Ufwzz88MMaMWKECgoKNGHCBL3//vut9nXChAkqKCjQyJEjNW/evIg2L730ksaMGaP8/HyNGTNGr7zyStjyO++8U4ZhhP30798/rI1pmrrzzjs1cOBAFRYW6qSTTtKXX37Z9hecRRwOhy699FJdeumlcjgYAyDbsP+A7JCqYzVaMChWgMgWcrYwdarUq1dwnsMhXXRReBspeoBIskrGRcsgcvvcYWMW5dvzZZpW1ggZRDnOXR2cPuBIyYjxd284pe6HprUrfFYCAAAAuYPz/9ySq/s7qQDRtddeqxkzZmjz5s16+eWX9fLLL+vbb7/Vj370I1177bWp7mPAggULdMMNN+i2227TJ598okmTJmn69OkqiVb/RtLmzZt1xhlnaNKkSfrkk09066236rrrrtNLL70UaLNixQrNmDFDF198sT777DNdfPHFuuCCC/TRRx+Fbeuwww5TaWlp4OeLL74IW37ffffp/vvv11//+letXLlS/fv319SpU1VdXa1cYbPZNHz4cA0fPly25lcK0eGx/4DskKpjNZEAkd0efHzuuZLbHd7mgAOkSZPC59V5mpWYswczPqIFiEIDSk67U/mO/EDAiDGIcpi3UTJD/uC6HyoZMf7uDUPqOiyt3eGzEgAAAMgdnP/nllzd30m90k2bNulXv/qV7CFXjOx2u2bOnKlNmzalrHPN3X///briiit05ZVXavTo0Zo7d66GDBmiRx55JGr7efPmaejQoZo7d65Gjx6tK6+8UpdffrnmzJkTaDN37lxNnTpVs2bN0qGHHqpZs2bplFNO0dy5c8O25XA41L9//8BPnz59AstM09TcuXN122236ZxzztHYsWP19NNPq66uTs8991xafhcAALRFIgEir9eattuls8+WnM7wNm63dM454fNCg0D5jnzlO/KjLvMLzRLKt+dbGURN/1FiLoeFZg8ZDqnLoJbb51PqGAAAAACAeCUVIDrqqKO0fv36iPnr16/X+PHj29qnqFwul1avXq1p06aFzZ82bZo++OCDqOusWLEiov1pp52mVatWyd10+3OsNs23+c0332jgwIEaMWKEfvSjH+nbb78NLNu8ebPKysrCtpOfn6/JkyfH7JskNTY2qqqqKuwnm3m9Xn388cf6+OOP5fVfTUTWYP8B2SFVx2q8AaJvv7XGG5Kk0aOlHj0it+V0SpMnh89r9DQGpkMziGIFfEKzhJx2Z7C9aVJiLpd5QgJEXYZIhj12Wyl2dlGK8FkJAAAA5A7O/3NLru7vpIrpXXfddbr++uu1ceNGHXvssZKkDz/8UA899JD++Mc/6vPPPw+0Pfzww1PS0fLycnm9XvXr1y9sfr9+/VRWVhZ1nbKysqjtPR6PysvLNWDAgJhtQrd5zDHHaP78+Tr44IO1a9cu/f73v9fxxx+vL7/8Ur179w60jbadrVu3xnxNs2fP1l133dX6i88SXq9X//73vyVJ48ePD8swQ8fH/gOyQ6qO1WpXZAnUaPNCP8YmTJBM06rk1dyYMeGZRaFZQv4AkSlTpmmqwdtyibl8ezDjyGf6CBDlstAMoq5DMtePJnxWAgAAALmD8//ckqv7O6kA0Y9//GNJ0s033xx1mWEYMk1ThmGkPNpmNLsq5X+eRNo3n9/aNqdPnx6YHjdunI477jiNGjVKTz/9tGbOnJl032bNmhW2flVVlYYMyfzFDwBA5xdPBpHLJe3dG3w8YYJVTi4vTxGcTunAA0PW9boC04EAkWmVjGutxFyBo0D5ditAZMpUras23peFziYsg2hw5voBAAAAAEAnlFSAaPPmzanuR6uKi4tlt9sjsoV2794dkbnj179//6jtHQ6Hevfu3WKbWNuUpK5du2rcuHH65ptvAtuQrIylAQMGxL2d/Px85efnx1wOAEC6xBMgKi21Mob8jj02enBIstqNHu2fNsMCRP4xhXymL2aJubAMomZjFtW6CRDlrNAMosLBks8t2Zyx27e2HAAAAAAABCRVqH3YsGExf4YOHRr2OFXy8vI0YcIELV68OGz+4sWLdfzxx0dd57jjjotov2jRIk2cOFHOpjo4sdrE2qZkjR20fv36QDBoxIgR6t+/f9h2XC6Xli1b1uJ2AADIlHgCRPv3B6cNQxo3Lvb23G7pkEOapn1umQpGlkJLzEnh4w35hc4LzSCSRAZRLnOHjM/YZXB4xBIAAAAAALRJUgGiiy++WDU1kReWtmzZohNPPLHNnYpl5syZeuyxx/TEE09o/fr1uvHGG1VSUqKrr75aklWy7ZJLLgm0v/rqq7V161bNnDlT69ev1xNPPKHHH39cN910U6DN9ddfr0WLFunee+/VV199pXvvvVdLlizRDTfcEGhz0003admyZdq8ebM++ugjnXfeeaqqqtKll14qySotd8MNN+iee+7RK6+8orVr1+qyyy5Tly5d9JOf/CRtvw8AAJIVT4CoKuTa/KBBUkFB7O05nZL/vpDmGUL+AJFftABRaIm5QkdhWAZRtIwj5IjmJeZsrSS/G0klxwMAAAAAkJOS+ha9bt06jRs3Ts8884y++93vSpKefvppXXfddZo6dWpKOxhqxowZ2rt3r+6++26VlpZq7NixWrhwYSBTqbS0VCUlJYH2I0aM0MKFC3XjjTfqoYce0sCBA/Xggw/q3HPPDbQ5/vjj9cILL+g3v/mNbr/9do0aNUoLFizQMcccE2izfft2/fjHP1Z5ebn69OmjY489Vh9++GFYhtTNN9+s+vp6XXPNNdq/f7+OOeYYLVq0SEVFRWn7fQAAkKxEA0Sh4wtFYxjSiBHWdPMxhpoHiEKDQYF57uhjEEmUmMtp7mpZ9zP5pG7DJaOVe5taGPsRAAAAAACESypA9NFHH+k3v/mNpkyZol/96lf65ptv9J///EcPPPCALr/88lT3Mcw111yja665Juqyp556KmLe5MmTtWbNmha3ed555+m8886LufyFF15otV+GYejOO+/UnXfe2WpbAAAyLdEA0ahRVnWvlq6/Nw3v12qAqKUMIkOGFSAKySBqvj3kEHe1FRQyfVLhoEz3BgAAAACATiWpAJHD4dAf//hH5efn63e/+50cDoeWLVum4447LtX9QxZxOBz68Y9/HJhGdmH/AdkhVcdqtABRVWNV+OMqKyBkmtLQodY4Q3l5EasF2JqSO0IzhAwZctgcrQZ86tx1MmTIMAzlO/LDMogIEOUwT3XTH6EkZ+azsvmsBAAAAHIH5/+5JVf3d1Kv1O1269e//rUeeughzZo1S8uXL9fZZ5+tJ554QmeccUaq+4gsYbPZdPDBB2e6G0gS+w/IDqk6VuMNENntksdjBYjird4VGtBx2BwyDCMsg6jR0xixTr27XjbDZgWI7PlhAaVo7ZEj3FVWcMiwSfbCTPeGz0oAAAAgh3D+n1tydX8nFSCaOHGi6urqtHTpUh177LEyTVP33XefzjnnHF1++eV6+OGHU91PAACQQs2DQZJU2VgZ3qYqGBQaMUJyOuPbdvMAUVlNmaobqwPzQscbCszzWAEiU6YVIArNIPI2yDRNGYwvk3vc1VZ5OWe3TPcEAAAAAIBOJ+kA0YMPPqiuXbtKssbfueWWW3TaaafpoosuSmkHkT28Xq+++OILSdK4ceNkt9sz3CMkgv0HZIdUHauhwSBDhkyZEVlFlSHxouHDW9+m220FkTbt2xSYV++p14D/HRDWrtpV3XzVQNDIUFOJuZAMIklq9DaqwFHQeifQuXiqJXklZ/dM90QSn5UAAABALuH8P7fk6v5OKkD0+OOPR50/fvx4rV69uk0dQvbyer167bXXJEljxozJmYOos2D/AdkhVcdqaEZPviNfDZ4G1bpqw9pUVUk+n5VFNGBA8y3E9u3+b1tcbsqMmFfnrgv2p1kGkWQFkAgQ5SBXhfWvI/PjD0l8VgIAAAC5hPP/3JKr+9uWSON//OMfcrlcgcdbtmyR1+sNPK6rq9MDDzyQut4BAIC0CM3i8Qdjmpd+q6qSvF6puFjKy1Or/GM4RhvfqLnmz1XvqQ8EjvId+WFjFvmXIwe5m9LYnB0jQAQAAAAAQGeSUIDoxz/+sSoqKgKPDz/8cG3dujXwuLq6WrNmzUpZ5wAAQHr4s4Vshk2FzkJJ1lg/Xl/wxo/9+61/e/WKb5v+IYJCs4Fi2V+/P+xxvadepmnKlKk8e57sNrtsRvA0JZ5tohNyN42V1UEyiAAAAAAA6EwSChCZptniYwAAkB38AZd8e35Y6bbQQIz/npDuCQ7/UuuubbVN6BhIkpVR5DN9Mk0zkNEUmkXUPOMIOcLdlOlGBhEAAAAAACmXUIAIAABkP5/pU4OnQZJU4ChQF2eXwLLQ8nCVTTGcRANE8WT7VDVWRaxjNv2X77ACRE6bM7CcEnM5ytsUbCRABAAAAABAyhEgAgAgx9S7g+P9FDgK1NXZNbAsNEBU3ZS8kWiAKJ5sn4qGirDH/uf1mT4yiGAxfZLXCmTK2d16DAAAAAAAUsaR6ApvvfWWevToIUny+Xx6++23tXbtWkkKG58IAAB0TKFBoEJnYcwMopqmyYQDRHFk+1S7qsMeh5al82cQ+QNFEmMQ5SRP8G9RjiLJ9EoG9zYBAAAAAJAqCQeILr300rDHP/vZz8IeG/4RqpFzHA6HzjvvvMA0sgv7D8gOqThWQ4NAXRxd1C2vW8Qyt1tqbLTmde8ueb2S3R7f9uPJ9qluDA8QhfZpf/1+bdy3MeycghJzOcgd8jfiLJKU+bEv+awEAAAAcgfn/7klV/d3Qq/U56O0B2Kz2Ww67LDDMt0NJIn9B2SHVByrodk7hc5CFToLZciQKTOwrDrk2nyiASL/+Ebx9kGSSipKAtMzF83UzEUzw5Z/Wvqpzhl9TnwdQOfgDQkKOoo6QnyIz0oAAAAgh3D+n1tydX9TpwMAgBwTmq3TNa+rCh2FgWwd/7KqqmD7REvMNXobW23TPIOotXW2Vm5NrBPIfqFjDjmLJLLUAQAAAABIqaRzpTZs2KC//OUvWr9+vQzD0KGHHqpf/OIXOvTQQ1PZP2QRn8+n9evXS5JGjx4tm434YzZh/wHZIRXHaliAyGkFiGyGTT7TFzVA1DT0YNziCRCFjjkkSWYr6SHN26eEzyPVbJbseVKXoQQgOhrTG5x2FElGnClsacRnJQAAAJA7OP/PLbm6v5N6lS+++KLGjh2r1atX64gjjtDhhx+uNWvWaNy4cfrnP/+Z6j4iS3g8Hr344ot68cUX5fF4Mt0dJIj9B2SHVByr/iCQIUNdnF0CJeZshi1mBlEi50Uur6vVNrWuxAI+de66hNq3yl0tvXOq9MbB0mvDpY//R/J5W10N7Sg0gyivp2Rk/uScz0oAAAAgd3D+n1tydX8nlUF08803a9asWbr77rvD5t9xxx265ZZbdP7556ekcwAAIPX8QSCbYbPGIHIUBh7HyiBKZHxGt9fdapvQjKB4xjhMaYDIUyctOVGq+CI4b9PjkrtK+u4LZBJ1GCF/F/aCzHUDAAAAAIBOKqlbMcvKynTJJZdEzL/oootUVlbW5k4BAID0qXHVyGbYrACRo1CFTitAZMgIBIhqglXodMABiW0/ngyi0IBPRUNFq+3r3fWJdaIlX/9V2v9ZeAkzmVLJP6TyFal7HrRNaAZRBygvBwAAAABAZ5NUBtFJJ52k999/XwceeGDY/OXLl2vSpEkp6RgAAEgPf4BIkhUgchTKNE0ZRjBA5A2JnSQ6BlE8AaLQgM/+hv2ttm/wNiTWiVhcldLaP0hRxzyySxsekPocn5rn6qC8XmnLFikvTxo8uAMnTIUFiNJYXq6kRCovD59XWipVVFjTPXtKAwZY0zlUZgAAAAAA0PklFSD6wQ9+oFtuuUWrV6/WscceK0n68MMP9c9//lN33XWXXn/99bC2AACg46hx1ciQFRUodFoZRF7TK7thDwSIQqu+de+e2PY9vtYvotd7EgwQeVIUINrwoOSpibHQK1V/k5rn6aD275fOOkt6/33r8WWXSX//u+R0ZrRbMYSWHkxTgKikRDrkEKkhzr8vp1O67TZrets2adSo9PQLAAAAAIB2kFSA6JprrpEkPfzww3r44YejLpMkwzDk9TLgMwAAHYk/CGTKDGYQyZTX542aQVRUlNj24woQhWQQxVNirtHTmFgnojFNafPTCg88NNOJS5lVVkrHHCN9+21w3tNPW8kyCxdKtjQm6SSlPUrMlZfHHxxqbu9eAkQAAAAAgKyW1KUAn88X1w/BIQAAOp7qxmqZMmWaZiCDSLICRlWNVZLCM4jy8hLbvs9sIQDTJDQjKJ4AUTxl61pVuU6q2dRyG7Pznrvce6+0aVN48M80pbfekhYvjr7OS+teUu/7emvljpXt08lQ7VViDgAAAACAHJVUBlGohoYGFRQUpKIvyHJ2u11nnXVWYBrZhf0HZIdUHKs17hr5TJ9M01QXZxd1cXYJLKtsrJQUHiBKNLPEG0eQpdEbzAiqbKhstX1KAkTbXrIyUTpxECiWbduk//3f8P3qZxjSn/8snXZa5LK/fvxX7avfp9c3vK6jBx2d/o6G6oABIrvXq7NefdWa/t73MtsZAAAAAGnFtbLckqv7O6kAkdfr1T333KN58+Zp165d+vrrrzVy5EjdfvvtGj58uK644opU9xNZwG63a/z48ZnuBpLE/gOyQyqO1erG6kCWj7/EXOgyKTyQYBiJbd80zVbbhJaMq3ZVt9o+JQGikn/kZHBIsrKHogWHJCuLaM+e6MtcPuv3XueuS1PPWtIBA0Q+n8Z/+qn1oMPV5AMAAACQSlwryy25ur+T+mb7hz/8QU899ZTuu+8+5YXUnRk3bpwee+yxlHUOAACknj9LSFJYiTkpGKwJLUOW6I0zploPEIUGfPxl7VoSz7hGLWrcJ1V+2bZtZCm3W3r2WcnTwq8wVhCw1lUrSdpbvzcNPWtFaDAv1hhEtSXSvjXWz443pc3PSntWtE//AAAAAADIckllEM2fP19///vfdcopp+jqq68OzD/88MP11VdfpaxzyC4+n08bN26UJB144IGycWdtVmH/AdkhFceqP0tIiswg8gcEfD4raGCaiWcQxcOfmdK8P7G0OUBU/kH0+Ya9qZRZ60GtbPXOO1JFRcttYmUX7W/YL0naW5eBAJFC/vCiZaXVlkj/OkTyNUQum/qB1Oe4lPfIZ7Np46hRkqQDfb7k7rQCAAAAkBW4VpZbcnV/J/Uqd+zYoQMPPDBivs/nk9vtbnOnkJ08Ho+ef/55Pf/88/K0dJsyOiT2H5AdUnGshpZ0a55B5C8l5g8QSYlV0vLFijQ04/YGzxdqXDWtb9eMb7sxlX8oGc3uizn4l9KMBun8Kmng9LZtvwN7/nnJkeSok/vq90mSyuvLU9ijOIWVlYuy/xvLoweHJKnm27R0yWO36/kLL9TzF14oT5x/6wAAAACyE9fKckuu7u+kAkSHHXaY3n///Yj5//znP3XkkUe2uVMAACB9/FlCUmQGUYOnQT7TF8goSTR7KJ5gjyQ1eoNjEIX2J5Y2B4j2rQkvWTb8Imnig5LNITkKpRNfl3pNbNtzZMC2bdL06dLQodK0adKWLeHLvV7plVdaLi/XEv/+LK/NQIAo9DS1rfsfAAAAAABESOp+0jvuuEMXX3yxduzYIZ/Pp5dfflkbNmzQ/Pnz9cYbb6S6jwAAIA6maWp//X51zeuqfEd+zHb+LCEpMoPIlKl6d7283q4yjMSyhyRpf+P+uNqFloyrdbceIIpnXKMW7VupQBk5wy4d8Xsr6GDYmsrMuaVxd0if/7Ztz9OOPvhA+t73pJoaKwBUWiodcYT0r39JJ55otfniC6mq9SGeWrWnbk/bN5IogwARAAAAAADplFQG0ZlnnqkFCxZo4cKFMgxDv/3tb7V+/Xr961//0tSpU1PdRwAAEIfPdn2m3n/qreEPDI/ZxjRN1XvqA4+bZxBJVtaIf8iXRDOIqhrii0YkGiBqk/pdVjkyv6EXSF2HhQcgbE5p0PelooPS25cUqauTfvQjK/jjzw7yeKxg0Y9+ZC2XpPfeiwzyjRghPfyw9Kc/ST16xH4OM2Tcn8rGyhS/gjgQIAIAAAAAIK2SrEgvnXbaaTrttNNS2RcAANAGu2p2SZIaPY0x2+yr3xdWru2MZ8+Q3WYPa7O+fL1stn6SpESHWYk3kOD1Bcu91bvrW2gZ5PF55LAlceqy/9Pwx4fdJvm8UrPXLZ9bGnlpy9syfZK3XnJ0TbwfKXTXXdKOHZH7x+eTdu2SHnlE+tWvpJUrw4N8hx0mLVtmBYYMQ/r+96UTToj+HPGWC0ybsACRN3Y7AAAAAACQlKQyiCSpoqJCjz32mG699Vbt22cNYLxmzRrt2LEjZZ0DAADxK60plRReQq65spqysMclVSXaXLE5bN6uml2y2STTTDxAVNUYXwZRaJAqNKOpJfvr4ytfF6HiU6uMnCR1GSz1PCwyOCRZWUR9JkXfhmlK38yT/tHN+nlzrFTxZXL9aaNdu6T//d/Y+8bnk55/3ppescIah8jvz3+2gkMOh2S3SwceKN1yS/TtNP9baf+AUehpKhlEAAAAAACkWlIBos8//1wHH3yw7r33Xv3pT39SRUWFJOmVV17RrFmzUtk/AAAQp53VOyVJjd7YGUTxjCWzt36v7HYrJmImOPRP83J1sYRmLTV4GuJaZ39DkgGimi0KnPL0ndxyW2dR9Pkf/Y+08udW9pAkVX0l/ecoqezt5PrUBvPnx7dfqqulb78NPv7ud6WpU63gkJ/DIf3yl1Lv3pHr76rdFf64Zldko3SixBwAAAAAAGmVVIm5mTNn6rLLLtN9992noqLghZTp06frJz/5Sco6h+xit9s1ffr0wDSyC/sPyA4tHatl1WXRVglTXlfeapt99ftUHHJt3uu1sk3iUeAoCHu8/PLlOrL/kZKke96/R/cuv1ce06MCe7Bd3AGiZDOIGnZJZtNAPX0nW6XkbM7obU1vMNvIb9sr0rePRbYzTemDi6UzN8QOLKWYaUrz5rWe2eXzSZ9+Gh5Iuvtuye2WnM1eusMhXRqlsl7zgNCu2l0a1WtUch1PRnuUmCsulgoKpIb4/gbtXq+mv/mm5HTKHu2XBgAAAKDT6AjXyhYvtsqH79lj3fT30ENSv34Z6Uqn1xH2dyYkFSBauXKl/va3v0XMHzRokMrKWr84hc7JbrfrO9/5Tqa7kXtMU9r6gvTV/0reBmno+dJht8a++BkD+w/IDi0dq6W1pa2uv7dub6tt9jfsV19bMLiQSBZR82BPz/ye6uLsIkkqyiuSDEmm5PK6Am1Cp1tS0VARf0dC1e+wnlSS+p7Y8vujaVp9DHRuv/TRlQp0PIxPatwtbXhAGvub5PqWoBUrwrOCWrJ6tWSzWcGi4mJpypTo7RwOqekcOEzzEnPNH6dfaJQyvjKECRs6VNqwQSoPCZyuXy9ddFF4u2eekUaPll3SdyTrFzp0aHr6BAAAAKBDyPS1srvuku68M/i97rXXpHfesYJGEyZkrFudVqb3d6YkFSAqKChQVVXkGAMbNmxQnz592twpAHEyfdIHF0lbn1fg4uUX66RtL0unLJPye2a4gwDa086qnYFpt9ctpz0yELKvfl+r26lsqJQt5Np8IuMQNR9PKM+eFzZtNkWbXD6XTNOUYRhq9MQuiReqorEi/o6EdaopcGYvkIoObLmtrdmp0aYnrSBRRHCoiemVtr/ebgGiN96wAjoeT+ttN260Mr98Punkk1tu2zFLzIXcseWqtD7zjKSHz4xt6NDWgz2jR0tHHZX65wYAAACAKBYvtoJDUvA7uccjVVVJF1wgrV0rFcZX4R1oUVLfss866yzdfffdcrvdkiTDMFRSUqJf//rXOvfcc1PaQWQPn8+nLVu2aMuWLfIlOqo5kvPVn5uCQ1Lw4qUpVX4pffn7hDbF/gOyQ0vH6vbq7YHpWNke8YzjU9lYGVZSLpG3hOYZRM0DRL6msWR8pk8enxXlcPniyyCqaoi8OSUujU3ZIT3HRZaPa4npk77+S3zt2snChZHBobPOku6/X2p+ClZaGmx7yilWeblYou3jaCXm2lVoMMhTnb4ycwngsxIAAADIHZk6/6+qki6+WGE3bvp5vdKWLdKDD7Zbd3JGrn7fSypANGfOHO3Zs0d9+/ZVfX29Jk+erAMPPFBFRUX6wx/+kOo+hnn44Yc1YsQIFRQUaMKECXr//fdbbL9s2TJNmDBBBQUFGjlypObNmxfR5qWXXtKYMWOUn5+vMWPG6JVXXglbPnv2bB199NEqKipS37599cMf/lAbNmwIa3PZZZfJMIywn2OPPbbtLziLeDwePf3003r66afliefWZrRNxVrp019HX2Z6pV3vJLQ59h+QHVo6VkMv6O+s3tl8VUnxlWmrbqwOOxFtS4m5iAyikEwcf1u3t4XIRYiqxiQCRJ66YHmynuMTC+aULZFqtyhm9lBA+5w4VlVJn38ePu+ee6RXX5V++UvpxRel//3f4LLt24P7bsqUyLGHQkU79y2rDQ8ytn8GUcgfobsqsT/ENOGzEgAAAMgdmTr/f/xxaffu2Ddr+nzSSy+1W3cyw+uStjwnbXhQ2rOiXZ4yV7/vJRUg6t69u5YvX66XX35Zf/zjH/WLX/xCCxcu1LJly9S1a9dU9zFgwYIFuuGGG3Tbbbfpk08+0aRJkzR9+nSVlJREbb9582adccYZmjRpkj755BPdeuutuu666/RSyBG0YsUKzZgxQxdffLE+++wzXXzxxbrgggv00UcfBdosW7ZM1157rT788EMtXrxYHo9H06ZNU21tbdjznX766SotLQ38LFy4MD2/CECS1qY3GAsgu7i8LjV6g6XaYgWIKhsqW91WtSs8QFRXF38/mgeI8h35UaelYDm65vNjOaDggPg7EuhQSFCj6CDJl8BJ3pbnJCOparxp8fHH4TGSY46RZs2yph1N3Zw5UzrhBGt6Z9OfQNeu0qhRLW/bEeVl7qjaEfa43ccgsofUS3BXt+9zAwAAAEAGeL3Sn//c+v1xnTrBZe9KaeHh0gcXSqtvkBYfL314Bd8L0yThqx4+n09PPfWUXn75ZW3ZskWGYWjEiBHq379/YCyBdLn//vt1xRVX6Morr5QkzZ07V2+99ZYeeeQRzZ49O6L9vHnzNHToUM2dO1eSNHr0aK1atUpz5swJlMKbO3eupk6dqllNV1hmzZqlZcuWae7cuXr+eat013/+85+w7T755JPq27evVq9erRNPPDEwPz8/X/3790/56wYi1G2Xtv2zQ5TbAdAxNL94HytAFE8WTq2rVraQmE11dfQxaqKpd9fLkBHIFGqeQRTKH0zqmd9T5XXlchgOXXHkFXr4+w9LsjJWBt4/MNC+KL8ovk6EPUlIgKiwnxTveYrpk3a8LpnNAko9x0ldR0h7lkuu1sdzSqUPPrDGFPJ6rZfxl79YJeRCgzsejzX/8sulPXuseUceGb00QWua/03tqN4Ro2WaOEP2t6c6/n0HAAAAAFnqzTelbdtab9dpA0S1W6V3TpU8/sSMpkjZ5qcld4V0wot8N0yxhC4XmKapH/zgB7ryyiu1Y8cOjRs3Tocddpi2bt2qyy67TGeffXa6+imXy6XVq1dr2rRpYfOnTZumDz74IOo6K1asiGh/2mmnadWqVYHxk2K1ibVNSaqstO6+7tWrV9j8pUuXqm/fvjr44IN11VVXaffu3fG9OES1f790443Sd74jTZ8utVJNMLd8/XCmewCgg2keEIoVIKpx1bS6rTp3XdgYRJWtJx0FNHgaZAspDRZPgKjBa/1rGIYKnAWyGTbZDJsKneEjbvozjhISGiAqGCDZWqizFqric8nVbLymw38vTf9Umvya9P31Up8TEu9PGyxfHvwS8L3vSUcfHZn543BI48dbWUSNTQllRx1lBZUSYZqmyuussZscTVlU7Z5B5OgWnHZXJzZ+FAAAAABkoWefVdj38Zzic0vvn2eVim9+U7zplba9LG39R2b61okllEH01FNP6b333tPbb7+tk08+OWzZO++8ox/+8IeaP3++LrnkkpR2UpLKy8vl9XrVr1+/sPn9+vVTWVn0CxZlZWVR23s8HpWXl2vAgAEx28Tapmmamjlzpk444QSNHTs2MH/69Ok6//zzNWzYMG3evFm33367pkyZotWrVys/P3rpnMbGRjU2BssBVVUlOfh2J/TRR1ZQqKrKuqhls0n/+Y90ww3WQNw5HSg2TWnzfLKHAISJCBDVRA8Q1bpro84P1eBpCAs8VFTE348GT4OVTdx0k48zJCDTPEBU764PrOOXb8+POh3aPiGhAaIuA2O3a273e5IMBV7IkHOlsbcFl+f3lia9JL1+YOJ9StJHHwXLDJx9tuR2Rx9XyO2Wxo0LPh450vosTeRLRo2rJlCyMM+eJ4/Hoz11e9rQ+yQYNqvMnLe+KYMoqcrIAAAAAJAVXC4rg6j5DX4zZljf6/71L2nt2sz0rV1sfkbat6rlNl8/KA2f0T79yREJBYief/553XrrrRHBIUmaMmWKfv3rX+vZZ59NS4DIr3kJu9bK2kVr33x+Itv8xS9+oc8//1zLly8Pmz9jRvAPc+zYsZo4caKGDRumN998U+ecc07Ubc2ePVt33XVXzL7nqtJS6cwzg8EhKXjH9Ny50vHHS+efn7HuZV7FZ1J9szI/eQdIh9xglePZ+DepakNGugYgc5oHiLZXbY/ars7d+oBC9Z56de8efLx/vxWYiCc4X++xSsxJksPmCPs8jZlB5A4JEMUYs8hu2K0MopISqbw8/ElLS4NRrJ49pQEDgsvKP7HGETI9Un74DSEt2rXMCkiYXiuTZeJfrWl/Fothl/J6S4ffJW3+v/i3m6SaGutzUbL2w1lnRQ8OSdb8wYODj/v3T/wOtNBsoS7OLqrz1KnB06AaV4265XVrYc0Uc3S1AkTUmgYAAADQya1cKYUOee9wSK+/bt1E7/VKd90l/c//SE89lbEupo/pk768R2E3akYTMvYyUiOhANHnn3+u++67L+by6dOn68EHH2xzp6IpLi6W3W6PyOzZvXt3RAaQX//+/aO2dzgc6t00mEKsNtG2+ctf/lKvv/663nvvPQ0OvfISxYABAzRs2DB98803MdvMmjVLM2fODDyuqqrSkCFDWtxuLrjoIutiZKxyOPfdl+MBotLFsqpDNkXNuo2Spn0g5fWSZEoHXSO9f45UX5rBTgJobzuqwgPHJRUlUdvFU6at0dMYFiDyB+yblzOLJjQbyNmsnFvzjCB/W3+miikzrI3NsMlu2OU1vTIMQ47tO6WTD5EaGhS3SyVNkeQwpPwD4lvHNKXd7wYzNQ+9UcrvE1nizGaXDrleKnsn/v4kaUfI7h0/vvUxoUKTkgcNSjxAtKs2mHnVLa+byuutoNyuml3q1qs9A0TdpMZyyU2WNQAAAIDO7d13g+POStKvfiWddpo1bbdbP488Ii1blrk+ps3216WajXE07KyDL2VOQgGiffv2xQzGSFZptv3798dc3hZ5eXmaMGGCFi9eHDbW0eLFi3XWWWdFXee4447Tv/71r7B5ixYt0sSJE+Vsuu32uOOO0+LFi3XjjTeGtTn++OMDj03T1C9/+Uu98sorWrp0qUaMGNFqf/fu3att27ZpQOhdzM3k5+fHLD+Xjex2u0499dTAdDLee096p5XrbDldXk6SypaEPDCkY5+0MohsTYez6ZWOfVp6/9yENpuK/Qcg/WIdq81LypXWRA8Sh2brxOLyutSjR/BxVVX8A2CGBYjs4QGiaBlEXp9Xbp81LqBpmmFZQ/5teD1eGTJkK9+XWHBIknrIiqnn945/DJvaLeHjDw2/sIXyZqbUb0pifUpCaIDou99tvWTczp1WeVafzwoQJWpXjRUgshk2dc/vLkOGTJnaVbtLo3qNSnyDyXI2RSo9UTKI8oslW4Hki/I3kdczLd3hsxIAAADIHe19/v/228Hv3qNGWRlDtmZfRe126W9/k265Je3daV/fPmF9Z8/gkBq5+n0voQCR1+uVo4Xbh+12uzweT5s7FcvMmTN18cUXa+LEiTruuOP097//XSUlJbr66qslWRk5O3bs0Pz58yVJV199tf76179q5syZuuqqq7RixQo9/vjjev755wPbvP7663XiiSfq3nvv1VlnnaXXXntNS5YsCSshd+211+q5557Ta6+9pqKiokDGUY8ePVRYWKiamhrdeeedOvfcczVgwABt2bJFt956q4qLi8OCWZ2d3W7Xd7/73TZt4847wyPl0aTxT6zj87qkPe8pEC0fdaXUd1J4G8NuXRg79FcJbToV+w9A+sU6VrdXhpeUq3ZVq95dr0JnYdj8Bm/rARaPzxORQRSvBk+DzKZ08OYZRBFjEHnqwwJKzTOI/Os0zzRKSJGsAFFBAuXlareErH+Q1P2QFhobUv9TEu9XgraH7N7jj7e+NLR0vlpaai33+aS+fRN/vrKaMhlN//Us6CnDMGSaZljpuXbh7Gn9G63EXNeh0pkbrAyjyvXSiouCywpj36DTFnxWAgAAALmjPc//GxulDz4Ijjv7619HBockq6T41KnSc8+1S7fah7ta2vmf8OBQXi9p7O1StxHS9tekb59Mezdy9fteQgEi0zR12WWXxcx6aWxMbw3AGTNmaO/evbr77rtVWlqqsWPHauHChRo2bJgkqbS0VCUlwZI6I0aM0MKFC3XjjTfqoYce0sCBA/Xggw/q3HODmRXHH3+8XnjhBf3mN7/R7bffrlGjRmnBggU65phjAm0eeeQRSdJJJ50U1p8nn3xSl112mex2u7744gvNnz9fFRUVGjBggE4++WQtWLBARUVFafyNdC5r11qplGjBvpVS6MXdsbdZNTqb39luc0iDv9++fQOQUduqtklSoCSbZGURjTxgZFg7l9fV6rZ8pi8iQBRv9ma9p14+0wpiNw8IRcsgCh0TyWf6IjKIQtdp9CRxnuEPoiQUIAopzzfwjPCxh5ozbFLPsYn3K0Hbt1sl/jweadKk2OMP+e3ebQWHunSRunZN/Pl21e6S3WaXx+dR7y69ZTNsMk0zkFnUbvyZQLHGIOo61PoBAAAAgCy2YYPkavq67nBI550X+3uf2y01Jbp0DruWSqY7+Lign3TGZ9a4v4ZNGnyWdYP8h5dnrIudWUIBoksvvbTVNpdccknSnYnHNddco2uuuSbqsqeijNA1efJkrVmzpsVtnnfeeTrvvPNiLjfNFgbGklRYWKi33nqrxTa5wOfzqbTUKmk0YMAA2aKFuVvw3HOR2UMHHSSdfrq0bZv02mvBKHrOqlirwGBtBxwldR2Wsk23df8BaB+xjlV/SblCZ6FqXDWSpJ3VOyMCRB5f62mYpkx17WoFhUzTChDFm13d4GkIfG7GU2Ku+ZhIzTOI/I9NmXFlP0Xw9zu/OP516rZJhkMyPVLfydYvoaUAWczyc6mzY4e1P+x2qYXqtQFlZdbnaf/+yT3frppdgUBfcZdieX1eOWyOsLGJ2oWzyArORSsxlwF8VgIAAAC5oz3P/0NyHjR5stSzZ+y2Tqc0bVrautL+yhYFv4NLTcNp9AoOpyFJI38q7XhTqvk2bd3I1e97CQWInnwy/alcyF4ej0ePPfaYJKvcX15eXitrhPvnP8ODQ//zP9Jf/2pdDLPZpP/+N743P5/PupbXKUtF1m5tesN0S0PPk3xuyRbrNvLEomlt3X8A2ke0Y7XOXRcICnXL66ZaV61MmdpZvTNifa8v3nq+PnXpYlNtrVRZGT21PZp6d32gxFxEsCckO8iQoXp3verd4QGiWFlHPtMXVo4ubv7PAlsC72l124LT/U4OPymNpsX34tTYts3KHhowIL7Pt9pa699kA0RltWWBAFH/bv1lypTP9LV/BpGjqUagp6Z9nzcGPisBAACA3NGe5/9btwZv0pw61coSaqlyRJ8+aetK+9vxZjA4NOISaeD0yDamTzrmMem9H6atG7n6fS83wmDo8DZvljZuDD7+znekhx6y3gj9FyWPPVZ68MHY2/jqK+knP5Hy8qz1TjhBeued9Pa73dVuVWD8oQGnW8GiWOIdjB1A1iutLg1M9yroJUmyGbaoASIzzuDxvoZ96tbNmk5kDKJad21guqVycTbDFj2DyBE9g8hn+pIbgygQIErgnpjardbJadfhwRJnLWnpvThFtmyxvigMHhxfe3dTdn6yAaIdVTsC0wOKrJQlr+nNwBhETaV6TZ/U7G8FAAAAADqLkhKrtJxkBYgcrd2n6Et/n9pF3Q6pdnPw8SHXhY9F5GfYJGd3qf/U9utbjiBAhA7h3/8Ojm9RWGhlEzVnt0tXXCFNmRK5bNkyafz4YBaSaUoffiidcor0xBNp7XrqmaZUukhaP0fa+Kjk2h9cVrPJepN09pAOOCL+QUEAdGr+QJAhQ7279JYpU4aMiABRayVTQ1U3VgfGIUokQBSaEdTSGESGYUSMQSS1nHXUPNsoLv4znUSCODVNJ6fxjm3TDu/FO5riNfEGiDxNN18VFib3fKGBoMFFwSfdUb0jWvP0cXZXICPWncAfIgAAAABkka1brWua3bpJR8Rxya/TBIiqvw5OFx0o9ZoQ+6Z305QGndk+/cohBIjQIfznP8E3vnPOkYYOjR4p93qln/40fN4nn0jTp1t3S3s84W0lq0xd1qj4Qlp4uPTuadKnv5Y+/pn0ymBp3Z+sN8HaLVa7Pse3y5gXALKDPxBkM2zq26WvJCvjpnmAqHkGzm2TbtPHV36sj6/8WHNPmxu2zJQZqHmcUIAoJMujebAnLEAkK0DUPOjTPIOowFEQ3HabAkR2KwslHnXbrX+7DEn8+dLA5ZL27bOmBw0KL8cai//zsLW7zqIxTVPldeWBx8N6BMe7a/cMIkdRcL/Vb2/f5wYAAACAdvLtt1bQ58AD4ysrnsx3vQ6pJiR7aPDZUktl8W126YDD09+nHNNZ/pSQ5b74Ihj5vvJK68JWtDc6u1067LDgY69Xuvxy6+JZ1kfO938uLZkcHIjbn07prZM+vVmy5UsNe6x53UZZF8wIEgGQFSCyGTYZhhEoB2bK1LaqbWHt/OMU+Y3pM0ZHDzpaUnhpOH/bpAJEIUGc0OCOFJlRVO+pjywxZ48dICotcEsFBVJDAmMRhZWYi5FBVVsiNZZL9aVS3U7rfVeSugxtl/GFWlMWEpMZPNj67GvtC4O/xFwyXxpqXDWBYKLD5tDAooGBZXvq9iS+wbZwFilQWrVmi3TA+A5ZQtXnk159Vbr3XmntWqmoyMp6vv56qW/fTPcOAAAAQEe3ZYv177BhLTbrfGo2S4bTGm99wOkSxZLaHQEiZJzXK21vuim4uFg68cSWB0MPDR499pj06adp72L6uWukd0+3gkPR6mxK0sa/KXCRrOswyeeR7LkxWBqAlu2s3im7YZfH59Gg7oMC87dVthwgKnQURp32t+3Z08ru3BNnTMDrDc8gai1AFE8GUaEz2K9vizzShg1SeTC7RevXSxddFN6RZ56RRo+2pjf9UHJva8pCiXKmWVsi/esQyRcl6NR1iJW9mWH1Ib+iQYNa/oz0C80g8vniW8cvNEuoe353HVB4QOBxg6dBNa4adcvrFv8G28I/BpEk1e+w7iaL53a6duTxWMGg+fOtrnm9Ul2dFSx69FFp+XLp4INT93w+n1RbK3Xtmth+BQAAANAxuVzBr7lDh8Z3U2CnUbtZkk+yF0h9J7V+Q2AHuImzs+FrJTJu+/bghazTT2/9Yod/uccj3XVXevvWbj7/rdSwK3ZwSLLeAP26DuuQd1ADyIwd1TvkNb0yZWpoj+C4Oc3LgUUEiEKCL6HT/rbdu1snpdXV1k9rfD6p0RMsY9c82GMzbLI3vXeZMuMagyisxJyn3jpbPuqo4I8/EBRq9Ojg8sKuTZ3zKGqAqLE8enBIsjKIbJm/l8Yd8vY/aFB8WUGhAaJEY1y7ancFpnsW9JTdZlc3ZzAgtKtmV7TV0sMREiCq294hM2cvv1z6v/+zpkPL/3m9VmnA//mf1DzPrl3S//t/Us+eUvfu1s/MmVJpaWq2DwAAACAztm8Pfm8bNiy+suKdRvU31vXQooPjC/wQHEq5zF/1QKdht9s1efLkwHQEd7W089+Su1LqfqjU5wTJMLRpU7DJaadZF8KcLRzr/gDRwoXhF0Xy8qTbb5euu86qQPT889KsWSl4YelW9Y20Ya5ilj7y84WMHdJtlFV3M4Va3X8AOoRox+q2ym3yNY3TMqDbABU4CqzsHE+9qhurVZRvXWRPNIOoe/fg+HDbt0ePxYSy2YLjHNkMW0TGkCQ5bU55vV6ZphnoY6jmQaV8e75shk0+05fcGERG0weK6Wl9lM/muo3sEAGJ0PH1Cgtjtwvlfxv3ehN/2aEBoOLCYklWoKjGbf397KrdpVG9RiW20WQ5mwWIMhywa378vfJKMDgUjT+bqK02bJBOOcUqN+j/slhbKz34oHW+s2xZarOUAAAAALTftbKtW4PTQ4fmUPaQJNU0XRjuNjKz/VDuXhslQISUsdvtOumkkyIXmD5p7e+kdfcFx3WQrMjwMY9p06ZJgVlHHtlycCjUM89Yd0Z7mq75zZ8vnXde8E30Jz+RvvMd6eqrk39N7eLrB60LkP7sIVueNOJSqf8p1ngYX/9FqvlW8rkkw2Fd5Oya+oKkMfcfgA4l2rEaOtZQcZdi9SropZ01OyVZ5ecOyT9EUnIZRH7ffisdckjLWZ52ezCDyJARNUDksDskr6yAj6de9e562Q27vE3vgc0ziPId+TKaMn/8waeE+IPpLWVoxtJlUOtt2kFoBlFenJVF/VlGniTiYmU1ZTJkyJSp4q5WgOiAwgO0vXp7YHm7cYb8EdZtb7/njSH0+KuutrKDDKPlLK3QAF8yysqk735XqqyMvJPQ67VKQF51lRUkAgAAAJA67XWtbPfu4PTIkVkSIKovtX4K+iX/3dlTLzXutaa7jbBKiqf4hvhE5Oq1UQJESC+vS/rgJ9K2lyKXVW+U3p6iTZ99LadzhNxuacSI+DZbXS299lrwostdd0kXXBB+EczplA46SJozp+0vI228jdK384MXLu2F0pS3peJjm8bL8EkHX2ONT1Sx1nqBtgIpv3dGuw2g4zBNM6wkWHGXYhV3LQ4PEBXHCBDFyCAyZAQCRL6moc+2brXec1sKUJimKXdTOUzDMCKCPVJwHCJTpurd9ar31MswjEASZbQMIv/y0PJ1cTOaTnXMJK7S2wpab9MOQgMM8ZSXC22XVAZR7S45bA75TJ96F1qfN3269pFk/W1krsRcSfs9bxwee0zauzc8ODRypDWWYmmptHhx8PhJlmla4xtVVMQuM+H1ho9TBQAAACC7uFzB6WGpvyc8tco/kj77jbRrSXBe35OkI/4g9Tk+sW3VbglOdx3RdH00G6JjnUvm66ag0zBNU7t379bu3btl+q+WfH67tO3lGGv4JNOjTZ99K69X6tNH6tIlvud6663gm2dxsXTzzdEvgDkc0tFHJ/xS2s/ONyVPlTVt2KRJL0u9v9MUCLI31dW0S5PfkPIOsC6gFqbnjvao+w9Ah9P8WK12VavBExxDp3eX3urbtW/g8c7qnYHp6sbwgYRiZRDZbXZVN1arR4/gRelt21oPNIRm+MTKIAqdV+euU527LpAhJEXJILIHM4i8pldur1sJ8dcndlUktp6U0TuXQrUlQJRM9soHJR/I4/PINE2t3b1WNy26SdsrrewdQ4aWlyxPfKPJal5iztfGdJw28h9/u3bt1oMPmmHBoXvvlb75RnrySek//5HWr5eGDGnb8738slVSt7Ua5G3NUgIAAAAQqb2ulYVWjSgqit0u4zb/n7T4BGn3u+Hzd78vLZksbXs9se3VbA5OdxuZ8ZLiuXptlAARUsbtduuRRx7RI488IrfbLe16V1p/n1obW+erbcPk81l33cbriy+CF79+/vOWL5i5E7yW2K62PCc1DdiuoRdIA0+PvCBps1tl53oeYT22p+eO9oj9B6BDan6shgaAuji7KM+ep75d+8pm2GQ37GHLa1w1YcGY0KyhAkfwvSU0g8hvy5bWS4BW1zeEPY41BpFfnbsuYlyhiAyiZo+bj1nUKn8GUUMSWS9GxwgQhQbm4j1H9X8uht6JFq+1e9bKlCmffPps12d68KMHtXH/RkmSTz59WvZp4htNVmgGkemV6ne033NH4T/+5s17RDt2BD8rZ8+2blYJLcE4YoRV9q1Pn+SeyzSlO+8M3+ahh0p/+5v04YfSo49Khx2W3LYBAAAAtK69rpWFbjremwLbXdkSacWlVnWOiBLuXmv+2jsT26a7IjhddFDGxwDO1WujHfVPDtnONKVV18mKQTbVVzFsVsph4QCp/MPAIGTb9vSTJI1KYLzrL78Mlm25/PKWx8SId0yjjChfEXxTHXt77FqbNoeU112SGbwbHgAUniHUs6CnJKl3YW/Zm4IbzQNENsMWGO+nizOYtmkzbMqz58nldQXahgaINm5svS+bt4UHb1rLIKr31EcEfKJlEIWqd9ere353xS2vh/VvogEio4VTpNoSqbHcqrfsz0zqNlLqc1xizxGn0M+xeM9R/evs2ZP484VmmvlMn3xmeJ20ffX7Et9osux5kuGUzKYXXrlO6jIk418cJOuLm9stTZki/frXkcudTmnwYGnWrOS2/+GH0tq1wccnnij9+9/Wdp1O6aijpIsukr73PWn//uSeAwAAAEDmud3BsU075PhD9buk5TMkGWo5ESDB72m+kC+4HWQM4FxEgAjpsetdqTLkqkbRgdJJ/7b+9dv4qLTy52p0WxcLR42y3hDjCeh89pkVIJo4URo+PLVdbzfuKqm+6cJt76OlHmNabu8v3dRSgKj5Rcs0XrAEcl5DubT1BWnnG5KrUio6WBp2gTQgSiZgGq3bsy4wXego1PKS5ap11QYu7K8vXx9Y3jxAFFpWTrKCMS6vS6ZMK0AUkvnQWoDI55M2bmk9gyg04OMfg8hsOsE0ZMjRLKW8zRlEBf2sYE/D7tbbhokxeExtifSvQyRfQ+SyqR+k5T039A6yeANE/rGiysoSf74Gb5TXFqLKVZX4Rtsir3tw4NL9n0r9T5GMFgbDaieh4yB6PNHv9HM6pWTHOP37361tejzS+PFW2bq8vOAXRqfTukFm4UJrnCIAAAAA2cnjsQJEmQgO7d4t/fOfVvUDt1s68kjpRz+SDj44pNEXd0juSoV9T+55uNT9UKn6a+t7mqSY36Nj8YWUvLBl/jteriJAhPTYOM+6IGd6pO6jpVPfC97F7TfqCim/WG6v9WfYq1d8pXNcLmlzU4nKY46xLkq2lEEkSSopkcrLw+eVllqjPktSz57SgAHhy4uLpaFDW+9QsiqDF3U1/GIrat5qdpCpmNH4WBct03TBEshp21+TVlzWdIIkSaa0b5W0Zb7UZ5J0wgIrW7IdLPxmYWB60/5NmvTkpLDl/93238B0jasmMG3IiMjOKXAUqNpVLZ/pU407PIOoosJ6Gy0ujt4Pj0favD38/af59qXwgE+Dp0F17rpAhorD5pDRbKCjPHteIIAkKaIkXasK+kkyrBNPd3X4mDYtMWOc2DaWRw8OSVLNt2kPEMU71ky/ftZnY6IBIp8vMmOouUZPY4vLU65wcHiAqAN9cRg7VjrhhJbbxHvzSyivV1qwILi/58yx/g6af2G0263zoF/9KrHtAwAAAOg4/F+D23PYG9O0xk/9xS+khoZgBtO//mWVuv79761qCEZDmbTp8WAFJGdPadJLUv8pwY3tfk967+zEO+FzK5CVRMWkjCFAhPTY+W/J1nRV47inpLyekQONGTb5Bp0tb9N1qLw4r/d8801wsOYxY6yLJy2uW1IiHXKI9W6XiIICacOG9AWJKkIyrPqd3Poboc0hybCCbtHEumjZ7IKlyyUtWiS98YZ1l0CfPlZ5mpNPTvwlADnp26ekD3+qiNRq/7FZvkJacYk0ZXG7dKe0prTF5aEBlRpXTSDYkmfPiwjG+Mch8pk+VTdWRwSDVq6Upk2LfldTXp709bf1UlNSkikzegZRswBRvbs+EJCIlXEUOjhknbuuhVcbRUG/4Ils4+74A0RSnIH79AsNLlRUWCftzXZdhP79rf20b19iAYqymtYjSt6IetNp1m24VPG5JDPkzrSO4bLLWv/9JlPqduNGqb7p0D3mGOmUU1re/pFHJv4cAAAAADoGp9P6nudLMAGnLX77WysI5Of/2u2/5vrSS9Ktt0r65hEFMoPy+0inLrUqqIQqPl6atkJa9YvEOuEPELVUQrydS7znIgJESJOmd5XBZ0m9vxOzldvlkz8jJi+v9QtekjX+kN/hh8dx4aW8PPHgkGStU16exgDRF9a4CvJFvrFGYzhl3QWf/CBpq1ZZ4xVs2GDdiez1WhcQ//53K4b24x8nvWkgN+xaJn10ZdODGLf2mB6r5Fw7Ka8tb3G51/TK5/PJZrOpxl0TCMY0L90mhY9JVNVYpT59rPdYf1mzlSulU0+Nnfa+cUuDNNqaNs0YAaKQrKJGb6NqXbWBx7ECSqEZLUmVmPOfzNaVSt2aDXiXXyzZCqIH2E2PpMwHiEIziLZvt26MaO2zb8CA4Al+eXlkkmwsX+75svVGsgJJ/bv1j2+jbdVlSFNWsluq2Sh5GyR7Qfs8dytOPTU9Yx1+8klw+mc/az0IlUyWEgAAAICOwR8gktp+bm+7y6bRfUbry2tif7d7+unw4FA0ptn0v28eCVbYGH+vdQ2zeRKAzSF1GyEdemPyHY8mgRLvxfcVa+LAifrPRf9JbR9yQOZH+EXn5B/c+9CZki92PRyvL/gnGG+dzfXrgxfLDjssvqBSh1TxmXWxq9soaxDu1vjvYk8yQLRkiXTcccFxRDwe633eX75m69akNgvkDm+j9OGl4Tnf3Q+Vxt0hHfVn6eBfSram4EesTL802N/Q+uj0Wyq2SJKqG6sDwRZ/tlCo0DGJqhqrZLNZmSh+q1fHPlGtqpJ27wuetPlMX9SAT+jzujwu1bpbCRDZ81NQYs6/8k7J1yz7petQ6cwN0nHPRK7rL2uWYT17Bqe3b4+v7ED//sH390TKzH2z75u42oWOfZV2hYMUCMiaPmnvymBWmF8rZfHSwW6XRo9Oz7Y//dQ61gxDOv/81r8gEhwCAAAAslfo+Xy8ZcWj2Va5TabMFr+v7dwp/fzn4fOOOkr6f/9P+s1vpDPOCFlQu0Vq3GNN9xgjjbw0MjjkZ3NKA6cn1mGbU5IZ+f3Or7US703Kasq0t36v3tr0VmLPD0lkECGF7Ha7jjvuOGnbS7LLJXUZLPU9scV1Qt8A3e74LnpVVFgXTIqLpQMOaFufM6qyqcRcz7Hxtbc5rYpW7sQHB//8c+nMM61U1Vjpqm63XRs3HqeLL7b2JYBmNj1u3b3iv1B94M+kCXObMht8ks0uHXS1tPyCtHYj8F7bNB1PRs1nuz7TyF4jVdUYfP+IFiDq6uwamK52VUuSRoyQtm2z5q1eHX37Pp+VoeizBU/c4ikx1+htDCsZ11p7KdkMoiYNu5pOPJu9x3UdKvWIcqW/dqv1WZZhxcXBTK7t2+MLBoQG9kpKpCOOiGO8Pkmb92+Oq0/f7P1GU0ZMab1hKnQZHB503f6a1Of48DbtFCCy2+3auvU4bd8ujRplj7s8bqJWr7a+GI4cKXXrlp7nAAAAANCy5t+/0yX0O97u3dKwYcltZ9nWZYHpffX71KuwV0SbP/zBGn5Csr4j3nqrNeaQaVo/Tqf03HPSvHmybs7zO+QG6/t0S+XgfG5pe2nsceCbjwFfsVOBayxtKPH+3tb3AtNVjVXqnt+9hdaxtdf+7mgIECFl7Ha7pk2dKr30E8nllXod3eo6oWVz/G9OrWlsGhu7b98kOtnOZi2ZpT/+94965uxndOHhF4YvdDcNFt9jbHxvgv7lDaVWVlasiH0zXq+hiy6yLiz6g0Mnnijdcos0aJB158CcOdI779j15ZfTNG1aAi8QyBXeRmnt3cHHR9wjHTYrcjCYooOk01dLKy5NW1fsdrumNR2oPp8vrPxaLF+VfyVJqmwMlr4rdBRGtAsNENW4rPeoESOkDz6wLlbv2GGNA3fggeEv2zSlt96STHt48CZaGbt8e74MGTKb/gstMRerfaikxiAKrFzS8slsc7VbpN7HxP1+my42m9SvnxUc2rEjvszZ0HPusrI4xutrsrUyvnTSTfs3xdUuJZoH6Xa+IR01J3xeO+0ju92uV1+dpv37pRkz0vMcpmkFiExTGj8+Pc8BAAAAoHWh37/TqUuw2rs2b05NgGh5yXL94JAfhC0vKbGGmQgdZ+gHP4i8mfCCC6TJkyXtXtk05IVXGv6T1q9dbi9NbBz4EyX9rGm6DQGiZVuCr/uDbR/o9ANPT2o77bW/OxpKzCG16ndKrqaSPL0mtFoOzTCCQaJ4A0Qul3XRJO67douLpYIkxiooKFDECO0JWvDlAknSi+tfjFzo/93k944vdSq/r3WHtOmTGuKvF/Tsa8P1xRfWm39BgfSXv0jLlkmnnWbdUT5tmvT229Ijj0iFkdeLAUhS+QdW9olM671tzC3W/OZX6m1OKwBx+O/apVvxXqT3t6turA7MCx1vKDAvLzivzmUFYoYODX+ZCxYETyb97Hbp5Zclnz38JDBaRlCePU+2kCBNnScY8ImW1RSRQZRoibm8A4JlT/d/llggobYkI6XLohkyxPp3+/b42odmEMUbVJKs1Px4bKvcFt8GU6F5gKhqg1S9MViGwPRZA5a2k9qmmObYsfGfuyRi1y5pf1PlyPHjg2OAAQAAAOicBod85dm8OfnvAG9/+3ZgOjRo4vfyy8Gbxy+8UPrhD6NXmnA4rJsUVf6RNTxG0SGSo2tkw+YSHQc+tJxeG77Tvb255deNlhEgQsqYpqmKko9U4e4p0zSk3kdLRuvpeP4AUWlpfOVvEg4QDR0qbdhg3Y7r/3kmylgTzzwT3mbDBmvdNthcYZXqWV6yPHyBz6PAoOm2fKt0XGu6DgteDKuJrwSQaUq3zTkicGHwgQeCdUb9mZL+f6+80tQNN1SooqJCZjwBKyCX7H4/+H42/o+x6+NKVpCo+0Fp64ppmqqosI7Vz8o+i2udksoSSQob7yc0W8iv0FEoe9PrrPPUyTRNDR0afnL68svh2Z+mKa1bZ41vZtriCxAZIdGKBk9wnebZQs3nGTISLzFnGFJeU1r9/k8SW7duW2RAKb9YssW46SCvZ2LbT8CwYdb79Y4d8bXv3Tv4meofzyYeDiO+AJrd1o7p9oWDIud9cnPwmDRs0oYH2qUrPp+pLl0q1LNnhbp3T89npT84JFkBonjOjQAAAACkXuj373ReKwvNGCopie8+8ubKasoC1yEl6Z0t70S0WbbM+orsdEr33ht7GApJcth90r6mOvO9W68SlZTQr/fV3yT1wsvryrVh74bA49BgUaLaa393NJSYQ8q43W49sOALSTdo1qg/KK/XUXGV8unWzQoub9oUftExFpvNejNr6U0swtChrQd7Ro+2RmWLxeeWtjwrbV1gRbUNh9R1sDTqKmngGRG3Z/sHhZesN6vqxmoV5Rc1bSvklmNbnqJGiGpLrMHYJOv5KtcHl9V8KxUf22rq5Vc7D9X2Musi8EknSf/zPy28PJ9b69Y9oHXrpFmzZikvXQMrANlo91IrS6HoQKn/qa23N71xBciT4Xa79cAD1sVw+4nxPYc/KyS0nFvXvOgBIsMwJFPymT41ehs1dGh4MOSTT6QPP5QmTLBOKg1DmjvXWuaz1wfKx0ktBIhC3vMaPY1hz99caAaRzbAlnkEkSYX9pMbd1ntq/S7rcTxqo5Sk6zpUOnODFTRccVGz5xkQ/rh+l7T3Q8m1X7IXSl1HNN08EWc6T4jBg63Pv/37rc/M1hJj7XapVy/rBq5YY0dFU1RQFJg+dtCxevPCNwOPj5x3pEqqSuQwHCrKK4q2eno4CiVnD8kdLJGo7a9IW/8hDbtA2vaKVLa4XbpSV+fWDTdYx19+/ixJqf+sDL3hrm/f4I0cAAAAANpX6PfvdF4r69PHuhHe5ZK2bk3gpvgQoePwSNLnuz4PG4/HNKWlS62KID/8oTXsRItqt0repoofvSZKXpcU5Tt+m+wOma751spWMhJ7jve3vh/2eE3pGtW6aqNe82hNe+3vjoYAEdLH2SOuZqNGWRewNsU5nEF+vnVtrbGx9bYp4fNYg9N/+XupbrusYE5TFLniU2uw7P7TpJMXhl0QfmvjW2GbeXfLu8Han6GBHdMd3J5fbYn0r0MkX4y0zNqtkev472oPWeedL6fIMEyZpqH77rPGoIgnCAcghM8t7VkhyZT6nBg57lA0aQoONVfRUBFXO/+4PaHZN9FKzBU6C8OCNzWuGg0ZEhmJuPRS6fPPrel33pEefdSa9tkaZDNs8jZlWMUKEIVq9AbfzAucUUrMhWYQGUbiYxBJVgZKxRfWdPkKadD34ys1VxejjFrXoVKP0bHXq90qrfuTtOnR8BsCJOvE+oh7rEBjAoGiQYOCpf2++iq+sWkGDLA+X3fulPbssb50xOLzWQGoHVXBFKUBRQPCBjXt27WvSqpK5DW9cZeiS5kuQ6XKL8Ln/XeG9OFlkjeJoGGSQssr2u1JxfpaFRogovQrAAAAkKVKSqwvZKFKS6WKCqlnz7CBYw1JA/sdri3bHCopSe7pmpdW85m+sPF4vvrKemrJGl/I5WolEOUJ3mCqnoenPjgkSaG/nppvlUyxs9BxlyTJa3q1YvsKnToyjpt7IYkAEdLFsMXObvFnxtSXSq4KHTzwOK2yj9C338Z3lSW/6VphXRLXCBPm80of/lTa8oyCWT4hgRl/mSnX3ogLwv/e+O+wx29tfCsYIDIcCgSavA0RsR41lscODknWxUej2e83yl3tS9aeKpsh9eknHZ2mbFCg09v3SfB47DtJMj2Rx1+G9CzoKbthl9f0ymlz6vUfvx5Y9sflf9R7W9+TKVPd87vL5XXJ47MK/NoMmwqdkVeem2fw1LhqNGxY5FhsX39tZRCNHi0tWRKcb9obAhlIUusl4yTrpDXW80vhGURJlZiTpML+1vuu6bGywQafGcdKNqlmU+LZYOvnSJ/+2pqOVopw3yfSp7dI09fEv01ZGUT+zNn33pPGjGn5ZN7tttb5oimm8t//St//fuybBLxeK0DkD/w4bA4dUHBAWJvirtbfgilTO6rjrHWXKt0PkSq/VKA8q187Boek8N+5v+RtqjUPQgEAAADIMiUl0iGHJDQez0jjHW3RSSopSe4uNH9ptdCqHsu2LAsEiN5/37rBzTSlKVPiyFIK/a7l7B5fJ/zjwMf7uhsl1UjqJql2c+wS79GukTaVeF/y7ZKIRcu2LCNAlAACRGhfUTJjRhm/laHfqKbGqX37rJI4LfEHiEpK2iEj5rNZVlk5yXoXHXKeNGaWdaHK9Ep7V0pr75bcVWGrub3uwBuUzbDJZ/r05jdv6iE9FNyWLU/yNVqlhxK9BblqXfR1Qu5q9/psevvLKfL6DJ18cmKbBxCiZmNwut+UVks7tqfS6tJAxk6fLn0CJ36S9ObXb+qDbR/I7XOrtKZUNa6awDKbYVMXR2QGUfOsohpXjYb3tDJP9uwJb/vll9ZPKJ+tISwDKZ4MIj9DRlgwyK95QCm5EnMDFQjy714WX8DHsFl3TO3/TDrgyPjep7c8J331vyHPO0gadbn1r7dOKn3L+klCaPr/Bx9I113Xcnun07ohzeGwPivfflv6wQ9abm+apsrrrFu4DBlh2UOS1LuwdyAg2e4ZRN1GWvvNTKS+bOqFBmzSlcmcH/Inn8j4rgAAAAA6iPLyhE/mR5ib5LBP1qZNhqqrpaJWqnq73cGxZkPH4Rnafai2Vm2VFD4ez4YN1vfDLl2smz1b5Q3pvz1GjfPmw2N4K6QPnpPMkEGV1q+XLgopz/7MM+Ed2HaZVPtF9PHWWynxvr9+v9btWSdJGlw0WNurt0uS3tn8jn6n38V8aS6X9Oqr0gsvWBU3PB7rusfpp8dcpVMjQIT0MH1Wabbmkd8omTGj+m2Sx2u9o23a1HqAaPhw68A1TWnzZumgdI0Fv/Mtaf2frOn8PtKUJdIBh1tZRf7BuftOkk5dKu0KT2f8eMfHgcHg+3ftr501O7W1cqu+3f+tRh4w0mrk6Cq5Gq07ohO94Lx3leSpt8ZliGHLnuGqbrDK/E2ZEv7BASABnpB0xcL+metHFKU1pYGsoN5deoctC328p3aPqhqDgWxDRvQMImdh4E4jSYGg0iGHRAaIovHZw4M3iQSIbIYtesZRs6BRUhlEPcY1lfOUVPG55KoI3G0Ukz/7Z9e7Us9x8WWNfXW/9a+9izThz9LIn8oKTDUFNQ69Udr/ubRhbsIvYfDg4PT778duFyp06L2337YyhGJpbJRcqgmU/DNl6oDC8AyiAwoOCAQk99TF8QeRSt1GWhlgHci2benJ8AkdX6q2NnY7AAAAAJ3HUJVIMuTzWWMFTZ/e8k3xodf4/OPwGDJ07OBjteebPapz12lN6RrVuevUxdklUInJP75tq0KvVfrckctbGh5j6gdSn+Oib7f5GPD1h0m166Tqr6NfS26hxPvykuUyZcqQoWMGH6Pyb8rV4GnQxzs/VoOnQQWO8MCWyyX94Q/SQw9Je/davwd/pQ7DsEro33pr9G53ZokX9gPi5alpvY2sAJHfhx9agYyWjBkTLOny6adWsCgt1t8ryWZl+pz8n+CbkS3kapD/zbLvCWGrvrXpLdmaBjY/vP/hMpr+CxuXqMcY69+KtYn1y7A3lUlaZgWrYqiuD95qMG4cwSEgad46Sbam0pkxcrBrS6R9a6Qdb0qbn7V+9qxIe9e2VW4LBHT6desXtqy4S3EgeOQ1vdpWGT6eTrRyboWOwrCSb6EBoniyNU17+IlhrACRGVFX0xpfqLWSdD7Tl9wYRL2ODOmkT/r6Ly2+fzY1tP7Z9U4CQXzDKmV30pvSyMut9WwO6+/G/7fT4zDp6EcSfQXq3z94Er9zp1U6rqXyZlu2SEceGfyMXL9e2r49ePIbyu2WPvpIYVlBXp83IoMo9HGDpyEsKy3tig5SZD3WzFq7Nj0BotBxh776qvXzIgAAAAAdjL/UWgKGOXfK47UqV7zzTutFLEK/27239T05bA7ZDJvGDxivcX3HSWoaj2ebdW2irs5aJ+5xTu0hDb1Rvoe3NDxGzbdxPomkriOCFTzKP0yoasSyrcsCr/vI/kdqbN+xkiSPz6OPtn8U1rayUjr1VOn3v7eCQ5J1vfTSS6UrrpBOOin+Lnc2BIiQPvs/i6s4/6i+wQDRwoWtBzIOOSQ4vW5deur/q75U2rVUkk8afZN0wBEtXyBsVq7ozW/eDFxkPXXEqYGLof/Z+J9gowPGW3ekV38TGYn319hsyc6FLX5a1LmCpaK6dm15UwBaYNglmbHfbPx3zfxngrTs+1ba84qLpMXHpz1IVFpTKsnKvunbtW/YsuIuxWGBmC0VW8KWx8ogCg0QVTdWS5IOPTR6YKE5n60h7DljBoii/C4NGa1mHPlMX3IZREUHhafEb3hAMl3hbaKNFyRJZW+HZ5G1yCeNu0Pqe2LkXU9+NntiYxo1cTrDy8y9+mr4WDWh3G7rjrMJE8Ln/+530T82nE7piSekXbW7AvNMmRFjEB1QeIC8Ib+nXTW71G56Ht5+zxWntQne3xGvoUODAdlPP2UcIgAAACDrDB1q1XRbvTr488wz4W2eeSZs+dD5fwgseuONlr8HeL3B8WYlacnmJfL4PPKaXh3R7whNGDBBTptTDptD7219T5J1w6F/DKK4hH6Hrt4YPYsoFbqNCFb8KP1PQgGit799O/C6x/cfr4kDJsphc8hu2LVsa7Dak8slnXWWVa7d57PG51250vq+9dRT0mOPWUG5detS+9KyBQEipIzNZtPEIw7RxB4fyyaftPfj4AHegj7d96gwz7r4tnSpVN/Ktb9+/aQeVuU0rV2bpsyYrf8ITo+6QokcKnvr9uqT0k8kWYN8nzv6XEnWxbYlm5fI7W36nfQYa2UCmR7rjTaUv8bm6aul45p9gPgvzm17qcV+GEbwHT+eN3+bzaaJEydq4sSJssWVa5pBPo+0+z3p8zulVddLK38hfTpL2v6adccBkEr2QlmZC2Z4DV6/VN01Eyf/sTph4gTtrtttddGwq3dhsxJzzR6XVJYEpk2ZMTOIQvkzRI46Kr4AkWmvDwv+RB1TyJEfNYOopfah/U4qg8iwhQcYGvdKXz9svZcE2jQ/+256H/Q1SjveCG8biy1POuSX1vO12C65Cr8nnhgMHDz7bOx7BOx264aLgQOl3iF/Bk8+Ke3YEb4v3W7prbekzz+PDPhEyyAKDSCGBpTSrqBYyu/bers0sz4fJ2rVqonavdum8vLUP0dennTwwdb0J5/EWf4BAACkXkmJtGZN+M+bb1onYm++GbmspKT1bQLIKjGvlbkqpS0vSP/9sfTvidIbo6V/T5CW/8gam9ZVYQWJjjoq+NN84B9/qbWmn5HHBauCbNxoXfNs6Xv4okXWv6XVpVq7O3j3WmVjpZx2p9w+tzw+j17d8Koka+whw1Cg1FyrugxR4HvxvlWtf89NVrcRwentr8b9fXl33V59tuuzwGOv6VVRflEgYPT6htcDy+bNk957zwqsXXut9K9/WRU3mhsyJIuujaYQYxDlmpISRVzNKC2VKiqs6Z49rVGtQxUXhw9kEIPD4dD3zpoh/fN/JI9X2r86shyTPzMm5GKqYUgj+mzWuh2HqaFBevFF6Uc/ih34MU1p7Fjpv/+VFi9O09g6O9+w/u01wRr3IAFLvl0SuPg5ts9YDT9guPp27avdtbtV567Th9s/1KRhk6SeYxUol7N7mVR0YHiWUteh1k8s9TulPf+Vio+L+ubZNT8YKKmqilgcweFw6Hvf+148LzFzardJn/9W2vay5KmySjkp5Aqp6Za6jpS+v16KMc4JkDBHt+B09dcZz2TwH6tlNWVyr7ICzqZMFXcpDmvX/PHO6p2BaZ/pi5lB5GfICAsQxcO0N4RlmMTKCPLFuCOotRJzklTrSjII3GuitO+T4I0LX9wpHXCk1H+K9bjkxfD23Q+Wqr6ypjfMlYZd0PpzDJwuOXsk1784fPe70nPPNXVpg/TII9LVV4eX//N4rGygjRutz9fvfEf6/+3dd3gU1f7H8feW9EYghCT03osgVRRBpFhALFhRfyoWbGCvF/ReC4od+1XxqlfUq2BBEVBEkd5B6b0kECCkQNruzu+Pk2yy6YGEEPJ5PU+ebJndndmzM3PmfM/5npkzzbkzOxseecR0VLOsvIuNJ54w/xPSErBh857DipqDKL/8KelOijpnwr6fqMpUc06nky5dLmTCBHN/xQo477yKH+XTowds2mQCdx6PgkQiIiIn3a5dJn1JeSaZDww0lbQC7SdZrixsNht+DuV9F6luCrWVZRyA5WNh15emA7fNaTp+5/4/sgZ2fQEhTUzH7+LS1BehUSOIjoYDph8oU6bACy8UvazbDXPmwIMPwrvL3vV57uqvr/a5v2b/Go5kHCEkpBZg5nMvU1uqMxjC20DK33Bo6XFlwiiTsHyTyyf/ZabiiGhXakDqvb+m+XQ+HT51uM/zy+OXk5aVRrAzlNdeM4/17Quvv25uF3UN5+9fDdpGK4EuN2uS3ApOt26+fxddBNddZ/4uuqjw861bl70njM0Gdbqb24eWFX4+d2RMgVEx3Zstxek0LVVTphR/kHK5TMS3UyezTHKyGXZZ4fn5Mw4AlpmYvDgF5xzJSSU1/rfx3kXWHlhL0DNBHDyWF5R7/NfHzY2IDnnvtePTss9x4Z+vR/eK+4o9YEYEJXtvL19uhlNWa7u+gh9am+/KZoMm10Gfz2DocrhgFfT7HlrdDeGtFRySihXZOe/2/rngOTV2pvwBH7fHXXgEUXDefafd6dOY77E8pY4gstvs3gBRrVpl6ieAx+E7BLS0lHEFlTaCCE4gQFSnu++oVlca/DYU/rgM5g6Bv5/zXb5295wgNHBwIWz5oPRRRNHnVurvo08f3xGhEyaY3l+58wy53ZCZCU8+mbdM9+6+Fd/PPoObbjIdB/bvh0GDYFnO6Xr/0f0483U4KGkOIhu2k5tiDkxAz1aGvk32QNMhpZJ0yhcj/vLL0oM3ZRl9V9AZZ5jXHT1qgkTFpRM8kc8QERGpccozIuiPP8oXHAKzfIEOuZ+t/YyAZwJo+lrTYl4kItXGwcUwo50JDjmCTBtU/5/hqky4OhuuyoIBc6D1vRDUoFzBITBNXeefn9cB8I03TMe/gnOvezzw9NOQmGju/7Tlp1Lf+9M1n9K5s2k/zcgwh7kyXUPU7W2uwZJWFk7LXtL0GP61yvDmOYIbQVC+fOqb3sSnM3gxZuyYX+oyn6z+hF9+gW3bzLX0/feXfm1VEylAVJMcPFj+Cg4UWckpimVZHD16lKOh3bHwg7StcHhV4YnAQxpBhO+wygu6/IjLZX6Oc+eaYZIFgz65vZ3feQfatcs7QL79dslR7+Pa8d05jZyOoKJzXxY158jsPnj2/8nmQ5vz3sZyk+HK8Oktv2xfTkucfwQExpjbiX+auYiKmwMjv6heeQ1kh5fBhpd9X5fTgNkoahfR4abx7tdfTcqaknjL7+jRIucHqVK7p8H8kSa9V/2LYfh26PMJNBxhgngR7SBmIHR7Ffp9W9VrK6ebsFZ5gdkDfxQ/MrIo5akUlVHuvrozcWfeY2UYQXTg6AGf+6WNIMofIALo3bv0URJuu+9Y9dICRPZ81RALq8gRRHabHUe+nkrHlWIOoG7fwo95ssyIxPifCz9Xu6vpAZZr1UM56QRLCBL5hVFkRTa3Q0ERnQrKo0MHkxYg16FDcMEFcPiwuZ+UBBdemNfjDEwPqYIXFB99ZIJ+9eub1K659qft9+mBVdQcRLmcdufJTTEHJlhbWurasNamI0pJI3BPgGVZREUdpU6do4DFl1+Wnhr3eHTpknfB9s47pU9QKyIiFSM1M5XQZ0Pp8X6Pql4VqWildZgt2Fn2uutO+CMzXZmMmzkOgL2pe72p6CucZcGxfXBkrRkxn7westNKf105nPHOGdiesrEtqeJTaEsZWZZJYb79U1h2N/x5DfxxBSy43qTfj59l0p5JhfK2lR3eiTXnPJM6rlZnk7mm26sQ3S+vjcDuZ647u74E53xzXJ/Xv3/e9VtWlunc53TmXRtkZ5tMA/lHFq1LLH1y1OkbpnP22Xn3f/utjO2ltbubNkd3OhyY73s9XNL0GEEFslOVxGaD+hfltXVufc+0k5Yy59Hag1tKfB5g2oZp/PST+Q6jo2HYsJLbkE/pttFKpABRTRIVZYY8l1dgoHltKbKzs5k0aRKTZgaRnRsP2fiKmZC7FOd3nI3dbnY8y4JRo8zooPyNWjYbjB1roud9++b1op4920zMVrABDMwBtKjHS+UMy9molKJH6BQz58gPG7/GQ8kh+HRXOhsPbjR36vTIG6K57pmyDdes3d230XLNP3znTErdBJjva1DHWTidVpkO/N7ymzSJ7AofknUC3Bmw/B7Abk4Y53yTl8Ip/6gru8OUVVlHYomUlc1mRobgMHNfFQwQFDMyEihfpaiMcvfVNdPW4Efe7z3/iCGAYL9gbzDG5XFxKP2QT6ClPHMQgblOLq1+5HH4ju4pNWVc/gyRllXkCCLAJx3HMddxBohCm5dvVElkF98VzDoMP3aCnVNNz7H1kwq/xnWMQunP8ncoKNCpoLxBIocD+vXzHbHy55/QsqUpnxYtYN4839f06VP29GcJRxNw5fy+bdiICPRNl1dwRNFJH0FUq0vpyziDKy04BGb/e/nlSdx99yT8/LJJTYU33yy5rpF2HO0znfMNXPzsM1MnKmn/K3MecRERKdGDsx/kaPZRlu5byg+bfqjq1ZGKdLwdZsujQNvJq4teJfFYovf+mB/HVFyDY1YybHwd5g2Hb6Jhen1TV53Z1Yxw+CrCzImy8qGydUQtwdztc1m1fxUAN06/sdh00fl5LA8bDm4gKT3phD5bMNefm9+Fb5vAd81h4fU5DfXZZrqBrCTY+j7MHWx+A+5TI+PF6cLbVvbGFLLdbtMedd6vpsO3zV64zdPuMG17/pFFv2Epzj3X9/6ff8LIkZCaau4vXQpDh+Z1qk9ISyhTJ8oV8Sto1ChvVpFffinjdB11uuO9xt3wcuEpLkIamc6VBQYClFvsoLy2TstjrpndGXlBogLHnUQXHHWV3lNv+b7lJOUchho2LD37wynbNlrJFCCqSRo1Mvlwly/P+/u0iAbNTz/1XaaIHLpltuMzSNlUeBRRAZEhR+jV7ai3h+yBA6ZX9LaczilZWTB+vBktBKbhpGW+FJVXXWV68BYMgtjtvql2yiy0mTmg7/+t6BFExfhwy7zSFwLeWvqWudH46rzK2o7PzOiEgo3PBT8/qrfvfXc6LLgGfjoDZp8DC2/wPjWg/a+4XKZhqahRWZXFY3lwuV0VU/nd8h4c22tOst1eN7+lypoYT6Q40ecAFmQmwrYPiw4SnWiF6Dj42fJqdAVHDIHvCJBD6Yew59t3ShtBZGEVChCVNgTd7u970V1UnvX8I4hs+QIwxY0gKviaDNdxXtjbbNBgRNlSlAH4hZsRm/mDRJmJsHAUzOoFOz8v/JpDiwuPMCumQwFgegCW09ChhQMFKSkmRUByER0GQ0JMp4qyzGGzN2Wv93aof6jP7wV8f08uj+vkz0EU1jyvA0dxHMfREeY45X6nL75YuFNLfrl1l/KIiICOHc3PNi0N/vWv4gNEHo8ZFSaVz+Mx1eKvvzYpHm+5Ba6/Hv7v/+Dee+Hdd2HBApMaUESqn9lbZ/Pu8rx5HG769iYOpx+uwjWSCnU8HWYDAkxO++LaT0poO9mXuo8J8yaYt8mp4y7as4j/rv3viW2HZZnA0PQGZh6UrGRo/zgMXgKXJ8EVqTAi3mTWaHCJmcvjBOYNSctK44bpeW0Mf+z6g3eWvVPq6x74+QHavtmW2i/UJtOVedyfX+NlHISZZ8LS2wELerwPV6TABSvh7K/grM/h3O9hxF4YthVa3aGU+ymbYMNrsOgm+LEz/K82fBkGX9WC6Y1g3jBY/SQk/FLqCJVCLDd0eBycIUXOBe6jtOeL0bw5NCswFfpXX0G9ehATY67tduzIe86bpShHiF8I4QHhhAeE+1xfp2SmkO3O5rzzzGiaOXNMKutSO9XX6pjXEXvv92aUYmmp149HvQG+x6qjO02we+cXJuX7xtd9Fl9a4LDi7/An0BFIoCPQJ216cmYydodpyDiuAQQ1xPH9WqX6atSo9GBP27Zln5G8OHXPgsN/mIPnov+DAbMB/xIPkCNHJLFwWd5k8EuXQvv2JhCUmOib5c5mMxfkEyaYoNDff5sR4TNmmPQ7uRM6jx0L80tPSVlY45Gw+3+QvtcMa4zq49srIDelVIFGv/0ZeS0Cwc5gmtdu7r2/4eAGsnNOPvFp8ebBBsPBEQLuoyZSPu8iGPh7ztxHtpzoeYEWocC6OZOtL/d9LmlVoc0Y0O5Xchs3H34YVlbSiPb8LMvirA/OYtHeRVzf+Xo+vuTjE3vDI2vNSSK8HYQ2KXqZo7tMI2x6vBnuG9rM5EkVqSjR50Du6MC1E0xw1xZS5cHK/OnAigoQRQVHedOApWSm+DxX2ggij+UhLV9qil69zDV1cR0vnU7wD04n9yjosDkKBRjAN9iTf/09lqfYEUT5X5OefQL5vBpdbnrXlVXDy8xooYLH4eLsmW6C9o58320x5wvguFIQjhhhGqLL49przfx9pckf8KkVWKvQ8wHOAAIcAWS6M7Gw2Ju6t9Aylcpmh7gLYPfXviNpvc87zPn6JEtMhAEDzFQFQUGmJ15uPWTiRPjiC3MOLq877oA77zS3X3vNzCc1cqRvsM/jgWnT4JNP4O67K2Z7pLDkZDNS7O23Yd8+6NEDzjzTpAIMCTF10T17YOZMs9zixRX0we5MM5o9d+Jjv3AoJpBeVpYFGzbA6tWmHXPzZtMj1e026Yjr1YNWrUwWpj59TDpKqRxut7lOWbzYlMlff5nrnexsc06NijLXQm3awNlnm9+dU1fvlSYlM8XbCG7DhoVF4rFE7vnpHj69tIhOldXdrl2F08jHx8ORI2bHz+1inisq6vg7jVY2y4KkFeZ6OGWjSd2elWyOnY4ACIw189SGt4bV8yEtX+ef9et9U8l9+qlpD8lV2naX0Hby4OwHvR2bbu12K28seQOAcT+PY1jrYYQFlNLppTjrX4RVD4MzFPr/BLGDc0aS5OuY5RcKsUMhdojpcHoC5f3InEfYnbIbMNcK6a507p91P0NbDKVpZNHzKk1bP41XFr/ivT/mxzH8++J/Y6vgnLmWZToXp6WZY6qfH9StC6Ghpb+2WsgdRZG8zsxhPXiR6YxWXNaUkCbQ9qGTuoqVLSEBpk83neH++sucL7OyzPkwK8uUd4cOZle8fMByujsfxJ44F0KaQuMrTfA0srPZXywXpG03x4qk1VC3z/FloKl3XtFtm7ntUnDCbVOXXQYvv+zbCT4z08whW9CiPYtw2p24PC6cdieHHz7svX7+fuP3DJs6DDBTYKyIX8HZZ/fks8/M/nPvvWaaj+KYaxo/aHi5mRfccsHSO0y7pcft205aysCAUvnXMt9twi9Aznsd22M6aBZhYYZpc3Bbbhw2BymPpHjbEwpuN6HxQH02bzbHizIfI1at8q185R43ofqdK0uhKqZUjpZ3wqLfzO2DC+CXAdB/prmwLWZEzpWXJPHAPxr6RHRdLlNnK8qoUfCPf+Td//13sx9ed525WP/f/0w6ujPOOI71j7vINPC502HjqxB9tu/zuSmlDvxhTthAugdWHDK9wZ12J3d0v4NJg/JSEF37zbV8se4L3JabeTvmYVkWNmcQNLkGtn1kDrTZKTC7L7S83cypc2wv/FVg4nQwzy++pdTNaFx3Fx3bpfP3xiDWrjWjsHJ7IVfGfAaWZXHPzHtYtHcRAP9Z/R/a1GnDo2c/evxv6m1gLmboQm76pvyNrweB9h9BZL6ZxE/jA7mcBJFdzF/SWlPZW3wz9PnMHM+Os2dQRXDlaySvE1Sn0PN1Q+pCTlaLDFeGT0+a0kYQeSwPaZl5AaLgYDOy89tvi05Z6XKBPSADcjIa+BVT2S44L1FuIwwUnZKu4OOZ7hPogVivPzjDwZVS8nL2QBPYaXo9rHqk7CNJXUdh23+g+c15v4vc80XmQZMPfmG+RojjSEHYoAEMHmzSq5aUOjR/WrlLLzXBhpKWt7A4eCyv4aBgOrlcEYER3vmsTvoIIoAGw2DXF0U/Z7lzgrknx5AhpmOKy2V63511Fjz7rAkWJSTApElm/qDjqodgAnv33WeCsm63qd8cOgS33moaQFwu+OADuOsuM9pIKsfevaZsd++Gyy+Hl14y+2FuGmObLa9e5ednGvfLlK6jII8bDsyDvT/A4aWQvt90CvILzQsyZx+FzAMQEG3qiXFDTaehMqRzdrnMRMdvvmmCWYMGmRGJ555rRqz5+5sL5qQkE+x8/XWTA79GquSGc4/H/I4mTTLf+eWXm/njJkyAsLC8zhipqbBkCSxcaNqfyxsc8nhM8GnWLNOZbts28ztwOMxvNDPTBJyDg02HvAEDYOBAEySsicbOHOvtxHdjlxuZtXUWe1P38tnaz7i0zaVc2u7SKl7DCpQ7F0950q0FBp5YZpF8PB7TsOvvX7YRzsVyZ8GGSWYy86wjJh153AXQaGROQN3f1M0yk0ya6B2fmtEWjsJ1YK+K6CwLvL/8fe9IIbvNzsFjB4kJiSHhaAKJxxIZ+dVIfrqu9EnlCzm01NRNAXp9aBpToehG7txzwwmU96ysDby59E0AIgIiGNN9DM/Nf44MVwbXTbuO32/8HUeBc9C6A+u49ptrAbyN1h+u/JCuMV25s8ed5drcglJSTMeYn34y7bY2GzRubBp7/f1Nyt3kZNi+3cw1ctFF5i+3LrZvn3mPY8fM1+F0mmNgUJA5tx/PjAyVau/3eXOl9v2y6OBQwc6ycFp0mD10yFy/fP21SaN9ww2mM1SbNr71rLQ0k2J75/JF9Ejuj83Khi4Toe0Deddw+a/XgxvlBIZOYJSVO928d/7OkEW1S+U6f0G5y+Pmm02WgtLY7fDr9l+9acJb1m7pc73dOSYvb7XdZmfeznmMvqIn991nRrz/9hs88ww8/ri53sh/DWlZsGyZ6aBC67F5GTQOLYZfB8K5M4AgTKd0C6wKSG3Y7EZImFWmRX85lhP8AVrWaenT2bTgdkd2n4nLdbP3+mnMmDLW1/v2LV8qpgo8V55s1S5A9NZbb/Hiiy8SHx9P+/btefXVVzn77LOLXX7evHncd999/PXXX8TFxfHQQw9x++23+yzz9ddf8+STT7J161aaN2/OM888w4gRI8r1uZZl8dRTT/Hee++RlJREz549efPNN2nfvn3FfgHVRdwFpvfC0Z2AZQ4g0xtCoytMg1h84R0+pp6LG280aVLKMlFa48amJ/V33+UNE0xKMhe/J8wZBA2vgJ3/NROYb5oMLcf4ngAKpJT6Ix2yckYIuTwuusd193nL7nHdmbpuKgAHjh3gr8S/6BDdAdqMha3/zlvQlWbmtihqfotcja+BFQ9A9pGSt8MeyAvPpDJ0hKkEP/usmcz8pZd8LzLdbnjoIaiT275cXJS8hItiy7J4eM7DTF4yGYBQv1DSstN47NfHCPILYmyvsSWva3Eiu4L1PiT/bXqEhTb3PcEXTN90EHgAyP6/8n1ONT6Qy4lzu02aysxM82ezmYwSAQHmgsFut0Gnf5lRfmB6z6RsMhX18FZVu/JAoCOwyIBPvZB62G12b57w/PnCyzIHUXKmb86yyy6Db4qZazM4GCx73r7odBRdxSgYIMqvLCOIMl2ZJsB+PFFuux80vNQ0EBQ1AgUgrC0MmJk3j03jK82w9uKW92GDlQ+YIEVYi7wLuJBGRc6Lk5ZmZ8Eyc8hdtcr8BoOC8lKJ2Wzm/OZymbpply7m79ZbzUiFkuQ/j9apA+efX3JQyeaf5hN8K2pEGpg0c7kBovw59U+a2CGYDMlFBe1sZlLYk+See0zANNe6dWbS04oSHg63327qNW63+bvrLnj6adOYu3WrCURVCI8L0raaXnruTHNetdw5DREBJo1GWCsIjK6cHiZV4dheSFoJR9aYi3rIaUiw8GbhdgRy/lXj2bsnkksusfF5vsySdrtpjCrouIJDSavhj0tN2skWd0C310xv16JSAlkeE2wOb1XmXq9Hj8IVV5jjRp8+sGiRqb4VFczyePCmHjlZXC4z2fLateZ3nZ5uGu5y1y8w0BwbmzUz7bZNmx7n91wWldxw7nKZRq7//tcEdlevNgEZl8t3m4KCIDLSVLsvuwxsu8sXtJq/vT7X3V+PPXvMSMS77zYNPEX9Zg8eNKkRBw829Z6a6Jnfn+GjVXm5OvPfBrj8q8vZeNdGWtZp6fP4kSMm+JaYaH4ymZlmHwoMNN9lRAR0jIonKjve99BZWse12NjCZbpzPhnuDM5rel6Fj8KoLAcPmuPOokUm+5rDYa7hAwLMbzEry/zt3Gn2gfPOMyPWzzrL/P5LlJ0Cv18K++dCvX5w9jTwjyg8kgZMxSqq50mbqzbLlcXdP+UN67Usiy//+tJn5PzMrTOZvXU25zc/v3xvfmhpzg2bqdMWdZ4oGDDYe7BcafNzHUg/yAVfXOC9n5yZzHPz8zqvLti9gFHTRvHfy/JS5m1L2kb/j/uTnjMvyHUdr+PTtZ/i8ri4+6e7CQsI4/rO15d7XQC+/NKkdLXZ4KmnzOiKuLiil3W7zTklONgEGB55xKTkatcOOnXKC8a7XOacs3On6TzxzTeVfxy0LFNn/P13Myrm779NMCs4OC9g6nabTgLnNdzDuLNt5vgR3rpw9ooKDkqcKhIS4JxzTMeGUaNMg77HY+omBQ9/oaEweJCFI2MYtswsk2KvXc4oqoIBnAoa3cPWD3JSkedTWlrxcn5O69bmvDxnTsntoy7SWb3PHBccNgdnxp3p83zD8IaE+YeRmmUmMJq7Yy4PnfUQDz5orik8HnjiCRMI+uijvJHjLpeZrmP2bPMcUT0g6iw4tMhcIyT+YdK/NR8N4W3MXOib3izXNhap0RWw6iFTTy8hi0e6B5bmfN0Om4MzY0ve7r/5mnPPvZk//oBXXjF1sdBQjczOr1p9FV988QVjx47lrbfe4qyzzuLdd99l6NCh/P333zQqokK+fft2LrjgAkaPHs2nn37Kn3/+yZgxY6hbty6XXXYZAAsXLuTKK6/kn//8JyNGjGDatGmMHDmS+fPn07NnzzJ/7gsvvMDLL7/MlClTaNWqFf/61784//zz2bhxI2Fhxzl0uCxO1aHhdiec8SLMvyLvMVeaGSlTgsceKz2Pfv6I9osvwvffn8B6lqTTeNjzNbjcsOweUwltc1/O/BW5EfK8itbPx8Bpc+DKiWB3r184QJTbOGu32fl5y88mQBTRDlrcaoJEZZ080hkEre6Cv58r/jXhbaH/TAYHR3P++WbYqMtl0qP89JO5WIyONhc0b79tfkqPP57z2vJEyXMuigfO/T9+3fGrWT2bk2aRzVh7YC0WFuN+HseyfcuOLz1D85vMMPqj22HpnTBglu9Q1pLSN1Wm+HjzV/Cxcl7sVRqPGzLiIWO/6V1nZZsGQJvDNPg5/CGwnkm5UIaex6ebDRvMRUZu2sW6dU3DU3i4uSiwLHORf/iw6YEGEB19AWM79qOe/U9slguOrIafukCdHmYCyiPrqmx7agXVKvLxOkF1cNgcRQaIgv2CCy1f8LGCAaKLLjKVqIK5e51OuPhimJFvQtTiAkH5g0AF5ykrbgRRoDOvO5+FRZY7q9hgUqnaPgDbS0h9GVjXN5jT6i4zR1yxbCYg1GgkLLvTnOt+ORf6TIWY/nkNFZbHe85IORbGU9+M540bOtHlDHj0UdNLzBukL+DYMfO7zD3/XXSROZTs31/0vFA2W+GGlfvvLzmo5ArMizTYbfZiA0RRwVFsPLQRMKPS0rLSCPU/iXk8AmqbufgOLsD3osFmRlIEFD3yqTKcdZb53f/0U+Xls37kEZgyxfSGzd1dDhwwf/kdV1th2jaTnz1hDgQ3ML0pI9qZnpWOIHNucGeBKxVSNpjl2j92winOqpRlmQD/micg8xC0vgdiBpnUvn6Ff8fZyftYv9X8pgYNMi93VPQp89g++LmnCUKfORla3Vl0r1SfRo0kUy8tY2PDl1+a36nNZo4DQTl9AYoKstjtJ9ijvxz++ss0Pvz8MwwfbkY0jRgBTZqYxmOHwzSK5DYg//031K9vGipyg0lpaSZzgNPpO09XVpZpsO9QJ572teNp3NhcAtlslFxfi48vfsKvYlgW/LXRj5XzTPaCgwfz0k3m53abBsqvvjL333vP1D9yR58Vxc+Pcget/qAv5/Ib2C1mz7Z5J7surlyjosx3X9Q6HDx6ED+HHxGBEWX67FOBx2Pqbtu2me/70CHzW7Is82e3m+/c4zGTVddrcph/zP1Hie9pYTH0s6FsuWcLv/8Okyeb0V19+5rAW4cOpod7YKB574wMc9zesQP6zX0X27+eKt9GjB9vhpRhGtzv+ekeZmyeAUCv+r147+L36FjvBIaO5s5NnL8d4URTreXj8ZjG+yefNPNlvPyy+csfoMxNxZorK8uUU5mPsbv+B/t/AWzQ7/u8OQjzB4GqaGTFiwte9Ol0Y2F5e7nnN3bmWP6686/ytemkHMVb/0nbASGNfTtPFhcweAHfDBtlKO+Lf76iyPXO7/N1n/PY2Y/RIboDGa4MOr7dkWPZx7zPT1k9xed7uGH6DTSLbEbfRuXr0DNzJlx5pdm/Vqww+1xJDbsOhxkZ8fDD5ut75x0z8htMM0fBw7zTeXLOfX/9ZTp6LVwIo0fDAw+Yw3txn+3e2wbbvJyVTfzTBCXy/8YrOChRqdyZcHCR6ZiTtt1Ms+AMM+1rucOxsYEng+/+143Nm6/DZjPnSru95GOD0+HKqSdZENG+cOqzkgJp5/1urv+Objfr5UrD2xnNskz7iavAD2bbh9DiNpNhJHf/q+C04gDjxpk6UnFsNnA2WewdPWRh0ble5wLL2Ogc05n5u+bjsTz8sfMP3B43993n4K23zKHH4zFp/P7808w7HBBggphbtxbIhHDGizD7rLz7x/bA2vHHtW3Fsjuh3aOw7K4SF1vsaIoL01BjYfmMGILC2/37zt/5731ufvvNwc6dJvj200+m/afgscSnKXT+/LwFCh434YTOlaeaahUgevnll7n55pu55RaTWuvVV1/l559/5u233+a55wqn4XrnnXdo1KgRr776KgBt27Zl2bJlTJo0yRsgevXVVzn//PN59FGTAuvRRx9l3rx5vPrqq3ye002wtM+1LItXX32Vxx9/nEsvNUPPP/74Y+rVq8d///tfbrvttsr5Qqp4aHipGl1u0vPs+LT0His56XyaNjU93F57rehrM4fD7MC5mjUzQY2nnir+Wu64L+RDm5kUUr+PACxY/ThseBVajTERco8L9v3oXfyHo3iDQxEBETSt5ZuP94zYM3x68v+05Sfu73O/ebLL82ZOhcwkvLk2i5Kb9ghMI+e2jyA9oejXOEMhpBE24MMPzYH+0KG8i9MHH/Rd/ER6Yt6x4HFvcAhM2qs1B9b4LPPZ2s/oEN2BR/o+Ur43t/vBmW/Cb0NND7FfB0GfT8xINE92Xvqm/b/BohsgCpgEdPw0b4RXZRzI333X/PDKI9/F3r7UfUxbP43JSyYTGRTJQ2c9xKDmg4pstC8Ty4I902DH53B0t2mYrtXJTOoeHGeCQjaHCSh6skzg6NByqH8BULkBouxsk5onPt4EXI4dM5U8T26dy5ZXJ3Q6TU/a6GhTma+M+Pqjj8Lzz5veYz/8YBoHLCuvIuCtn+bIu5i1wdGPzSShWUnmu3Snm5RARcm/v1aykhrzi1NaijmA1MxUn/vh4SbN3I8/Uigd6NVXwzdr8i6GiwsQFZyDyEZey3ZxQZ+Cjx/LPnb8AaJa7aHJtbBzahGjgmzQ4mbfh6J65ZzLPismIG/BGZOgzpkm5/3GVyHjAPw6AOr0NClBgxuai43tJtD05P/+yes/30uLFqaBqbS0n8EFDgt+fiawf8klRS9vWSawkN/AgaYi/MsvhYMZdjv0v3g/a3MyCjpsDiIDi+66W/A3tT9tP6G1T2KACKDpKDj4ZxGPX1f4sUpks5kGh9atzQiN4uohJ9LRu149c2E8cmTJy5WzPRsSfoVfzzMX5QPnmeCQJxuw5V3oHt0F7oOQnWrOIWEt4PCK8jU2uNLNBffRnZB5GNw5dVZv8CN3tI5l9i+/SAiMMiOVghuAXwWfBHZ+AQuuNp85Yi8ExRQOxqTHe//8so7Qp+v5LF5dly+/tHHTTXnnqgqTsR88OcfO2mdWSsqSkBDz37JMe2OlpdApRyPntj3+dLykPTabjS++MGnWihrR5HCYYEubNmaUS7NmZrnPPzdVu4LHx4Ks8e9iG1fO+trYsabLcq4SGlLnrwzhtolN2TDEn7ffNiMLiwv2g6mDf/21KYvt283cYhVtPW3x4MBmmQAGlN7w6ZOuJyuN//39Px6Y9QCH0g8BMKTFEB7o/QD9m/Yvcn7BtKw0ftz8I+PnjudwxmGu73Q9N3S5gfZ125+00S6JiaZq/sknJqB7440m8BgdXfTyWVlmxMBTq+/Hk29UatfYrt4OKweOHmBr0lYAtiZt5foH1/DJpE7ExpqRv9HR5n38/Io+1p95JjgO3gYj8g0vLct1SWws+9P2M2raKGZvm+2z6KK9i+j0Tif6NOjDf0b8x2fO23IpbW7iE0i1tmZN3rXm55+bUUEFFfxNFjW6rUTe84NlAv5BsQUmN6+akRVJ6UlMWmAygdiw0a5uO5/r39lbZ/OfNf8B4O+Df/PrvCkMGHJH2dt0bMDDduhoMyNPB/0JBJae8joKaFMX6hdTpgXKe96OeSzZt8R7v1lkM5pENAFMtpQ/d/+J23Jjw8bdP93Nr9f/yriZ43yCQ8W5+n9Xs+G2pYQc/B0S5wMW+NUyI8AConKuW5146wauY+xZUh8YCpQcUMmVnW06R3k85reYGxyCShyBWgY33mg6OVxzjWlOKO0awFH/PJO6eutH8OfVMGghBNcHci6gKyEoUSm2fggrHzKB3DMnm+ujElLl1W9hTu6WZUYYt2lTSt3L7gf1h5mUfFvegyajgICyjRr89TxofTfUv9hkjgjIdxLPXaeUPUBOz9Lw9nB0rekQeOZkkxLNckNQfdMulbHfdKxamG+k3HGkFQdzLrvoIhPIKGoUkWVBhwvnsWq3mYfHY3kKBUoAusZ0ZfGexWR7sjmafZTV+1fTNbYrU6eaz8jtcJiYWEqWirq9oeN4WPsUpc7ReyJtIc1vMlmcUjcV2yF+XmBHHLZdedtdr/TtbnDmah57rCvPPmuuwTt0MNkabr89r65w7Bj85z/53qRLl5JPUBWUlvRUUG0CRFlZWSxfvpxHCrR4DBo0iAULFhT5moULFzJo0CCfxwYPHswHH3xAdnY2fn5+LFy4kHHjxhVaJjeoVJbP3b59OwkJCT6fFRAQQL9+/ViwYEHlBYhOMXa7nc6dO3tvA+aAmbo5Z5LvYoJEHf8Jza739th+4QWzsy5e7HsQzG1Efvll35c//rhJz/Dtt4V7UjudJpfscWswHHpNgUU5Y5kzE3MOhr72ZMOm3MZlbPSo36PQxVCwXzCt67Rm/cH13gj2sexjJiDgXwv6/WBOTq50ivyuWt4F7R7M69nuH2FyKM/ph3dEU36t78nbjAZmBFHfvibnblEnF7vdTnx8Z4acfRT7n3/mRdZK6V302v7veGdJ3nfSoW4Hejc0FW4Li1+3/cr2I9uxsHj0l0dpUqsJV3W4qvAKlCRuMJz7E/x5FRz4Db5rZvIt1784Z6i10/ReyBUFdG4LtUs4UJ/ogfy223xzCZVysWdZFhuCjnLrh2czf/f8Qm834ou8tJYP93mY2zrdz6fv1eXYMZNKKC7OVHQ9Ht9KZG6jYIRnFeemXwbY4IJVJjhUUG6jF0BGommwTloFdSqhdSLHHXeYBtQePSpw0u4T9GtOLLNdOxMcAvOdlunCNKSx+S3+0t80dBaXdqzBCOj2KvutANZt+4VdybtYvX81u47swsKiU71OdIjuQIPwBnSu15lg/7IHBu12Oy3atuB/6//nbdCoF1KvyGWjgqOK7flXVIo5u82On92P7Jx0mUezjxZa5oUXTIAol9NpUhZddLGH7FV53W3KOgdRfmUZQQSQ7konktJyj5Sg01Om56ll4Q2w25xmVF3DIlriu70G+2ZC1qEClVQ7tLzDBIcAur5kfhdb3jHvd2ix+SugebRpbEpOttizx0aDBiXPW+JyFb4oGj7cHIJmzPA9pjscJp3cwIGF32fSJFPHzQ3Qgnnf8HDofu5++CFv2eLmIKodVBunzemd/2r/0f3H3zh1vJrfBBtegtStmPOl3ZwbW9xe2itPWMG6TlycSUdy8cV5x+j8bDbfRonjccUVJrBdRF8or/xt2WWSkW8IUmiznBv2vN6WFdGwlhuEArh4E8S1LLxMvmCMSfXRqFLPSfjnHDdsNshIyAkQuX0DMpvfhXV59ZoZt0dw3rO/8uuvXRk0yJRDbmOny5VX5rnnkJQU385MparV0YxU3DTZzG/X938QkdMRqTRZh8v0EZdfblIJv/CCmXPo44/NCLj88yjljqjI3Zb0dHNsyc42y7jdvh07cuXWQ5z7dhF9dmtsmWVr5HTQCDtbsWwOMjNtPu9VnMmTzei50aNNwLssbLffBsPL3zhf4ojvfHXIT9+Dvzebjli33lr6+jRpYkYQXXWV2Y7UVJMyyc/PBBrAt6OKvz+44hrhLMdojxFJTv7zSAYLlgdy9dUmO0N4uClLh8O3YTW3/O12iz93/8lV/7uKval7C633zC0zmbnFtBpd0e4KXjj/BSICInh/+fs8/MvDhZaftHASkxaaRvIWtVvw+WWf8/Ub3Zg+3Ub79qbPVO45L//vKXfb8/8WpkyBzZvNdUyBy3Yf06aZObYiIkzjTlDhao4Pf39Y75rBf9ZMAUzniFu73cpbF77lXSbbnU2LN1qwO3k3AF8unQt0IiAgb6RuUSmPcjmdlC2DQL7flGVZfL7uc2764KYS511csGcBLd9oyZsXvMmt3W4tNA9MVWrQwIwcOnDAZPvo0SPvGqaozptud07wPbGEDA0FR9JYzaDR3bDrDZhzLvSeYkZ0Wx5z/PSUkA2jjMfO4/GP3/7hTWlkYfHSoJcY3CLvgHVJm0uYtmEaqVmp2G12/jH3H/THopifUGEW8J4fTOkAR5bD922g3cPQeKSpxxYxV7JXGRupj2Yd5YbpN3gnf48IiGDVbasIC8jrtPHcH8/xxNwn8FgeftvxGzd/d7M3NaMNG5e1u4x7e97rXX75vuWM/XksAHtT97Ln2w605pA5B17g27HUewDIrR9kJHDF8FS++f0IP/1Si+HDzSEvOtoc1/KPLvF48uZRyR0hMH26mdcxIsIsX9Q1n/c3WMktpF27mgDR+vVmeoSIiMIpRvPLzga/bm+Yzom7v4EZ7c21R5OrzXdXAeV9UmyabK6jmt4ADS8p/HyBeueFQfDiNffz4H8nMXCgCaZdfLEp69xzZS673ZRbaufPCXNdaDoVzzkbOv3TzNVoc5hORxeuM8Hk1M2+31WdbuYaroR1snscdA672Hxe14mw5Q3Y9wMsuhnWPm3mSK17tglcu9IgvpRc4GVks5n0em3aFG7Hs9tN/X+Hba5PlpCiAiWdYzp7r+/tNju/7/ydrrFd6d/f1BFuuMF8VsF2wiLPbe2fMKPAdn9T/Io3vtp0gi8ixXqZOALh7G9gZlcz8ix/+6jNAfUGMHdXsu92FxEYK7jd83bM41//6kpAgKmHJCaa/08/bUZ0O53mMZfLzo03duaii/K1bZeFZZlpQNxZplN2bltDib0Icypmdn+z3c6wKkvnXW0CRAcPHsTtdlOvwKyZ9erVI6GYBOwJCQlFLu9yuTh48CCxsbHFLpP7nmX53Nz/RS2zc+fOYrcpMzOTzMy8Sl9KSgoA7om1+LP5ev5cHcqW3QFs3GxnX6ITy+HAwkNooIvW9Q/Sot4Bnp2YAalA/1kQWKfwxcKHb0CTSHNCyTpC8oEXiZjf2PSIHrSw6BVLXg+HMcGQ/fPgz+fgCDB0Oeu3BzJ/ZQjzFzlZsTGEtGx/7A6oFZJBj1Z76dsaHni5J0+zhgfuNz0jqP0SpIyHzNmYng52wA32UIh5HPatgN8bez/DD5j2lJPrH4nj5+VROB0ePB4bkWGZ/HvsL3ROjoc3R5vl+8/CGViHqQ/buD2tLlPm1MduA5vNwuW206v1Pt6/eS7JH4whIiilzNv9668Orr2uPbHEs2J5B2g2HQ5NgeTpOVfGuQcJNxDA0uBzgZ9xAm4sejoambHPiYl5F3Nhdvo4o9nIBuzYyP72DZr/I5lYNrBiOYAf1H8Ldj8Env2YUR05PWvr3AAhdxAb6kcsK5g9K7d3YgiEPgqpr4AtE2+gqM7NkN4V9zvBOA6lQ62OtOs9hb8+d3Lb+Bi+XxyN3WbhsFu4PTY8lo0BHfdwTYstnGN7EDYD1xRzEGsaBU3M97T38CbG5gSHHNhoF9acpd3fJ+Bwsne7jzTsSYdjD5GQdQQ3Fp9NfZir/a4mGuhStxcfd3mKmMCovO8qzM4fnr+5ffNHbEqPx2V5iJmwj1jqMmfm/6jt+RBSZ8O+GbD3x5yysJF/FFXysXAiZnYrc3mv/HUNZ9hy8tTm3+7cnrBRUVDXz1RQMxMh42BepaLbq9D63oLvbsQBsWb5Pp88yCIrvujlCpi4YCITv54J764Cytgz3N2Oz+64jmE9phO28mFzoRDZOa8xDAo1egGQBBwBa8hy/t4WyPxVofy52MHKfPt3RHAGPVrt46zWW7k+4hLvSwfX7c3F9c6huSsMkpOxgPW2fUxPW8YfKSYF1RmL/gdcVupFen6xtnhiieeXnxKI9F8IWTsgdQtk7QKnldNDzg6OSHDWJfnAYiKCC+zf+Xsxh7ohKueqITORr59eyQvPBfPZt9cydGgdrroKuna1aNECgoJ8T8YpKRa7d8PADgnEEp9zXLND46mw82Fw/QVWTq4S3IAD6tzE4N9+YdbcxsVu4/SN0ws9ZkXhPa4RaHouefYn8uHXEbzxazsy3XYuOWsn/7jyD9pba7mO6eQmvKyb6SzymFMnfQMey4OfzYGfy48MR4Z3bwlat8Gkq8x9TVQUhEGwzUkaLiwgPjABnrFB2/uhyTUAtE5M5J+XRvPol2dgt1kE+rl457ovcX2/GRvesQAEuXNyQIDP/h3kZxqmndhx4QEsnIALCNq2C46sKLROoWmp2LDhwMbB+qFEfF//OI/n+ZYJfQ6SH8s5dgLOehD3LmzeTmy7WvnKO2f5wKch4ykgIe88FjECbNdw28gkvvsqI+czRkOjM+HQB3B0IVg233OGPYJ7bvGjQ60BPP/jI3RoP5BLL7PTpw90725RLxoCAk09MSMDko/Atu1w/o4Q7/Gc3lMA+OSGw9ywtxXTlzfCz+Eh221naPc9fHLLj9hmb4TNL3vPrQAdgJ//5Wb4hC5kZDuxLIiNPMasZ6cxf7PpoewHuDzZRB4+WuRvKjIxAbflwomdyeln0eePnDQDxZ0z8tcp8h87RyRAUBGBzYxEM0olZ/nmHfoScewQHTvCx1PI+z2lXA68kLPv2SDyfli9jpVrNnKG/zUlr1OBzyjT8Tx5PcQn4sw4yCWhH8DGuTDRfLfn14HZb4Zw9cON2XsoED+HB7fHht1ucffw1Qzt8QWN/zkRywOOwHr81OtN2oQ1LfQ7v2PdC8w4tBIsD+vDUwhJtrzl/ezlEJMUxCMftiQj24HT7sHlsRPg5+aZGxaR4J5Io3/+AB4IDmnMunO/xGl3FvqMPovvZk/GQbDc9Pvfx9x/8ct0+r499hb/B9FnQ63Oplw8hQPLv284m3Pa/AGz+xR9rixwrGX/b/leXczFVYHzkvswOJLBE96JRaFfsmhtCOvXw7otASSmBJJt2fHz8xAVkUGHRgdIbfEcC+t9Bh4IC23Gqn7/NcHpfNtthVqcs+RedmYkguWh9Xs/89ilz3K2uy/OpsOgXn+o3c2M9HMEmBFqQfVhqWntrxWSzKJxPZn6+1W8veltevcOpUED6NLFokN7i5AQc0G9cxesXm3H4YAlY3POJfl/5yXUKZr3e4ChLVtx0yVf0zWlC9TubNarVhfT2NDrI9MjNT0e1r/I6p0duPXd93BnO3jydRctWtnweGxYlpVTZ7DlVAktbDYLsJjYyJ9B/zeAt9e/wsABHYiJszNoELRrZxEeZhEQAGlpNpKOwPz5Ng5sXMWSzV18AkclclOudL+N2cX6x1rxzx/Hc+foS/nyyzCGDs07H/v7mwaz7GzTGLR1K4y5aimz2MFnH19MrVpBDBgAnTpZxMTkzBWYj8tlceAAxP2WM0FFGetrv0/9nnMaf2EeL8Nx7fFRx/DfsJv/LLqeUaNqMWyYOZY3aABOp+86eTwWhw/D8AMhrB3TkLdW/4PHHx7Jgw/6MWAA9OhhERFuERwMx9IhJcXG0qU2IrN+5d9Xn1fyOuWrn9eNPMhvo7ryfuxoPl77CLGxjRgwwMY550DLlhZhoeY8k5Zm2t2XLrUxK6gh6/wKB4aK8tXfX/HV31+VaVmALYe30P397vC8WfchQ8z8S6VZ+dOvnLHtPJ4PAx7POYGvoNBxjcyDkJXEpSGZ/HWuk48XXc+110Zyww1mhFa9ehYOR+HGlowMi3FTbwTyGkUeq3Wxz7nPL8zOhHqDuSn5fRzYyTznfv5dfw2v/XIvzZt35OabbfToAZ07W0RG5o0kys42I0t37oTmK2uV6zr00W/eZuLBb71PNQiM5v8aDqNWlg3SjnI0yMmnh35hU/peLCzGzBhDk4++Y9WWLiTVuYI6rVsTFOokKNhm5tF02LDldAxxuzwcTXERm3Avl3T6wHxAGc/fiV+MZeayIWwMfYoMv0gcwYGEhuV8htMBdvC43GRlukk9lMGqce14bca9fP7u9Uyf3oDhw82+0aE9BAXnzUGUnm7SR+5aOpe7158HJbQ5FhTLPi5u157Hx/yPxr8MgqBoiB1sevj7hZoGypTNpuMO7rzz2LyLKqXecixtL+8tmZzbdYXmIQ0ZlBxlckTl1KVCw+zcHn0OL+35EZtl4Z9cB9vE3aZNJ6e+VlqbTuywm4kdto9X/zmXc9p9AsvHwvJ7ILA+hLUGhx9kHPK+3LvdM7uVabu/WPs1O5N34sAEex5ueh1hf2322ffuCmrDRHsAae5M3Hj4Oic45ABq+9fig0Z3E77+qHe7+4ZFs6huL75MXIwFvLG+Ns83ySA0IB4OL4eIDnkpbHMbR7e8560jRAA/DLfxn4jr+WjDkzRq2Iyz+tro1w9at7YIDTGjY9PSIOkILFli455etzGyTibvzbuV1q16c8GFNnr1sujWFcIjzAjU3N/g1i2wduc+3ktugOUBv6AYvjpzEl1rtS1Up7h57XPMSVoLloe10Va5rkPfuX0eA7K38sYvd9O61VmMuNSs05lnQu3aZhs8HnMNsH8/bN9u456RR4jlcV4YP4iBXT6CDa/A+hfAHgJhLU3DclZeB4Jiy7u4+lpxv/MS6i0dPr2evzwe6tmcDG0wlJfb3UdkcqZ3uz2h8GbqLF7e8xM7MhPplNidCQxnqOsbAnPnhK3VsfDIv3we6PMS54T/zpvr3+Laq88gMNjB4MHQob1FWG695aiNw4dg3u82NmwIwnnwE67u9jkvPf4lzBsGfhEmrWJ4R3NMsNxmbuucdrNv/ryEi3rMwH/FfRB3kWk/yT+CKIfT7uaSmOk0v3kDT99/lI4dJ/Dx630g6Ws4ugI2vgYb3sjXsG/q0St3dOGMJqtK3vcKXpf8eJ25fsu5/o4GZj+dych/dmBHYih2u2nrHDVgPW8M/ZbYDX9iw8IO1PaPpO7G3cBun+vvzuwz22Gz47Y8jF0+Dn4ZB/1ncV27OjT/IIRrHmnIjv3BOB0ecx5z2QkJzOJf1/5J89CWRBw9kHc9Fvyo6YVxbCqQO/I958hX53pWbh7IGTtz2kLKuN2xzQYUvv4OGQ/JzwPJedffIWdhhT7Msp1Dvdsd6V+L6I17gD0lbve4FffBr/fxj4GzGFC/EZO/rMvXc2rhdts4lGiBDdxuGx7LCck96X+oDc4vy37+Xv3rMjrbnih5u3MD3znbbftP+TJg3LD1eqYM+Q/414ahKwsH4fJ3Cs9MJGPvnsJvUgybVXACgFPUvn37qF+/PgsWLKB377xei8888wyffPIJGzZsKPSaVq1a8X//93/e9HEAf/75J3379iU+Pp6YmBj8/f35+OOPufrqq73LfPbZZ9x8881kZGSU6XMXLFjAWWedxb59+4jN16tl9OjR7N69m5nFjNGbMGECTxWRoiqKzbgjW3DdNW6GDLXR5yw7YWF5vSLS02HbVouFCzzcEppTne36CrQZ65t2LjAQpt8Oh171vvebq8/mzs5/QGhzGLalcJo6fye86DIjMHJ9DYu/6cH9vMSf9MVms+jc3kX33n5ER5vG6927YdH8LDJc/tyUNJoJaf8uvMFRQA8gGIgHlgDZwPDa4DhcqDJoAT9yAYvpSW0OcyNTqEWy6fLffXeRlceNtOJrLiMLf87lN85lHjRsyJtXNynXdq/f24YvHrqSCRQon9pAN8zFiAfTuL4UXFENeHzgEWy7TH6eq9ZBlyLiln80ghk589nv2HE9bbY0LfwZNqA70BBIBxZgThANGzJh902FlweoBfTFXN2sAnaY5Zd03E2PHwsvvpVmzOBC9lOPuiRyET/Qgq1s7dSD5g/nDCUftMDM81DKb2r8rBAy95pRBjethFaHCn/esjj4Xztze2nrWH6tW7ZAifczJowvvN0NgXZACKYmmg4cABz1ePPsVuUq7637m9K83vZybffS3W3p3nC96R1x1n9L/YyJG9vyn6z1DFwFLQ/DdWugVoF2lE11YGoH2F4L5jXwY/LKgSQtiMTevi0BjWOxwsKwBwdiczrBbsOy2bG53VhuNwHBDpZ8M5kJ8T9BXcxfHaBuMNSJBn8/CLZyGsMzof0B8719DQu+6c39vMQieuN0eOjS0c2ZvXz37yULskhN9yfh/2xkl6MTxYOWjbsX12f7zKYk2ONIj22GK7o+zshQLKcfOJ3YzBUrrrQMwvwzObxjLbff8C60BmIGQ/1LoP5gCIrLu3BI3QIzOoAn87iPa9Y3sI84NtKajbQmhXAybYG4/YPAsnBmHSOQDBo2hA1JR4o+rjUAugBBOb+/ZcBRmHBtR/7VYi0R6eD0QPRRqHsMItLBbYdDwZAYDIkhYLMgKRisNfgc1zLxZyg/MZcBmCOiDTtu6rOXBQ2v4MNz4zkWb3q09twDIwqfBtkQBVO6mNuJtWKpGx0Pm6D7XrhsfdFlNrsZ/JIzoODuYKj/XdHLfcswVnIGN/AxTdkBwL+u6UxardWwCUash57FtDVN6WLWLcUfwpsAm6B+Cty1hCJ7UK6Pgo9ztqNh1/KVd7HHc4BYzPHWBcwHUjDH2qTBRZe3H3Au5hywGVhrHv649ji2Hw4v/BmNgbaY41QWkAgsBeLyzmMuHGyiFavown7qkU4Q6QThwZ5zK536De006zipyOO5BXzBlaynLa3YxNV8jh0LusZAk4Qiz5UbaM03XEoAmVzHp9TjABlNGvCPAUew55zHiiu/Oc3MH0DDWmdx54icVG9Xuczok/zlUdS+l6uM9ZYJDw5lwr6fingDoCnQFXPeM4Oyjus8Vt7jOQBfU+i7deHgGy5lLR2JIJmrmEoD9jLxwgge6Z4MmP39zRlwxzLf11pA1ENwOGcw4eIlFFneyYTzOVezl/rEsY+r+ZxaJDPw1lr8GnsEK2cHWvMWdCwwT9HBYKj7UN4Hjn/pFvM7d2L2hfqYeo4T81sPxdTZegMOmL/xLPq2Ll95P/N/j/F43WfNOSkqCBrHQVRdCAwy3fT8ssCeBLFrwA6LP4XlP93BczzKfr+GDLvIzcUX2+h9lp3wcFN8GRmmF+XihR6eXzeCv0O+8x44Zv0Hzt/mu91/1YUOdxax3TYgGlOfiAL8c7bbkfMdDCEvA2u+8k4jhL9ozzo6sIcGZBKAExfhpNCOv+nS8BBxz+f8Bo/nd55bHtE5f8E5j7kwdZ1j8Ebqw9yz/HmzSWW8kts73OY9nmfiz1aas4lWbKYlqYThwok/WcSQQCs2cahXY55dfw+2ZIt3f21JaIT5MnJHeBT8D9B2fohp5GxzHzS91vT8v/RS0wLn7w8vXQ7JeZOZL1lgfucWsJuGrKUjW2hBBoFkEEgmAfiTRSAZBJFO96676NNkOq5vHGylOVtpzjaacdQZgScoBE9AMDbLjT0zHduxozSob9Hqzu/KtX8fz+88t06xi0ZspTlbaMERe208IWF4/AOx7A4cmcewpR8jOsZO+47/9O7fHmzspiEbaMMG2nCY2mTjhx/ZRJJEGzZQq5OdXg/n/D7KeFzb+0Xe+TuZcDbRim00YztNOUoILpz4kU00B2jKdpZfmcqMxn/QbyU0S4IbV0FggUFse8Pgg66m/vJbE7CFQ+dN0OQIXPE3dNrvu3y6Ez7vCH/XNX0BJ2yNIejXNhxwxmG1aAn16mGF18IRHICVO/mVx4PN48F9LBMr6BDXuO4uV8Bg7zCI+86UxTaasYMmJPrF4YwMw+0XiOX0w56VgS0jHZKSODRyPZ6on2ATtE2EG1YXfk+XHZ7qB9k5x4Pnw4Fv4CjBrKctf9Geg0R5f7ce7Dm3Mohr6ODI1QvKVW/5Pb4Bz8bvoctqqJ0O9y6CgAIxe7cN3u4Oe8JhfmBb/vzhbwD++CMvrWBJ5v/nY/o6bzR3yvA7f3PWGO76+E3i4mDxIosGDc1BN3e0Ru4xwIxGM+0WSy60eX/nh4lkBV3ZQBuOEUw6QWQSQACZBJFOMMdo2Okow2+dYq57e31kGnVLOYZMeP6WvPqaA6iHOX7GAIE5j7ly/tJgft2B9B02p8zb7aOMx/NJ39Xl4KFEAM7bVvicBKbcJvcwtwOdTZkwqnzXoRNuu8W3nuqHqRM1xZy7HZh6ZwaQCPMbD6TvZWXf7lQPPLMQ2GTuP/47hBUYtQEwrQ0sbmBu1wmL4lCqCQ4M2goDthdePj4UXssZgZuc0oZ6S0YyIeppc66rBcSGQb1Ys83+fmDPAv9UaL4D7L7HtVRCvce1bTQjjVDcOLzHteZspevw7UQ7NsE3kEEAa+jEajqTQjjpBHGMYPzJ8ta3HWds576LfyDLZuprUcfgu8+hTnreNrzXDSblm4LlwwM9+b+4xWaESr9vfX+zAE4HjHWb7cstq8XAN+Zc/DftWE1nDlPbew1gw/KuU9OGLlYlZfiWtwNzjdEip7ydOeV9DDgA85sNpO+AOWZfGrzElHf+9Sq4TuT8dqDMv/P2K/z5u6gfRXES2zD+zSuZYHvKlHe9nL8QJwQHQlAA+LnAPwPOzASHb3m7cLCNZmygDRtp7VNviSWeNmxgTe1zOXTYlnc95oep2zbC/LZNb25Tl0oGAuox4dfbmWB/yqxLFDm/xSCT5z7QHwI94DwGnY6Ao5jrkmCgc85r/cm75tsNW1t0pfktOR0mj+P8nd8xgviQm0ikLr1ZyBB+BmDiVWeQVHsl5JyPb19W+LUZTphwbt793PNYfh5szKcvv3EuLpx0YRUX8COBDaOZ4O5Q9PVYKNALiMT83hYBqcd3PVbouJYrAOiHuf7eirnuq8Dt3k8007mEA0TjwkkkSQxhJm0aHit3O/LmhOYEpmbS0NoDQ16F+t19K+o2G+z4N+z+yPtQ0zV2dgSVpSeWMcPWmAta7ISQpjC8iBPMmgk+ne8SU/yIviOb5ORkwktJcVBtAkRZWVkEBwfz1VdfMWLECO/j9957L6tWrWLevHmFXnPOOedwxhln8Nprr3kfmzZtGiNHjuTYsWP4+fnRqFEjxo0b55Nm7pVXXuHVV19l586dZfrcbdu20bx5c1asWMEZ+WbwGj58OLVq1eLjjz8ucpuKGkHUsGFDOnZMZvbscOrWLXky3OxsWHtwBSviV7DzyE52Je8CoHZiGpFH3SSFOHBH2allpRNqZdAkKJSAun1JdNYqtHxYSiZOhxN3cDZWlKnwNQsKp1FQMP/78hLefudCnE4Pt97qYPx4M5w3f1oKPz8zHH7r1mxSjsxhx4aFJKTFk5BmoiShKRnUOurC7XaTGh5AWnggADGhMcSGxRIQVovM1CPEpxZ+TXaIG3vOaOb6ASHEBASSEtma1Gz/Ipc/EuKEcAizMgm2MokNCCa7w0DiI2PKtd1Z6XGkJ1nFfkbBbejUsBvNQwtEbwv0vCbM4+35A7DGcrA19ViZP6Ok7yn/8rmvaRLXtsjlw1IycTgcPt9tnH8Idf2DOdj8DPbXiWFX8q4Sf1O531OzwN40Ccj73Zdluzf7hdB12ROkuUvOUXxBRDumNrmU7fbgMn1P3u+qU28OBVrlKu/UkDY++0bjrYd4+sEZ3vd94cXzSGsaWOzy+b8nl9uFLczCirJ5972o4KiSv6vc7wm831Vpv4+Cv3N7bM8i94vc8s7/XbUIC6VBaChf/nIp7350AU6nmzvvdPDkk2Z0Wu7+DXm9Iffuhfr2eDL2bOepje8z++AilicXjkr0DGvOsFpteTiqOw6bvcTtKLh/twpOoWXwEmw2B/Y+n5h0CZ7swhPO5htGvyIDVrR8gp3ZFFl2AG+/0Jf4ZhFl3r9zv9uyHHOKO66VeEwoQ3n/+M0drFg0FMvyjcjZ7dkMH7qdqW8F4peY6JvOsqh9L99nENECQlsVvU4FeuKW9ht0u914wsEehvc3WCuwFnGNB9Iguk+Zt7u867SiTm1WBPpX6vG8pGPt8ZzHjud4Xt79+0TOlbnLl1h2+X9T+Y7nxZVH5FF3mY61+Zcvqt4SbutUZNkVdVzL/W5p2qTIc0Bx57HyHM8bB4ZSO7AuWemxZCZbRdZ1CpZFtsPF5Qd/AUwKoytiz+Pzbs/5/M432nfTZsFowIyuuyKoA1fUH1bm8p7vjmdSylqsnHSzH3T+Bzc1Gu7zGTMzlzF05RPez7i71jmcHdW31N95hCOdhiFhRIVEkdagNQfCIos9V5b3WJtbdhGOdOoHhfPp9EeY8XNPmje3mDPHRpMmxadfzM6G1YnLzMgEwGlzMLrRCN7q9KjPdv8r8b9M2Pop7pz0FO82vI66AU3Ktd3ZQbEcS6fM9dTEFmf61DuLq1Mc7++8blB94g+34NB+N6nZDiynEz+/EEJtTgLckO3vBD8Lp8dFIDbqhPrT4WwXOzb+Wa7jeUnHkKK2+0DzbiTUjq2w/bsijmsFy6Kk/Tu3vlbSMeF4zjEVcTwvaTuKOq6VtE5Vdf4urk5RkeWdHNaUNCu0Ure7vPXz47kOLfGaocB3m3rkGJdPvoj12+vQf2AkN1zvT+3aOYuF5WSusZtAjstl0lodPQquusW3IxRcp/nTLuODf19G8+awdKlFZKR5Lju76CC1vz+sWfUzW/+aX6W/86LqayXVESqi3tKj9sVluzbO95sqqS5VVdtdnt9gqceDYra7rG0hudetJZ2LK+o8tqd2U65Z/yaZVgkpCnOMrNWel1Y1pMGUmaUum9+fo8/hQL9zKvU6tM2vq2n74fdlXqe5Y89n66iRZa639Kh9MVnZteky72rSPZklvDNMaX4d14e3Yi3OKi3vE2lfC7en0yA4gvCo9mRkUKj+X5HXJSfj/F2Z7UyVtd2V0d5S3HYHeTKpFxBKdrv+RbaNnki7A7UgzJFJ/eAQYoIDia1zNg2j+3tX/0h2Kpv3rGbTgQ20C6hP88gYwmsF5h1rLYt1los9aUkkHY3nqDuFQKcfodk2QrM8eIJc3h4+tfxs+HsCOWPUjNMrQATQs2dPunXrxltv5eUFbteuHcOHD+e5IhKzP/zww3z//ff8/fff3sfuuOMOVq1axcKFZnjYlVdeSWpqKj/mm1Bh6NCh1KpVi88//7xMn2tZFnFxcYwbN46HHjJdM7OysoiOjmbixIllnoMoJSWFiIgIXnopmfvuK7ngTpbFi02OcrfbTJJ8yy3Fp0PMysrylsOjjz6Kf7lnmpSqVBXl9/naz3nsl8fYkbzD5/EhzYfw7HnPckbsGUW/sDLEx/vmvC5l7qUy5RM/xS1YAGefbYJBU6aYHLYlpVj1eAo/b1kWqxJWsWD3Avo37U/bqLYnNhnx4lvMJJaRnc2Q2YKKmxej3w9Q/0Jze8UKMxlAfsuXV6vJA7/7zswxUxQ/vywef1zHWpGqcLznyg5vdeCvxL8AqBtcl/0P7Pc5Vr63/D1u+yGvvjjtymlc0uaSMq/XlsNbaPmGmePHz+7HLV1v8ZlHA+Bfv/+LCb9N8M5LNu/GeZzT+Jwyf0aRCh5vT+BYu2YN5EzvxB9/mHl+yjIXwJnvncnKhJV4LA91g+uS8EAC9nxzCnV+pzNr9q8BoH5YfXaO3Xny5+qowO9JRKQkGRlw6BAkJ5tr+Nz5wxyOnIGbfmauhVq1yjfNwZYt8MMP5r/TaTqA165t0nTZ7XnzV2RlmcDRffcVP6+KyKnsi3VfcNXXV5W4TMPwhmy7dxvO/YnFz5sFhefOgpPTjlCwbSP/epVlncpRb9lyeAv/+v1ffLw6r2N8h+gOvDToJc5vdv6JtQ2cItTWWbOcTuWdG2coS4CoDJddp4777ruPUaNGceaZZ9K7d2/ee+89du3axe233w6Ygtu7dy//+c9/ALj99tuZPHky9913H6NHj2bhwoV88MEH3sAPmJFA55xzDhMnTmT48OF8++23zJkzh/nz55f5c202G2PHjuXZZ5+lZcuWtGzZkmeffZbg4GCu8SZPLLsZM2DMGFOJK6lSlTv5XmV65BHTK6h/fzORqkhFurrj1VzR/gr+veLf3DHjDoL9gvnp2p9OvMHqeLz7LhSR8tGr4ITG48fDhAmVukqV7bHHzP/zzzcTE5amqOCRzWbjjNgzKi6YF30ubP3ApJA7vAIiu+R8UCl57fxrV8znnwIsC554wptpRUROA1e2v5Kn5j2F23KTeCyRrUlbaVG7hff5eTvneSeDDnQGMrj54HK9f/PI5jQIb8CelD1ke7JZuLtwnuzFexd7RxgFOYPo1aDXiW1UBQvMGwzsbVcpi7G9xjJq2igAEo8lct/P99E4wuQ9T8pI8gaHbNi4p+c9p9RE7iIiFS0wEOrXN38VqUULGDu2Yt9T5FR0ZYcraRPVhgs+u4B9aWYOk8jASJIykgAY13MckwZNMpPXn6qdRk/ierWo3YIpl0zhyXOe5P3l79O/aX8GNR90WgSGRGqSahUguvLKKzl06BBPP/008fHxdOjQgR9//JHGjc1FYHx8PLt27fIu37RpU3788UfGjRvHm2++SVxcHK+//jqXXXaZd5k+ffowdepUnnjiCZ588kmaN2/OF198Qc+ePcv8uQAPPfQQ6enpjBkzhqSkJHr27MmsWbMICwsr93b+9psJzt99N1xwAeT7GK/0dFi5Evr0KfxcRUpIMA2ULVtW7udIzeW0O7n9zNu5/czbq3ZFbrsNhg3zfay0XjbV3IEDZv9u0qSq1ySfpteBMwSW3Aqzz4KWd0HDS6BOD5NmLqQRXLzRpDRIj4eUjSanbd3epb51dfHzz7B2bVWvhYhUpMvbXc4/fvuH9/4X677g8naXA2Yk5s9bfsZtubFj56KWFxHkF1Su97fZbFzY8kI+WPkBLo+LdYnryHRlEuAM8C6zeM9iPJYHu83OgKYD8HecWr3hWrWC116De++FG2+Ezz83HRjcOXNv5O8U5fHkpWG+ot0V3Dj9Ru/IqNcXv+4dQeSx8qLsFhb/1+X/TtbmiIiISDXVOaYzy25dxnn/OY/1B9d7g0OvD3mdu3veXcVrVwl27cpLBwgmm0p+Be9HRUEj39RezWs35/nzn6+kFRSRylatAkQAY8aMYcyYMUU+N2XKlEKP9evXjxUrVpT4npdffjmXX375cX8umAvzCRMmMKECRhRs3Ahz58Kff8LHH5s8wR4PhITkDdkODISePaF798odut25M2zebFJ95M4NKXJaOlV7/1SiM8+ETZvM8SY93RxXTomOPg1HQP2LYf+vEP8zrPsXHN0BHhc4AsDmANcx879WJ2h9elXSJ00yjZ65jaIiUv21rduWWgG1OJJ5BIAn5j7BE3OfKLScBw8Dmw08rs8Y1HwQ7y5/FwCXx8XCPQvpGmvSgcSnxpN4zEya7bE8DGkx5Lg+o7Ldcw+0bw8TJ8KQISZodPHF0KMHRESY+TTS0kzqpKVLTaqj//0vgJ4NerJg9wLABIJyg0X5NY9sTt2Quid7k0RERKQaig2L5c+b/iR6UjQuj4tPR3zKtZ2urerVqni7dkHr1iY/ZXEKZlMJDDQNlwWCRCJSfVW7AFFNEB1t0rnlT+lmWWZSSYej5DlCKtqrr8Ls2ebYf8cdZh4ij0f5hEVOB6+8YvbvbdtMb+1PPjEBouL275OR1tLL7oTYQeYvP48bsMzzp6HERBOwK5harkMH00lg6dKqWS8ROXEd63Xkj11/lLrc8DbFTEBWigFNB/jc7/9x/2KWhPOanndcn3EynHee+UtMhGXLTKfVn3+Gw4dNJyk/PzPvRZs2MGiQqSO/POhlen1Qcsq8Cf0mnJwNEBERkdNCZFAkmU9kAvjMbygicro5PVvYTkMlNdpWppgY+PZbuOwyM4n9kiVm3pIhQyAy0nfZfftO/vqJyPGrU8fMeXbFFfDVV2b/vv9+GDoUmjfPW87thr//hkWLToG5yE7zuSN++ME3OBQSYo69uYNcV66Eq6+uklUTkRN0d4+7Sw0Q1QupR0xozHG9f63AWoT4hXA0+2iJy9ltdlrXaX1cn3Ey1a1rzkdDh5a+bM8GPTm/2fn8su0XLCzu6XEP0SHRPD73ccBMlnxd5+tKeRcRERERX6d9YKhRI9MjPH+KOSg53X4RKeZEpHpTgEhK1bevSUP16qsweTJcc415vG1bc16wLNizB/buhccfr9JVFZFy6toV/voLPvgA3njDzH0GpmGuXj0TrNizB1JSTEq6Kg8QneZmzvRNL/faa3DJJXnPd+xo5uX47rsqWT0ROQGXtb0Mp82Jy3IVu8yINiNO6DPOjDuTeTvnlbhMy9otzcTKp5lH+z7K7G2zAfht5280CG+ADRsWFo+c9UgVr52IiIjIKapRIwV8RGo4BYikTCIiYPx4+Mc/YOtWMz/SmjVw7JhJeXfWWXDGGXaystoRGMhp2fBwurPb7bRr1857W2qOwEC4807zl5QECxfC2rV5+3dYmAkk9exZ1Wt6enO7TYAoNzg0fDjcfLPvMk4ntG9vZ86cdjRpon1V5GQ7kXOl3W7nzh538sbiN7DZbFzZ/koe6PMAXd8z8wQ5bA7+2f+fJ7R+V3e4utQA0YWtLjyhzzhVndvkXFrVacWmQ5tYvX81fyf+jYVF7aDaXN6u5LlGRURERESKoraymqWmlrfNsiyrqldCjJSUFCIiIkhOTiY8PLyqV0dEpHpasQK6dfN9bPlyE+U6hS1eDL3yTaGxeTM0a1b0vHMndT4oEakwy/Yto/v73QFoUqsJzwx4hmu/uRYbNgY3H8xP1/10Qu+f4cog5NkQPJbJVdk1piv+Tn8W7VnkXWbL3VtoXrt5cW9RPgWPt1V8rH176duM+XGMz2NPnP0E/xxwYoG3E3aKfU8iIiIiInJ6K0+cQSOIRESketu1yzdn8vr1hZcp+NgpmDd51Soz35xlmXR+LVoUv6zNdtJWS0QqULfYbtQPq8/e1L3sOLKDHzf/iN1mx2N5GNl+5Am/f6AzkGGthvH9pu+xsLihyw3EhcVxxVdXeD//hIJDpR1vq/hYe12n63hg9gMcyz4GmHkDbjvztpP2+SIiIiIiItWNAkQiIlJ97doFrVtDRkbJy11XYHLywEAzGecpFCTats2kkMvOhquvNv/9/Kp6rUSkIuWmlnt50csAzNk2B4/lwW6zM6z1sAr5jMEtBvPtxm+x2Wws3beUuNA4nHYnlmVxQcsLjv+Ny3K8reJjbVhAGDefcTNvLHkDgOGth9MgvMFJ+WwREREREZHqqOYk05NKl5WVxVNPPcVTTz1FVlZWVa+OlJPKT6qlgwdLDw4VJSPDtxf8KWD79rz5h4YNKz44lJWVxT//qX1VpCpUxLnysnaXeW/vP7ofgH6N+1EnuE6FrOOg5oOwsPBYHhbuXsjivYtxeVy4LTeDmg86/jc+nuNtFRxrx3TPSzF3T897Tupni4iIiMjpRW1lNUtNLW8FiERERE4BGzeCx2M62peUXk5EqrdeDXoRHRLt89iV7a+ssPdvFtmMRhFmxM7WpK0s3bcUgGC/YHrW71lhn3OqahPVhkBnIGACbyIiIiIiIlI8BYhERKT6iooyKYzKKzDQvPYUsn27+d+7d9Wuh4hULrvNzsh2efMN2bBxSZtLKvQzLmx5ofd27nw85zU9Dz/HCeStPJ7jbRUda9MfT8cab2HThG0iIiIiIiIl0hxEIiJSfTVqZIbeFExhFB8PR46Y27VqQWys7/MneeL00hw5Aqmp5nazZpp/SOR0d3m7y5m8dDIAZzU8i3qh9Sr0/Qc1H8Tby972eWxIiyEn9qalHW+rwbFWREREREREfClAJCIi1VujRtW+ATJ39BBA06ZVtx4icnL0bdTXe3tk+5ElLHl8+jfpj91mx2N5vI+d0PxDuU6D462IiIiIiIjkUYBIRESkim3blne7ZUuNHhI53TnsDhw2B27LzaVtL63w948IjKBHXA8W7V0EQIPwBjSPbF7hnyPF2LXLd6TV+vW+zxe8r5FWIiIiIiJSRRQgEhERqWLbtoHDAW43tGhR1WsjIidD+uPpWJaFv9O/Ut5/aMuh3gDRBS0v0Hw8J8uuXdC6NWRkFL/Mddf53g8MNOn7FCQSEREREZGTTAEiqTB2u52WLVt6b0v1ovITqTr794PdDjZb4Sk8CtK+KlJ1KnL/83NU7lDBQc0HMf638QAMbj64Uj9L8jl4sOTgUFEyMszrFCASEREROaXo+rtmqanlbbMsy6rqlRAjJSWFiIgIkpOTCQ8Pr+rVERGRk+Tee+Htt6F+fd/5iEREjpfL48LvnyYIlfRwErUCa1XtCtUUK1ZAt27lf93y5dC1a8Wvj4iIiIiI1DjliTPUnFCYiIjIKSory/wPCana9RCR04fT7iQmNIYgZ5CCQyIiIiIiIlIkpZgTERGpYtnZYFngV7kZp0Skhom/P76qV0FEREREREROYQoQSYXJyspi0qRJADzwwAP4+1fOpMtSOVR+IlWnPAEi7asiVUf7n5QqKgoCA8s3D1FgoHmdiIiIiJxSVP+vWWpqeStAJBUqOzu7qldBToDKT6RqeDzmf1nnQNS+KlJ1tP9JiRo1go0b4eBB38fj4+HIEahVC2JjfZ+LijKvExEREZFTjur/NUtNLG8FiERERKqYnx/YbGYkkYiIVHONGingIyIiIiIi1UIZ+yqLiIhIZfH3NwGirKyqXhMREREREREREakpFCASERGpYrlzDylAJCIiIiIiIiIiJ4sCRCIiIlUsN0AUH1+16yEiIiIiIiIiIjWHAkQiIiJVLDwcLAtSUyEpqarXRkREREREREREagJnVa+AnD5sNhuNGzf23pbqReUnUnWaNgWXy9zetg26dSt+We2rIlVH+5+IiIiISM2h+n/NUlPL22ZZllXVKyFGSkoKERERJCcnEx4eXtWrIyIiJ8kff8A555jb//0vXHEFONWFQ0REREREREREyqk8cQalmBMREaliTZvm3d6+HTyeqlsXERERERERERGpGRQgEhERqWJxceDnZ25v25Z3W0REREREREREpLIogY1UmKysLF577TUA7r33Xvz9/at4jaQ8VH4iVcduh4YNTXBo7VooKdWt9lWRqqP9T0RERESk5lD9v2apqeWtAJFUqGPHjlX1KsgJUPmJVJ2WLU2AaNkySE6GiIjil9W+KlJ1tP+JiIiIiNQcqv/XLDWxvJViTkRE5BTQvLlJLefxwKxZ4HJV9RqJiIiIiIiIiMjpTAEiERGRU0CzZuB2m9tffQVOjfEVEREREREREZFKpACRiIjIKaB1azN6COD77yEtrWrXR0RERERERERETm8KEImIiJwCzjkHHA5zOyMD3nwzb0RRftnZJ3e9RERERERERETk9KQAkYiIyCkgPBx69QKbzdwfPx42b/adi8iyFCASEREREREREZGKoRkOpMLYbDbi4uK8t6V6UfmJVL0LLoBFi8zIocxMuPJK+P13CAkxwSGbDe66y0ZUVBzt22tfFTnZdK4UEREREak5VP+vWWpqedssy7KqeiXESElJISIiguTkZMLDw6t6dURE5CRbvRq6dPF9rG5dGDsWQkPh/fdh3To44wxYsaIq1lBERERERERERE5l5YkzVJsUc0lJSYwaNYqIiAgiIiIYNWoUR44cKfE1lmUxYcIE4uLiCAoK4txzz+Wvv/7yWSYzM5O7776bqKgoQkJCGDZsGHv27PE+v2PHDm6++WaaNm1KUFAQzZs3Z/z48WRlZfm8j81mK/T3zjvvVNj2i4jI6a9TJ2jWzPexxER4/HG4914THBIREREREREREakI1SZAdM0117Bq1SpmzpzJzJkzWbVqFaNGjSrxNS+88AIvv/wykydPZunSpcTExHD++eeTmprqXWbs2LFMmzaNqVOnMn/+fNLS0rjoootw58wMvmHDBjweD++++y5//fUXr7zyCu+88w6PPfZYoc/76KOPiI+P9/7dcMMNFfsliIjIac1mgzFj8uYhEhERERERERERqSzVIsXc+vXradeuHYsWLaJnz54ALFq0iN69e7NhwwZat25d6DWWZREXF8fYsWN5+OGHATNaqF69ekycOJHbbruN5ORk6tatyyeffMKVV14JwL59+2jYsCE//vgjgwcPLnJ9XnzxRd5++222bdvmfcxmszFt2jQuueSS497O6p5iLjs7mzfffBOAO++8Ez8/vypeIykPlZ/IqSEtDRo0gOTkop/388tm3Lg3iY3VvipysulcKSIiIiJSc6j+X7OcTuV92qWYW7hwIREREd7gEECvXr2IiIhgwYIFRb5m+/btJCQkMGjQIO9jAQEB9OvXz/ua5cuXk52d7bNMXFwcHTp0KPZ9AZKTk6ldu3ahx++66y6ioqLo3r0777zzDh6Pp8TtyszMJCUlxeevOrMsi+TkZJKTk6kGcUcpQOUncmoIDYX77gN7sWdoi+Bg7asiVUHnShERERGRmkP1/5qlppZ3tQgQJSQkEB0dXejx6OhoEhISin0NQL169Xwer1evnve5hIQE/P39iYyMLHaZgrZu3cobb7zB7bff7vP4P//5T7766ivmzJnDVVddxf3338+zzz5b4nY999xz3jmVIiIiaNiwYYnLi4hIzfDAA9CmDTgchZ9T+jkREREREREREakIVRogmjBhAjabrcS/ZcuWASaFW0GWZRX5eH4Fny/La4pbZt++fQwZMoQrrriCW265xee5J554gt69e9OlSxfuv/9+nn76aV588cUSP+fRRx/1RiWTk5PZvXt3icuLiEjNEBwM06dDYCA4nXmP2+1QgzqxiIiIiIiIiIhIJXKWvkjlueuuu7jqqqtKXKZJkyasWbOG/fv3F3ouMTGx0AihXDExMYAZJRQbG+t9/MCBA97XxMTEkJWVRVJSks8oogMHDtCnTx+f99u3bx/9+/end+/evPfee6VuW69evUhJSWH//v3FrmNAQAABAQGlvpeIiNQ8LVvCihUwejT8/rt5rFEjePddWLiwatdNRERERERERESqvyoNEEVFRREVFVXqcr179yY5OZklS5bQo0cPABYvXkxycnKhQE6upk2bEhMTw+zZsznjjDMAyMrKYt68eUycOBGAbt264efnx+zZsxk5ciQA8fHxrFu3jhdeeMH7Xnv37qV///5069aNjz76CHvxE0N4rVy5ksDAQGrVqlXqsiIiIkVp1Qp++w02bYKsLHPfZlOASERERERERERETlyVBojKqm3btgwZMoTRo0fz7rvvAnDrrbdy0UUX0bp1a+9ybdq04bnnnmPEiBHYbDbGjh3Ls88+S8uWLWnZsiXPPvsswcHBXHPNNQBERERw8803c//991OnTh1q167NAw88QMeOHRk4cCBgRg6de+65NGrUiEmTJpGYmOj9vNxRSt9//z0JCQn07t2boKAg5s6dy+OPP86tt96qEUIiInJCbDbId6ojK6vq1kVERERERERERE4f1SJABPDZZ59xzz33MGjQIACGDRvG5MmTfZbZuHEjycnJ3vsPPfQQ6enpjBkzhqSkJHr27MmsWbMICwvzLvPKK6/gdDoZOXIk6enpnHfeeUyZMgVHzszgs2bNYsuWLWzZsoUGDRr4fJ6VMxGEn58fb731Fvfddx8ej4dmzZrx9NNPc+edd1bKd3Gqstls1K1b13tbqheVn0j1oH1VpOpo/xMRERERqTlU/69Zamp52yxL012fKlJSUoiIiCA5OZnw8PCqXh0REREREREREREREalGyhNnKH0yHRERERERERERERERETmtKEAkIiIiIiIiIiIiIiJSw1SbOYjk1Jednc37778PwOjRo/Hz86viNZLyUPmJVA/aV0WqjvY/EREREZGaQ/X/mqWmlrcCRFJhLMsiMTHRe1uqF5WfSPWgfVWk6mj/ExERERGpOVT/r1lqankrxZyIiIiIiIiIiIiIiEgNowCRiIiIiIiIiIiIiIhIDaMAkYiIiIiIiIiIiIiISA2jAJGIiIiIiIiIiIiIiEgNowCRiIiIiIiIiIiIiIhIDeOs6hWQ04fNZiMiIsJ7W6oXlZ9I9aB9VaTqaP8TEREREak5VP+vWWpqedssy7KqeiXESElJISIiguTkZMLDw6t6dUREREREREREREREpBopT5xBKeZERERERERERERERERqGAWIREREREREREREREREahjNQSQVJjs7mylTpgBw44034ufnV7UrJOWi8hOpHrSvilQd7X8iIiIiIjWH6v81S00tbwWIpMJYlsW+ffu8t6V6UfmJVA/aV0WqjvY/EREREZGaQ/X/mqWmlrdSzImIiIiIiIiIiIiIiNQwChCJiIiIiIiIiIiIiIjUMAoQiYiIiIiIiIiIiIiI1DAKEImIiIiIiIiIiIiIiNQwChCJiIiIiIiIiIiIiIjUMM6qXgE5vQQHB1f1KsgJUPmJVA/aV0WqjvY/EREREZGaQ/X/mqUmlrfNsiyrqldCjJSUFCIiIkhOTiY8PLyqV0dERERERERERERERKqR8sQZlGJORERERERERERERESkhlGASEREREREREREREREpIbRHERSYbKzs/nss88AuPbaa/Hz86viNZLyUPmJVA/aV0WqjvY/EREREZGaQ/X/mqWmlrcCRFJhLMti586d3ttSvaj8RKoH7asiVUf7n4iIiIhIzaH6f81SU8tbKeZERERERERERERERERqGAWIREREREREREREREREahgFiERERERERERERERERGoYBYhERERERERERERERERqGAWIREREREREREREREREahhnVa+AnF78/PyqehXkBKj8RKoH7asiVUf7n4iIiIhIzaH6f81SE8vbZlmWVdUrIUZKSgoREREkJycTHh5e1asjIiIiIiIiIiIiIiLVSHniDEoxJyIiIiIiIiIiIiIiUsMoQCQiIiIiIiIiIiIiIlLDaA4iqTAul4svv/wSgJEjR+J06udVnaj8RKoH7asiVUf7n4iIiIhIzaH6f81SU8u7ZmylnBQej4fNmzd7b0v1ovITqR60r4pUHe1/IiIiIiI1h+r/NUtNLe9qk2IuKSmJUaNGERERQUREBKNGjeLIkSMlvsayLCZMmEBcXBxBQUGce+65/PXXXz7LZGZmcvfddxMVFUVISAjDhg1jz549Pss0adIEm83m8/fII4/4LLNr1y4uvvhiQkJCiIqK4p577iErK6tCtl1ERERERERERERERKQiVZsA0TXXXMOqVauYOXMmM2fOZNWqVYwaNarE17zwwgu8/PLLTJ48maVLlxITE8P5559Pamqqd5mxY8cybdo0pk6dyvz580lLS+Oiiy7C7Xb7vNfTTz9NfHy89++JJ57wPud2u7nwwgs5evQo8+fPZ+rUqXz99dfcf//9FfsliIiIiIiIiIiIiIiIVIBqkWJu/fr1zJw5k0WLFtGzZ08A3n//fXr37s3GjRtp3bp1oddYlsWrr77K448/zqWXXgrAxx9/TL169fjvf//LbbfdRnJyMh988AGffPIJAwcOBODTTz+lYcOGzJkzh8GDB3vfLywsjJiYmCLXb9asWfz999/s3r2buLg4AF566SVuvPFGnnnmGcLDwyv0+xARERERERERERERETkR1WIE0cKFC4mIiPAGhwB69epFREQECxYsKPI127dvJyEhgUGDBnkfCwgIoF+/ft7XLF++nOzsbJ9l4uLi6NChQ6H3nThxInXq1KFLly4888wzPunjFi5cSIcOHbzBIYDBgweTmZnJ8uXLi92uzMxMUlJSfP5EREREREREREREREQqW7UYQZSQkEB0dHShx6Ojo0lISCj2NQD16tXzebxevXrs3LnTu4y/vz+RkZGFlsn/vvfeey9du3YlMjKSJUuW8Oijj7J9+3b+/e9/e9+n4OdERkbi7+9f7PoBPPfcczz11FPFPi8iIiIiIiIiIiIiIlIZqjRANGHChFIDJEuXLgXAZrMVes6yrCIfz6/g82V5TcFlxo0b573dqVMnIiMjufzyy72jio53/R599FHuu+8+7/3k5GQaNWpUbUcSZWVlkZGRAUBKSgr+/v5VvEZSHio/kepB+6pI1dH+JyIiIiJSc6j+X7OcTuWdG1+wLKvUZas0QHTXXXdx1VVXlbhMkyZNWLNmDfv37y/0XGJiYqGRO7ly5wtKSEggNjbW+/iBAwe8r4mJiSErK4ukpCSfUUQHDhygT58+xa5Tr169ANiyZQt16tQhJiaGxYsX+yyTlJREdnZ2sesHJuVdQECA9/7BgwcBaNiwYbGvqS6ef/75ql4FOQEqP5HqQfuqSNXR/iciIiIiUnOo/l+znC7lnZqaSkRERInLVGmAKCoqiqioqFKX6927N8nJySxZsoQePXoAsHjxYpKTk4sN5DRt2pSYmBhmz57NGWecAZgo4Lx585g4cSIA3bp1w8/Pj9mzZzNy5EgA4uPjWbduHS+88EKx67Ny5UoAb+Cpd+/ePPPMM8THx3sfmzVrFgEBAXTr1q0sXwUAtWvXBmDXrl2lFpxUfykpKTRs2JDdu3cTHh5e1asjlUzlXbOovGsWlXfNovKuWVTeNYvKu2ZRedcsKu+aReVds6i8axaVd9lYlkVqaipxcXGlLlst5iBq27YtQ4YMYfTo0bz77rsA3HrrrVx00UW0bt3au1ybNm147rnnGDFiBDabjbFjx/Lss8/SsmVLWrZsybPPPktwcDDXXHMNABEREdx8883cf//91KlTh9q1a/PAAw/QsWNHBg4cCMDChQtZtGgR/fv3JyIigqVLlzJu3DiGDRtGo0aNABg0aBDt2rVj1KhRvPjiixw+fJgHHniA0aNHl+uHarfbveulH3jNER4ervKuQVTeNYvKu2ZRedcsKu+aReVds6i8axaVd82i8q5ZVN41i8q7ZlF5l66sA1CqRYAI4LPPPuOee+5h0KBBAAwbNozJkyf7LLNx40aSk5O99x966CHS09MZM2YMSUlJ9OzZk1mzZhEWFuZd5pVXXsHpdDJy5EjS09M577zzmDJlCg6HAzBp4L744gueeuopMjMzady4MaNHj+ahhx7yvofD4WDGjBmMGTOGs846i6CgIK655homTZpUmV+JiIiIiIiIiIiIiIjIcbFZZZmpSE6KlJQUIiIiSE5OVgS0BlB51ywq75pF5V2zqLxrFpV3zaLyrllU3jWLyrtmUXnXLCrvmkXlXbOovCuevapXQPIEBAQwfvx4AgICqnpV5CRQedcsKu+aReVds6i8axaVd82i8q5ZVN41i8q7ZlF51ywq75pF5V2zqLwrnkYQiYiIiIiIiIiIiIiI1DAaQSQiIiIiIiIiIiIiIlLDKEAkIiIiIiIiIiIiIiJSwyhAJCIiIiIiIiIiIiIiUsMoQCQiIiIiIiIiIiIiIlLDKEBUid5++206depEeHg44eHh9O7dm59++qnIZW+77TZsNhuvvvqqz+OZmZncfffdREVFERISwrBhw9izZ89JWHspr9LK+8Ybb8Rms/n89erVy+c9VN7VR1n27/Xr1zNs2DAiIiIICwujV69e7Nq1y/u8yrv6KK28C+7buX8vvviidxmVd/VRWnmnpaVx11130aBBA4KCgmjbti1vv/22z3uovKuP0sp7//793HjjjcTFxREcHMyQIUPYvHmzz3uovKuv5557DpvNxtixY72PWZbFhAkTiIuLIygoiHPPPZe//vrL53Uq8+qpqPL+5ptvGDx4MFFRUdhsNlatWlXodSrv6qlgeWdnZ/Pwww/TsWNHQkJCiIuL4/rrr2ffvn0+r1N5V09F7d8TJkygTZs2hISEEBkZycCBA1m8eLHP61Te1VNR5Z2f2thOL0WVt9rYTl/F7d9qY6s8ChBVogYNGvD888+zbNkyli1bxoABAxg+fHihC8zp06ezePFi4uLiCr3H2LFjmTZtGlOnTmX+/PmkpaVx0UUX4Xa7T9ZmSBmVpbyHDBlCfHy89+/HH3/0eQ+Vd/VRWnlv3bqVvn370qZNG3777TdWr17Nk08+SWBgoPc9VN7VR2nlnX+/jo+P58MPP8Rms3HZZZd530PlXX2UVt7jxo1j5syZfPrpp6xfv55x48Zx99138+2333rfQ+VdfZRU3pZlcckll7Bt2za+/fZbVq5cSePGjRk4cCBHjx71vofKu3paunQp7733Hp06dfJ5/IUXXuDll19m8uTJLF26lJiYGM4//3xSU1O9y6jMq5/iyvvo0aOcddZZPP/888W+VuVd/RRV3seOHWPFihU8+eSTrFixgm+++YZNmzYxbNgwn9eqvKuf4vbvVq1aMXnyn5caPwAAC1RJREFUZNauXcv8+fNp0qQJgwYNIjEx0buMyrv6Ka68c6mN7fRSUnmrje30U1x5q42tkllyUkVGRlr//ve/vff37Nlj1a9f31q3bp3VuHFj65VXXvE+d+TIEcvPz8+aOnWq97G9e/dadrvdmjlz5slcbTlO+cv7hhtusIYPH17ssirv6i9/eV955ZXWddddV+yyKu/qr+DxPL/hw4dbAwYM8N5XeVd/+cu7ffv21tNPP+3zfNeuXa0nnnjCsiyV9+kgt7w3btxoAda6deu8z7lcLqt27drW+++/b1mWyru6Sk1NtVq2bGnNnj3b6tevn3XvvfdalmVZHo/HiomJsZ5//nnvshkZGVZERIT1zjvvWJalMq+Oiivv/LZv324B1sqVK30eV3lXP2Up71xLliyxAGvnzp2WZam8q6PylHdycrIFWHPmzLEsS+VdHZVW3mpjO72UVN5qYzv9lFTeamOrXBpBdJK43W6mTp3K0aNH6d27NwAej4dRo0bx4IMP0r59+0KvWb58OdnZ2QwaNMj7WFxcHB06dGDBggUnbd2l/Ioqb4DffvuN6OhoWrVqxejRozlw4ID3OZV39VWwvD0eDzNmzKBVq1YMHjyY6OhoevbsyfTp072vUXlXX8Xt37n279/PjBkzuPnmm72Pqbyrr6LKu2/fvnz33Xfs3bsXy7KYO3cumzZtYvDgwYDKuzorWN6ZmZkAPj3THA4H/v7+zJ8/H1B5V1d33nknF154IQMHDvR5fPv27SQkJPiUZ0BAAP369fOWp8q8+imuvMtC5V39lKe8k5OTsdls1KpVC1B5V0dlLe+srCzee+89IiIi6Ny5M6Dyro5KKm+1sZ1+Stu/1cZ2eimuvNXGVvmcVb0Cp7u1a9fSu3dvMjIyCA0NZdq0abRr1w6AiRMn4nQ6ueeee4p8bUJCAv7+/kRGRvo8Xq9ePRISEip93aX8SirvoUOHcsUVV9C4cWO2b9/Ok08+yYABA1i+fDkBAQEq72qouPJOSEggLS2N559/nn/9619MnDiRmTNncumllzJ37lz69eun8q6GStq/8/v4448JCwvj0ksv9T6m8q5+Sirv119/ndGjR9OgQQOcTid2u51///vf9O3bF1B5V0fFlXd2djaNGzfm0Ucf5d133yUkJISXX36ZhIQE4uPjAZV3dTR16lRWrFjB0qVLCz2XW2b16tXzebxevXrs3LnTu4zKvPooqbzLQuVdvZSnvDMyMnjkkUe45pprCA8PB1Te1U1ZyvuHH37gqquu4tixY8TGxjJ79myioqIAlXd1U1p5q43t9FJaeauN7fRSUnkfOHBAbWyVTAGiSta6dWtWrVrFkSNH+Prrr7nhhhuYN28e6enpvPbaa6xYsQKbzVau97Qsq9yvkZOjuPJu164dV155pXe5Dh06cOaZZ9K4cWNmzJjh05BckMr71FVceef2QBw+fDjjxo0DoEuXLixYsIB33nmHfv36FfueKu9TV0n7d34ffvgh1157rc+Ig+KovE9dJZX366+/zqJFi/juu+9o3Lgxv//+O2PGjCE2NrbE3qsq71NXSeX99ddfc/PNN1O7dm0cDgcDBw5k6NChpb6nyvvUtHv3bu69915mzZpV4nG6YNmVpTxV5qeespb38VB5n3rKU97Z2dlcddVVeDwe3nrrrVLfW+V96ilreffv359Vq1Zx8OBB3n//fUaOHMnixYuJjo4u9jUq71NPaeW9fPlytbGdRsqyf6uN7fRRWnl7PB5AbWyVSSnmKpm/vz8tWrTgzDPP5LnnnqNz58689tpr/PHHHxw4cIBGjRrhdDpxOp3s3LmT+++/nyZNmgAQExNDVlYWSUlJPu954MCBQr0a5dRQXHkXJTY2lsaNG7N582ZA5V0dFVfeUVFROJ3OQoGDtm3bsmvXLkDlXR2VZf/+448/2LhxI7fccovP4yrv6qe48k5PT+exxx7j5Zdf5uKLL6ZTp07cddddXHnllUyaNAlQeVdHJe3f3bp18waP4uPjmTlzJocOHaJp06aAyru6Wb58OQcOHKBbt27eOvi8efN4/fXXcTqd3jIr2NMwf3mqzKuP0sq7LJMWq7yrj7KWd3Z2NiNHjmT79u3Mnj3bO3oIVN7VSVnLOyQkhBYtWtCrVy8++OADnE4nH3zwAaDyrk5KK+/ffvtNbWynkeM5f6uNrfoqrbzr1KmjNrZKpgDRSWZZFpmZmYwaNYo1a9awatUq719cXBwPPvggP//8M2AaJPz8/Jg9e7b39fHx8axbt44+ffpU1SZIOeSWd1EOHTrE7t27iY2NBVTep4Pc8vb396d79+5s3LjR5/lNmzbRuHFjQOV9Oihq//7ggw/o1q2bN695LpV39Zdb3tnZ2WRnZ2O3+1ahHA6Ht2eTyrv6K2r/joiIoG7dumzevJlly5YxfPhwQOVd3Zx33nmsXbvWpw5+5plncu2117Jq1SqaNWtGTEyMT3lmZWUxb948b3mqzKuP0srb4XCU+h4q7+qjLOWdGxzavHkzc+bMoU6dOj7vofKuPo53/85/jld5Vx+llfeNN96oNrbTyPHs32pjq75KK++AgAC1sVU2SyrNo48+av3+++/W9u3brTVr1liPPfaYZbfbrVmzZhW5fOPGja1XXnnF57Hbb7/datCggTVnzhxrxYoV1oABA6zOnTtbLpfrJGyBlEdJ5Z2ammrdf//91oIFC6zt27dbc+fOtXr37m3Vr1/fSklJ8b6Hyrv6KG3//uabbyw/Pz/rvffeszZv3my98cYblsPhsP744w/ve6i8q4+yHM+Tk5Ot4OBg6+233y7yPVTe1Udp5d2vXz+rffv21ty5c61t27ZZH330kRUYGGi99dZb3vdQeVcfpZX3l19+ac2dO9faunWrNX36dKtx48bWpZde6vMeKu/qrV+/fta9997rvf/8889bERER1jfffGOtXbvWuvrqq63Y2FjV2U4TBcv70KFD1sqVK60ZM2ZYgDV16lRr5cqVVnx8vHcZlXf1lb+8s7OzrWHDhlkNGjSwVq1aZcXHx3v/MjMzva9ReVdf+cs7LS3NevTRR62FCxdaO3bssJYvX27dfPPNVkBAgLVu3Trva1Te1VfB43lBamM7veQvb7Wxnf4K7t9qY6tcChBVoptuuslq3Lix5e/vb9WtW9c677zzig0OWVbRJ6/09HTrrrvusmrXrm0FBQVZF110kbVr165KXnM5HiWV97Fjx6xBgwZZdevWtfz8/KxGjRpZN9xwQ6GyVHlXH2XZvz/44AOrRYsWVmBgoNW5c2dr+vTpPs+rvKuPspT3u+++awUFBVlHjhwp8j1U3tVHaeUdHx9v3XjjjVZcXJwVGBhotW7d2nrppZcsj8fjXUblXX2UVt6vvfaa1aBBA+/5+4knnvBpSLQslXd1V/AC1OPxWOPHj7diYmKsgIAA65xzzrHWrl3r8xqVefVVsLw/+ugjCyj0N378eO8yKu/qK395b9++vciyBqy5c+d6X6Pyrr7yl3d6ero1YsQIKy4uzvL397diY2OtYcOGWUuWLPF5jcq7+jqeAJHKu/rKX95qYzv9FbV/q42t8tgsy7KqZuySiIiIiIiIiIiIiIiIVAXNQSQiIiIiIiIiIiIiIlLDKEAkIiIiIiIiIiIiIiJSwyhAJCIiIiIiIiIiIiIiUsMoQCQiIiIiIiIiIiIiIlLDKEAkIiIiIiIiIiIiIiJSwyhAJCIiIiIiIiIiIiIiUsMoQCQiIiIiIiIiIiIiIlLDKEAkIiIiIiIiIiIiIiJSwyhAJCIiIiIiIiIiIiIiUsMoQCQiIiIiIiIiIiIiIlLDKEAkIiIiIiIiIiIiIiJSwyhAJCIiIiIiIiIiIiIiUsP8P4T7F9WovE4lAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 17\n", + "st = 340\n", + "end = 466\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME3_cut_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TACGGCCTGAGGCAACAATGGGCCCATTGTTCACAGTGCAGCTGCCCGTCACGTGACACTC" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 17\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][406:406+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_tfap[\"tmp_array\"][363:363+1])\n", + "st = 363 - 4\n", + "end = 406 + 10 + 4\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=406,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=406+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=363,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=363+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME3_shortened_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)\n", + "\n", + "\n", + "\n", + "for nuc in onehot_[0][st:end]:\n", + " if nuc[0]==1:\n", + " print(\"A\",end=\"\")\n", + " if nuc[1]==1:\n", + " print(\"C\",end=\"\")\n", + " if nuc[2]==1:\n", + " print(\"G\",end=\"\")\n", + " if nuc[3]==1:\n", + " print(\"T\",end=\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 58\n", + "\n", + "ntrack = 4\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"0\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax2 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax3 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=3, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict_smtsmt[\"smtsmt\"][\"regions\"][ori_index:ori_index+1])\n", + "onehot_[0,motif_embedding_dict[\"smts\"][\"locations\"][ori_index]:motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox2\"].shape[1],:] = patterns_dict_irf4[\"sox2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"s\"][\"locations\"][ori_index]:motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict_irf4[\"sox1\"].shape[1],:] = patterns_dict_irf4[\"sox1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf1\"].shape[1],:] = patterns_dict_irf4[\"mitf1\"][0]\n", + "onehot_[0,motif_embedding_dict[\"sm\"][\"locations\"][ori_index]:motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict_irf4[\"mitf2\"].shape[1],:] = patterns_dict_irf4[\"mitf2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap2\"].shape[1],:] = patterns_dict_irf4[\"tfap2\"][0]\n", + "onehot_[0,motif_embedding_dict[\"smt\"][\"locations\"][ori_index]:motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict_irf4[\"tfap1\"].shape[1],:] = patterns_dict_irf4[\"tfap1\"][0]\n", + "ax4 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=4, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "for ax_ in [ax1,ax2,ax3,ax4]:\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smts\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + " ax_.axvline(x=motif_embedding_dict[\"smtsmt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + " \n", + "plt.savefig(\"figures/motif_embedding/ME4_rand_single_double_irf4_st0_end500_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 58\n", + "st = 315\n", + "end = 479\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"smt\"][\"regions\"][ori_index:ori_index+1])\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"sm\"][\"locations\"][ori_index]+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"smt\"][\"locations\"][ori_index]+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME4_cut_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GTAAGCCTGAGGCGAACAATGGGCCCATTGTTCGATAGTCACGTGACGATG" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ori_index = 58\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][411:411+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "onehot_ = np.copy(res_tfap[\"tmp_array\"][378:378+1])\n", + "st = 378 - 4\n", + "end = 411 + 10 + 4\n", + "\n", + "ntrack = 1\n", + "fig = plt.figure(figsize=(80/500*(end-st),ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_, class_no = 16)\n", + "\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index],linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=motif_embedding_dict[\"s\"][\"locations\"][ori_index]+patterns_dict[\"sox10\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=411,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=411+patterns_dict[\"mitf\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.axvline(x=378,linestyle=\"--\",color=\"gray\")\n", + "ax1.axvline(x=378+patterns_dict[\"tfap2\"].shape[1],linestyle=\"--\",color=\"gray\")\n", + "\n", + "ax1.set_xlim([st,end])\n", + "plt.savefig(\"figures/motif_embedding/ME4_shortened_st\"+str(st)+\"_end\"+str(end)+\"_deepexplainer_topic16.pdf\",transparent=True)\n", + "\n", + "for nuc in onehot_[0][st:end]:\n", + " if nuc[0]==1:\n", + " print(\"A\",end=\"\")\n", + " if nuc[1]==1:\n", + " print(\"C\",end=\"\")\n", + " if nuc[2]==1:\n", + " print(\"G\",end=\"\")\n", + " if nuc[3]==1:\n", + " print(\"T\",end=\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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piVwvuCMVXADDXQniDcES61QqnQmC6DuCfz4lLAli+LM1vxEWuxMbjtee1uPI4pUg42MD8fDy0VgyJhxmmxM3f37Qw0EEgGibNSk+EEqZBDYHKxZf9RWhKbpQtCzsSSgJQow0KAlCnBIEewoh0O/O9bMTMSkuEHqLHc/8nN3p76/9kY+cGh2C1HK8etkESCScYmJGErepPFDaIjaoXHO4Cpe+t8fD1snhZPHU2mxUt7XDXyVDIK/UOOCmIClpNGDOv/7Ee9u6VojUatthc7BQSCWI5D9HXLCPx2PSIv1cDdP5CYhlWXFDPCkuEACQwlf5/cpPsmkRfgjjPeK9KUGOlLfB7mRhsNihG+DKVnf1x+noSUIQxJlFMx8Abx3hageAUyIIQf4YL0qQPcVNsDlYqBVSxAT6eChERioGix02B+vx74GkTufeE2TkX2PDjZq2dtz/7VEcrehc0ThUKW92KUHSo/0RpJZDb7Fj3ktb8enuUuwvbcHX+11q5ix+zTcxNgAAMDk+EABwlK/iLOaVJcmhnZUgADCKT44UN4zcZChBDHfMNofodFCnpebBAlqTDccq28S9OUEMF/L4pGaj3uKhKj7VCEqQCbEBkEoY/PeayZgSHwhtuw03fHJALMoFXEqQ2CAfJPFritJ+NkcXlCBjIv0BuIqXa6lIlhhhUBKEGHTMNodoSeEtCSKVMPj3peMhkzDYmFPvkZw4XqXFhztKAAD/umQCwt2ePykuEAqpBA16C8qaTdCabHj25xwcLm/Fxpx68XENejOsdidkEgb7n1yGCyZGA/C00Vp9qAo1WjM+213a5aKtgu8HEhvkAymfiHH3eA/RKBDqq0QsnxgRlCB1OjMa9RZIJQzSo7kNsVD9JzTWHB3pKzbKbfTSl+NopStYMJCBQ4eTRaPB3Q6LJjmCIAaXFsOZkwQR5oFQXwXUCpn4e2EOMFm5viip4b6QSBjx9yM5CeKuAgEG3g7LvWJNaxpeSpDcGh32Fvesbh0oLHYHbv3iEN7ZWnTK3vOno9VYd6wGb285de/ZF/RmG+5adVgsimFZFmV8T5CkUDUkEgZzR4UC4LyyQzRcY/O9bqrkLD6AMZEvfJkYGwgJw1nD1mnNbnZY3pUgKaQEIYghj7viv4YqpcGyLNYcrsKiV7fiond24/9+PN5vWx6COB3k1blUFtm8GqMjTieLduvg9TRs0JtRpzNDwgDjorhkhFohw6c3TUdquC/qdGbc8vkhsW9JNV90Gx3gSoKU9DsJwn3+MZ2UIJTkJUYWlAQhBh0hsO4jl8JfJfP6mDGR/rhiehwA4M0/C8Tfv7wxDywLXDAxGmdnRHo8RyWXisqKA6XN+HxPmVhRWu0mAxR+jgxQwUchFW209rltWLfyPT0a9JZOwSchKVLu1g9EwN3eJC3Cz+N3Qpb+UFmr+HcfvodIRwuEnpQggo80MLCBw2aDxcNeq6nDvwmCIAaaFlEJYhvxlYKCJD3Gba4AgJhAHyhlriXYqHBu/nA1TB+5FeDC9y/0wTJY7AN6HbirG9uGUU8Qq92Jaz7eh6s/2oc/T9T3/IQB4GBpKzafqMebmwsHdVPvjnBPHK1oHZL3//Prc/Fbdh1e25QPrcmGJoMVBosdDOMqfHnwrDRcOCkab189GWvvmQuA6/1msNhhsTtEi5yJsYEAAI1ShtF8ZeUfuXXQm+2QMEBCiLrzAcBlh1XSYBiS54ggzjTy6nS46sO9Hp78QiEbMLTtYup15kFv9Fzd1o6rP9qHR77PRCtffPDtwUrc+r9DMA6w2pMgBgO7w4n8evckiE78uUFvxou/nsCVH+zFxOc2YfyzG0U3j4FGSL6khPlCo3TFzQLVCnx5y0yo5BLk1+vFeFUNn6CIdlOT96c5ek1bO8r5MU1QggjFy+42swQxEqAkCDHoCAvDCH8lGIbp8nF3L0qBXMpgd1EzDpW1YG9xM3YWNkEmYfDI8tFenyNYYm3Na8Rne0rF31e7eTMLP8cEcgqNmcncc/Lq9Gg1WlHd1u4x6e0uciVHvj1QgeQnf8Wl7+3BT0erAQAJbuoPdyXI6Eg/j99VtnDvuymXC2bMTw0VHytU+bk/N8zXe08Qu8MpyiIBoGUAPc6FYFGorwISBnCy6HOvFIIgiL4g2GE5nCx0A9wPYqhRJfYD8bROlEgYsWILANIiuDnhTFKCCAUDNgcLi31gqkWdTtZD0TicGswfq2xDGx88enRN1ilRZpbxNk9WhxP7Sk+NAkWwbmg12fpt2TBYbM6tx/eHqwAAdieLP/PqxXMUHeADpcxVyPLmVZNx/sRoxAWrERfsA7uTxcGyFuTV6mFzsAhSyxHrdt9P4S2x1vCvHxukhkou9XocCSFqSCUM9BZ7jzalDbzamCCIweO1TQXYV9KCz3a79pqCTR4wdJMgX++vwMwX/8SHO0sG7T1sDifu+PIQ9pW0QCWX4PGzx+D966ZAJZdgW34jrv5oH6wDNMcTxGBR1mz0uE6za1yxl//8UYgPd5Rgf2kL9BY77E4WD6/ORE6Nd7XIySAoScfzdpruRAaoxOIKocdYTRs39sQE+SAptP+FVB/xY8Ts5BAE8wpXUQmiIyUIMbKgJAgx6HTXD8Sd2CA1LpsaCwB4Y3MhXt6YBwC4eka8h/rCHSEJ8ntOHdpMNvAuVR28EvnJgU+ChPoqxSq7A2UtogpEYHdREwBOAfLBjhKwLHC4vFW06YoPcQWu3HuCiEkQftNb2WqC2ebAFr6i013JIvQEAQCZhEFyqC/C/b0rQfLr9Wi3uSo0B1IJIgRZogJ8RCWKexUtQRBEb/jzRD3+u6WwV1XL7nZIrcbhE6TuilajFWsOV8HmxfZBqHqPDeo8h7krAgUlYUo4NzdUNJu8vt5IQPj+Y4J8INRF6AbIEqvJaIHdreJ1MJUg7VYHznlzJ677eP+AVOsLaw+AO0cPfHts0JWZ7kG8nQVN3Txy4HBvIH7ETeV6umkxWvHEj8cBQLQn/S27TkzUJHXRvwMA5iRzRS57i5vFHnATYgM9Cn8mxwcBADL5AEdyWNevp5RJEc8X1HTXcFlvtmHlmztxzls7YbKO7IQyMXCUNRnRRAVPvabZYBH3ivludjnl7koQnXnIKelNVjte/yMfAFfUN1iqsre3FCG7WodAtRy/378Ady1KwdkZUfjmtlnwU8mQVaXF/lOUZCeGJyarHQX1+tOaLBOaggsqbUGRwbKseP8/uCwNv943HwvSwtBuc+D2/x0e8LFU7AcS0zkJAgBTE7i1xOFyTk3rXuzrrSdIb9YGLUYrvj1QCQC4e3GK+HuxJ8gQTfISRH+hJAgx6DTwQXVhIO2OuxeNgkzCYFdRE45WtEEll+DeJaO6fPzUhCCxPwcAXDszAUAHO6w2bpEaHehKWMzkkyf7S1qwLZ+b2JaPiwDA+TrbHU5kVmlR2mSEj1yKJ88Zg/ExAYjwV2LpmHDxdbzZYQmBHZPVgfWZNTBaHYj0V2ESn7kHAD+VHBF80iMpVAOFTIIwX+7fHav+jnYIEgxk0LBe70pQhftx3w/1BSEIoq888eNxvLqpADk1uh4f654EaRlGlfpd8fLGPDzyfSa+2FPW6W+CZ7h7wlzAPRkuJOYj/VVQK6SwO1mPAMtIQvj+Q32V8OWl/oYBUgTVd5Dsn0xPkHXHqnHZe3tQ24UX8i9ZNcit1WFXUdOAKBr2FHNJiNvmJ0GtkGJvSTPe31580q/bHe52LjsKGwf1vQAumOCeBBkqzdFbjFY88n0mmgwWpEX44qMbpgEAdhQ0Ipcf0xJDvRfjAMCcUZzN6t7iZmRW8v1AOlRxCkoQgeRQ7/1ABHqjCtuS14BmoxWNegu2dCjoIQhvtBitWP7GDlz5wd7TfShDiq35DV2OR+uO1YjJ9ZImI8x8YVqZWxLZ4WSHXGJp1b5yNPE92MqaTR6uB33BbHPgnxty8Xt2Xae/HatsE3tKvXBRBhLdksWT44MwK5kbG4ea6o8YOpisdlz63l4s/88OpD/zO859ayde35R/yq0ghabgy9O5otVarRlNBgvy6/Wo05mhkktwx8JkjIv2x9tXTUZSqAbVbe24a9XhAStaYlkWWdWCEiTQ62Om8AUVRyra0GSwwmp3gmG4WE4yf//Vas0wWe14Z2sRxj+7CS/+eqLb8/n57lK02xzIiPHHvFEu55JI0Q7LTNacxIiCkiDEoCMoQSJ7UIIAnJXUpVNixX//ZW6SRzP0jmiUMmTwmfLoABX+yidMGvQWWOzcItVdJigwk1+U7SxsFO2v7luaCn+VDHqzHdk1Oqzl7a9WpEfg9gUpWH/vPOx/cpnHAk+jlGFWcjDign2QHs35JyplUkTwCYWPd5aKryGReFqBCRvcNF5B0pUSREiCCAWFvQka2h1OnKjV9ViVJKg+IvyVYlKmJ+sFgiAId/Rmmzhu9VQtZLE7xN5NwPCyK+qKg3zfp11FnSvpu1OCCE2R1QqpqFRkGEasEB+plljCHBasUcCPT4LoBygJIiQshPmsrb3/fWc+3V2GQ+Wt+IavjuvItwddv99X0tKv9xAwWuziXH/9rEQ8d0E6AOCtPwvFtcxg4K4EKWoweCQoBgNtuw1Gt94jp1sJ0mq04uXf8zD/pS3YktcAmYTB61dMwoTYACSGqGGxO/EDb1+VGNK1cmM2v6bMrtFiL5/MmtAhgJEUqkGgWi7+uzslCOBKjHanBHEPSv6SOTj+5EOBFqMVH+4oJrvWAaCowQCr3YniRuOImH/dERIRfR3z8+p0+MtnB/GXzw967Z0hWNgJ7yHckx0LFQZ7/OwLJqsdH2zn7G0CfLhxx1sSozd8sqsUH+0sxVNrj3uc23arAw+t5hSLF0yMxnkTojs9VwjKjuQ+Z0T/YVkWj67JEvto2Rwscmp0eGtLkajM6A91WjN+OFzVJ3VWHv9+0xODxOs2p0aHrXlcgcjs5BDRwjJALcdHN0yDn1KGg2Wt2JDlff612p14Z2sRfutl/5B6nQWNegukEkZsit6RKbwSpKjBgFz+vIX7KaGQSRCkUYjrjC/3luPVTflwOFl8uKMEz63PFe9fs80h7tsMFjs+54u47l40ykPBKhQwm6wO6Km3DzGCoCQIMegISZDukhnu3LN4FJQyCYLUctyxILnHx58/IQoA8PDy0Qj3U8KHn6CE5IewKHVXgszilSCFDQa02zilRnq0P2ancBvZ7fmNWJ9ZAwC4cHJMt+//9a2zsPXhRR7ezkLVr1B1s6JDU3cAGM8nbwSFiGBH1WSweCzCj1ZyATYh89/WQ0+Q/SXNOPetXVj55k4seW0bVu0rF6uWOtLgZlUmfD+kBCEIoi+4BwIa9N2PH60dxq+B7HF0OjBY7GKy4nB5q8eGi2VZVPLWjLFBnZUg0xKDoJBJMHdUqEeSfKT3BWkxuCVBVNxmbaCSIML8JTShdjhZj6RbXyjjK1d3FHRWSBTU6z0a5O4rOTmrjwNlLbA7WcQG+SA+hLMGDfCRw2J3orB+cK4Dp5vaSEga7RxANYjDyeKVjXkezUMF2wbBbiK/Ttfv72cguPqjfXh3WzGMVgfGRfnj87/MQEZMABiGwdkZ3NpS2Ph3Z4cV7q9CSpgGLAvU8IngCXGeShCGYTA5LlD8d09JEEEpJgRcte02D//xdqsD2/Jd39fW/IYBPZcOJ4trPtqHaz7a1ymQdCorQlmWxYPfHcOLv+bhli8OnRa7lBd+ycU1H+3rci09nHBXto2EOcZqd+LjnSW48dMDmPTcJkx7YbNXVWZ3rDvG7ffaTDZUtHgmNnJrdMit1UEhlWAsH5TMq9PD5nB26jk5lPqC/G9vOZqNViSEqPHkOWMA9C8J0myw4L1tnCKxyWD1UA9+tb8cJY1GRPgr8fyF6V6fLxQOuqtmCELg/e0l2JBVC7mUwZo7Z2PnY4sxmVdNCvGP/vD4D1l4+PtMfLKr971w8niruzGR/kjnYzTZ1VrRMWTR6HCPx48K98Wt87k41XcHOxfLWO1O3PP1EbyyMR93fXUEH+3gjoVlWfxwuArnvb0TG3M878ks3k4zNdwXPgrvPcOCNQpxPfIrn3yJcYtxCQmcf/2WB5blVKgMA3y+pwx//eYobv3iECY//wem/3Mzznp9O+5adRg6sx3JoRqsSPeMV6kVMjGJerLjW622vUtlNUGcaigJQgw69dreK0EAID5Ejd8fWIBf7puPQLWix8ffMi8Jx54+C5dOjQXDMKLiQ7DEEv4fE+h6/3A3ySAALB4TBoZhMJeXAH68qwTNRitCNArMd5MFekMiYSCTet5K7jZZwRoFZiQGd3reX5eMwnvXTsH1szkLr1DeDsvuZMW+H20mq1g9s3h0GIDOShCzzYHcGh3WHavGfd8cxZUf7hOTL+XNJjy1NhvzXtrqVeZdLyZBlKIHNilBCILoC+5Bg54a9DYbPf8+3CtRc6q1EOKBejPnaSzQarLBxFe9u29QBGKD1Dj45DK8f91Uj98LSZDuKsCHM4IdFpcE4e2wLAOTDBOKLhJD1FDJuXm5rR+WWK1GK7R8P5GsqrZO1+k3ByoAcApUgEuCnExgeHchpx6Ym8KtNxiGEdWlQqXfQFOvN8Nid0ImYXD51DgAwI7CgesLsvlEPd7ZWoy//eSqHhaKU0ZH+iEm0AdOFsiqbBuw9+wLJqtdDHq8d+0UbLhvHualutZ7KzsUryR2kwQBgDkprudGBbgsRt0RilkAYFRY93ZYghKkuNGAyhYTVvxnB859a5cYyNxe0Ih2m0P0AbfYnfiT70E3EJQ1G7GnuBl7ipvFKl2As/ib/s/NeGxN5ilJhvx6vA7b+UTksco2/Pu3vEF/T3dajVZ8srsUe4qbkXmartWBRLgHAaC4YfgHpl/6PQ8vbDiB7QWNYsJy9aGqHp7lgmVZsegNcFniCPxwhHutpWPDRSvlvFodqlvb4XCyUMklmMgnPIeKb77RYseHfMD13iWpWJEeCamEQV6dXkzu95a3txR5JFcPlrlUj0IS9s6FKV3u1731KCAIgCu6EPq/PntBOqYlBiMuWC2ugzragfeWVqNVVGZ/trusV1ZV2nabmNQcE+WHDH79ta+kWSx4WcTHYdy5bFosGIazUndX1lrsDtz91WH8kVsv2rb/89cTeH1TPu7/9hge/j4T2dU6vPx7nsc8epy3wprgpSm6O8Ja4rdsLgniXuib5Ga1OS7KH1/fNgsvXToBDANsyKrF5hP1Yq/ZwgYDdvLrvjsXpnhYzAsI8buTGd8259Zj0SvbcO5buwZV3UwQvYWSIMSA03FTJPSdiAxQ9vo1kkI1XoNG3mAYxmPxJTyvqtUEndkmLoqjO7zezGRXYkLI7gubWKEq9fyJ0Z0SHL0hNtiVBDlrbITX1/BTybFyfJSoIJFLJQjWcJ+jkZf8H+M3XEmhGtE6xb0nSHGjAdP/uRnnvLUT9397DD9n1oBhgGtmxmP3E0vwzPnjEBPogyaDBTd/frBT1Vcdb4cV7q8SG9c3eFGCbC9oxKwX/xRtIQiCIAQ8lSDdJ0FaOvQ06vjv4YawYRE45BYgEPqBhPspPZSC7gSo5Z02HalC8HOkJkH4hEKQWgFfPgmiGzA7LGG9oUKgDzefavvRHL3UbTPrZCHaZgJc4cGPRzi7zKfPT4dCJkGD3nJSQZ7dxdzrC70lAIhWCLm96LPTFV/uLcPt/zsEvZfG82VNLpXS4jHc5n53UdOANfcVgvWtJpvoSy8qcwN8xGrPI6epL4hgVeenkmHl+CgPCwiAC0IISS4J41nc4o05Ka7vrqsAhtAc3U8pE9W/XZHCjwP1Oguu+XifmOB7YUMuzDYHfueDH2dnROI8XhG9fgAtsfLcrEjclU4/Z9agyWDF6kNVeHtLUY+vw7IsCur1WH2wEv/343E8tz6n1xWlerMNz63PAQAsTOOu0U93l4qfvSu0JttJ9QNyZ1dRk5joHgl9mtwrcYuGuRLkSEUrPt3N2Q4/dFYavr51JhiGSxz3tuL4SEWbOBYA8LDgsTmcWHeMG+svmxqLsVGcfXFenV5UNiSGaBAVwO0vh0qV8y9ZNWgxWpEYosZFk6IRqFaIln0dK8+7o6zJiFX7ygG4ehod5u0/zTaHmBCZ102xoFBwWNli6lHFVdJowNx/bxEr5gcT7UlYZZ5qzDbHsDnWvvBvXqlw1fQ4sacrAHFtcKyfSec/TtSL65hardlDjdoV+XxBREygD/xVctGtY2dhE+xOFsmhGiR4scSMCfQRr3/BNs/hZHHPV0ex+UQDlDIJPv/LdDx8VhoA4K0tRfg5swZSCQOZhEFxo9Gj0EVQHne00+zIlATu78La2UMJwqtIfZUyvHvtFKjkUlwxLQ5vXz0Z81ND8eCyNPxy7zwce/osvHnVJFw0KRpXz4jDRV04nwiWWPX9TIL8cLgKd6w6DIvdiRajddDUzQTRFygJQgwoOTVaTHhuE97cXAiA2/wIfSe8VcUNBoLtSHVbu7jhDlLLoVbIPB43M4lbECqkEnECSwnTeChWLu7BCqsr4tysT872YoXVFWJzdJ1nEmRyXCCC+ERPq1tF6oHSFujNdvjIpZieGIRrZsZj7d1z8eLF4xET6IO/zE3CpgcXYGJsAFpNNtzwyQEPu6sGt34tghKkvoOdTb3OjAe+PYo6nRmf7Snt1efIq9Nh/0nagxDEcKOwXj9kNsGnkooWV/BXGLu6omPSo3WYK0GyqrgkiCAXP1DmCugKgZW44O6Dpx1JjXApQUbixle4BkJ8XXZYA9YY3W1OE3yR+6ME6Vgt626J9Xt2HbTtNsQE+uCscRGixVF/+4I0Gyxipb27miA95uSSIHaHEy9vzMem3HqvBQxC1WJCiAYTYwPhp5KhzWTD8WotqtvasSGrtl8JJICrgtzspkoobOACDO72pO7NPU8HVbxVXVfJDYZhRCvT2CA1FLLut0xCrzmg6wDG7JQQ3DQnEX8/f1ynpEtH/FVycV1W2dKOuGAfRPqrUNXajne3FePPE5xFx8qMSNGLf0dBY7+/s47ku1XE7y12ree2u90Lr/9R0GNQ9am12Vj+nx147IcsfHOgAp/tLsPS17bhwx3FPVbovrapAA16CxJD1Pjg+qmiRe6j32d1mXQsbjRg0atbMePFzXhna9FJ22e5f97yluFfze5ezTucE+0WuwOPr8kCy3J7tfuWpmLOqFBxPBbuj574mU9yCPe3uxJkV2ETmgxWhPoqsCAtDGMi/cXHCAmx+GA1ogJOvlJ6IBEquy+cFCMW4Qlj2e99SIK8sikfdieLhWlhuGcx13PzYDk3zx2paIXF7kSYn1JUrXkjzE8JjUIKJ4tOVmMdWX2oCtVt7fiaV1oOFpty6jDxuU1iH4ShTEG9HuOf3Ygnf8o+3YfSJ1iWxU9Hq7D6UCX2Fjd32hvl1emQU6ODXMrg8bPHePxtEn8PFzUYxPnMYnfgsTWZ+Hx3z3GIjXwBhjB/frKrtMe1tHDfC4nO9GjPQoaFXlQgAldM45S0a/geJK9uysfmE/VQyiT45MbpmJ8ahnuXpoq2dHHBPvj+ztk4a1wEAK6wAACOV2mRWaWFQirpMXY0NSHI49/uhb6XT43FuROi8MH1Uz0UrOdNiMaXt8zE/ctSkRETgEC1AhdOisEbV03Gvy6Z0OUa52TGt6/2l+Ph7zPhcLKQS7k1T2/UzS1GK77YUzZgxQwE0RFKghADyic7S6E32/HTUW7D3WqyiRuQiF7aYZ0s7nZYghVWRxUIwEmbZyQF446FydDwzVkZhhErMZNDNT3KEbtCkP/6KWUelZ090bE5uiAFnRwfiCANF9BpdZsQhAnposkx+P7OOXjx4vGY6OY5DXDN2z+9aTqSQjWobmvHjZ8eQLvVAavdiWY+GBXhoQRxBTGdThYPrT4mvmd2tc7D87/NZMW2/AaPxYXZ5sBVH+7DdZ/s77E/AEGMFKpaTTjv7V248dMDp/tQTjlCRTngUrF1RbOhQxJkmPcEyeaVIFfPiAcAHCxtEcfD7vqBdEdCiAYyCQOj1TFkgioDibsdlu8AN0avc7PfFBJTbe19T7QJSRDhu9tR2AiWZcGyLL7ezwVoLp8WC6mEwSw++N3fviB7+eeNifTzUAeMi+LWH7m1Oq/Nensiu0Ynnte1x2o6/V3wdk8MUUMmlYgWFLf/7xDm/nsL7vn6CF7blN/n9wWAPUXNHt+pYO1WLSZBVGJzz6MVracl2VfZIiQpu74/r5weBx+5VLQj7Y5gjUKslp6d4n3dJ5UwePaCdDFo0hNCcDHcT4mvbpmF/+ODKG/9WQi9xY4wPyWmxAdhdKQfUsN9YXU4sTl3YCyxTtS5KuIPlLbA7nBCb7bhCG8NsiKdC+A89N0xsYrWG7t5W5KJcYG4Y0EypsQHwmh14MVf83Dpe3tgsnq/93NqtPjf3jIAwD8uyoBKLsUjK0ZjemIQ9BY7bvn8YKcASavRips/P4hWkw0WuxOvbMzHOW/t9GoH2xtYlvVIgJaREmTI8M7WYhQ2GBDqq8DT540Tf790LHddbsnzngRZfagS//djFtpMVtgdTmzgq8Rv5K2J89yu5R18j6Tl6ZGQSyVIi/ADw3C9MQSLnMRQdyXI4M3XPx6pwrM/5/Q4FzidLPbwSUt3e78V4yLAMNy+sjdKrKMVXLNnhgGeWDlGDLqWNBrRbLBgD6+OnJMS0m1Cl2EYV18Qfl612B247L09uP1/hzzGfqH3QmmTcVCtUn86yiW+urpGhhLb8htgc7D45kBFv8exwcZsc3RKaG/Ja8CD32XisTVZuPqjfZj9ry14Y3OB+HdBTbtkTDiCNJ5WaiG+SsTzxUNCj4yNOfVYfagKz/+S220vI73ZJiYB37xqMhQyCbKqtDhU3v25EwpRhERngFrusTbo2A/EneXpEQhUy1GrNeOZn7PFHjqvXD7R4x68fUEKdj62GH88uBBT4oNw/kSueOGXzFqwLCuqrs4ZHylapHdFarifuH4GPONc4f4qvHPNFNHi/WQRlCB1ur4V+bEsi5d4+8qb5ybh+lmJAHou7GkxWnHlB3vxzM85+PfvJzz+tqOgES/8kgudF3UzQfQFSoIQA4bObMOvvES9rNkErckmLrRCNIoeq+gGCpcdlksJ4s1ay08lx+o7ZuPh5aM9fn/tzHiE+ipx39LUHiv1umJqQhAeXJaGN66aBKXMuw2KN0QliN4Cq90p2kRMigtCMK8EaTNZxUWwIE0UsvRdEeKrxP9unoFQXwXy6vTYcLxWDFbKpQyC1HIxAdNksMDOL2Y+2FGC3UXN8JFLxQXJdrdGnA+vzsRNnx0UJaAAt+FtM9lgc7AeEnOCGMnsKWqGxe5EQb1hRDRP7QsePUG82Om54x4ABzr3OBpO6Mw2lPCb+utnJ0AmYVCnM4uB3p4qzbtCLpWIQYPCPlbqGiz2LoOKQwGr3SkGx4PVCvirhCTIwGxoBOVpZMDJKUFK+WDn5VPjoJBJUKs1o7jRgPVZtThQ1gKZhBED2e5JkP4E83eLwSTPDWtymAYKmQQGi11MqPXtdV39PY5VtnWqnHdXggDAAt5uyN3S7lBZ/4Iugk+1YPUm2B+4r8nGRflDKZOg1WQ7LX7xgl1dd/fnmEh/HH36LDx7gfemvx1599qp+Pb2WR69P06GOxamYNnYCKy6dSbiQ9S4YGI0prlVgK5Ij4CEP8fn8pZYPx6t6vN1aLTYUdEhwO+e2NBb7Mip0WFPcTPsThaJIWr895opmJ0cAqPVgTf/LOj4kiLC9fTGlZPwf+eMxZo75+DlyyYgwEeOrCotnl6X4/V5X+wpg5PlAkLzU7lrUy6V4J1rpyA6QIWSJiPu+uqwGHyz2B24Y9VhlDebEBvkgxcuykCIRoGiBgNu+uxgv8aYvDq9x/3Q8RwNBD8eqcJLv+eJ6+7BptatJ0hli2lYrlcqW0x4dytnxfbcBRkeQdSlY7lg5e6iJrRbPT+bzmzD39dm45sDlbjkvT1YfagKTQYrgtRy3MY3OC5vNsHI2yjv59V9whjvo5AiiR8vhQB6QogaUXzPycFqjN5ssOCJH47j8z1lONqDRdCJOh1ajFZoFFKxoh7gAqNT+XHp+k/2Y+3R6i6vOZZl8S8+eHnplFiMjfJHoFohWnUeLm/F7mLPPlbd0bEvyJHyNhwqb8Wm3HrRUrReZ/ZIQGVWaTu/0ADgdLJi4cFwUELl17mO8cVfTww5dbDJasfy/+zA+W/v8kjQCd9fhL8SCSHcHPvutmJUt7XD7nCKiahLp8R6fV3h2j3GF4P+wqslnCxXBCDgdLI4VNYi3utb8hpgdTiRHKrBrORgXMI7enyys3sFiWCDN4ZXggAQLbFUconYD8gbSpkUF03i3mfVPq5I5ua5SbiAT3K4ExesFu1xl4wJh0YhRXVbO7blN2JdJndOrpuV0Ol5HZFKGNE2DPAe5xooBIeUvo5v9ToLdGY7pBIGT6wcg4yYnvvcadttuP6T/eLeZ92xGnHuNtsceOC7Y/h4Vylu/98h6i1CnBSUBCEGjF8ya2G2uRZUx6u1orVS+ClSgQCcbQHAVRxW84t9b0qQrpiaEIxDTy3r0huxNzAMg/uXpYoVSb0lzE0JsqOgEXqzHaG+SoyN8hP7njhZiBnwOjfrj56IC1aLWfhfsmpE25BwPxUYhkGIRgkJw71+s9GK/Dq9WAX63AXpuGgSN5kLjfCqWk3YwlftrD5UKb6P4AMOdK76JoiRyv5SlxXOYG2EhyIWuwM1bpWljQaLuEljWRb/3JCLL/nqJgCi+kxoCjycG6MLKpDYIB/EBPognd8wCYFjodK8r0oQwNUXpLC+6wrrjhgsdix+dRsue2/vadko7y1uxqTnN4nVbN4Qvm8Jw1mIuRqjn3ziRm+2ia/j3hOkP9eYkCAYE+Unbn7XHK7G0+s4S4p7l6SK64rJ8YEn1RdE6CMzp4N6QC6VYEwktyHP6Ycl1h4+SCVYEAje9gKiEiSUWzNdOjUGdy9KwVPnjsX3d84GwNlY9dVOyO5w4g9ejSBYirrssFxrMoVMIgYZ+tsA9WQQEks92dWp5NJeF8REBqjEgOlAsDAtDB/fOA1pEdx1wDAMnjk/HcLhnJ0eJT72wkkxkDBcUu3Zn3P6NAbc8/URLH5tmzimGSx2MbktVIDvLWkWVREL0sIgl0rwyArO53x/SYvX9+OSslygQrAmkfAJxPevmwoJw1mIdLRrM1nt2JDFJdJumpPk8bdwPxU+uWk6NAop9hQ3469fH8Fz63Nw+ft7caC0Bb68+vm6WQnY8vAiJIdpoG23ecxDvUX4vEJFcFmzcUDH1gadGY//kIX3thVjfVZntdZAY7Y5xDlYIZXAyULsbTGc2F/aAruTxaS4QJwz3tM2ZnSEH2ICfWCxOz0SwQDw2/FaWPjxrKTRiCd/Og4AWDk+CuFutsD59XpoTTac4C1yZrkFQIUgqTDXcD1BeM98nXnAeiq5892hSlj5hEVPfdSEzzwzOQTyDv0oHzorDX5KGQobDHjgu2NY8tp2/JxZ0+ma/vNEAw6UtkApk+AhvpcBAExL5MaCbQWNohVob9wOhL4gQtHI/lKXanIdr1J0t50DgMx+9oPoiRN1OrEwokZrFhNeQ5UCtzXgwTIucTSU2J7fiIoWE/Lq9B7FGsLa9bb5ydj2yCLMSg6G1e7EaxvzsbOoCY16C4LU8i4VFmISpLINOrNNjD0AnH1UYb0eLMvisR+ycNn7e3Hpe3vQbLCI9oxnZ0SCYRjcPI+bPzbm1omFDx1xOlkx6S8oQQBgIm9rOTcltMu+fgLu6s4ZScGiarM7VHIplqdz49ejazJhtjkxJtKvk9VVV0x2K7YYzCRIPJ/Eyq7pmypZUOwkBHN2omP5PncnanVe59EWXsmZU6NDiEaB2CAfmKwO0S7shyNV4vi3r6QFD32XOSjjLXFmQEkQYsAQAuEKftGVVd0mKhUi/XvfFP1kEQJOdTqz6FU/mJPDQOJSgpixlg9YXDiJa86ukElE6aMwCQjB1ogelCAC503kNsy7CpvECT+C/26kEka04mjQWfDF3jLYnSyWjQ3H5dNisWgMt1DZUdgIu8OJNYerxGaRB8taUdFs4oIfbj7gTT1Y4xDESOFAmWtTV3MG9QWpam0Hy3KVUgBgc7DiBrOg3oCPdpbiH7/kigvVFiM3JghNf1uGgR2WzeH0umA/zgcBBNvEGXyA4GBZC+p1ZuTUCEmSvilBAFcSpKgPlYrHq7Ro1FuQW6sTgw2nknXHqtFm4hoZZ1d7r+IUAnBBagUkEmZA7bCExL6fSga1QtZvJQjLsmIyIylUgwV8Ffr724vRZrIhPdofdy9OER+vkkv73RfE6WRRzm/MR0f6dfp7f5ujm20OMRl3O99HYe3Rao8EZUcliFImxWNnj8Gt85MxLSEIfkoZbA62W+sJb+wvbUGryYZgjQLXzuRs4ooaDLA5nGJhjJBAEiyxTkdz9JNJUp5OxscG4MWLx+PeJaM8EmdJoRr8+5IJYBjgi73leG59bq8C9jV8FarDyYoNZIXAW5ifEueM59aNe4ubxUCl0KQ8IyYACpkEzUar1wSg0HdOo5CKtrMCs1NC8MAyLsD61NpsFDW4gn2/Hq+D0epAYoga0xM7B4TGRvnj7WsmQ8JwNimf7S5DVpUWUgmD/14zWUwaBajl+Cvfy+CTnaVitbDTyWJ/SXOPyVfh814zg6vM1Zvt/VKWdcWq/RWwObjv6IPtJYOevBb2DCq5BOOiubGluGH4JUGE63NibECnBCXDMKIa5M88z4CxYMHzl7mJSI92BTuFiu0x/HibV6vHwbIWsCx3X7kX8rkHSQGuJ0iYL1dEZney4r7nzc2FXiv3Myvb+mQV7HCy+Gqfq0dGT33UBCsgb1Y4c0aFYtcTS/DI8jQEaxSoaDHhvm+O4qJ392BvMadktDuceOl3TgXyl7lJHkWE0xKEggCu90FCiLpX65tEUQnCzSX73ebJ9Zk1cDhZ0WVA2IcOVhLEvb8RwCXDhioOJysWEAhKv5d+y+uxl1J3sCyLL/eW4UBp39YqXeHeY+aEW4V/Pn+PchZyDJ48ZywA4Kdj1Xh9E6ccvHBSTJcuIYLK4WhlGzbl1MPqcGJUuC+Wj4sAywJv/lmI1/8oEJ0ocmt1uPLDfdiax11HKzOixPefOyoELOvqvdGRdZnVaLc5oJRJkBjiup6vn52AB5el9UoJOi7aHxdNikZ6tD/+e83kTgnIrhDGnia+aPT62Qm9LroQkiUahRT+PrIeHt1/piYEQaOQolFvEZVbvUFYOwr7vZQwXyikEujNdg+nEIvdgQ93FGPhK1txuLwVAT5yrLp1Jm6akwgA+OZABZxOFh/zap4LJkZDLmWw4Xgt/vFL7gB9SuJMg5IgxIBQUK/Hsco2yCQMbpqbCADIqtS6lAq9DNIPBGG+SiikEjicrOjZGjNMNrnC4q+0yShWUgoSSwBufUH4JIiud3ZYAilhvhgb5Q+7k8X/9nJVce69WoSfS5uN+Jmvzrl5XhIYhsHE2EAEqeXQm+04WNaK7w9xCw8hiPXT0WrsL23x2CA2UxKEOAOoaWsXA2qAp93ESEcIpCaF+opBZ8E+RAiKWe1O0QZHSOCmhHGb4jaTtd+Bn1ajddCr+Oq0Zkz5xx/4y+cHO208s/jNwPiYQADAtEQuQLCzsAlXf7QPTQYrYoN8el3V5c4oPojXlySIe0NXQV1wKhHsD2wOFg98d8yrzUprBzs0oTH6QPj71mm5606YDwOEJEgfG0W3GK3Qm+1gGC7AJdhEAZyq4rUrJnba4PamL8jao9UY/dRvHtXJgvWlTMJ4nceFQJ2QUHM4Waw+VCned11xpJxrWhvup8Tdi0bBRy5FWbNJ/I4aDRaYrA5IGO9JAIZhxIrnE71oYumOEEhfPi5CTOw0Gax89R/XgDiE//6F5FFfm6PbHU68s7UI72wtwpGK1n5ZCfVWCTIUuXpGPB5ePlq0whK4YnocXrpkAgDg8z1leNPNNqQrhO8LcAVQ8wRrkEg/zOav7d1FTahqbYdc6uqDo5S5LHcOehlzhLmgKzX4PYtHYe6oELTbHLjnq6NikuJ7vqjqsqmxXQaEloyJwGtXTMRZ4yJw2/wkvHTpeGx+aGGnyuILJkYjLtgHzUYrvjlQAYeTxSPfZ+LKD/fhsTWZXZ4Xk9UuJhJXpEeIiuv+Kic+3lmCjGc24k++UMhid+Dr/S51Sl6dHrs6KBcGGqFAIzrAR+w309ck51BAsE0a3SEhISCo8P884epZWNliwv7SFjAMV52++o7ZuGxqLC6ZEoMZ/Nw9lh+v8up0olqhow3OGLdktVzKIDrQBzKpRNw/1WrNqGg24T+bC/DhjhKPOTy7WouL3t2NGz450Ot1z5a8BtFiE0C3jYLNNod4H87roh9AgI8cf12Sil2PL8bDZ6VBrZAis7INV3+0D8te344HV2eisMGAQLUcdy1K8XiuoAQR1IEdLRy7IknsCWLysHpWSDkF5e6iJuzk+6/cwSftM6vaBiUp2DEJMpSvf86uzgmlTIIXLx6PEI0CJU1GD/eFvpJdrcPf1+Xgwe+OnfTxWe1Oj74qufy8YbY5UN7sWdwxITYQF0yMBstCDKR3ZYUFcEkFhVSCFqMVH+7gemycNyEKD/LKpF+yavH2Fs4S7/6lqYgKUKGowYB2mwMxgT6i9RIAnD+BSzQI6kIBlmXx9p+FePA7bh64ZEoMZG5rO7VChvuXpfZ6jfDGVZOx4b75CPfrfcxrXmqouHfyVco8Yj49MSs5GMvGRuDOhSn9tm/vDUqZVFwH/3mi90okwW4uhVf+K2QSpEZwPwuWWM0GC1a+sRMv/poHvdmOcVH++OrWmRgb5Y9Lp8RCIZMgu1qHNzYXoLTJCH+VDP+6ZDxeu2ISAG6dI4wdBNEXKAlCDAjChmXJmHAs5jcgx6u1YmXmqWqKDnBS++hAQZrMbcD6Yod1OhEmzpwaHSx2J1LCNB4TudAXpNVoQ7vVAS0f3OnL+T2PryYRAhvuzxWk4J/sKoXBYkdiiFrcAEsljDgJ/vv3PFS3tcNfJXNVdxytEn3ABZrIDos4A+gY/KlpO3OUIMJGJ4GvhgQ4Oz8AohIPcNkgiEkQPgBjd7LQ9yOR0WywYOErW7HijR2DmmzdV8I1eN6W34jn1nt613dUgghe/RUtJpQ0GhEdoMI3t82Cj6L3faEEBLuwwgZDrwMB7h7+B/vZy6G/tFsdYnVugI8cRQ0G/Jv3FHdHVILwQXDfAbTDEhr+CnOayw6rb0kQIcgZHeADlVyKtAhfMUHxwLK0TpXAgCtQdrSy6/P+3cFKWOxOD8tIwXIoJsjHY/MtIFRrCxvGD3eU4LE1Wbjvm6PdfgbRr31UKDRKGZbzTazX8j7cwn0bHejTZd8yd+uC3lLebBQ/38rxUVArZK7m8nxVfXSASgzeC0qQ/Dpdn66Bf/ySi1c25uOVjfm45N09mPz8H50slVqMVnywvVhcJ7mjNdlE9dFwU4L0xBXT4/CPizIAcGu5nno+/OIWGMqu0aLZYEF+ndAk1g9jIv0QpJbDzqv5piUEe6g6posKuM7XvpAEEQp8OiKVMHjjyskI9VUiv16PZ3/OQUWzK1h9STdBMgC4eHIsPrphGv527jhcOT1eDLa6I5NKcPciTg3ywY5iPLT6GH7k74Nfj9d5KFDc2VfSDKvDidggHySFakRLkIouLFW6o8VoxX/+KIDBYsfD32eiVtuO9Zm1aDJYEemvwnWzOMXUhztK+vzafUEo0IgKVIlJkL4k2ocKBWISxNfr32clB0OtkKLBrXJZsAOcnRyC6EAfaJQyvHr5RLx+xSRxPBISv3m1etHidGayZxJEGBcBLoEq9D0Siv1q29o9FPHH3BQNe4qbwLJcEmdvNwlzd/63twwAIOPfpzslyJGKVphtToT6KpEW4f3cCKgVMty7NBXbHl2Ea2fGQyWXoLjRiPV8tfy9S1IR4CP3eE58sNrjXp7bCysswJUEqdOZsa+E658XolHg0qlcwPfFX09AZ7YjwEeOa2bGQy5l0GSwDnhfSbvDKX6vE/l126m6/rOrtXhtU36nPjXdIagpUiN8EeAjF1Wdm3L6b4klKEuq29pP2o52L78+FhDWCiWNRjicLPxVMjGuAACPrhgtuoWkhvt6xDc6opRJMZZf/xTwPcXOmxCNsVH+OHe8ywbygWWpePCsNKy+Y7Y4l58zPtIjKbAiPRJSCYPcWp1YnMWyLB7/IQuv/cGpUm6Zl4QXLhrf/5PRT+RSiZikuWxqbCfFZHcoZVJ8fOM03Ls0dbAOT0RILG8+0dDDI10U8yoroegN6Kxu/uZABUqajAj1VeKVyyZg/b3zkMHbpAZpFDgng7MLe4tPeF07KwEapQwXTIwWlSKvbMwfcr1yiKEPJUGIk8Zid4gNrq6YFoeMGH8wDDfBCoPcqUyCAJ2VH0JSZKjTcaN48eQYj4k8yK2ZsKAC8ZFLxeayvUGYbAU8kiD8z4IM+crp8R7vLyS4hL9fNDkGF06KFqtMBXWIkCwhOyyiO1qN1i49WocTwqZK2KTWnEE9QcQkSIga4f4uOz/3vwFAWYckSEygD3x4j93WHjyuvfFbdh10vKT6vm+PDpovrLsf86p9FWK/izaTVQyGZURzC/YQXyWS+cV+pL8K39w+q99V5slhGkgYrklgYy/H0RMeSZBTqwTJrdXB4WQR6qvEW1dPBsBVaHX0ZBe+/xBRCTLwdlhCxbZQXadt596TZVm8t624x6qx0ibXNQ1wqoi3r56MZ84fJ1apdkQIkNZrLV43Y3aHUwyGudsGCddQfBfXyZhIbj1Vr7OgqEEvNgPOrNJ2GbwF3Jutc0EqocfZ+swaWO1O8X5MDOkcNBYYJyZBeu5Lw7IsVu0rx8o3d6LZaEVMoI9YQCFYuwme3u5FKRH+KsQE+sDJAlm9tD/5394yfMErWRemhSHARw69xY5nf87xUIY9tfY4/vVbHj7YXtzpNQQVSKivAmrF4NlInC6unRGPqACVmMDtisoWE45VtoFhuDGZZYFdRU3iWDIm0h8SCYOZSa5g58LRYR6vISjgvCpBxN5zXVvihvkp8eZVk8AwXO+D+77lEnzzRoUOWAHTJVNiEOmvQr3OgnXHaiCTMGKQ+P3t3hMPgj3PwrQwMAwj2qSUNbnmNYvd0SsV0sc7S2Dkg59tJhse+PYYPtvNWXtcPzsBdyxIgYThlDi5NTocr9Li/348jm8OVHT3sn1GSBRHBfiI1blDuRLeG1qTTdz/CLZnHVHKpKJl20OruaSTYIV1cTf9HoUEd06NVrR0dL/2Ae4+ERTwCW7jdnQAd63Was34I9eV6M6sahN/du999NX+nr/bkkYDdhY2gWE46yAAaO0mqS/Mt/NGhfS6MjzcT4V/XjweB/62DP++ZDxmJnHV5UJizh2GYcRiDwDiGN8TgWqFqP787iBXNDkjKVj8TIKyZ35qKNQKmZhocj93A8Hxai0MFjv8VTKcz9sQnarr/9E1WXh7SxE+2dX7RKeQ7BOuc0F5czIqmTK3dbl7I/r+IBQ8CGOpkAQREi2jI/08rsO4YLWYyLlxTmKP16igFAW45KOQuH1kxWjEB6tx67wk3M8nAOKC1fjx7jl47oL0TkmBII1CtIcTlI9/nmjA6kNVkEoYvHBRBv5+3jgxoXmqeXzlGLx82QQ8sbLnPiKni8Wjw8Aw3FpfKPQraTTg/37M6jKR2NEOC/As7GFZVowfPn72aFw+La7Td3D1DNc4JJcyYuIDAP66ZBTUCimyqrTYeBKJQeLMhJIgxElhtNhx2/8Oo8lgRZifEotGh8FPJReboAnWC71p3D2QuPcAUcgkCNWcup4kJ0N4h94pF3aQRQaJShCr6O0bFaDqkwwyPkQtVi4Drp4gABDhJuGUSRhcNtWzCm9BWhjc3+qKaXHQKGU4m8/UW+xO+PEZeoCSIETXsCyLqz7ch8WvbsOuwsG1gBhsBG/dRXxwqPYM6gkiBnFD1KKSrUFUgrg2W6VNXGWYYE0UrHFtirvb1HeFu+psd1EzXtuU378P0AOF/OJesMB49uccvPR7Hv7LVyUlhqhF2yUAeHBZGhaPDsPXt80Uey30B5VcKgbGi+p73qQ7nKy4YQa4BJQQgDwVZPHBiomxAViYFiYGUN7YXODxuJYOShB/3g7LMABJkI72kIE+nj1B9pW04KXf8/D4mqxuX0dMELhVlU9LDMZf5iZ5VWsALhWn1eH02rj2RK0e7XxFfolb0KWCV510lSzTKGVI4q+j+7455qGaWnvUu7+1zmwTvw9h4z9/VCjC/ZRoNlrx361FHsnLrhACUbldNLF05/EfsvDU2myYrA7MSg7Gt7fPEr2+U/kAjmCB0jGwLXh/96YvyI6CRjy3nvOAfuzs0fji5hk48vezkBSqgd5iF3upVbWaxACNYIvqThWfBOlPv57hgETCiOuwnzOru3ycMI7OTAoWVcLbCxpFVZlgZTLbrfeI0CNHYGpCEBjG+5gjqAJ7sgeZOyoU9y3hAldCsrDj+vNkUMqkuGMhF3yTSRj895opeOlSzjZs7dHqTurNnBotvuWDtULxjzCel/MKx1ajFfNe2oprP97f7Xu3Gq34Yk8ZAODJc8ZArZBif2kLcmp0UMokuGZGPOKC1VjJVzdf/8l+nP/fXfjmQAWeWpvdryKBrqjl9w3RASqxOre40dCnZrenG8H2MSbQR7RT9MZjZ49BpD9nkXPeW7tQ0mSESi4Rz7M3UsJ8IZMwMFodcLJAXLBPp/FKImHE+8J9jheUIHl1Og9VlLsSxD0JsjG7rsfeIKv4XiCLR4djYhy3b+uuen8Xn/z21g+kJ/xVclw1Ix7f3TEbH984rUuFoJD0HBvljxDf3u+thSTiJj5BNDMpGDMSgz3iA4KVndCQuru+IBa7A29sLsAD3x7tUe0msIe3wpqVHCLOS6dCCVJQrxcTBKsPVfX6fhOUIKP5Yx0d6QeFVII2k61fijQAHlaa+SeRBHE4WdG2+z4+6VDV2g5tu0183VQvScqHl6dhO68+6glhbQC4XCwATlm047HFeOq8cR7xj3A/FW6ckyiuK905dzwXp/glq9aj783tC5Jx3ayEHo9lMPFVynDFtLgem6+fTkJ8lZjCN2L/M68BNocTd391BN8cqMSNnx7opMg3WOzifJMS6kqCjHVTghyv1qK40QilTCLGkToyIylYnKsumBjjUbgb6qvELXzj+9c25VOTdKJP9CsJ8u677yIpKQkqlQpTp07Fzp07e/W83bt3QyaTYdKkSf15W2KI0WSw4OqP9mFHQSN85FK8evlEMUAwgV/ACJxqJYj7xtbdemGo46eUQckHDqYnBnUKjIhJEJPtpKzG3BcTnkoQ14J22diITsqUYI1CXJxmxPiLkkX3yqqlY8MRzW8GyA6L6IqSJiPy6/WwO1nc+82RIakIqdOa8dnuUtH/2BtNBou4iRIqy3rTE6RBb8b3hyp7vXkbqgjWQQnBGnG8EAJf7kqQ0iYjWk1WsCzAMFyAWqjU72uQp9lgERtQP7piNADg3W3F2OTWoHGgKOQ3oX8/bxwumBgNu5NTE3y8i6viFcZAgfMnRuOzv8xAclj3VhS9YVQ4t4Es7MUmvaLFJDZ2FDbMh7wEf7uiuNGAz3eX9rvhZhZf8DCeT7DfuyQVCqkEB8taPSrEOypBXI3RB6InCD8ndtETRLCUqtGau/VVLxX63PQhiaWQSRDqy32mOi/Jp8PlrnNQozWLlhg9KUEAiJYQwvFfPSMOALD2WLXXYMr+khY4+Ya+QgBPJpXgmfO55p7vbi3Cn7yPd3dKkNGRfpAw3HcmJDa9oTfbsJpXgf79vHH4+lZPBZSgBBEONaZDUFHYWPfUF2RbfgPuWnUYDieLS6fE4q6FnF+9VMKIAZUv95aDZbmeZ8L7ZVdrO50noYfTcOwH0lsumMTNR5tPNHR5fwlWWOdNiBYVvBuz66Btt0EqYcTK2wVpYZBJGMQHqzE2yjOw5a+SixX0HcccV0+QnoOl9y1NFSvL/VQyrEj3HhTpL9fNSsBDZ6Xhy1tm4uyMSEyOD8Ls5BDYnSw+2umqzm4zWXHnqsOw2J1YNDoMS8YISRDuWhHmtT/zGtCot2B/aYtHNbnQ5HV7QSNYlsXHuzgVyLgof9w2PxnPX5ghPvbiyTFiQlhQmTUbrZBKGPipZHA4WTFo3B++PVCBv6/NFtUqQlAqKtAH8cFqyKUMzDan2CtkOCCoM0dHeleBCCSFarDmrtlIDFGLNowr0iPFOccbCplEvOYBYFaSd6WDoLCb4qaKEJLv6zNr4XCy4noor1YPs82BWm076nRmSCUM0qO53oyCet4bZpsDPxzh/n79rATRmsqbvaPTyWJ3UROO88nveal9T4L0liumxeKKabH4+7lj+/S8JD4QanNwY/GMpBAuWTvJ5U6wII077om8AkBIIH22uxQTnt2Ie74+gj1FTThW2Ybz3tqFNzYXYu2xGtFqsSeEnl1zUkLEwGpZs7FfPaW6oslgwd/XZnuoiAUrNoCb87vrHeaO8Bpp/LWukEnESvpj/Wwc3xslyJ7iJpz9xg5RDeWNIxWtaDJY4K+SYfm4SHFez6vVue5RL0kQhmGQEKLpVfHm5DjX/dXRxaKvLB8XCZmEwYlaHV7ZlC/2vblzYUrPTyYAQJwL/zxRjw93lIjXT3VbO+5adcRjr1zKW2GF+io9CsWEJEh1Wzs+54sDlqdHdpnQZhgG/7gwA2enR+Lh5Wmd/n7r/GQE+MhR2GDwuM8Ioif6nAT57rvv8MADD+Bvf/sbjh49ivnz52PlypWoqOhe1qnVanHDDTdg6dKl/T5YYujQbnXgig/2IqtKiyC1HF/fNlOUHgPwUBoAnmqDU4H7Jnu49AMBuMFeSEp0VIEAQLDGFTQ8mabz57otJjyUIG4/X8UHWjpyDR9sEDyWAa7qSHju2RlRCOUX/9QYnegKd/VHq8mGO7483Cev3L5QrzOLScO+8LefjuO59bkezUs7IjSgHh3hJ9rH9Cag8Pz6XDy6JgvPrMvp8bFDFYeTRRUfTEwIUYuWJw16C2wOp0czz9ImoxgAD/CRQyaViEoQb5Xz3fFHbj0cThYZMf64Z/EosRLo9T8Kenhm3zDbHGKQOi3CDy9fNgHPXZCOa2fG46xxEZg3KhS3zfdujzQQCA0EhSSb1e5ERbPJa1W+4OE/OtJP9DAXFEq94Zl1OXh2fW6fmh66kykqQQIBcMl1we/7/W0uO6IWU8fG6FxAymh1dFvFtauwCWlP/YY1hzsHjapaTXh3W5EYgBUqS4WiAa3JBpb1VMoUdGMl5U0J0huEudvbWNMxOCwkD3uTBBGaowOcNc8z56fDVylDVWs7DntRTwiWKHNSPAN454yPxNnpkbA7WbEqtTsliEouFb3cc7vpCyLYZUUFqHDLvKRORScdq0E7JUH4QOLRitYuFSdf7ivHzZ8fhNHqwNxRIXjxkgyPIMrlU+OgkkuQV6fHtoJGDxsho9WBkibPRKLYFH2E9QNxZxxvH2K1O71aRVQ0m5BVpYWEAc7OiMTUhCCo5BLRtikpVCNWpiaFarD2nrn46taZXoNXQl+QjmOOUOnenR2WgFTC4M2rJ2FFegSePm/cgFfFyqUSLtHidl/cvZgLgH17oBJ5dTpoTTbc/+0xVLa0Iy7YB29c6eoXkRDMK0H4IOLWfJc3+uZc1/n9eGcpXvw1Dzd+egBnv7ETn+8uAwDcvywVDMPg0ikxuH5WAsL8lLjDLQA3ITYQT5/HWe5te2SRGJz7pUMz397Csixe2HACX+4rx05+TBAUL5EBKsikEjEJOpz6guTV9S4JAnAFcd/fOUcMvF0zo+fqc/fG5zO7sHt6YFkatj6yCOe7FZRF8XZYguLvqulxCPVVwO5kkVOjE1UgYyL9xDXL1/srupz3NuZwycjoABUWpIW5FcF5rpe+3FuGRa9uw7Uf74eT5daiwrEMBn4qOV6+bCLm9FFtkuzWFyDARy6e58unxkIpk2DuqBBRMTaJV70cr9ZiU04dnv8lFzqzHRuyanHNx/tx0Tu7PYpDemObZbG7msbPGRWK6ADOktXmYPutqvDGN/sr8OW+ctzz1RHYHU6wLIt1xzjVZlww970IKrPusNqdKOEDye7JhEl8giizsusERXe4K0EEVVVHPttdhrw6vdjv1RsbeaXl0rERUMgkYnL8RK1O7OGR2kNfmp6ID1HjyXPG4LkL0kXL0f7ibon1AW+B+NfFozr1vSG6ZhnfF2RPUTPe/LMQAFe84KeU4UBZC/6+Nltcw4lWWGGe6+gAH7nYu0Wwwrp4cvcJrjmjQvH+9VO9xvMCfFyJrP9sLiA1CNFr+pwEef3113HLLbfg1ltvxdixY/HGG28gLi4O7733XrfPu+OOO3DNNddg9uzZ/T5YYujwzYEKlDQaEe6nxA93zcHk+CCPv7snQRRuwa5ThXtPkI4b7qHOQ2el4bKpsbhkSuckSKDarSeItv9JkJhAHzyyPA3XzYoXfYEBIDXcD1IJg+RQDeZ3sDwQuGJaHIr+uRLnuEnKpRIGH1w/Dc9fmI4V6RFilW+rydbvymJiZLOTT4JcNyseIRoFcmt1+Nva4wP+Ps0GC1a8sQPnvrWzT6oLg8UuHuPBbirqhX4gM5KCEcWPNXqzvdsmvzaHU/Rp/+5QJbbkDU8v0zqdGVaHE3Ipg+hAH7HysUFnRk1bOxxOVrTPq2o1iWOWMB90tanviV+FxssZ3BgkeMQKzRgHiuJGA5ws11si1FcBlVyKG+ck4p8Xj8dHN0zDqltnihWLg4GrOboeTieLW744iAWvbMVF7+7BBl7SLyAEokdH+Il2FYfKe5cEYVlWtE9yV+/0Fr3ZJm7W3ef+2xekgGG4imlhs91i8EyC+Lr1s+runvnmQAWsdid+O+4ZEPxgezHmvbQVL/+ejzaTDX4qmajOEZRGVocT7TYH8twqM92rNN1hWVZMgiSF9m3TLSRf6rSdk/+CJZNgESWcrwo+idhdEkRIrkoY4P/OGQOVXIqVvHWAsIkU0Jlt+JGvHhasRQQYhsHzF6V7bPp7SvT0pjl6Tg0XjHFP1rjjXlkNdC5MGRflD6VMglaTzaNKVeCNzQX4+9psOFnOIumzm2Z0smoJUMtxEV848uB3x6A325EUqsEU3k6jY8BIUB6OZCUIwzC4kFcndqyQbNRbxCDG7JQQhPoqoZJLMcst6DumQ5A5Iyagy/M1vYsxp0HXOzssgXA/FT64fhoun+a9CGegmTcqFBkx/mi3OXD2Gzsx8flN2F7QCJVcgg+umyauuQFX358mgwXadptH9flmPnnMsqxYvS9hODsbQQWyfBwXQGIYBv+4KAMH/7asUyP3m+cl4f/OGYu4YLW4xt5T3OyhlqxqNWF9Zg3+9dsJ3PfN0S4TGA16izim7uGTIC47LO4edPUFMXo8t6rVhG8OVHQ7JveXgno9rv9kf6/s77p6PuC9ytwbYX5KrLtnLnY+trjLpIY7Y9wan89MCvb6GKmEQVKoZzV7x73YWeMi3ALWbTjKf97J8YE4Z3wUAtVyVLe1Y5tbMs0doXeG4JMvrJfclSC12nb8fV0OKlpM8FPKcM3MeLx//dQeP+PpwP1an54YLCYXUyP8sOOxxfjw+mni35NDfeGnlMFsc+Ker4+AZYGLJkXj2pnxopLn/InRohK4O1WEw8liZ2EjHl6dyTeNVyA13BcSCSMmZgYyCSgoSQsbDPj+cBUOl7eiqrUdGoUUr18xCQDXS6MnBXRpkxF2Jws/lUxUGQEQbdH60y+lzWT1uH4K6vRe1aTCerDjuPBLVg0ufnc3pr3wh6iGXpHOjWvCOuVwRZuYVOrtPdodty9IwY1ufSBOBveG6jGBPrh+9um1wRpupEX4IjbIB1aHE1ZeKfngslS8dc1kSPieXoINqXBPpYR3ToQJ1wrLcqrwruJNveWmOYkIVMtR2dLea5WVN6paTdiYU0dN1s8Q+tQN0Gq14vDhw3jiiSc8fr98+XLs2bOny+d99tlnKC4uxqpVq/DCCy/0+D4WiwUWi2sTqdNxmy+j1Qipdej65Z0pmG0OvLMtG05YceeiFEQEMDBaPSfKhBAZGIkFDieLED8VTLZTa3UT7OuEE9xiP8SP7XR8Q5mz0gNxVnogWFhgtHoGU9RKO5wwo8mohZM1wwkzgjTOfn2+v8zjNsfu302wL/DdHZMR4quA2d79d2bpEE9OjZAjNSIMJpsJChkLMGY4WaCqrbVXG2CT1S5+Z0arEWzfhqdTwnA4xuGAzeHEnpJqOGHHeRODsWRsAG767CDWHCnGY2cnduvz3Ff+uzUPLSZu05xVXY/06IAensGxKbcOZgd3DxypqO3yHuM+hxkT4lRgGAt8VXbozHYUNzaJdkYd2V/aDJ3Ftel6ZM0B/HzPPNEWY7iQV98EJ8yIClTDbDfB14e7P+r0bcirb4QTZqSEalCrNcNkdWB/WQ2cMCNArYLRaoRGaYMTZtTr27odw7KrtShsMOC8CVEwWuzYVVQFJ1gsHO0Ho9WIADULmdQKs8OJosamAfP5z65pgBNmJIf5nPI5DABighk4YUZ+fSPe25GD7YVccO1oZR3u+roOqeEa/O/mmQhUK3C8ph5OmJEULkN6jAJOmJFdY0adrq3H+6lG2442M3c9Vra29nk+OVDOXQfRASqoFHYYrVzgLNwfOGtcIH7PqcPrfxzH9MQg/jjt8FHaxPeRyayw2p2o17dBJu383TmcLHYUVcEJGwobmzyOb83RYjhhxqS4AFwyORbLx0XCV+XgxmeWuy6sDieq2lqRX98IJ7iJK6emAUZr50rWBoMZeqsREgYI9u3b2iHIj1t3lLe2wGh1Bdtqte2o1rZBKmGwcHQ4NubUI6++ATMMajQYuOB8d+81Mc4H508KRka0P+KCpTBajTh7fCC+O1yE9VmleGRFgpgU+GBHEdrMBqSEaTAzWdPpNTVK4PGViXjix+OQSRiE9PAZUyJkcMKMrOoGGK3evfSPVnLX3qgIudfXYhggwp9FLR8QD9Q4Oj1ubLQCRyrasKe4GuH+rgIQs82Bt7dmwwkW9y0ZhTsXpsDmbIfNS/zokqmh+PpgIVpM3Bx99cwkVDSbcKjCjEPlNTh7vKtYp6ylBU6YEeLXv/XTcGFZegBe+cOMnUVVyK1NQkG9Hr9l12HziXrRlua8icHiOZiRrMGWfC74mhQm7fW5SY9Reh1z6vRaOGGDr499yJ7nh5cn4Nmfc9Cgt8BodUDCAM9dOAEJoZ6fXyYF/H0caGu34duDBdCaDdAopDBaHThYXovK1lZUt5pQ1NgMlVyCX++bjw3Ha7GnqAkPLEvu8xwS7g+kRcqRV6fHuswSXD4tDhuO1+LxH7I8kv1mhwn/4YOr7mTXNonr1e2FVbjdEIPWdm4t5K/m7sH4EAmcMON4TT3a2kOhNdvwwbZirD5UBavDiX2lMXjx4vH9OKtd8/bWbGwvrEGNtg1r757bJ7tilmWRW9cIJ+yIC5H06ZoK9kWvHp8Szo15MYGqPs0BgRqHeL4j/JRIDpNhTJQCm06YcbC8FrXadjhhxtgoJRysGRdOCsZne8rx/vZczEz2TKhUtBixq7gaDAOcOzEIRqsRCrkVTpjRbLKKx1Tc2AonzAj3U+C3+2dBrRCUlUPvXgv3h3h+JsWrPI7RVwUADo8977gYBfaWGGBxANMSgvDMBaOgkElw/7J41OnMSAnzRW6tFk6YcayyHnqzodO11GS04MZP9qOkyXXvLU8PF+/FhFApjteYkVvXiLmpJx+wB4DS5mbxc768MRPzUkPhhBlLxkZjXLQSo6PkOFGrx3eHC3H9rMQuXyezmptXU8IDPcaO1Ag5PyfXo61dD3kXfcq8caKujZv3NHLozQ7orU4Udlgz1+vMqNVx65LChkaP7+mFDUdRo3UpXcdE+mFaIrfOSArj7ptNueVwwoEQjdxjPTgUmJvqC4nEAruTxV+XpsLuNMNOrt19YkGaH1btb4VGIcWT5ybBZDNhRpIGN86NxCe7yvDl/gIsGO0v7gFjgzuP08nhMjhzuetoRUY4rI52nKwRxLL0AKw+WIXvjxRhUnzfi59ZlsWNn3EKszeunDTgdpzEqaO38x/D9iHdVVNTg5iYGOzevRtz5swRf//iiy/iiy++QH5+58akhYWFmDdvHnbu3Im0tDQ8++yzWLt2LY4dO9bl+zz77LN47rnnOv/hCQCntrUEQRAEQRAEQRAEQRAEQRAEQRBDDTOAf3OtOPz9vSvUgX42Ru/oB8uyrFePWIfDgWuuuQbPPfcc0tI6N7Ppiv/7v/+DVqsV/6us7Nk7kSAIgiAIgiAIgiAIgiAIgiAIwp0+ebmEhoZCKpWirq7O4/cNDQ2IiIjo9Hi9Xo9Dhw7h6NGj+Otf/woAcDq5JlEymQybNm3CkiVLOj1PqVRCqezcRK/m4ZpuMzpE/zFa7Dhc0YLyZhMumBCDALV3+4zVhyrxzM85CPNVYNODC7ttXLijsAH3fXMMfz93HC6dGjtYh94lf+TW42BZMx5bMQayPshFhzINejMWvrINEoZLRjqcLLY9uggRvfRbPpXc8vlB7Clpxr8vGe+1yXtHTFY7pr6wGQCwfFwE3rxq8mAfYp9xP8bDTy0TpedE37j24304UtGG5y5IxxW89/f1n+zHofJWvHb5RI9+M92xvbABd355RPz3+9dNwcI0zge/QW/G8v/sgMXuxOLRYdia34jFo8Pw7rU9+yXvK2nCXz4/hGC1HPNTw7AuswZ3LUzGfUs9k/nrjlXjiR+PY3pCEP53y0wAwDPrs7H6YJXXxwNAna4di1/dDgkD7HpsCYI0Cjy4+hh+z67D/UtH4c6Fo3r12YcCD3x3FBtz6vHEyjG4cXYiWJbF5H/8AYvdidGRfsiv0+Opc8eiSW/B+ztKxOfduSAZ9y9Lw4bjtXjk+0yP8+eO3eHE2W/uQHWbGXctTMbBslaxwfQv985FSpjLvuDVjXn4ZHcZrpsZj7+dO67Xn8Fsc0BnsSHct/MYuvLNHShrNuHTm6ZhdnLfmoAOFLd/eQg7C5sQ6CPHur/OFa0FzTYHFr+6DW3tNtw+Pwkf7ixFqK8COx/j1lTfHazEs+tzujy37gjXHwBEB6jw58OLOj0mt1aLS9/bCwC4anosnjk/Q/zb0te2oUZrxmc3TcMsL+fJZLWjtMmIsZH+Xq1PLnt/D3JqdHjvuslYlNZ5LXnjp/txoMzlH//21ZOxbGwEtubX4+6vjmJ0pB/W3j3X62e77pN9OFzehjGRfsir02PZ2HBsPsF5sO95fEknC7rX/8jHRztLcfX0ODx9frrX1+yKHYUNuOPLI0iL8MW6e+aJv7/0/d3IrdHjtcsnIiVcg4ve2QN/lQx3LUrBS7/n4+z0SPznykl9ei8AaDVacfuqQ8iu1kEuZSCXSmCyOvDq5RM9vK9PBpZlMfelLWg12bD69lkYzze+Fzhe3YYrPtiHQB859jyxxGtBFACsOVyJv6/LQXq0P9bcOafT3+v1Zizi1zb7n1wm+r4//XM2vj9UhdvmJ+Ghs0b36pjNNgeUMgkYhoHTyWLWv/+E3mzHmjtnIz06AMcqW3H1R/sR5a/ElkcW9+2EDENYlsWu4ibEBvogKbTnRrU6sw0WuxNhvj03M3dn1b4y/PPXPHGeFc5zV2PKcOStLYV4b1sxAIhzeFWrCVd8uE98TIhGgW2PLBqwfccl7+0Wez75KWX46Z45iAnk7Gue/Ok4fjpajetnxePJczznvdv+dwi7ipoQ4COHtp3rl6Q32zF3VCg+vsHVf4FlWVgdTphtTtidTgSrFWAYBl/tL8cLG04gLcIXa++e2+W97f46t/3vEHYXc57s6dH+WHXLTI994me7S/HyxnxMjAtAcYMRBosd/716MpaO7TzuA5yd0aJXtsHhZPHq5RNRq23Ha5sKsDIjUuyvMJQ4WNqMokYjrpoeJ56vc97cgVK+19GC1FB84Nb7otVoxYo3d0BvtuOlS8fjgokx+PV4LR7+PhPBajm2PrJY7CMFAPNe2oJmoxU/3sU1e3/rzwK8t72k05x8JvHy7yfw2Z5yXDk9Fs+6nQNhPEoI9sGG+xZA6mXtUVCvx4Xv7IafUob9Ty7t8RoX1lUA8PwF6Z16FxU36nHe267Xu/aT/Tha0dZpXSrct+eOj8Krl0/0+l4r3tiOipZ2fP6X6ZiZ5NnL5o3N+fhgRykumRKD1HBfvPQ758Ry2dQY/OPCru3rnvghC+sya/DgWamQMIzXe0nYuwu8ctkEnDchGt8cqMDzv+RifmqoR/8Wd675eB+OVrQBAJ45fxyumh7f5bEQI4+v95fjHxtOIESjQLPRCpVcgsN/O8vrul9vtkEulXQbR+wrwj5wRXoE3riy9zGkGm07znp9O5wskBquQWGDEbfOS8LDyz3XnNsK6nHXqqMAgAeWpeKOBSkDduzEwKHT6RD97+geH9enCJ5CocDUqVPxxx9/4OKLLxZ//8cff+DCCy/s9Hh/f38cP+7Z6Pbdd9/Fli1bsGbNGiQlJfXl7aFRaKBRdN/EkegbJ2p1ePbnHBwub4Wd95j9dn8DPr5xWic/e4eTxWe7aiGBCnctHIsQTfcJqZXpSTjxXMJpS0BcNCkZF01KPi3vPVjEBPhAAhXAcg2l5BIGCUHBXhd3p5tI/wBIYITBLO3VfasztXOfDYDWJBmS9zoDu3iMGoWGkiD9QG+24XiVBRKosGxMPDQKbjMfFRAICdqhb+/d9QIAPx1uhgQqcZP/5h+VWDEuERIG+GhHCWx2BabFB+LOBWOwPX8fShrtvXrtnQVlkECFs8bGYkJcINZntiC3xtrpuVUtTkigwtioMPFvScEhkKAJzQbv1/DBEu6YJ8cFIjaI86ifkRCFTdltyKu1DcnrviuqWlhIoEJaWKh43JH+AahsaUdRvQ0SqJAaHooQtRUS1IjPi/QPhEahQbR/ICRQwWCWef3cG7JqUdsGhGr88eCyCZBJGHy5rxwShsGEGE+/1rSIMEhQh5o2tk/n8LYv9mFPcTOmJgThymlxOHdCFDRKGcw2h/j9ToiOgEZxehLNl01JQX6tDS9dOh5JIa6NsEYBXDMjDe9vL8YXe+oggQrpUa7vYemYODy/vhjHKs1ot8oQ2k1AU/iuAKDZwMBHpu60adGZDOJjVh9swmVTLJiRFIxmgwV1WkACFaYnRkOj6FxAoVEAYb5d9+IJ8vGDBFbY7cpO353JakdmpZn7HmIDkFWlRU0r9x0L19+YiLAuv/MQdQAkMKOQ/4wzE6ORX2tDdVs7qludiA3yfF5+Lfe4jOjwPt+LSSEhkECFZj0jPtdosaOwjps35qbEIFij4K9513slh4b0677XKDT44Y4leGRNJjZk1cLhANLCg3Dp5JQBXRNkRIdjd1EzHv+hACEaBUJ9lXjh4gyE+6lQ2siNZxNiQuGr7DrAfsGEZGzO1eKyqbFeP2tyiAZxgUGobmtHcb0Nc0Zx10sBf46mxkf1+hx1bK00KTYCu4uaUVRvx4xEDZr0bZBAhYSQ4GE13p4MZ4/rOfkh0N/WVJNiIyFBGYrquXlW366HBCpEBQSOmPOcFhYKCbgm81PjgxAbFITogEBE+gWgQc/1M7h4UhICfAamvwDA3Tv5tVyQ88WLJyEt3NVE9pyMRKw72owdBXq8cKHas69EswMSqHD19GR8uKMERjMggQzxgUG9+j6unJaK1zaWo6jejoJ6GybHBeKTXaXYXdSE16+Y1CmB/Ht2HfYWG6GSqqFRSnGixornfi7Gm1dNEo9rf4kREqhw4YRktJqseGdrMT7cUY3zJyR5DUBvyGwB61RCAuAf64uRHu0PCVQY34/x+VSwaLQGizrkaqfER6G8mbtmZiRGexy3RqHBPYvS8fLv+fjvn1XYU2TE+swaSKDCFdOSEaT2vI5CNP5oNRpgtcuhUWigNUkhgQoxAWfOWNaRGYkx+GJPPXKrXWt0h5PFqn31kECF2xekw1/lffwbF6WCjFHBaAGMFhki/Ltf5xW6rZUOl7fjpjme57xJz62TEoL94av0xXvXzMF3Bytx89wkj7XRbfPGYt3RZvyR0wb9eVJEBni+r8lqR3Urt76ZGBMBjcJz/TY9IRofoRZHy9uxPU8nHlNhXfd7nKpWbk07OjwMPgopJKhASYPrOSzLIreG25+lR/sjp0aHan69Vd7k6HFtND46HJkVXK8H7rjPzGvyTOXSKaPw0m9laDVy1+6oUH/4dXHvDUYLzEunjMJnu+uwPV8Pp1PR6/6iPx2uBFgV5qWE4IbZibhz1WH8fKwZT5zt45GEzqywiPfaO1uqsCgtDlPig7p6WeI04VD0rsFMn6PTDz30ED7++GN8+umnOHHiBB588EFUVFTgzjvvBMBZWd1www3ci0skyMjI8PgvPDwcKpUKGRkZ0GhocDwZfsmqwUOrj6FBb/b6d227DQ98exT/+CXXo4meQGG9Htd+vB/7S1tgd7KIDfJBhL8SZc0mXPzOHmzNa/B4/I6CRlS0mBDgI8c1M3uX3R8pCoyhgkImESskASDcTzkkEyAAxKBbs6F3XcdO1OrEnxsNlm4eSQxn9pW0wOFkkRCiRlywqxmfUHXa1Mvvvlbbjj9P1AMAPr1pGvxVMuTX6/HJrhLc/uVhfL2/AgDw4FlpSIvgFmGVLe0w9dCkj2VZ/JHLve7y9EhM4iufMyvb0LGFVmED10w61S1hHMVvZmq17V5ff2s+N64u4hUrADCBf4/jVdruP/RJwrIsLPauFwdWuxPPrMvGb8dre3wtp5NFaRP3+ZPDXHO5oFQQTlVCsBpJYZ5zfYgvt/oN5BWHLabOYwTLsvhwJ6ceuW5WAlRyKWRSCf4yNwk3zkns9PjEEO49Spt63xC02WDBHr5q9XB5Kx77IQsr39wJndmGkkYjnCwQ4CNHmF/fKqIHkosnx+LQU8u8VspeOzMeEgZig+OxUa7ChIQQDSbGBsDhZLEhq+vvs93qQJnbObM5WK/fR53Oc53xxA9ZyKnR4ul1XFVkcpgG/r3ccHREmNP05s735v7SFtgcLGICfbBkDHfPlDRy112ReP91HeAVrjHhekyL9BPHgwL++QI2hxOHeaXR9KTgPn+OSD6A0mqywWzj7rPMyjY4nCyiA1SIDvSBSi5FTCDXtHFHYSMAID64czP43uKjkOLtqybjobPSEB+sxnMXpA/4mmB2Mpd8K2824UhFGzbl1uP9bdy9mV3NjVnpMd0XxQRpFPjylpndqkKnJXKbyd3FTQC48Si/jquAz4juOonWE8L4mlXVBgCoauXG5rig/p93ojNjIrlroLqtHVqTDY383iT8NI6fA01iqOuaWTyaS0ZIJIzH+HzJlJ6Vz33h8mmxSIvwxW3zkzrdP/NTQ6GQSVDZ0i6uRwBODVXdxl3n18zg5gmBqMDeJfQDfOQ4bwJXTfnl3nI8+dNxvLDhBLbmN+KHI1UejzXbHHhhQy4A4PYFyXj32qmQSRj8nFmDD3gVqNnmwIHSFgDAgrQw3DIvGWqFFNnVOjy2Jsvr3L2JX4vJpQz0Zjv2lXDPT4sYuCTTYDMpLlD8eXJ8YKe/3zw3CZH+KlS3tWN9Jlcscv7EaNy3NLXTY4P4+azNZAMANPKJt9O5RjndTOLPaV6dHu18d+WNOXWobGlHkFqOy6Z07UShlEnF+be4w3rAG8er28Sf9xQ1wdkhtlLBK36E14wO9MGDZ6V1ctfIiAnAjMRg2J0sVu0r7/Q+h8pawbLcPjrESwGLcE2VN5vQarKJ++38ej1sDmeXx1/OH19CiBpjIrl7qKTJKO4LyppN0JntUMgkoiJfWG8Jc7HwPG+4r0FTh9E9SgwMwRoFFo127W1TulmbDwbp0f5ICdPAandiY059r55jtjnw7UGu7cINsxOxdGw4Qn2VaDJYxRiDwH5eIRUdoILDyeL+b49CZ7b1+3jtDie+PVCBHzvMpwCQW6NDTZv3OAIxMPS5jPnKK69Ec3Mznn/+edTW1iIjIwO//vorEhISAAC1tbWoqKgY8AMFuMy4rIcA1pmCzeHEC7/kok5nwcbsOtyzeBSunRUPOZ90aDPacOv/DiKXl1CbrHY8de5YsdKmvMmEGz7djxajFelR/njtiomID1Gj2WDFA98ew+GKVvzl84P49MZpmJXCbYD/t7cMAHDhpGjxNYlTT4BaBoOFO/ehvsoh+z0IGfhabc+BZwA4Vtkm/tyoMw/Jz+V+TEPx+IYDW/O4RcWspGCPcxjgw18vba7rxelk8b+95ZiRFIxx0Z5BtlX7yuFkgakJQRgb5Y/b5ifjtT8K8OKveQA4ldRDy0djagIXWAtWy9FisiG7WouMmK4Daidqdahua4dSxmBKfCBkUgZyKQOd2Y7cWh2SQl0B/YJ6bnyNC/IRjzlIzQX4q1s7X/dWuxO7CrkA36xk1+dPDlODARdoLm8yIsx/cDa093x1FMcqW7Hh3vkI1HQOWP+SVYMv9pbj6/0VWBPk021wuabNDLPNCSnDJTVcn9/1ugy4RbFK5il3VsulMFnt8OFl0C0GC4wWm0cl6OHyVmRWtkEuZXD51Nge7zch+VTZYoK23SrOhd2xkw9CJ4aocdHkGKzaV46KFhP+u6UQo/jPnhyqQbutd1Ulp5oQX27DsYUvWEgMUXucp7MzopBZpcWPR6pw+TTvgYDjVVo4We7+YBgGzUYrypqMUCs8v7PKFm7zfE5GJA6UtaCkyYhz39ol/v3yqXH9HhOF66DZYIXJakdRgwGBPgqE+inEYozZycGIDeKSB4UNBpisduTxm/K4YJ8u31vT4XMkBKuRFKrB1vxG5NZoPZ6XVaVFu80Bf5UMsYFdv2ZXyKUMFFIGVgeL8iYT4kJ8sJ8P+o2PCxBfLyFEjeq2djGQFe538vP4rfOTcOt8Tl090HPTjXMSMTk+EHqzHYX1Brz2RwFWH6zAXYuSkcUnbkeF+570+84dFYJ1x2rwR0497lk8Crk1OlgdTvgppQjxlff79cdEcvfy0Yo2zpqND+pEBgzd9dNwRC5jEBWgQq3WjKOVrWIQPkitGDHnOczNNnFWcoj4uZaMCcM3ByqQFu6LpFD1gH5eX6UMa+/h7P68ve7MpGDsLGzCr8drxTGyoF4PlgX8lFKE+SmQHh2A43zCMlTT++v+kikx+OFIFX46Wu3x+9+z6zyK4d7dWoyq1nZE+itx09wEqBUyPHnOWDz/Sy5e3ZiH2ckhaNCbYbE7Ee6nREygCgzD4I4FKfjP5gJ8f7gK3x+uwsqMSDx/YTo0ShnarQ7sLOTG/9cun4j/+/E4jHyQOyFYM2yuqdFuQePUCO/j5BMrR+PRNVmYkxKK+5aOEoPJHR8r7Kvq+T1SPV+cEKCSDZvzMdAE+sgQ6qtAk8GKQ+UtmBIfiHd5y7qrZsSDBdvtuUkK1aCs2YSn1mVjUVoYFqSFYYaXIgiL3YE8vlhPygDNRiuOVbZhTJTr+y1u5BJ5UYGqHr+Pa2bG4UBZC77aX46b5yV62AK9u60IALB8XLjX1/FVyRDhr0S9jkuCPXnOGPx9bTaMVgdyarRek4TadhtajFyBS5ifEhqFFH5KKfQWB3KqdRgT5YcDpVyQd0ykHxL5RE5hvQFGiw0narnxo7t7T0iQxAX7QC5lzthr8kzm3AmR2MwnD+K7WZsPFueMj8LbW4rw45EqnDM+ssfHrz1ajRajFVEBKsxJCYbN4cTFk6Px0c5SrNpfgYV8sYPebBPXu+9fPxV3rjqMypZ2XPn+XvxlXiKWj4v0UI30RE61Dk+vy8YJfh/TbnPg4slckcPqg1Wi7d6U+ECcOz4K54yP6rJVAeFJb685hu1Y2joE0el0CAgIQNwDqyFRUuUWQRAEQRAEQRAEQRAEQRAEQZzJOC0mVL5xBbRabbe9xMmriCAIgiAIgiAIgiAIgiAIgiCIEcmwUoLUNjZ3m9E5k9Gbbdhe0IhdBU3YVdQEtVKGD6+fJvrXvrIxH5/tLgMARPgrcdnUWFw7I8GrJYrAF3vK8dLveQjRKCBhgEaDFa9dMQErM6JOxUciuuDxNVlYz3u8P3RWmmiBMdTIqdbh8g/2ItxPgW2PLu72sXqzDTNf3OLxu69unYHJQ6zhlMlqx7QX/gQAHHpqKTVG7yNmmwNT/rEZALD3iSUe0s7cGh0ue38vwnwV2P4Yd728/HsePt/j8st9/YqJALh7wOZkcev8JDx0Vlqv3vvbA5V4/pdczE8NxQfXT/X6mD9y63H/t8cQrJZjyyOLRGnrL1k1eGzNcWTEBGD1HbMAABuO1+LR77MwKS4QX9820+N15r+0Bc1GG9bcORvPrMtBTq0Oob4KRAf6IDpQhXuXpHrYagHANwcq8Y9fcjF3VCg+usHz+NZn1uDxH44jzFcBiYRBvc6CSH8ltjyyqFefHQD2FTfj5i8OAQAunBiNf1063uPvZU0mnPPWTsglDB5fOQYvbDgBCQO4Wx6PifDDj/fMAQC88Esuvj5QiZvnJeKR5a5OoD8crsLf+T4Rl0+NwXMXZgAAnliThZ/5cevo08ug5C2ylry6DXU6C767fRbGx3I2Zccq23DNR/vhp5Riz/8t7XWPgwe/O4aNOfV4bMVo3DQ3sdvHthltmPMSN+bsfGyx2KfkcHkrrv/kgPi4j26YirmjQnv1/kORH49U46m12UgJ0+Dnv85Fm8mO7QUNWDwmHAE+clz/yQEcLm/FixdnILOyDd8dqsJdC5Nxbwc/8nPf2onSJpOHReZA8emuUry6qQArMiKwr7gZ2nY7Lp8ag1+yatFucyI9yh/f3zUbgOt6uWdxCt7ZWoykUDU23De/y9f+LbsWD6/OAgBcNT0WT5+f7jGO73psMYJ9FXA6Wcz59xbozHZ8e/ssTIjtXw+KR1Zn4tfsOjy6fDQunx6LGf/0fB8A2FnQiDtWHQEAxASp8MeDC/v1XqcLvdmGxa9sg8nGeY9PjgvEVx3GwP7y0Y5S/GdzARakhqLVZMPxai1euXwCzh1/cutOYWyQMsCy9AhcPzMBUxKG1vpiJLAxpw4PfpeJjGh/OJwsTtTp8d61k7HQzSecGHgufXcPTtTp8fwF6bhsWqy4T7h/aSruWJgMs82BFf/ZASfL4o+HFnpY7/SVNzcX4oMdJViREYHXL5+Ic9/ahbJmE54+bxyumhHX6fFrDlXh6Z9zxH/vfnwJgrzsPVmWxXUfH8DRyjZcNiUGf+Y1oNVkw6c3TcOs5IGdc4YrH+4owRubC3HRpGg8umIM5vJrmGNPn9UnK5aRxt7iZtzCr28B4K5FKbh3yag+vw7Lsrhr1RHsKGxCargvvrtjlniv/P2nbPxwtBq3L0jCyowoXPzuHqhkEux7cikUMglYlsXUf2yG2e7Er/fN9+gf1BVakw2LX90Gs92JKfGBuGtRCm7732EAwPp75yElrPe9c4W13vTEIHxx8wxx3wJwfdNWpEfiv1uLcNGkaLx4Cbf+F/ZFkf5K/OfKSbjx0wOwOlj8ct88JIdqcN7bu1DSaMTs5BDsLWnGiowI/OeKSX08qwRxamkxWHH2mztgsDjwwoUZuGSq9z5dwr7U2554y4kG/PWbowjwkWHrI4tw46cHcbxaixcvzsBFkz1fz+ZwYm9xM07U6pFXr8PGbM4O7NXLJ+Cc8VH46Wg1/vZTNgBuzb94dDjOTo8U16Bakw2XfbAH1a2cveGkuEB8etM0cexhWRb7SlrwxZ4y7OAttQUeP3sMbpyTcJJnbGSh0+kQFRbSoxJkWEXw1AoZBR27QK2Q4Ypp8bhiGufRyrKsh7/6388dhwmxAQhUK7AgNaxXQaVb5iXhu4MVKOMbaYX6KnD+hJgzeqE1FAjzc3kSxwerh+w9EcN7E7cYbfCRSz2ux45kV+s6/U7Xbh+ynw2g8ag/CP61PnIpIgNUHteE0CS9xWSDUiaFVMKggW/6GBvkg6rWdjy9Lkfsh7MiPQKPLB/d6828EGAvaTR2+b2tOcw1J7tyRjwC+d4eADAziduAF9TpIZUwUMqkqOTHxTGRfp1eLyZIjWajFusza5BTq4OPXIpNDy5EsEaBrpjONwXOqdF2ul+q27iF0bJxEXjynLGY8Nwm1OksMFkdYkPEnqjXuxrOlzV3PgeHK7iG0FMTg3DLvCTsLGzC9gKuZ8ZV0+Pw7cFKFDUaxM9f0cL5vY+J8Pd4rVi3ZsPJYa5zMyrCD0AtfJUyBKldxxysUXKfxeYQH3uEb049Z1So6IHdG0aF+2JjTj2q29p7vDd38gvJUeG+4rUHAPNTw7BsbDg2n+C8yMfHBA7r+/yCSdF4/pdcFDca8crGAvxwuAp6ix1T4gPx7e2zUcj3tZkYF4hmA+cX3Wy0dvrMjXrub4mhmgE/H8Ea7nrYWdAEk9WBCH8l/n3pRNy3NA2f7S7DuROiXNdRuB/qdBZsyeOuzbSIzvefOxF+PuLP6fx3qVbIEB+sRkWLCZWt7YgNViOvTged2Q61QoqpCUG96injjVhxHLOKTVIj/VXi7wFgnFuT78SQgT+fg41aIcPl0+LwxV4uQT0xbuDukZXjI/GfzQXYV9oCYQSclhB80q//j4sysDIjCnNGhSDcr3eNoYm+MymOm8cKGwzwVXLfWVzw8LvGhxvnT4rGid/z8dOxatwwJxHlfA+nsVF+4pi3/t75YMGK421/OTsjEh/sKMHuwmYcKm9DWbMJGoUUV0yP8/o9Xz87Ab9l12FvSTPGxwSIewNvPHnuWFz+/l6sOcL1IAnwkWNBahhk/RyPRxoR/tzYZbDYobdwPaWC1HKP9eqZyIykYDAMwLLAZVNj8diK0d3uObvjtSsmYeWbO1DYYMBbfxbh2QvSAUD07p8SH4SJsYFiH5L8Oj1mJoegUW+B2e4Ew3Dryt7EStQKGd65dgoe+PYYjlS0iQmQc8ZHYnw3vQu9MZlvEJ9fp4ePXIpt+Y3i3wobDGg1cf16R4X7ivfpRZNj8MmuUlS3teOaj/fzfYRkGBfpD4mEQWq4L0oajThQxvU2y4gKoLGcGPKog2V4YFkaXthwAm/8WYALJ0d32ks2GSz4nW+efsv8pE7X9crxUYj5LQ/Vbe34+VgNcvl+QAvSwrzeA2dnROFsvkj8lY15eGdrMZ77ORcKmRTPrc8FANy7ZBQeOiut09ikVsjwwXXTcPVH+xDmq8QnN07rNE8vHRuBpWMj0M73xZJJGcgkTL/HuZGMvZdjFK0qRigdbwqJhMHFk2OxeHR4r6tqFTIJnlg5Vvz35dPiKAEyBHBvPCwsiIciQmW13clC227r9rHZfMNGdxoNFi+PJIYztXyj1KhAVacxKlijAMMADieLVhMXcK1u5R7/xMoxGB3hJyZAbpydgHevndqnasa0cK5hX3VbO/TmztdjebMROwubwDDANTPiPf4WH6xGkFoOq8OJnBpuIVTYwDXXHeWlebjQpPvLfVyQ8KoZcd0mQACueaZcyqDNZEMln2AQKG3imi0mhWrgp5IjmVeRHPdy33RFWbNR/LmwwYCOItDdfFJg3qhQMAyDVy+fiGtnxuPD66fiX5eMR5BaDruTRUEd97lL+ObCKeGelWphfq6FW0KIK/ArKF86ngfh3618w0YA2FPMNWfsqwIjKdS302cVaDVase5YNcx8k/N9Jdx7zPTSAPPRFWOgkEoQG+SDiEFqUn+q8FfJsYSvwv58Txn0/D10pKIND353DDqzHTIJg1Hhvojgr9s6nefYqzfbxHsvMmDg5xw/FbdgNfGL+4smx0AqYRAXrMbT54/DVLeK/WS+MvIEvyFJDe/cANSdQLf5coxbg9q0CO5aKWzgAhsH+QbmJ5MAAVxzcp3OLG6axkV7ViJFB/pAwb9HfPDw7HN3w5xE8eeOn+9kSA33RWyQD6x2Jyx2J3yVMiQMwDkK91PhoskxlAAZZBKC1VArpLDYnWjmx/Rwv+E9hg4HLpsaC5mEwdGKNuTW6FDCN2hODnOtTyIDVIgK6DoB0Vu4ALASBosdT/7IVZpfPCVGTHp1hGEYvHrFRJw7PgqPrBjt9TEC0xODsXSMSzW0ZEw4JUDcCPTh5rNWkw2NfGELjWlcw/i/nzsOt85Lwr8uGX9SgcEwPyVeuYxTnX++pwx7ippgtjlQwBeMjI8NhETCYE4Ktz7dXcStnSv4xGN0gE+fYiVLx0Zg3V/nimsSALh7Ud9VLKnh3B5CZ7ajuNEoJkGE5tBNfJFLQohrzR6sUWDDffOwfFwEhC3B+NgASPg4kTB+OHhJ+OjI7tdbBDFUuGF2IpJDNWgyWPHkT9nQmjz3/d8drITV4cSkuEBMiA3s9HyphMF1sziFxSsb8+FwsogN8vEo9OuKB5elYVpCEPQWO+775iisdifOGheBB5d1ToAIZMQEYM8TS7DxwQUI6aa40UchhY9CCrlUQgmQk4RWFkS3rEiPwLKxEQhSy8XBgDi9BLkFEaMGISA1UChlUvjzwS1h8dUV2TWdg7kNOkqCjDRqtJyiIdrLRlwulSCYr2YTNnfVfNIkMUSDN6+ehOmJQXj6vHF49oL0XidzBQLUcjEYU9hggMPJYt2xahwsawHLsvh6P1cltTAtzEMZAHCb+Nm8BdDPx2rE1wCA1IjOmwIh0OBkAbmUwW3zk3s8PqVMirFRXDAxq7rN42+lTdx7CUF+YcF2vKr3SRChKh3ggs3CdwFwG5w9xdxGTkg8hPkp8c+Lx2N5eiQYhkEGX5WWXaOFyWoXn58c6pkEcg94uQd4Z6eEIC7YB+dO8LS1EcazVn6BarY5cEhQgqT0NQnCvV9po2cSxGxz4JqP9+P+b4/h4e8zwbIs9pdwQW9vNhujI/3w6/3zsfqO2SNikXndrAQwDKdIePXyiaId3IbjnD1ZSpgvlDIpIvkAfr3btQEAdfy/A3zkg1IF6KvyfM1LJsd2+djkDjZyqRGdk5DuBPi4kiBpbgkT4b7N56s79/NJkBmJnZNifcH9HObyCdNxUZ5JAqmEEROE8cG9t7sYSqSE+eLyqbEI0SiwMC1swF6XYRiPIGh6tL8YkCGGPhIJ4xEokzDodkNPDAzhfiqsSOeCnW/9WQiDxQ4J41mIMFBIJAyWjeXuUWGNdu3M7veHMYE+eOfaKb0aKx49ezSEafescREnd7AjDEHx0WayiuvkMEoyAgBunpeEp84bd1JFDAKLx4Tj2plcMdRTa7ORWdkGu5NFiEaBaH7fPY9fKwv2NJV8EiQuuO+JxuQwX/x091zcszgFz54/Tlxv9wWFTCIWhXy4oxgmqwNRAdyaz31d3tGKN1CtwAfXT8XzF6YjJtAHV053WdqlhHmur8ZEkiU9MTxQyCR4+vxxADhL6UWvbsUXe8rQqLfA5nBiFV+k2J2V1JXTueJvI1+gJbhC9IRMKsGbV08W9x9pEb74z5WTelzL+qnkAzJ+Eb2DNG1EtzAMgw/5gAltRIcG7pXUg1GVO5CE+iqhM9vRZLB4rZgXyPFih9WopyTISENUgnRx3Yb5KdFs5DZ3SaEOMXkWG+SDQLUC398556TePy3CDw16Cwrr9fjpSLWo1BgfE4DKVm4D09Vm/qrp8fj1eB1+OFKFh5anoYxXZ6R6ua6jA12f75LJsYgO7N2maEJsALKqtMiq0uK8CdEAOGtDIagvbF7GxwTgp6PVyOpDEqTcLQkCAIX1esTwx5VdrYXObIefStalBD89OgA7C5uQXa0V+yUEqeUeSVmAC3gFaxSw2Bwem61QXyV2Prak0+sKyrYWI3e/Hy5vhdXuRIS/sk9+yIArSVSjNcNsc4hKoRc25IrKgQ1ZtRgfE4ATddy/ZyZ7D3p3N14NN+alhmL340sQrFGI5+SOhcn4YHsJAM4yBXDNJ3U6zyRILZ8EiRwk5aG/WxIkPdq/22rD5A6b8o6b9I7EBPpgRXoEwvyUHj2I0nn1wveHqjA7JQQH+CTIdC/KoL4QGcAFG+p0ZlgdXM8Mb0qJGUnBKGwwiBYWw5GXL5sAoLPy+GRZMjZCtNrqTzCIOL2MjfLH0Yo2ANx80NeCBaJ/XDMzHhuO1+L3nDoAnMWo0HtroFk6NgLfHqwEwKnnxkYNXHB0TKQ/njp3HHJrdFg6lnrJuCP0Umkz2US7WFJaDQ6PrxyDTbn1KGky4gle8ZQREyDOdwtHc9bixyrbUNSgF5Ug/VV3apQyPLpizEkdc3q0P3JrdfiBt5NbkR4JtUKG+5elij0J4r0kRhmGwQ2zE3HD7ESP37uvwdUKKWK7sbIjiKHGotHh+PKWGXh+fS4KGwx45uccPPNzDhRSCawOJ0I0CpzTTb+5YI0C50+Ixg9HOKvsWV3sF70RE+iDT2+ahjWHq3H3opQulZLE6YPSTUSPSCQMJUCGEEF8JVCAj/ykmhueCoR+BU3dWFu1Wx2iJYk7DXqzl0cTwxlBPRDVRVJAqGhr1FvECkONQupRzX0ypPHV329uLsSX+8rBMIBSJsHxai3aTDZEBaiweLT3SsV5o0IRH6yG3mzHO1uLYHey0CikXhM6ghJEwgB3Lkrp9fEJCo/Myjbxd416C4xWBySMa3MlJCGOd1CMdAXLsuIGbTR/Dop4JQsA7OLl/LOTQ7q0nsiI4YIc2V1YbQhIJQx+unsO1v11LjS9WPQJn+mXrFqYbQ7RWmBuSmifg6tBarkYUBcssTZk1WLVPk7lI6hQ/v1bHliWUxWcKVYS0YE+HvPFo8tHYwYf8J/Kqx8EKydtu020DQNcSpDBSrq7e/VeMqVrFQjgssMCAIbpOQkikTD44PppeOEiz6aHK9IjsSI9AlaHE3/9+iga9BYopBJMigvs+wdwQ7ieGnQW5PEqk45KEAB47oJ07Hxs8bBu+Mswg+NHPDMpGGoFd6321RedOP24B8QpQHvqmJ0cgkS3AGdH1dxAMm9UKJS85c91s+J7eHTfuWVeEl67YuKgJXGGK4E+vBKk3Saq5UkJMjj4q+R49nyuH4hgSSusvQFuvSSoFlftqzjpJMhAIBRcCPZVy9M5JdUV0+JwwcRo3Dw3Cf596LPnvsZPi/CjWBAx7JifGobf7p+Pf1yUgYQQNRgGYoHSTXMSe5xjbpjtKozs63p9akIw/nXJ+E7uEsTQgNJSBDHMSI/xR0KIGvNT+2YVczoQ+oI0d2OHlVeng5MFQjQK0UMaoJ4gI5FaLZfYiO5KCeKWNBP6gcQE+QxYoE3w3BWSMc+cNw7nT4zG1/srsCm3HncsTO4yCSCRMLh6Rjxe+j0Pn+0qA8CpBbwd25yUECSFarAiPbKT9Lw7JvJJkOxqLRxOFlIJgxJ+8xUXrBZ9hsdF+0PCcI3m63XmHnsDNRutMFjsYBhO5p9fr0dhvSsJIiYeuunBkcE3cz5RqxO9kbtSarh7DvfEldPj8NHOEpQ3m/DO1iKxH8icPvYDAbigbFKYLzIr21DWZITDyeKJH7IAAHctSsGjy0fDaLGLXskzh3EA+mSRSSX4/C/Tsa+kGfNTucSfv0oGH7kU7TYH6rRmJPLXrqAMGSz7RaEfkIRhcMHE6G4fGx3gA5VcArPNidggH/go+hckk0slePfaqXh+fY5bg++Aky4sEO5FYZPlq5R5DYrIpBLaGHWBSi7FvUtSsSWvHovHUCX4cGOsm5KLkiCnDmGN8q/f8gB4L1IYKHwUUvzz4vHIrdGJqlVi8BF6XDmcLEp4m1RKggwe54yPxOLRYdjKrxk7JuWvnZWATbn1+OFIFRL5de/pnNfTo13HF6SWi/aecqkEb109uc+vF+AjR6ivEk0Gi0dPNYIYTsikElw/KwHXz0qA1e5ErbYd2nabx/3SFRPjAvHESk6hRWv2kQUpQQhimOGvkmPbI4s6VbYORXqjBBGaO3e0DKGeICOP2rbeK0GqhCRIL62keoN7/467F6XgprlJCPFV4t6lqVh/77weN/OXT4uFXMqIAc5RXTRlDvFVYusji8SFU28ZFe4LtUIKo9UhKjUE263EEHdZukz0/u1NXxDBCivKXyUqOgT1VbvV1YOjuyRIfLAafkoZrHYnNuXUAxiYIIufSo7nLuCq7d7fXoysqjYAXCKpPyTxlbBv/lmEC/67G3qLHdMSgvDwWWmQSBi85uaPPK8fiZaRhFohw5IxEaIHLcMwXi2xagdZCRLqq8Rrl0/E+9dN7TGgI5Ew4r3QU1P0npBKGDx7QTr+ds5YqBVSXNqDCqU3KGQShLhZxI2NourJ/nDXohR8f+ecAVMBEqeOMR5KkDNDaTdUuGxqLBT8eN6TSm4g3uvp8wemBwPRO1RyKXz4RL1QyEJJkMGDYRg8f2EGfORSTinawb5y/qhQJIRwCnFhL3s6lSCCtSnAWdZ1VdTVF4RipzQv/Q8JYrihkEmQEKLBhNjAXlt13rkwBXcu7L2rAzE8oJULQQxDhkuzXkEJ0l1jdKEhrVAFL9BstIqSXmJkUNODEkRImjUaLKhu4wL3MQPoQTspLhCXTInBfUtG4dEVo/v8/FBfpdh8FOi5KXNfkUoYTE0IAgCxUbkgw++oKBnPy/KzqntOglS0cK8RH6IWA8eF9QawLIuNOXWw2p2ICfTptgeHRMKIicp8XgkyUHYbK9IjsXRMOGwOFk6W+6y97aPSEUG9cKJWB4eTxcqMSLx//VRxMxjiq8TqO2bjpUvHY2VGZHcvdUYiJIjq3ZIgdfx9O1g9QQDOBqu3TXBT+H4tA9G3hWEY3LYgGdnPrsBVMwbG1sVdmeXNCosgRjLu6qdwfwrQnkpCfJW4bUESIvyVWNiFtScxvBH6qAmWsZQEGVzigtVY99e5+O6OWZ2SuhIJg2s6rBtOZxLETyUX10UDtb69d0kqzpsQhQsnkeKLIIiRAyVBCIIYNHpSgrAsi/0lnP3NjA4NaR1OFi3GrpMnxPDCYLFDb7YD6GVPEFEJMnAbCqmEwetXTMJDy0f3O5F4zUzXhsdbU/STZU4Kp07YXcTdF4IdVnKHBIXYF4RXTnSHoARJDNEgMVQNqYSB3mJHvc6Cbw5w/TKumBbX4znp2KR4oOw2GIbBcxemixWO/VWBABCTSHHBPvjspul477qp4jgkkBiqwZXT46lC3wuC2qP+FCpB+sr1sxIwOzkEl009eeWGwEBeC+7nyVtTdIIY6Qi9dU5nQPBM5dEVY7D/yWUDqqIlhg4BaoXHv0ltNfikRfhhcnyQ17+5q680CimCNQqvjztV/OeKSXj50glYMkBWkvNSQ/Hfa6YgxJeSbQRBjByoJwhBEINGT0mQogYDmgxWKGUSjI91BYtCNHI0G21o0JupymmEIFST+6lk8O2iYbZ7EsTGW07FDqASZCCYnRyCyfGBKGownHQTZW/MGxWKlwDsL2mG3eHsWgkSIzRH14Jl2W4TGBV8EiQ+RA2lTIqEEDVKGo3YmFOH/aUtkDDAFdN7DigLVloAIJMwSAgZuABXbJAaL1yUgbe3FHokmvrK/NQwbH1kEaICVCfd3+FMRFB71GldY7arJ8jQuBdnJYdg1u1Dt5+LpxKEGnsTZx5PnjMW80aF4vweevwQBNE3BCWIAO2RTi8hvkqcMz4Sa4/VIC5YfdqdGsbHBohKcYIgCMI7lAQhCGLQCO2hMfo+XgUyLTEISpnU7XkqNBttaNRTX5CRQg3fDyS6m0CqmAQxWGC0cKqRgbTDGggYhsHXt86CzemEv2rg/erHRfsjwEcObbsNxyrbUN7sPQkyNsofMgmDJoMVtVpzt/ZRZfxrJAQLvRR8UdJoxBubCwAAi0eH9yrAneHWRC4+WD3gXuCXTo3FpQNQ3d+XZvSEJ0IAX1CCmG0OtJlsAIaOEmSoIySSpBJmwC3zCGI4EBmgwhXT4073YRDEiCPITQmilEngr6JQzunmzkUp2FHYhHPHR53uQyEIgiB6AdlhEQQxaLgrQZxe+nvs5ZMgs5I8q3pD+WB4AyVBRgy1vBIkKrDrQGoYf720mWxi9XnsELR08FFIByUBAnCB09nJ3P2w+lAlbA4WCpmkU/JIJZeKjQqzemiOXtHCKUEE5YbQF6SVD25f3cteCMlhvlDJJfzPlGgYiXRsjF7HW2H5yKUUbOklkQHcODYqzJfUSARBEMSAEeCmBAnzU5525QEBjIn0x+GnluHepamn+1AIgiCIXkBJEIIgBo3IABU0CilMVgd+PFrt8TeWZbGvhGuKPqtDD4AwXkFCSpCRg6AE6U5xEOAjh1zKbeicLKCQSjr1czgTmJvK9QX5ObMGAJAUovHas0DoC/Lapnxc/eE+XP7+Hhwub/F4jMFiRxOvxIoXkiBu1ekR/kos6mUDVamEERs9D1Q/EGJoESHaYXH3q9APJCpARcGWXrJodDgmxwfilnlJp/tQCIIgiBGEux1WOFlhDRlofUQQBDF8oCQIQRCDhkouFStj/vXrCWjbbeLfCuoNaDFaoZJLMDE20ON5oW69IYiRgaAEie7GUkciYTySHtGBqjOyefVcPilotnF9URJDvffeEJqAFzYYsLekGQfLWvG3n7I9VFdCP5BgjUJUrwhKEAC4clocZH2wtTp/YjQYBlg2NqIPn4gYLghKkAa9GU4nizpdu8fviZ6J8Ffhp7vnkh0QQRAEMaC422FRPxCCIAiC6DuUBCEIYlC5eW4SUsI0aDZa8fqmfPH3Yj+QhGAoZJ5DkWCLREmQkYNQUd5TMNV9UzfU+oGcKpJCNR7JoqRQ76qLiybH4OXLJuAfF2XgP1dOhJ9Shrw6PX7NrhUfI/QUiQ92JVKSwzTwVcogkzB9DtTeNCcRxf88BzOSgvv0PGJ4EO6nBMMANgeLFpO11/ctQRAEQRCDSyAlQQiCIAjipKAkCEEQg4pCJsHzF2YAAL7cV47saq5/gZAEmZXcOZga6sct8hv05lN0lMRgU9PGK0F66PER5qYEiRmC/UBOBQzDYM6oUPHfyV00+pZLJbhiWhyun5WAiyfH4tb5yQCA//xRAAevBinv0A8E4BRaX906E9/dMRuxQd5VJt0d25mozjlTkEslCNFw9+CR8lbUC0kQf0qCEARBEMTpJNDH3Q6L5mWCIAiC6CuUBCEIYtCZOyoU5/1/e/ceZWdd34v/sy9zyXVC7glJIGi4GYKaKARF8EI8EaW2/R0p9iCuA62cIMdI/bVy+K1qqT/i6mopehSUqqX8erisnuoRbUTTWjEUrBCIIlBFCUxCJgkJ5EIuM7Mvvz/2fvbckpAJSXbmeV6vtWY58+xnT77PIN8Vvu/5fD4LZkSlGnHV3z0af/PjZxshyOJB80AiIqaMTVqyqARJg2q1OmC2wMEMqASZMLwD+jR52+v7/r2Ye4hDyP/r20+OCaNb4jcv7o5vr63N4Hm+3g7rpIkDf5Znz57QaKcF/S2dPz0iIv7v//3zeKxze0S8+r+3AMDRdcKYgYPRAYDhEYIAx8T/c/GZMbOjPTbt3Bf/78qn4+U9vTGqpRBnnThhyL3aYR2ftr3SHVtfGf4/k517S7GnpxwRBx+MHqEdVuJtr6tVguRyB64EGWxce0v84Ttq1SA3r/pVXHv34/GtxzdERMScSYf2PeCGi8+Is2dPiB17e+OJeuXe9Ff59xYAOLr6t8MyGB0Ahk8IAhwT0zva44efujBW/M5ZMW9qbcbBe86cNmQeSERfO6w9PeV4pbt0TNfJ/nWXynHxFx+M931hdewe5j+TjfWh6CeMbolRrYWD3ts/BJmV4RBk6vj2+Mv/fHZ8/nfOikljD/0/dK9YfHJMGtMaG17eG9/52cbY11uJeVPHxjtOnfzqb4aotUv7m8sXxrTxff+/UwkCAM3Vvx2WShAAGL5isxcAZEd7SyEue+uc+L23zI7fvPjKAedDjGkrxpjWQuzuKceLu7pjbJutqtnWv7QnNu2stbT6l//YEpecPfOQ39tVD0FerQokwkyQ/v6vhbOG/Z4xbcX48w/Oj//5w1/H4lMmxW+9cWYsmNURuZw5Hhy6qePb4/bLF8WHvvpwRETMnpjd1nQAcDzoGNUSxXwuSpWqWV0AcBicLALHXC6Xi9dPHXfQe6aMa4vd2/bElp37Yu4htgPi6ElmS0RE3Ld247BCkI3ba+HJzAmv/h9sk+u/2ZbP1aqHGL73nTUj3nfWjGYvgxHu7NkT4p/++/mxr7ccHf1++xQAOPaKhXz8+Qfnx869vTFVCAIAwyYEAY5LU8e1x3Pb9sRmc0GOC8/1C0Ee+NWW2LGnNzpGH9rB6HAqQeZNHRtjWgtx6vRx0VLQsRGa6fX11oUAQPNd9tY5zV4CAIxYTpiA49Lr6odvD/9mW5NXQkTE89t2Nz7vLVfj+09tOuT3vvByPQQ5hEqQCaNb48E/eVfc/QfnDn+RAAAAADCIEAQ4Lr1/Qa2dz8onuqKnVGnyakgqQU6eVJsN8J2fbTyk91Uq1Xj42VqQ9YaZHYf0nhPGtEZ7y8EHqAMAAADAoRCCAMelc0+ZFFPGtcWOvb2x+pkXm72czOusV4L8twtfFxERD/1mW2x95dVblf1i447YvLM7xrQW4txTJh7VNQIAAADAYEIQ4LhUyOca1SD3HWLVAUdHb7kSG+otrS44dWosmNUR5Uo1vvdE16u+95+f2lx732lToq2ougMAAACAY0sIAhy3Ljl7ZkRE/ODJzbGnp9Tk1WTXxu17o1SpRntLPqaOa2v8c/n22oHh1E/XvRRn/un98ZUHftO4turpLRER8Z4zph27BQMAAABAnRAEOG69cfaEmDNxdOztLcc/1w/TOfaSeSBzJo6OfD4X718wMwr5XDz6/Mvxixd2NO77qx/8Mvb0lOPmVb+Kjdv3xoaX98TTXTsjn4t452lTm7V8AAAAADJMCAIct3K5XKPq4L61WmI1y/P1eSAnTRoTERHTO9obrcpu//GzERHxxIYd8e/rXoqIiJ5SJW7551/Fv9SDq0UnT4wTxrQe62UDAAAAgBAEOL5d8sZaCPLAr7bE9j09TV5NNj1frwQ5edLoxrU/fMcpERHxT090xfqX9sTfrK6FIWed2BEREf97zYa48+HnIiLiPWeoAgEAAACgOYQgwHHt1Gnj4nVTxkRvuRqPdb7c7OVk0uBKkIiIN8zsiLe/fnKUK9W4aeXT8U/1Iekrfues+E9vmB6VasRvXqy9zzwQAAAAAJpFCAIc914/dWxERKx/aW+TV5JNyUyQk/pVgkREfOyCWjXI936xKcqVaiw+ZVLMP7EjPvXe0yKfq91zypQxccqUscd0vQAAAACQEIIAx71ZJ9QO3ze8vKfJK8meSqUanS8l7bDGDHjt7a+fHGfOGN/4+g/eMTciaqHV7711TkREvP+sGcdopQAAAAAwlBAEOO7NPmFURKgEaYZNO/dFT6kSLYVczOhoH/BaLpdrVIPMmzo2Ljy1b/bHn13yhvjGRxfFNe96/TFdLwAAAAD0V2z2AgBezeyJ9UqQ7SpBjpZfvLAj7vppZ3x66ekxvr2lcf25+jyQ2SeMjmJhaG5+ydkzY1RLIc6cOT7ySQ+siGgp5ONdp5sFAgAAAEBzCUGA417SDkslyNHzZ995Mh557uU4bdq4uOK8kxvXn6/PA5kzaB5IIpfLxZI3TD8WSwQAAACAYdMOCzjuzaq3w9qxtzd27utt8mrSZ+e+3nisc3tERGzcMTBoSipBBs8DAQAAAICRQAgCHPfGtBVj4pjWiIjYoBrkiHvo11ujXKlGRMSWnd0DXuusV4KcdIBKEAAAAAA4nglBgBGhMRz9ZXNBjrQfP7O18fmWXfsGvPacEAQAAACAEUwIAowIyVyQDS+rBHktXt7dE9d/84n4+YbtERFRrVbjx796sfH65n6VINVqNTrr7bDmTNQOCwAAAICRRwgCjAizJtYrQV5SCfJafPeJrrj7p53x8bsej55SJdZt3T0gWNq8s68SZOfeUuzuKUdExIkTRh3ztQIAAADAa1Vs9gIADoVKkCNjT3cpIiI6X9oTd/+0M6rV2iyQBbM64ucbdsSufaXY01OK0a3FeGF77Wc9aUxrjGotNG3NAAAAAHC4VIIAI0IyE2SDmSCvSW+50vj8f/7wmbj/yU0REfG+s2bE6HrQkQxH31gPQWaqAgEAAABghBKCACNC/0qQpHqB4esp9YUgW1/piZ88+1JERLxj3pSYOq4tIvpaYm3ckYQg7cd4lQAAAABwZAhBgBFhVr0S5JXuUmzf09vk1YxcPeVagDR7Yl91x+SxbXHGjHExdXwt7Ni8q1YJ8sLLKkEAAAAAGNmEIMCI0N5SiCn1SgVzQQ5f0g7rffNnxPwTx0dExDvmTY5cLhfT6iHIlnolSDITxFB0AAAAAEYqIQgwYiRzQdabC3LYknZYbcV8/NV/fmNcvGBGXPOu10dExLTB7bCEIAAAAACMcEIQYMRI5oKsf0kIcriSSpCWQj5Omz4uvvzhN8frpoyNiGhUgmxuDEavhSHaYQEAAAAwUglBgBEjmWOhHdbh66mHIK3Fodv/1PF9lSC95Ups3iUEAQAAAGBkE4IAI0ajEkQ7rMOWtMNqKQzd/pNKkBd3dcemHfuiWq2FJZPHth7TNQIAAADAkSIEAUaM2fUQRCXI4Wu0w9pPJUhfO6x9A4ai53K5Y7dAAAAAADiChCDAiDHrhKQd1p6oVqtNXs3I1Fuu/dza9lMJMrU+GH13Tzme2bwrIiJmTmg/dosDAAAAgCNMCAKMGDMnjIpcLmJfbyW27Opu9nJGpL5KkKHVHWPaijGurRgREY93bo+IiJkd5oEAAAAAMHIJQYARo7WYjzOmj4+IiB/+x5Ymr2Zk6j7ITJCIvuHoj6/fHhGGogMAAAAwsglBgBHlkjfOjIiIb699ockrGZmSSpDWA4QgyVyQdVt3R0TEiScIQQAAAAAYuYQgwIjygbNrIci/r3spunYYkD5cBxuMHtEXgiROVAkCAAAAwAgmBAFGlBMnjIq3nHxCVKsR3/1ZV7OXM+L0lA5eCZIMR09ohwUAAADASCYEAUacS954YkRE3PezjU1eycjTW65GxMFmggysBJnR0b7f+wAAAABgJBCCACPOxWfNiGI+F0+8sCN+8+IrzV7OiNKoBDlgO6y+SpDJY9uivaVwTNYFAAAAAEeDEAQYcSaOaY3z502OiIj71qoGGY7GTJBCbr+v958JcuIEVSAAAAAAjGxCEGBEuuSNtQHp9z6yPn667qUmr2bk6CkffCbItHF9wYd5IAAAAACMdEIQYES66MzpMW18W2zauS8+9NWH4yPf+Gn8ctOuZi/ruNf7Ku2wpvZrhyUEAQAAAGCkE4IAI9LYtmJ8+5q3x4fPmRPFfC5+/KsX45q7Hmv2so57rzYYvb2lEB2jWiIi4kQhCAAAAAAjnBAEGLGmd7THTb99Vtx55VsjImL7nt4mr+j4Vq1WG+2wDhSCRERMr88FUQkCAAAAwEhXbPYCAF6rKWNrLZzKlUqTV3J8S6pAIg7cDisi4r+/e158/8lNccGpU47FsgAAAADgqDmsSpBbb7015s6dG+3t7bFw4cJYvXr1Ae998MEH421ve1tMmjQpRo0aFaeffnr89V//9WEvGGCwQj4XERGlSvVV7sy23nJfSHSgwegRERcvmBFfvOxNMaq1cCyWBQAAAABHzbArQe69995Yvnx53HrrrfG2t70tvvrVr8bSpUvjqaeeijlz5gy5f8yYMfHxj388FixYEGPGjIkHH3wwPvaxj8WYMWPiD//wD4/IQwDZVszXDvRLZSHIwfQPQVoKuSauBAAAAACOjWFXgtx8881x5ZVXxlVXXRVnnHFG3HLLLTF79uy47bbb9nv/m970prjsssviDW94Q5x88snxX/7Lf4n3vve9B60eARiOYv1Av6wS5KB6SrUQJJfrq54BAAAAgDQbVgjS09MTa9asiSVLlgy4vmTJknjooYcO6Xs8/vjj8dBDD8UFF1xwwHu6u7tj586dAz4ADqRYP9DvNRPkoJKh6K2FfORyQhAAAAAA0m9YIcjWrVujXC7HtGnTBlyfNm1abNq06aDvnTVrVrS1tcWiRYvimmuuiauuuuqA965YsSI6OjoaH7Nnzx7OMoGMKdbnW1SrERXVIAeUDEY/2DwQAAAAAEiTwzoJG/wbxNVq9VV/q3j16tXx6KOPxle+8pW45ZZb4u677z7gvddff33s2LGj8bF+/frDWSaQEf1bOxmOfmBJO6yWohAEAAAAgGwY1mD0yZMnR6FQGFL1sWXLliHVIYPNnTs3IiLOOuus2Lx5c3z2s5+Nyy67bL/3trW1RVtb23CWBmRYcUAIUonWw8t3U6+3XzssAAAAAMiCYZ2Etba2xsKFC2PVqlUDrq9atSrOO++8Q/4+1Wo1uru7h/NHAxxQMhg9QiXIwSQzQVqK5oEAAAAAkA3DqgSJiLjuuuvi8ssvj0WLFsXixYvj9ttvj87Ozrj66qsjotbK6oUXXog777wzIiK+/OUvx5w5c+L000+PiIgHH3ww/vIv/zKuvfbaI/gYQJYV8315brksBImohc23/PMzcfr0cbH0rBkR0a8dlkoQAAAAADJi2CHIpZdeGtu2bYsbb7wxurq6Yv78+bFy5co46aSTIiKiq6srOjs7G/dXKpW4/vrrY926dVEsFuN1r3tdfP7zn4+PfexjR+4pgEwr5HORy9UGo/dWKs1eznHhNy/uji/8yzMxfXx7IwTRDgsAAACArBl2CBIRsWzZsli2bNl+X7vjjjsGfH3ttdeq+gCOumI+F73lapS1w4qIiH295YiIeKW71LjWCEEMRgcAAAAgI5yEAalQqA9HL2mHFRHRCIOSMCQioqdUu6YdFgAAAABZ4SQMSIWW+lwQg9Frkp9DqVKNUr0CpDEYvWAwOgAAAADZIAQBUqFQP9gvmwkSETGgLdi++kD03lLSDqvQlDUBAAAAwLEmBAFSoVivBOnVDisiBoUg9ZZYfYPRVYIAAAAAkA1CECAVivmkEkQIErH/EKSvHZatHwAAAIBscBIGpEIyGD2pdsi6Ur+2YN31Nlg9jXZYtn4AAAAAssFJGJAKLQWVIP1Vqvtrh1W7phIEAAAAgKxwEgakQlIJUhKCREREqdw/BKkPRtcOCwAAAICMcRIGpEJysF8yGD0iBlaCdCczQUoGowMAAACQLUIQIBX6KkHMBIkYWBGzr5S0wzITBAAAAIBscRIGpEIxCUFUgkTEwNkoSTusHu2wAAAAAMgYJ2FAKhSTdlhmgkTE4BBkYDssIQgAAAAAWeEkDEiFpB1WWQgSEYPaYQ0ajK4dFgAAAABZ4SQMSIWimSADVPqFIN2NmSC1a60qQQAAAADICCdhQCo02mGZCRIR+68E6ZsJkmvKmgAAAADgWBOCAKlQ1A5rgIPNBGktFpqyJgAAAAA41oQgQCokIUivdlgRMSgEabTDUgkCAAAAQLYIQYBUKBZUgvTX/+fQbTA6AAAAABnlJAxIhUK+tp31mgkSEYNnggxsh9ViMDoAAAAAGeEkDEiFlsZMEO2wIiIq1f2EIPWAqFUIAgAAAEBGOAkDUqFQD0FK2mFFRESpX0VMd70CpDepBNEOCwAAAICMcBIGpEKxXt1Q0g4rIiLK+60EMRgdAAAAgGwRggCpUFQJMkD/tmD7Bg1Gb1MJAgAAAEBGOAkDUqHRDqtsJkjEoMHopVolSK/B6AAAAABkjJMwIBWSFk9llSAREVHpH4LUK0GSwehCEAAAAACywkkYkAqFfH0miBAkIgb+HLqTmSD1ipBW7bAAAAAAyAgnYUAqJJUg2mHVDKwEqbfDqleCtKoEAQAAACAjnIQBqVAwGH2AgTNBBg5G1w4LAAAAgKxwEgakQrExGF0IEjFwNkp3bzkqlWojGEmqZgAAAAAg7YQgQCoUC2aC9FceVAnS069NmJkgAAAAAGSFkzAgFZJKkHLFTJCIgSFIuVKNvT3lxtfaYQEAAACQFU7CgFRIQpBelSARMbQiZte+UuNzg9EBAAAAyAonYUAqFOoH+2UzQSIiolwd+HPYua83ImphUT5vJggAAAAA2SAEAVKhMRhdO6yIGBoGJSGIVlgAAAAAZInTMCAV+kIQlSARQytBknZYLQVVIAAAAABkhxAESIViIRmMLgSJGPpzSEKQ1mKhGcsBAAAAgKYQggCpUMjXtrPesnZYEfsbjF5rh9WqEgQAAACADBGCAKnQklcJ0l/lAJUgLUXbPgAAAADZ4TQMSIWCmSADDB4Qv8tgdAAAAAAyyGkYkArJ4X6pLASJiBiUgcTOvfWZIEIQAAAAADLEaRiQCipBBhpSCdJdrwTRDgsAAACADHEaBqRCMQlBDEaPiL7ZKMnPJZkJYjA6AAAAAFkiBAFSoVhv82Qwek25Wvs5jG4tRETEziQEUQkCAAAAQIY4DQNSQTusgZLZKGPaihFhMDoAAAAA2eQ0DEiFloJ2WP0lFTF9IUitEkQIAgAAAECWOA0DUkElyEBJO6zBlSDaYQEAAACQJU7DgFQo5mvbmRCkplEJUp8Jsq+3ViHTqhIEAAAAgAxxGgakQlE7rAEGt8NKJG3DAAAAACALhCBAKhTr7bDKKkEiYmglSMJMEAAAAACyxGkYkArF+uF+rxAkIvragg2uBDETBAAAAIAscRoGpIJKkIEqBwpBVIIAAAAAkCFOw4BUKPQLQapVQUhSCTJaOywAAAAAMsxpGJAKLfm+7SwJAF7a3RM3rXw6ntm8q1nLapqkEmSsdlgAAAAAZJjTMCAVCoVc4/OkJdZ3frYxbv/xs/E3q59t1rKa5kAzQVSCAAAAAJAlTsOAVEhmgkRE9JYrERHxSncpIiJ295SbsqZmKh+wHVZuf7cDAAAAQCoJQYBU6B+CJAFAd6kWhpTqoUiWlKv7b4fVph0WAAAAABniNAxIhUK/EKTUCEFqFSBJKJIV1Wq1XyWIdlgAAAAAZJfTMCAVcrlcoxqkVK4FAD31SpDecrZCkP6hz+BKECEIAAAAAFniNAxIjaQapFSphR9JCJJ8nRVJK6yIiNFtg2aCaIcFAAAAQIY4DQNSY3AlSN9MkOxWgowZ1A6rVSUIAAAAABniNAxIjWL9gD+ZCdJXCZLhEGRQJUhrMTf4dgAAAABILSEIkBpJJUh5cAhSzlg7rH4hSHtLIXL9cg8zQQAAAADIEqdhQGoUC7XT/t566NFTzmYlSP/nLeZz0V7sqwbRDgsAAACALHEaBqRGMV/b0pJKiO5SOSKyNxOkUn/+fC4il8tFe0vfVm8wOgAAAABZ4jQMSI1CMhi9Uq8EqbfD6q1kqx1WUgmShELtLSpBAAAAAMgmp2FAaiTtsJLKjyQEKWesHVbyvEko1Nav+qNVJQgAAAAAGeI0DEiNwYPRuxuD0bMdgvSvBDEYHQAAAIAsOazTsFtvvTXmzp0b7e3tsXDhwli9evUB7/3mN78ZF110UUyZMiXGjx8fixcvju9///uHvWCAA0naP/VWBlaCJIPSs6I0uBJkQAiSa8qaAAAAAKAZhh2C3HvvvbF8+fK44YYb4vHHH4/zzz8/li5dGp2dnfu9/8c//nFcdNFFsXLlylizZk28853vjA984APx+OOPv+bFA/SXtMMq12eAdGe0HValOqgSpH87LJUgAAAAAGTIsE/Dbr755rjyyivjqquuijPOOCNuueWWmD17dtx22237vf+WW26JP/7jP463vOUtMW/evLjpppti3rx58Z3vfOc1Lx6gv+TQvzeZCVLOaCVI+cDtsMwEAQAAACBLhnUa1tPTE2vWrIklS5YMuL5kyZJ46KGHDul7VCqV2LVrV0ycOPGA93R3d8fOnTsHfAC8mpZ6O6zGTJDeckT0tYfKiuT5i40QpG+rNxMEAAAAgCwZ1mnY1q1bo1wux7Rp0wZcnzZtWmzatOmQvsdf/dVfxe7du+NDH/rQAe9ZsWJFdHR0ND5mz549nGUCGZVUPiShR1IJkrkQpN4OK58zGB0AAACAbDus07BcbuBg3Wq1OuTa/tx9993x2c9+Nu69996YOnXqAe+7/vrrY8eOHY2P9evXH84ygYxJZoKU6uFHMhi9lLF2WMlMlOTn0V40GB0AAACAbCoO5+bJkydHoVAYUvWxZcuWIdUhg917771x5ZVXxj/8wz/Ee97znoPe29bWFm1tbcNZGkCj/VOpUo1SuRJJAUilGlGpVCOfz0YAkGQ+SWVMW70dVmshf0iBNQAAAACkxbAqQVpbW2PhwoWxatWqAddXrVoV55133gHfd/fdd8dHP/rRuOuuu+Liiy8+vJUCvIpCv5kg3aWB1R9ZaolVqleCFAa1w1IFAgAAAEDWDKsSJCLiuuuui8svvzwWLVoUixcvjttvvz06Ozvj6quvjohaK6sXXngh7rzzzoioBSAf+chH4gtf+EKce+65jSqSUaNGRUdHxxF8FCDrWvq1w+oZEoJUovXwOgCOOMlg9KQSpL1Ye+6WYjaeHwAAAAASww5BLr300ti2bVvceOON0dXVFfPnz4+VK1fGSSedFBERXV1d0dnZ2bj/q1/9apRKpbjmmmvimmuuaVy/4oor4o477njtTwBQ138wes+gOSC95exUggwOQdrqlSCthqIDAAAAkDHDDkEiIpYtWxbLli3b72uDg40f/ehHh/NHAAxbYyZIuRrdvQNDkHKG2mElz5r8PPraYQlBAAAAAMgWJ2JAahTrh/y1SpDygNdKgypD0qw0uB1WMhhdOywAAAAAMsaJGJAaSeVDuVIZMhi9N0OVIJUhM0G0wwIAAAAgm5yIAalRrA9G7y1XhwxGL2doJsjgSpC2lmQweq5pawIAAACAZhCCAKlRzNe2tHKlup9KkOy0w6pUB4YgJ04YFRER08e3N21NAAAAANAMhzUYHeB4lBz691YqQypBSlmqBCknIUgtFHrj7Alxzx+eG/Omjm3msgAAAADgmBOCAKmRtMMq76cdVilDlSDlejusZEZKLpeLc0+Z1MwlAQAAAEBTaIcFpEZy6F/aTzusLFWClOvtsPI5M0AAAAAAyDYhCJAayUyQUqUSPeXygNeyVAlSGlQJAgAAAABZJQQBUiM59C9X9tMOK0OVIJV6CFIoCEEAAAAAyDYhCJAayaF/735ngmQnBEmetaAdFgAAAAAZJwQBUqOl3g6rvJ+ZIL3l7LTDKtdbf2mHBQAAAEDWCUGA1CgcZDB6OUOVIEnekxeCAAAAAJBxQhAgNVrq7bBK5cqQdli9GZoJohIEAAAAAGqEIEBqFOrtsEqVavSUB88EyU47rMZMECEIAAAAABknBAFSI6l8KFeq0d2b3XZYFSEIAAAAAESEEARIkWK9HVZvuRI95fKA17LUDkslCAAAAADUCEGA1Cj0qwQZPBOkVM5OO6xytR6C5IQgAAAAAGSbEARIjZZCfSZIuRrdg0OQDLXDKterXgoFIQgAAAAA2SYEAVIjqQQpVSqZrgRJAp+idlgAAAAAZJwQBEiN4sHaYWWoEqSiHRYAAAAARIQQBEiRYr0dVm+5Gj31yo9iozokOyFI32B0WzwAAAAA2eaEDEiN/pUg3b21EGRMWzEistUOq5K0wzITBAAAAICME4IAqZHMBOmtVKK7HnqMbi3UrpWzVwmS1w4LAAAAgIwTggCp0VIYOhMkCUHKGWqHVTYYHQAAAAAiQggCpEgyA6NUrkZ3qRwRfe2weivZaYeVhCB5IQgAAAAAGVds9gIAjpS+IeiVyJVq15JKkFKG2mGpBAEAAACAGiEIkBrFfu2wqtX6YPTWYuNaVpTqVS8FIQgAAAAAGScEAVIjqXzoLVcjl6uFHqOTdljlLLXDqv2vEAQAAACArBOCAKlRrM8EKVeqjcqPMZlsh6USBAAAAAAihCBAihT6zQTprYceo+vtsEoZaoeV5D2FnBAEAAAAgGwTggCp0VKoVYL0lCqRZB5j2uqVIJUstcOqPWsyIwUAAAAAsirf7AUAHClJJUj/oo9GJUiG2mElz6odFgAAAABZJwQBUqO4n0P/LFaCVKr1EEQ7LAAAAAAyTggCpMbg9k/5XERbsbbNZaoSpKISBAAAAAAihCBAihTzA7e0tmKhca03Q4PRK/VnNRMEAAAAgKwTggCpMfjQv7WYb1wrZ6gdVlIJktcOCwAAAICME4IAqTF4BkZrMd9XCZKhdljlpBIkb4sHAAAAINuckAGpkc/nov8YjNZCXyVIqZydSpAkBJGBAAAAAJB1jsiAVCkW+ra1tpZ8FPNJOyyVIAAAAACQNU7IgFQp9isFqVWCZK8dVjITpJA3EwQAAACAbBOCAKnSPwRpK+ajpf51KUOD0ctCEAAAAACICCEIkDID2mEVC40goJTJdlhCEAAAAACyTQgCpEr/6ofWYl87rFKG2mGVq/XB6DkhCAAAAADZJgQBUqVlUAjSUqhXgpSz1w6rWBCCAAAAAJBtQhAgVQqFgYPRs9gOKwl8zAQBAAAAIOuEIECqFPP9ZoK05KMlaYeVoRAkedSCdlgAAAAAZJwQBEiV/sPAWwv5xte9GWqHVaqoBAEAAACACCEIkDJDBqPXK0PKWaoEqec9ZoIAAAAAkHVCECBVkvZXERFtxUIjCCiVsxOCNCpBtMMCAAAAIOOEIECqDKkEqYcgvZVstMOqVqt9M0G0wwIAAAAg44QgQKoUD9AOq1qNqGSgJVb/tl9CEAAAAACyTggCpEr/ORht/SpBIrJRDVISggAAAABAgxAESJWk8iOiFoK09Ps6C3NB+leC9P9ZAAAAAEAWOSEDUqV/5UdrMT+gGqKUhXZY1b5nlIEAAAAAkHWOyIBUGTATpJCPln6hSKmc/nZY5bJKEAAAAABIOCEDUqV/5UdbSz5yuVzjWuYqQYwEAQAAACDjhCBAqhQLfdtaa6EQEX3BSG8WKkHqQU8hn4tcTgoCAAAAQLYJQYBUGdAOq1jb4lrq18oZqAQp9QtBAAAAACDrhCBAqvSfg5GEIEl1SG85/SFIJQlBVIEAAAAAgBAESJf+lSBtSQjSmAmS/nZYSSVIUSUIAAAAAAhBgHQpFIa2wyrWr5UyUAlSrgc9/X8OAAAAAJBVQhAgVVr6zwQpJJUgtf8tZWAmSDL7XTssAAAAABCCAClT6DcTpL1lcCVIFtph1StBtMMCAAAAACEIkC4t/dthFQoR0X8mSPorQZKxJ0IQAAAAABCCACnT//A/mQnSUm+LlYWZICpBAAAAAKCPEARIleJ+QpAkEOitpL8dVrle7VIUggAAAACAEARIl2Khb1trK+YHXCtnoBIkCUHyQhAAAAAAOLwQ5NZbb425c+dGe3t7LFy4MFavXn3Ae7u6uuLDH/5wnHbaaZHP52P58uWHu1aAV7XfdliNmSAqQQAAAAAgS4Ydgtx7772xfPnyuOGGG+Lxxx+P888/P5YuXRqdnZ37vb+7uzumTJkSN9xwQ5x99tmvecEAB5Mc/udyfZ832mFloRKkWq8EyQlBAAAAAGDYIcjNN98cV155ZVx11VVxxhlnxC233BKzZ8+O2267bb/3n3zyyfGFL3whPvKRj0RHR8drXjDAwSStr9qK+cjVg4BkMHpSJZFmpaQSpCAEAQAAAIBhhSA9PT2xZs2aWLJkyYDrS5YsiYceeuiILaq7uzt27tw54APgUCTVH639ZoMkgUBvOQPtsOrVLoW8kU8AAAAAMKxTsq1bt0a5XI5p06YNuD5t2rTYtGnTEVvUihUroqOjo/Exe/bsI/a9gXRLAo/WYqHvWmMmSPorQZJ2WApBAAAAAOAwB6PnBvWar1arQ669Ftdff33s2LGj8bF+/foj9r2BdEsCj7Ziv0qQelVEJkKQxmB0lSAAAAAAUBzOzZMnT45CoTCk6mPLli1DqkNei7a2tmhrazti3w/IjqQN1IAQpF4WUcpAO6wk6EmGwQMAAABAlg3rV4VbW1tj4cKFsWrVqgHXV61aFeedd94RXRjA4WhptMPqXwmShCDprwSpCEEAAAAAoGFYlSAREdddd11cfvnlsWjRoli8eHHcfvvt0dnZGVdffXVE1FpZvfDCC3HnnXc23rN27dqIiHjllVfixRdfjLVr10Zra2uceeaZR+YpAOqSw/8BIUghO+2wVIIAAAAAQJ9hhyCXXnppbNu2LW688cbo6uqK+fPnx8qVK+Okk06KiIiurq7o7Owc8J43velNjc/XrFkTd911V5x00knx3HPPvbbVAwwyaUytld7ksX0t9Voy1A5LJQgAAAAA9Bl2CBIRsWzZsli2bNl+X7vjjjuGXKtW0//b18Dx4Zy5E+PLH35znD27o3EtCQR6VYIAAAAAQKYcVggCcLzK53Nx8YIZA64V68PSy5X0V4Ikz1gUggAAAADA8AajA4xEfe2w0l8JUq5XguSFIAAAAAAgBAHSr1CvBOnNQAiStMNSCQIAAAAAQhAgA5JKkCy0w6rUZzAVckIQAAAAABCCAKmXzAQxGB0AAAAAskUIAqResTETJP2VIOV6y6/kmQEAAAAgy4QgQOol8zFKGagEKdfbYeW1wwIAAAAAIQiQfsVCbasrZWAwetlgdAAAAABoEIIAqddXCZL+dlh9M0Fs7wAAAADglAxIvb6ZIOmvBKk0QpAmLwQAAAAAjgOOyYDUa6lXRWRhJohKEAAAAADo45QMSL1CvR1Wbzn97bDKKkEAAAAAoMExGZB6STuscgYqQcoqQQAAAACgwSkZkHot9bKILMwESdphJcPgAQAAACDLhCBA6jXaYVXS3w6rbzC6EAQAAAAAhCBA6rVkqB1WSQgCAAAAAA1CECD1ivX5GL0ZaIdVqdZDkJwQBAAAAACEIEDqJfMxSuX0t8NSCQIAAAAAfYQgQOoV64PRs9AOq1yfe1IsCEEAAAAAQAgCpF4SCGRhMHoS9OS1wwIAAAAAIQiQfn3tsLJQCVJ7xqJ2WAAAAAAgBAHSLxmMXspAOywzQQAAAACgjxAESL2WQnYGo5eFIAAAAADQIAQBUq+QwXZYQhAAAAAAEIIAGdBSyE47LCEIAAAAAPQRggCpV0zaYVWy0w7LYHQAAAAAEIIAGZBURfSWq1GtprsapG8wuu0dAAAAAJySAanX0i8QSHtHrEo1CUGavBAAAAAAOA44JgNSL2mHFRHRW053S6xk+LtKEAAAAAAQggAZUOwXCKR9OHqjEiRnJggAAAAACEGA1OtfCVIupzsE6ZsJIgQBAAAAACEIkHrFfoFAbyXd7bDK9RCkf/ADAAAAAFklBAFSL5fLNSojSimvBElCkLx2WAAAAAAgBAGyIakGKaWwEuSuf++Mz333qahUqn2VINphAQAAAEAUm70AgGOhpZCP7lIldZUg1Wo1/vy7T8Xe3nJcdOa0RshjJggAAAAAqAQBMqKQ0kqQl/f0xt7eckRE/HTdS1GuP54QBAAAAACEIEBGtBSSECRdlSAbt+9tfP7v616Kcj3k0Q4LAAAAALTDAjKimK9lvmlrh9W1Y1/j8zXPvxzJPPS8EAQAAAAAhCBANiTtoXrL6WqH1bWjrxIkaYsVoRIEAAAAACK0wwIyImmHVU5dO6x9+71uJggAAAAACEGAjCgWattdb+raYdUqQWZ0tA+4LgQBAAAAACEIkBFJe6hSJWXtsOqVIJe8ceaA60IQAAAAABCCABlRLCQhSLoqQTbWK0HeddrUGNfeN+apkBOCAAAAAIAQBMiEYr623ZVS1A6rUqnG5p21SpBZE0fHW06e2HgteV4AAAAAyDKnZEAmJIPRS+X0tMPa+kp39Jarkc9FTBvXFm+d2xeCFAoqQQAAAABACAJkQiGfvnZYG3fUqkCmjmuPYiEf5/QPQbTDAgAAAIAovvotACNfS6HeDitFg9G7ttfmgcyY0B4REfNP7IjTp4+L1mI+2ltk3AAAAAAgBAEyoVivBOlN0UyQpBJkZseoiKgFPd/7xPlRqUbkVIIAAAAAgBAEyIZCfVB4OUXtsBqVIB3tjWu5XC6MAwEAAACAGv1SgExI42D0rnolyIwJo5q8EgAAAAA4PglBgEwo1meCpKsdVq0SZGa/ShAAAAAAoI8QBMiEZCZIutphqQQBAAAAgIMRggCZ0BiMXklHO6xSuRJbdiWD0VWCAAAAAMD+CEGATEjaYZVS0g5r867uqFRrs04mj21r9nIAAAAA4LgkBAEyIakE6SmloxKka3ttHsi08e2Rrz8bAAAAADCQEATIhJMmjY6IiG//7IXY11tu8mpeu407klZY5oEAAAAAwIEIQYBMuOytc2La+LZY/9Le+Ma/rWv2cl6zpBJk5gTzQAAAAADgQIQgQCaMaSvGp5eeHhERX/rhr2PLzn1NXtFr01WvBJkxQSUIAAAAAByIEATIjN86+8R44+wJsaenHH/x/V82ezmvycakEqRDJQgAAAAAHIgQBMiMfD4Xn/nAmRER8b/XbIhfvLCjySvqs31PT1z1d4/EP67ZcEj3/+bFVyIiYoaZIAAAAABwQEIQIFPeNOeEeP+CGRER8b/+/fkmr6bP//r3zvjnp7fETSufjnKletB7n9q4M37z4u5oLeTjLSdPPEYrBAAAAICRRwgCZM6H3zonIiK++/Ou2NdbbvJqar7zs40REbFtd0888txLB733W4/XqkXefcbU6BjdctTXBgAAAAAjlRAEyJxzT5kUMzraY9e+UvzwP7Y0eznxzOZd8R+bdjW+vv8Xmw54b7lSjW+vrQUmv/2mE4/62gAAAABgJBOCAJmTz+fit95YCxC++dgLTV5NXxXIxDGtERHx/Sc3ReUALbEe+s3W2LKrOyaMbokLT5t6zNYIAAAAACOREATIpN95cy0E+dEvt8RLu3uato5qtRrf+XlXRER8+j+dHqNbC9G1Y1/8/ABD279VD23ev2BGtBZt4QAAAABwME7QgEw6ddq4mH/i+ChVqvHdn29s2jqe3Lgz1m3dHe0t+bh4wYx45+m16o79tcTa01OK+5+sXf/tN806pusEAAAAgJFICAJkVhIkNLMl1n31VljvPmNajGkrxtL50yMi4v5fdEWlUo07H34uLv7i6rjs9p/Ef/v7x2JPTzlOnjQ63jxnQtPWDAAAAAAjxWGFILfeemvMnTs32tvbY+HChbF69eqD3v/AAw/EwoULo729PU455ZT4yle+cliLBTiSLjl7ZhTyuVi7fnv8+Xefig0v74nuUjm+90RXfOz/ezQ+9JWH45q7Hos/+86TcfOqX8VXH3i28d59veX9fs+eUiXWbd0d217pjvIB5nokNm7f25gH8oEFMyMi4sLTpkZrMR/PbdsTv33bQ/Gn334ynty4Mx5+dls88KsXIyLig286MXK53JH4EQAAAABAqhWH+4Z77703li9fHrfeemu87W1vi69+9auxdOnSeOqpp2LOnDlD7l+3bl28733viz/4gz+Iv//7v49/+7d/i2XLlsWUKVPid3/3d4/IQwAcjinj2uJDi2bH3T/tjK8/uC7ueOi5GNNaiJ37Sq/63nNv+pc455RJccrkMTF5bFu0FPPx03UvxU+e3RZ7emoBSS4XMXVcW7x5zgmx6OSJMfuEUbFtd0+8uKs7Vj/zYjzy3MsRETGuvRgXnjYlIiLGthXjHfOmxD8/vTl+tn57tLfk45PvOTUmj22L51+qhTRXnX/K0fuhAAAAAECK5KrV6sF/VXmQc845J9785jfHbbfd1rh2xhlnxAc/+MFYsWLFkPv/5E/+JO677754+umnG9euvvrq+NnPfhYPP/zwIf2ZO3fujI6OjtixY0eMHz9+OMsFRog9PaU480+/HxERT9343hjdOuyM9rBUq9X40a9ejK+tfjb+7dfbIiJi2vi2+O03zYozZ46PF3d1x5Zd+2J3dyn2dJfim4+/+vyQtmI+ukuVV70vl4t4y8kT448uOjXOOWVS4/q//nJL/Nc7HomzZ02Imz90dpwyZezhPyAAAAAApNCh5gbDOmXs6emJNWvWxKc//ekB15csWRIPPfTQft/z8MMPx5IlSwZce+973xtf//rXo7e3N1paWoa8p7u7O7q7uwc8DMDRkMvl4p2nTY13njY1ntm8K7bv7Y03zzkhCvmh7ab29PSFIPd9/G3xsw07YvOOffHiru7Y1d0bC2ZNiHfMmxKnTx8XlWo1Xt7TG+u27o5Hn38pHln3Ury0pzcmj2mNSWNb49Rp4+LiBTNiRseoIX/OO0+bGmv/dEmMby9qewUAAAAAr8GwQpCtW7dGuVyOadOmDbg+bdq02LRp037fs2nTpv3eXyqVYuvWrTFjxowh71mxYkX82Z/92XCWBvCazZs27pDvff3UsbFg1oQDvp6PXEwZ1xZTxrXFW+dOjLhweGvpGDU0IAYAAAAAhuewBqMP/s3karV60N9W3t/9+7ueuP7662PHjh2Nj/Xr1x/OMgEAAAAAgAwbViXI5MmTo1AoDKn62LJly5Bqj8T06dP3e3+xWIxJkybt9z1tbW3R1tY2nKUBAAAAAAAMMKxKkNbW1li4cGGsWrVqwPVVq1bFeeedt9/3LF68eMj9P/jBD2LRokX7nQcCAAAAAABwJAy7HdZ1110XX/va1+Ib3/hGPP300/HJT34yOjs74+qrr46IWiurj3zkI437r7766nj++efjuuuui6effjq+8Y1vxNe//vX41Kc+deSeAgAAAAAAYJBhtcOKiLj00ktj27ZtceONN0ZXV1fMnz8/Vq5cGSeddFJERHR1dUVnZ2fj/rlz58bKlSvjk5/8ZHz5y1+OmTNnxhe/+MX43d/93SP3FAAAAAAAAIMMOwSJiFi2bFksW7Zsv6/dcccdQ65dcMEF8dhjjx3OHwUAAAAAAHBYht0OCwAAAAAAYCQQggAAAAAAAKkkBAEAAAAAAFJJCAIAAAAAAKSSEAQAAAAAAEglIQgAAAAAAJBKQhAAAAAAACCVhCAAAAAAAEAqFZu9gENRrVYjImLnzp1NXglwtOzpKUWle09E1P5dL7Uef9vTSFgjAAAAAGRBkhck+cGB5KqvdsdxYMOGDTF79uxmLwMAAAAAADiOrF+/PmbNmnXA10dECFKpVGLjxo0xbty4yOVyzV7OcWPnzp0xe/bsWL9+fYwfP77ZywEyxP4DNIO9B2gW+w/QLPYfoBlGyt5TrVZj165dMXPmzMjnDzz5Y0T0csnn8wdNcrJu/Pjxx/X/GYH0sv8AzWDvAZrF/gM0i/0HaIaRsPd0dHS86j0GowMAAAAAAKkkBAEAAAAAAFJJCDKCtbW1xWc+85loa2tr9lKAjLH/AM1g7wGaxf4DNIv9B2iGtO09I2IwOgAAAAAAwHCpBAEAAAAAAFJJCAIAAAAAAKSSEAQAAAAAAEglIQgAAAAAAJBKQhAAAAAAACCVhCAj2K233hpz586N9vb2WLhwYaxevbrZSwJGsB//+MfxgQ98IGbOnBm5XC7+z//5PwNer1ar8dnPfjZmzpwZo0aNigsvvDCefPLJAfd0d3fHtddeG5MnT44xY8bEJZdcEhs2bDiGTwGMNCtWrIi3vOUtMW7cuJg6dWp88IMfjF/+8pcD7rH/AEfDbbfdFgsWLIjx48fH+PHjY/HixfG9732v8bq9BzgWVqxYEblcLpYvX964Zv8BjobPfvazkcvlBnxMnz698Xqa9x4hyAh17733xvLly+OGG26Ixx9/PM4///xYunRpdHZ2NntpwAi1e/fuOPvss+NLX/rSfl//i7/4i7j55pvjS1/6UjzyyCMxffr0uOiii2LXrl2Ne5YvXx7f+ta34p577okHH3wwXnnllXj/+98f5XL5WD0GMMI88MADcc0118RPfvKTWLVqVZRKpViyZEns3r27cY/9BzgaZs2aFZ///Ofj0UcfjUcffTTe9a53xW/91m81/mPf3gMcbY888kjcfvvtsWDBggHX7T/A0fKGN7whurq6Gh9PPPFE47VU7z1VRqS3vvWt1auvvnrAtdNPP7366U9/ukkrAtIkIqrf+ta3Gl9XKpXq9OnTq5///Ocb1/bt21ft6OiofuUrX6lWq9Xq9u3bqy0tLdV77rmncc8LL7xQzefz1fvvv/+YrR0Y2bZs2VKNiOoDDzxQrVbtP8CxdcIJJ1S/9rWv2XuAo27Xrl3VefPmVVetWlW94IILqp/4xCeq1aq/+wBHz2c+85nq2Wefvd/X0r73qAQZgXp6emLNmjWxZMmSAdeXLFkSDz30UJNWBaTZunXrYtOmTQP2nba2trjgggsa+86aNWuit7d3wD0zZ86M+fPn25uAQ7Zjx46IiJg4cWJE2H+AY6NcLsc999wTu3fvjsWLF9t7gKPummuuiYsvvjje8573DLhu/wGOpmeeeSZmzpwZc+fOjd/7vd+LZ599NiLSv/cUm70Ahm/r1q1RLpdj2rRpA65PmzYtNm3a1KRVAWmW7C3723eef/75xj2tra1xwgknDLnH3gQcimq1Gtddd128/e1vj/nz50eE/Qc4up544olYvHhx7Nu3L8aOHRvf+ta34swzz2z8h7y9Bzga7rnnnnjsscfikUceGfKav/sAR8s555wTd955Z5x66qmxefPm+NznPhfnnXdePPnkk6nfe4QgI1gulxvwdbVaHXIN4Eg6nH3H3gQcqo9//OPx85//PB588MEhr9l/gKPhtNNOi7Vr18b27dvjH//xH+OKK66IBx54oPG6vQc40tavXx+f+MQn4gc/+EG0t7cf8D77D3CkLV26tPH5WWedFYsXL47Xve518Xd/93dx7rnnRkR69x7tsEagyZMnR6FQGJKwbdmyZUhaB3AkTJ8+PSLioPvO9OnTo6enJ15++eUD3gNwINdee23cd9998a//+q8xa9asxnX7D3A0tba2xutf//pYtGhRrFixIs4+++z4whe+YO8Bjpo1a9bEli1bYuHChVEsFqNYLMYDDzwQX/ziF6NYLDb2D/sPcLSNGTMmzjrrrHjmmWdS/3cfIcgI1NraGgsXLoxVq1YNuL5q1ao477zzmrQqIM3mzp0b06dPH7Dv9PT0xAMPPNDYdxYuXBgtLS0D7unq6opf/OIX9ibggKrVanz84x+Pb37zm/HDH/4w5s6dO+B1+w9wLFWr1eju7rb3AEfNu9/97njiiSdi7dq1jY9FixbF7//+78fatWvjlFNOsf8Ax0R3d3c8/fTTMWPGjNT/3Uc7rBHquuuui8svvzwWLVoUixcvjttvvz06Ozvj6quvbvbSgBHqlVdeiV//+teNr9etWxdr166NiRMnxpw5c2L58uVx0003xbx582LevHlx0003xejRo+PDH/5wRER0dHTElVdeGX/0R38UkyZNiokTJ8anPvWpOOuss4YM+wNIXHPNNXHXXXfFt7/97Rg3blzjN486Ojpi1KhRkcvl7D/AUfE//sf/iKVLl8bs2bNj165dcc8998SPfvSjuP/+++09wFEzbty4xuyzxJgxY2LSpEmN6/Yf4Gj41Kc+FR/4wAdizpw5sWXLlvjc5z4XO3fujCuuuCL1f/cRgoxQl156aWzbti1uvPHG6Orqivnz58fKlSvjpJNOavbSgBHq0UcfjXe+852Nr6+77rqIiLjiiivijjvuiD/+4z+OvXv3xrJly+Lll1+Oc845J37wgx/EuHHjGu/567/+6ygWi/GhD30o9u7dG+9+97vjjjvuiEKhcMyfBxgZbrvttoiIuPDCCwdc/9u//dv46Ec/GhFh/wGOis2bN8fll18eXV1d0dHREQsWLIj7778/Lrroooiw9wDNY/8BjoYNGzbEZZddFlu3bo0pU6bEueeeGz/5yU8a58lp3nty1Wq12uxFAAAAAAAAHGlmggAAAAAAAKkkBAEAAAAAAFJJCAIAAAAAAKSSEAQAAAAAAEglIQgAAAAAAJBKQhAAAAAAACCVhCAAAAAAAEAqCUEAAAAAAIBUEoIAAAAAAACpJAQBAAAAAABSSQgCAAAAAACk0v8P/bJeTI1Dh0wAAAAASUVORK5CYII=\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Topic = 16\n", + "ori_index = 1\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_mitf[\"prediction\"])\n", + "plt.axhline(y=model_dict[\"deepmel2\"].predict([onehot_,onehot_[:,::-1,::-1]])[0,Topic-1])\n", + "plt.axvline(x=77)\n", + "plt.axvline(x=63)\n", + "plt.axhline(y=res_mitf[\"prediction\"][63],color=\"green\")\n", + "plt.plot()\n", + "\n", + "\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][63:63+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_tfap[\"prediction\"])\n", + "plt.axhline(y=res_mitf[\"prediction\"][63],color=\"green\")\n", + "\n", + "plt.axvline(x=77)\n", + "plt.axvline(x=97)\n", + "plt.axhline(y=res_tfap[\"prediction\"][97],color=\"green\")" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Topic = 16\n", + "ori_index = 12\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_mitf[\"prediction\"])\n", + "plt.axhline(y=model_dict[\"deepmel2\"].predict([onehot_,onehot_[:,::-1,::-1]])[0,Topic-1])\n", + "plt.axvline(x=88)\n", + "plt.axvline(x=64)\n", + "plt.axhline(y=res_mitf[\"prediction\"][64],color=\"green\")\n", + "plt.plot()\n", + "\n", + "\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][64:64+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_tfap[\"prediction\"])\n", + "plt.axhline(y=res_mitf[\"prediction\"][64],color=\"green\")\n", + "\n", + "plt.axvline(x=88)\n", + "plt.axvline(x=111)\n", + "plt.axhline(y=res_tfap[\"prediction\"][111],color=\"green\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Topic = 16\n", + "ori_index = 17\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_mitf[\"prediction\"])\n", + "plt.axhline(y=model_dict[\"deepmel2\"].predict([onehot_,onehot_[:,::-1,::-1]])[0,Topic-1])\n", + "plt.axvline(x=372)\n", + "plt.axvline(x=406)\n", + "plt.axhline(y=res_mitf[\"prediction\"][406],color=\"green\")\n", + "plt.plot()\n", + "\n", + "\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][406:406+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_tfap[\"prediction\"])\n", + "plt.axhline(y=res_mitf[\"prediction\"][406],color=\"green\")\n", + "\n", + "plt.axvline(x=372)\n", + "plt.axvline(x=363)\n", + "plt.axhline(y=res_tfap[\"prediction\"][363],color=\"green\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Topic = 16\n", + "ori_index = 58\n", + "\n", + "onehot_ = np.copy(motif_embedding_dict[\"s\"][\"regions\"][ori_index:ori_index+1])\n", + "res_mitf = add_pattern_to_every(patterns_dict[\"mitf\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_mitf[\"prediction\"])\n", + "plt.axhline(y=model_dict[\"deepmel2\"].predict([onehot_,onehot_[:,::-1,::-1]])[0,Topic-1])\n", + "plt.axvline(x=388)\n", + "plt.axvline(x=411)\n", + "plt.axhline(y=res_mitf[\"prediction\"][411],color=\"green\")\n", + "plt.plot()\n", + "\n", + "\n", + "onehot_ = np.copy(res_mitf[\"tmp_array\"][411:411+1])\n", + "res_tfap = add_pattern_to_every(patterns_dict[\"tfap2\"], onehot_, model_dict[\"deepmel2\"], topic=16)\n", + "\n", + "plt.figure(figsize=(20,5))\n", + "plt.plot(res_tfap[\"prediction\"])\n", + "plt.axhline(y=res_mitf[\"prediction\"][411],color=\"green\")\n", + "\n", + "plt.axvline(x=388)\n", + "plt.axvline(x=378)\n", + "plt.axhline(y=res_tfap[\"prediction\"][378],color=\"green\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading and plotting luciferase results" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [], + "source": [ + "luciferase_dict = {\"ids\":[],\"values\":[]}\n", + "with open(\"data/motif_embedding/luciferase_ME_with_genomics.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " luciferase_dict[\"ids\"].append(sep[0])\n", + " luciferase_dict[\"values\"].append(sep[1:])\n", + "luciferase_dict[\"values\"] = np.array(luciferase_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5,5))\n", + "mean = np.mean(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "std = np.std(np.log2(luciferase_dict[\"values\"]),axis=1)\n", + "\n", + "index = np.argsort(mean)[::-1]\n", + "temp = sorted(mean)[::-1]\n", + "res = [temp.index(i) for i in mean]\n", + "\n", + "plt.bar(res[:4],mean[:4],color=\"navajowhite\",label=\"Motif Embedding (S,M,T)\",yerr=std[:4],capsize=3)\n", + "plt.bar(res[4:8],mean[4:8],color=\"orange\",label=\"Motif Embedding (S,M,T,S,M,T)\",yerr=std[4:8],capsize=3)\n", + "plt.bar(res[8:],mean[8:],color=\"red\",label=\"Genomic\",yerr=std[8:],capsize=3)\n", + "plt.legend()\n", + "\n", + "for i in range(11):\n", + " for k in np.log2(luciferase_dict[\"values\"][i]):\n", + " plt.scatter(res[i],k,color=\"black\",zorder=10,s=8)\n", + " \n", + " \n", + "_ = plt.xticks(range(11),np.array(luciferase_dict[\"ids\"])[index],rotation=90)\n", + "plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + "plt.savefig(\"figures/motif_embedding/genomic_single_double_motif_luciferase_withdot.pdf\",transparent=True,dpi=300)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "luciferase_dict = {\"ids\":[],\"values\":[]}\n", + "with open(\"data/motif_embedding/luciferase_ME.txt\",\"r\") as fr:\n", + " for line in fr:\n", + " if line.startswith(\"id\"):\n", + " continue\n", + " sep = line.strip().split(\"\\t\")\n", + " luciferase_dict[\"ids\"].append(sep[0])\n", + " luciferase_dict[\"values\"].append(sep[1:])\n", + "luciferase_dict[\"values\"] = np.array(luciferase_dict[\"values\"],dtype=\"float\")" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(25,5))\n", + "\n", + "selected = [2,7,12,17]\n", + "\n", + "for f,selected in enumerate([[2,7,12,17],[1,6,11,16],[0,5,10,15],[3,8,13,18],[4,9,14,19]]):\n", + " ax = fig.add_subplot(1,5,f+1)\n", + " mean_mm = np.mean(np.log2(luciferase_dict[\"values\"][selected,:3]),axis=1)\n", + " std_mm = np.std(np.log2(luciferase_dict[\"values\"][selected,:3]),axis=1)\n", + " mean_mm47 = np.mean(np.log2(luciferase_dict[\"values\"][selected,3:5]),axis=1)\n", + " std_mm47 = np.std(np.log2(luciferase_dict[\"values\"][selected,3:5]),axis=1)\n", + " index = np.argsort(mean_mm)[::-1]\n", + " temp = sorted(mean_mm)[::-1]\n", + " res = [temp.index(i) for i in mean_mm]\n", + " for i, pos in enumerate(res):\n", + " if i == 0:\n", + " plt.bar((3*i),mean_mm[i],color=\"orange\",label=\"MM001\",yerr=std_mm[i],capsize=3)\n", + " plt.bar((3*i)+1,mean_mm47[i],color=\"dimgray\",label=\"MM047\",yerr=std_mm47[i],capsize=3)\n", + " for k in np.log2(luciferase_dict[\"values\"][selected,:3][i]):\n", + " plt.scatter((3*i),k,color=\"black\",zorder=10,s=8)\n", + " for k in np.log2(luciferase_dict[\"values\"][selected,3:5][i]):\n", + " plt.scatter((3*i+1),k,color=\"black\",zorder=10,s=8)\n", + " else:\n", + " plt.bar((3*i),mean_mm[i],color=\"orange\",yerr=std_mm[i],capsize=3)\n", + " plt.bar((3*i)+1,mean_mm47[i],color=\"dimgray\",yerr=std_mm47[i],capsize=3)\n", + " for k in np.log2(luciferase_dict[\"values\"][selected,:3][i]):\n", + " plt.scatter((3*i),k,color=\"black\",zorder=10,s=8)\n", + " for k in np.log2(luciferase_dict[\"values\"][selected,3:5][i]):\n", + " plt.scatter((3*i+1),k,color=\"black\",zorder=10,s=8)\n", + " if f ==0:\n", + " plt.legend()\n", + " plt.ylabel(\"Luciferase activity (Log2 FC)\")\n", + " plt.ylim(-0.3,6)\n", + " _ = plt.xticks(np.array(list(range(1,12,3)))-0.5,np.array([\"MI-1\",\"MI-2\",\"MI-3\",\"MI-4\"]))\n", + " plt.title(\"SOX10, MITF, TFAP2 added once\")\n", + "plt.savefig(\"figures/motif_embedding/single_motif_luciferase_with_control_withdots.pdf\",transparent=True,dpi=300)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/the_code/Human/MM_ZEB2_ChIP.ipynb b/the_code/Human/MM_ZEB2_ChIP.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d3f5acd7865771585aaf7684d49b32056004c59f --- /dev/null +++ b/the_code/Human/MM_ZEB2_ChIP.ipynb @@ -0,0 +1,1035 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "09883fc4-c06c-4343-bb51-fc29e4c7b723", + "metadata": {}, + "source": [ + "# This notebook shows the experiments related to ZEB2 ChIP-seq on MM001 cell line." + ] + }, + { + "cell_type": "markdown", + "id": "78d11302-6000-41b3-9fbe-fbb4606f02a6", + "metadata": {}, + "source": [ + "#### Processed ZEB2 ChIP-seq (Antibody and input), ATAC-seq, and SOX10 ChIP-seq on MM001 files are in ./data/chip_seq\n", + "#### ZEB2 ChIP-seq summit file is in ./data/chip_seq\n", + "#### The notebook consists of:\n", + "* Plotting ZEB2 vs SOX10 ChIP-seq values compared with accessibility.\n", + "* Finding and plotting regions with high ZEB2 signal.\n", + "* Plotting ZEB2 and SOX10 ChIP-seq values on irf4 locus\n", + "#### Figures are saved to ./figures/chip_seq folder" + ] + }, + { + "cell_type": "markdown", + "id": "460f5a3d-c42d-4f2f-a59c-4033a5e1571b", + "metadata": {}, + "source": [ + "### General imports\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "abed5db4-4aac-45ee-a311-1edd529c0486", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "6b1c5a74-9234-47bf-b979-6bd9370f965c", + "metadata": {}, + "source": [ + "### Loading bigwig files" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e2369b19-bc46-4328-87d7-ba148073e53d", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pyBigWig\n", + "\n", + "Zeb2_Ab2_bw = pyBigWig.open(\"data/chip_seq/ChIPseq_MM001_ZEB2_Ab2.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "input_bw = pyBigWig.open(\"data/chip_seq/ChIPseq_MM001_input.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "ATAC_MM001_bw = pyBigWig.open(\"data/chip_seq/ATAC_MM001.sorted.dedup.q30.bw\")\n", + "Sox10_bw = pyBigWig.open(\"data/chip_seq/SOX10_ChIP.bw\")" + ] + }, + { + "cell_type": "markdown", + "id": "595c1d29-98c9-42e3-8f0b-e42d1ac2c309", + "metadata": {}, + "source": [ + "### Loading top 3000 ZEB2 peaks and calculating ATAC and ChIP-seq coverage on these regions" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "df0077f2-83d5-4f27-9e37-d33773861309", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "Zeb2_Ab2_values = []\n", + "input_values = []\n", + "ATAC_MM001_values = []\n", + "region_id = []\n", + "Sox10_values = []\n", + "with open(\"data/chip_seq/MM001_ZEB2_Ab2_summits_top3k_500bp.bed\",\"r\") as fr:\n", + " for line in fr:\n", + " chr_ = line.strip().split(\"\\t\")[0]\n", + " if chr_.endswith(\"_alt\") or chr_.endswith(\"_random\") or chr_.startswith(\"chrUn\") :\n", + " continue\n", + " start_ = int(line.strip().split(\"\\t\")[1])\n", + " end_ = int(line.strip().split(\"\\t\")[2])\n", + " region_id.append([chr_, start_, end_])\n", + " Zeb2_Ab2_values.append(Zeb2_Ab2_bw.stats(chr_, start_, end_))\n", + " input_values.append(input_bw.stats(chr_, start_, end_))\n", + " ATAC_MM001_values.append(ATAC_MM001_bw.stats(chr_, start_, end_))\n", + " Sox10_values.append(Sox10_bw.stats(chr_, start_, end_))" + ] + }, + { + "cell_type": "markdown", + "id": "d8489b4c-0394-4d97-8c7a-f2d25eb62dda", + "metadata": {}, + "source": [ + "### Plotting ZEB2 vs SOX10 ChIP-seq values compared with accessibility." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b41015f3-2462-4335-9f5d-62da7902fdd9", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(6,5))\n", + "plt.xlabel(\"ZEB2 ChIP-seq Ab2 (log)\")\n", + "plt.ylabel(\"SOX10 ChIP-seq (log)\")\n", + "plt.title(\"Top 3k ZEB2 ChIP-seq regions\")\n", + "plt.scatter(np.log1p(np.array(Zeb2_Ab2_values)/np.array(input_values)),np.log1p(np.array(Sox10_values)),c=np.log1p(np.array(ATAC_MM001_values)),s=7,cmap='jet')\n", + "cb = plt.colorbar()\n", + "cb.set_label('MM001 ATAC (log)')\n", + "\n", + "plt.figure(figsize=(6,5))\n", + "plt.xlabel(\"ZEB2 ChIP-seq Ab2 (log)\")\n", + "plt.ylabel(\"SOX10 ChIP-seq (log)\")\n", + "plt.title(\"Top 3k ZEB2 ChIP-seq regions\")\n", + "plt.scatter(np.log1p(np.array(Zeb2_Ab2_values)/np.array(input_values)),np.log1p(np.array(Sox10_values)),c=np.log1p(np.array(ATAC_MM001_values)),s=7,cmap='jet')\n", + "cb = plt.colorbar()\n", + "cb.set_label('MM001 ATAC-seq (log)')\n", + "plt.ylim([-0.02,0.7])\n", + "plt.savefig(\"figures/chip_seq/Zeb2_vs_Sox10_ATAC_scatter.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "b0d04f6b-2998-41c8-b40b-1c11c46073be", + "metadata": {}, + "source": [ + "### Loading DeepMEL2 model" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ca1787c5-ab30-499b-9819-d3fb45f3301d", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n", + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()\n", + "\n", + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])" + ] + }, + { + "cell_type": "markdown", + "id": "3ca9664b-9636-462b-8aa2-94ba7b8ce277", + "metadata": {}, + "source": [ + "### Printing the coordinates of the regions with the highest ZEB2 ChIP-seq signal" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "734831f7-c679-40de-8b6f-6037640a3b0c", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "chr16 90032296 90032796\n", + "chr17 83096431 83096931\n", + "chr13 113624773 113625273\n" + ] + } + ], + "source": [ + "for i in np.array(region_id)[np.argsort(np.log1p(np.array(Zeb2_Ab2_values)/np.array(input_values))[:,0])[::-1][:3]]:\n", + " print(*i)" + ] + }, + { + "cell_type": "markdown", + "id": "126f5712-f15d-42b3-8708-24deb2d47125", + "metadata": {}, + "source": [ + "### Plotting nucleotide contribution scores together with in silico saturation mutagenesis values for the regions with the highest ZEB2 ChIP-seq signal" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "e11ec7d5-3277-4b38-9198-089f89b6a7b4", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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xbtIvvNGcjEeoyr6kle3uLZK2Snpa0n5JR0s6VdZU63Mpq9zxfVV/TWJvQpGdEeVKgmfSs2lFdkYU3x5XeEt1d+OT8Q6okU7vwAFANfLnUkvKFZ9LubStpZ9RHy5d3e0lEJZ6B6x97GBGWuuT1oeKMgeX4potAAAAALQvxwHCkuT1eouCgyUpGAw6+owvfvGLuuKKK7R161atWbNGkpU9+MILL9QXv/hFSdJRRx2lT3/602XvveGGG3TjjTfqpptuKlr+N3/zN/rwhz9ctwDh17/+9fJ6vWXZgl9++eWyrMLLOeecc3TPPfcs+fqNN96o66+/fuH57OysAoGA8woDAAAALuH11ndwL5GwZiEuHGj0+60BXWa7BQAAQKORza3+fQCg2eiH2sQPhRrKZzyqtEkND7NJYV7WtHeT/MGCEzGPpNOW+LyD1Z+wmVlT0V3RsuBgScopJ0OGhnYNaWDzgLzL3Mi/lHzGu3S6cnY2w7BeJ+Md2oWZNZWcSipzICPfOp9CG0NV7Ttl6MABgHN2z5Hy5Vzc1tLPqD0Xr+724vE6nsyIa7YAAAAA0J6qChCuhQ0bNui73/2unn76af33f/+3crmcTj311KJsu/39/RXf++KLL+q9731v2fL3vOc9uuWWW+pW58MPP1xbt27Vd7/7XV1yySULy7/73e9qYGDA9uc89thj8i0zTe8RRxyhI444YlV1BQAAADpFImHN6lx6E1w6bS2Pxxm4BQAAQGORzQ1ob/RDbeKHQh2Q8QjLSiWkPdHibHZdfmlrzMqwVWitzRMxu+UqSE4lNT27dOq0nHJKzaaUnEqqL9jn+PPJeIdOktibUHRXtGif8nf7FdsWqzoL9wI6cADgnNNzKZe3tfQzasvlqxsAAAAAgLZj5HKV5pJ1t3e961267LLL9Ad/8AdFy7/85S/r3nvv1be//e26fffXvvY1XXHFFbrrrrt07rnn6nOf+5w+//nP67/+67+0adMm3XjjjUqn0/rqV78qSRoeHlYwGNQb3vAGHTp0SPfcc48+9alP6b777lPY5k0Ps7Oz6unp0czMjLq7u+v2twEAAACtxjSlYLB4NudC+SwZExMM4AIAAKBx8uepK2Vz4zy1gGlyFyZaAv1Qm/ih0GGqOYxx6KuxVEJKRqSybL3zkbKheHGQcNaUHghKc+kK75l/X5dfuniicgZiG0afGtWOxI4Vy42ERzR4+mBV3yFVTtYeCJDxDu0jsTehyM5IWTZuY37/jm+Pry5ImA4cXITzA7QMp+dStLUdhdWNVsfxGAAAAEA91DM+tGkZhCVpenpaDzzwgKampnTo0KGi12677bYl33fxxRfrwx/+sPbs2aNzzjlHkvTII4/o61//uj760Y/qgQceKCpbS//7f/9vvfLKK7rpppuUyWT0xje+Ud/61re0adMmSVImk9HU1NRC+UOHDumDH/yg0um01q5dqze84Q365je/qXe96101rRcAAADQiZLJpe81lqwBx1TKKtfX17BqAQAAoMORzc2hSlEtfr/1IxLVApehH2oTPxQ6SDWHMQ59NZY1rczBFYNTcpIMac+Q1DuwGOzr8VqZhZMR6/Wi986fsG0drjo4WJJ86+ylRLNbbilkvEM7M7OmoruiZcHBkpWF25ChoV1DGtg8IG+1+ysdOLgE5wdoKU7PpWhrOwqrG62M4zEAAACAVtS0DMIPPvigLr74Yp144ol65pln9MY3vlGTk5PK5XL6zd/8TX3ve99b8r0ej8fWdxiGIdM0a1XlpiGDMAAAAFDZ6Ki0Y+UkHBoZkQarT8IBAAAAVIVsbjYkEtbdgqVDFfm7BeNxfiy4Cv1Qm/ih0CGqOYxx6KuDl8alB/tXLnfhmHR8X/GyVMIKLp4rOGHrClgBLYHVrQgzayoYCyo9m64Y3GjIkL/br4noRPWBjUArs5GabXxyXP13r7x/j105pr5g3+rqQweuvrKmtC8pHcxIa33S+tCqJmFoN+12fuDGzItm1lRyKqnMgYx863wKbQxx/K0Fp+dStLUdhdWNVtNux2MAAAAA7lLP+NCqAoQffPBBPfjgg3r55ZeVzWaLXvvSl75k6zPOPvtsbdu2TTfddJPWrVunJ554Qscdd5ze/e53a9u2bfrTP/1Tp9VqWwQIAwAAAJWNj0v9Nu79GxsjIREAAACaw403xbqGaUrB4NJZRg3DSs8wMcGPBtegH2oTPxQ6QDWHMQ59dTI5Ku22MSnBeSNSsMKkBHUMWkvsTSiyMyJJRUHCxnxmvfj2uMJbuMMcHchmarbRp0a1I7Hy/j0SHtHg6TWYdIQOXH1UDCD0W9lHVzkZQztot/MDN2ZeTOxNKLorqunZxUr5u/2KbYtxHK4Fp+dStLUdhdWNVtFux2MAAAAA7uOqAOGPfvSjuummm3TWWWfJ5/PJyE+NNO/++++39Tnr1q3T448/rpNPPlmve93r9P3vf19veMMb9MQTT2hgYECTk5NOqtXWCBAGAAAAKssP0qTT5bO4SgzSAAAA2Nahd2q1S/aYll19BBCiBdEPtakdfyiy3tnSLsdWO6o5jHHoq5PVZBBugEpBSYHugIa3DROUhM7kIDVbYQZhT1YKPS/5XpUyR0nJTVLWY72lJhmEUR+phJSMSGWZ1OfXdyje8UHC7XR+4MbMi/nJOnIl2yCTddROI65LHXrN1J33PaVnn5/TyZu6dPWlp+vwNe3ZzwDQHO10PAYAAADgTvWMDz3M6RvuuusufeUrX9EVV1yxqi/+jd/4Df3qV7+SJJ1wwgl69tln9YY3vEGS9LOf/WzF9z/00EO69dZbtXfvXhmGoS1btuhDH/qQQqHQquoFAAAAoHV4vdaM45GIdXNB4Q0H+ZsNhodb515jAACApnBjapcGaJfsMS29+jKZ2pYDGoB+qE3t9kOR9c6Wdjm22lXNYYxDX52sD1n75Fxa5QFokmRYr69vzr0E4S1hDWwe6JjgeWBZpml1YCpNIJLLWecJQ0PSwIDk9Sq0MSR/t19nPzKt4V1SYHaxeKpbGtom/eicgEIbuVfIlbKmdQ5VsW3OSTKkPUNS70BHT7zSLucHDnfvxtQpayq6K1oWHCxJOeVkyNDQriENbB7guFylRlyXuuH2R3TbRzbKnDljYdkHe17Q9TdN6eZrz6nNlwDoeO1yPAYAAADQmTxO33Do0CGdd955q/7ic845Rw8//LAk6Xd/93f153/+5/r4xz+u97///TrnnOUv3Nxzzz266KKL1NXVpWuvvVbXXHON1q5dqwsvvFAjIyOrrhsAAACA1hEOWzOO9/YWL/f7l5+J3DStWWBHR61H06x3TQEAAFwon9ql8C4+ycr4GIlYr7ehfPaYwgAmSUrPphXZGVFib2v83S2/+ny+2pYDGqTafmjHaZcfKp/1bq6ksZ1LW8tTbm9sG6Ndjq1OVHMY49BXJx6vFbAvaSEj5YL551uHmxp85vV41Rfs0+Dpg+oL9hGEhM6VTJZ3YArlclIqZZWTte983Tuor++UemeLi/bOSl/fKe30Xs4+5Vb7kuXnUEVy0lzKKtfB2uX8wOHu3Zg6TSXLzk+L6qScUrMpJac6exssY3MQtdrrUmbW1PjkuEafGtX45LjM7NKDtDfc/ohuiZ4tc2ZD8WfMbNAt0bN1w+2POPjDVsDgMToB2/mS2uV4DAAAAKAzGblcpXn7lvbhD39YRx11lP76r/96VV/83HPP6dVXX9Wb3vQmzc3N6YMf/KC+//3v65RTTtFnPvMZbdq0acn3btmyRVdddZWuu+66ouW33XabPv/5z2vv3r2rqpvb1DOFNAAAANAuTNO6qSCTsQZlQqGlZyBv6SxrAAAAtWKaUjC49N2bhmGdJE1MtE6GRxvMrKlgLLjkDaKGDPm7/ZqITrj6JvO2WH35PyKdrpxiqCX+CHQyJ/3QjtbKP1TWlB4ILhPYMp+V9OKJjs561y7HVqeqOYxx6Kuzitm+A1ZwMNm+AXcYHZV27Fi53MiINDi40HDmpqfLwv8lKWdIhj9Aw+lWk6PSbhvr+7wRKThY//q4VLucHzjdvRth9KlR7UisXKmR8IgGT+/cbbCIzUHUaq9LJfYmFN0VLeo7+Lv9im2LKbyl+Hzt0Gumuta/NB8cXCkPTlbeozOae3mDDl+zyp2DwWN0ArbzZbXL8RgAAACAe9UzPvQwp2/45S9/qc997nP693//d73pTW/SmjVril6/7bbbbH3OSSedtPD/rq4u3Xnnnbbr8Nxzz+n3fu/3ypZffPHF+su//EvbnwMAAACgfXi9Ul/fyuXys1mXDurkZ7NupSRGAID20cpxM2hhTlK72DnRahFOssf0BfsaVzGH2mL1eb3WDWiRiHWHVeFJujF/+//wMA0iXMtuP7TjtfIP5STr3fF9jaqV67TLsdWpag5jHPrqLBCWuWFAT30vqblXMuo61qfTfzsk72oDRgDUjtPUbPMdn0rBwZJk5NQCHZ/VaelrRmttrm+75dpUu5wfuDHzom+dvS+zW67tORhErea6VGJvQpGdEeVU/Pnp2bQiOyOKb48XBQnfed9TMmfOWKbCHpn7e3XnfY9r6PLlyq2AwWN0Ahdv52bWVHIqqcyBjHzrfAptDDVlcrF2OR4DAAAA6EyVplZb1pNPPqkzzjhDHo9H//mf/6nHHnts4d/jjz9u+3NOOukkvfLKK2XL9+/fXxQ8XEkgENCDDz5YtvzBBx9UIBCwXQcAAAAAncU0rUlxK834ml82NGSVAwCgURIJa1by/n4ry0Z/v/U8kWh2zdD2MpnalmsRmQP2/h675ZqlbVZfOGzdgNbbW7zc7+cGTADNd9BmI2q3XJtql2NrNao5jHHoq59EQgqe5NWZ2/p0/rsHdea2PgVP8tK3AtwkFLIaPGOJkF/DkAIBq5zURh2f6rT6NSPzmJBe2O9XNlt5fWezhtL7AzKPCTW4Zu7TDucHTnfvhtRpY0j+br+MJaYZMGQo0B1QaCPboNNBVKfNs5k1Fd0VLQsOlrSwbGjXkMzs4iDts8/P2foOu+UqYvAYncDF23lib0LBWFD9d/drR2KH+u/uVzAWVGJvc0522uF4DAAAAKAzOc4gPDY2VpMvnpyclFmhQ/mrX/1K6XS64nve//73KxaL6c///M917bXX6vHHH9d5550nwzD0/e9/X1/5ylcUi8VqUj8AAAAAy8iaVnacgxlrZvf1IamGs7jWa0b8tsiyBgBtrqWzolTBxZO2t49O26iccGNqlwZol+wxbbX6wmFpYIB91Sa3ZNUAOgJZ72xpl2Nrtao5jHHoqz36VkCLcJqara06Ps60Q7uWfNir278cU3woomzWkMez+Mdks4ZkSH/25WFde5qXMRm1/vmBGzMvej1exbbFFNkZkSGjKDg1HzQ8vG24vfvUdq+NOhxEdZwQfiqp6dmlPz+nnFKzKSWnkuoL9kmSTt7UtfC6R6ZCSsqnjDLyKamQsvKWlXOMwWN0Apdu506zijdKqx+PAQAAAHQmxwHCq/XAAw8s/P/b3/62enp6Fp6bpqkHH3xQwWCw4nvvvvtufepTn9Kf/umfasOGDfr0pz+tnTt3SpK2bNmir33taxoYGKhr/QEAAICOl0pIe6LSXMEgUpdf2hqTAqsfoEkkrAlsC8eo/H7rpoLV3uzS4ckGAMD16nkMcKOVJm03DGvS9oEBbjyoWqdtVE7lU7uk05U3RMOwXm9kapcGyGePSc+mK2YtMWTI3+13ffaYtlt9Xi83WtqQ2JtQdFe06KZaf7dfsW2xptwwB7S99SHrmsdcWqpwzJAM6/X1rdLY1ke7HFtXo5rDGIe+2qFvBbSYfGq2Sv314eHi/nrbdXzsaZd2LZOR7v9xWJHhuGLvjSpw7OL6nv65X0P/PKz7fxzWZYzJLGj18wMnu3fD6rQlrPj2eMW+9PC24fbuSzu5NupwENVp85w5YO/zC8tdfenp+mDPC7p4Zrdiuk4BLf4dKfkV1Wf0wNHn6upLT7dX92X+npqVA9zIhdv5SlnFDRka2jWkgc0DTZnEodWPxwAAAAA6j+0A4bDNK3SJRGLZ13//939fkmQYhq688sqi19asWaNgMKhPf/rTFd+bK7iadMkll+iSSy6xVScAAAA0QJ0zysIlUgkpGVHZTbFzaWt5KL6qIOF6z4jfwckG4EZktASKtENWFKdcOml7++jEjcqp1aR2aeHz/3bJHuPGzDyor2qzanDaCayCx2tNiJaMSDJUfD1kvrHdOlzxGNhJ2b4Lj63erPTW5yXfq1LmKOn7m6SspzWOrWhdhX2ritnlcl76Vm2K85wWZjc1W4d2fNrlmlF+rOX+H4f1r3sGFDo1Kd/RGWX2+5R82mqfC8uhPbgx82J4S1gDmwc65vxckvNrow4HUQubZ69MvbXg/Ov789l9ixLCr7P3+YXlDl/j1Zcu/are86W/VOnYdK/Simu77gl/Qoev+Qt7dV/m76lZOcCNVrGd1+vaRjVZxQEAAAAASzNyuUpzuJX7gz/4A1sf+OUvf9lWuRNPPFE/+tGP9PrXv95WeUnyeDx66aWXtH79etvvaQezs7Pq6enRzMyMuru7m10dAACAcnXOKAuXyJrSA8Hi9VxkPmvOxRNVBYeYphQMLn3TS36m6YmJ6m8iyH/HSrNZr+Y7AFvIaAkUacQxwI1GR6UdO1YuNzIiDQ7Wvz5tpVM3qmpVOi4FAkundmmT8/9KmVgD3YGWyx7jdPWhNZlZU8FYcMkb5/LZOSeiE0U36XHaCdRIxWNfwAoOrnDs69Rs34/cfoM2fuQ2nTBjLix7ocerqZuu1znX3tzEmqHd5ftWlyihmKIVssvFdL/C9K3aDOc5HabDOj7tcs2IMRmgSaq5NvraIcnXJb1iVn6PJL3eK70wJ605fGHRIzcktPG2qE4wF7/rBa9fU9fHdM7Ni+1z/rpGejZdMWNoxesa839Hbno6Pz1TkZwkIxBg8BhYSZXbeT2vbYw+NaodiZVPdkbCIxo83cUnOwAAAADgQD3jQ20HCLuBx+NRT0+PDKPSJZ9FP//5zxtUo8YgQBgAALjafEbZnHJFA3O5fO6tVWaUhYu8NC492L9yuQvHpOP7ipfZSOUwPi712/j4sbHVzYifnzBbqpxsgGSCqLulZm1nI0QHa9QxwG069e9uCH5c5+ym3po//y/N2rGQRbHFzv/bJbsjmdPa3/jkuPrvXrldG7tybCGrBqedQI1lTWlfUjqYkdb6pPWhihOkLZXtO5+lfqls3y1vvtHJ5UquERrzfzmNDupofFy6vT+huKzzVE/Ba9n5LTKiuK4dC3P63yY4z+lQ1XR8WrSz1E6XNRiTcahFt9nVapfrM65RTSPy0rj0qX5peJnyQ5L+omAc2GEfIN9XklTUX1qyr8TgMVA7Drfzel/bqOZa54IOPVYCAAAAaH31jA89rKaf5sBNN9207Osf+chHKi7/6Ec/qp6ennpUCQAAAE5lTWlPtCw4WJKM+aXGniGpd6CqjLJwmYOZ6srZTOWQsfnxdsstJRy2xrcqValNkw3ATUzT2vgqzdWVy1mDsEND0sAAA5noKI06BrhNKGQdf1aatD0UanzdWl6nblSr4fWufCPd/Pl/eXCw5pcZUoud/3s93vIbjFqQndWH1pY5YK+9ypfjtBOoA4+3fEK0EmbWVHRXtGJGrPkrZRraNaSBzQPtFfBQ0OiUXSOk0akdboJeUug8U/+PNyqZxcHBkuRRTlkZ+gfvkDacNyCJ36zVcZ7TwZx2fFo4zXQ7XTNiTMaBFt5mV6OeGSo7VjXXRg9mpLfICgL+qqTC/CzHSHqvrNfz48BV9AHCW8KKb49XXN/D24bL1zeDx7CJrpINDrbzRlzbCG0Myd/tt7KKZw3p+ZD0qk86KiNtSsrw5OTv9iu0seRkp0OPlQAAAACwkqYFCN9///1Fz1977TVNTEzosMMO08knn7xkgPDll1+u4447rhFVBAAAwEr2JaW56bJBvzxDOWkuZZVb4QZKtIC1PufllkrlkE5bywtmovXZ/Hi75ZYTDlvj0QwUouGSyeIBy1K5nJRKWeWI8kEHaeQxwE28XuuehUjEul+q0qTtw8Mcn6rSqRtVvc2f/y+N83+gXnzr7LVX+XKcdgLNkZxKFt3oXiqnnFKzKSWnkm0xQcUCGp364yboZXl3J3WCufQ26FFOvWZK2s022A5ocmBLIiFFLi2f32p62loev8/V7We7XTNiTMYGB+Np7WSpDJXp2bQiOyOrzlDZsaq5Npof332LpK2Snpa0X9LRkk6VFmZhyZer8oAc3hLWwOYBexmjGTyGDXSVHLC5nTfi2obX41VsW0yX/u2/SLuGpdnA4ovdKeW2DWn4b99d3DZ06LESAAAAAOxoWoDwY489VrZsdnZW73vf+3TJJZdUfI9hLBV6AgAAgGbI/iJTlpFhNeXQJHan1F0f0pz8OjKblsdTPltsNmvolx6/utaHFj/XQSqHRs+IT5Y1NEWjM1pmTStI62DGumljfahlMjqis7RTVhSnSE5QJ528UdXTQZvHJ7vlANhWlFWjQvYOQ0ZRVg0SqQPN4TTbd8PVq49Io1Nf3AS9MrbBjsLqxopMU7rmqvLg4LycrNddnma63a4ZMSazjHZMjW5j7LERGSodVql9VHNtdH1I6vJLc2nJk5NOK3uT9Xp+HHgVB2Svx2svqNDlg8cdtU25FF2lKtjYzht2bWNvWPr6JeUrcLZX+npc+t+GtGV+WTseKwEA6CTcvwYAdeeqOI3u7m7ddNNN+uu//uuKr+cqde4AAADQNE/+j73ZeO2WQxMkElIwKPX3Szt2WI/BoLW8hJnzKvrVmGRYwcCFsllDMqShfx6WmZu/eONk5mgtzohv3QiQLSmcVU65lpoRH6iokbOdpxLSA0HpwX5p9w7r8YGgtRxwmfwxQFrMgpLXillRnAqHpclJaWxMGhmxHicmuHFlVTp9o6qXtTaPT3bLAbAtn1VDsoKBC+WfD28bXrhpmkTqQHM4zfbdUPXsI9Lo1M9KN0FL1k3QptnQarkO22BHYXVjRQ+NS5lXli+TecUq53JcM+oQDsfTXM/m2KOTDJUNqlL7qObaqMcrbY3lC5V84PzzrcOLN/E34oDs4mu8HbdNuRBdpfppxLWN/PpTzlD5bewea5KIoYL1127HSgAAOgn3rwFAQ7gqQFiS9u/fr5mZmYqvZbNZHXfccQ2uEQAA6GimKY2PS6Oj1iOjB0WefiWk1Cv+smDRvGzW0NTPAnr6FTKzNZTd7TY/pW7pQEp+St3Sgfqk9IVvhxUZjiv9ygnSTyTtlvQTafpnvYoMx/X5XeHFMZdqZo7ekpAui0jd6eIy3dPW8i1cGEKLy892XnojQ55hSIHA6mc7TyWkZESaK9m/59LWci6ywoXyWVF6e4uX+/2dMct7ftL2wUHrkbjVGqh2o8qa0kvj0uSo9ZilD7Agn0mk7CbBPEPqCixmEmkF9Pnqh32p5sJbwopvj6u3u7hd83f7Fd8eV3jLYrvWqNNOAMXy2b5LA/nzDBkKdAcWsn03zHwfMVfSR8zVqo9Io1M/3ARtD9tgR2mF1d2p3Qwza2p8clyjT41qfHJc5gp9gLr9Tv89XttyNeb07+aakX1Ot0HXaKfU6A7GHhuVodLhcGj7qObaaCAsheJSV8l7uvzW8kDBexp1QK7yGm8924OO3aZchq5S/TTi2obj9ddOx0oAADoJ968BQMMc1qwvvv3224ue53I5ZTIZ/fM//7O2bdvWpFoBAAAUSCSsKSsLr0r7/dYste0eoWLThhO8in4mpvhQRNmsIY9ncXrWwoyy197C3QoNY3e7XWlKXcOwptQdGFi422RhLOXHkn5cmrFq0UI5hzNHm1lT0V1R6bRp6dRvSM+HpFd90lEZaVNShienoV0/0sDmgYWsWEDLyc92HolY+1nhPlir2c6zprQnKqnC/q2cJEPaMyT1DizO9A64RDhsHXqSSet44vNZ9w9x4yOq5nSjSiWsNrRwgKrLb2XPCNAHWMgkkozIOgMsPNZUyCTidvT56od9qW7CW8Ia2Dyg5FRSmQMZ+db5FNoYKusjNeK0E0C5fLbvyM6IDBnKFRwrK2X7boj5PmJOuQp5wKwaGqvtI9Lo1A83QdvDNthR3L66O7WbkdibUHRXtCgbqL/br9i2WNFENgvl6/k7HV3jcjXUqdtHIzjdBl2lXVKjOxx7bGSGSgfDoe2lmgvugbDVN9iXlA5mpLU+azLA0r5CIw/IDv+OerYHHb9NuQhdpfppxLUNx+uvXY6VAAB0Eu5fA4CGMnK5Spcr6u/EE08seu7xeLR+/Xr99m//tm688UatW7euGdVypdnZWfX09GhmZkbd3d3Nrg4AAJ0hP+1r6alSfjCrE9LY2WCaUjAone1LaPiKqALHLg6yTf0soOvuGdaPXgxrYoIBsIZwst2Oj0v9/St/5tiYNSX9/Ftu708oroiknDwFxbLzA0ERxXXtWNh6S34DSacrj5IahnXny/wGMj45rv67rTp5slLoecn3qpQ5SkpukrLzXzh25Zj6gn0r1x1ws0p3ggUC1s0Syx1fTHPlGyBeGpcetLF/XzgmHd9XReUBoE3lZ68tG6CaP5cqzZLRySoGfwas4OBW+Y3o89VPPktlSSBaLn/7GPtSQ1V72glgdSrdkB7oDmh423BNA1TMQ6aeujOpuWcz6jrZp9OvDsl7eBP7iDQ6tVfFNbyOxjbYUdy4uju1m5HYm1BkZ6QoeERaDCCJb48XHf/q/ju98KB0+kXSz5cpc4ykp/5dOuHCVXyRM526fTSC023QdRyOp7mWw/MWM2sqGAsqPZsuW3eStf783X5NRCcqB6HZGC9Z7amUnSGZ1aj35zeEyw7I+fbAUE6htZLPK2VM6fsHrfHs5doDM2uuOCEbp+fuwbqov3pe23C8/trlWAkAQCfh/jUAKFPP+NCmBQjDPgKEAQBosPyF5cJBrEJcWC6Sv6HBY5h66+akfEdnlNnv0/efCSmb83JDQ6M43W5HR6UdO1b+3JERaXDQ+opDpl7qCmqDOV0UHJyXlaGM168NcxOLN6MmEspFLlUup5KAYqtKRvy+hQ1k9KlR7Ujs0CU/kWK7pMDsYvlUtxTdJt1/mjQSHtHg6YMr1x1wO6d3fthNLzE5Ku22sX+fNyIF2ZcAQJI1e+0DweKA1yKGlf304glmr83LmitnEnEr+nz1M78v5eamy7JUSvNzQXcF2JcarC1uOAZakJ2by1fjkRsS2nhbVCeYi8ezF7x+TV0f0zk3L/YRsxP/Is8P3rPi52XPvUeeE9+9+orR6NQWN0E7xzbYUdy0uju1m5EP8CsMHClUGuDXkN8pa0o3Hi/d/MrSZW44VvrkSw3rl3Tq9tEITrdB18oPuEqVM7G2woBrFWOP+WBOSRUzVC4ZzGlzvKSKKjn9iqq1VUZxlxyQ8+3BW8xpxdZLgTWLr6Vek4b2ST/yBiq2B3azDq9mm0Jt0VVqjHpd26hq/bXDsRIAgE7C/WsAUKae8aGH1fTTbHj/+99vq9yXvvSlOtcEAABgCcnk0iP0knWhOZWyyjHVqMJh6zp7NOrVQ3v7FpY3e6b+juN0u/X57H1uQTnv7mTRTaelPMqp10xJuxf3jcQW6V8uk4ZLAn6nu6Xrtknv3iLlNxHfOp8u+YkU31n+2b2z1vLIdsl3pc26A27n9do/jswPeOZyJZn40mkZkUjxgOdam/vIUuVcciMHADTUvuQywcGSlJPmUlY5Zq+1eLyt+1vQ56uf+X2pUnCwNJ+Pm32p4ZycdraTegdnAivxerzqC/bV5bMfuSGhs2+JSCWZ1jaYaW24JaJHFF8IEn5ydp/OsPGZdsutqFMbnXrxeq0okUjEuum50k3Qw8P02wtVsQ1yzGhdbmpyOrWbkZxKLhmYKVkBf6nZlJJTSfUF+xrzO3m80jWfkw5dKn1VxZmEj5H0XlmvN3A/79TtYzXsts2F26AnK4Wel3yvSpmjpOQmKesp3gZda3HAtTxitFUGXKsYewxvCSu+PV4xMHPJDJUOxkuqqFLhV5QFraXT1vLVxqDV+/MbziUH5ORUUm8xpxWvsN57D5O+7pMimfL2YKks5OnZtCI7I0WB6tVuU6g9ukqNUa9rG1Wtv3Y4VgJoOdw+A6zCau9fAwA40vAA4a985SvatGmTzjzzTJG8GAAAuFImU9tyHSAclgYGuCDWVE632/PPk471Sq+YS5d9vdcqV+V3mFnTGtA/TfrGqeU3ZeQ8hn60a0gDmwfk9XgV6j1P/8+3vZLMsgzFHllZh//hO15tuOc8AR3FNKVotOxmF0kycjnlDMkYGrIaYq/XyuDY5Zfm0iq9WXz+Xdbr60PlL7XVlPUA4MBBm+c5dsvB3ejz1U12Ll12Lr+ackC17Gb+AVqRecjUxtuiknIVrp/klJWhwG1DMv9uQN7DvXraWK9jX7NuiPdUmMEhm5Omfy09bayvTYAwao+boOuKYwZqpVO7GZkD9v6gfLmG/U6BsHT9fdJbr5UeS0v7JR0t6Uy/dHbMer2BOnX7qJaTtjm/bV3yEylWMlltqluKbpPuP83+ttpUrT7gGgpZ5ycrpYMMFY9NhLeENbB5wN5kHSuNl8goGi+ppkrzX1GxfC5nvadwSMapen9+J3txNq3Yeuv/pX0fj2H1fYbXS7tn0wvL8+PZpcHBkjXJhSFDQ4Xj2dVt5qgTukqtrar11+rHSgAthdtngFVazf1rAADHGh4g/Cd/8ie699579dxzz+n973+/3vOe9+iYY45pdDUAuAizcqPZmOWrflr2t2Xa16q4ZGLgzuV0u/35bukKUxpepux7TKtcPrOXw+8onLU965EeOrG0YPGs7d6Hd+uEmaUDlj2Seveb0sO7K29sWdPKRHYwY80stz7U0AwAQN3Mp5dYMhNfTsXpJTxeaWtMSkZk5ekrvMg6/ylbh8v3j7absh5AKfrfy2D22s5Cn69uGp6lEqjASeYfwG3sXE996s6kzjCXTkHoUU69ZkqP35nUGUN92tDdq+g+Ke6zbogvvFE+O7+bDO2Tru3urcNfhJrhJui64JiBWurUboZvnb0/KF+uob9TICz1Dkhvbf64QaduH9Vw2jb71vl0yU+k+M7yz+qdtZZHtku+K1vkx23lAddVpPO0naFypfESFafjrqZK9c74TUbx+jk1t0+BNUu/7jGkjWukn+f2LSwrHM+uJFc6nk3WWtehq9Taqll/prxKqk8ZST5JIUmsbgC1xu0zQA1Ue/8aAKAqDZ+k/84771Qmk9GHP/xh/du//ZsCgYC2b9+ub3/722QUBjpQYm9CwVhQ/Xf3a0dih/rv7lcwFlRib6LZVUOHSCSkYFDq75d27LAeg0FrOVanpX/b/LSvxhJDi4YhBQJM+wp3cbrdHsxIb5E0JKl0vp5j5pe/RcVZ8hx+h9PMAauaQj+VkB4ISg/2S7t3WI8PBK3lQIvLptMrFyotFwhLobjUVXKDd5ffWl6aIWOlKesla8p6c5ms4wBcjf73CvKz1y5ze6G6Asxe2y7o89XN08Z6pV5bDDgrlc1JU69Z5YB6WCnzjyQN7RqSmeW8Fu5j93rq3LP2rp/ky4U2hvQjr1+XZaT0r4vLTP9auiwj/dgbUGgjxz3XywcMDQ5aj9zxviocM1BrndrNCG0Myd/tl7FEf9qQoUD34nGm4b+Tx2tNghoctB6bdNNpp24fTlXTNod6z9Md37bWa+lNcPnn//Adr0K959WjyiiVTwfZWzI24ffXJIoim7Z3LlxYzmmV6p3xm4zi9fOmbnvXmwrLOR7PVt03c1SBrlJrc7L+WvpeNAAtg9tngBpyev8aAKBqDQ8QlqQjjjhCg4OD+u53v6uf/OQnesMb3qCrr75amzZt0quvvtqMKgFogvzMr6UzMeZnfuUmZdRbfpav0tlZ87N8cfGwei3/2+anfZXKR+qZ9hVu5XS7zWe/e4ukmKS/kvT/zj/G5pcXlqviO5xmDqh6Cv1Uwpppbq6k0ZlLW8sJEkaLe9K7b+VClcoFwtLFk9KFY9J5I9bjxROVL646mbIeVTFNaXxcGh21Hm0NFjl9U1Vfgk5A/9uG/Oy1ksqDhJm9tpJqmhzXNFNu7/O55ocqYLNO+SyVUnmQcGGWyg1kqUSdOMn807actiFZU3ppXJoctR4JhGsKJ9dTu062d/0kX87r8Sq2Lab7f2HoxEmpb1oazFiPJ01K9//C0PC2YXk5z0GH4ZjRGOYhU48Pj2v3n43q8eFxmYfa9zjj9m5GveSPM5LKgoTzzwuPM27/ncysqfHJcY0+NarxyfGaTRLg9r/bLappm70P79YJM+aSN8B5JPXuN+V9eHdtK9tpnPQzwmFpclIaG5NGRqzHiYmaRE0+uc/euXBpOSdVqnfGbzKK14+nNOjARjnH49nz6riZA1hCy9+LBqBlcPsMUGNO7l8DAFStKQHChQzDkGEYyuVyymazza4OgAZhVm40G7N81U/b/LZM+4pW5GS7LcyS55F0mqTz5h890pJZ8hx8h9PMAVVNoZ81pT1RqcI5xcKyPUPc4IyW9vSp65XqlpbqMWclTXVb5crYzZDBlPV1VdVs1k7fxJTZWAL9bweYvda2apoc1zVTbu3zue6HclYnslSi2arJ/NNWnLYhqYT0QFB6sF/avcN6fCDIRFsN5vR66ulXh/SC16/sEtdbsjKU9gZ0+tWLbW14S1jx7XH5uv166KB076vSQwelE7oDim+PK7yF8xx0no4/ZjTAIzck9FJXUGdc16/z7tihM67r10tdQT1yQ/seZ9zazai3/HGmt2QiIH+3v+Jxxq2/U2JvQsFYUP1392tHYof67+5XMBas2cRqbv273aSqtplr2/VXzbWKOqXzfHp9SCktfy48pYCeLh3fdFClemf8JqN4Hc2Pf1caNZbmR45Lxr8dj2cXIGst0Dhtcy8agJZAFwOoA7v3rwEAqtaUAOFf/epXGh0d1dvf/nZt3rxZTz31lO644w5NTU3pqKOOakaVADQYs3Kj2Zjlq37a6rdl2le0Irvb7Wqy5Nn8DqeZA6qaQn9fsjxzcJGcNJeyypVyY2Y2dBS7m+CGo3sV3Wb9vzRIOP98aJtVrmpMWV83+dmsX0ibumDLuC4/d1QXbBlX5gVz6dmsnU6BvYops2kK299q+t8duX0we+2KqmlyXDuzv9v6fG78oRzWiSyVbaKFDwDVZv5pC07bkFRCSkbK+9RzaWs5QcIN4/R6qvdwr6aut66flAZG5J+nrh+W9/Ditja8Jaxnr5nUZzY/pmuOfFif2fyYfnrNBMHB7ayK9ryFDwGOdfQxI6+OK/yRGxI6+5aINpjFDdwGM62zb4m0fZBwvbsZbtxXw1vCmoxOauzKMY2ERzR25ZgmoksfZ1zXHdubUGRnpOwaSno2rcjOSE2DhN30d7tNVW3zKq5tu3Ffch2XXavY0OtVVMufCw9pWBt6q7/uUO+M32QUr6P58W9DhnIl20dOhjU+XTL+7Xg8G0DtZU3ppXFpctR6rDChbVvdiwbA9Qq7Dh6ZukDjulyjukDj8sisWA4AAKDZjFyu0pxK9XP11Vfr3nvv1caNG/UHf/AHes973qNjjz22kVVoObOzs+rp6dHMzIy6u7ubXR2gJkafGtWOxI4Vy42ERzR4+mADaoROMzpqTW67kpERa7ZP2MdvC7SYVMLKwFt4Q3BXwBocrVEgTGJvQtFd0aIbawLdAQ1vG658c1AiYU3/WjjCEwhYo+Gld8lMjlpZjlZy3og1A91y3+H3WyPy3ImDBnCyCZpZU8FYUGc/Mq3hXVJgdvG1qW7pum3Sj84JaCI6Uf0NCqZpzfifTleeetkwrApOTHBXigP5n/UtGxKKvTeqwLGLKzz1il9D/xzTj14MF/+s+TctNcpdui6cli9AU9gZqu1/s32gkmqanFU0U53FjT/Uao4xTvsAcI8WPwDkz53Ts2nlKuQMMmTI3+1f3bmzGzndX7OmlSl4yQm3DKnLb02S0U6/k0tVez31kRsS2nhbVCcUBN+lvQGlrh/WOTeX768tvnvDqSpWeKdtIx17zMir4wo3D5l6qSuoDeZ0xRnrszKU8fq1YW6ibDIDrKzT9tVGyLcHS02w1vbtgYtU1TZXeW2bfckGF16ryFfp7OmEhhVVQIt1m1JA12lYPwqEa1IlJ8OVbvz8jlbF+DfXsoAmqbi/+q3J7gv2V+5FA9BIy51zpuTXkGI1O+cEAACdpZ7xoQ0PEPZ4PNq4caPOPPNMGaXT4BVINC1thPs42gBM05oGK5OxpqYJhTj7hCuNT46r/+7+FcuNXTmmvmBf/SuEjjM+LvWvvAlqbEzq66t3bSpo4fbc9b8tsJwW3vdWJWtaGXYPZqS1Pml9qOY3AJtZU8mppDIHMvKt8ym0MbT8jTR218VL49KDNhqdC8ek4/us/+dnOy/tCuX7J/E4I++oq2o2wXwGC082p7c+L/lelTJHSd/fJGU9huLb46u/QSFfMam4cuwbVRsfl27/UELxoYiknDwFl0GyWUMypMhwXNfeEl48L3J6MlXlyVfVTWEjjpWdejyuk2r63xwqsZRqmpxG9xFbtglx4w+1yjo57gOg+drkAJA/d5ZUFFSQz/xTk3PnBrLVrjndX6vpS6NuVtPcmodMPXVnUnPPZtR1sk+nXx2qGGzXJrs37Jpf4blccd60nDHfElZY4Z26jbTbMcO2Oq/wx4fHdcZ1Kzdsj39mTGcM9VX9PZ2oU/fVeuPeBXepqm12eG2bfcmmBl6rcHI9J7/+PDlTb1VSPmWUkU/fV0hZw1vT9Vfv60wtex2rFVQx/s21LKDBUgkpaY2hFps/IIfiC0HCqz4kOW0TaKCBjvfIDQmdfcv8fR4Fy7PzbdQPPxSvOEljVRpw3x4AAFhBg/oAbRUg/L73vW/ZwOC8L3/5yw2oTWuwvQEwvSVaSMfPyo2mc3WSvBZvz1392wLLafF9r2PNZz3KzU2rUi8jJ8noCixmPXLhbOfoLKvZBBsyezlT1tfUvSOmzn8lqN5jpouCg/OyWUPTP/dr9+sndPmO+RXudArsKqbMrno7bMSxkuNxzTntf3OoxHKqmaW/kTP7t3QT4sYfirQMnaXNDgDtkvnHdrvmdH+dHJV22yh/3ogUZP+ut3pfT22z3RsrmV/hueklrpUZkuEPFK3wTt9G2uWYYVsDVvjuPxvVeXesfJzZfc2IzvsHjjN2dfq+Wk+jT41qR2LlbXYkPKLB09lmG6GqttnmtW32JQcadF2gmus5DGUAQIubv8+jKHNwEcPKJDx/n8eh10x1rX9J5swGqShUb+ED5T06o7mXN+jwNSUHcJtZihe09EADgJpY6fqaDBmBGnUanLZRAACg9hrYB6hngPBhNf00G77yla80+is7w1LTW6bT1nKmt2xLrTxzodfjVWxbTJGdERkyKs78OrxtuOLf07ETtDFLVE15vdYxOxKxBvkqTSQ8PNyk4OAWb89d+9sCy2mDfa9jebx65PhBnf3cLcpJxdk551fn/z3+cp2TP2Ymk0vf9SFZ20AqZZWrlAWtU89DUDOr2QTDW8Ia2DzgqA9gN5vU4peEZf7e/09P3Xen5p5/Vl2bTtbpl14t75rDnf2hkCSdemxSAS29wj2enDa+PqWfH5uU1Gct9PnsfXi+nNPyqnI7bMSxssOPx077+HaPSYX9b2W90vNvlV71SUdlpE3flzzZov73Kg+VaHNVNDlVvacabm5CbO3fDf6hyjIKptMySn+oRtUJ9WfnumKbHQCqOXd2G0ftmtP9da3N8nbLYVXqfT21zXbv9uJw3MdWH2B+hS81XbeRU9kK7/RtpB2OGY40YIV3nWzv+GG33LKqyQ7Yotd4O31frZad9e1bZ29btFsOq1dV2xwOSwMDK67wRu9LrdrmSGrIdYFqr+fYXN0AOgX31LWefcllgoMlKSfNpaxyx/dpdzop83dul3bGJWWlknyekmS+48+0O32t+oJ9iy8tlaV4Lm0tL8hSLMndAw0AasPOCfpK19dUo06D0zYKzrV0hwwA0BBt1AdoeIAw6sA0rWj1StOK53LW3QNDQ9aVUU5q3M3BxapKM6b6u/2KbYu1zGzW4S1hxbfHK/4dS8382rETtDVolqhO6wuFw9Yxu9I21ZSZZduoPc//ttdda+rEdFI+ZZSRT5O9Id0W87b3/trJWrURaaN9rxOZWVOXPTKqt5hSbL0UWLP42vSvpev2ST96+V5N/NYnrRtHMhl7H1yhXMeeh6CmVrEJSrIC/YoGNZfxyA0JbbwtqjPMxY32hQ/6NXV9TOfcXHmjLetnPCP57/h0S/Uz3ORN/ysjvWKzXF4oZDUuK6UPC4WqK68qtsNGHCsbfDx222mL0z6+02NSeEtYH3zdbt32kY0yZ05YWO7teUHX3zSl8JZzFpattp1Ce6uiyanqPU65+ZTe9v7dwB+qNDhYkoxczprxvPCHakSdUH+phHI/jso4uLgN5tb6ZZxVcl2xDQ8ATs6d3cZxu+Z0f10fsq4vz6VVdvOR9Qbr9fXs341Sz2vVbbh7tweH4z52+wDZdLpiLqVSheXYRlr7mOFYA1b46VeH9MIH/dpgpuWpcJzJylDG69fpV6/yOFPF+GkrX+NlX3XO7voObQzJ3+1XejZdNLF5niFD/m6/Qhs5N2qkqtpmr3fFG/RXvS85uLDYym2OpLpfF1jt9Rwbq7sYAYToANWMfbhtvMQxMi+2poM2D8jz5TIHMtJp90vbI9KumDQbWCzTPS1tG5JOu1+ZA5ctLs+a1rZR8dpXTpIh7RmSeges44GbBxoA1EYioVw0KqPgBD3n98soPUFvRAfcaRsF51q+QwYAWFCvazor9gHUUn0AO+ODcDsn01vCvVIJ6YGg9GC/tHuH9fhA0FpeIrE3ocjOSNGNhZKUnk0rsjOixN7y97hVeEtYk9FJjV05ppHwiMauHNNEdGLJG6AjkfLNPT85Q6J1/mxn8rNElc6al58lqsI2Uo1EQgoGpf5+accO6zEYbOPfdV44LE1OSmNj0siI9Tgx0aT+X5u152ElNGkENa5+jWqHxtWvCQUVVptvVJ2qlRuRNtv3Ok1yKqnp2Wnd/wspOCn1TUuDGevxxEkp8QspNZtScmp+/VU523nHnoeg5hqViO+RGxI6+5aINpjFG+0GM62zb4nokRvau5/hFp7fsLcii8rl04dJi+nC8iqlD3NaXlVsh404VjbweOy20xan+141x6REQrp16ByZM8UrPzvr061D5xS9h4ShWE4VTU5V73HKraf0jvbv+R8ql7MCJgplZVjjETX6oWzNeF5QJ+vFOq081FcqoVzyUuVKrivm5qaVS15afF2RA4CrOG7XnO6vHq91o6xVoOTT559vHebGowar17Vqdm8Xcjju46QP8KR3n60qFJZjG+kwDVjh3sO9mrreOs5UOreVpNT1w/IevorjTBXjp61+jZd91Rkn69vr8Sq2zdpmjZJtNv98eNtw+2YW7zCr2pccXFhs9TZHUt2vCzT0eo6De7KAVlXN2Ifbxksca9A9daiDtTYPyPPlfOvmy592vzQUlK7sky4dtB6HTrSWF5aTnGUpltw70ACgNhIJ5SKXKleyn+emp5WLXKqGD5g7baPgTFt0yAAAkup7TWfFPoBaqg9AgHA7YKrY1ufgYpWZNRXdFa04c21+2dCuIZlZs65VrqX8zK+Dpw+qL9hXcWBtpckZJGtyBrN1/myrsuPj0uio9Vip8ivOEiVrlqhVru9O7wvlZ5YdHLQem3Zfazu15/MblVGyURmdslE5ZKc5aDgnlXJxI2JmTY1Pjmv0qVGNT45XPj62077XgTIHFtdLVtJDB6V7X7Ues5XK5Wc7L72RIc8wpECgaLbztjwPQdNUsQk6Zh4ytfE26xyytNOfz9oSuG1I5qHFjbYd+xmuMJ+ZrTxPoyUnQ+oKlGdmm08fluvtLS7v77XSipVGCOTLn1BSvrdyecfbYSOOlQ06HrvttMXpvlfNMan4PUbJe4yy9zSinUJry2c4LGmi5PdXbqKqfY8TjTylP/SaqeF7H9ef/f1uDd/7uA69VvnYWM2xNaGwIoorreIfalp+RRRXQqv7obJpez9AUbl6rzzUT9bU3CNXKZeTPCVtusewjgtzj1y1eF2RA4CrVNWuLXUO2bvE/hoIS6G41FWyf3f5reVk2WmKelyrZvd2GYfjPk77AE+ful6p7uLrYkVfL2mq2yqXxzbSYRq0ws+5OawffiiuF73Fx5mM168ffiiuc25exXGmivHT1VzjdcsYDvuqfdWs7/CWsOLb4+rtLt5m/d1+xbfHK05wjtZU9b7k4MJiW40r1fG6QGF/xiNTF2hcl2tUF2hcHpkVy1WFAEJ0gGonFnXTeIljDbqnrpHcct5ZqG51mh9DLZ+4Lq94DDW0MSR/t9+avMWTlU58SDr9XuvRk5UhQ4HugEIbCw7gDrMUc+8Q0MZMU3NXz4+XlLzk0fx4yf971WIjd/550rErXJh9vdcqVy2nbRTsa6sOWWezde/vamRN6aVxaXLUemyh80bATeq6r9b7mk46XdtyTUaAcDtgqtjW5vBiVT5L3lJyyhVnyWsTbTdBm90pGBswSxR9IRdpl/acjcoRV87I6qRSLl7fib0JBWNB9d/drx2JHeq/u1/BWLA8A2a77HsdqmgGWDvlqpjtvO3OQ9BUjUjE99SdSZ1gTi/Z4fcop14zpafuXNxoO7WfUXfzmdkMqSxIOJfPP7JEZrbEFik4lFPfldLgpVLflVIwmlNiS+WvumH6BB1xYLf6NKZBjahPYzpidrdumD6hrKzj7bARx8oGfIcbT1uc7nvVHJOcvoeEobCjmgyH9cqKKDXulP6G2x9R1/qXdN3gGbrjL87TdYNnqGv9S7rh9kfKyjrdv/NtVEJhBTVZ1J6fqAndb4RX3UY9uc/eD1BWrp4rD3VjvjSurtdeKQsOzvMYUtdrr8h8adxawAHAVapt1xIKK5grbkOCuYmlJxgIhKWLJ6ULx6TzRqzHiycIDm4z7N4u43Dcx+n5/IajexXdZv2/NEg4/3xom1Uuj22kwzRwhZ9zc1jHz03q8c+Mafc1I3r8M2PaMDexuuBgqarx02qv8bppDId91b5q13d4S1iT0UmNXTmmkfCIxq4c00R0guDgNlPVvuTwwmLbjSvV6bpAvj9ziRKaVFDj6teodmhc/ZpUUJcoUVSuKm0YQAiUWv3Eovbe4zptlnnRTeedDanT/BiqpfQC5vzzgjFUr8er2LbY/KtGSWnr+fC24eLENA6zFHPvENC+zIfG1fXSK8vcQyN1vfiKzIfGrQU/3y1dscJB8D2mVa5aTtso2Nd2HbLOZPve32rVMyMp0EHquq824prO2n21LddkBAi3A6aKbW0OL1YVZslbjt1yraKtJmhzMgXjKmaJsjuDH30hF2mX9pyNyjZXzsjqtFIuXd+JvQlFdkbKbshPz6YV2Rkp7nyEQpo71q/sEjOTZmVo7til9z03zuLaSYpmiq2g4kyxDmc7b6vzELhCvRPxzT1rb2MsLNep/YyGmM/MZpRkZjOWycyWP45NvZrWQydK954uPXSilHr1hfLjmKyAtVuiZ+u12V49pD7dq0E9pD69NturW6JnVwxcc7QdNuI8tQHfUXja4jFMXbBlXJefO6oLtozLY5hNOW1xuu9Vk1WjmuMYCUM7k9NZPavJcFiPrIhSY5qpfFtrzmwoWm7ObKjY1jrdvwvbqKy8Re15Vt6atFFPrw8ppeX7PlMK6OnSzPZS/VYe6uaZ6XHn5TgAuEY17Vr+ks5UurgNSb3gXf46k8crHd8nBQetxwqT16D1sXu7iMNxH6fn86GNIf3oHL8u2y6lu4vLTHdLl22XfnxOybUysY10nAaucO/hXp0x1Kfz/mFQZwz1yXt4DY4zVYyfVtM3duMYTsfvqzYzu6zmmr7X41VfsE+Dpw+qL9hXHGSCtuF4X3I4Hur6caUqBjdNQxoPSqNvtB7NpRI+OhAKSX90bEJxRdSr4t+3V2nFFdEHjk2s7vYItwcQMtCMGljtxKKVxhpa4raeNsq86MbzzobUaX4MVSVjqFpiDDW8Jaz49rh6u4vL+7v9im+Pl0/q4jBLcdvct7cKdc/UCNSBndOpZ/5z3NZnLZQ7mJHeImlI0jElhY6ZX/4Wre4Y47SNgn2u75BhJY7u/a1GvTOSAh2i7vtqI67pvHl9+bG+1DHz5VrAYc2uAGogP71lJGJ1QgundmOqWPdzeLHKcZa8NtE2E7StNAWjYVhTMA4MWPtslbNEJRLW1xRepPP7raaidDCLvpCLtEt7zkZli9PmwLWVcuH6NrOmoruiylWYNSg3n69xaNeQBjYPyOvxypRXUcX0WUWUlSFPwfvyN84PaVj/JK9KV4WT9hb1kZ8pNrIzIkNG0XpfcqZYyVpBAwPWqGYmY51EhEIVd7i2OQ+BqzjYBB3rOtnexlhYrlP7GQ0TCEu9A9YFqYMZ6/x9fahi8IXT49ih10zd9pGN8yVK54HzSMrqtr8J6O/+1NTha4q/z/Z22Ijz1AZ8R/505JKzEoq9N6rAsYsH8NQrfkW/GtP9Pw439DTV6b533PGmJK8uUUIxRRUouHEuJb+iiul+hRfKSdUfx+rZTsF9EnsTiu6KFl2493f7FdsWa4lMSfVuQqppa53u343oWm3otfo+8RX6Ptf2sqO3g8yvpdOqKccBwBWctmuuvM4E12H3dgmH4z5Oz+cXrpXNRvSvp+b01ucl36tS5ijp+5ukrMdQvNK1MrGNdJxWXuFVjJ8W9pOXky/n5mNrK6+6VUklrIwRhTeFdfmtzHMlwSNc04cdjvYlh512V2+DVQxu1uu6kVemYrIywZRfbckpK0PDGpJXA7LThlfk5gBCBppRI9VcV1wYL1lhrMHVt/W0SeZFN553NrRODsZQJStIeGDzgJJTSWUOZORb51NoY6jypC75LMXJiKwAvMI/qDxLcdvct1elVh8nQmeyezqVOcrmeEm+XP7Y8RZJWyU9LWm/pKMlnarFocLVHGOctlGwz9UdMqzE6T1Tjq2YkdSwMpL2DrD/Acuo+74qNeaazlG90nslDS9T5r3z5VoAGYTbRcdPFdvCHF6sKsqSl/VIExdIT11uPWY9lbPkuZ2NKZwKJ2irlOmpZSZoczptYxWzRDmdwY++UGPYnvi1ke2509lobc7KzUZljysT71ZTKReu7+RUsmxGokI55ZSaTSk5Zf0dyaT0hVfCiiiutIr3vWn5FVFcn38lXLYu3DiLa7VafRZQxzPF5tnMgsZEsaiXeiXiO/3qkF7wLp8dMO0N6PSrFzfaqrJxV6maCfHbYhJ9m5nZnB7H7rzvKZkzJ2jpSzwemft7ded9T1V81fZ2OH+emis5T831Ln+e6mjd1flc2OezgoPjQxH1HlOSkeJ1acWHIrrkrERDT1Md73ubkrpk7eeWzapxydrPSpsWT1xWcxwjYWhnqHpWT5c1zvVsQgrb2srZu8vbWqf7dyO6VqGQ9CN/WJct0fe5THH9OBBu2nmtyzaplufd0KfUa1K20vi2rOVTr1nlyt/MAcANnLRrDb/OxA7bsti9XcDhuE815/P5a2W+o/166ETp3tOlh06UTjg6sPy1MrGNdJxWXeHVZNnZlJS6U5KyS7wnK3VPLfSnXTmGU6BVV13VHGZ24Zo+7LK9LznstDd6G7R9el7F4Gb+utELs9O6YK10+VHSBWulzOz06rPBJJPqemV6mSvbOXW9snRja2t8s8EBhPVcF43U6mPHnaaa64o+nxUcvOxYgxo7XuJYm2RedON5Z8PrZHMMNc/r8aov2KfB0wfVF+xbPuDAYZbiTr0P+//P3tvHx1Gdh/7f2ZEcUEB2cI0la9eWQxowXCfO5SXCsLHcvNSkKYK17FomDeltcm9CEyR8wW3a3jTJTZsWE7Mi+Zm2aT+FJlgOFutAm8RNQiR3wahAbp24YNIGJEtar41jYgsQiaSZ+f0xO6t9lebM7oxmd8+XD5/1js7uzss5z3me5zznedLrRGdPZMUjj59Nlqf6m8R+3GUK6X6dHxF1St3QzljjnB4BRhvNdkD2HBPA3DW8PvUagLLNMaIyyuf4pt9Kp0BFIxozJYwXFUklkhqg5LFqRzfywqezLAwbgtBDfiXhizCPb/C/XWkhKwhXEzWbKray0S4Kc+pskKbGBIFAfrSWriskJ4I0XRRGZTbz9+bPPQQHozARmm3cOIaxqYfo525xnmnBa2ymcLIStD30lzGiv5tf6ann673c8kcR/3d30bSNglminGTws2yhRKLw5xTF/Lu0hZwjnPjVC3kuelICWbllp7KHDwvvOjspHz7v5Kv2rsNqZ13OASI8Sgdh4jSTJEkzccLoqYzUmZftxyyuTqmWLKBCmWIFqfFEsZIKRF2kMrqjl6ZdxasDju2I0rJottM6rsYtiJOE+LWWRF90Hnvx+KSt9nbbzUWMCHcYHazOmCuHjTD3olLoUTh6di7qwuHrNN7+e6mKFDlrQYGAga4rfOX3emi6roSKFIKIjr3TryZsVNW4g8Ovfm32N+Q8JpkDx1k9fSqc3RIhlgydr6JGpqwVHd9emFaz8iDCo0YH12fI8ycIoysq/dGFkQc+7VIVTXhVO594fSl/s/gMukHW3GdtGv7i60u5f1X7gpyfxB525ZqnfiY5YCWS0hBc93Gqz7vpK5NIFhwHVXZenkzCpvvg4X7M0N9MqzoVIryph5cntwA+XcOpVRxUdpG+EEnZETTaveyDttVzB4ublt/opjcb9C6DUP3sR8amoee0UVo1mBKEre31TWtzx2SCwnJEMf9ehkBPN5+Fl1TL2nEt4cSvGF6v8Xa1G7Tiaw1fUXtoWu/deokwVVJ50Y96px/PqSQEqxTXWhx2ep3o+ZvgYG/BeOSSq7/VOiJxl0j3qx1E1anw6nY+EVnK3zxwpphHgC9GlnL/6nbzjZdzjKiM8im+6rfSKVDRiMZMCeNFRVKJpAYoaaza1Y288OlYc/5kJ1xpwAvAWWAJcBlmkEUF2JUWsoJwtVFzqWIrn/iTKp/6h15QzM3Amei6Agp8+h+ixJ/MeJbHIrC/HyZysgZNtJjHj1WIFSiYETNydZFKTxeZlZ4iV1dApjInaRsFskQ5yeBn2UKQnzDJD7aQcFYp36ShMnGc+FVUnotct+hJCWbl9n2n8gk+LLzr7KR8+LybL7R3HVa7zMvRUTlEO/vo4hDt6c3Bue1KyZgqKqbczNDsuFqcTxHKFCuI00SxPpuWqoqavbc2M8u23R3h6bv6Oalmd9qkGuTpu/ppuzu/0zquxm0TJ3qRz5Pou4LoPHbJqgZb7e22K4b1LEYT2XPl2Am14LMo6dm55NtQX4mzYsl43uZgi0DAoGXJGOor3mYCFRl7l71wmtAbv5yzqsbKN97gshdOZ/9Gah4LBTU2rBlk27V9bFgzyMqQVs0JzyU2cJTV0+fC2Q0RcsmqBlsVNXJlrcj4zjatshc3rPflMK0sedAcDGTJ8+ZQYMHkgc+7VMWiBlRu2Pi3bElCYib7b+MzsCUJmzb+rQzqqgDsyDXP/ExywEokxRFxVAhWB3Hql3LTVyapTXzljxMcR80XNsPlB2BrJzQmsj/TOG4ev/xAwXWDufB1Vb2FQLAqli0cVnbxsvibr8ZGNeHBjbW9BpdhtBs566FGkfVQL/qgkHruYHEzPhrnam2c/mZoySlB0lIH+5vhKq2Eyk0Oha3Q+qYV6AnkVxkt3+YOt5+FV1Tb2nGtkOlXVAPZawBqwJRruX5F9XCcFdrcFbxbtDHUw973QyF8XHnR7hzjR73Tj+dUMoJVimspDjs+Gmd86Gp4uJ/ARBMbGGQbfWxgkMBEEzy8n7Ghq5zP97WOYNyldL/aQ1SdUgMqN+z8W7ZshURjdtvxRtiyFTbtzFkv8XKOEZVRPsOX/bZGK8JXA6IxU8J4UZFU4gjpX6ssHI9VEd3II59Oes6/IAiXA+sxXy8ILbhdKYpiGIXyp0j8xMTEBIsXL+bcuXM0NjbO/wFJRdHXB9u3w81Xxej9SHZl3NGfh+j5epQDz0bYu9f0N2gatLYWN26srH/Dwz73S4heiK7BY61zLP6lMkDcOOxv48i67vnSNhZ6gLo2b5Yoqz/Nh9WfMimUwSkUMp3EC2ULCWeV8lUaKg/Hq8h1ezn2/NipfEQp4sCXJ+Wj563pGq29rSQmEgUroSkoBBuDDHcPowZUR5ftVN6Kiik3MzRb96nYhpDc+yQx0TT7iWJ9Ni1VFTV7bwUzywJoUxpH98SZfDFJwyXNrL0tjLpo7jGt6VrZKww50YuqxvYRRHQem5rWaFh2Cu1cE4XzwOmoS5JMvtzEonpnN0r0Wfj22Y30wWEbE/j6vebim8fYGXv6Qw8R+PCH5/0u/RvfIHDLLdkHx2IYz3ajvDH7YIzzgyhXFZchkuqn72gf22Pzj4u9kb10ra0mx5QYU7+c4lRDKy1GsoikVRhXmmmaHGbReYvy/i4yt+68b4jdn12Jdm5F+pi6JMGOz49x9+1tZbme2LEYt3/nDhJHV8NrzXBBkpa1w9z3wXs9rwRTo13KU2LHYtxx8HZWTydoViGpwUh9kN2y8k9V4YmfSQ5YiaQ4Th0VNtZ9MhHxS0kk5ca3/jib4yjL36IrcDyc1oVZFUcJGCWvG9Q8DnyXtijRn+O27PTt2Kh0PLixTtbghu7bycrP7mbFudko1cQSlbHP76Dt9rsLfsatPiisnjtY3Nz3k4e47t8/TEsdBZMu6oaZgOrwu77Btnfckt/A7kUICFvH65sFZVTIDCQt0TfqxbPwArl2XPkM7Y+x8nQ3K5bMPsMTZ4OMLuulbUtOP/dpP3SMoG3lNiJzjB/1Tj+ek8Q9Hjqyjw9vuI6bJ/6NXu4glJEkdYwg3dzLgcZr+Mahw9yybtsCnmkFIhh3Kd2v9nEct3csxh3fuZ3VRxM0vwbJC2BkbZDdH5xjvcRnc4zf8H2/lQ7VikM0ZkqYtGyepyKp3/ejVBnSv1Z5OBqrTvekuOjTycKjOd/N/aFyg3AFINIB3AjkXojfqCUGB2HjRvPfAUUjfFmc5iVJkmebib8QRjfMezswYCYjy2w/F1b7TDzRc+3+iOiFnBqEx220f++AmUHJz1jpkiDbi2Zlli0hO1FWf0IjTJxmkiRpJk44XQmzUP8Af9lC1m3KnaWK3ibhD7hPKePVNqLX7fXYm56Cf9oD4y9C8BL47dugPj9Y2sJPfdALXBQHC3NSgg/QTZ3Cym4MZBkfSiprUG61LtHLdjK+RYerdQ2KbhA+Ttox+cQq0ANKydU8B0cG2fjg/BcxcOsA7a3tjn/Hz7jaB/03LVUNNXtvrexpeQ6V1IX7PFuZE7npiS7lJQLzpOg8tvO+IXZ1X5N6l7l1TQfgrt6ni24q02amOPrcHiYnXqSh8RLWXnEbal22vib6LHz77KrBrnR6cytchkjcQ1gnLHWAV6rRV+p121xIsOR//oaFJ1ACesk2QNZv5MiDYnOM2/h2zqgyqsanX6kyxCNc9zPJASuRFKZmHRWSWqJaurnb6wY1jZt+Bx/7c6plbPgOD26sE9vY7XU7UYTVcwf6/JEfR1n33B3zfuTIFfey7p098393IQSFbUnrm04CPW3YoV48Cy+Qa8fu46pbIzUXGxhZdZUMS7LlzsU+7YfVgKM5xod6p+Nz8qn/bmpaY88jR3nx+CSXrGrgts1rHSdWrjai+47wr10v0Y+pz2evNJsPvJN+3tP3Vnq2rcv6rE8ft38QtGVEY8lrmZLi6KtlvcQnSJVC4gaiPjxh0n4s8xdmqZH4GZ8lPpD+tcpFeKyW4ucVTbjr4/nezQ3ChQoeSCqU2LEYrb2tbHxwI9tj29n44EZae1uJHYvN/2Ef/UatEQ6bGS4UBXRD5dCxdvY91cWhY+3ohoqimAUYw2GzfTJp73tz28ViZpaejRvNzEkbN5rvY+V8dCI/Inohb9hsb7fdQhKJmNpKS0v28WCwZC1m/XUa6uIT3Ew/I7QyyEb62M4gGxmhlZvpR12SYP11WsHPq6pphHV1ma8L5bDRNDMTTKEUFtaxnh6znbMPeIPT8WobJ9ft5dgbi8G3L4Ff3gG/9lXz9duXmMcL4Imc8hkuioOFOSkBIeK2ThFZE6F/az8tjdnXEWwMFnQQiF525vxdiNz5W3S4arpG98FubnreYCQKgw9C3yPm63AUbn7eoOdgD5ruXK4lX7U3vu22qzTc7IM+nZaqgpq9t7pmZkErmLkwdexHPWY7n+JEL3Jdl/ISQUVHdB67+/Y27up9GnXxyazj6pLknJuDh57ayam+BtY9dwfrx77Kuufu4FRfA0NP7cxqJ/osfPvsloXNTIMUmcBRzAyDy8JenpUYKSXEKHIJhkK2EgJVIUMk7hFeGSbYGEw76HNRUAg1hgivLNExBZVt9JVy3WMxMwvq4xvNqlePbzTf59jGlg1gYEBAh9WHYO0+8zVgjs9SbYCs38jBOlbqb4ji2zmjylADKu2t7XSt7aK9td03i19CVLIM8QjX/UxywEok+dSso0JSS1RTN3d73aBmcdvv4FN/TjWNDV/hwY11YhtnfkYPwKHVsG+t+aqlIu98b0+LLm4C72hcZus37LYriKCwLWl9M6CaAaatXebrfLaxTTvUi2fhBbW+duw2rro1Mubi3F6lFJuLnaw1SObFqf/Vj3qno3Pyqf9u531DNCw7xR1d6/jqH63njq51NCw7xc77hhb0vPzCxdNX0IspQ3I3FARS/TZKDxdPX5H1N58+bn8hGHdp6Qo3XxVjpLeVwT/dSN+ntjP4pxsZ6W3l5qtiWe1qmVLUqapYL/ERctlA4gaiPjxhQhFzE3BDjqLTEKz+zcE2Yxe8QvrXKhvhsVrKnhQBn04t73mUG4SrBGv3/fhEdrntxESCzoc7y9KZvfiNWkRVobfX/HeusWK9j0Zn91g1N9v73sx2VmaN8Zxq7ImEebwsRrnoj4heyPk229ttt9BEIjAyYqZF2rvXfB0entOjp2lmtqW+PvO1kLJzOBHnxitupp+ttJD9LFpI0M9Wbrw8wuFEvKyXU27i8fyulIlhwNiY2c7ZB7zByXgVwsl1ezX2rAxLkznnN5kwj+cYE57IKZ/iQBw4w44QyTypl16ER+6F3k+Zry/+rGwn5ZVOEVkT4cVPjXDvpf/Op857knsv/Xd+9qnhog4CkWchOn+LDtf4aJyrh8bpfxhaJrLbtkzA/ofhqqEx4qPO5VrzhfbGt912lYTbfdCn01JV4Pd7q+kagyOD9B3tY3BksHzBQKfj+XNqFgZMjpntfIoTvch1XcorHCo6kTURRrpHGLh1gL2RvQzcOsBwd/F57O7b25g8vZx7+47wqb88zL19R5h8uWnOzcHXvLSLpkB2P20KaFzz0q6sTcKiz8K3zy6gwpWpCVwHngcOp171VJsrowuaGXNeUkqIgoKRo4QYimJu8sxUQqAqZEgmrsnaGkUNqPRuMsdF7iZh6310U3R2cdzpAK90o8/pdQvYxvHReJ5+momBwdhEaTZAKb8hYlKK4Ns5o8bxnaytdBniIa76meSArVm0aY0j/zLI4b19HPmXQbRpqX+l8bujwgPc0hEk/qHaurmov8WzNZxKxm2/Q6Y/p8C2J2BB/DnVNjZ8gwc31olt7IXNLoqwep6xuFnIrwjk+RUDucHSRbDbrigCwtaz9U0BO7SUZ2FroTkXlxSwWl47dhvX3RpO5mJVZeiuLgxjdnnEQscUt0N3bpOlQAUpZb7wo94pdE6pjm7kdHRjgf13O+8bYlf3NWjnmrKOa+ea2NV9TdFNwr7zj7rI5WeeJMR40c0EAQxWMsblZ55MH5PuWpsIxl02N5ubg/t7OmlZMp61lt2yeJz+nk5uviom3a+Urk5J5seuHPR62cCXvkhfnpT/EL1Noj48YUIRuHHErFS6fq/5euNw9W8OFojr9wLpX6t8hMaqB/vBan3PY91Cn4CkdObLPKag0HOwh45LOxxnuvHiN2oZK+Nad3f2JBcMmkZKplPFynyUSBTOlqEo5t/tVixUFDOzRkdHCcaQkx+5bj0sVeHMHBrer6lmO5jNDDyZoHD2YcX8u58rPeViVdq0QSxWuH/09mb3j5NnE/T+x9NAfgaIAAY6EP2Ppzl8NlHSqbuNcFYpn6ahEh2vwji5btGTcjL25s0UrpjZSVs6IKB6I6d8joA4cIZdIWIxFjOf4S/H4deAXwLf/rIZgFGiAeylTmFetsr4+Lr0sS/Pcdkg9ixE5m/R4XrybILeg+a/8+W5uSgXPQiHP+NcnlvV4hITiYLPQ0Eh2BicrRZXJXjRB306LVUFfr63sWMxug92ZzkXgo1Bejf1lu6cLCV7mk9wohe5rkt5QYmKjpW91i6L6lV6tq2b/7Rmplj5s90QgEDOgllAAd2A0M92o139RdS6RcLPwtfPLhSB1+6EP96dbY8uVeEvdlSGsz+lhCg5SohSSAmBqpAhFq7K2hrGyupZ6N5GN0Wz762TAV4NRp+T6xa0jb2o0uL0N0RNShF8PWfUKL6TtdUgQzzGNT+THLA1ydD+GCtPd7NuSUomnIETXwsyuqyXti1S//K1o8ID3NQRJP6hGru5qL/F9TWcSscLv4NV2eVH3dlBjA1Bc3PwAvhzqnFs+AIPbqwT29iPlVUdqeeRCEN39rNydzcrtNmxdCIQZGxHlLbcCTwVK2BMjhes4W0ASrkqeNsUtp6sbwraoU6fhe2F5kxcVMBqde3YbTxxaziYizVdY4vWx9VbofcghDKSlo83wh2b4BltH8P6l2QsqAClzhd+1DttnVOqoxtGgSrWhilRlAXw301Na+z+7MrUu8KRN7v/LMQXP6mxqH72vHznH3WZdyyz12+tdtJdK4Bg3GX4Oo23/143PGMQ+DrwymzLwEWgf9jgK7/XQ9N1HUCt31zn6pRkfkTkoJfLBr70RfrypPyH09sk6sMTxqpIWgsIxi54hfSvVQe2x6rL+8HknkdZQbgq8Ht1CYk97GZcc7tioSOc/Mgrh+F350n/8mHNbAe+zQzsBSIZ1y574TShieLCPQCsnDDb+ZnMbFEBRWPDmkG2XdvHhjWDBBQtv51Pq1e4nqnMyXWLZgZ2MvYEs5N6nQFIm5niyI+jHI5/miM/jqLNTJXni0s6KReziImmbXQ5S1RJOoXAffIqW6Xd+Vt0uHohz4WrxVUJXui1Pp2WqgK/3lvXM495kD2tFOyIZyd6ke+zvuoanBqEkT7ztVDGVJ+mOjz63B5WqFre5mCLgAItqsbR5/YA4s/C188uFoNP3JOfrOoV3TxeKSmtRdK2+1yG2KXWszy6je2snk4GuE9loRBOrlvQNvaiSouT35i1rbIXURIJoyy2la/njBrEl7K2GmRIBhWdSL6EAVtLVVdKxo6d4RFD+2NcM9VJ0+LsMdjUmOCaqU6G9kv9y7eOCg8oxf9a0bKwBqnhbi6xi1d+B59VdpFjwyU8uLFObGM/VlbNVM/VQHZMhRowJ9dc9TwWg/X3RAhpI7QzQBd7aWeAVdow6++J5M/fqVgBBYXcLV9mWKXieZyOJ+ubgnaok2cBiJcLdXkBvFbXjt3GE7eGg7nYWjM/cDm09kD7rdC12Xxd3QOxy1nYWNAKNRr8OF94QqqjF1l2NI8vgP9uzyNH0c6tYK7IG+1sC3seOZo+4kv/qMsEWuz1R6tdlblr3UUw7lJ9Jc6K/xon0EvW5mAw3wfug5b/GkN9Rd5cC0fV133kf/UjonLQq3U+X1Yu9+VJOcTFcVFNt6miEYxd8IqS3ECiNkOF2hhVhcv7wTzf8+hAdmqau3qy3CBcBfi5uoREDCvjWleX+VpMIbYyH7W0ZB8PBs3jpVQsdISTH3kjCVcDPcBFOe0uSh2/muwsh1Zm4IacC28ImscrodKTIPNlXAMz45qlo7xDW2bre+22WyjWX6ehLj7BzVf1M9LbyuCfbqTvU9sZ/NONjPS2cvNV/ahLEqy/LnXhVhqqXAvTQlEgFFqQ6hUi41UYp9cdiTAUvZNkY7YacGJxgKHonfknJTr2BLOTepkBaOipnZzqa2Ddc3ewfuyrrHvuDk71NTD01M7Sv9wpsRi0tsLGjbB9u/na2loey1dUiMybJQozS1QJDgDHOoXAfRK97FKxM3+LDlev5LlVLa6lMXt8BxuD9G/tr8rsp17otT6elioeP97b+TKPAfQc7CktAN7KnjbXsmq5svQLIjKNOdGLXNWlSmEsBo+1wuMb4fB28/Wx1vxEGj5NdTg58aJwO9Fn4ctn57WS4DZ2nQg+liF28UTWStJZPbvWdtHe2l482E90gPtUFgojet2CtrFVpSU3ANNCQSHUGCqpSovob8yKzVTW4AwMQ8HAKIvY9OWcUYP4VtZWiwzBXReQZzgYsLFjMVp7W9n44Ea2x7az8cGNtPa2VmVAZcnYtTM8QJvWWHna9BPmJhYKBAwwIHS6B226xvUvPzoqPKAU06oqZGGNUaPdXCKCl34Hq7JLa5f5uoCb1OTYcAkPbqwT+9sLm90JkQgc/maM0a9kx1SMfqWVw9+MZannmfO3jsoh2tlHF4doR0tVoCs4f6diBZScWAFlAeN0XF/fdGCHijyLLOz6eD3ybdfi2rHbeOLWcDAXZ66F6wE4tBr2rTVf9YxQogWJBa1go8Gv84XbzIwlytquXLx4fFKonW/9o26T0r/y6z+bGGTrX1XkrvUGkbjL1xLwj/N83z+m2knS2FWnAF/5X/2IUzno9jqfL8M85j0po3JiT1wcF758drWKYOyCVzh2A4naDBVsY1QdLu4H83TPowPZaXXDD32o9J8vRp17Xy3xCr9WlygJXTMzULyRNLPXLQsveGVYTdeIj8ZJvpqk+cJmwivDC5oVMRKBjg4zg0AyaWbGCIfzjRtPMtc6+RErK+HVwJXAC8BZYAlwGbPpC3KzHIYi0NLhu/7hFiIZ19rbIZBrYRXBbruF4nAizo0f/UP6r36G3I2KLW9J0N+zlc5nruZw4q9ob22fTUPV2YmhKCgZ1oShpNyuC1huxu54FSbjulGUbCtqjvRbsWMxOn9xD0q3Qfg4NL8GyQvgiVUa+i/uof9YW/7CjsjYE8xO6lWG7aGndnLNS7vy0qM0BTSaXtrFENB27d2l/YgoVnqsXAvYSo9VxENie04SFSIiWaKWt9u5wjyydAU9AMfD8FozXJCEVXEI6PntBO+T6GV7gehw9VKeR9ZE6Li0w1d6jpuUrNfa0FMdimfHaNMaR38YZ/JMkoalzaz9jTBqfXU+v1LurZV9q6xzMWKZx9pb2539iJU9Ld6JubifKQ9Lz57mFCfTmBO9yDVdyiljsdSzyLnwyYR5PNNZ5dNSIg2NlzhqJ/osfPfs/KgkZOKWoPKpDBHBE1krEUNkgPtUFjpC5LoFbWOrSkvnw52pyjyzY7VcVVpEf2NWbBZZkTOUsolN380ZNYhvZW2VyBCHLiB/IjBgrWoDuQFFVrUBGWCegYid4QFHfxhn3ZLiMiEQMGhZMsaRH8ZZ95vtnp2X7/DaCeQTnJpWlixUDI0NxGkmSZJmnhgP09mpVpYsrCFqtJtLRKgCv4MTShobPoyHcYQb1+GB0HFif3thsztiLEbbdCfGkmwdsnlJghXTnTA2q0OW5Br1YZyOq+ubTuxQgWfhCA9927W2dlwSNuSgJ24NB3OxbyvdeuhAcSMW1Lfzhct867/eoLOM7crFJasahNr51j/qNin9S+nsxGD+uMsqcdd6i11d6sen8ysH5/JKqp295X5JJj7zv/qRUuRgJAIdH9I4uifO5ItJGi5pZu1tYdRFpc95pajCru39mPekWNjYE7u4PC48D9FxK+amGhCMXfAKR24gUZuhqhZpq4RQBK35Qxx9bg+TEy/S0HgJa6+4DbVuUUlf65md60B2FuuG5UZuEK4CrMxjiYlEwawtCgrBxmBZqku4+RtpxmJm9cLMDUoNQdORtUDKd+xYjNu/cweJo6vTm5ha1g5z3wfvXdDgFSvz0VxYmTUSicICRVHMv5eUudbJj1jZCycTEDDg8rwPmX8vlEnYygxcAwhnXLMyuiXGUQpl3FFACfo/VfHJiQS973oaoGB1At2A6Lue5vBERja0SIShO/tZububFdqs/DgRCDK2I0rbAitvdsarI6z0W93d2ZZUMGhqxTnXnZnly0hlAc1Ewczy1XFpR74hbHfsZY7vgpVos8e3JULGE4bZSfOaG4SCSkndVpuZYuXPdkOgQJ9SQDcg9LPdaFd/MU/BdM1JMF96LEUx02N1dGRZN7FjMboPdmc5Y4KNQXo39ebPSaJCxIMsUZZOMT50DRyMwkRo9o+NY7Cph1DbM7M6hYP75NdsldZwveN2jdWJ2QC4kZYwu3vV7OFaqjwXDMqwqsXVAiXptQJ6qqB4dszQ/hgrT3fPBu2egRNfCzK6rJe2LQs397npb3Nyb2Mx6O42GB9XMtob9PYqJT8LzzKPWdnTCvbBqOe2ksNpzETRoDUOS5NwYTMoYWDuDuKaLiWKrpnPoKCOk6qu+KMec4EvoHpkkImz9orbOPGTO2kKaHm6EZi6UVJXWXvFbfl/FHx+Xjw72/qaX5UEsARVvmDr7S3PpOEzGZKJnTnD0yyPEvvYHeA+lYWOsXvdgrYxzFZpKWTzRTdF5/RD2pWFIr+RSOjkZdkqgN128+Gb+b5GKVXWumYDeChDtCl3gldK0p3BnxtIbAzY+aoNKCjF/ZC1hqid4QGTZ+zJBLvtqhqvnEA+wolpZcnCm4wYvXQTYvZejRGkx+ilpydSUBb6LYlzLVKD3dxzvIhfdPU3fOx3cBNHY2MshvFsN8obsx8wzg+iXLVw8TCOcDOuxwOh48T+LsVmF8H2vJfSIY0C9f6sLWlKhg5ZsmvUh3E6rq1vitqhGfp8oWdRFn3eY992La0dO8amHMzsToqhEc5IlBMnjKGo5XFrCM7FnsaC2qVkB4p9hOJuBPFqvvAT/3r+pbybIC0kCBToTzoK4wT51/Mv9XSD8G2b13Ln4hNo55oo7L/WUZckuW3zWqDG16JS+peSo38pBfSviljy8eMGMTu61BvL7H2X3Xa1gp3n7bX/1Y8+fRv3qSQ5GIuhdnezLtOG+3J54h2cqsJuzvckbFbytttuIfBgXGQ+kwD5urCOWLzvnLgdc1PpOIhd8AohN5CozeChjSGxT0H5/MMvlyyfPbFzHcjOubphuZEbhKsAP1aXcIwPM/TEjsXY/LmH4OATWZuYEo1jbH66h0c+h68dN55kdXbyIzWaSVgU4YxrmRndFHxXSdculxmnCdUX/3tAgZX18IpxOn0sFoPOeyIoRkeWEfGEFka/R6W/rYp1fIGqHX6scqiq0HXXELu6r0m1zXTK6mDAtjv/DVVtc3Y+wNHn9rBO1YqfsgItqsaR5/aw7p096eOuOgkcpMcSrroiKkQ8yBKlBlS61P3sevia/D9OtMDD+9l23dOzOoWD++TnbJURYtysdKNkBMAZBFHoBTKeXSny3IfJVvyEY73WgZ7qdhW0of0xrpnqhMXZ59TUmKBpqpOh/f0LsknYC3+byL2NxWBzp5HSUWdDM8bHDTZ3wiP9pW0S9jTDto+y9DuuFuTm3OoFp+PZ8jUPAybHzHbL231bZketW8To23bQ9NIudCM7gYqeOsWxt+2gJSdxih+fn9A5+VVJ8CpbpY9kiIXdOcO31Qwk9vCpLHQdh74vJ1VaROWz3d84rf4EWDfvpdptJ/E3pchaV20Aj2TI0M4YK3d3sy4z8eCdQUZ39NJ2d2kXUVKG9Aq28Wu26ooTRO0MD2hY2gxnbLaTuO8E8hlOTKt4HK4ej9FPvn+thQT76aRzrJ94PFJdfoQqosa6uad44U/1JEbSh34HLxAaG2MxjPjmdPyhhTE5DvHNKOFHfK/jAd7E9XggdJzY325XVhWa91I6ZIH8j0DK85ChQ/rVNepLRO1QL/R5+QD9hYActLrTQ5tjRIskyrklGimPeBOYi31Z6dajEnPCcTcOqLVK3G9dfSHd9NJPJzpK1iZhPdWfeojyntUXenpei+pVdnxhlF3dTUBukksdgB2fH2NRfQsg16Ls6l++X/Kp5A1iLS3lbVcL2H3eXvpf/ejTt3mfHMvBWAw6N+fvlRofN4/3P1LS+HOiCrs+359/ev42Iu0WAg/GhfVMbqZw0shuejlApHQzRlaInR+f79ux7QYStRk8L2MtmQ835bMndq4D2TlfNywnimF4sQ9ZUgoTExMsXryYc+fO0djYWLRdIUdxqDE0Z+Yx0URJTn7DNroGj7XOMWBSmSluHPZs8tF0jeW//wnOPPA3qSP5ToKlH/0Ep/7+ft87cArp96FQmbM6O/mRgsZQqKozCVvYyfyqadDaOn/GteHhnLHr9IH7JHuaPvwQgac+PH+7a79BYPUt6ftUbPIsep9qkL6jfWyPbQdMiRY+H5pVSGoQf8OSbLA3speutV2l/ZjN8a3pGq29rYwPXQ0He3Mqyo7CpjsItT3DcPewY1n7xKFPc33iq/O3a/kU12/4CpChhOoKHA+nK8iz6gmUgD6nEmprKPX1wfbt85/83r3Q1TV7nybGQQ/knFMcJWAQbAxm3ydNY3J5K+edKZ6l85dLgzScSg0OXWPykeWcN3WmaDXBXy5aSsPmU47n4tnxmr1RL02qYnR6vArep8zfEJadblPMEWF5yAs5IkTlebHFSOteL0CyFb8ipNf6UU+d1jj1tVaaFo8XHq+6QnIiSNPHh1Hr8/ULt6Z7J93cTTQNlrdMcubUeRTLCry06ZecGm9wfA8s+Txf5rFS5jE/4kA8F3XwWA6Yciy4u85IHxy2ceHr90Jrhi7liUEmztBTO1n5s92syEikktBUxt62g7Zr785q68fnJ3xOflQSatiYseaM3KoJTxBGV9SsOaNWZW3V4VNZ6Dou+77clM8PHdnHhzdcZyZzKqJL0TjONw4d5pZ12xz9hsQ/OJW1ntkALsqQoZ0xrtll2tLZKwDmRTx9V39Jm4Sd6M6AYxvfL5U2M/2Qc1EWP2Sl49TOcJG036ExQSBQwK84h99BUv04Ma32PaRx3YdbaWG8iFZhVpQ6/I1htt1ifsiPdqhEUm680KVmfyN7XUZRzPcyRtIjSlmD81OJaR+ul1QLovOe05gKP7lGfY9dO9QLfV7TmGxZznmnzhTz0PDLpqU0jJ8qXDGvxpI3uIoTORiLYWw2x3eu30EBlEfmmIxdngNcjQUVxbEDxT5ZcTcFkGsNzpia1mhYdoobzx2mlzuyNv+MEqKH3Ty25FomX25i0QL4EHbeN8Tuz65EO7cifUxdkmDH58e4+/bZYhW+X4vySVynhS+XfPwWsCJKWmEbL1rckWBIKmwWIs/bK/9ryqdvYGRFRRqWVr8QcXsC98mRHNQ0CC2H5BzZJpuXwlgBPdUmoraMJ/P9iw/BNR+GV+ZocxHw9DfgklvyrkdUnLsyBXgwLjQNPrE8xt+cKb4G94ml/dx/qoSEOTUcc2MhtC5Y6ft2RG0GD2wMv6NNT3H0kT1MHn+RhlWXsHbzbaj1i+b/oBvnUop8FhCErtq5DmRnfjecAObfH+oEuUG4ArC7QRjEBLzTREmuBZecGoTHN87f7r0DnmVIf/zFQd733y+ZNwjuB//vJd57iTfnVAqe+Aic/EgNOqNFMr9a9hkUzrhW1G8hnAHAR9nTBOXB4CBstNF8YEAmeBkcGWTjgxu5+c3Qu4ysSs1j09B9Gg68DgO3DpSncoeN8W2dk9k+f+MrAXPbcinn1N/3d3QaH5+/nfI1Ors+Ns+m5THY1FN007LtoSTYcdP36fmbi5xTN1x+IOs+ZRvYFMzSmWlga7rGJ/56OX+z2HTYFKom+IlzS7n/E6ccz/2i41V7fBD1ffN/QPvBAOp729PvHctOtyjFESGDMlzDtl7rQz31yL8Msu7M/Od0ZOkA636zPf3ezenej/62x3+o8b73zv9jP3hc472/4fykrMAdoGDmsWoMWBWW59Wy4F6KPPDZom36tGamOPrcHiYnXqSh8RLWXnEbak7lYD8+P8fn5DcloUaNGWvOuHq8cKbYHnp5JhTJmjNqUdZWJT6Vha7jku/Lbfk8ODLIxj+8Dx7uTx3JT57I1k4G/up2Wf2zShCVtZ7bAC7IEG1K41RDK01a8Q1rSTVI0+Qw6iJvfCHmDzuz8f1UaTPL5zcHZfNDVjI+9DsADO2Pcc1UJxhkbRLWdQUUeHpRP21bpP5Vq4iaVkeig6y7w4Yv694B1vW0+9IOlUjKjRe6lHDSVolraMnHUQfeN3+7jT9AbX7v7AG/lZj2qd5S6TiZ9478OMq65+6Y97uPXHEv697ZA/jPNVoR2LFDPRgXmq7xid9fzt88kFrHz/iblQT+Ex9dyv1/n7OO78cKdpWO6PMuZcL3KI7LL4nGvFgvkb4K99h53xC7uq8hgEaYJ9NJYeNch47KXb1PZ23G9ZqpaY09jxzlxeOTXLKqgds2ry24Wdm3a1F+iuvMwFdLPn4MWHGCVNjsIfq8vbBjUj59Y3K8kPWNASgNIW/j9hyMC2E5+MPH4b3z27o8/gP4jffO364IIkPDk/n+1CD85UaIztGmB/ij7D7lRJy7NgV4MS7SBY6Kr8FlFThyQo3G3Fg4Whes5H07os+7xvvH0H07WfnZ3aw4N1s45MRildEv7KDt9rvn+KQ7OJbPDgShn/Y85ndD9zYIF5K1kgpGDai0t7bTtbaL9tb2OTcHd3bm63yJhHk8Fiv9N4R5I1nedmVg8JCW2oBVbKgEYGKl2a4CUFVz7urqMl9dsXOd/EhANQVga5f5WilKhkMsAyp3cScxkaDz4U5ix7IHYCRiGi8tLdnfEwzOY++LPItShIIbLAtDQ7BgIjRIJUhrCJntMJ1MdrDbrpoJrwzzsWVL6W+Glrrsv7XUQX8zfHzZUsIrw+X5QRvjO/lqxoMJ6LD6EKzdZ74G9MLtBJnSb2XsTNAMXiuAriuM/jzElH4rAPHRuLk5+OH+VJKIDCZa4OH9jA1dRXw0nvUnoaEUDpsDWSl8TiiKmVoxnOrnrybNzcFFz6kfnr856z7F4/B3ZyJ00k+C7M+ME6STfr52JkI8dRnx0Th/d/oMnUlIzGT/xPgMdCbha6fP5F23CKLjNU6YMYLpDc256CiMEiJOdp91LDvdIh4v7mwD03M1Nkb6YWRiV56fjs8ROAxgwOSY2U4CCOi1PtRTJ8/Y+63Mdm5P96V0c7cY/I+flrVdMSJrIvRv7aelMVvoBBuDVbthTXAaM+fWIsFNYC4sjE2MlTTHeEJKTy0YUAnm8Qw9NQtPDDJx1LpFrHtnD+vDX2HdO3vyNgeDP5+f43Pym5JQo8ZMPG5uDu6nkxayn2MLCfbTyVVjsaw5oxZlbVXiU1noOi75vtyWz+GVYYJtz8DWLdCYyP5j4zhs3UKo7dny+RAkC46orPXcBnBBhhzdE2dFkc3BYCZba9HGOLrH+UWI6s6AIxtf1O/sNuGVYYKNwXTgUC4KCqHGkJQhUJqd4SJtWyI8vaifkzm+yOREUG4OlgibVu9YZs+msdr50Q6VSMqNF7rU7G8UmWMMxXOfba3y0/FB8XZerOGL/oYP10uqASfz3gvKMsamZ5M856IbMDpttrPwm2u0IrBjh3qgz8dH4/xd6xk6t0IiJ3Z0vBE6t8LXWnPW8VMV7PJsy8mEeXzM4zigakFUDjqd8D2M43ItFlQURw4UMezGHZUSn1Sr3H17G3f1Po2y+DSHaGcfXRyiHWXJywu+ORhgUb1Kz7Z1fOUP19OzbV3RSsa+XIvyW1xnBr5a8vFjwIoTpMJmD9Hn7YX/NeXTn+MXvI/bczAuhOXgfw7aOxe77YogMjQ8me+XhWFD0NwEfFHO3y7CPL4hu085EeeuTgFejIt4nIYim4PBXINrOFOibK7RmBsoYV2wkvfthMNMLl+KXuTPOjDZtHTWZvDAxvArQ/ft5JruXTRlbA4GaDqncU33Lobu2+n5OTmSzw4FoWt2rgPZOV83LCdyg7AD9uzZw+rVqznvvPO48soric8zKR06dIgrr7yS8847j7e+9a389V//tUdnWhhNMzfQF6odbR3r6THbecr5zeVtVw5es/lbdttJah5N1+g+2J2VWcnCOtZzsAdNzx6AkQiMjJgJSvbuNV+Hh8tk7/tRKARUuLIXBQUjZwI1UMygsiujaaX04uX2zs1uu2pGxawcDNnVYTPfR5eZ7byi+UJ7MtRuu0KsaKmn+x97QSFvk7BV8aLn61FWtJgllRNnT5pVeoF8dSn1/mDUbJdCeCipqpm9BvK1Put9NJr2nl7c0GzrnC5umL1Plk17gAitjNDOAF3spZ0BVjPMASJZ7Syl+sDr0DoC7ePQlTRfV4+YxzPbOaHZ5mO02iVfVunGvO7cTcLW+x6iJF/O77Wuyk5RvHBEyKAM9/Chntqw1N5vWe28mO596W+7wOaP2W03B5E1EUa6Rxi4dYC9kb0M3DrAcPdw1W5YE5zGqmfBPaWnmuR6bVLvM/TUasGPz6+kc/KTkiCqHFUJJxMavXQDRgHN1pyYovRwMpFjG9eYrJVI5sNt+awGVHo39aJcfgB6VsOt7bC5y3zteSvK5QeIborKqn1Vhois9aUNIMjkizaTL9lsVwhR3RkQtvGd+p3dxJIhMFtdwMJ6L2VICh/bGW1bIiz/+AhHlg5wmL0cWTpA08eH5eZgCSBmWhnNF9v6TqudH+1QiaTceKFLJRLFwuWctZM4Jzkzf5usdl449Z38hg/XS6oBJ/NeU2ML3afNf+duErbe95w222XiJ9do1eCBPp9ex78cWnug/Vbo2my+ru4xj2e2Q9fMysEF0/Knjv2ox2wnEUNUDjqZ8P0Yx+UFjhwoYngRn1TL3H17G5Onl3Nv3xE+9ZeHubfvCJMvNy345mBRfLUWVavywAnV4Ky2kArb/Ig+bw/0NX0yMX8jgXZlweG4EJKDS2yei912c2B3aHgy31t96moFeoE/Af4g9dqLeTyjTzkR565PAV6sS3ghm2s05saP64JeoCnQfYP571xvpvW+Z5PZDvDExvAj2vQUKz+7Gyi624DQn+1Gm57y9LyE5bMfdWEHsnOublj203P366uPb37zm/T09PAnf/In/Pu//zvhcJgbbriB0dHRgu2Hh4f54Ac/SDgc5t///d/54z/+Y26//XYeeeQRj898Ft8mSvJhhvT2/3Zp+t8BRWPDmkG2XdvHhjWDBBStYDtfo2lmjfK+PvNVOgbKht1bW0rGc9cyrvlVKIQiEO5HachesFIaghDuN/9usSoOjWPkq3sWOjSOmu0WCl2DU4Mw0me+zqN0a7rG4MggfUf7GBwZLJ+SfjpOw/SZvM3BFgEFGqbPeJqprKRqIjYHXzgMz5yM0Nm7n8QvcirpvhKks3c/z56KpJMAnX7hMlsV5E+/cFn6iKOhJJLa7HjY1jlxfPY+Zdq0OmpWlk49Yxu41S5T+daBQ2/AvtfM18zRVYpzJDMTTgCNDQyyjT42MEgALS8hU3OzucF5rirIB4gUtd89yVZpZ3yX4IiwPX3LoAz3yNRTdeB54HDqVYeF0FPX/kaYE2fnroyeOBti7W+Y51TqdG+nH/rR39a+QbWlI7RvKI9w8E2GbY8QmcaqasE9paeSo6dSSE+tEvz4/Eo+J7+ktK7RbJWXnY4TYu5MsSsZ47ICdkmtyVqJZC68kM9WpvDgkmZYfQjW7oPVhwgtWSGrd1cxdmVtSTaAoK/MLRousZl8yWa7YggXfhC08f1aadOXVVf8io/tDLVeZd1vtrN+exfrfrMdtUiVHYk4rq0DeIhd0yq+CsYa5/TQMNpotgN/2qESSbnxwp96Wv1JWdtJnKM2tduq9qo2tZsHvC0xbf83fBjXUw04mffCK8M8owbZkoREzgb08RnYkoRn1cJr7Kqi0b5mkK5r+2hfM4iqVJ4O4jtc1uez1vEDcGg17FtrvuqBAu1SFeyKY3hfwa5aEJWDTiZ8v8ZxeYHLlTO9iE+qdexW6vU7vlmLKlEeVIPfwTZeBqx4IQ/8spbtV5w8b5f1tZ9MnC5ru7JQwriwLQff055fQTeXi1LtyoCdoeHZfG/1qQuCcDmwHvP1glBen3Iizj1RCd1elyhRNtt6HDUac+PXdUG3iY/G+bvWM3RuhURj9t/GG6FzK3yt9Uz2dbtsY/iRo4/sYcU5ba7dBrSc1Tj6yJ7CDVxaxxeWz361jR3ITqsbhlZoXId751vn2jdXKbt37+b3f//3+djHPgZANBrlX/7lX7j//vv50pe+lNf+r//6r1m5ciXRaBSANWvW8Oyzz3LPPfewefNmod+emppiaip/l34gEKCuri6rXTEURSGZrE+/r68v3jaRUIDZttPT0xiFdt+nvre+vgxt33EvHL4l9Rfz2KLANJZTbfqduzFmNKCwkFm0aFH63zMzM+h68Uy3dtquvxaWt7zK+ubv0/uRHYSWjjOjq+gEGH+lhZ17/4onEh9g/bUNTE2Z51RfX4+SUjLmO4fMtpqmoc2hSIq0raurIxAIZLd97DG46y6znLpFSwt199xDINUXHX2vjba6rjMzUzwlrqqqqCkt3Q9tDcNgenradttHHpkudGvZtQtuuml2fBqGQeIXCeozxlUmOjpaqm+fmDgx51gWGffztk0kIDUmFcOgPuM+TWWMVRIJyPhs2cb9XG1DEaYv/iDG6SfhjZNwfhP82nozq0bqXBYtWsTLk0nYdB91sT4UxSB7A2VqDN6wg5cnZ+VuOWSExbzjfvwx+Pe74I0E9cq0aYc0BJlZdy/6ihvzvu+xnz7GXd+/i+OvHk9n8ll54Uq+/P4vc+Ol+e1zz2HO8TmRoM5QCCjm92qGimYUUAEnEvCWKcfjXqStgsK977uXW2Km/M/MaKSgoKGlq4lkjeUCck1takKNRiESyRv3994Lt9zy23z3Jzdw7a8/xfLGUyR/sYInfno9BgG++c0pNM00IpdOX5Y1R+q6iqaZ415RDOrqTBmxdPqy9JiyhlKxthaZQykQCFAXiUBHB8a//ivTJ05AUxOsX296LzLG3Mlk5nMyqK8vLKdOJmFmxqCuri5t+7788lTBBDqKAitWBAiHTRkRXhmm9cJWTrx6omBmKYCmxqa08j2fzlFs3N97L+zb/hh3cxdBEihA/fQ0YwTpMXrp2v3baJqBpsG73w2trfDtEx/iO8YNrOcwy6dfJkkzccKo9Tqrg1O8+91ZtytN5lieS/bktrUtI8ZizDyzA33yxOwfz2+Bd+2CoDle6+vrUVIPY+bkSfRCzghFgZYW6q+/Pm36zMzM8K1v6UXnmM2bc8b94nfDm1ox3jiBkvP86pUZUMwkC9pF69HmeHZejPuK0yNQmHnHvfCV7bAX+EVGw7eAul1H3RGFgCqsR8zVNnMOL9T2paX3ctHULTADdQGNuoB5TzVNYZp6hpfuZpmhoU1pmdM9hhFgZmZWN8iUdznTPYFAgMceq6O727S1rbZWP7wxY1pqa1MIButJJEzbO9fWSHVz3v1umJ72QI8Argu2sXzz7bzyjfusK8porTM9vYilkS/Svvp+d2SEjbZO7Qe/2Bof+pDGDTfA4cNw8mT2NKbrs23Xt6yfc47R0GhpbCG8MlwZMmJFB2pLB5yOo79+gplFy/P01ELf66WMKEdbMOf7dze9u+DzMzCYYQYFhWBjkHc3vbuofpA7Pp3qERbWOSVeTTDN7PVY9paCQsuFLVnnJCJPwAM9ApgxDHRTUTUPZP6GolA/PY2SylZZiTKiWNvLlibQFYVA6nq1QACtwOrdZUsTTE05t0t8oUe46I/wi4woR9tyywi324JHMmKetteHrifYGCQxkSCQ+i+TTFloGIZjGfGhSz7EDZ+8gcNjhzn52kmaLmhifWg9akr/LbeM8KqtH8Z9pcsIy2Y/ccKcwnJtjUWLptI2QNawHn+MwJE7qfvl8fShqTe1ZtnSmbgpI9beFubEnUGatARafV2epqqjcFJt4bKPZ1c6cSIjPvQhCurO559fYNynbHzeOEFmxSdzvQRAYea8VeiLzZtbyO+cqSOpqAQIkPhFgqkV+ffPTT0isiZCx6UdHBo+RHIimSVDMp+llBHA8g+h/taHUF85DG8k0d/UxMxb2graGbnf60cZMVdbkHpE7FiM7oPdnJw4mQ6GaLmwhV3v35W1DlAt/ojExEm+ekM934iZ7QJA/cwMimGgA5qqsuOGADdPnCxoh84wk7ZH1dR/uTafRdXKiBLaShnhTxmRq0vN/n1R6nOwatU07363UXD9A+Yf90vf9jz1FzXCqyuYnj4vfbyubgZF0QEdLkyw9G3PMzV1efrvle6zXOi2hcbnu5vX0/3acu5rfAVV0agPmPdJNwJM6eb4+/PXLiLavN7spymnvqppqKl7qisKM3U5YV4ZTn1hGZGq0GMoCtO535vZ9sSJdNphQwkwXSCux0QhgE5dqkqGlBH221oBkomJBCpqXqBkpn1voQbU9Br7d143uPY8aFLhpAZP/dK0Zfq2RtOB/OnxmRG7kOb8FhZd8+V0AKPf9IhS23omI5Z/CDbdAD8/nBffUqfrJekRxXz0Gho6uhlEe2FoVjeaSICebSOqip7eDK4bCjNGXTouZK5zkHpEARlRQA4qGNSn1mq5Msq0ppsxjgUmfCs+IvUjTK9ahZHpPMmM48psC0zX1WFY8Qa5C7v4w2dZsowo4kCpP++8tHQsRUbkxidZtoaCQoAAu9+3G21GS8fwAen4pLrjx2fXNUIhtN27sxfMM5C2hnjbqpERNtra1iOSSabr64tEcGXIiJRel/m9Vvxh4tXZOX9543J6N/USWROpXBlRrO3116MEg5BImOuOgZx4yIyAlfpS1jUOHCgYh82uXdRFItIfgUcy4vrrmS5kUFttDYO65mYIh7O/t4C+Frj4euoWvSn9Wacy4nltKY2/qmdFnVmkx9QNZu/TL7V6EjNmu8tzfsM1W6OtjfrUuMAwsvUI88vIXMRxpEc0tTPzsYvR7/1F8bYfa4RUMiyvZEQp83398eMo1ny/ciXal79cfL5vuYlAKnZIe+0E2psKxw4lEqAodRipWO1AQENV88e9pd7V1dWRTM7d1uLEiTqseDhHY7mIHaPWL0r7AhzLiAK6sKrrqCmZZyiKOZYLBP8+9hj87/+tMjo6G4u9atV0XrwiAPfei9K1DXXG3BBpANP19eiY3VzZvZt0cDjVoUfMtR8lc32w2Lpgse/1e3zEiQkzTvvA5fDPl6lcPxqg6TU4eQEcXmkm0KrHvG5jVUZ8xI03ohcLcJyaqnx/RE7bV0deTO8BqtM0ApZvMRBgJiM269WRF7P6nqqqqCcehR91m/GQRqptTkx8uq2gbqAGVKIfiLK9fzuQv18EYPf7d6d9WcaJE0zXF+7nkCFPkknvbY2U7AyceYq66VNmUu9lYaZmtMKbGYAb9ce4WbmDVxlncdFfLw3FmGtkSrKYmpqioaGB/fv3c/PNN6ePd3d3c+TIEQ4dOpT3mfe85z28613voteqCQ0cOHCArVu3Mjk5mSVULX71q1/xq1/9Kv1+YmKCUCjEH/3RH3Heeefltf/1X/91tm/fnn7/F3/xF0U77KpVq2ht/SgbN5rv77prF29+82TBthdeuIIdOz6efh+NRjl37lzBtsuWLeO2225Lv9+zZw+nTxfOcrN48WJ6enrS77/2ta9x4sSJgm0b1Ne56627zMx6V0Z54PEJjh8/XrBtfX09f/zHf5x+v3fvXv7rv/6rYFuAP/uzP0v/e//+/Tz//PNF2/7hW/+CRYEpAgp86+RN/PjVdUXb3nnnnbz5zW8G4Nvf/jbPPvts0bbd3d0sWbIEgO9973s89dRTRdt+8pOf5OKLLwZgcHCwYH+z+NjHPkZLKsvFk08+yQ9+8IOibW994AFav/xliER4+umn+e53v1u0bVdXF29/+9sBOHLkCI8++mjRts3Nnbz97VcQDsMLLzxHf39/0bYdHR2sW7cOgP/8z/+kr6+vaNsbbriBa665BoCRkREefPDBom3f9773cd111wGQSCT4u7/7u6JtN2zYQHt7OwAvv/wy999/f9G21157LR/4wAcA2LfvLD/9aW/RthdddBWf/vRvAfD6669zzz33FG17hCN8i28B8IPtP+CJvU8UbXv55ZezZcuW9PvPf/7zRdsKyYiRET76wAPp97vuuovJVH/OZcWKFXz84wssIxoauOuuuxgcGWTjgxv56Ot30vrmCwq2nWKK99/6ftpb24HyyojPfOYzaQX1W9/6Fj/+8Y+Ltr1z9d28uW4SUPj2yx/k2XNXF20bJcpZzgLwAT7AetYXbSskI0J/S8t55j198hfr+cHPP1C07a233kpraytAWWVEZ2cnV1xxBQDPPTe3jAheHeT3P/j7gA0Z8Z3vcM0zz0B/PyP//b/PKSO+9733cfjwdYRC8Bd/keDFF4vLiMHBDQwOtgOwbNnL/MEfFJcRTz55Ld//vnlPlyw5S09PcRlx1VVX8Vu/ZU9GLF/+Tj75yZsAc9Pdn/xJfmISi0wZEYvB0aPFZcSFF/46O3bMyogvfPELGFph9XCEEX5762+nq7vs2rWLycnCeoSQjHj5ZW7bsye1dAn3f+kvOJ2hC2Vy9uxiotEewDTeP/axr9HSMoeM+N87zMzHbyR54HunOJ4sfA6O9IixGMQ72Z/s5PnXrijaNi0jYjG+9fWv8+PUnFeITD3iK1/5Nq+8UlyPuPTSbrZtWwLMr0f8r9AeLn7TaZ5e1M8vl11UPj3CBzLCF3rE4CDtn/40RCJCesTZs2ez7IRcRGTEOy88wk1N3zKv7RerefDntxZt+9xzl7N//6we8bnPzS0j7rxzO4qhESbOhj/+VwKLCsuIVatW0dj4UTo7zfd33lnc1vCDHvH65JvYNfIMj3zuFiJrIjzwwAMLYmsI6RGVZmsIyIi97OVLW79EZE2k+mSEQ1ujrDLine/kpptuAkzfRqEEZxYitsZ/8p/0Yd7T/q39vHDghTn9ER/96EfT78ulR7zMy9zP/Wmn4W3cxsVcXLCtE1vDYsFkxBVXsCglWCtCRvyP/0HLiy9CMsmTMzP84KWXira99YEHaB0ZAeDpq6/mu6n+XIiq1iOqWEaI+izdkBHL3tLAbZ/aYS7CUn5/hMVC6hH//OI/0/lwJx10sI51Rdv6QkZIWwOobhmRaWsoCvzZn80hIxr+k+0te9Pv/+Jnf8y0sahgW9dkRMrWGNoZ45pdndx/2yf5+cU+1yN+/XNYCVX3T3+Z50cmirb9c/48HQRwEzdJGYGUEQstIypOj3BxXeOSD11C58OdGBh8lI/SSmvBtlXvj/j//j8uPn2a0Ub40u+207SsvWjbv+VvOYF5T6/jOt7P+4u2lTLCxDUZccUKfuuqC+D8Zl5v+O/cs/veom2ljDAR8lm+3sCuXXeli57cffcDvP56efSIz33u/2AFjG7Zsp8rrvC5jKhiPSK89Fv8xkVHAPjP13+dvhO3FG17w7e/ba59AiOtrTyY0Z9zEZYRABs38vKyZdz/B39QtO21wSAf+H1zrXZeGXHZRfzW73waqF49QtPMwiRPPhllZqZ8MiJ2LEbnw518jI/RQkvBtiK2hqIqfPZPP5t+P7+t8fl0lZOK0COqWEaI6BHf5ts8i3lPH2h/gOHB4aJt3/dr3+O6txwGIPHLFfzd2P8s2lbaGiZCMuJNCT5+2UG4MgqhiK34CGvC3/MXxeMjFp89S0+qMA3A1z7+cU7kVr5K4Sef5ULLiP/1v/4XTU1NwPwywrI1Qo0h/qT1Tzj5k5NF22ata1xzDd/94AeLtvWDjKg4W6OaZYRTW2NwkD3793O6mM/SkhEDA9DePretwevcg3lP+7f2M/FvCxOLLSwjzj8PTsf59sARnv1p4XsGKRnxwx9CZyffe//7eWp9meIsM/WIv/kbfnByDhmxejWtH/kIUBl6RFXLiCNHuOl3fxcikYWTEeeP8NHgAwDoBnz5pbuY1AvHYjc3r+Dtb/84yaRZSPXIkfllhGWXPPXUHqam5rA1Vq7ECuT62sc+5o4e8fe7+a/xVwu2Bfiz/7E2nYxoofSI6AsvcvZNowTXjvBHLXfx85/+vGhby2cJMNjezqFUfy6EiK3xwAO3MjLSCsDVVz/Nb/3W3DLixIm3s3EjrFt3hJtuKi4jLr+8ky1bKkhGDA7SPjgIimL6IzJs51wOP9nGr77/JppJ8oslb+Hann8r2vbnrzzNzge+Q2gCXm9o4J6dO4u2TesRmsbU4CBfemIB9msI6BHNzSv4n//TfgzVHvak39+9+G4mzxX+Xt+sfQroEddvv5737X0fINc+besRDz/MFal7+tzll9O/dWvRth3hIOtOfhww5vdZeqFHfPvb3D/Hc7v2ySf5wPe/DwMDnF23zv+2xn/+J9v37mUCWAycO3eOxsbGou2dUKxqtKQAP//5z9E0jeXLl2cdX758OSeLKP0nT54s2H5mZoaf/7ywcvGlL32JxYsXp/8PhULluYAUVjXBQsXrMrmg8B670hkfN3cr2aGuEd47ADcOFyy17RWKYhCY5375Fjs5AHp60llRykVvL2zcaCZ+efrpsn61b9A0mEOGA/DEE2K3VkEh1Bhifai4g0KSj5VRlzcXN9oUlHTVU38glp+jWDVXR5x3MVA5Qu3KFVfab2zJPBtybft20z86PEw6cUY5mG9+dcry5fbm71wi80yfqTWRNHWB4hnCr1h2RXpzsBsEMMzrm8OZmkkwCG972xwN9F/BY63w+EY4vB3OFncYCaNr8KNuhMZyJAJzOIwy0TRzDpmLL3zB/hxz6txytvT2s/V/R5gjwZakGHZumgv6lAivvOk3OcxejiwdYPlHnyvb9z73HNxkxBihlUE28iYKL05bRCLQ328mmLRLLGaaCF4TaDiX3hwsWXg+c/1n5LOoUIKNQfq39i/Y8ws1hmhpFBA6lUaRTLS+5cYbTeV6+3b467+eu+2yZRgVZJdIKpTXR0ybYMymL7ICiayJ0L+1n4b6hoU+FYkki2Bwoc/APm13R3j6rn5mlOIZiH1FQ9AM3G+ooJsskUiy6D7YXV6ff4Vy1/uh/VZY3QMvLLP/ucVvciu3usQW498y/e2Pb4R/EVi/8QtFNt/4jWDQ9LP+2q+V8UsbE/O3kXjCn7++hPZx6ErCZ4ovb5u4tfAI9oOHRJT7C95a2jn5nFjMjIHZuBGKhHw5xrLvFwUKJ04SJW/N107s0I96zDVQSUVh+ejfs+o9Ap+Sftmy03iZeHyjNeGXOSBYAu//xvuJHbPnE/5i+xcZuHWA4e5h/tvF/83+j8i6TJISmJwuvFEnj3A4XVG8KKGQ2c4Gli+i52BPZfglEt+ejfs6+f3520ciDEXv5PXyqFPZaBrMsfkGgK9+dUHjhiqdgwfL+GXt7fMHTXrI+AxMzBF69pOfzC6xb9w4fwxVpl0yb7yVk0AuUc5vmvvvC7j/I83B++DBQYgOw5lfX5BTWLZMzMS3TPb54lMvu6yk01o4gkG4t3jiQYD/yd8yyEb62M4+uuZs+9JF0Npj+pv/14ds/L41kG64wfYpLxQ/+Yn9rVcW1n6UaoshWB9aT7AxmK42KykzIw8hur/FVa6cZ/1BUYR04VpAVhAW4MSJE7S0tHD48GGuvfba9PE///M/5+tf/zovvPBC3mfe/va383u/93t85jOfSR978sknuf7660kmk+lMZZkUqyB8+vTpgjvEnZSjj8XMhDD19VNZvgpL8XjoIejosF82vmCJ+UcfhVtuwTDywz0XzcyYCmcksjDl6DWNRf/2b1jpdmauvRa9kNb1chwGb6BemU7fmxldRc/dW9/+XbjYFCyZZePnK3OfW2J+anqKw2OHOfnaSZouaGJ9aH26RLrjcvQ//CHapk3F287MEDAMGBhAC4cdl6N/7DG45ZZZ35em1aHrARQFFEXnm9+cKRrX7KTEvJtt5ysbb7UdHITf+A2DurribXU9wA9+UEd7++z3PvbTx7glZmbUyHS0GBhoaPRv7efmy262Xboe5h7387WNH49z//+5gW/EQDEM3pRxn36ZGtcfjsAn/+93Ca+anUAVRSGgBoiPxkm+muTi8y9mfXC2z2ZSUEaIyBMb4z52LMa2h7ehoGTdV0sJfCjyEJ1rO9PH5xuftuUJc4z7lAzJaltInqRkSPx4nBv2zrafYSZ9LSoqgZTs+e727GeRew7zyojkPxF40sxWohkBNMOSaakTW/8QBM0BO9e4z/teh22Fx/LAQFGjTNU01NT913/4Q2ZSGWdsfW/OOVhyDQw0rQ5NM9sqik59/QwPPZS/X+Oxx2DbNhVdVzEMM8FEXd101vya+ZnM8Tmf7AkEAjz2WF0qoVu27Mn9/kLjXtPg8GFz721TE6xfD6paXEZoupY3J9WpdVnj047OYZEey/F43vNTgPqMa5+ur8f47nfzlPapaY2vPfocL41NccmqBm7bvBYFvbCMGH8MDt/CosDsOU7rdRjWHJ7Rzy1Exv2iXxw2HdDAjF6HXszgbP8u9S2/kS0jpqcLPwxmx/LgILzvfTMEAsXPYWamnh/+UKG93Rxzg4Na+tYGFI31bz9M05KTnDzbxKHnNqAb5nN+/HGN668v/1j2jYxwo+3AADO/+ZvF2+o6qqbBwADGhg229AiwN+5FZMRcbePH49zwf+6H2DcwjAAzM7P9vb7+l+Y/Ih/mu//3k+k5Jh6HPZseY//MVkiNnqnUuLb6/Id5iE9+90bC4exxr2kwODhVqJsD+XaJKdMy5m87domuwc8PwxsnTWfzr61HyZFTmXpEIbl2/nnnF2xbCCEZUQ49ooxt5xtzTm2N/v/o55ZHbslbPLT0r72de9l8xea87y30LN606E2VKyNcsDXstC2njCjWFvLn+8zn19zYzIbVG9I2gIhu4EiPKNI2oBgcfW4PkxMvsqjhrVyx5uOodfkrv05tDdG2NSkjUspz3fS06WMANFVFs4R/AeW57p/+icCWLRiArijptoaSkiIZn6loPaLGZITTtmWRESkbIEunAOoDqfsf7me66bfL7o8QbeuWjPjV1K944vgTBf2KuW39oEf4oa0fxn01yQjTZn+el8Z+lbbZMXKeRYavLIBBXWD22qf0jEC3DH87uKtHZLb95eu/5D/+9kneeOkk57+1iSs+vh51kVqwracyIsP2WdTYAsvCEFDz2ub6na3qwQoKKip9kT5uvLSwk17KiPy2fhj31SQjctuCz/QID9vGj8fTGe4B6qgrGMxirQNUk62RK6esNRAFhQAB9kX2FZRTmq4xdGKIk6+fpPnCZta3rJ8zRkXKiPy2JcuIDF07gE5dQEu1VZg26gv628GHMiIWY6qrK38zR6rPKg89RH3n7FqiNZa16Smee/RrvDH6EuevfCtXdHycukVvKquMyFzDaWlZRDhs+lPLYWtYY29K1+D49fBaM3UXnkJZ+RRKQOehyEN5Y69i/BEpKk2PQIHDicMkX03S9OYm2la0FVxj57HHULdtM9c+DQNdUZipq8tfGEzhSEbEYhidnUzX12ePjYzfUG++WeoRwGOPKWzdWp++TfX15rpGocdRkl3yq1/y5OiTRe17x7ZG4ofoA8VjhxYFUvf/vQPMLL3ed3pEKW29GPePPPcI2/u321ovKXW+z/LRL25mQ6vpo89rm5q/DUDBQFV0VEXDQMEwFGau/WbB+Tv3HKStUUZbIzXhKydPUt/SgjXhF2yb8rkrhpEfS6EoBX3u4D+f5czMDPrMdN6aLgXiIZ3ICEvPyR17M5hjoX9rPx1v73A+7nPiW9JxloAWCMyugRSIb5G2hnjbipYRqQqExQIkMttaMY5531ckxnG6vx/jllT1thx9TTEM6vftS2+EnJ6e5l9H/jUr/jATy18I8INbfjBnsZUF90eMP0b9U1tRFPOaZ+O28+Mbre898MIBOh/uRNUDhEcDNL0GJy+Ap1aCHlDSto8jPWJwEO1970MLFK/LVjczQ+CHP4T29vzvzQncq3vPewik42ukjDBjh/JjsTN17ZtuKjLuCwRFBurrF0RGWPNSAINrzzNYXjdDUoMn3gCVRXn2txWfqusKMzOzekR9/TSKYhSJT3Vol2ga04ODGMUCuSiDHlEgjouAuiA+y9w9DTMz9RiGgqJAIKCxb582e29z5vv6mRmUzJgHa9yXON//0z/VsWWL2VZRNFRVS/3b/Hvms7O+d+d9Q3z5jitTbTPlj3mtPbue5S8/vX5WRjzyCDPbtxf1fal796JuLo9dItw2NVbVU6dQV6yAcBgjEMiPcYzD/Tc8xje4BVXXqE/dU0NR+FVdak9DRryiFXevo6Mxe//ryU6wkRl3H3jsMeq2bgXD1CKnrXFS4GF4aWvk9tuM1szM1Ftbr9Ljs9h+lExd+LffVn3xEen5HjVrbSVTl8qd72dmZpiemS7LPi2/+SOKtX36/j/lqrui1Gkadda+ikCAqdRYfXZXD9d88ouzH3g5jnroA6hKqq0RYMYo4K9MreN7pkc88oi1mSNPF1Y1DfXhhyESyZvvc9WD668P8KY3LZCtkZpnAoZB3cyMqxWE5QZhAaampmhoaGD//v3cfPPN6ePd3d0cOXKkYHnw97znPbzrXe/KKld94MABtm7dyuTkZJZQLcbExASLFy8ueweIxaC7Ozt7TCgE0WgZEudoGrS2YoyPF9wuYyigBENm2Ua1gOBwk0IXHgyaJW9zL3ykz8yAPB/r90Lr3JlJ5j2tYzG6D3YzPjF7XsHGIL2bekurxNTXZ6YVmo+9e6HL2TWkHnfRTESKYt7ihXjcblLKrS30vEONIaKbop5X3uo72sf22HZufh56D0JoYvZvo43QswkOXA57I3vpWjt7Ia712RLw030FhGWI9SzmI/dZOGIsZlY/ncwYuA0huDLqj4xdc+GBXLNwMle6Or968P2u4/D5CckcXTMzSE4WmZhQzCo7Nw6nF56EcVlHcHKbPBwatUcV3Nz0HPP8zXCwFyZCs39sHIVNPXD5gaw5Zt9DGtd9uJUWxnPT4wDmJuFxghz+xjDbbhEfSyXpkAXnsSBc2ev/eaxK0HSN1t7WLLmciYJCsDHIcPdw4eA2iaRcSHmw8JQi0CteuZX4Bi9sAIlEUhTbNruH/vZaxXf+UYlEkoen6wA+RMqpCqRadG2HtuvQfTtZ+dndrDg3G2R1YrHK6Bd20Hb73S6fdPmQY6+C8cJ3Iv0z81IVMTHSHnMNP6+XDO2PsfJ0NyuWzJ5b4myIsWVR2rbI8e17qkE+u7iG48nYq4I4AYkHCMQjO+63AvKgKvwODuxQ12VCScHCAjHrNUhV6NoZ2LW/nVx3td0rtxC+Tw89BB/+8Pxf/I1vzG5Sc4iIepeWa0NXF4n1u4NQ2zOzcq1KOohovKLwvOfT++T0tGrV5yd63X7c8+IFhXzbiSUqY58v4Nv2s99I0Db2neqVo0e6uUG4bv4mEotFixZx5ZVX8v3vfz9rg/D3v/99Ojo6Cn7m2muv5Z/+6Z+yjn3ve9/jqquusrU52E0iEej4kMbRPXEmX0zScEkza28LpzPiF0XTzF3sqeq76fS1mcTjUGRzMIBiAGNjZrv29jJcjU2sEmW5++ITCfO4lVrD4vxme99rt12x0zoWo/PhzrxsdomJBJ0Pd9K/td/55NNs89zstitA6nEDZsXC8GVxmpckSZ5tJv5CGN1Qy/u47fRBDyjl1kbWROi4tCNdfbf5wmbCK8NzOh80XRNqb5fmC80TPHA5PHoZhI9D82uQvADiq0APZLeDEvusi8/PyX11FUEZknmP58JuuzkJRaClA07H4Y2keQ6p6iMLip3+4YFcs4hEoKNDrMs6+YzwOf22xtEfxpk8k6RhaTNrfyOMWu9foz0LB89PWOacjs/hJAYwYHLMbLe83f65Z1KCjmBHnjvp5h4OjdqjhJurTU9x9JE9TB5/kYZVl7B2822o9flVLd0mPXdcfgAuexSOh+G1ZrggCavikKpWnTnHXHY6TojiYymAwUrGeOV0HGgXPqdMHbIQhlHEZBiLQbyTvFIxkwnzeLhfbgr0gPhovOjiGpiZCccmxoiPxmlvbffuxCT+Q9fc0zmlPPAHjgU67ivPktrBCxtAIpEURMhm98jfXm2I+IV95x+VuI5b6wYS9/B0HcAJLq/BOZJTPlkXrFmqRdd2YLsO3beTa7p35TVtOqfR1L2LIViwTcKi8l/qCBWMF74T6Z+Zl1LcX75B2mOuUcp6iZv6fCwGnb8TQaEjK47riZ+acVz9qtyT5HucyGc/6c4lrOHYCk/1Yq1SBmFI5kMwHtlxvxWQB773O9jBgR3qukxwKg9EY9arDRsCvVRd22/+Ubv2t5Prrgq7xAOE79P5p+19sd12cyCi3qXl2uXjRWP9xiaYlWtV0kFE4xWF5z2f3iene3Ec7UdxYDJUqqwFl/dp+Zy22+9G++QXOZITv9xSKH7Zz34jAeFpqV6KobGBOM0kSdLME+NhOjvVhVG9PLQX5QZhQXbs2MHv/u7vctVVV3Httdfyt3/7t4yOjvKJT3wCgM985jMkEgn+8R//EYBPfOITfPWrX2XHjh18/OMf56mnnuLv//7v6evrW8jLMInFULu7WZc5yX15nq3xNrfT64lEwawdudhtVxY0zTz3QkWzDcNMrdHTYwoPS1gsC5uZpiYT5DmrgHQmqmVh56ela3Qf7M6bdMA0ShUUeg720HFph7OJNBw2n1EiUfjarZQiYefXkEyarzdfFaP3I92Els72j7EzQbr/sZcDz0bS7UrCRykdSr21akC17WxwM3NJeGWYYGOQxEQCPWBwaHX2363saeGV5oWU1Gc9eH4i99VttKXrOaWpNAU0AgUyJugGJHWVpqXrUcl+FoXub+6zKJmA6q9gDbv9IzX4jPEESsF+qKCESpNrmaiquJ3n5DO2GYuh/qibdZYj9Azw7QqqkicoPB3JnDdsTjh22xXCoY5gV547mWM8mPJrF4c318rAtS6rusSdC1JdImuOCeiw+lDW3wvNMe9YZm+M2G2Xi13dMKudrplZpguOOwNQ4Ec9ZhIMGdzmKslX7T1Au+0kVYqb1X2lPPAPjgR6Bq4qz5KawQsbQCKR5CFss6dsaWOycHJRA1AaQiX526sNJ35hP/lHJe5SqxnPKx3P1wFE8GgNTkhO+WhdsGapFl1b0HbVpqdY+dndAHnxDAFAB0J/thvtk1/0PCGkU/kvdYQKxgvfifTPzEmp7i9f4EH8U63idL3ETX0+M0TOQOXQsfasvxcKkZP4FBH57CfduYQ1HLuX4clapQzCkMyFg3jkkvqtTXnga7+DXRzYoa7LBCfywEnMejVhU6CXomv71T9qx/52ct1VYZd4gPB9eucyuAh4ZY7GF6XalQG76l2WvCoQ65fXrko6iGi8ovC859P7VMpeHKH9KA5MhkqWta7v06oA1PpFrNvWM2877aIwp84GaWpMEAjk3y9dV0hOBGm6KMyC3CkbwtNSvW4yYvTSnZVsYIwgPUYvPT0R71Wv+fTIMuLZ3sxq4Xd+53eIRqN84QtfYN26dfzrv/4r3/nOd1i1ahUAyWSS0dHRdPvVq1fzne98h8HBQdatW8f//b//l/vuu4/Nmzcv1CWYWFvjczNgWFmJYrGinzFyPmMU+MxPVHtZUuy2KwsiGT8sAqoZuAyQF7KUen9ltKRgY5HMVY5QVXPWBtOgzMR6H42WJOWam02FpL+nk5aLsq+l5S0J+ns6ufmqWOnJD5z0WxfJvLVqQGPDmkG2XdvHhjWDqAFzI9Bct1bTYHDQrBo/OGi+L4SVuSS3n1iZS2LHSrtuNaDSu8m8ECWnn1vvo5uiacXHcZ/12fPzgvj4YT51ynywes58br3/9CmN+PhhQPxZZH+hBqcGYaTPfNWLdKgS0HSNwZFB+o72MTgyiFbO3xDpH6rKUFcvBqDn3Cc9tWV4aFt0YR1nbj0PK8NqbpZEK8PqWAWMI8F5yZHM8SKTkQMdQUSeO5m+PZjyaxcHN9eqLtF0Lnv8N53TuKZ7F0P37XTxhPNxMscEWuyNkYLtbMhBRwlWRTLFVgIezN9uURWZhyXuUoLeYkvvrDZ5UMnIDPoSP+DnbKYSSRUjbLMHVIaWd2EYhX1lhgFDy7fJ5B4p3PYLS/yJXR+s7B+VS0nrAG7ixzUcP55TLVIturag7Xr0kT2sOKcVDagJAC1nNY4+sqcsp2cXv8t/u+vfaSrYPyqpLarC/eVB/FOt4mS9xG157iRETlLh+E13driGI3IZnqxVlhCEIawXSSoPB8LWi36b6XdQgQ3nw7YLzFerpy6I30EEB3ao6/fWiTyo5QlZQKA7Ls7sZ/vYxiTg5Loz/x1AYwODbKOPDQwSQCvYzs9oM1Mc+XGUw/FPc+THUbSZqbJ8r/C9vaAFPjJP44+k2pUDm0qCsFzz2nB1SdkRjVcU9rf71MD3Yi+Oo+1jKVl74uw4G4Zh21HYMAzJs+MLL2tt4Po+rSoi/qTKp/6hFxRzM3Amuq6AAp/+hyjxJ/1r+8TjcPV4jH46acmpRN5Cgv10ctVYzHvVay49sszIDcIOuO222xgZGeFXv/oVP/rRj3jPe96T/tsDDzzA4OBgVvsNGzbw//7f/+NXv/oVw8PD6WrDC8Z8WYnAzEqUOTJTnzEMI99NbBjmxzI+88JlyxhrNDPnFkIHRhvNdp7hNONHKALhfmjIUewagubxEqseeZLNLhKB/n5oybmGYJBy1EkPX6fx1d8zs/7lVkkNBAww4Cu/10P4uhKkvZN+6wGRCBz+ZozRr7Qy+Kcb6fvUdgb/dCOjX2nl8Ddjcxbjbm2FjRth+3bztbU1X7maL3MJQM/BnpI3akbWROjf2k9LY3YfCTYG6d/an5XhxVGf9enzc5vkq0kOvA6dSUjMZP9tfMY8fuD17Hsl8izSjMXgsVZ4fCMc3m6+PtZa1s2isWMxWntb2fjgRrbHtrPxwY209raWR7kX7B+aBlv6InSynwTZ92mcIJ3sZ+u+yMJ1J7eex7wZVjEzrFZC8ITAvORI5lgZsAvWI8I8Xo6KRAI6ghN57mT6dnnKr20Ebu581SUgVV1iujyOTbuIzjHades5sVidU6dPLFHRrluf/QebctBKjFXM5lUUCIVyEi5XS8US8GT+dhMrA2Ouc9VCQSHUGPJ35mGJe5Sgt9jWO6tJHlQ6jgS6RFJmvLIBJBJJFqI2u6ZrbBnqK+or25KErUP7ypuUrkLxyi8s8Rd2dWHZPyofR+sAbuLHNRw/nlOtUi26tqDtOnn8RVtfa7ddOfC7/Le7/p2mwv2jktqiatxfLsc/1Sqi6yVeyHOfFsWSuIUfdWcHaziil+HZWqWDIAxhvUhSmTgQtl7128iaCIc/cCejb1UZDEJfMwwGYfStKoc/cOeCVvuzhQM71JN7KyoPanVCFhToTnRtX9vHNicBJ9dtfSZCjBFaGWQjfWxnkI2M0EqEWGXYJcDQUzs51dfAuufuYP3YV1n33B2c6mtg6KnSC24I39tlYdgQhB7MSsGZXIR5fEOZfF8CSoKwXPPScHVT2UldR/6OJROD/OsQ8rf71MB3ey+Oo+1jKVl70/MGI1EYfBD6HjFfh6Nw8/OG79eiPNmnVSUkk3Dg2Qid0X4Sv8jZm/FKkM5of8Eq1n6yfU4mNHpJjaOcvwVS+kGUHk4mFqDPFtMjy4zcIFxl2Np97yQrUeozxc2t7M80LWmhe5P5t9wNBdb7nk1mu3Jg67pLyfgRisCNI/DeAVi/13y9cXhO57jdLO+eVd6KRGBkBAYGYO9e83V4uCw7hdRX4qxYMp6nkFgEAgYtS8ZQXykh3YJfs2mNxWib7qR5Sfa5NS9J0DZduCqWSAYWLzOXRNZEGOkeYeDWAfZG9jJw6wDD3cN5DiFHfdavz89lrHtw4HVoHYH2cehKmq+rR8zjme0s7D4LwJOKsq5nWxPsH1bzA2ymlRHaGaCLvbQzwGqGOcDmhetODp+HJ1Xy/JaF3ea85EjmeJkB26aO4FSeO5m+XZzyJTZvrl+rS4DYHBNPHOZTv2nKimI6/ac/oBFPHJ79g4AczE6Mle19st7nJVyuloolVVAR3rcVjyT+wGlmeBG9s1rkgd+xo0OWkEHfM/ymC0vKj6yCI5EsCKI2u2UbF/OVxV5HZmlOITNa1x4iurDsH9WB0DqAQ2xnbffjGo4fz6lWqRZdW9B2bVh1ia2vtdtuXmwMWM/lv0DpB+EKJFXgH5XUFpXg/rKNg/gnydyIrpeUKs/tiGefFsWqeezGEgrjR93ZwRqO6GWUulYpVOVKIAjDb8WcJS7iQNh6tsY+FqNt+B6a1eyO3azqtA3f439924Ed6tm9FQnKqtUJWVCgOyrO7Ff/qMAk4OS6VRX2d8XYP0dlxIe3xXxvlww9tZNrXtpFUyBbRjUFNK55aVfJm4SF760lc65WoBf4E+APUq+9mMfL4fsSVBKE5ZpXhmvqOoyc6zDKpeykrkNRwMi5DkNRzEspcB22/e0+NfDd3ovjaPvYaJyrh8bpfxhaJrLbt0zA/ofhqqEistYnJWU926dVBVjqyIFnI7R2j9D+xQG6vrqX9i8OsLpnmAPPRrLagf9sn8tOxwkxPkfctsFKxris2D4Lt4lE0F56kZ/8/Zdc+wm5QbiKsL373kFWIj1h7zNWu/DKMM+0BdmyFRKN2W3GG2HLVni2rTzVpGxXYnVaAc0ioMLydmjtMl/nUPREKm16WnlLVaG9Hbq6zNdyKS9eVG7yYzatjKpY+W6IwlWxRDOweJ25RA2otLe207W2i/bW9oIOEUd91o/PzwMy75UOHHoD9r1mvurMPb7tPAsvKsp6km1NsH8kErOSXEflEO3so4tDtKMze58y23mCw+fhSZU8v2ZhtzEvOZ4nvcyAbUNHKEWeO5m+3ZryJdi6uX6sLpGJrTkGsz8euBw6i+j0nVvhwOUZ/daBHIxE4M7oEIHG7L4fWHyCO6NDeWso2tL1nNBU9EI/AegGJDQVbWkRnd4PVFFFeN9VPJL4ByeZ4UX1zlTm6DmzhlZCBSM/I6JDOsig7xl+1YUl5UdWwZFIPEfUZs+0eQv5yixklmaZ0brWENWFZf+oHuz6aJwglLXdj2s4fjynWqZadG0B23Xt5ttsxRas3Xxb6edlc8B6Kv8FhIhwBZIq8o9Kags/u7+EEYh/kthDZL2kFHluVzz7tChWTSMSSyiMH3VnB9U/nVyG07VKR1WubMQJ+LGYs8RFHApb19fYHcS0+hIHdqhn8Qt2g7JqdUJ2INCFizP70T/qYBIQtjE0jba+bpQilREVoG1fj68nGm1mipU/2w2QXyU19T70s91oM1Ml/Y7wvbVkzgVBuBxYj/l6Qag8vi+HSoKwXHPbcE1dh2EUmGMMw1zPKIeyk7oOJec6lHmuw7a/3YcGvj6ZKGu7XJzo2ifPJug9aP47X+aYRA+a7bLwUUlZT/dpVTiZaotuqBw61s6+p7o4dKwd3VDz1BY/2j7vWGavo9ttV25ix2K0fvUSwv/1Gdd+o861b5Z4irX7PneAWbvvs+YqB1mJfnK6mXU2PmK1s7KWdE508uhlBtcfh+bXIHkBPLEK9IBCfxmyMYlcdzxxmPt+U6P/YXPBLnOiyqyAdnviMO2t7c7PKZXlXZmBDc+8k+ZfNJB8yyTxq4/S+XBnnkKWvlcPd6KgZAWAVEzlLS8qN/kxm5ZIVazl7YBYBpb2dn9mLsnssypw/fnQrEJSgydSwXx5fdaPz88DXB/fDvqgKCLZ1hzLTsH+cVr9CdiYley2KxsOnoc1Z+QG/1mVQbLmDKey1srCnhtoYWVh93nwTknjKBSBlg7znr+RNO/NsvCCLHL7UZ5L3MPz6hIuYfXHA5fDo5dBOEOnj68CPZDdzqkcvOcXnSifhg3PvCNLd77nFwZtx7J15/j4Ye47pdHfbG4GznQWW5uGP31K4/bx0nR6C03XiI/GSb6apPnCZsIrw6Xr5R7M314SWROh49IOsfuka76QzSWjaabinkyaeko4LDMyWDjJDC+qdwZUhqZ7ucboxDAUAoFZHUHXFVDg36ajtFVi3/IDTnTISAQ6Ovw1LlLXYeQEQRiTCZQK0IUlDuZiH9kAEkktIGqze20bi6prTvR/0c/YbS/9CLWFqC4s+4dkPoTWjcGfazh+PKdap1p0bZu2q1q/iNEv7KCpe1fR2IKxz++gpX5RaecjMGA9k/+CQkR0/bva/KOA9BPWEH50f0n8g931EqfyXEQ8W0WxOjvN4N7Mz1Rc1esqQCguJAdbfgSPdeepaY09jxzlxeOTXLKqgds2r2VRfc45WZX44p2Ym4Qzr71w9U+nlyG6VilsLwkgrBdJKpsShK2jNXa7VJO+7cAOjayJ8KG3dcwvp7ygVidkhwJdRNf2pX/U4SQgZGOkfqN4+g3/TzRHn9vDOrX4brGAAi2qxpHn9rDunT0l/Zaw/eam76sEJUF4znDTcJ2vDxqUrw86uA4h94zPDPyfTJy2t1erUDsbF+5ENF/2wmlCE8XbBoCVE/DKC6dnQ/XdVLYdUBX7tDxCVG3xo+0TaLHX0e22KyfF/ALlRm4QrgLm232vKObu+46O1IC0tvcnEoU/pCjm3zOyEr2wLMxSgrSQIFCgU+oojBPkhWXhtHy3spbc/p07OMRqoBlIEmwcofeDu0vOxiR63ZkV0HoPkjVhjTdCzyZz88OWEjIGWVneb/re1fQ+NUbI+HH6b2Pfa6b72pX0NPbQcWlH1kRi3avug91ZQSDBxiDRTdHi98ovC01W1r/JBIUz/Srm30up3OSg37qOg6pYohlYrMwliYlEwQlBQSHYGPQ8c0lkTYTDH7iTlT/bzYoMY+2EpjL6th205fZZPz6/UhAYe47Htx08qN7tSbY1wf6x7LIXoHEpTLSQn5cIQIfGcbOdlxuEBZ/HfJVBFBR6DmbMGU5k7bxZ2BUzK2RLh6+DeEoaR1YG7AXGr/Jc4g5mdYk7aTqnFZNSJMtVXcJFMvutHjA4tDr773n91qEcvOl5I6WfZ+jOT5n6eZYcJKXTvw6dSehdBqH62a8dn4Ge03Dg9dJ0eovYsVhBudO7qbe43LGz8dWD+dtrrAyMthiLmXNT5qJkQ9AMEqikTXqxmGmQZnq6gkHTU1ZRpSLcQVu6nlOaSlNAy8v6CuaG/qSu0rR0PdYIEdU7NQ227IhwdVM/vR/pJrR09lmMvxLkjm9EeeZkhOHIAvnv/WKvO6EUHdLKmO0HUteRuzkYSLn9FZQK0IVrGUdzMfjGBpBIagURm91L21hUXXMic0Q/I9Je+hFqC1FdWPYPyVwIrxtDho9+vKjrmWDhijauJFfLOqcqWVeqFqpF17Zpu7bdfjdDwMrP7mbFudn10OQSlbHP76Dt9rtLOw/BAeuJ/HcgRIQrkFSbf1T6CSsbB8ks/eT+kvgPO+slTuS5Ex3PKopVSERFo1JEeYVwXEgGtv0IHurOO+8bYvdnV6KdW5c+dufiE+z4wih3396W3diqxFdwXTCaty5YymXYXat0ZC8J4MdizhKXKSpsWyA6tz4otMYugt/1bdE1VEE71FTPVcbH16WPfbnM6rmQL6QWJ+QSBLpdXduX/tESJgHbNkYVTDSTEy+Wtd18CNtvbvm+Snx2wnOGS4arnkgUjIV02m5eBK7DkXvGRwb+C8oylk5DS11+dW0w46zGZ8x26zL/YPPCLdE8njDAKPADikEoqGSJ5ndoy2yde7pdqcq2SwVHXN3HUWWIqC2+nJJSHd0YT5hJM3IwUFBC3q8rzeUXKDdlkb2ShUVk9z0wu70fZrfzWxTJStTUotKN+Rk9J6zSet9DlKaWHCF8LIISHYEHB+GRPvM1OgzHShekotedWQGttQfab4Wuzebr6h7zeGY7R+c0Gufq/hX0H36GFiNbmrUYJ+k//DRX9TcTH43nfTayJsJI9wgDtw6wN7KXgVsHGO4eLj7pxGLQ2gobN8L27eZra6t53GusrH8A5CoNhbP+CeOg37qOg6pYohlYrMwlMJupxGJBM5eMxWgbvofmnExOzapO2/A95saPTPz4/JziYOwJj2+7eFC925Nsa4L9o2VJE2zqTjXQs9tb7zf1mO28RPB5iFQGAZzJWpGskD7HtXHkEb6V5xJXsKpLQFEpxdjnd6CWWl3CZYT7rQM5ePXQOP0PQ0tOtrmWCdj/MFw1NJalO6d1+tehdQTax6Erab6uHjGPZ7ZzipWxK1dOW5m8Y8cKzPtjMXisFR7fCIe3m6+PtebrRR7M377FqkiaOzdZFUlz75VfsbId5hqkVrbDhbDJfEZ8/DCfOmXaCnqObyuz2nd8/HD6uKjeafkEDjwbobV7hPYvDtD11b20f3GA1T3DxJ6JZPtCvMRP9roTqkWHTF3HnBmUK+E6ahRHc7FEIlkw7NrsXtnGouqaE5kj+hnR9tKPUFuI6sKyf0jmQnjdGEzf+//pKrw5GMzjf7otbw0ndixGa28rGx/cyPbYdjY+uJHW3tby6GqpdQPDKLw2bRhUzrqSpKJpu/1ulp+e5EjfvRz+y09xpO9eml6eLH1zMAgPWE/kvwMhIlyBpJr8o9JPWNnY9elLJGXGiTx3pONhBu+OjMDAAOzda74OD1fnXiS/IhwXkkLIj+BRTNbO+4bY1X0N2rnsWBztXBO7uq9h531D+R8KReDGEXjvAKzfa77eOFwwabAXl+F0LNnF42LOEr9wNRA14E+AP8B8vdcwjy8Efta3XV5D9UI9d+QLqbUJ2QOB7kv/qBeTQBVMNA2Nl5S1XcVQBc8O4Cfq6bK2KxfV4J5pamyhO3XbisVZ9Zw226URuHBVha67hlKbdwtEtBoG2+4cyhLNgZYW7JBuV4qy7bKPptLjz73ErtriS7GW0kEUBYwcHcRQFFMNWYB1pfn8AuVEbhCuAhztvre29+cK7mCwYOn2cBieCUbYQj8Jsj8zTpAt9PNsKJK1mX52zskeXImEUpbJNvN6AmhsYJBt9LGBQQJoee2sjEEKCnoADq2GfWvNVz1gGgWhxlBJGYNOnDlB71NjgJE3uKzKy9Gnxjhx5kTBz1sZXrrWdtHe2l7cOPGjJmNl/WvI6VMNQfN4OaqBCfZbC03XGBwZpO9oH4Mjg2i6VrCdMFY1zznCjWkIZVXztDKw5Nq96U8oEMpJwm5lLmlpzL7uYGOQ/q393isnGdWkClVhAsxqUrn3uejza5nz+fmKEsae7fGdQtNgcBD6+sxXrUC31S4Kc+JsEF0v3KF0XSFxNoR2kXO5lik7AzpsGIZtR83XgF4e2QkIje/wyjDBtmdg6xZoTGS3bxyHrVsItT3rfYUMQZngqDqzqKz1e1ZIQUTHkSN0DU4Nwkif+VquOQMfynOJq7TdfjdP997FycXZ/TS5ROXp3rvKE0DmAUL9dlmYyfqleU4qC92AyfqlaTl48myC3oPm3/J1Z5PoQbOdRZZODxx6A/a9Zr7qlGdemi+TN5iVjbN0SpGNrw50yKpg3oqkFNYh/cZ82Q7BzHZYSHmrITKrfSdmsv82PmMeP/B6tp6TOb4LkTu+M30CuqFy6Fg7+57q4tCxdnRjVvZ6nhzXj/a6KD7XIbUpjSPRQQ5/uo8j0UG0qcLjTX/d3vnZbSfxDkdzsUQiWXBUA9pHoOs/zFe1iF1Qkm1sw2bPVNcCisaGNYNsu7aPDWsGUVLrBpnqmhOZI/qZzPa5/jVFLy7XpB+hdhDVhUH2D0lxHK0b6xpc3Ac9wEU5DS/CPH7xviy560VClxgROousTXfSTwzZzyXeoNYvYt22Htb/4VdYt62nfIkfHQxYS/6HGlew4XzYdgFsOB9WNraUR/47OCfh9e9q8Y9KP2FlUy3JLCUVi6g+X0plHqsoVleX+Srzq3iLk7gQR/5RhzF1dpma1tj92ZWpd4VXdnf/WYip6QLznlWJr7XLfJ0jzsPly3C9ypWTuEBJhWPpFL9KwOXAeszXX51YMJ3Ci3hCRzhcQ7UTQ2m1c6qe2/2NknwhtTYhuy3Q8aF/1ItJoAommrVX3MYJTZ0ztiyhqay94rbCDewOWL9RBc8O4IXLljHWmL+91EIHRhvNdl7htXvGrS4YXhnmGTXIliJxVluS8KyasU4keOGartGnbYGtnUXj7vdpW7NtDKsaa5Fuayhk91unyrZHPhpP4s+rBDtqi2/FWkoHUXJ0EMWGDuLW+LbrFygHdZ79ksQ1HO++j0TMEu3xuClom5vNEVhgBFsJfTo7IzxqdHA9cZpJkqSZJwijKyr90dmPllohXuR6biZGL92EmJ0UxgjSTS8HiORVYu18uBMFJcuJVq6MQYsenSRkFB/AAQxWGkkWPToJVzr8ES9urlNCEWjpMKvvvJE0s4wtC5dWOTgXgX4LplHefbA7yygPNgbp3dRbugFoVfOMd2IuYGY+k8LVPGfHkvmoMh/jXMmxImsidFzaQXw0TvLVJM0XNhNeGV4Y5USkmtTy9uw/WRnz/h04CywB3rWAGfNE8HDsxWLmT2X6w4JBs+9k6iXxJ1Xu+4de+ns60XWFQGD23HRdAQU+/Q9Rbr9cpb3d2blYsvOhz20mehBCGRUexxqhZ5PBLZ8rU7Y1m+M7Lc8nOjEuexSOXw+vNcMFSVj1BEpAJ7qp3/vxISgTHFdnFpG1fs4K6UfGYubmtUwZ1xA0n2s5El3gM3kucZ222+9G++QXOfLIHiaPv0jDqktYu/k2WnxeOTgXu/1WA7pPw98sNh22gQzjPzOT3f2AClz2wumseSWXALByAl554TSsM495odOLZPJub223sfFVMTe+tnSYstqBDlkVlKJD+gmRbIdOFbAqILPa96OvQ/h8aFYhqUH8jdnFgkw9R3R8+zIToZ/tdRF8rEMO7Yyxcnc367TZcXjiziCjO3ppuztbX/vJfzVb08ec/OS/mln31vKep6Q0hOdiiUSy8Nh1ZqVwZBvbtNktde3mq2L0fqSb0NKMdYMzQbr/sZcDz0bS6poTmSP6Gav9zc9DbwH/WvcmgwOXF5Zr0o9QGzi1dWX/kBTCka1k2exXY65fvsDsGs5lmE6aDJt9vg0LCgo9B3vouLTDcX+0zKtxInyLDsIZa9NxwhiKyjM9/jevJJK50JZfjJ3um9sucgHc3KqgvDF7zDgflAvKcFIOhIjw+ne1+Eeln7ByEfXpSyQuIaLP+9IfLrGFk7gQx/5RwZg6EfY8chTt3Lo5WgTQzraw55Ej9Gybq938uHgZro8lp3GBkgrFpzqFF/GEwjhcQxVxOztVz+3+hhe+kKrDTYFu/YSf/KNeTAJVMNGodYsYfdsOml7aVTS2bOxtO2ipKxBbJ7gW5Suq4NkBNC1poXsT9D9sxv1kpo2x4oB6NsHtS+xVni0HXrpn3OyCmetEj75ucH1GnNUTb4COQv/WjHUiwQtP2xiXj8Nlj8LxcEbcfRwCOmMTZNsYVjXWzk4MBZSMfmsoqdWrjH6rXdxsz9eZ2c6n+pRkfnwt1hzoIG6Ob7t+gXIgNwhXAdbu+0SisP2kKObfC+6+t7b328BK6NPdrXJofPYzoZA5eLM2rXkw2YbD8LGlMf7mTCe5k0ILCfrp5BNL+wmHZ0/MyhhUaMNodFO05A2jTWfOL2u7gni80KTpmpjxZGX9cxOb/dbK2JVrlFsZu8qSJcqq5lkwOC1acEPZ7FjKn0Ryx1ImVuaSBcdpNSkrwwuGmSnPwsqYV65K007QtPmVAI/GnpUsL1eeW8nyMpOXJJNw4NkIndH+vIDH8VeC9Hw9yoFnI2wpMfFI5BjcvD//nFomoH8/KL8DrCntN9LYHN9Z8jxwKH081Bgqizx3jIBMsCqDJCYSBZ2HCgrBxmDhKph2Za2VhX0yQWEDSjH/7vcs7F6QKaMysbJQlVFG+UaeSzzBqi5R6djpt/HROH93+gxnJqF3GYTqZ/82PmNuDj7w+hm2pxxJ79DsZQvMbedYp7cz3+Mgk7eTja8OdMiKp8SKpMJ2iVu4nVq8SsjUc3QMDr2R/fdieo7I+C7JF+IW1RIY6lMdcmhnjGt25etrTVqCpl2dDNGftUn4hTNhlp4J0vKWRFbwg4WuK4y/EuQFwrY2EkvKgx157qSqhkQiWUBEnFkZCNnGAjZ7MmluDu7vKbBu8JYE/T2ddEb7SSZT7R3IHNHPJF9NcvPzZsBELi0T5vHOrcW/149+BN/o51WEU1vXj/1DsrA4spUybfEA2Ws45LfzIqFLpnmlo3KInO+pEPNKUsPo2ryJXuOr4JJGUx/IrcMHZmDleCO8tIrZEZDSi5QcPUd5w8Zahh3/qEOHi/D6dzX4R6WfsHLxOJmlNjPF0ef2MDnxIg2Nl7D2ittQCwW7S2oSu/q8L/3hEltzq5O4kJL8owKxoCK8eHyyrO3mw6XL8GQsWXrRHT0aqy+I07wkSfJsMyOvh9l9r+r7/UsSAbzWKeyFO3gWTyh0Ug7WUGfdzqnNQSkSCYPOTiXP7exEPRdxbWf6QgIUSpA9ty+kZv2pogLdhi2d9xN+8o86DQ734Df81Afbrr2bIWDlz3azQp0tz5jUVcbetoO2a+/O/5DDtShR7Io1R3jRPxxit3+EV4b53bYgWxjPKzg13gh3bIJn20KFY55dohT3jMjz9qILZq4THcrwvxeMixe88CzbIaDD6kOFm+faGFY11px+qxTot3HCXEKQFhIECtg+OgrjBHmJ8Kyvs1oKjlQbNgdH2va5XWN1YjbJ60hLmN29C2z7COggbo/v+fwC5URuEK4CvNx9b3czvRdrISoavZgZI3IXzAIY6ChE6UGlAzLyUbiZMeiCX7eX8cRuu4J4uNDkavVdl/E0Y5eDyskeJMdyDyfVpPyc4cVuyg8Pxp5osjwrY+WBZyM8+qMOwpfNOpbjL4TRDfNelpQlNnVSipHpajMxZe/CVUHzVQa4TGzKBC+qYFZNFna38bOMkkgqCMtBNF/FUKtdoMWeTlyonfAcIJDiSziTt9ONrw50yIqmhIqkvrJLZJp+W5Si59gd377MRFgtgaE+1CG1KY2Vu+f2AYV296B9sQN1kXleTStUuu+dO0N6z9ej3L6rSuWuD7Erz51U1ZBIJAuEw8oPQgja7M1NGr0fSc0ZOc6sQMBA1xWiv9vDS03muoETmSP6meaGi+k9mDqHnDYBTFspehBe+ouLbX3vQuMr/bzK8K2/U1JROLKVBG12LxK6VIt5JalRxmJFNr72Zm18TU6+zH02qq5smXw5dbCEtQy7/tGUEDE6N2MUOCcFA6WIw0V4/bvS/aPST1i5lJjMUoShp3ay8me7WZcR9H7iJ3cyWizoXSIpgi/94bWOzbnVyXqJH/2jl6xqKGu7hcKrsRS5OsbNvd0ob8z2D+P8IMpVvYD0nVQNHuoUIhXNPIknFD0pQSN/1u2cvTkYwDBLGNLTo2S5nUXVc1HXtuXjuPnN+Qnzx6ah+7QZK1PIFyL9qTaxaUv7Hi+CwwV/w499sO3au9Gu/iJHcpIpFawc7MVaFB4VKPbh5gGR/pHWbSc6efQyg+uPQ/NrkLwAnlgFekChv9SYZ0GcumdEnrdHXRAQWCcSvPCSbAyb/Tb5ssp99NJPJzpK1iZhPTWf9xBly8sZn/NQn5LYRFAYRohxs9KNQobtQxCFyrB9vBjfc/kFyo1iGIUuReInJiYmWLx4MefOnaOxsbFou0JjsVB1Xy8YHISNG+dvNzBQQrY3T35EDG1K41RDK01a8cwXSTVI0+RwOmBVGI+uu1j1Xcs5WZbquy4yODLIxgfnv08Dtw6UJXuUn7IruY6uwWOt81eTunF4dgH31CA8bqPfvnfA2wwvxVJ+WF7fzJQfHow90Z/QNGhtnT+z5fBwCUaHD2VttVHIwC57JeSCDrRQ5WRhdxu/yihJTeKJTuFSukNh/Ss1kRmJcZRCBrYCSjBU4kSG2HyP+Qxae1vNjF26AsfD8FozXJCEVXGUgEGwMchw97D5bKQMsYcTHRIf2iWeKGDVgxd6jp98IVWnOzvQId2ax45EB1l3x/z39si9A6zraTfPJTVcr2mOEf3d7Azpoz8Pccc3ojxzMiKHq0eIyPOsuXiOqhrpuVgikSwcXsx9gvq2lhxEHZi/vbZxALW53ZHMyfyMohuEMwIg4qvACGR/Rvvh46jvfd/85/T4D1B/473zX2u5EbARfaefSySSogjZSoI2uxdrcNVmXlUNrpZRqRJSFX7NhNWzGNZsmVHh1xpLNz8PvTlVV0Ybzc3BBy7PGEtO/ZCC/tHYsRgPfW5zXiWY0VQlmFs+94ic70H6CaFyZYJHPv2hp3ZyzUu7ALKSF+mp7vL0W++Sm4QlwvjKH17LCM6tILZe4kf/6NS0RsOyU2jnmshPfwagoy5JMvlyE4vq/T8XxGIFqlwFy1TlKqUP5ttWqf6RoQ/m4aBypmQB8UinEBU5nqipoiclaOQ78QmIXrfobwyODHJf/0b6U/umCul3nUm4vTPbF+Jrf6qoPu+mjCpFdlYDLtpW6T6YF//0BEpArwyfvgeOQgfqXVXgtH94EvNsEyfznsvTmDcIXrgXNoZ1n24mRi/dhDI2jI4SoocoB4hk3ycZd+k6QlOM6OCoAuHp5fhOy86Xx+EvmXd/qBPkBuEKwO4GYfCP/90TI7OvD7Zvn7/d3r3Q1eXwR8QZ2hnjml2dAAUzXzx9Vz9td5cg6Dy4uZYSkKm4Zf1EBQRi9h3tY3ts/v6xN7KXrrWl9Q8/ZldynbRBDgWrSeUa5CN9cNjGeF2/F1o9Gq/WWBov3M/zxpIHY8+JWLN0Kyic2bJk3cqnsrba8GRDoFxIKI4fZZSkJvFEp3Ax3aEjR1JqIjMAJWMiM5TUckipE5nofJ8idizG5s89BAejMBGabd84Bpt6eORzt8xuYprWOPW1VpoaE1nVKS10XSE5EaTp48OoFbAg7iqCOqRv7RLXFbDqwgs9xy++kKoMDBXQId2cxw5/uo/1X51fXzv8qb2s/8qsvmYN14Cicf2lsxnSn/ipmSFdDldvcCLPrcVIoGBVjYpYrJZIagEv/EaiNrsDG9+JzCm2cWYstZkna+OMn/1rAjaib/VziURSFCFbScBm9yKYqBrNq4rHkzIqFU5qs70xOZ5T48rEAJSGUHqzvWjSEUdrGYL+0cz5PqAz/znVOrXsJ6xkmeAwmaUI2swUp/oaaApoWZtH0qdgQFJXaeqaRC1UIUsimQPf+MNrFYdrjyC2XuJH/+jO+4bY1X1N6l3mJmEdgLt6n+bu29s8PSfHxGIY3d0oGc/RCAZRSp3H0nNMkf4x1xxTLZUzawkvdAqHIsdVNdXJSVnJ48cTKAXulYGCEpr9zEMP6Xz4w4WSEWTzjW/o3HLLbDuR6xZ12TrR73ztTxXV592UUaXIzmrAgziu8aGr4WBvwfinUNsz/rfxXV5jKUG9q2hK7R9+KqwmIv+dPG/fLvMJTvhu2xiZPn3F0Agzm4wnThhDUfPHkgf6VC0jNMU43VdT4cLT6/Gt6RoHnzvIh97xIVc2CM+vQUsqClU1d6Z3dZmvCzWWVNUUHDA7x1hY76PREs+v2V6p+0LtNM3c7d/XZ75qWgnnkUPb3RGevqufk2pL1vGkGix9czB4cnPjo/GiRimYSsHYxBjx0bjj33Cb5gvt9Q+77YphKUu59ysxkaDz4U5ix2Ilfb9vCUXMYJCG7H5OQ7Bwtq7zbd5nu+3KQTxeXCkBU1keGzPbgSdjz4lYi0RMHb4l51EEg2Vacy5B1krsowZU2lvb6VrbRXtruzuGckA1Myi1dpmv0liaxY8ySlJzlKRT2FVuLadQ7vyXSJjHY6XpLWpApXeTOVcqOSFw1vvopmi2jEtNZErORKaUayITne8tjkVgfz9M5EywEy3m8WOz5xV/UuVT/9ALirkZOBNdV0CBT/9DlPiTUu6K6pC+tUtcV8CqCy/0HL/4QrxxhniMTR3Sbdu44RJ7elhuO2u4Nq9QOXSsnX1PdXHoWDsrWuTmYC9xIs8jayL0b+2npTFb1gYbg3JzcBWj6RqDI4P0He1jcGQQTS+j01biDl74jURtdgc2vhOZEzkG/fuhZSL7eMuEeTxyLOOgX/1rVsKmHJvJKGIj+lY/l0gkRRGylQRs9kwfkApsOB+2XWC+Wj+R5wNycO7VZl5VNC77FUvCzYV/UU7HocjmYEhtt58cM9uRPZaMgMKh1bBvLRxabb6HnLHkZC1D0D+aOd/rAbLOSQ/I+T6PWvUT+lkm2CGgmhsZAPJGbOr9ldGS1lKPPreHFWrhzSNgVpxrUTWOPrfH8W9Iahff+MNrFadrj4itl/jRP3r37W3c1fs06uKTWcfVJcmK2xxMZ2fW5mAAZZ55zJbamdIHi2Nk6YNprIRNuZ+dTJjHx3w+t9YqGTqFkaNTGGXSKTJFTkDR2LBmkG3X9rFhzSABRSsqclxVU53IQVVlqKsXg9lCSxZ6asvw0LZoelI7rf7E1qnkthO5blGXrXrmsC39Tj1zOH3Mt/5UUX3ebRnlVHZWAy7bVvHRuLn58+Ei8U8P72ds6Cr/2/gur7GUoN5VNKX2D09inm0iIv+dPO/MrhVAYwODbKOPDQwSQCvYzsJV16XghO+2jZHp0zcUlUO0s48uDtGOoZj9I8+n74GPxkv8FO8gPMWIDo4qEZ5eL+OrAZXwqnB5vqwAda59s6TmseacQlkHotEyrIWEw+aXzZc6Opw9gLxIZNp2dwTtix0c2RNn8sUkDZc0s/a2MC2LyjQ5uXxzk68my9puIQivDBNsDM6bvTy80rmA1XSN7oPdBb/fMPOa0XOwh45LO/ydXckpoQi0dNirJrUsbAaRzJfhZZl7E14eSZv9N7Ody2PPoVgjEoGODpeyxDo9KYmkkvCjjJLUFCXpFHaVW00z2xWS5YZhyvOeHnNCKWECsRxJhSpIRjdFCzuS3JzIHMz31q3CUMh3PAVQyL5VySQceDZCZ7Sf3o90E1o6e93jrwTp+XqUA89G2OJf1dlbBHRIX9slripgkorGdWeI//DCNl57W5gTdwZp0hIECvyOjkJSDbL2tnx9TQ7XhcepPI+sidBxaYdvMg9L3MXNKuQSF/HCbyRqszu08YVkTspoUIxCFkPqNzKNBj/611LXYBi54YugGKkZPMdG9LV+LpFIyoOAzR5ZE+HwB+5k5c92s0KdDXI5oamMvm0HbWWYv2vQvPInHvkVHeGzCqb6ZMJWhv7MdkL+VCd6jqB/VM73Dqg1x4OfZYIIVmKMglXQoiVXQZuceLGs7SQSiY9wEmvkED/6R+++vY0vflJjzyNHePH4JJesauC2zWtZVN8y/4f9gMN5zLba+YbN557ZTtfM+aigfmcACvyox7TVpG/cf4QiDK0uZBsHGHvbDtpK1CksUXLzVbG8WISxM0G6/7GXA89GCooc19RUhzEYW/oiXE0/vXQTIiOmgiB3EOWZfRGGv2Se37LLXoDGpakNa4WsLB0ax812rMv6i93rFnbZOhjfvrSvROWgFzLKieysBjywrRJnT5qVYYH8sRQAdDgYJfGZw/gal9dYPFTvfEXV9I8UduW/k+dtdcFrxmNEc+axMYL00MszoUheF/TEdSk44bttYzjy6bvso/EKP8U7OJpiRAdHlQhPPy7jl4LcICxxFcdGpqbN/yErzURnpznyMkdkkdTRViaE3MFrZUIoZxJXdZHKup728nxZIVxcaMqsqhsAwudDswpJDeJvgF6gnd+wMi53PtyJgpIVqFy0gp0gIhm+2lvbHf+Or7GqSdlpd2WvmTEMhWyHwQJleHGa8sPFsedArGV9tr295FMo70lJJJWCH2WUpKZwrFOIKLciGbtKnFAcOZLcmsgczPeit8r66IFnIzz6ow7Cl8VpXpIkebaZ+AthdEMVOpWawKYOadfeWDC7xDUFTFLx1FhgqBe2sbpIZXRHL027OtFRsjYJW5nGx3ZEiyZmk8N1YSlFnluZhyXVjVWFPDfRgFWFXFaN9jFe+I1EbfYSbHzbMkfUaPCjfy11DcUrHObbiL7XzyUSSXmwu+4zFqNt+B4MNXv+blZ1VgzfA8G2sgTu1Jh55T26Nv+GcA/9ikJ4ufBvk59MnM4JTbfXzrY/1YmeI+gflfO9Q2rJ8eBXmeAEkYTogjQ0XlLWdhKJxEd4XF7Ij/7RRfUqPdvWLfRpOMPBPDardqY2wqVIJAw6O5VstfN8m889s51I5Uw7tprEU2LHYnR+7x4UjKwY2yfe0NBfuof+JW0l+babm83Nwf09neRu0Gx5S4L+nk46o/00Nxf+DVfU1BJiMMaJ8CgdhInTTJIkzcQJo6NCxtBrWdIEm7rNqpboZG9cS0Uvb+qhZcntBX/aznVnumzVgMb1l87GeTzxUzPOI8tl62B8+9K+EpWDXsgoJ7KzGijRttJ0bV4/wukXLoOJ0BwnEYCJlZx+4ZXcvfb+wuU1Fq+rR/qFqukfGdiR/06et6rC/q4Y1+wqMB+TYD+dPL2tH1WdnY89dV0KTvhu2xiOfPou+mi8wG/xDo6mGNHBUSXC04/L+KVgJ4GpRFIS1pzT1TUbCzMnsRi0tsLGjbB9u/na2lqgjjmzaSZacrLQBYN5M+d8mRDAzISgLVwld3GEb649rOq7kTfDSCsMBqGv2XwdaYXImyHUGCqp+q4XWBmXWxqz+0ewMViWidaXGb78jJXhpSFnvDYEzeNeZ3ixUn4oSuG/KwqEQoVTfrg09kBIrHmHL09KIikzfpNRkprCkU4hqtx6nLHLciR1re2ivbV94TJZO5jvRW9V5k/ohsqhY+3se6qLQ8fa0Q11TpVCMjeWXaIU2bagoFSEXSKpUVy0GfyGV7Zx290Rnr6rn5Nqtr6WVIM8fVc/bXdLfc2vSHkumYv5qpAD9BzsQdMryWlbY3jhNxK12d228Z3YVz7zr+kJe9eQ2U7Kc4lEkiajekxeFXJrTv9Rj9muDNSQeeUtYzF4rBUe3wiHt5uvj7WaxzPxYyUAny78v6AsY2wa9EKFlTCPj06b7XKx7U8V1XME/aNyvpfMix9lQilYiTFau8zXMq1lrL3iNk5o6pzyIKGprL3itrL8nkQi8ZBSYo0kC4/gPDardmZvDgYwDLNgSZbauSxs6mVzpGSjIWS2s6jVyplVQKZvWwcOvQH7XjNfrS5Rqm87fJ3GV3/PtL8DOd0qEDDAgK/8Xg/h6zy0fUqMwdBROUQ7++jiEO3m5uCcduGVYYJtz8DWLdCYyP7+xnHYuoVQ27Ml2yWRCBz+ZozRr7Qy+Kcb6fvUdgb/dCOjX2nl8Ddj2S5bB+Pbl/aVqD7vhYxyIjurgRJsq9ixGK29rWx8cCPbY9vZ+OBGWntbiR3L9uks095h6yfstltQXFxjqVX1rqr6hwCOnrem0dbXjYJRoNay6SNv29eTVgp96rr0FEc+fZd8NG7jx3gHR1OM6OCoIuHps2X8kpAbhCX+wkqXkZuywEqXUWyT8MgIDAzA3r3m6/Bw3kgUyYRQ66gBlf1tXexvhpacOuMtdbC/GR5u27ZwGz0EiKyJMNI9wsCtA+yN7GXg1gGGu4fLkoXDlxm+/E4oAjeOwHsHYP1e8/XG4YXZeGel/IB85WSBU37YFGvypCSScuMnGSWpKRzpFKLKbZVk7BLGwXwveqt8rFJUPGpApXeTeXNzF82s99FN0YqwSySVj6ZrDI4M0ne0j8GRQblRLQMvbeO2uyMsnxzhyL0DHP7UXo7cO0DT5LDcHOxzpDyXzIVIFXKJj/HCbyRqs7tp4zu1r3zkX/vJaXvXkNlOynOJRJJGpHqMxJ+MxcwqtLnPcTJhHs/cJOxHv6JPF/6bGlvoPm3+O3dToPW+57TZriRE9BxB56Wc7yXz4keZ4EPUukWMvm0HUFwejL1tB2rdIo/PTCKRlIxcGKxsBOexWbWzSNC7oWSrnQEVrkz1jwLplAC4Mpq92aFWK2dWAV74ttVX4qxYMp63OdgiEDBoWTKG+oqHto8XMRgpu0S5/AD0rIZb22Fzl/na81aUyw+Uxy4Zi9E23Unzkuzn2LwkQdt0jm3sYHz70r4SfRheyCgnsrMacGhbWVUqc+WPVaUyc5NwS4u9bUJ22y04kQjaSy9ypO9eDv/lpzjSdy/aiz8reY2lVtW7qusfNnH0vFNKYfE0Btm+SK9dl5oGg4PQ12e+VvPGYz/ix3gHR1OM6OCoMuHpo2X8kqguiS2pbEpJl2EjzUS1JTJ1FV2j7VQfikJ+5jHFlNltp/aVLfO327hVwc6XGb4qAT9lePFxyg9fZsT35UlJJGXGTzJKUjM40ilKKXNb8EcqJ2OXMILzvZNb5WOVouKJrInQv7WflpzAyWBjkP6t/WVJ/CORzIfdDLy1ite2sbpIZV1PO+u/0sW6nnbURVJfqwSkPJcUw6sq5BIP8MJvJGqzu2Xjl2Jf+cS/9sKyMGME0YvM3zoKo4R4Iacqg5TnEokEkBWuKp2MCtD5FKgA7Ue/ok8X/sMrwzyjBtmShMRM9t/GZ2BLEp5Vy2Qfi+g5gs5LOd9L5sSPMsGntF17N0+/9S5O6tnjM6mrPP3Wu2i79u4FOjOJRFIycmGwchGcxxIJ3dbXZrULRSDcDw05/aMhaB7PTepSq5UzqwBPfNt+tb+9iMFI2SXBJc2w+hCs3QerDxFasqI8dkmGbZy/JbWAbQzi4xsfqQU9ZAAASlhJREFU2leiD8MrGeXg3lY8DgaGaJVK6ydQCvmAzOOVZL7FjsVo/eolvOund3DdL7/Ku356B61fvaQscRu1qN5VW/8QQfh5C/oivXRdxmLQ2gobN8L27eZra2vhmowSd/BjvINj953o4Kgy4emTZfySUAyj0G5MiZ+YmJhg8eLFnDt3jsbGxoU+HfcYHDRnpfkYGDBHnL++vro4NQiP27hZ7x0wFxxrGCsbE5BldFmB0XKRtELQNDMVTzJppkMJhytzVpf4Bk3XiI/GSb6apPnCZsIrwzKbukQimRNhncKJchuLQaf5G1lJeSxPQAUa5UIIzPdOb5VUKdxDzq2ShcKSz7mLbNLmy0baxhK7SHkuyWVwZJCND86v1w7cOkB7a7v7JySR2KXC7avBQbhvY4x+zGsIZMzf1qbhTvq5fSBScL1EynOJpMaR64iVjZPn57d5z8cL/5Z9HMDg+vOhWYWkBk+8Yc6xC2ofCzov5XwvKYrfZILP0WamOPrcHiYnXqSh8RLWXnGbrBwskVQLcmGwMhGYx6L7jnBH17p5v/LeviP0bMtpp2twOm5u3Dy/2dw8V0yXGotBPHVOWetRqXOq1s1xFY4nvm2/29+OYjAMDGN2t4qiGIBSPAbDLbuklHsrMr5T+Mq+EtXnvZRRDu5tRSP4LJzIHadjz2/Pwqu4DU/UOw/urd3rcNw/qgTbz1vQF5nZPIBGmDjNJEnSTJwwOmpmc8dYzy93N6B0z3iLX+MdSnLfiQpDaRsL4eb+ULlBuAKomQ3CfX1m6or52LvX3JYviKaZGTESicJFihXFTFYwPCzlESN9cNjGs1i/18xKXOPEjsXoPtjN+MR4+lioMUR0U1QGQEskNUghmRBsDNK7qVfKBIlEMidCOoVT5TYWg+5uGJ/9DUIhiEalRygHeaskEomma7T2tmbJ5UwUFIKNQYa7h2WALNI2lkgkzrBkbWIiUTDjuZS1El9TwUaDZVJeMx4jSjchZq9hlBB3EOWZUESul0gkksLoGjzWCpMJClehVcwKLzcOV3cQZ6XidB3YT/Oezxf+pX0sqQn8JBMkEolEIhHF5jz20JF9fHjDdTDRAgQKfJEOjeN849Bhblm3rbRzGouZ1UwnM86pIQRXRuXmYJ/iiW+7yuzvnfcNsfuzK9HOrUgfU5ck2PH5Me6+vc3bk6n1GGlRfV7KKPcQeBZ9R/vYHpu/3+6N7KVr7Wy/FTbfCj7vIFzZuyDPu6riNjy4t4WedzAIvb2Fn7c0720g6Iucaw1ujCA99Ja8Bmf9xnjhYbHQ7tGaws/xDnJ8+xO5QbjGsTrAP//zOTZtaqxeIe1Bpl+ZyNQmfs885kN8leFL4jpT0xp7HjnKi8cnuWRVA7dtXsuievm8JbLCnEQiKR1teoqjj+xh8viLNKy6hLWbb0OtL5JJXpa5dR15qyRzIW2A6sevWR79jBwXEonECbIKucQuvtTPfXlS9rBMyoChcX1G9vInCKMrqlwvkUgkcyMrXFUupawD+2ne8/nCv7SPJeXEt/3JTzJBIpFIJBJRbMxjgyODbPzD++Dh/tSRzE3CuvmytZOBv7q9POtEPqvWKJkfT3zbVWJ/p2PqdAWOh+G1ZrggCaueQAno3q8DyBhpsfgkkDLKTWzaVqXEL9g231Iyx8CwpAwAhiXZyilzPLhuLxC9t/kJH8onz51WlHVi3tecS0DQFzm0M8Y1u8znna1Bmu2fvquftrudP28Ptl1lUXPPWxAv4x1E97DIZ+c/5AbhGsfqAHCOYLCxaAaPiqeETL8iCyIyE8L8aNMap77WSlNjgkAg/1noukJyIkjTx4dRq3VTpJwNJUUomMlu8Ql2fGHU+0x2El9RVZnKJBLJwiCawq/YZ6RyK5G4TqFKMMHGIL2beuUGpioiMwNvQIfwcWh+DZIXQHwV6Ckvfm4GXolEIpGII6usSebDibkkmR9pUkokkpKQ1WMqk2qqQCUnMleRy+X+QPohJRKJRCJZONJxQEPXwMEoTIRm/9g4CpvuINT2jIwDqnE88W1XuP3ty5i6arKNU4jYcNLOqExcr1KZGhfG5HjW5mALAwWlXONCYNHHaeVkL7B9GWmZU6TcaxlkjpcVZWt2zc6uLzL1MIzxOcZSqLSH0dcH2+cfFuzdC10lDguvnrdvE+TZxAudUO5hqQ7kBuEaJ3ODsKKYHaBqM7c7yPTrxFCRi1lzMzgI990Vo7+nEwyyNgnrugIKdEb7uX1XpCxZRXxHzWqukvnYed8Qu7qvSb3Lzwp5V+/TUsGqYfyeqUwikfgcpyn8QCq3EonHpLMb5yy4yCqH1Yel3938PPQehNDE7N/GGqF7Exy4XOp3EolEUi4qfdFP4h6lmEuS+ZEmpUQiKQlZPaYyqZIKVICcyFxCLpf7A+mHlEgkEolk4ZmtehqA49cvfNVTiS/xxLddwfa3b2Pqqsg2FrHhpJ1R2bhapdKrytqCiz5+lSFCl+HBvfWqomzNr9nZ8UV68DCq7XlXS+IKN3VCuYelepAbhGuczA3C0FjWDB6+RCDTrzRU3MHKKnLzVTF6P9JNaOnssxj9eYier0c58GykLFlFfEfNa67uU6nr9FPTGg3LTqGdayJbsbLQUZckmXy5iUXVWllbMid+zlQmkUh8jpcp/CQSSUn4MruxxDU0XeMTv7+cv3ngDFDIvQqf+OhS7v/7U/J5SyQSiUTiEtJckkgkEonEJSq8ApXEPeRyuT8o2Q9ZwRtIJBKJRCLxG55UiJXUHJUaQ+kEX8fUVYFtLGLDeR3vIBPDuoNb85L+Uh+BofnHqt62l8BbHY5VB4s+rldOdoDwZYz0wWEb5V7X74VWZ/fWi4qycs3OJh48DOtZJBL58h/K8yy8et7VtB/MLf1O7mGpLtzcIFxX1m+TeIJhwNiYKTyqsnprJAIdHfNKR03X6D7YXVDZMzBQUOg52EPHpR3SoBCkudl8PfBshEd/1EH4sjjNS5IkzzYTfyGMbqhZ7aoGTTM3pxfSlAzD1GR6esz+WdOaq3MqOdv0nkeOop1bN0eLANrZFvY8coSebXO1k1QrzRfaE4p220kkkhoiHi/uSYEaMAAkksohPhovulgGpi06NjFGfDQuK8pWAaoBvd81/53rXg1gbhKOHjTbSSQSiUQicQdpLkkkEolE4hKhCLR0yA2Ekizkcrl/KMkPWXCTQxCu7K2YTQ4SiUQikfiJyJoIHZd2yE1ukrJRyTGUTvB1TF2F28aiNpyX8Q7VUg3Sj7g1L/3kv5pZZ7fdWx3+iINFHzWg0rupl86HO1FQClZOjm6KejovC1/G+Tblm912Bbh4uQbMfw/stiuEXLOzid0NNiVsxFFVU2/o7DRlfeY8YCWIiEZL89958byraT+Ym/qd3MMisUuh7eOSCiGZXOgzcBFVNWeKri7ztcDsJGKoSMQIh80JSVFAN1QOHWtn31NdHDrWjm6oKIpZ1DkcXugzLTMimoxEGCtTWe4tTiTM47HYwpyXXV48PlnWdpLqI7wyTLAxmHY65KKgEGoMEV5ZbcJTIpGUjF3FvqoNAImkMki+am8c2m0n8TnxOA2nzhR1ngWAhpNnpI0okUgkEomLSHNJIpFIJBIXCaiwvN2sTLK8vWICoCXuIZfL/YNjP+RYDOKd2ZuDASYT5vExny/KSyQSiUTiU9SASntrO11ru2hvbff9BgWJf6n0GEon+D6mroJtY1Ebzqt4B6saZG6Mf2IiQefDncSOVWFH9xg35qUXzoQZOxNE1wuPVV1XGP15iBfOlDBWHS76RNZE6N/aT0tjS9bxYGNwQaqLCl/GsrCZuKuIHATFrF6+rIR7uyoOjWOYqe4LoUPjqNnOIXLNziaZG3EKUaaNOJGIWSW+JXtYEAxmV493ihfP2/f7wXQNTg2aVcBPDZrvC+C2fif3sEjsIjcIVzBVV71VEBmY7R5WVhHI103KlVXEl0jN1TXmy1QGZqYyrbDe5AsuWdVQ1naS6sPKVAbkOTQXKlOZRCKpEDzIGieRSMqDr7MbS8qPtBElEolEIllwpLkkkUgkEolE4h3SFeIfHPkhdc2sHFyg6kr62I96igYzSiQSiUQikUjcpRpiKJ0gY+rcQ9SG8yLeYb5qkAA9B3vQpF3iO5pWqHT/Yy8o5G0S1nUFFOj5epSmFSWM1RIWfSJrIox0jzBw6wB7I3sZuHWA4e7hBalILXwZARWuTG3MyNsknHp/ZbSkBAUvTyZhU3fqXe4m4dT7TT1mO4fINTubeLgRJxKBkREYGIC9e83X4eHSNweDN8/b1/vBxmLwWCs8vhEObzdfH2vNS77nhX4n97BI7CI3CFckOkubJquvemsGmgaDg9DXZ74WEogyMNtd3M4q4kuk5iqMnbEK1ZFt+rbNa1EXn2Cu7ErqkgS3bV7r5WlJfIbfMpVJJJIKwaOscRKJpHR8n91YUl5KsBHt2koSiUQikUjmRppLEolEIpFIJN4hl8v9gyM/5Ol4fuXgLAyYHDPblQFN1xgcGaTvaB+DI4MywF8ikUgkEolkHqohhtIpMqbOHURtOC/iHXxfDVJSlHAYnjkZYUtvP4lfZI/V8VeCbOnt59lTkdLWY0pc9HGjcrITHF1GKALhfmjI2ZjREDSPh0qTg80XNsPlB2BrJzQmsv/YOG4ev/xASftq5JqdAB5uxFFVaG+Hri7ztVwFAL143r7dDzYWg3hnvp9tMmEez9gkXLJ+ZyPATO5hkdilbqFPQCLKbAYPlPuB6suYFIuZWRQyBWUwaCbSyJwLLUMlMZEomGlIQSHYGJSB2SUQiUBHhzkhJZOmkRgOV2HlYAtLk0kkCqfxUBTz71JzBeyPVaiObNOL6lV2fGGUXd1NmLI4M8eGKZt3fH6MRfUthT4uqSEiayJ0XNpBfDRO8tUkzRc2E14ZllkOJRJJcayscZ2dpr6RqYeUOWucRCIpDSu7cefDnSgoWbaozG5chTi0EUVsJYlEIpFIJHMjzSWJRCKRSCQS75DL5f7BkR/yDZuL7XbbzUHsWIzug91Zgf/BxiC9m3rl5g6JRCKRSCSSIlRDDGUpyJi68iNqw3kR7+DrapCSOZldj4nw6I86uP7SOM1LkiTPNvPET8Pohkp/f4nrMVWy6OP4MkIRaOkwE3e9kYTzm2FZuKTKwRbpfTWXfwvjskfheBhea4YLkrAqjhIwCJaYAKBKHp93VPhGHC+ety/3g+ka/KgbCpyPeUyBH/WYYzmglqbf2Qwwk3tYJHaRFYQrjVQGjzOtX6vK7DmxmDmJ5GZRSCTM47GMiuyWoQLkZTOSgdnlw62sIr7E0mQgP92J1FyzEBmrUD3Zpu++vY27ep9GXXwy67i6JMldvU9z9+1tC3RmEr/hl0xlEomkgvAwa5xEUhPoGpwahJE+87WM1StkduMawoGNKGorSWS1GYlEIqlVbCRDTiPNJYlEIjGRurNEInEbuVzuL4T9kOfbXGwv0E5kjokdi9H5cGdeVbDERILOhzuJHZMOMIlEIpFIJJJCVEsMpYUTP4WMqSsvTmw4p/EOU9Ma0X1H+PRfHSa67whT04Wft2+rQUpsYa3HNK9QOXSsnX1PdXHoWDsrWtTyrcdUyaKP48sIqLC8HVq7zNcyycGsfTUBA1YfgrX7YPUh8z3l2VdTJY/POyp8I47bz9uX+8FOx/MrB2dhwOSY2Y4S9DvBADO5h0ViB8UwCuWMkfiJiYkJFi9eDF3Xwa8/BQFzl//eyF661nYt8NmVD02D1tbiJdatTEbDw9lzY6HMpKHGENFNURmYLXFGoWwcoZBpKUvN1dFYtT4zX6ay3PHtV6amNfY8cpQXj09yyaoGbtu8lkX1FXDiEolEIvE/mlaxWeMkEt8wFjMz+WU66xqCcGWvmY2zTGi6JrMb1wp/uxP+eDecyVjk/DUV/nwH/M+704ec+jVqGVltRiKRSGoTm8mQ85DmkkQiqWWk7iyRSLxELpf7C9t+SF2Dx1phMkHhKieK6Se9cTgrAFlkjtF0jdbe1rzNwbO/YFZ2Ge4elr5SiUQikUgkkhyqKYZS+in8hRMbTiTeYed9Q+z+7Eq0cyvSx9TFJ9jxhdG8DUmWzTBfNUhpM/gbT9ZjqmTRx2+X4dW+Gr9dt8Rd3H7evtoPNtIHh7fP3279XmjtcqbflRBgJvewVD7W/tBz587R2NhY1u+WG4QrgPQG4T8Czps9PnDrAO2t7Qt1WmVncBA2bpy/3cCAmUAjExmYLSk7UnMtitOxaiU6gWwFyMpUJjMHSSQSiUQikUhKZiwG8U7yA+BSSme4v+gmYWlXSgpi9SndgBeAs8AS4DIgoGT1qVL8GrWIVW0md2HYygIqK3JLJBJJdWL5CHNXpqSPUCKRSIojdWeJRLIQyOXyCiXtH4VsH2lh/6joHDM4MsjGB+d3gFVbPJNEIpFIJBJJuaiGGErpp/An2pTG0T1xJl9M0nBJM2tvC6MuKt2I23nfELu6r0m9C2T8xSx2VqhqYbqP6AE4fj281gwXJGHVEygBXfYRicRlZPyTpBLxTb89NQiP2wj+eu+AWQUcB/qdDDCraeQG4Rond4NwtWbP6euD7TaSLezdC13VUzhZIqk4ShmrMtu0RCKRSCQSicQ10hUyimTXK1IhA2SGY0kRBPuU9GvYR1abkUgkktqkhGTIEolEUrNI3VkikUgkwozF4Efd2T6thhBcGc3aHOxkjuk72sf22PwOsL2RvXStrXEHmEQikUgkEkkRKjmGUvopfEqhThUMQm9vSZ1qalqjYdkptHNNZG8OttBRlySZfLkpr3qhSNVhiUQikUj8gjatceprrTQ1JggE8rda6rpCciJI08eHUTPmPiH9TgaY1TRubhAupK1JfIyVYSm6KVp1xlNzc3nbSSQSdyhlrEYiMDJiJjTZu9d8HR72v2NLIpFIJBKJRFIBnI7PsZETwIDJMbNdBlb22hMT42w4H7ZdABvOh+TEOJ0PdxI7FnP3vCX+RbBPSb+GfeKj8aKBAwAGBmMTY8RH40XbSCQSiaTyiMeLbw4GM6Py2JjZTiKRSCQmUneWSCQSiTChCNw4YlYyWb/XfL1xOGtzMDibY5ovtOfYsttOIpFIJBKJpBap5BhK6afwIVbZwlzneyJhHo85j3fY88jR1AbfYttNAmhnW9jzyNG8U7qnpw3tXLZdoE80c09PWymnJJFIJBWFpmsMjgzSd7SPwZFBNF1b6FOSzEP8SZVP/UMvKOZm4Ex0XQEFPv0PUeJPZu/lE9LvZICZxCXqFvoEJGIEG4NEN0WrsoJROGwmLEokskurW1jVA8Jh789NIpHMUupYVVVob3f1FCUSiUQikUgktcgbSeF2mq7RfbCbm95s0LsMQvWzzcamoee0Qc/BHjou7ai6JF0SGwj2KenXsE/yVXv31m47iUQikVQGSZti3W47iUQiqQWk7iyRSCQSRwRUWN4+ZxMnc0x4ZZhgY5DERAKDfAeYVTEuvFI6wCQSiUQikUjmolJjKKWfwmdomlmusNDitGGYC9Q9PdDRYXY6QV48PincLvuUsjdWGYZS6ilJJBJJxRA7FqP7YHdWYo1gY5DeTb1VuResWkgm4cCzETqj/fR+pJvQ0tnnN/5KkJ6vRznwbIQtBVQd2/qdDDCTuISsIFxBxD/0JYY//bOqnRBUFXp7zX8r2TZB+n00Kg0CiTiaBoOD0Ndnvmo2kq9MTWtE9x3h0391mOi+I0xNy4wtFnKsSiQSiUQikUh8yfk2s+ZltIuPxrlaG6e/GVpyUqi11MH+ZrhKkxmOaxbBPiVtJfvIajMSiURSm8hkyBKJRCKO1J0lEolE4hZO5hg1oNK7yXSAKTnB/tb76KaoTLYoqR50DU4Nwkif+SqrPUk8xknMm0QikbiJ9FP4jHg8v3JwJoYBY2NmOwdcsqpBuJ3LpySRSCQVQexYjM6HO7M2BwMkJhJ0PtxJ7Jgspe5XrHXqA89GaO0eof2LA3R9dS/tXxxgdc8wB56NZLVzhAwwk7iE3CBcQbzj2GdQ//kSGKveCSESgf5+aGnJPh4MmscLlliXSOYgFoPWVti4EbZvN19bW83jxdh53xANy05xR9c6vvpH67mjax0Ny06x874hr07b98ixKpFIJBKJRCLxHcvC0BAkNwvtLAo0hMx2KU5OJOhdZv47kPMx6310mdlOUoM46FPSVrKHVW0mN5DUQkEh1BiS1WYkEomkyrCSIeeuc1ooCoRCMhmyRCKRZCJ1Z4lEIpG4hdM5JrImQv/Wfloasx1gwcYg/Vv7q7bogaQGGYvBY63w+P/f3v1HR1Xf+R9/3Qw/BMsEXUCGzJDYtSIq0rNoha6zBOtq/FZJHfNFoXVx17rbtUqiXde1p/3q9h9ou2piPdrVtR73VGA9cbRubVn1a4LjIv5AWHG/LHJsYn50EOVIAkIBZz7fPy4zZJKZzA0kmdx7n49zcoa588nlwmvu/Hjf+76fJdKmFfbt81WePm8PY8uJnPMGACONOsUYk3Q4U7PTcf3ccu08Bcp/LyldYERaganduuXaeaO1SQAw5qXSKdVvqJfRwJlhM8saNjQoxQWoxqS+x7PTJqCNO6q1/vXl2rijWmkTGL7j2ZxghhFAg7DbHOyWEnWeLjbGYlJ7u9TSIq1da9+2tfEah6GLx6W6Oun3XSktVquu1zotVquSXSnV1eUvmP79g5v10/qvKNUzM2d5qmemflr/FZqE+2BfBQAAwJhSFpAWHLu63oADksfuL2i0xx1zjvlYkfEDm4Ozq7Sk2ePtcfChE3hOSXxXcoLZZgDAn7gYMgAMHZ+dAQAj5WTeY2JzY2qvb1fLyhatja1Vy8oWtdW30RwM7+iM2+fnHew3/Z0PztvD2JA5563/DIzd3Sp4zhsAjAbqFGOM0+kLT3CawwnjA7rjRx3H7vVvErbv3/GPnZow/njeI7xJAFBSqXRKre2tWrd9nVrbW/M2+SY6EgNmDu7LyKizt1OJDqZSH4tG9Xj2iZxglk5JH7VK7evsWxrN0YdljBl4aQKMKb29vSovL1fPY1JwsmTPUBOWlrYNOAkVgC2Vsq+aeFFXXE2qV0THP2h1KqwGNemtSExtbcffoI8cTWny9I+ONQfnu35CWoGpSR3cMzPnCy3cL5VOKdGRUHJ/UqEpIUVnRylSAQBKIpWSEgn7SpmhkH2lMU6OB4aoMy5tqc89cWdyxG7kjOQW0NJtT6ns9W8VXWV60S9VduY3h3lD4RpDeE5haOI74qrfUJ9zcCQSjKixppETSgHAw+Jxqb4+9yTXSMQ+mMoFNQAgPz47AwBGCu8xQD/plD1TcP/m4CzO28PIypzz1r85OMOy7Eml+p7zBgCjjc+QY8SxNw3T3SUrTzeIsSQrHDnpN42/f3Cz7v8/s5XqmZVdFpjarTv+sVM/WbUw3yapu1vK16HC+xgAt8r33hcOhtVU05Tz3rdu+zqtiK8our61sbVaPm/5iGwrTt6YPJ6d9/y1sD35BeevuUa2P7SnR8FgcFjXTYOwCwxsED7may3SGdWl2ixgTGttlR5cElez6iSZnHbf9LErldWpWataYqqutpc3rt+m25d/uei6H1i3TQ3XFx8Hd3D6gR0AgJGWr6gQDttXJOMkeWCI0inp44R0KClNCknTo/lP1PmoVfq/S4qvj+/fcPqcwpBxwSYA8CcujgQAQ8dnZwDASOE9BuiD4wYosdZWaYmDp2BLi7LnvAFAKfAZcmzY/ODf6yv1P5WkfudJ295sulMLV/3kpP+eI0dTeviZ7frgw4P648rJuuXaeQUnWorH7Rnvpdwm4czMi83NnAcFwF3iO+Kqe7pORrmtd9axnpTmZc3ZnoPW9lYtebL4B/qWlS2qrqoe9m3F8BlTx7M741LC7ovKdezNNdpMk7BLjGSD8LhhXRtG16FkqbcAGLN2d6fUpHr1bw6WpDIZpWWpUQ3a1F0ryX6n/uDDg47W7XQcxr5CH9i7e7tV93Rdzgd2AABGUqY43v/yTd3d9nKK48AQlQWcnZgzPSpNDssc7MqUy3IYSdbkiD0O/ub0OYUhC5QFOOgBAD4UCHASKwAMFZ+d4UacMA64A+8xQB9Oz8fjvD2MkKTDp5bTcQAwUvgMWXqpdEr/O7VOFy2TmjZIkd7jj3UFpdtrpLdS69WWXn3S38UnjA84nlgpFrPPc8o3SUJJZ14EgBOQSqdUv6F+QK+BJBkZWbLUsKFBtXNqFSgLKDo7qnAwrO7e7ry/Y8lSOBhWdDbnoo1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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr16 90032296 90032796\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "seq_onehot = utils.one_hot_encode_along_row_axis(\"AGGTGTGGTACAGGTGTGGTGTGGGTGAGCAGGAGTGTACAGGTATGTACAGGTGAGGAGGTGTGGTACAGGTGACCAGGTGTGTACGGGTACGGACAGGTGAGGAGGTGTGGTACAGGTGTGGTATGGGTGACCAGGTGTGTACAGGTATGGACAGGTGAGGAGGTGTGGTACAGGTGACCAGGTGTGTACGGGTACGGACAGGTGAGGAGGTGTGGTGCAGGTGTGGTATGGGTGACCAGGTGTGTACAGGTATGGATGGACAGGTAAGGAGGTGTGGTACAGGTGACCAGGTGTGTACAGGTATGGACAGGTGAGGAGGTGTGGTACAGGTGTGCTATGGGTGACCAGGTGTGCACAGGTACGGAAAGGTGAGGAGGTGTGGTGCAGGTGAGCAGATGGTACTCCCATTGCCCTGCAGGTGTACAAGCAGAAAGTGAAGCACCTGCTATATGAGCACCAGAACAACCTGACAGAGATGAAGGCTGAGGGCACTGTAG\")\n", + "\n", + "st = 100\n", + "end = 400\n", + "\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=seq_onehot, class_no = 16)\n", + "ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=seq_onehot, class_no = 16)\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/chip_seq/chr16_90032296_90032796_st100_end400_deepexplainer_topic16.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7c908aff-3db8-4a4f-a411-bd57b4caa0e6", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr17 83096431 83096931\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "seq_onehot = utils.one_hot_encode_along_row_axis(\"GTGTACCGGCTCAGGTGTGCACCGGCTCAGCTGTGCACCGGCTCAGCTGTTCACTGGCTCAGGTGTGTACCGGCTCAGGTGTGCACTGGCTCAGGTGTGTACCGTGCACTGGCTCAGGCGTTCACTGGCTCAGGTGTGTACCGGCTCAGGTGTGCACCGGCTCAGCTGTGCACCGGCTCAGGTGTGCACCGGCTCAGGTGTTCACCGGCTCAGGTGTGCACCAGCTCAGGTGTGTACCGTGCACTGGCTCAGGTGTGCACCAGCTCAGGTGTTCACTGGCTTAGGTGTGCACCGGCTCAGATGTGTACCAGCTCAGGTGTGCACCGGCTCAGGTGTGTACCGGCTCAGATGTGTGCCGGCTCAGGTGTGCACTGGCTCAGGTGTGCACCAGCTCAGATCTGAGCCAGCACAGGTCTGCAGGCTCCCACAGGTCACAACAAGAAGCAGGTGTTTCTGGGCGAGGACCTGAAGCAGCAGGCTGGGGCTGGGCCAGGTCCCAC\")\n", + "\n", + "st = 100\n", + "end = 400\n", + "\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=seq_onehot, class_no = 16)\n", + "ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=seq_onehot, class_no = 16)\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/chip_seq/chr17_83096431_83096931_st100_end400_deepexplainer_topic16.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "1f84cd80-c668-42f8-8fbf-6a3394054d0e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr13 113624773 113625273\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(48,ntrack*5))\n", + "seq_onehot = utils.one_hot_encode_along_row_axis(\"GTCTCTCAGGGTATCTCTCACATGTCCTCAGGTGTTTCTCAGGTGTCTCTCACGTGTCCTCAGGTGTTTCTCAGGTGTCTCTCACGTGTCCTCAGGTGTTTCTCAGGTGTCTCTCACGTGTCCTCCGGTGTCTCTCACTTGTCCTCAGGTGTTTCTCAGGTGTCTCTCACATGTCCCCAGGTGTCTCTCAGGGTATCTCTCACATGTCCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCACGTGTCCTCAGGTGTTTCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCAGGTGTCTCTCACGTGTCCTCAGGTGTCTCTCACTTGTCCTCAGCTGTTTCTCAGGTGTCTCTCACATGTCCCCAGGTGTCTCTCAGGGTATCTCTCACATGTCCTCAG\")\n", + "\n", + "st = 110\n", + "end = 410\n", + "\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=seq_onehot, class_no = 16)\n", + "ax2 = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=seq_onehot, class_no = 16)\n", + "\n", + "ax1.set_xlim([st,end])\n", + "ax2.set_xlim([st,end])\n", + "\n", + "plt.savefig(\"figures/chip_seq/chr13_113624773_113625273_st110_end410_deepexplainer_topic16.pdf\",transparent=True)\n" + ] + }, + { + "cell_type": "markdown", + "id": "8ea95ba0-4751-4565-a2eb-d79e86a5bb07", + "metadata": {}, + "source": [ + "### General imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "84dbae4f-5082-4ac8-b9fb-9d8de68cc85f", + "metadata": {}, + "outputs": [], + "source": [ + "import pyBigWig\n", + "import pyranges as pr\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.patches as mpatches\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "cell_type": "markdown", + "id": "d85d4611-ce65-437b-af1c-5d57b8ed8e5f", + "metadata": {}, + "source": [ + "### Loading bigwig files" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f7947e7b-b097-4b95-901e-bb2752625a2a", + "metadata": {}, + "outputs": [], + "source": [ + "Zeb2_Ab2_bw = pyBigWig.open(\"data/chip_seq/ChIPseq_MM001_ZEB2_Ab2.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "input_bw = pyBigWig.open(\"data/chip_seq/ChIPseq_MM001_input.bwa.out.fixmate.possorted.dedup.noblacklist.RPGCnormalized.bw\")\n", + "ATAC_MM001_bw = pyBigWig.open(\"data/chip_seq/ATAC_MM001.sorted.dedup.q30.bw\")\n", + "Sox10_bw = pyBigWig.open(\"data/chip_seq/SOX10_ChIP.bw\")" + ] + }, + { + "cell_type": "markdown", + "id": "23aad3ac-73bb-42e8-bc5e-43d82a35faa1", + "metadata": {}, + "source": [ + "### Calculating ATAC and ChIP-seq coverage on IRF4 enhancer" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "68ac1615-1e1e-4faf-844f-28280dc974c8", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "irf4_zeb2_ab2 = Zeb2_Ab2_bw.values(\"chr6\", 386829, 416366)\n", + "ATAC_MM001_ab2 = ATAC_MM001_bw.values(\"chr6\", 386829, 416366)\n", + "SOX10_chip = Sox10_bw.values(\"chr6\", 386829, 416366)" + ] + }, + { + "cell_type": "markdown", + "id": "b836a67e-ce45-4914-b256-093a3fd6efca", + "metadata": {}, + "source": [ + "### Loading IRF4 gtf files" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "afb5d9e8-8357-4371-b802-31b8c70ae951", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "pr_gtf = pr.read_gtf(\"data/IRF4.gtf\")\n", + "pr_region = pr.read_bed(\"data/IRF4_locus.bed\")" + ] + }, + { + "cell_type": "markdown", + "id": "d87d981c-9f60-4031-a46b-91a5ff85e4b4", + "metadata": {}, + "source": [ + "### Function to smooth coverage values" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "324d7a2f-f752-419b-984a-d34c6ad1ff5f", + "metadata": {}, + "outputs": [], + "source": [ + "def smooth(y, box_pts=100):\n", + " box = np.ones(box_pts)/box_pts\n", + " y_smooth = np.convolve(y, box, mode='same')\n", + " return y_smooth" + ] + }, + { + "cell_type": "markdown", + "id": "6e700dcd-f249-4b68-8223-1b1a8c031bef", + "metadata": {}, + "source": [ + "### Plotting the ATAC and ChIP-seq coverages on the IRF4 locus" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "4ad6262d-1289-494d-aab9-a6d6dc3f01d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 3\n", + "fig = plt.figure(figsize=(10,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(3,1,1)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "#ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(3,1,2)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(irf4_zeb2_ab2)),0,irf4_zeb2_ab2)\n", + "#ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(3,1,3)\n", + "\n", + "x = np.array(range(386829, 416366, 1))\n", + "gtf_region_intersect = pr_gtf.intersect(pr_region)\n", + "genes_in_window = set(gtf_region_intersect.gene_name)\n", + "n_genes_in_window = len(genes_in_window)\n", + "for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " # IRF4 enhancer chr6 396106 396605\n", + " rect = mpatches.Rectangle((396106, 1), 396605-396106, 0.2, fill=True, color=\"r\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([x.min(), x.max()])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0) \n", + " \n", + "#ax.set_xlabel(\"chr6:386829-416366\")\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/irf4_locus_atac_ZEB2chip_nolabel.png\",transparent=True,dpi=600)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "8679e674-c831-4396-b19b-fa94541c9cf0", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 3\n", + "fig = plt.figure(figsize=(10,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(3,1,1)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "ax = fig.add_subplot(3,1,2)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(irf4_zeb2_ab2)),0,irf4_zeb2_ab2)\n", + "ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(3,1,3)\n", + "\n", + "x = np.array(range(386829, 416366, 1))\n", + "gtf_region_intersect = pr_gtf.intersect(pr_region)\n", + "genes_in_window = set(gtf_region_intersect.gene_name)\n", + "n_genes_in_window = len(genes_in_window)\n", + "for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " # IRF4 enhancer chr6 396106 396605\n", + " rect = mpatches.Rectangle((396106, 1), 396605-396106, 0.2, fill=True, color=\"r\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([x.min(), x.max()])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0) \n", + " \n", + "ax.set_xlabel(\"chr6:386829-416366\")\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/irf4_locus_atac_ZEB2chip.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "417046f6-6d39-469f-a80d-298a86d4f20e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 4\n", + "fig = plt.figure(figsize=(10,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(4,1,1)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "#ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(4,1,2)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(SOX10_chip)),0,SOX10_chip)\n", + "#ax.set_title(\"SOX10 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "#ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(4,1,3)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(irf4_zeb2_ab2)),0,irf4_zeb2_ab2)\n", + "#ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(4,1,4)\n", + "\n", + "x = np.array(range(386829, 416366, 1))\n", + "gtf_region_intersect = pr_gtf.intersect(pr_region)\n", + "genes_in_window = set(gtf_region_intersect.gene_name)\n", + "n_genes_in_window = len(genes_in_window)\n", + "for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " # IRF4 enhancer chr6 396106 396605\n", + " rect = mpatches.Rectangle((396106, 1), 396605-396106, 0.2, fill=True, color=\"r\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([x.min(), x.max()])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0) \n", + " \n", + "#ax.set_xlabel(\"chr6:386829-416366\")\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/irf4_locus_atac_SOX10chip_ZEB2chip_nolabel.png\",transparent=True,dpi=600)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "4693e483-77b8-457f-b603-a8adadd7bb94", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_tracks = 4\n", + "fig = plt.figure(figsize=(10,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(4,1,1)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "ax = fig.add_subplot(4,1,2)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(SOX10_chip)),0,SOX10_chip)\n", + "ax.set_title(\"SOX10 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "#ax.set_ylim([0,100])\n", + "\n", + "ax = fig.add_subplot(4,1,3)\n", + "ax.fill_between(np.linspace(386829, 416366, num=len(irf4_zeb2_ab2)),0,irf4_zeb2_ab2)\n", + "ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(4,1,4)\n", + "\n", + "x = np.array(range(386829, 416366, 1))\n", + "gtf_region_intersect = pr_gtf.intersect(pr_region)\n", + "genes_in_window = set(gtf_region_intersect.gene_name)\n", + "n_genes_in_window = len(genes_in_window)\n", + "for idx, _gene in enumerate(genes_in_window):\n", + " for _, part in gtf_region_intersect.df.loc[gtf_region_intersect.df['gene_name'] == _gene].iterrows():\n", + " if part['Feature'] == 'exon':\n", + " exon_start = part['Start']\n", + " exon_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (exon_start, -1), exon_end-exon_start, 2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " elif part['Feature'] == 'transcript':\n", + " gene_start = part['Start']\n", + " gene_end = part['End']\n", + " rect = mpatches.Rectangle(\n", + " (gene_start, 0), gene_end-gene_start, 0.2, fill=True, color=\"k\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " # IRF4 enhancer chr6 396106 396605\n", + " rect = mpatches.Rectangle((396106, 1), 396605-396106, 0.2, fill=True, color=\"r\", linewidth=0)\n", + " ax.add_patch(rect)\n", + " \n", + " ax.set_ylim([-2/1.2, 2/1.2])\n", + " ax.set_xlim([x.min(), x.max()])\n", + " sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n", + " ax.patch.set_alpha(0) \n", + " \n", + "ax.set_xlabel(\"chr6:386829-416366\")\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/irf4_locus_atac_SOX10chip_ZEB2chip.pdf\",transparent=True)" + ] + }, + { + "cell_type": "markdown", + "id": "e09e4c4b-c392-4a3d-8880-87b9a86986ee", + "metadata": {}, + "source": [ + "### Plotting the ATAC and ChIP-seq coverages on the regions with the highest ChIP-seq signal" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "27c7d31c-5600-4f80-aabe-1499e33094a5", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr16 90032296 90032796\n", + "flank = 5000\n", + "chr_ = \"chr16\"\n", + "start = 90032296 - flank\n", + "end = 90032796 + flank\n", + "\n", + "zeb2_ab2 = Zeb2_Ab2_bw.values(chr_, start, end)\n", + "ATAC_MM001_ab2 = ATAC_MM001_bw.values(chr_, start, end)\n", + "\n", + "n_tracks = 3\n", + "fig = plt.figure(figsize=(5,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(3,1,1)\n", + "ax.fill_between(np.linspace(start, end, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(3,1,2)\n", + "ax.fill_between(np.linspace(start, end, num=len(zeb2_ab2)),0,zeb2_ab2)\n", + "ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(3,1,3)\n", + "\n", + "# IRF4 enhancer chr6 396106 396605\n", + "rect = mpatches.Rectangle((start+flank-250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([start,end])\n", + "sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0) \n", + "ax.set_xlabel(chr_+\":\"+str(start)+\"-\"+str(end))\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/\"+chr_+\"_\"+str(start)+\"-\"+str(end)+\"ATAC_ZEB2ChIP.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c611c405-daf1-48a4-beff-e20fa6ad7158", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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TERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDGoiIiIZY1ATERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImImlC50dLcVaDbDIOaiOgWsNlEjdOTlNomrgnd7hjURHRXEKLm4LxVKsxWaZ2ZJeXS9OyyiiatR12MFmtzV4HqwKAmojtaVct25fEMXMxRNck6hRDYF6/E1G9Pwmy1IaNEjySlFjabwIWsMqj15iapR20yistxLrMU2aV67IsrbNa6UN0Y1EQNVKIzNncV7komi+2mPpddpocQAklKHXZczG+UuhiuaS0DQIXJvlWqM1qw6XwusksrsPlCLlR6E06llyK7TI/1Z3NwOqO0UepxMyxWG1adykRWqR4f7U7AN0dSa+2mp+oM5qbvgWBQEzXQ3jhlc1fhrhSfr0HxTRwkZZdWIK24HNmlepzLLGuUuuSUVUBdcbVVnFCgsZtvsQrE5KigMZix4VwOirRGxOdr8HtKCXRGC36LLWiUetyMy3kaHE0uxsUcNU5nlCJRqYXJWvNBUJHWCHMt8+5GJosNCQVNP8aAQU23NV0Tj6C9mKNC+jXnG6l2uaqKRmt97IktwKbzOTiTXtrg1l+iUot1Z7IRk61CWpEOelPNfzPZpfp6L9NqEyjWGVGoMQAACrX2BxAagxkqvRlagwXJSi0OJxXhWHIxfjqRAQCIasagjslWIaesAgn5WhRpjTCYbbWORN8ek4ecepxTzymr/767XWWV6PF7SjGOpxY3+boZ1DJluXIUe32XWlPKvA0C6ZOohCY94j+RWoLUQl2Tre92FpenQZHWiDzVjX/oi3VGHEu+8Y/fV4dSkV6iR2yeBmcb2CrWGsyIii2A1mhBmd4MpabmVvmJtJJ6h7VKb0KR1oQ9cUpczlWjrNxkN79Yd/W9xmDBhSwVssv0SCuq/E415gHmwYSr55grTFbpt6M2So0BOqMFl3PV0rTE61qJmy/kIDZPjV9PZ9Xrd2DJvuQG1rpp/dHfUa3BjEXbY7EntgBn0pv+tMVtHdQXshqnG0uOdl8uwKm0EuxPaL5u1mSlrtZu3gPNWK9rrT+Xg/d2xAFomgOLrFI9TqY1vFXXEHfKOfC0Ih1OppVg9+XaW4/FOiN2Xy7Ap78l4veUmsN6W0we8tUVSCzQYM2ZLBxIqP/gp5W/p2PT+VxkllwN4NpGOacVlWP35fqdwz6XVYaLOSpcyCxD5O8ZSC8pl1qlRVojfjyeIZW12gR0RguEgNTFLETdf69ag7lef9NnM0tRqK1s2f90IgOHEotuWP5iTmVAa685WEgttl/PgYQibI/JR0qhDrl1HGgJIbDzYj5UetMNyzWXYp0Rn+//YwcSSo0BR5KKsPNiPi7laur+QCO7rYO6riP121WSUouVxzPwe2oJcht4Kcf1R8bXq6kr8tsjaTWWPZZSjEOJhdV+2JQaA345mdUsXUBA5f/7soMp+PF4BvQmKy5kqwAAF7JUKNQYbnrQUX0cTCiEzmhB6TU/Svsa+Zx1fL4Wl3LUdReUudJyE46nliAur/YftphsFb48kIxLueoa/3Z1RgvWnslCabkJSo0RxToT0ovr36NxLKUEWde1kq01HGTF5WmQUKCRWrx1uZitxoZzOchVVWDHxTz8ejIL5680HLQGM6JucHBSRVXDyG+13iz9/f5rbTTmb7h4w2UoNQZUmGw4klT5XfzpRCay6+iGvvbcepVTaSV2780WG2LzKv8Gr215R10uwPs74+zK5qsNqDBboW/G3r8bOZRYhG3RudAYbn6kfUqhDhabgNZoQbHOiOQmvhb+tg7qknKT1M1zPqtMOvd0Kq0ERdr6t0rM1spzNFVHpc1Fe+UPSWsw43xWGZYfTJH++IUQMFtt1bp5jRar1I1WYbLiH7+cw9eHU1GoNcBitcFqE9KRvtUmMP6LY3Y9EZvO52DnpXwcTCy0GxBjtFix6XwOLueqsfl8rt2P2+5L+TiUWIhnfzontYLq6m6rUtOPZNX2XctmEzUOuLHaBM5klOKrQ6lYfigFAJBaqIPZasP8DRfxztZYXM6rO+QSCjQoUDfs/9tgtiLvymdirwmfdWezq9XRYLY2qLtNCIEtF3Kx+1I+EpVaLNx2GafTS5FWpJP+zw1ma63773q38mDlRtcjX3uuM1dVga3Ruci4plVotFzdhvkbYhCTrYJSY4TVJnAuq0zaxp0X83E+qwyn00twPLUEZuvVde6NU0pdzeoKs7S8XFUF5q2NtqtPUQ29EzqDRTpgNVlsMJit2BevRHapHtorBwY1qfqeLTuYAq3RjJQiHc5klMJosUFrtGDWyrOoMFmxJ1ZZ6+CsaxVoDNCbLHYBsi0mF//45RysNoHzWSqczijFp3sSpYPl63tyFmy6hHKjBd8cSUVZuQmaCjM+2BV/w5uq1HSqKLu08vKxqm70Mr1J+m4bzJXlrTaBt7dexpoz2TiYUIhDiYUwW204mlzZgt95MR/74xt20Gq1iWoNgT8SqDUp0hqRpzbg5xOZACp7WV5ZF1PjwVRakQ4PfHJQ6h2o+h7tj7fvxdEYzNh5MR+f16PL32K1QW+yoFBT+Zt8IEEJm03g11M1/53VpNmCetmyZejQoQNatGiBsLAwnD59usHLyFVVYNOFXBRpjZi0/Dhe33gJRVojomILah0wkq+uPsBl16V8zP31PNadufqD29g/dHV1HxVpjZj23Smo9WaU6EwQArDYBH6LU8JkseFUeinWnc3Gd0fTkVZU2aJQ68347mg6pn13CgVqA97ZehlpxeW4mKNGamE5jqUU42xGKSJ+OI1cVQWis8uQXKjD21svA6j8A9p8IRfR2Sp8EpWIjedypB/hX09lQWOwIFdlwJJ9yXZ/1Fui82ATlT9cJVd+MHdeql+X4baY3Go/Itmllecei3VGaVRvSpEOn/6WWG2Qym+xBYjOVkFntEjnGvVmKxILKkeuRsUW4P2d8XXexOFEagk+/S2xXnWusueaA4fdV7Y3p0yP3+KUUhelwWzF1uhcLI5KxOsbL9Z4LtJitVX7MbqYo8bBxEKcSi/FyuPpOJ+lgsliQ+TvGfj5RCaKdUZ8fTgNp9JLqi2vSpHWCIvVhiSlFt8erbmXpDEcTy2BwWxFgdpQLTheXhsNm03AZLFBa7DAJoACtQGF2spQ2nohD0eu/LCX6c1255v3XC7A5/uTEZunxp7YAuyIyceyg6m4/rjAJq4emI/57DB+OpGBfHUFnv7uFHZcyofRYoXBbEVWiR4xV3pbrvXWlsv4aHcCdEYLtkTn4r2dcdgfr0RqUTn2xSkRn6+1+40wWqxIUmoRdbkAJosNn+9LRrG28jt67eabrDYcSymWgqsuPxxLx8trovG/35IghEBWiR6L9yRif0IhVp3KhEpfuY4DCYVYe+W36dw1B9kagxkHEgqxJToXSUod/rUuGlqjBWarwIe74ms9qEusIcQzS/U4mVaClCvjL/LVBmnbqpaz5cpvrdZgwae/JeLrw2nYdSlfOhXx6W+JdqcY6uP3lGKsviawlBoDfjiW/oevM686faQxmHEus/KccmZJOS5klSHyeAZKy43VMkJntGDU/x1GRokeEZFnoNQY8NOJDCg1Bqw/l2NXNrWw8lSHUmuQfqOyS/XIU1XAduVUR06ZHlabwOn0Ury8Jhq/ns7Cjov52H2pAMdSiut9mgUAnP7IzrhZa9euxbx587BixQqEhYVhyZIlGDt2LBITExEYGFjv5Ww+n4OtsWXIGla5o85nluGDXfHYH69E71BvuDg5IK2oHH3aeKNlC2fE5qmxOCoRs+/vhOFd/SGEQKHWiKPJxTiYWITMEj26BLZE/3Y+iM5WoVeIF5wcFSgtN8Hf0xVBXi3s1p9QoIFab0bftj7IU1WgU4BnjfU0mK14ZV00Vv5tEFo4O9ZY5off03ExR41PfkuAq9PVMnmqCvx8MhM/Hs+o7HItNyGzpBxvjOuB746mY8O5HBRoDHh1fQzOXLk281xmGS7lqjG2dxC8WjjjbGYZXlsfAz8PFwBAsdaEsnITVBVmHL0yiCcuX4PkQi0m9GuNnLIKKZSqgnPR9lg83CcESUot4vKvtiaLtEZEXS7A//Ym4aF7Q3A+swztW3kg2LtyX8XnaxDi3QIKKBCTo8K8dTHwcXPG4fkjcSK1BH4eLvj6cCpcnRzh4uQAhQL435P9cDajDElKHd7bEY8VzwyQ1vf5/mS4udjvQyEqf0SqnMssw6UcNQZ28KtxXwOV55rj8jSIulyA3qFeaOvnDqDyQC4hX4uRPar/HV7bZXgosQiXc9X47kogfvpbEmYM7QC9yYJP9yRCVWGG3mRF9+CWeHxAG+lvJz5fg/h8DWKyVZg7qisCWroCAFafzsLW6Dy79ZltNqgqzPjPjjgkF2pxKq0U8fka+Lq7oEBtkOqoN1mQrNThxxMZ+PvwTpj23UkIAHNGdqlx2202gTK9Ca08XavNK9EZ7aaXlVde/6tQAK193NDR3wOvro/Bs3/uhIOJRXikTwjG9g6Gt5uzdJCwLSYPAgKXrnSZ5qoqMH/DRfy5awDy1RVYdzYbA9v7IrOk3G7QlcUmsC06DyaLDbsv5yPE261at3WVPbEFOJtZBqXGiHe3x+F0einSr5xnvZClgtZgqTUwkwt10Bos8PNwQW5ZBdZe0yNitNiw8ngGQn1a4PEBbeHn4YKsEj3++u1JWG0C7i6OsNhsSC2quft9zemsaiPAa5OnrsCpKwOTpgxqiy8OpEBrqAyPd7bGSuXi8jVILNCiUGvA0v3JWPH0ACQX6nD6ykGb8Uqj4tqDkoOJRUgr0qFrUEtpWlpR5XbX1CGi0pvxztZYODoo8KeOfnYHmOoKM5KVWny4O16aVtWjZBVCOrVhtNiwJ7YAD/cJwan0UrT1dUP/dr61bn9akQ4HEgpRpjdhRHE5Ovp74KtDqVh5PAMqvRnzH+wOdYUZId5u9dqfVaw2gQ93J+CJAW1wIKFQOhg8n6XCurOVgVthsqJ3qDcAoFBrQG5ZBbbHXA3OmGwVluxLxtmM0hp73k6ml6BjKw9EXS5AblkFZg7viGUHU+Dh4oj/e7IffjqRgSNJRfgu4k9ILtThtzglfotTItirBUrKjUgp0kFTwymI2jRLUP/vf//D7Nmz8be//Q0AsGLFCuzcuRM//PAD3njjjWrljUYjjMarf/waTeUfht5kg4PCii8PVnaB5qoqsC0mD1abwP/9lojDSX44nlKMn2YNQu9Qb3y0OwFHk4sxqkcgTFYrkpU6JBZokXLlS5dWXI7nfzmHN8b1wO5L+Wjt6wZHBwdkl+rx17B26OTvgZgcNQa290WITwu8veUycssqMOm+NkgvLsej/UKRU1aBMb2C0NbPHevOZuPBe4Kx+lQWTqaVIqFAi35tfaptn9Zgln5UfjmZBUcHhTRPXWHGf3fYnxOKzdNgx8V8rD6dJbVoj10zEKfgyiUj22Ly0Mqj8kf3eGqJ3fzYPA2uWQ0AwGwVeGvLZUTX0Aop0hqx42IeIn/PsOttOJJUhMNJlXVfcSgVOy/l4+/3d5Lqvi9OiW5BnrAJYOP5HAhxpSWVUYrnfj6Htn5u8HBxkq5NdHVywLN/7oTP9iUBqGw5xeap0TvUG1su5CJfbajxHNu2GPuQ2x6Th4Ed/JCs1CJfbcCfuwUAqBytu/F8Li7nqhGXr5H+v58f0RlCCHy0OwE7L+ZjwUM90drHDd2CPJFZose9bbztBjsVaAyYty4aSUqdtL7YPDW6B7WUuseBylZTapEOfx3UDklKHXZdyseJtBJYbQJmm8AHj92LQq0B8TWcny3VmXDpyp201p3NgdUmkFmqR6HWUHlO97/jkFFSjvXncnAwoRBZpXpoDZUjm12cHGC22uDsWNlpJoTAD79nQAGglacLTqaVoEewF3zcnVFhsmJgBz8cTipCslKLrkEt0dbXDWN6B+NMRime/+Uc3Jwd0a+tD54Y2Ab5agPe3xkPi03gSFIR/Nxd8ED3ACw/lIrsUj1eXhuNYK8WKL1mJHTVgQ2gQLHOiD2xSpSWm+zKAJXf4e+PpQNArSFdtT+ude3/zfHUEmSVlEsHoTUp0Bjw1aFUeLao+Sfwg10JKNOb4e/pCmdHhXRA8emeRNgEYKul+z8+X2M3fuFGskuv9rIt2Zt8w0u2DiYUwmSx4WhyMZYeSMZvscpq+6fsulboqlNZWPRobwCVYbRwW2ydpwStNoH/bI+1+3+5lKvGG5su2R1UVTl93QjoU+ml+Hh3AjZdyEXXQE+8+XDl96jqgMFsteGnK13QR5KKUFpuQnJhZQ/G188MlA6AVh7PQOdAT5xOL0W/tj546k9t4elad1xlFJdj1+V8bDyfg0OJRXbX3adcc7VGSbkJa89m44mBbfD5/mRczlVL3+UqR5KKkKuqQHINV3lsOp+LUT0CUVpuwsm0EpxKr/xO2wTw4/EMfHU4FSaLDXF5Grtz91W/zamFOmgM9R/5rxBNfANck8kEd3d3bNiwARMnTpSmR0REQKVSYevWrdU+s2jRIrz77rvVpqvVanh5ed3K6hIRETWrJj9HXVxcDKvViqCgILvpQUFBKCio+YhywYIFUKvV0kulUqGwsBAtW7assTwREdGdolm6vhvK1dUVrq7Vz6cRERHd6Zq8Re3v7w9HR0colfbD+JVKJYKDg5u6OkRERLLW5EHt4uKCAQMGYP/+/dI0m82G/fv3Y8iQIU1dHSIiIllrlq7vefPmISIiAgMHDsSgQYOwZMkSlJeXS6PAiYiIqFKzBPVTTz2FoqIivPPOOygoKEC/fv0QFRVVbYAZERHR3a7JL88iIiKi+rut7/VNRER0p2NQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCaiWikUCsydO7e5q0F0V2NQE9WTQqGo87Vo0aJ6lX/++eelcjNmzLCb5+TkhLZt22LKlCmIi4uzq0NCQgLmz5+Pfv36oWXLlggJCcHDDz+Ms2fPNmhbUlNT8dxzz6FTp05o0aIFvLy8MGzYMHz++eeoqKho8L5ZuXIlFAqFXT0WLVpkt13u7u7o1asX3nrrLWg0mjqXaTKZ8Pnnn6N///7w8vKCj48PevfujWeffRYJCQkNriPR7cqpuStAdLv4+eefa523aNEipKamIiwszG76X/7yF0yfPr1a+W7dutm9d3V1xXfffQcAsFgsSE1NxYoVKxAVFYW4uDiEhoYCAL777jt8//33mDx5Mv75z39CrVbj66+/xuDBgxEVFYXw8PA6t2Pnzp144okn4OrqiunTp+Oee+6ByWTCsWPH8NprryE2NhbffPNNncupr6+++gqenp7Q6XT47bff8P777+PAgQP4/fffoVAoav3c5MmTsXv3bkydOhWzZ8+G2WxGQkICduzYgaFDh6JHjx6NVkciWRNE9Id8++23AoB44YUX7KYDEHPmzKnz8xEREcLDw6Pa9B07dggA4ptvvpGmnT17Vmi1WrtyxcXFIiAgQAwbNqzOdaWlpQlPT0/Ro0cPkZeXV21+cnKyWLJkSYO3ITIyUgAQZ86ckaYtXLhQABBFRUV2ZSdNmiQAiOPHj9e6vNOnTwsA4v333682z2KxiOLi4jrrRHSnYNc30R8QGxuLF198Ef3798cnn3zSqMsODg4GADg5Xe34GjBgADw9Pe3KtWrVCvfffz/i4+PrXObixYuh0+nw/fffIyQkpNr8Ll264KWXXqo2fcuWLbjnnnvg6uqK3r17IyoqqqGbIxk1ahQAID09vdYyqampAIBhw4ZVm+fo6IhWrVrZTcvNzcXMmTMRFBQk1fGHH36o9tmcnBxMnDgRHh4eCAwMxL/+9S/s2bMHCoUChw4duultIrqV2PVNdJP0ej2efPJJODo6Ys2aNXB1da1WxmAwoLi4uNp0Ly8vuLi42E2rKme1WpGWlobXX38drVq1wiOPPFJnXQoKCuDv719nue3bt6NTp04YOnRonWWrHDt2DJs2bcI///lPtGzZEkuXLsXkyZORlZVVLTDroyqEb/TZ9u3bAwBWrVqFYcOG2R2sXE+pVGLw4MHSwLeAgADs3r0bs2bNgkajwcsvvwwAqKiowOjRo5GVlYUXX3wRoaGh+Pnnn3HgwIEGbwNRk2ruJj3R7WrmzJkCgPjxxx9rnA+g1tfq1aulchERETWWad26tTh37lyd9Thy5IhQKBTi7bffvmE5tVotAIgJEybUexsBCBcXF5GSkiJNi4mJEQDEF198IU27Udd3YmKiKCoqEunp6eLrr78Wrq6uIigoSJSXl9e6XpvNJkaMGCEAiKCgIDF16lSxbNkykZmZWa3srFmzREhISLXu8ClTpghvb2+h1+uFEEIsWbJEABDr1q2TypSXl4suXboIAOLgwYP13i9ETYld30Q34ddff8UPP/yAZ555psbBYlUmTJiAvXv3VnuNHDnSrlyLFi2keXv27MHXX38NT09PPPTQQ0hKSqp1+YWFhfjrX/+Kjh07Yv78+Tesc9VI65YtWzZgS4Hw8HB07txZet+nTx94eXkhLS2tXp/v3r07AgIC0LFjRzz33HPo0qULdu7cCXd391o/o1AosGfPHrz33nvw9fXF6tWrMWfOHLRv3x5PPfUUVCoVAEAIgY0bN2L8+PEQQqC4uFh6jR07Fmq1GufPnwcA7Nq1CyEhIXj88cel9bi7u+PZZ59t0P4gamrs+iZqoOTkZDz//PPo1q0bli9ffsOybdq0qddIbEdHx2rlHnroIXTt2hULFizAxo0bq32mvLwcjzzyCLRaLY4dO1bt3PX1vLy8AABarbbO+lyrXbt21ab5+vqirKysXp/fuHEjvLy84OzsjDZt2tiFvlqttrsczMXFBX5+fgAqR8K/+eabePPNN5Gfn4/Dhw/j888/x7p16+Ds7IxffvkFRUVFUKlU+Oabb2odqV5YWAgAyMzMRJcuXaqNNO/evXu9toOouTCoiRrAaDTiqaeegslkwpo1a+oMxz+iTZs26N69O44cOVJtnslkwqRJk3Dx4kXs2bMH99xzT53L8/LyQmhoKC5fvtygejg6OtY4XQhRr8//+c9/rvX8+UsvvYQff/xRej9ixIgaB3WFhIRgypQpmDx5Mnr37o1169Zh5cqVsNlsAICnn34aERERNa6jT58+9aonkVwxqIka4NVXX8WFCxekG3HcahaLBTqdzm6azWbD9OnTsX//fqxbtw4jRoyo9/IeeeQRfPPNNzhx4gSGDBnS2NVtsPnz5+Ppp5+W3vv6+t6wvLOzM/r06YPk5GQUFxcjICAALVu2hNVqrbPnon379rh8+TKEEHat6sTExD+2EUS3GM9RE9XT5s2b8eWXX+LRRx/Fiy++eMvXl5SUhMTERPTt29du+gsvvIC1a9di+fLlmDRpUoOWOX/+fHh4eODvf/87lEpltfmpqan4/PPP/1C9G6JXr14IDw+XXgMGDABQeXohKyurWnmVSoUTJ07A19cXAQEBcHR0xOTJk7Fx48YaewqKioqkfz/00EPIy8vDhg0bpGl6vb5Rb+5CdCuwRU1UD/n5+Zg1axYcHR0xevRo/PLLLzWW69y5s11LNSkpqcayQUFB+Mtf/iK9t1gsUjmbzYaMjAysWLECNpsNCxculMotWbIEy5cvx5AhQ+Du7l5t2Y899hg8PDxq3Y7OnTvj119/xVNPPYWePXva3Zns+PHjWL9+PWbMmFGvfXIrxcTE4K9//SvGjRuH+++/H35+fsjNzcWPP/6IvLw8LFmyROqS/+ijj3Dw4EGEhYVh9uzZ6NWrF0pLS3H+/Hns27cPpaWlAIDZs2fjyy+/xPTp03Hu3DmEhITg559/vuGgNiJZaN5B50S3h4MHD97wcquqV0REhPSZG5UbMWKEVK6my7O8vLzE6NGjxb59++zqUdulXFWv9PT0em1PUlKSmD17tujQoYNwcXERLVu2FMOGDRNffPGFMBgMdttQ053J2rdvb7etDbkzWX0olUrx0UcfiREjRoiQkBDh5OQkfH19xahRo8SGDRtqLD9nzhzRtm1b4ezsLIKDg8Xo0aPt7uomhBCZmZni0UcfFe7u7sLf31+89NJLIioqipdnkawphKjniBAiojvQoUOHMHLkSBw8eBAPPPBAc1eHqBqeoyYiIpIxBjUREZGMMaiJiIhkrMFBfeTIEYwfPx6hoaFQKBTYsmWL3XwhBN555x2EhITAzc0N4eHhSE5OtitTWlqKadOmSQ+DnzVrVrVrRYmImsIDDzwAIQTPT5NsNTioy8vL0bdvXyxbtqzG+YsXL8bSpUuxYsUKnDp1Ch4eHhg7diwMBoNUZtq0aYiNjcXevXuxY8cOHDlyhPfbJSIiqsEfGvWtUCiwefNmTJw4EUBlazo0NBSvvPIKXn31VQCV9/INCgrCypUrMWXKFMTHx6NXr144c+YMBg4cCACIiorCQw89hJycHISGhlZbj9FohNFolN4LIWAymeDv71/tvr1ERER3kkY9R52eno6CggK7W/l5e3sjLCwMJ06cAACcOHECPj4+UkgDlU/ncXBwwKlTp2pc7ocffghvb2/p5ePjg8DAwAY/XICIiOh206hBXVBQAKDyrkvXCgoKkuYVFBQgMDDQbr6TkxP8/PykMtdbsGAB1Gq19MrOzm7MahMREcnWbXELUVdXV7i6ujZ3NYiIiJpco7aog4ODAaDazf6VSqU0Lzg4WHo+bBWLxYLS0lKpDBE1H4PZ2txVIKJrNGpQd+zYEcHBwdi/f780TaPR4NSpU9KDCoYMGQKVSoVz585JZQ4cOACbzYawsLDGrA4R3YQirbHuQkTUZBrc9a3T6ZCSkiK9T09PR3R0NPz8/NCuXTu8/PLLeO+999C1a1d07NgRb7/9NkJDQ6WR4T179sSDDz6I2bNnY8WKFTCbzZg7dy6mTJlS44hvImpah5KKML5PCHzcXZq7KkSEmwjqs2fPYuTIkdL7efPmAQAiIiKwcuVKzJ8/H+Xl5Xj22WehUqkwfPhwREVFoUWLFtJnVq1ahblz52L06NFwcHDA5MmTsXTp0kbYHCL6ow7EKzGogx+DmkgmbsunZ2k0Gnh7e0OtVsPLy6u5q0N0x7DaBEb/3yH8Z8I9+HO3gOauDhGB9/omomsU64woN1lRyPPURLLBoCYiSYHaAJPFhjxVRXNXhYiuYFATkaS03ASjxYpyk6W5q0JEVzCoiUhSqDXAYLbBYOK11ERywaAmIkmxzgQAMFlvuzGmRHcsBjURSYxX7kqmrjA1c02IqAqDmogkacXlACrvTqbneWoiWWBQE5Eks0QPAMhXG5CnMjRzbYgIYFAT0TWKdZXXT2sNFlhstmauDREBDGoiukIIcU1Qm2HhgDIiWWBQExEAwGITMF8JZ5sAyvQcUEYkBwxqIgKAai3omGxV81SEiOwwqIkIQPUWNJ9LTSQPDGoiAlA9qPW8OxmRLDCoiQgAql2OxSdoEckDg5qIAAAFavsnZmWV6pupJkR0LQY1EQEASsrtu741FeZmqgkRXYtBTUQAqg8eUzOoiWSBQU1EAAClxv4cdeV11bw7GVFzY1ATEQBAY6j+EA6ThUFN1NwY1EQEANDVENT51w0wI6Kmx6AmIgCA0VL9uumUwvJmqAkRXYtBTUQAIN3n+1rns8qaoSZEdC0GNRHBbLXVOHDsZFpJM9SGiK7FoCYiZJfqa3xaVk3nrYmoaTGoiQh5KgMM5uotaiNHfRM1OwY10V1ICAEhrp6TLtQaaizH66iJmh+DmuguVKAxIFd19dKr659FXUXLrm+iZsegJroLpRaWIyFfK73XGGq+XWiF2Qq1nrcSJWpODGqiu1CeugI5ZVefjpVRUvv10qfSOfKbqDkxqInuInpTZVd2WbkJyYU66SYnSk3tz57WGdn9TdScGNREd4linRFxeRqYrTaoKsyIyVGhUGOE1SZQoK55MFnV54io+TCoie4SOoMFBxIKUW60IKlAiySlDr/FKVGmN6HcVHurmQPKiJpXowf1okWLoFAo7F49evSQ5hsMBsyZMwetWrWCp6cnJk+eDKVS2djVIKLrWGw2ZJdVQF1hRnS2CiaLDUeSinAus+yGT8li1zdR87olLerevXsjPz9feh07dkya969//Qvbt2/H+vXrcfjwYeTl5WHSpEm3ohpEdA2NwQKL1YYLWSqUlFfehSylUIeDCYU3vF7aaqv50i0iahpOt2ShTk4IDg6uNl2tVuP777/Hr7/+ilGjRgEAIiMj0bNnT5w8eRKDBw+ucXlGoxFG49XzZBqN5lZUm+iOVqQ1olhnxMHEQmma3mTBxRz1De9AxnPURM3rlrSok5OTERoaik6dOmHatGnIysoCAJw7dw5msxnh4eFS2R49eqBdu3Y4ceJErcv78MMP4e3tLb3atm17K6pNdEcrLTdBa7AgJlslTSs3WpFVqoemovZrpUvLr94DnK1roqbX6EEdFhaGlStXIioqCl999RXS09Nx//33Q6vVoqCgAC4uLvDx8bH7TFBQEAoKCmpd5oIFC6BWq6VXdnZ2Y1eb6I5XWm5CnqoChdqrLWST1Qad0YIb5e+1re0bXW9NRLdGo3d9jxs3Tvp3nz59EBYWhvbt22PdunVwc3O7qWW6urrC1dW1sapIdFcyWWzQ3MQIbuM1D+vg07SImt4tvzzLx8cH3bp1Q0pKCoKDg2EymaBSqezKKJXKGs9pE1Hjqe3BG3UxXRloVqg1SP8moqZzy4Nap9MhNTUVISEhGDBgAJydnbF//35pfmJiIrKysjBkyJBbXRWiu1aJzogi7c0NCrNYbbDaBBLytUgp1DVyzYioLo3e9f3qq69i/PjxaN++PfLy8rBw4UI4Ojpi6tSp8Pb2xqxZszBv3jz4+fnBy8sLL7zwAoYMGVLriG8i+uOKdMabfra0xSYQn69BkdaIEo4AJ2pyjR7UOTk5mDp1KkpKShAQEIDhw4fj5MmTCAgIAAB89tlncHBwwOTJk2E0GjF27FgsX768satBRNcwmm033aI2WmzYGp2Lli2coTdZG7lmRFQXhbj26fG3CY1GA29vb6jVanh5eTV3dYhk72hyEeb+egHqG1yGVRsnBwV6t/ZGic6IB3sH461Het2CGhJRbW7JDU+ISF4ySvS1PnO6LhabQJ6qAkVaI+/7TdQM+FAOortAdJYKf6TvrOqmJ1rjzYU9Ed08BjXRXeBmuryvVXVHslyVgXcnI2piDGqiO1zVHckaQ3yeBmV6U90FiajRMKiJ7nB5qopGC1eT1YaMYt5GlKgpMaiJ7nC/xSlR3ojPlD6SVNRoyyKiujGoie5wRVrDTd3juzYbz+c22rKIqG4MaqI73B8dSHa9PHUFzLznN1GTYVAT3eEa+9pnIXDD51cTUeNiUBPd4XLKGmfE97VOpZc2+jKJqGYMaqI7nN7U+HcTW3smu9GXSUQ1Y1AT3cEsVhtU+sbvpj6ZVgKDmQ/oIGoKDGqiO1iF2XrTj7e8EaPFhkINH3lJ1BQY1ER3sKxS/S1b9s0+5IOIGoZBTXQHa+xLs67Frm+ipsGgJrqDmW5Bt3eVW3kQQERXMaiJ7jAagxnqKwPIbuXzo29ltzoRXcWgJrrDZJXopedGpxXdugdolOj4FC2ipsCgJrrD5JTpkazUAbg111BXKdYZb/ieiBoHg5roDmO02LDmTBYAoPwWBrXpuvt9/55SjAoTB5gRNTYGNdEdxmSx4UhSMVIKtbiYo75l67FYhd17ndHCVjXRLcCgJrrD5KoqUGG2Yu2Z7FtyV7IqFpt9i9pksSFJqUWyUnvL1kl0N2JQE91BinVGbIvOAwCUlpuRq2r8B3JU0RmtOJdZ+XAOk8WGo8nFiM3TIJFBTdSoGNREd5Ddl/KReeWyqZJyI6w2Uccnbl58vka6lvpkWgkOJBQiuVCHU2l8shZRY2JQE91BTqaVSuEcn6+5pesq0hpRfOUSrehsFQAgIV8DnfHWDWAjuhsxqInuIAkFV8NZ2QQPzSjWGaEzWnAmo7IVnVmqR4Xpapc4Ef1xDGqiO0iRtmlHXesMFhxOLMLx1BIAleeqL+WqcTylpEnrQXQnY1AT3UHKm/g65rSiclzIKrM7F16mN2HVqawmrQfRncypuStARI1DCHFLB4/VJLNUD8t169SbrNCbrFDrzfB2d27S+hDdidiiJrpDNMfTrNKLddDUsl6D5c64S1lKIS83o+bFoCa6jVmuuY1nWvGtewBHbYwWG1KKdDXOqxoJfrv7/lh6c1eB7nIMaqLbVIXJislfHUfk7+k4klSE746mNXkdhABKy2t+itZ/tsehtNwEg7nhLWshGq8L32oT2HIhF+VGC9adzW7QZ2OyVdh0PheHk4oavE6ixsKgbiLJSi1MFlvdBe9yjfkDfSez2QTe2nIZMTlqvLs9DmvPZGNvnLK5q2UnV1WBbdG5WHO65oFlJ9NKanyIR766olF7B85mlOLltdH4ZE8iVv6eYdcLUZOLOSoUqA0QQuB0eimMFhu+PVL/g6CDCYXYGp1b7/IagxmxefW7J3tZLQdFN6vcaEFmSXmj/zZZbaLad9lgtt7w+y2EkP1lfeY6/nZulWYL6mXLlqFDhw5o0aIFwsLCcPr06eaqSpP45kiaXcujrh+Lu9WJ1BLE5WlgvEPOb16vsS6fSinSYeP5HOn9zkv5MFvld5Dz9ZE0aA3Vb4BSoDbgjY0XseFcNi7nqnEosRBA5fng+Rsu4p2tl6Wu812X8pGk1OK/O+Lwe0oxDGZrg87HV41AX3k8A3H5Gqy9QatapTfhxdUX8FtcARIKtPj6SCqAym78qnVWmKzIKdPju6NpNT5G9J+rzuP9nfHS933T+Rxsjc6t8f/+QIISn+1NwourL9QZ1lGX87HyeIbdtPo8rUypMeDDXfE1zvv6SBpe23ARSo0BQOVNco4lF1crF5unhrrCjAtZZcgsqfsg6s3Nl/DGxkt2vSnvbL2Mj6MSoTXU/H9ntNjw1aFUqfcipVALdYUZp9JKkHcLb4VbH18dSsV/d8ThjY2XsD0mr87yOy/mN+r6m2XU99q1azFv3jysWLECYWFhWLJkCcaOHYvExEQEBgbesvVabQJagxkerk5wdqw8RhFCQF1hhrebMxQKBYDKEDVbBaxCwNP1xrvIYLaihbMjgMpWjsZghqerE5wcrx4DxeVpsOtSPrJK9fhm+kBsjc7Fj8cz8PHkPugZ4gWz1QZ3Fye4ONXvuElvskABBdxcHG9mN9wyVUfRVdt+7b6pTYnOCEcHBVycHGAw2/DS2mg4Oyjwr790wxMD20IIAa3RghZOjtCbLHBxcoC7S+3/Jyq9Cc6ODvC4wf+b3mSBg0Ih1c1gtsJgtsKrhTMcHBTQGS1wcrg632ixQghI7ytMVhgtVri5OMLVqXLaqbQSvL31Mj6e3Af92/lWW6fFaoMA8PiK4wj1dsOKpwfAaLXCxdEBPu4uNdbTZLFBb7JI2/LpnkS8OLor3F0c690Ca275agN+PJEBV2cHPDO4A+b+eh5zRnXB2YxSZJXq8elvSXBzdkTPkJb4Uwc//Hg8E0evBIWbcwr+8UBnvLP1MpwdHVCgMWBrdC7++UAX/HwyE08Pbo9ZwztK6zJarKgwWe2+SyaLDVGxBXZ1+ul4Jqb+qR2MFhvMNhu8Wjij3GiB2WrDf3fEI6NEj2+PpmF7TJ505zWd0YLN53PQM8QLeeoK/G9vEpQaI349lYU3xvXA5Vw1Zg7viNg8DSrMVlSYrYj44TQ2/GMIfj6ZCXWFGSU6E54Y2AYtWzjDaLHieGoJXlkXA63BAotNICFfi96h3lI9DycVoW8bb2gNFmSW6DF/w0XYBDC+byja+LrBYLbiaHIx7u/qD09XJ2yLycPaM9n4adYg6e8SALbH5OHbo2nw83CBo4MCDgoFZgztAI3BjO+PpqHcZMXyQ6lYOL4XFkcl4GKOGn/pFYRZwzsi1McNi7bF4lhKMQJaukKpMeC+dr74aFIfaAyVo/pdnRyg1ptRqDXi19NZSCrQ4lxWGYQAZv+5I9r5eWBfvBLrz+XAUaHAntgCzB/bHePuDZHqeDylGL+nFuN4agmUGiPe3xmHUB83KAB4tnBGW183XM7T4KeZgwBU/tZqjRZ4u129qmBrdC6WHUzB6w/2wOieQdLvT3pxOXzdndGyhTMcHRTS34qjQmH3O12kNWLadyfxwWP3YmAHP7vlLtmXBOM1vQ5/6RWEY8nF6BrkiSCvFnYZsD+hEP+3NxEjugdI+aGuMMPJQSF9l8uNFvz9x7NY/ezgen2PFKIZ+hrDwsLwpz/9CV9++SUAwGazoW3btnjhhRfwxhtvVCtvNBphNF49GtVoNGjbti3UajW8vLzqvd4tF3Lx8tpozPtLNwxs7wut0YJ8VQUWbY/Dx5PvxVN/aoffU4oRna3C0eQiKDVGLJ3SH/e28a5xeQcTCrH6dBbG9w1Fz5CWiM/X4oXVF7BgXA88Pbg9jqUUw83ZEc//cg76K0e+E/qF4lxmGXLKKjCiWwByVRVIKdThiQFtEN4rCC2cHWEwW9Ez2AvtWrkDqOxuOZBQCEeFAp0DPTF/QwzcXZzw3sR70NbP3a5OmSXlSCjQoq2vO3qFekFjMONEagl83V3Q2tcNl3PVaOfnjp4hXjiVVgJVhRmDO7aC3mzBxRw1Qr3dYLbZUKQ1YlgX/zoPVKqcyyzFmYwy6E1WtPNzR8sWTtgek4fxfUPRp403HB0UuJClQmsfN9zT2hu5qgpczlXj490JSCsux33tfHA+SyUt7752Ppj3l+7IU1fgg13xeKx/a0T+noGB7X2x/vkhUGqMiMlRIaClK+67Eow5ZXoM//gg7mnthW1zhsPBQQGjxYpDiUVwd3HE/V0DEJ+vwcJtsWjt44Z5f+mGzBI9Vp/Ows5L+fjk8T7o384Hc1ZdQAd/d/x34j0oKzfj26NpMJit+McDndE71BvzN8Rg3dkcLBzfCx39PWC02LDuTDb2JxSiW5AnXhnTHR1aeaB7cEvoTRYcTS7G5Vw1fN1d8J8dcQAqv+iHk4pgstjw+ZR+mNCvdbV9uuJwKj7anYA5IzsDAJYdTEWvEC88Pbg9PtwVD+1tdKtOZ0cFRvcIQlRsAR7r3xqbL9h3DXu1cEKItxtatnDC2cwyAICDAnBQKKpd/lWlfSt3LJ7cBx6uTshVVWDnxXxsi8nDa2O7o2ugJwSAzgEeCP/fkWqf/fXvYfjmaBou52rwxdT++CgqATF1DH57sHcwLuepkVNWe+vOxdHB7jndM4Z2sGsFt/Nzx8eT+2D9uWycSC1BvtogzesW5InFj/dFsFcLxOSo8ObmyyjWGfH4gDawWG3YcuVhK5Puaw0nBwXWnb3ao/LVtPvw44kMnEwrxcvhXfFyeDcAlQehk5YfR9w1t5P193TFfyf0xj9Wnber++BOfjh53X3auwZ6IrnQfrCggwJQKBSw2iobMmN6BWHThZq7+sfdEwwfdxdcyCpDQsHV0fO+7s44+vooeLo64VRaCXZczMfPJzNr3a8A4OrkgJV/G4T72vtgzelsvL8rHsffGAV/T1cAwOsbLmLt2Wy8+VBPtG/ljl2X8vHgPcH4bG8yEpVafDXtPoy7NwTR2Sr8fCITHVq545G+oXBUKBBfoMGe2AJsOp+LXiFeePPhntAZLRjcqRXWnM7Ch7sTpHoM7+KP/u188MWBFDw9uB0KNUZMHtAGgzr4ITZPg6e/PyXtu10v3Q+V3owRnxxEh1Ye2DJnGFycHPDM96dwNLkYGR89fMNtlogmZjQahaOjo9i8ebPd9OnTp4tHH320xs8sXLhQAKj2UqvVt6SOBoNBLFy4UBgMhluy/LsF92Pj4b5sPNyXjYP7sek0eYs6Ly8PrVu3xvHjxzFkyBBp+vz583H48GGcOnWq2meub1ELIWAymeDv7y91VzcmjUYDb2/vBrfYyR73Y+Phvmw83JeNg/ux6dwWdyZzdXWFq6trc1eDiIioyTX5qG9/f384OjpCqbS/lESpVCI4OLipq0NERCRrTR7ULi4uGDBgAPbv3y9Ns9ls2L9/v11XOBERETVT1/e8efMQERGBgQMHYtCgQViyZAnKy8vxt7/9rTmqU42rqysWLlzI7vY/iPux8XBfNh7uy8bB/dh0muXyLAD48ssv8cknn6CgoAD9+vXD0qVLERYW1hxVISIikq1mC2oiIiKqG+/1TUREJGMMaiIiIhljUBMREckYg5qIiEjG7qqgTkpKwoQJE+Dv7w8vLy8MHz4cBw8etCuTlZWFhx9+GO7u7ggMDMRrr70Gi8X+4QeHDh3CfffdB1dXV3Tp0gUrV66stq47/TGeO3fuRFhYGNzc3ODr64uJEyfazed+bBij0Yh+/fpBoVAgOjrabt7Fixdx//33o0WLFmjbti0WL15c7fPr169Hjx490KJFC9x7773YtWuX3XwhBN555x2EhITAzc0N4eHhSE5OvpWb1KQyMjIwa9YsdOzYEW5ubujcuTMWLlwIk8n++c3cl43nbvluykKz3WW8GXTt2lU89NBDIiYmRiQlJYl//vOfwt3dXeTn5wshhLBYLOKee+4R4eHh4sKFC2LXrl3C399fLFiwQFpGWlqacHd3F/PmzRNxcXHiiy++EI6OjiIqKkoqs2bNGuHi4iJ++OEHERsbK2bPni18fHyEUqls8m2+FTZs2CB8fX3FV199JRITE0VsbKxYu3atNJ/7seFefPFFMW7cOAFAXLhwQZquVqtFUFCQmDZtmrh8+bJYvXq1cHNzE19//bVU5vfffxeOjo5i8eLFIi4uTrz11lvC2dlZXLp0SSrz0UcfCW9vb7FlyxYRExMjHn30UdGxY0dRUVHRlJt5y+zevVvMmDFD7NmzR6SmpoqtW7eKwMBA8corr0hluC8bz9303ZSDuyaoi4qKBABx5MgRaZpGoxEAxN69e4UQQuzatUs4ODiIgoICqcxXX30lvLy8hNFoFEIIMX/+fNG7d2+7ZT/11FNi7Nix0vtBgwaJOXPmSO+tVqsIDQ0VH3744S3ZtqZkNptF69atxXfffVdrGe7Hhtm1a5fo0aOHiI2NrRbUy5cvF76+vtJ+E0KI119/XXTv3l16/+STT4qHH37YbplhYWHiueeeE0IIYbPZRHBwsPjkk0+k+SqVSri6uorVq1ffoq1qfosXLxYdO3aU3nNfNp675bspF3dN13erVq3QvXt3/PTTTygvL4fFYsHXX3+NwMBADBgwAABw4sQJ3HvvvQgKCpI+N3bsWGg0GsTGxkplwsPD7ZY9duxYnDhxAgBgMplw7tw5uzIODg4IDw+XytzOzp8/j9zcXDg4OKB///4ICQnBuHHjcPnyZakM92P9KZVKzJ49Gz///DPc3d2rzT9x4gT+/Oc/w8XFRZo2duxYJCYmoqysTCpzo32Znp6OgoICuzLe3t4ICwu7o/bl9dRqNfz8/KT33JeN4275bsrJXRPUCoUC+/btw4ULF9CyZUu0aNEC//vf/xAVFQVfX18AQEFBgV24AJDeFxQU3LCMRqNBRUUFiouLYbVaayxTtYzbWVpaGgBg0aJFeOutt7Bjxw74+vrigQceQGlp5UPnuR/rRwiBGTNm4Pnnn8fAgQNrLPNH9uW186/9XE1l7jQpKSn44osv8Nxzz0nTuC8bx93w3ZSb2z6o33jjDSgUihu+EhISIITAnDlzEBgYiKNHj+L06dOYOHEixo8fj/z8/ObejGZX3/1os9kAAG+++SYmT56MAQMGIDIyEgqFAuvXr2/mrZCH+u7LL774AlqtFgsWLGjuKstWfffltXJzc/Hggw/iiSeewOzZs5up5kSN57Z4HvWNvPLKK5gxY8YNy3Tq1AkHDhzAjh07UFZWJj3kfPny5di7dy9+/PFHvPHGGwgODq42crHqcZxVj+AMDg6u8RGdXl5ecHNzg6Oj4235GM/67seqg5pevXpJ011dXdGpUydkZWUBwF29H4GG/U2eOHGi2kMNBg4ciGnTpuHHH3+sdT8Bde/La+dXTQsJCbEr069fvwZvX1Oq776skpeXh5EjR2Lo0KH45ptv7Mrd7fuysfBRxc2guU+SN5Vt27YJBwcHodVq7aZ369ZNvP/++0KIq4Ogrh25+PXXXwsvLy9hMBiEEJWDoO655x67ZUydOrXaIKi5c+dK761Wq2jduvUdMdBCrVYLV1dXu8FkJpNJBAYGSqNnuR/rJzMzU1y6dEl67dmzRwAQGzZsENnZ2UKIqwOgTCaT9LkFCxZUGwD1yCOP2C17yJAh1QZAffrpp9L8qv/HO2kAVE5OjujatauYMmWKsFgs1eZzXzaeO/27KTd3TVAXFRWJVq1aiUmTJono6GiRmJgoXn31VeHs7Cyio6OFEFcvKxozZoyIjo4WUVFRIiAgoMbLil577TURHx8vli1bVuNlRa6urmLlypUiLi5OPPvss8LHx8duFPTt7KWXXhKtW7cWe/bsEQkJCWLWrFkiMDBQlJaWCiG4H29Wenp6tVHfKpVKBAUFiWeeeUZcvnxZrFmzRri7u1e7pMjJyUl8+umnIj4+XixcuLDGS4p8fHzE1q1bxcWLF8WECRPuqEuKcnJyRJcuXcTo0aNFTk6OyM/Pl15VuC8bz9323Wxud01QCyHEmTNnxJgxY4Sfn59o2bKlGDx4sNi1a5ddmYyMDDFu3Djh5uYm/P39xSuvvCLMZrNdmYMHD4p+/foJFxcX0alTJxEZGVltXV988YVo166dcHFxEYMGDRInT568lZvWpEwmk3jllVdEYGCgaNmypQgPDxeXL1+2K8P92HA1BbUQQsTExIjhw4cLV1dX0bp1a/HRRx9V++y6detEt27dhIuLi+jdu7fYuXOn3XybzSbefvttERQUJFxdXcXo0aNFYmLirdycJhUZGSkA1Pi6Fvdl47mbvpvNjY+5JCIikrHbftQ3ERHRnYxBTUREJGMMaiIiIhljUBMREckYg5qIiEjGGNREREQyxqAmIiKSMQY1ERHdtpKSkjBhwgT4+/vDy8sLw4cPx8GDB2/4mUWLFqFHjx7w8PCAr68vwsPDcerUKbsy77//PoYOHQp3d3f4+PjcVN06dOhQ44Nk5syZ06DlMKiJiEjWHnjgAaxcubLGeY888ggsFgsOHDiAc+fOoW/fvnjkkUdu+MjNbt264csvv8SlS5dw7NgxdOjQAWPGjEFRUZFUxmQy4YknnsA//vGPm673mTNnkJ+fL7327t0LAHjiiScatqDmvjUaERHRjYwYMaLGWwwXFRUJAOLIkSPSNI1GIwCIvXv31nv5arVaABD79u2rNi8yMlJ4e3vX+LlLly6JBx98UHh4eIjAwEDx9NNPi6KiolrX89JLL4nOnTsLm81W77oJIQRb1EREdFtq1aoVunfvjp9++gnl5eWwWCz4+uuvERgYiAEDBtRrGSaTCd988w28vb3Rt2/feq9bpVJh1KhR6N+/P86ePYuoqCgolUo8+eSTta7nl19+wcyZM6FQKOq9HuAOeB41ERHdnRQKBfbt24eJEyeiZcuWcHBwQGBgIKKiouDr63vDz+7YsQNTpkyBXq9HSEgI9u7dC39//3qv+8svv0T//v3xwQcfSNN++OEHtG3bFklJSejWrZtd+S1btkClUtX5fPWasEVNRESy8sEHH8DT01N6HT16FM8//7zdtKysLAghMGfOHAQGBuLo0aM4ffo0Jk6ciPHjxyM/P/+G6xg5ciSio6Nx/PhxPPjgg3jyySdRWFhY7zrGxMTg4MGDdnXq0aMHACA1NbVa+e+//x7jxo1DaGhow3YGAD49i4iIZKW0tBSlpaXS+2nTpmHy5MmYNGmSNK1Dhw44fPgwxowZg7KyMnh5eUnzunbtilmzZuGNN96o9zq7du2KmTNnYsGCBXbTV65ciZdffhkqlcpu+rhx4+Du7o6PP/642rJCQkLg4eEhvc/MzESnTp2wadMmTJgwod51qsKubyIikhU/Pz/4+flJ793c3BAYGIguXbrYldPr9QAABwf7zmEHBwfYbLYGrdNms8FoNNa7/H333YeNGzeiQ4cOcHK6cZRGRkYiMDAQDz/8cIPqVIVd30REdFsaMmQIfH19ERERgZiYGCQlJeG1115Denq6XSj26NEDmzdvBgCUl5fj3//+N06ePInMzEycO3cOM2fORG5urt1lU1lZWYiOjkZWVhasViuio6MRHR0NnU4HAJgzZw5KS0sxdepUnDlzBqmpqdizZw/+9re/wWq1Ssux2WyIjIxEREREnYFeGwY1ERHdlvz9/REVFQWdTodRo0Zh4MCBOHbsGLZu3Wo3gjsxMRFqtRoA4OjoiISEBEyePBndunXD+PHjUVJSgqNHj6J3797SZ9555x30798fCxcuhE6nQ//+/aUR3gAQGhqK33//HVarFWPGjMG9996Ll19+GT4+PnYt/H379iErKwszZ8686e3kOWoiIiIZY4uaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDGoiIiIZY1ATERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDGoiIiIZY1ATERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDGoiIiIZY1ATERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGTMqbkrQESNQKFo/GUK0fjLJKIGY4uaiIhIxhjUREREMsagJiIikjEGNRERkYxxMBnRnYADv4juWGxRExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjXd1jIyMqBQKBAdHd3cVSEiuiUY1HTXio2NxeTJk9GhQwcoFAosWbKkWpmqede/5syZc8Nl79mzB4MHD0bLli0REBCAyZMnIyMjQ5p/7NgxDBs2DK1atYKbmxt69OiBzz77rNpyli1bhg4dOqBFixYICwvD6dOn7eanpqbiscceQ0BAALy8vPDkk09CqVTalXn//fcxdOhQuLu7w8fH54b1LikpQZs2baBQKKBSqRpU3yNHjmD8+PEIDQ2FQqHAli1bbriuKgUFBXjmmWcQHBwMDw8P3Hfffdi4caNdmUcffRTt2rVDixYtEBISgmeeeQZ5eXnSfIPBgBkzZuDee++Fk5MTJk6cWOO6Dh06hPvuuw+urq7o0qULVq5c2eBtUCqVmDFjBkJDQ+Hu7o4HH3wQycnJdmWee+45dO7cGW5ubggICMCECROQkJBgV+bFF1/EgAED4Orqin79+tVrX9HdiUFNdx2r1QqbzQa9Xo9OnTrho48+QnBwcI1lz5w5g/z8fOm1d+9eAMATTzxR6/LT09MxYcIEjBo1CtHR0dizZw+Ki4sxadIkqYyHhwfmzp2LI0eOID4+Hm+99RbeeustfPPNN1KZtWvXYt68eVi4cCHOnz+Pvn37YuzYsSgsLAQAlJeXY8yYMVAoFDhw4AB+//13mEwmjB8/HjabTVqOyWTCE088gX/84x917ptZs2ahT58+1abXp77l5eXo27cvli1bVud6rjV9+nQkJiZi27ZtuHTpEiZNmoQnn3wSFy5ckMqMHDkS69atQ2JiIjZu3IjU1FQ8/vjj0nyr1Qo3Nze8+OKLCA8Pr3E96enpePjhhzFy5EhER0fj5Zdfxt///nfs2bOn3tsghMDEiRORlpaGrVu34sKFC2jfvj3Cw8NRXl4ulRswYAAiIyMRHx+PPXv2QAiBMWPGwGq12i1v5syZeOqppxq0v+guJIhuA1arVXz88ceic+fOwsXFRbRt21a89957Ij09XQAQGzduFA888IBwc3MTffr0EcePH5c+GxkZKby9vcXWrVtFz549haOjo0hPT7dbfvv27cVnn31WZz1eeukl0blzZ2Gz2Wots379euHk5CSsVqs0bdu2bUKhUAiTyVTr5x577DHx9NNPS+8HDRok5syZY7cPQkNDxYcffiiEEGLPnj3CwcFBqNVqqYxKpRIKhULs3bu32vKr9kNtli9fLkaMGCH2798vAIiysrJay9ZU32sBEJs3b77h56t4eHiIn376yW6an5+f+Pbbb2v9zNatW2vdnxEREWLChAnVps+fP1/07t3bbtpTTz0lxo4dW+M6atqGxMREAUBcvnxZmma1WkVAQMAN6xsTEyMAiJSUlGrzFi5cKPr27VvrZ4nYoqbbwoIFC/DRRx/h7bffRlxcHH799VcEBQVJ89988028+uqriI6ORrdu3TB16lRYLBZpvl6vx8cff4zvvvsOsbGxCAwMbHAdTCYTfvnlF8ycORMKhUKaPmPGDDzwwAPS+wEDBsDBwQGRkZGwWq1Qq9X4+eefER4eDmdn5xqXfeHCBRw/fhwjRoyQ1nXu3Dm71qGDgwPCw8Nx4sQJAIDRaIRCoYCrq6tUpkWLFnBwcMCxY8catG1xcXH4z3/+g59++gkODnX/LFxf3z9i6NChWLt2LUpLS2Gz2bBmzRoYDAa7fXqt0tJSrFq1CkOHDq11f9bkxIkT1VrbY8eOlfZnfRiNRgCV+7mKg4MDXF1da93n5eXliIyMRMeOHdG2bdt6r4uoCoOaZE+r1eLzzz/H4sWLERERgc6dO2P48OH4+9//LpV59dVX8fDDD6Nbt2549913kZmZiZSUFGm+2WzG8uXLMXToUHTv3h3u7u4NrseWLVugUqkwY8YMu+khISFo166d9L5jx4747bff8O9//xuurq7w8fFBTk4O1q1bV22Zbdq0gaurKwYOHIg5c+ZI21RcXAyr1Wp3MAIAQUFBKCgoAAAMHjwYHh4eeP3116HX61FeXo5XX30VVqsV+fn59d4uo9GIqVOn4pNPPrHbjprUVt8/Yt26dTCbzWjVqhVcXV3x3HPPYfPmzejSpYtduddffx0eHh5o1aoVsrKysHXr1gatp6CgoMb9qdFoUFFRUa9l9OjRA+3atcOCBQtQVlYGk8mEjz/+GDk5OdX2+fLly+Hp6QlPT0/s3r0be/fuhYuLS4PqTAQwqOk2EB8fD6PRiNGjR9da5trzqiEhIQAgncsFABcXlxrPvTbE999/j3HjxiE0NNRu+ocffoiffvpJel9QUIDZs2cjIiICZ86cweHDh+Hi4oLHH38cQgi7zx49ehRnz57FihUrsGTJEqxevbre9QkICMD69euxfft2eHp6wtvbGyqVCvfdd1+9WsVVFixYgJ49e+Lpp5+us+wfqe8HH3wgBZenpyeysrIAAG+//TZUKhX27duHs2fPYt68eXjyySdx6dIlu8+/9tpruHDhAn777Tc4Ojpi+vTp1fbnrebs7IxNmzYhKSkJfn5+cHd3x8GDBzFu3Lhq+3zatGm4cOECDh8+jG7duuHJJ5+EwWBo0vrSncGpuStAVBc3N7c6y1zbBVrVLX3tgCo3Nze77uqGyszMxL59+7Bp06Y6yy5btgze3t5YvHixNO2XX35B27ZtcerUKQwePFia3rFjRwDAvffeC6VSiUWLFmHq1Knw9/eHo6NjtRHcSqXSbuDbmDFjkJqaiuLiYjg5OcHHxwfBwcHo1KlTvbftwIEDuHTpEjZs2AAAUvj5+/vjzTffxLvvvltnfevj+eefx5NPPim9Dw0NRWpqKr788ktcvnwZvXv3BgD07dsXR48exbJly7BixQqpvL+/P/z9/dGtWzf07NkTbdu2xcmTJzFkyJB6rT84OLjG/enl5VWvv7EqAwYMQHR0NNRqNUwmEwICAhAWFoaBAwfalfP29oa3tze6du2KwYMHw9fXF5s3b673/iKqwqAm2evatSvc3Nywf//+RulqvRmRkZEIDAzEww8/XGdZvV5frXXl6OgIwP7g4Xo2m006B+ri4oIBAwZg//790qVGNpsN+/fvx9y5c6t91t/fH0Bl6BYWFuLRRx+t13YBwMaNG+26fs+cOYOZM2fi6NGj6Ny5c73qWx9+fn7w8/Ozm6bX6wGgxv1V174C0KD1DxkyBLt27bKbtnfv3noH/fW8vb0BAMnJyTh79iz++9//1lpWCAEhRIPqS1SFQU2y16JFC7z++uuYP38+XFxcMGzYMBQVFSE2NvaG3eF1MZlMiIuLk/6dm5uL6OhoeHp62p0ftdlsiIyMREREBJycqn9lFixYgNzcXKn7++GHH8Znn32G//znP5g6dSq0Wi3+/e9/o3379ujfvz+AylZ3u3bt0KNHDwCV1+9++umnePHFF6Xlzps3DxERERg4cCAGDRqEJUuWoLy8HH/729+kMpGRkejZsycCAgJw4sQJvPTSS/jXv/6F7t27S2WysrJQWlqKrKwsWK1W6eYwXbp0gaenZ7UwLi4uBgD07NlTuu66PvXV6XR24wLS09MRHR0NPz+/Ws999+jRA126dMFzzz2HTz/9FK1atcKWLVuwd+9e7NixAwBw6tQpnDlzBsOHD4evry9SU1Px9ttvo3PnznYhGxcXB5PJhNLSUmi1Wmk7q65Rfv755/Hll19i/vz5mDlzJg4cOIB169Zh586dDdqG9evXIyAgAO3atcOlS5fw0ksvYeLEiRgzZgwAIC0tDWvXrsWYMWMQEBCAnJwcfPTRR3Bzc8NDDz0kLTslJQU6nQ4FBQWoqKiQ6turVy+eyyZ7zTrmnKierFareO+990T79u2Fs7OzaNeunfjggw+ky7MuXLgglS0rKxMAxMGDB4UQtV+WVPXZ618jRoywK7dnzx4BQCQmJtZYt4iIiGqfWb16tejfv7/w8PAQAQEB4tFHHxXx8fHS/KVLl4revXsLd3d34eXlJfr37y+WL19ud0mXEEJ88cUXol27dsLFxUUMGjRInDx50m7+66+/LoKCgoSzs7Po2rWr+L//+79ql45FRETUuJ1V++d6Bw8erHZ5Vn3qW/W5618RERE1rqdKUlKSmDRpkggMDBTu7u6iT58+dpdrXbx4UYwcOVL4+fkJV1dX0aFDB/H888+LnJwcu+W0b9++xvVfv239+vUTLi4uolOnTiIyMrLGbb/RNnz++eeiTZs20t/hW2+9JYxGozQ/NzdXjBs3TgQGBgpnZ2fRpk0b8de//lUkJCTYrWvEiBE1ruv6SweJFEI08WgMIiIiqjeO+iYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhk7P8Bly3oI0P7D2sAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr17 83096431 83096931\n", + "flank = 5000\n", + "chr_ = \"chr17\"\n", + "start = 83096431 - flank\n", + "end = 83096931 + flank\n", + "\n", + "zeb2_ab2 = Zeb2_Ab2_bw.values(chr_, start, end)\n", + "ATAC_MM001_ab2 = ATAC_MM001_bw.values(chr_, start, end)\n", + "\n", + "n_tracks = 3\n", + "fig = plt.figure(figsize=(5,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(3,1,1)\n", + "ax.fill_between(np.linspace(start, end, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(3,1,2)\n", + "ax.fill_between(np.linspace(start, end, num=len(zeb2_ab2)),0,zeb2_ab2)\n", + "ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(3,1,3)\n", + "\n", + "# IRF4 enhancer chr6 396106 396605\n", + "rect = mpatches.Rectangle((start+flank-250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([start,end])\n", + "sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0) \n", + "ax.set_xlabel(chr_+\":\"+str(start)+\"-\"+str(end))\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/\"+chr_+\"_\"+str(start)+\"-\"+str(end)+\"ATAC_ZEB2ChIP.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "3c2092a8-2931-402a-a7b8-742c7123cc30", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# chr13 113624773 113625273\n", + "flank = 10000\n", + "chr_ = \"chr13\"\n", + "start = 113624773 - flank\n", + "end = 113625273 + flank\n", + "\n", + "zeb2_ab2 = Zeb2_Ab2_bw.values(chr_, start, end)\n", + "ATAC_MM001_ab2 = ATAC_MM001_bw.values(chr_, start, end)\n", + "\n", + "n_tracks = 3\n", + "fig = plt.figure(figsize=(5,1.5*n_tracks))\n", + "\n", + "ax = fig.add_subplot(3,1,1)\n", + "ax.fill_between(np.linspace(start, end, num=len(ATAC_MM001_ab2)),0,ATAC_MM001_ab2) \n", + "ax.set_title(\"ATAC-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "ax.set_xticks([])\n", + "\n", + "ax = fig.add_subplot(3,1,2)\n", + "ax.fill_between(np.linspace(start, end, num=len(zeb2_ab2)),0,zeb2_ab2)\n", + "ax.set_title(\"ZEB2 ChIP-Seq\")\n", + "ax.margins(x=0)\n", + "ax.set_ylim([0,100])\n", + "\n", + "sns.despine(top=True, right=True, bottom=True)\n", + "\n", + "ax = fig.add_subplot(3,1,3)\n", + "\n", + "# IRF4 enhancer chr6 396106 396605\n", + "rect = mpatches.Rectangle((start+flank-250, 1), 500, 0.2, fill=True, color=\"r\", linewidth=0)\n", + "ax.add_patch(rect)\n", + "\n", + "ax.set_ylim([-2/1.2, 2/1.2])\n", + "ax.set_xlim([start,end])\n", + "sns.despine(top=True, right=True, left=True, bottom=True, ax=ax)\n", + "ax.set_xticks([])\n", + "ax.set_yticks([])\n", + "ax.patch.set_alpha(0) \n", + "ax.set_xlabel(chr_+\":\"+str(start)+\"-\"+str(end))\n", + "fig.tight_layout()\n", + "plt.savefig(\"figures/chip_seq/\"+chr_+\"_\"+str(start)+\"-\"+str(end)+\"ATAC_ZEB2ChIP.pdf\",transparent=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b924d6a9-2101-4763-93f6-643f36a302b7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "20230504_pycistopic.sif", + "language": "python", + "name": "cistopic_20230504" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/MM_using_DeepMELs.ipynb b/the_code/Human/MM_using_DeepMELs.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..855cfccd5071575b47cdafa05bc24ff3dd195b73 --- /dev/null +++ b/the_code/Human/MM_using_DeepMELs.ipynb @@ -0,0 +1,328 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fa3b7a07-0d70-4f40-bc4c-3de646b12d1c", + "metadata": {}, + "source": [ + "## This notebook shows how to load and use the provided models." + ] + }, + { + "cell_type": "markdown", + "id": "b30bc7a4-8810-44d0-bb28-1ffc0a54a67f", + "metadata": {}, + "source": [ + "#### It shows how to calculate and plot:\n", + "*\t\tPredictions\n", + "*\t\tDeexplainer contribution scores\n", + "*\t\tIn silico saturation mutagenesis" + ] + }, + { + "cell_type": "markdown", + "id": "a7734ac7-f6f5-4e4c-a075-2cfcaf12fd45", + "metadata": {}, + "source": [ + "#### 3 models are provided in ./models folder: DeepMEL, DeepMEL2, and DeepMEL2 with GABPA extension.\n", + "#### These models can be downloaded from Zenodo, which are used by Kipoi database:\n", + "*\t\tDeepMEL: https://zenodo.org/records/3592129\n", + "*\t\tDeepMEL2: https://zenodo.org/records/4590308\n", + "*\t\tDeepMEL_GABPA: https://zenodo.org/records/4590405" + ] + }, + { + "cell_type": "markdown", + "id": "edb35b27-06c4-4a09-ab0f-9ba047ee3dbf", + "metadata": {}, + "source": [ + "#### General imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3c38e5c5-8df3-4c52-b397-7ad9aba7fbfc", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys \n", + "import os\n", + "import pickle\n", + "import utils\n", + "import numpy as np\n", + "import scipy\n", + "import tensorflow as tf\n", + "tf.disable_eager_execution()\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "matplotlib.style.use(\"default\")\n", + "matplotlib.rcParams['pdf.fonttype'] = 42\n", + "matplotlib.rcParams['ps.fonttype'] = 42" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "d935e20e-1aa5-45df-9ebf-17291a3ca52e", + "metadata": {}, + "source": [ + "#### Loading DeepMEL2 data to be used for the initialization of shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "15134f16-b0c5-4a2e-af35-aa04c0eb3c77", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data...\n" + ] + } + ], + "source": [ + "print('Loading data...')\n", + "f = open('./data/deepmel2/DeepMEL2_nonAugmented_data.pkl', \"rb\")\n", + "nonAugmented_data_dict = pickle.load(f)\n", + "f.close()" + ] + }, + { + "cell_type": "markdown", + "id": "1e097e24-1ee9-4943-807e-ab53e097b5cc", + "metadata": {}, + "source": [ + "#### Loading the models and initializing shap.DeepExplainer" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "b2d6301a-525e-4816-87dc-0836d5514ae1", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading model...\n" + ] + } + ], + "source": [ + "print('Loading model...')\n", + "import shap\n", + "tf.disable_eager_execution()\n", + "rn=np.random.choice(nonAugmented_data_dict[\"train_data\"].shape[0], 250, replace=False)\n", + "model_dict = {}\n", + "exp_dict = {} \n", + "\n", + "name = \"deepmel2\"\n", + "model_json_file = \"models/deepmel2/model.json\"\n", + "model_hdf5_file = \"models/deepmel2/model_epoch_07.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel2_gabpa\"\n", + "model_json_file = \"models/deepmel2_gabpa/model.json\"\n", + "model_hdf5_file = \"models/deepmel2_gabpa/model_epoch_09.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n", + "\n", + "\n", + "name = \"deepmel\"\n", + "model_json_file = \"models/deepmel/model.json\"\n", + "model_hdf5_file = \"models/deepmel/model_best_loss.hdf5\"\n", + "model_dict[name] = utils.load_model(model_json_file, model_hdf5_file)\n", + "exp_dict[name] = shap.DeepExplainer((model_dict[name].inputs, model_dict[name].layers[-1].output), [nonAugmented_data_dict[\"train_data\"][rn],nonAugmented_data_dict[\"train_data\"][rn][:,::-1,::-1]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "41d307f2-da9c-4768-b712-2013bff85ff3", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "nuc_to_onehot = {\"A\":[1, 0, 0, 0],\"C\":[0, 1, 0, 0],\"G\":[0, 0, 1, 0],\"T\":[0, 0, 0, 1]}" + ] + }, + { + "cell_type": "markdown", + "id": "a8098e2a-17aa-44bf-8909-78bf58ed65c5", + "metadata": {}, + "source": [ + "#### IRF4 enhancer and TERT promoter sequences" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "48a33683-ffdc-4f70-b0c2-8570fef84212", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "irf4_onehot = utils.one_hot_encode_along_row_axis(\"AGGGTCGGGCGTGTCCGCCTGTTGGAATATGCTTCTCAGGTCTTCTGGGAAACAGATGTTTTGTGGAAGTGGAAGATTTTGGAAGTAGTGCCTTATCATGTGAAACCACAGGGCAGCTGATCTCTTCAGGCTTTCTTGATGTGAATGACAGCTTTGTTTCATCCACTTTGGTGGGTAAAAGAAGGCAAATTCCCCTGTGGTACTTTTGGTGCCAGGTTTAGCCATATGACGAAGCTTTACATAAAACAGTACAAGTATCTCCATTGTCCTTTATGATCCTCCATGAGTGTTTTCACTTAGTCTGATGAAGGGTTCACTCCAGTCTTTTCGGATGATAAAATGCTTCGGCTGTCAGTCTAATAAGGGATTCCCTGAGGAGTTTGGAGGCTGTAAGAGCACCCCCCGTCTCAATGCCAGTGCTTCTTATCTCAGCCTCTCCTGCACTCCTTTACCCCCGTCTCGATGCCAGTGCTTCCTATCTCAGCCTCTCCTGCACTCCT\")\n", + "tert_onehot = utils.one_hot_encode_along_row_axis(\"CGCCAGCCCTGGGGCCCCAGGCGCCGCACGAACGTGGCCAGCGGCAGCACCTCGCGGTAGTGGCTGCGCAGCAGGGAGCGCACGGCTCGGCAGCGGGGAGCGCGCGGCATCGCGGGGGTGGCCGGGGCCAGGGCTTCCCACGTGCGCAGCAGGACGCAGCGCTGCCTGAAACTCGCGCCGCGAGGAGAgggcggggccgcggaaaggaaggggaggggctgggagggcccggagggggctgggccggggacccgggaggggtcgggacggggcggggtccgcgcggaggaggcggagctggaaggtgaaggggcaggacgggTGCCCGGGTCCCCAGTCCCTCCGCCACGTGGGAAGCGCGGTCCTGGGCGTCTGTGCCCGCGAATCCACTGGGAGCCCGGCCTGGCCCCGACAGCGCAGCTGCTCCGGGCGGACCCGGGGGTCTGGGCCGCGCTTCCCCGCCCGCGCGCCGCTCGCGCTCCCAGGGTGCAGGGACGCCA\")" + ] + }, + { + "cell_type": "markdown", + "id": "9526610a-9477-44d1-b118-e1ed88493661", + "metadata": {}, + "source": [ + "#### Calculating and plotting nucleotide contribution scores and in silico saturation mutagenesis values \n", + "#### using the DeepMEL2 model and IRF4 enhancer" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "68fd920b-e285-47f9-8a5c-fd7c45c512a0", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { 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IRiTgAqAj2DGwAbVvglBbbHmPb5vwhO6hCS4v7PL5gd3HKFNXF2tPndp/+Nqo5EQGnbwQoIiIiIiIiOx8HMeJtgPhQI+gTBGR7uKDLCJhEo7jDHnARXVbdcJya6CVouyifsc0LntctF3XXpesu4xCA56rHir+eqLhwDkTR3YsIiIiIiIiIiIiIiIiIiIiIiIiIiIiIoIr03dYXV3NhRde2GP9BRdcQHV1dZJbiIiIiIiIiIiIyGj28cewerUJutiptW2EhRfCq5+Fj66G0AgX+RAREZGMcByHoB2MtuMLTXpcnmjbwsIfMkEYvpAPB3Py1L0wZbZ7CAIutn8Sa7tzYcJhPcMtIuLGOJbV18faEyeCu5eHO6o5YcDq/WcF0F4Ojcug4lnYdL/5X7coY0MUERERERGRzGrxt0Tb3YvJi4gkEx8mUZJTAphg3obOhiG9n5r2msTltppeekKTrwkwc6TjcmMBF0MduiHDp7K1MtoekbALf0Ns3jRrQubvX0REREREREREREREREREREREREREREQSZLxaybHHHsvbb7/N7rvvnrD+nXfe4dOf/nSmhyMiIiIiIiIiIiKD9MIL4HKBbY/0SEZQ+aOw6EKwg+CEoOYNKH8Ejn0eivYY6dGJiIjIMAqEA9G2g4PX5Y0uW5aFx+UhZIewLAtfyAeAP+zHcZIHXGS5s3BZLmzHjvZPW2dVrD3xSIgbUw92sO/tY0RdXaw9adJYDbjoSoyzrOTb28vh6blgJ/m9OH4hTFwwfGMTERERERGREVHRWhFrt1Qws3jmCI5GRMaCSGiEy3JRkl0SXV/XXtfLLQame+hOdVs1e0xIfl00fkzjcmIBF82+5iEdkwyf+ICLytZKdh+/ex+9h4G/HuiaN80qzux9i4iIiIiIiIiIiIiIiIiIiIiIiIiIiEgPGQ+4OPXUU/npT3/K0qVL+dSnPgXAe++9xyOPPMKvf/1rnnrqqYS+IiIiIiIiIiIiMrq9+GKsFm/Et74Fp50GH30E114LgUDSm+4YWtbCwgvA9settKF9M7zzJThxMbjHftFoERERSc4fjp0DOI7TI7AiGnCBFe3rC/lwSB5w4XV7sboKdXWGOgc2KF8NWB4TvDXp6L5DLKyMXzIeFvX1sfaUKSM3jkGxXOar00tynL8+ebgFQNtGBVyIiIiIiIjsgLoXFBcR6U9TZxNgwiTG546Prm/obBjS+6lpq0lcbq/ppacZk4WFy3JRlFNEjicHX8hHW6AN27FxRebFZNQa+YCLBsAGbzFYYzHdWERERERERERERERERERERERERERERGTHkvFqJZdddhkAd9xxB3fccUfSbQCWZREOhzM6NhEREREREREREUlPOAyLFiUGXPzpT3DFFWbd8cfDpz8NRx89YkMcXnYI3j0PnCRzmU4YmlfAhr/Dnpf13C4iIiI7BF8oFjjg0DPgwuvy4sOX0NcX9GF3hRhku7MT+me5srAsC5zEfaelsxq6QjIYf1jfBb8sa2D3McrU1YHHA6EQlJaO9GgGyHIDTu8BFyIiIiIiIrLTqWipiLVbK/roKSJiNHY24rJcWFgJAReR4IuhUt1W3edyvCZfE26XGweHouwiCrIKoiHALf4WSnJKhnRsMvQSno9aRuD5yF9nrr9nj9XJXxEREREREREREREREREREREREREREZEdiyvTd2jbdkr/FW4hIiIiIiIiIiIy+q1aBZ2dseUDD4Tvf9+0LQvcbjjySLj44pEYXQZsewKaloET6qWDA5v+nckRiYiISIb5Q/6EZa/bm7DscXl69O0IdUTXZXu6BVy4s7C6wim67ztlvprY+cmEQ8HK+GXhjKuvj2V1jBs3smMZMMsFOP12ExERERERkZ1HZWtl0raISG8aOxtxW25sx2Z87ni8LjNf2eJvwXGGbu6puj31gIvGzkYsLGzHpjCrkIKsgoRtMvqN+PNRoNl8zZ6Q+fsWERERERERERERERERERERERERERERkR5GtJKJz+cbybsXERERERERERGRQVq0KFZIGODWW6F7dq1twx/+AHl5GR1aZqz5E+Duu4+tMF8REZEdmS+UeM0zy52VdNnBifb1BWO3SRZwEeEPDzDgomMb4EDuLpA9fmD7GGPq6sx5Z2EheL399x+VrLjzSkfnkCIiIiIiIjIKCoqLyJgTCYywHZvC7ELyvOYibdgJ0xZoG7L7qWqtSliuaavptW9TZxMOTnRMRdlFCdtk9KtorUjazhi7K9BZARciIiIiIiIiIiIiIiIiIiIiIiIiIiIio0LGAy7C4TC/+c1vmDZtGgUFBWzcuBGAX/ziF9x9992ZHo6IiIiIiIiIiIgMwqJF4O6qw3vkkXDMMT0LCrtcMH48nHFG5sc3rBo/hPqFQH/Fh+1MjEZERERGSPcQiu4BF163OTlyHCfatyPU0W9/gEAoMLBBdXYVvCzZd2C3H4Pq6kzQ2sSJIz2SQbDiLt87OocUERERERER2Na6Ldou314+giMRkbGi0deI7dg4OBRmFVKQVRDb1hV+MRQqWhJDDqraqnrpCU2+JkJdAQWFWYUUZxcnbJPRL/45aEQCl5yugIssBVyIiIiIiIiIiIiIiIiIiIiIiIiIiIiIjAYZD7j47W9/yz333MONN95IVlasWMt+++3HP/7xj0wPR0RERERERERERAbh/fch1FVL4pRTIBjsve+xx2ZkSJmz6V6wPCM9ChERERlhvpAvYdnr8iZddnCifX3B2G2y3dkJ/eMDL7qHZ6TMX2++5kwd2O3HoI6uzJDS0pEdx6BY7lhbARciIiIiIiI7LseBqpdh3V+h4jmz3Iut27fG2i1be+0nIhLR0NFA2AkDUJRdRGF2YXTbUAZc1LTXAGBhAVDRWtFr37r2umi7MLuQkpySYRmTDJ9tLSMcuNT1O407J/P3LSIiIiIiIiIiIiIiIiIiIiIiIiIiIiI9ZLz62r333svf/vY3PvvZz/Ktb30run7//fdnzZo1mR6OiIiIiIiIiIiIDMK2WB0LTjsNvN7k/dxuOOCAzIwpbeXlUF+fuK6qCpqboaQEpnYrDF1aCjNmwNb/ghPqtm0BFM2FmtehfctwjlpERERGCX8oMYQiPqAiftl27GhgRWeoEwCX5eq1P0DQDuI4DpZlpT6gUAeEu9IeciaDHQLXjh/KFQlamzhxZMcxOK64tgIuREREREREdkjtW+C9S6Dmldi60gXwqXugaM8e3eMLile3VWdggCIy1tV3xK57FmYXUpxdHF1u8jUNyX2E7XB0Xx6Xh6Ad7PMY1dDZEBtTViGF2YW4LTdhJ0xT59CMSYaP4zjRQBNIfG7K3CC6Ai4stwkHtlx99xcRERERERERERERERERERERERERERGRYZXxSiYVFRXsvvvuPdbbtk0wUnVERERERERERERERr2ODmhrM+2pU2Gvvfru7xmNdZXLy2HuXPD5Ur9NTg589CJ0bE1cf8ifYe73TTvUAYsugq2PDt1YRUREZFTyhRLPI7oHVmS7s6PtzqAJtogEXVhYSQMuHJzociAcINuTTcp8sUJj5E4xxb52AuGu+mbFxX33S9BX0Bn0HnY2c+YAR9mP+KJsYT+4c4fnfkRERERERGRkBFvhteOhbVPi+oYP4LXPwuc/hqyS6GrbsanrqIsudwQ7aPW3UphdmKEBi8hYFB9wUZRdxLjccdHlxs7GIbsPu2veMceTQzAQpKGjodew3vj7LcwupDCrEJflwrKsIRuTDJ9mXzOBcCC6XNNek34w82A5IfPVckPc/LmIiIiIiIiIiIiIiIiIiIiIiIiIiIiIjIyMl5TbZ599ePvtt9l1110T1j/yyCMcdNBBmR6OiIiIiIiIiIiIDFBFRay9YEH//YNB8HqHbzwDUl+fXrgFmP4VLwEW0eIZs/4nFm4BphjxgntNUSoRERHZoUXCKiK8bm+vy9GAi1BXwIXVS8CFEyvQ5Qv50gu46KyOtXMmJ4Ym7MAiARcph6oNJOgMTNhZWdnwhFxY7lg72JJQ1FRERERERER2AIsugraN4IQT1zth6KyCj34Kh90VXV3XXhctIB9R1ValgAsR6VOzrznaLswqpCi7CJflwnbsIQuTqGmPhezmZ+XTGmglaAdp9jUnBGpEbPdvTxhTYZY5jllYNPmahmRMMnwqWisSlgPhAE2+Jsbnjs/cIOyugAuXx1yiz2C2hoiIiIiIiIiIiIiIiIiIiIiIiIiIiIj0lPGAi2uvvZavfOUrVFRUYNs2jz32GGVlZdx7770888wzmR6OiIiIiIiIiIiIDFD3gItAALKyeu/vdve+bcxpX2IKEDshyJ4Ah9wGjh0rIG1ZprjGYXfC8p+N7FhFRERkWPlCiQEJ3QMr4sMpOkNdARddoRgWFl5Xt0AMlxeHxICLYorTGFCsuBy5u5hzkp1AqKu+WcrnnAMJOgNzm/r6YQq4iAsjCTRD/jDch4iIiIiIiIyMmjdh2+O9b3fC0LA4YVX3guIAFS0V7Dlhz6EenYjsIBzHSQyTyDZhEi7LhctyDVnARXWbCdm1sCjMKqSa6uj67gEXgXAgYQ61MLswGtTj4NDUqYCL0a6ytTLpuowGXETCoSw3xM2fi4iIiIiIiIiIiIiIiIiIiIiIiIiIiMjIcPXfZWidcsopPPTQQzz33HNYlsUvf/lLVq9ezdNPP83xxx8/rPd9xx13MHv2bHJycjjkkEN4++23++z/5ptvcsghh5CTk8OcOXO48847e/T573//y9577012djZ77703jz+e+OGzt956i1NOOYVddtkFy7J44oknhvIhiYiIiIiIiIiIjJjuARdeb+99AVwZn42ME/bDujth8XdgxS+ho2cRjrR0fGDCLQD2uhK8RYkFiQFcXtjlZBh34ODua5TbuBF+/3u47jpYuHCkRyMiIpJ5/pA/Ybl7YEV84EWkkFswHEy6PbLsOLECXZEwjJT5qgHLtPOmpXfbMSwScOHxgDNW65u5YmEoBFTYT0REREREZIfy8S+7inL3JfE6Q28FxUVEetMaaMV27OhyUXYRRdlFWF3/hirgoqbNhOxalkVxTjFW13xkTXtNj77dAywKs0zohu3YhO0wjb6hGZMMn1HxfBT5ve4r4KK9HBqXQcWzsOl+qFuUseGJiIiIiIiIiIiIiIiIiIiIiIiIiIiI7Gw8I3GnJ554IieeeGJG7/Ohhx7iiiuu4I477uDII4/krrvu4uSTT+aTTz5h5syZPfpv2rSJz3/+83zjG9/gvvvu49133+Wyyy5j4sSJnHXWWQAsWrSIc889l9/85jecccYZPP7445xzzjm88847HH744QC0t7dzwAEH8NWvfjV6OxERERERERERkR1BRQW43RAOw267gWWN9Ih6Uf8BvHMWdFSA5QFs+ORGOOhG4Kj091cChOMKsex6Hrh6mWq1gzDlc+nfxxhg23D11XDLLaaItGXBtdfCqafCffdBYeFIj1BERCQzIqEVEd0DK3I8OdF2Z6gTx3EIhAO99s9yZ+HEFejqvv9++RtMkS8nBNmT0rvtGBYOm69ud+zcZMzJKo61Aw2maFv3EDUREREREREZe+rfh9q3UuhoJyxVtFT06FHR2nOdiEhEfICFy3KR68mlMMtctHNwhizgorqtGrflxnZsxueMx2W5CDthqtuqe/Rt8sWuq3pcHrI92RRmFxJ2zIRefUf9kIxJhk/S56Mk64ZVZMLXcYgGPMdrL4en54LdbT79+IUwccGwD09ERERERERERERERERERERERERERERkZzMi1TCam5v5xz/+wTXXXENjo/mQxLJly6ioGL43ud9yyy18/etf55JLLmHevHnceuutzJgxg7/+9a9J+995553MnDmTW2+9lXnz5nHJJZfwta99jZtvvjna59Zbb+X444/n6quvZq+99uLqq6/ms5/9LLfeemu0z8knn8z111/PmWeeOWyPTUREREREREREZCRUVIDLZf5PnDjSo+lFy1p4/STorAQccILghMH2w9LLoebN9PdZGtcu2R8KZvfe1+WFqZkN+82Uq66CG2+EUMgUlA6FzPpnn4Uf/nBkxyYiIpJJ/rAfK66gVvfAimx3drTtC/kI2sGEAItkARfx0g64sIOAZc5D4gMTdnDdAy7GJG98wMV2c94qIiIiIiIiY9+mf3cFcMdx50LRXuAp6PVmla2VKa0TEYmID7DI8+RhWRaF2YXYjk3YDg9pwAWY0IwJeRMAE6iRLOCirr0u2s715NLqb8UTd0yM3y6j06h4PooEAfc2Z+qv7xluAdC2cfjGJCIiIiIiIiIiIiIiIiIiIiIiIiIiIrITy3jAxYoVK9hzzz254YYbuOmmm2hubgbg8ccf5+qrrx6W+wwEAixdupQTTjghYf0JJ5zAwoULk95m0aJFPfqfeOKJLFmyhGAw2Gef3vYpIiIiIiIiIiKyI6moMIWEJ00yhYRHHTsIb34RQi3g2Mn7rP97+vuND7iYehLYob77Z09Iutr6tcWEG5NvG+0eeABuuin5tnAYli3L7HhERERGki/kw7JiARdetzdhu9ftjQZgBMKBHoEVQx5w4XSdm2SNzfOMnVp8wEVw+xhO6hAREREREZEox4YtD8VerwNMPw1O2wJfXA2nl8Os85PedKAFxX0+uO022GcfmDkTzj0XVq0a8CMQkTGkqbMp2i7INgE6RdlFhJ0wDg71HfVDcj817TXYXddfJ+VPIuyEcVtuatpqevR9ddOr0XZroJWiPxTx1ae+Gl1X1lA2JGOS4bOtdVuPdRWtFZkdhNX1hgQnDHHz8SIiIiIiIiIiIiIiIiIiIiIiIiIiIiIyMjyZvsMrr7ySiy++mBtvvJHCwsLo+pNPPpnzz0/+Aa3Bqq+vJxwOM3ny5IT1kydPprq6Oultqqurk/YPhULU19czderUXvv0ts9U+f1+/H5/dLmlpWVQ+xMRERERERERERkOW7aAbcO0aSM9kl5s+Ae0ruu7z0CKX0wAkx1sw+TPAP3swwnHCm506Qx2AtDY2Zj+/Y+wzk648krzreut5rLdS56IiIjIjsgf8uOyXNGCbskCK1yWi7ATxh/y4w/FrgM6OEkDMbrvPy2RgpmurL777WAigWvhsVzfLKsk1g4293uaKSIiIiIiImNA41IIxF0LGHcwHPVI7LqBtxgW/Ac6KiCY+H7hbS09C4pv2b6lz7urq4OjjoJ162Jz+FVV8Mgj8I9/wNe+NqhHIyKj3AvrX4i2a9pqKPx9ISE7FrCzuHLxkNxPRWsFDuYgs0vBLgCEnTDV7T0/R5Es9CJeZF5VRq/y7eU91qUSuDSkrK6PPjlhNHEqIiIiIiIiIiIiIiIiIiIiIiIiIiIiMvJcmb7DxYsXc+mll/ZYP23atEEHQ/TH6lbJxHGcHuv66999fbr7TMXvf/97iouLo/9nzJgxqP2JiIiIiIiIiIgMh21ddZVGZcBFsA2W/6z/fk44/X2XArhM8alJnwaXu+/+SVIgNjRtSP9+R4k//xlqanoPtxAREdnZ+EI+rLiCWskCLiIC4QC+kC+67DhOn/0j+0+LHTL1vVye9G43xu0QARfeolg7sJ0RuJwvIiIiIiIiQ63yuViYhacAPv0oYIHV9ZrPcoFjw5EPJQYfklhQ3NXVv6Klote7am2Fz34WNm5MnMMPhczyJZfAyy8PxYMSkdEqPnTAwaEt0JYwvxgIBYb8fqYVmYvFtmNT3dbz8yB1HXX97q8j0DEk45LhEfl5e12xcOb+ApeGXDTgIoQCLkRERERERERERERERERERERERERERERGXsarmuTk5NDS0tJjfVlZGRMnThyW+ywtLcXtdvcI0KitrWXy5MlJbzNlypSk/T0eDxMmTOizT2/7TNXVV1/NlVdeGV1uaWlRyIWIiIiIiIiIiIwqjgN1XbVIpk0D2wbXaKq/u+VBCDT1XO8tglB7LNiiyAM5OeBLo3D0JBcQhryZ4Mnrv3+S4tJrG9ZG253BTnK9uanf/wgKheBPf1K4hYiISDx/2J+wHF/kK7JsWRY4SQIuGIaACycEDrGCXzsJT9fDDYXGcMCFywvuHAj7INjc8zwyuxRcOWAn+Z3oVgRVREREREREhkF5OdTXJ66rqoLmZtMuKYGpUxO3b300dk1it69D/q6xcIsIlweyJ8DMcxNWV7bFCooXZBXQ5Guitr0Wx3HMXEM3v/oVrFplrtn05rrr4Pjj+36YIjJ21XfU97ndpo8DRBpq22uj7RnFsc85bGvZ1qNvQ0dDv/vbsn0L8ybOG5KxydAK2+Ho79W4nHHUd9ZjO3afgUvDIhIW5YzlhGMRERERERERERERERERERERERERERGRHUfGq5qcdtppXHfddTz88MMAWJZFeXk5V111FWedddaw3GdWVhaHHHIIL7/8MmeccUZ0/csvv8xpp52W9DYLFizg6aefTlj30ksvMX/+fLxeb7TPyy+/zA9+8IOEPkccccSgxpudnU12dvag9iEiIiIiIiIiIjKcAgEId9VjmjbNFBLOyur7Nhm18Z+ACyJFWiYcBofeCeMPAn8jLL8G1t8Fk7KgrCyxINXq1XDBBbHl++6DeXEFVbacC53rTcDFAJXVl0Xb6xrXsf/k/Qe8r0x6+WWojdWrweOBq66CH//Y5ITce69ZFhER2Zl0D6BIFlhhYQpuhZ0wHcGO6DbH6T/gonuARr/skPmaJGRrRxYJuIico45ZnkITcBHY3nNb/kw4pQxq34ZFFyRuy53as7+IiIiIiIgMnfJymDs3vcBsC7iH2Lu1d/9m731dHph+enTRH/LT7GsGYFzuOIqyi2jyNRG0gzR0NlCaV5pw89Wr4c9/7jvcwnHSG76IjD2NnY399mn2NVOSUzLg+wiGg9Hjk4XFzKLYNdPqtuqe9+dv7nef5dvLFXAxStW212I75sllYv5EgnaQJl8TDZ0NhO0wbpc7MwOJ3E+oLTP3JyIiIiIiIiIiIiIiIiIiIiIiIiIiIiJ9ynhVk5tvvpnPf/7zTJo0ic7OTo455hiqq6tZsGABv/3tb4ftfq+88kq+8pWvMH/+fBYsWMDf/vY3ysvL+da3vgXA1VdfTUVFBffeey8A3/rWt/jLX/7ClVdeyTe+8Q0WLVrE3XffzQMPPBDd5+WXX87RRx/NDTfcwGmnncaTTz7JK6+8wjvvvBPt09bWxvr166PLmzZt4qOPPmL8+PHMnDnwAngiIiIiIiIiIiIjKRSKtadOBcsa+L6+9uTXWNewjre/9vbgBwbQWQX17wGOWS7cAz7zCrhzzXJWCRx2JzhhaFwKM2ea/72ZNw8OPji2vL6rMEv+rgMe4trGtbF2w9oxE3Dx6KOmeHTk53/LLfCd74DLZZYvvhj23Rcuv3zEhigiIpJx/lBiAEV/gRWtgdZo28HB6/ImbO++3D1Ao19OV8KD1UdhsfZy8Neb86ZAMxTMgYkL0rufUcYdqW8W6rtfVGmpSehKt7JnTo657XDxFoG/DoJJAi7AhFwUq9ifiIiIiIhIxtXXp/8achyxd2oX7wPFe/fdP3dytBlfJL40t5SS3BLWN5r3I1e2VvYIuLj22tSu1Yz5YEgR6dN2fy9zSnE2N23mwKkHDvg+6jrqou2CrAIm5k+MLjd2NmI7Ni7LFV3X4m/pd5/bWrYNeDwyOBUVUFsL06bBpEk9t1e2Vkbbk/In4Qv5aPI1YTs2te21TC3MUPCu1fWE6qvPzP2JiIiIiIiIiIiIiIiIiIiIiIiIiIiISJ8yHnBRVFTEO++8w+uvv87SpUuxbZuDDz6Yz33uc8N6v+eeey4NDQ1cd911VFVVse+++/Lcc8+x666mCF1VVRXl5eXR/rNnz+a5557jBz/4Abfffju77LILt912G2eddVa0zxFHHMGDDz7Iz3/+c37xi1+w22678dBDD3H44YdH+yxZsoTjjjsuunzllVcCcNFFF3HPPfcM62MWEREREREREREZLvGFg3NzYwEHA/Gvj/4FgOM4WINJyojY9kSs7c6DY58Fdw64uqZDLRc4Dhx6B7x3SXr7DrZAqM2083cFOwjdilCn4pO6T6LttQ1r++g5eoRC8N//xn72X/0qfO97iX08Hjj0UPjpTzM/PhERkZHiC/lwuoK1LCzcrsRgie6BFa3+1oTl/gIx0g64iARbOL1UrGwvh6fngt1tv8cvHNMhF5GAi+391/AzZs6EsjJToDRi9Wq44ILEfvfdZwLPIkpL+w5HG6ys8cAGEzwiIiIiIiIiY1t8ofBpXwQ7DK4+AinjrjlUtFZEV0/Mn8j43PHR5YqWioTg7OpqeOyxxPCKQw+FH/0IJk+GJ5+Ev/41/XwOERl7us89JlO+vXxQARfxATwlOSXkefPwuDyE7BC2Y9PQ0ZAQetHmb+t3n/HHPMmMZcvgmmvgxRfNsssFZ5wBv/sd7LlnrF/kZ2NhRQMuNjRtiG7LWMBFZJ490JCZ+xukQAA2bjTz1rvtNrj3U4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiMRhkNuLBtm3vuuYfHHnuMzZs3Y1kWs2fPZsqUKUNXvK4Pl112GZdddlnSbcnCJo455hiWLVvW5z7PPvtszj777F63H3vssTiOk9Y4RURERERERERERkR5eWKBX4CqKmhuNu2SEphqClQEm9zAAQB4vTAkuRQt25hRPGPwO9r6BGABDsy+EAp2M6EW8SwLHAv2+FZ6+27fEmvnzzT3MQBl9WWxdkNZHz0zz3GgvR2yssz/iHffjRWMzsqCm24yfbv/7N1uOPPMzI1XRERkpPnD/uj1QI+r5+XX7oEVLf6WPrfHL7ssV/oBF5Ex2KHk2/31PcMtANo2jumAC29XfbPup7N9mjmz/7CKefPg4IMHPK60ZXcVLA2mmtQhIiIiIiIyNtk2PPII3HYbLF9uwrTPPRcuvxz22GOkRzdEJmMuI1jAtFP6v5hixeYVKlsrzSosJhdMpji7OFpAPrIt4pFHzPcz4vTTTWB1OGyCqT/9aTjtNDjhhCF5VCIyirUH2/vts61126Duo6atJtoenzsey7Ioyi6isbPRbG+vSQi4SGVMNe01/faRofPCCybMIhiMrbNteOIJePVVeOst2G8/s76ytRILC4/LQ2leKYFwIHqb7s9Hwyq763fKP7oDLvx++P3v4S9/gYauoc6ZAz/9KXzjG0PzvgoRERERERERERERERERERERERERERGR0SBjAReO43Dqqafy3HPPccABB7DffvvhOA6rV6/m4osv5rHHHuOJJ57I1HBEREREREREREQkXnk5zJ0LvtQKKIeYDFQDpjjSQAsx1LbXRtsra1cOTcBF04dAVyWnuZf33s/lSb+Isy82XvJngeVNd3Q0dDSw3R8rWPxJ7Sdp72M4dHbCn/9sim1UVIDLBV/8oim2ccQRpsCYy2WKm5x1FkyY0Pu+gsFYkWkRkSHRvhXW3wVbH4OwDyYcBnteBpOOHumRieAL+bAdc+6RLODC6058Uuxe0K2vgAsLC3/In96ALE9X1lcvARc7qLw887WubmTHMWhZ4wAX+KpHeiQiIiIiIiLDxueDiy6Chx82ocnhsAlevusuuPtuePZZ+MxnRnqUQ2ASEMa8W3vcQT3DuLuLu9hS0VKBy3LhttyU5pZSnFMcLTBe0VqRcLP77ou1Dz0UHnjAtCPz9JYFRx1lvre33DLoRyUio1gqc4ndjyHpqm6LzVtFgizG5YyLBlxUt1Wz76R9o33iAxF6E3/NWIbX8uVwyinmmm98OBKY5+PWVvjWt+Ddd826ipaK6Lx3JODC4/IQtsNUtAzudykt2aVm7tufTsJxZjU3w6mnmu9d/Pd20ya49FJYvx5uuEEhFyIiIiIiIiIiIiIiIiIiIiIiIiIiIrJjyFjAxT333MNbb73Fq6++ynHHHZew7bXXXuP000/n3nvv5cILL8zUkERERERERERERCSivj7lcAuAUNzU4mACLlbWrkxon7zHyQPbUUSwFfxdVY1LDoDivfrub4dM0EWq7LgCLAVzBvTA1zWuS1he27g27X0MtZoaE2axbFms2IZtw3PPwTPPwL//DWVlptCYbZvCY6GQ+dkno3ALERlSFc/BO18C2w9O2Kzr2ArlD8G+18J+16oakIwoX8iHgwP0DLMAE1gR2Q7QFmjrsb23Zcuy8IVSP0cDzLmNQ+zvZScxcaI5V6kfvfXNUuMtBssNoXYINHUFXoiIiIiIiOw4HAfOPhuef94sh+NevoZCZvnHP4alS0dmfENqCiaEMnsiePLSumllayVuyw2YguLFOcXYjo3LclHZWhntt20bfPBB7Ha3327m7l3dsjTcbrjgAnjjjYE9FBEZG4J2sN8+NW01g7qP6rZqPC4PtmMzIXcCABPyJrChaUN0e7yQ3X8Qb2NH46DGJKnx++H8881zcfdwi4hwGIJxv0aVrZU4ONiOHQ24iAQuxT8fDbvsCYAF4U4I+8Gdnbn7ToFtw5lnwsKFPb+3TtflgVdf1eUsERERERERERERERERERERERERERER2XFkLODigQce4JprrukRbgHwmc98hquuuor7779fARciIiIiIiIiIiJjgEOs8sJgijAkBFzUreyjZ4paymLtGWf2H2BhuXrflkx8URhvcXq37VJWX5aw3OJvob6jntK80gHtb7A6O+G442Ddup7FNkJd9WZuuQWKi00xk+Ji+Mxneg+3EBEZUtuegrdO71qIBQTgdB2gKp6G/X+V4UHJTi0cMOcWcecQncHOaNvr6iXgwuk94KJ7KEb8ssUAAi6srifp+GCunUBpqSne2dJizlnGbOBW/Dlm22YYr4ALERERERHZsdx+Ozz7bO/bHWcHKv48FXADhbulfdPKtkpsx8bBiQZchJ0wYSdMRUtFtN+yZbHbHHEEHHpo7/sMBkFv0xbZscUH7famrr1uUPexpmENjuNE5y7f3vJ2NJDHhYs1dWti43GclMbU5Gsa1JjGvPLynsm9VVXQ3AwlJTB1auK20lKYOTPtu7n9dli9Oha40JtQXCbJtpZt0ZCS0rxS/CE/tmNjWVaGAy5Kga6L2YEmyJ2SuftOwZ//DK+/3nef/r7vIiIiIiIiIiIiIiIiIiIiIiIiIiIiImNJxkqQrVixghtvvLHX7SeffDK33XZbpoYjIiIiIiIiIiIig+AlFvQQDA684NTHNR9H28uqlvXRM0XxARe7nARdxVR6NZiAi76CM/qwtmFt0nUjFXBx5ZVQVtYz3KK7Tz4xX485ZgwXjBaRYeE4jineb4Er3eNqX9q3wqKvRO6lt3sfuvsT6U1gO6z5E2z8J3RsBcsL074Ie10Bk46mI9QR7do9rAJM6EV8EbeOYEfC9ix3Vp/L/rA/vfFGAi78DendrpvXN73OZ+79DHtP3JtVl60a1L4yobQ0ViCsuRkmThzR4QxcVgnRY1vrOijZH1z9nNOKiIiIiIiMERUV8MMf9t+vv/nqEVFaCjk54EsjiHJS19eC3dO+u/Lt5YSdMAAT8iZQnB0LRNyyfUu0/ckn4HZDOAxf/WrfoY9eLxx1VNpDEZExorGjMaV+DZ2DnzeMHJ+eLHuSJ8uejG6zsXlxw4tc/9nrzZg6UxtTi79lUGMa08rLYe7c9J5fcnLMBd40Qi6CQfjDHxJDFk47Da65xtz98uXwq1/1DGmIf86ZkDsBf8hvfv4ObG3ZmvqYByt7AnT93hFo6BlwkV0Krhywu30fs0qGfWg1NXD11T3X5+WZ52d/mlP8IiIiIiIiIiIiIiIiIiIiIiIiIiIiImPBEFYZ6ltjYyOTJ0/udfvkyZNpamrK1HBERERERERERERkEDyEou1QKLEQRjo+qv4o2i6rLyNshwc3sNayWFHnor0GlrrRl/iAC2tgARdlDWU91iULvciExYvhzjsTi4VZFkydCgUFsXXhMNTWmva8eeZnLiIS8czaZ3D/xs1+f91vaHe8+NsQ6kAhFjKimlfC8wfBqutNuAWAE4SKp+GVY2HNrfiCsYJZXlfPCpJZ7ixsJ/Zk2x5sx8JK2N69fzxfKI3CZgAuL+CAHYDgwAvDLa1aCsDGpo0D3kcmTZwYO0eprx/ZsQyKtzhWqK19U6wtIiIiIiKyA7jpJjPfHLHrrmaOevNmWLoUvvnNoZ/WHzIzZ5pi4kuXxv7fd1/PfvfdZ7Z98Abkdq0r3C3x+kIKtm6PFQ0vzStNCMmubK2MtiPh1FlZcM45CqgW2Zlt3r45pX7NvuZB3c923/Y+t8cHaGxu3pzSPtsCbYMZ0thWX59euAWY/mlOgj71FNTVxZYvuwyeeAIOOQSKi+GII+Dll+HssxNvV91WHW13fz6Kf64adtmx+8VX23N7/kw4pQwWdHtuzp06vOMCbrst8fr5vvvCq69Cezu0tcEDD4zhQGYRERERERERERERERERERERERERERGRXgysAtsAhMNhPJ7e787tdhNSVTQREREREREREZExYSgCLhzHYVXdquhy0A6yoWkDe07Yc+ADaykDx4bsieAtGvh+euPEzWH2FnDRXg7+roIinVUQaIaCOTBxAUD0MVtYOF1F28vqe4ZeZMJ114HHEyu4cdppcMstMGcOBIPw8MPwne+A3x+7zdy5Aw80GQjHgSVLTJGu7Gw49liYMiVz9y8i/VtaaYrgb27aPHQ7bVgClc/Gll3ZsO/PYM7F5vhe+QJ8fO3Q3Z9IMu3l8MrRJiSie8hA5Jxg070JARTdwymSresIdOCyXIS79tlXwIWDk37ARfaE2Hh9NQM+J/qw6kOzi3Tvf4SUxtU3q6kxoVxjUlYJ0WCftk3gytglfRERERERkWHV1gb/+Ecs4GLvveGNN6CkxIQyzJgBd90Fhx8Od9wxkiPtw8yZ5n9f5s2Dgw+GjgpY17WuYLe076qqtSrazs/KJ9+bH11u6GwgEAqQ5clixQrzPT30UChKYQogk/P7IpJZW5q3pNSv1d86qPvpCHX0uT0+QGPL9tTG1B5sH8yQJAV33glut3nOOP10uP12s97tNl89HrBtePBBuOQSs64z2Ml2fyzQJN+bT0FWQXS5orUiQ6MHsibE2r5asMPgcif2yZ8JxZmdGPb7zfc2cn5zyCHwyitQ0PVt8njgrLPMqcH3vpfRoYmIiIiIiIiIiIiIiIiIiIiIiIiIiIgMq4xVw3Ach4svvpjs7Oyk2/3xFdJERERERERERERkVPMSjLZ9PlPswu3u4wZJlG8vpzPUmbBuZe3KwQVcNK8EbCiaO/B99MVyxS3YPbe3l8PTc8FOUgj6+IXYpYezsWkjACU5JTT5mgBY27B2GAbbt40b4dlnY8Wsvv51+NvfYtu9Xjj3XNhvPzj//Nj6ffc12zLh2WfhssugvDy2zrLgC18whdAmT87MOESkbx9WmyL4/RW1SkvZn02QkBMCTyEc8zRMPCpWrGjGmTD1RFjy/aG7T5F4dhDePBWCrT3DLbrxhWPP+153zyfJ7us6gh1YlhXNMOgz4MIZQMBFzmSiO++ohMI90rt9l6VVS6PtjmAHed68Ae0nUyZOjLVrakxBsXTPT0cFb3Gs3bqu2/mniIiIiIjI2HX//dDRNX00YQK8/TYUFsbmm11dL38uvtgUgx7z7ECsnTMJXKlPrFe2VCbMNxz1z6N69Fles5xDph5KWVd+9rx5Zr7fsvre95h8rSwyBA6+62A8Lg8ffOODkR7KsNnWsi2lfq2BwQVchOxQn9vbA7GwCk+38FaL2EHKIZa447F2hAP/6NXRAa+9Frumf/PNyedPXS4IheCKK8zy4orFCdvn3p54Db410Eqzr5mSnJLhG3xEdlzCsb+ha95+5J/UHn8cGhtNu7gYXn7ZhFvEn8t4vTB7NvzpTyMzRhEREREREREREREREREREREREREREZHhkLFqGBdddBGTJk2iuLg46f9JkyZx4YUXZmo4IiIiIiIiIiIiEq+0FHJyUu7uIVa4pLo6FpKQjpW1K1Nal5b2TeZr0dyBDao/8cVVkhW79tcnD7cAaNvItpZtBMKmqNXM4pnRTavqVg3lKFNy112xgmHz55vACMuKrQNTeGPePDjiiFgRjrnDlB3S3c9+Bl/8ImzrVovHceCFF+CcczIzDhHp3+LKWIGjVv/gCmMB0FkDWx404RYAR/4fTDwyFm4BpiCgpwAOu3Pw9yeSzNo7oHlF7PfQ8sC0U+GA38NeP4S8GdGu/pA/2s52Z/fYVfcAC1/Il1DIzdutwGX8soODP+wnLTlTYu3OSuin4FwyYTtMWUNZdHl59fK095FppXH1zerqTIG2MSmrJNZuWTNiwxARERERERlqjz8ea//sZ1BUlDxM2eWC887L3LiGjR0LCseV+vUXMOEV/VlZu5KtW00IOcDee0Mw2PdtRHZWjuPwYfWHLK5cjDMc1w9Hicn5icnwC6Yv4Jhdj+GYXY9hSn5szrAou2jA99Hia+m3TzDu+Nf9+73lii3Y19rY19pcdeRV0bnQZMHBMnRWrDDhFgCnnw677dZ74JHHAwccYNqpXMNeUb1iaAbZn+wJsXZH+agJBn755dh19J/8xJzfJAvq8nrNc7WIiIiIiIiIiIiIiIiIiIiIiIiIiIjIjiLJW6eHx7/+9a9M3ZWIiIiIiIiIiIika+ZMKCuD+vrYutWr4YILEvvddx/Mm4fXBtfhDrZtUVGRvEhDf4Yl4CJSALpwT3CCYGX13T9d8QWo7fQrRZXVm0LRFha7j9udNfVr8If9bGzaSNgO43b1UklkGLz0Uqzw85/+ZApfJSsm5vXC+PEm/GLCBFOUY7jdeiv87nemHSm2Ei8Ugo6O4R+HiPTPF/JR1VYVXV5atZRjZx07uJ3WvBYLFZh8HEz7YvJ+roxd5pKdTdgHq64Huoqv5UyBY5+B8YeAHQDLDQf+Ht6/BJo/TgigSCXgojPU2ed2y7JwW27CThjbsfGFegnP6k1uXCE7XzU43Z5Ms0tNYc3uoVxxwQrx4RYASyqXsGDGgvTGkWETJ8baVVXm3GVM8hbH2p2VEGwFb+HIjUdERERERGQIOA4sXmy+jh8Pl102sOsKY4odiLVdvVyraC83wdkAnVUQaIaCOXxS90m/u19Tv4Yp1bHlffbZCb6nIgMUP9e1qXkTc8bNGcHRDJ/2YHvC8ktfeYmCrAIArnjhCu5YfAdBO4jdfb4wTigE774Ly5ebwKHDDoP5800bUgs8cHDwhXzkeHJo7GxM2FaYXZjQdrrmYLf7t6f0GGVgPvrIzJc6DnzrW+bn3NdzRuS68dqGtf3ue2XdSo6edfTQDbY3WeNi7e2rR801ovffN9/PvDz43vd6Dw4Bc22+r+0iIiIiIiIiIiIiIiIiIiIiIiIiIiIiY8noeFe3iIiIiIiIiIiIjLyZM83/vsybBwcfjAsoLYXaWqioiBU1SUd8mIWFhYPDh1Ufpr+jCDsMdBVkySoBhqGqcULARaD3fr1Y27AWCwuPy8PMkplMLZzK5ubNBO0gW1u2Mqtk1tCNtQ+BAKzs+vbPnw9HHdV3f19X/evx44d3XABLl8KVVyaumz4d9tzThFqsWGG+RsI5RGRkfVT9UcLy4orFgw+4aFwCltcEFe1zDdih3gsV9VHAyHFg40aoqzMBPbvvPoYL3ktmbbo3VlwyuxROWgo5XekJ0YKUFiz4N3xyA4EPr4/etHtYBYDXlZgg1T2worfbhLue7DqCaaY65cQHXNT0/MXPnwmnlEHt27AoLswsd2q0uaRyScJNllQlLo9G48aZc1Lbhk8+SR7cNSZkT0xcbvjAhP1YAzjhFhERERERGSWqqqCxq8b5xRf3H8QwZl/TxYsEuELyOaz2cnh6bs8ASmC99/R+d7+peRO7N8eW99tvYNdqRHYG75a/m9DeUQMuGjsbo8G5Fhb53vzotsKsWLBEk6+px20dB+6911yja2w0xxPHMf+nTYN//QuOPx7K6st63DaZsvoyDphyAE2+puiYgGjgRmRMkbCNQDgQDcXY6ZSWQk5O7IJsKnJyzO1S9NFH5rnX7Ybjjus/ZCHyPLy5eXO/+17XsC7lcQyKywOeQgi1QsvqzNxnP/x+WLPGtM85BwoK+u6vcAsRERERERERERERERERERERERERERHZkeijTCIiIiIiIiIiIjIg06ebrxUVA7v9h9WxMItJ+ZMA2Ni8EX/IP7AdxgdOuHoWih4SVlxVrc7KtG++tmEtHpeHsBNmRtEMZpfMTtg2lGzHJhgOErZ7JkGsXAmhrtpal1wCwWDf+4pszxqmb2uE48AVV8SKcLlccM01sGkTvPoqLFoEq1fDggXDOw6RTKqqgn/+E77zHfj2t+Evf4ENG0Z6VKn7oOKDhOX3K94f/E7r3zfhFoW7w5TP9RlikUwwCH/8I+y6qwm1WLDAhORMnw6/+50pOCTSp43/JhqUdeCNkDMpMeQKYmEDcy8nEHcOku3J7rG7+AALl+VKKeDC44793vuCaRQ2A/DkgzvXtDure44dTMhF8bxed9E94GLR1kXpjWEEuFxQXGzaq1aN7FgGJWdS4rls/UJwlOwlIiIiIiJj29KlsfZJJ+0kIaTx1xPsJJPw/vqk4RYAm5s39rv7ipYK/H7zvXS5YtdsRKSnd7fGAi4Wbl04giMZXo2djbi65i3zvHlYcQfbouyiaJhEW6At4fphOAwXXGACiJq6si9s21y3A3Md46c/Ne0NTaldwFhTb6r+N3U2RceU7c7GEzffX5gdC7iI9N0pzZwJZWXmyTLy/777Evvcd1/i9rIyc7sULV5srp3st196IQvbWrb122dT86bUdzhYWePM17aNie8NGCErV5q/H4Bjj41dfxcRERERERERERERERERERERERERERHZGaRXEUhERERERERERESky667wocfDizgImSHooEOuZ5c9hi/BzXtNdiOTVlDGftP3j/9nfYIuEhSIau93BSNAuisgkAzFMyBiSkmJnjyY+22jVByILhSrwKypn4Nwa5CVtOLpjOzeCZuy43t2KxtWMsJu52Q8r7687u3f8cvXv8FJ8w5gRe/8mLCtiVxNauPOQa8SepexwsETBGb4Q64eO01eOcd087OhpdfhiOPjAVeAOyyi+lzww3DOxaR4dbeDtddB7fcYgreRP4OQyHz93bllXDzzaO/2N/iisUJy4u2pVEE3w5DoAncWeAtiq1rWmbaEz9tvhlpfBMqKuCEE0wYTqT4VkRlJfz85/D++/Dkk6kPU3YydhAalwIOFM2FORfFwiyScHARCKcecGFh4Q/5Ewq3ed09n4i9caEUHaGOdB8FZE+EjnLwVad/W3qG1Wxo3EBboI2CrIIB7S9Txo83Rfg2bDDnL32du6R5eMkcy4K8GdDWVSyw/r3kISUiIiIiIiJjyLJl4PGYua/58xPnfHdY8a/l0izCXdXZ3G+fmvYa/EHzvRzuuXuRse7NLW9G229seWPkBjLMGjsbo+38rPyEbYXZhYTjQlSbfc1MyJuA48A3vgEPPGDWd59XBxN2EbGleUtKY1nXuK7HmPK8eYljyirsMf6phVNT2v8OZ+bMvgMr5s2Dgw8e0K5DIRPEAHDQQebnmerzcF1HXb99KloG8GaBgcqZZOa9nTC0boTivTJ330ksW2amcx0HDj+8/2vuIiIiIiIiIiIiIiIiIiIiIiIiIiIiIjsSBVyIiIiIiIiIiIjsRKxfmyq+zrVJqpOkado0U5CquhrCYXCnnvPAhsYN0aCHXUt2ZfcJu7No2yLCTpiVtSsHFnCRUKE4yeNrL4en54Lt67nt+IWphVzkz4jb3xZTPIPUH/gn9Z9E2zOKZzCjaAYuy4XLclFWX5byflLx1pa3AFhcubjHtiVLzM/O64U99uh/X5FvbbKiNkPpr381v0fhMPzqVz3DLcCMG+BHPxresYgMp8ZGOOkkWLo0VhgqGEzs89Zbo7Twejfvbn0XALflJuyEqWytpKathskFk3u/UeMyWHk9VL8CoVazLn8WzDwHZpwJ4U6zbvx8EzbgTq1CX2UlHHGE+drb8cpxoKoqxQcnO6fmFWD7TXvu5ea5vo+Ai25/uglhFhHxARaWZeEP+3HizlX6u40vmOTcpT+5u5hCX80r075pyA6xvHo5AEXZRbT4W7Cx+aj6I46aeVT6Y8mgKVNMuIVtQ1kZ7Ldf733jw4VGncI9YgEXDe+DY/f5eygiIiIiIjLaRebBZsyAceNGejQZ4op7vR9O77V9va+13z6NnY0EbDOHmN0zb3NgHAecEFiesTE5KZKC+o56NjZtjC6X1Zex3bed4pziERzV8Gj0NUZDLLoH1SYLk5iQN4GHH4Z//Su2vqQEfvELOOwwc73uzTfhD3+Iba9sq0xpLJEgjCZfUzTst8eYshPH1ORrSmnfkp7Nm00YMMCBB5p50VSDkZo6+/+ZpBKCMWRyJsXa9YugcLcRDQeOBHi53aldcxcRERERERERERERERERERERERERERHZkagKhoiIiIiIiIiIyE6iPdAebW9r2Tbo/U2bZmodhcOmWHs6VtbGii3vMX4PZpfMxrIsvC5vwra0uOIqOIX99Ai58NcnD7cAaNuYfH13udOITqu2l4Mr9XALfzhIRUtFdHlG0QxmFM8gaAcJ2kHWNKxJeV+piARcNPmaCNvhhG3vv2+Klxx4YGrBJNnZppZVpPjJcHAceP118/s0axb88Ic9wy1EdgR+P5x4oil6Ewm3yMuD/feHgw6C4q6aWuFw7/sYLZp9zWxq3gTAxPyJ0fXJgnUACLbAB5fCC/Oh4qlYuAVA+2ZYczO8fVZsXemnUg63cBz4n/8x4RahkFm3YAE88IA5tjz0EBxzjFkf2S6SVN0ioKuA49QT+y2O5QvFzi1clitpWEX8OgsTcBEp6tZ9e4Q37n47Q52pjj4mbxpgQWcF+NM7UVtdtxp/2IR8zCyaGR33ksol6Y8jwyZPjtXfXLSo73OXURtuAVAwG6yuAfoboO5dsMfAE4OIiIiIiEgvVq0yc2EHHzzSI8mg+ICLzkoT5Jqi5kBHv33aAm3R+cVBzaU7DlQ8A298AR4pggez4KEceOUY2HC3Xo/KmLdo66KEZQeH97a91+/tHAc++AAefRTuvx9efBFa+8+eGVENHQ3Recfi7MQAj6LsooTlJl8T7e1w+eWx+bQzzoB16+D734ejjjJz6j/7GaxZA/Pnmz6BcGoXCyPzi42dsdCN7mPoHrqRSpiCpC/+9/aAA1IPtwBoD7b326exM803CgxG9kQTwgTQuBis1K/VD4f1602A/X77pXbNXURERERERERERERERERERERERERERGRHovJgIiIiIiIiIiIiO4nXNr0WbT+37rlB72/atFiR8E2b0rvtytqVeFwevC4vc8bNYXbJbEJ2iJAd4uOajwc2oPgC1HaAHgEXQ8HlgZxJpt2+pWfRjOxScOUkvembDVtx4sZ05YtXcv+K+6PLC7cuHLJhVrVWRQvHAHxY/WHC9tpa8/Xgg2MF9vsSKXTi9/fdbzDKymJBKZdf3n//UV2UWqQPv/89LF1qAixcLvj616G8HJYvN6EXlZVw1VXpFRgaKZFi9xYWu4/bHTAF/hdXJAm4sIPw1hmmKB4OOEkK4zm22WZ5zP+SfVMey/33wxtvmOelwkL4179g4UI4+2w49lg480yz/YEHoKion53Jzq1+EVguyBoPBXP67e4PxZ4cLayEYIqI7usCoUCf2yEx9CL+OT1lOVPiCn0t6fr7Sk3kb9ttuZk3cV6P9aPZxIng6XrY7703hs8X8mcDcT+zTf+JVRoUERGRqJUr4dJL4fjj4YgjTEHe22+HzgHkg4mIyPCKHJvnzt2Jwke9cYXb2zakddPOFArIB+1gdA5xwOHULWXw6mfgzVOg8gUItZn1dgBq34b3L4HXTkhrXkFktHl367sprYtwHHjuORPocPjh8KUvwQUXwEknwYwZ8Nvfjt6gi7qOumi7JKckYVthdmKYRGNnI3/7G9TVmcd81FHwyCMwfnxsfg1M0f5p0+C228zypLxJ0W37T96fxd9YHP0/Mc8EYXssD6V5pQDUttdG+/cIuEgyJhl6vlhGMyUlqd/Otu1oOElfOoL9hzINmdwpRAOqGz4wc/kjqKProc/p/1KCiIiIiIiIiIiIiIiIiIiIiIiIiIiIyA5HARciIiIiIiIiIiI7iWfXPRttP7P2mUHvb9q0WHvRov4LKDlxeRMf134cLYoxu2Q2s8fNNn1w+Kjmo4ENyHLFAic6q4gWtxhq+bPM147yJNtmwillcNJSWHBfwqZXa9cnLD+6+lHe2fpOdLkj2EFjx9AUbnl548sJyy9teClhORJUMXFiasXEsrPN15qaoRhdcm+9FavbfNJJY7ggtUgf1q0zxa8cxxSIeukl+Mc/YNy4WJ+8PNPngQdGbpyp+qDiA9yWG8uy2H/y/gDYjs17297r2fnDH0PN67Fgi6knwQnvwVkNcEYVLPg35M3sKpZnQdY4cKWW8uE48JOfmGOIZZmwiwsuMNsihbgiX88+G268cRAPWnZ89QvN72npp1Lq7gvFqoNZlpUQTBHRfV0grkilx+XBShJckBBwERpIwMVkomFfDYuTh8r0YknlEjyWh7ATZv4u8wFzjrZo66L0x5FhU6fGzjkXLeo7E2K0FiIEoGBW4s9s639NUFDkwdk7SzVYERGR5D78EE47DfbbD/75T3jlFfPc/+ST8L3vmcLDd92VOBclIiID5DgQaodgy6AOrJE56dzc1EKXdwjeQvB2Tfy1bUgM6e6D7YCdYoC37fJh2wMMp27dAC8fCXVvR/ZmvkQCMyNjCLWMeAFxkcF4e8vbPdeV91wHJoj9iCPgC18wodTdbd8Ov/yl2T4axV9n7B5w0T1corGzkaeeMof2rCy47z7TdiX5c3e7zX+AiraK6PrZJbOZv8v86P8pBVMAsLGpbquO3k9vYyrMigVcuCwXTb6mlB+rJBcIQHU1VFTEwqXiAy5yc1PfV0NnQ0r9wk4YJ1MvvgrnghM07eYVMJBw6CEU+R7n5IzoMERERERERERERERERERERERERERERERGhD5xJCIiIiIiIiIishNwHIenyp6KLr+88eWBFUuO0z3gIqufOuTxQQrvbXsPGxvbsWkLtFHVWhXdtq1lGw0dqRXM6MHTVZyltSzlYlFpK5hjgjTaNiffnj8Txh8MxfMSVq+oTwy4sB3z+OO9ueXNIRniC+tfSFh+bt1zCcuRQiapFjEpLjZFx9raoLZ2KEbY01tvmeI4EybAXnsNz32IjLR7743VAfzd7+C440y7e8Eol8sUZB3tPqj4IHosO2LGEdH171e8n1jMqOZNKPsz4IAnH457GY57HsYfAtnjIXcK7HoenLoeivY2+UTuPg5Q7eXQuAwqnoVN97P89eVUVZnv7UUXwSmnxAItuvN44NBDh+Thy44q0Gy+jj/YBAr0wx9XQMui/4ALB4eAHRdwYSX/ZU0IuBhIka7cKeB0nXzVvpnWedF7294j1HXbBdMXkO02SVcbmzfS4m9JfywZtPfesXPOsjJTlDCZUMgUxh618mcnLgcaYenlJrHDsSE4mtM5REREhtfzz8Nhh8FzXVMd8fNNjmP+NzTA3/7Wd9iViIj0Y/sn8MGl8HA+PFwAjxTDg1nw9tlQtzDtsItIQHYkTHmnUbib+dq6IeWbNHTLqLz88Mt5+OyHefjsh7n6qKsTtvlpwXEgGDTz9ykLdcDrJ0JguwlYzBoPB/4BvtQC5wXhXB8c/k8T+J1GaKbIaBMIB1hStQSAoqwi8rx5QNf8V7cA0Y4OOOEEWLzYLIfDcOCB8P3vm4Dls88288u2De3tQzA4x4Hat+Gjq+D9b8AH34YVv4KWsgHvstnXDIDbclOYXZiwLT5MwsKiuqmFd94xw/j61801id7m1SEWTF/ZWgmYec3xueMT+kzMmwiYa6AVrRUJY3JZrh4hG/FjdFvuhDAMSc/SpfA//2NC1KdOhenTTfuzn4X3kmSSp6K+oz5h+RdH/yL6fPSdQ7+TsC1j88bFe8fadhC2PJjSPP5wiQRMZWcrYFFERERERERERERERERERERERERERER2Pn18DEFERERERERERER2FKvqVlHVFguR8IV8vLXlLY7f7fgB77N7wEV/IoVPmn3N0aImAD9//ec9+j5V9hRfPeir6Q+qaC40vDeo4i/9yt8VcEGw2YRcFMxK6WYbWrb122fRtkWcMe+MwYwO27GjARdel5egHeS9be/R6m+NFoqJFNhItdDj3LmmkA/AJ5/AxIlDXyTyww9NUcqjjhra/YqMJk8+af6W9tkHfvjDnsEW8foqJDVaLNy6EAdzQDls2mGMzx1PY2cj2/3b2dS8iTnj5piOn/zeBAM5YTjiAZh8rFnvinuQkeL7Ew6B+rdN/2Tay+HpuWD7oquee/Jq3K79CdsWv/+9KTDW1/cWgPJyqE8szkRVFTQ3Q0mJqQAVr7QUZs7sZ6eyQ4j8bnmKUqpI5Qv5Epa9SYIkvO7YOsdxCIVjxfM87v4DLoLhARToypkSa9e9a4p8pRByEQgH+Lj24+jyvInzmDNuDqvrVwOwrGoZx846Nv3xZMi++8bajgP/+AdceWXPY6rHA48/Dkcfndnxpaxgds916++C7FIo2Q9W/S7zYxIRERkFli6F004zr6scxzz3/+xncOKJkJMD27bBn/8Md989dMVFq6vhpZdMcJZlmZcGJ51kAjpFRHZInTWw6EKofgksTyw8EUx725PQ8AGcsg7cqadVRF6XhUJ999vhFM2Fpg+hLUnARXYpuHIS5rkAKrvlSXxxzy/yuTmfA2BWySx+/87vo9tC3gYcZxIAq1enEez64Y+hbRNgw+Tj4JinzFgi83XubJh9Acz+il6Dypj2YdWHBMImYWf/yfvjD/tZXLkYX8jHxzUfc9DUg6J9v/99c63Ktk0Q+403mjDlcNis83rNtPIvfgEff9zbPabADsGme2HNn2D7SnOsBUzysw0rf20CoY/4T+/z5EmE7BBtQZN047JcCYEWkBgm4XF5+PC9wugx+dRTUz9/joQeWJbVI+CiNL8Ul+XCdmyqWqtwHIfWQGvvY+q23NTZlNogJKqqCs49F95+2zzXhrs9h7z5JqxcGVv2JT7l9CkSZhJx1ryzOGDKAQDkZ+Vz++LbE/oW5xSnPf60Fe2VuLz+Tphz0fDfby+yuqbxAwEFLIqIiIiIiIiIiIiIiIiIiIiIiIiIiMjOZwyURxIREREREREREZHBem7dc0nXDSbgoqAA8vOhvd0UdNm0CWYnqcUbESk4/tKGl/rd91vlbw0s4KJ4b2hcAi1re27rpVgUAFklqd9H/q6xol7VL8Gci8GV1edNAKra6vrts6J6Rerj6MXy6uU0+UwBmJnFM9nQtIGwE+aNzW9wytxTAMjONgVMUi1iMndurL16NRxxRKxgx1BpMzV32G03U+RsLBT3F0lHRUWs6NX555siQ/2GMIxiFS0V1HWY45rH5WH2uNnMK53Hu1vfBeCDig9MwEVgO1S/asItZl8I00/pe8eubHBIfqwG8Nf32PbMsi9iO3DggTBlSvKbxbO2lpsDWzqVnHJyoKxMIRfDYbSFjXQVvMOdk3x7e7n5PQTorMJf9WHC5vhgimTrHBxCccVBkwViAGR7YkVCA+EAjuNgpVMhq2SfWDvcAQ2LofTwfovirapdRdA2gRpF2UWU5pWy76R9KWsw4WFLKpeM6oCL3Xc35xCR4nx33AE/+lFiH9s2x+S33878+FKWPQG8xRDcnrh+1W9HZjwiIiKjQHs7nHmmeS53HLj5ZhMcGAzGQlV32w1uuw1+/nP43vcGfl+OY0It7roLnnoq8fVbpLjxpZfCrbeCO/WawyIio19HBbx8FHRs7Vphw7RTYNxB5vVk61oof9TMtacRbgFmThrMdMxOVQC6YDfAgkATBFvAWxTblj8TTikz8wzbV8OiCwCo6BYCMiE3lqo0IS8xYSl36mZgHgArVpj5MW9/+ZbBFlj/d8CGwt3hmGfMnJyr25Oay9uVKNUzpFxkrHh367u4LBcuy8UBUw4gEA6wrGoZtmPz7tZ3owEXCxeakDQw4RYLF5rroGDO9yLnfNOnw7//bc45ByTUCe+cA5XPAF0nmC4PZE8yc+i+arOudV1a4RYAzb7mhOWi7KI+l1e9Nw2Px5znHnNMaue1HcEOOoIdgJnn7B5wMT5nfDTgoqa9htZAK7ZjA2BhJYRsgAkG9rq8BO0gtmNHr29KarZuhaOOgsq4HIpzzoGDDzY/zw0b4P77Ydw4qK0121tbU99/RWtFwnJpXmnSdqTvvInz0n4MacsqhuyJ4O+67l7/HjSvguJ5YEVetGUuTSs313xN53KTiIiIiIiIiIiIiIiIiIiIiIiIiIiIyI5CJcJERERERERERGTnZodMWIEre4euqvRU2VPRtoWFg8MTZU/wp5P+NKj97rILrFtn2k8+Cd/5TvLiSbYNK1fC/vvDG5vf6He/Aw56KJoLOKaQc2cV5MYVxe6lWBSQ2K8/+TPNfQDUvA67fzOlm7WHOvvts6F5Q+rj6MWLG17EZblwHIf5u8xnQ9MGXJaLFze8mBBwAdDSklqB/d12M/1sG9asGZ7ijZ1d3568PHM/A/Wlh7/Eo6sfpfLKSqYWpvFzFRlmzz4ba59++tgPcYl/XpmQO4EHPn6ALHcW7q6iW0+ueZIv7/tlqHwuFgq0x2Xg2LEiQ8l4cgEHgqlVWWrtLOD9DYfjOBYnn5xiQE59ffrVhnw+czsFXAyt8lEYNuLygB0AJ9hzW3s5PD03IWTF1+3pvb+AC9uxCcUV2ErWHyAnLmDDwSFoB3vtm1T+bPAUQKgrQWr9XTDxiH5vdueSO6PtYDjIAXceQHVrdbQQ3T+W/YMfHfGj3m4+4rxec95SZvI42LIFnn4aPv/52Dmq45gihIM538iIor2g4f2RHoWIiMio8dhj5vQR4KqrTLgFJM5DReY4JkyAv/1tYPcTCMC3vw3//Kd5bREOm1PQqVPNeURlpenz/vtjLNzCVwedlRDuNOeJBXPAkzfSoxKR0STUAW98ATq2dQWVfgX2v97Mh9tBwDFBz4fcBpvvS3v3kTnpysqxPy+WloLdYnNj9e/B5M8mBknkz+y65hBT2a0ud28Fxd2WG6t0LZZ1Mo5jwqlTusxV8Uxs3uOwf5ggi+7hFhGWZV5A77iXz2QH9075OwCE7TD7TtrXBMni4LJcvFv+Lt897LsA3HefOTZ5PPDEEybcItn1zsj55ne/O4DB2GF450tQ9bxZLtoD9vw+zLk4dl7mq4W1t0PdO2nvvrGzMdp2cCjMSgyTyPXkRsMnbMemblsRoZAJSIgU6e9PTVtNtB22w4zLGZewfVzuOKyuA0aLv4XqtuqE7d3HBJCflU+zr5mwE6ahsyG1gQgdHfCFL5gg33AYvvY1+O1vTQh4oCvD2eMxwYC33mpCAMGEIR10UAphSEBlayVuy03YCQOJIUvdAy4qWyvJmOJ9ofb12PLqG2DBvaZth5PP7Q+TvK4/3a1b++6XoK/QbxiZ4G8RERERERGRMcC2TaBnc7OZuh4/HmbP3qE//iEiIiIiIiIiIiIiIiIiMurtTB8TExERERERERERgbAPKl+A8odNEZ9QVwFtywuln4JZ58GMsyFn4siOcwg1+5pZtG0RAONzxzOlYAqf1H3C5ubNrGtYxx4T9hjwvg89FDZuNIUznnkGrrgieT/bhrfeMgEXH1Z92O9+NzVvMo10Czy0ekzxLYCm5ZA9qd9iUWnL3zXWrnzeFPdy9V0FZFMgGonRp6rWqsGNDXh+/fPRItQn73EyD616CNuxeXbds/yFvwBQXAy1tbB8eWrFxLKyYMYMUyR65crhKeAY+YCRk8o3qhchO8Sjqx8F4K9L/sp1x103BCOT0aqxs5EJN04gz5tH+zXtIz2cfq1aZQoGTZwIe++d4o1GcZGb/6z4T7Rd017DhU9cmLD9mXXPmMbWx8DyQHYplB7e/449heY4HmqDjgrIm9Zn9/rWUmzHHJSOOiq10B4ZRUZj2Igr2wRchNp7Fm/01yeEWwD4uz1ved09zwm83c4Twna4120RWZ7EMAtfyJdewIVlwbiDoO5ts7z5/2D/6yBvRp8hM2+VvxVtd4Y6WVGTGDq2vnF96mMYIQcdBOvXm/NTgF/+Ej73OXN8cBzYtAn+/neYM2dkx9mv4n2gcWmsEKqIiMhO7j//MfMRs2bB9df33dfrNUWJ0xUOw3nnweOPm+V99jHFi//nf2JFf1tb4d//htdeS3//Geerg/JHzLlg/UISZqdcOTDtFNjtqzD1JFV+EdlJBMOm4HOy166suxOaVwAO7PUDOPgWE1QKifPf2eNh7vfTvu/p081U17JlO9khp3D3WLviGZjyuX5vUhECj8tNyO5ZULwwqxCPy0PIDuGyXNQGtjB9uims/cknKYaHbHkILDfk7gKTj+m/f2/hFyKjnG3bvLbpteg1s7AdjoY7ALy88WXAhCY/8ID5es45Jo+3PwO6lrXmjyYQGgemnw5HPQRYicfYnEmw7y8h2JL27ps6m6LtsB2mKLsoYbtlWeR582gLtBF2wnS0mgPGlCmp30d8YIWDw/jc8Qnbx+eOj35/ATY2bYy2bcemMLtnwEWBt4BmXzMAde11qQ9mJ/f3v5trto5jwv9uvjn2e5kVN42cnw8/+hH86lfmd/zDD00YRioqWipwWS7CTpgcTw45nlgo84Tc2HOTx+WhoqViCB5Vikr2MSEwkSCLTf8xc6l7/xSwYekPMjaUXXc1z73Ll5v3Q/R7jWogod8w/MHfIiIiIiIiIqPYBx/Agw+aObzqxDxVZs2Cb3/bzH/ovaMiIiIiIiIiIiIiIiIiIpmngAsREREREREREdl5lD8K718Cwe2m2LYThqxxph1shrp3oX0LzLl4pEeaXPdC5ykWOX9pw0vYjo2FxYLpC5hWOI2y+jIcHJ5b9xyXT7h8wENasMB8YARMYb+lS+GAAxKLKDkOtLfDo4+aooAbmjb0u99mX/PACjxMBW7uam97EqaekPptU5U/C3ABtvldqn4FphwPrt6nW8u71SUu8Bbg7ioK5Qv58If9QKzA2EC1B9pZuHVhdPmUPU8h35tPe7Cdzc2b2dS0idnjZjN/vgkmWbo09X3vs4/5kbzzDrS1DaxQ5H8/+S9nP3I2X9zzizx93tMJ2yKFIjs6Bv4hoyfXPBlt/+WDv3DNp69JKLYiO5bbP7gdgI5gBxubNjJn3OiuVN7WZo6Hu+yS4g1GeZGb1XWr+9zeFmjDF/KRs32lKc4+9UTzDeivgmHJ/kSLrtYvMoW++ji+tvliB6Px41M8fpSWmu9TOt/bnBxzO9nxefJNANr21eDqP1DCF1fMzsFJGkLRfV18kbekRUWBbHd2wrI/5IfspF17N+FQqH/PFPpyQvDxdfCpu+MG0jM4YXPT5j53GXbC0fOJEdFRCZXPQttGCHWAJ9eEj+3y+WgI2b77wiOPxG6yYgWceCLcdBNs324KuG3fPjLDT0vJvrFisiIiIju5mhp45RXzkuKCC1IrKOxNcprlOKag69q1Zv4hJ8e8RjviCFME9tZbTbiF48BXvgL//Kdpx++rsBAuvRS+8Y0he3jDo/wReO9rJrgNC9zZ5vWWOxcCjdC8ErY9Dm3rYZeTR3q0IpIBte21TL55MgD2L22s+Dkax4H1d5p26RFwUNckex8Biek69FBYvNiEMAQCicW3d2gFu8XaFc/A/Nv6vUll3Mv1HE8Oed686LJlWZTklFDfUU/YCVPZWsn++8O2beY5rt/i2uEATuXzWE4YZp5trpNZCrCQHdNb5W+x3R+bBPru899N2N7Q2cDiisU0rTo0ern1/PNNCEB/YTHJguCXVy/nwLsOZI/xe7D2e2sTN9phWHMr4EDpp+Coh83fXrLjrMsN3p5BEP1p7GyMth2c5GESWQW0BdoA8PvNg8hOY84xPuACSBpwEXZi4b6bmjZF22EnTGFWzzEVZhdCa8/HkGkdgQ4syyLXmztiY0iV48CdXU/bCxbAjTeadm+XX7KzYd48+Phj+Oij1K/DVrZWEuqaQx6fk/izLsouwm25CTthLCwqWysH8EgGqOSAWLhFxEdXwdrbTXh6oCn57YbBwQfDv/5lrgFu2gS77dbPDQYS+g3DH/wtIiIiIiIiMgq1tcFll8F//mPm60IhE6Y9a1bXZY31sHmzeZ/YT34y0qMVEREREREREREREREREdk5KeBCRERERERERER2fI4DH/8KVl4HWFC8D+z+Ddj1y5BjCjoR9pniQnXvmEJvcTZtgpdeghdfhA0bTP2AnBxToODEE83/WbOG+TEMpNB5V5Hz59Y9h8flwXEcjphxBFMLpvK3ZX/DwuKZdc9w+acGF3ARKSroOHD55SYAIZ7jwLXXQkuLWY4vTuKyXLi7iifZjh0teuLgULXpY6amW+ChFrAx+RPbHodDb0//QfXHkwfjDoSmZWZ5/d+TFwKMq7bYPeBi3ffXMaVgCgB3L7ubS56+BICAHaCho4EJeRMGNLQn1jwRLTSyS8EubGjcwJ4T9uTD6g8BeGjVQ1x11FXMnw8PPQSNjabw1fTp/e973jx4+WVTfOyJJ+Dcc5MXi4Tea9hf89o1ADyz9hnaA+3kZ+VHt0UCM8rK+i8c1Js/LvpjtN3ka+LBlQ9y8YEXD2xnMqp1BDu45b1bost/XPhHbv/CMPy9DyGfz/xtpFwsaoSK3NTVmcKx77wDTU2mKF5BgSnSc8IJsPvuELJDNPub+93XM2uf4exgV2WqnMmmwL6V5MDRXg7+euisMsXrsQAHGpeYgIt42aXgygHbfG8cYgeb/rIzombONAeb+NCo1atNpdyI++4zB76IrtAoGWKjMWxk/MFQ+YIJWEmBv1tx5WQBF91DLOIDLpL1j6y3sHC6Al98oQEcD8YdnFjoa9O9MPV4cw7sONC5LaH7dn8rvnD/9/PIJ4/wkyMz+KlgOwwb/gbr7oTmFWZd5Fhi0RXU4cCk4+AzL3HIIR7C4cRdvPuuKVw9pkw4HHNiKyIiIq++GptmufDC5AWF+/LBB3DXXfD00+Y1T3d5eXDeefDcc+Z+Pvc5uOce8xoj2esMr9e8Vhq1Vt8MH/4YsExo1t4/helnmDmtiM4q2Hy/mQ8VkZ3CTe/eFG2/sP4FTt4jbk67fhG0rjPtud/rCj0YunALMHNLwa6XqCtXmuWdQs4kcOeYa1Dtm0wQ5fhDTQH7XlSEIGSbF7bjcsb12D4hdwL1HfXYjk359nI+vY+5hlVdDQsXmus2vT5XBrdjReYKSo8wObOpzqlJ/7oH1UMsrL6PoPpRpa/HAGPncQAPrXyo3z7/9/H/MW3lobjd5trUCScM/BrVL1//JQDrGtdR3VYdvQ4IQNUL4Ksy7f26rlf3dZztI/S5N93DIZKGSWQVUo0JqQh7TPhHZ2fq91HTXpMwZzkuN/EY1f2YVb69PPH+k4RuFGUXRdvNvubUBzOENjVtYs5tJkS9RwjUEKmshNdeM1/9fsjNNddbjj3W/Fml44MPYM0a077sMgiH+w+tOPRQcxlk+fIUwpC6bNm+JfqzLs1PnJOPBC41dDYQskOZDbgY38tJRMfWzI2hy8EHx16rvv8+7LrrwI8hIiIiIiIiIhLT0GDm6pYvN9drv/pV+OY3Yf78WB/bNnPizz47cuMUEREREREREREREREREdnZ6e3TIiIiIiIiIiIy7CpaKqhpr+HgqSNUsWjLg13hFsBul8RCD1xxxYbdOTD9NJh5dnTVhx/Cd74DixaZD0d4vbDHHqbIRHu7+UDEE0+YcIB169IoWj4QAyl07vMRqq3mgZUPREMPXtn4CrkeE+Dh4PDqxlepbatlUsGkAQ1r//3N4/b7zfK778L995uigC4XhEKmhvgdd8C++0KrvzUaYgFwwpwTOGjqQQBUtVVxz0f3RLeVezuYmm7R6zDQAEwEfDWmQPXU4xN/1kNh6vGmwLITMkEalc/DlM8l3k9c8ZO1QfC6PATtEB6Xh0n5se/3jOIZCbte17huwAEXNy2MFSmrbKvksH8clrD9tvdviwZcRAoxLlwIZ57Zf7GNuXNjBcjuvjuxDnx3tt2zgNZbW95ibcPa6PJfl/yVHx3xo+jyoYea35V33km9sEq8JZVLWLTNFCOPFNe5eeHNXHTARcNSiGbM89WZYmqBBrCD4M6Doj1h3EEDKpyUaf/68F8JhY7+8eE/uPbYaxP+tkab/HxzWGhvH+mRJPfKK3DVVbB0qVnOyjLBFpYFbW3wz3+a57u1a+H1rS+ntM+n1z7N2ZFjvtVLVb32cnh6bjSwIkHDkp6/j/kz4ZQyqH0bFl1AQU5bdFNzcxrHj5kz+y66Nm/eTlRpcQSNxrCR0iOg6kVo32yCV7LjCnd1C1gB8MUFXNiOjTfJOYfLcuGyXNFgi0hRMIBsT/ITyCx3Fi7LFT1vGlDAxYRDE5edELx7PlQ8DVnjYOO9CZuf2PhmSrt9fdPrmQu46KyGt86AhvcACyYfB9O+aMIssoog2Aa1b0HlM+BvAJcn4YPMY9q4g8DymJ+biAye40DHNgg0mvNfTx7kzwZPbv+3FZER19hoXpu43TBnTuq3CwTgxz+G//1fc9vSUvja1+Doo6G42Ew5LV5sgi1ef93Ubgb41a/Ma4u+5krSnbfImPoPusItgF3PhQVd53zdz1Nzp8LcK2DWRRkdnoiMjNr2Wv7ywV+iyz9//eectPtJsXnTbU+a1x+eAphx1tDPpwOHHBJrv/027Ldf7wHKOxTLgvHzoe5dwDGB2Ycf3udNtsS9DCzN6xnyOblgMmUNZQBsa9nG3nvH5u7vvbfvgEc70Eb0KcxbmDxoIxJGCyYQKdAMBXNg4oI+x73TG0RQ/agJhxjIY4DR9zi6vFX+Vr99Xt/8Oqe2mHO7ceMGflz6qPojnlr7VHT5hndu4E8n/SnWYeO/zRx53gxzjXEYNHY2JsxBxgdHRMSvC3ubANiaRiZAdVs1HpeHoG0OOuNzxyds777cPfQgWehGSU5JtN3ib8FxnIxf17vmtWui7Uc+eYRz9jlnSPbb2gp//CP83/+Z9xKAeV1iWWaaIhw27c9/3rznINVghKefNn3z8uCcc1L7vT3wQPjXv8w1qvffh8MO6zs4MBiEitaK6PLk/Mk9+kzIm0BDZwMODlu2b0lt8EOheJ9RM2+6//7m+GHb5n0SX/5yPzcYSOg3DH/wt0gmODaEOsD2gyvbzM8OcaieiIiIiIjsOH70IxNu4fXCww/DKafE3vce4XKZwOejjhqZMYqI7FAcB9o2QMsaM4fj8pr3GY+fD96CkR6diIiIiIiIiIiIiIiMYqO/SpWIiIiIyA6sxdfCnUvu5OQ9Tma/yfuN9HBERESGRSAcYPqfpgPwyJce4ey9z+7nFkPMDsHynwEumHoCHP633vvGFW264w74/vdN+1OfMsXwTjjBFPuOaGuDl16CJ58c5nALGFixg5wc7t/+DoFwILrqzS2JhYsdHG774Dau/8z1AxqW12uCCd5917ynGeDCC02RjjPPNIXSL788Vlzpk7pPEm7/gwU/4ITdTgCgoaMhGnBhYbHUW8fh/RW9hp6Frxt+C/VPmaIWa2+DaZ8f0GPr06Rj4ZMbYssfXApfXG3aLq/5vWv+OLp5TQDCXQVlJudPxhX3Qf3pRdMTdl1WX8anpn9qQMNaVbeqz+1VbVX4Qj4OOignWjzlvvtM8ZO+hMOm0EnEG2+YWkW77Za82EqygIufv/bzhOXfvf07vjX/WxRkmT+qo4+Ge+6BlhZYudIUBEnHre/dGm3vN3k/VtSsYFXdKt7c8ibHzjo2vZ2NIJ/PhOu89x5UVJjwGK8XJk82dc/mz088DqWlYxus/qMpbN62IXkfdy5MOx2O+E/y4ma9KS9P/FsFUxm0udmkAk2dmrhtEAXqQ3aIP7z7BzNcy03YCRMIB7jt/YEfyzKhuNgUKlq/3hwT+y04lKEiN36/OU7fdZf5u/3iF+H88+Gkk0xBLzBDePNNc0zPyYHXNr2WsA93XHhFfIjRiuoVMK0QfNUQaEoecuGvTx5ugQtq3zRhRdmTEkKDyJ8Jxea4P6GgAQsbBxeLFsFnPzuKC81KcqMtbKR0AUR+j2vfgmmnxoJWIgEr/nrYvhoWXYA/LuDCcRyy3FlJd+t1efGH/T3WZ7t7D7iwLItIFsaAAi4K94Cs8aaYe2yUsPn/knYva9qc0m67F6YbNmEfvLQAOrZC7jQ48kGYdJQpTB9fbLV4b5j7PfMzwRwCZ82CzZszM8xh48mFkv2g6cP++7pyEsNYRMQI+2Dz/Sa4qOYN8Nclbrc8MO5AmH467HO1CqqJjGKBgDnPT6fgsOPAaafBiy+aAL8bb4Tvfte8tAiFzHxGOAxf+pIpOvu5z8GWLbDXXnDkkcP3WIbdx780r70Kd4cj7gOs3o9vLg9kl2RydCIyQm569yZ84djrymVVy3hh/QucvMfJZkWgwXwt3K33cItI6MEAAw/mzo2FZd99t5mP6kvkWL1DmHYq1C3EvCb/D+x5GZTsn/i9tmNFuivj6nUnC/SdlD8pGvJc017D3kc5gJk7u/9+85xXUtLLWNw5sXao0xQajn+e6CuM9viFozbkIhCAFStMYP3HH5vrd5Zl5tL3399c59t//2EOVRlgUD319aMnGGIgjwFG3+Posr5xfb99yhrKolPPjtN3375c+8a1Cct3LLmDnxz5E6YWdl0bad9k5hwnHd37TgZ5nG3sbMRtuaMBF4XZfYdJhEqX43Z/nqVLLVpaoKhnHkYPNW01Cct9BVx4XB5q2mui13F6G1NRdlE0mCPshGkPtkevHWbCsqplPLjywejyT17+CafvdXqv87ypeuMNOPdc86cxfrx538EJJ5jr6tnZ5jj15pvmvQZr1qT3nBcJANx1V/NaJxUHHRT7Hf/rX03xx764PTZ17WYexWW5mJg/sUefyfmTWduwFkgMwxh27myYcBjULwIG8Yc7BPLzzfXydetMkMkf/2iuo/XGnj4T10De/zDcwd8iw6V5FVQ8aa631b0LobbYNnc+TDzCPDdOPwtK5vW+HxERERER2amsX2/CnG0bbrjBhINC8veF9hXgKSIi/XAcqHoJNt6d/L11ALhgyglw7FO9X0cWEREREREREREREZGd2o7y8S8RERERkVHB6fokqBVfeLMP5z56Li9seIGfvvpTOq7pINebO5zDExERGRE3vBMLAbj0mUv5zOzP9Ch2MazKHzZFQwAO+L0pEuTqe1rsvfdMwTvHgZ//HH7zm+TFlAoK4NRTTZDDsJs50yQKRIodpFjo4J7XLkroEilqEu+x1Y8Nqij8iSeaokHhrlrQtg2//rX5393K2pUJy7NLZkfb43PHk+fNoyPYgcflMX0Pvaz/Yg3dC19v/Qq8/ZhpV70Imx+AmeckFuuPKxY1IBOPMsVQna79dGyFFw+Dw/8FRXNh2xOw5DvR7p/4Y9/7mcWJj2dG0Yxo2+vyRguBpGvh1oWEUnhc9y6/l28e8k3mzIENG+DZZ00B6Bkzev+gj9ttij/NnGlyDAC+9jVTnMVxEuvOgynecdVVseXXN73O2+VvAzCnZA4bmzfS5Gvi9g9u56dH/RSAY46J9X/uOdh779SLuVS2VvLQqocAyHHn8K353+KyZy/DwuKWRbeMiYCL99+H66+HF14wx5tJk+DAAyEvzxR9e/RR8z3ddVdzKEgrVMdxYPXNsOJnpmBZ6RGw15Uw5TNQ0FW0Lrgd6t6Dmlegfkn64RZz56YdwENZ2YCKsTy86mG2tWwD4ITdTuClDS8RdsLc9v5t/PTInyYtkDQafPrTcPPNJtzirbfg2GP7+XBd9+M+pHbs9/vNbeJv10fYyPX37Mbf/15Mfr4pgHfaaT2f83JyTLHX4483y76QL1pwqiCrgGuPiRXvuv/j+1levRwHxxTkz58FrRug9vU0i0Y75hi75s9wwG+A5N+s4rwWDp69jGWbD+G55yx+9as07kIkmQmHAi7AhrV3wIxuJ3r5M83/Lj7blJB0MMFhvRU+87g8SQMuvO7kH/jyurxYxJ5gk922X5YFk48z5yVx4TO9qekqghd2wkzJn8JrF8XCbH75+i95fM3jhJ0w9R31fexlCK25Bdq3mIJlJ7wLubuY9d0/JBdZLtw9uuqUU0yhttAgT/lG3MSjoHklOMHe+xTOhc+8lPB7KSLA1idg8bdNWFb+LJh1Hkz8tAnFsTwm/Kd+IVS/BhVPwb4/G+kRi0gfCgvNvFNnpylgnUoR10cfNa+xwcwzHHNMrOhJpLh1/OueUMjcx9y5Qzv2jGr+2MyFAex7rZkD6K/AQPz29q3mmNiw2BSL7SiHcMDMEXiLYfwhppDslONh4pEKBhIZI+ra6/jLB38BoMBbQFvQFJX95eu/5KTdT+oKV+x6zZgsnBR6Dz1II/DA44H99oMlS0wAweuvw1FH9R44sMOEWwDs8nn46CembQfh7S/BFz4GLHO9yg6ZYzYQdKCp6zKO23InDbgozS3F4/IQtIMEwgFmzWtiwoTxNDRAR4cp+PW73/Wctw+FoL65mCmRFS1rwPlC4vG81zBaoG3jqAu4qK42j/XvfzfT08XFJih68mSzfdMmePBBs37t2mEOuBhgUH06YcXDLkOhy5nQ3NlMIBzot58v5CMnz084nE1Tk5leT+v6C/Bh1Yc8VfYUYELtt7VsIxAOcMO7N3DrSbeaTqEO89Wdm/zC2hAcZxs7GxOWC7N6XispzimOBuQ4c14g/NY1gAlZOO20/v9GqtqqotciLSyKshNTMcbljou2LSzqOupwWa5YwEWSMRVmFUavN0QeRyYDLn780o8Tlrds38Lfl/6d7xz2nV5u0b+PPzbXVBzHhFzcdZe53uc4see34mITtnfeeeZYlo7INfl0Cjjuv3+s/dBD8Ic/wJQpyQtDhkKw+JO66M/Nbbkpze35Nx4fuFTXXoft2Lgy9Rphl5Oh4f2U5r2H2+GHw8aN5jLc3XfDpZf2fh7jctF/6DdkPvhbZKh1VMLSy2Hro+DKgolHw7wfQsmB4MmHcAc0LTehFxv/bbYNlr8Rtq+CYIs5t3Znm3nhwt01fyEiIjslnw9WroRly0woaGureS2Rk2NC2g4+2Pyf2DPLTkRkxN1yi3kNPXGi+TyHQizS5NjQWQ2hdsAxc5K5u6T3vnARGbvaNpmwisYl0PAB+GrN9Ul3FuTNMO/5GD8fivaCD38INa+DpwB2PQ+mfNa8vy6r2My9tq4325uWK9xCRERERERERERERER6tSN9BExEREREZESF7BDjbhhHW6CN5//neU7a/aQ++z+y6hFe2PBCdPnHL/+Yv3z+L8M9TBERkYxaVbuK6966Lrrc2NnIFS9cwb1n3Ju5QTR/DJYXcqfA+AOT92kvN0V7OqsIdWznkq+ejsuVx6c/bcItoPciBBktstRfsYMkhQ7er3i/392WNZRh2zauZBUsUnDCCfCLX6TWd2XtSrwuL0E7iIWVEPZgWRa7Fu/K6vrVBO0gy6uXD2g8TD0BXDmxIjDvf928AXvc/qZAlx0cfLELbwFMOsa8YZuualPbP4GXDu/R1XZgY1dxZbflZva42QnbC7MLo4XFwk54wAEX/17+78Qhxr2JPGjHiiL/95P/8s1Dvskxx8CWLaZIyY9/DI88kny/oRBs2wazZpkiLH/6k1m3cCF861umUEcoZD5M5HLBP/4BDz8cC7hwHIefv/bz6P5+sOAHfO/57wHw+3d+z2WHXkZhdiGzZ5tQh9pa+POf4Yor+v77CgZjhXZ+9NKPCNthLCz2LN2T5s7maEGVp9c+zdvlb/PpmZ/uuRM7aArvt6zuKtwVNG++z54ARfNMsYNkb8Z3bFMgwQ6YIkTuPPNG/gFwHPje9+D2201ozg9+AN/+Nsye3bNvVRU8/3z6xZVYd4cpoObKhiPvh5lfij3WCG8xTP2c+R8ptJSq+vr0C175fOZ2M6ZD3TtQ/545Xjcvh0CzKermzjYfpBh3IJTsC1NPxs6dxnVvxp5XvrzvlwnaQV7Z+AqtgVZuX3w7Vx11Va93O5I++1nzOxsMwlNPmYCLfqVb5CbNsJFPmMcfWIEN/Pa38MUvmvXJ/vbiPyT43rb3osWmDt3lUH50xI+i29oD7aysXUnIDrG2cS2BqZeSVf0KtJRB6zoo2D2xeFd2aeIxO8oESLL2NtjrCtOvl+Ijpxz0NB+VH8KSJdDQAOPH96wPJkMk0ATbV5uChuFOwDIfgCzczRw3B3gsHFW8hSasqmU11Lxqjk/jD+n1w1l+JxZwAX0EVri9kCSjIMedk7R/96AMXyjN42zE9DNg639T6vpe9cfRomUHTDmAeRNj4Tmfmv4pHltjAsQq2yqp76inNG8YCxcG22Dl9YBjQpnyZvRfgCjuZ/T5z8P//u/wDS9jJhwOa/t5INkTR3W4xSefwIsvmsJ+S5dCRYV5LnS7oagIDjjAFNg79lg4+uhhLjYqO48tD8G7XzZBFgf+wRxHLMucfEcCLx3HHN/3uhJaN43seEWkX3vsEWs//zx84Qt9zxk4Dlx+uZmn+NKX4DOf6f8+Is9B4ZGvjzpwreti7aknJD+HjcyDAnRWmdfgngJzzrj5fvNafPrpsMe3YNzBkFXSNX+yFhqXQu27sM/VKg4pMobctPAmAnYAC4uLD7yYVze9yur61SypWsKLG14072vwlgAWdGxLvpPeQg/SDDz47Gfhww/NsfYnP4HFi5P3CwZh1SoTAJyW8vLE0FeIBb9C0vBXSksHFMKbluK9IXcadFaY5fZN8Opn4PC/Q8n+5vvYFZhdHYrNMbgsV9LX3t3X1XRUcv7546NBjzfcAAcdBGedFZvTC4dN4f4TP5/H/Rceyr5Tl5iCw/uMzrnUVLz4onmMPh+cdBL86ldmmrT7pS7bNr9POcmnYIZOKoHFSYLqh/33Lx0DDV0ebY+DntdH7zntHvaZtA8Ay6uXc8nTl0S35e76CbZ9EIEAPPMMnHpqevMT175xbfSa1BWHX8HVr15N0A5yx+I7+MmRP2GXwl3MORWAvy755PUQHGcbfY3ReXugR/hEZJ3b5TYhFdPfIyfXxtfp4rHH4Oyz+7+PytZKnK6jVGF2YY8wg/G546PtsBOm2decsD1ZQHlhdmFC0G9TZ1PC9ePh9PKGl3ltswn53X/y/qysXYnt2Pzi9V9w4QEXDihQPRyGr33N/JgPO8z8uUDyIInI71m6BWVLSszXbdvMMS6VS/xFRbBgAbz/vgkNvOYauOee5H09Hrj1n5XQlVfi4PT6fBQJXAo7Yera65hcMDm9BzNQU0+EFSm8QcGVY64vDaNjj439nH/zm9jPv3vxzWDQhJnMmDGswxEZeZ3V8PyB5pri5M+ac96C2WZuwXKb+QTHNiFwLq+Zm3Dnpn8/jgOVz8PGf5mgDF8V5Ezuup7kNkEXrevMfPDkz8HRj8fmhkVERHZgmzebQLt77zXn/vvtB/Pnw5w55hx1+3YTPHvjjSZcfN26AbwXUUR2CsEgVFaa+VfLMuGdu+zSzzyEHTTvKXTCJuzOnTegN3KWlZm57iOP1DEqJY5j3uO45QFTzL75Y/P+9qwSwILgdvO1eG9zDXna6VB6mK73iuxomlfB8quh4hnzHpBdPg8zzjLvh3bnmNCb7Suh8UPY+rg5PrdvgUlHw5EPQc4kM2cTP38y7iAo2U/hFiIiIiIiIiIiIiIi0ie9O1NEREREZAg4jsP3n/8+bYE2AE554BSWfnMp+0/eP2n/8u3lfP2prwOmyHHYCXP74ts5efeT+cKeX8jYuAcl0Ay1b0NrV5HS9q0Q7nrnqqfAfCitcA9T/Gb8fOilwKOIiOy4wnaYi564yBTIAGaVzGJz82b+s+I/nL/f+f2GQQ2ZSGH/3t5U214OT8+NFg1ZXzmXVWvOB+BnPzMfkMhoiMUQqmmroTPUGV3O8eREiyWH7BAdQVPE3nZsVtauZP8pyc9d+nPooSb8YPPm/vsur1keDVuYlD+JbE/iJ0/2mLAHa+rX4ODwce3HOI6Dle6HWzx5MO0U2PY4OCHzYZlXPm0Kl045AdrWp1bwoj8zz4aa1/rtVhECX1dFKpflYkZRz6oVuxTtwtqGteZnUbdyQMOpa6uLFtAZnzOeiw68KLrtsdWPsWX7FtOvow6Ab3wD/vlPs/3RR037a19L3GcoBO3t5m/h/vtNUcibbopt/+c/YdMmE5CRnw//+pf5cOQBB8T6/O8H/8vCbQsBE7qxomYFUwqmUN1WzXb/dr7x9Dd48OwHsSw4/nh48EFT3OPXvzYF95N9GMpxTIEYrxcaOxp5cOWD0YI6H9d8zMraldFlgO89+z0++vZHXQ+qAzbfBxvugcbFUDALJnwKvEXgyYdwhyl2UH+1+YDPF9eA7Tdv5K96EZpXgK/ehJx4C80HsYKtEPKZfU0+DqZ90RSkdrm7D72HP/3JhFvk5cGiRbD33r1/nmvqVLjwwn53mailDJZdadoH/gFmnGnayY6JVtd4Pfnp3UdpqakOlk7IRU42BF+AJ0+Djgrzoakpx8Psr0DBHDO+YBts/xiaPoZN98Lsr3D929dT1lAW3c1FT1yUsNufvfozvnvYdynIKkjvMWRAfj4cdxy88gr85z9w7bWmCNEAs4WGxH1cADhMnmyCVlIZSyAcYHmNCSDyurzsM3GfhO17le4Vfe63HZsV3tnMj/w9brwH9v8NxBWrIn8mnFJmXl8uiiuUlj/HFPsLtcOir8DRT5nf0SSFRz5/4HP86rFfA+b72l9R+1QLPkmXpo9g3V2w9TEItZgPM+VOM8dAMMfATfdA2yb4wkrzQaixbsaZ8MkfzDH+g0vhpKVgh5Me130OuIjGXfUIpojw9nIu2v1cKGLoAi5OMWFvTpJ0jTidZLOmaTNgxjqvdF7C9rmlcxMK5C2tXMqJu584sDGlomNbV4gKplhZsg/UJivOXDAHJi7gmGPMB5z9/t7vYkwE4Uw6uu/tlhsmHJKZsaRp4UJzjrhwIeyzD3z5y3DmmaaARn6+Oc/ctAmWL4ePPoIjjlC4hQyR9i0m5BDLFGCf96PYMST+796yzPERID8DlQVHa7FlkVGiuRnWrzf/t20zz+GWBbm5sOuuJgSytNT8Gd13H5x2Wt/7a2w0f2Jgnn/C4Z7FRbubNs30+eijMfyawXHiFpKc7HSbB01guWHGGXDYXSb4Mxwwr80jJ03jDoBdz43NHYjImLC6bjV/XPTH6Ou5soayhNebFz1+EVU/rMI16WgouxU6K6HmDZh41LAUf/3GN0zxPIAlS+C734W//MUcviKHm2DQPBf87Gfw7LNp7DzN4NeonBxTLWs4z7ssC2adD2tuiYVvN3wAzx1ginzZgWjXyrigpb4KiofjQrwrWyv58pf3jc6JOY6ZR25rg4suMs9vmzfD178OK1bAi2vOY9+pS01wUfsWyJseO773GkZLrED/KLBxo7le0dFhirRff30siLs7lysxi2FYDSCoftRJN3R5lFq4dSEelyc6V3323meTn2Wufew+fvdowIXbctM6+XkmTTqI2lp44AETnNKfyPXjh1Y9xNNrnwbAwuKj6o+YXjSdTc2bCNkh/ue//8PrF78OEw41f/dVL5o573Svw6SgsbMx4diQNEwiKy5MwhPk0CNbefe1Yh580Mzj7Ltv7/MzwaA53kSU5JT06JPrycXr8hK0g9iOzXbf9ujPIHL/ycbU/XFkQsgO8e1nvx1dPm3P0yjOLubt8rdp9jVz1StXcfsXbk97v++9Z57jAG691by26O+9Bum+F+HYY83zaX29Cfs5/vjU9nHZZeZaJMC//22u7//qV7HXP5Gv3/42LNlcCZ8yfcN2OKXApcrWyswFXIw72FzbDbb03qdobzju+WEPB/7yl03AYns71NTAGWfAk0+abZHXoaEQNDXBFVfAf1PLox6cvuahNAclw8mxYeH5EGg0QW7HPY+5ikbi+xMsV2zONntS+vfTvgXePNW8d2P8oXDQjbDLyWY+I54dgKYVUPWCwi1ERGSn8NxzcPrpZirqu9+Fn/4UJk0yc0XBrreMuN3mfygEL700SgvH63xWZEQ0NcHDD8Pzz5t5ZL/f/HkVFJg5g9ZWqK01QZ2f+xx84fMOxx2wFG/1Y9D0IWxfbd5r7ck3896hNnO9MW8XKN7XvK9/l5Ni7znsQ+SS55h4b9dIa1kLiy6Chveg5ADY/RKY/Bnzec7I6zAnbIJ0G5fC9DPAPbCD/6ZN8NZbsHat+b91q/k9cbtNuOoee8Cee5rPlXzqU5CV/G2UIjuvsA+qXjLXYlvWwPZV5rMSnmywQ+bgVzAbSvaB0k+bY2beLqntu24hvHqs2cfeP4F9f2k+U2UHwPKYeRg7DNNPM8eGRRfDpv9A7hQ4+klzbI6fr4mIf3+diMgOLhiEujpzfuNymbeSTJw4Rt9DKCIiIiIiMpbpWqGIyJikd2iKiIiIiAyBP7//Z/665K/R5ZAd4sT7TmTpN5eyS2HiG4nCdpjz/3s+rYFWAL532Pe49f1bAfjK41/hk+98wpSCKb3e1+bmzbhwMbNkhCZWmj6CFb+EyufMmx+nnwqzvgI5k0yRXycMwXZTiLT+Axh/0I4RbqHJr1GrI9jBm5vf5JBdDmFS/gA+8Ciys3NsUxQ23AmhTlP41pVtChN7CiBr3IA/HXDFC1ewtGopADOKZnDKnqfwvx+Y6jrn/fc8Vn17FbsUpfiG28HIn2menzq2ga/WFOeJf+Otvz6hUE+7P1ZQZPz4sRtuAfDihhcTlpd8Ywn7TDKFyBs6Gii9yRSdcFkunl///IADLizLFKb6xS/Mh1h64/HAipoV0eXdx+/eo89u43bD4/IQtIO0BlqpaqvqcT6Vkt0vga2PxJZD7bDyN+b/UJl1Piz7oQlE6MPauHrSITvE9KLpPXdVMou1DWsB2Ni0EduxcSUr5NyLsB3mlU2v4ODgcXk4ba/TuOXEW6LbC7MK+d07vyNkh1hevZymziYOP3wcBx5oPohk26a4VW2tKWATKbZRUQFf+ELsQybz55u6RWvWxD5A9Prr5n8ytm1zzavXJIzzno/uSSiQ/dCqh7jp+JuYUTyD737XBGmACdI47DBTBCS+sGQwaJZ//Wv4/e/hBy/+ICHMwsHBSSjoCMtrl1O+vZyZVie8ehx0VsOcr8KCe6Boz64b2uZYYbljx4j2rbD+LvjoKnNc3OM75k3/4w5M8kPwQ/37MPFT5sNZKdi+3Xy/AX73O/O97e/Nr8mOSWsb1jL3L3MBeP//2TvrMKvKtY3/1trd08nA0B0S0mKBit2KrdhxjGPrEbv7CHaCgYGKIKWCdCshMQwwTHfu2b3X98e7c/ak9aln7uuaa3asvda73vXGk/czfT2HZx4e/rL0e1HoR1JB3xubJ6IMEoQHycEhRBDeLnTtKkjgIuXlXbvgwohiBbNnh1nEFAXqZ0LuvWDsKgjxbQOikyiCsPaFrLNCSRPPrHmm1ab48XPTtzfx9qlvt6/tfzJOOQWWLhXJgFde+QeQ2HTwWdQ92QXpCzWJie0PvN5euj1UqMjr99IvqV/U95HvZUlmVcUBRiaMFMlxu56B7Auik+dA7NW2Jixz2dNg5yPidfES+P5YOOLLMDFJBFHXiO6bSUzwUlmlZtYsOOssGD++eSIuj0d00aBB7bvf34SmeuTfjcRaUWDrvwX5oqkHjHhBEN4GC1gEn0FwXfE6/xnFLQD63Ai7nhb3WLMNfjgOjpgHGMTYjSBlcyrR1MEtFbL4rQUuXN5WKjW0Bo1VJLoVLYyaN1Gw9OXnfk/gzzkdEHO7b1LfqEP6JobfqyQVm4o2/bEFLiLv3+cU+3Tk/tAaOfPkNRiSx3LMMbBoUcvy6d8i4cSUJQpxVW4gXEYlAooP0k/405vVFr77DqZOFcvI66+LPc/jETJmZL+npQn5srOwRSd+VxQuEEXtJBUMeqD1Ajm/Vv7tKP7KZMud6MT/I6qrxT4xZ44gqT7iCPGXkhImSmloEMWQPvoIpk2DmTNh/nwxNXr0aHkPiSxm4fM1qfvQAi6+WJC85uXBN9/ACSf8Dfcoc/fw67LlgigmUg5tYgeNQtJYGP9xWL5vWritpeLBnehEJ/7SuPTLS6Nssd8d+C7q+7LGMh5f9Tj3TrgDtIngroScWZB6ZPSJWip60MGCBz17wpQpogCszycK/9bViSLAiQGTz+rVcP75sWaTvz26XyJsDU0RUdwCRMHsIFojFI98roV1hVw6VhBH5eSIfc/lEjb/u+8Wvq6cHNHnAMv2nsVtRwWKIm+8Ho78JnzyYDFaV4UgJIssSGv46zyUBx8UxS0GDoSHHhKftebP+zv7+jrx6/DjoR/x+cWgz7JmhYpbgCjMkGpKpdReioLC6sIfmTbtHv77X/j6a9i8GYYMaVkWjCzKc+PCG6O++3jnxyEflYLC8rzlbCraxMheV8GeFwMVP9+HnldGE23/Dutsub086n1zhcCtOmvU+9HHFrFymQ0Q8vZm4dqPuXePB+rrFSoaw/buREMTEnFAkiRselvouAZ3Q5QPr9miGzpL1JpW7axu7vZ+d/zr23+RW50bev/wyrAPWUFh5qaZXD3yaoakdsx/XhVRnyM7+49Zf6ZMEftkcTG8+qrQXdqDM88UJLe1teL9gw9CURHcd58wPezbJ15/+ilknVYY+l17Cy4V1hdyWPphv+ne2g1ZJeyi+Z+D4m3+GJXuDy9uAaKY7+WXC33V5xNFR447Dt58E3oFwiE2boSLLhJkj384fo0dqtMG1YnfCw37oTQQPDL0cUCKLR7fSvHydsFZBt8dLc6TfSGM+0DEQzRnt5C1kDBc/HWiE53oRCc68Q/Htm1C5vd64aWXRIG7oO4qSbEk42q1KJbXYfzROTWd8mwnOvH/ghdeELZkg0EUcXzsMRgwIPY4nw9++gmGdN+LZv258P1PkHEi9Lg0ULzCFvuj6p+EntDl5HbHFvbsCStXwvr1wi71t/PZ/lmwH4JlR4KrDPrcACNfbl4/klQiZteU/at8vosWwX/+I2yHkyfDyScLW2J8vLCLeL2iAMrevaL46+GH//biFt/mfMtdy+7irIFncd/E+5A6q5104u8MRYHdz8OOhwAJel4O/W+HlPGxOScNB6HsR+h2bkwxGq/fi6IoaJrmaTvLYcVJIsim/20w7Inwd5Hnl1VAMEnoG8APPa8QeYNN80t+q/0mEn4f1O2CinVQ+wv47CK2z+8SfhG1QbTBNgiSJ4ClZ/Pxfp3458LvFWOjIVeMDV8wt1UPKoOIg48fAobMzupXnfjdoCgiJnHePFixAgoKICtLxFYYjWJJtduhpET4/saPF0XejjlGxL53ov3YWryVN7a8wbUjr2Vw6uD/7+Z0ohOd6EQnOtGJTvz/QVFEjqykEja6Tv2mE51oHp2+wk50ohOd+NvifyplZ+bMmTz99NMUFxczcOBAXnjhBSZOnNji8StWrODWW29l586dZGRkcMcdd3DNNddEHfP5559z//33k5ubS8+ePXn00Uc5/fTTf9N1O9GJTnSiE534S6K1IFT4e5Dy/S/jTyDmVxSREP/TT7Bjh3Dm6vXi8yAZrSSB2w29e8OoUSIZOCk29/H/F/Z8qFwHNduhdg+ojU2MgpIgMFZbBNFL3BCe3/09ty67AwC9Ws/kHpOZv3c+JQ0ljHtrHBumbyDFHCbdnzpnKqvzV4fe/3fjf5GQUFCodlYzaOYgSv5dglqOFtfdPjcPLn+Qx1Y9BsCjRz/KHePviDkOhNN8xw7YuVO89nrDZAWyLALSzWbo1w+GDhUkQCpVzGliUfA1rDpXBDSN+xC6nSMCSAJks1Gw9Ib0Kc0T6P7d0Gn8+stia/FWJrwzgUaPIBZfOG0hJ/T+6xE7dqITvxaKovDBtg+45MtLMGlMrL58NUPThrb6G7vbzi2LbmFv1V5ePuHl5gN/ylZC4ddQvk4Q59j6i2BTVZCw1yWKAdTthvpcQTqePBHSJoOle+z5msHyg8v578b/ht7n1+WHilsA1DhrOG72cWy/bnv7OuO3oPvF8PN94K0XQcEjXor+vglhSHbSQTQqNx6flsWLxV7Zrn3yL4hv9n6DSlLhU3yYNCb6J4fJwxONiWTHZXOw5iCKovD1nq+5c8Kdv/paF18sCC9ag1OuoNJRCQhi5OYKXHSP6443gjR6R9mOX1fgIu1YiD9MkFK3ROb8W6GxQs/pkPNKq9fY6xbE1wqCACTLmhVzTDdbN9SyGq/fi9vnpqCugK629ssRm4o2hQqo+fy+6AIHwKjMUaF+9ePn+wPfc+aAM7n3Xjj77PBxd98tEhwnTBAqxIoVQp4/LMBFIkkiSeX889vXrlmbZmH32MMfSESR1ARx/cLr+fr8rxkzRpCwLF0qZNgzzhCEIC+/LIJEQci4558vEqkee0xhSe6SdrXloy2vcWfla+CpFUkBhz0pyLJDbZNFIZzIYPz97whiFEMmHLtCJPe0FDSg0kHy+FiChlZQWRkm3e7f/9etNUtylzB1ztTQ+9FvjuaD0z/gwiEB4jFJRXD0CXLwZhIQWiEI71CRi9Zk3/79YXiAOKJwIewJFKA4ahFYAmtBZBJFM6TDK+pqQ+O8NXz2y2e8ecqbHSoS82fhkkvgkUdEMZkvvoCbbhLFXGQ5nIQXJAD/4ANxfIfRgWfRcwz4PoMDB6C8XARktzUONxZtDOmwCkpMgYs+iX1C30tIbCzaCMNuhHWXCLlj+VSYslYUSYwcj/4mBEQZJ0DuG+AsFe/LV8G8DEg/Tqy/xeEiTrKs8Oi9RVxzW1f8frGuvfMOnHSS0IVVqvD/FSvgqadgSfuWjl+Pf4IeueNhUdzCkA5TVgVkpojEKEkVO1f/SHLwPxOGVOh1lSD1VHyiWNC3h0HfmyD5CEGes/t5AFxNyJKbFqYIIiapDFEEpqXjm37u9HaQFD0S3aZB4fyWv9dY2VRdEDW3IwtaAHSP7x6SVRQUMbf/SBizwNgFGotg3+vCxhSJ1siZG/ZD8lguvxwWLvxjm/mnoPuFULm++e9Uekg54s9tTxtQFFFoyOuFf/8bpk8Xn7eUbN7S59WOaq74+gpyq3J5/eTXGd1l9B/T4E788xAqwCQ3L7v/XvJvJzrRid+E7dtFQc3CQlH48YEHhJ7vdoupK8tiTwmSB6vVsHWrsFl4vXDqqbBmDVgssXuJogjS0NRUYdv44IP22TGOOkr4zfbsEbaPY48V7WhJR/J6/4Jk2QnDhR23Yg1snwFZZ0R/3xJxMkDXgIGo6dr5exIXdKITnfhTUVJfwoaiDaH3siSjCthiFEUJEY4/veZp7pl4D1Kv6aI46aG5cPAU6HZ+OAYgWPSgbOVvLnhw992C+DmIDz6ATz4RxUirq4WdCloucFFYV0h+XT6jMkahirTFtqfwK0QX4oWY+Jhl+5cxdc5UJEli6UVLOaLb76RzxQ2ELqcJwpiWiLiBIm+0P6E5AvlEY/gztaymqL4ISRJ9e9ll0ceWlYm/SFQ0ZkHKUVC+EooWwM/3wtBHhX1OVovnbeoabT//i6GsTNj7srP/JgUs/0KoclRxwRcXsLt8N6+e9OofW8D0/wlev5f1BetDNurm/OtDU4eydP9S/IqfNflrePgCPy+8IAbTGWcIIrakpFhZMygDPv44DDvnG8obw0UlgiRrkiQRUdOB6xZcx4YrN4g4s4r1sO1+SD9e2L6C9tbfYZ2NLD5hUBua9ZFYtJaoghMjT/iFvu/0Z98+Udz+iCPg7bdh8GBxr4oiyOjWrYMnX2jANSRchLe5ggcgCogE2+L2hYv4SEiYNKaY4606a1SRhGrHH1/gwu6289rm19o8btrn09hx3Y4OnTvSvL9hgyh08HuTMKpUcNVVwt/09deikMLll7e8HgbHrcEAt94qClsE/ZNvvCH+1GpxXBAefREaWRMqeB659wSRaEiM8vsW1Rf9bvfYLvS+Gg590vL36tiCKn8Ubr1VFLgIYsUKUXiqd29RdCovT3we9Ll3ohP/WEQWb1ObYmOKfw/b7ME50HBA+EfGvCNk1qYErX92geNO/LEoLhZ/TT9rKQciPf0fWDGxE53oRCfaxpdfipizpCRR2K496LCu8k+IhepEJ/5icDhg/35RHMDlCvtKdTrxl5QE3br9sXkMTzwhbMvp6fDjj60X7FSp4LCeu5GXjhV5GcOeggG3t1x0DiBuiCAtbyb3sSXcfDO89ZbITX3jDWEH+cv5Zf8K2Pm4KG5h6S2KW0Db+lEHdaOXXxZFT5KTRYHyMWPEOG1awCIxUZBCH3PMbxuviqLw3Nrn+PfSfwOwrWwb+6v3M3PqTAwaw68/cSf+OPwJeet/e2z+F+x9WczVY74P2/2by7k2Z4MxM2YurytYx9i3xNydMWkG90y8JxyTXP0TuAN29T7XN9+GpnEfQRuO4kd4Jpsc+3vE1rlrhA/y4Bww9xQxKV3PBGt/YdeRNWL/8DmgZifU/CR8JX/B/I9O/AHwOiBnJuR/AY2FkHoEJIwCc3dQZ4q8Il8jeOqgaiPkfQyjX293saz/dRw8KAqFbdsmeD8MhmgfkiRBY6PI0Rs3TnB9DB4sjvtfQHW1yIH95htRVP6RR4SM05K86XQK/Tko49TVCTW3pETI8E6n8LtptUKGt1iEfygr6y8Yy/An7tuKovDW1re4cv6VgMgvfefUd7h02KW/6nyd+B9FU/9AW/xWnf6BTnSiE53oxF8B3kYoXgIVq6F6m9B7zd1BZRQ6jeIDnxtc5UJHjx8KiaMgcbTg9OksfNGJTnSiE53oRCf+pvifced+8skn3HzzzcycOZPx48fz2muvccIJJ/DLL7/QtRlj2oEDB5g6dSpXXnkls2fPZvXq1Vx33XUkJydz5plnArB27VrOPfdcHn74YU4//XTmzZvHOeecw6pVqxg9evSvum4nOtGJTvy/47c6JRS/cGz7vYFkXAUkjQhAkrWdjuW/K35NECp0BqL+CbDbBfFLVZUIRg4WMVCrhbNUp4NM3yHSjuyL1JHnp9PB559Hz/kW1gKfD979oRsPvCSSGO+4Ay64AHr2bN6Z63DA3r0wYMDvn7wZA0URBr2GA9CYL4JwFAkkv/gOAFnE4Hgb4MBsqNsFva+F7pfCoIEtB1i6qkFrZfa2j0LFLUCQDc7fGyYMzKvNo+fLPam8vRKtWsv8PfNZsj+aRdPbhMSz0lHJFV9dwXunvxf6bHvpdqZ9MY0dZeGk2Xu/v5cvd3/JB6d/QN+kvrjdInDzmWeEvfLGGwUxcf/+ophF1DW9Ikhhx44OBrtu+48gPc++TBS3gNgg038quWUn2g+/FxyFgiDaUQReJ+ALB71JKvGnSwBTDzBmgKZjScVev5fHVj7GA8sfiPp86odTuXL4lTwz+Rmseuvvd09/FDwNoq8cxcJRoXgCRWOkgAylAY1NBOjpU1pek34PNBZB0UJR4MdrF3NblyzIuiU5wKLiE9+5q0ATB6YuYO0HSeOhGSKCfyScZYIYtvpn8NQLGVefHCgMoQ70k1c8T3clqMyCHNfSG1ImgS6+3ZfKq8lj+vzpLNu/DAC7x86w14Zx38T7uO+I+9CpdVHHK4rCvN3zuHjexSEy+SGvDuGWMbcw48gZWHVWEdi35mIo/Aq6nA4TPhFzUFHE+FMUQsGpkhQec4q/Q7K8oihcMi+akTtIoBFJmrSjfAdLc5cyuefkdp/7V0EbBwPuFPtYzmuQNA6yp4UZ8poQhiRaqrj31Ed5cN4MHnlE4oILhPjTmuzi8fwJsk0H4fV7+XbftyFCkFGZo2KITCZ0nUB+bT4+xce6wnVUO6qJN7R/nEaiSxc491z49NNwYa1IqFRg7bUz9F6SJLrHxRZM6R7fPTRGZElmR9kOpvScEnNcm5BkGP48fHdk28fKekHw92vQ90ZR4KLlk7NHnYFaLsETkPuybLEFLpoWvdhTsadDBS6W5C4JFTNRUBiVMSrq+5EZI0Ov1bKaJblLOHPAmZxxBkycKEghg8+tuFg8x5Zw7rmCkP/nn5t/1kEoisI7W98JkWVbdVZO7Xtq6Ps1+WvYX70fBYXvD3xPjbOGOH0czz0ngmODePttmDtXyK2NjUJF9fkEAch3B76jxF4SOnbW1FmcPTBcsePkj05mXcE6FBSW7XiTOxNFgRWyzgisARFzorVg/C6ngqVn8zfqKA7/uWvA2kcEE7QDmZnCtFJVJZJMp3RgqPv9fq7+5mre3Ppm6DO9So/T5+SieRcxd+dcPjv7M7Tpx4PaLPbwHQ/B4Afbv6a7q9rfoI7AXRl+berWfEJVM8/i+SJQIePDj0lj4q1T3goV/NtYtJEnVz8JQL27nvl75nNqv1P5q8FshtdeE2SsIJK/vvxSJAkecYTQo7dsgTvvFPvKrypw0QFcfTU8/7ywLVx7LXz2WbhIZUtYX7gelawK6bJNC1wYNAYyrZkU1BXgU3ysPrQaTp8NeR9CyTKw58H83tDvVrE/qwNyZGN+9IVUerGOr5kW/szvbpGkf/pFFbz1cVe2bhXmzZNPhqlT4ZZbIC1NkN4F+/sfQyDUGpkH/PaA3Yo14n/CyOaJ1FpaN/8p5OCDHoADc0RhJPyiaMLmm2MOc7azwEVzn0tIaFrQ8zQqTRTZ3G8qcNH1LEGc17AfaI6cUmFz0eaoud03KbrAhVpW083WjdzqXPyKn/WFLRRc+L0ga2DEi7DyTFFsquBryDwpvIe1Rs6sjQPgtNOge3dhA1OaPCe1Go4//o+8gd8RXc+GTTcRxYwIIKmhyxmg/mtlFPn90NAg/nfpIv53JHFZURTmbJ/DxfMuDs2BMW+N4eoRV/P4MY//an2lE/9DSJscSIB1w54XRXGi9hZh/qPk39+JbLkTnfgn4frrhR5y2mlCHwqiKRFGJA47TBQJfPllMaXGjxfF604+WdgJ/H6xx1dVCcJhiwVKS+Hbb4Wd48wzW9d1fD64/37h5/z5Z0FEO3++KJYB4d/6fMKkWFsriDr+chj6CCybJGz9G66BUTMDZI/qsB3UVQG1u6LJk2t3Nu/z6ywK1IlO/DH4Ewg6n1/3fMg2C3DRkIswakQV4dzq3FDh4FpXLUtyl3Bcn5sg9y1BgLL2EnDXCuJoRQmvIZbev+ZuozBpkliTv/wybF92u4VNrDVUOap4fOXjPLP2GQAS9Am8d/p7nNj7xBCpfJuFXyG6EG8Eqh3V3Lr4Vt79+d1wW9+dxDUjr+HJY58UfrbfisEzoODLVg8plBNQy3Uhf0JzBPKRn0lIFNYXAoKE4eWX27bd+3zAmLdgwSDxZudjUL0Vhj4G8cPCBzrLWjrF/zvGjBGFUtauFft9YmInwVlbCOrbl355ach3ePyc4zl34Lm8cPwLpJnT/p9b+Pthe+l2HF4HIGxaQ1KGxBwzJHUIPxz8AY/fQ727HmPXXdx660Cef174oUaPFkXPLr00emzt3An33COW7NXZr4TWWb1az7kDzw2tR1uKtrC9bDsKCluKt5Bfm0/WkIfg+yngqoSlE2DSN5BwWJgA8DeuszXOmtBrk7b5+A2LzoLPH14gaj2VzJoFRx8t3m/eLJbIK68U/30+QVw3ezb0nxD2x8mS3GKBiyRjEvuq9gFE2TeNGmN4vY5skzYcL6SSVFQ5/iDdPAKvb349qqhGkjEp5G9qcDfQ4G4AYGf5TvZW7qVPYp92n3voUFH8dd48ob/s3Bku2tcSfk2swXXXCX9Tebnw9dTViVhBSRK2OEkKn3fNGuGDAlGI4e23BUFk5F4RWdwCwGssjHp+be1HGllDYV1hx27ityLlSLANFLpNU7u3pArHNv4JyM4Wvr3HHw/bohVFxMn+6WiPHarTBtWJPwrmnmDqDo2HYM8LkDKh/b9tt222DTKHTlvGPw+vvSaqM7UXDzwAM2b8Yc3pRCc68c+H3w+VlYKo0uEI52lJkpCvNRphvsvM/GuRf1osQga120WMpU73xxLi/2H4FfKsy5LE+oNd2bkA8vNF6qPJFNaNgqHibrd4punpMLRHDn1TtpAVl4vsqQlUPG/yQBVF5JnJGrD0EWTMcYNA0yQ5qxOdAJFXYj8ocqicpcI3p/gR+qos4p0kGa86jblLhvDp/BQOFag5/HAYOFAQ4Nps4s/vF+O4sBA2bYLp0//Y+RyMFz/uOOjVq+3j5ZJF4KkBWSeKW0D7i84ljhQk1o0F4CwBnwvwgz/ggJVUIGsYmJjMOacfzmdfmbjrLonBg4VvWJJi+d3ainf9R0MRhUlbJPv+HeI7//MfsRzecIOwy0PLPv3fOk6L6oo47/PzWHloJQAmjQm7x867P73LioMrmHPGHMZmNd/ujYUbeejHh9CpdMw4cgaDUgb9tsY0A0VRKG0oJcGY0GKM6P8c/leLX3UkdltRYO8s8br3tWDIjF3ImhafiMjHdngc3P/D/Ty79tnQ4TNWzOCzXZ8x+/TZosC3PiV8rro9It47cl1uzVaS+wb0u0XkiMrtmMTttd84K2DhYJHb3/8OGPaY8IVI6vD9R963p060YdtCULpFn6s1H7rPF7v4tBZH39HjodN2+kfAngffHS14HwbcDUMeFPEIPjcE19fg+PA6hb3R3Auqtnba9trA+vWiUNjWrSI279JLherUko+qtlbkN/0tdcffgPPPh6VL4dhjRcxBc0tDJPR64S996SVR3H7SJOFLHjRILBk6nZBH3W6hk+/aJfKybrhBfPeXwZ+4b5fUl3D515fz7b5vAUL5rpd9dRnzds/jzZPfJNmU3KFzduJ/FP+L/oHWON/gf0de8doFB0uQdwVFyLiSGtRGUFtweyT27oUDB0S31dUJfVVRwvbAoE0wKQn69IEePSAj4y+093UWDOxEJ/55KPgaNlwNPicMe1zwOahF3HbIZhy0gwaRlyccU7UuYKv4rLW1v3Mt6MTfDb+GB+HHH6M37DZ8hQ5zMou3ZLH1LeHjlSThbzEaw/5Cn0/IBZWV4pI+nyg+DgE3oQri46P9ED6fKJLo9wueigEDYNgwwavZiU50ohOdiMX/TDrPc889xxVXXMH06dMBeOGFF1i8eDGzZs3i8ccfjzn+1VdfpWvXrrzwwgsA9O/fn02bNvHMM8+ECly88MILTJ48mbvvvhuAu+++mxUrVvDCCy/w0Ucf/arrdqITnfgDoSgicMZVJRydXjsB9tmwZYrAn9oAmgRBgqS14fHKNDSIoES/P0xYIMviT6cTgW9/+yTJjjolbMAENdw4BeK7gilbOMINaYI4UdYAkiCQ8TaAo0QQ/TbmiyAkQ6ZILlIbwqRUihLIO5AIGRi1CaBPFefW2DqrTP5e6IjiV1wcywDWBvxI7PP3Im+lnlIluvBCMEAUwsqf3y+UQosFUlIE8VXy39Ev5SiFirXQkCveS2phVFIbiEmq8bnE/FAZBHm4PlWQhJuzWzx9QwO88opI9I+PhxNPFIpv167ifbB/gwp1aSnk/AwdTkF2ueCkk9p16FKOYzqLAIWDByW6dWv9eIMBhgz5g6eytxF+vhcOfggJw6HP9ZA0VqxPQSNfZACMPR/WXgTeehEQMeyxiL0hgCBhbfC1u4ZDkpVrF1zbZnMa3A3cvvR2Hj3mUW5YeEPoc5PGxMSuE0PJuzvKdpBfJwg952yfw23jbmNQyiBO/uhkFuYsbPbcG4s20u+Vfpw36DyG5nzI3XdLxMeLZ99a4qtaLQJPe/ToYCCnKVsQ4tTvEUFFyNHBS/9Ucst/SuLnH02UcvAj2PtfMacG3QsJIyD1aNAFGJ6i5l0e1O0FtQVsfVs+ZzPYV7WP3i+3nNT/xpY3eGPLGyy5cMkfT5r/a1DyPeTMhIr1ghQmYYQgKdCnBopJqERfOUpFkHvNdvCPBWPmH9embf+BHQ+DpRdMWS+Kj4AoaKH4ASXw/KoEkYmn9n+zeM2el2HzTeJZHb85/EwUX+AP0U/uykA/1f2qfvIrfk6Yc0KIWKgpHln5CI+sfITXTnyNq0ZeBcDS3KWc8vEpzZLePr/ueZ5f9zwXD7mYdw8/F6nwK/HFyJdEcQsIWNkDQYDN7HkdIWsHeGvrWxyqOxR6f+HgCxmWNix0f0+ufpIqRxUSEld/czU7r9uJQfMHZ3r1uwVKv4PSFbDmAihdDv1uFpXsQRCG2MLr+J0nP8knO+5ib66BkSPh9dcF4Z7fH06ECP6XZVi1Co46qoNt+oNJqdfkrwmRb6hlNeOzxsccMyZzDHO2zQHEs1mSu4RzB53bkbuIwnPPCeI/uz32O58Pxp++gzU7BNGL1++le3wzBS4iil4EC1z8aqROgm7nQd5cmidzlsXYnjBXjIFfA0svQYC9/QFiSIcD2K3phsdfEHrftJgFiKIXQUJpCYm9lXs7tI8tzFkYImJRy2oGpw6O+j7NnEaqKZVSeylev5cFOQtQFAVZlvjoIxFYWVcnxnVziBSNJUnoJRMnRut3TbFo3yI2l2wGxLN8YNID3Dr21tD3qw6tYuI7EwFweB28uO5FHjjyAfr1E8QqF18cPldDgyCAiYRKBc+tfS4U6KiW1UwbMi2KaOyiIRexrmAdAKury7Cnp2DyVELOLPHs/b5Y8sbmUL5SJKCp9LGJWDmvwY7IYDkZjpgn5GVfY6AAqCQ+j4KCTvHx2UuZHH3hFF59Ffr2lfjXv1omsgl+7vK6GPrqUPZU7on63ukL7wPz984n5ZkU8m7Ow3b466JIwM7HQZsoSH6DgRBNivxEoTlC+98DaZPB2FUUQ9tyCxz+WpjAqQXsdsPXdlDwo5bVXDz04qj16uS+JzNr4yzq3HWoJBWPrnyUU/qe0ixZ0v83TjkF/v1vUZwQRGLtBRfEHvdnFGEwGuHNN+GEE4St4fTT4dVXITVVjLegvdPrFWPP7Ya1+WtD65VRYyTDkhFz3oHJAymsE+RHebV5VDmrSRg7GxaPErZBr13In788JWQrv0skdjZF9vlQvAgOzg7IpS1A1qMyJvHJJyJYvLpatHnhQvHXFH9KIGJTPfKPILHuaLAudCxgN2MqFC8WhS7qdovkkPasmX8UOfifDX0SHPE5fHdsq4e5muyDGlXza1mzBS4kqd0FMX5TgQtZDYc9BSvPiP1OUkHWmaz94d3Q3DaoDaSbY/eAgckDQ8WpShpKKG0oJdWc+uvb1Ra6nC4KOBTME20fcCcMvFcE9hnSYep2oX/V74vewwL7l0oFd98NV10Ve2qvVyTu/C2gTwnMx0UBuSIAxQs9Lv1/a1ZLUKlE0aSXX4Znn4UzzhD7SntI/BbsXcBpn5wWUxAY4LXNr/Ha5tc4b+B5fHjmh3/JPb4TfxHY+sGIl2DjNfDTXcLP2OOScJLs/4f8C7+JbLkTnfgnIlg0ojJQ/7C9xCPBgpsrV8Lu3UK/GjxYEPIajUK/+uwzEfIwfLgQwWfPhvPOE2Sj998vfJVud/icWq2wWy1cCNOmCfvDY48Je1/PnnDRRUKe6NVLtHP3bqE37dwp2vGXQ8oRMPAeQVa+7zWo3QED74O0Y8ME9aaugZiZCOx7HRJHQ8/L29TRgX+O3N+JTvx/4Q9OwK1orOClDS+hoKCSVBzX8zjePe3d0Pcur4uUZ1Kocwlb2v0/3M+U6euRJn0D3x0lYlk2XQ+/PA69rxNFD2QNFC9tf5tbweuvi3W2oqLlQgxBkb/cXs45n57DirwVUUTbVc4qTv7oZBINidwz8Z4o23NHcd2C65i1aVaz37266VVe3fQqd4y7gycnP/mrrwFA/FDRnzmzaN6fIFOkzcSv1IY+aYtQ3Ov3UlRfJH4tiz1q3LiWbfeyHCi0bO4O4z+GH08TbSn6VvwljBR6qKdW+LP/LNTlCL23YT9o4wOxVAbQWAMxKTIQSPDz2rnndCeL5p3Lxh2pnHKKzNdfizgzRYm1/Xm9YX/e/yq+2/8dx80+LorQP4hPdn7CJzs/4biex7HwgoXI7S2Q/RfG6vzVocITHr+HgSkDY44ZmDIQj98T9ZvHHx/I1q0iNy4/XxR5ePRRGDtWcHfs3w8rVojj+x2zgUW5iwBByHHLmFt47JjHQufbW7mXvv8Nx8I8vupxZp44E0b+V6yvjiJYNBxSj4Je1wh/vN8D+V/8qntWFIVaV3jtiCwaEQmrzhpaS9WymipHFUcdBQ89JMjqQKzLr74a+1uvLmzDV0kqEgwJzV4j2dh80GdrRTeCkCWZamd1s8f9Xqh11vLgigdD1xufNZ4fL/sx9H25vZyM5zLw+r2oJTV3LbuLL87t2HN5+WX47jsxjsaOhQ8+EHpL5HoU3P9UKkE4NKEDHPAgYmwXLBCFK5xOuO024Xe65hoYMULY4nJyYNYsEeMeLCRlNgsdKVjwojnIMrj1hVE2urb2IwUltB/9aZAk6H87rLu0uS8h688rcAFCXFuwQOiKTQuGBPGnEWW0ZYdqpw3K7/cj/y9voJ3oOFQ6mPg5LD4c8ufB1ttFETWk6NgEV4UotLk2IiikvbbZ7AsCMap5sO4SGDenfXYM6LRl/F1x9dXCCBhEW7HbHSwO2WEofiHL2fPDpMx+TziWPjL/IBjjoIkTMbn6FNCng6Z5uagTnfgnod5VT15tHl1tXX+foqF/MFasgHfeEUSVZ54pYil79hRFLPR6Iccpgby42looKxNFzv5wdCD348pRMu/1H8jOPRrOOgu++kr4NFrKKfJ6f0Ue7J+VU9MBefbtt0UhP40GvvlGFAJotYBgXQ7KqrORan6GhEdFrpnGFn1MDDG/Ikh1k8d07D468c+H3ydihw/MFvJs33+JHMbUI8MFU5rkUJ00rR+LV2Vw4omi0CgIv6VGE5tnGcy37WhRzI5iwgRBgrx6NVRVidzeVq8ZfxihnPHS5ZAyMZqQrTUidWt/6P9vcY7Uo8N5S5H91LAfqn/i+QdMbN0xmtxc4Qu+7Tbhs+3RI/qUu3fD11/DXXf9hk74u6L39ZD3MVRvg93Pi3wZv7ftGM8O6Ebdu8O2bfDTT2I8NmeD/z2wpWgLI94YEfWZ3RP2Zx+oOcC4t8fx6omvcvXIqwERT/noj4/y/rb3OVQbzl36fNfn9E/qz0VDL+L2cbeLwrYdzduJyNnZUrSFuTvn8uSasI/o1L6ncsVhVzCl5xR06ljm6gZ3A6sOreLtLW+joHD5YZczoeuEKFvoXx05lTl89stn3PP9PagCc/y/U//LqX1PJd3yB+tdEfj5ZzH+CgtFbEew4FiQMDzoD1MUYSf1esV3RqPgKBg+XOTd/67oqJ/3ESBbgrIVYq/w+8M6ZCtr5rtd7uWyHx5t9pQ7ynYw7LVhDEkdwqYrN6Hp/2/Y9azIkZ+yFkyBJP+2fD7OClh+ovAZmrOFfhtlv/lFnDOI9tpv7AeEzgzQ9Wzxv62iGxXAv4Gw66ZtqFQtO5ubg1rdsvG2JfxVi7IoCvgcInfVUy/25aAvFQLFtVSiIJXGInyuLRVE+rNRtkrs9wAD7w7LEZHFLToL2P4qnHEGFBUJuShYkLu1UGubreXv/smoqxP/EwKiaFuyzZw5Qu01GCA3XZIvhwABAABJREFUV4gIbnfLRb/69w9zUXUI/xCS8+/3f88xHxwT9VlknMLXe74mZU8KP176IxO7TQx97vF5WJ2/mre3vs3cnXPxK34ePPJBTu9/On0T+3bmDfwT8Gty6U87LewfaE9OXkf9A39wfn+H8WsK0cBfV15pLxzFwrZS+n2Ah66fyDs2ZgoeGlkNSELm8TVSW1LCTfcPZO632Zx2uoabb4Zjj1UwGFpeJ/LzhR3ms8/Ca7hKJdZ2WY5w6yjie7dbfKdWi+W2d+/oodbsbTjg4EHxGGtqxDn8/vA+E1l0w+sFS/UhTr2jLyrP/1jBwAAURXAG1NcLPoqgHcwfSHlXqcSzMRpFzoHZ/L8d+9eJvxE23yT04X63Qu9ror8LFEEOcfk4iuHAPjj2DnC5mz9fc/grrwWKIrgCPPUiV0XxRhT2kMO6qsoodFWVoZNL9H8BfwQPQoSvcP58UcjQ6xXFDCcG1AxFEftLJM+pLIu956ijhF/k5pvhiSfCtkZFCdvBg8dHygn/a8N1507RpwcOCB3aZArvzcG9Orh/19dDY6P43O0WMf1Dh/45XCmd6EQn/jr4u1Oxtwtut5vNmzdzVxPv9JQpU1izZk2zv1m7di1TpkyJ+uy4447jrbfewuPxoNFoWLt2LbfcckvMMcGiGL/mur8HnE4ny1YvwK8ouFUOjFoTerUOnUqHpIDb78Hpc+L0udCrtGhVOqTKNLx2FYriw2zRkJadgdQs6R+ARFW1QlmJG4/bR1ycisQkNUZTyxqgzy+zZ6+M1+1Fr/djjZNJSRbpQ7GJehJ+ZCoOFeGsdyBrNNgSjSQmya1u7CWFDn7a4sbt9NJ9QCpGsxGNPmARjrxExDkO5atx2N1o1W6Sk/x0721AUnwgNWmTIqFIKsqL7NTVelEkHXHxKlJSW1d8GxoUigpcuBxeLFZISNRjtukC9x0LBRm1Yw9ej4Ii61DpTMTHa/F4QVGkEMGgEHgUVDJUVss0NEioJC86gwZ0yciSB/AhKX4EeaOMIsmAmsZGhar8Q3g8EJ+sxWaVMbYRG5uTq6XR7kWWJUwWHWld45EUFyj+wDhRAtdQgaSm7pccfAf24fdDfKIWixk01eXI9cLS77dY8Uey1ituFKuDWrUNv2xCb0nAFB+PghSTZClJgOLnqustFBRpmXKChgsvNqAoUpQQ2BQZe6YQ7/oO0o+DoxbFHtCEwHXZokYmXzICSRJGqszMdjiw6/exfk0js2apsCVoufEmCZtVCjnGI+9BlhXs1TU49uxBV1OGKc4KGjNIWuRy0VdN+8nrk9hl74pDb0FnUGG2GUlOM4LiiXjWEHrekobSQ6U4GxyoNTJxCVqSYvOLotD4Sw49fb4YusWWoFwC0mgv1K+D4xY0f1Cwb32NgAybA8TuQ5+AgXe2fDyAq5xDh3LZXnYIpy4ZtUEQa+lVerSyBgVC65nD68CqNSMhk5ebS4Wjii3ubTTKThplJ7XuOjSyGrWsxqaxYtNaGRDXn0Hx/Ymrs6Cyi+cUl2LFlpyArGp5i6yqqSLvUC5uh4+MtBSSElMxmGMnUp27HpffhV/x4zpYj9flQ2fUY0kwY01qPrkviJIyFZXlMm63F7NVQ3KXFHQaNy3NbQXQuPNwu0HWaDEYVBj0Ej5/9BgMjj+NGjz3P0TSex+02o5I5E27lJqhh+H1+rElWbBVVZB8d/QeV/XU03h7iPKCT3/Sm2c+HUTmnVBQ0NwZY3Fg2148TidqVLgrNRRWtn687KlEdpfjaHSjMdqwpabixyiKafilEBGKSlaEQiTZ2f7LTvB7sVjjSbBkCGNHEzR4GnAESEFripNwNKgABYNZQ0aPLkj+RiTFi6R4AT+KpAbUKLKWzB2TMbq3Q88rYPSbsY1uMsZ9DeUc/MmD2qFHq7OjUm8Ftra4Fnz2YxZ3vTQSEEmHbSlwKSlQk2rhwCdfoqqpwWAShWfU+3NJuOP20HGRz04qKyPxphuRve2LBOnBfuKlKmqJY+FCuPZa0fdeb6xzNvi5o66W0v15AJgsunZp77v3anE6PKg1MiariZSuaaD4kPxOJMUJioIi61FkPYb6DWTtfUGQVR3+OpiaEAg3E+Dg8anQqEApX4vkqhSE/JEFHJqQ1tb54OgDGuwBUjm1pOaDI96giylMQP/Szpl8lvcVCgovbXiJlTuXk2/PD33/4sgnOb5rmLS41FHGuG+OweV3oygKZ75zOhaVia2N29vsn493fMzO4t5I0oM4nQo7d8oMGxaOt2kafB58FoX5+ykuygMJUuOT0Ktig+oURaHCJSakor+JLnItyeXL8X83BXnYI6J4SDDYyR8bELShNBPv2vWoUzxk2FKbdSK7fW5qPXUoioKz0gG1HlxOD0mZCZjjbGj0se0KwuOBnP1aXI0edAYVljgziakGJMUTkFd8gISCMHYqkpayvGKcdgdanYw1ru09sq6ilpqyClwO0SajzYpZbyQl4pgyvRGP0QyAz+ujcPNO3Kt/xmwzYY43Y46Pa/UaZYdKsNc2IEsy1iQz8anJrc+Ngq9JL7sHRZuCPOV7MAbHeWDRd5aI4lIo4CgDTw2VMxaQNPvz1m82Ajsvvp+CUy7F6/ZgsUBqt2RUsj8gzwZlD1EgTAG6b7salVIvCIp7NWGPbCGwaG1RN5T+96JPHkCqtfkkd4fXQUOAaGnxrmU8lPNEu9o/dfYJ3N7vfo7UXYzT7sFk0WBNshEXr0FSPEL2xy/aLwlSDEU2ULzvAG6nB4NJjS1O3aYcWFoqU1mu4HE3YrHKJGUko9XLzcr9ChJddl6FzpMLg2fAoPtiT2g/BN8MiOqr+UXpFHS5kA+rVlPhrqDSWUWVqxqL1ozD6yRJn0iiLoEh8QOZmnUc1CkcqMjly8pv2eXaS4MvlmleJ+tI1CfwrwHXcXnjpyQBSvxwpFBxC79wDgQLbiwYHNWmraWZOPo8gDqhD+lxqc0SXbh8buo8Qg9wV7nxVTsi5rYVjb7lwDivx0vRvjzcDi+WBDPmOIuQm1tBycFiHHUNyGoV1gQz8WkprR5fV1lHTWk5LoeHxIx4THE2dIaW2xR3YCkmQLH0QYosbhHZTwuj++lgeTfqhn6FnDRU7IuKD9kvnDHBMaggfq9IGnYU/cJ9W67kl8ZtrbYd4OoFV7Nm9wqqq6r4uroZPacJ3t/2PnvyVrIgtReJyj782x9BHvEsqE0ikD2g25HzKux4KPS7eoeJskNpqLP+jSEuJbQ2tSSvFHsquWmvkPslJLoYMni03z2oIgoiaQcr3LzhThQUDtQc4Jo3H+CClGtD8m9Kt0zUGhWS4grs9R4USSv2ekmL0+6gKi+3w7qts+Fl+stP0M0/GyX3HaTcN8DSRxTekzWCuDkAvdbF+i8Wcv1DR/PB3HjOPluhWzeJ446DMWOE4b2xEdatg8WLITWxkdmvCflGpTEgya3bMQCkhx4g86N323x2QZRbEyk4Zxp1R08mMT2ehJJCmlKKlx3IC+1HH25+DxkZP368fi9Z9iQKd++NOr6HNz1EYqKSVCxe/BWZv5hRadRY480kV5bRdCZFXkP2ViG7ykIyeXx6Cs88nMa1t6YixpToBElSuOzCOmpYgyzJocA0c506pk3aCDnU6/eS9/NeVrkWhOZ2SmV5q22qrpEpLhE2H0uclvikl+lrOoTevj4gFwgoqFBkI8XdZmPfWQPUoDNoUGtUaA7kRe/zEecHKChUU10j9nyTWUNa9zvJNs5H17gldI3g3Vem38fPG98O/VYjqXEdqqJQiiZn0deEX8tI/LRiDV/utaA3GeiS1IX45ESaotZdh9vvpt7TwIbCMNFUL2N3yvbkIkUWIgOGxQ1mqb0cP35qGwrZsvpVEpVkNAYLn76VxTlX9KWuXsbnix28J0xugJq8wLqnZswANR+8ZuH8K9KRZQW/P/I3CtPOruOORXeExiDAMYaxUc87W0kmy9SFfHsBfsXPf9c8yQXG3qhdWo7qb+ax+/pz32NdA0X8otukUinoMnbx7b5vA30mMyl1AvUHSqinJHTcGPWQ0GuXInNKbl/mda3AeuA9/I4S5P63iCQpWdMkGH8XrL0Qp1tLo9tIAttRlkxAGnw/ZJ4YTj4DUbDK0juCHNcPP54Kx64QpJJNEdQLXeXgrGDSiFy+eHU1V907mltuUfPuu3DZZRITJ4pkWY1GOFD37hWkbz+sz2PHoJPYUxsubpFpzMAa0G8bvY3kBfSOWlctQ18ZwuPdZ9Nf9RwDfQ+g3nIr5LyK1PVMSDlSFPpR6QKFGZugPkcUMQWcTgm3W8LjBa9XQqUS9gW1WkGn9bJ/+0Hwe9FbTKj0FjQHClqdRyWG2fRpvBzLvtfx1+1D7nczpB8r+rYZ0uFHyjRIeFAQa8MU68SY9ePELsfx6YEv8Co+NhZu5P33XqG7rhtGqwlLvBlzQlzsPUagcH8lNZVO/MjYkuKwpSSiasUA3FhbT21JEU6Hk+QMG7ZEEwZz6wWb1I49uB1ubjxTh69+MM+/1g2VSokZ47IsVpHi3ALqK6uQZQmDWRezPjXt28b6RioKinE1eohPsWGKt2LNa31NG5q8j89mGrnhgcP56isDS5bA+PFiz+vZUziTi4sFGVNRZR17J4b7vbupG0V7cmLus6sqHZWkwqt4wW3g9Q9XMMAwkCTjOwxV34TJsx0FCcnvgsZwYllw7dxdPAR3TjoqM2jjZpJurcRUuzBGxlZQ4Ysbjnr0THDX0D2uhjWLLRx9chcKi9VN1qZw3ybY7OzdIBIjDEYtslpuc+0vyi3AZXeg1qqxxFuIS21dkawpr6GurDIk/ybI6th9O0KPrKvzMfM/Lvze3Yw+Ip70LCMajSoke0Xa94LwphyF+9/dcbsgOU1LX3UhSXfeHnWNSJtPTb2TaiQcc74O6batyb8+3/E4tffQy/UE0pKJMOAOpO4XgCFwJ83M1e1l6dRvK0eVt5wkW2KzdgaH10mDVxTh8tR58VbYhUyeHo/JZsN8sPVn8cseLW6HB41WhTnORFKXcIEFydeAhB+/bAl1VuWhQzjqapBkiYQkHWmleTQtyRB5jfoGmfxCNY4GN2Zrd7qnzCS77AaERhdt91AAu64rfgoh8F1tQSmF7uj1CUDyxPrdFL9CQ2kV+Tt+QW5ivHFU1OAPOIZMHhPla/ezfNfXxKfYMMZbsLUxt/fu0+Kwe1GpJYxWPaldTyPTMhlj/XchH6CCGp8qgVz1+eytvCf022xT12bndqacEprbegnWr57JENNg1Doz5oR44pKFAq0oUFsro9MpGAzhebtx63Y8jkbUWg3J8RloDbFleSNts/YaM/bKJ+lGBn2UmbDzKaRdz4oiZslHCL+KtxEKm1Syqc8RgW6SzMWnSbz9Rhc2btFHrLUKN15dQ8/UOg5ud+N2OFBrVOgMmjbX2aZz2xxnxdjK+uFxeyjOPRSl28YV5rf67PLyNdTW+lH8Ckazhoxe3dAkvki34oFIeAPlwVXUx59JSf1k3EVVaH3CCG+yijnd2prm9/kp2HsAt9OLySb2yPiiwlbbFLRbSRLYkqyktKEn3DG9DldlPG981INRIxVuvEnmootE0mhTNDbCj2scvJ13IZ8WtE0W+PHOj9l0aANPdnuQVH9CyLcTl5IYI/9GQvI1oHIV4LC70RgsWJISscRbcbkk8ecW8o1ep6DTKcKeWp8jiIlkrfAlBBI0/X5oaJDx+cBq9YeCzvfkHKSyohxZpZAYl4rRlCls1BGItJVoFDdJSh0Ouxu1wYwlMQFbYhyKAvX1Mi63hCwrmIwKer2YS7nbD+FzOdEYdGhNZlG8rBVUFlfSUFmNx+sjMS0eS2I86laYCJyNLsryCnA5vMQlWTDZLBhtrSdX5x7Q0FDvEwHkZj1pPQIPWlGQ/HYkxY1fZQslIlZUQHm5sE9braIAil6nICnugA3AFWED0OFxeSjP3Y3HC3EJWqw2GbO5lQYBBw5OJk5+mH7+x1Ctuxz2vICUdZYgkrD2FQmbEUQlFfUJlNelwM+1GNOLWz5xAF4v5OSqcTr96A0ytngDialmUBRkf72QcQC/rEeRzSBJlB/Yj7OhIeS3TS9tfb0pLSujuPgQLqeXjIxUUhLT0Rlj9+0KZyUKCj6vj5LcfNxuLxabhaykzGbl38h1tiy/DGeDHUmCzJR0UtIzkJrY+CLHbENNA7VlFbgcXjIzUklOSENnipV/q13VeAN6f90BCY/Li86owWwzE58aHLOxcSIABw/upbq6AmSZrOR0UtNsMXPb6/dS7a4BoL62gZrScjwBv21yYhp6szGmTUH92eP3UlvQBbfDj0otYbIaSOmaHrDVBexQiHgNRdKhSFpKyySqqoReZrFARkaA0EPxI/kbkf0O/LIRRTaCJCH57GhcuYKIRK8lPk4mLk6sHXV1Mm6PmNtGg4LRKPphw+ZteF0ONHodGQlZzc5tp89Fvade9HFJNfaaGjxeH1npmSSnpMXMbb/ip9IliClcjU5KCwrxOhVSk5NISUhtdm4Hx4fX78Nd0Ijf6UWtVWONt2JLbX29qSmroa68EpfbQ1J6AuZ4Gxpdy76dJ+7xUVWSzIoVSZxyip/HH5cZGOAdDiapQHTQq2zfh9bbyII5as6b3pVvFplRqxW2b5fYHuVKU8S4TizjvRdKGdA9mf88nsZTT8Hzz8NRR0lMmiSSdJ1OQVi1eDH06eXhlIm7eOQ2SDancNu9qdTWwIsvSrz4YtM7UBgxAvJ3HcRRX49KLaM3tpC1Gon8z0kvn4GiSxO+naBsHZwTjuJwkr+jDMVVTc4BE0rlBnQaF3L8QNSZxzR76iCE3eoKMiQDg5SHkcrXwfITkLQJotinyiBIS8rXogB1jVaqG5PpklKDav10ODAbqdd0SJ4QbSup/gnWXwHA3uJesNuDtvIXNNq2ww8PHNxPdXUligKZaWmkpKbHxGR4/B5q3IKUWet3kUh9xL6dgDVBrNs+n7D/6bQKFkt4Ldm3LQ+/24XWoENjsogCR62gsriChooavD6FhDQb1sQEVJqW78Vpd1J2qBCXw0NckhVTnBWjtfUNqTDnEK5GJxq9DmuCGVsz9r1IlJWrKC+XcTk9WGxaEjLT0AfXfr8b2V8vdB1ZjDWXSwSLezzCXh0fH06+RvEi++pAUuOXzSFfbum+vbgdTnR6FVabhsQ2fKQVlSrKylQ4HG6sNi0J6anozYbAGmhH9jtRJC1+lVns9X4PWucuPG5QaTXYbCoSA7dtt0s4nCK+K1K+wX5IJLIgg8YYJtsAXC4Ju10iPt4f0ofzC0vIP1QAipe4xGRspkyQo/fIyL3C54Oq/AxcTg86nQpzvJnEjMAurCiBfpLwq8I+qPx8EWQPIhC/a9ewPi75XUh+O35VXKhfG6qqqSvOx+OB5DQdVquErg1uiOKs3siPPo/epMdgMWKrLGsxhgOg2Kui/tOFIEFcUtvy70MbnsDlFTKJT/Ex1XZUjC3t9KyTmZ37MT7Fx8aijTz17jwGGQeTIM9hpH86GqpQGouQfr4n6nchy7+kA2c5VG8X9sUA/H5obJRwuiSMBqEXShIiWakxH3xuEtRmlszNZPJZ/amqUuFtxiY99YQqbv34QZ7f81KrfVnpqOS2Jbfx/sZ3uSfrNrp4k0NzO7G0hKYpxZEy16GqAu5afx8/1q1t9RoAT615ij0FO7nRNh2tRy3mdryZpPKSVuW68goVZWXhuZ2Y8Ti9TD8167NwGQawtzYuKrnfU1RHYU30s3NHkDopKLgrdlC4fh4+v0wXg5mP3+7P2ZekB/bQcN+qVAoTxjq4/rIqtm3rApxMco85pB68SsRC4YOqTVHXUgCXR2ZLeS/Ysh9TvIskU/PrWVDmAig9WIKrsRFZpaJLSjrJ6bFFciNlzb57L8DgPQi9r4XB/4k9eZN4K42qjK/e2sA1MyYx75s4+vRRuPBCiSlTYPx4QjEgZWWCmO2XX+CSMw/SWFeHrJIxmNret+urG6guKcXVGLZb6UytT+5Du3LxuLwYzUbM8RYSSlrXt/cfyKWmpgpFgS5p6aSkpcfM7cg9Uqe4SFDqo3Rba4I1kPQr4XTJqFUKJpMfrRZcXjfTv7iX2YVft3m/i3MX0+2Zrjzb8xEyfSn4FYX4FBtJZSU0teBE3kdtXR0HDu7F5fCSlppMclIqxmaUtsjxUZiTj9flRm8wkJWaiS0pdkxFjo+qkioaa2rxeH1kpqeTmpKJusm+Hbn2z986L1TgAsBSqqJQEz2PUhrD8rBKUrFzx6eUeZKYeZ+Omx4czdIfk1CrFA4elDh4MPw7SVJQFKgaHPaB+RQfJ1gnRa2zJmB44lB+qtyOT/Hx2vp3GV9/GTb/ZLprn6K/+x5hoyv9Aan0h6i2BdfZgv3Z+L7YgMqYi1Yn7jfoo4foWOx6XyP+iCLRWo+Kgz9ti4nJcJfXhe9bUfAWbODQ6s+5ZIqBhvJBPPVy12Z9FmqVgs8Y1pcVRUFt98fsLQB6tzpUnD4SWp+a/Vu3xdiknaU1odd+n8L29T6+Kc9Bq1NhiTORmBlp/20U11eF9b6KgwdxNtShUgt9OzGx9XCrhzY8QZ0r0IeKn7OSToq5j6mZx7GgYBFexcu83fOY896rZOkyMZqNmOIsWJPiWr4AoHIXs+R9J9ffN5wNPyczcoTCqMMlJk8WeZUGgyDFXbNGJADajHW89dJBAExmHchSmz4LtSOHFJeLT19J5JLbxlJeqaW0VOGBB5revMKI4UBjEbgqAYkJQ3S8/5qFS69NCyRlRuwVsoJGoxDfdR91ESFezkNVFKoaos7sbQiPJ6/fS92OMlY6vkGr12FJMJNU1voe2dRulVha3Oq+7XRJ7D+owWn3YDSpsSTaiEs6nyzTa+jtG6L21Yr0+7GXJeOvDcQka1Xo9G3bf2VPJZKrDKfDg8ZoIyEzFUNAJne7oa5exmyKkGX9bkHE5fOgVRv45r1UJp8ziJxcbcw8kiSFMaOc5O0oxNXY2G6bdG1FDbWlYZu0yWZF24pvJzLeyhxvwhxnIb6odb/tjztXsr1yB+9UfEiFtzJk14mERtKQbenKDf2vpo/cE1uDIRxvZbM1a7cKQlFg114tLocndm4rCpK/AQklyrezP3cbDXWVyLJEl5REMlJ0MXM7cq/w1HvwVjTiavSQkBaPOc7arN0qEkG/LSodeouN5Ah/U12djN8PNltYFxEEx9XihtRmCNh/vV5hL3Z7pICu6hcJ0dV2ig+UgN+DKc4GWquI0Wq1TTl4nC4USYPWZCG1m5ChRCJw2CYdcik5S8FVJeJ2NRYwZoCswecLt0mrCbeppqaeX3bvAb8XW1wicaZ04Wtpghp3bagQlCOvHq/T0wHd1opX/R4DPbdj3PUMSt5cpO4XQfJESBwhYrPVJqhYB0CDS8PWikxU67cRn6ZgNTRvjw7arXyKD6f8FoOU67Ad/BB/zW7kfjdBxgmieEAz/svyukSq7fGw24OpPnbvagq3G/Yd0OKye9AbVVgSbMSnJYZ0SEkRMo1fNqCoAnL//lycdjtanQprnKZ9McmlFe2e2z6vj7L1W5BKyjFY9BitJowWc4vxewBFHokGlTYck9xGLKXkrUXlLqaxwY1fHYcxPgmtwYy/hXwUGT8/79iMWuXBaDaRFp8lCjk0Qb2nAWfAJh3nr0PrdeLxKKj1ZtK6d0GlVgWISCUaHRIWsz+Uf1Bbaac0LziP4kFnQdNK7DZA/rptuF2bMJgNmOMsWJNaDwDen7efmqpK/IpCdnoWCSnJMXaryDj6tPwXSaufK2JtTtwZe8ImugvOCvblKvgNZrQ6NxpdYavtAZDdpUiuKpwuHxqDheSsdLR6LR6PWAu8PgmNWsxttRoa650Ur9uOurwMncWErDaB2tjq+Njd2JUGnS2UJ5ianYnkdwRi7z1I+FEkTcBfo2Nf/k72l2zjl4btVKoLccn1NHjrhX9C8WHRmLFqLFi1Vo5JPxKzYsZWpcPt8GIN+JtMbfib9h/U0FAvchSNFh3p3bs00yZ1oF16CkoOUl12CJ9XJjsziZQEXQwZt6IoVLur8Sl+6hsb2HtgFyX2MvYoubjUbpySiwavHRkZvUqHOXAfgxIG0N2cja62H95GQ5TfFgjY6uxIihdF1oX2sOpqKC0V64jNJnRTk4mQz0z2O6JsaT6fKErm8QguGptN5P8ASL56YXtDEj6zwHpTu3kDSuEBVCoJi1VDXFzLegJAvd1FhR8cGmO7dVt1427cTg+odBisNpIC+3Zjo5inAAa9gskkFobvtq5jdcFGXsr7gEpPbYvntWjM3DX4Vg5P6MtggzlGt/X5wOGQcDiFbms0Kmi1wq6U89MBFK8HrVGPxmgRxTFbgewuAVcVbrcftd5CSnYmarUat1vC4ZBC+7bBIObReed0p6RMwxlnwMMPt3pqkpNFQeylKxfi83jwqXzEG20Y1QY0sgZJkvD5fbj9bho8DbgVLxpZTe+CN8h0zhN2+slrw6TGQTTJbXXUVNL4xDckzv609QYFYAY+v+Y6pmlm8O23yQzo7+f6G2ROPFHEf0WGwFVWCn3kh4UlXH/yTtQVFSFbSWvjyeX2UeTy4dQasSaaMcVZiWtjXS7avg/Xuu0i3irOTFxa8/kiQXQ0JuODd9KprbVw5pkKo0eHY6xa0guVirWiuIXGBr2ubr64RZOcl6qGeAqqusCYD9BnDA2cyCdsxYobSXEH1ictiqTF51exa8cKvD6JeJuBLokJWJshjg3myCiKgqvEibfBFYrJiEtNivHbRqK2TqawWMQ2WWxabMmJWGxqJL8bCOY7yoF2qVFkE5t/WoTKb8Bi0dI1KYm4uNhOsnvsNPocePxe3KVOaPC2OyajuqaavEO5uBxe0tNSSGnBbxspaxbuzcPr9mI0muiSktnsvh0p9+ce2s/u8l18XjmfXE8edV7xeZQdSG0mzZjKTf2vpYucgbrGj9vhIz01maQW7FbBHGBFUXDmNeB1eUK6bWvyr9qxh9RdDwMSTPoa4gY16dDY8eStXgJkI8siNziI5sZs8LNQvm1At20LNWU11JZV4PH4SEyPb9Nve9t0Nw0lRt6e24OxY/3cf7/MaafRYlxGtXYSjt5fkrbvXKQfToBB9yL1uEwQT7aFES9C+uToz1rINUsH1nz4MZfcM5UFSyw8+6zCk09KDB4sigz5/bBvn+ByGzVKYdopB3A2NLTbbxvMN3DaG7HaID7JitGiFza7KI4JCRQJv6KicG8OXq8ai82ANU7d7NyOhMpViN9Vi8cLap2J9J5ZyLIc8n8F5bpg7FFpWRW5uftB8ZKckIbRlBodrx5su6tGxOYCbvU7DPFej37LrSilK5D6XCf8vGpjs/pRUXUaDbs9yMXbMZhbHhdBvPeik8uu78IXXyRw+ul+/vMfmRERdSh8vmgCZ7sdinfvxO/zodWp0eja9iV/+PNc7tv9UNRnciBXEQjlIQBcs+Aatu7cSE19JZ9UftniOXdV7OKe7+7h/u/v57p+V3LL5zV0n/txm20JYuF15/NuPzufVjVvW/9qz1d8tecrAI5MO4LT0k+ksryMzyvm84szVu/8bNdnoddD4wdzae8L6Os5EVwGQMFkCcdbSX5nIN7KH5AdrSBJVFaKeKugrJmaKmRIFF9AV/WgSOqAP1mD2y2KNns8wh4ZHw+JCf5AbExg/0ICWRuKj/lm67ssKv2CpTXfRLU/aOu9dsG1XLvgWgCu7HMpJ1gn0/X5V1EqqohLsWIwmzEU5rfo8/R5fRTnl6J88AUGqx6jpXXdtqDcwIhrjwfg22/h+OPb8fDc1aIgIYCsw69I1BdKeDxSiHNAkKUKnhaT0YfGuQd8HkH+r7Hh1aTgcEh4vWKeKgpo1ApqtbALlo8dimfWi8hq0JlMqAuqSLjjjqhmRN53g91BgvIUcQVf4f9hKvKgeyF5XHRxoAg4/XDDoTjeymm+uEUktpVuY8jLA/lP9ouMVVXTzfkOfDMIqecl0PVcSBgRHfdRuRE2XkOD08Shiiwye6Vhq1yO8s0ApK6ni7ya5Iki3sKQAZWbQ9daX9QN3/ptaBPtpFubRmELhHKAFS8phvPIcHyMf/3VyGPfgbiBAZZAD/jcNI0dc7h16BQ3cgs8PM3hYFpXqi++HFVSAmarkbjqiqjxB+FnIZeXk3DTDe3mUAFwomOPdwBFXxag6ebDkmAVsW+KX+irfofIV5eNKJLgSTh4UKyFKpXQB7OyCBwveBAkxSdiCiU9SGr2F+5kb9EmttRupEDKoV6pocZdjYSE0+ckThtHgi6eRH0Cp2RNpa+3gMMrHgIkOKsKDGniL6ozg2Sph8BdQ27lYOyOSuQ9T6IzxyP1uQZ0iRE8QRDKEZdkJJ8dlacSt1eF1qAnORk0ahG/4fGIeRHkKtFqFTTqcC6RzmJCrTc3ayMKQvb0wKQegdW7Gf+mG5FHvijiOf0B4tOIAvVB1NqtlNalwKbdmLIT2sVJ8ePWH5DdKqxWKykJQhaM5DbwKB4aPHZcPjcuv5O8Q/kcqMnlk4ovyfcWUucVQSOysEgAYNVY6WbO4rp+08lU90df3zeQb6DFlhyP1aYWtkPFF+Y1kNSACr9sZNVPX1PntlPgz0HWeVDpPLj8bmQkZElGq9KilbWkG9LIMmWiauiGvz4Oj0fwgKV0y0Sj9gWuIfLjw7YSHYePlPjyaw1r1ihUVEgkJYl9QJKiOSYURXyuVsPG9Svxeb3oddoW8/sjZXKrYsfobQzZrRIy0nF79fh8sdwuajWY9I2onAfFvFebQRePXx2P2y1it4OxlFqNiN1WqeDiK8wUFms4+lgdJ59miCrWEzliQdzbnm1VbNnYSM4+hZNOs5HZRcKgb3m2XzfdS0mBnrlzjaSkKMyYIZGYGObdIOLcarWIyQKR91FfL5GeTiDPMbY4RpBAtaYGSgIhgGK/9gf2d2/E+AhzdPnzS+h50mBUnvYTGyuZGkpf+y/u+FRknZGkrGwcDgm/InIwFSX6WbidNdS98yqqmioMNsFvpT7Q8r6N4ke21NCYvxGpeDtGqw1zUipOp4TXF87zVKkU1CrQ6308v/IN7tv+fLvaf8x7x3BHj5upsVfybunH2JXGmGPu+f4e7vlexCyNThrJ+T3PZnhDfxQv7fbbFhapqa4Gr8eHyaIhtXsX1LIPAvq8mEea0DySFQdq10FBgK8XMWAqlYzXJ3yqQVlClhVkCfR6BYN3r4gbb5JvIGI4JPx+YYeyWoXPaW9OHhUVZcgqhfSELqgNKTH5BpE2abdTS21pEs6GRsxmBVuSGWucCUkK8n0EfhPQXRRJRXHOftxu0Bv12BK0bfNklKmoqJBxuTxYrFoSs9LR6TQB2dEVsH1oQ7HVkuJC48zB4wa1TsT267RBmUuMj0iZy2BQaLzvYeLfbj+/Vbk1iYJzzg/n0qtaz8nD70ZdvBFXrgdZZ8QYF4fRloTLFT1m1Sqx1hiNfuz3P0rcW++3u02V5njyz7uQmiOPbRdPhtvtZufun/E4fSTEx5GenNEsT0ajtxG7txF1UTEDOsD5BrBQdwLPS7cinytz1yMuLFYVstQ8s6EE+Lx+Gn/+gQNrS9Hp1HTpKtO3X8tcdwDEe/GaNXi8oNKaSOjSFZdLhc9PyIcky2JeqGSwN1aQlyd026TEVEzGtFZ1266Fj5BQ+63IATs3lg8FCMs3nlo2brXw/pe90WjgqacC8hatywY33ejhy680HHUUfP99e3oW9m2O0G0lNYW7Wz++S/8+ANx9Nzz2WNvnb9zRiCS1xO/ZPJRUH0U/LcKRl4GssRGXlh7DKwfhdUqnlKPxl6NVe5C1Vvy6NBochmY52dRqUEtOCnLywe/FYLMgay3NcrJFYv8BDQ0NQq40WfSkdU9D9jdG86gE5CFF1nHTTRKLluqZOBF+/FHkZrQGR6ODzZvW8PlnMpLfTJ+uJk4+JdbWELRrKopCklKL7HHh88soKhPxGdl4vOF1PLKPVDI01lbj2LMXTWVZaI9sjQMSxYcU14DDYEHSGDBabcSnJeN2i/x7l1tCkhS0GiEv63QKkiMf3HWABGoTXn037HY5SoYKrpkajYLHUUf5oTJQPJgS4kFri4mTjhobfoWStZuQS8vRm/QYrUaMVkurc7vYq6JeVodjktuwSVdWVpFfuB+Xw0tGeirJianoTbH230i7VZq/Ak/A36QzW0nMSMPhCOsVTfVtjTc6JkMxZtLo0ASOF2u5Wi1kD41GwaCpR3IUBGRNC+gThF7vFf6mYCylXi/+fD64/U4NtbUSw0ebGDrc1GahWLOqCGdtOdt/8mBLMHDcVB0abcttUiediMY+C4qWIPXaI/LXFF9EgQdVNJdPBfh9UofWfsXso/yXxTQeSkBjsJLYJRWNVh/Kj/R4hc1RF8iP9DjdHNrTsbn9nxk68gu1jBqj48RTTajUrVeF65J/KZmeOZA0DqasDhRYjBhzTXxgztpyNh/0IlVtwarzYovrg5x1Ssx5g3ukoii4Ch14G13t5pKqrpYpLhV8M9Y4LXFpKRgtRrE++R3hHAjZAJIG8KN17MTjAVmtQatTYzGL59wc/69aBQYOoVXqhIqqNqEYu+J0ySEuDr9fQq0SsXg6nUJZRSkHDx5CxkdKcgYGQ0qzczs4jzx+LzWHuuJ2BnLpbUaSM21IfmdArxDrb4ivStZTnl+Ks74OWZaJT2o7ltJXtoG4oqfwKRrME59BNiZH8wI6y0XcA4CrgsICP4eddTmVNQZmzoRrr231MQBQetzJ7NP2Z+FC6NVXwzGZ++j6cDT3bKQu0uhwU+oFx5z25dJ/tzARuz2RXr0URo0K2JQDe1xTvkUQxai2bhWvzzorXNwCgnbD6OMVBZx2B0U/rkFdUYHOoEYOGMRbW2e3NdRgV6vR6HR0S+7SLCdFZJ6gp9IN+wuQyyuwJYl8Xm11TSvczR6kuEbq1Va8shmdOR5TfLyQzyJkI0kKsC7KCpUbf0YqLUSvl9GZTaCJa9U3fOyVUyipNnHHHaLmSFtwOpxs2rhaxCmZTcQb4pqVoSLndk1JMk67SsRkmNRk9kyNGeORXLvFRW7276nH54OsHhbBcd2a60zxY/Dsor7GhUqjIT7FSEpmIh5PWH+O1PE0GoWqomJc9Q3IWjCYraBrnQOyqqyRAzkNuJwekrNSMFot6A26gIja1N8kXpXm7MHldGG26UhINpGY1vq6vOOnOgrzfag0KjK7J2KyWZDlaP4RCDdz80YPz7xoRatTeOMtPRkZUhv2NIWqtT/wy7ISnG4VXbNlRozQtDrG63wHUJR8JK2JxD7j0eh1SBFBCZK7EskdIBH2VOFuqKGiPhmnS0JjSUUTl40+vhnCgQis/nkFPpcTn85HUlwyCfGp6GQNkiTjU7w4fSLmx+f3oVVpqdtvoLLAgKJA1z4pGMyt72Fup4PG8kM47G6SUo0kJuuxJbYeT1NXko+zUewhBrOFpC5pgR6MRrC3SwtqKClsQPL7sKUkobNYUKk1zWowCuBxuajIO4jb4SY+yYgt2Yg1vo1kesDj8uJ2eZFVKnqNGNjm8X8UJEVpjgr+n4WioiIyMzNZvXo148aNC33+2GOP8d5777Fnz56Y3/Tp04dLL72Ue+4JJ+etWbOG8ePHU1RURHp6OlqtlnfffZdp06aFjvnwww+57LLLcLlcv+q6AC6XC5fLFXpfV1dHVlYWtbW1WK2tk3kCfLvia6YuP7XN4yKh9A68GDcbsi+IPaAJ6dq2z15iSOYGYSA7vxny6yYBmfUFe7Hk3CTeT2thyDW5BgsvhBqg703Q4xJxTHl5uOKwRQZLQOJzV3Pegz35ZO0J4n7aM6obi+DLzI61KUhS1/cmEUjRxn0vf/cjjuz2XsvXaHJ88aEGMsacCcC2bTB4cNu3seyOYzh22PeQfjwc9W3bbfpoEUfqXhB9e0LYqRjq2yb9ijMfT+1zaNReGDkT+jQjTTbtp39fCG3zz4Qwt9dZnLtPBNu159n5fGGhsb39tOahiYzrtQoypsKRzRRi2DYjirT8w9XnccHMj5CkMHFCWwju27NnwwXNTKOmyH1xAD1/3NXuvirolUmXBwPBzKfmCYdyU7Q0jwb9B7IC60Jz88hdDe4atmz/luHmNVBPeHw0rWL86sPQpzu4q3HV7WTxqgImDFhLwvhbIPFwsPQUwphKL8ght82IJoRvtGA11kO/W2D4c7H30OT44/Yms0Qqb18n/UqE1sDe18KomeJ1ZIVzsw+SAgKKq5yL3ryL2f6fQr/XyVqsahN61Cg+Hw7c1Pob8UYkDIauEbkWBK+RlATJmqhnN/+Fjzl59DeQdiwcvTS20U3m9uxZB7joYVG1s907+yuSGB9HLQZ9UvMVq199GLLjwF0D9feLzxJGwPGbRHWFyGgkgO9nw9D+4Crno7dLmXbfxSQkCIWuXUU/g20aNxtsgfLFrYzZe9/S8OyCf3HYYfDxXB2JSWIiNlf1UFHg1a+f5PYcUZRDK6n5+vDnOS5lXPgaSUlsVfZx1KbbqfU50Erw0NY7GNltI+NOSMGQNRpM6aBPF8Y/SR1IDqqAxmJwFPDm604unzATEkchT/wY9KnCuBRM5t82I2qMF1alk/lDcbvXgjosvHDizXyx+Qy6HDaY085QMXCg6F+bTSjIKpVwoHo8IlG7/NOpjMsO7BHBMdj0+UU8O7+9DHnhxa2vBW+/DNnxoWdRt+cpXl12Dd/mX45d34sRh6sZNEi0y2gUhS6cTlFBOScHelVN54whb0W3CcLzosm8w1lBtz7jOXf4Jzz1wFbwHgSjBaw9QZcUMGxJIpjRXgC1u7n1ibM4d9xchh4O+t6nQtxQMPcAfbKYP4tGiaqvAfznswfZk9OHC8bP4ZQpeyGxHyQcBtZ+wpDpc4CzTPx25+N83+jjmIgckyf738QdvS6JGrMNRjf9dt9GoVuQF8dJUBO43TFxg1kz4R2kioqoMX5vxcc8li+C3w5vzGaD8WDoGv8ddAfXZJ8VuEYlJCXydOVn3L3vndAx+5QevLL0epZXXEFSVwsjRgpCoNRUEYymUonq33V1sHs3zJck1gRiQMfHD+WHca+hqayJatMr9Yu5YZ+QaaQ9J5H60Wuc2G8Bbz67GBpWg+wWwY+6JGHEdFdDYwGU/gAoSLF8iK2iMDmVjLhSkch2ZkX02ICY8bF33c/0cQQMVyfvFeTCTdHSHnnY05B2tDimlfVm5+7PGJj5s/iuHfOo7EA+KVuvbFnmSkoCC2L9CFwjtM6OeFHImy3dd+AeVn/4EeO7LxAG7ZOaseZsmxG13gBQTXSb2pjboTb1ukoUrWipXwFc5bzwRAndfPOYOORnksZcBHFDBHG8IQNcpfDtiKh5t88NvfPCp/vvoDu5vvs5Uf1UqKngiI23st9ZBkB3GQ4EttgsfSrLx71Oj0ZdqJ9qDA6OO/g4G+oFWe3Zh85k7jGfi/F0zPLYoPFmkslCcv85dhHU28azCB2fMgmOXd5mPy2ce4DGPUs5YvBGUsZdAvHDwNpHBC3IOnHswiFRfdXRedRRxB08kn+VHcGpI7/isEmZkHw4WPuLdqnNYqwuOzLUpkofZOyHYLjME/1v5M5el0bNI8UsceqhZ5hfJSy7BxK6kC0XQL0RpqwMX7wFXSRnfxm9bYEsoXbKUKFnMW4OZE+LPh5inl1It23pGk3Wm5qSMh65rZSzx8xl9JEmSBkjxpQlQIzoqoDvjo56dm8vuZTBmdsZNKkvhgHniT1LnyyOl1SBvaUUFC80HuKMT55mniKISVXIvDz4Dk5PO0pkE1VV4Tb6ub1sDnMrwkT2kTgqYQSPDbgBU50TqmsgPo4v7Wt4KHcO3kBgd8aD+Vw85n0uOWM5/XrkQkI/SBgOph6C3NxrFwVyHCWQM5MVuyYw6Zcf2y2vzB0I554dfv/+sIe4KOvEqLntNfnouepiDgUTP2cUcurArznv5HUcOfagECAsmYLIKqhb+NxiP67dwfLv3BzZ+6t2PzucFaT3OJp0ilmxHCzqHVC3CGq+BaWm+RsJrpnxQ1mt/4TZCxNYsMJMfkVsIEVWcj1nTljBC/NOAn6FTD7hU7D0aFMmbyh/ArPeDqbucOr+NmXyEz68i0UNP4W+KpuyjGRdfNSz8Ji8WL4/DVfAWRzSXY5eKvSRlq7RL0nMu623C9bzOg0cty50yOyP1Ux/fiAur3gO91ywg4emreCsXe/wZUN4b8w/diFdDKkxe2TSD2dRGSC+DrVpzDvQ49I223T0Bcewa61COsVsCV7KVw+HngbnwnDSiWEopN5Jo7Yfxr3DxWct7fOrF0G/5JjxdP11cMUVgWNKD0LV8yCtEu8lDSTfjBJ3NkkLjqAKIXR1M6Rz8NhA0H/EGrhHVUC/TdGB7UFsPeJDhtn6xvTT4WuvY2OD2PNkwuWnrss+m1cG3xUj3zxe/SX3HJwLwJOJcIdElGywv0DLDQ+nsmhTUshxlWxzcve5G7l52h6kHbHyzbwvJW6e2YdDlYKIwWLwcN+0DUw/bzOZq/9FMN3o5NQj+Prw52Pa9Fj1PO49KOxCN9rgJU10m9ZvN3LjY2ls3BsXuqZe6+WiY3Yz4cJZXJIzM/T5e8Me5OKsk2KuMSF3BqvrRLJI2owiMqRCzj1xHXdctQAcW4BGiD9MrM1qkyjS6SyDyg18tv5MbnzpZSZ1W87HsxZAw4/gq4SkkcL+obGI4AJHKZQsBRScbh16rQuGPwv9bo19oNtmNCunOeqyeLduFfN+iGPdNiP1DmEAU6vDQbJ6rZeJl97M0oxXQj99bci9XNXtjKjxscC5nlN+mhEKpE6bUUQ6xbzyUgNj+30B9lXQuA1oxrYLrNozni9WnsGeytEMPf5wMrqoSU2TSEsTjlqNJqx3lpdD/u793JAVCGLtwDzKkAp56bHVjB+4ABw/gbcCzN3F+i+pBRlHtRgL3XP0HAyMqEx9CoeOXSAKbEXMox98Ozh6m4gAU/lkvKn+Dsnk0in3AcLJOmNGs10ThZXPXM7EjHei7xta3Y9CukigTat/MvHvp1NZv9sW5TAe0LWKmXdsYlL8ceKDnlfC6NfbXPuXv/85R2a90fqziDg+sk2uozfxzvxk5v9o4/uNZpzuaIedLPk5/ewtfDVgFMG47Ysyp/L+8Idj5t3rDcu4Oudt8X7j1aQteCC8Lit+qP0KSmeCUhVxBQl0AyDzKtLHnk06xXy7UOizKD449DI0fg5SMHBZBvMR0P1R+HG86FdLb5jwMXaHzKMvW5n5dRdqHeFkRbPBw9VTd3DqmAVMzLi/9X5qMmZDsuZx64UdNPJZQ4ysWbb4VlKsZWKtOLOszWe34YcCRl8gNpV2yxIfBsbMxHmQdVqbe+QvXzzNgPQmum3kfTQZs0V5dkaMHcuQ+J9Z/PHXUP89uA+AtbfQ8zQ2wC/WzPLV7HUrDM4L6wnN2UqwyNxf+QmPHBKy3Nf+wzm5bxOZvI0xG9yHt0RMbYqWQ+0bIAX0Y/0gSL4eTIfD7sC5BtwNwx5r81lcc1sPvvrIHH0N5y4oeBS8u8K/ka2QcD63VjTyfI4ItJaR2H7kXAZYesSsNydtvosFVT/FPMYH+lzFjL5Xx/TTx47VnL9brPf3107ioZErflU/rV0TEWRTVgiVj4AU6HNNFnSdRb7aQI9vjgnN7WkZxzNnxKMxbXrb/gNX7BVrzGVWeFtLzDr7wzIf//pvL7bniyj4iybv57GLV/Az33NS7uzQcfNGPsNp6UfFXOP8gpf4uDwgVz7kIc1fzrjsYj7/8ADUfgM1y8DfSkXlprYPoPZgNUfdehhb8wTb7+Un7OONGxchm/RQcKU46NiVkDKhzXlUuPAuMuMLxPg/u6bNZ7F3Uw596m8MdGzHZM3HH4PjAtuA6KevgNdB8oG2O3R9A9TxbP/uOgZnrm/9GhFtqjxUSGLuFR1qU2gNDMo3bcwjfr4fcjeSm9uDt2pWM/9HG3vydJjMMn37iiR4rxfy8sTfqJOWs2HEUaFTHZs0mif634ixrhGqqyE+nq/t67hv37sh3TakJ/S7DYY/I163YkNk13P8tLSUrzacys/KLWAykpimoXt3CZNJzBOfTxBFl5RAwUEXH07Sh8aT1wtL1ll551MzX61NxuMT55YkhUmDCznr2GXca7uM2kCX3pB9Li8PviNmjL/R8B1X5Qjb+B3x8KQKPJVqFlt3sWCVjZ/2GtixT49XUWMyCT9lTQ10SaxnWPdivr65rzjX2bVCfm3pvps+u+SJMPnHNvtp9ZerGd9Be0xwzH7+GXTvDrhyoeh9cC4FKWwjwXAYxJ+H8fjbGJGwmiuO/pxLz/0F5HqwpIO5p7DFyTpBDuhzQM0vbN2scFjGwl/Vpjdm1TKix2dgXwOOHRBa6aJxsLwr2cmHWk6MaGLf273TzVGTRzI8aQsLPvoBGjeDJx8M8aCPE3qFogRInEvBUQPewNo19j3ofnGb683Y2dezzl8LwCBLT7ZN+kQEiUbIv2uVPYz7SegWeq8Op1r0t4zEsrGzOCppVNR+VKWvZ+iaqygI+CxMQPBu/9PnSh7se03MmP1P5VwePvQlAFN96SxUiX5I1yWxZsI7ZBszotr0mXMd5+56OaSLNOsjba5vXeV4G0vpNucSigKHXp51Km8N+0+sLFExl0fyRZuOcmfxgza/+XO3gD5P7eLiMR9w7y3bQNUI5hSw9hA2ZFmH8De5BJFGXQ7pR79BOsUcczQ8/UQ92FdDxTJwrQPJET6xbBPyqSTBwa/5ZW9/vvQtZeVWMwdL9MSnaLBYZYxGsQY2NkJ1uQuPJ5dd5w0M0XDe2/sKHu57bZT/qFhfy7H7H+OXRuGYGqKCbYEfTEkew6LR/43xN71av5RrA/6jcQ19WGNum7wvEqFnd8LPED9EvG5lvan97npsjbXgSYWjAnO2uFgsYgBGP8QFAhXd1dD4M76Ct1m2+Vg+qZ7DknVW0GiYMEEiOVnsFaKgEBQUQEO9n+/OVIl1eeTLkDyOjTuNPPxKAvPXRwenJ1od3HXmam497lLkikKolckZsI135yfy1XIbO/fH2vcyExu497LVXJt9fGjtzyvW8taXibz+WQKlNdHkHl2S6plx9W6uGBDQDQ5/A3pNb7Of1n30LmOyl4FtEJy4Pbbjt82Ishm4vWq06sDa1cE18Jqr4apLi6DuW6ieD76mc0UG/SAufeNtFi/KoLt2P2u+/RbqloDzF/DbhY9UYxHJ48HA9Ei0o032+gKyP55OReDQ67PP4b+D74yZ28/UzOf2Ax8B8GSixB2SEiXX/bzXwOOz4li4IYl6p4hAHphdw8XH7OSmE35E77qn5TY18yxCe2TmyYJ0qKXjAVzlrPjkOyalPN2hZxG6xmmFgmS0jTYFn12/vvDhh4Hzl2yH6veAVSB5hM3RegIkXs6Xqwdx7b+NYd3FZ4f676DiM/BGECxKGjBPAtupUBCQTY/bCIkj22xTyqgzUVVWMyihmKXzc6DhB6jdAO5dIEUQDUla0PYCdQIUrIIaKBi+jQ8XJbBuu5G1PxkoqY4O9O2eWsu4foeYffYQ8ayHPyeK2QHlOTU8+FYmr37XG59fpltqA89euZITR6yn17bHKFSETWtiwmH8OP5NccKI/WiDksPonwJR9LWZpD2/MVrHUxQo/ALqZ4N0SHymHwiJl4PlSNJHpJNOMXfdCeecE/hN6W6oehv4ASQ/qBIh6SqIO5UNix/g8OzFLY+P5mxEwfHRUZl84L0w9JGWn13gGoPeuICdivDB2NRmSqcsRafSRvXTJvYxaut/QpcM2hC3bEbshXWLofwd8B2KenaoEiH9Itj+gnh2XU6mvsdDfLvayldL9HyzLom6CHtMSpyTU8fu49/Hz6CP6vOouZ1fouHGR1L4el0KiiIFjndwz3kbOfP09WStDdvMexq78O+eF5Hu0kJdHQoKi707eKPie3xN9YT04+CoRW3qLjd88DSvOL4LfXVvr8u5NvtspKoqqKpCiY/n2crPef7QvNAxoWuccgDM2W3KdXLPaaQqJUzoUcynnwa+L90PVbOA78PR69apkHILI767kS3usP/fMXWNKCAaIdcpZgX9dyfjDvp2khD9OuZtiB8KwMIFCrfM7M3eEqE3qFV+rj1xO49dsIh+N9yAr7yOvpZili8HfDWQ/xI4Foq1JvywwTSWh/JTeaDyc3EeScWeo76gh6lLVJsaDA66r7yYigDRhwEISkoP972W+/pMj1n7Ly2axXulwm98z77ruXbUl6Rmp6AZ/RwYMkU8m8YmEvu2zWgx/mFj11289nkSyzebyS1oPqng1Ck1fHlJIGN/+PPQ72bxurV9++MPGNPtj5vbDfUFdP14OtWBQ2/pcQHPDbw1pp8eqfqC+/M+A2BWssw1irB7b87+hc+/i2fjTiMbdxqotYczdGRZoU9mNX2H/cBXI84KfX5kwgieG3Qr5lpnSN9e7NzMbXtex00TX2H2BSKGry1b2tsP8Zp3DQAm2cDs4Y9wctrEUGyTYpZ42/49N+x7D08EEVkQQyy9ODdjCl29Jmiox6v4+dG7h4+r1+AIrPcZEiE9oSWb9JzGlVy4ZxYAaR4rJRqRcKVCxj51dfQamJSE3ejE8v1poYSS0Dya+AWYu7Fhh5EZLyfy7abohJzMxAbuPW8Z96SeTk3gdg6PG8T6ie/FtOmthu+ZnhPYp3KPIe2DD8LrrLcKauZB5Yex/mpNV0g9H158st0++ioDZNwJQS18UuJwlo8L+Aoi1v7vvds5ZvvjAPTXwi9WYnwWNz+RxqYcW+jckqRw5JBCzrz+JW4oejr0+XMDbuWWnhfE3PetZe/zfOEiAPTIOAPPfbi1H5snzYlpU9R+5LSQ9sSeWPtvaS5UPQ3SxsB1joG0e0FlC9t/hz0JAwL7Rit75IA3zmNXoM8TNFaKpyxBK2ui2vSj7xcmbXskdPmOxv8G/S5Kt/P5puJhPl0ax7erLFTUxZIrdk+r5bHz7+K8ka9GX6Odvh1O2IzLLTF3aTxPv53I9oPRiW4ZiQ08fsNOLk4eI45POxYOexKA75b4uHVmL7blhxlNxg0s44WrlnNO9bUcRPhwTCoDDVNXxTy7eoMd65orY/vpzErQJbQdaxBcM5PGwpQ1ba43H39q4pZ/9WxmfOyDqltBCgRz2k6DtPtE3MnWAeKzqdtFfE9bbdowHSqc4EoL5RssW+zjuU8y+G5nGm6vCpXsZ8Lgcq4/cQtnjfwcqeitqHlUWy9z6+NJfLAsPWRDtBrd/Ou0n/jP9O2oiwO641GLIX1Km23K/epheqbsEXEz50UQG7WwH+XtOEC38kC+RztlTen9C+kIlsqHcWzPrdHXaKVNztoquvc/MvrZeUqgYBY4F4EU0HslDVhPpsh8Kr2XX0LQI9iSHyVyj3zfNZ6LBq1ud5ua89sqCsz5RM3zn2ay5WAiAH261HHjKVu5dvIqVIX3QQ3UJ1/I3IJH+HGLmU3bdewtMOL1y6ECnXqNj4HZlVx39MNcfsR/f3WbXG6Jb1dbef8LM9+sTwqNJ4DxA4q49OgtTO93sjg+dRKr5ddYsMrGqo1aNu6x4fSEjzfqvIzuV4L5yIuZH/8DIPSEHUfOjYnZ2S3nc9ja63AG9uHQ3D69OEyW1w7ddtBAD++/tFD4Fxu3QDPkVABP5/TmDnJC72UkdLIWjaQCv4JH8uHye0L2RgjqLkV8OXsdXa1fg+Nn8JYKv6wxSxCGOyvAfgCAyoYEEs1VIj7z9KKW7yHwLNatVTj9zKEMT9ocYf8tCNt/VUYgYP+1l4CzLmz/nTQfMk9qs5/2zHuCvmk72j0+Cvfkkfny1R3K0yKw7TJqFvS+ps02XXaVmXeXnUpKiiDobwsfb/+Y8784P/T+pyM+YqitT9R48pv99Ft1GTlOccKQzNVrOvS+lr15Ot780MhbizKoagjb3/pm1XLN1G0MS3meI/vNi+6ntvbIpjJ55H03s283XQP7mLqRpYpH4/XjU/wUKTXscRWFcoP+VX48L4xbJOJaTs4R63Mkts2I1V2COM8TJklpzW618EKUaljfcCVfljzEpl+MHCzSYknSYTRJGAwiF8BuV2ioaOCC0a/zIP9u//iQ4Kz+czlz5OeccVY9uuTuYM4EUxfQxgkiNmeFiKdxlICjAGnp7DZPG4kTq0fyzeGbxJv2PIvGEi44U8Vpw7/kxFNcGDN7gzlL2NS0ccJ27yoXBbscxdBYQMbSdylub8If0KehK3vNh9o+MAJBW8mLz1YycchicGwD+w7wlYAshQq+gg60WRx+z3zyc2xiz1tfDvU/gH0j2DeA0hA+saQBXT9KGkdz2EUPka05wNolK8G+Flw54K8CnVnYZ1HA2yDWGskMH+3v0Fqw/pbDGT2y/XHSkWNwTcZu5v0Qx5bdBrbv1dPg1mKxCDdIXR0Y1U4GdSvlx7OzO9SvryTDxU4T3248gZXKK2zcZcKnNdCnr4zVKogfBfkQ5OcrFO1vYNu/rB3Lyzh0P7v29uObkn+zseoMDlUaScnUkt1dzCGtVviFGxshd5+fXtL7FBZZ+bl8ItNvTGbYMOjRQ8Qs6XQiB8fvF/7k+nqoqoKBn7ZNqBoJd3e1yM/tdj6M/zD2gG0zotaPVbvHMyF1dcdyPw7dj1INK20reXNRf+GjKtZhNIoC7iqVcNuUloLV6KR8lhXtV552j6nNg4cz4q4t4k1H7ZrHroCUI8TrVtbAggX30CXhkBj/59Q1f42Itb907x7efraYeVtOJ+vwEYweo6J/f1GEJBgH4PeLOMe6Oigv9fDRvW9z0cQPGD3Bi7bbkSKXw9xLFMtylsLSiVG5AEc8tJwe5v0cP3Ax551TAbZMMGeI3F5ZDyqtIOP1u6FuNxv2/cLoXYtCvz81dRKXZJ2Mxe6G2jp8VjML7Rt5rWBBOHY7uEf2+5fwJUOrufQPvW2kl20pQ3oWMOiEKaL4mj4NDKmBdbxMrJmKD+x5eBvy0SwKx9q2B+GYjIgc4FZkqGlv3sZHfuGbiNdYmDfyWSYljYjSI19vWMZ1Oe+G7LmR6G3sytHJI8nyW8DeiMugYb1jN0uqtnSo3ZE4qrEnPxhzQ+/Py5jCKamT0NudUFdHvdbNpw3r+CaQ7wIRz+LY5WGSr5ZyzVzV3PSMlfPGfsLQkU5MA84K5C52F/mkzpKYHCqPV82HS6fx6cazKNIez/hJGgYNgj59CK2Bfr/IwSwrEya8C2ub5Bu01qZgvoHDDq4MOHJ+y8dDwG+7FYre5pe9/Xm35gfm/2jlYIme4cMlUlMF0WBw/cvLA5Pew/71FfQx7uG9lxaQnfAdOPeApZvIb1ObxXxoLIKK1YDCv95/npMGLeDwYYXYhk0LzLsegX4qhW+HR/UTELL/KsdvZslaCx8vSeCzpTYanNGMVPFmJ7dfup+7xw4UHwTzDaDV9ebHDz7kiF4Lw/GdTdEkTqSxsgTjtsB5O2Aj8laq+N79PN/sO5ete4yUVGmIT9FiMkvodIIEvdHup66sgW4XD+M7ndBjkrVxzD/8BUbHDw49P8Us8Ur9Yv6V+0FUfHhXdR7rlywTfmHnTvDViXGoSxb2dUdJSD8KxdZ1OwcG3Nn2+Kj7BH/JahZvOo6PK2ezbIMFr6Rh3DiJ+Hjh1xeF2ETBEbXsYdUN2g71U6/ZF5IbuGRXQxprxr9DZoMUapPT5OWkvKf5rkasMaMd3VhvCCcjdjOkMz5hKFaPCpxOqtQeVjbsoNgdjk8Oze2jlwq7VRt5O9KW+2PHRCsYae/BJtP+Dv0mqNvOm7Odbgnfg3M3OA+AVi3WH0kt5EB3PUhWEi7fjq7BzpE9tvPRa8vAsRXsu0GqA61ZxFx5HeBpAPSsyT2Bh944l3NGzeXyi/LBkiD2L3N3MU9lLaAECrgegLocpO/ndugefjb1ZkhGDiDBtMBDbGXfLtidR5f/tl+3rcfM5Oyl7CgcxEVXmHnkEZFXEZTnmqKhAd679yVunzWdvr18vP+xmayuEHTGNeXvUhQoLfby1k3P8Ut+f3oefRw9+6pJTZPJyBCyhFotficKnIowmHO8gRMNfgAGz2jTrnn5Tb1Y9LmeUwd+xawnFoN9nfDHJY8RhdsUwFsv9u6KNWxywqiI8I7T045i1uC70VXXidzCxESWurZw0fancAV8O0Hd5bILirjxws8CukUu4BdrrUoH3sZQ3Md9cx/mra+uELrLyq1Q+7XQXbzFzT6L3W7oH5EDHJMniJirY/b9h5/th0JtmtxzCZeftZgjR20CnVrE39v6C9uK1w7uSnCUw8H3+XHXBI5IXtkhXoNQ7vNp+WDs0rb9d/6F4vyBfIMW14IAj8rXK5O57vFxnNhvAa89t1HohHId2PqJZ6c2irwIX6OYR7X7yThnA2cMnscDt28g2bIPDFqwdhe8FCp9QI90in2ybg+J69ZQ1QHKrzNc3fl80AGi5l1TbJvRvG1ixAvQ91+xnzfJvc9bNotPFoxj44HxJI44nvQsDWkZclQukd8vdKqKCijal8896V07pLNlnHoZF4yaw/UXLSc7bRfEZYsYFlN3QYDtqYX6/ZAzE/CxPncUo3sGfETt0G19jWWoZ1/c7n79NThr93RmDFmNLd5Il5MeDMjiGhHXK2tEfzpKhUzeWAzOEqQvOra/jJ21iovGfcAxRxygz8h0sHQVthJ9iljHXVXgrgoX4y5ZzrKlXZiz+gI228+nez8dw4ZJ9Osn9myTSezbDoeIky6rbuQBtyl0vUkJw7km+yySHRLU1qIosErZy8sVi6nyikjTa5a9wqebz2HMRD0vzjRhNksBgtdwuyOHtK7gbXZ9+BpfbTiVXarrMaUYSE7T0LWbhNks1nO/XxRwqqyEA/u9vPmWkPf27RMFG9uCRu3B69MwYADs3Nn28RQtwvHJ6cxbezpfVL7Cj1stZHRVM3YsJCaKfvL5hJxWWAi1NX4eHzKIV5Zdz6ryafQcYmP4CJl+/YSuHeTucDqFTLR3LxQue5YLD3+dhMxMUiY/EBgX2gBhtjowPkpC42P/sh30+NeLLaX4xcCFlv6JuzhQ2YOrr4ZXX237N9ufHcfg9LXiTTtsrXu3VTHjXoUDZd05/dpRZGWrSE0VsZ3BewYCBUuhqMTD2Wu11AdOPdjSi+XjXieh1h3aK8r1DUza/xC7GoWd/jC/ja1ybftuOgAlnui9AsJxqnFxEK+OWm/GTD+Gi8Z9wPHHHKDn0GSwZInifPrkwDyqFMf6PdCQy1sfxDH9ladJSxOnbRdekagptvGV5ieWrbewPdeAT9YSlyRyAWRZjKf6Gg+u6hp+uSIc7zrI3JNZQ+6mp9MgDE5Apb6R20pms6RGxJfeWHkUL40Rvp32cNdF2WPamW+Q3uMoTuy3kNMnr+HEyfvFQzZniLiooO3D5xZ7WM0OFi0xcfZTL6LVa/nqGy0jRxKK+2q6HkiS+G94O6jbfgaW7m3K5I0Vj2HUOUR+wSn72pS5Nn2/j8efTqO4LptpNw8jLUMmJUUU+9HrxZgNFqFpbBQ69zG7A20aNQuSDm+zTQf2v0N39X6o1wn/dhAt8GQsyNnOSZWvhw7rb+7O2PghJPt00NhIg05ig2MPG+vC8d2hMT7kQeFvaqNNk+6czI+7RtOjB+Tm0iYaahowX2HpkI25T/Iecsr7cMEFglOvLUx7tD8feUXsW5oukVXj36KnKSuqnz5xrGHa7lfwozBEC/fknc1Rg1aQMuEKUQzO0lvYuoLy046HYIfIcfH5ZT5aej5z1l5AjXUix51kZtgwsWekpAgZPpiP7XaLtXzRG5/z2DsnkNFFy2dfqOnVS4xNkym2/R6P+J3pq8BgbqduO3JSXzbnj2TaNJgzJ/a8TbHitReY5Lql3Rx/fmcNqtPuA+Dnn2HIkLav8dBJ/2HJ9ikk9enN1bekoDdAfLwU4iYL+rd9Pqithb3LPuGcjPPaf98Nh3jjoQ0M7rKNkVOHoM4YK+QUfWpYr3VVgKNI2Cvthxh1xhlsOjCSE06AhQvbvof3vpjJpduvD73va+rGyLgBJPq04HBQp1HY7NzH9oYD4R/NEG1/9lm4tZn0/qbIeXEQvX/c2f55kQwbLhnFF+vPYK/uWqypBpLTNXTrJmG1CvlGUcQ4qquD/bk+6ja8y57CvvSbdBjnX2xEVon1yWIJFogJ27GrqsC3dApjspeK67VD/nXXlKG97+KO+ZL/S8BvezX0vkp81oqN6OK1L/KBtA+AFG08y8bOYrC1d9Tcfs++nMv3viHsVo0JzMw7h+92HI112Cn06qcmPVMmLU2MwaC+7fGIfbKoCLxLrmDFzknYE49k5NGZZHSRSU0VfaVWh/n03G5x2S6Vd5NdNotvNpzEKuV5tuca0VgM9O4rY7GI9T8kqxTBgT12tuwQE7+9atiHl05j2fZjqTIdwchjupPeRdxDUpJ41pEcf+Xl8PFHfkpXL+OyI95h2mlbwZwKiYeJ3BGNVaxrrnKo2wO7ngN8UIFYC45cBIbkNtd+38EH+Gb9SXyXfxYHVadhTTGQmqkmK0vcs0Yj2uNyQX4+6Es/5ZEx5/wqroVNm2K33+aw6bExjMxeH47dboptM6L5XQ9lc4HrYOj9UEtvJiYeRqJHA42N1OskVjf+wvq6cCx1yGdxxFfQ5RTxuhX5ZvjJJ1C7r4ozhn7B0zO2CE4NvVro9GqzeBZ+t7CX1O5mw08pjL5XtL2hofk9IhJ+Pyy/+Wi+2nQqhYbTyB6cQXqWmvR0UUBPpxNz2+MRukJxMbxdkMpaqRlbdAvor4W5ykASTJVkTH1Y8ONJUqBYijrAV1UabZPeGlj42plvsPLdt5jY7dNojr9IbJsR9ey2HRrM0Lu3AWIutlpYIIggD0KPy0Sce1s8GR98yZFd2h9L6aqt4vMn5vPBmgtpTJnM4WM1DB0q/C6JiaKNsiza29Aghr5x4VheX34l2xumctgRqYwcKdG7tyicpdOFZQmXS3Rf8co3uXD7le1eZ8uNkH4HoTzBx/pdz929L49aZ+1GN0ftf5iNgT3M11NCnqe0+xpLux/DlAPLgA5wUpwpdWiveOD4Gbyz7jK69M3gsSfUZGRAcrLgOY2oYwAIffjzRR9z2S/hOCKTSk+aLgkrOiSvjwbZQ5m3hpqAjUEF1GYZMekboe8tMOK52EY0sVuNPm4gG3KGIctijW8Lm1ZXMWqC4BXYuRMGDGjHjQfHbDvzDc64MIN5a0RufIe5xjq4Lt9+uyjy1hZuOGcFr3w6iaQkcdp2oYPjIxSXFsw3aIptM6LWj8e+uot754r49fb2k/Rgx2IygnLgkUfCDz+0ffiqD95nQt0lv+pZ7Nkj1pm2oNc6cXn09O4tbEZtYcvCZQw/MLlj8TG9RkP/ycLfCnBC6/71uro6bDZbu+sbdAT/UwUu1qxZw9ixY0OfP/roo3zwwQfs3h1LBtunTx8uu+wy7r777tBnq1evZsKECRQXF5OWloZWq+W9997j/PPDC+mcOXO44oorcDqdv+q6ADNmzODBB2MdBu0dAIUlhdz20FBcVZVsTgefDIEioqgU8V7lF6/7VkDXWriiSxrj4kogeyIcPSNwJgXhsFOg4H0ofD90jZ0F/TE5S8n2VMPF3wpDFIStTPnvQsF7oeM9XhUNtVriJQdMeB56nR0+PjgEdz8Le58P/eabl7py0vr2Bw7uyezDK+ZTydqjcNgN49EYNBGGrvC9SJKo3GdK9DI843RUaiU60TwS22ZELYzfLsrghIQiSOkNJz4R7qfgfZd+AuVh5+3+smzU9lq6uqrh3LlgyYhYURU49A7kvxM6vqI+keRrxOb1yScRCbKtIbgJ9v2XcCq1cQ95FVlUzIURq5smrreAFCD4WKZug7jBbV7j8h+GcaIHTCYL46acj1Rehfm6GUieQMCVWkK6WYE4cfwvFf0ZP3MFWrefD76OY/hoTaCbAn0VGCfieUogwcrz0uj/QyJ2XQK+5DS8Jht+vRFJrRJVtiQJye8LeMfcbGUoVdULeaBxgWDqMEmQYBaeGFkWC7XWAzoPHF0Nalj/gZpuixKpIgG72kajJRXMZhS1BkWlCVTJ9iF5PBjitJxz8DbyGgYyfTq88UbbXbt10Q/s+OYuTHYPx54mEnwi+6ppPznUWgxZgcSUlghAmjyLb1/qygkdmEfbew1k7ZkiUenMy+9FVqmRisqwTb4UyeVB0cpIT/shSRzv88s8fPtUZpR8AxrAFvjTISRHGTAjMlZ1QHICM1ZnM2PfFtHnpsCfVSeehUoFFgU0HkTpQjufJ/dhrqaUMkc1+xLEeuaTQe0Hryx4SVWKWNcOL4I4JxBvxVJcR24CJDrEZxYXyAo41VCth2oDmDxgc4GUPpIJfi+JSSkMn3ham2P204Z07vZVkGtqn4doVCGcazsCi8rPyHHH0n3g+Oh+1WlwvX8yem8zkl07C4Es2TaZ455cItrbzp390X8fSbLax7BRE+k97OioNgExz/vUDaM4Ua/DbLFxwnk3t3k8wOY5MGShmlJSqSaeKhLwGiz4tXr8Kg2S4kf2CS3clqqnPnMLR6/La9rUFpGlOUSBJ4uLL4b33mv7+JW/rOTc2cdQrBNtlhQYVgKJgZyZeh1sSodgDtCRwA8h8patInguEvZDML+vcMQEsGLXEfzwppUZ5d+IcW5FzAOtWvxZJdD7xRhXeWlMSOdzaxbGBjcjxk0mIbV79FqgUeN+aCI6X1haXrgSpi4Wq2QVCRSRQSWJeFHjQYMPFRo8qPGiw4V3ZDJ7jxH7y5mX3Y2s1rY6txUF3tg+AYAJx5xGeo+hbY7Z+e/ByUsCvwfKSOEg2bjQ4USPBw06XOhxYqQR+bA4to+zY2xwc9SJF6LWGltdA9FBrUGPLdEPw56BPlcLp6HiF4TgCuAshqqfYNU5oLiZ8fBgZuzeHvo9CYg1ShX4iwt87gP0sFsazcebk8WaBmJdSxPfoQG0gWM9gBGUhBTeSbCR/JNIrDphn1ibmmJPIuwVuW740tNRBbyZg8qge03s8fVaWJ4tXldbUvFkKKTsKSPFDqMLY48HWJ0lEpUBbD3hiG/Faz8SB8mmlNTQs/Ajh56FhXoevqKWz7IOhR7eabvh8nBsLruT4K5jwK8S3/fMT+HChYeH+4lAf6YE+lgjjsMd6KukVC4fouJnitiS0Xz7g5D9MC4fLigcjnyYEY1Gy2mX3t3memN3GjDpA9QI7dwjF7/UleM6sEf+3Hcw60+zAXD29P8IWaOVeeR0a9n5Zmr7ZS7gnumjGeFxkd6lG4NGHdfmfrSxYATLlyVwu30pWLWQFAcWExj0Qr4x+kHrFn9j80EFr22biITC+GNOJaPHsDbn9sGDZrKzG9ptRN52aDBfvNhNjA8VEB/40xB+r0fwyBmgKDmO4xNdbLeEScB6VkFmIBfBpYafUsEVGFcaP7yzKh1roZhHI4sgPSLfJ4gGLfyQLV73OjKO/pNqwg7sNu4B4Kktk4hT+xg++ih6DjmizTH4w49JHDW4QgQInbU+sBkrwiisKELX2fNs6Pz5lV1467Fh4X6KC/SNNtBPaoSMpBP9RGLC/7F31+FNXu0Dx79PPHUvdYq7u2/IYIMxGGODGbN39s7d+c3eubu7CzM25gIbG8PdnSKFlnpjz++P0yaVtGlKSwvcn+vK1TR5kpzksXPOc859c7MWStim7eRboMM+SMmH6BJVv3EaYF8obIqCPWFlAc6j2uGy7aXTylzS8qDTPgirMMfZrcGmaFgbB9khsN8TDzv6+/btEFRCbHtZmcyUnc/UOsyJjaJfUikb7MWgqf33rc+gW4W+9A+6wP3DfP9fu6Yn07dn13m/yLOH8cGVPQA4/qTpxCa3DbjNXrtgGB2sHtq070LPYacGXHfLtnVhfm4UAFMuuAPNYKh133a6TNx301jf72RDHf/sZevNRFnbouy5FlEwMlctWx50uKplMyttgz9ua83WBQUkrNhDZq46X1SlAz+1gmKTCma/vWM8Gav3YXXDqE1qu6hqVTxsjFb14ZXu7sxcu9T3ZAiQiO98Z0Idw8vm3a1v0Yf57QyEFDgYfuJ0LNawWs/bbh3eWNiChFW7gZrPkSsSYHMUmG3Q9Sw7KSnFkPkf6POwukCn66A71RcuzlKDtkp2w9ypbN2XyO/rkggpcDB0zGnYQqNrr0sAM18cycztP1UuhAakodabERVppwBIT+TDiD2c/kP1334jrdlGOiXYsFFCBltpzSa2te3DRQXXEpMFp87sSnK7cHRd92UoL+tiqWjOv+eSYnbTtedAOvQZE3CbXbCxN4sL7dhsIUw4+4aAy6/Pi+T3H2wkrNiDyaPWhT+/tFTHToB5Jw2nlcVN+y696DZwQp3r/b39DCTYQQqr6UgqO+iI6gfb0a4Vc3pAwhI1gP+k9f632V9bqnoRwE8nDqOT1UOrdp3pPXxKwDL9uW4g378YW7m+Ui4OSAbygC3qIVd6Bq9NSwNg6OhJtGjZLeDxZubM3sxcv7DquytpqG1vJ5TF/GDOkF7sSM4lYckmokpgqJ9qiMMIc8oGXn7QBd7vCmXjunjvE5i2ovLyOhBxC5TP7374zwTab1EHjU77oHVO9c/YFQ4Lk9T9hEgwxftfd9tIYxWdCKWQAczHjAvS0viry3YGfuun7Jj5i4E4sNCHf4kmF9LS+GZoazz//gpA533Qyk+ZDthVfRYgJlyNXfFXpi1ksIYOWCmlP38TQjF6WiqvDwwnfslqAI7bUvl8V678GAiw0NyemSvXVl7ACiThOxa4UceCEtjVohsvZaVX3p4MqPNkHL76b2nZLSGRmbvbM3Pr7+r9wlDn9TAzhIaAyQihuuqHMjpVwN/0MBauKaj0vT1orKMdO0mhBBsWHCSyh06sYlf7VvzQ3U3Ckk1ElsKwGprRC5Jhd1jZ93YOYubmPysvYERtr2Fl951AMWS7YknYvhcdAzffDP/7n//3r6gor4h37j8BgBHjphKf2jHwfnRnP2Zu/KfyG9mBFHx1EBfqZFcMszv3ICskl4QlW0jOh95+Boq6NZjdtvw3hNT4tKDq5Fd0ugDXqt4ktI1k5DXlo7xqvvC1f99G9hU9DMAp51yP2Rpaa10C4J93oZ+fbXwfcSymJx4MdGYlaeyAtDTOmZzGEJuBhBapDJ9wQcBj4Ka9LflxdyoAE6Zfqc6RAcr05zswqMq+7cDMEnqQSxRujIRRQDeWEZkWydfDWqMv+BWANgego58xC3tC4Z8Udf9ASQabHV39H5eTUPUpF+q4XAikpTFTa8PMbX6uHJqAtmV/t6MuzqWl8X6H7Uz7ofribgwsohf7iCeGA/ThX0y42du+K7PK2nhjJp1HZFx6wG32gV8H0NZRQqu2nWndZXDANtvCA71YaK5727bEYeX15wfT4R8PId3aYIyNwq0b0DWDqhZpBjTdo7ZIDawJEbyb9B3trB7aduhOj6GnBPyMpVu68Xeeus5Ut7atlQduGV153WlAbNl6Kx984gRKYVNaLK1H7FeLeVTd9Hs/16QHXAh/p6j36nuwIxdaVMfJ5PNuxmiyBtxmZ143vnKZBgCXo47H5bF63GX3Z6VxYXIG/WyQnJbJ4LHn1KGdUKFtW1U8arstBTaozylpmco7/ewkLllPiwLou6v6y0D1S89NV/cLU5MI3ZGFQYcxG1V7tyod+DkTiszgCMlg/wnqhDn+jP9iD48N/DvdNIqZO36s/sYa0Ap1/tsElABpaXw9rC36gp8BVY/o5GfQwt7QsnWHGkQZXuW8/TozOJ/XMeLCjZpcYsRFBHncOWIA14xQ/WhGD/zfL3DbH9U/o+PlsKYsbqC25iTu/FWrvi7iUOvCgtr+slHrvGs8C0P2+a1LFBLCInphp5ieLMaIB9LSuHVKK1pa3HTs2psuA8YH3D4Wbe7Jv/mhGI0mJp9/mypnLesiryiMDzb0AOretp15xwBmbppf/UtQ9r1bAKvxxulf1n8Y80eojagubdtSp5k3V/cHYNiYU0nM6BKwTJf9M5QeNp2MzHb0GzWtXu0EF0bW05adpFCKFRMuIjlIJ1YRmh7J84NMZCzagtUNozf6PwOX1+uKzTBn1BD62yA5NYPB42YELNPZz73JO/PO4fjhLt7/yEhCgrpm7PRzqcdgUAPR5p+oMeBb+J2hnM6H7CYJE05c3gOgYsRFi1aFZJ0djacsoV633bDUz4Sh8ybC293Vta7WZrj400k8sehpdhtSmHSyi2lnmejbt3LS8OJilax4wT86B9YfR4zJTc/+I2jTbXjA7z35n36MtVmIiIzmhKlXBlw+K6cFX21vA8DYKRcRHp0ceJu9dTgzt/6mrodcDnTBdxyuqOyxbdmtSYvdiBY/FPq/6Et47imr/JX3ARTvgbmnsT8/lE83dQZg9MnnEJWYGbhMtw9m5uZ5lT/fCKSj6r8G1PGjRH3k0i6DMHfeRCfHPjj3Q7V8xSzqez+EfR973yq/OJS1S2LpM3AbRHaHbjMhabRKbFGucBvkLoffJ4Pu4OoFwbVtJ26M4ktPrvftvngfTq7SlDnhLNVH5DaAwa0R6oF8kw46hDvgpa/UtVIAjwZ3HAcLk8FTNogw3GEg3+wBDeIKYedjYKkwuM9hhOTrYH9ZvLYO+clsDt1FqQHQIMShzmMhZfvRznD4vWVZ94em+npnWZLo4syC/udBxxMrjxEBNb6i7Ld16jBsgZ350b7+4u/ehhMqTLhZlAR9Lyr7DjoM2JuMy7KfxRGluKtuc1WElcK1DritsxGLzQojZqn1BmpyWnm5ql5vurczM1evhEHADFQbz42avBU3QK13Zz7smwdF+zjgas3Emx5n7r4JjBnp5sZbDAwdqvmdXA+wYUcOFz3cml9j/DSa/TC7YNgeOz+l+H6nNz+Hcyp0922LVOfUIou6HtouJ4YYvZDFEaWUBBhAbHXCwB0wNGY4qRY3XXoOoGOfEwLXNRd2pfOTKzC563ixOgwWDqt8rijFwhZasp00SrFiwIONElqyhbQ0+KXzFkb7uVSxhQy2kU4xdmLZT2dWYqcEhsezMLR63WAnyaynLUWEYKOEZHbRnrVorVJY2GFnteVdGFlCDw4QgwEPseynO0sxpKVyx9hkejhKSUnLpFOf0QHbCfO39+OPnyKrX9sJsasTkN1d6dqOR4NXVpRdtx09iaQ69Vv1YuZ6P4MRE1HX8iyo498uIB8WJ47lC81Uvc4Vj6/e70a11wqBlok8M6wdFoPOgOEnktaub61lKvFAhxVmttmc6BpYXLDtcUgsrLDujZB2rbrWgQ79dHjuX7V96MAd3M393IYBj7eeWU7Dw4C0nZxz0mnEF5fSsVs/Ulv3CLguTt83gJE2E9Gx8YyafFnAbXzH/hRm78wE4MSplxAamRhwXdy3aHhQYzJm3t+OmSsrjFhtB1yPut5Q8RjnBkoh683evLghSa27kcBZ+PqqqgwYxw2EJnL73A6kW9x06t6Pzv3GBSzTnGVjWPWli2vG/Qy9Ad0KqSdCwuCyhLHh4C6BPb/C8pmAh59fj+ajH+/nFS7EZNaYPFlj6HAD/furCYS6ribM/P03LF/i4ow9ZsbM8RV1Dwn04V+ySPKubwNuPBi5XbuT/91xL+6yTuX0XNj6BNV83gEml82z00pt3Pn6KN82rgHTgRNRHUjlv1X5/d/TmPlTC2ZuWOB7wzhgJqq+U74uyg9382HF30P483j1b13GZAC8tEzt23W9bnvRP0Poa4OU9FYMOuHsgOvu5x0t2fx3MQkr9tQ41kAHvm3rG1u6sGAsM3f5OdCmVvju+cA2ICWNzzpuZ/L38BGncQnPk0MsJpxExJjp21fFlM7Lg/nzobTQyeCem3g0qUON1xNW0IUQihjIX94+6WeG2MhYuB6jrtoJ/trPG6NVW8FhhA/GDGC0zURUTCyjT/1vwN9p+b4W/PO7XuvvBPBnGuwvG5OxZPxwEs1uuvUeQvteIwN+xuerr2DpK5v99zO0QB1r96OuKQCrunbgr44OEpZsQgPG1zCQfU5r9Z0BQlrBSD+rzo2B+QygkFC6spwk1LW7H+KnM8+YV71MRiAD1bddDGwGnPDe8GTOPE51eJjccNpKeK/KMLd7h8FdI3x1zfQCM9tCnaCp1yx9oXJfw/et4YSzff/3mD+EiUuimLnna1Vnj8TXZ28yQJQRbG5wecrGIUazcG9Ote3pANGsoAuFhKKhE0ohXVlOVFoEl5/aku5WnYzW7el3/BkB192qHR2Ze6Cs32rGTRjNtoD7tndMxvETSG7dq9Z9u7jsHLm9wjly6xPQosIYiINWSL8G8myADsPdcOlvnXn+j2f4jRGktnAy7WwjAwca6N3bF2xu82Z1nF3wt5N+rk6kL9qA2aP2I6Of6tq6WDW+yWGEz8YMZLjNSFxCEsdN/E/A3+nNXfHMKKzr7Bel9wErC2NKAy9YJrbEwH6raruEOmD/g2CtMjHp5GnwTVu1DSYVxTNzNSStVdfQx9Qwib/ifhTeSs0RrWoTmd76aSz76cpyLDh5f1x/isL3kbBkU4395IVm1b8HUOCMY23xAP/7XXlb1Q0cRB0P0tK4f2wK7R0lZLbpSJuuQwPWbz7MbU/BxlwSVtZ8TKvYR2m0QGK6/+tyu0hiGd0w4qYXi4jlAHpaKu8NTiBikaprdtsDGX7ijayJg/VqPhhbUtsQEnqQhLX7iCmGwX4u2VQcK+fSTSzNH1v5d4oA/ofvmEDZb5UHPJfGpaNb0tOmk57Zlv6jpgfcZn/Y3opt/xSSsGIPSQVq7FFVOup6k6fsHLnjlKEYNZ1Bx40npU3vgOftWW/CKd9Xf8/VdCSLJEqxYqeY1mwkne1s6N6fn8eqxtrJZ16NNSQy4PHmr3eodt22/DN20wIXJm/bxZSWzCcdtjPFz3UUHVhKd3bTgnS20Ql13XV+366szCwkYcmmGvcjHfi6wgStFROGE2ty06PfMNp2Py7gupj0Tz/G2SyER0Qx9vSrAi6/80AyL9/Xy/851QB0QF3jLb8Wn5bGXae1IsVc97Yt+Po1HZi5kJd5m3O99dFyGm50jFza/nMuaD3Z736UTSyL6IUJFwOYTwjFkJbGTVNa0dripn3nnnQbdHLAMi3e3J0F+eFomsaUC+9Un1/L9lFYYufddWpC74hxpxOf2iHgNvvIVy2wbtpNch60yVFzjCqeL5wGWB2vxvjsiIQoc2ccg+o538CCqo8fh6qb++lD3G+KJ3lNNg6D6udqewDWPl29z7jT5bA6Tr1Pn9x2XGRVAYHqc922FAuX8AJvcJ53/ap1rSqgZ6b9xikdRrL2h5u5n1spNYVyxlQ3409W/bkZGWoahMOhgm798w/8++NyuqVeBgR/3XYOYziTd9lPHEacuKv0SRtwk5qm8UgHIx1+6MJlPMdchhId7uSkiSYGDtTo3l3VyQsL1Tzv+X95WJr/DKv7XKUuqXmgZxa89blvNTgMcOrpsCFGHQNNHphZdIhtW8rWdRK+saRO1HXeUvizVysu7pbFirBi6qJHFkycM5SZW6pcZLKj2i7lbWgnahyzC/7tOIy1GUWEOw2MGD8j4Dk1pySSzQcj6DVgO0T1hK53Buz/vWHBMNpaPbTv1JNugwPv20u2duOfg2XXbS+6S/1MtWwfRaU2Pl3YLaj5BldkD6WrVSezdQf6HH96wDI9/+MlXPb680REqCA2gXy3/jvGvTcOUHX+qSvh3SrthC/bw8TyKZc6fPmXmm+QSyRn8zZfM6HSdcVy5fveyJ6LOG3MNQCccvZ1mG1hAfejp5cMw2rwMGD4ONLa9Qs85vSHWJ5K34+7al9KDSb93p5uq9oyc//Xqt1SPj8tIgwsZlVnsXvUXBGtGKIjeDimC5FGD70HHk+rLkMDrounnmvNK/M+YzndmDbVxUWXmBg82H8A15IS+OnLLRz4/XRCChwMGX0q9rDY2rePSFQ/YVgrNanZHFm2jjxq3LOfOTKPbWjLih0HKDqwH4dRzcMKL1XHEl1TfdF5VtWG6bQPIl1xtOjbAaj7mAxAJQ45cZkv6Fo5f2Xa2IpZ+3axKLyEwhr638v12gVd9oVDFITszWdzFESUQoRDtcV01LWWfKv6HgkFEOaExI39uH3QP3A8YIlQwbJTxql+MXuievP8DfBNZ/A4+GPNEH59LZw7Bn4L41HHo9CWkHScCuRqjgB3qQr2vfE1ShwWZn/SkcmnLFHbUOtLoeVUiOkJWoWTZIXvf+svwc03WJXbkbnG4MZkvP1cLx6c9yYr6cKo41xMO8vIpEkqiHVFBw/CTz/B7lm9Ma5aRHK+Om+3z6583taBjTHqvL0nDLa6JvDsmldw2xL4331uzj3P6A0S4/Gom6b5AiUCzB+cwYA/6zb3oxgbE1Ke4uedFzB8mM5Tzxjo2lWVyF021RTUZ5QHjiJvHQuntaf3bCjBShZJZJHknQvlxIwBT9k9J/FpNh4ft4yi7Cx+yVTzG8tvdheUGFU/lskDqXnQdS+0Wt+BO7etUe2/MBPER0N4SFmEvbLrA1aHmlM5aCe78lvwddl123FT/kNYdFLA/ei3t2F4lbZtHuGsoAv5hOPGiI2SsrbINhYMH8naLvnEuIwMHXd2wO1pX3Esn7vUtd3RE88lKqFlwDLd8u9wMhtxTAb46vA6kEM0W2hJPuE4sODAgoZeds9BXJqdj8x5vjEZZtR7VZ1rVj4XwAJFI0MIiSpS+2j/siQR5de20cqubZcFV5l7GtuK3fTZAPusfjoza/D1t+mcFMT8psJ7QghtVQSZZ8PAt6o8Wf2Y6dJhytwQdjuL+Dut9vdOylN9Cq1C+jDI4yI+MYkegyYE3D6eKUzkCmsdsmRV0DPHyuLouvURmdzw4MJ4HHn7iC+EljnQ7kDlMcOlRnW8WR+j5g5vi03ghV77KPHXIeZHXCF8PjeDIX/VfW7rzE4dmLmqLFaEBd/cRRN+5y6SFMXCrFxvO7KAUDbQhnzCKcVKKVaMuLHgwEopSWkmtqZs5bgg5tsu6N4bQ9jeuo+d9XPd1o2BLbT0zg3V0AmhiDZsIDnNyP+Z0quPyYjANw/TgBrXpAMl8It5Mr/lOnzz0KPLfpvy36nKXDNio1mYXb3/txSLd1yrAQ/R5NCDJZjSkrn61MygxmRs2N2KNi02qWBmp2xXSbUqWjaz0jwfl9vAaysHAXWfb/DIUwN4/O9P2G1I4ar/ujnrXCM9elQP/ARqbNDNL93DU7l31ryu/LjrxROZmVXlh4pAzZewoE7KDtR4x/hEZmHhlL/rPq6aFFjYvfL2UYKVjbRmF8k4sGDETSiFtGEDLdLMPH56JmFGD30Gjyaz06CAv9O3H2TgWqu28V5Zar5cVUVm+KmsrzU3PIk9LR20X76fxELoV8M1sLnpkGtTY152jRxOnMlNj77DaNsjcL/VZ5+k4Vy3nRBnzXMgCizwW4Y6/2+PiWNnSzcDF+UQWaLmx1a9puUyqOtNuTZ1nLK5enP5qQvVWP6k8dDqHEge60uuA5WO6XOWjiamYB19B2yF0DQVfDJ9MkRWichVuA2+akdJiY7N4oCIbjC+bECJ7lY3NHUrzoIDi2DuaaA7efrzOFJXZGP2wOBtat5iVdsiYWmiWidEd+fgYFXeYNu2fQaPJjohcNv22z9g3Bwows5eEsgmjoNE4jFbcRst6AYjBpcDo6sUs6eUOyIf4I+DAxkzBubMqVr66h54wMMttxjq3BYG+M/VQ+ljg9T0Vgysw3XbJVu6M+vptMr9muVz16NQx0EPahxHKXhaJPBaRhiJSzZh9qi+WX9zrir2xS/UujFz7bLKCxhRfSXh+OYJ5qrPWJM8mA/2Rlfva41C9eGUz6UvGyeyvWMc/QflkWVRJ16TB578FlpW+M2e6qeu/+llx7i7PuzEzNWrKn/n8ve2lv3vKLvZYEd8V2b3U+3TE0+7hNCowGMy7l04nASzm+59htCuZ+Drtif/05fxNiuhYeGcOO3agMtn58XgynfSIqUA2v4XOt2g9r9yugcKt8PBFd4+ot1ZobRIKoQON0PX21Qwe10vi4Ogq/0uZ4l3XNoLG9uyePNuDHvz0XRILoDEAtVmLTWqY1hWmJoLln4Q3KWRhGwawl3535T1QWgQEwoR4apfwmRUc5WiSmB4NpigpMSIzeaG9ldC7yerb0zLZnrPeXlF4SRetocSp50339Q55xxf667icMqKj5UWlbDyhHZBzduZ2aZv5TEZIajr5hZ8c6ydeOcVrYwawKK2HkIKHBx/8gyMRkut80g9Opy+I4yi/ALmpat+T5dRjY2wuMFpBLNbHatbH1Dzd7u54mH/PmKL1HG/7QHfuEhQc3LXx6i+0wMhMH5kOB065EPicTDy51p/13Ln/xyJac9BFiWpzza71f5kLJsj7jSqv4mFMMgIt4xD9Q+Mngdx/ct+9LITTNGOavV+qDx2uwQr62lLPuGUYKMYOyZc2CjBRgkxmW4mn7qGFWGF1FlZoMC6zjU764wC3v0wjOOGufj2eyNWq4bbrdrnmuYbTlo+dNNshs+OT6b9rzEU2WPxxCfiCQ3HY7WXRUE2oFeKJVXKgXQbi3fm0nqdmZZT+6mfqXx7rRhdvyzWWFiiC8+qyyvVbwoJYQstvfWb8nGL6WwjLQ3+6LzJOybDg8ZWMthNC2/sDjfGstp8KWEU0P7p9YTEFELri6D/S1SzbGal7SOvKIyvFnXAVuSi35CxRMan13qOLHSEEHa3Wm+vvQbnnRd4XSz7cS7zf1Qx9Ooy3+DRb67h+vcew25XyQDq4rNpgzAvUkk0htRQl9hvV3UigB2JmRxMPEjnZQdIyVfXLKpeCyo1wu8Zau5Ath3OWa7VfYxqG+D/UElnRv+pEumAatNrBr/70R0f3829s+6gZUs17iIQXYdrOl3N82seJDrRwp136EyabCApyf/yeXlwxW2teStuU92+A3DhzmReHJqFQddh/BKI6lzWl1u2ba+4B1beW+k1DywaHtR8g23b7aSnFUPGOdD3SdU+qmV+/50f3co9s+4KKhHIzOtGkNyIc+lveO8hHvnmBjIyYMuWupXp5mtH0MripkOX3nQdGLjfavGWHnhm76/zOW9NvJ0TZzjZHOqq0/KxRXCWI7j5BoUlIXz3Ziotfw/DnZyGJywSly0UzWJW8xENRjTdQ/nEGXO0jXWd/iCkwEGvAccTm9QmYJ1cu13tc3ffDXfcEfh7PPn5w9y0+CZKDTpoalz60G0qxhuo+Qb/JuPd4dvuh+mflLVtjah+lSh81/yqxq5LiGHWzgPeMRnF2NhOGntIxIEFJ2ZcmLx9uVZKadW7kF2JS+kx20A2cWQTx35icRptuE1W3CYrmseN0e3A4CghLs3OT6fnB9W2/eQNOPUHOEgk2cRxgBjyjVEQFobHaFbrwuPG6CpFLyjE0DGK9ePVWL6TTr+MkIj4Wo/LHo9G3AVZ5DgSuf12uOeewOuivO52110wc2bg5Xdv3sWXL54OwNjJFxIem1L3+Hjj16jEp1Utm1mtTvTXWxZS5ySQSxSFpkhKIhIgNBTdYEQ3mlQ8R48bCgvJynRy68jv2WKvWx9iUj5kPaq22XvugdtvD/yaJXN+ZflXN9U5BuRV3zzBU39dRY8uThYvV9fxy+s3FRN/ecp2vT17fPPDvvkGTjwxcJlW/DqfpR9dga3IxciJF2AwGGuv/3rg3T39CClw0HPAccQltQ24b3/1VRoTgugjen5wMjePyCLPXLfzcPQHL5Oz5kKsVnU9M5CcHIgpa+N+/DFMmRL4Ne++vJNLLgvBHh3NE495OO10A2Yz3oRG5XVMg8GX6OjdYZ1pPzcEd2IyWlwsbmtIWfR7I3p54gBdXawyREUw6DvV31HXOteWLfDGwAm+9rYR1f63o9o6ZlQfQHl7JzaR+7p3qPOYjPziMNpcsYS9xa258ToXDz6irrOXb4NQecqWwQD7d2Sx46z+QbXZ3h+eRqffoikJi4PERDwhYbjNNjSTqex30tT5pSxb3WK9Ozn7v+CO4m/V9fNwC8SGQ0hoWXxXXbVVLU4Yvo+lhWGcvLWEbfa6nSPjC+FcpxqT0a5TD7oPnhjwHLlyeycyo9cTEmWFrvdDm3N818UBCraohIHFWfD7ZJZs7kjP25YAap5DamrtZfr4YxUjODoaVq2CFi0Cf49XZz3Li7/fxOKwQlwB5r8l5qtpJNeXxSqvazy9YOcbLNvahV/eieeqgl8gMQaiIyHUDharun5pK1tvFgf02QhG+O0tO63mxJJDNCWhsTgiE/CEhKKbzGBQMRE0twvN7cIWaeXpwUsZajOQkJjC8JMvDBwnY09LftyjVsD4aVdgD4sJeK1w3jswuGwsZRF2NtGKHKK91wrL4y1acBCVFs6aDrOZWjaW0oWRHaSykxTv8k7MWHB46xL2TmGsOO4gIQUOBo86lZDw2sdkHNBh9H4bi6J8B8ChW33j6Mvjoewq7wrW4OHFfUlM1Yh1GxkyNvB12/UH2tDp8ZUYdQ9ffWdh+HGa9zp71Ri05eemx68YVBYnoxOtuwwJ+BnYYOHP0GO2gf3EspcEVYfCjEsz4zZZMbidmDwOTLgo7Grk5hP+ZGUdx4B1OgAry7o76PM0tPtv9YWWzay0jf+7qTcvvDmR5A06x905DM1Y1tddFs9LB28cDnRYsjmEa95QbcG6xua95T8D6OOo+5iMJdndeeSLs2mxWeeEuwdjtqtjc3msMW+ZQMUgA0JnTaHPvLpfG76txwQilnQkLCWSzmf1rPykn76PiJgssub8Hy1/Cac4IhF3VCwuewRYLd46Fx4PBt2N7nBij7GzuOt8YopK6dJzIEktuwasSzz/fRsuzdsAYRHQY2h5YcBQVhZzCZhL1fGj3b+szmrP5Y/eS8wenXMf6058ut0XW5yqX0lH0+Dl7/pRciCLX1r6xmO4DWBzqbiUpvIxGQfVmIy0HSMIWdgfS6SdXpf2xxe/vOyNK+wgug4Ocwlxv14V1DlyUvrT6NtS6X1SC8ZcmOFdueXbV4VVoZrs/67ih3dWkbLPzCkPDvIt6y+Agg7FRQeJ/+rMoMqkn5mM9k4NE6H8kAQXh8jhcBASEsLHH3/MpEmTvI9fddVVLFmyhN9++63aa4YNG0bPnj158klfB/3nn3/O1KlTKSoqwmw2k56ezjXXXMM111zjXebxxx/niSeeYOvWrfX6XIDS0lJKS30Nqry8PNLS0oLbALKyqvcA1ZJ1ZZluZGN+EVn5WewuUA3fsLwSogpduN1uPNFgiIIQrZSkkBCi7FEcNGey/kC+d/mKr3FGuDFEqcdSQkJpEWLjoDmTAmeY38/IDTVBFIQbS+u0vNvtxhMBhrITc4o1lBZWGwfDMynQ/b/GGequtnxedHvynZaAZSr/3lpET79lCs8rxWg0Bv296/U7RUC4XkqIXkqSNQRDYm9cbif5hVspceYQFhJGNCZC3GaMRgO61YFucqLrHkI1J+GWEHJiTmDT9j11/53C03HoBvIKt1FQuo8IeyiRHiOhLiOgg92NbnFg9BQTbQ+lsPM5LCkuYWvuVrYdVCfPmH0FhOeVYjKacIc40ePUUbWVPYJ0ewiO4mSKc/SA39u7rqPaUeCyBtw+yn+nKFsUedHtWXdgv991lxtqoiDCBkCb8DBSw8Jw2pMoKqbOZapte6qpTHtb9+Zvg8P7O5X/VtGF7hp/p5IcFzkFW8kpysKiuYlyaEQ6dYpCzOghbmyUEmsxERcWhSNxTI3rusYytezG32Y9qDLVtu7Kf9cWYS1ICk/CGh5FaX5ujfuRv9d0S+tN67B0KqkhgzGOXIhsA2Ht/C9f9Ri4cwueS5/E4KhbY7ecx2LC8NksVoeV8MO+v3l80ztsKctqPSi0LRckj2BMdFdSDZrf42zSjoNc+uRc7/u9eVVfilKs3nVhjO+CR/dQULQVp6eQiNAIojQLdt2C0WDAbS5FM5bi0T2E4CDUbCM7qub17W+b3du6N7tjkqrtq9GFblxuF1q4jh6nEaaX0NIehjV+CPtMUY26bwe7H5n0ZFbk9WXFLgsuzU6IPZYwLYRwswnNYASThm7UATcGh4fYcJg8JYm+n41mS3ENkebKhBgsrOt4OUaW4y7dTnh8G+zJwzGFp6PZWqiLMiV74bfxKhtnBUt3wzzDBHa7fKOQatsvyGzJfpvud13khBpxxxmI0ovr9LvWtG/va9OH+Vppnfft/NAOftd3sGXyniP9nF+i5uXR7m1fg6VWF6ImtEX3qpxVrqJlMysH2t+tsTHmv2SVFNX5eFPTMaqmdVfr8Ql8x6i6HJ8qLg/1O6bVpV5XZfswhLfhffbx2vYvA66GdEs0CztczC5jRI2fUZffSdd19mVtIGvvRjLN8UREhlX+nYDlTvhj7xa/x0yAj6/sQXZqmHd7yg9NxaGZOFi4jcLS/YTabES4jYS5NEpsJnSrC6teTIRJI9oeQl5szfWhw3WOrHoMjPojh3bv/h5wPVQ076Jh7B0+LOC6KK/fFKS2Z294dMB9u/zYH6F1q33frkd9tur20TGlOzeteZov9wT+7ks7XE63pCHB7UelB1jjOcjewn2Uug6A0UCIPYRQrNg8GrrJAcZSdN2NHQd2k4WdraawuEJ9NmPjfu6+4ZtKH/n8Q0PIz7Qett8p6OMNVD9+BDje1Hb88FemlMTWTF54EztLAmeIPjGiLbNan8lqLMzdtdF/O9JfWyQkg3xDRMA6VPny+9I6k9Uis87rLi4kDld+Iht27fGWqepnVD3e5IVmkK9F1Pl3SrbvI6R4I0ajk5C4toSGJWCzRmA0haJpBnR3PpozB4/Hg1ayDzwO7PFnoZUm+l/fjXiuqO0cWVt9xd8xsJVtIC2tPetWpuJlUPRy2cayHKK6VN+Ils2sdgE760NICnz68qrtmOl2u8mPsFb63i2TO9badqlXP8Mh1snjQuLID+3AvwUH61wnD2pdOHJZFBvDIpslqDI5ipPZtG1Xnfft5IxRpCYMarIyNWadvKHatnOyFzB2g5p0ZtKM3NLmPO7ucGml3ynLsp/k388EwIDG2SG9eGPkS/7fH4I+9h/KNl5eh+rUfkrN67oeZfK3H9W6PVX8jEM4BgbbTqhteX/Hm/LXbNm1us7Hm2D3o0DthKplWvDHqcz7pyc2eyzXX2+mUyd1MT4mRo0JLp9c5XKpyRy5uXAwZBGLshY1WNvW3+8UbB9RsNtTTf3Lta2LqsfyqvWP5x8aQlaryKDbCeX7kbPLKLKiWwTVH1Nbmz7Ytou/9lFj7NuHuh/V57y9r00fv79tTdts8nvb6PCKn+hPtfjl6tH8PKF/o/Wl1fYd6lqXONRttuq6u233u6wp2IwO2AxW8sb9hnl/rnf7KAhxELXsQtx4MKAxJCydxwfeWOO5PtDvFOJYwTmxf6vpdn4u5upRPVnc8xW/x6dDWRdBHZ/8HJfr00dUW52oPvt21f3ohE7j69burFCmivv2/CXxvPPSveh69dFVBoOLIWMX8Xs/NdrEiIHTU8bwbq/7Kn2GK0zHvnQGLl2NqOsWmsbbvR5g7rqfG+y83Rj7UaB10VB9rbWdI8lsyaKSLY1WptqWr/g71XUbbIx2Qk19AFmtIsm0RXDVtJfIzw9j5kw1QNvfZLuqli2Zw1uv5vLYs1MADYvFwIQJalBq9+5qgOumTSoB95o1oJ05iN+z5qOjY8BA3rjfCc0pqLQftV59NZvK+lJCV55N0SdvYrXCl19qjB6t6lcmk//yOJ2wPLtynStQ30fVazu1/U41re+qr3no4ZEUZNoqrWs95yCD9dcI1QoxaroKANDyLBX832CB3GWw6kF8kaCB4+ZA0hg/P/zMan0Ai0oMLOp4P1uLC+pcpmD3o6p18oqvqdq/NzBkFXHadrTonjBmvhrEbKiw4vwEDVlUAosyrmCrFlm363LmcM7/dxY5zgJAIzMkhZe63YZ28CAcPMgaw24u3/E6oMYzXRE/gAtbTqLvv3dQqvvJ/FfFS+kTcVhj+O/6172PfdDrf5xu6endZj9wzWfalme8zz+bNp5hLYbRdcGNAd+/oy2R+e0vZIshtPY6eVTlMRkpLUZx6ppXWVu4JeBnJJrCWdzxUpLienrPq3nOAhYfXMuszbMJK9WZmNCXLvHJ2AwWdfzIex+cf0J4G5iw3v8bL5tZ7XpTSHw32hiX4tHBkDEVutwOUV0rv65gC3zdngG3/8qCTX2ZcLKJWbPUQHFjgMHH+q5d3PHrndy3/tWA33t1xytoGd+H45Y9wvzc5d7HzZqJshw7OHGjl+1vds3Mgg4X07nFYO/vVOwuYUX+Rr7c+C0UF3FyyvF0SWiJ3ZUf9HG2/HiTkm9jwLmfYgziuvvSFCObbruMLK2oTuft+ozJqDpOpOJrGqJ/L6jrnWXmXTSMpb3aBuy3qunaTn2PgQ3Z91G1L62mMpUf0zy0Y9q/DwOqH+vC9ElcF32imo0CfOj4mzt3f+J9/ZsZk+kR04cNeUU89coIfvttZK2/ae/ebr4afhlJj/mZEFyDX64ezcazpzbqOTLQ8uWf4e96k7tkPZfGz8WAB4OfOotHB8I7siL+ZkI2PUsbrSyJqDUeWk5XQa1CMlSQhKw5MP98wMMih4VF7e+u8ZxatUzJVjv99n2ByVOCIXUC9HtJBe/zONQ5vlz23/D9AEqdFvrc8Turdvahf38jH32k+pQcjupBGMsfW7ZkDhtXziUrP4vtOQd449mH2LurJR7df6Uo7q4EsjU1ut9msFB04p9qUHOFPqJn8+dwxYa3vMfCB1tMom1YZ7Lys+is/cqwsI011wWje7Is6X/eMuUWbufS+D+INBb7XRe6Djuip7Ov53W11tMCbU8QXJ28LttsrdcHDqH/Bnz9MS+/3JdZXw8DPIwbZ+C222DgwMrBmZxO+PlneOcduOE63/o+5HYCVOv/rant3JTXUYzR3bA609i2+u+GuZ7QAONEghlLWV6mjwr/4cOsH7z71X/SJ5PkVpEMCm0GnsiahQs3BjQGh6bzepdr6LPwDnJdKhKVAQ27wVI2eUSnWHd4WwdtLDEs6HAJ24xhNV5Lbow+gLpcSw6079V33/ZuH4aOnPbPA2W5iTTGJw7l/MjjVFQD4KPSv3k/50/vb/Vq2HVcfdc9FBZbuPxyI4884qtrVq1zeo+9QY4nr89+lG7pxzXL3uHrvX6ymVbw38ShPJU8Gi2qLaX2DO5d/xqfZf3MqoLqwRtOiOrGDS2GMTIkkYdyV3HLpg/wlP0SX/V7nPGGjt5jQV5ICXHLL8apuzGiMTQsg1/6/q9Rx1tF2aKqH6MauJ+8tuuXNfVbNfSx/1CvywG194UGLFMWZ8UsoI11X7XzsEfX2B89ge0976pTX8mhnCMDtY+q1n8DjiMK8prFoVxP8I4RTOrvt61T7+uRQfZhH64xyQ2xHzmKk1m/eQ/PPHce61f3Q9cN1KR3LzevvfpjjfWbprq2E2xds9Z9Avzu24tiY/i8JCuo600lOS56ud4i1bTTt08bbRCSBmhQuBU8ah7V5TsMvFgC7rJgXcuHf0iX0khvmVabs+i0+gYATBg4P7YXF/c6r9Z9tbZrYC+9ejrLFo6scX336ummc+ftvP1OBsnJGr//Dq1b19yf63SqGAiLsmrvz/VXpi8+7c0Lr50Mmk5MtIHp02HGDOjUSZ3vd+5Udet//4VzzprHtOn9cXs0LrzQyMMPQ0RE9TZY+f8HD8Lni5/gvN+uqV5oP2a1mk5a68FB9REFOgbWVv/NLs3h1/0LeX37V8zeq8bvjY3szfnpJzAiNJV43PUa/9CqNITRNz5f936ry0EfAFp8Xxg9Fwjc/7tsN2wMOZ0swmod91yUYq5xTHJTtSMr1n+DHQN2d+lWvstZhhsPGhqLh71HWpEJ9u+H2FhOWHsbi/LX4QEijTa+6ngdG/aEcdP/zSB7Xzy6biQlRV13GTMGwsJUkJePP4YPP4R27eCVb2oei1KXa2CBztv9YibQ0tqTvSUHeHfnbD7N+pl5OUu9y3ewJnNWi8FMTxhIptHcIOMfats+7I5kzrv/fUpKLdx7r5Fbbgncx+x2w9K9dR+z081wkC45v2DR3DD4fUibXPkN/WzjAHT7Ehwpvv+DrP/WNv430+4gI3QlEeyDng9D5jlgiw9cphygw+sQ3c1bpsK9O7BpFowRpkMba1u6n7zi9wh3rUeL7QXH/+hLvKEZfOXa+wf8dZavqA4IMYMWkgR9noW0Sb5gcBgAXQUzndPP+xrdHIM2+tey4MSGyhcxq3zGohJY1PZ2tjoJqi5R17Zt0ZbOXHfd9TgcZp580sB//+s7r/njdII5u5Z2J1TaPvTSHCInX0R+sYX779e45Rb/71tVxT7EQPXf7B0DuP7ppwB1Dbe9n5hawX5GQ/RbBTNuMdi5Hw051+xQxqXVpUz1OUdW/IzDMXexYl0iJSyO88I/wKKVone7D63LrapAHqcKkAl+r2+TY2BF66e4YO3z/JO70u8219qWwF0pJ3B2ZLs690uUb4PtQvIIDzlIiFkjtM2pmMIzMNhbgL2FOo79NqHaXEc9B7SKx8yK22wDzbctCDEybGYGi4tqD9R5UcIgXkg5AUNUOzwhbXhp22d8vOtHft6/oNJyUaZQpsb14/rEIbQ1Wuo9J2++s5SbVz3Nbweqz0c0YWBUdBceS5tAR5Mt6D4iLb5nrWNOG6Jfsz7XSA+GZ7I+L7/OfQC1xWY41P2oLmMymqr/t9b6bx3mgdVWv8nb14EZ9z+KR9f49FMDEyf6gjjXxOWC4p3r6fnR8Wws2lHzgsDliUN5Onk0yzEFfW0n2LG2wcbuCLQuaqqTV9LA822D7bdq9DIVr8Fd9Aqa7sDQ50lof4UKtFy17VmlrqnroMUPVGOujPbqy5dmw8HVlV7jSTgew6ifyv5xgGb2bYjLZlY+h+UYoMeXYK8QkTnIPqKKv+3hGEtZ9RhooQXL8oeybJsBlxZCeFgsVksEEWYjFo8B3WwAowddd2N06ngcVv5ckcLqVXDyKfF0724hMxOSk8vykBnVdU+nUwXkPHAASFrEsn3Na0zy4ZgjEx+fwaSFN5LtyCGQOxNHMDlpNJsKihts7uKhjGutb5/05ILvCXftR8s8Bwa+Wf2L1tRWNYXBVD/ZeqDGumOlfa+BrjfVJWZO1VhSibZQHnv9bn6YP5STToLXX4f4eAKqa5utLueWmuoSHX5eSsfXvgpcmPKf9fwJRF8+s/KDDTm2v2QnW9zbyCvehzk8FpM9ArstAospFBNG0IvAk4+u6xidBzHqLsJanFvznOGqZSrZTmnRK1j1A+hd70brWiWieA3b37LdsDF8BlluY53btoaItpy56DbmHljiHcNfUZI5issSB3NbfH9+yYlk7towNu/RMVjDCA+NJdRoJ9xswmAwoJs0dINHBSJ0uHn+1a5s2xXO9Ok6776r9q/axkm7XLBqRc3bk79jvzGiLaWxHYKakxfsGMFg6+QJdiuGCDv5xfsIiWpBWFg8Nls4VlMoRt0AemGF7SMXIx7WJ49ncXFp3Y+BuelkbQll4+4SDhS6sJhjCHNbCceER9fQbQY0sxuTpxS7x01CtJ0OZ3Xjy/Vf1um8HeuJYc7sE9i+NZq4pFiSUiKIiQojOtKExaxhMBnQAd3tweXU8bjdnH1CAaZ9vrp1pW0cgq9DVV0+2LZqArjuUYdlvc9zaO0u9T2ne9SY3286V08Us9PEUu0ytuRHsCevCM0QQaTLSKgD3FYDmt0DupsIjCxdOYi3vj6e2FhYuVLNu6ypH80rK4vcrWvp+8c5bCiqOWBlhNHOn52uprM5pPY5wH7aLntbdGN3dHqd2kfdLR5OKPhF1TVP+BPiBlYvzLKZVRIAGpm1tDPL9IvJLg1HN1mxWSIIN1qwoeEym9CNOiZcmD06MSEGuk0PZ9m+JY02lz7SEc/PP45kx9ZoWqTFEpcQSmR4OFERJixmA5pBU9usx4OzVMeAiy4nbmbZvsWNOpc+KXkoiUmDeX7Lp3yx+xd+2V+5b6JrWEsmxnTnmoSBxHich2V+f7DzKUsKU9i3w8aGrCKycoswG6MJcdgIcxswGIy4rRqaxY2Gm1BdJzXaQreTutP1s+O948xq0iMkhbltz2ejwd7obdvajuV1WT5QnLhAfUSNPU7E3/loi3MCS9a0JuuAhaTUOGKiIwm3hRARalKJjgwaOjq67qGk0E2o1UnfwWvZsnZenfo+kqwWQsOLsOj52CPiCE3ogi0sCZM1Bs0UgqYZwZWLXpKN7jiAXrwH3eNhtac381YtDWrsSkJcH17e+jlf7vmd7/fNr7QdDYrsyMnR3bg8rg9hnpJqx0zdo2HPdRFZ6Mbl8uAO1zBGeAilhGSbjbjQ8KBiQH787CXMnj2MPn3cLFigLuA5yxK4lLchQcX9L0848Pab/zB/7h4OloSQmBxNdFQkEXY7oTYjmkFDM2rouo7H46akwEl84VamPzQKQ2ngeUHl/k03seTVe9lqKGi0OHHG+O6MWPUIBe7as1+Ni+rEna6ruPXj4fy9PINbb7UxbBi0aqXaF1XHk7tcqr19z93r+f1XjYSkBCZODKN1awOpqSqBgNGobi6Xuu3fD8OHQ36+zsyZGnfdVbffqba2S9X9qIUlhA//vpl/lrQnLjGeqVNDad9eIyXFF2vBaFTrubxMBw9CiK329tGhjG0KyWvFFReo+RLlCVM8Hv8Jdct5PLBiWcO22RoivmvrxAHER3Tkqc0fMGv3r/ydu6JSuTuEpDEppgfXtxjs9xxZW/2mjc3GpDz1nNb/VWh9fuUfpbb2VIVxH7pHI+Sgg8hCNzl2C0ToRFBCii0ErTCFu969mRVrW3LzzQauuAISEnSMxpo7gEtKdGw5u73XVZ0eJ+sKt/HLll9IKDYyOK4DyTGRal5EWby0De5dHCjai24owRwSRag9ArspBItmxm00AYUYXHmY3MVYNA9btYFs3L0/4HW5+sTQCjY2b3OOk1GfsZTB1qFSLX25Ztk73vFPtfk483SmpE9Ufa375jZaTIr6xLeqWtes65jT5QfX8/XeP3hq0wfsduz3ftdbW57B2Ig2DA1J9PZzbck/SG7BFg4WZ2EzGYl2QaTLhEf3QJgHrC7MegmRJggLTaQk4QTmrVpS5/rvwah27C8KZdOefHbm5OF2hRBRaiLMoVFot6LbPYToJcSazKREh9F/1zZSHn8l4HqrqLZ4ZjWVqaY42v72o/rUNYOt/9Z1G6/rOOlgjx9+21PpI0lLHFz5xz6EMRkN0UdUn3Pkwah2rM85UPfrcnXcPsqXT+g2gZYDL6jz9ioJLhpA//796d27N88995z3sU6dOjFx4kT+5yct8E033cRXX33FqlW+rOCXXnopS5Ys4a+/VLbY008/nfz8fGbP9qXlHTduHFFRUbz//vv1+lx/GnMDEEKIY962bWq0al1SfVZks8Hatb4UqYHMnAn/938BF/Oqa/pbUS8ej4fLvrmMFxe96Pf5SR0m8d6p72Ez2ao/6XGDuxB0txo0VLgNnAfVBWNXoQriENYK4v1cuBGV+ZtAnZWlIqNGRVEpNX3Jath7NxRvgi53QoerwVxWK9c96lacBSV71M2RCxHtILbv4fkuRziPx8Og1wbx986/a1zGbDCz9r9ryYzObPwC1efYHOxxuTmqbZ+A6vsFqP+rPnaEeuTPR7jr17socqqLGRajBYdbXXAZkjaEj6d+TIuwFk1TuEWLoHfvyo8tXAi9ejVNeZqRRVmL6P1S71qXCTGHsPu63YRbw2tdrpqGOBYEWnfH6vGmufG4YO1TsOJeFRir822QdELlCYrFWepWfr9wOzgzoOqgvprqEnBUHTPF0e9A8QFiH4oFwKAZmNxhMh9P/bjSMj9v/pmRb6ngfkbNyD3H3cMtQ+s441OIOtJ1NTBk927Yu1cNtHE61WALo1ENujSZIDEROncOHCT6mFC1/iH1xqPH0dpma+Bt9pE/H+GmH29SAweAeefPY1Cab0L/nA1zGPvuWAA0NJ4/6Xku7nNx/T7MXaIGEhXtADz+lwnvAMfPgVCpvzcmhwPatoUdO9SgN39699HZNCWWnBI1ua1TfCdWXlZ5Ev/a7LV0eLYDoPqi/tP7Pzxz4jPV3ksIvwL0ASxdCnffDd9/D1OnwuTJKklFcnL1gZwFBbB9uzrEDxmitusOHdTgz1atKk+ucrtVHaiwEF5d+QTXzrnWOxD/l3N/YUTLEd73zS7KJv5h1dY1GUxYntxN0f5YrrkGHn20nnWpYPut6tPPFehc4SpUQXjy1qprJ51uhi53qOB0ugfQ4MBC+L5/5feNHwZ9n4Oozup/jwvQoXgXFO9Wryvd57+/v6nrXL+MhawfIHksjPim+vM1TV4d/WdQ148+WfUJp318WsDlwi3hZF2XRagllE9XfcqUj6fUuvy0LtN479T3cLqdtHu6HVsObgEgzBxGp/hO3uVW7ltJobMQgMyoTNZdsQ6TwcS2g9sY9844VmWr8TSR1kgOlh70vu70zqfz3uT3MNQ2SroWS7KW0POlngGXmz19NuPajgvuzUsPwJpHYV3ZttfmEjUZKzTDN/G/vB+qOEutS08pLCoL+tfnWWh3mdq2tSrf78Ai+K43ra7eyJbsDK680sgTTwRXvAU7F/Cfr//Dkt1Lqj13aZ9LeeyEx7zXL7fkbiHzycDXbJ4a+xRX9L8iuIL4U5fjx7ZtvkGCELi+HBd35PezNkU7oamPgf7UoUxTPprCp6s/DfhWPVr0YNF/FqFpGq++Chde6HsuJAQuugjatIGiIvjqK5g7F3r2hEXfBLkuqq6HxjhHBlq+pte4iuG7XpC/Xp1ba6OZVBILgNSJMOhdFcwEfMep7H8qn4fHLoSYXoHLpHvgh6Gw/291Hh71h3rPise/KoFSrnn7UZ6acxUpqUaWLlWBVQMl+anogQfg1ltVn1RNov57Irlx33r/z7kphyhbVKVlbv3pVh758xGcHjVrzFsvy54P3w+C2iZOhreH47/3tSP/vRLWP1f7uqj6Gmj8fbUZXL/84QcVgBTgf/+Dm2+uOeimy6Xq3fWsHohmoMhZRMLDCd76YU0MmoGtV28lNSKV95e/z/TPpgd8738u/Ie+KU0wvudwHPvr4OzPz+adZe8EXG5MqzHse3wOy5bB2LHw9deH9LGNYn/Rfu769S6eXfBspcfvGHYHNw2+iVBLqN/X7S7YzVN/P8WirEVc3vdyxrUdh6lCYK6c4hySH0umxFWCyWBiepfpvDnJF0joveXvceZnZ3r//3ra15zU7qQG/naiSWx6C+afW/Pz0T1h3KLKjx2Oc2RzrJOLBnXbbap+U14vtdng1FPVNdEDB+Dzz9Wk9J491eZw2DXHbbAuZfr3CtUngwdM4Sp4Y8cbwRKpnt/7O/w4HID1Dmi/VdXcjZqRW4feyt3H3e19q7t/u5u7f7sbd1k9ffXlq+kQ1yH4MgFvvw3nnFP712vXDtatU/f/+AMGDKg5AFetApSpYh178GD44gsVrAEq16VdLtUn3bOn6o6ZNEklBAikPLDBhPcm8PX62isTF/S4gFcmvlK9v2f1ajjrrMoLv/MOdOyo7jfH/p5gxwjeDrQHMqbAUD8/rL/+30+Bz4IsV9X5IkdgO3JX/i4ynsjA5QkcUOzlCS9zbtcL6d0bVq1S2+P998ONN6rjbXlb0u1W22lhoZp+8/DDQRYq0DZbcXsFv9us0+1k3f51ZEZnEmIOCbIAfgQxl2gBfeiHCu69ZAl069ZIY3F0j0pOnrsSiraDq0j1kRut6uDryFXXf5wHwZkLoZnQ65HKAXQDqc8cqluuhLw1agxAcZbq9zKYysp0oKxM+eDMA2ssZJwBCUOC+up1tuV9+LOsTTt5L1iiAya78TKFwkkrwZ7sC4Bf/ho/QYdJGQ/D/QTprOkzhn8NKUG0eYLYL86+I4P3vouhf3+NP/+s+0cEY9w4+O47dc777DNV19J1/+dWXVfnvYCBASvIyYFRo9Rh76KL4PHHITTUF2DKYFD7lcej3t9gCK4PUwQp2GMBNL85laX7YeMrKpm0ZlH96xHt1NxBox0ceVCSpZJe5K0Fx35o8x/v9e0SVwnvL3+f879UAZRuG3obV/S7gsSwxNo+NXiuIlUG3aWCdDpywWBU19zdpRDWuu7Xqg9xvu1qeyEXf30xf2yrnAz1vO7n8dDoh4gLjfP78mJnMZ+u+pTV+1dzTrdzaB9Xxww1deR0O5m1Zha3/XwbVpOVB0c9yNg2YzFUve4rjg6N0UcUxDHtMyZxalkjITtbte2CuUby1/a/uPjri1m+d3mlx6d3mc7Dox8mOSK57m92uFW9hh6oTn4kjLNtaCvvh6W3gTkKTvOTLKC2uuaI2Wq+VdVrtjUtHz8EDDZ17oroAOGtwRypxnWV7IGiXSrpaGm2CvZ3jM/HdrlUfKyiIl/QTF33zZmw21UwzmDqp0eTJVlL6P1yb+8YcX+Oa3kcP5/782EsVSOaewZs+xDiBsDIn8sSxBh9DfXa9r12/1WxEMrnRnrjIOyC4j1Qsle1t/GofbOZ7XsHD6p+ic2b1Vwih0NV9TTN12+uaVBcrM5xl15az/7SYAQTkwKOjvOLrsPBFWr8bcEWNY5RM6h+BwDHQXAWqPulewGD2vYSh9br41weF5+t/ozpn07HrbuZ0WMGtwy5hXax7QK/uAb5+fDqq6r973Sq9nqnTqrPPSxMbVduN5SWqjrTvn1qfLcQNarazwW1HwtiY8C+Te1HRTvVY5rJd23KcRBcBWp/K9kNGKD9lXXej/77X3juObVdr1gRePmq9hTs4d7f7+WZBb45MxPbT+SBUQ9Uv+4VjGCu7egecM6GnU+remKX2yBpnEqiWc7f/P7Y3s3u/HUkKHYWM2vNLPJK8zit82nE2GOaukiNJrsom1M+OIV52+cBYDVaKXWXAmo+4eV9L+fJsU/We75BoztW48QdAd/b4XYwe91sStwlnNz+5Ia5lhcEXYdff4VPP4WtWyEhAVJS1Fyz8HCwWtX1B4cD8vLUGJMrr6ye1KFWzTgGjsfj4f9+/z/u/e1ePFXm8yaHJ/PMuGeY1HFSpcdzcnzV+cJC1dYuT/5RnrgiOlrN3ys/JOi6Or0fOOBrn7vdqt1hMql2+aOPwrPPqi7Ajz5S68DtVr9/xWQjbre6BbUO/HC51On1wAFfnIWKZTKZ1PYQG9u4sRb++UddQ//jDzjpJDj+eOjSBdLS1Hc0mVTZHA4113fnTnVtrrnLK83j/eXvU+Qq4qyuZxEfWiXbYlD1GxdsOBHcOWpsUu8nKicur609H+S8v/x8VZTt29U2Xlqqtk9dL0tWW5b02OFQx4qpUxvxuuThiqUqgnLBFxfw+pLXvfONW0a29M7jjLBE8OYpb3JKx1OaroCHQamrFF3XsZn9xHNtjo7WeCJClGnM/AaN3UXcbFx77bWcffbZ9OnTh4EDB/LSSy+xbds2LrnkEgBuueUWdu7cyVtvvQXAJZdcwjPPPMO1117LRRddxF9//cWrr77qTVwBcNVVVzFs2DAefPBBJk6cyBdffMGPP/7I3Llz6/y5Qgghmlh6umpc1XQRAxom2MbFF8PJJ/v/jJoqq6LRGAwGXpjwAv/p8x9Ofv9kduari1EWo4Wvp33N6Naja3mxEQwVKmS2+JqXFbULqlHWCzxnwN5fYO8f8Oe54MoDewqYI8BoBgzgcaiJC65iSA8c9EkoBoOB+RfO54G5D3DLTyoocpQtitySXAAGpg7ku7O+I8IqydYa1THeUXH9oOuZ1mUap39yOvO2z/Mmt3jzlDc5p3uAGaQNzV/HdlUVH2uOkzIPk15JvVh2yTJGvz2aPYV7AOiT3Id/d/0LQN/kvnx/9vfBJ7cQxxaDCTpeqwb+5CxREydXPaAGSJvCy4Jhll29waAmJ0Z2hI4XBjdhUogjSIw9hpZRLdmSuwWP7mHZ3mXVllm9bzUaGjo6bt1N/9T+ft5JiEOjaWowRWysSmAhxDHtaGmzBWrvVP0/yPbO1M5TueGHGwAVcOiXzb9USnDxy5ZfMBlMuDwuNE3j1E6nBv0VvFY9rIJt1BaYNH+NGmw0Ya0kuWhEr5TFN6qNx60xJH0I36z/Bo/uYf3+9bg9bowG34islft8CS+cHicDUyWJsGg43burAcROJ6xfD2vWwLvvqsmoHo8vUUX54Ng2beCtt9Rj6ekqeHZk2VyWihPxygcVhoTAhHYTuGaOCoJv1Iz8uf3PSgku5u+Y773v8riItVspLpvkd0QnCtv0hgrEgw49HoRON/qeK59M7a/9HtNLJbssyQJLlAqoYbSBwar6+t0lagI1Bhj8duN/j2D0ehx+PwV2fQsLr4Zud6trFR6X6sewt4CTlkPJfjVx0JlXr+ToUzpNITU8lR35O7yPlbcDK7pz+J3eQLGndjqVZZcs4/g3jye7WJ3zQ82h3kDEr054lfN7qeApZqOZC3pewB2/3gFAgbOAf3b947csF/S8wBtgNj0yneWXLeeheQ9xy0+3eJNbhJpD+Xr615W2+/rokdSDr874iikfT/FOZJnScQqfrP4EUEGTXxr/UvDJLQCsMdD9Puh2LxRsVIGytn+mEl9omi9IPGXRjazxsO5Z9X/yWJXcAmoO7g68ecm5THnyE55/LoHkZI0rr1TjfZ3O6gHbTabKQSz6pvRl4X8W8vTfT3P1nKsB9Xt/ccYX9GjRo9JrW0a15Jdzf2Hcu+MocakByBPbT+S7Dd95f7cbBt1Q/+QWwfaTg6o7NnVAzcPtaGknHAYPjnqQz1Z/Vu0YVtVDox5C0zT27oVrrvE9PnGimoTSooXvvH3jjep8/vrrNM91Ud/rTWufUEGwKv5WpjAISVPB/Vz5vsfLj1vJ42Dop4BWPQFPffvRi3dDdlkUu063VH9vP5M75q0bgkc3MmKELwhrXe3fD/fdV3tyCwBLfhvMCWZv8opd+buqJbjYlb+rUlCN1tGt1Tl6/nnqO9SWrCJ/ra8d6cwrOw/UHKCj2muOkbany6Um3RmNMHy4Sm4BNU+6afRgFqLRhZhDeOXkV5j26bRal7t2wLWkRqQCMK3rNNZkr+Hu31UwaqNmZGL7iXy25jPv/69PfL1pkls0I0+e8CQfrPig1qDABgy8NOElOvxHnQePO65y8sXmIjYklmdOfIaLe1/MBV9eQKg5lNdPeZ2WUS1rfV2LsBbcP/L+Gp+PtkdzdtezeXnxy7g8Lt5a9hbfrPclG8wrzfPeTw5Prl9bQTQ/uq4CvaFRYx+wq1jVSY6R8684PFavhgcf9NVLx4yBl16CjAzfsfehh+CKK3wJD0Qd7P4J1pUF5wlJhTF/gT1JBYQrZwrz3m1rgRGpffllxwLcupt7f7+XR/961Pt8sbPY274clj6s3kF+8vJUvbYigwH69VMTzv/+W00yd1doQqSmNt5k87vuUu/dsaNKdmGx+A+AajKpPu7Nm9X/d9zhS15Rm/Lnv5r+FdfOuZbH5z8OQGJoIiWuEm8/3z3H3cPtw26v++T3ikEDmuPEd3/zRWqbK1KyBrJuUP2GS++ALreq4NWesg4+exKctAJKslUwUFc+dIuA21Iqf25dJjcf4ZLDk5nQbgKfr/m81uVCzaHM6DGDTz6C5WXxeZ97Tk2xqbrdVrzu8uCDQRaoLtts1SAXfrZZs9FM54QGHCRT21wiqLR9dC3VOOHWEr7/zca116rgf+Hh6jjkL4Cq06mOCUFfZ9IMEN1D3RpLfeZQWWMgfhDNgqsswaNmUAHvgulj63yrOt9VPM/VFigl+2/I3wChLev2OZYggp4FuV9E8AxwCfv3GxstYek338DLL8OLL0Lbtipw5YABKgBRRITaLV0udQ11yxZ1mzGj7u8fHQ0LFsAnn8CsWeq909OhRw9o3VoFJbZYVICZoiJ1CCgogOefb9jvKcoEcQz0am7nSGssdLpJ3UAdHwq3qevZHgcYLWXXui0Q2wfsqer6dxmbycZ5Pc/jvJ7nNW45TRUCuVljD+29DnG+bUfgtxm/8f6K9znrs7OwmWz8cPYPDE4fXOvH2s12zup+Vq3LHAqz0cxpnU/jtM4y31DUUxD1m5H5BobfUsrv863MmAHvv6+CODudNdfrKj4+MG0giy9ezLMLnuWq764C4Odzfua4zOMa/Gs1uBdfrD0YZtU6+dESBDQYUd3UX+dBOLBI/V/X+uaBf9W14brq8ZAar+RxQ/FOdf3T41DJjyyxYEtSdXBrLFgTgv8uRxmTqflVRZqTHkk92H3dbo578zjveN9oWzQ5JSpRy+MnPM7VA65uwhI2sEHvqDGOqx+BrztC64sg8TiI6an6ikLT1RiB0mzIWw95q6DFCeqyxp6fYcFlakyaPQGscWpcpMEE7mK1DxZsVmPTMs5o6m9aTWSkGgcwfHhTl6SC5jguqLFpGkR1VbfDwGQwMbXzVE7rdFrZxx/6wObwcLj6anUDNTZo40bVN5+drdrmRqNqp1ssKjBveRBYIfxKT6/H9YeWkDCsMUrDlVfCnDnq+uLVV6triBaLurZkNlfelv315SaGJfL0iU9zzcBreHXRq0xoP4EBqQMOrVD1vbazZhWE56j5/WseU2MHzeFAhejMaCoBcUQHiO55aOU8RtnNdqZ1rX3s1dEiLiSOuefP5Y0lb3DeF+d5x7anRaTx1bSv6N6iexOXMIBjNU7cEfC9LUZLkwYC1zQ1du+4Cl00JSUqcUNpqboZDL76TXh4PRIrBOqfbYhYiPVkMBj4vxH/x4zuM5j+2XTvPLkr+l3BA6Me8JtwJDpa3Tp1qvvnaJrvdTV55hl1Onv9dbXZxsera01duqjf3W5X59+SEpXkIScH7rkn2G/sYzKpeQwtWgRetjH16wcff6xOz/v2qbFLK1bAv/+q7a+8n9FqVbd27Y6MOnaENYKL+1zs/8n61G9CgXMMoD2vkp1lngsJQyG8beX2PEDuSji4ClJPDnreX3i4Wif9+gX1MnEMeXXiq5zf83zGvz+e3JJcb3KLkZkj+fi0j4m2Bznp5ghkNVmbugjBORb7oIRoIM1sakvjOf3009m/fz933303WVlZdOnShdmzZ5ORkQFAVlYW2ypEXsnMzGT27Nlcc801PPvssyQnJ/PUU09x6qm+QDuDBg3igw8+4Pbbb+eOO+6gdevWfPjhh/Tv37/OnyuEEKIZqNdFjCBJhbVZ6pXUi1WXr+L0T04nrySPT6Z+QlK4rKdmy2CEFqPUrSrdo3rTDI00a+wYcfOQm7Gb7Fw952pvcovhGcP5Zvo33uBYh0Wwk8ngmE4wcDRJiUjhtxm/ceW3V7IoaxGvn/J6vSef1tvRMinzMOqa2JW/LviLga8OZE/hHm9yi8Fpg/n+7O/rn/X+cFx4a8YX945JBpOa2BPbp6lLIkSzMDhtMDsO7sClu9iUswmXx+UNJgqwOns1JoMJp8eJhkafZNl3hBBCBNBAAT1qkx6ZTs8WPVm8ezFu3c3T/zzN2v1rvc9/s/4bb7C+oelDiQuJC/prAGqy+OqHqRbYrDzYaoVApnhK1GAjCXLWKJzOus8vHZQ2iNnrZ6vXeZxsytlE29i23udX7VuFSTPhKgvSOzBNElyIhmc2q0GxgQbGrlzpOyTefLMKplJb4FCjEVrHtKZtTFvWH1iPjs7cbXMrLfPn9j+9SX5MBhOvvmLk1IkqSUy/fnDeeTVPZC8P5N3QAWQOma7D2qfV/YRhlZNblCvc5g38X0nm2WoCaDmPqywISCkYLCrZhVafqEyHQWRHGLcItrwP2z6Cz9MguivEDVaJ0U2h6rdxFULJbijZC4Pql6Tju7O+o/dLvb2TOk7teCpL9ixhw4ENgGo7Xj/o+kqv6ZrYlXkXzGPo60PZW7jXm9zi3cnvMr3r9ErL3jr0Vh7+6+FKAWGrfV1rJLcMuaXSYwbNwM1DbqZvcl9GvT2KKGsUKy5bQUpESg3vEpzx7ccz56w5jHp7FC6Pq1KAtI9P+5jJHScf2gdoGoS3UbeU8TUvd2ARLL5O3e98mwqIHiAg1dAOc1n1UCfeyvqDz77qxP33Q58+KoBSdDSEhqp9vagItm5VXZMffeR7S4Nm4KoBV3FC6xNYsW8FE9pNqHEw54iWI/j13F8Z/sZwSt2lzF4/2xvw3RuIsD7q008Ox3xfuahd65jWXNX/Kp74+wkAzAYzwzOG89eOv7zHqZPbnczo1qMBFfOkqEi9dvJklajK7fYloyo3darav5qd+l5vWrUUVj2It62jGaD7A9D+vypAgrsElt4Oax6t/D49H8NvcouazsN1UfF453FQa3LBMhlxW1m0pRerVpnqFFy1oscfV0HrAjEXtMFdIUHFzryddIqvXLnbfnC7dxmzwazOTzu+VImNymlGyJgGGaerNuS6Z2D3D+q58nbk6ofLEmIESHBR8TXHSNtz0SIVUBfg7rubZ6B90fDO6HIGy/cs5/65KhFBh9gOtIpuxewNqq0/ucNkHh7zcKXX/N9x/0ekLZLrvr8Ot+7m2w3fep/7ZOonnNLhlMNW/uYqJiSGVya8wowvZgAq8cfVA67mmX+e8bYDHhnzCBlRGXTuDEuWwI8/wnXXNV2ZA+ma2JV/LvKfPK++Tu96Oi8vftn7//7i/X6XG54xHEPV86E4Mu35SSWRqo0kOBaN4NprffdnzFAT4cuTG5TXd2Jj4YMPDmMQ5EZOXn5YrH9R1cE1Iwz/BmwtKrc5/JjUagS/7FgAgI5OkbPI73Intz/Z7+N18eKLKpBWuWHDVNDR5GT1/4EDKobHunWqibdxI9x0k1rG7a69DlxTX29N/vgD/vpL3b/zTvXetSXSqPjexcWBkwVW9dgJjxFuCefu3+9mT+Ee7+NPjX2q/glTm7Og5ov0AseJKrnzto9h7ZMQ1x/iB6ugg6ZQ1U50FULxLhXkaeDrwZdp2zbVuCp3JO7bwHunvkf8w/EUOAoAiLHHEG4JZ+vBrd5l3jzlTUwGE48+qvoKevaESy+t/X0NBpW45agQxFwiG/DNj/DYY/D009CyJUyaBKNHq37m0FDVhVRcrALl/POP6pI9lGAsjeZIn0OVMgFC0lUQ4AWXQf9X1LWs8vF7FQOfFGdB0U5YUBZ0Jax1cJ/lPAhz+kGHayH9NIho7/8z8tZB3ICgA6sE4x7uYJ42hBUbujFlisabb6rApv7Oa8Ge68oZDOr8evHFajteskTdZs1S23ZxsXpfu13dOnasWyKnqp8xdaq6gUpgsWmT7/0dDnVYtdth4ECV+EI0kiP9WOCPKVRdLz7aHeJ8W03TmN51erXr00I0mmATz0PwdewgjmmRwI+/w5NPqrZncjKcdBKMHAldu6pkF1aruh6am6vag5s3wwsv+N7DaDByZf8ruaKfaqM1RJDpw+IICIbZ5FLGw4A34O8L4Kfjods9kHmOSqwGKlnaSSvBmavqgY4c2DsPtr4Dy2aqxL+dblQJlTwu1c9y4nIo3a/Gw5TuU2OVIjr46o4Go/ShigYRHxrPbzN+Y+RbI1m6Z6k3ucVzJz7HpX0DNPaPNAaT2tc6Xq/GXRxYAFveU2ML3KWgu9Q+p5nBaIWIzhDfX/V7+kve6HGpsWcGS/McEylEmcasc8TGqpsQR4t27VQ3/9NPw1tvwZtvwqhRMGKESpgeHq6u9eTnqwDUW7f6n3vTKroV942873AXvzLNqMb1VxzbL0QDmNFjBn2S+zD+vfGkhKfw7VnfEmGNaOpiBXY09mvWxbH6vQ+RzaZuDepwxEM8BJnRmcw7fx4fr/yYFmEtGN6yabLjDRjgm0dQXKzGNeflqeH7xcVq3EVcnDovt2x5ZCR6qCtNg4QEdRsypKlL0wwVAq9b4IalELoX9v8NK+8HV5Fqz3tcao6Awaza6TF9Ie4Iz1JxiMnLReMZnD6Y5ZcuJ/PJTFweF1f1v4pHxzyKUWJlCiGOMsfUlLLLLruMyy67zO9zb7zxRrXHhg8fzqKKg0X9mDJlClOmTKn35wohhBCiaUVYI/j2zG8DLyiaN80AR0kHYlO7asBVGA1Grvj2CmLtsXx75rfYzfbDX5Bm3tkuGo/RYOTZk55t6mKIIGVGZ/L7eb/T/hk1qSojMoNvz/y2/sktyh2OY4Ecb4QQzVT/lP68t/w9AFweF5tzNlcKAL1i7wpv0Mo2MW2OjEE9QgghjgntYtuxePdiAPYU7vGez4BKQUgPKaHhto/Ble/73xwB3f8HbS4EDLDiXljxf/V/f1Fn33yjBttXZLPB0KFq3NOCBb7HB6YOrLQNrNy3slL9ZuXelehlQXNj7DFkRmU2ZtHFka6RJ6a/954ayBoWBuefX/fgLMdnHs/6A+vx6B6+3fAtoff7EgeXuErwlAVH7p7YnZNOsPPTT3D11eozXngBpk2DXr2gc2c1qcXtVuMIlyxRE9mbXQDTfX/4gk22+y94nGpwZzk/wf+9irMq/28wgSEMCGu04jYoU6g677S5UAUzK9kDBZtUACNPKaCpZBcJw1Qgo3qOhO6c0JnXJr7GmZ+dCcD6A+u9yS0SQxP5Zvo3fl/XLrYdf57/J22ebgPAR1M+4rTOp1VbzmAw8OGpHzLuvXGACgL+8oSXueiri7xtzg+nfIihhqhBI1uNRL8ryOh5dTS85XDenfwup39yuvf88dTYpw49uUUwnBXqG7aEgIEXy8WGH+CayQe5Zqbaj3ftUvtwVpYK+GQwqEHyY8ZAq1b+36NDfAc6xAeuL/VP7c8HUz5g0oeTvOvs/B7nc9vQ2+pUViHqpZ7BVR874TFW7F3Bj5t/xOlx0j62PT9u/hGA9rHt+Xjqx4A6ZH7yidp/EhPVxE+Px39gT7NZTTg5auybpQLagZosMeg9SJvkS1xhtEHGGZUTXLQYBZF+jhc1nYernoNrYkuA5JMg6ztYfheknAQe/AfxK3vfxzJK+eVkncWL4aqrVNAet7vmulR5UgSXC15+2Rc4uNzYsSrgz48/qs0OwFrY2lunAtiVv6va+27L2+a9nxGZoQKdr39WHcfLkxUNeg8ypqr/QQWK+e4H35s4cmHbJ2oSS7nUSdDt/1Rwww0vwRI/yb2OETk5vvvp6ZLc4lhyz/H38M/Of/hx84+s2b+GNftVppNW0a14a9Jbfl9zzYBr2HBgA8//+zzFLpXJ5rExjx3+5BaHI8BZPZ3b41yW7VnGY/Mfw627mb9jvje5xYzuM7hm4DWAOj/27g0//ACXXKKSA1ks6txZcT/UdXVsrU+g0eZqZOZIEkMTvQG4DRgwGox4dE+l/qanxj3VVEUUDW3Nk75zd22OsSRTonHl5sL336v2R+vWvqCSVdsi5d0kF198GAp1GJKXNzpnAez8Uu3PbS+FqC51Ss53edep3Pjn05S41Hc3aAaMmhG37va2CaxGK9cMuKZexXK51Lm0PID+ySfDxx9XXt/R0fDhh/DAAyrhyYgRKlFpdjbcdpv631+3mcMBv/6q+n7q6ptv1Pk8JgZOPTVwEO9u3WDQIPj7b9XH/McfgRPPVX1+5oiZFDoLefQv1cb838j/VU5uUZ/J70fLxHdLFHS4Wt08TrWNFmxSge7dpaqv1xwJUV0hvG3w/b9Hw75dxmay8ePZPzLw1YHe63zHZx7P60tU0o/rBl7HqZ1OZdky+Pdf9Zqrr65bYPygk34H2maPkGANRiPccANcfz0sXw6LF8OqVfDFF+prlJaqYMgxMdCmDfToEXzwf1EH9kQY9Sv8MhY2vgr5G1UCiqRRKhEtqDpoeT20YJsvQe2+PyB9auX389OXhiMXwlpBZCfY/gns+hY2vwPuIrDGgikc0MFVACXZ6njT/vLgvkeQ+0UM8Jslhgfe1Xj+eV8w7pNPhowMlezCYFB9Qzt3wooVcO+9wRWp0s8SCoMHq1tjCgtT504hhBBHqfoknodGr2ObTGqcz3XXqfECy5fDhg3w9tsqwG15H258vKrXnXmm/6bFEZPYopwEw6ybVudCi5Gqrrn+eVh0LcT2VXU+c7gKmO/KV0kr9v4OUd3g5I2w/gXY9DqsfgjiBqlkjJYoMIaCu1hdaz6wABwH4YT5Tf0txVEqNiSWX2f8SvSD0QC8evKrnN/z/CYuVSPSDBDVWd1azaj/+xhMHGMhvoQQ4pgQHg633qpuu3erpOkbN6p+3ZISVce3WNSY4ZEjD0Nf7rF8bUc0W10SurDl6i1NXQwhRAMzaAZO73J6UxfDy26Hnj2buhSiURxy4oZ2kHCMZAGR+FnNVmpEKoW3FuLyuA49FpsQQjRT0vsthBBCCCGEqOS//f7LZX1VgjZD1YmEQhzt5MJ9vbWLbcfyS5cze/1sLup1EeHW8MNfiGYclEQIIYLVP7W/d+I3wOrs1ZUDQO9bCYDJYGJwWiPP8BRCCHF0OEwBPW4cfCMfrvzQ+7+7hgBkNw2+Kaj3rWTz24AB8KhA6kNnQcJQX6DV5BMlwcVh8v77KshKeSDaoUPhgw9UoAuAn39WgZgA+iT3waAZ8OgejJqRlXtXVgpmuXTPUty6G4NmYHDa4CNvcq44fA7DxPTyxC2ZmSpIUF11T+xe6f8iZ5Hf5drEqKQDgwerRDBLl6oAZv/8Ay++CNu3qyBoRiOEhECnTipYmmvTNky5QfR9NHa/x/5/VLBJg1kFfDZUGYJSmu0/uQWooD11Vc9A6oeNZgB7kro1gmldpvHe8vf4Zv03LN2z1Pv4qye/SqQtssbXtY5pTf4t+Xg8HiJsNSdFHNt2LOd0P4e3lr6F0+Nk1ppZ3kQJ53Y/lxPanNBwXyZIUztP5a/tf/HE308wpvWYygH2DoeQVN/9/QsgNKNyEpfaAlLFDwTUfpyWpm6N5ZQOp/C/kf/jlp9uIcQcwgvjXzi08+ghDwAXR7VDCMCopafz4oQX6fRsJ0rdpby8+GXvIq9NfA2L0QLAsmWwd696/M471bm4tkmd/hJfNLn6Xm9aMQHQAB063gBpp1QP/Fr1/4j2KtlS1cdrOg/X9RysaTDobZjdA/LWwk+joN9LKmiD7lazb0NSwZ6iyhvTi7SYPcz53sy0afDMM/Dbb3DFFWpybsWEPm63+nkWLoSzz1aBWMvXOUBEhAos3L9/WZEdcOWVqp5kLWztXc5kMLEzf2e1ou/O362+Ahrt49pD4VbY/ZMqJ0D/VyF9Stn3rGED2vNz5YDamefAwDd9CTIShtftdzxKxcX57m/YoDZlSXJxbDBoBt6a9Badn+tMTokv08lHUz4i1BLq9zWapvHUuKf4eOXHZBdnM67NOK4ecPVhKnGZZhrgrKJ7j7+XWWtnsSlnE/O2zwNUUrvHxz7uXaZlS5g3z3dMnDULzjhDHS/79FHHT7db7Zf//KP+lgdnPxrcfdzdXPy1iiZvNBi5oNcFzNkwh825m9HQGN9uPHEhcQHeRRwRnPkqyVag5BZCNLCff/YlO3jkkcDBZQ5LMPHs7MDnr6pKStTrmksbfedXZQlhgcyzqz9fQ3I+Q+kebhx0I3f/fjcAEdYILu97Oc8veJ4DJQcAuH7Q9TUmZg1k9mzVRAMVTPTdd1WdtuLbaZq63XSTanuuWqWuizz/PJxwgmqvdu0Kbduq4ETFxbBypequ7NkzuAQX5U3FFi3qtl2ZTCr5VY8eqo959Gh49lnVl+zxqECpmuZLhGUwqKBKnTpV/H4aD49+mDBzGCHmEG4c4ieJn0x+V/2B4a3VraEcDft2Bf1T+3NR74t4aeFLHCg+wJtL3wQgKSyJmSNmArBli2/50aMbMRnbUbTNapoKyC9B+ZtQWCactEolatr4Gsw/V/WthbeGkAx1XcyZDwdXgTMPYnqrYMLrnoPUUyDx+Mp9dhUTYgB4XL5ra60vUDcAj1slVveUAAYwWsGWWL3/r66C3C8igf/9D/7v/+D331V/7S+/wJo1UFhY1i0YoprZAwaodmiz7KMVQgghmpHMTHUTopKQVOh6l7q5HSqxYv56cBWqvlGjBeyp6tqmNUa9puud0OUOKN2nkoXmrYaSfSrBqMGs6o0db4DILsEnYxQiCFG2KBy3O9B1HYvJ0tTFEUIIIZqFFi3UbdiwJi7IUdRPLoQQQggBSP1GHBUsRot3zpQQQhyNZEqZEEIIIYQQohpJbCGOadKxXW9dErrQJaFL03z4ERCURAghgtE9sTtGzYhbd6Oh8caSN9hdoAKzFTuLyS5SwfFcHhf9U/s3ZVGFOLY192DLQlR1GNo7vZJ6EW4JJ9+RD6g+hvKkBh5dRYaKC4kjM7qeMzaL98CeX/AGJu39NCQOqxyUtGqAddEoSkvh6699yS3S0uCLL1QwxXLDhsE776jAxKGWUDKjMtmYsxG37uaJv59g9obZAOi6zupsdcz06B76Jvc93F9HiEpMJjW/1+UK7nUX9LyAy2ZfFnC5qsFcu3dXt1rVp++jsfs9HAcBA1iiG+/YewiB1I+Wepemabw4/kXaP9OeQmchANO7TuekdicFfG2YJaxOn3Hf8ffx4YoPKXWX8vX6rwGwGq3cd/x99S94A3l87OM8dsJjTfPh4a0h7VTY8QUsvQXSJvsCm5erLSDVYXTzkJu5ot8VGA1GzMYGiA4n/eSiJocYgLFVdCv+b8T/cfNPN+NwOwC4uPfFDEob5F38229V4E2PRyVLa7SAh40t2P3ImQdzl6n71jjofFvNyRcqcjtQSTGqsMaBwVY5SGw2sMkJOYvU/3VJFN7ta8h+Dja+ArO7QtxgiOsH0T3AFAruUji4QiW+chyk99h/WLlSBVp97TW47jrIz1fthNhYtV737lWBX48/XiW4mDVL1b/KA7C+9x707u0rgsUCzz2nArVn52aioaGjo6GxK39XpeIWOgopcBYAKgFG25i2sO0TX2TX2P7Q6tzAv+uub/EmG4kfDP1fKQsCU7ZOjvF2Z8+eKpDu8uVw++0q4H4gEkPn6JEUnsRbk95iwvsTAHho1EP0Tu5d62tMBhNbrt7CvsJ9pEamHv6klvU5f8FhDSJsN9t565S3GPL6EO9jr098nShbVKXlOnRQSYCWL4fPPlMBrd97z5eoEdS5s3NnGDfu6Ao0elGvi3jmn2dYvnc5To+TUZmjeG3xa4BKePHC+KMom8exLut70Kt0ysT0hs63q/tLboH8NYe/XOKo9913ql5qs8FJJwVuixyWBF9xcapAwZzHbLbKGcma2p6fQTOp5LCx/ao/X0tyvtuH3c7Li14mqyCL3JJcerbo6U1ukRiayJ3D76x3sebOVevY6VR1Wput5sQSHo86n5pMqg1z9tkqEd/q1Sp58YED6n+rFU4+WdWV27QhqGvJYYUpaCRw8GDd60lJSSrpxu23wyuvqPN/374q8VXXruo7FRWpMv77r3rNokWV30PTNGYeN7POnykayNGwb1fxwMgH+Hjlx+SU5HivCT974rPePurSUt+ywSQWF6LJGYyQNkndAIp3q74wZ566HmC0QkgaRHYCow3+vQrWPQW/nATt/wudbgJbgnqt7gYMqoPEXQw7Z0P6qf4/MyT5sH3FmlgsMGqUugkhhBDNWn0Sz4OM5xXNi9ECkR3ULRBNU3VMWwIkDm/8sglRgwYZnySEEEIIIYQQQgghhBBCiCPesT3LTgghhBBCCCGEEEIIIZohq8lKqCWUvNI8dHQ+X/M5n6/53O+yLSNbHt7CCSEUCbYsRI0u6HkBT/z9BACp4alc1FsFn9tTuAeAS/tcWv833/UN3uQWoZnQ5iKQRJ1N4tdfVWAkUHMmP/8cwsIqB000meDEE1UgWoAQc4j3ueyibG/Srqqi7FGNU2hxdDgME9MzMlQQ0HXr1MfUNWaUxWShVVQrNuVuAsCAAaPBiEf34NZVNhir0cqA1AF1e8PmzmQHdHAV+X/eX2DtcmGtGrVoR5uUiBSeHPskF351IQBPjX2qQd8/NSKVGwbdwL1/3IvLo4KI3jj4RlIiUhr0c+rrsAdArqjXo7DzKyjcDr+eBEM+AkskoFWug3jc6oRYmgP2+CYpaqgltEk+VxxjGiAA47UDr+Xu3++myKnOHw+MeqDS4t98owLhd+sGiYkNUuojw4EKUUbb/EcFMamLveUJAKscK0PTYcJaFSy2OAs2b4Dzb4TS82p/v5r6MrrcrpI+7JunEv+sf14ltzBY1Dk/YQhkTAfdg9lsYNo0mDZNrcuNG1Xc1qIiFTA2LEyt35QU9fzHH/sSi119tWpDVD30ly83aZKVFmEtyCrIwuVxsTNvZ6XlKia8cHlctI5pDQf+8v0+Xe4AjxMMAYJt5CzG2/bs8RDe4IMCUOvx6adh6FD480+46SZ48EG1Hv0FenY61d8jNmGNqGZ8u/Fc1Osidhfs5rpB19XpNaGW0Karr9Tn/AWHPYjw4PTBjGo1ih83/Uib6DaMazuuxmW7dlW3cqWl6uuZzbUH6D6SaZrGDYNu4JxZ5wDw1N9PeRNmnd75dJLDmz4ArGggu39UwfDLk1wkj4NhX/qetyfD9/2bpmziqKXrqi3icsGIEc2o3hKoL/RICNDpyFEBvcPbBv1Ss9HMtQOv5YYfbgDgiflPeJ+7ZsA1WCq2m4JIJgEw/9dOOJ02oqLgootqT1jib3uwWAIkLg7yWnJ/puDkY7ZuVXXsfv3qlkQlNhaefx5mzoSffoK//oI//lCJsBwOVc7UVBg+HEaOlMRzzcbh2LcD7RP+HjuE40e0PZonxj7BubNUUslxbcZxSodTfM9H+5bdulUlwjwa66ziGGBvoW416fMkJI2BRdfBmsdgzRMQ0R5i+4A5EtwlkLsccpZCZEf/CS6EEEIIEbxgE88LIYQQQgghhBBCCCGEEEIIIYRoEJLgQgghhBBCCCGEEEe+wxDcUgghDreMyAyW710ecLlhGcMOQ2mEENVkZwcfEK2kRL1O6h/iKHfzkJt58u8n0dHZVbCL83qcx52/3AmA2WDm+kHX1//Nc5eDZgbdCe2vVEGRJMFFk/juOxVcyeVSQZF69/a/nKbBjBnq/uC0wXWq30zrMq3hCiqOTo08Mf288+COO1SA0Mcfh7vvrpy8pTYX9b6IW366BYBIWySX9b2Mz1Z/xprsNQCVAjoFpT59H43d7xHaUgWbdB6EnGUQ1Rm0Cj9U1cDajrJyhrWC+IF1+4yjIYhfAzm/5/k43A46xXciNiS2wd//xsE3cu8f91b6XwChGXDc9/D7JNj7K3zVBlqdD6knQ9wAFdjdXQJ7/4CdX6oA9WPmNXWphWg8DXBcNhvNvDf5PaZ+MpU7ht1BlC2q0uIbN6qAm8cdpxJO1fUcfMQ78C9gADzQ5uLK59Ta5G+AHbMgZUL1pA2h6eoGsGcRlDqCL5e3L6MXtLlQ3YKgadCmjbr5s3at2nxAresbbvAfbNVohMhImDABvoxtS1ZBFjo6Ww9urbRcxQQXOjqto1vDmqdU2zEkVQXIrlMbsiy5RUwfiB9Uh+WPPUOGwAMPwM03wyOPwNy56v7o0Sq4frm8PPj6a/jkExVkVxw9XprwUlMXoe7qey25tFS9pvx1AQJlN0Rb5MszvmT9gfVkRmUG9TqrVd2Odqd3OZ3rvr+OfUX7mLfdV+++duC1TVgq0eB2/+BLbmEKh/6vqgqCt34kkdlFw8vJgV1lVckxY1SCrmaV5OJI7uvylAI6GGs4UdWUJLcsQe5FvS7izl/upNhVzPyd8wGwmWz8p/d/fMsGmUzCg8ZC8gE45ZTK9dcGE+S15Ml8Riab2EImM2dqfP99cB+XmAjTp6ubOEI05r5dl30Cak5yWc9ynd3tbG+Ci2dPfLZS4uKBAyE8HPLz4dln4cUX6/URQhwZUk6CpLGQuxT2/KoS1Gb/A+4iMFjBngSdboAWYyTzkBBCCCGEEEIIIYQQQgghhBBCCCGEEOKIJgkuhBBCCCGEEEIIcXQ40id0CyFEFXUJAB1qDiXEEnKYSiSEqCQuTgV4CCbJhc2mXifEUS4xLJHhLYfz65ZfcXlcvLroVXR0NDTGtR1HhDWi/m+eu0Ilt9CMkHlO9QCu4rBZsUIltwC49NLaA35FRqq/p3U+jRcWvlDr+9pMNuJC5FgpmlZCgkpy8dpr8OSTcPLJKomLqYYRFhW3/8v6XsYdv9yBy+MipySH6wZex2uLX0MvC5J83cDr6l+w5tb3kXqKCjTpyod1T0M/PwFuKwbWhrLEREFGKm9u37uJaJrGpX0vbbT3D7eGc3Hvi3lx4Ytc0ucSwixhjfZZR5zE4TBhDSy+AbZ+CGsehbVPqoCrmgF0D2gm9X+cBEEXx4AGOC5P7DCR0ttL/T5XWKj+xsUdYwku9i8ANLDGVz53livcppJGHawSTB0D/HslxPQGe3LNbaTYmOD7MaDR+zLWrPHdHzeuemz5qqZOhTWL2/Hn9j9xeVzszN9Z6fmq/7eNTIX8jeqftFPxJq6oq8xzwOOUtmcNbroJevWC88+HP/+EyZNVnbl7d7DbVeDSpUvVsl27Nm1ZhQj6/BVkoGzgkAMCA9jNdroldqv36492FqOFqwdczW0/34ZbdwMwJG0IvZJ6NXHJRIMpzoKCjb7/u9+j6kcV+xIMx0oFURxOBQW++23aNKPkFkcDU4Tahx0H/T/vL0luhQS5kbZILu59MU/8/QQuj7oocWGvC4m2R/veI8hkEmtpTxGhAPTrp/p3LZZ6fbuaBXkt2YiH200PcoHrRX74AS65RCUB8Hiqb48uV8191UIAQe8TXt4kl/Wrz2qahudOj/d+RaGhart+7DF45x2YOVNdi6ltW5ZtXRzRDEaI6aVuHSUhnxBCCCGEEEIIIYQQQgghhBBCCCGEEOLoJMP8hBBCCCGEEEIIIYQQohma1GFSwADQ7WPbH6bSCCGqSU9Xwcqysys/npUFubkQFVU9KmNcnARnFseM6V2m8+uWXwH4at1XAOjoTOsy7dDeOHeZ+pswAqwxh/Ze4pCsLourGxoK48fXHvCrPADNiIwRaGjeQP/+tI1p28AlFaJ+br0VPv1UndZHjoQXXoDp00HXVVCx8thMJhMsW6YSYABEWCMYkTGCnzb/hI7O1+u+JqsgC4C4kDh6J/dumi9UV9u2Va7frK4SRLvq/wlTIesN2PIOtL0cojrXHABa95QlApBAlM3V8yc9zwvjX0DXgwz+fSywJcDAN6HvC7DnF9g1G4q2gasITGEQlgkp4yF+aFOXVIgjXnkStWMuoGz2fMANsX2qP1e4Db5qDx4/wSk1owoC+11f6P8qpJwE6OBxgwYYLOpY5f619n4MaJK+jHXrVBITt1slr6gtcZ7BAGlp0GZrG++5KrsoG7fHjbEs0PWu/F0YNSNu3Y1BM5BBPqCCaxLTy39dpHBb9cQhmkm9ruW05pHcIlAdzd9jh6kfavRo2LgRfv8dvvwSZs2Cf/9V69RshlatVOKLKVNUXbpKjFMhmq/6BAU+xIDAom4u7n0xt/18m/f/6wdd34SlEQ1uz2+++8YQaHMxGGTKi2h85Yn2AMIk52dgwfQh5ltUnrkDC8FZAGY/P3DVJLlVXDXgKp74+wnv/9cMuKbyAkEmk1hAX+/9gQMbIbkF1Ota8oyYOObfDy+/DC++CIsWwZVXwqmnqgRyoPqmf/oJfvgBHnmkEcotjg5B7hNeDZDksmpii4r++1+V4KK4WF13+flniI+vnsTCU9aMX7ZMJVUUQgghhBBCCCGEEEIIIYQQQgghhBBCCCFE8ySj/YUQQgghhBBCCCGEEKIZGtVqVMBlhqQPOQwlEULUKD1dgpUJUYPJHSdz6TeX4tbdrNi3AgCr0cr4duPr/6aOg1C6V92P6w8elwQ3ayIlJbBrl7p/wgmBgz+VB6YxGAxkRGaw5eAWABJDE0kITWDd/nWUuksBGN1qdCOVWojgZGTAb7/BqFEqBtnZZ8MNN8BZZ0Hnzmq73rwZ3n0XQkJUsLFyEztM5KfNP6GhMWvNLAA0NCa2n4hBMxy+LxFsIOSsLBUtrbS05vc866zK/6dZ4EETuEvhlzFw3LcQ07v6MdrjAt0FS26G3k/U6+uIxlcefKy2IGTHPJMdUk5UNyFEowgJgaIiFWC2WR2Ogk0CFUxyAcdBlTQHIKZP9fNoabb/5BYAHW+Adc+A4wD8fjLYkyB9qgoO63FB7nLY/hlEtIdxM5pdP8a6dWo9m0wwcWLgxCYuF7SMbolbdwPg0T1M+nASdrOK9ro4azEeXUXCjLHFYM5b6XtxTN/qySpqSh6iu9RvZj20wJ4NYts2aN8+cGDSqvU0m00F1D0M69xiUfXmUaPgqafUY263Sl4ihBANLTYklikdp/DJ6k8ADq2/UTQ/eWtUoindBcnjwGhr6hKJY4TV6rsfbDz4Y05d6qcV66YtgftQSfi2fwItzww6iVzLqJakRaSxPW87iaGJtIpuVXmBIJNJLH8iBfP7OppBo3PnoIoSnCCvJRtQiZYzM+G221Sf89lnw8UXq/5qkwl27oQDB6Bv34BvJ45lgfYJaJIkl+np8MYbarteswZ69oTrroMLLoCYGN9yGzbAc8/Bn3/CP/80WnGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQghxiCTiixBCCCGEEEIIIYQQQjRDBoOBXi16sWi3ipQ7o/sMRrYayTmfn4OOrh7rMaMJSyiEEELULDYklpGZI/l+0/eUuFSQowntJhBmCav/m+ZVCBgb2cn/MoXb4KCfAO6iQW3aBLqqjjByJDgcgZNclLu4z8Xc/vPtAByfeTxvTXoL+3127/OX97u8oYsrRL117gxLl8IVV8Bnn8GePfDoo77tH1TQ3u7dK79uQrsJXPHtFQD8vfNvAHR0JrafeLiKXv9AyMHa7oDkx2DndSr49pwBkHoKtL8SYvup4NzFWbDhZdj4MthaHNrnCSGEOOpFRan4i8uXB052cNgEG8AVgksu4Mjx3Y/uFVxmj8hOcOJiWHwz7JgFxbth7dOASvLgDRBtjqj7ex5Gq1appBXdu0NEHYpoNAJ65ce+Xve1975e4Um37oacpaCZ1W8a3rb6G9aWPCSimbQ7s7PrF2W5pES9tomSmkhyC3HEi4tTx/Jg9j+bTb1ONLrrB13PJ6s/4dSOp2I0yAHnqFK01Xc/7VTwOIMOhC9EfYRVuHSxd6+qo5pktpV/wdZPtwD7gHhgw4uQeU69PvahUQ8x44sZPDz6Yf8LBJFMoiAU0KBt22bU7ixjMMAtt8CkSfD22/DmmyqpRcWciuHhcPLJTVdGcYQIMsHK4XLWWWo7nzED9u+HG29UCV26dlVJT/fv923vffo0aVGFEEIIIYQQQgghhBBCCCGEEEIIIYQQQggRgAy5FkIIIYQQQgghhBBCiGbqpHYnsWzvMjQ07GY73RO7e4O0Rdui6dGiR9MWUAghhKjFtK7T+H7T997/z+hyxqG94cFVvvtR3VXQ9IoKt8FX7asHJy3OOrTPFdWsW+e736lT3ZNbAAxMHagCzQJL9yxl44GNuDwuAGLsMWRGZTZkUYU4ZAkJ8OGHcOAAfPABfPqpCnLndKq4pWPHqkBMFWVEZdAxriOrs1ezK38XABajhZGtRh6+gtc3EHJ9hA+H4V/CH6eB7oDtn6hbVZpRElwIIYQIaMQI2LIFfvqpGQWVrc95NZjkAu4K722NVefMYIS1gqEfqUQZWz+CPT+D44BK7GBPhNRJkDwuuPc8TNauVX/btavb8poGg9MHV3pMr5rxokxSWBKU7lUJPvy1IQOJ7AgeV+XX1dTuBGl7CnG0SU9XB6ns7MqPZ2VBbq7KyJSUVPm5uLhmGUT4aNQ/tT/6Xf6P/+IIV7BZnbsBkkZLcgtx2MTEqMDqRUXwyy8wfXpTl+goMxeYZIDs+bD8Luh2T9BvcUbXMzij6yFeZypTXAweD4SGNsjbNYoOHeC+++Cee1QCyH37wO1WVZDu3VVeLSGOVNOnq+346adVIpeiIli2TLX5PWX5OlNS4D//adpyCiGEEEIIIYQQQgghhBBCCCGEEEIIIYQQonbNYfqnEEIIIYQQQgghhBBCCD/6p/T3BnxesXcFq7NXA6ChMSB1AJqmNWXxhBBCiFqd0uEUzvviPO//J7Y98dDeMG+1CtCKG8LbVn++NNt/kFFH7qF9rqhm3TowGlUwpQ4dgnttn+Q+GDQDHt3D+v3rWbF3BaDqN0PShkj9RjRbMTFw2WXqVheTOkxi9dzV3oDLozJHEWIOacQSNrGU8XDyBtjwMqx/Dkr3lT2hAboK1J16CnS6pQkLKYQQ4khw4onwyiuQnw9//gmDB6u651HNXey7b7TX/30s0dD2YnU7Ahw8qJKIgUpw4XSCuQ4xrFMjUtHQakxsUS4zOhPcpYAOtsTgCxjZqfpjNbU7ofHannFxKnptsElWbDb1WiFE/aWnS8IKIQ63gs3qb0QHsMp5TBw+JhOMHAnffAPff6+CrIsa1Kd++qsVpoaCMxdW3Ato0PlW0Ey+hHIeF+hu2PRGo7dpSktB14+MJBEGg0oEIMTRpnNneOEFePRRmDVLJTstLITISOjRA0aNOgb6g4QQQgghhBBCCCGEEEIIIYQQQgghhBBCiCOcJLgQQgghhBBCCCGEEEKIZqpfSj/v/VX7VrF632pMBhO6rjMwdWATlkwIIYQILMoWRZQ1itzSXNrFtMNuPoRArQCOHECH0JZgtDZEEUU9rV+vAnzZ7dCiRXCvDbWE0iW+C8v2LsPpcfLHtj8waipCzaC0QY1QWiGaxoT2E7h/7v3e/yd2mHh4C1DfQMjBqhg4OSQFus2ELrfB7p+geBd4HGCOgoRhEJLcuGURQghxVBg50pdM7fHHYdiw2pd3uVQw2kZVn/NqMMkFKkXP9ZO0wRoHBpv/xAphrepepmZm3Trf/XbtggsibDfbKXIW1bpM5/jO4F6k/jHWI3JtVDdfsN2mlJ4Oa9dCdnblx7OyIDdX3Y+KgqSkys/HxUlgfiGEEEcW3QPFWep+/GAVfV6yDIjDaOxY+Ppr2L4dVq2C9u1rD65+zG6igeqnNdVNLRvglzGqybPiHtjwIrS/GqJ7ABrkLoU1j4M9udETXJjNat05nY36MUKIOggNhTPPbOpSCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQoj6awew7IYQQQgghhBBCCCGEEP7Eh8aTGpHKjrwd7C/ez9I9S3F73OjolZJfCCGEEM3VhPYTeHvZ20zqMOnQ38xdCuhgSzz09xKHZM0aFUi4Y8f6vX5oxlCW712Ojs7CXQtx624ABqZJAi9x9KhaXx/fbvzhLUB9AyGXloLV6v81dQ2cbDBD8thDK78QQohjVkQEDBoEc+fCrFnw+ecwYUIDJ7HYtq3yOXL16urLVH3s558P/RxZE0OF5Avu4urPh6bDhLVQWlbm4ixw5KrkFvFHbh1682bf/c6dg1vHCaEJbMndUusyfVP6ws756h+Dxf9CtSUPCUmre4EaW3q6JKsQQghx9CvZA3pZtPmwVuq+VsM5XIhGcMIJKmkFwE03wVdf1b78MZncoly96qfpMOg9mDcNNAOU7IWlt1ZfLKTx6702m1p/xX6aX0IIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCiLqRBBdCCCGEEEIIIYQQQgjRjA1JG8IHKz8AYHHWYnRUVA1JcCGEEOJI8OYpb/LWpLfQy6NCHQqPQ0WXMlgDLysa1cGD6m/btvV7/cDUgTy74FkA1u5fC4BRM9InuU9DFE+IZsGgGRjRcgS/bvkVgOTw5MNfCAmELIQQ4gh1ww3wxx/q/rnnwvffw4AB4PGAwaAedzpV8+CBB+DOO4N4823boH17KPGT0KCis86q/L/NppJHNca51WT33S/NBo8bDMbKy4Smq9tRpOIqCLZtkRGZETDBxdD0obD7JfWPu9T/QhWThxRnwc6vYcML6rmakmIIIYQQonEUbvXdD80ADH6W2QYH/SQnE6IBtG6tbps2wddfw9tvw/TpYDRWX9blgsWLoW/fw1/OI1rGVIjqCivuhq0fglblx9XdkHh8oxfDblcJLrZuDbysEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBDCPz+j/oUQQgghhBBCCCGEEEI0FxUTWWzP2w5AZlQm0fbopiqSEEIIUWeaplX6e0g8DsADRgky2tRKy2LDtmihggwHa2DaQO/97KJsALokdCHEHNIQxROi2RiVOQpQ9XchhBBC1N2ECXDSSSqQbH4+DBoE550H2arqiNutkl507AizZgX55tnZgZNb+FNS4itAQ7PE+O4fWAg0QILAI0BphZwToaHBvbZDbIdK/xs1IwbNNxxWQyMxLBGMZW0MTy3rPDQdYnpBykkQWyHpnsEcXKGEEEIIcWgKt/nuh2aCwVT9+a/aw19VEpEVZzV+2cQx43//U4n0AC65BF57Td13udRft1v9/fJLuOmmw1++o0JkRxj8Ppy0EjreAJnnQObZ0PF6OGkF9Hyg0YvQurVapzk5kuRCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQoj6kgQXQgghhBBCCCGEEEII0Yz1T+3vve/WVcSMwWmDm6o4QgghRNPRDIAGeg0ZFaxxYLBVfzysVaMW61jkcKi/Fkv9ElxkRmUSY1dBfPWy4L1D04c2VPGEaDau6HcF70x6h5/O+ampiyKEEEIccV55BWJiVJILXYc33oDERJUIwWKB8eNh06amLmUDMYerIM4AB/6tHsz5KOVwgKaBwaDWczDGtBnjvW81Wnl49MNM6TjF+1ir6LJ2oNEKGKBoR93eWK+YXMRPosaa2p0gbU8hhBDiUBVuBa2sUhDmJ1loabb/pFWO3EYtlji2TJkCI0aAyQRFRfCf/8CQIfDNN/DvvzBnjmqLnHoq5OY2dWmPcJEdocf9MOBVGPAa9PgfRHY6LB/dt6+v6j9vni+BiRBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQou6OjZmQQgghhBBCCCGEEEIIcYTq2aInRs3oTW4BlZNeCCGEEMcMg1VFP3WX+n8+NB0mrFWBzoqzVGCzsFYQP/CwFvNYUDHBRaX4r3WkaRpD0obw5bovvY8NTJP1JI4+EbYIzux2ZlMXQwghxJFs2zbIzvb9v3p15eer/h8XB+npjV+uw6BFCxVodNgw2LcP3GVdY0VFvmU0P/kHjlhxA6FoGxxY2NQlOWzKE1yYzcG/dkj6EO/9Uncpl/a9lAJHAZ+t+Qxd1xmcXpYg2J6iAmXnrQW3A4yW2t/YaPXd9zirJxvx1+4EaXsKIYQQDaFoG2BQFQRbQlOXRhyjNA3eekslQMjOVu2QefPUrSqD4fCXTzSMHj1Ukj23GxYsgNNPb+oSCSGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQghx5JEEF0IIIYQQQgghhBBCCNGM2c12Osd3ZtneZd7H+qX0a8ISCSGEEE3EYAE0cBfVvExourqJRuXxqL9GY/3fY2DawEoJLgakDjjEUgkhhBBCHGW2bYP27aGkpOZlzjqr8v82G6xde9QkuWjbFpYsgRtugLffVsFmTSaVZM3lUvk87rsvyDeNi1O/U22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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "onehot_seq = np.copy(irf4_onehot)\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_seq, class_no = 16)\n", + "_ = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_seq, class_no = 16)\n", + "#plt.savefig(\"tmp/irf4.pdf\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "f3e234c9-40d7-4878-b8c5-53d3020542f0", + "metadata": {}, + "source": [ + "#### Calculating and plotting nucleotide contribution scores and in silico saturation mutagenesis values \n", + "#### using the DeepMEL2_GABPA model and TERT promoter" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "22971289-b4c2-4ce0-9074-7df308516a3a", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "onehot_seq = np.copy(tert_onehot)\n", + "ntrack = 2\n", + "fig = plt.figure(figsize=(80,ntrack*5))\n", + "ax1 = utils.plot_deepexplainer_givenax_withrc(explainer=exp_dict[\"deepmel2_gabpa\"], fig=fig, ntrack=ntrack, track_no=1, seq_onehot=onehot_seq, class_no = 14)\n", + "_ = utils.plot_mutagenesis_givenax_fast_withrc(model=model_dict[\"deepmel2_gabpa\"], fig=fig, ntrack=ntrack, track_no=2, seq_onehot=onehot_seq, class_no = 14)\n", + "#plt.savefig(\"tmp/tert.pdf\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "974802be-468c-497a-9722-47a7390029e3", + "metadata": {}, + "source": [ + "#### Plotting prediction scores on IRF4 enhancer" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e8f43e84-3e05-4e8b-92db-1bc6ac84e4d2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "onehot_seq = np.copy(irf4_onehot)\n", + "prediction = model_dict[\"deepmel2\"].predict([onehot_seq,onehot_seq[:,::-1,::-1]])\n", + "\n", + "plt.figure(figsize=(8,4))\n", + "plt.bar(range(len(prediction[0])),prediction[0])\n", + "plt.title(\"DeepMEL2 - IRF4\")\n", + "plt.xlabel(\"Topics/Classes\")\n", + "plt.ylabel(\"Prediction scores\")\n", + "_ = plt.xticks(range(len(prediction[0])),range(1,len(prediction[0])+1),rotation=90)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4af7fcbd-2d95-42c6-8963-e09fa45dfcb5", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Deeplearning tf1.15", + "language": "python", + "name": "deeplearning_tf115" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/the_code/Human/README.txt b/the_code/Human/README.txt new file mode 100644 index 0000000000000000000000000000000000000000..b6d99172a8f7a0e0bcd6969145703ef36234e273 --- /dev/null +++ b/the_code/Human/README.txt @@ -0,0 +1,160 @@ +Dependencies: + DL Python environment to use DeepMEL, DeepMEL2, and DeepFlyBrain: + python=3.7 tensorflow-gpu=1.15 numpy=1.19.5 matplotlib=3.1.1 shap=0.29.3 ipykernel=5.1.2 h5py=2.10.0 TF-MoDISco 0.5.5.4 + + DL Python environment to train GAN models: + python=3.6 tensorflow-gpu=1.14.0 keras-gpu=2.2.4 numpy=1.16.2 matplotlib=3.1.1 shap=0.29.3 ipykernel=5.1.2 + + +Deepexplainer script update: + In order to calculate nucleotide contribution scores for only the selected class, + conda_env/lib/python3.7/site-packages/shap/explainers/_deep/deep_tf.py is updated by inserting the following codes at line 277: + elif output_rank_order.isnumeric(): + model_output_ranks = np.argsort(-model_output_values) + model_output_ranks[0] = int(output_rank_order) + + +MM_using_DeepMELs: + This notebook shows how to load and use the provided models. + It shows how to calculate and plot: + Predictions + Deepexplainer contribution scores + In silico saturation mutagenesis + 3 models are provided: DeepMEL, DeepMEL2, and DeepMEL2 with GABPA extension. + These models can be downloaded from Zenodo, which are used by Kipoi database: + DeepMEL: https://zenodo.org/records/3592129 + DeepMEL2: https://zenodo.org/records/4590308 + DeepMEL_GABPA: https://zenodo.org/records/4590405 + + +MM_EFS: + This notebook shows how to design synthetic sequences by using in silico evolution. + It uses the selected enhancers from the MM_Cbust_Homer notebook + It consists of: + Generating GC-adjusted random sequences: + Performing in silico evolution and random drift experiments. + Plotting the findings. + Printing generated DNA sequences in nucleotide letters. + Luciferase values are in ./data/luciferase folder + Intermediate files are saved to ./data/deepmel2 folder + Figures are saved to ./figures/evolution_from_scratch + + +MM_EFS_TFModisco: + This notebook shows the TFModiscco experiments. + It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. + It consists of: + Calculating contribution scores on synthetic sequences. + Performing TFModisco on contribution scores. + Plotting identified patterns. + Saving trimmed patterns as txt file to be later used for motif analysis. + Result files are saved to ./data/tfmodisco folder + Figures are saved to ./figures/tfmodisco folder + + +MM_EFS_Steps_Repressors: + This notebook shows how to perform mutations on generated sequences and visualize mutational steps. + It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. + It consists of: + Printing DNA sequences in nucleotide letters for different mutational steps. + Applying mutations to selected position and substation. + Plotting the findings. + Luciferase values are in ./data/luciferase folder + Result files are saved to ./data/tfmodisco folder + Figures are saved to ./figures/mutational_steps and ./figures/repressor_addition folders + + +MM_Enhance_Rescue: + This notebook shows the near-enhancer and enhancing active enhancer experiments. + Luciferase values are in ./data/enhance_rescue/luciferase folder + Figures are saved to ./figures/enhance_rescue folder + + +MM_IRF4_Experiments: + This notebook shows the experiments performed on IRF4 enhancer. + It consists of: + Loading the IRF4 enhancer sequence with different motif modifications. + Loading saturation mutagenesis assay performed on IRF4 enhancer by Kircher et al. + Showing individual mutations generating repressor binding sites on IRF4 enhancer. + Plotting the findings. + In vitro saturation mutagenesis assay value file is in ./data/irf4/ + Luciferase values are in ./data/luciferase folder + Figures are saved to ./figures/irf4 folder + + +MM_ZEB2_ChIP: + This notebook shows the experiments related to ZEB2 ChIP-seq on MM001 cell line. + Processed ZEB2 ChIP-seq (Antibody and input), ATAC-seq, and SOX10 ChIP-seq on MM001 files are in ./data/chip_seq + ZEB2 ChIP-seq summit file is in ./data/chip_seq + The notebook consists of: + Plotting ZEB2 vs SOX10 ChIP-seq values compared with accessibility. + Finding and plotting regions with high ZEB2 signal. + Plotting ZEB2 and SOX10 ChIP-seq values on irf4 locus + Figures are saved to ./figures/chip_seq folder + + +MM_Lenti_ATAC: + This notebook shows the experiments related to ATAC-seq on synthetic enhancer integrated cell lines. + Processed ATAC-seq data is in data/lenti_atac_chip folder. + It consist of: + Reading ATAC-seq files and calculating the coverage on the enhancers + Figures are saved to ./figures/lenti_atac_chip folder + + +MM_ChromBPnet_Experiments: + This notebooks shows scoring synthetic and genomic enhancer by using the ChromBPNet models trained on MM001 and MM047 cell lines. + It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. + The model files are provided in ./data/chrombpnet. + Figures are saved to ./figures/chrombpnet folder. + + +MM_Enformer_Experiments: + This notebooks shows scoring synthetic and genomic enhancer by using the Enformer model. + Enformer model is loaded from "https://tfhub.dev/deepmind/enformer/1" + Enformer class annotation is in ./data/enformer folder. + It uses the synthetic sequences file generated via MM_using_DeepMELs notebook. + The intermediate prediction files are in ./data/enformer folder. + Figures are saved to ./figures/enformer folder. + + +MM_Motif_Implanting: + This notebook shows how to design synthetic sequences by using motif implantation. + It consists of: + Performing motif implantation experiments. + Visualising motif distance preference experiments. + Replacing motifs on synthetic sequences with weaker ones from IRF4 enhancer. + Cutting and shortening designed sequences. + Luciferase values are in ./data/motif_embedding folder + Intermediate files are saved to ./data/motif_embedding folder + Figures are saved to ./figures/motif_embedding + + +MM_GAN: + This notebook shows how to load and analyse GAN generated sequences. + GAN generated sequences are provided in ./data/gan/generated_seqs folder. + Background sequences are provided in ./data/gan/background_seqs folder. + Genomic sequences are provided in ./data/gan folder + It consists of: + Reading GAN generated, genomic, and background sequences. + Scoring generated sequences with the DeepMEL model. + Visualising prediction scores on gan generated sequences at different training steps. + Comparing GC content of GAN generated and background sequences. + Visializing the luciferase results and contribution score plots. + Luciferase values are in ./data/luciferase folder + Intermediate files are saved to ./data/gan folder + Figures are saved to ./figures/gan folder + + +MM_Cbust_Homer: + This notebook shows ClusterBuster and Homer experiments. + It uses contribution scores and TFModisco scores generated in the MM_EFS_TFModisco notebook. + The motif database file is provided in ./data/tomtom folder + It consists of: + Getting TFModisco patterns and saving as txt file to be later used by ClusterBuster. + Running Tomtom on TFModisco patterns. + Running ClusterBuster by using TFModisco pattern PWMs on the sequences generated by in silico evolution, motif implantation, and GAN. + Running Homer using Random and Evolved sequences as foreground and background sequences, and vice versa. + ClusterBuster results are in ./data/cbust folder. + Homer results are in ./data/homer folder. + Figures are saved to ./figures/cbust folder + \ No newline at end of file diff --git a/the_code/Human/data/IRF4.gtf b/the_code/Human/data/IRF4.gtf new file mode 100644 index 0000000000000000000000000000000000000000..a3cecf89b19ee94c19b955fefe0a5d0f7eaabe8e 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index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/__pycache__/one_hot.cpython-38.pyc b/the_code/Human/data/chrombpnet/chrombpnet_utils/__pycache__/one_hot.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..327a352def5fb993534f49023d7c17a3c36c1c5c Binary files /dev/null and b/the_code/Human/data/chrombpnet/chrombpnet_utils/__pycache__/one_hot.cpython-38.pyc differ diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/argmanager.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/argmanager.py new file mode 100755 index 0000000000000000000000000000000000000000..bdaf232c1fe3137d89757af6c6e425f1eaab1629 --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/argmanager.py @@ -0,0 +1,61 @@ +import argparse + +def update_data_args(parser): + parser.add_argument("-g", "--genome", type=str, required=True, help="Genome fasta") + parser.add_argument("-b", "--bigwig", type=str, required=False, help="Bigwig of tn5 insertions. Ensure it is +4/-4 shifted") + parser.add_argument("-p", "--peaks", type=str, default="None", help="10 column bed file of peaks. Sequences and labels will be extracted centered at start (2nd col) + summit (10th col).") + parser.add_argument("-n", "--nonpeaks", type=str, default="None" ,help="10 column bed file of non-peak regions, centered at summit (10th column)") + parser.add_argument("-o", "--output_prefix", type=str, required=True, help="Output prefix") + parser.add_argument("-fl", "--chr_fold_path", type=str, required=True, help="Fold information - see splits.py to set folds") + parser.add_argument("--trackables",nargs="*",default=['loss','val_loss'], help="list of things to track per batch, such as logcount_predictions_loss,loss,profile_predictions_loss,val_logcount_predictions_loss,val_loss,val_profile_predictions_loss") + + +def update_train_args(parser): + parser.add_argument("-e", "--epochs", type=int, default=50, help="Maximum epochs to train") + parser.add_argument("-es", "--early-stop", type=int, default=5, help="Early stop limit, corresponds to 'patience' in callback") + parser.add_argument("-bs", "--batch_size", type=int, default=64) + parser.add_argument("-l", "--learning-rate", type=float, default=0.001) + parser.add_argument("-pf", "--params", type=str, required=True, default=None) + +def update_model_args(parser): + parser.add_argument("-s", "--seed", type=int, default=1234, help="seed to use for model training") + parser.add_argument("-a","--architecture_from_file",type=str,required=True, default=None, help="Model to use for training") + +def fetch_train_args(): + parser = argparse.ArgumentParser() + update_data_args(parser) + update_train_args(parser) + update_model_args(parser) + args = parser.parse_args() + + assert((args.peaks.lower() != "none") or (args.nonpeaks.lower() != "none")) #Both peaks and nonpeaks are empty" + + return args + +def fetch_predict_args(): + parser = argparse.ArgumentParser() + update_data_args(parser) + parser.add_argument("-m", "--model_h5", type=str, required=True, help="Path to model hdf5") + parser.add_argument("-bs", "--batch_size", type=int, default=512) + parser.add_argument("-s", "--seed", type=int, default=1234, help="seed to use for model training") + parser.add_argument("-il", "--inputlen", type=int, default=2114, help="Sequence input length") + parser.add_argument("-ol", "--outputlen", type=int, default=1000, help="Prediction output length") + args = parser.parse_args() + + assert((args.peaks.lower() != "none") or (args.nonpeaks.lower() != "none")) #Both peaks and nonpeaks are empty" + assert(args.inputlen % 2 ==0) + assert(args.outputlen % 2 ==0) + + return args + + +def fetch_modisco_args(): + parser = argparse.ArgumentParser() + parser.add_argument("-s", "--scores-prefix", type=str, required=True, help="Prefix to counts/profile h5 files. Will use prefix.{profile,counts}_scores.h5") + parser.add_argument("-p","--profile-or-counts", type=str, required=True, help="Scoring method to use, profile or counts scores") + parser.add_argument("-o", "--output-dir", type=str, required=True, help="Output directory") + parser.add_argument("-c", "--crop", type=int, default=500, help="Crop scores to this width from the center for each example") + parser.add_argument("-m", "--max-seqlets", type=int, default=50000, help="Max number of seqlets per metacluster for modisco") + + args = parser.parse_args() + return args diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/augment.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/augment.py new file mode 100755 index 0000000000000000000000000000000000000000..2d43c510ff900c127b8986e006aba2f813013db5 --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/augment.py @@ -0,0 +1,84 @@ +import numpy as np + +# https://stackoverflow.com/questions/46091111/python-slice-array-at-different-position-on-every-row +def take_per_row(A, indx, num_elem): + """ + Matrix A, indx is a vector for each row which specifies + slice beginning for that row. Each has width num_elem. + """ + + all_indx = indx[:,None] + np.arange(num_elem) + return A[np.arange(all_indx.shape[0])[:,None], all_indx] + + +def random_crop(seqs, labels, seq_crop_width, label_crop_width, coords): + """ + Takes sequences and corresponding counts labels. They should have the same + #examples. The widths would correspond to inputlen and outputlen respectively, + and any additional flanking width for jittering which should be the same + for seqs and labels. Each example is cropped starting at a random offset. + + seq_crop_width - label_crop_width should be equal to seqs width - labels width, + essentially implying they should have the same flanking width. + """ + + assert(seqs.shape[1]>=seq_crop_width) + assert(labels.shape[1]>=label_crop_width) + assert(seqs.shape[1] - seq_crop_width == labels.shape[1] - label_crop_width) + + max_start = seqs.shape[1] - seq_crop_width # This should be the same for both input and output + + starts = np.random.choice(range(max_start+1), size=seqs.shape[0], replace=True) + + new_coords = coords.copy() + new_coords[:,1] = new_coords[:,1].astype(int) - (seqs.shape[1]//2) + starts + + return take_per_row(seqs, starts, seq_crop_width), take_per_row(labels, starts, label_crop_width), new_coords + +def random_rev_comp(seqs, labels, coords, frac=0.5): + """ + Data augmentation: applies reverse complement randomly to a fraction of + sequences and labels. + + Assumes seqs are arranged in ACGT. Then ::-1 gives TGCA which is revcomp. + + NOTE: Performs in-place modification. + """ + + pos_to_rc = np.random.choice(range(seqs.shape[0]), + size=int(seqs.shape[0]*frac), + replace=False) + + seqs[pos_to_rc] = seqs[pos_to_rc, ::-1, ::-1] + labels[pos_to_rc] = labels[pos_to_rc, ::-1] + coords[pos_to_rc,2] = "r" + + return seqs, labels, coords + +def crop_revcomp_augment(seqs, labels, coords, seq_crop_width, label_crop_width, add_revcomp, rc_frac=0.5, shuffle=False): + """ + seqs: B x IL x 4 + labels: B x OL + + Applies random crop to seqs and labels and reverse complements rc_frac. + """ + + assert(seqs.shape[0]==labels.shape[0]) + + # this does not modify seqs and labels + #mod_seqs, mod_labels, mod_coords = random_crop(seqs, labels, seq_crop_width, label_crop_width, coords) + mod_seqs, mod_labels, mod_coords = seqs, labels, coords + + # this modifies mod_seqs, mod_labels in-place + if add_revcomp: + mod_seqs, mod_labels, mod_coords = random_rev_comp(mod_seqs, mod_labels, mod_coords, frac=rc_frac) + + + if shuffle: + perm = np.random.permutation(mod_seqs.shape[0]) + mod_seqs = mod_seqs[perm] + mod_labels = mod_labels[perm] + mod_coords = mod_coords[perm] + + + return mod_seqs, mod_labels, mod_coords diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/callbacks.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/callbacks.py new file mode 100755 index 0000000000000000000000000000000000000000..7a9fcb8714c4c26180e064fc7caf45aee8eeb208 --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/callbacks.py @@ -0,0 +1,40 @@ +import tensorflow.keras as keras + +class LossHistory(keras.callbacks.Callback): + """ + Callbacks to store train, validation loss at the the end of every batch and the end of every epoch. + You can also track the counts loss and profile loss seperatley using the callbacks provided. + """ + + def __init__(self,model_output_path_logs_name,to_track): + self.model_output_path_logs_name=model_output_path_logs_name + self.to_track=to_track + self.outf=open(self.model_output_path_logs_name,'w') + self.outf.write('Epoch\tBatch\t'+'\t'.join(self.to_track)+'\n') + keras.callbacks.Callback.__init__(self) + + def on_train_begin(self, logs={}): + self.losses ={} + + def on_epoch_begin(self,epoch, logs={}): + self.losses[epoch]={} + for trackable in self.to_track: + self.losses[epoch][trackable]=[] + self.cur_epoch=epoch + + def on_batch_end(self, batch, logs={}): + for trackable in self.to_track: + self.losses[self.cur_epoch][trackable].append(logs.get(trackable)) + + def on_epoch_end(self,epoch,logs={}): + marker=self.to_track[0] + num_batches=len(self.losses[self.cur_epoch][marker]) + for i in range(num_batches): + self.outf.write(str(epoch)+'\t'+str(i)) + for trackable in self.to_track: + self.outf.write('\t'+str(self.losses[epoch][trackable][i])) + self.outf.write('\n') + + + def on_train_end(self,logs={}): + self.outf.close() diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/data_utils.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/data_utils.py new file mode 100755 index 0000000000000000000000000000000000000000..261fd64ee3e321372b41cb02ead0cbbc67f00107 --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/data_utils.py @@ -0,0 +1,100 @@ +import numpy as np +import pandas as pd +import pyBigWig +import pyfaidx +from chrombpnet.training.utils import one_hot + + +def get_seq(peaks_df, genome, width): + """ + Same as get_cts, but fetches sequence from a given genome. + """ + vals = [] + + for i, r in peaks_df.iterrows(): + sequence = str(genome[r['chr']][(r['start']+r['summit'] - width//2):(r['start'] + r['summit'] + width//2)]) + vals.append(sequence) + + return one_hot.dna_to_one_hot(vals) + + +def get_cts(peaks_df, bw, width): + """ + Fetches values from a bigwig bw, given a df with minimally + chr, start and summit columns. Summit is relative to start. + Retrieves values of specified width centered at summit. + + "cts" = per base counts across a region + """ + vals = [] + for i, r in peaks_df.iterrows(): + vals.append(np.nan_to_num(bw.values(r['chr'], + r['start'] + r['summit'] - width//2, + r['start'] + r['summit'] + width//2))) + + return np.array(vals) + +def get_coords(peaks_df, peaks_bool): + """ + Fetch the co-ordinates of the regions in bed file + returns a list of tuples with (chrom, summit) + """ + vals = [] + for i, r in peaks_df.iterrows(): + vals.append([r['chr'], r['start']+r['summit'], "f", peaks_bool]) + + return np.array(vals) + +def get_seq_cts_coords(peaks_df, genome, bw, input_width, output_width, peaks_bool): + + seq = get_seq(peaks_df, genome, input_width) + cts = get_cts(peaks_df, bw, output_width) + coords = get_coords(peaks_df, peaks_bool) + return seq, cts, coords + +def load_data(bed_regions, nonpeak_regions, genome_fasta, cts_bw_file, inputlen, outputlen, max_jitter): + """ + Load sequences and corresponding base resolution counts for training, + validation regions in peaks and nonpeaks (2 x 2 x 2 = 8 matrices). + + For training peaks/nonpeaks, values for inputlen + 2*max_jitter and outputlen + 2*max_jitter + are returned centered at peak summit. This allows for jittering examples by randomly + cropping. Data of width inputlen/outputlen is returned for validation + data. + + If outliers is not None, removes training examples with counts > outlier%ile + """ + + cts_bw = pyBigWig.open(cts_bw_file) + genome = pyfaidx.Fasta(genome_fasta) + + train_peaks_seqs=None + train_peaks_cts=None + train_peaks_coords=None + train_nonpeaks_seqs=None + train_nonpeaks_cts=None + train_nonpeaks_coords=None + + if bed_regions is not None: + train_peaks_seqs, train_peaks_cts, train_peaks_coords = get_seq_cts_coords(bed_regions, + genome, + cts_bw, + inputlen+2*max_jitter, + outputlen+2*max_jitter, + peaks_bool=1) + + if nonpeak_regions is not None: + train_nonpeaks_seqs, train_nonpeaks_cts, train_nonpeaks_coords = get_seq_cts_coords(nonpeak_regions, + genome, + cts_bw, + inputlen, + outputlen, + peaks_bool=0) + + + + cts_bw.close() + genome.close() + + return (train_peaks_seqs, train_peaks_cts, train_peaks_coords, + train_nonpeaks_seqs, train_nonpeaks_cts, train_nonpeaks_coords) diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/losses.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/losses.py new file mode 100755 index 0000000000000000000000000000000000000000..525e38bc5b0af1c05ef94b8c28ebf57aa854044d --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/losses.py @@ -0,0 +1,20 @@ +import tensorflow as tf +import tensorflow_probability as tfp + + +#from https://github.com/kundajelab/basepair/blob/cda0875571066343cdf90aed031f7c51714d991a/basepair/losses.py#L87 +def multinomial_nll(true_counts, logits): + """Compute the multinomial negative log-likelihood + Args: + true_counts: observed count values + logits: predicted logit values + """ + counts_per_example = tf.reduce_sum(true_counts, axis=-1) + dist = tfp.distributions.Multinomial(total_count=counts_per_example, + logits=logits) + return (-tf.reduce_sum(dist.log_prob(true_counts)) / + tf.cast(tf.shape(true_counts)[0], dtype=tf.float32)) + + + + diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/metrics_utils.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/metrics_utils.py new file mode 100755 index 0000000000000000000000000000000000000000..55711f6240e77af49c909510135161017d4cf55b --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/metrics_utils.py @@ -0,0 +1,204 @@ + +import numpy as np +import matplotlib +from matplotlib import pyplot as plt +from matplotlib import cm +from matplotlib.colors import Normalize +from scipy.interpolate import interpn +from scipy.stats import multinomial +import math +from scipy.spatial.distance import jensenshannon + + +plt.rcParams["figure.figsize"]=10,5 +font = {'family' : 'normal', + 'weight' : 'bold', + 'size' : 10} +matplotlib.rc('font', **font) + + +def _fix_sum_to_one(probs): + """ + Fix probability arrays whose sum is fractinally above or + below 1.0 + + Args: + probs (numpy.ndarray): An array whose sum is almost equal + to 1.0 + + Returns: + np.ndarray: array that sums to 1 + """ + + _probs = np.copy(probs) + + if np.sum(_probs) > 1.0: + _probs[np.argmax(_probs)] -= np.sum(_probs) - 1.0 + + if np.sum(_probs) < 1.0: + _probs[np.argmin(_probs)] += 1.0 - np.sum(_probs) + + return _probs + + +def density_scatter(x, y, xlab, ylab, ax = None, sort = True, bins = 20): + """ + Scatter plot colored by 2d histogram + """ + bad_indices=np.where(np.isnan(x))+np.where(np.isnan(y)) + x=x[~np.isin(np.arange(x.size),bad_indices)] + y=y[~np.isin(np.arange(y.size),bad_indices)] + + if ax is None : + fig , ax = plt.subplots() + data , x_e, y_e = np.histogram2d( x, y, bins = bins, density = True ) + z = interpn( ( 0.5*(x_e[1:] + x_e[:-1]) , 0.5*(y_e[1:]+y_e[:-1]) ) , data , np.vstack([x,y]).T , method = "splinef2d", bounds_error = False) + + #To be sure to plot all data + z[np.where(np.isnan(z))] = 0.0 + # Sort the points by density, so that the densest points are plotted last + if sort : + idx = z.argsort() + x, y, z = x[idx], y[idx], z[idx] + + ax.scatter( x, y, c=z ) + + norm = Normalize(vmin = np.min(z), vmax = np.max(z)) + cbar = fig.colorbar(cm.ScalarMappable(norm = norm), ax=ax) + cbar.ax.set_ylabel('Density') + plt.xlabel(xlab) + plt.ylabel(ylab) + return ax + +#https://github.com/kundajelab/basepairmodels/blob/cf8e346e9df1bad9e55bd459041976b41207e6e5/basepairmodels/cli/metrics.py#L18 +# replacing TracebackExceptions with assertions +def mnll(true_counts, logits=None, probs=None): + """ + Compute the multinomial negative log-likelihood between true + counts and predicted values of a BPNet-like profile model + + One of `logits` or `probs` must be given. If both are + given `logits` takes preference. + Args: + true_counts (numpy.array): observed counts values + + logits (numpy.array): predicted logits values + + probs (numpy.array): predicted values as probabilities + + Returns: + float: cross entropy + + """ + + dist = None + + if logits is not None: + + # check for length mismatch + assert (len(logits) == len(true_counts)) + + # convert logits to softmax probabilities + probs = logits - logsumexp(logits) + probs = np.exp(probs) + + elif probs is not None: + + # check for length mistmatch + assert(len(probs) == len(true_counts)) + + # check if probs sums to 1 + # why is this nans sometimes + assert( abs(1.0 - np.sum(probs)) < 1e-1) + + else: + + # both 'probs' and 'logits' are None + print( + "At least one of probs or logits must be provided. " + "Both are None.") + + # compute the nmultinomial distribution + mnom = multinomial(np.sum(true_counts), probs) + return -(mnom.logpmf(true_counts) / len(true_counts)) + +#https://github.com/kundajelab/basepairmodels/blob/cf8e346e9df1bad9e55bd459041976b41207e6e5/basepairmodels/cli/metrics.py#L129 +def get_min_max_normalized_value(val, minimum, maximum): + ret_val = (val - minimum) / (maximum - minimum) + + if ret_val < 0: + return 0 + + if ret_val > 1: + return 1 + return ret_val + +#https://github.com/kundajelab/basepairmodels/blob/cf8e346e9df1bad9e55bd459041976b41207e6e5/basepairmodels/cli/fastpredict.py#L59 +def mnll_min_max_bounds(profile): + """ + Min Max bounds for the mnll metric + + Args: + profile (numpy.ndarray): true profile + Returns: + tuple: (min, max) bounds values + """ + + # uniform distribution profile + uniform_profile = np.ones(len(profile)) * (1.0 / len(profile)) + + # profile as probabilities + profile = profile.astype(np.float64) + + # profile as probabilities + profile_prob = profile / np.sum(profile) + + # the scipy.stats.multinomial function is very sensitive to + # profile_prob summing to exactly 1.0, if not you get NaN as the + # resuls. In majority of the cases we can fix that problem by + # adding or substracting the difference (but unfortunately it + # doesnt always and there are cases where we still see NaNs, and + # those we'll set to 0) + profile_prob = _fix_sum_to_one(profile_prob) + #print(profile, profile_prob) + + # mnll of profile with itself + min_mnll = mnll(profile, probs=profile_prob) + + # if we still find a NaN, even after the above fix, set it to zero + if math.isnan(min_mnll): + min_mnll = 0.0 + + if math.isinf(min_mnll): + min_mnll = 0.0 + + # mnll of profile with uniform profile + max_mnll = mnll(profile, probs=uniform_profile) + + return (min_mnll, max_mnll) + +#https://github.com/kundajelab/basepairmodels/blob/cf8e346e9df1bad9e55bd459041976b41207e6e5/basepairmodels/cli/fastpredict.py#L131 +def jsd_min_max_bounds(profile): + """ + Min Max bounds for the jsd metric + + Args: + profile (numpy.ndarray): true profile + + Returns: + tuple: (min, max) bounds values + """ + + # uniform distribution profile + uniform_profile = np.ones(len(profile)) * (1.0 / len(profile)) + + # profile as probabilities + profile_prob = profile / np.sum(profile) + + # jsd of profile with uniform profile + max_jsd = jensenshannon(profile_prob, uniform_profile) + + # jsd of profile with itself (upper bound) + min_jsd = 0.0 + + return (min_jsd, max_jsd) diff --git a/the_code/Human/data/chrombpnet/chrombpnet_utils/one_hot.py b/the_code/Human/data/chrombpnet/chrombpnet_utils/one_hot.py new file mode 100755 index 0000000000000000000000000000000000000000..4fadf92a3738e7462cc1b99c55cf7fa6127dff8e --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_utils/one_hot.py @@ -0,0 +1,61 @@ +""" +Written by Alex Tseng + +https://gist.github.com/amtseng/010dd522daaabc92b014f075a34a0a0b +""" + +import numpy as np + +def dna_to_one_hot(seqs): + """ + Converts a list of DNA ("ACGT") sequences to one-hot encodings, where the + position of 1s is ordered alphabetically by "ACGT". `seqs` must be a list + of N strings, where every string is the same length L. Returns an N x L x 4 + NumPy array of one-hot encodings, in the same order as the input sequences. + All bases will be converted to upper-case prior to performing the encoding. + Any bases that are not "ACGT" will be given an encoding of all 0s. + """ + seq_len = len(seqs[0]) + assert np.all(np.array([len(s) for s in seqs]) == seq_len) + + # Join all sequences together into one long string, all uppercase + seq_concat = "".join(seqs).upper() + "ACGT" + # Add one example of each base, so np.unique doesn't miss indices later + + one_hot_map = np.identity(5)[:, :-1].astype(np.int8) + + # Convert string into array of ASCII character codes; + base_vals = np.frombuffer(bytearray(seq_concat, "utf8"), dtype=np.int8) + + # Anything that's not an A, C, G, or T gets assigned a higher code + base_vals[~np.isin(base_vals, np.array([65, 67, 71, 84]))] = 85 + + # Convert the codes into indices in [0, 4], in ascending order by code + _, base_inds = np.unique(base_vals, return_inverse=True) + + # Get the one-hot encoding for those indices, and reshape back to separate + return one_hot_map[base_inds[:-4]].reshape((len(seqs), seq_len, 4)) + + +def one_hot_to_dna(one_hot): + """ + Converts a one-hot encoding into a list of DNA ("ACGT") sequences, where the + position of 1s is ordered alphabetically by "ACGT". `one_hot` must be an + N x L x 4 array of one-hot encodings. Returns a lits of N "ACGT" strings, + each of length L, in the same order as the input array. The returned + sequences will only consist of letters "A", "C", "G", "T", or "N" (all + upper-case). Any encodings that are all 0s will be translated to "N". + """ + bases = np.array(["A", "C", "G", "T", "N"]) + # Create N x L array of all 5s + one_hot_inds = np.tile(one_hot.shape[2], one_hot.shape[:2]) + + # Get indices of where the 1s are + batch_inds, seq_inds, base_inds = np.where(one_hot) + + # In each of the locations in the N x L array, fill in the location of the 1 + one_hot_inds[batch_inds, seq_inds] = base_inds + + # Fetch the corresponding base for each position using indexing + seq_array = bases[one_hot_inds] + return ["".join(seq) for seq in seq_array] diff --git a/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM001.h5 b/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM001.h5 new file mode 100755 index 0000000000000000000000000000000000000000..e08a341f61b0465dc1a4bae14281a877dba133fb --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM001.h5 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f7eea9ff9e6264f4b2c1cccfd30512982ee2077d5246f79941de813afe56a3a5 +size 25582648 diff --git a/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM047.h5 b/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM047.h5 new file mode 100755 index 0000000000000000000000000000000000000000..ac1b82eb7dfb18cf72d2e33d2a8f0790341a5374 --- /dev/null +++ b/the_code/Human/data/chrombpnet/chrombpnet_wo_bias_MM047.h5 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:86e95e1826ac06ca86150cff19c996bf47af6038c001004e726b709ad3837d15 +size 25582648 diff --git a/the_code/Human/data/deepmel2/DeepMEL2_nonAugmented_data.pkl b/the_code/Human/data/deepmel2/DeepMEL2_nonAugmented_data.pkl new file mode 100644 index 0000000000000000000000000000000000000000..e8f8b667311dd2c720950228086532201c8b0e78 --- /dev/null +++ b/the_code/Human/data/deepmel2/DeepMEL2_nonAugmented_data.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4c7d5f0bb2c5a31d5d49b68ced4d0f0e6c145a16791f8d499a7638fb23e91e4a +size 440085279 diff --git a/the_code/Human/data/deepmel2/Genomic_MEL_regions.fa b/the_code/Human/data/deepmel2/Genomic_MEL_regions.fa new file mode 100644 index 0000000000000000000000000000000000000000..9cd3e17bb7e44f585245aff055eff95e4bfc20b6 --- /dev/null +++ b/the_code/Human/data/deepmel2/Genomic_MEL_regions.fa @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2acfc770926abdb83c085808e2900abf75855a20e652402d5267f3380e02925c +size 2047064 diff --git a/the_code/Human/data/deepmel2/MM_EFS_4000_withmut.pkl b/the_code/Human/data/deepmel2/MM_EFS_4000_withmut.pkl new file mode 100644 index 0000000000000000000000000000000000000000..caa7ad52b699abdddb953023576bbbefb141a8c2 --- /dev/null +++ b/the_code/Human/data/deepmel2/MM_EFS_4000_withmut.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f6be787444dd8a1c42bcc1b3e0f5294d26f61c7d6c159a332446511af3dc52df +size 28183920 diff --git a/the_code/Human/data/deepmel2/MM_RandomDrift_4000_withmut.pkl b/the_code/Human/data/deepmel2/MM_RandomDrift_4000_withmut.pkl new file mode 100644 index 0000000000000000000000000000000000000000..9ea75a0affbc993d6f85fda65cb86096c2282de3 --- /dev/null +++ b/the_code/Human/data/deepmel2/MM_RandomDrift_4000_withmut.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:315cc9eed356687bffdd65a30859efb39fec0df6d309a127f40bbc0697d9df42 +size 33392430 diff --git a/the_code/Human/data/enformer/Enformer_classes.txt b/the_code/Human/data/enformer/Enformer_classes.txt new file mode 100644 index 0000000000000000000000000000000000000000..adf6358a7c579b6f9e0f0876b9c460d1ea1c42bc --- /dev/null +++ b/the_code/Human/data/enformer/Enformer_classes.txt @@ -0,0 +1,5314 @@ +index genome identifier file clip scale sum_stat description assay_type target assay_subtype DNASE: cell-type agnostic CAGE: cell-type agnostic CAGE: IRF6 CAGE: TERT-GBM CAGE: ZFAND3 CAGE: HNF4A,MSMB,TERT-HEK293T,MYCrs6983267 CAGE: GP1BB,HBB,HBG1,PKLR CAGE: F9,LDLR,SORT1 DNASE: IRF4 DNASE: IRF6 DNASE: ZFAND3 DNASE: HNF4A,MSMB,TERT-HEK293T,MYCrs6983267 DNASE: GP1BB,HBB,HBG1,PKLR DNASE: F9,LDLR,SORT1 +0 0 ENCFF833POA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIJ/summary/coverage.w5 32 2 mean DNASE:cerebellum male adult (27 years) and male adult (35 years) DNASE DNase/cerebellum male adult (27 years) and male adult (35 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1 0 ENCFF110QGM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIK/summary/coverage.w5 32 2 mean DNASE:frontal cortex male adult (27 years) and male adult (35 years) DNASE DNase/frontal cortex male adult (27 years) and male adult (35 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2 0 ENCFF880MKD /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIL/summary/coverage.w5 32 2 mean DNASE:chorion DNASE DNase/chorion DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3 0 ENCFF463ZLQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIP/summary/coverage.w5 32 2 mean DNASE:Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour DNASE DNase/Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4 0 ENCFF890OGQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIS/summary/coverage.w5 32 2 mean DNASE:GM03348 DNASE DNase/GM03348 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5 0 ENCFF996AEF /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIT/summary/coverage.w5 32 2 mean DNASE:GM03348 genetically modified using transduction treated with 3 ug/mL doxycycline for 10 days DNASE "DNase/GM03348 genetically modified using transduction treated with 3 ug;mL doxycycline for 10 days" DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +6 0 ENCFF660YSU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIV/summary/coverage.w5 32 2 mean DNASE:AG08395 DNASE DNase/AG08395 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +7 0 ENCFF787MSC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIW/summary/coverage.w5 32 2 mean DNASE:AG08396 DNASE DNase/AG08396 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +8 0 ENCFF568LMQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIX/summary/coverage.w5 32 2 mean DNASE:AG20443 DNASE DNase/AG20443 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +9 0 ENCFF685MZL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EIY/summary/coverage.w5 32 2 mean DNASE:frontal cortex female adult (67 years) and female adult (80 years) DNASE DNase/frontal cortex female adult (67 years) and female adult (80 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +10 0 ENCFF452DLO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJA/summary/coverage.w5 32 2 mean DNASE:H54 DNASE DNase/H54 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +11 0 ENCFF149TAY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJB/summary/coverage.w5 32 2 mean DNASE:GM10248 DNASE DNase/GM10248 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +12 0 ENCFF093VXI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJD/summary/coverage.w5 32 2 mean DNASE:GM12878 DNASE DNase/GM12878 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +13 0 ENCFF713YTW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJE/summary/coverage.w5 32 2 mean DNASE:GM12891 DNASE DNase/GM12891 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +14 0 ENCFF536IEC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJF/summary/coverage.w5 32 2 mean DNASE:GM12892 DNASE DNase/GM12892 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +15 0 ENCFF714ZSE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJI/summary/coverage.w5 32 2 mean DNASE:GM18507 DNASE DNase/GM18507 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +16 0 ENCFF385ITM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJJ/summary/coverage.w5 32 2 mean DNASE:GM19238 DNASE DNase/GM19238 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +17 0 ENCFF919WIT /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJK/summary/coverage.w5 32 2 mean DNASE:GM19239 DNASE DNase/GM19239 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +18 0 ENCFF814MPK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJL/summary/coverage.w5 32 2 mean DNASE:GM19240 DNASE DNase/GM19240 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +19 0 ENCFF153XQL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJN/summary/coverage.w5 32 2 mean DNASE:H1-hESC DNASE DNase/H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +20 0 ENCFF753SCX /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJO/summary/coverage.w5 32 2 mean DNASE:H7-hESC DNASE DNase/H7-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +21 0 ENCFF663TLI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJP/summary/coverage.w5 32 2 mean DNASE:H9 DNASE DNase/H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +22 0 ENCFF082SFS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJQ/summary/coverage.w5 32 2 mean DNASE:heart male adult (27 years) and male adult (35 years) DNASE DNase/heart male adult (27 years) and male adult (35 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +23 0 ENCFF148BGE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJR/summary/coverage.w5 32 2 mean DNASE:HEK293T DNASE DNase/HEK293T DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE +24 0 ENCFF422TAV /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJS/summary/coverage.w5 32 2 mean DNASE:HeLa-S3 treated with interferon alpha for 4 hours DNASE DNase/HeLa-S3 treated with interferon alpha for 4 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +25 0 ENCFF050BDU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJT/summary/coverage.w5 32 2 mean DNASE:HeLa-S3 DNASE DNase/HeLa-S3 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +26 0 ENCFF818FXA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJU/summary/coverage.w5 32 2 mean DNASE:hepatocyte DNASE DNase/hepatocyte DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +27 0 ENCFF136DBS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EJV/summary/coverage.w5 32 2 mean DNASE:HepG2 DNASE DNase/HepG2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE +28 0 ENCFF284JHO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKC/summary/coverage.w5 32 2 mean DNASE:HTR-8/SVneo DNASE "DNase/HTR-8;SVneo" DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +29 0 ENCFF305BCB /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKF/summary/coverage.w5 32 2 mean DNASE:endothelial cell of umbilical vein newborn DNASE DNase/endothelial cell of umbilical vein newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +30 0 ENCFF015IAT /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKI/summary/coverage.w5 32 2 mean DNASE:CWRU1 male DNASE DNase/CWRU1 male DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +31 0 ENCFF565AEK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKJ/summary/coverage.w5 32 2 mean DNASE:iPS-NIHi11 male adult (71 year) originated from AG20443 DNASE DNase/iPS-NIHi11 male adult (71 year) originated from AG20443 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +32 0 ENCFF637TYS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKK/summary/coverage.w5 32 2 mean DNASE:iPS-NIHi7 female adult (85 years) originated from AG08395 DNASE DNase/iPS-NIHi7 female adult (85 years) originated from AG08395 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +33 0 ENCFF899YDP /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKN/summary/coverage.w5 32 2 mean DNASE:K562 treated with 1 uM vorinostat for 72 hours DNASE DNase/K562 treated with 1 uM vorinostat for 72 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +34 0 ENCFF515UNC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKP/summary/coverage.w5 32 2 mean DNASE:K562 G2 phase DNASE DNase/K562 G2 phase DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +35 0 ENCFF708UIS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKQ/summary/coverage.w5 32 2 mean DNASE:K562 G1 phase DNASE DNase/K562 G1 phase DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +36 0 ENCFF809IIW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKT/summary/coverage.w5 32 2 mean DNASE:LNCaP clone FGC DNASE DNase/LNCaP clone FGC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +37 0 ENCFF009NEA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKU/summary/coverage.w5 32 2 mean DNASE:LNCaP clone FGC treated with 1 nM 17B-hydroxy-17-methylestra-4,9,11-trien-3-one for 12 hours DNASE DNase/LNCaP clone FGC treated with 1 nM 17B-hydroxy-17-methylestra-4,9,11-trien-3-one for 12 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +38 0 ENCFF382YNA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EKZ/summary/coverage.w5 32 2 mean DNASE:MCF-7 originated from MCF-7 DNASE DNase/MCF-7 originated from MCF-7 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +39 0 ENCFF585BKY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELA/summary/coverage.w5 32 2 mean DNASE:medulloblastoma DNASE DNase/medulloblastoma DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +40 0 ENCFF863UGY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELD/summary/coverage.w5 32 2 mean DNASE:epidermal melanocyte DNASE DNase/epidermal melanocyte DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +41 0 ENCFF678LXL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELE/summary/coverage.w5 32 2 mean DNASE:CD14-positive monocyte female DNASE DNase/CD14-positive monocyte female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +42 0 ENCFF690MIA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELH/summary/coverage.w5 32 2 mean DNASE:keratinocyte female DNASE DNase/keratinocyte female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE +43 0 ENCFF300IKA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELJ/summary/coverage.w5 32 2 mean DNASE:osteoblast DNASE DNase/osteoblast DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +44 0 ENCFF927VUO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELO/summary/coverage.w5 32 2 mean DNASE:psoas muscle male adult (27 years) and male adult (35 years) DNASE DNase/psoas muscle male adult (27 years) and male adult (35 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +45 0 ENCFF613XPC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELS/summary/coverage.w5 32 2 mean DNASE:T47D treated with 10 nM 17B-estradiol for 30 minutes DNASE DNase/T47D treated with 10 nM 17B-estradiol for 30 minutes DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +46 0 ENCFF300QLZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELV/summary/coverage.w5 32 2 mean DNASE:urothelium cell line DNASE DNase/urothelium cell line DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +47 0 ENCFF688CJL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELW/summary/coverage.w5 32 2 mean DNASE:A549 DNASE DNase/A549 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +48 0 ENCFF802ZBQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELX/summary/coverage.w5 32 2 mean DNASE:AG04449 DNASE DNase/AG04449 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +49 0 ENCFF882YMD /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELY/summary/coverage.w5 32 2 mean DNASE:AG04450 DNASE DNase/AG04450 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +50 0 ENCFF160AIM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ELZ/summary/coverage.w5 32 2 mean DNASE:AG09309 DNASE DNase/AG09309 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +51 0 ENCFF294KLB /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMA/summary/coverage.w5 32 2 mean DNASE:AG09319 DNASE DNase/AG09319 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +52 0 ENCFF211SDO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMB/summary/coverage.w5 32 2 mean DNASE:AG10803 DNASE DNase/AG10803 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +53 0 ENCFF869ECL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMC/summary/coverage.w5 32 2 mean DNASE:fibroblast of the aortic adventitia female DNASE DNase/fibroblast of the aortic adventitia female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +54 0 ENCFF695WLT /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMD/summary/coverage.w5 32 2 mean DNASE:BE2C DNASE DNase/BE2C DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +55 0 ENCFF107IJY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EME/summary/coverage.w5 32 2 mean DNASE:BJ DNASE DNase/BJ DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +56 0 ENCFF132EIR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMF/summary/coverage.w5 32 2 mean DNASE:HS-27A DNASE DNase/HS-27A DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +57 0 ENCFF964WLS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMG/summary/coverage.w5 32 2 mean DNASE:HS-5 DNASE DNase/HS-5 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +58 0 ENCFF747REW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMH/summary/coverage.w5 32 2 mean DNASE:stromal cell of bone marrow male DNASE DNase/stromal cell of bone marrow male DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +59 0 ENCFF085OHV /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMI/summary/coverage.w5 32 2 mean DNASE:Caco-2 DNASE DNase/Caco-2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +60 0 ENCFF801IWM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMJ/summary/coverage.w5 32 2 mean DNASE:B cell female adult (43 years) DNASE DNase/B cell female adult (43 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +61 0 ENCFF274MGW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMK/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell DNASE DNase/hematopoietic multipotent progenitor cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +62 0 ENCFF753ETN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EML/summary/coverage.w5 32 2 mean DNASE:naive thymus-derived CD4-positive, alpha-beta T cell male adult (26 years) DNASE DNase/naive thymus-derived CD4-positive, alpha-beta T cell male adult (26 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +63 0 ENCFF391HDR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMN/summary/coverage.w5 32 2 mean DNASE:CMK DNASE DNase/CMK DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +64 0 ENCFF171BUA /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMO/summary/coverage.w5 32 2 mean DNASE:GM04503 DNASE DNase/GM04503 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +65 0 ENCFF602PIH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMP/summary/coverage.w5 32 2 mean DNASE:GM04504 DNASE DNase/GM04504 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +66 0 ENCFF617HEH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMQ/summary/coverage.w5 32 2 mean DNASE:GM06990 DNASE DNase/GM06990 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +67 0 ENCFF709TDR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMR/summary/coverage.w5 32 2 mean DNASE:GM12864 DNASE DNase/GM12864 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +68 0 ENCFF427FEF /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMS/summary/coverage.w5 32 2 mean DNASE:GM12865 DNASE DNase/GM12865 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +69 0 ENCFF915DFR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMT/summary/coverage.w5 32 2 mean DNASE:GM12878 DNASE DNase/GM12878 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +70 0 ENCFF131HMO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMU/summary/coverage.w5 32 2 mean DNASE:H1-hESC DNASE DNase/H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +71 0 ENCFF554DWH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMV/summary/coverage.w5 32 2 mean DNASE:cardiac mesoderm DNASE DNase/cardiac mesoderm DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +72 0 ENCFF274NDO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMW/summary/coverage.w5 32 2 mean DNASE:cardiac mesoderm DNASE DNase/cardiac mesoderm DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +73 0 ENCFF501KNP /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMX/summary/coverage.w5 32 2 mean DNASE:cardiac mesoderm DNASE DNase/cardiac mesoderm DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +74 0 ENCFF213FJN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMY/summary/coverage.w5 32 2 mean DNASE:cardiac mesoderm DNASE DNase/cardiac mesoderm DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +75 0 ENCFF696IEW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EMZ/summary/coverage.w5 32 2 mean DNASE:H7-hESC DNASE DNase/H7-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +76 0 ENCFF499UDS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENA/summary/coverage.w5 32 2 mean DNASE:astrocyte of the hippocampus DNASE DNase/astrocyte of the hippocampus DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +77 0 ENCFF901UBX /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENB/summary/coverage.w5 32 2 mean DNASE:astrocyte of the spinal cord DNASE DNase/astrocyte of the spinal cord DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +78 0 ENCFF382FZE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENC/summary/coverage.w5 32 2 mean DNASE:astrocyte of the cerebellum DNASE DNase/astrocyte of the cerebellum DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +79 0 ENCFF102UQK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000END/summary/coverage.w5 32 2 mean DNASE:amniotic epithelial cell DNASE DNase/amniotic epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +80 0 ENCFF025HHG /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENE/summary/coverage.w5 32 2 mean DNASE:brain microvascular endothelial cell DNASE DNase/brain microvascular endothelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +81 0 ENCFF353QSZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENF/summary/coverage.w5 32 2 mean DNASE:brain pericyte DNASE DNase/brain pericyte DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +82 0 ENCFF443IYY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENG/summary/coverage.w5 32 2 mean DNASE:smooth muscle cell of the brain vasculature female DNASE DNase/smooth muscle cell of the brain vasculature female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +83 0 ENCFF049FGZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENH/summary/coverage.w5 32 2 mean DNASE:cardiac fibroblast DNASE DNase/cardiac fibroblast DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +84 0 ENCFF472TFO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENI/summary/coverage.w5 32 2 mean DNASE:cardiac fibroblast female DNASE DNase/cardiac fibroblast female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +85 0 ENCFF484UXW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENJ/summary/coverage.w5 32 2 mean DNASE:cardiac muscle cell DNASE DNase/cardiac muscle cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +86 0 ENCFF923EUB /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENK/summary/coverage.w5 32 2 mean DNASE:fibroblast of the conjunctiva DNASE DNase/fibroblast of the conjunctiva DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +87 0 ENCFF021NBR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENL/summary/coverage.w5 32 2 mean DNASE:choroid plexus epithelial cell DNASE DNase/choroid plexus epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +88 0 ENCFF169PCK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENM/summary/coverage.w5 32 2 mean DNASE:HCT116 DNASE DNase/HCT116 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +89 0 ENCFF655LKW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENN/summary/coverage.w5 32 2 mean DNASE:epithelial cell of esophagus DNASE DNase/epithelial cell of esophagus DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +90 0 ENCFF830FDL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENO/summary/coverage.w5 32 2 mean DNASE:HeLa-S3 G1b phase DNASE DNase/HeLa-S3 G1b phase DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +91 0 ENCFF205TKQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENP/summary/coverage.w5 32 2 mean DNASE:HepG2 DNASE DNase/HepG2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE +92 0 ENCFF111BCZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENQ/summary/coverage.w5 32 2 mean DNASE:foreskin fibroblast male newborn DNASE DNase/foreskin fibroblast male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +93 0 ENCFF103JVK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENR/summary/coverage.w5 32 2 mean DNASE:HFF-Myc originated from foreskin fibroblast DNASE DNase/HFF-Myc originated from foreskin fibroblast DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +94 0 ENCFF117RGP /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENS/summary/coverage.w5 32 2 mean DNASE:fibroblast of gingiva DNASE DNase/fibroblast of gingiva DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +95 0 ENCFF390MSL /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENT/summary/coverage.w5 32 2 mean DNASE:iris pigment epithelial cell DNASE DNase/iris pigment epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +96 0 ENCFF634ZUJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENU/summary/coverage.w5 32 2 mean DNASE:HL-60 DNASE DNase/HL-60 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +97 0 ENCFF263BZU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENV/summary/coverage.w5 32 2 mean DNASE:mammary epithelial cell female DNASE DNase/mammary epithelial cell female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +98 0 ENCFF724CMH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENW/summary/coverage.w5 32 2 mean DNASE:fibroblast of mammary gland female DNASE DNase/fibroblast of mammary gland female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +99 0 ENCFF969NNQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENX/summary/coverage.w5 32 2 mean DNASE:dermis blood vessel endothelial cell female adult DNASE DNase/dermis blood vessel endothelial cell female adult DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +100 0 ENCFF250ZZO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENY/summary/coverage.w5 32 2 mean DNASE:dermis blood vessel endothelial cell female adult DNASE DNase/dermis blood vessel endothelial cell female adult DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +101 0 ENCFF189TQN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000ENZ/summary/coverage.w5 32 2 mean DNASE:dermis blood vessel endothelial cell male newborn DNASE DNase/dermis blood vessel endothelial cell male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +102 0 ENCFF130RBG /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOA/summary/coverage.w5 32 2 mean DNASE:dermis microvascular lymphatic vessel endothelial cell female DNASE DNase/dermis microvascular lymphatic vessel endothelial cell female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +103 0 ENCFF431JNM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOB/summary/coverage.w5 32 2 mean DNASE:dermis microvascular lymphatic vessel endothelial cell male DNASE DNase/dermis microvascular lymphatic vessel endothelial cell male DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +104 0 ENCFF468FOP /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOC/summary/coverage.w5 32 2 mean DNASE:dermis blood vessel endothelial cell male newborn DNASE DNase/dermis blood vessel endothelial cell male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +105 0 ENCFF010NPI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOD/summary/coverage.w5 32 2 mean DNASE:lung microvascular endothelial cell female DNASE DNase/lung microvascular endothelial cell female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +106 0 ENCFF999UJH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOE/summary/coverage.w5 32 2 mean DNASE:lung microvascular endothelial cell female DNASE DNase/lung microvascular endothelial cell female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +107 0 ENCFF714QQU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOF/summary/coverage.w5 32 2 mean DNASE:non-pigmented ciliary epithelial cell DNASE DNase/non-pigmented ciliary epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +108 0 ENCFF719ZEX /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOG/summary/coverage.w5 32 2 mean DNASE:pulmonary artery endothelial cell female DNASE DNase/pulmonary artery endothelial cell female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +109 0 ENCFF184UHW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOH/summary/coverage.w5 32 2 mean DNASE:fibroblast of pulmonary artery DNASE DNase/fibroblast of pulmonary artery DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +110 0 ENCFF519CAJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOI/summary/coverage.w5 32 2 mean DNASE:fibroblast of peridontal ligament male DNASE DNase/fibroblast of peridontal ligament male DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +111 0 ENCFF655AEV /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOJ/summary/coverage.w5 32 2 mean DNASE:fibroblast of lung DNASE DNase/fibroblast of lung DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +112 0 ENCFF457RRO /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOK/summary/coverage.w5 32 2 mean DNASE:renal cortical epithelial cell DNASE DNase/renal cortical epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +113 0 ENCFF221IPJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOL/summary/coverage.w5 32 2 mean DNASE:kidney epithelial cell DNASE DNase/kidney epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +114 0 ENCFF656ZYW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOM/summary/coverage.w5 32 2 mean DNASE:glomerular endothelial cell DNASE DNase/glomerular endothelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +115 0 ENCFF634YGE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EON/summary/coverage.w5 32 2 mean DNASE:retinal pigment epithelial cell DNASE DNase/retinal pigment epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +116 0 ENCFF549TYD /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOO/summary/coverage.w5 32 2 mean DNASE:skeletal muscle myoblast DNASE DNase/skeletal muscle myoblast DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +117 0 ENCFF684FJC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOP/summary/coverage.w5 32 2 mean DNASE:myotube originated from skeletal muscle myoblast DNASE DNase/myotube originated from skeletal muscle myoblast DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +118 0 ENCFF752DYE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOQ/summary/coverage.w5 32 2 mean DNASE:endothelial cell of umbilical vein newborn DNASE DNase/endothelial cell of umbilical vein newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +119 0 ENCFF652HJH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOR/summary/coverage.w5 32 2 mean DNASE:fibroblast of villous mesenchyme DNASE DNase/fibroblast of villous mesenchyme DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +120 0 ENCFF916JRN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOS/summary/coverage.w5 32 2 mean DNASE:Jurkat clone E61 DNASE DNase/Jurkat clone E61 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +121 0 ENCFF413AHU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOT/summary/coverage.w5 32 2 mean DNASE:K562 DNASE DNase/K562 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +122 0 ENCFF868NHV /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EOY/summary/coverage.w5 32 2 mean DNASE:K562 DNASE DNase/K562 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +123 0 ENCFF565YDB /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPC/summary/coverage.w5 32 2 mean DNASE:K562 DNASE DNase/K562 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +124 0 ENCFF748YJM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPD/summary/coverage.w5 32 2 mean DNASE:myocyte originated from LHCN-M2 DNASE DNase/myocyte originated from LHCN-M2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +125 0 ENCFF639MPM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPE/summary/coverage.w5 32 2 mean DNASE:LHCN-M2 DNASE DNase/LHCN-M2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +126 0 ENCFF571HTM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPF/summary/coverage.w5 32 2 mean DNASE:LNCaP clone FGC DNASE DNase/LNCaP clone FGC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +127 0 ENCFF250TLK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPG/summary/coverage.w5 32 2 mean DNASE:M059J DNASE DNase/M059J DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +128 0 ENCFF924FJR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPH/summary/coverage.w5 32 2 mean DNASE:MCF-7 DNASE DNase/MCF-7 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +129 0 ENCFF606KFN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPI/summary/coverage.w5 32 2 mean DNASE:MCF-7 treated with 100 nM estradiol for 1 hour DNASE DNase/MCF-7 treated with 100 nM estradiol for 1 hour DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +130 0 ENCFF411ZPI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPJ/summary/coverage.w5 32 2 mean DNASE:MCF-7 DNASE DNase/MCF-7 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +131 0 ENCFF659BVQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPK/summary/coverage.w5 32 2 mean DNASE:CD14-positive monocyte female DNASE DNase/CD14-positive monocyte female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +132 0 ENCFF897EZG /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPL/summary/coverage.w5 32 2 mean DNASE:NB4 DNASE DNase/NB4 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +133 0 ENCFF320CHE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPM/summary/coverage.w5 32 2 mean DNASE:astrocyte DNASE DNase/astrocyte DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +134 0 ENCFF940PZT /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPN/summary/coverage.w5 32 2 mean DNASE:bronchial epithelial cell female treated with retinoic acid DNASE DNase/bronchial epithelial cell female treated with retinoic acid DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +135 0 ENCFF302JEV /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPO/summary/coverage.w5 32 2 mean DNASE:fibroblast of dermis female adult DNASE DNase/fibroblast of dermis female adult DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +136 0 ENCFF861ULS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPP/summary/coverage.w5 32 2 mean DNASE:foreskin fibroblast male newborn DNASE DNase/foreskin fibroblast male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +137 0 ENCFF767YBP /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPQ/summary/coverage.w5 32 2 mean DNASE:keratinocyte female DNASE DNase/keratinocyte female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE +138 0 ENCFF330KHN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPR/summary/coverage.w5 32 2 mean DNASE:fibroblast of lung male adult (45 years) DNASE DNase/fibroblast of lung male adult (45 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +139 0 ENCFF644NWU /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPS/summary/coverage.w5 32 2 mean DNASE:NT2/D1 DNASE "DNase/NT2;D1" DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +140 0 ENCFF698HGI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPT/summary/coverage.w5 32 2 mean DNASE:Panc1 DNASE DNase/Panc1 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +141 0 ENCFF739CBQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPU/summary/coverage.w5 32 2 mean DNASE:epithelial cell of prostate DNASE DNase/epithelial cell of prostate DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +142 0 ENCFF991YWM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPV/summary/coverage.w5 32 2 mean DNASE:RPMI-7951 DNASE DNase/RPMI-7951 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +143 0 ENCFF499KPZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPW/summary/coverage.w5 32 2 mean DNASE:epithelial cell of proximal tubule DNASE DNase/epithelial cell of proximal tubule DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +144 0 ENCFF827VFY /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPX/summary/coverage.w5 32 2 mean DNASE:bronchial epithelial cell DNASE DNase/bronchial epithelial cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +145 0 ENCFF440XZH /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPY/summary/coverage.w5 32 2 mean DNASE:SK-N-MC DNASE DNase/SK-N-MC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +146 0 ENCFF851VBR /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EPZ/summary/coverage.w5 32 2 mean DNASE:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours DNASE DNase/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +147 0 ENCFF627SBE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQA/summary/coverage.w5 32 2 mean DNASE:skeletal muscle cell DNASE DNase/skeletal muscle cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +148 0 ENCFF367ZVE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQB/summary/coverage.w5 32 2 mean DNASE:T47D DNASE DNase/T47D DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +149 0 ENCFF479VHW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQC/summary/coverage.w5 32 2 mean DNASE:T-helper 1 cell DNASE DNase/T-helper 1 cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +150 0 ENCFF204BQM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQD/summary/coverage.w5 32 2 mean DNASE:T-helper 1 cell female adult (26 years) DNASE DNase/T-helper 1 cell female adult (26 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +151 0 ENCFF795TGF /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQE/summary/coverage.w5 32 2 mean DNASE:T-helper 1 cell male adult (33 years) DNASE DNase/T-helper 1 cell male adult (33 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +152 0 ENCFF566QDG /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQF/summary/coverage.w5 32 2 mean DNASE:T-helper 17 cell DNASE DNase/T-helper 17 cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +153 0 ENCFF335KDD /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQG/summary/coverage.w5 32 2 mean DNASE:T-helper 2 cell DNASE DNase/T-helper 2 cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +154 0 ENCFF768PJS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQH/summary/coverage.w5 32 2 mean DNASE:T-helper 2 cell female adult (26 years) DNASE DNase/T-helper 2 cell female adult (26 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +155 0 ENCFF438GIW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQI/summary/coverage.w5 32 2 mean DNASE:T-helper 2 cell male adult (33 years) DNASE DNase/T-helper 2 cell male adult (33 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +156 0 ENCFF313YWE /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQJ/summary/coverage.w5 32 2 mean DNASE:regulatory T cell female adult (35 years) DNASE DNase/regulatory T cell female adult (35 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +157 0 ENCFF622JVD /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQK/summary/coverage.w5 32 2 mean DNASE:regulatory T cell male adult (28 years) DNASE DNase/regulatory T cell male adult (28 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +158 0 ENCFF369NZI /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQL/summary/coverage.w5 32 2 mean DNASE:WERI-Rb-1 DNASE DNase/WERI-Rb-1 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +159 0 ENCFF189ULK /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQM/summary/coverage.w5 32 2 mean DNASE:WI38 genetically modified using stable transfection originated from WI38 treated with 20 nM afimoxifene for 72 hours DNASE DNase/WI38 genetically modified using stable transfection originated from WI38 treated with 20 nM afimoxifene for 72 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +160 0 ENCFF040DSN /home/drk/tillage/datasets/human/dnase/encode/ENCSR000EQN/summary/coverage.w5 32 2 mean DNASE:WI38 genetically modified using stable transfection originated from WI38 DNASE DNase/WI38 genetically modified using stable transfection originated from WI38 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +161 0 ENCFF953AFG /home/drk/tillage/datasets/human/dnase/encode/ENCSR000FDI/summary/coverage.w5 32 2 mean DNASE:HT1080 DNASE DNase/HT1080 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +162 0 ENCFF810XTS /home/drk/tillage/datasets/human/dnase/encode/ENCSR000FEK/summary/coverage.w5 32 2 mean DNASE:SK-MEL-5 DNASE DNase/SK-MEL-5 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE +163 0 ENCFF741DDM /home/drk/tillage/datasets/human/dnase/encode/ENCSR000FFJ/summary/coverage.w5 32 2 mean DNASE:SJCRH30 DNASE DNase/SJCRH30 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +164 0 ENCFF143RMC /home/drk/tillage/datasets/human/dnase/encode/ENCSR000FJH/summary/coverage.w5 32 2 mean DNASE:NCI-H460 DNASE DNase/NCI-H460 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +165 0 ENCFF989ALW /home/drk/tillage/datasets/human/dnase/encode/ENCSR000FJL/summary/coverage.w5 32 2 mean DNASE:SK-N-DZ treated with dimethyl sulfoxide for 72 hours DNASE DNase/SK-N-DZ treated with dimethyl sulfoxide for 72 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +166 0 ENCFF938XUM /home/drk/tillage/datasets/human/dnase/encode/ENCSR004SUL/summary/coverage.w5 32 2 mean DNASE:GM23338 male adult (53 years) originated from GM23248 DNASE DNase/GM23338 male adult (53 years) originated from GM23248 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +167 0 ENCFF362UJZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR006IJP/summary/coverage.w5 32 2 mean DNASE:lung embryo (112 days) DNASE DNase/lung embryo (112 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +168 0 ENCFF820SGC /home/drk/tillage/datasets/human/dnase/encode/ENCSR008SDL/summary/coverage.w5 32 2 mean DNASE:SK-MEL-5 DNASE DNase/SK-MEL-5 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE +169 0 ENCFF739XXP /home/drk/tillage/datasets/human/dnase/encode/ENCSR010ZMK/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (113 days) DNASE DNase/muscle of back female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +170 0 ENCFF694RNX /home/drk/tillage/datasets/human/dnase/encode/ENCSR014FPY/summary/coverage.w5 32 2 mean DNASE:iPS DF 4.7 male newborn DNASE DNase/iPS DF 4.7 male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +171 0 ENCFF461CDQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR014VAC/summary/coverage.w5 32 2 mean DNASE:right renal cortex interstitium male embryo (105 days) DNASE DNase/right renal cortex interstitium male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +172 0 ENCFF498QFP /home/drk/tillage/datasets/human/dnase/encode/ENCSR015BGH/summary/coverage.w5 32 2 mean DNASE:caudate nucleus male adult (78 years) DNASE DNase/caudate nucleus male adult (78 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +173 0 ENCFF245IYM /home/drk/tillage/datasets/human/dnase/encode/ENCSR016THC/summary/coverage.w5 32 2 mean DNASE:left renal pelvis male embryo (105 days) DNASE DNase/left renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +174 0 ENCFF855CJL /home/drk/tillage/datasets/human/dnase/encode/ENCSR017OZH/summary/coverage.w5 32 2 mean DNASE:H9 S1 phase genetically modified using stable transfection DNASE DNase/H9 S1 phase genetically modified using stable transfection DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +175 0 ENCFF960UKQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR017TFH/summary/coverage.w5 32 2 mean DNASE:right kidney female embryo (87 days) DNASE DNase/right kidney female embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +176 0 ENCFF220RFB /home/drk/tillage/datasets/human/dnase/encode/ENCSR019JDO/summary/coverage.w5 32 2 mean DNASE:Karpas-422 DNASE DNase/Karpas-422 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +177 0 ENCFF439EFF /home/drk/tillage/datasets/human/dnase/encode/ENCSR020LUD/summary/coverage.w5 32 2 mean DNASE:CD8-positive, alpha-beta T cell male adult (21 year) DNASE DNase/CD8-positive, alpha-beta T cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +178 0 ENCFF825MFH /home/drk/tillage/datasets/human/dnase/encode/ENCSR022ECC/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium female embryo (96 days) DNASE DNase/renal cortex interstitium female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +179 0 ENCFF735MKP /home/drk/tillage/datasets/human/dnase/encode/ENCSR026EOM/summary/coverage.w5 32 2 mean DNASE:brain female embryo (85 days) DNASE DNase/brain female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +180 0 ENCFF920AZN /home/drk/tillage/datasets/human/dnase/encode/ENCSR033DQS/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (97 days) DNASE DNase/muscle of leg male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +181 0 ENCFF577QJI /home/drk/tillage/datasets/human/dnase/encode/ENCSR033STL/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (105 days) DNASE DNase/muscle of back female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +182 0 ENCFF681MHT /home/drk/tillage/datasets/human/dnase/encode/ENCSR035QHH/summary/coverage.w5 32 2 mean DNASE:placenta female embryo (113 days) DNASE DNase/placenta female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +183 0 ENCFF971NFK /home/drk/tillage/datasets/human/dnase/encode/ENCSR035RVH/summary/coverage.w5 32 2 mean DNASE:foreskin keratinocyte male newborn DNASE DNase/foreskin keratinocyte male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE +184 0 ENCFF842TPR /home/drk/tillage/datasets/human/dnase/encode/ENCSR036VRV/summary/coverage.w5 32 2 mean DNASE:right kidney female embryo (107 days) DNASE DNase/right kidney female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +185 0 ENCFF076JMD /home/drk/tillage/datasets/human/dnase/encode/ENCSR037PGI/summary/coverage.w5 32 2 mean DNASE:RCC 7860 DNASE DNase/RCC 7860 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +186 0 ENCFF188JVI /home/drk/tillage/datasets/human/dnase/encode/ENCSR038XTK/summary/coverage.w5 32 2 mean DNASE:colon epithelial cell line DNASE DNase/colon epithelial cell line DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +187 0 ENCFF269PEU /home/drk/tillage/datasets/human/dnase/encode/ENCSR039ZVQ/summary/coverage.w5 32 2 mean DNASE:left renal cortex interstitium male embryo (120 days) DNASE DNase/left renal cortex interstitium male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +188 0 ENCFF400NBT /home/drk/tillage/datasets/human/dnase/encode/ENCSR040DGJ/summary/coverage.w5 32 2 mean DNASE:T-cell DNASE DNase/T-cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +189 0 ENCFF304TGP /home/drk/tillage/datasets/human/dnase/encode/ENCSR047FNH/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (113 days) DNASE DNase/large intestine male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +190 0 ENCFF999OEJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR052AWE/summary/coverage.w5 32 2 mean DNASE:PC-3 DNASE DNase/PC-3 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +191 0 ENCFF813VDR /home/drk/tillage/datasets/human/dnase/encode/ENCSR059LXL/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (96 days) DNASE DNase/muscle of leg male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +192 0 ENCFF613SVD /home/drk/tillage/datasets/human/dnase/encode/ENCSR060BFU/summary/coverage.w5 32 2 mean DNASE:adrenal gland embryo (96 days) DNASE DNase/adrenal gland embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +193 0 ENCFF519PNO /home/drk/tillage/datasets/human/dnase/encode/ENCSR060HPL/summary/coverage.w5 32 2 mean DNASE:coronary artery female adult (53 years) DNASE DNase/coronary artery female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +194 0 ENCFF022OWT /home/drk/tillage/datasets/human/dnase/encode/ENCSR062DUU/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (105 days) DNASE DNase/stomach female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +195 0 ENCFF529MMP /home/drk/tillage/datasets/human/dnase/encode/ENCSR062DXC/summary/coverage.w5 32 2 mean DNASE:muscle of arm female embryo (115 days) DNASE DNase/muscle of arm female embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +196 0 ENCFF854MAD /home/drk/tillage/datasets/human/dnase/encode/ENCSR064GBK/summary/coverage.w5 32 2 mean DNASE:heart female embryo (91 day) DNASE DNase/heart female embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +197 0 ENCFF734DOF /home/drk/tillage/datasets/human/dnase/encode/ENCSR066WZJ/summary/coverage.w5 32 2 mean DNASE:kidney embryo (80 days) DNASE DNase/kidney embryo (80 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +198 0 ENCFF678EIG /home/drk/tillage/datasets/human/dnase/encode/ENCSR070CMW/summary/coverage.w5 32 2 mean DNASE:heart left ventricle female adult (53 years) DNASE DNase/heart left ventricle female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +199 0 ENCFF581JDF /home/drk/tillage/datasets/human/dnase/encode/ENCSR072NBR/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (98 days) DNASE DNase/muscle of back female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +200 0 ENCFF475YJR /home/drk/tillage/datasets/human/dnase/encode/ENCSR076YBB/summary/coverage.w5 32 2 mean DNASE:lung male embryo (108 days) DNASE DNase/lung male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +201 0 ENCFF146VLD /home/drk/tillage/datasets/human/dnase/encode/ENCSR080ISA/summary/coverage.w5 32 2 mean DNASE:tibial artery female adult (53 years) DNASE DNase/tibial artery female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +202 0 ENCFF580LWU /home/drk/tillage/datasets/human/dnase/encode/ENCSR080PZL/summary/coverage.w5 32 2 mean DNASE:adrenal gland male embryo (101 day) DNASE DNase/adrenal gland male embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +203 0 ENCFF192KLJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR082JCE/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (121 day) DNASE DNase/kidney female embryo (121 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +204 0 ENCFF534VWZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR082XEU/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (107 days) DNASE DNase/stomach female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +205 0 ENCFF343DFM /home/drk/tillage/datasets/human/dnase/encode/ENCSR083FBK/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (110 days) DNASE DNase/small intestine female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +206 0 ENCFF723FDT /home/drk/tillage/datasets/human/dnase/encode/ENCSR083STA/summary/coverage.w5 32 2 mean DNASE:MG63 DNASE DNase/MG63 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +207 0 ENCFF792NVL /home/drk/tillage/datasets/human/dnase/encode/ENCSR092OFK/summary/coverage.w5 32 2 mean DNASE:skin of body female embryo (82 days) DNASE DNase/skin of body female embryo (82 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +208 0 ENCFF617ONE /home/drk/tillage/datasets/human/dnase/encode/ENCSR092WMD/summary/coverage.w5 32 2 mean DNASE:left renal cortex interstitium male embryo (105 days) DNASE DNase/left renal cortex interstitium male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +209 0 ENCFF873DWP /home/drk/tillage/datasets/human/dnase/encode/ENCSR095GWE/summary/coverage.w5 32 2 mean DNASE:stomach male embryo (58 days) and male embryo (76 days) DNASE DNase/stomach male embryo (58 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +210 0 ENCFF862JVF /home/drk/tillage/datasets/human/dnase/encode/ENCSR097BWW/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (59 days) and male embryo (91 day) DNASE DNase/left kidney female embryo (59 days) and male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +211 0 ENCFF996GHG /home/drk/tillage/datasets/human/dnase/encode/ENCSR098PTC/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell DNASE DNase/hematopoietic multipotent progenitor cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +212 0 ENCFF969UJW /home/drk/tillage/datasets/human/dnase/encode/ENCSR106OKX/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (120 days) DNASE DNase/kidney female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +213 0 ENCFF413KYW /home/drk/tillage/datasets/human/dnase/encode/ENCSR106RBR/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (115 days) DNASE DNase/muscle of back female embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +214 0 ENCFF771PWA /home/drk/tillage/datasets/human/dnase/encode/ENCSR115YPI/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell male adult (25 years) treated with erythropoietin for 20 days, hydrocortisone succinate for 20 days, kit ligand for 20 days, interleukin-3 for 20 days DNASE DNase/hematopoietic multipotent progenitor cell male adult (25 years) treated with erythropoietin for 20 days, hydrocortisone succinate for 20 days, kit ligand for 20 days, interleukin-3 for 20 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +215 0 ENCFF671BMS /home/drk/tillage/datasets/human/dnase/encode/ENCSR116WWW/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (120 days) DNASE DNase/small intestine female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +216 0 ENCFF657KLL /home/drk/tillage/datasets/human/dnase/encode/ENCSR118WIQ/summary/coverage.w5 32 2 mean DNASE:brain embryo (112 days) DNASE DNase/brain embryo (112 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +217 0 ENCFF424IXN /home/drk/tillage/datasets/human/dnase/encode/ENCSR119HXE/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (105 days) DNASE DNase/stomach female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +218 0 ENCFF415LNY /home/drk/tillage/datasets/human/dnase/encode/ENCSR120LVW/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (98 days) DNASE DNase/left kidney female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +219 0 ENCFF248OBP /home/drk/tillage/datasets/human/dnase/encode/ENCSR121ZSL/summary/coverage.w5 32 2 mean DNASE:trophoblast cell embryo (21 week) DNASE DNase/trophoblast cell embryo (21 week) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +220 0 ENCFF328DCV /home/drk/tillage/datasets/human/dnase/encode/ENCSR122VUW/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive female adult (27 years) DNASE DNase/common myeloid progenitor, CD34-positive female adult (27 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +221 0 ENCFF681KGX /home/drk/tillage/datasets/human/dnase/encode/ENCSR127PWK/summary/coverage.w5 32 2 mean DNASE:eye female embryo (76 days) DNASE DNase/eye female embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +222 0 ENCFF332EJM /home/drk/tillage/datasets/human/dnase/encode/ENCSR129KIV/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (108 days) DNASE DNase/renal cortex interstitium male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +223 0 ENCFF987HVM /home/drk/tillage/datasets/human/dnase/encode/ENCSR129TSG/summary/coverage.w5 32 2 mean DNASE:placenta female embryo (108 days) DNASE DNase/placenta female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +224 0 ENCFF922TBR /home/drk/tillage/datasets/human/dnase/encode/ENCSR131JVA/summary/coverage.w5 32 2 mean DNASE:stomach female adult (53 years) DNASE DNase/stomach female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +225 0 ENCFF209YFM /home/drk/tillage/datasets/human/dnase/encode/ENCSR133KBX/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (107 days) DNASE DNase/small intestine female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +226 0 ENCFF811EUQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR133SPH/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (120 days) DNASE DNase/large intestine female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +227 0 ENCFF798YGS /home/drk/tillage/datasets/human/dnase/encode/ENCSR136KEL/summary/coverage.w5 32 2 mean DNASE:kidney glomerular epithelial cell male adult (43 years) and male adult (62 years) DNASE DNase/kidney glomerular epithelial cell male adult (43 years) and male adult (62 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +228 0 ENCFF319GAX /home/drk/tillage/datasets/human/dnase/encode/ENCSR141DMX/summary/coverage.w5 32 2 mean DNASE:renal pelvis female embryo (96 days) DNASE DNase/renal pelvis female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +229 0 ENCFF083VCD /home/drk/tillage/datasets/human/dnase/encode/ENCSR141IUS/summary/coverage.w5 32 2 mean DNASE:lung female embryo (76 days) DNASE DNase/lung female embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +230 0 ENCFF044CTX /home/drk/tillage/datasets/human/dnase/encode/ENCSR141NSQ/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (104 days) DNASE DNase/muscle of back male embryo (104 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +231 0 ENCFF899HCF /home/drk/tillage/datasets/human/dnase/encode/ENCSR141VGA/summary/coverage.w5 32 2 mean DNASE:lung female embryo (85 days) DNASE DNase/lung female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +232 0 ENCFF085EFX /home/drk/tillage/datasets/human/dnase/encode/ENCSR148MFM/summary/coverage.w5 32 2 mean DNASE:spinal cord male embryo (105 days) DNASE DNase/spinal cord male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +233 0 ENCFF833WVM /home/drk/tillage/datasets/human/dnase/encode/ENCSR148VUP/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 4 days, kit ligand for 4 days, hydrocortisone succinate for 4 days, erythropoietin for 4 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 4 days, kit ligand for 4 days, hydrocortisone succinate for 4 days, erythropoietin for 4 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +234 0 ENCFF577SOF /home/drk/tillage/datasets/human/dnase/encode/ENCSR149XIL/summary/coverage.w5 32 2 mean DNASE:HepG2 DNASE DNase/HepG2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE +235 0 ENCFF366GCX /home/drk/tillage/datasets/human/dnase/encode/ENCSR153LHP/summary/coverage.w5 32 2 mean DNASE:foreskin fibroblast male newborn DNASE DNase/foreskin fibroblast male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +236 0 ENCFF575XEK /home/drk/tillage/datasets/human/dnase/encode/ENCSR154OUQ/summary/coverage.w5 32 2 mean DNASE:omental fat pad female adult (53 years) DNASE DNase/omental fat pad female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +237 0 ENCFF207LXN /home/drk/tillage/datasets/human/dnase/encode/ENCSR154YPL/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (110 days) DNASE DNase/large intestine female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +238 0 ENCFF604EJP /home/drk/tillage/datasets/human/dnase/encode/ENCSR154ZNQ/summary/coverage.w5 32 2 mean DNASE:heart female embryo (105 days) DNASE DNase/heart female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +239 0 ENCFF365HVU /home/drk/tillage/datasets/human/dnase/encode/ENCSR155NPL/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (113 days) DNASE DNase/renal cortex interstitium male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +240 0 ENCFF064KBT /home/drk/tillage/datasets/human/dnase/encode/ENCSR156CLC/summary/coverage.w5 32 2 mean DNASE:brain female embryo (96 days) DNASE DNase/brain female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +241 0 ENCFF677VKI /home/drk/tillage/datasets/human/dnase/encode/ENCSR158VAT/summary/coverage.w5 32 2 mean DNASE:thyroid gland male adult (37 years) DNASE DNase/thyroid gland male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +242 0 ENCFF068ZBX /home/drk/tillage/datasets/human/dnase/encode/ENCSR158YXM/summary/coverage.w5 32 2 mean DNASE:liver embryo (59 days) and embryo (80 days) DNASE DNase/liver embryo (59 days) and embryo (80 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +243 0 ENCFF288HWP /home/drk/tillage/datasets/human/dnase/encode/ENCSR163PKT/summary/coverage.w5 32 2 mean DNASE:stomach male adult (54 years) DNASE DNase/stomach male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +244 0 ENCFF921GFL /home/drk/tillage/datasets/human/dnase/encode/ENCSR164PQJ/summary/coverage.w5 32 2 mean DNASE:thymus male embryo (127 days) DNASE DNase/thymus male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +245 0 ENCFF414NAA /home/drk/tillage/datasets/human/dnase/encode/ENCSR164WOF/summary/coverage.w5 32 2 mean DNASE:upper lobe of left lung male adult (37 years) DNASE DNase/upper lobe of left lung male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +246 0 ENCFF131GBV /home/drk/tillage/datasets/human/dnase/encode/ENCSR166KPV/summary/coverage.w5 32 2 mean DNASE:endodermal cell DNASE DNase/endodermal cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +247 0 ENCFF016KEV /home/drk/tillage/datasets/human/dnase/encode/ENCSR166TEE/summary/coverage.w5 32 2 mean DNASE:forelimb muscle female embryo (108 days) DNASE DNase/forelimb muscle female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +248 0 ENCFF522NPH /home/drk/tillage/datasets/human/dnase/encode/ENCSR167JFX/summary/coverage.w5 32 2 mean DNASE:CD4-positive, alpha-beta T cell male adult (37 years) DNASE DNase/CD4-positive, alpha-beta T cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +249 0 ENCFF858BSX /home/drk/tillage/datasets/human/dnase/encode/ENCSR167XSQ/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (101 day) DNASE DNase/muscle of leg male embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +250 0 ENCFF161KLK /home/drk/tillage/datasets/human/dnase/encode/ENCSR171ADO/summary/coverage.w5 32 2 mean DNASE:gastrocnemius medialis male adult (37 years) DNASE DNase/gastrocnemius medialis male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +251 0 ENCFF073UDC /home/drk/tillage/datasets/human/dnase/encode/ENCSR171ETY/summary/coverage.w5 32 2 mean DNASE:gastrocnemius medialis male adult (54 years) DNASE DNase/gastrocnemius medialis male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +252 0 ENCFF362OUW /home/drk/tillage/datasets/human/dnase/encode/ENCSR172PVJ/summary/coverage.w5 32 2 mean DNASE:stomach male embryo (91 day) DNASE DNase/stomach male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +253 0 ENCFF499LIJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR174GXG/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (101 day) DNASE DNase/muscle of back male embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +254 0 ENCFF008DNO /home/drk/tillage/datasets/human/dnase/encode/ENCSR174JMM/summary/coverage.w5 32 2 mean DNASE:heart female embryo (117 days) DNASE DNase/heart female embryo (117 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +255 0 ENCFF294LJN /home/drk/tillage/datasets/human/dnase/encode/ENCSR175IWT/summary/coverage.w5 32 2 mean DNASE:kidney tubule cell female adult (80 years) and male adult (62 years) DNASE DNase/kidney tubule cell female adult (80 years) and male adult (62 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +256 0 ENCFF433QRU /home/drk/tillage/datasets/human/dnase/encode/ENCSR176KYD/summary/coverage.w5 32 2 mean DNASE:fibroblast of skin of abdomen male embryo (97 days) DNASE DNase/fibroblast of skin of abdomen male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +257 0 ENCFF230OUF /home/drk/tillage/datasets/human/dnase/encode/ENCSR178JBL/summary/coverage.w5 32 2 mean DNASE:pancreas male adult (34 years) DNASE DNase/pancreas male adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +258 0 ENCFF532VGP /home/drk/tillage/datasets/human/dnase/encode/ENCSR179CDH/summary/coverage.w5 32 2 mean DNASE:trophoblast cell originated from H1-hESC DNASE DNase/trophoblast cell originated from H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +259 0 ENCFF401OYD /home/drk/tillage/datasets/human/dnase/encode/ENCSR184DFF/summary/coverage.w5 32 2 mean DNASE:left kidney male embryo (96 days) DNASE DNase/left kidney male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +260 0 ENCFF338NJM /home/drk/tillage/datasets/human/dnase/encode/ENCSR184LMY/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +261 0 ENCFF378OWK /home/drk/tillage/datasets/human/dnase/encode/ENCSR187PYY/summary/coverage.w5 32 2 mean DNASE:brain female embryo (142 days) DNASE DNase/brain female embryo (142 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +262 0 ENCFF687KFN /home/drk/tillage/datasets/human/dnase/encode/ENCSR188JLO/summary/coverage.w5 32 2 mean DNASE:small intestine male embryo (105 days) DNASE DNase/small intestine male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +263 0 ENCFF509TTX /home/drk/tillage/datasets/human/dnase/encode/ENCSR189YJQ/summary/coverage.w5 32 2 mean DNASE:heart female embryo (110 days) DNASE DNase/heart female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +264 0 ENCFF103KGP /home/drk/tillage/datasets/human/dnase/encode/ENCSR191EII/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive female DNASE DNase/common myeloid progenitor, CD34-positive female DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +265 0 ENCFF452CPH /home/drk/tillage/datasets/human/dnase/encode/ENCSR191FOV/summary/coverage.w5 32 2 mean DNASE:adrenal gland male adult (37 years) DNASE DNase/adrenal gland male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +266 0 ENCFF748UWO /home/drk/tillage/datasets/human/dnase/encode/ENCSR193LYA/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (85 days) DNASE DNase/muscle of back female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +267 0 ENCFF875TFI /home/drk/tillage/datasets/human/dnase/encode/ENCSR198JXW/summary/coverage.w5 32 2 mean DNASE:muscle of leg female embryo (85 days) DNASE DNase/muscle of leg female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +268 0 ENCFF340RUK /home/drk/tillage/datasets/human/dnase/encode/ENCSR206FSY/summary/coverage.w5 32 2 mean DNASE:Peyer's patch male adult (54 years) DNASE DNase/Peyer's patch male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +269 0 ENCFF410CYG /home/drk/tillage/datasets/human/dnase/encode/ENCSR207TUX/summary/coverage.w5 32 2 mean DNASE:amniotic stem cell DNASE DNase/amniotic stem cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +270 0 ENCFF978RWQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR208DMX/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (98 days) DNASE DNase/stomach female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +271 0 ENCFF584GYN /home/drk/tillage/datasets/human/dnase/encode/ENCSR214QEO/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (91 day) DNASE DNase/large intestine female embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +272 0 ENCFF029QDT /home/drk/tillage/datasets/human/dnase/encode/ENCSR214XJO/summary/coverage.w5 32 2 mean DNASE:lung female embryo (120 days) DNASE DNase/lung female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +273 0 ENCFF285PVN /home/drk/tillage/datasets/human/dnase/encode/ENCSR217RVH/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +274 0 ENCFF726FED /home/drk/tillage/datasets/human/dnase/encode/ENCSR217SET/summary/coverage.w5 32 2 mean DNASE:SW480 DNASE DNase/SW480 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +275 0 ENCFF711EJL /home/drk/tillage/datasets/human/dnase/encode/ENCSR217TAW/summary/coverage.w5 32 2 mean DNASE:GM23248 DNASE DNase/GM23248 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +276 0 ENCFF484VHZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR217YRJ/summary/coverage.w5 32 2 mean DNASE:muscle of trunk female embryo (120 days) DNASE DNase/muscle of trunk female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +277 0 ENCFF639JCH /home/drk/tillage/datasets/human/dnase/encode/ENCSR224FOA/summary/coverage.w5 32 2 mean DNASE:islet precursor cell DNASE DNase/islet precursor cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +278 0 ENCFF151SBP /home/drk/tillage/datasets/human/dnase/encode/ENCSR224IYD/summary/coverage.w5 32 2 mean DNASE:medulla oblongata male adult (78 years) and male adult (84 years) DNASE DNase/medulla oblongata male adult (78 years) and male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +279 0 ENCFF640UAZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR228BOM/summary/coverage.w5 32 2 mean DNASE:right lung male embryo (115 days) DNASE DNase/right lung male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +280 0 ENCFF102SIK /home/drk/tillage/datasets/human/dnase/encode/ENCSR228IKB/summary/coverage.w5 32 2 mean DNASE:body of pancreas male adult (54 years) DNASE DNase/body of pancreas male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +281 0 ENCFF227VUS /home/drk/tillage/datasets/human/dnase/encode/ENCSR228VNQ/summary/coverage.w5 32 2 mean DNASE:mammary epithelial cell female adult (18 years) DNASE DNase/mammary epithelial cell female adult (18 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +282 0 ENCFF082TEM /home/drk/tillage/datasets/human/dnase/encode/ENCSR236SFP/summary/coverage.w5 32 2 mean DNASE:gastrocnemius medialis female adult (51 year) DNASE DNase/gastrocnemius medialis female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +283 0 ENCFF037DUA /home/drk/tillage/datasets/human/dnase/encode/ENCSR237WJY/summary/coverage.w5 32 2 mean DNASE:uterus female adult (53 years) DNASE DNase/uterus female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +284 0 ENCFF818DSK /home/drk/tillage/datasets/human/dnase/encode/ENCSR240TPI/summary/coverage.w5 32 2 mean DNASE:ELR DNASE DNase/ELR DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +285 0 ENCFF037ZSW /home/drk/tillage/datasets/human/dnase/encode/ENCSR244ZEJ/summary/coverage.w5 32 2 mean DNASE:omental fat pad female adult (51 year) DNASE DNase/omental fat pad female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +286 0 ENCFF280CMC /home/drk/tillage/datasets/human/dnase/encode/ENCSR246PXX/summary/coverage.w5 32 2 mean DNASE:stomach male child (3 years) DNASE DNase/stomach male child (3 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +287 0 ENCFF570XSN /home/drk/tillage/datasets/human/dnase/encode/ENCSR247IUJ/summary/coverage.w5 32 2 mean DNASE:B cell male adult (37 years) DNASE DNase/B cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +288 0 ENCFF113YFF /home/drk/tillage/datasets/human/dnase/encode/ENCSR251UPG/summary/coverage.w5 32 2 mean DNASE:foreskin fibroblast male newborn DNASE DNase/foreskin fibroblast male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +289 0 ENCFF981AOU /home/drk/tillage/datasets/human/dnase/encode/ENCSR254AGA/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (91 day) DNASE DNase/renal cortex interstitium male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +290 0 ENCFF828TLX /home/drk/tillage/datasets/human/dnase/encode/ENCSR257BGZ/summary/coverage.w5 32 2 mean DNASE:ACHN DNASE DNase/ACHN DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +291 0 ENCFF054DND /home/drk/tillage/datasets/human/dnase/encode/ENCSR257CIZ/summary/coverage.w5 32 2 mean DNASE:kidney tubule cell female adult (80 years) treated with 5 uM cisplatin DNASE DNase/kidney tubule cell female adult (80 years) treated with 5 uM cisplatin DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +292 0 ENCFF468WHL /home/drk/tillage/datasets/human/dnase/encode/ENCSR258IBL/summary/coverage.w5 32 2 mean DNASE:left renal pelvis male embryo (105 days) DNASE DNase/left renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +293 0 ENCFF669AED /home/drk/tillage/datasets/human/dnase/encode/ENCSR261SMF/summary/coverage.w5 32 2 mean DNASE:iPS DF 6.9 male newborn DNASE DNase/iPS DF 6.9 male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +294 0 ENCFF369CRG /home/drk/tillage/datasets/human/dnase/encode/ENCSR262QJC/summary/coverage.w5 32 2 mean DNASE:kidney male embryo (87 days) DNASE DNase/kidney male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +295 0 ENCFF784RSW /home/drk/tillage/datasets/human/dnase/encode/ENCSR263IGU/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (91 day) DNASE DNase/right lung female embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +296 0 ENCFF564MGY /home/drk/tillage/datasets/human/dnase/encode/ENCSR265TEK/summary/coverage.w5 32 2 mean DNASE:NCI-H226 DNASE DNase/NCI-H226 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +297 0 ENCFF973VII /home/drk/tillage/datasets/human/dnase/encode/ENCSR268QCH/summary/coverage.w5 32 2 mean DNASE:right renal cortex interstitium male embryo (105 days) DNASE DNase/right renal cortex interstitium male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +298 0 ENCFF006KSE /home/drk/tillage/datasets/human/dnase/encode/ENCSR269SIA/summary/coverage.w5 32 2 mean DNASE:G401 DNASE DNase/G401 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +299 0 ENCFF789PQN /home/drk/tillage/datasets/human/dnase/encode/ENCSR270LZE/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (113 days) DNASE DNase/muscle of arm male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +300 0 ENCFF992LZL /home/drk/tillage/datasets/human/dnase/encode/ENCSR271QSV/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult DNASE DNase/common myeloid progenitor, CD34-positive male adult DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +301 0 ENCFF716VIS /home/drk/tillage/datasets/human/dnase/encode/ENCSR272RQX/summary/coverage.w5 32 2 mean DNASE:muscle of leg female embryo (113 days) DNASE DNase/muscle of leg female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +302 0 ENCFF430CNF /home/drk/tillage/datasets/human/dnase/encode/ENCSR274SDO/summary/coverage.w5 32 2 mean DNASE:arm bone male embryo (81 day) DNASE DNase/arm bone male embryo (81 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +303 0 ENCFF334GMP /home/drk/tillage/datasets/human/dnase/encode/ENCSR275ICP/summary/coverage.w5 32 2 mean DNASE:H9 DNASE DNase/H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +304 0 ENCFF639ZOF /home/drk/tillage/datasets/human/dnase/encode/ENCSR278FHC/summary/coverage.w5 32 2 mean DNASE:testis male embryo DNASE DNase/testis male embryo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +305 0 ENCFF372SLF /home/drk/tillage/datasets/human/dnase/encode/ENCSR278FVO/summary/coverage.w5 32 2 mean DNASE:neural stem progenitor cell originated from H1-hESC DNASE DNase/neural stem progenitor cell originated from H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +306 0 ENCFF312ZWZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR278SKG/summary/coverage.w5 32 2 mean DNASE:right atrium auricular region female adult (51 year) DNASE DNase/right atrium auricular region female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +307 0 ENCFF819IOM /home/drk/tillage/datasets/human/dnase/encode/ENCSR281HBB/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult (49 years) DNASE DNase/common myeloid progenitor, CD34-positive male adult (49 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +308 0 ENCFF688EZK /home/drk/tillage/datasets/human/dnase/encode/ENCSR282QFE/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (121 day) DNASE DNase/stomach female embryo (121 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +309 0 ENCFF502QQC /home/drk/tillage/datasets/human/dnase/encode/ENCSR286WIA/summary/coverage.w5 32 2 mean DNASE:muscle of leg female embryo (105 days) DNASE DNase/muscle of leg female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +310 0 ENCFF674WBH /home/drk/tillage/datasets/human/dnase/encode/ENCSR294QCR/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (97 days) DNASE DNase/muscle of leg male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +311 0 ENCFF541UPO /home/drk/tillage/datasets/human/dnase/encode/ENCSR295DUI/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (87 days) DNASE DNase/left kidney female embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +312 0 ENCFF034GYI /home/drk/tillage/datasets/human/dnase/encode/ENCSR295ELC/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (97 days) DNASE DNase/muscle of back male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +313 0 ENCFF160KJF /home/drk/tillage/datasets/human/dnase/encode/ENCSR297ORG/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (96 days) DNASE DNase/muscle of leg male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +314 0 ENCFF071LJS /home/drk/tillage/datasets/human/dnase/encode/ENCSR299INS/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (105 days) DNASE DNase/right lung female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +315 0 ENCFF193BCL /home/drk/tillage/datasets/human/dnase/encode/ENCSR301OGM/summary/coverage.w5 32 2 mean DNASE:NAMALWA treated with Sendai virus for 2 hours DNASE DNase/NAMALWA treated with Sendai virus for 2 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +316 0 ENCFF964WUW /home/drk/tillage/datasets/human/dnase/encode/ENCSR301RCD/summary/coverage.w5 32 2 mean DNASE:renal pelvis male embryo (127 days) DNASE DNase/renal pelvis male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +317 0 ENCFF736ZAN /home/drk/tillage/datasets/human/dnase/encode/ENCSR303YII/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (96 days) DNASE DNase/muscle of arm male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +318 0 ENCFF064YHT /home/drk/tillage/datasets/human/dnase/encode/ENCSR305UJX/summary/coverage.w5 32 2 mean DNASE:heart male child (3 years) DNASE DNase/heart male child (3 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +319 0 ENCFF536FNG /home/drk/tillage/datasets/human/dnase/encode/ENCSR309FOO/summary/coverage.w5 32 2 mean DNASE:brain female embryo (117 days) DNASE DNase/brain female embryo (117 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +320 0 ENCFF428DTK /home/drk/tillage/datasets/human/dnase/encode/ENCSR309YDN/summary/coverage.w5 32 2 mean DNASE:muscle of arm female embryo (85 days) DNASE DNase/muscle of arm female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +321 0 ENCFF782WKY /home/drk/tillage/datasets/human/dnase/encode/ENCSR311LLZ/summary/coverage.w5 32 2 mean DNASE:heart male embryo (110 days) DNASE DNase/heart male embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +322 0 ENCFF464NHA /home/drk/tillage/datasets/human/dnase/encode/ENCSR314EZY/summary/coverage.w5 32 2 mean DNASE:L1-S8 DNASE DNase/L1-S8 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +323 0 ENCFF468PTJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR316UDN/summary/coverage.w5 32 2 mean DNASE:CD8-positive, alpha-beta T cell male adult (37 years) DNASE DNase/CD8-positive, alpha-beta T cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +324 0 ENCFF847HLP /home/drk/tillage/datasets/human/dnase/encode/ENCSR317SIH/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (91 day) DNASE DNase/muscle of back male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +325 0 ENCFF637LBX /home/drk/tillage/datasets/human/dnase/encode/ENCSR318JAA/summary/coverage.w5 32 2 mean DNASE:left renal pelvis male embryo (105 days) DNASE DNase/left renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +326 0 ENCFF751LHL /home/drk/tillage/datasets/human/dnase/encode/ENCSR318PRQ/summary/coverage.w5 32 2 mean DNASE:middle frontal gyrus male adult (78 years) DNASE DNase/middle frontal gyrus male adult (78 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +327 0 ENCFF267BLE /home/drk/tillage/datasets/human/dnase/encode/ENCSR318WOD/summary/coverage.w5 32 2 mean DNASE:lung male embryo (103 days) DNASE DNase/lung male embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +328 0 ENCFF915OOI /home/drk/tillage/datasets/human/dnase/encode/ENCSR320PGJ/summary/coverage.w5 32 2 mean DNASE:heart male embryo (105 days) DNASE DNase/heart male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +329 0 ENCFF688UBR /home/drk/tillage/datasets/human/dnase/encode/ENCSR320SVK/summary/coverage.w5 32 2 mean DNASE:left renal pelvis male embryo (120 days) DNASE DNase/left renal pelvis male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +330 0 ENCFF570PTC /home/drk/tillage/datasets/human/dnase/encode/ENCSR320TUJ/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive female adult (50 years) DNASE DNase/common myeloid progenitor, CD34-positive female adult (50 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +331 0 ENCFF137XIB /home/drk/tillage/datasets/human/dnase/encode/ENCSR322UXF/summary/coverage.w5 32 2 mean DNASE:Peyer's patch female adult (53 years) DNASE DNase/Peyer's patch female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +332 0 ENCFF123ENC /home/drk/tillage/datasets/human/dnase/encode/ENCSR325LYJ/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +333 0 ENCFF158ALT /home/drk/tillage/datasets/human/dnase/encode/ENCSR328UMC/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell DNASE DNase/hematopoietic multipotent progenitor cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +334 0 ENCFF386DMJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR332BSB/summary/coverage.w5 32 2 mean DNASE:right kidney male embryo (87 days) DNASE DNase/right kidney male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +335 0 ENCFF367MHB /home/drk/tillage/datasets/human/dnase/encode/ENCSR332MRT/summary/coverage.w5 32 2 mean DNASE:tibial artery male adult (37 years) DNASE DNase/tibial artery male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +336 0 ENCFF620RYJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR337IRF/summary/coverage.w5 32 2 mean DNASE:renal cell carcinoma DNASE DNase/renal cell carcinoma DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +337 0 ENCFF936MHE /home/drk/tillage/datasets/human/dnase/encode/ENCSR342NCX/summary/coverage.w5 32 2 mean DNASE:thymus female embryo (113 days) DNASE DNase/thymus female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +338 0 ENCFF003FBE /home/drk/tillage/datasets/human/dnase/encode/ENCSR344FLH/summary/coverage.w5 32 2 mean DNASE:brain female embryo (109 days) DNASE DNase/brain female embryo (109 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +339 0 ENCFF399TJD /home/drk/tillage/datasets/human/dnase/encode/ENCSR346IHH/summary/coverage.w5 32 2 mean DNASE:Daoy DNASE DNase/Daoy DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +340 0 ENCFF305GOM /home/drk/tillage/datasets/human/dnase/encode/ENCSR346JWH/summary/coverage.w5 32 2 mean DNASE:A673 DNASE DNase/A673 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +341 0 ENCFF147PGS /home/drk/tillage/datasets/human/dnase/encode/ENCSR356QCD/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (101 day) DNASE DNase/muscle of arm male embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +342 0 ENCFF941ILF /home/drk/tillage/datasets/human/dnase/encode/ENCSR357PMV/summary/coverage.w5 32 2 mean DNASE:muscle of arm female embryo (120 days) DNASE DNase/muscle of arm female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +343 0 ENCFF779BIA /home/drk/tillage/datasets/human/dnase/encode/ENCSR357RED/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (105 days) DNASE DNase/muscle of back male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +344 0 ENCFF647YEC /home/drk/tillage/datasets/human/dnase/encode/ENCSR360LBD/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +345 0 ENCFF095HIQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR360XIS/summary/coverage.w5 32 2 mean DNASE:ecto neural progenitor cell originated from H9 DNASE DNase/ecto neural progenitor cell originated from H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +346 0 ENCFF708ZHA /home/drk/tillage/datasets/human/dnase/encode/ENCSR362JSZ/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 17 days, kit ligand for 17 days, hydrocortisone succinate for 17 days, erythropoietin for 17 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 17 days, kit ligand for 17 days, hydrocortisone succinate for 17 days, erythropoietin for 17 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +347 0 ENCFF136YOJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR364MFN/summary/coverage.w5 32 2 mean DNASE:hepatocyte originated from H9 DNASE DNase/hepatocyte originated from H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +348 0 ENCFF078RPO /home/drk/tillage/datasets/human/dnase/encode/ENCSR364TKL/summary/coverage.w5 32 2 mean DNASE:renal pelvis male embryo (97 days) DNASE DNase/renal pelvis male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +349 0 ENCFF802UAF /home/drk/tillage/datasets/human/dnase/encode/ENCSR366EGE/summary/coverage.w5 32 2 mean DNASE:heart embryo (101 day) DNASE DNase/heart embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +350 0 ENCFF761ZJC /home/drk/tillage/datasets/human/dnase/encode/ENCSR366EQH/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (115 days) DNASE DNase/large intestine male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +351 0 ENCFF010ZNC /home/drk/tillage/datasets/human/dnase/encode/ENCSR366YTD/summary/coverage.w5 32 2 mean DNASE:T-cell male adult (37 years) DNASE DNase/T-cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +352 0 ENCFF053JYY /home/drk/tillage/datasets/human/dnase/encode/ENCSR371KRY/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +353 0 ENCFF259NLK /home/drk/tillage/datasets/human/dnase/encode/ENCSR373BIX/summary/coverage.w5 32 2 mean DNASE:CD1c-positive myeloid dendritic cell DNASE DNase/CD1c-positive myeloid dendritic cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +354 0 ENCFF220IWU /home/drk/tillage/datasets/human/dnase/encode/ENCSR381PXW/summary/coverage.w5 32 2 mean DNASE:B cell male adult (21 year) DNASE DNase/B cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +355 0 ENCFF029ZOX /home/drk/tillage/datasets/human/dnase/encode/ENCSR382JUJ/summary/coverage.w5 32 2 mean DNASE:superior temporal gyrus male adult (84 years) DNASE DNase/superior temporal gyrus male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +356 0 ENCFF801JJS /home/drk/tillage/datasets/human/dnase/encode/ENCSR383BLX/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +357 0 ENCFF294LWY /home/drk/tillage/datasets/human/dnase/encode/ENCSR383SNM/summary/coverage.w5 32 2 mean DNASE:iPS DF 19.11 male newborn DNASE DNase/iPS DF 19.11 male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +358 0 ENCFF973KXU /home/drk/tillage/datasets/human/dnase/encode/ENCSR385AMY/summary/coverage.w5 32 2 mean DNASE:hindlimb muscle male embryo (120 days) DNASE DNase/hindlimb muscle male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +359 0 ENCFF955DHP /home/drk/tillage/datasets/human/dnase/encode/ENCSR385SZQ/summary/coverage.w5 32 2 mean DNASE:MCF 10A treated with 1 uM tamoxifen for 6 hours DNASE DNase/MCF 10A treated with 1 uM tamoxifen for 6 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +360 0 ENCFF017NBX /home/drk/tillage/datasets/human/dnase/encode/ENCSR391YAV/summary/coverage.w5 32 2 mean DNASE:sigmoid colon male adult (54 years) DNASE DNase/sigmoid colon male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +361 0 ENCFF851MCI /home/drk/tillage/datasets/human/dnase/encode/ENCSR392GCE/summary/coverage.w5 32 2 mean DNASE:heart male embryo (120 days) DNASE DNase/heart male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +362 0 ENCFF083ELT /home/drk/tillage/datasets/human/dnase/encode/ENCSR401ESD/summary/coverage.w5 32 2 mean DNASE:tibial nerve female adult (51 year) DNASE DNase/tibial nerve female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +363 0 ENCFF531MYW /home/drk/tillage/datasets/human/dnase/encode/ENCSR405TXU/summary/coverage.w5 32 2 mean DNASE:adipocyte DNASE DNase/adipocyte DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +364 0 ENCFF562EUF /home/drk/tillage/datasets/human/dnase/encode/ENCSR411MGY/summary/coverage.w5 32 2 mean DNASE:muscle of trunk female embryo (121 day) DNASE DNase/muscle of trunk female embryo (121 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +365 0 ENCFF920CTO /home/drk/tillage/datasets/human/dnase/encode/ENCSR412NMI/summary/coverage.w5 32 2 mean DNASE:left cardiac atrium female embryo (101 day) DNASE DNase/left cardiac atrium female embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +366 0 ENCFF213QWE /home/drk/tillage/datasets/human/dnase/encode/ENCSR414IHC/summary/coverage.w5 32 2 mean DNASE:T-cell male adult (21 year) DNASE DNase/T-cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +367 0 ENCFF645BQM /home/drk/tillage/datasets/human/dnase/encode/ENCSR414ZUA/summary/coverage.w5 32 2 mean DNASE:right kidney male embryo (108 days) DNASE DNase/right kidney male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +368 0 ENCFF166VWE /home/drk/tillage/datasets/human/dnase/encode/ENCSR419MZH/summary/coverage.w5 32 2 mean DNASE:adrenal gland female embryo (108 days) DNASE DNase/adrenal gland female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +369 0 ENCFF121CVF /home/drk/tillage/datasets/human/dnase/encode/ENCSR420NOA/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 11 day, kit ligand for 11 day, hydrocortisone succinate for 11 day, erythropoietin for 11 day DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 11 day, kit ligand for 11 day, hydrocortisone succinate for 11 day, erythropoietin for 11 day DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +370 0 ENCFF947HEA /home/drk/tillage/datasets/human/dnase/encode/ENCSR420RWU/summary/coverage.w5 32 2 mean DNASE:brain male embryo (105 days) DNASE DNase/brain male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +371 0 ENCFF116YEY /home/drk/tillage/datasets/human/dnase/encode/ENCSR421KNA/summary/coverage.w5 32 2 mean DNASE:body of pancreas female adult (53 years) DNASE DNase/body of pancreas female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +372 0 ENCFF963ION /home/drk/tillage/datasets/human/dnase/encode/ENCSR422PVL/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (147 days) DNASE DNase/left kidney female embryo (147 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +373 0 ENCFF133LMW /home/drk/tillage/datasets/human/dnase/encode/ENCSR425MRQ/summary/coverage.w5 32 2 mean DNASE:CD4-positive, alpha-beta T cell male adult (37 years) DNASE DNase/CD4-positive, alpha-beta T cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +374 0 ENCFF953EXS /home/drk/tillage/datasets/human/dnase/encode/ENCSR426IEA/summary/coverage.w5 32 2 mean DNASE:KBM-7 DNASE DNase/KBM-7 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +375 0 ENCFF241XMS /home/drk/tillage/datasets/human/dnase/encode/ENCSR426TPQ/summary/coverage.w5 32 2 mean DNASE:psoas muscle male child (3 years) DNASE DNase/psoas muscle male child (3 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +376 0 ENCFF190AUQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR428XAX/summary/coverage.w5 32 2 mean DNASE:ovary female embryo DNASE DNase/ovary female embryo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +377 0 ENCFF175IFH /home/drk/tillage/datasets/human/dnase/encode/ENCSR429RHR/summary/coverage.w5 32 2 mean DNASE:RKO DNASE DNase/RKO DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +378 0 ENCFF869XYK /home/drk/tillage/datasets/human/dnase/encode/ENCSR431UEM/summary/coverage.w5 32 2 mean DNASE:leg bone male embryo (81 day) DNASE DNase/leg bone male embryo (81 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +379 0 ENCFF479JXO /home/drk/tillage/datasets/human/dnase/encode/ENCSR432SZT/summary/coverage.w5 32 2 mean DNASE:glomerular visceral epithelial cell child (3 years) DNASE DNase/glomerular visceral epithelial cell child (3 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +380 0 ENCFF520XMG /home/drk/tillage/datasets/human/dnase/encode/ENCSR434OBM/summary/coverage.w5 32 2 mean DNASE:foreskin melanocyte male newborn DNASE DNase/foreskin melanocyte male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +381 0 ENCFF249WKV /home/drk/tillage/datasets/human/dnase/encode/ENCSR435NHO/summary/coverage.w5 32 2 mean DNASE:embryonic facial prominence embryo (53 days) and embryo (58 days) DNASE DNase/embryonic facial prominence embryo (53 days) and embryo (58 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +382 0 ENCFF154NSS /home/drk/tillage/datasets/human/dnase/encode/ENCSR437AYW/summary/coverage.w5 32 2 mean DNASE:vagina female adult (53 years) DNASE DNase/vagina female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +383 0 ENCFF890HSZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR437KLY/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (85 days) DNASE DNase/kidney female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +384 0 ENCFF990QEC /home/drk/tillage/datasets/human/dnase/encode/ENCSR438TWI/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (96 days) DNASE DNase/muscle of back male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +385 0 ENCFF736QYT /home/drk/tillage/datasets/human/dnase/encode/ENCSR440FZS/summary/coverage.w5 32 2 mean DNASE:muscle of trunk female embryo (113 days) DNASE DNase/muscle of trunk female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +386 0 ENCFF732WSQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR440QMR/summary/coverage.w5 32 2 mean DNASE:iPS DF 19.7 male newborn DNASE DNase/iPS DF 19.7 male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +387 0 ENCFF631ZXV /home/drk/tillage/datasets/human/dnase/encode/ENCSR441MMO/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (110 days) DNASE DNase/right lung female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +388 0 ENCFF216TLU /home/drk/tillage/datasets/human/dnase/encode/ENCSR441OGH/summary/coverage.w5 32 2 mean DNASE:left lung male embryo (87 days) DNASE DNase/left lung male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +389 0 ENCFF471TWL /home/drk/tillage/datasets/human/dnase/encode/ENCSR444VTC/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (105 days) DNASE DNase/large intestine female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +390 0 ENCFF338GCP /home/drk/tillage/datasets/human/dnase/encode/ENCSR445XYW/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (98 days) DNASE DNase/right lung female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +391 0 ENCFF573KUK /home/drk/tillage/datasets/human/dnase/encode/ENCSR449HOQ/summary/coverage.w5 32 2 mean DNASE:leg bone male embryo (81 day) DNASE DNase/leg bone male embryo (81 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +392 0 ENCFF724HAH /home/drk/tillage/datasets/human/dnase/encode/ENCSR452DCM/summary/coverage.w5 32 2 mean DNASE:CD14-positive monocyte male adult (21 year) DNASE DNase/CD14-positive monocyte male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +393 0 ENCFF897JFY /home/drk/tillage/datasets/human/dnase/encode/ENCSR452EGE/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (120 days) DNASE DNase/muscle of arm male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +394 0 ENCFF799HNC /home/drk/tillage/datasets/human/dnase/encode/ENCSR452ZMO/summary/coverage.w5 32 2 mean DNASE:Peyer's patch male adult (37 years) DNASE DNase/Peyer's patch male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +395 0 ENCFF139ZYV /home/drk/tillage/datasets/human/dnase/encode/ENCSR453EVC/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult (36 years) DNASE DNase/common myeloid progenitor, CD34-positive male adult (36 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +396 0 ENCFF549BSX /home/drk/tillage/datasets/human/dnase/encode/ENCSR456KDF/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (108 days) DNASE DNase/left lung female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +397 0 ENCFF359LKO /home/drk/tillage/datasets/human/dnase/encode/ENCSR457ILW/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (91 day) DNASE DNase/small intestine female embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +398 0 ENCFF896FUI /home/drk/tillage/datasets/human/dnase/encode/ENCSR458LIB/summary/coverage.w5 32 2 mean DNASE:MM.1S DNASE DNase/MM.1S DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +399 0 ENCFF410TTD /home/drk/tillage/datasets/human/dnase/encode/ENCSR462XTM/summary/coverage.w5 32 2 mean DNASE:sigmoid colon female adult (51 year) DNASE DNase/sigmoid colon female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +400 0 ENCFF852RDH /home/drk/tillage/datasets/human/dnase/encode/ENCSR468OVW/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (105 days) DNASE DNase/left lung female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +401 0 ENCFF523VFS /home/drk/tillage/datasets/human/dnase/encode/ENCSR468ZXN/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive female adult (33 years) DNASE DNase/common myeloid progenitor, CD34-positive female adult (33 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +402 0 ENCFF773NZF /home/drk/tillage/datasets/human/dnase/encode/ENCSR474GZQ/summary/coverage.w5 32 2 mean DNASE:retina embryo (125 days) and male embryo (103 days) DNASE DNase/retina embryo (125 days) and male embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +403 0 ENCFF468SMI /home/drk/tillage/datasets/human/dnase/encode/ENCSR475VQD/summary/coverage.w5 32 2 mean DNASE:brain male embryo (72 days) and male embryo (76 days) DNASE DNase/brain male embryo (72 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +404 0 ENCFF302BVR /home/drk/tillage/datasets/human/dnase/encode/ENCSR476SDZ/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (108 days) DNASE DNase/muscle of back male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +405 0 ENCFF706WOH /home/drk/tillage/datasets/human/dnase/encode/ENCSR477RTP/summary/coverage.w5 32 2 mean DNASE:IMR-90 DNASE DNase/IMR-90 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +406 0 ENCFF036RHD /home/drk/tillage/datasets/human/dnase/encode/ENCSR482HQE/summary/coverage.w5 32 2 mean DNASE:lung female embryo (108 days) DNASE DNase/lung female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +407 0 ENCFF877ULZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR488PHT/summary/coverage.w5 32 2 mean DNASE:left lung male embryo (113 days) DNASE DNase/left lung male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +408 0 ENCFF506FHA /home/drk/tillage/datasets/human/dnase/encode/ENCSR489NAM/summary/coverage.w5 32 2 mean DNASE:OCI-LY7 DNASE DNase/OCI-LY7 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +409 0 ENCFF300WUQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR490JVQ/summary/coverage.w5 32 2 mean DNASE:upper lobe of left lung female adult (51 year) DNASE DNase/upper lobe of left lung female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +410 0 ENCFF117DAB /home/drk/tillage/datasets/human/dnase/encode/ENCSR493IAY/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 18 days, kit ligand for 18 days, hydrocortisone succinate for 18 days, erythropoietin for 18 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 18 days, kit ligand for 18 days, hydrocortisone succinate for 18 days, erythropoietin for 18 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +411 0 ENCFF681JFJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR493VDS/summary/coverage.w5 32 2 mean DNASE:putamen male adult (78 years) DNASE DNase/putamen male adult (78 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +412 0 ENCFF893ONO /home/drk/tillage/datasets/human/dnase/encode/ENCSR495INQ/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult (42 years) DNASE DNase/common myeloid progenitor, CD34-positive male adult (42 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +413 0 ENCFF555ENQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR499IFY/summary/coverage.w5 32 2 mean DNASE:placenta embryo (53 days) DNASE DNase/placenta embryo (53 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +414 0 ENCFF758ZBZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR499PZA/summary/coverage.w5 32 2 mean DNASE:kidney male embryo (105 days) DNASE DNase/kidney male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +415 0 ENCFF185JEB /home/drk/tillage/datasets/human/dnase/encode/ENCSR501FWC/summary/coverage.w5 32 2 mean DNASE:heart left ventricle female embryo (136 days) DNASE DNase/heart left ventricle female embryo (136 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +416 0 ENCFF966IYT /home/drk/tillage/datasets/human/dnase/encode/ENCSR502NDK/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (108 days) DNASE DNase/small intestine female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +417 0 ENCFF692FQU /home/drk/tillage/datasets/human/dnase/encode/ENCSR503BEM/summary/coverage.w5 32 2 mean DNASE:LoVo DNASE DNase/LoVo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +418 0 ENCFF564DYF /home/drk/tillage/datasets/human/dnase/encode/ENCSR503HIB/summary/coverage.w5 32 2 mean DNASE:cerebellar cortex male adult (78 years) and male adult (84 years) DNASE DNase/cerebellar cortex male adult (78 years) and male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +419 0 ENCFF710LQM /home/drk/tillage/datasets/human/dnase/encode/ENCSR504KZE/summary/coverage.w5 32 2 mean DNASE:lung embryo (67 days) DNASE DNase/lung embryo (67 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +420 0 ENCFF413EKZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR504WYA/summary/coverage.w5 32 2 mean DNASE:transverse colon female adult (53 years) DNASE DNase/transverse colon female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +421 0 ENCFF482UKP /home/drk/tillage/datasets/human/dnase/encode/ENCSR507GFJ/summary/coverage.w5 32 2 mean DNASE:brain embryo (80 days) DNASE DNase/brain embryo (80 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +422 0 ENCFF922XNR /home/drk/tillage/datasets/human/dnase/encode/ENCSR511GQA/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (108 days) DNASE DNase/stomach female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +423 0 ENCFF622CII /home/drk/tillage/datasets/human/dnase/encode/ENCSR512CWR/summary/coverage.w5 32 2 mean DNASE:umbilical cord embryo (59 days) and male embryo (76 days) DNASE DNase/umbilical cord embryo (59 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +424 0 ENCFF683HAF /home/drk/tillage/datasets/human/dnase/encode/ENCSR514QHN/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (105 days) DNASE DNase/muscle of leg male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +425 0 ENCFF109WQI /home/drk/tillage/datasets/human/dnase/encode/ENCSR515EWI/summary/coverage.w5 32 2 mean DNASE:Caki2 DNASE DNase/Caki2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +426 0 ENCFF644WCO /home/drk/tillage/datasets/human/dnase/encode/ENCSR517NHP/summary/coverage.w5 32 2 mean DNASE:muscle of arm female embryo (105 days) DNASE DNase/muscle of arm female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +427 0 ENCFF910FZX /home/drk/tillage/datasets/human/dnase/encode/ENCSR518JGY/summary/coverage.w5 32 2 mean DNASE:foreskin melanocyte male newborn DNASE DNase/foreskin melanocyte male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +428 0 ENCFF450EHI /home/drk/tillage/datasets/human/dnase/encode/ENCSR522FGG/summary/coverage.w5 32 2 mean DNASE:stomach male embryo (108 days) DNASE DNase/stomach male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +429 0 ENCFF381POQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR522WLH/summary/coverage.w5 32 2 mean DNASE:body of pancreas male adult (37 years) DNASE DNase/body of pancreas male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +430 0 ENCFF631XBY /home/drk/tillage/datasets/human/dnase/encode/ENCSR524DWS/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium female embryo (120 days) DNASE DNase/renal cortex interstitium female embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +431 0 ENCFF095KFF /home/drk/tillage/datasets/human/dnase/encode/ENCSR524OCB/summary/coverage.w5 32 2 mean DNASE:body of pancreas female adult (51 year) DNASE DNase/body of pancreas female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +432 0 ENCFF824OUT /home/drk/tillage/datasets/human/dnase/encode/ENCSR531HPD/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (105 days) DNASE DNase/large intestine male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +433 0 ENCFF850IPE /home/drk/tillage/datasets/human/dnase/encode/ENCSR532CRI/summary/coverage.w5 32 2 mean DNASE:limb embryo (58 days) and embryo (59 days) DNASE DNase/limb embryo (58 days) and embryo (59 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +434 0 ENCFF461COG /home/drk/tillage/datasets/human/dnase/encode/ENCSR533VAF/summary/coverage.w5 32 2 mean DNASE:heart female embryo (147 days) DNASE DNase/heart female embryo (147 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +435 0 ENCFF135BIN /home/drk/tillage/datasets/human/dnase/encode/ENCSR536NGW/summary/coverage.w5 32 2 mean DNASE:heart male embryo (96 days) DNASE DNase/heart male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +436 0 ENCFF785TYR /home/drk/tillage/datasets/human/dnase/encode/ENCSR540PVZ/summary/coverage.w5 32 2 mean DNASE:right renal pelvis male embryo (120 days) DNASE DNase/right renal pelvis male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +437 0 ENCFF149IUC /home/drk/tillage/datasets/human/dnase/encode/ENCSR541AVF/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (117 days) DNASE DNase/left lung female embryo (117 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +438 0 ENCFF858RAV /home/drk/tillage/datasets/human/dnase/encode/ENCSR541UPY/summary/coverage.w5 32 2 mean DNASE:thymus female embryo (98 days) DNASE DNase/thymus female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +439 0 ENCFF802LRO /home/drk/tillage/datasets/human/dnase/encode/ENCSR542KIX/summary/coverage.w5 32 2 mean DNASE:ovary female adult (53 years) DNASE DNase/ovary female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +440 0 ENCFF925SLC /home/drk/tillage/datasets/human/dnase/encode/ENCSR543YPH/summary/coverage.w5 32 2 mean DNASE:left kidney male embryo (115 days) DNASE DNase/left kidney male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +441 0 ENCFF527VFR /home/drk/tillage/datasets/human/dnase/encode/ENCSR544KDB/summary/coverage.w5 32 2 mean DNASE:thymus male embryo (113 days) DNASE DNase/thymus male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +442 0 ENCFF176WVA /home/drk/tillage/datasets/human/dnase/encode/ENCSR545KQR/summary/coverage.w5 32 2 mean DNASE:placenta female embryo (105 days) DNASE DNase/placenta female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +443 0 ENCFF746DZE /home/drk/tillage/datasets/human/dnase/encode/ENCSR548MMD/summary/coverage.w5 32 2 mean DNASE:EH DNASE DNase/EH DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +444 0 ENCFF354FAY /home/drk/tillage/datasets/human/dnase/encode/ENCSR550UWM/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (97 days) DNASE DNase/renal cortex interstitium male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +445 0 ENCFF933ZHA /home/drk/tillage/datasets/human/dnase/encode/ENCSR552RKI/summary/coverage.w5 32 2 mean DNASE:placenta embryo (102 days) DNASE DNase/placenta embryo (102 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +446 0 ENCFF708XRO /home/drk/tillage/datasets/human/dnase/encode/ENCSR552XJI/summary/coverage.w5 32 2 mean DNASE:placenta embryo (56 days) and embryo (59 days) DNASE DNase/placenta embryo (56 days) and embryo (59 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +447 0 ENCFF407LCA /home/drk/tillage/datasets/human/dnase/encode/ENCSR554WUJ/summary/coverage.w5 32 2 mean DNASE:renal pelvis female embryo (103 days) DNASE DNase/renal pelvis female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +448 0 ENCFF462ZLK /home/drk/tillage/datasets/human/dnase/encode/ENCSR555QAY/summary/coverage.w5 32 2 mean DNASE:right lobe of liver female adult (53 years) DNASE DNase/right lobe of liver female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +449 0 ENCFF660PED /home/drk/tillage/datasets/human/dnase/encode/ENCSR555TFE/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +450 0 ENCFF616AAF /home/drk/tillage/datasets/human/dnase/encode/ENCSR559WMK/summary/coverage.w5 32 2 mean DNASE:tongue male embryo (72 days) DNASE DNase/tongue male embryo (72 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +451 0 ENCFF723EYP /home/drk/tillage/datasets/human/dnase/encode/ENCSR562ACY/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +452 0 ENCFF775FBE /home/drk/tillage/datasets/human/dnase/encode/ENCSR562FNN/summary/coverage.w5 32 2 mean DNASE:liver female embryo (101 day) and female embryo (113 days) DNASE DNase/liver female embryo (101 day) and female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +453 0 ENCFF658BNW /home/drk/tillage/datasets/human/dnase/encode/ENCSR563XRP/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (107 days) DNASE DNase/large intestine female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +454 0 ENCFF438MEL /home/drk/tillage/datasets/human/dnase/encode/ENCSR564JUY/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 6 days, kit ligand for 6 days, hydrocortisone succinate for 6 days, erythropoietin for 6 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 6 days, kit ligand for 6 days, hydrocortisone succinate for 6 days, erythropoietin for 6 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +455 0 ENCFF819VID /home/drk/tillage/datasets/human/dnase/encode/ENCSR564TUY/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male DNASE DNase/common myeloid progenitor, CD34-positive male DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +456 0 ENCFF389EEG /home/drk/tillage/datasets/human/dnase/encode/ENCSR565EBN/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (98 days) DNASE DNase/small intestine female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +457 0 ENCFF658FXQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR569ATD/summary/coverage.w5 32 2 mean DNASE:CD4-positive, alpha-beta T cell male adult (21 year) DNASE DNase/CD4-positive, alpha-beta T cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +458 0 ENCFF503ZTL /home/drk/tillage/datasets/human/dnase/encode/ENCSR572LDG/summary/coverage.w5 32 2 mean DNASE:brain male embryo (101 day) DNASE DNase/brain male embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +459 0 ENCFF124SMB /home/drk/tillage/datasets/human/dnase/encode/ENCSR575VMI/summary/coverage.w5 32 2 mean DNASE:placenta female embryo (101 day) and male embryo (105 days) DNASE DNase/placenta female embryo (101 day) and male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +460 0 ENCFF069WLL /home/drk/tillage/datasets/human/dnase/encode/ENCSR580OAH/summary/coverage.w5 32 2 mean DNASE:renal pelvis male embryo (91 day) DNASE DNase/renal pelvis male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +461 0 ENCFF830TGU /home/drk/tillage/datasets/human/dnase/encode/ENCSR582IPV/summary/coverage.w5 32 2 mean DNASE:lung embryo (80 days) and male embryo (76 days) DNASE DNase/lung embryo (80 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +462 0 ENCFF460VUW /home/drk/tillage/datasets/human/dnase/encode/ENCSR584LUZ/summary/coverage.w5 32 2 mean DNASE:Ammon's horn male adult (84 years) DNASE DNase/Ammon's horn male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +463 0 ENCFF596JMX /home/drk/tillage/datasets/human/dnase/encode/ENCSR585CGU/summary/coverage.w5 32 2 mean DNASE:muscle of back female embryo (105 days) DNASE DNase/muscle of back female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +464 0 ENCFF606ESZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR587HPR/summary/coverage.w5 32 2 mean DNASE:lung male embryo (82 days) DNASE DNase/lung male embryo (82 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +465 0 ENCFF946AQO /home/drk/tillage/datasets/human/dnase/encode/ENCSR588JXI/summary/coverage.w5 32 2 mean DNASE:left renal cortex interstitium male embryo (105 days) DNASE DNase/left renal cortex interstitium male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +466 0 ENCFF925UKW /home/drk/tillage/datasets/human/dnase/encode/ENCSR593LTJ/summary/coverage.w5 32 2 mean DNASE:trophoblast cell embryo (17 weeks) and embryo (18 weeks) DNASE DNase/trophoblast cell embryo (17 weeks) and embryo (18 weeks) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +467 0 ENCFF548BBX /home/drk/tillage/datasets/human/dnase/encode/ENCSR594NOE/summary/coverage.w5 32 2 mean DNASE:RPMI8226 DNASE DNase/RPMI8226 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +468 0 ENCFF243OFZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR594OWA/summary/coverage.w5 32 2 mean DNASE:small intestine male embryo (91 day) DNASE DNase/small intestine male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +469 0 ENCFF641HVS /home/drk/tillage/datasets/human/dnase/encode/ENCSR595CSH/summary/coverage.w5 32 2 mean DNASE:brain embryo (56 days) and male embryo (58 days) DNASE DNase/brain embryo (56 days) and male embryo (58 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +470 0 ENCFF158QOY /home/drk/tillage/datasets/human/dnase/encode/ENCSR595HZQ/summary/coverage.w5 32 2 mean DNASE:pancreas female adult (30 years) DNASE DNase/pancreas female adult (30 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE +471 0 ENCFF080JZX /home/drk/tillage/datasets/human/dnase/encode/ENCSR597NVK/summary/coverage.w5 32 2 mean DNASE:adrenal gland female adult (53 years) DNASE DNase/adrenal gland female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +472 0 ENCFF322ALX /home/drk/tillage/datasets/human/dnase/encode/ENCSR600KUR/summary/coverage.w5 32 2 mean DNASE:breast epithelium female adult (51 year) DNASE DNase/breast epithelium female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +473 0 ENCFF028YSP /home/drk/tillage/datasets/human/dnase/encode/ENCSR600RAA/summary/coverage.w5 32 2 mean DNASE:left kidney male embryo (87 days) DNASE DNase/left kidney male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +474 0 ENCFF010FIA /home/drk/tillage/datasets/human/dnase/encode/ENCSR606UAR/summary/coverage.w5 32 2 mean DNASE:renal pelvis female embryo (96 days) DNASE DNase/renal pelvis female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +475 0 ENCFF581JYZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR608AHQ/summary/coverage.w5 32 2 mean DNASE:stomach male embryo (127 days) DNASE DNase/stomach male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +476 0 ENCFF726GTU /home/drk/tillage/datasets/human/dnase/encode/ENCSR609DDQ/summary/coverage.w5 32 2 mean DNASE:CD8-positive, alpha-beta T cell female adult (34 years) DNASE DNase/CD8-positive, alpha-beta T cell female adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +477 0 ENCFF599PVD /home/drk/tillage/datasets/human/dnase/encode/ENCSR615WIN/summary/coverage.w5 32 2 mean DNASE:spinal cord female embryo (89 days) DNASE DNase/spinal cord female embryo (89 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +478 0 ENCFF174TXJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR619BNL/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (97 days) DNASE DNase/muscle of arm male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +479 0 ENCFF161NZJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR619DRM/summary/coverage.w5 32 2 mean DNASE:renal pelvis female embryo (105 days) DNASE DNase/renal pelvis female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +480 0 ENCFF442SRX /home/drk/tillage/datasets/human/dnase/encode/ENCSR620QNS/summary/coverage.w5 32 2 mean DNASE:HAP-1 DNASE DNase/HAP-1 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +481 0 ENCFF909HEZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR620WAR/summary/coverage.w5 32 2 mean DNASE:SJSA1 DNASE DNase/SJSA1 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +482 0 ENCFF113RRS /home/drk/tillage/datasets/human/dnase/encode/ENCSR621ENC/summary/coverage.w5 32 2 mean DNASE:retina embryo (74 days) and embryo (85 days) DNASE DNase/retina embryo (74 days) and embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +483 0 ENCFF906KHN /home/drk/tillage/datasets/human/dnase/encode/ENCSR622CAH/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (127 days) DNASE DNase/muscle of leg male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +484 0 ENCFF900LOG /home/drk/tillage/datasets/human/dnase/encode/ENCSR622TWS/summary/coverage.w5 32 2 mean DNASE:fibroblast of skin of abdomen male embryo (97 days) DNASE DNase/fibroblast of skin of abdomen male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +485 0 ENCFF399ISP /home/drk/tillage/datasets/human/dnase/encode/ENCSR626RVD/summary/coverage.w5 32 2 mean DNASE:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days DNASE "DNase/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +486 0 ENCFF138ZHG /home/drk/tillage/datasets/human/dnase/encode/ENCSR627KFV/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (147 days) DNASE DNase/stomach female embryo (147 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +487 0 ENCFF969AND /home/drk/tillage/datasets/human/dnase/encode/ENCSR627NIF/summary/coverage.w5 32 2 mean DNASE:lung male embryo (54 days) and male embryo (58 days) DNASE DNase/lung male embryo (54 days) and male embryo (58 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +488 0 ENCFF508ADO /home/drk/tillage/datasets/human/dnase/encode/ENCSR627UDJ/summary/coverage.w5 32 2 mean DNASE:T-cell male adult (36 years) DNASE DNase/T-cell male adult (36 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +489 0 ENCFF801DBL /home/drk/tillage/datasets/human/dnase/encode/ENCSR628IRM/summary/coverage.w5 32 2 mean DNASE:T-cell male adult (21 year) DNASE DNase/T-cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +490 0 ENCFF401DZU /home/drk/tillage/datasets/human/dnase/encode/ENCSR634YVQ/summary/coverage.w5 32 2 mean DNASE:HK-2 DNASE DNase/HK-2 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +491 0 ENCFF673ICX /home/drk/tillage/datasets/human/dnase/encode/ENCSR638HMQ/summary/coverage.w5 32 2 mean DNASE:NCI-H460 DNASE DNase/NCI-H460 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +492 0 ENCFF655RAK /home/drk/tillage/datasets/human/dnase/encode/ENCSR639XWF/summary/coverage.w5 32 2 mean DNASE:left lung male embryo (96 days) DNASE DNase/left lung male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +493 0 ENCFF005DPL /home/drk/tillage/datasets/human/dnase/encode/ENCSR639ZJI/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult (23 years) DNASE DNase/common myeloid progenitor, CD34-positive male adult (23 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +494 0 ENCFF766YIL /home/drk/tillage/datasets/human/dnase/encode/ENCSR641ZPF/summary/coverage.w5 32 2 mean DNASE:stomach female adult (51 year) DNASE DNase/stomach female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +495 0 ENCFF502EPK /home/drk/tillage/datasets/human/dnase/encode/ENCSR643GHI/summary/coverage.w5 32 2 mean DNASE:CD4-positive, alpha-beta T cell female adult (33 years) DNASE DNase/CD4-positive, alpha-beta T cell female adult (33 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +496 0 ENCFF740DGO /home/drk/tillage/datasets/human/dnase/encode/ENCSR645GJD/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (113 days) DNASE DNase/kidney female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +497 0 ENCFF600WZF /home/drk/tillage/datasets/human/dnase/encode/ENCSR648GDP/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +498 0 ENCFF180IFD /home/drk/tillage/datasets/human/dnase/encode/ENCSR648RAX/summary/coverage.w5 32 2 mean DNASE:placenta female embryo (85 days) DNASE DNase/placenta female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +499 0 ENCFF361UTR /home/drk/tillage/datasets/human/dnase/encode/ENCSR649KBB/summary/coverage.w5 32 2 mean DNASE:brain male embryo (122 days) DNASE DNase/brain male embryo (122 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +500 0 ENCFF903LEE /home/drk/tillage/datasets/human/dnase/encode/ENCSR649PJN/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (97 days) DNASE DNase/muscle of arm male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +501 0 ENCFF161UUJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR656QYL/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium female embryo (103 days) DNASE DNase/renal cortex interstitium female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +502 0 ENCFF126DFR /home/drk/tillage/datasets/human/dnase/encode/ENCSR657DFR/summary/coverage.w5 32 2 mean DNASE:thyroid gland female adult (51 year) DNASE DNase/thyroid gland female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +503 0 ENCFF889CMZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR662HMO/summary/coverage.w5 32 2 mean DNASE:NAMALWA DNASE DNase/NAMALWA DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +504 0 ENCFF351UQV /home/drk/tillage/datasets/human/dnase/encode/ENCSR664PKM/summary/coverage.w5 32 2 mean DNASE:heart embryo (59 days) and female embryo (76 days) DNASE DNase/heart embryo (59 days) and female embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +505 0 ENCFF365LXQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR666YVE/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (105 days) DNASE DNase/large intestine male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +506 0 ENCFF260OFK /home/drk/tillage/datasets/human/dnase/encode/ENCSR670VQZ/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +507 0 ENCFF307BRD /home/drk/tillage/datasets/human/dnase/encode/ENCSR670ZSA/summary/coverage.w5 32 2 mean DNASE:right kidney male embryo (96 days) DNASE DNase/right kidney male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +508 0 ENCFF722MXM /home/drk/tillage/datasets/human/dnase/encode/ENCSR674JIL/summary/coverage.w5 32 2 mean DNASE:CD14-positive monocyte male adult (37 years) DNASE DNase/CD14-positive monocyte male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +509 0 ENCFF422YYH /home/drk/tillage/datasets/human/dnase/encode/ENCSR678ILN/summary/coverage.w5 32 2 mean DNASE:ELF-1 DNASE DNase/ELF-1 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +510 0 ENCFF024WMP /home/drk/tillage/datasets/human/dnase/encode/ENCSR678PDD/summary/coverage.w5 32 2 mean DNASE:spinal cord female embryo (113 days) DNASE DNase/spinal cord female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +511 0 ENCFF090EZE /home/drk/tillage/datasets/human/dnase/encode/ENCSR679IFH/summary/coverage.w5 32 2 mean DNASE:spleen embryo (112 days) DNASE DNase/spleen embryo (112 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +512 0 ENCFF010TXA /home/drk/tillage/datasets/human/dnase/encode/ENCSR680SDS/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (107 days) DNASE DNase/left lung female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +513 0 ENCFF538SYZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR682PKY/summary/coverage.w5 32 2 mean DNASE:thymus female embryo DNASE DNase/thymus female embryo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +514 0 ENCFF131RGB /home/drk/tillage/datasets/human/dnase/encode/ENCSR683QJJ/summary/coverage.w5 32 2 mean DNASE:CD4-positive, alpha-beta T cell male adult (21 year) DNASE DNase/CD4-positive, alpha-beta T cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +515 0 ENCFF827CLR /home/drk/tillage/datasets/human/dnase/encode/ENCSR683YLO/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (96 days) DNASE DNase/stomach female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +516 0 ENCFF923JHL /home/drk/tillage/datasets/human/dnase/encode/ENCSR691MQJ/summary/coverage.w5 32 2 mean DNASE:EL DNASE DNase/EL DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +517 0 ENCFF759CKK /home/drk/tillage/datasets/human/dnase/encode/ENCSR695AUY/summary/coverage.w5 32 2 mean DNASE:CD14-positive monocyte female adult (34 years) DNASE DNase/CD14-positive monocyte female adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +518 0 ENCFF290ZJP /home/drk/tillage/datasets/human/dnase/encode/ENCSR696TPW/summary/coverage.w5 32 2 mean DNASE:thyroid gland female adult (53 years) DNASE DNase/thyroid gland female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +519 0 ENCFF815MQN /home/drk/tillage/datasets/human/dnase/encode/ENCSR696XSJ/summary/coverage.w5 32 2 mean DNASE:adrenal gland female embryo (113 days) DNASE DNase/adrenal gland female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +520 0 ENCFF545YJA /home/drk/tillage/datasets/human/dnase/encode/ENCSR698CUE/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (96 days) DNASE DNase/muscle of back male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +521 0 ENCFF332XCB /home/drk/tillage/datasets/human/dnase/encode/ENCSR700ILE/summary/coverage.w5 32 2 mean DNASE:SJCRH30 DNASE DNase/SJCRH30 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +522 0 ENCFF985WGD /home/drk/tillage/datasets/human/dnase/encode/ENCSR704HNG/summary/coverage.w5 32 2 mean DNASE:natural killer cell male adult (21 year) DNASE DNase/natural killer cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +523 0 ENCFF702IWR /home/drk/tillage/datasets/human/dnase/encode/ENCSR705CNJ/summary/coverage.w5 32 2 mean DNASE:heart male embryo (72 days) and male embryo (76 days) DNASE DNase/heart male embryo (72 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +524 0 ENCFF225GCE /home/drk/tillage/datasets/human/dnase/encode/ENCSR706IDL/summary/coverage.w5 32 2 mean DNASE:midbrain male adult (78 years) and male adult (84 years) DNASE DNase/midbrain male adult (78 years) and male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +525 0 ENCFF338CIA /home/drk/tillage/datasets/human/dnase/encode/ENCSR712PYJ/summary/coverage.w5 32 2 mean DNASE:ovary female adult (30 years) DNASE DNase/ovary female adult (30 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +526 0 ENCFF918FRW /home/drk/tillage/datasets/human/dnase/encode/ENCSR714DIF/summary/coverage.w5 32 2 mean DNASE:mesendoderm originated from H1-hESC DNASE DNase/mesendoderm originated from H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +527 0 ENCFF104JJN /home/drk/tillage/datasets/human/dnase/encode/ENCSR718AAB/summary/coverage.w5 32 2 mean DNASE:natural killer cell male adult (37 years) DNASE DNase/natural killer cell male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +528 0 ENCFF125SYT /home/drk/tillage/datasets/human/dnase/encode/ENCSR723JLG/summary/coverage.w5 32 2 mean DNASE:natural killer cell female adult (34 years) DNASE DNase/natural killer cell female adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +529 0 ENCFF380PKB /home/drk/tillage/datasets/human/dnase/encode/ENCSR724CND/summary/coverage.w5 32 2 mean DNASE:foreskin keratinocyte male newborn DNASE DNase/foreskin keratinocyte male newborn DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE +530 0 ENCFF488GEQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR726YMS/summary/coverage.w5 32 2 mean DNASE:stomach female embryo DNASE DNase/stomach female embryo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +531 0 ENCFF285UPE /home/drk/tillage/datasets/human/dnase/encode/ENCSR728BAD/summary/coverage.w5 32 2 mean DNASE:adrenal gland male embryo (108 days) DNASE DNase/adrenal gland male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +532 0 ENCFF037YBR /home/drk/tillage/datasets/human/dnase/encode/ENCSR729DRB/summary/coverage.w5 32 2 mean DNASE:testis male embryo DNASE DNase/testis male embryo DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +533 0 ENCFF594UFP /home/drk/tillage/datasets/human/dnase/encode/ENCSR731QLJ/summary/coverage.w5 32 2 mean DNASE:mesenchymal stem cell originated from H1-hESC DNASE DNase/mesenchymal stem cell originated from H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +534 0 ENCFF264JCE /home/drk/tillage/datasets/human/dnase/encode/ENCSR733YNW/summary/coverage.w5 32 2 mean DNASE:vagina female adult (51 year) DNASE DNase/vagina female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +535 0 ENCFF158JPG /home/drk/tillage/datasets/human/dnase/encode/ENCSR735BIM/summary/coverage.w5 32 2 mean DNASE:common myeloid progenitor, CD34-positive male adult (43 years) DNASE DNase/common myeloid progenitor, CD34-positive male adult (43 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +536 0 ENCFF062BSK /home/drk/tillage/datasets/human/dnase/encode/ENCSR746RDJ/summary/coverage.w5 32 2 mean DNASE:heart right ventricle female embryo (101 day) and female embryo (103 days) DNASE DNase/heart right ventricle female embryo (101 day) and female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +537 0 ENCFF572BDN /home/drk/tillage/datasets/human/dnase/encode/ENCSR746ZPP/summary/coverage.w5 32 2 mean DNASE:L1-S8R DNASE DNase/L1-S8R DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +538 0 ENCFF162WFN /home/drk/tillage/datasets/human/dnase/encode/ENCSR749BWV/summary/coverage.w5 32 2 mean DNASE:heart female embryo (116 days) and female embryo (98 days) DNASE DNase/heart female embryo (116 days) and female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +539 0 ENCFF747RHY /home/drk/tillage/datasets/human/dnase/encode/ENCSR752EPH/summary/coverage.w5 32 2 mean DNASE:MCF 10A treated with 1 uM tamoxifen for 24 hours DNASE DNase/MCF 10A treated with 1 uM tamoxifen for 24 hours DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +540 0 ENCFF923TRG /home/drk/tillage/datasets/human/dnase/encode/ENCSR752NTF/summary/coverage.w5 32 2 mean DNASE:right renal pelvis male embryo (105 days) DNASE DNase/right renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +541 0 ENCFF851IQY /home/drk/tillage/datasets/human/dnase/encode/ENCSR753QKD/summary/coverage.w5 32 2 mean DNASE:muscle of arm female embryo (98 days) DNASE DNase/muscle of arm female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +542 0 ENCFF685WFL /home/drk/tillage/datasets/human/dnase/encode/ENCSR754LIN/summary/coverage.w5 32 2 mean DNASE:H9 G1 phase genetically modified using stable transfection DNASE DNase/H9 G1 phase genetically modified using stable transfection DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +543 0 ENCFF094FZF /home/drk/tillage/datasets/human/dnase/encode/ENCSR754WNA/summary/coverage.w5 32 2 mean DNASE:tibial nerve male adult (37 years) DNASE DNase/tibial nerve male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +544 0 ENCFF098CIC /home/drk/tillage/datasets/human/dnase/encode/ENCSR757EPJ/summary/coverage.w5 32 2 mean DNASE:kidney male embryo (85 days) DNASE DNase/kidney male embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +545 0 ENCFF645CDA /home/drk/tillage/datasets/human/dnase/encode/ENCSR759UNY/summary/coverage.w5 32 2 mean DNASE:tongue female embryo (59 days) and female embryo (76 days) DNASE DNase/tongue female embryo (59 days) and female embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +546 0 ENCFF950KRY /home/drk/tillage/datasets/human/dnase/encode/ENCSR760QZM/summary/coverage.w5 32 2 mean DNASE:transverse colon female adult (51 year) DNASE DNase/transverse colon female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +547 0 ENCFF881JSN /home/drk/tillage/datasets/human/dnase/encode/ENCSR761ZFA/summary/coverage.w5 32 2 mean DNASE:right renal pelvis male embryo (105 days) DNASE DNase/right renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +548 0 ENCFF484MWV /home/drk/tillage/datasets/human/dnase/encode/ENCSR762FCX/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (91 day) DNASE DNase/large intestine male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +549 0 ENCFF712OII /home/drk/tillage/datasets/human/dnase/encode/ENCSR765BSU/summary/coverage.w5 32 2 mean DNASE:right kidney female embryo (117 days) DNASE DNase/right kidney female embryo (117 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +550 0 ENCFF268XHZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR768OLL/summary/coverage.w5 32 2 mean DNASE:right kidney male embryo (91 day) DNASE DNase/right kidney male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +551 0 ENCFF375JUQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR770DEN/summary/coverage.w5 32 2 mean DNASE:skin fibroblast male embryo (97 days) DNASE DNase/skin fibroblast male embryo (97 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +552 0 ENCFF328BAN /home/drk/tillage/datasets/human/dnase/encode/ENCSR771DAX/summary/coverage.w5 32 2 mean DNASE:globus pallidus male adult (78 years) and male adult (84 years) DNASE DNase/globus pallidus male adult (78 years) and male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +553 0 ENCFF518IQW /home/drk/tillage/datasets/human/dnase/encode/ENCSR774RCO/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (105 days) DNASE DNase/kidney female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +554 0 ENCFF412KRU /home/drk/tillage/datasets/human/dnase/encode/ENCSR777DXQ/summary/coverage.w5 32 2 mean DNASE:right atrium auricular region female adult (53 years) DNASE DNase/right atrium auricular region female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +555 0 ENCFF721IYP /home/drk/tillage/datasets/human/dnase/encode/ENCSR777USE/summary/coverage.w5 32 2 mean DNASE:thymus female embryo (147 days) DNASE DNase/thymus female embryo (147 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +556 0 ENCFF017FGP /home/drk/tillage/datasets/human/dnase/encode/ENCSR782SSS/summary/coverage.w5 32 2 mean DNASE:stomach male adult (34 years) DNASE DNase/stomach male adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +557 0 ENCFF540MDC /home/drk/tillage/datasets/human/dnase/encode/ENCSR782XFY/summary/coverage.w5 32 2 mean DNASE:eye embryo (56 days) and male embryo (76 days) DNASE DNase/eye embryo (56 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +558 0 ENCFF376RIO /home/drk/tillage/datasets/human/dnase/encode/ENCSR783OCW/summary/coverage.w5 32 2 mean DNASE:esophagus squamous epithelium male adult (37 years) DNASE DNase/esophagus squamous epithelium male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +559 0 ENCFF888PNL /home/drk/tillage/datasets/human/dnase/encode/ENCSR785BDQ/summary/coverage.w5 32 2 mean DNASE:glomerular visceral epithelial cell child (3 years) DNASE DNase/glomerular visceral epithelial cell child (3 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +560 0 ENCFF167DZY /home/drk/tillage/datasets/human/dnase/encode/ENCSR786FWF/summary/coverage.w5 32 2 mean DNASE:muscle of back male embryo (127 days) DNASE DNase/muscle of back male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +561 0 ENCFF072UOA /home/drk/tillage/datasets/human/dnase/encode/ENCSR788SOI/summary/coverage.w5 32 2 mean DNASE:spinal cord male embryo (96 days) DNASE DNase/spinal cord male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +562 0 ENCFF222GDV /home/drk/tillage/datasets/human/dnase/encode/ENCSR789VGQ/summary/coverage.w5 32 2 mean DNASE:MCF 10A DNASE DNase/MCF 10A DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +563 0 ENCFF098CAJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR790FIS/summary/coverage.w5 32 2 mean DNASE:transverse colon male adult (54 years) DNASE DNase/transverse colon male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +564 0 ENCFF419BLQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR792ZXA/summary/coverage.w5 32 2 mean DNASE:kidney embryo (59 days) and female embryo (59 days) DNASE DNase/kidney embryo (59 days) and female embryo (59 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +565 0 ENCFF117WXM /home/drk/tillage/datasets/human/dnase/encode/ENCSR794OFW/summary/coverage.w5 32 2 mean DNASE:H1-hESC DNASE DNase/H1-hESC DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +566 0 ENCFF112GQO /home/drk/tillage/datasets/human/dnase/encode/ENCSR796SJV/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (98 days) DNASE DNase/large intestine female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +567 0 ENCFF691QJR /home/drk/tillage/datasets/human/dnase/encode/ENCSR800QGE/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (103 days) DNASE DNase/large intestine female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +568 0 ENCFF804AOO /home/drk/tillage/datasets/human/dnase/encode/ENCSR802AJE/summary/coverage.w5 32 2 mean DNASE:placenta male embryo (85 days) DNASE DNase/placenta male embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +569 0 ENCFF772ECZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR803VCR/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (91 day) DNASE DNase/left lung female embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +570 0 ENCFF751LRX /home/drk/tillage/datasets/human/dnase/encode/ENCSR804RSI/summary/coverage.w5 32 2 mean DNASE:heart embryo (80 days) DNASE DNase/heart embryo (80 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +571 0 ENCFF130BQK /home/drk/tillage/datasets/human/dnase/encode/ENCSR805XIF/summary/coverage.w5 32 2 mean DNASE:femur female embryo (98 days) DNASE DNase/femur female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +572 0 ENCFF345ALB /home/drk/tillage/datasets/human/dnase/encode/ENCSR809CEA/summary/coverage.w5 32 2 mean DNASE:H4 DNASE DNase/H4 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +573 0 ENCFF497YLT /home/drk/tillage/datasets/human/dnase/encode/ENCSR809LCE/summary/coverage.w5 32 2 mean DNASE:trophoblast cell embryo (23 weeks) DNASE DNase/trophoblast cell embryo (23 weeks) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +574 0 ENCFF258PIV /home/drk/tillage/datasets/human/dnase/encode/ENCSR813CKU/summary/coverage.w5 32 2 mean DNASE:urinary bladder male embryo (76 days) DNASE DNase/urinary bladder male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +575 0 ENCFF528SGI /home/drk/tillage/datasets/human/dnase/encode/ENCSR814KRX/summary/coverage.w5 32 2 mean DNASE:HT-29 DNASE DNase/HT-29 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +576 0 ENCFF540ITV /home/drk/tillage/datasets/human/dnase/encode/ENCSR818JGZ/summary/coverage.w5 32 2 mean DNASE:limb embryo (53 days) and embryo (56 days) DNASE DNase/limb embryo (53 days) and embryo (56 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +577 0 ENCFF489DYU /home/drk/tillage/datasets/human/dnase/encode/ENCSR820ICX/summary/coverage.w5 32 2 mean DNASE:retina female embryo (89 days) DNASE DNase/retina female embryo (89 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +578 0 ENCFF867YFT /home/drk/tillage/datasets/human/dnase/encode/ENCSR820WLP/summary/coverage.w5 32 2 mean DNASE:dedifferentiated amniotic fluid mesenchymal stem cell DNASE DNase/dedifferentiated amniotic fluid mesenchymal stem cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +579 0 ENCFF427FTE /home/drk/tillage/datasets/human/dnase/encode/ENCSR820WNB/summary/coverage.w5 32 2 mean DNASE:upper lobe of left lung female adult (53 years) DNASE DNase/upper lobe of left lung female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +580 0 ENCFF643ARA /home/drk/tillage/datasets/human/dnase/encode/ENCSR820XRX/summary/coverage.w5 32 2 mean DNASE:brain female embryo (105 days) DNASE DNase/brain female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +581 0 ENCFF924PVB /home/drk/tillage/datasets/human/dnase/encode/ENCSR826ERZ/summary/coverage.w5 32 2 mean DNASE:muscle of arm embryo (101 day) DNASE DNase/muscle of arm embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +582 0 ENCFF331URX /home/drk/tillage/datasets/human/dnase/encode/ENCSR828RNY/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (108 days) DNASE DNase/renal cortex interstitium male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +583 0 ENCFF210SQU /home/drk/tillage/datasets/human/dnase/encode/ENCSR829MXU/summary/coverage.w5 32 2 mean DNASE:pons male adult (78 years) DNASE DNase/pons male adult (78 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +584 0 ENCFF353EKI /home/drk/tillage/datasets/human/dnase/encode/ENCSR838IPF/summary/coverage.w5 32 2 mean DNASE:thymus female embryo (105 days) DNASE DNase/thymus female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +585 0 ENCFF398WIV /home/drk/tillage/datasets/human/dnase/encode/ENCSR840TVG/summary/coverage.w5 32 2 mean DNASE:CD8-positive, alpha-beta T cell female adult (33 years) DNASE DNase/CD8-positive, alpha-beta T cell female adult (33 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +586 0 ENCFF446JBL /home/drk/tillage/datasets/human/dnase/encode/ENCSR842KCP/summary/coverage.w5 32 2 mean DNASE:cardiac muscle cell DNASE DNase/cardiac muscle cell DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +587 0 ENCFF825SRM /home/drk/tillage/datasets/human/dnase/encode/ENCSR842VTJ/summary/coverage.w5 32 2 mean DNASE:CD8-positive, alpha-beta T cell male adult (21 year) DNASE DNase/CD8-positive, alpha-beta T cell male adult (21 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +588 0 ENCFF800PMS /home/drk/tillage/datasets/human/dnase/encode/ENCSR845CFB/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 8 days, kit ligand for 8 days, hydrocortisone succinate for 8 days, erythropoietin for 8 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 8 days, kit ligand for 8 days, hydrocortisone succinate for 8 days, erythropoietin for 8 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +589 0 ENCFF520PUY /home/drk/tillage/datasets/human/dnase/encode/ENCSR845MEJ/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (117 days) DNASE DNase/right lung female embryo (117 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +590 0 ENCFF942LPA /home/drk/tillage/datasets/human/dnase/encode/ENCSR846CTA/summary/coverage.w5 32 2 mean DNASE:right lung male embryo (105 days) DNASE DNase/right lung male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +591 0 ENCFF609EGN /home/drk/tillage/datasets/human/dnase/encode/ENCSR847RSJ/summary/coverage.w5 32 2 mean DNASE:lung female embryo (96 days) DNASE DNase/lung female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +592 0 ENCFF415UET /home/drk/tillage/datasets/human/dnase/encode/ENCSR848XIY/summary/coverage.w5 32 2 mean DNASE:adrenal gland male adult (54 years) DNASE DNase/adrenal gland male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +593 0 ENCFF493QSG /home/drk/tillage/datasets/human/dnase/encode/ENCSR849OKE/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium male embryo (127 days) DNASE DNase/renal cortex interstitium male embryo (127 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +594 0 ENCFF047HXB /home/drk/tillage/datasets/human/dnase/encode/ENCSR850YHJ/summary/coverage.w5 32 2 mean DNASE:spleen male adult (54 years) DNASE DNase/spleen male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +595 0 ENCFF590MET /home/drk/tillage/datasets/human/dnase/encode/ENCSR851ZFT/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium female embryo (89 days) DNASE DNase/renal cortex interstitium female embryo (89 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +596 0 ENCFF233ORX /home/drk/tillage/datasets/human/dnase/encode/ENCSR852TRT/summary/coverage.w5 32 2 mean DNASE:ascending aorta female adult (51 year) DNASE DNase/ascending aorta female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +597 0 ENCFF141YBL /home/drk/tillage/datasets/human/dnase/encode/ENCSR855DJV/summary/coverage.w5 32 2 mean DNASE:ovary female adult (51 year) DNASE DNase/ovary female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +598 0 ENCFF667COT /home/drk/tillage/datasets/human/dnase/encode/ENCSR855FOP/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 13 days, kit ligand for 13 days, hydrocortisone succinate for 13 days, erythropoietin for 13 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 13 days, kit ligand for 13 days, hydrocortisone succinate for 13 days, erythropoietin for 13 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +599 0 ENCFF626LYV /home/drk/tillage/datasets/human/dnase/encode/ENCSR856NXV/summary/coverage.w5 32 2 mean DNASE:cardiac fibroblast female embryo (94 days) and female embryo (98 days) DNASE DNase/cardiac fibroblast female embryo (94 days) and female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +600 0 ENCFF378ZLF /home/drk/tillage/datasets/human/dnase/encode/ENCSR856QJX/summary/coverage.w5 32 2 mean DNASE:adrenal gland male embryo (85 days) DNASE DNase/adrenal gland male embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +601 0 ENCFF443KCU /home/drk/tillage/datasets/human/dnase/encode/ENCSR857AEB/summary/coverage.w5 32 2 mean DNASE:large intestine male embryo (108 days) DNASE DNase/large intestine male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +602 0 ENCFF568EAH /home/drk/tillage/datasets/human/dnase/encode/ENCSR859CZM/summary/coverage.w5 32 2 mean DNASE:occipital lobe male adult (84 years) DNASE DNase/occipital lobe male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +603 0 ENCFF586GLK /home/drk/tillage/datasets/human/dnase/encode/ENCSR859KGQ/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (107 days) DNASE DNase/right lung female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +604 0 ENCFF374WLB /home/drk/tillage/datasets/human/dnase/encode/ENCSR860NDZ/summary/coverage.w5 32 2 mean DNASE:small intestine female embryo (105 days) DNASE DNase/small intestine female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +605 0 ENCFF779SYM /home/drk/tillage/datasets/human/dnase/encode/ENCSR861NUH/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (104 days) DNASE DNase/muscle of leg male embryo (104 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +606 0 ENCFF561DJM /home/drk/tillage/datasets/human/dnase/encode/ENCSR864IGD/summary/coverage.w5 32 2 mean DNASE:lower leg skin female adult (53 years) DNASE DNase/lower leg skin female adult (53 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +607 0 ENCFF193WRL /home/drk/tillage/datasets/human/dnase/encode/ENCSR865ICK/summary/coverage.w5 32 2 mean DNASE:adrenal gland female adult (51 year) DNASE DNase/adrenal gland female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +608 0 ENCFF530PCA /home/drk/tillage/datasets/human/dnase/encode/ENCSR866RCY/summary/coverage.w5 32 2 mean DNASE:adrenal gland female embryo (85 days) DNASE DNase/adrenal gland female embryo (85 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +609 0 ENCFF170QVL /home/drk/tillage/datasets/human/dnase/encode/ENCSR868XPR/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (115 days) DNASE DNase/muscle of arm male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +610 0 ENCFF200VXY /home/drk/tillage/datasets/human/dnase/encode/ENCSR871APX/summary/coverage.w5 32 2 mean DNASE:right kidney female embryo (147 days) DNASE DNase/right kidney female embryo (147 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +611 0 ENCFF248ZTQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR873ANE/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (76 days) and male embryo (76 days) DNASE DNase/kidney female embryo (76 days) and male embryo (76 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +612 0 ENCFF367ZCY /home/drk/tillage/datasets/human/dnase/encode/ENCSR874CAK/summary/coverage.w5 32 2 mean DNASE:large intestine female embryo (108 days) DNASE DNase/large intestine female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +613 0 ENCFF759AQQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR884MCZ/summary/coverage.w5 32 2 mean DNASE:right kidney female embryo (98 days) DNASE DNase/right kidney female embryo (98 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +614 0 ENCFF596RFA /home/drk/tillage/datasets/human/dnase/encode/ENCSR887BNC/summary/coverage.w5 32 2 mean DNASE:right renal cortex interstitium male embryo (120 days) DNASE DNase/right renal cortex interstitium male embryo (120 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +615 0 ENCFF259GAI /home/drk/tillage/datasets/human/dnase/encode/ENCSR888GBS/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (96 days) DNASE DNase/muscle of arm male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +616 0 ENCFF350RPE /home/drk/tillage/datasets/human/dnase/encode/ENCSR888UPQ/summary/coverage.w5 32 2 mean DNASE:thymus male embryo (108 days) DNASE DNase/thymus male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +617 0 ENCFF104EQW /home/drk/tillage/datasets/human/dnase/encode/ENCSR891VOV/summary/coverage.w5 32 2 mean DNASE:B cell female adult (34 years) DNASE DNase/B cell female adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +618 0 ENCFF762FMJ /home/drk/tillage/datasets/human/dnase/encode/ENCSR902XFY/summary/coverage.w5 32 2 mean DNASE:thyroid gland male adult (54 years) DNASE DNase/thyroid gland male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +619 0 ENCFF370CZR /home/drk/tillage/datasets/human/dnase/encode/ENCSR910OQF/summary/coverage.w5 32 2 mean DNASE:spinal cord female embryo (59 days) and male embryo (72 days) DNASE DNase/spinal cord female embryo (59 days) and male embryo (72 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +620 0 ENCFF326FWY /home/drk/tillage/datasets/human/dnase/encode/ENCSR911LTI/summary/coverage.w5 32 2 mean DNASE:heart embryo (96 days) DNASE DNase/heart embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +621 0 ENCFF734APY /home/drk/tillage/datasets/human/dnase/encode/ENCSR911YVV/summary/coverage.w5 32 2 mean DNASE:renal pelvis female embryo (89 days) DNASE DNase/renal pelvis female embryo (89 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +622 0 ENCFF643GKF /home/drk/tillage/datasets/human/dnase/encode/ENCSR913NYL/summary/coverage.w5 32 2 mean DNASE:renal pelvis male embryo (108 days) DNASE DNase/renal pelvis male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +623 0 ENCFF281GOQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR914DOH/summary/coverage.w5 32 2 mean DNASE:heart female embryo (103 days) DNASE DNase/heart female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +624 0 ENCFF745RLH /home/drk/tillage/datasets/human/dnase/encode/ENCSR915BSC/summary/coverage.w5 32 2 mean DNASE:H9 DNASE DNase/H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +625 0 ENCFF971AHO /home/drk/tillage/datasets/human/dnase/encode/ENCSR921NMD/summary/coverage.w5 32 2 mean DNASE:K562 DNASE DNase/K562 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE +626 0 ENCFF168UHZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR928SYE/summary/coverage.w5 32 2 mean DNASE:left renal cortex interstitium male embryo (105 days) DNASE DNase/left renal cortex interstitium male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +627 0 ENCFF499TWX /home/drk/tillage/datasets/human/dnase/encode/ENCSR930AUG/summary/coverage.w5 32 2 mean DNASE:right lung female embryo (108 days) DNASE DNase/right lung female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +628 0 ENCFF218SJO /home/drk/tillage/datasets/human/dnase/encode/ENCSR930YSB/summary/coverage.w5 32 2 mean DNASE:stomach female embryo (96 days) DNASE DNase/stomach female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +629 0 ENCFF619LIB /home/drk/tillage/datasets/human/dnase/encode/ENCSR931UQB/summary/coverage.w5 32 2 mean DNASE:small intestine male adult (34 years) DNASE DNase/small intestine male adult (34 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +630 0 ENCFF701FFX /home/drk/tillage/datasets/human/dnase/encode/ENCSR932DHT/summary/coverage.w5 32 2 mean DNASE:renal cortex interstitium female embryo (96 days) DNASE DNase/renal cortex interstitium female embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +631 0 ENCFF385DEA /home/drk/tillage/datasets/human/dnase/encode/ENCSR932KWJ/summary/coverage.w5 32 2 mean DNASE:A172 DNASE DNase/A172 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +632 0 ENCFF106TCU /home/drk/tillage/datasets/human/dnase/encode/ENCSR935EVZ/summary/coverage.w5 32 2 mean DNASE:left lung male embryo (115 days) DNASE DNase/left lung male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +633 0 ENCFF198FAC /home/drk/tillage/datasets/human/dnase/encode/ENCSR937RVN/summary/coverage.w5 32 2 mean DNASE:muscle of leg male embryo (115 days) DNASE DNase/muscle of leg male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +634 0 ENCFF907UIY /home/drk/tillage/datasets/human/dnase/encode/ENCSR937UWI/summary/coverage.w5 32 2 mean DNASE:hematopoietic multipotent progenitor cell treated with interleukin-3 for 15 days, kit ligand for 15 days, hydrocortisone succinate for 15 days, erythropoietin for 15 days DNASE DNase/hematopoietic multipotent progenitor cell treated with interleukin-3 for 15 days, kit ligand for 15 days, hydrocortisone succinate for 15 days, erythropoietin for 15 days DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +635 0 ENCFF131DEL /home/drk/tillage/datasets/human/dnase/encode/ENCSR938UOR/summary/coverage.w5 32 2 mean DNASE:muscle of leg female embryo (115 days) DNASE DNase/muscle of leg female embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +636 0 ENCFF363RKM /home/drk/tillage/datasets/human/dnase/encode/ENCSR940NLN/summary/coverage.w5 32 2 mean DNASE:PC-9 DNASE DNase/PC-9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +637 0 ENCFF547ICI /home/drk/tillage/datasets/human/dnase/encode/ENCSR941DTJ/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (108 days) DNASE DNase/kidney female embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +638 0 ENCFF047HGQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR941SMM/summary/coverage.w5 32 2 mean DNASE:stomach embryo (101 day) DNASE DNase/stomach embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +639 0 ENCFF692AJS /home/drk/tillage/datasets/human/dnase/encode/ENCSR943SYS/summary/coverage.w5 32 2 mean DNASE:H9 G2 phase genetically modified using stable transfection DNASE DNase/H9 G2 phase genetically modified using stable transfection DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +640 0 ENCFF951HWM /home/drk/tillage/datasets/human/dnase/encode/ENCSR944JCE/summary/coverage.w5 32 2 mean DNASE:esophagus muscularis mucosa male adult (37 years) DNASE DNase/esophagus muscularis mucosa male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +641 0 ENCFF053FMQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR945RWN/summary/coverage.w5 32 2 mean DNASE:small intestine male embryo (108 days) DNASE DNase/small intestine male embryo (108 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +642 0 ENCFF791FRX /home/drk/tillage/datasets/human/dnase/encode/ENCSR946DXB/summary/coverage.w5 32 2 mean DNASE:heart left ventricle female embryo (101 day) and female embryo (103 days) DNASE DNase/heart left ventricle female embryo (101 day) and female embryo (103 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +643 0 ENCFF461SNA /home/drk/tillage/datasets/human/dnase/encode/ENCSR946MVP/summary/coverage.w5 32 2 mean DNASE:SK-N-DZ DNASE DNase/SK-N-DZ DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +644 0 ENCFF622PZI /home/drk/tillage/datasets/human/dnase/encode/ENCSR947POC/summary/coverage.w5 32 2 mean DNASE:brain male embryo (104 days) DNASE DNase/brain male embryo (104 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +645 0 ENCFF030GLD /home/drk/tillage/datasets/human/dnase/encode/ENCSR947VPG/summary/coverage.w5 32 2 mean DNASE:right lung male embryo (87 days) DNASE DNase/right lung male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +646 0 ENCFF293NBG /home/drk/tillage/datasets/human/dnase/encode/ENCSR949JYS/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (105 days) DNASE DNase/muscle of arm male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +647 0 ENCFF778GKQ /home/drk/tillage/datasets/human/dnase/encode/ENCSR951XEN/summary/coverage.w5 32 2 mean DNASE:muscle of arm male embryo (104 days) DNASE DNase/muscle of arm male embryo (104 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +648 0 ENCFF207ECZ /home/drk/tillage/datasets/human/dnase/encode/ENCSR953JVX/summary/coverage.w5 32 2 mean DNASE:kidney female embryo (105 days) DNASE DNase/kidney female embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +649 0 ENCFF459LFA /home/drk/tillage/datasets/human/dnase/encode/ENCSR953WJO/summary/coverage.w5 32 2 mean DNASE:left lung male embryo (105 days) DNASE DNase/left lung male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +650 0 ENCFF532VZC /home/drk/tillage/datasets/human/dnase/encode/ENCSR953XJU/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (107 days) DNASE DNase/left kidney female embryo (107 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +651 0 ENCFF220BQY /home/drk/tillage/datasets/human/dnase/encode/ENCSR954AJK/summary/coverage.w5 32 2 mean DNASE:Peyer's patch male adult (37 years) DNASE DNase/Peyer's patch male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +652 0 ENCFF884QVN /home/drk/tillage/datasets/human/dnase/encode/ENCSR956ZHU/summary/coverage.w5 32 2 mean DNASE:renal pelvis male embryo (113 days) DNASE DNase/renal pelvis male embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +653 0 ENCFF069GRI /home/drk/tillage/datasets/human/dnase/encode/ENCSR958QXU/summary/coverage.w5 32 2 mean DNASE:prostate gland male adult (37 years) DNASE DNase/prostate gland male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +654 0 ENCFF977IGB /home/drk/tillage/datasets/human/dnase/encode/ENCSR959ZXU/summary/coverage.w5 32 2 mean DNASE:HeLa-S3 DNASE DNase/HeLa-S3 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +655 0 ENCFF609SYX /home/drk/tillage/datasets/human/dnase/encode/ENCSR960EJV/summary/coverage.w5 32 2 mean DNASE:left lung female embryo (110 days) DNASE DNase/left lung female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +656 0 ENCFF689ZKP /home/drk/tillage/datasets/human/dnase/encode/ENCSR962EAP/summary/coverage.w5 32 2 mean DNASE:thymus male embryo (104 days) DNASE DNase/thymus male embryo (104 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +657 0 ENCFF417MBH /home/drk/tillage/datasets/human/dnase/encode/ENCSR963ALV/summary/coverage.w5 32 2 mean DNASE:neural progenitor cell originated from H9 DNASE DNase/neural progenitor cell originated from H9 DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +658 0 ENCFF833HDX /home/drk/tillage/datasets/human/dnase/encode/ENCSR964MZQ/summary/coverage.w5 32 2 mean DNASE:trophoblast cell embryo (39 weeks) and embryo (40 weeks) DNASE DNase/trophoblast cell embryo (39 weeks) and embryo (40 weeks) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +659 0 ENCFF491HNC /home/drk/tillage/datasets/human/dnase/encode/ENCSR964VVW/summary/coverage.w5 32 2 mean DNASE:right lung male embryo (96 days) DNASE DNase/right lung male embryo (96 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +660 0 ENCFF091ZXC /home/drk/tillage/datasets/human/dnase/encode/ENCSR964WHY/summary/coverage.w5 32 2 mean DNASE:H9 G1 phase genetically modified using stable transfection DNASE DNase/H9 G1 phase genetically modified using stable transfection DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +661 0 ENCFF746JHF /home/drk/tillage/datasets/human/dnase/encode/ENCSR970ZLG/summary/coverage.w5 32 2 mean DNASE:small intestine male embryo (87 days) DNASE DNase/small intestine male embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +662 0 ENCFF217JVN /home/drk/tillage/datasets/human/dnase/encode/ENCSR973MKT/summary/coverage.w5 32 2 mean DNASE:spinal cord female embryo (87 days) DNASE DNase/spinal cord female embryo (87 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +663 0 ENCFF623DPF /home/drk/tillage/datasets/human/dnase/encode/ENCSR974TXT/summary/coverage.w5 32 2 mean DNASE:left kidney female embryo (110 days) DNASE DNase/left kidney female embryo (110 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +664 0 ENCFF658GXI /home/drk/tillage/datasets/human/dnase/encode/ENCSR976XOY/summary/coverage.w5 32 2 mean DNASE:arm bone male embryo (81 day) DNASE DNase/arm bone male embryo (81 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +665 0 ENCFF068YUS /home/drk/tillage/datasets/human/dnase/encode/ENCSR978QUT/summary/coverage.w5 32 2 mean DNASE:testis male adult (54 years) DNASE DNase/testis male adult (54 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +666 0 ENCFF624FJD /home/drk/tillage/datasets/human/dnase/encode/ENCSR979ZJS/summary/coverage.w5 32 2 mean DNASE:transverse colon male adult (37 years) DNASE DNase/transverse colon male adult (37 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +667 0 ENCFF630KCX /home/drk/tillage/datasets/human/dnase/encode/ENCSR986HEN/summary/coverage.w5 32 2 mean DNASE:right renal pelvis male embryo (105 days) DNASE DNase/right renal pelvis male embryo (105 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +668 0 ENCFF283WCF /home/drk/tillage/datasets/human/dnase/encode/ENCSR986XLW/summary/coverage.w5 32 2 mean DNASE:lung embryo (101 day) DNASE DNase/lung embryo (101 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +669 0 ENCFF848BGL /home/drk/tillage/datasets/human/dnase/encode/ENCSR986YWZ/summary/coverage.w5 32 2 mean DNASE:inferior parietal cortex male adult (84 years) DNASE DNase/inferior parietal cortex male adult (84 years) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +670 0 ENCFF403BFX /home/drk/tillage/datasets/human/dnase/encode/ENCSR988YKR/summary/coverage.w5 32 2 mean DNASE:kidney capillary endothelial cell female embryo (113 days) DNASE DNase/kidney capillary endothelial cell female embryo (113 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +671 0 ENCFF383SIU /home/drk/tillage/datasets/human/dnase/encode/ENCSR989YIV/summary/coverage.w5 32 2 mean DNASE:placenta male embryo (91 day) DNASE DNase/placenta male embryo (91 day) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +672 0 ENCFF253IUB /home/drk/tillage/datasets/human/dnase/encode/ENCSR990XXC/summary/coverage.w5 32 2 mean DNASE:right kidney male embryo (115 days) DNASE DNase/right kidney male embryo (115 days) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +673 0 ENCFF871GME /home/drk/tillage/datasets/human/dnase/encode/ENCSR999TSD/summary/coverage.w5 32 2 mean DNASE:coronary artery female adult (51 year) DNASE DNase/coronary artery female adult (51 year) DNase TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +674 0 GSM2543089 /home/drk/tillage/datasets/human/atac/geo/GSM2543089/summary/coverage.w5 64 1 sum ATAC:BM0106-Day0-MCP-A / Bone Marrow CD34+ / pDC ATAC "ATAC/BM0106-Day0-MCP-A ; Bone Marrow CD34+ ; pDC" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +675 0 GSM2543090 /home/drk/tillage/datasets/human/atac/geo/GSM2543090/summary/coverage.w5 64 1 sum ATAC:BM0106-UNK-ATAC-2 / Bone Marrow CD34+ / UNK ATAC "ATAC/BM0106-UNK-ATAC-2 ; Bone Marrow CD34+ ; UNK" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +676 0 GSM2543091 /home/drk/tillage/datasets/human/atac/geo/GSM2543091/summary/coverage.w5 64 1 sum ATAC:BM0828-MEGA1-A-151109 / Bone Marrow CD34+ / Mega ATAC "ATAC/BM0828-MEGA1-A-151109 ; Bone Marrow CD34+ ; Mega" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +677 0 GSM2543093 /home/drk/tillage/datasets/human/atac/geo/GSM2543093/summary/coverage.w5 64 1 sum ATAC:BM1077-MCP / Bone Marrow CD34+ / pDC ATAC "ATAC/BM1077-MCP ; Bone Marrow CD34+ ; pDC" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +678 0 GSM2543094 /home/drk/tillage/datasets/human/atac/geo/GSM2543094/summary/coverage.w5 64 1 sum ATAC:BM1077-UNK / Bone Marrow CD34+ / UNK ATAC "ATAC/BM1077-UNK ; Bone Marrow CD34+ ; UNK" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +679 0 GSM2543095 /home/drk/tillage/datasets/human/atac/geo/GSM2543095/summary/coverage.w5 64 1 sum ATAC:BM1137-GMP1-low-ATAC-2 / Bone Marrow CD34+ / GMP-A ATAC "ATAC/BM1137-GMP1-low-ATAC-2 ; Bone Marrow CD34+ ; GMP-A" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +680 0 GSM2543096 /home/drk/tillage/datasets/human/atac/geo/GSM2543096/summary/coverage.w5 64 1 sum ATAC:BM1137-GMP2-mid-ATAC-1 / Bone Marrow CD34+ / GMP-B ATAC "ATAC/BM1137-GMP2-mid-ATAC-1 ; Bone Marrow CD34+ ; GMP-B" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +681 0 GSM2543098 /home/drk/tillage/datasets/human/atac/geo/GSM2543098/summary/coverage.w5 64 1 sum ATAC:BM1137-GMP3-high-ATAC-2 / Bone Marrow CD34+ / GMP-C ATAC "ATAC/BM1137-GMP3-high-ATAC-2 ; Bone Marrow CD34+ ; GMP-C" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +682 0 GSM2543099 /home/drk/tillage/datasets/human/atac/geo/GSM2543099/summary/coverage.w5 64 1 sum ATAC:BM1214-Day0-MCP / Bone Marrow CD34+ / pDC ATAC "ATAC/BM1214-Day0-MCP ; Bone Marrow CD34+ ; pDC" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +683 0 GSM2543100 /home/drk/tillage/datasets/human/atac/geo/GSM2543100/summary/coverage.w5 64 1 sum ATAC:BM1214-Day0-UNK-A / Bone Marrow CD34+ / UNK ATAC "ATAC/BM1214-Day0-UNK-A ; Bone Marrow CD34+ ; UNK" ATAC FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +684 0 ENCFF991NDB /home/drk/tillage/datasets/human/chip/encode/ENCSR000AHD/summary/ENCFF991NDB.w5 32 2 mean CHIP:CTCF:MCF-7 CHIP ChIP-TF:CTCF/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +685 0 ENCFF831FHP /home/drk/tillage/datasets/human/chip/encode/ENCSR000AHF/summary/ENCFF831FHP.w5 32 2 mean CHIP:TAF1:MCF-7 CHIP ChIP-TF:TAF1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +686 0 ENCFF776DPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKA/summary/ENCFF776DPQ.w5 32 2 mean CHIP:H3K4me3:GM12878 CHIP ChIP-Histone:H3K4me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +687 0 ENCFF279CYY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKB/summary/ENCFF279CYY.w5 32 2 mean CHIP:CTCF:GM12878 CHIP ChIP-TF:CTCF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +688 0 ENCFF340JIF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKC/summary/ENCFF340JIF.w5 32 2 mean CHIP:H3K27ac:GM12878 CHIP ChIP-Histone:H3K27ac/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +689 0 ENCFF313LYI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKD/summary/ENCFF313LYI.w5 32 2 mean CHIP:H3K27me3:GM12878 CHIP ChIP-Histone:H3K27me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +690 0 ENCFF831ZHL /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKF/summary/ENCFF831ZHL.w5 32 2 mean CHIP:H3K4me1:GM12878 CHIP ChIP-Histone:H3K4me1/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +691 0 ENCFF039HDL /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKG/summary/ENCFF039HDL.w5 32 2 mean CHIP:H3K4me2:GM12878 CHIP ChIP-Histone:H3K4me2/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +692 0 ENCFF028KBY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKH/summary/ENCFF028KBY.w5 32 2 mean CHIP:H3K9ac:GM12878 CHIP ChIP-Histone:H3K9ac/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +693 0 ENCFF309OEW /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKI/summary/ENCFF309OEW.w5 32 2 mean CHIP:H4K20me1:GM12878 CHIP ChIP-TF:H4K20me1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +694 0 ENCFF670AYF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKK/summary/ENCFF670AYF.w5 32 2 mean CHIP:H3K27me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K27me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +695 0 ENCFF887SAU /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKM/summary/ENCFF887SAU.w5 32 2 mean CHIP:H3K4me2:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K4me2/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +696 0 ENCFF930RTT /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKN/summary/ENCFF930RTT.w5 32 2 mean CHIP:H3K4me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K4me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +697 0 ENCFF405AYC /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKO/summary/ENCFF405AYC.w5 32 2 mean CHIP:CTCF:K562 CHIP ChIP-TF:CTCF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +698 0 ENCFF914VFE /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKQ/summary/ENCFF914VFE.w5 32 2 mean CHIP:H3K27me3:K562 CHIP ChIP-Histone:H3K27me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +699 0 ENCFF954JHK /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKR/summary/ENCFF954JHK.w5 32 2 mean CHIP:H3K36me3:K562 CHIP ChIP-Histone:H3K36me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +700 0 ENCFF491AUC /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKT/summary/ENCFF491AUC.w5 32 2 mean CHIP:H3K4me2:K562 CHIP ChIP-Histone:H3K4me2/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +701 0 ENCFF814IYI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKU/summary/ENCFF814IYI.w5 32 2 mean CHIP:H3K4me3:K562 CHIP ChIP-Histone:H3K4me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +702 0 ENCFF115LJM /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKV/summary/ENCFF115LJM.w5 32 2 mean CHIP:H3K9ac:K562 CHIP ChIP-Histone:H3K9ac/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +703 0 ENCFF271KWX /home/drk/tillage/datasets/human/chip/encode/ENCSR000AKW/summary/ENCFF271KWX.w5 32 2 mean CHIP:H3K9me1:K562 CHIP ChIP-Histone:H3K9me1/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +704 0 ENCFF822MVW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALA/summary/ENCFF822MVW.w5 32 2 mean CHIP:CTCF:endothelial cell of umbilical vein male newborn CHIP ChIP-TF:CTCF/endothelial cell of umbilical vein male newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +705 0 ENCFF656TFQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALB/summary/ENCFF656TFQ.w5 32 2 mean CHIP:H3K27ac:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K27ac/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +706 0 ENCFF717RJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALK/summary/ENCFF717RJQ.w5 32 2 mean CHIP:H3K27ac:keratinocyte female CHIP ChIP-Histone:H3K27ac/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +707 0 ENCFF210BII /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALW/summary/ENCFF210BII.w5 32 2 mean CHIP:H3K27ac:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K27ac/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +708 0 ENCFF379TLT /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALX/summary/ENCFF379TLT.w5 32 2 mean CHIP:H3K27me3:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K27me3/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +709 0 ENCFF032JOU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ALY/summary/ENCFF032JOU.w5 32 2 mean CHIP:H3K36me3:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K36me3/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +710 0 ENCFF109QAV /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMC/summary/ENCFF109QAV.w5 32 2 mean CHIP:H3K4me2:HepG2 CHIP ChIP-Histone:H3K4me2/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +711 0 ENCFF053ROV /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMD/summary/ENCFF053ROV.w5 32 2 mean CHIP:H3K9ac:HepG2 CHIP ChIP-Histone:H3K9ac/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +712 0 ENCFF520THR /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMF/summary/ENCFF520THR.w5 32 2 mean CHIP:CTCF:H1-hESC CHIP ChIP-TF:CTCF/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +713 0 ENCFF649FRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMJ/summary/ENCFF649FRQ.w5 32 2 mean CHIP:H3K4me1:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K4me1/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +714 0 ENCFF458AJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMK/summary/ENCFF458AJQ.w5 32 2 mean CHIP:H3K4me2:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K4me2/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +715 0 ENCFF277MXO /home/drk/tillage/datasets/human/chip/encode/ENCSR000AML/summary/ENCFF277MXO.w5 32 2 mean CHIP:H3K4me3:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K4me3/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +716 0 ENCFF991CBZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMM/summary/ENCFF991CBZ.w5 32 2 mean CHIP:H4K20me1:mammary epithelial cell female adult (50 years) CHIP ChIP-TF:H4K20me1/mammary epithelial cell female adult (50 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +717 0 ENCFF746CXV /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMP/summary/ENCFF746CXV.w5 32 2 mean CHIP:H3K4me3:HepG2 CHIP ChIP-Histone:H3K4me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +718 0 ENCFF554JDF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMQ/summary/ENCFF554JDF.w5 32 2 mean CHIP:H4K20me1:HepG2 CHIP ChIP-TF:H4K20me1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +719 0 ENCFF637KNN /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMR/summary/ENCFF637KNN.w5 32 2 mean CHIP:H3K27ac:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K27ac/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +720 0 ENCFF590JWS /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMS/summary/ENCFF590JWS.w5 32 2 mean CHIP:H3K27me3:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K27me3/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +721 0 ENCFF135HOI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMT/summary/ENCFF135HOI.w5 32 2 mean CHIP:H3K36me3:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K36me3/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +722 0 ENCFF021KNK /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMW/summary/ENCFF021KNK.w5 32 2 mean CHIP:H3K4me3:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K4me3/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +723 0 ENCFF685RSM /home/drk/tillage/datasets/human/chip/encode/ENCSR000AMX/summary/ENCFF685RSM.w5 32 2 mean CHIP:H3K9ac:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K9ac/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +724 0 ENCFF743ROG /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANF/summary/ENCFF743ROG.w5 32 2 mean CHIP:H3K27ac:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K27ac/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +725 0 ENCFF231WDC /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANG/summary/ENCFF231WDC.w5 32 2 mean CHIP:H3K27me3:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K27me3/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +726 0 ENCFF273DOW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANH/summary/ENCFF273DOW.w5 32 2 mean CHIP:H3K36me3:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K36me3/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +727 0 ENCFF653ORE /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANI/summary/ENCFF653ORE.w5 32 2 mean CHIP:H3K4me1:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K4me1/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +728 0 ENCFF434MOL /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANJ/summary/ENCFF434MOL.w5 32 2 mean CHIP:H3K4me2:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K4me2/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +729 0 ENCFF363RJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANK/summary/ENCFF363RJQ.w5 32 2 mean CHIP:H3K4me3:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K4me3/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +730 0 ENCFF546LUX /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANL/summary/ENCFF546LUX.w5 32 2 mean CHIP:H3K9ac:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K9ac/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +731 0 ENCFF126AZH /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANM/summary/ENCFF126AZH.w5 32 2 mean CHIP:H4K20me1:skeletal muscle myoblast male adult (22 years) CHIP ChIP-TF:H4K20me1/skeletal muscle myoblast male adult (22 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +732 0 ENCFF423TVA /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANP/summary/ENCFF423TVA.w5 32 2 mean CHIP:H3K27ac:H1-hESC CHIP ChIP-Histone:H3K27ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +733 0 ENCFF572MQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANQ/summary/ENCFF572MQQ.w5 32 2 mean CHIP:H3K79me2:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K79me2/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +734 0 ENCFF310GVO /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANR/summary/ENCFF310GVO.w5 32 2 mean CHIP:H3K9me3:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K9me3/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +735 0 ENCFF737HMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANS/summary/ENCFF737HMZ.w5 32 2 mean CHIP:CTCF:myotube CHIP ChIP-TF:CTCF/myotube ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +736 0 ENCFF129YOI /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANU/summary/ENCFF129YOI.w5 32 2 mean CHIP:H2AFZ:myotube CHIP ChIP-TF:H2AFZ/myotube ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +737 0 ENCFF040VCY /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANV/summary/ENCFF040VCY.w5 32 2 mean CHIP:H3K27ac:myotube CHIP ChIP-Histone:H3K27ac/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +738 0 ENCFF037YNU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANW/summary/ENCFF037YNU.w5 32 2 mean CHIP:H3K36me3:myotube CHIP ChIP-Histone:H3K36me3/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +739 0 ENCFF441CVF /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANX/summary/ENCFF441CVF.w5 32 2 mean CHIP:H3K4me1:myotube CHIP ChIP-Histone:H3K4me1/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +740 0 ENCFF520IHF /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANY/summary/ENCFF520IHF.w5 32 2 mean CHIP:H3K4me2:myotube CHIP ChIP-Histone:H3K4me2/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +741 0 ENCFF793JPB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ANZ/summary/ENCFF793JPB.w5 32 2 mean CHIP:H3K4me3:myotube CHIP ChIP-Histone:H3K4me3/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +742 0 ENCFF836JPY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOA/summary/ENCFF836JPY.w5 32 2 mean CHIP:CTCF:HeLa-S3 CHIP ChIP-TF:CTCF/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +743 0 ENCFF194XTD /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOC/summary/ENCFF194XTD.w5 32 2 mean CHIP:H3K27ac:HeLa-S3 CHIP ChIP-Histone:H3K27ac/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +744 0 ENCFF752UST /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOE/summary/ENCFF752UST.w5 32 2 mean CHIP:H3K4me2:HeLa-S3 CHIP ChIP-Histone:H3K4me2/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +745 0 ENCFF489CIY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOF/summary/ENCFF489CIY.w5 32 2 mean CHIP:H3K4me3:HeLa-S3 CHIP ChIP-Histone:H3K4me3/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +746 0 ENCFF303MHF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOG/summary/ENCFF303MHF.w5 32 2 mean CHIP:H3K79me2:HeLa-S3 CHIP ChIP-Histone:H3K79me2/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +747 0 ENCFF431ISH /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOH/summary/ENCFF431ISH.w5 32 2 mean CHIP:H3K9ac:HeLa-S3 CHIP ChIP-Histone:H3K9ac/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +748 0 ENCFF324PJA /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOI/summary/ENCFF324PJA.w5 32 2 mean CHIP:H4K20me1:HeLa-S3 CHIP ChIP-TF:H4K20me1/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +749 0 ENCFF598TWA /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOL/summary/ENCFF598TWA.w5 32 2 mean CHIP:H3K27me3:HepG2 CHIP ChIP-Histone:H3K27me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +750 0 ENCFF565ZIH /home/drk/tillage/datasets/human/chip/encode/ENCSR000AON/summary/ENCFF565ZIH.w5 32 2 mean CHIP:H3K79me2:myotube CHIP ChIP-Histone:H3K79me2/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +751 0 ENCFF033TTE /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOO/summary/ENCFF033TTE.w5 32 2 mean CHIP:CTCF:astrocyte CHIP ChIP-TF:CTCF/astrocyte ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +752 0 ENCFF058GEM /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOQ/summary/ENCFF058GEM.w5 32 2 mean CHIP:H3K27ac:astrocyte CHIP ChIP-Histone:H3K27ac/astrocyte ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +753 0 ENCFF184NZS /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOU/summary/ENCFF184NZS.w5 32 2 mean CHIP:H3K4me3:astrocyte CHIP ChIP-Histone:H3K4me3/astrocyte ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +754 0 ENCFF601YET /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOV/summary/ENCFF601YET.w5 32 2 mean CHIP:H2AFZ:GM12878 CHIP ChIP-TF:H2AFZ/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +755 0 ENCFF803DJF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOW/summary/ENCFF803DJF.w5 32 2 mean CHIP:H3K79me2:GM12878 CHIP ChIP-Histone:H3K79me2/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +756 0 ENCFF883NVE /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOY/summary/ENCFF883NVE.w5 32 2 mean CHIP:H3K9ac:myotube CHIP ChIP-Histone:H3K9ac/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +757 0 ENCFF937FXS /home/drk/tillage/datasets/human/chip/encode/ENCSR000AOZ/summary/ENCFF937FXS.w5 32 2 mean CHIP:H4K20me1:myotube CHIP ChIP-TF:H4K20me1/myotube ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +758 0 ENCFF128DVX /home/drk/tillage/datasets/human/chip/encode/ENCSR000APA/summary/ENCFF128DVX.w5 32 2 mean CHIP:H2AFZ:skeletal muscle myoblast male adult (22 years) CHIP ChIP-TF:H2AFZ/skeletal muscle myoblast male adult (22 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +759 0 ENCFF614HNF /home/drk/tillage/datasets/human/chip/encode/ENCSR000APB/summary/ENCFF614HNF.w5 32 2 mean CHIP:H3K27me3:HeLa-S3 CHIP ChIP-Histone:H3K27me3/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +760 0 ENCFF494WCA /home/drk/tillage/datasets/human/chip/encode/ENCSR000APC/summary/ENCFF494WCA.w5 32 2 mean CHIP:H2AFZ:K562 CHIP ChIP-TF:H2AFZ/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +761 0 ENCFF901YVS /home/drk/tillage/datasets/human/chip/encode/ENCSR000APD/summary/ENCFF901YVS.w5 32 2 mean CHIP:H3K79me2:K562 CHIP ChIP-Histone:H3K79me2/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +762 0 ENCFF812HRW /home/drk/tillage/datasets/human/chip/encode/ENCSR000APE/summary/ENCFF812HRW.w5 32 2 mean CHIP:H3K9me3:K562 CHIP ChIP-Histone:H3K9me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +763 0 ENCFF247XSJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000APG/summary/ENCFF247XSJ.w5 32 2 mean CHIP:H2AFZ:osteoblast CHIP ChIP-TF:H2AFZ/osteoblast ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +764 0 ENCFF376MGT /home/drk/tillage/datasets/human/chip/encode/ENCSR000APH/summary/ENCFF376MGT.w5 32 2 mean CHIP:H3K27ac:osteoblast CHIP ChIP-Histone:H3K27ac/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +765 0 ENCFF726KMK /home/drk/tillage/datasets/human/chip/encode/ENCSR000API/summary/ENCFF726KMK.w5 32 2 mean CHIP:H3K36me3:osteoblast CHIP ChIP-Histone:H3K36me3/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +766 0 ENCFF858RDM /home/drk/tillage/datasets/human/chip/encode/ENCSR000APJ/summary/ENCFF858RDM.w5 32 2 mean CHIP:H3K4me1:osteoblast CHIP ChIP-Histone:H3K4me1/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +767 0 ENCFF559URT /home/drk/tillage/datasets/human/chip/encode/ENCSR000APK/summary/ENCFF559URT.w5 32 2 mean CHIP:H3K4me2:osteoblast CHIP ChIP-Histone:H3K4me2/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +768 0 ENCFF039BLU /home/drk/tillage/datasets/human/chip/encode/ENCSR000APL/summary/ENCFF039BLU.w5 32 2 mean CHIP:H3K9me3:osteoblast CHIP ChIP-Histone:H3K9me3/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +769 0 ENCFF146YJY /home/drk/tillage/datasets/human/chip/encode/ENCSR000APM/summary/ENCFF146YJY.w5 32 2 mean CHIP:CTCF:fibroblast of dermis CHIP ChIP-TF:CTCF/fibroblast of dermis ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +770 0 ENCFF969ORH /home/drk/tillage/datasets/human/chip/encode/ENCSR000APN/summary/ENCFF969ORH.w5 32 2 mean CHIP:H3K27ac:fibroblast of dermis CHIP ChIP-Histone:H3K27ac/fibroblast of dermis ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +771 0 ENCFF684QGK /home/drk/tillage/datasets/human/chip/encode/ENCSR000APR/summary/ENCFF684QGK.w5 32 2 mean CHIP:H3K4me3:fibroblast of dermis NONE and female adult CHIP ChIP-Histone:H3K4me3/fibroblast of dermis NONE and female adult ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +772 0 ENCFF058GCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000APV/summary/ENCFF058GCZ.w5 32 2 mean CHIP:H3K4me1:HepG2 CHIP ChIP-Histone:H3K4me1/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +773 0 ENCFF430ZMK /home/drk/tillage/datasets/human/chip/encode/ENCSR000APW/summary/ENCFF430ZMK.w5 32 2 mean CHIP:H3K4me1:HeLa-S3 CHIP ChIP-Histone:H3K4me1/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +774 0 ENCFF253NQI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQA/summary/ENCFF253NQI.w5 32 2 mean CHIP:KDM5B:K562 CHIP ChIP-TF:KDM5B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +775 0 ENCFF076ZMU /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQC/summary/ENCFF076ZMU.w5 32 2 mean CHIP:RBBP5:H1-hESC CHIP ChIP-TF:RBBP5/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +776 0 ENCFF730PEC /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQF/summary/ENCFF730PEC.w5 32 2 mean CHIP:HDAC1:K562 CHIP ChIP-TF:HDAC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +777 0 ENCFF337NZT /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQG/summary/ENCFF337NZT.w5 32 2 mean CHIP:HDAC2:K562 CHIP ChIP-TF:HDAC2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +778 0 ENCFF414RIR /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQH/summary/ENCFF414RIR.w5 32 2 mean CHIP:PHF8:K562 CHIP ChIP-TF:PHF8/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +779 0 ENCFF614LBP /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQI/summary/ENCFF614LBP.w5 32 2 mean CHIP:RBBP5:K562 CHIP ChIP-TF:RBBP5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +780 0 ENCFF899OJV /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQJ/summary/ENCFF899OJV.w5 32 2 mean CHIP:SAP30:K562 CHIP ChIP-TF:SAP30/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +781 0 ENCFF576FUZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQK/summary/ENCFF576FUZ.w5 32 2 mean CHIP:CHD1:H1-hESC CHIP ChIP-TF:CHD1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +782 0 ENCFF902NIY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQM/summary/ENCFF902NIY.w5 32 2 mean CHIP:H3K9me3:myotube CHIP ChIP-Histone:H3K9me3/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +783 0 ENCFF642VOB /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQN/summary/ENCFF642VOB.w5 32 2 mean CHIP:H2AFZ:HeLa-S3 CHIP ChIP-TF:H2AFZ/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +784 0 ENCFF891XLY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQO/summary/ENCFF891XLY.w5 32 2 mean CHIP:H3K9me3:HeLa-S3 CHIP ChIP-Histone:H3K9me3/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +785 0 ENCFF525VQI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQS/summary/ENCFF525VQI.w5 32 2 mean CHIP:H3K27me3:osteoblast CHIP ChIP-Histone:H3K27me3/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +786 0 ENCFF567GDX /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQT/summary/ENCFF567GDX.w5 32 2 mean CHIP:H4K20me1:osteoblast CHIP ChIP-TF:H4K20me1/osteoblast ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +787 0 ENCFF895JGU /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQV/summary/ENCFF895JGU.w5 32 2 mean CHIP:H2AFZ:DND-41 CHIP ChIP-TF:H2AFZ/DND-41 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +788 0 ENCFF454MCD /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQW/summary/ENCFF454MCD.w5 32 2 mean CHIP:H3K27ac:DND-41 CHIP ChIP-Histone:H3K27ac/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +789 0 ENCFF147LEK /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQX/summary/ENCFF147LEK.w5 32 2 mean CHIP:H3K36me3:DND-41 CHIP ChIP-Histone:H3K36me3/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +790 0 ENCFF549GYA /home/drk/tillage/datasets/human/chip/encode/ENCSR000AQY/summary/ENCFF549GYA.w5 32 2 mean CHIP:H3K4me1:DND-41 CHIP ChIP-Histone:H3K4me1/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +791 0 ENCFF791ZHJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARA/summary/ENCFF791ZHJ.w5 32 2 mean CHIP:H3K4me3:DND-41 CHIP ChIP-Histone:H3K4me3/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +792 0 ENCFF146IXR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARB/summary/ENCFF146IXR.w5 32 2 mean CHIP:H3K79me2:DND-41 CHIP ChIP-Histone:H3K79me2/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +793 0 ENCFF347EGU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARC/summary/ENCFF347EGU.w5 32 2 mean CHIP:H4K20me1:DND-41 CHIP ChIP-TF:H4K20me1/DND-41 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +794 0 ENCFF775CVC /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARD/summary/ENCFF775CVC.w5 32 2 mean CHIP:EZH2:GM12878 CHIP ChIP-TF:EZH2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +795 0 ENCFF062KTR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARE/summary/ENCFF062KTR.w5 32 2 mean CHIP:EZH2:mammary epithelial cell female adult (50 years) CHIP ChIP-TF:EZH2/mammary epithelial cell female adult (50 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +796 0 ENCFF789FNH /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARF/summary/ENCFF789FNH.w5 32 2 mean CHIP:H2AFZ:mammary epithelial cell female adult (50 years) CHIP ChIP-TF:H2AFZ/mammary epithelial cell female adult (50 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +797 0 ENCFF921LCI /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARG/summary/ENCFF921LCI.w5 32 2 mean CHIP:H3K9me3:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K9me3/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +798 0 ENCFF211JBX /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARH/summary/ENCFF211JBX.w5 32 2 mean CHIP:EZH2:skeletal muscle myoblast male adult (22 years) CHIP ChIP-TF:EZH2/skeletal muscle myoblast male adult (22 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +799 0 ENCFF321AHD /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARI/summary/ENCFF321AHD.w5 32 2 mean CHIP:EZH2:HepG2 CHIP ChIP-TF:EZH2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +800 0 ENCFF344HLB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARL/summary/ENCFF344HLB.w5 32 2 mean CHIP:H2AFZ:keratinocyte female CHIP ChIP-TF:H2AFZ/keratinocyte female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +801 0 ENCFF690YPY /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARM/summary/ENCFF690YPY.w5 32 2 mean CHIP:H3K79me2:keratinocyte female CHIP ChIP-Histone:H3K79me2/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +802 0 ENCFF251CYW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARN/summary/ENCFF251CYW.w5 32 2 mean CHIP:H3K9me3:keratinocyte female CHIP ChIP-Histone:H3K9me3/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +803 0 ENCFF324EOP /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARO/summary/ENCFF324EOP.w5 32 2 mean CHIP:EZH2:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-TF:EZH2/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +804 0 ENCFF094EGN /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARP/summary/ENCFF094EGN.w5 32 2 mean CHIP:H2AFZ:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-TF:H2AFZ/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +805 0 ENCFF143LCY /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARQ/summary/ENCFF143LCY.w5 32 2 mean CHIP:H3K9me3:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K9me3/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +806 0 ENCFF656QVF /home/drk/tillage/datasets/human/chip/encode/ENCSR000ART/summary/ENCFF656QVF.w5 32 2 mean CHIP:H3K9ac:astrocyte CHIP ChIP-Histone:H3K9ac/astrocyte ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +807 0 ENCFF736AZD /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARU/summary/ENCFF736AZD.w5 32 2 mean CHIP:H4K20me1:astrocyte CHIP ChIP-TF:H4K20me1/astrocyte ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +808 0 ENCFF920EUW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARY/summary/ENCFF920EUW.w5 32 2 mean CHIP:H3K9ac:DND-41 CHIP ChIP-Histone:H3K9ac/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +809 0 ENCFF091QTN /home/drk/tillage/datasets/human/chip/encode/ENCSR000ARZ/summary/ENCFF091QTN.w5 32 2 mean CHIP:H3K9me3:DND-41 CHIP ChIP-Histone:H3K9me3/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +810 0 ENCFF659QTS /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASB/summary/ENCFF659QTS.w5 32 2 mean CHIP:H3K79me2:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K79me2/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +811 0 ENCFF168RCB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASC/summary/ENCFF168RCB.w5 32 2 mean CHIP:H2AFZ:endothelial cell of umbilical vein male newborn CHIP ChIP-TF:H2AFZ/endothelial cell of umbilical vein male newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +812 0 ENCFF492JYB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASD/summary/ENCFF492JYB.w5 32 2 mean CHIP:H3K79me2:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K79me2/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +813 0 ENCFF556JXZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASE/summary/ENCFF556JXZ.w5 32 2 mean CHIP:EZH2:fibroblast of dermis CHIP ChIP-TF:EZH2/fibroblast of dermis ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +814 0 ENCFF528KDW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASF/summary/ENCFF528KDW.w5 32 2 mean CHIP:H3K79me2:fibroblast of lung female child (11 year) and male adult (45 years) CHIP ChIP-Histone:H3K79me2/fibroblast of lung female child (11 year) and male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +815 0 ENCFF637OOB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASG/summary/ENCFF637OOB.w5 32 2 mean CHIP:H3K79me2:osteoblast CHIP ChIP-Histone:H3K79me2/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +816 0 ENCFF838MAH /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASH/summary/ENCFF838MAH.w5 32 2 mean CHIP:H3K4me3:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K4me3/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +817 0 ENCFF526GZE /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASJ/summary/ENCFF526GZE.w5 32 2 mean CHIP:H3K27ac:CD14-positive monocyte female CHIP ChIP-Histone:H3K27ac/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +818 0 ENCFF493ZLU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASK/summary/ENCFF493ZLU.w5 32 2 mean CHIP:H3K27me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K27me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +819 0 ENCFF981RED /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASL/summary/ENCFF981RED.w5 32 2 mean CHIP:H3K36me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K36me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +820 0 ENCFF579IKK /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASM/summary/ENCFF579IKK.w5 32 2 mean CHIP:H3K4me1:CD14-positive monocyte female CHIP ChIP-Histone:H3K4me1/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +821 0 ENCFF032QOM /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASN/summary/ENCFF032QOM.w5 32 2 mean CHIP:H3K4me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K4me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +822 0 ENCFF142KIH /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASO/summary/ENCFF142KIH.w5 32 2 mean CHIP:H3K79me2:CD14-positive monocyte female CHIP ChIP-Histone:H3K79me2/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +823 0 ENCFF229JAM /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASP/summary/ENCFF229JAM.w5 32 2 mean CHIP:H3K9me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K9me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +824 0 ENCFF772DVW /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASQ/summary/ENCFF772DVW.w5 32 2 mean CHIP:H4K20me1:CD14-positive monocyte female CHIP ChIP-TF:H4K20me1/CD14-positive monocyte female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +825 0 ENCFF645TWL /home/drk/tillage/datasets/human/chip/encode/ENCSR000AST/summary/ENCFF645TWL.w5 32 2 mean CHIP:H3K4me3:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-Histone:H3K4me3/A549 treated with 100 nM dexamethasone for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +826 0 ENCFF808VAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASV/summary/ENCFF808VAQ.w5 32 2 mean CHIP:H3K9ac:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K9ac/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +827 0 ENCFF769OSR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ASX/summary/ENCFF769OSR.w5 32 2 mean CHIP:H3K27me3:DND-41 CHIP ChIP-Histone:H3K27me3/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +828 0 ENCFF923UUB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATB/summary/ENCFF923UUB.w5 32 2 mean CHIP:H3K9me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K9me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +829 0 ENCFF967TSR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATC/summary/ENCFF967TSR.w5 32 2 mean CHIP:EZH2:HeLa-S3 CHIP ChIP-TF:EZH2/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +830 0 ENCFF485BCI /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATD/summary/ENCFF485BCI.w5 32 2 mean CHIP:H3K9me3:HepG2 CHIP ChIP-Histone:H3K9me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +831 0 ENCFF080TRB /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATF/summary/ENCFF080TRB.w5 32 2 mean CHIP:H3K9ac:CD14-positive monocyte female CHIP ChIP-Histone:H3K9ac/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +832 0 ENCFF644KJR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATH/summary/ENCFF644KJR.w5 32 2 mean CHIP:H3K4me3:osteoblast CHIP ChIP-Histone:H3K4me3/osteoblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +833 0 ENCFF815PSP /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATI/summary/ENCFF815PSP.w5 32 2 mean CHIP:H3K27me3:myotube CHIP ChIP-Histone:H3K27me3/myotube ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +834 0 ENCFF896GKF /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATJ/summary/ENCFF896GKF.w5 32 2 mean CHIP:HDAC6:K562 CHIP ChIP-TF:HDAC6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +835 0 ENCFF935JRI /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATK/summary/ENCFF935JRI.w5 32 2 mean CHIP:PHF8:H1-hESC CHIP ChIP-TF:PHF8/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +836 0 ENCFF974NBA /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATN/summary/ENCFF974NBA.w5 32 2 mean CHIP:CTCF:CD14-positive monocyte female CHIP ChIP-TF:CTCF/CD14-positive monocyte female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +837 0 ENCFF375NRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATP/summary/ENCFF375NRQ.w5 32 2 mean CHIP:H3K79me2:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K79me2/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +838 0 ENCFF243FNC /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATQ/summary/ENCFF243FNC.w5 32 2 mean CHIP:HDAC6:H1-hESC CHIP ChIP-TF:HDAC6/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +839 0 ENCFF779YFX /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATR/summary/ENCFF779YFX.w5 32 2 mean CHIP:SAP30:H1-hESC CHIP ChIP-TF:SAP30/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +840 0 ENCFF008SLD /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATS/summary/ENCFF008SLD.w5 32 2 mean CHIP:SUZ12:H1-hESC CHIP ChIP-TF:SUZ12/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +841 0 ENCFF151HDM /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATT/summary/ENCFF151HDM.w5 32 2 mean CHIP:CREBBP:K562 CHIP ChIP-TF:CREBBP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +842 0 ENCFF952ESR /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATV/summary/ENCFF952ESR.w5 32 2 mean CHIP:CBX3:K562 CHIP ChIP-TF:CBX3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +843 0 ENCFF624BHU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ATZ/summary/ENCFF624BHU.w5 32 2 mean CHIP:KAT2B:K562 CHIP ChIP-TF:KAT2B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +844 0 ENCFF563TWG /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUB/summary/ENCFF563TWG.w5 32 2 mean CHIP:SIRT6:K562 CHIP ChIP-TF:SIRT6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +845 0 ENCFF208PNQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUC/summary/ENCFF208PNQ.w5 32 2 mean CHIP:SUZ12:K562 CHIP ChIP-TF:SUZ12/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +846 0 ENCFF744LTW /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUE/summary/ENCFF744LTW.w5 32 2 mean CHIP:CTCF:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-TF:CTCF/A549 treated with 100 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +847 0 ENCFF152JNI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUH/summary/ENCFF152JNI.w5 32 2 mean CHIP:H2AFZ:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:H2AFZ/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +848 0 ENCFF681WFO /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUI/summary/ENCFF681WFO.w5 32 2 mean CHIP:H3K27ac:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K27ac/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +849 0 ENCFF069CME /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUK/summary/ENCFF069CME.w5 32 2 mean CHIP:H3K27me3:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K27me3/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +850 0 ENCFF151OKU /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUM/summary/ENCFF151OKU.w5 32 2 mean CHIP:H3K4me1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K4me1/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +851 0 ENCFF916SWF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUN/summary/ENCFF916SWF.w5 32 2 mean CHIP:H3K9me3:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K9me3/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +852 0 ENCFF417UUX /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUO/summary/ENCFF417UUX.w5 32 2 mean CHIP:H4K20me1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:H4K20me1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +853 0 ENCFF696PMM /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUP/summary/ENCFF696PMM.w5 32 2 mean CHIP:H3K27ac:B cell female adult (27 years) CHIP ChIP-Histone:H3K27ac/B cell female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +854 0 ENCFF489CQP /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUQ/summary/ENCFF489CQP.w5 32 2 mean CHIP:EP300:H1-hESC CHIP ChIP-TF:EP300/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +855 0 ENCFF822ZVD /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUS/summary/ENCFF822ZVD.w5 32 2 mean CHIP:SIRT6:H1-hESC CHIP ChIP-TF:SIRT6/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +856 0 ENCFF100AEJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUT/summary/ENCFF100AEJ.w5 32 2 mean CHIP:SETDB1:K562 CHIP ChIP-TF:SETDB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +857 0 ENCFF031CXE /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUV/summary/ENCFF031CXE.w5 32 2 mean CHIP:CTCF:B cell female adult (27 years) and female adult (43 years) CHIP ChIP-TF:CTCF/B cell female adult (27 years) and female adult (43 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +858 0 ENCFF883JHY /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUX/summary/ENCFF883JHY.w5 32 2 mean CHIP:H2AFZ:B cell female adult (27 years) and female adult (43 years) CHIP ChIP-TF:H2AFZ/B cell female adult (27 years) and female adult (43 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +859 0 ENCFF945VIU /home/drk/tillage/datasets/human/chip/encode/ENCSR000AUY/summary/ENCFF945VIU.w5 32 2 mean CHIP:H3K4me2:B cell female adult (27 years) and female adult (43 years) CHIP ChIP-Histone:H3K4me2/B cell female adult (27 years) and female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +860 0 ENCFF575OWE /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVA/summary/ENCFF575OWE.w5 32 2 mean CHIP:CHD7:H1-hESC CHIP ChIP-TF:CHD7/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +861 0 ENCFF948IYF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVB/summary/ENCFF948IYF.w5 32 2 mean CHIP:HDAC2:H1-hESC CHIP ChIP-TF:HDAC2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +862 0 ENCFF916KLB /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVC/summary/ENCFF916KLB.w5 32 2 mean CHIP:KDM4A:H1-hESC CHIP ChIP-TF:KDM4A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +863 0 ENCFF813CWF /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVE/summary/ENCFF813CWF.w5 32 2 mean CHIP:WHSC1:K562 CHIP ChIP-TF:WHSC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +864 0 ENCFF640PJT /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVF/summary/ENCFF640PJT.w5 32 2 mean CHIP:H3K27ac:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-Histone:H3K27ac/A549 treated with 100 nM dexamethasone for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +865 0 ENCFF435QBI /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVI/summary/ENCFF435QBI.w5 32 2 mean CHIP:H3K4me2:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-Histone:H3K4me2/A549 treated with 0.02% ethanol for 1 hour ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +866 0 ENCFF572IZL /home/drk/tillage/datasets/human/chip/encode/ENCSR000AVJ/summary/ENCFF572IZL.w5 32 2 mean CHIP:H4K20me1:B cell female adult (27 years) CHIP ChIP-TF:H4K20me1/B cell female adult (27 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +867 0 ENCFF240XIO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGB/summary/ENCFF240XIO.w5 32 2 mean CHIP:FOXP2:SK-N-MC CHIP ChIP-TF:FOXP2/SK-N-MC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +868 0 ENCFF600UCV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGD/summary/ENCFF600UCV.w5 32 2 mean CHIP:POLR2A:GM12878 CHIP ChIP-TF:POLR2A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +869 0 ENCFF839SCO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGE/summary/ENCFF839SCO.w5 32 2 mean CHIP:SRF:GM12878 CHIP ChIP-TF:SRF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +870 0 ENCFF557SNT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGF/summary/ENCFF557SNT.w5 32 2 mean CHIP:REST:GM12878 CHIP ChIP-TF:REST/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +871 0 ENCFF344JQP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGI/summary/ENCFF344JQP.w5 32 2 mean CHIP:USF1:GM12878 CHIP ChIP-TF:USF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +872 0 ENCFF009FVW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGK/summary/ENCFF009FVW.w5 32 2 mean CHIP:JUND:HepG2 CHIP ChIP-TF:JUND/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +873 0 ENCFF746QKY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGL/summary/ENCFF746QKY.w5 32 2 mean CHIP:SIN3A:HepG2 CHIP ChIP-TF:SIN3A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +874 0 ENCFF924RJY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGM/summary/ENCFF924RJY.w5 32 2 mean CHIP:USF1:HepG2 CHIP ChIP-TF:USF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +875 0 ENCFF144IVU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGO/summary/ENCFF144IVU.w5 32 2 mean CHIP:POLR2A:HeLa-S3 CHIP ChIP-TF:POLR2A/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +876 0 ENCFF535BIH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGR/summary/ENCFF535BIH.w5 32 2 mean CHIP:PBX3:GM12878 CHIP ChIP-TF:PBX3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +877 0 ENCFF105MPH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGS/summary/ENCFF105MPH.w5 32 2 mean CHIP:TAF1:GM12878 CHIP ChIP-TF:TAF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +878 0 ENCFF424MMT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGT/summary/ENCFF424MMT.w5 32 2 mean CHIP:BATF:GM12878 CHIP ChIP-TF:BATF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +879 0 ENCFF107LDM /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGU/summary/ENCFF107LDM.w5 32 2 mean CHIP:EBF1:GM12878 CHIP ChIP-TF:EBF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +880 0 ENCFF185INW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGY/summary/ENCFF185INW.w5 32 2 mean CHIP:IRF4:GM12878 CHIP ChIP-TF:IRF4/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +881 0 ENCFF481DWO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BGZ/summary/ENCFF481DWO.w5 32 2 mean CHIP:TCF12:GM12878 CHIP ChIP-TF:TCF12/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +882 0 ENCFF898IWR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHA/summary/ENCFF898IWR.w5 32 2 mean CHIP:BCL11A:GM12878 CHIP ChIP-TF:BCL11A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +883 0 ENCFF399SZY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHB/summary/ENCFF399SZY.w5 32 2 mean CHIP:EP300:GM12878 CHIP ChIP-TF:EP300/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +884 0 ENCFF806TFL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHC/summary/ENCFF806TFL.w5 32 2 mean CHIP:ZBTB33:GM12878 CHIP ChIP-TF:ZBTB33/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +885 0 ENCFF702MTT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHD/summary/ENCFF702MTT.w5 32 2 mean CHIP:PAX5:GM12878 CHIP ChIP-TF:PAX5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +886 0 ENCFF834YUX /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHE/summary/ENCFF834YUX.w5 32 2 mean CHIP:NR3C1:A549 treated with 500 pM dexamethasone for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 500 pM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +887 0 ENCFF370ILE /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHF/summary/ENCFF370ILE.w5 32 2 mean CHIP:NR3C1:A549 treated with 50 nM dexamethasone for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 50 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +888 0 ENCFF548YOD /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHG/summary/ENCFF548YOD.w5 32 2 mean CHIP:NR3C1:A549 treated with 5 nM dexamethasone for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 5 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +889 0 ENCFF951FGK /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHH/summary/ENCFF951FGK.w5 32 2 mean CHIP:POLR2A:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:POLR2A/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +890 0 ENCFF688CLH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHI/summary/ENCFF688CLH.w5 32 2 mean CHIP:POLR2A:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-TF:POLR2A/A549 treated with 100 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +891 0 ENCFF851GCH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHJ/summary/ENCFF851GCH.w5 32 2 mean CHIP:PAX5:GM12878 CHIP ChIP-TF:PAX5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +892 0 ENCFF648WCI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHM/summary/ENCFF648WCI.w5 32 2 mean CHIP:REST:H1-hESC CHIP ChIP-TF:REST/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +893 0 ENCFF379IRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHN/summary/ENCFF379IRQ.w5 32 2 mean CHIP:POLR2A:H1-hESC CHIP ChIP-TF:POLR2A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +894 0 ENCFF689QWC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHO/summary/ENCFF689QWC.w5 32 2 mean CHIP:TAF1:H1-hESC CHIP ChIP-TF:TAF1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +895 0 ENCFF858SNG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHP/summary/ENCFF858SNG.w5 32 2 mean CHIP:FOSL2:HepG2 CHIP ChIP-TF:FOSL2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +896 0 ENCFF937PQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHS/summary/ENCFF937PQQ.w5 32 2 mean CHIP:GABPA:HeLa-S3 CHIP ChIP-TF:GABPA/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +897 0 ENCFF147UKA /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHT/summary/ENCFF147UKA.w5 32 2 mean CHIP:TAF1:HeLa-S3 CHIP ChIP-TF:TAF1/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +898 0 ENCFF174EJM /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHU/summary/ENCFF174EJM.w5 32 2 mean CHIP:RXRA:HepG2 CHIP ChIP-TF:RXRA/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +899 0 ENCFF069VVC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BHZ/summary/ENCFF069VVC.w5 32 2 mean CHIP:POLR2A:GM12892 CHIP ChIP-TF:POLR2A/GM12892 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +900 0 ENCFF484MOG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIA/summary/ENCFF484MOG.w5 32 2 mean CHIP:POLR2AphosphoS5:GM12892 CHIP ChIP-TF:POLR2AphosphoS5/GM12892 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +901 0 ENCFF307XCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIB/summary/ENCFF307XCZ.w5 32 2 mean CHIP:TAF1:GM12892 CHIP ChIP-TF:TAF1/GM12892 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +902 0 ENCFF655OPV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIC/summary/ENCFF655OPV.w5 32 2 mean CHIP:POLR2AphosphoS5:H1-hESC CHIP ChIP-TF:POLR2AphosphoS5/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +903 0 ENCFF016XRZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BID/summary/ENCFF016XRZ.w5 32 2 mean CHIP:BHLHE40:HepG2 CHIP ChIP-TF:BHLHE40/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +904 0 ENCFF601JOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIE/summary/ENCFF601JOJ.w5 32 2 mean CHIP:CTCF:HepG2 CHIP ChIP-TF:CTCF/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +905 0 ENCFF647IAI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIF/summary/ENCFF647IAI.w5 32 2 mean CHIP:POLR2AphosphoS5:GM12878 CHIP ChIP-TF:POLR2AphosphoS5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +906 0 ENCFF601RJF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BII/summary/ENCFF601RJF.w5 32 2 mean CHIP:POU2F2:GM12891 CHIP ChIP-TF:POU2F2/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +907 0 ENCFF998DST /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIJ/summary/ENCFF998DST.w5 32 2 mean CHIP:SPI1:GM12891 CHIP ChIP-TF:SPI1/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +908 0 ENCFF724GDC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIK/summary/ENCFF724GDC.w5 32 2 mean CHIP:POLR2A:GM12891 CHIP ChIP-TF:POLR2A/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +909 0 ENCFF998MBP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIL/summary/ENCFF998MBP.w5 32 2 mean CHIP:POLR2AphosphoS5:GM12891 CHIP ChIP-TF:POLR2AphosphoS5/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +910 0 ENCFF630ZKZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIM/summary/ENCFF630ZKZ.w5 32 2 mean CHIP:TAF1:GM12891 CHIP ChIP-TF:TAF1/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +911 0 ENCFF132AXT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIO/summary/ENCFF132AXT.w5 32 2 mean CHIP:NR3C1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +912 0 ENCFF203IVF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIP/summary/ENCFF203IVF.w5 32 2 mean CHIP:BCL11A:H1-hESC CHIP ChIP-TF:BCL11A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +913 0 ENCFF665USC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIQ/summary/ENCFF665USC.w5 32 2 mean CHIP:SIX5:H1-hESC CHIP ChIP-TF:SIX5/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +914 0 ENCFF256MVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIR/summary/ENCFF256MVQ.w5 32 2 mean CHIP:SP1:H1-hESC CHIP ChIP-TF:SP1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +915 0 ENCFF571JNW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIS/summary/ENCFF571JNW.w5 32 2 mean CHIP:SIN3A:H1-hESC CHIP ChIP-TF:SIN3A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +916 0 ENCFF715MYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIT/summary/ENCFF715MYQ.w5 32 2 mean CHIP:TCF12:H1-hESC CHIP ChIP-TF:TCF12/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +917 0 ENCFF133IZI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIU/summary/ENCFF133IZI.w5 32 2 mean CHIP:USF1:H1-hESC CHIP ChIP-TF:USF1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +918 0 ENCFF941KEV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIV/summary/ENCFF941KEV.w5 32 2 mean CHIP:SRF:H1-hESC CHIP ChIP-TF:SRF/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +919 0 ENCFF401DOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIW/summary/ENCFF401DOJ.w5 32 2 mean CHIP:GABPA:H1-hESC CHIP ChIP-TF:GABPA/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +920 0 ENCFF169OSJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIY/summary/ENCFF169OSJ.w5 32 2 mean CHIP:ESR1:Ishikawa treated with 10 nM estradiol for 1 hour CHIP ChIP-TF:ESR1/Ishikawa treated with 10 nM estradiol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +921 0 ENCFF185QLG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BIZ/summary/ENCFF185QLG.w5 32 2 mean CHIP:ESR1:Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:ESR1/Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +922 0 ENCFF341OGJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJA/summary/ENCFF341OGJ.w5 32 2 mean CHIP:EGR1:H1-hESC CHIP ChIP-TF:EGR1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +923 0 ENCFF894HFP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJC/summary/ENCFF894HFP.w5 32 2 mean CHIP:NR3C1:Ishikawa treated with 100 nM dexamethasone for 1 hour CHIP ChIP-TF:NR3C1/Ishikawa treated with 100 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +924 0 ENCFF951RXW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJD/summary/ENCFF951RXW.w5 32 2 mean CHIP:RXRA:GM12878 CHIP ChIP-TF:RXRA/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +925 0 ENCFF916XGL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJE/summary/ENCFF916XGL.w5 32 2 mean CHIP:SIX5:GM12878 CHIP ChIP-TF:SIX5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +926 0 ENCFF883ERP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJG/summary/ENCFF883ERP.w5 32 2 mean CHIP:TCF12:HepG2 CHIP ChIP-TF:TCF12/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +927 0 ENCFF723BZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJH/summary/ENCFF723BZQ.w5 32 2 mean CHIP:PAX5:GM12891 CHIP ChIP-TF:PAX5/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +928 0 ENCFF955MCC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJJ/summary/ENCFF955MCC.w5 32 2 mean CHIP:REST:SK-N-SH CHIP ChIP-TF:REST/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +929 0 ENCFF351OIU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJK/summary/ENCFF351OIU.w5 32 2 mean CHIP:GABPA:HepG2 CHIP ChIP-TF:GABPA/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +930 0 ENCFF353IMU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJL/summary/ENCFF353IMU.w5 32 2 mean CHIP:REST:HepG2 CHIP ChIP-TF:REST/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +931 0 ENCFF378NKG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJM/summary/ENCFF378NKG.w5 32 2 mean CHIP:POLR2A:HepG2 CHIP ChIP-TF:POLR2A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +932 0 ENCFF066KEN /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJN/summary/ENCFF066KEN.w5 32 2 mean CHIP:TAF1:HepG2 CHIP ChIP-TF:TAF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +933 0 ENCFF464BAU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJO/summary/ENCFF464BAU.w5 32 2 mean CHIP:REST:Panc1 CHIP ChIP-TF:REST/Panc1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +934 0 ENCFF631ILW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJP/summary/ENCFF631ILW.w5 32 2 mean CHIP:REST:PFSK-1 CHIP ChIP-TF:REST/PFSK-1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +935 0 ENCFF995NTI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJR/summary/ENCFF995NTI.w5 32 2 mean CHIP:NR3C1:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 100 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +936 0 ENCFF468WTB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJS/summary/ENCFF468WTB.w5 32 2 mean CHIP:ESR1:T47D treated with 100 nM genistein for 1 hour CHIP ChIP-TF:ESR1/T47D treated with 100 nM genistein for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +937 0 ENCFF525GZV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJT/summary/ENCFF525GZV.w5 32 2 mean CHIP:NR3C1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:NR3C1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +938 0 ENCFF134SMY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJW/summary/ENCFF134SMY.w5 32 2 mean CHIP:RXRA:H1-hESC CHIP ChIP-TF:RXRA/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +939 0 ENCFF537QIE /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJX/summary/ENCFF537QIE.w5 32 2 mean CHIP:SP1:HepG2 CHIP ChIP-TF:SP1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +940 0 ENCFF870HVW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BJZ/summary/ENCFF870HVW.w5 32 2 mean CHIP:BCLAF1:GM12878 CHIP ChIP-TF:BCLAF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +941 0 ENCFF103EJS /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKA/summary/ENCFF103EJS.w5 32 2 mean CHIP:ETS1:GM12878 CHIP ChIP-TF:ETS1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +942 0 ENCFF373KCT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKB/summary/ENCFF373KCT.w5 32 2 mean CHIP:MEF2A:GM12878 CHIP ChIP-TF:MEF2A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +943 0 ENCFF481EHX /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKC/summary/ENCFF481EHX.w5 32 2 mean CHIP:ATF3:H1-hESC CHIP ChIP-TF:ATF3/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +944 0 ENCFF406PYH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKD/summary/ENCFF406PYH.w5 32 2 mean CHIP:YY1:H1-hESC CHIP ChIP-TF:YY1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +945 0 ENCFF461IPU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKE/summary/ENCFF461IPU.w5 32 2 mean CHIP:ATF3:HepG2 CHIP ChIP-TF:ATF3/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +946 0 ENCFF240CAY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKH/summary/ENCFF240CAY.w5 32 2 mean CHIP:BCLAF1:K562 CHIP ChIP-TF:BCLAF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +947 0 ENCFF709BXS /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKI/summary/ENCFF709BXS.w5 32 2 mean CHIP:POLR2A:Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:POLR2A/Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +948 0 ENCFF294KFW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKJ/summary/ENCFF294KFW.w5 32 2 mean CHIP:YY1:GM12891 CHIP ChIP-TF:YY1/GM12891 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +949 0 ENCFF491ZOF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKK/summary/ENCFF491ZOF.w5 32 2 mean CHIP:EP300:H1-hESC CHIP ChIP-TF:EP300/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +950 0 ENCFF128BVN /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKP/summary/ENCFF128BVN.w5 32 2 mean CHIP:JUND:H1-hESC CHIP ChIP-TF:JUND/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +951 0 ENCFF291YLM /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKQ/summary/ENCFF291YLM.w5 32 2 mean CHIP:ETS1:K562 CHIP ChIP-TF:ETS1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +952 0 ENCFF811SWR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKR/summary/ENCFF811SWR.w5 32 2 mean CHIP:POLR2AphosphoS5:K562 CHIP ChIP-TF:POLR2AphosphoS5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +953 0 ENCFF079MWL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BKY/summary/ENCFF079MWL.w5 32 2 mean CHIP:FOXA1:T47D treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:FOXA1/T47D treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +954 0 ENCFF577EAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLB/summary/ENCFF577EAZ.w5 32 2 mean CHIP:NR3C1:Ishikawa treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:NR3C1/Ishikawa treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +955 0 ENCFF791XXJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLD/summary/ENCFF791XXJ.w5 32 2 mean CHIP:RAD21:H1-hESC CHIP ChIP-TF:RAD21/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +956 0 ENCFF529CBU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLE/summary/ENCFF529CBU.w5 32 2 mean CHIP:FOXA1:HepG2 CHIP ChIP-TF:FOXA1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +957 0 ENCFF080FZD /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLF/summary/ENCFF080FZD.w5 32 2 mean CHIP:HNF4A:HepG2 CHIP ChIP-TF:HNF4A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +958 0 ENCFF631VAT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLI/summary/ENCFF631VAT.w5 32 2 mean CHIP:E2F6:K562 CHIP ChIP-TF:E2F6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +959 0 ENCFF023DPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLL/summary/ENCFF023DPZ.w5 32 2 mean CHIP:ESR1:T47D treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:ESR1/T47D treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +960 0 ENCFF908PGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLO/summary/ENCFF908PGZ.w5 32 2 mean CHIP:GABPA:K562 CHIP ChIP-TF:GABPA/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +961 0 ENCFF070ERF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLP/summary/ENCFF070ERF.w5 32 2 mean CHIP:MAX:K562 CHIP ChIP-TF:MAX/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +962 0 ENCFF876MPC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLR/summary/ENCFF876MPC.w5 32 2 mean CHIP:SIN3A:K562 CHIP ChIP-TF:SIN3A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +963 0 ENCFF871PVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLS/summary/ENCFF871PVZ.w5 32 2 mean CHIP:RAD21:HepG2 CHIP ChIP-TF:RAD21/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +964 0 ENCFF895YUC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLT/summary/ENCFF895YUC.w5 32 2 mean CHIP:YY1:GM12892 CHIP ChIP-TF:YY1/GM12892 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +965 0 ENCFF160JKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLU/summary/ENCFF160JKQ.w5 32 2 mean CHIP:TAF7:H1-hESC CHIP ChIP-TF:TAF7/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +966 0 ENCFF772VBV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLW/summary/ENCFF772VBV.w5 32 2 mean CHIP:EP300:HepG2 CHIP ChIP-TF:EP300/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +967 0 ENCFF222GQG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLX/summary/ENCFF222GQG.w5 32 2 mean CHIP:CTCF:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-TF:CTCF/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +968 0 ENCFF087JUG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLY/summary/ENCFF087JUG.w5 32 2 mean CHIP:RAD21:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-TF:RAD21/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +969 0 ENCFF183SML /home/drk/tillage/datasets/human/chip/encode/ENCSR000BLZ/summary/ENCFF183SML.w5 32 2 mean CHIP:YY1:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-TF:YY1/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +970 0 ENCFF792BDE /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMC/summary/ENCFF792BDE.w5 32 2 mean CHIP:HDAC2:HepG2 CHIP ChIP-TF:HDAC2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +971 0 ENCFF961EMF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BME/summary/ENCFF961EMF.w5 32 2 mean CHIP:ZBTB7A:K562 CHIP ChIP-TF:ZBTB7A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +972 0 ENCFF632WIC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMF/summary/ENCFF632WIC.w5 32 2 mean CHIP:USF1:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-TF:USF1/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +973 0 ENCFF023AFF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMH/summary/ENCFF023AFF.w5 32 2 mean CHIP:YY1:K562 CHIP ChIP-TF:YY1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +974 0 ENCFF821PRO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMI/summary/ENCFF821PRO.w5 32 2 mean CHIP:SRF:GM12878 CHIP ChIP-TF:SRF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +975 0 ENCFF735TIA /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMJ/summary/ENCFF735TIA.w5 32 2 mean CHIP:BCL11A:H1-hESC CHIP ChIP-TF:BCL11A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +976 0 ENCFF794LVU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BML/summary/ENCFF794LVU.w5 32 2 mean CHIP:POLR2AphosphoS5:HCT116 CHIP ChIP-TF:POLR2AphosphoS5/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +977 0 ENCFF089QUB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMN/summary/ENCFF089QUB.w5 32 2 mean CHIP:REST:HeLa-S3 CHIP ChIP-TF:REST/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +978 0 ENCFF163CFH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMO/summary/ENCFF163CFH.w5 32 2 mean CHIP:FOXA1:HepG2 CHIP ChIP-TF:FOXA1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +979 0 ENCFF547IOW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMR/summary/ENCFF547IOW.w5 32 2 mean CHIP:POLR2A:K562 CHIP ChIP-TF:POLR2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +980 0 ENCFF305LHR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMT/summary/ENCFF305LHR.w5 32 2 mean CHIP:NANOG:H1-hESC CHIP ChIP-TF:NANOG/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +981 0 ENCFF331ETG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMV/summary/ENCFF331ETG.w5 32 2 mean CHIP:FOSL1:K562 CHIP ChIP-TF:FOSL1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +982 0 ENCFF384IZU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMW/summary/ENCFF384IZU.w5 32 2 mean CHIP:REST:K562 CHIP ChIP-TF:REST/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +983 0 ENCFF313EMB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMX/summary/ENCFF313EMB.w5 32 2 mean CHIP:GATA3:T47D treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:GATA3/T47D treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +984 0 ENCFF916YVI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMY/summary/ENCFF916YVI.w5 32 2 mean CHIP:RAD21:GM12878 CHIP ChIP-TF:RAD21/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +985 0 ENCFF979PVN /home/drk/tillage/datasets/human/chip/encode/ENCSR000BMZ/summary/ENCFF979PVN.w5 32 2 mean CHIP:ELF1:HepG2 CHIP ChIP-TF:ELF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +986 0 ENCFF336BUE /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNA/summary/ENCFF336BUE.w5 32 2 mean CHIP:ZBTB33:HepG2 CHIP ChIP-TF:ZBTB33/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +987 0 ENCFF422BSY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNE/summary/ENCFF422BSY.w5 32 2 mean CHIP:EGR1:K562 CHIP ChIP-TF:EGR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +988 0 ENCFF872HOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNG/summary/ENCFF872HOJ.w5 32 2 mean CHIP:MEF2C:GM12878 CHIP ChIP-TF:MEF2C/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +989 0 ENCFF473IZV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNH/summary/ENCFF473IZV.w5 32 2 mean CHIP:CTCF:H1-hESC CHIP ChIP-TF:CTCF/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +990 0 ENCFF626IVY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNI/summary/ENCFF626IVY.w5 32 2 mean CHIP:FOXA2:HepG2 CHIP ChIP-TF:FOXA2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +991 0 ENCFF870IIO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNJ/summary/ENCFF870IIO.w5 32 2 mean CHIP:HNF4G:HepG2 CHIP ChIP-TF:HNF4G/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +992 0 ENCFF665COJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNM/summary/ENCFF665COJ.w5 32 2 mean CHIP:TAF7:K562 CHIP ChIP-TF:TAF7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +993 0 ENCFF862ATB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNN/summary/ENCFF862ATB.w5 32 2 mean CHIP:THAP1:K562 CHIP ChIP-TF:THAP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +994 0 ENCFF683NGY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNP/summary/ENCFF683NGY.w5 32 2 mean CHIP:YY1:GM12878 CHIP ChIP-TF:YY1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +995 0 ENCFF641QFU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNQ/summary/ENCFF641QFU.w5 32 2 mean CHIP:BCL3:GM12878 CHIP ChIP-TF:BCL3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +996 0 ENCFF640QBB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNR/summary/ENCFF640QBB.w5 32 2 mean CHIP:HDAC2:H1-hESC CHIP ChIP-TF:HDAC2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +997 0 ENCFF498IQF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNS/summary/ENCFF498IQF.w5 32 2 mean CHIP:FOSL1:H1-hESC CHIP ChIP-TF:FOSL1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +998 0 ENCFF677ERZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNT/summary/ENCFF677ERZ.w5 32 2 mean CHIP:YY1:HepG2 CHIP ChIP-TF:YY1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +999 0 ENCFF619WVY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNU/summary/ENCFF619WVY.w5 32 2 mean CHIP:ATF3:K562 CHIP ChIP-TF:ATF3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1000 0 ENCFF072MKT /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNV/summary/ENCFF072MKT.w5 32 2 mean CHIP:MEF2A:K562 CHIP ChIP-TF:MEF2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1001 0 ENCFF619NSR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BNW/summary/ENCFF619NSR.w5 32 2 mean CHIP:SIX5:K562 CHIP ChIP-TF:SIX5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1002 0 ENCFF352HRD /home/drk/tillage/datasets/human/chip/encode/ENCSR000BOT/summary/ENCFF352HRD.w5 32 2 mean CHIP:REST:HepG2 CHIP ChIP-TF:REST/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1003 0 ENCFF567DPU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BOV/summary/ENCFF567DPU.w5 32 2 mean CHIP:POLR2AphosphoS5:Panc1 CHIP ChIP-TF:POLR2AphosphoS5/Panc1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1004 0 ENCFF364BPR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BOX/summary/ENCFF364BPR.w5 32 2 mean CHIP:REST:PFSK-1 CHIP ChIP-TF:REST/PFSK-1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1005 0 ENCFF689BDC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BOZ/summary/ENCFF689BDC.w5 32 2 mean CHIP:REST:SK-N-SH CHIP ChIP-TF:REST/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1006 0 ENCFF602NKU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPA/summary/ENCFF602NKU.w5 32 2 mean CHIP:POLR2AphosphoS5:SK-N-SH CHIP ChIP-TF:POLR2AphosphoS5/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1007 0 ENCFF476PLO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPB/summary/ENCFF476PLO.w5 32 2 mean CHIP:SIN3A:SK-N-SH CHIP ChIP-TF:SIN3A/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1008 0 ENCFF238OET /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPC/summary/ENCFF238OET.w5 32 2 mean CHIP:POLR2AphosphoS5:PFSK-1 CHIP ChIP-TF:POLR2AphosphoS5/PFSK-1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1009 0 ENCFF476BDL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPE/summary/ENCFF476BDL.w5 32 2 mean CHIP:SP1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:SP1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1010 0 ENCFF618STH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPF/summary/ENCFF618STH.w5 32 2 mean CHIP:TAF1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:TAF1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1011 0 ENCFF206RHP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPI/summary/ENCFF206RHP.w5 32 2 mean CHIP:POLR2AphosphoS5:HepG2 CHIP ChIP-TF:POLR2AphosphoS5/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1012 0 ENCFF233ZLL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPJ/summary/ENCFF233ZLL.w5 32 2 mean CHIP:CTCF:K562 CHIP ChIP-TF:CTCF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1013 0 ENCFF435PZF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPL/summary/ENCFF435PZF.w5 32 2 mean CHIP:POLR2AphosphoS5:SK-N-MC CHIP ChIP-TF:POLR2AphosphoS5/SK-N-MC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1014 0 ENCFF882FLP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPM/summary/ENCFF882FLP.w5 32 2 mean CHIP:YY1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:YY1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1015 0 ENCFF705EUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPS/summary/ENCFF705EUJ.w5 32 2 mean CHIP:ATF3:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:ATF3/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1016 0 ENCFF527SIP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPT/summary/ENCFF527SIP.w5 32 2 mean CHIP:ELF1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:ELF1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1017 0 ENCFF509OEY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPU/summary/ENCFF509OEY.w5 32 2 mean CHIP:ETS1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:ETS1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1018 0 ENCFF865MYW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPX/summary/ENCFF865MYW.w5 32 2 mean CHIP:FOXA1:A549 treated with 100 nM dexamethasone for 1 hour CHIP ChIP-TF:FOXA1/A549 treated with 100 nM dexamethasone for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1019 0 ENCFF896FCK /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPY/summary/ENCFF896FCK.w5 32 2 mean CHIP:GABPA:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:GABPA/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1020 0 ENCFF295LJY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BPZ/summary/ENCFF295LJY.w5 32 2 mean CHIP:ZBTB33:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:ZBTB33/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1021 0 ENCFF842TXL /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQA/summary/ENCFF842TXL.w5 32 2 mean CHIP:ZBTB7A:HepG2 CHIP ChIP-TF:ZBTB7A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1022 0 ENCFF166KIG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQB/summary/ENCFF166KIG.w5 32 2 mean CHIP:POLR2A:endothelial cell of umbilical vein newborn CHIP ChIP-TF:POLR2A/endothelial cell of umbilical vein newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1023 0 ENCFF074TFD /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQC/summary/ENCFF074TFD.w5 32 2 mean CHIP:POLR2AphosphoS5:endothelial cell of umbilical vein newborn CHIP ChIP-TF:POLR2AphosphoS5/endothelial cell of umbilical vein newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1024 0 ENCFF373MQA /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQD/summary/ENCFF373MQA.w5 32 2 mean CHIP:ESR1:T47D treated with 100 nM bisphenol A for 30 minutes CHIP ChIP-TF:ESR1/T47D treated with 100 nM bisphenol A for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1025 0 ENCFF992ZMC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQE/summary/ENCFF992ZMC.w5 32 2 mean CHIP:CTCF:Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour CHIP ChIP-TF:CTCF/Ishikawa treated with 0.02% dimethyl sulfoxide for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1026 0 ENCFF342FDS /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQF/summary/ENCFF342FDS.w5 32 2 mean CHIP:TAF1:SK-N-SH CHIP ChIP-TF:TAF1/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1027 0 ENCFF517WBB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQH/summary/ENCFF517WBB.w5 32 2 mean CHIP:BCL3:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:BCL3/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1028 0 ENCFF003HJB /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQI/summary/ENCFF003HJB.w5 32 2 mean CHIP:CEBPB:HepG2 CHIP ChIP-TF:CEBPB/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1029 0 ENCFF732LDY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQK/summary/ENCFF732LDY.w5 32 2 mean CHIP:ATF2:GM12878 CHIP ChIP-TF:ATF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1030 0 ENCFF564YOV /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQL/summary/ENCFF564YOV.w5 32 2 mean CHIP:NFATC1:GM12878 CHIP ChIP-TF:NFATC1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1031 0 ENCFF937ONI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQN/summary/ENCFF937ONI.w5 32 2 mean CHIP:TAF1:PFSK-1 CHIP ChIP-TF:TAF1/PFSK-1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1032 0 ENCFF340TFY /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQO/summary/ENCFF340TFY.w5 32 2 mean CHIP:FOSL2:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:FOSL2/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1033 0 ENCFF355REQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQP/summary/ENCFF355REQ.w5 32 2 mean CHIP:REST:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:REST/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1034 0 ENCFF042IFX /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQQ/summary/ENCFF042IFX.w5 32 2 mean CHIP:TCF12:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:TCF12/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1035 0 ENCFF004DHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQR/summary/ENCFF004DHQ.w5 32 2 mean CHIP:ESR1:Ishikawa treated with 100 nM bisphenol A for 1 hour CHIP ChIP-TF:ESR1/Ishikawa treated with 100 nM bisphenol A for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1036 0 ENCFF027PQW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQS/summary/ENCFF027PQW.w5 32 2 mean CHIP:REST:GM12878 CHIP ChIP-TF:REST/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1037 0 ENCFF668SKC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQY/summary/ENCFF668SKC.w5 32 2 mean CHIP:PML:K562 CHIP ChIP-TF:PML/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1038 0 ENCFF249CGE /home/drk/tillage/datasets/human/chip/encode/ENCSR000BQZ/summary/ENCFF249CGE.w5 32 2 mean CHIP:STAT5A:GM12878 CHIP ChIP-TF:STAT5A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1039 0 ENCFF157FKC /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRA/summary/ENCFF157FKC.w5 32 2 mean CHIP:CREB1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:CREB1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1040 0 ENCFF655WPA /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRC/summary/ENCFF655WPA.w5 32 2 mean CHIP:CREB1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:CREB1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1041 0 ENCFF529JIR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRD/summary/ENCFF529JIR.w5 32 2 mean CHIP:FOXA1:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:FOXA1/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1042 0 ENCFF165UOQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRF/summary/ENCFF165UOQ.w5 32 2 mean CHIP:JUND:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:JUND/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1043 0 ENCFF357OHD /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRG/summary/ENCFF357OHD.w5 32 2 mean CHIP:EGR1:GM12878 CHIP ChIP-TF:EGR1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1044 0 ENCFF655JEP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRH/summary/ENCFF655JEP.w5 32 2 mean CHIP:MTA3:GM12878 CHIP ChIP-TF:MTA3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1045 0 ENCFF335BBU /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRI/summary/ENCFF335BBU.w5 32 2 mean CHIP:RUNX3:GM12878 CHIP ChIP-TF:RUNX3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1046 0 ENCFF950JFN /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRK/summary/ENCFF950JFN.w5 32 2 mean CHIP:TEAD4:K562 CHIP ChIP-TF:TEAD4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1047 0 ENCFF043CDP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRL/summary/ENCFF043CDP.w5 32 2 mean CHIP:SIX5:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:SIX5/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1048 0 ENCFF369URM /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRM/summary/ENCFF369URM.w5 32 2 mean CHIP:SIN3A:A549 treated with 0.02% ethanol for 1 hour CHIP ChIP-TF:SIN3A/A549 treated with 0.02% ethanol for 1 hour ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1049 0 ENCFF388KAP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRN/summary/ENCFF388KAP.w5 32 2 mean CHIP:NFIC:GM12878 CHIP ChIP-TF:NFIC/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1050 0 ENCFF738ISI /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRR/summary/ENCFF738ISI.w5 32 2 mean CHIP:STAT5A:K562 CHIP ChIP-TF:STAT5A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1051 0 ENCFF600YIF /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRS/summary/ENCFF600YIF.w5 32 2 mean CHIP:NR2F2:K562 CHIP ChIP-TF:NR2F2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1052 0 ENCFF646PFR /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRT/summary/ENCFF646PFR.w5 32 2 mean CHIP:CBX3:K562 CHIP ChIP-TF:CBX3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1053 0 ENCFF651CUK /home/drk/tillage/datasets/human/chip/encode/ENCSR000BRW/summary/ENCFF651CUK.w5 32 2 mean CHIP:TRIM28:K562 CHIP ChIP-TF:TRIM28/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1054 0 ENCFF415KJH /home/drk/tillage/datasets/human/chip/encode/ENCSR000BSA/summary/ENCFF415KJH.w5 32 2 mean CHIP:JUND:HCT116 CHIP ChIP-TF:JUND/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1055 0 ENCFF142PEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BSE/summary/ENCFF142PEQ.w5 32 2 mean CHIP:CTCF:HCT116 CHIP ChIP-TF:CTCF/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1056 0 ENCFF008ACO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BSK/summary/ENCFF008ACO.w5 32 2 mean CHIP:JUND:SK-N-SH CHIP ChIP-TF:JUND/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1057 0 ENCFF459CCO /home/drk/tillage/datasets/human/chip/encode/ENCSR000BSU/summary/ENCFF459CCO.w5 32 2 mean CHIP:JUND:MCF-7 CHIP ChIP-TF:JUND/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1058 0 ENCFF496DGW /home/drk/tillage/datasets/human/chip/encode/ENCSR000BTF/summary/ENCFF496DGW.w5 32 2 mean CHIP:REST:HL-60 CHIP ChIP-TF:REST/HL-60 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1059 0 ENCFF724AUK /home/drk/tillage/datasets/human/chip/encode/ENCSR000BTK/summary/ENCFF724AUK.w5 32 2 mean CHIP:GABPA:HL-60 CHIP ChIP-TF:GABPA/HL-60 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1060 0 ENCFF771XTJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000BTL/summary/ENCFF771XTJ.w5 32 2 mean CHIP:POLR2AphosphoS5:HL-60 CHIP ChIP-TF:POLR2AphosphoS5/HL-60 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1061 0 ENCFF443HSG /home/drk/tillage/datasets/human/chip/encode/ENCSR000BTW/summary/ENCFF443HSG.w5 32 2 mean CHIP:POLR2AphosphoS5:neural cell CHIP ChIP-TF:POLR2AphosphoS5/neural cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1062 0 ENCFF973NJP /home/drk/tillage/datasets/human/chip/encode/ENCSR000BUW/summary/ENCFF973NJP.w5 32 2 mean CHIP:SPI1:HL-60 CHIP ChIP-TF:SPI1/HL-60 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1063 0 ENCFF970LMA /home/drk/tillage/datasets/human/chip/encode/ENCSR000BVO/summary/ENCFF970LMA.w5 32 2 mean CHIP:JUND:T47D CHIP ChIP-TF:JUND/T47D ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1064 0 ENCFF085GMS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DJW/summary/ENCFF085GMS.w5 32 2 mean CHIP:eGFP-NR4A1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NR4A1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1065 0 ENCFF115ZOD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DJZ/summary/ENCFF115ZOD.w5 32 2 mean CHIP:eGFP-HDAC8:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-HDAC8/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1066 0 ENCFF879COR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DKA/summary/ENCFF879COR.w5 32 2 mean CHIP:eGFP-GATA2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-GATA2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1067 0 ENCFF105OZZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DKN/summary/ENCFF105OZZ.w5 32 2 mean CHIP:CTCF:H54 CHIP ChIP-TF:CTCF/H54 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1068 0 ENCFF606NRM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DKP/summary/ENCFF606NRM.w5 32 2 mean CHIP:CTCF:GM10248 CHIP ChIP-TF:CTCF/GM10248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1069 0 ENCFF238GME /home/drk/tillage/datasets/human/chip/encode/ENCSR000DKR/summary/ENCFF238GME.w5 32 2 mean CHIP:CTCF:GM10266 CHIP ChIP-TF:CTCF/GM10266 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1070 0 ENCFF553JDS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DKZ/summary/ENCFF553JDS.w5 32 2 mean CHIP:CTCF:GM13976 CHIP ChIP-TF:CTCF/GM13976 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1071 0 ENCFF983RTJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DLB/summary/ENCFF983RTJ.w5 32 2 mean CHIP:CTCF:GM13977 CHIP ChIP-TF:CTCF/GM13977 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1072 0 ENCFF251SEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DLG/summary/ENCFF251SEQ.w5 32 2 mean CHIP:CTCF:GM20000 CHIP ChIP-TF:CTCF/GM20000 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1073 0 ENCFF975VIV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DLJ/summary/ENCFF975VIV.w5 32 2 mean CHIP:POLR2A:H1-hESC CHIP ChIP-TF:POLR2A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1074 0 ENCFF586WDJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DLK/summary/ENCFF586WDJ.w5 32 2 mean CHIP:CTCF:H1-hESC CHIP ChIP-TF:CTCF/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1075 0 ENCFF273CND /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMF/summary/ENCFF273CND.w5 32 2 mean CHIP:CTCF:LNCaP clone FGC CHIP ChIP-TF:CTCF/LNCaP clone FGC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1076 0 ENCFF006FZE /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMJ/summary/ENCFF006FZE.w5 32 2 mean CHIP:MYC:MCF-7 originated from MCF-7 CHIP ChIP-TF:MYC/MCF-7 originated from MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1077 0 ENCFF608JCM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMM/summary/ENCFF608JCM.w5 32 2 mean CHIP:MYC:MCF-7 originated from MCF-7 CHIP ChIP-TF:MYC/MCF-7 originated from MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1078 0 ENCFF663QKE /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMN/summary/ENCFF663QKE.w5 32 2 mean CHIP:POLR2A:MCF-7 originated from MCF-7 CHIP ChIP-TF:POLR2A/MCF-7 originated from MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1079 0 ENCFF697ZLF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMO/summary/ENCFF697ZLF.w5 32 2 mean CHIP:CTCF:MCF-7 originated from MCF-7 CHIP ChIP-TF:CTCF/MCF-7 originated from MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1080 0 ENCFF298WLL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMQ/summary/ENCFF298WLL.w5 32 2 mean CHIP:MYC:MCF-7 CHIP ChIP-TF:MYC/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1081 0 ENCFF849IUY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMR/summary/ENCFF849IUY.w5 32 2 mean CHIP:CTCF:MCF-7 CHIP ChIP-TF:CTCF/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1082 0 ENCFF628MBW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMS/summary/ENCFF628MBW.w5 32 2 mean CHIP:CTCF:MCF-7 treated with 100 nM 17B-estradiol for 45 minutes CHIP ChIP-TF:CTCF/MCF-7 treated with 100 nM 17B-estradiol for 45 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1083 0 ENCFF120OYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DMY/summary/ENCFF120OYZ.w5 32 2 mean CHIP:CTCF:medulloblastoma CHIP ChIP-TF:CTCF/medulloblastoma ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1084 0 ENCFF344MYT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNA/summary/ENCFF344MYT.w5 32 2 mean CHIP:CTCF:A549 CHIP ChIP-TF:CTCF/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1085 0 ENCFF261CVM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNC/summary/ENCFF261CVM.w5 32 2 mean CHIP:CTCF:keratinocyte female CHIP ChIP-TF:CTCF/keratinocyte female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1086 0 ENCFF292KXW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNI/summary/ENCFF292KXW.w5 32 2 mean CHIP:CTCF:spleen female adult (20 years) and female adult (30 years) CHIP ChIP-TF:CTCF/spleen female adult (20 years) and female adult (30 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1087 0 ENCFF239BIV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNM/summary/ENCFF239BIV.w5 32 2 mean CHIP:NFYB:GM12878 CHIP ChIP-TF:NFYB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1088 0 ENCFF878TJY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNN/summary/ENCFF878TJY.w5 32 2 mean CHIP:NFYA:GM12878 CHIP ChIP-TF:NFYA/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1089 0 ENCFF720RCP /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNO/summary/ENCFF720RCP.w5 32 2 mean CHIP:KAT2A:GM12878 CHIP ChIP-TF:KAT2A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1090 0 ENCFF087OWB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNP/summary/ENCFF087OWB.w5 32 2 mean CHIP:SUPT20H:GM12878 CHIP ChIP-TF:SUPT20H/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1091 0 ENCFF636KMF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DNQ/summary/ENCFF636KMF.w5 32 2 mean CHIP:ZZZ3:GM12878 CHIP ChIP-TF:ZZZ3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1092 0 ENCFF219FDG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DON/summary/ENCFF219FDG.w5 32 2 mean CHIP:FOS:MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours CHIP ChIP-TF:FOS/MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1093 0 ENCFF546GVT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOO/summary/ENCFF546GVT.w5 32 2 mean CHIP:FOS:MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 4 hours CHIP ChIP-TF:FOS/MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 4 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1094 0 ENCFF047ZQF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOP/summary/ENCFF047ZQF.w5 32 2 mean CHIP:FOS:MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 12 hours CHIP ChIP-TF:FOS/MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 12 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1095 0 ENCFF202JSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOQ/summary/ENCFF202JSQ.w5 32 2 mean CHIP:STAT3:MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 12 hours CHIP ChIP-TF:STAT3/MCF 10A genetically modified using stable transfection treated with 1 uM afimoxifene for 12 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1096 0 ENCFF532TVO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOS/summary/ENCFF532TVO.w5 32 2 mean CHIP:MYC:MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours CHIP ChIP-TF:MYC/MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1097 0 ENCFF338VNY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOT/summary/ENCFF338VNY.w5 32 2 mean CHIP:FOS:MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours CHIP ChIP-TF:FOS/MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1098 0 ENCFF224YUA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DOZ/summary/ENCFF224YUA.w5 32 2 mean CHIP:STAT3:MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours CHIP ChIP-TF:STAT3/MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1099 0 ENCFF869KFA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPA/summary/ENCFF869KFA.w5 32 2 mean CHIP:POLR2A:MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours CHIP ChIP-TF:POLR2A/MCF 10A genetically modified using stable transfection treated with 0.01% ethanol for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1100 0 ENCFF960CHO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPB/summary/ENCFF960CHO.w5 32 2 mean CHIP:STAT3:MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours CHIP ChIP-TF:STAT3/MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1101 0 ENCFF715OCD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPC/summary/ENCFF715OCD.w5 32 2 mean CHIP:POLR2A:MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours CHIP ChIP-TF:POLR2A/MCF 10A originated from MCF 10A treated with 1 uM afimoxifene for 36 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1102 0 ENCFF152LRB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPD/summary/ENCFF152LRB.w5 32 2 mean CHIP:H3K4me3:A549 CHIP ChIP-Histone:H3K4me3/A549 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1103 0 ENCFF078VLY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPG/summary/ENCFF078VLY.w5 32 2 mean CHIP:CTCF:AG04449 CHIP ChIP-TF:CTCF/AG04449 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1104 0 ENCFF665GSY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPI/summary/ENCFF665GSY.w5 32 2 mean CHIP:H3K4me3:AG04449 CHIP ChIP-Histone:H3K4me3/AG04449 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1105 0 ENCFF416EBF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPJ/summary/ENCFF416EBF.w5 32 2 mean CHIP:H3K9me3:AG04450 CHIP ChIP-Histone:H3K9me3/AG04450 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1106 0 ENCFF098HRZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPK/summary/ENCFF098HRZ.w5 32 2 mean CHIP:H3K27me3:AG04450 CHIP ChIP-Histone:H3K27me3/AG04450 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1107 0 ENCFF671LAW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPL/summary/ENCFF671LAW.w5 32 2 mean CHIP:H3K27ac:AG04450 CHIP ChIP-Histone:H3K27ac/AG04450 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1108 0 ENCFF993AJR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPM/summary/ENCFF993AJR.w5 32 2 mean CHIP:CTCF:AG04450 CHIP ChIP-TF:CTCF/AG04450 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1109 0 ENCFF229ICS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPO/summary/ENCFF229ICS.w5 32 2 mean CHIP:H3K4me3:AG04450 CHIP ChIP-Histone:H3K4me3/AG04450 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1110 0 ENCFF640EZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPP/summary/ENCFF640EZJ.w5 32 2 mean CHIP:CTCF:AG09309 CHIP ChIP-TF:CTCF/AG09309 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1111 0 ENCFF252FYX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPR/summary/ENCFF252FYX.w5 32 2 mean CHIP:H3K4me3:AG09309 CHIP ChIP-Histone:H3K4me3/AG09309 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1112 0 ENCFF336CTF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPS/summary/ENCFF336CTF.w5 32 2 mean CHIP:CTCF:AG09319 CHIP ChIP-TF:CTCF/AG09319 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1113 0 ENCFF175JFX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPU/summary/ENCFF175JFX.w5 32 2 mean CHIP:H3K4me3:AG09319 CHIP ChIP-Histone:H3K4me3/AG09319 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1114 0 ENCFF694SQA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPV/summary/ENCFF694SQA.w5 32 2 mean CHIP:CTCF:AG10803 CHIP ChIP-TF:CTCF/AG10803 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1115 0 ENCFF150CNL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPX/summary/ENCFF150CNL.w5 32 2 mean CHIP:H3K4me3:AG10803 CHIP ChIP-Histone:H3K4me3/AG10803 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1116 0 ENCFF475VZY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DPY/summary/ENCFF475VZY.w5 32 2 mean CHIP:CTCF:fibroblast of the aortic adventitia female CHIP ChIP-TF:CTCF/fibroblast of the aortic adventitia female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1117 0 ENCFF029UXF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQA/summary/ENCFF029UXF.w5 32 2 mean CHIP:H3K4me3:fibroblast of the aortic adventitia female CHIP ChIP-Histone:H3K4me3/fibroblast of the aortic adventitia female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1118 0 ENCFF314PWW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQB/summary/ENCFF314PWW.w5 32 2 mean CHIP:H3K4me3:BE2C CHIP ChIP-Histone:H3K4me3/BE2C ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1119 0 ENCFF578IWZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQD/summary/ENCFF578IWZ.w5 32 2 mean CHIP:CTCF:BE2C CHIP ChIP-TF:CTCF/BE2C ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1120 0 ENCFF225GEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQF/summary/ENCFF225GEQ.w5 32 2 mean CHIP:H3K36me3:BJ CHIP ChIP-Histone:H3K36me3/BJ ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1121 0 ENCFF890AJI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQG/summary/ENCFF890AJI.w5 32 2 mean CHIP:H3K27me3:BJ CHIP ChIP-Histone:H3K27me3/BJ ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1122 0 ENCFF770QSA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQH/summary/ENCFF770QSA.w5 32 2 mean CHIP:H3K4me3:BJ CHIP ChIP-Histone:H3K4me3/BJ ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1123 0 ENCFF354SRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQI/summary/ENCFF354SRQ.w5 32 2 mean CHIP:CTCF:BJ CHIP ChIP-TF:CTCF/BJ ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1124 0 ENCFF141QAK /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQK/summary/ENCFF141QAK.w5 32 2 mean CHIP:H3K36me3:Caco-2 CHIP ChIP-Histone:H3K36me3/Caco-2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1125 0 ENCFF468RGR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQL/summary/ENCFF468RGR.w5 32 2 mean CHIP:H3K27me3:Caco-2 CHIP ChIP-Histone:H3K27me3/Caco-2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1126 0 ENCFF109LUV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQM/summary/ENCFF109LUV.w5 32 2 mean CHIP:H3K4me3:Caco-2 CHIP ChIP-Histone:H3K4me3/Caco-2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1127 0 ENCFF473QVA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQN/summary/ENCFF473QVA.w5 32 2 mean CHIP:CTCF:Caco-2 CHIP ChIP-TF:CTCF/Caco-2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1128 0 ENCFF778UUA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQP/summary/ENCFF778UUA.w5 32 2 mean CHIP:H3K4me3:B cell female adult (43 years) CHIP ChIP-Histone:H3K4me3/B cell female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1129 0 ENCFF035KWP /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQR/summary/ENCFF035KWP.w5 32 2 mean CHIP:H3K4me3:B cell female adult (27 years) CHIP ChIP-Histone:H3K4me3/B cell female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1130 0 ENCFF372TOU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQT/summary/ENCFF372TOU.w5 32 2 mean CHIP:H3K36me3:GM06990 CHIP ChIP-Histone:H3K36me3/GM06990 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1131 0 ENCFF750NUB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQU/summary/ENCFF750NUB.w5 32 2 mean CHIP:H3K27me3:GM06990 CHIP ChIP-Histone:H3K27me3/GM06990 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1132 0 ENCFF851EPY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQV/summary/ENCFF851EPY.w5 32 2 mean CHIP:H3K4me3:GM06990 CHIP ChIP-Histone:H3K4me3/GM06990 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1133 0 ENCFF272DTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQW/summary/ENCFF272DTZ.w5 32 2 mean CHIP:CTCF:GM06990 CHIP ChIP-TF:CTCF/GM06990 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1134 0 ENCFF928ETA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DQZ/summary/ENCFF928ETA.w5 32 2 mean CHIP:H3K4me3:GM12864 CHIP ChIP-Histone:H3K4me3/GM12864 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1135 0 ENCFF593YIG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRB/summary/ENCFF593YIG.w5 32 2 mean CHIP:CTCF:GM12864 CHIP ChIP-TF:CTCF/GM12864 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1136 0 ENCFF599QMA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRC/summary/ENCFF599QMA.w5 32 2 mean CHIP:H3K4me3:GM12865 CHIP ChIP-Histone:H3K4me3/GM12865 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1137 0 ENCFF676FHP /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRE/summary/ENCFF676FHP.w5 32 2 mean CHIP:CTCF:GM12865 CHIP ChIP-TF:CTCF/GM12865 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1138 0 ENCFF489APG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRP/summary/ENCFF489APG.w5 32 2 mean CHIP:CTCF:GM12873 CHIP ChIP-TF:CTCF/GM12873 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1139 0 ENCFF086QBD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRR/summary/ENCFF086QBD.w5 32 2 mean CHIP:CTCF:GM12874 CHIP ChIP-TF:CTCF/GM12874 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1140 0 ENCFF718PYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRS/summary/ENCFF718PYZ.w5 32 2 mean CHIP:H3K4me3:GM12875 CHIP ChIP-Histone:H3K4me3/GM12875 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1141 0 ENCFF171MDW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRW/summary/ENCFF171MDW.w5 32 2 mean CHIP:H3K36me3:GM12878 CHIP ChIP-Histone:H3K36me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1142 0 ENCFF039JOT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRX/summary/ENCFF039JOT.w5 32 2 mean CHIP:H3K27me3:GM12878 CHIP ChIP-Histone:H3K27me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1143 0 ENCFF583MDQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DRY/summary/ENCFF583MDQ.w5 32 2 mean CHIP:H3K4me3:GM12878 CHIP ChIP-Histone:H3K4me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1144 0 ENCFF591TLE /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSD/summary/ENCFF591TLE.w5 32 2 mean CHIP:H3K4me3:cardiac mesoderm CHIP ChIP-Histone:H3K4me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1145 0 ENCFF421AVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSE/summary/ENCFF421AVJ.w5 32 2 mean CHIP:H3K4me3:cardiac mesoderm CHIP ChIP-Histone:H3K4me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1146 0 ENCFF475OPJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSF/summary/ENCFF475OPJ.w5 32 2 mean CHIP:H3K36me3:cardiac mesoderm CHIP ChIP-Histone:H3K36me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1147 0 ENCFF176JHR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSG/summary/ENCFF176JHR.w5 32 2 mean CHIP:H3K36me3:cardiac mesoderm CHIP ChIP-Histone:H3K36me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1148 0 ENCFF797MUR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSH/summary/ENCFF797MUR.w5 32 2 mean CHIP:H3K36me3:cardiac mesoderm CHIP ChIP-Histone:H3K36me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1149 0 ENCFF681IUI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSI/summary/ENCFF681IUI.w5 32 2 mean CHIP:H3K36me3:cardiac mesoderm CHIP ChIP-Histone:H3K36me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1150 0 ENCFF054IIB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSJ/summary/ENCFF054IIB.w5 32 2 mean CHIP:H3K27me3:cardiac mesoderm CHIP ChIP-Histone:H3K27me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1151 0 ENCFF055WTJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSK/summary/ENCFF055WTJ.w5 32 2 mean CHIP:H3K27me3:cardiac mesoderm CHIP ChIP-Histone:H3K27me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1152 0 ENCFF699QRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSL/summary/ENCFF699QRQ.w5 32 2 mean CHIP:H3K27me3:cardiac mesoderm CHIP ChIP-Histone:H3K27me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1153 0 ENCFF440OLV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSM/summary/ENCFF440OLV.w5 32 2 mean CHIP:H3K27me3:cardiac mesoderm CHIP ChIP-Histone:H3K27me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1154 0 ENCFF823NVC /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSO/summary/ENCFF823NVC.w5 32 2 mean CHIP:H3K4me3:cardiac mesoderm CHIP ChIP-Histone:H3K4me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1155 0 ENCFF013QVO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSP/summary/ENCFF013QVO.w5 32 2 mean CHIP:H3K4me3:cardiac mesoderm CHIP ChIP-Histone:H3K4me3/cardiac mesoderm ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1156 0 ENCFF181RQZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSR/summary/ENCFF181RQZ.w5 32 2 mean CHIP:H3K4me3:H7-hESC CHIP ChIP-Histone:H3K4me3/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1157 0 ENCFF652IGB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSS/summary/ENCFF652IGB.w5 32 2 mean CHIP:H3K36me3:H7-hESC CHIP ChIP-Histone:H3K36me3/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1158 0 ENCFF518RVU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DST/summary/ENCFF518RVU.w5 32 2 mean CHIP:H3K27me3:H7-hESC CHIP ChIP-Histone:H3K27me3/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1159 0 ENCFF424JNY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSU/summary/ENCFF424JNY.w5 32 2 mean CHIP:CTCF:astrocyte of the spinal cord CHIP ChIP-TF:CTCF/astrocyte of the spinal cord ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1160 0 ENCFF510YMH /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSW/summary/ENCFF510YMH.w5 32 2 mean CHIP:H3K4me3:astrocyte of the spinal cord CHIP ChIP-Histone:H3K4me3/astrocyte of the spinal cord ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1161 0 ENCFF072YMW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSY/summary/ENCFF072YMW.w5 32 2 mean CHIP:H3K4me3:astrocyte of the cerebellum CHIP ChIP-Histone:H3K4me3/astrocyte of the cerebellum ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1162 0 ENCFF757YRI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DSZ/summary/ENCFF757YRI.w5 32 2 mean CHIP:CTCF:astrocyte of the cerebellum CHIP ChIP-TF:CTCF/astrocyte of the cerebellum ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1163 0 ENCFF210HSY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTA/summary/ENCFF210HSY.w5 32 2 mean CHIP:CTCF:brain microvascular endothelial cell CHIP ChIP-TF:CTCF/brain microvascular endothelial cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1164 0 ENCFF256KXI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTC/summary/ENCFF256KXI.w5 32 2 mean CHIP:H3K4me3:brain microvascular endothelial cell CHIP ChIP-Histone:H3K4me3/brain microvascular endothelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1165 0 ENCFF493FOT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTE/summary/ENCFF493FOT.w5 32 2 mean CHIP:H3K4me3:cardiac fibroblast CHIP ChIP-Histone:H3K4me3/cardiac fibroblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1166 0 ENCFF921GHG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTF/summary/ENCFF921GHG.w5 32 2 mean CHIP:CTCF:cardiac fibroblast female CHIP ChIP-TF:CTCF/cardiac fibroblast female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1167 0 ENCFF419MUF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTH/summary/ENCFF419MUF.w5 32 2 mean CHIP:H3K4me3:cardiac fibroblast female CHIP ChIP-Histone:H3K4me3/cardiac fibroblast female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1168 0 ENCFF467BZS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTI/summary/ENCFF467BZS.w5 32 2 mean CHIP:CTCF:cardiac muscle cell CHIP ChIP-TF:CTCF/cardiac muscle cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1169 0 ENCFF269FSL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTK/summary/ENCFF269FSL.w5 32 2 mean CHIP:H3K4me3:cardiac muscle cell CHIP ChIP-Histone:H3K4me3/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1170 0 ENCFF844WPW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTL/summary/ENCFF844WPW.w5 32 2 mean CHIP:CTCF:choroid plexus epithelial cell CHIP ChIP-TF:CTCF/choroid plexus epithelial cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1171 0 ENCFF129PMO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTN/summary/ENCFF129PMO.w5 32 2 mean CHIP:H3K4me3:choroid plexus epithelial cell CHIP ChIP-Histone:H3K4me3/choroid plexus epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1172 0 ENCFF620LDT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTO/summary/ENCFF620LDT.w5 32 2 mean CHIP:CTCF:HCT116 CHIP ChIP-TF:CTCF/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1173 0 ENCFF176SFX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTQ/summary/ENCFF176SFX.w5 32 2 mean CHIP:H3K4me3:HCT116 CHIP ChIP-Histone:H3K4me3/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1174 0 ENCFF659HPU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTR/summary/ENCFF659HPU.w5 32 2 mean CHIP:CTCF:epithelial cell of esophagus CHIP ChIP-TF:CTCF/epithelial cell of esophagus ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1175 0 ENCFF901LXI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTT/summary/ENCFF901LXI.w5 32 2 mean CHIP:H3K4me3:epithelial cell of esophagus CHIP ChIP-Histone:H3K4me3/epithelial cell of esophagus ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1176 0 ENCFF342FTF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTU/summary/ENCFF342FTF.w5 32 2 mean CHIP:H3K4me3:HEK293 CHIP ChIP-Histone:H3K4me3/HEK293 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1177 0 ENCFF772IJJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTY/summary/ENCFF772IJJ.w5 32 2 mean CHIP:H3K27me3:HeLa-S3 G1b phase CHIP ChIP-Histone:H3K27me3/HeLa-S3 G1b phase ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1178 0 ENCFF521FCP /home/drk/tillage/datasets/human/chip/encode/ENCSR000DTZ/summary/ENCFF521FCP.w5 32 2 mean CHIP:H3K36me3:HeLa-S3 G1b phase CHIP ChIP-Histone:H3K36me3/HeLa-S3 G1b phase ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1179 0 ENCFF509ECR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUA/summary/ENCFF509ECR.w5 32 2 mean CHIP:H3K4me3:HeLa-S3 G1b phase CHIP ChIP-Histone:H3K4me3/HeLa-S3 G1b phase ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1180 0 ENCFF104ECN /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUD/summary/ENCFF104ECN.w5 32 2 mean CHIP:H3K36me3:HepG2 CHIP ChIP-Histone:H3K36me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1181 0 ENCFF419FUZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUE/summary/ENCFF419FUZ.w5 32 2 mean CHIP:H3K27me3:HepG2 CHIP ChIP-Histone:H3K27me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1182 0 ENCFF777EVS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUF/summary/ENCFF777EVS.w5 32 2 mean CHIP:H3K4me3:HepG2 CHIP ChIP-Histone:H3K4me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1183 0 ENCFF380PGD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUH/summary/ENCFF380PGD.w5 32 2 mean CHIP:CTCF:foreskin fibroblast male newborn CHIP ChIP-TF:CTCF/foreskin fibroblast male newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1184 0 ENCFF259BDX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUJ/summary/ENCFF259BDX.w5 32 2 mean CHIP:H3K4me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1185 0 ENCFF044HJS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUK/summary/ENCFF044HJS.w5 32 2 mean CHIP:H3K4me3:HFF-Myc originated from foreskin fibroblast CHIP ChIP-Histone:H3K4me3/HFF-Myc originated from foreskin fibroblast ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1186 0 ENCFF839WGK /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUM/summary/ENCFF839WGK.w5 32 2 mean CHIP:CTCF:HFF-Myc originated from foreskin fibroblast CHIP ChIP-TF:CTCF/HFF-Myc originated from foreskin fibroblast ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1187 0 ENCFF334AJI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUO/summary/ENCFF334AJI.w5 32 2 mean CHIP:H3K4me3:HL-60 CHIP ChIP-Histone:H3K4me3/HL-60 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1188 0 ENCFF914EDX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUP/summary/ENCFF914EDX.w5 32 2 mean CHIP:CTCF:HL-60 CHIP ChIP-TF:CTCF/HL-60 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1189 0 ENCFF499KDV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUQ/summary/ENCFF499KDV.w5 32 2 mean CHIP:H3K4me3:mammary epithelial cell female CHIP ChIP-Histone:H3K4me3/mammary epithelial cell female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1190 0 ENCFF587EDB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUS/summary/ENCFF587EDB.w5 32 2 mean CHIP:CTCF:mammary epithelial cell female CHIP ChIP-TF:CTCF/mammary epithelial cell female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1191 0 ENCFF816IUS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUU/summary/ENCFF816IUS.w5 32 2 mean CHIP:CTCF:fibroblast of mammary gland female CHIP ChIP-TF:CTCF/fibroblast of mammary gland female ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1192 0 ENCFF024BEV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUW/summary/ENCFF024BEV.w5 32 2 mean CHIP:H3K4me3:fibroblast of mammary gland female CHIP ChIP-Histone:H3K4me3/fibroblast of mammary gland female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1193 0 ENCFF702TBG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUX/summary/ENCFF702TBG.w5 32 2 mean CHIP:CTCF:fibroblast of pulmonary artery CHIP ChIP-TF:CTCF/fibroblast of pulmonary artery ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1194 0 ENCFF104DXZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DUZ/summary/ENCFF104DXZ.w5 32 2 mean CHIP:H3K4me3:fibroblast of pulmonary artery CHIP ChIP-Histone:H3K4me3/fibroblast of pulmonary artery ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1195 0 ENCFF117BRM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVA/summary/ENCFF117BRM.w5 32 2 mean CHIP:CTCF:fibroblast of lung CHIP ChIP-TF:CTCF/fibroblast of lung ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1196 0 ENCFF103CWS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVC/summary/ENCFF103CWS.w5 32 2 mean CHIP:H3K4me3:fibroblast of lung CHIP ChIP-Histone:H3K4me3/fibroblast of lung ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1197 0 ENCFF045WHX /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVE/summary/ENCFF045WHX.w5 32 2 mean CHIP:H3K36me3:kidney epithelial cell CHIP ChIP-Histone:H3K36me3/kidney epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1198 0 ENCFF558NEF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVF/summary/ENCFF558NEF.w5 32 2 mean CHIP:H3K27me3:kidney epithelial cell CHIP ChIP-Histone:H3K27me3/kidney epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1199 0 ENCFF354SQM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVG/summary/ENCFF354SQM.w5 32 2 mean CHIP:H3K4me3:kidney epithelial cell CHIP ChIP-Histone:H3K4me3/kidney epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1200 0 ENCFF640EBA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVH/summary/ENCFF640EBA.w5 32 2 mean CHIP:CTCF:kidney epithelial cell CHIP ChIP-TF:CTCF/kidney epithelial cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1201 0 ENCFF732MRP /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVI/summary/ENCFF732MRP.w5 32 2 mean CHIP:CTCF:retinal pigment epithelial cell CHIP ChIP-TF:CTCF/retinal pigment epithelial cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1202 0 ENCFF405LBE /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVK/summary/ENCFF405LBE.w5 32 2 mean CHIP:H3K4me3:retinal pigment epithelial cell CHIP ChIP-Histone:H3K4me3/retinal pigment epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1203 0 ENCFF661CPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVM/summary/ENCFF661CPQ.w5 32 2 mean CHIP:H3K36me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K36me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1204 0 ENCFF669KWL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVN/summary/ENCFF669KWL.w5 32 2 mean CHIP:H3K4me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K4me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1205 0 ENCFF993XMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVO/summary/ENCFF993XMQ.w5 32 2 mean CHIP:H3K27me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K27me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1206 0 ENCFF734VFU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVQ/summary/ENCFF734VFU.w5 32 2 mean CHIP:CTCF:fibroblast of villous mesenchyme CHIP ChIP-TF:CTCF/fibroblast of villous mesenchyme ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1207 0 ENCFF254FXT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVS/summary/ENCFF254FXT.w5 32 2 mean CHIP:H3K4me3:fibroblast of villous mesenchyme CHIP ChIP-Histone:H3K4me3/fibroblast of villous mesenchyme ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1208 0 ENCFF017AFO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DVU/summary/ENCFF017AFO.w5 32 2 mean CHIP:H3K4me3:Jurkat clone E61 CHIP ChIP-Histone:H3K4me3/Jurkat clone E61 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1209 0 ENCFF440XMD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWB/summary/ENCFF440XMD.w5 32 2 mean CHIP:H3K36me3:K562 CHIP ChIP-Histone:H3K36me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1210 0 ENCFF847JMY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWD/summary/ENCFF847JMY.w5 32 2 mean CHIP:H3K4me3:K562 CHIP ChIP-Histone:H3K4me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1211 0 ENCFF675GVW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWE/summary/ENCFF675GVW.w5 32 2 mean CHIP:CTCF:K562 CHIP ChIP-TF:CTCF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1212 0 ENCFF315WID /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWF/summary/ENCFF315WID.w5 32 2 mean CHIP:H3K4me3:LNCaP clone FGC CHIP ChIP-Histone:H3K4me3/LNCaP clone FGC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1213 0 ENCFF551DQV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWH/summary/ENCFF551DQV.w5 32 2 mean CHIP:CTCF:MCF-7 CHIP ChIP-TF:CTCF/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1214 0 ENCFF530LJW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWJ/summary/ENCFF530LJW.w5 32 2 mean CHIP:H3K4me3:MCF-7 CHIP ChIP-Histone:H3K4me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1215 0 ENCFF227YKR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWL/summary/ENCFF227YKR.w5 32 2 mean CHIP:H3K4me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K4me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1216 0 ENCFF934UNQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWM/summary/ENCFF934UNQ.w5 32 2 mean CHIP:H3K27me3:CD14-positive monocyte female CHIP ChIP-Histone:H3K27me3/CD14-positive monocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1217 0 ENCFF977ZXO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWN/summary/ENCFF977ZXO.w5 32 2 mean CHIP:CTCF:NB4 CHIP ChIP-TF:CTCF/NB4 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1218 0 ENCFF493FQG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWP/summary/ENCFF493FQG.w5 32 2 mean CHIP:H3K4me3:NB4 CHIP ChIP-Histone:H3K4me3/NB4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1219 0 ENCFF761RHS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWQ/summary/ENCFF761RHS.w5 32 2 mean CHIP:CTCF:foreskin fibroblast male newborn CHIP ChIP-TF:CTCF/foreskin fibroblast male newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1220 0 ENCFF442WNT /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWS/summary/ENCFF442WNT.w5 32 2 mean CHIP:H3K4me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1221 0 ENCFF721SBI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWV/summary/ENCFF721SBI.w5 32 2 mean CHIP:H3K4me3:keratinocyte female CHIP ChIP-Histone:H3K4me3/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1222 0 ENCFF638EOB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWW/summary/ENCFF638EOB.w5 32 2 mean CHIP:H3K36me3:keratinocyte female CHIP ChIP-Histone:H3K36me3/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1223 0 ENCFF339PQD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWY/summary/ENCFF339PQD.w5 32 2 mean CHIP:CTCF:fibroblast of lung male adult (45 years) CHIP ChIP-TF:CTCF/fibroblast of lung male adult (45 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1224 0 ENCFF626WKG /home/drk/tillage/datasets/human/chip/encode/ENCSR000DWZ/summary/ENCFF626WKG.w5 32 2 mean CHIP:H3K4me3:fibroblast of lung male adult (45 years) CHIP ChIP-Histone:H3K4me3/fibroblast of lung male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1225 0 ENCFF840SHA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXB/summary/ENCFF840SHA.w5 32 2 mean CHIP:H3K4me3:Panc1 CHIP ChIP-Histone:H3K4me3/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1226 0 ENCFF585EEJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXD/summary/ENCFF585EEJ.w5 32 2 mean CHIP:CTCF:epithelial cell of proximal tubule CHIP ChIP-TF:CTCF/epithelial cell of proximal tubule ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1227 0 ENCFF451ARW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXF/summary/ENCFF451ARW.w5 32 2 mean CHIP:H3K4me3:epithelial cell of proximal tubule CHIP ChIP-Histone:H3K4me3/epithelial cell of proximal tubule ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1228 0 ENCFF492DQI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXH/summary/ENCFF492DQI.w5 32 2 mean CHIP:H3K36me3:bronchial epithelial cell CHIP ChIP-Histone:H3K36me3/bronchial epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1229 0 ENCFF880KYS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXJ/summary/ENCFF880KYS.w5 32 2 mean CHIP:H3K4me3:bronchial epithelial cell CHIP ChIP-Histone:H3K4me3/bronchial epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1230 0 ENCFF068KKR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXK/summary/ENCFF068KKR.w5 32 2 mean CHIP:H3K27me3:bronchial epithelial cell CHIP ChIP-Histone:H3K27me3/bronchial epithelial cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1231 0 ENCFF877SOO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXL/summary/ENCFF877SOO.w5 32 2 mean CHIP:H3K4me3:SK-N-MC CHIP ChIP-Histone:H3K4me3/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1232 0 ENCFF754WGM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXO/summary/ENCFF754WGM.w5 32 2 mean CHIP:H3K36me3:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-Histone:H3K36me3/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1233 0 ENCFF588ANO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXP/summary/ENCFF588ANO.w5 32 2 mean CHIP:H3K27me3:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-Histone:H3K27me3/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1234 0 ENCFF749OUM /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXR/summary/ENCFF749OUM.w5 32 2 mean CHIP:H3K4me3:SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours CHIP ChIP-Histone:H3K4me3/SK-N-SH treated with 6 uM all-trans-retinoic acid for 48 hours ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1235 0 ENCFF338EKW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXT/summary/ENCFF338EKW.w5 32 2 mean CHIP:H3K4me3:skeletal muscle cell CHIP ChIP-Histone:H3K4me3/skeletal muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1236 0 ENCFF272MMD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXU/summary/ENCFF272MMD.w5 32 2 mean CHIP:H3K4me3:WERI-Rb-1 CHIP ChIP-Histone:H3K4me3/WERI-Rb-1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1237 0 ENCFF548YUO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXW/summary/ENCFF548YUO.w5 32 2 mean CHIP:CTCF:WERI-Rb-1 CHIP ChIP-TF:CTCF/WERI-Rb-1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1238 0 ENCFF181HKY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXY/summary/ENCFF181HKY.w5 32 2 mean CHIP:H3K4me3:WI38 genetically modified using stable transfection treated with 20 nM afimoxifene for 72 hours CHIP ChIP-Histone:H3K4me3/WI38 genetically modified using stable transfection treated with 20 nM afimoxifene for 72 hours ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1239 0 ENCFF319QVY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DXZ/summary/ENCFF319QVY.w5 32 2 mean CHIP:H3K4me3:WI38 CHIP ChIP-Histone:H3K4me3/WI38 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1240 0 ENCFF645TQU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYB/summary/ENCFF645TQU.w5 32 2 mean CHIP:CTCF:WI38 CHIP ChIP-TF:CTCF/WI38 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1241 0 ENCFF338VRO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYC/summary/ENCFF338VRO.w5 32 2 mean CHIP:MYC:A549 CHIP ChIP-TF:MYC/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1242 0 ENCFF751HWN /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYD/summary/ENCFF751HWN.w5 32 2 mean CHIP:CTCF:A549 CHIP ChIP-TF:CTCF/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1243 0 ENCFF840MLF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYE/summary/ENCFF840MLF.w5 32 2 mean CHIP:RAD21:A549 CHIP ChIP-TF:RAD21/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1244 0 ENCFF356QCU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYF/summary/ENCFF356QCU.w5 32 2 mean CHIP:POLR2AphosphoS2:A549 CHIP ChIP-TF:POLR2AphosphoS2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1245 0 ENCFF221XZD /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYI/summary/ENCFF221XZD.w5 32 2 mean CHIP:CEBPB:A549 CHIP ChIP-TF:CEBPB/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1246 0 ENCFF469XZI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYP/summary/ENCFF469XZI.w5 32 2 mean CHIP:ZNF384:GM12878 CHIP ChIP-TF:ZNF384/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1247 0 ENCFF440TNS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYQ/summary/ENCFF440TNS.w5 32 2 mean CHIP:ESRRA:GM12878 CHIP ChIP-TF:ESRRA/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1248 0 ENCFF195RAW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYR/summary/ENCFF195RAW.w5 32 2 mean CHIP:CUX1:GM12878 CHIP ChIP-TF:CUX1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1249 0 ENCFF116XIJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYS/summary/ENCFF116XIJ.w5 32 2 mean CHIP:JUND:GM12878 CHIP ChIP-TF:JUND/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1250 0 ENCFF100QMI /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYV/summary/ENCFF100QMI.w5 32 2 mean CHIP:MAFK:GM12878 CHIP ChIP-TF:MAFK/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1251 0 ENCFF109XHK /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYX/summary/ENCFF109XHK.w5 32 2 mean CHIP:SIN3A:GM12878 CHIP ChIP-TF:SIN3A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1252 0 ENCFF417WYL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYY/summary/ENCFF417WYL.w5 32 2 mean CHIP:E2F4:GM12878 CHIP ChIP-TF:E2F4/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1253 0 ENCFF061ZIL /home/drk/tillage/datasets/human/chip/encode/ENCSR000DYZ/summary/ENCFF061ZIL.w5 32 2 mean CHIP:TBL1XR1:GM12878 CHIP ChIP-TF:TBL1XR1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1254 0 ENCFF256TBW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZA/summary/ENCFF256TBW.w5 32 2 mean CHIP:MAZ:GM12878 CHIP ChIP-TF:MAZ/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1255 0 ENCFF308NKV /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZB/summary/ENCFF308NKV.w5 32 2 mean CHIP:ELK1:GM12878 CHIP ChIP-TF:ELK1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1256 0 ENCFF118ZGB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZC/summary/ENCFF118ZGB.w5 32 2 mean CHIP:RCOR1:GM12878 CHIP ChIP-TF:RCOR1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1257 0 ENCFF977NLF /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZD/summary/ENCFF977NLF.w5 32 2 mean CHIP:EP300:GM12878 CHIP ChIP-TF:EP300/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1258 0 ENCFF322MQW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZE/summary/ENCFF322MQW.w5 32 2 mean CHIP:CHD1:GM12878 CHIP ChIP-TF:CHD1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1259 0 ENCFF348NRU /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZF/summary/ENCFF348NRU.w5 32 2 mean CHIP:MAX:GM12878 CHIP ChIP-TF:MAX/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1260 0 ENCFF167VDA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZG/summary/ENCFF167VDA.w5 32 2 mean CHIP:EP300:GM12878 CHIP ChIP-TF:EP300/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1261 0 ENCFF482UOW /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZI/summary/ENCFF482UOW.w5 32 2 mean CHIP:MXI1:GM12878 CHIP ChIP-TF:MXI1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1262 0 ENCFF945XXY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZJ/summary/ENCFF945XXY.w5 32 2 mean CHIP:BHLHE40:GM12878 CHIP ChIP-TF:BHLHE40/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1263 0 ENCFF086FEO /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZK/summary/ENCFF086FEO.w5 32 2 mean CHIP:POLR2AphosphoS2:GM12878 CHIP ChIP-TF:POLR2AphosphoS2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1264 0 ENCFF972SJN /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZL/summary/ENCFF972SJN.w5 32 2 mean CHIP:ZNF143:GM12878 CHIP ChIP-TF:ZNF143/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1265 0 ENCFF578TBN /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZN/summary/ENCFF578TBN.w5 32 2 mean CHIP:CTCF:GM12878 CHIP ChIP-TF:CTCF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1266 0 ENCFF293CPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZO/summary/ENCFF293CPQ.w5 32 2 mean CHIP:NRF1:GM12878 CHIP ChIP-TF:NRF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1267 0 ENCFF782WWH /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZP/summary/ENCFF782WWH.w5 32 2 mean CHIP:SMC3:GM12878 CHIP ChIP-TF:SMC3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1268 0 ENCFF170NTY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZQ/summary/ENCFF170NTY.w5 32 2 mean CHIP:EBF1:GM12878 CHIP ChIP-TF:EBF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1269 0 ENCFF766HMR /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZR/summary/ENCFF766HMR.w5 32 2 mean CHIP:CHD2:GM12878 CHIP ChIP-TF:CHD2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1270 0 ENCFF983EKB /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZS/summary/ENCFF983EKB.w5 32 2 mean CHIP:BRCA1:GM12878 CHIP ChIP-TF:BRCA1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1271 0 ENCFF109ZHE /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZU/summary/ENCFF109ZHE.w5 32 2 mean CHIP:USF2:GM12878 CHIP ChIP-TF:USF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1272 0 ENCFF950RYY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZV/summary/ENCFF950RYY.w5 32 2 mean CHIP:STAT3:GM12878 CHIP ChIP-TF:STAT3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1273 0 ENCFF300YPA /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZW/summary/ENCFF300YPA.w5 32 2 mean CHIP:RFX5:GM12878 CHIP ChIP-TF:RFX5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1274 0 ENCFF595QZS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZX/summary/ENCFF595QZS.w5 32 2 mean CHIP:IRF3:GM12878 CHIP ChIP-TF:IRF3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1275 0 ENCFF899KXS /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZY/summary/ENCFF899KXS.w5 32 2 mean CHIP:NFE2:GM12878 CHIP ChIP-TF:NFE2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1276 0 ENCFF554YCY /home/drk/tillage/datasets/human/chip/encode/ENCSR000DZZ/summary/ENCFF554YCY.w5 32 2 mean CHIP:TBP:GM12878 CHIP ChIP-TF:TBP/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1277 0 ENCFF483PQP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EAA/summary/ENCFF483PQP.w5 32 2 mean CHIP:WRNIP1:GM12878 CHIP ChIP-TF:WRNIP1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1278 0 ENCFF350OAA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBO/summary/ENCFF350OAA.w5 32 2 mean CHIP:SIN3A:H1-hESC CHIP ChIP-TF:SIN3A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1279 0 ENCFF173BEC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBP/summary/ENCFF173BEC.w5 32 2 mean CHIP:GTF2F1:H1-hESC CHIP ChIP-TF:GTF2F1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1280 0 ENCFF594ALF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBQ/summary/ENCFF594ALF.w5 32 2 mean CHIP:BACH1:H1-hESC CHIP ChIP-TF:BACH1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1281 0 ENCFF640RNH /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBS/summary/ENCFF640RNH.w5 32 2 mean CHIP:MAFK:H1-hESC CHIP ChIP-TF:MAFK/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1282 0 ENCFF318NSO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBT/summary/ENCFF318NSO.w5 32 2 mean CHIP:CHD2:H1-hESC CHIP ChIP-TF:CHD2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1283 0 ENCFF563QHP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBU/summary/ENCFF563QHP.w5 32 2 mean CHIP:CHD1:H1-hESC CHIP ChIP-TF:CHD1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1284 0 ENCFF377SDG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBW/summary/ENCFF377SDG.w5 32 2 mean CHIP:ZNF143:H1-hESC CHIP ChIP-TF:ZNF143/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1285 0 ENCFF620MRE /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBX/summary/ENCFF620MRE.w5 32 2 mean CHIP:BRCA1:H1-hESC CHIP ChIP-TF:BRCA1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1286 0 ENCFF878ZLF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBY/summary/ENCFF878ZLF.w5 32 2 mean CHIP:MYC:H1-hESC CHIP ChIP-TF:MYC/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1287 0 ENCFF744ISC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EBZ/summary/ENCFF744ISC.w5 32 2 mean CHIP:JUND:H1-hESC CHIP ChIP-TF:JUND/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1288 0 ENCFF815WEI /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECA/summary/ENCFF815WEI.w5 32 2 mean CHIP:JUN:H1-hESC CHIP ChIP-TF:JUN/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1289 0 ENCFF052TRV /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECB/summary/ENCFF052TRV.w5 32 2 mean CHIP:TBP:H1-hESC CHIP ChIP-TF:TBP/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1290 0 ENCFF515ERL /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECC/summary/ENCFF515ERL.w5 32 2 mean CHIP:NRF1:H1-hESC CHIP ChIP-TF:NRF1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1291 0 ENCFF757FPX /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECD/summary/ENCFF757FPX.w5 32 2 mean CHIP:USF2:H1-hESC CHIP ChIP-TF:USF2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1292 0 ENCFF913JGA /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECE/summary/ENCFF913JGA.w5 32 2 mean CHIP:RAD21:H1-hESC CHIP ChIP-TF:RAD21/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1293 0 ENCFF027CMH /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECF/summary/ENCFF027CMH.w5 32 2 mean CHIP:RFX5:H1-hESC CHIP ChIP-TF:RFX5/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1294 0 ENCFF949NBY /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECK/summary/ENCFF949NBY.w5 32 2 mean CHIP:MAFK:HeLa-S3 CHIP ChIP-TF:MAFK/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1295 0 ENCFF703ZFU /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECQ/summary/ENCFF703ZFU.w5 32 2 mean CHIP:SUPT20H:HeLa-S3 CHIP ChIP-TF:SUPT20H/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1296 0 ENCFF637LQS /home/drk/tillage/datasets/human/chip/encode/ENCSR000ECZ/summary/ENCFF637LQS.w5 32 2 mean CHIP:GTF2F1:HeLa-S3 CHIP ChIP-TF:GTF2F1/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1297 0 ENCFF613BCN /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDD/summary/ENCFF613BCN.w5 32 2 mean CHIP:TBP:HeLa-S3 CHIP ChIP-TF:TBP/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1298 0 ENCFF495UJE /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDN/summary/ENCFF495UJE.w5 32 2 mean CHIP:MAZ:HepG2 CHIP ChIP-TF:MAZ/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1299 0 ENCFF322XIA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDO/summary/ENCFF322XIA.w5 32 2 mean CHIP:CEBPZ:HepG2 CHIP ChIP-TF:CEBPZ/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1300 0 ENCFF116CGF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDP/summary/ENCFF116CGF.w5 32 2 mean CHIP:ARID3A:HepG2 CHIP ChIP-TF:ARID3A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1301 0 ENCFF085SFU /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDQ/summary/ENCFF085SFU.w5 32 2 mean CHIP:RCOR1:HepG2 CHIP ChIP-TF:RCOR1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1302 0 ENCFF016QMU /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDS/summary/ENCFF016QMU.w5 32 2 mean CHIP:MAX:HepG2 CHIP ChIP-TF:MAX/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1303 0 ENCFF348USU /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDT/summary/ENCFF348USU.w5 32 2 mean CHIP:BHLHE40:HepG2 CHIP ChIP-TF:BHLHE40/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1304 0 ENCFF432IMS /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDV/summary/ENCFF432IMS.w5 32 2 mean CHIP:EP300:HepG2 CHIP ChIP-TF:EP300/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1305 0 ENCFF789EFR /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDW/summary/ENCFF789EFR.w5 32 2 mean CHIP:SMC3:HepG2 CHIP ChIP-TF:SMC3/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1306 0 ENCFF037LMD /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDX/summary/ENCFF037LMD.w5 32 2 mean CHIP:POLR2AphosphoS2:HepG2 CHIP ChIP-TF:POLR2AphosphoS2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1307 0 ENCFF191NNV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDY/summary/ENCFF191NNV.w5 32 2 mean CHIP:BRCA1:HepG2 CHIP ChIP-TF:BRCA1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1308 0 ENCFF931OYF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EDZ/summary/ENCFF931OYF.w5 32 2 mean CHIP:MAFK:HepG2 CHIP ChIP-TF:MAFK/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1309 0 ENCFF227GPX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEA/summary/ENCFF227GPX.w5 32 2 mean CHIP:RFX5:HepG2 CHIP ChIP-TF:RFX5/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1310 0 ENCFF748HVA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEB/summary/ENCFF748HVA.w5 32 2 mean CHIP:MAFK:HepG2 CHIP ChIP-TF:MAFK/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1311 0 ENCFF998ARN /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEC/summary/ENCFF998ARN.w5 32 2 mean CHIP:MAFF:HepG2 CHIP ChIP-TF:MAFF/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1312 0 ENCFF138VIL /home/drk/tillage/datasets/human/chip/encode/ENCSR000EED/summary/ENCFF138VIL.w5 32 2 mean CHIP:CHD2:HepG2 CHIP ChIP-TF:CHD2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1313 0 ENCFF154FVM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEE/summary/ENCFF154FVM.w5 32 2 mean CHIP:CEBPB:HepG2 CHIP ChIP-TF:CEBPB/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1314 0 ENCFF256YKN /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEG/summary/ENCFF256YKN.w5 32 2 mean CHIP:RAD21:HepG2 CHIP ChIP-TF:RAD21/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1315 0 ENCFF032ECF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEH/summary/ENCFF032ECF.w5 32 2 mean CHIP:NRF1:HepG2 CHIP ChIP-TF:NRF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1316 0 ENCFF720EHK /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEI/summary/ENCFF720EHK.w5 32 2 mean CHIP:JUND:HepG2 CHIP ChIP-TF:JUND/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1317 0 ENCFF147UHT /home/drk/tillage/datasets/human/chip/encode/ENCSR000EEL/summary/ENCFF147UHT.w5 32 2 mean CHIP:TBP:HepG2 CHIP ChIP-TF:TBP/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1318 0 ENCFF842VSX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFC/summary/ENCFF842VSX.w5 32 2 mean CHIP:CHD1:IMR-90 CHIP ChIP-TF:CHD1/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1319 0 ENCFF089OHX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFF/summary/ENCFF089OHX.w5 32 2 mean CHIP:MAZ:IMR-90 CHIP ChIP-TF:MAZ/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1320 0 ENCFF171ZVC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFG/summary/ENCFF171ZVC.w5 32 2 mean CHIP:RCOR1:IMR-90 CHIP ChIP-TF:RCOR1/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1321 0 ENCFF329BBV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFH/summary/ENCFF329BBV.w5 32 2 mean CHIP:MAFK:IMR-90 CHIP ChIP-TF:MAFK/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1322 0 ENCFF256DUS /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFI/summary/ENCFF256DUS.w5 32 2 mean CHIP:CTCF:IMR-90 CHIP ChIP-TF:CTCF/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1323 0 ENCFF879GKM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFJ/summary/ENCFF879GKM.w5 32 2 mean CHIP:RAD21:IMR-90 CHIP ChIP-TF:RAD21/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1324 0 ENCFF712KEF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFM/summary/ENCFF712KEF.w5 32 2 mean CHIP:CEBPB:IMR-90 CHIP ChIP-TF:CEBPB/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1325 0 ENCFF339TEC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFN/summary/ENCFF339TEC.w5 32 2 mean CHIP:HCFC1:K562 CHIP ChIP-TF:HCFC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1326 0 ENCFF200ZIM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFO/summary/ENCFF200ZIM.w5 32 2 mean CHIP:CUX1:K562 CHIP ChIP-TF:CUX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1327 0 ENCFF540SQX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFP/summary/ENCFF540SQX.w5 32 2 mean CHIP:ZNF384:K562 CHIP ChIP-TF:ZNF384/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1328 0 ENCFF267EQO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFR/summary/ENCFF267EQO.w5 32 2 mean CHIP:ZC3H11A:K562 CHIP ChIP-TF:ZC3H11A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1329 0 ENCFF345MES /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFS/summary/ENCFF345MES.w5 32 2 mean CHIP:JUN:K562 CHIP ChIP-TF:JUN/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1330 0 ENCFF932GTA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFT/summary/ENCFF932GTA.w5 32 2 mean CHIP:GATA1:K562 CHIP ChIP-TF:GATA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1331 0 ENCFF792ZTJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFU/summary/ENCFF792ZTJ.w5 32 2 mean CHIP:ELK1:K562 CHIP ChIP-TF:ELK1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1332 0 ENCFF796GHK /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFV/summary/ENCFF796GHK.w5 32 2 mean CHIP:MAX:K562 CHIP ChIP-TF:MAX/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1333 0 ENCFF990MNV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFW/summary/ENCFF990MNV.w5 32 2 mean CHIP:UBTF:K562 CHIP ChIP-TF:UBTF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1334 0 ENCFF424NIV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFY/summary/ENCFF424NIV.w5 32 2 mean CHIP:ARID3A:K562 CHIP ChIP-TF:ARID3A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1335 0 ENCFF505BKT /home/drk/tillage/datasets/human/chip/encode/ENCSR000EFZ/summary/ENCFF505BKT.w5 32 2 mean CHIP:UBTF:K562 CHIP ChIP-TF:UBTF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1336 0 ENCFF012SWD /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGA/summary/ENCFF012SWD.w5 32 2 mean CHIP:TBL1XR1:K562 CHIP ChIP-TF:TBL1XR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1337 0 ENCFF805ZUL /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGB/summary/ENCFF805ZUL.w5 32 2 mean CHIP:TBL1XR1:K562 CHIP ChIP-TF:TBL1XR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1338 0 ENCFF976DAC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGC/summary/ENCFF976DAC.w5 32 2 mean CHIP:RCOR1:K562 CHIP ChIP-TF:RCOR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1339 0 ENCFF836PHI /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGD/summary/ENCFF836PHI.w5 32 2 mean CHIP:BACH1:K562 CHIP ChIP-TF:BACH1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1340 0 ENCFF907QZG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGE/summary/ENCFF907QZG.w5 32 2 mean CHIP:EP300:K562 CHIP ChIP-TF:EP300/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1341 0 ENCFF881EJC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGF/summary/ENCFF881EJC.w5 32 2 mean CHIP:POLR2AphosphoS2:K562 CHIP ChIP-TF:POLR2AphosphoS2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1342 0 ENCFF585OJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGH/summary/ENCFF585OJQ.w5 32 2 mean CHIP:JUN:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:JUN/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1343 0 ENCFF291VIM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGI/summary/ENCFF291VIM.w5 32 2 mean CHIP:MAFF:K562 CHIP ChIP-TF:MAFF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1344 0 ENCFF677COF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGJ/summary/ENCFF677COF.w5 32 2 mean CHIP:MYC:K562 CHIP ChIP-TF:MYC/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1345 0 ENCFF093VAP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGK/summary/ENCFF093VAP.w5 32 2 mean CHIP:IRF1:K562 treated with interferon gamma for 30 minutes CHIP ChIP-TF:IRF1/K562 treated with interferon gamma for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1346 0 ENCFF452YAU /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGL/summary/ENCFF452YAU.w5 32 2 mean CHIP:IRF1:K562 treated with interferon alpha for 6 hours CHIP ChIP-TF:IRF1/K562 treated with interferon alpha for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1347 0 ENCFF050CCI /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGM/summary/ENCFF050CCI.w5 32 2 mean CHIP:CTCF:K562 CHIP ChIP-TF:CTCF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1348 0 ENCFF024PVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGN/summary/ENCFF024PVQ.w5 32 2 mean CHIP:JUND:K562 CHIP ChIP-TF:JUND/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1349 0 ENCFF559GNS /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGO/summary/ENCFF559GNS.w5 32 2 mean CHIP:RFX5:K562 CHIP ChIP-TF:RFX5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1350 0 ENCFF811ZGP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGP/summary/ENCFF811ZGP.w5 32 2 mean CHIP:ZNF143:K562 CHIP ChIP-TF:ZNF143/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1351 0 ENCFF667QJZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGS/summary/ENCFF667QJZ.w5 32 2 mean CHIP:MYC:K562 treated with interferon gamma for 30 minutes CHIP ChIP-TF:MYC/K562 treated with interferon gamma for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1352 0 ENCFF176RYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGT/summary/ENCFF176RYJ.w5 32 2 mean CHIP:IRF1:K562 treated with interferon gamma for 6 hours CHIP ChIP-TF:IRF1/K562 treated with interferon gamma for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1353 0 ENCFF918SEG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGU/summary/ENCFF918SEG.w5 32 2 mean CHIP:IRF1:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:IRF1/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1354 0 ENCFF505LZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGV/summary/ENCFF505LZQ.w5 32 2 mean CHIP:BHLHE40:K562 CHIP ChIP-TF:BHLHE40/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1355 0 ENCFF387DUZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGW/summary/ENCFF387DUZ.w5 32 2 mean CHIP:SMC3:K562 CHIP ChIP-TF:SMC3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1356 0 ENCFF509GUW /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGX/summary/ENCFF509GUW.w5 32 2 mean CHIP:MAFK:K562 CHIP ChIP-TF:MAFK/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1357 0 ENCFF918DNW /home/drk/tillage/datasets/human/chip/encode/ENCSR000EGZ/summary/ENCFF918DNW.w5 32 2 mean CHIP:MXI1:K562 CHIP ChIP-TF:MXI1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1358 0 ENCFF727KHF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHA/summary/ENCFF727KHF.w5 32 2 mean CHIP:TBP:K562 CHIP ChIP-TF:TBP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1359 0 ENCFF868FYM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHB/summary/ENCFF868FYM.w5 32 2 mean CHIP:TAL1:K562 CHIP ChIP-TF:TAL1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1360 0 ENCFF349YBX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHC/summary/ENCFF349YBX.w5 32 2 mean CHIP:GTF2F1:K562 CHIP ChIP-TF:GTF2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1361 0 ENCFF430NNH /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHE/summary/ENCFF430NNH.w5 32 2 mean CHIP:CEBPB:K562 CHIP ChIP-TF:CEBPB/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1362 0 ENCFF266FDB /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHG/summary/ENCFF266FDB.w5 32 2 mean CHIP:USF2:K562 CHIP ChIP-TF:USF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1363 0 ENCFF097REV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHJ/summary/ENCFF097REV.w5 32 2 mean CHIP:STAT1:K562 treated with interferon gamma for 6 hours CHIP ChIP-TF:STAT1/K562 treated with interferon gamma for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1364 0 ENCFF597CEP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHL/summary/ENCFF597CEP.w5 32 2 mean CHIP:POLR2A:K562 CHIP ChIP-TF:POLR2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1365 0 ENCFF276GCO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHN/summary/ENCFF276GCO.w5 32 2 mean CHIP:SMARCB1:K562 CHIP ChIP-TF:SMARCB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1366 0 ENCFF110DDG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHO/summary/ENCFF110DDG.w5 32 2 mean CHIP:SMARCA4:K562 CHIP ChIP-TF:SMARCA4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1367 0 ENCFF058BQT /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHP/summary/ENCFF058BQT.w5 32 2 mean CHIP:POLR2A:K562 treated with interferon gamma for 30 minutes CHIP ChIP-TF:POLR2A/K562 treated with interferon gamma for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1368 0 ENCFF376NTC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EHY/summary/ENCFF376NTC.w5 32 2 mean CHIP:RFX5:SK-N-SH CHIP ChIP-TF:RFX5/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1369 0 ENCFF470CFY /home/drk/tillage/datasets/human/chip/encode/ENCSR000EIA/summary/ENCFF470CFY.w5 32 2 mean CHIP:MXI1:SK-N-SH CHIP ChIP-TF:MXI1/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1370 0 ENCFF969FAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EIB/summary/ENCFF969FAZ.w5 32 2 mean CHIP:JUND:SK-N-SH CHIP ChIP-TF:JUND/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1371 0 ENCFF944FHB /home/drk/tillage/datasets/human/chip/encode/ENCSR000EIC/summary/ENCFF944FHB.w5 32 2 mean CHIP:CTCF:SK-N-SH CHIP ChIP-TF:CTCF/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1372 0 ENCFF961VQG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUI/summary/ENCFF961VQG.w5 32 2 mean CHIP:ZNF274:GM08714 CHIP ChIP-TF:ZNF274/GM08714 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1373 0 ENCFF935KTD /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUJ/summary/ENCFF935KTD.w5 32 2 mean CHIP:IKZF1:GM12878 CHIP ChIP-TF:IKZF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1374 0 ENCFF725QBH /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUL/summary/ENCFF725QBH.w5 32 2 mean CHIP:NR2C2:GM12878 CHIP ChIP-TF:NR2C2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1375 0 ENCFF985ZEV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUM/summary/ENCFF985ZEV.w5 32 2 mean CHIP:YY1:GM12878 CHIP ChIP-TF:YY1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1376 0 ENCFF562PRB /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUO/summary/ENCFF562PRB.w5 32 2 mean CHIP:CTBP2:H1-hESC CHIP ChIP-TF:CTBP2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1377 0 ENCFF723MAM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUQ/summary/ENCFF723MAM.w5 32 2 mean CHIP:SUZ12:H1-hESC CHIP ChIP-TF:SUZ12/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1378 0 ENCFF240UKK /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUS/summary/ENCFF240UKK.w5 32 2 mean CHIP:H3K4me1:HCT116 CHIP ChIP-Histone:H3K4me1/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1379 0 ENCFF329BPA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUT/summary/ENCFF329BPA.w5 32 2 mean CHIP:H3K27ac:HCT116 CHIP ChIP-Histone:H3K27ac/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1380 0 ENCFF208YVO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EUZ/summary/ENCFF208YVO.w5 32 2 mean CHIP:TRIM28:HEK293 CHIP ChIP-TF:TRIM28/HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1381 0 ENCFF367HGG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVD/summary/ENCFF367HGG.w5 32 2 mean CHIP:ZNF263:HEK293 CHIP ChIP-TF:ZNF263/HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1382 0 ENCFF822JCS /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVU/summary/ENCFF822JCS.w5 32 2 mean CHIP:FOS:endothelial cell of umbilical vein newborn CHIP ChIP-TF:FOS/endothelial cell of umbilical vein newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1383 0 ENCFF543BEX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVW/summary/ENCFF543BEX.w5 32 2 mean CHIP:GATA2:endothelial cell of umbilical vein newborn CHIP ChIP-TF:GATA2/endothelial cell of umbilical vein newborn ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1384 0 ENCFF767MPH /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVX/summary/ENCFF767MPH.w5 32 2 mean CHIP:ZNF274:K562 CHIP ChIP-TF:ZNF274/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1385 0 ENCFF009LSV /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVY/summary/ENCFF009LSV.w5 32 2 mean CHIP:TRIM28:K562 CHIP ChIP-TF:TRIM28/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1386 0 ENCFF937QUK /home/drk/tillage/datasets/human/chip/encode/ENCSR000EVZ/summary/ENCFF937QUK.w5 32 2 mean CHIP:H3K9ac:K562 CHIP ChIP-Histone:H3K9ac/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1387 0 ENCFF712XRE /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWA/summary/ENCFF712XRE.w5 32 2 mean CHIP:H3K4me3:K562 CHIP ChIP-Histone:H3K4me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1388 0 ENCFF928NWQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWB/summary/ENCFF928NWQ.w5 32 2 mean CHIP:H3K27me3:K562 CHIP ChIP-Histone:H3K27me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1389 0 ENCFF761XBZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWC/summary/ENCFF761XBZ.w5 32 2 mean CHIP:H3K4me1:K562 CHIP ChIP-Histone:H3K4me1/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1390 0 ENCFF388VDO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWE/summary/ENCFF388VDO.w5 32 2 mean CHIP:ZNF274:K562 CHIP ChIP-TF:ZNF274/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1391 0 ENCFF477WFX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWF/summary/ENCFF477WFX.w5 32 2 mean CHIP:YY1:K562 CHIP ChIP-TF:YY1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1392 0 ENCFF781FFF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWG/summary/ENCFF781FFF.w5 32 2 mean CHIP:GATA2:K562 CHIP ChIP-TF:GATA2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1393 0 ENCFF893JAF /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWH/summary/ENCFF893JAF.w5 32 2 mean CHIP:NR2C2:K562 CHIP ChIP-TF:NR2C2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1394 0 ENCFF422PHA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWI/summary/ENCFF422PHA.w5 32 2 mean CHIP:SETDB1:K562 CHIP ChIP-TF:SETDB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1395 0 ENCFF081UQC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWP/summary/ENCFF081UQC.w5 32 2 mean CHIP:H3K27me3:MCF-7 CHIP ChIP-Histone:H3K27me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1396 0 ENCFF754TEC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWQ/summary/ENCFF754TEC.w5 32 2 mean CHIP:H3K9me3:MCF-7 CHIP ChIP-Histone:H3K9me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1397 0 ENCFF986ZEW /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWR/summary/ENCFF986ZEW.w5 32 2 mean CHIP:H3K27ac:MCF-7 CHIP ChIP-Histone:H3K27ac/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1398 0 ENCFF263GHK /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWY/summary/ENCFF263GHK.w5 32 2 mean CHIP:ZNF274:NT2/D1 CHIP "ChIP-TF:ZNF274/NT2;D1" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1399 0 ENCFF314EQX /home/drk/tillage/datasets/human/chip/encode/ENCSR000EWZ/summary/ENCFF314EQX.w5 32 2 mean CHIP:H3K9me3:NT2/D1 CHIP "ChIP-Histone:H3K9me3/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1400 0 ENCFF162DCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXA/summary/ENCFF162DCZ.w5 32 2 mean CHIP:H3K4me1:NT2/D1 CHIP "ChIP-Histone:H3K4me1/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1401 0 ENCFF729JYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXB/summary/ENCFF729JYJ.w5 32 2 mean CHIP:H3K36me3:NT2/D1 CHIP "ChIP-Histone:H3K36me3/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1402 0 ENCFF865WLD /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXC/summary/ENCFF865WLD.w5 32 2 mean CHIP:H3K9ac:NT2/D1 CHIP "ChIP-Histone:H3K9ac/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1403 0 ENCFF928RUE /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXD/summary/ENCFF928RUE.w5 32 2 mean CHIP:H3K4me3:NT2/D1 CHIP "ChIP-Histone:H3K4me3/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1404 0 ENCFF336PTU /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXE/summary/ENCFF336PTU.w5 32 2 mean CHIP:H3K27me3:NT2/D1 CHIP "ChIP-Histone:H3K27me3/NT2;D1" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1405 0 ENCFF830JAP /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXG/summary/ENCFF830JAP.w5 32 2 mean CHIP:YY1:NT2/D1 CHIP "ChIP-TF:YY1/NT2;D1" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1406 0 ENCFF922FRM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXI/summary/ENCFF922FRM.w5 32 2 mean CHIP:H3K4me3:Panc1 CHIP ChIP-Histone:H3K4me3/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1407 0 ENCFF135DCA /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXJ/summary/ENCFF135DCA.w5 32 2 mean CHIP:H3K4me1:Panc1 CHIP ChIP-Histone:H3K4me1/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1408 0 ENCFF541JDS /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXK/summary/ENCFF541JDS.w5 32 2 mean CHIP:H3K27ac:Panc1 CHIP ChIP-Histone:H3K27ac/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1409 0 ENCFF742SZL /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXL/summary/ENCFF742SZL.w5 32 2 mean CHIP:TCF7L2:Panc1 CHIP ChIP-TF:TCF7L2/Panc1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1410 0 ENCFF738YHN /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXP/summary/ENCFF738YHN.w5 32 2 mean CHIP:GATA1:erythroblast male CHIP ChIP-TF:GATA1/erythroblast male ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1411 0 ENCFF679FNB /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXR/summary/ENCFF679FNB.w5 32 2 mean CHIP:GATA1:erythroblast embryo (16-19 weeks) CHIP ChIP-TF:GATA1/erythroblast embryo (16-19 weeks) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1412 0 ENCFF470CHC /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXT/summary/ENCFF470CHC.w5 32 2 mean CHIP:H3K4me3:mononuclear cell male CHIP ChIP-Histone:H3K4me3/mononuclear cell male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1413 0 ENCFF887GSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXU/summary/ENCFF887GSQ.w5 32 2 mean CHIP:H3K9me3:mononuclear cell male CHIP ChIP-Histone:H3K9me3/mononuclear cell male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1414 0 ENCFF316ZVD /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXV/summary/ENCFF316ZVD.w5 32 2 mean CHIP:H3K4me1:mononuclear cell male CHIP ChIP-Histone:H3K4me1/mononuclear cell male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1415 0 ENCFF475ESO /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXW/summary/ENCFF475ESO.w5 32 2 mean CHIP:H3K27me3:mononuclear cell male CHIP ChIP-Histone:H3K27me3/mononuclear cell male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1416 0 ENCFF740KGG /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXX/summary/ENCFF740KGG.w5 32 2 mean CHIP:POLR2A:Raji CHIP ChIP-TF:POLR2A/Raji ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1417 0 ENCFF962SPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EXZ/summary/ENCFF962SPQ.w5 32 2 mean CHIP:GATA3:SH-SY5Y CHIP ChIP-TF:GATA3/SH-SY5Y ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1418 0 ENCFF295BOZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EYB/summary/ENCFF295BOZ.w5 32 2 mean CHIP:GATA2:SH-SY5Y CHIP ChIP-TF:GATA2/SH-SY5Y ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1419 0 ENCFF198YAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR000EZT/summary/ENCFF198YAZ.w5 32 2 mean CHIP:JUN:K562 treated with interferon gamma for 30 minutes CHIP ChIP-TF:JUN/K562 treated with interferon gamma for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1420 0 ENCFF576GQM /home/drk/tillage/datasets/human/chip/encode/ENCSR000EZU/summary/ENCFF576GQM.w5 32 2 mean CHIP:MYC:K562 treated with interferon gamma for 6 hours CHIP ChIP-TF:MYC/K562 treated with interferon gamma for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1421 0 ENCFF518ATL /home/drk/tillage/datasets/human/chip/encode/ENCSR000EZV/summary/ENCFF518ATL.w5 32 2 mean CHIP:MYC:K562 treated with interferon alpha for 6 hours CHIP ChIP-TF:MYC/K562 treated with interferon alpha for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1422 0 ENCFF081FTI /home/drk/tillage/datasets/human/chip/encode/ENCSR000EZW/summary/ENCFF081FTI.w5 32 2 mean CHIP:JUN:K562 treated with interferon gamma for 6 hours CHIP ChIP-TF:JUN/K562 treated with interferon gamma for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1423 0 ENCFF040RHL /home/drk/tillage/datasets/human/chip/encode/ENCSR000EZX/summary/ENCFF040RHL.w5 32 2 mean CHIP:JUN:K562 treated with interferon alpha for 6 hours CHIP ChIP-TF:JUN/K562 treated with interferon alpha for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1424 0 ENCFF998JTX /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAT/summary/ENCFF998JTX.w5 32 2 mean CHIP:STAT2:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:STAT2/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1425 0 ENCFF501LIV /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAU/summary/ENCFF501LIV.w5 32 2 mean CHIP:STAT1:K562 treated with interferon alpha for 6 hours CHIP ChIP-TF:STAT1/K562 treated with interferon alpha for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1426 0 ENCFF364CEV /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAV/summary/ENCFF364CEV.w5 32 2 mean CHIP:STAT1:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:STAT1/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1427 0 ENCFF042IXM /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAW/summary/ENCFF042IXM.w5 32 2 mean CHIP:POLR2A:K562 treated with interferon gamma for 6 hours CHIP ChIP-TF:POLR2A/K562 treated with interferon gamma for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1428 0 ENCFF904LCF /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAX/summary/ENCFF904LCF.w5 32 2 mean CHIP:POLR2A:K562 treated with interferon alpha for 6 hours CHIP ChIP-TF:POLR2A/K562 treated with interferon alpha for 6 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1429 0 ENCFF002ZYX /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAY/summary/ENCFF002ZYX.w5 32 2 mean CHIP:POLR2A:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:POLR2A/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1430 0 ENCFF028KGK /home/drk/tillage/datasets/human/chip/encode/ENCSR000FAZ/summary/ENCFF028KGK.w5 32 2 mean CHIP:MYC:K562 treated with interferon alpha for 30 minutes CHIP ChIP-TF:MYC/K562 treated with interferon alpha for 30 minutes ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1431 0 ENCFF442BPG /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCB/summary/ENCFF442BPG.w5 32 2 mean CHIP:MITF:K562 CHIP ChIP-TF:MITF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1432 0 ENCFF115ALQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCC/summary/ENCFF115ALQ.w5 32 2 mean CHIP:NFE2:K562 CHIP ChIP-TF:NFE2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1433 0 ENCFF059XSX /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCD/summary/ENCFF059XSX.w5 32 2 mean CHIP:SMAD5:K562 CHIP ChIP-TF:SMAD5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1434 0 ENCFF328UEJ /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCE/summary/ENCFF328UEJ.w5 32 2 mean CHIP:ETV6:K562 CHIP ChIP-TF:ETV6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1435 0 ENCFF717JWL /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCG/summary/ENCFF717JWL.w5 32 2 mean CHIP:H3K4me1:HEK293 CHIP ChIP-Histone:H3K4me1/HEK293 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1436 0 ENCFF902RQI /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCJ/summary/ENCFF902RQI.w5 32 2 mean CHIP:H3K9me3:HEK293 CHIP ChIP-Histone:H3K9me3/HEK293 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1437 0 ENCFF788XNP /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCL/summary/ENCFF788XNP.w5 32 2 mean CHIP:H3K4me3:GM08714 CHIP ChIP-Histone:H3K4me3/GM08714 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1438 0 ENCFF924OSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCM/summary/ENCFF924OSQ.w5 32 2 mean CHIP:H3K36me3:Panc1 CHIP ChIP-Histone:H3K36me3/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1439 0 ENCFF248QSM /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCO/summary/ENCFF248QSM.w5 32 2 mean CHIP:H3K27me3:Panc1 CHIP ChIP-Histone:H3K27me3/Panc1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1440 0 ENCFF845JSM /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCR/summary/ENCFF845JSM.w5 32 2 mean CHIP:H3K4me1:SK-N-SH CHIP ChIP-Histone:H3K4me1/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1441 0 ENCFF555ZEF /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCS/summary/ENCFF555ZEF.w5 32 2 mean CHIP:H3K4me3:SK-N-SH CHIP ChIP-Histone:H3K4me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1442 0 ENCFF932EUO /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCT/summary/ENCFF932EUO.w5 32 2 mean CHIP:H3K9me3:SK-N-SH CHIP ChIP-Histone:H3K9me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1443 0 ENCFF143WKK /home/drk/tillage/datasets/human/chip/encode/ENCSR000FCU/summary/ENCFF143WKK.w5 32 2 mean CHIP:H3K27ac:SK-N-SH CHIP ChIP-Histone:H3K27ac/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1444 0 ENCFF869ZLL /home/drk/tillage/datasets/human/chip/encode/ENCSR000GGX/summary/ENCFF869ZLL.w5 32 2 mean CHIP:H3K9me3:neuron originated from H9 CHIP ChIP-Histone:H3K9me3/neuron originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1445 0 ENCFF889ZOU /home/drk/tillage/datasets/human/chip/encode/ENCSR000HPG/summary/ENCFF889ZOU.w5 32 2 mean CHIP:SMC3:IMR-90 CHIP ChIP-TF:SMC3/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1446 0 ENCFF141ZUP /home/drk/tillage/datasets/human/chip/encode/ENCSR000HPR/summary/ENCFF141ZUP.w5 32 2 mean CHIP:H3K9me3:kidney male adult (67 years) CHIP ChIP-Histone:H3K9me3/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1447 0 ENCFF732IFW /home/drk/tillage/datasets/human/chip/encode/ENCSR000MMZ/summary/ENCFF732IFW.w5 32 2 mean CHIP:EP300:upper lobe of left lung female adult (51 year) CHIP ChIP-TF:EP300/upper lobe of left lung female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1448 0 ENCFF190PRO /home/drk/tillage/datasets/human/chip/encode/ENCSR000NPF/summary/ENCFF190PRO.w5 32 2 mean CHIP:H3K27ac:cardiac muscle cell CHIP ChIP-Histone:H3K27ac/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1449 0 ENCFF218VMU /home/drk/tillage/datasets/human/chip/encode/ENCSR000XAA/summary/ENCFF218VMU.w5 32 2 mean CHIP:H3K9me3:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K9me3/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1450 0 ENCFF034RXK /home/drk/tillage/datasets/human/chip/encode/ENCSR001SHB/summary/ENCFF034RXK.w5 32 2 mean CHIP:H3K27ac:stomach male adult (34 years) CHIP ChIP-Histone:H3K27ac/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1451 0 ENCFF203SHR /home/drk/tillage/datasets/human/chip/encode/ENCSR002EZN/summary/ENCFF203SHR.w5 32 2 mean CHIP:H3K4me2:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K4me2/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1452 0 ENCFF663RRL /home/drk/tillage/datasets/human/chip/encode/ENCSR002YRE/summary/ENCFF663RRL.w5 32 2 mean CHIP:H3K27ac:IMR-90 CHIP ChIP-Histone:H3K27ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1453 0 ENCFF268COV /home/drk/tillage/datasets/human/chip/encode/ENCSR003SZZ/summary/ENCFF268COV.w5 32 2 mean CHIP:CTCF:esophagus squamous epithelium female adult (51 year) CHIP ChIP-TF:CTCF/esophagus squamous epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1454 0 ENCFF828RQS /home/drk/tillage/datasets/human/chip/encode/ENCSR003WKF/summary/ENCFF828RQS.w5 32 2 mean CHIP:H3K9me3:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K9me3/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1455 0 ENCFF731PKC /home/drk/tillage/datasets/human/chip/encode/ENCSR004AKD/summary/ENCFF731PKC.w5 32 2 mean CHIP:H3K4me3:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K4me3/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1456 0 ENCFF033HWS /home/drk/tillage/datasets/human/chip/encode/ENCSR004EKY/summary/ENCFF033HWS.w5 32 2 mean CHIP:H3K27ac:muscle layer of colon female adult (56 years) CHIP ChIP-Histone:H3K27ac/muscle layer of colon female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1457 0 ENCFF357KCF /home/drk/tillage/datasets/human/chip/encode/ENCSR004GKA/summary/ENCFF357KCF.w5 32 2 mean CHIP:ZEB2:K562 CHIP ChIP-TF:ZEB2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1458 0 ENCFF432HNP /home/drk/tillage/datasets/human/chip/encode/ENCSR004PLU/summary/ENCFF432HNP.w5 32 2 mean CHIP:eGFP-ZBTB10:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB10/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1459 0 ENCFF562RUL /home/drk/tillage/datasets/human/chip/encode/ENCSR004ZWW/summary/ENCFF562RUL.w5 32 2 mean CHIP:H4K8ac:IMR-90 CHIP ChIP-TF:H4K8ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1460 0 ENCFF412AZH /home/drk/tillage/datasets/human/chip/encode/ENCSR005LPI/summary/ENCFF412AZH.w5 32 2 mean CHIP:CTCF:omental fat pad male adult (54 years) CHIP ChIP-TF:CTCF/omental fat pad male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1461 0 ENCFF896NIM /home/drk/tillage/datasets/human/chip/encode/ENCSR005LTG/summary/ENCFF896NIM.w5 32 2 mean CHIP:H3K9me3:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K9me3/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1462 0 ENCFF411ROG /home/drk/tillage/datasets/human/chip/encode/ENCSR005NMT/summary/ENCFF411ROG.w5 32 2 mean CHIP:eGFP-ID3:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ID3/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1463 0 ENCFF852DRP /home/drk/tillage/datasets/human/chip/encode/ENCSR005SXO/summary/ENCFF852DRP.w5 32 2 mean CHIP:H3K4me3:OCI-LY7 CHIP ChIP-Histone:H3K4me3/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1464 0 ENCFF506BWA /home/drk/tillage/datasets/human/chip/encode/ENCSR005UXZ/summary/ENCFF506BWA.w5 32 2 mean CHIP:H3K9me3:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K9me3/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1465 0 ENCFF843LVW /home/drk/tillage/datasets/human/chip/encode/ENCSR005WWZ/summary/ENCFF843LVW.w5 32 2 mean CHIP:H3K9me3:B cell female adult (43 years) CHIP ChIP-Histone:H3K9me3/B cell female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1466 0 ENCFF295RJI /home/drk/tillage/datasets/human/chip/encode/ENCSR005YZH/summary/ENCFF295RJI.w5 32 2 mean CHIP:H3K36me3:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K36me3/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1467 0 ENCFF249QCY /home/drk/tillage/datasets/human/chip/encode/ENCSR006GAQ/summary/ENCFF249QCY.w5 32 2 mean CHIP:eGFP-KLF10:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF10/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1468 0 ENCFF802IHY /home/drk/tillage/datasets/human/chip/encode/ENCSR006GPM/summary/ENCFF802IHY.w5 32 2 mean CHIP:H3K9ac:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K9ac/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1469 0 ENCFF099BUE /home/drk/tillage/datasets/human/chip/encode/ENCSR006WUS/summary/ENCFF099BUE.w5 32 2 mean CHIP:NEUROD1:MCF-7 CHIP ChIP-TF:NEUROD1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1470 0 ENCFF526VJO /home/drk/tillage/datasets/human/chip/encode/ENCSR007HLH/summary/ENCFF526VJO.w5 32 2 mean CHIP:H3K27ac:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K27ac/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1471 0 ENCFF676VSY /home/drk/tillage/datasets/human/chip/encode/ENCSR007YOT/summary/ENCFF676VSY.w5 32 2 mean CHIP:H3K27ac:GM23248 CHIP ChIP-Histone:H3K27ac/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1472 0 ENCFF529XBR /home/drk/tillage/datasets/human/chip/encode/ENCSR009KLQ/summary/ENCFF529XBR.w5 32 2 mean CHIP:3xFLAG-KLF16:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KLF16/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1473 0 ENCFF039XKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR009MBP/summary/ENCFF039XKQ.w5 32 2 mean CHIP:HSF1:GM12878 CHIP ChIP-TF:HSF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1474 0 ENCFF076DVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR009MUF/summary/ENCFF076DVZ.w5 32 2 mean CHIP:H3K4me1:kidney male adult (67 years) CHIP ChIP-Histone:H3K4me1/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1475 0 ENCFF505ACR /home/drk/tillage/datasets/human/chip/encode/ENCSR009TKN/summary/ENCFF505ACR.w5 32 2 mean CHIP:RCOR1:SK-N-SH CHIP ChIP-TF:RCOR1/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1476 0 ENCFF249LCG /home/drk/tillage/datasets/human/chip/encode/ENCSR011CIR/summary/ENCFF249LCG.w5 32 2 mean CHIP:3xFLAG-ZNF614:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF614/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1477 0 ENCFF339XUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR011CKE/summary/ENCFF339XUQ.w5 32 2 mean CHIP:eGFP-ZNF2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1478 0 ENCFF845OGQ /home/drk/tillage/datasets/human/chip/encode/ENCSR011CSR/summary/ENCFF845OGQ.w5 32 2 mean CHIP:H3K4me1:NCI-H929 CHIP ChIP-Histone:H3K4me1/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1479 0 ENCFF735XKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR011GVU/summary/ENCFF735XKQ.w5 32 2 mean CHIP:H3K36me3:muscle layer of colon female adult (56 years) CHIP ChIP-Histone:H3K36me3/muscle layer of colon female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1480 0 ENCFF414NQV /home/drk/tillage/datasets/human/chip/encode/ENCSR011IVX/summary/ENCFF414NQV.w5 32 2 mean CHIP:H3K36me3:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K36me3/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1481 0 ENCFF743KWB /home/drk/tillage/datasets/human/chip/encode/ENCSR011MGQ/summary/ENCFF743KWB.w5 32 2 mean CHIP:H3K27ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K27ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1482 0 ENCFF979RNH /home/drk/tillage/datasets/human/chip/encode/ENCSR011NOZ/summary/ENCFF979RNH.w5 32 2 mean CHIP:ZNF407:K562 CHIP ChIP-TF:ZNF407/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1483 0 ENCFF579ALH /home/drk/tillage/datasets/human/chip/encode/ENCSR011PEI/summary/ENCFF579ALH.w5 32 2 mean CHIP:eGFP-ZNF175:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF175/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1484 0 ENCFF325XXG /home/drk/tillage/datasets/human/chip/encode/ENCSR011QFP/summary/ENCFF325XXG.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive male adult (36 years) CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1485 0 ENCFF793OOX /home/drk/tillage/datasets/human/chip/encode/ENCSR011XCI/summary/ENCFF793OOX.w5 32 2 mean CHIP:eGFP-ZNF585B:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF585B/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1486 0 ENCFF692FAL /home/drk/tillage/datasets/human/chip/encode/ENCSR012KUR/summary/ENCFF692FAL.w5 32 2 mean CHIP:H3K27me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1487 0 ENCFF601NLG /home/drk/tillage/datasets/human/chip/encode/ENCSR012PII/summary/ENCFF601NLG.w5 32 2 mean CHIP:H3K27ac:CD14-positive monocyte male adult (21 year) CHIP ChIP-Histone:H3K27ac/CD14-positive monocyte male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1488 0 ENCFF301WTK /home/drk/tillage/datasets/human/chip/encode/ENCSR013KEC/summary/ENCFF301WTK.w5 32 2 mean CHIP:H3K27ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K27ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1489 0 ENCFF103CRE /home/drk/tillage/datasets/human/chip/encode/ENCSR014BTW/summary/ENCFF103CRE.w5 32 2 mean CHIP:H3K4me1:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1490 0 ENCFF117XJK /home/drk/tillage/datasets/human/chip/encode/ENCSR014GSQ/summary/ENCFF117XJK.w5 32 2 mean CHIP:CTCF:adrenal gland female adult (51 year) CHIP ChIP-TF:CTCF/adrenal gland female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1491 0 ENCFF854OYD /home/drk/tillage/datasets/human/chip/encode/ENCSR014RCS/summary/ENCFF854OYD.w5 32 2 mean CHIP:HNRNPK:K562 CHIP ChIP-TF:HNRNPK/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1492 0 ENCFF194NPN /home/drk/tillage/datasets/human/chip/encode/ENCSR014TDK/summary/ENCFF194NPN.w5 32 2 mean CHIP:H3K27ac:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K27ac/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1493 0 ENCFF710EKC /home/drk/tillage/datasets/human/chip/encode/ENCSR014YCR/summary/ENCFF710EKC.w5 32 2 mean CHIP:ATF7:GM12878 CHIP ChIP-TF:ATF7/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1494 0 ENCFF477GTH /home/drk/tillage/datasets/human/chip/encode/ENCSR015GFK/summary/ENCFF477GTH.w5 32 2 mean CHIP:H3K27ac:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K27ac/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1495 0 ENCFF285DLJ /home/drk/tillage/datasets/human/chip/encode/ENCSR015TKV/summary/ENCFF285DLJ.w5 32 2 mean CHIP:BCLAF1:HepG2 CHIP ChIP-TF:BCLAF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1496 0 ENCFF662VRT /home/drk/tillage/datasets/human/chip/encode/ENCSR016BMM/summary/ENCFF662VRT.w5 32 2 mean CHIP:TAF1:liver female child (4 years) CHIP ChIP-TF:TAF1/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1497 0 ENCFF448PHV /home/drk/tillage/datasets/human/chip/encode/ENCSR016JWS/summary/ENCFF448PHV.w5 32 2 mean CHIP:H3K4me3:mammary epithelial cell female adult (50 years) CHIP ChIP-Histone:H3K4me3/mammary epithelial cell female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1498 0 ENCFF436YJO /home/drk/tillage/datasets/human/chip/encode/ENCSR016UEH/summary/ENCFF436YJO.w5 32 2 mean CHIP:TARDBP:GM12878 CHIP ChIP-TF:TARDBP/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1499 0 ENCFF186CZK /home/drk/tillage/datasets/human/chip/encode/ENCSR016XBE/summary/ENCFF186CZK.w5 32 2 mean CHIP:H3K27ac:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K27ac/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1500 0 ENCFF649GIG /home/drk/tillage/datasets/human/chip/encode/ENCSR017CEO/summary/ENCFF649GIG.w5 32 2 mean CHIP:CUX1:MCF-7 CHIP ChIP-TF:CUX1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1501 0 ENCFF791FIG /home/drk/tillage/datasets/human/chip/encode/ENCSR017GBO/summary/ENCFF791FIG.w5 32 2 mean CHIP:eGFP-TFDP1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-TFDP1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1502 0 ENCFF820KSO /home/drk/tillage/datasets/human/chip/encode/ENCSR017QBI/summary/ENCFF820KSO.w5 32 2 mean CHIP:eGFP-ZNF600:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF600/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1503 0 ENCFF556OUI /home/drk/tillage/datasets/human/chip/encode/ENCSR018LUP/summary/ENCFF556OUI.w5 32 2 mean CHIP:H3K9me2:SU-DHL-6 CHIP ChIP-Histone:H3K9me2/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1504 0 ENCFF498EZK /home/drk/tillage/datasets/human/chip/encode/ENCSR018MQH/summary/ENCFF498EZK.w5 32 2 mean CHIP:ZNF579:MCF-7 CHIP ChIP-TF:ZNF579/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1505 0 ENCFF970ISQ /home/drk/tillage/datasets/human/chip/encode/ENCSR018MSO/summary/ENCFF970ISQ.w5 32 2 mean CHIP:eGFP-ZNF148:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF148/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1506 0 ENCFF707FCC /home/drk/tillage/datasets/human/chip/encode/ENCSR018OGF/summary/ENCFF707FCC.w5 32 2 mean CHIP:H3K9me3:brain female embryo (120 days) CHIP ChIP-Histone:H3K9me3/brain female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1507 0 ENCFF107XFS /home/drk/tillage/datasets/human/chip/encode/ENCSR019KPC/summary/ENCFF107XFS.w5 32 2 mean CHIP:PLRG1:HepG2 CHIP ChIP-TF:PLRG1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1508 0 ENCFF567JHI /home/drk/tillage/datasets/human/chip/encode/ENCSR019NPF/summary/ENCFF567JHI.w5 32 2 mean CHIP:3xFLAG-SP5:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SP5/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1509 0 ENCFF372YWG /home/drk/tillage/datasets/human/chip/encode/ENCSR019SQX/summary/ENCFF372YWG.w5 32 2 mean CHIP:H3K4me3:H1-hESC CHIP ChIP-Histone:H3K4me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1510 0 ENCFF439FBA /home/drk/tillage/datasets/human/chip/encode/ENCSR019WUS/summary/ENCFF439FBA.w5 32 2 mean CHIP:eGFP-ZNF10:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF10/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1511 0 ENCFF308QXV /home/drk/tillage/datasets/human/chip/encode/ENCSR019ZRR/summary/ENCFF308QXV.w5 32 2 mean CHIP:H3K36me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K36me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1512 0 ENCFF485JCV /home/drk/tillage/datasets/human/chip/encode/ENCSR020UPN/summary/ENCFF485JCV.w5 32 2 mean CHIP:eGFP-ZNF184:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF184/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1513 0 ENCFF501YDC /home/drk/tillage/datasets/human/chip/encode/ENCSR021BCU/summary/ENCFF501YDC.w5 32 2 mean CHIP:H3K9ac:liver male adult (31 year) CHIP ChIP-Histone:H3K9ac/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1514 0 ENCFF609KBN /home/drk/tillage/datasets/human/chip/encode/ENCSR021DJC/summary/ENCFF609KBN.w5 32 2 mean CHIP:eGFP-BCL11A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-BCL11A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1515 0 ENCFF144OXR /home/drk/tillage/datasets/human/chip/encode/ENCSR021FSY/summary/ENCFF144OXR.w5 32 2 mean CHIP:H3K9me3:natural killer cell male adult (21 year) CHIP ChIP-Histone:H3K9me3/natural killer cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1516 0 ENCFF777EIM /home/drk/tillage/datasets/human/chip/encode/ENCSR021HLX/summary/ENCFF777EIM.w5 32 2 mean CHIP:H2AFZ:neural stem progenitor cell originated from H9 CHIP ChIP-TF:H2AFZ/neural stem progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1517 0 ENCFF741JWI /home/drk/tillage/datasets/human/chip/encode/ENCSR022IZK/summary/ENCFF741JWI.w5 32 2 mean CHIP:eGFP-ZNF623:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF623/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1518 0 ENCFF103YRF /home/drk/tillage/datasets/human/chip/encode/ENCSR022LOH/summary/ENCFF103YRF.w5 32 2 mean CHIP:H3K27me3:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K27me3/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1519 0 ENCFF640DMT /home/drk/tillage/datasets/human/chip/encode/ENCSR023ALV/summary/ENCFF640DMT.w5 32 2 mean CHIP:H3K4me1:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K4me1/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1520 0 ENCFF911ZOQ /home/drk/tillage/datasets/human/chip/encode/ENCSR023MFG/summary/ENCFF911ZOQ.w5 32 2 mean CHIP:H3K4me1:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K4me1/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1521 0 ENCFF559WKE /home/drk/tillage/datasets/human/chip/encode/ENCSR024CNP/summary/ENCFF559WKE.w5 32 2 mean CHIP:EGR1:K562 CHIP ChIP-TF:EGR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1522 0 ENCFF162QDX /home/drk/tillage/datasets/human/chip/encode/ENCSR024DUV/summary/ENCFF162QDX.w5 32 2 mean CHIP:H3K36me3:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K36me3/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1523 0 ENCFF656AYV /home/drk/tillage/datasets/human/chip/encode/ENCSR024LKA/summary/ENCFF656AYV.w5 32 2 mean CHIP:HDAC3:K562 CHIP ChIP-TF:HDAC3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1524 0 ENCFF846QJB /home/drk/tillage/datasets/human/chip/encode/ENCSR025CGR/summary/ENCFF846QJB.w5 32 2 mean CHIP:H3K9me3:gastroesophageal sphincter female adult (53 years) CHIP ChIP-Histone:H3K9me3/gastroesophageal sphincter female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1525 0 ENCFF046ZOY /home/drk/tillage/datasets/human/chip/encode/ENCSR025ZZA/summary/ENCFF046ZOY.w5 32 2 mean CHIP:POLR2A:suprapubic skin female adult (51 year) CHIP ChIP-TF:POLR2A/suprapubic skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1526 0 ENCFF413JBK /home/drk/tillage/datasets/human/chip/encode/ENCSR027BAJ/summary/ENCFF413JBK.w5 32 2 mean CHIP:H3K4me1:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1527 0 ENCFF976WZF /home/drk/tillage/datasets/human/chip/encode/ENCSR027FSZ/summary/ENCFF976WZF.w5 32 2 mean CHIP:CTCF:upper lobe of left lung male adult (37 years) CHIP ChIP-TF:CTCF/upper lobe of left lung male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1528 0 ENCFF455RLT /home/drk/tillage/datasets/human/chip/encode/ENCSR027HML/summary/ENCFF455RLT.w5 32 2 mean CHIP:CTCF:OCI-LY7 CHIP ChIP-TF:CTCF/OCI-LY7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1529 0 ENCFF947AXY /home/drk/tillage/datasets/human/chip/encode/ENCSR027UFT/summary/ENCFF947AXY.w5 32 2 mean CHIP:ZFX:C4-2B CHIP ChIP-TF:ZFX/C4-2B ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1530 0 ENCFF731PVG /home/drk/tillage/datasets/human/chip/encode/ENCSR028EGI/summary/ENCFF731PVG.w5 32 2 mean CHIP:eGFP-ZNF26:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF26/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1531 0 ENCFF535TPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR028IND/summary/ENCFF535TPQ.w5 32 2 mean CHIP:H3K27me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K27me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1532 0 ENCFF017WTF /home/drk/tillage/datasets/human/chip/encode/ENCSR028NUR/summary/ENCFF017WTF.w5 32 2 mean CHIP:ZNF592:MCF-7 CHIP ChIP-TF:ZNF592/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1533 0 ENCFF592FPI /home/drk/tillage/datasets/human/chip/encode/ENCSR028NXO/summary/ENCFF592FPI.w5 32 2 mean CHIP:H3K27ac:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K27ac/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1534 0 ENCFF468HHO /home/drk/tillage/datasets/human/chip/encode/ENCSR028QEA/summary/ENCFF468HHO.w5 32 2 mean CHIP:H3K27ac:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1535 0 ENCFF481PMC /home/drk/tillage/datasets/human/chip/encode/ENCSR028UIU/summary/ENCFF481PMC.w5 32 2 mean CHIP:ATF3:K562 CHIP ChIP-TF:ATF3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1536 0 ENCFF158LCC /home/drk/tillage/datasets/human/chip/encode/ENCSR028YEV/summary/ENCFF158LCC.w5 32 2 mean CHIP:CTCF:spleen male adult (54 years) CHIP ChIP-TF:CTCF/spleen male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1537 0 ENCFF866XWN /home/drk/tillage/datasets/human/chip/encode/ENCSR029IBC/summary/ENCFF866XWN.w5 32 2 mean CHIP:ARNT:HepG2 CHIP ChIP-TF:ARNT/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1538 0 ENCFF910ZUF /home/drk/tillage/datasets/human/chip/encode/ENCSR029LBT/summary/ENCFF910ZUF.w5 32 2 mean CHIP:FOXP1:HepG2 CHIP ChIP-TF:FOXP1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1539 0 ENCFF226ZWP /home/drk/tillage/datasets/human/chip/encode/ENCSR030TJP/summary/ENCFF226ZWP.w5 32 2 mean CHIP:DACH1:K562 CHIP ChIP-TF:DACH1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1540 0 ENCFF605DZE /home/drk/tillage/datasets/human/chip/encode/ENCSR031ING/summary/ENCFF605DZE.w5 32 2 mean CHIP:3xFLAG-KDM6A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KDM6A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1541 0 ENCFF490AFN /home/drk/tillage/datasets/human/chip/encode/ENCSR031KWR/summary/ENCFF490AFN.w5 32 2 mean CHIP:POLR2A:adrenal gland female adult (53 years) CHIP ChIP-TF:POLR2A/adrenal gland female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1542 0 ENCFF311RLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR031TFS/summary/ENCFF311RLQ.w5 32 2 mean CHIP:POLR2A:K562 CHIP ChIP-TF:POLR2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1543 0 ENCFF778OGY /home/drk/tillage/datasets/human/chip/encode/ENCSR031URL/summary/ENCFF778OGY.w5 32 2 mean CHIP:XRCC5:HepG2 CHIP ChIP-TF:XRCC5/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1544 0 ENCFF065CFJ /home/drk/tillage/datasets/human/chip/encode/ENCSR032BMQ/summary/ENCFF065CFJ.w5 32 2 mean CHIP:H3K4me3:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K4me3/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1545 0 ENCFF710HLV /home/drk/tillage/datasets/human/chip/encode/ENCSR032FUX/summary/ENCFF710HLV.w5 32 2 mean CHIP:H3K4me1:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K4me1/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1546 0 ENCFF225KQB /home/drk/tillage/datasets/human/chip/encode/ENCSR033FDW/summary/ENCFF225KQB.w5 32 2 mean CHIP:POLR2AphosphoS5:stomach male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/stomach male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1547 0 ENCFF817TFH /home/drk/tillage/datasets/human/chip/encode/ENCSR033NHF/summary/ENCFF817TFH.w5 32 2 mean CHIP:POLR2A:upper lobe of left lung male adult (54 years) CHIP ChIP-TF:POLR2A/upper lobe of left lung male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1548 0 ENCFF869IEP /home/drk/tillage/datasets/human/chip/encode/ENCSR033NQK/summary/ENCFF869IEP.w5 32 2 mean CHIP:ZNF830:K562 CHIP ChIP-TF:ZNF830/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1549 0 ENCFF521HRT /home/drk/tillage/datasets/human/chip/encode/ENCSR033OKS/summary/ENCFF521HRT.w5 32 2 mean CHIP:H3K4me3:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K4me3/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1550 0 ENCFF098QMC /home/drk/tillage/datasets/human/chip/encode/ENCSR033VAZ/summary/ENCFF098QMC.w5 32 2 mean CHIP:TARDBP:K562 CHIP ChIP-TF:TARDBP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1551 0 ENCFF385GLF /home/drk/tillage/datasets/human/chip/encode/ENCSR034BEQ/summary/ENCFF385GLF.w5 32 2 mean CHIP:H3K36me3:hepatocyte originated from H9 CHIP ChIP-Histone:H3K36me3/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1552 0 ENCFF711MPU /home/drk/tillage/datasets/human/chip/encode/ENCSR034LMV/summary/ENCFF711MPU.w5 32 2 mean CHIP:H3K9me3:iPS-18c female adult (48 years) CHIP ChIP-Histone:H3K9me3/iPS-18c female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1553 0 ENCFF607JRN /home/drk/tillage/datasets/human/chip/encode/ENCSR034RQV/summary/ENCFF607JRN.w5 32 2 mean CHIP:H3K27ac:Parathyroid adenoma male adult (65 years) CHIP ChIP-Histone:H3K27ac/Parathyroid adenoma male adult (65 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1554 0 ENCFF486EQJ /home/drk/tillage/datasets/human/chip/encode/ENCSR034ZHF/summary/ENCFF486EQJ.w5 32 2 mean CHIP:H3K36me3:esophagus male adult (34 years) CHIP ChIP-Histone:H3K36me3/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1555 0 ENCFF766AYD /home/drk/tillage/datasets/human/chip/encode/ENCSR034ZKE/summary/ENCFF766AYD.w5 32 2 mean CHIP:H3K27ac:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K27ac/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1556 0 ENCFF740JWV /home/drk/tillage/datasets/human/chip/encode/ENCSR035BZI/summary/ENCFF740JWV.w5 32 2 mean CHIP:H4K5ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H4K5ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1557 0 ENCFF958QFI /home/drk/tillage/datasets/human/chip/encode/ENCSR035DUS/summary/ENCFF958QFI.w5 32 2 mean CHIP:H3K4me1:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K4me1/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1558 0 ENCFF244LXR /home/drk/tillage/datasets/human/chip/encode/ENCSR035QNZ/summary/ENCFF244LXR.w5 32 2 mean CHIP:H3K9me3:pancreas male adult (34 years) CHIP ChIP-Histone:H3K9me3/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1559 0 ENCFF721VWV /home/drk/tillage/datasets/human/chip/encode/ENCSR036AQX/summary/ENCFF721VWV.w5 32 2 mean CHIP:H3K9me3:stomach smooth muscle male adult (59 years) CHIP ChIP-Histone:H3K9me3/stomach smooth muscle male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1560 0 ENCFF539YKP /home/drk/tillage/datasets/human/chip/encode/ENCSR036HAT/summary/ENCFF539YKP.w5 32 2 mean CHIP:H3K4me3:spinal cord female embryo (113 days) CHIP ChIP-Histone:H3K4me3/spinal cord female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1561 0 ENCFF889OOM /home/drk/tillage/datasets/human/chip/encode/ENCSR036KFJ/summary/ENCFF889OOM.w5 32 2 mean CHIP:H3K4me1:Loucy CHIP ChIP-Histone:H3K4me1/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1562 0 ENCFF542YUX /home/drk/tillage/datasets/human/chip/encode/ENCSR036NSK/summary/ENCFF542YUX.w5 32 2 mean CHIP:H3K56ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K56ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1563 0 ENCFF561BGB /home/drk/tillage/datasets/human/chip/encode/ENCSR037RJI/summary/ENCFF561BGB.w5 32 2 mean CHIP:H3K4me1:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K4me1/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1564 0 ENCFF832QFE /home/drk/tillage/datasets/human/chip/encode/ENCSR037SNV/summary/ENCFF832QFE.w5 32 2 mean CHIP:H3K27me3:ovary female adult (30 years) CHIP ChIP-Histone:H3K27me3/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1565 0 ENCFF847VYT /home/drk/tillage/datasets/human/chip/encode/ENCSR038DJJ/summary/ENCFF847VYT.w5 32 2 mean CHIP:SMAD1:K562 CHIP ChIP-TF:SMAD1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1566 0 ENCFF967TUN /home/drk/tillage/datasets/human/chip/encode/ENCSR038FOS/summary/ENCFF967TUN.w5 32 2 mean CHIP:CTCF:suprapubic skin male adult (54 years) CHIP ChIP-TF:CTCF/suprapubic skin male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1567 0 ENCFF745YIN /home/drk/tillage/datasets/human/chip/encode/ENCSR038GMB/summary/ENCFF745YIN.w5 32 2 mean CHIP:GABPA:liver male adult (32 years) CHIP ChIP-TF:GABPA/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1568 0 ENCFF337KXY /home/drk/tillage/datasets/human/chip/encode/ENCSR038GYF/summary/ENCFF337KXY.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1569 0 ENCFF475YJV /home/drk/tillage/datasets/human/chip/encode/ENCSR038MKB/summary/ENCFF475YJV.w5 32 2 mean CHIP:H2AK9ac:IMR-90 CHIP ChIP-TF:H2AK9ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1570 0 ENCFF994ANB /home/drk/tillage/datasets/human/chip/encode/ENCSR038OIN/summary/ENCFF994ANB.w5 32 2 mean CHIP:H3K36me3:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K36me3/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1571 0 ENCFF770CZV /home/drk/tillage/datasets/human/chip/encode/ENCSR038RGL/summary/ENCFF770CZV.w5 32 2 mean CHIP:MCM7:K562 CHIP ChIP-TF:MCM7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1572 0 ENCFF367UUW /home/drk/tillage/datasets/human/chip/encode/ENCSR038RXU/summary/ENCFF367UUW.w5 32 2 mean CHIP:eGFP-GABPA:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-GABPA/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1573 0 ENCFF357JHD /home/drk/tillage/datasets/human/chip/encode/ENCSR038XIA/summary/ENCFF357JHD.w5 32 2 mean CHIP:ZNF444:MCF-7 CHIP ChIP-TF:ZNF444/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1574 0 ENCFF757GDD /home/drk/tillage/datasets/human/chip/encode/ENCSR038YKU/summary/ENCFF757GDD.w5 32 2 mean CHIP:POLR2A:stomach female adult (51 year) CHIP ChIP-TF:POLR2A/stomach female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1575 0 ENCFF040ICX /home/drk/tillage/datasets/human/chip/encode/ENCSR039LLX/summary/ENCFF040ICX.w5 32 2 mean CHIP:H3K36me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K36me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1576 0 ENCFF390VRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR039ZLS/summary/ENCFF390VRQ.w5 32 2 mean CHIP:H3K4ac:IMR-90 CHIP ChIP-Histone:H3K4ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1577 0 ENCFF967TET /home/drk/tillage/datasets/human/chip/encode/ENCSR040TUS/summary/ENCFF967TET.w5 32 2 mean CHIP:H3K4me1:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K4me1/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1578 0 ENCFF931NXG /home/drk/tillage/datasets/human/chip/encode/ENCSR041AXL/summary/ENCFF931NXG.w5 32 2 mean CHIP:RFX1:K562 CHIP ChIP-TF:RFX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1579 0 ENCFF328RKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR041UZZ/summary/ENCFF328RKQ.w5 32 2 mean CHIP:H3K27ac:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K27ac/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1580 0 ENCFF569CSW /home/drk/tillage/datasets/human/chip/encode/ENCSR041XML/summary/ENCFF569CSW.w5 32 2 mean CHIP:SRF:GM12878 CHIP ChIP-TF:SRF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1581 0 ENCFF894TNN /home/drk/tillage/datasets/human/chip/encode/ENCSR041ZIQ/summary/ENCFF894TNN.w5 32 2 mean CHIP:eGFP-SALL1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SALL1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1582 0 ENCFF597ZGD /home/drk/tillage/datasets/human/chip/encode/ENCSR042ITN/summary/ENCFF597ZGD.w5 32 2 mean CHIP:H3K4me3:cerebellum male adult (53 years) CHIP ChIP-Histone:H3K4me3/cerebellum male adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1583 0 ENCFF020WCV /home/drk/tillage/datasets/human/chip/encode/ENCSR042ORP/summary/ENCFF020WCV.w5 32 2 mean CHIP:H3K36me3:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K36me3/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1584 0 ENCFF640UBB /home/drk/tillage/datasets/human/chip/encode/ENCSR042RIW/summary/ENCFF640UBB.w5 32 2 mean CHIP:H3K27me3:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K27me3/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1585 0 ENCFF784OCR /home/drk/tillage/datasets/human/chip/encode/ENCSR042TWZ/summary/ENCFF784OCR.w5 32 2 mean CHIP:SNIP1:MCF-7 CHIP ChIP-TF:SNIP1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1586 0 ENCFF153LTQ /home/drk/tillage/datasets/human/chip/encode/ENCSR043SBG/summary/ENCFF153LTQ.w5 32 2 mean CHIP:H3K27me3:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1587 0 ENCFF657WHR /home/drk/tillage/datasets/human/chip/encode/ENCSR043SJS/summary/ENCFF657WHR.w5 32 2 mean CHIP:H3K9me3:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K9me3/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1588 0 ENCFF029GLM /home/drk/tillage/datasets/human/chip/encode/ENCSR044FMM/summary/ENCFF029GLM.w5 32 2 mean CHIP:eGFP-SALL2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SALL2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1589 0 ENCFF431NKO /home/drk/tillage/datasets/human/chip/encode/ENCSR044WCY/summary/ENCFF431NKO.w5 32 2 mean CHIP:H3K9me3:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K9me3/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1590 0 ENCFF958RRJ /home/drk/tillage/datasets/human/chip/encode/ENCSR045HLL/summary/ENCFF958RRJ.w5 32 2 mean CHIP:H3K4me2:neural cell CHIP ChIP-Histone:H3K4me2/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1591 0 ENCFF773MPY /home/drk/tillage/datasets/human/chip/encode/ENCSR045QJH/summary/ENCFF773MPY.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1592 0 ENCFF162UNP /home/drk/tillage/datasets/human/chip/encode/ENCSR045YHA/summary/ENCFF162UNP.w5 32 2 mean CHIP:EZH2:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:EZH2/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1593 0 ENCFF604ZUW /home/drk/tillage/datasets/human/chip/encode/ENCSR046HGP/summary/ENCFF604ZUW.w5 32 2 mean CHIP:EZH2:HCT116 CHIP ChIP-TF:EZH2/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1594 0 ENCFF329YTM /home/drk/tillage/datasets/human/chip/encode/ENCSR046INL/summary/ENCFF329YTM.w5 32 2 mean CHIP:EP300:testis male adult (37 years) CHIP ChIP-TF:EP300/testis male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1595 0 ENCFF087SPC /home/drk/tillage/datasets/human/chip/encode/ENCSR047AFY/summary/ENCFF087SPC.w5 32 2 mean CHIP:H3K27me3:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K27me3/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1596 0 ENCFF064LQT /home/drk/tillage/datasets/human/chip/encode/ENCSR047BUZ/summary/ENCFF064LQT.w5 32 2 mean CHIP:ATF2:HepG2 CHIP ChIP-TF:ATF2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1597 0 ENCFF830DPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR047DRF/summary/ENCFF830DPZ.w5 32 2 mean CHIP:EP300:omental fat pad male adult (54 years) CHIP ChIP-TF:EP300/omental fat pad male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1598 0 ENCFF998ZUC /home/drk/tillage/datasets/human/chip/encode/ENCSR047LSJ/summary/ENCFF998ZUC.w5 32 2 mean CHIP:TAF15:K562 CHIP ChIP-TF:TAF15/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1599 0 ENCFF010NMW /home/drk/tillage/datasets/human/chip/encode/ENCSR047TJL/summary/ENCFF010NMW.w5 32 2 mean CHIP:H3K56ac:H9 CHIP ChIP-Histone:H3K56ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1600 0 ENCFF590LKJ /home/drk/tillage/datasets/human/chip/encode/ENCSR048JDL/summary/ENCFF590LKJ.w5 32 2 mean CHIP:H3K36me3:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K36me3/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1601 0 ENCFF376KWR /home/drk/tillage/datasets/human/chip/encode/ENCSR050FLB/summary/ENCFF376KWR.w5 32 2 mean CHIP:H3K4me1:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1602 0 ENCFF722ASP /home/drk/tillage/datasets/human/chip/encode/ENCSR050SCZ/summary/ENCFF722ASP.w5 32 2 mean CHIP:H3K4me1:trophoblast female embryo (20 weeks) CHIP ChIP-Histone:H3K4me1/trophoblast female embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1603 0 ENCFF589BOI /home/drk/tillage/datasets/human/chip/encode/ENCSR051DXE/summary/ENCFF589BOI.w5 32 2 mean CHIP:FUS:K562 CHIP ChIP-TF:FUS/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1604 0 ENCFF500LDJ /home/drk/tillage/datasets/human/chip/encode/ENCSR051FXN/summary/ENCFF500LDJ.w5 32 2 mean CHIP:H3K4me1:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K4me1/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1605 0 ENCFF322YEU /home/drk/tillage/datasets/human/chip/encode/ENCSR051OUX/summary/ENCFF322YEU.w5 32 2 mean CHIP:NFATC3:K562 CHIP ChIP-TF:NFATC3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1606 0 ENCFF786NJZ /home/drk/tillage/datasets/human/chip/encode/ENCSR051VDI/summary/ENCFF786NJZ.w5 32 2 mean CHIP:H3K79me2:B cell female adult (27 years) CHIP ChIP-Histone:H3K79me2/B cell female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1607 0 ENCFF521VPM /home/drk/tillage/datasets/human/chip/encode/ENCSR052PTN/summary/ENCFF521VPM.w5 32 2 mean CHIP:PCBP1:K562 CHIP ChIP-TF:PCBP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1608 0 ENCFF981FNN /home/drk/tillage/datasets/human/chip/encode/ENCSR052WRV/summary/ENCFF981FNN.w5 32 2 mean CHIP:H3K4me3:DOHH2 CHIP ChIP-Histone:H3K4me3/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1609 0 ENCFF244ONW /home/drk/tillage/datasets/human/chip/encode/ENCSR053PIY/summary/ENCFF244ONW.w5 32 2 mean CHIP:H3K9me3:adrenal gland male adult (37 years) CHIP ChIP-Histone:H3K9me3/adrenal gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1610 0 ENCFF627OFU /home/drk/tillage/datasets/human/chip/encode/ENCSR054BKO/summary/ENCFF627OFU.w5 32 2 mean CHIP:H3K27ac:urinary bladder male adult (34 years) CHIP ChIP-Histone:H3K27ac/urinary bladder male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1611 0 ENCFF771KZZ /home/drk/tillage/datasets/human/chip/encode/ENCSR054FKH/summary/ENCFF771KZZ.w5 32 2 mean CHIP:3xFLAG-RAD21:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RAD21/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1612 0 ENCFF575ZQY /home/drk/tillage/datasets/human/chip/encode/ENCSR054IRX/summary/ENCFF575ZQY.w5 32 2 mean CHIP:H2BK20ac:IMR-90 CHIP ChIP-TF:H2BK20ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1613 0 ENCFF029WKN /home/drk/tillage/datasets/human/chip/encode/ENCSR054PMB/summary/ENCFF029WKN.w5 32 2 mean CHIP:H3K4me1:muscle layer of duodenum male adult (73 years) CHIP ChIP-Histone:H3K4me1/muscle layer of duodenum male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1614 0 ENCFF530IRV /home/drk/tillage/datasets/human/chip/encode/ENCSR055MOQ/summary/ENCFF530IRV.w5 32 2 mean CHIP:H3K36me3:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K36me3/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1615 0 ENCFF458VHN /home/drk/tillage/datasets/human/chip/encode/ENCSR055WBT/summary/ENCFF458VHN.w5 32 2 mean CHIP:POLR2A:body of pancreas male adult (37 years) CHIP ChIP-TF:POLR2A/body of pancreas male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1616 0 ENCFF224YHG /home/drk/tillage/datasets/human/chip/encode/ENCSR055ZZY/summary/ENCFF224YHG.w5 32 2 mean CHIP:H3K9me3:IMR-90 CHIP ChIP-Histone:H3K9me3/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1617 0 ENCFF058NKU /home/drk/tillage/datasets/human/chip/encode/ENCSR056UBA/summary/ENCFF058NKU.w5 32 2 mean CHIP:H3K9ac:MCF-7 CHIP ChIP-Histone:H3K9ac/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1618 0 ENCFF726VVG /home/drk/tillage/datasets/human/chip/encode/ENCSR057BFO/summary/ENCFF726VVG.w5 32 2 mean CHIP:H3K27me3:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K27me3/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1619 0 ENCFF605ROH /home/drk/tillage/datasets/human/chip/encode/ENCSR057BTG/summary/ENCFF605ROH.w5 32 2 mean CHIP:H3K14ac:H1-hESC CHIP ChIP-Histone:H3K14ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1620 0 ENCFF003DXG /home/drk/tillage/datasets/human/chip/encode/ENCSR057BWO/summary/ENCFF003DXG.w5 32 2 mean CHIP:H3K4me3:GM12878 CHIP ChIP-Histone:H3K4me3/GM12878 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1621 0 ENCFF368UUK /home/drk/tillage/datasets/human/chip/encode/ENCSR057MWG/summary/ENCFF368UUK.w5 32 2 mean CHIP:H2AFZ:MCF-7 CHIP ChIP-TF:H2AFZ/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1622 0 ENCFF797WZE /home/drk/tillage/datasets/human/chip/encode/ENCSR057RET/summary/ENCFF797WZE.w5 32 2 mean CHIP:H3K4me3:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K4me3/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1623 0 ENCFF949PZX /home/drk/tillage/datasets/human/chip/encode/ENCSR057XPL/summary/ENCFF949PZX.w5 32 2 mean CHIP:H3K9me3:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K9me3/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1624 0 ENCFF242BZH /home/drk/tillage/datasets/human/chip/encode/ENCSR057YVO/summary/ENCFF242BZH.w5 32 2 mean CHIP:H3K9me3:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K9me3/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1625 0 ENCFF605JJH /home/drk/tillage/datasets/human/chip/encode/ENCSR058AUB/summary/ENCFF605JJH.w5 32 2 mean CHIP:H3K9ac:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K9ac/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1626 0 ENCFF981CZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR058FCG/summary/ENCFF981CZJ.w5 32 2 mean CHIP:H3K27me3:neutrophil CHIP ChIP-Histone:H3K27me3/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1627 0 ENCFF014VAP /home/drk/tillage/datasets/human/chip/encode/ENCSR058SHN/summary/ENCFF014VAP.w5 32 2 mean CHIP:H3K9ac:Karpas-422 CHIP ChIP-Histone:H3K9ac/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1628 0 ENCFF556MMP /home/drk/tillage/datasets/human/chip/encode/ENCSR059MVB/summary/ENCFF556MMP.w5 32 2 mean CHIP:H3K27ac:ACC112 CHIP ChIP-Histone:H3K27ac/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1629 0 ENCFF583VZK /home/drk/tillage/datasets/human/chip/encode/ENCSR060WGK/summary/ENCFF583VZK.w5 32 2 mean CHIP:H3K4me1:OCI-LY7 CHIP ChIP-Histone:H3K4me1/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1630 0 ENCFF293HQH /home/drk/tillage/datasets/human/chip/encode/ENCSR060YIB/summary/ENCFF293HQH.w5 32 2 mean CHIP:H3K36me3:common myeloid progenitor, CD34-positive male adult (42 years) CHIP ChIP-Histone:H3K36me3/common myeloid progenitor, CD34-positive male adult (42 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1631 0 ENCFF067WTK /home/drk/tillage/datasets/human/chip/encode/ENCSR061DGF/summary/ENCFF067WTK.w5 32 2 mean CHIP:NANOG:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:NANOG/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1632 0 ENCFF718SOR /home/drk/tillage/datasets/human/chip/encode/ENCSR061NWO/summary/ENCFF718SOR.w5 32 2 mean CHIP:H3K9ac:endocrine pancreas male adult (46 years) CHIP ChIP-Histone:H3K9ac/endocrine pancreas male adult (46 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1633 0 ENCFF574SCO /home/drk/tillage/datasets/human/chip/encode/ENCSR062ARL/summary/ENCFF574SCO.w5 32 2 mean CHIP:H3K27me3:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K27me3/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1634 0 ENCFF121SET /home/drk/tillage/datasets/human/chip/encode/ENCSR062HDL/summary/ENCFF121SET.w5 32 2 mean CHIP:HSF1:MCF-7 CHIP ChIP-TF:HSF1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1635 0 ENCFF325LPL /home/drk/tillage/datasets/human/chip/encode/ENCSR063WYJ/summary/ENCFF325LPL.w5 32 2 mean CHIP:H3K23me2:H9 CHIP ChIP-Histone:H3K23me2/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1636 0 ENCFF818IGJ /home/drk/tillage/datasets/human/chip/encode/ENCSR064LHU/summary/ENCFF818IGJ.w5 32 2 mean CHIP:H3K4me1:thyroid gland female adult (53 years) CHIP ChIP-Histone:H3K4me1/thyroid gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1637 0 ENCFF827BUN /home/drk/tillage/datasets/human/chip/encode/ENCSR064LJN/summary/ENCFF827BUN.w5 32 2 mean CHIP:RFX5:A549 CHIP ChIP-TF:RFX5/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1638 0 ENCFF847IWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR064VLH/summary/ENCFF847IWJ.w5 32 2 mean CHIP:H3K4me1:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K4me1/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1639 0 ENCFF678FKJ /home/drk/tillage/datasets/human/chip/encode/ENCSR065HOR/summary/ENCFF678FKJ.w5 32 2 mean CHIP:H3K4me1:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K4me1/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1640 0 ENCFF055YXU /home/drk/tillage/datasets/human/chip/encode/ENCSR065IQH/summary/ENCFF055YXU.w5 32 2 mean CHIP:H3K4me1:urinary bladder male adult (34 years) CHIP ChIP-Histone:H3K4me1/urinary bladder male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1641 0 ENCFF085LTS /home/drk/tillage/datasets/human/chip/encode/ENCSR065WUF/summary/ENCFF085LTS.w5 32 2 mean CHIP:eGFP-KLF17:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF17/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1642 0 ENCFF653DDA /home/drk/tillage/datasets/human/chip/encode/ENCSR065XVO/summary/ENCFF653DDA.w5 32 2 mean CHIP:CHAMP1:K562 CHIP ChIP-TF:CHAMP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1643 0 ENCFF383WLC /home/drk/tillage/datasets/human/chip/encode/ENCSR065ZNA/summary/ENCFF383WLC.w5 32 2 mean CHIP:H3K9me3:aorta male adult (34 years) CHIP ChIP-Histone:H3K9me3/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1644 0 ENCFF596ZSJ /home/drk/tillage/datasets/human/chip/encode/ENCSR066BZZ/summary/ENCFF596ZSJ.w5 32 2 mean CHIP:CTCF:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:CTCF/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1645 0 ENCFF348LLH /home/drk/tillage/datasets/human/chip/encode/ENCSR066EBK/summary/ENCFF348LLH.w5 32 2 mean CHIP:FOXA2:HepG2 CHIP ChIP-TF:FOXA2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1646 0 ENCFF793QFH /home/drk/tillage/datasets/human/chip/encode/ENCSR066FXN/summary/ENCFF793QFH.w5 32 2 mean CHIP:HNRNPH1:HepG2 CHIP ChIP-TF:HNRNPH1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1647 0 ENCFF751QZF /home/drk/tillage/datasets/human/chip/encode/ENCSR066GBX/summary/ENCFF751QZF.w5 32 2 mean CHIP:CTCF:right atrium auricular region female adult (53 years) CHIP ChIP-TF:CTCF/right atrium auricular region female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1648 0 ENCFF626DKO /home/drk/tillage/datasets/human/chip/encode/ENCSR066GUY/summary/ENCFF626DKO.w5 32 2 mean CHIP:H3K27ac:placental basal plate male embryo (38 weeks) CHIP ChIP-Histone:H3K27ac/placental basal plate male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1649 0 ENCFF534CCF /home/drk/tillage/datasets/human/chip/encode/ENCSR066TET/summary/ENCFF534CCF.w5 32 2 mean CHIP:RFX1:MCF-7 CHIP ChIP-TF:RFX1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1650 0 ENCFF601KKI /home/drk/tillage/datasets/human/chip/encode/ENCSR067BMB/summary/ENCFF601KKI.w5 32 2 mean CHIP:H3K4me1:lung female embryo (82 days) CHIP ChIP-Histone:H3K4me1/lung female embryo (82 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1651 0 ENCFF469RQU /home/drk/tillage/datasets/human/chip/encode/ENCSR067BNI/summary/ENCFF469RQU.w5 32 2 mean CHIP:H3K36me3:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K36me3/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1652 0 ENCFF866DHV /home/drk/tillage/datasets/human/chip/encode/ENCSR067HGI/summary/ENCFF866DHV.w5 32 2 mean CHIP:CHD2:A549 CHIP ChIP-TF:CHD2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1653 0 ENCFF893NOP /home/drk/tillage/datasets/human/chip/encode/ENCSR068CQX/summary/ENCFF893NOP.w5 32 2 mean CHIP:H3K27me3:heart right ventricle male adult (34 years) CHIP ChIP-Histone:H3K27me3/heart right ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1654 0 ENCFF977JAS /home/drk/tillage/datasets/human/chip/encode/ENCSR068VRA/summary/ENCFF977JAS.w5 32 2 mean CHIP:MCM7:K562 CHIP ChIP-TF:MCM7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1655 0 ENCFF310WCC /home/drk/tillage/datasets/human/chip/encode/ENCSR068WNI/summary/ENCFF310WCC.w5 32 2 mean CHIP:POLR2A:upper lobe of left lung female adult (53 years) CHIP ChIP-TF:POLR2A/upper lobe of left lung female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1656 0 ENCFF898WWB /home/drk/tillage/datasets/human/chip/encode/ENCSR069DPL/summary/ENCFF898WWB.w5 32 2 mean CHIP:EZH2:neural progenitor cell originated from H9 CHIP ChIP-TF:EZH2/neural progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1657 0 ENCFF604LTF /home/drk/tillage/datasets/human/chip/encode/ENCSR069EGE/summary/ENCFF604LTF.w5 32 2 mean CHIP:H3K27ac:transverse colon male adult (54 years) CHIP ChIP-Histone:H3K27ac/transverse colon male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1658 0 ENCFF291BYX /home/drk/tillage/datasets/human/chip/encode/ENCSR069KYE/summary/ENCFF291BYX.w5 32 2 mean CHIP:H3K9me3:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K9me3/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1659 0 ENCFF651IGX /home/drk/tillage/datasets/human/chip/encode/ENCSR069UMW/summary/ENCFF651IGX.w5 32 2 mean CHIP:H3K27ac:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K27ac/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1660 0 ENCFF621RES /home/drk/tillage/datasets/human/chip/encode/ENCSR070GTK/summary/ENCFF621RES.w5 32 2 mean CHIP:H3K9me3:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K9me3/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1661 0 ENCFF978QZR /home/drk/tillage/datasets/human/chip/encode/ENCSR070HWF/summary/ENCFF978QZR.w5 32 2 mean CHIP:eGFP-ZNF768:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF768/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1662 0 ENCFF863VDR /home/drk/tillage/datasets/human/chip/encode/ENCSR071XWO/summary/ENCFF863VDR.w5 32 2 mean CHIP:CTCF:gastrocnemius medialis female adult (51 year) CHIP ChIP-TF:CTCF/gastrocnemius medialis female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1663 0 ENCFF583TMU /home/drk/tillage/datasets/human/chip/encode/ENCSR071YVR/summary/ENCFF583TMU.w5 32 2 mean CHIP:3xFLAG-KMT2B:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KMT2B/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1664 0 ENCFF910GAU /home/drk/tillage/datasets/human/chip/encode/ENCSR072EUE/summary/ENCFF910GAU.w5 32 2 mean CHIP:CTCF:OCI-LY1 CHIP ChIP-TF:CTCF/OCI-LY1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1665 0 ENCFF722YGP /home/drk/tillage/datasets/human/chip/encode/ENCSR072GJV/summary/ENCFF722YGP.w5 32 2 mean CHIP:3xFLAG-HMG20A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HMG20A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1666 0 ENCFF198UIH /home/drk/tillage/datasets/human/chip/encode/ENCSR072LQF/summary/ENCFF198UIH.w5 32 2 mean CHIP:eGFP-ZNF76:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF76/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1667 0 ENCFF629RRF /home/drk/tillage/datasets/human/chip/encode/ENCSR072PWP/summary/ENCFF629RRF.w5 32 2 mean CHIP:ZNF24:GM12878 CHIP ChIP-TF:ZNF24/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1668 0 ENCFF297ZVT /home/drk/tillage/datasets/human/chip/encode/ENCSR072QBN/summary/ENCFF297ZVT.w5 32 2 mean CHIP:H3K36me3:neutrophil male CHIP ChIP-Histone:H3K36me3/neutrophil male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1669 0 ENCFF711WLJ /home/drk/tillage/datasets/human/chip/encode/ENCSR072VUO/summary/ENCFF711WLJ.w5 32 2 mean CHIP:SAFB:K562 CHIP ChIP-TF:SAFB/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1670 0 ENCFF521BFE /home/drk/tillage/datasets/human/chip/encode/ENCSR073YZL/summary/ENCFF521BFE.w5 32 2 mean CHIP:H3K36me3:small intestine female adult (30 years) CHIP ChIP-Histone:H3K36me3/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1671 0 ENCFF983HIO /home/drk/tillage/datasets/human/chip/encode/ENCSR074ECR/summary/ENCFF983HIO.w5 32 2 mean CHIP:H3K27ac:right cardiac atrium male adult (34 years) CHIP ChIP-Histone:H3K27ac/right cardiac atrium male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1672 0 ENCFF772SIL /home/drk/tillage/datasets/human/chip/encode/ENCSR074FPH/summary/ENCFF772SIL.w5 32 2 mean CHIP:H3K4me3:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1673 0 ENCFF786YLI /home/drk/tillage/datasets/human/chip/encode/ENCSR074SFL/summary/ENCFF786YLI.w5 32 2 mean CHIP:CTCF:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-TF:CTCF/esophagus muscularis mucosa female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1674 0 ENCFF292GRD /home/drk/tillage/datasets/human/chip/encode/ENCSR074TRC/summary/ENCFF292GRD.w5 32 2 mean CHIP:H3K79me2:SK-N-SH CHIP ChIP-Histone:H3K79me2/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1675 0 ENCFF051KWV /home/drk/tillage/datasets/human/chip/encode/ENCSR074VAI/summary/ENCFF051KWV.w5 32 2 mean CHIP:eGFP-ZIK1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZIK1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1676 0 ENCFF791ZIC /home/drk/tillage/datasets/human/chip/encode/ENCSR075FNZ/summary/ENCFF791ZIC.w5 32 2 mean CHIP:ZNF622:GM12878 CHIP ChIP-TF:ZNF622/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1677 0 ENCFF088GRY /home/drk/tillage/datasets/human/chip/encode/ENCSR075HTM/summary/ENCFF088GRY.w5 32 2 mean CHIP:HDAC2:K562 CHIP ChIP-TF:HDAC2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1678 0 ENCFF491HAF /home/drk/tillage/datasets/human/chip/encode/ENCSR075OQB/summary/ENCFF491HAF.w5 32 2 mean CHIP:H3K4me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1679 0 ENCFF895GSC /home/drk/tillage/datasets/human/chip/encode/ENCSR075PTL/summary/ENCFF895GSC.w5 32 2 mean CHIP:H3K4me3:muscle layer of duodenum male adult (73 years) CHIP ChIP-Histone:H3K4me3/muscle layer of duodenum male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1680 0 ENCFF603RHJ /home/drk/tillage/datasets/human/chip/encode/ENCSR076CZA/summary/ENCFF603RHJ.w5 32 2 mean CHIP:H3K4me1:heart right ventricle male adult (34 years) CHIP ChIP-Histone:H3K4me1/heart right ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1681 0 ENCFF158CYH /home/drk/tillage/datasets/human/chip/encode/ENCSR076EZB/summary/ENCFF158CYH.w5 32 2 mean CHIP:eGFP-KLF9:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF9/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1682 0 ENCFF149KEA /home/drk/tillage/datasets/human/chip/encode/ENCSR076JBA/summary/ENCFF149KEA.w5 32 2 mean CHIP:H3K9ac:OCI-LY1 CHIP ChIP-Histone:H3K9ac/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1683 0 ENCFF993HZN /home/drk/tillage/datasets/human/chip/encode/ENCSR076KZW/summary/ENCFF993HZN.w5 32 2 mean CHIP:eGFP-ZNF280C:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF280C/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1684 0 ENCFF981JSZ /home/drk/tillage/datasets/human/chip/encode/ENCSR076STK/summary/ENCFF981JSZ.w5 32 2 mean CHIP:H3K27me3:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K27me3/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1685 0 ENCFF939VMB /home/drk/tillage/datasets/human/chip/encode/ENCSR076STQ/summary/ENCFF939VMB.w5 32 2 mean CHIP:eGFP-ZBTB44:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB44/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1686 0 ENCFF657DIW /home/drk/tillage/datasets/human/chip/encode/ENCSR076YPO/summary/ENCFF657DIW.w5 32 2 mean CHIP:RNF2:K562 CHIP ChIP-TF:RNF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1687 0 ENCFF900REU /home/drk/tillage/datasets/human/chip/encode/ENCSR077DKV/summary/ENCFF900REU.w5 32 2 mean CHIP:CREM:K562 CHIP ChIP-TF:CREM/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1688 0 ENCFF236HUG /home/drk/tillage/datasets/human/chip/encode/ENCSR077FZT/summary/ENCFF236HUG.w5 32 2 mean CHIP:H3K4me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1689 0 ENCFF866QGH /home/drk/tillage/datasets/human/chip/encode/ENCSR078BHK/summary/ENCFF866QGH.w5 32 2 mean CHIP:H3K36me3:spleen female adult (30 years) CHIP ChIP-Histone:H3K36me3/spleen female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1690 0 ENCFF275XPP /home/drk/tillage/datasets/human/chip/encode/ENCSR078ZGC/summary/ENCFF275XPP.w5 32 2 mean CHIP:H3K36me3:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K36me3/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1691 0 ENCFF645VAU /home/drk/tillage/datasets/human/chip/encode/ENCSR079WHK/summary/ENCFF645VAU.w5 32 2 mean CHIP:MCM5:K562 CHIP ChIP-TF:MCM5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1692 0 ENCFF507JDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR079ZQI/summary/ENCFF507JDZ.w5 32 2 mean CHIP:H3K4me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1693 0 ENCFF843EUT /home/drk/tillage/datasets/human/chip/encode/ENCSR080CST/summary/ENCFF843EUT.w5 32 2 mean CHIP:eGFP-ZNF639:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF639/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1694 0 ENCFF288IVG /home/drk/tillage/datasets/human/chip/encode/ENCSR080QVO/summary/ENCFF288IVG.w5 32 2 mean CHIP:H3K36me3:right lobe of liver female adult (53 years) CHIP ChIP-Histone:H3K36me3/right lobe of liver female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1695 0 ENCFF574PCV /home/drk/tillage/datasets/human/chip/encode/ENCSR080XEY/summary/ENCFF574PCV.w5 32 2 mean CHIP:FOXA2:liver female child (4 years) CHIP ChIP-TF:FOXA2/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1696 0 ENCFF777EGG /home/drk/tillage/datasets/human/chip/encode/ENCSR080XUB/summary/ENCFF777EGG.w5 32 2 mean CHIP:H3K27me3:CD14-positive monocyte male adult (21 year) CHIP ChIP-Histone:H3K27me3/CD14-positive monocyte male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1697 0 ENCFF119EVR /home/drk/tillage/datasets/human/chip/encode/ENCSR081JRM/summary/ENCFF119EVR.w5 32 2 mean CHIP:H3K18ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K18ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1698 0 ENCFF133RYX /home/drk/tillage/datasets/human/chip/encode/ENCSR081WLS/summary/ENCFF133RYX.w5 32 2 mean CHIP:RAD51:HepG2 CHIP ChIP-TF:RAD51/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1699 0 ENCFF777XEM /home/drk/tillage/datasets/human/chip/encode/ENCSR082NQB/summary/ENCFF777XEM.w5 32 2 mean CHIP:H3K4me3:NCI-H929 CHIP ChIP-Histone:H3K4me3/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1700 0 ENCFF648TPI /home/drk/tillage/datasets/human/chip/encode/ENCSR082SHT/summary/ENCFF648TPI.w5 32 2 mean CHIP:H3K27ac:adipose tissue male adult (34 years) CHIP ChIP-Histone:H3K27ac/adipose tissue male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1701 0 ENCFF057OBD /home/drk/tillage/datasets/human/chip/encode/ENCSR083DXD/summary/ENCFF057OBD.w5 32 2 mean CHIP:H3K9me3:transverse colon male adult (37 years) CHIP ChIP-Histone:H3K9me3/transverse colon male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1702 0 ENCFF129RUF /home/drk/tillage/datasets/human/chip/encode/ENCSR083MAZ/summary/ENCFF129RUF.w5 32 2 mean CHIP:H3K36me3:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K36me3/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1703 0 ENCFF343CJE /home/drk/tillage/datasets/human/chip/encode/ENCSR083QRE/summary/ENCFF343CJE.w5 32 2 mean CHIP:H3K36me3:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K36me3/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1704 0 ENCFF282TMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR083RXV/summary/ENCFF282TMZ.w5 32 2 mean CHIP:H3K36me3:spinal cord female embryo (113 days) CHIP ChIP-Histone:H3K36me3/spinal cord female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1705 0 ENCFF580RBF /home/drk/tillage/datasets/human/chip/encode/ENCSR083ZUY/summary/ENCFF580RBF.w5 32 2 mean CHIP:H3K36me3:stomach smooth muscle male adult (59 years) CHIP ChIP-Histone:H3K36me3/stomach smooth muscle male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1706 0 ENCFF884IIL /home/drk/tillage/datasets/human/chip/encode/ENCSR084RDK/summary/ENCFF884IIL.w5 32 2 mean CHIP:CTCF:DOHH2 CHIP ChIP-TF:CTCF/DOHH2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1707 0 ENCFF302PLG /home/drk/tillage/datasets/human/chip/encode/ENCSR085DDI/summary/ENCFF302PLG.w5 32 2 mean CHIP:NFXL1:K562 CHIP ChIP-TF:NFXL1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1708 0 ENCFF064NJL /home/drk/tillage/datasets/human/chip/encode/ENCSR085FXN/summary/ENCFF064NJL.w5 32 2 mean CHIP:H3K9ac:heart male embryo (105 days) CHIP ChIP-Histone:H3K9ac/heart male embryo (105 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1709 0 ENCFF816UQX /home/drk/tillage/datasets/human/chip/encode/ENCSR085IXF/summary/ENCFF816UQX.w5 32 2 mean CHIP:SP1:liver male adult (32 years) CHIP ChIP-TF:SP1/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1710 0 ENCFF312ZCJ /home/drk/tillage/datasets/human/chip/encode/ENCSR085KRD/summary/ENCFF312ZCJ.w5 32 2 mean CHIP:H3K9me3:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K9me3/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1711 0 ENCFF065RHP /home/drk/tillage/datasets/human/chip/encode/ENCSR085QEV/summary/ENCFF065RHP.w5 32 2 mean CHIP:NBN:K562 CHIP ChIP-TF:NBN/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1712 0 ENCFF055NYH /home/drk/tillage/datasets/human/chip/encode/ENCSR086FIZ/summary/ENCFF055NYH.w5 32 2 mean CHIP:H3K79me2:Parathyroid adenoma male adult (65 years) CHIP ChIP-Histone:H3K79me2/Parathyroid adenoma male adult (65 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1713 0 ENCFF352FRL /home/drk/tillage/datasets/human/chip/encode/ENCSR086FZL/summary/ENCFF352FRL.w5 32 2 mean CHIP:KAT8:K562 CHIP ChIP-TF:KAT8/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1714 0 ENCFF154JOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR086JMA/summary/ENCFF154JOJ.w5 32 2 mean CHIP:H3K9me3:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K9me3/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1715 0 ENCFF627DBB /home/drk/tillage/datasets/human/chip/encode/ENCSR086XCT/summary/ENCFF627DBB.w5 32 2 mean CHIP:H3K27ac:spleen female adult (30 years) CHIP ChIP-Histone:H3K27ac/spleen female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1716 0 ENCFF034GQG /home/drk/tillage/datasets/human/chip/encode/ENCSR086YIH/summary/ENCFF034GQG.w5 32 2 mean CHIP:H3K4me2:MM.1S CHIP ChIP-Histone:H3K4me2/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1717 0 ENCFF199QXO /home/drk/tillage/datasets/human/chip/encode/ENCSR087MJR/summary/ENCFF199QXO.w5 32 2 mean CHIP:H3K9ac:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K9ac/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1718 0 ENCFF753WRC /home/drk/tillage/datasets/human/chip/encode/ENCSR087NSR/summary/ENCFF753WRC.w5 32 2 mean CHIP:3xFLAG-KDM1A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KDM1A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1719 0 ENCFF721URL /home/drk/tillage/datasets/human/chip/encode/ENCSR087PFU/summary/ENCFF721URL.w5 32 2 mean CHIP:H3K4me3:IMR-90 CHIP ChIP-Histone:H3K4me3/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1720 0 ENCFF669GZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR088GXB/summary/ENCFF669GZJ.w5 32 2 mean CHIP:H3K27me3:esophagus male adult (34 years) CHIP ChIP-Histone:H3K27me3/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1721 0 ENCFF294OXN /home/drk/tillage/datasets/human/chip/encode/ENCSR088HZI/summary/ENCFF294OXN.w5 32 2 mean CHIP:EZH2phosphoT487:SU-DHL-6 CHIP ChIP-TF:EZH2phosphoT487/SU-DHL-6 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1722 0 ENCFF439FLW /home/drk/tillage/datasets/human/chip/encode/ENCSR088VUG/summary/ENCFF439FLW.w5 32 2 mean CHIP:EP300:gastroesophageal sphincter female adult (53 years) CHIP ChIP-TF:EP300/gastroesophageal sphincter female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1723 0 ENCFF304IIJ /home/drk/tillage/datasets/human/chip/encode/ENCSR089DTY/summary/ENCFF304IIJ.w5 32 2 mean CHIP:CTCF:omental fat pad male adult (37 years) CHIP ChIP-TF:CTCF/omental fat pad male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1724 0 ENCFF979SUI /home/drk/tillage/datasets/human/chip/encode/ENCSR089NBT/summary/ENCFF979SUI.w5 32 2 mean CHIP:H3K4me1:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K4me1/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1725 0 ENCFF137GVV /home/drk/tillage/datasets/human/chip/encode/ENCSR089TWS/summary/ENCFF137GVV.w5 32 2 mean CHIP:H3K36me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1726 0 ENCFF131BZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR090JNM/summary/ENCFF131BZQ.w5 32 2 mean CHIP:HLTF:K562 CHIP ChIP-TF:HLTF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1727 0 ENCFF431KKT /home/drk/tillage/datasets/human/chip/encode/ENCSR090QTV/summary/ENCFF431KKT.w5 32 2 mean CHIP:H3K9me3:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K9me3/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1728 0 ENCFF588JAY /home/drk/tillage/datasets/human/chip/encode/ENCSR090ZDO/summary/ENCFF588JAY.w5 32 2 mean CHIP:SUZ12:HEK293T CHIP ChIP-TF:SUZ12/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1729 0 ENCFF912GHA /home/drk/tillage/datasets/human/chip/encode/ENCSR091BOQ/summary/ENCFF912GHA.w5 32 2 mean CHIP:SUZ12:GM12878 CHIP ChIP-TF:SUZ12/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1730 0 ENCFF597SVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR091CSG/summary/ENCFF597SVQ.w5 32 2 mean CHIP:POLR2A:gastroesophageal sphincter male adult (54 years) CHIP ChIP-TF:POLR2A/gastroesophageal sphincter male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1731 0 ENCFF415CUC /home/drk/tillage/datasets/human/chip/encode/ENCSR091GVJ/summary/ENCFF415CUC.w5 32 2 mean CHIP:eGFP-ATF1:K562 genetically modified using stable transfection originated from K562 CHIP ChIP-TF:eGFP-ATF1/K562 genetically modified using stable transfection originated from K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1732 0 ENCFF883YBM /home/drk/tillage/datasets/human/chip/encode/ENCSR091JXL/summary/ENCFF883YBM.w5 32 2 mean CHIP:HES1:K562 CHIP ChIP-TF:HES1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1733 0 ENCFF514ZYW /home/drk/tillage/datasets/human/chip/encode/ENCSR091QXP/summary/ENCFF514ZYW.w5 32 2 mean CHIP:H3K36me3:HCT116 CHIP ChIP-Histone:H3K36me3/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1734 0 ENCFF601GYH /home/drk/tillage/datasets/human/chip/encode/ENCSR091TTT/summary/ENCFF601GYH.w5 32 2 mean CHIP:H3K4me1:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K4me1/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1735 0 ENCFF531VJG /home/drk/tillage/datasets/human/chip/encode/ENCSR092OVN/summary/ENCFF531VJG.w5 32 2 mean CHIP:3xFLAG-FOXA3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-FOXA3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1736 0 ENCFF543DHU /home/drk/tillage/datasets/human/chip/encode/ENCSR093FKD/summary/ENCFF543DHU.w5 32 2 mean CHIP:eGFP-CREB3:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-CREB3/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1737 0 ENCFF664AMM /home/drk/tillage/datasets/human/chip/encode/ENCSR093HXE/summary/ENCFF664AMM.w5 32 2 mean CHIP:eGFP-ZNF16:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF16/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1738 0 ENCFF187IFT /home/drk/tillage/datasets/human/chip/encode/ENCSR093SHE/summary/ENCFF187IFT.w5 32 2 mean CHIP:H3K9ac:HCT116 CHIP ChIP-Histone:H3K9ac/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1739 0 ENCFF614MKK /home/drk/tillage/datasets/human/chip/encode/ENCSR094NYB/summary/ENCFF614MKK.w5 32 2 mean CHIP:H3K4me1:brain female embryo (120 days) CHIP ChIP-Histone:H3K4me1/brain female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1740 0 ENCFF017PMA /home/drk/tillage/datasets/human/chip/encode/ENCSR094VCE/summary/ENCFF017PMA.w5 32 2 mean CHIP:H3K4me1:MM.1S CHIP ChIP-Histone:H3K4me1/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1741 0 ENCFF462WGK /home/drk/tillage/datasets/human/chip/encode/ENCSR094VJC/summary/ENCFF462WGK.w5 32 2 mean CHIP:H3K27ac:adrenal gland male adult (37 years) CHIP ChIP-Histone:H3K27ac/adrenal gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1742 0 ENCFF886XRG /home/drk/tillage/datasets/human/chip/encode/ENCSR094WHO/summary/ENCFF886XRG.w5 32 2 mean CHIP:FOXA1:HEK293T CHIP ChIP-TF:FOXA1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1743 0 ENCFF776TQY /home/drk/tillage/datasets/human/chip/encode/ENCSR094ZCF/summary/ENCFF776TQY.w5 32 2 mean CHIP:eGFP-CEBPG:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-CEBPG/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1744 0 ENCFF883NAP /home/drk/tillage/datasets/human/chip/encode/ENCSR095YMD/summary/ENCFF883NAP.w5 32 2 mean CHIP:H3K27ac:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K27ac/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1745 0 ENCFF486AVO /home/drk/tillage/datasets/human/chip/encode/ENCSR096EZX/summary/ENCFF486AVO.w5 32 2 mean CHIP:H3K4me3:kidney female embryo (120 days) CHIP ChIP-Histone:H3K4me3/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1746 0 ENCFF487IOR /home/drk/tillage/datasets/human/chip/encode/ENCSR096IIB/summary/ENCFF487IOR.w5 32 2 mean CHIP:3xFLAG-ETV5:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ETV5/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1747 0 ENCFF327JSZ /home/drk/tillage/datasets/human/chip/encode/ENCSR096KPA/summary/ENCFF327JSZ.w5 32 2 mean CHIP:EZH2phosphoT487:GM23248 CHIP ChIP-TF:EZH2phosphoT487/GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1748 0 ENCFF742SOT /home/drk/tillage/datasets/human/chip/encode/ENCSR096KWU/summary/ENCFF742SOT.w5 32 2 mean CHIP:ZNF207:MCF-7 CHIP ChIP-TF:ZNF207/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1749 0 ENCFF899YMS /home/drk/tillage/datasets/human/chip/encode/ENCSR096LSN/summary/ENCFF899YMS.w5 32 2 mean CHIP:eGFP-ZNF311:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF311/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1750 0 ENCFF670PUL /home/drk/tillage/datasets/human/chip/encode/ENCSR097EEA/summary/ENCFF670PUL.w5 32 2 mean CHIP:POLR2A:gastroesophageal sphincter female adult (53 years) CHIP ChIP-TF:POLR2A/gastroesophageal sphincter female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1751 0 ENCFF224OLU /home/drk/tillage/datasets/human/chip/encode/ENCSR097ORD/summary/ENCFF224OLU.w5 32 2 mean CHIP:H3K9ac:ES-I3 CHIP ChIP-Histone:H3K9ac/ES-I3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1752 0 ENCFF462HVU /home/drk/tillage/datasets/human/chip/encode/ENCSR097PJQ/summary/ENCFF462HVU.w5 32 2 mean CHIP:H3K4me3:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1753 0 ENCFF717QXO /home/drk/tillage/datasets/human/chip/encode/ENCSR098ALO/summary/ENCFF717QXO.w5 32 2 mean CHIP:H3K4me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1754 0 ENCFF586QFS /home/drk/tillage/datasets/human/chip/encode/ENCSR098XMN/summary/ENCFF586QFS.w5 32 2 mean CHIP:RXRA:liver male adult (32 years) CHIP ChIP-TF:RXRA/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1755 0 ENCFF418IUK /home/drk/tillage/datasets/human/chip/encode/ENCSR098YIU/summary/ENCFF418IUK.w5 32 2 mean CHIP:H3K4me1:stomach female embryo (96 days) CHIP ChIP-Histone:H3K4me1/stomach female embryo (96 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1756 0 ENCFF284YVG /home/drk/tillage/datasets/human/chip/encode/ENCSR098YLE/summary/ENCFF284YVG.w5 32 2 mean CHIP:eGFP-PRDM1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1757 0 ENCFF042QGF /home/drk/tillage/datasets/human/chip/encode/ENCSR099NCH/summary/ENCFF042QGF.w5 32 2 mean CHIP:ZNF24:K562 CHIP ChIP-TF:ZNF24/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1758 0 ENCFF197WCC /home/drk/tillage/datasets/human/chip/encode/ENCSR100HGO/summary/ENCFF197WCC.w5 32 2 mean CHIP:H3K9ac:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K9ac/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1759 0 ENCFF369UBB /home/drk/tillage/datasets/human/chip/encode/ENCSR100LWU/summary/ENCFF369UBB.w5 32 2 mean CHIP:H3K36me3:mesodermal cell originated from HUES64 CHIP ChIP-Histone:H3K36me3/mesodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1760 0 ENCFF438RHT /home/drk/tillage/datasets/human/chip/encode/ENCSR100OZR/summary/ENCFF438RHT.w5 32 2 mean CHIP:H3K4me3:kidney male adult (50 years) CHIP ChIP-Histone:H3K4me3/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1761 0 ENCFF360BPK /home/drk/tillage/datasets/human/chip/encode/ENCSR100PNV/summary/ENCFF360BPK.w5 32 2 mean CHIP:H3K27me3:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K27me3/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1762 0 ENCFF448WRF /home/drk/tillage/datasets/human/chip/encode/ENCSR100QDR/summary/ENCFF448WRF.w5 32 2 mean CHIP:H3K4me1:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K4me1/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1763 0 ENCFF414ANN /home/drk/tillage/datasets/human/chip/encode/ENCSR100UQX/summary/ENCFF414ANN.w5 32 2 mean CHIP:TAF9B:K562 CHIP ChIP-TF:TAF9B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1764 0 ENCFF307BSP /home/drk/tillage/datasets/human/chip/encode/ENCSR100YTJ/summary/ENCFF307BSP.w5 32 2 mean CHIP:H3K36me3:lung female embryo (96 days) CHIP ChIP-Histone:H3K36me3/lung female embryo (96 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1765 0 ENCFF494KSM /home/drk/tillage/datasets/human/chip/encode/ENCSR101EEJ/summary/ENCFF494KSM.w5 32 2 mean CHIP:H3K36me3:transverse colon male adult (54 years) CHIP ChIP-Histone:H3K36me3/transverse colon male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1766 0 ENCFF933FCB /home/drk/tillage/datasets/human/chip/encode/ENCSR101FJS/summary/ENCFF933FCB.w5 32 2 mean CHIP:TBL1XR1:HepG2 CHIP ChIP-TF:TBL1XR1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1767 0 ENCFF389WJM /home/drk/tillage/datasets/human/chip/encode/ENCSR101FJU/summary/ENCFF389WJM.w5 32 2 mean CHIP:ZNF384:HepG2 CHIP ChIP-TF:ZNF384/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1768 0 ENCFF417EIW /home/drk/tillage/datasets/human/chip/encode/ENCSR101NFY/summary/ENCFF417EIW.w5 32 2 mean CHIP:H3K36me3:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K36me3/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1769 0 ENCFF653KIU /home/drk/tillage/datasets/human/chip/encode/ENCSR102CSD/summary/ENCFF653KIU.w5 32 2 mean CHIP:CTCF:transverse colon male adult (37 years) CHIP ChIP-TF:CTCF/transverse colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1770 0 ENCFF152NWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR102KIN/summary/ENCFF152NWJ.w5 32 2 mean CHIP:ZMYM3:K562 CHIP ChIP-TF:ZMYM3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1771 0 ENCFF510GVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR103GAK/summary/ENCFF510GVZ.w5 32 2 mean CHIP:eGFP-ZNF175:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF175/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1772 0 ENCFF499VWN /home/drk/tillage/datasets/human/chip/encode/ENCSR103GGR/summary/ENCFF499VWN.w5 32 2 mean CHIP:H3K27me3:CD8-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K27me3/CD8-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1773 0 ENCFF823NMC /home/drk/tillage/datasets/human/chip/encode/ENCSR103HMP/summary/ENCFF823NMC.w5 32 2 mean CHIP:H3K4me3:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me3/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1774 0 ENCFF573NUO /home/drk/tillage/datasets/human/chip/encode/ENCSR103QHX/summary/ENCFF573NUO.w5 32 2 mean CHIP:H3K27me3:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K27me3/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1775 0 ENCFF752PDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR103SZL/summary/ENCFF752PDZ.w5 32 2 mean CHIP:TFAP4:HepG2 CHIP ChIP-TF:TFAP4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1776 0 ENCFF898ZTX /home/drk/tillage/datasets/human/chip/encode/ENCSR103UPR/summary/ENCFF898ZTX.w5 32 2 mean CHIP:POLR2A:gastrocnemius medialis female adult (53 years) CHIP ChIP-TF:POLR2A/gastrocnemius medialis female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1777 0 ENCFF217USF /home/drk/tillage/datasets/human/chip/encode/ENCSR104BSN/summary/ENCFF217USF.w5 32 2 mean CHIP:H3K9me3:radial glial cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K9me3/radial glial cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1778 0 ENCFF810HHZ /home/drk/tillage/datasets/human/chip/encode/ENCSR105EMQ/summary/ENCFF810HHZ.w5 32 2 mean CHIP:H3K27ac:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K27ac/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1779 0 ENCFF903ZFE /home/drk/tillage/datasets/human/chip/encode/ENCSR105NMJ/summary/ENCFF903ZFE.w5 32 2 mean CHIP:H3K9ac:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K9ac/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1780 0 ENCFF615TSW /home/drk/tillage/datasets/human/chip/encode/ENCSR105URN/summary/ENCFF615TSW.w5 32 2 mean CHIP:H3K9me3:spleen female adult (53 years) CHIP ChIP-Histone:H3K9me3/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1781 0 ENCFF974AEG /home/drk/tillage/datasets/human/chip/encode/ENCSR105YNJ/summary/ENCFF974AEG.w5 32 2 mean CHIP:H3K36me3:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K36me3/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1782 0 ENCFF581ZXS /home/drk/tillage/datasets/human/chip/encode/ENCSR106EBH/summary/ENCFF581ZXS.w5 32 2 mean CHIP:eGFP-ZNF366:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF366/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1783 0 ENCFF019EEM /home/drk/tillage/datasets/human/chip/encode/ENCSR106FRG/summary/ENCFF019EEM.w5 32 2 mean CHIP:TAL1:K562 CHIP ChIP-TF:TAL1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1784 0 ENCFF961GMN /home/drk/tillage/datasets/human/chip/encode/ENCSR106GXJ/summary/ENCFF961GMN.w5 32 2 mean CHIP:H3K4me2:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K4me2/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1785 0 ENCFF795RWB /home/drk/tillage/datasets/human/chip/encode/ENCSR107EUS/summary/ENCFF795RWB.w5 32 2 mean CHIP:POLR2A:transverse colon female adult (53 years) CHIP ChIP-TF:POLR2A/transverse colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1786 0 ENCFF720MIG /home/drk/tillage/datasets/human/chip/encode/ENCSR107GRP/summary/ENCFF720MIG.w5 32 2 mean CHIP:MLLT1:K562 CHIP ChIP-TF:MLLT1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1787 0 ENCFF069RMH /home/drk/tillage/datasets/human/chip/encode/ENCSR107RDP/summary/ENCFF069RMH.w5 32 2 mean CHIP:H3K4me3:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K4me3/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1788 0 ENCFF454AJP /home/drk/tillage/datasets/human/chip/encode/ENCSR107RHZ/summary/ENCFF454AJP.w5 32 2 mean CHIP:YBX1:K562 CHIP ChIP-TF:YBX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1789 0 ENCFF421TPV /home/drk/tillage/datasets/human/chip/encode/ENCSR108NVQ/summary/ENCFF421TPV.w5 32 2 mean CHIP:H3K27ac:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27ac/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1790 0 ENCFF308CRA /home/drk/tillage/datasets/human/chip/encode/ENCSR108TYQ/summary/ENCFF308CRA.w5 32 2 mean CHIP:3xFLAG-GATAD1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-GATAD1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1791 0 ENCFF285IPK /home/drk/tillage/datasets/human/chip/encode/ENCSR109NBJ/summary/ENCFF285IPK.w5 32 2 mean CHIP:H3K9me3:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K9me3/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1792 0 ENCFF031HSG /home/drk/tillage/datasets/human/chip/encode/ENCSR109ODF/summary/ENCFF031HSG.w5 32 2 mean CHIP:HES1:MCF-7 CHIP ChIP-TF:HES1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1793 0 ENCFF341OYD /home/drk/tillage/datasets/human/chip/encode/ENCSR109RDK/summary/ENCFF341OYD.w5 32 2 mean CHIP:H3K27me3:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K27me3/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1794 0 ENCFF347RWX /home/drk/tillage/datasets/human/chip/encode/ENCSR109YGM/summary/ENCFF347RWX.w5 32 2 mean CHIP:CREB3L1:K562 CHIP ChIP-TF:CREB3L1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1795 0 ENCFF138TTW /home/drk/tillage/datasets/human/chip/encode/ENCSR110UIN/summary/ENCFF138TTW.w5 32 2 mean CHIP:H3K27me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K27me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1796 0 ENCFF324TEB /home/drk/tillage/datasets/human/chip/encode/ENCSR111KKC/summary/ENCFF324TEB.w5 32 2 mean CHIP:H3K27me3:lung female embryo (120 days) CHIP ChIP-Histone:H3K27me3/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1797 0 ENCFF383GNY /home/drk/tillage/datasets/human/chip/encode/ENCSR111OHT/summary/ENCFF383GNY.w5 32 2 mean CHIP:H3K4me1:liver male adult (31 year) CHIP ChIP-Histone:H3K4me1/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1798 0 ENCFF669NEV /home/drk/tillage/datasets/human/chip/encode/ENCSR111QAW/summary/ENCFF669NEV.w5 32 2 mean CHIP:H3K9ac:SK-N-MC CHIP ChIP-Histone:H3K9ac/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1799 0 ENCFF024TKA /home/drk/tillage/datasets/human/chip/encode/ENCSR111RZN/summary/ENCFF024TKA.w5 32 2 mean CHIP:H3K9me3:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K9me3/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1800 0 ENCFF928JXF /home/drk/tillage/datasets/human/chip/encode/ENCSR111WGZ/summary/ENCFF928JXF.w5 32 2 mean CHIP:H3K4me1:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K4me1/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1801 0 ENCFF853TTW /home/drk/tillage/datasets/human/chip/encode/ENCSR112ALD/summary/ENCFF853TTW.w5 32 2 mean CHIP:CREB1:HepG2 CHIP ChIP-TF:CREB1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1802 0 ENCFF779GAL /home/drk/tillage/datasets/human/chip/encode/ENCSR112RNT/summary/ENCFF779GAL.w5 32 2 mean CHIP:HNRNPLL:K562 CHIP ChIP-TF:HNRNPLL/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1803 0 ENCFF217VXB /home/drk/tillage/datasets/human/chip/encode/ENCSR113AFY/summary/ENCFF217VXB.w5 32 2 mean CHIP:H3K4me1:ovary female adult (30 years) CHIP ChIP-Histone:H3K4me1/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1804 0 ENCFF642OLV /home/drk/tillage/datasets/human/chip/encode/ENCSR113GDB/summary/ENCFF642OLV.w5 32 2 mean CHIP:EZH2:SK-N-MC CHIP ChIP-TF:EZH2/SK-N-MC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1805 0 ENCFF113RTQ /home/drk/tillage/datasets/human/chip/encode/ENCSR113LAS/summary/ENCFF113RTQ.w5 32 2 mean CHIP:MTA2:K562 CHIP ChIP-TF:MTA2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1806 0 ENCFF914CIK /home/drk/tillage/datasets/human/chip/encode/ENCSR113LFZ/summary/ENCFF914CIK.w5 32 2 mean CHIP:H3K27me3:mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K27me3/mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1807 0 ENCFF798TPW /home/drk/tillage/datasets/human/chip/encode/ENCSR113OII/summary/ENCFF798TPW.w5 32 2 mean CHIP:H3K27me3:luminal epithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K27me3/luminal epithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1808 0 ENCFF960LHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR113OKR/summary/ENCFF960LHQ.w5 32 2 mean CHIP:H3K36me3:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K36me3/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1809 0 ENCFF471NDH /home/drk/tillage/datasets/human/chip/encode/ENCSR114GLZ/summary/ENCFF471NDH.w5 32 2 mean CHIP:H3K9ac:SU-DHL-6 CHIP ChIP-Histone:H3K9ac/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1810 0 ENCFF129ETR /home/drk/tillage/datasets/human/chip/encode/ENCSR115BBC/summary/ENCFF129ETR.w5 32 2 mean CHIP:ASH1L:K562 CHIP ChIP-TF:ASH1L/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1811 0 ENCFF831LSX /home/drk/tillage/datasets/human/chip/encode/ENCSR115BLD/summary/ENCFF831LSX.w5 32 2 mean CHIP:KDM1A:HepG2 CHIP ChIP-TF:KDM1A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1812 0 ENCFF593GVE /home/drk/tillage/datasets/human/chip/encode/ENCSR115BXL/summary/ENCFF593GVE.w5 32 2 mean CHIP:H3K4me1:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1813 0 ENCFF601TLP /home/drk/tillage/datasets/human/chip/encode/ENCSR115GFR/summary/ENCFF601TLP.w5 32 2 mean CHIP:H3K9me3:T-cell male adult (21 year) CHIP ChIP-Histone:H3K9me3/T-cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1814 0 ENCFF887OHO /home/drk/tillage/datasets/human/chip/encode/ENCSR115PIK/summary/ENCFF887OHO.w5 32 2 mean CHIP:3xFLAG-MIER2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MIER2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1815 0 ENCFF720XZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR115PQP/summary/ENCFF720XZQ.w5 32 2 mean CHIP:H3K4ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K4ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1816 0 ENCFF229VFD /home/drk/tillage/datasets/human/chip/encode/ENCSR115SMW/summary/ENCFF229VFD.w5 32 2 mean CHIP:PKNOX1:K562 CHIP ChIP-TF:PKNOX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1817 0 ENCFF939SGH /home/drk/tillage/datasets/human/chip/encode/ENCSR115TSA/summary/ENCFF939SGH.w5 32 2 mean CHIP:H3K4me1:spleen female adult (30 years) CHIP ChIP-Histone:H3K4me1/spleen female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1818 0 ENCFF783NGV /home/drk/tillage/datasets/human/chip/encode/ENCSR115VDV/summary/ENCFF783NGV.w5 32 2 mean CHIP:H3K4me1:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K4me1/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1819 0 ENCFF819TJP /home/drk/tillage/datasets/human/chip/encode/ENCSR116QUR/summary/ENCFF819TJP.w5 32 2 mean CHIP:CSDE1:MCF-7 CHIP ChIP-TF:CSDE1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1820 0 ENCFF984WNZ /home/drk/tillage/datasets/human/chip/encode/ENCSR116RGC/summary/ENCFF984WNZ.w5 32 2 mean CHIP:EP300:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-TF:EP300/esophagus muscularis mucosa female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1821 0 ENCFF390RDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR117CHD/summary/ENCFF390RDZ.w5 32 2 mean CHIP:3xFLAG-HOMEZ:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HOMEZ/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1822 0 ENCFF885FVT /home/drk/tillage/datasets/human/chip/encode/ENCSR117IJB/summary/ENCFF885FVT.w5 32 2 mean CHIP:H3K4me1:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K4me1/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1823 0 ENCFF094AZY /home/drk/tillage/datasets/human/chip/encode/ENCSR117IQD/summary/ENCFF094AZY.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1824 0 ENCFF676UXN /home/drk/tillage/datasets/human/chip/encode/ENCSR117KWH/summary/ENCFF676UXN.w5 32 2 mean CHIP:ZNF207:GM12878 CHIP ChIP-TF:ZNF207/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1825 0 ENCFF134JNY /home/drk/tillage/datasets/human/chip/encode/ENCSR117WTM/summary/ENCFF134JNY.w5 32 2 mean CHIP:eGFP-ZNF24:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF24/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1826 0 ENCFF835XJJ /home/drk/tillage/datasets/human/chip/encode/ENCSR119ULQ/summary/ENCFF835XJJ.w5 32 2 mean CHIP:NCOA4:K562 CHIP ChIP-TF:NCOA4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1827 0 ENCFF530LGP /home/drk/tillage/datasets/human/chip/encode/ENCSR119VCX/summary/ENCFF530LGP.w5 32 2 mean CHIP:PHF21A:K562 CHIP ChIP-TF:PHF21A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1828 0 ENCFF242LAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR120LGC/summary/ENCFF242LAQ.w5 32 2 mean CHIP:H3K36me3:MM.1S CHIP ChIP-Histone:H3K36me3/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1829 0 ENCFF187MZK /home/drk/tillage/datasets/human/chip/encode/ENCSR120MPG/summary/ENCFF187MZK.w5 32 2 mean CHIP:PRDM10:K562 CHIP ChIP-TF:PRDM10/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1830 0 ENCFF511ZZY /home/drk/tillage/datasets/human/chip/encode/ENCSR120ZZJ/summary/ENCFF511ZZY.w5 32 2 mean CHIP:H3K4me3:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1831 0 ENCFF192FUE /home/drk/tillage/datasets/human/chip/encode/ENCSR121INC/summary/ENCFF192FUE.w5 32 2 mean CHIP:H3K9ac:SK-N-SH CHIP ChIP-Histone:H3K9ac/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1832 0 ENCFF738RCM /home/drk/tillage/datasets/human/chip/encode/ENCSR121PFY/summary/ENCFF738RCM.w5 32 2 mean CHIP:CDC5L:K562 CHIP ChIP-TF:CDC5L/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1833 0 ENCFF888CPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR121RSS/summary/ENCFF888CPZ.w5 32 2 mean CHIP:H3K4me1:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K4me1/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1834 0 ENCFF053EPF /home/drk/tillage/datasets/human/chip/encode/ENCSR122EYE/summary/ENCFF053EPF.w5 32 2 mean CHIP:POLR2A:stomach male adult (54 years) CHIP ChIP-TF:POLR2A/stomach male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1835 0 ENCFF560BAF /home/drk/tillage/datasets/human/chip/encode/ENCSR122IJJ/summary/ENCFF560BAF.w5 32 2 mean CHIP:H3K4me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1836 0 ENCFF278UPX /home/drk/tillage/datasets/human/chip/encode/ENCSR122LGV/summary/ENCFF278UPX.w5 32 2 mean CHIP:POLR2A:prostate gland male adult (54 years) CHIP ChIP-TF:POLR2A/prostate gland male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1837 0 ENCFF151YZO /home/drk/tillage/datasets/human/chip/encode/ENCSR122LOZ/summary/ENCFF151YZO.w5 32 2 mean CHIP:H3K4me3:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K4me3/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1838 0 ENCFF472YNZ /home/drk/tillage/datasets/human/chip/encode/ENCSR123HEE/summary/ENCFF472YNZ.w5 32 2 mean CHIP:H3K27ac:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K27ac/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1839 0 ENCFF231XXF /home/drk/tillage/datasets/human/chip/encode/ENCSR123JZO/summary/ENCFF231XXF.w5 32 2 mean CHIP:H2BK15ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H2BK15ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1840 0 ENCFF228HNI /home/drk/tillage/datasets/human/chip/encode/ENCSR124AIG/summary/ENCFF228HNI.w5 32 2 mean CHIP:FOS:IMR-90 CHIP ChIP-TF:FOS/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1841 0 ENCFF492DSP /home/drk/tillage/datasets/human/chip/encode/ENCSR124BJR/summary/ENCFF492DSP.w5 32 2 mean CHIP:ETV6:K562 CHIP ChIP-TF:ETV6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1842 0 ENCFF575IJZ /home/drk/tillage/datasets/human/chip/encode/ENCSR124DYB/summary/ENCFF575IJZ.w5 32 2 mean CHIP:H2AFZ:IMR-90 CHIP ChIP-TF:H2AFZ/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1843 0 ENCFF579UBJ /home/drk/tillage/datasets/human/chip/encode/ENCSR124MTJ/summary/ENCFF579UBJ.w5 32 2 mean CHIP:H3K4me2:GM23248 CHIP ChIP-Histone:H3K4me2/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1844 0 ENCFF688DBU /home/drk/tillage/datasets/human/chip/encode/ENCSR124VOE/summary/ENCFF688DBU.w5 32 2 mean CHIP:H3K27ac:neural cell CHIP ChIP-Histone:H3K27ac/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1845 0 ENCFF127MNH /home/drk/tillage/datasets/human/chip/encode/ENCSR125DAD/summary/ENCFF127MNH.w5 32 2 mean CHIP:3xFLAG-MLX:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MLX/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1846 0 ENCFF560IHK /home/drk/tillage/datasets/human/chip/encode/ENCSR125DKL/summary/ENCFF560IHK.w5 32 2 mean CHIP:CTCF:SU-DHL-6 CHIP ChIP-TF:CTCF/SU-DHL-6 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1847 0 ENCFF527AQC /home/drk/tillage/datasets/human/chip/encode/ENCSR125DNC/summary/ENCFF527AQC.w5 32 2 mean CHIP:eGFP-ZNF394:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF394/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1848 0 ENCFF118RYN /home/drk/tillage/datasets/human/chip/encode/ENCSR125IJY/summary/ENCFF118RYN.w5 32 2 mean CHIP:H3F3A:SK-N-SH CHIP ChIP-Histone:H3F3A/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1849 0 ENCFF573GSH /home/drk/tillage/datasets/human/chip/encode/ENCSR125NBL/summary/ENCFF573GSH.w5 32 2 mean CHIP:CTCF:neural progenitor cell originated from H9 CHIP ChIP-TF:CTCF/neural progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1850 0 ENCFF406DST /home/drk/tillage/datasets/human/chip/encode/ENCSR125ULS/summary/ENCFF406DST.w5 32 2 mean CHIP:eGFP-ZNF561:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF561/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1851 0 ENCFF764OEC /home/drk/tillage/datasets/human/chip/encode/ENCSR125ZYC/summary/ENCFF764OEC.w5 32 2 mean CHIP:eGFP-KLF9:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-KLF9/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1852 0 ENCFF260TTI /home/drk/tillage/datasets/human/chip/encode/ENCSR126BGU/summary/ENCFF260TTI.w5 32 2 mean CHIP:H3K4me2:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K4me2/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1853 0 ENCFF270SIE /home/drk/tillage/datasets/human/chip/encode/ENCSR126FJY/summary/ENCFF270SIE.w5 32 2 mean CHIP:H3K36me3:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K36me3/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1854 0 ENCFF069ETX /home/drk/tillage/datasets/human/chip/encode/ENCSR126FZN/summary/ENCFF069ETX.w5 32 2 mean CHIP:eGFP-PTRF:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-PTRF/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1855 0 ENCFF008ABX /home/drk/tillage/datasets/human/chip/encode/ENCSR126YEB/summary/ENCFF008ABX.w5 32 2 mean CHIP:FOXA1:MCF-7 CHIP ChIP-TF:FOXA1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1856 0 ENCFF791HEH /home/drk/tillage/datasets/human/chip/encode/ENCSR127MFA/summary/ENCFF791HEH.w5 32 2 mean CHIP:H3K36me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K36me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1857 0 ENCFF080SCQ /home/drk/tillage/datasets/human/chip/encode/ENCSR127ZSP/summary/ENCFF080SCQ.w5 32 2 mean CHIP:H3K36me3:tibial artery female adult (53 years) CHIP ChIP-Histone:H3K36me3/tibial artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1858 0 ENCFF659KLD /home/drk/tillage/datasets/human/chip/encode/ENCSR128IYN/summary/ENCFF659KLD.w5 32 2 mean CHIP:SNRNP70:HepG2 CHIP ChIP-TF:SNRNP70/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1859 0 ENCFF362YRX /home/drk/tillage/datasets/human/chip/encode/ENCSR128QKM/summary/ENCFF362YRX.w5 32 2 mean CHIP:H3K4me3:muscle of leg female embryo (110 days) CHIP ChIP-Histone:H3K4me3/muscle of leg female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1860 0 ENCFF182VPC /home/drk/tillage/datasets/human/chip/encode/ENCSR128VHV/summary/ENCFF182VPC.w5 32 2 mean CHIP:H3K27me3:aorta female adult (30 years) CHIP ChIP-Histone:H3K27me3/aorta female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1861 0 ENCFF710OZO /home/drk/tillage/datasets/human/chip/encode/ENCSR129NCV/summary/ENCFF710OZO.w5 32 2 mean CHIP:H3K4me3:stomach male adult (34 years) CHIP ChIP-Histone:H3K4me3/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1862 0 ENCFF571UTM /home/drk/tillage/datasets/human/chip/encode/ENCSR130EML/summary/ENCFF571UTM.w5 32 2 mean CHIP:H3K4ac:H1-hESC CHIP ChIP-Histone:H3K4ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1863 0 ENCFF954FLY /home/drk/tillage/datasets/human/chip/encode/ENCSR130HEG/summary/ENCFF954FLY.w5 32 2 mean CHIP:COPS2:K562 CHIP ChIP-TF:COPS2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1864 0 ENCFF536HIX /home/drk/tillage/datasets/human/chip/encode/ENCSR130IMV/summary/ENCFF536HIX.w5 32 2 mean CHIP:H3K4me1:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K4me1/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1865 0 ENCFF204RHD /home/drk/tillage/datasets/human/chip/encode/ENCSR130PDE/summary/ENCFF204RHD.w5 32 2 mean CHIP:eGFP-NR4A1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NR4A1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1866 0 ENCFF384DPM /home/drk/tillage/datasets/human/chip/encode/ENCSR130PLZ/summary/ENCFF384DPM.w5 32 2 mean CHIP:H3K4me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1867 0 ENCFF432XEL /home/drk/tillage/datasets/human/chip/encode/ENCSR130VQL/summary/ENCFF432XEL.w5 32 2 mean CHIP:3xFLAG-PPARG:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-PPARG/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1868 0 ENCFF558MZX /home/drk/tillage/datasets/human/chip/encode/ENCSR131EED/summary/ENCFF558MZX.w5 32 2 mean CHIP:H3K36me3:placenta female embryo (113 days) CHIP ChIP-Histone:H3K36me3/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1869 0 ENCFF160ISV /home/drk/tillage/datasets/human/chip/encode/ENCSR131FFJ/summary/ENCFF160ISV.w5 32 2 mean CHIP:EZH2:GM23248 CHIP ChIP-TF:EZH2/GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1870 0 ENCFF757YCH /home/drk/tillage/datasets/human/chip/encode/ENCSR132XRW/summary/ENCFF757YCH.w5 32 2 mean CHIP:POLR2A:transverse colon male adult (54 years) CHIP ChIP-TF:POLR2A/transverse colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1871 0 ENCFF026WLD /home/drk/tillage/datasets/human/chip/encode/ENCSR133NBJ/summary/ENCFF026WLD.w5 32 2 mean CHIP:H3K27ac:stomach female adult (53 years) CHIP ChIP-Histone:H3K27ac/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1872 0 ENCFF958RCA /home/drk/tillage/datasets/human/chip/encode/ENCSR133QBG/summary/ENCFF958RCA.w5 32 2 mean CHIP:H3K9me3:prostate male adult (54 years) CHIP ChIP-Histone:H3K9me3/prostate male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1873 0 ENCFF820FLV /home/drk/tillage/datasets/human/chip/encode/ENCSR134HVI/summary/ENCFF820FLV.w5 32 2 mean CHIP:H3K27me3:mammary epithelial cell female adult (18 years) CHIP ChIP-Histone:H3K27me3/mammary epithelial cell female adult (18 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1874 0 ENCFF416FPU /home/drk/tillage/datasets/human/chip/encode/ENCSR134QIE/summary/ENCFF416FPU.w5 32 2 mean CHIP:eGFP-ZFP3:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFP3/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1875 0 ENCFF478YJL /home/drk/tillage/datasets/human/chip/encode/ENCSR135ANT/summary/ENCFF478YJL.w5 32 2 mean CHIP:NRF1:MCF-7 CHIP ChIP-TF:NRF1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1876 0 ENCFF847NNM /home/drk/tillage/datasets/human/chip/encode/ENCSR136NUH/summary/ENCFF847NNM.w5 32 2 mean CHIP:H3K36me3:radial glial cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K36me3/radial glial cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1877 0 ENCFF707FBC /home/drk/tillage/datasets/human/chip/encode/ENCSR136QKZ/summary/ENCFF707FBC.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1878 0 ENCFF568YMA /home/drk/tillage/datasets/human/chip/encode/ENCSR136VLK/summary/ENCFF568YMA.w5 32 2 mean CHIP:H3K27me3:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K27me3/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1879 0 ENCFF440JSE /home/drk/tillage/datasets/human/chip/encode/ENCSR136ZLJ/summary/ENCFF440JSE.w5 32 2 mean CHIP:H3K4me1:ectodermal cell originated from embryonic stem cell CHIP ChIP-Histone:H3K4me1/ectodermal cell originated from embryonic stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1880 0 ENCFF446UUC /home/drk/tillage/datasets/human/chip/encode/ENCSR136ZNV/summary/ENCFF446UUC.w5 32 2 mean CHIP:H3K36me3:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K36me3/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1881 0 ENCFF413WUI /home/drk/tillage/datasets/human/chip/encode/ENCSR137ZMQ/summary/ENCFF413WUI.w5 32 2 mean CHIP:REST:K562 CHIP ChIP-TF:REST/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1882 0 ENCFF701MUZ /home/drk/tillage/datasets/human/chip/encode/ENCSR138DOM/summary/ENCFF701MUZ.w5 32 2 mean CHIP:H3K27ac:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K27ac/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1883 0 ENCFF786JIS /home/drk/tillage/datasets/human/chip/encode/ENCSR138FUZ/summary/ENCFF786JIS.w5 32 2 mean CHIP:RNF2:K562 CHIP ChIP-TF:RNF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1884 0 ENCFF385ABB /home/drk/tillage/datasets/human/chip/encode/ENCSR138RCE/summary/ENCFF385ABB.w5 32 2 mean CHIP:eGFP-ZNF132:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF132/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1885 0 ENCFF308NHY /home/drk/tillage/datasets/human/chip/encode/ENCSR138SFL/summary/ENCFF308NHY.w5 32 2 mean CHIP:MCM2:K562 CHIP ChIP-TF:MCM2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1886 0 ENCFF902BRN /home/drk/tillage/datasets/human/chip/encode/ENCSR138YYY/summary/ENCFF902BRN.w5 32 2 mean CHIP:GABPB1:K562 CHIP ChIP-TF:GABPB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1887 0 ENCFF486KWO /home/drk/tillage/datasets/human/chip/encode/ENCSR139PIA/summary/ENCFF486KWO.w5 32 2 mean CHIP:H3K27me3:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K27me3/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1888 0 ENCFF381JBK /home/drk/tillage/datasets/human/chip/encode/ENCSR139TLA/summary/ENCFF381JBK.w5 32 2 mean CHIP:H3K4me3:ovary female adult (30 years) CHIP ChIP-Histone:H3K4me3/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1889 0 ENCFF218QWU /home/drk/tillage/datasets/human/chip/encode/ENCSR140DSL/summary/ENCFF218QWU.w5 32 2 mean CHIP:MAFF:HeLa-S3 CHIP ChIP-TF:MAFF/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1890 0 ENCFF771CRO /home/drk/tillage/datasets/human/chip/encode/ENCSR141PZA/summary/ENCFF771CRO.w5 32 2 mean CHIP:eGFP-SP3:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SP3/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1891 0 ENCFF087QEY /home/drk/tillage/datasets/human/chip/encode/ENCSR142BBV/summary/ENCFF087QEY.w5 32 2 mean CHIP:H3K36me3:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K36me3/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1892 0 ENCFF559CVP /home/drk/tillage/datasets/human/chip/encode/ENCSR142IGM/summary/ENCFF559CVP.w5 32 2 mean CHIP:3xFLAG-CEBPA:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-CEBPA/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1893 0 ENCFF292XMX /home/drk/tillage/datasets/human/chip/encode/ENCSR142OBQ/summary/ENCFF292XMX.w5 32 2 mean CHIP:H3K36me3:heart right ventricle male adult (34 years) CHIP ChIP-Histone:H3K36me3/heart right ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1894 0 ENCFF950NNK /home/drk/tillage/datasets/human/chip/encode/ENCSR142SQX/summary/ENCFF950NNK.w5 32 2 mean CHIP:POLR2A:uterus female adult (53 years) CHIP ChIP-TF:POLR2A/uterus female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1895 0 ENCFF786YHA /home/drk/tillage/datasets/human/chip/encode/ENCSR142YYA/summary/ENCFF786YHA.w5 32 2 mean CHIP:EWSR1:K562 CHIP ChIP-TF:EWSR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1896 0 ENCFF228NZS /home/drk/tillage/datasets/human/chip/encode/ENCSR143CEO/summary/ENCFF228NZS.w5 32 2 mean CHIP:ZC3H8:K562 CHIP ChIP-TF:ZC3H8/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1897 0 ENCFF942CMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR143MZL/summary/ENCFF942CMQ.w5 32 2 mean CHIP:H3K4me3:brain male embryo (122 days) CHIP ChIP-Histone:H3K4me3/brain male embryo (122 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1898 0 ENCFF058CLL /home/drk/tillage/datasets/human/chip/encode/ENCSR143RMH/summary/ENCFF058CLL.w5 32 2 mean CHIP:H3K27me3:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K27me3/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1899 0 ENCFF761ZQJ /home/drk/tillage/datasets/human/chip/encode/ENCSR144NDE/summary/ENCFF761ZQJ.w5 32 2 mean CHIP:H3K27me3:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1900 0 ENCFF030VBS /home/drk/tillage/datasets/human/chip/encode/ENCSR144RXL/summary/ENCFF030VBS.w5 32 2 mean CHIP:H3K36me3:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K36me3/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1901 0 ENCFF529UHP /home/drk/tillage/datasets/human/chip/encode/ENCSR145BHD/summary/ENCFF529UHP.w5 32 2 mean CHIP:NFRKB:HepG2 CHIP ChIP-TF:NFRKB/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1902 0 ENCFF159FEG /home/drk/tillage/datasets/human/chip/encode/ENCSR145CXH/summary/ENCFF159FEG.w5 32 2 mean CHIP:TARDBP:HepG2 CHIP ChIP-TF:TARDBP/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1903 0 ENCFF308UOK /home/drk/tillage/datasets/human/chip/encode/ENCSR145TSJ/summary/ENCFF308UOK.w5 32 2 mean CHIP:ATF4:K562 CHIP ChIP-TF:ATF4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1904 0 ENCFF928WEU /home/drk/tillage/datasets/human/chip/encode/ENCSR145XQO/summary/ENCFF928WEU.w5 32 2 mean CHIP:HDGF:GM12878 CHIP ChIP-TF:HDGF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1905 0 ENCFF853FVW /home/drk/tillage/datasets/human/chip/encode/ENCSR146BGM/summary/ENCFF853FVW.w5 32 2 mean CHIP:CTCF:gastroesophageal sphincter female adult (51 year) CHIP ChIP-TF:CTCF/gastroesophageal sphincter female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1906 0 ENCFF673DEB /home/drk/tillage/datasets/human/chip/encode/ENCSR146DAL/summary/ENCFF673DEB.w5 32 2 mean CHIP:H3K4me3:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K4me3/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1907 0 ENCFF307HCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR146JFX/summary/ENCFF307HCZ.w5 32 2 mean CHIP:H3K4me1:skeletal muscle tissue CHIP ChIP-Histone:H3K4me1/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1908 0 ENCFF509ZSV /home/drk/tillage/datasets/human/chip/encode/ENCSR146JLC/summary/ENCFF509ZSV.w5 32 2 mean CHIP:H3K9ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K9ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1909 0 ENCFF985OQZ /home/drk/tillage/datasets/human/chip/encode/ENCSR146KXZ/summary/ENCFF985OQZ.w5 32 2 mean CHIP:H3K9me3:brain female embryo (17 weeks) CHIP ChIP-Histone:H3K9me3/brain female embryo (17 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1910 0 ENCFF872WHG /home/drk/tillage/datasets/human/chip/encode/ENCSR146NLL/summary/ENCFF872WHG.w5 32 2 mean CHIP:eGFP-REPIN1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-REPIN1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1911 0 ENCFF154YUA /home/drk/tillage/datasets/human/chip/encode/ENCSR146TGM/summary/ENCFF154YUA.w5 32 2 mean CHIP:H3K9ac:kidney male adult (50 years) CHIP ChIP-Histone:H3K9ac/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1912 0 ENCFF913FVO /home/drk/tillage/datasets/human/chip/encode/ENCSR147GWR/summary/ENCFF913FVO.w5 32 2 mean CHIP:H3K27me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1913 0 ENCFF233SKC /home/drk/tillage/datasets/human/chip/encode/ENCSR147PYL/summary/ENCFF233SKC.w5 32 2 mean CHIP:POLR2A:esophagus squamous epithelium female adult (53 years) CHIP ChIP-TF:POLR2A/esophagus squamous epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1914 0 ENCFF614KES /home/drk/tillage/datasets/human/chip/encode/ENCSR147VKD/summary/ENCFF614KES.w5 32 2 mean CHIP:EP300:subcutaneous adipose tissue female adult (53 years) CHIP ChIP-TF:EP300/subcutaneous adipose tissue female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1915 0 ENCFF189NUC /home/drk/tillage/datasets/human/chip/encode/ENCSR148FWR/summary/ENCFF189NUC.w5 32 2 mean CHIP:H3K4me1:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K4me1/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1916 0 ENCFF830TIW /home/drk/tillage/datasets/human/chip/encode/ENCSR149XIH/summary/ENCFF830TIW.w5 32 2 mean CHIP:H3K4me3:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K4me3/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1917 0 ENCFF057THX /home/drk/tillage/datasets/human/chip/encode/ENCSR149ZBI/summary/ENCFF057THX.w5 32 2 mean CHIP:eGFP-ZNF584:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF584/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1918 0 ENCFF911PGT /home/drk/tillage/datasets/human/chip/encode/ENCSR150GLE/summary/ENCFF911PGT.w5 32 2 mean CHIP:H3K9me3:esophagus male adult (34 years) CHIP ChIP-Histone:H3K9me3/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1919 0 ENCFF214MPJ /home/drk/tillage/datasets/human/chip/encode/ENCSR150GWJ/summary/ENCFF214MPJ.w5 32 2 mean CHIP:H3K4me1:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K4me1/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1920 0 ENCFF680UAP /home/drk/tillage/datasets/human/chip/encode/ENCSR150MZT/summary/ENCFF680UAP.w5 32 2 mean CHIP:H3K36me3:muscle of leg female embryo (110 days) CHIP ChIP-Histone:H3K36me3/muscle of leg female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1921 0 ENCFF630HIW /home/drk/tillage/datasets/human/chip/encode/ENCSR150QXE/summary/ENCFF630HIW.w5 32 2 mean CHIP:H3K27ac:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K27ac/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1922 0 ENCFF106GWO /home/drk/tillage/datasets/human/chip/encode/ENCSR150YAU/summary/ENCFF106GWO.w5 32 2 mean CHIP:H3K36me3:sigmoid colon female adult (53 years) CHIP ChIP-Histone:H3K36me3/sigmoid colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1923 0 ENCFF808CTN /home/drk/tillage/datasets/human/chip/encode/ENCSR151NQL/summary/ENCFF808CTN.w5 32 2 mean CHIP:AGO2:HepG2 CHIP ChIP-TF:AGO2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1924 0 ENCFF894YHR /home/drk/tillage/datasets/human/chip/encode/ENCSR152GST/summary/ENCFF894YHR.w5 32 2 mean CHIP:H3K9ac:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K9ac/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1925 0 ENCFF723TXS /home/drk/tillage/datasets/human/chip/encode/ENCSR152QRE/summary/ENCFF723TXS.w5 32 2 mean CHIP:H3K4me1:SK-N-MC CHIP ChIP-Histone:H3K4me1/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1926 0 ENCFF310YOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR152UWC/summary/ENCFF310YOJ.w5 32 2 mean CHIP:H3K9ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K9ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1927 0 ENCFF266MQE /home/drk/tillage/datasets/human/chip/encode/ENCSR152YYY/summary/ENCFF266MQE.w5 32 2 mean CHIP:H4K20me1:PC-9 CHIP ChIP-TF:H4K20me1/PC-9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1928 0 ENCFF681BXS /home/drk/tillage/datasets/human/chip/encode/ENCSR153AGA/summary/ENCFF681BXS.w5 32 2 mean CHIP:POLR2A:lower leg skin male adult (54 years) CHIP ChIP-TF:POLR2A/lower leg skin male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1929 0 ENCFF557FCH /home/drk/tillage/datasets/human/chip/encode/ENCSR153SGD/summary/ENCFF557FCH.w5 32 2 mean CHIP:H3K4me3:HUES48 CHIP ChIP-Histone:H3K4me3/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1930 0 ENCFF782QHB /home/drk/tillage/datasets/human/chip/encode/ENCSR154EIH/summary/ENCFF782QHB.w5 32 2 mean CHIP:TRIP13:K562 CHIP ChIP-TF:TRIP13/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1931 0 ENCFF314DQL /home/drk/tillage/datasets/human/chip/encode/ENCSR154GUK/summary/ENCFF314DQL.w5 32 2 mean CHIP:POLR2A:tibial nerve female adult (51 year) CHIP ChIP-TF:POLR2A/tibial nerve female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1932 0 ENCFF079OZR /home/drk/tillage/datasets/human/chip/encode/ENCSR154HDX/summary/ENCFF079OZR.w5 32 2 mean CHIP:H3K79me2:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K79me2/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1933 0 ENCFF981KCA /home/drk/tillage/datasets/human/chip/encode/ENCSR155KHM/summary/ENCFF981KCA.w5 32 2 mean CHIP:ARNT:K562 CHIP ChIP-TF:ARNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1934 0 ENCFF636YCB /home/drk/tillage/datasets/human/chip/encode/ENCSR155VDK/summary/ENCFF636YCB.w5 32 2 mean CHIP:ZBTB11:MCF-7 CHIP ChIP-TF:ZBTB11/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1935 0 ENCFF133PYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR156APP/summary/ENCFF133PYQ.w5 32 2 mean CHIP:PTBP1:HepG2 CHIP ChIP-TF:PTBP1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1936 0 ENCFF351DSM /home/drk/tillage/datasets/human/chip/encode/ENCSR156CWW/summary/ENCFF351DSM.w5 32 2 mean CHIP:3xFLAG-DNMT3B:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-DNMT3B/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1937 0 ENCFF144TOB /home/drk/tillage/datasets/human/chip/encode/ENCSR156UQO/summary/ENCFF144TOB.w5 32 2 mean CHIP:POLR2A:esophagus squamous epithelium male adult (37 years) CHIP ChIP-TF:POLR2A/esophagus squamous epithelium male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1938 0 ENCFF067MDM /home/drk/tillage/datasets/human/chip/encode/ENCSR156XNC/summary/ENCFF067MDM.w5 32 2 mean CHIP:H3K27ac:peripheral blood mononuclear cell female adult (28 years) CHIP ChIP-Histone:H3K27ac/peripheral blood mononuclear cell female adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1939 0 ENCFF584FVR /home/drk/tillage/datasets/human/chip/encode/ENCSR157CAU/summary/ENCFF584FVR.w5 32 2 mean CHIP:ZKSCAN1:HepG2 CHIP ChIP-TF:ZKSCAN1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1940 0 ENCFF564KJB /home/drk/tillage/datasets/human/chip/encode/ENCSR157CEN/summary/ENCFF564KJB.w5 32 2 mean CHIP:3xFLAG-ZNF205:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF205/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1941 0 ENCFF119OVG /home/drk/tillage/datasets/human/chip/encode/ENCSR157EML/summary/ENCFF119OVG.w5 32 2 mean CHIP:H3K4me3:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K4me3/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1942 0 ENCFF143CCT /home/drk/tillage/datasets/human/chip/encode/ENCSR157FDN/summary/ENCFF143CCT.w5 32 2 mean CHIP:H3K27me3:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K27me3/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1943 0 ENCFF939SCH /home/drk/tillage/datasets/human/chip/encode/ENCSR157TCS/summary/ENCFF939SCH.w5 32 2 mean CHIP:SMARCE1:K562 CHIP ChIP-TF:SMARCE1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1944 0 ENCFF134TOV /home/drk/tillage/datasets/human/chip/encode/ENCSR157ZVP/summary/ENCFF134TOV.w5 32 2 mean CHIP:H3K36me3:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K36me3/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1945 0 ENCFF836TFW /home/drk/tillage/datasets/human/chip/encode/ENCSR158RYZ/summary/ENCFF836TFW.w5 32 2 mean CHIP:eGFP-ZBTB40:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZBTB40/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1946 0 ENCFF763AVY /home/drk/tillage/datasets/human/chip/encode/ENCSR158TRP/summary/ENCFF763AVY.w5 32 2 mean CHIP:EP300:ovary female adult (51 year) CHIP ChIP-TF:EP300/ovary female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1947 0 ENCFF005WUD /home/drk/tillage/datasets/human/chip/encode/ENCSR159CDJ/summary/ENCFF005WUD.w5 32 2 mean CHIP:H4K20me1:Karpas-422 CHIP ChIP-TF:H4K20me1/Karpas-422 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1948 0 ENCFF159LQN /home/drk/tillage/datasets/human/chip/encode/ENCSR159DQO/summary/ENCFF159LQN.w5 32 2 mean CHIP:3xFLAG-ERF:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ERF/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1949 0 ENCFF463XAL /home/drk/tillage/datasets/human/chip/encode/ENCSR159GFL/summary/ENCFF463XAL.w5 32 2 mean CHIP:eGFP-ZNF518A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF518A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1950 0 ENCFF278PDS /home/drk/tillage/datasets/human/chip/encode/ENCSR159OCC/summary/ENCFF278PDS.w5 32 2 mean CHIP:3xFLAG-ATF1:K562 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ATF1/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1951 0 ENCFF165JCH /home/drk/tillage/datasets/human/chip/encode/ENCSR160CPS/summary/ENCFF165JCH.w5 32 2 mean CHIP:H3K36me3:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K36me3/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1952 0 ENCFF714OII /home/drk/tillage/datasets/human/chip/encode/ENCSR160QYK/summary/ENCFF714OII.w5 32 2 mean CHIP:GATAD2A:K562 CHIP ChIP-TF:GATAD2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1953 0 ENCFF825WLX /home/drk/tillage/datasets/human/chip/encode/ENCSR160ZLP/summary/ENCFF825WLX.w5 32 2 mean CHIP:KDM5A:H1-hESC CHIP ChIP-TF:KDM5A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1954 0 ENCFF390DQO /home/drk/tillage/datasets/human/chip/encode/ENCSR161FEJ/summary/ENCFF390DQO.w5 32 2 mean CHIP:H3K27me3:spleen female adult (53 years) CHIP ChIP-Histone:H3K27me3/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1955 0 ENCFF987TME /home/drk/tillage/datasets/human/chip/encode/ENCSR161HZJ/summary/ENCFF987TME.w5 32 2 mean CHIP:H3K4me1:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K4me1/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1956 0 ENCFF774BWO /home/drk/tillage/datasets/human/chip/encode/ENCSR161MXP/summary/ENCFF774BWO.w5 32 2 mean CHIP:H3K4me1:HCT116 CHIP ChIP-Histone:H3K4me1/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1957 0 ENCFF451CYN /home/drk/tillage/datasets/human/chip/encode/ENCSR161NON/summary/ENCFF451CYN.w5 32 2 mean CHIP:H2BK5ac:H1-hESC CHIP ChIP-TF:H2BK5ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1958 0 ENCFF220PSW /home/drk/tillage/datasets/human/chip/encode/ENCSR161XBV/summary/ENCFF220PSW.w5 32 2 mean CHIP:H3K4me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1959 0 ENCFF974GIJ /home/drk/tillage/datasets/human/chip/encode/ENCSR162DGX/summary/ENCFF974GIJ.w5 32 2 mean CHIP:H3K27me3:B cell female adult (27 years) CHIP ChIP-Histone:H3K27me3/B cell female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1960 0 ENCFF415HOL /home/drk/tillage/datasets/human/chip/encode/ENCSR162IEM/summary/ENCFF415HOL.w5 32 2 mean CHIP:MYBL2:K562 CHIP ChIP-TF:MYBL2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1961 0 ENCFF669MCA /home/drk/tillage/datasets/human/chip/encode/ENCSR162MGR/summary/ENCFF669MCA.w5 32 2 mean CHIP:H3K36me3:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K36me3/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1962 0 ENCFF545DRY /home/drk/tillage/datasets/human/chip/encode/ENCSR162VXO/summary/ENCFF545DRY.w5 32 2 mean CHIP:H3K9ac:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K9ac/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1963 0 ENCFF435KGO /home/drk/tillage/datasets/human/chip/encode/ENCSR163ALM/summary/ENCFF435KGO.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive male adult CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive male adult ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1964 0 ENCFF127GCV /home/drk/tillage/datasets/human/chip/encode/ENCSR163RYW/summary/ENCFF127GCV.w5 32 2 mean CHIP:eGFP-ZNF189:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF189/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1965 0 ENCFF755INA /home/drk/tillage/datasets/human/chip/encode/ENCSR164RFI/summary/ENCFF755INA.w5 32 2 mean CHIP:H4K91ac:IMR-90 CHIP ChIP-TF:H4K91ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1966 0 ENCFF179IKX /home/drk/tillage/datasets/human/chip/encode/ENCSR164ROX/summary/ENCFF179IKX.w5 32 2 mean CHIP:H3K36me3:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K36me3/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1967 0 ENCFF840MKR /home/drk/tillage/datasets/human/chip/encode/ENCSR165LOF/summary/ENCFF840MKR.w5 32 2 mean CHIP:H3K4me2:Loucy CHIP ChIP-Histone:H3K4me2/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1968 0 ENCFF542LHD /home/drk/tillage/datasets/human/chip/encode/ENCSR166CNR/summary/ENCFF542LHD.w5 32 2 mean CHIP:H3K36me3:stomach female adult (53 years) CHIP ChIP-Histone:H3K36me3/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1969 0 ENCFF095DEK /home/drk/tillage/datasets/human/chip/encode/ENCSR166KLM/summary/ENCFF095DEK.w5 32 2 mean CHIP:H3K9ac:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K9ac/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1970 0 ENCFF433GKF /home/drk/tillage/datasets/human/chip/encode/ENCSR166VXF/summary/ENCFF433GKF.w5 32 2 mean CHIP:H3K9me3:tibial artery female adult (53 years) CHIP ChIP-Histone:H3K9me3/tibial artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1971 0 ENCFF323SGW /home/drk/tillage/datasets/human/chip/encode/ENCSR166ZZZ/summary/ENCFF323SGW.w5 32 2 mean CHIP:H3K4me3:CD8-positive, alpha-beta T cell male adult (28 years) CHIP ChIP-Histone:H3K4me3/CD8-positive, alpha-beta T cell male adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1972 0 ENCFF090ECP /home/drk/tillage/datasets/human/chip/encode/ENCSR167JBG/summary/ENCFF090ECP.w5 32 2 mean CHIP:eGFP-DIDO1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-DIDO1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1973 0 ENCFF911IYO /home/drk/tillage/datasets/human/chip/encode/ENCSR167KBO/summary/ENCFF911IYO.w5 32 2 mean CHIP:ZNF316:K562 CHIP ChIP-TF:ZNF316/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1974 0 ENCFF688WRA /home/drk/tillage/datasets/human/chip/encode/ENCSR167XFW/summary/ENCFF688WRA.w5 32 2 mean CHIP:eGFP-ZNF544:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF544/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1975 0 ENCFF051CKS /home/drk/tillage/datasets/human/chip/encode/ENCSR168CEE/summary/ENCFF051CKS.w5 32 2 mean CHIP:NCOA6:K562 CHIP ChIP-TF:NCOA6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1976 0 ENCFF607RBE /home/drk/tillage/datasets/human/chip/encode/ENCSR168PQI/summary/ENCFF607RBE.w5 32 2 mean CHIP:H3K4me3:stomach smooth muscle male adult (59 years) CHIP ChIP-Histone:H3K4me3/stomach smooth muscle male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1977 0 ENCFF869EBO /home/drk/tillage/datasets/human/chip/encode/ENCSR168SMX/summary/ENCFF869EBO.w5 32 2 mean CHIP:NR2F2:liver female child (4 years) CHIP ChIP-TF:NR2F2/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1978 0 ENCFF798DTB /home/drk/tillage/datasets/human/chip/encode/ENCSR168WTY/summary/ENCFF798DTB.w5 32 2 mean CHIP:H3K9me3:muscle layer of duodenum male adult (73 years) CHIP ChIP-Histone:H3K9me3/muscle layer of duodenum male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1979 0 ENCFF405BPK /home/drk/tillage/datasets/human/chip/encode/ENCSR169BGF/summary/ENCFF405BPK.w5 32 2 mean CHIP:H3K4me1:neural stem progenitor cell originated from H9 CHIP ChIP-Histone:H3K4me1/neural stem progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1980 0 ENCFF811AVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR170DNV/summary/ENCFF811AVZ.w5 32 2 mean CHIP:PHB2:HepG2 CHIP ChIP-TF:PHB2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1981 0 ENCFF529KNT /home/drk/tillage/datasets/human/chip/encode/ENCSR170MAJ/summary/ENCFF529KNT.w5 32 2 mean CHIP:H3K27ac:spleen male child (3 years) CHIP ChIP-Histone:H3K27ac/spleen male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1982 0 ENCFF563RCJ /home/drk/tillage/datasets/human/chip/encode/ENCSR170NCG/summary/ENCFF563RCJ.w5 32 2 mean CHIP:H3K4me1:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K4me1/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1983 0 ENCFF043ZLX /home/drk/tillage/datasets/human/chip/encode/ENCSR170NMC/summary/ENCFF043ZLX.w5 32 2 mean CHIP:POLR2AphosphoS5:transverse colon female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/transverse colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1984 0 ENCFF041CMH /home/drk/tillage/datasets/human/chip/encode/ENCSR170VSJ/summary/ENCFF041CMH.w5 32 2 mean CHIP:H3K4me3:muscle layer of colon female adult (56 years) CHIP ChIP-Histone:H3K4me3/muscle layer of colon female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1985 0 ENCFF896XZH /home/drk/tillage/datasets/human/chip/encode/ENCSR171CAY/summary/ENCFF896XZH.w5 32 2 mean CHIP:E2F7:K562 CHIP ChIP-TF:E2F7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1986 0 ENCFF193XGX /home/drk/tillage/datasets/human/chip/encode/ENCSR171FUX/summary/ENCFF193XGX.w5 32 2 mean CHIP:FOXK2:HepG2 CHIP ChIP-TF:FOXK2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1987 0 ENCFF813MOH /home/drk/tillage/datasets/human/chip/encode/ENCSR172CVZ/summary/ENCFF813MOH.w5 32 2 mean CHIP:H4K8ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H4K8ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1988 0 ENCFF927LSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR172FMH/summary/ENCFF927LSQ.w5 32 2 mean CHIP:H3K4me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1989 0 ENCFF464YGC /home/drk/tillage/datasets/human/chip/encode/ENCSR173AIR/summary/ENCFF464YGC.w5 32 2 mean CHIP:CTCF:stomach female adult (51 year) CHIP ChIP-TF:CTCF/stomach female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1990 0 ENCFF856NOM /home/drk/tillage/datasets/human/chip/encode/ENCSR173CTF/summary/ENCFF856NOM.w5 32 2 mean CHIP:3xFLAG-ZNF580:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF580/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1991 0 ENCFF421KUP /home/drk/tillage/datasets/human/chip/encode/ENCSR173EEH/summary/ENCFF421KUP.w5 32 2 mean CHIP:COPS2:MCF-7 CHIP ChIP-TF:COPS2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1992 0 ENCFF722IZG /home/drk/tillage/datasets/human/chip/encode/ENCSR173ZMH/summary/ENCFF722IZG.w5 32 2 mean CHIP:H3K36me3:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K36me3/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1993 0 ENCFF319YAI /home/drk/tillage/datasets/human/chip/encode/ENCSR173ZVL/summary/ENCFF319YAI.w5 32 2 mean CHIP:ZNF592:GM12878 CHIP ChIP-TF:ZNF592/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1994 0 ENCFF849BNL /home/drk/tillage/datasets/human/chip/encode/ENCSR175BVD/summary/ENCFF849BNL.w5 32 2 mean CHIP:POLR2A:lower leg skin male adult (37 years) CHIP ChIP-TF:POLR2A/lower leg skin male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1995 0 ENCFF728OAR /home/drk/tillage/datasets/human/chip/encode/ENCSR175EOM/summary/ENCFF728OAR.w5 32 2 mean CHIP:EHMT2:K562 CHIP ChIP-TF:EHMT2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1996 0 ENCFF112QRR /home/drk/tillage/datasets/human/chip/encode/ENCSR175FLL/summary/ENCFF112QRR.w5 32 2 mean CHIP:CTCF:coronary artery female adult (53 years) CHIP ChIP-TF:CTCF/coronary artery female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1997 0 ENCFF349SHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR175HIV/summary/ENCFF349SHQ.w5 32 2 mean CHIP:H3K9ac:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K9ac/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1998 0 ENCFF043ACF /home/drk/tillage/datasets/human/chip/encode/ENCSR175OYG/summary/ENCFF043ACF.w5 32 2 mean CHIP:H3K9me2:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K9me2/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +1999 0 ENCFF706ZWX /home/drk/tillage/datasets/human/chip/encode/ENCSR175SZH/summary/ENCFF706ZWX.w5 32 2 mean CHIP:ZSCAN29:K562 CHIP ChIP-TF:ZSCAN29/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2000 0 ENCFF638VOA /home/drk/tillage/datasets/human/chip/encode/ENCSR175XPY/summary/ENCFF638VOA.w5 32 2 mean CHIP:H3K27ac:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K27ac/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2001 0 ENCFF519LEW /home/drk/tillage/datasets/human/chip/encode/ENCSR176ABZ/summary/ENCFF519LEW.w5 32 2 mean CHIP:H3K4me3:HUES6 CHIP ChIP-Histone:H3K4me3/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2002 0 ENCFF331CAB /home/drk/tillage/datasets/human/chip/encode/ENCSR176BAH/summary/ENCFF331CAB.w5 32 2 mean CHIP:EP300:subcutaneous adipose tissue male adult (37 years) CHIP ChIP-TF:EP300/subcutaneous adipose tissue male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2003 0 ENCFF373OIB /home/drk/tillage/datasets/human/chip/encode/ENCSR176EXN/summary/ENCFF373OIB.w5 32 2 mean CHIP:JUN:MCF-7 CHIP ChIP-TF:JUN/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2004 0 ENCFF988JKE /home/drk/tillage/datasets/human/chip/encode/ENCSR176KNR/summary/ENCFF988JKE.w5 32 2 mean CHIP:H3K9me3:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K9me3/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2005 0 ENCFF977RZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR176WAS/summary/ENCFF977RZQ.w5 32 2 mean CHIP:H3K36me3:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K36me3/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2006 0 ENCFF448GLM /home/drk/tillage/datasets/human/chip/encode/ENCSR177CGN/summary/ENCFF448GLM.w5 32 2 mean CHIP:H3K27me3:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K27me3/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2007 0 ENCFF616OHG /home/drk/tillage/datasets/human/chip/encode/ENCSR177DNR/summary/ENCFF616OHG.w5 32 2 mean CHIP:FIP1L1:K562 CHIP ChIP-TF:FIP1L1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2008 0 ENCFF824FEH /home/drk/tillage/datasets/human/chip/encode/ENCSR177QFY/summary/ENCFF824FEH.w5 32 2 mean CHIP:H3K27ac:adrenal gland male adult (54 years) CHIP ChIP-Histone:H3K27ac/adrenal gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2009 0 ENCFF080JHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR177QXA/summary/ENCFF080JHQ.w5 32 2 mean CHIP:H3K4me3:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K4me3/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2010 0 ENCFF676GTP /home/drk/tillage/datasets/human/chip/encode/ENCSR177VFS/summary/ENCFF676GTP.w5 32 2 mean CHIP:MEF2B:GM12878 CHIP ChIP-TF:MEF2B/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2011 0 ENCFF802JFC /home/drk/tillage/datasets/human/chip/encode/ENCSR177XCS/summary/ENCFF802JFC.w5 32 2 mean CHIP:BRD9:K562 CHIP ChIP-TF:BRD9/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2012 0 ENCFF841YHR /home/drk/tillage/datasets/human/chip/encode/ENCSR178DEG/summary/ENCFF841YHR.w5 32 2 mean CHIP:eGFP-NR2C1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NR2C1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2013 0 ENCFF897IOX /home/drk/tillage/datasets/human/chip/encode/ENCSR178NTX/summary/ENCFF897IOX.w5 32 2 mean CHIP:eGFP-CUX1:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-CUX1/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2014 0 ENCFF619FLZ /home/drk/tillage/datasets/human/chip/encode/ENCSR178QVJ/summary/ENCFF619FLZ.w5 32 2 mean CHIP:eGFP-ZNF274:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF274/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2015 0 ENCFF542HPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR179BUC/summary/ENCFF542HPZ.w5 32 2 mean CHIP:H3K9me3:HCT116 CHIP ChIP-Histone:H3K9me3/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2016 0 ENCFF923PSI /home/drk/tillage/datasets/human/chip/encode/ENCSR179MIQ/summary/ENCFF923PSI.w5 32 2 mean CHIP:H3K9me3:common myeloid progenitor, CD34-positive male adult (36 years) CHIP ChIP-Histone:H3K9me3/common myeloid progenitor, CD34-positive male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2017 0 ENCFF318UCG /home/drk/tillage/datasets/human/chip/encode/ENCSR179NYV/summary/ENCFF318UCG.w5 32 2 mean CHIP:H3K4me1:small intestine male child (3 years) CHIP ChIP-Histone:H3K4me1/small intestine male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2018 0 ENCFF885NCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR179SAO/summary/ENCFF885NCZ.w5 32 2 mean CHIP:EZH2:A673 CHIP ChIP-TF:EZH2/A673 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2019 0 ENCFF420GOW /home/drk/tillage/datasets/human/chip/encode/ENCSR180AAB/summary/ENCFF420GOW.w5 32 2 mean CHIP:H3F3A:PC-9 CHIP ChIP-Histone:H3F3A/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2020 0 ENCFF680EVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR180CHR/summary/ENCFF680EVZ.w5 32 2 mean CHIP:H3K27me3:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K27me3/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2021 0 ENCFF019XYA /home/drk/tillage/datasets/human/chip/encode/ENCSR181JFC/summary/ENCFF019XYA.w5 32 2 mean CHIP:H3K27me3:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K27me3/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2022 0 ENCFF296KGM /home/drk/tillage/datasets/human/chip/encode/ENCSR182QWU/summary/ENCFF296KGM.w5 32 2 mean CHIP:3xFLAG-ZNF3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2023 0 ENCFF610ZRX /home/drk/tillage/datasets/human/chip/encode/ENCSR182XTG/summary/ENCFF610ZRX.w5 32 2 mean CHIP:H3K18ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K18ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2024 0 ENCFF945HYM /home/drk/tillage/datasets/human/chip/encode/ENCSR183AXJ/summary/ENCFF945HYM.w5 32 2 mean CHIP:HNRNPUL1:HepG2 CHIP ChIP-TF:HNRNPUL1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2025 0 ENCFF297DRN /home/drk/tillage/datasets/human/chip/encode/ENCSR183CQK/summary/ENCFF297DRN.w5 32 2 mean CHIP:H3K27me3:Loucy CHIP ChIP-Histone:H3K27me3/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2026 0 ENCFF656QWS /home/drk/tillage/datasets/human/chip/encode/ENCSR183LNU/summary/ENCFF656QWS.w5 32 2 mean CHIP:H3K9me3:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K9me3/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2027 0 ENCFF940YAF /home/drk/tillage/datasets/human/chip/encode/ENCSR184MFH/summary/ENCFF940YAF.w5 32 2 mean CHIP:ZFP36:HeLa-S3 CHIP ChIP-TF:ZFP36/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2028 0 ENCFF445OKW /home/drk/tillage/datasets/human/chip/encode/ENCSR184QUS/summary/ENCFF445OKW.w5 32 2 mean CHIP:H3K4me1:OCI-LY1 CHIP ChIP-Histone:H3K4me1/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2029 0 ENCFF939AAT /home/drk/tillage/datasets/human/chip/encode/ENCSR184SVO/summary/ENCFF939AAT.w5 32 2 mean CHIP:3xFLAG-ZBTB26:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZBTB26/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2030 0 ENCFF333IRA /home/drk/tillage/datasets/human/chip/encode/ENCSR185FOY/summary/ENCFF333IRA.w5 32 2 mean CHIP:eGFP-ZNF341:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF341/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2031 0 ENCFF983ANC /home/drk/tillage/datasets/human/chip/encode/ENCSR185QFX/summary/ENCFF983ANC.w5 32 2 mean CHIP:eGFP-ZNF549:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF549/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2032 0 ENCFF228DCW /home/drk/tillage/datasets/human/chip/encode/ENCSR186EAD/summary/ENCFF228DCW.w5 32 2 mean CHIP:H3K9me2:Loucy CHIP ChIP-Histone:H3K9me2/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2033 0 ENCFF440WKB /home/drk/tillage/datasets/human/chip/encode/ENCSR186NVR/summary/ENCFF440WKB.w5 32 2 mean CHIP:CTCF:gastroesophageal sphincter male adult (37 years) CHIP ChIP-TF:CTCF/gastroesophageal sphincter male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2034 0 ENCFF095OPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR186OBR/summary/ENCFF095OPQ.w5 32 2 mean CHIP:H3K27me3:H1-hESC CHIP ChIP-Histone:H3K27me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2035 0 ENCFF254ENM /home/drk/tillage/datasets/human/chip/encode/ENCSR186QKH/summary/ENCFF254ENM.w5 32 2 mean CHIP:H3K27me3:pancreas male adult (34 years) CHIP ChIP-Histone:H3K27me3/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2036 0 ENCFF255LMC /home/drk/tillage/datasets/human/chip/encode/ENCSR188GJE/summary/ENCFF255LMC.w5 32 2 mean CHIP:H3K79me2:H9 CHIP ChIP-Histone:H3K79me2/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2037 0 ENCFF238AGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR189AGR/summary/ENCFF238AGZ.w5 32 2 mean CHIP:H3K9me3:OCI-LY1 CHIP ChIP-Histone:H3K9me3/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2038 0 ENCFF615WRA /home/drk/tillage/datasets/human/chip/encode/ENCSR189PYJ/summary/ENCFF615WRA.w5 32 2 mean CHIP:SMAD2:K562 CHIP ChIP-TF:SMAD2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2039 0 ENCFF024VVX /home/drk/tillage/datasets/human/chip/encode/ENCSR189QAD/summary/ENCFF024VVX.w5 32 2 mean CHIP:H3K27ac:adrenal gland female adult (53 years) CHIP ChIP-Histone:H3K27ac/adrenal gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2040 0 ENCFF007RUV /home/drk/tillage/datasets/human/chip/encode/ENCSR189TRZ/summary/ENCFF007RUV.w5 32 2 mean CHIP:TCF12:K562 CHIP ChIP-TF:TCF12/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2041 0 ENCFF644QPE /home/drk/tillage/datasets/human/chip/encode/ENCSR189VXS/summary/ENCFF644QPE.w5 32 2 mean CHIP:GTF2F1:K562 CHIP ChIP-TF:GTF2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2042 0 ENCFF817LJR /home/drk/tillage/datasets/human/chip/encode/ENCSR189XIE/summary/ENCFF817LJR.w5 32 2 mean CHIP:H4K20me1:smooth muscle cell originated from H9 CHIP ChIP-TF:H4K20me1/smooth muscle cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2043 0 ENCFF550FGL /home/drk/tillage/datasets/human/chip/encode/ENCSR189YMA/summary/ENCFF550FGL.w5 32 2 mean CHIP:eGFP-VEZF1:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-VEZF1/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2044 0 ENCFF366YYF /home/drk/tillage/datasets/human/chip/encode/ENCSR189YYK/summary/ENCFF366YYF.w5 32 2 mean CHIP:ZBTB40:GM12878 CHIP ChIP-TF:ZBTB40/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2045 0 ENCFF218PDV /home/drk/tillage/datasets/human/chip/encode/ENCSR191OEG/summary/ENCFF218PDV.w5 32 2 mean CHIP:H3K9ac:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K9ac/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2046 0 ENCFF661KMI /home/drk/tillage/datasets/human/chip/encode/ENCSR191TLD/summary/ENCFF661KMI.w5 32 2 mean CHIP:3xFLAG-PHF5A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-PHF5A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2047 0 ENCFF951ZBV /home/drk/tillage/datasets/human/chip/encode/ENCSR191ZQT/summary/ENCFF951ZBV.w5 32 2 mean CHIP:H3K27ac:B cell male adult (37 years) CHIP ChIP-Histone:H3K27ac/B cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2048 0 ENCFF359QVU /home/drk/tillage/datasets/human/chip/encode/ENCSR192AFN/summary/ENCFF359QVU.w5 32 2 mean CHIP:PAX8:GM12878 CHIP ChIP-TF:PAX8/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2049 0 ENCFF558SMG /home/drk/tillage/datasets/human/chip/encode/ENCSR192GUR/summary/ENCFF558SMG.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive male adult (42 years) CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive male adult (42 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2050 0 ENCFF205ZQF /home/drk/tillage/datasets/human/chip/encode/ENCSR193XWO/summary/ENCFF205ZQF.w5 32 2 mean CHIP:H3K36me3:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K36me3/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2051 0 ENCFF568ZUR /home/drk/tillage/datasets/human/chip/encode/ENCSR194BBY/summary/ENCFF568ZUR.w5 32 2 mean CHIP:eGFP-ZNF221:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF221/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2052 0 ENCFF082UPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR194IJN/summary/ENCFF082UPZ.w5 32 2 mean CHIP:eGFP-ZNF766:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF766/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2053 0 ENCFF065FDJ /home/drk/tillage/datasets/human/chip/encode/ENCSR194KWL/summary/ENCFF065FDJ.w5 32 2 mean CHIP:eGFP-ZNF704:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF704/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2054 0 ENCFF837UAW /home/drk/tillage/datasets/human/chip/encode/ENCSR194MJA/summary/ENCFF837UAW.w5 32 2 mean CHIP:H3K4me3:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K4me3/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2055 0 ENCFF871YGU /home/drk/tillage/datasets/human/chip/encode/ENCSR194TFK/summary/ENCFF871YGU.w5 32 2 mean CHIP:H3K4me1:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K4me1/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2056 0 ENCFF843SWO /home/drk/tillage/datasets/human/chip/encode/ENCSR194ZHE/summary/ENCFF843SWO.w5 32 2 mean CHIP:H3K4me1:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2057 0 ENCFF976FME /home/drk/tillage/datasets/human/chip/encode/ENCSR195CFR/summary/ENCFF976FME.w5 32 2 mean CHIP:H3K27ac:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K27ac/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2058 0 ENCFF207LBR /home/drk/tillage/datasets/human/chip/encode/ENCSR195QFV/summary/ENCFF207LBR.w5 32 2 mean CHIP:3xFLAG-ZNF3:K562 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF3/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2059 0 ENCFF528FTD /home/drk/tillage/datasets/human/chip/encode/ENCSR196HGZ/summary/ENCFF528FTD.w5 32 2 mean CHIP:JUND:liver female child (4 years) CHIP ChIP-TF:JUND/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2060 0 ENCFF573GPU /home/drk/tillage/datasets/human/chip/encode/ENCSR196HOM/summary/ENCFF573GPU.w5 32 2 mean CHIP:CTCF:epithelial cell of prostate male CHIP ChIP-TF:CTCF/epithelial cell of prostate male ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2061 0 ENCFF834TID /home/drk/tillage/datasets/human/chip/encode/ENCSR196KYU/summary/ENCFF834TID.w5 32 2 mean CHIP:H3K4me1:common myeloid progenitor, CD34-positive male adult (36 years) CHIP ChIP-Histone:H3K4me1/common myeloid progenitor, CD34-positive male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2062 0 ENCFF893KHE /home/drk/tillage/datasets/human/chip/encode/ENCSR196LEI/summary/ENCFF893KHE.w5 32 2 mean CHIP:H3K4me1:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K4me1/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2063 0 ENCFF397BWR /home/drk/tillage/datasets/human/chip/encode/ENCSR196PGM/summary/ENCFF397BWR.w5 32 2 mean CHIP:H3K27me3:aorta male adult (34 years) CHIP ChIP-Histone:H3K27me3/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2064 0 ENCFF127ZFX /home/drk/tillage/datasets/human/chip/encode/ENCSR197ALX/summary/ENCFF127ZFX.w5 32 2 mean CHIP:HDGF:K562 CHIP ChIP-TF:HDGF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2065 0 ENCFF254KOD /home/drk/tillage/datasets/human/chip/encode/ENCSR197DJH/summary/ENCFF254KOD.w5 32 2 mean CHIP:SREBF1:MCF-7 CHIP ChIP-TF:SREBF1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2066 0 ENCFF601HLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR197QDK/summary/ENCFF601HLQ.w5 32 2 mean CHIP:H3K4me3:spleen female adult (53 years) CHIP ChIP-Histone:H3K4me3/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2067 0 ENCFF920QCM /home/drk/tillage/datasets/human/chip/encode/ENCSR197QXT/summary/ENCFF920QCM.w5 32 2 mean CHIP:H3K9ac:PC-3 CHIP ChIP-Histone:H3K9ac/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2068 0 ENCFF323BAX /home/drk/tillage/datasets/human/chip/encode/ENCSR197WGI/summary/ENCFF323BAX.w5 32 2 mean CHIP:NFE2L2:IMR-90 CHIP ChIP-TF:NFE2L2/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2069 0 ENCFF203QTN /home/drk/tillage/datasets/human/chip/encode/ENCSR197XDQ/summary/ENCFF203QTN.w5 32 2 mean CHIP:H3F3A:MCF-7 CHIP ChIP-Histone:H3F3A/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2070 0 ENCFF742GMF /home/drk/tillage/datasets/human/chip/encode/ENCSR198HVO/summary/ENCFF742GMF.w5 32 2 mean CHIP:H3K27me3:H7-hESC CHIP ChIP-Histone:H3K27me3/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2071 0 ENCFF809NEB /home/drk/tillage/datasets/human/chip/encode/ENCSR198YHG/summary/ENCFF809NEB.w5 32 2 mean CHIP:H3K36me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2072 0 ENCFF093REE /home/drk/tillage/datasets/human/chip/encode/ENCSR198ZYJ/summary/ENCFF093REE.w5 32 2 mean CHIP:RAD21:neural cell originated from H1-hESC CHIP ChIP-TF:RAD21/neural cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2073 0 ENCFF516POG /home/drk/tillage/datasets/human/chip/encode/ENCSR199KHR/summary/ENCFF516POG.w5 32 2 mean CHIP:H3K9me2:OCI-LY7 CHIP ChIP-Histone:H3K9me2/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2074 0 ENCFF636AJD /home/drk/tillage/datasets/human/chip/encode/ENCSR199VMI/summary/ENCFF636AJD.w5 32 2 mean CHIP:H3K4me1:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K4me1/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2075 0 ENCFF699ETX /home/drk/tillage/datasets/human/chip/encode/ENCSR199WXF/summary/ENCFF699ETX.w5 32 2 mean CHIP:EED:GM12878 CHIP ChIP-TF:EED/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2076 0 ENCFF752OQN /home/drk/tillage/datasets/human/chip/encode/ENCSR200CUA/summary/ENCFF752OQN.w5 32 2 mean CHIP:HDGF:MCF-7 CHIP ChIP-TF:HDGF/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2077 0 ENCFF864CEK /home/drk/tillage/datasets/human/chip/encode/ENCSR200ETW/summary/ENCFF864CEK.w5 32 2 mean CHIP:H3K27ac:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K27ac/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2078 0 ENCFF404USP /home/drk/tillage/datasets/human/chip/encode/ENCSR200JYP/summary/ENCFF404USP.w5 32 2 mean CHIP:ZNF316:K562 CHIP ChIP-TF:ZNF316/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2079 0 ENCFF381IAJ /home/drk/tillage/datasets/human/chip/encode/ENCSR200WDD/summary/ENCFF381IAJ.w5 32 2 mean CHIP:H3K9me3:esophagus female adult (30 years) CHIP ChIP-Histone:H3K9me3/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2080 0 ENCFF162UJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR201GCJ/summary/ENCFF162UJQ.w5 32 2 mean CHIP:H3K9me3:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K9me3/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2081 0 ENCFF277QPV /home/drk/tillage/datasets/human/chip/encode/ENCSR201GGK/summary/ENCFF277QPV.w5 32 2 mean CHIP:3xFLAG-NFIL3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NFIL3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2082 0 ENCFF888DFU /home/drk/tillage/datasets/human/chip/encode/ENCSR201NQZ/summary/ENCFF888DFU.w5 32 2 mean CHIP:CTBP1:K562 CHIP ChIP-TF:CTBP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2083 0 ENCFF450PNO /home/drk/tillage/datasets/human/chip/encode/ENCSR201OSX/summary/ENCFF450PNO.w5 32 2 mean CHIP:H3K27me3:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K27me3/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2084 0 ENCFF905GLU /home/drk/tillage/datasets/human/chip/encode/ENCSR202RXT/summary/ENCFF905GLU.w5 32 2 mean CHIP:H3K4me3:stomach female embryo (98 days) CHIP ChIP-Histone:H3K4me3/stomach female embryo (98 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2085 0 ENCFF082ADJ /home/drk/tillage/datasets/human/chip/encode/ENCSR202XTW/summary/ENCFF082ADJ.w5 32 2 mean CHIP:H3K4me1:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K4me1/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2086 0 ENCFF654HDQ /home/drk/tillage/datasets/human/chip/encode/ENCSR203BOA/summary/ENCFF654HDQ.w5 32 2 mean CHIP:H3K36me3:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2087 0 ENCFF215WGG /home/drk/tillage/datasets/human/chip/encode/ENCSR203BQB/summary/ENCFF215WGG.w5 32 2 mean CHIP:H3K9me3:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K9me3/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2088 0 ENCFF189ZIC /home/drk/tillage/datasets/human/chip/encode/ENCSR203GEP/summary/ENCFF189ZIC.w5 32 2 mean CHIP:H3K27me3:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K27me3/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2089 0 ENCFF331NIO /home/drk/tillage/datasets/human/chip/encode/ENCSR203KCB/summary/ENCFF331NIO.w5 32 2 mean CHIP:H3K27ac:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K27ac/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2090 0 ENCFF042VGD /home/drk/tillage/datasets/human/chip/encode/ENCSR203KEU/summary/ENCFF042VGD.w5 32 2 mean CHIP:H3K27ac:RWPE1 CHIP ChIP-Histone:H3K27ac/RWPE1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2091 0 ENCFF266BGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR203QEB/summary/ENCFF266BGZ.w5 32 2 mean CHIP:CTCF:Panc1 CHIP ChIP-TF:CTCF/Panc1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2092 0 ENCFF245XLB /home/drk/tillage/datasets/human/chip/encode/ENCSR203RKZ/summary/ENCFF245XLB.w5 32 2 mean CHIP:H3K4me1:liver male adult (78 years) CHIP ChIP-Histone:H3K4me1/liver male adult (78 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2093 0 ENCFF465USG /home/drk/tillage/datasets/human/chip/encode/ENCSR204DMS/summary/ENCFF465USG.w5 32 2 mean CHIP:H3K36me3:adrenal gland male adult (37 years) CHIP ChIP-Histone:H3K36me3/adrenal gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2094 0 ENCFF212XAA /home/drk/tillage/datasets/human/chip/encode/ENCSR204NFO/summary/ENCFF212XAA.w5 32 2 mean CHIP:H3K27me3:lung female adult (30 years) CHIP ChIP-Histone:H3K27me3/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2095 0 ENCFF328EUU /home/drk/tillage/datasets/human/chip/encode/ENCSR205FOW/summary/ENCFF328EUU.w5 32 2 mean CHIP:ATF3:liver female child (4 years) CHIP ChIP-TF:ATF3/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2096 0 ENCFF003ZRK /home/drk/tillage/datasets/human/chip/encode/ENCSR205NEW/summary/ENCFF003ZRK.w5 32 2 mean CHIP:H3K36me3:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K36me3/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2097 0 ENCFF764KSL /home/drk/tillage/datasets/human/chip/encode/ENCSR205SKQ/summary/ENCFF764KSL.w5 32 2 mean CHIP:YBX1:GM12878 CHIP ChIP-TF:YBX1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2098 0 ENCFF525WKF /home/drk/tillage/datasets/human/chip/encode/ENCSR206ETG/summary/ENCFF525WKF.w5 32 2 mean CHIP:CTCF:gastroesophageal sphincter female adult (53 years) CHIP ChIP-TF:CTCF/gastroesophageal sphincter female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2099 0 ENCFF074XHZ /home/drk/tillage/datasets/human/chip/encode/ENCSR206JRX/summary/ENCFF074XHZ.w5 32 2 mean CHIP:H3K4me3:peripheral blood mononuclear cell female adult (28 years) CHIP ChIP-Histone:H3K4me3/peripheral blood mononuclear cell female adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2100 0 ENCFF444XUK /home/drk/tillage/datasets/human/chip/encode/ENCSR206STN/summary/ENCFF444XUK.w5 32 2 mean CHIP:H3K4me3:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K4me3/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2101 0 ENCFF568JGE /home/drk/tillage/datasets/human/chip/encode/ENCSR207JOI/summary/ENCFF568JGE.w5 32 2 mean CHIP:H3K9me3:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K9me3/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2102 0 ENCFF794XLB /home/drk/tillage/datasets/human/chip/encode/ENCSR207PFI/summary/ENCFF794XLB.w5 32 2 mean CHIP:ZBED1:GM12878 CHIP ChIP-TF:ZBED1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2103 0 ENCFF700HMI /home/drk/tillage/datasets/human/chip/encode/ENCSR207ZIA/summary/ENCFF700HMI.w5 32 2 mean CHIP:H3K4me1:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K4me1/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2104 0 ENCFF083BTK /home/drk/tillage/datasets/human/chip/encode/ENCSR208QRN/summary/ENCFF083BTK.w5 32 2 mean CHIP:H3K27ac:transverse colon female adult (53 years) CHIP ChIP-Histone:H3K27ac/transverse colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2105 0 ENCFF721UKX /home/drk/tillage/datasets/human/chip/encode/ENCSR208WDY/summary/ENCFF721UKX.w5 32 2 mean CHIP:H3K4me3:upper lobe of left lung female adult (53 years) CHIP ChIP-Histone:H3K4me3/upper lobe of left lung female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2106 0 ENCFF168YVD /home/drk/tillage/datasets/human/chip/encode/ENCSR209QGZ/summary/ENCFF168YVD.w5 32 2 mean CHIP:H3K27ac:spinal cord female embryo (108 days) CHIP ChIP-Histone:H3K27ac/spinal cord female embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2107 0 ENCFF975VCA /home/drk/tillage/datasets/human/chip/encode/ENCSR209WQN/summary/ENCFF975VCA.w5 32 2 mean CHIP:H3K27me3:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K27me3/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2108 0 ENCFF078QFT /home/drk/tillage/datasets/human/chip/encode/ENCSR210HBN/summary/ENCFF078QFT.w5 32 2 mean CHIP:3xFLAG-IKZF5:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-IKZF5/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2109 0 ENCFF021OEU /home/drk/tillage/datasets/human/chip/encode/ENCSR210MET/summary/ENCFF021OEU.w5 32 2 mean CHIP:eGFP-ZNF391:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF391/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2110 0 ENCFF811FXD /home/drk/tillage/datasets/human/chip/encode/ENCSR210RXE/summary/ENCFF811FXD.w5 32 2 mean CHIP:H2BK120ac:IMR-90 CHIP ChIP-TF:H2BK120ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2111 0 ENCFF360FGJ /home/drk/tillage/datasets/human/chip/encode/ENCSR210ZPC/summary/ENCFF360FGJ.w5 32 2 mean CHIP:H3K27ac:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K27ac/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2112 0 ENCFF838RFR /home/drk/tillage/datasets/human/chip/encode/ENCSR210ZYL/summary/ENCFF838RFR.w5 32 2 mean CHIP:NBN:HepG2 CHIP ChIP-TF:NBN/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2113 0 ENCFF052QYR /home/drk/tillage/datasets/human/chip/encode/ENCSR211GNP/summary/ENCFF052QYR.w5 32 2 mean CHIP:eGFP-ZSCAN4:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN4/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2114 0 ENCFF226GXE /home/drk/tillage/datasets/human/chip/encode/ENCSR211LTF/summary/ENCFF226GXE.w5 32 2 mean CHIP:EGR1:K562 CHIP ChIP-TF:EGR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2115 0 ENCFF916QDA /home/drk/tillage/datasets/human/chip/encode/ENCSR211PZO/summary/ENCFF916QDA.w5 32 2 mean CHIP:eGFP-GLI4:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-GLI4/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2116 0 ENCFF955BUK /home/drk/tillage/datasets/human/chip/encode/ENCSR212LIS/summary/ENCFF955BUK.w5 32 2 mean CHIP:H3K36me3:luminal epithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K36me3/luminal epithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2117 0 ENCFF484QFK /home/drk/tillage/datasets/human/chip/encode/ENCSR212YKD/summary/ENCFF484QFK.w5 32 2 mean CHIP:SKIL:GM12878 CHIP ChIP-TF:SKIL/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2118 0 ENCFF415DMT /home/drk/tillage/datasets/human/chip/encode/ENCSR213APK/summary/ENCFF415DMT.w5 32 2 mean CHIP:H3K9me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K9me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2119 0 ENCFF241GXI /home/drk/tillage/datasets/human/chip/encode/ENCSR213DKS/summary/ENCFF241GXI.w5 32 2 mean CHIP:H3K36me3:liver female adult (25 years) CHIP ChIP-Histone:H3K36me3/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2120 0 ENCFF857WCP /home/drk/tillage/datasets/human/chip/encode/ENCSR213HBY/summary/ENCFF857WCP.w5 32 2 mean CHIP:TOE1:K562 CHIP ChIP-TF:TOE1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2121 0 ENCFF031NZC /home/drk/tillage/datasets/human/chip/encode/ENCSR213JMO/summary/ENCFF031NZC.w5 32 2 mean CHIP:H3K79me1:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K79me1/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2122 0 ENCFF361CCL /home/drk/tillage/datasets/human/chip/encode/ENCSR213SMK/summary/ENCFF361CCL.w5 32 2 mean CHIP:H3K27ac:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K27ac/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2123 0 ENCFF248GEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR213TIR/summary/ENCFF248GEZ.w5 32 2 mean CHIP:H2BK5ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H2BK5ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2124 0 ENCFF310HLY /home/drk/tillage/datasets/human/chip/encode/ENCSR213VUI/summary/ENCFF310HLY.w5 32 2 mean CHIP:TRIM25:K562 CHIP ChIP-TF:TRIM25/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2125 0 ENCFF998TXG /home/drk/tillage/datasets/human/chip/encode/ENCSR214JUK/summary/ENCFF998TXG.w5 32 2 mean CHIP:H3K27me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K27me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2126 0 ENCFF159WKL /home/drk/tillage/datasets/human/chip/encode/ENCSR214VUB/summary/ENCFF159WKL.w5 32 2 mean CHIP:H3K4me1:B cell male adult (21 year) CHIP ChIP-Histone:H3K4me1/B cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2127 0 ENCFF822AKT /home/drk/tillage/datasets/human/chip/encode/ENCSR214WRA/summary/ENCFF822AKT.w5 32 2 mean CHIP:H3K9me3:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K9me3/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2128 0 ENCFF389FXB /home/drk/tillage/datasets/human/chip/encode/ENCSR215EFA/summary/ENCFF389FXB.w5 32 2 mean CHIP:H3K4me3:chorion male embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/chorion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2129 0 ENCFF043JFV /home/drk/tillage/datasets/human/chip/encode/ENCSR216OGD/summary/ENCFF043JFV.w5 32 2 mean CHIP:H3K27me3:H1-hESC CHIP ChIP-Histone:H3K27me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2130 0 ENCFF493JRG /home/drk/tillage/datasets/human/chip/encode/ENCSR217CEY/summary/ENCFF493JRG.w5 32 2 mean CHIP:H3K27me3:stomach smooth muscle male adult (59 years) CHIP ChIP-Histone:H3K27me3/stomach smooth muscle male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2131 0 ENCFF955YWG /home/drk/tillage/datasets/human/chip/encode/ENCSR217HTK/summary/ENCFF955YWG.w5 32 2 mean CHIP:eGFP-ATF2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ATF2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2132 0 ENCFF425ROI /home/drk/tillage/datasets/human/chip/encode/ENCSR217KAL/summary/ENCFF425ROI.w5 32 2 mean CHIP:POLR2AphosphoS5:esophagus muscularis mucosa male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/esophagus muscularis mucosa male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2133 0 ENCFF327AKS /home/drk/tillage/datasets/human/chip/encode/ENCSR217QCK/summary/ENCFF327AKS.w5 32 2 mean CHIP:eGFP-ZNF697:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF697/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2134 0 ENCFF583OIB /home/drk/tillage/datasets/human/chip/encode/ENCSR217WRC/summary/ENCFF583OIB.w5 32 2 mean CHIP:eGFP-TSHZ1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-TSHZ1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2135 0 ENCFF250ASJ /home/drk/tillage/datasets/human/chip/encode/ENCSR218BPG/summary/ENCFF250ASJ.w5 32 2 mean CHIP:H3K27me3:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K27me3/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2136 0 ENCFF013BCN /home/drk/tillage/datasets/human/chip/encode/ENCSR218GSN/summary/ENCFF013BCN.w5 32 2 mean CHIP:ZFX:HEK293T CHIP ChIP-TF:ZFX/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2137 0 ENCFF088LSP /home/drk/tillage/datasets/human/chip/encode/ENCSR218HDF/summary/ENCFF088LSP.w5 32 2 mean CHIP:H3K27me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2138 0 ENCFF578PZY /home/drk/tillage/datasets/human/chip/encode/ENCSR218OEZ/summary/ENCFF578PZY.w5 32 2 mean CHIP:H3K4me1:T-cell male adult (21 year) CHIP ChIP-Histone:H3K4me1/T-cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2139 0 ENCFF884ZRE /home/drk/tillage/datasets/human/chip/encode/ENCSR218QFN/summary/ENCFF884ZRE.w5 32 2 mean CHIP:EZH2:PC-3 CHIP ChIP-TF:EZH2/PC-3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2140 0 ENCFF549OBG /home/drk/tillage/datasets/human/chip/encode/ENCSR218ZMU/summary/ENCFF549OBG.w5 32 2 mean CHIP:H3K4me1:liver male adult (32 years) CHIP ChIP-Histone:H3K4me1/liver male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2141 0 ENCFF747XEM /home/drk/tillage/datasets/human/chip/encode/ENCSR219BXP/summary/ENCFF747XEM.w5 32 2 mean CHIP:DPF2:K562 CHIP ChIP-TF:DPF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2142 0 ENCFF602TFL /home/drk/tillage/datasets/human/chip/encode/ENCSR219MKK/summary/ENCFF602TFL.w5 32 2 mean CHIP:DEK:HeLa-S3 CHIP ChIP-TF:DEK/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2143 0 ENCFF980ZYS /home/drk/tillage/datasets/human/chip/encode/ENCSR219MYH/summary/ENCFF980ZYS.w5 32 2 mean CHIP:H3K9ac:IMR-90 CHIP ChIP-Histone:H3K9ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2144 0 ENCFF713BPL /home/drk/tillage/datasets/human/chip/encode/ENCSR219NRT/summary/ENCFF713BPL.w5 32 2 mean CHIP:GTF2F1:HepG2 CHIP ChIP-TF:GTF2F1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2145 0 ENCFF365LVN /home/drk/tillage/datasets/human/chip/encode/ENCSR220XCD/summary/ENCFF365LVN.w5 32 2 mean CHIP:H3K4me2:hepatocyte originated from H9 CHIP ChIP-Histone:H3K4me2/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2146 0 ENCFF705IRU /home/drk/tillage/datasets/human/chip/encode/ENCSR220YXI/summary/ENCFF705IRU.w5 32 2 mean CHIP:PRPF4:K562 CHIP ChIP-TF:PRPF4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2147 0 ENCFF205QAK /home/drk/tillage/datasets/human/chip/encode/ENCSR221GAN/summary/ENCFF205QAK.w5 32 2 mean CHIP:MBD2:K562 CHIP ChIP-TF:MBD2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2148 0 ENCFF188YMA /home/drk/tillage/datasets/human/chip/encode/ENCSR221ZRM/summary/ENCFF188YMA.w5 32 2 mean CHIP:H3K27me3:trophoblast female embryo (20 weeks) CHIP ChIP-Histone:H3K27me3/trophoblast female embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2149 0 ENCFF129NIH /home/drk/tillage/datasets/human/chip/encode/ENCSR222MYK/summary/ENCFF129NIH.w5 32 2 mean CHIP:SRSF7:K562 CHIP ChIP-TF:SRSF7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2150 0 ENCFF750GKW /home/drk/tillage/datasets/human/chip/encode/ENCSR222QLW/summary/ENCFF750GKW.w5 32 2 mean CHIP:H3K27ac:T-cell male adult (37 years) CHIP ChIP-Histone:H3K27ac/T-cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2151 0 ENCFF599OCP /home/drk/tillage/datasets/human/chip/encode/ENCSR222SQE/summary/ENCFF599OCP.w5 32 2 mean CHIP:CTCF:sigmoid colon male adult (54 years) CHIP ChIP-TF:CTCF/sigmoid colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2152 0 ENCFF988KPC /home/drk/tillage/datasets/human/chip/encode/ENCSR223APP/summary/ENCFF988KPC.w5 32 2 mean CHIP:H3K4me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2153 0 ENCFF549BUB /home/drk/tillage/datasets/human/chip/encode/ENCSR223MLH/summary/ENCFF549BUB.w5 32 2 mean CHIP:BRCA1:K562 CHIP ChIP-TF:BRCA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2154 0 ENCFF773LQW /home/drk/tillage/datasets/human/chip/encode/ENCSR223TAV/summary/ENCFF773LQW.w5 32 2 mean CHIP:eGFP-PRDM10:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM10/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2155 0 ENCFF332HAA /home/drk/tillage/datasets/human/chip/encode/ENCSR223UPC/summary/ENCFF332HAA.w5 32 2 mean CHIP:H3K27ac:HUES48 CHIP ChIP-Histone:H3K27ac/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2156 0 ENCFF294MJZ /home/drk/tillage/datasets/human/chip/encode/ENCSR224LFY/summary/ENCFF294MJZ.w5 32 2 mean CHIP:H3K9me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2157 0 ENCFF362TVO /home/drk/tillage/datasets/human/chip/encode/ENCSR224NFP/summary/ENCFF362TVO.w5 32 2 mean CHIP:eGFP-ZNF426:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF426/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2158 0 ENCFF600OCW /home/drk/tillage/datasets/human/chip/encode/ENCSR224QDY/summary/ENCFF600OCW.w5 32 2 mean CHIP:eGFP-ZNF121:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF121/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2159 0 ENCFF606IEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR225OKX/summary/ENCFF606IEQ.w5 32 2 mean CHIP:CTCF:omental fat pad female adult (51 year) CHIP ChIP-TF:CTCF/omental fat pad female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2160 0 ENCFF105FOI /home/drk/tillage/datasets/human/chip/encode/ENCSR225VCV/summary/ENCFF105FOI.w5 32 2 mean CHIP:H3K36me3:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K36me3/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2161 0 ENCFF501PAT /home/drk/tillage/datasets/human/chip/encode/ENCSR226QQM/summary/ENCFF501PAT.w5 32 2 mean CHIP:3xFLAG-NFIA:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NFIA/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2162 0 ENCFF174WXW /home/drk/tillage/datasets/human/chip/encode/ENCSR227FYJ/summary/ENCFF174WXW.w5 32 2 mean CHIP:H3K27ac:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K27ac/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2163 0 ENCFF236ZOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR227XNT/summary/ENCFF236ZOJ.w5 32 2 mean CHIP:H2AFZ:HCT116 CHIP ChIP-TF:H2AFZ/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2164 0 ENCFF979ADD /home/drk/tillage/datasets/human/chip/encode/ENCSR228PGT/summary/ENCFF979ADD.w5 32 2 mean CHIP:eGFP-ZNF292:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF292/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2165 0 ENCFF353YJE /home/drk/tillage/datasets/human/chip/encode/ENCSR228ZPZ/summary/ENCFF353YJE.w5 32 2 mean CHIP:EP300:stomach male adult (37 years) CHIP ChIP-TF:EP300/stomach male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2166 0 ENCFF686HOP /home/drk/tillage/datasets/human/chip/encode/ENCSR229DYF/summary/ENCFF686HOP.w5 32 2 mean CHIP:eGFP-ZBTB26:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB26/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2167 0 ENCFF809BZU /home/drk/tillage/datasets/human/chip/encode/ENCSR229KWP/summary/ENCFF809BZU.w5 32 2 mean CHIP:H3K4me1:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K4me1/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2168 0 ENCFF532GZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR229QYR/summary/ENCFF532GZQ.w5 32 2 mean CHIP:H3K9me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2169 0 ENCFF722YGU /home/drk/tillage/datasets/human/chip/encode/ENCSR230BWN/summary/ENCFF722YGU.w5 32 2 mean CHIP:H3K27ac:kidney male adult (67 years) CHIP ChIP-Histone:H3K27ac/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2170 0 ENCFF905FLR /home/drk/tillage/datasets/human/chip/encode/ENCSR230IMS/summary/ENCFF905FLR.w5 32 2 mean CHIP:H3K27ac:liver male adult (31 year) CHIP ChIP-Histone:H3K27ac/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2171 0 ENCFF565YXD /home/drk/tillage/datasets/human/chip/encode/ENCSR230KKL/summary/ENCFF565YXD.w5 32 2 mean CHIP:H3K27me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2172 0 ENCFF814JMY /home/drk/tillage/datasets/human/chip/encode/ENCSR230PTV/summary/ENCFF814JMY.w5 32 2 mean CHIP:ZBTB2:K562 CHIP ChIP-TF:ZBTB2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2173 0 ENCFF136KEU /home/drk/tillage/datasets/human/chip/encode/ENCSR230VEM/summary/ENCFF136KEU.w5 32 2 mean CHIP:H3K4me1:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K4me1/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2174 0 ENCFF920TPY /home/drk/tillage/datasets/human/chip/encode/ENCSR230WNU/summary/ENCFF920TPY.w5 32 2 mean CHIP:H3K4ac:H9 CHIP ChIP-Histone:H3K4ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2175 0 ENCFF299FAH /home/drk/tillage/datasets/human/chip/encode/ENCSR230ZWH/summary/ENCFF299FAH.w5 32 2 mean CHIP:RAD21:liver female child (4 years) CHIP ChIP-TF:RAD21/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2176 0 ENCFF468GVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR231ENE/summary/ENCFF468GVQ.w5 32 2 mean CHIP:ARID3A:MCF-7 CHIP ChIP-TF:ARID3A/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2177 0 ENCFF677JDF /home/drk/tillage/datasets/human/chip/encode/ENCSR231FDF/summary/ENCFF677JDF.w5 32 2 mean CHIP:H3K4me3:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me3/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2178 0 ENCFF076INM /home/drk/tillage/datasets/human/chip/encode/ENCSR231YFE/summary/ENCFF076INM.w5 32 2 mean CHIP:ZBTB33:MCF-7 CHIP ChIP-TF:ZBTB33/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2179 0 ENCFF051PPP /home/drk/tillage/datasets/human/chip/encode/ENCSR233FAG/summary/ENCFF051PPP.w5 32 2 mean CHIP:PKNOX1:HEK293T CHIP ChIP-TF:PKNOX1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2180 0 ENCFF363FAB /home/drk/tillage/datasets/human/chip/encode/ENCSR233LCT/summary/ENCFF363FAB.w5 32 2 mean CHIP:H3K4me1:tibial artery female adult (53 years) CHIP ChIP-Histone:H3K4me1/tibial artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2181 0 ENCFF835ZIW /home/drk/tillage/datasets/human/chip/encode/ENCSR233MWH/summary/ENCFF835ZIW.w5 32 2 mean CHIP:eGFP-ZNF670:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF670/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2182 0 ENCFF600BSH /home/drk/tillage/datasets/human/chip/encode/ENCSR234HEM/summary/ENCFF600BSH.w5 32 2 mean CHIP:CTCF:spleen male adult (37 years) CHIP ChIP-TF:CTCF/spleen male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2183 0 ENCFF048SIP /home/drk/tillage/datasets/human/chip/encode/ENCSR234VCE/summary/ENCFF048SIP.w5 32 2 mean CHIP:DPF2:MCF-7 CHIP ChIP-TF:DPF2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2184 0 ENCFF714QZH /home/drk/tillage/datasets/human/chip/encode/ENCSR234YIU/summary/ENCFF714QZH.w5 32 2 mean CHIP:H3K4me3:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K4me3/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2185 0 ENCFF465PQM /home/drk/tillage/datasets/human/chip/encode/ENCSR235APD/summary/ENCFF465PQM.w5 32 2 mean CHIP:H3K4me1:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K4me1/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2186 0 ENCFF420QJU /home/drk/tillage/datasets/human/chip/encode/ENCSR235CEI/summary/ENCFF420QJU.w5 32 2 mean CHIP:H3K9me3:ectodermal cell originated from embryonic stem cell CHIP ChIP-Histone:H3K9me3/ectodermal cell originated from embryonic stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2187 0 ENCFF866INJ /home/drk/tillage/datasets/human/chip/encode/ENCSR235OVI/summary/ENCFF866INJ.w5 32 2 mean CHIP:3xFLAG-NFKBIZ:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NFKBIZ/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2188 0 ENCFF557ZRD /home/drk/tillage/datasets/human/chip/encode/ENCSR235ZBF/summary/ENCFF557ZRD.w5 32 2 mean CHIP:H3K27ac:spleen male adult (34 years) CHIP ChIP-Histone:H3K27ac/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2189 0 ENCFF688ARC /home/drk/tillage/datasets/human/chip/encode/ENCSR236JVK/summary/ENCFF688ARC.w5 32 2 mean CHIP:H3K9me3:CD14-positive monocyte male adult (21 year) CHIP ChIP-Histone:H3K9me3/CD14-positive monocyte male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2190 0 ENCFF261RPA /home/drk/tillage/datasets/human/chip/encode/ENCSR236XRR/summary/ENCFF261RPA.w5 32 2 mean CHIP:H3K4me3:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K4me3/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2191 0 ENCFF975VDL /home/drk/tillage/datasets/human/chip/encode/ENCSR236YGF/summary/ENCFF975VDL.w5 32 2 mean CHIP:CTCF:transverse colon female adult (53 years) CHIP ChIP-TF:CTCF/transverse colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2192 0 ENCFF322WPO /home/drk/tillage/datasets/human/chip/encode/ENCSR236YPE/summary/ENCFF322WPO.w5 32 2 mean CHIP:H3K36me3:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K36me3/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2193 0 ENCFF595BUX /home/drk/tillage/datasets/human/chip/encode/ENCSR237OBF/summary/ENCFF595BUX.w5 32 2 mean CHIP:H3K36me3:HUES6 CHIP ChIP-Histone:H3K36me3/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2194 0 ENCFF033OVU /home/drk/tillage/datasets/human/chip/encode/ENCSR237QFJ/summary/ENCFF033OVU.w5 32 2 mean CHIP:H3K4me3:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K4me3/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2195 0 ENCFF686MNU /home/drk/tillage/datasets/human/chip/encode/ENCSR237TFX/summary/ENCFF686MNU.w5 32 2 mean CHIP:CTBP1:HEK293T CHIP ChIP-TF:CTBP1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2196 0 ENCFF455HJE /home/drk/tillage/datasets/human/chip/encode/ENCSR237VLT/summary/ENCFF455HJE.w5 32 2 mean CHIP:ZBTB40:K562 CHIP ChIP-TF:ZBTB40/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2197 0 ENCFF735EGF /home/drk/tillage/datasets/human/chip/encode/ENCSR238LEG/summary/ENCFF735EGF.w5 32 2 mean CHIP:H3K4me3:skeletal muscle tissue CHIP ChIP-Histone:H3K4me3/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2198 0 ENCFF015ETD /home/drk/tillage/datasets/human/chip/encode/ENCSR238QRG/summary/ENCFF015ETD.w5 32 2 mean CHIP:TBX3:HepG2 CHIP ChIP-TF:TBX3/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2199 0 ENCFF958PIC /home/drk/tillage/datasets/human/chip/encode/ENCSR238WMO/summary/ENCFF958PIC.w5 32 2 mean CHIP:H3K36me3:neural stem progenitor cell originated from H9 CHIP ChIP-Histone:H3K36me3/neural stem progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2200 0 ENCFF989QYL /home/drk/tillage/datasets/human/chip/encode/ENCSR239SNR/summary/ENCFF989QYL.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2201 0 ENCFF094CHG /home/drk/tillage/datasets/human/chip/encode/ENCSR239ZLZ/summary/ENCFF094CHG.w5 32 2 mean CHIP:eGFP-FOSL1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-FOSL1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2202 0 ENCFF996QRU /home/drk/tillage/datasets/human/chip/encode/ENCSR240LEQ/summary/ENCFF996QRU.w5 32 2 mean CHIP:H3K36me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K36me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2203 0 ENCFF115GQW /home/drk/tillage/datasets/human/chip/encode/ENCSR240PRQ/summary/ENCFF115GQW.w5 32 2 mean CHIP:CTCF:HCT116 CHIP ChIP-TF:CTCF/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2204 0 ENCFF078RMJ /home/drk/tillage/datasets/human/chip/encode/ENCSR240XWM/summary/ENCFF078RMJ.w5 32 2 mean CHIP:LEF1:HEK293T CHIP ChIP-TF:LEF1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2205 0 ENCFF956PHC /home/drk/tillage/datasets/human/chip/encode/ENCSR240ZWZ/summary/ENCFF956PHC.w5 32 2 mean CHIP:H3K36me3:lung female embryo (120 days) CHIP ChIP-Histone:H3K36me3/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2206 0 ENCFF933EFO /home/drk/tillage/datasets/human/chip/encode/ENCSR241JLU/summary/ENCFF933EFO.w5 32 2 mean CHIP:H3K27me3:chorion female embryo (40 weeks) CHIP ChIP-Histone:H3K27me3/chorion female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2207 0 ENCFF422AHV /home/drk/tillage/datasets/human/chip/encode/ENCSR241LIH/summary/ENCFF422AHV.w5 32 2 mean CHIP:AFF1:K562 CHIP ChIP-TF:AFF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2208 0 ENCFF954XJO /home/drk/tillage/datasets/human/chip/encode/ENCSR241PXI/summary/ENCFF954XJO.w5 32 2 mean CHIP:H3K9me3:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K9me3/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2209 0 ENCFF742AUT /home/drk/tillage/datasets/human/chip/encode/ENCSR242BGR/summary/ENCFF742AUT.w5 32 2 mean CHIP:eGFP-ZNF770:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF770/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2210 0 ENCFF517YDA /home/drk/tillage/datasets/human/chip/encode/ENCSR243AIS/summary/ENCFF517YDA.w5 32 2 mean CHIP:H3K36me3:OCI-LY7 CHIP ChIP-Histone:H3K36me3/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2211 0 ENCFF160DIZ /home/drk/tillage/datasets/human/chip/encode/ENCSR243INX/summary/ENCFF160DIZ.w5 32 2 mean CHIP:CTCF:PC-9 CHIP ChIP-TF:CTCF/PC-9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2212 0 ENCFF535QFN /home/drk/tillage/datasets/human/chip/encode/ENCSR243LNQ/summary/ENCFF535QFN.w5 32 2 mean CHIP:PRPF4:HepG2 CHIP ChIP-TF:PRPF4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2213 0 ENCFF777DPY /home/drk/tillage/datasets/human/chip/encode/ENCSR243UVC/summary/ENCFF777DPY.w5 32 2 mean CHIP:H3K9ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K9ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2214 0 ENCFF546FJS /home/drk/tillage/datasets/human/chip/encode/ENCSR244MNY/summary/ENCFF546FJS.w5 32 2 mean CHIP:H3K4me1:chorion female embryo (40 weeks) CHIP ChIP-Histone:H3K4me1/chorion female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2215 0 ENCFF568YMC /home/drk/tillage/datasets/human/chip/encode/ENCSR244XWL/summary/ENCFF568YMC.w5 32 2 mean CHIP:H3K36me3:CD14-positive monocyte male adult (21 year) CHIP ChIP-Histone:H3K36me3/CD14-positive monocyte male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2216 0 ENCFF410UFX /home/drk/tillage/datasets/human/chip/encode/ENCSR244ZAO/summary/ENCFF410UFX.w5 32 2 mean CHIP:EP300:sigmoid colon female adult (51 year) CHIP ChIP-TF:EP300/sigmoid colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2217 0 ENCFF024VLY /home/drk/tillage/datasets/human/chip/encode/ENCSR245BEV/summary/ENCFF024VLY.w5 32 2 mean CHIP:H3K4me3:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K4me3/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2218 0 ENCFF882JPE /home/drk/tillage/datasets/human/chip/encode/ENCSR245QTD/summary/ENCFF882JPE.w5 32 2 mean CHIP:H3K4me1:stomach male child (3 years) CHIP ChIP-Histone:H3K4me1/stomach male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2219 0 ENCFF901VHY /home/drk/tillage/datasets/human/chip/encode/ENCSR245YZT/summary/ENCFF901VHY.w5 32 2 mean CHIP:H3K36me3:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K36me3/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2220 0 ENCFF513PZM /home/drk/tillage/datasets/human/chip/encode/ENCSR245ZCU/summary/ENCFF513PZM.w5 32 2 mean CHIP:H3K9me3:common myeloid progenitor, CD34-positive male adult (42 years) CHIP ChIP-Histone:H3K9me3/common myeloid progenitor, CD34-positive male adult (42 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2221 0 ENCFF210HBA /home/drk/tillage/datasets/human/chip/encode/ENCSR246ARY/summary/ENCFF210HBA.w5 32 2 mean CHIP:H3K4me1:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K4me1/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2222 0 ENCFF839QLL /home/drk/tillage/datasets/human/chip/encode/ENCSR246MLJ/summary/ENCFF839QLL.w5 32 2 mean CHIP:ZFX:22Rv1 CHIP ChIP-TF:ZFX/22Rv1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2223 0 ENCFF380HMH /home/drk/tillage/datasets/human/chip/encode/ENCSR247PYK/summary/ENCFF380HMH.w5 32 2 mean CHIP:H3K9me3:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K9me3/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2224 0 ENCFF615WGO /home/drk/tillage/datasets/human/chip/encode/ENCSR247XFV/summary/ENCFF615WGO.w5 32 2 mean CHIP:CCAR2:HepG2 CHIP ChIP-TF:CCAR2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2225 0 ENCFF462OVP /home/drk/tillage/datasets/human/chip/encode/ENCSR248IMH/summary/ENCFF462OVP.w5 32 2 mean CHIP:NFRKB:MCF-7 CHIP ChIP-TF:NFRKB/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2226 0 ENCFF889GET /home/drk/tillage/datasets/human/chip/encode/ENCSR248KRU/summary/ENCFF889GET.w5 32 2 mean CHIP:H2BK5ac:IMR-90 CHIP ChIP-TF:H2BK5ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2227 0 ENCFF953LUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR248PES/summary/ENCFF953LUQ.w5 32 2 mean CHIP:H3K36me3:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K36me3/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2228 0 ENCFF815TUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR249AWJ/summary/ENCFF815TUQ.w5 32 2 mean CHIP:H3K4me1:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2229 0 ENCFF987EAL /home/drk/tillage/datasets/human/chip/encode/ENCSR249BHQ/summary/ENCFF987EAL.w5 32 2 mean CHIP:ZNF592:K562 CHIP ChIP-TF:ZNF592/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2230 0 ENCFF343NAL /home/drk/tillage/datasets/human/chip/encode/ENCSR249INE/summary/ENCFF343NAL.w5 32 2 mean CHIP:H3K27ac:uterus female adult (53 years) CHIP ChIP-Histone:H3K27ac/uterus female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2231 0 ENCFF995QZD /home/drk/tillage/datasets/human/chip/encode/ENCSR249LNW/summary/ENCFF995QZD.w5 32 2 mean CHIP:H2AFZ:Parathyroid adenoma male adult (65 years) CHIP ChIP-TF:H2AFZ/Parathyroid adenoma male adult (65 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2232 0 ENCFF761MXU /home/drk/tillage/datasets/human/chip/encode/ENCSR249XEB/summary/ENCFF761MXU.w5 32 2 mean CHIP:H3K9me3:spleen male child (3 years) CHIP ChIP-Histone:H3K9me3/spleen male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2233 0 ENCFF335SGC /home/drk/tillage/datasets/human/chip/encode/ENCSR249YGG/summary/ENCFF335SGC.w5 32 2 mean CHIP:H3K4me1:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K4me1/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2234 0 ENCFF088CPA /home/drk/tillage/datasets/human/chip/encode/ENCSR250NHD/summary/ENCFF088CPA.w5 32 2 mean CHIP:H3K27ac:psoas muscle female adult (30 years) CHIP ChIP-Histone:H3K27ac/psoas muscle female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2235 0 ENCFF176WTT /home/drk/tillage/datasets/human/chip/encode/ENCSR250VGX/summary/ENCFF176WTT.w5 32 2 mean CHIP:H2BK12ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2BK12ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2236 0 ENCFF562GJY /home/drk/tillage/datasets/human/chip/encode/ENCSR251OVJ/summary/ENCFF562GJY.w5 32 2 mean CHIP:SMAD5:GM12878 CHIP ChIP-TF:SMAD5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2237 0 ENCFF300TSI /home/drk/tillage/datasets/human/chip/encode/ENCSR252QYR/summary/ENCFF300TSI.w5 32 2 mean CHIP:CTCF:hepatocyte originated from H9 CHIP ChIP-TF:CTCF/hepatocyte originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2238 0 ENCFF041MGW /home/drk/tillage/datasets/human/chip/encode/ENCSR252XWG/summary/ENCFF041MGW.w5 32 2 mean CHIP:CTCF:lower leg skin male adult (54 years) CHIP ChIP-TF:CTCF/lower leg skin male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2239 0 ENCFF425RKN /home/drk/tillage/datasets/human/chip/encode/ENCSR253CKN/summary/ENCFF425RKN.w5 32 2 mean CHIP:eGFP-ZSCAN21:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN21/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2240 0 ENCFF599AVS /home/drk/tillage/datasets/human/chip/encode/ENCSR253JFN/summary/ENCFF599AVS.w5 32 2 mean CHIP:H3K4me1:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K4me1/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2241 0 ENCFF912JZP /home/drk/tillage/datasets/human/chip/encode/ENCSR253OON/summary/ENCFF912JZP.w5 32 2 mean CHIP:3xFLAG-ATF1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ATF1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2242 0 ENCFF616HTG /home/drk/tillage/datasets/human/chip/encode/ENCSR253WMN/summary/ENCFF616HTG.w5 32 2 mean CHIP:H3K9me3:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K9me3/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2243 0 ENCFF155CCW /home/drk/tillage/datasets/human/chip/encode/ENCSR254NLC/summary/ENCFF155CCW.w5 32 2 mean CHIP:H3K4me1:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K4me1/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2244 0 ENCFF366OKB /home/drk/tillage/datasets/human/chip/encode/ENCSR254XTB/summary/ENCFF366OKB.w5 32 2 mean CHIP:H3K27me3:neutrophil male CHIP ChIP-Histone:H3K27me3/neutrophil male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2245 0 ENCFF722DBY /home/drk/tillage/datasets/human/chip/encode/ENCSR254YRM/summary/ENCFF722DBY.w5 32 2 mean CHIP:CTCF:liver female child (6 years) and male adult (32 years) CHIP ChIP-TF:CTCF/liver female child (6 years) and male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2246 0 ENCFF659ZUU /home/drk/tillage/datasets/human/chip/encode/ENCSR256ESY/summary/ENCFF659ZUU.w5 32 2 mean CHIP:H3K36me3:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K36me3/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2247 0 ENCFF584VCI /home/drk/tillage/datasets/human/chip/encode/ENCSR256KRN/summary/ENCFF584VCI.w5 32 2 mean CHIP:H2AFZ:Parathyroid adenoma male adult (62 years) CHIP ChIP-TF:H2AFZ/Parathyroid adenoma male adult (62 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2248 0 ENCFF399FCX /home/drk/tillage/datasets/human/chip/encode/ENCSR256KTR/summary/ENCFF399FCX.w5 32 2 mean CHIP:H3K9me3:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K9me3/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2249 0 ENCFF883GGF /home/drk/tillage/datasets/human/chip/encode/ENCSR257BCD/summary/ENCFF883GGF.w5 32 2 mean CHIP:H3K4me1:stomach male adult (34 years) CHIP ChIP-Histone:H3K4me1/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2250 0 ENCFF735BNC /home/drk/tillage/datasets/human/chip/encode/ENCSR257XVY/summary/ENCFF735BNC.w5 32 2 mean CHIP:eGFP-ZNF83:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF83/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2251 0 ENCFF994TBX /home/drk/tillage/datasets/human/chip/encode/ENCSR258ORJ/summary/ENCFF994TBX.w5 32 2 mean CHIP:H3K9me3:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K9me3/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2252 0 ENCFF487UBR /home/drk/tillage/datasets/human/chip/encode/ENCSR258SXK/summary/ENCFF487UBR.w5 32 2 mean CHIP:SFPQ:HepG2 CHIP ChIP-TF:SFPQ/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2253 0 ENCFF513SIP /home/drk/tillage/datasets/human/chip/encode/ENCSR258UUX/summary/ENCFF513SIP.w5 32 2 mean CHIP:H3K4me3:vagina female adult (53 years) CHIP ChIP-Histone:H3K4me3/vagina female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2254 0 ENCFF710LDA /home/drk/tillage/datasets/human/chip/encode/ENCSR260CXF/summary/ENCFF710LDA.w5 32 2 mean CHIP:H4K91ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H4K91ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2255 0 ENCFF309ZYD /home/drk/tillage/datasets/human/chip/encode/ENCSR260OWP/summary/ENCFF309ZYD.w5 32 2 mean CHIP:H2BK120ac:H9 CHIP ChIP-TF:H2BK120ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2256 0 ENCFF490YHP /home/drk/tillage/datasets/human/chip/encode/ENCSR260UJI/summary/ENCFF490YHP.w5 32 2 mean CHIP:3xFLAG-MBD1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MBD1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2257 0 ENCFF366QWA /home/drk/tillage/datasets/human/chip/encode/ENCSR261EDU/summary/ENCFF366QWA.w5 32 2 mean CHIP:MNT:HepG2 CHIP ChIP-TF:MNT/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2258 0 ENCFF231ZKR /home/drk/tillage/datasets/human/chip/encode/ENCSR261VAS/summary/ENCFF231ZKR.w5 32 2 mean CHIP:CTCF:smooth muscle cell originated from H9 CHIP ChIP-TF:CTCF/smooth muscle cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2259 0 ENCFF074AHS /home/drk/tillage/datasets/human/chip/encode/ENCSR262LFG/summary/ENCFF074AHS.w5 32 2 mean CHIP:H3K9me3:spinal cord female embryo (108 days) CHIP ChIP-Histone:H3K9me3/spinal cord female embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2260 0 ENCFF345HPM /home/drk/tillage/datasets/human/chip/encode/ENCSR262NQD/summary/ENCFF345HPM.w5 32 2 mean CHIP:H3K27me3:HUES48 CHIP ChIP-Histone:H3K27me3/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2261 0 ENCFF174VAY /home/drk/tillage/datasets/human/chip/encode/ENCSR262VXI/summary/ENCFF174VAY.w5 32 2 mean CHIP:H3K27me3:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K27me3/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2262 0 ENCFF379KCI /home/drk/tillage/datasets/human/chip/encode/ENCSR263BGI/summary/ENCFF379KCI.w5 32 2 mean CHIP:H3K4me1:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K4me1/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2263 0 ENCFF932TME /home/drk/tillage/datasets/human/chip/encode/ENCSR263DFP/summary/ENCFF932TME.w5 32 2 mean CHIP:eGFP-PBX2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-PBX2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2264 0 ENCFF455FFY /home/drk/tillage/datasets/human/chip/encode/ENCSR263ELQ/summary/ENCFF455FFY.w5 32 2 mean CHIP:H3K4me3:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K4me3/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2265 0 ENCFF362UQH /home/drk/tillage/datasets/human/chip/encode/ENCSR263WGU/summary/ENCFF362UQH.w5 32 2 mean CHIP:H3K36me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K36me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2266 0 ENCFF067KWB /home/drk/tillage/datasets/human/chip/encode/ENCSR263WLD/summary/ENCFF067KWB.w5 32 2 mean CHIP:H3K4me3:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me3/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2267 0 ENCFF387XNO /home/drk/tillage/datasets/human/chip/encode/ENCSR264APD/summary/ENCFF387XNO.w5 32 2 mean CHIP:H3K4me3:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K4me3/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2268 0 ENCFF887SKH /home/drk/tillage/datasets/human/chip/encode/ENCSR264CZJ/summary/ENCFF887SKH.w5 32 2 mean CHIP:THRA:K562 CHIP ChIP-TF:THRA/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2269 0 ENCFF058VKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR264RJX/summary/ENCFF058VKQ.w5 32 2 mean CHIP:POU5F1:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:POU5F1/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2270 0 ENCFF481SWU /home/drk/tillage/datasets/human/chip/encode/ENCSR264YGM/summary/ENCFF481SWU.w5 32 2 mean CHIP:H3K4me1:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K4me1/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2271 0 ENCFF031ROV /home/drk/tillage/datasets/human/chip/encode/ENCSR265ARE/summary/ENCFF031ROV.w5 32 2 mean CHIP:CTCF:VCaP CHIP ChIP-TF:CTCF/VCaP ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2272 0 ENCFF509VQI /home/drk/tillage/datasets/human/chip/encode/ENCSR265EDV/summary/ENCFF509VQI.w5 32 2 mean CHIP:H2AFZ:H9 CHIP ChIP-TF:H2AFZ/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2273 0 ENCFF114RHO /home/drk/tillage/datasets/human/chip/encode/ENCSR265PFQ/summary/ENCFF114RHO.w5 32 2 mean CHIP:CTCF:body of pancreas male adult (54 years) CHIP ChIP-TF:CTCF/body of pancreas male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2274 0 ENCFF306WEW /home/drk/tillage/datasets/human/chip/encode/ENCSR265WJC/summary/ENCFF306WEW.w5 32 2 mean CHIP:eGFP-KLF4:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-KLF4/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2275 0 ENCFF945AMT /home/drk/tillage/datasets/human/chip/encode/ENCSR266EYO/summary/ENCFF945AMT.w5 32 2 mean CHIP:H3K9me3:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K9me3/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2276 0 ENCFF653YIU /home/drk/tillage/datasets/human/chip/encode/ENCSR266OIG/summary/ENCFF653YIU.w5 32 2 mean CHIP:H3K27me3:liver male adult (31 year) CHIP ChIP-Histone:H3K27me3/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2277 0 ENCFF405MZO /home/drk/tillage/datasets/human/chip/encode/ENCSR266XFE/summary/ENCFF405MZO.w5 32 2 mean CHIP:POLR2A:spleen male adult (54 years) CHIP ChIP-TF:POLR2A/spleen male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2278 0 ENCFF795JUV /home/drk/tillage/datasets/human/chip/encode/ENCSR267DFA/summary/ENCFF795JUV.w5 32 2 mean CHIP:FOXA1:HepG2 CHIP ChIP-TF:FOXA1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2279 0 ENCFF238GQS /home/drk/tillage/datasets/human/chip/encode/ENCSR267UCE/summary/ENCFF238GQS.w5 32 2 mean CHIP:H3F3A:Loucy CHIP ChIP-Histone:H3F3A/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2280 0 ENCFF909JRL /home/drk/tillage/datasets/human/chip/encode/ENCSR267YXV/summary/ENCFF909JRL.w5 32 2 mean CHIP:H3K27ac:neutrophil CHIP ChIP-Histone:H3K27ac/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2281 0 ENCFF011VAN /home/drk/tillage/datasets/human/chip/encode/ENCSR268BMX/summary/ENCFF011VAN.w5 32 2 mean CHIP:H3K27me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2282 0 ENCFF124PPH /home/drk/tillage/datasets/human/chip/encode/ENCSR268JEO/summary/ENCFF124PPH.w5 32 2 mean CHIP:H3K36me3:common myeloid progenitor, CD34-positive male adult (36 years) CHIP ChIP-Histone:H3K36me3/common myeloid progenitor, CD34-positive male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2283 0 ENCFF088WXE /home/drk/tillage/datasets/human/chip/encode/ENCSR268JQE/summary/ENCFF088WXE.w5 32 2 mean CHIP:H3K27ac:ovary female adult (30 years) CHIP ChIP-Histone:H3K27ac/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2284 0 ENCFF207HTQ /home/drk/tillage/datasets/human/chip/encode/ENCSR268QIQ/summary/ENCFF207HTQ.w5 32 2 mean CHIP:SRSF3:K562 CHIP ChIP-TF:SRSF3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2285 0 ENCFF544HBF /home/drk/tillage/datasets/human/chip/encode/ENCSR268ZCF/summary/ENCFF544HBF.w5 32 2 mean CHIP:H3K27ac:sigmoid colon female adult (53 years) CHIP ChIP-Histone:H3K27ac/sigmoid colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2286 0 ENCFF041ACY /home/drk/tillage/datasets/human/chip/encode/ENCSR269GMC/summary/ENCFF041ACY.w5 32 2 mean CHIP:H3K36me3:stomach male child (3 years) CHIP ChIP-Histone:H3K36me3/stomach male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2287 0 ENCFF192BGD /home/drk/tillage/datasets/human/chip/encode/ENCSR269TNX/summary/ENCFF192BGD.w5 32 2 mean CHIP:3xFLAG-GABPA:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-GABPA/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2288 0 ENCFF014FHY /home/drk/tillage/datasets/human/chip/encode/ENCSR269ULZ/summary/ENCFF014FHY.w5 32 2 mean CHIP:H3K9me3:cardiac muscle cell CHIP ChIP-Histone:H3K9me3/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2289 0 ENCFF007GYM /home/drk/tillage/datasets/human/chip/encode/ENCSR270TYZ/summary/ENCFF007GYM.w5 32 2 mean CHIP:EP300:suprapubic skin male adult (37 years) CHIP ChIP-TF:EP300/suprapubic skin male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2290 0 ENCFF139WXH /home/drk/tillage/datasets/human/chip/encode/ENCSR270VNK/summary/ENCFF139WXH.w5 32 2 mean CHIP:H3K9me3:small intestine female adult (30 years) CHIP ChIP-Histone:H3K9me3/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2291 0 ENCFF593OAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR271TFS/summary/ENCFF593OAZ.w5 32 2 mean CHIP:H3K4me1:H1-hESC CHIP ChIP-Histone:H3K4me1/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2292 0 ENCFF055JAB /home/drk/tillage/datasets/human/chip/encode/ENCSR272GZG/summary/ENCFF055JAB.w5 32 2 mean CHIP:H3K36me3:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K36me3/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2293 0 ENCFF803KNM /home/drk/tillage/datasets/human/chip/encode/ENCSR272JAT/summary/ENCFF803KNM.w5 32 2 mean CHIP:CBX5:K562 CHIP ChIP-TF:CBX5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2294 0 ENCFF711TRT /home/drk/tillage/datasets/human/chip/encode/ENCSR273IYV/summary/ENCFF711TRT.w5 32 2 mean CHIP:H3K27me3:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K27me3/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2295 0 ENCFF158FNU /home/drk/tillage/datasets/human/chip/encode/ENCSR273NXD/summary/ENCFF158FNU.w5 32 2 mean CHIP:H3K27me3:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2296 0 ENCFF260ELZ /home/drk/tillage/datasets/human/chip/encode/ENCSR273TNG/summary/ENCFF260ELZ.w5 32 2 mean CHIP:H3K4me1:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K4me1/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2297 0 ENCFF120LKN /home/drk/tillage/datasets/human/chip/encode/ENCSR274LVQ/summary/ENCFF120LKN.w5 32 2 mean CHIP:eGFP-ZNF776:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF776/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2298 0 ENCFF291KNR /home/drk/tillage/datasets/human/chip/encode/ENCSR274OIJ/summary/ENCFF291KNR.w5 32 2 mean CHIP:H3K4me1:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K4me1/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2299 0 ENCFF566XNE /home/drk/tillage/datasets/human/chip/encode/ENCSR274SLQ/summary/ENCFF566XNE.w5 32 2 mean CHIP:CHD2:SK-N-SH CHIP ChIP-TF:CHD2/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2300 0 ENCFF910ERS /home/drk/tillage/datasets/human/chip/encode/ENCSR274TJB/summary/ENCFF910ERS.w5 32 2 mean CHIP:H2BK15ac:IMR-90 CHIP ChIP-TF:H2BK15ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2301 0 ENCFF495VSL /home/drk/tillage/datasets/human/chip/encode/ENCSR275DXO/summary/ENCFF495VSL.w5 32 2 mean CHIP:H3K27me3:liver male adult (78 years) CHIP ChIP-Histone:H3K27me3/liver male adult (78 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2302 0 ENCFF557YZA /home/drk/tillage/datasets/human/chip/encode/ENCSR275EAG/summary/ENCFF557YZA.w5 32 2 mean CHIP:H3K4me3:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K4me3/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2303 0 ENCFF526LAW /home/drk/tillage/datasets/human/chip/encode/ENCSR275GBW/summary/ENCFF526LAW.w5 32 2 mean CHIP:H3K9ac:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K9ac/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2304 0 ENCFF932KMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR275NCH/summary/ENCFF932KMQ.w5 32 2 mean CHIP:H3K4me3:PC-3 CHIP ChIP-Histone:H3K4me3/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2305 0 ENCFF688IVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR276BXF/summary/ENCFF688IVJ.w5 32 2 mean CHIP:H3K4me3:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K4me3/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2306 0 ENCFF767AJL /home/drk/tillage/datasets/human/chip/encode/ENCSR276HBK/summary/ENCFF767AJL.w5 32 2 mean CHIP:H3K4me1:H9 CHIP ChIP-Histone:H3K4me1/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2307 0 ENCFF772PRW /home/drk/tillage/datasets/human/chip/encode/ENCSR276OLB/summary/ENCFF772PRW.w5 32 2 mean CHIP:H3K4me1:cardiac muscle cell CHIP ChIP-Histone:H3K4me1/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2308 0 ENCFF419AJY /home/drk/tillage/datasets/human/chip/encode/ENCSR276ZBE/summary/ENCFF419AJY.w5 32 2 mean CHIP:H3K4me1:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K4me1/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2309 0 ENCFF277WLP /home/drk/tillage/datasets/human/chip/encode/ENCSR276ZSL/summary/ENCFF277WLP.w5 32 2 mean CHIP:H3K9me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2310 0 ENCFF005GDA /home/drk/tillage/datasets/human/chip/encode/ENCSR277BXW/summary/ENCFF005GDA.w5 32 2 mean CHIP:ZBTB7B:MCF-7 CHIP ChIP-TF:ZBTB7B/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2311 0 ENCFF344GVP /home/drk/tillage/datasets/human/chip/encode/ENCSR277DMR/summary/ENCFF344GVP.w5 32 2 mean CHIP:eGFP-ETV1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ETV1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2312 0 ENCFF300OZI /home/drk/tillage/datasets/human/chip/encode/ENCSR277JAU/summary/ENCFF300OZI.w5 32 2 mean CHIP:H4K8ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H4K8ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2313 0 ENCFF539BSO /home/drk/tillage/datasets/human/chip/encode/ENCSR277OOQ/summary/ENCFF539BSO.w5 32 2 mean CHIP:ZC3H11A:A549 CHIP ChIP-TF:ZC3H11A/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2314 0 ENCFF804DFG /home/drk/tillage/datasets/human/chip/encode/ENCSR277PDE/summary/ENCFF804DFG.w5 32 2 mean CHIP:H3K36me3:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K36me3/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2315 0 ENCFF636TVU /home/drk/tillage/datasets/human/chip/encode/ENCSR277VIC/summary/ENCFF636TVU.w5 32 2 mean CHIP:HDAC6:HepG2 CHIP ChIP-TF:HDAC6/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2316 0 ENCFF788XJB /home/drk/tillage/datasets/human/chip/encode/ENCSR278JQG/summary/ENCFF788XJB.w5 32 2 mean CHIP:IKZF1:HepG2 CHIP ChIP-TF:IKZF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2317 0 ENCFF355PIJ /home/drk/tillage/datasets/human/chip/encode/ENCSR278SQL/summary/ENCFF355PIJ.w5 32 2 mean CHIP:NBN:GM12878 CHIP ChIP-TF:NBN/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2318 0 ENCFF207WDT /home/drk/tillage/datasets/human/chip/encode/ENCSR279HKO/summary/ENCFF207WDT.w5 32 2 mean CHIP:H3K4me1:radial glial cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K4me1/radial glial cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2319 0 ENCFF498KTC /home/drk/tillage/datasets/human/chip/encode/ENCSR279IEM/summary/ENCFF498KTC.w5 32 2 mean CHIP:SIX4:MCF-7 CHIP ChIP-TF:SIX4/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2320 0 ENCFF180ETH /home/drk/tillage/datasets/human/chip/encode/ENCSR279JHU/summary/ENCFF180ETH.w5 32 2 mean CHIP:H4K20me1:DOHH2 CHIP ChIP-TF:H4K20me1/DOHH2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2321 0 ENCFF784RXL /home/drk/tillage/datasets/human/chip/encode/ENCSR279KDC/summary/ENCFF784RXL.w5 32 2 mean CHIP:eGFP-ZNF677:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF677/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2322 0 ENCFF785XPE /home/drk/tillage/datasets/human/chip/encode/ENCSR279KIX/summary/ENCFF785XPE.w5 32 2 mean CHIP:H3K27ac:C4-2B CHIP ChIP-Histone:H3K27ac/C4-2B ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2323 0 ENCFF546GZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR279MCN/summary/ENCFF546GZQ.w5 32 2 mean CHIP:H3K36me3:esophagus female adult (30 years) CHIP ChIP-Histone:H3K36me3/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2324 0 ENCFF391TUR /home/drk/tillage/datasets/human/chip/encode/ENCSR280IFJ/summary/ENCFF391TUR.w5 32 2 mean CHIP:H3K79me1:H9 CHIP ChIP-Histone:H3K79me1/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2325 0 ENCFF665DKU /home/drk/tillage/datasets/human/chip/encode/ENCSR281JXC/summary/ENCFF665DKU.w5 32 2 mean CHIP:H3K27me3:heart embryo (101 day) CHIP ChIP-Histone:H3K27me3/heart embryo (101 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2326 0 ENCFF209WPF /home/drk/tillage/datasets/human/chip/encode/ENCSR282SNG/summary/ENCFF209WPF.w5 32 2 mean CHIP:H3K23ac:H9 CHIP ChIP-Histone:H3K23ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2327 0 ENCFF384ZUA /home/drk/tillage/datasets/human/chip/encode/ENCSR283DOU/summary/ENCFF384ZUA.w5 32 2 mean CHIP:eGFP-ZNF660:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF660/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2328 0 ENCFF491FSW /home/drk/tillage/datasets/human/chip/encode/ENCSR283MWQ/summary/ENCFF491FSW.w5 32 2 mean CHIP:eGFP-ZNF133:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF133/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2329 0 ENCFF481UCN /home/drk/tillage/datasets/human/chip/encode/ENCSR283STF/summary/ENCFF481UCN.w5 32 2 mean CHIP:H3K14ac:IMR-90 CHIP ChIP-Histone:H3K14ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2330 0 ENCFF381GEM /home/drk/tillage/datasets/human/chip/encode/ENCSR283ZNI/summary/ENCFF381GEM.w5 32 2 mean CHIP:ZBTB8A:K562 CHIP ChIP-TF:ZBTB8A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2331 0 ENCFF151PMX /home/drk/tillage/datasets/human/chip/encode/ENCSR283ZRI/summary/ENCFF151PMX.w5 32 2 mean CHIP:POLR2G:K562 CHIP ChIP-TF:POLR2G/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2332 0 ENCFF691LHZ /home/drk/tillage/datasets/human/chip/encode/ENCSR284EJR/summary/ENCFF691LHZ.w5 32 2 mean CHIP:H3K27me3:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K27me3/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2333 0 ENCFF027GWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR285UTJ/summary/ENCFF027GWJ.w5 32 2 mean CHIP:H3K27me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2334 0 ENCFF891OWF /home/drk/tillage/datasets/human/chip/encode/ENCSR286PCG/summary/ENCFF891OWF.w5 32 2 mean CHIP:ZBED1:K562 CHIP ChIP-TF:ZBED1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2335 0 ENCFF565ZIS /home/drk/tillage/datasets/human/chip/encode/ENCSR286VMZ/summary/ENCFF565ZIS.w5 32 2 mean CHIP:H3K36me3:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K36me3/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2336 0 ENCFF917DKU /home/drk/tillage/datasets/human/chip/encode/ENCSR286WUR/summary/ENCFF917DKU.w5 32 2 mean CHIP:H3K9me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K9me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2337 0 ENCFF340EYA /home/drk/tillage/datasets/human/chip/encode/ENCSR287UQG/summary/ENCFF340EYA.w5 32 2 mean CHIP:H3K36me3:muscle layer of duodenum male adult (73 years) CHIP ChIP-Histone:H3K36me3/muscle layer of duodenum male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2338 0 ENCFF014YCW /home/drk/tillage/datasets/human/chip/encode/ENCSR287VPM/summary/ENCFF014YCW.w5 32 2 mean CHIP:H3K4me3:SK-N-MC CHIP ChIP-Histone:H3K4me3/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2339 0 ENCFF744ANQ /home/drk/tillage/datasets/human/chip/encode/ENCSR287YDU/summary/ENCFF744ANQ.w5 32 2 mean CHIP:H3K4me3:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K4me3/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2340 0 ENCFF137NZS /home/drk/tillage/datasets/human/chip/encode/ENCSR288IJC/summary/ENCFF137NZS.w5 32 2 mean CHIP:MAZ:MCF-7 CHIP ChIP-TF:MAZ/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2341 0 ENCFF242YCI /home/drk/tillage/datasets/human/chip/encode/ENCSR288MOZ/summary/ENCFF242YCI.w5 32 2 mean CHIP:LARP7:K562 CHIP ChIP-TF:LARP7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2342 0 ENCFF972NXF /home/drk/tillage/datasets/human/chip/encode/ENCSR289NSN/summary/ENCFF972NXF.w5 32 2 mean CHIP:eGFP-ZNF354C:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF354C/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2343 0 ENCFF878RPM /home/drk/tillage/datasets/human/chip/encode/ENCSR289TGF/summary/ENCFF878RPM.w5 32 2 mean CHIP:H4K20me1:hepatocyte originated from H9 CHIP ChIP-TF:H4K20me1/hepatocyte originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2344 0 ENCFF038PEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR289VTP/summary/ENCFF038PEZ.w5 32 2 mean CHIP:POLR2A:spleen female adult (53 years) CHIP ChIP-TF:POLR2A/spleen female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2345 0 ENCFF942UAU /home/drk/tillage/datasets/human/chip/encode/ENCSR290EHP/summary/ENCFF942UAU.w5 32 2 mean CHIP:H3K4me1:mid-neurogenesis radial glial cells genetically modified using stable transfection NONE and originated from H9 CHIP ChIP-Histone:H3K4me1/mid-neurogenesis radial glial cells genetically modified using stable transfection NONE and originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2346 0 ENCFF477SSU /home/drk/tillage/datasets/human/chip/encode/ENCSR290MUH/summary/ENCFF477SSU.w5 32 2 mean CHIP:eGFP-GABPA:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-GABPA/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2347 0 ENCFF621LMW /home/drk/tillage/datasets/human/chip/encode/ENCSR290QBB/summary/ENCFF621LMW.w5 32 2 mean CHIP:EP300:upper lobe of left lung male adult (54 years) CHIP ChIP-TF:EP300/upper lobe of left lung male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2348 0 ENCFF085TTG /home/drk/tillage/datasets/human/chip/encode/ENCSR290SSQ/summary/ENCFF085TTG.w5 32 2 mean CHIP:eGFP-MAZ:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-MAZ/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2349 0 ENCFF929BLX /home/drk/tillage/datasets/human/chip/encode/ENCSR290YLQ/summary/ENCFF929BLX.w5 32 2 mean CHIP:H3K4me1:B cell female adult (27 years) CHIP ChIP-Histone:H3K4me1/B cell female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2350 0 ENCFF287REX /home/drk/tillage/datasets/human/chip/encode/ENCSR290ZOS/summary/ENCFF287REX.w5 32 2 mean CHIP:EGR1:liver female child (4 years) CHIP ChIP-TF:EGR1/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2351 0 ENCFF342QXW /home/drk/tillage/datasets/human/chip/encode/ENCSR291KBJ/summary/ENCFF342QXW.w5 32 2 mean CHIP:H3K4me3:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me3/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2352 0 ENCFF196CZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR292WQY/summary/ENCFF196CZJ.w5 32 2 mean CHIP:H3K4me1:endocrine pancreas male adult (46 years) CHIP ChIP-Histone:H3K4me1/endocrine pancreas male adult (46 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2353 0 ENCFF159UNP /home/drk/tillage/datasets/human/chip/encode/ENCSR292ZMG/summary/ENCFF159UNP.w5 32 2 mean CHIP:H3K36me3:regulatory T cell originated from blood cell CHIP ChIP-Histone:H3K36me3/regulatory T cell originated from blood cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2354 0 ENCFF244AQE /home/drk/tillage/datasets/human/chip/encode/ENCSR293MTQ/summary/ENCFF244AQE.w5 32 2 mean CHIP:H3K4me3:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me3/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2355 0 ENCFF711IUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR293NAJ/summary/ENCFF711IUJ.w5 32 2 mean CHIP:H4K20me1:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:H4K20me1/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2356 0 ENCFF353YGE /home/drk/tillage/datasets/human/chip/encode/ENCSR293QAR/summary/ENCFF353YGE.w5 32 2 mean CHIP:MTA2:GM12878 CHIP ChIP-TF:MTA2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2357 0 ENCFF696ZBD /home/drk/tillage/datasets/human/chip/encode/ENCSR293UEB/summary/ENCFF696ZBD.w5 32 2 mean CHIP:H3K4me1:luminal epithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K4me1/luminal epithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2358 0 ENCFF455KGB /home/drk/tillage/datasets/human/chip/encode/ENCSR294GDI/summary/ENCFF455KGB.w5 32 2 mean CHIP:H3K9me3:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K9me3/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2359 0 ENCFF604QPX /home/drk/tillage/datasets/human/chip/encode/ENCSR294JWV/summary/ENCFF604QPX.w5 32 2 mean CHIP:ZFP36:A549 CHIP ChIP-TF:ZFP36/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2360 0 ENCFF579CVA /home/drk/tillage/datasets/human/chip/encode/ENCSR294PQF/summary/ENCFF579CVA.w5 32 2 mean CHIP:H3K4me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K4me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2361 0 ENCFF336BKJ /home/drk/tillage/datasets/human/chip/encode/ENCSR294WUR/summary/ENCFF336BKJ.w5 32 2 mean CHIP:H3K18ac:H9 CHIP ChIP-Histone:H3K18ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2362 0 ENCFF150AVW /home/drk/tillage/datasets/human/chip/encode/ENCSR295BIP/summary/ENCFF150AVW.w5 32 2 mean CHIP:eGFP-ZNF777:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF777/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2363 0 ENCFF348EOC /home/drk/tillage/datasets/human/chip/encode/ENCSR295GRB/summary/ENCFF348EOC.w5 32 2 mean CHIP:eGFP-ZNF213:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF213/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2364 0 ENCFF125BNT /home/drk/tillage/datasets/human/chip/encode/ENCSR295LHC/summary/ENCFF125BNT.w5 32 2 mean CHIP:H3K27me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K27me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2365 0 ENCFF461DIC /home/drk/tillage/datasets/human/chip/encode/ENCSR296MXW/summary/ENCFF461DIC.w5 32 2 mean CHIP:HNRNPUL1:K562 CHIP ChIP-TF:HNRNPUL1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2366 0 ENCFF442JEY /home/drk/tillage/datasets/human/chip/encode/ENCSR297AUZ/summary/ENCFF442JEY.w5 32 2 mean CHIP:H2BK15ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H2BK15ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2367 0 ENCFF794EAC /home/drk/tillage/datasets/human/chip/encode/ENCSR297GII/summary/ENCFF794EAC.w5 32 2 mean CHIP:HNF4G:liver female child (4 years) CHIP ChIP-TF:HNF4G/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2368 0 ENCFF190VXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR297MUV/summary/ENCFF190VXQ.w5 32 2 mean CHIP:EZH2phosphoT487:SK-N-SH CHIP ChIP-TF:EZH2phosphoT487/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2369 0 ENCFF417DPL /home/drk/tillage/datasets/human/chip/encode/ENCSR297YOC/summary/ENCFF417DPL.w5 32 2 mean CHIP:H3K36me3:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K36me3/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2370 0 ENCFF200ZNJ /home/drk/tillage/datasets/human/chip/encode/ENCSR298JCG/summary/ENCFF200ZNJ.w5 32 2 mean CHIP:NCOR1:K562 CHIP ChIP-TF:NCOR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2371 0 ENCFF753POK /home/drk/tillage/datasets/human/chip/encode/ENCSR298PMB/summary/ENCFF753POK.w5 32 2 mean CHIP:H3K9me3:thymus male child (3 years) CHIP ChIP-Histone:H3K9me3/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2372 0 ENCFF951QOC /home/drk/tillage/datasets/human/chip/encode/ENCSR298QUH/summary/ENCFF951QOC.w5 32 2 mean CHIP:eGFP-MZF1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-MZF1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2373 0 ENCFF916KUH /home/drk/tillage/datasets/human/chip/encode/ENCSR299CAV/summary/ENCFF916KUH.w5 32 2 mean CHIP:POLR2A:breast epithelium female adult (53 years) CHIP ChIP-TF:POLR2A/breast epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2374 0 ENCFF031GKU /home/drk/tillage/datasets/human/chip/encode/ENCSR300KUL/summary/ENCFF031GKU.w5 32 2 mean CHIP:EP300:suprapubic skin female adult (51 year) CHIP ChIP-TF:EP300/suprapubic skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2375 0 ENCFF011TOL /home/drk/tillage/datasets/human/chip/encode/ENCSR301AEA/summary/ENCFF011TOL.w5 32 2 mean CHIP:H3K4me1:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K4me1/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2376 0 ENCFF833AVU /home/drk/tillage/datasets/human/chip/encode/ENCSR301HRV/summary/ENCFF833AVU.w5 32 2 mean CHIP:H3K79me2:H1-hESC CHIP ChIP-Histone:H3K79me2/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2377 0 ENCFF102QWZ /home/drk/tillage/datasets/human/chip/encode/ENCSR301VIW/summary/ENCFF102QWZ.w5 32 2 mean CHIP:H2AFZ:smooth muscle cell originated from H9 CHIP ChIP-TF:H2AFZ/smooth muscle cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2378 0 ENCFF648RXN /home/drk/tillage/datasets/human/chip/encode/ENCSR302AWT/summary/ENCFF648RXN.w5 32 2 mean CHIP:FOXK2:K562 CHIP ChIP-TF:FOXK2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2379 0 ENCFF614JOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR303GFI/summary/ENCFF614JOJ.w5 32 2 mean CHIP:CTCF:RWPE1 CHIP ChIP-TF:CTCF/RWPE1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2380 0 ENCFF418XFA /home/drk/tillage/datasets/human/chip/encode/ENCSR303IKJ/summary/ENCFF418XFA.w5 32 2 mean CHIP:H3K27ac:thymus male child (3 years) CHIP ChIP-Histone:H3K27ac/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2381 0 ENCFF245VXE /home/drk/tillage/datasets/human/chip/encode/ENCSR303OIB/summary/ENCFF245VXE.w5 32 2 mean CHIP:H3K4me1:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K4me1/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2382 0 ENCFF435QCJ /home/drk/tillage/datasets/human/chip/encode/ENCSR304AMN/summary/ENCFF435QCJ.w5 32 2 mean CHIP:eGFP-IKZF3:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-IKZF3/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2383 0 ENCFF692HMO /home/drk/tillage/datasets/human/chip/encode/ENCSR304IVU/summary/ENCFF692HMO.w5 32 2 mean CHIP:POLR2A:breast epithelium female adult (51 year) CHIP ChIP-TF:POLR2A/breast epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2384 0 ENCFF499EZR /home/drk/tillage/datasets/human/chip/encode/ENCSR304XUZ/summary/ENCFF499EZR.w5 32 2 mean CHIP:CTCF:breast epithelium female adult (53 years) CHIP ChIP-TF:CTCF/breast epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2385 0 ENCFF647BNU /home/drk/tillage/datasets/human/chip/encode/ENCSR305ISQ/summary/ENCFF647BNU.w5 32 2 mean CHIP:H3K27ac:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K27ac/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2386 0 ENCFF051KHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR306VSH/summary/ENCFF051KHQ.w5 32 2 mean CHIP:H3K4me1:Karpas-422 CHIP ChIP-Histone:H3K4me1/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2387 0 ENCFF683EMI /home/drk/tillage/datasets/human/chip/encode/ENCSR306ZBD/summary/ENCFF683EMI.w5 32 2 mean CHIP:H3K4me1:esophagus male adult (34 years) CHIP ChIP-Histone:H3K4me1/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2388 0 ENCFF681KAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR307CKC/summary/ENCFF681KAZ.w5 32 2 mean CHIP:eGFP-ZNF680:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF680/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2389 0 ENCFF529EAW /home/drk/tillage/datasets/human/chip/encode/ENCSR307DQT/summary/ENCFF529EAW.w5 32 2 mean CHIP:H3K27ac:SU-DHL-6 CHIP ChIP-Histone:H3K27ac/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2390 0 ENCFF092ORD /home/drk/tillage/datasets/human/chip/encode/ENCSR307OAJ/summary/ENCFF092ORD.w5 32 2 mean CHIP:H3K4me1:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K4me1/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2391 0 ENCFF603HTW /home/drk/tillage/datasets/human/chip/encode/ENCSR307PFP/summary/ENCFF603HTW.w5 32 2 mean CHIP:CTCF:body of pancreas male adult (37 years) CHIP ChIP-TF:CTCF/body of pancreas male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2392 0 ENCFF584VBB /home/drk/tillage/datasets/human/chip/encode/ENCSR308ZMD/summary/ENCFF584VBB.w5 32 2 mean CHIP:H3K4me3:thymus female embryo (110 days) CHIP ChIP-Histone:H3K4me3/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2393 0 ENCFF186VXN /home/drk/tillage/datasets/human/chip/encode/ENCSR309ELI/summary/ENCFF186VXN.w5 32 2 mean CHIP:ZBTB1:MCF-7 CHIP ChIP-TF:ZBTB1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2394 0 ENCFF227URY /home/drk/tillage/datasets/human/chip/encode/ENCSR310NYI/summary/ENCFF227URY.w5 32 2 mean CHIP:FOXA2:liver male adult (32 years) CHIP ChIP-TF:FOXA2/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2395 0 ENCFF068HXC /home/drk/tillage/datasets/human/chip/encode/ENCSR311DQO/summary/ENCFF068HXC.w5 32 2 mean CHIP:H2AFZ:ACC112 CHIP ChIP-TF:H2AFZ/ACC112 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2396 0 ENCFF021XZY /home/drk/tillage/datasets/human/chip/encode/ENCSR311OCP/summary/ENCFF021XZY.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2397 0 ENCFF087ZKE /home/drk/tillage/datasets/human/chip/encode/ENCSR311RML/summary/ENCFF087ZKE.w5 32 2 mean CHIP:H3K27me3:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K27me3/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2398 0 ENCFF754IPD /home/drk/tillage/datasets/human/chip/encode/ENCSR311XVL/summary/ENCFF754IPD.w5 32 2 mean CHIP:H3K9me3:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K9me3/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2399 0 ENCFF365LDJ /home/drk/tillage/datasets/human/chip/encode/ENCSR312CKN/summary/ENCFF365LDJ.w5 32 2 mean CHIP:H3K27me3:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K27me3/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2400 0 ENCFF368GND /home/drk/tillage/datasets/human/chip/encode/ENCSR312NYS/summary/ENCFF368GND.w5 32 2 mean CHIP:H3K36me3:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K36me3/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2401 0 ENCFF439OWG /home/drk/tillage/datasets/human/chip/encode/ENCSR313BMV/summary/ENCFF439OWG.w5 32 2 mean CHIP:EP300:sigmoid colon female adult (53 years) CHIP ChIP-TF:EP300/sigmoid colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2402 0 ENCFF448HTE /home/drk/tillage/datasets/human/chip/encode/ENCSR313GUP/summary/ENCFF448HTE.w5 32 2 mean CHIP:H3K36me3:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K36me3/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2403 0 ENCFF016ZPC /home/drk/tillage/datasets/human/chip/encode/ENCSR313NJN/summary/ENCFF016ZPC.w5 32 2 mean CHIP:H3F3A:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3F3A/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2404 0 ENCFF337CGA /home/drk/tillage/datasets/human/chip/encode/ENCSR313SEO/summary/ENCFF337CGA.w5 32 2 mean CHIP:H3K4me3:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2405 0 ENCFF222TTP /home/drk/tillage/datasets/human/chip/encode/ENCSR313VZG/summary/ENCFF222TTP.w5 32 2 mean CHIP:FIP1L1:HepG2 CHIP ChIP-TF:FIP1L1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2406 0 ENCFF570CAT /home/drk/tillage/datasets/human/chip/encode/ENCSR314BBS/summary/ENCFF570CAT.w5 32 2 mean CHIP:eGFP-PTTG1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-PTTG1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2407 0 ENCFF810PQK /home/drk/tillage/datasets/human/chip/encode/ENCSR314BEX/summary/ENCFF810PQK.w5 32 2 mean CHIP:H3K27ac:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27ac/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2408 0 ENCFF921FBI /home/drk/tillage/datasets/human/chip/encode/ENCSR314SPW/summary/ENCFF921FBI.w5 32 2 mean CHIP:H3K4me3:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K4me3/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2409 0 ENCFF548EWI /home/drk/tillage/datasets/human/chip/encode/ENCSR314WYC/summary/ENCFF548EWI.w5 32 2 mean CHIP:H3K4me3:neuron originated from H9 CHIP ChIP-Histone:H3K4me3/neuron originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2410 0 ENCFF905JES /home/drk/tillage/datasets/human/chip/encode/ENCSR315IRO/summary/ENCFF905JES.w5 32 2 mean CHIP:H3K27ac:HUES6 CHIP ChIP-Histone:H3K27ac/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2411 0 ENCFF331ZDS /home/drk/tillage/datasets/human/chip/encode/ENCSR315JJE/summary/ENCFF331ZDS.w5 32 2 mean CHIP:HNRNPL:HepG2 CHIP ChIP-TF:HNRNPL/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2412 0 ENCFF942UQE /home/drk/tillage/datasets/human/chip/encode/ENCSR315LPR/summary/ENCFF942UQE.w5 32 2 mean CHIP:H3K4me3:pancreas female adult (30 years) CHIP ChIP-Histone:H3K4me3/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2413 0 ENCFF734ERD /home/drk/tillage/datasets/human/chip/encode/ENCSR315NAC/summary/ENCFF734ERD.w5 32 2 mean CHIP:CTCF:LNCAP CHIP ChIP-TF:CTCF/LNCAP ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2414 0 ENCFF819HQT /home/drk/tillage/datasets/human/chip/encode/ENCSR315NNL/summary/ENCFF819HQT.w5 32 2 mean CHIP:CHAMP1:K562 CHIP ChIP-TF:CHAMP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2415 0 ENCFF795MUD /home/drk/tillage/datasets/human/chip/encode/ENCSR316KHQ/summary/ENCFF795MUD.w5 32 2 mean CHIP:H3K36me3:SU-DHL-6 CHIP ChIP-Histone:H3K36me3/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2416 0 ENCFF247WCG /home/drk/tillage/datasets/human/chip/encode/ENCSR316MNI/summary/ENCFF247WCG.w5 32 2 mean CHIP:H3K9me3:HUES64 CHIP ChIP-Histone:H3K9me3/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2417 0 ENCFF315KPL /home/drk/tillage/datasets/human/chip/encode/ENCSR317MKR/summary/ENCFF315KPL.w5 32 2 mean CHIP:H3K9ac:kidney female embryo (120 days) CHIP ChIP-Histone:H3K9ac/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2418 0 ENCFF291KAF /home/drk/tillage/datasets/human/chip/encode/ENCSR317NQG/summary/ENCFF291KAF.w5 32 2 mean CHIP:H2AFZ:Karpas-422 CHIP ChIP-TF:H2AFZ/Karpas-422 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2419 0 ENCFF117RLY /home/drk/tillage/datasets/human/chip/encode/ENCSR318DAP/summary/ENCFF117RLY.w5 32 2 mean CHIP:H3K9me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K9me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2420 0 ENCFF721SMI /home/drk/tillage/datasets/human/chip/encode/ENCSR318HUC/summary/ENCFF721SMI.w5 32 2 mean CHIP:H3K27ac:thoracic aorta male adult (54 years) CHIP ChIP-Histone:H3K27ac/thoracic aorta male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2421 0 ENCFF129CTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR318LVG/summary/ENCFF129CTZ.w5 32 2 mean CHIP:ZBTB40:MCF-7 CHIP ChIP-TF:ZBTB40/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2422 0 ENCFF834YLW /home/drk/tillage/datasets/human/chip/encode/ENCSR319WAD/summary/ENCFF834YLW.w5 32 2 mean CHIP:H3K9me3:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K9me3/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2423 0 ENCFF643OVE /home/drk/tillage/datasets/human/chip/encode/ENCSR320MYR/summary/ENCFF643OVE.w5 32 2 mean CHIP:H3K4me3:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K4me3/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2424 0 ENCFF387NIL /home/drk/tillage/datasets/human/chip/encode/ENCSR321BJQ/summary/ENCFF387NIL.w5 32 2 mean CHIP:EHMT2:A549 CHIP ChIP-TF:EHMT2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2425 0 ENCFF308VMB /home/drk/tillage/datasets/human/chip/encode/ENCSR321LKT/summary/ENCFF308VMB.w5 32 2 mean CHIP:H3K27ac:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K27ac/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2426 0 ENCFF807TFA /home/drk/tillage/datasets/human/chip/encode/ENCSR321MSF/summary/ENCFF807TFA.w5 32 2 mean CHIP:eGFP-ZBTB21:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB21/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2427 0 ENCFF984ZZC /home/drk/tillage/datasets/human/chip/encode/ENCSR321SZE/summary/ENCFF984ZZC.w5 32 2 mean CHIP:H3K4me3:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K4me3/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2428 0 ENCFF896AGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR322BLC/summary/ENCFF896AGZ.w5 32 2 mean CHIP:H3K9me3:lung female embryo (85 days) CHIP ChIP-Histone:H3K9me3/lung female embryo (85 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2429 0 ENCFF498ZJU /home/drk/tillage/datasets/human/chip/encode/ENCSR322CFO/summary/ENCFF498ZJU.w5 32 2 mean CHIP:ZEB2:K562 CHIP ChIP-TF:ZEB2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2430 0 ENCFF877MFN /home/drk/tillage/datasets/human/chip/encode/ENCSR322FGP/summary/ENCFF877MFN.w5 32 2 mean CHIP:H3K4me3:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K4me3/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2431 0 ENCFF624FIC /home/drk/tillage/datasets/human/chip/encode/ENCSR322JEO/summary/ENCFF624FIC.w5 32 2 mean CHIP:POLR2A:sigmoid colon female adult (53 years) CHIP ChIP-TF:POLR2A/sigmoid colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2432 0 ENCFF502TJG /home/drk/tillage/datasets/human/chip/encode/ENCSR322MEI/summary/ENCFF502TJG.w5 32 2 mean CHIP:H3K4me2:H1-hESC CHIP ChIP-Histone:H3K4me2/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2433 0 ENCFF763TYO /home/drk/tillage/datasets/human/chip/encode/ENCSR322TJD/summary/ENCFF763TYO.w5 32 2 mean CHIP:H3K27ac:aorta female adult (30 years) CHIP ChIP-Histone:H3K27ac/aorta female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2434 0 ENCFF838PEA /home/drk/tillage/datasets/human/chip/encode/ENCSR323YPH/summary/ENCFF838PEA.w5 32 2 mean CHIP:H3K36me3:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K36me3/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2435 0 ENCFF825UDG /home/drk/tillage/datasets/human/chip/encode/ENCSR324EPZ/summary/ENCFF825UDG.w5 32 2 mean CHIP:H3K36me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2436 0 ENCFF409AKL /home/drk/tillage/datasets/human/chip/encode/ENCSR324JDC/summary/ENCFF409AKL.w5 32 2 mean CHIP:H3K27ac:endocrine pancreas male adult (45 years) CHIP ChIP-Histone:H3K27ac/endocrine pancreas male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2437 0 ENCFF448FAS /home/drk/tillage/datasets/human/chip/encode/ENCSR324LTM/summary/ENCFF448FAS.w5 32 2 mean CHIP:eGFP-OSR2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-OSR2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2438 0 ENCFF954BOA /home/drk/tillage/datasets/human/chip/encode/ENCSR324RCI/summary/ENCFF954BOA.w5 32 2 mean CHIP:FOXA1:liver female child (4 years) CHIP ChIP-TF:FOXA1/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2439 0 ENCFF602QAM /home/drk/tillage/datasets/human/chip/encode/ENCSR324UNL/summary/ENCFF602QAM.w5 32 2 mean CHIP:H3K36me3:H9 CHIP ChIP-Histone:H3K36me3/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2440 0 ENCFF442QSP /home/drk/tillage/datasets/human/chip/encode/ENCSR324VZT/summary/ENCFF442QSP.w5 32 2 mean CHIP:H3K4me1:fibroblast of breast female adult (17 years) CHIP ChIP-Histone:H3K4me1/fibroblast of breast female adult (17 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2441 0 ENCFF452PDH /home/drk/tillage/datasets/human/chip/encode/ENCSR325DER/summary/ENCFF452PDH.w5 32 2 mean CHIP:NR3C1:K562 CHIP ChIP-TF:NR3C1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2442 0 ENCFF300YKS /home/drk/tillage/datasets/human/chip/encode/ENCSR325RLL/summary/ENCFF300YKS.w5 32 2 mean CHIP:POLR2B:K562 CHIP ChIP-TF:POLR2B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2443 0 ENCFF261LVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR325VOA/summary/ENCFF261LVJ.w5 32 2 mean CHIP:H3K4me1:aorta male adult (34 years) CHIP ChIP-Histone:H3K4me1/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2444 0 ENCFF517UOA /home/drk/tillage/datasets/human/chip/encode/ENCSR326NQF/summary/ENCFF517UOA.w5 32 2 mean CHIP:H3K23me2:H1-hESC CHIP ChIP-Histone:H3K23me2/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2445 0 ENCFF970HXE /home/drk/tillage/datasets/human/chip/encode/ENCSR327JOJ/summary/ENCFF970HXE.w5 32 2 mean CHIP:H2BK5ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H2BK5ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2446 0 ENCFF153VNW /home/drk/tillage/datasets/human/chip/encode/ENCSR327OGS/summary/ENCFF153VNW.w5 32 2 mean CHIP:H3K9ac:NCI-H929 CHIP ChIP-Histone:H3K9ac/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2447 0 ENCFF880MUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR327RFM/summary/ENCFF880MUQ.w5 32 2 mean CHIP:3xFLAG-PAF1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-PAF1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2448 0 ENCFF932HOT /home/drk/tillage/datasets/human/chip/encode/ENCSR327XTS/summary/ENCFF932HOT.w5 32 2 mean CHIP:H3K27ac:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K27ac/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2449 0 ENCFF517RDP /home/drk/tillage/datasets/human/chip/encode/ENCSR328AVV/summary/ENCFF517RDP.w5 32 2 mean CHIP:H3K9me2:GM23248 CHIP ChIP-Histone:H3K9me2/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2450 0 ENCFF802RZV /home/drk/tillage/datasets/human/chip/encode/ENCSR328CWP/summary/ENCFF802RZV.w5 32 2 mean CHIP:H3K9me3:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K9me3/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2451 0 ENCFF684CBW /home/drk/tillage/datasets/human/chip/encode/ENCSR328KRD/summary/ENCFF684CBW.w5 32 2 mean CHIP:H3K9ac:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K9ac/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2452 0 ENCFF761CJK /home/drk/tillage/datasets/human/chip/encode/ENCSR328SUD/summary/ENCFF761CJK.w5 32 2 mean CHIP:eGFP-ZNF335:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF335/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2453 0 ENCFF950JTD /home/drk/tillage/datasets/human/chip/encode/ENCSR329DTQ/summary/ENCFF950JTD.w5 32 2 mean CHIP:H3K27me3:skeletal muscle tissue CHIP ChIP-Histone:H3K27me3/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2454 0 ENCFF096AVB /home/drk/tillage/datasets/human/chip/encode/ENCSR329FXI/summary/ENCFF096AVB.w5 32 2 mean CHIP:H3K27ac:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K27ac/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2455 0 ENCFF541XSB /home/drk/tillage/datasets/human/chip/encode/ENCSR330ADN/summary/ENCFF541XSB.w5 32 2 mean CHIP:DDX20:MCF-7 CHIP ChIP-TF:DDX20/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2456 0 ENCFF213GXY /home/drk/tillage/datasets/human/chip/encode/ENCSR330EXS/summary/ENCFF213GXY.w5 32 2 mean CHIP:RBBP5:GM12878 CHIP ChIP-TF:RBBP5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2457 0 ENCFF439FMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR330NKU/summary/ENCFF439FMZ.w5 32 2 mean CHIP:H3K4me1:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K4me1/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2458 0 ENCFF159SQB /home/drk/tillage/datasets/human/chip/encode/ENCSR330OEO/summary/ENCFF159SQB.w5 32 2 mean CHIP:HDAC2:GM12878 CHIP ChIP-TF:HDAC2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2459 0 ENCFF306DWK /home/drk/tillage/datasets/human/chip/encode/ENCSR331BDJ/summary/ENCFF306DWK.w5 32 2 mean CHIP:NKRF:K562 CHIP ChIP-TF:NKRF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2460 0 ENCFF285VAE /home/drk/tillage/datasets/human/chip/encode/ENCSR331CRR/summary/ENCFF285VAE.w5 32 2 mean CHIP:H3K36me3:kidney male adult (50 years) CHIP ChIP-Histone:H3K36me3/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2461 0 ENCFF777KJU /home/drk/tillage/datasets/human/chip/encode/ENCSR331GDC/summary/ENCFF777KJU.w5 32 2 mean CHIP:ZBTB11:K562 CHIP ChIP-TF:ZBTB11/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2462 0 ENCFF381QHK /home/drk/tillage/datasets/human/chip/encode/ENCSR331HPA/summary/ENCFF381QHK.w5 32 2 mean CHIP:GABPA:GM12878 CHIP ChIP-TF:GABPA/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2463 0 ENCFF618PGT /home/drk/tillage/datasets/human/chip/encode/ENCSR331ORD/summary/ENCFF618PGT.w5 32 2 mean CHIP:3xFLAG-CREB1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-CREB1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2464 0 ENCFF167IXI /home/drk/tillage/datasets/human/chip/encode/ENCSR331RGM/summary/ENCFF167IXI.w5 32 2 mean CHIP:H2AFZ:OCI-LY7 CHIP ChIP-TF:H2AFZ/OCI-LY7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2465 0 ENCFF085KGM /home/drk/tillage/datasets/human/chip/encode/ENCSR332EYT/summary/ENCFF085KGM.w5 32 2 mean CHIP:STAT1:GM12878 CHIP ChIP-TF:STAT1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2466 0 ENCFF392BIV /home/drk/tillage/datasets/human/chip/encode/ENCSR333LVY/summary/ENCFF392BIV.w5 32 2 mean CHIP:H2AK5ac:H9 CHIP ChIP-TF:H2AK5ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2467 0 ENCFF144ZRX /home/drk/tillage/datasets/human/chip/encode/ENCSR333OPW/summary/ENCFF144ZRX.w5 32 2 mean CHIP:H3K4me3:HCT116 CHIP ChIP-Histone:H3K4me3/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2468 0 ENCFF080LID /home/drk/tillage/datasets/human/chip/encode/ENCSR333VFQ/summary/ENCFF080LID.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2469 0 ENCFF885BSP /home/drk/tillage/datasets/human/chip/encode/ENCSR333ZAR/summary/ENCFF885BSP.w5 32 2 mean CHIP:H3K4me1:adrenal gland female adult (30 years) CHIP ChIP-Histone:H3K4me1/adrenal gland female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2470 0 ENCFF806RPA /home/drk/tillage/datasets/human/chip/encode/ENCSR334HSW/summary/ENCFF806RPA.w5 32 2 mean CHIP:ZNF318:K562 CHIP ChIP-TF:ZNF318/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2471 0 ENCFF972FHU /home/drk/tillage/datasets/human/chip/encode/ENCSR334KIQ/summary/ENCFF972FHU.w5 32 2 mean CHIP:SP1:HepG2 CHIP ChIP-TF:SP1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2472 0 ENCFF041TOQ /home/drk/tillage/datasets/human/chip/encode/ENCSR335ELI/summary/ENCFF041TOQ.w5 32 2 mean CHIP:H3K9ac:HUES48 CHIP ChIP-Histone:H3K9ac/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2473 0 ENCFF263SSG /home/drk/tillage/datasets/human/chip/encode/ENCSR335LTZ/summary/ENCFF263SSG.w5 32 2 mean CHIP:H3K9ac:Parathyroid adenoma male adult (65 years) CHIP ChIP-Histone:H3K9ac/Parathyroid adenoma male adult (65 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2474 0 ENCFF759CXX /home/drk/tillage/datasets/human/chip/encode/ENCSR336DXE/summary/ENCFF759CXX.w5 32 2 mean CHIP:SKIL:K562 CHIP ChIP-TF:SKIL/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2475 0 ENCFF087RIC /home/drk/tillage/datasets/human/chip/encode/ENCSR336PTS/summary/ENCFF087RIC.w5 32 2 mean CHIP:CTCF:Parathyroid adenoma male adult (65 years) CHIP ChIP-TF:CTCF/Parathyroid adenoma male adult (65 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2476 0 ENCFF850MYM /home/drk/tillage/datasets/human/chip/encode/ENCSR336RLL/summary/ENCFF850MYM.w5 32 2 mean CHIP:H3K27me3:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K27me3/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2477 0 ENCFF640ALB /home/drk/tillage/datasets/human/chip/encode/ENCSR336YRS/summary/ENCFF640ALB.w5 32 2 mean CHIP:POLR2A:heart left ventricle female adult (53 years) CHIP ChIP-TF:POLR2A/heart left ventricle female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2478 0 ENCFF569RYG /home/drk/tillage/datasets/human/chip/encode/ENCSR336ZSZ/summary/ENCFF569RYG.w5 32 2 mean CHIP:H3K4me1:peripheral blood mononuclear cell male adult (27 years) CHIP ChIP-Histone:H3K4me1/peripheral blood mononuclear cell male adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2479 0 ENCFF361GWV /home/drk/tillage/datasets/human/chip/encode/ENCSR337NQP/summary/ENCFF361GWV.w5 32 2 mean CHIP:ESRRA:MCF-7 CHIP ChIP-TF:ESRRA/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2480 0 ENCFF576URK /home/drk/tillage/datasets/human/chip/encode/ENCSR337NWW/summary/ENCFF576URK.w5 32 2 mean CHIP:HDAC2:HepG2 CHIP ChIP-TF:HDAC2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2481 0 ENCFF548JBQ /home/drk/tillage/datasets/human/chip/encode/ENCSR338DGO/summary/ENCFF548JBQ.w5 32 2 mean CHIP:eGFP-SCRT2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SCRT2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2482 0 ENCFF363ACC /home/drk/tillage/datasets/human/chip/encode/ENCSR338MMB/summary/ENCFF363ACC.w5 32 2 mean CHIP:NR2F2:liver male adult (32 years) CHIP ChIP-TF:NR2F2/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2483 0 ENCFF748KBY /home/drk/tillage/datasets/human/chip/encode/ENCSR338SEM/summary/ENCFF748KBY.w5 32 2 mean CHIP:eGFP-ZNF248:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF248/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2484 0 ENCFF278YOZ /home/drk/tillage/datasets/human/chip/encode/ENCSR339FOO/summary/ENCFF278YOZ.w5 32 2 mean CHIP:H3K79me2:NCI-H929 CHIP ChIP-Histone:H3K79me2/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2485 0 ENCFF764IIZ /home/drk/tillage/datasets/human/chip/encode/ENCSR339JTP/summary/ENCFF764IIZ.w5 32 2 mean CHIP:RBM39:HepG2 CHIP ChIP-TF:RBM39/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2486 0 ENCFF427QAM /home/drk/tillage/datasets/human/chip/encode/ENCSR339PHE/summary/ENCFF427QAM.w5 32 2 mean CHIP:H3K4me1:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K4me1/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2487 0 ENCFF710TJH /home/drk/tillage/datasets/human/chip/encode/ENCSR339PLH/summary/ENCFF710TJH.w5 32 2 mean CHIP:H3K9ac:stomach smooth muscle male adult (59 years) CHIP ChIP-Histone:H3K9ac/stomach smooth muscle male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2488 0 ENCFF787UOA /home/drk/tillage/datasets/human/chip/encode/ENCSR339ZMJ/summary/ENCFF787UOA.w5 32 2 mean CHIP:H3K9me3:PC-3 CHIP ChIP-Histone:H3K9me3/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2489 0 ENCFF877RQP /home/drk/tillage/datasets/human/chip/encode/ENCSR340BXT/summary/ENCFF877RQP.w5 32 2 mean CHIP:3xFLAG-KAT7:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KAT7/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2490 0 ENCFF434ALZ /home/drk/tillage/datasets/human/chip/encode/ENCSR340DBD/summary/ENCFF434ALZ.w5 32 2 mean CHIP:H3K36me3:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K36me3/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2491 0 ENCFF665AYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR340OPI/summary/ENCFF665AYQ.w5 32 2 mean CHIP:H3K27me3:small intestine male child (3 years) CHIP ChIP-Histone:H3K27me3/small intestine male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2492 0 ENCFF969NZS /home/drk/tillage/datasets/human/chip/encode/ENCSR340SGE/summary/ENCFF969NZS.w5 32 2 mean CHIP:H3K4me1:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K4me1/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2493 0 ENCFF913SUG /home/drk/tillage/datasets/human/chip/encode/ENCSR340WQU/summary/ENCFF913SUG.w5 32 2 mean CHIP:H3K4me3:HeLa-S3 CHIP ChIP-Histone:H3K4me3/HeLa-S3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2494 0 ENCFF625BUD /home/drk/tillage/datasets/human/chip/encode/ENCSR341VYI/summary/ENCFF625BUD.w5 32 2 mean CHIP:EZH2phosphoT487:hepatocyte originated from H9 CHIP ChIP-TF:EZH2phosphoT487/hepatocyte originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2495 0 ENCFF856LYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR342THD/summary/ENCFF856LYZ.w5 32 2 mean CHIP:BCLAF1:GM12878 CHIP ChIP-TF:BCLAF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2496 0 ENCFF750BPV /home/drk/tillage/datasets/human/chip/encode/ENCSR343ELW/summary/ENCFF750BPV.w5 32 2 mean CHIP:LEF1:K562 CHIP ChIP-TF:LEF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2497 0 ENCFF791ETT /home/drk/tillage/datasets/human/chip/encode/ENCSR343IFJ/summary/ENCFF791ETT.w5 32 2 mean CHIP:CC2D1A:K562 CHIP ChIP-TF:CC2D1A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2498 0 ENCFF397IIG /home/drk/tillage/datasets/human/chip/encode/ENCSR343ZOV/summary/ENCFF397IIG.w5 32 2 mean CHIP:H3K4me3:coronary artery female adult (53 years) CHIP ChIP-Histone:H3K4me3/coronary artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2499 0 ENCFF807NBH /home/drk/tillage/datasets/human/chip/encode/ENCSR344SBD/summary/ENCFF807NBH.w5 32 2 mean CHIP:eGFP-ZNF596:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF596/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2500 0 ENCFF958VCA /home/drk/tillage/datasets/human/chip/encode/ENCSR344TLI/summary/ENCFF958VCA.w5 32 2 mean CHIP:H3K4me3:right lobe of liver female adult (53 years) CHIP ChIP-Histone:H3K4me3/right lobe of liver female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2501 0 ENCFF241CSS /home/drk/tillage/datasets/human/chip/encode/ENCSR344VNY/summary/ENCFF241CSS.w5 32 2 mean CHIP:H3K27me3:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K27me3/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2502 0 ENCFF972TYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR344WLV/summary/ENCFF972TYZ.w5 32 2 mean CHIP:H3K4me1:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me1/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2503 0 ENCFF420MNP /home/drk/tillage/datasets/human/chip/encode/ENCSR344YYP/summary/ENCFF420MNP.w5 32 2 mean CHIP:H3K9ac:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K9ac/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2504 0 ENCFF999IEY /home/drk/tillage/datasets/human/chip/encode/ENCSR345PSR/summary/ENCFF999IEY.w5 32 2 mean CHIP:H3K36me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K36me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2505 0 ENCFF385PMK /home/drk/tillage/datasets/human/chip/encode/ENCSR345QKG/summary/ENCFF385PMK.w5 32 2 mean CHIP:H3K4me3:placental basal plate male embryo (38 weeks) CHIP ChIP-Histone:H3K4me3/placental basal plate male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2506 0 ENCFF032DMC /home/drk/tillage/datasets/human/chip/encode/ENCSR345YWJ/summary/ENCFF032DMC.w5 32 2 mean CHIP:ZBTB33:liver female child (4 years) CHIP ChIP-TF:ZBTB33/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2507 0 ENCFF381CZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR346DKN/summary/ENCFF381CZQ.w5 32 2 mean CHIP:EP300:breast epithelium male adult (37 years) CHIP ChIP-TF:EP300/breast epithelium male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2508 0 ENCFF061VBQ /home/drk/tillage/datasets/human/chip/encode/ENCSR346DNL/summary/ENCFF061VBQ.w5 32 2 mean CHIP:H3K4me1:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me1/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2509 0 ENCFF788KIN /home/drk/tillage/datasets/human/chip/encode/ENCSR346KKE/summary/ENCFF788KIN.w5 32 2 mean CHIP:H3K4me3:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K4me3/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2510 0 ENCFF268JQO /home/drk/tillage/datasets/human/chip/encode/ENCSR347HBG/summary/ENCFF268JQO.w5 32 2 mean CHIP:H3K27ac:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K27ac/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2511 0 ENCFF401YZO /home/drk/tillage/datasets/human/chip/encode/ENCSR347NOB/summary/ENCFF401YZO.w5 32 2 mean CHIP:CEBPZ:GM12878 CHIP ChIP-TF:CEBPZ/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2512 0 ENCFF531VTG /home/drk/tillage/datasets/human/chip/encode/ENCSR348JOJ/summary/ENCFF531VTG.w5 32 2 mean CHIP:MTA1:MCF-7 CHIP ChIP-TF:MTA1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2513 0 ENCFF061EEU /home/drk/tillage/datasets/human/chip/encode/ENCSR348ONY/summary/ENCFF061EEU.w5 32 2 mean CHIP:eGFP-ZFP41:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFP41/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2514 0 ENCFF935KCD /home/drk/tillage/datasets/human/chip/encode/ENCSR348TQM/summary/ENCFF935KCD.w5 32 2 mean CHIP:H3K4me1:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K4me1/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2515 0 ENCFF872UPB /home/drk/tillage/datasets/human/chip/encode/ENCSR348UWU/summary/ENCFF872UPB.w5 32 2 mean CHIP:H3K9ac:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K9ac/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2516 0 ENCFF802JHI /home/drk/tillage/datasets/human/chip/encode/ENCSR349III/summary/ENCFF802JHI.w5 32 2 mean CHIP:H3K9me3:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K9me3/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2517 0 ENCFF086KNG /home/drk/tillage/datasets/human/chip/encode/ENCSR349TZO/summary/ENCFF086KNG.w5 32 2 mean CHIP:NCOA2:K562 CHIP ChIP-TF:NCOA2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2518 0 ENCFF089RTD /home/drk/tillage/datasets/human/chip/encode/ENCSR350JZR/summary/ENCFF089RTD.w5 32 2 mean CHIP:H3K4me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2519 0 ENCFF882NIX /home/drk/tillage/datasets/human/chip/encode/ENCSR350ORK/summary/ENCFF882NIX.w5 32 2 mean CHIP:GABPA:liver female child (4 years) CHIP ChIP-TF:GABPA/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2520 0 ENCFF294WYN /home/drk/tillage/datasets/human/chip/encode/ENCSR350PUV/summary/ENCFF294WYN.w5 32 2 mean CHIP:POLR2AphosphoS5:spleen female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/spleen female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2521 0 ENCFF398UVR /home/drk/tillage/datasets/human/chip/encode/ENCSR350RYG/summary/ENCFF398UVR.w5 32 2 mean CHIP:H3K27me3:DOHH2 CHIP ChIP-Histone:H3K27me3/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2522 0 ENCFF210EVB /home/drk/tillage/datasets/human/chip/encode/ENCSR350XWY/summary/ENCFF210EVB.w5 32 2 mean CHIP:C11orf30:K562 CHIP ChIP-TF:C11orf30/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2523 0 ENCFF034GOB /home/drk/tillage/datasets/human/chip/encode/ENCSR350YQC/summary/ENCFF034GOB.w5 32 2 mean CHIP:H4K8ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H4K8ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2524 0 ENCFF368YHR /home/drk/tillage/datasets/human/chip/encode/ENCSR351DLF/summary/ENCFF368YHR.w5 32 2 mean CHIP:H3K9me3:liver male adult (31 year) CHIP ChIP-Histone:H3K9me3/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2525 0 ENCFF708EYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR351NON/summary/ENCFF708EYJ.w5 32 2 mean CHIP:eGFP-ZNF629:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF629/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2526 0 ENCFF784RPP /home/drk/tillage/datasets/human/chip/encode/ENCSR351SZH/summary/ENCFF784RPP.w5 32 2 mean CHIP:H3K4me1:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2527 0 ENCFF373YVF /home/drk/tillage/datasets/human/chip/encode/ENCSR352BJL/summary/ENCFF373YVF.w5 32 2 mean CHIP:ZNF318:K562 CHIP ChIP-TF:ZNF318/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2528 0 ENCFF491SLY /home/drk/tillage/datasets/human/chip/encode/ENCSR352QSB/summary/ENCFF491SLY.w5 32 2 mean CHIP:RXRA:liver female child (4 years) CHIP ChIP-TF:RXRA/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2529 0 ENCFF126SJO /home/drk/tillage/datasets/human/chip/encode/ENCSR352UID/summary/ENCFF126SJO.w5 32 2 mean CHIP:H3K27me3:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K27me3/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2530 0 ENCFF754CTN /home/drk/tillage/datasets/human/chip/encode/ENCSR353DFU/summary/ENCFF754CTN.w5 32 2 mean CHIP:CTCF:esophagus muscularis mucosa female adult (51 year) CHIP ChIP-TF:CTCF/esophagus muscularis mucosa female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2531 0 ENCFF623ZTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR353HEP/summary/ENCFF623ZTZ.w5 32 2 mean CHIP:TARDBP:K562 CHIP ChIP-TF:TARDBP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2532 0 ENCFF439KUX /home/drk/tillage/datasets/human/chip/encode/ENCSR353LBX/summary/ENCFF439KUX.w5 32 2 mean CHIP:H3K9me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K9me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2533 0 ENCFF330FVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR354IST/summary/ENCFF330FVQ.w5 32 2 mean CHIP:H3K27me3:stomach female embryo (96 days) CHIP ChIP-Histone:H3K27me3/stomach female embryo (96 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2534 0 ENCFF611MWG /home/drk/tillage/datasets/human/chip/encode/ENCSR354UVU/summary/ENCFF611MWG.w5 32 2 mean CHIP:H3K4ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K4ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2535 0 ENCFF729NDF /home/drk/tillage/datasets/human/chip/encode/ENCSR354XWM/summary/ENCFF729NDF.w5 32 2 mean CHIP:H3K4me3:neural stem progenitor cell originated from H9 CHIP ChIP-Histone:H3K4me3/neural stem progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2536 0 ENCFF764FFY /home/drk/tillage/datasets/human/chip/encode/ENCSR355PUX/summary/ENCFF764FFY.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2537 0 ENCFF227KJH /home/drk/tillage/datasets/human/chip/encode/ENCSR355UYP/summary/ENCFF227KJH.w5 32 2 mean CHIP:H3K27ac:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K27ac/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2538 0 ENCFF498NTH /home/drk/tillage/datasets/human/chip/encode/ENCSR355ZYK/summary/ENCFF498NTH.w5 32 2 mean CHIP:H2BK120ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H2BK120ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2539 0 ENCFF551TJE /home/drk/tillage/datasets/human/chip/encode/ENCSR356ANC/summary/ENCFF551TJE.w5 32 2 mean CHIP:H3K4me1:lung female adult (30 years) CHIP ChIP-Histone:H3K4me1/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2540 0 ENCFF655TBA /home/drk/tillage/datasets/human/chip/encode/ENCSR356ECR/summary/ENCFF655TBA.w5 32 2 mean CHIP:RBM22:HepG2 CHIP ChIP-TF:RBM22/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2541 0 ENCFF846WHW /home/drk/tillage/datasets/human/chip/encode/ENCSR356JTB/summary/ENCFF846WHW.w5 32 2 mean CHIP:H3K9me3:trophoblast female embryo (40 weeks) CHIP ChIP-Histone:H3K9me3/trophoblast female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2542 0 ENCFF240FDY /home/drk/tillage/datasets/human/chip/encode/ENCSR357HAN/summary/ENCFF240FDY.w5 32 2 mean CHIP:H3K79me1:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K79me1/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2543 0 ENCFF004DAD /home/drk/tillage/datasets/human/chip/encode/ENCSR357QJR/summary/ENCFF004DAD.w5 32 2 mean CHIP:eGFP-ZSCAN5A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN5A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2544 0 ENCFF759FJI /home/drk/tillage/datasets/human/chip/encode/ENCSR357ROS/summary/ENCFF759FJI.w5 32 2 mean CHIP:H3K27me3:stomach female adult (53 years) CHIP ChIP-Histone:H3K27me3/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2545 0 ENCFF399SZC /home/drk/tillage/datasets/human/chip/encode/ENCSR358KID/summary/ENCFF399SZC.w5 32 2 mean CHIP:H3K27me3:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K27me3/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2546 0 ENCFF650XMH /home/drk/tillage/datasets/human/chip/encode/ENCSR358RVW/summary/ENCFF650XMH.w5 32 2 mean CHIP:H3K4me3:heart male embryo (91 day) CHIP ChIP-Histone:H3K4me3/heart male embryo (91 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2547 0 ENCFF720MFS /home/drk/tillage/datasets/human/chip/encode/ENCSR359JHU/summary/ENCFF720MFS.w5 32 2 mean CHIP:H3K9me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K9me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2548 0 ENCFF633UOG /home/drk/tillage/datasets/human/chip/encode/ENCSR359LOD/summary/ENCFF633UOG.w5 32 2 mean CHIP:CTCF:PC-3 CHIP ChIP-TF:CTCF/PC-3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2549 0 ENCFF457UYN /home/drk/tillage/datasets/human/chip/encode/ENCSR359NFW/summary/ENCFF457UYN.w5 32 2 mean CHIP:eGFP-USF2:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-USF2/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2550 0 ENCFF285GEA /home/drk/tillage/datasets/human/chip/encode/ENCSR360BLQ/summary/ENCFF285GEA.w5 32 2 mean CHIP:EP300:esophagus muscularis mucosa male adult (37 years) CHIP ChIP-TF:EP300/esophagus muscularis mucosa male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2551 0 ENCFF818OZI /home/drk/tillage/datasets/human/chip/encode/ENCSR360HRA/summary/ENCFF818OZI.w5 32 2 mean CHIP:KDM1A:K562 CHIP ChIP-TF:KDM1A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2552 0 ENCFF204LFY /home/drk/tillage/datasets/human/chip/encode/ENCSR360JOC/summary/ENCFF204LFY.w5 32 2 mean CHIP:CHD1:MCF-7 CHIP ChIP-TF:CHD1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2553 0 ENCFF039PUD /home/drk/tillage/datasets/human/chip/encode/ENCSR361FWQ/summary/ENCFF039PUD.w5 32 2 mean CHIP:H3K4me3:MM.1S CHIP ChIP-Histone:H3K4me3/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2554 0 ENCFF868JIG /home/drk/tillage/datasets/human/chip/encode/ENCSR361LIU/summary/ENCFF868JIG.w5 32 2 mean CHIP:H3K23ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K23ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2555 0 ENCFF701NNS /home/drk/tillage/datasets/human/chip/encode/ENCSR362CPB/summary/ENCFF701NNS.w5 32 2 mean CHIP:HDAC1:HepG2 CHIP ChIP-TF:HDAC1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2556 0 ENCFF716TVA /home/drk/tillage/datasets/human/chip/encode/ENCSR362NWP/summary/ENCFF716TVA.w5 32 2 mean CHIP:ZNF24:HepG2 CHIP ChIP-TF:ZNF24/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2557 0 ENCFF729ZRR /home/drk/tillage/datasets/human/chip/encode/ENCSR363CJF/summary/ENCFF729ZRR.w5 32 2 mean CHIP:H3K36me3:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K36me3/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2558 0 ENCFF969OZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR363SSI/summary/ENCFF969OZJ.w5 32 2 mean CHIP:H3K9me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K9me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2559 0 ENCFF325ADD /home/drk/tillage/datasets/human/chip/encode/ENCSR363XBR/summary/ENCFF325ADD.w5 32 2 mean CHIP:eGFP-ZNF488:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF488/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2560 0 ENCFF873OYG /home/drk/tillage/datasets/human/chip/encode/ENCSR364BKW/summary/ENCFF873OYG.w5 32 2 mean CHIP:H2BK12ac:H1-hESC CHIP ChIP-TF:H2BK12ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2561 0 ENCFF374LYX /home/drk/tillage/datasets/human/chip/encode/ENCSR364OZJ/summary/ENCFF374LYX.w5 32 2 mean CHIP:H3K27me3:chorion male embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/chorion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2562 0 ENCFF906LPL /home/drk/tillage/datasets/human/chip/encode/ENCSR364SNE/summary/ENCFF906LPL.w5 32 2 mean CHIP:POU5F1:K562 CHIP ChIP-TF:POU5F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2563 0 ENCFF159NNA /home/drk/tillage/datasets/human/chip/encode/ENCSR365DQH/summary/ENCFF159NNA.w5 32 2 mean CHIP:eGFP-ZNF211:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF211/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2564 0 ENCFF510KPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR365DWX/summary/ENCFF510KPQ.w5 32 2 mean CHIP:H3K9ac:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K9ac/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2565 0 ENCFF686VCT /home/drk/tillage/datasets/human/chip/encode/ENCSR365GRX/summary/ENCFF686VCT.w5 32 2 mean CHIP:eGFP-ZFP37:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFP37/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2566 0 ENCFF537OFZ /home/drk/tillage/datasets/human/chip/encode/ENCSR366AOJ/summary/ENCFF537OFZ.w5 32 2 mean CHIP:H3K36me3:kidney female embryo (120 days) CHIP ChIP-Histone:H3K36me3/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2567 0 ENCFF421PQS /home/drk/tillage/datasets/human/chip/encode/ENCSR366QMB/summary/ENCFF421PQS.w5 32 2 mean CHIP:H2AFZ:SK-N-SH CHIP ChIP-TF:H2AFZ/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2568 0 ENCFF745BAW /home/drk/tillage/datasets/human/chip/encode/ENCSR367HVD/summary/ENCFF745BAW.w5 32 2 mean CHIP:H3K4me1:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me1/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2569 0 ENCFF782VON /home/drk/tillage/datasets/human/chip/encode/ENCSR367JIO/summary/ENCFF782VON.w5 32 2 mean CHIP:H4K8ac:H9 CHIP ChIP-TF:H4K8ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2570 0 ENCFF388DPI /home/drk/tillage/datasets/human/chip/encode/ENCSR367UUC/summary/ENCFF388DPI.w5 32 2 mean CHIP:POLR2A:gastroesophageal sphincter female adult (51 year) CHIP ChIP-TF:POLR2A/gastroesophageal sphincter female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2571 0 ENCFF691WBL /home/drk/tillage/datasets/human/chip/encode/ENCSR367VRA/summary/ENCFF691WBL.w5 32 2 mean CHIP:H3K4me3:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K4me3/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2572 0 ENCFF406PPG /home/drk/tillage/datasets/human/chip/encode/ENCSR367WYJ/summary/ENCFF406PPG.w5 32 2 mean CHIP:H3K27ac:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K27ac/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2573 0 ENCFF340WNS /home/drk/tillage/datasets/human/chip/encode/ENCSR368ORV/summary/ENCFF340WNS.w5 32 2 mean CHIP:H3K4me1:right atrium auricular region female adult (53 years) CHIP ChIP-Histone:H3K4me1/right atrium auricular region female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2574 0 ENCFF102TLL /home/drk/tillage/datasets/human/chip/encode/ENCSR368YAQ/summary/ENCFF102TLL.w5 32 2 mean CHIP:H3K4me1:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K4me1/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2575 0 ENCFF714BHC /home/drk/tillage/datasets/human/chip/encode/ENCSR368YPC/summary/ENCFF714BHC.w5 32 2 mean CHIP:H3K4me3:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K4me3/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2576 0 ENCFF720VQM /home/drk/tillage/datasets/human/chip/encode/ENCSR368ZJL/summary/ENCFF720VQM.w5 32 2 mean CHIP:H3K27me3:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2577 0 ENCFF170YDM /home/drk/tillage/datasets/human/chip/encode/ENCSR369NGL/summary/ENCFF170YDM.w5 32 2 mean CHIP:POLR2AphosphoS5:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:POLR2AphosphoS5/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2578 0 ENCFF375LJC /home/drk/tillage/datasets/human/chip/encode/ENCSR369YUK/summary/ENCFF375LJC.w5 32 2 mean CHIP:3xFLAG-FOXP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-FOXP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2579 0 ENCFF512ODL /home/drk/tillage/datasets/human/chip/encode/ENCSR370KYM/summary/ENCFF512ODL.w5 32 2 mean CHIP:H3K27me3:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K27me3/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2580 0 ENCFF616UEL /home/drk/tillage/datasets/human/chip/encode/ENCSR370NFS/summary/ENCFF616UEL.w5 32 2 mean CHIP:ZNF280A:K562 CHIP ChIP-TF:ZNF280A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2581 0 ENCFF877NXH /home/drk/tillage/datasets/human/chip/encode/ENCSR370RJP/summary/ENCFF877NXH.w5 32 2 mean CHIP:H3K36me3:endocrine pancreas male adult (46 years) CHIP ChIP-Histone:H3K36me3/endocrine pancreas male adult (46 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2582 0 ENCFF751NMA /home/drk/tillage/datasets/human/chip/encode/ENCSR371FHD/summary/ENCFF751NMA.w5 32 2 mean CHIP:H4K91ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H4K91ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2583 0 ENCFF104ZNJ /home/drk/tillage/datasets/human/chip/encode/ENCSR371LLY/summary/ENCFF104ZNJ.w5 32 2 mean CHIP:eGFP-ZNF37A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF37A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2584 0 ENCFF674GHR /home/drk/tillage/datasets/human/chip/encode/ENCSR372GIN/summary/ENCFF674GHR.w5 32 2 mean CHIP:CBX5:GM12878 CHIP ChIP-TF:CBX5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2585 0 ENCFF366KTI /home/drk/tillage/datasets/human/chip/encode/ENCSR372JXR/summary/ENCFF366KTI.w5 32 2 mean CHIP:3xFLAG-ZNF511:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF511/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2586 0 ENCFF156XNH /home/drk/tillage/datasets/human/chip/encode/ENCSR372MTE/summary/ENCFF156XNH.w5 32 2 mean CHIP:H3K4me1:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me1/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2587 0 ENCFF423AQA /home/drk/tillage/datasets/human/chip/encode/ENCSR372OTD/summary/ENCFF423AQA.w5 32 2 mean CHIP:H3K36me3:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K36me3/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2588 0 ENCFF356ZPT /home/drk/tillage/datasets/human/chip/encode/ENCSR373WCB/summary/ENCFF356ZPT.w5 32 2 mean CHIP:H3K36me3:neutrophil CHIP ChIP-Histone:H3K36me3/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2589 0 ENCFF389BJB /home/drk/tillage/datasets/human/chip/encode/ENCSR374OSU/summary/ENCFF389BJB.w5 32 2 mean CHIP:H3K27me3:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K27me3/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2590 0 ENCFF357DQF /home/drk/tillage/datasets/human/chip/encode/ENCSR374RZR/summary/ENCFF357DQF.w5 32 2 mean CHIP:H3K9me2:MCF-7 CHIP ChIP-Histone:H3K9me2/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2591 0 ENCFF429LOR /home/drk/tillage/datasets/human/chip/encode/ENCSR375DWY/summary/ENCFF429LOR.w5 32 2 mean CHIP:H3K9ac:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K9ac/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2592 0 ENCFF643URD /home/drk/tillage/datasets/human/chip/encode/ENCSR375IXS/summary/ENCFF643URD.w5 32 2 mean CHIP:H3K36me3:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K36me3/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2593 0 ENCFF018VYW /home/drk/tillage/datasets/human/chip/encode/ENCSR375VXU/summary/ENCFF018VYW.w5 32 2 mean CHIP:CTCF:Peyer's patch female adult (53 years) CHIP ChIP-TF:CTCF/Peyer's patch female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2594 0 ENCFF169HZN /home/drk/tillage/datasets/human/chip/encode/ENCSR376FMN/summary/ENCFF169HZN.w5 32 2 mean CHIP:EHMT2:HepG2 CHIP ChIP-TF:EHMT2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2595 0 ENCFF276VSX /home/drk/tillage/datasets/human/chip/encode/ENCSR376JOC/summary/ENCFF276VSX.w5 32 2 mean CHIP:H3K9me3:testis male adult (37 years) CHIP ChIP-Histone:H3K9me3/testis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2596 0 ENCFF887HOR /home/drk/tillage/datasets/human/chip/encode/ENCSR376WCJ/summary/ENCFF887HOR.w5 32 2 mean CHIP:IRF2:K562 CHIP ChIP-TF:IRF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2597 0 ENCFF487RXG /home/drk/tillage/datasets/human/chip/encode/ENCSR377BLZ/summary/ENCFF487RXG.w5 32 2 mean CHIP:GTF2F1:K562 CHIP ChIP-TF:GTF2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2598 0 ENCFF728ENE /home/drk/tillage/datasets/human/chip/encode/ENCSR377FXG/summary/ENCFF728ENE.w5 32 2 mean CHIP:H3K36me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2599 0 ENCFF094USN /home/drk/tillage/datasets/human/chip/encode/ENCSR377KDN/summary/ENCFF094USN.w5 32 2 mean CHIP:H3K4me3:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K4me3/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2600 0 ENCFF311OXM /home/drk/tillage/datasets/human/chip/encode/ENCSR377MFD/summary/ENCFF311OXM.w5 32 2 mean CHIP:H3K9me3:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K9me3/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2601 0 ENCFF885NDK /home/drk/tillage/datasets/human/chip/encode/ENCSR377MRR/summary/ENCFF885NDK.w5 32 2 mean CHIP:H3K27me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2602 0 ENCFF666PCU /home/drk/tillage/datasets/human/chip/encode/ENCSR377QMP/summary/ENCFF666PCU.w5 32 2 mean CHIP:H3F3A:GM23248 CHIP ChIP-Histone:H3F3A/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2603 0 ENCFF449COI /home/drk/tillage/datasets/human/chip/encode/ENCSR378HAM/summary/ENCFF449COI.w5 32 2 mean CHIP:H3K9me3:kidney male adult (50 years) CHIP ChIP-Histone:H3K9me3/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2604 0 ENCFF623CXL /home/drk/tillage/datasets/human/chip/encode/ENCSR379WXM/summary/ENCFF623CXL.w5 32 2 mean CHIP:H3K27ac:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K27ac/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2605 0 ENCFF593NCO /home/drk/tillage/datasets/human/chip/encode/ENCSR380KNE/summary/ENCFF593NCO.w5 32 2 mean CHIP:H3K36me3:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K36me3/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2606 0 ENCFF518CHL /home/drk/tillage/datasets/human/chip/encode/ENCSR380KOO/summary/ENCFF518CHL.w5 32 2 mean CHIP:H3K27ac:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K27ac/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2607 0 ENCFF852QSB /home/drk/tillage/datasets/human/chip/encode/ENCSR381EFC/summary/ENCFF852QSB.w5 32 2 mean CHIP:H3K27me3:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K27me3/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2608 0 ENCFF557CRC /home/drk/tillage/datasets/human/chip/encode/ENCSR381VYR/summary/ENCFF557CRC.w5 32 2 mean CHIP:eGFP-ZFP69B:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFP69B/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2609 0 ENCFF378ZCH /home/drk/tillage/datasets/human/chip/encode/ENCSR381XDC/summary/ENCFF378ZCH.w5 32 2 mean CHIP:H3K27me3:thymus female embryo (110 days) CHIP ChIP-Histone:H3K27me3/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2610 0 ENCFF126WGU /home/drk/tillage/datasets/human/chip/encode/ENCSR382AIB/summary/ENCFF126WGU.w5 32 2 mean CHIP:eGFP-DDX20:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-DDX20/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2611 0 ENCFF435QQJ /home/drk/tillage/datasets/human/chip/encode/ENCSR382GSF/summary/ENCFF435QQJ.w5 32 2 mean CHIP:eGFP-INSM2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-INSM2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2612 0 ENCFF057SLO /home/drk/tillage/datasets/human/chip/encode/ENCSR382MOM/summary/ENCFF057SLO.w5 32 2 mean CHIP:YY1:liver male adult (32 years) CHIP ChIP-TF:YY1/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2613 0 ENCFF967OKU /home/drk/tillage/datasets/human/chip/encode/ENCSR382PVA/summary/ENCFF967OKU.w5 32 2 mean CHIP:GTF2F1:HepG2 CHIP ChIP-TF:GTF2F1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2614 0 ENCFF771NBX /home/drk/tillage/datasets/human/chip/encode/ENCSR382VAU/summary/ENCFF771NBX.w5 32 2 mean CHIP:H3K4me1:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2615 0 ENCFF398XNT /home/drk/tillage/datasets/human/chip/encode/ENCSR382WLL/summary/ENCFF398XNT.w5 32 2 mean CHIP:ELK1:MCF-7 CHIP ChIP-TF:ELK1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2616 0 ENCFF705KGP /home/drk/tillage/datasets/human/chip/encode/ENCSR382XLA/summary/ENCFF705KGP.w5 32 2 mean CHIP:ZFP36:HepG2 CHIP ChIP-TF:ZFP36/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2617 0 ENCFF279WOL /home/drk/tillage/datasets/human/chip/encode/ENCSR383AEO/summary/ENCFF279WOL.w5 32 2 mean CHIP:H3K4me3:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K4me3/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2618 0 ENCFF577VAD /home/drk/tillage/datasets/human/chip/encode/ENCSR383CBN/summary/ENCFF577VAD.w5 32 2 mean CHIP:H3K18ac:IMR-90 CHIP ChIP-Histone:H3K18ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2619 0 ENCFF649BYY /home/drk/tillage/datasets/human/chip/encode/ENCSR384LKH/summary/ENCFF649BYY.w5 32 2 mean CHIP:H3K9ac:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K9ac/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2620 0 ENCFF522SLB /home/drk/tillage/datasets/human/chip/encode/ENCSR384LYW/summary/ENCFF522SLB.w5 32 2 mean CHIP:EZH2:hepatocyte originated from H9 CHIP ChIP-TF:EZH2/hepatocyte originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2621 0 ENCFF468PJO /home/drk/tillage/datasets/human/chip/encode/ENCSR385AHH/summary/ENCFF468PJO.w5 32 2 mean CHIP:ZNF24:K562 CHIP ChIP-TF:ZNF24/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2622 0 ENCFF835LIY /home/drk/tillage/datasets/human/chip/encode/ENCSR385NUC/summary/ENCFF835LIY.w5 32 2 mean CHIP:H3K4me1:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K4me1/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2623 0 ENCFF321KUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR386JEL/summary/ENCFF321KUJ.w5 32 2 mean CHIP:H3K4me1:brain female embryo (17 weeks) CHIP ChIP-Histone:H3K4me1/brain female embryo (17 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2624 0 ENCFF943TXM /home/drk/tillage/datasets/human/chip/encode/ENCSR386RIJ/summary/ENCFF943TXM.w5 32 2 mean CHIP:H3K27me3:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K27me3/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2625 0 ENCFF740YDG /home/drk/tillage/datasets/human/chip/encode/ENCSR386WCR/summary/ENCFF740YDG.w5 32 2 mean CHIP:H4K91ac:H9 CHIP ChIP-TF:H4K91ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2626 0 ENCFF693ZNN /home/drk/tillage/datasets/human/chip/encode/ENCSR386YIH/summary/ENCFF693ZNN.w5 32 2 mean CHIP:SP1:liver female child (4 years) CHIP ChIP-TF:SP1/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2627 0 ENCFF032IAM /home/drk/tillage/datasets/human/chip/encode/ENCSR387JKT/summary/ENCFF032IAM.w5 32 2 mean CHIP:3xFLAG-KDM3A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KDM3A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2628 0 ENCFF621JFM /home/drk/tillage/datasets/human/chip/encode/ENCSR387QUV/summary/ENCFF621JFM.w5 32 2 mean CHIP:RELB:GM12878 CHIP ChIP-TF:RELB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2629 0 ENCFF766RAU /home/drk/tillage/datasets/human/chip/encode/ENCSR387SYS/summary/ENCFF766RAU.w5 32 2 mean CHIP:DEAF1:K562 CHIP ChIP-TF:DEAF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2630 0 ENCFF412CHL /home/drk/tillage/datasets/human/chip/encode/ENCSR387UWP/summary/ENCFF412CHL.w5 32 2 mean CHIP:HDAC1:K562 CHIP ChIP-TF:HDAC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2631 0 ENCFF321FZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR388QZF/summary/ENCFF321FZQ.w5 32 2 mean CHIP:POLR2A:K562 CHIP ChIP-TF:POLR2A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2632 0 ENCFF496ETO /home/drk/tillage/datasets/human/chip/encode/ENCSR389BLX/summary/ENCFF496ETO.w5 32 2 mean CHIP:GATAD2B:MCF-7 CHIP ChIP-TF:GATAD2B/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2633 0 ENCFF967HST /home/drk/tillage/datasets/human/chip/encode/ENCSR389IVA/summary/ENCFF967HST.w5 32 2 mean CHIP:H3K9me3:peripheral blood mononuclear cell male adult (27 years) CHIP ChIP-Histone:H3K9me3/peripheral blood mononuclear cell male adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2634 0 ENCFF629AKZ /home/drk/tillage/datasets/human/chip/encode/ENCSR389OFJ/summary/ENCFF629AKZ.w5 32 2 mean CHIP:H3K4me1:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K4me1/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2635 0 ENCFF622AKD /home/drk/tillage/datasets/human/chip/encode/ENCSR389PWB/summary/ENCFF622AKD.w5 32 2 mean CHIP:ZBTB5:K562 CHIP ChIP-TF:ZBTB5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2636 0 ENCFF886XTQ /home/drk/tillage/datasets/human/chip/encode/ENCSR389SGO/summary/ENCFF886XTQ.w5 32 2 mean CHIP:H3K9me3:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K9me3/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2637 0 ENCFF855PIZ /home/drk/tillage/datasets/human/chip/encode/ENCSR389WWC/summary/ENCFF855PIZ.w5 32 2 mean CHIP:H3K9me3:OCI-LY7 CHIP ChIP-Histone:H3K9me3/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2638 0 ENCFF719RRR /home/drk/tillage/datasets/human/chip/encode/ENCSR390SFH/summary/ENCFF719RRR.w5 32 2 mean CHIP:H3K27me3:peripheral blood mononuclear cell female adult (28 years) CHIP ChIP-Histone:H3K27me3/peripheral blood mononuclear cell female adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2639 0 ENCFF307NZC /home/drk/tillage/datasets/human/chip/encode/ENCSR390VGH/summary/ENCFF307NZC.w5 32 2 mean CHIP:MNT:K562 CHIP ChIP-TF:MNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2640 0 ENCFF293ETP /home/drk/tillage/datasets/human/chip/encode/ENCSR391EQV/summary/ENCFF293ETP.w5 32 2 mean CHIP:H3K27ac:natural killer cell male adult (37 years) CHIP ChIP-Histone:H3K27ac/natural killer cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2641 0 ENCFF323SMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR391IWM/summary/ENCFF323SMQ.w5 32 2 mean CHIP:KDM1A:GM12878 CHIP ChIP-TF:KDM1A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2642 0 ENCFF259MJI /home/drk/tillage/datasets/human/chip/encode/ENCSR391JII/summary/ENCFF259MJI.w5 32 2 mean CHIP:RCOR1:MCF-7 CHIP ChIP-TF:RCOR1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2643 0 ENCFF195UTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR391KQC/summary/ENCFF195UTZ.w5 32 2 mean CHIP:MTA3:MCF-7 CHIP ChIP-TF:MTA3/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2644 0 ENCFF062MFT /home/drk/tillage/datasets/human/chip/encode/ENCSR391NPE/summary/ENCFF062MFT.w5 32 2 mean CHIP:H3K27ac:22Rv1 CHIP ChIP-Histone:H3K27ac/22Rv1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2645 0 ENCFF411PDM /home/drk/tillage/datasets/human/chip/encode/ENCSR391WDE/summary/ENCFF411PDM.w5 32 2 mean CHIP:H3K9me3:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K9me3/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2646 0 ENCFF534GRR /home/drk/tillage/datasets/human/chip/encode/ENCSR391ZKN/summary/ENCFF534GRR.w5 32 2 mean CHIP:CTCF:Peyer's patch female adult (51 year) CHIP ChIP-TF:CTCF/Peyer's patch female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2647 0 ENCFF994ERU /home/drk/tillage/datasets/human/chip/encode/ENCSR392SFJ/summary/ENCFF994ERU.w5 32 2 mean CHIP:CTCF:uterus female adult (53 years) CHIP ChIP-TF:CTCF/uterus female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2648 0 ENCFF505ULB /home/drk/tillage/datasets/human/chip/encode/ENCSR393HBQ/summary/ENCFF505ULB.w5 32 2 mean CHIP:H3K36me3:pancreas female adult (30 years) CHIP ChIP-Histone:H3K36me3/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2649 0 ENCFF527ROT /home/drk/tillage/datasets/human/chip/encode/ENCSR393HDC/summary/ENCFF527ROT.w5 32 2 mean CHIP:H3K9me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K9me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2650 0 ENCFF628GHA /home/drk/tillage/datasets/human/chip/encode/ENCSR393SYU/summary/ENCFF628GHA.w5 32 2 mean CHIP:H3K4me3:neutrophil CHIP ChIP-Histone:H3K4me3/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2651 0 ENCFF890MAI /home/drk/tillage/datasets/human/chip/encode/ENCSR394DRL/summary/ENCFF890MAI.w5 32 2 mean CHIP:H3K9me3:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K9me3/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2652 0 ENCFF517NJW /home/drk/tillage/datasets/human/chip/encode/ENCSR395HWC/summary/ENCFF517NJW.w5 32 2 mean CHIP:IKZF1:K562 CHIP ChIP-TF:IKZF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2653 0 ENCFF752UGN /home/drk/tillage/datasets/human/chip/encode/ENCSR395USV/summary/ENCFF752UGN.w5 32 2 mean CHIP:H3K9me3:H1-hESC CHIP ChIP-Histone:H3K9me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2654 0 ENCFF310JVO /home/drk/tillage/datasets/human/chip/encode/ENCSR395YXN/summary/ENCFF310JVO.w5 32 2 mean CHIP:H3K4me3:T-cell male adult (37 years) CHIP ChIP-Histone:H3K4me3/T-cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2655 0 ENCFF883ZNP /home/drk/tillage/datasets/human/chip/encode/ENCSR396QWK/summary/ENCFF883ZNP.w5 32 2 mean CHIP:3xFLAG-MBD1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MBD1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2656 0 ENCFF538EEF /home/drk/tillage/datasets/human/chip/encode/ENCSR396SKI/summary/ENCFF538EEF.w5 32 2 mean CHIP:eGFP-ZNF331:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF331/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2657 0 ENCFF404QLC /home/drk/tillage/datasets/human/chip/encode/ENCSR396SOH/summary/ENCFF404QLC.w5 32 2 mean CHIP:3xFLAG-ZNF792:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF792/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2658 0 ENCFF752CCS /home/drk/tillage/datasets/human/chip/encode/ENCSR397DQC/summary/ENCFF752CCS.w5 32 2 mean CHIP:eGFP-KLF16:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF16/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2659 0 ENCFF514SQD /home/drk/tillage/datasets/human/chip/encode/ENCSR397FAN/summary/ENCFF514SQD.w5 32 2 mean CHIP:H3K4me1:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2660 0 ENCFF122EGP /home/drk/tillage/datasets/human/chip/encode/ENCSR397HSO/summary/ENCFF122EGP.w5 32 2 mean CHIP:H3K9me2:neural cell CHIP ChIP-Histone:H3K9me2/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2661 0 ENCFF998YEH /home/drk/tillage/datasets/human/chip/encode/ENCSR397TUH/summary/ENCFF998YEH.w5 32 2 mean CHIP:H2AFZ:GM23248 CHIP ChIP-TF:H2AFZ/GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2662 0 ENCFF037JDO /home/drk/tillage/datasets/human/chip/encode/ENCSR399SJE/summary/ENCFF037JDO.w5 32 2 mean CHIP:H3K36me3:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K36me3/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2663 0 ENCFF807DXV /home/drk/tillage/datasets/human/chip/encode/ENCSR399VPY/summary/ENCFF807DXV.w5 32 2 mean CHIP:H3K9me2:MM.1S CHIP ChIP-Histone:H3K9me2/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2664 0 ENCFF276SWS /home/drk/tillage/datasets/human/chip/encode/ENCSR400FSM/summary/ENCFF276SWS.w5 32 2 mean CHIP:eGFP-POLR2H:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-POLR2H/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2665 0 ENCFF577YZK /home/drk/tillage/datasets/human/chip/encode/ENCSR400VWA/summary/ENCFF577YZK.w5 32 2 mean CHIP:H3K4me1:CD14-positive monocyte male adult (21 year) CHIP ChIP-Histone:H3K4me1/CD14-positive monocyte male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2666 0 ENCFF643JAF /home/drk/tillage/datasets/human/chip/encode/ENCSR400WEK/summary/ENCFF643JAF.w5 32 2 mean CHIP:POLR2AphosphoS5:breast epithelium female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/breast epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2667 0 ENCFF992JPT /home/drk/tillage/datasets/human/chip/encode/ENCSR401CJA/summary/ENCFF992JPT.w5 32 2 mean CHIP:H3K4me1:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K4me1/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2668 0 ENCFF416EKA /home/drk/tillage/datasets/human/chip/encode/ENCSR401ORC/summary/ENCFF416EKA.w5 32 2 mean CHIP:POLR2A:vagina female adult (53 years) CHIP ChIP-TF:POLR2A/vagina female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2669 0 ENCFF708QSO /home/drk/tillage/datasets/human/chip/encode/ENCSR401VZL/summary/ENCFF708QSO.w5 32 2 mean CHIP:H3K4me3:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K4me3/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2670 0 ENCFF913NVD /home/drk/tillage/datasets/human/chip/encode/ENCSR402HFW/summary/ENCFF913NVD.w5 32 2 mean CHIP:H3K27ac:pancreas female adult (30 years) CHIP ChIP-Histone:H3K27ac/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2671 0 ENCFF558FUO /home/drk/tillage/datasets/human/chip/encode/ENCSR402IDP/summary/ENCFF558FUO.w5 32 2 mean CHIP:CTCF:MM.1S CHIP ChIP-TF:CTCF/MM.1S ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2672 0 ENCFF914RPB /home/drk/tillage/datasets/human/chip/encode/ENCSR402JAC/summary/ENCFF914RPB.w5 32 2 mean CHIP:ZNF574:MCF-7 CHIP ChIP-TF:ZNF574/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2673 0 ENCFF663BHW /home/drk/tillage/datasets/human/chip/encode/ENCSR402SJV/summary/ENCFF663BHW.w5 32 2 mean CHIP:H3K36me3:PC-9 CHIP ChIP-Histone:H3K36me3/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2674 0 ENCFF410LEX /home/drk/tillage/datasets/human/chip/encode/ENCSR402XII/summary/ENCFF410LEX.w5 32 2 mean CHIP:CSDE1:K562 CHIP ChIP-TF:CSDE1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2675 0 ENCFF073ODD /home/drk/tillage/datasets/human/chip/encode/ENCSR403KAA/summary/ENCFF073ODD.w5 32 2 mean CHIP:H3K4me3:fibroblast of breast female adult (17 years) CHIP ChIP-Histone:H3K4me3/fibroblast of breast female adult (17 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2676 0 ENCFF091BXR /home/drk/tillage/datasets/human/chip/encode/ENCSR403UOU/summary/ENCFF091BXR.w5 32 2 mean CHIP:H3K9me3:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K9me3/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2677 0 ENCFF675WFV /home/drk/tillage/datasets/human/chip/encode/ENCSR403USE/summary/ENCFF675WFV.w5 32 2 mean CHIP:POLR2AphosphoS5:sigmoid colon female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/sigmoid colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2678 0 ENCFF938GRJ /home/drk/tillage/datasets/human/chip/encode/ENCSR404BPV/summary/ENCFF938GRJ.w5 32 2 mean CHIP:SMC3:neural cell originated from H1-hESC CHIP ChIP-TF:SMC3/neural cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2679 0 ENCFF615KRJ /home/drk/tillage/datasets/human/chip/encode/ENCSR404LJZ/summary/ENCFF615KRJ.w5 32 2 mean CHIP:H3K27me3:MM.1S CHIP ChIP-Histone:H3K27me3/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2680 0 ENCFF046VLL /home/drk/tillage/datasets/human/chip/encode/ENCSR404MOX/summary/ENCFF046VLL.w5 32 2 mean CHIP:H3K27me3:B cell male adult (21 year) CHIP ChIP-Histone:H3K27me3/B cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2681 0 ENCFF805OFW /home/drk/tillage/datasets/human/chip/encode/ENCSR404VWY/summary/ENCFF805OFW.w5 32 2 mean CHIP:POLR2AphosphoS5:prostate gland male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/prostate gland male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2682 0 ENCFF389GSX /home/drk/tillage/datasets/human/chip/encode/ENCSR405AXO/summary/ENCFF389GSX.w5 32 2 mean CHIP:H3K27me3:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K27me3/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2683 0 ENCFF608OTO /home/drk/tillage/datasets/human/chip/encode/ENCSR405ESP/summary/ENCFF608OTO.w5 32 2 mean CHIP:H3K27ac:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K27ac/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2684 0 ENCFF463NRD /home/drk/tillage/datasets/human/chip/encode/ENCSR405FZE/summary/ENCFF463NRD.w5 32 2 mean CHIP:H3K27ac:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K27ac/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2685 0 ENCFF996FDL /home/drk/tillage/datasets/human/chip/encode/ENCSR405NQJ/summary/ENCFF996FDL.w5 32 2 mean CHIP:H3K9me3:neural cell CHIP ChIP-Histone:H3K9me3/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2686 0 ENCFF438WFE /home/drk/tillage/datasets/human/chip/encode/ENCSR405YYG/summary/ENCFF438WFE.w5 32 2 mean CHIP:H3K9me3:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K9me3/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2687 0 ENCFF843ULH /home/drk/tillage/datasets/human/chip/encode/ENCSR406PCK/summary/ENCFF843ULH.w5 32 2 mean CHIP:H3K4me1:adrenal gland male adult (54 years) CHIP ChIP-Histone:H3K4me1/adrenal gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2688 0 ENCFF266GSU /home/drk/tillage/datasets/human/chip/encode/ENCSR406VUH/summary/ENCFF266GSU.w5 32 2 mean CHIP:H3K9me3:thymus female embryo (110 days) CHIP ChIP-Histone:H3K9me3/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2689 0 ENCFF615KKS /home/drk/tillage/datasets/human/chip/encode/ENCSR407BEZ/summary/ENCFF615KKS.w5 32 2 mean CHIP:ZHX2:HepG2 CHIP ChIP-TF:ZHX2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2690 0 ENCFF161JPA /home/drk/tillage/datasets/human/chip/encode/ENCSR408JQO/summary/ENCFF161JPA.w5 32 2 mean CHIP:IRF3:GM12878 CHIP ChIP-TF:IRF3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2691 0 ENCFF705RLR /home/drk/tillage/datasets/human/chip/encode/ENCSR408ONP/summary/ENCFF705RLR.w5 32 2 mean CHIP:H3K27me3:spleen male adult (34 years) CHIP ChIP-Histone:H3K27me3/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2692 0 ENCFF788GYB /home/drk/tillage/datasets/human/chip/encode/ENCSR408XTO/summary/ENCFF788GYB.w5 32 2 mean CHIP:CTCF:body of pancreas female adult (51 year) CHIP ChIP-TF:CTCF/body of pancreas female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2693 0 ENCFF472JYR /home/drk/tillage/datasets/human/chip/encode/ENCSR408ZEW/summary/ENCFF472JYR.w5 32 2 mean CHIP:H3K9me3:adrenal gland male adult (54 years) CHIP ChIP-Histone:H3K9me3/adrenal gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2694 0 ENCFF729ABI /home/drk/tillage/datasets/human/chip/encode/ENCSR409RGJ/summary/ENCFF729ABI.w5 32 2 mean CHIP:H3K4me1:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me1/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2695 0 ENCFF035DWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR410DWC/summary/ENCFF035DWJ.w5 32 2 mean CHIP:eGFP-PYGO2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-PYGO2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2696 0 ENCFF319CHA /home/drk/tillage/datasets/human/chip/encode/ENCSR410FIQ/summary/ENCFF319CHA.w5 32 2 mean CHIP:H3K4me1:mesodermal cell originated from HUES64 CHIP ChIP-Histone:H3K4me1/mesodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2697 0 ENCFF069FLU /home/drk/tillage/datasets/human/chip/encode/ENCSR410GUN/summary/ENCFF069FLU.w5 32 2 mean CHIP:H3K27me3:HUES6 CHIP ChIP-Histone:H3K27me3/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2698 0 ENCFF336QAJ /home/drk/tillage/datasets/human/chip/encode/ENCSR410UUH/summary/ENCFF336QAJ.w5 32 2 mean CHIP:H3K4me1:psoas muscle male adult (34 years) CHIP ChIP-Histone:H3K4me1/psoas muscle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2699 0 ENCFF905FAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR411UYA/summary/ENCFF905FAZ.w5 32 2 mean CHIP:MTA2:K562 CHIP ChIP-TF:MTA2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2700 0 ENCFF417FWT /home/drk/tillage/datasets/human/chip/encode/ENCSR412CTM/summary/ENCFF417FWT.w5 32 2 mean CHIP:SUZ12:K562 CHIP ChIP-TF:SUZ12/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2701 0 ENCFF732KHL /home/drk/tillage/datasets/human/chip/encode/ENCSR412QBS/summary/ENCFF732KHL.w5 32 2 mean CHIP:TARDBP:GM12878 CHIP ChIP-TF:TARDBP/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2702 0 ENCFF272KCH /home/drk/tillage/datasets/human/chip/encode/ENCSR412QGD/summary/ENCFF272KCH.w5 32 2 mean CHIP:POLR2A:adrenal gland female adult (51 year) CHIP ChIP-TF:POLR2A/adrenal gland female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2703 0 ENCFF052YOW /home/drk/tillage/datasets/human/chip/encode/ENCSR412YGM/summary/ENCFF052YOW.w5 32 2 mean CHIP:ZSCAN29:GM12878 CHIP ChIP-TF:ZSCAN29/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2704 0 ENCFF916DXW /home/drk/tillage/datasets/human/chip/encode/ENCSR412ZDC/summary/ENCFF916DXW.w5 32 2 mean CHIP:3xFLAG-AHR:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-AHR/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2705 0 ENCFF298LTL /home/drk/tillage/datasets/human/chip/encode/ENCSR413QXO/summary/ENCFF298LTL.w5 32 2 mean CHIP:H3K4me3:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K4me3/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2706 0 ENCFF603DYO /home/drk/tillage/datasets/human/chip/encode/ENCSR413WJD/summary/ENCFF603DYO.w5 32 2 mean CHIP:H3K4me3:lung embryo (101 day) CHIP ChIP-Histone:H3K4me3/lung embryo (101 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2707 0 ENCFF440SDS /home/drk/tillage/datasets/human/chip/encode/ENCSR414SWG/summary/ENCFF440SDS.w5 32 2 mean CHIP:POLR2A:gastrocnemius medialis female adult (51 year) CHIP ChIP-TF:POLR2A/gastrocnemius medialis female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2708 0 ENCFF425FCE /home/drk/tillage/datasets/human/chip/encode/ENCSR414TPL/summary/ENCFF425FCE.w5 32 2 mean CHIP:POLR2A:gastroesophageal sphincter male adult (37 years) CHIP ChIP-TF:POLR2A/gastroesophageal sphincter male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2709 0 ENCFF580PSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR414TYY/summary/ENCFF580PSQ.w5 32 2 mean CHIP:RUNX1:K562 CHIP ChIP-TF:RUNX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2710 0 ENCFF605TCK /home/drk/tillage/datasets/human/chip/encode/ENCSR415AEB/summary/ENCFF605TCK.w5 32 2 mean CHIP:3xFLAG-ZNF48:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF48/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2711 0 ENCFF072BII /home/drk/tillage/datasets/human/chip/encode/ENCSR415MOW/summary/ENCFF072BII.w5 32 2 mean CHIP:POLR2A:right lobe of liver female adult (53 years) CHIP ChIP-TF:POLR2A/right lobe of liver female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2712 0 ENCFF976IUW /home/drk/tillage/datasets/human/chip/encode/ENCSR415TXN/summary/ENCFF976IUW.w5 32 2 mean CHIP:NONO:K562 CHIP ChIP-TF:NONO/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2713 0 ENCFF382HRD /home/drk/tillage/datasets/human/chip/encode/ENCSR416AUW/summary/ENCFF382HRD.w5 32 2 mean CHIP:H3K4me3:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K4me3/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2714 0 ENCFF652OON /home/drk/tillage/datasets/human/chip/encode/ENCSR416CYZ/summary/ENCFF652OON.w5 32 2 mean CHIP:H3K4me1:thoracic aorta male adult (54 years) CHIP ChIP-Histone:H3K4me1/thoracic aorta male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2715 0 ENCFF988PMK /home/drk/tillage/datasets/human/chip/encode/ENCSR416QLJ/summary/ENCFF988PMK.w5 32 2 mean CHIP:eGFP-CEBPB:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-CEBPB/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2716 0 ENCFF884QIE /home/drk/tillage/datasets/human/chip/encode/ENCSR417DKD/summary/ENCFF884QIE.w5 32 2 mean CHIP:NFXL1:MCF-7 CHIP ChIP-TF:NFXL1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2717 0 ENCFF610XUT /home/drk/tillage/datasets/human/chip/encode/ENCSR417IEJ/summary/ENCFF610XUT.w5 32 2 mean CHIP:H3K27me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2718 0 ENCFF695NFP /home/drk/tillage/datasets/human/chip/encode/ENCSR417RFS/summary/ENCFF695NFP.w5 32 2 mean CHIP:H3K9me3:small intestine male child (3 years) CHIP ChIP-Histone:H3K9me3/small intestine male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2719 0 ENCFF034PTR /home/drk/tillage/datasets/human/chip/encode/ENCSR417VWF/summary/ENCFF034PTR.w5 32 2 mean CHIP:eGFP-ZEB2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZEB2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2720 0 ENCFF605OIM /home/drk/tillage/datasets/human/chip/encode/ENCSR418JIS/summary/ENCFF605OIM.w5 32 2 mean CHIP:H3K4me3:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K4me3/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2721 0 ENCFF286MEX /home/drk/tillage/datasets/human/chip/encode/ENCSR418KUS/summary/ENCFF286MEX.w5 32 2 mean CHIP:ZEB1:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:ZEB1/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2722 0 ENCFF278CLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR418MKG/summary/ENCFF278CLQ.w5 32 2 mean CHIP:eGFP-ZNF692:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF692/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2723 0 ENCFF025YPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR418NZA/summary/ENCFF025YPQ.w5 32 2 mean CHIP:eGFP-ZNF524:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF524/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2724 0 ENCFF222RPJ /home/drk/tillage/datasets/human/chip/encode/ENCSR418RRF/summary/ENCFF222RPJ.w5 32 2 mean CHIP:KDM1A:H1-hESC CHIP ChIP-TF:KDM1A/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2725 0 ENCFF112FNQ /home/drk/tillage/datasets/human/chip/encode/ENCSR419ANE/summary/ENCFF112FNQ.w5 32 2 mean CHIP:CTCF:Peyer's patch male adult (37 years) CHIP ChIP-TF:CTCF/Peyer's patch male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2726 0 ENCFF374VXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR419BDT/summary/ENCFF374VXQ.w5 32 2 mean CHIP:H3K4me3:placenta female embryo (113 days) CHIP ChIP-Histone:H3K4me3/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2727 0 ENCFF214PES /home/drk/tillage/datasets/human/chip/encode/ENCSR419KSZ/summary/ENCFF214PES.w5 32 2 mean CHIP:NCOR1:HepG2 CHIP ChIP-TF:NCOR1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2728 0 ENCFF765BPW /home/drk/tillage/datasets/human/chip/encode/ENCSR419ODQ/summary/ENCFF765BPW.w5 32 2 mean CHIP:ZNF507:MCF-7 CHIP ChIP-TF:ZNF507/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2729 0 ENCFF457MJJ /home/drk/tillage/datasets/human/chip/encode/ENCSR420EWO/summary/ENCFF457MJJ.w5 32 2 mean CHIP:H3K4me1:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K4me1/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2730 0 ENCFF456YYL /home/drk/tillage/datasets/human/chip/encode/ENCSR420IOA/summary/ENCFF456YYL.w5 32 2 mean CHIP:H3K4me3:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K4me3/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2731 0 ENCFF530YMW /home/drk/tillage/datasets/human/chip/encode/ENCSR421FPV/summary/ENCFF530YMW.w5 32 2 mean CHIP:H3K9me3:spleen male adult (34 years) CHIP ChIP-Histone:H3K9me3/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2732 0 ENCFF995GIN /home/drk/tillage/datasets/human/chip/encode/ENCSR421HUB/summary/ENCFF995GIN.w5 32 2 mean CHIP:H3K4me3:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K4me3/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2733 0 ENCFF775ZUT /home/drk/tillage/datasets/human/chip/encode/ENCSR421QXA/summary/ENCFF775ZUT.w5 32 2 mean CHIP:eGFP-ZNF571:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF571/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2734 0 ENCFF104CMX /home/drk/tillage/datasets/human/chip/encode/ENCSR422JNY/summary/ENCFF104CMX.w5 32 2 mean CHIP:H3K4me3:OCI-LY1 CHIP ChIP-Histone:H3K4me3/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2735 0 ENCFF252JXI /home/drk/tillage/datasets/human/chip/encode/ENCSR422LQX/summary/ENCFF252JXI.w5 32 2 mean CHIP:H3K4me1:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K4me1/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2736 0 ENCFF994ZRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR422ZAO/summary/ENCFF994ZRQ.w5 32 2 mean CHIP:IRF3:SK-N-SH CHIP ChIP-TF:IRF3/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2737 0 ENCFF819IDN /home/drk/tillage/datasets/human/chip/encode/ENCSR423AKG/summary/ENCFF819IDN.w5 32 2 mean CHIP:H3K4me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2738 0 ENCFF892RWK /home/drk/tillage/datasets/human/chip/encode/ENCSR423FCW/summary/ENCFF892RWK.w5 32 2 mean CHIP:RBM14:K562 CHIP ChIP-TF:RBM14/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2739 0 ENCFF663SGN /home/drk/tillage/datasets/human/chip/encode/ENCSR423LXQ/summary/ENCFF663SGN.w5 32 2 mean CHIP:H3K27me3:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K27me3/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2740 0 ENCFF703CUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR423RTK/summary/ENCFF703CUQ.w5 32 2 mean CHIP:GATA3:MCF-7 CHIP ChIP-TF:GATA3/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2741 0 ENCFF745IIB /home/drk/tillage/datasets/human/chip/encode/ENCSR423UOT/summary/ENCFF745IIB.w5 32 2 mean CHIP:H3K9me2:SK-N-SH CHIP ChIP-Histone:H3K9me2/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2742 0 ENCFF021IQE /home/drk/tillage/datasets/human/chip/encode/ENCSR424XBP/summary/ENCFF021IQE.w5 32 2 mean CHIP:H3K36me3:B cell female adult (27 years) and female adult (43 years) CHIP ChIP-Histone:H3K36me3/B cell female adult (27 years) and female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2743 0 ENCFF329HEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR424ZJH/summary/ENCFF329HEZ.w5 32 2 mean CHIP:H2AK5ac:IMR-90 CHIP ChIP-TF:H2AK5ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2744 0 ENCFF637PCM /home/drk/tillage/datasets/human/chip/encode/ENCSR425NQT/summary/ENCFF637PCM.w5 32 2 mean CHIP:H3K4me3:adrenal gland female adult (30 years) CHIP ChIP-Histone:H3K4me3/adrenal gland female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2745 0 ENCFF197AVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR425PQI/summary/ENCFF197AVJ.w5 32 2 mean CHIP:H3K27ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K27ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2746 0 ENCFF973ANO /home/drk/tillage/datasets/human/chip/encode/ENCSR426CZM/summary/ENCFF973ANO.w5 32 2 mean CHIP:H3K36me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K36me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2747 0 ENCFF406QJG /home/drk/tillage/datasets/human/chip/encode/ENCSR426MDV/summary/ENCFF406QJG.w5 32 2 mean CHIP:MIER1:K562 CHIP ChIP-TF:MIER1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2748 0 ENCFF368AZA /home/drk/tillage/datasets/human/chip/encode/ENCSR426URK/summary/ENCFF368AZA.w5 32 2 mean CHIP:AFF1:K562 CHIP ChIP-TF:AFF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2749 0 ENCFF772JCX /home/drk/tillage/datasets/human/chip/encode/ENCSR426UWA/summary/ENCFF772JCX.w5 32 2 mean CHIP:H3K36me3:HUES64 CHIP ChIP-Histone:H3K36me3/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2750 0 ENCFF737EQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR427BBI/summary/ENCFF737EQQ.w5 32 2 mean CHIP:MLLT1:MCF-7 CHIP ChIP-TF:MLLT1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2751 0 ENCFF830SCA /home/drk/tillage/datasets/human/chip/encode/ENCSR427RFW/summary/ENCFF830SCA.w5 32 2 mean CHIP:H2AK5ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H2AK5ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2752 0 ENCFF167XIH /home/drk/tillage/datasets/human/chip/encode/ENCSR428BKN/summary/ENCFF167XIH.w5 32 2 mean CHIP:CTCF:gastrocnemius medialis female adult (53 years) CHIP ChIP-TF:CTCF/gastrocnemius medialis female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2753 0 ENCFF011JWE /home/drk/tillage/datasets/human/chip/encode/ENCSR429CLV/summary/ENCFF011JWE.w5 32 2 mean CHIP:EZH2phosphoT487:HCT116 CHIP ChIP-TF:EZH2phosphoT487/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2754 0 ENCFF617NYM /home/drk/tillage/datasets/human/chip/encode/ENCSR429EVA/summary/ENCFF617NYM.w5 32 2 mean CHIP:H3K9me3:skeletal muscle tissue CHIP ChIP-Histone:H3K9me3/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2755 0 ENCFF305XIN /home/drk/tillage/datasets/human/chip/encode/ENCSR429JTR/summary/ENCFF305XIN.w5 32 2 mean CHIP:EP300:transverse colon male adult (37 years) CHIP ChIP-TF:EP300/transverse colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2756 0 ENCFF237UPT /home/drk/tillage/datasets/human/chip/encode/ENCSR429MNF/summary/ENCFF237UPT.w5 32 2 mean CHIP:H3K36me3:lung male child (3 years) CHIP ChIP-Histone:H3K36me3/lung male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2757 0 ENCFF742LMU /home/drk/tillage/datasets/human/chip/encode/ENCSR429QPP/summary/ENCFF742LMU.w5 32 2 mean CHIP:FOXM1:K562 CHIP ChIP-TF:FOXM1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2758 0 ENCFF377YHN /home/drk/tillage/datasets/human/chip/encode/ENCSR429QYS/summary/ENCFF377YHN.w5 32 2 mean CHIP:H3K79me2:Loucy CHIP ChIP-Histone:H3K79me2/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2759 0 ENCFF308NJP /home/drk/tillage/datasets/human/chip/encode/ENCSR429XBU/summary/ENCFF308NJP.w5 32 2 mean CHIP:H3K4me1:body of pancreas female adult (53 years) CHIP ChIP-Histone:H3K4me1/body of pancreas female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2760 0 ENCFF134EIU /home/drk/tillage/datasets/human/chip/encode/ENCSR429XTR/summary/ENCFF134EIU.w5 32 2 mean CHIP:TARDBP:K562 CHIP ChIP-TF:TARDBP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2761 0 ENCFF817HZX /home/drk/tillage/datasets/human/chip/encode/ENCSR429YAE/summary/ENCFF817HZX.w5 32 2 mean CHIP:H3K27ac:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K27ac/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2762 0 ENCFF231BNU /home/drk/tillage/datasets/human/chip/encode/ENCSR430JGJ/summary/ENCFF231BNU.w5 32 2 mean CHIP:3xFLAG-THRB:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-THRB/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2763 0 ENCFF546WRX /home/drk/tillage/datasets/human/chip/encode/ENCSR430RVP/summary/ENCFF546WRX.w5 32 2 mean CHIP:H3K27ac:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2764 0 ENCFF645EDR /home/drk/tillage/datasets/human/chip/encode/ENCSR430TEE/summary/ENCFF645EDR.w5 32 2 mean CHIP:CTCF:lower leg skin female adult (53 years) CHIP ChIP-TF:CTCF/lower leg skin female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2765 0 ENCFF263OPD /home/drk/tillage/datasets/human/chip/encode/ENCSR430ULY/summary/ENCFF263OPD.w5 32 2 mean CHIP:H3K4me1:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2766 0 ENCFF265BPR /home/drk/tillage/datasets/human/chip/encode/ENCSR430YRJ/summary/ENCFF265BPR.w5 32 2 mean CHIP:CTCF:KMS-11 CHIP ChIP-TF:CTCF/KMS-11 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2767 0 ENCFF127POB /home/drk/tillage/datasets/human/chip/encode/ENCSR431EHE/summary/ENCFF127POB.w5 32 2 mean CHIP:POLR2A:sigmoid colon male adult (37 years) CHIP ChIP-TF:POLR2A/sigmoid colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2768 0 ENCFF881CWL /home/drk/tillage/datasets/human/chip/encode/ENCSR431FOF/summary/ENCFF881CWL.w5 32 2 mean CHIP:CHD4:HepG2 CHIP ChIP-TF:CHD4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2769 0 ENCFF531UZT /home/drk/tillage/datasets/human/chip/encode/ENCSR431FZZ/summary/ENCFF531UZT.w5 32 2 mean CHIP:H3K9me3:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K9me3/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2770 0 ENCFF415SYA /home/drk/tillage/datasets/human/chip/encode/ENCSR431TLD/summary/ENCFF415SYA.w5 32 2 mean CHIP:SMARCE1:MCF-7 CHIP ChIP-TF:SMARCE1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2771 0 ENCFF427IDA /home/drk/tillage/datasets/human/chip/encode/ENCSR431UUY/summary/ENCFF427IDA.w5 32 2 mean CHIP:H3K27me3:IMR-90 CHIP ChIP-Histone:H3K27me3/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2772 0 ENCFF150UQM /home/drk/tillage/datasets/human/chip/encode/ENCSR431XGJ/summary/ENCFF150UQM.w5 32 2 mean CHIP:PYGO2:K562 CHIP ChIP-TF:PYGO2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2773 0 ENCFF058VCF /home/drk/tillage/datasets/human/chip/encode/ENCSR432GAO/summary/ENCFF058VCF.w5 32 2 mean CHIP:POLR2A:thyroid gland female adult (51 year) CHIP ChIP-TF:POLR2A/thyroid gland female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2774 0 ENCFF400CTE /home/drk/tillage/datasets/human/chip/encode/ENCSR432KIH/summary/ENCFF400CTE.w5 32 2 mean CHIP:H3K4me3:spleen male adult (34 years) CHIP ChIP-Histone:H3K4me3/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2775 0 ENCFF258FCQ /home/drk/tillage/datasets/human/chip/encode/ENCSR432OIW/summary/ENCFF258FCQ.w5 32 2 mean CHIP:EP300:breast epithelium female adult (53 years) CHIP ChIP-TF:EP300/breast epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2776 0 ENCFF683KJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR433FJP/summary/ENCFF683KJQ.w5 32 2 mean CHIP:H3K18ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K18ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2777 0 ENCFF883CXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR433PUR/summary/ENCFF883CXQ.w5 32 2 mean CHIP:H3K4me3:radial glial cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K4me3/radial glial cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2778 0 ENCFF891PZS /home/drk/tillage/datasets/human/chip/encode/ENCSR434AFF/summary/ENCFF891PZS.w5 32 2 mean CHIP:H3K4me3:neutrophil male CHIP ChIP-Histone:H3K4me3/neutrophil male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2779 0 ENCFF234AHA /home/drk/tillage/datasets/human/chip/encode/ENCSR434MDA/summary/ENCFF234AHA.w5 32 2 mean CHIP:H3K36me3:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K36me3/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2780 0 ENCFF072IOC /home/drk/tillage/datasets/human/chip/encode/ENCSR434MWV/summary/ENCFF072IOC.w5 32 2 mean CHIP:POLR2A:stomach female adult (53 years) CHIP ChIP-TF:POLR2A/stomach female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2781 0 ENCFF831WLO /home/drk/tillage/datasets/human/chip/encode/ENCSR434NUA/summary/ENCFF831WLO.w5 32 2 mean CHIP:H3K4me1:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K4me1/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2782 0 ENCFF725SHA /home/drk/tillage/datasets/human/chip/encode/ENCSR434XLP/summary/ENCFF725SHA.w5 32 2 mean CHIP:CTCF:tibial nerve male adult (37 years) CHIP ChIP-TF:CTCF/tibial nerve male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2783 0 ENCFF938RYF /home/drk/tillage/datasets/human/chip/encode/ENCSR435FGK/summary/ENCFF938RYF.w5 32 2 mean CHIP:H3K4me3:A673 CHIP ChIP-Histone:H3K4me3/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2784 0 ENCFF065SHH /home/drk/tillage/datasets/human/chip/encode/ENCSR435OQD/summary/ENCFF065SHH.w5 32 2 mean CHIP:ZFX:MCF-7 CHIP ChIP-TF:ZFX/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2785 0 ENCFF085FZW /home/drk/tillage/datasets/human/chip/encode/ENCSR435WPP/summary/ENCFF085FZW.w5 32 2 mean CHIP:H3K36me3:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K36me3/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2786 0 ENCFF724KWV /home/drk/tillage/datasets/human/chip/encode/ENCSR437GBJ/summary/ENCFF724KWV.w5 32 2 mean CHIP:NFATC3:GM12878 CHIP ChIP-TF:NFATC3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2787 0 ENCFF777GYB /home/drk/tillage/datasets/human/chip/encode/ENCSR437MHW/summary/ENCFF777GYB.w5 32 2 mean CHIP:H3K9me3:neutrophil male CHIP ChIP-Histone:H3K9me3/neutrophil male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2788 0 ENCFF175TOT /home/drk/tillage/datasets/human/chip/encode/ENCSR437ORF/summary/ENCFF175TOT.w5 32 2 mean CHIP:H3K36me3:IMR-90 CHIP ChIP-Histone:H3K36me3/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2789 0 ENCFF015VNH /home/drk/tillage/datasets/human/chip/encode/ENCSR437QMD/summary/ENCFF015VNH.w5 32 2 mean CHIP:H3K27ac:stomach male child (3 years) CHIP ChIP-Histone:H3K27ac/stomach male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2790 0 ENCFF622TRE /home/drk/tillage/datasets/human/chip/encode/ENCSR438BEX/summary/ENCFF622TRE.w5 32 2 mean CHIP:H3K4me3:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K4me3/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2791 0 ENCFF270FRB /home/drk/tillage/datasets/human/chip/encode/ENCSR438DSO/summary/ENCFF270FRB.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive male adult (36 years) CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2792 0 ENCFF852BNY /home/drk/tillage/datasets/human/chip/encode/ENCSR438FON/summary/ENCFF852BNY.w5 32 2 mean CHIP:H3K4me1:H7-hESC CHIP ChIP-Histone:H3K4me1/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2793 0 ENCFF221FZH /home/drk/tillage/datasets/human/chip/encode/ENCSR438PYA/summary/ENCFF221FZH.w5 32 2 mean CHIP:H3K9me3:KOPT-K1 CHIP ChIP-Histone:H3K9me3/KOPT-K1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2794 0 ENCFF203URF /home/drk/tillage/datasets/human/chip/encode/ENCSR438QZN/summary/ENCFF203URF.w5 32 2 mean CHIP:H3K4me1:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K4me1/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2795 0 ENCFF871QBB /home/drk/tillage/datasets/human/chip/encode/ENCSR438SPO/summary/ENCFF871QBB.w5 32 2 mean CHIP:H3K27ac:kidney male adult (50 years) CHIP ChIP-Histone:H3K27ac/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2796 0 ENCFF866ZIT /home/drk/tillage/datasets/human/chip/encode/ENCSR438ZIS/summary/ENCFF866ZIT.w5 32 2 mean CHIP:H3K27me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K27me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2797 0 ENCFF282EYD /home/drk/tillage/datasets/human/chip/encode/ENCSR439EHQ/summary/ENCFF282EYD.w5 32 2 mean CHIP:H3K9me3:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K9me3/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2798 0 ENCFF385ZWT /home/drk/tillage/datasets/human/chip/encode/ENCSR439OCL/summary/ENCFF385ZWT.w5 32 2 mean CHIP:ZNF407:K562 CHIP ChIP-TF:ZNF407/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2799 0 ENCFF028VTH /home/drk/tillage/datasets/human/chip/encode/ENCSR439WAF/summary/ENCFF028VTH.w5 32 2 mean CHIP:E4F1:GM12878 CHIP ChIP-TF:E4F1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2800 0 ENCFF439AAR /home/drk/tillage/datasets/human/chip/encode/ENCSR440BZV/summary/ENCFF439AAR.w5 32 2 mean CHIP:H3K14ac:H9 CHIP ChIP-Histone:H3K14ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2801 0 ENCFF861GEB /home/drk/tillage/datasets/human/chip/encode/ENCSR440COG/summary/ENCFF861GEB.w5 32 2 mean CHIP:eGFP-ZNF239:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF239/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2802 0 ENCFF340UTP /home/drk/tillage/datasets/human/chip/encode/ENCSR440VKE/summary/ENCFF340UTP.w5 32 2 mean CHIP:eGFP-ADNP:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ADNP/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2803 0 ENCFF912RES /home/drk/tillage/datasets/human/chip/encode/ENCSR441JWF/summary/ENCFF912RES.w5 32 2 mean CHIP:H3K4me3:PC-9 CHIP ChIP-Histone:H3K4me3/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2804 0 ENCFF293LNG /home/drk/tillage/datasets/human/chip/encode/ENCSR441KFW/summary/ENCFF293LNG.w5 32 2 mean CHIP:3xFLAG-MXD4:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MXD4/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2805 0 ENCFF516NRP /home/drk/tillage/datasets/human/chip/encode/ENCSR441RDQ/summary/ENCFF516NRP.w5 32 2 mean CHIP:H3K9me3:regulatory T cell originated from blood cell CHIP ChIP-Histone:H3K9me3/regulatory T cell originated from blood cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2806 0 ENCFF748XLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR441SAT/summary/ENCFF748XLQ.w5 32 2 mean CHIP:H3K4me3:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K4me3/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2807 0 ENCFF651AAI /home/drk/tillage/datasets/human/chip/encode/ENCSR441UBA/summary/ENCFF651AAI.w5 32 2 mean CHIP:eGFP-RBAK:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-RBAK/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2808 0 ENCFF834AZA /home/drk/tillage/datasets/human/chip/encode/ENCSR441UHO/summary/ENCFF834AZA.w5 32 2 mean CHIP:H3K9ac:H1-hESC CHIP ChIP-Histone:H3K9ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2809 0 ENCFF828IPR /home/drk/tillage/datasets/human/chip/encode/ENCSR441VHN/summary/ENCFF828IPR.w5 32 2 mean CHIP:IKZF1:GM12878 CHIP ChIP-TF:IKZF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2810 0 ENCFF771GOX /home/drk/tillage/datasets/human/chip/encode/ENCSR441YQA/summary/ENCFF771GOX.w5 32 2 mean CHIP:H3K9me3:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K9me3/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2811 0 ENCFF490DDF /home/drk/tillage/datasets/human/chip/encode/ENCSR442BHP/summary/ENCFF490DDF.w5 32 2 mean CHIP:H3K27me3:peripheral blood mononuclear cell male adult (28 years) CHIP ChIP-Histone:H3K27me3/peripheral blood mononuclear cell male adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2812 0 ENCFF695KSV /home/drk/tillage/datasets/human/chip/encode/ENCSR442CIF/summary/ENCFF695KSV.w5 32 2 mean CHIP:POLR2AphosphoS5:prostate gland male adult (54 years) CHIP ChIP-TF:POLR2AphosphoS5/prostate gland male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2813 0 ENCFF349YSW /home/drk/tillage/datasets/human/chip/encode/ENCSR442DGE/summary/ENCFF349YSW.w5 32 2 mean CHIP:H3K79me1:H1-hESC CHIP ChIP-Histone:H3K79me1/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2814 0 ENCFF816CTI /home/drk/tillage/datasets/human/chip/encode/ENCSR442JTA/summary/ENCFF816CTI.w5 32 2 mean CHIP:H3K9me3:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K9me3/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2815 0 ENCFF139MUH /home/drk/tillage/datasets/human/chip/encode/ENCSR442VBJ/summary/ENCFF139MUH.w5 32 2 mean CHIP:RAD51:MCF-7 CHIP ChIP-TF:RAD51/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2816 0 ENCFF735SZZ /home/drk/tillage/datasets/human/chip/encode/ENCSR442ZOI/summary/ENCFF735SZZ.w5 32 2 mean CHIP:H3K4me3:hepatocyte originated from H9 CHIP ChIP-Histone:H3K4me3/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2817 0 ENCFF149NUT /home/drk/tillage/datasets/human/chip/encode/ENCSR442ZTI/summary/ENCFF149NUT.w5 32 2 mean CHIP:POLR2AphosphoS5:esophagus muscularis mucosa female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/esophagus muscularis mucosa female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2818 0 ENCFF758PXZ /home/drk/tillage/datasets/human/chip/encode/ENCSR443MVV/summary/ENCFF758PXZ.w5 32 2 mean CHIP:eGFP-PRDM4:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM4/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2819 0 ENCFF996JSH /home/drk/tillage/datasets/human/chip/encode/ENCSR443NEP/summary/ENCFF996JSH.w5 32 2 mean CHIP:H3K4me1:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K4me1/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2820 0 ENCFF312ENS /home/drk/tillage/datasets/human/chip/encode/ENCSR443SLY/summary/ENCFF312ENS.w5 32 2 mean CHIP:H3K4me3:peripheral blood mononuclear cell male adult (27 years) CHIP ChIP-Histone:H3K4me3/peripheral blood mononuclear cell male adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2821 0 ENCFF970RKM /home/drk/tillage/datasets/human/chip/encode/ENCSR443UYU/summary/ENCFF970RKM.w5 32 2 mean CHIP:H3K27ac:coronary artery female adult (53 years) CHIP ChIP-Histone:H3K27ac/coronary artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2822 0 ENCFF614GXY /home/drk/tillage/datasets/human/chip/encode/ENCSR444LIN/summary/ENCFF614GXY.w5 32 2 mean CHIP:TCF7:HepG2 CHIP ChIP-TF:TCF7/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2823 0 ENCFF536MBM /home/drk/tillage/datasets/human/chip/encode/ENCSR444TMC/summary/ENCFF536MBM.w5 32 2 mean CHIP:H4K8ac:IMR-90 CHIP ChIP-TF:H4K8ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2824 0 ENCFF406JQM /home/drk/tillage/datasets/human/chip/encode/ENCSR444TQQ/summary/ENCFF406JQM.w5 32 2 mean CHIP:H3K27me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K27me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2825 0 ENCFF717RHJ /home/drk/tillage/datasets/human/chip/encode/ENCSR445ACU/summary/ENCFF717RHJ.w5 32 2 mean CHIP:SOX13:HepG2 CHIP ChIP-TF:SOX13/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2826 0 ENCFF174ISN /home/drk/tillage/datasets/human/chip/encode/ENCSR445PDR/summary/ENCFF174ISN.w5 32 2 mean CHIP:eGFP-GFI1B:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-GFI1B/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2827 0 ENCFF352PXN /home/drk/tillage/datasets/human/chip/encode/ENCSR445QRF/summary/ENCFF352PXN.w5 32 2 mean CHIP:HNF4A:liver female child (4 years) CHIP ChIP-TF:HNF4A/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2828 0 ENCFF024AYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR445RFF/summary/ENCFF024AYJ.w5 32 2 mean CHIP:H3K36me3:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K36me3/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2829 0 ENCFF386YEM /home/drk/tillage/datasets/human/chip/encode/ENCSR446LAV/summary/ENCFF386YEM.w5 32 2 mean CHIP:DDX20:K562 CHIP ChIP-TF:DDX20/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2830 0 ENCFF478GLT /home/drk/tillage/datasets/human/chip/encode/ENCSR446ZCY/summary/ENCFF478GLT.w5 32 2 mean CHIP:H3K4me3:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K4me3/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2831 0 ENCFF116RGG /home/drk/tillage/datasets/human/chip/encode/ENCSR447GWQ/summary/ENCFF116RGG.w5 32 2 mean CHIP:H3K9me3:stomach female embryo (96 days) CHIP ChIP-Histone:H3K9me3/stomach female embryo (96 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2832 0 ENCFF696UYH /home/drk/tillage/datasets/human/chip/encode/ENCSR447OHF/summary/ENCFF696UYH.w5 32 2 mean CHIP:H3K27ac:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K27ac/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2833 0 ENCFF787GTX /home/drk/tillage/datasets/human/chip/encode/ENCSR447ZGY/summary/ENCFF787GTX.w5 32 2 mean CHIP:H3K27ac:OCI-LY7 CHIP ChIP-Histone:H3K27ac/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2834 0 ENCFF197LVG /home/drk/tillage/datasets/human/chip/encode/ENCSR447ZTA/summary/ENCFF197LVG.w5 32 2 mean CHIP:eGFP-ZNF558:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF558/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2835 0 ENCFF380SRO /home/drk/tillage/datasets/human/chip/encode/ENCSR448FZC/summary/ENCFF380SRO.w5 32 2 mean CHIP:H3K4me3:spleen male child (3 years) CHIP ChIP-Histone:H3K4me3/spleen male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2836 0 ENCFF042FPP /home/drk/tillage/datasets/human/chip/encode/ENCSR448MML/summary/ENCFF042FPP.w5 32 2 mean CHIP:H3K9ac:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K9ac/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2837 0 ENCFF399GPT /home/drk/tillage/datasets/human/chip/encode/ENCSR448TUF/summary/ENCFF399GPT.w5 32 2 mean CHIP:H3K14ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K14ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2838 0 ENCFF447WWY /home/drk/tillage/datasets/human/chip/encode/ENCSR448UKK/summary/ENCFF447WWY.w5 32 2 mean CHIP:eGFP-ZKSCAN8:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZKSCAN8/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2839 0 ENCFF520NLE /home/drk/tillage/datasets/human/chip/encode/ENCSR449AXO/summary/ENCFF520NLE.w5 32 2 mean CHIP:H3K27ac:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K27ac/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2840 0 ENCFF295ABZ /home/drk/tillage/datasets/human/chip/encode/ENCSR449AYM/summary/ENCFF295ABZ.w5 32 2 mean CHIP:H3K36me3:OCI-LY1 CHIP ChIP-Histone:H3K36me3/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2841 0 ENCFF012HNX /home/drk/tillage/datasets/human/chip/encode/ENCSR449EBF/summary/ENCFF012HNX.w5 32 2 mean CHIP:H3K4me1:muscle of leg female embryo (110 days) CHIP ChIP-Histone:H3K4me1/muscle of leg female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2842 0 ENCFF788JCR /home/drk/tillage/datasets/human/chip/encode/ENCSR449FFA/summary/ENCFF788JCR.w5 32 2 mean CHIP:H3K36me3:chorion female embryo (40 weeks) CHIP ChIP-Histone:H3K36me3/chorion female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2843 0 ENCFF597VCD /home/drk/tillage/datasets/human/chip/encode/ENCSR449PYI/summary/ENCFF597VCD.w5 32 2 mean CHIP:H3K4me1:pancreas male adult (34 years) CHIP ChIP-Histone:H3K4me1/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2844 0 ENCFF975JDY /home/drk/tillage/datasets/human/chip/encode/ENCSR449SFZ/summary/ENCFF975JDY.w5 32 2 mean CHIP:H3K36me3:peripheral blood mononuclear cell male adult (28 years) CHIP ChIP-Histone:H3K36me3/peripheral blood mononuclear cell male adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2845 0 ENCFF755ULT /home/drk/tillage/datasets/human/chip/encode/ENCSR449TNC/summary/ENCFF755ULT.w5 32 2 mean CHIP:H3K36me3:urinary bladder male adult (34 years) CHIP ChIP-Histone:H3K36me3/urinary bladder male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2846 0 ENCFF131IDT /home/drk/tillage/datasets/human/chip/encode/ENCSR449UFF/summary/ENCFF131IDT.w5 32 2 mean CHIP:ZKSCAN1:MCF-7 CHIP ChIP-TF:ZKSCAN1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2847 0 ENCFF952XPH /home/drk/tillage/datasets/human/chip/encode/ENCSR450BLH/summary/ENCFF952XPH.w5 32 2 mean CHIP:CTCF:adrenal gland male adult (54 years) CHIP ChIP-TF:CTCF/adrenal gland male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2848 0 ENCFF632ENA /home/drk/tillage/datasets/human/chip/encode/ENCSR450FRI/summary/ENCFF632ENA.w5 32 2 mean CHIP:CTCF:esophagus squamous epithelium male adult (54 years) CHIP ChIP-TF:CTCF/esophagus squamous epithelium male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2849 0 ENCFF808ARD /home/drk/tillage/datasets/human/chip/encode/ENCSR451CYX/summary/ENCFF808ARD.w5 32 2 mean CHIP:eGFP-ZNF280D:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF280D/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2850 0 ENCFF227FWU /home/drk/tillage/datasets/human/chip/encode/ENCSR451EKU/summary/ENCFF227FWU.w5 32 2 mean CHIP:H3K9me3:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K9me3/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2851 0 ENCFF402QOD /home/drk/tillage/datasets/human/chip/encode/ENCSR451GTQ/summary/ENCFF402QOD.w5 32 2 mean CHIP:H3K9me3:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K9me3/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2852 0 ENCFF688OAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR452YHM/summary/ENCFF688OAQ.w5 32 2 mean CHIP:SIN3B:HepG2 CHIP ChIP-TF:SIN3B/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2853 0 ENCFF353AHL /home/drk/tillage/datasets/human/chip/encode/ENCSR453GNY/summary/ENCFF353AHL.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2854 0 ENCFF866FPE /home/drk/tillage/datasets/human/chip/encode/ENCSR453XEY/summary/ENCFF866FPE.w5 32 2 mean CHIP:H3K4me1:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me1/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2855 0 ENCFF507TJP /home/drk/tillage/datasets/human/chip/encode/ENCSR454ERY/summary/ENCFF507TJP.w5 32 2 mean CHIP:H3K27me3:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K27me3/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2856 0 ENCFF515SJR /home/drk/tillage/datasets/human/chip/encode/ENCSR454VRA/summary/ENCFF515SJR.w5 32 2 mean CHIP:H3K27ac:small intestine male child (3 years) CHIP ChIP-Histone:H3K27ac/small intestine male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2857 0 ENCFF984WOD /home/drk/tillage/datasets/human/chip/encode/ENCSR454WZX/summary/ENCFF984WOD.w5 32 2 mean CHIP:H3K9me3:lung female embryo (120 days) CHIP ChIP-Histone:H3K9me3/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2858 0 ENCFF922ZYU /home/drk/tillage/datasets/human/chip/encode/ENCSR455DOO/summary/ENCFF922ZYU.w5 32 2 mean CHIP:3xFLAG-RCOR2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RCOR2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2859 0 ENCFF888TUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR455JUO/summary/ENCFF888TUQ.w5 32 2 mean CHIP:H3K4me1:adrenal gland male adult (37 years) CHIP ChIP-Histone:H3K4me1/adrenal gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2860 0 ENCFF883XTW /home/drk/tillage/datasets/human/chip/encode/ENCSR456TZO/summary/ENCFF883XTW.w5 32 2 mean CHIP:H3K9me3:lung male child (3 years) CHIP ChIP-Histone:H3K9me3/lung male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2861 0 ENCFF698MQR /home/drk/tillage/datasets/human/chip/encode/ENCSR458PCE/summary/ENCFF698MQR.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive male adult (42 years) CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive male adult (42 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2862 0 ENCFF891SNS /home/drk/tillage/datasets/human/chip/encode/ENCSR458RRZ/summary/ENCFF891SNS.w5 32 2 mean CHIP:H3K27ac:heart left ventricle male adult (32 years) CHIP ChIP-Histone:H3K27ac/heart left ventricle male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2863 0 ENCFF151YYY /home/drk/tillage/datasets/human/chip/encode/ENCSR458WIH/summary/ENCFF151YYY.w5 32 2 mean CHIP:H3K4me3:liver male adult (31 year) CHIP ChIP-Histone:H3K4me3/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2864 0 ENCFF151LGF /home/drk/tillage/datasets/human/chip/encode/ENCSR459FTB/summary/ENCFF151LGF.w5 32 2 mean CHIP:UBTF:GM12878 CHIP ChIP-TF:UBTF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2865 0 ENCFF012GTV /home/drk/tillage/datasets/human/chip/encode/ENCSR459GCS/summary/ENCFF012GTV.w5 32 2 mean CHIP:H3K4me1:kidney female embryo (120 days) CHIP ChIP-Histone:H3K4me1/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2866 0 ENCFF319XGW /home/drk/tillage/datasets/human/chip/encode/ENCSR460LGH/summary/ENCFF319XGW.w5 32 2 mean CHIP:CTCF:C4-2B CHIP ChIP-TF:CTCF/C4-2B ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2867 0 ENCFF841UXV /home/drk/tillage/datasets/human/chip/encode/ENCSR460MBI/summary/ENCFF841UXV.w5 32 2 mean CHIP:eGFP-ZBTB20:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB20/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2868 0 ENCFF650WAB /home/drk/tillage/datasets/human/chip/encode/ENCSR460RHN/summary/ENCFF650WAB.w5 32 2 mean CHIP:H3K36me3:liver male adult (31 year) CHIP ChIP-Histone:H3K36me3/liver male adult (31 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2869 0 ENCFF341SIR /home/drk/tillage/datasets/human/chip/encode/ENCSR460SEN/summary/ENCFF341SIR.w5 32 2 mean CHIP:H3K4me1:DOHH2 CHIP ChIP-Histone:H3K4me1/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2870 0 ENCFF257PJW /home/drk/tillage/datasets/human/chip/encode/ENCSR460XGV/summary/ENCFF257PJW.w5 32 2 mean CHIP:MNT:MCF-7 CHIP ChIP-TF:MNT/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2871 0 ENCFF633ZFV /home/drk/tillage/datasets/human/chip/encode/ENCSR461HUD/summary/ENCFF633ZFV.w5 32 2 mean CHIP:H3F3A:PC-3 CHIP ChIP-Histone:H3F3A/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2872 0 ENCFF052LIP /home/drk/tillage/datasets/human/chip/encode/ENCSR461LTR/summary/ENCFF052LIP.w5 32 2 mean CHIP:H3K9me3:MM.1S CHIP ChIP-Histone:H3K9me3/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2873 0 ENCFF862HTP /home/drk/tillage/datasets/human/chip/encode/ENCSR461ZJT/summary/ENCFF862HTP.w5 32 2 mean CHIP:eGFP-ZNF501:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF501/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2874 0 ENCFF255THX /home/drk/tillage/datasets/human/chip/encode/ENCSR462FWS/summary/ENCFF255THX.w5 32 2 mean CHIP:eGFP-ZNF101:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF101/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2875 0 ENCFF556AXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR462KYU/summary/ENCFF556AXQ.w5 32 2 mean CHIP:3xFLAG-GABPB1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-GABPB1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2876 0 ENCFF171QBI /home/drk/tillage/datasets/human/chip/encode/ENCSR462QZZ/summary/ENCFF171QBI.w5 32 2 mean CHIP:eGFP-ZNF395:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF395/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2877 0 ENCFF382GFP /home/drk/tillage/datasets/human/chip/encode/ENCSR462XRE/summary/ENCFF382GFP.w5 32 2 mean CHIP:H2BK20ac:H1-hESC CHIP ChIP-TF:H2BK20ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2878 0 ENCFF184HFT /home/drk/tillage/datasets/human/chip/encode/ENCSR463DSJ/summary/ENCFF184HFT.w5 32 2 mean CHIP:H3K9me2:DOHH2 CHIP ChIP-Histone:H3K9me2/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2879 0 ENCFF318NHJ /home/drk/tillage/datasets/human/chip/encode/ENCSR464CSO/summary/ENCFF318NHJ.w5 32 2 mean CHIP:POLR2AphosphoS5:suprapubic skin male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/suprapubic skin male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2880 0 ENCFF915MLY /home/drk/tillage/datasets/human/chip/encode/ENCSR464DKE/summary/ENCFF915MLY.w5 32 2 mean CHIP:CTCF:Loucy CHIP ChIP-TF:CTCF/Loucy ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2881 0 ENCFF289QWH /home/drk/tillage/datasets/human/chip/encode/ENCSR464KFG/summary/ENCFF289QWH.w5 32 2 mean CHIP:eGFP-ZNF140:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF140/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2882 0 ENCFF730TAM /home/drk/tillage/datasets/human/chip/encode/ENCSR465BWW/summary/ENCFF730TAM.w5 32 2 mean CHIP:SRSF1:HepG2 CHIP ChIP-TF:SRSF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2883 0 ENCFF725DVY /home/drk/tillage/datasets/human/chip/encode/ENCSR465VLK/summary/ENCFF725DVY.w5 32 2 mean CHIP:FOXK2:MCF-7 CHIP ChIP-TF:FOXK2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2884 0 ENCFF385YHK /home/drk/tillage/datasets/human/chip/encode/ENCSR465XQW/summary/ENCFF385YHK.w5 32 2 mean CHIP:ZNF217:MCF-7 CHIP ChIP-TF:ZNF217/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2885 0 ENCFF849NRD /home/drk/tillage/datasets/human/chip/encode/ENCSR466DUB/summary/ENCFF849NRD.w5 32 2 mean CHIP:H3K36me3:spleen male adult (34 years) CHIP ChIP-Histone:H3K36me3/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2886 0 ENCFF293ASZ /home/drk/tillage/datasets/human/chip/encode/ENCSR466DZW/summary/ENCFF293ASZ.w5 32 2 mean CHIP:H3K4me3:lung female adult (30 years) CHIP ChIP-Histone:H3K4me3/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2887 0 ENCFF999DUA /home/drk/tillage/datasets/human/chip/encode/ENCSR466VYP/summary/ENCFF999DUA.w5 32 2 mean CHIP:eGFP-ZNF266:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF266/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2888 0 ENCFF524RRF /home/drk/tillage/datasets/human/chip/encode/ENCSR466XPN/summary/ENCFF524RRF.w5 32 2 mean CHIP:H3K4me1:CD4-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K4me1/CD4-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2889 0 ENCFF986LBH /home/drk/tillage/datasets/human/chip/encode/ENCSR467FMR/summary/ENCFF986LBH.w5 32 2 mean CHIP:H3K36me3:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K36me3/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2890 0 ENCFF558MRF /home/drk/tillage/datasets/human/chip/encode/ENCSR468IJT/summary/ENCFF558MRF.w5 32 2 mean CHIP:eGFP-SP7:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SP7/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2891 0 ENCFF034IDS /home/drk/tillage/datasets/human/chip/encode/ENCSR468LUO/summary/ENCFF034IDS.w5 32 2 mean CHIP:SIN3A:MCF-7 CHIP ChIP-TF:SIN3A/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2892 0 ENCFF423FWZ /home/drk/tillage/datasets/human/chip/encode/ENCSR469POZ/summary/ENCFF423FWZ.w5 32 2 mean CHIP:CTCF:tibial nerve female adult (53 years) CHIP ChIP-TF:CTCF/tibial nerve female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2893 0 ENCFF528YPX /home/drk/tillage/datasets/human/chip/encode/ENCSR469WAO/summary/ENCFF528YPX.w5 32 2 mean CHIP:CBX2:A549 CHIP ChIP-TF:CBX2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2894 0 ENCFF294JNU /home/drk/tillage/datasets/human/chip/encode/ENCSR469WII/summary/ENCFF294JNU.w5 32 2 mean CHIP:BMI1:GM12878 CHIP ChIP-TF:BMI1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2895 0 ENCFF202TKU /home/drk/tillage/datasets/human/chip/encode/ENCSR470PLJ/summary/ENCFF202TKU.w5 32 2 mean CHIP:H3K9ac:HUES64 CHIP ChIP-Histone:H3K9ac/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2896 0 ENCFF155KWT /home/drk/tillage/datasets/human/chip/encode/ENCSR472SEY/summary/ENCFF155KWT.w5 32 2 mean CHIP:H3K27me3:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K27me3/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2897 0 ENCFF972TRW /home/drk/tillage/datasets/human/chip/encode/ENCSR472VBD/summary/ENCFF972TRW.w5 32 2 mean CHIP:POLR2A:sigmoid colon male adult (54 years) CHIP ChIP-TF:POLR2A/sigmoid colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2898 0 ENCFF646APT /home/drk/tillage/datasets/human/chip/encode/ENCSR473AQI/summary/ENCFF646APT.w5 32 2 mean CHIP:H3K23ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K23ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2899 0 ENCFF313DOD /home/drk/tillage/datasets/human/chip/encode/ENCSR473PNT/summary/ENCFF313DOD.w5 32 2 mean CHIP:H3K27ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K27ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2900 0 ENCFF182ZBH /home/drk/tillage/datasets/human/chip/encode/ENCSR473SUA/summary/ENCFF182ZBH.w5 32 2 mean CHIP:ESRRA:A549 CHIP ChIP-TF:ESRRA/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2901 0 ENCFF424TNY /home/drk/tillage/datasets/human/chip/encode/ENCSR473TDG/summary/ENCFF424TNY.w5 32 2 mean CHIP:H3K9me2:Karpas-422 CHIP ChIP-Histone:H3K9me2/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2902 0 ENCFF372CGE /home/drk/tillage/datasets/human/chip/encode/ENCSR473ZFG/summary/ENCFF372CGE.w5 32 2 mean CHIP:H3K4me1:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K4me1/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2903 0 ENCFF507TJE /home/drk/tillage/datasets/human/chip/encode/ENCSR474CVP/summary/ENCFF507TJE.w5 32 2 mean CHIP:TRIM28:K562 CHIP ChIP-TF:TRIM28/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2904 0 ENCFF431PNC /home/drk/tillage/datasets/human/chip/encode/ENCSR474DOV/summary/ENCFF431PNC.w5 32 2 mean CHIP:H4K20me1:HCT116 CHIP ChIP-TF:H4K20me1/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2905 0 ENCFF940ZCU /home/drk/tillage/datasets/human/chip/encode/ENCSR474VGQ/summary/ENCFF940ZCU.w5 32 2 mean CHIP:H3K27me3:KMS-11 CHIP ChIP-Histone:H3K27me3/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2906 0 ENCFF697CGU /home/drk/tillage/datasets/human/chip/encode/ENCSR475HRT/summary/ENCFF697CGU.w5 32 2 mean CHIP:H3K4me1:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K4me1/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2907 0 ENCFF392XNK /home/drk/tillage/datasets/human/chip/encode/ENCSR475NLR/summary/ENCFF392XNK.w5 32 2 mean CHIP:H3K27me3:ACC112 CHIP ChIP-Histone:H3K27me3/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2908 0 ENCFF457RHX /home/drk/tillage/datasets/human/chip/encode/ENCSR475SOC/summary/ENCFF457RHX.w5 32 2 mean CHIP:eGFP-ELF1:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ELF1/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2909 0 ENCFF986RVV /home/drk/tillage/datasets/human/chip/encode/ENCSR476BQA/summary/ENCFF986RVV.w5 32 2 mean CHIP:NONO:HepG2 CHIP ChIP-TF:NONO/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2910 0 ENCFF356QHS /home/drk/tillage/datasets/human/chip/encode/ENCSR476FBL/summary/ENCFF356QHS.w5 32 2 mean CHIP:H3K4ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K4ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2911 0 ENCFF141YAA /home/drk/tillage/datasets/human/chip/encode/ENCSR476KTK/summary/ENCFF141YAA.w5 32 2 mean CHIP:H3K36me3:H1-hESC CHIP ChIP-Histone:H3K36me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2912 0 ENCFF402HML /home/drk/tillage/datasets/human/chip/encode/ENCSR477BHF/summary/ENCFF402HML.w5 32 2 mean CHIP:H3K4me3:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K4me3/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2913 0 ENCFF944QYL /home/drk/tillage/datasets/human/chip/encode/ENCSR477OJI/summary/ENCFF944QYL.w5 32 2 mean CHIP:eGFP-ZNF423:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF423/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2914 0 ENCFF860ARQ /home/drk/tillage/datasets/human/chip/encode/ENCSR478BKA/summary/ENCFF860ARQ.w5 32 2 mean CHIP:H3K4me1:esophagus female adult (30 years) CHIP ChIP-Histone:H3K4me1/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2915 0 ENCFF547MCY /home/drk/tillage/datasets/human/chip/encode/ENCSR478UIR/summary/ENCFF547MCY.w5 32 2 mean CHIP:H3K9me3:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K9me3/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2916 0 ENCFF139FPN /home/drk/tillage/datasets/human/chip/encode/ENCSR479BPF/summary/ENCFF139FPN.w5 32 2 mean CHIP:H3K27me3:brain female embryo (120 days) CHIP ChIP-Histone:H3K27me3/brain female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2917 0 ENCFF639TZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR479GJI/summary/ENCFF639TZJ.w5 32 2 mean CHIP:H3K4me1:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K4me1/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2918 0 ENCFF851LAU /home/drk/tillage/datasets/human/chip/encode/ENCSR479GPU/summary/ENCFF851LAU.w5 32 2 mean CHIP:H3K9me3:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K9me3/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2919 0 ENCFF285HWO /home/drk/tillage/datasets/human/chip/encode/ENCSR479HKJ/summary/ENCFF285HWO.w5 32 2 mean CHIP:H3K4me3:GM23248 CHIP ChIP-Histone:H3K4me3/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2920 0 ENCFF484LUS /home/drk/tillage/datasets/human/chip/encode/ENCSR479QAJ/summary/ENCFF484LUS.w5 32 2 mean CHIP:U2AF2:K562 CHIP ChIP-TF:U2AF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2921 0 ENCFF015BTM /home/drk/tillage/datasets/human/chip/encode/ENCSR479YCJ/summary/ENCFF015BTM.w5 32 2 mean CHIP:H3K4me1:thymus female embryo (110 days) CHIP ChIP-Histone:H3K4me1/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2922 0 ENCFF608OBE /home/drk/tillage/datasets/human/chip/encode/ENCSR480LIS/summary/ENCFF608OBE.w5 32 2 mean CHIP:ATF3:liver male adult (32 years) CHIP ChIP-TF:ATF3/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2923 0 ENCFF965PJE /home/drk/tillage/datasets/human/chip/encode/ENCSR480OFK/summary/ENCFF965PJE.w5 32 2 mean CHIP:H3K4me1:heart male embryo (105 days) CHIP ChIP-Histone:H3K4me1/heart male embryo (105 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2924 0 ENCFF676UZG /home/drk/tillage/datasets/human/chip/encode/ENCSR480WMC/summary/ENCFF676UZG.w5 32 2 mean CHIP:H3K4me1:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2925 0 ENCFF859MJW /home/drk/tillage/datasets/human/chip/encode/ENCSR481FEC/summary/ENCFF859MJW.w5 32 2 mean CHIP:eGFP-ZBTB8A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB8A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2926 0 ENCFF107JGL /home/drk/tillage/datasets/human/chip/encode/ENCSR481IYI/summary/ENCFF107JGL.w5 32 2 mean CHIP:H3K36me3:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K36me3/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2927 0 ENCFF648CVA /home/drk/tillage/datasets/human/chip/encode/ENCSR481QER/summary/ENCFF648CVA.w5 32 2 mean CHIP:H3K4me1:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K4me1/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2928 0 ENCFF684BHN /home/drk/tillage/datasets/human/chip/encode/ENCSR481YGZ/summary/ENCFF684BHN.w5 32 2 mean CHIP:H3K4me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2929 0 ENCFF452UOZ /home/drk/tillage/datasets/human/chip/encode/ENCSR481YWD/summary/ENCFF452UOZ.w5 32 2 mean CHIP:SMC3:A549 CHIP ChIP-TF:SMC3/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2930 0 ENCFF667SCC /home/drk/tillage/datasets/human/chip/encode/ENCSR482BBZ/summary/ENCFF667SCC.w5 32 2 mean CHIP:eGFP-GLIS1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-GLIS1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2931 0 ENCFF948WAI /home/drk/tillage/datasets/human/chip/encode/ENCSR482KJD/summary/ENCFF948WAI.w5 32 2 mean CHIP:H3K36me3:trophoblast female embryo (40 weeks) CHIP ChIP-Histone:H3K36me3/trophoblast female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2932 0 ENCFF887GWM /home/drk/tillage/datasets/human/chip/encode/ENCSR482PMN/summary/ENCFF887GWM.w5 32 2 mean CHIP:CTCF:spleen female adult (51 year) CHIP ChIP-TF:CTCF/spleen female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2933 0 ENCFF797UHN /home/drk/tillage/datasets/human/chip/encode/ENCSR482QXO/summary/ENCFF797UHN.w5 32 2 mean CHIP:H3K4me1:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K4me1/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2934 0 ENCFF367WTF /home/drk/tillage/datasets/human/chip/encode/ENCSR482TWQ/summary/ENCFF367WTF.w5 32 2 mean CHIP:RAD51:GM12878 CHIP ChIP-TF:RAD51/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2935 0 ENCFF911MEH /home/drk/tillage/datasets/human/chip/encode/ENCSR483VJQ/summary/ENCFF911MEH.w5 32 2 mean CHIP:eGFP-ZNF662:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF662/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2936 0 ENCFF115FSX /home/drk/tillage/datasets/human/chip/encode/ENCSR484DDO/summary/ENCFF115FSX.w5 32 2 mean CHIP:CTCF:body of pancreas female adult (53 years) CHIP ChIP-TF:CTCF/body of pancreas female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2937 0 ENCFF246UAN /home/drk/tillage/datasets/human/chip/encode/ENCSR484MFB/summary/ENCFF246UAN.w5 32 2 mean CHIP:H3K9me2:hepatocyte originated from H9 CHIP ChIP-Histone:H3K9me2/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2938 0 ENCFF324STM /home/drk/tillage/datasets/human/chip/encode/ENCSR484PTR/summary/ENCFF324STM.w5 32 2 mean CHIP:H3K79me2:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K79me2/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2939 0 ENCFF390MQD /home/drk/tillage/datasets/human/chip/encode/ENCSR485BEB/summary/ENCFF390MQD.w5 32 2 mean CHIP:POLR2A:thyroid gland female adult (53 years) CHIP ChIP-TF:POLR2A/thyroid gland female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2940 0 ENCFF351YKP /home/drk/tillage/datasets/human/chip/encode/ENCSR485FST/summary/ENCFF351YKP.w5 32 2 mean CHIP:H3K9ac:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K9ac/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2941 0 ENCFF531GSL /home/drk/tillage/datasets/human/chip/encode/ENCSR485OSV/summary/ENCFF531GSL.w5 32 2 mean CHIP:H2AFZ:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H2AFZ/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2942 0 ENCFF041PBD /home/drk/tillage/datasets/human/chip/encode/ENCSR485OYR/summary/ENCFF041PBD.w5 32 2 mean CHIP:3xFLAG-ZBTB25:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZBTB25/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2943 0 ENCFF079DVI /home/drk/tillage/datasets/human/chip/encode/ENCSR485URZ/summary/ENCFF079DVI.w5 32 2 mean CHIP:H3K27me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2944 0 ENCFF603SAT /home/drk/tillage/datasets/human/chip/encode/ENCSR485ZKB/summary/ENCFF603SAT.w5 32 2 mean CHIP:H3K27me3:UCSF-4 CHIP ChIP-Histone:H3K27me3/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2945 0 ENCFF234NTT /home/drk/tillage/datasets/human/chip/encode/ENCSR486GER/summary/ENCFF234NTT.w5 32 2 mean CHIP:H3K4me1:Parathyroid adenoma male adult (65 years) CHIP ChIP-Histone:H3K4me1/Parathyroid adenoma male adult (65 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2946 0 ENCFF894IHE /home/drk/tillage/datasets/human/chip/encode/ENCSR486GWT/summary/ENCFF894IHE.w5 32 2 mean CHIP:H3K4me2:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K4me2/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2947 0 ENCFF241ISR /home/drk/tillage/datasets/human/chip/encode/ENCSR486IFJ/summary/ENCFF241ISR.w5 32 2 mean CHIP:ESRRA:K562 CHIP ChIP-TF:ESRRA/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2948 0 ENCFF418JEV /home/drk/tillage/datasets/human/chip/encode/ENCSR486NDF/summary/ENCFF418JEV.w5 32 2 mean CHIP:H3K27me3:pancreas female adult (30 years) CHIP ChIP-Histone:H3K27me3/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2949 0 ENCFF917VNM /home/drk/tillage/datasets/human/chip/encode/ENCSR486PWP/summary/ENCFF917VNM.w5 32 2 mean CHIP:H3K79me2:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K79me2/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2950 0 ENCFF710EXS /home/drk/tillage/datasets/human/chip/encode/ENCSR486QMV/summary/ENCFF710EXS.w5 32 2 mean CHIP:H3K4me3:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K4me3/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2951 0 ENCFF996IOS /home/drk/tillage/datasets/human/chip/encode/ENCSR486ZKB/summary/ENCFF996IOS.w5 32 2 mean CHIP:H3K36me3:neuron originated from H9 CHIP ChIP-Histone:H3K36me3/neuron originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2952 0 ENCFF982AQL /home/drk/tillage/datasets/human/chip/encode/ENCSR487ASM/summary/ENCFF982AQL.w5 32 2 mean CHIP:SMARCA5:MCF-7 CHIP ChIP-TF:SMARCA5/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2953 0 ENCFF259CAK /home/drk/tillage/datasets/human/chip/encode/ENCSR487BEW/summary/ENCFF259CAK.w5 32 2 mean CHIP:H3K4me3:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K4me3/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2954 0 ENCFF702EUF /home/drk/tillage/datasets/human/chip/encode/ENCSR487CPI/summary/ENCFF702EUF.w5 32 2 mean CHIP:3xFLAG-ZFP64:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZFP64/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2955 0 ENCFF962KZP /home/drk/tillage/datasets/human/chip/encode/ENCSR487LUQ/summary/ENCFF962KZP.w5 32 2 mean CHIP:PHF8:HepG2 CHIP ChIP-TF:PHF8/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2956 0 ENCFF435UFG /home/drk/tillage/datasets/human/chip/encode/ENCSR488EES/summary/ENCFF435UFG.w5 32 2 mean CHIP:NFE2L2:HepG2 CHIP ChIP-TF:NFE2L2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2957 0 ENCFF973WVY /home/drk/tillage/datasets/human/chip/encode/ENCSR489DUV/summary/ENCFF973WVY.w5 32 2 mean CHIP:H3K4me1:right lobe of liver female adult (53 years) CHIP ChIP-Histone:H3K4me1/right lobe of liver female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2958 0 ENCFF194SCU /home/drk/tillage/datasets/human/chip/encode/ENCSR489RQV/summary/ENCFF194SCU.w5 32 2 mean CHIP:H3K9me3:liver male adult (78 years) CHIP ChIP-Histone:H3K9me3/liver male adult (78 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2959 0 ENCFF043ERH /home/drk/tillage/datasets/human/chip/encode/ENCSR489TBW/summary/ENCFF043ERH.w5 32 2 mean CHIP:H3K9me3:peripheral blood mononuclear cell male adult (28 years) CHIP ChIP-Histone:H3K9me3/peripheral blood mononuclear cell male adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2960 0 ENCFF290ETW /home/drk/tillage/datasets/human/chip/encode/ENCSR489ZLL/summary/ENCFF290ETW.w5 32 2 mean CHIP:H3K4me3:stomach female adult (53 years) CHIP ChIP-Histone:H3K4me3/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2961 0 ENCFF649LJJ /home/drk/tillage/datasets/human/chip/encode/ENCSR490LWA/summary/ENCFF649LJJ.w5 32 2 mean CHIP:eGFP-CEBPG:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-CEBPG/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2962 0 ENCFF620UYN /home/drk/tillage/datasets/human/chip/encode/ENCSR490YCL/summary/ENCFF620UYN.w5 32 2 mean CHIP:H3K4me1:spleen male adult (34 years) CHIP ChIP-Histone:H3K4me1/spleen male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2963 0 ENCFF668AMF /home/drk/tillage/datasets/human/chip/encode/ENCSR491CCY/summary/ENCFF668AMF.w5 32 2 mean CHIP:H2BK15ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2BK15ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2964 0 ENCFF835KBE /home/drk/tillage/datasets/human/chip/encode/ENCSR491EBY/summary/ENCFF835KBE.w5 32 2 mean CHIP:ARID2:K562 CHIP ChIP-TF:ARID2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2965 0 ENCFF209EBN /home/drk/tillage/datasets/human/chip/encode/ENCSR491PTJ/summary/ENCFF209EBN.w5 32 2 mean CHIP:POLR2AphosphoS5:suprapubic skin female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/suprapubic skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2966 0 ENCFF096QYY /home/drk/tillage/datasets/human/chip/encode/ENCSR491VZZ/summary/ENCFF096QYY.w5 32 2 mean CHIP:H3K23ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K23ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2967 0 ENCFF961QGV /home/drk/tillage/datasets/human/chip/encode/ENCSR491WAP/summary/ENCFF961QGV.w5 32 2 mean CHIP:H2AFZ:PC-9 CHIP ChIP-TF:H2AFZ/PC-9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2968 0 ENCFF231QIO /home/drk/tillage/datasets/human/chip/encode/ENCSR492DBQ/summary/ENCFF231QIO.w5 32 2 mean CHIP:H3K9ac:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K9ac/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2969 0 ENCFF355YUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR492LTS/summary/ENCFF355YUJ.w5 32 2 mean CHIP:BCLAF1:K562 CHIP ChIP-TF:BCLAF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2970 0 ENCFF592MXT /home/drk/tillage/datasets/human/chip/encode/ENCSR492PXH/summary/ENCFF592MXT.w5 32 2 mean CHIP:H3K27ac:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K27ac/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2971 0 ENCFF198JTS /home/drk/tillage/datasets/human/chip/encode/ENCSR492ZIW/summary/ENCFF198JTS.w5 32 2 mean CHIP:CTCF:thyroid gland male adult (54 years) CHIP ChIP-TF:CTCF/thyroid gland male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2972 0 ENCFF703ZRL /home/drk/tillage/datasets/human/chip/encode/ENCSR493APD/summary/ENCFF703ZRL.w5 32 2 mean CHIP:CTCF:ovary female adult (53 years) CHIP ChIP-TF:CTCF/ovary female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2973 0 ENCFF720TUF /home/drk/tillage/datasets/human/chip/encode/ENCSR493FIV/summary/ENCFF720TUF.w5 32 2 mean CHIP:H3K79me2:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K79me2/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2974 0 ENCFF275KBS /home/drk/tillage/datasets/human/chip/encode/ENCSR493NBY/summary/ENCFF275KBS.w5 32 2 mean CHIP:H3K4me1:MCF-7 CHIP ChIP-Histone:H3K4me1/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2975 0 ENCFF413MAJ /home/drk/tillage/datasets/human/chip/encode/ENCSR494LJG/summary/ENCFF413MAJ.w5 32 2 mean CHIP:H3K4me3:SU-DHL-6 CHIP ChIP-Histone:H3K4me3/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2976 0 ENCFF043ZYE /home/drk/tillage/datasets/human/chip/encode/ENCSR494MDB/summary/ENCFF043ZYE.w5 32 2 mean CHIP:H3K27ac:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K27ac/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2977 0 ENCFF006FDD /home/drk/tillage/datasets/human/chip/encode/ENCSR494OPF/summary/ENCFF006FDD.w5 32 2 mean CHIP:H3K27me3:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K27me3/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2978 0 ENCFF787EIU /home/drk/tillage/datasets/human/chip/encode/ENCSR494OXB/summary/ENCFF787EIU.w5 32 2 mean CHIP:H3K27me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K27me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2979 0 ENCFF153GCI /home/drk/tillage/datasets/human/chip/encode/ENCSR494PWZ/summary/ENCFF153GCI.w5 32 2 mean CHIP:ZC3H8:K562 CHIP ChIP-TF:ZC3H8/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2980 0 ENCFF458LDQ /home/drk/tillage/datasets/human/chip/encode/ENCSR494TDU/summary/ENCFF458LDQ.w5 32 2 mean CHIP:NRF1:K562 CHIP ChIP-TF:NRF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2981 0 ENCFF686GDH /home/drk/tillage/datasets/human/chip/encode/ENCSR494TNM/summary/ENCFF686GDH.w5 32 2 mean CHIP:CTCF:testis male adult (37 years) CHIP ChIP-TF:CTCF/testis male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2982 0 ENCFF532SLM /home/drk/tillage/datasets/human/chip/encode/ENCSR494UQJ/summary/ENCFF532SLM.w5 32 2 mean CHIP:NR3C1:K562 CHIP ChIP-TF:NR3C1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2983 0 ENCFF268YQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR495GRN/summary/ENCFF268YQQ.w5 32 2 mean CHIP:H3K9me3:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K9me3/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2984 0 ENCFF683KUC /home/drk/tillage/datasets/human/chip/encode/ENCSR495OEG/summary/ENCFF683KUC.w5 32 2 mean CHIP:H3K27me3:trophoblast female embryo (40 weeks) CHIP ChIP-Histone:H3K27me3/trophoblast female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2985 0 ENCFF591LCS /home/drk/tillage/datasets/human/chip/encode/ENCSR496DCY/summary/ENCFF591LCS.w5 32 2 mean CHIP:H3K36me3:H1-hESC CHIP ChIP-Histone:H3K36me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2986 0 ENCFF988KQC /home/drk/tillage/datasets/human/chip/encode/ENCSR497IAS/summary/ENCFF988KQC.w5 32 2 mean CHIP:eGFP-ZNF747:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF747/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2987 0 ENCFF479OGO /home/drk/tillage/datasets/human/chip/encode/ENCSR497JLX/summary/ENCFF479OGO.w5 32 2 mean CHIP:3xFLAG-TEAD1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-TEAD1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2988 0 ENCFF448DIU /home/drk/tillage/datasets/human/chip/encode/ENCSR497UIB/summary/ENCFF448DIU.w5 32 2 mean CHIP:H3K36me3:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K36me3/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2989 0 ENCFF027NWG /home/drk/tillage/datasets/human/chip/encode/ENCSR497VFH/summary/ENCFF027NWG.w5 32 2 mean CHIP:ZNF639:K562 CHIP ChIP-TF:ZNF639/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2990 0 ENCFF042DUU /home/drk/tillage/datasets/human/chip/encode/ENCSR498PMM/summary/ENCFF042DUU.w5 32 2 mean CHIP:H3K9me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K9me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2991 0 ENCFF689XXW /home/drk/tillage/datasets/human/chip/encode/ENCSR498ZRC/summary/ENCFF689XXW.w5 32 2 mean CHIP:H3K27ac:placenta female embryo (113 days) CHIP ChIP-Histone:H3K27ac/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2992 0 ENCFF456EBZ /home/drk/tillage/datasets/human/chip/encode/ENCSR499CAZ/summary/ENCFF456EBZ.w5 32 2 mean CHIP:H3K14ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K14ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2993 0 ENCFF453PFK /home/drk/tillage/datasets/human/chip/encode/ENCSR499FXI/summary/ENCFF453PFK.w5 32 2 mean CHIP:H3K36me3:prostate male adult (54 years) CHIP ChIP-Histone:H3K36me3/prostate male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2994 0 ENCFF015PTE /home/drk/tillage/datasets/human/chip/encode/ENCSR499IIR/summary/ENCFF015PTE.w5 32 2 mean CHIP:H3K27ac:chorion female embryo (40 weeks) CHIP ChIP-Histone:H3K27ac/chorion female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2995 0 ENCFF471AHV /home/drk/tillage/datasets/human/chip/encode/ENCSR499RMZ/summary/ENCFF471AHV.w5 32 2 mean CHIP:H2AFZ:KMS-11 CHIP ChIP-TF:H2AFZ/KMS-11 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2996 0 ENCFF675UPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR499WAQ/summary/ENCFF675UPZ.w5 32 2 mean CHIP:H3K36me3:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K36me3/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2997 0 ENCFF910JMH /home/drk/tillage/datasets/human/chip/encode/ENCSR500GXT/summary/ENCFF910JMH.w5 32 2 mean CHIP:H3K4me3:lung male child (3 years) CHIP ChIP-Histone:H3K4me3/lung male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2998 0 ENCFF409IGH /home/drk/tillage/datasets/human/chip/encode/ENCSR500WXT/summary/ENCFF409IGH.w5 32 2 mean CHIP:3xFLAG-RARA:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RARA/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +2999 0 ENCFF467VQP /home/drk/tillage/datasets/human/chip/encode/ENCSR500ZGF/summary/ENCFF467VQP.w5 32 2 mean CHIP:H3K36me3:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K36me3/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3000 0 ENCFF861VZC /home/drk/tillage/datasets/human/chip/encode/ENCSR501DKS/summary/ENCFF861VZC.w5 32 2 mean CHIP:TCF7:GM12878 CHIP ChIP-TF:TCF7/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3001 0 ENCFF308DJX /home/drk/tillage/datasets/human/chip/encode/ENCSR501FTL/summary/ENCFF308DJX.w5 32 2 mean CHIP:H3K4me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K4me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3002 0 ENCFF712CJP /home/drk/tillage/datasets/human/chip/encode/ENCSR501JET/summary/ENCFF712CJP.w5 32 2 mean CHIP:H3K4me3:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K4me3/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3003 0 ENCFF384VWO /home/drk/tillage/datasets/human/chip/encode/ENCSR501LEH/summary/ENCFF384VWO.w5 32 2 mean CHIP:EP300:breast epithelium male adult (54 years) CHIP ChIP-TF:EP300/breast epithelium male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3004 0 ENCFF958WAC /home/drk/tillage/datasets/human/chip/encode/ENCSR501NSC/summary/ENCFF958WAC.w5 32 2 mean CHIP:eGFP-ZSCAN26:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN26/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3005 0 ENCFF120NLZ /home/drk/tillage/datasets/human/chip/encode/ENCSR502GAX/summary/ENCFF120NLZ.w5 32 2 mean CHIP:3xFLAG-ZNF652:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF652/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3006 0 ENCFF486BJL /home/drk/tillage/datasets/human/chip/encode/ENCSR502IWF/summary/ENCFF486BJL.w5 32 2 mean CHIP:H2BK120ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2BK120ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3007 0 ENCFF745QJA /home/drk/tillage/datasets/human/chip/encode/ENCSR502KPJ/summary/ENCFF745QJA.w5 32 2 mean CHIP:eGFP-ZNF843:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF843/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3008 0 ENCFF814THY /home/drk/tillage/datasets/human/chip/encode/ENCSR502NRF/summary/ENCFF814THY.w5 32 2 mean CHIP:ELF1:MCF-7 CHIP ChIP-TF:ELF1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3009 0 ENCFF036DKA /home/drk/tillage/datasets/human/chip/encode/ENCSR502OEK/summary/ENCFF036DKA.w5 32 2 mean CHIP:ELF1:K562 CHIP ChIP-TF:ELF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3010 0 ENCFF250GOA /home/drk/tillage/datasets/human/chip/encode/ENCSR503DPC/summary/ENCFF250GOA.w5 32 2 mean CHIP:eGFP-ZNF513:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF513/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3011 0 ENCFF168KEG /home/drk/tillage/datasets/human/chip/encode/ENCSR503GVO/summary/ENCFF168KEG.w5 32 2 mean CHIP:ZFX:HCT116 CHIP ChIP-TF:ZFX/HCT116 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3012 0 ENCFF406CAU /home/drk/tillage/datasets/human/chip/encode/ENCSR503UUB/summary/ENCFF406CAU.w5 32 2 mean CHIP:H3K9me3:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K9me3/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3013 0 ENCFF067FRC /home/drk/tillage/datasets/human/chip/encode/ENCSR503VTG/summary/ENCFF067FRC.w5 32 2 mean CHIP:ZNF24:MCF-7 CHIP ChIP-TF:ZNF24/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3014 0 ENCFF930UVO /home/drk/tillage/datasets/human/chip/encode/ENCSR503YOF/summary/ENCFF930UVO.w5 32 2 mean CHIP:H3K27me3:heart left ventricle male adult (34 years) CHIP ChIP-Histone:H3K27me3/heart left ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3015 0 ENCFF138QDA /home/drk/tillage/datasets/human/chip/encode/ENCSR504SKC/summary/ENCFF138QDA.w5 32 2 mean CHIP:H3K4me1:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K4me1/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3016 0 ENCFF726VUP /home/drk/tillage/datasets/human/chip/encode/ENCSR504VDV/summary/ENCFF726VUP.w5 32 2 mean CHIP:eGFP-ZNF654:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF654/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3017 0 ENCFF424RJL /home/drk/tillage/datasets/human/chip/encode/ENCSR505JQC/summary/ENCFF424RJL.w5 32 2 mean CHIP:H3K4me3:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K4me3/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3018 0 ENCFF724FPR /home/drk/tillage/datasets/human/chip/encode/ENCSR505NMN/summary/ENCFF724FPR.w5 32 2 mean CHIP:eGFP-E2F4:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-E2F4/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3019 0 ENCFF787RFT /home/drk/tillage/datasets/human/chip/encode/ENCSR505OPZ/summary/ENCFF787RFT.w5 32 2 mean CHIP:H3K27ac:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K27ac/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3020 0 ENCFF989ANO /home/drk/tillage/datasets/human/chip/encode/ENCSR505THJ/summary/ENCFF989ANO.w5 32 2 mean CHIP:H3K36me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3021 0 ENCFF566GIR /home/drk/tillage/datasets/human/chip/encode/ENCSR506HXN/summary/ENCFF566GIR.w5 32 2 mean CHIP:TRIM22:HepG2 CHIP ChIP-TF:TRIM22/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3022 0 ENCFF095TJV /home/drk/tillage/datasets/human/chip/encode/ENCSR506KWJ/summary/ENCFF095TJV.w5 32 2 mean CHIP:XRCC5:K562 CHIP ChIP-TF:XRCC5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3023 0 ENCFF916XFM /home/drk/tillage/datasets/human/chip/encode/ENCSR506QLL/summary/ENCFF916XFM.w5 32 2 mean CHIP:H3K4me1:trophoblast female embryo (40 weeks) CHIP ChIP-Histone:H3K4me1/trophoblast female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3024 0 ENCFF235OKK /home/drk/tillage/datasets/human/chip/encode/ENCSR507SRD/summary/ENCFF235OKK.w5 32 2 mean CHIP:H3K27ac:trophoblast female embryo (20 weeks) CHIP ChIP-Histone:H3K27ac/trophoblast female embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3025 0 ENCFF606PZU /home/drk/tillage/datasets/human/chip/encode/ENCSR507UDH/summary/ENCFF606PZU.w5 32 2 mean CHIP:H3K27ac:hepatocyte originated from H9 CHIP ChIP-Histone:H3K27ac/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3026 0 ENCFF523BNY /home/drk/tillage/datasets/human/chip/encode/ENCSR508DQA/summary/ENCFF523BNY.w5 32 2 mean CHIP:FOXK2:K562 CHIP ChIP-TF:FOXK2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3027 0 ENCFF971PWH /home/drk/tillage/datasets/human/chip/encode/ENCSR508LMH/summary/ENCFF971PWH.w5 32 2 mean CHIP:ASH2L:HepG2 CHIP ChIP-TF:ASH2L/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3028 0 ENCFF515MXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR508UPW/summary/ENCFF515MXQ.w5 32 2 mean CHIP:H3K4me3:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K4me3/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3029 0 ENCFF441EEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR509DOK/summary/ENCFF441EEQ.w5 32 2 mean CHIP:PPP1R10:MCF-7 CHIP ChIP-TF:PPP1R10/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3030 0 ENCFF793IOP /home/drk/tillage/datasets/human/chip/encode/ENCSR509FWH/summary/ENCFF793IOP.w5 32 2 mean CHIP:DPF2:GM12878 CHIP ChIP-TF:DPF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3031 0 ENCFF060TPE /home/drk/tillage/datasets/human/chip/encode/ENCSR509MHV/summary/ENCFF060TPE.w5 32 2 mean CHIP:H4K91ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H4K91ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3032 0 ENCFF435XKF /home/drk/tillage/datasets/human/chip/encode/ENCSR510NXV/summary/ENCFF435XKF.w5 32 2 mean CHIP:H3K4me3:gastroesophageal sphincter female adult (53 years) CHIP ChIP-Histone:H3K4me3/gastroesophageal sphincter female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3033 0 ENCFF911RRU /home/drk/tillage/datasets/human/chip/encode/ENCSR511CUH/summary/ENCFF911RRU.w5 32 2 mean CHIP:EZH2:neural cell CHIP ChIP-TF:EZH2/neural cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3034 0 ENCFF886ZHW /home/drk/tillage/datasets/human/chip/encode/ENCSR511GOF/summary/ENCFF886ZHW.w5 32 2 mean CHIP:H3K4me1:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K4me1/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3035 0 ENCFF876SCB /home/drk/tillage/datasets/human/chip/encode/ENCSR511OIE/summary/ENCFF876SCB.w5 32 2 mean CHIP:H3K27me3:SU-DHL-6 CHIP ChIP-Histone:H3K27me3/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3036 0 ENCFF838CFO /home/drk/tillage/datasets/human/chip/encode/ENCSR512BHQ/summary/ENCFF838CFO.w5 32 2 mean CHIP:H3K9me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K9me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3037 0 ENCFF568MCF /home/drk/tillage/datasets/human/chip/encode/ENCSR512CSM/summary/ENCFF568MCF.w5 32 2 mean CHIP:H3K4me1:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K4me1/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3038 0 ENCFF259GQW /home/drk/tillage/datasets/human/chip/encode/ENCSR512GFQ/summary/ENCFF259GQW.w5 32 2 mean CHIP:H3K27me3:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3039 0 ENCFF605PQC /home/drk/tillage/datasets/human/chip/encode/ENCSR512NLO/summary/ENCFF605PQC.w5 32 2 mean CHIP:MNT:K562 CHIP ChIP-TF:MNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3040 0 ENCFF298GHF /home/drk/tillage/datasets/human/chip/encode/ENCSR513KNS/summary/ENCFF298GHF.w5 32 2 mean CHIP:H3K4me2:PC-9 CHIP ChIP-Histone:H3K4me2/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3041 0 ENCFF129XQV /home/drk/tillage/datasets/human/chip/encode/ENCSR513MGG/summary/ENCFF129XQV.w5 32 2 mean CHIP:eGFP-ZNF302:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF302/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3042 0 ENCFF602MKK /home/drk/tillage/datasets/human/chip/encode/ENCSR513NFT/summary/ENCFF602MKK.w5 32 2 mean CHIP:H3K4me1:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K4me1/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3043 0 ENCFF295DVX /home/drk/tillage/datasets/human/chip/encode/ENCSR513UQG/summary/ENCFF295DVX.w5 32 2 mean CHIP:USF2:IMR-90 CHIP ChIP-TF:USF2/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3044 0 ENCFF070LJS /home/drk/tillage/datasets/human/chip/encode/ENCSR513XQX/summary/ENCFF070LJS.w5 32 2 mean CHIP:SIN3A:A549 CHIP ChIP-TF:SIN3A/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3045 0 ENCFF273QJO /home/drk/tillage/datasets/human/chip/encode/ENCSR514DNQ/summary/ENCFF273QJO.w5 32 2 mean CHIP:H3K4me1:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K4me1/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3046 0 ENCFF548MPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR514EOE/summary/ENCFF548MPZ.w5 32 2 mean CHIP:BRD4:HepG2 CHIP ChIP-TF:BRD4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3047 0 ENCFF654LQC /home/drk/tillage/datasets/human/chip/encode/ENCSR514VAY/summary/ENCFF654LQC.w5 32 2 mean CHIP:HCFC1:GM12878 CHIP ChIP-TF:HCFC1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3048 0 ENCFF652WYR /home/drk/tillage/datasets/human/chip/encode/ENCSR514VYD/summary/ENCFF652WYR.w5 32 2 mean CHIP:NR2F1:GM12878 CHIP ChIP-TF:NR2F1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3049 0 ENCFF331CWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR515LRI/summary/ENCFF331CWJ.w5 32 2 mean CHIP:CTCF:suprapubic skin female adult (53 years) CHIP ChIP-TF:CTCF/suprapubic skin female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3050 0 ENCFF034PSU /home/drk/tillage/datasets/human/chip/encode/ENCSR515PKY/summary/ENCFF034PSU.w5 32 2 mean CHIP:H3K4me3:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K4me3/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3051 0 ENCFF245JEE /home/drk/tillage/datasets/human/chip/encode/ENCSR516HUP/summary/ENCFF245JEE.w5 32 2 mean CHIP:ZBTB33:liver male adult (32 years) CHIP ChIP-TF:ZBTB33/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3052 0 ENCFF145SYS /home/drk/tillage/datasets/human/chip/encode/ENCSR516KSY/summary/ENCFF145SYS.w5 32 2 mean CHIP:H3K9me3:H9 genetically modified using stable transfection CHIP ChIP-Histone:H3K9me3/H9 genetically modified using stable transfection ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3053 0 ENCFF223XXK /home/drk/tillage/datasets/human/chip/encode/ENCSR516VQK/summary/ENCFF223XXK.w5 32 2 mean CHIP:eGFP-ZNF174:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF174/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3054 0 ENCFF724NPC /home/drk/tillage/datasets/human/chip/encode/ENCSR517CFV/summary/ENCFF724NPC.w5 32 2 mean CHIP:H3K27me3:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K27me3/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3055 0 ENCFF598ORF /home/drk/tillage/datasets/human/chip/encode/ENCSR517DDU/summary/ENCFF598ORF.w5 32 2 mean CHIP:eGFP-ZNF48:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF48/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3056 0 ENCFF410VLN /home/drk/tillage/datasets/human/chip/encode/ENCSR517FVL/summary/ENCFF410VLN.w5 32 2 mean CHIP:POLR2A:body of pancreas male adult (54 years) CHIP ChIP-TF:POLR2A/body of pancreas male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3057 0 ENCFF634ZZA /home/drk/tillage/datasets/human/chip/encode/ENCSR517SMA/summary/ENCFF634ZZA.w5 32 2 mean CHIP:H3K27me3:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27me3/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3058 0 ENCFF641YFP /home/drk/tillage/datasets/human/chip/encode/ENCSR518LDN/summary/ENCFF641YFP.w5 32 2 mean CHIP:H3K79me2:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K79me2/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3059 0 ENCFF441AMP /home/drk/tillage/datasets/human/chip/encode/ENCSR518WPL/summary/ENCFF441AMP.w5 32 2 mean CHIP:NR2F6:HepG2 CHIP ChIP-TF:NR2F6/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3060 0 ENCFF039JTK /home/drk/tillage/datasets/human/chip/encode/ENCSR519CFV/summary/ENCFF039JTK.w5 32 2 mean CHIP:H3K27ac:aorta male adult (34 years) CHIP ChIP-Histone:H3K27ac/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3061 0 ENCFF126YPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR519QAA/summary/ENCFF126YPQ.w5 32 2 mean CHIP:HNRNPK:HepG2 CHIP ChIP-TF:HNRNPK/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3062 0 ENCFF448GRO /home/drk/tillage/datasets/human/chip/encode/ENCSR519SOC/summary/ENCFF448GRO.w5 32 2 mean CHIP:H3K36me3:natural killer cell male adult (21 year) CHIP ChIP-Histone:H3K36me3/natural killer cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3063 0 ENCFF053QSU /home/drk/tillage/datasets/human/chip/encode/ENCSR519WMW/summary/ENCFF053QSU.w5 32 2 mean CHIP:SMARCC2:K562 CHIP ChIP-TF:SMARCC2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3064 0 ENCFF579HBN /home/drk/tillage/datasets/human/chip/encode/ENCSR519WQH/summary/ENCFF579HBN.w5 32 2 mean CHIP:H3K27me3:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K27me3/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3065 0 ENCFF366LIL /home/drk/tillage/datasets/human/chip/encode/ENCSR520BIM/summary/ENCFF366LIL.w5 32 2 mean CHIP:H3K27ac:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K27ac/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3066 0 ENCFF669BCZ /home/drk/tillage/datasets/human/chip/encode/ENCSR520BUX/summary/ENCFF669BCZ.w5 32 2 mean CHIP:H3K4me3:liver male adult (78 years) CHIP ChIP-Histone:H3K4me3/liver male adult (78 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3067 0 ENCFF876BRQ /home/drk/tillage/datasets/human/chip/encode/ENCSR520VTO/summary/ENCFF876BRQ.w5 32 2 mean CHIP:EZH2:OCI-LY1 CHIP ChIP-TF:EZH2/OCI-LY1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3068 0 ENCFF039IBU /home/drk/tillage/datasets/human/chip/encode/ENCSR521AIV/summary/ENCFF039IBU.w5 32 2 mean CHIP:H3K9ac:KMS-11 CHIP ChIP-Histone:H3K9ac/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3069 0 ENCFF024XDW /home/drk/tillage/datasets/human/chip/encode/ENCSR521FND/summary/ENCFF024XDW.w5 32 2 mean CHIP:H3K4me1:mammary epithelial cell female adult (18 years) CHIP ChIP-Histone:H3K4me1/mammary epithelial cell female adult (18 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3070 0 ENCFF191NWQ /home/drk/tillage/datasets/human/chip/encode/ENCSR521GRK/summary/ENCFF191NWQ.w5 32 2 mean CHIP:H3K9me2:PC-9 CHIP ChIP-Histone:H3K9me2/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3071 0 ENCFF919WRR /home/drk/tillage/datasets/human/chip/encode/ENCSR521IID/summary/ENCFF919WRR.w5 32 2 mean CHIP:MAX:liver male adult (32 years) CHIP ChIP-TF:MAX/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3072 0 ENCFF399QFV /home/drk/tillage/datasets/human/chip/encode/ENCSR521IZK/summary/ENCFF399QFV.w5 32 2 mean CHIP:H3K4me1:A673 CHIP ChIP-Histone:H3K4me1/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3073 0 ENCFF814WEL /home/drk/tillage/datasets/human/chip/encode/ENCSR522LDJ/summary/ENCFF814WEL.w5 32 2 mean CHIP:HDGF:HEK293T CHIP ChIP-TF:HDGF/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3074 0 ENCFF776VSV /home/drk/tillage/datasets/human/chip/encode/ENCSR523BMU/summary/ENCFF776VSV.w5 32 2 mean CHIP:H3K4me1:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K4me1/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3075 0 ENCFF870XFG /home/drk/tillage/datasets/human/chip/encode/ENCSR523ENE/summary/ENCFF870XFG.w5 32 2 mean CHIP:H2BK12ac:IMR-90 CHIP ChIP-TF:H2BK12ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3076 0 ENCFF179LIQ /home/drk/tillage/datasets/human/chip/encode/ENCSR523JCB/summary/ENCFF179LIQ.w5 32 2 mean CHIP:H3K36me3:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K36me3/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3077 0 ENCFF015EQK /home/drk/tillage/datasets/human/chip/encode/ENCSR523XCR/summary/ENCFF015EQK.w5 32 2 mean CHIP:RNF2:HepG2 CHIP ChIP-TF:RNF2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3078 0 ENCFF715NFE /home/drk/tillage/datasets/human/chip/encode/ENCSR524BUE/summary/ENCFF715NFE.w5 32 2 mean CHIP:RAD51:K562 CHIP ChIP-TF:RAD51/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3079 0 ENCFF616MCB /home/drk/tillage/datasets/human/chip/encode/ENCSR524RIH/summary/ENCFF616MCB.w5 32 2 mean CHIP:H3K9me3:neutrophil CHIP ChIP-Histone:H3K9me3/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3080 0 ENCFF202DBT /home/drk/tillage/datasets/human/chip/encode/ENCSR525XER/summary/ENCFF202DBT.w5 32 2 mean CHIP:H3K9me3:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K9me3/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3081 0 ENCFF505XLJ /home/drk/tillage/datasets/human/chip/encode/ENCSR525YFS/summary/ENCFF505XLJ.w5 32 2 mean CHIP:ZBTB40:HepG2 CHIP ChIP-TF:ZBTB40/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3082 0 ENCFF250AKU /home/drk/tillage/datasets/human/chip/encode/ENCSR526NKM/summary/ENCFF250AKU.w5 32 2 mean CHIP:H2AFZ:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2AFZ/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3083 0 ENCFF462QER /home/drk/tillage/datasets/human/chip/encode/ENCSR526RGE/summary/ENCFF462QER.w5 32 2 mean CHIP:H3K27ac:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K27ac/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3084 0 ENCFF925BCL /home/drk/tillage/datasets/human/chip/encode/ENCSR527BFF/summary/ENCFF925BCL.w5 32 2 mean CHIP:H3K27me3:stomach male adult (34 years) CHIP ChIP-Histone:H3K27me3/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3085 0 ENCFF322CKA /home/drk/tillage/datasets/human/chip/encode/ENCSR528PSI/summary/ENCFF322CKA.w5 32 2 mean CHIP:3xFLAG-HLF:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HLF/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3086 0 ENCFF811YIS /home/drk/tillage/datasets/human/chip/encode/ENCSR528QDT/summary/ENCFF811YIS.w5 32 2 mean CHIP:H3K4me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K4me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3087 0 ENCFF141YEU /home/drk/tillage/datasets/human/chip/encode/ENCSR528UBJ/summary/ENCFF141YEU.w5 32 2 mean CHIP:EP300:breast epithelium female adult (51 year) CHIP ChIP-TF:EP300/breast epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3088 0 ENCFF562EMK /home/drk/tillage/datasets/human/chip/encode/ENCSR529ECZ/summary/ENCFF562EMK.w5 32 2 mean CHIP:H3K9me3:luminal epithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K9me3/luminal epithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3089 0 ENCFF719YDE /home/drk/tillage/datasets/human/chip/encode/ENCSR529JYA/summary/ENCFF719YDE.w5 32 2 mean CHIP:HCFC1:HepG2 CHIP ChIP-TF:HCFC1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3090 0 ENCFF808NPC /home/drk/tillage/datasets/human/chip/encode/ENCSR530LYV/summary/ENCFF808NPC.w5 32 2 mean CHIP:H3K36me3:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K36me3/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3091 0 ENCFF194DSG /home/drk/tillage/datasets/human/chip/encode/ENCSR530XQI/summary/ENCFF194DSG.w5 32 2 mean CHIP:L3MBTL2:K562 CHIP ChIP-TF:L3MBTL2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3092 0 ENCFF039CCR /home/drk/tillage/datasets/human/chip/encode/ENCSR531QHM/summary/ENCFF039CCR.w5 32 2 mean CHIP:H3K9ac:neural cell CHIP ChIP-Histone:H3K9ac/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3093 0 ENCFF914BGC /home/drk/tillage/datasets/human/chip/encode/ENCSR531VIJ/summary/ENCFF914BGC.w5 32 2 mean CHIP:3xFLAG-MIER3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MIER3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3094 0 ENCFF413LVA /home/drk/tillage/datasets/human/chip/encode/ENCSR532EMP/summary/ENCFF413LVA.w5 32 2 mean CHIP:eGFP-ZNF740:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF740/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3095 0 ENCFF327QYA /home/drk/tillage/datasets/human/chip/encode/ENCSR532FEO/summary/ENCFF327QYA.w5 32 2 mean CHIP:H3K4me3:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K4me3/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3096 0 ENCFF600BXX /home/drk/tillage/datasets/human/chip/encode/ENCSR532KTI/summary/ENCFF600BXX.w5 32 2 mean CHIP:eGFP-GTF2E2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-GTF2E2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3097 0 ENCFF198TWQ /home/drk/tillage/datasets/human/chip/encode/ENCSR533DRE/summary/ENCFF198TWQ.w5 32 2 mean CHIP:H3K9me3:kidney female embryo (120 days) CHIP ChIP-Histone:H3K9me3/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3098 0 ENCFF327GAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR533HDU/summary/ENCFF327GAQ.w5 32 2 mean CHIP:H3K9me3:pancreas female adult (30 years) CHIP ChIP-Histone:H3K9me3/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3099 0 ENCFF312IMW /home/drk/tillage/datasets/human/chip/encode/ENCSR534NZI/summary/ENCFF312IMW.w5 32 2 mean CHIP:eGFP-ZNF195:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF195/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3100 0 ENCFF835WYM /home/drk/tillage/datasets/human/chip/encode/ENCSR534VHI/summary/ENCFF835WYM.w5 32 2 mean CHIP:ETS1:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:ETS1/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3101 0 ENCFF539JSB /home/drk/tillage/datasets/human/chip/encode/ENCSR535DIA/summary/ENCFF539JSB.w5 32 2 mean CHIP:eGFP-GLIS2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-GLIS2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3102 0 ENCFF941AKN /home/drk/tillage/datasets/human/chip/encode/ENCSR535XRY/summary/ENCFF941AKN.w5 32 2 mean CHIP:H3K4me3:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K4me3/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3103 0 ENCFF819WFH /home/drk/tillage/datasets/human/chip/encode/ENCSR536SZD/summary/ENCFF819WFH.w5 32 2 mean CHIP:H3F3A:NCI-H929 CHIP ChIP-Histone:H3F3A/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3104 0 ENCFF701JGR /home/drk/tillage/datasets/human/chip/encode/ENCSR538JMW/summary/ENCFF701JGR.w5 32 2 mean CHIP:H3K4me1:small intestine female adult (30 years) CHIP ChIP-Histone:H3K4me1/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3105 0 ENCFF649FAV /home/drk/tillage/datasets/human/chip/encode/ENCSR538KLU/summary/ENCFF649FAV.w5 32 2 mean CHIP:H4K20me1:SU-DHL-6 CHIP ChIP-TF:H4K20me1/SU-DHL-6 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3106 0 ENCFF288ZFT /home/drk/tillage/datasets/human/chip/encode/ENCSR538RDA/summary/ENCFF288ZFT.w5 32 2 mean CHIP:eGFP-ZNF560:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF560/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3107 0 ENCFF873IGF /home/drk/tillage/datasets/human/chip/encode/ENCSR539TKY/summary/ENCFF873IGF.w5 32 2 mean CHIP:H3K4me3:KMS-11 CHIP ChIP-Histone:H3K4me3/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3108 0 ENCFF629RAA /home/drk/tillage/datasets/human/chip/encode/ENCSR540ADS/summary/ENCFF629RAA.w5 32 2 mean CHIP:H3K27ac:lung female adult (30 years) CHIP ChIP-Histone:H3K27ac/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3109 0 ENCFF911DRS /home/drk/tillage/datasets/human/chip/encode/ENCSR540UZV/summary/ENCFF911DRS.w5 32 2 mean CHIP:H3K9ac:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K9ac/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3110 0 ENCFF031JNH /home/drk/tillage/datasets/human/chip/encode/ENCSR541AMF/summary/ENCFF031JNH.w5 32 2 mean CHIP:CTCF:SK-N-SH CHIP ChIP-TF:CTCF/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3111 0 ENCFF454PBC /home/drk/tillage/datasets/human/chip/encode/ENCSR541AOQ/summary/ENCFF454PBC.w5 32 2 mean CHIP:PHF8:A549 CHIP ChIP-TF:PHF8/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3112 0 ENCFF658EZL /home/drk/tillage/datasets/human/chip/encode/ENCSR541WQI/summary/ENCFF658EZL.w5 32 2 mean CHIP:MAFK:A549 CHIP ChIP-TF:MAFK/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3113 0 ENCFF434YEG /home/drk/tillage/datasets/human/chip/encode/ENCSR542FLV/summary/ENCFF434YEG.w5 32 2 mean CHIP:ZBTB33:GM12878 CHIP ChIP-TF:ZBTB33/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3114 0 ENCFF951YWA /home/drk/tillage/datasets/human/chip/encode/ENCSR542WJU/summary/ENCFF951YWA.w5 32 2 mean CHIP:MCM7:K562 CHIP ChIP-TF:MCM7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3115 0 ENCFF680IWA /home/drk/tillage/datasets/human/chip/encode/ENCSR543BVU/summary/ENCFF680IWA.w5 32 2 mean CHIP:SOX6:HepG2 CHIP ChIP-TF:SOX6/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3116 0 ENCFF465TWC /home/drk/tillage/datasets/human/chip/encode/ENCSR543CPW/summary/ENCFF465TWC.w5 32 2 mean CHIP:H3K27ac:small intestine male adult (34 years) CHIP ChIP-Histone:H3K27ac/small intestine male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3117 0 ENCFF740UWT /home/drk/tillage/datasets/human/chip/encode/ENCSR543DAS/summary/ENCFF740UWT.w5 32 2 mean CHIP:H3K27me3:tibial artery female adult (53 years) CHIP ChIP-Histone:H3K27me3/tibial artery female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3118 0 ENCFF956WVT /home/drk/tillage/datasets/human/chip/encode/ENCSR543DUC/summary/ENCFF956WVT.w5 32 2 mean CHIP:POLR2A:lower leg skin female adult (51 year) CHIP ChIP-TF:POLR2A/lower leg skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3119 0 ENCFF577AQW /home/drk/tillage/datasets/human/chip/encode/ENCSR543IKB/summary/ENCFF577AQW.w5 32 2 mean CHIP:H3K9ac:Loucy CHIP ChIP-Histone:H3K9ac/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3120 0 ENCFF146BUS /home/drk/tillage/datasets/human/chip/encode/ENCSR543KOA/summary/ENCFF146BUS.w5 32 2 mean CHIP:eGFP-ZBTB12:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB12/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3121 0 ENCFF674SFT /home/drk/tillage/datasets/human/chip/encode/ENCSR543YQF/summary/ENCFF674SFT.w5 32 2 mean CHIP:H3K36me3:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K36me3/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3122 0 ENCFF556RUC /home/drk/tillage/datasets/human/chip/encode/ENCSR544APK/summary/ENCFF556RUC.w5 32 2 mean CHIP:CTCF:heart left ventricle female adult (53 years) CHIP ChIP-TF:CTCF/heart left ventricle female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3123 0 ENCFF729XPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR545FXC/summary/ENCFF729XPZ.w5 32 2 mean CHIP:ATF7:HepG2 CHIP ChIP-TF:ATF7/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3124 0 ENCFF374WEW /home/drk/tillage/datasets/human/chip/encode/ENCSR546HZF/summary/ENCFF374WEW.w5 32 2 mean CHIP:H3K9me3:stomach female adult (53 years) CHIP ChIP-Histone:H3K9me3/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3125 0 ENCFF689NUE /home/drk/tillage/datasets/human/chip/encode/ENCSR546IHU/summary/ENCFF689NUE.w5 32 2 mean CHIP:ZNF184:K562 CHIP ChIP-TF:ZNF184/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3126 0 ENCFF080PKN /home/drk/tillage/datasets/human/chip/encode/ENCSR546KCN/summary/ENCFF080PKN.w5 32 2 mean CHIP:eGFP-FOSL2:MCF-7 genetically modified using stable transfection CHIP ChIP-TF:eGFP-FOSL2/MCF-7 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3127 0 ENCFF042LSM /home/drk/tillage/datasets/human/chip/encode/ENCSR546SDM/summary/ENCFF042LSM.w5 32 2 mean CHIP:H3K27ac:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27ac/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3128 0 ENCFF035IBD /home/drk/tillage/datasets/human/chip/encode/ENCSR547LKC/summary/ENCFF035IBD.w5 32 2 mean CHIP:GATAD2B:K562 CHIP ChIP-TF:GATAD2B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3129 0 ENCFF172ZJC /home/drk/tillage/datasets/human/chip/encode/ENCSR547TGL/summary/ENCFF172ZJC.w5 32 2 mean CHIP:eGFP-ZNF701:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF701/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3130 0 ENCFF932OWO /home/drk/tillage/datasets/human/chip/encode/ENCSR548DDS/summary/ENCFF932OWO.w5 32 2 mean CHIP:CTCF:ovary female adult (51 year) CHIP ChIP-TF:CTCF/ovary female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3131 0 ENCFF958IXF /home/drk/tillage/datasets/human/chip/encode/ENCSR548LZS/summary/ENCFF958IXF.w5 32 2 mean CHIP:H3K4me3:right cardiac atrium male adult (34 years) CHIP ChIP-Histone:H3K4me3/right cardiac atrium male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3132 0 ENCFF917EGP /home/drk/tillage/datasets/human/chip/encode/ENCSR548PZS/summary/ENCFF917EGP.w5 32 2 mean CHIP:H3K4me3:OCI-LY3 CHIP ChIP-Histone:H3K4me3/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3133 0 ENCFF741ZGT /home/drk/tillage/datasets/human/chip/encode/ENCSR549NPZ/summary/ENCFF741ZGT.w5 32 2 mean CHIP:CBX3:GM12878 CHIP ChIP-TF:CBX3/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3134 0 ENCFF684OBP /home/drk/tillage/datasets/human/chip/encode/ENCSR549WAU/summary/ENCFF684OBP.w5 32 2 mean CHIP:CTCF:stomach male adult (54 years) CHIP ChIP-TF:CTCF/stomach male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3135 0 ENCFF099BHP /home/drk/tillage/datasets/human/chip/encode/ENCSR550GSE/summary/ENCFF099BHP.w5 32 2 mean CHIP:H3K9me3:UCSF-4 CHIP ChIP-Histone:H3K9me3/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3136 0 ENCFF191STL /home/drk/tillage/datasets/human/chip/encode/ENCSR550HCT/summary/ENCFF191STL.w5 32 2 mean CHIP:eGFP-KLF1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-KLF1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3137 0 ENCFF603JLN /home/drk/tillage/datasets/human/chip/encode/ENCSR550SCU/summary/ENCFF603JLN.w5 32 2 mean CHIP:CHD4:A549 CHIP ChIP-TF:CHD4/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3138 0 ENCFF105RLH /home/drk/tillage/datasets/human/chip/encode/ENCSR550WUX/summary/ENCFF105RLH.w5 32 2 mean CHIP:H3K27ac:lung male child (3 years) CHIP ChIP-Histone:H3K27ac/lung male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3139 0 ENCFF380EUR /home/drk/tillage/datasets/human/chip/encode/ENCSR550XZG/summary/ENCFF380EUR.w5 32 2 mean CHIP:H3K27me3:neural stem progenitor cell originated from H9 CHIP ChIP-Histone:H3K27me3/neural stem progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3140 0 ENCFF822QVL /home/drk/tillage/datasets/human/chip/encode/ENCSR550ZZK/summary/ENCFF822QVL.w5 32 2 mean CHIP:eGFP-ZNF493:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF493/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3141 0 ENCFF572NTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR551KAP/summary/ENCFF572NTZ.w5 32 2 mean CHIP:eGFP-ZNF138:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF138/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3142 0 ENCFF977MTB /home/drk/tillage/datasets/human/chip/encode/ENCSR551MLB/summary/ENCFF977MTB.w5 32 2 mean CHIP:EP300:gastroesophageal sphincter male adult (37 years) CHIP ChIP-TF:EP300/gastroesophageal sphincter male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3143 0 ENCFF028OGH /home/drk/tillage/datasets/human/chip/encode/ENCSR551QXE/summary/ENCFF028OGH.w5 32 2 mean CHIP:H3K4me3:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K4me3/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3144 0 ENCFF681CSL /home/drk/tillage/datasets/human/chip/encode/ENCSR551ZDZ/summary/ENCFF681CSL.w5 32 2 mean CHIP:MTA2:MCF-7 CHIP ChIP-TF:MTA2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3145 0 ENCFF012YOU /home/drk/tillage/datasets/human/chip/encode/ENCSR552MZH/summary/ENCFF012YOU.w5 32 2 mean CHIP:H3K36me3:stomach male adult (34 years) CHIP ChIP-Histone:H3K36me3/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3146 0 ENCFF588FOZ /home/drk/tillage/datasets/human/chip/encode/ENCSR552PSV/summary/ENCFF588FOZ.w5 32 2 mean CHIP:MCM2:K562 CHIP ChIP-TF:MCM2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3147 0 ENCFF897JYH /home/drk/tillage/datasets/human/chip/encode/ENCSR552TQB/summary/ENCFF897JYH.w5 32 2 mean CHIP:H3K9me3:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K9me3/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3148 0 ENCFF984HLU /home/drk/tillage/datasets/human/chip/encode/ENCSR552XSN/summary/ENCFF984HLU.w5 32 2 mean CHIP:MLLT1:GM12878 CHIP ChIP-TF:MLLT1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3149 0 ENCFF704MKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR552YGL/summary/ENCFF704MKQ.w5 32 2 mean CHIP:eGFP-NFE2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NFE2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3150 0 ENCFF508MXW /home/drk/tillage/datasets/human/chip/encode/ENCSR553IAW/summary/ENCFF508MXW.w5 32 2 mean CHIP:H3K4me1:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K4me1/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3151 0 ENCFF585VWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR553OEU/summary/ENCFF585VWJ.w5 32 2 mean CHIP:H3K79me1:IMR-90 CHIP ChIP-Histone:H3K79me1/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3152 0 ENCFF802XFR /home/drk/tillage/datasets/human/chip/encode/ENCSR553QMC/summary/ENCFF802XFR.w5 32 2 mean CHIP:3xFLAG-ZNF7:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF7/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3153 0 ENCFF014MYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR553XBX/summary/ENCFF014MYJ.w5 32 2 mean CHIP:H3K27me3:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K27me3/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3154 0 ENCFF242BVN /home/drk/tillage/datasets/human/chip/encode/ENCSR554RQQ/summary/ENCFF242BVN.w5 32 2 mean CHIP:H3K4me3:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K4me3/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3155 0 ENCFF512TZG /home/drk/tillage/datasets/human/chip/encode/ENCSR554TZE/summary/ENCFF512TZG.w5 32 2 mean CHIP:H4K5ac:H9 CHIP ChIP-TF:H4K5ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3156 0 ENCFF927MHC /home/drk/tillage/datasets/human/chip/encode/ENCSR555DCF/summary/ENCFF927MHC.w5 32 2 mean CHIP:ZNF512B:MCF-7 CHIP ChIP-TF:ZNF512B/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3157 0 ENCFF807PSQ /home/drk/tillage/datasets/human/chip/encode/ENCSR555LYM/summary/ENCFF807PSQ.w5 32 2 mean CHIP:H3K9me2:HCT116 CHIP ChIP-Histone:H3K9me2/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3158 0 ENCFF456EBS /home/drk/tillage/datasets/human/chip/encode/ENCSR555PBN/summary/ENCFF456EBS.w5 32 2 mean CHIP:MAFK:MCF-7 CHIP ChIP-TF:MAFK/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3159 0 ENCFF604XOA /home/drk/tillage/datasets/human/chip/encode/ENCSR555QHZ/summary/ENCFF604XOA.w5 32 2 mean CHIP:H3K36me3:mesenchymal stem cell originated from adipose tissue CHIP ChIP-Histone:H3K36me3/mesenchymal stem cell originated from adipose tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3160 0 ENCFF700QJI /home/drk/tillage/datasets/human/chip/encode/ENCSR555TAX/summary/ENCFF700QJI.w5 32 2 mean CHIP:H3K9me3:PC-9 CHIP ChIP-Histone:H3K9me3/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3161 0 ENCFF587FTV /home/drk/tillage/datasets/human/chip/encode/ENCSR555ZMV/summary/ENCFF587FTV.w5 32 2 mean CHIP:AGO1:HepG2 CHIP ChIP-TF:AGO1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3162 0 ENCFF010EUT /home/drk/tillage/datasets/human/chip/encode/ENCSR557DFM/summary/ENCFF010EUT.w5 32 2 mean CHIP:H3K27ac:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K27ac/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3163 0 ENCFF273OEJ /home/drk/tillage/datasets/human/chip/encode/ENCSR557JTZ/summary/ENCFF273OEJ.w5 32 2 mean CHIP:GTF2F1:MCF-7 CHIP ChIP-TF:GTF2F1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3164 0 ENCFF611IES /home/drk/tillage/datasets/human/chip/encode/ENCSR557OPY/summary/ENCFF611IES.w5 32 2 mean CHIP:H3K36me3:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K36me3/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3165 0 ENCFF255VEW /home/drk/tillage/datasets/human/chip/encode/ENCSR557RVF/summary/ENCFF255VEW.w5 32 2 mean CHIP:ZHX1:K562 CHIP ChIP-TF:ZHX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3166 0 ENCFF824WXK /home/drk/tillage/datasets/human/chip/encode/ENCSR557TNE/summary/ENCFF824WXK.w5 32 2 mean CHIP:H3K27me3:B cell male adult (37 years) CHIP ChIP-Histone:H3K27me3/B cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3167 0 ENCFF091JGF /home/drk/tillage/datasets/human/chip/encode/ENCSR558AXI/summary/ENCFF091JGF.w5 32 2 mean CHIP:H3K9me3:thyroid gland female adult (51 year) CHIP ChIP-Histone:H3K9me3/thyroid gland female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3168 0 ENCFF748PHO /home/drk/tillage/datasets/human/chip/encode/ENCSR558HTE/summary/ENCFF748PHO.w5 32 2 mean CHIP:CTCF:transverse colon female adult (51 year) CHIP ChIP-TF:CTCF/transverse colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3169 0 ENCFF675EXW /home/drk/tillage/datasets/human/chip/encode/ENCSR558SJC/summary/ENCFF675EXW.w5 32 2 mean CHIP:H3K36me3:kidney male adult (67 years) CHIP ChIP-Histone:H3K36me3/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3170 0 ENCFF215AYX /home/drk/tillage/datasets/human/chip/encode/ENCSR558XOU/summary/ENCFF215AYX.w5 32 2 mean CHIP:H3K9me3:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K9me3/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3171 0 ENCFF762ZSH /home/drk/tillage/datasets/human/chip/encode/ENCSR559BMF/summary/ENCFF762ZSH.w5 32 2 mean CHIP:H3K36me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3172 0 ENCFF358RAF /home/drk/tillage/datasets/human/chip/encode/ENCSR559CSJ/summary/ENCFF358RAF.w5 32 2 mean CHIP:H3K4me1:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K4me1/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3173 0 ENCFF550VRK /home/drk/tillage/datasets/human/chip/encode/ENCSR559IFS/summary/ENCFF550VRK.w5 32 2 mean CHIP:H2AFZ:NCI-H929 CHIP ChIP-TF:H2AFZ/NCI-H929 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3174 0 ENCFF856FNH /home/drk/tillage/datasets/human/chip/encode/ENCSR559IOZ/summary/ENCFF856FNH.w5 32 2 mean CHIP:eGFP-ZXDB:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZXDB/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3175 0 ENCFF817PJG /home/drk/tillage/datasets/human/chip/encode/ENCSR559KAB/summary/ENCFF817PJG.w5 32 2 mean CHIP:CTCF:esophagus muscularis mucosa male adult (37 years) CHIP ChIP-TF:CTCF/esophagus muscularis mucosa male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3176 0 ENCFF362LEO /home/drk/tillage/datasets/human/chip/encode/ENCSR559RGT/summary/ENCFF362LEO.w5 32 2 mean CHIP:H3K36me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K36me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3177 0 ENCFF606YFS /home/drk/tillage/datasets/human/chip/encode/ENCSR560BUE/summary/ENCFF606YFS.w5 32 2 mean CHIP:CTCF:MCF-7 CHIP ChIP-TF:CTCF/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3178 0 ENCFF251CHW /home/drk/tillage/datasets/human/chip/encode/ENCSR560IDY/summary/ENCFF251CHW.w5 32 2 mean CHIP:H3K9ac:skeletal muscle tissue CHIP ChIP-Histone:H3K9ac/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3179 0 ENCFF657IBD /home/drk/tillage/datasets/human/chip/encode/ENCSR560OUF/summary/ENCFF657IBD.w5 32 2 mean CHIP:H3K9me3:HUES48 CHIP ChIP-Histone:H3K9me3/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3180 0 ENCFF697IBR /home/drk/tillage/datasets/human/chip/encode/ENCSR560SEP/summary/ENCFF697IBR.w5 32 2 mean CHIP:3xFLAG-RXRB:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RXRB/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3181 0 ENCFF181OXO /home/drk/tillage/datasets/human/chip/encode/ENCSR561KOM/summary/ENCFF181OXO.w5 32 2 mean CHIP:H3K27ac:CD4-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K27ac/CD4-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3182 0 ENCFF437RZA /home/drk/tillage/datasets/human/chip/encode/ENCSR561MYM/summary/ENCFF437RZA.w5 32 2 mean CHIP:H3K36me3:testis male adult (37 years) CHIP ChIP-Histone:H3K36me3/testis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3183 0 ENCFF605ZMK /home/drk/tillage/datasets/human/chip/encode/ENCSR561YSH/summary/ENCFF605ZMK.w5 32 2 mean CHIP:H3K27ac:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K27ac/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3184 0 ENCFF741MHK /home/drk/tillage/datasets/human/chip/encode/ENCSR562JTY/summary/ENCFF741MHK.w5 32 2 mean CHIP:H3K36me3:NCI-H929 CHIP ChIP-Histone:H3K36me3/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3185 0 ENCFF283GZE /home/drk/tillage/datasets/human/chip/encode/ENCSR562MOC/summary/ENCFF283GZE.w5 32 2 mean CHIP:H3K9ac:GM23248 CHIP ChIP-Histone:H3K9ac/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3186 0 ENCFF071DMU /home/drk/tillage/datasets/human/chip/encode/ENCSR562NOP/summary/ENCFF071DMU.w5 32 2 mean CHIP:EZH2phosphoT487:DOHH2 CHIP ChIP-TF:EZH2phosphoT487/DOHH2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3187 0 ENCFF206SFE /home/drk/tillage/datasets/human/chip/encode/ENCSR562POI/summary/ENCFF206SFE.w5 32 2 mean CHIP:3xFLAG-THAP11:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-THAP11/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3188 0 ENCFF155OGQ /home/drk/tillage/datasets/human/chip/encode/ENCSR562SRW/summary/ENCFF155OGQ.w5 32 2 mean CHIP:H3F3A:MM.1S CHIP ChIP-Histone:H3F3A/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3189 0 ENCFF967EEA /home/drk/tillage/datasets/human/chip/encode/ENCSR563FBT/summary/ENCFF967EEA.w5 32 2 mean CHIP:USF2:A549 CHIP ChIP-TF:USF2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3190 0 ENCFF527AMK /home/drk/tillage/datasets/human/chip/encode/ENCSR563LLO/summary/ENCFF527AMK.w5 32 2 mean CHIP:E2F1:K562 CHIP ChIP-TF:E2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3191 0 ENCFF422WMR /home/drk/tillage/datasets/human/chip/encode/ENCSR563YDA/summary/ENCFF422WMR.w5 32 2 mean CHIP:HDGF:K562 CHIP ChIP-TF:HDGF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3192 0 ENCFF334PFQ /home/drk/tillage/datasets/human/chip/encode/ENCSR563YGF/summary/ENCFF334PFQ.w5 32 2 mean CHIP:H3K9me3:liver male adult (32 years) CHIP ChIP-Histone:H3K9me3/liver male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3193 0 ENCFF797FSX /home/drk/tillage/datasets/human/chip/encode/ENCSR564GWG/summary/ENCFF797FSX.w5 32 2 mean CHIP:H3K4me1:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K4me1/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3194 0 ENCFF151FXB /home/drk/tillage/datasets/human/chip/encode/ENCSR564IGJ/summary/ENCFF151FXB.w5 32 2 mean CHIP:H3K27ac:SK-N-SH CHIP ChIP-Histone:H3K27ac/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3195 0 ENCFF638SDV /home/drk/tillage/datasets/human/chip/encode/ENCSR564RWY/summary/ENCFF638SDV.w5 32 2 mean CHIP:H3K27me3:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K27me3/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3196 0 ENCFF102UVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR564VIX/summary/ENCFF102UVJ.w5 32 2 mean CHIP:H3K4me3:DND-41 CHIP ChIP-Histone:H3K4me3/DND-41 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3197 0 ENCFF204XKT /home/drk/tillage/datasets/human/chip/encode/ENCSR564YYW/summary/ENCFF204XKT.w5 32 2 mean CHIP:eGFP-ZNF157:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF157/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3198 0 ENCFF309VNF /home/drk/tillage/datasets/human/chip/encode/ENCSR565XSL/summary/ENCFF309VNF.w5 32 2 mean CHIP:EZH2phosphoT487:OCI-LY7 CHIP ChIP-TF:EZH2phosphoT487/OCI-LY7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3199 0 ENCFF712KGJ /home/drk/tillage/datasets/human/chip/encode/ENCSR565XTT/summary/ENCFF712KGJ.w5 32 2 mean CHIP:H3K18ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K18ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3200 0 ENCFF262CEV /home/drk/tillage/datasets/human/chip/encode/ENCSR566UMF/summary/ENCFF262CEV.w5 32 2 mean CHIP:H3K4me1:PC-3 CHIP ChIP-Histone:H3K4me1/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3201 0 ENCFF975RQY /home/drk/tillage/datasets/human/chip/encode/ENCSR566VBK/summary/ENCFF975RQY.w5 32 2 mean CHIP:H3K27me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K27me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3202 0 ENCFF803WBW /home/drk/tillage/datasets/human/chip/encode/ENCSR566ZFQ/summary/ENCFF803WBW.w5 32 2 mean CHIP:H3K9me3:placental basal plate female embryo (40 weeks) CHIP ChIP-Histone:H3K9me3/placental basal plate female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3203 0 ENCFF833ETX /home/drk/tillage/datasets/human/chip/encode/ENCSR567ILB/summary/ENCFF833ETX.w5 32 2 mean CHIP:H3K9ac:lung female embryo (82 days) CHIP ChIP-Histone:H3K9ac/lung female embryo (82 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3204 0 ENCFF321FEG /home/drk/tillage/datasets/human/chip/encode/ENCSR567JEU/summary/ENCFF321FEG.w5 32 2 mean CHIP:YBX3:K562 CHIP ChIP-TF:YBX3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3205 0 ENCFF444CNE /home/drk/tillage/datasets/human/chip/encode/ENCSR567XAM/summary/ENCFF444CNE.w5 32 2 mean CHIP:eGFP-ZNF473:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF473/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3206 0 ENCFF938GGR /home/drk/tillage/datasets/human/chip/encode/ENCSR568CDB/summary/ENCFF938GGR.w5 32 2 mean CHIP:H3K9me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K9me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3207 0 ENCFF174YGI /home/drk/tillage/datasets/human/chip/encode/ENCSR568EZU/summary/ENCFF174YGI.w5 32 2 mean CHIP:H3K9me3:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K9me3/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3208 0 ENCFF752GHN /home/drk/tillage/datasets/human/chip/encode/ENCSR568OLP/summary/ENCFF752GHN.w5 32 2 mean CHIP:H3K9me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K9me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3209 0 ENCFF741BVS /home/drk/tillage/datasets/human/chip/encode/ENCSR568PGX/summary/ENCFF741BVS.w5 32 2 mean CHIP:HDAC1:K562 CHIP ChIP-TF:HDAC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3210 0 ENCFF798EMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR569AGQ/summary/ENCFF798EMZ.w5 32 2 mean CHIP:H3K27me3:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K27me3/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3211 0 ENCFF210DOS /home/drk/tillage/datasets/human/chip/encode/ENCSR569ARC/summary/ENCFF210DOS.w5 32 2 mean CHIP:3xFLAG-NFYC:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NFYC/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3212 0 ENCFF004UZT /home/drk/tillage/datasets/human/chip/encode/ENCSR569SZK/summary/ENCFF004UZT.w5 32 2 mean CHIP:EP300:tibial nerve female adult (51 year) CHIP ChIP-TF:EP300/tibial nerve female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3213 0 ENCFF160WPD /home/drk/tillage/datasets/human/chip/encode/ENCSR569XNP/summary/ENCFF160WPD.w5 32 2 mean CHIP:FOS:MCF-7 CHIP ChIP-TF:FOS/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3214 0 ENCFF977TEF /home/drk/tillage/datasets/human/chip/encode/ENCSR570AUC/summary/ENCFF977TEF.w5 32 2 mean CHIP:H3K4me3:natural killer cell male adult (37 years) CHIP ChIP-Histone:H3K4me3/natural killer cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3215 0 ENCFF475SUV /home/drk/tillage/datasets/human/chip/encode/ENCSR570POG/summary/ENCFF475SUV.w5 32 2 mean CHIP:H3K79me1:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K79me1/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3216 0 ENCFF955KWH /home/drk/tillage/datasets/human/chip/encode/ENCSR571BUF/summary/ENCFF955KWH.w5 32 2 mean CHIP:ARHGAP35:K562 CHIP ChIP-TF:ARHGAP35/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3217 0 ENCFF876EXE /home/drk/tillage/datasets/human/chip/encode/ENCSR571CSC/summary/ENCFF876EXE.w5 32 2 mean CHIP:H3K9me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K9me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3218 0 ENCFF157VMK /home/drk/tillage/datasets/human/chip/encode/ENCSR571IIS/summary/ENCFF157VMK.w5 32 2 mean CHIP:H2AFZ:H1-hESC CHIP ChIP-TF:H2AFZ/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3219 0 ENCFF615LFZ /home/drk/tillage/datasets/human/chip/encode/ENCSR571PDN/summary/ENCFF615LFZ.w5 32 2 mean CHIP:3xFLAG-SSRP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SSRP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3220 0 ENCFF249HWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR572DUJ/summary/ENCFF249HWJ.w5 32 2 mean CHIP:CTCF:body of pancreas male adult (37 years) CHIP ChIP-TF:CTCF/body of pancreas male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3221 0 ENCFF055FMF /home/drk/tillage/datasets/human/chip/encode/ENCSR573CWZ/summary/ENCFF055FMF.w5 32 2 mean CHIP:H3K36me3:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K36me3/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3222 0 ENCFF443GIH /home/drk/tillage/datasets/human/chip/encode/ENCSR573OJP/summary/ENCFF443GIH.w5 32 2 mean CHIP:NCOA3:MCF-7 CHIP ChIP-TF:NCOA3/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3223 0 ENCFF137FJR /home/drk/tillage/datasets/human/chip/encode/ENCSR573WYW/summary/ENCFF137FJR.w5 32 2 mean CHIP:EP300:stomach female adult (53 years) CHIP ChIP-TF:EP300/stomach female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3224 0 ENCFF817OYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR574KCT/summary/ENCFF817OYZ.w5 32 2 mean CHIP:H3K36me3:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3225 0 ENCFF949FTC /home/drk/tillage/datasets/human/chip/encode/ENCSR574XEO/summary/ENCFF949FTC.w5 32 2 mean CHIP:NUFIP1:K562 CHIP ChIP-TF:NUFIP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3226 0 ENCFF988XYF /home/drk/tillage/datasets/human/chip/encode/ENCSR575ICR/summary/ENCFF988XYF.w5 32 2 mean CHIP:H3K4me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K4me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3227 0 ENCFF736LHE /home/drk/tillage/datasets/human/chip/encode/ENCSR575RRX/summary/ENCFF736LHE.w5 32 2 mean CHIP:H3K4me3:HepG2 CHIP ChIP-Histone:H3K4me3/HepG2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3228 0 ENCFF232QEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR575SWA/summary/ENCFF232QEZ.w5 32 2 mean CHIP:H3K4me1:lung male child (3 years) CHIP ChIP-Histone:H3K4me1/lung male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3229 0 ENCFF431EQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR575ZNE/summary/ENCFF431EQQ.w5 32 2 mean CHIP:H3K79me2:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K79me2/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3230 0 ENCFF764XKD /home/drk/tillage/datasets/human/chip/encode/ENCSR576PII/summary/ENCFF764XKD.w5 32 2 mean CHIP:POLR2A:Peyer's patch male adult (54 years) CHIP ChIP-TF:POLR2A/Peyer's patch male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3231 0 ENCFF576CRZ /home/drk/tillage/datasets/human/chip/encode/ENCSR576YAD/summary/ENCFF576CRZ.w5 32 2 mean CHIP:H3K9me3:muscle layer of colon female adult (56 years) CHIP ChIP-Histone:H3K9me3/muscle layer of colon female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3232 0 ENCFF927GCK /home/drk/tillage/datasets/human/chip/encode/ENCSR577CDW/summary/ENCFF927GCK.w5 32 2 mean CHIP:H3K9me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K9me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3233 0 ENCFF861DEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR577DVK/summary/ENCFF861DEQ.w5 32 2 mean CHIP:H3K4me3:colonic mucosa female adult (73 years) CHIP ChIP-Histone:H3K4me3/colonic mucosa female adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3234 0 ENCFF711EZH /home/drk/tillage/datasets/human/chip/encode/ENCSR577GVS/summary/ENCFF711EZH.w5 32 2 mean CHIP:H3K27ac:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K27ac/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3235 0 ENCFF633LAF /home/drk/tillage/datasets/human/chip/encode/ENCSR577ILY/summary/ENCFF633LAF.w5 32 2 mean CHIP:H3K4me3:esophagus male adult (34 years) CHIP ChIP-Histone:H3K4me3/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3236 0 ENCFF126BUH /home/drk/tillage/datasets/human/chip/encode/ENCSR578CXC/summary/ENCFF126BUH.w5 32 2 mean CHIP:3xFLAG-ZNF644:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF644/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3237 0 ENCFF796NYG /home/drk/tillage/datasets/human/chip/encode/ENCSR578MTT/summary/ENCFF796NYG.w5 32 2 mean CHIP:H3K9me3:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K9me3/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3238 0 ENCFF032KUS /home/drk/tillage/datasets/human/chip/encode/ENCSR578QSO/summary/ENCFF032KUS.w5 32 2 mean CHIP:H3K4me3:endothelial cell of umbilical vein male newborn CHIP ChIP-Histone:H3K4me3/endothelial cell of umbilical vein male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3239 0 ENCFF093FLS /home/drk/tillage/datasets/human/chip/encode/ENCSR579DZQ/summary/ENCFF093FLS.w5 32 2 mean CHIP:H3K4me3:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K4me3/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3240 0 ENCFF883TLY /home/drk/tillage/datasets/human/chip/encode/ENCSR579OVQ/summary/ENCFF883TLY.w5 32 2 mean CHIP:H3K4me1:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3241 0 ENCFF689QGV /home/drk/tillage/datasets/human/chip/encode/ENCSR579TJT/summary/ENCFF689QGV.w5 32 2 mean CHIP:H3K79me1:IMR-90 CHIP ChIP-Histone:H3K79me1/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3242 0 ENCFF971LUI /home/drk/tillage/datasets/human/chip/encode/ENCSR579YLO/summary/ENCFF971LUI.w5 32 2 mean CHIP:H3K27ac:fibroblast of breast female adult (17 years) CHIP ChIP-Histone:H3K27ac/fibroblast of breast female adult (17 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3243 0 ENCFF563CUY /home/drk/tillage/datasets/human/chip/encode/ENCSR580IAO/summary/ENCFF563CUY.w5 32 2 mean CHIP:eGFP-ZNF197:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF197/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3244 0 ENCFF884DJG /home/drk/tillage/datasets/human/chip/encode/ENCSR580LZO/summary/ENCFF884DJG.w5 32 2 mean CHIP:H3K9me1:IMR-90 CHIP ChIP-Histone:H3K9me1/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3245 0 ENCFF652DFI /home/drk/tillage/datasets/human/chip/encode/ENCSR580WRV/summary/ENCFF652DFI.w5 32 2 mean CHIP:H3K36me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K36me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3246 0 ENCFF469CEQ /home/drk/tillage/datasets/human/chip/encode/ENCSR580XUK/summary/ENCFF469CEQ.w5 32 2 mean CHIP:EP300:tibial nerve male adult (37 years) CHIP ChIP-TF:EP300/tibial nerve male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3247 0 ENCFF452ULT /home/drk/tillage/datasets/human/chip/encode/ENCSR581CVA/summary/ENCFF452ULT.w5 32 2 mean CHIP:HNRNPH1:K562 CHIP ChIP-TF:HNRNPH1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3248 0 ENCFF404LTK /home/drk/tillage/datasets/human/chip/encode/ENCSR581LZU/summary/ENCFF404LTK.w5 32 2 mean CHIP:H3K4me1:OCI-LY3 CHIP ChIP-Histone:H3K4me1/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3249 0 ENCFF198HBU /home/drk/tillage/datasets/human/chip/encode/ENCSR581PUR/summary/ENCFF198HBU.w5 32 2 mean CHIP:H3K36me3:A673 CHIP ChIP-Histone:H3K36me3/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3250 0 ENCFF069QJI /home/drk/tillage/datasets/human/chip/encode/ENCSR581UGC/summary/ENCFF069QJI.w5 32 2 mean CHIP:H3K27me3:endocrine pancreas male adult (46 years) CHIP ChIP-Histone:H3K27me3/endocrine pancreas male adult (46 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3251 0 ENCFF744XNM /home/drk/tillage/datasets/human/chip/encode/ENCSR581YZL/summary/ENCFF744XNM.w5 32 2 mean CHIP:H3K27me3:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K27me3/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3252 0 ENCFF836USZ /home/drk/tillage/datasets/human/chip/encode/ENCSR582MTM/summary/ENCFF836USZ.w5 32 2 mean CHIP:CTCF:lower leg skin male adult (37 years) CHIP ChIP-TF:CTCF/lower leg skin male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3253 0 ENCFF310XVY /home/drk/tillage/datasets/human/chip/encode/ENCSR582PKH/summary/ENCFF310XVY.w5 32 2 mean CHIP:H3K27me3:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K27me3/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3254 0 ENCFF623QXD /home/drk/tillage/datasets/human/chip/encode/ENCSR582UTE/summary/ENCFF623QXD.w5 32 2 mean CHIP:H3K27ac:stomach female adult (30 years) CHIP ChIP-Histone:H3K27ac/stomach female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3255 0 ENCFF834FDG /home/drk/tillage/datasets/human/chip/encode/ENCSR582ZOA/summary/ENCFF834FDG.w5 32 2 mean CHIP:NFIB:MCF-7 CHIP ChIP-TF:NFIB/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3256 0 ENCFF888JOO /home/drk/tillage/datasets/human/chip/encode/ENCSR583ACG/summary/ENCFF888JOO.w5 32 2 mean CHIP:BRD4:K562 CHIP ChIP-TF:BRD4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3257 0 ENCFF411SAF /home/drk/tillage/datasets/human/chip/encode/ENCSR583ALI/summary/ENCFF411SAF.w5 32 2 mean CHIP:H3K9ac:HUES6 CHIP ChIP-Histone:H3K9ac/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3258 0 ENCFF850RAU /home/drk/tillage/datasets/human/chip/encode/ENCSR584ATA/summary/ENCFF850RAU.w5 32 2 mean CHIP:EZH2phosphoT487:OCI-LY3 CHIP ChIP-TF:EZH2phosphoT487/OCI-LY3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3259 0 ENCFF668LIG /home/drk/tillage/datasets/human/chip/encode/ENCSR584GHV/summary/ENCFF668LIG.w5 32 2 mean CHIP:NFE2L2:A549 CHIP ChIP-TF:NFE2L2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3260 0 ENCFF309YBQ /home/drk/tillage/datasets/human/chip/encode/ENCSR585GLZ/summary/ENCFF309YBQ.w5 32 2 mean CHIP:H3K9ac:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K9ac/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3261 0 ENCFF476BNO /home/drk/tillage/datasets/human/chip/encode/ENCSR585KLQ/summary/ENCFF476BNO.w5 32 2 mean CHIP:H3K36me3:liver male adult (78 years) CHIP ChIP-Histone:H3K36me3/liver male adult (78 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3262 0 ENCFF113PLA /home/drk/tillage/datasets/human/chip/encode/ENCSR586BRJ/summary/ENCFF113PLA.w5 32 2 mean CHIP:eGFP-ZNF433:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF433/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3263 0 ENCFF638BJN /home/drk/tillage/datasets/human/chip/encode/ENCSR586DEH/summary/ENCFF638BJN.w5 32 2 mean CHIP:3xFLAG-ZFP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZFP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3264 0 ENCFF897XDW /home/drk/tillage/datasets/human/chip/encode/ENCSR586POT/summary/ENCFF897XDW.w5 32 2 mean CHIP:H3K4me1:neutrophil male CHIP ChIP-Histone:H3K4me1/neutrophil male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3265 0 ENCFF330MXO /home/drk/tillage/datasets/human/chip/encode/ENCSR587FCM/summary/ENCFF330MXO.w5 32 2 mean CHIP:H3K9me3:SU-DHL-6 CHIP ChIP-Histone:H3K9me3/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3266 0 ENCFF118DJE /home/drk/tillage/datasets/human/chip/encode/ENCSR587OQL/summary/ENCFF118DJE.w5 32 2 mean CHIP:SMARCA4:K562 CHIP ChIP-TF:SMARCA4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3267 0 ENCFF185TTH /home/drk/tillage/datasets/human/chip/encode/ENCSR588AKU/summary/ENCFF185TTH.w5 32 2 mean CHIP:RUNX1:K562 CHIP ChIP-TF:RUNX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3268 0 ENCFF921YAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR588WOD/summary/ENCFF921YAQ.w5 32 2 mean CHIP:H3K27me3:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K27me3/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3269 0 ENCFF178UXM /home/drk/tillage/datasets/human/chip/encode/ENCSR589GII/summary/ENCFF178UXM.w5 32 2 mean CHIP:H3K27me3:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K27me3/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3270 0 ENCFF448DBP /home/drk/tillage/datasets/human/chip/encode/ENCSR589SNT/summary/ENCFF448DBP.w5 32 2 mean CHIP:3xFLAG-TFE3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-TFE3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3271 0 ENCFF293GPX /home/drk/tillage/datasets/human/chip/encode/ENCSR589TCU/summary/ENCFF293GPX.w5 32 2 mean CHIP:H3K36me3:spleen female adult (53 years) CHIP ChIP-Histone:H3K36me3/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3272 0 ENCFF832BFI /home/drk/tillage/datasets/human/chip/encode/ENCSR590CNM/summary/ENCFF832BFI.w5 32 2 mean CHIP:GATA4:HepG2 CHIP ChIP-TF:GATA4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3273 0 ENCFF561TKX /home/drk/tillage/datasets/human/chip/encode/ENCSR590KEQ/summary/ENCFF561TKX.w5 32 2 mean CHIP:ARNT:GM12878 CHIP ChIP-TF:ARNT/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3274 0 ENCFF089NBN /home/drk/tillage/datasets/human/chip/encode/ENCSR590QQP/summary/ENCFF089NBN.w5 32 2 mean CHIP:FUS:HepG2 CHIP ChIP-TF:FUS/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3275 0 ENCFF843CXH /home/drk/tillage/datasets/human/chip/encode/ENCSR591CCL/summary/ENCFF843CXH.w5 32 2 mean CHIP:eGFP-ZNF512:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF512/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3276 0 ENCFF117WAO /home/drk/tillage/datasets/human/chip/encode/ENCSR591DTH/summary/ENCFF117WAO.w5 32 2 mean CHIP:EZH2phosphoT487:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:EZH2phosphoT487/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3277 0 ENCFF226RHI /home/drk/tillage/datasets/human/chip/encode/ENCSR591EBL/summary/ENCFF226RHI.w5 32 2 mean CHIP:NBN:MCF-7 CHIP ChIP-TF:NBN/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3278 0 ENCFF904ZMJ /home/drk/tillage/datasets/human/chip/encode/ENCSR591FTM/summary/ENCFF904ZMJ.w5 32 2 mean CHIP:H3K9me3:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K9me3/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3279 0 ENCFF482DLD /home/drk/tillage/datasets/human/chip/encode/ENCSR591JZS/summary/ENCFF482DLD.w5 32 2 mean CHIP:H3K9me3:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K9me3/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3280 0 ENCFF022MRT /home/drk/tillage/datasets/human/chip/encode/ENCSR591KSN/summary/ENCFF022MRT.w5 32 2 mean CHIP:H3F3A:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3F3A/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3281 0 ENCFF315NRF /home/drk/tillage/datasets/human/chip/encode/ENCSR591YVZ/summary/ENCFF315NRF.w5 32 2 mean CHIP:H3K9ac:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K9ac/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3282 0 ENCFF869HFT /home/drk/tillage/datasets/human/chip/encode/ENCSR592ETL/summary/ENCFF869HFT.w5 32 2 mean CHIP:H3K9ac:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K9ac/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3283 0 ENCFF739SJR /home/drk/tillage/datasets/human/chip/encode/ENCSR592JNN/summary/ENCFF739SJR.w5 32 2 mean CHIP:H3K23ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K23ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3284 0 ENCFF627QFP /home/drk/tillage/datasets/human/chip/encode/ENCSR592KSP/summary/ENCFF627QFP.w5 32 2 mean CHIP:eGFP-ZFP64:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFP64/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3285 0 ENCFF880HJF /home/drk/tillage/datasets/human/chip/encode/ENCSR593KDJ/summary/ENCFF880HJF.w5 32 2 mean CHIP:H3K27ac:right atrium auricular region female adult (53 years) CHIP ChIP-Histone:H3K27ac/right atrium auricular region female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3286 0 ENCFF861SBJ /home/drk/tillage/datasets/human/chip/encode/ENCSR594AQO/summary/ENCFF861SBJ.w5 32 2 mean CHIP:H3K79me1:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K79me1/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3287 0 ENCFF447DXS /home/drk/tillage/datasets/human/chip/encode/ENCSR594BNR/summary/ENCFF447DXS.w5 32 2 mean CHIP:HNRNPL:K562 CHIP ChIP-TF:HNRNPL/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3288 0 ENCFF283FON /home/drk/tillage/datasets/human/chip/encode/ENCSR594SMP/summary/ENCFF283FON.w5 32 2 mean CHIP:PHF20:K562 CHIP ChIP-TF:PHF20/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3289 0 ENCFF515YNU /home/drk/tillage/datasets/human/chip/encode/ENCSR595FAO/summary/ENCFF515YNU.w5 32 2 mean CHIP:eGFP-ZNF510:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF510/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3290 0 ENCFF509ZBB /home/drk/tillage/datasets/human/chip/encode/ENCSR595FWR/summary/ENCFF509ZBB.w5 32 2 mean CHIP:H3K27me3:fibroblast of breast female adult (17 years) CHIP ChIP-Histone:H3K27me3/fibroblast of breast female adult (17 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3291 0 ENCFF243OEH /home/drk/tillage/datasets/human/chip/encode/ENCSR595KPI/summary/ENCFF243OEH.w5 32 2 mean CHIP:H3K4me3:UCSF-4 CHIP ChIP-Histone:H3K4me3/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3292 0 ENCFF124MGU /home/drk/tillage/datasets/human/chip/encode/ENCSR596BHN/summary/ENCFF124MGU.w5 32 2 mean CHIP:H3K9me3:right cardiac atrium male adult (34 years) CHIP ChIP-Histone:H3K9me3/right cardiac atrium male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3293 0 ENCFF906KUK /home/drk/tillage/datasets/human/chip/encode/ENCSR596FEL/summary/ENCFF906KUK.w5 32 2 mean CHIP:3xFLAG-RBPJ:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RBPJ/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3294 0 ENCFF597XDB /home/drk/tillage/datasets/human/chip/encode/ENCSR596IKD/summary/ENCFF597XDB.w5 32 2 mean CHIP:eGFP-ETS2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ETS2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3295 0 ENCFF700DPA /home/drk/tillage/datasets/human/chip/encode/ENCSR596NOF/summary/ENCFF700DPA.w5 32 2 mean CHIP:H3K4me3:skeletal muscle myoblast male adult (22 years) CHIP ChIP-Histone:H3K4me3/skeletal muscle myoblast male adult (22 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3296 0 ENCFF548KBM /home/drk/tillage/datasets/human/chip/encode/ENCSR596PFU/summary/ENCFF548KBM.w5 32 2 mean CHIP:H3K27ac:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K27ac/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3297 0 ENCFF259FFL /home/drk/tillage/datasets/human/chip/encode/ENCSR597BWL/summary/ENCFF259FFL.w5 32 2 mean CHIP:H3K27ac:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K27ac/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3298 0 ENCFF660RWC /home/drk/tillage/datasets/human/chip/encode/ENCSR597RXT/summary/ENCFF660RWC.w5 32 2 mean CHIP:H3K36me3:mammary epithelial cell female adult (18 years) CHIP ChIP-Histone:H3K36me3/mammary epithelial cell female adult (18 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3299 0 ENCFF061BXV /home/drk/tillage/datasets/human/chip/encode/ENCSR597UDW/summary/ENCFF061BXV.w5 32 2 mean CHIP:H3K27ac:OCI-LY1 CHIP ChIP-Histone:H3K27ac/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3300 0 ENCFF829NYY /home/drk/tillage/datasets/human/chip/encode/ENCSR597ULV/summary/ENCFF829NYY.w5 32 2 mean CHIP:H3K27ac:VCaP CHIP ChIP-Histone:H3K27ac/VCaP ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3301 0 ENCFF328AZH /home/drk/tillage/datasets/human/chip/encode/ENCSR597VGC/summary/ENCFF328AZH.w5 32 2 mean CHIP:ETV6:GM12878 CHIP ChIP-TF:ETV6/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3302 0 ENCFF630KAJ /home/drk/tillage/datasets/human/chip/encode/ENCSR598AGY/summary/ENCFF630KAJ.w5 32 2 mean CHIP:H3K4me1:subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) CHIP ChIP-Histone:H3K4me1/subcutaneous abdominal adipose tissue nuclear fraction female adult (41 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3303 0 ENCFF642YKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR598GER/summary/ENCFF642YKQ.w5 32 2 mean CHIP:CCAR2:K562 CHIP ChIP-TF:CCAR2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3304 0 ENCFF257WVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR598TIR/summary/ENCFF257WVJ.w5 32 2 mean CHIP:eGFP-ZNF507:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF507/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3305 0 ENCFF714FHY /home/drk/tillage/datasets/human/chip/encode/ENCSR598UDU/summary/ENCFF714FHY.w5 32 2 mean CHIP:H2AK5ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H2AK5ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3306 0 ENCFF827REY /home/drk/tillage/datasets/human/chip/encode/ENCSR599EKW/summary/ENCFF827REY.w5 32 2 mean CHIP:H3K9me3:placenta female embryo (113 days) CHIP ChIP-Histone:H3K9me3/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3307 0 ENCFF419EMP /home/drk/tillage/datasets/human/chip/encode/ENCSR601OGE/summary/ENCFF419EMP.w5 32 2 mean CHIP:HNF4A:liver male adult (32 years) CHIP ChIP-TF:HNF4A/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3308 0 ENCFF114VUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR603REQ/summary/ENCFF114VUJ.w5 32 2 mean CHIP:PCBP2:K562 CHIP ChIP-TF:PCBP2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3309 0 ENCFF473CJP /home/drk/tillage/datasets/human/chip/encode/ENCSR603XLW/summary/ENCFF473CJP.w5 32 2 mean CHIP:eGFP-ZNF589:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF589/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3310 0 ENCFF818AGB /home/drk/tillage/datasets/human/chip/encode/ENCSR604CNJ/summary/ENCFF818AGB.w5 32 2 mean CHIP:eGFP-ZNF416:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF416/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3311 0 ENCFF207QAE /home/drk/tillage/datasets/human/chip/encode/ENCSR604III/summary/ENCFF207QAE.w5 32 2 mean CHIP:H3K79me2:Karpas-422 CHIP ChIP-Histone:H3K79me2/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3312 0 ENCFF020ZHY /home/drk/tillage/datasets/human/chip/encode/ENCSR604JDV/summary/ENCFF020ZHY.w5 32 2 mean CHIP:H3K27ac:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K27ac/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3313 0 ENCFF788ZYB /home/drk/tillage/datasets/human/chip/encode/ENCSR604JFH/summary/ENCFF788ZYB.w5 32 2 mean CHIP:H3K9me3:OCI-LY3 CHIP ChIP-Histone:H3K9me3/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3314 0 ENCFF588KME /home/drk/tillage/datasets/human/chip/encode/ENCSR604THF/summary/ENCFF588KME.w5 32 2 mean CHIP:H3K18ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K18ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3315 0 ENCFF453VLW /home/drk/tillage/datasets/human/chip/encode/ENCSR604UJV/summary/ENCFF453VLW.w5 32 2 mean CHIP:3xFLAG-IRF2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-IRF2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3316 0 ENCFF100XMW /home/drk/tillage/datasets/human/chip/encode/ENCSR604VWJ/summary/ENCFF100XMW.w5 32 2 mean CHIP:eGFP-KLF7:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF7/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3317 0 ENCFF052NHH /home/drk/tillage/datasets/human/chip/encode/ENCSR605MGM/summary/ENCFF052NHH.w5 32 2 mean CHIP:eGFP-SCRT1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SCRT1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3318 0 ENCFF535CDG /home/drk/tillage/datasets/human/chip/encode/ENCSR605NNZ/summary/ENCFF535CDG.w5 32 2 mean CHIP:H3K4me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K4me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3319 0 ENCFF092RSX /home/drk/tillage/datasets/human/chip/encode/ENCSR605OYC/summary/ENCFF092RSX.w5 32 2 mean CHIP:H3K9me3:peripheral blood mononuclear cell female adult (28 years) CHIP ChIP-Histone:H3K9me3/peripheral blood mononuclear cell female adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3320 0 ENCFF477RTV /home/drk/tillage/datasets/human/chip/encode/ENCSR605QAV/summary/ENCFF477RTV.w5 32 2 mean CHIP:H3K4me3:adrenal gland female adult (53 years) CHIP ChIP-Histone:H3K4me3/adrenal gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3321 0 ENCFF989CWU /home/drk/tillage/datasets/human/chip/encode/ENCSR605SXJ/summary/ENCFF989CWU.w5 32 2 mean CHIP:H3K36me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3322 0 ENCFF764LRI /home/drk/tillage/datasets/human/chip/encode/ENCSR605YWG/summary/ENCFF764LRI.w5 32 2 mean CHIP:TBX3:HepG2 CHIP ChIP-TF:TBX3/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3323 0 ENCFF469VIV /home/drk/tillage/datasets/human/chip/encode/ENCSR606TNN/summary/ENCFF469VIV.w5 32 2 mean CHIP:CTCF:vagina female adult (53 years) CHIP ChIP-TF:CTCF/vagina female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3324 0 ENCFF617MCD /home/drk/tillage/datasets/human/chip/encode/ENCSR606WJA/summary/ENCFF617MCD.w5 32 2 mean CHIP:H3K27ac:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3325 0 ENCFF078OGK /home/drk/tillage/datasets/human/chip/encode/ENCSR607ARN/summary/ENCFF078OGK.w5 32 2 mean CHIP:H3K4me3:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K4me3/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3326 0 ENCFF415CJV /home/drk/tillage/datasets/human/chip/encode/ENCSR608FDQ/summary/ENCFF415CJV.w5 32 2 mean CHIP:H3K27me3:spleen male child (3 years) CHIP ChIP-Histone:H3K27me3/spleen male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3327 0 ENCFF314TEX /home/drk/tillage/datasets/human/chip/encode/ENCSR608HVP/summary/ENCFF314TEX.w5 32 2 mean CHIP:eGFP-KLF13:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-KLF13/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3328 0 ENCFF864VYP /home/drk/tillage/datasets/human/chip/encode/ENCSR608VNA/summary/ENCFF864VYP.w5 32 2 mean CHIP:H3K4me3:neural cell CHIP ChIP-Histone:H3K4me3/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3329 0 ENCFF117OCW /home/drk/tillage/datasets/human/chip/encode/ENCSR608WPS/summary/ENCFF117OCW.w5 32 2 mean CHIP:CTCF:transverse colon male adult (37 years) CHIP ChIP-TF:CTCF/transverse colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3330 0 ENCFF682YSX /home/drk/tillage/datasets/human/chip/encode/ENCSR608XIG/summary/ENCFF682YSX.w5 32 2 mean CHIP:H3K27ac:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K27ac/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3331 0 ENCFF336ZFU /home/drk/tillage/datasets/human/chip/encode/ENCSR608XTF/summary/ENCFF336ZFU.w5 32 2 mean CHIP:RNF2:K562 CHIP ChIP-TF:RNF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3332 0 ENCFF859GUF /home/drk/tillage/datasets/human/chip/encode/ENCSR610EFT/summary/ENCFF859GUF.w5 32 2 mean CHIP:POLR2A:body of pancreas female adult (51 year) CHIP ChIP-TF:POLR2A/body of pancreas female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3333 0 ENCFF635CKC /home/drk/tillage/datasets/human/chip/encode/ENCSR610IIJ/summary/ENCFF635CKC.w5 32 2 mean CHIP:H3K36me3:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3334 0 ENCFF698BBP /home/drk/tillage/datasets/human/chip/encode/ENCSR611CRY/summary/ENCFF698BBP.w5 32 2 mean CHIP:H3K79me2:GM23248 CHIP ChIP-Histone:H3K79me2/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3335 0 ENCFF430NDD /home/drk/tillage/datasets/human/chip/encode/ENCSR611DJQ/summary/ENCFF430NDD.w5 32 2 mean CHIP:H3K4me3:testis male adult (37 years) CHIP ChIP-Histone:H3K4me3/testis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3336 0 ENCFF478HIR /home/drk/tillage/datasets/human/chip/encode/ENCSR611JJS/summary/ENCFF478HIR.w5 32 2 mean CHIP:CTCF:A673 CHIP ChIP-TF:CTCF/A673 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3337 0 ENCFF806EVC /home/drk/tillage/datasets/human/chip/encode/ENCSR611WZO/summary/ENCFF806EVC.w5 32 2 mean CHIP:SREBF2:HeLa-S3 CHIP ChIP-TF:SREBF2/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3338 0 ENCFF338MNH /home/drk/tillage/datasets/human/chip/encode/ENCSR611YUJ/summary/ENCFF338MNH.w5 32 2 mean CHIP:H3K27me3:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K27me3/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3339 0 ENCFF342YVM /home/drk/tillage/datasets/human/chip/encode/ENCSR612BWE/summary/ENCFF342YVM.w5 32 2 mean CHIP:H3K27ac:pancreas male adult (34 years) CHIP ChIP-Histone:H3K27ac/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3340 0 ENCFF073GYV /home/drk/tillage/datasets/human/chip/encode/ENCSR612MZB/summary/ENCFF073GYV.w5 32 2 mean CHIP:H3K9me3:trophoblast female embryo (20 weeks) CHIP ChIP-Histone:H3K9me3/trophoblast female embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3341 0 ENCFF578UME /home/drk/tillage/datasets/human/chip/encode/ENCSR613NUC/summary/ENCFF578UME.w5 32 2 mean CHIP:ARNT:K562 CHIP ChIP-TF:ARNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3342 0 ENCFF256PUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR614JFD/summary/ENCFF256PUQ.w5 32 2 mean CHIP:H3K9me3:right lobe of liver female adult (53 years) CHIP ChIP-Histone:H3K9me3/right lobe of liver female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3343 0 ENCFF590YLH /home/drk/tillage/datasets/human/chip/encode/ENCSR615HXA/summary/ENCFF590YLH.w5 32 2 mean CHIP:H3K27ac:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K27ac/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3344 0 ENCFF671XER /home/drk/tillage/datasets/human/chip/encode/ENCSR615PBJ/summary/ENCFF671XER.w5 32 2 mean CHIP:H3K27me3:angular gyrus male adult (81 year) CHIP ChIP-Histone:H3K27me3/angular gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3345 0 ENCFF626EKV /home/drk/tillage/datasets/human/chip/encode/ENCSR615YKN/summary/ENCFF626EKV.w5 32 2 mean CHIP:H3K4me1:UCSF-4 CHIP ChIP-Histone:H3K4me1/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3346 0 ENCFF290AKW /home/drk/tillage/datasets/human/chip/encode/ENCSR616MOB/summary/ENCFF290AKW.w5 32 2 mean CHIP:CBX8:A549 CHIP ChIP-TF:CBX8/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3347 0 ENCFF508TIU /home/drk/tillage/datasets/human/chip/encode/ENCSR616OSG/summary/ENCFF508TIU.w5 32 2 mean CHIP:3xFLAG-KLF11:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KLF11/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3348 0 ENCFF468GIA /home/drk/tillage/datasets/human/chip/encode/ENCSR616VTK/summary/ENCFF468GIA.w5 32 2 mean CHIP:H3K36me3:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K36me3/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3349 0 ENCFF648KAV /home/drk/tillage/datasets/human/chip/encode/ENCSR616WEG/summary/ENCFF648KAV.w5 32 2 mean CHIP:3xFLAG-HBP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HBP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3350 0 ENCFF032ZFY /home/drk/tillage/datasets/human/chip/encode/ENCSR617IFZ/summary/ENCFF032ZFY.w5 32 2 mean CHIP:eGFP-CTCF:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-CTCF/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3351 0 ENCFF395HFM /home/drk/tillage/datasets/human/chip/encode/ENCSR617RSQ/summary/ENCFF395HFM.w5 32 2 mean CHIP:EZH2phosphoT487:PC-3 CHIP ChIP-TF:EZH2phosphoT487/PC-3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3352 0 ENCFF410WYL /home/drk/tillage/datasets/human/chip/encode/ENCSR617SRM/summary/ENCFF410WYL.w5 32 2 mean CHIP:H3K4me1:lung female embryo (120 days) CHIP ChIP-Histone:H3K4me1/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3353 0 ENCFF387BYC /home/drk/tillage/datasets/human/chip/encode/ENCSR618GDK/summary/ENCFF387BYC.w5 32 2 mean CHIP:CEBPZ:K562 CHIP ChIP-TF:CEBPZ/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3354 0 ENCFF374NIY /home/drk/tillage/datasets/human/chip/encode/ENCSR618ICR/summary/ENCFF374NIY.w5 32 2 mean CHIP:RCOR1:A549 CHIP ChIP-TF:RCOR1/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3355 0 ENCFF293VSF /home/drk/tillage/datasets/human/chip/encode/ENCSR618QYE/summary/ENCFF293VSF.w5 32 2 mean CHIP:CTCF:stomach male adult (37 years) CHIP ChIP-TF:CTCF/stomach male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3356 0 ENCFF133MNV /home/drk/tillage/datasets/human/chip/encode/ENCSR619AAK/summary/ENCFF133MNV.w5 32 2 mean CHIP:H3K79me2:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K79me2/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3357 0 ENCFF472NPM /home/drk/tillage/datasets/human/chip/encode/ENCSR619GFP/summary/ENCFF472NPM.w5 32 2 mean CHIP:eGFP-HINFP:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-HINFP/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3358 0 ENCFF205ZOQ /home/drk/tillage/datasets/human/chip/encode/ENCSR619IUE/summary/ENCFF205ZOQ.w5 32 2 mean CHIP:CTCF:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:CTCF/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3359 0 ENCFF588XSZ /home/drk/tillage/datasets/human/chip/encode/ENCSR619OUC/summary/ENCFF588XSZ.w5 32 2 mean CHIP:eGFP-ZBTB6:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB6/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3360 0 ENCFF550YNT /home/drk/tillage/datasets/human/chip/encode/ENCSR619POC/summary/ENCFF550YNT.w5 32 2 mean CHIP:H3K27ac:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K27ac/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3361 0 ENCFF537WOR /home/drk/tillage/datasets/human/chip/encode/ENCSR619QFT/summary/ENCFF537WOR.w5 32 2 mean CHIP:eGFP-ZNF300:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF300/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3362 0 ENCFF483JCG /home/drk/tillage/datasets/human/chip/encode/ENCSR619YUY/summary/ENCFF483JCG.w5 32 2 mean CHIP:H3K36me3:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K36me3/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3363 0 ENCFF360CFP /home/drk/tillage/datasets/human/chip/encode/ENCSR620AZM/summary/ENCFF360CFP.w5 32 2 mean CHIP:H3K27ac:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K27ac/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3364 0 ENCFF993QJW /home/drk/tillage/datasets/human/chip/encode/ENCSR620DUQ/summary/ENCFF993QJW.w5 32 2 mean CHIP:CREB1:MCF-7 CHIP ChIP-TF:CREB1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3365 0 ENCFF610TBO /home/drk/tillage/datasets/human/chip/encode/ENCSR620TXL/summary/ENCFF610TBO.w5 32 2 mean CHIP:H3K4me3:adrenal gland male adult (37 years) CHIP ChIP-Histone:H3K4me3/adrenal gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3366 0 ENCFF641ZDT /home/drk/tillage/datasets/human/chip/encode/ENCSR620VIC/summary/ENCFF641ZDT.w5 32 2 mean CHIP:eGFP-CEBPG:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-CEBPG/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3367 0 ENCFF452XTX /home/drk/tillage/datasets/human/chip/encode/ENCSR620YNB/summary/ENCFF452XTX.w5 32 2 mean CHIP:KAT2B:HepG2 CHIP ChIP-TF:KAT2B/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3368 0 ENCFF540DKX /home/drk/tillage/datasets/human/chip/encode/ENCSR621ATC/summary/ENCFF540DKX.w5 32 2 mean CHIP:ZNF184:K562 CHIP ChIP-TF:ZNF184/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3369 0 ENCFF443VWK /home/drk/tillage/datasets/human/chip/encode/ENCSR621BZD/summary/ENCFF443VWK.w5 32 2 mean CHIP:H3K4me1:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K4me1/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3370 0 ENCFF090HJP /home/drk/tillage/datasets/human/chip/encode/ENCSR621EXD/summary/ENCFF090HJP.w5 32 2 mean CHIP:H3K36me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K36me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3371 0 ENCFF688KQB /home/drk/tillage/datasets/human/chip/encode/ENCSR621WQY/summary/ENCFF688KQB.w5 32 2 mean CHIP:H3K36me3:heart embryo (101 day) CHIP ChIP-Histone:H3K36me3/heart embryo (101 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3372 0 ENCFF867DUX /home/drk/tillage/datasets/human/chip/encode/ENCSR623GZY/summary/ENCFF867DUX.w5 32 2 mean CHIP:H3K79me2:DOHH2 CHIP ChIP-Histone:H3K79me2/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3373 0 ENCFF060SYK /home/drk/tillage/datasets/human/chip/encode/ENCSR623KNM/summary/ENCFF060SYK.w5 32 2 mean CHIP:ELK1:A549 CHIP ChIP-TF:ELK1/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3374 0 ENCFF813YZR /home/drk/tillage/datasets/human/chip/encode/ENCSR624GNZ/summary/ENCFF813YZR.w5 32 2 mean CHIP:SRSF9:HepG2 CHIP ChIP-TF:SRSF9/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3375 0 ENCFF829BOS /home/drk/tillage/datasets/human/chip/encode/ENCSR624YTO/summary/ENCFF829BOS.w5 32 2 mean CHIP:H3K9me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K9me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3376 0 ENCFF670MXH /home/drk/tillage/datasets/human/chip/encode/ENCSR625ORP/summary/ENCFF670MXH.w5 32 2 mean CHIP:SYNCRIP:HepG2 CHIP ChIP-TF:SYNCRIP/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3377 0 ENCFF131AUL /home/drk/tillage/datasets/human/chip/encode/ENCSR626QJQ/summary/ENCFF131AUL.w5 32 2 mean CHIP:CSDE1:K562 CHIP ChIP-TF:CSDE1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3378 0 ENCFF871IXB /home/drk/tillage/datasets/human/chip/encode/ENCSR626UPW/summary/ENCFF871IXB.w5 32 2 mean CHIP:H3K9ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K9ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3379 0 ENCFF304SIN /home/drk/tillage/datasets/human/chip/encode/ENCSR626VUC/summary/ENCFF304SIN.w5 32 2 mean CHIP:ETV6:GM12878 CHIP ChIP-TF:ETV6/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3380 0 ENCFF628RWE /home/drk/tillage/datasets/human/chip/encode/ENCSR627STE/summary/ENCFF628RWE.w5 32 2 mean CHIP:H3K27me3:brain male embryo (122 days) CHIP ChIP-Histone:H3K27me3/brain male embryo (122 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3381 0 ENCFF572FTV /home/drk/tillage/datasets/human/chip/encode/ENCSR627TNG/summary/ENCFF572FTV.w5 32 2 mean CHIP:H3K9me3:DOHH2 CHIP ChIP-Histone:H3K9me3/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3382 0 ENCFF288GPT /home/drk/tillage/datasets/human/chip/encode/ENCSR628APV/summary/ENCFF288GPT.w5 32 2 mean CHIP:MCM5:K562 CHIP ChIP-TF:MCM5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3383 0 ENCFF550HXP /home/drk/tillage/datasets/human/chip/encode/ENCSR628CTX/summary/ENCFF550HXP.w5 32 2 mean CHIP:H3K4me1:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K4me1/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3384 0 ENCFF870MXG /home/drk/tillage/datasets/human/chip/encode/ENCSR629RBC/summary/ENCFF870MXG.w5 32 2 mean CHIP:H3K36me3:placental basal plate male embryo (38 weeks) CHIP ChIP-Histone:H3K36me3/placental basal plate male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3385 0 ENCFF159IUM /home/drk/tillage/datasets/human/chip/encode/ENCSR629RJB/summary/ENCFF159IUM.w5 32 2 mean CHIP:H3K36me3:middle frontal area 46 female adult (75 years) CHIP ChIP-Histone:H3K36me3/middle frontal area 46 female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3386 0 ENCFF180NCY /home/drk/tillage/datasets/human/chip/encode/ENCSR629TDG/summary/ENCFF180NCY.w5 32 2 mean CHIP:H2AFZ:OCI-LY3 CHIP ChIP-TF:H2AFZ/OCI-LY3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3387 0 ENCFF693VUV /home/drk/tillage/datasets/human/chip/encode/ENCSR630IBN/summary/ENCFF693VUV.w5 32 2 mean CHIP:H3K4me1:KOPT-K1 CHIP ChIP-Histone:H3K4me1/KOPT-K1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3388 0 ENCFF564MDP /home/drk/tillage/datasets/human/chip/encode/ENCSR630LQO/summary/ENCFF564MDP.w5 32 2 mean CHIP:H3K27me3:regulatory T cell originated from blood cell CHIP ChIP-Histone:H3K27me3/regulatory T cell originated from blood cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3389 0 ENCFF240DRS /home/drk/tillage/datasets/human/chip/encode/ENCSR631BPS/summary/ENCFF240DRS.w5 32 2 mean CHIP:H3K4me1:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3390 0 ENCFF591KWL /home/drk/tillage/datasets/human/chip/encode/ENCSR631RJR/summary/ENCFF591KWL.w5 32 2 mean CHIP:H3K4me1:H1-hESC CHIP ChIP-Histone:H3K4me1/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3391 0 ENCFF844WBT /home/drk/tillage/datasets/human/chip/encode/ENCSR631WAA/summary/ENCFF844WBT.w5 32 2 mean CHIP:eGFP-ZBTB17:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB17/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3392 0 ENCFF021ELR /home/drk/tillage/datasets/human/chip/encode/ENCSR632DCH/summary/ENCFF021ELR.w5 32 2 mean CHIP:eGFP-ATF3:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ATF3/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3393 0 ENCFF469KTC /home/drk/tillage/datasets/human/chip/encode/ENCSR632OWD/summary/ENCFF469KTC.w5 32 2 mean CHIP:H3K4me3:urinary bladder male adult (34 years) CHIP ChIP-Histone:H3K4me3/urinary bladder male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3394 0 ENCFF837FTN /home/drk/tillage/datasets/human/chip/encode/ENCSR632QHJ/summary/ENCFF837FTN.w5 32 2 mean CHIP:H3K4me1:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K4me1/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3395 0 ENCFF893XQZ /home/drk/tillage/datasets/human/chip/encode/ENCSR632SHZ/summary/ENCFF893XQZ.w5 32 2 mean CHIP:eGFP-NFE2L1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NFE2L1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3396 0 ENCFF934EVF /home/drk/tillage/datasets/human/chip/encode/ENCSR632SIM/summary/ENCFF934EVF.w5 32 2 mean CHIP:eGFP-ZFHX2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZFHX2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3397 0 ENCFF210NDG /home/drk/tillage/datasets/human/chip/encode/ENCSR632TJQ/summary/ENCFF210NDG.w5 32 2 mean CHIP:ILF3:K562 CHIP ChIP-TF:ILF3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3398 0 ENCFF255VXF /home/drk/tillage/datasets/human/chip/encode/ENCSR633EIC/summary/ENCFF255VXF.w5 32 2 mean CHIP:3xFLAG-PBX2:K562 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-PBX2/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3399 0 ENCFF068MCQ /home/drk/tillage/datasets/human/chip/encode/ENCSR633OEO/summary/ENCFF068MCQ.w5 32 2 mean CHIP:POLR2AphosphoS5:sigmoid colon female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/sigmoid colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3400 0 ENCFF851YMO /home/drk/tillage/datasets/human/chip/encode/ENCSR633OVO/summary/ENCFF851YMO.w5 32 2 mean CHIP:3xFLAG-RFX3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RFX3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3401 0 ENCFF902CLH /home/drk/tillage/datasets/human/chip/encode/ENCSR634IIF/summary/ENCFF902CLH.w5 32 2 mean CHIP:H2BK12ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H2BK12ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3402 0 ENCFF021OWW /home/drk/tillage/datasets/human/chip/encode/ENCSR634MAK/summary/ENCFF021OWW.w5 32 2 mean CHIP:H3K27me3:HUES64 CHIP ChIP-Histone:H3K27me3/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3403 0 ENCFF175OKQ /home/drk/tillage/datasets/human/chip/encode/ENCSR634OAQ/summary/ENCFF175OKQ.w5 32 2 mean CHIP:CTCF:NCI-H929 CHIP ChIP-TF:CTCF/NCI-H929 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3404 0 ENCFF538PUA /home/drk/tillage/datasets/human/chip/encode/ENCSR634ZGP/summary/ENCFF538PUA.w5 32 2 mean CHIP:UBTF:HeLa-S3 CHIP ChIP-TF:UBTF/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3405 0 ENCFF963EIT /home/drk/tillage/datasets/human/chip/encode/ENCSR635EXI/summary/ENCFF963EIT.w5 32 2 mean CHIP:ZSCAN29:K562 CHIP ChIP-TF:ZSCAN29/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3406 0 ENCFF923VES /home/drk/tillage/datasets/human/chip/encode/ENCSR635GTR/summary/ENCFF923VES.w5 32 2 mean CHIP:eGFP-TEAD2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-TEAD2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3407 0 ENCFF639MGL /home/drk/tillage/datasets/human/chip/encode/ENCSR635NOQ/summary/ENCFF639MGL.w5 32 2 mean CHIP:eGFP-KLF8:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF8/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3408 0 ENCFF303ZNL /home/drk/tillage/datasets/human/chip/encode/ENCSR635OSG/summary/ENCFF303ZNL.w5 32 2 mean CHIP:RAD21:liver female child (6 years) and male adult (32 years) CHIP ChIP-TF:RAD21/liver female child (6 years) and male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3409 0 ENCFF155JOU /home/drk/tillage/datasets/human/chip/encode/ENCSR635XBA/summary/ENCFF155JOU.w5 32 2 mean CHIP:H3K36me3:mammary stem cell CHIP ChIP-Histone:H3K36me3/mammary stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3410 0 ENCFF780PVG /home/drk/tillage/datasets/human/chip/encode/ENCSR635XLM/summary/ENCFF780PVG.w5 32 2 mean CHIP:EP300:upper lobe of left lung female adult (53 years) CHIP ChIP-TF:EP300/upper lobe of left lung female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3411 0 ENCFF396IQS /home/drk/tillage/datasets/human/chip/encode/ENCSR636EYA/summary/ENCFF396IQS.w5 32 2 mean CHIP:CTBP1:MCF-7 CHIP ChIP-TF:CTBP1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3412 0 ENCFF886MRR /home/drk/tillage/datasets/human/chip/encode/ENCSR636FCX/summary/ENCFF886MRR.w5 32 2 mean CHIP:H3K27me3:myoepithelial cell of mammary gland female adult (33 years) CHIP ChIP-Histone:H3K27me3/myoepithelial cell of mammary gland female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3413 0 ENCFF952VBL /home/drk/tillage/datasets/human/chip/encode/ENCSR636IDR/summary/ENCFF952VBL.w5 32 2 mean CHIP:H3K9me3:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K9me3/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3414 0 ENCFF936AEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR636MKU/summary/ENCFF936AEZ.w5 32 2 mean CHIP:BACH1:GM12878 CHIP ChIP-TF:BACH1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3415 0 ENCFF866CZX /home/drk/tillage/datasets/human/chip/encode/ENCSR636YLV/summary/ENCFF866CZX.w5 32 2 mean CHIP:MAZ:A549 CHIP ChIP-TF:MAZ/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3416 0 ENCFF875FWQ /home/drk/tillage/datasets/human/chip/encode/ENCSR637IOH/summary/ENCFF875FWQ.w5 32 2 mean CHIP:H3K27me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3417 0 ENCFF876DXW /home/drk/tillage/datasets/human/chip/encode/ENCSR637QAM/summary/ENCFF876DXW.w5 32 2 mean CHIP:TRIM22:GM12878 CHIP ChIP-TF:TRIM22/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3418 0 ENCFF435FIF /home/drk/tillage/datasets/human/chip/encode/ENCSR637RLN/summary/ENCFF435FIF.w5 32 2 mean CHIP:H3K27me3:hepatocyte originated from H9 CHIP ChIP-Histone:H3K27me3/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3419 0 ENCFF939CTN /home/drk/tillage/datasets/human/chip/encode/ENCSR638FRE/summary/ENCFF939CTN.w5 32 2 mean CHIP:H3K36me3:OCI-LY3 CHIP ChIP-Histone:H3K36me3/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3420 0 ENCFF183CWI /home/drk/tillage/datasets/human/chip/encode/ENCSR638HSG/summary/ENCFF183CWI.w5 32 2 mean CHIP:H3K4me1:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K4me1/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3421 0 ENCFF383OZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR638QHV/summary/ENCFF383OZJ.w5 32 2 mean CHIP:ELF4:K562 CHIP ChIP-TF:ELF4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3422 0 ENCFF263SSR /home/drk/tillage/datasets/human/chip/encode/ENCSR638QYO/summary/ENCFF263SSR.w5 32 2 mean CHIP:SREBF2:A549 CHIP ChIP-TF:SREBF2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3423 0 ENCFF051XRB /home/drk/tillage/datasets/human/chip/encode/ENCSR639GWS/summary/ENCFF051XRB.w5 32 2 mean CHIP:KDM1A:A549 CHIP ChIP-TF:KDM1A/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3424 0 ENCFF783KDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR639HVJ/summary/ENCFF783KDZ.w5 32 2 mean CHIP:H3K27me3:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K27me3/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3425 0 ENCFF995KYW /home/drk/tillage/datasets/human/chip/encode/ENCSR639IIZ/summary/ENCFF995KYW.w5 32 2 mean CHIP:3xFLAG-CEBPG:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-CEBPG/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3426 0 ENCFF268DUW /home/drk/tillage/datasets/human/chip/encode/ENCSR639NMN/summary/ENCFF268DUW.w5 32 2 mean CHIP:H3K4me1:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K4me1/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3427 0 ENCFF103NJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR639RHG/summary/ENCFF103NJQ.w5 32 2 mean CHIP:H4K20me1:MCF-7 CHIP ChIP-TF:H4K20me1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3428 0 ENCFF377JMB /home/drk/tillage/datasets/human/chip/encode/ENCSR639RKZ/summary/ENCFF377JMB.w5 32 2 mean CHIP:H3K9me3:stomach male adult (34 years) CHIP ChIP-Histone:H3K9me3/stomach male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3429 0 ENCFF253WKZ /home/drk/tillage/datasets/human/chip/encode/ENCSR640XRV/summary/ENCFF253WKZ.w5 32 2 mean CHIP:H3K27ac:transverse colon male adult (37 years) CHIP ChIP-Histone:H3K27ac/transverse colon male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3430 0 ENCFF849NJM /home/drk/tillage/datasets/human/chip/encode/ENCSR641BSL/summary/ENCFF849NJM.w5 32 2 mean CHIP:AGO1:K562 CHIP ChIP-TF:AGO1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3431 0 ENCFF722OSG /home/drk/tillage/datasets/human/chip/encode/ENCSR641RQV/summary/ENCFF722OSG.w5 32 2 mean CHIP:H3K27me3:esophagus female adult (30 years) CHIP ChIP-Histone:H3K27me3/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3432 0 ENCFF144KMG /home/drk/tillage/datasets/human/chip/encode/ENCSR642HHF/summary/ENCFF144KMG.w5 32 2 mean CHIP:H3K27ac:adrenal gland female adult (30 years) CHIP ChIP-Histone:H3K27ac/adrenal gland female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3433 0 ENCFF063HVC /home/drk/tillage/datasets/human/chip/encode/ENCSR642HII/summary/ENCFF063HVC.w5 32 2 mean CHIP:H3K4me1:liver female adult (25 years) CHIP ChIP-Histone:H3K4me1/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3434 0 ENCFF112GHP /home/drk/tillage/datasets/human/chip/encode/ENCSR642VZY/summary/ENCFF112GHP.w5 32 2 mean CHIP:KDM4B:K562 CHIP ChIP-TF:KDM4B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3435 0 ENCFF922CAD /home/drk/tillage/datasets/human/chip/encode/ENCSR643KID/summary/ENCFF922CAD.w5 32 2 mean CHIP:H3K27me3:transverse colon male adult (37 years) CHIP ChIP-Histone:H3K27me3/transverse colon male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3436 0 ENCFF266YLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR643TBI/summary/ENCFF266YLQ.w5 32 2 mean CHIP:H3K27ac:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K27ac/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3437 0 ENCFF405KAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR643ULB/summary/ENCFF405KAZ.w5 32 2 mean CHIP:H3K9ac:kidney male adult (67 years) CHIP ChIP-Histone:H3K9ac/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3438 0 ENCFF745GLK /home/drk/tillage/datasets/human/chip/encode/ENCSR643VTW/summary/ENCFF745GLK.w5 32 2 mean CHIP:SMARCA4:K562 CHIP ChIP-TF:SMARCA4/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3439 0 ENCFF072BUM /home/drk/tillage/datasets/human/chip/encode/ENCSR645BCH/summary/ENCFF072BUM.w5 32 2 mean CHIP:H3K4me2:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K4me2/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3440 0 ENCFF757WJJ /home/drk/tillage/datasets/human/chip/encode/ENCSR645FBM/summary/ENCFF757WJJ.w5 32 2 mean CHIP:H3K4me3:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K4me3/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3441 0 ENCFF108IFR /home/drk/tillage/datasets/human/chip/encode/ENCSR645JVW/summary/ENCFF108IFR.w5 32 2 mean CHIP:POLR2AphosphoS5:vagina female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/vagina female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3442 0 ENCFF112FHC /home/drk/tillage/datasets/human/chip/encode/ENCSR645NLL/summary/ENCFF112FHC.w5 32 2 mean CHIP:H3K27me3:duodenal mucosa male adult (76 years) CHIP ChIP-Histone:H3K27me3/duodenal mucosa male adult (76 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3443 0 ENCFF260CLC /home/drk/tillage/datasets/human/chip/encode/ENCSR645QZT/summary/ENCFF260CLC.w5 32 2 mean CHIP:H3K36me3:thymus female embryo (110 days) CHIP ChIP-Histone:H3K36me3/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3444 0 ENCFF620QPO /home/drk/tillage/datasets/human/chip/encode/ENCSR645SYH/summary/ENCFF620QPO.w5 32 2 mean CHIP:H3K27ac:esophagus female adult (30 years) CHIP ChIP-Histone:H3K27ac/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3445 0 ENCFF518GSE /home/drk/tillage/datasets/human/chip/encode/ENCSR646YBA/summary/ENCFF518GSE.w5 32 2 mean CHIP:H3K36me3:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K36me3/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3446 0 ENCFF098CBY /home/drk/tillage/datasets/human/chip/encode/ENCSR647ZXA/summary/ENCFF098CBY.w5 32 2 mean CHIP:eGFP-MEF2D:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-MEF2D/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3447 0 ENCFF524GCL /home/drk/tillage/datasets/human/chip/encode/ENCSR648INT/summary/ENCFF524GCL.w5 32 2 mean CHIP:eGFP-ILK:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ILK/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3448 0 ENCFF802VGK /home/drk/tillage/datasets/human/chip/encode/ENCSR649FAP/summary/ENCFF802VGK.w5 32 2 mean CHIP:H3K36me3:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3449 0 ENCFF033FFU /home/drk/tillage/datasets/human/chip/encode/ENCSR651IVN/summary/ENCFF033FFU.w5 32 2 mean CHIP:H3K9me3:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K9me3/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3450 0 ENCFF794EFO /home/drk/tillage/datasets/human/chip/encode/ENCSR651JDA/summary/ENCFF794EFO.w5 32 2 mean CHIP:H3K36me3:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K36me3/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3451 0 ENCFF837UHE /home/drk/tillage/datasets/human/chip/encode/ENCSR651SVZ/summary/ENCFF837UHE.w5 32 2 mean CHIP:H2BK5ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H2BK5ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3452 0 ENCFF852WXE /home/drk/tillage/datasets/human/chip/encode/ENCSR652QNW/summary/ENCFF852WXE.w5 32 2 mean CHIP:H3K4me3:cardiac muscle cell CHIP ChIP-Histone:H3K4me3/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3453 0 ENCFF996AGB /home/drk/tillage/datasets/human/chip/encode/ENCSR654CQU/summary/ENCFF996AGB.w5 32 2 mean CHIP:SNIP1:K562 CHIP ChIP-TF:SNIP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3454 0 ENCFF870PDE /home/drk/tillage/datasets/human/chip/encode/ENCSR654ORQ/summary/ENCFF870PDE.w5 32 2 mean CHIP:3xFLAG-SLC30A9:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SLC30A9/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3455 0 ENCFF804IIT /home/drk/tillage/datasets/human/chip/encode/ENCSR654VRX/summary/ENCFF804IIT.w5 32 2 mean CHIP:H3K27me3:neural cell CHIP ChIP-Histone:H3K27me3/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3456 0 ENCFF028ZYN /home/drk/tillage/datasets/human/chip/encode/ENCSR655ECZ/summary/ENCFF028ZYN.w5 32 2 mean CHIP:CTCF:vagina female adult (51 year) CHIP ChIP-TF:CTCF/vagina female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3457 0 ENCFF087KLN /home/drk/tillage/datasets/human/chip/encode/ENCSR655XLM/summary/ENCFF087KLN.w5 32 2 mean CHIP:H3K27ac:small intestine female adult (30 years) CHIP ChIP-Histone:H3K27ac/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3458 0 ENCFF744DQP /home/drk/tillage/datasets/human/chip/encode/ENCSR656JZL/summary/ENCFF744DQP.w5 32 2 mean CHIP:3xFLAG-HHEX:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HHEX/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3459 0 ENCFF516ALS /home/drk/tillage/datasets/human/chip/encode/ENCSR656MXA/summary/ENCFF516ALS.w5 32 2 mean CHIP:EZH2phosphoT487:neural progenitor cell originated from H9 CHIP ChIP-TF:EZH2phosphoT487/neural progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3460 0 ENCFF866FPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR656PGJ/summary/ENCFF866FPZ.w5 32 2 mean CHIP:H3K27ac:UCSF-4 CHIP ChIP-Histone:H3K27ac/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3461 0 ENCFF322AOQ /home/drk/tillage/datasets/human/chip/encode/ENCSR656SIB/summary/ENCFF322AOQ.w5 32 2 mean CHIP:3xFLAG-ZBED5:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZBED5/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3462 0 ENCFF881WBN /home/drk/tillage/datasets/human/chip/encode/ENCSR656ZEQ/summary/ENCFF881WBN.w5 32 2 mean CHIP:H3K27ac:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K27ac/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3463 0 ENCFF984QGK /home/drk/tillage/datasets/human/chip/encode/ENCSR657DYL/summary/ENCFF984QGK.w5 32 2 mean CHIP:H3K4me3:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K4me3/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3464 0 ENCFF595VMB /home/drk/tillage/datasets/human/chip/encode/ENCSR657EOF/summary/ENCFF595VMB.w5 32 2 mean CHIP:NFRKB:K562 CHIP ChIP-TF:NFRKB/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3465 0 ENCFF266DPA /home/drk/tillage/datasets/human/chip/encode/ENCSR657JLK/summary/ENCFF266DPA.w5 32 2 mean CHIP:SIN3B:K562 CHIP ChIP-TF:SIN3B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3466 0 ENCFF919ISB /home/drk/tillage/datasets/human/chip/encode/ENCSR657OGA/summary/ENCFF919ISB.w5 32 2 mean CHIP:H3K9me3:SK-N-SH CHIP ChIP-Histone:H3K9me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3467 0 ENCFF917YSR /home/drk/tillage/datasets/human/chip/encode/ENCSR657PEW/summary/ENCFF917YSR.w5 32 2 mean CHIP:LARP7:GM12878 CHIP ChIP-TF:LARP7/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3468 0 ENCFF280RTW /home/drk/tillage/datasets/human/chip/encode/ENCSR657RRI/summary/ENCFF280RTW.w5 32 2 mean CHIP:H3K4me3:Loucy CHIP ChIP-Histone:H3K4me3/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3469 0 ENCFF376JMO /home/drk/tillage/datasets/human/chip/encode/ENCSR657SQM/summary/ENCFF376JMO.w5 32 2 mean CHIP:H3K4me1:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3470 0 ENCFF410TJB /home/drk/tillage/datasets/human/chip/encode/ENCSR658VPF/summary/ENCFF410TJB.w5 32 2 mean CHIP:H3K9me3:thyroid gland female adult (53 years) CHIP ChIP-Histone:H3K9me3/thyroid gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3471 0 ENCFF468WLM /home/drk/tillage/datasets/human/chip/encode/ENCSR658WFQ/summary/ENCFF468WLM.w5 32 2 mean CHIP:NCOA1:K562 CHIP ChIP-TF:NCOA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3472 0 ENCFF122PSF /home/drk/tillage/datasets/human/chip/encode/ENCSR659FAS/summary/ENCFF122PSF.w5 32 2 mean CHIP:H3K4me3:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K4me3/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3473 0 ENCFF543YLG /home/drk/tillage/datasets/human/chip/encode/ENCSR659LJJ/summary/ENCFF543YLG.w5 32 2 mean CHIP:HDAC2:A549 CHIP ChIP-TF:HDAC2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3474 0 ENCFF618JDV /home/drk/tillage/datasets/human/chip/encode/ENCSR659MYS/summary/ENCFF618JDV.w5 32 2 mean CHIP:H3K36me3:ovary female adult (30 years) CHIP ChIP-Histone:H3K36me3/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3475 0 ENCFF851RBH /home/drk/tillage/datasets/human/chip/encode/ENCSR659RHV/summary/ENCFF851RBH.w5 32 2 mean CHIP:H3K27ac:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K27ac/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3476 0 ENCFF179TJW /home/drk/tillage/datasets/human/chip/encode/ENCSR659RJP/summary/ENCFF179TJW.w5 32 2 mean CHIP:H3K4me1:spleen female adult (53 years) CHIP ChIP-Histone:H3K4me1/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3477 0 ENCFF154JTJ /home/drk/tillage/datasets/human/chip/encode/ENCSR659SCK/summary/ENCFF154JTJ.w5 32 2 mean CHIP:TOE1:HepG2 CHIP ChIP-TF:TOE1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3478 0 ENCFF746SWH /home/drk/tillage/datasets/human/chip/encode/ENCSR660IQS/summary/ENCFF746SWH.w5 32 2 mean CHIP:H3K27ac:Karpas-422 CHIP ChIP-Histone:H3K27ac/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3479 0 ENCFF595SQU /home/drk/tillage/datasets/human/chip/encode/ENCSR660KHZ/summary/ENCFF595SQU.w5 32 2 mean CHIP:H3K4me3:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K4me3/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3480 0 ENCFF147WWK /home/drk/tillage/datasets/human/chip/encode/ENCSR660RNO/summary/ENCFF147WWK.w5 32 2 mean CHIP:KDM4B:K562 CHIP ChIP-TF:KDM4B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3481 0 ENCFF497TFP /home/drk/tillage/datasets/human/chip/encode/ENCSR660RYC/summary/ENCFF497TFP.w5 32 2 mean CHIP:H3K9me3:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K9me3/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3482 0 ENCFF910NPA /home/drk/tillage/datasets/human/chip/encode/ENCSR660WQO/summary/ENCFF910NPA.w5 32 2 mean CHIP:H3K4me1:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me1/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3483 0 ENCFF037GZN /home/drk/tillage/datasets/human/chip/encode/ENCSR661AXW/summary/ENCFF037GZN.w5 32 2 mean CHIP:eGFP-ZNF169:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF169/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3484 0 ENCFF840FTR /home/drk/tillage/datasets/human/chip/encode/ENCSR661BMA/summary/ENCFF840FTR.w5 32 2 mean CHIP:H3K4me1:SK-N-SH CHIP ChIP-Histone:H3K4me1/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3485 0 ENCFF984WLE /home/drk/tillage/datasets/human/chip/encode/ENCSR661KMA/summary/ENCFF984WLE.w5 32 2 mean CHIP:H3K27ac:HCT116 CHIP ChIP-Histone:H3K27ac/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3486 0 ENCFF651TUQ /home/drk/tillage/datasets/human/chip/encode/ENCSR661MUS/summary/ENCFF651TUQ.w5 32 2 mean CHIP:H3K4me3:neural progenitor cell originated from H9 CHIP ChIP-Histone:H3K4me3/neural progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3487 0 ENCFF009LCG /home/drk/tillage/datasets/human/chip/encode/ENCSR661NXJ/summary/ENCFF009LCG.w5 32 2 mean CHIP:CTCF:breast epithelium female adult (51 year) CHIP ChIP-TF:CTCF/breast epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3488 0 ENCFF328CQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR661XNQ/summary/ENCFF328CQQ.w5 32 2 mean CHIP:CTCF:gastroesophageal sphincter male adult (54 years) CHIP ChIP-TF:CTCF/gastroesophageal sphincter male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3489 0 ENCFF027EMM /home/drk/tillage/datasets/human/chip/encode/ENCSR662EOU/summary/ENCFF027EMM.w5 32 2 mean CHIP:3xFLAG-NR2F1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NR2F1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3490 0 ENCFF319LDF /home/drk/tillage/datasets/human/chip/encode/ENCSR662PLB/summary/ENCFF319LDF.w5 32 2 mean CHIP:H3K4me3:neuroepithelial stem cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K4me3/neuroepithelial stem cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3491 0 ENCFF600PQH /home/drk/tillage/datasets/human/chip/encode/ENCSR663WAR/summary/ENCFF600PQH.w5 32 2 mean CHIP:REST:H1-hESC CHIP ChIP-TF:REST/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3492 0 ENCFF030VXP /home/drk/tillage/datasets/human/chip/encode/ENCSR663ZZZ/summary/ENCFF030VXP.w5 32 2 mean CHIP:MNT:MCF-7 CHIP ChIP-TF:MNT/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3493 0 ENCFF408UAY /home/drk/tillage/datasets/human/chip/encode/ENCSR664AOA/summary/ENCFF408UAY.w5 32 2 mean CHIP:TRIM25:K562 CHIP ChIP-TF:TRIM25/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3494 0 ENCFF404GUH /home/drk/tillage/datasets/human/chip/encode/ENCSR664KWY/summary/ENCFF404GUH.w5 32 2 mean CHIP:H3K4me1:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K4me1/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3495 0 ENCFF090ZGT /home/drk/tillage/datasets/human/chip/encode/ENCSR664OKA/summary/ENCFF090ZGT.w5 32 2 mean CHIP:ELK1:IMR-90 CHIP ChIP-TF:ELK1/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3496 0 ENCFF646WIH /home/drk/tillage/datasets/human/chip/encode/ENCSR664RRY/summary/ENCFF646WIH.w5 32 2 mean CHIP:H3K4me1:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K4me1/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3497 0 ENCFF844JCE /home/drk/tillage/datasets/human/chip/encode/ENCSR665KYH/summary/ENCFF844JCE.w5 32 2 mean CHIP:eGFP-ZNF521:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF521/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3498 0 ENCFF750WPB /home/drk/tillage/datasets/human/chip/encode/ENCSR665UFC/summary/ENCFF750WPB.w5 32 2 mean CHIP:3xFLAG-ZNF639:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF639/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3499 0 ENCFF476YVH /home/drk/tillage/datasets/human/chip/encode/ENCSR666FYM/summary/ENCFF476YVH.w5 32 2 mean CHIP:H3K27me3:liver male adult (32 years) CHIP ChIP-Histone:H3K27me3/liver male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3500 0 ENCFF464BRV /home/drk/tillage/datasets/human/chip/encode/ENCSR666QNP/summary/ENCFF464BRV.w5 32 2 mean CHIP:3xFLAG-TEAD3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-TEAD3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3501 0 ENCFF061ZZS /home/drk/tillage/datasets/human/chip/encode/ENCSR666TFS/summary/ENCFF061ZZS.w5 32 2 mean CHIP:H3K27ac:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K27ac/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3502 0 ENCFF820MYI /home/drk/tillage/datasets/human/chip/encode/ENCSR666TSJ/summary/ENCFF820MYI.w5 32 2 mean CHIP:H3K9ac:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K9ac/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3503 0 ENCFF502AUB /home/drk/tillage/datasets/human/chip/encode/ENCSR667UWT/summary/ENCFF502AUB.w5 32 2 mean CHIP:POLR2A:transverse colon male adult (37 years) CHIP ChIP-TF:POLR2A/transverse colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3504 0 ENCFF075CNP /home/drk/tillage/datasets/human/chip/encode/ENCSR668BTN/summary/ENCFF075CNP.w5 32 2 mean CHIP:CTCF:thoracic aorta male adult (37 years) CHIP ChIP-TF:CTCF/thoracic aorta male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3505 0 ENCFF653IYA /home/drk/tillage/datasets/human/chip/encode/ENCSR668GKQ/summary/ENCFF653IYA.w5 32 2 mean CHIP:H3K9me3:mammary epithelial cell female adult (18 years) CHIP ChIP-Histone:H3K9me3/mammary epithelial cell female adult (18 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3506 0 ENCFF644XAH /home/drk/tillage/datasets/human/chip/encode/ENCSR668HOP/summary/ENCFF644XAH.w5 32 2 mean CHIP:eGFP-ZNF580:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF580/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3507 0 ENCFF525ZRM /home/drk/tillage/datasets/human/chip/encode/ENCSR668LDD/summary/ENCFF525ZRM.w5 32 2 mean CHIP:H3K4me3:K562 CHIP ChIP-Histone:H3K4me3/K562 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3508 0 ENCFF597BTG /home/drk/tillage/datasets/human/chip/encode/ENCSR668NXG/summary/ENCFF597BTG.w5 32 2 mean CHIP:H3K4me1:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K4me1/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3509 0 ENCFF450KFO /home/drk/tillage/datasets/human/chip/encode/ENCSR669GUM/summary/ENCFF450KFO.w5 32 2 mean CHIP:eGFP-ZNF404:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF404/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3510 0 ENCFF864ZRY /home/drk/tillage/datasets/human/chip/encode/ENCSR669LCD/summary/ENCFF864ZRY.w5 32 2 mean CHIP:3xFLAG-ATF4:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ATF4/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3511 0 ENCFF806CWA /home/drk/tillage/datasets/human/chip/encode/ENCSR669NFS/summary/ENCFF806CWA.w5 32 2 mean CHIP:ARNT:K562 CHIP ChIP-TF:ARNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3512 0 ENCFF273ZXW /home/drk/tillage/datasets/human/chip/encode/ENCSR670FDA/summary/ENCFF273ZXW.w5 32 2 mean CHIP:NFATC3:K562 CHIP ChIP-TF:NFATC3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3513 0 ENCFF169OTC /home/drk/tillage/datasets/human/chip/encode/ENCSR670JDQ/summary/ENCFF169OTC.w5 32 2 mean CHIP:RB1:K562 CHIP ChIP-TF:RB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3514 0 ENCFF367BNC /home/drk/tillage/datasets/human/chip/encode/ENCSR670YPQ/summary/ENCFF367BNC.w5 32 2 mean CHIP:3xFLAG-DMAP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-DMAP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3515 0 ENCFF776IPC /home/drk/tillage/datasets/human/chip/encode/ENCSR671BOA/summary/ENCFF776IPC.w5 32 2 mean CHIP:H3K4me1:right cardiac atrium male adult (34 years) CHIP ChIP-Histone:H3K4me1/right cardiac atrium male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3516 0 ENCFF446TLB /home/drk/tillage/datasets/human/chip/encode/ENCSR671GFC/summary/ENCFF446TLB.w5 32 2 mean CHIP:eGFP-TAF7:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-TAF7/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3517 0 ENCFF869ICH /home/drk/tillage/datasets/human/chip/encode/ENCSR671JMQ/summary/ENCFF869ICH.w5 32 2 mean CHIP:H3K9me3:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K9me3/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3518 0 ENCFF345TBP /home/drk/tillage/datasets/human/chip/encode/ENCSR671NXL/summary/ENCFF345TBP.w5 32 2 mean CHIP:H3K36me3:lung female adult (30 years) CHIP ChIP-Histone:H3K36me3/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3519 0 ENCFF725BQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR671WZX/summary/ENCFF725BQQ.w5 32 2 mean CHIP:H3K27me3:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K27me3/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3520 0 ENCFF982BRX /home/drk/tillage/datasets/human/chip/encode/ENCSR672FMZ/summary/ENCFF982BRX.w5 32 2 mean CHIP:H3K9ac:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K9ac/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3521 0 ENCFF981JQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR672HBY/summary/ENCFF981JQQ.w5 32 2 mean CHIP:H3F3A:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3F3A/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3522 0 ENCFF440QGE /home/drk/tillage/datasets/human/chip/encode/ENCSR672XZZ/summary/ENCFF440QGE.w5 32 2 mean CHIP:H3K4me2:IMR-90 CHIP ChIP-Histone:H3K4me2/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3523 0 ENCFF968LVP /home/drk/tillage/datasets/human/chip/encode/ENCSR673JYT/summary/ENCFF968LVP.w5 32 2 mean CHIP:H3K36me3:aorta male adult (34 years) CHIP ChIP-Histone:H3K36me3/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3524 0 ENCFF615CPD /home/drk/tillage/datasets/human/chip/encode/ENCSR673OPX/summary/ENCFF615CPD.w5 32 2 mean CHIP:H3K9me3:GM23248 CHIP ChIP-Histone:H3K9me3/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3525 0 ENCFF531LMY /home/drk/tillage/datasets/human/chip/encode/ENCSR673SGK/summary/ENCFF531LMY.w5 32 2 mean CHIP:eGFP-BCL6B:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-BCL6B/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3526 0 ENCFF376FKS /home/drk/tillage/datasets/human/chip/encode/ENCSR673WZL/summary/ENCFF376FKS.w5 32 2 mean CHIP:CTCF:LNCAP treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours CHIP ChIP-TF:CTCF/LNCAP treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3527 0 ENCFF390BAT /home/drk/tillage/datasets/human/chip/encode/ENCSR673XMI/summary/ENCFF390BAT.w5 32 2 mean CHIP:H3K27me3:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3528 0 ENCFF503RHD /home/drk/tillage/datasets/human/chip/encode/ENCSR674IEI/summary/ENCFF503RHD.w5 32 2 mean CHIP:POLR2A:upper lobe of left lung male adult (37 years) CHIP ChIP-TF:POLR2A/upper lobe of left lung male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3529 0 ENCFF154ICY /home/drk/tillage/datasets/human/chip/encode/ENCSR674SCQ/summary/ENCFF154ICY.w5 32 2 mean CHIP:eGFP-ZNF354B:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF354B/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3530 0 ENCFF719VWH /home/drk/tillage/datasets/human/chip/encode/ENCSR674VPA/summary/ENCFF719VWH.w5 32 2 mean CHIP:H3K27ac:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27ac/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3531 0 ENCFF897EBK /home/drk/tillage/datasets/human/chip/encode/ENCSR675EXE/summary/ENCFF897EBK.w5 32 2 mean CHIP:H3K27me3:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K27me3/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3532 0 ENCFF114DFQ /home/drk/tillage/datasets/human/chip/encode/ENCSR675FLJ/summary/ENCFF114DFQ.w5 32 2 mean CHIP:H4K5ac:H1-hESC CHIP ChIP-TF:H4K5ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3533 0 ENCFF837HCK /home/drk/tillage/datasets/human/chip/encode/ENCSR675LRO/summary/ENCFF837HCK.w5 32 2 mean CHIP:MLLT1:K562 CHIP ChIP-TF:MLLT1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3534 0 ENCFF845QWZ /home/drk/tillage/datasets/human/chip/encode/ENCSR676LPF/summary/ENCFF845QWZ.w5 32 2 mean CHIP:H3K27me3:heart right ventricle male child (3 years) CHIP ChIP-Histone:H3K27me3/heart right ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3535 0 ENCFF774TEE /home/drk/tillage/datasets/human/chip/encode/ENCSR676ZEF/summary/ENCFF774TEE.w5 32 2 mean CHIP:eGFP-ZNF398:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF398/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3536 0 ENCFF366DMT /home/drk/tillage/datasets/human/chip/encode/ENCSR676ZKW/summary/ENCFF366DMT.w5 32 2 mean CHIP:H3K4me1:heart male embryo (91 day) CHIP ChIP-Histone:H3K4me1/heart male embryo (91 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3537 0 ENCFF185PIA /home/drk/tillage/datasets/human/chip/encode/ENCSR677EZB/summary/ENCFF185PIA.w5 32 2 mean CHIP:H3K36me3:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K36me3/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3538 0 ENCFF625AQW /home/drk/tillage/datasets/human/chip/encode/ENCSR677FYM/summary/ENCFF625AQW.w5 32 2 mean CHIP:EP300:omental fat pad female adult (53 years) CHIP ChIP-TF:EP300/omental fat pad female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3539 0 ENCFF219UQX /home/drk/tillage/datasets/human/chip/encode/ENCSR677LBH/summary/ENCFF219UQX.w5 32 2 mean CHIP:H3K27ac:gastroesophageal sphincter female adult (53 years) CHIP ChIP-Histone:H3K27ac/gastroesophageal sphincter female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3540 0 ENCFF815OFM /home/drk/tillage/datasets/human/chip/encode/ENCSR677XPJ/summary/ENCFF815OFM.w5 32 2 mean CHIP:H2AFZ:neural progenitor cell originated from H9 CHIP ChIP-TF:H2AFZ/neural progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3541 0 ENCFF101DFB /home/drk/tillage/datasets/human/chip/encode/ENCSR678AFU/summary/ENCFF101DFB.w5 32 2 mean CHIP:H3F3A:OCI-LY1 CHIP ChIP-Histone:H3F3A/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3542 0 ENCFF611FWS /home/drk/tillage/datasets/human/chip/encode/ENCSR678LND/summary/ENCFF611FWS.w5 32 2 mean CHIP:H3K27ac:liver female adult (25 years) CHIP ChIP-Histone:H3K27ac/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3543 0 ENCFF740GPW /home/drk/tillage/datasets/human/chip/encode/ENCSR678RCY/summary/ENCFF740GPW.w5 32 2 mean CHIP:H3K9me3:T-helper 17 cell originated from blood cell CHIP ChIP-Histone:H3K9me3/T-helper 17 cell originated from blood cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3544 0 ENCFF547WYC /home/drk/tillage/datasets/human/chip/encode/ENCSR678WMQ/summary/ENCFF547WYC.w5 32 2 mean CHIP:H3K9me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K9me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3545 0 ENCFF896WFU /home/drk/tillage/datasets/human/chip/encode/ENCSR679CHH/summary/ENCFF896WFU.w5 32 2 mean CHIP:H3K9me3:SK-N-MC CHIP ChIP-Histone:H3K9me3/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3546 0 ENCFF385ACQ /home/drk/tillage/datasets/human/chip/encode/ENCSR679KXF/summary/ENCFF385ACQ.w5 32 2 mean CHIP:eGFP-ZNF23:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF23/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3547 0 ENCFF385ZVU /home/drk/tillage/datasets/human/chip/encode/ENCSR679OVD/summary/ENCFF385ZVU.w5 32 2 mean CHIP:H3K27ac:esophagus male adult (34 years) CHIP ChIP-Histone:H3K27ac/esophagus male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3548 0 ENCFF390DEF /home/drk/tillage/datasets/human/chip/encode/ENCSR679STZ/summary/ENCFF390DEF.w5 32 2 mean CHIP:eGFP-ZNF792:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF792/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3549 0 ENCFF949BRD /home/drk/tillage/datasets/human/chip/encode/ENCSR680OFU/summary/ENCFF949BRD.w5 32 2 mean CHIP:EP300:HeLa-S3 CHIP ChIP-TF:EP300/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3550 0 ENCFF613CYH /home/drk/tillage/datasets/human/chip/encode/ENCSR680UQE/summary/ENCFF613CYH.w5 32 2 mean CHIP:IKZF2:GM12878 CHIP ChIP-TF:IKZF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3551 0 ENCFF630HDY /home/drk/tillage/datasets/human/chip/encode/ENCSR681AIW/summary/ENCFF630HDY.w5 32 2 mean CHIP:H3K9me3:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K9me3/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3552 0 ENCFF033UNX /home/drk/tillage/datasets/human/chip/encode/ENCSR681HMF/summary/ENCFF033UNX.w5 32 2 mean CHIP:H3K4me3:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K4me3/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3553 0 ENCFF586FDC /home/drk/tillage/datasets/human/chip/encode/ENCSR681NOM/summary/ENCFF586FDC.w5 32 2 mean CHIP:CEBPB:GM12878 CHIP ChIP-TF:CEBPB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3554 0 ENCFF914AXF /home/drk/tillage/datasets/human/chip/encode/ENCSR681OSD/summary/ENCFF914AXF.w5 32 2 mean CHIP:H3K36me3:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K36me3/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3555 0 ENCFF869EQY /home/drk/tillage/datasets/human/chip/encode/ENCSR681WHQ/summary/ENCFF869EQY.w5 32 2 mean CHIP:ETS1:HepG2 CHIP ChIP-TF:ETS1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3556 0 ENCFF337JNF /home/drk/tillage/datasets/human/chip/encode/ENCSR682GOI/summary/ENCFF337JNF.w5 32 2 mean CHIP:H3K9me3:sigmoid colon female adult (53 years) CHIP ChIP-Histone:H3K9me3/sigmoid colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3557 0 ENCFF674OQZ /home/drk/tillage/datasets/human/chip/encode/ENCSR682MXX/summary/ENCFF674OQZ.w5 32 2 mean CHIP:H3K9ac:liver female adult (25 years) CHIP ChIP-Histone:H3K9ac/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3558 0 ENCFF388USP /home/drk/tillage/datasets/human/chip/encode/ENCSR683CSF/summary/ENCFF388USP.w5 32 2 mean CHIP:ZNF207:HepG2 CHIP ChIP-TF:ZNF207/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3559 0 ENCFF424JDL /home/drk/tillage/datasets/human/chip/encode/ENCSR683ORH/summary/ENCFF424JDL.w5 32 2 mean CHIP:H3F3A:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3F3A/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3560 0 ENCFF179FYG /home/drk/tillage/datasets/human/chip/encode/ENCSR684BMS/summary/ENCFF179FYG.w5 32 2 mean CHIP:H4K20me1:MM.1S CHIP ChIP-TF:H4K20me1/MM.1S ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3561 0 ENCFF429UPL /home/drk/tillage/datasets/human/chip/encode/ENCSR684NJD/summary/ENCFF429UPL.w5 32 2 mean CHIP:EP300:stomach male adult (54 years) CHIP ChIP-TF:EP300/stomach male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3562 0 ENCFF277SAA /home/drk/tillage/datasets/human/chip/encode/ENCSR686EYO/summary/ENCFF277SAA.w5 32 2 mean CHIP:KHSRP:K562 CHIP ChIP-TF:KHSRP/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3563 0 ENCFF946TCS /home/drk/tillage/datasets/human/chip/encode/ENCSR686PTV/summary/ENCFF946TCS.w5 32 2 mean CHIP:H3K27me3:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K27me3/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3564 0 ENCFF265ADQ /home/drk/tillage/datasets/human/chip/encode/ENCSR686SOV/summary/ENCFF265ADQ.w5 32 2 mean CHIP:NCOA3:MCF-7 CHIP ChIP-TF:NCOA3/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3565 0 ENCFF183WCI /home/drk/tillage/datasets/human/chip/encode/ENCSR687EBF/summary/ENCFF183WCI.w5 32 2 mean CHIP:H3K14ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K14ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3566 0 ENCFF770SEF /home/drk/tillage/datasets/human/chip/encode/ENCSR688OUZ/summary/ENCFF770SEF.w5 32 2 mean CHIP:H3K27me3:neuron originated from H9 CHIP ChIP-Histone:H3K27me3/neuron originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3567 0 ENCFF420NYN /home/drk/tillage/datasets/human/chip/encode/ENCSR688SJY/summary/ENCFF420NYN.w5 32 2 mean CHIP:H3K9me3:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K9me3/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3568 0 ENCFF525XNI /home/drk/tillage/datasets/human/chip/encode/ENCSR688ZOS/summary/ENCFF525XNI.w5 32 2 mean CHIP:H3K36me3:neuroepithelial stem cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K36me3/neuroepithelial stem cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3569 0 ENCFF838FBE /home/drk/tillage/datasets/human/chip/encode/ENCSR689QUB/summary/ENCFF838FBE.w5 32 2 mean CHIP:H3K4me1:hepatocyte originated from H9 CHIP ChIP-Histone:H3K4me1/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3570 0 ENCFF537YFN /home/drk/tillage/datasets/human/chip/encode/ENCSR689SFJ/summary/ENCFF537YFN.w5 32 2 mean CHIP:H3K36me3:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K36me3/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3571 0 ENCFF887JZO /home/drk/tillage/datasets/human/chip/encode/ENCSR689YFA/summary/ENCFF887JZO.w5 32 2 mean CHIP:eGFP-ZNF146:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF146/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3572 0 ENCFF860UJL /home/drk/tillage/datasets/human/chip/encode/ENCSR690GLT/summary/ENCFF860UJL.w5 32 2 mean CHIP:H3K27me3:ectodermal cell originated from embryonic stem cell CHIP ChIP-Histone:H3K27me3/ectodermal cell originated from embryonic stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3573 0 ENCFF209UZT /home/drk/tillage/datasets/human/chip/encode/ENCSR690GUG/summary/ENCFF209UZT.w5 32 2 mean CHIP:U2AF1:K562 CHIP ChIP-TF:U2AF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3574 0 ENCFF337KKY /home/drk/tillage/datasets/human/chip/encode/ENCSR690UYB/summary/ENCFF337KKY.w5 32 2 mean CHIP:H3K36me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K36me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3575 0 ENCFF195HLW /home/drk/tillage/datasets/human/chip/encode/ENCSR691BNO/summary/ENCFF195HLW.w5 32 2 mean CHIP:H3K9me3:mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K9me3/mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3576 0 ENCFF314DQV /home/drk/tillage/datasets/human/chip/encode/ENCSR691CPM/summary/ENCFF314DQV.w5 32 2 mean CHIP:POLR2A:spleen female adult (51 year) CHIP ChIP-TF:POLR2A/spleen female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3577 0 ENCFF653LIS /home/drk/tillage/datasets/human/chip/encode/ENCSR691CSS/summary/ENCFF653LIS.w5 32 2 mean CHIP:H3K4me1:common myeloid progenitor, CD34-positive male adult (42 years) CHIP ChIP-Histone:H3K4me1/common myeloid progenitor, CD34-positive male adult (42 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3578 0 ENCFF344UTH /home/drk/tillage/datasets/human/chip/encode/ENCSR691IZA/summary/ENCFF344UTH.w5 32 2 mean CHIP:H3K36me3:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K36me3/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3579 0 ENCFF413NYF /home/drk/tillage/datasets/human/chip/encode/ENCSR691TXI/summary/ENCFF413NYF.w5 32 2 mean CHIP:eGFP-ZNF610:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF610/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3580 0 ENCFF235KGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR692CTK/summary/ENCFF235KGZ.w5 32 2 mean CHIP:H3K27me3:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K27me3/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3581 0 ENCFF903ARI /home/drk/tillage/datasets/human/chip/encode/ENCSR692DOM/summary/ENCFF903ARI.w5 32 2 mean CHIP:H3K36me3:peripheral blood mononuclear cell male adult (39 years) CHIP ChIP-Histone:H3K36me3/peripheral blood mononuclear cell male adult (39 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3582 0 ENCFF149GYM /home/drk/tillage/datasets/human/chip/encode/ENCSR692HIO/summary/ENCFF149GYM.w5 32 2 mean CHIP:H3K4me2:NCI-H929 CHIP ChIP-Histone:H3K4me2/NCI-H929 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3583 0 ENCFF684EAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR692HSE/summary/ENCFF684EAQ.w5 32 2 mean CHIP:eGFP-YY2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-YY2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3584 0 ENCFF010VZL /home/drk/tillage/datasets/human/chip/encode/ENCSR692ICP/summary/ENCFF010VZL.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3585 0 ENCFF551SXN /home/drk/tillage/datasets/human/chip/encode/ENCSR692ILH/summary/ENCFF551SXN.w5 32 2 mean CHIP:CTCF:spleen female adult (53 years) CHIP ChIP-TF:CTCF/spleen female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3586 0 ENCFF985JVY /home/drk/tillage/datasets/human/chip/encode/ENCSR692OFN/summary/ENCFF985JVY.w5 32 2 mean CHIP:H3K36me3:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K36me3/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3587 0 ENCFF671FBK /home/drk/tillage/datasets/human/chip/encode/ENCSR693GVU/summary/ENCFF671FBK.w5 32 2 mean CHIP:H3K4me3:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K4me3/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3588 0 ENCFF101BWM /home/drk/tillage/datasets/human/chip/encode/ENCSR693VHX/summary/ENCFF101BWM.w5 32 2 mean CHIP:H3K27ac:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K27ac/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3589 0 ENCFF283KQB /home/drk/tillage/datasets/human/chip/encode/ENCSR694CDP/summary/ENCFF283KQB.w5 32 2 mean CHIP:H3K36me3:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3590 0 ENCFF404RAR /home/drk/tillage/datasets/human/chip/encode/ENCSR694LBI/summary/ENCFF404RAR.w5 32 2 mean CHIP:H3K27me3:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K27me3/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3591 0 ENCFF480RDD /home/drk/tillage/datasets/human/chip/encode/ENCSR694PCO/summary/ENCFF480RDD.w5 32 2 mean CHIP:H3K9me3:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K9me3/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3592 0 ENCFF318MIL /home/drk/tillage/datasets/human/chip/encode/ENCSR694RCH/summary/ENCFF318MIL.w5 32 2 mean CHIP:H3K27ac:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K27ac/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3593 0 ENCFF026MQA /home/drk/tillage/datasets/human/chip/encode/ENCSR695EQB/summary/ENCFF026MQA.w5 32 2 mean CHIP:ZNF24:K562 CHIP ChIP-TF:ZNF24/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3594 0 ENCFF093NFQ /home/drk/tillage/datasets/human/chip/encode/ENCSR695HYL/summary/ENCFF093NFQ.w5 32 2 mean CHIP:H3K79me2:hepatocyte originated from H9 CHIP ChIP-Histone:H3K79me2/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3595 0 ENCFF142ZLR /home/drk/tillage/datasets/human/chip/encode/ENCSR696HTM/summary/ENCFF142ZLR.w5 32 2 mean CHIP:POLR2A:vagina female adult (51 year) CHIP ChIP-TF:POLR2A/vagina female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3596 0 ENCFF115AYZ /home/drk/tillage/datasets/human/chip/encode/ENCSR696LQU/summary/ENCFF115AYZ.w5 32 2 mean CHIP:EP300:ovary female adult (53 years) CHIP ChIP-TF:EP300/ovary female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3597 0 ENCFF123VBF /home/drk/tillage/datasets/human/chip/encode/ENCSR696MBC/summary/ENCFF123VBF.w5 32 2 mean CHIP:SRSF4:HepG2 CHIP ChIP-TF:SRSF4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3598 0 ENCFF244WBV /home/drk/tillage/datasets/human/chip/encode/ENCSR697CUP/summary/ENCFF244WBV.w5 32 2 mean CHIP:HCFC1:MCF-7 CHIP ChIP-TF:HCFC1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3599 0 ENCFF418JJK /home/drk/tillage/datasets/human/chip/encode/ENCSR697GPO/summary/ENCFF418JJK.w5 32 2 mean CHIP:H3K4me3:esophagus female adult (30 years) CHIP ChIP-Histone:H3K4me3/esophagus female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3600 0 ENCFF582YKY /home/drk/tillage/datasets/human/chip/encode/ENCSR697RIW/summary/ENCFF582YKY.w5 32 2 mean CHIP:H3K9me3:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K9me3/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3601 0 ENCFF270ZPN /home/drk/tillage/datasets/human/chip/encode/ENCSR697YIN/summary/ENCFF270ZPN.w5 32 2 mean CHIP:CTCF:breast epithelium male adult (54 years) CHIP ChIP-TF:CTCF/breast epithelium male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3602 0 ENCFF609FYE /home/drk/tillage/datasets/human/chip/encode/ENCSR697YLJ/summary/ENCFF609FYE.w5 32 2 mean CHIP:CBFA2T3:K562 CHIP ChIP-TF:CBFA2T3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3603 0 ENCFF413VKO /home/drk/tillage/datasets/human/chip/encode/ENCSR697YSL/summary/ENCFF413VKO.w5 32 2 mean CHIP:H3K36me3:stomach female embryo (98 days) CHIP ChIP-Histone:H3K36me3/stomach female embryo (98 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3604 0 ENCFF081XLE /home/drk/tillage/datasets/human/chip/encode/ENCSR698CKZ/summary/ENCFF081XLE.w5 32 2 mean CHIP:H2AFZ:MM.1S CHIP ChIP-TF:H2AFZ/MM.1S ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3605 0 ENCFF072KUF /home/drk/tillage/datasets/human/chip/encode/ENCSR699BEK/summary/ENCFF072KUF.w5 32 2 mean CHIP:CTCF:tibial artery male adult (37 years) CHIP ChIP-TF:CTCF/tibial artery male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3606 0 ENCFF991PYT /home/drk/tillage/datasets/human/chip/encode/ENCSR699FHH/summary/ENCFF991PYT.w5 32 2 mean CHIP:H3K9me3:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K9me3/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3607 0 ENCFF119YZL /home/drk/tillage/datasets/human/chip/encode/ENCSR699PVC/summary/ENCFF119YZL.w5 32 2 mean CHIP:CBFA2T2:K562 CHIP ChIP-TF:CBFA2T2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3608 0 ENCFF340WVN /home/drk/tillage/datasets/human/chip/encode/ENCSR699YFX/summary/ENCFF340WVN.w5 32 2 mean CHIP:CLOCK:MCF-7 CHIP ChIP-TF:CLOCK/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3609 0 ENCFF630NCN /home/drk/tillage/datasets/human/chip/encode/ENCSR699ZGH/summary/ENCFF630NCN.w5 32 2 mean CHIP:POLR2A:heart left ventricle female adult (51 year) CHIP ChIP-TF:POLR2A/heart left ventricle female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3610 0 ENCFF673QAP /home/drk/tillage/datasets/human/chip/encode/ENCSR700NGJ/summary/ENCFF673QAP.w5 32 2 mean CHIP:H3K4me1:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K4me1/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3611 0 ENCFF347HIL /home/drk/tillage/datasets/human/chip/encode/ENCSR700VCN/summary/ENCFF347HIL.w5 32 2 mean CHIP:H3K9me2:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K9me2/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3612 0 ENCFF294VXO /home/drk/tillage/datasets/human/chip/encode/ENCSR701AQS/summary/ENCFF294VXO.w5 32 2 mean CHIP:ZNF592:MCF-7 CHIP ChIP-TF:ZNF592/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3613 0 ENCFF937JUR /home/drk/tillage/datasets/human/chip/encode/ENCSR701KJD/summary/ENCFF937JUR.w5 32 2 mean CHIP:H3K9ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K9ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3614 0 ENCFF123MKH /home/drk/tillage/datasets/human/chip/encode/ENCSR701RXW/summary/ENCFF123MKH.w5 32 2 mean CHIP:eGFP-ZNF530:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF530/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3615 0 ENCFF948IZK /home/drk/tillage/datasets/human/chip/encode/ENCSR701ZDB/summary/ENCFF948IZK.w5 32 2 mean CHIP:H3K4me2:OCI-LY3 CHIP ChIP-Histone:H3K4me2/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3616 0 ENCFF095RDM /home/drk/tillage/datasets/human/chip/encode/ENCSR702BYX/summary/ENCFF095RDM.w5 32 2 mean CHIP:NFIB:MCF-7 CHIP ChIP-TF:NFIB/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3617 0 ENCFF429ZMO /home/drk/tillage/datasets/human/chip/encode/ENCSR702GMW/summary/ENCFF429ZMO.w5 32 2 mean CHIP:EZH2phosphoT487:PC-9 CHIP ChIP-TF:EZH2phosphoT487/PC-9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3618 0 ENCFF327BUB /home/drk/tillage/datasets/human/chip/encode/ENCSR702RZM/summary/ENCFF327BUB.w5 32 2 mean CHIP:H3K27me3:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27me3/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3619 0 ENCFF701QYD /home/drk/tillage/datasets/human/chip/encode/ENCSR703CYD/summary/ENCFF701QYD.w5 32 2 mean CHIP:H3K4me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K4me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3620 0 ENCFF799EIL /home/drk/tillage/datasets/human/chip/encode/ENCSR703DFH/summary/ENCFF799EIL.w5 32 2 mean CHIP:H3K4me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K4me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3621 0 ENCFF345NNP /home/drk/tillage/datasets/human/chip/encode/ENCSR703KWN/summary/ENCFF345NNP.w5 32 2 mean CHIP:EZH2:MM.1S CHIP ChIP-TF:EZH2/MM.1S ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3622 0 ENCFF508WLD /home/drk/tillage/datasets/human/chip/encode/ENCSR703KXH/summary/ENCFF508WLD.w5 32 2 mean CHIP:H2AK5ac:H1-hESC CHIP ChIP-TF:H2AK5ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3623 0 ENCFF513QHS /home/drk/tillage/datasets/human/chip/encode/ENCSR703TNG/summary/ENCFF513QHS.w5 32 2 mean CHIP:3xFLAG-RAD21:MCF-7 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RAD21/MCF-7 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3624 0 ENCFF661QMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR704BRU/summary/ENCFF661QMZ.w5 32 2 mean CHIP:H3K9me3:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K9me3/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3625 0 ENCFF018PYH /home/drk/tillage/datasets/human/chip/encode/ENCSR704IGU/summary/ENCFF018PYH.w5 32 2 mean CHIP:3xFLAG-ZGPAT:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZGPAT/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3626 0 ENCFF049ZCB /home/drk/tillage/datasets/human/chip/encode/ENCSR704IJM/summary/ENCFF049ZCB.w5 32 2 mean CHIP:EP300:transverse colon female adult (51 year) CHIP ChIP-TF:EP300/transverse colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3627 0 ENCFF204COR /home/drk/tillage/datasets/human/chip/encode/ENCSR705ASR/summary/ENCFF204COR.w5 32 2 mean CHIP:eGFP-ZSCAN23:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN23/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3628 0 ENCFF500YAA /home/drk/tillage/datasets/human/chip/encode/ENCSR705SZP/summary/ENCFF500YAA.w5 32 2 mean CHIP:H3K79me2:PC-9 CHIP ChIP-Histone:H3K79me2/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3629 0 ENCFF252EGE /home/drk/tillage/datasets/human/chip/encode/ENCSR706BJO/summary/ENCFF252EGE.w5 32 2 mean CHIP:eGFP-ZBTB11:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZBTB11/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3630 0 ENCFF224SPM /home/drk/tillage/datasets/human/chip/encode/ENCSR706RRA/summary/ENCFF224SPM.w5 32 2 mean CHIP:H4K5ac:IMR-90 CHIP ChIP-TF:H4K5ac/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3631 0 ENCFF562RHH /home/drk/tillage/datasets/human/chip/encode/ENCSR706YUH/summary/ENCFF562RHH.w5 32 2 mean CHIP:SMARCA5:GM12878 CHIP ChIP-TF:SMARCA5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3632 0 ENCFF918NVX /home/drk/tillage/datasets/human/chip/encode/ENCSR707AEW/summary/ENCFF918NVX.w5 32 2 mean CHIP:H3K4me1:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K4me1/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3633 0 ENCFF429TDQ /home/drk/tillage/datasets/human/chip/encode/ENCSR707BNG/summary/ENCFF429TDQ.w5 32 2 mean CHIP:eGFP-MYNN:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-MYNN/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3634 0 ENCFF870YFB /home/drk/tillage/datasets/human/chip/encode/ENCSR707IUN/summary/ENCFF870YFB.w5 32 2 mean CHIP:NFE2L2:HeLa-S3 CHIP ChIP-TF:NFE2L2/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3635 0 ENCFF745IWH /home/drk/tillage/datasets/human/chip/encode/ENCSR707QWA/summary/ENCFF745IWH.w5 32 2 mean CHIP:NR2F6:K562 CHIP ChIP-TF:NR2F6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3636 0 ENCFF580MXP /home/drk/tillage/datasets/human/chip/encode/ENCSR708IFN/summary/ENCFF580MXP.w5 32 2 mean CHIP:H3K27me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3637 0 ENCFF740EXI /home/drk/tillage/datasets/human/chip/encode/ENCSR709DRM/summary/ENCFF740EXI.w5 32 2 mean CHIP:eGFP-E2F5:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-E2F5/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3638 0 ENCFF432FYS /home/drk/tillage/datasets/human/chip/encode/ENCSR710WLO/summary/ENCFF432FYS.w5 32 2 mean CHIP:MGA:K562 CHIP ChIP-TF:MGA/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3639 0 ENCFF048RJY /home/drk/tillage/datasets/human/chip/encode/ENCSR711SNW/summary/ENCFF048RJY.w5 32 2 mean CHIP:NCOA1:K562 CHIP ChIP-TF:NCOA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3640 0 ENCFF859VKK /home/drk/tillage/datasets/human/chip/encode/ENCSR711UOA/summary/ENCFF859VKK.w5 32 2 mean CHIP:eGFP-ZNF837:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF837/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3641 0 ENCFF089UTW /home/drk/tillage/datasets/human/chip/encode/ENCSR711VWL/summary/ENCFF089UTW.w5 32 2 mean CHIP:HDAC1:K562 CHIP ChIP-TF:HDAC1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3642 0 ENCFF604ISL /home/drk/tillage/datasets/human/chip/encode/ENCSR711XNY/summary/ENCFF604ISL.w5 32 2 mean CHIP:PKNOX1:GM12878 CHIP ChIP-TF:PKNOX1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3643 0 ENCFF175PRM /home/drk/tillage/datasets/human/chip/encode/ENCSR712FAM/summary/ENCFF175PRM.w5 32 2 mean CHIP:3xFLAG-ZSCAN9:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZSCAN9/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3644 0 ENCFF523QJV /home/drk/tillage/datasets/human/chip/encode/ENCSR712WTM/summary/ENCFF523QJV.w5 32 2 mean CHIP:H3K9me3:heart embryo (101 day) CHIP ChIP-Histone:H3K9me3/heart embryo (101 day) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3645 0 ENCFF927FZR /home/drk/tillage/datasets/human/chip/encode/ENCSR713HJS/summary/ENCFF927FZR.w5 32 2 mean CHIP:H3K27me3:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K27me3/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3646 0 ENCFF059WGK /home/drk/tillage/datasets/human/chip/encode/ENCSR713IFY/summary/ENCFF059WGK.w5 32 2 mean CHIP:3xFLAG-ZNF146:K562 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZNF146/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3647 0 ENCFF763YOO /home/drk/tillage/datasets/human/chip/encode/ENCSR713QLX/summary/ENCFF763YOO.w5 32 2 mean CHIP:H3K79me2:IMR-90 CHIP ChIP-Histone:H3K79me2/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3648 0 ENCFF622LED /home/drk/tillage/datasets/human/chip/encode/ENCSR713SXF/summary/ENCFF622LED.w5 32 2 mean CHIP:CTCF:cardiac muscle cell CHIP ChIP-TF:CTCF/cardiac muscle cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3649 0 ENCFF221ODV /home/drk/tillage/datasets/human/chip/encode/ENCSR714BDG/summary/ENCFF221ODV.w5 32 2 mean CHIP:H3K4me1:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K4me1/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3650 0 ENCFF594BQL /home/drk/tillage/datasets/human/chip/encode/ENCSR714EQS/summary/ENCFF594BQL.w5 32 2 mean CHIP:POLR2AphosphoS5:transverse colon female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/transverse colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3651 0 ENCFF249ABO /home/drk/tillage/datasets/human/chip/encode/ENCSR714JRB/summary/ENCFF249ABO.w5 32 2 mean CHIP:POLR2AphosphoS5:stomach female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/stomach female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3652 0 ENCFF369POJ /home/drk/tillage/datasets/human/chip/encode/ENCSR714KGG/summary/ENCFF369POJ.w5 32 2 mean CHIP:H3K36me3:neural cell CHIP ChIP-Histone:H3K36me3/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3653 0 ENCFF855AXA /home/drk/tillage/datasets/human/chip/encode/ENCSR714KWW/summary/ENCFF855AXA.w5 32 2 mean CHIP:H3K4me3:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K4me3/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3654 0 ENCFF751CCH /home/drk/tillage/datasets/human/chip/encode/ENCSR714LYA/summary/ENCFF751CCH.w5 32 2 mean CHIP:eGFP-PRDM2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3655 0 ENCFF797QMZ /home/drk/tillage/datasets/human/chip/encode/ENCSR714LZQ/summary/ENCFF797QMZ.w5 32 2 mean CHIP:eGFP-ZNF664:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF664/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3656 0 ENCFF257DIP /home/drk/tillage/datasets/human/chip/encode/ENCSR714SGY/summary/ENCFF257DIP.w5 32 2 mean CHIP:H3K4me3:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K4me3/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3657 0 ENCFF261CVS /home/drk/tillage/datasets/human/chip/encode/ENCSR714TJD/summary/ENCFF261CVS.w5 32 2 mean CHIP:H3K27ac:A673 CHIP ChIP-Histone:H3K27ac/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3658 0 ENCFF744PPC /home/drk/tillage/datasets/human/chip/encode/ENCSR714YZG/summary/ENCFF744PPC.w5 32 2 mean CHIP:ETV4:HepG2 CHIP ChIP-TF:ETV4/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3659 0 ENCFF772BIP /home/drk/tillage/datasets/human/chip/encode/ENCSR715CCR/summary/ENCFF772BIP.w5 32 2 mean CHIP:DPF2:K562 CHIP ChIP-TF:DPF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3660 0 ENCFF947RXV /home/drk/tillage/datasets/human/chip/encode/ENCSR715KGX/summary/ENCFF947RXV.w5 32 2 mean CHIP:H3K4me3:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K4me3/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3661 0 ENCFF869XYH /home/drk/tillage/datasets/human/chip/encode/ENCSR715QNO/summary/ENCFF869XYH.w5 32 2 mean CHIP:eGFP-ZNF362:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF362/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3662 0 ENCFF183ETK /home/drk/tillage/datasets/human/chip/encode/ENCSR715UCI/summary/ENCFF183ETK.w5 32 2 mean CHIP:3xFLAG-SOX13:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SOX13/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3663 0 ENCFF003LAB /home/drk/tillage/datasets/human/chip/encode/ENCSR716CWA/summary/ENCFF003LAB.w5 32 2 mean CHIP:H3K36me3:naive thymus-derived CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/naive thymus-derived CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3664 0 ENCFF674SKA /home/drk/tillage/datasets/human/chip/encode/ENCSR716FUH/summary/ENCFF674SKA.w5 32 2 mean CHIP:H3K27ac:thyroid gland female adult (53 years) CHIP ChIP-Histone:H3K27ac/thyroid gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3665 0 ENCFF380LRO /home/drk/tillage/datasets/human/chip/encode/ENCSR716VIQ/summary/ENCFF380LRO.w5 32 2 mean CHIP:H3K36me3:T-cell male adult (21 year) CHIP ChIP-Histone:H3K36me3/T-cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3666 0 ENCFF369QLG /home/drk/tillage/datasets/human/chip/encode/ENCSR716YIT/summary/ENCFF369QLG.w5 32 2 mean CHIP:H3K4me3:kidney male adult (67 years) CHIP ChIP-Histone:H3K4me3/kidney male adult (67 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3667 0 ENCFF085UOM /home/drk/tillage/datasets/human/chip/encode/ENCSR716ZJH/summary/ENCFF085UOM.w5 32 2 mean CHIP:H3K4me3:H9 genetically modified using stable transfection CHIP ChIP-Histone:H3K4me3/H9 genetically modified using stable transfection ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3668 0 ENCFF158JUA /home/drk/tillage/datasets/human/chip/encode/ENCSR717AJD/summary/ENCFF158JUA.w5 32 2 mean CHIP:H3K4me3:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K4me3/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3669 0 ENCFF516ZKE /home/drk/tillage/datasets/human/chip/encode/ENCSR717BNA/summary/ENCFF516ZKE.w5 32 2 mean CHIP:H3K36me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K36me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3670 0 ENCFF890SIF /home/drk/tillage/datasets/human/chip/encode/ENCSR717HIA/summary/ENCFF890SIF.w5 32 2 mean CHIP:H3K27ac:placenta male embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/placenta male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3671 0 ENCFF035ZNG /home/drk/tillage/datasets/human/chip/encode/ENCSR718BTD/summary/ENCFF035ZNG.w5 32 2 mean CHIP:H3K27ac:vagina female adult (53 years) CHIP ChIP-Histone:H3K27ac/vagina female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3672 0 ENCFF015KQA /home/drk/tillage/datasets/human/chip/encode/ENCSR718SDE/summary/ENCFF015KQA.w5 32 2 mean CHIP:RLF:K562 CHIP ChIP-TF:RLF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3673 0 ENCFF498NYN /home/drk/tillage/datasets/human/chip/encode/ENCSR719COF/summary/ENCFF498NYN.w5 32 2 mean CHIP:H3K9me3:body of pancreas female adult (53 years) CHIP ChIP-Histone:H3K9me3/body of pancreas female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3674 0 ENCFF748YAH /home/drk/tillage/datasets/human/chip/encode/ENCSR719FEJ/summary/ENCFF748YAH.w5 32 2 mean CHIP:H3K27ac:KOPT-K1 CHIP ChIP-Histone:H3K27ac/KOPT-K1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3675 0 ENCFF375XLU /home/drk/tillage/datasets/human/chip/encode/ENCSR719QMW/summary/ENCFF375XLU.w5 32 2 mean CHIP:H3K14ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K14ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3676 0 ENCFF852NLH /home/drk/tillage/datasets/human/chip/encode/ENCSR720HUL/summary/ENCFF852NLH.w5 32 2 mean CHIP:E2F1:K562 CHIP ChIP-TF:E2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3677 0 ENCFF935RPR /home/drk/tillage/datasets/human/chip/encode/ENCSR720SAS/summary/ENCFF935RPR.w5 32 2 mean CHIP:H3K27me3:psoas muscle male adult (34 years) CHIP ChIP-Histone:H3K27me3/psoas muscle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3678 0 ENCFF306NUN /home/drk/tillage/datasets/human/chip/encode/ENCSR720USO/summary/ENCFF306NUN.w5 32 2 mean CHIP:CTCF:prostate gland male adult (37 years) CHIP ChIP-TF:CTCF/prostate gland male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3679 0 ENCFF049QOR /home/drk/tillage/datasets/human/chip/encode/ENCSR720ZAX/summary/ENCFF049QOR.w5 32 2 mean CHIP:H4K20me1:neural progenitor cell originated from H9 CHIP ChIP-TF:H4K20me1/neural progenitor cell originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3680 0 ENCFF717BMW /home/drk/tillage/datasets/human/chip/encode/ENCSR721AHD/summary/ENCFF717BMW.w5 32 2 mean CHIP:CTCF:sigmoid colon male adult (37 years) CHIP ChIP-TF:CTCF/sigmoid colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3681 0 ENCFF144CAK /home/drk/tillage/datasets/human/chip/encode/ENCSR721MPV/summary/ENCFF144CAK.w5 32 2 mean CHIP:H4K8ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H4K8ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3682 0 ENCFF163RZC /home/drk/tillage/datasets/human/chip/encode/ENCSR721QZV/summary/ENCFF163RZC.w5 32 2 mean CHIP:eGFP-ZSCAN18:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN18/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3683 0 ENCFF050VHG /home/drk/tillage/datasets/human/chip/encode/ENCSR723IKM/summary/ENCFF050VHG.w5 32 2 mean CHIP:H3K9me3:ascending aorta female adult (53 years) CHIP ChIP-Histone:H3K9me3/ascending aorta female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3684 0 ENCFF737FFB /home/drk/tillage/datasets/human/chip/encode/ENCSR724FCJ/summary/ENCFF737FFB.w5 32 2 mean CHIP:POLR2A:sigmoid colon female adult (51 year) CHIP ChIP-TF:POLR2A/sigmoid colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3685 0 ENCFF429QIM /home/drk/tillage/datasets/human/chip/encode/ENCSR724GSW/summary/ENCFF429QIM.w5 32 2 mean CHIP:SAFB2:K562 CHIP ChIP-TF:SAFB2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3686 0 ENCFF519MZR /home/drk/tillage/datasets/human/chip/encode/ENCSR724GUS/summary/ENCFF519MZR.w5 32 2 mean CHIP:H3K27ac:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27ac/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3687 0 ENCFF027RWI /home/drk/tillage/datasets/human/chip/encode/ENCSR724TOA/summary/ENCFF027RWI.w5 32 2 mean CHIP:H3K4me1:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K4me1/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3688 0 ENCFF365IQC /home/drk/tillage/datasets/human/chip/encode/ENCSR725ELR/summary/ENCFF365IQC.w5 32 2 mean CHIP:LARP7:MCF-7 CHIP ChIP-TF:LARP7/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3689 0 ENCFF013ZOI /home/drk/tillage/datasets/human/chip/encode/ENCSR725VFL/summary/ENCFF013ZOI.w5 32 2 mean CHIP:TCF12:GM12878 CHIP ChIP-TF:TCF12/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3690 0 ENCFF812BTH /home/drk/tillage/datasets/human/chip/encode/ENCSR726HTS/summary/ENCFF812BTH.w5 32 2 mean CHIP:H3K27ac:spleen female adult (53 years) CHIP ChIP-Histone:H3K27ac/spleen female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3691 0 ENCFF201TMB /home/drk/tillage/datasets/human/chip/encode/ENCSR726LZG/summary/ENCFF201TMB.w5 32 2 mean CHIP:H3K27me3:PC-9 CHIP ChIP-Histone:H3K27me3/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3692 0 ENCFF198BHD /home/drk/tillage/datasets/human/chip/encode/ENCSR726WVB/summary/ENCFF198BHD.w5 32 2 mean CHIP:H3K27ac:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K27ac/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3693 0 ENCFF314ICJ /home/drk/tillage/datasets/human/chip/encode/ENCSR726ZZX/summary/ENCFF314ICJ.w5 32 2 mean CHIP:H3K4me1:ACC112 CHIP ChIP-Histone:H3K4me1/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3694 0 ENCFF913XZA /home/drk/tillage/datasets/human/chip/encode/ENCSR727HME/summary/ENCFF913XZA.w5 32 2 mean CHIP:CTCF:lower leg skin female adult (51 year) CHIP ChIP-TF:CTCF/lower leg skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3695 0 ENCFF776NRS /home/drk/tillage/datasets/human/chip/encode/ENCSR727PIC/summary/ENCFF776NRS.w5 32 2 mean CHIP:eGFP-ZNF34:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF34/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3696 0 ENCFF565BPR /home/drk/tillage/datasets/human/chip/encode/ENCSR727TQS/summary/ENCFF565BPR.w5 32 2 mean CHIP:H3K4me1:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K4me1/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3697 0 ENCFF059LYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR727VOB/summary/ENCFF059LYJ.w5 32 2 mean CHIP:H3K27me3:lung female embryo (82 days) CHIP ChIP-Histone:H3K27me3/lung female embryo (82 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3698 0 ENCFF615TDR /home/drk/tillage/datasets/human/chip/encode/ENCSR728FLA/summary/ENCFF615TDR.w5 32 2 mean CHIP:H3K9me3:lung female adult (30 years) CHIP ChIP-Histone:H3K9me3/lung female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3699 0 ENCFF479WYV /home/drk/tillage/datasets/human/chip/encode/ENCSR728GTL/summary/ENCFF479WYV.w5 32 2 mean CHIP:H3K36me3:fibroblast of breast female adult (17 years) CHIP ChIP-Histone:H3K36me3/fibroblast of breast female adult (17 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3700 0 ENCFF836MBX /home/drk/tillage/datasets/human/chip/encode/ENCSR728MWW/summary/ENCFF836MBX.w5 32 2 mean CHIP:eGFP-ZIC2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZIC2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3701 0 ENCFF772CZB /home/drk/tillage/datasets/human/chip/encode/ENCSR728SZE/summary/ENCFF772CZB.w5 32 2 mean CHIP:H4K20me1:H1-hESC CHIP ChIP-TF:H4K20me1/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3702 0 ENCFF459NSX /home/drk/tillage/datasets/human/chip/encode/ENCSR729ENO/summary/ENCFF459NSX.w5 32 2 mean CHIP:H3K27ac:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K27ac/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3703 0 ENCFF703VST /home/drk/tillage/datasets/human/chip/encode/ENCSR729GQT/summary/ENCFF703VST.w5 32 2 mean CHIP:H3K27ac:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K27ac/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3704 0 ENCFF038YXS /home/drk/tillage/datasets/human/chip/encode/ENCSR729GXE/summary/ENCFF038YXS.w5 32 2 mean CHIP:POLR2A:spleen male adult (37 years) CHIP ChIP-TF:POLR2A/spleen male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3705 0 ENCFF837LRU /home/drk/tillage/datasets/human/chip/encode/ENCSR729HVR/summary/ENCFF837LRU.w5 32 2 mean CHIP:eGFP-ZNF644:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF644/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3706 0 ENCFF072FPF /home/drk/tillage/datasets/human/chip/encode/ENCSR729LGA/summary/ENCFF072FPF.w5 32 2 mean CHIP:SP1:MCF-7 CHIP ChIP-TF:SP1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3707 0 ENCFF506MUV /home/drk/tillage/datasets/human/chip/encode/ENCSR729NVN/summary/ENCFF506MUV.w5 32 2 mean CHIP:H4K20me1:H9 CHIP ChIP-TF:H4K20me1/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3708 0 ENCFF540UFJ /home/drk/tillage/datasets/human/chip/encode/ENCSR730FLZ/summary/ENCFF540UFJ.w5 32 2 mean CHIP:H3K4me1:ES-I3 CHIP ChIP-Histone:H3K4me1/ES-I3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3709 0 ENCFF241GZH /home/drk/tillage/datasets/human/chip/encode/ENCSR730TBC/summary/ENCFF241GZH.w5 32 2 mean CHIP:MNT:HepG2 CHIP ChIP-TF:MNT/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3710 0 ENCFF908OIU /home/drk/tillage/datasets/human/chip/encode/ENCSR731AGO/summary/ENCFF908OIU.w5 32 2 mean CHIP:eGFP-ZSCAN5C:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN5C/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3711 0 ENCFF654UPJ /home/drk/tillage/datasets/human/chip/encode/ENCSR731JZN/summary/ENCFF654UPJ.w5 32 2 mean CHIP:H3K27me3:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K27me3/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3712 0 ENCFF113PXT /home/drk/tillage/datasets/human/chip/encode/ENCSR731LHZ/summary/ENCFF113PXT.w5 32 2 mean CHIP:E4F1:K562 CHIP ChIP-TF:E4F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3713 0 ENCFF022TXB /home/drk/tillage/datasets/human/chip/encode/ENCSR731OMG/summary/ENCFF022TXB.w5 32 2 mean CHIP:H3K36me3:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K36me3/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3714 0 ENCFF897KPI /home/drk/tillage/datasets/human/chip/encode/ENCSR731XOV/summary/ENCFF897KPI.w5 32 2 mean CHIP:H3K27me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K27me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3715 0 ENCFF820LLO /home/drk/tillage/datasets/human/chip/encode/ENCSR732NFR/summary/ENCFF820LLO.w5 32 2 mean CHIP:H2AK5ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H2AK5ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3716 0 ENCFF905CGC /home/drk/tillage/datasets/human/chip/encode/ENCSR732PJX/summary/ENCFF905CGC.w5 32 2 mean CHIP:NKRF:GM12878 CHIP ChIP-TF:NKRF/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3717 0 ENCFF811VAX /home/drk/tillage/datasets/human/chip/encode/ENCSR733QOZ/summary/ENCFF811VAX.w5 32 2 mean CHIP:H3K27me3:CD4-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K27me3/CD4-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3718 0 ENCFF422PMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR734ESI/summary/ENCFF422PMQ.w5 32 2 mean CHIP:H3K9me3:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K9me3/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3719 0 ENCFF419LKB /home/drk/tillage/datasets/human/chip/encode/ENCSR734MEM/summary/ENCFF419LKB.w5 32 2 mean CHIP:H3K23ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K23ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3720 0 ENCFF149ZYU /home/drk/tillage/datasets/human/chip/encode/ENCSR734NCK/summary/ENCFF149ZYU.w5 32 2 mean CHIP:H2BK15ac:H9 CHIP ChIP-TF:H2BK15ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3721 0 ENCFF818MQG /home/drk/tillage/datasets/human/chip/encode/ENCSR734QPK/summary/ENCFF818MQG.w5 32 2 mean CHIP:H3K36me3:UCSF-4 CHIP ChIP-Histone:H3K36me3/UCSF-4 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3722 0 ENCFF953XOJ /home/drk/tillage/datasets/human/chip/encode/ENCSR734ZOZ/summary/ENCFF953XOJ.w5 32 2 mean CHIP:POLR2A:esophagus squamous epithelium male adult (54 years) CHIP ChIP-TF:POLR2A/esophagus squamous epithelium male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3723 0 ENCFF180STN /home/drk/tillage/datasets/human/chip/encode/ENCSR735KEY/summary/ENCFF180STN.w5 32 2 mean CHIP:FOXA1:liver male adult (32 years) CHIP ChIP-TF:FOXA1/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3724 0 ENCFF122JJG /home/drk/tillage/datasets/human/chip/encode/ENCSR735SLW/summary/ENCFF122JJG.w5 32 2 mean CHIP:H3K27ac:Parathyroid adenoma male adult (62 years) CHIP ChIP-Histone:H3K27ac/Parathyroid adenoma male adult (62 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3725 0 ENCFF208VLV /home/drk/tillage/datasets/human/chip/encode/ENCSR736ALU/summary/ENCFF208VLV.w5 32 2 mean CHIP:H3K27ac:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K27ac/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3726 0 ENCFF971SPU /home/drk/tillage/datasets/human/chip/encode/ENCSR736BUG/summary/ENCFF971SPU.w5 32 2 mean CHIP:EGR1:liver male adult (32 years) CHIP ChIP-TF:EGR1/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3727 0 ENCFF191EYK /home/drk/tillage/datasets/human/chip/encode/ENCSR736PKV/summary/ENCFF191EYK.w5 32 2 mean CHIP:H3K36me3:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K36me3/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3728 0 ENCFF141YFL /home/drk/tillage/datasets/human/chip/encode/ENCSR736SFP/summary/ENCFF141YFL.w5 32 2 mean CHIP:H3K36me3:cingulate gyrus male adult (81 year) CHIP ChIP-Histone:H3K36me3/cingulate gyrus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3729 0 ENCFF518EVZ /home/drk/tillage/datasets/human/chip/encode/ENCSR736ZKL/summary/ENCFF518EVZ.w5 32 2 mean CHIP:eGFP-ZNF148:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF148/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3730 0 ENCFF169IXM /home/drk/tillage/datasets/human/chip/encode/ENCSR737LTZ/summary/ENCFF169IXM.w5 32 2 mean CHIP:MYNN:K562 CHIP ChIP-TF:MYNN/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3731 0 ENCFF526NXJ /home/drk/tillage/datasets/human/chip/encode/ENCSR737NLJ/summary/ENCFF526NXJ.w5 32 2 mean CHIP:H3K9me3:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K9me3/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3732 0 ENCFF415NMY /home/drk/tillage/datasets/human/chip/encode/ENCSR737UST/summary/ENCFF415NMY.w5 32 2 mean CHIP:eGFP-ZNF740:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ZNF740/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3733 0 ENCFF881TPS /home/drk/tillage/datasets/human/chip/encode/ENCSR738BJJ/summary/ENCFF881TPS.w5 32 2 mean CHIP:H2BK12ac:H9 CHIP ChIP-TF:H2BK12ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3734 0 ENCFF403KRP /home/drk/tillage/datasets/human/chip/encode/ENCSR738LBP/summary/ENCFF403KRP.w5 32 2 mean CHIP:H3K4me3:thymus male child (3 years) CHIP ChIP-Histone:H3K4me3/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3735 0 ENCFF681ORM /home/drk/tillage/datasets/human/chip/encode/ENCSR738SLS/summary/ENCFF681ORM.w5 32 2 mean CHIP:eGFP-ZNF449:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF449/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3736 0 ENCFF870RAN /home/drk/tillage/datasets/human/chip/encode/ENCSR738SXD/summary/ENCFF870RAN.w5 32 2 mean CHIP:H3K27ac:upper lobe of left lung female adult (53 years) CHIP ChIP-Histone:H3K27ac/upper lobe of left lung female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3737 0 ENCFF236YZE /home/drk/tillage/datasets/human/chip/encode/ENCSR739BZR/summary/ENCFF236YZE.w5 32 2 mean CHIP:H2BK15ac:H1-hESC CHIP ChIP-TF:H2BK15ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3738 0 ENCFF858QNH /home/drk/tillage/datasets/human/chip/encode/ENCSR739IHN/summary/ENCFF858QNH.w5 32 2 mean CHIP:TBX21:GM12878 CHIP ChIP-TF:TBX21/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3739 0 ENCFF995BBB /home/drk/tillage/datasets/human/chip/encode/ENCSR740FYN/summary/ENCFF995BBB.w5 32 2 mean CHIP:H3K4me2:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-Histone:H3K4me2/GM23338 male adult (53 years) originated from GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3740 0 ENCFF245AYE /home/drk/tillage/datasets/human/chip/encode/ENCSR740NPG/summary/ENCFF245AYE.w5 32 2 mean CHIP:eGFP-BACH1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-BACH1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3741 0 ENCFF345HFH /home/drk/tillage/datasets/human/chip/encode/ENCSR741FIA/summary/ENCFF345HFH.w5 32 2 mean CHIP:H2BK5ac:H9 CHIP ChIP-TF:H2BK5ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3742 0 ENCFF709SLB /home/drk/tillage/datasets/human/chip/encode/ENCSR741FTW/summary/ENCFF709SLB.w5 32 2 mean CHIP:H3K9me3:neurosphere female embryo (17 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K9me3/neurosphere female embryo (17 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3743 0 ENCFF905WQK /home/drk/tillage/datasets/human/chip/encode/ENCSR741GJT/summary/ENCFF905WQK.w5 32 2 mean CHIP:H3K79me2:ACC112 CHIP ChIP-Histone:H3K79me2/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3744 0 ENCFF890NAY /home/drk/tillage/datasets/human/chip/encode/ENCSR741STU/summary/ENCFF890NAY.w5 32 2 mean CHIP:H3K27ac:DOHH2 CHIP ChIP-Histone:H3K27ac/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3745 0 ENCFF987BMP /home/drk/tillage/datasets/human/chip/encode/ENCSR742IDN/summary/ENCFF987BMP.w5 32 2 mean CHIP:NR2C1:K562 CHIP ChIP-TF:NR2C1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3746 0 ENCFF916WAT /home/drk/tillage/datasets/human/chip/encode/ENCSR742TMU/summary/ENCFF916WAT.w5 32 2 mean CHIP:ZNF282:K562 CHIP ChIP-TF:ZNF282/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3747 0 ENCFF218KJG /home/drk/tillage/datasets/human/chip/encode/ENCSR743DDX/summary/ENCFF218KJG.w5 32 2 mean CHIP:H3K27ac:stomach female embryo (96 days) CHIP ChIP-Histone:H3K27ac/stomach female embryo (96 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3748 0 ENCFF969VZS /home/drk/tillage/datasets/human/chip/encode/ENCSR743JIT/summary/ENCFF969VZS.w5 32 2 mean CHIP:H3K27me3:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K27me3/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3749 0 ENCFF517RZE /home/drk/tillage/datasets/human/chip/encode/ENCSR743KZR/summary/ENCFF517RZE.w5 32 2 mean CHIP:H3K36me3:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-Histone:H3K36me3/esophagus muscularis mucosa female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3750 0 ENCFF505OTI /home/drk/tillage/datasets/human/chip/encode/ENCSR744WOO/summary/ENCFF505OTI.w5 32 2 mean CHIP:TCF12:K562 CHIP ChIP-TF:TCF12/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3751 0 ENCFF455YHL /home/drk/tillage/datasets/human/chip/encode/ENCSR744YJR/summary/ENCFF455YHL.w5 32 2 mean CHIP:CTCF:thyroid gland female adult (53 years) CHIP ChIP-TF:CTCF/thyroid gland female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3752 0 ENCFF573WUB /home/drk/tillage/datasets/human/chip/encode/ENCSR745VSQ/summary/ENCFF573WUB.w5 32 2 mean CHIP:3xFLAG-GMEB2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-GMEB2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3753 0 ENCFF642LUI /home/drk/tillage/datasets/human/chip/encode/ENCSR746CUY/summary/ENCFF642LUI.w5 32 2 mean CHIP:H3K9me3:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K9me3/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3754 0 ENCFF283VUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR746MTU/summary/ENCFF283VUJ.w5 32 2 mean CHIP:H3K36me3:trophoblast female embryo (20 weeks) CHIP ChIP-Histone:H3K36me3/trophoblast female embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3755 0 ENCFF488UTF /home/drk/tillage/datasets/human/chip/encode/ENCSR746QFI/summary/ENCFF488UTF.w5 32 2 mean CHIP:H3K9me3:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K9me3/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3756 0 ENCFF153FDP /home/drk/tillage/datasets/human/chip/encode/ENCSR746XEG/summary/ENCFF153FDP.w5 32 2 mean CHIP:NFXL1:GM12878 CHIP ChIP-TF:NFXL1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3757 0 ENCFF067OGD /home/drk/tillage/datasets/human/chip/encode/ENCSR746ZXP/summary/ENCFF067OGD.w5 32 2 mean CHIP:H3K27me3:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K27me3/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3758 0 ENCFF957ZMS /home/drk/tillage/datasets/human/chip/encode/ENCSR747BYL/summary/ENCFF957ZMS.w5 32 2 mean CHIP:H3K27me3:A673 CHIP ChIP-Histone:H3K27me3/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3759 0 ENCFF706UPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR747HAM/summary/ENCFF706UPZ.w5 32 2 mean CHIP:H3K27ac:ectodermal cell originated from embryonic stem cell CHIP ChIP-Histone:H3K27ac/ectodermal cell originated from embryonic stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3760 0 ENCFF494ZIO /home/drk/tillage/datasets/human/chip/encode/ENCSR747VED/summary/ENCFF494ZIO.w5 32 2 mean CHIP:H3K4me3:pancreas male adult (34 years) CHIP ChIP-Histone:H3K4me3/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3761 0 ENCFF745LUT /home/drk/tillage/datasets/human/chip/encode/ENCSR747ZDF/summary/ENCFF745LUT.w5 32 2 mean CHIP:H4K20me1:OCI-LY7 CHIP ChIP-TF:H4K20me1/OCI-LY7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3762 0 ENCFF583GTP /home/drk/tillage/datasets/human/chip/encode/ENCSR748LUA/summary/ENCFF583GTP.w5 32 2 mean CHIP:H3K27me3:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K27me3/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3763 0 ENCFF180DCO /home/drk/tillage/datasets/human/chip/encode/ENCSR748RBT/summary/ENCFF180DCO.w5 32 2 mean CHIP:H3K4me3:prostate male adult (54 years) CHIP ChIP-Histone:H3K4me3/prostate male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3764 0 ENCFF411PEL /home/drk/tillage/datasets/human/chip/encode/ENCSR748TFF/summary/ENCFF411PEL.w5 32 2 mean CHIP:H3K27ac:body of pancreas female adult (53 years) CHIP ChIP-Histone:H3K27ac/body of pancreas female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3765 0 ENCFF232SNC /home/drk/tillage/datasets/human/chip/encode/ENCSR749ABB/summary/ENCFF232SNC.w5 32 2 mean CHIP:H3K36me3:transverse colon male adult (37 years) CHIP ChIP-Histone:H3K36me3/transverse colon male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3766 0 ENCFF942EMM /home/drk/tillage/datasets/human/chip/encode/ENCSR749ANR/summary/ENCFF942EMM.w5 32 2 mean CHIP:H3K9me3:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K9me3/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3767 0 ENCFF513ULH /home/drk/tillage/datasets/human/chip/encode/ENCSR750LYM/summary/ENCFF513ULH.w5 32 2 mean CHIP:eGFP-NR2C2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-NR2C2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3768 0 ENCFF766GZR /home/drk/tillage/datasets/human/chip/encode/ENCSR750ZCV/summary/ENCFF766GZR.w5 32 2 mean CHIP:H3K9me3:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3769 0 ENCFF030RTP /home/drk/tillage/datasets/human/chip/encode/ENCSR751CJG/summary/ENCFF030RTP.w5 32 2 mean CHIP:CHD4:GM12878 CHIP ChIP-TF:CHD4/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3770 0 ENCFF721EMT /home/drk/tillage/datasets/human/chip/encode/ENCSR751JOQ/summary/ENCFF721EMT.w5 32 2 mean CHIP:H3K36me3:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K36me3/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3771 0 ENCFF081XMI /home/drk/tillage/datasets/human/chip/encode/ENCSR751PNN/summary/ENCFF081XMI.w5 32 2 mean CHIP:eGFP-ZNF112:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF112/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3772 0 ENCFF368GGO /home/drk/tillage/datasets/human/chip/encode/ENCSR752NDX/summary/ENCFF368GGO.w5 32 2 mean CHIP:ZNF282:HepG2 CHIP ChIP-TF:ZNF282/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3773 0 ENCFF515VXR /home/drk/tillage/datasets/human/chip/encode/ENCSR752UOD/summary/ENCFF515VXR.w5 32 2 mean CHIP:H3K27ac:MCF-7 CHIP ChIP-Histone:H3K27ac/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3774 0 ENCFF251VAC /home/drk/tillage/datasets/human/chip/encode/ENCSR753GIA/summary/ENCFF251VAC.w5 32 2 mean CHIP:TARDBP:HEK293T CHIP ChIP-TF:TARDBP/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3775 0 ENCFF476BKI /home/drk/tillage/datasets/human/chip/encode/ENCSR753RYH/summary/ENCFF476BKI.w5 32 2 mean CHIP:H2AK5ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2AK5ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3776 0 ENCFF117QXU /home/drk/tillage/datasets/human/chip/encode/ENCSR754DWU/summary/ENCFF117QXU.w5 32 2 mean CHIP:POLR2A:ovary female adult (53 years) CHIP ChIP-TF:POLR2A/ovary female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3777 0 ENCFF242HGF /home/drk/tillage/datasets/human/chip/encode/ENCSR754MUD/summary/ENCFF242HGF.w5 32 2 mean CHIP:SKI:HepG2 CHIP ChIP-TF:SKI/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3778 0 ENCFF419JCY /home/drk/tillage/datasets/human/chip/encode/ENCSR754SOI/summary/ENCFF419JCY.w5 32 2 mean CHIP:eGFP-ZNF529:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF529/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3779 0 ENCFF716WLE /home/drk/tillage/datasets/human/chip/encode/ENCSR754VAJ/summary/ENCFF716WLE.w5 32 2 mean CHIP:H3K27me3:H9 genetically modified using stable transfection CHIP ChIP-Histone:H3K27me3/H9 genetically modified using stable transfection ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3780 0 ENCFF962YWD /home/drk/tillage/datasets/human/chip/encode/ENCSR754ZHU/summary/ENCFF962YWD.w5 32 2 mean CHIP:SNRNP70:K562 CHIP ChIP-TF:SNRNP70/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3781 0 ENCFF743FWJ /home/drk/tillage/datasets/human/chip/encode/ENCSR756KRS/summary/ENCFF743FWJ.w5 32 2 mean CHIP:CTCF:suprapubic skin female adult (51 year) CHIP ChIP-TF:CTCF/suprapubic skin female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3782 0 ENCFF788DWH /home/drk/tillage/datasets/human/chip/encode/ENCSR756RGW/summary/ENCFF788DWH.w5 32 2 mean CHIP:H3K9ac:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K9ac/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3783 0 ENCFF945NTG /home/drk/tillage/datasets/human/chip/encode/ENCSR756URL/summary/ENCFF945NTG.w5 32 2 mean CHIP:CTCF:esophagus squamous epithelium female adult (53 years) CHIP ChIP-TF:CTCF/esophagus squamous epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3784 0 ENCFF832UOL /home/drk/tillage/datasets/human/chip/encode/ENCSR756ZKG/summary/ENCFF832UOL.w5 32 2 mean CHIP:CTCF:OCI-LY3 CHIP ChIP-TF:CTCF/OCI-LY3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3785 0 ENCFF215RSZ /home/drk/tillage/datasets/human/chip/encode/ENCSR757EKM/summary/ENCFF215RSZ.w5 32 2 mean CHIP:3xFLAG-KLF6:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KLF6/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3786 0 ENCFF610VCS /home/drk/tillage/datasets/human/chip/encode/ENCSR757EMK/summary/ENCFF610VCS.w5 32 2 mean CHIP:SUZ12:MCF-7 CHIP ChIP-TF:SUZ12/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3787 0 ENCFF677HOP /home/drk/tillage/datasets/human/chip/encode/ENCSR757IIU/summary/ENCFF677HOP.w5 32 2 mean CHIP:HMBOX1:K562 CHIP ChIP-TF:HMBOX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3788 0 ENCFF824FYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR758GMX/summary/ENCFF824FYQ.w5 32 2 mean CHIP:H3K9me3:hepatocyte originated from H9 CHIP ChIP-Histone:H3K9me3/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3789 0 ENCFF226XSS /home/drk/tillage/datasets/human/chip/encode/ENCSR758OEC/summary/ENCFF226XSS.w5 32 2 mean CHIP:H3K27ac:MM.1S CHIP ChIP-Histone:H3K27ac/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3790 0 ENCFF311BHZ /home/drk/tillage/datasets/human/chip/encode/ENCSR759BDG/summary/ENCFF311BHZ.w5 32 2 mean CHIP:3xFLAG-BCL6:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-BCL6/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3791 0 ENCFF103YFF /home/drk/tillage/datasets/human/chip/encode/ENCSR760AAY/summary/ENCFF103YFF.w5 32 2 mean CHIP:eGFP-PRDM12:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM12/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3792 0 ENCFF328UXQ /home/drk/tillage/datasets/human/chip/encode/ENCSR760EGQ/summary/ENCFF328UXQ.w5 32 2 mean CHIP:H3K9me3:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K9me3/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3793 0 ENCFF120IIN /home/drk/tillage/datasets/human/chip/encode/ENCSR760LFY/summary/ENCFF120IIN.w5 32 2 mean CHIP:H3K36me3:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K36me3/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3794 0 ENCFF843GNH /home/drk/tillage/datasets/human/chip/encode/ENCSR760UKJ/summary/ENCFF843GNH.w5 32 2 mean CHIP:ARNT:HEK293T CHIP ChIP-TF:ARNT/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3795 0 ENCFF845AHN /home/drk/tillage/datasets/human/chip/encode/ENCSR760UVO/summary/ENCFF845AHN.w5 32 2 mean CHIP:KLF16:K562 CHIP ChIP-TF:KLF16/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3796 0 ENCFF594JWP /home/drk/tillage/datasets/human/chip/encode/ENCSR760ZVL/summary/ENCFF594JWP.w5 32 2 mean CHIP:H4K20me1:Loucy CHIP ChIP-TF:H4K20me1/Loucy ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3797 0 ENCFF221VOV /home/drk/tillage/datasets/human/chip/encode/ENCSR761AKF/summary/ENCFF221VOV.w5 32 2 mean CHIP:H3K9ac:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K9ac/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3798 0 ENCFF495QYP /home/drk/tillage/datasets/human/chip/encode/ENCSR761DLU/summary/ENCFF495QYP.w5 32 2 mean CHIP:H3K27me3:MCF-7 CHIP ChIP-Histone:H3K27me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3799 0 ENCFF803HAQ /home/drk/tillage/datasets/human/chip/encode/ENCSR761KZV/summary/ENCFF803HAQ.w5 32 2 mean CHIP:H3K27me3:kidney female embryo (120 days) CHIP ChIP-Histone:H3K27me3/kidney female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3800 0 ENCFF330XDO /home/drk/tillage/datasets/human/chip/encode/ENCSR761LRR/summary/ENCFF330XDO.w5 32 2 mean CHIP:ZNF512B:MCF-7 CHIP ChIP-TF:ZNF512B/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3801 0 ENCFF366KBC /home/drk/tillage/datasets/human/chip/encode/ENCSR761RDB/summary/ENCFF366KBC.w5 32 2 mean CHIP:EP300:transverse colon female adult (53 years) CHIP ChIP-TF:EP300/transverse colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3802 0 ENCFF468USL /home/drk/tillage/datasets/human/chip/encode/ENCSR761WVQ/summary/ENCFF468USL.w5 32 2 mean CHIP:H3K4me3:thyroid gland female adult (53 years) CHIP ChIP-Histone:H3K4me3/thyroid gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3803 0 ENCFF591HEB /home/drk/tillage/datasets/human/chip/encode/ENCSR762DQP/summary/ENCFF591HEB.w5 32 2 mean CHIP:eGFP-ZNF658:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF658/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3804 0 ENCFF966IHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR762PCG/summary/ENCFF966IHQ.w5 32 2 mean CHIP:CTCF:subcutaneous adipose tissue female adult (53 years) CHIP ChIP-TF:CTCF/subcutaneous adipose tissue female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3805 0 ENCFF710VGE /home/drk/tillage/datasets/human/chip/encode/ENCSR762ZLM/summary/ENCFF710VGE.w5 32 2 mean CHIP:H3K4me1:thymus male child (3 years) CHIP ChIP-Histone:H3K4me1/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3806 0 ENCFF589HRX /home/drk/tillage/datasets/human/chip/encode/ENCSR763IDK/summary/ENCFF589HRX.w5 32 2 mean CHIP:H3K27ac:prostate male adult (54 years) CHIP ChIP-Histone:H3K27ac/prostate male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3807 0 ENCFF700YOH /home/drk/tillage/datasets/human/chip/encode/ENCSR764CZW/summary/ENCFF700YOH.w5 32 2 mean CHIP:ZNF217:GM12878 CHIP ChIP-TF:ZNF217/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3808 0 ENCFF117BEB /home/drk/tillage/datasets/human/chip/encode/ENCSR764KFK/summary/ENCFF117BEB.w5 32 2 mean CHIP:H4K20me1:PC-3 CHIP ChIP-TF:H4K20me1/PC-3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3809 0 ENCFF102ZEV /home/drk/tillage/datasets/human/chip/encode/ENCSR764OXF/summary/ENCFF102ZEV.w5 32 2 mean CHIP:RBM39:K562 CHIP ChIP-TF:RBM39/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3810 0 ENCFF984NUR /home/drk/tillage/datasets/human/chip/encode/ENCSR764XUL/summary/ENCFF984NUR.w5 32 2 mean CHIP:H3K4me1:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K4me1/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3811 0 ENCFF661MCI /home/drk/tillage/datasets/human/chip/encode/ENCSR764YDL/summary/ENCFF661MCI.w5 32 2 mean CHIP:NR0B1:K562 CHIP ChIP-TF:NR0B1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3812 0 ENCFF277XHE /home/drk/tillage/datasets/human/chip/encode/ENCSR765MKZ/summary/ENCFF277XHE.w5 32 2 mean CHIP:3xFLAG-DRAP1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-DRAP1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3813 0 ENCFF615NDO /home/drk/tillage/datasets/human/chip/encode/ENCSR765SCM/summary/ENCFF615NDO.w5 32 2 mean CHIP:H3K36me3:neurosphere embryo (15 weeks) originated from ganglionic eminence CHIP ChIP-Histone:H3K36me3/neurosphere embryo (15 weeks) originated from ganglionic eminence ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3814 0 ENCFF525KYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR767NIF/summary/ENCFF525KYJ.w5 32 2 mean CHIP:H3K4me3:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K4me3/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3815 0 ENCFF853XLN /home/drk/tillage/datasets/human/chip/encode/ENCSR767NPV/summary/ENCFF853XLN.w5 32 2 mean CHIP:H3K9me3:chorionic villus male embryo (16 weeks) CHIP ChIP-Histone:H3K9me3/chorionic villus male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3816 0 ENCFF080CYW /home/drk/tillage/datasets/human/chip/encode/ENCSR767WVZ/summary/ENCFF080CYW.w5 32 2 mean CHIP:H3K4me1:chorion male embryo (16 weeks) CHIP ChIP-Histone:H3K4me1/chorion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3817 0 ENCFF935ARE /home/drk/tillage/datasets/human/chip/encode/ENCSR767XSF/summary/ENCFF935ARE.w5 32 2 mean CHIP:eGFP-ZNF555:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF555/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3818 0 ENCFF692RJD /home/drk/tillage/datasets/human/chip/encode/ENCSR768DMK/summary/ENCFF692RJD.w5 32 2 mean CHIP:H3K9ac:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K9ac/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3819 0 ENCFF688YVV /home/drk/tillage/datasets/human/chip/encode/ENCSR768FWX/summary/ENCFF688YVV.w5 32 2 mean CHIP:H3K56ac:H1-hESC CHIP ChIP-Histone:H3K56ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3820 0 ENCFF554CJS /home/drk/tillage/datasets/human/chip/encode/ENCSR768HOH/summary/ENCFF554CJS.w5 32 2 mean CHIP:eGFP-ZNF324:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF324/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3821 0 ENCFF285VPD /home/drk/tillage/datasets/human/chip/encode/ENCSR768LIO/summary/ENCFF285VPD.w5 32 2 mean CHIP:eGFP-OVOL3:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-OVOL3/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3822 0 ENCFF647TKC /home/drk/tillage/datasets/human/chip/encode/ENCSR768SPE/summary/ENCFF647TKC.w5 32 2 mean CHIP:H3K9me3:B cell male adult (37 years) CHIP ChIP-Histone:H3K9me3/B cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3823 0 ENCFF983KHI /home/drk/tillage/datasets/human/chip/encode/ENCSR768VNZ/summary/ENCFF983KHI.w5 32 2 mean CHIP:eGFP-ZSCAN30:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN30/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3824 0 ENCFF951CMP /home/drk/tillage/datasets/human/chip/encode/ENCSR769FOC/summary/ENCFF951CMP.w5 32 2 mean CHIP:H3K27ac:PC-9 CHIP ChIP-Histone:H3K27ac/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3825 0 ENCFF620XVA /home/drk/tillage/datasets/human/chip/encode/ENCSR769HUN/summary/ENCFF620XVA.w5 32 2 mean CHIP:H3K27me3:adipocyte originated from mesenchymal stem cell CHIP ChIP-Histone:H3K27me3/adipocyte originated from mesenchymal stem cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3826 0 ENCFF981MMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR769JRS/summary/ENCFF981MMQ.w5 32 2 mean CHIP:eGFP-AEBP2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-AEBP2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3827 0 ENCFF720HUE /home/drk/tillage/datasets/human/chip/encode/ENCSR769SGQ/summary/ENCFF720HUE.w5 32 2 mean CHIP:H3K27me3:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K27me3/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3828 0 ENCFF458ZYU /home/drk/tillage/datasets/human/chip/encode/ENCSR769WKR/summary/ENCFF458ZYU.w5 32 2 mean CHIP:CTCF:transverse colon female adult (53 years) CHIP ChIP-TF:CTCF/transverse colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3829 0 ENCFF439CMK /home/drk/tillage/datasets/human/chip/encode/ENCSR770AOR/summary/ENCFF439CMK.w5 32 2 mean CHIP:3xFLAG-ELF3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ELF3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3830 0 ENCFF020KPS /home/drk/tillage/datasets/human/chip/encode/ENCSR770GNM/summary/ENCFF020KPS.w5 32 2 mean CHIP:H3K27me3:mucosa of stomach male adult (59 years) CHIP ChIP-Histone:H3K27me3/mucosa of stomach male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3831 0 ENCFF350UER /home/drk/tillage/datasets/human/chip/encode/ENCSR770IWO/summary/ENCFF350UER.w5 32 2 mean CHIP:CTCF:adrenal gland female adult (53 years) CHIP ChIP-TF:CTCF/adrenal gland female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3832 0 ENCFF951KMM /home/drk/tillage/datasets/human/chip/encode/ENCSR770PQN/summary/ENCFF951KMM.w5 32 2 mean CHIP:eGFP-BCL11B:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-BCL11B/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3833 0 ENCFF504KHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR770WSE/summary/ENCFF504KHQ.w5 32 2 mean CHIP:H3K27me3:breast epithelium female adult (53 years) CHIP ChIP-Histone:H3K27me3/breast epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3834 0 ENCFF673YNA /home/drk/tillage/datasets/human/chip/encode/ENCSR771GTF/summary/ENCFF673YNA.w5 32 2 mean CHIP:SUZ12:HepG2 CHIP ChIP-TF:SUZ12/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3835 0 ENCFF211JNO /home/drk/tillage/datasets/human/chip/encode/ENCSR771QCM/summary/ENCFF211JNO.w5 32 2 mean CHIP:H3F3A:SU-DHL-6 CHIP ChIP-Histone:H3F3A/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3836 0 ENCFF420PYG /home/drk/tillage/datasets/human/chip/encode/ENCSR771YJT/summary/ENCFF420PYG.w5 32 2 mean CHIP:H3K27ac:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K27ac/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3837 0 ENCFF591WOF /home/drk/tillage/datasets/human/chip/encode/ENCSR772EEN/summary/ENCFF591WOF.w5 32 2 mean CHIP:eGFP-RELA:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-RELA/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3838 0 ENCFF216RHI /home/drk/tillage/datasets/human/chip/encode/ENCSR773JBP/summary/ENCFF216RHI.w5 32 2 mean CHIP:CTCF:esophagus squamous epithelium female adult (53 years) CHIP ChIP-TF:CTCF/esophagus squamous epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3839 0 ENCFF105NEW /home/drk/tillage/datasets/human/chip/encode/ENCSR773QRB/summary/ENCFF105NEW.w5 32 2 mean CHIP:EP300:suprapubic skin male adult (54 years) CHIP ChIP-TF:EP300/suprapubic skin male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3840 0 ENCFF788EEP /home/drk/tillage/datasets/human/chip/encode/ENCSR773REP/summary/ENCFF788EEP.w5 32 2 mean CHIP:eGFP-ZBTB7A:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB7A/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3841 0 ENCFF840WKB /home/drk/tillage/datasets/human/chip/encode/ENCSR773TWR/summary/ENCFF840WKB.w5 32 2 mean CHIP:H3K9me3:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K9me3/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3842 0 ENCFF661FZC /home/drk/tillage/datasets/human/chip/encode/ENCSR774CFO/summary/ENCFF661FZC.w5 32 2 mean CHIP:H3K27me3:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K27me3/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3843 0 ENCFF235QUM /home/drk/tillage/datasets/human/chip/encode/ENCSR774OKQ/summary/ENCFF235QUM.w5 32 2 mean CHIP:H3K36me3:CD4-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K36me3/CD4-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3844 0 ENCFF100ZDL /home/drk/tillage/datasets/human/chip/encode/ENCSR775FTU/summary/ENCFF100ZDL.w5 32 2 mean CHIP:H3K27ac:muscle of trunk female embryo (115 days) CHIP ChIP-Histone:H3K27ac/muscle of trunk female embryo (115 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3845 0 ENCFF130MZO /home/drk/tillage/datasets/human/chip/encode/ENCSR775GZI/summary/ENCFF130MZO.w5 32 2 mean CHIP:H3K36me3:HUES48 CHIP ChIP-Histone:H3K36me3/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3846 0 ENCFF471ITM /home/drk/tillage/datasets/human/chip/encode/ENCSR775HFF/summary/ENCFF471ITM.w5 32 2 mean CHIP:eGFP-ZNF791:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF791/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3847 0 ENCFF966AKF /home/drk/tillage/datasets/human/chip/encode/ENCSR775VUA/summary/ENCFF966AKF.w5 32 2 mean CHIP:POLR2A:stomach male adult (37 years) CHIP ChIP-TF:POLR2A/stomach male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3848 0 ENCFF848ZIL /home/drk/tillage/datasets/human/chip/encode/ENCSR776AEL/summary/ENCFF848ZIL.w5 32 2 mean CHIP:CTCF:stomach female adult (53 years) CHIP ChIP-TF:CTCF/stomach female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3849 0 ENCFF414YUK /home/drk/tillage/datasets/human/chip/encode/ENCSR776CYN/summary/ENCFF414YUK.w5 32 2 mean CHIP:ZFP36:K562 CHIP ChIP-TF:ZFP36/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3850 0 ENCFF121ELJ /home/drk/tillage/datasets/human/chip/encode/ENCSR776EAH/summary/ENCFF121ELJ.w5 32 2 mean CHIP:H3K4me1:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K4me1/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3851 0 ENCFF291OIO /home/drk/tillage/datasets/human/chip/encode/ENCSR776KLS/summary/ENCFF291OIO.w5 32 2 mean CHIP:H3K27ac:thymus female embryo (110 days) CHIP ChIP-Histone:H3K27ac/thymus female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3852 0 ENCFF627WFI /home/drk/tillage/datasets/human/chip/encode/ENCSR776LDJ/summary/ENCFF627WFI.w5 32 2 mean CHIP:eGFP-ZNF645:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF645/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3853 0 ENCFF802NYF /home/drk/tillage/datasets/human/chip/encode/ENCSR776MDR/summary/ENCFF802NYF.w5 32 2 mean CHIP:eGFP-ZNF577:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF577/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3854 0 ENCFF611AMV /home/drk/tillage/datasets/human/chip/encode/ENCSR777CQW/summary/ENCFF611AMV.w5 32 2 mean CHIP:H3K27ac:22Rv1 treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours CHIP ChIP-Histone:H3K27ac/22Rv1 treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3855 0 ENCFF704DNO /home/drk/tillage/datasets/human/chip/encode/ENCSR777RWW/summary/ENCFF704DNO.w5 32 2 mean CHIP:H3K4me1:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3856 0 ENCFF994SQI /home/drk/tillage/datasets/human/chip/encode/ENCSR777YSB/summary/ENCFF994SQI.w5 32 2 mean CHIP:eGFP-ZNF781:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF781/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3857 0 ENCFF737TZT /home/drk/tillage/datasets/human/chip/encode/ENCSR778QLY/summary/ENCFF737TZT.w5 32 2 mean CHIP:ELF4:HEK293T CHIP ChIP-TF:ELF4/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3858 0 ENCFF805NTL /home/drk/tillage/datasets/human/chip/encode/ENCSR778UBR/summary/ENCFF805NTL.w5 32 2 mean CHIP:ARID3A:GM12878 CHIP ChIP-TF:ARID3A/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3859 0 ENCFF260LNF /home/drk/tillage/datasets/human/chip/encode/ENCSR778VGY/summary/ENCFF260LNF.w5 32 2 mean CHIP:H3K4me3:ACC112 CHIP ChIP-Histone:H3K4me3/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3860 0 ENCFF459YNI /home/drk/tillage/datasets/human/chip/encode/ENCSR779KYW/summary/ENCFF459YNI.w5 32 2 mean CHIP:H4K20me1:OCI-LY3 CHIP ChIP-TF:H4K20me1/OCI-LY3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3861 0 ENCFF347PIT /home/drk/tillage/datasets/human/chip/encode/ENCSR779NON/summary/ENCFF347PIT.w5 32 2 mean CHIP:EP300:omental fat pad female adult (51 year) CHIP ChIP-TF:EP300/omental fat pad female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3862 0 ENCFF681ZVH /home/drk/tillage/datasets/human/chip/encode/ENCSR780BBJ/summary/ENCFF681ZVH.w5 32 2 mean CHIP:ZZZ3:K562 CHIP ChIP-TF:ZZZ3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3863 0 ENCFF447KQW /home/drk/tillage/datasets/human/chip/encode/ENCSR780ESQ/summary/ENCFF447KQW.w5 32 2 mean CHIP:eGFP-KLF14:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF14/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3864 0 ENCFF997IXW /home/drk/tillage/datasets/human/chip/encode/ENCSR780FXX/summary/ENCFF997IXW.w5 32 2 mean CHIP:H3K4me3:brain female embryo (17 weeks) CHIP ChIP-Histone:H3K4me3/brain female embryo (17 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3865 0 ENCFF837MFV /home/drk/tillage/datasets/human/chip/encode/ENCSR780OZE/summary/ENCFF837MFV.w5 32 2 mean CHIP:CTCF:Parathyroid adenoma male adult (62 years) CHIP ChIP-TF:CTCF/Parathyroid adenoma male adult (62 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3866 0 ENCFF525DEC /home/drk/tillage/datasets/human/chip/encode/ENCSR781EQJ/summary/ENCFF525DEC.w5 32 2 mean CHIP:eGFP-ZBTB48:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB48/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3867 0 ENCFF226CBX /home/drk/tillage/datasets/human/chip/encode/ENCSR781OGI/summary/ENCFF226CBX.w5 32 2 mean CHIP:H3K36me3:temporal lobe female adult (75 years) CHIP ChIP-Histone:H3K36me3/temporal lobe female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3868 0 ENCFF178ZHP /home/drk/tillage/datasets/human/chip/encode/ENCSR781UXO/summary/ENCFF178ZHP.w5 32 2 mean CHIP:H3K9ac:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K9ac/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3869 0 ENCFF639NFJ /home/drk/tillage/datasets/human/chip/encode/ENCSR782NOO/summary/ENCFF639NFJ.w5 32 2 mean CHIP:H3K36me3:CD8-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K36me3/CD8-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3870 0 ENCFF528VSB /home/drk/tillage/datasets/human/chip/encode/ENCSR782OZZ/summary/ENCFF528VSB.w5 32 2 mean CHIP:H3K4me1:sigmoid colon male adult (34 years) CHIP ChIP-Histone:H3K4me1/sigmoid colon male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3871 0 ENCFF376OMS /home/drk/tillage/datasets/human/chip/encode/ENCSR782WRO/summary/ENCFF376OMS.w5 32 2 mean CHIP:BMI1:K562 CHIP ChIP-TF:BMI1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3872 0 ENCFF736JLA /home/drk/tillage/datasets/human/chip/encode/ENCSR783AXV/summary/ENCFF736JLA.w5 32 2 mean CHIP:H3K4me2:smooth muscle cell originated from H9 CHIP ChIP-Histone:H3K4me2/smooth muscle cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3873 0 ENCFF288NSX /home/drk/tillage/datasets/human/chip/encode/ENCSR783QUL/summary/ENCFF288NSX.w5 32 2 mean CHIP:EZH2phosphoT487:Loucy CHIP ChIP-TF:EZH2phosphoT487/Loucy ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3874 0 ENCFF590RFM /home/drk/tillage/datasets/human/chip/encode/ENCSR784AQY/summary/ENCFF590RFM.w5 32 2 mean CHIP:H3K36me3:DOHH2 CHIP ChIP-Histone:H3K36me3/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3875 0 ENCFF025DFU /home/drk/tillage/datasets/human/chip/encode/ENCSR784FYS/summary/ENCFF025DFU.w5 32 2 mean CHIP:RBFOX2:HepG2 CHIP ChIP-TF:RBFOX2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3876 0 ENCFF980IVI /home/drk/tillage/datasets/human/chip/encode/ENCSR784VIQ/summary/ENCFF980IVI.w5 32 2 mean CHIP:NR2C1:GM12878 CHIP ChIP-TF:NR2C1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3877 0 ENCFF308TCO /home/drk/tillage/datasets/human/chip/encode/ENCSR784VUY/summary/ENCFF308TCO.w5 32 2 mean CHIP:RNF2:H1-hESC CHIP ChIP-TF:RNF2/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3878 0 ENCFF549MDM /home/drk/tillage/datasets/human/chip/encode/ENCSR785DJD/summary/ENCFF549MDM.w5 32 2 mean CHIP:H3K4me3:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K4me3/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3879 0 ENCFF609ZOH /home/drk/tillage/datasets/human/chip/encode/ENCSR785OKZ/summary/ENCFF609ZOH.w5 32 2 mean CHIP:RB1:GM12878 CHIP ChIP-TF:RB1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3880 0 ENCFF722QMK /home/drk/tillage/datasets/human/chip/encode/ENCSR785UCD/summary/ENCFF722QMK.w5 32 2 mean CHIP:ZNF8:MCF-7 CHIP ChIP-TF:ZNF8/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3881 0 ENCFF822HVX /home/drk/tillage/datasets/human/chip/encode/ENCSR785YRL/summary/ENCFF822HVX.w5 32 2 mean CHIP:CTCF:neutrophil CHIP ChIP-TF:CTCF/neutrophil ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3882 0 ENCFF317HRT /home/drk/tillage/datasets/human/chip/encode/ENCSR786DQB/summary/ENCFF317HRT.w5 32 2 mean CHIP:H3K36me3:amnion male embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/amnion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3883 0 ENCFF423TYW /home/drk/tillage/datasets/human/chip/encode/ENCSR786ESI/summary/ENCFF423TYW.w5 32 2 mean CHIP:H3K27me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3884 0 ENCFF603WMX /home/drk/tillage/datasets/human/chip/encode/ENCSR786GJM/summary/ENCFF603WMX.w5 32 2 mean CHIP:H3K4me2:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K4me2/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3885 0 ENCFF893QJX /home/drk/tillage/datasets/human/chip/encode/ENCSR786OQY/summary/ENCFF893QJX.w5 32 2 mean CHIP:ZBTB5:K562 CHIP ChIP-TF:ZBTB5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3886 0 ENCFF123OGY /home/drk/tillage/datasets/human/chip/encode/ENCSR787CAJ/summary/ENCFF123OGY.w5 32 2 mean CHIP:H3K4me3:chorion female embryo (40 weeks) CHIP ChIP-Histone:H3K4me3/chorion female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3887 0 ENCFF281HGI /home/drk/tillage/datasets/human/chip/encode/ENCSR787RVK/summary/ENCFF281HGI.w5 32 2 mean CHIP:eGFP-TSC22D4:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-TSC22D4/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3888 0 ENCFF729UMG /home/drk/tillage/datasets/human/chip/encode/ENCSR787WLV/summary/ENCFF729UMG.w5 32 2 mean CHIP:H3K9me3:CD4-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K9me3/CD4-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3889 0 ENCFF059QLV /home/drk/tillage/datasets/human/chip/encode/ENCSR788EQL/summary/ENCFF059QLV.w5 32 2 mean CHIP:H3K4me2:PC-3 CHIP ChIP-Histone:H3K4me2/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3890 0 ENCFF049NNZ /home/drk/tillage/datasets/human/chip/encode/ENCSR788RSW/summary/ENCFF049NNZ.w5 32 2 mean CHIP:SOX6:K562 CHIP ChIP-TF:SOX6/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3891 0 ENCFF948OZS /home/drk/tillage/datasets/human/chip/encode/ENCSR788XNX/summary/ENCFF948OZS.w5 32 2 mean CHIP:RFX1:MCF-7 CHIP ChIP-TF:RFX1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3892 0 ENCFF110SAT /home/drk/tillage/datasets/human/chip/encode/ENCSR789GVU/summary/ENCFF110SAT.w5 32 2 mean CHIP:BHLHE40:HEK293T CHIP ChIP-TF:BHLHE40/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3893 0 ENCFF297UBV /home/drk/tillage/datasets/human/chip/encode/ENCSR790EDQ/summary/ENCFF297UBV.w5 32 2 mean CHIP:H3K4me2:OCI-LY1 CHIP ChIP-Histone:H3K4me2/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3894 0 ENCFF678COX /home/drk/tillage/datasets/human/chip/encode/ENCSR790QWJ/summary/ENCFF678COX.w5 32 2 mean CHIP:H4K20me1:KMS-11 CHIP ChIP-TF:H4K20me1/KMS-11 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3895 0 ENCFF496YPU /home/drk/tillage/datasets/human/chip/encode/ENCSR790VEV/summary/ENCFF496YPU.w5 32 2 mean CHIP:CTCF:subcutaneous adipose tissue female adult (51 year) CHIP ChIP-TF:CTCF/subcutaneous adipose tissue female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3896 0 ENCFF541SRY /home/drk/tillage/datasets/human/chip/encode/ENCSR791AGT/summary/ENCFF541SRY.w5 32 2 mean CHIP:ZNF24:HepG2 CHIP ChIP-TF:ZNF24/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3897 0 ENCFF167JXJ /home/drk/tillage/datasets/human/chip/encode/ENCSR791AYW/summary/ENCFF167JXJ.w5 32 2 mean CHIP:CTCF:heart left ventricle female adult (51 year) CHIP ChIP-TF:CTCF/heart left ventricle female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3898 0 ENCFF986CZC /home/drk/tillage/datasets/human/chip/encode/ENCSR791GCO/summary/ENCFF986CZC.w5 32 2 mean CHIP:H3K4me3:heart right ventricle male adult (34 years) CHIP ChIP-Histone:H3K4me3/heart right ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3899 0 ENCFF868AWA /home/drk/tillage/datasets/human/chip/encode/ENCSR791INM/summary/ENCFF868AWA.w5 32 2 mean CHIP:H3K4me2:SK-N-SH CHIP ChIP-Histone:H3K4me2/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3900 0 ENCFF713BLF /home/drk/tillage/datasets/human/chip/encode/ENCSR791ISZ/summary/ENCFF713BLF.w5 32 2 mean CHIP:H3K27ac:psoas muscle male adult (34 years) CHIP ChIP-Histone:H3K27ac/psoas muscle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3901 0 ENCFF759FCM /home/drk/tillage/datasets/human/chip/encode/ENCSR791KFQ/summary/ENCFF759FCM.w5 32 2 mean CHIP:H3K4me3:right atrium auricular region female adult (53 years) CHIP ChIP-Histone:H3K4me3/right atrium auricular region female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3902 0 ENCFF077HMG /home/drk/tillage/datasets/human/chip/encode/ENCSR791LZY/summary/ENCFF077HMG.w5 32 2 mean CHIP:H3K4me1:transverse colon female adult (53 years) CHIP ChIP-Histone:H3K4me1/transverse colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3903 0 ENCFF218VKE /home/drk/tillage/datasets/human/chip/encode/ENCSR791OZM/summary/ENCFF218VKE.w5 32 2 mean CHIP:RBM25:K562 CHIP ChIP-TF:RBM25/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3904 0 ENCFF783ZFY /home/drk/tillage/datasets/human/chip/encode/ENCSR792GCH/summary/ENCFF783ZFY.w5 32 2 mean CHIP:H3K27me3:H9 CHIP ChIP-Histone:H3K27me3/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3905 0 ENCFF843QTK /home/drk/tillage/datasets/human/chip/encode/ENCSR792IJA/summary/ENCFF843QTK.w5 32 2 mean CHIP:H3K4me3:small intestine male adult (34 years) CHIP ChIP-Histone:H3K4me3/small intestine male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3906 0 ENCFF305XLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR792IYC/summary/ENCFF305XLQ.w5 32 2 mean CHIP:BCLAF1:K562 CHIP ChIP-TF:BCLAF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3907 0 ENCFF110LLP /home/drk/tillage/datasets/human/chip/encode/ENCSR792MZV/summary/ENCFF110LLP.w5 32 2 mean CHIP:3xFLAG-MYRF:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MYRF/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3908 0 ENCFF562LWC /home/drk/tillage/datasets/human/chip/encode/ENCSR792NZO/summary/ENCFF562LWC.w5 32 2 mean CHIP:H3K4me3:iPS-18c female adult (48 years) CHIP ChIP-Histone:H3K4me3/iPS-18c female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3909 0 ENCFF873VXN /home/drk/tillage/datasets/human/chip/encode/ENCSR793HVL/summary/ENCFF873VXN.w5 32 2 mean CHIP:E2F8:GM12878 CHIP ChIP-TF:E2F8/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3910 0 ENCFF614LQR /home/drk/tillage/datasets/human/chip/encode/ENCSR793PLF/summary/ENCFF614LQR.w5 32 2 mean CHIP:H3K27me3:right atrium auricular region female adult (53 years) CHIP ChIP-Histone:H3K27me3/right atrium auricular region female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3911 0 ENCFF218VVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR793USK/summary/ENCFF218VVQ.w5 32 2 mean CHIP:EZH2:PC-9 CHIP ChIP-TF:EZH2/PC-9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3912 0 ENCFF783QRO /home/drk/tillage/datasets/human/chip/encode/ENCSR794ULT/summary/ENCFF783QRO.w5 32 2 mean CHIP:H3K4me2:HCT116 CHIP ChIP-Histone:H3K4me2/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3913 0 ENCFF694DDU /home/drk/tillage/datasets/human/chip/encode/ENCSR795IYP/summary/ENCFF694DDU.w5 32 2 mean CHIP:JUNB:K562 CHIP ChIP-TF:JUNB/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3914 0 ENCFF641UEZ /home/drk/tillage/datasets/human/chip/encode/ENCSR795VEN/summary/ENCFF641UEZ.w5 32 2 mean CHIP:H3K4me3:liver male adult (32 years) CHIP ChIP-Histone:H3K4me3/liver male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3915 0 ENCFF039MOH /home/drk/tillage/datasets/human/chip/encode/ENCSR796CSH/summary/ENCFF039MOH.w5 32 2 mean CHIP:H3K4me3:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K4me3/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3916 0 ENCFF363RHA /home/drk/tillage/datasets/human/chip/encode/ENCSR796FCS/summary/ENCFF363RHA.w5 32 2 mean CHIP:H3K4me3:CD14-positive monocyte male adult (37 years) CHIP ChIP-Histone:H3K4me3/CD14-positive monocyte male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3917 0 ENCFF630OGT /home/drk/tillage/datasets/human/chip/encode/ENCSR796ITY/summary/ENCFF630OGT.w5 32 2 mean CHIP:NFIC:K562 CHIP ChIP-TF:NFIC/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3918 0 ENCFF677GHO /home/drk/tillage/datasets/human/chip/encode/ENCSR797GOJ/summary/ENCFF677GHO.w5 32 2 mean CHIP:H3K27me3:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27me3/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3919 0 ENCFF909HXM /home/drk/tillage/datasets/human/chip/encode/ENCSR797IXN/summary/ENCFF909HXM.w5 32 2 mean CHIP:H3K4me1:layer of hippocampus male adult (73 years) CHIP ChIP-Histone:H3K4me1/layer of hippocampus male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3920 0 ENCFF808IWR /home/drk/tillage/datasets/human/chip/encode/ENCSR797SWM/summary/ENCFF808IWR.w5 32 2 mean CHIP:MITF:K562 CHIP ChIP-TF:MITF/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3921 0 ENCFF752ZNW /home/drk/tillage/datasets/human/chip/encode/ENCSR798EGJ/summary/ENCFF752ZNW.w5 32 2 mean CHIP:RNF2:A549 CHIP ChIP-TF:RNF2/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3922 0 ENCFF851CDJ /home/drk/tillage/datasets/human/chip/encode/ENCSR798IJO/summary/ENCFF851CDJ.w5 32 2 mean CHIP:3xFLAG-NR2F6:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-NR2F6/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3923 0 ENCFF864EVQ /home/drk/tillage/datasets/human/chip/encode/ENCSR798ILC/summary/ENCFF864EVQ.w5 32 2 mean CHIP:NCOR1:K562 CHIP ChIP-TF:NCOR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3924 0 ENCFF791NUX /home/drk/tillage/datasets/human/chip/encode/ENCSR798NVH/summary/ENCFF791NUX.w5 32 2 mean CHIP:CTCF:uterus female adult (51 year) CHIP ChIP-TF:CTCF/uterus female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3925 0 ENCFF961LCE /home/drk/tillage/datasets/human/chip/encode/ENCSR798RTU/summary/ENCFF961LCE.w5 32 2 mean CHIP:H3K27ac:caudate nucleus female adult (75 years) CHIP ChIP-Histone:H3K27ac/caudate nucleus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3926 0 ENCFF864YCT /home/drk/tillage/datasets/human/chip/encode/ENCSR799GOY/summary/ENCFF864YCT.w5 32 2 mean CHIP:YBX1:HepG2 CHIP ChIP-TF:YBX1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3927 0 ENCFF145ZOK /home/drk/tillage/datasets/human/chip/encode/ENCSR799SLA/summary/ENCFF145ZOK.w5 32 2 mean CHIP:H3K9ac:B cell female adult (27 years) and female adult (43 years) CHIP ChIP-Histone:H3K9ac/B cell female adult (27 years) and female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3928 0 ENCFF827WME /home/drk/tillage/datasets/human/chip/encode/ENCSR799SRL/summary/ENCFF827WME.w5 32 2 mean CHIP:H3K27ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K27ac/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3929 0 ENCFF243BGZ /home/drk/tillage/datasets/human/chip/encode/ENCSR799TMR/summary/ENCFF243BGZ.w5 32 2 mean CHIP:H3K4me3:duodenal mucosa male adult (59 years) CHIP ChIP-Histone:H3K4me3/duodenal mucosa male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3930 0 ENCFF683ZWT /home/drk/tillage/datasets/human/chip/encode/ENCSR799WDT/summary/ENCFF683ZWT.w5 32 2 mean CHIP:CTCF:Peyer's patch male adult (54 years) CHIP ChIP-TF:CTCF/Peyer's patch male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3931 0 ENCFF036TVD /home/drk/tillage/datasets/human/chip/encode/ENCSR800IIW/summary/ENCFF036TVD.w5 32 2 mean CHIP:H3K9me3:neural stem progenitor cell originated from H9 CHIP ChIP-Histone:H3K9me3/neural stem progenitor cell originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3932 0 ENCFF422DYK /home/drk/tillage/datasets/human/chip/encode/ENCSR800QIT/summary/ENCFF422DYK.w5 32 2 mean CHIP:HNF1A:HepG2 CHIP ChIP-TF:HNF1A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3933 0 ENCFF406SLN /home/drk/tillage/datasets/human/chip/encode/ENCSR801BWR/summary/ENCFF406SLN.w5 32 2 mean CHIP:eGFP-ZNF155:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF155/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3934 0 ENCFF849LAF /home/drk/tillage/datasets/human/chip/encode/ENCSR801FWU/summary/ENCFF849LAF.w5 32 2 mean CHIP:H3K36me3:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K36me3/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3935 0 ENCFF002FVF /home/drk/tillage/datasets/human/chip/encode/ENCSR801GJU/summary/ENCFF002FVF.w5 32 2 mean CHIP:CBX2:HepG2 CHIP ChIP-TF:CBX2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3936 0 ENCFF518NUV /home/drk/tillage/datasets/human/chip/encode/ENCSR801IPH/summary/ENCFF518NUV.w5 32 2 mean CHIP:H3K27ac:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K27ac/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3937 0 ENCFF128JAV /home/drk/tillage/datasets/human/chip/encode/ENCSR801RPW/summary/ENCFF128JAV.w5 32 2 mean CHIP:eGFP-GTF2A2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-GTF2A2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3938 0 ENCFF828GEW /home/drk/tillage/datasets/human/chip/encode/ENCSR801SWX/summary/ENCFF828GEW.w5 32 2 mean CHIP:TARDBP:MCF-7 CHIP ChIP-TF:TARDBP/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3939 0 ENCFF526WXA /home/drk/tillage/datasets/human/chip/encode/ENCSR803EKW/summary/ENCFF526WXA.w5 32 2 mean CHIP:NCOA2:K562 CHIP ChIP-TF:NCOA2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3940 0 ENCFF815NJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR803FAP/summary/ENCFF815NJQ.w5 32 2 mean CHIP:POLR2A:testis male adult (54 years) CHIP ChIP-TF:POLR2A/testis male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3941 0 ENCFF662TPP /home/drk/tillage/datasets/human/chip/encode/ENCSR803GYT/summary/ENCFF662TPP.w5 32 2 mean CHIP:eGFP-HIC1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-HIC1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3942 0 ENCFF749KKG /home/drk/tillage/datasets/human/chip/encode/ENCSR803IBD/summary/ENCFF749KKG.w5 32 2 mean CHIP:H3K4me1:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K4me1/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3943 0 ENCFF069ZID /home/drk/tillage/datasets/human/chip/encode/ENCSR803JYI/summary/ENCFF069ZID.w5 32 2 mean CHIP:H3K4me3:liver female adult (25 years) CHIP ChIP-Histone:H3K4me3/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3944 0 ENCFF357KFJ /home/drk/tillage/datasets/human/chip/encode/ENCSR804FSU/summary/ENCFF357KFJ.w5 32 2 mean CHIP:H3K9ac:peripheral blood mononuclear cell male adult (28 years) CHIP ChIP-Histone:H3K9ac/peripheral blood mononuclear cell male adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3945 0 ENCFF236DXP /home/drk/tillage/datasets/human/chip/encode/ENCSR804HMZ/summary/ENCFF236DXP.w5 32 2 mean CHIP:HNRNPLL:HepG2 CHIP ChIP-TF:HNRNPLL/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3946 0 ENCFF057DRT /home/drk/tillage/datasets/human/chip/encode/ENCSR804MAP/summary/ENCFF057DRT.w5 32 2 mean CHIP:H3K27ac:HUES64 CHIP ChIP-Histone:H3K27ac/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3947 0 ENCFF533UHM /home/drk/tillage/datasets/human/chip/encode/ENCSR804MDH/summary/ENCFF533UHM.w5 32 2 mean CHIP:H3K4me2:SU-DHL-6 CHIP ChIP-Histone:H3K4me2/SU-DHL-6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3948 0 ENCFF488CWE /home/drk/tillage/datasets/human/chip/encode/ENCSR804RMP/summary/ENCFF488CWE.w5 32 2 mean CHIP:H3K27me3:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K27me3/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3949 0 ENCFF163BOS /home/drk/tillage/datasets/human/chip/encode/ENCSR804SRO/summary/ENCFF163BOS.w5 32 2 mean CHIP:H4K20me1:IMR-90 CHIP ChIP-TF:H4K20me1/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3950 0 ENCFF837TLG /home/drk/tillage/datasets/human/chip/encode/ENCSR805OWG/summary/ENCFF837TLG.w5 32 2 mean CHIP:H3K27me3:muscle layer of duodenum male adult (73 years) CHIP ChIP-Histone:H3K27me3/muscle layer of duodenum male adult (73 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3951 0 ENCFF450CPH /home/drk/tillage/datasets/human/chip/encode/ENCSR806XIU/summary/ENCFF450CPH.w5 32 2 mean CHIP:H3K4me2:KMS-11 CHIP ChIP-Histone:H3K4me2/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3952 0 ENCFF132APO /home/drk/tillage/datasets/human/chip/encode/ENCSR807BGP/summary/ENCFF132APO.w5 32 2 mean CHIP:MTA1:K562 CHIP ChIP-TF:MTA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3953 0 ENCFF975XRR /home/drk/tillage/datasets/human/chip/encode/ENCSR807LQP/summary/ENCFF975XRR.w5 32 2 mean CHIP:eGFP-SP2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-SP2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3954 0 ENCFF500EXB /home/drk/tillage/datasets/human/chip/encode/ENCSR807YQE/summary/ENCFF500EXB.w5 32 2 mean CHIP:H3K4me3:mammary epithelial cell female adult (18 years) CHIP ChIP-Histone:H3K4me3/mammary epithelial cell female adult (18 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3955 0 ENCFF464MCC /home/drk/tillage/datasets/human/chip/encode/ENCSR808AKZ/summary/ENCFF464MCC.w5 32 2 mean CHIP:BCOR:K562 CHIP ChIP-TF:BCOR/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3956 0 ENCFF118FXA /home/drk/tillage/datasets/human/chip/encode/ENCSR808FFI/summary/ENCFF118FXA.w5 32 2 mean CHIP:3xFLAG-ZKSCAN8:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ZKSCAN8/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3957 0 ENCFF921VMW /home/drk/tillage/datasets/human/chip/encode/ENCSR809CVZ/summary/ENCFF921VMW.w5 32 2 mean CHIP:H2BK5ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2BK5ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3958 0 ENCFF984BVG /home/drk/tillage/datasets/human/chip/encode/ENCSR810BDB/summary/ENCFF984BVG.w5 32 2 mean CHIP:H3K27me3:HCT116 CHIP ChIP-Histone:H3K27me3/HCT116 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3959 0 ENCFF365WHC /home/drk/tillage/datasets/human/chip/encode/ENCSR810EPZ/summary/ENCFF365WHC.w5 32 2 mean CHIP:H3K27ac:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K27ac/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3960 0 ENCFF810SGV /home/drk/tillage/datasets/human/chip/encode/ENCSR810WXH/summary/ENCFF810SGV.w5 32 2 mean CHIP:TOE1:MCF-7 CHIP ChIP-TF:TOE1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3961 0 ENCFF106SAP /home/drk/tillage/datasets/human/chip/encode/ENCSR811JJM/summary/ENCFF106SAP.w5 32 2 mean CHIP:eGFP-ZNF19:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF19/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3962 0 ENCFF555WFF /home/drk/tillage/datasets/human/chip/encode/ENCSR811NNT/summary/ENCFF555WFF.w5 32 2 mean CHIP:H2BK120ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H2BK120ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3963 0 ENCFF799AQK /home/drk/tillage/datasets/human/chip/encode/ENCSR812POE/summary/ENCFF799AQK.w5 32 2 mean CHIP:H3K4me1:sigmoid colon female adult (53 years) CHIP ChIP-Histone:H3K4me1/sigmoid colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3964 0 ENCFF595BNN /home/drk/tillage/datasets/human/chip/encode/ENCSR813CFB/summary/ENCFF595BNN.w5 32 2 mean CHIP:H3K4me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K4me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3965 0 ENCFF848LJL /home/drk/tillage/datasets/human/chip/encode/ENCSR813DCK/summary/ENCFF848LJL.w5 32 2 mean CHIP:SMAD1:GM12878 CHIP ChIP-TF:SMAD1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3966 0 ENCFF483ZIO /home/drk/tillage/datasets/human/chip/encode/ENCSR813HFV/summary/ENCFF483ZIO.w5 32 2 mean CHIP:H3K9ac:lung female embryo (120 days) CHIP ChIP-Histone:H3K9ac/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3967 0 ENCFF104SXE /home/drk/tillage/datasets/human/chip/encode/ENCSR813ULW/summary/ENCFF104SXE.w5 32 2 mean CHIP:H3K4me1:myoepithelial cell of mammary gland female adult (36 years) CHIP ChIP-Histone:H3K4me1/myoepithelial cell of mammary gland female adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3968 0 ENCFF412IPU /home/drk/tillage/datasets/human/chip/encode/ENCSR813ZEY/summary/ENCFF412IPU.w5 32 2 mean CHIP:H3K4me3:transverse colon male adult (37 years) CHIP ChIP-Histone:H3K4me3/transverse colon male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3969 0 ENCFF622FMX /home/drk/tillage/datasets/human/chip/encode/ENCSR814AJH/summary/ENCFF622FMX.w5 32 2 mean CHIP:SRSF9:K562 CHIP ChIP-TF:SRSF9/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3970 0 ENCFF538ADF /home/drk/tillage/datasets/human/chip/encode/ENCSR814MAF/summary/ENCFF538ADF.w5 32 2 mean CHIP:H3K4ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K4ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3971 0 ENCFF950LSJ /home/drk/tillage/datasets/human/chip/encode/ENCSR814TSD/summary/ENCFF950LSJ.w5 32 2 mean CHIP:H3K4me1:neuron originated from H9 CHIP ChIP-Histone:H3K4me1/neuron originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3972 0 ENCFF730VVX /home/drk/tillage/datasets/human/chip/encode/ENCSR814XPE/summary/ENCFF730VVX.w5 32 2 mean CHIP:H3K4me3:H1-hESC CHIP ChIP-Histone:H3K4me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3973 0 ENCFF702VBW /home/drk/tillage/datasets/human/chip/encode/ENCSR815DXY/summary/ENCFF702VBW.w5 32 2 mean CHIP:H3K9ac:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K9ac/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3974 0 ENCFF464QEO /home/drk/tillage/datasets/human/chip/encode/ENCSR815LBP/summary/ENCFF464QEO.w5 32 2 mean CHIP:H3K23ac:H1-hESC CHIP ChIP-Histone:H3K23ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3975 0 ENCFF240NPA /home/drk/tillage/datasets/human/chip/encode/ENCSR815PSO/summary/ENCFF240NPA.w5 32 2 mean CHIP:H3K9me3:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K9me3/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3976 0 ENCFF953MOS /home/drk/tillage/datasets/human/chip/encode/ENCSR815VLQ/summary/ENCFF953MOS.w5 32 2 mean CHIP:H3K36me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K36me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3977 0 ENCFF235NNS /home/drk/tillage/datasets/human/chip/encode/ENCSR815ZDS/summary/ENCFF235NNS.w5 32 2 mean CHIP:SREBF1:K562 CHIP ChIP-TF:SREBF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3978 0 ENCFF239UVR /home/drk/tillage/datasets/human/chip/encode/ENCSR816JBG/summary/ENCFF239UVR.w5 32 2 mean CHIP:H2AFZ:neural cell CHIP ChIP-TF:H2AFZ/neural cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3979 0 ENCFF292LTH /home/drk/tillage/datasets/human/chip/encode/ENCSR816NKX/summary/ENCFF292LTH.w5 32 2 mean CHIP:H3K36me3:B cell male adult (21 year) CHIP ChIP-Histone:H3K36me3/B cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3980 0 ENCFF637MFA /home/drk/tillage/datasets/human/chip/encode/ENCSR817QHX/summary/ENCFF637MFA.w5 32 2 mean CHIP:H3K4me1:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K4me1/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3981 0 ENCFF931ZYG /home/drk/tillage/datasets/human/chip/encode/ENCSR817QKV/summary/ENCFF931ZYG.w5 32 2 mean CHIP:EP400:K562 CHIP ChIP-TF:EP400/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3982 0 ENCFF042GTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR818DQV/summary/ENCFF042GTZ.w5 32 2 mean CHIP:eGFP-MAFG:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-MAFG/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3983 0 ENCFF779ODE /home/drk/tillage/datasets/human/chip/encode/ENCSR819ATC/summary/ENCFF779ODE.w5 32 2 mean CHIP:MYB:GM12878 CHIP ChIP-TF:MYB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3984 0 ENCFF447BFP /home/drk/tillage/datasets/human/chip/encode/ENCSR819HSS/summary/ENCFF447BFP.w5 32 2 mean CHIP:H3K4me3:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K4me3/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3985 0 ENCFF589LQL /home/drk/tillage/datasets/human/chip/encode/ENCSR819LHG/summary/ENCFF589LQL.w5 32 2 mean CHIP:FOXA1:K562 CHIP ChIP-TF:FOXA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3986 0 ENCFF998IVF /home/drk/tillage/datasets/human/chip/encode/ENCSR820ABR/summary/ENCFF998IVF.w5 32 2 mean CHIP:H3K9me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K9me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3987 0 ENCFF394UYP /home/drk/tillage/datasets/human/chip/encode/ENCSR820GND/summary/ENCFF394UYP.w5 32 2 mean CHIP:RNF2:K562 CHIP ChIP-TF:RNF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3988 0 ENCFF965UTU /home/drk/tillage/datasets/human/chip/encode/ENCSR821GUG/summary/ENCFF965UTU.w5 32 2 mean CHIP:H4K20me1:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:H4K20me1/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3989 0 ENCFF357TFM /home/drk/tillage/datasets/human/chip/encode/ENCSR821IAK/summary/ENCFF357TFM.w5 32 2 mean CHIP:H3K4me2:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K4me2/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3990 0 ENCFF614WVD /home/drk/tillage/datasets/human/chip/encode/ENCSR822AHX/summary/ENCFF614WVD.w5 32 2 mean CHIP:IKZF2:GM12878 CHIP ChIP-TF:IKZF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3991 0 ENCFF697GTL /home/drk/tillage/datasets/human/chip/encode/ENCSR822CCM/summary/ENCFF697GTL.w5 32 2 mean CHIP:ARID1B:K562 CHIP ChIP-TF:ARID1B/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3992 0 ENCFF182VZV /home/drk/tillage/datasets/human/chip/encode/ENCSR822CEA/summary/ENCFF182VZV.w5 32 2 mean CHIP:CTCF:neural cell originated from H1-hESC CHIP ChIP-TF:CTCF/neural cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3993 0 ENCFF051NQJ /home/drk/tillage/datasets/human/chip/encode/ENCSR822LBD/summary/ENCFF051NQJ.w5 32 2 mean CHIP:RBFOX2:K562 CHIP ChIP-TF:RBFOX2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3994 0 ENCFF991GMN /home/drk/tillage/datasets/human/chip/encode/ENCSR822PJT/summary/ENCFF991GMN.w5 32 2 mean CHIP:CTCF:tibial nerve female adult (51 year) CHIP ChIP-TF:CTCF/tibial nerve female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3995 0 ENCFF978ZWH /home/drk/tillage/datasets/human/chip/encode/ENCSR822ZIG/summary/ENCFF978ZWH.w5 32 2 mean CHIP:H3K27ac:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27ac/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3996 0 ENCFF033YFQ /home/drk/tillage/datasets/human/chip/encode/ENCSR823ADL/summary/ENCFF033YFQ.w5 32 2 mean CHIP:3xFLAG-RFXANK:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RFXANK/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3997 0 ENCFF890EZE /home/drk/tillage/datasets/human/chip/encode/ENCSR823BHO/summary/ENCFF890EZE.w5 32 2 mean CHIP:H3K9me3:endodermal cell originated from HUES64 CHIP ChIP-Histone:H3K9me3/endodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3998 0 ENCFF909YUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR823FFR/summary/ENCFF909YUJ.w5 32 2 mean CHIP:POLR2AphosphoS5:stomach female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/stomach female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +3999 0 ENCFF223TMR /home/drk/tillage/datasets/human/chip/encode/ENCSR823QYQ/summary/ENCFF223TMR.w5 32 2 mean CHIP:H3K4me1:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K4me1/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4000 0 ENCFF257GFK /home/drk/tillage/datasets/human/chip/encode/ENCSR824PXG/summary/ENCFF257GFK.w5 32 2 mean CHIP:H3K9me3:CD8-positive, alpha-beta T cell male adult (37 years) CHIP ChIP-Histone:H3K9me3/CD8-positive, alpha-beta T cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4001 0 ENCFF278HYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR824UNY/summary/ENCFF278HYJ.w5 32 2 mean CHIP:H3K36me3:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K36me3/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4002 0 ENCFF683TLR /home/drk/tillage/datasets/human/chip/encode/ENCSR825MZS/summary/ENCFF683TLR.w5 32 2 mean CHIP:TAF15:HepG2 CHIP ChIP-TF:TAF15/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4003 0 ENCFF975UWV /home/drk/tillage/datasets/human/chip/encode/ENCSR825RBI/summary/ENCFF975UWV.w5 32 2 mean CHIP:POLR2A:suprapubic skin female adult (53 years) CHIP ChIP-TF:POLR2A/suprapubic skin female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4004 0 ENCFF287SLL /home/drk/tillage/datasets/human/chip/encode/ENCSR826UTD/summary/ENCFF287SLL.w5 32 2 mean CHIP:H3K27ac:PC-3 CHIP ChIP-Histone:H3K27ac/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4005 0 ENCFF376PIF /home/drk/tillage/datasets/human/chip/encode/ENCSR826VJY/summary/ENCFF376PIF.w5 32 2 mean CHIP:H3K4me1:neutrophil CHIP ChIP-Histone:H3K4me1/neutrophil ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4006 0 ENCFF425LTP /home/drk/tillage/datasets/human/chip/encode/ENCSR826YMT/summary/ENCFF425LTP.w5 32 2 mean CHIP:3xFLAG-SMAD4:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SMAD4/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4007 0 ENCFF939PLA /home/drk/tillage/datasets/human/chip/encode/ENCSR826ZCF/summary/ENCFF939PLA.w5 32 2 mean CHIP:H3K4me1:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K4me1/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4008 0 ENCFF618LPH /home/drk/tillage/datasets/human/chip/encode/ENCSR827NKO/summary/ENCFF618LPH.w5 32 2 mean CHIP:H3K4me1:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K4me1/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4009 0 ENCFF985JDF /home/drk/tillage/datasets/human/chip/encode/ENCSR827NWO/summary/ENCFF985JDF.w5 32 2 mean CHIP:eGFP-FEZF1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-FEZF1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4010 0 ENCFF224ZEB /home/drk/tillage/datasets/human/chip/encode/ENCSR828CCQ/summary/ENCFF224ZEB.w5 32 2 mean CHIP:H3K4me3:ovary female adult (53 years) CHIP ChIP-Histone:H3K4me3/ovary female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4011 0 ENCFF344NUU /home/drk/tillage/datasets/human/chip/encode/ENCSR828NCB/summary/ENCFF344NUU.w5 32 2 mean CHIP:GATAD2B:GM12878 CHIP ChIP-TF:GATAD2B/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4012 0 ENCFF195CQW /home/drk/tillage/datasets/human/chip/encode/ENCSR828PZH/summary/ENCFF195CQW.w5 32 2 mean CHIP:EP300:upper lobe of left lung male adult (37 years) CHIP ChIP-TF:EP300/upper lobe of left lung male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4013 0 ENCFF536HDR /home/drk/tillage/datasets/human/chip/encode/ENCSR828WZG/summary/ENCFF536HDR.w5 32 2 mean CHIP:H3K36me3:CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K36me3/CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4014 0 ENCFF242LSD /home/drk/tillage/datasets/human/chip/encode/ENCSR829HTO/summary/ENCFF242LSD.w5 32 2 mean CHIP:CTCF:prostate gland male adult (54 years) CHIP ChIP-TF:CTCF/prostate gland male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4015 0 ENCFF495TLF /home/drk/tillage/datasets/human/chip/encode/ENCSR829NJE/summary/ENCFF495TLF.w5 32 2 mean CHIP:H3K9me3:brain male embryo (122 days) CHIP ChIP-Histone:H3K9me3/brain male embryo (122 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4016 0 ENCFF081OON /home/drk/tillage/datasets/human/chip/encode/ENCSR830HUE/summary/ENCFF081OON.w5 32 2 mean CHIP:H3K9me3:mucosa of rectum female adult (61 year) CHIP ChIP-Histone:H3K9me3/mucosa of rectum female adult (61 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4017 0 ENCFF469OGA /home/drk/tillage/datasets/human/chip/encode/ENCSR831EIW/summary/ENCFF469OGA.w5 32 2 mean CHIP:FOXM1:HEK293T CHIP ChIP-TF:FOXM1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4018 0 ENCFF671AIP /home/drk/tillage/datasets/human/chip/encode/ENCSR831JSP/summary/ENCFF671AIP.w5 32 2 mean CHIP:H3K4me1:IMR-90 CHIP ChIP-Histone:H3K4me1/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4019 0 ENCFF829QZN /home/drk/tillage/datasets/human/chip/encode/ENCSR831LTX/summary/ENCFF829QZN.w5 32 2 mean CHIP:H3K27me3:colonic mucosa female adult (56 years) CHIP ChIP-Histone:H3K27me3/colonic mucosa female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4020 0 ENCFF310MRD /home/drk/tillage/datasets/human/chip/encode/ENCSR832DMO/summary/ENCFF310MRD.w5 32 2 mean CHIP:SRSF1:K562 CHIP ChIP-TF:SRSF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4021 0 ENCFF512OYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR832JVP/summary/ENCFF512OYQ.w5 32 2 mean CHIP:H3K27me3:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K27me3/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4022 0 ENCFF171FLK /home/drk/tillage/datasets/human/chip/encode/ENCSR832LMT/summary/ENCFF171FLK.w5 32 2 mean CHIP:H3K36me3:placenta embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/placenta embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4023 0 ENCFF420RRI /home/drk/tillage/datasets/human/chip/encode/ENCSR832OGB/summary/ENCFF420RRI.w5 32 2 mean CHIP:LEF1:K562 CHIP ChIP-TF:LEF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4024 0 ENCFF007DYR /home/drk/tillage/datasets/human/chip/encode/ENCSR833FWC/summary/ENCFF007DYR.w5 32 2 mean CHIP:CTCF:transverse colon male adult (54 years) CHIP ChIP-TF:CTCF/transverse colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4025 0 ENCFF132DSA /home/drk/tillage/datasets/human/chip/encode/ENCSR834BXU/summary/ENCFF132DSA.w5 32 2 mean CHIP:H3K9me3:muscle of leg female embryo (110 days) CHIP ChIP-Histone:H3K9me3/muscle of leg female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4026 0 ENCFF695FFO /home/drk/tillage/datasets/human/chip/encode/ENCSR835MMN/summary/ENCFF695FFO.w5 32 2 mean CHIP:H3K27ac:SK-N-MC CHIP ChIP-Histone:H3K27ac/SK-N-MC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4027 0 ENCFF383VYS /home/drk/tillage/datasets/human/chip/encode/ENCSR835OJV/summary/ENCFF383VYS.w5 32 2 mean CHIP:H3K27ac:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27ac/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4028 0 ENCFF584SIV /home/drk/tillage/datasets/human/chip/encode/ENCSR835TCD/summary/ENCFF584SIV.w5 32 2 mean CHIP:eGFP-HDAC8:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-HDAC8/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4029 0 ENCFF547HHK /home/drk/tillage/datasets/human/chip/encode/ENCSR835XKS/summary/ENCFF547HHK.w5 32 2 mean CHIP:TRIM22:GM12878 CHIP ChIP-TF:TRIM22/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4030 0 ENCFF596TFK /home/drk/tillage/datasets/human/chip/encode/ENCSR835YBD/summary/ENCFF596TFK.w5 32 2 mean CHIP:H3K36me3:KMS-11 CHIP ChIP-Histone:H3K36me3/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4031 0 ENCFF937WPQ /home/drk/tillage/datasets/human/chip/encode/ENCSR836COE/summary/ENCFF937WPQ.w5 32 2 mean CHIP:RBM17:K562 CHIP ChIP-TF:RBM17/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4032 0 ENCFF953VID /home/drk/tillage/datasets/human/chip/encode/ENCSR836GCA/summary/ENCFF953VID.w5 32 2 mean CHIP:H3K36me3:skeletal muscle tissue CHIP ChIP-Histone:H3K36me3/skeletal muscle tissue ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4033 0 ENCFF903BKT /home/drk/tillage/datasets/human/chip/encode/ENCSR836KDL/summary/ENCFF903BKT.w5 32 2 mean CHIP:H3K36me3:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K36me3/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4034 0 ENCFF932HVW /home/drk/tillage/datasets/human/chip/encode/ENCSR837EYC/summary/ENCFF932HVW.w5 32 2 mean CHIP:NRF1:K562 CHIP ChIP-TF:NRF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4035 0 ENCFF928WPG /home/drk/tillage/datasets/human/chip/encode/ENCSR837GTK/summary/ENCFF928WPG.w5 32 2 mean CHIP:JUND:liver male adult (32 years) CHIP ChIP-TF:JUND/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4036 0 ENCFF859ITG /home/drk/tillage/datasets/human/chip/encode/ENCSR837SGJ/summary/ENCFF859ITG.w5 32 2 mean CHIP:H3K27ac:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K27ac/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4037 0 ENCFF862PJG /home/drk/tillage/datasets/human/chip/encode/ENCSR837SUQ/summary/ENCFF862PJG.w5 32 2 mean CHIP:H3K36me3:Loucy CHIP ChIP-Histone:H3K36me3/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4038 0 ENCFF052XJF /home/drk/tillage/datasets/human/chip/encode/ENCSR838RUX/summary/ENCFF052XJF.w5 32 2 mean CHIP:CTCF:esophagus squamous epithelium male adult (37 years) CHIP ChIP-TF:CTCF/esophagus squamous epithelium male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4039 0 ENCFF424VVO /home/drk/tillage/datasets/human/chip/encode/ENCSR839ICQ/summary/ENCFF424VVO.w5 32 2 mean CHIP:H3K27me3:placenta female embryo (113 days) CHIP ChIP-Histone:H3K27me3/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4040 0 ENCFF053ULC /home/drk/tillage/datasets/human/chip/encode/ENCSR839PUY/summary/ENCFF053ULC.w5 32 2 mean CHIP:H3K9ac:mesendoderm originated from H1-hESC CHIP ChIP-Histone:H3K9ac/mesendoderm originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4041 0 ENCFF573DQZ /home/drk/tillage/datasets/human/chip/encode/ENCSR839SFJ/summary/ENCFF573DQZ.w5 32 2 mean CHIP:SMARCA4:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:SMARCA4/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4042 0 ENCFF639LCK /home/drk/tillage/datasets/human/chip/encode/ENCSR839XZU/summary/ENCFF639LCK.w5 32 2 mean CHIP:CREM:GM12878 CHIP ChIP-TF:CREM/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4043 0 ENCFF337DTR /home/drk/tillage/datasets/human/chip/encode/ENCSR840KVX/summary/ENCFF337DTR.w5 32 2 mean CHIP:H3K4me3:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K4me3/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4044 0 ENCFF254JVO /home/drk/tillage/datasets/human/chip/encode/ENCSR840VWD/summary/ENCFF254JVO.w5 32 2 mean CHIP:H3K27me3:transverse colon female adult (53 years) CHIP ChIP-Histone:H3K27me3/transverse colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4045 0 ENCFF992JJW /home/drk/tillage/datasets/human/chip/encode/ENCSR841NDX/summary/ENCFF992JJW.w5 32 2 mean CHIP:ELF1:GM12878 CHIP ChIP-TF:ELF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4046 0 ENCFF837KRP /home/drk/tillage/datasets/human/chip/encode/ENCSR841YWU/summary/ENCFF837KRP.w5 32 2 mean CHIP:E4F1:MCF-7 CHIP ChIP-TF:E4F1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4047 0 ENCFF547RRP /home/drk/tillage/datasets/human/chip/encode/ENCSR842ASU/summary/ENCFF547RRP.w5 32 2 mean CHIP:H3K9ac:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K9ac/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4048 0 ENCFF166CIB /home/drk/tillage/datasets/human/chip/encode/ENCSR842NGQ/summary/ENCFF166CIB.w5 32 2 mean CHIP:H3K27ac:neuroepithelial stem cell genetically modified using stable transfection NONE and originated from H9 CHIP ChIP-Histone:H3K27ac/neuroepithelial stem cell genetically modified using stable transfection NONE and originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4049 0 ENCFF533PTN /home/drk/tillage/datasets/human/chip/encode/ENCSR843KHS/summary/ENCFF533PTN.w5 32 2 mean CHIP:H3K27me3:psoas muscle male child (3 years) CHIP ChIP-Histone:H3K27me3/psoas muscle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4050 0 ENCFF616DFJ /home/drk/tillage/datasets/human/chip/encode/ENCSR843ZUP/summary/ENCFF616DFJ.w5 32 2 mean CHIP:EP300:neural cell originated from H1-hESC CHIP ChIP-TF:EP300/neural cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4051 0 ENCFF768WDS /home/drk/tillage/datasets/human/chip/encode/ENCSR844DRI/summary/ENCFF768WDS.w5 32 2 mean CHIP:H3K36me3:ES-I3 CHIP ChIP-Histone:H3K36me3/ES-I3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4052 0 ENCFF534ZUJ /home/drk/tillage/datasets/human/chip/encode/ENCSR844PVS/summary/ENCFF534ZUJ.w5 32 2 mean CHIP:POLR2AphosphoS5:breast epithelium male adult (54 years) CHIP ChIP-TF:POLR2AphosphoS5/breast epithelium male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4053 0 ENCFF826JXZ /home/drk/tillage/datasets/human/chip/encode/ENCSR845BCL/summary/ENCFF826JXZ.w5 32 2 mean CHIP:eGFP-ZNF639:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZNF639/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4054 0 ENCFF383CVA /home/drk/tillage/datasets/human/chip/encode/ENCSR845WAQ/summary/ENCFF383CVA.w5 32 2 mean CHIP:H3K4me1:HUES64 CHIP ChIP-Histone:H3K4me1/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4055 0 ENCFF297TKC /home/drk/tillage/datasets/human/chip/encode/ENCSR846DXV/summary/ENCFF297TKC.w5 32 2 mean CHIP:H2BK20ac:H9 CHIP ChIP-TF:H2BK20ac/H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4056 0 ENCFF221GRG /home/drk/tillage/datasets/human/chip/encode/ENCSR846TPT/summary/ENCFF221GRG.w5 32 2 mean CHIP:EP300:omental fat pad male adult (37 years) CHIP ChIP-TF:EP300/omental fat pad male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4057 0 ENCFF988BQU /home/drk/tillage/datasets/human/chip/encode/ENCSR847AIA/summary/ENCFF988BQU.w5 32 2 mean CHIP:H3K27ac:adrenal gland male embryo (97 days) CHIP ChIP-Histone:H3K27ac/adrenal gland male embryo (97 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4058 0 ENCFF964SBO /home/drk/tillage/datasets/human/chip/encode/ENCSR847DIT/summary/ENCFF964SBO.w5 32 2 mean CHIP:MAX:liver female child (4 years) CHIP ChIP-TF:MAX/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4059 0 ENCFF388NFD /home/drk/tillage/datasets/human/chip/encode/ENCSR847LBF/summary/ENCFF388NFD.w5 32 2 mean CHIP:eGFP-FOXJ2:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-FOXJ2/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4060 0 ENCFF844FLY /home/drk/tillage/datasets/human/chip/encode/ENCSR847UJW/summary/ENCFF844FLY.w5 32 2 mean CHIP:H3K79me2:KMS-11 CHIP ChIP-Histone:H3K79me2/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4061 0 ENCFF589EBF /home/drk/tillage/datasets/human/chip/encode/ENCSR847XGE/summary/ENCFF589EBF.w5 32 2 mean CHIP:CTCF:22Rv1 treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours CHIP ChIP-TF:CTCF/22Rv1 treated with 10 nM 17B-hydroxy-5a-androstan-3-one for 4 hours ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4062 0 ENCFF386VOI /home/drk/tillage/datasets/human/chip/encode/ENCSR848AOP/summary/ENCFF386VOI.w5 32 2 mean CHIP:RBM22:K562 CHIP ChIP-TF:RBM22/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4063 0 ENCFF757EYT /home/drk/tillage/datasets/human/chip/encode/ENCSR848DUN/summary/ENCFF757EYT.w5 32 2 mean CHIP:H2BK120ac:H1-hESC CHIP ChIP-TF:H2BK120ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4064 0 ENCFF555ESM /home/drk/tillage/datasets/human/chip/encode/ENCSR848EZM/summary/ENCFF555ESM.w5 32 2 mean CHIP:H3K9ac:iPS-15b female adult (48 years) CHIP ChIP-Histone:H3K9ac/iPS-15b female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4065 0 ENCFF296KKE /home/drk/tillage/datasets/human/chip/encode/ENCSR848TLB/summary/ENCFF296KKE.w5 32 2 mean CHIP:H3K4me1:aorta female adult (30 years) CHIP ChIP-Histone:H3K4me1/aorta female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4066 0 ENCFF693WQA /home/drk/tillage/datasets/human/chip/encode/ENCSR848YWD/summary/ENCFF693WQA.w5 32 2 mean CHIP:ZMYM3:HepG2 CHIP ChIP-TF:ZMYM3/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4067 0 ENCFF840SKF /home/drk/tillage/datasets/human/chip/encode/ENCSR849APH/summary/ENCFF840SKF.w5 32 2 mean CHIP:H3K36me3:PC-3 CHIP ChIP-Histone:H3K36me3/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4068 0 ENCFF393EHU /home/drk/tillage/datasets/human/chip/encode/ENCSR849DFF/summary/ENCFF393EHU.w5 32 2 mean CHIP:3xFLAG-PBX2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-PBX2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4069 0 ENCFF520INY /home/drk/tillage/datasets/human/chip/encode/ENCSR849NQE/summary/ENCFF520INY.w5 32 2 mean CHIP:H3K9me3:endocrine pancreas male CHIP ChIP-Histone:H3K9me3/endocrine pancreas male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4070 0 ENCFF384BWK /home/drk/tillage/datasets/human/chip/encode/ENCSR849WCQ/summary/ENCFF384BWK.w5 32 2 mean CHIP:ASH2L:GM12878 CHIP ChIP-TF:ASH2L/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4071 0 ENCFF834UFV /home/drk/tillage/datasets/human/chip/encode/ENCSR849YFO/summary/ENCFF834UFV.w5 32 2 mean CHIP:H3K4me3:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K4me3/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4072 0 ENCFF806OYX /home/drk/tillage/datasets/human/chip/encode/ENCSR850KIP/summary/ENCFF806OYX.w5 32 2 mean CHIP:ASH2L:H1-hESC CHIP ChIP-TF:ASH2L/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4073 0 ENCFF991DHO /home/drk/tillage/datasets/human/chip/encode/ENCSR850ODD/summary/ENCFF991DHO.w5 32 2 mean CHIP:H3K9ac:hepatocyte originated from H9 CHIP ChIP-Histone:H3K9ac/hepatocyte originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4074 0 ENCFF273FDF /home/drk/tillage/datasets/human/chip/encode/ENCSR850QKN/summary/ENCFF273FDF.w5 32 2 mean CHIP:H3K4me2:OCI-LY7 CHIP ChIP-Histone:H3K4me2/OCI-LY7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4075 0 ENCFF486TEG /home/drk/tillage/datasets/human/chip/encode/ENCSR850RVA/summary/ENCFF486TEG.w5 32 2 mean CHIP:H3K4me1:tibial nerve female adult (53 years) CHIP ChIP-Histone:H3K4me1/tibial nerve female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4076 0 ENCFF322KBR /home/drk/tillage/datasets/human/chip/encode/ENCSR850WUE/summary/ENCFF322KBR.w5 32 2 mean CHIP:RBM15:K562 CHIP ChIP-TF:RBM15/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4077 0 ENCFF965POF /home/drk/tillage/datasets/human/chip/encode/ENCSR851BNE/summary/ENCFF965POF.w5 32 2 mean CHIP:MEIS2:K562 CHIP ChIP-TF:MEIS2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4078 0 ENCFF140MBA /home/drk/tillage/datasets/human/chip/encode/ENCSR851DHU/summary/ENCFF140MBA.w5 32 2 mean CHIP:H3K4me1:CD8-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K4me1/CD8-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4079 0 ENCFF243ALK /home/drk/tillage/datasets/human/chip/encode/ENCSR851XLW/summary/ENCFF243ALK.w5 32 2 mean CHIP:ZNF830:K562 CHIP ChIP-TF:ZNF830/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4080 0 ENCFF438NJV /home/drk/tillage/datasets/human/chip/encode/ENCSR852FRR/summary/ENCFF438NJV.w5 32 2 mean CHIP:H3K4me3:CD4-positive, alpha-beta T cell male adult (21 year) CHIP ChIP-Histone:H3K4me3/CD4-positive, alpha-beta T cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4081 0 ENCFF382WBN /home/drk/tillage/datasets/human/chip/encode/ENCSR853ADA/summary/ENCFF382WBN.w5 32 2 mean CHIP:NRF1:HepG2 CHIP ChIP-TF:NRF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4082 0 ENCFF087PEW /home/drk/tillage/datasets/human/chip/encode/ENCSR853JJZ/summary/ENCFF087PEW.w5 32 2 mean CHIP:H3K27me3:chorionic villus female embryo (40 weeks) CHIP ChIP-Histone:H3K27me3/chorionic villus female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4083 0 ENCFF318ORB /home/drk/tillage/datasets/human/chip/encode/ENCSR853JYB/summary/ENCFF318ORB.w5 32 2 mean CHIP:H3K9me3:liver female adult (25 years) CHIP ChIP-Histone:H3K9me3/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4084 0 ENCFF282JXB /home/drk/tillage/datasets/human/chip/encode/ENCSR853XJK/summary/ENCFF282JXB.w5 32 2 mean CHIP:H3K27me3:foreskin keratinocyte male newborn CHIP ChIP-Histone:H3K27me3/foreskin keratinocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4085 0 ENCFF446BDT /home/drk/tillage/datasets/human/chip/encode/ENCSR854IPI/summary/ENCFF446BDT.w5 32 2 mean CHIP:eGFP-ZNF707:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF707/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4086 0 ENCFF360QQU /home/drk/tillage/datasets/human/chip/encode/ENCSR854JES/summary/ENCFF360QQU.w5 32 2 mean CHIP:POLR2G:HepG2 CHIP ChIP-TF:POLR2G/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4087 0 ENCFF630FXX /home/drk/tillage/datasets/human/chip/encode/ENCSR854MCV/summary/ENCFF630FXX.w5 32 2 mean CHIP:eGFP-IRF1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-IRF1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4088 0 ENCFF068NFG /home/drk/tillage/datasets/human/chip/encode/ENCSR854ORP/summary/ENCFF068NFG.w5 32 2 mean CHIP:eGFP-ZNF350:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF350/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4089 0 ENCFF491UMQ /home/drk/tillage/datasets/human/chip/encode/ENCSR854OXF/summary/ENCFF491UMQ.w5 32 2 mean CHIP:H3K27ac:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K27ac/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4090 0 ENCFF686SJS /home/drk/tillage/datasets/human/chip/encode/ENCSR855JPU/summary/ENCFF686SJS.w5 32 2 mean CHIP:H3K27me3:spinal cord female embryo (108 days) CHIP ChIP-Histone:H3K27me3/spinal cord female embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4091 0 ENCFF755PCR /home/drk/tillage/datasets/human/chip/encode/ENCSR855XNQ/summary/ENCFF755PCR.w5 32 2 mean CHIP:H3K36me3:thyroid gland female adult (53 years) CHIP ChIP-Histone:H3K36me3/thyroid gland female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4092 0 ENCFF934BWM /home/drk/tillage/datasets/human/chip/encode/ENCSR856JJB/summary/ENCFF934BWM.w5 32 2 mean CHIP:CTCF:RWPE2 CHIP ChIP-TF:CTCF/RWPE2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4093 0 ENCFF378QIB /home/drk/tillage/datasets/human/chip/encode/ENCSR857GMX/summary/ENCFF378QIB.w5 32 2 mean CHIP:H3K27ac:OCI-LY3 CHIP ChIP-Histone:H3K27ac/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4094 0 ENCFF281HOI /home/drk/tillage/datasets/human/chip/encode/ENCSR857LLS/summary/ENCFF281HOI.w5 32 2 mean CHIP:H3K4me1:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K4me1/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4095 0 ENCFF809PHW /home/drk/tillage/datasets/human/chip/encode/ENCSR857PBV/summary/ENCFF809PHW.w5 32 2 mean CHIP:CTCF:22Rv1 CHIP ChIP-TF:CTCF/22Rv1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4096 0 ENCFF016NTU /home/drk/tillage/datasets/human/chip/encode/ENCSR857XRG/summary/ENCFF016NTU.w5 32 2 mean CHIP:H3K36me3:adrenal gland male adult (54 years) CHIP ChIP-Histone:H3K36me3/adrenal gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4097 0 ENCFF068LXN /home/drk/tillage/datasets/human/chip/encode/ENCSR858BOF/summary/ENCFF068LXN.w5 32 2 mean CHIP:H4K91ac:H1-hESC CHIP ChIP-TF:H4K91ac/H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4098 0 ENCFF700SDV /home/drk/tillage/datasets/human/chip/encode/ENCSR858FAN/summary/ENCFF700SDV.w5 32 2 mean CHIP:eGFP-ZNF621:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF621/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4099 0 ENCFF439OFO /home/drk/tillage/datasets/human/chip/encode/ENCSR858LJY/summary/ENCFF439OFO.w5 32 2 mean CHIP:H3K27me3:muscle layer of colon female adult (56 years) CHIP ChIP-Histone:H3K27me3/muscle layer of colon female adult (56 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4100 0 ENCFF317CKJ /home/drk/tillage/datasets/human/chip/encode/ENCSR859BMR/summary/ENCFF317CKJ.w5 32 2 mean CHIP:eGFP-KLF1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4101 0 ENCFF607KCL /home/drk/tillage/datasets/human/chip/encode/ENCSR859EIX/summary/ENCFF607KCL.w5 32 2 mean CHIP:H3K27me3:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K27me3/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4102 0 ENCFF038IYA /home/drk/tillage/datasets/human/chip/encode/ENCSR859FDL/summary/ENCFF038IYA.w5 32 2 mean CHIP:ZNF687:GM12878 CHIP ChIP-TF:ZNF687/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4103 0 ENCFF623EGG /home/drk/tillage/datasets/human/chip/encode/ENCSR859FGW/summary/ENCFF623EGG.w5 32 2 mean CHIP:H2AFZ:DOHH2 CHIP ChIP-TF:H2AFZ/DOHH2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4104 0 ENCFF782TNO /home/drk/tillage/datasets/human/chip/encode/ENCSR859JGF/summary/ENCFF782TNO.w5 32 2 mean CHIP:ATM:HepG2 CHIP ChIP-TF:ATM/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4105 0 ENCFF223VDP /home/drk/tillage/datasets/human/chip/encode/ENCSR859JNA/summary/ENCFF223VDP.w5 32 2 mean CHIP:H3K27me3:OCI-LY1 CHIP ChIP-Histone:H3K27me3/OCI-LY1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4106 0 ENCFF173TIG /home/drk/tillage/datasets/human/chip/encode/ENCSR859MXQ/summary/ENCFF173TIG.w5 32 2 mean CHIP:H3K27me3:upper lobe of left lung female adult (53 years) CHIP ChIP-Histone:H3K27me3/upper lobe of left lung female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4107 0 ENCFF362IEJ /home/drk/tillage/datasets/human/chip/encode/ENCSR859RAO/summary/ENCFF362IEJ.w5 32 2 mean CHIP:eGFP-YY1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-YY1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4108 0 ENCFF128CJE /home/drk/tillage/datasets/human/chip/encode/ENCSR860MYX/summary/ENCFF128CJE.w5 32 2 mean CHIP:H3K9me3:CD4-positive, CD25-positive, alpha-beta regulatory T cell CHIP ChIP-Histone:H3K9me3/CD4-positive, CD25-positive, alpha-beta regulatory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4109 0 ENCFF317ZAO /home/drk/tillage/datasets/human/chip/encode/ENCSR860PEV/summary/ENCFF317ZAO.w5 32 2 mean CHIP:H3K9ac:cingulate gyrus female adult (75 years) CHIP ChIP-Histone:H3K9ac/cingulate gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4110 0 ENCFF930HBS /home/drk/tillage/datasets/human/chip/encode/ENCSR860UHK/summary/ENCFF930HBS.w5 32 2 mean CHIP:CBFB:GM12878 CHIP ChIP-TF:CBFB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4111 0 ENCFF291BKK /home/drk/tillage/datasets/human/chip/encode/ENCSR861JUQ/summary/ENCFF291BKK.w5 32 2 mean CHIP:FOXK2:GM12878 CHIP ChIP-TF:FOXK2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4112 0 ENCFF270DYF /home/drk/tillage/datasets/human/chip/encode/ENCSR861XGM/summary/ENCFF270DYF.w5 32 2 mean CHIP:POLR2AphosphoS5:suprapubic skin male adult (54 years) CHIP ChIP-TF:POLR2AphosphoS5/suprapubic skin male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4113 0 ENCFF206KOB /home/drk/tillage/datasets/human/chip/encode/ENCSR862NIZ/summary/ENCFF206KOB.w5 32 2 mean CHIP:H3K27me3:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K27me3/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4114 0 ENCFF002XED /home/drk/tillage/datasets/human/chip/encode/ENCSR862NOW/summary/ENCFF002XED.w5 32 2 mean CHIP:EP300:esophagus muscularis mucosa male adult (54 years) CHIP ChIP-TF:EP300/esophagus muscularis mucosa male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4115 0 ENCFF817OXY /home/drk/tillage/datasets/human/chip/encode/ENCSR862PNL/summary/ENCFF817OXY.w5 32 2 mean CHIP:L3MBTL2:HEK293T CHIP ChIP-TF:L3MBTL2/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4116 0 ENCFF993YJQ /home/drk/tillage/datasets/human/chip/encode/ENCSR862SCU/summary/ENCFF993YJQ.w5 32 2 mean CHIP:H3K9me3:HUES6 CHIP ChIP-Histone:H3K9me3/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4117 0 ENCFF479QQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR863GVT/summary/ENCFF479QQQ.w5 32 2 mean CHIP:H3K4me1:spinal cord female embryo (108 days) CHIP ChIP-Histone:H3K4me1/spinal cord female embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4118 0 ENCFF957KCO /home/drk/tillage/datasets/human/chip/encode/ENCSR863KUB/summary/ENCFF957KCO.w5 32 2 mean CHIP:TCF7:K562 CHIP ChIP-TF:TCF7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4119 0 ENCFF231OHT /home/drk/tillage/datasets/human/chip/encode/ENCSR863TAL/summary/ENCFF231OHT.w5 32 2 mean CHIP:H3K9me3:body of pancreas male adult (54 years) CHIP ChIP-Histone:H3K9me3/body of pancreas male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4120 0 ENCFF239ARM /home/drk/tillage/datasets/human/chip/encode/ENCSR864KNH/summary/ENCFF239ARM.w5 32 2 mean CHIP:YBX1:MCF-7 CHIP ChIP-TF:YBX1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4121 0 ENCFF486JXL /home/drk/tillage/datasets/human/chip/encode/ENCSR864LRY/summary/ENCFF486JXL.w5 32 2 mean CHIP:H3K27me3:cardiac muscle cell CHIP ChIP-Histone:H3K27me3/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4122 0 ENCFF489MCJ /home/drk/tillage/datasets/human/chip/encode/ENCSR864VJE/summary/ENCFF489MCJ.w5 32 2 mean CHIP:eGFP-ZSCAN16:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZSCAN16/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4123 0 ENCFF539PSS /home/drk/tillage/datasets/human/chip/encode/ENCSR866KFY/summary/ENCFF539PSS.w5 32 2 mean CHIP:H3K27me3:GM23248 CHIP ChIP-Histone:H3K27me3/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4124 0 ENCFF405ELW /home/drk/tillage/datasets/human/chip/encode/ENCSR866QPZ/summary/ENCFF405ELW.w5 32 2 mean CHIP:ATF7:MCF-7 CHIP ChIP-TF:ATF7/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4125 0 ENCFF470FUY /home/drk/tillage/datasets/human/chip/encode/ENCSR866UQO/summary/ENCFF470FUY.w5 32 2 mean CHIP:H3K27me3:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K27me3/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4126 0 ENCFF626SMI /home/drk/tillage/datasets/human/chip/encode/ENCSR867TPP/summary/ENCFF626SMI.w5 32 2 mean CHIP:H3K27me3:OCI-LY3 CHIP ChIP-Histone:H3K27me3/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4127 0 ENCFF130UTN /home/drk/tillage/datasets/human/chip/encode/ENCSR867UKC/summary/ENCFF130UTN.w5 32 2 mean CHIP:H3K36me3:Karpas-422 CHIP ChIP-Histone:H3K36me3/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4128 0 ENCFF932WPR /home/drk/tillage/datasets/human/chip/encode/ENCSR867WPH/summary/ENCFF932WPR.w5 32 2 mean CHIP:REST:liver male adult (32 years) CHIP ChIP-TF:REST/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4129 0 ENCFF242XQC /home/drk/tillage/datasets/human/chip/encode/ENCSR868JLS/summary/ENCFF242XQC.w5 32 2 mean CHIP:U2AF1:HepG2 CHIP ChIP-TF:U2AF1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4130 0 ENCFF805GWE /home/drk/tillage/datasets/human/chip/encode/ENCSR869GBP/summary/ENCFF805GWE.w5 32 2 mean CHIP:H3K36me3:upper lobe of left lung female adult (53 years) CHIP ChIP-Histone:H3K36me3/upper lobe of left lung female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4131 0 ENCFF134GIR /home/drk/tillage/datasets/human/chip/encode/ENCSR869HJR/summary/ENCFF134GIR.w5 32 2 mean CHIP:H2AFZ:SU-DHL-6 CHIP ChIP-TF:H2AFZ/SU-DHL-6 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4132 0 ENCFF749BWV /home/drk/tillage/datasets/human/chip/encode/ENCSR869IUD/summary/ENCFF749BWV.w5 32 2 mean CHIP:ATF2:K562 CHIP ChIP-TF:ATF2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4133 0 ENCFF135VPT /home/drk/tillage/datasets/human/chip/encode/ENCSR869WSC/summary/ENCFF135VPT.w5 32 2 mean CHIP:H3K36me3:brain female embryo (17 weeks) CHIP ChIP-Histone:H3K36me3/brain female embryo (17 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4134 0 ENCFF019NRS /home/drk/tillage/datasets/human/chip/encode/ENCSR870IGD/summary/ENCFF019NRS.w5 32 2 mean CHIP:H3K4me2:Karpas-422 CHIP ChIP-Histone:H3K4me2/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4135 0 ENCFF897BZM /home/drk/tillage/datasets/human/chip/encode/ENCSR870IUC/summary/ENCFF897BZM.w5 32 2 mean CHIP:H3K36me3:H9 genetically modified using stable transfection CHIP ChIP-Histone:H3K36me3/H9 genetically modified using stable transfection ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4136 0 ENCFF735ASE /home/drk/tillage/datasets/human/chip/encode/ENCSR871KYB/summary/ENCFF735ASE.w5 32 2 mean CHIP:REST:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:REST/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4137 0 ENCFF690NQB /home/drk/tillage/datasets/human/chip/encode/ENCSR871TKJ/summary/ENCFF690NQB.w5 32 2 mean CHIP:THRAP3:K562 CHIP ChIP-TF:THRAP3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4138 0 ENCFF890KDF /home/drk/tillage/datasets/human/chip/encode/ENCSR872BOU/summary/ENCFF890KDF.w5 32 2 mean CHIP:FOXK2:HEK293T CHIP ChIP-TF:FOXK2/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4139 0 ENCFF332CBV /home/drk/tillage/datasets/human/chip/encode/ENCSR872EVQ/summary/ENCFF332CBV.w5 32 2 mean CHIP:PCBP1:HepG2 CHIP ChIP-TF:PCBP1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4140 0 ENCFF916SJB /home/drk/tillage/datasets/human/chip/encode/ENCSR872PRJ/summary/ENCFF916SJB.w5 32 2 mean CHIP:H3K9ac:MM.1S CHIP ChIP-Histone:H3K9ac/MM.1S ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4141 0 ENCFF916JAF /home/drk/tillage/datasets/human/chip/encode/ENCSR872WVR/summary/ENCFF916JAF.w5 32 2 mean CHIP:H3K4me1:gastroesophageal sphincter female adult (53 years) CHIP ChIP-Histone:H3K4me1/gastroesophageal sphincter female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4142 0 ENCFF821XXG /home/drk/tillage/datasets/human/chip/encode/ENCSR872ZHM/summary/ENCFF821XXG.w5 32 2 mean CHIP:KDM5A:HepG2 CHIP ChIP-TF:KDM5A/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4143 0 ENCFF385FQR /home/drk/tillage/datasets/human/chip/encode/ENCSR873EIA/summary/ENCFF385FQR.w5 32 2 mean CHIP:H3F3A:neural cell CHIP ChIP-Histone:H3F3A/neural cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4144 0 ENCFF723XZS /home/drk/tillage/datasets/human/chip/encode/ENCSR874AFU/summary/ENCFF723XZS.w5 32 2 mean CHIP:IKZF1:GM12878 CHIP ChIP-TF:IKZF1/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4145 0 ENCFF879VWW /home/drk/tillage/datasets/human/chip/encode/ENCSR874HSH/summary/ENCFF879VWW.w5 32 2 mean CHIP:H2AFZ:OCI-LY1 CHIP ChIP-TF:H2AFZ/OCI-LY1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4146 0 ENCFF281YYH /home/drk/tillage/datasets/human/chip/encode/ENCSR874WOB/summary/ENCFF281YYH.w5 32 2 mean CHIP:H3K4me3:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K4me3/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4147 0 ENCFF299JCQ /home/drk/tillage/datasets/human/chip/encode/ENCSR875KOJ/summary/ENCFF299JCQ.w5 32 2 mean CHIP:H3K4me2:MCF-7 CHIP ChIP-Histone:H3K4me2/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4148 0 ENCFF224IXF /home/drk/tillage/datasets/human/chip/encode/ENCSR875PEI/summary/ENCFF224IXF.w5 32 2 mean CHIP:TRIM22:MCF-7 CHIP ChIP-TF:TRIM22/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4149 0 ENCFF426AIF /home/drk/tillage/datasets/human/chip/encode/ENCSR875QDS/summary/ENCFF426AIF.w5 32 2 mean CHIP:H3K27ac:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K27ac/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4150 0 ENCFF685WIZ /home/drk/tillage/datasets/human/chip/encode/ENCSR876DCP/summary/ENCFF685WIZ.w5 32 2 mean CHIP:H3K4me3:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K4me3/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4151 0 ENCFF033QAN /home/drk/tillage/datasets/human/chip/encode/ENCSR876GXA/summary/ENCFF033QAN.w5 32 2 mean CHIP:ZBTB33:K562 CHIP ChIP-TF:ZBTB33/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4152 0 ENCFF250HNU /home/drk/tillage/datasets/human/chip/encode/ENCSR876RGF/summary/ENCFF250HNU.w5 32 2 mean CHIP:H3K27ac:H9 CHIP ChIP-Histone:H3K27ac/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4153 0 ENCFF474YTK /home/drk/tillage/datasets/human/chip/encode/ENCSR876UYH/summary/ENCFF474YTK.w5 32 2 mean CHIP:ZHX2:MCF-7 CHIP ChIP-TF:ZHX2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4154 0 ENCFF720RWF /home/drk/tillage/datasets/human/chip/encode/ENCSR877OYD/summary/ENCFF720RWF.w5 32 2 mean CHIP:POLR2A:esophagus squamous epithelium female adult (51 year) CHIP ChIP-TF:POLR2A/esophagus squamous epithelium female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4155 0 ENCFF454DUN /home/drk/tillage/datasets/human/chip/encode/ENCSR877PAS/summary/ENCFF454DUN.w5 32 2 mean CHIP:H3K27me3:small intestine female adult (30 years) CHIP ChIP-Histone:H3K27me3/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4156 0 ENCFF895NKH /home/drk/tillage/datasets/human/chip/encode/ENCSR877RMK/summary/ENCFF895NKH.w5 32 2 mean CHIP:H3K36me3:heart left ventricle male child (3 years) CHIP ChIP-Histone:H3K36me3/heart left ventricle male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4157 0 ENCFF718FJH /home/drk/tillage/datasets/human/chip/encode/ENCSR877SNO/summary/ENCFF718FJH.w5 32 2 mean CHIP:EP300:vagina female adult (53 years) CHIP ChIP-TF:EP300/vagina female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4158 0 ENCFF215CDE /home/drk/tillage/datasets/human/chip/encode/ENCSR877ZUK/summary/ENCFF215CDE.w5 32 2 mean CHIP:H3K36me3:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K36me3/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4159 0 ENCFF794ABB /home/drk/tillage/datasets/human/chip/encode/ENCSR878DES/summary/ENCFF794ABB.w5 32 2 mean CHIP:eGFP-ZNF624:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF624/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4160 0 ENCFF158FYK /home/drk/tillage/datasets/human/chip/encode/ENCSR878HPJ/summary/ENCFF158FYK.w5 32 2 mean CHIP:H4K20me1:SK-N-SH CHIP ChIP-TF:H4K20me1/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4161 0 ENCFF631DER /home/drk/tillage/datasets/human/chip/encode/ENCSR878JSF/summary/ENCFF631DER.w5 32 2 mean CHIP:H3K4me3:B cell female adult (43 years) CHIP ChIP-Histone:H3K4me3/B cell female adult (43 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4162 0 ENCFF063ITE /home/drk/tillage/datasets/human/chip/encode/ENCSR878KIY/summary/ENCFF063ITE.w5 32 2 mean CHIP:H3K4me3:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K4me3/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4163 0 ENCFF041XVA /home/drk/tillage/datasets/human/chip/encode/ENCSR879WTY/summary/ENCFF041XVA.w5 32 2 mean CHIP:H3K36me3:KOPT-K1 CHIP ChIP-Histone:H3K36me3/KOPT-K1 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4164 0 ENCFF986PCY /home/drk/tillage/datasets/human/chip/encode/ENCSR880SUY/summary/ENCFF986PCY.w5 32 2 mean CHIP:H3K27ac:H1-hESC CHIP ChIP-Histone:H3K27ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4165 0 ENCFF635DUG /home/drk/tillage/datasets/human/chip/encode/ENCSR881TWJ/summary/ENCFF635DUG.w5 32 2 mean CHIP:H3K27me3:PC-3 CHIP ChIP-Histone:H3K27me3/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4166 0 ENCFF933HRZ /home/drk/tillage/datasets/human/chip/encode/ENCSR882ERE/summary/ENCFF933HRZ.w5 32 2 mean CHIP:ZKSCAN1:K562 CHIP ChIP-TF:ZKSCAN1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4167 0 ENCFF618UQG /home/drk/tillage/datasets/human/chip/encode/ENCSR882ICT/summary/ENCFF618UQG.w5 32 2 mean CHIP:ZNF384:HEK293T CHIP ChIP-TF:ZNF384/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4168 0 ENCFF550CVX /home/drk/tillage/datasets/human/chip/encode/ENCSR882ZTS/summary/ENCFF550CVX.w5 32 2 mean CHIP:eGFP-ZBTB11:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB11/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4169 0 ENCFF300CCI /home/drk/tillage/datasets/human/chip/encode/ENCSR883AQJ/summary/ENCFF300CCI.w5 32 2 mean CHIP:H3K9me3:H1-hESC CHIP ChIP-Histone:H3K9me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4170 0 ENCFF680BLM /home/drk/tillage/datasets/human/chip/encode/ENCSR883QMZ/summary/ENCFF680BLM.w5 32 2 mean CHIP:H3K4me3:substantia nigra male adult (81 year) CHIP ChIP-Histone:H3K4me3/substantia nigra male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4171 0 ENCFF686RSH /home/drk/tillage/datasets/human/chip/encode/ENCSR883XRM/summary/ENCFF686RSH.w5 32 2 mean CHIP:H2AFZ:hepatocyte originated from H9 CHIP ChIP-TF:H2AFZ/hepatocyte originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4172 0 ENCFF136PJT /home/drk/tillage/datasets/human/chip/encode/ENCSR884EVT/summary/ENCFF136PJT.w5 32 2 mean CHIP:H3K4me3:endocrine pancreas adult (59 years) CHIP ChIP-Histone:H3K4me3/endocrine pancreas adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4173 0 ENCFF588UEY /home/drk/tillage/datasets/human/chip/encode/ENCSR884QDT/summary/ENCFF588UEY.w5 32 2 mean CHIP:H3K9me3:Loucy CHIP ChIP-Histone:H3K9me3/Loucy ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4174 0 ENCFF306TOR /home/drk/tillage/datasets/human/chip/encode/ENCSR885CMN/summary/ENCFF306TOR.w5 32 2 mean CHIP:H3K9me3:stomach male child (3 years) CHIP ChIP-Histone:H3K9me3/stomach male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4175 0 ENCFF229IOE /home/drk/tillage/datasets/human/chip/encode/ENCSR886KKK/summary/ENCFF229IOE.w5 32 2 mean CHIP:EZH2phosphoT487:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:EZH2phosphoT487/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4176 0 ENCFF378PWA /home/drk/tillage/datasets/human/chip/encode/ENCSR886RYH/summary/ENCFF378PWA.w5 32 2 mean CHIP:NONO:K562 CHIP ChIP-TF:NONO/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4177 0 ENCFF986YKG /home/drk/tillage/datasets/human/chip/encode/ENCSR887ESB/summary/ENCFF986YKG.w5 32 2 mean CHIP:H3K4me1:CD4-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me1/CD4-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4178 0 ENCFF104ERF /home/drk/tillage/datasets/human/chip/encode/ENCSR887LYD/summary/ENCFF104ERF.w5 32 2 mean CHIP:SMARCC2:HepG2 CHIP ChIP-TF:SMARCC2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4179 0 ENCFF236COL /home/drk/tillage/datasets/human/chip/encode/ENCSR887MXT/summary/ENCFF236COL.w5 32 2 mean CHIP:ZHX1:HeLa-S3 CHIP ChIP-TF:ZHX1/HeLa-S3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4180 0 ENCFF555GFA /home/drk/tillage/datasets/human/chip/encode/ENCSR887ZPC/summary/ENCFF555GFA.w5 32 2 mean CHIP:H3K9me3:mesodermal cell originated from HUES64 CHIP ChIP-Histone:H3K9me3/mesodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4181 0 ENCFF683WTT /home/drk/tillage/datasets/human/chip/encode/ENCSR888HXN/summary/ENCFF683WTT.w5 32 2 mean CHIP:POLR2A:lower leg skin female adult (53 years) CHIP ChIP-TF:POLR2A/lower leg skin female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4182 0 ENCFF988QYQ /home/drk/tillage/datasets/human/chip/encode/ENCSR888JWS/summary/ENCFF988QYQ.w5 32 2 mean CHIP:H3K36me3:brain male embryo (122 days) CHIP ChIP-Histone:H3K36me3/brain male embryo (122 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4183 0 ENCFF086QSN /home/drk/tillage/datasets/human/chip/encode/ENCSR888MKB/summary/ENCFF086QSN.w5 32 2 mean CHIP:H4K8ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H4K8ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4184 0 ENCFF862PUG /home/drk/tillage/datasets/human/chip/encode/ENCSR888OSH/summary/ENCFF862PUG.w5 32 2 mean CHIP:H3K4me1:HUES48 CHIP ChIP-Histone:H3K4me1/HUES48 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4185 0 ENCFF824JNI /home/drk/tillage/datasets/human/chip/encode/ENCSR888OWU/summary/ENCFF824JNI.w5 32 2 mean CHIP:POLR2A:upper lobe of left lung female adult (51 year) CHIP ChIP-TF:POLR2A/upper lobe of left lung female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4186 0 ENCFF488WNX /home/drk/tillage/datasets/human/chip/encode/ENCSR888WZL/summary/ENCFF488WNX.w5 32 2 mean CHIP:H3K4me3:iPS DF 19.11 male newborn CHIP ChIP-Histone:H3K4me3/iPS DF 19.11 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4187 0 ENCFF491WEL /home/drk/tillage/datasets/human/chip/encode/ENCSR888XZK/summary/ENCFF491WEL.w5 32 2 mean CHIP:TCF7L2:K562 CHIP ChIP-TF:TCF7L2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4188 0 ENCFF912TKR /home/drk/tillage/datasets/human/chip/encode/ENCSR889GGV/summary/ENCFF912TKR.w5 32 2 mean CHIP:POLR2AphosphoS5:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:POLR2AphosphoS5/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4189 0 ENCFF513MJF /home/drk/tillage/datasets/human/chip/encode/ENCSR889OUV/summary/ENCFF513MJF.w5 32 2 mean CHIP:H3K36me3:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K36me3/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4190 0 ENCFF726UCT /home/drk/tillage/datasets/human/chip/encode/ENCSR890NXD/summary/ENCFF726UCT.w5 32 2 mean CHIP:H3K4me1:neuroepithelial stem cell genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K4me1/neuroepithelial stem cell genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4191 0 ENCFF535RPW /home/drk/tillage/datasets/human/chip/encode/ENCSR890QGK/summary/ENCFF535RPW.w5 32 2 mean CHIP:H3K9me3:B cell male adult (21 year) CHIP ChIP-Histone:H3K9me3/B cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4192 0 ENCFF901XNI /home/drk/tillage/datasets/human/chip/encode/ENCSR891KSP/summary/ENCFF901XNI.w5 32 2 mean CHIP:H3K27ac:common myeloid progenitor, CD34-positive female adult (27 years) CHIP ChIP-Histone:H3K27ac/common myeloid progenitor, CD34-positive female adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4193 0 ENCFF078WGV /home/drk/tillage/datasets/human/chip/encode/ENCSR891WPD/summary/ENCFF078WGV.w5 32 2 mean CHIP:EP300:esophagus muscularis mucosa female adult (51 year) CHIP ChIP-TF:EP300/esophagus muscularis mucosa female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4194 0 ENCFF284EJX /home/drk/tillage/datasets/human/chip/encode/ENCSR891XGQ/summary/ENCFF284EJX.w5 32 2 mean CHIP:H3K27ac:angular gyrus female adult (75 years) CHIP ChIP-Histone:H3K27ac/angular gyrus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4195 0 ENCFF373VDA /home/drk/tillage/datasets/human/chip/encode/ENCSR892DRK/summary/ENCFF373VDA.w5 32 2 mean CHIP:REST:A549 CHIP ChIP-TF:REST/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4196 0 ENCFF129BLW /home/drk/tillage/datasets/human/chip/encode/ENCSR892HPQ/summary/ENCFF129BLW.w5 32 2 mean CHIP:H3K27ac:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K27ac/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4197 0 ENCFF303YLL /home/drk/tillage/datasets/human/chip/encode/ENCSR892MHG/summary/ENCFF303YLL.w5 32 2 mean CHIP:H3K36me3:liver male adult (32 years) CHIP ChIP-Histone:H3K36me3/liver male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4198 0 ENCFF284GIN /home/drk/tillage/datasets/human/chip/encode/ENCSR892QHR/summary/ENCFF284GIN.w5 32 2 mean CHIP:eGFP-PRDM6:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PRDM6/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4199 0 ENCFF433WFS /home/drk/tillage/datasets/human/chip/encode/ENCSR892RZN/summary/ENCFF433WFS.w5 32 2 mean CHIP:H3K9ac:layer of hippocampus female adult (75 years) CHIP ChIP-Histone:H3K9ac/layer of hippocampus female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4200 0 ENCFF357DTZ /home/drk/tillage/datasets/human/chip/encode/ENCSR892XFG/summary/ENCFF357DTZ.w5 32 2 mean CHIP:H3K27ac:small intestine male embryo (108 days) CHIP ChIP-Histone:H3K27ac/small intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4201 0 ENCFF352ABL /home/drk/tillage/datasets/human/chip/encode/ENCSR892ZTO/summary/ENCFF352ABL.w5 32 2 mean CHIP:eGFP-ZNF548:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF548/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4202 0 ENCFF626TMX /home/drk/tillage/datasets/human/chip/encode/ENCSR893MHU/summary/ENCFF626TMX.w5 32 2 mean CHIP:H3K36me3:caudate nucleus male adult (81 year) CHIP ChIP-Histone:H3K36me3/caudate nucleus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4203 0 ENCFF463TDC /home/drk/tillage/datasets/human/chip/encode/ENCSR893MYW/summary/ENCFF463TDC.w5 32 2 mean CHIP:POLR2AphosphoS5:upper lobe of left lung female adult (51 year) CHIP ChIP-TF:POLR2AphosphoS5/upper lobe of left lung female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4204 0 ENCFF196LYG /home/drk/tillage/datasets/human/chip/encode/ENCSR893QWP/summary/ENCFF196LYG.w5 32 2 mean CHIP:REST:liver female child (4 years) CHIP ChIP-TF:REST/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4205 0 ENCFF689LWD /home/drk/tillage/datasets/human/chip/encode/ENCSR893WSB/summary/ENCFF689LWD.w5 32 2 mean CHIP:HDAC2:K562 CHIP ChIP-TF:HDAC2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4206 0 ENCFF564JHK /home/drk/tillage/datasets/human/chip/encode/ENCSR894CGX/summary/ENCFF564JHK.w5 32 2 mean CHIP:SUPT5H:K562 CHIP ChIP-TF:SUPT5H/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4207 0 ENCFF181JZF /home/drk/tillage/datasets/human/chip/encode/ENCSR894OYM/summary/ENCFF181JZF.w5 32 2 mean CHIP:H3K4me3:HUES64 CHIP ChIP-Histone:H3K4me3/HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4208 0 ENCFF248CKW /home/drk/tillage/datasets/human/chip/encode/ENCSR894QWM/summary/ENCFF248CKW.w5 32 2 mean CHIP:EZH2phosphoT487:MM.1S CHIP ChIP-TF:EZH2phosphoT487/MM.1S ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4209 0 ENCFF833UKH /home/drk/tillage/datasets/human/chip/encode/ENCSR894SXR/summary/ENCFF833UKH.w5 32 2 mean CHIP:TCF12:HepG2 CHIP ChIP-TF:TCF12/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4210 0 ENCFF917GZE /home/drk/tillage/datasets/human/chip/encode/ENCSR895HSJ/summary/ENCFF917GZE.w5 32 2 mean CHIP:SMARCA5:K562 CHIP ChIP-TF:SMARCA5/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4211 0 ENCFF805MZK /home/drk/tillage/datasets/human/chip/encode/ENCSR895IWH/summary/ENCFF805MZK.w5 32 2 mean CHIP:H3K9me3:ES-I3 CHIP ChIP-Histone:H3K9me3/ES-I3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4212 0 ENCFF374SUU /home/drk/tillage/datasets/human/chip/encode/ENCSR895YWA/summary/ENCFF374SUU.w5 32 2 mean CHIP:H2BK12ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-TF:H2BK12ac/mesenchymal stem cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4213 0 ENCFF101RSR /home/drk/tillage/datasets/human/chip/encode/ENCSR896UBV/summary/ENCFF101RSR.w5 32 2 mean CHIP:eGFP-REST:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-REST/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4214 0 ENCFF483GFH /home/drk/tillage/datasets/human/chip/encode/ENCSR897FOZ/summary/ENCFF483GFH.w5 32 2 mean CHIP:H3K36me3:ACC112 CHIP ChIP-Histone:H3K36me3/ACC112 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4215 0 ENCFF848PUB /home/drk/tillage/datasets/human/chip/encode/ENCSR897JAS/summary/ENCFF848PUB.w5 32 2 mean CHIP:CREB1:MCF-7 CHIP ChIP-TF:CREB1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4216 0 ENCFF774DID /home/drk/tillage/datasets/human/chip/encode/ENCSR897JCM/summary/ENCFF774DID.w5 32 2 mean CHIP:eGFP-ZNF491:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF491/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4217 0 ENCFF103OHX /home/drk/tillage/datasets/human/chip/encode/ENCSR897MMC/summary/ENCFF103OHX.w5 32 2 mean CHIP:JUNB:GM12878 CHIP ChIP-TF:JUNB/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4218 0 ENCFF238ACS /home/drk/tillage/datasets/human/chip/encode/ENCSR897MYK/summary/ENCFF238ACS.w5 32 2 mean CHIP:SREBF1:A549 CHIP ChIP-TF:SREBF1/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4219 0 ENCFF288CAL /home/drk/tillage/datasets/human/chip/encode/ENCSR897RVP/summary/ENCFF288CAL.w5 32 2 mean CHIP:eGFP-ZNF514:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF514/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4220 0 ENCFF529ZIO /home/drk/tillage/datasets/human/chip/encode/ENCSR897TGR/summary/ENCFF529ZIO.w5 32 2 mean CHIP:H3K27me3:sigmoid colon male child (3 years) CHIP ChIP-Histone:H3K27me3/sigmoid colon male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4221 0 ENCFF496QAX /home/drk/tillage/datasets/human/chip/encode/ENCSR897ZXU/summary/ENCFF496QAX.w5 32 2 mean CHIP:E2F8:MCF-7 CHIP ChIP-TF:E2F8/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4222 0 ENCFF324PVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR898XMH/summary/ENCFF324PVJ.w5 32 2 mean CHIP:ZFP91:K562 CHIP ChIP-TF:ZFP91/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4223 0 ENCFF930AUF /home/drk/tillage/datasets/human/chip/encode/ENCSR899BKM/summary/ENCFF930AUF.w5 32 2 mean CHIP:ZNF687:MCF-7 CHIP ChIP-TF:ZNF687/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4224 0 ENCFF225MPH /home/drk/tillage/datasets/human/chip/encode/ENCSR899GSH/summary/ENCFF225MPH.w5 32 2 mean CHIP:RBM34:K562 CHIP ChIP-TF:RBM34/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4225 0 ENCFF532QGW /home/drk/tillage/datasets/human/chip/encode/ENCSR899JSO/summary/ENCFF532QGW.w5 32 2 mean CHIP:CTCF:adrenal gland male adult (37 years) CHIP ChIP-TF:CTCF/adrenal gland male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4226 0 ENCFF933SRS /home/drk/tillage/datasets/human/chip/encode/ENCSR899MFS/summary/ENCFF933SRS.w5 32 2 mean CHIP:H3K36me3:adrenal gland female adult (30 years) CHIP ChIP-Histone:H3K36me3/adrenal gland female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4227 0 ENCFF189ZFO /home/drk/tillage/datasets/human/chip/encode/ENCSR899TDF/summary/ENCFF189ZFO.w5 32 2 mean CHIP:H3K9me3:gastrocnemius medialis female adult (53 years) CHIP ChIP-Histone:H3K9me3/gastrocnemius medialis female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4228 0 ENCFF352XRA /home/drk/tillage/datasets/human/chip/encode/ENCSR900AQX/summary/ENCFF352XRA.w5 32 2 mean CHIP:H4K20me1:GM23248 CHIP ChIP-TF:H4K20me1/GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4229 0 ENCFF338VZQ /home/drk/tillage/datasets/human/chip/encode/ENCSR900EUT/summary/ENCFF338VZQ.w5 32 2 mean CHIP:H2BK120ac:mesendoderm originated from H1-hESC CHIP ChIP-TF:H2BK120ac/mesendoderm originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4230 0 ENCFF128GMY /home/drk/tillage/datasets/human/chip/encode/ENCSR900HAP/summary/ENCFF128GMY.w5 32 2 mean CHIP:H2AFZ:Loucy CHIP ChIP-TF:H2AFZ/Loucy ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4231 0 ENCFF949COK /home/drk/tillage/datasets/human/chip/encode/ENCSR900UIP/summary/ENCFF949COK.w5 32 2 mean CHIP:H3K4me3:sigmoid colon female adult (53 years) CHIP ChIP-Histone:H3K4me3/sigmoid colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4232 0 ENCFF735YSE /home/drk/tillage/datasets/human/chip/encode/ENCSR900XDB/summary/ENCFF735YSE.w5 32 2 mean CHIP:ZFP36:GM12878 CHIP ChIP-TF:ZFP36/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4233 0 ENCFF552YTU /home/drk/tillage/datasets/human/chip/encode/ENCSR901BRV/summary/ENCFF552YTU.w5 32 2 mean CHIP:H3K4me3:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K4me3/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4234 0 ENCFF904CBR /home/drk/tillage/datasets/human/chip/encode/ENCSR901JIL/summary/ENCFF904CBR.w5 32 2 mean CHIP:H3K4me1:mucosa of rectum female adult (50 years) CHIP ChIP-Histone:H3K4me1/mucosa of rectum female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4235 0 ENCFF407AKM /home/drk/tillage/datasets/human/chip/encode/ENCSR901SCD/summary/ENCFF407AKM.w5 32 2 mean CHIP:H3K4me1:temporal lobe male adult (81 year) CHIP ChIP-Histone:H3K4me1/temporal lobe male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4236 0 ENCFF254JZR /home/drk/tillage/datasets/human/chip/encode/ENCSR901SIL/summary/ENCFF254JZR.w5 32 2 mean CHIP:H3K4me3:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K4me3/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4237 0 ENCFF081VTF /home/drk/tillage/datasets/human/chip/encode/ENCSR902EEI/summary/ENCFF081VTF.w5 32 2 mean CHIP:H3K4ac:mesenchymal stem cell originated from H1-hESC CHIP ChIP-Histone:H3K4ac/mesenchymal stem cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4238 0 ENCFF797BMA /home/drk/tillage/datasets/human/chip/encode/ENCSR902OPY/summary/ENCFF797BMA.w5 32 2 mean CHIP:H3K9ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) CHIP ChIP-Histone:H3K9ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4239 0 ENCFF116FZG /home/drk/tillage/datasets/human/chip/encode/ENCSR902QIJ/summary/ENCFF116FZG.w5 32 2 mean CHIP:H3K4me3:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K4me3/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4240 0 ENCFF906AXR /home/drk/tillage/datasets/human/chip/encode/ENCSR903ELW/summary/ENCFF906AXR.w5 32 2 mean CHIP:CREM:HepG2 CHIP ChIP-TF:CREM/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4241 0 ENCFF784XVJ /home/drk/tillage/datasets/human/chip/encode/ENCSR903GLL/summary/ENCFF784XVJ.w5 32 2 mean CHIP:H3K27me3:body of pancreas female adult (53 years) CHIP ChIP-Histone:H3K27me3/body of pancreas female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4242 0 ENCFF329CTC /home/drk/tillage/datasets/human/chip/encode/ENCSR903QBX/summary/ENCFF329CTC.w5 32 2 mean CHIP:H3K4me1:stomach female adult (53 years) CHIP ChIP-Histone:H3K4me1/stomach female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4243 0 ENCFF179RUF /home/drk/tillage/datasets/human/chip/encode/ENCSR904LIL/summary/ENCFF179RUF.w5 32 2 mean CHIP:H3K27me3:liver female adult (25 years) CHIP ChIP-Histone:H3K27me3/liver female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4244 0 ENCFF863CFM /home/drk/tillage/datasets/human/chip/encode/ENCSR905SHH/summary/ENCFF863CFM.w5 32 2 mean CHIP:H3K9me3:CD8-positive, alpha-beta T cell CHIP ChIP-Histone:H3K9me3/CD8-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4245 0 ENCFF346CWF /home/drk/tillage/datasets/human/chip/encode/ENCSR905TYC/summary/ENCFF346CWF.w5 32 2 mean CHIP:H3K27ac:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-Histone:H3K27ac/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4246 0 ENCFF013LVR /home/drk/tillage/datasets/human/chip/encode/ENCSR906NGD/summary/ENCFF013LVR.w5 32 2 mean CHIP:H3K4me1:GM23248 CHIP ChIP-Histone:H3K4me1/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4247 0 ENCFF755ELJ /home/drk/tillage/datasets/human/chip/encode/ENCSR906OMM/summary/ENCFF755ELJ.w5 32 2 mean CHIP:EP300:gastroesophageal sphincter male adult (54 years) CHIP ChIP-TF:EP300/gastroesophageal sphincter male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4248 0 ENCFF263BSM /home/drk/tillage/datasets/human/chip/encode/ENCSR906PCS/summary/ENCFF263BSM.w5 32 2 mean CHIP:eGFP-ZNF223:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF223/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4249 0 ENCFF229HKY /home/drk/tillage/datasets/human/chip/encode/ENCSR906PEI/summary/ENCFF229HKY.w5 32 2 mean CHIP:SP1:HEK293T CHIP ChIP-TF:SP1/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4250 0 ENCFF587VFM /home/drk/tillage/datasets/human/chip/encode/ENCSR906UPC/summary/ENCFF587VFM.w5 32 2 mean CHIP:EP300:sigmoid colon male adult (37 years) CHIP ChIP-TF:EP300/sigmoid colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4251 0 ENCFF733GQJ /home/drk/tillage/datasets/human/chip/encode/ENCSR906YES/summary/ENCFF733GQJ.w5 32 2 mean CHIP:H3K4me1:thyroid gland male adult (37 years) CHIP ChIP-Histone:H3K4me1/thyroid gland male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4252 0 ENCFF991QOA /home/drk/tillage/datasets/human/chip/encode/ENCSR907BES/summary/ENCFF991QOA.w5 32 2 mean CHIP:CTCF:transverse colon male adult (54 years) CHIP ChIP-TF:CTCF/transverse colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4253 0 ENCFF656SAU /home/drk/tillage/datasets/human/chip/encode/ENCSR907JPB/summary/ENCFF656SAU.w5 32 2 mean CHIP:ZMIZ1:K562 CHIP ChIP-TF:ZMIZ1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4254 0 ENCFF398OOI /home/drk/tillage/datasets/human/chip/encode/ENCSR907MZR/summary/ENCFF398OOI.w5 32 2 mean CHIP:TRIM24:K562 CHIP ChIP-TF:TRIM24/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4255 0 ENCFF900ZKJ /home/drk/tillage/datasets/human/chip/encode/ENCSR908CMW/summary/ENCFF900ZKJ.w5 32 2 mean CHIP:KDM1A:K562 CHIP ChIP-TF:KDM1A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4256 0 ENCFF204CLP /home/drk/tillage/datasets/human/chip/encode/ENCSR908DTR/summary/ENCFF204CLP.w5 32 2 mean CHIP:H3K36me3:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K36me3/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4257 0 ENCFF851GXF /home/drk/tillage/datasets/human/chip/encode/ENCSR908FQA/summary/ENCFF851GXF.w5 32 2 mean CHIP:H2AFZ:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:H2AFZ/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4258 0 ENCFF309ZRK /home/drk/tillage/datasets/human/chip/encode/ENCSR909GJR/summary/ENCFF309ZRK.w5 32 2 mean CHIP:3xFLAG-MXD3:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MXD3/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4259 0 ENCFF971UQV /home/drk/tillage/datasets/human/chip/encode/ENCSR909HMT/summary/ENCFF971UQV.w5 32 2 mean CHIP:eGFP-ZEB1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZEB1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4260 0 ENCFF123TCV /home/drk/tillage/datasets/human/chip/encode/ENCSR909TSW/summary/ENCFF123TCV.w5 32 2 mean CHIP:eGFP-ZNF547:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF547/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4261 0 ENCFF511QGD /home/drk/tillage/datasets/human/chip/encode/ENCSR909UAG/summary/ENCFF511QGD.w5 32 2 mean CHIP:H3K27ac:esophagus squamous epithelium female adult (53 years) CHIP ChIP-Histone:H3K27ac/esophagus squamous epithelium female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4262 0 ENCFF249NHD /home/drk/tillage/datasets/human/chip/encode/ENCSR909VUB/summary/ENCFF249NHD.w5 32 2 mean CHIP:H3K9me3:thoracic aorta male adult (54 years) CHIP ChIP-Histone:H3K9me3/thoracic aorta male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4263 0 ENCFF942GZB /home/drk/tillage/datasets/human/chip/encode/ENCSR909ZLE/summary/ENCFF942GZB.w5 32 2 mean CHIP:H3K27ac:chorion male embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/chorion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4264 0 ENCFF833UPN /home/drk/tillage/datasets/human/chip/encode/ENCSR910JAI/summary/ENCFF833UPN.w5 32 2 mean CHIP:NCOR1:K562 CHIP ChIP-TF:NCOR1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4265 0 ENCFF321LUP /home/drk/tillage/datasets/human/chip/encode/ENCSR910LIE/summary/ENCFF321LUP.w5 32 2 mean CHIP:H3K36me3:HEK293 CHIP ChIP-Histone:H3K36me3/HEK293 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4266 0 ENCFF068PBX /home/drk/tillage/datasets/human/chip/encode/ENCSR910PDW/summary/ENCFF068PBX.w5 32 2 mean CHIP:H3K27ac:epithelial cell of prostate male CHIP ChIP-Histone:H3K27ac/epithelial cell of prostate male ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4267 0 ENCFF389OHA /home/drk/tillage/datasets/human/chip/encode/ENCSR910XKX/summary/ENCFF389OHA.w5 32 2 mean CHIP:H3K4me3:Karpas-422 CHIP ChIP-Histone:H3K4me3/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4268 0 ENCFF273UYD /home/drk/tillage/datasets/human/chip/encode/ENCSR911BCA/summary/ENCFF273UYD.w5 32 2 mean CHIP:H3K4me1:effector memory CD4-positive, alpha-beta T cell CHIP ChIP-Histone:H3K4me1/effector memory CD4-positive, alpha-beta T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4269 0 ENCFF646FIY /home/drk/tillage/datasets/human/chip/encode/ENCSR911GFJ/summary/ENCFF646FIY.w5 32 2 mean CHIP:CTCF:right lobe of liver female adult (53 years) CHIP ChIP-TF:CTCF/right lobe of liver female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4270 0 ENCFF493VXF /home/drk/tillage/datasets/human/chip/encode/ENCSR911JAX/summary/ENCFF493VXF.w5 32 2 mean CHIP:POLR2A:prostate gland male adult (37 years) CHIP ChIP-TF:POLR2A/prostate gland male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4271 0 ENCFF541FUB /home/drk/tillage/datasets/human/chip/encode/ENCSR911WPA/summary/ENCFF541FUB.w5 32 2 mean CHIP:H3K27me3:germinal matrix male embryo (20 weeks) CHIP ChIP-Histone:H3K27me3/germinal matrix male embryo (20 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4272 0 ENCFF931FJL /home/drk/tillage/datasets/human/chip/encode/ENCSR912ATU/summary/ENCFF931FJL.w5 32 2 mean CHIP:ZNF217:MCF-7 CHIP ChIP-TF:ZNF217/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4273 0 ENCFF455JTU /home/drk/tillage/datasets/human/chip/encode/ENCSR912IDH/summary/ENCFF455JTU.w5 32 2 mean CHIP:H3K4me1:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K4me1/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4274 0 ENCFF767COZ /home/drk/tillage/datasets/human/chip/encode/ENCSR912NMR/summary/ENCFF767COZ.w5 32 2 mean CHIP:NONO:MCF-7 CHIP ChIP-TF:NONO/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4275 0 ENCFF564VOY /home/drk/tillage/datasets/human/chip/encode/ENCSR912TVO/summary/ENCFF564VOY.w5 32 2 mean CHIP:H3K27ac:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K27ac/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4276 0 ENCFF446WTP /home/drk/tillage/datasets/human/chip/encode/ENCSR913MGR/summary/ENCFF446WTP.w5 32 2 mean CHIP:H3K4me1:PC-9 CHIP ChIP-Histone:H3K4me1/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4277 0 ENCFF668FSK /home/drk/tillage/datasets/human/chip/encode/ENCSR914AWT/summary/ENCFF668FSK.w5 32 2 mean CHIP:H3K36me3:GM23248 CHIP ChIP-Histone:H3K36me3/GM23248 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4278 0 ENCFF648XXD /home/drk/tillage/datasets/human/chip/encode/ENCSR914NEI/summary/ENCFF648XXD.w5 32 2 mean CHIP:MTA3:K562 CHIP ChIP-TF:MTA3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4279 0 ENCFF224TVD /home/drk/tillage/datasets/human/chip/encode/ENCSR914QOK/summary/ENCFF224TVD.w5 32 2 mean CHIP:H3K27me3:SK-N-SH CHIP ChIP-Histone:H3K27me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4280 0 ENCFF568CZP /home/drk/tillage/datasets/human/chip/encode/ENCSR916JAC/summary/ENCFF568CZP.w5 32 2 mean CHIP:POLR2AphosphoS5:gastroesophageal sphincter male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/gastroesophageal sphincter male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4281 0 ENCFF792VIR /home/drk/tillage/datasets/human/chip/encode/ENCSR916MHZ/summary/ENCFF792VIR.w5 32 2 mean CHIP:H3K27me3:iPS DF 6.9 male newborn CHIP ChIP-Histone:H3K27me3/iPS DF 6.9 male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4282 0 ENCFF078JZB /home/drk/tillage/datasets/human/chip/encode/ENCSR917QEH/summary/ENCFF078JZB.w5 32 2 mean CHIP:H3K27ac:foreskin fibroblast male newborn CHIP ChIP-Histone:H3K27ac/foreskin fibroblast male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4283 0 ENCFF667HOI /home/drk/tillage/datasets/human/chip/encode/ENCSR917QNE/summary/ENCFF667HOI.w5 32 2 mean CHIP:RAD21:liver male adult (32 years) CHIP ChIP-TF:RAD21/liver male adult (32 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4284 0 ENCFF637HQY /home/drk/tillage/datasets/human/chip/encode/ENCSR919CZU/summary/ENCFF637HQY.w5 32 2 mean CHIP:eGFP-EGR2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-EGR2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4285 0 ENCFF489EZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR919DBC/summary/ENCFF489EZJ.w5 32 2 mean CHIP:H3K4me1:HUES6 CHIP ChIP-Histone:H3K4me1/HUES6 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4286 0 ENCFF948LKS /home/drk/tillage/datasets/human/chip/encode/ENCSR919UCY/summary/ENCFF948LKS.w5 32 2 mean CHIP:POLR2AphosphoS5:vagina female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/vagina female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4287 0 ENCFF201REJ /home/drk/tillage/datasets/human/chip/encode/ENCSR920ASP/summary/ENCFF201REJ.w5 32 2 mean CHIP:eGFP-ZFX:K562 genetically modified using CRISPR CHIP ChIP-TF:eGFP-ZFX/K562 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4288 0 ENCFF743WQN /home/drk/tillage/datasets/human/chip/encode/ENCSR920BLG/summary/ENCFF743WQN.w5 32 2 mean CHIP:SIN3A:K562 CHIP ChIP-TF:SIN3A/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4289 0 ENCFF273YMG /home/drk/tillage/datasets/human/chip/encode/ENCSR920EOT/summary/ENCFF273YMG.w5 32 2 mean CHIP:H3K27me3:T-cell male adult (37 years) CHIP ChIP-Histone:H3K27me3/T-cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4290 0 ENCFF078WQQ /home/drk/tillage/datasets/human/chip/encode/ENCSR920FID/summary/ENCFF078WQQ.w5 32 2 mean CHIP:POLR2AphosphoS5:sigmoid colon male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/sigmoid colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4291 0 ENCFF606BTV /home/drk/tillage/datasets/human/chip/encode/ENCSR920YBY/summary/ENCFF606BTV.w5 32 2 mean CHIP:H3K36me3:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K36me3/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4292 0 ENCFF359OXE /home/drk/tillage/datasets/human/chip/encode/ENCSR922CAT/summary/ENCFF359OXE.w5 32 2 mean CHIP:H3K4me3:mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 CHIP ChIP-Histone:H3K4me3/mid-neurogenesis radial glial cells genetically modified using stable transfection originated from H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4293 0 ENCFF561TVM /home/drk/tillage/datasets/human/chip/encode/ENCSR922GUA/summary/ENCFF561TVM.w5 32 2 mean CHIP:POLR2A:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-TF:POLR2A/esophagus muscularis mucosa female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4294 0 ENCFF481NBQ /home/drk/tillage/datasets/human/chip/encode/ENCSR922JMI/summary/ENCFF481NBQ.w5 32 2 mean CHIP:H3K9ac:subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) CHIP ChIP-Histone:H3K9ac/subcutaneous abdominal adipose tissue nuclear fraction female adult (25 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4295 0 ENCFF635ZJW /home/drk/tillage/datasets/human/chip/encode/ENCSR922OXX/summary/ENCFF635ZJW.w5 32 2 mean CHIP:H3K9me3:gastrocnemius medialis male adult (37 years) CHIP ChIP-Histone:H3K9me3/gastrocnemius medialis male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4296 0 ENCFF179GFG /home/drk/tillage/datasets/human/chip/encode/ENCSR923IIU/summary/ENCFF179GFG.w5 32 2 mean CHIP:H3K4me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) CHIP ChIP-Histone:H3K4me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4297 0 ENCFF236VKH /home/drk/tillage/datasets/human/chip/encode/ENCSR923UTX/summary/ENCFF236VKH.w5 32 2 mean CHIP:NONO:HepG2 CHIP ChIP-TF:NONO/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4298 0 ENCFF902HKG /home/drk/tillage/datasets/human/chip/encode/ENCSR923WJS/summary/ENCFF902HKG.w5 32 2 mean CHIP:EP300:sigmoid colon male adult (54 years) CHIP ChIP-TF:EP300/sigmoid colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4299 0 ENCFF272PJK /home/drk/tillage/datasets/human/chip/encode/ENCSR923WPP/summary/ENCFF272PJK.w5 32 2 mean CHIP:H3K36me3:thymus male child (3 years) CHIP ChIP-Histone:H3K36me3/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4300 0 ENCFF670XAO /home/drk/tillage/datasets/human/chip/encode/ENCSR924GRG/summary/ENCFF670XAO.w5 32 2 mean CHIP:eGFP-ZBTB49:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB49/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4301 0 ENCFF539UUP /home/drk/tillage/datasets/human/chip/encode/ENCSR924GXX/summary/ENCFF539UUP.w5 32 2 mean CHIP:PHB2:K562 CHIP ChIP-TF:PHB2/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4302 0 ENCFF291QJT /home/drk/tillage/datasets/human/chip/encode/ENCSR924TVL/summary/ENCFF291QJT.w5 32 2 mean CHIP:RFX5:MCF-7 CHIP ChIP-TF:RFX5/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4303 0 ENCFF016LJK /home/drk/tillage/datasets/human/chip/encode/ENCSR925BFV/summary/ENCFF016LJK.w5 32 2 mean CHIP:3xFLAG-GATAD2A:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-GATAD2A/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4304 0 ENCFF903AWD /home/drk/tillage/datasets/human/chip/encode/ENCSR925GDS/summary/ENCFF903AWD.w5 32 2 mean CHIP:CTCF:sigmoid colon female adult (53 years) CHIP ChIP-TF:CTCF/sigmoid colon female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4305 0 ENCFF918TJS /home/drk/tillage/datasets/human/chip/encode/ENCSR925LJZ/summary/ENCFF918TJS.w5 32 2 mean CHIP:H3K36me3:H1-hESC CHIP ChIP-Histone:H3K36me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4306 0 ENCFF412CCL /home/drk/tillage/datasets/human/chip/encode/ENCSR925QAW/summary/ENCFF412CCL.w5 32 2 mean CHIP:3xFLAG-HMG20B:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-HMG20B/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4307 0 ENCFF315HCK /home/drk/tillage/datasets/human/chip/encode/ENCSR925WMT/summary/ENCFF315HCK.w5 32 2 mean CHIP:H3K36me3:skeletal muscle tissue male adult (54 years) CHIP ChIP-Histone:H3K36me3/skeletal muscle tissue male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4308 0 ENCFF340JFR /home/drk/tillage/datasets/human/chip/encode/ENCSR926KTP/summary/ENCFF340JFR.w5 32 2 mean CHIP:eGFP-IRF9:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-IRF9/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4309 0 ENCFF174JGJ /home/drk/tillage/datasets/human/chip/encode/ENCSR926NMC/summary/ENCFF174JGJ.w5 32 2 mean CHIP:H3K4me3:adrenal gland male adult (54 years) CHIP ChIP-Histone:H3K4me3/adrenal gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4310 0 ENCFF528IMH /home/drk/tillage/datasets/human/chip/encode/ENCSR927UJQ/summary/ENCFF528IMH.w5 32 2 mean CHIP:eGFP-ZBTB1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZBTB1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4311 0 ENCFF826JSB /home/drk/tillage/datasets/human/chip/encode/ENCSR928API/summary/ENCFF826JSB.w5 32 2 mean CHIP:RFX1:HepG2 CHIP ChIP-TF:RFX1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4312 0 ENCFF799BTI /home/drk/tillage/datasets/human/chip/encode/ENCSR928HSI/summary/ENCFF799BTI.w5 32 2 mean CHIP:H3K27ac:heart right ventricle male adult (34 years) CHIP ChIP-Histone:H3K27ac/heart right ventricle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4313 0 ENCFF502GXT /home/drk/tillage/datasets/human/chip/encode/ENCSR928HYM/summary/ENCFF502GXT.w5 32 2 mean CHIP:H3K27me3:H1-hESC CHIP ChIP-Histone:H3K27me3/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4314 0 ENCFF015ZEB /home/drk/tillage/datasets/human/chip/encode/ENCSR928KOR/summary/ENCFF015ZEB.w5 32 2 mean CHIP:GMEB1:K562 CHIP ChIP-TF:GMEB1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4315 0 ENCFF184LRB /home/drk/tillage/datasets/human/chip/encode/ENCSR928LDG/summary/ENCFF184LRB.w5 32 2 mean CHIP:EP300:suprapubic skin female adult (53 years) CHIP ChIP-TF:EP300/suprapubic skin female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4316 0 ENCFF588UZN /home/drk/tillage/datasets/human/chip/encode/ENCSR928UVY/summary/ENCFF588UZN.w5 32 2 mean CHIP:H2AFZ:neuron originated from H9 CHIP ChIP-TF:H2AFZ/neuron originated from H9 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4317 0 ENCFF093DHH /home/drk/tillage/datasets/human/chip/encode/ENCSR929AXP/summary/ENCFF093DHH.w5 32 2 mean CHIP:H3K27me3:muscle layer of duodenum male adult (59 years) CHIP ChIP-Histone:H3K27me3/muscle layer of duodenum male adult (59 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4318 0 ENCFF640OPA /home/drk/tillage/datasets/human/chip/encode/ENCSR930CPA/summary/ENCFF640OPA.w5 32 2 mean CHIP:POLR2AphosphoS5:transverse colon male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/transverse colon male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4319 0 ENCFF713DRZ /home/drk/tillage/datasets/human/chip/encode/ENCSR930HLX/summary/ENCFF713DRZ.w5 32 2 mean CHIP:H3K4me3:thoracic aorta male adult (54 years) CHIP ChIP-Histone:H3K4me3/thoracic aorta male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4320 0 ENCFF730HGY /home/drk/tillage/datasets/human/chip/encode/ENCSR930OZC/summary/ENCFF730HGY.w5 32 2 mean CHIP:H3K36me3:skeletal muscle tissue female adult (72 years) CHIP ChIP-Histone:H3K36me3/skeletal muscle tissue female adult (72 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4321 0 ENCFF995OEX /home/drk/tillage/datasets/human/chip/encode/ENCSR930SYJ/summary/ENCFF995OEX.w5 32 2 mean CHIP:H3K9me3:H7-hESC CHIP ChIP-Histone:H3K9me3/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4322 0 ENCFF428TVE /home/drk/tillage/datasets/human/chip/encode/ENCSR931HNY/summary/ENCFF428TVE.w5 32 2 mean CHIP:NCOA1:K562 CHIP ChIP-TF:NCOA1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4323 0 ENCFF454UPE /home/drk/tillage/datasets/human/chip/encode/ENCSR931WLE/summary/ENCFF454UPE.w5 32 2 mean CHIP:H3K27ac:mesodermal cell originated from HUES64 CHIP ChIP-Histone:H3K27ac/mesodermal cell originated from HUES64 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4324 0 ENCFF391AZY /home/drk/tillage/datasets/human/chip/encode/ENCSR932ZMX/summary/ENCFF391AZY.w5 32 2 mean CHIP:CTCF:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:CTCF/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4325 0 ENCFF254GWA /home/drk/tillage/datasets/human/chip/encode/ENCSR933BVL/summary/ENCFF254GWA.w5 32 2 mean CHIP:H3K4me3:transverse colon female adult (53 years) CHIP ChIP-Histone:H3K4me3/transverse colon female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4326 0 ENCFF714MSZ /home/drk/tillage/datasets/human/chip/encode/ENCSR933EYC/summary/ENCFF714MSZ.w5 32 2 mean CHIP:HDAC6:GM12878 CHIP ChIP-TF:HDAC6/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4327 0 ENCFF674QOX /home/drk/tillage/datasets/human/chip/encode/ENCSR933MHJ/summary/ENCFF674QOX.w5 32 2 mean CHIP:KDM5A:A549 CHIP ChIP-TF:KDM5A/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4328 0 ENCFF082RWR /home/drk/tillage/datasets/human/chip/encode/ENCSR934JDG/summary/ENCFF082RWR.w5 32 2 mean CHIP:CLOCK:MCF-7 CHIP ChIP-TF:CLOCK/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4329 0 ENCFF489TBQ /home/drk/tillage/datasets/human/chip/encode/ENCSR934NHU/summary/ENCFF489TBQ.w5 32 2 mean CHIP:MXI1:neural cell originated from H1-hESC CHIP ChIP-TF:MXI1/neural cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4330 0 ENCFF188HNM /home/drk/tillage/datasets/human/chip/encode/ENCSR935XOT/summary/ENCFF188HNM.w5 32 2 mean CHIP:POLR2A:tibial nerve female adult (53 years) CHIP ChIP-TF:POLR2A/tibial nerve female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4331 0 ENCFF127MNE /home/drk/tillage/datasets/human/chip/encode/ENCSR936FAH/summary/ENCFF127MNE.w5 32 2 mean CHIP:H3K4me3:lung female embryo (120 days) CHIP ChIP-Histone:H3K4me3/lung female embryo (120 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4332 0 ENCFF996MPK /home/drk/tillage/datasets/human/chip/encode/ENCSR936JHB/summary/ENCFF996MPK.w5 32 2 mean CHIP:POLR2AphosphoS5:esophagus muscularis mucosa female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/esophagus muscularis mucosa female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4333 0 ENCFF232VFZ /home/drk/tillage/datasets/human/chip/encode/ENCSR936XTK/summary/ENCFF232VFZ.w5 32 2 mean CHIP:ZNF143:GM12878 CHIP ChIP-TF:ZNF143/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4334 0 ENCFF165CAC /home/drk/tillage/datasets/human/chip/encode/ENCSR938ETG/summary/ENCFF165CAC.w5 32 2 mean CHIP:3xFLAG-KLF9:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KLF9/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4335 0 ENCFF385QPB /home/drk/tillage/datasets/human/chip/encode/ENCSR939FGB/summary/ENCFF385QPB.w5 32 2 mean CHIP:POLR2AphosphoS5:breast epithelium female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/breast epithelium female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4336 0 ENCFF936TIC /home/drk/tillage/datasets/human/chip/encode/ENCSR939JZW/summary/ENCFF936TIC.w5 32 2 mean CHIP:H3K27me3:natural killer cell male adult (21 year) CHIP ChIP-Histone:H3K27me3/natural killer cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4337 0 ENCFF008EYF /home/drk/tillage/datasets/human/chip/encode/ENCSR939RLS/summary/ENCFF008EYF.w5 32 2 mean CHIP:H3K27me3:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K27me3/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4338 0 ENCFF713JLD /home/drk/tillage/datasets/human/chip/encode/ENCSR939UQD/summary/ENCFF713JLD.w5 32 2 mean CHIP:H3K4me3:B cell male adult (37 years) CHIP ChIP-Histone:H3K4me3/B cell male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4339 0 ENCFF201IMK /home/drk/tillage/datasets/human/chip/encode/ENCSR940MHE/summary/ENCFF201IMK.w5 32 2 mean CHIP:MBD2:MCF-7 CHIP ChIP-TF:MBD2/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4340 0 ENCFF038BSL /home/drk/tillage/datasets/human/chip/encode/ENCSR940RIU/summary/ENCFF038BSL.w5 32 2 mean CHIP:H2BK12ac:neural stem progenitor cell originated from H1-hESC CHIP ChIP-TF:H2BK12ac/neural stem progenitor cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4341 0 ENCFF630RSV /home/drk/tillage/datasets/human/chip/encode/ENCSR941QJQ/summary/ENCFF630RSV.w5 32 2 mean CHIP:H3K4me2:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K4me2/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4342 0 ENCFF459UPU /home/drk/tillage/datasets/human/chip/encode/ENCSR941WHT/summary/ENCFF459UPU.w5 32 2 mean CHIP:H3K27me3:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K27me3/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4343 0 ENCFF651NSI /home/drk/tillage/datasets/human/chip/encode/ENCSR941YPY/summary/ENCFF651NSI.w5 32 2 mean CHIP:H3K4me3:iPS-11a male adult (36 years) CHIP ChIP-Histone:H3K4me3/iPS-11a male adult (36 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4344 0 ENCFF222DOT /home/drk/tillage/datasets/human/chip/encode/ENCSR942NME/summary/ENCFF222DOT.w5 32 2 mean CHIP:H3K23ac:IMR-90 CHIP ChIP-Histone:H3K23ac/IMR-90 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4345 0 ENCFF517JDW /home/drk/tillage/datasets/human/chip/encode/ENCSR942XCE/summary/ENCFF517JDW.w5 32 2 mean CHIP:H3K36me3:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K36me3/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4346 0 ENCFF990LTW /home/drk/tillage/datasets/human/chip/encode/ENCSR943JOF/summary/ENCFF990LTW.w5 32 2 mean CHIP:H3K36me3:pancreas male adult (34 years) CHIP ChIP-Histone:H3K36me3/pancreas male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4347 0 ENCFF138PTS /home/drk/tillage/datasets/human/chip/encode/ENCSR943LZX/summary/ENCFF138PTS.w5 32 2 mean CHIP:H3K9me2:PC-3 CHIP ChIP-Histone:H3K9me2/PC-3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4348 0 ENCFF183LFN /home/drk/tillage/datasets/human/chip/encode/ENCSR943PIR/summary/ENCFF183LFN.w5 32 2 mean CHIP:H3K4me3:muscle layer of colon female adult (77 years) CHIP ChIP-Histone:H3K4me3/muscle layer of colon female adult (77 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4349 0 ENCFF246LCK /home/drk/tillage/datasets/human/chip/encode/ENCSR944QSH/summary/ENCFF246LCK.w5 32 2 mean CHIP:H3K4me3:small intestine female adult (30 years) CHIP ChIP-Histone:H3K4me3/small intestine female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4350 0 ENCFF943RRM /home/drk/tillage/datasets/human/chip/encode/ENCSR944RKI/summary/ENCFF943RRM.w5 32 2 mean CHIP:H3K36me3:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K36me3/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4351 0 ENCFF008SBY /home/drk/tillage/datasets/human/chip/encode/ENCSR945KBK/summary/ENCFF008SBY.w5 32 2 mean CHIP:H3K9ac:PC-9 CHIP ChIP-Histone:H3K9ac/PC-9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4352 0 ENCFF359GGR /home/drk/tillage/datasets/human/chip/encode/ENCSR945NFL/summary/ENCFF359GGR.w5 32 2 mean CHIP:USF2:SK-N-SH CHIP ChIP-TF:USF2/SK-N-SH ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4353 0 ENCFF707DIF /home/drk/tillage/datasets/human/chip/encode/ENCSR945NSF/summary/ENCFF707DIF.w5 32 2 mean CHIP:PCBP2:HepG2 CHIP ChIP-TF:PCBP2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4354 0 ENCFF934FKI /home/drk/tillage/datasets/human/chip/encode/ENCSR946QFD/summary/ENCFF934FKI.w5 32 2 mean CHIP:H2AFZ:PC-3 CHIP ChIP-TF:H2AFZ/PC-3 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4355 0 ENCFF469FBI /home/drk/tillage/datasets/human/chip/encode/ENCSR946ZLI/summary/ENCFF469FBI.w5 32 2 mean CHIP:eGFP-KLF13:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-KLF13/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4356 0 ENCFF109FPX /home/drk/tillage/datasets/human/chip/encode/ENCSR948KMB/summary/ENCFF109FPX.w5 32 2 mean CHIP:PTBP1:K562 CHIP ChIP-TF:PTBP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4357 0 ENCFF058NFI /home/drk/tillage/datasets/human/chip/encode/ENCSR948QLZ/summary/ENCFF058NFI.w5 32 2 mean CHIP:CBX1:K562 CHIP ChIP-TF:CBX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4358 0 ENCFF741DZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR948VFL/summary/ENCFF741DZJ.w5 32 2 mean CHIP:IKZF1:K562 CHIP ChIP-TF:IKZF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4359 0 ENCFF360XRD /home/drk/tillage/datasets/human/chip/encode/ENCSR948YYZ/summary/ENCFF360XRD.w5 32 2 mean CHIP:H3K27ac:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K27ac/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4360 0 ENCFF196AMW /home/drk/tillage/datasets/human/chip/encode/ENCSR949HMJ/summary/ENCFF196AMW.w5 32 2 mean CHIP:H3K27me3:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K27me3/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4361 0 ENCFF071RAX /home/drk/tillage/datasets/human/chip/encode/ENCSR949IWY/summary/ENCFF071RAX.w5 32 2 mean CHIP:PAX8:MCF-7 CHIP ChIP-TF:PAX8/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4362 0 ENCFF177SPZ /home/drk/tillage/datasets/human/chip/encode/ENCSR949NVY/summary/ENCFF177SPZ.w5 32 2 mean CHIP:ZNF639:K562 CHIP ChIP-TF:ZNF639/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4363 0 ENCFF639BRW /home/drk/tillage/datasets/human/chip/encode/ENCSR949OYZ/summary/ENCFF639BRW.w5 32 2 mean CHIP:H3K4me3:psoas muscle male adult (34 years) CHIP ChIP-Histone:H3K4me3/psoas muscle male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4364 0 ENCFF865KVU /home/drk/tillage/datasets/human/chip/encode/ENCSR950ACO/summary/ENCFF865KVU.w5 32 2 mean CHIP:eGFP-ZNF785:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF785/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4365 0 ENCFF233LVU /home/drk/tillage/datasets/human/chip/encode/ENCSR950CUQ/summary/ENCFF233LVU.w5 32 2 mean CHIP:POLR2AphosphoS5:spleen male adult (37 years) CHIP ChIP-TF:POLR2AphosphoS5/spleen male adult (37 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4366 0 ENCFF952IJH /home/drk/tillage/datasets/human/chip/encode/ENCSR950NAZ/summary/ENCFF952IJH.w5 32 2 mean CHIP:LCORL:HepG2 CHIP ChIP-TF:LCORL/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4367 0 ENCFF344PHI /home/drk/tillage/datasets/human/chip/encode/ENCSR952EID/summary/ENCFF344PHI.w5 32 2 mean CHIP:H3K27me3:thymus male child (3 years) CHIP ChIP-Histone:H3K27me3/thymus male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4368 0 ENCFF978MIP /home/drk/tillage/datasets/human/chip/encode/ENCSR952GVX/summary/ENCFF978MIP.w5 32 2 mean CHIP:H3K9ac:H1-hESC CHIP ChIP-Histone:H3K9ac/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4369 0 ENCFF690TMV /home/drk/tillage/datasets/human/chip/encode/ENCSR953DVM/summary/ENCFF690TMV.w5 32 2 mean CHIP:E2F8:K562 CHIP ChIP-TF:E2F8/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4370 0 ENCFF557FOT /home/drk/tillage/datasets/human/chip/encode/ENCSR953GFW/summary/ENCFF557FOT.w5 32 2 mean CHIP:H3K4me3:rectal smooth muscle tissue female adult (50 years) CHIP ChIP-Histone:H3K4me3/rectal smooth muscle tissue female adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4371 0 ENCFF804FZZ /home/drk/tillage/datasets/human/chip/encode/ENCSR953HJN/summary/ENCFF804FZZ.w5 32 2 mean CHIP:H3K9me3:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K9me3/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4372 0 ENCFF193GYL /home/drk/tillage/datasets/human/chip/encode/ENCSR953ULK/summary/ENCFF193GYL.w5 32 2 mean CHIP:H3K36me3:fibroblast of breast female adult (26 years) CHIP ChIP-Histone:H3K36me3/fibroblast of breast female adult (26 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4373 0 ENCFF127KLE /home/drk/tillage/datasets/human/chip/encode/ENCSR953XVZ/summary/ENCFF127KLE.w5 32 2 mean CHIP:H3K4me1:lung female embryo (85 days) CHIP ChIP-Histone:H3K4me1/lung female embryo (85 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4374 0 ENCFF656USH /home/drk/tillage/datasets/human/chip/encode/ENCSR954KIC/summary/ENCFF656USH.w5 32 2 mean CHIP:3xFLAG-KAT8:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-KAT8/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4375 0 ENCFF618HBD /home/drk/tillage/datasets/human/chip/encode/ENCSR954WVZ/summary/ENCFF618HBD.w5 32 2 mean CHIP:ESRRA:MCF-7 CHIP ChIP-TF:ESRRA/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4376 0 ENCFF608EMH /home/drk/tillage/datasets/human/chip/encode/ENCSR954ZUG/summary/ENCFF608EMH.w5 32 2 mean CHIP:H3K27me3:muscle of leg female embryo (110 days) CHIP ChIP-Histone:H3K27me3/muscle of leg female embryo (110 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4377 0 ENCFF698JTY /home/drk/tillage/datasets/human/chip/encode/ENCSR955BIB/summary/ENCFF698JTY.w5 32 2 mean CHIP:CTCF:thyroid gland female adult (51 year) CHIP ChIP-TF:CTCF/thyroid gland female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4378 0 ENCFF869JLM /home/drk/tillage/datasets/human/chip/encode/ENCSR955IXZ/summary/ENCFF869JLM.w5 32 2 mean CHIP:H3K27ac:KMS-11 CHIP ChIP-Histone:H3K27ac/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4379 0 ENCFF390UVG /home/drk/tillage/datasets/human/chip/encode/ENCSR955OBN/summary/ENCFF390UVG.w5 32 2 mean CHIP:H3K27me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K27me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4380 0 ENCFF210SFK /home/drk/tillage/datasets/human/chip/encode/ENCSR955XFL/summary/ENCFF210SFK.w5 32 2 mean CHIP:H3K27ac:trophoblast female embryo (40 weeks) CHIP ChIP-Histone:H3K27ac/trophoblast female embryo (40 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4381 0 ENCFF366FNG /home/drk/tillage/datasets/human/chip/encode/ENCSR956CFX/summary/ENCFF366FNG.w5 32 2 mean CHIP:H3K4me3:layer of hippocampus male adult (81 year) CHIP ChIP-Histone:H3K4me3/layer of hippocampus male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4382 0 ENCFF015ZVX /home/drk/tillage/datasets/human/chip/encode/ENCSR956CTX/summary/ENCFF015ZVX.w5 32 2 mean CHIP:H3K4me3:neural stem progenitor cell originated from H1-hESC CHIP ChIP-Histone:H3K4me3/neural stem progenitor cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4383 0 ENCFF920TVY /home/drk/tillage/datasets/human/chip/encode/ENCSR956UFV/summary/ENCFF920TVY.w5 32 2 mean CHIP:H3K9me3:ovary female adult (30 years) CHIP ChIP-Histone:H3K9me3/ovary female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4384 0 ENCFF432XVD /home/drk/tillage/datasets/human/chip/encode/ENCSR957BPJ/summary/ENCFF432XVD.w5 32 2 mean CHIP:H3K4me3:aorta male adult (34 years) CHIP ChIP-Histone:H3K4me3/aorta male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4385 0 ENCFF216VSW /home/drk/tillage/datasets/human/chip/encode/ENCSR957CQH/summary/ENCFF216VSW.w5 32 2 mean CHIP:H3K79me2:OCI-LY3 CHIP ChIP-Histone:H3K79me2/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4386 0 ENCFF234XSH /home/drk/tillage/datasets/human/chip/encode/ENCSR957CYJ/summary/ENCFF234XSH.w5 32 2 mean CHIP:H3K4me3:neurosphere female embryo (17 weeks) originated from cortex CHIP ChIP-Histone:H3K4me3/neurosphere female embryo (17 weeks) originated from cortex ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4387 0 ENCFF918AWV /home/drk/tillage/datasets/human/chip/encode/ENCSR957GYL/summary/ENCFF918AWV.w5 32 2 mean CHIP:H3T11ph:H9 CHIP ChIP-Histone:H3T11ph/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4388 0 ENCFF005JHG /home/drk/tillage/datasets/human/chip/encode/ENCSR957KYB/summary/ENCFF005JHG.w5 32 2 mean CHIP:BHLHE40:IMR-90 CHIP ChIP-TF:BHLHE40/IMR-90 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4389 0 ENCFF792FZX /home/drk/tillage/datasets/human/chip/encode/ENCSR957LDM/summary/ENCFF792FZX.w5 32 2 mean CHIP:TRIM24:K562 CHIP ChIP-TF:TRIM24/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4390 0 ENCFF712OZC /home/drk/tillage/datasets/human/chip/encode/ENCSR957TGI/summary/ENCFF712OZC.w5 32 2 mean CHIP:H3K9me3:chorionic villus male embryo (38 weeks) CHIP ChIP-Histone:H3K9me3/chorionic villus male embryo (38 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4391 0 ENCFF340VVU /home/drk/tillage/datasets/human/chip/encode/ENCSR957UQS/summary/ENCFF340VVU.w5 32 2 mean CHIP:H3K4me3:endocrine pancreas male adult (45 years) CHIP ChIP-Histone:H3K4me3/endocrine pancreas male adult (45 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4392 0 ENCFF124CKS /home/drk/tillage/datasets/human/chip/encode/ENCSR957WQX/summary/ENCFF124CKS.w5 32 2 mean CHIP:H3K9me3:common myeloid progenitor, CD34-positive female adult (33 years) CHIP ChIP-Histone:H3K9me3/common myeloid progenitor, CD34-positive female adult (33 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4393 0 ENCFF704LYJ /home/drk/tillage/datasets/human/chip/encode/ENCSR957XEV/summary/ENCFF704LYJ.w5 32 2 mean CHIP:H3K4me3:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K4me3/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4394 0 ENCFF659QSC /home/drk/tillage/datasets/human/chip/encode/ENCSR958DEW/summary/ENCFF659QSC.w5 32 2 mean CHIP:H3K36me3:small intestine male child (3 years) CHIP ChIP-Histone:H3K36me3/small intestine male child (3 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4395 0 ENCFF723MZN /home/drk/tillage/datasets/human/chip/encode/ENCSR958WOY/summary/ENCFF723MZN.w5 32 2 mean CHIP:H3K9ac:H7-hESC CHIP ChIP-Histone:H3K9ac/H7-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4396 0 ENCFF232MPP /home/drk/tillage/datasets/human/chip/encode/ENCSR958ZMM/summary/ENCFF232MPP.w5 32 2 mean CHIP:H4K20me1:neural cell CHIP ChIP-TF:H4K20me1/neural cell ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4397 0 ENCFF549MBZ /home/drk/tillage/datasets/human/chip/encode/ENCSR959OMS/summary/ENCFF549MBZ.w5 32 2 mean CHIP:3xFLAG-SAP130:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SAP130/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4398 0 ENCFF748RWG /home/drk/tillage/datasets/human/chip/encode/ENCSR959UQA/summary/ENCFF748RWG.w5 32 2 mean CHIP:POLR2AphosphoS5:spleen female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/spleen female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4399 0 ENCFF860HQU /home/drk/tillage/datasets/human/chip/encode/ENCSR960AIZ/summary/ENCFF860HQU.w5 32 2 mean CHIP:H3K36me3:chorion male embryo (16 weeks) CHIP ChIP-Histone:H3K36me3/chorion male embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4400 0 ENCFF535IIL /home/drk/tillage/datasets/human/chip/encode/ENCSR960CWQ/summary/ENCFF535IIL.w5 32 2 mean CHIP:H3K27me3:trophoblast cell originated from H1-hESC CHIP ChIP-Histone:H3K27me3/trophoblast cell originated from H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4401 0 ENCFF328OPT /home/drk/tillage/datasets/human/chip/encode/ENCSR960EVO/summary/ENCFF328OPT.w5 32 2 mean CHIP:H3K4me3:aorta female adult (30 years) CHIP ChIP-Histone:H3K4me3/aorta female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4402 0 ENCFF115DSH /home/drk/tillage/datasets/human/chip/encode/ENCSR960JPH/summary/ENCFF115DSH.w5 32 2 mean CHIP:H4K12ac:trophoblast cell originated from H1-hESC CHIP ChIP-TF:H4K12ac/trophoblast cell originated from H1-hESC ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4403 0 ENCFF142LSJ /home/drk/tillage/datasets/human/chip/encode/ENCSR960MDF/summary/ENCFF142LSJ.w5 32 2 mean CHIP:CTCF:ascending aorta female adult (51 year) CHIP ChIP-TF:CTCF/ascending aorta female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4404 0 ENCFF078MUI /home/drk/tillage/datasets/human/chip/encode/ENCSR960ZMM/summary/ENCFF078MUI.w5 32 2 mean CHIP:H4K20me1:OCI-LY1 CHIP ChIP-TF:H4K20me1/OCI-LY1 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4405 0 ENCFF472KMT /home/drk/tillage/datasets/human/chip/encode/ENCSR961PPA/summary/ENCFF472KMT.w5 32 2 mean CHIP:ATF2:GM12878 CHIP ChIP-TF:ATF2/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4406 0 ENCFF895QBI /home/drk/tillage/datasets/human/chip/encode/ENCSR961WLZ/summary/ENCFF895QBI.w5 32 2 mean CHIP:3xFLAG-SOX5:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-SOX5/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4407 0 ENCFF489LFC /home/drk/tillage/datasets/human/chip/encode/ENCSR962AKF/summary/ENCFF489LFC.w5 32 2 mean CHIP:H3K4me3:CD8-positive, alpha-beta memory T cell CHIP ChIP-Histone:H3K4me3/CD8-positive, alpha-beta memory T cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4408 0 ENCFF908NRK /home/drk/tillage/datasets/human/chip/encode/ENCSR962MYX/summary/ENCFF908NRK.w5 32 2 mean CHIP:H3K36me3:vagina female adult (53 years) CHIP ChIP-Histone:H3K36me3/vagina female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4409 0 ENCFF781RAH /home/drk/tillage/datasets/human/chip/encode/ENCSR963HAR/summary/ENCFF781RAH.w5 32 2 mean CHIP:H3K27me3:Karpas-422 CHIP ChIP-Histone:H3K27me3/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4410 0 ENCFF970ISL /home/drk/tillage/datasets/human/chip/encode/ENCSR963LVX/summary/ENCFF970ISL.w5 32 2 mean CHIP:H3K27ac:chorionic villus embryo (16 weeks) CHIP ChIP-Histone:H3K27ac/chorionic villus embryo (16 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4411 0 ENCFF076XUR /home/drk/tillage/datasets/human/chip/encode/ENCSR963TKB/summary/ENCFF076XUR.w5 32 2 mean CHIP:H3K4me1:natural killer cell male adult (21 year) CHIP ChIP-Histone:H3K4me1/natural killer cell male adult (21 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4412 0 ENCFF344WUU /home/drk/tillage/datasets/human/chip/encode/ENCSR964BKO/summary/ENCFF344WUU.w5 32 2 mean CHIP:CTCF:upper lobe of left lung male adult (54 years) CHIP ChIP-TF:CTCF/upper lobe of left lung male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4413 0 ENCFF520JQX /home/drk/tillage/datasets/human/chip/encode/ENCSR966HBM/summary/ENCFF520JQX.w5 32 2 mean CHIP:H3F3A:DOHH2 CHIP ChIP-Histone:H3F3A/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4414 0 ENCFF031EAG /home/drk/tillage/datasets/human/chip/encode/ENCSR966PJJ/summary/ENCFF031EAG.w5 32 2 mean CHIP:eGFP-WT1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-WT1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4415 0 ENCFF485OQI /home/drk/tillage/datasets/human/chip/encode/ENCSR966PJY/summary/ENCFF485OQI.w5 32 2 mean CHIP:3xFLAG-MIXL1:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-MIXL1/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4416 0 ENCFF706HRP /home/drk/tillage/datasets/human/chip/encode/ENCSR966QUX/summary/ENCFF706HRP.w5 32 2 mean CHIP:H3K4me3:regulatory T cell originated from blood cell CHIP ChIP-Histone:H3K4me3/regulatory T cell originated from blood cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4417 0 ENCFF368RZP /home/drk/tillage/datasets/human/chip/encode/ENCSR966ULI/summary/ENCFF368RZP.w5 32 2 mean CHIP:eGFP-PATZ1:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-PATZ1/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4418 0 ENCFF134YVM /home/drk/tillage/datasets/human/chip/encode/ENCSR966YYJ/summary/ENCFF134YVM.w5 32 2 mean CHIP:BMI1:MCF-7 CHIP ChIP-TF:BMI1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4419 0 ENCFF290DMA /home/drk/tillage/datasets/human/chip/encode/ENCSR967HXD/summary/ENCFF290DMA.w5 32 2 mean CHIP:H3K4me1:H9 genetically modified using stable transfection CHIP ChIP-Histone:H3K4me1/H9 genetically modified using stable transfection ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4420 0 ENCFF754NUD /home/drk/tillage/datasets/human/chip/encode/ENCSR967KZJ/summary/ENCFF754NUD.w5 32 2 mean CHIP:H3K36me3:right atrium auricular region female adult (53 years) CHIP ChIP-Histone:H3K36me3/right atrium auricular region female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4421 0 ENCFF825MVK /home/drk/tillage/datasets/human/chip/encode/ENCSR968GIB/summary/ENCFF825MVK.w5 32 2 mean CHIP:RFX1:K562 CHIP ChIP-TF:RFX1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4422 0 ENCFF894IOS /home/drk/tillage/datasets/human/chip/encode/ENCSR968QDP/summary/ENCFF894IOS.w5 32 2 mean CHIP:SMARCE1:HepG2 CHIP ChIP-TF:SMARCE1/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4423 0 ENCFF422ZNS /home/drk/tillage/datasets/human/chip/encode/ENCSR969DAF/summary/ENCFF422ZNS.w5 32 2 mean CHIP:H3K9ac:peripheral blood mononuclear cell male adult (27 years) CHIP ChIP-Histone:H3K9ac/peripheral blood mononuclear cell male adult (27 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4424 0 ENCFF138LAA /home/drk/tillage/datasets/human/chip/encode/ENCSR970FPM/summary/ENCFF138LAA.w5 32 2 mean CHIP:H3K4me3:keratinocyte female CHIP ChIP-Histone:H3K4me3/keratinocyte female ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4425 0 ENCFF814GLP /home/drk/tillage/datasets/human/chip/encode/ENCSR970NKQ/summary/ENCFF814GLP.w5 32 2 mean CHIP:NR2F1:K562 CHIP ChIP-TF:NR2F1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4426 0 ENCFF645MYR /home/drk/tillage/datasets/human/chip/encode/ENCSR970UZD/summary/ENCFF645MYR.w5 32 2 mean CHIP:CTCF:upper lobe of left lung female adult (53 years) CHIP ChIP-TF:CTCF/upper lobe of left lung female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4427 0 ENCFF175PZL /home/drk/tillage/datasets/human/chip/encode/ENCSR971ETA/summary/ENCFF175PZL.w5 32 2 mean CHIP:H3K27ac:stomach smooth muscle female adult (84 years) CHIP ChIP-Histone:H3K27ac/stomach smooth muscle female adult (84 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4428 0 ENCFF068SDD /home/drk/tillage/datasets/human/chip/encode/ENCSR971QHH/summary/ENCFF068SDD.w5 32 2 mean CHIP:H3K4me1:CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K4me1/CD4-positive, alpha-beta T cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4429 0 ENCFF135XRF /home/drk/tillage/datasets/human/chip/encode/ENCSR972ETR/summary/ENCFF135XRF.w5 32 2 mean CHIP:H3K4me3:gastrocnemius medialis male adult (54 years) CHIP ChIP-Histone:H3K4me3/gastrocnemius medialis male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4430 0 ENCFF283YML /home/drk/tillage/datasets/human/chip/encode/ENCSR972LYL/summary/ENCFF283YML.w5 32 2 mean CHIP:CTCF:upper lobe of left lung female adult (51 year) CHIP ChIP-TF:CTCF/upper lobe of left lung female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4431 0 ENCFF662IZN /home/drk/tillage/datasets/human/chip/encode/ENCSR972NUZ/summary/ENCFF662IZN.w5 32 2 mean CHIP:H3K4me1:foreskin melanocyte male newborn CHIP ChIP-Histone:H3K4me1/foreskin melanocyte male newborn ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4432 0 ENCFF278YAD /home/drk/tillage/datasets/human/chip/encode/ENCSR972RKX/summary/ENCFF278YAD.w5 32 2 mean CHIP:H3K27me3:right cardiac atrium male adult (34 years) CHIP ChIP-Histone:H3K27me3/right cardiac atrium male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4433 0 ENCFF078OIB /home/drk/tillage/datasets/human/chip/encode/ENCSR972SMV/summary/ENCFF078OIB.w5 32 2 mean CHIP:H3K9me3:H9 CHIP ChIP-Histone:H3K9me3/H9 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4434 0 ENCFF204NFC /home/drk/tillage/datasets/human/chip/encode/ENCSR972ZBV/summary/ENCFF204NFC.w5 32 2 mean CHIP:ATF7:K562 CHIP ChIP-TF:ATF7/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4435 0 ENCFF599QVB /home/drk/tillage/datasets/human/chip/encode/ENCSR974EGY/summary/ENCFF599QVB.w5 32 2 mean CHIP:H3K9me3:T-cell CHIP ChIP-Histone:H3K9me3/T-cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4436 0 ENCFF946YRI /home/drk/tillage/datasets/human/chip/encode/ENCSR974HQI/summary/ENCFF946YRI.w5 32 2 mean CHIP:POLR2A:transverse colon female adult (51 year) CHIP ChIP-TF:POLR2A/transverse colon female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4437 0 ENCFF217RFD /home/drk/tillage/datasets/human/chip/encode/ENCSR974OFJ/summary/ENCFF217RFD.w5 32 2 mean CHIP:KLF5:GM12878 CHIP ChIP-TF:KLF5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4438 0 ENCFF644PXV /home/drk/tillage/datasets/human/chip/encode/ENCSR974OMC/summary/ENCFF644PXV.w5 32 2 mean CHIP:H3K9me3:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K9me3/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4439 0 ENCFF208OZM /home/drk/tillage/datasets/human/chip/encode/ENCSR975GZA/summary/ENCFF208OZM.w5 32 2 mean CHIP:H3K4me3:SK-N-SH CHIP ChIP-Histone:H3K4me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4440 0 ENCFF916BKG /home/drk/tillage/datasets/human/chip/encode/ENCSR975NOU/summary/ENCFF916BKG.w5 32 2 mean CHIP:H3K4me3:thyroid gland male adult (54 years) CHIP ChIP-Histone:H3K4me3/thyroid gland male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4441 0 ENCFF609BNY /home/drk/tillage/datasets/human/chip/encode/ENCSR975QNR/summary/ENCFF609BNY.w5 32 2 mean CHIP:EP300:vagina female adult (51 year) CHIP ChIP-TF:EP300/vagina female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4442 0 ENCFF256DOK /home/drk/tillage/datasets/human/chip/encode/ENCSR975RSD/summary/ENCFF256DOK.w5 32 2 mean CHIP:H3K9me3:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K9me3/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4443 0 ENCFF223LQK /home/drk/tillage/datasets/human/chip/encode/ENCSR975SSR/summary/ENCFF223LQK.w5 32 2 mean CHIP:eGFP-ELF1:K562 genetically modified using stable transfection CHIP ChIP-TF:eGFP-ELF1/K562 genetically modified using stable transfection ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4444 0 ENCFF208OVP /home/drk/tillage/datasets/human/chip/encode/ENCSR976JHS/summary/ENCFF208OVP.w5 32 2 mean CHIP:H3K4me1:KMS-11 CHIP ChIP-Histone:H3K4me1/KMS-11 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4445 0 ENCFF398JJK /home/drk/tillage/datasets/human/chip/encode/ENCSR976TBC/summary/ENCFF398JJK.w5 32 2 mean CHIP:IRF5:GM12878 CHIP ChIP-TF:IRF5/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4446 0 ENCFF743IOZ /home/drk/tillage/datasets/human/chip/encode/ENCSR977CEC/summary/ENCFF743IOZ.w5 32 2 mean CHIP:H3K27me3:body of pancreas male adult (37 years) CHIP ChIP-Histone:H3K27me3/body of pancreas male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4447 0 ENCFF163JON /home/drk/tillage/datasets/human/chip/encode/ENCSR977HTH/summary/ENCFF163JON.w5 32 2 mean CHIP:eGFP-ZNF18:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF18/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4448 0 ENCFF759QZV /home/drk/tillage/datasets/human/chip/encode/ENCSR977TKR/summary/ENCFF759QZV.w5 32 2 mean CHIP:H3K4me1:placenta female embryo (113 days) CHIP ChIP-Histone:H3K4me1/placenta female embryo (113 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4449 0 ENCFF504CGA /home/drk/tillage/datasets/human/chip/encode/ENCSR978BQI/summary/ENCFF504CGA.w5 32 2 mean CHIP:H3K9me3:Karpas-422 CHIP ChIP-Histone:H3K9me3/Karpas-422 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4450 0 ENCFF681BMN /home/drk/tillage/datasets/human/chip/encode/ENCSR978CNH/summary/ENCFF681BMN.w5 32 2 mean CHIP:H3K36me3:SK-N-SH CHIP ChIP-Histone:H3K36me3/SK-N-SH ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4451 0 ENCFF100PJN /home/drk/tillage/datasets/human/chip/encode/ENCSR978EQY/summary/ENCFF100PJN.w5 32 2 mean CHIP:eGFP-GLI2:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-GLI2/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4452 0 ENCFF547PHI /home/drk/tillage/datasets/human/chip/encode/ENCSR978LQC/summary/ENCFF547PHI.w5 32 2 mean CHIP:POLR2AphosphoS5:sigmoid colon male adult (54 years) CHIP ChIP-TF:POLR2AphosphoS5/sigmoid colon male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4453 0 ENCFF971EVG /home/drk/tillage/datasets/human/chip/encode/ENCSR979DMN/summary/ENCFF971EVG.w5 32 2 mean CHIP:POLR2A:body of pancreas female adult (53 years) CHIP ChIP-TF:POLR2A/body of pancreas female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4454 0 ENCFF845CAW /home/drk/tillage/datasets/human/chip/encode/ENCSR979FQP/summary/ENCFF845CAW.w5 32 2 mean CHIP:GATAD2B:MCF-7 CHIP ChIP-TF:GATAD2B/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4455 0 ENCFF665LAS /home/drk/tillage/datasets/human/chip/encode/ENCSR979QYJ/summary/ENCFF665LAS.w5 32 2 mean CHIP:MNT:K562 CHIP ChIP-TF:MNT/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4456 0 ENCFF810OZJ /home/drk/tillage/datasets/human/chip/encode/ENCSR979RHZ/summary/ENCFF810OZJ.w5 32 2 mean CHIP:H3K9me3:common myeloid progenitor, CD34-positive CHIP ChIP-Histone:H3K9me3/common myeloid progenitor, CD34-positive ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4457 0 ENCFF733OJY /home/drk/tillage/datasets/human/chip/encode/ENCSR979TIC/summary/ENCFF733OJY.w5 32 2 mean CHIP:H3K9me3:iPS-18a female adult (48 years) CHIP ChIP-Histone:H3K9me3/iPS-18a female adult (48 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4458 0 ENCFF225KVV /home/drk/tillage/datasets/human/chip/encode/ENCSR980OPB/summary/ENCFF225KVV.w5 32 2 mean CHIP:EP300:subcutaneous adipose tissue male adult (54 years) CHIP ChIP-TF:EP300/subcutaneous adipose tissue male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4459 0 ENCFF075HSB /home/drk/tillage/datasets/human/chip/encode/ENCSR980XMX/summary/ENCFF075HSB.w5 32 2 mean CHIP:H3K9me3:peripheral blood mononuclear cell male adult (32 years) CHIP ChIP-Histone:H3K9me3/peripheral blood mononuclear cell male adult (32 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4460 0 ENCFF343ULH /home/drk/tillage/datasets/human/chip/encode/ENCSR981CID/summary/ENCFF343ULH.w5 32 2 mean CHIP:CTCF:testis male adult (54 years) CHIP ChIP-TF:CTCF/testis male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4461 0 ENCFF035NGT /home/drk/tillage/datasets/human/chip/encode/ENCSR981UJA/summary/ENCFF035NGT.w5 32 2 mean CHIP:H3K27ac:right lobe of liver female adult (53 years) CHIP ChIP-Histone:H3K27ac/right lobe of liver female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4462 0 ENCFF034ZLM /home/drk/tillage/datasets/human/chip/encode/ENCSR982PLJ/summary/ENCFF034ZLM.w5 32 2 mean CHIP:H3K27me3:Peyer's patch female adult (53 years) CHIP ChIP-Histone:H3K27me3/Peyer's patch female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4463 0 ENCFF109PKU /home/drk/tillage/datasets/human/chip/encode/ENCSR982QIF/summary/ENCFF109PKU.w5 32 2 mean CHIP:H3K27ac:ascending aorta female adult (51 year) CHIP ChIP-Histone:H3K27ac/ascending aorta female adult (51 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4464 0 ENCFF897UZP /home/drk/tillage/datasets/human/chip/encode/ENCSR983CSB/summary/ENCFF897UZP.w5 32 2 mean CHIP:H2AFZ:bipolar neuron originated from GM23338 treated with 0.5 ug/mL doxycycline hyclate for 4 days CHIP "ChIP-TF:H2AFZ/bipolar neuron originated from GM23338 treated with 0.5 ug;mL doxycycline hyclate for 4 days" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4465 0 ENCFF647ASU /home/drk/tillage/datasets/human/chip/encode/ENCSR983SZL/summary/ENCFF647ASU.w5 32 2 mean CHIP:EP300:subcutaneous adipose tissue female adult (51 year) CHIP ChIP-TF:EP300/subcutaneous adipose tissue female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4466 0 ENCFF715CEI /home/drk/tillage/datasets/human/chip/encode/ENCSR984KWT/summary/ENCFF715CEI.w5 32 2 mean CHIP:H3K4me3:thoracic aorta male adult (37 years) CHIP ChIP-Histone:H3K4me3/thoracic aorta male adult (37 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4467 0 ENCFF047UXI /home/drk/tillage/datasets/human/chip/encode/ENCSR984MDV/summary/ENCFF047UXI.w5 32 2 mean CHIP:eGFP-ZNF24:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF24/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4468 0 ENCFF174QFD /home/drk/tillage/datasets/human/chip/encode/ENCSR984UHU/summary/ENCFF174QFD.w5 32 2 mean CHIP:H3K4me1:pancreas female adult (30 years) CHIP ChIP-Histone:H3K4me1/pancreas female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4469 0 ENCFF797IUA /home/drk/tillage/datasets/human/chip/encode/ENCSR985MIB/summary/ENCFF797IUA.w5 32 2 mean CHIP:H3K4me3:MCF-7 CHIP ChIP-Histone:H3K4me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4470 0 ENCFF939EUV /home/drk/tillage/datasets/human/chip/encode/ENCSR985MYI/summary/ENCFF939EUV.w5 32 2 mean CHIP:eGFP-ZNF114:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF114/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4471 0 ENCFF189CHX /home/drk/tillage/datasets/human/chip/encode/ENCSR986CDX/summary/ENCFF189CHX.w5 32 2 mean CHIP:NEUROD1:K562 CHIP ChIP-TF:NEUROD1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4472 0 ENCFF168MBT /home/drk/tillage/datasets/human/chip/encode/ENCSR986QAR/summary/ENCFF168MBT.w5 32 2 mean CHIP:POLR2AphosphoS5:upper lobe of left lung female adult (53 years) CHIP ChIP-TF:POLR2AphosphoS5/upper lobe of left lung female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4473 0 ENCFF284DOO /home/drk/tillage/datasets/human/chip/encode/ENCSR986XYK/summary/ENCFF284DOO.w5 32 2 mean CHIP:PKNOX1:MCF-7 CHIP ChIP-TF:PKNOX1/MCF-7 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4474 0 ENCFF031SGA /home/drk/tillage/datasets/human/chip/encode/ENCSR987GXT/summary/ENCFF031SGA.w5 32 2 mean CHIP:CTCF:GM23338 male adult (53 years) originated from GM23248 CHIP ChIP-TF:CTCF/GM23338 male adult (53 years) originated from GM23248 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4475 0 ENCFF402ZMX /home/drk/tillage/datasets/human/chip/encode/ENCSR987MTA/summary/ENCFF402ZMX.w5 32 2 mean CHIP:BHLHE40:GM12878 CHIP ChIP-TF:BHLHE40/GM12878 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4476 0 ENCFF992NLQ /home/drk/tillage/datasets/human/chip/encode/ENCSR987PBI/summary/ENCFF992NLQ.w5 32 2 mean CHIP:DNMT1:K562 CHIP ChIP-TF:DNMT1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4477 0 ENCFF459NZD /home/drk/tillage/datasets/human/chip/encode/ENCSR987PNT/summary/ENCFF459NZD.w5 32 2 mean CHIP:H3K27ac:RWPE2 CHIP ChIP-Histone:H3K27ac/RWPE2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4478 0 ENCFF703NUB /home/drk/tillage/datasets/human/chip/encode/ENCSR988DFT/summary/ENCFF703NUB.w5 32 2 mean CHIP:H3K36me3:thoracic aorta male adult (54 years) CHIP ChIP-Histone:H3K36me3/thoracic aorta male adult (54 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4479 0 ENCFF970YJR /home/drk/tillage/datasets/human/chip/encode/ENCSR988EGR/summary/ENCFF970YJR.w5 32 2 mean CHIP:H3K9me3:A673 CHIP ChIP-Histone:H3K9me3/A673 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4480 0 ENCFF403ATC /home/drk/tillage/datasets/human/chip/encode/ENCSR988JLN/summary/ENCFF403ATC.w5 32 2 mean CHIP:H3K27me3:heart left ventricle female adult (53 years) CHIP ChIP-Histone:H3K27me3/heart left ventricle female adult (53 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4481 0 ENCFF971IZU /home/drk/tillage/datasets/human/chip/encode/ENCSR988LZG/summary/ENCFF971IZU.w5 32 2 mean CHIP:3xFLAG-ARID4B:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-ARID4B/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4482 0 ENCFF597CWQ /home/drk/tillage/datasets/human/chip/encode/ENCSR988ZSI/summary/ENCFF597CWQ.w5 32 2 mean CHIP:3xFLAG-RERE:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-RERE/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4483 0 ENCFF281FXG /home/drk/tillage/datasets/human/chip/encode/ENCSR989AMI/summary/ENCFF281FXG.w5 32 2 mean CHIP:H3K36me3:aorta female adult (30 years) CHIP ChIP-Histone:H3K36me3/aorta female adult (30 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4484 0 ENCFF774HMD /home/drk/tillage/datasets/human/chip/encode/ENCSR989POD/summary/ENCFF774HMD.w5 32 2 mean CHIP:H3K36me3:subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) CHIP ChIP-Histone:H3K36me3/subcutaneous abdominal adipose tissue nuclear fraction female adult (49 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4485 0 ENCFF483DAZ /home/drk/tillage/datasets/human/chip/encode/ENCSR989RAL/summary/ENCFF483DAZ.w5 32 2 mean CHIP:H3K4me3:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K4me3/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4486 0 ENCFF419BHQ /home/drk/tillage/datasets/human/chip/encode/ENCSR990AZC/summary/ENCFF419BHQ.w5 32 2 mean CHIP:MCM3:K562 CHIP ChIP-TF:MCM3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4487 0 ENCFF837KEU /home/drk/tillage/datasets/human/chip/encode/ENCSR991ADX/summary/ENCFF837KEU.w5 32 2 mean CHIP:U2AF2:HepG2 CHIP ChIP-TF:U2AF2/HepG2 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4488 0 ENCFF936LEU /home/drk/tillage/datasets/human/chip/encode/ENCSR991BTY/summary/ENCFF936LEU.w5 32 2 mean CHIP:H3K4me1:H1-hESC CHIP ChIP-Histone:H3K4me1/H1-hESC ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4489 0 ENCFF949TXJ /home/drk/tillage/datasets/human/chip/encode/ENCSR991ELG/summary/ENCFF949TXJ.w5 32 2 mean CHIP:SP1:K562 CHIP ChIP-TF:SP1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4490 0 ENCFF516HCH /home/drk/tillage/datasets/human/chip/encode/ENCSR992DEK/summary/ENCFF516HCH.w5 32 2 mean CHIP:H3K9me3:middle frontal area 46 male adult (81 year) CHIP ChIP-Histone:H3K9me3/middle frontal area 46 male adult (81 year) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4491 0 ENCFF241YPG /home/drk/tillage/datasets/human/chip/encode/ENCSR992ODD/summary/ENCFF241YPG.w5 32 2 mean CHIP:H3K36me3:peripheral blood mononuclear cell female adult (28 years) CHIP ChIP-Histone:H3K36me3/peripheral blood mononuclear cell female adult (28 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4492 0 ENCFF121VYW /home/drk/tillage/datasets/human/chip/encode/ENCSR992VZG/summary/ENCFF121VYW.w5 32 2 mean CHIP:H3K9me3:adrenal gland male adult (34 years) CHIP ChIP-Histone:H3K9me3/adrenal gland male adult (34 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4493 0 ENCFF130TQV /home/drk/tillage/datasets/human/chip/encode/ENCSR992YSL/summary/ENCFF130TQV.w5 32 2 mean CHIP:H3K4me2:DOHH2 CHIP ChIP-Histone:H3K4me2/DOHH2 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4494 0 ENCFF122KXG /home/drk/tillage/datasets/human/chip/encode/ENCSR993DED/summary/ENCFF122KXG.w5 32 2 mean CHIP:eGFP-ZNF214:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF214/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4495 0 ENCFF397LLR /home/drk/tillage/datasets/human/chip/encode/ENCSR993LMB/summary/ENCFF397LLR.w5 32 2 mean CHIP:3xFLAG-TGIF2:HepG2 genetically modified using CRISPR CHIP ChIP-TF:3xFLAG-TGIF2/HepG2 genetically modified using CRISPR ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4496 0 ENCFF313QRX /home/drk/tillage/datasets/human/chip/encode/ENCSR994BPD/summary/ENCFF313QRX.w5 32 2 mean CHIP:H3K4me1:kidney male adult (50 years) CHIP ChIP-Histone:H3K4me1/kidney male adult (50 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4497 0 ENCFF366IXP /home/drk/tillage/datasets/human/chip/encode/ENCSR994NPK/summary/ENCFF366IXP.w5 32 2 mean CHIP:H3K36me3:cardiac muscle cell CHIP ChIP-Histone:H3K36me3/cardiac muscle cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4498 0 ENCFF152OQL /home/drk/tillage/datasets/human/chip/encode/ENCSR994YLZ/summary/ENCFF152OQL.w5 32 2 mean CHIP:YY1:liver female child (4 years) CHIP ChIP-TF:YY1/liver female child (4 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4499 0 ENCFF705MDH /home/drk/tillage/datasets/human/chip/encode/ENCSR995QNB/summary/ENCFF705MDH.w5 32 2 mean CHIP:POLR2A:Peyer's patch female adult (53 years) CHIP ChIP-TF:POLR2A/Peyer's patch female adult (53 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4500 0 ENCFF823ZDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR995UTR/summary/ENCFF823ZDZ.w5 32 2 mean CHIP:H3K36me3:skeletal muscle satellite cell female adult originated from mesodermal cell CHIP ChIP-Histone:H3K36me3/skeletal muscle satellite cell female adult originated from mesodermal cell ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4501 0 ENCFF114IVM /home/drk/tillage/datasets/human/chip/encode/ENCSR996DUT/summary/ENCFF114IVM.w5 32 2 mean CHIP:JUN:A549 CHIP ChIP-TF:JUN/A549 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4502 0 ENCFF810CDQ /home/drk/tillage/datasets/human/chip/encode/ENCSR996ENW/summary/ENCFF810CDQ.w5 32 2 mean CHIP:H3K36me3:substantia nigra female adult (75 years) CHIP ChIP-Histone:H3K36me3/substantia nigra female adult (75 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4503 0 ENCFF898OLL /home/drk/tillage/datasets/human/chip/encode/ENCSR996ESX/summary/ENCFF898OLL.w5 32 2 mean CHIP:NFRKB:K562 CHIP ChIP-TF:NFRKB/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4504 0 ENCFF784QYR /home/drk/tillage/datasets/human/chip/encode/ENCSR996FWI/summary/ENCFF784QYR.w5 32 2 mean CHIP:H3K4me1:iPS-20b male adult (55 years) CHIP ChIP-Histone:H3K4me1/iPS-20b male adult (55 years) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4505 0 ENCFF446PCG /home/drk/tillage/datasets/human/chip/encode/ENCSR996FYT/summary/ENCFF446PCG.w5 32 2 mean CHIP:eGFP-ZNF202:HEK293 genetically modified using site-specific recombination originated from HEK293 CHIP ChIP-TF:eGFP-ZNF202/HEK293 genetically modified using site-specific recombination originated from HEK293 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4506 0 ENCFF514YOV /home/drk/tillage/datasets/human/chip/encode/ENCSR996GHD/summary/ENCFF514YOV.w5 32 2 mean CHIP:H3K9ac:OCI-LY3 CHIP ChIP-Histone:H3K9ac/OCI-LY3 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4507 0 ENCFF194OBU /home/drk/tillage/datasets/human/chip/encode/ENCSR997GPO/summary/ENCFF194OBU.w5 32 2 mean CHIP:NFRKB:HEK293T CHIP ChIP-TF:NFRKB/HEK293T ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4508 0 ENCFF521HWT /home/drk/tillage/datasets/human/chip/encode/ENCSR997NGQ/summary/ENCFF521HWT.w5 32 2 mean CHIP:XRCC3:K562 CHIP ChIP-TF:XRCC3/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4509 0 ENCFF204VPY /home/drk/tillage/datasets/human/chip/encode/ENCSR997YTW/summary/ENCFF204VPY.w5 32 2 mean CHIP:H3K27me3:brain female embryo (17 weeks) CHIP ChIP-Histone:H3K27me3/brain female embryo (17 weeks) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4510 0 ENCFF271IWM /home/drk/tillage/datasets/human/chip/encode/ENCSR998AJK/summary/ENCFF271IWM.w5 32 2 mean CHIP:NRF1:K562 CHIP ChIP-TF:NRF1/K562 ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4511 0 ENCFF211PSD /home/drk/tillage/datasets/human/chip/encode/ENCSR998NQG/summary/ENCFF211PSD.w5 32 2 mean CHIP:CTCF:gastrocnemius medialis male adult (54 years) CHIP ChIP-TF:CTCF/gastrocnemius medialis male adult (54 years) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4512 0 ENCFF897WSR /home/drk/tillage/datasets/human/chip/encode/ENCSR998RVD/summary/ENCFF897WSR.w5 32 2 mean CHIP:H3K36me3:T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin CHIP ChIP-Histone:H3K36me3/T-helper 17 cell treated with phorbol 13-acetate 12-myristate , ionomycin ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4513 0 ENCFF177LLX /home/drk/tillage/datasets/human/chip/encode/ENCSR998ZWM/summary/ENCFF177LLX.w5 32 2 mean CHIP:H3K4me1:large intestine male embryo (108 days) CHIP ChIP-Histone:H3K4me1/large intestine male embryo (108 days) ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4514 0 ENCFF134ANM /home/drk/tillage/datasets/human/chip/encode/ENCSR999QVR/summary/ENCFF134ANM.w5 32 2 mean CHIP:POLR2A:uterus female adult (51 year) CHIP ChIP-TF:POLR2A/uterus female adult (51 year) ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4515 0 ENCFF191LDZ /home/drk/tillage/datasets/human/chip/encode/ENCSR999WHE/summary/ENCFF191LDZ.w5 32 2 mean CHIP:H3K9me3:MCF-7 CHIP ChIP-Histone:H3K9me3/MCF-7 ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4516 0 GSM1208590 /home/drk/tillage/datasets/human/chip/geo/GSM1208590/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ARNT_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ARNT_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4517 0 GSM1208591 /home/drk/tillage/datasets/human/chip/geo/GSM1208591/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ASCL2_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ASCL2_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4518 0 GSM1208592 /home/drk/tillage/datasets/human/chip/geo/GSM1208592/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ATOH1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ATOH1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4519 0 GSM1208593 /home/drk/tillage/datasets/human/chip/geo/GSM1208593/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_BARX2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_BARX2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4520 0 GSM1208594 /home/drk/tillage/datasets/human/chip/geo/GSM1208594/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_CAMTA2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_CAMTA2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4521 0 GSM1208595 /home/drk/tillage/datasets/human/chip/geo/GSM1208595/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_CASP8AP2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_CASP8AP2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4522 0 GSM1208598 /home/drk/tillage/datasets/human/chip/geo/GSM1208598/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_CEBPB_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_CEBPB_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4523 0 GSM1208599 /home/drk/tillage/datasets/human/chip/geo/GSM1208599/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_CEBPG_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_CEBPG_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4524 0 GSM1208603 /home/drk/tillage/datasets/human/chip/geo/GSM1208603/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_CTCF_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_CTCF_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4525 0 GSM1208605 /home/drk/tillage/datasets/human/chip/geo/GSM1208605/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_DBP_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_DBP_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4526 0 GSM1208606 /home/drk/tillage/datasets/human/chip/geo/GSM1208606/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_E2F2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_E2F2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4527 0 GSM1208607 /home/drk/tillage/datasets/human/chip/geo/GSM1208607/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_E2F4_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_E2F4_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4528 0 GSM1208608 /home/drk/tillage/datasets/human/chip/geo/GSM1208608/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_EGR1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_EGR1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4529 0 GSM1208609 /home/drk/tillage/datasets/human/chip/geo/GSM1208609/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_EHF_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_EHF_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4530 0 GSM1208610 /home/drk/tillage/datasets/human/chip/geo/GSM1208610/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ELF1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ELF1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4531 0 GSM1208611 /home/drk/tillage/datasets/human/chip/geo/GSM1208611/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_USF2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_USF2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4532 0 GSM1208615 /home/drk/tillage/datasets/human/chip/geo/GSM1208615/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ESRRA_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ESRRA_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4533 0 GSM1208616 /home/drk/tillage/datasets/human/chip/geo/GSM1208616/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ETV4_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ETV4_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4534 0 GSM1208620 /home/drk/tillage/datasets/human/chip/geo/GSM1208620/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_GATA4_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_GATA4_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4535 0 GSM1208621 /home/drk/tillage/datasets/human/chip/geo/GSM1208621/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_GATA6_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_GATA6_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4536 0 GSM1208622 /home/drk/tillage/datasets/human/chip/geo/GSM1208622/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_GLI2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_GLI2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4537 0 GSM1208625 /home/drk/tillage/datasets/human/chip/geo/GSM1208625/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_GMEB1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_GMEB1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4538 0 GSM1208626 /home/drk/tillage/datasets/human/chip/geo/GSM1208626/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_GMEB2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_GMEB2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4539 0 GSM1208627 /home/drk/tillage/datasets/human/chip/geo/GSM1208627/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HBP1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HBP1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4540 0 GSM1208629 /home/drk/tillage/datasets/human/chip/geo/GSM1208629/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HES2_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HES2_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4541 0 GSM1208630 /home/drk/tillage/datasets/human/chip/geo/GSM1208630/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HES4_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HES4_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4542 0 GSM1208631 /home/drk/tillage/datasets/human/chip/geo/GSM1208631/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HINFP_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HINFP_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4543 0 GSM1208632 /home/drk/tillage/datasets/human/chip/geo/GSM1208632/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HNF4A_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HNF4A_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4544 0 GSM1208633 /home/drk/tillage/datasets/human/chip/geo/GSM1208633/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HOXA10_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HOXA10_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4545 0 GSM1208634 /home/drk/tillage/datasets/human/chip/geo/GSM1208634/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HOXA1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HOXA1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4546 0 GSM1208635 /home/drk/tillage/datasets/human/chip/geo/GSM1208635/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_HOXA7_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_HOXA7_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4547 0 GSM1208638 /home/drk/tillage/datasets/human/chip/geo/GSM1208638/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_IRX3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_IRX3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4548 0 GSM1208639 /home/drk/tillage/datasets/human/chip/geo/GSM1208639/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_JUN_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_JUN_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4549 0 GSM1208641 /home/drk/tillage/datasets/human/chip/geo/GSM1208641/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_KLF3_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_KLF3_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4550 0 GSM1208642 /home/drk/tillage/datasets/human/chip/geo/GSM1208642/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_KLF5_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_KLF5_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4551 0 GSM1208644 /home/drk/tillage/datasets/human/chip/geo/GSM1208644/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_LHX2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_LHX2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4552 0 GSM1208646 /home/drk/tillage/datasets/human/chip/geo/GSM1208646/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MED12_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MED12_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4553 0 GSM1208647 /home/drk/tillage/datasets/human/chip/geo/GSM1208647/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MED1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MED1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4554 0 GSM1208649 /home/drk/tillage/datasets/human/chip/geo/GSM1208649/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MEF2C_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MEF2C_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4555 0 GSM1208652 /home/drk/tillage/datasets/human/chip/geo/GSM1208652/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MYB_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MYB_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4556 0 GSM1208653 /home/drk/tillage/datasets/human/chip/geo/GSM1208653/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MYBL2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MYBL2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4557 0 GSM1208654 /home/drk/tillage/datasets/human/chip/geo/GSM1208654/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MYC_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MYC_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4558 0 GSM1208655 /home/drk/tillage/datasets/human/chip/geo/GSM1208655/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_MZF1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_MZF1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4559 0 GSM1208656 /home/drk/tillage/datasets/human/chip/geo/GSM1208656/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NEUROG3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NEUROG3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4560 0 GSM1208657 /home/drk/tillage/datasets/human/chip/geo/GSM1208657/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NFAT5_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NFAT5_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4561 0 GSM1208659 /home/drk/tillage/datasets/human/chip/geo/GSM1208659/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NFE2L2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NFE2L2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4562 0 GSM1208660 /home/drk/tillage/datasets/human/chip/geo/GSM1208660/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NFIL3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NFIL3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4563 0 GSM1208661 /home/drk/tillage/datasets/human/chip/geo/GSM1208661/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NIPBL_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NIPBL_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4564 0 GSM1208662 /home/drk/tillage/datasets/human/chip/geo/GSM1208662/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NPAT_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NPAT_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4565 0 GSM1208664 /home/drk/tillage/datasets/human/chip/geo/GSM1208664/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NR2F1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NR2F1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4566 0 GSM1208665 /home/drk/tillage/datasets/human/chip/geo/GSM1208665/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NR2F2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NR2F2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4567 0 GSM1208666 /home/drk/tillage/datasets/human/chip/geo/GSM1208666/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_NR3C1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_NR3C1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4568 0 GSM1208668 /home/drk/tillage/datasets/human/chip/geo/GSM1208668/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_RAD21_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_RAD21_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4569 0 GSM1208670 /home/drk/tillage/datasets/human/chip/geo/GSM1208670/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_RFX1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_RFX1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4570 0 GSM1208671 /home/drk/tillage/datasets/human/chip/geo/GSM1208671/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_RFX2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_RFX2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4571 0 GSM1208672 /home/drk/tillage/datasets/human/chip/geo/GSM1208672/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_RFX5_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_RFX5_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4572 0 GSM1208673 /home/drk/tillage/datasets/human/chip/geo/GSM1208673/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_RXRA_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_RXRA_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4573 0 GSM1208674 /home/drk/tillage/datasets/human/chip/geo/GSM1208674/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SMAD2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SMAD2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4574 0 GSM1208676 /home/drk/tillage/datasets/human/chip/geo/GSM1208676/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SMAD3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SMAD3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4575 0 GSM1208678 /home/drk/tillage/datasets/human/chip/geo/GSM1208678/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SMC1A_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SMC1A_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4576 0 GSM1208679 /home/drk/tillage/datasets/human/chip/geo/GSM1208679/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SMC3_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SMC3_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4577 0 GSM1208681 /home/drk/tillage/datasets/human/chip/geo/GSM1208681/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SOX4_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SOX4_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4578 0 GSM1208683 /home/drk/tillage/datasets/human/chip/geo/GSM1208683/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SP1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SP1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4579 0 GSM1208684 /home/drk/tillage/datasets/human/chip/geo/GSM1208684/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_SP3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_SP3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4580 0 GSM1208687 /home/drk/tillage/datasets/human/chip/geo/GSM1208687/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_TBX3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_TBX3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4581 0 GSM1208688 /home/drk/tillage/datasets/human/chip/geo/GSM1208688/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_TCF12_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_TCF12_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4582 0 GSM1208689 /home/drk/tillage/datasets/human/chip/geo/GSM1208689/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_TCF7L2_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_TCF7L2_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4583 0 GSM1208690 /home/drk/tillage/datasets/human/chip/geo/GSM1208690/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_TFAP2A_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_TFAP2A_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4584 0 GSM1208691 /home/drk/tillage/datasets/human/chip/geo/GSM1208691/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_TFDP1_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_TFDP1_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4585 0 GSM1208697 /home/drk/tillage/datasets/human/chip/geo/GSM1208697/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_UBTF_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_UBTF_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4586 0 GSM1208699 /home/drk/tillage/datasets/human/chip/geo/GSM1208699/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_YY1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_YY1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4587 0 GSM1208700 /home/drk/tillage/datasets/human/chip/geo/GSM1208700/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZBED4_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZBED4_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4588 0 GSM1208702 /home/drk/tillage/datasets/human/chip/geo/GSM1208702/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZBTB7B_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZBTB7B_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4589 0 GSM1208703 /home/drk/tillage/datasets/human/chip/geo/GSM1208703/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZNF236_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZNF236_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4590 0 GSM1208704 /home/drk/tillage/datasets/human/chip/geo/GSM1208704/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZNF250_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZNF250_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4591 0 GSM1208705 /home/drk/tillage/datasets/human/chip/geo/GSM1208705/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZNF407_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZNF407_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4592 0 GSM1208706 /home/drk/tillage/datasets/human/chip/geo/GSM1208706/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_ZNF706_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_ZNF706_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4593 0 GSM1208709 /home/drk/tillage/datasets/human/chip/geo/GSM1208709/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_AEBP2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_AEBP2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4594 0 GSM1208712 /home/drk/tillage/datasets/human/chip/geo/GSM1208712/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ATF1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ATF1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4595 0 GSM1208713 /home/drk/tillage/datasets/human/chip/geo/GSM1208713/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ATF5_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ATF5_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4596 0 GSM1208714 /home/drk/tillage/datasets/human/chip/geo/GSM1208714/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_BARHL1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_BARHL1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4597 0 GSM1208719 /home/drk/tillage/datasets/human/chip/geo/GSM1208719/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_CLOCK_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_CLOCK_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4598 0 GSM1208721 /home/drk/tillage/datasets/human/chip/geo/GSM1208721/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_CREB3L4_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_CREB3L4_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4599 0 GSM1208723 /home/drk/tillage/datasets/human/chip/geo/GSM1208723/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_DLX1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_DLX1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4600 0 GSM1208729 /home/drk/tillage/datasets/human/chip/geo/GSM1208729/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_E2F3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_E2F3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4601 0 GSM1208730 /home/drk/tillage/datasets/human/chip/geo/GSM1208730/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_E2F7_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_E2F7_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4602 0 GSM1208731 /home/drk/tillage/datasets/human/chip/geo/GSM1208731/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_E2F8_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_E2F8_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4603 0 GSM1208736 /home/drk/tillage/datasets/human/chip/geo/GSM1208736/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ERM_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ERM_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4604 0 GSM1208737 /home/drk/tillage/datasets/human/chip/geo/GSM1208737/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ESR1_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ESR1_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4605 0 GSM1208738 /home/drk/tillage/datasets/human/chip/geo/GSM1208738/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ETS2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ETS2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4606 0 GSM1208739 /home/drk/tillage/datasets/human/chip/geo/GSM1208739/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ETV7_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ETV7_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4607 0 GSM1208740 /home/drk/tillage/datasets/human/chip/geo/GSM1208740/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_EVI1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_EVI1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4608 0 GSM1208742 /home/drk/tillage/datasets/human/chip/geo/GSM1208742/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_FEV_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_FEV_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4609 0 GSM1208743 /home/drk/tillage/datasets/human/chip/geo/GSM1208743/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_ZFHX3_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_ZFHX3_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4610 0 GSM1208745 /home/drk/tillage/datasets/human/chip/geo/GSM1208745/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_FOXD2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_FOXD2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4611 0 GSM1208746 /home/drk/tillage/datasets/human/chip/geo/GSM1208746/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_FOXG1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_FOXG1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4612 0 GSM1208749 /home/drk/tillage/datasets/human/chip/geo/GSM1208749/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_GATA1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_GATA1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4613 0 GSM1208751 /home/drk/tillage/datasets/human/chip/geo/GSM1208751/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_GLI3_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_GLI3_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4614 0 GSM1208752 /home/drk/tillage/datasets/human/chip/geo/GSM1208752/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_GLIS1_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_GLIS1_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4615 0 GSM1208756 /home/drk/tillage/datasets/human/chip/geo/GSM1208756/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_HOXA13_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_HOXA13_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4616 0 GSM1208757 /home/drk/tillage/datasets/human/chip/geo/GSM1208757/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_HOXA2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_HOXA2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4617 0 GSM1208758 /home/drk/tillage/datasets/human/chip/geo/GSM1208758/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_HOXC6_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_HOXC6_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4618 0 GSM1208763 /home/drk/tillage/datasets/human/chip/geo/GSM1208763/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_JUND_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_JUND_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4619 0 GSM1208767 /home/drk/tillage/datasets/human/chip/geo/GSM1208767/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_LYL1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_LYL1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4620 0 GSM1208768 /home/drk/tillage/datasets/human/chip/geo/GSM1208768/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_MAZ_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_MAZ_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4621 0 GSM1208771 /home/drk/tillage/datasets/human/chip/geo/GSM1208771/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_MNT_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_MNT_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4622 0 GSM1208776 /home/drk/tillage/datasets/human/chip/geo/GSM1208776/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_NFKB2_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_NFKB2_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4623 0 GSM1208777 /home/drk/tillage/datasets/human/chip/geo/GSM1208777/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_NFYA_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_NFYA_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4624 0 GSM1208780 /home/drk/tillage/datasets/human/chip/geo/GSM1208780/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_NKX2.2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_NKX2.2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4625 0 GSM1208788 /home/drk/tillage/datasets/human/chip/geo/GSM1208788/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_RARG_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_RARG_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4626 0 GSM1208789 /home/drk/tillage/datasets/human/chip/geo/GSM1208789/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_RBCK1_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_RBCK1_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4627 0 GSM1208790 /home/drk/tillage/datasets/human/chip/geo/GSM1208790/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_REST_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_REST_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4628 0 GSM1208794 /home/drk/tillage/datasets/human/chip/geo/GSM1208794/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_SOX2_Goat_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_SOX2_Goat_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4629 0 GSM1208796 /home/drk/tillage/datasets/human/chip/geo/GSM1208796/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_SP2_Mouse_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_SP2_Mouse_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4630 0 GSM1208802 /home/drk/tillage/datasets/human/chip/geo/GSM1208802/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_TEAD2_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_TEAD2_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4631 0 GSM1208805 /home/drk/tillage/datasets/human/chip/geo/GSM1208805/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_TP73_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_TP73_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4632 0 GSM1208807 /home/drk/tillage/datasets/human/chip/geo/GSM1208807/summary/coverage.w5 64 1 sum CHIP:.:batch2_chrom1_LoVo_VEZF1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch2_chrom1_LoVo_VEZF1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4633 0 GSM1208809 /home/drk/tillage/datasets/human/chip/geo/GSM1208809/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_H3_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_H3_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4634 0 GSM1208810 /home/drk/tillage/datasets/human/chip/geo/GSM1208810/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_H3K4me1_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_H3K4me1_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4635 0 GSM1208811 /home/drk/tillage/datasets/human/chip/geo/GSM1208811/summary/coverage.w5 64 1 sum CHIP:.:batch1_chrom1_LoVo_H3K4me3_Rabbit_PassedQC / LoVo / colon adenocarcinoma CHIP "ChIP-TF:./batch1_chrom1_LoVo_H3K4me3_Rabbit_PassedQC ; LoVo ; colon adenocarcinoma" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4636 0 GSM1684630 /home/drk/tillage/datasets/human/chip/geo/GSM1684630/summary/coverage.w5 64 1 sum CHIP:RNAPII:ChIP-seq, RNAPII_LowDensity_noDMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:RNAPII/ChIP-seq, RNAPII_LowDensity_noDMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4637 0 GSM1684631 /home/drk/tillage/datasets/human/chip/geo/GSM1684631/summary/coverage.w5 64 1 sum CHIP:RNAPII:ChIP-seq, RNAPII_HighDensity_noDMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:RNAPII/ChIP-seq, RNAPII_HighDensity_noDMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4638 0 GSM1684632 /home/drk/tillage/datasets/human/chip/geo/GSM1684632/summary/coverage.w5 64 1 sum CHIP:RNAPII:ChIP-seq, RNAPII_LowDensity_DMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:RNAPII/ChIP-seq, RNAPII_LowDensity_DMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4639 0 GSM1684633 /home/drk/tillage/datasets/human/chip/geo/GSM1684633/summary/coverage.w5 64 1 sum CHIP:RNAPII:ChIP-seq, RNAPII_HighDensity_DMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:RNAPII/ChIP-seq, RNAPII_HighDensity_DMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4640 0 GSM1684634 /home/drk/tillage/datasets/human/chip/geo/GSM1684634/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, CEBPb_HighDensity_noDMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, CEBPb_HighDensity_noDMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4641 0 GSM1684635 /home/drk/tillage/datasets/human/chip/geo/GSM1684635/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, CEBPb_LowDensity_DMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, CEBPb_LowDensity_DMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4642 0 GSM1684636 /home/drk/tillage/datasets/human/chip/geo/GSM1684636/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, CEBPb_HighDensity_DMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, CEBPb_HighDensity_DMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4643 0 GSM1684637 /home/drk/tillage/datasets/human/chip/geo/GSM1684637/summary/coverage.w5 64 1 sum CHIP:GR:ChIP-seq, GR_HighDensity_DMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:GR/ChIP-seq, GR_HighDensity_DMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4644 0 GSM1684638 /home/drk/tillage/datasets/human/chip/geo/GSM1684638/summary/coverage.w5 64 1 sum CHIP:ATF4:ChIP-seq, ATF4_HighDensity_noDMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:ATF4/ChIP-seq, ATF4_HighDensity_noDMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4645 0 GSM1684639 /home/drk/tillage/datasets/human/chip/geo/GSM1684639/summary/coverage.w5 64 1 sum CHIP:H3K27Ac:ChIP-seq, H3K27Ac_HighDensity_noDMI / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-Histone:H3K27Ac/ChIP-seq, H3K27Ac_HighDensity_noDMI ; hMSC ; Human Mesenchymal Stem Cells" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4646 0 GSM1684640 /home/drk/tillage/datasets/human/chip/geo/GSM1684640/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_0.1uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_0.1uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4647 0 GSM1684641 /home/drk/tillage/datasets/human/chip/geo/GSM1684641/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_0.25uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_0.25uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4648 0 GSM1684642 /home/drk/tillage/datasets/human/chip/geo/GSM1684642/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_1.0uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_1.0uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4649 0 GSM1684643 /home/drk/tillage/datasets/human/chip/geo/GSM1684643/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_10uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_10uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4650 0 GSM1684644 /home/drk/tillage/datasets/human/chip/geo/GSM1684644/summary/coverage.w5 64 1 sum CHIP:ATF4:ChIP-seq, InVitroCistromics_ATF4_5uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:ATF4/ChIP-seq, InVitroCistromics_ATF4_5uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4651 0 GSM1684645 /home/drk/tillage/datasets/human/chip/geo/GSM1684645/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.002uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.002uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4652 0 GSM1684646 /home/drk/tillage/datasets/human/chip/geo/GSM1684646/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.02uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.02uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4653 0 GSM1684647 /home/drk/tillage/datasets/human/chip/geo/GSM1684647/summary/coverage.w5 64 1 sum CHIP:CEBPb:ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.2uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:CEBPb/ChIP-seq, InVitroCistromics_CEBPb_0.1uL_plusATF4_0.2uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4654 0 GSM1684648 /home/drk/tillage/datasets/human/chip/geo/GSM1684648/summary/coverage.w5 64 1 sum CHIP:ATF4:ChIP-seq, InVitroCistromics_ATF4_0.02uL_plusCEBPb_0.1uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:ATF4/ChIP-seq, InVitroCistromics_ATF4_0.02uL_plusCEBPb_0.1uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4655 0 GSM1684649 /home/drk/tillage/datasets/human/chip/geo/GSM1684649/summary/coverage.w5 64 1 sum CHIP:ATF4:ChIP-seq, InVitroCistromics_ATF4_0.2uL_plusCEBPb_0.1uL / hMSC / Human Mesenchymal Stem Cells CHIP "ChIP-TF:ATF4/ChIP-seq, InVitroCistromics_ATF4_0.2uL_plusCEBPb_0.1uL ; hMSC ; Human Mesenchymal Stem Cells" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4656 0 GSM1692868 /home/drk/tillage/datasets/human/chip/geo/GSM1692868/summary/coverage.w5 64 1 sum CHIP:hBMAL1:ChIP_hBMAL1 Chip-seq / U2OS cells / . CHIP "ChIP-TF:hBMAL1/ChIP_hBMAL1 Chip-seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4657 0 GSM1692869 /home/drk/tillage/datasets/human/chip/geo/GSM1692869/summary/coverage.w5 64 1 sum CHIP:hHIF1A:ChIP_hHIF1A Chip-seq / U2OS cells / . CHIP "ChIP-TF:hHIF1A/ChIP_hHIF1A Chip-seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4658 0 GSM1697346 /home/drk/tillage/datasets/human/chip/geo/GSM1697346/summary/coverage.w5 64 1 sum CHIP:ATF4:anti-ATF4 (sc-200) / HAP1, 2 mM histidinol for 24 hours, ATF4 ChIP / HAP1 CHIP "ChIP-TF:ATF4/anti-ATF4 (sc-200) ; HAP1, 2 mM histidinol for 24 hours, ATF4 ChIP ; HAP1" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4659 0 GSM1920690 /home/drk/tillage/datasets/human/chip/geo/GSM1920690/summary/coverage.w5 64 1 sum CHIP:BMAL1:BMAL1_DMSO_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-TF:BMAL1/BMAL1_DMSO_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4660 0 GSM1920691 /home/drk/tillage/datasets/human/chip/geo/GSM1920691/summary/coverage.w5 64 1 sum CHIP:BMAL1:BMAL1_6AN_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-TF:BMAL1/BMAL1_6AN_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4661 0 GSM1920692 /home/drk/tillage/datasets/human/chip/geo/GSM1920692/summary/coverage.w5 64 1 sum CHIP:CLOCK:CLOCK_DMSO_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-TF:CLOCK/CLOCK_DMSO_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4662 0 GSM1920693 /home/drk/tillage/datasets/human/chip/geo/GSM1920693/summary/coverage.w5 64 1 sum CHIP:CLOCK:CLOCK_6AN_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-TF:CLOCK/CLOCK_6AN_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4663 0 GSM2060761 /home/drk/tillage/datasets/human/chip/geo/GSM2060761/summary/coverage.w5 64 1 sum CHIP:H3K4me3:H3K4me3_DMSO_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-Histone:H3K4me3/H3K4me3_DMSO_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4664 0 GSM2060762 /home/drk/tillage/datasets/human/chip/geo/GSM2060762/summary/coverage.w5 64 1 sum CHIP:H3K4me3:H3K4me3_6AN_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-Histone:H3K4me3/H3K4me3_6AN_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4665 0 GSM2060763 /home/drk/tillage/datasets/human/chip/geo/GSM2060763/summary/coverage.w5 64 1 sum CHIP:H3K9ac:H3K9ac_DMSO_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-Histone:H3K9ac/H3K9ac_DMSO_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4666 0 GSM2060764 /home/drk/tillage/datasets/human/chip/geo/GSM2060764/summary/coverage.w5 64 1 sum CHIP:H3K9ac:H3K9ac_6AN_ChIPSeq / U2OS cells stably expressing Bmal1:Luc / osteosarcoma cell line U2OS stably expressing Bmal1:Luc CHIP "ChIP-Histone:H3K9ac/H3K9ac_6AN_ChIPSeq ; U2OS cells stably expressing Bmal1:Luc ; osteosarcoma cell line U2OS stably expressing Bmal1:Luc" ChIP-Histone FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4667 0 GSM2257666 /home/drk/tillage/datasets/human/chip/geo/GSM2257666/summary/coverage.w5 64 1 sum CHIP:abcam:ChIP_hBMAL1-peak-DMOG CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:abcam/ChIP_hBMAL1-peak-DMOG CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4668 0 GSM2257667 /home/drk/tillage/datasets/human/chip/geo/GSM2257667/summary/coverage.w5 64 1 sum CHIP:abcam:ChIP_hBMAL1-trough-DMOG CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:abcam/ChIP_hBMAL1-trough-DMOG CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4669 0 GSM2257668 /home/drk/tillage/datasets/human/chip/geo/GSM2257668/summary/coverage.w5 64 1 sum CHIP:abcam:ChIP_hBMAL1-peak-DMSO CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:abcam/ChIP_hBMAL1-peak-DMSO CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4670 0 GSM2257669 /home/drk/tillage/datasets/human/chip/geo/GSM2257669/summary/coverage.w5 64 1 sum CHIP:abcam:ChIP_hBMAL1-trough-DMSO CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:abcam/ChIP_hBMAL1-trough-DMSO CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4671 0 GSM2257670 /home/drk/tillage/datasets/human/chip/geo/GSM2257670/summary/coverage.w5 64 1 sum CHIP:active:ChIP_hHIF1a-peak-DMOG CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:active/ChIP_hHIF1a-peak-DMOG CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4672 0 GSM2257671 /home/drk/tillage/datasets/human/chip/geo/GSM2257671/summary/coverage.w5 64 1 sum CHIP:active:ChIP_hHIF1a-trough-DMOG CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:active/ChIP_hHIF1a-trough-DMOG CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4673 0 GSM2257672 /home/drk/tillage/datasets/human/chip/geo/GSM2257672/summary/coverage.w5 64 1 sum CHIP:active:ChIP_hHIF1a-peak-DMSO CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:active/ChIP_hHIF1a-peak-DMSO CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4674 0 GSM2257673 /home/drk/tillage/datasets/human/chip/geo/GSM2257673/summary/coverage.w5 64 1 sum CHIP:active:ChIP_hHIF1a-trough-DMSO CHIP-Seq / U2OS cells / . CHIP "ChIP-TF:active/ChIP_hHIF1a-trough-DMSO CHIP-Seq ; U2OS cells ; ." ChIP-TF FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4675 0 CNhs10608 /home/drk/tillage/datasets/human/cage/fantom/CNhs10608/summary/coverage.w5 384 1 sum CAGE:Clontech Human Universal Reference Total RNA, pool1 CAGE CAGE/Clontech Human Universal Reference Total RNA, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4676 0 CNhs10610 /home/drk/tillage/datasets/human/cage/fantom/CNhs10610/summary/coverage.w5 384 1 sum CAGE:SABiosciences XpressRef Human Universal Total RNA, pool1 CAGE CAGE/SABiosciences XpressRef Human Universal Total RNA, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4677 0 CNhs10612 /home/drk/tillage/datasets/human/cage/fantom/CNhs10612/summary/coverage.w5 384 1 sum CAGE:Universal RNA - Human Normal Tissues Biochain, pool1 CAGE CAGE/Universal RNA - Human Normal Tissues Biochain, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4678 0 CNhs10615 /home/drk/tillage/datasets/human/cage/fantom/CNhs10615/summary/coverage.w5 384 1 sum CAGE:adipose tissue, adult, pool1 CAGE CAGE/adipose tissue, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4679 0 CNhs10616 /home/drk/tillage/datasets/human/cage/fantom/CNhs10616/summary/coverage.w5 384 1 sum CAGE:bladder, adult, pool1 CAGE CAGE/bladder, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4680 0 CNhs10617 /home/drk/tillage/datasets/human/cage/fantom/CNhs10617/summary/coverage.w5 384 1 sum CAGE:brain, adult, pool1 CAGE CAGE/brain, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4681 0 CNhs10618 /home/drk/tillage/datasets/human/cage/fantom/CNhs10618/summary/coverage.w5 384 1 sum CAGE:cervix, adult, pool1 CAGE CAGE/cervix, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4682 0 CNhs10619 /home/drk/tillage/datasets/human/cage/fantom/CNhs10619/summary/coverage.w5 384 1 sum CAGE:colon, adult, pool1 CAGE CAGE/colon, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4683 0 CNhs10620 /home/drk/tillage/datasets/human/cage/fantom/CNhs10620/summary/coverage.w5 384 1 sum CAGE:esophagus, adult, pool1 CAGE CAGE/esophagus, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4684 0 CNhs10621 /home/drk/tillage/datasets/human/cage/fantom/CNhs10621/summary/coverage.w5 384 1 sum CAGE:heart, adult, pool1 CAGE CAGE/heart, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4685 0 CNhs10622 /home/drk/tillage/datasets/human/cage/fantom/CNhs10622/summary/coverage.w5 384 1 sum CAGE:kidney, adult, pool1 CAGE CAGE/kidney, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4686 0 CNhs10624 /home/drk/tillage/datasets/human/cage/fantom/CNhs10624/summary/coverage.w5 384 1 sum CAGE:liver, adult, pool1 CAGE CAGE/liver, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4687 0 CNhs10625 /home/drk/tillage/datasets/human/cage/fantom/CNhs10625/summary/coverage.w5 384 1 sum CAGE:lung, adult, pool1 CAGE CAGE/lung, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4688 0 CNhs10626 /home/drk/tillage/datasets/human/cage/fantom/CNhs10626/summary/coverage.w5 384 1 sum CAGE:ovary, adult, pool1 CAGE CAGE/ovary, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4689 0 CNhs10627 /home/drk/tillage/datasets/human/cage/fantom/CNhs10627/summary/coverage.w5 384 1 sum CAGE:placenta, adult, pool1 CAGE CAGE/placenta, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4690 0 CNhs10628 /home/drk/tillage/datasets/human/cage/fantom/CNhs10628/summary/coverage.w5 384 1 sum CAGE:prostate, adult, pool1 CAGE CAGE/prostate, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4691 0 CNhs10629 /home/drk/tillage/datasets/human/cage/fantom/CNhs10629/summary/coverage.w5 384 1 sum CAGE:skeletal muscle, adult, pool1 CAGE CAGE/skeletal muscle, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4692 0 CNhs10630 /home/drk/tillage/datasets/human/cage/fantom/CNhs10630/summary/coverage.w5 384 1 sum CAGE:small intestine, adult, pool1 CAGE CAGE/small intestine, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4693 0 CNhs10631 /home/drk/tillage/datasets/human/cage/fantom/CNhs10631/summary/coverage.w5 384 1 sum CAGE:spleen, adult, pool1 CAGE CAGE/spleen, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4694 0 CNhs10632 /home/drk/tillage/datasets/human/cage/fantom/CNhs10632/summary/coverage.w5 384 1 sum CAGE:testis, adult, pool1 CAGE CAGE/testis, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4695 0 CNhs10633 /home/drk/tillage/datasets/human/cage/fantom/CNhs10633/summary/coverage.w5 384 1 sum CAGE:thymus, adult, pool1 CAGE CAGE/thymus, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4696 0 CNhs10634 /home/drk/tillage/datasets/human/cage/fantom/CNhs10634/summary/coverage.w5 384 1 sum CAGE:thyroid, adult, pool1 CAGE CAGE/thyroid, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4697 0 CNhs10635 /home/drk/tillage/datasets/human/cage/fantom/CNhs10635/summary/coverage.w5 384 1 sum CAGE:trachea, adult, pool1 CAGE CAGE/trachea, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4698 0 CNhs10636 /home/drk/tillage/datasets/human/cage/fantom/CNhs10636/summary/coverage.w5 384 1 sum CAGE:retina, adult, pool1 CAGE CAGE/retina, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4699 0 CNhs10637 /home/drk/tillage/datasets/human/cage/fantom/CNhs10637/summary/coverage.w5 384 1 sum CAGE:temporal lobe, adult, pool1 CAGE CAGE/temporal lobe, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4700 0 CNhs10638 /home/drk/tillage/datasets/human/cage/fantom/CNhs10638/summary/coverage.w5 384 1 sum CAGE:postcentral gyrus, adult, pool1 CAGE CAGE/postcentral gyrus, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4701 0 CNhs10640 /home/drk/tillage/datasets/human/cage/fantom/CNhs10640/summary/coverage.w5 384 1 sum CAGE:pons, adult, pool1 CAGE CAGE/pons, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4702 0 CNhs10641 /home/drk/tillage/datasets/human/cage/fantom/CNhs10641/summary/coverage.w5 384 1 sum CAGE:parietal lobe, adult, pool1 CAGE CAGE/parietal lobe, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4703 0 CNhs10642 /home/drk/tillage/datasets/human/cage/fantom/CNhs10642/summary/coverage.w5 384 1 sum CAGE:paracentral gyrus, adult, pool1 CAGE CAGE/paracentral gyrus, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4704 0 CNhs10643 /home/drk/tillage/datasets/human/cage/fantom/CNhs10643/summary/coverage.w5 384 1 sum CAGE:occipital pole, adult, pool1 CAGE CAGE/occipital pole, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4705 0 CNhs10644 /home/drk/tillage/datasets/human/cage/fantom/CNhs10644/summary/coverage.w5 384 1 sum CAGE:nucleus accumbens, adult, pool1 CAGE CAGE/nucleus accumbens, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4706 0 CNhs10645 /home/drk/tillage/datasets/human/cage/fantom/CNhs10645/summary/coverage.w5 384 1 sum CAGE:medulla oblongata, adult, pool1 CAGE CAGE/medulla oblongata, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4707 0 CNhs10646 /home/drk/tillage/datasets/human/cage/fantom/CNhs10646/summary/coverage.w5 384 1 sum CAGE:insula, adult, pool1 CAGE CAGE/insula, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4708 0 CNhs10647 /home/drk/tillage/datasets/human/cage/fantom/CNhs10647/summary/coverage.w5 384 1 sum CAGE:frontal lobe, adult, pool1 CAGE CAGE/frontal lobe, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4709 0 CNhs10648 /home/drk/tillage/datasets/human/cage/fantom/CNhs10648/summary/coverage.w5 384 1 sum CAGE:dura mater, adult, CAGE CAGE/dura mater, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4710 0 CNhs10649 /home/drk/tillage/datasets/human/cage/fantom/CNhs10649/summary/coverage.w5 384 1 sum CAGE:corpus callosum, adult, pool1 CAGE CAGE/corpus callosum, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4711 0 CNhs10650 /home/drk/tillage/datasets/human/cage/fantom/CNhs10650/summary/coverage.w5 384 1 sum CAGE:thymus, fetal, pool1 CAGE CAGE/thymus, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4712 0 CNhs10651 /home/drk/tillage/datasets/human/cage/fantom/CNhs10651/summary/coverage.w5 384 1 sum CAGE:spleen, fetal, pool1 CAGE CAGE/spleen, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4713 0 CNhs10652 /home/drk/tillage/datasets/human/cage/fantom/CNhs10652/summary/coverage.w5 384 1 sum CAGE:kidney, fetal, pool1 CAGE CAGE/kidney, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4714 0 CNhs10653 /home/drk/tillage/datasets/human/cage/fantom/CNhs10653/summary/coverage.w5 384 1 sum CAGE:heart, fetal, pool1 CAGE CAGE/heart, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4715 0 CNhs10654 /home/drk/tillage/datasets/human/cage/fantom/CNhs10654/summary/coverage.w5 384 1 sum CAGE:tonsil, adult, pool1 CAGE CAGE/tonsil, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4716 0 CNhs10722 /home/drk/tillage/datasets/human/cage/fantom/CNhs10722/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:THP-1 (fresh) CAGE CAGE/acute myeloid leukemia (FAB M5) cell line:THP-1 (fresh) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4717 0 CNhs10723 /home/drk/tillage/datasets/human/cage/fantom/CNhs10723/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:THP-1 (revived) CAGE CAGE/acute myeloid leukemia (FAB M5) cell line:THP-1 (revived) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4718 0 CNhs10724 /home/drk/tillage/datasets/human/cage/fantom/CNhs10724/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:THP-1 (thawed) CAGE CAGE/acute myeloid leukemia (FAB M5) cell line:THP-1 (thawed) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4719 0 CNhs10726 /home/drk/tillage/datasets/human/cage/fantom/CNhs10726/summary/coverage.w5 384 1 sum CAGE:lung adenocarcinoma cell line:PC-14 CAGE CAGE/lung adenocarcinoma cell line:PC-14 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4720 0 CNhs10727 /home/drk/tillage/datasets/human/cage/fantom/CNhs10727/summary/coverage.w5 384 1 sum CAGE:chronic myelogenous leukemia cell line:KU812 CAGE CAGE/chronic myelogenous leukemia cell line:KU812 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4721 0 CNhs10728 /home/drk/tillage/datasets/human/cage/fantom/CNhs10728/summary/coverage.w5 384 1 sum CAGE:extraskeletal myxoid chondrosarcoma cell line:H-EMC-SS CAGE CAGE/extraskeletal myxoid chondrosarcoma cell line:H-EMC-SS CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4722 0 CNhs10729 /home/drk/tillage/datasets/human/cage/fantom/CNhs10729/summary/coverage.w5 384 1 sum CAGE:renal cell carcinoma cell line:OS-RC-2 CAGE CAGE/renal cell carcinoma cell line:OS-RC-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4723 0 CNhs10730 /home/drk/tillage/datasets/human/cage/fantom/CNhs10730/summary/coverage.w5 384 1 sum CAGE:malignant trichilemmal cyst cell line:DJM-1 CAGE CAGE/malignant trichilemmal cyst cell line:DJM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4724 0 CNhs10731 /home/drk/tillage/datasets/human/cage/fantom/CNhs10731/summary/coverage.w5 384 1 sum CAGE:glioma cell line:GI-1 CAGE CAGE/glioma cell line:GI-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4725 0 CNhs10732 /home/drk/tillage/datasets/human/cage/fantom/CNhs10732/summary/coverage.w5 384 1 sum CAGE:maxillary sinus tumor cell line:HSQ-89 CAGE CAGE/maxillary sinus tumor cell line:HSQ-89 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4726 0 CNhs10733 /home/drk/tillage/datasets/human/cage/fantom/CNhs10733/summary/coverage.w5 384 1 sum CAGE:gall bladder carcinoma cell line:TGBC2TKB CAGE CAGE/gall bladder carcinoma cell line:TGBC2TKB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4727 0 CNhs10734 /home/drk/tillage/datasets/human/cage/fantom/CNhs10734/summary/coverage.w5 384 1 sum CAGE:papillotubular adenocarcinoma cell line:TGBC18TKB CAGE CAGE/papillotubular adenocarcinoma cell line:TGBC18TKB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4728 0 CNhs10735 /home/drk/tillage/datasets/human/cage/fantom/CNhs10735/summary/coverage.w5 384 1 sum CAGE:transitional-cell carcinoma cell line:5637 CAGE CAGE/transitional-cell carcinoma cell line:5637 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4729 0 CNhs10736 /home/drk/tillage/datasets/human/cage/fantom/CNhs10736/summary/coverage.w5 384 1 sum CAGE:breast carcinoma cell line:MDA-MB-453 CAGE CAGE/breast carcinoma cell line:MDA-MB-453 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4730 0 CNhs10737 /home/drk/tillage/datasets/human/cage/fantom/CNhs10737/summary/coverage.w5 384 1 sum CAGE:colon carcinoma cell line:COLO-320 CAGE CAGE/colon carcinoma cell line:COLO-320 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4731 0 CNhs10738 /home/drk/tillage/datasets/human/cage/fantom/CNhs10738/summary/coverage.w5 384 1 sum CAGE:adult T-cell leukemia cell line:ATN-1 CAGE CAGE/adult T-cell leukemia cell line:ATN-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4732 0 CNhs10739 /home/drk/tillage/datasets/human/cage/fantom/CNhs10739/summary/coverage.w5 384 1 sum CAGE:Burkitt's lymphoma cell line:DAUDI CAGE CAGE/Burkitt's lymphoma cell line:DAUDI CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4733 0 CNhs10740 /home/drk/tillage/datasets/human/cage/fantom/CNhs10740/summary/coverage.w5 384 1 sum CAGE:choriocarcinoma cell line:BeWo CAGE CAGE/choriocarcinoma cell line:BeWo CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4734 0 CNhs10741 /home/drk/tillage/datasets/human/cage/fantom/CNhs10741/summary/coverage.w5 384 1 sum CAGE:splenic lymphoma with villous lymphocytes cell line:SLVL CAGE CAGE/splenic lymphoma with villous lymphocytes cell line:SLVL CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4735 0 CNhs10742 /home/drk/tillage/datasets/human/cage/fantom/CNhs10742/summary/coverage.w5 384 1 sum CAGE:astrocytoma cell line:TM-31 CAGE CAGE/astrocytoma cell line:TM-31 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4736 0 CNhs10743 /home/drk/tillage/datasets/human/cage/fantom/CNhs10743/summary/coverage.w5 384 1 sum CAGE:epidermoid carcinoma cell line:A431 CAGE CAGE/epidermoid carcinoma cell line:A431 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4737 0 CNhs10744 /home/drk/tillage/datasets/human/cage/fantom/CNhs10744/summary/coverage.w5 384 1 sum CAGE:b cell line:RPMI1788 CAGE CAGE/b cell line:RPMI1788 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4738 0 CNhs10745 /home/drk/tillage/datasets/human/cage/fantom/CNhs10745/summary/coverage.w5 384 1 sum CAGE:anaplastic carcinoma cell line:8305C CAGE CAGE/anaplastic carcinoma cell line:8305C CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4739 0 CNhs10746 /home/drk/tillage/datasets/human/cage/fantom/CNhs10746/summary/coverage.w5 384 1 sum CAGE:acute lymphoblastic leukemia (T-ALL) cell line:HPB-ALL CAGE CAGE/acute lymphoblastic leukemia (T-ALL) cell line:HPB-ALL CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4740 0 CNhs10747 /home/drk/tillage/datasets/human/cage/fantom/CNhs10747/summary/coverage.w5 384 1 sum CAGE:non T non B acute lymphoblastic leukemia (ALL) cell line:P30/OHK CAGE "CAGE/non T non B acute lymphoblastic leukemia (ALL) cell line:P30;OHK" CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4741 0 CNhs10748 /home/drk/tillage/datasets/human/cage/fantom/CNhs10748/summary/coverage.w5 384 1 sum CAGE:epidermoid carcinoma cell line:Ca Ski CAGE CAGE/epidermoid carcinoma cell line:Ca Ski CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4742 0 CNhs10750 /home/drk/tillage/datasets/human/cage/fantom/CNhs10750/summary/coverage.w5 384 1 sum CAGE:bile duct carcinoma cell line:HuCCT1 CAGE CAGE/bile duct carcinoma cell line:HuCCT1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4743 0 CNhs10751 /home/drk/tillage/datasets/human/cage/fantom/CNhs10751/summary/coverage.w5 384 1 sum CAGE:giant cell carcinoma cell line:Lu99B CAGE CAGE/giant cell carcinoma cell line:Lu99B CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4744 0 CNhs10752 /home/drk/tillage/datasets/human/cage/fantom/CNhs10752/summary/coverage.w5 384 1 sum CAGE:oral squamous cell carcinoma cell line:Ca9-22 CAGE CAGE/oral squamous cell carcinoma cell line:Ca9-22 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4745 0 CNhs10753 /home/drk/tillage/datasets/human/cage/fantom/CNhs10753/summary/coverage.w5 384 1 sum CAGE:signet ring carcinoma cell line:Kato III CAGE CAGE/signet ring carcinoma cell line:Kato III CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4746 0 CNhs10837 /home/drk/tillage/datasets/human/cage/fantom/CNhs10837/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Aortic, CAGE CAGE/Endothelial Cells - Aortic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4747 0 CNhs11309 /home/drk/tillage/datasets/human/cage/fantom/CNhs10838/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Aortic, CAGE CAGE/Smooth Muscle Cells - Aortic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4748 0 CNhs10839 /home/drk/tillage/datasets/human/cage/fantom/CNhs10839/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Umbilical artery, CAGE CAGE/Smooth Muscle Cells - Umbilical artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4749 0 CNhs10842 /home/drk/tillage/datasets/human/cage/fantom/CNhs10842/summary/coverage.w5 384 1 sum CAGE:Retinal Pigment Epithelial Cells, CAGE CAGE/Retinal Pigment Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4750 0 CNhs10843 /home/drk/tillage/datasets/human/cage/fantom/CNhs10843/summary/coverage.w5 384 1 sum CAGE:Urothelial cells, CAGE CAGE/Urothelial cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4751 0 CNhs10844 /home/drk/tillage/datasets/human/cage/fantom/CNhs10844/summary/coverage.w5 384 1 sum CAGE:Mesenchymal stem cells - adipose, CAGE CAGE/Mesenchymal stem cells - adipose, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4752 0 CNhs10845 /home/drk/tillage/datasets/human/cage/fantom/CNhs10845/summary/coverage.w5 384 1 sum CAGE:Mesenchymal stem cells - hepatic, CAGE CAGE/Mesenchymal stem cells - hepatic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4753 0 CNhs10846 /home/drk/tillage/datasets/human/cage/fantom/CNhs10846/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - Vertebral, CAGE CAGE/Mesenchymal Stem Cells - Vertebral, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4754 0 CNhs11951 /home/drk/tillage/datasets/human/cage/fantom/CNhs10847/summary/coverage.w5 384 1 sum CAGE:Sebocyte, CAGE CAGE/Sebocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4755 0 CNhs10848 /home/drk/tillage/datasets/human/cage/fantom/CNhs10848/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (GFH2) CAGE CAGE/Fibroblast - Gingival, (GFH2) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4756 0 CNhs12012 /home/drk/tillage/datasets/human/cage/fantom/CNhs10850/summary/coverage.w5 384 1 sum CAGE:Mesothelial Cells, CAGE CAGE/Mesothelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4757 0 CNhs11974 /home/drk/tillage/datasets/human/cage/fantom/CNhs10851/summary/coverage.w5 384 1 sum CAGE:Sertoli Cells, CAGE CAGE/Sertoli Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4758 0 CNhs10852 /home/drk/tillage/datasets/human/cage/fantom/CNhs10852/summary/coverage.w5 384 1 sum CAGE:CD14+ Monocytes, CAGE CAGE/CD14+ Monocytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4759 0 CNhs11955 /home/drk/tillage/datasets/human/cage/fantom/CNhs10853/summary/coverage.w5 384 1 sum CAGE:CD4+ T Cells, CAGE CAGE/CD4+ T Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4760 0 CNhs11956 /home/drk/tillage/datasets/human/cage/fantom/CNhs10854/summary/coverage.w5 384 1 sum CAGE:CD8+ T Cells, CAGE CAGE/CD8+ T Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4761 0 CNhs11062 /home/drk/tillage/datasets/human/cage/fantom/CNhs10855/summary/coverage.w5 384 1 sum CAGE:Dendritic Cells - monocyte immature derived, , tech_ CAGE CAGE/Dendritic Cells - monocyte immature derived, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4762 0 CNhs12196 /home/drk/tillage/datasets/human/cage/fantom/CNhs10857/summary/coverage.w5 384 1 sum CAGE:Dendritic Cells - plasmacytoid, CAGE CAGE/Dendritic Cells - plasmacytoid, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4763 0 CNhs11904 /home/drk/tillage/datasets/human/cage/fantom/CNhs10858/summary/coverage.w5 384 1 sum CAGE:CD14+ monocyte derived endothelial progenitor cells, CAGE CAGE/CD14+ monocyte derived endothelial progenitor cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4764 0 CNhs11957 /home/drk/tillage/datasets/human/cage/fantom/CNhs10859/summary/coverage.w5 384 1 sum CAGE:Natural Killer Cells, CAGE CAGE/Natural Killer Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4765 0 CNhs11958 /home/drk/tillage/datasets/human/cage/fantom/CNhs10860/summary/coverage.w5 384 1 sum CAGE:Peripheral Blood Mononuclear Cells, CAGE CAGE/Peripheral Blood Mononuclear Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4766 0 CNhs12003 /home/drk/tillage/datasets/human/cage/fantom/CNhs10861/summary/coverage.w5 384 1 sum CAGE:Macrophage - monocyte derived, CAGE CAGE/Macrophage - monocyte derived, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4767 0 CNhs10862 /home/drk/tillage/datasets/human/cage/fantom/CNhs10862/summary/coverage.w5 384 1 sum CAGE:Neutrophils, CAGE CAGE/Neutrophils, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4768 0 CNhs11900 /home/drk/tillage/datasets/human/cage/fantom/CNhs10863/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Brain Vascular, CAGE CAGE/Smooth Muscle Cells - Brain Vascular, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4769 0 CNhs12005 /home/drk/tillage/datasets/human/cage/fantom/CNhs10864/summary/coverage.w5 384 1 sum CAGE:Astrocyte - cerebral cortex, CAGE CAGE/Astrocyte - cerebral cortex, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4770 0 CNhs11906 /home/drk/tillage/datasets/human/cage/fantom/CNhs10865/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Lymphatic, CAGE CAGE/Endothelial Cells - Lymphatic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4771 0 CNhs12006 /home/drk/tillage/datasets/human/cage/fantom/CNhs10866/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, CAGE CAGE/Fibroblast - Gingival, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4772 0 CNhs11962 /home/drk/tillage/datasets/human/cage/fantom/CNhs10867/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Periodontal Ligament, CAGE CAGE/Fibroblast - Periodontal Ligament, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4773 0 CNhs10868 /home/drk/tillage/datasets/human/cage/fantom/CNhs10868/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Colonic, CAGE CAGE/Smooth Muscle Cells - Colonic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4774 0 CNhs12008 /home/drk/tillage/datasets/human/cage/fantom/CNhs10869/summary/coverage.w5 384 1 sum CAGE:Skeletal Muscle Satellite Cells, CAGE CAGE/Skeletal Muscle Satellite Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4775 0 CNhs10870 /home/drk/tillage/datasets/human/cage/fantom/CNhs10870/summary/coverage.w5 384 1 sum CAGE:Myoblast, CAGE CAGE/Myoblast, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4776 0 CNhs11966 /home/drk/tillage/datasets/human/cage/fantom/CNhs10871/summary/coverage.w5 384 1 sum CAGE:Ciliary Epithelial Cells, CAGE CAGE/Ciliary Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4777 0 CNhs12010 /home/drk/tillage/datasets/human/cage/fantom/CNhs10872/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Umbilical vein, CAGE CAGE/Endothelial Cells - Umbilical vein, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4778 0 CNhs11968 /home/drk/tillage/datasets/human/cage/fantom/CNhs10874/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Aortic Adventitial, CAGE CAGE/Fibroblast - Aortic Adventitial, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4779 0 CNhs10875 /home/drk/tillage/datasets/human/cage/fantom/CNhs10875/summary/coverage.w5 384 1 sum CAGE:Intestinal epithelial cells (polarized), CAGE CAGE/Intestinal epithelial cells (polarized), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4780 0 CNhs10876 /home/drk/tillage/datasets/human/cage/fantom/CNhs10876/summary/coverage.w5 384 1 sum CAGE:Anulus Pulposus Cell, CAGE CAGE/Anulus Pulposus Cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4781 0 CNhs10877 /home/drk/tillage/datasets/human/cage/fantom/CNhs10877/summary/coverage.w5 384 1 sum CAGE:Pancreatic stromal cells, CAGE CAGE/Pancreatic stromal cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4782 0 CNhs10878 /home/drk/tillage/datasets/human/cage/fantom/CNhs10878/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Pulmonary Artery, CAGE CAGE/Fibroblast - Pulmonary Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4783 0 CNhs10879 /home/drk/tillage/datasets/human/cage/fantom/CNhs10879/summary/coverage.w5 384 1 sum CAGE:Keratinocyte - oral, CAGE CAGE/Keratinocyte - oral, CAGE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4784 0 CNhs12019 /home/drk/tillage/datasets/human/cage/fantom/CNhs10881/summary/coverage.w5 384 1 sum CAGE:Nucleus Pulposus Cell, CAGE CAGE/Nucleus Pulposus Cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4785 0 CNhs10882 /home/drk/tillage/datasets/human/cage/fantom/CNhs10882/summary/coverage.w5 384 1 sum CAGE:Prostate Epithelial Cells (polarized), CAGE CAGE/Prostate Epithelial Cells (polarized), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4786 0 CNhs10883 /home/drk/tillage/datasets/human/cage/fantom/CNhs10883/summary/coverage.w5 384 1 sum CAGE:Prostate Stromal Cells, CAGE CAGE/Prostate Stromal Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4787 0 CNhs10884 /home/drk/tillage/datasets/human/cage/fantom/CNhs10884/summary/coverage.w5 384 1 sum CAGE:Small Airway Epithelial Cells, CAGE CAGE/Small Airway Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4788 0 CNhs11045 /home/drk/tillage/datasets/human/cage/fantom/CNhs11045/summary/coverage.w5 384 1 sum CAGE:cord blood derived cell line:COBL-a untreated CAGE CAGE/cord blood derived cell line:COBL-a untreated CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4789 0 CNhs11046 /home/drk/tillage/datasets/human/cage/fantom/CNhs11046/summary/coverage.w5 384 1 sum CAGE:embryonic kidney cell line: HEK293/SLAM untreated CAGE "CAGE/embryonic kidney cell line: HEK293;SLAM untreated" CAGE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4790 0 CNhs11047 /home/drk/tillage/datasets/human/cage/fantom/CNhs11047/summary/coverage.w5 384 1 sum CAGE:embryonic kidney cell line: HEK293/SLAM infection, 24hr CAGE "CAGE/embryonic kidney cell line: HEK293;SLAM infection, 24hr" CAGE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4791 0 CNhs11049 /home/drk/tillage/datasets/human/cage/fantom/CNhs11049/summary/coverage.w5 384 1 sum CAGE:cord blood derived cell line:COBL-a 24h infection(-C) CAGE CAGE/cord blood derived cell line:COBL-a 24h infection(-C) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4792 0 CNhs11050 /home/drk/tillage/datasets/human/cage/fantom/CNhs11050/summary/coverage.w5 384 1 sum CAGE:cord blood derived cell line:COBL-a 24h infection CAGE CAGE/cord blood derived cell line:COBL-a 24h infection CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4793 0 CNhs11969 /home/drk/tillage/datasets/human/cage/fantom/CNhs11051/summary/coverage.w5 384 1 sum CAGE:Adipocyte - breast, CAGE CAGE/Adipocyte - breast, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4794 0 CNhs11052 /home/drk/tillage/datasets/human/cage/fantom/CNhs11052/summary/coverage.w5 384 1 sum CAGE:Preadipocyte - breast, CAGE CAGE/Preadipocyte - breast, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4795 0 CNhs11054 /home/drk/tillage/datasets/human/cage/fantom/CNhs11054/summary/coverage.w5 384 1 sum CAGE:Adipocyte - omental, CAGE CAGE/Adipocyte - omental, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4796 0 CNhs11057 /home/drk/tillage/datasets/human/cage/fantom/CNhs11057/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - Wharton's Jelly, CAGE CAGE/Mesenchymal Stem Cells - Wharton's Jelly, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4797 0 CNhs11061 /home/drk/tillage/datasets/human/cage/fantom/CNhs11061/summary/coverage.w5 384 1 sum CAGE:Gingival epithelial cells, (GEA11) CAGE CAGE/Gingival epithelial cells, (GEA11) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4798 0 CNhs11384 /home/drk/tillage/datasets/human/cage/fantom/CNhs11063/summary/coverage.w5 384 1 sum CAGE:Neural stem cells, CAGE CAGE/Neural stem cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4799 0 CNhs11381 /home/drk/tillage/datasets/human/cage/fantom/CNhs11064/summary/coverage.w5 384 1 sum CAGE:Keratinocyte - epidermal, CAGE CAGE/Keratinocyte - epidermal, CAGE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4800 0 CNhs12013 /home/drk/tillage/datasets/human/cage/fantom/CNhs11065/summary/coverage.w5 384 1 sum CAGE:Preadipocyte - omental, CAGE CAGE/Preadipocyte - omental, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4801 0 CNhs12046 /home/drk/tillage/datasets/human/cage/fantom/CNhs11067/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Internal Thoracic Artery, CAGE CAGE/Smooth Muscle Cells - Internal Thoracic Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4802 0 CNhs12050 /home/drk/tillage/datasets/human/cage/fantom/CNhs11068/summary/coverage.w5 384 1 sum CAGE:Synoviocyte, CAGE CAGE/Synoviocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4803 0 CNhs11073 /home/drk/tillage/datasets/human/cage/fantom/CNhs11073/summary/coverage.w5 384 1 sum CAGE:Mast cell - stimulated, CAGE CAGE/Mast cell - stimulated, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4804 0 CNhs11074 /home/drk/tillage/datasets/human/cage/fantom/CNhs11074/summary/coverage.w5 384 1 sum CAGE:Fibroblast - skin spinal muscular atrophy, CAGE CAGE/Fibroblast - skin spinal muscular atrophy, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4805 0 CNhs11675 /home/drk/tillage/datasets/human/cage/fantom/CNhs11075/summary/coverage.w5 384 1 sum CAGE:Whole blood (ribopure), , donation1 CAGE CAGE/Whole blood (ribopure), , donation1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4806 0 CNhs11671 /home/drk/tillage/datasets/human/cage/fantom/CNhs11076/summary/coverage.w5 384 1 sum CAGE:Whole blood (ribopure), , donation2 CAGE CAGE/Whole blood (ribopure), , donation2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4807 0 CNhs11077 /home/drk/tillage/datasets/human/cage/fantom/CNhs11077/summary/coverage.w5 384 1 sum CAGE:Mammary Epithelial Cell, CAGE CAGE/Mammary Epithelial Cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4808 0 CNhs11385 /home/drk/tillage/datasets/human/cage/fantom/CNhs11078/summary/coverage.w5 384 1 sum CAGE:Osteoblast, CAGE CAGE/Osteoblast, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4809 0 CNhs11386 /home/drk/tillage/datasets/human/cage/fantom/CNhs11079/summary/coverage.w5 384 1 sum CAGE:Placental Epithelial Cells, CAGE CAGE/Placental Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4810 0 CNhs11981 /home/drk/tillage/datasets/human/cage/fantom/CNhs11081/summary/coverage.w5 384 1 sum CAGE:Preadipocyte - subcutaneous, CAGE CAGE/Preadipocyte - subcutaneous, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4811 0 CNhs11982 /home/drk/tillage/datasets/human/cage/fantom/CNhs11082/summary/coverage.w5 384 1 sum CAGE:Preadipocyte - visceral, CAGE CAGE/Preadipocyte - visceral, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4812 0 CNhs11983 /home/drk/tillage/datasets/human/cage/fantom/CNhs11083/summary/coverage.w5 384 1 sum CAGE:Skeletal Muscle Cells, CAGE CAGE/Skeletal Muscle Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4813 0 CNhs11984 /home/drk/tillage/datasets/human/cage/fantom/CNhs11084/summary/coverage.w5 384 1 sum CAGE:Skeletal muscle cells differentiated into Myotubes - multinucleated, CAGE CAGE/Skeletal muscle cells differentiated into Myotubes - multinucleated, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4814 0 CNhs11086 /home/drk/tillage/datasets/human/cage/fantom/CNhs11086/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Brachiocephalic, CAGE CAGE/Smooth Muscle Cells - Brachiocephalic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4815 0 CNhs11087 /home/drk/tillage/datasets/human/cage/fantom/CNhs11087/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Carotid, CAGE CAGE/Smooth Muscle Cells - Carotid, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4816 0 CNhs11987 /home/drk/tillage/datasets/human/cage/fantom/CNhs11088/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Coronary Artery, CAGE CAGE/Smooth Muscle Cells - Coronary Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4817 0 CNhs11089 /home/drk/tillage/datasets/human/cage/fantom/CNhs11089/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Pulmonary Artery, CAGE CAGE/Smooth Muscle Cells - Pulmonary Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4818 0 CNhs11090 /home/drk/tillage/datasets/human/cage/fantom/CNhs11090/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Subclavian Artery, CAGE CAGE/Smooth Muscle Cells - Subclavian Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4819 0 CNhs11091 /home/drk/tillage/datasets/human/cage/fantom/CNhs11091/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Umbilical Artery, CAGE CAGE/Smooth Muscle Cells - Umbilical Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4820 0 CNhs11092 /home/drk/tillage/datasets/human/cage/fantom/CNhs11092/summary/coverage.w5 384 1 sum CAGE:Tracheal Epithelial Cells, CAGE CAGE/Tracheal Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4821 0 CNhs11100 /home/drk/tillage/datasets/human/cage/fantom/CNhs11100/summary/coverage.w5 384 1 sum CAGE:ductal cell carcinoma cell line:KLM-1 CAGE CAGE/ductal cell carcinoma cell line:KLM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4822 0 CNhs11245 /home/drk/tillage/datasets/human/cage/fantom/CNhs11183/summary/coverage.w5 384 1 sum CAGE:schwannoma cell line:HS-PSS, tech_ CAGE CAGE/schwannoma cell line:HS-PSS, tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4823 0 CNhs11185 /home/drk/tillage/datasets/human/cage/fantom/CNhs11185/summary/coverage.w5 384 1 sum CAGE:glioblastoma cell line:A172, tech_ CAGE CAGE/glioblastoma cell line:A172, tech_ CAGE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4824 0 CNhs11243 /home/drk/tillage/datasets/human/cage/fantom/CNhs11243/summary/coverage.w5 384 1 sum CAGE:prostate cancer cell line:PC-3 CAGE CAGE/prostate cancer cell line:PC-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4825 0 CNhs11244 /home/drk/tillage/datasets/human/cage/fantom/CNhs11244/summary/coverage.w5 384 1 sum CAGE:synovial sarcoma cell line:HS-SY-II CAGE CAGE/synovial sarcoma cell line:HS-SY-II CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4826 0 CNhs11247 /home/drk/tillage/datasets/human/cage/fantom/CNhs11247/summary/coverage.w5 384 1 sum CAGE:epithelioid sarcoma cell line:HS-ES-1 CAGE CAGE/epithelioid sarcoma cell line:HS-ES-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4827 0 CNhs11249 /home/drk/tillage/datasets/human/cage/fantom/CNhs11249/summary/coverage.w5 384 1 sum CAGE:endometrial stromal sarcoma cell line:OMC-9 CAGE CAGE/endometrial stromal sarcoma cell line:OMC-9 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4828 0 CNhs11250 /home/drk/tillage/datasets/human/cage/fantom/CNhs11250/summary/coverage.w5 384 1 sum CAGE:chronic myelogenous leukemia cell line:K562 CAGE CAGE/chronic myelogenous leukemia cell line:K562 CAGE FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4829 0 CNhs11251 /home/drk/tillage/datasets/human/cage/fantom/CNhs11251/summary/coverage.w5 384 1 sum CAGE:acute lymphoblastic leukemia (B-ALL) cell line:BALL-1 CAGE CAGE/acute lymphoblastic leukemia (B-ALL) cell line:BALL-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4830 0 CNhs11252 /home/drk/tillage/datasets/human/cage/fantom/CNhs11252/summary/coverage.w5 384 1 sum CAGE:squamous cell carcinoma cell line:EC-GI-10 CAGE CAGE/squamous cell carcinoma cell line:EC-GI-10 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4831 0 CNhs11253 /home/drk/tillage/datasets/human/cage/fantom/CNhs11253/summary/coverage.w5 384 1 sum CAGE:acute lymphoblastic leukemia (T-ALL) cell line:Jurkat CAGE CAGE/acute lymphoblastic leukemia (T-ALL) cell line:Jurkat CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4832 0 CNhs11254 /home/drk/tillage/datasets/human/cage/fantom/CNhs11254/summary/coverage.w5 384 1 sum CAGE:melanoma cell line:G-361 CAGE CAGE/melanoma cell line:G-361 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4833 0 CNhs11255 /home/drk/tillage/datasets/human/cage/fantom/CNhs11255/summary/coverage.w5 384 1 sum CAGE:rectal cancer cell line:TT1TKB CAGE CAGE/rectal cancer cell line:TT1TKB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4834 0 CNhs11256 /home/drk/tillage/datasets/human/cage/fantom/CNhs11256/summary/coverage.w5 384 1 sum CAGE:gall bladder carcinoma cell line:TGBC14TKB CAGE CAGE/gall bladder carcinoma cell line:TGBC14TKB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4835 0 CNhs11257 /home/drk/tillage/datasets/human/cage/fantom/CNhs11257/summary/coverage.w5 384 1 sum CAGE:renal cell carcinoma cell line:TUHR10TKB CAGE CAGE/renal cell carcinoma cell line:TUHR10TKB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4836 0 CNhs11258 /home/drk/tillage/datasets/human/cage/fantom/CNhs11258/summary/coverage.w5 384 1 sum CAGE:myeloma cell line:PCM6 CAGE CAGE/myeloma cell line:PCM6 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4837 0 CNhs11259 /home/drk/tillage/datasets/human/cage/fantom/CNhs11259/summary/coverage.w5 384 1 sum CAGE:ductal cell carcinoma cell line:MIA Paca2 CAGE CAGE/ductal cell carcinoma cell line:MIA Paca2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4838 0 CNhs11260 /home/drk/tillage/datasets/human/cage/fantom/CNhs11260/summary/coverage.w5 384 1 sum CAGE:prostate cancer cell line:DU145 CAGE CAGE/prostate cancer cell line:DU145 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4839 0 CNhs11261 /home/drk/tillage/datasets/human/cage/fantom/CNhs11261/summary/coverage.w5 384 1 sum CAGE:transitional-cell carcinoma cell line:JMSU1 CAGE CAGE/transitional-cell carcinoma cell line:JMSU1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4840 0 CNhs11263 /home/drk/tillage/datasets/human/cage/fantom/CNhs11263/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:ACC-MESO-1 CAGE CAGE/mesothelioma cell line:ACC-MESO-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4841 0 CNhs11264 /home/drk/tillage/datasets/human/cage/fantom/CNhs11264/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:ACC-MESO-4 CAGE CAGE/mesothelioma cell line:ACC-MESO-4 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4842 0 CNhs11265 /home/drk/tillage/datasets/human/cage/fantom/CNhs11265/summary/coverage.w5 384 1 sum CAGE:bile duct carcinoma cell line:TFK-1 CAGE CAGE/bile duct carcinoma cell line:TFK-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4843 0 CNhs11266 /home/drk/tillage/datasets/human/cage/fantom/CNhs11266/summary/coverage.w5 384 1 sum CAGE:endometrial carcinoma cell line:OMC-2 CAGE CAGE/endometrial carcinoma cell line:OMC-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4844 0 CNhs11267 /home/drk/tillage/datasets/human/cage/fantom/CNhs11267/summary/coverage.w5 384 1 sum CAGE:retinoblastoma cell line:Y79 CAGE CAGE/retinoblastoma cell line:Y79 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4845 0 CNhs11268 /home/drk/tillage/datasets/human/cage/fantom/CNhs11268/summary/coverage.w5 384 1 sum CAGE:Burkitt's lymphoma cell line:RAJI CAGE CAGE/Burkitt's lymphoma cell line:RAJI CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4846 0 CNhs11269 /home/drk/tillage/datasets/human/cage/fantom/CNhs11269/summary/coverage.w5 384 1 sum CAGE:rhabdomyosarcoma cell line:RMS-YM CAGE CAGE/rhabdomyosarcoma cell line:RMS-YM CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4847 0 CNhs11270 /home/drk/tillage/datasets/human/cage/fantom/CNhs11270/summary/coverage.w5 384 1 sum CAGE:signet ring carcinoma cell line:NUGC-4 CAGE CAGE/signet ring carcinoma cell line:NUGC-4 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4848 0 CNhs11271 /home/drk/tillage/datasets/human/cage/fantom/CNhs11271/summary/coverage.w5 384 1 sum CAGE:hepatoma cell line:Li-7 CAGE CAGE/hepatoma cell line:Li-7 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4849 0 CNhs11272 /home/drk/tillage/datasets/human/cage/fantom/CNhs11272/summary/coverage.w5 384 1 sum CAGE:glioblastoma cell line:T98G CAGE CAGE/glioblastoma cell line:T98G CAGE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4850 0 CNhs11273 /home/drk/tillage/datasets/human/cage/fantom/CNhs11273/summary/coverage.w5 384 1 sum CAGE:squamous cell lung carcinoma cell line:EBC-1 CAGE CAGE/squamous cell lung carcinoma cell line:EBC-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4851 0 CNhs11274 /home/drk/tillage/datasets/human/cage/fantom/CNhs11274/summary/coverage.w5 384 1 sum CAGE:giant cell carcinoma cell line:LU65 CAGE CAGE/giant cell carcinoma cell line:LU65 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4852 0 CNhs11275 /home/drk/tillage/datasets/human/cage/fantom/CNhs11275/summary/coverage.w5 384 1 sum CAGE:lung adenocarcinoma cell line:A549 CAGE CAGE/lung adenocarcinoma cell line:A549 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4853 0 CNhs11276 /home/drk/tillage/datasets/human/cage/fantom/CNhs11276/summary/coverage.w5 384 1 sum CAGE:neuroblastoma cell line:CHP-134 CAGE CAGE/neuroblastoma cell line:CHP-134 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4854 0 CNhs11277 /home/drk/tillage/datasets/human/cage/fantom/CNhs11277/summary/coverage.w5 384 1 sum CAGE:large cell lung carcinoma cell line:IA-LM CAGE CAGE/large cell lung carcinoma cell line:IA-LM CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4855 0 CNhs11279 /home/drk/tillage/datasets/human/cage/fantom/CNhs11279/summary/coverage.w5 384 1 sum CAGE:osteosarcoma cell line:143B/TK^(-)neo^(R) CAGE "CAGE/osteosarcoma cell line:143B;TK^(-)neo^(R)" CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4856 0 CNhs11280 /home/drk/tillage/datasets/human/cage/fantom/CNhs11280/summary/coverage.w5 384 1 sum CAGE:colon carcinoma cell line:CACO-2 CAGE CAGE/colon carcinoma cell line:CACO-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4857 0 CNhs11281 /home/drk/tillage/datasets/human/cage/fantom/CNhs11281/summary/coverage.w5 384 1 sum CAGE:melanoma cell line:COLO 679 CAGE CAGE/melanoma cell line:COLO 679 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4858 0 CNhs11282 /home/drk/tillage/datasets/human/cage/fantom/CNhs11282/summary/coverage.w5 384 1 sum CAGE:acute lymphoblastic leukemia (B-ALL) cell line:NALM-6 CAGE CAGE/acute lymphoblastic leukemia (B-ALL) cell line:NALM-6 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4859 0 CNhs11283 /home/drk/tillage/datasets/human/cage/fantom/CNhs11283/summary/coverage.w5 384 1 sum CAGE:cholangiocellular carcinoma cell line:HuH-28 CAGE CAGE/cholangiocellular carcinoma cell line:HuH-28 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4860 0 CNhs11284 /home/drk/tillage/datasets/human/cage/fantom/CNhs11284/summary/coverage.w5 384 1 sum CAGE:neuroblastoma cell line:NB-1 CAGE CAGE/neuroblastoma cell line:NB-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4861 0 CNhs11285 /home/drk/tillage/datasets/human/cage/fantom/CNhs11285/summary/coverage.w5 384 1 sum CAGE:small cell lung carcinoma cell line:LK-2 CAGE CAGE/small cell lung carcinoma cell line:LK-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4862 0 CNhs11286 /home/drk/tillage/datasets/human/cage/fantom/CNhs11286/summary/coverage.w5 384 1 sum CAGE:gastric cancer cell line:AZ521 CAGE CAGE/gastric cancer cell line:AZ521 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4863 0 CNhs11287 /home/drk/tillage/datasets/human/cage/fantom/CNhs11287/summary/coverage.w5 384 1 sum CAGE:oral squamous cell carcinoma cell line:HO-1-u-1 CAGE CAGE/oral squamous cell carcinoma cell line:HO-1-u-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4864 0 CNhs11288 /home/drk/tillage/datasets/human/cage/fantom/CNhs11288/summary/coverage.w5 384 1 sum CAGE:cervical cancer cell line:D98-AH2 CAGE CAGE/cervical cancer cell line:D98-AH2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4865 0 CNhs11289 /home/drk/tillage/datasets/human/cage/fantom/CNhs11289/summary/coverage.w5 384 1 sum CAGE:cervical cancer cell line:ME-180 CAGE CAGE/cervical cancer cell line:ME-180 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4866 0 CNhs11290 /home/drk/tillage/datasets/human/cage/fantom/CNhs11290/summary/coverage.w5 384 1 sum CAGE:osteosarcoma cell line:HS-Os-1 CAGE CAGE/osteosarcoma cell line:HS-Os-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4867 0 CNhs11303 /home/drk/tillage/datasets/human/cage/fantom/CNhs11303/summary/coverage.w5 384 1 sum CAGE:Melanocyte - light, CAGE CAGE/Melanocyte - light, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4868 0 CNhs12035 /home/drk/tillage/datasets/human/cage/fantom/CNhs11311/summary/coverage.w5 384 1 sum CAGE:Osteoblast - differentiated, CAGE CAGE/Osteoblast - differentiated, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4869 0 CNhs11344 /home/drk/tillage/datasets/human/cage/fantom/CNhs11316/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - bone marrow, CAGE CAGE/Mesenchymal Stem Cells - bone marrow, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4870 0 CNhs11317 /home/drk/tillage/datasets/human/cage/fantom/CNhs11317/summary/coverage.w5 384 1 sum CAGE:Pericytes, CAGE CAGE/Pericytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4871 0 CNhs11319 /home/drk/tillage/datasets/human/cage/fantom/CNhs11319/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Choroid Plexus, CAGE CAGE/Fibroblast - Choroid Plexus, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4872 0 CNhs12080 /home/drk/tillage/datasets/human/cage/fantom/CNhs11320/summary/coverage.w5 384 1 sum CAGE:Meningeal Cells, CAGE CAGE/Meningeal Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4873 0 CNhs12117 /home/drk/tillage/datasets/human/cage/fantom/CNhs11321/summary/coverage.w5 384 1 sum CAGE:Astrocyte - cerebellum, CAGE CAGE/Astrocyte - cerebellum, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4874 0 CNhs11322 /home/drk/tillage/datasets/human/cage/fantom/CNhs11322/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Lymphatic, CAGE CAGE/Fibroblast - Lymphatic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4875 0 CNhs12083 /home/drk/tillage/datasets/human/cage/fantom/CNhs11323/summary/coverage.w5 384 1 sum CAGE:Esophageal Epithelial Cells, CAGE CAGE/Esophageal Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4876 0 CNhs12727 /home/drk/tillage/datasets/human/cage/fantom/CNhs11324/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Esophageal, CAGE CAGE/Smooth Muscle Cells - Esophageal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4877 0 CNhs12084 /home/drk/tillage/datasets/human/cage/fantom/CNhs11325/summary/coverage.w5 384 1 sum CAGE:Alveolar Epithelial Cells, CAGE CAGE/Alveolar Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4878 0 CNhs12623 /home/drk/tillage/datasets/human/cage/fantom/CNhs11327/summary/coverage.w5 384 1 sum CAGE:Bronchial Epithelial Cell, CAGE CAGE/Bronchial Epithelial Cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4879 0 CNhs12348 /home/drk/tillage/datasets/human/cage/fantom/CNhs11328/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Bronchial, CAGE CAGE/Smooth Muscle Cells - Bronchial, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4880 0 CNhs12894 /home/drk/tillage/datasets/human/cage/fantom/CNhs11329/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Tracheal, CAGE CAGE/Smooth Muscle Cells - Tracheal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4881 0 CNhs11330 /home/drk/tillage/datasets/human/cage/fantom/CNhs11330/summary/coverage.w5 384 1 sum CAGE:Renal Proximal Tubular Epithelial Cell, CAGE CAGE/Renal Proximal Tubular Epithelial Cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4882 0 CNhs12728 /home/drk/tillage/datasets/human/cage/fantom/CNhs11331/summary/coverage.w5 384 1 sum CAGE:Renal Cortical Epithelial Cells, CAGE CAGE/Renal Cortical Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4883 0 CNhs11332 /home/drk/tillage/datasets/human/cage/fantom/CNhs11332/summary/coverage.w5 384 1 sum CAGE:Renal Epithelial Cells, CAGE CAGE/Renal Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4884 0 CNhs11333 /home/drk/tillage/datasets/human/cage/fantom/CNhs11333/summary/coverage.w5 384 1 sum CAGE:Renal Mesangial Cells, CAGE CAGE/Renal Mesangial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4885 0 CNhs12091 /home/drk/tillage/datasets/human/cage/fantom/CNhs11334/summary/coverage.w5 384 1 sum CAGE:Urothelial Cells, CAGE CAGE/Urothelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4886 0 CNhs12093 /home/drk/tillage/datasets/human/cage/fantom/CNhs11335/summary/coverage.w5 384 1 sum CAGE:Hepatic Stellate Cells (lipocyte), CAGE CAGE/Hepatic Stellate Cells (lipocyte), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4887 0 CNhs12123 /home/drk/tillage/datasets/human/cage/fantom/CNhs11336/summary/coverage.w5 384 1 sum CAGE:Corneal Epithelial Cells, CAGE CAGE/Corneal Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4888 0 CNhs12921 /home/drk/tillage/datasets/human/cage/fantom/CNhs11337/summary/coverage.w5 384 1 sum CAGE:Keratocytes, CAGE CAGE/Keratocytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4889 0 CNhs12734 /home/drk/tillage/datasets/human/cage/fantom/CNhs11339/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Conjunctival, CAGE CAGE/Fibroblast - Conjunctival, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4890 0 CNhs12124 /home/drk/tillage/datasets/human/cage/fantom/CNhs11340/summary/coverage.w5 384 1 sum CAGE:Trabecular Meshwork Cells, CAGE CAGE/Trabecular Meshwork Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4891 0 CNhs12125 /home/drk/tillage/datasets/human/cage/fantom/CNhs11341/summary/coverage.w5 384 1 sum CAGE:Amniotic Epithelial Cells, CAGE CAGE/Amniotic Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4892 0 CNhs11343 /home/drk/tillage/datasets/human/cage/fantom/CNhs11343/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Villous Mesenchymal, CAGE CAGE/Fibroblast - Villous Mesenchymal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4893 0 CNhs12922 /home/drk/tillage/datasets/human/cage/fantom/CNhs11345/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - adipose, CAGE CAGE/Mesenchymal Stem Cells - adipose, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4894 0 CNhs12730 /home/drk/tillage/datasets/human/cage/fantom/CNhs11346/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - hepatic, CAGE CAGE/Mesenchymal Stem Cells - hepatic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4895 0 CNhs11347 /home/drk/tillage/datasets/human/cage/fantom/CNhs11347/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - umbilical, CAGE CAGE/Mesenchymal Stem Cells - umbilical, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4896 0 CNhs11348 /home/drk/tillage/datasets/human/cage/fantom/CNhs11348/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Mammary, CAGE CAGE/Fibroblast - Mammary, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4897 0 CNhs11349 /home/drk/tillage/datasets/human/cage/fantom/CNhs11349/summary/coverage.w5 384 1 sum CAGE:Mesenchymal Stem Cells - amniotic membrane, CAGE CAGE/Mesenchymal Stem Cells - amniotic membrane, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4898 0 CNhs11350 /home/drk/tillage/datasets/human/cage/fantom/CNhs11350/summary/coverage.w5 384 1 sum CAGE:Multipotent Cord Blood Unrestricted Somatic Stem Cells, CAGE CAGE/Multipotent Cord Blood Unrestricted Somatic Stem Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4899 0 CNhs11351 /home/drk/tillage/datasets/human/cage/fantom/CNhs11351/summary/coverage.w5 384 1 sum CAGE:Fibroblast - skin normal, CAGE CAGE/Fibroblast - skin normal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4900 0 CNhs11352 /home/drk/tillage/datasets/human/cage/fantom/CNhs11352/summary/coverage.w5 384 1 sum CAGE:Fibroblast - skin walker warburg, CAGE CAGE/Fibroblast - skin walker warburg, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4901 0 CNhs11913 /home/drk/tillage/datasets/human/cage/fantom/CNhs11353/summary/coverage.w5 384 1 sum CAGE:Fibroblast - skin dystrophia myotonica, CAGE CAGE/Fibroblast - skin dystrophia myotonica, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4902 0 CNhs12017 /home/drk/tillage/datasets/human/cage/fantom/CNhs11371/summary/coverage.w5 384 1 sum CAGE:Adipocyte - subcutaneous, CAGE CAGE/Adipocyte - subcutaneous, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4903 0 CNhs11923 /home/drk/tillage/datasets/human/cage/fantom/CNhs11372/summary/coverage.w5 384 1 sum CAGE:Chondrocyte - de diff, CAGE CAGE/Chondrocyte - de diff, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4904 0 CNhs11373 /home/drk/tillage/datasets/human/cage/fantom/CNhs11373/summary/coverage.w5 384 1 sum CAGE:Chondrocyte - re diff, CAGE CAGE/Chondrocyte - re diff, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4905 0 CNhs12024 /home/drk/tillage/datasets/human/cage/fantom/CNhs11376/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Microvascular, CAGE CAGE/Endothelial Cells - Microvascular, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4906 0 CNhs12026 /home/drk/tillage/datasets/human/cage/fantom/CNhs11377/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Vein, CAGE CAGE/Endothelial Cells - Vein, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4907 0 CNhs11909 /home/drk/tillage/datasets/human/cage/fantom/CNhs11378/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Cardiac, CAGE CAGE/Fibroblast - Cardiac, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4908 0 CNhs12499 /home/drk/tillage/datasets/human/cage/fantom/CNhs11379/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Dermal, CAGE CAGE/Fibroblast - Dermal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4909 0 CNhs12029 /home/drk/tillage/datasets/human/cage/fantom/CNhs11380/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Lung, CAGE CAGE/Fibroblast - Lung, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4910 0 CNhs11676 /home/drk/tillage/datasets/human/cage/fantom/CNhs11676/summary/coverage.w5 384 1 sum CAGE:uterus, adult, pool1 CAGE CAGE/uterus, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4911 0 CNhs11677 /home/drk/tillage/datasets/human/cage/fantom/CNhs11677/summary/coverage.w5 384 1 sum CAGE:salivary gland, adult, pool1 CAGE CAGE/salivary gland, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4912 0 CNhs11680 /home/drk/tillage/datasets/human/cage/fantom/CNhs11680/summary/coverage.w5 384 1 sum CAGE:lung, fetal, CAGE CAGE/lung, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4913 0 CNhs11714 /home/drk/tillage/datasets/human/cage/fantom/CNhs11714/summary/coverage.w5 384 1 sum CAGE:chronic lymphocytic leukemia (T-CLL) cell line:SKW-3 CAGE CAGE/chronic lymphocytic leukemia (T-CLL) cell line:SKW-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4914 0 CNhs11715 /home/drk/tillage/datasets/human/cage/fantom/CNhs11715/summary/coverage.w5 384 1 sum CAGE:Hodgkin's lymphoma cell line:HD-Mar2 CAGE CAGE/Hodgkin's lymphoma cell line:HD-Mar2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4915 0 CNhs11716 /home/drk/tillage/datasets/human/cage/fantom/CNhs11716/summary/coverage.w5 384 1 sum CAGE:papillary adenocarcinoma cell line:8505C CAGE CAGE/papillary adenocarcinoma cell line:8505C CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4916 0 CNhs11717 /home/drk/tillage/datasets/human/cage/fantom/CNhs11717/summary/coverage.w5 384 1 sum CAGE:oral squamous cell carcinoma cell line:HSC-3 CAGE CAGE/oral squamous cell carcinoma cell line:HSC-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4917 0 CNhs11718 /home/drk/tillage/datasets/human/cage/fantom/CNhs11718/summary/coverage.w5 384 1 sum CAGE:mesenchymal stem cell line:Hu5/E18 CAGE "CAGE/mesenchymal stem cell line:Hu5;E18" CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4918 0 CNhs11722 /home/drk/tillage/datasets/human/cage/fantom/CNhs11722/summary/coverage.w5 384 1 sum CAGE:leiomyoma cell line:10964C CAGE CAGE/leiomyoma cell line:10964C CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4919 0 CNhs11723 /home/drk/tillage/datasets/human/cage/fantom/CNhs11723/summary/coverage.w5 384 1 sum CAGE:leiomyoma cell line:15242A CAGE CAGE/leiomyoma cell line:15242A CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4920 0 CNhs11724 /home/drk/tillage/datasets/human/cage/fantom/CNhs11724/summary/coverage.w5 384 1 sum CAGE:leiomyoma cell line:15425 CAGE CAGE/leiomyoma cell line:15425 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4921 0 CNhs11725 /home/drk/tillage/datasets/human/cage/fantom/CNhs11725/summary/coverage.w5 384 1 sum CAGE:argyrophil small cell carcinoma cell line:TC-YIK CAGE CAGE/argyrophil small cell carcinoma cell line:TC-YIK CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4922 0 CNhs11726 /home/drk/tillage/datasets/human/cage/fantom/CNhs11726/summary/coverage.w5 384 1 sum CAGE:testicular germ cell embryonal carcinoma cell line:NEC8 CAGE CAGE/testicular germ cell embryonal carcinoma cell line:NEC8 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4923 0 CNhs11728 /home/drk/tillage/datasets/human/cage/fantom/CNhs11728/summary/coverage.w5 384 1 sum CAGE:Wilms' tumor cell line:HFWT CAGE CAGE/Wilms' tumor cell line:HFWT CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4924 0 CNhs11729 /home/drk/tillage/datasets/human/cage/fantom/CNhs11729/summary/coverage.w5 384 1 sum CAGE:myxofibrosarcoma cell line:MFH-ino CAGE CAGE/myxofibrosarcoma cell line:MFH-ino CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4925 0 CNhs11731 /home/drk/tillage/datasets/human/cage/fantom/CNhs11731/summary/coverage.w5 384 1 sum CAGE:embryonic pancreas cell line:1B2C6 CAGE CAGE/embryonic pancreas cell line:1B2C6 CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4926 0 CNhs11732 /home/drk/tillage/datasets/human/cage/fantom/CNhs11732/summary/coverage.w5 384 1 sum CAGE:embryonic pancreas cell line:1C3D3 CAGE CAGE/embryonic pancreas cell line:1C3D3 CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4927 0 CNhs11733 /home/drk/tillage/datasets/human/cage/fantom/CNhs11733/summary/coverage.w5 384 1 sum CAGE:embryonic pancreas cell line:1C3IKEI CAGE CAGE/embryonic pancreas cell line:1C3IKEI CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4928 0 CNhs11734 /home/drk/tillage/datasets/human/cage/fantom/CNhs11734/summary/coverage.w5 384 1 sum CAGE:small-cell gastrointestinal carcinoma cell line:ECC4 CAGE CAGE/small-cell gastrointestinal carcinoma cell line:ECC4 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4929 0 CNhs11736 /home/drk/tillage/datasets/human/cage/fantom/CNhs11736/summary/coverage.w5 384 1 sum CAGE:small cell gastrointestinal carcinoma cell line:ECC10 CAGE CAGE/small cell gastrointestinal carcinoma cell line:ECC10 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4930 0 CNhs11737 /home/drk/tillage/datasets/human/cage/fantom/CNhs11737/summary/coverage.w5 384 1 sum CAGE:gastric adenocarcinoma cell line:MKN1 CAGE CAGE/gastric adenocarcinoma cell line:MKN1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4931 0 CNhs11738 /home/drk/tillage/datasets/human/cage/fantom/CNhs11738/summary/coverage.w5 384 1 sum CAGE:gastrointestinal carcinoma cell line:ECC12 CAGE CAGE/gastrointestinal carcinoma cell line:ECC12 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4932 0 CNhs11739 /home/drk/tillage/datasets/human/cage/fantom/CNhs11739/summary/coverage.w5 384 1 sum CAGE:squamous cell carcinoma cell line:T3M-5 CAGE CAGE/squamous cell carcinoma cell line:T3M-5 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4933 0 CNhs11740 /home/drk/tillage/datasets/human/cage/fantom/CNhs11740/summary/coverage.w5 384 1 sum CAGE:granulosa cell tumor cell line:KGN CAGE CAGE/granulosa cell tumor cell line:KGN CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4934 0 CNhs11741 /home/drk/tillage/datasets/human/cage/fantom/CNhs11741/summary/coverage.w5 384 1 sum CAGE:diffuse large B-cell lymphoma cell line:CTB-1 CAGE CAGE/diffuse large B-cell lymphoma cell line:CTB-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4935 0 CNhs11742 /home/drk/tillage/datasets/human/cage/fantom/CNhs11742/summary/coverage.w5 384 1 sum CAGE:hepatoblastoma cell line:HuH-6 CAGE CAGE/hepatoblastoma cell line:HuH-6 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4936 0 CNhs11744 /home/drk/tillage/datasets/human/cage/fantom/CNhs11744/summary/coverage.w5 384 1 sum CAGE:neuroectodermal tumor cell line:FU-RPNT-1 CAGE CAGE/neuroectodermal tumor cell line:FU-RPNT-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4937 0 CNhs11745 /home/drk/tillage/datasets/human/cage/fantom/CNhs11745/summary/coverage.w5 384 1 sum CAGE:clear cell carcinoma cell line:JHOC-5 CAGE CAGE/clear cell carcinoma cell line:JHOC-5 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4938 0 CNhs11746 /home/drk/tillage/datasets/human/cage/fantom/CNhs11746/summary/coverage.w5 384 1 sum CAGE:serous adenocarcinoma cell line:JHOS-2 CAGE CAGE/serous adenocarcinoma cell line:JHOS-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4939 0 CNhs11747 /home/drk/tillage/datasets/human/cage/fantom/CNhs11747/summary/coverage.w5 384 1 sum CAGE:carcinosarcoma cell line:JHUCS-1 CAGE CAGE/carcinosarcoma cell line:JHUCS-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4940 0 CNhs11748 /home/drk/tillage/datasets/human/cage/fantom/CNhs11748/summary/coverage.w5 384 1 sum CAGE:endometrioid adenocarcinoma cell line:JHUEM-1 CAGE CAGE/endometrioid adenocarcinoma cell line:JHUEM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4941 0 CNhs11749 /home/drk/tillage/datasets/human/cage/fantom/CNhs11749/summary/coverage.w5 384 1 sum CAGE:squamous cell carcinoma cell line:JHUS-nk1 CAGE CAGE/squamous cell carcinoma cell line:JHUS-nk1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4942 0 CNhs11750 /home/drk/tillage/datasets/human/cage/fantom/CNhs11750/summary/coverage.w5 384 1 sum CAGE:lens epithelial cell line:SRA 01/04 CAGE "CAGE/lens epithelial cell line:SRA 01;04" CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4943 0 CNhs11752 /home/drk/tillage/datasets/human/cage/fantom/CNhs11752/summary/coverage.w5 384 1 sum CAGE:mucinous adenocarcinoma cell line:JHOM-1 CAGE CAGE/mucinous adenocarcinoma cell line:JHOM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4944 0 CNhs11753 /home/drk/tillage/datasets/human/cage/fantom/CNhs11753/summary/coverage.w5 384 1 sum CAGE:neuroectodermal tumor cell line:FU-RPNT-2 CAGE CAGE/neuroectodermal tumor cell line:FU-RPNT-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4945 0 CNhs11755 /home/drk/tillage/datasets/human/cage/fantom/CNhs11755/summary/coverage.w5 384 1 sum CAGE:smooth muscle, adult, pool1 CAGE CAGE/smooth muscle, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4946 0 CNhs11756 /home/drk/tillage/datasets/human/cage/fantom/CNhs11756/summary/coverage.w5 384 1 sum CAGE:pancreas, adult, CAGE CAGE/pancreas, adult, CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4947 0 CNhs11757 /home/drk/tillage/datasets/human/cage/fantom/CNhs11757/summary/coverage.w5 384 1 sum CAGE:heart, adult, diseased post-infarction, CAGE CAGE/heart, adult, diseased post-infarction, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4948 0 CNhs11758 /home/drk/tillage/datasets/human/cage/fantom/CNhs11758/summary/coverage.w5 384 1 sum CAGE:heart, adult, diseased, CAGE CAGE/heart, adult, diseased, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4949 0 CNhs11760 /home/drk/tillage/datasets/human/cage/fantom/CNhs11760/summary/coverage.w5 384 1 sum CAGE:aorta, adult, pool1 CAGE CAGE/aorta, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4950 0 CNhs11761 /home/drk/tillage/datasets/human/cage/fantom/CNhs11761/summary/coverage.w5 384 1 sum CAGE:blood, adult, pool1 CAGE CAGE/blood, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4951 0 CNhs11762 /home/drk/tillage/datasets/human/cage/fantom/CNhs11762/summary/coverage.w5 384 1 sum CAGE:eye, fetal, CAGE CAGE/eye, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4952 0 CNhs11763 /home/drk/tillage/datasets/human/cage/fantom/CNhs11763/summary/coverage.w5 384 1 sum CAGE:uterus, fetal, CAGE CAGE/uterus, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4953 0 CNhs11764 /home/drk/tillage/datasets/human/cage/fantom/CNhs11764/summary/coverage.w5 384 1 sum CAGE:spinal cord, fetal, CAGE CAGE/spinal cord, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4954 0 CNhs11765 /home/drk/tillage/datasets/human/cage/fantom/CNhs11765/summary/coverage.w5 384 1 sum CAGE:umbilical cord, fetal, CAGE CAGE/umbilical cord, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4955 0 CNhs11766 /home/drk/tillage/datasets/human/cage/fantom/CNhs11766/summary/coverage.w5 384 1 sum CAGE:trachea, fetal, CAGE CAGE/trachea, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4956 0 CNhs11768 /home/drk/tillage/datasets/human/cage/fantom/CNhs11768/summary/coverage.w5 384 1 sum CAGE:tongue, fetal, CAGE CAGE/tongue, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4957 0 CNhs11769 /home/drk/tillage/datasets/human/cage/fantom/CNhs11769/summary/coverage.w5 384 1 sum CAGE:thyroid, fetal, CAGE CAGE/thyroid, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4958 0 CNhs11770 /home/drk/tillage/datasets/human/cage/fantom/CNhs11770/summary/coverage.w5 384 1 sum CAGE:throat, fetal, CAGE CAGE/throat, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4959 0 CNhs11771 /home/drk/tillage/datasets/human/cage/fantom/CNhs11771/summary/coverage.w5 384 1 sum CAGE:stomach, fetal, CAGE CAGE/stomach, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4960 0 CNhs11772 /home/drk/tillage/datasets/human/cage/fantom/CNhs11772/summary/coverage.w5 384 1 sum CAGE:temporal lobe, fetal, , tech_ CAGE CAGE/temporal lobe, fetal, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4961 0 CNhs11773 /home/drk/tillage/datasets/human/cage/fantom/CNhs11773/summary/coverage.w5 384 1 sum CAGE:small intestine, fetal, CAGE CAGE/small intestine, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4962 0 CNhs11774 /home/drk/tillage/datasets/human/cage/fantom/CNhs11774/summary/coverage.w5 384 1 sum CAGE:skin, fetal, CAGE CAGE/skin, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4963 0 CNhs11776 /home/drk/tillage/datasets/human/cage/fantom/CNhs11776/summary/coverage.w5 384 1 sum CAGE:skeletal muscle, fetal, CAGE CAGE/skeletal muscle, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4964 0 CNhs11777 /home/drk/tillage/datasets/human/cage/fantom/CNhs11777/summary/coverage.w5 384 1 sum CAGE:rectum, fetal, CAGE CAGE/rectum, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4965 0 CNhs11779 /home/drk/tillage/datasets/human/cage/fantom/CNhs11779/summary/coverage.w5 384 1 sum CAGE:diaphragm, fetal, CAGE CAGE/diaphragm, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4966 0 CNhs11780 /home/drk/tillage/datasets/human/cage/fantom/CNhs11780/summary/coverage.w5 384 1 sum CAGE:colon, fetal, CAGE CAGE/colon, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4967 0 CNhs12997 /home/drk/tillage/datasets/human/cage/fantom/CNhs11781/summary/coverage.w5 384 1 sum CAGE:duodenum, fetal, , tech_ CAGE CAGE/duodenum, fetal, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4968 0 CNhs11782 /home/drk/tillage/datasets/human/cage/fantom/CNhs11782/summary/coverage.w5 384 1 sum CAGE:parietal lobe, fetal, CAGE CAGE/parietal lobe, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4969 0 CNhs11784 /home/drk/tillage/datasets/human/cage/fantom/CNhs11784/summary/coverage.w5 384 1 sum CAGE:occipital lobe, fetal, CAGE CAGE/occipital lobe, fetal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4970 0 CNhs11785 /home/drk/tillage/datasets/human/cage/fantom/CNhs11785/summary/coverage.w5 384 1 sum CAGE:skin, adult, CAGE CAGE/skin, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4971 0 CNhs11786 /home/drk/tillage/datasets/human/cage/fantom/CNhs11786/summary/coverage.w5 384 1 sum CAGE:lung, right lower lobe, adult, CAGE CAGE/lung, right lower lobe, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4972 0 CNhs11787 /home/drk/tillage/datasets/human/cage/fantom/CNhs11787/summary/coverage.w5 384 1 sum CAGE:occipital lobe, adult, CAGE CAGE/occipital lobe, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4973 0 CNhs11788 /home/drk/tillage/datasets/human/cage/fantom/CNhs11788/summary/coverage.w5 384 1 sum CAGE:lymph node, adult, CAGE CAGE/lymph node, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4974 0 CNhs11789 /home/drk/tillage/datasets/human/cage/fantom/CNhs11789/summary/coverage.w5 384 1 sum CAGE:left ventricle, adult, CAGE CAGE/left ventricle, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4975 0 CNhs11790 /home/drk/tillage/datasets/human/cage/fantom/CNhs11790/summary/coverage.w5 384 1 sum CAGE:left atrium, adult, CAGE CAGE/left atrium, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4976 0 CNhs11792 /home/drk/tillage/datasets/human/cage/fantom/CNhs11792/summary/coverage.w5 384 1 sum CAGE:breast, adult, CAGE CAGE/breast, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4977 0 CNhs11793 /home/drk/tillage/datasets/human/cage/fantom/CNhs11793/summary/coverage.w5 384 1 sum CAGE:adrenal gland, adult, pool1 CAGE CAGE/adrenal gland, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4978 0 CNhs11794 /home/drk/tillage/datasets/human/cage/fantom/CNhs11794/summary/coverage.w5 384 1 sum CAGE:colon, adult, CAGE CAGE/colon, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4979 0 CNhs11795 /home/drk/tillage/datasets/human/cage/fantom/CNhs11795/summary/coverage.w5 384 1 sum CAGE:cerebellum, adult, pool1 CAGE CAGE/cerebellum, adult, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4980 0 CNhs11796 /home/drk/tillage/datasets/human/cage/fantom/CNhs11796/summary/coverage.w5 384 1 sum CAGE:brain, adult, CAGE CAGE/brain, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4981 0 CNhs11797 /home/drk/tillage/datasets/human/cage/fantom/CNhs11797/summary/coverage.w5 384 1 sum CAGE:brain, fetal, pool1 CAGE CAGE/brain, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4982 0 CNhs11798 /home/drk/tillage/datasets/human/cage/fantom/CNhs11798/summary/coverage.w5 384 1 sum CAGE:liver, fetal, pool1 CAGE CAGE/liver, fetal, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4983 0 CNhs11810 /home/drk/tillage/datasets/human/cage/fantom/CNhs11810/summary/coverage.w5 384 1 sum CAGE:oral squamous cell carcinoma cell line:SAS CAGE CAGE/oral squamous cell carcinoma cell line:SAS CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4984 0 CNhs11811 /home/drk/tillage/datasets/human/cage/fantom/CNhs11811/summary/coverage.w5 384 1 sum CAGE:neuroblastoma cell line:NH-12 CAGE CAGE/neuroblastoma cell line:NH-12 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4985 0 CNhs11812 /home/drk/tillage/datasets/human/cage/fantom/CNhs11812/summary/coverage.w5 384 1 sum CAGE:small cell lung carcinoma cell line:WA-hT CAGE CAGE/small cell lung carcinoma cell line:WA-hT CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4986 0 CNhs11813 /home/drk/tillage/datasets/human/cage/fantom/CNhs11813/summary/coverage.w5 384 1 sum CAGE:xeroderma pigentosum b cell line:XPL 17 CAGE CAGE/xeroderma pigentosum b cell line:XPL 17 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4987 0 CNhs11814 /home/drk/tillage/datasets/human/cage/fantom/CNhs11814/summary/coverage.w5 384 1 sum CAGE:embryonic pancreas cell line:2C6 CAGE CAGE/embryonic pancreas cell line:2C6 CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4988 0 CNhs11818 /home/drk/tillage/datasets/human/cage/fantom/CNhs11818/summary/coverage.w5 384 1 sum CAGE:neuroblastoma cell line:NBsusSR CAGE CAGE/neuroblastoma cell line:NBsusSR CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4989 0 CNhs11819 /home/drk/tillage/datasets/human/cage/fantom/CNhs11819/summary/coverage.w5 384 1 sum CAGE:gastric adenocarcinoma cell line:MKN45 CAGE CAGE/gastric adenocarcinoma cell line:MKN45 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4990 0 CNhs11820 /home/drk/tillage/datasets/human/cage/fantom/CNhs11820/summary/coverage.w5 384 1 sum CAGE:choriocarcinoma cell line:T3M-3 CAGE CAGE/choriocarcinoma cell line:T3M-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4991 0 CNhs11821 /home/drk/tillage/datasets/human/cage/fantom/CNhs11821/summary/coverage.w5 384 1 sum CAGE:myxofibrosarcoma cell line:NMFH-1 CAGE CAGE/myxofibrosarcoma cell line:NMFH-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4992 0 CNhs11822 /home/drk/tillage/datasets/human/cage/fantom/CNhs11822/summary/coverage.w5 384 1 sum CAGE:Krukenberg tumor cell line:HSKTC CAGE CAGE/Krukenberg tumor cell line:HSKTC CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4993 0 CNhs11824 /home/drk/tillage/datasets/human/cage/fantom/CNhs11824/summary/coverage.w5 384 1 sum CAGE:glassy cell carcinoma cell line:HOKUG CAGE CAGE/glassy cell carcinoma cell line:HOKUG CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4994 0 CNhs11825 /home/drk/tillage/datasets/human/cage/fantom/CNhs11825/summary/coverage.w5 384 1 sum CAGE:large cell non-keratinizing squamous carcinoma cell line:SKG-II-SF CAGE CAGE/large cell non-keratinizing squamous carcinoma cell line:SKG-II-SF CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4995 0 CNhs11827 /home/drk/tillage/datasets/human/cage/fantom/CNhs11827/summary/coverage.w5 384 1 sum CAGE:serous cystadenocarcinoma cell line:HTOA CAGE CAGE/serous cystadenocarcinoma cell line:HTOA CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4996 0 CNhs11828 /home/drk/tillage/datasets/human/cage/fantom/CNhs11828/summary/coverage.w5 384 1 sum CAGE:tridermal teratoma cell line:HGRT CAGE CAGE/tridermal teratoma cell line:HGRT CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4997 0 CNhs11829 /home/drk/tillage/datasets/human/cage/fantom/CNhs11829/summary/coverage.w5 384 1 sum CAGE:sacrococcigeal teratoma cell line:HTST CAGE CAGE/sacrococcigeal teratoma cell line:HTST CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4998 0 CNhs11830 /home/drk/tillage/datasets/human/cage/fantom/CNhs11830/summary/coverage.w5 384 1 sum CAGE:peripheral neuroectodermal tumor cell line:KU-SN CAGE CAGE/peripheral neuroectodermal tumor cell line:KU-SN CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +4999 0 CNhs11832 /home/drk/tillage/datasets/human/cage/fantom/CNhs11832/summary/coverage.w5 384 1 sum CAGE:pancreatic carcinoma cell line:NOR-P1 CAGE CAGE/pancreatic carcinoma cell line:NOR-P1 CAGE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5000 0 CNhs11833 /home/drk/tillage/datasets/human/cage/fantom/CNhs11833/summary/coverage.w5 384 1 sum CAGE:chondrosarcoma cell line:SW 1353 CAGE CAGE/chondrosarcoma cell line:SW 1353 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5001 0 CNhs11834 /home/drk/tillage/datasets/human/cage/fantom/CNhs11834/summary/coverage.w5 384 1 sum CAGE:carcinoid cell line:NCI-H1770 CAGE CAGE/carcinoid cell line:NCI-H1770 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5002 0 CNhs11835 /home/drk/tillage/datasets/human/cage/fantom/CNhs11835/summary/coverage.w5 384 1 sum CAGE:osteoclastoma cell line:Hs 706.T CAGE CAGE/osteoclastoma cell line:Hs 706.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5003 0 CNhs11836 /home/drk/tillage/datasets/human/cage/fantom/CNhs11836/summary/coverage.w5 384 1 sum CAGE:Ewing's sarcoma cell line:Hs 863.T CAGE CAGE/Ewing's sarcoma cell line:Hs 863.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5004 0 CNhs11837 /home/drk/tillage/datasets/human/cage/fantom/CNhs11837/summary/coverage.w5 384 1 sum CAGE:transitional cell carcinoma cell line:Hs 769.T CAGE CAGE/transitional cell carcinoma cell line:Hs 769.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5005 0 CNhs11838 /home/drk/tillage/datasets/human/cage/fantom/CNhs11838/summary/coverage.w5 384 1 sum CAGE:alveolar cell carcinoma cell line:SW 1573 CAGE CAGE/alveolar cell carcinoma cell line:SW 1573 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5006 0 CNhs11840 /home/drk/tillage/datasets/human/cage/fantom/CNhs11840/summary/coverage.w5 384 1 sum CAGE:bronchioalveolar carcinoma cell line:NCI-H358 CAGE CAGE/bronchioalveolar carcinoma cell line:NCI-H358 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5007 0 CNhs11841 /home/drk/tillage/datasets/human/cage/fantom/CNhs11841/summary/coverage.w5 384 1 sum CAGE:bronchogenic carcinoma cell line:ChaGo-K-1 CAGE CAGE/bronchogenic carcinoma cell line:ChaGo-K-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5008 0 CNhs11842 /home/drk/tillage/datasets/human/cage/fantom/CNhs11842/summary/coverage.w5 384 1 sum CAGE:fibrous histiocytoma cell line:GCT TIB-223 CAGE CAGE/fibrous histiocytoma cell line:GCT TIB-223 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5009 0 CNhs11843 /home/drk/tillage/datasets/human/cage/fantom/CNhs11843/summary/coverage.w5 384 1 sum CAGE:hairy cell leukemia cell line:Mo CAGE CAGE/hairy cell leukemia cell line:Mo CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5010 0 CNhs11844 /home/drk/tillage/datasets/human/cage/fantom/CNhs11844/summary/coverage.w5 384 1 sum CAGE:acantholytic squamous carcinoma cell line:HCC1806 CAGE CAGE/acantholytic squamous carcinoma cell line:HCC1806 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5011 0 CNhs11845 /home/drk/tillage/datasets/human/cage/fantom/CNhs11845/summary/coverage.w5 384 1 sum CAGE:biphenotypic B myelomonocytic leukemia cell line:MV-4-11 CAGE CAGE/biphenotypic B myelomonocytic leukemia cell line:MV-4-11 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5012 0 CNhs11846 /home/drk/tillage/datasets/human/cage/fantom/CNhs11846/summary/coverage.w5 384 1 sum CAGE:carcinoid cell line:SK-PN-DW CAGE CAGE/carcinoid cell line:SK-PN-DW CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5013 0 CNhs11848 /home/drk/tillage/datasets/human/cage/fantom/CNhs11848/summary/coverage.w5 384 1 sum CAGE:leiomyoblastoma cell line:G-402 CAGE CAGE/leiomyoblastoma cell line:G-402 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5014 0 CNhs11849 /home/drk/tillage/datasets/human/cage/fantom/CNhs11849/summary/coverage.w5 384 1 sum CAGE:pharyngeal carcinoma cell line:Detroit 562 CAGE CAGE/pharyngeal carcinoma cell line:Detroit 562 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5015 0 CNhs11851 /home/drk/tillage/datasets/human/cage/fantom/CNhs11851/summary/coverage.w5 384 1 sum CAGE:liposarcoma cell line:SW 872 CAGE CAGE/liposarcoma cell line:SW 872 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5016 0 CNhs11852 /home/drk/tillage/datasets/human/cage/fantom/CNhs11852/summary/coverage.w5 384 1 sum CAGE:lymphangiectasia cell line:DS-1 CAGE CAGE/lymphangiectasia cell line:DS-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5017 0 CNhs11853 /home/drk/tillage/datasets/human/cage/fantom/CNhs11853/summary/coverage.w5 384 1 sum CAGE:neuroepithelioma cell line:SK-N-MC CAGE CAGE/neuroepithelioma cell line:SK-N-MC CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5018 0 CNhs11854 /home/drk/tillage/datasets/human/cage/fantom/CNhs11854/summary/coverage.w5 384 1 sum CAGE:neurofibroma cell line:Hs 53.T CAGE CAGE/neurofibroma cell line:Hs 53.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5019 0 CNhs11856 /home/drk/tillage/datasets/human/cage/fantom/CNhs11856/summary/coverage.w5 384 1 sum CAGE:pagetoid sarcoma cell line:Hs 925.T CAGE CAGE/pagetoid sarcoma cell line:Hs 925.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5020 0 CNhs11857 /home/drk/tillage/datasets/human/cage/fantom/CNhs11857/summary/coverage.w5 384 1 sum CAGE:spindle cell sarcoma cell line:Hs 132.T CAGE CAGE/spindle cell sarcoma cell line:Hs 132.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5021 0 CNhs11858 /home/drk/tillage/datasets/human/cage/fantom/CNhs11858/summary/coverage.w5 384 1 sum CAGE:mycosis fungoides, T cell lymphoma cell line:HuT 102 TIB-162 CAGE CAGE/mycosis fungoides, T cell lymphoma cell line:HuT 102 TIB-162 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5022 0 CNhs11859 /home/drk/tillage/datasets/human/cage/fantom/CNhs11859/summary/coverage.w5 384 1 sum CAGE:leukemia, chronic megakaryoblastic cell line:MEG-01 CAGE CAGE/leukemia, chronic megakaryoblastic cell line:MEG-01 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5023 0 CNhs11860 /home/drk/tillage/datasets/human/cage/fantom/CNhs11860/summary/coverage.w5 384 1 sum CAGE:fibrosarcoma cell line:HT-1080 CAGE CAGE/fibrosarcoma cell line:HT-1080 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5024 0 CNhs11861 /home/drk/tillage/datasets/human/cage/fantom/CNhs11861/summary/coverage.w5 384 1 sum CAGE:medulloblastoma cell line:ONS-76 CAGE CAGE/medulloblastoma cell line:ONS-76 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5025 0 CNhs11862 /home/drk/tillage/datasets/human/cage/fantom/CNhs11862/summary/coverage.w5 384 1 sum CAGE:bronchial squamous cell carcinoma cell line:KNS-62 CAGE CAGE/bronchial squamous cell carcinoma cell line:KNS-62 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5026 0 CNhs11864 /home/drk/tillage/datasets/human/cage/fantom/CNhs11864/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M2) cell line:NKM-1 CAGE CAGE/acute myeloid leukemia (FAB M2) cell line:NKM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5027 0 CNhs11865 /home/drk/tillage/datasets/human/cage/fantom/CNhs11865/summary/coverage.w5 384 1 sum CAGE:chronic myelogenous leukemia (CML) cell line:MEG-A2 CAGE CAGE/chronic myelogenous leukemia (CML) cell line:MEG-A2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5028 0 CNhs11866 /home/drk/tillage/datasets/human/cage/fantom/CNhs11866/summary/coverage.w5 384 1 sum CAGE:neuroectodermal tumor cell line:TASK1 CAGE CAGE/neuroectodermal tumor cell line:TASK1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5029 0 CNhs11867 /home/drk/tillage/datasets/human/cage/fantom/CNhs11867/summary/coverage.w5 384 1 sum CAGE:NK T cell leukemia cell line:KHYG-1 CAGE CAGE/NK T cell leukemia cell line:KHYG-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5030 0 CNhs11868 /home/drk/tillage/datasets/human/cage/fantom/CNhs11868/summary/coverage.w5 384 1 sum CAGE:hepatic mesenchymal tumor cell line:LI90 CAGE CAGE/hepatic mesenchymal tumor cell line:LI90 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5031 0 CNhs11869 /home/drk/tillage/datasets/human/cage/fantom/CNhs11869/summary/coverage.w5 384 1 sum CAGE:somatostatinoma cell line:QGP-1 CAGE CAGE/somatostatinoma cell line:QGP-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5032 0 CNhs11870 /home/drk/tillage/datasets/human/cage/fantom/CNhs11870/summary/coverage.w5 384 1 sum CAGE:liposarcoma cell line:KMLS-1 CAGE CAGE/liposarcoma cell line:KMLS-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5033 0 CNhs11872 /home/drk/tillage/datasets/human/cage/fantom/CNhs11872/summary/coverage.w5 384 1 sum CAGE:thyroid carcinoma cell line:TCO-1 CAGE CAGE/thyroid carcinoma cell line:TCO-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5034 0 CNhs11873 /home/drk/tillage/datasets/human/cage/fantom/CNhs11873/summary/coverage.w5 384 1 sum CAGE:mucinous cystadenocarcinoma cell line:MCAS CAGE CAGE/mucinous cystadenocarcinoma cell line:MCAS CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5035 0 CNhs11875 /home/drk/tillage/datasets/human/cage/fantom/CNhs11875/summary/coverage.w5 384 1 sum CAGE:choriocarcinoma cell line:SCH CAGE CAGE/choriocarcinoma cell line:SCH CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5036 0 CNhs11876 /home/drk/tillage/datasets/human/cage/fantom/CNhs11876/summary/coverage.w5 384 1 sum CAGE:testicular germ cell embryonal carcinoma cell line:ITO-II CAGE CAGE/testicular germ cell embryonal carcinoma cell line:ITO-II CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5037 0 CNhs11877 /home/drk/tillage/datasets/human/cage/fantom/CNhs11877/summary/coverage.w5 384 1 sum CAGE:rhabdomyosarcoma cell line:KYM-1 CAGE CAGE/rhabdomyosarcoma cell line:KYM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5038 0 CNhs11878 /home/drk/tillage/datasets/human/cage/fantom/CNhs11878/summary/coverage.w5 384 1 sum CAGE:teratocarcinoma cell line:NCC-IT-A3 CAGE CAGE/teratocarcinoma cell line:NCC-IT-A3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5039 0 CNhs11880 /home/drk/tillage/datasets/human/cage/fantom/CNhs11880/summary/coverage.w5 384 1 sum CAGE:keratoacanthoma cell line:HKA-1 CAGE CAGE/keratoacanthoma cell line:HKA-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5040 0 CNhs11881 /home/drk/tillage/datasets/human/cage/fantom/CNhs11881/summary/coverage.w5 384 1 sum CAGE:anaplastic large cell lymphoma cell line:Ki-JK CAGE CAGE/anaplastic large cell lymphoma cell line:Ki-JK CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5041 0 CNhs11882 /home/drk/tillage/datasets/human/cage/fantom/CNhs11882/summary/coverage.w5 384 1 sum CAGE:adenocarcinoma cell line:IM95m CAGE CAGE/adenocarcinoma cell line:IM95m CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5042 0 CNhs11883 /home/drk/tillage/datasets/human/cage/fantom/CNhs11883/summary/coverage.w5 384 1 sum CAGE:tubular adenocarcinoma cell line:SUIT-2 CAGE CAGE/tubular adenocarcinoma cell line:SUIT-2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5043 0 CNhs11884 /home/drk/tillage/datasets/human/cage/fantom/CNhs11884/summary/coverage.w5 384 1 sum CAGE:teratocarcinoma cell line:NCR-G1 CAGE CAGE/teratocarcinoma cell line:NCR-G1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5044 0 CNhs11885 /home/drk/tillage/datasets/human/cage/fantom/CNhs11885/summary/coverage.w5 384 1 sum CAGE:small cell cervical cancer cell line:HCSC-1 CAGE CAGE/small cell cervical cancer cell line:HCSC-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5045 0 CNhs11886 /home/drk/tillage/datasets/human/cage/fantom/CNhs11886/summary/coverage.w5 384 1 sum CAGE:chronic myeloblastic leukemia (CML) cell line:KCL-22 CAGE CAGE/chronic myeloblastic leukemia (CML) cell line:KCL-22 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5046 0 CNhs11888 /home/drk/tillage/datasets/human/cage/fantom/CNhs11888/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M7) cell line:MKPL-1 CAGE CAGE/acute myeloid leukemia (FAB M7) cell line:MKPL-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5047 0 CNhs11889 /home/drk/tillage/datasets/human/cage/fantom/CNhs11889/summary/coverage.w5 384 1 sum CAGE:anaplastic squamous cell carcinoma cell line:RPMI 2650 CAGE CAGE/anaplastic squamous cell carcinoma cell line:RPMI 2650 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5048 0 CNhs11890 /home/drk/tillage/datasets/human/cage/fantom/CNhs11890/summary/coverage.w5 384 1 sum CAGE:teratocarcinoma cell line:PA-1 CAGE CAGE/teratocarcinoma cell line:PA-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5049 0 CNhs11891 /home/drk/tillage/datasets/human/cage/fantom/CNhs11891/summary/coverage.w5 384 1 sum CAGE:hereditary spherocytic anemia cell line:WIL2-NS CAGE CAGE/hereditary spherocytic anemia cell line:WIL2-NS CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5050 0 CNhs11892 /home/drk/tillage/datasets/human/cage/fantom/CNhs11892/summary/coverage.w5 384 1 sum CAGE:Wilms' tumor cell line:G-401 CAGE CAGE/Wilms' tumor cell line:G-401 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5051 0 CNhs11893 /home/drk/tillage/datasets/human/cage/fantom/CNhs11893/summary/coverage.w5 384 1 sum CAGE:adrenal cortex adenocarcinoma cell line:SW-13 CAGE CAGE/adrenal cortex adenocarcinoma cell line:SW-13 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5052 0 CNhs11894 /home/drk/tillage/datasets/human/cage/fantom/CNhs11894/summary/coverage.w5 384 1 sum CAGE:normal embryonic palatal mesenchymal cell line:HEPM CAGE CAGE/normal embryonic palatal mesenchymal cell line:HEPM CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5053 0 CNhs11896 /home/drk/tillage/datasets/human/cage/fantom/CNhs11896/summary/coverage.w5 384 1 sum CAGE:Gingival epithelial cells, (GEA14) CAGE CAGE/Gingival epithelial cells, (GEA14) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5054 0 CNhs11903 /home/drk/tillage/datasets/human/cage/fantom/CNhs11903/summary/coverage.w5 384 1 sum CAGE:Gingival epithelial cells, (GEA15) CAGE CAGE/Gingival epithelial cells, (GEA15) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5055 0 CNhs11910 /home/drk/tillage/datasets/human/cage/fantom/CNhs11910/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Prostate, CAGE CAGE/Smooth Muscle Cells - Prostate, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5056 0 CNhs11927 /home/drk/tillage/datasets/human/cage/fantom/CNhs11921/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Uterine, CAGE CAGE/Smooth Muscle Cells - Uterine, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5057 0 CNhs11978 /home/drk/tillage/datasets/human/cage/fantom/CNhs11926/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Thoracic, CAGE CAGE/Endothelial Cells - Thoracic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5058 0 CNhs11930 /home/drk/tillage/datasets/human/cage/fantom/CNhs11930/summary/coverage.w5 384 1 sum CAGE:clear cell carcinoma cell line:TEN CAGE CAGE/clear cell carcinoma cell line:TEN CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5059 0 CNhs11931 /home/drk/tillage/datasets/human/cage/fantom/CNhs11931/summary/coverage.w5 384 1 sum CAGE:bone marrow stromal cell line:StromaNKtert CAGE CAGE/bone marrow stromal cell line:StromaNKtert CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5060 0 CNhs11932 /home/drk/tillage/datasets/human/cage/fantom/CNhs11932/summary/coverage.w5 384 1 sum CAGE:basal cell carcinoma cell line:TE 354.T CAGE CAGE/basal cell carcinoma cell line:TE 354.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5061 0 CNhs11933 /home/drk/tillage/datasets/human/cage/fantom/CNhs11933/summary/coverage.w5 384 1 sum CAGE:pleomorphic hepatocellular carcinoma cell line:SNU-387 CAGE CAGE/pleomorphic hepatocellular carcinoma cell line:SNU-387 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5062 0 CNhs11934 /home/drk/tillage/datasets/human/cage/fantom/CNhs11934/summary/coverage.w5 384 1 sum CAGE:myelodysplastic syndrome cell line:SKM-1 CAGE CAGE/myelodysplastic syndrome cell line:SKM-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5063 0 CNhs11935 /home/drk/tillage/datasets/human/cage/fantom/CNhs11935/summary/coverage.w5 384 1 sum CAGE:lymphoma, malignant, hairy B-cell cell line:MLMA CAGE CAGE/lymphoma, malignant, hairy B-cell cell line:MLMA CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5064 0 CNhs11943 /home/drk/tillage/datasets/human/cage/fantom/CNhs11943/summary/coverage.w5 384 1 sum CAGE:breast carcinoma cell line:MCF7 CAGE CAGE/breast carcinoma cell line:MCF7 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5065 0 CNhs11944 /home/drk/tillage/datasets/human/cage/fantom/CNhs11944/summary/coverage.w5 384 1 sum CAGE:mixed mullerian tumor cell line:HTMMT CAGE CAGE/mixed mullerian tumor cell line:HTMMT CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5066 0 CNhs11945 /home/drk/tillage/datasets/human/cage/fantom/CNhs11945/summary/coverage.w5 384 1 sum CAGE:meningioma cell line:HKBMM CAGE CAGE/meningioma cell line:HKBMM CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5067 0 CNhs11949 /home/drk/tillage/datasets/human/cage/fantom/CNhs11948/summary/coverage.w5 384 1 sum CAGE:Whole blood (ribopure), , donation3 CAGE CAGE/Whole blood (ribopure), , donation3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5068 0 CNhs11950 /home/drk/tillage/datasets/human/cage/fantom/CNhs11950/summary/coverage.w5 384 1 sum CAGE:normal intestinal epithelial cell line:FHs 74 Int CAGE CAGE/normal intestinal epithelial cell line:FHs 74 Int CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5069 0 CNhs11952 /home/drk/tillage/datasets/human/cage/fantom/CNhs11952/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (GFH3) CAGE CAGE/Fibroblast - Gingival, (GFH3) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5070 0 CNhs11953 /home/drk/tillage/datasets/human/cage/fantom/CNhs11953/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Periodontal Ligament, (PL30) CAGE CAGE/Fibroblast - Periodontal Ligament, (PL30) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5071 0 CNhs12014 /home/drk/tillage/datasets/human/cage/fantom/CNhs11972/summary/coverage.w5 384 1 sum CAGE:Prostate Epithelial Cells, CAGE CAGE/Prostate Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5072 0 CNhs11977 /home/drk/tillage/datasets/human/cage/fantom/CNhs11977/summary/coverage.w5 384 1 sum CAGE:Endothelial Cells - Artery, CAGE CAGE/Endothelial Cells - Artery, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5073 0 CNhs11979 /home/drk/tillage/datasets/human/cage/fantom/CNhs11979/summary/coverage.w5 384 1 sum CAGE:Hair Follicle Dermal Papilla Cells, CAGE CAGE/Hair Follicle Dermal Papilla Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5074 0 CNhs11996 /home/drk/tillage/datasets/human/cage/fantom/CNhs11996/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Periodontal Ligament, (PLH3) CAGE CAGE/Fibroblast - Periodontal Ligament, (PLH3) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5075 0 CNhs12195 /home/drk/tillage/datasets/human/cage/fantom/CNhs12000/summary/coverage.w5 384 1 sum CAGE:Dendritic Cells - monocyte immature derived, CAGE CAGE/Dendritic Cells - monocyte immature derived, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5076 0 CNhs12065 /home/drk/tillage/datasets/human/cage/fantom/CNhs12065/summary/coverage.w5 384 1 sum CAGE:Preadipocyte - perirenal, CAGE CAGE/Preadipocyte - perirenal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5077 0 CNhs12069 /home/drk/tillage/datasets/human/cage/fantom/CNhs12069/summary/coverage.w5 384 1 sum CAGE:Adipocyte - perirenal, CAGE CAGE/Adipocyte - perirenal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5078 0 CNhs12073 /home/drk/tillage/datasets/human/cage/fantom/CNhs12073/summary/coverage.w5 384 1 sum CAGE:Schwann Cells, CAGE CAGE/Schwann Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5079 0 CNhs12086 /home/drk/tillage/datasets/human/cage/fantom/CNhs12074/summary/coverage.w5 384 1 sum CAGE:Renal Glomerular Endothelial Cells, CAGE CAGE/Renal Glomerular Endothelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5080 0 CNhs12092 /home/drk/tillage/datasets/human/cage/fantom/CNhs12075/summary/coverage.w5 384 1 sum CAGE:Hepatic Sinusoidal Endothelial Cells, CAGE CAGE/Hepatic Sinusoidal Endothelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5081 0 CNhs12179 /home/drk/tillage/datasets/human/cage/fantom/CNhs12175/summary/coverage.w5 384 1 sum CAGE:CD19+ B Cells (pluriselect), , donation2 CAGE CAGE/CD19+ B Cells (pluriselect), , donation2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5082 0 CNhs12182 /home/drk/tillage/datasets/human/cage/fantom/CNhs12176/summary/coverage.w5 384 1 sum CAGE:CD8+ T Cells (pluriselect), , donation1 CAGE CAGE/CD8+ T Cells (pluriselect), , donation1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5083 0 CNhs12531 /home/drk/tillage/datasets/human/cage/fantom/CNhs12177/summary/coverage.w5 384 1 sum CAGE:CD19+ B Cells (pluriselect), , donation1 CAGE CAGE/CD19+ B Cells (pluriselect), , donation1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5084 0 CNhs12178 /home/drk/tillage/datasets/human/cage/fantom/CNhs12178/summary/coverage.w5 384 1 sum CAGE:CD8+ T Cells (pluriselect), , donation2 CAGE CAGE/CD8+ T Cells (pluriselect), , donation2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5085 0 CNhs12187 /home/drk/tillage/datasets/human/cage/fantom/CNhs12180/summary/coverage.w5 384 1 sum CAGE:CD8+ T Cells (pluriselect), , donation3 CAGE CAGE/CD8+ T Cells (pluriselect), , donation3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5086 0 CNhs12181 /home/drk/tillage/datasets/human/cage/fantom/CNhs12181/summary/coverage.w5 384 1 sum CAGE:CD19+ B Cells (pluriselect), , donation3 CAGE CAGE/CD19+ B Cells (pluriselect), , donation3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5087 0 CNhs12191 /home/drk/tillage/datasets/human/cage/fantom/CNhs12191/summary/coverage.w5 384 1 sum CAGE:mesodermal tumor cell line:HIRS-BM CAGE CAGE/mesodermal tumor cell line:HIRS-BM CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5088 0 CNhs12192 /home/drk/tillage/datasets/human/cage/fantom/CNhs12192/summary/coverage.w5 384 1 sum CAGE:leiomyosarcoma cell line:Hs 5.T CAGE CAGE/leiomyosarcoma cell line:Hs 5.T CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5089 0 CNhs12193 /home/drk/tillage/datasets/human/cage/fantom/CNhs12193/summary/coverage.w5 384 1 sum CAGE:non-small cell lung cancer cell line:NCI-H1385 CAGE CAGE/non-small cell lung cancer cell line:NCI-H1385 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5090 0 CNhs13227 /home/drk/tillage/datasets/human/cage/fantom/CNhs12205/summary/coverage.w5 384 1 sum CAGE:CD34+ Progenitors, CAGE CAGE/CD34+ Progenitors, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5091 0 CNhs14222 /home/drk/tillage/datasets/human/cage/fantom/CNhs12227/summary/coverage.w5 384 1 sum CAGE:spinal cord, adult, CAGE CAGE/spinal cord, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5092 0 CNhs14230 /home/drk/tillage/datasets/human/cage/fantom/CNhs12228/summary/coverage.w5 384 1 sum CAGE:pineal gland, adult, CAGE CAGE/pineal gland, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5093 0 CNhs14231 /home/drk/tillage/datasets/human/cage/fantom/CNhs12229/summary/coverage.w5 384 1 sum CAGE:pituitary gland, adult, CAGE CAGE/pituitary gland, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5094 0 CNhs12310 /home/drk/tillage/datasets/human/cage/fantom/CNhs12310/summary/coverage.w5 384 1 sum CAGE:medial frontal gyrus, adult, CAGE CAGE/medial frontal gyrus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5095 0 CNhs12311 /home/drk/tillage/datasets/human/cage/fantom/CNhs12311/summary/coverage.w5 384 1 sum CAGE:amygdala, adult, CAGE CAGE/amygdala, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5096 0 CNhs12312 /home/drk/tillage/datasets/human/cage/fantom/CNhs12312/summary/coverage.w5 384 1 sum CAGE:hippocampus, adult, CAGE CAGE/hippocampus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5097 0 CNhs12314 /home/drk/tillage/datasets/human/cage/fantom/CNhs12314/summary/coverage.w5 384 1 sum CAGE:thalamus, adult, CAGE CAGE/thalamus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5098 0 CNhs12315 /home/drk/tillage/datasets/human/cage/fantom/CNhs12315/summary/coverage.w5 384 1 sum CAGE:medulla oblongata, adult, CAGE CAGE/medulla oblongata, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5099 0 CNhs12316 /home/drk/tillage/datasets/human/cage/fantom/CNhs12316/summary/coverage.w5 384 1 sum CAGE:medial temporal gyrus, adult, CAGE CAGE/medial temporal gyrus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5100 0 CNhs12317 /home/drk/tillage/datasets/human/cage/fantom/CNhs12317/summary/coverage.w5 384 1 sum CAGE:parietal lobe, adult, CAGE CAGE/parietal lobe, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5101 0 CNhs12318 /home/drk/tillage/datasets/human/cage/fantom/CNhs12318/summary/coverage.w5 384 1 sum CAGE:substantia nigra, adult, CAGE CAGE/substantia nigra, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5102 0 CNhs12319 /home/drk/tillage/datasets/human/cage/fantom/CNhs12319/summary/coverage.w5 384 1 sum CAGE:globus pallidus, adult, CAGE CAGE/globus pallidus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5103 0 CNhs12320 /home/drk/tillage/datasets/human/cage/fantom/CNhs12320/summary/coverage.w5 384 1 sum CAGE:occipital cortex, adult, CAGE CAGE/occipital cortex, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5104 0 CNhs12321 /home/drk/tillage/datasets/human/cage/fantom/CNhs12321/summary/coverage.w5 384 1 sum CAGE:caudate nucleus, adult, CAGE CAGE/caudate nucleus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5105 0 CNhs14550 /home/drk/tillage/datasets/human/cage/fantom/CNhs12322/summary/coverage.w5 384 1 sum CAGE:locus coeruleus, adult, CAGE CAGE/locus coeruleus, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5106 0 CNhs12323 /home/drk/tillage/datasets/human/cage/fantom/CNhs12323/summary/coverage.w5 384 1 sum CAGE:cerebellum, adult, CAGE CAGE/cerebellum, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5107 0 CNhs13912 /home/drk/tillage/datasets/human/cage/fantom/CNhs12324/summary/coverage.w5 384 1 sum CAGE:putamen, adult, CAGE CAGE/putamen, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5108 0 CNhs12326 /home/drk/tillage/datasets/human/cage/fantom/CNhs12325/summary/coverage.w5 384 1 sum CAGE:epitheloid carcinoma cell line: HelaS3 ENCODE, biol_ CAGE CAGE/epitheloid carcinoma cell line: HelaS3 ENCODE, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5109 0 CNhs12328 /home/drk/tillage/datasets/human/cage/fantom/CNhs12328/summary/coverage.w5 384 1 sum CAGE:hepatocellular carcinoma cell line: HepG2 ENCODE, biol_ CAGE CAGE/hepatocellular carcinoma cell line: HepG2 ENCODE, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE +5110 0 CNhs12333 /home/drk/tillage/datasets/human/cage/fantom/CNhs12331/summary/coverage.w5 384 1 sum CAGE:B lymphoblastoid cell line: GM12878 ENCODE, biol_ CAGE CAGE/B lymphoblastoid cell line: GM12878 ENCODE, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5111 0 CNhs12336 /home/drk/tillage/datasets/human/cage/fantom/CNhs12334/summary/coverage.w5 384 1 sum CAGE:chronic myelogenous leukemia cell line:K562 ENCODE, biol_ CAGE CAGE/chronic myelogenous leukemia cell line:K562 ENCODE, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5112 0 CNhs12338 /home/drk/tillage/datasets/human/cage/fantom/CNhs12338/summary/coverage.w5 384 1 sum CAGE:Neurons, CAGE CAGE/Neurons, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5113 0 CNhs12347 /home/drk/tillage/datasets/human/cage/fantom/CNhs12339/summary/coverage.w5 384 1 sum CAGE:Hair Follicle Outer Root Sheath Cells, CAGE CAGE/Hair Follicle Outer Root Sheath Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5114 0 CNhs12349 /home/drk/tillage/datasets/human/cage/fantom/CNhs12340/summary/coverage.w5 384 1 sum CAGE:Hepatocyte, CAGE CAGE/Hepatocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5115 0 CNhs12341 /home/drk/tillage/datasets/human/cage/fantom/CNhs12341/summary/coverage.w5 384 1 sum CAGE:Cardiac Myocyte, CAGE CAGE/Cardiac Myocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5116 0 CNhs12342 /home/drk/tillage/datasets/human/cage/fantom/CNhs12342/summary/coverage.w5 384 1 sum CAGE:Lens Epithelial Cells, CAGE CAGE/Lens Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5117 0 CNhs12354 /home/drk/tillage/datasets/human/cage/fantom/CNhs12343/summary/coverage.w5 384 1 sum CAGE:CD19+ B Cells, CAGE CAGE/CD19+ B Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5118 0 CNhs12570 /home/drk/tillage/datasets/human/cage/fantom/CNhs12346/summary/coverage.w5 384 1 sum CAGE:Melanocyte - dark, CAGE CAGE/Melanocyte - dark, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5119 0 CNhs12351 /home/drk/tillage/datasets/human/cage/fantom/CNhs12351/summary/coverage.w5 384 1 sum CAGE:testicular germ cell embryonal carcinoma cell line:NEC14 CAGE CAGE/testicular germ cell embryonal carcinoma cell line:NEC14 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5120 0 CNhs12362 /home/drk/tillage/datasets/human/cage/fantom/CNhs12362/summary/coverage.w5 384 1 sum CAGE:testicular germ cell embryonal carcinoma cell line:NEC15 CAGE CAGE/testicular germ cell embryonal carcinoma cell line:NEC15 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5121 0 CNhs12364 /home/drk/tillage/datasets/human/cage/fantom/CNhs12363/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - adipose, CAGE CAGE/mesenchymal precursor cell - adipose, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5122 0 CNhs13098 /home/drk/tillage/datasets/human/cage/fantom/CNhs12366/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - bone marrow, CAGE CAGE/mesenchymal precursor cell - bone marrow, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5123 0 CNhs12369 /home/drk/tillage/datasets/human/cage/fantom/CNhs12368/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - cardiac, CAGE CAGE/mesenchymal precursor cell - cardiac, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5124 0 CNhs13094 /home/drk/tillage/datasets/human/cage/fantom/CNhs12372/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - ovarian cancer left ovary, CAGE CAGE/mesenchymal precursor cell - ovarian cancer left ovary, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5125 0 CNhs12373 /home/drk/tillage/datasets/human/cage/fantom/CNhs12373/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - ovarian cancer right ovary, CAGE CAGE/mesenchymal precursor cell - ovarian cancer right ovary, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5126 0 CNhs13097 /home/drk/tillage/datasets/human/cage/fantom/CNhs12374/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - ovarian cancer metastasis, CAGE CAGE/mesenchymal precursor cell - ovarian cancer metastasis, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5127 0 CNhs12377 /home/drk/tillage/datasets/human/cage/fantom/CNhs12377/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - ovarian cancer right ovary, (SOC-57-02) CAGE CAGE/mesenchymal precursor cell - ovarian cancer right ovary, (SOC-57-02) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5128 0 CNhs12502 /home/drk/tillage/datasets/human/cage/fantom/CNhs12379/summary/coverage.w5 384 1 sum CAGE:amniotic membrane cells, CAGE CAGE/amniotic membrane cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5129 0 CNhs12506 /home/drk/tillage/datasets/human/cage/fantom/CNhs12380/summary/coverage.w5 384 1 sum CAGE:chorionic membrane cells, CAGE CAGE/chorionic membrane cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5130 0 CNhs12492 /home/drk/tillage/datasets/human/cage/fantom/CNhs12492/summary/coverage.w5 384 1 sum CAGE:Mesenchymal stem cells - umbilical, CAGE CAGE/Mesenchymal stem cells - umbilical, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5131 0 CNhs12493 /home/drk/tillage/datasets/human/cage/fantom/CNhs12493/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Periodontal Ligament, (PL29) CAGE CAGE/Fibroblast - Periodontal Ligament, (PL29) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5132 0 CNhs12518 /home/drk/tillage/datasets/human/cage/fantom/CNhs12518/summary/coverage.w5 384 1 sum CAGE:common myeloid progenitor CMP, CAGE CAGE/common myeloid progenitor CMP, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5133 0 CNhs12519 /home/drk/tillage/datasets/human/cage/fantom/CNhs12519/summary/coverage.w5 384 1 sum CAGE:granulocyte macrophage progenitor, CAGE CAGE/granulocyte macrophage progenitor, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5134 0 CNhs12529 /home/drk/tillage/datasets/human/cage/fantom/CNhs12520/summary/coverage.w5 384 1 sum CAGE:promyelocytes/myelocytes PMC, CAGE "CAGE/promyelocytes;myelocytes PMC," CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5135 0 CNhs12530 /home/drk/tillage/datasets/human/cage/fantom/CNhs12522/summary/coverage.w5 384 1 sum CAGE:neutrophil PMN, CAGE CAGE/neutrophil PMN, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5136 0 CNhs12538 /home/drk/tillage/datasets/human/cage/fantom/CNhs12538/summary/coverage.w5 384 1 sum CAGE:Mallassez-derived cells, (MZH3) CAGE CAGE/Mallassez-derived cells, (MZH3) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5137 0 CNhs12545 /home/drk/tillage/datasets/human/cage/fantom/CNhs12545/summary/coverage.w5 384 1 sum CAGE:CD133+ stem cells - cord blood derived, pool1 CAGE CAGE/CD133+ stem cells - cord blood derived, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5138 0 CNhs12546 /home/drk/tillage/datasets/human/cage/fantom/CNhs12546/summary/coverage.w5 384 1 sum CAGE:Basophils, CAGE CAGE/Basophils, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5139 0 CNhs12549 /home/drk/tillage/datasets/human/cage/fantom/CNhs12547/summary/coverage.w5 384 1 sum CAGE:Eosinophils, CAGE CAGE/Eosinophils, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5140 0 CNhs12552 /home/drk/tillage/datasets/human/cage/fantom/CNhs12552/summary/coverage.w5 384 1 sum CAGE:CD133+ stem cells - adult bone marrow derived, pool1 CAGE CAGE/CD133+ stem cells - adult bone marrow derived, pool1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5141 0 CNhs12553 /home/drk/tillage/datasets/human/cage/fantom/CNhs12553/summary/coverage.w5 384 1 sum CAGE:CD34+ stem cells - adult bone marrow derived, , tech_ CAGE CAGE/CD34+ stem cells - adult bone marrow derived, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5142 0 CNhs12554 /home/drk/tillage/datasets/human/cage/fantom/CNhs12554/summary/coverage.w5 384 1 sum CAGE:nasal epithelial cells, , tech_ CAGE CAGE/nasal epithelial cells, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5143 0 CNhs12562 /home/drk/tillage/datasets/human/cage/fantom/CNhs12558/summary/coverage.w5 384 1 sum CAGE:mature adipocyte, CAGE CAGE/mature adipocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5144 0 CNhs12566 /home/drk/tillage/datasets/human/cage/fantom/CNhs12566/summary/coverage.w5 384 1 sum CAGE:Mast cell, CAGE CAGE/Mast cell, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5145 0 CNhs13076 /home/drk/tillage/datasets/human/cage/fantom/CNhs12569/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Umbilical Vein, CAGE CAGE/Smooth Muscle Cells - Umbilical Vein, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5146 0 CNhs12574 /home/drk/tillage/datasets/human/cage/fantom/CNhs12574/summary/coverage.w5 384 1 sum CAGE:nasal epithelial cells, CAGE CAGE/nasal epithelial cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5147 0 CNhs12586 /home/drk/tillage/datasets/human/cage/fantom/CNhs12586/summary/coverage.w5 384 1 sum CAGE:Oligodendrocyte - precursors, CAGE CAGE/Oligodendrocyte - precursors, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5148 0 CNhs12590 /home/drk/tillage/datasets/human/cage/fantom/CNhs12587/summary/coverage.w5 384 1 sum CAGE:Perineurial Cells, CAGE CAGE/Perineurial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5149 0 CNhs12595 /home/drk/tillage/datasets/human/cage/fantom/CNhs12595/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Intestinal, CAGE CAGE/Smooth Muscle Cells - Intestinal, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5150 0 CNhs12596 /home/drk/tillage/datasets/human/cage/fantom/CNhs12596/summary/coverage.w5 384 1 sum CAGE:Iris Pigment Epithelial Cells, CAGE CAGE/Iris Pigment Epithelial Cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5151 0 CNhs12610 /home/drk/tillage/datasets/human/cage/fantom/CNhs12610/summary/coverage.w5 384 1 sum CAGE:diencephalon, adult CAGE CAGE/diencephalon, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5152 0 CNhs12611 /home/drk/tillage/datasets/human/cage/fantom/CNhs12611/summary/coverage.w5 384 1 sum CAGE:olfactory region, adult CAGE CAGE/olfactory region, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5153 0 CNhs12641 /home/drk/tillage/datasets/human/cage/fantom/CNhs12639/summary/coverage.w5 384 1 sum CAGE:tenocyte, CAGE CAGE/tenocyte, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5154 0 CNhs12805 /home/drk/tillage/datasets/human/cage/fantom/CNhs12805/summary/coverage.w5 384 1 sum CAGE:medulloblastoma cell line:D283 Med CAGE CAGE/medulloblastoma cell line:D283 Med CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5155 0 CNhs12806 /home/drk/tillage/datasets/human/cage/fantom/CNhs12806/summary/coverage.w5 384 1 sum CAGE:large cell lung carcinoma cell line:NCI-H460 CAGE CAGE/large cell lung carcinoma cell line:NCI-H460 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5156 0 CNhs12807 /home/drk/tillage/datasets/human/cage/fantom/CNhs12807/summary/coverage.w5 384 1 sum CAGE:plasma cell leukemia cell line:ARH-77 CAGE CAGE/plasma cell leukemia cell line:ARH-77 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5157 0 CNhs12808 /home/drk/tillage/datasets/human/cage/fantom/CNhs12808/summary/coverage.w5 384 1 sum CAGE:small cell lung carcinoma cell line:DMS 144 CAGE CAGE/small cell lung carcinoma cell line:DMS 144 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5158 0 CNhs12809 /home/drk/tillage/datasets/human/cage/fantom/CNhs12809/summary/coverage.w5 384 1 sum CAGE:small cell lung carcinoma cell line:NCI-H82 CAGE CAGE/small cell lung carcinoma cell line:NCI-H82 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5159 0 CNhs12811 /home/drk/tillage/datasets/human/cage/fantom/CNhs12810/summary/coverage.w5 384 1 sum CAGE:salivary acinar cells, CAGE CAGE/salivary acinar cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5160 0 CNhs12838 /home/drk/tillage/datasets/human/cage/fantom/CNhs12838/summary/coverage.w5 384 1 sum CAGE:merkel cell carcinoma cell line:MKL-1 CAGE CAGE/merkel cell carcinoma cell line:MKL-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5161 0 CNhs12839 /home/drk/tillage/datasets/human/cage/fantom/CNhs12839/summary/coverage.w5 384 1 sum CAGE:merkel cell carcinoma cell line:MS-1 CAGE CAGE/merkel cell carcinoma cell line:MS-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5162 0 CNhs12840 /home/drk/tillage/datasets/human/cage/fantom/CNhs12840/summary/coverage.w5 384 1 sum CAGE:cerebral meninges, adult CAGE CAGE/cerebral meninges, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5163 0 CNhs12842 /home/drk/tillage/datasets/human/cage/fantom/CNhs12842/summary/coverage.w5 384 1 sum CAGE:appendix, adult CAGE CAGE/appendix, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5164 0 CNhs12843 /home/drk/tillage/datasets/human/cage/fantom/CNhs12843/summary/coverage.w5 384 1 sum CAGE:artery, adult CAGE CAGE/artery, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5165 0 CNhs12844 /home/drk/tillage/datasets/human/cage/fantom/CNhs12844/summary/coverage.w5 384 1 sum CAGE:vein, adult CAGE CAGE/vein, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5166 0 CNhs12845 /home/drk/tillage/datasets/human/cage/fantom/CNhs12845/summary/coverage.w5 384 1 sum CAGE:bone marrow, adult CAGE CAGE/bone marrow, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5167 0 CNhs12846 /home/drk/tillage/datasets/human/cage/fantom/CNhs12846/summary/coverage.w5 384 1 sum CAGE:ductus deferens, adult CAGE CAGE/ductus deferens, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5168 0 CNhs12847 /home/drk/tillage/datasets/human/cage/fantom/CNhs12847/summary/coverage.w5 384 1 sum CAGE:epididymis, adult CAGE CAGE/epididymis, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5169 0 CNhs12848 /home/drk/tillage/datasets/human/cage/fantom/CNhs12848/summary/coverage.w5 384 1 sum CAGE:gall bladder, adult CAGE CAGE/gall bladder, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5170 0 CNhs12849 /home/drk/tillage/datasets/human/cage/fantom/CNhs12849/summary/coverage.w5 384 1 sum CAGE:parotid gland, adult CAGE CAGE/parotid gland, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5171 0 CNhs12850 /home/drk/tillage/datasets/human/cage/fantom/CNhs12850/summary/coverage.w5 384 1 sum CAGE:penis, adult CAGE CAGE/penis, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5172 0 CNhs12851 /home/drk/tillage/datasets/human/cage/fantom/CNhs12851/summary/coverage.w5 384 1 sum CAGE:seminal vesicle, adult CAGE CAGE/seminal vesicle, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5173 0 CNhs12852 /home/drk/tillage/datasets/human/cage/fantom/CNhs12852/summary/coverage.w5 384 1 sum CAGE:submaxillary gland, adult CAGE CAGE/submaxillary gland, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5174 0 CNhs12853 /home/drk/tillage/datasets/human/cage/fantom/CNhs12853/summary/coverage.w5 384 1 sum CAGE:tongue, adult CAGE CAGE/tongue, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5175 0 CNhs12854 /home/drk/tillage/datasets/human/cage/fantom/CNhs12854/summary/coverage.w5 384 1 sum CAGE:vagina, adult CAGE CAGE/vagina, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5176 0 CNhs12855 /home/drk/tillage/datasets/human/cage/fantom/CNhs12855/summary/coverage.w5 384 1 sum CAGE:heart - mitral valve, adult CAGE CAGE/heart - mitral valve, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5177 0 CNhs12856 /home/drk/tillage/datasets/human/cage/fantom/CNhs12856/summary/coverage.w5 384 1 sum CAGE:heart - pulmonic valve, adult CAGE CAGE/heart - pulmonic valve, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5178 0 CNhs12857 /home/drk/tillage/datasets/human/cage/fantom/CNhs12857/summary/coverage.w5 384 1 sum CAGE:heart - tricuspid valve, adult CAGE CAGE/heart - tricuspid valve, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5179 0 CNhs12858 /home/drk/tillage/datasets/human/cage/fantom/CNhs12858/summary/coverage.w5 384 1 sum CAGE:throat, adult CAGE CAGE/throat, adult CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5180 0 CNhs12893 /home/drk/tillage/datasets/human/cage/fantom/CNhs12893/summary/coverage.w5 384 1 sum CAGE:Smooth Muscle Cells - Bladder, CAGE CAGE/Smooth Muscle Cells - Bladder, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5181 0 CNhs12998 /home/drk/tillage/datasets/human/cage/fantom/CNhs12998/summary/coverage.w5 384 1 sum CAGE:testis, adult, pool2 CAGE CAGE/testis, adult, pool2 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5182 0 CNhs13049 /home/drk/tillage/datasets/human/cage/fantom/CNhs13049/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M7) cell line:M-MOK CAGE CAGE/acute myeloid leukemia (FAB M7) cell line:M-MOK CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5183 0 CNhs13050 /home/drk/tillage/datasets/human/cage/fantom/CNhs13050/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:NOMO-1 CAGE CAGE/acute myeloid leukemia (FAB M5) cell line:NOMO-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5184 0 CNhs13051 /home/drk/tillage/datasets/human/cage/fantom/CNhs13051/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:P31/FUJ CAGE "CAGE/acute myeloid leukemia (FAB M5) cell line:P31;FUJ" CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5185 0 CNhs13052 /home/drk/tillage/datasets/human/cage/fantom/CNhs13052/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M2) cell line:Kasumi-6 CAGE CAGE/acute myeloid leukemia (FAB M2) cell line:Kasumi-6 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5186 0 CNhs13053 /home/drk/tillage/datasets/human/cage/fantom/CNhs13053/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M0) cell line:KG-1 CAGE CAGE/acute myeloid leukemia (FAB M0) cell line:KG-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5187 0 CNhs13054 /home/drk/tillage/datasets/human/cage/fantom/CNhs13054/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M1) cell line:HYT-1 CAGE CAGE/acute myeloid leukemia (FAB M1) cell line:HYT-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5188 0 CNhs13055 /home/drk/tillage/datasets/human/cage/fantom/CNhs13055/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M3) cell line:HL60 CAGE CAGE/acute myeloid leukemia (FAB M3) cell line:HL60 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5189 0 CNhs13056 /home/drk/tillage/datasets/human/cage/fantom/CNhs13056/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M4eo) cell line:EoL-1 CAGE CAGE/acute myeloid leukemia (FAB M4eo) cell line:EoL-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5190 0 CNhs13057 /home/drk/tillage/datasets/human/cage/fantom/CNhs13057/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M4eo) cell line:EoL-3 CAGE CAGE/acute myeloid leukemia (FAB M4eo) cell line:EoL-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5191 0 CNhs13058 /home/drk/tillage/datasets/human/cage/fantom/CNhs13058/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M5) cell line:U-937 DE-4 CAGE CAGE/acute myeloid leukemia (FAB M5) cell line:U-937 DE-4 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5192 0 CNhs13059 /home/drk/tillage/datasets/human/cage/fantom/CNhs13059/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M6) cell line:EEB CAGE CAGE/acute myeloid leukemia (FAB M6) cell line:EEB CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5193 0 CNhs13060 /home/drk/tillage/datasets/human/cage/fantom/CNhs13060/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M6) cell line:F-36E CAGE CAGE/acute myeloid leukemia (FAB M6) cell line:F-36E CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5194 0 CNhs13061 /home/drk/tillage/datasets/human/cage/fantom/CNhs13061/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:NCI-H28 CAGE CAGE/mesothelioma cell line:NCI-H28 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5195 0 CNhs13062 /home/drk/tillage/datasets/human/cage/fantom/CNhs13062/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:NCI-H226 CAGE CAGE/mesothelioma cell line:NCI-H226 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5196 0 CNhs13063 /home/drk/tillage/datasets/human/cage/fantom/CNhs13063/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:NCI-H2052 CAGE CAGE/mesothelioma cell line:NCI-H2052 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5197 0 CNhs13064 /home/drk/tillage/datasets/human/cage/fantom/CNhs13064/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:NCI-H2452 CAGE CAGE/mesothelioma cell line:NCI-H2452 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5198 0 CNhs14376 /home/drk/tillage/datasets/human/cage/fantom/CNhs13065/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-14, tech_ CAGE CAGE/mesothelioma cell line:Mero-14, tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5199 0 CNhs13066 /home/drk/tillage/datasets/human/cage/fantom/CNhs13066/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-25 CAGE CAGE/mesothelioma cell line:Mero-25 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5200 0 CNhs13067 /home/drk/tillage/datasets/human/cage/fantom/CNhs13067/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-41 CAGE CAGE/mesothelioma cell line:Mero-41 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5201 0 CNhs13068 /home/drk/tillage/datasets/human/cage/fantom/CNhs13068/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-48a CAGE CAGE/mesothelioma cell line:Mero-48a CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5202 0 CNhs13069 /home/drk/tillage/datasets/human/cage/fantom/CNhs13069/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-82 CAGE CAGE/mesothelioma cell line:Mero-82 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5203 0 CNhs13070 /home/drk/tillage/datasets/human/cage/fantom/CNhs13070/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-83 CAGE CAGE/mesothelioma cell line:Mero-83 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5204 0 CNhs13072 /home/drk/tillage/datasets/human/cage/fantom/CNhs13072/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-84 CAGE CAGE/mesothelioma cell line:Mero-84 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5205 0 CNhs13073 /home/drk/tillage/datasets/human/cage/fantom/CNhs13073/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:Mero-95 CAGE CAGE/mesothelioma cell line:Mero-95 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5206 0 CNhs13074 /home/drk/tillage/datasets/human/cage/fantom/CNhs13074/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:No36 CAGE CAGE/mesothelioma cell line:No36 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5207 0 CNhs13075 /home/drk/tillage/datasets/human/cage/fantom/CNhs13075/summary/coverage.w5 384 1 sum CAGE:mesothelioma cell line:ONE58 CAGE CAGE/mesothelioma cell line:ONE58 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5208 0 CNhs13099 /home/drk/tillage/datasets/human/cage/fantom/CNhs13099/summary/coverage.w5 384 1 sum CAGE:serous adenocarcinoma cell line:SK-OV-3-R, biol_ CAGE CAGE/serous adenocarcinoma cell line:SK-OV-3-R, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5209 0 CNhs13538 /home/drk/tillage/datasets/human/cage/fantom/CNhs13195/summary/coverage.w5 384 1 sum CAGE:CD4+CD25+CD45RA- memory regulatory T cells, CAGE CAGE/CD4+CD25+CD45RA- memory regulatory T cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5210 0 CNhs13813 /home/drk/tillage/datasets/human/cage/fantom/CNhs13202/summary/coverage.w5 384 1 sum CAGE:CD4+CD25-CD45RA+ naive conventional T cells expanded, CAGE CAGE/CD4+CD25-CD45RA+ naive conventional T cells expanded, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5211 0 CNhs13918 /home/drk/tillage/datasets/human/cage/fantom/CNhs13203/summary/coverage.w5 384 1 sum CAGE:CD4+CD25+CD45RA+ naive regulatory T cells expanded, CAGE CAGE/CD4+CD25+CD45RA+ naive regulatory T cells expanded, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5212 0 CNhs13204 /home/drk/tillage/datasets/human/cage/fantom/CNhs13204/summary/coverage.w5 384 1 sum CAGE:CD4+CD25+CD45RA- memory regulatory T cells expanded, CAGE CAGE/CD4+CD25+CD45RA- memory regulatory T cells expanded, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5213 0 CNhs13512 /home/drk/tillage/datasets/human/cage/fantom/CNhs13205/summary/coverage.w5 384 1 sum CAGE:CD4+CD25-CD45RA+ naive conventional T cells, CAGE CAGE/CD4+CD25-CD45RA+ naive conventional T cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5214 0 CNhs13207 /home/drk/tillage/datasets/human/cage/fantom/CNhs13207/summary/coverage.w5 384 1 sum CAGE:CD14-CD16+ Monocytes, CAGE CAGE/CD14-CD16+ Monocytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5215 0 CNhs13208 /home/drk/tillage/datasets/human/cage/fantom/CNhs13208/summary/coverage.w5 384 1 sum CAGE:CD14+CD16+ Monocytes, CAGE CAGE/CD14+CD16+ Monocytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5216 0 CNhs13921 /home/drk/tillage/datasets/human/cage/fantom/CNhs13215/summary/coverage.w5 384 1 sum CAGE:CD4+CD25-CD45RA- memory conventional T cells expanded, CAGE CAGE/CD4+CD25-CD45RA- memory conventional T cells expanded, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5217 0 CNhs13224 /home/drk/tillage/datasets/human/cage/fantom/CNhs13216/summary/coverage.w5 384 1 sum CAGE:CD14+CD16- Monocytes, CAGE CAGE/CD14+CD16- Monocytes, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5218 0 CNhs13513 /home/drk/tillage/datasets/human/cage/fantom/CNhs13235/summary/coverage.w5 384 1 sum CAGE:CD4+CD25+CD45RA+ naive regulatory T cells, CAGE CAGE/CD4+CD25+CD45RA+ naive regulatory T cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5219 0 CNhs13239 /home/drk/tillage/datasets/human/cage/fantom/CNhs13237/summary/coverage.w5 384 1 sum CAGE:CD4+CD25-CD45RA- memory conventional T cells, CAGE CAGE/CD4+CD25-CD45RA- memory conventional T cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5220 0 CNhs13241 /home/drk/tillage/datasets/human/cage/fantom/CNhs13241/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M0) cell line:Kasumi-3 CAGE CAGE/acute myeloid leukemia (FAB M0) cell line:Kasumi-3 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5221 0 CNhs13435 /home/drk/tillage/datasets/human/cage/fantom/CNhs13435/summary/coverage.w5 384 1 sum CAGE:achilles tendon, CAGE CAGE/achilles tendon, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5222 0 CNhs13437 /home/drk/tillage/datasets/human/cage/fantom/CNhs13437/summary/coverage.w5 384 1 sum CAGE:cerebrospinal fluid, CAGE CAGE/cerebrospinal fluid, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5223 0 CNhs13439 /home/drk/tillage/datasets/human/cage/fantom/CNhs13439/summary/coverage.w5 384 1 sum CAGE:cruciate ligament, CAGE CAGE/cruciate ligament, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5224 0 CNhs13440 /home/drk/tillage/datasets/human/cage/fantom/CNhs13440/summary/coverage.w5 384 1 sum CAGE:eye - vitreous humor, CAGE CAGE/eye - vitreous humor, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5225 0 CNhs13441 /home/drk/tillage/datasets/human/cage/fantom/CNhs13441/summary/coverage.w5 384 1 sum CAGE:eye - muscle superior, CAGE CAGE/eye - muscle superior, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5226 0 CNhs13442 /home/drk/tillage/datasets/human/cage/fantom/CNhs13442/summary/coverage.w5 384 1 sum CAGE:eye - muscle lateral, CAGE CAGE/eye - muscle lateral, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5227 0 CNhs13443 /home/drk/tillage/datasets/human/cage/fantom/CNhs13443/summary/coverage.w5 384 1 sum CAGE:eye - muscle medial, CAGE CAGE/eye - muscle medial, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5228 0 CNhs13444 /home/drk/tillage/datasets/human/cage/fantom/CNhs13444/summary/coverage.w5 384 1 sum CAGE:eye - muscle inferior rectus, CAGE CAGE/eye - muscle inferior rectus, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5229 0 CNhs13445 /home/drk/tillage/datasets/human/cage/fantom/CNhs13445/summary/coverage.w5 384 1 sum CAGE:Fingernail (including nail plate, eponychium and hyponychium), CAGE CAGE/Fingernail (including nail plate, eponychium and hyponychium), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5230 0 CNhs13449 /home/drk/tillage/datasets/human/cage/fantom/CNhs13449/summary/coverage.w5 384 1 sum CAGE:optic nerve, CAGE CAGE/optic nerve, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5231 0 CNhs13454 /home/drk/tillage/datasets/human/cage/fantom/CNhs13454/summary/coverage.w5 384 1 sum CAGE:skeletal muscle - soleus muscle, CAGE CAGE/skeletal muscle - soleus muscle, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5232 0 CNhs13458 /home/drk/tillage/datasets/human/cage/fantom/CNhs13458/summary/coverage.w5 384 1 sum CAGE:Skin - palm, CAGE CAGE/Skin - palm, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5233 0 CNhs13460 /home/drk/tillage/datasets/human/cage/fantom/CNhs13460/summary/coverage.w5 384 1 sum CAGE:tongue epidermis (fungiform papillae), CAGE CAGE/tongue epidermis (fungiform papillae), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5234 0 CNhs13464 /home/drk/tillage/datasets/human/cage/fantom/CNhs13464/summary/coverage.w5 384 1 sum CAGE:Urethra, CAGE CAGE/Urethra, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5235 0 CNhs13475 /home/drk/tillage/datasets/human/cage/fantom/CNhs13465/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with BCG, CAGE CAGE/CD14+ monocytes - treated with BCG, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5236 0 CNhs13466 /home/drk/tillage/datasets/human/cage/fantom/CNhs13466/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with IFN + N-hexane, CAGE CAGE/CD14+ monocytes - treated with IFN + N-hexane, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5237 0 CNhs13483 /home/drk/tillage/datasets/human/cage/fantom/CNhs13467/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with Trehalose dimycolate (TDM), CAGE CAGE/CD14+ monocytes - treated with Trehalose dimycolate (TDM), CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5238 0 CNhs13484 /home/drk/tillage/datasets/human/cage/fantom/CNhs13468/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - mock treated, CAGE CAGE/CD14+ monocytes - mock treated, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5239 0 CNhs13532 /home/drk/tillage/datasets/human/cage/fantom/CNhs13469/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with Group A streptococci, CAGE CAGE/CD14+ monocytes - treated with Group A streptococci, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5240 0 CNhs13533 /home/drk/tillage/datasets/human/cage/fantom/CNhs13470/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with lipopolysaccharide, CAGE CAGE/CD14+ monocytes - treated with lipopolysaccharide, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5241 0 CNhs13493 /home/drk/tillage/datasets/human/cage/fantom/CNhs13471/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with Salmonella, CAGE CAGE/CD14+ monocytes - treated with Salmonella, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5242 0 CNhs13487 /home/drk/tillage/datasets/human/cage/fantom/CNhs13472/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with Cryptococcus, CAGE CAGE/CD14+ monocytes - treated with Cryptococcus, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5243 0 CNhs13488 /home/drk/tillage/datasets/human/cage/fantom/CNhs13473/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with Candida, CAGE CAGE/CD14+ monocytes - treated with Candida, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5244 0 CNhs13495 /home/drk/tillage/datasets/human/cage/fantom/CNhs13474/summary/coverage.w5 384 1 sum CAGE:CD14+ monocytes - treated with B-glucan, CAGE CAGE/CD14+ monocytes - treated with B-glucan, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5245 0 CNhs13496 /home/drk/tillage/datasets/human/cage/fantom/CNhs13477/summary/coverage.w5 384 1 sum CAGE:Hep-2 cells treated with Streptococci strain 5448, biol_ CAGE CAGE/Hep-2 cells treated with Streptococci strain 5448, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5246 0 CNhs13498 /home/drk/tillage/datasets/human/cage/fantom/CNhs13478/summary/coverage.w5 384 1 sum CAGE:Hep-2 cells treated with Streptococci strain JRS4, biol_ CAGE CAGE/Hep-2 cells treated with Streptococci strain JRS4, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5247 0 CNhs13479 /home/drk/tillage/datasets/human/cage/fantom/CNhs13479/summary/coverage.w5 384 1 sum CAGE:Hep-2 cells mock treated, biol_ CAGE CAGE/Hep-2 cells mock treated, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5248 0 CNhs13480 /home/drk/tillage/datasets/human/cage/fantom/CNhs13480/summary/coverage.w5 384 1 sum CAGE:immature langerhans cells, CAGE CAGE/immature langerhans cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5249 0 CNhs13502 /home/drk/tillage/datasets/human/cage/fantom/CNhs13502/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M2) cell line:Kasumi-1 CAGE CAGE/acute myeloid leukemia (FAB M2) cell line:Kasumi-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5250 0 CNhs13503 /home/drk/tillage/datasets/human/cage/fantom/CNhs13503/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M4) cell line:FKH-1 CAGE CAGE/acute myeloid leukemia (FAB M4) cell line:FKH-1 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5251 0 CNhs13504 /home/drk/tillage/datasets/human/cage/fantom/CNhs13504/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M4) cell line:HNT-34 CAGE CAGE/acute myeloid leukemia (FAB M4) cell line:HNT-34 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5252 0 CNhs13505 /home/drk/tillage/datasets/human/cage/fantom/CNhs13505/summary/coverage.w5 384 1 sum CAGE:acute myeloid leukemia (FAB M6) cell line:F-36P CAGE CAGE/acute myeloid leukemia (FAB M6) cell line:F-36P CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5253 0 CNhs13507 /home/drk/tillage/datasets/human/cage/fantom/CNhs13507/summary/coverage.w5 384 1 sum CAGE:mesenchymal precursor cell - ovarian cancer right ovary, (SOC-57-02-G) CAGE CAGE/mesenchymal precursor cell - ovarian cancer right ovary, (SOC-57-02-G) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5254 0 CNhs13508 /home/drk/tillage/datasets/human/cage/fantom/CNhs13508/summary/coverage.w5 384 1 sum CAGE:serous adenocarcinoma cell line:SK-OV-3-R after co-culture with SOC-57-02-G, biol_ CAGE CAGE/serous adenocarcinoma cell line:SK-OV-3-R after co-culture with SOC-57-02-G, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5255 0 CNhs13547 /home/drk/tillage/datasets/human/cage/fantom/CNhs13535/summary/coverage.w5 384 1 sum CAGE:migratory langerhans cells, CAGE CAGE/migratory langerhans cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5256 0 CNhs13551 /home/drk/tillage/datasets/human/cage/fantom/CNhs13550/summary/coverage.w5 384 1 sum CAGE:Mallassez-derived cells, CAGE CAGE/Mallassez-derived cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5257 0 CNhs13553 /home/drk/tillage/datasets/human/cage/fantom/CNhs13552/summary/coverage.w5 384 1 sum CAGE:CD34 cells differentiated to erythrocyte lineage, biol_ CAGE CAGE/CD34 cells differentiated to erythrocyte lineage, biol_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5258 0 CNhs13793 /home/drk/tillage/datasets/human/cage/fantom/CNhs13793/summary/coverage.w5 384 1 sum CAGE:amygdala - adult, CAGE CAGE/amygdala - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5259 0 CNhs13794 /home/drk/tillage/datasets/human/cage/fantom/CNhs13794/summary/coverage.w5 384 1 sum CAGE:thalamus - adult, CAGE CAGE/thalamus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5260 0 CNhs13795 /home/drk/tillage/datasets/human/cage/fantom/CNhs13795/summary/coverage.w5 384 1 sum CAGE:hippocampus - adult, CAGE CAGE/hippocampus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5261 0 CNhs13796 /home/drk/tillage/datasets/human/cage/fantom/CNhs13796/summary/coverage.w5 384 1 sum CAGE:medial frontal gyrus - adult, CAGE CAGE/medial frontal gyrus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5262 0 CNhs13797 /home/drk/tillage/datasets/human/cage/fantom/CNhs13797/summary/coverage.w5 384 1 sum CAGE:parietal lobe - adult, CAGE CAGE/parietal lobe - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5263 0 CNhs13798 /home/drk/tillage/datasets/human/cage/fantom/CNhs13798/summary/coverage.w5 384 1 sum CAGE:occipital cortex - adult, CAGE CAGE/occipital cortex - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5264 0 CNhs13799 /home/drk/tillage/datasets/human/cage/fantom/CNhs13799/summary/coverage.w5 384 1 sum CAGE:cerebellum - adult, CAGE CAGE/cerebellum - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5265 0 CNhs13800 /home/drk/tillage/datasets/human/cage/fantom/CNhs13800/summary/coverage.w5 384 1 sum CAGE:medulla oblongata - adult, CAGE CAGE/medulla oblongata - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5266 0 CNhs13801 /home/drk/tillage/datasets/human/cage/fantom/CNhs13801/summary/coverage.w5 384 1 sum CAGE:globus pallidus - adult, CAGE CAGE/globus pallidus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5267 0 CNhs13802 /home/drk/tillage/datasets/human/cage/fantom/CNhs13802/summary/coverage.w5 384 1 sum CAGE:caudate nucleus - adult, CAGE CAGE/caudate nucleus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5268 0 CNhs13803 /home/drk/tillage/datasets/human/cage/fantom/CNhs13803/summary/coverage.w5 384 1 sum CAGE:substantia nigra - adult, CAGE CAGE/substantia nigra - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5269 0 CNhs13804 /home/drk/tillage/datasets/human/cage/fantom/CNhs13804/summary/coverage.w5 384 1 sum CAGE:pineal gland - adult, CAGE CAGE/pineal gland - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5270 0 CNhs13805 /home/drk/tillage/datasets/human/cage/fantom/CNhs13805/summary/coverage.w5 384 1 sum CAGE:pituitary gland - adult, CAGE CAGE/pituitary gland - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5271 0 CNhs13807 /home/drk/tillage/datasets/human/cage/fantom/CNhs13807/summary/coverage.w5 384 1 sum CAGE:spinal cord - adult, CAGE CAGE/spinal cord - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5272 0 CNhs13808 /home/drk/tillage/datasets/human/cage/fantom/CNhs13808/summary/coverage.w5 384 1 sum CAGE:locus coeruleus - adult, CAGE CAGE/locus coeruleus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5273 0 CNhs13809 /home/drk/tillage/datasets/human/cage/fantom/CNhs13809/summary/coverage.w5 384 1 sum CAGE:medial temporal gyrus - adult, CAGE CAGE/medial temporal gyrus - adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5274 0 CNhs13816 /home/drk/tillage/datasets/human/cage/fantom/CNhs13816/summary/coverage.w5 384 1 sum CAGE:Olfactory epithelial cells, CAGE CAGE/Olfactory epithelial cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5275 0 CNhs13915 /home/drk/tillage/datasets/human/cage/fantom/CNhs13914/summary/coverage.w5 384 1 sum CAGE:gamma delta positive T cells, CAGE CAGE/gamma delta positive T cells, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5276 0 CNhs13924 /home/drk/tillage/datasets/human/cage/fantom/CNhs13924/summary/coverage.w5 384 1 sum CAGE:Mast cell, expanded, CAGE CAGE/Mast cell, expanded, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5277 0 CNhs13925 /home/drk/tillage/datasets/human/cage/fantom/CNhs13925/summary/coverage.w5 384 1 sum CAGE:Mast cell, expanded and stimulated, CAGE CAGE/Mast cell, expanded and stimulated, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5278 0 CNhs13975 /home/drk/tillage/datasets/human/cage/fantom/CNhs13972/summary/coverage.w5 384 1 sum CAGE:adipose, CAGE CAGE/adipose, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5279 0 CNhs14069 /home/drk/tillage/datasets/human/cage/fantom/CNhs14069/summary/coverage.w5 384 1 sum CAGE:medial frontal gyrus, newborn, CAGE CAGE/medial frontal gyrus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5280 0 CNhs14070 /home/drk/tillage/datasets/human/cage/fantom/CNhs14070/summary/coverage.w5 384 1 sum CAGE:medial temporal gyrus, newborn, CAGE CAGE/medial temporal gyrus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5281 0 CNhs14071 /home/drk/tillage/datasets/human/cage/fantom/CNhs14071/summary/coverage.w5 384 1 sum CAGE:caudate nucleus, newborn, CAGE CAGE/caudate nucleus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5282 0 CNhs14073 /home/drk/tillage/datasets/human/cage/fantom/CNhs14073/summary/coverage.w5 384 1 sum CAGE:occipital cortex, newborn, CAGE CAGE/occipital cortex, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5283 0 CNhs14074 /home/drk/tillage/datasets/human/cage/fantom/CNhs14074/summary/coverage.w5 384 1 sum CAGE:parietal lobe, newborn, CAGE CAGE/parietal lobe, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5284 0 CNhs14075 /home/drk/tillage/datasets/human/cage/fantom/CNhs14075/summary/coverage.w5 384 1 sum CAGE:cerebellum, newborn, CAGE CAGE/cerebellum, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5285 0 CNhs14076 /home/drk/tillage/datasets/human/cage/fantom/CNhs14076/summary/coverage.w5 384 1 sum CAGE:substantia nigra, newborn, CAGE CAGE/substantia nigra, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5286 0 CNhs14077 /home/drk/tillage/datasets/human/cage/fantom/CNhs14077/summary/coverage.w5 384 1 sum CAGE:spinal cord, newborn, CAGE CAGE/spinal cord, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5287 0 CNhs14078 /home/drk/tillage/datasets/human/cage/fantom/CNhs14078/summary/coverage.w5 384 1 sum CAGE:amygdala, newborn, CAGE CAGE/amygdala, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5288 0 CNhs14079 /home/drk/tillage/datasets/human/cage/fantom/CNhs14079/summary/coverage.w5 384 1 sum CAGE:medulla oblongata, newborn, CAGE CAGE/medulla oblongata, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5289 0 CNhs14080 /home/drk/tillage/datasets/human/cage/fantom/CNhs14080/summary/coverage.w5 384 1 sum CAGE:locus coeruleus, newborn, CAGE CAGE/locus coeruleus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5290 0 CNhs14081 /home/drk/tillage/datasets/human/cage/fantom/CNhs14081/summary/coverage.w5 384 1 sum CAGE:hippocampus, newborn, CAGE CAGE/hippocampus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5291 0 CNhs14082 /home/drk/tillage/datasets/human/cage/fantom/CNhs14082/summary/coverage.w5 384 1 sum CAGE:globus pallidus, newborn, CAGE CAGE/globus pallidus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5292 0 CNhs14083 /home/drk/tillage/datasets/human/cage/fantom/CNhs14083/summary/coverage.w5 384 1 sum CAGE:putamen, newborn, CAGE CAGE/putamen, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5293 0 CNhs14084 /home/drk/tillage/datasets/human/cage/fantom/CNhs14084/summary/coverage.w5 384 1 sum CAGE:thalamus, newborn, CAGE CAGE/thalamus, newborn, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5294 0 CNhs14130 /home/drk/tillage/datasets/human/cage/fantom/CNhs14128/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (aggressive periodontitis) CAGE CAGE/Fibroblast - Gingival, (aggressive periodontitis) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5295 0 CNhs14131 /home/drk/tillage/datasets/human/cage/fantom/CNhs14129/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (control) CAGE CAGE/Fibroblast - Gingival, (control) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5296 0 CNhs14132 /home/drk/tillage/datasets/human/cage/fantom/CNhs14132/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (chronic periodontitis) CAGE CAGE/Fibroblast - Gingival, (chronic periodontitis) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5297 0 CNhs14135 /home/drk/tillage/datasets/human/cage/fantom/CNhs14135/summary/coverage.w5 384 1 sum CAGE:Fibroblast - Gingival, (periodontitis) CAGE CAGE/Fibroblast - Gingival, (periodontitis) CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5298 0 CNhs14138 /home/drk/tillage/datasets/human/cage/fantom/CNhs14138/summary/coverage.w5 384 1 sum CAGE:bronchioalveolar carcinoma cell line:NCI-H650 CAGE CAGE/bronchioalveolar carcinoma cell line:NCI-H650 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5299 0 CNhs14139 /home/drk/tillage/datasets/human/cage/fantom/CNhs14139/summary/coverage.w5 384 1 sum CAGE:thymic carcinoma cell line:Ty-82 CAGE CAGE/thymic carcinoma cell line:Ty-82 CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5300 0 CNhs14140 /home/drk/tillage/datasets/human/cage/fantom/CNhs14140/summary/coverage.w5 384 1 sum CAGE:thyroid carcinoma cell line:KHM-5M CAGE CAGE/thyroid carcinoma cell line:KHM-5M CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5301 0 CNhs14184 /home/drk/tillage/datasets/human/cage/fantom/CNhs14183/summary/coverage.w5 384 1 sum CAGE:Smooth muscle cells - airway, asthmatic, CAGE CAGE/Smooth muscle cells - airway, asthmatic, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5302 0 CNhs14192 /home/drk/tillage/datasets/human/cage/fantom/CNhs14190/summary/coverage.w5 384 1 sum CAGE:Smooth muscle cells - airway, control, CAGE CAGE/Smooth muscle cells - airway, control, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5303 0 CNhs14551 /home/drk/tillage/datasets/human/cage/fantom/CNhs14223/summary/coverage.w5 384 1 sum CAGE:thalamus, adult, , tech_ CAGE CAGE/thalamus, adult, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5304 0 CNhs14618 /home/drk/tillage/datasets/human/cage/fantom/CNhs14225/summary/coverage.w5 384 1 sum CAGE:putamen, adult, , tech_ CAGE CAGE/putamen, adult, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5305 0 CNhs14226 /home/drk/tillage/datasets/human/cage/fantom/CNhs14226/summary/coverage.w5 384 1 sum CAGE:parietal cortex, adult, CAGE CAGE/parietal cortex, adult, CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5306 0 CNhs14229 /home/drk/tillage/datasets/human/cage/fantom/CNhs14229/summary/coverage.w5 384 1 sum CAGE:medial temporal gyrus, adult, , tech_ CAGE CAGE/medial temporal gyrus, adult, , tech_ CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5307 0 CNhs14238 /home/drk/tillage/datasets/human/cage/fantom/CNhs14238/summary/coverage.w5 384 1 sum CAGE:squamous cell lung carcinoma cell line:LC-1F CAGE CAGE/squamous cell lung carcinoma cell line:LC-1F CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5308 0 CNhs14239 /home/drk/tillage/datasets/human/cage/fantom/CNhs14239/summary/coverage.w5 384 1 sum CAGE:epithelioid sarcoma cell line:HS-ES-2R CAGE CAGE/epithelioid sarcoma cell line:HS-ES-2R CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5309 0 CNhs14240 /home/drk/tillage/datasets/human/cage/fantom/CNhs14240/summary/coverage.w5 384 1 sum CAGE:squamous cell lung carcinoma cell line:RERF-LC-AI CAGE CAGE/squamous cell lung carcinoma cell line:RERF-LC-AI CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5310 0 CNhs14241 /home/drk/tillage/datasets/human/cage/fantom/CNhs14241/summary/coverage.w5 384 1 sum CAGE:gastric cancer cell line:GSS CAGE CAGE/gastric cancer cell line:GSS CAGE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE +5311 0 CNhs14244 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Tpos:215.1,Tstd:105.9,Bpos:206.4,Bstd:93.1,StrandBias:0.6,Multiplicity:1.03 +0.121 0.858 0.020 0.001 +0.001 0.892 0.106 0.001 +0.899 0.050 0.001 0.050 +0.001 0.049 0.001 0.949 +0.001 0.899 0.099 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.050 0.200 0.600 0.150 +0.001 0.001 0.949 0.049 +0.001 0.001 0.049 0.949 +>CACCTCACCA 3-CACCTCACCA 7.271332 -7.811697 0 T:184.0(4.60%),B:125.5(3.15%),P:1e-3 Tpos:253.6,Tstd:133.7,Bpos:249.9,Bstd:144.5,StrandBias:0.0,Multiplicity:1.00 +0.077 0.764 0.075 0.084 +0.842 0.065 0.056 0.037 +0.059 0.822 0.060 0.059 +0.072 0.794 0.058 0.076 +0.030 0.069 0.058 0.843 +0.089 0.832 0.039 0.040 +0.808 0.069 0.092 0.031 +0.098 0.739 0.065 0.098 +0.056 0.788 0.088 0.068 +0.780 0.076 0.084 0.060 +>CTATCTTTCT 4-CTATCTTTCT 9.437671 -7.108680 0 T:85.0(2.13%),B:48.6(1.22%),P:1e-3 Tpos:259.9,Tstd:128.6,Bpos:261.7,Bstd:149.8,StrandBias:0.4,Multiplicity:1.00 +0.001 0.930 0.001 0.068 +0.001 0.001 0.074 0.924 +0.964 0.001 0.001 0.034 +0.001 0.001 0.034 0.964 +0.035 0.801 0.085 0.079 +0.001 0.089 0.075 0.835 +0.001 0.058 0.001 0.940 +0.001 0.001 0.084 0.914 +0.098 0.832 0.001 0.069 +0.001 0.059 0.051 0.889 +>GAGGGCACCT 5-GAGGGCACCT 9.805876 -5.724401 0 T:52.0(1.30%),B:27.0(0.68%),P:1e-2 Tpos:242.7,Tstd:132.1,Bpos:260.6,Bstd:155.8,StrandBias:0.1,Multiplicity:1.02 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.053 0.001 0.893 0.053 +0.001 0.001 0.946 0.052 +0.001 0.052 0.946 0.001 +0.001 0.798 0.113 0.088 +0.789 0.104 0.001 0.106 +0.053 0.646 0.089 0.212 +0.021 0.977 0.001 0.001 +0.001 0.001 0.001 0.997 +>AVTTGAGCAATT 1-AVTTGAGCAATT 8.994152 -11.321453 0 T:32.0(0.80%),B:6.7(0.17%),P:1e-4 Tpos:236.5,Tstd:120.9,Bpos:242.5,Bstd:173.9,StrandBias:0.1,Multiplicity:1.00 +0.575 0.210 0.199 0.016 +0.339 0.253 0.272 0.136 +0.170 0.027 0.211 0.592 +0.240 0.190 0.032 0.538 +0.027 0.172 0.618 0.183 +0.682 0.151 0.138 0.029 +0.047 0.197 0.672 0.084 +0.027 0.892 0.025 0.056 +0.736 0.045 0.192 0.027 +0.613 0.027 0.014 0.346 +0.027 0.181 0.152 0.640 +0.201 0.029 0.129 0.641 +>GACATCAGGTGG 2-GACATCAGGTGG 9.345447 -11.195270 0 T:25.0(0.63%),B:3.6(0.09%),P:1e-4 Tpos:269.4,Tstd:105.6,Bpos:397.9,Bstd:53.9,StrandBias:0.8,Multiplicity:1.00 +0.091 0.172 0.637 0.100 +0.528 0.178 0.147 0.147 +0.291 0.590 0.044 0.075 +0.925 0.056 0.018 0.001 +0.001 0.147 0.100 0.752 +0.185 0.589 0.113 0.113 +0.759 0.122 0.044 0.075 +0.063 0.047 0.834 0.056 +0.122 0.088 0.624 0.166 +0.147 0.059 0.060 0.734 +0.166 0.088 0.649 0.097 +0.001 0.169 0.605 0.225 +>TACCTCGTACGT 3-TACCTCGTACGT 9.488826 -10.609444 0 T:24.0(0.60%),B:3.7(0.09%),P:1e-4 Tpos:216.3,Tstd:100.8,Bpos:181.3,Bstd:113.4,StrandBias:-0.5,Multiplicity:1.00 +0.117 0.004 0.158 0.721 +0.894 0.001 0.001 0.104 +0.121 0.683 0.079 0.117 +0.090 0.665 0.056 0.189 +0.218 0.079 0.083 0.620 +0.053 0.558 0.170 0.219 +0.121 0.117 0.645 0.117 +0.001 0.143 0.090 0.766 +0.714 0.075 0.094 0.117 +0.001 0.592 0.283 0.124 +0.064 0.144 0.532 0.260 +0.001 0.072 0.120 0.807 +>GGTGTTATTCAG 4-GGTGTTATTCAG 9.665970 -7.616403 0 T:14.0(0.35%),B:2.0(0.05%),P:1e-3 Tpos:202.4,Tstd:114.6,Bpos:229.6,Bstd:144.8,StrandBias:-2.6,Multiplicity:1.00 +0.055 0.117 0.791 0.037 +0.126 0.091 0.692 0.091 +0.100 0.073 0.055 0.772 +0.047 0.099 0.781 0.073 +0.091 0.117 0.082 0.710 +0.046 0.117 0.046 0.791 +0.745 0.135 0.029 0.091 +0.126 0.011 0.126 0.737 +0.082 0.047 0.126 0.745 +0.056 0.701 0.117 0.126 +0.737 0.126 0.064 0.073 +0.082 0.073 0.781 0.064 +>GTCAACTCTGTG 5-GTCAACTCTGTG 11.745920 -6.987655 0 T:13.0(0.33%),B:1.7(0.04%),P:1e-3 Tpos:253.8,Tstd:123.4,Bpos:404.7,Bstd:46.3,StrandBias:1.7,Multiplicity:1.00 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.001 0.997 0.001 0.001 +0.777 0.001 0.111 0.111 +0.888 0.001 0.001 0.110 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.110 0.888 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.888 0.110 +0.001 0.111 0.111 0.777 +0.110 0.001 0.888 0.001 +>NYACCTGT 1-NYACCTGT 5.873685 -59.271922 0 T:2084.0(52.11%),B:1607.8(40.31%),P:1e-25 Tpos:255.8,Tstd:142.6,Bpos:256.4,Bstd:157.2,StrandBias:-0.0,Multiplicity:1.42 +0.233 0.234 0.245 0.288 +0.117 0.380 0.001 0.502 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.072 0.001 0.722 0.205 +0.173 0.134 0.229 0.464 +>HMDCACCT 2-HMDCACCT 1.281595 -40.964797 0 T:2272.0(56.81%),B:1877.1(47.06%),P:1e-17 Tpos:246.2,Tstd:140.1,Bpos:245.2,Bstd:150.0,StrandBias:0.1,Multiplicity:1.28 +0.248 0.351 0.091 0.310 +0.363 0.249 0.208 0.180 +0.359 0.001 0.268 0.372 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +>ATWTTTTT 3-ATWTTTTT 4.857828 -10.622533 0 T:2198.0(54.96%),B:2010.5(50.40%),P:1e-4 Tpos:246.2,Tstd:151.2,Bpos:247.7,Bstd:161.2,StrandBias:0.1,Multiplicity:1.43 +0.530 0.184 0.192 0.094 +0.307 0.213 0.001 0.479 +0.431 0.108 0.001 0.460 +0.031 0.030 0.001 0.938 +0.051 0.125 0.193 0.631 +0.111 0.153 0.214 0.522 +0.148 0.147 0.218 0.486 +0.001 0.207 0.218 0.574 +>ACWTGGAG 4-ACWTGGAG 6.413528 -7.183465 0 T:1323.0(33.08%),B:1187.5(29.77%),P:1e-3 Tpos:250.4,Tstd:140.7,Bpos:249.5,Bstd:146.5,StrandBias:0.0,Multiplicity:1.22 +0.986 0.008 0.005 0.001 +0.159 0.424 0.253 0.164 +0.435 0.001 0.001 0.563 +0.085 0.129 0.003 0.783 +0.001 0.006 0.754 0.239 +0.058 0.001 0.934 0.007 +0.661 0.001 0.334 0.004 +0.111 0.001 0.885 0.003 +>ACATTTTC 5-ACATTTTC 4.872034 -6.933166 0 T:2183.0(54.59%),B:2038.1(51.09%),P:1e-3 Tpos:252.7,Tstd:146.8,Bpos:252.3,Bstd:153.4,StrandBias:-0.1,Multiplicity:1.37 +0.698 0.139 0.076 0.087 +0.074 0.764 0.076 0.086 +0.752 0.068 0.084 0.096 +0.060 0.099 0.073 0.768 +0.121 0.029 0.042 0.808 +0.072 0.106 0.053 0.769 +0.099 0.072 0.102 0.727 +0.097 0.723 0.076 0.104 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs10 b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs10 new file mode 100644 index 0000000000000000000000000000000000000000..4e94a9a9d51c33eb900480bcce8b4b3f55f6322e --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs10 @@ -0,0 +1,55 @@ +>NANCAGGTRM 1-NANCAGGTRM 3.301854 -72.247213 0 T:2232.0(55.81%),B:1702.3(42.67%),P:1e-31 Tpos:253.8,Tstd:141.9,Bpos:255.1,Bstd:155.3,StrandBias:-0.0,Multiplicity:1.42 +0.199 0.236 0.311 0.254 +0.454 0.248 0.054 0.244 +0.208 0.254 0.274 0.264 +0.029 0.969 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.443 0.001 0.555 0.001 +0.370 0.378 0.080 0.172 +>CCATCAAGGT 2-CCATCAAGGT 9.745095 -8.980493 0 T:53.0(1.33%),B:21.7(0.54%),P:1e-3 Tpos:215.1,Tstd:105.9,Bpos:206.4,Bstd:93.1,StrandBias:0.6,Multiplicity:1.03 +0.121 0.858 0.020 0.001 +0.001 0.892 0.106 0.001 +0.899 0.050 0.001 0.050 +0.001 0.049 0.001 0.949 +0.001 0.899 0.099 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.050 0.200 0.600 0.150 +0.001 0.001 0.949 0.049 +0.001 0.001 0.049 0.949 +>CACCTCACCA 3-CACCTCACCA 7.271332 -7.811697 0 T:184.0(4.60%),B:125.5(3.15%),P:1e-3 Tpos:253.6,Tstd:133.7,Bpos:249.9,Bstd:144.5,StrandBias:0.0,Multiplicity:1.00 +0.077 0.764 0.075 0.084 +0.842 0.065 0.056 0.037 +0.059 0.822 0.060 0.059 +0.072 0.794 0.058 0.076 +0.030 0.069 0.058 0.843 +0.089 0.832 0.039 0.040 +0.808 0.069 0.092 0.031 +0.098 0.739 0.065 0.098 +0.056 0.788 0.088 0.068 +0.780 0.076 0.084 0.060 +>CTATCTTTCT 4-CTATCTTTCT 9.437671 -7.108680 0 T:85.0(2.13%),B:48.6(1.22%),P:1e-3 Tpos:259.9,Tstd:128.6,Bpos:261.7,Bstd:149.8,StrandBias:0.4,Multiplicity:1.00 +0.001 0.930 0.001 0.068 +0.001 0.001 0.074 0.924 +0.964 0.001 0.001 0.034 +0.001 0.001 0.034 0.964 +0.035 0.801 0.085 0.079 +0.001 0.089 0.075 0.835 +0.001 0.058 0.001 0.940 +0.001 0.001 0.084 0.914 +0.098 0.832 0.001 0.069 +0.001 0.059 0.051 0.889 +>GAGGGCACCT 5-GAGGGCACCT 9.805876 -5.724401 0 T:52.0(1.30%),B:27.0(0.68%),P:1e-2 Tpos:242.7,Tstd:132.1,Bpos:260.6,Bstd:155.8,StrandBias:0.1,Multiplicity:1.02 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.053 0.001 0.893 0.053 +0.001 0.001 0.946 0.052 +0.001 0.052 0.946 0.001 +0.001 0.798 0.113 0.088 +0.789 0.104 0.001 0.106 +0.053 0.646 0.089 0.212 +0.021 0.977 0.001 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs12 b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs12 new file mode 100644 index 0000000000000000000000000000000000000000..d38b9398327bd60da867c9ce1b73a701093163dd --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs12 @@ -0,0 +1,65 @@ +>AVTTGAGCAATT 1-AVTTGAGCAATT 8.994152 -11.321453 0 T:32.0(0.80%),B:6.7(0.17%),P:1e-4 Tpos:236.5,Tstd:120.9,Bpos:242.5,Bstd:173.9,StrandBias:0.1,Multiplicity:1.00 +0.575 0.210 0.199 0.016 +0.339 0.253 0.272 0.136 +0.170 0.027 0.211 0.592 +0.240 0.190 0.032 0.538 +0.027 0.172 0.618 0.183 +0.682 0.151 0.138 0.029 +0.047 0.197 0.672 0.084 +0.027 0.892 0.025 0.056 +0.736 0.045 0.192 0.027 +0.613 0.027 0.014 0.346 +0.027 0.181 0.152 0.640 +0.201 0.029 0.129 0.641 +>GACATCAGGTGG 2-GACATCAGGTGG 9.345447 -11.195270 0 T:25.0(0.63%),B:3.6(0.09%),P:1e-4 Tpos:269.4,Tstd:105.6,Bpos:397.9,Bstd:53.9,StrandBias:0.8,Multiplicity:1.00 +0.091 0.172 0.637 0.100 +0.528 0.178 0.147 0.147 +0.291 0.590 0.044 0.075 +0.925 0.056 0.018 0.001 +0.001 0.147 0.100 0.752 +0.185 0.589 0.113 0.113 +0.759 0.122 0.044 0.075 +0.063 0.047 0.834 0.056 +0.122 0.088 0.624 0.166 +0.147 0.059 0.060 0.734 +0.166 0.088 0.649 0.097 +0.001 0.169 0.605 0.225 +>TACCTCGTACGT 3-TACCTCGTACGT 9.488826 -10.609444 0 T:24.0(0.60%),B:3.7(0.09%),P:1e-4 Tpos:216.3,Tstd:100.8,Bpos:181.3,Bstd:113.4,StrandBias:-0.5,Multiplicity:1.00 +0.117 0.004 0.158 0.721 +0.894 0.001 0.001 0.104 +0.121 0.683 0.079 0.117 +0.090 0.665 0.056 0.189 +0.218 0.079 0.083 0.620 +0.053 0.558 0.170 0.219 +0.121 0.117 0.645 0.117 +0.001 0.143 0.090 0.766 +0.714 0.075 0.094 0.117 +0.001 0.592 0.283 0.124 +0.064 0.144 0.532 0.260 +0.001 0.072 0.120 0.807 +>GGTGTTATTCAG 4-GGTGTTATTCAG 9.665970 -7.616403 0 T:14.0(0.35%),B:2.0(0.05%),P:1e-3 Tpos:202.4,Tstd:114.6,Bpos:229.6,Bstd:144.8,StrandBias:-2.6,Multiplicity:1.00 +0.055 0.117 0.791 0.037 +0.126 0.091 0.692 0.091 +0.100 0.073 0.055 0.772 +0.047 0.099 0.781 0.073 +0.091 0.117 0.082 0.710 +0.046 0.117 0.046 0.791 +0.745 0.135 0.029 0.091 +0.126 0.011 0.126 0.737 +0.082 0.047 0.126 0.745 +0.056 0.701 0.117 0.126 +0.737 0.126 0.064 0.073 +0.082 0.073 0.781 0.064 +>GTCAACTCTGTG 5-GTCAACTCTGTG 11.745920 -6.987655 0 T:13.0(0.33%),B:1.7(0.04%),P:1e-3 Tpos:253.8,Tstd:123.4,Bpos:404.7,Bstd:46.3,StrandBias:1.7,Multiplicity:1.00 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.001 0.997 0.001 0.001 +0.777 0.001 0.111 0.111 +0.888 0.001 0.001 0.110 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.110 0.888 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.888 0.110 +0.001 0.111 0.111 0.777 +0.110 0.001 0.888 0.001 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs8 b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs8 new file mode 100644 index 0000000000000000000000000000000000000000..b0f5e8da701c32a1a0e5496a83b87530bb8f360d --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerMotifs.motifs8 @@ -0,0 +1,45 @@ +>NYACCTGT 1-NYACCTGT 5.873685 -59.271922 0 T:2084.0(52.11%),B:1607.8(40.31%),P:1e-25 Tpos:255.8,Tstd:142.6,Bpos:256.4,Bstd:157.2,StrandBias:-0.0,Multiplicity:1.42 +0.233 0.234 0.245 0.288 +0.117 0.380 0.001 0.502 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.072 0.001 0.722 0.205 +0.173 0.134 0.229 0.464 +>HMDCACCT 2-HMDCACCT 1.281595 -40.964797 0 T:2272.0(56.81%),B:1877.1(47.06%),P:1e-17 Tpos:246.2,Tstd:140.1,Bpos:245.2,Bstd:150.0,StrandBias:0.1,Multiplicity:1.28 +0.248 0.351 0.091 0.310 +0.363 0.249 0.208 0.180 +0.359 0.001 0.268 0.372 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +>ATWTTTTT 3-ATWTTTTT 4.857828 -10.622533 0 T:2198.0(54.96%),B:2010.5(50.40%),P:1e-4 Tpos:246.2,Tstd:151.2,Bpos:247.7,Bstd:161.2,StrandBias:0.1,Multiplicity:1.43 +0.530 0.184 0.192 0.094 +0.307 0.213 0.001 0.479 +0.431 0.108 0.001 0.460 +0.031 0.030 0.001 0.938 +0.051 0.125 0.193 0.631 +0.111 0.153 0.214 0.522 +0.148 0.147 0.218 0.486 +0.001 0.207 0.218 0.574 +>ACWTGGAG 4-ACWTGGAG 6.413528 -7.183465 0 T:1323.0(33.08%),B:1187.5(29.77%),P:1e-3 Tpos:250.4,Tstd:140.7,Bpos:249.5,Bstd:146.5,StrandBias:0.0,Multiplicity:1.22 +0.986 0.008 0.005 0.001 +0.159 0.424 0.253 0.164 +0.435 0.001 0.001 0.563 +0.085 0.129 0.003 0.783 +0.001 0.006 0.754 0.239 +0.058 0.001 0.934 0.007 +0.661 0.001 0.334 0.004 +0.111 0.001 0.885 0.003 +>ACATTTTC 5-ACATTTTC 4.872034 -6.933166 0 T:2183.0(54.59%),B:2038.1(51.09%),P:1e-3 Tpos:252.7,Tstd:146.8,Bpos:252.3,Bstd:153.4,StrandBias:-0.1,Multiplicity:1.37 +0.698 0.139 0.076 0.087 +0.074 0.764 0.076 0.086 +0.752 0.068 0.084 0.096 +0.060 0.099 0.073 0.768 +0.121 0.029 0.042 0.808 +0.072 0.106 0.053 0.769 +0.099 0.072 0.102 0.727 +0.097 0.723 0.076 0.104 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults.html b/the_code/Human/data/homer/M0_vs_M15/homerResults.html new file mode 100644 index 0000000000000000000000000000000000000000..fc2f3475055fb45e158bc4c418cfb72dbc3c340e --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults.html @@ -0,0 +1,657 @@ +.// - Homer de novo Motif Results + +

Homer de novo Motif Results (.//)

+Known Motif Enrichment Results
+Gene Ontology Enrichment Results
+If Homer is having trouble matching a motif to a known motif, try copy/pasting the matrix file into +STAMP
+More information on motif finding results: HOMER + | Description of Results + | Tips +
+Total target sequences = 3999
+Total background sequences = 3989
+* - possible false positive
+ + + + + + + + + + + + + + + +
RankMotifP-valuelog P-pvalue% of Targets% of BackgroundSTD(Bg STD)Best Match/DetailsMotif File
1 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + +1e-31-7.225e+0155.81%42.67%141.9bp (155.3bp)ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer(0.951)
More Information | Similar Motifs Found		motif file (matrix)
2 +* + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + +1e-4-1.132e+010.80%0.17%120.9bp (173.9bp)CEBP(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer(0.721)
More Information | Similar Motifs Found		motif file (matrix)
3 +* + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + +1e-4-1.062e+0154.96%50.40%151.2bp (161.2bp)PABPC4(RRM)/Homo_sapiens-RNCMPT00043-PBM/HughesRNA(0.844)
More Information | Similar Motifs Found		motif file (matrix)
4 +* + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + +1e-4-1.061e+010.60%0.09%100.8bp (113.4bp)SMZ/MA0553.1/Jaspar(0.700)
More Information | Similar Motifs Found		motif file (matrix)
5 +* + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + +1e-3-8.980e+001.33%0.54%105.9bp (93.1bp)ZAP1/ZAP1_YPD/[](Harbison)/Yeast(0.743)
More Information | Similar Motifs Found		motif file (matrix)
6 +* + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + +1e-3-7.812e+004.60%3.15%133.7bp (144.5bp)AGL55/MA1202.1/Jaspar(0.766)
More Information | Similar Motifs Found		motif file (matrix)
7 +* + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + +1e-3-7.616e+000.35%0.05%114.6bp (144.8bp)STB5/STB5_YPD/[](Harbison)/Yeast(0.700)
More Information | Similar Motifs Found		motif file (matrix)
8 +* + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + + +1e-3-7.183e+0033.08%29.77%140.7bp (146.5bp)Pp_0237(RRM)/Physcomitrella_patens-RNCMPT00237-PBM/HughesRNA(0.767)
More Information | Similar Motifs Found		motif file (matrix)
9 +* + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + +1e-3-7.109e+002.13%1.22%128.6bp (149.8bp)HNRNPAB(RRM)/Tetraodon_nigroviridis-RNCMPT00245-PBM/HughesRNA(0.735)
More Information | Similar Motifs Found		motif file (matrix)
10 +* + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + +1e-3-6.988e+000.33%0.04%123.4bp (46.3bp)WRKY30/MA1083.1/Jaspar(0.703)
More Information | Similar Motifs Found		motif file (matrix)
11 +* + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + +1e-2-5.724e+001.30%0.68%132.1bp (155.8bp)HIC2/MA0738.1/Jaspar(0.655)
More Information | Similar Motifs Found		motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.info.html new file mode 100644 index 0000000000000000000000000000000000000000..7abca7e547de3924c563468940973eb74c03ce06 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.info.html @@ -0,0 +1,1493 @@ +Motif 1 +

Information for 1-NANCAGGTRM (Motif 1)

+ + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + + +
+Reverse Opposite:
+ + C + A + T + G + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + T + G + A + C + + C + A + G + T + + T + G + A + C + + + +
+ + + + + + + + + + + + + + +
p-value:1e-31
log p-value:-7.225e+01
Information Content per bp:1.693
Number of Target Sequences with motif2232.0
Percentage of Target Sequences with motif55.81%
Number of Background Sequences with motif1702.3
Percentage of Background Sequences with motif42.67%
Average Position of motif in Targets253.8 +/- 141.9bp
Average Position of motif in Background255.1 +/- 155.3bp
Strand Bias (log2 ratio + to - strand density)-0.0
Multiplicity (# of sites on avg that occur together)1.42
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer

+
+ + + +
Match Rank:1
Score:0.95 +
Offset:2 +
Orientation:forward strand
Alignment:NANCAGGTRM--
--VCAGGTRDRY
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + T + G + C + A + + G + T + A + C + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + C + G + A + T + + T + C + G + A + + A + G + T + C + + + + +
+
+

NGA4(ABI3VP1)/col-NGA4-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:2
Score:0.94 +
Offset:-1 +
Orientation:forward strand
Alignment:-NANCAGGTRM
TKNTCAGGTG-
+		 + + + A + C + G + T + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + + +
+ + + G + A + C + T + + A + C + G + T + + C + G + A + T + + A + G + C + T + + A + G + T + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + C + G + A + T + + C + T + A + G + + A + C + G + T + + + + +
+
+

E2A(bHLH),near_PU.1/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer

+
+ + + +
Match Rank:3
Score:0.93 +
Offset:1 +
Orientation:reverse strand
Alignment:NANCAGGTRM-
-NNCAGGTGNN
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + C + G + T + + C + A + G + T + + T + A + C + G + + A + G + T + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + A + C + T + G + + A + C + G + T + + T + A + C + G + + + + +
+
+

SNAI2/MA0745.1/Jaspar

+
+ + + +
Match Rank:4
Score:0.93 +
Offset:1 +
Orientation:forward strand
Alignment:NANCAGGTRM
-AACAGGTGT
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + + +
+ + + A + C + G + T + + C + T + G + A + + C + T + G + A + + G + T + A + C + + G + C + T + A + + C + T + A + G + + C + T + A + G + + G + A + C + T + + C + A + T + G + + A + G + C + T + + + + +
+
+

ZEB1/MA0103.3/Jaspar

+
+ + + +
Match Rank:5
Score:0.92 +
Offset:0 +
Orientation:reverse strand
Alignment:NANCAGGTRM-
NNGCAGGTGNN
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + T + A + C + G + + A + T + G + C + + T + A + C + G + + A + G + T + C + + T + C + G + A + + A + T + C + G + + T + C + A + G + + G + A + C + T + + T + C + A + G + + T + A + C + G + + T + A + C + G + + + + +
+
+

esg/dmmpmm(Bergman)/fly

+
+ + + +
Match Rank:6
Score:0.92 +
Offset:0 +
Orientation:forward strand
Alignment:NANCAGGTRM--
NNACAGGTGCNN
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + A + C + T + + C + T + A + G + + C + T + G + A + + G + A + T + C + + C + G + T + A + + C + T + A + G + + A + C + T + G + + A + C + G + T + + T + A + C + G + + A + G + T + C + + C + G + T + A + + A + T + C + G + + + + +
+
+

TCF4/MA0830.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.91 +
Offset:1 +
Orientation:reverse strand
Alignment:NANCAGGTRM-
-NNCAGGTGCG
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + C + G + T + + G + C + T + A + + T + A + C + G + + G + A + T + C + + C + G + T + A + + A + T + C + G + + T + A + C + G + + A + C + G + T + + C + T + A + G + + A + G + T + C + + C + T + A + G + + + + +
+
+

TCF3/MA0522.2/Jaspar

+
+ + + +
Match Rank:8
Score:0.90 +
Offset:1 +
Orientation:reverse strand
Alignment:NANCAGGTRM-
-NNCAGGTGTN
+		 + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + C + G + T + + G + T + C + A + + T + C + A + G + + A + G + T + C + + C + G + T + A + + A + T + C + G + + T + A + C + G + + C + G + A + T + + A + C + T + G + + A + G + C + T + + C + A + G + T + + + + +
+
+

RAV1(2)(AP2/EREBP)/Arabidopsis thaliana/AthaMap

+
+ + + +
Match Rank:9
Score:0.90 +
Offset:-1 +
Orientation:reverse strand
Alignment:-NANCAGGTRM-
GNNTCAGGTGAN
+		 + + + A + C + G + T + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + C + T + A + G + + A + T + G + C + + A + T + G + C + + A + G + C + T + + A + G + T + C + + C + G + T + A + + A + C + T + G + + T + C + A + G + + G + C + A + T + + C + A + T + G + + C + T + G + A + + C + G + A + T + + + + +
+
+

RAV1(var.2)/MA0583.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.90 +
Offset:-1 +
Orientation:reverse strand
Alignment:-NANCAGGTRM-
GNNTCAGGTGAN
+		 + + + A + C + G + T + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + A + C + G + T + + + + +
+ + + C + T + A + G + + A + T + G + C + + A + T + G + C + + A + G + C + T + + A + G + T + C + + C + G + T + A + + A + C + T + G + + T + C + A + G + + G + C + A + T + + C + A + T + G + + C + T + G + A + + C + G + A + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..b3c7534f3f49fef73d548fabaf77f9b98a77fcdf --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.logo.svg @@ -0,0 +1,54 @@ + + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.motif new file mode 100644 index 0000000000000000000000000000000000000000..3992f21a9b0cb2b4aa882aa80d7bc72e8e467692 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.motif @@ -0,0 +1,11 @@ +>NANCAGGTRM 1-NANCAGGTRM,BestGuess:ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer(0.951) 3.301854 -72.247213 0 T:2232.0(55.81%),B:1702.3(42.67%),P:1e-31 +0.199 0.236 0.311 0.254 +0.454 0.248 0.054 0.244 +0.208 0.254 0.274 0.264 +0.029 0.969 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.443 0.001 0.555 0.001 +0.370 0.378 0.080 0.172 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..bfb3d61ae44f97cdbea20cb35d85ac76e92720c2 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar.html @@ -0,0 +1,290 @@ +motif1 +

Information for motif1

+ + + A + C + T + G + + G + T + C + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + G + T + A + C + + + +
+Reverse Opposite:
+ + C + A + T + G + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + T + G + A + C + + C + A + G + T + + T + G + A + C + + + +
+ + + + + + + + + + + + + +
p-value:1e-31
log p-value:-7.225e+01
Information Content per bp:1.693
Number of Target Sequences with motif2232.0
Percentage of Target Sequences with motif55.81%
Number of Background Sequences with motif1702.3
Percentage of Background Sequences with motif42.67%
Average Position of motif in Targets253.8 +/- 141.9bp
Average Position of motif in Background255.1 +/- 155.3bp
Strand Bias (log2 ratio + to - strand density)-0.0
Multiplicity (# of sites on avg that occur together)1.42
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.953 + + A + C + G + T + + G + A + C + T + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + C + A + T + G + + C + A + G + T + + + + +1e-25-59.27192252.11%40.31%motif file (matrix)
20.839 + + G + A + T + C + + T + G + C + A + + C + G + A + T + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + + + +1e-17-40.96479756.81%47.06%motif file (matrix)
30.687 + + A + T + C + G + + G + T + C + A + + G + T + A + C + + T + G + C + A + + A + G + C + T + + G + T + A + C + + G + T + C + A + + C + T + A + G + + C + A + T + G + + C + G + A + T + + C + T + A + G + + A + C + T + G + + + + +1e-4-11.1952700.63%0.09%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar1.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..aaa55c466ab993a491e0d183b71810cbbdc8a02a --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar1.motif @@ -0,0 +1,9 @@ +>NYACCTGT 1-NYACCTGT 5.873685 -59.271922 0 T:2084.0(52.11%),B:1607.8(40.31%),P:1e-25 +0.233 0.234 0.245 0.288 +0.117 0.380 0.001 0.502 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.072 0.001 0.722 0.205 +0.173 0.134 0.229 0.464 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar2.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar2.motif new file mode 100644 index 0000000000000000000000000000000000000000..981c6c407d10ba0cf541a8ddc1273b5912d4ff89 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar2.motif @@ -0,0 +1,9 @@ +>HMDCACCT 2-HMDCACCT 1.281595 -40.964797 0 T:2272.0(56.81%),B:1877.1(47.06%),P:1e-17 +0.248 0.351 0.091 0.310 +0.363 0.249 0.208 0.180 +0.359 0.001 0.268 0.372 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar3.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar3.motif new file mode 100644 index 0000000000000000000000000000000000000000..0106b4dec78bdf3e4dba939edfd9dd4397bb2eee --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1.similar3.motif @@ -0,0 +1,13 @@ +>GACATCAGGTGG 2-GACATCAGGTGG 9.345447 -11.195270 0 T:25.0(0.63%),B:3.6(0.09%),P:1e-4 +0.091 0.172 0.637 0.100 +0.528 0.178 0.147 0.147 +0.291 0.590 0.044 0.075 +0.925 0.056 0.018 0.001 +0.001 0.147 0.100 0.752 +0.185 0.589 0.113 0.113 +0.759 0.122 0.044 0.075 +0.063 0.047 0.834 0.056 +0.122 0.088 0.624 0.166 +0.147 0.059 0.060 0.734 +0.166 0.088 0.649 0.097 +0.001 0.169 0.605 0.225 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.info.html new file mode 100644 index 0000000000000000000000000000000000000000..46f88ded0c2caa6a08c337ad961703d2043da5bb --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.info.html @@ -0,0 +1,1913 @@ +Motif 10 +

Information for 5-GTCAACTCTGTG (Motif 10)

+ + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+Reverse Opposite:
+ + A + G + T + C + + T + C + G + A + + G + T + A + C + + C + G + T + A + + A + C + T + G + + C + G + T + A + + A + C + T + G + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + G + T + A + + A + G + T + C + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-6.988e+00
Information Content per bp:1.876
Number of Target Sequences with motif13.0
Percentage of Target Sequences with motif0.33%
Number of Background Sequences with motif1.7
Percentage of Background Sequences with motif0.04%
Average Position of motif in Targets253.8 +/- 123.4bp
Average Position of motif in Background404.7 +/- 46.3bp
Strand Bias (log2 ratio + to - strand density)1.7
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

WRKY30/MA1083.1/Jaspar

+
+ + + +
Match Rank:1
Score:0.70 +
Offset:-1 +
Orientation:forward strand
Alignment:-GTCAACTCTGTG
GGTCAACGCT---
+		 + + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + T + C + A + G + + A + T + C + G + + A + G + C + T + + G + T + A + C + + G + T + C + A + + C + T + G + A + + G + A + T + C + + A + T + C + G + + T + A + G + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY47(WRKY)/colamp-WRKY47-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:2
Score:0.69 +
Offset:-3 +
Orientation:forward strand
Alignment:---GTCAACTCTGTG
WAAGTCAACGBT---
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + G + C + T + A + + G + C + T + A + + C + T + G + A + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + G + T + A + C + + A + C + T + G + + A + T + G + C + + G + C + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY75/MA1093.1/Jaspar

+
+ + + +
Match Rank:3
Score:0.67 +
Offset:-2 +
Orientation:forward strand
Alignment:--GTCAACTCTGTG
AAGTCAAC------
+		 + + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + G + C + T + A + + T + C + G + A + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + G + T + A + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY21/MA1079.1/Jaspar

+
+ + + +
Match Rank:4
Score:0.67 +
Offset:-3 +
Orientation:forward strand
Alignment:---GTCAACTCTGTG
AAGGTCAACG-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + C + T + G + A + + C + G + T + A + + C + T + A + G + + C + T + A + G + + G + C + A + T + + A + G + T + C + + G + T + C + A + + C + T + G + A + + G + T + A + C + + A + T + C + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY27(WRKY)/colamp-WRKY27-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:5
Score:0.67 +
Offset:-4 +
Orientation:reverse strand
Alignment:----GTCAACTCTGTG
HWARGTCAACDN----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + G + C + T + A + + G + C + T + A + + G + C + T + A + + C + T + G + A + + C + A + T + G + + C + A + G + T + + G + T + A + C + + G + C + T + A + + C + T + G + A + + G + T + A + C + + C + A + T + G + + G + A + C + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY15/MA1076.1/Jaspar

+
+ + + +
Match Rank:6
Score:0.67 +
Offset:-2 +
Orientation:forward strand
Alignment:--GTCAACTCTGTG
AGGTCAACGC----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + C + T + G + A + + T + C + A + G + + A + C + T + G + + C + G + A + T + + G + T + A + C + + G + T + C + A + + C + T + G + A + + G + T + A + C + + T + A + C + G + + A + T + G + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY29(WRKY)/colamp-WRKY29-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:7
Score:0.66 +
Offset:-3 +
Orientation:reverse strand
Alignment:---GTCAACTCTGTG
AAAGTCAACK-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + G + C + T + A + + C + G + T + A + + C + T + G + A + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + T + G + A + + G + T + A + C + + C + A + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY15(WRKY)/col-WRKY15-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:8
Score:0.66 +
Offset:-3 +
Orientation:reverse strand
Alignment:---GTCAACTCTGTG
WWAGTCAACB-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + C + G + A + T + + C + G + T + A + + C + T + G + A + + C + T + A + G + + C + A + G + T + + A + G + T + C + + C + T + G + A + + C + T + G + A + + G + T + A + C + + A + T + C + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

WRKY42/MA1310.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.66 +
Offset:-4 +
Orientation:reverse strand
Alignment:----GTCAACTCTGTG-----
NAAAGTCAACGNNNNNTNAAN
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + T + C + A + + C + G + T + A + + C + G + T + A + + T + C + G + A + + A + C + T + G + + A + C + G + T + + G + T + A + C + + C + G + T + A + + C + G + T + A + + G + T + A + C + + C + A + T + G + + T + G + A + C + + G + A + C + T + + C + T + G + A + + C + T + G + A + + C + A + G + T + + C + A + G + T + + G + T + C + A + + G + T + C + A + + G + C + T + A + + T + C + G + A + + + + +
+
+

WRKY30(WRKY)/colamp-WRKY30-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:10
Score:0.66 +
Offset:-3 +
Orientation:reverse strand
Alignment:---GTCAACTCTGTG
NAAGTCAACG-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + + +
+ + + A + C + G + T + + C + G + T + A + + T + C + G + A + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + G + T + A + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..c085c6930db3f20189050ea14433d72bb479b306 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.logo.svg @@ -0,0 +1,64 @@ + + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.motif new file mode 100644 index 0000000000000000000000000000000000000000..32c1d0073208e8ac7373c1c41c9a75e0b346e18b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.motif @@ -0,0 +1,13 @@ +>GTCAACTCTGTG 5-GTCAACTCTGTG,BestGuess:WRKY30/MA1083.1/Jaspar(0.703) 11.745920 -6.987655 0 T:13.0(0.33%),B:1.7(0.04%),P:1e-3 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.001 0.997 0.001 0.001 +0.777 0.001 0.111 0.111 +0.888 0.001 0.001 0.110 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.110 0.888 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.888 0.110 +0.001 0.111 0.111 0.777 +0.110 0.001 0.888 0.001 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..b382f3c103da748836e1b11805bea66002d0e268 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10.similar.html @@ -0,0 +1,152 @@ +motif10 +

Information for motif10

+ + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + G + T + C + + A + C + G + T + + G + T + A + C + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + T + A + G + + + +
+Reverse Opposite:
+ + A + G + T + C + + T + C + G + A + + G + T + A + C + + C + G + T + A + + A + C + T + G + + C + G + T + A + + A + C + T + G + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + G + T + A + + A + G + T + C + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-6.988e+00
Information Content per bp:1.876
Number of Target Sequences with motif13.0
Percentage of Target Sequences with motif0.33%
Number of Background Sequences with motif1.7
Percentage of Background Sequences with motif0.04%
Average Position of motif in Targets253.8 +/- 123.4bp
Average Position of motif in Background404.7 +/- 46.3bp
Strand Bias (log2 ratio + to - strand density)1.7
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..2abfb8258ef59f876355bd4e74a1bb00bc78c554 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.logo.svg @@ -0,0 +1,64 @@ + + + A + G + T + C + + T + C + G + A + + G + T + A + C + + C + G + T + A + + A + C + T + G + + C + G + T + A + + A + C + T + G + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + G + T + A + + A + G + T + C + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..d22b9f020a0c5c03b93a8852981cb60b6f6d4c08 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif10RV.motif @@ -0,0 +1,13 @@ +>CACAGAGTTGAC 5-GTCAACTCTGTG 11.745920 -6.987655 0 T:13.0(0.33%),B:1.7(0.04%),P:1e-3 +0.001 0.888 0.001 0.110 +0.777 0.111 0.111 0.001 +0.110 0.888 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.888 0.110 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.110 0.001 0.001 0.888 +0.111 0.111 0.001 0.777 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.info.html new file mode 100644 index 0000000000000000000000000000000000000000..cb606ab272794e205632e802d2377346c2323953 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.info.html @@ -0,0 +1,1513 @@ +Motif 11 +

Information for 5-GAGGGCACCT (Motif 11)

+ + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+Reverse Opposite:
+ + C + G + T + A + + A + C + T + G + + T + C + A + G + + C + G + A + T + + T + A + C + G + + A + T + G + C + + G + T + A + C + + G + A + T + C + + A + C + G + T + + A + G + T + C + + + +
+ + + + + + + + + + + + + + +
p-value:1e-2
log p-value:-5.724e+00
Information Content per bp:1.833
Number of Target Sequences with motif52.0
Percentage of Target Sequences with motif1.30%
Number of Background Sequences with motif27.0
Percentage of Background Sequences with motif0.68%
Average Position of motif in Targets242.7 +/- 132.1bp
Average Position of motif in Background260.6 +/- 155.8bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.02
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

HIC2/MA0738.1/Jaspar

+
+ + + +
Match Rank:1
Score:0.65 +
Offset:-1 +
Orientation:reverse strand
Alignment:-GAGGGCACCT
NGTGGGCAT--
+		 + + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + T + C + A + G + + A + T + C + G + + A + G + C + T + + A + C + T + G + + C + A + T + G + + A + C + T + G + + A + G + T + C + + C + T + G + A + + A + G + C + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

B52(RRM)/Drosophila_melanogaster-RNCMPT00134-PBM/HughesRNA

+
+ + + +
Match Rank:2
Score:0.65 +
Offset:-1 +
Orientation:forward strand
Alignment:-GAGGGCACCT
GGAGGGN----
+		 + + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + C + T + G + + A + C + T + G + + C + G + T + A + + A + T + C + G + + A + C + T + G + + C + T + A + G + + T + C + A + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

TBP3(MYBrelated)/col-TBP3-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:3
Score:0.63 +
Offset:-2 +
Orientation:forward strand
Alignment:--GAGGGCACCT
VYTAGGGCAN--
+		 + + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + T + C + A + G + + G + A + C + T + + A + C + G + T + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + T + G + + A + G + T + C + + C + G + T + A + + G + T + C + A + + A + C + G + T + + A + C + G + T + + + + +
+
+

HNRNPH2(RRM)/Homo_sapiens-RNCMPT00160-PBM/HughesRNA

+
+ + + +
Match Rank:4
Score:0.63 +
Offset:-2 +
Orientation:forward strand
Alignment:--GAGGGCACCT
GGGAGGG-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + T + C + G + + A + T + C + G + + T + C + A + G + + C + G + T + A + + A + C + T + G + + A + T + C + G + + T + C + A + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

THRb(NR)/Liver-NR1A2-ChIP-Seq(GSE52613)/Homer

+
+ + + +
Match Rank:5
Score:0.62 +
Offset:-1 +
Orientation:forward strand
Alignment:-GAGGGCACCT
TRAGGTCA---
+		 + + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + G + C + A + T + + T + C + A + G + + C + T + G + A + + A + T + C + G + + A + C + T + G + + C + G + A + T + + G + A + T + C + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

AT2G33550(Trihelix)/colamp-AT2G33550-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:6
Score:0.62 +
Offset:-3 +
Orientation:forward strand
Alignment:---GAGGGCACCT--
TTTAAGGGCAYTTTT
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + C + A + T + + G + C + A + T + + C + G + A + T + + C + G + T + A + + C + T + G + A + + C + T + A + G + + A + C + T + G + + C + T + A + G + + G + A + T + C + + G + C + T + A + + G + A + C + T + + G + C + A + T + + G + C + A + T + + G + C + A + T + + G + A + C + T + + + + +
+
+

LIN28A(CSD)/Homo_sapiens-RNCMPT00162-PBM/HughesRNA

+
+ + + +
Match Rank:7
Score:0.62 +
Offset:-2 +
Orientation:forward strand
Alignment:--GAGGGCACCT
CGGAGGA-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + G + T + C + + A + T + C + G + + T + A + C + G + + G + T + C + A + + A + T + C + G + + A + T + C + G + + T + C + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

THAP1/MA0597.1/Jaspar

+
+ + + +
Match Rank:8
Score:0.62 +
Offset:-1 +
Orientation:reverse strand
Alignment:-GAGGGCACCT
TNNGGGCAG--
+		 + + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + C + A + G + T + + T + C + A + G + + G + T + A + C + + C + A + T + G + + C + A + T + G + + C + T + A + G + + G + T + A + C + + C + T + G + A + + T + C + A + G + + A + C + G + T + + A + C + G + T + + + + +
+
+

RBM5(Znf)/Homo_sapiens-RNCMPT00055-PBM/HughesRNA

+
+ + + +
Match Rank:9
Score:0.61 +
Offset:0 +
Orientation:forward strand
Alignment:GAGGGCACCT
GAAGGAA---
+		 + + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + C + T + A + G + + C + G + T + A + + C + T + G + A + + A + C + T + G + + A + C + T + G + + C + G + T + A + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

RGM1/MA0366.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.61 +
Offset:1 +
Orientation:forward strand
Alignment:GAGGGCACCT
-AGGGG----
+		 + + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + + +
+ + + A + C + G + T + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + T + G + + T + A + C + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..0b38ba037d63f31b1c64ba31237b1b212f5edafb --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.logo.svg @@ -0,0 +1,54 @@ + + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.motif new file mode 100644 index 0000000000000000000000000000000000000000..ee03617b551d8f9a0e09b46173512c7efef57ab4 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.motif @@ -0,0 +1,11 @@ +>GAGGGCACCT 5-GAGGGCACCT,BestGuess:HIC2/MA0738.1/Jaspar(0.655) 9.805876 -5.724401 0 T:52.0(1.30%),B:27.0(0.68%),P:1e-2 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.053 0.001 0.893 0.053 +0.001 0.001 0.946 0.052 +0.001 0.052 0.946 0.001 +0.001 0.798 0.113 0.088 +0.789 0.104 0.001 0.106 +0.053 0.646 0.089 0.212 +0.021 0.977 0.001 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..c3d83904d5ef53a092ca968245db9863964bb8ae --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11.similar.html @@ -0,0 +1,132 @@ +motif11 +

Information for motif11

+ + + A + C + T + G + + C + G + T + A + + C + A + T + G + + A + C + T + G + + A + T + C + G + + A + T + G + C + + G + C + T + A + + A + G + T + C + + G + T + A + C + + A + C + G + T + + + +
+Reverse Opposite:
+ + C + G + T + A + + A + C + T + G + + T + C + A + G + + C + G + A + T + + T + A + C + G + + A + T + G + C + + G + T + A + C + + G + A + T + C + + A + C + G + T + + A + G + T + C + + + +
+ + + + + + + + + + + + + +
p-value:1e-2
log p-value:-5.724e+00
Information Content per bp:1.833
Number of Target Sequences with motif52.0
Percentage of Target Sequences with motif1.30%
Number of Background Sequences with motif27.0
Percentage of Background Sequences with motif0.68%
Average Position of motif in Targets242.7 +/- 132.1bp
Average Position of motif in Background260.6 +/- 155.8bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.02
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..b00cbd3e39561d55fbed8facc76bb412ac2e84ad --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.logo.svg @@ -0,0 +1,54 @@ + + + C + G + T + A + + A + C + T + G + + T + C + A + G + + C + G + A + T + + T + A + C + G + + A + T + G + C + + G + T + A + C + + G + A + T + C + + A + C + G + T + + A + G + T + C + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..0092b4605d0471a698fc303d9b74e064704fd4f7 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif11RV.motif @@ -0,0 +1,11 @@ +>AGGTGCCCTC 5-GAGGGCACCT 9.805876 -5.724401 0 T:52.0(1.30%),B:27.0(0.68%),P:1e-2 +0.997 0.001 0.001 0.001 +0.001 0.001 0.977 0.021 +0.212 0.089 0.646 0.053 +0.106 0.001 0.104 0.789 +0.088 0.113 0.798 0.001 +0.001 0.946 0.052 0.001 +0.052 0.946 0.001 0.001 +0.053 0.893 0.001 0.053 +0.001 0.001 0.001 0.997 +0.001 0.997 0.001 0.001 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..84834a5bf0708a05f2a746ec41ad944592b8689c --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.logo.svg @@ -0,0 +1,54 @@ + + + C + A + T + G + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + T + G + A + C + + C + A + G + T + + T + G + A + C + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..7a83fc6bd2945ea633e1ce3a694b075d1e5f5168 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif1RV.motif @@ -0,0 +1,11 @@ +>KYACCTGNTN 1-NANCAGGTRM 3.301854 -72.247213 0 T:2232.0(55.81%),B:1702.3(42.67%),P:1e-31 +0.172 0.080 0.378 0.370 +0.001 0.555 0.001 0.443 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.969 0.029 +0.264 0.274 0.254 0.208 +0.244 0.054 0.248 0.454 +0.254 0.311 0.236 0.199 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.info.html new file mode 100644 index 0000000000000000000000000000000000000000..9bf8d60945143f7fb8d37ae6ed077a3c0a2ce5e7 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.info.html @@ -0,0 +1,1633 @@ +Motif 2 +

Information for 1-AVTTGAGCAATT (Motif 2)

+ + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+Reverse Opposite:
+ + G + C + T + A + + T + C + G + A + + C + G + A + T + + A + G + C + T + + C + T + A + G + + T + A + G + C + + A + C + G + T + + T + G + A + C + + C + G + T + A + + G + T + C + A + + A + G + C + T + + A + C + G + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.132e+01
Information Content per bp:1.525
Number of Target Sequences with motif32.0
Percentage of Target Sequences with motif0.80%
Number of Background Sequences with motif6.7
Percentage of Background Sequences with motif0.17%
Average Position of motif in Targets236.5 +/- 120.9bp
Average Position of motif in Background242.5 +/- 173.9bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

CEBP(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer

+
+ + + +
Match Rank:1
Score:0.72 +
Offset:1 +
Orientation:reverse strand
Alignment:AVTTGAGCAATT
-GTTGCGCAAT-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + T + C + A + G + + A + G + C + T + + A + C + G + T + + C + T + A + G + + G + A + T + C + + C + T + A + G + + G + A + T + C + + G + T + C + A + + C + T + G + A + + A + C + G + T + + A + C + G + T + + + + +
+
+

CEBPG/MA0838.1/Jaspar

+
+ + + +
Match Rank:2
Score:0.69 +
Offset:1 +
Orientation:forward strand
Alignment:AVTTGAGCAATT
-ATTGCGCAAT-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + T + C + G + A + + C + A + G + T + + C + A + G + T + + C + T + A + G + + G + A + T + C + + C + T + A + G + + G + A + T + C + + C + T + G + A + + C + G + T + A + + A + G + C + T + + A + C + G + T + + + + +
+
+

MAC1/MA0326.1/Jaspar

+
+ + + +
Match Rank:3
Score:0.68 +
Offset:3 +
Orientation:reverse strand
Alignment:AVTTGAGCAATT
---TGAGCAAA-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + G + T + A + + A + C + T + G + + A + G + T + C + + C + G + T + A + + G + T + C + A + + C + G + T + A + + A + C + G + T + + + + +
+
+

MAC1/MA0326.1/Jaspar

+
+ + + +
Match Rank:4
Score:0.68 +
Offset:3 +
Orientation:reverse strand
Alignment:AVTTGAGCAATT
---TGAGCAAA-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + G + T + A + + A + C + T + G + + A + G + T + C + + C + G + T + A + + G + T + C + A + + C + G + T + A + + A + C + G + T + + + + +
+
+

PB0042.1_Mafk_1/Jaspar

+
+ + + +
Match Rank:5
Score:0.68 +
Offset:0 +
Orientation:reverse strand
Alignment:AVTTGAGCAATT---
AAGTCAGCANTTTTN
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + T + G + A + + C + G + T + A + + T + C + A + G + + C + G + A + T + + G + T + A + C + + C + G + T + A + + C + A + T + G + + G + T + A + C + + C + T + G + A + + G + C + A + T + + C + G + A + T + + G + C + A + T + + G + C + A + T + + G + C + A + T + + G + C + T + A + + + + +
+
+

Dr/dmmpmm(Noyes_hd)/fly

+
+ + + +
Match Rank:6
Score:0.67 +
Offset:4 +
Orientation:forward strand
Alignment:AVTTGAGCAATT--
----GACCAATTAA
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + A + C + G + + C + G + T + A + + A + T + G + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + C + G + T + A + + A + C + G + T + + + + +
+
+

CEBPD/MA0836.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.67 +
Offset:1 +
Orientation:forward strand
Alignment:AVTTGAGCAATT
-ATTGCGCAAT-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + T + C + G + A + + A + C + G + T + + A + C + G + T + + C + T + A + G + + G + A + T + C + + T + C + A + G + + G + T + A + C + + G + T + C + A + + C + G + T + A + + A + G + C + T + + A + C + G + T + + + + +
+
+

slbo/dmmpmm(Bergman)/fly

+
+ + + +
Match Rank:8
Score:0.67 +
Offset:2 +
Orientation:reverse strand
Alignment:AVTTGAGCAATT
--TTNNACAATA
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + A + G + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + G + T + A + C + + + + +
+
+

CEBPB/MA0466.2/Jaspar

+
+ + + +
Match Rank:9
Score:0.67 +
Offset:1 +
Orientation:forward strand
Alignment:AVTTGAGCAATT
-ATTGCGCAAT-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + T + C + G + A + + G + A + C + T + + C + A + G + T + + C + T + A + G + + G + A + T + C + + T + C + A + G + + G + T + A + C + + T + G + C + A + + G + C + T + A + + A + G + C + T + + A + C + G + T + + + + +
+
+

CEBPE/MA0837.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.67 +
Offset:1 +
Orientation:forward strand
Alignment:AVTTGAGCAATT
-ATTGCGCAAT-
+		 + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + + +
+ + + A + C + G + T + + T + C + G + A + + G + A + C + T + + C + A + G + T + + C + T + A + G + + G + A + T + C + + T + C + A + G + + G + T + A + C + + G + T + C + A + + C + G + T + A + + A + G + C + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..79f41b8f805bb908809d827f3970895361bb41bf --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.logo.svg @@ -0,0 +1,64 @@ + + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.motif new file mode 100644 index 0000000000000000000000000000000000000000..8479df9fdf8b399856c51e611ef62c101f3b5a09 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.motif @@ -0,0 +1,13 @@ +>AVTTGAGCAATT 1-AVTTGAGCAATT,BestGuess:CEBP(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer(0.721) 8.994152 -11.321453 0 T:32.0(0.80%),B:6.7(0.17%),P:1e-4 +0.575 0.210 0.199 0.016 +0.339 0.253 0.272 0.136 +0.170 0.027 0.211 0.592 +0.240 0.190 0.032 0.538 +0.027 0.172 0.618 0.183 +0.682 0.151 0.138 0.029 +0.047 0.197 0.672 0.084 +0.027 0.892 0.025 0.056 +0.736 0.045 0.192 0.027 +0.613 0.027 0.014 0.346 +0.027 0.181 0.152 0.640 +0.201 0.029 0.129 0.641 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..3bfc7a3e0180f848b9a83f27251a35f862d6f5a9 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2.similar.html @@ -0,0 +1,152 @@ +motif2 +

Information for motif2

+ + + T + G + C + A + + T + C + G + A + + C + A + G + T + + G + C + A + T + + A + C + T + G + + T + G + C + A + + A + T + C + G + + G + A + T + C + + T + C + G + A + + G + C + T + A + + A + G + C + T + + C + G + A + T + + + +
+Reverse Opposite:
+ + G + C + T + A + + T + C + G + A + + C + G + A + T + + A + G + C + T + + C + T + A + G + + T + A + G + C + + A + C + G + T + + T + G + A + C + + C + G + T + A + + G + T + C + A + + A + G + C + T + + A + C + G + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.132e+01
Information Content per bp:1.525
Number of Target Sequences with motif32.0
Percentage of Target Sequences with motif0.80%
Number of Background Sequences with motif6.7
Percentage of Background Sequences with motif0.17%
Average Position of motif in Targets236.5 +/- 120.9bp
Average Position of motif in Background242.5 +/- 173.9bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..18389ac0bad828fbb0030c7b97afd82bdd1243bb --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.logo.svg @@ -0,0 +1,64 @@ + + + G + C + T + A + + T + C + G + A + + C + G + A + T + + A + G + C + T + + C + T + A + G + + T + A + G + C + + A + C + G + T + + T + G + A + C + + C + G + T + A + + G + T + C + A + + A + G + C + T + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..cde7cc0d44e8f8fa30734419ad19c6da2221abbc --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif2RV.motif @@ -0,0 +1,13 @@ +>AATTGCTCAABT 1-AVTTGAGCAATT 8.994152 -11.321453 0 T:32.0(0.80%),B:6.7(0.17%),P:1e-4 +0.641 0.129 0.029 0.201 +0.640 0.152 0.181 0.027 +0.346 0.014 0.027 0.613 +0.027 0.192 0.045 0.736 +0.056 0.025 0.892 0.027 +0.084 0.672 0.197 0.047 +0.029 0.138 0.151 0.682 +0.183 0.618 0.172 0.027 +0.538 0.032 0.190 0.240 +0.592 0.211 0.027 0.170 +0.136 0.272 0.253 0.339 +0.016 0.199 0.210 0.575 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.info.html new file mode 100644 index 0000000000000000000000000000000000000000..b15af39630fe30172545890a274b8d192bd26c3b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.info.html @@ -0,0 +1,1153 @@ +Motif 3 +

Information for 3-ATWTTTTT (Motif 3)

+ + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+Reverse Opposite:
+ + T + G + C + A + + G + T + C + A + + T + G + C + A + + T + G + C + A + + C + G + T + A + + C + G + T + A + + C + G + T + A + + A + G + C + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.062e+01
Information Content per bp:1.504
Number of Target Sequences with motif2198.0
Percentage of Target Sequences with motif54.96%
Number of Background Sequences with motif2010.5
Percentage of Background Sequences with motif50.40%
Average Position of motif in Targets246.2 +/- 151.2bp
Average Position of motif in Background247.7 +/- 161.2bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.43
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

PABPC4(RRM)/Homo_sapiens-RNCMPT00043-PBM/HughesRNA

+
+ + + +
Match Rank:1
Score:0.84 +
Offset:1 +
Orientation:reverse strand
Alignment:ATWTTTTT
-TTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + G + C + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + + + +
+
+

Pp_0228(RRM)/Physcomitrella_patens-RNCMPT00228-PBM/HughesRNA

+
+ + + +
Match Rank:2
Score:0.84 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-TTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + G + C + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + + + +
+
+

Tv_0236(RRM)/Trichomonas_vaginalis-RNCMPT00236-PBM/HughesRNA

+
+ + + +
Match Rank:3
Score:0.83 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-TTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + G + C + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + A + C + G + T + + + + +
+
+

Ot_0262(RRM)/Ostreococcus_tauri-RNCMPT00262-PBM/HughesRNA

+
+ + + +
Match Rank:4
Score:0.83 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-TTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + A + C + G + T + + + + +
+
+

REM19(REM)/colamp-REM19-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:5
Score:0.82 +
Offset:0 +
Orientation:reverse strand
Alignment:ATWTTTTT
TTTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + C + G + A + T + + C + G + A + T + + C + G + A + T + + A + C + G + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + + + +
+
+

Smp_067420(RRM)/Schistosoma_mansoni-RNCMPT00232-PBM/HughesRNA

+
+ + + +
Match Rank:6
Score:0.82 +
Offset:0 +
Orientation:forward strand
Alignment:ATWTTTTT
ATTTTTT-
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + C + G + A + T + + C + G + A + T + + C + A + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + A + C + G + T + + + + +
+
+

TIAR-3(RRM)/Caenorhabditis_elegans-RNCMPT00005-PBM/HughesRNA

+
+ + + +
Match Rank:7
Score:0.81 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-CTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + G + A + T + C + + G + C + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

SXL(RRM)/Drosophila_melanogaster-RNCMPT00119-PBM/HughesRNA

+
+ + + +
Match Rank:8
Score:0.81 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-TTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + G + A + C + T + + G + A + C + T + + C + G + A + T + + C + G + A + T + + C + G + A + T + + C + G + A + T + + C + G + A + T + + + + +
+
+

TIA1(RRM)/Homo_sapiens-RNCMPT00165-PBM/HughesRNA

+
+ + + +
Match Rank:9
Score:0.81 +
Offset:2 +
Orientation:forward strand
Alignment:ATWTTTTT-
--TTTTTTC
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + G + C + A + T + + A + C + G + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + + + +
+
+

CPEB4(RRM)/Homo_sapiens-RNCMPT00158-PBM/HughesRNA

+
+ + + +
Match Rank:10
Score:0.81 +
Offset:1 +
Orientation:forward strand
Alignment:ATWTTTTT
-CTTTTTT
+		 + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + G + A + T + C + + G + C + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..23f34fd40db098f2d70af935ae25adc719747b6b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.logo.svg @@ -0,0 +1,44 @@ + + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.motif new file mode 100644 index 0000000000000000000000000000000000000000..003f70f088aa4428ea7dd1d40547dae36d1ed2b1 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.motif @@ -0,0 +1,9 @@ +>ATWTTTTT 3-ATWTTTTT,BestGuess:PABPC4(RRM)/Homo_sapiens-RNCMPT00043-PBM/HughesRNA(0.844) 4.857828 -10.622533 0 T:2198.0(54.96%),B:2010.5(50.40%),P:1e-4 +0.530 0.184 0.192 0.094 +0.307 0.213 0.001 0.479 +0.431 0.108 0.001 0.460 +0.031 0.030 0.001 0.938 +0.051 0.125 0.193 0.631 +0.111 0.153 0.214 0.522 +0.148 0.147 0.218 0.486 +0.001 0.207 0.218 0.574 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..71c827a9dbad6247ae69ae89bbb01e6e961165e8 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar.html @@ -0,0 +1,158 @@ +motif3 +

Information for motif3

+ + + T + C + G + A + + G + C + A + T + + G + C + A + T + + G + C + A + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + + +
+Reverse Opposite:
+ + T + G + C + A + + G + T + C + A + + T + G + C + A + + T + G + C + A + + C + G + T + A + + C + G + T + A + + C + G + T + A + + A + G + C + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.062e+01
Information Content per bp:1.504
Number of Target Sequences with motif2198.0
Percentage of Target Sequences with motif54.96%
Number of Background Sequences with motif2010.5
Percentage of Background Sequences with motif50.40%
Average Position of motif in Targets246.2 +/- 151.2bp
Average Position of motif in Background247.7 +/- 161.2bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.43
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.649 + + G + T + C + A + + A + G + T + C + + C + G + T + A + + A + G + C + T + + C + G + A + T + + G + A + C + T + + C + A + G + T + + G + A + T + C + + + + +1e-3-6.93316654.59%51.09%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar1.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..aae15dd181f94d0d6b0029d7d60536578d59bcd3 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3.similar1.motif @@ -0,0 +1,9 @@ +>ACATTTTC 5-ACATTTTC 4.872034 -6.933166 0 T:2183.0(54.59%),B:2038.1(51.09%),P:1e-3 +0.698 0.139 0.076 0.087 +0.074 0.764 0.076 0.086 +0.752 0.068 0.084 0.096 +0.060 0.099 0.073 0.768 +0.121 0.029 0.042 0.808 +0.072 0.106 0.053 0.769 +0.099 0.072 0.102 0.727 +0.097 0.723 0.076 0.104 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..9468563354133cc466ffa8ba7fe659c4f2eb987f --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.logo.svg @@ -0,0 +1,44 @@ + + + T + G + C + A + + G + T + C + A + + T + G + C + A + + T + G + C + A + + C + G + T + A + + C + G + T + A + + C + G + T + A + + A + G + C + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..69e3dcdcbea108bd6b5867d02a5b117206b483e7 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif3RV.motif @@ -0,0 +1,9 @@ +>AAAAAWAT 3-ATWTTTTT 4.857828 -10.622533 0 T:2198.0(54.96%),B:2010.5(50.40%),P:1e-4 +0.574 0.218 0.207 0.001 +0.486 0.218 0.147 0.148 +0.522 0.214 0.153 0.111 +0.631 0.193 0.125 0.051 +0.938 0.001 0.030 0.031 +0.460 0.001 0.108 0.431 +0.479 0.001 0.213 0.307 +0.094 0.192 0.184 0.530 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.info.html new file mode 100644 index 0000000000000000000000000000000000000000..4f45ba7080f38e5984401ed0748649dde95650ba --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.info.html @@ -0,0 +1,1833 @@ +Motif 4 +

Information for 3-TACCTCGTACGT (Motif 4)

+ + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + + +
+Reverse Opposite:
+ + T + G + C + A + + T + G + A + C + + T + A + C + G + + G + C + A + T + + T + C + G + A + + A + G + T + C + + T + C + A + G + + G + C + T + A + + C + T + A + G + + C + A + T + G + + C + G + A + T + + G + T + C + A + + + +
+ + + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.061e+01
Information Content per bp:1.559
Number of Target Sequences with motif24.0
Percentage of Target Sequences with motif0.60%
Number of Background Sequences with motif3.7
Percentage of Background Sequences with motif0.09%
Average Position of motif in Targets216.3 +/- 100.8bp
Average Position of motif in Background181.3 +/- 113.4bp
Strand Bias (log2 ratio + to - strand density)-0.5
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

SMZ/MA0553.1/Jaspar

+
+ + + +
Match Rank:1
Score:0.70 +
Offset:2 +
Orientation:forward strand
Alignment:TACCTCGTACGT
--CCTCGTAC--
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + T + G + C + + A + C + G + T + + A + G + T + C + + A + C + T + G + + A + C + G + T + + G + T + C + A + + A + G + T + C + + A + C + G + T + + A + C + G + T + + + + +
+
+

SPL9(SBP)/colamp-SPL9-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:2
Score:0.63 +
Offset:4 +
Orientation:forward strand
Alignment:TACCTCGTACGT
----BTGTACTT
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + G + A + C + T + + A + C + T + G + + A + C + G + T + + G + T + C + A + + A + G + T + C + + A + C + G + T + + C + G + A + T + + + + +
+
+

SPL1(SBP)/colamp-SPL1-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:3
Score:0.60 +
Offset:4 +
Orientation:forward strand
Alignment:TACCTCGTACGT--
----HYGTACDTWH
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + A + C + + G + A + T + C + + C + T + A + G + + C + G + A + T + + G + T + C + A + + G + T + A + C + + C + T + A + G + + C + A + G + T + + G + C + A + T + + G + A + C + T + + + + +
+
+

SPL9/MA1322.1/Jaspar

+
+ + + +
Match Rank:4
Score:0.58 +
Offset:3 +
Orientation:forward strand
Alignment:TACCTCGTACGT--
---ATTGTACGGAT
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + C + A + + G + C + A + T + + A + G + C + T + + A + C + T + G + + C + G + A + T + + G + T + C + A + + A + G + T + C + + A + C + T + G + + C + A + T + G + + G + C + T + A + + G + A + C + T + + + + +
+
+

AtSPL3(SBP)/Arabidopsis thaliana/AthaMap

+
+ + + +
Match Rank:5
Score:0.58 +
Offset:0 +
Orientation:reverse strand
Alignment:TACCTCGTACGT----
NAANNNGTACGGNAAN
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + T + A + G + + C + G + T + A + + C + G + T + A + + C + T + G + A + + C + G + A + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + C + G + T + A + + A + G + T + C + + A + C + T + G + + C + A + T + G + + G + A + T + C + + G + C + A + T + + G + C + T + A + + G + A + C + T + + + + +
+
+

SPL3/MA0577.1/Jaspar

+
+ + + +
Match Rank:6
Score:0.58 +
Offset:0 +
Orientation:reverse strand
Alignment:TACCTCGTACGT----
NAANNNGTACGGNAAN
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + T + A + G + + C + G + T + A + + C + G + T + A + + C + T + G + A + + C + G + A + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + C + G + T + A + + A + G + T + C + + A + C + T + G + + C + A + T + G + + G + A + T + C + + G + C + A + T + + G + C + T + A + + G + A + C + T + + + + +
+
+

SPL15(SBP)/colamp-SPL15-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:7
Score:0.57 +
Offset:3 +
Orientation:reverse strand
Alignment:TACCTCGTACGT---
---WHTGTACKKWHW
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + C + A + T + + G + C + A + T + + G + A + C + T + + A + C + T + G + + A + C + G + T + + C + G + T + A + + A + G + T + C + + A + C + T + G + + C + A + T + G + + C + G + T + A + + G + C + A + T + + G + C + T + A + + + + +
+
+

SPL5(SBP)/colamp-SPL5-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:8
Score:0.56 +
Offset:3 +
Orientation:forward strand
Alignment:TACCTCGTACGT---
---NNHGTACGGHNN
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + T + A + + G + C + A + T + + G + A + C + T + + C + T + A + G + + A + C + G + T + + G + T + C + A + + A + G + T + C + + A + C + T + G + + C + T + A + G + + G + C + T + A + + G + T + A + C + + G + C + T + A + + + + +
+
+

SPL11/MA1056.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.56 +
Offset:2 +
Orientation:forward strand
Alignment:TACCTCGTACGT--
--TATCGTACGGAT
+		 + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + T + A + + A + G + C + T + + G + A + T + C + + A + C + T + G + + A + C + G + T + + C + G + T + A + + A + G + T + C + + A + C + T + G + + A + C + T + G + + C + G + T + A + + A + G + C + T + + + + +
+
+

SD0001.1_at_AC_acceptor/Jaspar

+
+ + + +
Match Rank:10
Score:0.56 +
Offset:-5 +
Orientation:reverse strand
Alignment:-----TACCTCGTACGT
NNACTTACCTN------
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + + +
+ + + C + T + G + A + + G + A + C + T + + G + C + T + A + + G + A + T + C + + G + C + A + T + + G + A + C + T + + C + G + T + A + + A + G + T + C + + G + A + T + C + + G + C + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..a17eb0bafbed116db7b95ec812038e8988e73634 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.logo.svg @@ -0,0 +1,64 @@ + + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.motif new file mode 100644 index 0000000000000000000000000000000000000000..3ada503c48bc12b6efaba5bdacb6b06616f53ed6 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.motif @@ -0,0 +1,13 @@ +>TACCTCGTACGT 3-TACCTCGTACGT,BestGuess:SMZ/MA0553.1/Jaspar(0.700) 9.488826 -10.609444 0 T:24.0(0.60%),B:3.7(0.09%),P:1e-4 +0.117 0.004 0.158 0.721 +0.894 0.001 0.001 0.104 +0.121 0.683 0.079 0.117 +0.090 0.665 0.056 0.189 +0.218 0.079 0.083 0.620 +0.053 0.558 0.170 0.219 +0.121 0.117 0.645 0.117 +0.001 0.143 0.090 0.766 +0.714 0.075 0.094 0.117 +0.001 0.592 0.283 0.124 +0.064 0.144 0.532 0.260 +0.001 0.072 0.120 0.807 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..c1c257e9f6a8305ac963c14072e9ac8cb85a5bcf --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4.similar.html @@ -0,0 +1,152 @@ +motif4 +

Information for motif4

+ + + C + A + G + T + + C + G + T + A + + G + T + A + C + + G + A + T + C + + C + G + A + T + + A + G + T + C + + C + T + A + G + + A + G + C + T + + C + G + T + A + + A + T + G + C + + A + C + T + G + + A + C + G + T + + + +
+Reverse Opposite:
+ + T + G + C + A + + T + G + A + C + + T + A + C + G + + G + C + A + T + + T + C + G + A + + A + G + T + C + + T + C + A + G + + G + C + T + A + + C + T + A + G + + C + A + T + G + + C + G + A + T + + G + T + C + A + + + +
+ + + + + + + + + + + + + +
p-value:1e-4
log p-value:-1.061e+01
Information Content per bp:1.559
Number of Target Sequences with motif24.0
Percentage of Target Sequences with motif0.60%
Number of Background Sequences with motif3.7
Percentage of Background Sequences with motif0.09%
Average Position of motif in Targets216.3 +/- 100.8bp
Average Position of motif in Background181.3 +/- 113.4bp
Strand Bias (log2 ratio + to - strand density)-0.5
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..059bff337151da8b185c40d266cc0d64b12d101d --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.logo.svg @@ -0,0 +1,64 @@ + + + T + G + C + A + + T + G + A + C + + T + A + C + G + + G + C + A + T + + T + C + G + A + + A + G + T + C + + T + C + A + G + + G + C + T + A + + C + T + A + G + + C + A + T + G + + C + G + A + T + + G + T + C + A + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..4654053b64dfdcbd611a61ecc3dca1496a9ff6a7 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif4RV.motif @@ -0,0 +1,13 @@ +>ACGTACGAGGTA 3-TACCTCGTACGT 9.488826 -10.609444 0 T:24.0(0.60%),B:3.7(0.09%),P:1e-4 +0.807 0.120 0.072 0.001 +0.260 0.532 0.144 0.064 +0.124 0.283 0.592 0.001 +0.117 0.094 0.075 0.714 +0.766 0.090 0.143 0.001 +0.117 0.645 0.117 0.121 +0.219 0.170 0.558 0.053 +0.620 0.083 0.079 0.218 +0.189 0.056 0.665 0.090 +0.117 0.079 0.683 0.121 +0.104 0.001 0.001 0.894 +0.721 0.158 0.004 0.117 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.info.html new file mode 100644 index 0000000000000000000000000000000000000000..0aa6237912f6643aaf8e3d5672785bb1fa208711 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.info.html @@ -0,0 +1,1753 @@ +Motif 5 +

Information for 2-CCATCAAGGT (Motif 5)

+ + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + + +
+Reverse Opposite:
+ + G + T + C + A + + G + T + A + C + + T + A + G + C + + A + C + G + T + + A + C + G + T + + A + T + C + G + + C + T + G + A + + C + A + G + T + + A + T + C + G + + A + C + T + G + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-8.980e+00
Information Content per bp:1.834
Number of Target Sequences with motif53.0
Percentage of Target Sequences with motif1.33%
Number of Background Sequences with motif21.7
Percentage of Background Sequences with motif0.54%
Average Position of motif in Targets215.1 +/- 105.9bp
Average Position of motif in Background206.4 +/- 93.1bp
Strand Bias (log2 ratio + to - strand density)0.6
Multiplicity (# of sites on avg that occur together)1.03
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

ZAP1/ZAP1_YPD/[](Harbison)/Yeast

+
+ + + +
Match Rank:1
Score:0.74 +
Offset:-1 +
Orientation:forward strand
Alignment:-CCATCAAGGT---
ACCCTCAAGGTTGT
+		 + + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + G + T + C + + A + C + G + T + + G + T + A + C + + C + G + T + A + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + A + G + C + T + + T + C + A + G + + A + C + G + T + + + + +
+
+

HAP3(CCAATHAP3)/col-HAP3-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:2
Score:0.72 +
Offset:-2 +
Orientation:reverse strand
Alignment:--CCATCAAGGT
WTCCATCA----
+		 + + + A + C + G + T + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + + +
+ + + G + C + A + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

PH0134.1_Pbx1/Jaspar

+
+ + + +
Match Rank:3
Score:0.71 +
Offset:-4 +
Orientation:forward strand
Alignment:----CCATCAAGGT---
TCACCCATCAATAAACA
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + A + C + T + + A + G + T + C + + C + G + T + A + + G + A + T + C + + G + T + A + C + + T + G + A + C + + C + T + G + A + + C + G + A + T + + G + T + A + C + + G + T + C + A + + G + C + T + A + + C + G + A + T + + G + T + A + C + + G + C + T + A + + C + G + A + T + + T + G + A + C + + T + G + C + A + + + + +
+
+

SNRNP70(RRM)/Homo_sapiens-RNCMPT00070-PBM/HughesRNA

+
+ + + +
Match Rank:4
Score:0.71 +
Offset:1 +
Orientation:forward strand
Alignment:CCATCAAGGT
-GATCAAG--
+		 + + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + C + T + A + G + + C + G + T + A + + A + C + G + T + + A + G + T + C + + C + G + T + A + + C + G + T + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + + + +
+
+

ESRRB/MA0141.3/Jaspar

+
+ + + +
Match Rank:5
Score:0.71 +
Offset:3 +
Orientation:forward strand
Alignment:CCATCAAGGT----
---TCAAGGTCATA
+		 + + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + C + T + + T + A + G + C + + G + C + T + A + + T + C + G + A + + T + C + A + G + + A + T + C + G + + A + G + C + T + + G + A + T + C + + C + T + G + A + + G + C + A + T + + G + C + T + A + + + + +
+
+

Abd-B/dmmpmm(Bergman)/fly

+
+ + + +
Match Rank:6
Score:0.70 +
Offset:-4 +
Orientation:forward strand
Alignment:----CCATCAAGGT
NNNGCCATAAANGN
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + + +
+ + + T + A + C + G + + A + C + G + T + + A + T + G + C + + A + T + C + G + + A + G + T + C + + G + T + A + C + + C + T + G + A + + C + G + A + T + + G + C + T + A + + G + C + T + A + + T + G + C + A + + A + C + G + T + + A + T + C + G + + A + G + C + T + + + + +
+
+

ZAP1/MA0440.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.69 +
Offset:-1 +
Orientation:forward strand
Alignment:-CCATCAAGGT----
ACCTTAAAGGTCATG
+		 + + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + G + C + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + T + C + G + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + T + G + A + + G + A + C + T + + C + T + A + G + + + + +
+
+

ZAP1/MA0440.1/Jaspar

+
+ + + +
Match Rank:8
Score:0.69 +
Offset:-1 +
Orientation:forward strand
Alignment:-CCATCAAGGT----
ACCTTAAAGGTCATG
+		 + + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + G + C + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + T + C + G + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + T + G + A + + G + A + C + T + + C + T + A + G + + + + +
+
+

Esrrg/MA0643.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.69 +
Offset:3 +
Orientation:forward strand
Alignment:CCATCAAGGT---
---TCAAGGTCAT
+		 + + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + C + T + + T + A + G + C + + C + T + G + A + + T + C + G + A + + C + A + T + G + + A + T + C + G + + C + A + G + T + + A + G + T + C + + C + T + G + A + + G + C + A + T + + + + +
+
+

ZAP1(MacIsaac)/Yeast

+
+ + + +
Match Rank:10
Score:0.68 +
Offset:-1 +
Orientation:forward strand
Alignment:-CCATCAAGGT----
ACCTTAAAGGTCATG
+		 + + + A + C + G + T + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + G + C + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + T + C + G + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + T + G + A + + G + A + C + T + + C + T + A + G + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..a08962ad547def1f5c1b4c69c3c5cb7066d9cfeb --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.logo.svg @@ -0,0 +1,54 @@ + + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.motif new file mode 100644 index 0000000000000000000000000000000000000000..42e3e21080bccc4f70c0a4f6ca67a4f9f6298550 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.motif @@ -0,0 +1,11 @@ +>CCATCAAGGT 2-CCATCAAGGT,BestGuess:ZAP1/ZAP1_YPD/[](Harbison)/Yeast(0.743) 9.745095 -8.980493 0 T:53.0(1.33%),B:21.7(0.54%),P:1e-3 +0.121 0.858 0.020 0.001 +0.001 0.892 0.106 0.001 +0.899 0.050 0.001 0.050 +0.001 0.049 0.001 0.949 +0.001 0.899 0.099 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.050 0.200 0.600 0.150 +0.001 0.001 0.949 0.049 +0.001 0.001 0.049 0.949 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..15a26c0c76c816e7d0b0a14e8bb2e3fd3d1b6d1d --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5.similar.html @@ -0,0 +1,132 @@ +motif5 +

Information for motif5

+ + + T + G + A + C + + A + T + G + C + + G + C + T + A + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + + +
+Reverse Opposite:
+ + G + T + C + A + + G + T + A + C + + T + A + G + C + + A + C + G + T + + A + C + G + T + + A + T + C + G + + C + T + G + A + + C + A + G + T + + A + T + C + G + + A + C + T + G + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-8.980e+00
Information Content per bp:1.834
Number of Target Sequences with motif53.0
Percentage of Target Sequences with motif1.33%
Number of Background Sequences with motif21.7
Percentage of Background Sequences with motif0.54%
Average Position of motif in Targets215.1 +/- 105.9bp
Average Position of motif in Background206.4 +/- 93.1bp
Strand Bias (log2 ratio + to - strand density)0.6
Multiplicity (# of sites on avg that occur together)1.03
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..0f049283a2ace9a4dbe9ce5b7c48d55c7199aa64 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.logo.svg @@ -0,0 +1,54 @@ + + + G + T + C + A + + G + T + A + C + + T + A + G + C + + A + C + G + T + + A + C + G + T + + A + T + C + G + + C + T + G + A + + C + A + G + T + + A + T + C + G + + A + C + T + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..4421c6bd3137eeac1bbeb2c066f408b9e0634b29 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif5RV.motif @@ -0,0 +1,11 @@ +>ACCTTGATGG 2-CCATCAAGGT 9.745095 -8.980493 0 T:53.0(1.33%),B:21.7(0.54%),P:1e-3 +0.949 0.049 0.001 0.001 +0.049 0.949 0.001 0.001 +0.150 0.600 0.200 0.050 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.099 0.899 0.001 +0.949 0.001 0.049 0.001 +0.050 0.001 0.050 0.899 +0.001 0.106 0.892 0.001 +0.001 0.020 0.858 0.121 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.info.html new file mode 100644 index 0000000000000000000000000000000000000000..a6b9642ba3166a65ca8715d6078a011ca10ef58a --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.info.html @@ -0,0 +1,1633 @@ +Motif 6 +

Information for 3-CACCTCACCA (Motif 6)

+ + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+Reverse Opposite:
+ + A + G + C + T + + T + A + C + G + + C + A + T + G + + A + G + C + T + + C + A + T + G + + T + C + G + A + + C + T + A + G + + A + T + C + G + + A + C + G + T + + C + T + A + G + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.812e+00
Information Content per bp:1.646
Number of Target Sequences with motif184.0
Percentage of Target Sequences with motif4.60%
Number of Background Sequences with motif125.5
Percentage of Background Sequences with motif3.15%
Average Position of motif in Targets253.6 +/- 133.7bp
Average Position of motif in Background249.9 +/- 144.5bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

AGL55/MA1202.1/Jaspar

+
+ + + +
Match Rank:1
Score:0.77 +
Offset:4 +
Orientation:forward strand
Alignment:CACCTCACCA
----TCACCA
+		 + + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + C + G + T + A + + + + +
+
+

ASHR1(ND)/col-ASHR1-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:2
Score:0.75 +
Offset:3 +
Orientation:reverse strand
Alignment:CACCTCACCA-
---NTCACCAN
+		 + + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + C + A + G + + C + G + A + T + + G + T + A + C + + C + G + T + A + + T + A + G + C + + G + T + A + C + + G + C + T + A + + G + A + C + T + + + + +
+
+

bZIP44(bZIP)/colamp-bZIP44-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:3
Score:0.71 +
Offset:-5 +
Orientation:forward strand
Alignment:-----CACCTCACCA
NDTGCCACGTCAGCH
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + A + C + G + T + + C + G + A + T + + C + A + G + T + + A + C + T + G + + G + T + A + C + + A + G + T + C + + C + G + T + A + + A + T + G + C + + T + C + A + G + + A + C + G + T + + G + T + A + C + + C + T + G + A + + A + C + T + G + + G + A + T + C + + G + T + C + A + + + + +
+
+

bZIP911/MA0097.1/Jaspar

+
+ + + +
Match Rank:4
Score:0.71 +
Offset:-3 +
Orientation:reverse strand
Alignment:---CACCTCACCA
GGCCACGTCATC-
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + T + G + C + + C + G + T + A + + A + G + T + C + + A + C + T + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + G + C + T + + G + A + T + C + + A + C + G + T + + + + +
+
+

bZIP42/MA1350.1/Jaspar

+
+ + + +
Match Rank:5
Score:0.70 +
Offset:-2 +
Orientation:reverse strand
Alignment:--CACCTCACCA
GCCACGTCAGCA
+		 + + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + A + C + T + G + + G + T + A + C + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + C + T + G + + A + C + G + T + + G + T + A + C + + C + G + T + A + + A + C + T + G + + G + T + A + C + + C + G + T + A + + + + +
+
+

TGA1/MA0588.1/Jaspar

+
+ + + +
Match Rank:6
Score:0.70 +
Offset:-1 +
Orientation:reverse strand
Alignment:-CACCTCACCA
TNACGTCANCA
+		 + + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + G + C + A + T + + A + G + C + T + + T + C + G + A + + A + G + T + C + + C + T + A + G + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + T + G + C + + T + G + C + A + + + + +
+
+

CREB3/MA0638.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.70 +
Offset:-4 +
Orientation:forward strand
Alignment:----CACCTCACCA
GTGCCACGTCATCA
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + T + C + A + G + + A + G + C + T + + C + A + T + G + + G + T + A + C + + A + T + G + C + + C + G + T + A + + A + G + T + C + + C + T + A + G + + G + A + C + T + + T + G + A + C + + C + T + G + A + + A + G + C + T + + G + T + A + C + + T + C + G + A + + + + +
+
+

GBF6/MA1334.1/Jaspar

+
+ + + +
Match Rank:8
Score:0.70 +
Offset:-3 +
Orientation:forward strand
Alignment:---CACCTCACCA--
TGCCACGTCAGCATC
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + C + A + T + G + + G + T + A + C + + A + T + G + C + + C + G + T + A + + A + T + G + C + + T + C + A + G + + A + C + G + T + + T + G + A + C + + C + T + G + A + + A + C + T + G + + G + T + A + C + + G + C + T + A + + G + C + A + T + + G + A + T + C + + + + +
+
+

bZIP48/MA1345.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.70 +
Offset:-2 +
Orientation:forward strand
Alignment:--CACCTCACCA--
GCCACGTCAGCATC
+		 + + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + A + T + G + + G + T + A + C + + A + G + T + C + + C + G + T + A + + G + A + T + C + + T + C + A + G + + A + G + C + T + + G + T + A + C + + C + T + G + A + + A + C + T + G + + G + T + A + C + + G + C + T + A + + G + C + A + T + + G + A + T + C + + + + +
+
+

bZIP42(bZIP)/colamp-bZIP42-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:10
Score:0.70 +
Offset:-2 +
Orientation:forward strand
Alignment:--CACCTCACCA
GCCACGTCAGCA
+		 + + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + + +
+ + + A + C + T + G + + G + T + A + C + + A + G + T + C + + C + G + T + A + + A + G + T + C + + T + A + C + G + + A + C + G + T + + G + T + A + C + + C + G + T + A + + A + C + T + G + + A + G + T + C + + G + C + T + A + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..4d2dec408cfeb11b91cb36296bfe8aea3f2c1441 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.logo.svg @@ -0,0 +1,54 @@ + + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.motif new file mode 100644 index 0000000000000000000000000000000000000000..d6a3634fdb2cb4801248d793f14956da1b04df8f --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.motif @@ -0,0 +1,11 @@ +>CACCTCACCA 3-CACCTCACCA,BestGuess:AGL55/MA1202.1/Jaspar(0.766) 7.271332 -7.811697 0 T:184.0(4.60%),B:125.5(3.15%),P:1e-3 +0.077 0.764 0.075 0.084 +0.842 0.065 0.056 0.037 +0.059 0.822 0.060 0.059 +0.072 0.794 0.058 0.076 +0.030 0.069 0.058 0.843 +0.089 0.832 0.039 0.040 +0.808 0.069 0.092 0.031 +0.098 0.739 0.065 0.098 +0.056 0.788 0.088 0.068 +0.780 0.076 0.084 0.060 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..d605dd8e33a451e90154cdde7edfbf15cb1bf23c --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6.similar.html @@ -0,0 +1,132 @@ +motif6 +

Information for motif6

+ + + G + A + T + C + + T + G + C + A + + A + T + G + C + + G + A + T + C + + A + G + C + T + + G + T + A + C + + T + C + G + A + + G + A + T + C + + A + T + G + C + + T + C + G + A + + + +
+Reverse Opposite:
+ + A + G + C + T + + T + A + C + G + + C + A + T + G + + A + G + C + T + + C + A + T + G + + T + C + G + A + + C + T + A + G + + A + T + C + G + + A + C + G + T + + C + T + A + G + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.812e+00
Information Content per bp:1.646
Number of Target Sequences with motif184.0
Percentage of Target Sequences with motif4.60%
Number of Background Sequences with motif125.5
Percentage of Background Sequences with motif3.15%
Average Position of motif in Targets253.6 +/- 133.7bp
Average Position of motif in Background249.9 +/- 144.5bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..b19bbb2ee324bba98bc1b4f2d25d9e8d62ce59e7 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.logo.svg @@ -0,0 +1,54 @@ + + + A + G + C + T + + T + A + C + G + + C + A + T + G + + A + G + C + T + + C + A + T + G + + T + C + G + A + + C + T + A + G + + A + T + C + G + + A + C + G + T + + C + T + A + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..202db89634de4bba36fec620227a5167311a6e8a --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif6RV.motif @@ -0,0 +1,11 @@ +>TGGTGAGGTG 3-CACCTCACCA 7.271332 -7.811697 0 T:184.0(4.60%),B:125.5(3.15%),P:1e-3 +0.060 0.084 0.076 0.780 +0.068 0.088 0.788 0.056 +0.098 0.065 0.739 0.098 +0.031 0.092 0.069 0.808 +0.040 0.039 0.832 0.089 +0.843 0.058 0.069 0.030 +0.076 0.058 0.794 0.072 +0.059 0.060 0.822 0.059 +0.037 0.056 0.065 0.842 +0.084 0.075 0.764 0.077 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.info.html new file mode 100644 index 0000000000000000000000000000000000000000..69b28475b64f4aedebda6a0df644dcf914b60f35 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.info.html @@ -0,0 +1,1683 @@ +Motif 7 +

Information for 4-GGTGTTATTCAG (Motif 7)

+ + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+Reverse Opposite:
+ + A + G + T + C + + C + A + G + T + + T + C + A + G + + G + T + C + A + + G + C + T + A + + C + A + G + T + + C + T + G + A + + C + T + G + A + + T + A + G + C + + C + G + T + A + + A + G + T + C + + A + T + G + C + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.616e+00
Information Content per bp:1.591
Number of Target Sequences with motif14.0
Percentage of Target Sequences with motif0.35%
Number of Background Sequences with motif2.0
Percentage of Background Sequences with motif0.05%
Average Position of motif in Targets202.4 +/- 114.6bp
Average Position of motif in Background229.6 +/- 144.8bp
Strand Bias (log2 ratio + to - strand density)-2.6
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

STB5/STB5_YPD/[](Harbison)/Yeast

+
+ + + +
Match Rank:1
Score:0.70 +
Offset:-1 +
Orientation:forward strand
Alignment:-GGTGTTATTCAG
CGGTGTTATA---
+		 + + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + G + A + T + C + + T + A + C + G + + C + T + A + G + + C + G + A + T + + T + A + C + G + + G + C + A + T + + A + C + G + T + + C + G + T + A + + G + C + A + T + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

STB5(MacIsaac)/Yeast

+
+ + + +
Match Rank:2
Score:0.70 +
Offset:-1 +
Orientation:forward strand
Alignment:-GGTGTTATTCAG
CGGTGTTATA---
+		 + + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + G + T + C + + A + C + T + G + + A + T + C + G + + C + A + G + T + + A + T + C + G + + G + A + C + T + + C + G + A + T + + C + G + T + A + + G + C + A + T + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

ara/dmmpmm(Noyes_hd)/fly

+
+ + + +
Match Rank:3
Score:0.69 +
Offset:0 +
Orientation:reverse strand
Alignment:GGTGTTATTCAG
NNTGTTATTN--
+		 + + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + C + G + A + T + + G + C + T + A + + C + G + A + T + + A + C + G + T + + G + A + C + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

PH0164.1_Six4/Jaspar

+
+ + + +
Match Rank:4
Score:0.66 +
Offset:-5 +
Orientation:reverse strand
Alignment:-----GGTGTTATTCAG
TNNNNGGTGTCATNTNT
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + G + C + T + + T + C + A + G + + T + C + G + A + + C + A + G + T + + C + T + G + A + + T + C + A + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + A + C + G + T + + G + T + A + C + + C + T + G + A + + C + G + A + T + + C + A + G + T + + G + A + C + T + + G + T + C + A + + C + A + G + T + + + + +
+
+

vvl/dmmpmm(Bigfoot)/fly

+
+ + + +
Match Rank:5
Score:0.65 +
Offset:5 +
Orientation:forward strand
Alignment:GGTGTTATTCAG
-----TATTCA-
+		 + + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + C + A + + C + G + A + T + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + C + G + T + + + + +
+
+

Caup/dmmpmm(Noyes_hd)/fly

+
+ + + +
Match Rank:6
Score:0.65 +
Offset:0 +
Orientation:reverse strand
Alignment:GGTGTTATTCAG
NNTGTTATTG--
+		 + + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + G + C + A + T + + G + C + T + A + + G + C + A + T + + G + C + A + T + + C + A + T + G + + A + C + G + T + + A + C + G + T + + + + +
+
+

TBX5/MA0807.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.64 +
Offset:-1 +
Orientation:forward strand
Alignment:-GGTGTTATTCAG
AGGTGTGA-----
+		 + + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + C + T + G + A + + T + C + A + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + A + G + C + T + + A + C + T + G + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Mirr/dmmpmm(Noyes_hd)/fly

+
+ + + +
Match Rank:8
Score:0.64 +
Offset:0 +
Orientation:reverse strand
Alignment:GGTGTTATTCAG
NNTGTTTTTT--
+		 + + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + G + C + A + T + + C + G + A + T + + A + C + G + T + + G + A + C + T + + C + G + A + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Eomes(T-box)/H9-Eomes-ChIP-Seq(GSE26097)/Homer

+
+ + + +
Match Rank:9
Score:0.64 +
Offset:-1 +
Orientation:reverse strand
Alignment:-GGTGTTATTCAG
AGGTGTTAAT---
+		 + + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + C + T + G + A + + C + T + A + G + + A + T + C + G + + C + G + A + T + + C + T + A + G + + G + C + A + T + + A + C + G + T + + C + T + G + A + + C + T + G + A + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

TBX4/MA0806.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.64 +
Offset:-1 +
Orientation:forward strand
Alignment:-GGTGTTATTCAG
AGGTGTGA-----
+		 + + + A + C + G + T + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + + +
+ + + C + T + G + A + + T + C + A + G + + T + A + C + G + + A + G + C + T + + A + C + T + G + + G + A + C + T + + A + C + T + G + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..af7802186954982597ededc422e65ac7eb84418f --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.logo.svg @@ -0,0 +1,64 @@ + + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.motif new file mode 100644 index 0000000000000000000000000000000000000000..2dc6852f4b2d1cd007cf45e05eee4000f99a225d --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.motif @@ -0,0 +1,13 @@ +>GGTGTTATTCAG 4-GGTGTTATTCAG,BestGuess:STB5/STB5_YPD/[](Harbison)/Yeast(0.700) 9.665970 -7.616403 0 T:14.0(0.35%),B:2.0(0.05%),P:1e-3 +0.055 0.117 0.791 0.037 +0.126 0.091 0.692 0.091 +0.100 0.073 0.055 0.772 +0.047 0.099 0.781 0.073 +0.091 0.117 0.082 0.710 +0.046 0.117 0.046 0.791 +0.745 0.135 0.029 0.091 +0.126 0.011 0.126 0.737 +0.082 0.047 0.126 0.745 +0.056 0.701 0.117 0.126 +0.737 0.126 0.064 0.073 +0.082 0.073 0.781 0.064 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..7e3ed552a642032ae00b4fe3753a54a203fd406c --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7.similar.html @@ -0,0 +1,152 @@ +motif7 +

Information for motif7

+ + + T + A + C + G + + C + T + A + G + + G + C + A + T + + A + T + C + G + + G + A + C + T + + A + G + C + T + + G + T + C + A + + C + A + G + T + + C + A + G + T + + A + G + T + C + + G + T + C + A + + T + C + A + G + + + +
+Reverse Opposite:
+ + A + G + T + C + + C + A + G + T + + T + C + A + G + + G + T + C + A + + G + C + T + A + + C + A + G + T + + C + T + G + A + + C + T + G + A + + T + A + G + C + + C + G + T + A + + A + G + T + C + + A + T + G + C + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.616e+00
Information Content per bp:1.591
Number of Target Sequences with motif14.0
Percentage of Target Sequences with motif0.35%
Number of Background Sequences with motif2.0
Percentage of Background Sequences with motif0.05%
Average Position of motif in Targets202.4 +/- 114.6bp
Average Position of motif in Background229.6 +/- 144.8bp
Strand Bias (log2 ratio + to - strand density)-2.6
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..282b353b881c240e0775d943ecf1242a8845525b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.logo.svg @@ -0,0 +1,64 @@ + + + A + G + T + C + + C + A + G + T + + T + C + A + G + + G + T + C + A + + G + C + T + A + + C + A + G + T + + C + T + G + A + + C + T + G + A + + T + A + G + C + + C + G + T + A + + A + G + T + C + + A + T + G + C + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..ca574df52ebc0d2fcec47546e4ba9706733f00e9 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif7RV.motif @@ -0,0 +1,13 @@ +>CTGAATAACACC 4-GGTGTTATTCAG 9.665970 -7.616403 0 T:14.0(0.35%),B:2.0(0.05%),P:1e-3 +0.064 0.781 0.073 0.082 +0.073 0.064 0.126 0.737 +0.126 0.117 0.701 0.056 +0.745 0.126 0.047 0.082 +0.737 0.126 0.011 0.126 +0.091 0.029 0.135 0.745 +0.791 0.046 0.117 0.046 +0.710 0.082 0.117 0.091 +0.073 0.781 0.099 0.047 +0.772 0.055 0.073 0.100 +0.091 0.692 0.091 0.126 +0.037 0.791 0.117 0.055 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.info.html new file mode 100644 index 0000000000000000000000000000000000000000..ebe0db69c5e5a560cf4f145c71b7a17a8f1bbd86 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.info.html @@ -0,0 +1,1283 @@ +Motif 8 +

Information for 4-ACWTGGAG (Motif 8)

+ + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + + + +
+Reverse Opposite:
+ + G + A + T + C + + G + A + C + T + + G + A + T + C + + T + G + A + C + + C + T + G + A + + C + G + T + A + + T + A + C + G + + A + C + G + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.183e+00
Information Content per bp:1.708
Number of Target Sequences with motif1323.0
Percentage of Target Sequences with motif33.08%
Number of Background Sequences with motif1187.5
Percentage of Background Sequences with motif29.77%
Average Position of motif in Targets250.4 +/- 140.7bp
Average Position of motif in Background249.5 +/- 146.5bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.22
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

Pp_0237(RRM)/Physcomitrella_patens-RNCMPT00237-PBM/HughesRNA

+
+ + + +
Match Rank:1
Score:0.77 +
Offset:1 +
Orientation:forward strand
Alignment:ACWTGGAG-
-GATGGAGT
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + T + G + + C + G + T + A + + A + C + G + T + + A + C + T + G + + A + C + T + G + + C + G + T + A + + C + T + A + G + + A + C + G + T + + + + +
+
+

ADR1/MA0268.1/Jaspar

+
+ + + +
Match Rank:2
Score:0.70 +
Offset:2 +
Orientation:reverse strand
Alignment:ACWTGGAG-
--GTGGGGT
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + C + A + T + G + + G + A + C + T + + A + C + T + G + + A + C + T + G + + C + T + A + G + + A + C + T + G + + C + A + G + T + + + + +
+
+

ADR1/MA0268.1/Jaspar

+
+ + + +
Match Rank:3
Score:0.70 +
Offset:2 +
Orientation:reverse strand
Alignment:ACWTGGAG-
--GTGGGGT
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + C + A + T + G + + G + A + C + T + + A + C + T + G + + A + C + T + G + + C + T + A + G + + A + C + T + G + + C + A + G + T + + + + +
+
+

ADR1/Literature(Harbison)/Yeast

+
+ + + +
Match Rank:4
Score:0.69 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG-
---NGGAGG
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + T + G + + C + T + A + G + + A + C + T + G + + A + C + G + T + + + + +
+
+

ADR1(MacIsaac)/Yeast

+
+ + + +
Match Rank:5
Score:0.69 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG-
---NGGAGG
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + T + G + + C + T + A + G + + A + C + T + G + + A + C + G + T + + + + +
+
+

SRSF2(RRM)/Homo_sapiens-RNCMPT00072-PBM/HughesRNA

+
+ + + +
Match Rank:6
Score:0.63 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG---
---AGGAGANG
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + T + A + + A + C + T + G + + A + C + T + G + + C + G + T + A + + A + C + T + G + + C + G + T + A + + C + T + A + G + + C + T + A + G + + + + +
+
+

LIN28A(CSD,Znf)/Homo_sapiens-RNCMPT00036-PBM/HughesRNA

+
+ + + +
Match Rank:7
Score:0.63 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG--
---NGGAGAA
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + A + C + + A + C + T + G + + A + C + T + G + + C + G + T + A + + A + C + T + G + + C + G + T + A + + C + T + G + A + + + + +
+
+

ESRP2(RRM)/Homo_sapiens-RNCMPT00150-PBM/HughesRNA

+
+ + + +
Match Rank:8
Score:0.62 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG--
---TGGGGAT
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + T + G + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + G + A + T + + + + +
+
+

XBP1/Literature(Harbison)/Yeast

+
+ + + +
Match Rank:9
Score:0.61 +
Offset:1 +
Orientation:forward strand
Alignment:ACWTGGAG
-CTTCGAG
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + + + +
+ + + A + C + G + T + + A + G + T + C + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + C + T + G + + C + G + T + A + + A + C + T + G + + + + +
+
+

z/dmmpmm(SeSiMCMC)/fly

+
+ + + +
Match Rank:10
Score:0.60 +
Offset:3 +
Orientation:forward strand
Alignment:ACWTGGAG--
---TTGAGTG
+		 + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + A + T + + A + G + C + T + + A + C + T + G + + C + G + T + A + + A + C + T + G + + G + A + C + T + + A + C + T + G + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..c871e4a8e60255837cfc94aa658788da934ec537 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.logo.svg @@ -0,0 +1,44 @@ + + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.motif new file mode 100644 index 0000000000000000000000000000000000000000..cf68674e9597cd23a5b9d9fb4952555798a88bfe --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.motif @@ -0,0 +1,9 @@ +>ACWTGGAG 4-ACWTGGAG,BestGuess:Pp_0237(RRM)/Physcomitrella_patens-RNCMPT00237-PBM/HughesRNA(0.767) 6.413528 -7.183465 0 T:1323.0(33.08%),B:1187.5(29.77%),P:1e-3 +0.986 0.008 0.005 0.001 +0.159 0.424 0.253 0.164 +0.435 0.001 0.001 0.563 +0.085 0.129 0.003 0.783 +0.001 0.006 0.754 0.239 +0.058 0.001 0.934 0.007 +0.661 0.001 0.334 0.004 +0.111 0.001 0.885 0.003 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..d76b7a973c8b366bb56888f29182711b6cc3e04b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8.similar.html @@ -0,0 +1,112 @@ +motif8 +

Information for motif8

+ + + T + G + C + A + + A + T + G + C + + C + G + A + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + C + T + G + A + + C + T + A + G + + + +
+Reverse Opposite:
+ + G + A + T + C + + G + A + C + T + + G + A + T + C + + T + G + A + C + + C + T + G + A + + C + G + T + A + + T + A + C + G + + A + C + G + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.183e+00
Information Content per bp:1.708
Number of Target Sequences with motif1323.0
Percentage of Target Sequences with motif33.08%
Number of Background Sequences with motif1187.5
Percentage of Background Sequences with motif29.77%
Average Position of motif in Targets250.4 +/- 140.7bp
Average Position of motif in Background249.5 +/- 146.5bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.22
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..887757d6e1e480f1f3a96655bbf8ab0134e2d08f --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.logo.svg @@ -0,0 +1,44 @@ + + + G + A + T + C + + G + A + C + T + + G + A + T + C + + T + G + A + C + + C + T + G + A + + C + G + T + A + + T + A + C + G + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..c6186a18f9931293d813aa0027efc4fc6ee5a80c --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif8RV.motif @@ -0,0 +1,9 @@ +>CTCCAWGT 4-ACWTGGAG 6.413528 -7.183465 0 T:1323.0(33.08%),B:1187.5(29.77%),P:1e-3 +0.003 0.885 0.001 0.111 +0.004 0.334 0.001 0.661 +0.007 0.934 0.001 0.058 +0.239 0.754 0.006 0.001 +0.783 0.003 0.129 0.085 +0.563 0.001 0.001 0.435 +0.164 0.253 0.424 0.159 +0.001 0.005 0.008 0.986 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.info.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.info.html new file mode 100644 index 0000000000000000000000000000000000000000..448e34688ba1ee2b4ea888d0ff6673385f0e3211 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.info.html @@ -0,0 +1,1423 @@ +Motif 9 +

Information for 4-CTATCTTTCT (Motif 9)

+ + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+Reverse Opposite:
+ + T + C + G + A + + C + A + T + G + + G + T + C + A + + C + T + G + A + + T + C + G + A + + T + A + C + G + + G + T + C + A + + C + G + A + T + + G + T + C + A + + C + T + A + G + + + +
+ + + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.109e+00
Information Content per bp:1.816
Number of Target Sequences with motif85.0
Percentage of Target Sequences with motif2.13%
Number of Background Sequences with motif48.6
Percentage of Background Sequences with motif1.22%
Average Position of motif in Targets259.9 +/- 128.6bp
Average Position of motif in Background261.7 +/- 149.8bp
Strand Bias (log2 ratio + to - strand density)0.4
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

HNRNPAB(RRM)/Tetraodon_nigroviridis-RNCMPT00245-PBM/HughesRNA

+
+ + + +
Match Rank:1
Score:0.74 +
Offset:0 +
Orientation:reverse strand
Alignment:CTATCTTTCT
CTATCTA---
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + G + T + C + + C + G + A + T + + C + G + T + A + + G + C + A + T + + G + T + A + C + + A + G + C + T + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Tb_0220(RRM)/Trypanosoma_brucei-RNCMPT00220-PBM/HughesRNA

+
+ + + +
Match Rank:2
Score:0.73 +
Offset:4 +
Orientation:forward strand
Alignment:CTATCTTTCT-
----CTTTCTN
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + C + T + + A + C + G + T + + A + G + C + T + + A + G + T + C + + A + G + C + T + + G + A + C + T + + + + +
+
+

Tb_0253(RRM)/Trypanosoma_brucei-RNCMPT00253-PBM/HughesRNA

+
+ + + +
Match Rank:3
Score:0.73 +
Offset:3 +
Orientation:reverse strand
Alignment:CTATCTTTCT
---TTTTTCT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + C + T + + A + G + C + T + + A + C + G + T + + A + G + C + T + + A + C + G + T + + A + G + T + C + + A + C + G + T + + + + +
+
+

br-Z4/dmmpmm(Bergman)/fly

+
+ + + +
Match Rank:4
Score:0.71 +
Offset:3 +
Orientation:reverse strand
Alignment:CTATCTTTCT
---TCTTTAC
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + T + C + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+
+

PTBP1(RRM)/Homo_sapiens-RNCMPT00269-PBM/HughesRNA

+
+ + + +
Match Rank:5
Score:0.69 +
Offset:3 +
Orientation:forward strand
Alignment:CTATCTTTCT
---ACTTTCT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + T + C + A + + A + G + T + C + + A + C + G + T + + C + G + A + T + + C + G + A + T + + A + G + T + C + + A + G + C + T + + + + +
+
+

SART3(RRM)/Homo_sapiens-RNCMPT00064-PBM/HughesRNA

+
+ + + +
Match Rank:6
Score:0.66 +
Offset:3 +
Orientation:reverse strand
Alignment:CTATCTTTCT
---TTTTTCT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + C + G + T + + + + +
+
+

PABPC1(RRM)/Homo_sapiens-RNCMPT00155-PBM/HughesRNA

+
+ + + +
Match Rank:7
Score:0.66 +
Offset:3 +
Orientation:reverse strand
Alignment:CTATCTTTCT
---TTTTTCT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + A + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + C + G + T + + + + +
+
+

Dref/dmmpmm(SeSiMCMC)/fly

+
+ + + +
Match Rank:8
Score:0.65 +
Offset:0 +
Orientation:reverse strand
Alignment:CTATCTTTCT
CTATCGATAT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + G + T + C + + A + C + T + G + + C + G + T + A + + C + A + G + T + + G + C + T + A + + C + G + A + T + + + + +
+
+

Dref/dmmpmm(Bigfoot)/fly

+
+ + + +
Match Rank:9
Score:0.65 +
Offset:0 +
Orientation:reverse strand
Alignment:CTATCTTTCT
CTATCGATAT
+		 + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + + +
+ + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + G + T + C + + A + C + T + G + + C + G + T + A + + C + A + G + T + + G + C + T + A + + C + G + A + T + + + + +
+
+

MEF2C/MA0497.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.64 +
Offset:-2 +
Orientation:reverse strand
Alignment:--CTATCTTTCT---
TTCTATTTTTAGNNN
+		 + + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + A + T + + C + A + G + T + + A + G + T + C + + A + G + C + T + + C + T + G + A + + G + C + A + T + + G + C + A + T + + G + A + C + T + + G + A + C + T + + C + G + A + T + + C + T + G + A + + C + A + T + G + + G + T + A + C + + G + C + T + A + + G + A + C + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..f9187cef113655cff042ad96187050942adfc6d2 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.logo.svg @@ -0,0 +1,54 @@ + + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.motif new file mode 100644 index 0000000000000000000000000000000000000000..df2e6584d6c3e244e545c9db41dd37868ecb8971 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.motif @@ -0,0 +1,11 @@ +>CTATCTTTCT 4-CTATCTTTCT,BestGuess:HNRNPAB(RRM)/Tetraodon_nigroviridis-RNCMPT00245-PBM/HughesRNA(0.735) 9.437671 -7.108680 0 T:85.0(2.13%),B:48.6(1.22%),P:1e-3 +0.001 0.930 0.001 0.068 +0.001 0.001 0.074 0.924 +0.964 0.001 0.001 0.034 +0.001 0.001 0.034 0.964 +0.035 0.801 0.085 0.079 +0.001 0.089 0.075 0.835 +0.001 0.058 0.001 0.940 +0.001 0.001 0.084 0.914 +0.098 0.832 0.001 0.069 +0.001 0.059 0.051 0.889 diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.similar.html b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..6755646aa1cee0714500aff34a472836c34ade23 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9.similar.html @@ -0,0 +1,132 @@ +motif9 +

Information for motif9

+ + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + T + G + C + + A + G + C + T + + A + G + C + T + + A + C + G + T + + G + T + A + C + + A + G + C + T + + + +
+Reverse Opposite:
+ + T + C + G + A + + C + A + T + G + + G + T + C + A + + C + T + G + A + + T + C + G + A + + T + A + C + G + + G + T + C + A + + C + G + A + T + + G + T + C + A + + C + T + A + G + + + +
+ + + + + + + + + + + + + +
p-value:1e-3
log p-value:-7.109e+00
Information Content per bp:1.816
Number of Target Sequences with motif85.0
Percentage of Target Sequences with motif2.13%
Number of Background Sequences with motif48.6
Percentage of Background Sequences with motif1.22%
Average Position of motif in Targets259.9 +/- 128.6bp
Average Position of motif in Background261.7 +/- 149.8bp
Strand Bias (log2 ratio + to - strand density)0.4
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.logo.svg b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..3429c79051343b9437166e3b00d2af88c58c2a90 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.logo.svg @@ -0,0 +1,54 @@ + + + T + C + G + A + + C + A + T + G + + G + T + C + A + + C + T + G + A + + T + C + G + A + + T + A + C + G + + G + T + C + A + + C + G + A + T + + G + T + C + A + + C + T + A + G + + + diff --git a/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.motif b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..787b085fd2028f451391ddc6e4b0f6a8eaefca7a --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/homerResults/motif9RV.motif @@ -0,0 +1,11 @@ +>AGAAAGATAG 4-CTATCTTTCT 9.437671 -7.108680 0 T:85.0(2.13%),B:48.6(1.22%),P:1e-3 +0.889 0.051 0.059 0.001 +0.069 0.001 0.832 0.098 +0.914 0.084 0.001 0.001 +0.940 0.001 0.058 0.001 +0.835 0.075 0.089 0.001 +0.079 0.085 0.801 0.035 +0.964 0.034 0.001 0.001 +0.034 0.001 0.001 0.964 +0.924 0.074 0.001 0.001 +0.068 0.001 0.930 0.001 diff --git a/the_code/Human/data/homer/M0_vs_M15/knownResults.html b/the_code/Human/data/homer/M0_vs_M15/knownResults.html new file mode 100644 index 0000000000000000000000000000000000000000..b22ed087bc21f4fa9c19cee8bb2a86e3ac4c956b --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/knownResults.html @@ -0,0 +1,1211 @@ +./ - Homer Known Motif Enrichment Results + +

Homer Known Motif Enrichment Results (./)

+Homer de novo Motif Results
+Gene Ontology Enrichment Results
+Known Motif Enrichment Results (txt file)
+Total Target Sequences = 3999, Total Background Sequences = 3988
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
RankMotifNameP-valuelog P-pvalueq-value (Benjamini)# Target Sequences with Motif% of Targets Sequences with Motif# Background Sequences with Motif% of Background Sequences with MotifMotif FileSVG
1 + + + T + G + C + A + + G + T + A + C + + C + G + T + A + + A + T + C + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + C + G + A + T + + T + C + G + A + + A + G + T + C + + + + +ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer1e-15-3.578e+010.00001105.027.63%794.119.91%motif file (matrix)svg
2 + + + G + A + C + T + + A + C + G + T + + C + G + A + T + + A + G + C + T + + A + G + T + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + C + G + A + T + + C + T + A + G + + + + +NGA4(ABI3VP1)/col-NGA4-DAP-Seq(GSE60143)/Homer1e-14-3.415e+010.00001624.040.61%1280.532.10%motif file (matrix)svg
3 + + + A + T + G + C + + T + G + C + A + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + A + T + G + C + + G + T + C + A + + + + +E2A(bHLH),near_PU.1/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer1e-11-2.716e+010.0000729.018.23%502.112.59%motif file (matrix)svg
4 + + + C + T + A + G + + A + C + T + G + + T + G + C + A + + A + G + T + C + + C + G + T + A + + A + C + T + G + + A + C + T + G + + A + C + G + T + + C + T + A + G + + C + G + A + T + + T + A + C + G + + A + G + T + C + + + + +ZEB2(Zf)/SNU398-ZEB2-ChIP-Seq(GSE103048)/Homer1e-9-2.124e+010.0000514.012.85%344.18.63%motif file (matrix)svg
5 + + + A + C + T + G + + A + T + C + G + + A + G + T + C + + A + C + G + T + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + C + G + T + A + + + + +Zelda(Zf)/Embryo-zld-ChIP-Seq(GSE65441)/Homer1e-5-1.327e+010.0003382.09.55%267.16.70%motif file (matrix)svg
6 + + + T + A + C + G + + C + T + A + G + + T + A + C + G + + A + G + T + C + + C + G + T + A + + A + G + T + C + + A + G + T + C + + A + C + G + T + + A + C + T + G + + A + G + T + C + + G + A + T + C + + T + A + G + C + + + + +Slug(Zf)/Mesoderm-Snai2-ChIP-Seq(GSE61475)/Homer1e-5-1.303e+010.0004252.06.30%160.44.02%motif file (matrix)svg
7 + + + C + G + T + A + + T + G + A + C + + T + C + G + A + + A + G + T + C + + C + G + T + A + + A + T + C + G + + A + T + G + C + + A + C + G + T + + A + C + T + G + + A + G + T + C + + + + +E2A(bHLH)/proBcell-E2A-ChIP-Seq(GSE21978)/Homer1e-4-1.104e+010.0023600.015.00%471.811.83%motif file (matrix)svg
8 + + + C + T + G + A + + C + T + A + G + + A + T + C + G + + A + G + C + T + + A + C + T + G + + G + A + C + T + + A + G + T + C + + C + T + G + A + + + + +Tbx5(T-box)/HL1-Tbx5.biotin-ChIP-Seq(GSE21529)/Homer1e-4-1.043e+010.00372123.053.09%1937.248.56%motif file (matrix)svg
9 + + + T + C + G + A + + A + G + T + C + + C + G + T + A + + A + T + C + G + + T + A + G + C + + A + C + G + T + + A + C + T + G + + A + G + C + T + + A + C + G + T + + A + G + T + C + + + + +Ptf1a(bHLH)/Panc1-Ptf1a-ChIP-Seq(GSE47459)/Homer1e-4-9.398e+000.00921317.032.93%1157.229.01%motif file (matrix)svg
10 + + + T + G + A + C + + A + T + G + C + + C + G + T + A + + A + T + C + G + + A + T + G + C + + C + A + G + T + + C + A + T + G + + A + C + T + G + + A + G + T + C + + G + T + A + C + + + + +HEB(bHLH)/mES-Heb-ChIP-Seq(GSE53233)/Homer1e-3-8.081e+000.0307887.022.18%761.019.08%motif file (matrix)svg
11 + + + T + A + C + G + + T + A + C + G + + C + T + A + G + + T + C + A + G + + A + G + T + C + + C + G + T + A + + A + T + C + G + + A + T + G + C + + A + C + G + T + + A + C + T + G + + A + G + T + C + + G + A + C + T + + + + +Ascl2(bHLH)/ESC-Ascl2-ChIP-Seq(GSE97712)/Homer1e-3-7.928e+000.0326491.012.28%395.09.90%motif file (matrix)svg
12 + + + C + T + A + G + + C + T + G + A + + T + C + A + G + + A + T + C + G + + A + G + C + T + + C + A + T + G + + G + A + C + T + + A + G + T + C + + C + T + G + A + + T + G + C + A + + + + +Tbx6(T-box)/ESC-Tbx6-ChIP-Seq(GSE93524)/Homer1e-3-7.867e+000.0326888.022.21%763.619.14%motif file (matrix)svg
13 + + + C + T + A + G + + A + G + T + C + + T + A + C + G + + T + A + C + G + + T + G + A + C + + C + G + T + A + + A + C + T + G + + T + A + G + C + + G + C + A + T + + C + A + T + G + + A + T + G + C + + A + G + C + T + + + + +Ascl1(bHLH)/NeuralTubes-Ascl1-ChIP-Seq(GSE55840)/Homer1e-2-6.745e+000.0900669.016.73%568.714.26%motif file (matrix)svg
14 + + + G + C + T + A + + G + A + C + T + + G + A + C + T + + T + G + C + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + T + A + G + C + + G + A + T + C + + G + A + C + T + + + + +Eomes(T-box)/H9-Eomes-ChIP-Seq(GSE26097)/Homer1e-2-6.317e+000.12821676.041.91%1543.938.70%motif file (matrix)svg
15 + + + C + G + T + A + + C + T + A + G + + C + A + T + G + + A + G + C + T + + A + C + T + G + + C + G + A + T + + A + T + C + G + + C + G + T + A + + G + T + C + A + + G + T + C + A + + + + +Tbet(T-box)/CD8-Tbet-ChIP-Seq(GSE33802)/Homer1e-2-5.407e+000.2973856.021.41%759.819.05%motif file (matrix)svg
16 + + + A + C + T + G + + A + G + T + C + + G + T + C + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + T + A + G + + C + T + A + G + + G + A + C + T + + C + A + T + G + + + + +SCRT1(Zf)/HEK293-SCRT1.eGFP-ChIP-Seq(Encode)/Homer1e-2-5.146e+000.3618256.06.40%202.75.08%motif file (matrix)svg
17 + + + G + A + T + C + + C + T + A + G + + G + T + C + A + + T + C + G + A + + A + C + G + T + + G + C + A + T + + C + G + T + A + + G + C + A + T + + + + +AtHB32(ZFHD)/col200-AtHB32-DAP-Seq(GSE60143)/Homer1e-2-4.949e+000.41442024.050.61%1908.347.84%motif file (matrix)svg
18 + + + C + G + T + A + + C + T + A + G + + C + A + G + T + + A + C + G + T + + C + G + T + A + + A + C + T + G + + C + A + T + G + + G + C + A + T + + T + C + A + G + + C + T + G + A + + + + +MYB49(MYB)/col-MYB49-DAP-Seq(GSE60143)/Homer1e-2-4.796e+000.45621093.027.33%995.224.95%motif file (matrix)svg
19 + + + T + C + G + A + + T + C + G + A + + A + G + T + C + + C + G + T + A + + C + T + A + G + + T + A + G + C + + A + C + G + T + + A + C + T + G + + + + +MyoG(bHLH)/C2C12-MyoG-ChIP-Seq(GSE36024)/Homer1e-2-4.789e+000.4562415.010.38%350.58.79%motif file (matrix)svg
20 + + + C + G + T + A + + C + G + T + A + + G + C + T + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + C + T + + G + C + A + T + + G + C + A + T + + + + +AT2G40260(G2like)/colamp-AT2G40260-DAP-Seq(GSE60143)/Homer1e-2-4.610e+000.49441445.036.13%1341.633.63%motif file (matrix)svg
diff --git a/the_code/Human/data/homer/M0_vs_M15/knownResults.txt b/the_code/Human/data/homer/M0_vs_M15/knownResults.txt new file mode 100644 index 0000000000000000000000000000000000000000..59b56caf0146aec2a252b9555c6fd1f84392c073 --- /dev/null +++ b/the_code/Human/data/homer/M0_vs_M15/knownResults.txt @@ -0,0 +1,995 @@ +Motif Name Consensus P-value Log P-value q-value (Benjamini) # of Target Sequences with Motif(of 3999) % of Target Sequences with Motif # of Background Sequences with Motif(of 3988) % of Background Sequences with Motif +ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer VCAGGTRDRY 1e-15 -3.578e+01 0.0000 1105.0 27.63% 794.1 19.91% +NGA4(ABI3VP1)/col-NGA4-DAP-Seq(GSE60143)/Homer TKNTCAGGTG 1e-14 -3.415e+01 0.0000 1624.0 40.61% 1280.5 32.10% +E2A(bHLH),near_PU.1/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer NVCACCTGBN 1e-11 -2.716e+01 0.0000 729.0 18.23% 502.1 12.59% +ZEB2(Zf)/SNU398-ZEB2-ChIP-Seq(GSE103048)/Homer GNMCAGGTGTGC 1e-9 -2.124e+01 0.0000 514.0 12.85% 344.1 8.63% +Zelda(Zf)/Embryo-zld-ChIP-Seq(GSE65441)/Homer KBCTACCTGW 1e-5 -1.327e+01 0.0003 382.0 9.55% 267.1 6.70% +Slug(Zf)/Mesoderm-Snai2-ChIP-Seq(GSE61475)/Homer SNGCACCTGCHS 1e-5 -1.303e+01 0.0004 252.0 6.30% 160.4 4.02% +E2A(bHLH)/proBcell-E2A-ChIP-Seq(GSE21978)/Homer DNRCAGCTGY 1e-4 -1.104e+01 0.0023 600.0 15.00% 471.8 11.83% +Tbx5(T-box)/HL1-Tbx5.biotin-ChIP-Seq(GSE21529)/Homer AGGTGTCA 1e-4 -1.043e+01 0.0037 2123.0 53.09% 1937.2 48.56% +Ptf1a(bHLH)/Panc1-Ptf1a-ChIP-Seq(GSE47459)/Homer ACAGCTGTTN 1e-4 -9.398e+00 0.0092 1317.0 32.93% 1157.2 29.01% +HEB(bHLH)/mES-Heb-ChIP-Seq(GSE53233)/Homer VCAGCTGBNN 1e-3 -8.081e+00 0.0307 887.0 22.18% 761.0 19.08% +Ascl2(bHLH)/ESC-Ascl2-ChIP-Seq(GSE97712)/Homer SSRGCAGCTGCH 1e-3 -7.928e+00 0.0326 491.0 12.28% 395.0 9.90% +Tbx6(T-box)/ESC-Tbx6-ChIP-Seq(GSE93524)/Homer DAGGTGTBAA 1e-3 -7.867e+00 0.0326 888.0 22.21% 763.6 19.14% +Ascl1(bHLH)/NeuralTubes-Ascl1-ChIP-Seq(GSE55840)/Homer NNVVCAGCTGBN 1e-2 -6.745e+00 0.0900 669.0 16.73% 568.7 14.26% +Eomes(T-box)/H9-Eomes-ChIP-Seq(GSE26097)/Homer ATTAACACCT 1e-2 -6.317e+00 0.1282 1676.0 41.91% 1543.9 38.70% +Tbet(T-box)/CD8-Tbet-ChIP-Seq(GSE33802)/Homer AGGTGTGAAM 1e-2 -5.407e+00 0.2973 856.0 21.41% 759.8 19.05% +SCRT1(Zf)/HEK293-SCRT1.eGFP-ChIP-Seq(Encode)/Homer GCAACAGGTG 1e-2 -5.146e+00 0.3618 256.0 6.40% 202.7 5.08% +AtHB32(ZFHD)/col200-AtHB32-DAP-Seq(GSE60143)/Homer CGAATTAT 1e-2 -4.949e+00 0.4144 2024.0 50.61% 1908.3 47.84% +MYB49(MYB)/col-MYB49-DAP-Seq(GSE60143)/Homer ARKTAGGTRR 1e-2 -4.796e+00 0.4562 1093.0 27.33% 995.2 24.95% +MyoG(bHLH)/C2C12-MyoG-ChIP-Seq(GSE36024)/Homer AACAGCTG 1e-2 -4.789e+00 0.4562 415.0 10.38% 350.5 8.79% +AT2G40260(G2like)/colamp-AT2G40260-DAP-Seq(GSE60143)/Homer WAAAYATTCTTT 1e-2 -4.610e+00 0.4944 1445.0 36.13% 1341.6 33.63% +MYB4(MYB)/col200-MYB4-DAP-Seq(GSE60143)/Homer WAGKTAGGTARR 1e-1 -4.412e+00 0.5743 626.0 15.65% 552.2 13.84% +Tbx21(T-box)/GM12878-TBX21-ChIP-Seq(Encode)/Homer AGGTGTGAAA 1e-1 -4.395e+00 0.5743 734.0 18.35% 655.2 16.43% +AT5G63260(C3H)/col-AT5G63260-DAP-Seq(GSE60143)/Homer RAAAAAGTRA 1e-1 -4.371e+00 0.5743 1801.0 45.04% 1696.5 42.53% +Hoxd13(Homeobox)/ChickenMSG-Hoxd13.Flag-ChIP-Seq(GSE86088)/Homer NCYAATAAAA 1e-1 -3.832e+00 0.8974 1577.0 39.43% 1484.7 37.22% +ATY19(MYB)/col-ATY19-DAP-Seq(GSE60143)/Homer YYCACCWACCAT 1e-1 -3.809e+00 0.8974 659.0 16.48% 591.1 14.82% +bZIP18(bZIP)/colamp-bZIP18-DAP-Seq(GSE60143)/Homer KGMCAGCTND 1e-1 -3.756e+00 0.8974 3088.0 77.22% 3003.4 75.29% +ATHB40(HB)/col-ATHB40-DAP-Seq(GSE60143)/Homer HCAATWATTG 1e-1 -3.680e+00 0.9290 922.0 23.06% 846.9 21.23% +HOXD13(Homeobox)/Chicken-Hoxd13-ChIP-Seq(GSE38910)/Homer NCYAATAAAA 1e-1 -3.648e+00 0.9290 906.0 22.66% 831.5 20.84% +HOXB13(Homeobox)/ProstateTumor-HOXB13-ChIP-Seq(GSE56288)/Homer TTTTATKRGG 1e-1 -3.647e+00 0.9290 1202.0 30.06% 1119.0 28.05% +MYB67(MYB)/col-MYB67-DAP-Seq(GSE60143)/Homer YYYACCTAAC 1e-1 -3.563e+00 0.9398 984.0 24.61% 908.4 22.77% +SeqBias: TA-repeat TATATATATA 1e-1 -3.471e+00 0.9968 2215.0 55.39% 2125.9 53.29% +MYB74(MYB)/colamp-MYB74-DAP-Seq(GSE60143)/Homer YYYACCTACCWH 1e-1 -3.406e+00 1.0000 624.0 15.60% 564.0 14.14% +ATHB25(ZFHD)/colamp-ATHB25-DAP-Seq(GSE60143)/Homer TAATTAVB 1e-1 -3.390e+00 1.0000 1521.0 38.03% 1437.2 36.03% +Adof1(C2C2dof)/col-Adof1-DAP-Seq(GSE60143)/Homer NRWAAAGYDV 1e-1 -3.371e+00 1.0000 2121.0 53.04% 2033.6 50.98% +At1g64620(C2C2dof)/colamp-At1g64620-DAP-Seq(GSE60143)/Homer CACTTTTT 1e-1 -3.365e+00 1.0000 1032.0 25.81% 958.0 24.02% +ATHB23(ZFHD)/col-ATHB23-DAP-Seq(GSE60143)/Homer HTAATTARNN 1e-1 -3.321e+00 1.0000 1241.0 31.03% 1163.3 29.16% +AT4G26030(C2H2)/col-AT4G26030-DAP-Seq(GSE60143)/Homer BYYACCWACY 1e-1 -3.271e+00 1.0000 980.0 24.51% 909.5 22.80% +MYB61(MYB)/colamp-MYB61-DAP-Seq(GSE60143)/Homer HCYACCTACC 1e-1 -3.225e+00 1.0000 1399.0 34.98% 1320.1 33.09% +Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/Homer CTAATKGV 1e-1 -3.223e+00 1.0000 2181.0 54.54% 2096.3 52.55% +At4g01280(MYBrelated)/colamp-At4g01280-DAP-Seq(GSE60143)/Homer AAATATCT 1e-1 -3.217e+00 1.0000 503.0 12.58% 450.4 11.29% +ATHB13(Homeobox)/col-ATHB13-DAP-Seq(GSE60143)/Homer CAATAATT 1e-1 -3.200e+00 1.0000 1111.0 27.78% 1038.9 26.04% +bcd(Homeobox)/Embryo-Bcd-ChIP-Seq(GSE86966)/Homer VNNGGATTADNN 1e-1 -3.196e+00 1.0000 1506.0 37.66% 1426.1 35.75% +RVE1(MYBrelated)/col-RVE1-DAP-Seq(GSE60143)/Homer AAATATCT 1e-1 -3.186e+00 1.0000 706.0 17.65% 645.2 16.18% +HDG1(Homeobox)/col100-HDG1-DAP-Seq(GSE60143)/Homer DDYAATTAATGH 1e-1 -3.185e+00 1.0000 491.0 12.28% 439.8 11.03% +Twist2(bHLH)/Myoblast-Twist2.Ty1-ChIP-Seq(GSE127998)/Homer MCAGCTGBYH 1e-1 -3.182e+00 1.0000 927.0 23.18% 859.4 21.54% +HIC1(Zf)/Treg-ZBTB29-ChIP-Seq(GSE99889)/Homer TGCCAGCB 1e-1 -3.141e+00 1.0000 1210.0 30.26% 1136.8 28.50% +TAGL1(MADS)/Tomato-TAGL1-ChIP-Seq(GSE116581)/Homer CCAAAAATRG 1e-1 -3.140e+00 1.0000 991.0 24.78% 923.0 23.14% +GSC(Homeobox)/FrogEmbryos-GSC-ChIP-Seq(DRA000576)/Homer RGGATTAR 1e-1 -3.108e+00 1.0000 1568.0 39.21% 1489.4 37.34% +ATHB6(Homeobox)/col-ATHB6-DAP-Seq(GSE60143)/Homer AATGATTG 1e-1 -3.081e+00 1.0000 1457.0 36.43% 1380.3 34.60% +NF1-halfsite(CTF)/LNCaP-NF1-ChIP-Seq(Unpublished)/Homer YTGCCAAG 1e-1 -3.064e+00 1.0000 966.0 24.16% 899.8 22.56% +Hoxd11(Homeobox)/ChickenMSG-Hoxd11.Flag-ChIP-Seq(GSE86088)/Homer VGCCATAAAA 1e-1 -3.039e+00 1.0000 2300.0 57.51% 2219.9 55.65% +At5g52660(MYBrelated)/colamp-At5g52660-DAP-Seq(GSE60143)/Homer HAAAAATATCTW 1e-1 -3.035e+00 1.0000 337.0 8.43% 296.0 7.42% +SCL(bHLH)/HPC7-Scl-ChIP-Seq(GSE13511)/Homer AVCAGCTG 1e-1 -3.035e+00 1.0000 2119.0 52.99% 2038.5 51.10% +EPR1(MYBrelated)/colamp-EPR1-DAP-Seq(GSE60143)/Homer AAATATCT 1e-1 -2.993e+00 1.0000 381.0 9.53% 337.2 8.45% +LHY1(MYBrelated)/col-LHY1-DAP-Seq(GSE60143)/Homer AAATATCT 1e-1 -2.993e+00 1.0000 381.0 9.53% 337.2 8.45% +MYB17(MYB)/colamp-MYB17-DAP-Seq(GSE60143)/Homer GGTAGGTGRG 1e-1 -2.960e+00 1.0000 491.0 12.28% 442.6 11.10% +caudal(Homeobox)/Drosophila-Embryos-ChIP-Chip(modEncode)/Homer GGYCATAAAW 1e-1 -2.960e+00 1.0000 923.0 23.08% 859.8 21.55% +AT1G20910(ARID)/col-AT1G20910-DAP-Seq(GSE60143)/Homer THAATTRAWN 1e-1 -2.958e+00 1.0000 1797.0 44.94% 1719.3 43.10% +MYB51(MYB)/col-MYB51-DAP-Seq(GSE60143)/Homer GGTAGGTG 1e-1 -2.958e+00 1.0000 852.0 21.31% 790.0 19.80% +AT2G28810(C2C2dof)/colamp-AT2G28810-DAP-Seq(GSE60143)/Homer VAAAAAGTWA 1e-1 -2.947e+00 1.0000 1702.0 42.56% 1625.7 40.75% +MYB93(MYB)/colamp-MYB93-DAP-Seq(GSE60143)/Homer GGTAGGTGRD 1e-1 -2.942e+00 1.0000 1058.0 26.46% 991.1 24.85% +Tbr1(T-box)/Cortex-Tbr1-ChIP-Seq(GSE71384)/Homer AAGGTGTKAA 1e-1 -2.938e+00 1.0000 1260.0 31.51% 1189.4 29.82% +MYB3(MYB)/Arabidopsis-MYB3-ChIP-Seq(GSE80564)/Homer GKTAGGTRGG 1e-1 -2.933e+00 1.0000 1460.0 36.51% 1386.9 34.77% +DAG2(C2C2dof)/col-DAG2-DAP-Seq(GSE60143)/Homer WWTTHACTTTTT 1e-1 -2.931e+00 1.0000 1213.0 30.33% 1143.9 28.68% +OBP1(C2C2dof)/col-OBP1-DAP-Seq(GSE60143)/Homer NHHACTTTWT 1e-1 -2.895e+00 1.0000 2223.0 55.59% 2145.9 53.80% +MYB41(MYB)/col-MYB41-DAP-Seq(GSE60143)/Homer BYTYACCTAA 1e-1 -2.884e+00 1.0000 407.0 10.18% 363.5 9.11% +At2g41835(C2H2)/col-At2g41835-DAP-Seq(GSE60143)/Homer TTTGAAAA 1e-1 -2.884e+00 1.0000 315.0 7.88% 276.2 6.92% +CDX4(Homeobox)/ZebrafishEmbryos-Cdx4.Myc-ChIP-Seq(GSE48254)/Homer NGYCATAAAWCH 1e-1 -2.883e+00 1.0000 978.0 24.46% 914.3 22.92% +ATHB34(ZFHD)/colamp-ATHB34-DAP-Seq(GSE60143)/Homer TRATTARS 1e-1 -2.868e+00 1.0000 1124.0 28.11% 1057.4 26.51% +At1g69690(TCP)/colamp-At1g69690-DAP-Seq(GSE60143)/Homer NHGTGGGGCCCACHW 1e-1 -2.854e+00 1.0000 129.0 3.23% 104.6 2.62% +PRDM15(Zf)/ESC-Prdm15-ChIP-Seq(GSE73694)/Homer YCCDNTCCAGGTTTT 1e-1 -2.849e+00 1.0000 603.0 15.08% 551.7 13.83% +dof24(C2C2dof)/col-dof24-DAP-Seq(GSE60143)/Homer TWMCTTTTTG 1e-1 -2.831e+00 1.0000 1553.0 38.83% 1480.4 37.11% +LMI1(HB)/colamp-LMI1-DAP-Seq(GSE60143)/Homer AATTATTG 1e-1 -2.829e+00 1.0000 759.0 18.98% 702.4 17.61% +MS188(MYB)/colamp-MS188-DAP-Seq(GSE60143)/Homer WARKTAGGTRRA 1e-1 -2.826e+00 1.0000 828.0 20.71% 769.5 19.29% +PBX2(Homeobox)/K562-PBX2-ChIP-Seq(Encode)/Homer RTGATTKATRGN 1e-1 -2.818e+00 1.0000 946.0 23.66% 884.9 22.18% +MYB13(MYB)/col-MYB13-DAP-Seq(GSE60143)/Homer HYCACCWACCHH 1e-1 -2.798e+00 1.0000 521.0 13.03% 473.4 11.87% +MYB92(MYB)/colamp-MYB92-DAP-Seq(GSE60143)/Homer GGTAGGTR 1e-1 -2.797e+00 1.0000 883.0 22.08% 823.8 20.65% +ANL2(HB)/col-ANL2-DAP-Seq(GSE60143)/Homer CATTAATTGC 1e-1 -2.797e+00 1.0000 546.0 13.65% 497.0 12.46% +MYB83(MYB)/colamp-MYB83-DAP-Seq(GSE60143)/Homer CACCAACCWH 1e-1 -2.772e+00 1.0000 1493.0 37.33% 1422.4 35.66% +OCT:OCT(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)/Homer ATGAATATTCATGAG 1e-1 -2.768e+00 1.0000 4.0 0.10% 1.0 0.02% +Bapx1(Homeobox)/VertebralCol-Bapx1-ChIP-Seq(GSE36672)/Homer TTRAGTGSYK 1e-1 -2.758e+00 1.0000 1718.0 42.96% 1645.2 41.24% +Tcf12(bHLH)/GM12878-Tcf12-ChIP-Seq(GSE32465)/Homer VCAGCTGYTG 1e-1 -2.740e+00 1.0000 345.0 8.63% 307.0 7.70% +ERRg(NR)/Kidney-ESRRG-ChIP-Seq(GSE104905)/Homer GTGACCTTGRVN 1e-1 -2.730e+00 1.0000 521.0 13.03% 474.7 11.90% +CRX(Homeobox)/Retina-Crx-ChIP-Seq(GSE20012)/Homer GCTAATCC 1e-1 -2.693e+00 1.0000 2607.0 65.19% 2535.5 63.56% +At1g76110(ARID)/colamp-At1g76110-DAP-Seq(GSE60143)/Homer ATTTAATG 1e-1 -2.676e+00 1.0000 683.0 17.08% 631.7 15.84% +Barx1(Homeobox)/Stomach-Barx1.3xFlag-ChIP-Seq(GSE69483)/Homer AAACMATTAN 1e-1 -2.675e+00 1.0000 542.0 13.55% 495.0 12.41% +At5g62940(C2C2dof)/col-At5g62940-DAP-Seq(GSE60143)/Homer WHWHHACTTTTT 1e-1 -2.660e+00 1.0000 2485.0 62.14% 2414.0 60.52% +NeuroG2(bHLH)/Fibroblast-NeuroG2-ChIP-Seq(GSE75910)/Homer ACCATCTGTT 1e-1 -2.654e+00 1.0000 832.0 20.81% 776.6 19.47% +FUS3(ABI3VP1)/col-FUS3-DAP-Seq(GSE60143)/Homer DNNWTNTGCATGKNN 1e-1 -2.644e+00 1.0000 733.0 18.33% 680.1 17.05% +AT3G52440(C2C2dof)/colamp-AT3G52440-DAP-Seq(GSE60143)/Homer DTHACTTTTT 1e-1 -2.637e+00 1.0000 1825.0 45.64% 1754.3 43.98% +Phox2a(Homeobox)/Neuron-Phox2a-ChIP-Seq(GSE31456)/Homer YTAATYNRATTA 1e-1 -2.633e+00 1.0000 392.0 9.80% 352.9 8.85% +AT3G12130(C3H)/colamp-AT3G12130-DAP-Seq(GSE60143)/Homer TMACTTTTTV 1e-1 -2.625e+00 1.0000 1875.0 46.89% 1804.9 45.25% +AT5G66940(C2C2dof)/col-AT5G66940-DAP-Seq(GSE60143)/Homer NNHACTTTWT 1e-1 -2.575e+00 1.0000 1625.0 40.64% 1557.5 39.04% +Prop1(Homeobox)/GHFT1-PROP1.biotin-ChIP-Seq(GSE77302)/Homer NTAATBNAATTA 1e-1 -2.564e+00 1.0000 649.0 16.23% 600.5 15.05% +Myf5(bHLH)/GM-Myf5-ChIP-Seq(GSE24852)/Homer BAACAGCTGT 1e-1 -2.564e+00 1.0000 274.0 6.85% 241.4 6.05% +HDG7(HB)/col-HDG7-DAP-Seq(GSE60143)/Homer WGCATTTAATGC 1e-1 -2.541e+00 1.0000 184.0 4.60% 157.8 3.96% +Nr5a2(NR)/mES-Nr5a2-ChIP-Seq(GSE19019)/Homer BTCAAGGTCA 1e-1 -2.535e+00 1.0000 280.0 7.00% 247.3 6.20% +Dlx3(Homeobox)/Kerainocytes-Dlx3-ChIP-Seq(GSE89884)/Homer NDGTAATTAC 1e-1 -2.532e+00 1.0000 969.0 24.23% 912.3 22.87% +AT5G47660(Trihelix)/colamp-AT5G47660-DAP-Seq(GSE60143)/Homer AWTTTTACCG 1e-1 -2.530e+00 1.0000 1443.0 36.08% 1378.9 34.57% +AT2G28920(ND)/col-AT2G28920-DAP-Seq(GSE60143)/Homer WAGATATTTWTW 1e-1 -2.522e+00 1.0000 216.0 5.40% 187.7 4.71% +AT2G38300(G2like)/col-AT2G38300-DAP-Seq(GSE60143)/Homer ADRGAATGTT 1e-1 -2.506e+00 1.0000 1092.0 27.31% 1033.5 25.91% +ATHB24(ZFHD)/colamp-ATHB24-DAP-Seq(GSE60143)/Homer TAATTAAS 1e-1 -2.493e+00 1.0000 1107.0 27.68% 1048.9 26.30% +MYB40(MYB)/col-MYB40-DAP-Seq(GSE60143)/Homer TGGTAGGTRARA 1e-1 -2.483e+00 1.0000 310.0 7.75% 276.5 6.93% +MYB10(MYB)/col-MYB10-DAP-Seq(GSE60143)/Homer YCCACCTACCHH 1e-1 -2.466e+00 1.0000 376.0 9.40% 339.8 8.52% +TCF4(bHLH)/SHSY5Y-TCF4-ChIP-Seq(GSE96915)/Homer SMCATCTGKH 1e-1 -2.461e+00 1.0000 818.0 20.46% 766.3 19.21% +At5g04390(C2H2)/col200-At5g04390-DAP-Seq(GSE60143)/Homer AGTGANDN 1e-1 -2.432e+00 1.0000 3476.0 86.92% 3424.3 85.84% +Lhx2(Homeobox)/HFSC-Lhx2-ChIP-Seq(GSE48068)/Homer TAATTAGN 1e-1 -2.431e+00 1.0000 1468.0 36.71% 1405.7 35.24% +GT2(Trihelix)/colamp-GT2-DAP-Seq(GSE60143)/Homer AMGGTAAAWWWN 1e-1 -2.430e+00 1.0000 1072.0 26.81% 1015.4 25.45% +TRPS1(Zf)/MCF7-TRPS1-ChIP-Seq(GSE107013)/Homer AGATAAGANN 1e-1 -2.424e+00 1.0000 2129.0 53.24% 2062.7 51.71% +TCP1(TCP)/col-TCP1-DAP-Seq(GSE60143)/Homer GGGGGCCCMMCN 1e-1 -2.404e+00 1.0000 134.0 3.35% 112.4 2.82% +AT3G10113(MYBrelated)/col-AT3G10113-DAP-Seq(GSE60143)/Homer WNAAATATCWWN 1e-1 -2.399e+00 1.0000 524.0 13.10% 482.2 12.09% +AGL63(MADS)/col-AGL63-DAP-Seq(GSE60143)/Homer TTCCAAWWWTGG 1e-1 -2.399e+00 1.0000 749.0 18.73% 700.2 17.55% +CCA(Myb)/Arabidopsis-CCA.GFP-ChIP-Seq(GSE70533)/Homer AGATATYTTT 1e-1 -2.391e+00 1.0000 964.0 24.11% 910.8 22.83% +TSO1(CPP)/col-TSO1-DAP-Seq(GSE60143)/Homer RAATTTRAAW 1e-1 -2.378e+00 1.0000 63.0 1.58% 48.7 1.22% +HAT1(Homeobox)/col-HAT1-DAP-Seq(GSE60143)/Homer SCAATCATTGNN 1e-1 -2.367e+00 1.0000 194.0 4.85% 169.0 4.24% +GLIS3(Zf)/Thyroid-Glis3.GFP-ChIP-Seq(GSE103297)/Homer CTCCCTGGGAGGCCN 1e-1 -2.364e+00 1.0000 570.0 14.25% 527.0 13.21% +KAN2(G2like)/colamp-KAN2-DAP-Seq(GSE60143)/Homer ATATTCTY 1e-1 -2.356e+00 1.0000 1226.0 30.66% 1168.0 29.28% +At3g09600(MYBrelated)/colamp-At3g09600-DAP-Seq(GSE60143)/Homer AAAATATCTT 1e-1 -2.352e+00 1.0000 389.0 9.73% 353.3 8.86% +MYB55(MYB)/colamp-MYB55-DAP-Seq(GSE60143)/Homer YACCWAMC 1e-1 -2.349e+00 1.0000 1173.0 29.33% 1116.4 27.99% +OBP4(C2C2dof)/col-OBP4-DAP-Seq(GSE60143)/Homer WTTHACTTTTTB 1e-1 -2.328e+00 1.0000 1141.0 28.53% 1085.3 27.21% +MYB62(MYB)/colamp-MYB62-DAP-Seq(GSE60143)/Homer NTACCTAACT 1e-1 -2.328e+00 1.0000 1612.0 40.31% 1550.8 38.88% +REM19(REM)/colamp-REM19-DAP-Seq(GSE60143)/Homer AAAAAAAA 1e-1 -2.326e+00 1.0000 185.0 4.63% 160.5 4.02% +GTL1(Trihelix)/colamp-GTL1-DAP-Seq(GSE60143)/Homer WWTTTACCKY 1e-1 -2.325e+00 1.0000 1034.0 25.86% 980.3 24.58% +At3g45610(C2C2dof)/col-At3g45610-DAP-Seq(GSE60143)/Homer TWACTTTTTS 1e-1 -2.323e+00 1.0000 1090.0 27.26% 1035.1 25.95% +ELT-3(Gata)/cElegans-L1-ELT3-ChIP-Seq(modEncode)/Homer AWTGATAAGA 1e-1 -2.303e+00 1.0000 512.0 12.80% 472.8 11.85% +ZNF143|STAF(Zf)/CUTLL-ZNF143-ChIP-Seq(GSE29600)/Homer ATTTCCCAGVAKSCY 1e0 -2.296e+00 1.0000 97.0 2.43% 80.0 2.01% +Lhx1(Homeobox)/EmbryoCarcinoma-Lhx1-ChIP-Seq(GSE70957)/Homer NNYTAATTAR 1e0 -2.295e+00 1.0000 1402.0 35.06% 1343.0 33.67% +HSF3(HSF)/colamp-HSF3-DAP-Seq(GSE60143)/Homer NTTCTAGAAKCTTCT 1e0 -2.289e+00 1.0000 679.0 16.98% 634.3 15.90% +RAR:RXR(NR),DR5/ES-RAR-ChIP-Seq(GSE56893)/Homer AGGTCAAGGTCA 1e0 -2.277e+00 1.0000 51.0 1.28% 38.1 0.95% +LIN-39(Homeobox)/cElegans.L3-LIN39-ChIP-Seq(modEncode)/Homer ATGATTRATG 1e0 -2.272e+00 1.0000 1043.0 26.08% 990.2 24.82% +AT3G10580(MYBrelated)/colamp-AT3G10580-DAP-Seq(GSE60143)/Homer TACCTAACWNHW 1e0 -2.268e+00 1.0000 529.0 13.23% 489.8 12.28% +ATHB53(HB)/col-ATHB53-DAP-Seq(GSE60143)/Homer CAATAATT 1e0 -2.248e+00 1.0000 539.0 13.48% 499.3 12.52% +MYB107(MYB)/col-MYB107-DAP-Seq(GSE60143)/Homer RGTWGGTRRR 1e0 -2.247e+00 1.0000 1507.0 37.68% 1448.1 36.30% +Nr5a2(NR)/Pancreas-LRH1-ChIP-Seq(GSE34295)/Homer BTCAAGGTCA 1e0 -2.232e+00 1.0000 383.0 9.58% 349.2 8.75% +OBP3(C2C2dof)/col-OBP3-DAP-Seq(GSE60143)/Homer NYWACTTTTT 1e0 -2.224e+00 1.0000 2288.0 57.21% 2226.3 55.81% +AT5G60130(ABI3VP1)/col-AT5G60130-DAP-Seq(GSE60143)/Homer WTTYTAAGVAAA 1e0 -2.221e+00 1.0000 996.0 24.91% 945.6 23.70% +RIN(MADS)/Tomato-RIN-ChIP-Seq(GSE116581)/Homer CYAAAAWWGG 1e0 -2.187e+00 1.0000 1037.0 25.93% 986.6 24.73% +WIP5(C2H2)/colamp-WIP5-DAP-Seq(GSE60143)/Homer TDTTCTCMAGGT 1e0 -2.153e+00 1.0000 872.0 21.81% 825.5 20.69% +CDF3(C2C2dof)/colamp-CDF3-DAP-Seq(GSE60143)/Homer AAAAGTRM 1e0 -2.124e+00 1.0000 1337.0 33.43% 1283.8 32.18% +NLP7(RWPRK)/col-NLP7-DAP-Seq(GSE60143)/Homer TGRCCYTTCR 1e0 -2.120e+00 1.0000 1344.0 33.61% 1290.3 32.35% +Unknown4/Drosophila-Promoters/Homer AAAAATACCRMA 1e0 -2.119e+00 1.0000 113.0 2.83% 96.0 2.41% +LBD19(LOBAS2)/colamp-LBD19-DAP-Seq(GSE60143)/Homer CCKGAAWTTCMGGAW 1e0 -2.118e+00 1.0000 2051.0 51.29% 1992.4 49.95% +Tgif2(Homeobox)/mES-Tgif2-ChIP-Seq(GSE55404)/Homer TGTCANYT 1e0 -2.112e+00 1.0000 2337.0 58.44% 2278.2 57.11% +Hoxa11(Homeobox)/ChickenMSG-Hoxa11.Flag-ChIP-Seq(GSE86088)/Homer TTTTATGGCM 1e0 -2.109e+00 1.0000 2253.0 56.34% 2194.2 55.01% +Six4(Homeobox)/MCF7-SIX4-ChIP-Seq(Encode)/Homer TGWAAYCTGABACCB 1e0 -2.103e+00 1.0000 42.0 1.05% 31.5 0.79% +MYB63(MYB)/col-MYB63-DAP-Seq(GSE60143)/Homer BHYACCWACCHH 1e0 -2.093e+00 1.0000 385.0 9.63% 353.9 8.87% +Rfx6(HTH)/Min6b1-Rfx6.HA-ChIP-Seq(GSE62844)/Homer TGTTKCCTAGCAACM 1e0 -2.086e+00 1.0000 675.0 16.88% 634.5 15.91% +BBX31(Orphan)/col-BBX31-DAP-Seq(GSE60143)/Homer NAAAAAGTDA 1e0 -2.086e+00 1.0000 1255.0 31.38% 1203.7 30.18% +Pax7(Paired,Homeobox),long/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer TAATCHGATTAC 1e0 -2.080e+00 1.0000 17.0 0.43% 10.7 0.27% +At5g58900(MYBrelated)/colamp-At5g58900-DAP-Seq(GSE60143)/Homer WWWTYTTATCTWWWW 1e0 -2.078e+00 1.0000 1539.0 38.48% 1484.8 37.22% +Esrrb(NR)/mES-Esrrb-ChIP-Seq(GSE11431)/Homer KTGACCTTGA 1e0 -2.076e+00 1.0000 419.0 10.48% 386.1 9.68% +Olig2(bHLH)/Neuron-Olig2-ChIP-Seq(GSE30882)/Homer RCCATMTGTT 1e0 -2.063e+00 1.0000 1223.0 30.58% 1172.9 29.40% +ZKSCAN1(Zf)/HepG2-ZKSCAN1-ChIP-Seq(Encode)/Homer GCACAYAGTAGGKCY 1e0 -2.058e+00 1.0000 29.0 0.73% 20.6 0.52% +Unknown2/Drosophila-Promoters/Homer CATCMCTA 1e0 -2.050e+00 1.0000 704.0 17.60% 663.8 16.64% +At1g49010(MYBrelated)/col-At1g49010-DAP-Seq(GSE60143)/Homer RGATAASNTT 1e0 -2.038e+00 1.0000 2133.0 53.34% 2076.5 52.06% +BHLHA15(bHLH)/NIH3T3-BHLHB8.HA-ChIP-Seq(GSE119782)/Homer NAMCAGCTGK 1e0 -2.028e+00 1.0000 682.0 17.05% 642.7 16.11% +MYNN(Zf)/HEK293-MYNN.eGFP-ChIP-Seq(Encode)/Homer TTCAAAWTAAAAGTC 1e0 -2.023e+00 1.0000 206.0 5.15% 183.8 4.61% +ATHB6(Homeobox)/Arabidopsis-HB6-ChIP-Seq(GSE80564)/Homer CAATNATTBN 1e0 -2.018e+00 1.0000 870.0 21.76% 826.4 20.72% +JGL(C2H2)/col-JGL-DAP-Seq(GSE60143)/Homer ACYTTCAGTT 1e0 -2.010e+00 1.0000 1416.0 35.41% 1364.6 34.21% +Unknown6/Drosophila-Promoters/Homer AATTTTAAAA 1e0 -2.000e+00 1.0000 370.0 9.25% 340.2 8.53% +At2g01060(G2like)/colamp-At2g01060-DAP-Seq(GSE60143)/Homer AGATKCBNWW 1e0 -1.986e+00 1.0000 2978.0 74.47% 2926.7 73.37% +ATHB21(HB)/colamp-ATHB21-DAP-Seq(GSE60143)/Homer YCAATWAT 1e0 -1.985e+00 1.0000 677.0 16.93% 638.4 16.00% +LBD18(LOBAS2)/colamp-LBD18-DAP-Seq(GSE60143)/Homer CKGAWWTTCHGS 1e0 -1.983e+00 1.0000 2736.0 68.42% 2682.1 67.24% +dof45(C2C2dof)/col-dof45-DAP-Seq(GSE60143)/Homer NVAWAAAGTN 1e0 -1.979e+00 1.0000 1976.0 49.41% 1921.6 48.17% +Oct4(POU,Homeobox)/mES-Oct4-ChIP-Seq(GSE11431)/Homer ATTTGCATAW 1e0 -1.963e+00 1.0000 333.0 8.33% 305.5 7.66% +CRC(C2C2YABBY)/col-CRC-DAP-Seq(GSE60143)/Homer TWATSATA 1e0 -1.957e+00 1.0000 1567.0 39.18% 1516.0 38.00% +AT5G61620(MYBrelated)/colamp-AT5G61620-DAP-Seq(GSE60143)/Homer CTTATCCA 1e0 -1.946e+00 1.0000 1748.0 43.71% 1696.0 42.52% +NeuroD1(bHLH)/Islet-NeuroD1-ChIP-Seq(GSE30298)/Homer GCCATCTGTT 1e0 -1.939e+00 1.0000 369.0 9.23% 340.8 8.54% +Atoh1(bHLH)/Cerebellum-Atoh1-ChIP-Seq(GSE22111)/Homer VNRVCAGCTGGY 1e0 -1.936e+00 1.0000 491.0 12.28% 458.4 11.49% +RARa(NR)/K562-RARa-ChIP-Seq(Encode)/Homer TTGAMCTTTG 1e0 -1.933e+00 1.0000 1815.0 45.39% 1762.7 44.19% +Mef2c(MADS)/GM12878-Mef2c-ChIP-Seq(GSE32465)/Homer DCYAAAAATAGM 1e0 -1.933e+00 1.0000 271.0 6.78% 246.1 6.17% +Unknown-ESC-element(?)/mES-Nanog-ChIP-Seq(GSE11724)/Homer CACAGCAGGGGG 1e0 -1.932e+00 1.0000 170.0 4.25% 150.4 3.77% +Nkx6.1(Homeobox)/Islet-Nkx6.1-ChIP-Seq(GSE40975)/Homer GKTAATGR 1e0 -1.932e+00 1.0000 3040.0 76.02% 2990.9 74.98% +WRKY7(WRKY)/colamp-WRKY7-DAP-Seq(GSE60143)/Homer AAAAGTCAACGSHWD 1e0 -1.929e+00 1.0000 6.0 0.15% 2.7 0.07% +COUP-TFII(NR)/Artia-Nr2f2-ChIP-Seq(GSE46497)/Homer AGRGGTCA 1e0 -1.928e+00 1.0000 1180.0 29.51% 1133.5 28.41% +CEBP:CEBP(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer NTNATGCAAYMNNHTGMAAY 1e0 -1.912e+00 1.0000 96.0 2.40% 81.5 2.04% +AZF1(C2H2)/colamp-AZF1-DAP-Seq(GSE60143)/Homer DKSWCACT 1e0 -1.906e+00 1.0000 3343.0 83.60% 3298.6 82.69% +HNF1b(Homeobox)/PDAC-HNF1B-ChIP-Seq(GSE64557)/Homer GTTAATNATTAA 1e0 -1.905e+00 1.0000 141.0 3.53% 123.7 3.10% +Cdx2(Homeobox)/mES-Cdx2-ChIP-Seq(GSE14586)/Homer GYMATAAAAH 1e0 -1.902e+00 1.0000 624.0 15.60% 588.8 14.76% +ZNF416(Zf)/HEK293-ZNF416.GFP-ChIP-Seq(GSE58341)/Homer WDNCTGGGCA 1e0 -1.892e+00 1.0000 519.0 12.98% 486.3 12.19% +AT5G02460(C2C2dof)/col-AT5G02460-DAP-Seq(GSE60143)/Homer CHCCTTTT 1e0 -1.889e+00 1.0000 1344.0 33.61% 1296.2 32.49% +LCL1(MYBrelated)/colamp-LCL1-DAP-Seq(GSE60143)/Homer NAAAATATCTWHWWN 1e0 -1.876e+00 1.0000 100.0 2.50% 85.9 2.15% +COUP-TFII(NR)/K562-NR2F1-ChIP-Seq(Encode)/Homer GKBCARAGGTCA 1e0 -1.873e+00 1.0000 887.0 22.18% 847.0 21.23% +ATHB15(HB)/col-ATHB15-DAP-Seq(GSE60143)/Homer GYAATSATTA 1e0 -1.868e+00 1.0000 373.0 9.33% 345.1 8.65% +ZNF382(Zf)/HEK293-ZNF382.GFP-ChIP-Seq(GSE58341)/Homer GNCTGTASTRNTGBCTCHTT 1e0 -1.864e+00 1.0000 15.0 0.38% 9.6 0.24% +WRKY17(WRKY)/colamp-WRKY17-DAP-Seq(GSE60143)/Homer GCGTTGACTTTT 1e0 -1.864e+00 1.0000 15.0 0.38% 9.7 0.24% +Otx2(Homeobox)/EpiLC-Otx2-ChIP-Seq(GSE56098)/Homer NYTAATCCYB 1e0 -1.853e+00 1.0000 973.0 24.33% 931.9 23.36% +Pitx1:Ebox(Homeobox,bHLH)/Hindlimb-Pitx1-ChIP-Seq(GSE41591)/Homer YTAATTRAWWCCAGATGT 1e0 -1.850e+00 1.0000 103.0 2.58% 88.4 2.22% +HOXA9(Homeobox)/HSC-Hoxa9-ChIP-Seq(GSE33509)/Homer GGCCATAAATCA 1e0 -1.844e+00 1.0000 720.0 18.00% 683.6 17.14% +Nkx2.2(Homeobox)/NPC-Nkx2.2-ChIP-Seq(GSE61673)/Homer BTBRAGTGSN 1e0 -1.841e+00 1.0000 1476.0 36.91% 1428.7 35.82% +AT1G47655(C2C2dof)/colamp-AT1G47655-DAP-Seq(GSE60143)/Homer YHACTTTTTS 1e0 -1.841e+00 1.0000 2564.0 64.12% 2513.4 63.01% +AIL7(AP2EREBP)/colamp-AIL7-DAP-Seq(GSE60143)/Homer KCACRAWTYYCGAGG 1e0 -1.835e+00 1.0000 559.0 13.98% 526.1 13.19% +HLH-1(bHLH)/cElegans-Embryo-HLH1-ChIP-Seq(modEncode)/Homer RACAGCTGTTBH 1e0 -1.819e+00 1.0000 462.0 11.55% 432.6 10.84% +ATHB18(Homeobox)/colamp-ATHB18-DAP-Seq(GSE60143)/Homer YCAATSATTG 1e0 -1.810e+00 1.0000 218.0 5.45% 197.2 4.94% +At3g12730(G2like)/colamp-At3g12730-DAP-Seq(GSE60143)/Homer AAGATTCT 1e0 -1.804e+00 1.0000 1607.0 40.19% 1559.2 39.09% +MYB99(MYB)/colamp-MYB99-DAP-Seq(GSE60143)/Homer GGTAGGTG 1e0 -1.798e+00 1.0000 996.0 24.91% 955.9 23.96% +Twist(bHLH)/HMLE-TWIST1-ChIP-Seq(Chang_et_al)/Homer VCAKCTGGNNNCCAGMTGBN 1e0 -1.796e+00 1.0000 38.0 0.95% 29.1 0.73% +Pdx1(Homeobox)/Islet-Pdx1-ChIP-Seq(SRA008281)/Homer YCATYAATCA 1e0 -1.790e+00 1.0000 946.0 23.66% 906.3 22.72% +Nkx2.1(Homeobox)/LungAC-Nkx2.1-ChIP-Seq(GSE43252)/Homer RSCACTYRAG 1e0 -1.790e+00 1.0000 2210.0 55.26% 2160.0 54.15% +At1g72010(TCP)/colamp-At1g72010-DAP-Seq(GSE60143)/Homer GGDCCCAC 1e0 -1.786e+00 1.0000 248.0 6.20% 226.9 5.69% +RBFox2(?)/Heart-RBFox2-CLIP-Seq(GSE57926)/Homer TGCATGCA 1e0 -1.782e+00 1.0000 1699.0 42.49% 1652.0 41.41% +BPC1(BBRBPC)/colamp-BPC1-DAP-Seq(GSE60143)/Homer GARGAGAGAGAA 1e0 -1.781e+00 1.0000 164.0 4.10% 146.3 3.67% +MYB39(MYB)/col-MYB39-DAP-Seq(GSE60143)/Homer WWAARKTAGGTGRAA 1e0 -1.781e+00 1.0000 164.0 4.10% 146.4 3.67% +WRKY8(WRKY)/colamp-WRKY8-DAP-Seq(GSE60143)/Homer CGTTGACTTT 1e0 -1.765e+00 1.0000 85.0 2.13% 72.3 1.81% +MYB94(MYB)/col-MYB94-DAP-Seq(GSE60143)/Homer WGGTRGTTGGKA 1e0 -1.760e+00 1.0000 282.0 7.05% 260.0 6.52% +At2g45680(TCP)/colamp-At2g45680-DAP-Seq(GSE60143)/Homer GTGGGNCCCACNDND 1e0 -1.759e+00 1.0000 31.0 0.78% 23.7 0.59% +AT1G76880(Trihelix)/col-AT1G76880-DAP-Seq(GSE60143)/Homer ACGGTAAAAW 1e0 -1.756e+00 1.0000 339.0 8.48% 314.0 7.87% +At1g68670(G2like)/colamp-At1g68670-DAP-Seq(GSE60143)/Homer WNWWHNRAAGATTCT 1e0 -1.755e+00 1.0000 434.0 10.85% 406.8 10.20% +TCP20(TCP)/col-TCP20-DAP-Seq(GSE60143)/Homer GGDCCCAC 1e0 -1.741e+00 1.0000 173.0 4.33% 155.6 3.90% +PHV(HB)/col-PHV-DAP-Seq(GSE60143)/Homer RTAATSATTA 1e0 -1.739e+00 1.0000 410.0 10.25% 383.3 9.61% +Tal1 CATCTG 1e0 -1.738e+00 1.0000 846.0 21.16% 809.8 20.30% +AT2G15740(C2H2)/col-AT2G15740-DAP-Seq(GSE60143)/Homer DHNDWATCGATD 1e0 -1.736e+00 1.0000 2562.0 64.07% 2514.8 63.04% +MYB58(MYB)/colamp-MYB58-DAP-Seq(GSE60143)/Homer YYYACCWACC 1e0 -1.735e+00 1.0000 971.0 24.28% 932.4 23.37% +Meis1(Homeobox)/MastCells-Meis1-ChIP-Seq(GSE48085)/Homer VGCTGWCAVB 1e0 -1.735e+00 1.0000 1190.0 29.76% 1148.0 28.78% +MYB113(MYB)/col-MYB113-DAP-Seq(GSE60143)/Homer HNDAWTCMGTTAYWN 1e0 -1.726e+00 1.0000 863.0 21.58% 826.8 20.73% +AT3G51470(DBP)/col-AT3G51470-DAP-Seq(GSE60143)/Homer TTWHGGTGCACC 1e0 -1.725e+00 1.0000 1828.0 45.71% 1781.8 44.67% +bZIP:IRF(bZIP,IRF)/Th17-BatF-ChIP-Seq(GSE39756)/Homer NAGTTTCABTHTGACTNW 1e0 -1.716e+00 1.0000 179.0 4.48% 161.7 4.05% +Mef2b(MADS)/HEK293-Mef2b.V5-ChIP-Seq(GSE67450)/Homer GCTATTTTTGGM 1e0 -1.716e+00 1.0000 714.0 17.85% 680.6 17.06% +CES-1(Homeobox)/cElegans-L1-CES1-ChIP-Seq(modEncode)/Homer AAATTSAATTTN 1e0 -1.715e+00 1.0000 497.0 12.43% 468.3 11.74% +bHLH130(bHLH)/col-bHLH130-DAP-Seq(GSE60143)/Homer GCAACTTG 1e0 -1.714e+00 1.0000 537.0 13.43% 508.0 12.73% +Zic(Zf)/Cerebellum-ZIC1.2-ChIP-Seq(GSE60731)/Homer CCTGCTGAGH 1e0 -1.709e+00 1.0000 464.0 11.60% 437.0 10.95% +AT1G69570(C2C2dof)/col-AT1G69570-DAP-Seq(GSE60143)/Homer WAAAAGTGHH 1e0 -1.700e+00 1.0000 1107.0 27.68% 1067.6 26.76% +ZNF692(Zf)/HEK293-ZNF692.GFP-ChIP-Seq(GSE58341)/Homer GTGGGCCCCA 1e0 -1.694e+00 1.0000 54.0 1.35% 44.4 1.11% +WRKY71(WRKY)/col-WRKY71-DAP-Seq(GSE60143)/Homer CKTTGACYWW 1e0 -1.688e+00 1.0000 696.0 17.40% 663.8 16.64% +WRKY40(WRKY)/colamp-WRKY40-DAP-Seq(GSE60143)/Homer AHWAGTCAAC 1e0 -1.682e+00 1.0000 523.0 13.08% 494.9 12.41% +PQM-1(?)/cElegans-L3-ChIP-Seq(modEncode)/Homer ACTGATAAGA 1e0 -1.678e+00 1.0000 487.0 12.18% 459.4 11.52% +At4g32800(AP2EREBP)/colamp-At4g32800-DAP-Seq(GSE60143)/Homer DYCACCGACAHWWWH 1e0 -1.675e+00 1.0000 237.0 5.93% 217.5 5.45% +WRKY21(WRKY)/colamp-WRKY21-DAP-Seq(GSE60143)/Homer DCGTTGACTTTT 1e0 -1.669e+00 1.0000 82.0 2.05% 70.8 1.78% +GATA3(Zf)/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATAASR 1e0 -1.669e+00 1.0000 1773.0 44.34% 1728.9 43.34% +NFAT:AP1(RHD,bZIP)/Jurkat-NFATC1-ChIP-Seq(Jolma_et_al.)/Homer SARTGGAAAAWRTGAGTCAB 1e0 -1.655e+00 1.0000 57.0 1.43% 47.5 1.19% +Hnf1(Homeobox)/Liver-Foxa2-Chip-Seq(GSE25694)/Homer GGTTAAWCATTAA 1e0 -1.648e+00 1.0000 100.0 2.50% 87.5 2.19% +CHR(?)/Hela-CellCycle-Expression/Homer SRGTTTCAAA 1e0 -1.645e+00 1.0000 366.0 9.15% 342.8 8.59% +LHY(Myb)/Seedling-LHY-ChIP-Seq(GSE52175)/Homer ADAAATATCT 1e0 -1.643e+00 1.0000 1240.0 31.01% 1200.2 30.09% +bHLH28(bHLH)/col-bHLH28-DAP-Seq(GSE60143)/Homer NHHTGTACGGAH 1e0 -1.631e+00 1.0000 1024.0 25.61% 987.9 24.76% +WRKY43(WRKY)/colamp-WRKY43-DAP-Seq(GSE60143)/Homer NCGTTGACTTTT 1e0 -1.630e+00 1.0000 311.0 7.78% 289.4 7.25% +MYB33(MYB)/col-MYB33-DAP-Seq(GSE60143)/Homer DDTYNGTTAN 1e0 -1.627e+00 1.0000 2207.0 55.19% 2162.9 54.22% +LBD2(LOBAS2)/colamp-LBD2-DAP-Seq(GSE60143)/Homer TCCGAWTTTTTCGGN 1e0 -1.615e+00 1.0000 734.0 18.35% 702.5 17.61% +SVP(MADS)/col-SVP-DAP-Seq(GSE60143)/Homer ANTTWCCHAATTTGG 1e0 -1.612e+00 1.0000 460.0 11.50% 434.8 10.90% +Unknown(Homeobox)/Limb-p300-ChIP-Seq/Homer SSCMATWAAA 1e0 -1.606e+00 1.0000 642.0 16.05% 612.6 15.36% +AT1G01250(AP2EREBP)/col-AT1G01250-DAP-Seq(GSE60143)/Homer YCACCGACAHTW 1e0 -1.604e+00 1.0000 125.0 3.13% 112.0 2.81% +EAR2(NR)/K562-NR2F6-ChIP-Seq(Encode)/Homer NRBCARRGGTCA 1e0 -1.602e+00 1.0000 810.0 20.26% 777.9 19.50% +At3g24120(G2like)/col-At3g24120-DAP-Seq(GSE60143)/Homer NWWAGMATMW 1e0 -1.592e+00 1.0000 2926.0 73.17% 2884.1 72.30% +bHLH122(bHLH)/col100-bHLH122-DAP-Seq(GSE60143)/Homer NDDCAASTTGHHNWW 1e0 -1.584e+00 1.0000 617.0 15.43% 588.3 14.75% +ATHB20(Homeobox)/colamp-ATHB20-DAP-Seq(GSE60143)/Homer CAATHATT 1e0 -1.584e+00 1.0000 443.0 11.08% 418.4 10.49% +Hoxa13(Homeobox)/ChickenMSG-Hoxa13.Flag-ChIP-Seq(GSE86088)/Homer CYHATAAAAN 1e0 -1.564e+00 1.0000 2198.0 54.96% 2155.4 54.04% +bHLH80(bHLH)/col-bHLH80-DAP-Seq(GSE60143)/Homer NNNNDCAASTTGHNN 1e0 -1.549e+00 1.0000 658.0 16.45% 629.3 15.78% +Oct2(POU,Homeobox)/Bcell-Oct2-ChIP-Seq(GSE21512)/Homer ATATGCAAAT 1e0 -1.549e+00 1.0000 181.0 4.53% 165.7 4.15% +SEP3(MADS)/Arabidoposis-Flower-Sep3-ChIP-Seq/Homer CCAAAAAGGG 1e0 -1.548e+00 1.0000 833.0 20.83% 801.2 20.08% +TR4(NR),DR1/Hela-TR4-ChIP-Seq(GSE24685)/Homer GAGGTCAAAGGTCA 1e0 -1.543e+00 1.0000 15.0 0.38% 10.3 0.26% +OCT:OCT(POU,Homeobox)/NPC-OCT6-ChIP-Seq(GSE43916)/Homer YATGCATATRCATRT 1e0 -1.534e+00 1.0000 32.0 0.80% 25.9 0.65% +ZNF165(Zf)/WHIM12-ZNF165-ChIP-Seq(GSE65937)/Homer AAGGKGRCGCAGGCA 1e0 -1.529e+00 1.0000 23.0 0.58% 17.6 0.44% +SPL14(SBP)/col-SPL14-DAP-Seq(GSE60143)/Homer NNWHTGTACGGAHNH 1e0 -1.517e+00 1.0000 594.0 14.85% 567.9 14.24% +Pax7(Paired,Homeobox)/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer TAATCAATTA 1e0 -1.514e+00 1.0000 105.0 2.63% 93.5 2.34% +CEBP:AP1(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer DRTGTTGCAA 1e0 -1.506e+00 1.0000 661.0 16.53% 633.1 15.87% +Lhx3(Homeobox)/Neuron-Lhx3-ChIP-Seq(GSE31456)/Homer ADBTAATTAR 1e0 -1.483e+00 1.0000 2032.0 50.81% 1992.4 49.95% +At3g60580(C2H2)/col-At3g60580-DAP-Seq(GSE60143)/Homer WTTYTACT 1e0 -1.483e+00 1.0000 3555.0 88.90% 3523.5 88.33% +ATHB33(ZFHD)/col-ATHB33-DAP-Seq(GSE60143)/Homer NGTRATTAAK 1e0 -1.482e+00 1.0000 1773.0 44.34% 1734.1 43.47% +PABPC1(?)/MEL-PABC1-CLIP-Seq(GSE69755)/Homer HAATAAAGNN 1e0 -1.477e+00 1.0000 1346.0 33.66% 1310.3 32.85% +AT5G45580(G2like)/colamp-AT5G45580-DAP-Seq(GSE60143)/Homer ADRGAATCTH 1e0 -1.475e+00 1.0000 1629.0 40.74% 1591.4 39.89% +PPARE(NR),DR1/3T3L1-Pparg-ChIP-Seq(GSE13511)/Homer TGACCTTTGCCCCA 1e0 -1.468e+00 1.0000 338.0 8.45% 318.3 7.98% +PAX6(Paired,Homeobox)/Forebrain-Pax6-ChIP-Seq(GSE66961)/Homer NGTGTTCAVTSAAGCGKAAA 1e0 -1.464e+00 1.0000 78.0 1.95% 68.7 1.72% +Zfp809(Zf)/ES-Zfp809-ChIP-Seq(GSE70799)/Homer GGGGCTYGKCTGGGA 1e0 -1.456e+00 1.0000 49.0 1.23% 41.9 1.05% +NFkB-p65(RHD)/GM12787-p65-ChIP-Seq(GSE19485)/Homer WGGGGATTTCCC 1e0 -1.453e+00 1.0000 278.0 6.95% 260.1 6.52% +Foxh1(Forkhead)/hESC-FOXH1-ChIP-Seq(GSE29422)/Homer NNTGTGGATTSS 1e0 -1.451e+00 1.0000 624.0 15.60% 599.0 15.02% +Oct11(POU,Homeobox)/NCIH1048-POU2F3-ChIP-seq(GSE115123)/Homer GATTTGCATA 1e0 -1.449e+00 1.0000 218.0 5.45% 202.7 5.08% +MYB121(MYB)/col-MYB121-DAP-Seq(GSE60143)/Homer YNTACCTAACWW 1e0 -1.448e+00 1.0000 477.0 11.93% 454.2 11.39% +At3g11280(MYBrelated)/col-At3g11280-DAP-Seq(GSE60143)/Homer GATAAGRT 1e0 -1.422e+00 1.0000 1209.0 30.23% 1176.4 29.49% +RARg(NR)/ES-RARg-ChIP-Seq(GSE30538)/Homer AGGTCAAGGTCA 1e0 -1.419e+00 1.0000 11.0 0.28% 7.1 0.18% +GT1(Trihelix)/col-GT1-DAP-Seq(GSE60143)/Homer TTAACCATGGTTAAD 1e0 -1.419e+00 1.0000 11.0 0.28% 7.8 0.20% +WRKY27(WRKY)/colamp-WRKY27-DAP-Seq(GSE60143)/Homer NHGTTGACYTWD 1e0 -1.412e+00 1.0000 811.0 20.28% 783.1 19.63% +Nur77(NR)/K562-NR4A1-ChIP-Seq(GSE31363)/Homer TGACCTTTNCNT 1e0 -1.403e+00 1.0000 130.0 3.25% 118.1 2.96% +At4g38000(C2C2dof)/col-At4g38000-DAP-Seq(GSE60143)/Homer WWWTWACTTTTT 1e0 -1.397e+00 1.0000 915.0 22.88% 886.1 22.21% +ATHB5(HB)/colamp-ATHB5-DAP-Seq(GSE60143)/Homer AATGATTG 1e0 -1.394e+00 1.0000 1007.0 25.18% 977.1 24.49% +Phox2b(Homeobox)/CLBGA-PHOX2B-ChIP-Seq(GSE90683)/Homer TTAATTNAATTA 1e0 -1.393e+00 1.0000 245.0 6.13% 229.8 5.76% +Nkx2.5(Homeobox)/HL1-Nkx2.5.biotin-ChIP-Seq(GSE21529)/Homer RRSCACTYAA 1e0 -1.389e+00 1.0000 1807.0 45.19% 1771.8 44.42% +SOC1(MADS)/Seedling-SOC1-ChIP-Seq(GSE45846)/Homer TWCCAWWTWTGG 1e0 -1.386e+00 1.0000 359.0 8.98% 340.8 8.54% +Six1(Homeobox)/Myoblast-Six1-ChIP-Chip(GSE20150)/Homer GKVTCADRTTWC 1e0 -1.382e+00 1.0000 251.0 6.28% 235.6 5.91% +Gli2(Zf)/GM2-Gli2-ChIP-Chip(GSE112702)/Homer YSTGGGTGGTCT 1e0 -1.377e+00 1.0000 93.0 2.33% 83.9 2.10% +BOS1(MYB)/col-BOS1-DAP-Seq(GSE60143)/Homer NNRCCTAACT 1e0 -1.376e+00 1.0000 1056.0 26.41% 1026.5 25.73% +LXRE(NR),DR4/RAW-LXRb.biotin-ChIP-Seq(GSE21512)/Homer RGGTTACTANAGGTCA 1e0 -1.364e+00 1.0000 44.0 1.10% 38.0 0.95% +At5g29000(G2like)/col-At5g29000-DAP-Seq(GSE60143)/Homer RGAATATTCYHH 1e0 -1.358e+00 1.0000 341.0 8.53% 323.8 8.12% +HRE(HSF)/HepG2-HSF1-ChIP-Seq(GSE31477)/Homer BSTTCTRGAABVTTCYAGAA 1e0 -1.357e+00 1.0000 60.0 1.50% 52.4 1.31% +MYB73(MYB)/col-MYB73-DAP-Seq(GSE60143)/Homer NNNNHAACNGHHDHN 1e0 -1.354e+00 1.0000 2298.0 57.46% 2262.7 56.72% +WRKY45(WRKY)/col-WRKY45-DAP-Seq(GSE60143)/Homer HNNNKTTGACTWWNH 1e0 -1.348e+00 1.0000 349.0 8.73% 331.3 8.31% +RFX(HTH)/K562-RFX3-ChIP-Seq(SRA012198)/Homer CGGTTGCCATGGCAAC 1e0 -1.339e+00 1.0000 33.0 0.83% 27.7 0.70% +VDR(NR),DR3/GM10855-VDR+vitD-ChIP-Seq(GSE22484)/Homer ARAGGTCANWGAGTTCANNN 1e0 -1.336e+00 1.0000 102.0 2.55% 92.6 2.32% +HIF2a(bHLH)/785_O-HIF2a-ChIP-Seq(GSE34871)/Homer GCACGTACCC 1e0 -1.336e+00 1.0000 821.0 20.53% 795.2 19.93% +Ets1-distal(ETS)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer MACAGGAAGT 1e0 -1.335e+00 1.0000 151.0 3.78% 139.2 3.49% +MafF(bZIP)/HepG2-MafF-ChIP-Seq(GSE31477)/Homer HWWGTCAGCAWWTTT 1e0 -1.329e+00 1.0000 213.0 5.33% 199.9 5.01% +MYB70(MYB)/col-MYB70-DAP-Seq(GSE60143)/Homer WTAACNGTTA 1e0 -1.329e+00 1.0000 2220.0 55.51% 2185.1 54.78% +At3g04030(G2like)/col-At3g04030-DAP-Seq(GSE60143)/Homer DRGAATCT 1e0 -1.326e+00 1.0000 925.0 23.13% 898.0 22.51% +IRF8(IRF)/BMDM-IRF8-ChIP-Seq(GSE77884)/Homer GRAASTGAAAST 1e0 -1.323e+00 1.0000 129.0 3.23% 118.7 2.97% +TEAD2(TEA)/Py2T-Tead2-ChIP-Seq(GSE55709)/Homer CCWGGAATGY 1e0 -1.321e+00 1.0000 329.0 8.23% 312.4 7.83% +E2F(E2F)/Hela-CellCycle-Expression/Homer TTSGCGCGAAAA 1e0 -1.320e+00 1.0000 106.0 2.65% 96.4 2.42% +RXR(NR),DR1/3T3L1-RXR-ChIP-Seq(GSE13511)/Homer TAGGGCAAAGGTCA 1e0 -1.318e+00 1.0000 375.0 9.38% 357.8 8.97% +AT3G09735(S1Falike)/col-AT3G09735-DAP-Seq(GSE60143)/Homer TTCTAGAANMTTCTA 1e0 -1.310e+00 1.0000 297.0 7.43% 281.5 7.06% +COG1(C2C2dof)/col-COG1-DAP-Seq(GSE60143)/Homer DAAAAAGTGA 1e0 -1.309e+00 1.0000 1065.0 26.63% 1037.6 26.01% +Arnt:Ahr(bHLH)/MCF7-Arnt-ChIP-Seq(Lo_et_al.)/Homer TBGCACGCAA 1e0 -1.302e+00 1.0000 1088.0 27.21% 1060.2 26.58% +AGL95(ND)/col-AGL95-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -1.300e+00 1.0000 51.0 1.28% 44.6 1.12% +PRDM9(Zf)/Testis-DMC1-ChIP-Seq(GSE35498)/Homer ADGGYAGYAGCATCT 1e0 -1.299e+00 1.0000 196.0 4.90% 183.4 4.60% +HSF6(HSF)/col-HSF6-DAP-Seq(GSE60143)/Homer TTYTAGAAGCTTCTA 1e0 -1.296e+00 1.0000 138.0 3.45% 127.2 3.19% +WRKY11(WRKY)/col-WRKY11-DAP-Seq(GSE60143)/Homer SCGTTGACTTTN 1e0 -1.290e+00 1.0000 114.0 2.85% 104.6 2.62% +At5g47390(MYBrelated)/col-At5g47390-DAP-Seq(GSE60143)/Homer CTTATCCA 1e0 -1.285e+00 1.0000 1551.0 38.78% 1520.3 38.11% +PRDM14(Zf)/H1-PRDM14-ChIP-Seq(GSE22767)/Homer RGGTCTCTAACY 1e0 -1.282e+00 1.0000 319.0 7.98% 303.8 7.62% +Hoxc9(Homeobox)/Ainv15-Hoxc9-ChIP-Seq(GSE21812)/Homer GGCCATAAATCA 1e0 -1.275e+00 1.0000 529.0 13.23% 509.8 12.78% +AGL25(MADS)/colamp-AGL25-DAP-Seq(GSE60143)/Homer TTTCCATWTWTGGAA 1e0 -1.264e+00 1.0000 26.0 0.65% 21.8 0.55% +AT2G20110(CPP)/colamp-AT2G20110-DAP-Seq(GSE60143)/Homer ATTYAAATHY 1e0 -1.255e+00 1.0000 1146.0 28.66% 1119.9 28.07% +RAV1(RAV)/colamp-RAV1-DAP-Seq(GSE60143)/Homer TWWTTTCTGTTG 1e0 -1.255e+00 1.0000 444.0 11.10% 426.4 10.69% +AT3G58630(Trihelix)/col-AT3G58630-DAP-Seq(GSE60143)/Homer TCTCCGGCGA 1e0 -1.251e+00 1.0000 187.0 4.68% 175.2 4.39% +GATA(Zf),IR4/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer NAGATWNBNATCTNN 1e0 -1.250e+00 1.0000 78.0 1.95% 70.8 1.77% +Nkx3.1(Homeobox)/LNCaP-Nkx3.1-ChIP-Seq(GSE28264)/Homer AAGCACTTAA 1e0 -1.245e+00 1.0000 1859.0 46.49% 1828.3 45.83% +NFkB-p50,p52(RHD)/Monocyte-p50-ChIP-Chip(Schreiber_et_al.)/Homer GGGGGAATCCCC 1e0 -1.244e+00 1.0000 59.0 1.48% 52.8 1.32% +RBPJ:Ebox(?,bHLH)/Panc1-Rbpj1-ChIP-Seq(GSE47459)/Homer GGGRAARRGRMCAGMTG 1e0 -1.244e+00 1.0000 59.0 1.48% 52.8 1.32% +EMB1789(C3H)/col-EMB1789-DAP-Seq(GSE60143)/Homer TWTTTACCGYND 1e0 -1.238e+00 1.0000 524.0 13.10% 505.9 12.68% +AT3G25990(Trihelix)/colamp-AT3G25990-DAP-Seq(GSE60143)/Homer TTAACCATAG 1e0 -1.234e+00 1.0000 909.0 22.73% 885.3 22.19% +AT5G25475(ABI3VP1)/col-AT5G25475-DAP-Seq(GSE60143)/Homer RNNRNCAAGCADNDB 1e0 -1.232e+00 1.0000 826.0 20.66% 803.1 20.13% +RLR1?/SacCer-Promoters/Homer WTTTTCYYTTTT 1e0 -1.232e+00 1.0000 82.0 2.05% 74.9 1.88% +p53(p53)/mES-cMyc-ChIP-Seq(GSE11431)/Homer ACATGCCCGGGCAT 1e0 -1.231e+00 1.0000 8.0 0.20% 5.6 0.14% +AT4G27900(C2C2COlike)/col-AT4G27900-DAP-Seq(GSE60143)/Homer TCTCVACCGTTSATT 1e0 -1.231e+00 1.0000 8.0 0.20% 5.1 0.13% +LIN-15B(Zf)/cElegans-L3-LIN15B-ChIP-Seq(modEncode)/Homer CARTGGAGCGCRYTTGCATT 1e0 -1.231e+00 1.0000 8.0 0.20% 5.7 0.14% +AT4G37180(G2like)/col-AT4G37180-DAP-Seq(GSE60143)/Homer AGAATCTTNN 1e0 -1.230e+00 1.0000 1131.0 28.28% 1105.8 27.72% +CAMTA5(CAMTA)/col-CAMTA5-DAP-Seq(GSE60143)/Homer ACGCGTTTTANACRC 1e0 -1.226e+00 1.0000 759.0 18.98% 737.8 18.50% +IRF3(IRF)/BMDM-Irf3-ChIP-Seq(GSE67343)/Homer AGTTTCAKTTTC 1e0 -1.226e+00 1.0000 108.0 2.70% 99.0 2.48% +Zic3(Zf)/mES-Zic3-ChIP-Seq(GSE37889)/Homer GGCCYCCTGCTGDGH 1e0 -1.225e+00 1.0000 167.0 4.18% 156.3 3.92% +dHNF4(NR)/Fly-HNF4-ChIP-Seq(GSE73675)/Homer GGTCCAAAGTCCAMT 1e0 -1.223e+00 1.0000 29.0 0.73% 24.5 0.61% +Erra(NR)/HepG2-Erra-ChIP-Seq(GSE31477)/Homer CAAAGGTCAG 1e0 -1.223e+00 1.0000 1046.0 26.16% 1021.1 25.60% +Hand2(bHLH)/Mesoderm-Hand2-ChIP-Seq(GSE61475)/Homer TGACANARRCCAGRC 1e0 -1.221e+00 1.0000 169.0 4.23% 158.1 3.96% +SPL5(SBP)/colamp-SPL5-DAP-Seq(GSE60143)/Homer NNHGTACGGHNN 1e0 -1.216e+00 1.0000 1651.0 41.29% 1622.2 40.67% +WRKY46(WRKY)/colamp-WRKY46-DAP-Seq(GSE60143)/Homer AAAGTCAACGSN 1e0 -1.215e+00 1.0000 86.0 2.15% 78.4 1.97% +PTF1(TCP)/colamp-PTF1-DAP-Seq(GSE60143)/Homer RDDGGGACCACA 1e0 -1.215e+00 1.0000 64.0 1.60% 57.6 1.44% +AT1G44830(AP2EREBP)/col-AT1G44830-DAP-Seq(GSE60143)/Homer NCCACCGACA 1e0 -1.210e+00 1.0000 293.0 7.33% 279.2 7.00% +GATA3(Zf),DR8/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATSTNDNNDSAGATAASN 1e0 -1.210e+00 1.0000 65.0 1.63% 58.8 1.47% +KANADI1(Myb)/Seedling-KAN1-ChIP-Seq(GSE48081)/Homer ARGAATAWWN 1e0 -1.208e+00 1.0000 1515.0 37.88% 1487.4 37.29% +M1BP(Zf)/S2R+-M1BP-ChIP-Seq(GSE49842)/Homer CAGTGTGACCGT 1e0 -1.207e+00 1.0000 176.0 4.40% 165.2 4.14% +AT1G77200(AP2EREBP)/colamp-AT1G77200-DAP-Seq(GSE60143)/Homer ACCGACAHWD 1e0 -1.205e+00 1.0000 1374.0 34.36% 1347.2 33.77% +WRKY18(WRKY)/col-WRKY18-DAP-Seq(GSE60143)/Homer NNNTTGACYWNNNNN 1e0 -1.203e+00 1.0000 1550.0 38.76% 1522.3 38.16% +DREB26(AP2EREBP)/col-DREB26-DAP-Seq(GSE60143)/Homer CCACCGACAH 1e0 -1.200e+00 1.0000 217.0 5.43% 205.3 5.15% +Brn2(POU,Homeobox)/NPC-Brn2-ChIP-Seq(GSE35496)/Homer ATGAATATTC 1e0 -1.200e+00 1.0000 67.0 1.68% 60.6 1.52% +Tgif1(Homeobox)/mES-Tgif1-ChIP-Seq(GSE55404)/Homer YTGWCADY 1e0 -1.196e+00 1.0000 2183.0 54.59% 2153.9 54.00% +AMYB(HTH)/Testes-AMYB-ChIP-Seq(GSE44588)/Homer TGGCAGTTGG 1e0 -1.196e+00 1.0000 1827.0 45.69% 1798.8 45.09% +Tcf21(bHLH)/ArterySmoothMuscle-Tcf21-ChIP-Seq(GSE61369)/Homer NAACAGCTGG 1e0 -1.195e+00 1.0000 356.0 8.90% 341.6 8.56% +ASHR1(ND)/col-ASHR1-DAP-Seq(GSE60143)/Homer NTGGTGAN 1e0 -1.193e+00 1.0000 846.0 21.16% 824.7 20.67% +SOL1(CPP)/colamp-SOL1-DAP-Seq(GSE60143)/Homer ATTTAAATHN 1e0 -1.190e+00 1.0000 1055.0 26.38% 1031.1 25.85% +At5g22890(C2H2)/col-At5g22890-DAP-Seq(GSE60143)/Homer NSAGGTKWTATCTGD 1e0 -1.189e+00 1.0000 32.0 0.80% 27.0 0.68% +AT5G59990(C2C2COlike)/colamp-AT5G59990-DAP-Seq(GSE60143)/Homer TCTCAACCGTTCATT 1e0 -1.188e+00 1.0000 49.0 1.23% 43.8 1.10% +YY1(Zf)/Promoter/Homer CAAGATGGCGGC 1e0 -1.179e+00 1.0000 33.0 0.83% 28.9 0.72% +GATA:SCL(Zf,bHLH)/Ter119-SCL-ChIP-Seq(GSE18720)/Homer CRGCTGBNGNSNNSAGATAA 1e0 -1.172e+00 1.0000 73.0 1.83% 66.6 1.67% +CUC1(NAC)/col-CUC1-DAP-Seq(GSE60143)/Homer TACTTGTNNNACAAG 1e0 -1.170e+00 1.0000 508.0 12.70% 491.1 12.31% +ISRE(IRF)/ThioMac-LPS-Expression(GSE23622)/Homer AGTTTCASTTTC 1e0 -1.167e+00 1.0000 20.0 0.50% 16.7 0.42% +FOXM1(Forkhead)/MCF7-FOXM1-ChIP-Seq(GSE72977)/Homer TRTTTACTTW 1e0 -1.166e+00 1.0000 660.0 16.50% 641.8 16.09% +At2g03500(G2like)/col-At2g03500-DAP-Seq(GSE60143)/Homer WWAGAATATTCT 1e0 -1.163e+00 1.0000 340.0 8.50% 326.6 8.19% +Pit1+1bp(Homeobox)/GCrat-Pit1-ChIP-Seq(GSE58009)/Homer ATGCATAATTCA 1e0 -1.156e+00 1.0000 250.0 6.25% 238.3 5.97% +AT5G22990(C2H2)/col-AT5G22990-DAP-Seq(GSE60143)/Homer WCGAHDTCGWHN 1e0 -1.149e+00 1.0000 619.0 15.48% 601.4 15.08% +At1g77640(AP2EREBP)/col-At1g77640-DAP-Seq(GSE60143)/Homer TGTCGGTGGA 1e0 -1.142e+00 1.0000 177.0 4.43% 167.6 4.20% +AT1G49560(G2like)/colamp-AT1G49560-DAP-Seq(GSE60143)/Homer GAWTCTNWDA 1e0 -1.141e+00 1.0000 1435.0 35.88% 1410.2 35.35% +WRKY50(WRKY)/col-WRKY50-DAP-Seq(GSE60143)/Homer NNTTGACTWNNGNNN 1e0 -1.141e+00 1.0000 912.0 22.81% 891.9 22.36% +WRKY31(WRKY)/colamp-WRKY31-DAP-Seq(GSE60143)/Homer NCGTTGACTWWK 1e0 -1.139e+00 1.0000 642.0 16.05% 624.2 15.65% +DEL2(E2FDP)/col-DEL2-DAP-Seq(GSE60143)/Homer WTTTCSCGCC 1e0 -1.139e+00 1.0000 430.0 10.75% 415.1 10.41% +HOXA2(Homeobox)/mES-Hoxa2-ChIP-Seq(Donaldson_et_al.)/Homer GYCATCMATCAT 1e0 -1.138e+00 1.0000 82.0 2.05% 75.9 1.90% +O2(bZIP)/Corn-O2-ChIP-Seq(GSE63991)/Homer GCTGACGTGGCA 1e0 -1.133e+00 1.0000 112.0 2.80% 104.3 2.61% +ARF16(ARF)/col-ARF16-DAP-Seq(GSE60143)/Homer ATTTTACGAT 1e0 -1.129e+00 1.0000 513.0 12.83% 497.7 12.48% +WRKY14(WRKY)/colamp-WRKY14-DAP-Seq(GSE60143)/Homer NCGTTGACTTTN 1e0 -1.128e+00 1.0000 447.0 11.18% 432.2 10.83% +At5g08520(MYBrelated)/colamp-At5g08520-DAP-Seq(GSE60143)/Homer ADBSTTATCY 1e0 -1.124e+00 1.0000 1377.0 34.43% 1353.9 33.94% +At1g22810(AP2EREBP)/colamp-At1g22810-DAP-Seq(GSE60143)/Homer BCACCGACANNN 1e0 -1.123e+00 1.0000 600.0 15.00% 583.3 14.62% +MYB30(MYB)/colamp-MYB30-DAP-Seq(GSE60143)/Homer AGGTAGTTGG 1e0 -1.120e+00 1.0000 880.0 22.01% 860.3 21.57% +WRKY47(WRKY)/colamp-WRKY47-DAP-Seq(GSE60143)/Homer WAAGTCAACGBT 1e0 -1.119e+00 1.0000 285.0 7.13% 273.5 6.86% +AGL6(MADS)/col-AGL6-DAP-Seq(GSE60143)/Homer TTWCCWWAWWDGGWA 1e0 -1.115e+00 1.0000 89.0 2.23% 82.0 2.06% +ZBTB18(Zf)/HEK293-ZBTB18.GFP-ChIP-Seq(GSE58341)/Homer AACATCTGGA 1e0 -1.113e+00 1.0000 196.0 4.90% 186.7 4.68% +PBX1(Homeobox)/MCF7-PBX1-ChIP-Seq(GSE28007)/Homer GSCTGTCACTCA 1e0 -1.113e+00 1.0000 24.0 0.60% 20.7 0.52% +Rfx2(HTH)/LoVo-RFX2-ChIP-Seq(GSE49402)/Homer GTTGCCATGGCAACM 1e0 -1.108e+00 1.0000 42.0 1.05% 37.5 0.94% +ZNF317(Zf)/HEK293-ZNF317.GFP-ChIP-Seq(GSE58341)/Homer GTCWGCTGTYYCTCT 1e0 -1.108e+00 1.0000 42.0 1.05% 37.7 0.95% +THRa(NR)/C17.2-THRa-ChIP-Seq(GSE38347)/Homer GGTCANYTGAGGWCA 1e0 -1.107e+00 1.0000 201.0 5.03% 191.8 4.81% +HSFB4(HSF)/col-HSFB4-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -1.097e+00 1.0000 12.0 0.30% 9.7 0.24% +GATA(Zf),IR3/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer NNNNNBAGATAWYATCTVHN 1e0 -1.095e+00 1.0000 129.0 3.23% 121.3 3.04% +Unknown1(NR/Ini-like)/Drosophila-Promoters/Homer MYGGTCACACTG 1e0 -1.095e+00 1.0000 129.0 3.23% 122.0 3.06% +DPL-1(E2F)/cElegans-Adult-ChIP-Seq(modEncode)/Homer TAGCGCGC 1e0 -1.093e+00 1.0000 1248.0 31.21% 1226.7 30.75% +HAT5(Homeobox)/colamp-HAT5-DAP-Seq(GSE60143)/Homer DCAATWATTG 1e0 -1.092e+00 1.0000 169.0 4.23% 160.2 4.02% +SFP1/SacCer-Promoters/Homer DDAAAAATTTTY 1e0 -1.091e+00 1.0000 26.0 0.65% 22.3 0.56% +bZIP69(bZIP)/col-bZIP69-DAP-Seq(GSE60143)/Homer GACAGCTGKCAW 1e0 -1.090e+00 1.0000 45.0 1.13% 40.3 1.01% +MYB57(MYB)/col-MYB57-DAP-Seq(GSE60143)/Homer TTACCTAACT 1e0 -1.090e+00 1.0000 681.0 17.03% 664.6 16.66% +ANAC017(NAC)/colamp-ANAC017-DAP-Seq(GSE60143)/Homer TMCTTGNNNNNCAAG 1e0 -1.090e+00 1.0000 98.0 2.45% 91.7 2.30% +WRKY30(WRKY)/colamp-WRKY30-DAP-Seq(GSE60143)/Homer CGTTGACTTN 1e0 -1.088e+00 1.0000 320.0 8.00% 308.3 7.73% +Pitx1(Homeobox)/Chicken-Pitx1-ChIP-Seq(GSE38910)/Homer TAATCCCN 1e0 -1.083e+00 1.0000 3347.0 83.70% 3323.7 83.32% +p63(p53)/Keratinocyte-p63-ChIP-Seq(GSE17611)/Homer NNDRCATGYCYNRRCATGYH 1e0 -1.082e+00 1.0000 221.0 5.53% 211.2 5.29% +dof43(C2C2dof)/colamp-dof43-DAP-Seq(GSE60143)/Homer NAAAAAGTDA 1e0 -1.082e+00 1.0000 1166.0 29.16% 1145.4 28.72% +TEAD4(TEA)/Tropoblast-Tead4-ChIP-Seq(GSE37350)/Homer CCWGGAATGY 1e0 -1.081e+00 1.0000 618.0 15.45% 602.3 15.10% +WRKY24(WRKY)/colamp-WRKY24-DAP-Seq(GSE60143)/Homer CGTTGACTWW 1e0 -1.073e+00 1.0000 834.0 20.86% 816.2 20.46% +AT3G42860(zfGRF)/col-AT3G42860-DAP-Seq(GSE60143)/Homer CGTTGACTTN 1e0 -1.068e+00 1.0000 288.0 7.20% 278.0 6.97% +Unknown4/Arabidopsis-Promoters/Homer CKTCKTCTTY 1e0 -1.064e+00 1.0000 574.0 14.35% 559.7 14.03% +bZIP42(bZIP)/colamp-bZIP42-DAP-Seq(GSE60143)/Homer GCCACGTCAGCA 1e0 -1.064e+00 1.0000 4.0 0.10% 2.8 0.07% +RORg(NR)/Liver-Rorc-ChIP-Seq(GSE101115)/Homer WAABTAGGTCAV 1e0 -1.063e+00 1.0000 77.0 1.93% 71.8 1.80% +ANAC079(NAC)/colamp-ANAC079-DAP-Seq(GSE60143)/Homer TACACGCAACCT 1e0 -1.056e+00 1.0000 789.0 19.73% 772.4 19.36% +ZNF264(Zf)/HEK293-ZNF264.GFP-ChIP-Seq(GSE58341)/Homer RGGGCACTAACY 1e0 -1.054e+00 1.0000 600.0 15.00% 585.9 14.69% +E2F1(E2F)/Hela-E2F1-ChIP-Seq(GSE22478)/Homer CWGGCGGGAA 1e0 -1.049e+00 1.0000 202.0 5.05% 193.1 4.84% +FOXA1(Forkhead)/MCF7-FOXA1-ChIP-Seq(GSE26831)/Homer WAAGTAAACA 1e0 -1.049e+00 1.0000 614.0 15.35% 599.0 15.02% +Initiator/Drosophila-Promoters/Homer NTCAGTYG 1e0 -1.040e+00 1.0000 1913.0 47.84% 1890.3 47.39% +WRKY65(WRKY)/colamp-WRKY65-DAP-Seq(GSE60143)/Homer AWWWAGTCAACG 1e0 -1.038e+00 1.0000 470.0 11.75% 457.3 11.46% +WRKY29(WRKY)/colamp-WRKY29-DAP-Seq(GSE60143)/Homer MGTTGACTTT 1e0 -1.032e+00 1.0000 1009.0 25.23% 991.5 24.86% +Pbx3(Homeobox)/GM12878-PBX3-ChIP-Seq(GSE32465)/Homer SCTGTCAMTCAN 1e0 -1.031e+00 1.0000 126.0 3.15% 120.0 3.01% +GRHL2(CP2)/HBE-GRHL2-ChIP-Seq(GSE46194)/Homer AAACYKGTTWDACMRGTTTB 1e0 -1.029e+00 1.0000 278.0 6.95% 268.3 6.73% +WRKY55(WRKY)/col-WRKY55-DAP-Seq(GSE60143)/Homer NCGTTGACTT 1e0 -1.028e+00 1.0000 1027.0 25.68% 1009.7 25.31% +HSFA6B(HSF)/colamp-HSFA6B-DAP-Seq(GSE60143)/Homer NTTCTAGAANHTTCT 1e0 -1.028e+00 1.0000 344.0 8.60% 333.8 8.37% +TCX2(CPP)/colamp-TCX2-DAP-Seq(GSE60143)/Homer NNWWTTYRAAHN 1e0 -1.027e+00 1.0000 1176.0 29.41% 1157.4 29.02% +Tbox:Smad(T-box,MAD)/ESCd5-Smad2_3-ChIP-Seq(GSE29422)/Homer AGGTGHCAGACA 1e0 -1.026e+00 1.0000 91.0 2.28% 85.1 2.13% +FOXA1(Forkhead)/LNCAP-FOXA1-ChIP-Seq(GSE27824)/Homer WAAGTAAACA 1e0 -1.023e+00 1.0000 798.0 19.95% 782.1 19.61% +Rfx1(HTH)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer KGTTGCCATGGCAA 1e0 -1.021e+00 1.0000 93.0 2.33% 87.4 2.19% +Brn1(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)/Homer TATGCWAATBAV 1e0 -1.018e+00 1.0000 233.0 5.83% 224.7 5.63% +MyoD(bHLH)/Myotube-MyoD-ChIP-Seq(GSE21614)/Homer RRCAGCTGYTSY 1e0 -1.012e+00 1.0000 240.0 6.00% 231.1 5.79% +ZNF669(Zf)/HEK293-ZNF669.GFP-ChIP-Seq(GSE58341)/Homer GARTGGTCATCGCCC 1e0 -9.988e-01 1.0000 68.0 1.70% 63.7 1.60% +RORa(NR)/Liver-Rora-ChIP-Seq(GSE101115)/Homer AAWCTAGGTCARDNN 1e0 -9.970e-01 1.0000 105.0 2.63% 99.2 2.49% +Hoxb4(Homeobox)/ES-Hoxb4-ChIP-Seq(GSE34014)/Homer TGATTRATGGCY 1e0 -9.931e-01 1.0000 204.0 5.10% 196.5 4.93% +NF1:FOXA1(CTF,Forkhead)/LNCAP-FOXA1-ChIP-Seq(GSE27824)/Homer WNTGTTTRYTTTGGCA 1e0 -9.922e-01 1.0000 19.0 0.48% 16.8 0.42% +bZIP44(bZIP)/colamp-bZIP44-DAP-Seq(GSE60143)/Homer NDTGCCACGTCAGCH 1e0 -9.922e-01 1.0000 19.0 0.48% 16.8 0.42% +Tlx?(NR)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer CTGGCAGSCTGCCA 1e0 -9.899e-01 1.0000 109.0 2.73% 103.3 2.59% +WRKY25(WRKY)/colamp-WRKY25-DAP-Seq(GSE60143)/Homer NNNNHRGTCAAMNNN 1e0 -9.861e-01 1.0000 1115.0 27.88% 1098.1 27.53% +AT2G01818(PLATZ)/col-AT2G01818-DAP-Seq(GSE60143)/Homer TCTAGAABSTTC 1e0 -9.832e-01 1.0000 113.0 2.83% 107.0 2.68% +VRN1(ABI3VP1)/col-VRN1-DAP-Seq(GSE60143)/Homer TTTTTTTTTT 1e0 -9.713e-01 1.0000 6.0 0.15% 4.9 0.12% +IRF1(IRF)/PBMC-IRF1-ChIP-Seq(GSE43036)/Homer GAAAGTGAAAGT 1e0 -9.704e-01 1.0000 46.0 1.15% 42.1 1.06% +Ap4(bHLH)/AML-Tfap4-ChIP-Seq(GSE45738)/Homer NAHCAGCTGD 1e0 -9.672e-01 1.0000 468.0 11.70% 457.3 11.46% +GATA3(Zf),DR4/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATGKDGAGATAAG 1e0 -9.648e-01 1.0000 82.0 2.05% 77.4 1.94% +ANAC045(NAC)/col-ANAC045-DAP-Seq(GSE60143)/Homer DNCKTVNNNNNNAMG 1e0 -9.638e-01 1.0000 2013.0 50.34% 1993.2 49.97% +AT1G19040(NAC)/col-AT1G19040-DAP-Seq(GSE60143)/Homer CTTGNDNHNCAAGYW 1e0 -9.627e-01 1.0000 83.0 2.08% 78.9 1.98% +RAP21(AP2EREBP)/colamp-RAP21-DAP-Seq(GSE60143)/Homer BCACCGACAHNN 1e0 -9.563e-01 1.0000 323.0 8.08% 314.9 7.89% +ERF38(AP2EREBP)/col-ERF38-DAP-Seq(GSE60143)/Homer CACCGACA 1e0 -9.552e-01 1.0000 720.0 18.00% 708.0 17.75% +DEAR5(AP2EREBP)/col-DEAR5-DAP-Seq(GSE60143)/Homer NDWTGTCGGTGRWDN 1e0 -9.550e-01 1.0000 252.0 6.30% 244.4 6.13% +MYB96(MYB)/colamp-MYB96-DAP-Seq(GSE60143)/Homer WGGTRGTTGG 1e0 -9.533e-01 1.0000 728.0 18.20% 715.8 17.94% +LXH9(Homeobox)/Hct116-LXH9.V5-ChIP-Seq(GSE116822)/Homer NGCTAATTAG 1e0 -9.510e-01 1.0000 1869.0 46.74% 1850.7 46.39% +MYB81(MYB)/col-MYB81-DAP-Seq(GSE60143)/Homer NWAACSGWTWNN 1e0 -9.504e-01 1.0000 2273.0 56.84% 2253.6 56.50% +TF3A(C2H2)/col-TF3A-DAP-Seq(GSE60143)/Homer NNDDGAGGAGGWNNN 1e0 -9.447e-01 1.0000 346.0 8.65% 337.1 8.45% +HRE(HSF)/Striatum-HSF1-ChIP-Seq(GSE38000)/Homer TTCTAGAABNTTCTA 1e0 -9.441e-01 1.0000 93.0 2.33% 88.4 2.22% +p53(p53)/Saos-p53-ChIP-Seq(GSE15780)/Homer RRCATGYCYRGRCATGYYYN 1e0 -9.440e-01 1.0000 54.0 1.35% 50.6 1.27% +p53(p53)/Saos-p53-ChIP-Seq/Homer RRCATGYCYRGRCATGYYYN 1e0 -9.440e-01 1.0000 54.0 1.35% 50.6 1.27% +TCP16(TCP)/colamp-TCP16-DAP-Seq(GSE60143)/Homer GTGGDCCYNNNNNNN 1e0 -9.414e-01 1.0000 353.0 8.83% 344.4 8.63% +AT1G04880(ARID)/colamp-AT1G04880-DAP-Seq(GSE60143)/Homer AAACTATATADTATA 1e0 -9.408e-01 1.0000 95.0 2.38% 91.0 2.28% +ATY13(MYB)/col-ATY13-DAP-Seq(GSE60143)/Homer YYYAACYRHH 1e0 -9.389e-01 1.0000 2929.0 73.24% 2909.2 72.93% +AT1G10720(BSD)/col-AT1G10720-DAP-Seq(GSE60143)/Homer TTCTAGAAKCTTCTA 1e0 -9.233e-01 1.0000 8.0 0.20% 6.3 0.16% +HAP3(CCAATHAP3)/col-HAP3-DAP-Seq(GSE60143)/Homer TGATGGAW 1e0 -9.195e-01 1.0000 235.0 5.88% 228.0 5.72% +SPL9(SBP)/colamp-SPL9-DAP-Seq(GSE60143)/Homer BTGTACTT 1e0 -9.157e-01 1.0000 2698.0 67.47% 2679.5 67.17% +SPL3(SBP)/colamp-SPL3-DAP-Seq(GSE60143)/Homer WDTTGTACGGAH 1e0 -9.070e-01 1.0000 182.0 4.55% 176.5 4.42% +OCT:OCT(POU,Homeobox,IR1)/NPC-Brn2-ChIP-Seq(GSE35496)/Homer ATGAATWATTCATGA 1e0 -9.066e-01 1.0000 9.0 0.23% 7.9 0.20% +dof42(C2C2dof)/col-dof42-DAP-Seq(GSE60143)/Homer AAAAAGGC 1e0 -9.056e-01 1.0000 558.0 13.95% 548.1 13.74% +SF1(NR)/H295R-Nr5a1-ChIP-Seq(GSE44220)/Homer CAAGGHCANV 1e0 -9.054e-01 1.0000 184.0 4.60% 178.9 4.48% +ZBTB33(Zf)/GM12878-ZBTB33-ChIP-Seq(GSE32465)/Homer GGVTCTCGCGAGAAC 1e0 -9.027e-01 1.0000 72.0 1.80% 68.5 1.72% +VIP1(bZIP)/col-VIP1-DAP-Seq(GSE60143)/Homer NTTGACAGCTGTCAN 1e0 -8.892e-01 1.0000 80.0 2.00% 76.7 1.92% +Tcfcp2l1(CP2)/mES-Tcfcp2l1-ChIP-Seq(GSE11431)/Homer NRAACCRGTTYRAACCRGYT 1e0 -8.778e-01 1.0000 88.0 2.20% 84.7 2.12% +WRKY3(WRKY)/col-WRKY3-DAP-Seq(GSE60143)/Homer NCKTTGACYDDN 1e0 -8.725e-01 1.0000 568.0 14.20% 559.2 14.02% +GATA20(C2C2gata)/colamp-GATA20-DAP-Seq(GSE60143)/Homer TNGATCNDNM 1e0 -8.702e-01 1.0000 2708.0 67.72% 2691.2 67.47% +HSFA6A(HSF)/col-HSFA6A-DAP-Seq(GSE60143)/Homer RGAAGNTTCTAGAAN 1e0 -8.629e-01 1.0000 13.0 0.33% 11.0 0.28% +SND2(NAC)/colamp-SND2-DAP-Seq(GSE60143)/Homer CTTVWNNNWBAAGNW 1e0 -8.614e-01 1.0000 620.0 15.50% 611.5 15.33% +Foxa2(Forkhead)/Liver-Foxa2-ChIP-Seq(GSE25694)/Homer CYTGTTTACWYW 1e0 -8.608e-01 1.0000 623.0 15.58% 614.2 15.40% +THRb(NR)/Liver-NR1A2-ChIP-Seq(GSE52613)/Homer TRAGGTCA 1e0 -8.594e-01 1.0000 2373.0 59.34% 2357.5 59.10% +LEP(AP2EREBP)/col-LEP-DAP-Seq(GSE60143)/Homer CDCCGCCGTC 1e0 -8.558e-01 1.0000 182.0 4.55% 177.5 4.45% +X-box(HTH)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer GGTTGCCATGGCAA 1e0 -8.529e-01 1.0000 52.0 1.30% 49.8 1.25% +Trl(Zf)/S2-GAGAfactor-ChIP-Seq(GSE40646)/Homer RGAGAGAG 1e0 -8.499e-01 1.0000 1251.0 31.28% 1239.3 31.07% +PU.1:IRF8(ETS:IRF)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer GGAAGTGAAAST 1e0 -8.492e-01 1.0000 54.0 1.35% 51.8 1.30% +At1g13300(G2like)/col-At1g13300-DAP-Seq(GSE60143)/Homer GAATCTWAGATTCYN 1e0 -8.486e-01 1.0000 15.0 0.38% 13.0 0.33% +Zfp57(Zf)/H1-ZFP57.HA-ChIP-Seq(GSE115387)/Homer NANTGCSGCA 1e0 -8.485e-01 1.0000 690.0 17.25% 681.4 17.08% +RORgt(NR)/EL4-RORgt.Flag-ChIP-Seq(GSE56019)/Homer AAYTAGGTCA 1e0 -8.459e-01 1.0000 118.0 2.95% 114.1 2.86% +RORgt(NR)/EL4-RORgt.Flag-ChIP-Seq(GSE56019)/Homer AAYTAGGTCA 1e0 -8.459e-01 1.0000 118.0 2.95% 114.1 2.86% +AT1G72740(MYBrelated)/colamp-AT1G72740-DAP-Seq(GSE60143)/Homer NNWWAMCCTAAHWNN 1e0 -8.428e-01 1.0000 1327.0 33.18% 1315.5 32.98% +TEAD1(TEAD)/HepG2-TEAD1-ChIP-Seq(Encode)/Homer CYRCATTCCA 1e0 -8.385e-01 1.0000 752.0 18.80% 743.2 18.63% +Mef2d(MADS)/Retina-Mef2d-ChIP-Seq(GSE61391)/Homer GCTATTTTTAGC 1e0 -8.364e-01 1.0000 130.0 3.25% 127.0 3.18% +TATA-Box(TBP)/Promoter/Homer CCTTTTAWAGSC 1e0 -8.332e-01 1.0000 1195.0 29.88% 1184.5 29.69% +GEI-11(Myb?)/cElegans-L4-GEI11-ChIP-Seq(modEncode)/Homer CCGACAYYTYACGGG 1e0 -8.319e-01 1.0000 65.0 1.63% 62.2 1.56% +At1g14580(C2H2)/colamp-At1g14580-DAP-Seq(GSE60143)/Homer CASAAAAMGACAAAA 1e0 -8.280e-01 1.0000 68.0 1.70% 65.6 1.64% +TCP17(TCP)/col-TCP17-DAP-Seq(GSE60143)/Homer GTGGTCCCCA 1e0 -8.276e-01 1.0000 19.0 0.48% 17.3 0.43% +CDM1(C3H)/colamp-CDM1-DAP-Seq(GSE60143)/Homer CCGAWAWTWTCGGAN 1e0 -8.274e-01 1.0000 358.0 8.95% 352.8 8.84% +MYB116(MYB)/colamp-MYB116-DAP-Seq(GSE60143)/Homer AGTTAGGCAN 1e0 -8.257e-01 1.0000 844.0 21.11% 835.5 20.94% +MYB3R4(MYB)/col-MYB3R4-DAP-Seq(GSE60143)/Homer AWWTAACCGTTR 1e0 -8.172e-01 1.0000 548.0 13.70% 541.1 13.56% +Rbpj1(?)/Panc1-Rbpj1-ChIP-Seq(GSE47459)/Homer HTTTCCCASG 1e0 -8.165e-01 1.0000 724.0 18.10% 716.5 17.96% +AT5G56840(MYBrelated)/colamp-AT5G56840-DAP-Seq(GSE60143)/Homer TGGATAAGGT 1e0 -8.119e-01 1.0000 1443.0 36.08% 1432.5 35.91% +AT1G12630(AP2EREBP)/colamp-AT1G12630-DAP-Seq(GSE60143)/Homer TGTCGGCA 1e0 -8.109e-01 1.0000 765.0 19.13% 757.7 18.99% +ANAC096(NAC)/colamp-ANAC096-DAP-Seq(GSE60143)/Homer TACTTGWNNNWCAAG 1e0 -8.101e-01 1.0000 589.0 14.73% 582.0 14.59% +CUC2(NAC)/colamp-CUC2-DAP-Seq(GSE60143)/Homer TRCKTGTNNNWCAMG 1e0 -8.064e-01 1.0000 446.0 11.15% 440.8 11.05% +HSFC1(HSF)/col-HSFC1-DAP-Seq(GSE60143)/Homer HTTCTAGAADCTTCT 1e0 -8.006e-01 1.0000 96.0 2.40% 93.3 2.34% +ZNF467(Zf)/HEK293-ZNF467.GFP-ChIP-Seq(GSE58341)/Homer TGGGGAAGGGCM 1e0 -8.004e-01 1.0000 197.0 4.93% 193.6 4.85% +AGL13(MADS)/col-AGL13-DAP-Seq(GSE60143)/Homer TWCCAWWTWTGGWAA 1e0 -7.989e-01 1.0000 28.0 0.70% 26.2 0.66% +FRS9(ND)/col-FRS9-DAP-Seq(GSE60143)/Homer RGAGAGAGAAAG 1e0 -7.989e-01 1.0000 28.0 0.70% 26.4 0.66% +ZNF341(Zf)/EBV-ZNF341-ChIP-Seq(GSE113194)/Homer GGAACAGCCG 1e0 -7.968e-01 1.0000 339.0 8.48% 334.9 8.39% +p73(p53)/Trachea-p73-ChIP-Seq(PRJNA310161)/Homer NRRRCAWGTCCDGRCATGYY 1e0 -7.966e-01 1.0000 29.0 0.73% 27.4 0.69% +HSF7(HSF)/colamp-HSF7-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -7.962e-01 1.0000 102.0 2.55% 99.7 2.50% +ZML2(C2C2gata)/col-ZML2-DAP-Seq(GSE60143)/Homer CATCATCATC 1e0 -7.935e-01 1.0000 106.0 2.65% 103.1 2.58% +TEAD3(TEA)/HepG2-TEAD3-ChIP-Seq(Encode)/Homer TRCATTCCAG 1e0 -7.887e-01 1.0000 960.0 24.01% 952.5 23.88% +At1g25550(G2like)/colamp-At1g25550-DAP-Seq(GSE60143)/Homer NAGATTCY 1e0 -7.885e-01 1.0000 962.0 24.06% 954.8 23.94% +AT2G20400(G2like)/colamp-AT2G20400-DAP-Seq(GSE60143)/Homer DNVGAATATTCBNHN 1e0 -7.880e-01 1.0000 232.0 5.80% 228.6 5.73% +Foxa3(Forkhead)/Liver-Foxa3-ChIP-Seq(GSE77670)/Homer BSNTGTTTACWYWGN 1e0 -7.855e-01 1.0000 240.0 6.00% 236.7 5.93% +At4g16750(AP2EREBP)/col-At4g16750-DAP-Seq(GSE60143)/Homer HACCGACAHA 1e0 -7.814e-01 1.0000 1298.0 32.46% 1289.8 32.33% +Pax8(Paired,Homeobox)/Thyroid-Pax8-ChIP-Seq(GSE26938)/Homer GTCATGCHTGRCTGS 1e0 -7.809e-01 1.0000 128.0 3.20% 125.1 3.14% +HSFA1E(HSF)/col-HSFA1E-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -7.802e-01 1.0000 38.0 0.95% 36.2 0.91% +Srebp1a(bHLH)/HepG2-Srebp1a-ChIP-Seq(GSE31477)/Homer RTCACSCCAY 1e0 -7.722e-01 1.0000 147.0 3.68% 144.2 3.61% +ANAC046(NAC)/colamp-ANAC046-DAP-Seq(GSE60143)/Homer ACACGYWAYC 1e0 -7.721e-01 1.0000 2504.0 62.62% 2492.4 62.48% +ANAC038(NAC)/col-ANAC038-DAP-Seq(GSE60143)/Homer ACACGTWAYC 1e0 -7.711e-01 1.0000 2526.0 63.17% 2514.4 63.03% +GLI3(Zf)/Limb-GLI3-ChIP-Chip(GSE11077)/Homer CGTGGGTGGTCC 1e0 -7.710e-01 1.0000 45.0 1.13% 44.0 1.10% +GATA4(C2C2gata)/col-GATA4-DAP-Seq(GSE60143)/Homer DDWTYAGATCTR 1e0 -7.710e-01 1.0000 906.0 22.66% 899.1 22.54% +TOD6?/SacCer-Promoters/Homer GCGATGAGMT 1e0 -7.702e-01 1.0000 152.0 3.80% 149.0 3.74% +NFkB-p65-Rel(RHD)/ThioMac-LPS-Expression(GSE23622)/Homer GGAAATTCCC 1e0 -7.677e-01 1.0000 48.0 1.20% 46.3 1.16% +WRKY15(WRKY)/col-WRKY15-DAP-Seq(GSE60143)/Homer VGTTGACTWW 1e0 -7.671e-01 1.0000 948.0 23.71% 942.0 23.61% +CArG(MADS)/PUER-Srf-ChIP-Seq(Sullivan_et_al.)/Homer CCATATATGGNM 1e0 -7.654e-01 1.0000 321.0 8.03% 317.5 7.96% +GBF6(bZIP)/colamp-GBF6-DAP-Seq(GSE60143)/Homer WWTGMCACGTCABCW 1e0 -7.642e-01 1.0000 327.0 8.18% 323.3 8.11% +At5g05790(MYBrelated)/col-At5g05790-DAP-Seq(GSE60143)/Homer AYCTTATC 1e0 -7.630e-01 1.0000 1268.0 31.71% 1260.6 31.60% +IRF2(IRF)/Erythroblas-IRF2-ChIP-Seq(GSE36985)/Homer GAAASYGAAASY 1e0 -7.619e-01 1.0000 54.0 1.35% 52.7 1.32% +NUC(C2H2)/col-NUC-DAP-Seq(GSE60143)/Homer HAVAAAACGACAAAA 1e0 -7.602e-01 1.0000 56.0 1.40% 54.8 1.37% +WRKY22(WRKY)/colamp-WRKY22-DAP-Seq(GSE60143)/Homer WWAAAGTCAACK 1e0 -7.592e-01 1.0000 556.0 13.90% 551.4 13.82% +Mef2a(MADS)/HL1-Mef2a.biotin-ChIP-Seq(GSE21529)/Homer CYAAAAATAG 1e0 -7.572e-01 1.0000 365.0 9.13% 361.7 9.07% +Bcl11a(Zf)/HSPC-BCL11A-ChIP-Seq(GSE104676)/Homer TYTGACCASWRG 1e0 -7.567e-01 1.0000 368.0 9.20% 364.8 9.14% +CELF2(RRM)/JSL1-CELF2-CLIP-Seq(GSE71264)/Homer RGTGTCAG 1e0 -7.541e-01 1.0000 202.0 5.05% 199.0 4.99% +BMYB(HTH)/Hela-BMYB-ChIP-Seq(GSE27030)/Homer NHAACBGYYV 1e0 -7.536e-01 1.0000 2079.0 51.99% 2069.9 51.89% +PPARa(NR),DR1/Liver-Ppara-ChIP-Seq(GSE47954)/Homer VNAGGKCAAAGGTCA 1e0 -7.520e-01 1.0000 397.0 9.93% 393.3 9.86% +bZIP52(bZIP)/colamp-bZIP52-DAP-Seq(GSE60143)/Homer NDNHCAGCTGTCANN 1e0 -7.510e-01 1.0000 873.0 21.83% 867.0 21.74% +SPL13(SBP)/col-SPL13-DAP-Seq(GSE60143)/Homer WAHTGTACGGAH 1e0 -7.504e-01 1.0000 407.0 10.18% 403.6 10.12% +ZNF519(Zf)/HEK293-ZNF519.GFP-ChIP-Seq(GSE58341)/Homer GAGSCCGAGC 1e0 -7.489e-01 1.0000 72.0 1.80% 70.3 1.76% +WRKY20(WRKY)/col-WRKY20-DAP-Seq(GSE60143)/Homer CKTTGACYWD 1e0 -7.449e-01 1.0000 683.0 17.08% 678.9 17.02% +At4g31060(AP2EREBP)/colamp-At4g31060-DAP-Seq(GSE60143)/Homer CACCGACAAW 1e0 -7.446e-01 1.0000 686.0 17.15% 681.3 17.08% +WRKY26(WRKY)/colamp-WRKY26-DAP-Seq(GSE60143)/Homer CGTTGACTWDKN 1e0 -7.442e-01 1.0000 451.0 11.28% 447.1 11.21% +TBP3(MYBrelated)/col-TBP3-DAP-Seq(GSE60143)/Homer VYTAGGGCAN 1e0 -7.429e-01 1.0000 971.0 24.28% 965.9 24.21% +Pit1(Homeobox)/GCrat-Pit1-ChIP-Seq(GSE58009)/Homer ATGMATATDC 1e0 -7.398e-01 1.0000 1012.0 25.31% 1006.9 25.24% +FHY3(FAR1)/Arabidopsis-FHY3-ChIP-Seq(GSE30711)/Homer HHCACGCGCBTN 1e0 -7.366e-01 1.0000 513.0 12.83% 509.6 12.78% +ZBTB12(Zf)/HEK293-ZBTB12.GFP-ChIP-Seq(GSE58341)/Homer NGNTCTAGAACCNGV 1e0 -7.336e-01 1.0000 302.0 7.55% 299.4 7.51% +E2F7(E2F)/Hela-E2F7-ChIP-Seq(GSE32673)/Homer VDTTTCCCGCCA 1e0 -7.287e-01 1.0000 121.0 3.03% 119.3 2.99% +Dorsal(RHD)/Embryo-dl-ChIP-Seq(GSE65441)/Homer GGGAAAAMCCCG 1e0 -7.287e-01 1.0000 121.0 3.03% 119.8 3.00% +MYB3R1(MYB)/col-MYB3R1-DAP-Seq(GSE60143)/Homer WWDTDACCGTTR 1e0 -7.255e-01 1.0000 912.0 22.81% 907.9 22.76% +GRF9(GRF)/colamp-GRF9-DAP-Seq(GSE60143)/Homer NWCTGACANNNNNNN 1e0 -7.241e-01 1.0000 638.0 15.95% 634.9 15.92% +ANAC075(NAC)/col-ANAC075-DAP-Seq(GSE60143)/Homer CTTSWWNWWSAAGYT 1e0 -7.236e-01 1.0000 373.0 9.33% 370.8 9.29% +ZNF7(Zf)/HepG2-ZNF7.Flag-ChIP-Seq(Encode)/Homer CTGCCWVCTTTTRTA 1e0 -7.221e-01 1.0000 385.0 9.63% 382.2 9.58% +At1g19000(MYBrelated)/colamp-At1g19000-DAP-Seq(GSE60143)/Homer WWTGGATAADDT 1e0 -7.214e-01 1.0000 969.0 24.23% 964.7 24.18% +WRKY42(WRKY)/colamp-WRKY42-DAP-Seq(GSE60143)/Homer NAAAGTCAACGN 1e0 -7.204e-01 1.0000 400.0 10.00% 397.2 9.96% +ESE3(AP2EREBP)/col-ESE3-DAP-Seq(GSE60143)/Homer GACGGTGG 1e0 -7.185e-01 1.0000 1338.0 33.46% 1332.4 33.40% +TINY(AP2EREBP)/col-TINY-DAP-Seq(GSE60143)/Homer NNCACCGACA 1e0 -7.185e-01 1.0000 417.0 10.43% 414.6 10.39% +GATA11(C2C2gata)/col-GATA11-DAP-Seq(GSE60143)/Homer DDHYYAGATCTR 1e0 -7.174e-01 1.0000 427.0 10.68% 424.1 10.63% +AT4G00250(GeBP)/col-AT4G00250-DAP-Seq(GSE60143)/Homer WDTGGATAAKRT 1e0 -7.173e-01 1.0000 718.0 17.95% 714.8 17.92% +MYB(HTH)/ERMYB-Myb-ChIPSeq(GSE22095)/Homer GGCVGTTR 1e0 -7.141e-01 1.0000 2501.0 62.54% 2492.4 62.48% +AT1G24250(Orphan)/col-AT1G24250-DAP-Seq(GSE60143)/Homer KTDGTTGGTDGTTGG 1e0 -7.135e-01 1.0000 190.0 4.75% 188.2 4.72% +GATA15(C2C2gata)/col-GATA15-DAP-Seq(GSE60143)/Homer KATGATCA 1e0 -7.134e-01 1.0000 1776.0 44.41% 1769.1 44.35% +GT3a(Trihelix)/col-GT3a-DAP-Seq(GSE60143)/Homer WNACACGTGTYWWAW 1e0 -7.091e-01 1.0000 218.0 5.45% 216.8 5.44% +REB1/SacCer-Promoters/Homer KCCGGGTAAYRR 1e0 -7.077e-01 1.0000 228.0 5.70% 226.3 5.67% +ZNF652/HepG2-ZNF652.Flag-ChIP-Seq(Encode)/Homer TTAACCCTTTVNKKN 1e0 -7.074e-01 1.0000 230.0 5.75% 228.7 5.73% +ATHB7(Homeobox)/col-ATHB7-DAP-Seq(GSE60143)/Homer AATGATTG 1e0 -7.073e-01 1.0000 856.0 21.41% 852.8 21.38% +WRKY75(WRKY)/col-WRKY75-DAP-Seq(GSE60143)/Homer CGTTGACTWW 1e0 -7.048e-01 1.0000 895.0 22.38% 891.2 22.34% +STOP1(C2H2)/colamp-STOP1-DAP-Seq(GSE60143)/Homer DTATCTGGKGRAGGT 1e0 -7.026e-01 1.0000 268.0 6.70% 266.9 6.69% +Gata4(Zf)/Heart-Gata4-ChIP-Seq(GSE35151)/Homer NBWGATAAGR 1e0 -7.012e-01 1.0000 1301.0 32.53% 1296.8 32.51% +HIF-1a(bHLH)/MCF7-HIF1a-ChIP-Seq(GSE28352)/Homer TACGTGCV 1e0 -6.978e-01 1.0000 657.0 16.43% 655.0 16.42% +DUX(Homeobox)/C2C12-Dux-ChIP-Seq(GSE87279)/Homer BCWGATTCAATCAAN 1e0 -6.918e-01 1.0000 1.0 0.03% 0.0 0.00% +ZNF189(Zf)/HEK293-ZNF189.GFP-ChIP-Seq(GSE58341)/Homer TGGAACAGMA 1e0 -6.913e-01 1.0000 386.0 9.65% 384.6 9.64% +CTCF-SatelliteElement(Zf?)/CD4+-CTCF-ChIP-Seq(Barski_et_al.)/Homer TGCAGTTCCMVNWRTGGCCA 1e0 -6.911e-01 1.0000 2.0 0.05% 2.0 0.05% +DEL1(E2FDP)/colamp-DEL1-DAP-Seq(GSE60143)/Homer TTCCCGCCAA 1e0 -6.911e-01 1.0000 2.0 0.05% 1.6 0.04% +AtGRF6(GRF)/col-AtGRF6-DAP-Seq(GSE60143)/Homer NTGTCAGADNNNNNN 1e0 -6.907e-01 1.0000 1136.0 28.41% 1132.5 28.39% +RAR:RXR(NR),DR5/ES-RAR-ChIP-Seq(GSE56893)/Homer RGGTCADNNAGAGGTCAV 1e0 -6.888e-01 1.0000 8.0 0.20% 7.7 0.19% +ZNF768(Zf)/Rajj-ZNF768-ChIP-Seq(GSE111879)/Homer RHHCAGAGAGGB 1e0 -6.888e-01 1.0000 8.0 0.20% 7.6 0.19% +Smad2(MAD)/ES-SMAD2-ChIP-Seq(GSE29422)/Homer CTGTCTGG 1e0 -6.877e-01 1.0000 1192.0 29.81% 1188.2 29.79% +WRKY33(WRKY)/col-WRKY33-DAP-Seq(GSE60143)/Homer CGTTGACYAW 1e0 -6.874e-01 1.0000 822.0 20.56% 819.2 20.54% +AT1G23810(Orphan)/col-AT1G23810-DAP-Seq(GSE60143)/Homer TTCTAGAAGSTTCTA 1e0 -6.872e-01 1.0000 15.0 0.38% 14.4 0.36% +GFX(?)/Promoter/Homer ATTCTCGCGAGA 1e0 -6.859e-01 1.0000 22.0 0.55% 21.5 0.54% +Unknown3/Drosophila-Promoters/Homer ACVAKCTGGCAGCGC 1e0 -6.850e-01 1.0000 28.0 0.70% 27.9 0.70% +HSFB3(HSF)/colamp-HSFB3-DAP-Seq(GSE60143)/Homer TTCTAGAAGMTTHTW 1e0 -6.845e-01 1.0000 31.0 0.78% 30.2 0.76% +PU.1-IRF(ETS:IRF)/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer MGGAAGTGAAAC 1e0 -6.838e-01 1.0000 489.0 12.23% 487.6 12.22% +HSF21(HSF)/col-HSF21-DAP-Seq(GSE60143)/Homer CTTCTAGAAGMTTYW 1e0 -6.818e-01 1.0000 53.0 1.33% 52.4 1.31% +IDD2(C2H2)/colamp-IDD2-DAP-Seq(GSE60143)/Homer HAVAAAAMGACAAAA 1e0 -6.803e-01 1.0000 68.0 1.70% 67.7 1.70% +Srebp2(bHLH)/HepG2-Srebp2-ChIP-Seq(GSE31477)/Homer CGGTCACSCCAC 1e0 -6.788e-01 1.0000 85.0 2.13% 84.5 2.12% +BZR1(BZR)/col-BZR1-DAP-Seq(GSE60143)/Homer NNCRCACGTGCG 1e0 -6.785e-01 1.0000 89.0 2.23% 88.7 2.22% +Six2(Homeobox)/NephronProgenitor-Six2-ChIP-Seq(GSE39837)/Homer GWAAYHTGAKMC 1e0 -6.762e-01 1.0000 1031.0 25.78% 1028.4 25.78% +TRP2(MYBrelated)/colamp-TRP2-DAP-Seq(GSE60143)/Homer TAAACCCT 1e0 -6.760e-01 1.0000 120.0 3.00% 119.3 2.99% +OCT:OCT-short(POU,Homeobox)/NPC-OCT6-ChIP-Seq(GSE43916)/Homer ATGCATWATGCATRW 1e0 -6.753e-01 1.0000 630.0 15.75% 629.0 15.77% +STZ(C2H2)/colamp-STZ-DAP-Seq(GSE60143)/Homer HNBTCACT 1e0 -6.742e-01 1.0000 3524.0 88.12% 3514.3 88.10% +MafB(bZIP)/BMM-Mafb-ChIP-Seq(GSE75722)/Homer WNTGCTGASTCAGCANWTTY 1e0 -6.713e-01 1.0000 193.0 4.83% 192.2 4.82% +PRDM1(Zf)/Hela-PRDM1-ChIP-Seq(GSE31477)/Homer ACTTTCACTTTC 1e0 -6.697e-01 1.0000 221.0 5.53% 220.9 5.54% +SND3(NAC)/col-SND3-DAP-Seq(GSE60143)/Homer CTTNHNNNDNAAGNH 1e0 -6.688e-01 1.0000 757.0 18.93% 755.1 18.93% +MYB77(MYB)/col-MYB77-DAP-Seq(GSE60143)/Homer NYAACBGYMC 1e0 -6.683e-01 1.0000 1967.0 49.19% 1963.0 49.21% +HOXA1(Homeobox)/mES-Hoxa1-ChIP-Seq(SRP084292)/Homer TGATKGATGR 1e0 -6.682e-01 1.0000 249.0 6.23% 248.8 6.24% +Oct6(POU,Homeobox)/NPC-Pou3f1-ChIP-Seq(GSE35496)/Homer WATGCAAATGAG 1e0 -6.675e-01 1.0000 262.0 6.55% 261.6 6.56% +GAGA-repeat/Arabidopsis-Promoters/Homer CTCTCTCTCY 1e0 -6.623e-01 1.0000 370.0 9.25% 369.6 9.27% +bHLH10(bHLH)/colamp-bHLH10-DAP-Seq(GSE60143)/Homer YACCGACA 1e0 -6.581e-01 1.0000 467.0 11.68% 466.2 11.69% +AT3G60490(AP2EREBP)/colamp-AT3G60490-DAP-Seq(GSE60143)/Homer NNRCCGACANNNNNN 1e0 -6.576e-01 1.0000 477.0 11.93% 476.5 11.95% +Rap210(AP2EREBP)/col-Rap210-DAP-Seq(GSE60143)/Homer TGTCGGCA 1e0 -6.569e-01 1.0000 1019.0 25.48% 1017.7 25.51% +NFAT(RHD)/Jurkat-NFATC1-ChIP-Seq(Jolma_et_al.)/Homer ATTTTCCATT 1e0 -6.541e-01 1.0000 565.0 14.13% 564.7 14.16% +At1g74840(MYBrelated)/col100-At1g74840-DAP-Seq(GSE60143)/Homer YHTTATCCAWWT 1e0 -6.437e-01 1.0000 842.0 21.06% 841.2 21.09% +Knotted(Homeobox)/Corn-KN1-ChIP-Seq(GSE39161)/Homer GAYGNGACRGGN 1e0 -6.403e-01 1.0000 1421.0 35.53% 1419.9 35.60% +NTM1(NAC)/col-NTM1-DAP-Seq(GSE60143)/Homer ACTTRTARAASAAGT 1e0 -6.331e-01 1.0000 332.0 8.30% 332.2 8.33% +EBF2(EBF)/BrownAdipose-EBF2-ChIP-Seq(GSE97114)/Homer NABTCCCWDGGGAVH 1e0 -6.329e-01 1.0000 373.0 9.33% 373.8 9.37% +At2g44940(AP2EREBP)/colamp-At2g44940-DAP-Seq(GSE60143)/Homer NYACCGACAHNNNNN 1e0 -6.326e-01 1.0000 399.0 9.98% 399.8 10.02% +Rfx5(HTH)/GM12878-Rfx5-ChIP-Seq(GSE31477)/Homer SCCTAGCAACAG 1e0 -6.319e-01 1.0000 206.0 5.15% 206.4 5.17% +At4g18890(BZR)/col-At4g18890-DAP-Seq(GSE60143)/Homer NDBRCACGTGYR 1e0 -6.310e-01 1.0000 184.0 4.60% 184.3 4.62% +ABI5(bZIP)/col-ABI5-DAP-Seq(GSE60143)/Homer GCCACGTG 1e0 -6.306e-01 1.0000 526.0 13.15% 526.8 13.21% +Smad4(MAD)/ESC-SMAD4-ChIP-Seq(GSE29422)/Homer VBSYGTCTGG 1e0 -6.297e-01 1.0000 1232.0 30.81% 1231.9 30.88% +ANAC058(NAC)/col-ANAC058-DAP-Seq(GSE60143)/Homer TWCTTGTDNNACAAG 1e0 -6.296e-01 1.0000 573.0 14.33% 573.8 14.38% +RKD2(RWPRK)/colamp-RKD2-DAP-Seq(GSE60143)/Homer GACKTTTCRDCTTCC 1e0 -6.294e-01 1.0000 581.0 14.53% 581.1 14.57% +TATA-box/SacCer-Promoters/Homer BBHWTATATA 1e0 -6.283e-01 1.0000 635.0 15.88% 635.0 15.92% +ANAC028(NAC)/col-ANAC028-DAP-Seq(GSE60143)/Homer WRCTTGNNNNNCAAG 1e0 -6.281e-01 1.0000 644.0 16.10% 644.3 16.15% +FoxL2(Forkhead)/Ovary-FoxL2-ChIP-Seq(GSE60858)/Homer WWTRTAAACAVG 1e0 -6.277e-01 1.0000 658.0 16.45% 658.9 16.52% +AT3G16280(AP2EREBP)/colamp-AT3G16280-DAP-Seq(GSE60143)/Homer HCACCGACAHHDHHN 1e0 -6.267e-01 1.0000 703.0 17.58% 703.9 17.65% +Gata1(Zf)/K562-GATA1-ChIP-Seq(GSE18829)/Homer SAGATAAGRV 1e0 -6.259e-01 1.0000 733.0 18.33% 733.1 18.38% +WRKY6(WRKY)/colamp-WRKY6-DAP-Seq(GSE60143)/Homer NCGTTGACTWWD 1e0 -6.247e-01 1.0000 781.0 19.53% 781.3 19.59% +RAP211(AP2EREBP)/colamp-RAP211-DAP-Seq(GSE60143)/Homer RGCCGGCYWW 1e0 -6.207e-01 1.0000 1891.0 47.29% 1889.9 47.38% +TATA-box/Drosophila-Promoters/Homer CTATAAAAGCSV 1e0 -6.187e-01 1.0000 81.0 2.03% 81.1 2.03% +ANAC050(NAC)/colamp-ANAC050-DAP-Seq(GSE60143)/Homer WNCTTGNNNNNCAAG 1e0 -6.062e-01 1.0000 507.0 12.68% 508.3 12.74% +DREB2(AP2EREBP)/col-DREB2-DAP-Seq(GSE60143)/Homer TMACCGACATWA 1e0 -6.053e-01 1.0000 683.0 17.08% 684.3 17.15% +CBF2(AP2EREBP)/colamp-CBF2-DAP-Seq(GSE60143)/Homer YBRCCGACATNNNNN 1e0 -6.029e-01 1.0000 850.0 21.26% 851.2 21.34% +E2F6(E2F)/Hela-E2F6-ChIP-Seq(GSE31477)/Homer GGCGGGAARN 1e0 -5.997e-01 1.0000 260.0 6.50% 261.1 6.55% +ANAC062(NAC)/colamp-ANAC062-DAP-Seq(GSE60143)/Homer TACTTANTNWNYAAG 1e0 -5.993e-01 1.0000 255.0 6.38% 256.9 6.44% +Chop(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer ATTGCATCAT 1e0 -5.971e-01 1.0000 228.0 5.70% 229.5 5.75% +Brachyury(T-box)/Mesoendoderm-Brachyury-ChIP-exo(GSE54963)/Homer ANTTMRCASBNNNGTGYKAAN 1e0 -5.969e-01 1.0000 226.0 5.65% 227.5 5.70% +ANAC070(NAC)/colamp-ANAC070-DAP-Seq(GSE60143)/Homer CTTRHDNHNBAAGHW 1e0 -5.940e-01 1.0000 1242.0 31.06% 1243.9 31.18% +NFE2L2(bZIP)/HepG2-NFE2L2-ChIP-Seq(Encode)/Homer AWWWTGCTGAGTCAT 1e0 -5.888e-01 1.0000 31.0 0.78% 31.7 0.80% +GATA12(C2C2gata)/col-GATA12-DAP-Seq(GSE60143)/Homer YAGATCTRAW 1e0 -5.838e-01 1.0000 631.0 15.78% 633.2 15.87% +DDF1(AP2EREBP)/col-DDF1-DAP-Seq(GSE60143)/Homer GCCGACAT 1e0 -5.837e-01 1.0000 804.0 20.11% 806.0 20.21% +NF1(CTF)/LNCAP-NF1-ChIP-Seq(Unpublished)/Homer CYTGGCABNSTGCCAR 1e0 -5.818e-01 1.0000 131.0 3.28% 132.6 3.32% +PSE(SNAPc)/K562-mStart-Seq/Homer WAVTCACCMTAASYDAAAAG 1e0 -5.817e-01 1.0000 489.0 12.23% 491.6 12.32% +ETS:E-box(ETS,bHLH)/HPC7-Scl-ChIP-Seq(GSE22178)/Homer AGGAARCAGCTG 1e0 -5.795e-01 1.0000 25.0 0.63% 25.8 0.65% +Gfi1b(Zf)/HPC7-Gfi1b-ChIP-Seq(GSE22178)/Homer MAATCACTGC 1e0 -5.779e-01 1.0000 387.0 9.68% 389.2 9.76% +E-box/Drosophila-Promoters/Homer AACAGCTGTTHN 1e0 -5.740e-01 1.0000 106.0 2.65% 107.2 2.69% +TCP7(TCP)/col-TCP7-DAP-Seq(GSE60143)/Homer GTGGGSCCCACHHNN 1e0 -5.726e-01 1.0000 308.0 7.70% 310.4 7.78% +AGL15(MADS)/col-AGL15-DAP-Seq(GSE60143)/Homer TTTCCHWATWDGGAA 1e0 -5.708e-01 1.0000 98.0 2.45% 99.1 2.48% +MYB27(MYB)/colamp-MYB27-DAP-Seq(GSE60143)/Homer TACCTAACWT 1e0 -5.674e-01 1.0000 258.0 6.45% 260.7 6.54% +Gata2(Zf)/K562-GATA2-ChIP-Seq(GSE18829)/Homer BBCTTATCTS 1e0 -5.641e-01 1.0000 779.0 19.48% 782.7 19.62% +FXR(NR),IR1/Liver-FXR-ChIP-Seq(Chong_et_al.)/Homer AGGTCANTGACCTB 1e0 -5.640e-01 1.0000 233.0 5.83% 235.9 5.91% +ANAC011(NAC)/col-ANAC011-DAP-Seq(GSE60143)/Homer TDCTTGYRNNDCAAG 1e0 -5.616e-01 1.0000 218.0 5.45% 221.0 5.54% +FoxD3(forkhead)/ZebrafishEmbryo-Foxd3.biotin-ChIP-seq(GSE106676)/Homer TGTTTAYTTAGC 1e0 -5.570e-01 1.0000 468.0 11.70% 471.6 11.82% +AREB3(bZIP)/col-AREB3-DAP-Seq(GSE60143)/Homer NKGMCACGTGDCMNN 1e0 -5.562e-01 1.0000 454.0 11.35% 457.1 11.46% +AT2G31460(REMB3)/col-AT2G31460-DAP-Seq(GSE60143)/Homer WNWARWDGAAATGAT 1e0 -5.543e-01 1.0000 181.0 4.53% 183.9 4.61% +At1g75490(AP2EREBP)/colamp-At1g75490-DAP-Seq(GSE60143)/Homer CACCGMCT 1e0 -5.541e-01 1.0000 2563.0 64.09% 2563.9 64.27% +MYB44(MYB)/colamp-MYB44-DAP-Seq(GSE60143)/Homer CVGTTWWKTCNGTTA 1e0 -5.538e-01 1.0000 68.0 1.70% 69.7 1.75% +FAR1(FAR1)/col-FAR1-DAP-Seq(GSE60143)/Homer TKNNNYYCACGCGCY 1e0 -5.523e-01 1.0000 173.0 4.33% 175.4 4.40% +GATA1(C2C2gata)/colamp-GATA1-DAP-Seq(GSE60143)/Homer DDWWYYAGATCTRRW 1e0 -5.517e-01 1.0000 386.0 9.65% 389.6 9.77% +HNF4a(NR),DR1/HepG2-HNF4a-ChIP-Seq(GSE25021)/Homer CARRGKBCAAAGTYCA 1e0 -5.485e-01 1.0000 159.0 3.98% 161.1 4.04% +At5g08330(TCP)/col-At5g08330-DAP-Seq(GSE60143)/Homer GGRCCCAC 1e0 -5.478e-01 1.0000 342.0 8.55% 345.2 8.65% +Unknown5/Drosophila-Promoters/Homer GCTGATAASV 1e0 -5.457e-01 1.0000 880.0 22.01% 884.3 22.17% +ZNF711(Zf)/SHSY5Y-ZNF711-ChIP-Seq(GSE20673)/Homer AGGCCTAG 1e0 -5.454e-01 1.0000 1083.0 27.08% 1087.6 27.27% +ANAC042(NAC)/col-ANAC042-DAP-Seq(GSE60143)/Homer CGTNDHNDHNACGKY 1e0 -5.447e-01 1.0000 1154.0 28.86% 1158.1 29.03% +ANAC103(NAC)/col-ANAC103-DAP-Seq(GSE60143)/Homer AACTTGNWNWNCAAG 1e0 -5.442e-01 1.0000 310.0 7.75% 313.2 7.85% +ERF115(AP2EREBP)/colamp-ERF115-DAP-Seq(GSE60143)/Homer WTKRCGGCGB 1e0 -5.438e-01 1.0000 1833.0 45.84% 1836.4 46.04% +Pknox1(Homeobox)/ES-Prep1-ChIP-Seq(GSE63282)/Homer SCTGTCAVTCAV 1e0 -5.427e-01 1.0000 141.0 3.53% 143.2 3.59% +MafA(bZIP)/Islet-MafA-ChIP-Seq(GSE30298)/Homer TGCTGACTCA 1e0 -5.360e-01 1.0000 506.0 12.65% 511.0 12.81% +bZIP53(bZIP)/colamp-bZIP53-DAP-Seq(GSE60143)/Homer NDNHSACGTGKMNNN 1e0 -5.359e-01 1.0000 504.0 12.60% 508.1 12.74% +JKD(C2H2)/col-JKD-DAP-Seq(GSE60143)/Homer TTTTGTCGTTTT 1e0 -5.347e-01 1.0000 121.0 3.03% 123.6 3.10% +bZIP48(bZIP)/colamp-bZIP48-DAP-Seq(GSE60143)/Homer DDWWKVTSACGTGGC 1e0 -5.282e-01 1.0000 403.0 10.08% 407.4 10.21% +bZIP3(bZIP)/col-bZIP3-DAP-Seq(GSE60143)/Homer DWKNHSACGTGGCAD 1e0 -5.195e-01 1.0000 594.0 14.85% 599.7 15.03% +PLT3(AP2EREBP)/col-PLT3-DAP-Seq(GSE60143)/Homer GCACGNWTHYCGAGG 1e0 -5.185e-01 1.0000 92.0 2.30% 94.8 2.38% +ANAC092(NAC)/colamp-ANAC092-DAP-Seq(GSE60143)/Homer WRCKTGWNNNWCAMG 1e0 -5.144e-01 1.0000 511.0 12.78% 516.8 12.96% +NTM2(NAC)/col-NTM2-DAP-Seq(GSE60143)/Homer CTTRTNNNAYAAGBH 1e0 -5.132e-01 1.0000 496.0 12.40% 501.5 12.57% +WRKY28(WRKY)/col-WRKY28-DAP-Seq(GSE60143)/Homer BGTTGACTWH 1e0 -5.121e-01 1.0000 1160.0 29.01% 1166.7 29.25% +MYB65(MYB)/colamp-MYB65-DAP-Seq(GSE60143)/Homer RACNGTTA 1e0 -5.116e-01 1.0000 1907.0 47.69% 1912.1 47.93% +TCFL2(HMG)/K562-TCF7L2-ChIP-Seq(GSE29196)/Homer ACWTCAAAGG 1e0 -5.110e-01 1.0000 34.0 0.85% 35.8 0.90% +ASL18(LOBAS2)/colamp-ASL18-DAP-Seq(GSE60143)/Homer CCGGAAAWTCMGGAR 1e0 -5.102e-01 1.0000 1382.0 34.56% 1388.2 34.80% +ANAC087(NAC)/col-ANAC087-DAP-Seq(GSE60143)/Homer WVCKTGHNNNWCAMG 1e0 -5.069e-01 1.0000 427.0 10.68% 432.7 10.85% +bZIP16(bZIP)/colamp-bZIP16-DAP-Seq(GSE60143)/Homer TGCCACGTGD 1e0 -5.041e-01 1.0000 402.0 10.05% 407.8 10.22% +MYB3R5(MYB)/col-MYB3R5-DAP-Seq(GSE60143)/Homer THYAACGGTHAWAWT 1e0 -5.041e-01 1.0000 245.0 6.13% 249.1 6.24% +ANAC020(NAC)/col-ANAC020-DAP-Seq(GSE60143)/Homer DVCKTGHNNNDCAAG 1e0 -5.026e-01 1.0000 650.0 16.25% 656.4 16.46% +bHLH157(bHLH)/col-bHLH157-DAP-Seq(GSE60143)/Homer KACACGTCTCTY 1e0 -4.993e-01 1.0000 365.0 9.13% 370.3 9.28% +PRDM10(Zf)/HEK293-PRDM10.eGFP-ChIP-Seq(Encode)/Homer TGGTACATTCCA 1e0 -4.951e-01 1.0000 338.0 8.45% 343.5 8.61% +GAGA-repeat/SacCer-Promoters/Homer CTYTCTYTCTCTCTC 1e0 -4.936e-01 1.0000 1502.0 37.56% 1509.9 37.85% +AGL16(MADS)/col-AGL16-DAP-Seq(GSE60143)/Homer TWCCHWATWDGGAAA 1e0 -4.908e-01 1.0000 62.0 1.55% 64.3 1.61% +CUC3(NAC)/col-CUC3-DAP-Seq(GSE60143)/Homer TRCKTGWNNNACAMG 1e0 -4.884e-01 1.0000 463.0 11.58% 469.2 11.76% +Foxf1(Forkhead)/Lung-Foxf1-ChIP-Seq(GSE77951)/Homer WWATRTAAACAN 1e0 -4.871e-01 1.0000 714.0 17.85% 721.7 18.09% +DDF2(AP2EREBP)/col-DDF2-DAP-Seq(GSE60143)/Homer GATGTCGRCR 1e0 -4.826e-01 1.0000 105.0 2.63% 108.5 2.72% +At2g33710(AP2EREBP)/colamp-At2g33710-DAP-Seq(GSE60143)/Homer WTKGCGGCKR 1e0 -4.809e-01 1.0000 1972.0 49.31% 1979.3 49.62% +Nrf2(bZIP)/Lymphoblast-Nrf2-ChIP-Seq(GSE37589)/Homer HTGCTGAGTCAT 1e0 -4.804e-01 1.0000 23.0 0.58% 24.8 0.62% +DEAR2(AP2EREBP)/colamp-DEAR2-DAP-Seq(GSE60143)/Homer HCACCGACAWHD 1e0 -4.785e-01 1.0000 1549.0 38.73% 1557.2 39.04% +ANAC083(NAC)/col-ANAC083-DAP-Seq(GSE60143)/Homer CKTRWNNNWYAMGTA 1e0 -4.783e-01 1.0000 952.0 23.81% 960.1 24.07% +PAX3:FKHR-fusion(Paired,Homeobox)/Rh4-PAX3:FKHR-ChIP-Seq(GSE19063)/Homer ACCRTGACTAATTNN 1e0 -4.782e-01 1.0000 256.0 6.40% 261.3 6.55% +NST1(NAC)/colamp-NST1-DAP-Seq(GSE60143)/Homer WRCTTRWWNWWYAAG 1e0 -4.776e-01 1.0000 922.0 23.06% 930.2 23.32% +SeqBias: GA-repeat GAGAGAGAGA 1e0 -4.771e-01 1.0000 2580.0 64.52% 2586.0 64.83% +Unknown1/Arabidopsis-Promoters/Homer RGGGTAWWWTHGTAA 1e0 -4.731e-01 1.0000 93.0 2.33% 96.9 2.43% +ANAC016(NAC)/col-ANAC016-DAP-Seq(GSE60143)/Homer WNCTTGNNNNNCAMG 1e0 -4.723e-01 1.0000 774.0 19.35% 782.0 19.60% +Pax7(Paired,Homeobox),longest/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer NTAATTDGCYAATTANNWWD 1e0 -4.683e-01 1.0000 20.0 0.50% 21.3 0.53% +DREF/Drosophila-Promoters/Homer AVYTATCGATAD 1e0 -4.677e-01 1.0000 87.0 2.18% 90.4 2.27% +Gata6(Zf)/HUG1N-GATA6-ChIP-Seq(GSE51936)/Homer YCTTATCTBN 1e0 -4.654e-01 1.0000 1102.0 27.56% 1111.6 27.87% +LBD23(LOBAS2)/colamp-LBD23-DAP-Seq(GSE60143)/Homer GCGNAWWWTNCGCYW 1e0 -4.653e-01 1.0000 1488.0 37.21% 1497.3 37.54% +Nanog(Homeobox)/mES-Nanog-ChIP-Seq(GSE11724)/Homer RGCCATTAAC 1e0 -4.631e-01 1.0000 3309.0 82.75% 3310.1 82.98% +GATA6(C2C2gata)/col200-GATA6-DAP-Seq(GSE60143)/Homer TAGATCTARAHH 1e0 -4.591e-01 1.0000 129.0 3.23% 133.8 3.35% +DEAR3(AP2EREBP)/colamp-DEAR3-DAP-Seq(GSE60143)/Homer BCACCGACAWNNNNN 1e0 -4.584e-01 1.0000 567.0 14.18% 575.3 14.42% +ZNF415(Zf)/HEK293-ZNF415.GFP-ChIP-Seq(GSE58341)/Homer GRTGMTRGAGCC 1e0 -4.576e-01 1.0000 280.0 7.00% 286.2 7.17% +HIF-1b(HLH)/T47D-HIF1b-ChIP-Seq(GSE59937)/Homer RTACGTGC 1e0 -4.575e-01 1.0000 1860.0 46.51% 1869.8 46.87% +GBF3(bZIP)/Arabidopsis-GBF3-ChIP-Seq(GSE80564)/Homer TGCCACGTSAYC 1e0 -4.523e-01 1.0000 366.0 9.15% 373.3 9.36% +SRS7(SRS)/colamp-SRS7-DAP-Seq(GSE60143)/Homer HATAGGTTTH 1e0 -4.491e-01 1.0000 3175.0 79.39% 3178.3 79.68% +T1ISRE(IRF)/ThioMac-Ifnb-Expression/Homer ACTTTCGTTTCT 1e0 -4.490e-01 1.0000 4.0 0.10% 4.6 0.12% +VND3(NAC)/colamp-VND3-DAP-Seq(GSE60143)/Homer TRCTTGWDNHWCAAG 1e0 -4.473e-01 1.0000 650.0 16.25% 659.3 16.53% +BAM8(BES1)/col-BAM8-DAP-Seq(GSE60143)/Homer NNWSACACGTGTSWN 1e0 -4.465e-01 1.0000 168.0 4.20% 173.9 4.36% +Duxbl(Homeobox)/NIH3T3-Duxbl.HA-ChIP-Seq(GSE119782)/Homer TAAYCYAATCAA 1e0 -4.449e-01 1.0000 67.0 1.68% 70.4 1.76% +MafK(bZIP)/C2C12-MafK-ChIP-Seq(GSE36030)/Homer GCTGASTCAGCA 1e0 -4.448e-01 1.0000 109.0 2.73% 113.1 2.84% +SeqBias: CG bias SSSSSSSSSS 1e0 -4.433e-01 1.0000 3984.0 99.62% 3975.0 99.65% +CBF3(AP2EREBP)/colamp-CBF3-DAP-Seq(GSE60143)/Homer YNRCCGACATNN 1e0 -4.408e-01 1.0000 808.0 20.21% 818.4 20.52% +Bach1(bZIP)/K562-Bach1-ChIP-Seq(GSE31477)/Homer AWWNTGCTGAGTCAT 1e0 -4.388e-01 1.0000 34.0 0.85% 36.9 0.92% +Mouse_Recombination_Hotspot(Zf)/Testis-DMC1-ChIP-Seq(GSE24438)/Homer ACTYKNATTCGTGNTACTTC 1e0 -4.388e-01 1.0000 34.0 0.85% 36.9 0.93% +GATA14(C2C2gata)/col-GATA14-DAP-Seq(GSE60143)/Homer AYCAGATCTG 1e0 -4.330e-01 1.0000 688.0 17.20% 698.4 17.51% +AT1G76870(Trihelix)/col-AT1G76870-DAP-Seq(GSE60143)/Homer AAAACCRGWW 1e0 -4.303e-01 1.0000 489.0 12.23% 498.2 12.49% +THRb(NR)/HepG2-THRb.Flag-ChIP-Seq(Encode)/Homer GGTCACCTGAGGTCA 1e0 -4.263e-01 1.0000 260.0 6.50% 267.1 6.70% +SPL11(SBP)/col100-SPL11-DAP-Seq(GSE60143)/Homer YTGTACTTBH 1e0 -4.249e-01 1.0000 808.0 20.21% 819.9 20.55% +CBF4(AP2EREBP)/colamp-CBF4-DAP-Seq(GSE60143)/Homer NRCCGACDWNNNNNN 1e0 -4.241e-01 1.0000 1229.0 30.73% 1241.4 31.12% +SPL15(SBP)/colamp-SPL15-DAP-Seq(GSE60143)/Homer WDWMMGTACADW 1e0 -4.226e-01 1.0000 2370.0 59.26% 2380.4 59.68% +IRF:BATF(IRF:bZIP)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer CTTTCANTATGACTV 1e0 -4.225e-01 1.0000 53.0 1.33% 56.6 1.42% +Atf4(bZIP)/MEF-Atf4-ChIP-Seq(GSE35681)/Homer MTGATGCAAT 1e0 -4.179e-01 1.0000 314.0 7.85% 322.9 8.10% +ANAC004(NAC)/colamp-ANAC004-DAP-Seq(GSE60143)/Homer WNCTTVYNNNRBAAG 1e0 -4.121e-01 1.0000 221.0 5.53% 228.7 5.73% +ANAC094(NAC)/col-ANAC094-DAP-Seq(GSE60143)/Homer DVCGTRNNNNNYACG 1e0 -4.115e-01 1.0000 841.0 21.03% 853.7 21.40% +ABR1(AP2EREBP)/colamp-ABR1-DAP-Seq(GSE60143)/Homer AAATGGCGGCGG 1e0 -4.112e-01 1.0000 1274.0 31.86% 1287.7 32.28% +Unknown2/Arabidopsis-Promoters/Homer AAACGACGTCGTTTT 1e0 -4.097e-01 1.0000 11.0 0.28% 12.8 0.32% +IRF4(IRF)/GM12878-IRF4-ChIP-Seq(GSE32465)/Homer ACTGAAACCA 1e0 -4.095e-01 1.0000 370.0 9.25% 379.2 9.51% +CTCF(Zf)/CD4+-CTCF-ChIP-Seq(Barski_et_al.)/Homer AYAGTGCCMYCTRGTGGCCA 1e0 -4.076e-01 1.0000 25.0 0.63% 27.6 0.69% +EBF(EBF)/proBcell-EBF-ChIP-Seq(GSE21978)/Homer DGTCCCYRGGGA 1e0 -4.050e-01 1.0000 72.0 1.80% 76.0 1.91% +PAX5(Paired,Homeobox),condensed/GM12878-PAX5-ChIP-Seq(GSE32465)/Homer GTCACGCTCSCTGM 1e0 -3.975e-01 1.0000 67.0 1.68% 71.0 1.78% +TEAD(TEA)/Fibroblast-PU.1-ChIP-Seq(Unpublished)/Homer YCWGGAATGY 1e0 -3.958e-01 1.0000 401.0 10.03% 411.0 10.30% +bZIP68(bZIP)/col-bZIP68-DAP-Seq(GSE60143)/Homer WGCCACGTGK 1e0 -3.958e-01 1.0000 507.0 12.68% 518.2 12.99% +VND4(NAC)/colamp-VND4-DAP-Seq(GSE60143)/Homer WRCTTGWANWWCAAG 1e0 -3.949e-01 1.0000 814.0 20.36% 827.3 20.74% +Unknown3/Arabidopsis-Promoters/Homer AYTAAACCGG 1e0 -3.948e-01 1.0000 501.0 12.53% 512.9 12.86% +ZML1(C2C2gata)/colamp-ZML1-DAP-Seq(GSE60143)/Homer ATCWYRACCGTTSRW 1e0 -3.931e-01 1.0000 40.0 1.00% 43.4 1.09% +GBF5(bZIP)/colamp-GBF5-DAP-Seq(GSE60143)/Homer WKNWSACGTGGCAWN 1e0 -3.910e-01 1.0000 379.0 9.48% 389.3 9.76% +SPL1(SBP)/colamp-SPL1-DAP-Seq(GSE60143)/Homer HYGTACDTWH 1e0 -3.888e-01 1.0000 2675.0 66.89% 2686.4 67.35% +Fox:Ebox(Forkhead,bHLH)/Panc1-Foxa2-ChIP-Seq(GSE47459)/Homer NNNVCTGWGYAAACASN 1e0 -3.882e-01 1.0000 577.0 14.43% 589.1 14.77% +CAMTA1(CAMTA)/col-CAMTA1-DAP-Seq(GSE60143)/Homer WWAACGCGTT 1e0 -3.858e-01 1.0000 1300.0 32.51% 1315.9 32.99% +STAT6(Stat)/CD4-Stat6-ChIP-Seq(GSE22104)/Homer ABTTCYYRRGAA 1e0 -3.846e-01 1.0000 279.0 6.98% 288.5 7.23% +CBF1(AP2EREBP)/colamp-CBF1-DAP-Seq(GSE60143)/Homer YRCCGACATN 1e0 -3.801e-01 1.0000 1068.0 26.71% 1083.8 27.17% +SMB(NAC)/colamp-SMB-DAP-Seq(GSE60143)/Homer CTTVNNNNDBAAGHW 1e0 -3.786e-01 1.0000 1030.0 25.76% 1046.0 26.22% +ZIM(C2C2gata)/col-ZIM-DAP-Seq(GSE60143)/Homer ATCSRACGGTYRAGA 1e0 -3.783e-01 1.0000 35.0 0.88% 38.3 0.96% +EGL-5(Homeobox)/cElegans-L3-EGL5-ChIP-Seq(modEncode)/Homer ATTTAATGGG 1e0 -3.748e-01 1.0000 1438.0 35.96% 1454.5 36.46% +ZNF41(Zf)/HEK293-ZNF41.GFP-ChIP-Seq(GSE58341)/Homer CCTCATGGTGYCYTWYTCCCTTGTG 1e0 -3.744e-01 1.0000 8.0 0.20% 9.7 0.24% +REST-NRSF(Zf)/Jurkat-NRSF-ChIP-Seq/Homer GGMGCTGTCCATGGTGCTGA 1e0 -3.731e-01 1.0000 2.0 0.05% 2.3 0.06% +DREB19(AP2EREBP)/colamp-DREB19-DAP-Seq(GSE60143)/Homer AATGTCGGTK 1e0 -3.647e-01 1.0000 796.0 19.90% 811.3 20.34% +OCT4-SOX2-TCF-NANOG(POU,Homeobox,HMG)/mES-Oct4-ChIP-Seq(GSE11431)/Homer ATTTGCATAACAATG 1e0 -3.639e-01 1.0000 73.0 1.83% 78.5 1.97% +SUT1?/SacCer-Promoters/Homer CCCCGCGC 1e0 -3.635e-01 1.0000 3636.0 90.92% 3638.8 91.22% +ERF7(AP2EREBP)/col-ERF7-DAP-Seq(GSE60143)/Homer ATGRCGGCGG 1e0 -3.629e-01 1.0000 1431.0 35.78% 1448.7 36.32% +MYB105(MYB)/colamp-MYB105-DAP-Seq(GSE60143)/Homer RATWCCGTTA 1e0 -3.613e-01 1.0000 1299.0 32.48% 1317.0 33.02% +At1g19210(AP2EREBP)/colamp-At1g19210-DAP-Seq(GSE60143)/Homer HCACCGACCAHN 1e0 -3.583e-01 1.0000 1902.0 47.56% 1919.6 48.12% +ANAC053(NAC)/colamp-ANAC053-DAP-Seq(GSE60143)/Homer TDCTTGNNNNNCAAG 1e0 -3.533e-01 1.0000 463.0 11.58% 476.9 11.96% +bZIP28(bZIP)/col-bZIP28-DAP-Seq(GSE60143)/Homer TGCCACGTSABH 1e0 -3.516e-01 1.0000 376.0 9.40% 388.7 9.75% +PU.1(ETS)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer AGAGGAAGTG 1e0 -3.470e-01 1.0000 193.0 4.83% 203.0 5.09% +EIN3(EIL)/col-EIN3-DAP-Seq(GSE60143)/Homer ARATTCAATGWATYT 1e0 -3.466e-01 1.0000 117.0 2.93% 124.4 3.12% +c-Jun-CRE(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer ATGACGTCATCY 1e0 -3.387e-01 1.0000 179.0 4.48% 188.8 4.73% +STAT1(Stat)/HelaS3-STAT1-ChIP-Seq(GSE12782)/Homer NATTTCCNGGAAAT 1e0 -3.383e-01 1.0000 141.0 3.53% 149.9 3.76% +ERF10(AP2EREBP)/col-ERF10-DAP-Seq(GSE60143)/Homer RTGGCGGCGG 1e0 -3.380e-01 1.0000 560.0 14.00% 576.0 14.44% +NAC2(NAC)/colamp-NAC2-DAP-Seq(GSE60143)/Homer TDCTTGNNNNNCAAG 1e0 -3.376e-01 1.0000 558.0 13.95% 573.1 14.37% +Stat3+il21(Stat)/CD4-Stat3-ChIP-Seq(GSE19198)/Homer SVYTTCCNGGAARB 1e0 -3.361e-01 1.0000 386.0 9.65% 399.4 10.01% +Bcl6(Zf)/Liver-Bcl6-ChIP-Seq(GSE31578)/Homer NNNCTTTCCAGGAAA 1e0 -3.359e-01 1.0000 547.0 13.68% 562.8 14.11% +Replumless(BLH)/Arabidopsis-RPL.GFP-ChIP-Seq(GSE78727)/Homer HGTCWHATCA 1e0 -3.354e-01 1.0000 1200.0 30.01% 1219.3 30.57% +MYB118(MYB)/colamp-MYB118-DAP-Seq(GSE60143)/Homer TAWCCGTTAC 1e0 -3.348e-01 1.0000 767.0 19.18% 784.6 19.67% +ANAC005(NAC)/col-ANAC005-DAP-Seq(GSE60143)/Homer WVCTTVTWNHABAAG 1e0 -3.315e-01 1.0000 308.0 7.70% 320.5 8.03% +AT4G18450(AP2EREBP)/col-AT4G18450-DAP-Seq(GSE60143)/Homer ATGGCGGCKG 1e0 -3.299e-01 1.0000 251.0 6.28% 262.8 6.59% +AT3G10030(Trihelix)/colamp-AT3G10030-DAP-Seq(GSE60143)/Homer GCCGTTAA 1e0 -3.297e-01 1.0000 1524.0 38.11% 1544.6 38.72% +VND1(NAC)/col-VND1-DAP-Seq(GSE60143)/Homer CTTRWDNHWYAAGYW 1e0 -3.295e-01 1.0000 856.0 21.41% 874.7 21.93% +EFL-1(E2F)/cElegans-L1-EFL1-ChIP-Seq(modEncode)/Homer TGCAARYGCGCTCYA 1e0 -3.288e-01 1.0000 23.0 0.58% 26.5 0.66% +AT5G05550(Trihelix)/col-AT5G05550-DAP-Seq(GSE60143)/Homer HDNHDTCKCCGGMGA 1e0 -3.273e-01 1.0000 1836.0 45.91% 1856.6 46.54% +AT3G57600(AP2EREBP)/col-AT3G57600-DAP-Seq(GSE60143)/Homer GGCGGTGG 1e0 -3.265e-01 1.0000 417.0 10.43% 431.5 10.82% +EBF1(EBF)/Near-E2A-ChIP-Seq(GSE21512)/Homer GTCCCCWGGGGA 1e0 -3.262e-01 1.0000 293.0 7.33% 305.8 7.67% +ABF1(bZIP)/Arabidopsis-ABF1-ChIP-Seq(GSE80564)/Homer CACGTGGC 1e0 -3.243e-01 1.0000 795.0 19.88% 813.9 20.40% +ANAC057(NAC)/colamp-ANAC057-DAP-Seq(GSE60143)/Homer DVCKTGNNNNNCAMG 1e0 -3.232e-01 1.0000 784.0 19.60% 802.1 20.11% +E2FA(E2FDP)/colamp-E2FA-DAP-Seq(GSE60143)/Homer WWTGGCGCCAWWWNN 1e0 -3.222e-01 1.0000 1148.0 28.71% 1168.6 29.29% +SpiB(ETS)/OCILY3-SPIB-ChIP-Seq(GSE56857)/Homer AAAGRGGAAGTG 1e0 -3.182e-01 1.0000 92.0 2.30% 99.4 2.49% +ERE(NR),IR3/MCF7-ERa-ChIP-Seq(Unpublished)/Homer VAGGTCACNSTGACC 1e0 -3.164e-01 1.0000 117.0 2.93% 125.8 3.15% +ERF4(AP2EREBP)/colamp-ERF4-DAP-Seq(GSE60143)/Homer WDWTGGCGGCGG 1e0 -3.149e-01 1.0000 1265.0 31.63% 1286.2 32.24% +AP-1(bZIP)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer VTGACTCATC 1e0 -3.097e-01 1.0000 567.0 14.18% 584.1 14.64% +WT1(Zf)/Kidney-WT1-ChIP-Seq(GSE90016)/Homer MCTCCCMCRCAB 1e0 -3.038e-01 1.0000 164.0 4.10% 174.3 4.37% +ERF105(AP2EREBP)/colamp-ERF105-DAP-Seq(GSE60143)/Homer TGGCGGCT 1e0 -3.033e-01 1.0000 996.0 24.91% 1017.2 25.50% +TCP3(TCP)/colamp-TCP3-DAP-Seq(GSE60143)/Homer WGTGGTCCCAAHWWW 1e0 -3.024e-01 1.0000 197.0 4.93% 208.9 5.24% +FOXK2(Forkhead)/U2OS-FOXK2-ChIP-Seq(E-MTAB-2204)/Homer SCHTGTTTACAT 1e0 -2.963e-01 1.0000 493.0 12.33% 510.6 12.80% +Znf263(Zf)/K562-Znf263-ChIP-Seq(GSE31477)/Homer CVGTSCTCCC 1e0 -2.943e-01 1.0000 645.0 16.13% 664.8 16.67% +PLT1(AP2EREBP)/colamp-PLT1-DAP-Seq(GSE60143)/Homer GCACGAWTYCCGAGG 1e0 -2.934e-01 1.0000 97.0 2.43% 105.9 2.65% +VND2(NAC)/col-VND2-DAP-Seq(GSE60143)/Homer DNCKTNNNNNNNAAG 1e0 -2.930e-01 1.0000 1011.0 25.28% 1033.8 25.92% +ABF1/SacCer-Promoters/Homer CGTRNAAARTGA 1e0 -2.927e-01 1.0000 634.0 15.85% 653.9 16.39% +ERF11(AP2EREBP)/col-ERF11-DAP-Seq(GSE60143)/Homer RTGGCGGCGG 1e0 -2.897e-01 1.0000 960.0 24.01% 982.6 24.63% +DMRT6(DM)/Testis-DMRT6-ChIP-Seq(GSE60440)/Homer YDGHTACAWTGTADC 1e0 -2.890e-01 1.0000 176.0 4.40% 187.8 4.71% +CRF10(AP2EREBP)/col100-CRF10-DAP-Seq(GSE60143)/Homer DCCGCCGYHA 1e0 -2.883e-01 1.0000 1495.0 37.38% 1519.1 38.08% +FEA4(bZIP)/Corn-FEA4-ChIP-Seq(GSE61954)/Homer TGACGTCACS 1e0 -2.879e-01 1.0000 1114.0 27.86% 1137.3 28.51% +Zfp281(Zf)/ES-Zfp281-ChIP-Seq(GSE81042)/Homer CCCCTCCCCCAC 1e0 -2.870e-01 1.0000 9.0 0.23% 11.6 0.29% +ZSCAN22(Zf)/HEK293-ZSCAN22.GFP-ChIP-Seq(GSE58341)/Homer SMCAGTCWGAKGGAGGAGGC 1e0 -2.870e-01 1.0000 9.0 0.23% 11.7 0.29% +ZNF528(Zf)/HEK293-ZNF528.GFP-ChIP-Seq(GSE58341)/Homer AGAAATGACTTCCCT 1e0 -2.867e-01 1.0000 1.0 0.03% 1.1 0.03% +BPC6(BBRBPC)/col-BPC6-DAP-Seq(GSE60143)/Homer YTYTCTCTCTCTCTA 1e0 -2.867e-01 1.0000 1.0 0.03% 1.7 0.04% +PAX5(Paired,Homeobox)/GM12878-PAX5-ChIP-Seq(GSE32465)/Homer GCAGCCAAGCRTGACH 1e0 -2.853e-01 1.0000 284.0 7.10% 298.2 7.48% +VND6(NAC)/col-VND6-DAP-Seq(GSE60143)/Homer DCTTNHTTTTYAMGY 1e0 -2.827e-01 1.0000 1239.0 30.98% 1263.1 31.66% +At5g08750(C3H)/col-At5g08750-DAP-Seq(GSE60143)/Homer NWDTTGCGGCTR 1e0 -2.824e-01 1.0000 1229.0 30.73% 1253.1 31.41% +ANAC071(NAC)/col-ANAC071-DAP-Seq(GSE60143)/Homer DNCKTNDNNNHNAAG 1e0 -2.818e-01 1.0000 1004.0 25.11% 1027.8 25.77% +AS2(LOBAS2)/col-AS2-DAP-Seq(GSE60143)/Homer CCGDAAWWHMCGSCG 1e0 -2.812e-01 1.0000 88.0 2.20% 96.1 2.41% +ANAC013(NAC)/col-ANAC013-DAP-Seq(GSE60143)/Homer CTTGNNNNNCAAGNA 1e0 -2.808e-01 1.0000 318.0 7.95% 333.9 8.37% +CRF4(AP2EREBP)/colamp-CRF4-DAP-Seq(GSE60143)/Homer CGCCGCCA 1e0 -2.777e-01 1.0000 412.0 10.30% 429.6 10.77% +BATF(bZIP)/Th17-BATF-ChIP-Seq(GSE39756)/Homer DATGASTCAT 1e0 -2.730e-01 1.0000 516.0 12.90% 535.4 13.42% +GFY(?)/Promoter/Homer ACTACAATTCCC 1e0 -2.663e-01 1.0000 33.0 0.83% 38.7 0.97% +AARE(HLH)/mES-cMyc-ChIP-Seq/Homer GATTGCATCA 1e0 -2.641e-01 1.0000 77.0 1.93% 85.1 2.13% +ERF8(AP2EREBP)/colamp-ERF8-DAP-Seq(GSE60143)/Homer CGCCGYCATW 1e0 -2.590e-01 1.0000 1430.0 35.76% 1457.8 36.55% +Tbx20(T-box)/Heart-Tbx20-ChIP-Seq(GSE29636)/Homer GGTGYTGACAGS 1e0 -2.588e-01 1.0000 114.0 2.85% 124.0 3.11% +DUX4(Homeobox)/Myoblasts-DUX4.V5-ChIP-Seq(GSE75791)/Homer NWTAAYCYAATCAWN 1e0 -2.539e-01 1.0000 30.0 0.75% 35.9 0.90% +MYB56(MYB)/colamp-MYB56-DAP-Seq(GSE60143)/Homer HTAACGRMHY 1e0 -2.522e-01 1.0000 1622.0 40.56% 1650.3 41.37% +ZNF322(Zf)/HEK293-ZNF322.GFP-ChIP-Seq(GSE58341)/Homer GAGCCTGGTACTGWGCCTGR 1e0 -2.519e-01 1.0000 41.0 1.03% 47.5 1.19% +ARF2(ARF)/col-ARF2-DAP-Seq(GSE60143)/Homer TTGTCGGMWN 1e0 -2.499e-01 1.0000 2208.0 55.21% 2235.1 56.03% +Reverb(NR),DR2/RAW-Reverba.biotin-ChIP-Seq(GSE45914)/Homer GTRGGTCASTGGGTCA 1e0 -2.487e-01 1.0000 40.0 1.00% 46.6 1.17% +Hoxa10(Homeobox)/ChickenMSG-Hoxa10.Flag-ChIP-Seq(GSE86088)/Homer GGYAATGAAA 1e0 -2.453e-01 1.0000 450.0 11.25% 470.1 11.78% +STAT4(Stat)/CD4-Stat4-ChIP-Seq(GSE22104)/Homer NYTTCCWGGAAR 1e0 -2.390e-01 1.0000 536.0 13.40% 558.5 14.00% +E2F4(E2F)/K562-E2F4-ChIP-Seq(GSE31477)/Homer GGCGGGAAAH 1e0 -2.359e-01 1.0000 653.0 16.33% 677.5 16.98% +EWS:ERG-fusion(ETS)/CADO_ES1-EWS:ERG-ChIP-Seq(SRA014231)/Homer ATTTCCTGTN 1e0 -2.291e-01 1.0000 306.0 7.65% 324.7 8.14% +c-Myc(bHLH)/mES-cMyc-ChIP-Seq(GSE11431)/Homer VVCCACGTGG 1e0 -2.279e-01 1.0000 342.0 8.55% 361.0 9.05% +Hnf6b(Homeobox)/LNCaP-Hnf6b-ChIP-Seq(GSE106305)/Homer TATTGAYY 1e0 -2.232e-01 1.0000 1377.0 34.43% 1408.1 35.30% +PHA-4(Forkhead)/cElegans-Embryos-PHA4-ChIP-Seq(modEncode)/Homer KTGTTTGC 1e0 -2.180e-01 1.0000 2187.0 54.69% 2218.3 55.61% +HuR(?)/HEK293-HuR-CLIP-Seq(GSE87887)/Homer BTTTGGTTTG 1e0 -2.163e-01 1.0000 2232.0 55.81% 2263.5 56.74% +PCF/Arabidopsis-Promoters/Homer NNWWWTGGGCYTDDN 1e0 -2.154e-01 1.0000 241.0 6.03% 258.7 6.49% +Foxo3(Forkhead)/U2OS-Foxo3-ChIP-Seq(E-MTAB-2701)/Homer DGTAAACA 1e0 -2.100e-01 1.0000 621.0 15.53% 647.8 16.24% +HNF6(Homeobox)/Liver-Hnf6-ChIP-Seq(ERP000394)/Homer NTATYGATCH 1e0 -2.081e-01 1.0000 1186.0 29.66% 1218.9 30.56% +RAP212(AP2EREBP)/col-RAP212-DAP-Seq(GSE60143)/Homer CGCCGCCATTTT 1e0 -2.076e-01 1.0000 825.0 20.63% 854.2 21.41% +MYB101(MYB)/colamp-MYB101-DAP-Seq(GSE60143)/Homer TAACNRMY 1e0 -2.076e-01 1.0000 2544.0 63.62% 2574.2 64.53% +ABF2(bZIP)/col-ABF2-DAP-Seq(GSE60143)/Homer KGMCACGTGDCMHHH 1e0 -2.068e-01 1.0000 254.0 6.35% 272.4 6.83% +AR-halfsite(NR)/LNCaP-AR-ChIP-Seq(GSE27824)/Homer CCAGGAACAG 1e0 -2.051e-01 1.0000 2120.0 53.01% 2153.4 53.98% +AT5G23930(mTERF)/col-AT5G23930-DAP-Seq(GSE60143)/Homer GGCGGCTG 1e0 -2.037e-01 1.0000 876.0 21.91% 906.2 22.72% +HAT2(Homeobox)/colamp-HAT2-DAP-Seq(GSE60143)/Homer CYAATSATTR 1e0 -2.008e-01 1.0000 941.0 23.53% 972.6 24.38% +STAT5(Stat)/mCD4+-Stat5-ChIP-Seq(GSE12346)/Homer RTTTCTNAGAAA 1e0 -1.957e-01 1.0000 137.0 3.43% 151.1 3.79% +bHLH18(bHLH)/col-bHLH18-DAP-Seq(GSE60143)/Homer CACGTGTTYCACGTG 1e0 -1.950e-01 1.0000 19.0 0.48% 24.8 0.62% +JunB(bZIP)/DendriticCells-Junb-ChIP-Seq(GSE36099)/Homer RATGASTCAT 1e0 -1.899e-01 1.0000 421.0 10.53% 445.2 11.16% +LOB(LOBAS2)/col-LOB-DAP-Seq(GSE60143)/Homer CGCCGKAWWTTHCGS 1e0 -1.898e-01 1.0000 344.0 8.60% 366.3 9.18% +SeqBias: CA-repeat CACACACACA 1e0 -1.887e-01 1.0000 2489.0 62.24% 2522.3 63.23% +RAP26(AP2EREBP)/colamp-RAP26-DAP-Seq(GSE60143)/Homer HDATGGCGGCGG 1e0 -1.873e-01 1.0000 1473.0 36.83% 1509.7 37.85% +At4g28140(AP2EREBP)/colamp-At4g28140-DAP-Seq(GSE60143)/Homer DCCACCGACCAW 1e0 -1.847e-01 1.0000 402.0 10.05% 426.5 10.69% +Fra1(bZIP)/BT549-Fra1-ChIP-Seq(GSE46166)/Homer NNATGASTCATH 1e0 -1.843e-01 1.0000 441.0 11.03% 466.6 11.70% +CEJ1(AP2EREBP)/col-CEJ1-DAP-Seq(GSE60143)/Homer WWTGTCGGTG 1e0 -1.796e-01 1.0000 1440.0 36.01% 1477.4 37.04% +STAT6(Stat)/Macrophage-Stat6-ChIP-Seq(GSE38377)/Homer TTCCKNAGAA 1e0 -1.770e-01 1.0000 278.0 6.95% 299.5 7.51% +Cux2(Homeobox)/Liver-Cux2-ChIP-Seq(GSE35985)/Homer HNRAATCAAT 1e0 -1.731e-01 1.0000 899.0 22.48% 933.5 23.40% +PUCHI(AP2EREBP)/colamp-PUCHI-DAP-Seq(GSE60143)/Homer GCGCCGTY 1e0 -1.728e-01 1.0000 745.0 18.63% 777.7 19.50% +Pho4(bHLH)/Yeast-Pho4-ChIP-Seq(GSE29506)/Homer AAGCACGTGBGD 1e0 -1.706e-01 1.0000 189.0 4.73% 207.6 5.21% +DMRT1(DM)/Testis-DMRT1-ChIP-Seq(GSE64892)/Homer TWGHWACAWTGTWDC 1e0 -1.689e-01 1.0000 209.0 5.23% 228.9 5.74% +RRTF1(AP2EREBP)/colamp-RRTF1-DAP-Seq(GSE60143)/Homer CCGCCGCHATTT 1e0 -1.677e-01 1.0000 456.0 11.40% 483.3 12.12% +AT1G71450(AP2EREBP)/col-AT1G71450-DAP-Seq(GSE60143)/Homer DHDWTGTCGGTG 1e0 -1.673e-01 1.0000 1994.0 49.86% 2033.7 50.98% +FOXA1:AR(Forkhead,NR)/LNCAP-AR-ChIP-Seq(GSE27824)/Homer AGTAAACAAAAAAGAACAND 1e0 -1.658e-01 1.0000 15.0 0.38% 20.3 0.51% +IBL1(bHLH)/Seedling-IBL1-ChIP-Seq(GSE51120)/Homer CACGTGCC 1e0 -1.634e-01 1.0000 1725.0 43.14% 1765.7 44.27% +NF-E2(bZIP)/K562-NFE2-ChIP-Seq(GSE31477)/Homer GATGACTCAGCA 1e0 -1.618e-01 1.0000 27.0 0.68% 34.7 0.87% +Hoxa9(Homeobox)/ChickenMSG-Hoxa9.Flag-ChIP-Seq(GSE86088)/Homer RGCAATNAAA 1e0 -1.597e-01 1.0000 2264.0 56.61% 2303.3 57.74% +E-box/Arabidopsis-Promoters/Homer GCCACGTG 1e0 -1.498e-01 1.0000 540.0 13.50% 571.3 14.32% +MYB119(MYB)/colamp-MYB119-DAP-Seq(GSE60143)/Homer YRACCGTTACDD 1e0 -1.448e-01 1.0000 900.0 22.51% 938.1 23.52% +ERF3(AP2EREBP)/colamp-ERF3-DAP-Seq(GSE60143)/Homer ATGGCGGCGG 1e0 -1.429e-01 1.0000 591.0 14.78% 625.0 15.67% +NRF1(NRF)/MCF7-NRF1-ChIP-Seq(Unpublished)/Homer CTGCGCATGCGC 1e0 -1.385e-01 1.0000 36.0 0.90% 45.7 1.15% +ERF5(AP2EREBP)/colamp-ERF5-DAP-Seq(GSE60143)/Homer DCMGCCGCCA 1e0 -1.355e-01 1.0000 261.0 6.53% 285.1 7.15% +At1g36060(AP2EREBP)/colamp-At1g36060-DAP-Seq(GSE60143)/Homer NNWWKGTCGGTG 1e0 -1.343e-01 1.0000 927.0 23.18% 967.1 24.24% +ZNF675(Zf)/HEK293-ZNF675.GFP-ChIP-Seq(GSE58341)/Homer ARGAGGMCAAAATGW 1e0 -1.339e-01 1.0000 61.0 1.53% 73.5 1.84% +ERF9(AP2EREBP)/colamp-ERF9-DAP-Seq(GSE60143)/Homer AWATGGCGGCGG 1e0 -1.296e-01 1.0000 205.0 5.13% 227.4 5.70% +HINFP(Zf)/K562-HINFP.eGFP-ChIP-Seq(Encode)/Homer TWVGGTCCGC 1e0 -1.272e-01 1.0000 543.0 13.58% 577.6 14.48% +TGA10(bZIP)/colamp-TGA10-DAP-Seq(GSE60143)/Homer ATGACGTC 1e0 -1.223e-01 1.0000 797.0 19.93% 837.8 21.00% +NRF(NRF)/Promoter/Homer STGCGCATGCGC 1e0 -1.204e-01 1.0000 110.0 2.75% 127.3 3.19% +ERF104(AP2EREBP)/col-ERF104-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e0 -1.157e-01 1.0000 736.0 18.40% 776.5 19.47% +Atf3(bZIP)/GBM-ATF3-ChIP-Seq(GSE33912)/Homer DATGASTCATHN 1e0 -1.130e-01 1.0000 504.0 12.60% 539.2 13.52% +Stat3(Stat)/mES-Stat3-ChIP-Seq(GSE11431)/Homer CTTCCGGGAA 1e0 -1.116e-01 1.0000 272.0 6.80% 299.3 7.50% +JunD(bZIP)/K562-JunD-ChIP-Seq/Homer ATGACGTCATCN 1e0 -1.068e-01 1.0000 48.0 1.20% 60.3 1.51% +Foxo1(Forkhead)/RAW-Foxo1-ChIP-Seq(Fan_et_al.)/Homer CTGTTTAC 1e0 -1.049e-01 1.0000 1146.0 28.66% 1194.1 29.93% +FOXK1(Forkhead)/HEK293-FOXK1-ChIP-Seq(GSE51673)/Homer NVWTGTTTAC 1e0 -1.021e-01 1.0000 877.0 21.93% 922.1 23.12% +GATA19(C2C2gata)/colamp-GATA19-DAP-Seq(GSE60143)/Homer ATCSGATCVG 1e0 -1.010e-01 1.0000 158.0 3.95% 180.0 4.51% +ZFX(Zf)/mES-Zfx-ChIP-Seq(GSE11431)/Homer AGGCCTRG 1e0 -1.009e-01 1.0000 580.0 14.50% 619.0 15.52% +At5g65130(AP2EREBP)/colamp-At5g65130-DAP-Seq(GSE60143)/Homer CCRCCGACAWTN 1e0 -9.603e-02 1.0000 234.0 5.85% 261.2 6.55% +BORIS(Zf)/K562-CTCFL-ChIP-Seq(GSE32465)/Homer CNNBRGCGCCCCCTGSTGGC 1e0 -9.565e-02 1.0000 30.0 0.75% 40.2 1.01% +LBD13(LOBAS2)/colamp-LBD13-DAP-Seq(GSE60143)/Homer KCCGTNWTTTBCGGC 1e0 -9.488e-02 1.0000 1046.0 26.16% 1095.7 27.47% +At1g78700(BZR)/col-At1g78700-DAP-Seq(GSE60143)/Homer NNNNCACGTGNNNNN 1e0 -9.430e-02 1.0000 336.0 8.40% 368.5 9.24% +MGP(C2H2)/colamp-MGP-DAP-Seq(GSE60143)/Homer TTTTGTCGTTTW 1e0 -9.304e-02 1.0000 246.0 6.15% 274.2 6.88% +ELF3(ETS)/PDAC-ELF3-ChIP-Seq(GSE64557)/Homer ANCAGGAAGT 1e0 -9.031e-02 1.0000 300.0 7.50% 331.7 8.32% +GFY-Staf(?,Zf)/Promoter/Homer RACTACAATTCCCAGAAKGC 1e0 -8.989e-02 1.0000 14.0 0.35% 21.8 0.55% +IDD5(C2H2)/colamp-IDD5-DAP-Seq(GSE60143)/Homer TTTTGTCTTTTTBTK 1e0 -8.770e-02 1.0000 233.0 5.83% 261.4 6.55% +AT2G33550(Trihelix)/colamp-AT2G33550-DAP-Seq(GSE60143)/Homer TTTAAGGGCAYTTTT 1e0 -8.164e-02 1.0000 1760.0 44.01% 1817.2 45.56% +Hoxd10(Homeobox)/ChickenMSG-Hoxd10.Flag-ChIP-Seq(GSE86088)/Homer GGCMATGAAA 1e0 -8.163e-02 1.0000 970.0 24.26% 1021.9 25.62% +Hoxd12(Homeobox)/ChickenMSG-Hoxd12.Flag-ChIP-Seq(GSE86088)/Homer HDGYAATGAAAN 1e0 -7.926e-02 1.0000 1509.0 37.73% 1566.2 39.26% +SeqBias: CG-repeat CGCGCGCGCG 1e0 -7.680e-02 1.0000 1092.0 27.31% 1146.2 28.73% +NPAS(bHLH)/Liver-NPAS-ChIP-Seq(GSE39860)/Homer NVCACGTG 1e0 -7.624e-02 1.0000 1370.0 34.26% 1427.2 35.78% +ESE1(AP2EREBP)/col-ESE1-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e0 -7.369e-02 1.0000 424.0 10.60% 463.8 11.63% +At4g36780(BZR)/col-At4g36780-DAP-Seq(GSE60143)/Homer NNNNNNCACGTGNNN 1e0 -7.281e-02 1.0000 348.0 8.70% 384.6 9.64% +MYB98(MYB)/col-MYB98-DAP-Seq(GSE60143)/Homer NWDCCGTTAC 1e0 -7.236e-02 1.0000 594.0 14.85% 639.7 16.04% +n-Myc(bHLH)/mES-nMyc-ChIP-Seq(GSE11431)/Homer VRCCACGTGG 1e0 -7.156e-02 1.0000 555.0 13.88% 599.8 15.04% +Tcf3(HMG)/mES-Tcf3-ChIP-Seq(GSE11724)/Homer ASWTCAAAGG 1e0 -7.099e-02 1.0000 140.0 3.50% 164.2 4.12% +bHLH34(bHLH)/colamp-bHLH34-DAP-Seq(GSE60143)/Homer HGWGRHWGACACGTG 1e0 -6.980e-02 1.0000 315.0 7.88% 350.4 8.78% +E2F3(E2F)/MEF-E2F3-ChIP-Seq(GSE71376)/Homer BTKGGCGGGAAA 1e0 -6.853e-02 1.0000 423.0 10.58% 463.3 11.62% +PIF7(bHLH)/col-PIF7-DAP-Seq(GSE60143)/Homer CCACGTGGNH 1e0 -6.269e-02 1.0000 151.0 3.78% 177.4 4.45% +MNT(bHLH)/HepG2-MNT-ChIP-Seq(Encode)/Homer DGCACACGTG 1e0 -6.199e-02 1.0000 758.0 18.95% 810.4 20.32% +FOXP1(Forkhead)/H9-FOXP1-ChIP-Seq(GSE31006)/Homer NYYTGTTTACHN 1e0 -6.180e-02 1.0000 345.0 8.63% 383.0 9.60% +ANAC047(NAC)/colamp-ANAC047-DAP-Seq(GSE60143)/Homer WACACGTAACTT 1e0 -6.157e-02 1.0000 1429.0 35.73% 1491.9 37.40% +bHLHE41(bHLH)/proB-Bhlhe41-ChIP-Seq(GSE93764)/Homer KCACGTGMCN 1e0 -5.939e-02 1.0000 1335.0 33.38% 1397.1 35.02% +ERF15(AP2EREBP)/colamp-ERF15-DAP-Seq(GSE60143)/Homer WDHAGCMGCCAT 1e0 -5.830e-02 1.0000 1295.0 32.38% 1357.7 34.04% +TGA2(bZIP)/colamp-TGA2-DAP-Seq(GSE60143)/Homer ACGTCAYCHH 1e0 -4.977e-02 1.0000 998.0 24.96% 1059.1 26.55% +Pho2(bHLH)/Yeast-Pho2-ChIP-Seq(GSE29506)/Homer CCCACGTGCT 1e0 -4.619e-02 1.0000 392.0 9.80% 436.8 10.95% +HLF(bZIP)/HSC-HLF.Flag-ChIP-Seq(GSE69817)/Homer RTTATGYAAB 1e0 -4.585e-02 1.0000 1025.0 25.63% 1088.8 27.30% +IDD7(C2H2)/col-IDD7-DAP-Seq(GSE60143)/Homer TTTGTCKTTTTN 1e0 -4.392e-02 1.0000 287.0 7.18% 326.9 8.19% +NPAS2(bHLH)/Liver-NPAS2-ChIP-Seq(GSE39860)/Homer KCCACGTGAC 1e0 -4.238e-02 1.0000 817.0 20.43% 877.4 22.00% +WUS1(Homeobox)/colamp-WUS1-DAP-Seq(GSE60143)/Homer CAWTCATTCA 1e0 -4.160e-02 1.0000 328.0 8.20% 371.0 9.30% +AtIDD11(C2H2)/colamp-AtIDD11-DAP-Seq(GSE60143)/Homer TTTGTCGTTT 1e0 -3.884e-02 1.0000 314.0 7.85% 356.5 8.94% +CUX1(Homeobox)/K562-CUX1-ChIP-Seq(GSE92882)/Homer TATCGATNAN 1e0 -3.778e-02 1.0000 1336.0 33.41% 1407.9 35.30% +bZIP50(bZIP)/colamp-bZIP50-DAP-Seq(GSE60143)/Homer GATGACGTCA 1e0 -3.746e-02 1.0000 1571.0 39.28% 1644.3 41.22% +ERF13(AP2EREBP)/colamp-ERF13-DAP-Seq(GSE60143)/Homer TYAGCCGCCATT 1e0 -3.742e-02 1.0000 941.0 23.53% 1006.2 25.22% +Fosl2(bZIP)/3T3L1-Fosl2-ChIP-Seq(GSE56872)/Homer NATGASTCABNN 1e0 -3.622e-02 1.0000 213.0 5.33% 249.1 6.24% +Bach2(bZIP)/OCILy7-Bach2-ChIP-Seq(GSE44420)/Homer TGCTGAGTCA 1e0 -3.613e-02 1.0000 114.0 2.85% 141.6 3.55% +Max(bHLH)/K562-Max-ChIP-Seq(GSE31477)/Homer RCCACGTGGYYN 1e0 -3.515e-02 1.0000 512.0 12.80% 565.0 14.16% +Egr1(Zf)/K562-Egr1-ChIP-Seq(GSE32465)/Homer TGCGTGGGYG 1e0 -3.500e-02 1.0000 279.0 6.98% 320.1 8.03% +TGA9(bZIP)/colamp-TGA9-DAP-Seq(GSE60143)/Homer VTGACGTC 1e0 -3.475e-02 1.0000 1495.0 37.38% 1569.4 39.34% +CRE(bZIP)/Promoter/Homer CSGTGACGTCAC 1e0 -3.317e-02 1.0000 215.0 5.38% 252.6 6.33% +Fra2(bZIP)/Striatum-Fra2-ChIP-Seq(GSE43429)/Homer GGATGACTCATC 1e0 -3.163e-02 1.0000 342.0 8.55% 388.5 9.74% +MYB88(MYB)/col-MYB88-DAP-Seq(GSE60143)/Homer HNACGCTCCT 1e0 -3.154e-02 1.0000 1515.0 37.88% 1591.3 39.89% +TGA3(bZIP)/colamp-TGA3-DAP-Seq(GSE60143)/Homer WTGATGACGTCATCW 1e0 -3.065e-02 1.0000 22.0 0.55% 35.4 0.89% +bHLHE40(bHLH)/HepG2-BHLHE40-ChIP-Seq(GSE31477)/Homer KCACGTGMCN 1e0 -2.940e-02 1.0000 328.0 8.20% 374.4 9.39% +CEBP(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer ATTGCGCAAC 1e0 -2.636e-02 1.0000 863.0 21.58% 932.4 23.37% +E-box(bHLH)/Promoter/Homer SSGGTCACGTGA 1e0 -2.418e-02 1.0000 65.0 1.63% 88.3 2.21% +ZNF136(Zf)/HEK293-ZNF136.GFP-ChIP-Seq(GSE58341)/Homer YTKGATAHAGTATTCTWGGTNGGCA 1e0 -2.373e-02 1.0000 53.0 1.33% 74.2 1.86% +TGA1(bZIP)/colamp-TGA1-DAP-Seq(GSE60143)/Homer TGACGTCAKC 1e0 -2.281e-02 1.0000 454.0 11.35% 510.3 12.79% +EKLF(Zf)/Erythrocyte-Klf1-ChIP-Seq(GSE20478)/Homer NWGGGTGTGGCY 1e0 -2.020e-02 1.0000 44.0 1.10% 64.0 1.60% +TGA4(bZIP)/colamp-TGA4-DAP-Seq(GSE60143)/Homer RTGACGTCAKCW 1e0 -2.014e-02 1.0000 341.0 8.53% 392.2 9.83% +Atf2(bZIP)/3T3L1-Atf2-ChIP-Seq(GSE56872)/Homer NRRTGACGTCAT 1e0 -2.006e-02 1.0000 243.0 6.08% 287.4 7.20% +Atf7(bZIP)/3T3L1-Atf7-ChIP-Seq(GSE56872)/Homer NGRTGACGTCAY 1e0 -1.603e-02 1.0000 431.0 10.78% 491.0 12.31% +BMAL1(bHLH)/Liver-Bmal1-ChIP-Seq(GSE39860)/Homer GNCACGTG 1e0 -1.475e-02 1.0000 1436.0 35.91% 1525.5 38.24% +RUNX-AML(Runt)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer GCTGTGGTTW 1e0 -1.395e-02 1.0000 388.0 9.70% 446.1 11.18% +Smad3(MAD)/NPC-Smad3-ChIP-Seq(GSE36673)/Homer TWGTCTGV 1e0 -1.318e-02 1.0000 1844.0 46.11% 1937.4 48.57% +ERF73(AP2EREBP)/col-ERF73-DAP-Seq(GSE60143)/Homer CCGCCGCC 1e0 -1.298e-02 1.0000 346.0 8.65% 402.1 10.08% +CLOCK(bHLH)/Liver-Clock-ChIP-Seq(GSE39860)/Homer GHCACGTG 1e0 -1.263e-02 1.0000 508.0 12.70% 575.0 14.41% +c-Myc(bHLH)/LNCAP-cMyc-ChIP-Seq(Unpublished)/Homer VCCACGTG 1e0 -1.166e-02 1.0000 548.0 13.70% 617.3 15.48% +bHLH74(bHLH)/col-bHLH74-DAP-Seq(GSE60143)/Homer DRATCACGTGAB 1e0 -1.119e-02 1.0000 218.0 5.45% 265.2 6.65% +TGA6(bZIP)/colamp-TGA6-DAP-Seq(GSE60143)/Homer TGACGTCABC 1e0 -1.105e-02 1.0000 890.0 22.26% 973.1 24.39% +ETS:RUNX(ETS,Runt)/Jurkat-RUNX1-ChIP-Seq(GSE17954)/Homer RCAGGATGTGGT 1e0 -1.065e-02 1.0000 20.0 0.50% 36.2 0.91% +AT1G28160(AP2EREBP)/colamp-AT1G28160-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e0 -1.052e-02 1.0000 1471.0 36.78% 1566.0 39.26% +ELF5(ETS)/T47D-ELF5-ChIP-Seq(GSE30407)/Homer ACVAGGAAGT 1e0 -9.908e-03 1.0000 457.0 11.43% 523.5 13.12% +NAP(NAC)/col-NAP-DAP-Seq(GSE60143)/Homer ARGTTACGTRTN 1e0 -9.710e-03 1.0000 1955.0 48.89% 2053.6 51.48% +BIM1(bHLH)/colamp-BIM1-DAP-Seq(GSE60143)/Homer NNNNNNVTCACGTGM 1e0 -9.297e-03 1.0000 134.0 3.35% 173.9 4.36% +At5g18450(AP2EREBP)/col-At5g18450-DAP-Seq(GSE60143)/Homer CACCGCTT 1e0 -8.245e-03 1.0000 1478.0 36.96% 1577.5 39.55% +ERF2(AP2EREBP)/colamp-ERF2-DAP-Seq(GSE60143)/Homer GGCGGCTG 1e0 -7.990e-03 1.0000 361.0 9.03% 423.9 10.63% +LRF(Zf)/Erythroblasts-ZBTB7A-ChIP-Seq(GSE74977)/Homer AAGACCCYYN 1e0 -7.734e-03 1.0000 920.0 23.01% 1009.3 25.30% +NAM(NAC)/col-NAM-DAP-Seq(GSE60143)/Homer RGTTRCGTRW 1e0 -6.907e-03 1.0000 2197.0 54.94% 2299.6 57.65% +Atf1(bZIP)/K562-ATF1-ChIP-Seq(GSE31477)/Homer GATGACGTCA 1e0 -6.453e-03 1.0000 816.0 20.41% 904.5 22.68% +KLF10(Zf)/HEK293-KLF10.GFP-ChIP-Seq(GSE58341)/Homer GGGGGTGTGTCC 1e0 -5.960e-03 1.0000 181.0 4.53% 229.1 5.74% +EIL4(EIL)/Tomato-EIL4-ChIP-Seq(GSE116581)/Homer GATTCAWTGAAT 1e0 -5.668e-03 1.0000 94.0 2.35% 130.7 3.28% +NFIL3(bZIP)/HepG2-NFIL3-ChIP-Seq(Encode)/Homer VTTACGTAAYNNNNN 1e0 -5.431e-03 1.0000 864.0 21.61% 956.5 23.98% +ERF1(AP2EREBP)/colamp-ERF1-DAP-Seq(GSE60143)/Homer GGCGGCTR 1e0 -5.048e-03 1.0000 330.0 8.25% 394.9 9.90% +At5g66730(C2H2)/colamp-At5g66730-DAP-Seq(GSE60143)/Homer TTTGTCKTTTTK 1e0 -3.986e-03 1.0000 190.0 4.75% 242.8 6.09% +BIM3(bHLH)/col-BIM3-DAP-Seq(GSE60143)/Homer TWVTCACGTGAB 1e0 -3.695e-03 1.0000 141.0 3.53% 187.7 4.71% +ATAF1(NAC)/col-ATAF1-DAP-Seq(GSE60143)/Homer YACGTMAY 1e0 -3.420e-03 1.0000 3372.0 84.32% 3447.3 86.42% +HY5(bZIP)/colamp-HY5-DAP-Seq(GSE60143)/Homer RRTSACGTSD 1e0 -3.328e-03 1.0000 1500.0 37.51% 1613.6 40.45% +Egr2(Zf)/Thymocytes-Egr2-ChIP-Seq(GSE34254)/Homer NGCGTGGGCGGR 1e0 -3.302e-03 1.0000 65.0 1.63% 98.8 2.48% +GRE(NR),IR3/A549-GR-ChIP-Seq(GSE32465)/Homer NRGVACABNVTGTYCY 1e0 -3.180e-03 1.0000 88.0 2.20% 126.9 3.18% +TFE3(bHLH)/MEF-TFE3-ChIP-Seq(GSE75757)/Homer GTCACGTGACYV 1e0 -2.735e-03 1.0000 70.0 1.75% 105.3 2.64% +RUNX1(Runt)/Jurkat-RUNX1-ChIP-Seq(GSE29180)/Homer AAACCACARM 1e0 -2.615e-03 1.0000 655.0 16.38% 747.3 18.73% +Jun-AP1(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer GATGASTCATCN 1e0 -2.381e-03 1.0000 130.0 3.25% 177.4 4.45% +Ronin(THAP)/ES-Thap11-ChIP-Seq(GSE51522)/Homer RACTACAACTCCCAGVAKGC 1e0 -1.922e-03 1.0000 1.0 0.03% 8.5 0.21% +RUNX2(Runt)/PCa-RUNX2-ChIP-Seq(GSE33889)/Homer NWAACCACADNN 1e0 -1.823e-03 1.0000 492.0 12.30% 578.6 14.50% +SPDEF(ETS)/VCaP-SPDEF-ChIP-Seq(SRA014231)/Homer ASWTCCTGBT 1e0 -1.545e-03 1.0000 716.0 17.90% 817.4 20.49% +PIF4(bHLH)/Seedling-PIF4-ChIP-Seq(GSE35315)/Homer NNBCACGTGN 1e0 -1.460e-03 1.0000 905.0 22.63% 1015.8 25.47% +SHN3(AP2EREBP)/col-SHN3-DAP-Seq(GSE60143)/Homer CCGCCGCC 1e0 -1.174e-03 1.0000 113.0 2.83% 161.2 4.04% +PGR(NR)/EndoStromal-PGR-ChIP-Seq(GSE69539)/Homer AAGAACATWHTGTTC 1e0 -9.470e-04 1.0000 152.0 3.80% 209.0 5.24% +EHF(ETS)/LoVo-EHF-ChIP-Seq(GSE49402)/Homer AVCAGGAAGT 1e0 -9.380e-04 1.0000 654.0 16.35% 757.0 18.98% +Maz(Zf)/HepG2-Maz-ChIP-Seq(GSE31477)/Homer GGGGGGGG 1e0 -7.730e-04 1.0000 275.0 6.88% 349.7 8.77% +TGA5(bZIP)/col-TGA5-DAP-Seq(GSE60143)/Homer NNGATGACGTCATCN 1e0 -6.740e-04 1.0000 77.0 1.93% 120.1 3.01% +ARE(NR)/LNCAP-AR-ChIP-Seq(GSE27824)/Homer RGRACASNSTGTYCYB 1e0 -6.300e-04 1.0000 122.0 3.05% 175.2 4.39% +BIM2(bHLH)/col-BIM2-DAP-Seq(GSE60143)/Homer NNNNCACGTGNN 1e0 -5.200e-04 1.0000 688.0 17.20% 799.2 20.04% +IDD4(C2H2)/col-IDD4-DAP-Seq(GSE60143)/Homer TTTGTCTTTWTB 1e0 -5.030e-04 1.0000 431.0 10.78% 524.3 13.14% +SPCH(bHLH)/Seedling-SPCH-ChIP-Seq(GSE57497)/Homer WNBCACGTGA 1e0 -4.410e-04 1.0000 1170.0 29.26% 1303.1 32.67% +Zac1(Zf)/Neuro2A-Plagl1-ChIP-Seq(GSE75942)/Homer HAWGRGGCCM 1e0 -3.830e-04 1.0000 1533.0 38.33% 1675.4 42.00% +USF1(bHLH)/GM12878-Usf1-ChIP-Seq(GSE32465)/Homer SGTCACGTGR 1e0 -3.640e-04 1.0000 391.0 9.78% 483.6 12.12% +PIF5ox(bHLH)/Arabidopsis-PIF5ox-ChIP-Seq(GSE35062)/Homer BCACGTGVDN 1e0 -3.360e-04 1.0000 770.0 19.25% 890.5 22.32% +Etv2(ETS)/ES-ER71-ChIP-Seq(GSE59402)/Homer NNAYTTCCTGHN 1e0 -2.190e-04 1.0000 401.0 10.03% 498.3 12.49% +Cbf1(bHLH)/Yeast-Cbf1-ChIP-Seq(GSE29506)/Homer TCACGTGAYH 1e0 -2.060e-04 1.0000 250.0 6.25% 330.4 8.28% +GRE(NR),IR3/RAW264.7-GRE-ChIP-Seq(Unpublished)/Homer VAGRACAKWCTGTYC 1e0 -1.870e-04 1.0000 174.0 4.35% 243.8 6.11% +RUNX(Runt)/HPC7-Runx1-ChIP-Seq(GSE22178)/Homer SAAACCACAG 1e0 -1.570e-04 1.0000 503.0 12.58% 612.6 15.36% +Tcf7(HMG)/GM12878-TCF7-ChIP-Seq(Encode)/Homer CTTTGATGTGSB 1e0 -1.080e-04 1.0000 185.0 4.63% 259.7 6.51% +SGR5(C2H2)/colamp-SGR5-DAP-Seq(GSE60143)/Homer TTTGTCTTTTTT 1e0 -6.100e-05 1.0000 404.0 10.10% 511.4 12.82% +Elf4(ETS)/BMDM-Elf4-ChIP-Seq(GSE88699)/Homer ACTTCCKGKT 1e0 -5.600e-05 1.0000 606.0 15.15% 732.3 18.36% +PR(NR)/T47D-PR-ChIP-Seq(GSE31130)/Homer VAGRACAKNCTGTBC 1e0 -4.500e-05 1.0000 1404.0 35.11% 1568.2 39.31% +ERG(ETS)/VCaP-ERG-ChIP-Seq(GSE14097)/Homer ACAGGAAGTG 1e0 -4.200e-05 1.0000 696.0 17.40% 831.9 20.86% +REF6(Zf)/Arabidopsis-REF6-ChIP-Seq(GSE106942)/Homer TVCTCTGTTT 1e0 -3.300e-05 1.0000 241.0 6.03% 331.9 8.32% +EWS:FLI1-fusion(ETS)/SK_N_MC-EWS:FLI1-ChIP-Seq(SRA014231)/Homer VACAGGAAAT 1e0 -2.000e-05 1.0000 331.0 8.28% 437.3 10.96% +ETS1(ETS)/Jurkat-ETS1-ChIP-Seq(GSE17954)/Homer ACAGGAAGTG 1e0 -1.800e-05 1.0000 588.0 14.70% 722.8 18.12% +ETV1(ETS)/GIST48-ETV1-ChIP-Seq(GSE22441)/Homer AACCGGAAGT 1e0 -6.000e-06 1.0000 912.0 22.81% 1078.4 27.03% +ETV4(ETS)/HepG2-ETV4-ChIP-Seq(ENCODE)/Homer ACCGGAAGTG 1e0 -5.000e-06 1.0000 916.0 22.91% 1084.3 27.18% +Usf2(bHLH)/C2C12-Usf2-ChIP-Seq(GSE36030)/Homer GTCACGTGGT 1e0 -4.000e-06 1.0000 266.0 6.65% 373.0 9.35% +MITF(bHLH)/MastCells-MITF-ChIP-Seq(GSE48085)/Homer RTCATGTGAC 1e0 -1.000e-06 1.0000 839.0 20.98% 1019.1 25.55% +GABPA(ETS)/Jurkat-GABPa-ChIP-Seq(GSE17954)/Homer RACCGGAAGT 1e0 -0.000e+00 1.0000 634.0 15.85% 799.9 20.05% +Fli1(ETS)/CD8-FLI-ChIP-Seq(GSE20898)/Homer NRYTTCCGGH 1e0 -0.000e+00 1.0000 1030.0 25.76% 1228.0 30.78% +ELF1(ETS)/Jurkat-ELF1-ChIP-Seq(SRA014231)/Homer AVCCGGAAGT 1e0 -0.000e+00 1.0000 538.0 13.45% 708.4 17.76% +Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer HACTTCCGGY 1e0 -0.000e+00 1.0000 717.0 17.93% 911.8 22.86% +Tcf4(HMG)/Hct116-Tcf4-ChIP-Seq(SRA012054)/Homer ASATCAAAGGVA 1e0 -0.000e+00 1.0000 248.0 6.20% 380.6 9.54% +Klf4(Zf)/mES-Klf4-ChIP-Seq(GSE11431)/Homer GCCACACCCA 1e0 -0.000e+00 1.0000 100.0 2.50% 192.3 4.82% +Elk4(ETS)/Hela-Elk4-ChIP-Seq(GSE31477)/Homer NRYTTCCGGY 1e0 -0.000e+00 1.0000 862.0 21.56% 1082.7 27.14% +ETS(ETS)/Promoter/Homer AACCGGAAGT 1e0 -0.000e+00 1.0000 300.0 7.50% 450.8 11.30% +KLF6(Zf)/PDAC-KLF6-ChIP-Seq(GSE64557)/Homer MKGGGYGTGGCC 1e0 -0.000e+00 1.0000 404.0 10.10% 592.7 14.86% +Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132)/Homer CCWTTGTYYB 1e0 -0.000e+00 1.0000 1077.0 26.93% 2100.4 52.66% +Sox6(HMG)/Myotubes-Sox6-ChIP-Seq(GSE32627)/Homer CCATTGTTNY 1e0 -0.000e+00 1.0000 1231.0 30.78% 2122.0 53.20% +Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer BCCATTGTTC 1e0 -0.000e+00 1.0000 570.0 14.25% 1629.3 40.85% +Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer CCWTTGTY 1e0 -0.000e+00 1.0000 1209.0 30.23% 2214.5 55.52% +Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer AGGVNCCTTTGT 1e0 -0.000e+00 1.0000 498.0 12.45% 1690.2 42.37% +Sox17(HMG)/Endoderm-Sox17-ChIP-Seq(GSE61475)/Homer CCATTGTTYB 1e0 -0.000e+00 1.0000 561.0 14.03% 1563.7 39.20% +NFY(CCAAT)/Promoter/Homer RGCCAATSRG 1e0 -0.000e+00 1.0000 1010.0 25.26% 1293.3 32.42% +Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer YCTTTGTTCC 1e0 -0.000e+00 1.0000 453.0 11.33% 1405.0 35.22% +Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer RGKGGGCGGAGC 1e0 -0.000e+00 1.0000 278.0 6.95% 692.6 17.36% +KLF5(Zf)/LoVo-KLF5-ChIP-Seq(GSE49402)/Homer DGGGYGKGGC 1e0 -0.000e+00 1.0000 511.0 12.78% 798.8 20.03% +Sox15(HMG)/CPA-Sox15-ChIP-Seq(GSE62909)/Homer RAACAATGGN 1e0 -0.000e+00 1.0000 696.0 17.40% 1697.0 42.54% +KLF14(Zf)/HEK293-KLF14.GFP-ChIP-Seq(GSE58341)/Homer RGKGGGCGKGGC 1e0 -0.000e+00 1.0000 541.0 13.53% 926.8 23.23% +Sp2(Zf)/HEK293-Sp2.eGFP-ChIP-Seq(Encode)/Homer YGGCCCCGCCCC 1e0 -0.000e+00 1.0000 626.0 15.65% 1061.6 26.61% +AP-2gamma(AP2)/MCF7-TFAP2C-ChIP-Seq(GSE21234)/Homer SCCTSAGGSCAW 1e0 -0.000e+00 1.0000 375.0 9.38% 610.3 15.30% +LEF1(HMG)/H1-LEF1-ChIP-Seq(GSE64758)/Homer CCTTTGATST 1e0 -0.000e+00 1.0000 414.0 10.35% 668.7 16.76% +AP-2alpha(AP2)/Hela-AP2alpha-ChIP-Seq(GSE31477)/Homer ATGCCCTGAGGC 1e0 -0.000e+00 1.0000 279.0 6.98% 492.3 12.34% +Klf9(Zf)/GBM-Klf9-ChIP-Seq(GSE62211)/Homer GCCACRCCCACY 1e0 -0.000e+00 1.0000 79.0 1.98% 178.7 4.48% +KLF3(Zf)/MEF-Klf3-ChIP-Seq(GSE44748)/Homer NRGCCCCRCCCHBNN 1e0 -0.000e+00 1.0000 138.0 3.45% 369.8 9.27% +Oct4:Sox17(POU,Homeobox,HMG)/F9-Sox17-ChIP-Seq(GSE44553)/Homer CCATTGTATGCAAAT 1e0 -0.000e+00 1.0000 74.0 1.85% 204.5 5.13% +Sp1(Zf)/Promoter/Homer GGCCCCGCCCCC 1e0 -0.000e+00 1.0000 40.0 1.00% 204.7 5.13% +EBNA1(EBV-virus)/Raji-EBNA1-ChIP-Seq(GSE30709)/Homer GGYAGCAYDTGCTDCCCNNN 1e0 -0.000e+00 1.0000 0.0 0.00% 1.3 0.03% +ZFP3(Zf)/HEK293-ZFP3.GFP-ChIP-Seq(GSE58341)/Homer GGGTTTTGAAGGATGARTAGGAGTT 1e0 -0.000e+00 1.0000 0.0 0.00% 1.2 0.03% +ZNF16(Zf)/HEK293-ZNF16.GFP-ChIP-Seq(GSE58341)/Homer MACCTTCYATGGCTCCCTAKTGCCY 1e0 0.000e+00 1.0000 0.0 0.00% 0.0 0.00% +SeqBias: polyA-repeat AAAAAAAAAA 1e0 0.000e+00 1.0000 3999.0 100.00% 3989.0 100.00% +SeqBias: C/A-bias MMMMMMMMMM 1e0 0.000e+00 1.0000 3999.0 100.00% 3989.0 100.00% +SeqBias: polyC-repeat CCCCCCCCCC 1e0 0.000e+00 1.0000 3999.0 100.00% 3989.0 100.00% +SeqBias: G/A bias RRRRRRRRRR 1e0 0.000e+00 1.0000 3999.0 100.00% 3989.0 100.00% 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1.62% 1.008 +GTA 1.65% 1.64% 1.007 +TTA 1.86% 1.80% 1.031 +AAC 1.65% 1.67% 0.986 +CAC 1.46% 1.42% 1.025 +GAC 1.47% 1.47% 0.998 +TAC 1.65% 1.64% 1.007 +ACC 1.46% 1.39% 1.048 +CCC 1.30% 1.31% 0.993 +GCC 1.31% 1.37% 0.951 +TCC 1.46% 1.47% 0.992 +AGC 1.46% 1.46% 0.995 +CGC 1.31% 1.36% 0.963 +GGC 1.31% 1.37% 0.951 +TGC 1.46% 1.43% 1.026 +ATC 1.64% 1.61% 1.020 +CTC 1.46% 1.45% 1.012 +GTC 1.47% 1.47% 0.998 +TTC 1.64% 1.67% 0.987 +AAG 1.64% 1.68% 0.981 +CAG 1.47% 1.42% 1.031 +GAG 1.46% 1.45% 1.012 +TAG 1.63% 1.62% 1.008 +ACG 1.47% 1.47% 1.002 +CCG 1.31% 1.33% 0.983 +GCG 1.31% 1.36% 0.963 +TCG 1.47% 1.44% 1.015 +AGG 1.45% 1.46% 0.996 +CGG 1.31% 1.33% 0.983 +GGG 1.30% 1.31% 0.993 +TGG 1.46% 1.45% 1.011 +ATG 1.65% 1.65% 0.996 +CTG 1.47% 1.42% 1.031 +GTG 1.46% 1.42% 1.025 +TTG 1.65% 1.76% 0.938 +AAT 1.86% 1.88% 0.990 +CAT 1.65% 1.65% 0.996 +GAT 1.64% 1.61% 1.020 +TAT 1.87% 1.83% 1.019 +ACT 1.66% 1.61% 1.030 +CCT 1.45% 1.46% 0.996 +GCT 1.46% 1.46% 0.995 +TCT 1.64% 1.64% 1.004 +AGT 1.66% 1.61% 1.030 +CGT 1.47% 1.47% 1.002 +GGT 1.46% 1.39% 1.048 +TGT 1.64% 1.73% 0.945 +ATT 1.86% 1.88% 0.990 +CTT 1.64% 1.68% 0.981 +GTT 1.65% 1.67% 0.986 +TTT 1.87% 1.85% 1.016 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerMotifs.all.motifs b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.all.motifs new file mode 100644 index 0000000000000000000000000000000000000000..3784f40c0b8c75dc5a9d241b80902826fee2fa2b --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.all.motifs @@ -0,0 +1,274 @@ +>AAACAAWGGV 1-AAACAAWGGV 7.977153 -477.649721 0 T:1398.0(34.95%),B:304.7(7.64%),P:1e-207 Tpos:247.6,Tstd:121.7,Bpos:249.9,Bstd:149.3,StrandBias:0.1,Multiplicity:1.51 +0.503 0.062 0.324 0.111 +0.460 0.190 0.168 0.182 +0.972 0.023 0.001 0.004 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.544 0.001 0.022 0.433 +0.107 0.001 0.891 0.001 +0.239 0.107 0.653 0.001 +0.337 0.339 0.302 0.022 +>YCCATTGTTH 2-YCCATTGTTH 7.297898 -388.098645 0 T:1983.0(49.58%),B:810.9(20.34%),P:1e-168 Tpos:249.2,Tstd:122.2,Bpos:251.2,Bstd:145.0,StrandBias:0.1,Multiplicity:1.42 +0.192 0.349 0.161 0.299 +0.001 0.479 0.240 0.280 +0.001 0.745 0.001 0.253 +0.607 0.001 0.001 0.391 +0.001 0.027 0.001 0.971 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.012 0.001 0.001 0.986 +0.235 0.170 0.201 0.395 +0.262 0.376 0.133 0.230 +>CCATTGTTTB 3-CCATTGTTTB 6.732604 -283.261857 0 T:2115.0(52.88%),B:1081.5(27.13%),P:1e-123 Tpos:253.2,Tstd:128.1,Bpos:253.1,Bstd:154.4,StrandBias:0.1,Multiplicity:1.27 +0.070 0.453 0.274 0.204 +0.001 0.577 0.001 0.421 +0.483 0.256 0.001 0.260 +0.001 0.189 0.001 0.809 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.179 0.162 0.139 0.520 +0.117 0.261 0.144 0.478 +0.179 0.238 0.239 0.344 +>NNWACAAWGG 4-NNWACAAWGG 5.813508 -243.574450 0 T:2465.0(61.62%),B:1484.0(37.23%),P:1e-105 Tpos:248.9,Tstd:128.2,Bpos:247.9,Bstd:147.4,StrandBias:0.1,Multiplicity:1.23 +0.273 0.231 0.239 0.257 +0.298 0.209 0.288 0.205 +0.379 0.188 0.177 0.256 +0.697 0.126 0.012 0.165 +0.005 0.767 0.062 0.166 +0.958 0.023 0.003 0.016 +0.830 0.012 0.146 0.012 +0.412 0.019 0.220 0.349 +0.060 0.118 0.792 0.030 +0.309 0.198 0.468 0.025 +>DGGGCGKRGC 5-DGGGCGKRGC 8.088729 -168.212734 0 T:723.0(18.07%),B:212.1(5.32%),P:1e-73 Tpos:253.3,Tstd:125.9,Bpos:254.5,Bstd:137.8,StrandBias:0.1,Multiplicity:1.26 +0.327 0.027 0.266 0.380 +0.346 0.006 0.647 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.010 0.988 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.041 0.513 0.445 +0.367 0.188 0.378 0.067 +0.198 0.117 0.658 0.027 +0.140 0.661 0.001 0.198 +>YCCATTCATV 6-YCCATTCATV 7.957512 -102.257713 0 T:660.0(16.50%),B:262.8(6.59%),P:1e-44 Tpos:252.5,Tstd:118.2,Bpos:254.6,Bstd:145.4,StrandBias:0.1,Multiplicity:1.12 +0.064 0.373 0.221 0.342 +0.001 0.603 0.143 0.253 +0.001 0.816 0.001 0.182 +0.752 0.001 0.001 0.246 +0.001 0.001 0.001 0.997 +0.001 0.045 0.001 0.953 +0.001 0.833 0.165 0.001 +0.997 0.001 0.001 0.001 +0.037 0.015 0.102 0.846 +0.342 0.316 0.288 0.054 +>GRCCAATCGG 7-GRCCAATCGG 7.881463 -100.094038 0 T:557.0(13.93%),B:198.1(4.97%),P:1e-43 Tpos:256.8,Tstd:120.7,Bpos:252.3,Bstd:145.4,StrandBias:0.0,Multiplicity:1.19 +0.272 0.195 0.532 0.001 +0.328 0.059 0.477 0.136 +0.001 0.980 0.001 0.018 +0.001 0.997 0.001 0.001 +0.630 0.001 0.212 0.157 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.183 0.526 0.037 0.254 +0.011 0.001 0.987 0.001 +0.046 0.051 0.871 0.032 +>BAYTTCCGGH 8-BAYTTCCGGH 8.326461 -27.204860 0 T:154.0(3.85%),B:56.0(1.40%),P:1e-11 Tpos:264.5,Tstd:130.4,Bpos:263.5,Bstd:139.2,StrandBias:-0.2,Multiplicity:1.06 +0.149 0.340 0.223 0.288 +0.745 0.173 0.045 0.037 +0.055 0.387 0.209 0.349 +0.102 0.023 0.077 0.798 +0.091 0.027 0.088 0.794 +0.083 0.885 0.020 0.012 +0.001 0.895 0.103 0.001 +0.025 0.043 0.855 0.077 +0.140 0.175 0.590 0.095 +0.238 0.294 0.082 0.386 +>DGGVNCCWTTGT 1-DGGVNCCWTTGT 7.745431 -646.936096 0 T:1557.0(38.92%),B:263.1(6.60%),P:1e-280 Tpos:246.4,Tstd:119.4,Bpos:241.4,Bstd:141.3,StrandBias:-0.0,Multiplicity:1.60 +0.419 0.010 0.282 0.289 +0.279 0.100 0.496 0.126 +0.247 0.210 0.496 0.048 +0.244 0.260 0.335 0.160 +0.199 0.306 0.245 0.250 +0.014 0.520 0.220 0.246 +0.021 0.687 0.042 0.250 +0.458 0.175 0.003 0.364 +0.001 0.070 0.001 0.928 +0.001 0.001 0.001 0.997 +0.018 0.033 0.948 0.001 +0.125 0.001 0.001 0.873 +>AACAAWGVNNYY 2-AACAAWGVNNYY 6.738451 -466.711602 0 T:1938.0(48.45%),B:677.7(17.00%),P:1e-202 Tpos:250.6,Tstd:120.5,Bpos:244.4,Bstd:148.8,StrandBias:-0.1,Multiplicity:1.25 +0.383 0.191 0.211 0.216 +0.924 0.001 0.001 0.074 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.773 0.001 0.225 0.001 +0.341 0.028 0.189 0.441 +0.310 0.115 0.552 0.023 +0.258 0.277 0.405 0.060 +0.244 0.241 0.255 0.260 +0.202 0.294 0.243 0.261 +0.120 0.383 0.231 0.265 +0.155 0.395 0.163 0.287 +>WRGYYMCGCCCH 3-WRGYYMCGCCCH 7.901978 -168.093300 0 T:761.0(19.02%),B:235.8(5.91%),P:1e-73 Tpos:254.0,Tstd:126.1,Bpos:254.0,Bstd:137.7,StrandBias:-0.0,Multiplicity:1.22 +0.314 0.154 0.167 0.366 +0.388 0.159 0.280 0.173 +0.324 0.087 0.480 0.109 +0.079 0.452 0.146 0.323 +0.081 0.344 0.125 0.449 +0.420 0.568 0.009 0.003 +0.001 0.997 0.001 0.001 +0.029 0.001 0.934 0.036 +0.009 0.985 0.003 0.003 +0.003 0.978 0.018 0.001 +0.003 0.654 0.018 0.325 +0.388 0.264 0.105 0.242 +>AATGAATGGRCC 4-AATGAATGGRCC 9.843291 -104.870845 0 T:249.0(6.22%),B:29.2(0.73%),P:1e-45 Tpos:246.5,Tstd:109.9,Bpos:259.1,Bstd:155.7,StrandBias:0.1,Multiplicity:1.03 +0.490 0.107 0.259 0.144 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.248 0.001 0.001 0.750 +0.192 0.001 0.806 0.001 +0.177 0.001 0.821 0.001 +0.390 0.161 0.447 0.001 +0.036 0.493 0.305 0.166 +0.053 0.767 0.001 0.179 +>NVGCCDATYGGH 5-NVGCCDATYGGH 7.916613 -102.443439 0 T:589.0(14.72%),B:215.7(5.41%),P:1e-44 Tpos:257.6,Tstd:122.1,Bpos:260.6,Bstd:141.2,StrandBias:0.0,Multiplicity:1.20 +0.240 0.297 0.214 0.249 +0.259 0.284 0.325 0.132 +0.245 0.142 0.404 0.210 +0.001 0.927 0.001 0.071 +0.001 0.997 0.001 0.001 +0.367 0.079 0.323 0.231 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.203 0.370 0.001 0.427 +0.001 0.001 0.997 0.001 +0.199 0.001 0.644 0.156 +0.210 0.340 0.151 0.299 +>AAGGAACAATTG 6-AAGGAACAATTG 8.965680 -31.001112 0 T:63.0(1.57%),B:5.8(0.14%),P:1e-13 Tpos:257.7,Tstd:114.0,Bpos:291.6,Bstd:64.5,StrandBias:-0.6,Multiplicity:1.00 +0.717 0.171 0.108 0.004 +0.544 0.102 0.133 0.221 +0.192 0.070 0.624 0.114 +0.149 0.105 0.544 0.202 +0.662 0.005 0.245 0.088 +0.610 0.053 0.151 0.186 +0.083 0.756 0.078 0.083 +0.578 0.117 0.182 0.123 +0.672 0.066 0.135 0.127 +0.004 0.160 0.162 0.674 +0.115 0.101 0.104 0.680 +0.081 0.081 0.752 0.086 +>CCATTGTT 1-CCATTGTT 7.403096 -378.127440 0 T:1528.0(38.20%),B:483.3(12.12%),P:1e-164 Tpos:248.7,Tstd:125.0,Bpos:249.5,Bstd:150.9,StrandBias:0.0,Multiplicity:1.52 +0.001 0.838 0.089 0.072 +0.001 0.892 0.001 0.106 +0.684 0.027 0.001 0.288 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.018 0.001 0.012 0.969 +0.069 0.051 0.072 0.808 +>GKCTTTGT 2-GKCTTTGT 3.391840 -315.247951 0 T:2013.0(50.32%),B:940.9(23.60%),P:1e-136 Tpos:248.3,Tstd:119.6,Bpos:246.8,Bstd:145.2,StrandBias:0.0,Multiplicity:1.55 +0.001 0.351 0.507 0.141 +0.001 0.005 0.431 0.563 +0.001 0.997 0.001 0.001 +0.345 0.001 0.001 0.653 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +>CYTTTGTT 3-CYTTTGTT 7.951910 -246.707833 0 T:1325.0(33.12%),B:505.6(12.68%),P:1e-107 Tpos:254.3,Tstd:125.6,Bpos:255.6,Bstd:149.5,StrandBias:-0.1,Multiplicity:1.08 +0.001 0.854 0.141 0.004 +0.001 0.472 0.001 0.526 +0.373 0.001 0.001 0.625 +0.001 0.401 0.001 0.597 +0.001 0.001 0.001 0.997 +0.109 0.001 0.889 0.001 +0.121 0.001 0.001 0.877 +0.025 0.025 0.025 0.925 +>CCTATTGT 4-CCTATTGT 7.941009 -117.312516 0 T:889.0(22.23%),B:396.4(9.94%),P:1e-50 Tpos:250.9,Tstd:131.5,Bpos:246.5,Bstd:150.7,StrandBias:-0.0,Multiplicity:1.13 +0.101 0.511 0.192 0.196 +0.001 0.848 0.047 0.104 +0.001 0.001 0.001 0.997 +0.860 0.035 0.001 0.104 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.035 0.001 0.001 0.963 +>GGGCGGAG 5-GGGCGGAG 7.053362 -114.366633 0 T:894.0(22.35%),B:405.6(10.18%),P:1e-49 Tpos:248.6,Tstd:130.0,Bpos:241.7,Bstd:141.6,StrandBias:-0.1,Multiplicity:1.25 +0.134 0.001 0.864 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.792 0.206 +0.738 0.055 0.206 0.001 +0.136 0.001 0.862 0.001 +>CCATTCAT 6-CCATTCAT 8.401474 -102.655927 0 T:652.0(16.30%),B:256.2(6.43%),P:1e-44 Tpos:247.7,Tstd:120.0,Bpos:240.2,Bstd:147.2,StrandBias:0.1,Multiplicity:1.11 +0.001 0.997 0.001 0.001 +0.001 0.804 0.001 0.194 +0.773 0.001 0.001 0.225 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.887 0.111 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +>AYCCTTGT 7-AYCCTTGT 4.988747 -95.484135 0 T:1044.0(26.10%),B:558.4(14.01%),P:1e-41 Tpos:251.6,Tstd:130.6,Bpos:259.3,Bstd:147.6,StrandBias:-0.1,Multiplicity:1.14 +0.997 0.001 0.001 0.001 +0.001 0.494 0.076 0.430 +0.001 0.997 0.001 0.001 +0.030 0.925 0.001 0.044 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +>CCAATCGG 8-CCAATCGG 7.893395 -85.675268 0 T:662.0(16.55%),B:292.2(7.33%),P:1e-37 Tpos:254.4,Tstd:124.8,Bpos:247.9,Bstd:147.9,StrandBias:0.1,Multiplicity:1.23 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.785 0.001 0.067 0.147 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.152 0.683 0.088 0.077 +0.001 0.001 0.997 0.001 +0.091 0.001 0.907 0.001 +>GGCGTAGC 9-GGCGTAGC 9.158752 -56.749078 0 T:372.0(9.30%),B:146.1(3.67%),P:1e-24 Tpos:251.3,Tstd:126.6,Bpos:262.2,Bstd:132.1,StrandBias:0.3,Multiplicity:1.05 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.766 0.232 0.001 0.001 +0.362 0.001 0.636 0.001 +0.001 0.997 0.001 0.001 +>AACAAGGG 10-AACAAGGG 7.996592 -48.039847 0 T:644.0(16.10%),B:362.9(9.10%),P:1e-20 Tpos:247.4,Tstd:118.8,Bpos:250.7,Bstd:138.6,StrandBias:0.2,Multiplicity:1.09 +0.809 0.001 0.084 0.106 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.190 0.001 0.808 0.001 +0.211 0.110 0.678 0.001 +>CCGGAAGT 11-CCGGAAGT 9.037943 -18.900278 0 T:282.0(7.05%),B:164.2(4.12%),P:1e-8 Tpos:262.3,Tstd:136.0,Bpos:270.9,Bstd:146.3,StrandBias:0.0,Multiplicity:1.08 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.831 0.001 0.001 0.167 +0.997 0.001 0.001 0.001 +0.215 0.001 0.783 0.001 +0.001 0.001 0.001 0.997 +>TGTATTGT 12-TGTATTGT 9.957625 -14.541802 0 T:240.0(6.00%),B:145.8(3.66%),P:1e-6 Tpos:245.7,Tstd:130.1,Bpos:242.0,Bstd:156.1,StrandBias:0.0,Multiplicity:1.04 +0.001 0.329 0.001 0.669 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs10 b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs10 new file mode 100644 index 0000000000000000000000000000000000000000..b8029580b8c2bdcd21525e3b8f7849ded43e37f0 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs10 @@ -0,0 +1,88 @@ +>AAACAAWGGV 1-AAACAAWGGV 7.977153 -477.649721 0 T:1398.0(34.95%),B:304.7(7.64%),P:1e-207 Tpos:247.6,Tstd:121.7,Bpos:249.9,Bstd:149.3,StrandBias:0.1,Multiplicity:1.51 +0.503 0.062 0.324 0.111 +0.460 0.190 0.168 0.182 +0.972 0.023 0.001 0.004 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.544 0.001 0.022 0.433 +0.107 0.001 0.891 0.001 +0.239 0.107 0.653 0.001 +0.337 0.339 0.302 0.022 +>YCCATTGTTH 2-YCCATTGTTH 7.297898 -388.098645 0 T:1983.0(49.58%),B:810.9(20.34%),P:1e-168 Tpos:249.2,Tstd:122.2,Bpos:251.2,Bstd:145.0,StrandBias:0.1,Multiplicity:1.42 +0.192 0.349 0.161 0.299 +0.001 0.479 0.240 0.280 +0.001 0.745 0.001 0.253 +0.607 0.001 0.001 0.391 +0.001 0.027 0.001 0.971 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.012 0.001 0.001 0.986 +0.235 0.170 0.201 0.395 +0.262 0.376 0.133 0.230 +>CCATTGTTTB 3-CCATTGTTTB 6.732604 -283.261857 0 T:2115.0(52.88%),B:1081.5(27.13%),P:1e-123 Tpos:253.2,Tstd:128.1,Bpos:253.1,Bstd:154.4,StrandBias:0.1,Multiplicity:1.27 +0.070 0.453 0.274 0.204 +0.001 0.577 0.001 0.421 +0.483 0.256 0.001 0.260 +0.001 0.189 0.001 0.809 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.179 0.162 0.139 0.520 +0.117 0.261 0.144 0.478 +0.179 0.238 0.239 0.344 +>NNWACAAWGG 4-NNWACAAWGG 5.813508 -243.574450 0 T:2465.0(61.62%),B:1484.0(37.23%),P:1e-105 Tpos:248.9,Tstd:128.2,Bpos:247.9,Bstd:147.4,StrandBias:0.1,Multiplicity:1.23 +0.273 0.231 0.239 0.257 +0.298 0.209 0.288 0.205 +0.379 0.188 0.177 0.256 +0.697 0.126 0.012 0.165 +0.005 0.767 0.062 0.166 +0.958 0.023 0.003 0.016 +0.830 0.012 0.146 0.012 +0.412 0.019 0.220 0.349 +0.060 0.118 0.792 0.030 +0.309 0.198 0.468 0.025 +>DGGGCGKRGC 5-DGGGCGKRGC 8.088729 -168.212734 0 T:723.0(18.07%),B:212.1(5.32%),P:1e-73 Tpos:253.3,Tstd:125.9,Bpos:254.5,Bstd:137.8,StrandBias:0.1,Multiplicity:1.26 +0.327 0.027 0.266 0.380 +0.346 0.006 0.647 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.010 0.988 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.041 0.513 0.445 +0.367 0.188 0.378 0.067 +0.198 0.117 0.658 0.027 +0.140 0.661 0.001 0.198 +>YCCATTCATV 6-YCCATTCATV 7.957512 -102.257713 0 T:660.0(16.50%),B:262.8(6.59%),P:1e-44 Tpos:252.5,Tstd:118.2,Bpos:254.6,Bstd:145.4,StrandBias:0.1,Multiplicity:1.12 +0.064 0.373 0.221 0.342 +0.001 0.603 0.143 0.253 +0.001 0.816 0.001 0.182 +0.752 0.001 0.001 0.246 +0.001 0.001 0.001 0.997 +0.001 0.045 0.001 0.953 +0.001 0.833 0.165 0.001 +0.997 0.001 0.001 0.001 +0.037 0.015 0.102 0.846 +0.342 0.316 0.288 0.054 +>GRCCAATCGG 7-GRCCAATCGG 7.881463 -100.094038 0 T:557.0(13.93%),B:198.1(4.97%),P:1e-43 Tpos:256.8,Tstd:120.7,Bpos:252.3,Bstd:145.4,StrandBias:0.0,Multiplicity:1.19 +0.272 0.195 0.532 0.001 +0.328 0.059 0.477 0.136 +0.001 0.980 0.001 0.018 +0.001 0.997 0.001 0.001 +0.630 0.001 0.212 0.157 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.183 0.526 0.037 0.254 +0.011 0.001 0.987 0.001 +0.046 0.051 0.871 0.032 +>BAYTTCCGGH 8-BAYTTCCGGH 8.326461 -27.204860 0 T:154.0(3.85%),B:56.0(1.40%),P:1e-11 Tpos:264.5,Tstd:130.4,Bpos:263.5,Bstd:139.2,StrandBias:-0.2,Multiplicity:1.06 +0.149 0.340 0.223 0.288 +0.745 0.173 0.045 0.037 +0.055 0.387 0.209 0.349 +0.102 0.023 0.077 0.798 +0.091 0.027 0.088 0.794 +0.083 0.885 0.020 0.012 +0.001 0.895 0.103 0.001 +0.025 0.043 0.855 0.077 +0.140 0.175 0.590 0.095 +0.238 0.294 0.082 0.386 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs12 b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs12 new file mode 100644 index 0000000000000000000000000000000000000000..7f376ca01f90292bdbcc55330b4baa022a387a9b --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs12 @@ -0,0 +1,78 @@ +>DGGVNCCWTTGT 1-DGGVNCCWTTGT 7.745431 -646.936096 0 T:1557.0(38.92%),B:263.1(6.60%),P:1e-280 Tpos:246.4,Tstd:119.4,Bpos:241.4,Bstd:141.3,StrandBias:-0.0,Multiplicity:1.60 +0.419 0.010 0.282 0.289 +0.279 0.100 0.496 0.126 +0.247 0.210 0.496 0.048 +0.244 0.260 0.335 0.160 +0.199 0.306 0.245 0.250 +0.014 0.520 0.220 0.246 +0.021 0.687 0.042 0.250 +0.458 0.175 0.003 0.364 +0.001 0.070 0.001 0.928 +0.001 0.001 0.001 0.997 +0.018 0.033 0.948 0.001 +0.125 0.001 0.001 0.873 +>AACAAWGVNNYY 2-AACAAWGVNNYY 6.738451 -466.711602 0 T:1938.0(48.45%),B:677.7(17.00%),P:1e-202 Tpos:250.6,Tstd:120.5,Bpos:244.4,Bstd:148.8,StrandBias:-0.1,Multiplicity:1.25 +0.383 0.191 0.211 0.216 +0.924 0.001 0.001 0.074 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.773 0.001 0.225 0.001 +0.341 0.028 0.189 0.441 +0.310 0.115 0.552 0.023 +0.258 0.277 0.405 0.060 +0.244 0.241 0.255 0.260 +0.202 0.294 0.243 0.261 +0.120 0.383 0.231 0.265 +0.155 0.395 0.163 0.287 +>WRGYYMCGCCCH 3-WRGYYMCGCCCH 7.901978 -168.093300 0 T:761.0(19.02%),B:235.8(5.91%),P:1e-73 Tpos:254.0,Tstd:126.1,Bpos:254.0,Bstd:137.7,StrandBias:-0.0,Multiplicity:1.22 +0.314 0.154 0.167 0.366 +0.388 0.159 0.280 0.173 +0.324 0.087 0.480 0.109 +0.079 0.452 0.146 0.323 +0.081 0.344 0.125 0.449 +0.420 0.568 0.009 0.003 +0.001 0.997 0.001 0.001 +0.029 0.001 0.934 0.036 +0.009 0.985 0.003 0.003 +0.003 0.978 0.018 0.001 +0.003 0.654 0.018 0.325 +0.388 0.264 0.105 0.242 +>AATGAATGGRCC 4-AATGAATGGRCC 9.843291 -104.870845 0 T:249.0(6.22%),B:29.2(0.73%),P:1e-45 Tpos:246.5,Tstd:109.9,Bpos:259.1,Bstd:155.7,StrandBias:0.1,Multiplicity:1.03 +0.490 0.107 0.259 0.144 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.248 0.001 0.001 0.750 +0.192 0.001 0.806 0.001 +0.177 0.001 0.821 0.001 +0.390 0.161 0.447 0.001 +0.036 0.493 0.305 0.166 +0.053 0.767 0.001 0.179 +>NVGCCDATYGGH 5-NVGCCDATYGGH 7.916613 -102.443439 0 T:589.0(14.72%),B:215.7(5.41%),P:1e-44 Tpos:257.6,Tstd:122.1,Bpos:260.6,Bstd:141.2,StrandBias:0.0,Multiplicity:1.20 +0.240 0.297 0.214 0.249 +0.259 0.284 0.325 0.132 +0.245 0.142 0.404 0.210 +0.001 0.927 0.001 0.071 +0.001 0.997 0.001 0.001 +0.367 0.079 0.323 0.231 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.203 0.370 0.001 0.427 +0.001 0.001 0.997 0.001 +0.199 0.001 0.644 0.156 +0.210 0.340 0.151 0.299 +>AAGGAACAATTG 6-AAGGAACAATTG 8.965680 -31.001112 0 T:63.0(1.57%),B:5.8(0.14%),P:1e-13 Tpos:257.7,Tstd:114.0,Bpos:291.6,Bstd:64.5,StrandBias:-0.6,Multiplicity:1.00 +0.717 0.171 0.108 0.004 +0.544 0.102 0.133 0.221 +0.192 0.070 0.624 0.114 +0.149 0.105 0.544 0.202 +0.662 0.005 0.245 0.088 +0.610 0.053 0.151 0.186 +0.083 0.756 0.078 0.083 +0.578 0.117 0.182 0.123 +0.672 0.066 0.135 0.127 +0.004 0.160 0.162 0.674 +0.115 0.101 0.104 0.680 +0.081 0.081 0.752 0.086 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs8 b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs8 new file mode 100644 index 0000000000000000000000000000000000000000..ede637980ff7c6555b11901e575b4f66a7f9e8b7 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerMotifs.motifs8 @@ -0,0 +1,108 @@ +>CCATTGTT 1-CCATTGTT 7.403096 -378.127440 0 T:1528.0(38.20%),B:483.3(12.12%),P:1e-164 Tpos:248.7,Tstd:125.0,Bpos:249.5,Bstd:150.9,StrandBias:0.0,Multiplicity:1.52 +0.001 0.838 0.089 0.072 +0.001 0.892 0.001 0.106 +0.684 0.027 0.001 0.288 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.018 0.001 0.012 0.969 +0.069 0.051 0.072 0.808 +>GKCTTTGT 2-GKCTTTGT 3.391840 -315.247951 0 T:2013.0(50.32%),B:940.9(23.60%),P:1e-136 Tpos:248.3,Tstd:119.6,Bpos:246.8,Bstd:145.2,StrandBias:0.0,Multiplicity:1.55 +0.001 0.351 0.507 0.141 +0.001 0.005 0.431 0.563 +0.001 0.997 0.001 0.001 +0.345 0.001 0.001 0.653 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +>CYTTTGTT 3-CYTTTGTT 7.951910 -246.707833 0 T:1325.0(33.12%),B:505.6(12.68%),P:1e-107 Tpos:254.3,Tstd:125.6,Bpos:255.6,Bstd:149.5,StrandBias:-0.1,Multiplicity:1.08 +0.001 0.854 0.141 0.004 +0.001 0.472 0.001 0.526 +0.373 0.001 0.001 0.625 +0.001 0.401 0.001 0.597 +0.001 0.001 0.001 0.997 +0.109 0.001 0.889 0.001 +0.121 0.001 0.001 0.877 +0.025 0.025 0.025 0.925 +>CCTATTGT 4-CCTATTGT 7.941009 -117.312516 0 T:889.0(22.23%),B:396.4(9.94%),P:1e-50 Tpos:250.9,Tstd:131.5,Bpos:246.5,Bstd:150.7,StrandBias:-0.0,Multiplicity:1.13 +0.101 0.511 0.192 0.196 +0.001 0.848 0.047 0.104 +0.001 0.001 0.001 0.997 +0.860 0.035 0.001 0.104 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.035 0.001 0.001 0.963 +>GGGCGGAG 5-GGGCGGAG 7.053362 -114.366633 0 T:894.0(22.35%),B:405.6(10.18%),P:1e-49 Tpos:248.6,Tstd:130.0,Bpos:241.7,Bstd:141.6,StrandBias:-0.1,Multiplicity:1.25 +0.134 0.001 0.864 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.792 0.206 +0.738 0.055 0.206 0.001 +0.136 0.001 0.862 0.001 +>CCATTCAT 6-CCATTCAT 8.401474 -102.655927 0 T:652.0(16.30%),B:256.2(6.43%),P:1e-44 Tpos:247.7,Tstd:120.0,Bpos:240.2,Bstd:147.2,StrandBias:0.1,Multiplicity:1.11 +0.001 0.997 0.001 0.001 +0.001 0.804 0.001 0.194 +0.773 0.001 0.001 0.225 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.887 0.111 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +>AYCCTTGT 7-AYCCTTGT 4.988747 -95.484135 0 T:1044.0(26.10%),B:558.4(14.01%),P:1e-41 Tpos:251.6,Tstd:130.6,Bpos:259.3,Bstd:147.6,StrandBias:-0.1,Multiplicity:1.14 +0.997 0.001 0.001 0.001 +0.001 0.494 0.076 0.430 +0.001 0.997 0.001 0.001 +0.030 0.925 0.001 0.044 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +>CCAATCGG 8-CCAATCGG 7.893395 -85.675268 0 T:662.0(16.55%),B:292.2(7.33%),P:1e-37 Tpos:254.4,Tstd:124.8,Bpos:247.9,Bstd:147.9,StrandBias:0.1,Multiplicity:1.23 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.785 0.001 0.067 0.147 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.152 0.683 0.088 0.077 +0.001 0.001 0.997 0.001 +0.091 0.001 0.907 0.001 +>GGCGTAGC 9-GGCGTAGC 9.158752 -56.749078 0 T:372.0(9.30%),B:146.1(3.67%),P:1e-24 Tpos:251.3,Tstd:126.6,Bpos:262.2,Bstd:132.1,StrandBias:0.3,Multiplicity:1.05 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.766 0.232 0.001 0.001 +0.362 0.001 0.636 0.001 +0.001 0.997 0.001 0.001 +>AACAAGGG 10-AACAAGGG 7.996592 -48.039847 0 T:644.0(16.10%),B:362.9(9.10%),P:1e-20 Tpos:247.4,Tstd:118.8,Bpos:250.7,Bstd:138.6,StrandBias:0.2,Multiplicity:1.09 +0.809 0.001 0.084 0.106 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.190 0.001 0.808 0.001 +0.211 0.110 0.678 0.001 +>CCGGAAGT 11-CCGGAAGT 9.037943 -18.900278 0 T:282.0(7.05%),B:164.2(4.12%),P:1e-8 Tpos:262.3,Tstd:136.0,Bpos:270.9,Bstd:146.3,StrandBias:0.0,Multiplicity:1.08 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.831 0.001 0.001 0.167 +0.997 0.001 0.001 0.001 +0.215 0.001 0.783 0.001 +0.001 0.001 0.001 0.997 +>TGTATTGT 12-TGTATTGT 9.957625 -14.541802 0 T:240.0(6.00%),B:145.8(3.66%),P:1e-6 Tpos:245.7,Tstd:130.1,Bpos:242.0,Bstd:156.1,StrandBias:0.0,Multiplicity:1.04 +0.001 0.329 0.001 0.669 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults.html b/the_code/Human/data/homer/M15_vs_M0/homerResults.html new file mode 100644 index 0000000000000000000000000000000000000000..adfe336ccd32d0f30a94c3da0bfed936416fcbae --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults.html @@ -0,0 +1,397 @@ +.// - Homer de novo Motif Results + +

Homer de novo Motif Results (.//)

+Known Motif Enrichment Results
+Gene Ontology Enrichment Results
+If Homer is having trouble matching a motif to a known motif, try copy/pasting the matrix file into +STAMP
+More information on motif finding results: HOMER + | Description of Results + | Tips +
+Total target sequences = 4000
+Total background sequences = 3988
+* - possible false positive
+ + + + + + + + + + +
RankMotifP-valuelog P-pvalue% of Targets% of BackgroundSTD(Bg STD)Best Match/DetailsMotif File
1 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + + +1e-280-6.469e+0238.92%6.60%119.4bp (141.3bp)Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer(0.973)
More Information | Similar Motifs Found		motif file (matrix)
2 + + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + +1e-73-1.682e+0218.07%5.32%125.9bp (137.8bp)Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer(0.889)
More Information | Similar Motifs Found		motif file (matrix)
3 + + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + +1e-45-1.049e+026.22%0.73%109.9bp (155.7bp)PB0178.1_Sox8_2/Jaspar(0.779)
More Information | Similar Motifs Found		motif file (matrix)
4 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + +1e-44-1.024e+0214.72%5.41%122.1bp (141.2bp)NFY(CCAAT)/Promoter/Homer(0.811)
More Information | Similar Motifs Found		motif file (matrix)
5 + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + + +1e-13-3.100e+011.57%0.14%114.0bp (64.5bp)PB0173.1_Sox21_2/Jaspar(0.771)
More Information | Similar Motifs Found		motif file (matrix)
6 +* + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + +1e-11-2.720e+013.85%1.40%130.4bp (139.2bp)Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer(0.965)
More Information | Similar Motifs Found		motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.info.html new file mode 100644 index 0000000000000000000000000000000000000000..7c86d1541c54ea66ae3bc646a6dba0bba415dcfa --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.info.html @@ -0,0 +1,1793 @@ +Motif 1 +

Information for 1-DGGVNCCWTTGT (Motif 1)

+ + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + + + +
+Reverse Opposite:
+ + C + G + T + A + + A + T + G + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + T + C + A + G + + T + C + A + G + + T + C + A + G + + A + T + G + C + + A + G + T + C + + G + A + T + C + + G + C + A + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-280
log p-value:-6.469e+02
Information Content per bp:1.580
Number of Target Sequences with motif1557.0
Percentage of Target Sequences with motif38.92%
Number of Background Sequences with motif263.1
Percentage of Background Sequences with motif6.60%
Average Position of motif in Targets246.4 +/- 119.4bp
Average Position of motif in Background241.4 +/- 141.3bp
Strand Bias (log2 ratio + to - strand density)-0.0
Multiplicity (# of sites on avg that occur together)1.60
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer

+
+ + + +
Match Rank:1
Score:0.97 +
Offset:0 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT
AGGVNCCTTTGT
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + + + +
+ + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + C + A + G + + A + G + T + C + + A + T + G + C + + A + G + T + C + + G + C + A + T + + A + G + C + T + + A + C + G + T + + A + T + C + G + + C + G + A + T + + + + +
+
+

Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132)/Homer

+
+ + + +
Match Rank:2
Score:0.92 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT---
-----CCWTTGTYYB
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + T + G + C + + A + G + T + C + + G + C + A + T + + A + G + C + T + + A + C + G + T + + T + C + A + G + + C + G + A + T + + A + G + C + T + + G + A + T + C + + A + T + C + G + + + + +
+
+

Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer

+
+ + + +
Match Rank:3
Score:0.92 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT-
-----CCWTTGTY
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + T + G + C + + G + A + T + C + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + A + G + T + + A + G + C + T + + + + +
+
+

Sox6(HMG)/Myotubes-Sox6-ChIP-Seq(GSE32627)/Homer

+
+ + + +
Match Rank:4
Score:0.90 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT---
-----CCATTGTTNY
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + T + G + C + + G + T + A + C + + C + G + T + A + + A + G + C + T + + G + C + A + T + + T + A + C + G + + A + G + C + T + + A + G + C + T + + A + G + T + C + + A + G + C + T + + + + +
+
+

SOX15/MA1152.1/Jaspar

+
+ + + +
Match Rank:5
Score:0.89 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT---
-----CTATTGTTTT
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + G + A + C + T + + C + G + T + A + + A + C + G + T + + C + G + A + T + + T + C + A + G + + C + G + A + T + + G + A + C + T + + G + A + C + T + + G + C + A + T + + + + +
+
+

SOX13/MA1120.1/Jaspar

+
+ + + +
Match Rank:6
Score:0.89 +
Offset:3 +
Orientation:reverse strand
Alignment:DGGVNCCWTTGT--
---NNCCATTGTNN
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + G + T + C + + G + A + T + C + + C + G + T + A + + G + A + C + T + + C + G + A + T + + T + C + A + G + + G + A + C + T + + A + G + C + T + + G + A + C + T + + + + +
+
+

Sox15(HMG)/CPA-Sox15-ChIP-Seq(GSE62909)/Homer

+
+ + + +
Match Rank:7
Score:0.89 +
Offset:4 +
Orientation:reverse strand
Alignment:DGGVNCCWTTGT--
----NCCATTGTTY
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + A + G + + A + G + T + C + + G + A + T + C + + G + C + T + A + + C + G + A + T + + A + C + G + T + + A + T + C + G + + A + C + G + T + + A + G + C + T + + G + A + C + T + + + + +
+
+

Sox2/MA0143.3/Jaspar

+
+ + + +
Match Rank:8
Score:0.89 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT-
-----CCTTTGTT
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + C + T + + + + +
+
+

Sox17(HMG)/Endoderm-Sox17-ChIP-Seq(GSE61475)/Homer

+
+ + + +
Match Rank:9
Score:0.88 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT---
-----CCATTGTTYB
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + T + G + C + + G + A + T + C + + C + G + T + A + + A + G + C + T + + C + A + G + T + + A + T + C + G + + G + C + A + T + + A + G + C + T + + G + A + C + T + + A + C + T + G + + + + +
+
+

Sox6/MA0515.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.87 +
Offset:5 +
Orientation:forward strand
Alignment:DGGVNCCWTTGT---
-----CCATTGTTTT
+		 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + C + T + + G + A + C + T + + A + G + C + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..0569e140113989296bb4d9107f02583f2248aff7 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.logo.svg @@ -0,0 +1,64 @@ + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.motif new file mode 100644 index 0000000000000000000000000000000000000000..c92b960b76d894b25e888b1a1934fd93fb9d2fff --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.motif @@ -0,0 +1,13 @@ +>DGGVNCCWTTGT 1-DGGVNCCWTTGT,BestGuess:Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer(0.973) 7.745431 -646.936096 0 T:1557.0(38.92%),B:263.1(6.60%),P:1e-280 +0.419 0.010 0.282 0.289 +0.279 0.100 0.496 0.126 +0.247 0.210 0.496 0.048 +0.244 0.260 0.335 0.160 +0.199 0.306 0.245 0.250 +0.014 0.520 0.220 0.246 +0.021 0.687 0.042 0.250 +0.458 0.175 0.003 0.364 +0.001 0.070 0.001 0.928 +0.001 0.001 0.001 0.997 +0.018 0.033 0.948 0.001 +0.125 0.001 0.001 0.873 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..887579134e15b36f21353c7821dc87161ebc5bc4 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar.html @@ -0,0 +1,764 @@ +motif1 +

Information for motif1

+ + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + T + A + C + G + + C + G + A + T + + + +
+Reverse Opposite:
+ + C + G + T + A + + A + T + G + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + T + C + A + G + + T + C + A + G + + T + C + A + G + + A + T + G + C + + A + G + T + C + + G + A + T + C + + G + C + A + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-280
log p-value:-6.469e+02
Information Content per bp:1.580
Number of Target Sequences with motif1557.0
Percentage of Target Sequences with motif38.92%
Number of Background Sequences with motif263.1
Percentage of Background Sequences with motif6.60%
Average Position of motif in Targets246.4 +/- 119.4bp
Average Position of motif in Background241.4 +/- 141.3bp
Strand Bias (log2 ratio + to - strand density)-0.0
Multiplicity (# of sites on avg that occur together)1.60
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + + + + + + + + + + + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.910 + + C + T + G + A + + G + T + C + A + + G + T + C + A + + A + G + T + C + + C + G + T + A + + C + G + T + A + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + G + A + C + + + + +1e-207-477.64972134.95%7.64%motif file (matrix)
20.961 + + C + G + T + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + T + C + A + G + + T + A + C + G + + C + A + G + T + + A + G + T + C + + A + G + T + C + + A + G + T + C + + + + +1e-202-466.71160248.45%17.00%motif file (matrix)
30.935 + + G + A + T + C + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + G + C + T + + A + C + G + T + + A + C + T + G + + C + G + A + T + + C + G + A + T + + G + T + A + C + + + + +1e-168-388.09864549.58%20.34%motif file (matrix)
40.880 + + A + T + G + C + + A + G + T + C + + G + C + T + A + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + A + T + + C + A + G + T + + + + +1e-164-378.12744038.20%12.12%motif file (matrix)
50.858 + + A + T + C + G + + A + C + G + T + + A + G + T + C + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + + + +1e-136-315.24795150.32%23.60%motif file (matrix)
60.904 + + A + T + G + C + + A + G + T + C + + G + C + T + A + + A + G + C + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + G + C + A + T + + A + G + C + T + + A + C + G + T + + + + +1e-123-283.26185752.88%27.13%motif file (matrix)
70.782 + + A + T + G + C + + A + G + C + T + + C + G + A + T + + A + G + C + T + + A + C + G + T + + C + T + A + G + + C + G + A + T + + A + C + G + T + + + + +1e-107-246.70783333.12%12.68%motif file (matrix)
80.919 + + C + G + T + A + + T + C + G + A + + G + C + T + A + + G + C + T + A + + A + G + T + C + + G + T + C + A + + C + T + G + A + + C + G + T + A + + T + A + C + G + + T + C + A + G + + + + +1e-105-243.57445061.62%37.23%motif file (matrix)
90.786 + + A + G + T + C + + A + G + T + C + + A + C + G + T + + G + C + T + A + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + G + A + T + + + + +1e-50-117.31251622.23%9.94%motif file (matrix)
100.756 + + C + G + T + A + + A + G + T + C + + A + G + T + C + + G + A + T + C + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + + + +1e-41-95.48413526.10%14.01%motif file (matrix)
110.787 + + C + G + T + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + T + G + + C + T + A + G + + T + C + A + G + + + + +1e-20-48.03984716.10%9.10%motif file (matrix)
120.678 + + A + G + C + T + + A + C + T + G + + A + C + G + T + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + + + +1e-6-14.5418026.00%3.66%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..19d7d75c073fcc48640f1873034c3008923e2d6c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar1.motif @@ -0,0 +1,11 @@ +>AAACAAWGGV 1-AAACAAWGGV 7.977153 -477.649721 0 T:1398.0(34.95%),B:304.7(7.64%),P:1e-207 +0.503 0.062 0.324 0.111 +0.460 0.190 0.168 0.182 +0.972 0.023 0.001 0.004 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.544 0.001 0.022 0.433 +0.107 0.001 0.891 0.001 +0.239 0.107 0.653 0.001 +0.337 0.339 0.302 0.022 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar10.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar10.motif new file mode 100644 index 0000000000000000000000000000000000000000..c3ed08bbcbf320cec94e72569f3b083cf3cc29ce --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar10.motif @@ -0,0 +1,9 @@ +>AYCCTTGT 7-AYCCTTGT 4.988747 -95.484135 0 T:1044.0(26.10%),B:558.4(14.01%),P:1e-41 +0.997 0.001 0.001 0.001 +0.001 0.494 0.076 0.430 +0.001 0.997 0.001 0.001 +0.030 0.925 0.001 0.044 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar11.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar11.motif new file mode 100644 index 0000000000000000000000000000000000000000..1ad357d3622c6c2695e86a0e2324ff72990ccf88 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar11.motif @@ -0,0 +1,9 @@ +>AACAAGGG 10-AACAAGGG 7.996592 -48.039847 0 T:644.0(16.10%),B:362.9(9.10%),P:1e-20 +0.809 0.001 0.084 0.106 +0.997 0.001 0.001 0.001 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.997 0.001 +0.190 0.001 0.808 0.001 +0.211 0.110 0.678 0.001 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar12.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar12.motif new file mode 100644 index 0000000000000000000000000000000000000000..984c9f5171741186c635c8665ff4ece1bb6c235a --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar12.motif @@ -0,0 +1,9 @@ +>TGTATTGT 12-TGTATTGT 9.957625 -14.541802 0 T:240.0(6.00%),B:145.8(3.66%),P:1e-6 +0.001 0.329 0.001 0.669 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar2.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar2.motif new file mode 100644 index 0000000000000000000000000000000000000000..880af5736d0789f1fbbd38da12aabd27d3ca09e1 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar2.motif @@ -0,0 +1,13 @@ +>AACAAWGVNNYY 2-AACAAWGVNNYY 6.738451 -466.711602 0 T:1938.0(48.45%),B:677.7(17.00%),P:1e-202 +0.383 0.191 0.211 0.216 +0.924 0.001 0.001 0.074 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.773 0.001 0.225 0.001 +0.341 0.028 0.189 0.441 +0.310 0.115 0.552 0.023 +0.258 0.277 0.405 0.060 +0.244 0.241 0.255 0.260 +0.202 0.294 0.243 0.261 +0.120 0.383 0.231 0.265 +0.155 0.395 0.163 0.287 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar3.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar3.motif new file mode 100644 index 0000000000000000000000000000000000000000..fc2907f3b312423670e8d348466e24c4f6a2f006 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar3.motif @@ -0,0 +1,11 @@ +>YCCATTGTTH 2-YCCATTGTTH 7.297898 -388.098645 0 T:1983.0(49.58%),B:810.9(20.34%),P:1e-168 +0.192 0.349 0.161 0.299 +0.001 0.479 0.240 0.280 +0.001 0.745 0.001 0.253 +0.607 0.001 0.001 0.391 +0.001 0.027 0.001 0.971 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.012 0.001 0.001 0.986 +0.235 0.170 0.201 0.395 +0.262 0.376 0.133 0.230 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar4.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar4.motif new file mode 100644 index 0000000000000000000000000000000000000000..14d53889fb5a38e4c69505f333d2adf97c603728 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar4.motif @@ -0,0 +1,9 @@ +>CCATTGTT 1-CCATTGTT 7.403096 -378.127440 0 T:1528.0(38.20%),B:483.3(12.12%),P:1e-164 +0.001 0.838 0.089 0.072 +0.001 0.892 0.001 0.106 +0.684 0.027 0.001 0.288 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.018 0.001 0.012 0.969 +0.069 0.051 0.072 0.808 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar5.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar5.motif new file mode 100644 index 0000000000000000000000000000000000000000..0147839d7143d7ee8da34f84a57df65821735ce0 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar5.motif @@ -0,0 +1,9 @@ +>GKCTTTGT 2-GKCTTTGT 3.391840 -315.247951 0 T:2013.0(50.32%),B:940.9(23.60%),P:1e-136 +0.001 0.351 0.507 0.141 +0.001 0.005 0.431 0.563 +0.001 0.997 0.001 0.001 +0.345 0.001 0.001 0.653 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar6.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar6.motif new file mode 100644 index 0000000000000000000000000000000000000000..b6d1774d0d6544905204cce7c38ad30124a231d1 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar6.motif @@ -0,0 +1,11 @@ +>CCATTGTTTB 3-CCATTGTTTB 6.732604 -283.261857 0 T:2115.0(52.88%),B:1081.5(27.13%),P:1e-123 +0.070 0.453 0.274 0.204 +0.001 0.577 0.001 0.421 +0.483 0.256 0.001 0.260 +0.001 0.189 0.001 0.809 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.179 0.162 0.139 0.520 +0.117 0.261 0.144 0.478 +0.179 0.238 0.239 0.344 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar7.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar7.motif new file mode 100644 index 0000000000000000000000000000000000000000..21542d61cc351521643e2b542dbf15330e892b21 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar7.motif @@ -0,0 +1,9 @@ +>CYTTTGTT 3-CYTTTGTT 7.951910 -246.707833 0 T:1325.0(33.12%),B:505.6(12.68%),P:1e-107 +0.001 0.854 0.141 0.004 +0.001 0.472 0.001 0.526 +0.373 0.001 0.001 0.625 +0.001 0.401 0.001 0.597 +0.001 0.001 0.001 0.997 +0.109 0.001 0.889 0.001 +0.121 0.001 0.001 0.877 +0.025 0.025 0.025 0.925 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar8.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar8.motif new file mode 100644 index 0000000000000000000000000000000000000000..5bd686f1747424a68b66c86742f9feebad39b24c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar8.motif @@ -0,0 +1,11 @@ +>NNWACAAWGG 4-NNWACAAWGG 5.813508 -243.574450 0 T:2465.0(61.62%),B:1484.0(37.23%),P:1e-105 +0.273 0.231 0.239 0.257 +0.298 0.209 0.288 0.205 +0.379 0.188 0.177 0.256 +0.697 0.126 0.012 0.165 +0.005 0.767 0.062 0.166 +0.958 0.023 0.003 0.016 +0.830 0.012 0.146 0.012 +0.412 0.019 0.220 0.349 +0.060 0.118 0.792 0.030 +0.309 0.198 0.468 0.025 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar9.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar9.motif new file mode 100644 index 0000000000000000000000000000000000000000..f7079a691594309f476c1c8ce6b8a4dec6b8a675 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1.similar9.motif @@ -0,0 +1,9 @@ +>CCTATTGT 4-CCTATTGT 7.941009 -117.312516 0 T:889.0(22.23%),B:396.4(9.94%),P:1e-50 +0.101 0.511 0.192 0.196 +0.001 0.848 0.047 0.104 +0.001 0.001 0.001 0.997 +0.860 0.035 0.001 0.104 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.035 0.001 0.001 0.963 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..4ee04ffb94d6b64afd84709decd5b810c4592d89 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.logo.svg @@ -0,0 +1,64 @@ + + + C + G + T + A + + A + T + G + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + T + C + A + G + + T + C + A + G + + T + C + A + G + + A + T + G + C + + A + G + T + C + + G + A + T + C + + G + C + A + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..8e476c872038cb5e9916eef98340e39bdbcfe67f --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif1RV.motif @@ -0,0 +1,13 @@ +>ACAAWGGNBCCH 1-DGGVNCCWTTGT 7.745431 -646.936096 0 T:1557.0(38.92%),B:263.1(6.60%),P:1e-280 +0.873 0.001 0.001 0.125 +0.001 0.948 0.033 0.018 +0.997 0.001 0.001 0.001 +0.928 0.001 0.070 0.001 +0.364 0.003 0.175 0.458 +0.250 0.042 0.687 0.021 +0.246 0.220 0.520 0.014 +0.250 0.245 0.306 0.199 +0.160 0.335 0.260 0.244 +0.048 0.496 0.210 0.247 +0.126 0.496 0.100 0.279 +0.289 0.282 0.010 0.419 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.info.html new file mode 100644 index 0000000000000000000000000000000000000000..3d36c8c39413b4786533be77716cfdfbba4d4126 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.info.html @@ -0,0 +1,1643 @@ +Motif 2 +

Information for 5-DGGGCGKRGC (Motif 2)

+ + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + + +
+Reverse Opposite:
+ + C + T + A + G + + A + G + T + C + + A + G + T + C + + T + G + A + C + + A + G + T + C + + A + C + T + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + + +
+ + + + + + + + + + + + + + +
p-value:1e-73
log p-value:-1.682e+02
Information Content per bp:1.705
Number of Target Sequences with motif723.0
Percentage of Target Sequences with motif18.07%
Number of Background Sequences with motif212.1
Percentage of Background Sequences with motif5.32%
Average Position of motif in Targets253.3 +/- 125.9bp
Average Position of motif in Background254.5 +/- 137.8bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.26
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer

+
+ + + +
Match Rank:1
Score:0.89 +
Offset:-2 +
Orientation:forward strand
Alignment:--DGGGCGKRGC
RGKGGGCGGAGC
+		 + + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + + +
+ + + C + T + G + A + + T + C + A + G + + C + A + G + T + + C + T + A + G + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + C + G + + A + C + T + G + + C + T + G + A + + T + C + A + G + + G + A + T + C + + + + +
+
+

Sp2(Zf)/HEK293-Sp2.eGFP-ChIP-Seq(Encode)/Homer

+
+ + + +
Match Rank:2
Score:0.89 +
Offset:0 +
Orientation:reverse strand
Alignment:DGGGCGKRGC--
GGGGCGGGGCCR
+		 + + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + A + T + G + + C + T + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + C + T + A + G + + C + A + T + G + + C + T + A + G + + T + C + A + G + + G + A + T + C + + G + A + T + C + + T + C + A + G + + + + +
+
+

POL003.1_GC-box/Jaspar

+
+ + + +
Match Rank:3
Score:0.88 +
Offset:-2 +
Orientation:forward strand
Alignment:--DGGGCGKRGC--
AGGGGGCGGGGCTG
+		 + + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + T + A + + C + T + A + G + + C + A + T + G + + T + C + A + G + + A + C + T + G + + C + T + A + G + + G + T + A + C + + C + T + A + G + + A + C + T + G + + C + T + A + G + + C + A + T + G + + A + G + T + C + + A + G + C + T + + C + A + T + G + + + + +
+
+

KLF3(Zf)/MEF-Klf3-ChIP-Seq(GSE44748)/Homer

+
+ + + +
Match Rank:4
Score:0.87 +
Offset:-3 +
Orientation:reverse strand
Alignment:---DGGGCGKRGC--
NNVDGGGYGGGGCYN
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + A + C + G + T + + + + +
+ + + T + A + C + G + + T + G + A + C + + T + C + A + G + + C + T + G + A + + A + C + T + G + + A + C + T + G + + A + C + T + G + + A + G + C + T + + A + C + T + G + + A + C + T + G + + C + T + A + G + + A + C + T + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + + + +
+
+

Sp1(Zf)/Promoter/Homer

+
+ + + +
Match Rank:5
Score:0.87 +
Offset:-1 +
Orientation:reverse strand
Alignment:-DGGGCGKRGC-
GGGGGCGGGGCC
+		 + + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + + + +
+ + + T + C + A + G + + C + A + T + G + + C + T + A + G + + A + C + T + G + + A + C + T + G + + A + G + T + C + + A + C + T + G + + A + C + T + G + + C + T + A + G + + T + A + C + G + + A + G + T + C + + A + T + G + C + + + + +
+
+

KLF14(Zf)/HEK293-KLF14.GFP-ChIP-Seq(GSE58341)/Homer

+
+ + + +
Match Rank:6
Score:0.86 +
Offset:-2 +
Orientation:forward strand
Alignment:--DGGGCGKRGC
RGKGGGCGKGGC
+		 + + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + + +
+ + + C + T + A + G + + T + C + A + G + + C + A + G + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + C + T + A + G + + A + C + T + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + + + +
+
+

PB0039.1_Klf7_1/Jaspar

+
+ + + +
Match Rank:7
Score:0.86 +
Offset:-3 +
Orientation:reverse strand
Alignment:---DGGGCGKRGC---
NNAGGGGCGGGGTNNA
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + C + T + A + + C + G + A + T + + C + T + G + A + + C + T + A + G + + C + T + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + C + A + T + G + + A + C + T + G + + C + A + T + G + + C + A + T + G + + A + G + C + T + + G + A + T + C + + T + C + A + G + + C + G + T + A + + + + +
+
+

KLF5(Zf)/LoVo-KLF5-ChIP-Seq(GSE49402)/Homer

+
+ + + +
Match Rank:8
Score:0.86 +
Offset:0 +
Orientation:forward strand
Alignment:DGGGCGKRGC
DGGGYGKGGC
+		 + + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + + +
+ + + C + G + T + A + + C + T + A + G + + A + C + T + G + + A + C + T + G + + G + A + C + T + + C + T + A + G + + C + A + G + T + + C + T + A + G + + C + A + T + G + + G + A + T + C + + + + +
+
+

KLF5/MA0599.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.85 +
Offset:0 +
Orientation:reverse strand
Alignment:DGGGCGKRGC
GGGGNGGGGC
+		 + + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + + +
+ + + C + T + A + G + + C + T + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + A + C + T + G + + C + A + T + G + + C + T + A + G + + C + T + A + G + + T + G + A + C + + + + +
+
+

PB0180.1_Sp4_2/Jaspar

+
+ + + +
Match Rank:10
Score:0.84 +
Offset:-2 +
Orientation:forward strand
Alignment:--DGGGCGKRGC---
CAAAGGCGTGGCCAG
+		 + + + A + C + G + T + + A + C + G + T + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + G + T + C + + C + G + T + A + + C + G + T + A + + T + C + G + A + + A + T + C + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + G + T + + C + T + A + G + + A + C + T + G + + G + A + T + C + + G + A + T + C + + G + T + C + A + + C + A + T + G + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..bf5854e89e787252e63fef266f47fea677a997c4 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.logo.svg @@ -0,0 +1,54 @@ + + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.motif new file mode 100644 index 0000000000000000000000000000000000000000..e930deecdfe87b9424437c6f46eec7a0e2868328 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.motif @@ -0,0 +1,11 @@ +>DGGGCGKRGC 5-DGGGCGKRGC,BestGuess:Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer(0.889) 8.088729 -168.212734 0 T:723.0(18.07%),B:212.1(5.32%),P:1e-73 +0.327 0.027 0.266 0.380 +0.346 0.006 0.647 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.010 0.988 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.041 0.513 0.445 +0.367 0.188 0.378 0.067 +0.198 0.117 0.658 0.027 +0.140 0.661 0.001 0.198 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..23eba47885a71ce322667d3213a157f09e54ec0c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar.html @@ -0,0 +1,290 @@ +motif2 +

Information for motif2

+ + + C + G + A + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + T + A + C + + A + C + T + G + + A + C + T + G + + T + C + A + G + + T + C + A + G + + G + A + T + C + + + +
+Reverse Opposite:
+ + C + T + A + G + + A + G + T + C + + A + G + T + C + + T + G + A + C + + A + G + T + C + + A + C + T + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + + +
+ + + + + + + + + + + + + +
p-value:1e-73
log p-value:-1.682e+02
Information Content per bp:1.705
Number of Target Sequences with motif723.0
Percentage of Target Sequences with motif18.07%
Number of Background Sequences with motif212.1
Percentage of Background Sequences with motif5.32%
Average Position of motif in Targets253.3 +/- 125.9bp
Average Position of motif in Background254.5 +/- 137.8bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.26
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.973 + + C + G + A + T + + C + T + G + A + + C + T + A + G + + A + G + T + C + + A + G + C + T + + T + G + A + C + + A + G + T + C + + C + A + T + G + + G + T + A + C + + T + A + G + C + + A + G + T + C + + G + T + C + A + + + + +1e-73-168.09330019.02%5.91%motif file (matrix)
20.913 + + C + T + A + G + + A + C + T + G + + A + C + T + G + + A + G + T + C + + A + C + T + G + + A + C + T + G + + T + C + G + A + + C + T + A + G + + + + +1e-49-114.36663322.35%10.18%motif file (matrix)
30.848 + + A + C + T + G + + A + C + T + G + + A + G + T + C + + A + C + T + G + + A + C + G + T + + G + T + C + A + + C + T + A + G + + A + G + T + C + + + + +1e-24-56.7490789.30%3.67%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..2f74851336d5ca846fc93e8a1335f511932905de --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar1.motif @@ -0,0 +1,13 @@ +>WRGYYMCGCCCH 3-WRGYYMCGCCCH 7.901978 -168.093300 0 T:761.0(19.02%),B:235.8(5.91%),P:1e-73 +0.314 0.154 0.167 0.366 +0.388 0.159 0.280 0.173 +0.324 0.087 0.480 0.109 +0.079 0.452 0.146 0.323 +0.081 0.344 0.125 0.449 +0.420 0.568 0.009 0.003 +0.001 0.997 0.001 0.001 +0.029 0.001 0.934 0.036 +0.009 0.985 0.003 0.003 +0.003 0.978 0.018 0.001 +0.003 0.654 0.018 0.325 +0.388 0.264 0.105 0.242 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar2.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar2.motif new file mode 100644 index 0000000000000000000000000000000000000000..172f44e7d4cfc1bc676847a6badede6d821cf7f6 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar2.motif @@ -0,0 +1,9 @@ +>GGGCGGAG 5-GGGCGGAG 7.053362 -114.366633 0 T:894.0(22.35%),B:405.6(10.18%),P:1e-49 +0.134 0.001 0.864 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.792 0.206 +0.738 0.055 0.206 0.001 +0.136 0.001 0.862 0.001 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar3.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar3.motif new file mode 100644 index 0000000000000000000000000000000000000000..f2660de0c784d5c5815affaec97da3dff6a1873d --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2.similar3.motif @@ -0,0 +1,9 @@ +>GGCGTAGC 9-GGCGTAGC 9.158752 -56.749078 0 T:372.0(9.30%),B:146.1(3.67%),P:1e-24 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.001 0.997 +0.766 0.232 0.001 0.001 +0.362 0.001 0.636 0.001 +0.001 0.997 0.001 0.001 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..b0b16ecb31dd2be18decb1aae205df2dd997227c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.logo.svg @@ -0,0 +1,54 @@ + + + C + T + A + G + + A + G + T + C + + A + G + T + C + + T + G + A + C + + A + G + T + C + + A + C + T + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + C + T + A + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..2efe1670e95b4d119e293e85ae7e245a613821be --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif2RV.motif @@ -0,0 +1,11 @@ +>GCYMCGCCCH 5-DGGGCGKRGC 8.088729 -168.212734 0 T:723.0(18.07%),B:212.1(5.32%),P:1e-73 +0.198 0.001 0.661 0.140 +0.027 0.658 0.117 0.198 +0.067 0.378 0.188 0.367 +0.445 0.513 0.041 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.988 0.010 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.647 0.006 0.346 +0.380 0.266 0.027 0.327 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.info.html new file mode 100644 index 0000000000000000000000000000000000000000..a85d5d64c73a75168f73232e17251cfecc102aed --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.info.html @@ -0,0 +1,1833 @@ +Motif 3 +

Information for 4-AATGAATGGRCC (Motif 3)

+ + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+Reverse Opposite:
+ + C + T + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + C + G + T + + G + A + C + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-45
log p-value:-1.049e+02
Information Content per bp:1.761
Number of Target Sequences with motif249.0
Percentage of Target Sequences with motif6.22%
Number of Background Sequences with motif29.2
Percentage of Background Sequences with motif0.73%
Average Position of motif in Targets246.5 +/- 109.9bp
Average Position of motif in Background259.1 +/- 155.7bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.03
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

PB0178.1_Sox8_2/Jaspar

+
+ + + +
Match Rank:1
Score:0.78 +
Offset:-5 +
Orientation:reverse strand
Alignment:-----AATGAATGGRCC
NNTNTCATGAATGT---
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + A + T + G + C + + T + A + C + G + + C + A + G + T + + A + C + T + G + + C + G + A + T + + G + A + T + C + + T + G + C + A + + A + G + C + T + + C + T + A + G + + C + G + T + A + + T + C + G + A + + C + G + A + T + + C + T + A + G + + G + A + C + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

PB0170.1_Sox17_2/Jaspar

+
+ + + +
Match Rank:2
Score:0.75 +
Offset:-4 +
Orientation:reverse strand
Alignment:----AATGAATGGRCC-
NTTNTATGAATGTGNNC
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + A + C + G + T + + + + +
+ + + G + C + T + A + + G + C + A + T + + A + G + C + T + + C + T + A + G + + A + G + C + T + + T + C + G + A + + A + G + C + T + + A + C + T + G + + G + C + T + A + + C + T + G + A + + C + G + A + T + + T + C + A + G + + C + A + G + T + + C + A + T + G + + T + C + A + G + + C + G + A + T + + A + T + G + C + + + + +
+
+

PB0028.1_Hbp1_1/Jaspar

+
+ + + +
Match Rank:3
Score:0.74 +
Offset:-6 +
Orientation:forward strand
Alignment:------AATGAATGGRCC
ACTATGAATGAATGAT--
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + G + C + T + A + + G + T + A + C + + C + G + A + T + + G + C + T + A + + G + C + A + T + + T + A + C + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + A + C + T + G + + C + T + G + A + + T + C + G + A + + G + A + C + T + + C + A + T + G + + C + T + G + A + + A + G + C + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

RBM46(RRM)/Homo_sapiens-RNCMPT00054-PBM/HughesRNA

+
+ + + +
Match Rank:4
Score:0.72 +
Offset:0 +
Orientation:forward strand
Alignment:AATGAATGGRCC
AATCAAN-----
+		 + + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + T + G + C + + C + G + T + A + + C + G + T + A + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Hoxa10(Homeobox)/ChickenMSG-Hoxa10.Flag-ChIP-Seq(GSE86088)/Homer

+
+ + + +
Match Rank:5
Score:0.71 +
Offset:-3 +
Orientation:forward strand
Alignment:---AATGAATGGRCC
GGYAATGAAA-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + C + T + A + G + + T + A + C + G + + G + A + C + T + + T + G + C + A + + T + G + C + A + + C + G + A + T + + T + A + C + G + + C + T + G + A + + T + C + G + A + + C + T + G + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Rbm47(RRM)/Xenopus_tropicalis-RNCMPT00280-PBM/HughesRNA

+
+ + + +
Match Rank:6
Score:0.71 +
Offset:0 +
Orientation:forward strand
Alignment:AATGAATGGRCC
GATGATN-----
+		 + + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + A + C + T + G + + C + G + T + A + + A + C + G + T + + A + T + C + G + + C + G + T + A + + C + G + A + T + + G + A + C + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

TARDBP(RRM)/Homo_sapiens-RNCMPT00076-PBM/HughesRNA

+
+ + + +
Match Rank:7
Score:0.70 +
Offset:2 +
Orientation:forward strand
Alignment:AATGAATGGRCC
--NGAATGAN--
+		 + + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + C + G + A + T + + A + C + T + G + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + T + A + G + + A + C + G + T + + A + C + G + T + + + + +
+
+

ZNF24/MA1124.1/Jaspar

+
+ + + +
Match Rank:8
Score:0.70 +
Offset:-1 +
Orientation:reverse strand
Alignment:-AATGAATGGRCC
GAATGAATGAATG
+		 + + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + C + T + A + G + + T + C + G + A + + C + T + G + A + + A + G + C + T + + C + T + A + G + + C + T + G + A + + T + C + G + A + + A + G + C + T + + C + T + A + G + + T + C + G + A + + C + T + G + A + + A + G + C + T + + C + T + A + G + + + + +
+
+

WUS1(Homeobox)/colamp-WUS1-DAP-Seq(GSE60143)/Homer

+
+ + + +
Match Rank:9
Score:0.69 +
Offset:-2 +
Orientation:reverse strand
Alignment:--AATGAATGGRCC
TGAATGAWTG----
+		 + + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + C + G + A + T + + T + C + A + G + + G + C + T + A + + G + C + T + A + + C + G + A + T + + C + T + A + G + + G + T + C + A + + G + C + T + A + + C + G + A + T + + C + A + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

Hoxd10(Homeobox)/ChickenMSG-Hoxd10.Flag-ChIP-Seq(GSE86088)/Homer

+
+ + + +
Match Rank:10
Score:0.69 +
Offset:-3 +
Orientation:forward strand
Alignment:---AATGAATGGRCC
GGCMATGAAA-----
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + + +
+ + + C + T + A + G + + T + A + C + G + + G + A + T + C + + G + T + C + A + + T + C + G + A + + A + C + G + T + + T + C + A + G + + C + G + T + A + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..cdda5ab199c5d4fd972d67f5767a7875f8fe37a6 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.logo.svg @@ -0,0 +1,64 @@ + + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.motif new file mode 100644 index 0000000000000000000000000000000000000000..4df404498bca06d533404247c9012d977781667c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.motif @@ -0,0 +1,13 @@ +>AATGAATGGRCC 4-AATGAATGGRCC,BestGuess:PB0178.1_Sox8_2/Jaspar(0.779) 9.843291 -104.870845 0 T:249.0(6.22%),B:29.2(0.73%),P:1e-45 +0.490 0.107 0.259 0.144 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.001 0.001 0.997 0.001 +0.997 0.001 0.001 0.001 +0.997 0.001 0.001 0.001 +0.248 0.001 0.001 0.750 +0.192 0.001 0.806 0.001 +0.177 0.001 0.821 0.001 +0.390 0.161 0.447 0.001 +0.036 0.493 0.305 0.166 +0.053 0.767 0.001 0.179 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..5752b726f0c2216f30b2547c4243f163a6fcecad --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar.html @@ -0,0 +1,254 @@ +motif3 +

Information for motif3

+ + + C + T + G + A + + C + G + T + A + + A + C + G + T + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + G + A + T + C + + + +
+Reverse Opposite:
+ + C + T + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + C + G + T + + G + A + C + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-45
log p-value:-1.049e+02
Information Content per bp:1.761
Number of Target Sequences with motif249.0
Percentage of Target Sequences with motif6.22%
Number of Background Sequences with motif29.2
Percentage of Background Sequences with motif0.73%
Average Position of motif in Targets246.5 +/- 109.9bp
Average Position of motif in Background259.1 +/- 155.7bp
Strand Bias (log2 ratio + to - strand density)0.1
Multiplicity (# of sites on avg that occur together)1.03
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.928 + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + T + G + C + + C + G + T + A + + A + C + G + T + + + + +1e-44-102.65592716.30%6.43%motif file (matrix)
20.916 + + A + G + T + C + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + G + C + T + + A + T + G + C + + C + G + T + A + + C + A + G + T + + T + G + C + A + + + + +1e-44-102.25771316.50%6.59%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..4cf3cfef8b86944c9236f20bc0c4864dab763311 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar1.motif @@ -0,0 +1,9 @@ +>CCATTCAT 6-CCATTCAT 8.401474 -102.655927 0 T:652.0(16.30%),B:256.2(6.43%),P:1e-44 +0.001 0.997 0.001 0.001 +0.001 0.804 0.001 0.194 +0.773 0.001 0.001 0.225 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.887 0.111 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar2.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar2.motif new file mode 100644 index 0000000000000000000000000000000000000000..3915601b22557703f6391cfabd2c1415d7daf8e5 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3.similar2.motif @@ -0,0 +1,11 @@ +>YCCATTCATV 6-YCCATTCATV 7.957512 -102.257713 0 T:660.0(16.50%),B:262.8(6.59%),P:1e-44 +0.064 0.373 0.221 0.342 +0.001 0.603 0.143 0.253 +0.001 0.816 0.001 0.182 +0.752 0.001 0.001 0.246 +0.001 0.001 0.001 0.997 +0.001 0.045 0.001 0.953 +0.001 0.833 0.165 0.001 +0.997 0.001 0.001 0.001 +0.037 0.015 0.102 0.846 +0.342 0.316 0.288 0.054 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..424085515c1d2e384789e0854792bd56af1e1071 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.logo.svg @@ -0,0 +1,64 @@ + + + C + T + A + G + + T + A + C + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + G + T + C + + C + G + T + A + + A + C + G + T + + G + A + C + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..b1bb54951fedbe16c7eb925fda6639fdd258b197 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif3RV.motif @@ -0,0 +1,13 @@ +>GGYCCATTCATT 4-AATGAATGGRCC 9.843291 -104.870845 0 T:249.0(6.22%),B:29.2(0.73%),P:1e-45 +0.179 0.001 0.767 0.053 +0.166 0.305 0.493 0.036 +0.001 0.447 0.161 0.390 +0.001 0.821 0.001 0.177 +0.001 0.806 0.001 0.192 +0.750 0.001 0.001 0.248 +0.001 0.001 0.001 0.997 +0.001 0.001 0.001 0.997 +0.001 0.997 0.001 0.001 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.144 0.259 0.107 0.490 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.info.html new file mode 100644 index 0000000000000000000000000000000000000000..9549645745ab3ce4bc2d3c7fa130673758220aae --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.info.html @@ -0,0 +1,1633 @@ +Motif 4 +

Information for 5-NVGCCDATYGGH (Motif 4)

+ + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+Reverse Opposite:
+ + C + T + A + G + + G + A + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + G + C + + C + T + A + G + + + +
+ + + + + + + + + + + + + + +
p-value:1e-44
log p-value:-1.024e+02
Information Content per bp:1.626
Number of Target Sequences with motif589.0
Percentage of Target Sequences with motif14.72%
Number of Background Sequences with motif215.7
Percentage of Background Sequences with motif5.41%
Average Position of motif in Targets257.6 +/- 122.1bp
Average Position of motif in Background260.6 +/- 141.2bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.20
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

NFY(CCAAT)/Promoter/Homer

+
+ + + +
Match Rank:1
Score:0.81 +
Offset:1 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
-AGCCAATCGG-
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + T + C + G + A + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + T + A + G + C + + T + C + A + G + + T + A + C + G + + A + C + G + T + + + + +
+
+

HAP2/Literature(Harbison)/Yeast

+
+ + + +
Match Rank:2
Score:0.78 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAAT----
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

HAP3/Literature(Harbison)/Yeast

+
+ + + +
Match Rank:3
Score:0.78 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAAT----
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

HAP5/Literature(Harbison)/Yeast

+
+ + + +
Match Rank:4
Score:0.78 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAAT----
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

HAP5(MacIsaac)/Yeast

+
+ + + +
Match Rank:5
Score:0.78 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAAT----
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

HAP3(MacIsaac)/Yeast

+
+ + + +
Match Rank:6
Score:0.78 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAAT----
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+
+

NFYB/MA0502.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.72 +
Offset:-4 +
Orientation:forward strand
Alignment:----NVGCCDATYGGH
AAATGGACCAATCAG-
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + T + C + G + A + + G + T + C + A + + G + T + C + A + + A + G + C + T + + A + T + C + G + + T + C + A + G + + C + T + G + A + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + T + G + A + + A + C + G + T + + T + A + G + C + + T + C + G + A + + T + A + C + G + + A + C + G + T + + + + +
+
+

HAP2(MacIsaac)/Yeast

+
+ + + +
Match Rank:8
Score:0.70 +
Offset:3 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
---CCAATGAG-
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + G + T + C + + G + T + A + C + + C + T + G + A + + C + G + T + A + + A + G + C + T + + A + T + C + G + + C + T + G + A + + T + C + A + G + + A + C + G + T + + + + +
+
+

NFYA/MA0060.3/Jaspar

+
+ + + +
Match Rank:9
Score:0.70 +
Offset:1 +
Orientation:forward strand
Alignment:NVGCCDATYGGH
-AACCAATCAGA
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + + +
+ + + A + C + G + T + + T + C + G + A + + C + T + G + A + + A + G + T + C + + G + A + T + C + + G + C + T + A + + T + C + G + A + + G + A + C + T + + T + A + G + C + + T + C + G + A + + T + A + C + G + + T + G + C + A + + + + +
+
+

ceh-48/MA0921.1/Jaspar

+
+ + + +
Match Rank:10
Score:0.69 +
Offset:4 +
Orientation:reverse strand
Alignment:NVGCCDATYGGH-
----NTATCGATN
+		 + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + G + A + T + + C + G + A + T + + C + G + T + A + + C + G + A + T + + G + A + T + C + + C + A + T + G + + C + T + G + A + + G + C + A + T + + G + A + C + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..bf500050b4b357c15577069984a3929b307c3827 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.logo.svg @@ -0,0 +1,64 @@ + + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.motif new file mode 100644 index 0000000000000000000000000000000000000000..a9ca396e169a70a1b058c9cb7e4ff9ceb9c1a9af --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.motif @@ -0,0 +1,13 @@ +>NVGCCDATYGGH 5-NVGCCDATYGGH,BestGuess:NFY(CCAAT)/Promoter/Homer(0.811) 7.916613 -102.443439 0 T:589.0(14.72%),B:215.7(5.41%),P:1e-44 +0.240 0.297 0.214 0.249 +0.259 0.284 0.325 0.132 +0.245 0.142 0.404 0.210 +0.001 0.927 0.001 0.071 +0.001 0.997 0.001 0.001 +0.367 0.079 0.323 0.231 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.203 0.370 0.001 0.427 +0.001 0.001 0.997 0.001 +0.199 0.001 0.644 0.156 +0.210 0.340 0.151 0.299 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..3766d0a2c140039211ad28ef91e34b39662f40d2 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar.html @@ -0,0 +1,254 @@ +motif4 +

Information for motif4

+ + + G + A + T + C + + T + A + C + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + + +
+Reverse Opposite:
+ + C + T + A + G + + G + A + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + G + C + + C + T + A + G + + + +
+ + + + + + + + + + + + + +
p-value:1e-44
log p-value:-1.024e+02
Information Content per bp:1.626
Number of Target Sequences with motif589.0
Percentage of Target Sequences with motif14.72%
Number of Background Sequences with motif215.7
Percentage of Background Sequences with motif5.41%
Average Position of motif in Targets257.6 +/- 122.1bp
Average Position of motif in Background260.6 +/- 141.2bp
Strand Bias (log2 ratio + to - strand density)0.0
Multiplicity (# of sites on avg that occur together)1.20
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.962 + + T + C + A + G + + C + T + A + G + + A + G + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + T + C + + C + T + A + G + + T + A + C + G + + + + +1e-43-100.09403813.93%4.97%motif file (matrix)
20.929 + + A + G + T + C + + A + G + T + C + + C + G + T + A + + C + G + T + A + + A + C + G + T + + T + G + A + C + + A + C + T + G + + C + T + A + G + + + + +1e-37-85.67526816.55%7.33%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..44dcb1b2b7f0f4424cde65bc6aa55643404f999c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar1.motif @@ -0,0 +1,11 @@ +>GRCCAATCGG 7-GRCCAATCGG 7.881463 -100.094038 0 T:557.0(13.93%),B:198.1(4.97%),P:1e-43 +0.272 0.195 0.532 0.001 +0.328 0.059 0.477 0.136 +0.001 0.980 0.001 0.018 +0.001 0.997 0.001 0.001 +0.630 0.001 0.212 0.157 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.183 0.526 0.037 0.254 +0.011 0.001 0.987 0.001 +0.046 0.051 0.871 0.032 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar2.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar2.motif new file mode 100644 index 0000000000000000000000000000000000000000..0571510d9df44a7b76a3d109f42033692474f00c --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4.similar2.motif @@ -0,0 +1,9 @@ +>CCAATCGG 8-CCAATCGG 7.893395 -85.675268 0 T:662.0(16.55%),B:292.2(7.33%),P:1e-37 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.785 0.001 0.067 0.147 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.152 0.683 0.088 0.077 +0.001 0.001 0.997 0.001 +0.091 0.001 0.907 0.001 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..e71873635685edf64334b623fe548b939b2266dd --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.logo.svg @@ -0,0 +1,64 @@ + + + C + T + A + G + + G + A + T + C + + A + G + T + C + + C + T + G + A + + C + G + T + A + + A + C + G + T + + G + A + C + T + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + G + C + + C + T + A + G + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..8502cd0c75388b192a4d3d75c74b0906b6897bfc --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif4RV.motif @@ -0,0 +1,13 @@ +>DCCRATHGGCBN 5-NVGCCDATYGGH 7.916613 -102.443439 0 T:589.0(14.72%),B:215.7(5.41%),P:1e-44 +0.299 0.151 0.340 0.210 +0.156 0.644 0.001 0.199 +0.001 0.997 0.001 0.001 +0.427 0.001 0.370 0.203 +0.997 0.001 0.001 0.001 +0.001 0.001 0.001 0.997 +0.231 0.323 0.079 0.367 +0.001 0.001 0.997 0.001 +0.071 0.001 0.927 0.001 +0.210 0.404 0.142 0.245 +0.132 0.325 0.284 0.259 +0.249 0.214 0.297 0.240 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.info.html new file mode 100644 index 0000000000000000000000000000000000000000..ee796c9e8bb081283ebe09fcd48ed9686e08184e --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.info.html @@ -0,0 +1,2013 @@ +Motif 5 +

Information for 6-AAGGAACAATTG (Motif 5)

+ + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + + + +
+Reverse Opposite:
+ + G + T + A + C + + G + C + T + A + + T + G + C + A + + G + A + C + T + + G + A + C + T + + C + A + T + G + + G + C + A + T + + G + A + C + T + + G + T + A + C + + G + A + T + C + + G + C + A + T + + A + C + G + T + + + +
+ + + + + + + + + + + + + + +
p-value:1e-13
log p-value:-3.100e+01
Information Content per bp:1.511
Number of Target Sequences with motif63.0
Percentage of Target Sequences with motif1.57%
Number of Background Sequences with motif5.8
Percentage of Background Sequences with motif0.14%
Average Position of motif in Targets257.7 +/- 114.0bp
Average Position of motif in Background291.6 +/- 64.5bp
Strand Bias (log2 ratio + to - strand density)-0.6
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

PB0173.1_Sox21_2/Jaspar

+
+ + + +
Match Rank:1
Score:0.77 +
Offset:-2 +
Orientation:reverse strand
Alignment:--AAGGAACAATTG---
NNNNNGAACAATTGANN
+		 + + + A + C + G + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + G + C + T + + G + T + C + A + + C + T + A + G + + G + T + A + C + + A + C + T + G + + T + A + C + G + + T + C + G + A + + C + G + T + A + + A + T + G + C + + C + G + T + A + + T + C + G + A + + G + C + A + T + + C + G + A + T + + T + A + C + G + + T + C + G + A + + A + G + C + T + + A + C + G + T + + + + +
+
+

PB0070.1_Sox30_1/Jaspar

+
+ + + +
Match Rank:2
Score:0.76 +
Offset:0 +
Orientation:forward strand
Alignment:AAGGAACAATTG----
AATGAACAATGGAATT
+		 + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + T + G + A + + G + C + A + T + + C + A + G + T + + A + T + C + G + + T + C + G + A + + C + G + T + A + + A + G + T + C + + G + C + T + A + + C + T + G + A + + C + G + A + T + + C + A + T + G + + T + C + A + G + + G + C + T + A + + G + T + C + A + + G + A + C + T + + G + A + C + T + + + + +
+
+

SOX9/MA0077.1/Jaspar

+
+ + + +
Match Rank:3
Score:0.74 +
Offset:3 +
Orientation:reverse strand
Alignment:AAGGAACAATTG
---GAACAATGG
+		 + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + A + G + + C + G + T + A + + G + C + T + A + + A + G + T + C + + G + C + T + A + + G + C + T + A + + C + G + A + T + + C + T + A + G + + T + A + C + G + + + + +
+
+

PB0073.1_Sox7_1/Jaspar

+
+ + + +
Match Rank:4
Score:0.73 +
Offset:-3 +
Orientation:forward strand
Alignment:---AAGGAACAATTG-------
AATAAAGAACAATAGAATTTCA
+		 + + + A + C + G + T + + A + C + G + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + T + C + A + + G + C + T + A + + A + C + G + T + + C + T + G + A + + G + C + T + A + + C + G + T + A + + C + T + A + G + + C + T + G + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + C + G + T + A + + T + C + A + G + + G + C + T + A + + G + C + T + A + + G + A + C + T + + G + C + A + T + + G + C + A + T + + A + G + T + C + + G + C + T + A + + + + +
+
+

PB0065.1_Sox15_1/Jaspar

+
+ + + +
Match Rank:5
Score:0.73 +
Offset:-1 +
Orientation:forward strand
Alignment:-AAGGAACAATTG----
TAGTGAACAATAGATTT
+		 + + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + C + A + T + + C + T + A + G + + C + A + T + G + + C + G + A + T + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + G + T + A + + C + G + T + A + + G + C + A + T + + C + G + T + A + + C + T + A + G + + C + T + G + A + + A + G + C + T + + G + C + A + T + + A + C + G + T + + + + +
+
+

PB0072.1_Sox5_1/Jaspar

+
+ + + +
Match Rank:6
Score:0.72 +
Offset:-1 +
Orientation:forward strand
Alignment:-AAGGAACAATTG---
TTTAGAACAATAAAAT
+		 + + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + C + G + A + T + + G + C + A + T + + C + A + G + T + + C + T + G + A + + C + T + A + G + + T + C + G + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + G + T + A + + G + C + A + T + + C + G + T + A + + C + T + G + A + + C + G + T + A + + G + C + T + A + + C + G + A + T + + + + +
+
+

PB0074.1_Sox8_1/Jaspar

+
+ + + +
Match Rank:7
Score:0.71 +
Offset:-1 +
Orientation:reverse strand
Alignment:-AAGGAACAATTG----
TNNAGAACAATANATNN
+		 + + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + C + A + T + + G + C + T + A + + G + T + C + A + + C + G + T + A + + C + A + T + G + + C + T + G + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + T + G + A + + C + G + A + T + + C + G + T + A + + T + C + A + G + + G + C + T + A + + G + C + A + T + + G + T + C + A + + G + T + A + C + + + + +
+
+

PB0183.1_Sry_2/Jaspar

+
+ + + +
Match Rank:8
Score:0.71 +
Offset:-2 +
Orientation:forward strand
Alignment:--AAGGAACAATTG---
TCACGGAACAATAGGTG
+		 + + + A + C + G + T + + A + C + G + T + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + G + A + C + T + + G + A + T + C + + C + G + T + A + + G + T + A + C + + C + A + T + G + + T + C + A + G + + T + G + C + A + + C + G + T + A + + A + G + T + C + + C + T + G + A + + C + G + T + A + + G + C + A + T + + C + T + G + A + + C + T + A + G + + T + C + A + G + + G + A + C + T + + T + A + C + G + + + + +
+
+

PB0066.1_Sox17_1/Jaspar

+
+ + + +
Match Rank:9
Score:0.71 +
Offset:1 +
Orientation:forward strand
Alignment:AAGGAACAATTG----
-ATAAACAATTAAACA
+		 + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + A + C + G + T + + A + C + G + T + + A + C + G + T + + + + +
+ + + A + C + G + T + + T + G + C + A + + C + G + A + T + + C + T + G + A + + C + G + T + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + G + A + T + + T + C + G + A + + G + C + T + A + + G + C + A + T + + G + A + T + C + + C + G + T + A + + + + +
+
+

Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer

+
+ + + +
Match Rank:10
Score:0.70 +
Offset:3 +
Orientation:reverse strand
Alignment:AAGGAACAATTG-
---GAACAATGGN
+		 + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + A + C + G + T + + + + +
+ + + A + C + G + T + + A + C + G + T + + A + C + G + T + + C + T + A + G + + T + C + G + A + + C + G + T + A + + A + G + T + C + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + T + C + A + G + + T + A + C + G + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..d892fa9a69aff3e43ad52603b0827ffe951670d2 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.logo.svg @@ -0,0 +1,64 @@ + + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.motif new file mode 100644 index 0000000000000000000000000000000000000000..4447b896429ea7bdab58cad4fbd9957b872becb8 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.motif @@ -0,0 +1,13 @@ +>AAGGAACAATTG 6-AAGGAACAATTG,BestGuess:PB0173.1_Sox21_2/Jaspar(0.771) 8.965680 -31.001112 0 T:63.0(1.57%),B:5.8(0.14%),P:1e-13 +0.717 0.171 0.108 0.004 +0.544 0.102 0.133 0.221 +0.192 0.070 0.624 0.114 +0.149 0.105 0.544 0.202 +0.662 0.005 0.245 0.088 +0.610 0.053 0.151 0.186 +0.083 0.756 0.078 0.083 +0.578 0.117 0.182 0.123 +0.672 0.066 0.135 0.127 +0.004 0.160 0.162 0.674 +0.115 0.101 0.104 0.680 +0.081 0.081 0.752 0.086 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..4e49bfd21b9813e9d9da0ae2aae242a2549d4d30 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5.similar.html @@ -0,0 +1,152 @@ +motif5 +

Information for motif5

+ + + T + G + C + A + + C + G + T + A + + C + T + A + G + + C + A + T + G + + C + T + G + A + + C + G + T + A + + G + A + T + C + + C + T + G + A + + C + T + G + A + + A + C + G + T + + C + G + A + T + + A + C + T + G + + + +
+Reverse Opposite:
+ + G + T + A + C + + G + C + T + A + + T + G + C + A + + G + A + C + T + + G + A + C + T + + C + A + T + G + + G + C + A + T + + G + A + C + T + + G + T + A + C + + G + A + T + C + + G + C + A + T + + A + C + G + T + + + +
+ + + + + + + + + + + + + +
p-value:1e-13
log p-value:-3.100e+01
Information Content per bp:1.511
Number of Target Sequences with motif63.0
Percentage of Target Sequences with motif1.57%
Number of Background Sequences with motif5.8
Percentage of Background Sequences with motif0.14%
Average Position of motif in Targets257.7 +/- 114.0bp
Average Position of motif in Background291.6 +/- 64.5bp
Strand Bias (log2 ratio + to - strand density)-0.6
Multiplicity (# of sites on avg that occur together)1.00
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..6a0f5d18d56459f48f7980c830e8a372a05a8265 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.logo.svg @@ -0,0 +1,64 @@ + + + G + T + A + C + + G + C + T + A + + T + G + C + A + + G + A + C + T + + G + A + C + T + + C + A + T + G + + G + C + A + T + + G + A + C + T + + G + T + A + C + + G + A + T + C + + G + C + A + T + + A + C + G + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..b0b3e03fdfce5c7b71561901b496d7f481564aa4 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif5RV.motif @@ -0,0 +1,13 @@ +>CAATTGTTCCTT 6-AAGGAACAATTG 8.965680 -31.001112 0 T:63.0(1.57%),B:5.8(0.14%),P:1e-13 +0.086 0.752 0.081 0.081 +0.680 0.104 0.101 0.115 +0.674 0.162 0.160 0.004 +0.127 0.135 0.066 0.672 +0.123 0.182 0.117 0.578 +0.083 0.078 0.756 0.083 +0.186 0.151 0.053 0.610 +0.088 0.245 0.005 0.662 +0.202 0.544 0.105 0.149 +0.114 0.624 0.070 0.192 +0.221 0.133 0.102 0.544 +0.004 0.108 0.171 0.717 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.info.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.info.html new file mode 100644 index 0000000000000000000000000000000000000000..260623cffad3881991f6a4647c815f61aa50c68a --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.info.html @@ -0,0 +1,1363 @@ +Motif 6 +

Information for 8-BAYTTCCGGH (Motif 6)

+ + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+Reverse Opposite:
+ + C + T + G + A + + A + T + G + C + + T + G + A + C + + A + T + C + G + + A + C + T + G + + G + C + T + A + + G + C + T + A + + T + C + A + G + + A + C + G + T + + T + C + A + G + + + +
+ + + + + + + + + + + + + + +
p-value:1e-11
log p-value:-2.720e+01
Information Content per bp:1.575
Number of Target Sequences with motif154.0
Percentage of Target Sequences with motif3.85%
Number of Background Sequences with motif56.0
Percentage of Background Sequences with motif1.40%
Average Position of motif in Targets264.5 +/- 130.4bp
Average Position of motif in Background263.5 +/- 139.2bp
Strand Bias (log2 ratio + to - strand density)-0.2
Multiplicity (# of sites on avg that occur together)1.06
Motif File:file (matrix)
reverse opposite
SVG Files for Logos:forward logo
reverse opposite
+

Matches to Known Motifs

+ + + + + + + + + + + +
+

Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer

+
+ + + +
Match Rank:1
Score:0.97 +
Offset:0 +
Orientation:forward strand
Alignment:BAYTTCCGGH
HACTTCCGGY
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + T + C + + T + C + G + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + A + G + T + C + + A + T + G + C + + A + C + T + G + + A + T + C + G + + G + A + C + T + + + + +
+
+

ELK3/MA0759.1/Jaspar

+
+ + + +
Match Rank:2
Score:0.96 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
NACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + C + T + + T + C + G + A + + A + G + T + C + + C + G + A + T + + A + C + G + T + + T + G + A + C + + A + G + T + C + + A + C + T + G + + A + C + T + G + + G + A + C + T + + + + +
+
+

FEV/MA0156.2/Jaspar

+
+ + + +
Match Rank:3
Score:0.96 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
NACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + T + C + + T + C + G + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + G + T + A + C + + G + A + T + C + + A + C + T + G + + A + C + T + G + + G + C + A + T + + + + +
+
+

ERG/MA0474.2/Jaspar

+
+ + + +
Match Rank:4
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
NACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + A + T + G + C + + T + C + G + A + + A + G + T + C + + C + G + A + T + + C + A + G + T + + T + G + A + C + + A + G + T + C + + A + C + T + G + + A + C + T + G + + G + C + A + T + + + + +
+
+

ETV4/MA0764.1/Jaspar

+
+ + + +
Match Rank:5
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
TACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + C + T + + T + C + G + A + + A + G + T + C + + C + G + A + T + + G + A + C + T + + G + T + A + C + + A + T + G + C + + A + C + T + G + + A + T + C + G + + G + A + C + T + + + + +
+
+

Elk4(ETS)/Hela-Elk4-ChIP-Seq(GSE31477)/Homer

+
+ + + +
Match Rank:6
Score:0.95 +
Offset:0 +
Orientation:forward strand
Alignment:BAYTTCCGGH
NRYTTCCGGY
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + T + C + + C + T + G + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + G + A + T + C + + A + G + T + C + + A + C + T + G + + A + T + C + G + + A + G + C + T + + + + +
+
+

ETV1/MA0761.1/Jaspar

+
+ + + +
Match Rank:7
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
NACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + G + A + C + T + + T + C + G + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + G + T + A + C + + A + G + T + C + + A + C + T + G + + A + T + C + G + + G + A + C + T + + + + +
+
+

FLI1/MA0475.2/Jaspar

+
+ + + +
Match Rank:8
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
CACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + A + G + T + C + + T + C + G + A + + A + G + T + C + + C + G + A + T + + A + C + G + T + + G + T + A + C + + G + A + T + C + + A + C + T + G + + A + C + T + G + + G + A + C + T + + + + +
+
+

ERF/MA0760.1/Jaspar

+
+ + + +
Match Rank:9
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
CACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + A + G + T + C + + T + C + G + A + + A + G + T + C + + C + G + A + T + + A + C + G + T + + A + T + G + C + + A + G + T + C + + A + C + T + G + + T + C + A + G + + A + G + C + T + + + + +
+
+

ETS1/MA0098.3/Jaspar

+
+ + + +
Match Rank:10
Score:0.95 +
Offset:0 +
Orientation:reverse strand
Alignment:BAYTTCCGGH
CACTTCCGGT
+		 + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + + +
+ + + A + G + T + C + + T + C + G + A + + A + G + T + C + + G + C + A + T + + A + C + G + T + + G + T + A + C + + A + T + G + C + + A + C + T + G + + A + T + C + G + + G + A + C + T + + + + +
+
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..014d6badc74f2c13ecbba3864033ef67ebbb1257 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.logo.svg @@ -0,0 +1,54 @@ + + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.motif new file mode 100644 index 0000000000000000000000000000000000000000..c11745a2b3a13df4fb32fd49c26c358a52b4f0cd --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.motif @@ -0,0 +1,11 @@ +>BAYTTCCGGH 8-BAYTTCCGGH,BestGuess:Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer(0.965) 8.326461 -27.204860 0 T:154.0(3.85%),B:56.0(1.40%),P:1e-11 +0.149 0.340 0.223 0.288 +0.745 0.173 0.045 0.037 +0.055 0.387 0.209 0.349 +0.102 0.023 0.077 0.798 +0.091 0.027 0.088 0.794 +0.083 0.885 0.020 0.012 +0.001 0.895 0.103 0.001 +0.025 0.043 0.855 0.077 +0.140 0.175 0.590 0.095 +0.238 0.294 0.082 0.386 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar.html b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar.html new file mode 100644 index 0000000000000000000000000000000000000000..0e061a7d01b998b32a28205c342755121982a0b8 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar.html @@ -0,0 +1,178 @@ +motif6 +

Information for motif6

+ + + A + G + T + C + + T + G + C + A + + A + G + T + C + + C + G + A + T + + C + G + A + T + + T + G + A + C + + A + T + G + C + + A + C + T + G + + T + A + C + G + + G + A + C + T + + + +
+Reverse Opposite:
+ + C + T + G + A + + A + T + G + C + + T + G + A + C + + A + T + C + G + + A + C + T + G + + G + C + T + A + + G + C + T + A + + T + C + A + G + + A + C + G + T + + T + C + A + G + + + +
+ + + + + + + + + + + + + +
p-value:1e-11
log p-value:-2.720e+01
Information Content per bp:1.575
Number of Target Sequences with motif154.0
Percentage of Target Sequences with motif3.85%
Number of Background Sequences with motif56.0
Percentage of Background Sequences with motif1.40%
Average Position of motif in Targets264.5 +/- 130.4bp
Average Position of motif in Background263.5 +/- 139.2bp
Strand Bias (log2 ratio + to - strand density)-0.2
Multiplicity (# of sites on avg that occur together)1.06
Motif File:file (matrix)
reverse opposite
+

Similar de novo motifs found

+ + + +
RankMatch ScoreRedundant MotifP-valuelog P-value% of Targets% of BackgroundMotif file
10.947 + + A + G + T + C + + A + G + T + C + + A + C + T + G + + A + C + T + G + + C + G + T + A + + C + G + T + A + + C + T + A + G + + A + C + G + T + + + + +1e-8-18.9002787.05%4.12%motif file (matrix)
+

+ diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar1.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar1.motif new file mode 100644 index 0000000000000000000000000000000000000000..cbca8b4c807174bcbbd2da87cb569154bc48b62f --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6.similar1.motif @@ -0,0 +1,9 @@ +>CCGGAAGT 11-CCGGAAGT 9.037943 -18.900278 0 T:282.0(7.05%),B:164.2(4.12%),P:1e-8 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.001 0.997 0.001 +0.001 0.001 0.997 0.001 +0.831 0.001 0.001 0.167 +0.997 0.001 0.001 0.001 +0.215 0.001 0.783 0.001 +0.001 0.001 0.001 0.997 diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.logo.svg b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..f3195470317becf96180f873f04905dfb5436934 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.logo.svg @@ -0,0 +1,54 @@ + + + C + T + G + A + + A + T + G + C + + T + G + A + C + + A + T + C + G + + A + C + T + G + + G + C + T + A + + G + C + T + A + + T + C + A + G + + A + C + G + T + + T + C + A + G + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.motif b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.motif new file mode 100644 index 0000000000000000000000000000000000000000..0554175613f0e2691bac72841b04e19850bc5d89 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/homerResults/motif6RV.motif @@ -0,0 +1,11 @@ +>DCCGGAARTV 8-BAYTTCCGGH 8.326461 -27.204860 0 T:154.0(3.85%),B:56.0(1.40%),P:1e-11 +0.386 0.082 0.294 0.238 +0.095 0.590 0.175 0.140 +0.077 0.855 0.043 0.025 +0.001 0.103 0.895 0.001 +0.012 0.020 0.885 0.083 +0.794 0.088 0.027 0.091 +0.798 0.077 0.023 0.102 +0.349 0.209 0.387 0.055 +0.037 0.045 0.173 0.745 +0.288 0.223 0.340 0.149 diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults.html b/the_code/Human/data/homer/M15_vs_M0/knownResults.html new file mode 100644 index 0000000000000000000000000000000000000000..19323cde8e9c689748fa849476a09d04cef57596 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults.html @@ -0,0 +1,5495 @@ +./ - Homer Known Motif Enrichment Results + +

Homer Known Motif Enrichment Results (./)

+Homer de novo Motif Results
+Gene Ontology Enrichment Results
+Known Motif Enrichment Results (txt file)
+Total Target Sequences = 4000, Total Background Sequences = 3985
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
RankMotifNameP-valuelog P-pvalueq-value (Benjamini)# Target Sequences with Motif% of Targets Sequences with Motif# Background Sequences with Motif% of Background Sequences with MotifMotif FileSVG
1 + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + C + A + G + + A + G + T + C + + A + T + G + C + + A + G + T + C + + G + C + A + T + + A + G + C + T + + A + C + G + T + + A + T + C + G + + C + G + A + T + + + + +Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer1e-221-5.111e+020.00001770.044.25%508.512.76%motif file (matrix)svg
2 + + + A + T + G + C + + A + G + T + C + + G + A + T + C + + C + G + T + A + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + C + T + + G + A + T + C + + + + +Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer1e-176-4.063e+020.00001708.042.70%578.014.50%motif file (matrix)svg
3 + + + A + T + G + C + + G + A + T + C + + C + G + T + A + + A + G + C + T + + C + A + G + T + + A + T + C + G + + G + C + A + T + + A + G + C + T + + G + A + C + T + + A + C + T + G + + + + +Sox17(HMG)/Endoderm-Sox17-ChIP-Seq(GSE61475)/Homer1e-162-3.744e+020.00001639.040.98%566.014.20%motif file (matrix)svg
4 + + + A + G + T + C + + A + G + T + C + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + A + C + G + T + + A + G + C + T + + A + G + T + C + + A + G + T + C + + + + +Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer1e-159-3.669e+020.00001480.037.00%463.711.63%motif file (matrix)svg
5 + + + C + T + G + A + + T + C + G + A + + C + G + T + A + + A + T + G + C + + C + G + T + A + + C + G + T + A + + C + G + A + T + + C + T + A + G + + T + C + A + G + + G + A + T + C + + + + +Sox15(HMG)/CPA-Sox15-ChIP-Seq(GSE62909)/Homer1e-150-3.459e+020.00001768.044.20%697.817.51%motif file (matrix)svg
6 + + + A + T + G + C + + A + G + T + C + + G + C + A + T + + A + G + C + T + + A + C + G + T + + T + C + A + G + + C + G + A + T + + A + G + C + T + + G + A + T + C + + A + T + C + G + + + + +Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132)/Homer1e-134-3.102e+020.00002178.054.45%1092.027.40%motif file (matrix)svg
7 + + + A + T + G + C + + G + A + T + C + + C + G + A + T + + A + C + G + T + + A + C + G + T + + A + C + T + G + + C + A + G + T + + A + G + C + T + + + + +Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer1e-126-2.922e+020.00002287.057.17%1222.830.68%motif file (matrix)svg
8 + + + A + T + G + C + + G + T + A + C + + C + G + T + A + + A + G + C + T + + G + C + A + T + + T + A + C + G + + A + G + C + T + + A + G + C + T + + A + G + T + C + + A + G + C + T + + + + +Sox6(HMG)/Myotubes-Sox6-ChIP-Seq(GSE32627)/Homer1e-100-2.310e+020.00002192.054.80%1247.731.30%motif file (matrix)svg
9 + + + C + T + G + A + + T + C + A + G + + C + A + G + T + + C + T + A + G + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + C + G + + A + C + T + G + + C + T + G + A + + T + C + A + G + + G + A + T + C + + + + +Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer1e-55-1.280e+020.0000753.018.82%284.77.14%motif file (matrix)svg
10 + + + A + G + T + C + + C + T + A + G + + C + T + A + G + + A + G + T + C + + G + A + T + C + + G + T + A + C + + A + G + T + C + + C + T + A + G + + A + G + T + C + + A + G + T + C + + A + G + T + C + + G + T + A + C + + + + +Sp2(Zf)/HEK293-Sp2.eGFP-ChIP-Seq(Encode)/Homer1e-39-9.162e+010.00001131.028.27%637.916.00%motif file (matrix)svg
11 + + + C + T + A + G + + T + C + A + G + + C + A + G + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + C + T + A + G + + A + C + T + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + + + +KLF14(Zf)/HEK293-KLF14.GFP-ChIP-Seq(GSE58341)/Homer1e-34-7.875e+010.0000992.024.80%557.913.99%motif file (matrix)svg
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diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults.txt b/the_code/Human/data/homer/M15_vs_M0/knownResults.txt new file mode 100644 index 0000000000000000000000000000000000000000..4ba9df0d3d6c3231559a83965aa299d5ce24732e --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults.txt @@ -0,0 +1,995 @@ +Motif Name Consensus P-value Log P-value q-value (Benjamini) # of Target Sequences with Motif(of 4000) % of Target Sequences with Motif # of Background Sequences with Motif(of 3985) % of Background Sequences with Motif +Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer AGGVNCCTTTGT 1e-221 -5.111e+02 0.0000 1770.0 44.25% 508.5 12.76% +Sox2(HMG)/mES-Sox2-ChIP-Seq(GSE11431)/Homer BCCATTGTTC 1e-176 -4.063e+02 0.0000 1708.0 42.70% 578.0 14.50% +Sox17(HMG)/Endoderm-Sox17-ChIP-Seq(GSE61475)/Homer CCATTGTTYB 1e-162 -3.744e+02 0.0000 1639.0 40.98% 566.0 14.20% +Sox4(HMG)/proB-Sox4-ChIP-Seq(GSE50066)/Homer YCTTTGTTCC 1e-159 -3.669e+02 0.0000 1480.0 37.00% 463.7 11.63% +Sox15(HMG)/CPA-Sox15-ChIP-Seq(GSE62909)/Homer RAACAATGGN 1e-150 -3.459e+02 0.0000 1768.0 44.20% 697.8 17.51% +Sox10(HMG)/SciaticNerve-Sox3-ChIP-Seq(GSE35132)/Homer CCWTTGTYYB 1e-134 -3.102e+02 0.0000 2178.0 54.45% 1092.0 27.40% +Sox3(HMG)/NPC-Sox3-ChIP-Seq(GSE33059)/Homer CCWTTGTY 1e-126 -2.922e+02 0.0000 2287.0 57.17% 1222.8 30.68% +Sox6(HMG)/Myotubes-Sox6-ChIP-Seq(GSE32627)/Homer CCATTGTTNY 1e-100 -2.310e+02 0.0000 2192.0 54.80% 1247.7 31.30% +Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer RGKGGGCGGAGC 1e-55 -1.280e+02 0.0000 753.0 18.82% 284.7 7.14% +Sp2(Zf)/HEK293-Sp2.eGFP-ChIP-Seq(Encode)/Homer YGGCCCCGCCCC 1e-39 -9.162e+01 0.0000 1131.0 28.27% 637.9 16.00% +KLF14(Zf)/HEK293-KLF14.GFP-ChIP-Seq(GSE58341)/Homer RGKGGGCGKGGC 1e-34 -7.875e+01 0.0000 992.0 24.80% 557.9 13.99% +Sp1(Zf)/Promoter/Homer GGCCCCGCCCCC 1e-32 -7.516e+01 0.0000 235.0 5.88% 45.1 1.13% +KLF3(Zf)/MEF-Klf3-ChIP-Seq(GSE44748)/Homer NRGCCCCRCCCHBNN 1e-31 -7.299e+01 0.0000 402.0 10.05% 140.2 3.52% +KLF5(Zf)/LoVo-KLF5-ChIP-Seq(GSE49402)/Homer DGGGYGKGGC 1e-21 -5.049e+01 0.0000 846.0 21.15% 517.6 12.99% +LEF1(HMG)/H1-LEF1-ChIP-Seq(GSE64758)/Homer CCTTTGATST 1e-18 -4.253e+01 0.0000 687.0 17.18% 412.9 10.36% +AP-2alpha(AP2)/Hela-AP2alpha-ChIP-Seq(GSE31477)/Homer ATGCCCTGAGGC 1e-16 -3.729e+01 0.0000 511.0 12.78% 288.3 7.23% +AP-2gamma(AP2)/MCF7-TFAP2C-ChIP-Seq(GSE21234)/Homer SCCTSAGGSCAW 1e-15 -3.676e+01 0.0000 635.0 15.88% 388.1 9.74% +Oct4:Sox17(POU,Homeobox,HMG)/F9-Sox17-ChIP-Seq(GSE44553)/Homer CCATTGTATGCAAAT 1e-15 -3.647e+01 0.0000 211.0 5.27% 76.6 1.92% +NFY(CCAAT)/Promoter/Homer RGCCAATSRG 1e-13 -3.217e+01 0.0000 1346.0 33.65% 1029.6 25.83% +Klf9(Zf)/GBM-Klf9-ChIP-Seq(GSE62211)/Homer GCCACRCCCACY 1e-12 -2.976e+01 0.0000 197.0 4.92% 78.4 1.97% +KLF6(Zf)/PDAC-KLF6-ChIP-Seq(GSE64557)/Homer MKGGGYGTGGCC 1e-12 -2.805e+01 0.0000 631.0 15.78% 415.2 10.42% +Elk4(ETS)/Hela-Elk4-ChIP-Seq(GSE31477)/Homer NRYTTCCGGY 1e-9 -2.221e+01 0.0000 1127.0 28.18% 881.1 22.10% +Klf4(Zf)/mES-Klf4-ChIP-Seq(GSE11431)/Homer GCCACACCCA 1e-9 -2.198e+01 0.0000 207.0 5.17% 100.4 2.52% +ETS(ETS)/Promoter/Homer AACCGGAAGT 1e-9 -2.160e+01 0.0000 480.0 12.00% 314.2 7.88% +Tcf4(HMG)/Hct116-Tcf4-ChIP-Seq(SRA012054)/Homer ASATCAAAGGVA 1e-8 -2.033e+01 0.0000 390.0 9.75% 245.6 6.16% +Elk1(ETS)/Hela-Elk1-ChIP-Seq(GSE31477)/Homer HACTTCCGGY 1e-8 -2.014e+01 0.0000 953.0 23.82% 734.8 18.43% +ELF1(ETS)/Jurkat-ELF1-ChIP-Seq(SRA014231)/Homer AVCCGGAAGT 1e-8 -1.870e+01 0.0000 747.0 18.68% 557.1 13.98% +Fli1(ETS)/CD8-FLI-ChIP-Seq(GSE20898)/Homer NRYTTCCGGH 1e-7 -1.814e+01 0.0000 1282.0 32.05% 1051.2 26.37% +MITF(bHLH)/MastCells-MITF-ChIP-Seq(GSE48085)/Homer RTCATGTGAC 1e-7 -1.628e+01 0.0000 1036.0 25.90% 835.0 20.95% +GABPA(ETS)/Jurkat-GABPa-ChIP-Seq(GSE17954)/Homer RACCGGAAGT 1e-6 -1.564e+01 0.0000 832.0 20.80% 651.4 16.34% +ETV4(ETS)/HepG2-ETV4-ChIP-Seq(ENCODE)/Homer ACCGGAAGTG 1e-6 -1.447e+01 0.0000 1137.0 28.43% 941.7 23.62% +Usf2(bHLH)/C2C12-Usf2-ChIP-Seq(GSE36030)/Homer GTCACGTGGT 1e-5 -1.359e+01 0.0000 384.0 9.60% 267.7 6.71% +ETV1(ETS)/GIST48-ETV1-ChIP-Seq(GSE22441)/Homer AACCGGAAGT 1e-5 -1.332e+01 0.0000 1116.0 27.90% 930.3 23.34% +EWS:FLI1-fusion(ETS)/SK_N_MC-EWS:FLI1-ChIP-Seq(SRA014231)/Homer VACAGGAAAT 1e-5 -1.239e+01 0.0001 455.0 11.38% 334.9 8.40% +ETS1(ETS)/Jurkat-ETS1-ChIP-Seq(GSE17954)/Homer ACAGGAAGTG 1e-5 -1.224e+01 0.0001 757.0 18.93% 605.4 15.19% +ERG(ETS)/VCaP-ERG-ChIP-Seq(GSE14097)/Homer ACAGGAAGTG 1e-5 -1.164e+01 0.0002 861.0 21.52% 705.2 17.69% +REF6(Zf)/Arabidopsis-REF6-ChIP-Seq(GSE106942)/Homer TVCTCTGTTT 1e-4 -1.127e+01 0.0003 330.0 8.25% 232.6 5.83% +PR(NR)/T47D-PR-ChIP-Seq(GSE31130)/Homer VAGRACAKNCTGTBC 1e-4 -1.104e+01 0.0004 1585.0 39.62% 1399.8 35.12% +Elf4(ETS)/BMDM-Elf4-ChIP-Seq(GSE88699)/Homer ACTTCCKGKT 1e-4 -1.082e+01 0.0005 760.0 19.00% 618.9 15.53% +Tcf7(HMG)/GM12878-TCF7-ChIP-Seq(Encode)/Homer CTTTGATGTGSB 1e-4 -1.047e+01 0.0007 270.0 6.75% 185.0 4.64% +SGR5(C2H2)/colamp-SGR5-DAP-Seq(GSE60143)/Homer TTTGTCTTTTTT 1e-4 -9.673e+00 0.0015 517.0 12.93% 405.7 10.18% +Etv2(ETS)/ES-ER71-ChIP-Seq(GSE59402)/Homer NNAYTTCCTGHN 1e-4 -9.493e+00 0.0018 519.0 12.97% 408.4 10.24% +GRE(NR),IR3/RAW264.7-GRE-ChIP-Seq(Unpublished)/Homer VAGRACAKWCTGTYC 1e-3 -9.093e+00 0.0026 253.0 6.33% 178.0 4.47% +Maz(Zf)/HepG2-Maz-ChIP-Seq(GSE31477)/Homer GGGGGGGG 1e-3 -8.816e+00 0.0034 375.0 9.38% 284.6 7.14% +Cbf1(bHLH)/Yeast-Cbf1-ChIP-Seq(GSE29506)/Homer TCACGTGAYH 1e-3 -8.781e+00 0.0034 336.0 8.40% 250.5 6.28% +PIF5ox(bHLH)/Arabidopsis-PIF5ox-ChIP-Seq(GSE35062)/Homer BCACGTGVDN 1e-3 -8.767e+00 0.0034 904.0 22.60% 769.2 19.30% +USF1(bHLH)/GM12878-Usf1-ChIP-Seq(GSE32465)/Homer SGTCACGTGR 1e-3 -8.671e+00 0.0036 495.0 12.38% 392.4 9.85% +RUNX(Runt)/HPC7-Runx1-ChIP-Seq(GSE22178)/Homer SAAACCACAG 1e-3 -8.321e+00 0.0050 614.0 15.35% 503.8 12.64% +SPCH(bHLH)/Seedling-SPCH-ChIP-Seq(GSE57497)/Homer WNBCACGTGA 1e-3 -8.229e+00 0.0054 1328.0 33.20% 1179.7 29.59% +IDD4(C2H2)/col-IDD4-DAP-Seq(GSE60143)/Homer TTTGTCTTTWTB 1e-3 -8.129e+00 0.0059 526.0 13.15% 424.8 10.66% +SHN3(AP2EREBP)/col-SHN3-DAP-Seq(GSE60143)/Homer CCGCCGCC 1e-3 -8.070e+00 0.0061 177.0 4.42% 118.8 2.98% +BIM2(bHLH)/col-BIM2-DAP-Seq(GSE60143)/Homer NNNNCACGTGNN 1e-3 -7.848e+00 0.0075 813.0 20.32% 692.8 17.38% +PGR(NR)/EndoStromal-PGR-ChIP-Seq(GSE69539)/Homer AAGAACATWHTGTTC 1e-3 -7.793e+00 0.0077 215.0 5.38% 151.2 3.79% +Zac1(Zf)/Neuro2A-Plagl1-ChIP-Seq(GSE75942)/Homer HAWGRGGCCM 1e-3 -7.732e+00 0.0081 1716.0 42.90% 1563.6 39.23% +EHF(ETS)/LoVo-EHF-ChIP-Seq(GSE49402)/Homer AVCAGGAAGT 1e-3 -7.440e+00 0.0106 778.0 19.45% 663.5 16.65% +ARE(NR)/LNCAP-AR-ChIP-Seq(GSE27824)/Homer RGRACASNSTGTYCYB 1e-3 -7.409e+00 0.0108 182.0 4.55% 125.5 3.15% +TGA5(bZIP)/col-TGA5-DAP-Seq(GSE60143)/Homer NNGATGACGTCATCN 1e-3 -7.374e+00 0.0109 122.0 3.05% 76.8 1.93% +PIF4(bHLH)/Seedling-PIF4-ChIP-Seq(GSE35315)/Homer NNBCACGTGN 1e-3 -7.196e+00 0.0128 1032.0 25.80% 906.9 22.75% +SPDEF(ETS)/VCaP-SPDEF-ChIP-Seq(SRA014231)/Homer ASWTCCTGBT 1e-3 -6.991e+00 0.0155 836.0 20.90% 722.6 18.13% +Egr2(Zf)/Thymocytes-Egr2-ChIP-Seq(GSE34254)/Homer NGCGTGGGCGGR 1e-2 -6.590e+00 0.0228 111.0 2.77% 70.2 1.76% +RUNX2(Runt)/PCa-RUNX2-ChIP-Seq(GSE33889)/Homer NWAACCACADNN 1e-2 -6.528e+00 0.0238 576.0 14.40% 483.9 12.14% +ERF1(AP2EREBP)/colamp-ERF1-DAP-Seq(GSE60143)/Homer GGCGGCTR 1e-2 -6.386e+00 0.0270 429.0 10.72% 349.6 8.77% +RUNX1(Runt)/Jurkat-RUNX1-ChIP-Seq(GSE29180)/Homer AAACCACARM 1e-2 -6.181e+00 0.0326 753.0 18.82% 652.5 16.37% +HY5(bZIP)/colamp-HY5-DAP-Seq(GSE60143)/Homer RRTSACGTSD 1e-2 -6.091e+00 0.0352 1612.0 40.30% 1482.1 37.18% +EIL4(EIL)/Tomato-EIL4-ChIP-Seq(GSE116581)/Homer GATTCAWTGAAT 1e-2 -6.074e+00 0.0352 133.0 3.33% 90.3 2.26% +TFE3(bHLH)/MEF-TFE3-ChIP-Seq(GSE75757)/Homer GTCACGTGACYV 1e-2 -5.938e+00 0.0397 108.0 2.70% 70.6 1.77% +GRE(NR),IR3/A549-GR-ChIP-Seq(GSE32465)/Homer NRGVACABNVTGTYCY 1e-2 -5.843e+00 0.0430 133.0 3.33% 91.5 2.30% +ERF2(AP2EREBP)/colamp-ERF2-DAP-Seq(GSE60143)/Homer GGCGGCTG 1e-2 -5.711e+00 0.0484 460.0 11.50% 383.1 9.61% +Jun-AP1(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer GATGASTCATCN 1e-2 -5.704e+00 0.0484 177.0 4.42% 129.6 3.25% +BIM3(bHLH)/col-BIM3-DAP-Seq(GSE60143)/Homer TWVTCACGTGAB 1e-2 -5.672e+00 0.0489 193.0 4.83% 143.9 3.61% +NFIL3(bZIP)/HepG2-NFIL3-ChIP-Seq(Encode)/Homer VTTACGTAAYNNNNN 1e-2 -5.670e+00 0.0489 952.0 23.80% 847.7 21.27% +KLF10(Zf)/HEK293-KLF10.GFP-ChIP-Seq(GSE58341)/Homer GGGGGTGTGTCC 1e-2 -5.660e+00 0.0489 242.0 6.05% 186.4 4.68% +At5g66730(C2H2)/colamp-At5g66730-DAP-Seq(GSE60143)/Homer TTTGTCKTTTTK 1e-2 -5.588e+00 0.0510 246.0 6.15% 190.4 4.78% +Atf1(bZIP)/K562-ATF1-ChIP-Seq(GSE31477)/Homer GATGACGTCA 1e-2 -5.554e+00 0.0520 915.0 22.88% 813.4 20.41% +ATAF1(NAC)/col-ATAF1-DAP-Seq(GSE60143)/Homer YACGTMAY 1e-2 -5.428e+00 0.0582 3451.0 86.28% 3355.9 84.19% +ERF73(AP2EREBP)/col-ERF73-DAP-Seq(GSE60143)/Homer CCGCCGCC 1e-2 -5.124e+00 0.0779 437.0 10.93% 367.5 9.22% +At5g18450(AP2EREBP)/col-At5g18450-DAP-Seq(GSE60143)/Homer CACCGCTT 1e-2 -5.047e+00 0.0830 1622.0 40.55% 1507.2 37.81% +NAP(NAC)/col-NAP-DAP-Seq(GSE60143)/Homer ARGTTACGTRTN 1e-2 -5.039e+00 0.0830 2051.0 51.28% 1932.2 48.47% +TGA6(bZIP)/colamp-TGA6-DAP-Seq(GSE60143)/Homer TGACGTCABC 1e-2 -5.014e+00 0.0836 985.0 24.62% 887.1 22.25% +NAM(NAC)/col-NAM-DAP-Seq(GSE60143)/Homer RGTTRCGTRW 1e-2 -4.974e+00 0.0859 2305.0 57.63% 2187.5 54.88% +bHLH74(bHLH)/col-bHLH74-DAP-Seq(GSE60143)/Homer DRATCACGTGAB 1e-2 -4.908e+00 0.0906 271.0 6.78% 217.1 5.45% +BIM1(bHLH)/colamp-BIM1-DAP-Seq(GSE60143)/Homer NNNNNNVTCACGTGM 1e-2 -4.849e+00 0.0950 175.0 4.38% 132.9 3.33% +AT1G28160(AP2EREBP)/colamp-AT1G28160-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e-2 -4.781e+00 0.1005 1633.0 40.83% 1522.5 38.20% +CLOCK(bHLH)/Liver-Clock-ChIP-Seq(GSE39860)/Homer GHCACGTG 1e-2 -4.662e+00 0.1118 584.0 14.60% 509.9 12.79% +LRF(Zf)/Erythroblasts-ZBTB7A-ChIP-Seq(GSE74977)/Homer AAGACCCYYN 1e-2 -4.653e+00 0.1118 1040.0 26.00% 945.3 23.71% +ELF5(ETS)/T47D-ELF5-ChIP-Seq(GSE30407)/Homer ACVAGGAAGT 1e-2 -4.630e+00 0.1127 539.0 13.48% 467.7 11.73% +Ronin(THAP)/ES-Thap11-ChIP-Seq(GSE51522)/Homer RACTACAACTCCCAGVAKGC 1e-1 -4.523e+00 0.1241 9.0 0.22% 1.0 0.03% +c-Myc(bHLH)/LNCAP-cMyc-ChIP-Seq(Unpublished)/Homer VCCACGTG 1e-1 -4.358e+00 0.1446 630.0 15.75% 556.9 13.97% +TGA4(bZIP)/colamp-TGA4-DAP-Seq(GSE60143)/Homer RTGACGTCAKCW 1e-1 -4.288e+00 0.1534 394.0 9.85% 335.3 8.41% +EKLF(Zf)/Erythrocyte-Klf1-ChIP-Seq(GSE20478)/Homer NWGGGTGTGGCY 1e-1 -4.266e+00 0.1551 67.0 1.68% 43.9 1.10% +RUNX-AML(Runt)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer GCTGTGGTTW 1e-1 -4.260e+00 0.1551 442.0 11.05% 380.8 9.55% +Atf7(bZIP)/3T3L1-Atf7-ChIP-Seq(GSE56872)/Homer NGRTGACGTCAY 1e-1 -4.160e+00 0.1686 491.0 12.28% 427.8 10.73% +BMAL1(bHLH)/Liver-Bmal1-ChIP-Seq(GSE39860)/Homer GNCACGTG 1e-1 -4.140e+00 0.1701 1540.0 38.50% 1441.6 36.17% +TGA1(bZIP)/colamp-TGA1-DAP-Seq(GSE60143)/Homer TGACGTCAKC 1e-1 -4.124e+00 0.1712 515.0 12.88% 450.1 11.29% +ETS:RUNX(ETS,Runt)/Jurkat-RUNX1-ChIP-Seq(GSE17954)/Homer RCAGGATGTGGT 1e-1 -3.994e+00 0.1928 38.0 0.95% 21.5 0.54% +Smad3(MAD)/NPC-Smad3-ChIP-Seq(GSE36673)/Homer TWGTCTGV 1e-1 -3.954e+00 0.1985 1934.0 48.35% 1834.2 46.02% +CUX1(Homeobox)/K562-CUX1-ChIP-Seq(GSE92882)/Homer TATCGATNAN 1e-1 -3.936e+00 0.2001 1398.0 34.95% 1305.2 32.74% +ZNF136(Zf)/HEK293-ZNF136.GFP-ChIP-Seq(GSE58341)/Homer YTKGATAHAGTATTCTWGGTNGGCA 1e-1 -3.863e+00 0.2130 76.0 1.90% 53.0 1.33% +Atf2(bZIP)/3T3L1-Atf2-ChIP-Seq(GSE56872)/Homer NRRTGACGTCAT 1e-1 -3.852e+00 0.2132 288.0 7.20% 241.1 6.05% +CEBP(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer ATTGCGCAAC 1e-1 -3.795e+00 0.2234 939.0 23.47% 860.8 21.60% +E-box(bHLH)/Promoter/Homer SSGGTCACGTGA 1e-1 -3.759e+00 0.2294 92.0 2.30% 66.2 1.66% +Egr1(Zf)/K562-Egr1-ChIP-Seq(GSE32465)/Homer TGCGTGGGYG 1e-1 -3.757e+00 0.2294 340.0 8.50% 290.7 7.29% +ERF13(AP2EREBP)/colamp-ERF13-DAP-Seq(GSE60143)/Homer TYAGCCGCCATT 1e-1 -3.711e+00 0.2359 1049.0 26.22% 968.5 24.30% +CRE(bZIP)/Promoter/Homer CSGTGACGTCAC 1e-1 -3.691e+00 0.2385 256.0 6.40% 213.2 5.35% +TGA9(bZIP)/colamp-TGA9-DAP-Seq(GSE60143)/Homer VTGACGTC 1e-1 -3.666e+00 0.2423 1570.0 39.25% 1479.2 37.11% +bZIP50(bZIP)/colamp-bZIP50-DAP-Seq(GSE60143)/Homer GATGACGTCA 1e-1 -3.610e+00 0.2536 1649.0 41.23% 1558.7 39.10% +NPAS2(bHLH)/Liver-NPAS2-ChIP-Seq(GSE39860)/Homer KCCACGTGAC 1e-1 -3.585e+00 0.2576 886.0 22.15% 812.3 20.38% +Bach2(bZIP)/OCILy7-Bach2-ChIP-Seq(GSE44420)/Homer TGCTGAGTCA 1e-1 -3.527e+00 0.2704 142.0 3.55% 111.2 2.79% +AtIDD11(C2H2)/colamp-AtIDD11-DAP-Seq(GSE60143)/Homer TTTGTCGTTT 1e-1 -3.507e+00 0.2733 363.0 9.07% 314.7 7.90% +MYB88(MYB)/col-MYB88-DAP-Seq(GSE60143)/Homer HNACGCTCCT 1e-1 -3.455e+00 0.2854 1646.0 41.15% 1558.9 39.11% +ERF15(AP2EREBP)/colamp-ERF15-DAP-Seq(GSE60143)/Homer WDHAGCMGCCAT 1e-1 -3.427e+00 0.2910 1407.0 35.17% 1323.2 33.20% +bHLHE40(bHLH)/HepG2-BHLHE40-ChIP-Seq(GSE31477)/Homer KCACGTGMCN 1e-1 -3.426e+00 0.2910 377.0 9.43% 328.5 8.24% +Max(bHLH)/K562-Max-ChIP-Seq(GSE31477)/Homer RCCACGTGGYYN 1e-1 -3.394e+00 0.2952 573.0 14.32% 514.8 12.91% +TGA2(bZIP)/colamp-TGA2-DAP-Seq(GSE60143)/Homer ACGTCAYCHH 1e-1 -3.335e+00 0.3105 1062.0 26.55% 987.8 24.78% +Pho2(bHLH)/Yeast-Pho2-ChIP-Seq(GSE29506)/Homer CCCACGTGCT 1e-1 -3.332e+00 0.3105 448.0 11.20% 396.3 9.94% +WUS1(Homeobox)/colamp-WUS1-DAP-Seq(GSE60143)/Homer CAWTCATTCA 1e-1 -3.311e+00 0.3125 365.0 9.12% 318.2 7.98% +HLF(bZIP)/HSC-HLF.Flag-ChIP-Seq(GSE69817)/Homer RTTATGYAAB 1e-1 -3.196e+00 0.3477 1081.0 27.02% 1009.0 25.31% +MNT(bHLH)/HepG2-MNT-ChIP-Seq(Encode)/Homer DGCACACGTG 1e-1 -3.160e+00 0.3573 819.0 20.47% 755.0 18.94% +bHLHE41(bHLH)/proB-Bhlhe41-ChIP-Seq(GSE93764)/Homer KCACGTGMCN 1e-1 -3.160e+00 0.3573 1415.0 35.38% 1336.8 33.54% +Tcf3(HMG)/mES-Tcf3-ChIP-Seq(GSE11724)/Homer ASWTCAAAGG 1e-1 -3.144e+00 0.3573 169.0 4.23% 138.9 3.49% +Fra2(bZIP)/Striatum-Fra2-ChIP-Seq(GSE43429)/Homer GGATGACTCATC 1e-1 -3.140e+00 0.3573 381.0 9.53% 335.5 8.42% +TGA3(bZIP)/colamp-TGA3-DAP-Seq(GSE60143)/Homer WTGATGACGTCATCW 1e-1 -3.120e+00 0.3596 36.0 0.90% 22.8 0.57% +ESE1(AP2EREBP)/col-ESE1-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e-1 -3.112e+00 0.3598 504.0 12.60% 452.7 11.36% +Fosl2(bZIP)/3T3L1-Fosl2-ChIP-Seq(GSE56872)/Homer NATGASTCABNN 1e-1 -3.103e+00 0.3600 247.0 6.17% 210.4 5.28% +At5g65130(AP2EREBP)/colamp-At5g65130-DAP-Seq(GSE60143)/Homer CCRCCGACAWTN 1e-1 -3.098e+00 0.3600 276.0 6.90% 237.1 5.95% +PIF7(bHLH)/col-PIF7-DAP-Seq(GSE60143)/Homer CCACGTGGNH 1e-1 -3.092e+00 0.3600 185.0 4.62% 153.2 3.84% +IDD7(C2H2)/col-IDD7-DAP-Seq(GSE60143)/Homer TTTGTCKTTTTN 1e-1 -3.063e+00 0.3658 328.0 8.20% 286.8 7.20% +AT2G33550(Trihelix)/colamp-AT2G33550-DAP-Seq(GSE60143)/Homer TTTAAGGGCAYTTTT 1e-1 -3.035e+00 0.3735 1803.0 45.07% 1722.7 43.22% +MYB98(MYB)/col-MYB98-DAP-Seq(GSE60143)/Homer NWDCCGTTAC 1e-1 -2.985e+00 0.3895 642.0 16.05% 586.0 14.70% +FOXP1(Forkhead)/H9-FOXP1-ChIP-Seq(GSE31006)/Homer NYYTGTTTACHN 1e-1 -2.822e+00 0.4548 378.0 9.45% 336.4 8.44% +SeqBias: CG-repeat CGCGCGCGCG 1e-1 -2.814e+00 0.4551 1239.0 30.98% 1170.7 29.37% +n-Myc(bHLH)/mES-nMyc-ChIP-Seq(GSE11431)/Homer VRCCACGTGG 1e-1 -2.807e+00 0.4551 609.0 15.22% 557.2 13.98% +E2F3(E2F)/MEF-E2F3-ChIP-Seq(GSE71376)/Homer BTKGGCGGGAAA 1e-1 -2.805e+00 0.4551 487.0 12.17% 440.3 11.05% +GATA19(C2C2gata)/colamp-GATA19-DAP-Seq(GSE60143)/Homer ATCSGATCVG 1e-1 -2.670e+00 0.5137 180.0 4.50% 152.1 3.82% +bHLH34(bHLH)/colamp-bHLH34-DAP-Seq(GSE60143)/Homer HGWGRHWGACACGTG 1e-1 -2.670e+00 0.5137 357.0 8.92% 319.0 8.00% +GFY-Staf(?,Zf)/Promoter/Homer RACTACAATTCCCAGAAKGC 1e-1 -2.622e+00 0.5311 24.0 0.60% 14.5 0.36% +TGA10(bZIP)/colamp-TGA10-DAP-Seq(GSE60143)/Homer ATGACGTC 1e-1 -2.603e+00 0.5373 845.0 21.12% 789.4 19.80% +ANAC047(NAC)/colamp-ANAC047-DAP-Seq(GSE60143)/Homer WACACGTAACTT 1e-1 -2.593e+00 0.5387 1483.0 37.08% 1415.9 35.52% +LBD13(LOBAS2)/colamp-LBD13-DAP-Seq(GSE60143)/Homer KCCGTNWTTTBCGGC 1e-1 -2.571e+00 0.5467 1135.0 28.38% 1073.4 26.93% +ERF9(AP2EREBP)/colamp-ERF9-DAP-Seq(GSE60143)/Homer AWATGGCGGCGG 1e-1 -2.535e+00 0.5628 243.0 6.08% 212.4 5.33% +ERF104(AP2EREBP)/col-ERF104-DAP-Seq(GSE60143)/Homer GGCGGCGG 1e-1 -2.517e+00 0.5689 831.0 20.77% 777.0 19.49% +NPAS(bHLH)/Liver-NPAS-ChIP-Seq(GSE39860)/Homer NVCACGTG 1e-1 -2.490e+00 0.5805 1433.0 35.83% 1368.9 34.34% +At4g36780(BZR)/col-At4g36780-DAP-Seq(GSE60143)/Homer NNNNNNCACGTGNNN 1e-1 -2.489e+00 0.5805 385.0 9.62% 347.7 8.72% +At1g36060(AP2EREBP)/colamp-At1g36060-DAP-Seq(GSE60143)/Homer NNWWKGTCGGTG 1e-1 -2.477e+00 0.5805 988.0 24.70% 931.5 23.37% +HINFP(Zf)/K562-HINFP.eGFP-ChIP-Seq(Encode)/Homer TWVGGTCCGC 1e-1 -2.457e+00 0.5873 600.0 15.00% 554.2 13.90% +Hoxd12(Homeobox)/ChickenMSG-Hoxd12.Flag-ChIP-Seq(GSE86088)/Homer HDGYAATGAAAN 1e-1 -2.429e+00 0.6001 1552.0 38.80% 1487.7 37.32% +FOXK1(Forkhead)/HEK293-FOXK1-ChIP-Seq(GSE51673)/Homer NVWTGTTTAC 1e-1 -2.409e+00 0.6081 917.0 22.93% 863.7 21.67% +Hoxd10(Homeobox)/ChickenMSG-Hoxd10.Flag-ChIP-Seq(GSE86088)/Homer GGCMATGAAA 1e-1 -2.353e+00 0.6384 1016.0 25.40% 961.6 24.12% +Foxo1(Forkhead)/RAW-Foxo1-ChIP-Seq(Fan_et_al.)/Homer CTGTTTAC 1e-1 -2.337e+00 0.6447 1198.0 29.95% 1140.9 28.62% +BORIS(Zf)/K562-CTCFL-ChIP-Seq(GSE32465)/Homer CNNBRGCGCCCCCTGSTGGC 1e0 -2.283e+00 0.6757 43.0 1.07% 31.4 0.79% +RAP212(AP2EREBP)/col-RAP212-DAP-Seq(GSE60143)/Homer CGCCGCCATTTT 1e0 -2.273e+00 0.6783 909.0 22.73% 858.3 21.53% +At1g78700(BZR)/col-At1g78700-DAP-Seq(GSE60143)/Homer NNNNCACGTGNNNNN 1e0 -2.257e+00 0.6842 368.0 9.20% 334.5 8.39% +Cux2(Homeobox)/Liver-Cux2-ChIP-Seq(GSE35985)/Homer HNRAATCAAT 1e0 -2.251e+00 0.6842 930.0 23.25% 879.4 22.06% +ERF5(AP2EREBP)/colamp-ERF5-DAP-Seq(GSE60143)/Homer DCMGCCGCCA 1e0 -2.249e+00 0.6842 305.0 7.62% 274.4 6.88% +ELF3(ETS)/PDAC-ELF3-ChIP-Seq(GSE64557)/Homer ANCAGGAAGT 1e0 -2.219e+00 0.6972 335.0 8.38% 303.5 7.61% +RRTF1(AP2EREBP)/colamp-RRTF1-DAP-Seq(GSE60143)/Homer CCGCCGCHATTT 1e0 -2.172e+00 0.7262 507.0 12.68% 469.1 11.77% +JunD(bZIP)/K562-JunD-ChIP-Seq/Homer ATGACGTCATCN 1e0 -2.136e+00 0.7480 57.0 1.43% 44.7 1.12% +NRF(NRF)/Promoter/Homer STGCGCATGCGC 1e0 -2.134e+00 0.7480 137.0 3.43% 117.6 2.95% +ZFX(Zf)/mES-Zfx-ChIP-Seq(GSE11431)/Homer AGGCCTRG 1e0 -2.117e+00 0.7530 636.0 15.90% 595.8 14.95% +AT5G23930(mTERF)/col-AT5G23930-DAP-Seq(GSE60143)/Homer GGCGGCTG 1e0 -2.091e+00 0.7675 955.0 23.88% 907.9 22.78% +HNF6(Homeobox)/Liver-Hnf6-ChIP-Seq(ERP000394)/Homer NTATYGATCH 1e0 -2.072e+00 0.7777 1216.0 30.40% 1164.8 29.22% +MYB119(MYB)/colamp-MYB119-DAP-Seq(GSE60143)/Homer YRACCGTTACDD 1e0 -2.069e+00 0.7777 930.0 23.25% 883.3 22.16% +MGP(C2H2)/colamp-MGP-DAP-Seq(GSE60143)/Homer TTTTGTCGTTTW 1e0 -2.050e+00 0.7849 276.0 6.90% 249.0 6.25% +ERF3(AP2EREBP)/colamp-ERF3-DAP-Seq(GSE60143)/Homer ATGGCGGCGG 1e0 -2.037e+00 0.7904 656.0 16.40% 616.5 15.47% +STAT6(Stat)/Macrophage-Stat6-ChIP-Seq(GSE38377)/Homer TTCCKNAGAA 1e0 -2.027e+00 0.7933 305.0 7.62% 277.9 6.97% +NF-E2(bZIP)/K562-NFE2-ChIP-Seq(GSE31477)/Homer GATGACTCAGCA 1e0 -2.023e+00 0.7933 37.0 0.92% 27.6 0.69% +At4g28140(AP2EREBP)/colamp-At4g28140-DAP-Seq(GSE60143)/Homer DCCACCGACCAW 1e0 -2.006e+00 0.8008 443.0 11.07% 410.3 10.29% +Pho4(bHLH)/Yeast-Pho4-ChIP-Seq(GSE29506)/Homer AAGCACGTGBGD 1e0 -1.993e+00 0.8067 210.0 5.25% 187.8 4.71% +AT1G71450(AP2EREBP)/col-AT1G71450-DAP-Seq(GSE60143)/Homer DHDWTGTCGGTG 1e0 -1.986e+00 0.8073 2080.0 52.00% 2023.4 50.76% +Stat3(Stat)/mES-Stat3-ChIP-Seq(GSE11431)/Homer CTTCCGGGAA 1e0 -1.969e+00 0.8165 301.0 7.52% 274.2 6.88% +IDD5(C2H2)/colamp-IDD5-DAP-Seq(GSE60143)/Homer TTTTGTCTTTTTBTK 1e0 -1.959e+00 0.8197 259.0 6.48% 234.5 5.88% +bHLH18(bHLH)/col-bHLH18-DAP-Seq(GSE60143)/Homer CACGTGTTYCACGTG 1e0 -1.953e+00 0.8200 25.0 0.62% 17.9 0.45% +EWS:ERG-fusion(ETS)/CADO_ES1-EWS:ERG-ChIP-Seq(SRA014231)/Homer ATTTCCTGTN 1e0 -1.950e+00 0.8200 332.0 8.30% 304.5 7.64% +E-box/Arabidopsis-Promoters/Homer GCCACGTG 1e0 -1.943e+00 0.8200 577.0 14.42% 541.9 13.60% +Hoxa9(Homeobox)/ChickenMSG-Hoxa9.Flag-ChIP-Seq(GSE86088)/Homer RGCAATNAAA 1e0 -1.938e+00 0.8200 2303.0 57.57% 2248.0 56.39% +DMRT1(DM)/Testis-DMRT1-ChIP-Seq(GSE64892)/Homer TWGHWACAWTGTWDC 1e0 -1.918e+00 0.8299 228.0 5.70% 205.8 5.16% +NRF1(NRF)/MCF7-NRF1-ChIP-Seq(Unpublished)/Homer CTGCGCATGCGC 1e0 -1.917e+00 0.8299 50.0 1.25% 39.7 1.00% +Atf3(bZIP)/GBM-ATF3-ChIP-Seq(GSE33912)/Homer DATGASTCATHN 1e0 -1.906e+00 0.8299 531.0 13.28% 497.6 12.48% +Hnf6b(Homeobox)/LNCaP-Hnf6b-ChIP-Seq(GSE106305)/Homer TATTGAYY 1e0 -1.862e+00 0.8631 1413.0 35.33% 1364.2 34.22% +IBL1(bHLH)/Seedling-IBL1-ChIP-Seq(GSE51120)/Homer CACGTGCC 1e0 -1.820e+00 0.8951 1800.0 45.00% 1749.0 43.88% +LOB(LOBAS2)/col-LOB-DAP-Seq(GSE60143)/Homer CGCCGKAWWTTHCGS 1e0 -1.819e+00 0.8951 389.0 9.72% 361.3 9.06% +PUCHI(AP2EREBP)/colamp-PUCHI-DAP-Seq(GSE60143)/Homer GCGCCGTY 1e0 -1.810e+00 0.8951 828.0 20.70% 789.9 19.82% +PCF/Arabidopsis-Promoters/Homer NNWWWTGGGCYTDDN 1e0 -1.803e+00 0.8954 262.0 6.55% 239.1 6.00% +RAP26(AP2EREBP)/colamp-RAP26-DAP-Seq(GSE60143)/Homer HDATGGCGGCGG 1e0 -1.772e+00 0.9180 1574.0 39.35% 1526.7 38.30% +CEJ1(AP2EREBP)/col-CEJ1-DAP-Seq(GSE60143)/Homer WWTGTCGGTG 1e0 -1.727e+00 0.9552 1496.0 37.40% 1450.1 36.38% +HuR(?)/HEK293-HuR-CLIP-Seq(GSE87887)/Homer BTTTGGTTTG 1e0 -1.700e+00 0.9758 2253.0 56.33% 2204.5 55.30% +ERF8(AP2EREBP)/colamp-ERF8-DAP-Seq(GSE60143)/Homer CGCCGYCATW 1e0 -1.684e+00 0.9862 1526.0 38.15% 1481.8 37.17% +c-Myc(bHLH)/mES-cMyc-ChIP-Seq(GSE11431)/Homer VVCCACGTGG 1e0 -1.625e+00 1.0000 369.0 9.22% 345.7 8.67% +HAT2(Homeobox)/colamp-HAT2-DAP-Seq(GSE60143)/Homer CYAATSATTR 1e0 -1.604e+00 1.0000 955.0 23.88% 919.7 23.07% +Foxo3(Forkhead)/U2OS-Foxo3-ChIP-Seq(E-MTAB-2701)/Homer DGTAAACA 1e0 -1.588e+00 1.0000 639.0 15.97% 609.9 15.30% +MYB101(MYB)/colamp-MYB101-DAP-Seq(GSE60143)/Homer TAACNRMY 1e0 -1.574e+00 1.0000 2567.0 64.18% 2522.6 63.29% +JunB(bZIP)/DendriticCells-Junb-ChIP-Seq(GSE36099)/Homer RATGASTCAT 1e0 -1.572e+00 1.0000 440.0 11.00% 415.9 10.43% +STAT5(Stat)/mCD4+-Stat5-ChIP-Seq(GSE12346)/Homer RTTTCTNAGAAA 1e0 -1.563e+00 1.0000 152.0 3.80% 137.6 3.45% +ANAC013(NAC)/col-ANAC013-DAP-Seq(GSE60143)/Homer CTTGNNNNNCAAGNA 1e0 -1.555e+00 1.0000 344.0 8.60% 322.3 8.09% +Fra1(bZIP)/BT549-Fra1-ChIP-Seq(GSE46166)/Homer NNATGASTCATH 1e0 -1.550e+00 1.0000 457.0 11.43% 432.8 10.86% +SeqBias: CA-repeat CACACACACA 1e0 -1.542e+00 1.0000 2556.0 63.90% 2512.3 63.03% +ERF11(AP2EREBP)/col-ERF11-DAP-Seq(GSE60143)/Homer RTGGCGGCGG 1e0 -1.529e+00 1.0000 1029.0 25.72% 994.5 24.95% +MYB118(MYB)/colamp-MYB118-DAP-Seq(GSE60143)/Homer TAWCCGTTAC 1e0 -1.519e+00 1.0000 783.0 19.57% 752.8 18.89% +ABF2(bZIP)/col-ABF2-DAP-Seq(GSE60143)/Homer KGMCACGTGDCMHHH 1e0 -1.507e+00 1.0000 275.0 6.88% 256.1 6.43% +Tbx20(T-box)/Heart-Tbx20-ChIP-Seq(GSE29636)/Homer GGTGYTGACAGS 1e0 -1.503e+00 1.0000 125.0 3.12% 112.2 2.81% +ZNF675(Zf)/HEK293-ZNF675.GFP-ChIP-Seq(GSE58341)/Homer ARGAGGMCAAAATGW 1e0 -1.502e+00 1.0000 72.0 1.80% 62.4 1.56% +ERE(NR),IR3/MCF7-ERa-ChIP-Seq(Unpublished)/Homer VAGGTCACNSTGACC 1e0 -1.498e+00 1.0000 126.0 3.15% 114.0 2.86% +CRF4(AP2EREBP)/colamp-CRF4-DAP-Seq(GSE60143)/Homer CGCCGCCA 1e0 -1.497e+00 1.0000 460.0 11.50% 436.9 10.96% +E2F4(E2F)/K562-E2F4-ChIP-Seq(GSE31477)/Homer GGCGGGAAAH 1e0 -1.493e+00 1.0000 706.0 17.65% 677.1 16.99% +STAT4(Stat)/CD4-Stat4-ChIP-Seq(GSE22104)/Homer NYTTCCWGGAAR 1e0 -1.483e+00 1.0000 563.0 14.07% 537.2 13.48% +AR-halfsite(NR)/LNCaP-AR-ChIP-Seq(GSE27824)/Homer CCAGGAACAG 1e0 -1.456e+00 1.0000 2170.0 54.25% 2129.0 53.41% +AT5G05550(Trihelix)/col-AT5G05550-DAP-Seq(GSE60143)/Homer HDNHDTCKCCGGMGA 1e0 -1.454e+00 1.0000 1893.0 47.33% 1853.7 46.50% +ERF10(AP2EREBP)/col-ERF10-DAP-Seq(GSE60143)/Homer RTGGCGGCGG 1e0 -1.446e+00 1.0000 607.0 15.17% 581.4 14.59% +FOXK2(Forkhead)/U2OS-FOXK2-ChIP-Seq(E-MTAB-2204)/Homer SCHTGTTTACAT 1e0 -1.446e+00 1.0000 509.0 12.72% 485.5 12.18% +At5g08750(C3H)/col-At5g08750-DAP-Seq(GSE60143)/Homer NWDTTGCGGCTR 1e0 -1.439e+00 1.0000 1265.0 31.62% 1230.9 30.88% +Hoxa10(Homeobox)/ChickenMSG-Hoxa10.Flag-ChIP-Seq(GSE86088)/Homer GGYAATGAAA 1e0 -1.437e+00 1.0000 472.0 11.80% 449.6 11.28% +VND6(NAC)/col-VND6-DAP-Seq(GSE60143)/Homer DCTTNHTTTTYAMGY 1e0 -1.437e+00 1.0000 1272.0 31.80% 1237.5 31.04% +AT4G18450(AP2EREBP)/col-AT4G18450-DAP-Seq(GSE60143)/Homer ATGGCGGCKG 1e0 -1.434e+00 1.0000 282.0 7.05% 264.8 6.64% +FOXA1:AR(Forkhead,NR)/LNCAP-AR-ChIP-Seq(GSE27824)/Homer AGTAAACAAAAAAGAACAND 1e0 -1.431e+00 1.0000 18.0 0.45% 13.1 0.33% +ZNF322(Zf)/HEK293-ZNF322.GFP-ChIP-Seq(GSE58341)/Homer GAGCCTGGTACTGWGCCTGR 1e0 -1.430e+00 1.0000 51.0 1.27% 43.7 1.10% +ARF2(ARF)/col-ARF2-DAP-Seq(GSE60143)/Homer TTGTCGGMWN 1e0 -1.421e+00 1.0000 2271.0 56.77% 2231.9 55.99% +E2FA(E2FDP)/colamp-E2FA-DAP-Seq(GSE60143)/Homer WWTGGCGCCAWWWNN 1e0 -1.421e+00 1.0000 1222.0 30.55% 1188.8 29.82% +ERF4(AP2EREBP)/colamp-ERF4-DAP-Seq(GSE60143)/Homer WDWTGGCGGCGG 1e0 -1.416e+00 1.0000 1343.0 33.58% 1308.9 32.84% +ABF1/SacCer-Promoters/Homer CGTRNAAARTGA 1e0 -1.411e+00 1.0000 654.0 16.35% 628.3 15.76% +AT3G57600(AP2EREBP)/col-AT3G57600-DAP-Seq(GSE60143)/Homer GGCGGTGG 1e0 -1.410e+00 1.0000 454.0 11.35% 432.2 10.84% +ERF105(AP2EREBP)/colamp-ERF105-DAP-Seq(GSE60143)/Homer TGGCGGCT 1e0 -1.409e+00 1.0000 1073.0 26.82% 1041.7 26.13% +GFY(?)/Promoter/Homer ACTACAATTCCC 1e0 -1.406e+00 1.0000 40.0 1.00% 33.9 0.85% +AARE(HLH)/mES-cMyc-ChIP-Seq/Homer GATTGCATCA 1e0 -1.397e+00 1.0000 88.0 2.20% 78.5 1.97% +PHA-4(Forkhead)/cElegans-Embryos-PHA4-ChIP-Seq(modEncode)/Homer KTGTTTGC 1e0 -1.395e+00 1.0000 2216.0 55.40% 2177.1 54.62% +CRF10(AP2EREBP)/col100-CRF10-DAP-Seq(GSE60143)/Homer DCCGCCGYHA 1e0 -1.389e+00 1.0000 1584.0 39.60% 1548.8 38.86% +EBNA1(EBV-virus)/Raji-EBNA1-ChIP-Seq(GSE30709)/Homer GGYAGCAYDTGCTDCCCNNN 1e0 -1.383e+00 1.0000 2.0 0.05% 0.0 0.00% +DMRT6(DM)/Testis-DMRT6-ChIP-Seq(GSE60440)/Homer YDGHTACAWTGTADC 1e0 -1.377e+00 1.0000 187.0 4.67% 173.8 4.36% +Zfp281(Zf)/ES-Zfp281-ChIP-Seq(GSE81042)/Homer CCCCTCCCCCAC 1e0 -1.370e+00 1.0000 12.0 0.30% 8.8 0.22% +VND2(NAC)/col-VND2-DAP-Seq(GSE60143)/Homer DNCKTNNNNNNNAAG 1e0 -1.358e+00 1.0000 1035.0 25.87% 1005.1 25.22% +FEA4(bZIP)/Corn-FEA4-ChIP-Seq(GSE61954)/Homer TGACGTCACS 1e0 -1.353e+00 1.0000 1141.0 28.52% 1110.2 27.85% +MYB56(MYB)/colamp-MYB56-DAP-Seq(GSE60143)/Homer HTAACGRMHY 1e0 -1.351e+00 1.0000 1630.0 40.75% 1595.2 40.02% +PAX5(Paired,Homeobox)/GM12878-PAX5-ChIP-Seq(GSE32465)/Homer GCAGCCAAGCRTGACH 1e0 -1.350e+00 1.0000 299.0 7.47% 282.9 7.10% +WT1(Zf)/Kidney-WT1-ChIP-Seq(GSE90016)/Homer MCTCCCMCRCAB 1e0 -1.322e+00 1.0000 181.0 4.52% 168.6 4.23% +STAT6(Stat)/CD4-Stat6-ChIP-Seq(GSE22104)/Homer ABTTCYYRRGAA 1e0 -1.305e+00 1.0000 292.0 7.30% 276.3 6.93% +ANAC071(NAC)/col-ANAC071-DAP-Seq(GSE60143)/Homer DNCKTNDNNNHNAAG 1e0 -1.298e+00 1.0000 1024.0 25.60% 996.8 25.01% +CBF4(AP2EREBP)/colamp-CBF4-DAP-Seq(GSE60143)/Homer NRCCGACDWNNNNNN 1e0 -1.285e+00 1.0000 1271.0 31.77% 1241.2 31.14% +Znf263(Zf)/K562-Znf263-ChIP-Seq(GSE31477)/Homer CVGTSCTCCC 1e0 -1.284e+00 1.0000 673.0 16.83% 650.7 16.32% +Bach1(bZIP)/K562-Bach1-ChIP-Seq(GSE31477)/Homer AWWNTGCTGAGTCAT 1e0 -1.276e+00 1.0000 38.0 0.95% 33.0 0.83% +ANAC005(NAC)/col-ANAC005-DAP-Seq(GSE60143)/Homer WVCTTVTWNHABAAG 1e0 -1.273e+00 1.0000 317.0 7.92% 301.3 7.56% +SUT1?/SacCer-Promoters/Homer CCCCGCGC 1e0 -1.270e+00 1.0000 3685.0 92.12% 3657.4 91.75% +CBF1(AP2EREBP)/colamp-CBF1-DAP-Seq(GSE60143)/Homer YRCCGACATN 1e0 -1.269e+00 1.0000 1114.0 27.85% 1086.5 27.26% +BATF(bZIP)/Th17-BATF-ChIP-Seq(GSE39756)/Homer DATGASTCAT 1e0 -1.260e+00 1.0000 528.0 13.20% 508.2 12.75% +STAT1(Stat)/HelaS3-STAT1-ChIP-Seq(GSE12782)/Homer NATTTCCNGGAAAT 1e0 -1.251e+00 1.0000 152.0 3.80% 141.6 3.55% +ABR1(AP2EREBP)/colamp-ABR1-DAP-Seq(GSE60143)/Homer AAATGGCGGCGG 1e0 -1.238e+00 1.0000 1348.0 33.70% 1319.1 33.09% +ZML1(C2C2gata)/colamp-ZML1-DAP-Seq(GSE60143)/Homer ATCWYRACCGTTSRW 1e0 -1.229e+00 1.0000 43.0 1.07% 37.2 0.93% +PU.1(ETS)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer AGAGGAAGTG 1e0 -1.210e+00 1.0000 205.0 5.12% 193.0 4.84% +Bcl6(Zf)/Liver-Bcl6-ChIP-Seq(GSE31578)/Homer NNNCTTTCCAGGAAA 1e0 -1.204e+00 1.0000 555.0 13.88% 536.5 13.46% +EGL-5(Homeobox)/cElegans-L3-EGL5-ChIP-Seq(modEncode)/Homer ATTTAATGGG 1e0 -1.193e+00 1.0000 1432.0 35.80% 1404.4 35.23% +Replumless(BLH)/Arabidopsis-RPL.GFP-ChIP-Seq(GSE78727)/Homer HGTCWHATCA 1e0 -1.186e+00 1.0000 1207.0 30.18% 1181.2 29.63% +EIN3(EIL)/col-EIN3-DAP-Seq(GSE60143)/Homer ARATTCAATGWATYT 1e0 -1.184e+00 1.0000 120.0 3.00% 111.1 2.79% +DREB19(AP2EREBP)/colamp-DREB19-DAP-Seq(GSE60143)/Homer AATGTCGGTK 1e0 -1.180e+00 1.0000 826.0 20.65% 804.9 20.19% +ANAC004(NAC)/colamp-ANAC004-DAP-Seq(GSE60143)/Homer WNCTTVYNNNRBAAG 1e0 -1.176e+00 1.0000 227.0 5.67% 215.4 5.40% +AT3G10030(Trihelix)/colamp-AT3G10030-DAP-Seq(GSE60143)/Homer GCCGTTAA 1e0 -1.176e+00 1.0000 1529.0 38.22% 1501.3 37.66% +CBF3(AP2EREBP)/colamp-CBF3-DAP-Seq(GSE60143)/Homer YNRCCGACATNN 1e0 -1.175e+00 1.0000 839.0 20.97% 817.5 20.51% +EBF1(EBF)/Near-E2A-ChIP-Seq(GSE21512)/Homer GTCCCCWGGGGA 1e0 -1.175e+00 1.0000 316.0 7.90% 302.4 7.59% +c-Jun-CRE(bZIP)/K562-cJun-ChIP-Seq(GSE31477)/Homer ATGACGTCATCY 1e0 -1.174e+00 1.0000 190.0 4.75% 180.0 4.52% +ANAC053(NAC)/colamp-ANAC053-DAP-Seq(GSE60143)/Homer TDCTTGNNNNNCAAG 1e0 -1.170e+00 1.0000 485.0 12.12% 468.1 11.74% +MYB105(MYB)/colamp-MYB105-DAP-Seq(GSE60143)/Homer RATWCCGTTA 1e0 -1.165e+00 1.0000 1300.0 32.50% 1274.5 31.97% +SpiB(ETS)/OCILY3-SPIB-ChIP-Seq(GSE56857)/Homer AAAGRGGAAGTG 1e0 -1.161e+00 1.0000 100.0 2.50% 93.0 2.33% +AP-1(bZIP)/ThioMac-PU.1-ChIP-Seq(GSE21512)/Homer VTGACTCATC 1e0 -1.157e+00 1.0000 571.0 14.27% 553.6 13.89% +AS2(LOBAS2)/col-AS2-DAP-Seq(GSE60143)/Homer CCGDAAWWHMCGSCG 1e0 -1.155e+00 1.0000 102.0 2.55% 94.1 2.36% +ERF7(AP2EREBP)/col-ERF7-DAP-Seq(GSE60143)/Homer ATGRCGGCGG 1e0 -1.154e+00 1.0000 1501.0 37.52% 1474.8 37.00% +Unknown3/Arabidopsis-Promoters/Homer AYTAAACCGG 1e0 -1.154e+00 1.0000 510.0 12.75% 493.7 12.39% +ZNF41(Zf)/HEK293-ZNF41.GFP-ChIP-Seq(GSE58341)/Homer CCTCATGGTGYCYTWYTCCCTTGTG 1e0 -1.149e+00 1.0000 10.0 0.25% 7.9 0.20% +At1g19210(AP2EREBP)/colamp-At1g19210-DAP-Seq(GSE60143)/Homer HCACCGACCAHN 1e0 -1.148e+00 1.0000 1951.0 48.77% 1922.4 48.23% +OCT4-SOX2-TCF-NANOG(POU,Homeobox,HMG)/mES-Oct4-ChIP-Seq(GSE11431)/Homer ATTTGCATAACAATG 1e0 -1.147e+00 1.0000 78.0 1.95% 71.6 1.80% +Fox:Ebox(Forkhead,bHLH)/Panc1-Foxa2-ChIP-Seq(GSE47459)/Homer NNNVCTGWGYAAACASN 1e0 -1.145e+00 1.0000 595.0 14.88% 577.4 14.49% +SMB(NAC)/colamp-SMB-DAP-Seq(GSE60143)/Homer CTTVNNNNDBAAGHW 1e0 -1.141e+00 1.0000 1047.0 26.17% 1024.5 25.70% +PLT1(AP2EREBP)/colamp-PLT1-DAP-Seq(GSE60143)/Homer GCACGAWTYCCGAGG 1e0 -1.140e+00 1.0000 107.0 2.67% 99.5 2.50% +IRF4(IRF)/GM12878-IRF4-ChIP-Seq(GSE32465)/Homer ACTGAAACCA 1e0 -1.122e+00 1.0000 377.0 9.43% 363.9 9.13% +ABF1(bZIP)/Arabidopsis-ABF1-ChIP-Seq(GSE80564)/Homer CACGTGGC 1e0 -1.116e+00 1.0000 829.0 20.72% 809.1 20.30% +Atf4(bZIP)/MEF-Atf4-ChIP-Seq(GSE35681)/Homer MTGATGCAAT 1e0 -1.116e+00 1.0000 329.0 8.22% 316.2 7.93% +SPL1(SBP)/colamp-SPL1-DAP-Seq(GSE60143)/Homer HYGTACDTWH 1e0 -1.112e+00 1.0000 2685.0 67.12% 2656.9 66.65% +Stat3+il21(Stat)/CD4-Stat3-ChIP-Seq(GSE19198)/Homer SVYTTCCNGGAARB 1e0 -1.104e+00 1.0000 402.0 10.05% 388.9 9.76% +VND1(NAC)/col-VND1-DAP-Seq(GSE60143)/Homer CTTRWDNHWYAAGYW 1e0 -1.103e+00 1.0000 871.0 21.77% 851.3 21.36% +ANAC094(NAC)/col-ANAC094-DAP-Seq(GSE60143)/Homer DVCGTRNNNNNYACG 1e0 -1.101e+00 1.0000 879.0 21.98% 859.1 21.55% +CAMTA1(CAMTA)/col-CAMTA1-DAP-Seq(GSE60143)/Homer WWAACGCGTT 1e0 -1.100e+00 1.0000 1362.0 34.05% 1338.8 33.59% +LBD23(LOBAS2)/colamp-LBD23-DAP-Seq(GSE60143)/Homer GCGNAWWWTNCGCYW 1e0 -1.098e+00 1.0000 1533.0 38.32% 1508.3 37.84% +ZSCAN22(Zf)/HEK293-ZSCAN22.GFP-ChIP-Seq(GSE58341)/Homer SMCAGTCWGAKGGAGGAGGC 1e0 -1.095e+00 1.0000 12.0 0.30% 9.9 0.25% +ANAC057(NAC)/colamp-ANAC057-DAP-Seq(GSE60143)/Homer DVCKTGNNNNNCAMG 1e0 -1.091e+00 1.0000 813.0 20.32% 794.9 19.94% +TCP3(TCP)/colamp-TCP3-DAP-Seq(GSE60143)/Homer WGTGGTCCCAAHWWW 1e0 -1.089e+00 1.0000 208.0 5.20% 198.6 4.98% +AT1G76870(Trihelix)/col-AT1G76870-DAP-Seq(GSE60143)/Homer AAAACCRGWW 1e0 -1.089e+00 1.0000 492.0 12.30% 478.0 11.99% +Reverb(NR),DR2/RAW-Reverba.biotin-ChIP-Seq(GSE45914)/Homer GTRGGTCASTGGGTCA 1e0 -1.086e+00 1.0000 45.0 1.12% 40.5 1.02% +NAC2(NAC)/colamp-NAC2-DAP-Seq(GSE60143)/Homer TDCTTGNNNNNCAAG 1e0 -1.082e+00 1.0000 578.0 14.45% 562.2 14.10% +bZIP68(bZIP)/col-bZIP68-DAP-Seq(GSE60143)/Homer WGCCACGTGK 1e0 -1.075e+00 1.0000 519.0 12.97% 504.6 12.66% +EFL-1(E2F)/cElegans-L1-EFL1-ChIP-Seq(modEncode)/Homer TGCAARYGCGCTCYA 1e0 -1.070e+00 1.0000 28.0 0.70% 24.6 0.62% +PAX5(Paired,Homeobox),condensed/GM12878-PAX5-ChIP-Seq(GSE32465)/Homer GTCACGCTCSCTGM 1e0 -1.064e+00 1.0000 75.0 1.88% 69.2 1.74% +TEAD(TEA)/Fibroblast-PU.1-ChIP-Seq(Unpublished)/Homer YCWGGAATGY 1e0 -1.057e+00 1.0000 411.0 10.27% 398.2 9.99% +MYB65(MYB)/colamp-MYB65-DAP-Seq(GSE60143)/Homer RACNGTTA 1e0 -1.054e+00 1.0000 1899.0 47.48% 1874.4 47.02% +DEAR3(AP2EREBP)/colamp-DEAR3-DAP-Seq(GSE60143)/Homer BCACCGACAWNNNNN 1e0 -1.046e+00 1.0000 582.0 14.55% 567.5 14.24% +GBF3(bZIP)/Arabidopsis-GBF3-ChIP-Seq(GSE80564)/Homer TGCCACGTSAYC 1e0 -1.038e+00 1.0000 376.0 9.40% 364.3 9.14% +bZIP28(bZIP)/col-bZIP28-DAP-Seq(GSE60143)/Homer TGCCACGTSABH 1e0 -1.032e+00 1.0000 387.0 9.68% 375.7 9.43% +DREF/Drosophila-Promoters/Homer AVYTATCGATAD 1e0 -1.018e+00 1.0000 92.0 2.30% 86.3 2.16% +GATA14(C2C2gata)/col-GATA14-DAP-Seq(GSE60143)/Homer AYCAGATCTG 1e0 -1.009e+00 1.0000 686.0 17.15% 671.1 16.84% +MafA(bZIP)/Islet-MafA-ChIP-Seq(GSE30298)/Homer TGCTGACTCA 1e0 -1.009e+00 1.0000 507.0 12.68% 494.9 12.42% +TCFL2(HMG)/K562-TCF7L2-ChIP-Seq(GSE29196)/Homer ACWTCAAAGG 1e0 -1.008e+00 1.0000 37.0 0.92% 33.4 0.84% +ZIM(C2C2gata)/col-ZIM-DAP-Seq(GSE60143)/Homer ATCSRACGGTYRAGA 1e0 -1.008e+00 1.0000 37.0 0.92% 33.5 0.84% +SPL11(SBP)/col100-SPL11-DAP-Seq(GSE60143)/Homer YTGTACTTBH 1e0 -1.002e+00 1.0000 815.0 20.38% 799.8 20.06% +VND4(NAC)/colamp-VND4-DAP-Seq(GSE60143)/Homer WRCTTGWANWWCAAG 1e0 -9.981e-01 1.0000 829.0 20.72% 813.6 20.41% +GBF5(bZIP)/colamp-GBF5-DAP-Seq(GSE60143)/Homer WKNWSACGTGGCAWN 1e0 -9.910e-01 1.0000 389.0 9.72% 378.5 9.50% +DDF2(AP2EREBP)/col-DDF2-DAP-Seq(GSE60143)/Homer GATGTCGRCR 1e0 -9.843e-01 1.0000 109.0 2.73% 103.9 2.61% +THRb(NR)/HepG2-THRb.Flag-ChIP-Seq(Encode)/Homer GGTCACCTGAGGTCA 1e0 -9.789e-01 1.0000 271.0 6.78% 262.8 6.59% +DEAR2(AP2EREBP)/colamp-DEAR2-DAP-Seq(GSE60143)/Homer HCACCGACAWHD 1e0 -9.709e-01 1.0000 1583.0 39.57% 1563.6 39.23% +Gata6(Zf)/HUG1N-GATA6-ChIP-Seq(GSE51936)/Homer YCTTATCTBN 1e0 -9.699e-01 1.0000 1088.0 27.20% 1071.9 26.89% +EBF(EBF)/proBcell-EBF-ChIP-Seq(GSE21978)/Homer DGTCCCYRGGGA 1e0 -9.665e-01 1.0000 79.0 1.98% 74.6 1.87% +bHLH157(bHLH)/col-bHLH157-DAP-Seq(GSE60143)/Homer KACACGTCTCTY 1e0 -9.639e-01 1.0000 366.0 9.15% 356.7 8.95% +GAGA-repeat/SacCer-Promoters/Homer CTYTCTYTCTCTCTC 1e0 -9.576e-01 1.0000 1500.0 37.50% 1481.4 37.16% +At2g33710(AP2EREBP)/colamp-At2g33710-DAP-Seq(GSE60143)/Homer WTKGCGGCKR 1e0 -9.501e-01 1.0000 2046.0 51.15% 2025.8 50.82% +ANAC016(NAC)/col-ANAC016-DAP-Seq(GSE60143)/Homer WNCTTGNNNNNCAMG 1e0 -9.488e-01 1.0000 800.0 20.00% 786.2 19.72% +At1g75490(AP2EREBP)/colamp-At1g75490-DAP-Seq(GSE60143)/Homer CACCGMCT 1e0 -9.421e-01 1.0000 2590.0 64.75% 2568.8 64.44% +IRF:BATF(IRF:bZIP)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer CTTTCANTATGACTV 1e0 -9.402e-01 1.0000 54.0 1.35% 50.6 1.27% +Nrf2(bZIP)/Lymphoblast-Nrf2-ChIP-Seq(GSE37589)/Homer HTGCTGAGTCAT 1e0 -9.362e-01 1.0000 26.0 0.65% 23.2 0.58% +WRKY28(WRKY)/col-WRKY28-DAP-Seq(GSE60143)/Homer BGTTGACTWH 1e0 -9.312e-01 1.0000 1173.0 29.33% 1157.3 29.03% +Unknown5/Drosophila-Promoters/Homer GCTGATAASV 1e0 -9.290e-01 1.0000 893.0 22.32% 879.2 22.06% +FoxD3(forkhead)/ZebrafishEmbryo-Foxd3.biotin-ChIP-seq(GSE106676)/Homer TGTTTAYTTAGC 1e0 -9.224e-01 1.0000 463.0 11.58% 453.5 11.38% +CTCF(Zf)/CD4+-CTCF-ChIP-Seq(Barski_et_al.)/Homer AYAGTGCCMYCTRGTGGCCA 1e0 -9.199e-01 1.0000 29.0 0.73% 26.5 0.66% +GATA1(C2C2gata)/colamp-GATA1-DAP-Seq(GSE60143)/Homer DDWWYYAGATCTRRW 1e0 -9.199e-01 1.0000 378.0 9.45% 369.8 9.28% +ERF115(AP2EREBP)/colamp-ERF115-DAP-Seq(GSE60143)/Homer WTKRCGGCGB 1e0 -9.176e-01 1.0000 1902.0 47.55% 1883.2 47.25% +DREB2(AP2EREBP)/col-DREB2-DAP-Seq(GSE60143)/Homer TMACCGACATWA 1e0 -9.162e-01 1.0000 699.0 17.47% 687.3 17.24% +Foxf1(Forkhead)/Lung-Foxf1-ChIP-Seq(GSE77951)/Homer WWATRTAAACAN 1e0 -9.150e-01 1.0000 704.0 17.60% 692.9 17.38% +AT3G16280(AP2EREBP)/colamp-AT3G16280-DAP-Seq(GSE60143)/Homer HCACCGACAHHDHHN 1e0 -9.105e-01 1.0000 723.0 18.07% 711.6 17.85% +FXR(NR),IR1/Liver-FXR-ChIP-Seq(Chong_et_al.)/Homer AGGTCANTGACCTB 1e0 -9.096e-01 1.0000 238.0 5.95% 232.0 5.82% +SRS7(SRS)/colamp-SRS7-DAP-Seq(GSE60143)/Homer HATAGGTTTH 1e0 -9.093e-01 1.0000 3200.0 80.00% 3179.3 79.76% +ANAC042(NAC)/col-ANAC042-DAP-Seq(GSE60143)/Homer CGTNDHNDHNACGKY 1e0 -9.044e-01 1.0000 1194.0 29.85% 1179.1 29.58% +DUX4(Homeobox)/Myoblasts-DUX4.V5-ChIP-Seq(GSE75791)/Homer NWTAAYCYAATCAWN 1e0 -9.022e-01 1.0000 33.0 0.83% 30.2 0.76% +AT2G31460(REMB3)/col-AT2G31460-DAP-Seq(GSE60143)/Homer WNWARWDGAAATGAT 1e0 -9.008e-01 1.0000 181.0 4.52% 175.0 4.39% +PAX3:FKHR-fusion(Paired,Homeobox)/Rh4-PAX3:FKHR-ChIP-Seq(GSE19063)/Homer ACCRTGACTAATTNN 1e0 -9.005e-01 1.0000 253.0 6.33% 246.1 6.17% +ASL18(LOBAS2)/colamp-ASL18-DAP-Seq(GSE60143)/Homer CCGGAAAWTCMGGAR 1e0 -8.996e-01 1.0000 1414.0 35.35% 1398.2 35.08% +Mouse_Recombination_Hotspot(Zf)/Testis-DMC1-ChIP-Seq(GSE24438)/Homer ACTYKNATTCGTGNTACTTC 1e0 -8.982e-01 1.0000 34.0 0.85% 31.7 0.79% +NST1(NAC)/colamp-NST1-DAP-Seq(GSE60143)/Homer WRCTTRWWNWWYAAG 1e0 -8.970e-01 1.0000 926.0 23.15% 914.0 22.93% +ANAC020(NAC)/col-ANAC020-DAP-Seq(GSE60143)/Homer DVCKTGHNNNDCAAG 1e0 -8.969e-01 1.0000 659.0 16.48% 648.1 16.26% +GATA6(C2C2gata)/col200-GATA6-DAP-Seq(GSE60143)/Homer TAGATCTARAHH 1e0 -8.922e-01 1.0000 128.0 3.20% 123.6 3.10% +DDF1(AP2EREBP)/col-DDF1-DAP-Seq(GSE60143)/Homer GCCGACAT 1e0 -8.898e-01 1.0000 823.0 20.57% 811.2 20.35% +SPL15(SBP)/colamp-SPL15-DAP-Seq(GSE60143)/Homer WDWMMGTACADW 1e0 -8.860e-01 1.0000 2365.0 59.13% 2346.7 58.87% +CBF2(AP2EREBP)/colamp-CBF2-DAP-Seq(GSE60143)/Homer YBRCCGACATNNNNN 1e0 -8.809e-01 1.0000 872.0 21.80% 860.6 21.59% +NTM2(NAC)/col-NTM2-DAP-Seq(GSE60143)/Homer CTTRTNNNAYAAGBH 1e0 -8.777e-01 1.0000 499.0 12.47% 490.1 12.29% +bZIP16(bZIP)/colamp-bZIP16-DAP-Seq(GSE60143)/Homer TGCCACGTGD 1e0 -8.721e-01 1.0000 409.0 10.22% 401.1 10.06% +WRKY6(WRKY)/colamp-WRKY6-DAP-Seq(GSE60143)/Homer NCGTTGACTWWD 1e0 -8.702e-01 1.0000 787.0 19.68% 776.2 19.47% +VND3(NAC)/colamp-VND3-DAP-Seq(GSE60143)/Homer TRCTTGWDNHWCAAG 1e0 -8.683e-01 1.0000 659.0 16.48% 649.9 16.30% +Unknown1/Arabidopsis-Promoters/Homer RGGGTAWWWTHGTAA 1e0 -8.641e-01 1.0000 95.0 2.38% 91.4 2.29% +BAM8(BES1)/col-BAM8-DAP-Seq(GSE60143)/Homer NNWSACACGTGTSWN 1e0 -8.555e-01 1.0000 172.0 4.30% 168.0 4.21% +bZIP3(bZIP)/col-bZIP3-DAP-Seq(GSE60143)/Homer DWKNHSACGTGGCAD 1e0 -8.521e-01 1.0000 602.0 15.05% 593.2 14.88% +MafK(bZIP)/C2C12-MafK-ChIP-Seq(GSE36030)/Homer GCTGASTCAGCA 1e0 -8.489e-01 1.0000 109.0 2.73% 105.1 2.64% +ANAC083(NAC)/col-ANAC083-DAP-Seq(GSE60143)/Homer CKTRWNNNWYAMGTA 1e0 -8.420e-01 1.0000 962.0 24.05% 951.3 23.87% +bZIP48(bZIP)/colamp-bZIP48-DAP-Seq(GSE60143)/Homer DDWWKVTSACGTGGC 1e0 -8.375e-01 1.0000 410.0 10.25% 403.5 10.12% +JKD(C2H2)/col-JKD-DAP-Seq(GSE60143)/Homer TTTTGTCGTTTT 1e0 -8.372e-01 1.0000 122.0 3.05% 118.6 2.97% +RAP211(AP2EREBP)/colamp-RAP211-DAP-Seq(GSE60143)/Homer RGCCGGCYWW 1e0 -8.301e-01 1.0000 1948.0 48.70% 1933.2 48.50% +Foxa3(Forkhead)/Liver-Foxa3-ChIP-Seq(GSE77670)/Homer BSNTGTTTACWYWGN 1e0 -8.208e-01 1.0000 238.0 5.95% 233.3 5.85% +At2g44940(AP2EREBP)/colamp-At2g44940-DAP-Seq(GSE60143)/Homer NYACCGACAHNNNNN 1e0 -8.049e-01 1.0000 407.0 10.17% 401.2 10.06% +BZR1(BZR)/col-BZR1-DAP-Seq(GSE60143)/Homer NNCRCACGTGCG 1e0 -8.026e-01 1.0000 88.0 2.20% 85.6 2.15% +RKD2(RWPRK)/colamp-RKD2-DAP-Seq(GSE60143)/Homer GACKTTTCRDCTTCC 1e0 -7.983e-01 1.0000 586.0 14.65% 579.4 14.54% +FAR1(FAR1)/col-FAR1-DAP-Seq(GSE60143)/Homer TKNNNYYCACGCGCY 1e0 -7.971e-01 1.0000 189.0 4.72% 185.9 4.66% +AtGRF6(GRF)/col-AtGRF6-DAP-Seq(GSE60143)/Homer NTGTCAGADNNNNNN 1e0 -7.970e-01 1.0000 1145.0 28.62% 1135.8 28.49% +bHLH10(bHLH)/colamp-bHLH10-DAP-Seq(GSE60143)/Homer YACCGACA 1e0 -7.896e-01 1.0000 477.0 11.92% 471.7 11.83% +NFE2L2(bZIP)/HepG2-NFE2L2-ChIP-Seq(Encode)/Homer AWWWTGCTGAGTCAT 1e0 -7.878e-01 1.0000 32.0 0.80% 30.3 0.76% +ANAC070(NAC)/colamp-ANAC070-DAP-Seq(GSE60143)/Homer CTTRHDNHNBAAGHW 1e0 -7.877e-01 1.0000 1238.0 30.95% 1228.9 30.83% +At5g08330(TCP)/col-At5g08330-DAP-Seq(GSE60143)/Homer GGRCCCAC 1e0 -7.835e-01 1.0000 357.0 8.92% 352.0 8.83% +GATA4(C2C2gata)/col-GATA4-DAP-Seq(GSE60143)/Homer DDWTYAGATCTR 1e0 -7.799e-01 1.0000 894.0 22.35% 886.0 22.23% +Chop(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer ATTGCATCAT 1e0 -7.798e-01 1.0000 235.0 5.88% 231.1 5.80% +ABI5(bZIP)/col-ABI5-DAP-Seq(GSE60143)/Homer GCCACGTG 1e0 -7.791e-01 1.0000 534.0 13.35% 528.4 13.26% +HIF-1b(HLH)/T47D-HIF1b-ChIP-Seq(GSE59937)/Homer RTACGTGC 1e0 -7.773e-01 1.0000 1855.0 46.38% 1843.6 46.25% +ANAC058(NAC)/col-ANAC058-DAP-Seq(GSE60143)/Homer TWCTTGTDNNACAAG 1e0 -7.721e-01 1.0000 577.0 14.42% 571.7 14.34% +Gata2(Zf)/K562-GATA2-ChIP-Seq(GSE18829)/Homer BBCTTATCTS 1e0 -7.711e-01 1.0000 770.0 19.25% 763.3 19.15% +Knotted(Homeobox)/Corn-KN1-ChIP-Seq(GSE39161)/Homer GAYGNGACRGGN 1e0 -7.705e-01 1.0000 1431.0 35.77% 1421.9 35.67% +Pknox1(Homeobox)/ES-Prep1-ChIP-Seq(GSE63282)/Homer SCTGTCAVTCAV 1e0 -7.662e-01 1.0000 148.0 3.70% 145.5 3.65% +ANAC087(NAC)/col-ANAC087-DAP-Seq(GSE60143)/Homer WVCKTGHNNNWCAMG 1e0 -7.661e-01 1.0000 440.0 11.00% 435.3 10.92% +GATA12(C2C2gata)/col-GATA12-DAP-Seq(GSE60143)/Homer YAGATCTRAW 1e0 -7.647e-01 1.0000 627.0 15.68% 621.4 15.59% +Rap210(AP2EREBP)/col-Rap210-DAP-Seq(GSE60143)/Homer TGTCGGCA 1e0 -7.641e-01 1.0000 1040.0 26.00% 1033.0 25.91% +TCP7(TCP)/col-TCP7-DAP-Seq(GSE60143)/Homer GTGGGSCCCACHHNN 1e0 -7.588e-01 1.0000 313.0 7.83% 309.8 7.77% +PU.1-IRF(ETS:IRF)/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer MGGAAGTGAAAC 1e0 -7.569e-01 1.0000 494.0 12.35% 490.0 12.29% +PRDM10(Zf)/HEK293-PRDM10.eGFP-ChIP-Seq(Encode)/Homer TGGTACATTCCA 1e0 -7.530e-01 1.0000 340.0 8.50% 336.1 8.43% +AGL16(MADS)/col-AGL16-DAP-Seq(GSE60143)/Homer TWCCHWATWDGGAAA 1e0 -7.519e-01 1.0000 62.0 1.55% 60.1 1.51% +Gata1(Zf)/K562-GATA1-ChIP-Seq(GSE18829)/Homer SAGATAAGRV 1e0 -7.519e-01 1.0000 726.0 18.15% 720.9 18.09% +IDD2(C2H2)/colamp-IDD2-DAP-Seq(GSE60143)/Homer HAVAAAAMGACAAAA 1e0 -7.477e-01 1.0000 68.0 1.70% 66.7 1.67% +GAGA-repeat/Arabidopsis-Promoters/Homer CTCTCTCTCY 1e0 -7.471e-01 1.0000 371.0 9.28% 367.5 9.22% +ZNF7(Zf)/HepG2-ZNF7.Flag-ChIP-Seq(Encode)/Homer CTGCCWVCTTTTRTA 1e0 -7.460e-01 1.0000 377.0 9.43% 373.7 9.37% +Brachyury(T-box)/Mesoendoderm-Brachyury-ChIP-exo(GSE54963)/Homer ANTTMRCASBNNNGTGYKAAN 1e0 -7.415e-01 1.0000 225.0 5.62% 222.9 5.59% +TINY(AP2EREBP)/col-TINY-DAP-Seq(GSE60143)/Homer NNCACCGACA 1e0 -7.384e-01 1.0000 423.0 10.57% 419.3 10.52% +MYB3R5(MYB)/col-MYB3R5-DAP-Seq(GSE60143)/Homer THYAACGGTHAWAWT 1e0 -7.370e-01 1.0000 244.0 6.10% 241.4 6.06% +GRF9(GRF)/colamp-GRF9-DAP-Seq(GSE60143)/Homer NWCTGACANNNNNNN 1e0 -7.364e-01 1.0000 646.0 16.15% 641.3 16.09% +ZNF711(Zf)/SHSY5Y-ZNF711-ChIP-Seq(GSE20673)/Homer AGGCCTAG 1e0 -7.348e-01 1.0000 1128.0 28.20% 1121.7 28.14% +WRKY75(WRKY)/col-WRKY75-DAP-Seq(GSE60143)/Homer CGTTGACTWW 1e0 -7.339e-01 1.0000 897.0 22.43% 891.7 22.37% +AREB3(bZIP)/col-AREB3-DAP-Seq(GSE60143)/Homer NKGMCACGTGDCMNN 1e0 -7.331e-01 1.0000 459.0 11.47% 456.0 11.44% +PLT3(AP2EREBP)/col-PLT3-DAP-Seq(GSE60143)/Homer GCACGNWTHYCGAGG 1e0 -7.329e-01 1.0000 96.0 2.40% 94.2 2.36% +CUC3(NAC)/col-CUC3-DAP-Seq(GSE60143)/Homer TRCKTGWNNNACAMG 1e0 -7.314e-01 1.0000 471.0 11.77% 467.5 11.73% +SeqBias: GA-repeat GAGAGAGAGA 1e0 -7.307e-01 1.0000 2579.0 64.48% 2567.8 64.42% +AT3G60490(AP2EREBP)/colamp-AT3G60490-DAP-Seq(GSE60143)/Homer NNRCCGACANNNNNN 1e0 -7.293e-01 1.0000 487.0 12.17% 483.8 12.14% +E-box/Drosophila-Promoters/Homer AACAGCTGTTHN 1e0 -7.290e-01 1.0000 106.0 2.65% 104.5 2.62% +Nanog(Homeobox)/mES-Nanog-ChIP-Seq(GSE11724)/Homer RGCCATTAAC 1e0 -7.280e-01 1.0000 3298.0 82.45% 3284.4 82.40% +bZIP53(bZIP)/colamp-bZIP53-DAP-Seq(GSE60143)/Homer NDNHSACGTGKMNNN 1e0 -7.271e-01 1.0000 504.0 12.60% 500.9 12.57% +ZBTB12(Zf)/HEK293-ZBTB12.GFP-ChIP-Seq(GSE58341)/Homer NGNTCTAGAACCNGV 1e0 -7.258e-01 1.0000 301.0 7.52% 298.1 7.48% +ANAC050(NAC)/colamp-ANAC050-DAP-Seq(GSE60143)/Homer WNCTTGNNNNNCAAG 1e0 -7.257e-01 1.0000 515.0 12.88% 512.0 12.84% +ANAC092(NAC)/colamp-ANAC092-DAP-Seq(GSE60143)/Homer WRCKTGWNNNWCAMG 1e0 -7.250e-01 1.0000 521.0 13.03% 517.5 12.98% +Six2(Homeobox)/NephronProgenitor-Six2-ChIP-Seq(GSE39837)/Homer GWAAYHTGAKMC 1e0 -7.233e-01 1.0000 1016.0 25.40% 1010.5 25.35% +E2F7(E2F)/Hela-E2F7-ChIP-Seq(GSE32673)/Homer VDTTTCCCGCCA 1e0 -7.220e-01 1.0000 127.0 3.17% 125.9 3.16% +WRKY33(WRKY)/col-WRKY33-DAP-Seq(GSE60143)/Homer CGTTGACYAW 1e0 -7.184e-01 1.0000 821.0 20.52% 816.4 20.48% +HNF4a(NR),DR1/HepG2-HNF4a-ChIP-Seq(GSE25021)/Homer CARRGKBCAAAGTYCA 1e0 -7.129e-01 1.0000 163.0 4.08% 161.5 4.05% +ANAC028(NAC)/col-ANAC028-DAP-Seq(GSE60143)/Homer WRCTTGNNNNNCAAG 1e0 -7.113e-01 1.0000 646.0 16.15% 642.0 16.11% +At4g18890(BZR)/col-At4g18890-DAP-Seq(GSE60143)/Homer NDBRCACGTGYR 1e0 -7.083e-01 1.0000 185.0 4.62% 183.2 4.60% +At4g31060(AP2EREBP)/colamp-At4g31060-DAP-Seq(GSE60143)/Homer CACCGACAAW 1e0 -7.070e-01 1.0000 691.0 17.27% 687.7 17.25% +Smad4(MAD)/ESC-SMAD4-ChIP-Seq(GSE29422)/Homer VBSYGTCTGG 1e0 -7.067e-01 1.0000 1231.0 30.78% 1225.3 30.74% +ZNF467(Zf)/HEK293-ZNF467.GFP-ChIP-Seq(GSE58341)/Homer TGGGGAAGGGCM 1e0 -7.056e-01 1.0000 200.0 5.00% 198.8 4.99% +SeqBias: CG bias SSSSSSSSSS 1e0 -7.000e-01 1.0000 3989.0 99.72% 3974.4 99.71% +MYB27(MYB)/colamp-MYB27-DAP-Seq(GSE60143)/Homer TACCTAACWT 1e0 -6.977e-01 1.0000 251.0 6.28% 249.4 6.26% +E2F6(E2F)/Hela-E2F6-ChIP-Seq(GSE31477)/Homer GGCGGGAARN 1e0 -6.954e-01 1.0000 268.0 6.70% 266.4 6.68% +ZNF415(Zf)/HEK293-ZNF415.GFP-ChIP-Seq(GSE58341)/Homer GRTGMTRGAGCC 1e0 -6.935e-01 1.0000 283.0 7.07% 281.7 7.07% +ZFP3(Zf)/HEK293-ZFP3.GFP-ChIP-Seq(GSE58341)/Homer GGGTTTTGAAGGATGARTAGGAGTT 1e0 -6.914e-01 1.0000 1.0 0.03% 0.0 0.00% +ZNF528(Zf)/HEK293-ZNF528.GFP-ChIP-Seq(GSE58341)/Homer AGAAATGACTTCCCT 1e0 -6.914e-01 1.0000 1.0 0.03% 1.0 0.02% +REST-NRSF(Zf)/Jurkat-NRSF-ChIP-Seq/Homer GGMGCTGTCCATGGTGCTGA 1e0 -6.905e-01 1.0000 2.0 0.05% 1.6 0.04% +BPC6(BBRBPC)/col-BPC6-DAP-Seq(GSE60143)/Homer YTYTCTCTCTCTCTA 1e0 -6.905e-01 1.0000 2.0 0.05% 1.3 0.03% +T1ISRE(IRF)/ThioMac-Ifnb-Expression/Homer ACTTTCGTTTCT 1e0 -6.888e-01 1.0000 5.0 0.12% 4.3 0.11% +NTM1(NAC)/col-NTM1-DAP-Seq(GSE60143)/Homer ACTTRTARAASAAGT 1e0 -6.884e-01 1.0000 328.0 8.20% 326.3 8.18% +RAR:RXR(NR),DR5/ES-RAR-ChIP-Seq(GSE56893)/Homer RGGTCADNNAGAGGTCAV 1e0 -6.876e-01 1.0000 8.0 0.20% 7.9 0.20% +FoxL2(Forkhead)/Ovary-FoxL2-ChIP-Seq(GSE60858)/Homer WWTRTAAACAVG 1e0 -6.874e-01 1.0000 639.0 15.97% 636.9 15.98% +Unknown2/Arabidopsis-Promoters/Homer AAACGACGTCGTTTT 1e0 -6.861e-01 1.0000 13.0 0.33% 12.8 0.32% +Pax7(Paired,Homeobox),longest/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer NTAATTDGCYAATTANNWWD 1e0 -6.844e-01 1.0000 20.0 0.50% 19.1 0.48% +ETS:E-box(ETS,bHLH)/HPC7-Scl-ChIP-Seq(GSE22178)/Homer AGGAARCAGCTG 1e0 -6.833e-01 1.0000 25.0 0.62% 24.4 0.61% +Zfp57(Zf)/H1-ZFP57.HA-ChIP-Seq(GSE115387)/Homer NANTGCSGCA 1e0 -6.818e-01 1.0000 711.0 17.77% 708.1 17.76% +IRF2(IRF)/Erythroblas-IRF2-ChIP-Seq(GSE36985)/Homer GAAASYGAAASY 1e0 -6.789e-01 1.0000 52.0 1.30% 51.6 1.29% +WRKY26(WRKY)/colamp-WRKY26-DAP-Seq(GSE60143)/Homer CGTTGACTWDKN 1e0 -6.772e-01 1.0000 448.0 11.20% 446.9 11.21% +Duxbl(Homeobox)/NIH3T3-Duxbl.HA-ChIP-Seq(GSE119782)/Homer TAAYCYAATCAA 1e0 -6.771e-01 1.0000 66.0 1.65% 65.9 1.65% +MYB44(MYB)/colamp-MYB44-DAP-Seq(GSE60143)/Homer CVGTTWWKTCNGTTA 1e0 -6.767e-01 1.0000 69.0 1.73% 68.1 1.71% +NF1(CTF)/LNCAP-NF1-ChIP-Seq(Unpublished)/Homer CYTGGCABNSTGCCAR 1e0 -6.701e-01 1.0000 134.0 3.35% 133.6 3.35% +WRKY22(WRKY)/colamp-WRKY22-DAP-Seq(GSE60143)/Homer WWAAAGTCAACK 1e0 -6.694e-01 1.0000 551.0 13.78% 549.4 13.78% +WRKY15(WRKY)/col-WRKY15-DAP-Seq(GSE60143)/Homer VGTTGACTWW 1e0 -6.659e-01 1.0000 947.0 23.67% 944.2 23.69% +Gata4(Zf)/Heart-Gata4-ChIP-Seq(GSE35151)/Homer NBWGATAAGR 1e0 -6.657e-01 1.0000 1272.0 31.80% 1268.1 31.81% +GT3a(Trihelix)/col-GT3a-DAP-Seq(GSE60143)/Homer WNACACGTGTYWWAW 1e0 -6.637e-01 1.0000 216.0 5.40% 216.0 5.42% +ANAC011(NAC)/col-ANAC011-DAP-Seq(GSE60143)/Homer TDCTTGYRNNDCAAG 1e0 -6.634e-01 1.0000 220.0 5.50% 219.9 5.52% +REB1/SacCer-Promoters/Homer KCCGGGTAAYRR 1e0 -6.629e-01 1.0000 227.0 5.67% 227.0 5.69% +MYB(HTH)/ERMYB-Myb-ChIPSeq(GSE22095)/Homer GGCVGTTR 1e0 -6.610e-01 1.0000 2506.0 62.65% 2498.8 62.69% +Rbpj1(?)/Panc1-Rbpj1-ChIP-Seq(GSE47459)/Homer HTTTCCCASG 1e0 -6.582e-01 1.0000 724.0 18.10% 722.1 18.12% +ANAC103(NAC)/col-ANAC103-DAP-Seq(GSE60143)/Homer AACTTGNWNWNCAAG 1e0 -6.573e-01 1.0000 315.0 7.88% 314.6 7.89% +BMYB(HTH)/Hela-BMYB-ChIP-Seq(GSE27030)/Homer NHAACBGYYV 1e0 -6.536e-01 1.0000 2073.0 51.82% 2067.8 51.87% +EBF2(EBF)/BrownAdipose-EBF2-ChIP-Seq(GSE97114)/Homer NABTCCCWDGGGAVH 1e0 -6.529e-01 1.0000 389.0 9.72% 388.8 9.75% +Smad2(MAD)/ES-SMAD2-ChIP-Seq(GSE29422)/Homer CTGTCTGG 1e0 -6.519e-01 1.0000 1187.0 29.68% 1184.8 29.72% +ESE3(AP2EREBP)/col-ESE3-DAP-Seq(GSE60143)/Homer GACGGTGG 1e0 -6.417e-01 1.0000 1374.0 34.35% 1371.4 34.41% +WRKY20(WRKY)/col-WRKY20-DAP-Seq(GSE60143)/Homer CKTTGACYWD 1e0 -6.381e-01 1.0000 681.0 17.03% 680.8 17.08% +At1g74840(MYBrelated)/col100-At1g74840-DAP-Seq(GSE60143)/Homer YHTTATCCAWWT 1e0 -6.318e-01 1.0000 816.0 20.40% 815.8 20.47% +At4g16750(AP2EREBP)/col-At4g16750-DAP-Seq(GSE60143)/Homer HACCGACAHA 1e0 -6.268e-01 1.0000 1318.0 32.95% 1316.0 33.01% +ANAC062(NAC)/colamp-ANAC062-DAP-Seq(GSE60143)/Homer TACTTANTNWNYAAG 1e0 -6.263e-01 1.0000 251.0 6.28% 251.2 6.30% +HOXA1(Homeobox)/mES-Hoxa1-ChIP-Seq(SRP084292)/Homer TGATKGATGR 1e0 -6.263e-01 1.0000 244.0 6.10% 244.8 6.14% +STOP1(C2H2)/colamp-STOP1-DAP-Seq(GSE60143)/Homer DTATCTGGKGRAGGT 1e0 -6.263e-01 1.0000 261.0 6.53% 261.1 6.55% +Rfx5(HTH)/GM12878-Rfx5-ChIP-Seq(GSE31477)/Homer SCCTAGCAACAG 1e0 -6.260e-01 1.0000 207.0 5.17% 207.7 5.21% +CELF2(RRM)/JSL1-CELF2-CLIP-Seq(GSE71264)/Homer RGTGTCAG 1e0 -6.259e-01 1.0000 201.0 5.03% 201.5 5.05% +AT1G24250(Orphan)/col-AT1G24250-DAP-Seq(GSE60143)/Homer KTDGTTGGTDGTTGG 1e0 -6.257e-01 1.0000 190.0 4.75% 190.6 4.78% +ZNF341(Zf)/EBV-ZNF341-ChIP-Seq(GSE113194)/Homer GGAACAGCCG 1e0 -6.254e-01 1.0000 343.0 8.58% 343.5 8.62% +ANAC075(NAC)/col-ANAC075-DAP-Seq(GSE60143)/Homer CTTSWWNWWSAAGYT 1e0 -6.249e-01 1.0000 369.0 9.22% 369.6 9.27% +PPARa(NR),DR1/Liver-Ppara-ChIP-Seq(GSE47954)/Homer VNAGGKCAAAGGTCA 1e0 -6.244e-01 1.0000 394.0 9.85% 394.1 9.89% +TOD6?/SacCer-Promoters/Homer GCGATGAGMT 1e0 -6.240e-01 1.0000 149.0 3.72% 149.7 3.76% +GATA11(C2C2gata)/col-GATA11-DAP-Seq(GSE60143)/Homer DDHYYAGATCTR 1e0 -6.238e-01 1.0000 418.0 10.45% 418.9 10.51% +TRP2(MYBrelated)/colamp-TRP2-DAP-Seq(GSE60143)/Homer TAAACCCT 1e0 -6.212e-01 1.0000 117.0 2.93% 117.5 2.95% +FHY3(FAR1)/Arabidopsis-FHY3-ChIP-Seq(GSE30711)/Homer HHCACGCGCBTN 1e0 -6.206e-01 1.0000 535.0 13.38% 535.9 13.45% +TATA-box/SacCer-Promoters/Homer BBHWTATATA 1e0 -6.182e-01 1.0000 610.0 15.25% 610.7 15.32% +AGL15(MADS)/col-AGL15-DAP-Seq(GSE60143)/Homer TTTCCHWATWDGGAA 1e0 -6.182e-01 1.0000 96.0 2.40% 96.3 2.42% +TATA-Box(TBP)/Promoter/Homer CCTTTTAWAGSC 1e0 -6.162e-01 1.0000 1164.0 29.10% 1163.9 29.20% +Srebp2(bHLH)/HepG2-Srebp2-ChIP-Seq(GSE31477)/Homer CGGTCACSCCAC 1e0 -6.160e-01 1.0000 85.0 2.12% 85.6 2.15% +GATA20(C2C2gata)/colamp-GATA20-DAP-Seq(GSE60143)/Homer TNGATCNDNM 1e0 -6.127e-01 1.0000 2688.0 67.20% 2682.4 67.29% +ANAC046(NAC)/colamp-ANAC046-DAP-Seq(GSE60143)/Homer ACACGYWAYC 1e0 -6.097e-01 1.0000 2493.0 62.32% 2488.1 62.42% +ANAC038(NAC)/col-ANAC038-DAP-Seq(GSE60143)/Homer ACACGTWAYC 1e0 -6.078e-01 1.0000 2520.0 63.00% 2515.5 63.11% +TBP3(MYBrelated)/col-TBP3-DAP-Seq(GSE60143)/Homer VYTAGGGCAN 1e0 -6.060e-01 1.0000 960.0 24.00% 961.0 24.11% +NUC(C2H2)/col-NUC-DAP-Seq(GSE60143)/Homer HAVAAAACGACAAAA 1e0 -6.059e-01 1.0000 55.0 1.38% 55.6 1.40% +HSF21(HSF)/col-HSF21-DAP-Seq(GSE60143)/Homer CTTCTAGAAGMTTYW 1e0 -6.038e-01 1.0000 51.0 1.27% 51.7 1.30% +PSE(SNAPc)/K562-mStart-Seq/Homer WAVTCACCMTAASYDAAAAG 1e0 -5.971e-01 1.0000 476.0 11.90% 477.1 11.97% +WRKY42(WRKY)/colamp-WRKY42-DAP-Seq(GSE60143)/Homer NAAAGTCAACGN 1e0 -5.970e-01 1.0000 402.0 10.05% 403.7 10.13% +Gfi1b(Zf)/HPC7-Gfi1b-ChIP-Seq(GSE22178)/Homer MAATCACTGC 1e0 -5.969e-01 1.0000 389.0 9.72% 390.5 9.80% +WRKY3(WRKY)/col-WRKY3-DAP-Seq(GSE60143)/Homer NCKTTGACYDDN 1e0 -5.963e-01 1.0000 562.0 14.05% 563.5 14.14% +At5g05790(MYBrelated)/col-At5g05790-DAP-Seq(GSE60143)/Homer AYCTTATC 1e0 -5.953e-01 1.0000 1237.0 30.93% 1237.8 31.05% +Oct6(POU,Homeobox)/NPC-Pou3f1-ChIP-Seq(GSE35496)/Homer WATGCAAATGAG 1e0 -5.929e-01 1.0000 253.0 6.33% 254.9 6.39% +SND3(NAC)/col-SND3-DAP-Seq(GSE60143)/Homer CTTNHNNNDNAAGNH 1e0 -5.929e-01 1.0000 748.0 18.70% 749.4 18.80% +AT1G12630(AP2EREBP)/colamp-AT1G12630-DAP-Seq(GSE60143)/Homer TGTCGGCA 1e0 -5.922e-01 1.0000 775.0 19.38% 776.9 19.49% +ZNF652/HepG2-ZNF652.Flag-ChIP-Seq(Encode)/Homer TTAACCCTTTVNKKN 1e0 -5.905e-01 1.0000 220.0 5.50% 221.3 5.55% +At1g19000(MYBrelated)/colamp-At1g19000-DAP-Seq(GSE60143)/Homer WWTGGATAADDT 1e0 -5.878e-01 1.0000 939.0 23.47% 940.3 23.59% +At1g25550(G2like)/colamp-At1g25550-DAP-Seq(GSE60143)/Homer NAGATTCY 1e0 -5.876e-01 1.0000 945.0 23.62% 946.8 23.75% +MYB77(MYB)/col-MYB77-DAP-Seq(GSE60143)/Homer NYAACBGYMC 1e0 -5.775e-01 1.0000 1967.0 49.18% 1966.1 49.32% +AT1G72740(MYBrelated)/colamp-AT1G72740-DAP-Seq(GSE60143)/Homer NNWWAMCCTAAHWNN 1e0 -5.760e-01 1.0000 1296.0 32.40% 1297.3 32.55% +Dorsal(RHD)/Embryo-dl-ChIP-Seq(GSE65441)/Homer GGGAAAAMCCCG 1e0 -5.749e-01 1.0000 121.0 3.02% 122.7 3.08% +Foxa2(Forkhead)/Liver-Foxa2-ChIP-Seq(GSE25694)/Homer CYTGTTTACWYW 1e0 -5.736e-01 1.0000 616.0 15.40% 618.2 15.51% +HIF-1a(bHLH)/MCF7-HIF1a-ChIP-Seq(GSE28352)/Homer TACGTGCV 1e0 -5.734e-01 1.0000 658.0 16.45% 660.9 16.58% +MYB3R1(MYB)/col-MYB3R1-DAP-Seq(GSE60143)/Homer WWDTDACCGTTR 1e0 -5.701e-01 1.0000 898.0 22.45% 900.9 22.60% +GFX(?)/Promoter/Homer ATTCTCGCGAGA 1e0 -5.694e-01 1.0000 21.0 0.53% 21.8 0.55% +ZML2(C2C2gata)/col-ZML2-DAP-Seq(GSE60143)/Homer CATCATCATC 1e0 -5.687e-01 1.0000 102.0 2.55% 103.4 2.59% +RAP21(AP2EREBP)/colamp-RAP21-DAP-Seq(GSE60143)/Homer BCACCGACAHNN 1e0 -5.667e-01 1.0000 321.0 8.03% 323.6 8.12% +CArG(MADS)/PUER-Srf-ChIP-Seq(Sullivan_et_al.)/Homer CCATATATGGNM 1e0 -5.662e-01 1.0000 313.0 7.83% 315.9 7.92% +STZ(C2H2)/colamp-STZ-DAP-Seq(GSE60143)/Homer HNBTCACT 1e0 -5.629e-01 1.0000 3489.0 87.22% 3481.1 87.33% +TATA-box/Drosophila-Promoters/Homer CTATAAAAGCSV 1e0 -5.573e-01 1.0000 78.0 1.95% 79.5 1.99% +GATA15(C2C2gata)/col-GATA15-DAP-Seq(GSE60143)/Homer KATGATCA 1e0 -5.573e-01 1.0000 1748.0 43.70% 1749.7 43.89% +PRDM1(Zf)/Hela-PRDM1-ChIP-Seq(GSE31477)/Homer ACTTTCACTTTC 1e0 -5.553e-01 1.0000 213.0 5.33% 215.4 5.40% +MYB116(MYB)/colamp-MYB116-DAP-Seq(GSE60143)/Homer AGTTAGGCAN 1e0 -5.524e-01 1.0000 834.0 20.85% 837.1 21.00% +ZBTB33(Zf)/GM12878-ZBTB33-ChIP-Seq(GSE32465)/Homer GGVTCTCGCGAGAAC 1e0 -5.522e-01 1.0000 70.0 1.75% 71.8 1.80% +AT1G23810(Orphan)/col-AT1G23810-DAP-Seq(GSE60143)/Homer TTCTAGAAGSTTCTA 1e0 -5.514e-01 1.0000 15.0 0.38% 15.8 0.40% +dof42(C2C2dof)/col-dof42-DAP-Seq(GSE60143)/Homer AAAAAGGC 1e0 -5.510e-01 1.0000 543.0 13.58% 546.2 13.70% +TEAD3(TEA)/HepG2-TEAD3-ChIP-Seq(Encode)/Homer TRCATTCCAG 1e0 -5.508e-01 1.0000 958.0 23.95% 961.1 24.11% +ZNF669(Zf)/HEK293-ZNF669.GFP-ChIP-Seq(GSE58341)/Homer GARTGGTCATCGCCC 1e0 -5.492e-01 1.0000 66.0 1.65% 67.7 1.70% +GEI-11(Myb?)/cElegans-L4-GEI11-ChIP-Seq(modEncode)/Homer CCGACAYYTYACGGG 1e0 -5.485e-01 1.0000 65.0 1.62% 66.7 1.67% +WRKY65(WRKY)/colamp-WRKY65-DAP-Seq(GSE60143)/Homer AWWWAGTCAACG 1e0 -5.484e-01 1.0000 462.0 11.55% 465.8 11.68% +SPL13(SBP)/col-SPL13-DAP-Seq(GSE60143)/Homer WAHTGTACGGAH 1e0 -5.455e-01 1.0000 406.0 10.15% 409.7 10.28% +ZNF189(Zf)/HEK293-ZNF189.GFP-ChIP-Seq(GSE58341)/Homer TGGAACAGMA 1e0 -5.445e-01 1.0000 389.0 9.72% 392.3 9.84% +ANAC045(NAC)/col-ANAC045-DAP-Seq(GSE60143)/Homer DNCKTVNNNNNNAMG 1e0 -5.440e-01 1.0000 2015.0 50.38% 2016.3 50.58% +AT5G56840(MYBrelated)/colamp-AT5G56840-DAP-Seq(GSE60143)/Homer TGGATAAGGT 1e0 -5.398e-01 1.0000 1404.0 35.10% 1407.3 35.31% +PU.1:IRF8(ETS:IRF)/pDC-Irf8-ChIP-Seq(GSE66899)/Homer GGAAGTGAAAST 1e0 -5.363e-01 1.0000 52.0 1.30% 53.5 1.34% +X-box(HTH)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer GGTTGCCATGGCAA 1e0 -5.352e-01 1.0000 51.0 1.27% 52.4 1.31% +ATHB7(Homeobox)/col-ATHB7-DAP-Seq(GSE60143)/Homer AATGATTG 1e0 -5.338e-01 1.0000 845.0 21.12% 849.5 21.31% +OCT:OCT-short(POU,Homeobox)/NPC-OCT6-ChIP-Seq(GSE43916)/Homer ATGCATWATGCATRW 1e0 -5.314e-01 1.0000 612.0 15.30% 616.6 15.47% +ZNF264(Zf)/HEK293-ZNF264.GFP-ChIP-Seq(GSE58341)/Homer RGGGCACTAACY 1e0 -5.308e-01 1.0000 593.0 14.82% 597.6 14.99% +NFkB-p65-Rel(RHD)/ThioMac-LPS-Expression(GSE23622)/Homer GGAAATTCCC 1e0 -5.290e-01 1.0000 46.0 1.15% 47.3 1.19% +CUC2(NAC)/colamp-CUC2-DAP-Seq(GSE60143)/Homer TRCKTGTNNNWCAMG 1e0 -5.242e-01 1.0000 448.0 11.20% 452.7 11.36% +HSF7(HSF)/colamp-HSF7-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -5.189e-01 1.0000 98.0 2.45% 100.3 2.52% +Bcl11a(Zf)/HSPC-BCL11A-ChIP-Seq(GSE104676)/Homer TYTGACCASWRG 1e0 -5.174e-01 1.0000 367.0 9.18% 371.5 9.32% +MafB(bZIP)/BMM-Mafb-ChIP-Seq(GSE75722)/Homer WNTGCTGASTCAGCANWTTY 1e0 -5.159e-01 1.0000 188.0 4.70% 191.0 4.79% +Mef2a(MADS)/HL1-Mef2a.biotin-ChIP-Seq(GSE21529)/Homer CYAAAAATAG 1e0 -5.152e-01 1.0000 347.0 8.67% 351.8 8.83% +HSFC1(HSF)/col-HSFC1-DAP-Seq(GSE60143)/Homer HTTCTAGAADCTTCT 1e0 -5.151e-01 1.0000 92.0 2.30% 95.0 2.38% +WRKY25(WRKY)/colamp-WRKY25-DAP-Seq(GSE60143)/Homer NNNNHRGTCAAMNNN 1e0 -5.149e-01 1.0000 1103.0 27.57% 1108.5 27.81% +TEAD1(TEAD)/HepG2-TEAD1-ChIP-Seq(Encode)/Homer CYRCATTCCA 1e0 -5.148e-01 1.0000 749.0 18.73% 754.4 18.93% +SF1(NR)/H295R-Nr5a1-ChIP-Seq(GSE44220)/Homer CAAGGHCANV 1e0 -5.148e-01 1.0000 184.0 4.60% 187.7 4.71% +ERF38(AP2EREBP)/col-ERF38-DAP-Seq(GSE60143)/Homer CACCGACA 1e0 -5.144e-01 1.0000 726.0 18.15% 731.8 18.36% +SPL9(SBP)/colamp-SPL9-DAP-Seq(GSE60143)/Homer BTGTACTT 1e0 -5.142e-01 1.0000 2684.0 67.10% 2684.2 67.34% +AT4G00250(GeBP)/col-AT4G00250-DAP-Seq(GSE60143)/Homer WDTGGATAAKRT 1e0 -5.137e-01 1.0000 697.0 17.42% 702.3 17.62% +Tcfcp2l1(CP2)/mES-Tcfcp2l1-ChIP-Seq(GSE11431)/Homer NRAACCRGTTYRAACCRGYT 1e0 -5.131e-01 1.0000 89.0 2.23% 91.9 2.31% +HSFA1E(HSF)/col-HSFA1E-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -5.130e-01 1.0000 36.0 0.90% 37.9 0.95% +Trl(Zf)/S2-GAGAfactor-ChIP-Seq(GSE40646)/Homer RGAGAGAG 1e0 -5.128e-01 1.0000 1240.0 31.00% 1245.3 31.24% +GBF6(bZIP)/colamp-GBF6-DAP-Seq(GSE60143)/Homer WWTGMCACGTCABCW 1e0 -5.122e-01 1.0000 323.0 8.08% 327.2 8.21% +ZNF768(Zf)/Rajj-ZNF768-ChIP-Seq(GSE111879)/Homer RHHCAGAGAGGB 1e0 -5.091e-01 1.0000 8.0 0.20% 8.2 0.21% +VIP1(bZIP)/col-VIP1-DAP-Seq(GSE60143)/Homer NTTGACAGCTGTCAN 1e0 -5.045e-01 1.0000 78.0 1.95% 80.5 2.02% +MYB81(MYB)/col-MYB81-DAP-Seq(GSE60143)/Homer NWAACSGWTWNN 1e0 -5.018e-01 1.0000 2240.0 56.00% 2243.8 56.29% +Pit1(Homeobox)/GCrat-Pit1-ChIP-Seq(GSE58009)/Homer ATGMATATDC 1e0 -4.993e-01 1.0000 979.0 24.47% 985.7 24.73% +ZNF519(Zf)/HEK293-ZNF519.GFP-ChIP-Seq(GSE58341)/Homer GAGSCCGAGC 1e0 -4.980e-01 1.0000 71.0 1.77% 73.7 1.85% +Unknown3/Drosophila-Promoters/Homer ACVAKCTGGCAGCGC 1e0 -4.973e-01 1.0000 29.0 0.73% 30.4 0.76% +HSFB3(HSF)/colamp-HSFB3-DAP-Seq(GSE60143)/Homer TTCTAGAAGMTTHTW 1e0 -4.973e-01 1.0000 29.0 0.73% 30.9 0.77% +MYB96(MYB)/colamp-MYB96-DAP-Seq(GSE60143)/Homer WGGTRGTTGG 1e0 -4.956e-01 1.0000 715.0 17.88% 721.3 18.09% +LXH9(Homeobox)/Hct116-LXH9.V5-ChIP-Seq(GSE116822)/Homer NGCTAATTAG 1e0 -4.947e-01 1.0000 1825.0 45.62% 1830.6 45.93% +AT2G20400(G2like)/colamp-AT2G20400-DAP-Seq(GSE60143)/Homer DNVGAATATTCBNHN 1e0 -4.933e-01 1.0000 223.0 5.58% 227.5 5.71% +Pax8(Paired,Homeobox)/Thyroid-Pax8-ChIP-Seq(GSE26938)/Homer GTCATGCHTGRCTGS 1e0 -4.920e-01 1.0000 126.0 3.15% 129.6 3.25% +NFAT(RHD)/Jurkat-NFATC1-ChIP-Seq(Jolma_et_al.)/Homer ATTTTCCATT 1e0 -4.883e-01 1.0000 557.0 13.93% 563.8 14.14% +TF3A(C2H2)/col-TF3A-DAP-Seq(GSE60143)/Homer NNDDGAGGAGGWNNN 1e0 -4.881e-01 1.0000 334.0 8.35% 339.7 8.52% +AGL13(MADS)/col-AGL13-DAP-Seq(GSE60143)/Homer TWCCAWWTWTGGWAA 1e0 -4.857e-01 1.0000 25.0 0.62% 26.6 0.67% +FRS9(ND)/col-FRS9-DAP-Seq(GSE60143)/Homer RGAGAGAGAAAG 1e0 -4.857e-01 1.0000 25.0 0.62% 26.7 0.67% +RORgt(NR)/EL4-RORgt.Flag-ChIP-Seq(GSE56019)/Homer AAYTAGGTCA 1e0 -4.851e-01 1.0000 114.0 2.85% 118.0 2.96% +RORgt(NR)/EL4-RORgt.Flag-ChIP-Seq(GSE56019)/Homer AAYTAGGTCA 1e0 -4.851e-01 1.0000 114.0 2.85% 118.0 2.96% +LEP(AP2EREBP)/col-LEP-DAP-Seq(GSE60143)/Homer CDCCGCCGTC 1e0 -4.828e-01 1.0000 188.0 4.70% 192.9 4.84% +RBPJ:Ebox(?,bHLH)/Panc1-Rbpj1-ChIP-Seq(GSE47459)/Homer GGGRAARRGRMCAGMTG 1e0 -4.817e-01 1.0000 57.0 1.43% 59.9 1.50% +VRN1(ABI3VP1)/col-VRN1-DAP-Seq(GSE60143)/Homer TTTTTTTTTT 1e0 -4.696e-01 1.0000 5.0 0.12% 5.5 0.14% +MYB3R4(MYB)/col-MYB3R4-DAP-Seq(GSE60143)/Homer AWWTAACCGTTR 1e0 -4.674e-01 1.0000 542.0 13.55% 549.2 13.78% +WRKY29(WRKY)/colamp-WRKY29-DAP-Seq(GSE60143)/Homer MGTTGACTTT 1e0 -4.674e-01 1.0000 996.0 24.90% 1004.4 25.20% +TCP17(TCP)/col-TCP17-DAP-Seq(GSE60143)/Homer GTGGTCCCCA 1e0 -4.668e-01 1.0000 20.0 0.50% 21.7 0.54% +THRb(NR)/Liver-NR1A2-ChIP-Seq(GSE52613)/Homer TRAGGTCA 1e0 -4.663e-01 1.0000 2356.0 58.90% 2361.4 59.24% +HRE(HSF)/Striatum-HSF1-ChIP-Seq(GSE38000)/Homer TTCTAGAABNTTCTA 1e0 -4.655e-01 1.0000 88.0 2.20% 91.9 2.31% +GLI3(Zf)/Limb-GLI3-ChIP-Chip(GSE11077)/Homer CGTGGGTGGTCC 1e0 -4.604e-01 1.0000 44.0 1.10% 46.2 1.16% +E2F1(E2F)/Hela-E2F1-ChIP-Seq(GSE22478)/Homer CWGGCGGGAA 1e0 -4.577e-01 1.0000 205.0 5.12% 210.5 5.28% +IRF1(IRF)/PBMC-IRF1-ChIP-Seq(GSE43036)/Homer GAAAGTGAAAGT 1e0 -4.564e-01 1.0000 42.0 1.05% 44.9 1.13% +ZNF317(Zf)/HEK293-ZNF317.GFP-ChIP-Seq(GSE58341)/Homer GTCWGCTGTYYCTCT 1e0 -4.542e-01 1.0000 41.0 1.03% 43.2 1.08% +DPL-1(E2F)/cElegans-Adult-ChIP-Seq(modEncode)/Homer TAGCGCGC 1e0 -4.528e-01 1.0000 1274.0 31.85% 1283.1 32.19% +At1g22810(AP2EREBP)/colamp-At1g22810-DAP-Seq(GSE60143)/Homer BCACCGACANNN 1e0 -4.523e-01 1.0000 592.0 14.80% 600.9 15.08% +bZIP44(bZIP)/colamp-bZIP44-DAP-Seq(GSE60143)/Homer NDTGCCACGTCAGCH 1e0 -4.521e-01 1.0000 17.0 0.43% 19.0 0.48% +FOXA1(Forkhead)/MCF7-FOXA1-ChIP-Seq(GSE26831)/Homer WAAGTAAACA 1e0 -4.518e-01 1.0000 586.0 14.65% 594.6 14.92% +ANAC096(NAC)/colamp-ANAC096-DAP-Seq(GSE60143)/Homer TACTTGWNNNWCAAG 1e0 -4.512e-01 1.0000 578.0 14.45% 586.1 14.70% +Mef2d(MADS)/Retina-Mef2d-ChIP-Seq(GSE61391)/Homer GCTATTTTTAGC 1e0 -4.503e-01 1.0000 121.0 3.02% 125.6 3.15% +bZIP42(bZIP)/colamp-bZIP42-DAP-Seq(GSE60143)/Homer GCCACGTCAGCA 1e0 -4.483e-01 1.0000 4.0 0.10% 4.9 0.12% +RORg(NR)/Liver-Rorc-ChIP-Seq(GSE101115)/Homer WAABTAGGTCAV 1e0 -4.475e-01 1.0000 71.0 1.77% 74.2 1.86% +FOXA1(Forkhead)/LNCAP-FOXA1-ChIP-Seq(GSE27824)/Homer WAAGTAAACA 1e0 -4.454e-01 1.0000 769.0 19.23% 778.1 19.52% +DEAR5(AP2EREBP)/col-DEAR5-DAP-Seq(GSE60143)/Homer NDWTGTCGGTGRWDN 1e0 -4.444e-01 1.0000 251.0 6.28% 257.8 6.47% +ARF16(ARF)/col-ARF16-DAP-Seq(GSE60143)/Homer ATTTTACGAT 1e0 -4.426e-01 1.0000 490.0 12.25% 498.5 12.51% +At1g14580(C2H2)/colamp-At1g14580-DAP-Seq(GSE60143)/Homer CASAAAAMGACAAAA 1e0 -4.423e-01 1.0000 67.0 1.68% 70.3 1.76% +Ap4(bHLH)/AML-Tfap4-ChIP-Seq(GSE45738)/Homer NAHCAGCTGD 1e0 -4.383e-01 1.0000 455.0 11.38% 463.9 11.64% +MyoD(bHLH)/Myotube-MyoD-ChIP-Seq(GSE21614)/Homer RRCAGCTGYTSY 1e0 -4.381e-01 1.0000 231.0 5.78% 237.5 5.96% +FOXM1(Forkhead)/MCF7-FOXM1-ChIP-Seq(GSE72977)/Homer TRTTTACTTW 1e0 -4.380e-01 1.0000 641.0 16.02% 650.9 16.33% +WRKY55(WRKY)/col-WRKY55-DAP-Seq(GSE60143)/Homer NCGTTGACTT 1e0 -4.372e-01 1.0000 1014.0 25.35% 1024.2 25.69% +bZIP52(bZIP)/colamp-bZIP52-DAP-Seq(GSE60143)/Homer NDNHCAGCTGTCANN 1e0 -4.332e-01 1.0000 862.0 21.55% 872.4 21.89% +MYB73(MYB)/col-MYB73-DAP-Seq(GSE60143)/Homer NNNNHAACNGHHDHN 1e0 -4.324e-01 1.0000 2259.0 56.47% 2267.1 56.88% +RORa(NR)/Liver-Rora-ChIP-Seq(GSE101115)/Homer AAWCTAGGTCARDNN 1e0 -4.321e-01 1.0000 98.0 2.45% 102.5 2.57% +WRKY24(WRKY)/colamp-WRKY24-DAP-Seq(GSE60143)/Homer CGTTGACTWW 1e0 -4.317e-01 1.0000 824.0 20.60% 834.1 20.93% +ANAC017(NAC)/colamp-ANAC017-DAP-Seq(GSE60143)/Homer TMCTTGNNNNNCAAG 1e0 -4.302e-01 1.0000 96.0 2.40% 100.7 2.53% +Brn2(POU,Homeobox)/NPC-Brn2-ChIP-Seq(GSE35496)/Homer ATGAATATTC 1e0 -4.290e-01 1.0000 58.0 1.45% 61.8 1.55% +Srebp1a(bHLH)/HepG2-Srebp1a-ChIP-Seq(GSE31477)/Homer RTCACSCCAY 1e0 -4.288e-01 1.0000 143.0 3.57% 148.6 3.73% +AT3G42860(zfGRF)/col-AT3G42860-DAP-Seq(GSE60143)/Homer CGTTGACTTN 1e0 -4.276e-01 1.0000 282.0 7.05% 289.6 7.27% +At1g13300(G2like)/col-At1g13300-DAP-Seq(GSE60143)/Homer GAATCTWAGATTCYN 1e0 -4.260e-01 1.0000 13.0 0.33% 14.0 0.35% +Hoxb4(Homeobox)/ES-Hoxb4-ChIP-Seq(GSE34014)/Homer TGATTRATGGCY 1e0 -4.244e-01 1.0000 195.0 4.88% 201.6 5.06% +KANADI1(Myb)/Seedling-KAN1-ChIP-Seq(GSE48081)/Homer ARGAATAWWN 1e0 -4.236e-01 1.0000 1466.0 36.65% 1477.6 37.07% +CDM1(C3H)/colamp-CDM1-DAP-Seq(GSE60143)/Homer CCGAWAWTWTCGGAN 1e0 -4.207e-01 1.0000 350.0 8.75% 358.7 9.00% +ZBTB18(Zf)/HEK293-ZBTB18.GFP-ChIP-Seq(GSE58341)/Homer AACATCTGGA 1e0 -4.204e-01 1.0000 186.0 4.65% 192.8 4.84% +Tbox:Smad(T-box,MAD)/ESCd5-Smad2_3-ChIP-Seq(GSE29422)/Homer AGGTGHCAGACA 1e0 -4.188e-01 1.0000 85.0 2.12% 89.6 2.25% +AT1G04880(ARID)/colamp-AT1G04880-DAP-Seq(GSE60143)/Homer AAACTATATADTATA 1e0 -4.188e-01 1.0000 85.0 2.12% 89.5 2.24% +Pitx1(Homeobox)/Chicken-Pitx1-ChIP-Seq(GSE38910)/Homer TAATCCCN 1e0 -4.186e-01 1.0000 3317.0 82.93% 3318.1 83.24% +p53(p53)/Saos-p53-ChIP-Seq(GSE15780)/Homer RRCATGYCYRGRCATGYYYN 1e0 -4.184e-01 1.0000 52.0 1.30% 55.4 1.39% +p53(p53)/Saos-p53-ChIP-Seq/Homer RRCATGYCYRGRCATGYYYN 1e0 -4.184e-01 1.0000 52.0 1.30% 55.4 1.39% +TEAD4(TEA)/Tropoblast-Tead4-ChIP-Seq(GSE37350)/Homer CCWGGAATGY 1e0 -4.180e-01 1.0000 609.0 15.22% 619.7 15.55% +p73(p53)/Trachea-p73-ChIP-Seq(PRJNA310161)/Homer NRRRCAWGTCCDGRCATGYY 1e0 -4.178e-01 1.0000 28.0 0.70% 30.1 0.76% +SND2(NAC)/colamp-SND2-DAP-Seq(GSE60143)/Homer CTTVWNNNWBAAGNW 1e0 -4.178e-01 1.0000 607.0 15.17% 617.0 15.48% +WRKY14(WRKY)/colamp-WRKY14-DAP-Seq(GSE60143)/Homer NCGTTGACTTTN 1e0 -4.151e-01 1.0000 433.0 10.82% 443.0 11.11% +SPL3(SBP)/colamp-SPL3-DAP-Seq(GSE60143)/Homer WDTTGTACGGAH 1e0 -4.145e-01 1.0000 174.0 4.35% 181.0 4.54% +IRF8(IRF)/BMDM-IRF8-ChIP-Seq(GSE77884)/Homer GRAASTGAAAST 1e0 -4.137e-01 1.0000 121.0 3.02% 126.6 3.18% +AT1G19040(NAC)/col-AT1G19040-DAP-Seq(GSE60143)/Homer CTTGNDNHNCAAGYW 1e0 -4.130e-01 1.0000 80.0 2.00% 84.8 2.13% +WRKY30(WRKY)/colamp-WRKY30-DAP-Seq(GSE60143)/Homer CGTTGACTTN 1e0 -4.124e-01 1.0000 314.0 7.85% 322.0 8.08% +AT1G77200(AP2EREBP)/colamp-AT1G77200-DAP-Seq(GSE60143)/Homer ACCGACAHWD 1e0 -4.114e-01 1.0000 1382.0 34.55% 1395.0 35.00% +HOXA2(Homeobox)/mES-Hoxa2-ChIP-Seq(Donaldson_et_al.)/Homer GYCATCMATCAT 1e0 -4.092e-01 1.0000 77.0 1.93% 81.6 2.05% +p63(p53)/Keratinocyte-p63-ChIP-Seq(GSE17611)/Homer NNDRCATGYCYNRRCATGYH 1e0 -4.060e-01 1.0000 217.0 5.42% 224.4 5.63% +MYB57(MYB)/col-MYB57-DAP-Seq(GSE60143)/Homer TTACCTAACT 1e0 -4.048e-01 1.0000 650.0 16.25% 661.9 16.60% +ATY13(MYB)/col-ATY13-DAP-Seq(GSE60143)/Homer YYYAACYRHH 1e0 -4.041e-01 1.0000 2908.0 72.70% 2914.2 73.11% +Ets1-distal(ETS)/CD4+-PolII-ChIP-Seq(Barski_et_al.)/Homer MACAGGAAGT 1e0 -3.982e-01 1.0000 146.0 3.65% 152.3 3.82% +DEL2(E2FDP)/col-DEL2-DAP-Seq(GSE60143)/Homer WTTTCSCGCC 1e0 -3.958e-01 1.0000 434.0 10.85% 444.1 11.14% +GATA(Zf),IR4/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer NAGATWNBNATCTNN 1e0 -3.951e-01 1.0000 67.0 1.68% 71.8 1.80% +HSFA6B(HSF)/colamp-HSFA6B-DAP-Seq(GSE60143)/Homer NTTCTAGAANHTTCT 1e0 -3.931e-01 1.0000 325.0 8.12% 334.1 8.38% +IRF3(IRF)/BMDM-Irf3-ChIP-Seq(GSE67343)/Homer AGTTTCAKTTTC 1e0 -3.920e-01 1.0000 97.0 2.43% 102.5 2.57% +Rfx2(HTH)/LoVo-RFX2-ChIP-Seq(GSE49402)/Homer GTTGCCATGGCAACM 1e0 -3.885e-01 1.0000 39.0 0.97% 42.2 1.06% +WRKY31(WRKY)/colamp-WRKY31-DAP-Seq(GSE60143)/Homer NCGTTGACTWWK 1e0 -3.864e-01 1.0000 627.0 15.68% 639.3 16.04% +AT5G25475(ABI3VP1)/col-AT5G25475-DAP-Seq(GSE60143)/Homer RNNRNCAAGCADNDB 1e0 -3.859e-01 1.0000 816.0 20.40% 829.7 20.81% +HAP3(CCAATHAP3)/col-HAP3-DAP-Seq(GSE60143)/Homer TGATGGAW 1e0 -3.852e-01 1.0000 229.0 5.73% 237.1 5.95% +Pbx3(Homeobox)/GM12878-PBX3-ChIP-Seq(GSE32465)/Homer SCTGTCAMTCAN 1e0 -3.836e-01 1.0000 126.0 3.15% 132.2 3.32% +Hand2(bHLH)/Mesoderm-Hand2-ChIP-Seq(GSE61475)/Homer TGACANARRCCAGRC 1e0 -3.790e-01 1.0000 163.0 4.08% 170.7 4.28% +WRKY47(WRKY)/colamp-WRKY47-DAP-Seq(GSE60143)/Homer WAAGTCAACGBT 1e0 -3.781e-01 1.0000 274.0 6.85% 283.6 7.11% +Unknown1(NR/Ini-like)/Drosophila-Promoters/Homer MYGGTCACACTG 1e0 -3.769e-01 1.0000 118.0 2.95% 124.6 3.13% +GRHL2(CP2)/HBE-GRHL2-ChIP-Seq(GSE46194)/Homer AAACYKGTTWDACMRGTTTB 1e0 -3.747e-01 1.0000 264.0 6.60% 273.2 6.85% +GATA(Zf),IR3/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer NNNNNBAGATAWYATCTVHN 1e0 -3.742e-01 1.0000 115.0 2.88% 121.5 3.05% +MYB30(MYB)/colamp-MYB30-DAP-Seq(GSE60143)/Homer AGGTAGTTGG 1e0 -3.741e-01 1.0000 857.0 21.43% 871.2 21.86% +CTCF-SatelliteElement(Zf?)/CD4+-CTCF-ChIP-Seq(Barski_et_al.)/Homer TGCAGTTCCMVNWRTGGCCA 1e0 -3.727e-01 1.0000 2.0 0.05% 2.1 0.05% +DEL1(E2FDP)/colamp-DEL1-DAP-Seq(GSE60143)/Homer TTCCCGCCAA 1e0 -3.727e-01 1.0000 2.0 0.05% 2.5 0.06% +THRa(NR)/C17.2-THRa-ChIP-Seq(GSE38347)/Homer GGTCANYTGAGGWCA 1e0 -3.702e-01 1.0000 196.0 4.90% 204.1 5.12% +COG1(C2C2dof)/col-COG1-DAP-Seq(GSE60143)/Homer DAAAAAGTGA 1e0 -3.678e-01 1.0000 1012.0 25.30% 1027.4 25.77% +Tlx?(NR)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer CTGGCAGSCTGCCA 1e0 -3.665e-01 1.0000 107.0 2.67% 113.6 2.85% +AT2G01818(PLATZ)/col-AT2G01818-DAP-Seq(GSE60143)/Homer TCTAGAABSTTC 1e0 -3.665e-01 1.0000 107.0 2.67% 113.8 2.85% +GATA3(Zf),DR4/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATGKDGAGATAAG 1e0 -3.601e-01 1.0000 72.0 1.80% 77.2 1.94% +YY1(Zf)/Promoter/Homer CAAGATGGCGGC 1e0 -3.591e-01 1.0000 30.0 0.75% 33.5 0.84% +TCP16(TCP)/colamp-TCP16-DAP-Seq(GSE60143)/Homer GTGGDCCYNNNNNNN 1e0 -3.584e-01 1.0000 349.0 8.72% 360.7 9.05% +dof43(C2C2dof)/colamp-dof43-DAP-Seq(GSE60143)/Homer NAAAAAGTDA 1e0 -3.583e-01 1.0000 1114.0 27.85% 1130.5 28.36% +OCT:OCT(POU,Homeobox,IR1)/NPC-Brn2-ChIP-Seq(GSE35496)/Homer ATGAATWATTCATGA 1e0 -3.582e-01 1.0000 7.0 0.18% 8.1 0.20% +LIN-15B(Zf)/cElegans-L3-LIN15B-ChIP-Seq(modEncode)/Homer CARTGGAGCGCRYTTGCATT 1e0 -3.582e-01 1.0000 7.0 0.18% 8.9 0.22% +ISRE(IRF)/ThioMac-LPS-Expression(GSE23622)/Homer AGTTTCASTTTC 1e0 -3.564e-01 1.0000 16.0 0.40% 18.2 0.46% +NF1:FOXA1(CTF,Forkhead)/LNCAP-FOXA1-ChIP-Seq(GSE27824)/Homer WNTGTTTRYTTTGGCA 1e0 -3.564e-01 1.0000 16.0 0.40% 18.9 0.47% +RFX(HTH)/K562-RFX3-ChIP-Seq(SRA012198)/Homer CGGTTGCCATGGCAAC 1e0 -3.552e-01 1.0000 29.0 0.73% 33.0 0.83% +Initiator/Drosophila-Promoters/Homer NTCAGTYG 1e0 -3.545e-01 1.0000 1870.0 46.75% 1886.4 47.32% +At1g77640(AP2EREBP)/col-At1g77640-DAP-Seq(GSE60143)/Homer TGTCGGTGGA 1e0 -3.543e-01 1.0000 168.0 4.20% 176.6 4.43% +DREB26(AP2EREBP)/col-DREB26-DAP-Seq(GSE60143)/Homer CCACCGACAH 1e0 -3.521e-01 1.0000 210.0 5.25% 219.6 5.51% +M1BP(Zf)/S2R+-M1BP-ChIP-Seq(GSE49842)/Homer CAGTGTGACCGT 1e0 -3.517e-01 1.0000 164.0 4.10% 172.5 4.33% +WRKY18(WRKY)/col-WRKY18-DAP-Seq(GSE60143)/Homer NNNTTGACYWNNNNN 1e0 -3.500e-01 1.0000 1530.0 38.25% 1547.2 38.81% +WRKY50(WRKY)/col-WRKY50-DAP-Seq(GSE60143)/Homer NNTTGACTWNNGNNN 1e0 -3.489e-01 1.0000 889.0 22.23% 905.8 22.72% +AT5G59990(C2C2COlike)/colamp-AT5G59990-DAP-Seq(GSE60143)/Homer TCTCAACCGTTCATT 1e0 -3.485e-01 1.0000 44.0 1.10% 48.7 1.22% +AMYB(HTH)/Testes-AMYB-ChIP-Seq(GSE44588)/Homer TGGCAGTTGG 1e0 -3.453e-01 1.0000 1807.0 45.17% 1824.0 45.76% +p53(p53)/mES-cMyc-ChIP-Seq(GSE11431)/Homer ACATGCCCGGGCAT 1e0 -3.399e-01 1.0000 6.0 0.15% 7.6 0.19% +AT5G22990(C2H2)/col-AT5G22990-DAP-Seq(GSE60143)/Homer WCGAHDTCGWHN 1e0 -3.374e-01 1.0000 603.0 15.07% 618.7 15.52% +Tcf21(bHLH)/ArterySmoothMuscle-Tcf21-ChIP-Seq(GSE61369)/Homer NAACAGCTGG 1e0 -3.359e-01 1.0000 337.0 8.43% 349.0 8.76% +TCX2(CPP)/colamp-TCX2-DAP-Seq(GSE60143)/Homer NNWWTTYRAAHN 1e0 -3.350e-01 1.0000 1142.0 28.55% 1160.1 29.10% +O2(bZIP)/Corn-O2-ChIP-Seq(GSE63991)/Homer GCTGACGTGGCA 1e0 -3.346e-01 1.0000 108.0 2.70% 115.1 2.89% +WRKY45(WRKY)/col-WRKY45-DAP-Seq(GSE60143)/Homer HNNNKTTGACTWWNH 1e0 -3.341e-01 1.0000 331.0 8.28% 343.9 8.63% +AGL6(MADS)/col-AGL6-DAP-Seq(GSE60143)/Homer TTWCCWWAWWDGGWA 1e0 -3.337e-01 1.0000 80.0 2.00% 86.2 2.16% +AT4G37180(G2like)/col-AT4G37180-DAP-Seq(GSE60143)/Homer AGAATCTTNN 1e0 -3.336e-01 1.0000 1097.0 27.43% 1115.6 27.99% +GATA3(Zf),DR8/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATSTNDNNDSAGATAASN 1e0 -3.330e-01 1.0000 57.0 1.43% 62.8 1.58% +Brn1(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)/Homer TATGCWAATBAV 1e0 -3.321e-01 1.0000 217.0 5.42% 227.1 5.70% +MYB70(MYB)/col-MYB70-DAP-Seq(GSE60143)/Homer WTAACNGTTA 1e0 -3.316e-01 1.0000 2170.0 54.25% 2188.0 54.89% +ASHR1(ND)/col-ASHR1-DAP-Seq(GSE60143)/Homer NTGGTGAN 1e0 -3.298e-01 1.0000 800.0 20.00% 817.0 20.50% +Lhx3(Homeobox)/Neuron-Lhx3-ChIP-Seq(GSE31456)/Homer ADBTAATTAR 1e0 -3.294e-01 1.0000 1974.0 49.35% 1992.7 49.99% +AT1G49560(G2like)/colamp-AT1G49560-DAP-Seq(GSE60143)/Homer GAWTCTNWDA 1e0 -3.279e-01 1.0000 1397.0 34.92% 1416.4 35.53% +LXRE(NR),DR4/RAW-LXRb.biotin-ChIP-Seq(GSE21512)/Homer RGGTTACTANAGGTCA 1e0 -3.279e-01 1.0000 37.0 0.92% 41.4 1.04% +AGL25(MADS)/colamp-AGL25-DAP-Seq(GSE60143)/Homer TTTCCATWTWTGGAA 1e0 -3.276e-01 1.0000 23.0 0.57% 27.0 0.68% +CAMTA5(CAMTA)/col-CAMTA5-DAP-Seq(GSE60143)/Homer ACGCGTTTTANACRC 1e0 -3.249e-01 1.0000 744.0 18.60% 761.8 19.11% +HSF6(HSF)/col-HSF6-DAP-Seq(GSE60143)/Homer TTYTAGAAGCTTCTA 1e0 -3.242e-01 1.0000 128.0 3.20% 136.9 3.43% +SFP1/SacCer-Promoters/Homer DDAAAAATTTTY 1e0 -3.221e-01 1.0000 22.0 0.55% 25.4 0.64% +HSFA6A(HSF)/col-HSFA6A-DAP-Seq(GSE60143)/Homer RGAAGNTTCTAGAAN 1e0 -3.219e-01 1.0000 12.0 0.30% 14.2 0.36% +RLR1?/SacCer-Promoters/Homer WTTTTCYYTTTT 1e0 -3.212e-01 1.0000 72.0 1.80% 78.9 1.98% +AT1G44830(AP2EREBP)/col-AT1G44830-DAP-Seq(GSE60143)/Homer NCCACCGACA 1e0 -3.182e-01 1.0000 283.0 7.07% 295.2 7.41% +Unknown4/Arabidopsis-Promoters/Homer CKTCKTCTTY 1e0 -3.179e-01 1.0000 568.0 14.20% 584.1 14.65% +PBX1(Homeobox)/MCF7-PBX1-ChIP-Seq(GSE28007)/Homer GSCTGTCACTCA 1e0 -3.164e-01 1.0000 21.0 0.53% 24.9 0.62% +At5g08520(MYBrelated)/colamp-At5g08520-DAP-Seq(GSE60143)/Homer ADBSTTATCY 1e0 -3.164e-01 1.0000 1327.0 33.17% 1347.8 33.81% +GATA:SCL(Zf,bHLH)/Ter119-SCL-ChIP-Seq(GSE18720)/Homer CRGCTGBNGNSNNSAGATAA 1e0 -3.161e-01 1.0000 69.0 1.73% 75.7 1.90% +Rfx1(HTH)/NPC-H3K4me1-ChIP-Seq(GSE16256)/Homer KGTTGCCATGGCAA 1e0 -3.132e-01 1.0000 90.0 2.25% 97.5 2.45% +ZNF165(Zf)/WHIM12-ZNF165-ChIP-Seq(GSE65937)/Homer AAGGKGRCGCAGGCA 1e0 -3.104e-01 1.0000 20.0 0.50% 23.6 0.59% +TEAD2(TEA)/Py2T-Tead2-ChIP-Seq(GSE55709)/Homer CCWGGAATGY 1e0 -3.092e-01 1.0000 311.0 7.78% 324.6 8.14% +AGL95(ND)/col-AGL95-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -3.070e-01 1.0000 46.0 1.15% 51.0 1.28% +Zfp809(Zf)/ES-Zfp809-ChIP-Seq(GSE70799)/Homer GGGGCTYGKCTGGGA 1e0 -3.043e-01 1.0000 45.0 1.12% 50.9 1.28% +WRKY11(WRKY)/col-WRKY11-DAP-Seq(GSE60143)/Homer SCGTTGACTTTN 1e0 -3.030e-01 1.0000 107.0 2.67% 115.6 2.90% +WRKY46(WRKY)/colamp-WRKY46-DAP-Seq(GSE60143)/Homer AAAGTCAACGSN 1e0 -3.019e-01 1.0000 82.0 2.05% 89.5 2.25% +HSFB4(HSF)/col-HSFB4-DAP-Seq(GSE60143)/Homer TTCTAGAAGCTTCTA 1e0 -2.994e-01 1.0000 10.0 0.25% 12.6 0.32% +Zic3(Zf)/mES-Zic3-ChIP-Seq(GSE37889)/Homer GGCCYCCTGCTGDGH 1e0 -2.993e-01 1.0000 162.0 4.05% 172.7 4.33% +AT3G09735(S1Falike)/col-AT3G09735-DAP-Seq(GSE60143)/Homer TTCTAGAANMTTCTA 1e0 -2.972e-01 1.0000 278.0 6.95% 291.9 7.32% +Nkx2.5(Homeobox)/HL1-Nkx2.5.biotin-ChIP-Seq(GSE21529)/Homer RRSCACTYAA 1e0 -2.949e-01 1.0000 1755.0 43.88% 1777.0 44.58% +RAV1(RAV)/colamp-RAV1-DAP-Seq(GSE60143)/Homer TWWTTTCTGTTG 1e0 -2.909e-01 1.0000 424.0 10.60% 440.4 11.05% +RXR(NR),DR1/3T3L1-RXR-ChIP-Seq(GSE13511)/Homer TAGGGCAAAGGTCA 1e0 -2.908e-01 1.0000 363.0 9.07% 378.4 9.49% +ANAC079(NAC)/colamp-ANAC079-DAP-Seq(GSE60143)/Homer TACACGCAACCT 1e0 -2.898e-01 1.0000 772.0 19.30% 792.1 19.87% +AT3G25990(Trihelix)/colamp-AT3G25990-DAP-Seq(GSE60143)/Homer TTAACCATAG 1e0 -2.863e-01 1.0000 866.0 21.65% 887.2 22.26% +NFkB-p50,p52(RHD)/Monocyte-p50-ChIP-Chip(Schreiber_et_al.)/Homer GGGGGAATCCCC 1e0 -2.858e-01 1.0000 54.0 1.35% 60.3 1.51% +SOL1(CPP)/colamp-SOL1-DAP-Seq(GSE60143)/Homer ATTTAAATHN 1e0 -2.847e-01 1.0000 1012.0 25.30% 1034.8 25.96% +VDR(NR),DR3/GM10855-VDR+vitD-ChIP-Seq(GSE22484)/Homer ARAGGTCANWGAGTTCANNN 1e0 -2.832e-01 1.0000 91.0 2.27% 99.9 2.51% +dHNF4(NR)/Fly-HNF4-ChIP-Seq(GSE73675)/Homer GGTCCAAAGTCCAMT 1e0 -2.790e-01 1.0000 25.0 0.62% 29.3 0.73% +Hoxc9(Homeobox)/Ainv15-Hoxc9-ChIP-Seq(GSE21812)/Homer GGCCATAAATCA 1e0 -2.781e-01 1.0000 500.0 12.50% 518.8 13.01% +CUC1(NAC)/col-CUC1-DAP-Seq(GSE60143)/Homer TACTTGTNNNACAAG 1e0 -2.773e-01 1.0000 496.0 12.40% 514.4 12.91% +SPL5(SBP)/colamp-SPL5-DAP-Seq(GSE60143)/Homer NNHGTACGGHNN 1e0 -2.773e-01 1.0000 1616.0 40.40% 1640.1 41.14% +At2g03500(G2like)/col-At2g03500-DAP-Seq(GSE60143)/Homer WWAGAATATTCT 1e0 -2.766e-01 1.0000 318.0 7.95% 333.0 8.35% +At3g04030(G2like)/col-At3g04030-DAP-Seq(GSE60143)/Homer DRGAATCT 1e0 -2.763e-01 1.0000 882.0 22.05% 904.7 22.70% +Nkx3.1(Homeobox)/LNCaP-Nkx3.1-ChIP-Seq(GSE28264)/Homer AAGCACTTAA 1e0 -2.748e-01 1.0000 1815.0 45.38% 1839.1 46.14% +MYB33(MYB)/col-MYB33-DAP-Seq(GSE60143)/Homer DDTYNGTTAN 1e0 -2.735e-01 1.0000 2145.0 53.62% 2168.3 54.40% +HAT5(Homeobox)/colamp-HAT5-DAP-Seq(GSE60143)/Homer DCAATWATTG 1e0 -2.730e-01 1.0000 158.0 3.95% 169.2 4.24% +Tgif1(Homeobox)/mES-Tgif1-ChIP-Seq(GSE55404)/Homer YTGWCADY 1e0 -2.724e-01 1.0000 2170.0 54.25% 2193.9 55.04% +AT2G15740(C2H2)/col-AT2G15740-DAP-Seq(GSE60143)/Homer DHNDWATCGATD 1e0 -2.716e-01 1.0000 2499.0 62.48% 2520.1 63.22% +WRKY43(WRKY)/colamp-WRKY43-DAP-Seq(GSE60143)/Homer NCGTTGACTTTT 1e0 -2.675e-01 1.0000 293.0 7.32% 308.9 7.75% +SOC1(MADS)/Seedling-SOC1-ChIP-Seq(GSE45846)/Homer TWCCAWWTWTGG 1e0 -2.628e-01 1.0000 325.0 8.12% 341.2 8.56% +PPARE(NR),DR1/3T3L1-Pparg-ChIP-Seq(GSE13511)/Homer TGACCTTTGCCCCA 1e0 -2.617e-01 1.0000 322.0 8.05% 338.4 8.49% +At5g29000(G2like)/col-At5g29000-DAP-Seq(GSE60143)/Homer RGAATATTCYHH 1e0 -2.600e-01 1.0000 317.0 7.92% 333.8 8.37% +Six1(Homeobox)/Myoblast-Six1-ChIP-Chip(GSE20150)/Homer GKVTCADRTTWC 1e0 -2.596e-01 1.0000 235.0 5.88% 249.9 6.27% +Nur77(NR)/K562-NR4A1-ChIP-Seq(GSE31363)/Homer TGACCTTTNCNT 1e0 -2.576e-01 1.0000 115.0 2.88% 125.2 3.14% +WRKY27(WRKY)/colamp-WRKY27-DAP-Seq(GSE60143)/Homer NHGTTGACYTWD 1e0 -2.566e-01 1.0000 782.0 19.55% 805.6 20.21% +PABPC1(?)/MEL-PABC1-CLIP-Seq(GSE69755)/Homer HAATAAAGNN 1e0 -2.552e-01 1.0000 1272.0 31.80% 1298.6 32.58% +NFkB-p65(RHD)/GM12787-p65-ChIP-Seq(GSE19485)/Homer WGGGGATTTCCC 1e0 -2.552e-01 1.0000 263.0 6.58% 278.3 6.98% +MafF(bZIP)/HepG2-MafF-ChIP-Seq(GSE31477)/Homer HWWGTCAGCAWWTTT 1e0 -2.551e-01 1.0000 193.0 4.83% 206.3 5.18% +AT1G10720(BSD)/col-AT1G10720-DAP-Seq(GSE60143)/Homer TTCTAGAAKCTTCTA 1e0 -2.547e-01 1.0000 7.0 0.18% 9.0 0.23% +Erra(NR)/HepG2-Erra-ChIP-Seq(GSE31477)/Homer CAAAGGTCAG 1e0 -2.547e-01 1.0000 1027.0 25.67% 1052.2 26.40% +AT1G01250(AP2EREBP)/col-AT1G01250-DAP-Seq(GSE60143)/Homer YCACCGACAHTW 1e0 -2.543e-01 1.0000 112.0 2.80% 122.8 3.08% +bZIP69(bZIP)/col-bZIP69-DAP-Seq(GSE60143)/Homer GACAGCTGKCAW 1e0 -2.537e-01 1.0000 42.0 1.05% 48.2 1.21% +At3g11280(MYBrelated)/col-At3g11280-DAP-Seq(GSE60143)/Homer GATAAGRT 1e0 -2.511e-01 1.0000 1151.0 28.78% 1177.3 29.53% +AT3G58630(Trihelix)/col-AT3G58630-DAP-Seq(GSE60143)/Homer TCTCCGGCGA 1e0 -2.506e-01 1.0000 186.0 4.65% 199.9 5.02% +ATHB5(HB)/colamp-ATHB5-DAP-Seq(GSE60143)/Homer AATGATTG 1e0 -2.505e-01 1.0000 960.0 24.00% 985.4 24.72% +AT5G45580(G2like)/colamp-AT5G45580-DAP-Seq(GSE60143)/Homer ADRGAATCTH 1e0 -2.503e-01 1.0000 1579.0 39.48% 1606.6 40.30% +At5g47390(MYBrelated)/col-At5g47390-DAP-Seq(GSE60143)/Homer CTTATCCA 1e0 -2.499e-01 1.0000 1489.0 37.23% 1516.5 38.04% +PAX6(Paired,Homeobox)/Forebrain-Pax6-ChIP-Seq(GSE66961)/Homer NGTGTTCAVTSAAGCGKAAA 1e0 -2.482e-01 1.0000 69.0 1.73% 77.2 1.94% +Gli2(Zf)/GM2-Gli2-ChIP-Chip(GSE112702)/Homer YSTGGGTGGTCT 1e0 -2.472e-01 1.0000 86.0 2.15% 95.9 2.41% +BOS1(MYB)/col-BOS1-DAP-Seq(GSE60143)/Homer NNRCCTAACT 1e0 -2.452e-01 1.0000 1030.0 25.75% 1056.7 26.51% +At4g38000(C2C2dof)/col-At4g38000-DAP-Seq(GSE60143)/Homer WWWTWACTTTTT 1e0 -2.419e-01 1.0000 848.0 21.20% 874.0 21.93% +CEBP:AP1(bZIP)/ThioMac-CEBPb-ChIP-Seq(GSE21512)/Homer DRTGTTGCAA 1e0 -2.400e-01 1.0000 643.0 16.07% 666.1 16.71% +AT2G20110(CPP)/colamp-AT2G20110-DAP-Seq(GSE60143)/Homer ATTYAAATHY 1e0 -2.397e-01 1.0000 1103.0 27.57% 1131.0 28.37% +MYB113(MYB)/col-MYB113-DAP-Seq(GSE60143)/Homer HNDAWTCMGTTAYWN 1e0 -2.388e-01 1.0000 815.0 20.38% 840.8 21.09% +Arnt:Ahr(bHLH)/MCF7-Arnt-ChIP-Seq(Lo_et_al.)/Homer TBGCACGCAA 1e0 -2.380e-01 1.0000 1071.0 26.77% 1098.8 27.56% +PRDM14(Zf)/H1-PRDM14-ChIP-Seq(GSE22767)/Homer RGGTCTCTAACY 1e0 -2.374e-01 1.0000 298.0 7.45% 315.2 7.91% +ZNF692(Zf)/HEK293-ZNF692.GFP-ChIP-Seq(GSE58341)/Homer GTGGGCCCCA 1e0 -2.367e-01 1.0000 49.0 1.23% 56.4 1.41% +EMB1789(C3H)/col-EMB1789-DAP-Seq(GSE60143)/Homer TWTTTACCGYND 1e0 -2.364e-01 1.0000 487.0 12.17% 508.6 12.76% +EAR2(NR)/K562-NR2F6-ChIP-Seq(Encode)/Homer NRBCARRGGTCA 1e0 -2.349e-01 1.0000 776.0 19.40% 801.3 20.10% +At5g22890(C2H2)/col-At5g22890-DAP-Seq(GSE60143)/Homer NSAGGTKWTATCTGD 1e0 -2.343e-01 1.0000 26.0 0.65% 31.8 0.80% +WRKY71(WRKY)/col-WRKY71-DAP-Seq(GSE60143)/Homer CKTTGACYWW 1e0 -2.327e-01 1.0000 669.0 16.73% 693.0 17.39% +Pax7(Paired,Homeobox)/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer TAATCAATTA 1e0 -2.321e-01 1.0000 94.0 2.35% 104.8 2.63% +At2g45680(TCP)/colamp-At2g45680-DAP-Seq(GSE60143)/Homer GTGGGNCCCACNDND 1e0 -2.292e-01 1.0000 25.0 0.62% 30.4 0.76% +PTF1(TCP)/colamp-PTF1-DAP-Seq(GSE60143)/Homer RDDGGGACCACA 1e0 -2.280e-01 1.0000 59.0 1.47% 67.6 1.70% +PRDM9(Zf)/Testis-DMC1-ChIP-Seq(GSE35498)/Homer ADGGYAGYAGCATCT 1e0 -2.269e-01 1.0000 179.0 4.47% 193.2 4.85% +HIF2a(bHLH)/785_O-HIF2a-ChIP-Seq(GSE34871)/Homer GCACGTACCC 1e0 -2.266e-01 1.0000 792.0 19.80% 818.2 20.53% +Oct11(POU,Homeobox)/NCIH1048-POU2F3-ChIP-seq(GSE115123)/Homer GATTTGCATA 1e0 -2.232e-01 1.0000 201.0 5.03% 216.2 5.42% +Foxh1(Forkhead)/hESC-FOXH1-ChIP-Seq(GSE29422)/Homer NNTGTGGATTSS 1e0 -2.229e-01 1.0000 602.0 15.05% 626.9 15.73% +BPC1(BBRBPC)/colamp-BPC1-DAP-Seq(GSE60143)/Homer GARGAGAGAGAA 1e0 -2.207e-01 1.0000 146.0 3.65% 159.2 3.99% +Pit1+1bp(Homeobox)/GCrat-Pit1-ChIP-Seq(GSE58009)/Homer ATGCATAATTCA 1e0 -2.206e-01 1.0000 226.0 5.65% 242.1 6.07% +bHLH80(bHLH)/col-bHLH80-DAP-Seq(GSE60143)/Homer NNNNDCAASTTGHNN 1e0 -2.185e-01 1.0000 643.0 16.07% 668.8 16.78% +At4g32800(AP2EREBP)/colamp-At4g32800-DAP-Seq(GSE60143)/Homer DYCACCGACAHWWWH 1e0 -2.173e-01 1.0000 220.0 5.50% 236.0 5.92% +GATA3(Zf)/iTreg-Gata3-ChIP-Seq(GSE20898)/Homer AGATAASR 1e0 -2.170e-01 1.0000 1699.0 42.48% 1730.6 43.41% +AT3G51470(DBP)/col-AT3G51470-DAP-Seq(GSE60143)/Homer TTWHGGTGCACC 1e0 -2.163e-01 1.0000 1776.0 44.40% 1807.7 45.35% +HRE(HSF)/HepG2-HSF1-ChIP-Seq(GSE31477)/Homer BSTTCTRGAABVTTCYAGAA 1e0 -2.142e-01 1.0000 53.0 1.32% 61.7 1.55% +Phox2b(Homeobox)/CLBGA-PHOX2B-ChIP-Seq(GSE90683)/Homer TTAATTNAATTA 1e0 -2.134e-01 1.0000 213.0 5.33% 229.7 5.76% +bHLH122(bHLH)/col100-bHLH122-DAP-Seq(GSE60143)/Homer NDDCAASTTGHHNWW 1e0 -2.127e-01 1.0000 604.0 15.10% 629.9 15.80% +RARg(NR)/ES-RARg-ChIP-Seq(GSE30538)/Homer AGGTCAAGGTCA 1e0 -2.097e-01 1.0000 9.0 0.22% 12.5 0.31% +At3g12730(G2like)/colamp-At3g12730-DAP-Seq(GSE60143)/Homer AAGATTCT 1e0 -2.093e-01 1.0000 1546.0 38.65% 1578.5 39.60% +At3g24120(G2like)/col-At3g24120-DAP-Seq(GSE60143)/Homer NWWAGMATMW 1e0 -2.026e-01 1.0000 2872.0 71.80% 2898.0 72.70% +Unknown(Homeobox)/Limb-p300-ChIP-Seq/Homer SSCMATWAAA 1e0 -2.015e-01 1.0000 598.0 14.95% 624.6 15.67% +Hoxa13(Homeobox)/ChickenMSG-Hoxa13.Flag-ChIP-Seq(GSE86088)/Homer CYHATAAAAN 1e0 -2.003e-01 1.0000 2132.0 53.30% 2164.9 54.31% +WRKY21(WRKY)/colamp-WRKY21-DAP-Seq(GSE60143)/Homer DCGTTGACTTTT 1e0 -1.997e-01 1.0000 73.0 1.82% 83.8 2.10% +TCP20(TCP)/col-TCP20-DAP-Seq(GSE60143)/Homer GGDCCCAC 1e0 -1.982e-01 1.0000 164.0 4.10% 179.6 4.50% +Oct2(POU,Homeobox)/Bcell-Oct2-ChIP-Seq(GSE21512)/Homer ATATGCAAAT 1e0 -1.974e-01 1.0000 163.0 4.08% 178.2 4.47% +SPL14(SBP)/col-SPL14-DAP-Seq(GSE60143)/Homer NNWHTGTACGGAHNH 1e0 -1.972e-01 1.0000 572.0 14.30% 598.6 15.02% +AT1G69570(C2C2dof)/col-AT1G69570-DAP-Seq(GSE60143)/Homer WAAAAGTGHH 1e0 -1.936e-01 1.0000 1043.0 26.07% 1075.2 26.97% +MYB94(MYB)/col-MYB94-DAP-Seq(GSE60143)/Homer WGGTRGTTGGKA 1e0 -1.934e-01 1.0000 262.0 6.55% 281.8 7.07% +LHY(Myb)/Seedling-LHY-ChIP-Seq(GSE52175)/Homer ADAAATATCT 1e0 -1.920e-01 1.0000 1161.0 29.03% 1195.0 29.98% +bHLH28(bHLH)/col-bHLH28-DAP-Seq(GSE60143)/Homer NHHTGTACGGAH 1e0 -1.903e-01 1.0000 992.0 24.80% 1024.0 25.69% +Hnf1(Homeobox)/Liver-Foxa2-Chip-Seq(GSE25694)/Homer GGTTAAWCATTAA 1e0 -1.889e-01 1.0000 81.0 2.02% 92.6 2.32% +bHLH130(bHLH)/col-bHLH130-DAP-Seq(GSE60143)/Homer GCAACTTG 1e0 -1.884e-01 1.0000 524.0 13.10% 550.2 13.80% +COUP-TFII(NR)/K562-NR2F1-ChIP-Seq(Encode)/Homer GKBCARAGGTCA 1e0 -1.867e-01 1.0000 845.0 21.12% 876.9 22.00% +dof45(C2C2dof)/col-dof45-DAP-Seq(GSE60143)/Homer NVAWAAAGTN 1e0 -1.858e-01 1.0000 1882.0 47.05% 1917.5 48.10% +SVP(MADS)/col-SVP-DAP-Seq(GSE60143)/Homer ANTTWCCHAATTTGG 1e0 -1.858e-01 1.0000 419.0 10.47% 443.5 11.13% +MYB58(MYB)/colamp-MYB58-DAP-Seq(GSE60143)/Homer YYYACCWACC 1e0 -1.850e-01 1.0000 920.0 23.00% 952.1 23.88% +WRKY40(WRKY)/colamp-WRKY40-DAP-Seq(GSE60143)/Homer AHWAGTCAAC 1e0 -1.820e-01 1.0000 492.0 12.30% 518.8 13.02% +OCT:OCT(POU,Homeobox)/NPC-OCT6-ChIP-Seq(GSE43916)/Homer YATGCATATRCATRT 1e0 -1.820e-01 1.0000 24.0 0.60% 30.1 0.75% +LBD2(LOBAS2)/colamp-LBD2-DAP-Seq(GSE60143)/Homer TCCGAWTTTTTCGGN 1e0 -1.808e-01 1.0000 713.0 17.82% 743.7 18.66% +SEP3(MADS)/Arabidoposis-Flower-Sep3-ChIP-Seq/Homer CCAAAAAGGG 1e0 -1.805e-01 1.0000 783.0 19.57% 814.2 20.43% +At3g60580(C2H2)/col-At3g60580-DAP-Seq(GSE60143)/Homer WTTYTACT 1e0 -1.801e-01 1.0000 3506.0 87.65% 3521.9 88.35% +GT1(Trihelix)/col-GT1-DAP-Seq(GSE60143)/Homer TTAACCATGGTTAAD 1e0 -1.792e-01 1.0000 7.0 0.18% 10.8 0.27% +MYNN(Zf)/HEK293-MYNN.eGFP-ChIP-Seq(Encode)/Homer TTCAAAWTAAAAGTC 1e0 -1.779e-01 1.0000 181.0 4.52% 198.3 4.97% +bZIP:IRF(bZIP,IRF)/Th17-BatF-ChIP-Seq(GSE39756)/Homer NAGTTTCABTHTGACTNW 1e0 -1.769e-01 1.0000 158.0 3.95% 174.9 4.39% +AT5G02460(C2C2dof)/col-AT5G02460-DAP-Seq(GSE60143)/Homer CHCCTTTT 1e0 -1.747e-01 1.0000 1276.0 31.90% 1312.6 32.93% +E2F(E2F)/Hela-CellCycle-Expression/Homer TTSGCGCGAAAA 1e0 -1.745e-01 1.0000 101.0 2.53% 114.1 2.86% +CHR(?)/Hela-CellCycle-Expression/Homer SRGTTTCAAA 1e0 -1.744e-01 1.0000 342.0 8.55% 365.8 9.18% +Unknown-ESC-element(?)/mES-Nanog-ChIP-Seq(GSE11724)/Homer CACAGCAGGGGG 1e0 -1.738e-01 1.0000 154.0 3.85% 170.7 4.28% +NFAT:AP1(RHD,bZIP)/Jurkat-NFATC1-ChIP-Seq(Jolma_et_al.)/Homer SARTGGAAAAWRTGAGTCAB 1e0 -1.726e-01 1.0000 48.0 1.20% 57.7 1.45% +MYB121(MYB)/col-MYB121-DAP-Seq(GSE60143)/Homer YNTACCTAACWW 1e0 -1.698e-01 1.0000 438.0 10.95% 464.8 11.66% +ATHB33(ZFHD)/col-ATHB33-DAP-Seq(GSE60143)/Homer NGTRATTAAK 1e0 -1.678e-01 1.0000 1682.0 42.05% 1720.6 43.16% +Unknown4/Drosophila-Promoters/Homer AAAAATACCRMA 1e0 -1.643e-01 1.0000 93.0 2.33% 106.9 2.68% +TR4(NR),DR1/Hela-TR4-ChIP-Seq(GSE24685)/Homer GAGGTCAAAGGTCA 1e0 -1.641e-01 1.0000 10.0 0.25% 14.5 0.36% +ZNF382(Zf)/HEK293-ZNF382.GFP-ChIP-Seq(GSE58341)/Homer GNCTGTASTRNTGBCTCHTT 1e0 -1.641e-01 1.0000 10.0 0.25% 14.9 0.37% +PQM-1(?)/cElegans-L3-ChIP-Seq(modEncode)/Homer ACTGATAAGA 1e0 -1.632e-01 1.0000 451.0 11.28% 478.1 11.99% +AIL7(AP2EREBP)/colamp-AIL7-DAP-Seq(GSE60143)/Homer KCACRAWTYYCGAGG 1e0 -1.620e-01 1.0000 533.0 13.33% 562.7 14.12% +PHV(HB)/col-PHV-DAP-Seq(GSE60143)/Homer RTAATSATTA 1e0 -1.614e-01 1.0000 369.0 9.22% 394.7 9.90% +ATHB20(Homeobox)/colamp-ATHB20-DAP-Seq(GSE60143)/Homer CAATHATT 1e0 -1.611e-01 1.0000 404.0 10.10% 430.5 10.80% +WRKY8(WRKY)/colamp-WRKY8-DAP-Seq(GSE60143)/Homer CGTTGACTTT 1e0 -1.593e-01 1.0000 76.0 1.90% 88.3 2.21% +Zic(Zf)/Cerebellum-ZIC1.2-ChIP-Seq(GSE60731)/Homer CCTGCTGAGH 1e0 -1.586e-01 1.0000 432.0 10.80% 459.3 11.52% +HLH-1(bHLH)/cElegans-Embryo-HLH1-ChIP-Seq(modEncode)/Homer RACAGCTGTTBH 1e0 -1.581e-01 1.0000 430.0 10.75% 457.8 11.48% +Mef2b(MADS)/HEK293-Mef2b.V5-ChIP-Seq(GSE67450)/Homer GCTATTTTTGGM 1e0 -1.579e-01 1.0000 664.0 16.60% 696.0 17.46% +Esrrb(NR)/mES-Esrrb-ChIP-Seq(GSE11431)/Homer KTGACCTTGA 1e0 -1.568e-01 1.0000 388.0 9.70% 414.8 10.41% +RAR:RXR(NR),DR5/ES-RAR-ChIP-Seq(GSE56893)/Homer AGGTCAAGGTCA 1e0 -1.561e-01 1.0000 42.0 1.05% 52.0 1.30% +At1g72010(TCP)/colamp-At1g72010-DAP-Seq(GSE60143)/Homer GGDCCCAC 1e0 -1.558e-01 1.0000 237.0 5.92% 258.1 6.48% +Otx2(Homeobox)/EpiLC-Otx2-ChIP-Seq(GSE56098)/Homer NYTAATCCYB 1e0 -1.552e-01 1.0000 920.0 23.00% 956.2 23.99% +Tal1 CATCTG 1e0 -1.517e-01 1.0000 802.0 20.05% 837.5 21.01% +HOXA9(Homeobox)/HSC-Hoxa9-ChIP-Seq(GSE33509)/Homer GGCCATAAATCA 1e0 -1.514e-01 1.0000 673.0 16.83% 706.4 17.72% +NeuroD1(bHLH)/Islet-NeuroD1-ChIP-Seq(GSE30298)/Homer GCCATCTGTT 1e0 -1.504e-01 1.0000 334.0 8.35% 359.4 9.02% +COUP-TFII(NR)/Artia-Nr2f2-ChIP-Seq(GSE46497)/Homer AGRGGTCA 1e0 -1.486e-01 1.0000 1127.0 28.18% 1166.1 29.25% +Atoh1(bHLH)/Cerebellum-Atoh1-ChIP-Seq(GSE22111)/Homer VNRVCAGCTGGY 1e0 -1.468e-01 1.0000 459.0 11.47% 488.9 12.26% +ATHB21(HB)/colamp-ATHB21-DAP-Seq(GSE60143)/Homer YCAATWAT 1e0 -1.459e-01 1.0000 634.0 15.85% 667.6 16.75% +CEBP:CEBP(bZIP)/MEF-Chop-ChIP-Seq(GSE35681)/Homer NTNATGCAAYMNNHTGMAAY 1e0 -1.459e-01 1.0000 80.0 2.00% 93.4 2.34% +LBD18(LOBAS2)/colamp-LBD18-DAP-Seq(GSE60143)/Homer CKGAWWTTCHGS 1e0 -1.431e-01 1.0000 2681.0 67.03% 2717.2 68.17% +AT4G27900(C2C2COlike)/col-AT4G27900-DAP-Seq(GSE60143)/Homer TCTCVACCGTTSATT 1e0 -1.414e-01 1.0000 5.0 0.12% 8.1 0.20% +At5g58900(MYBrelated)/colamp-At5g58900-DAP-Seq(GSE60143)/Homer WWWTYTTATCTWWWW 1e0 -1.413e-01 1.0000 1439.0 35.98% 1481.1 37.16% +AT1G76880(Trihelix)/col-AT1G76880-DAP-Seq(GSE60143)/Homer ACGGTAAAAW 1e0 -1.401e-01 1.0000 304.0 7.60% 329.7 8.27% +BHLHA15(bHLH)/NIH3T3-BHLHB8.HA-ChIP-Seq(GSE119782)/Homer NAMCAGCTGK 1e0 -1.392e-01 1.0000 639.0 15.97% 673.5 16.90% +At1g68670(G2like)/colamp-At1g68670-DAP-Seq(GSE60143)/Homer WNWWHNRAAGATTCT 1e0 -1.392e-01 1.0000 392.0 9.80% 420.1 10.54% +Meis1(Homeobox)/MastCells-Meis1-ChIP-Seq(GSE48085)/Homer VGCTGWCAVB 1e0 -1.380e-01 1.0000 1160.0 29.00% 1201.9 30.15% +Nkx2.1(Homeobox)/LungAC-Nkx2.1-ChIP-Seq(GSE43252)/Homer RSCACTYRAG 1e0 -1.370e-01 1.0000 2139.0 53.47% 2181.9 54.74% +Nkx2.2(Homeobox)/NPC-Nkx2.2-ChIP-Seq(GSE61673)/Homer BTBRAGTGSN 1e0 -1.354e-01 1.0000 1427.0 35.68% 1470.7 36.90% +MYB39(MYB)/col-MYB39-DAP-Seq(GSE60143)/Homer WWAARKTAGGTGRAA 1e0 -1.322e-01 1.0000 139.0 3.48% 157.6 3.95% +LCL1(MYBrelated)/colamp-LCL1-DAP-Seq(GSE60143)/Homer NAAAATATCTWHWWN 1e0 -1.311e-01 1.0000 82.0 2.05% 96.1 2.41% +CRC(C2C2YABBY)/col-CRC-DAP-Seq(GSE60143)/Homer TWATSATA 1e0 -1.310e-01 1.0000 1478.0 36.95% 1522.1 38.18% +At2g01060(G2like)/colamp-At2g01060-DAP-Seq(GSE60143)/Homer AGATKCBNWW 1e0 -1.302e-01 1.0000 2897.0 72.42% 2932.7 73.57% +Oct4(POU,Homeobox)/mES-Oct4-ChIP-Seq(GSE11431)/Homer ATTTGCATAW 1e0 -1.287e-01 1.0000 299.0 7.47% 325.0 8.15% +Nr5a2(NR)/Pancreas-LRH1-ChIP-Seq(GSE34295)/Homer BTCAAGGTCA 1e0 -1.280e-01 1.0000 352.0 8.80% 380.3 9.54% +AT5G61620(MYBrelated)/colamp-AT5G61620-DAP-Seq(GSE60143)/Homer CTTATCCA 1e0 -1.276e-01 1.0000 1668.0 41.70% 1713.2 42.98% +RBFox2(?)/Heart-RBFox2-CLIP-Seq(GSE57926)/Homer TGCATGCA 1e0 -1.276e-01 1.0000 1659.0 41.48% 1704.2 42.75% +CDF3(C2C2dof)/colamp-CDF3-DAP-Seq(GSE60143)/Homer AAAAGTRM 1e0 -1.252e-01 1.0000 1257.0 31.42% 1301.7 32.66% +RARa(NR)/K562-RARa-ChIP-Seq(Encode)/Homer TTGAMCTTTG 1e0 -1.225e-01 1.0000 1762.0 44.05% 1808.4 45.37% +Olig2(bHLH)/Neuron-Olig2-ChIP-Seq(GSE30882)/Homer RCCATMTGTT 1e0 -1.216e-01 1.0000 1169.0 29.23% 1213.1 30.43% +CES-1(Homeobox)/cElegans-L1-CES1-ChIP-Seq(modEncode)/Homer AAATTSAATTTN 1e0 -1.211e-01 1.0000 452.0 11.30% 484.4 12.15% +ZNF416(Zf)/HEK293-ZNF416.GFP-ChIP-Seq(GSE58341)/Homer WDNCTGGGCA 1e0 -1.208e-01 1.0000 486.0 12.15% 519.2 13.02% +Cdx2(Homeobox)/mES-Cdx2-ChIP-Seq(GSE14586)/Homer GYMATAAAAH 1e0 -1.208e-01 1.0000 564.0 14.10% 599.9 15.05% +Pax7(Paired,Homeobox),long/Myoblast-Pax7-ChIP-Seq(GSE25064)/Homer TAATCHGATTAC 1e0 -1.196e-01 1.0000 10.0 0.25% 15.3 0.38% +MYB99(MYB)/colamp-MYB99-DAP-Seq(GSE60143)/Homer GGTAGGTG 1e0 -1.195e-01 1.0000 943.0 23.57% 985.2 24.72% +ELT-3(Gata)/cElegans-L1-ELT3-ChIP-Seq(modEncode)/Homer AWTGATAAGA 1e0 -1.170e-01 1.0000 467.0 11.68% 500.5 12.56% +NLP7(RWPRK)/col-NLP7-DAP-Seq(GSE60143)/Homer TGRCCYTTCR 1e0 -1.165e-01 1.0000 1305.0 32.62% 1351.6 33.91% +Unknown2/Drosophila-Promoters/Homer CATCMCTA 1e0 -1.162e-01 1.0000 667.0 16.68% 705.6 17.70% +WIP5(C2H2)/colamp-WIP5-DAP-Seq(GSE60143)/Homer TDTTCTCMAGGT 1e0 -1.147e-01 1.0000 817.0 20.42% 858.9 21.55% +BBX31(Orphan)/col-BBX31-DAP-Seq(GSE60143)/Homer NAAAAAGTDA 1e0 -1.115e-01 1.0000 1172.0 29.30% 1218.9 30.58% +KAN2(G2like)/colamp-KAN2-DAP-Seq(GSE60143)/Homer ATATTCTY 1e0 -1.107e-01 1.0000 1155.0 28.88% 1202.0 30.15% +ATHB18(Homeobox)/colamp-ATHB18-DAP-Seq(GSE60143)/Homer YCAATSATTG 1e0 -1.101e-01 1.0000 192.0 4.80% 215.4 5.40% +At5g62940(C2C2dof)/col-At5g62940-DAP-Seq(GSE60143)/Homer WHWHHACTTTTT 1e0 -1.078e-01 1.0000 2389.0 59.72% 2435.9 61.11% +ATHB15(HB)/col-ATHB15-DAP-Seq(GSE60143)/Homer GYAATSATTA 1e0 -1.048e-01 1.0000 329.0 8.22% 359.0 9.01% +Pdx1(Homeobox)/Islet-Pdx1-ChIP-Seq(SRA008281)/Homer YCATYAATCA 1e0 -1.043e-01 1.0000 884.0 22.10% 928.3 23.29% +AT1G47655(C2C2dof)/colamp-AT1G47655-DAP-Seq(GSE60143)/Homer YHACTTTTTS 1e0 -1.040e-01 1.0000 2473.0 61.82% 2519.8 63.21% +ZKSCAN1(Zf)/HepG2-ZKSCAN1-ChIP-Seq(Encode)/Homer GCACAYAGTAGGKCY 1e0 -1.036e-01 1.0000 21.0 0.53% 29.6 0.74% +MYB63(MYB)/col-MYB63-DAP-Seq(GSE60143)/Homer BHYACCWACCHH 1e0 -1.034e-01 1.0000 350.0 8.75% 381.2 9.56% +Mef2c(MADS)/GM12878-Mef2c-ChIP-Seq(GSE32465)/Homer DCYAAAAATAGM 1e0 -1.033e-01 1.0000 235.0 5.88% 261.4 6.56% +JGL(C2H2)/col-JGL-DAP-Seq(GSE60143)/Homer ACYTTCAGTT 1e0 -1.032e-01 1.0000 1338.0 33.45% 1387.2 34.80% +Hoxa11(Homeobox)/ChickenMSG-Hoxa11.Flag-ChIP-Seq(GSE86088)/Homer TTTTATGGCM 1e0 -1.025e-01 1.0000 2160.0 54.00% 2209.6 55.43% +Pitx1:Ebox(Homeobox,bHLH)/Hindlimb-Pitx1-ChIP-Seq(GSE41591)/Homer YTAATTRAWWCCAGATGT 1e0 -1.020e-01 1.0000 83.0 2.08% 99.2 2.49% +LBD19(LOBAS2)/colamp-LBD19-DAP-Seq(GSE60143)/Homer CCKGAAWTTCMGGAW 1e0 -1.016e-01 1.0000 2006.0 50.15% 2056.1 51.58% +Nr5a2(NR)/mES-Nr5a2-ChIP-Seq(GSE19019)/Homer BTCAAGGTCA 1e0 -1.015e-01 1.0000 251.0 6.28% 279.0 7.00% +At1g49010(MYBrelated)/col-At1g49010-DAP-Seq(GSE60143)/Homer RGATAASNTT 1e0 -1.011e-01 1.0000 2038.0 50.95% 2088.9 52.40% +Rfx6(HTH)/Min6b1-Rfx6.HA-ChIP-Seq(GSE62844)/Homer TGTTKCCTAGCAACM 1e0 -1.010e-01 1.0000 641.0 16.02% 681.3 17.09% +MYB62(MYB)/colamp-MYB62-DAP-Seq(GSE60143)/Homer NTACCTAACT 1e0 -9.865e-02 1.0000 1552.0 38.80% 1603.4 40.22% +AZF1(C2H2)/colamp-AZF1-DAP-Seq(GSE60143)/Homer DKSWCACT 1e0 -9.800e-02 1.0000 3288.0 82.20% 3320.4 83.30% +WRKY17(WRKY)/colamp-WRKY17-DAP-Seq(GSE60143)/Homer GCGTTGACTTTT 1e0 -9.491e-02 1.0000 11.0 0.27% 17.0 0.43% +RIN(MADS)/Tomato-RIN-ChIP-Seq(GSE116581)/Homer CYAAAAWWGG 1e0 -9.486e-02 1.0000 956.0 23.90% 1003.8 25.18% +GTL1(Trihelix)/colamp-GTL1-DAP-Seq(GSE60143)/Homer WWTTTACCKY 1e0 -9.432e-02 1.0000 948.0 23.70% 995.9 24.99% +MYB107(MYB)/col-MYB107-DAP-Seq(GSE60143)/Homer RGTWGGTRRR 1e0 -9.262e-02 1.0000 1435.0 35.88% 1487.8 37.32% +AT5G60130(ABI3VP1)/col-AT5G60130-DAP-Seq(GSE60143)/Homer WTTYTAAGVAAA 1e0 -9.218e-02 1.0000 917.0 22.93% 964.2 24.19% +Lhx1(Homeobox)/EmbryoCarcinoma-Lhx1-ChIP-Seq(GSE70957)/Homer NNYTAATTAR 1e0 -8.942e-02 1.0000 1306.0 32.65% 1358.5 34.08% +Nkx6.1(Homeobox)/Islet-Nkx6.1-ChIP-Seq(GSE40975)/Homer GKTAATGR 1e0 -8.925e-02 1.0000 2950.0 73.75% 2992.5 75.07% +ATHB6(Homeobox)/Arabidopsis-HB6-ChIP-Seq(GSE80564)/Homer CAATNATTBN 1e0 -8.803e-02 1.0000 806.0 20.15% 852.7 21.39% +Lhx2(Homeobox)/HFSC-Lhx2-ChIP-Seq(GSE48068)/Homer TAATTAGN 1e0 -8.713e-02 1.0000 1368.0 34.20% 1421.8 35.67% +HNF1b(Homeobox)/PDAC-HNF1B-ChIP-Seq(GSE64557)/Homer GTTAATNATTAA 1e0 -8.699e-02 1.0000 114.0 2.85% 134.9 3.38% +Six4(Homeobox)/MCF7-SIX4-ChIP-Seq(Encode)/Homer TGWAAYCTGABACCB 1e0 -8.569e-02 1.0000 33.0 0.83% 44.7 1.12% +MYB55(MYB)/colamp-MYB55-DAP-Seq(GSE60143)/Homer YACCWAMC 1e0 -8.560e-02 1.0000 1100.0 27.50% 1151.9 28.90% +CRX(Homeobox)/Retina-Crx-ChIP-Seq(GSE20012)/Homer GCTAATCC 1e0 -8.496e-02 1.0000 2522.0 63.05% 2572.7 64.54% +HSF3(HSF)/colamp-HSF3-DAP-Seq(GSE60143)/Homer NTTCTAGAAKCTTCT 1e0 -8.343e-02 1.0000 626.0 15.65% 669.5 16.80% +OBP3(C2C2dof)/col-OBP3-DAP-Seq(GSE60143)/Homer NYWACTTTTT 1e0 -7.870e-02 1.0000 2181.0 54.52% 2236.3 56.10% +TRPS1(Zf)/MCF7-TRPS1-ChIP-Seq(GSE107013)/Homer AGATAAGANN 1e0 -7.831e-02 1.0000 2024.0 50.60% 2080.5 52.19% +At5g04390(C2H2)/col200-At5g04390-DAP-Seq(GSE60143)/Homer AGTGANDN 1e0 -7.777e-02 1.0000 3408.0 85.20% 3440.9 86.32% +CCA(Myb)/Arabidopsis-CCA.GFP-ChIP-Seq(GSE70533)/Homer AGATATYTTT 1e0 -7.738e-02 1.0000 890.0 22.25% 940.5 23.60% +At3g45610(C2C2dof)/col-At3g45610-DAP-Seq(GSE60143)/Homer TWACTTTTTS 1e0 -7.651e-02 1.0000 1001.0 25.02% 1053.3 26.43% +TCF4(bHLH)/SHSY5Y-TCF4-ChIP-Seq(GSE96915)/Homer SMCATCTGKH 1e0 -7.574e-02 1.0000 766.0 19.15% 814.2 20.42% +LIN-39(Homeobox)/cElegans.L3-LIN39-ChIP-Seq(modEncode)/Homer ATGATTRATG 1e0 -7.461e-02 1.0000 968.0 24.20% 1020.6 25.60% +TSO1(CPP)/col-TSO1-DAP-Seq(GSE60143)/Homer RAATTTRAAW 1e0 -7.300e-02 1.0000 47.0 1.18% 61.6 1.55% +GLIS3(Zf)/Thyroid-Glis3.GFP-ChIP-Seq(GSE103297)/Homer CTCCCTGGGAGGCCN 1e0 -7.256e-02 1.0000 544.0 13.60% 587.1 14.73% +Tgif2(Homeobox)/mES-Tgif2-ChIP-Seq(GSE55404)/Homer TGTCANYT 1e0 -7.233e-02 1.0000 2293.0 57.33% 2349.2 58.94% +TCP1(TCP)/col-TCP1-DAP-Seq(GSE60143)/Homer GGGGGCCCMMCN 1e0 -7.129e-02 1.0000 118.0 2.95% 140.7 3.53% +OBP4(C2C2dof)/col-OBP4-DAP-Seq(GSE60143)/Homer WTTHACTTTTTB 1e0 -7.123e-02 1.0000 1041.0 26.02% 1095.7 27.49% +Twist(bHLH)/HMLE-TWIST1-ChIP-Seq(Chang_et_al)/Homer VCAKCTGGNNNCCAGMTGBN 1e0 -7.072e-02 1.0000 28.0 0.70% 39.2 0.98% +AT3G12130(C3H)/colamp-AT3G12130-DAP-Seq(GSE60143)/Homer TMACTTTTTV 1e0 -7.036e-02 1.0000 1770.0 44.25% 1829.7 45.90% +REM19(REM)/colamp-REM19-DAP-Seq(GSE60143)/Homer AAAAAAAA 1e0 -7.017e-02 1.0000 153.0 3.82% 178.3 4.47% +AT2G38300(G2like)/col-AT2G38300-DAP-Seq(GSE60143)/Homer ADRGAATGTT 1e0 -7.006e-02 1.0000 1018.0 25.45% 1072.3 26.90% +PRDM15(Zf)/ESC-Prdm15-ChIP-Seq(GSE73694)/Homer YCCDNTCCAGGTTTT 1e0 -6.988e-02 1.0000 557.0 13.93% 602.0 15.10% +AT2G28920(ND)/col-AT2G28920-DAP-Seq(GSE60143)/Homer WAGATATTTWTW 1e0 -6.938e-02 1.0000 179.0 4.47% 206.8 5.19% +ATHB53(HB)/col-ATHB53-DAP-Seq(GSE60143)/Homer CAATAATT 1e0 -6.860e-02 1.0000 487.0 12.17% 529.3 13.28% +AT5G47660(Trihelix)/colamp-AT5G47660-DAP-Seq(GSE60143)/Homer AWTTTTACCG 1e0 -6.860e-02 1.0000 1341.0 33.52% 1399.3 35.11% +MYB40(MYB)/col-MYB40-DAP-Seq(GSE60143)/Homer TGGTAGGTRARA 1e0 -6.730e-02 1.0000 272.0 6.80% 305.1 7.65% +AT3G52440(C2C2dof)/colamp-AT3G52440-DAP-Seq(GSE60143)/Homer DTHACTTTTT 1e0 -6.718e-02 1.0000 1711.0 42.77% 1771.5 44.44% +MYB10(MYB)/col-MYB10-DAP-Seq(GSE60143)/Homer YCCACCTACCHH 1e0 -6.639e-02 1.0000 328.0 8.20% 364.9 9.15% +ZNF143|STAF(Zf)/CUTLL-ZNF143-ChIP-Seq(GSE29600)/Homer ATTTCCCAGVAKSCY 1e0 -6.529e-02 1.0000 81.0 2.02% 100.7 2.53% +NeuroG2(bHLH)/Fibroblast-NeuroG2-ChIP-Seq(GSE75910)/Homer ACCATCTGTT 1e0 -6.523e-02 1.0000 780.0 19.50% 831.4 20.86% +GT2(Trihelix)/colamp-GT2-DAP-Seq(GSE60143)/Homer AMGGTAAAWWWN 1e0 -6.447e-02 1.0000 978.0 24.45% 1033.8 25.93% +OCT:OCT(POU,Homeobox)/NPC-Brn1-ChIP-Seq(GSE35496)/Homer ATGAATATTCATGAG 1e0 -6.402e-02 1.0000 1.0 0.03% 3.5 0.09% +Bapx1(Homeobox)/VertebralCol-Bapx1-ChIP-Seq(GSE36672)/Homer TTRAGTGSYK 1e0 -6.385e-02 1.0000 1639.0 40.98% 1701.0 42.67% +AGL63(MADS)/col-AGL63-DAP-Seq(GSE60143)/Homer TTCCAAWWWTGG 1e0 -6.372e-02 1.0000 680.0 17.00% 729.4 18.30% +Barx1(Homeobox)/Stomach-Barx1.3xFlag-ChIP-Seq(GSE69483)/Homer AAACMATTAN 1e0 -6.278e-02 1.0000 478.0 11.95% 521.3 13.08% +ATHB24(ZFHD)/colamp-ATHB24-DAP-Seq(GSE60143)/Homer TAATTAAS 1e0 -6.255e-02 1.0000 1004.0 25.10% 1060.2 26.60% +Dlx3(Homeobox)/Kerainocytes-Dlx3-ChIP-Seq(GSE89884)/Homer NDGTAATTAC 1e0 -6.244e-02 1.0000 887.0 22.18% 941.0 23.61% +PBX2(Homeobox)/K562-PBX2-ChIP-Seq(Encode)/Homer RTGATTKATRGN 1e0 -6.205e-02 1.0000 881.0 22.02% 935.9 23.48% +AT3G10580(MYBrelated)/colamp-AT3G10580-DAP-Seq(GSE60143)/Homer TACCTAACWNHW 1e0 -6.122e-02 1.0000 468.0 11.70% 512.0 12.84% +HDG7(HB)/col-HDG7-DAP-Seq(GSE60143)/Homer WGCATTTAATGC 1e0 -6.070e-02 1.0000 149.0 3.72% 175.9 4.41% +At3g09600(MYBrelated)/colamp-At3g09600-DAP-Seq(GSE60143)/Homer AAAATATCTT 1e0 -5.957e-02 1.0000 341.0 8.53% 379.3 9.51% +Unknown6/Drosophila-Promoters/Homer AATTTTAAAA 1e0 -5.918e-02 1.0000 319.0 7.98% 356.3 8.94% +AT5G66940(C2C2dof)/col-AT5G66940-DAP-Seq(GSE60143)/Homer NNHACTTTWT 1e0 -5.696e-02 1.0000 1514.0 37.85% 1577.0 39.56% +Prop1(Homeobox)/GHFT1-PROP1.biotin-ChIP-Seq(GSE77302)/Homer NTAATBNAATTA 1e0 -5.653e-02 1.0000 578.0 14.45% 626.2 15.71% +At1g69690(TCP)/colamp-At1g69690-DAP-Seq(GSE60143)/Homer NHGTGGGGCCCACHW 1e0 -5.583e-02 1.0000 108.0 2.70% 131.7 3.30% +WRKY7(WRKY)/colamp-WRKY7-DAP-Seq(GSE60143)/Homer AAAAGTCAACGSHWD 1e0 -5.547e-02 1.0000 3.0 0.07% 7.1 0.18% +Tcf12(bHLH)/GM12878-Tcf12-ChIP-Seq(GSE32465)/Homer VCAGCTGYTG 1e0 -5.526e-02 1.0000 303.0 7.58% 340.1 8.53% +MYB3(MYB)/Arabidopsis-MYB3-ChIP-Seq(GSE80564)/Homer GKTAGGTRGG 1e0 -5.476e-02 1.0000 1381.0 34.52% 1444.4 36.23% +MYB17(MYB)/colamp-MYB17-DAP-Seq(GSE60143)/Homer GGTAGGTGRG 1e0 -5.359e-02 1.0000 445.0 11.12% 489.8 12.29% +At2g41835(C2H2)/col-At2g41835-DAP-Seq(GSE60143)/Homer TTTGAAAA 1e0 -5.348e-02 1.0000 278.0 6.95% 314.1 7.88% +MYB13(MYB)/col-MYB13-DAP-Seq(GSE60143)/Homer HYCACCWACCHH 1e0 -5.342e-02 1.0000 469.0 11.72% 514.1 12.90% +AT3G10113(MYBrelated)/col-AT3G10113-DAP-Seq(GSE60143)/Homer WNAAATATCWWN 1e0 -5.298e-02 1.0000 466.0 11.65% 511.5 12.83% +bcd(Homeobox)/Embryo-Bcd-ChIP-Seq(GSE86966)/Homer VNNGGATTADNN 1e0 -5.285e-02 1.0000 1419.0 35.48% 1483.6 37.22% +MYB93(MYB)/colamp-MYB93-DAP-Seq(GSE60143)/Homer GGTAGGTGRD 1e0 -5.251e-02 1.0000 985.0 24.62% 1044.2 26.20% +MS188(MYB)/colamp-MS188-DAP-Seq(GSE60143)/Homer WARKTAGGTRRA 1e0 -5.250e-02 1.0000 747.0 18.68% 802.0 20.12% +LMI1(HB)/colamp-LMI1-DAP-Seq(GSE60143)/Homer AATTATTG 1e0 -5.016e-02 1.0000 681.0 17.03% 734.2 18.42% +HAT1(Homeobox)/col-HAT1-DAP-Seq(GSE60143)/Homer SCAATCATTGNN 1e0 -4.933e-02 1.0000 163.0 4.08% 192.7 4.83% +Myf5(bHLH)/GM-Myf5-ChIP-Seq(GSE24852)/Homer BAACAGCTGT 1e0 -4.860e-02 1.0000 244.0 6.10% 279.1 7.00% +dof24(C2C2dof)/col-dof24-DAP-Seq(GSE60143)/Homer TWMCTTTTTG 1e0 -4.849e-02 1.0000 1456.0 36.40% 1522.9 38.21% +CDX4(Homeobox)/ZebrafishEmbryos-Cdx4.Myc-ChIP-Seq(GSE48254)/Homer NGYCATAAAWCH 1e0 -4.776e-02 1.0000 894.0 22.35% 953.5 23.92% +FUS3(ABI3VP1)/col-FUS3-DAP-Seq(GSE60143)/Homer DNNWTNTGCATGKNN 1e0 -4.707e-02 1.0000 680.0 17.00% 734.5 18.43% +ATHB34(ZFHD)/colamp-ATHB34-DAP-Seq(GSE60143)/Homer TRATTARS 1e0 -4.600e-02 1.0000 1017.0 25.42% 1079.5 27.08% +MYB92(MYB)/colamp-MYB92-DAP-Seq(GSE60143)/Homer GGTAGGTR 1e0 -4.582e-02 1.0000 816.0 20.40% 874.4 21.94% +At1g76110(ARID)/colamp-At1g76110-DAP-Seq(GSE60143)/Homer ATTTAATG 1e0 -4.570e-02 1.0000 600.0 15.00% 652.3 16.36% +MYB83(MYB)/colamp-MYB83-DAP-Seq(GSE60143)/Homer CACCAACCWH 1e0 -4.545e-02 1.0000 1412.0 35.30% 1479.5 37.12% +AT2G28810(C2C2dof)/colamp-AT2G28810-DAP-Seq(GSE60143)/Homer VAAAAAGTWA 1e0 -4.544e-02 1.0000 1591.0 39.77% 1659.7 41.64% +MYB41(MYB)/col-MYB41-DAP-Seq(GSE60143)/Homer BYTYACCTAA 1e0 -4.501e-02 1.0000 351.0 8.77% 393.6 9.88% +ANL2(HB)/col-ANL2-DAP-Seq(GSE60143)/Homer CATTAATTGC 1e0 -4.467e-02 1.0000 481.0 12.03% 529.8 13.29% +ERRg(NR)/Kidney-ESRRG-ChIP-Seq(GSE104905)/Homer GTGACCTTGRVN 1e0 -4.454e-02 1.0000 480.0 12.00% 528.6 13.26% +HIC1(Zf)/Treg-ZBTB29-ChIP-Seq(GSE99889)/Homer TGCCAGCB 1e0 -4.435e-02 1.0000 1170.0 29.25% 1235.1 30.98% +Hoxd11(Homeobox)/ChickenMSG-Hoxd11.Flag-ChIP-Seq(GSE86088)/Homer VGCCATAAAA 1e0 -4.259e-02 1.0000 2197.0 54.93% 2265.0 56.82% +At5g52660(MYBrelated)/colamp-At5g52660-DAP-Seq(GSE60143)/Homer HAAAAATATCTW 1e0 -4.231e-02 1.0000 284.0 7.10% 324.0 8.13% +Tbr1(T-box)/Cortex-Tbr1-ChIP-Seq(GSE71384)/Homer AAGGTGTKAA 1e0 -4.224e-02 1.0000 1176.0 29.40% 1242.2 31.16% +OBP1(C2C2dof)/col-OBP1-DAP-Seq(GSE60143)/Homer NHHACTTTWT 1e0 -4.188e-02 1.0000 2105.0 52.62% 2174.8 54.56% +SCL(bHLH)/HPC7-Scl-ChIP-Seq(GSE13511)/Homer AVCAGCTG 1e0 -4.069e-02 1.0000 2030.0 50.75% 2100.6 52.70% +Isl1(Homeobox)/Neuron-Isl1-ChIP-Seq(GSE31456)/Homer CTAATKGV 1e0 -4.014e-02 1.0000 2082.0 52.05% 2152.3 53.99% +GSC(Homeobox)/FrogEmbryos-GSC-ChIP-Seq(DRA000576)/Homer RGGATTAR 1e0 -3.985e-02 1.0000 1468.0 36.70% 1538.0 38.58% +Twist2(bHLH)/Myoblast-Twist2.Ty1-ChIP-Seq(GSE127998)/Homer MCAGCTGBYH 1e0 -3.865e-02 1.0000 863.0 21.57% 925.8 23.23% +Phox2a(Homeobox)/Neuron-Phox2a-ChIP-Seq(GSE31456)/Homer YTAATYNRATTA 1e0 -3.823e-02 1.0000 333.0 8.33% 376.7 9.45% +NF1-halfsite(CTF)/LNCaP-NF1-ChIP-Seq(Unpublished)/Homer YTGCCAAG 1e0 -3.730e-02 1.0000 926.0 23.15% 990.6 24.85% +MYB61(MYB)/colamp-MYB61-DAP-Seq(GSE60143)/Homer HCYACCTACC 1e0 -3.715e-02 1.0000 1308.0 32.70% 1378.8 34.59% +caudal(Homeobox)/Drosophila-Embryos-ChIP-Chip(modEncode)/Homer GGYCATAAAW 1e0 -3.514e-02 1.0000 838.0 20.95% 901.9 22.63% +ATHB6(Homeobox)/col-ATHB6-DAP-Seq(GSE60143)/Homer AATGATTG 1e0 -3.438e-02 1.0000 1361.0 34.02% 1433.9 35.97% +ATHB13(Homeobox)/col-ATHB13-DAP-Seq(GSE60143)/Homer CAATAATT 1e0 -3.435e-02 1.0000 1004.0 25.10% 1071.4 26.88% +MYB51(MYB)/col-MYB51-DAP-Seq(GSE60143)/Homer GGTAGGTG 1e0 -3.420e-02 1.0000 782.0 19.55% 845.0 21.20% +AT1G20910(ARID)/col-AT1G20910-DAP-Seq(GSE60143)/Homer THAATTRAWN 1e0 -3.242e-02 1.0000 1686.0 42.15% 1761.8 44.20% +At1g64620(C2C2dof)/colamp-At1g64620-DAP-Seq(GSE60143)/Homer CACTTTTT 1e0 -3.018e-02 1.0000 944.0 23.60% 1012.3 25.39% +DAG2(C2C2dof)/col-DAG2-DAP-Seq(GSE60143)/Homer WWTTHACTTTTT 1e0 -3.015e-02 1.0000 1099.0 27.47% 1170.1 29.35% +AT4G26030(C2H2)/col-AT4G26030-DAP-Seq(GSE60143)/Homer BYYACCWACY 1e0 -2.658e-02 1.0000 896.0 22.40% 965.9 24.23% +EPR1(MYBrelated)/colamp-EPR1-DAP-Seq(GSE60143)/Homer AAATATCT 1e0 -2.609e-02 1.0000 327.0 8.18% 374.2 9.39% +LHY1(MYBrelated)/col-LHY1-DAP-Seq(GSE60143)/Homer AAATATCT 1e0 -2.609e-02 1.0000 327.0 8.18% 374.2 9.39% +ATHB23(ZFHD)/col-ATHB23-DAP-Seq(GSE60143)/Homer HTAATTARNN 1e0 -2.599e-02 1.0000 1123.0 28.07% 1197.1 30.03% +TAGL1(MADS)/Tomato-TAGL1-ChIP-Seq(GSE116581)/Homer CCAAAAATRG 1e0 -2.529e-02 1.0000 904.0 22.60% 974.6 24.45% +Adof1(C2C2dof)/col-Adof1-DAP-Seq(GSE60143)/Homer NRWAAAGYDV 1e0 -2.329e-02 1.0000 1991.0 49.78% 2072.7 52.00% +RVE1(MYBrelated)/col-RVE1-DAP-Seq(GSE60143)/Homer AAATATCT 1e0 -2.315e-02 1.0000 629.0 15.72% 692.1 17.36% +ATHB25(ZFHD)/colamp-ATHB25-DAP-Seq(GSE60143)/Homer TAATTAVB 1e0 -2.138e-02 1.0000 1391.0 34.77% 1472.3 36.94% +At4g01280(MYBrelated)/colamp-At4g01280-DAP-Seq(GSE60143)/Homer AAATATCT 1e0 -2.069e-02 1.0000 438.0 10.95% 494.7 12.41% +MYB67(MYB)/col-MYB67-DAP-Seq(GSE60143)/Homer YYYACCTAAC 1e0 -2.066e-02 1.0000 895.0 22.38% 968.0 24.28% +MYB74(MYB)/colamp-MYB74-DAP-Seq(GSE60143)/Homer YYYACCTACCWH 1e0 -1.969e-02 1.0000 550.0 13.75% 612.0 15.35% +HOXB13(Homeobox)/ProstateTumor-HOXB13-ChIP-Seq(GSE56288)/Homer TTTTATKRGG 1e0 -1.881e-02 1.0000 1097.0 27.43% 1177.0 29.53% +HDG1(Homeobox)/col100-HDG1-DAP-Seq(GSE60143)/Homer DDYAATTAATGH 1e0 -1.881e-02 1.0000 417.0 10.42% 473.4 11.88% +Hoxd13(Homeobox)/ChickenMSG-Hoxd13.Flag-ChIP-Seq(GSE86088)/Homer NCYAATAAAA 1e0 -1.666e-02 1.0000 1459.0 36.48% 1545.2 38.76% +HOXD13(Homeobox)/Chicken-Hoxd13-ChIP-Seq(GSE38910)/Homer NCYAATAAAA 1e0 -1.532e-02 1.0000 806.0 20.15% 881.8 22.12% +ATHB40(HB)/col-ATHB40-DAP-Seq(GSE60143)/Homer HCAATWATTG 1e0 -1.483e-02 1.0000 823.0 20.57% 899.1 22.56% +bZIP18(bZIP)/colamp-bZIP18-DAP-Seq(GSE60143)/Homer KGMCAGCTND 1e0 -1.452e-02 1.0000 3022.0 75.55% 3093.9 77.62% +ATY19(MYB)/col-ATY19-DAP-Seq(GSE60143)/Homer YYCACCWACCAT 1e0 -1.265e-02 1.0000 579.0 14.47% 648.6 16.27% +SeqBias: TA-repeat TATATATATA 1e0 -1.164e-02 1.0000 2049.0 51.23% 2142.4 53.75% +MYB4(MYB)/col200-MYB4-DAP-Seq(GSE60143)/Homer WAGKTAGGTARR 1e0 -1.014e-02 1.0000 543.0 13.58% 613.8 15.40% +AT2G40260(G2like)/colamp-AT2G40260-DAP-Seq(GSE60143)/Homer WAAAYATTCTTT 1e0 -8.290e-03 1.0000 1329.0 33.23% 1425.7 35.77% +Tbx21(T-box)/GM12878-TBX21-ChIP-Seq(Encode)/Homer AGGTGTGAAA 1e0 -7.387e-03 1.0000 651.0 16.28% 730.1 18.32% +AtHB32(ZFHD)/col200-AtHB32-DAP-Seq(GSE60143)/Homer CGAATTAT 1e0 -5.439e-03 1.0000 1872.0 46.80% 1978.5 49.63% +MYB49(MYB)/col-MYB49-DAP-Seq(GSE60143)/Homer ARKTAGGTRR 1e0 -5.347e-03 1.0000 975.0 24.38% 1070.5 26.85% +AT5G63260(C3H)/col-AT5G63260-DAP-Seq(GSE60143)/Homer RAAAAAGTRA 1e0 -5.299e-03 1.0000 1647.0 41.17% 1753.8 44.00% +MyoG(bHLH)/C2C12-MyoG-ChIP-Seq(GSE36024)/Homer AACAGCTG 1e0 -4.108e-03 1.0000 347.0 8.67% 414.5 10.40% +Tbet(T-box)/CD8-Tbet-ChIP-Seq(GSE33802)/Homer AGGTGTGAAM 1e0 -4.015e-03 1.0000 754.0 18.85% 845.4 21.21% +SCRT1(Zf)/HEK293-SCRT1.eGFP-ChIP-Seq(Encode)/Homer GCAACAGGTG 1e0 -3.240e-03 1.0000 204.0 5.10% 259.7 6.52% +Eomes(T-box)/H9-Eomes-ChIP-Seq(GSE26097)/Homer ATTAACACCT 1e0 -1.128e-03 1.0000 1523.0 38.07% 1650.5 41.41% +Ascl1(bHLH)/NeuralTubes-Ascl1-ChIP-Seq(GSE55840)/Homer NNVVCAGCTGBN 1e0 -5.310e-04 1.0000 558.0 13.95% 661.0 16.58% +Tbx6(T-box)/ESC-Tbx6-ChIP-Seq(GSE93524)/Homer DAGGTGTBAA 1e0 -1.150e-04 1.0000 754.0 18.85% 883.7 22.17% +HEB(bHLH)/mES-Heb-ChIP-Seq(GSE53233)/Homer VCAGCTGBNN 1e0 -1.000e-04 1.0000 749.0 18.73% 879.6 22.07% +Ascl2(bHLH)/ESC-Ascl2-ChIP-Seq(GSE97712)/Homer SSRGCAGCTGCH 1e0 -9.100e-05 1.0000 388.0 9.70% 490.5 12.31% +Ptf1a(bHLH)/Panc1-Ptf1a-ChIP-Seq(GSE47459)/Homer ACAGCTGTTN 1e0 -2.200e-05 1.0000 1146.0 28.65% 1309.4 32.85% +Tbx5(T-box)/HL1-Tbx5.biotin-ChIP-Seq(GSE21529)/Homer AGGTGTCA 1e0 -5.000e-06 1.0000 1929.0 48.23% 2118.1 53.14% +E2A(bHLH)/proBcell-E2A-ChIP-Seq(GSE21978)/Homer DNRCAGCTGY 1e0 -3.000e-06 1.0000 459.0 11.47% 593.6 14.89% +Zelda(Zf)/Embryo-zld-ChIP-Seq(GSE65441)/Homer KBCTACCTGW 1e0 -1.000e-06 1.0000 259.0 6.48% 374.3 9.39% +Slug(Zf)/Mesoderm-Snai2-ChIP-Seq(GSE61475)/Homer SNGCACCTGCHS 1e0 -0.000e+00 1.0000 152.0 3.80% 251.4 6.31% +NGA4(ABI3VP1)/col-NGA4-DAP-Seq(GSE60143)/Homer TKNTCAGGTG 1e0 -0.000e+00 1.0000 1242.0 31.05% 1600.1 40.14% +ZEB2(Zf)/SNU398-ZEB2-ChIP-Seq(GSE103048)/Homer GNMCAGGTGTGC 1e0 -0.000e+00 1.0000 335.0 8.38% 511.9 12.84% +E2A(bHLH),near_PU.1/Bcell-PU.1-ChIP-Seq(GSE21512)/Homer NVCACCTGBN 1e0 -0.000e+00 1.0000 477.0 11.92% 718.7 18.03% +ZEB1(Zf)/PDAC-ZEB1-ChIP-Seq(GSE64557)/Homer VCAGGTRDRY 1e0 -0.000e+00 1.0000 761.0 19.02% 1085.8 27.24% +DUX(Homeobox)/C2C12-Dux-ChIP-Seq(GSE87279)/Homer BCWGATTCAATCAAN 1e0 -0.000e+00 1.0000 0.0 0.00% 1.5 0.04% +ZNF16(Zf)/HEK293-ZNF16.GFP-ChIP-Seq(GSE58341)/Homer MACCTTCYATGGCTCCCTAKTGCCY 1e0 0.000e+00 1.0000 0.0 0.00% 0.0 0.00% +SeqBias: polyA-repeat AAAAAAAAAA 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +SeqBias: C/A-bias MMMMMMMMMM 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +SeqBias: polyC-repeat CCCCCCCCCC 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +SeqBias: G/A bias RRRRRRRRRR 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +SeqBias: GCW-triplet GCWGCWGCWGCW 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +SeqBias: A/T bias WWWWWWWWWW 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% + Ik-1 NHTTGGGAATRCC 1e0 0.000e+00 1.0000 4000.0 100.00% 3986.1 100.00% +AT4G12670(MYBrelated)/col-AT4G12670-DAP-Seq(GSE60143)/Homer AGGGTTTAGGGTTTA 1e0 0.000e+00 1.0000 0.0 0.00% 0.0 0.00% +REM16(ABI3VP1)/col-REM16-DAP-Seq(GSE60143)/Homer DTTTTTSCCGSMAAA 1e0 0.000e+00 1.0000 0.0 0.00% 0.0 0.00% diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.logo.svg b/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..52459bb73866153b9e27f97e211bd40a502b7205 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.logo.svg @@ -0,0 +1,64 @@ + + + C + G + T + A + + C + T + A + G + + T + C + A + G + + T + C + A + G + + A + G + T + C + + A + T + G + C + + A + G + T + C + + G + C + A + T + + A + G + C + T + + A + C + G + T + + A + T + C + G + + C + G + A + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.motif b/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.motif new file mode 100644 index 0000000000000000000000000000000000000000..df4eb3dff287750b65a8fccc0679da0001f07c5b --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known1.motif @@ -0,0 +1,13 @@ +>AGGVNCCTTTGT Sox9(HMG)/Limb-SOX9-ChIP-Seq(GSE73225)/Homer 7.192449 -511.135958 0 T:1770.0(44.25%),B:508.5(12.76%),P:1e-221 +0.565 0.002 0.193 0.240 +0.264 0.024 0.593 0.119 +0.317 0.146 0.478 0.059 +0.274 0.232 0.366 0.128 +0.150 0.299 0.267 0.284 +0.061 0.439 0.267 0.234 +0.001 0.821 0.015 0.163 +0.352 0.127 0.001 0.520 +0.001 0.123 0.090 0.786 +0.001 0.001 0.001 0.997 +0.006 0.079 0.903 0.012 +0.028 0.001 0.006 0.965 diff --git 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-91.616036 0 T:1131.0(28.27%),B:637.9(16.00%),P:1e-39 +0.160 0.403 0.162 0.274 +0.255 0.030 0.504 0.211 +0.158 0.001 0.772 0.069 +0.063 0.548 0.083 0.306 +0.032 0.816 0.001 0.151 +0.088 0.905 0.001 0.006 +0.001 0.985 0.001 0.013 +0.187 0.001 0.778 0.034 +0.001 0.997 0.001 0.001 +0.001 0.997 0.001 0.001 +0.001 0.851 0.001 0.147 +0.232 0.598 0.001 0.169 diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known11.logo.svg b/the_code/Human/data/homer/M15_vs_M0/knownResults/known11.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..53519f47d3f416b366cb365b2b8679cb7d124768 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known11.logo.svg @@ -0,0 +1,64 @@ + + + C + T + A + G + + T + C + A + G + + C + A + G + T + + T + C + A + G + + A + C + T + G + + A + C + T + G + + G + A + T + C + + C + T + A + G + + A + C + T + G + + C + T + A + G + + T + C + A + G + + A + T + G + C + + + diff --git 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+ T + C + G + + T + C + A + G + + G + C + T + A + + T + C + G + A + + T + C + A + G + + A + G + C + T + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known86.motif b/the_code/Human/data/homer/M15_vs_M0/knownResults/known86.motif new file mode 100644 index 0000000000000000000000000000000000000000..42424b83a027cd1b3e5113b5e573f075c5894b2d --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known86.motif @@ -0,0 +1,11 @@ +>ACVAGGAAGT ELF5(ETS)/T47D-ELF5-ChIP-Seq(GSE30407)/Homer 6.854302 -4.630009 0 T:539.0(13.48%),B:467.7(11.73%),P:1e-2 +0.891 0.009 0.005 0.095 +0.125 0.478 0.139 0.258 +0.270 0.345 0.376 0.008 +0.611 0.333 0.048 0.008 +0.006 0.021 0.967 0.006 +0.025 0.012 0.952 0.011 +0.974 0.010 0.005 0.011 +0.982 0.007 0.010 0.001 +0.082 0.025 0.889 0.004 +0.003 0.089 0.028 0.880 diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.logo.svg b/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.logo.svg new file mode 100644 index 0000000000000000000000000000000000000000..6b3e7106b7caf40cdb282952bb0c614010a6c4a3 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.logo.svg @@ -0,0 +1,64 @@ + + + C + T + G + A + + T + C + A + G + + C + A + G + T + + C + T + A + G + + A + C + T + G + + C + T + A + G + + G + A + T + C + + A + T + C + G + + A + C + T + G + + C + T + G + A + + T + C + A + G + + G + A + T + C + + + diff --git a/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.motif b/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.motif new file mode 100644 index 0000000000000000000000000000000000000000..738280ecba08fe3b617e930acc1500feb989ba59 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/knownResults/known9.motif @@ -0,0 +1,13 @@ +>RGKGGGCGGAGC Sp5(Zf)/mES-Sp5.Flag-ChIP-Seq(GSE72989)/Homer 6.519753 -128.011877 0 T:753.0(18.82%),B:284.7(7.14%),P:1e-55 +0.413 0.088 0.264 0.235 +0.110 0.106 0.774 0.010 +0.114 0.001 0.401 0.485 +0.134 0.001 0.864 0.001 +0.001 0.001 0.997 0.001 +0.003 0.001 0.995 0.001 +0.058 0.802 0.001 0.139 +0.001 0.003 0.995 0.001 +0.001 0.001 0.914 0.084 +0.665 0.004 0.315 0.016 +0.066 0.049 0.881 0.004 +0.127 0.702 0.006 0.165 diff --git a/the_code/Human/data/homer/M15_vs_M0/motifFindingParameters.txt b/the_code/Human/data/homer/M15_vs_M0/motifFindingParameters.txt new file mode 100644 index 0000000000000000000000000000000000000000..4312fb5f7614e9f9883c55794f186d5ab3db5a80 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/motifFindingParameters.txt @@ -0,0 +1 @@ +cmd = /staging/leuven/stg_00002/lcb/itask/files/EnhancerDesign/MM/evolution_from_scratch/fasta/MMEFS_M15.fa fasta ./ -fasta /staging/leuven/stg_00002/lcb/itask/files/EnhancerDesign/MM/evolution_from_scratch/fasta/MMEFS_M0.fa diff --git a/the_code/Human/data/homer/M15_vs_M0/seq.autonorm.tsv b/the_code/Human/data/homer/M15_vs_M0/seq.autonorm.tsv new file mode 100644 index 0000000000000000000000000000000000000000..8d7d66d721aa9d91ff553b4c3704eda61980b2e3 --- /dev/null +++ b/the_code/Human/data/homer/M15_vs_M0/seq.autonorm.tsv @@ -0,0 +1,85 @@ +Oligo TargetCounts BackgroundCounts NormalizationFactor +A 26.30% 26.36% 0.998 +C 23.70% 23.64% 1.003 +G 23.70% 23.64% 1.003 +T 26.30% 26.36% 0.998 +AA 7.01% 6.96% 1.006 +CA 6.25% 6.23% 1.004 +GA 6.20% 6.23% 0.996 +TA 6.83% 6.94% 0.985 +AC 6.21% 6.23% 0.996 +CC 5.62% 5.59% 1.004 +GC 5.68% 5.60% 1.016 +TC 6.20% 6.23% 0.996 +AG 6.16% 6.21% 0.992 +CG 5.68% 5.62% 1.011 +GG 5.62% 5.59% 1.004 +TG 6.25% 6.23% 1.004 +AT 6.92% 6.95% 0.995 +CT 6.16% 6.21% 0.992 +GT 6.21% 6.23% 0.996 +TT 7.01% 6.96% 1.006 +AAA 1.82% 1.85% 0.984 +CAA 1.75% 1.65% 1.064 +GAA 1.66% 1.64% 1.013 +TAA 1.78% 1.83% 0.971 +ACA 1.72% 1.63% 1.055 +CCA 1.46% 1.47% 0.989 +GCA 1.43% 1.47% 0.973 +TCA 1.64% 1.65% 0.994 +AGA 1.63% 1.63% 0.995 +CGA 1.46% 1.48% 0.987 +GGA 1.48% 1.47% 1.008 +TGA 1.64% 1.65% 0.994 +ATA 1.81% 1.84% 0.983 +CTA 1.61% 1.63% 0.993 +GTA 1.63% 1.64% 0.994 +TTA 1.78% 1.83% 0.971 +AAC 1.67% 1.64% 1.013 +CAC 1.43% 1.47% 0.974 +GAC 1.48% 1.48% 1.001 +TAC 1.63% 1.64% 0.994 +ACC 1.40% 1.47% 0.955 +CCC 1.34% 1.33% 1.006 +GCC 1.40% 1.33% 1.052 +TCC 1.48% 1.47% 1.008 +AGC 1.47% 1.46% 1.004 +CGC 1.38% 1.33% 1.040 +GGC 1.40% 1.33% 1.052 +TGC 1.43% 1.47% 0.973 +ATC 1.61% 1.64% 0.983 +CTC 1.45% 1.47% 0.987 +GTC 1.48% 1.48% 1.001 +TTC 1.66% 1.64% 1.013 +AAG 1.67% 1.64% 1.019 +CAG 1.43% 1.48% 0.968 +GAG 1.45% 1.47% 0.987 +TAG 1.61% 1.63% 0.993 +ACG 1.48% 1.48% 1.000 +CCG 1.36% 1.33% 1.019 +GCG 1.38% 1.33% 1.040 +TCG 1.46% 1.48% 0.987 +AGG 1.47% 1.46% 1.003 +CGG 1.36% 1.33% 1.019 +GGG 1.34% 1.33% 1.006 +TGG 1.46% 1.47% 0.989 +ATG 1.64% 1.64% 1.003 +CTG 1.43% 1.48% 0.968 +GTG 1.43% 1.47% 0.974 +TTG 1.75% 1.65% 1.064 +AAT 1.85% 1.83% 1.012 +CAT 1.64% 1.64% 1.003 +GAT 1.61% 1.64% 0.983 +TAT 1.81% 1.84% 0.983 +ACT 1.60% 1.65% 0.970 +CCT 1.47% 1.46% 1.003 +GCT 1.47% 1.46% 1.004 +TCT 1.63% 1.63% 0.995 +AGT 1.60% 1.65% 0.970 +CGT 1.48% 1.48% 1.000 +GGT 1.40% 1.47% 0.955 +TGT 1.72% 1.63% 1.055 +ATT 1.85% 1.83% 1.012 +CTT 1.67% 1.64% 1.019 +GTT 1.67% 1.64% 1.013 +TTT 1.82% 1.85% 0.984 diff --git a/the_code/Human/data/irf4/GRCh37_IRF4.tsv b/the_code/Human/data/irf4/GRCh37_IRF4.tsv new file mode 100644 index 0000000000000000000000000000000000000000..7b76bfdd9788a909649be871dedad88bdadaae33 --- /dev/null +++ b/the_code/Human/data/irf4/GRCh37_IRF4.tsv @@ -0,0 +1,1510 @@ +6 396143 G - 34 4909 3770 -0.12 0.45796 IRF4 +6 396143 G A 608 60327 42920 -0.09 0.02007 IRF4 +6 396143 G C 392 34986 24767 -0.16 0.00079 IRF4 +6 396143 G T 259 21168 19223 0.17 0.00349 IRF4 +6 396144 G - 52 7529 5815 0.34 0.00747 IRF4 +6 396144 G A 712 63554 62584 0.38 0 IRF4 +6 396144 G C 428 44059 29015 -0.13 0.00314 IRF4 +6 396144 G T 418 42876 32336 -0.01 0.86259 IRF4 +6 396145 C - 3 374 393 0.52 0.33313 IRF4 +6 396145 C A 539 56326 36203 -0.12 0.00334 IRF4 +6 396145 C G 187 18104 14235 0.08 0.23636 IRF4 +6 396145 C T 3212 330489 233836 -0.17 0 IRF4 +6 396146 G A 1713 167700 125423 -0.01 0.61459 IRF4 +6 396146 G C 336 33187 28414 0.09 0.06541 IRF4 +6 396146 G T 249 23381 16216 -0.08 0.14885 IRF4 +6 396147 T A 161 17340 12521 -0.22 0.00204 IRF4 +6 396147 T C 507 50436 37454 -0.18 2e-05 IRF4 +6 396147 T G 66 6437 4631 -0.05 0.67284 IRF4 +6 396148 G A 890 96280 77840 0.07 0.01745 IRF4 +6 396148 G C 452 47679 36918 0.02 0.58048 IRF4 +6 396148 G T 81 6949 5655 0 0.96222 IRF4 +6 396149 T - 6 1017 1537 0.42 0.26442 IRF4 +6 396149 T A 274 24805 28041 0.4 0 IRF4 +6 396149 T C 419 44057 31466 -0.13 0.00542 IRF4 +6 396149 T G 30 3253 2491 0.01 0.95604 IRF4 +6 396150 C - 618 66895 49729 -0.07 0.04656 IRF4 +6 396150 C A 103 9339 7725 0.09 0.34991 IRF4 +6 396150 C G 53 6462 4116 -0.39 0.00199 IRF4 +6 396150 C T 774 81014 63459 0.01 0.69868 IRF4 +6 396151 C A 612 63933 62161 0.38 0 IRF4 +6 396151 C G 82 7148 5569 0.11 0.28828 IRF4 +6 396151 C T 1542 160687 138837 0.18 0 IRF4 +6 396152 G - 2 81 19 0.43 0.51208 IRF4 +6 396152 G A 1017 102778 40365 -1.01 0 IRF4 +6 396152 G C 351 33287 28937 0.19 1e-04 IRF4 +6 396152 G T 356 35270 26205 0.07 0.13417 IRF4 +6 396153 C - 797 86475 60295 -0.14 1e-05 IRF4 +6 396153 C A 296 31193 24571 -0.04 0.48094 IRF4 +6 396153 C G 139 11529 9042 0.06 0.47587 IRF4 +6 396153 C T 1515 157589 116231 -0.05 0.05354 IRF4 +6 396154 C A 1580 158881 97393 -0.27 0 IRF4 +6 396154 C G 119 11112 6441 -0.33 0.00011 IRF4 +6 396154 C T 1268 134740 116047 0.14 0 IRF4 +6 396155 T A 592 64746 54513 0.03 0.47959 IRF4 +6 396155 T C 755 77880 55998 0.04 0.26097 IRF4 +6 396155 T G 248 24896 17086 -0.06 0.31138 IRF4 +6 396156 G A 984 104179 88290 0.07 0.01387 IRF4 +6 396156 G C 546 52272 41288 0.05 0.24333 IRF4 +6 396156 G T 250 23601 18974 0.06 0.33916 IRF4 +6 396157 T - 1080 108541 78148 -0.09 0.00117 IRF4 +6 396157 T A 664 69942 53628 0 0.94934 IRF4 +6 396157 T C 669 74417 57844 -0.03 0.42332 IRF4 +6 396157 T G 259 24740 18293 -0.03 0.59465 IRF4 +6 396158 T A 232 21129 15292 0.12 0.05408 IRF4 +6 396158 T C 552 57282 42327 -0.02 0.54304 IRF4 +6 396158 T G 808 83712 67197 0.08 0.01669 IRF4 +6 396159 G - 212 21821 15763 -0.13 0.04501 IRF4 +6 396159 G A 739 85719 69546 0.11 0.00187 IRF4 +6 396159 G C 255 30634 23219 -0.02 0.75461 IRF4 +6 396159 G T 282 28831 25080 0.24 1e-05 IRF4 +6 396160 G A 1148 112845 96486 0.26 0 IRF4 +6 396160 G C 1228 126931 106638 0.17 0 IRF4 +6 396160 G T 546 57130 47428 0.15 1e-04 IRF4 +6 396161 A - 364 38754 29288 -0.04 0.45102 IRF4 +6 396161 A C 100499 10076748 6110374 -0.39 0 IRF4 +6 396161 A G 3617 375137 273482 -0.1 0 IRF4 +6 396161 A T 1062 112820 92972 0.01 0.84133 IRF4 +6 396162 A C 1024 99912 81029 0.33 0 IRF4 +6 396162 A G 2057 220064 161706 0.02 0.38769 IRF4 +6 396162 A T 1663 176731 141552 0.05 0.03508 IRF4 +6 396163 T A 646 67778 58561 0.19 0 IRF4 +6 396163 T C 1057 120717 83149 -0.11 0.00013 IRF4 +6 396163 T G 72 8031 5640 -0.13 0.23969 IRF4 +6 396164 A C 83 8600 6902 0.09 0.34986 IRF4 +6 396164 A G 1106 113471 90597 0 0.94672 IRF4 +6 396164 A T 582 64733 58109 0.31 0 IRF4 +6 396165 T A 1150 116983 85142 0.09 0.00089 IRF4 +6 396165 T C 1825 182172 129366 -0.05 0.02586 IRF4 +6 396165 T G 170 17103 14176 0.06 0.36997 IRF4 +6 396166 G A 1538 159314 127498 0.12 0 IRF4 +6 396166 G C 284 30805 22924 0.11 0.0471 IRF4 +6 396166 G T 189 19620 16014 0.19 0.00592 IRF4 +6 396167 C A 615 66725 55160 0.2 0 IRF4 +6 396167 C G 305 31639 23232 0.09 0.07756 IRF4 +6 396167 C T 1674 166933 139662 0.1 1e-05 IRF4 +6 396168 T - 26 2440 2062 0.06 0.75375 IRF4 +6 396168 T A 956 98385 78424 -0.03 0.39393 IRF4 +6 396168 T C 1892 199520 158788 0.15 0 IRF4 +6 396168 T G 319 35337 28434 0.08 0.13839 IRF4 +6 396169 T A 878 98071 80767 0.12 8e-05 IRF4 +6 396169 T C 2170 222568 177187 0.09 0 IRF4 +6 396169 T G 209 21760 19742 0.11 0.09268 IRF4 +6 396170 C A 837 91474 86463 0.31 0 IRF4 +6 396170 C G 62 5494 4924 0.42 0.00037 IRF4 +6 396170 C T 568 61422 36471 -0.34 0 IRF4 +6 396171 T A 685 74497 52333 -0.08 0.02457 IRF4 +6 396171 T C 1689 161752 128864 0.12 0 IRF4 +6 396171 T G 146 14544 10066 -0.3 0.00011 IRF4 +6 396172 C A 212 23151 19646 0.07 0.27293 IRF4 +6 396172 C G 35 4230 4351 0.25 0.1145 IRF4 +6 396172 C T 820 86010 67337 0.2 0 IRF4 +6 396173 A C 273 27050 23864 0.12 0.02905 IRF4 +6 396173 A G 1767 181797 137242 0.04 0.07549 IRF4 +6 396173 A T 1369 147699 121991 0.15 0 IRF4 +6 396174 G - 110 12830 9599 0.06 0.48887 IRF4 +6 396174 G A 1078 112889 92850 0.18 0 IRF4 +6 396174 G C 255 27639 21148 0.13 0.02121 IRF4 +6 396174 G T 1360 133615 117115 0.29 0 IRF4 +6 396175 G A 1376 137993 112296 0.16 0 IRF4 +6 396175 G C 348 31532 26709 0.21 2e-05 IRF4 +6 396175 G T 265 24164 20575 0.17 0.00246 IRF4 +6 396176 T A 629 61875 48972 0.13 0.00031 IRF4 +6 396176 T C 1924 205626 173329 0.26 0 IRF4 +6 396176 T G 158 16465 14172 0.15 0.0372 IRF4 +6 396177 C A 489 45840 24264 -0.63 0 IRF4 +6 396177 C G 36 3955 969 -1.38 0 IRF4 +6 396177 C T 837 86688 60354 -0.12 0.00013 IRF4 +6 396178 T - 32 2499 2294 -0.01 0.96441 IRF4 +6 396178 T A 1093 103341 106261 0.51 0 IRF4 +6 396178 T C 2073 216162 181567 0.15 0 IRF4 +6 396178 T G 441 43594 38797 0.26 0 IRF4 +6 396179 T A 625 66100 47517 -0.08 0.04093 IRF4 +6 396179 T C 1878 186587 225628 0.7 0 IRF4 +6 396179 T G 179 18565 15198 0.03 0.67191 IRF4 +6 396180 C A 1247 127020 114995 0.26 0 IRF4 +6 396180 C G 80 9873 9697 0.27 0.00949 IRF4 +6 396180 C T 865 91079 71862 0 0.90881 IRF4 +6 396181 T - 3 194 109 1.01 0.05963 IRF4 +6 396181 T A 1061 114612 81533 -0.03 0.26382 IRF4 +6 396181 T C 1702 169506 65649 -0.98 0 IRF4 +6 396181 T G 282 30753 18430 -0.33 0 IRF4 +6 396182 G - 683 72658 49406 -0.29 0 IRF4 +6 396182 G A 807 89808 22171 -1.61 0 IRF4 +6 396182 G C 174 17649 12619 -0.08 0.26646 IRF4 +6 396182 G T 153 14840 8223 -0.23 0.00254 IRF4 +6 396183 G A 779 74823 66622 0.2 0 IRF4 +6 396183 G C 160 15755 10954 -0.08 0.28618 IRF4 +6 396183 G T 533 50783 45715 0.32 0 IRF4 +6 396184 G A 614 63802 47162 0.02 0.57589 IRF4 +6 396184 G C 108 11650 9552 0.14 0.10455 IRF4 +6 396184 G T 353 36739 34552 0.24 0 IRF4 +6 396185 A - 235 22345 16775 0.09 0.15422 IRF4 +6 396185 A C 183 17096 11997 0.06 0.35015 IRF4 +6 396185 A G 2305 246645 189271 0.04 0.02984 IRF4 +6 396185 A T 1111 120363 95929 0.11 0.00014 IRF4 +6 396186 A C 149 15623 14545 0.2 0.00998 IRF4 +6 396186 A G 2590 267185 201659 0.03 0.08925 IRF4 +6 396186 A T 708 74059 47234 -0.24 0 IRF4 +6 396187 A C 612 60845 44364 -0.12 0.00181 IRF4 +6 396187 A G 2647 257556 205256 0.07 6e-05 IRF4 +6 396187 A T 742 77467 89806 0.75 0 IRF4 +6 396188 C A 137 14658 12061 0.18 0.0238 IRF4 +6 396188 C G 181 18967 16429 0.14 0.04336 IRF4 +6 396188 C T 1148 115142 95954 0.19 0 IRF4 +6 396189 A C 394 41355 32493 0.05 0.32107 IRF4 +6 396189 A G 2138 226078 265065 0.72 0 IRF4 +6 396189 A T 1490 151213 125100 0.14 0 IRF4 +6 396190 G A 941 97844 73227 0.06 0.06113 IRF4 +6 396190 G C 168 16599 15200 0.25 0.00047 IRF4 +6 396190 G T 963 85518 66052 0.05 0.07009 IRF4 +6 396191 A C 147 15699 11579 0.22 0.00429 IRF4 +6 396191 A G 1318 150332 24046 -2.35 0 IRF4 +6 396191 A T 651 65035 57639 0.21 0 IRF4 +6 396192 T A 1011 94677 80153 0.2 0 IRF4 +6 396192 T C 1632 163698 139231 0.2 0 IRF4 +6 396192 T G 153 14696 12522 0.26 0.00049 IRF4 +6 396193 G A 654 63889 52820 0.21 0 IRF4 +6 396193 G C 107 10688 7551 -0.29 0.00141 IRF4 +6 396193 G T 74 8280 6164 0.12 0.26542 IRF4 +6 396194 T - 812 80084 58094 0.05 0.09397 IRF4 +6 396194 T A 1193 115799 116485 0.4 0 IRF4 +6 396194 T C 2017 201373 170340 0.15 0 IRF4 +6 396194 T G 476 42612 36554 0.2 0 IRF4 +6 396195 T A 771 78624 62502 0.01 0.78384 IRF4 +6 396195 T C 1672 158787 136260 0.23 0 IRF4 +6 396195 T G 414 39221 29189 -0.07 0.1327 IRF4 +6 396196 T A 1734 156405 138643 0.23 0 IRF4 +6 396196 T C 1988 198004 147649 0.02 0.39639 IRF4 +6 396196 T G 522 49188 42247 0.1 0.01664 IRF4 +6 396197 T A 1151 114191 86957 0.06 0.02889 IRF4 +6 396197 T C 2326 227020 151057 -0.18 0 IRF4 +6 396197 T G 229 22393 17325 0.14 0.02412 IRF4 +6 396198 G A 1636 163574 127799 0.05 0.04404 IRF4 +6 396198 G C 446 44175 30036 0.02 0.61304 IRF4 +6 396198 G T 232 24919 19095 0.09 0.13395 IRF4 +6 396199 T A 992 104376 101568 0.31 0 IRF4 +6 396199 T C 1725 161029 186631 0.64 0 IRF4 +6 396199 T G 192 17705 15393 0.2 0.00222 IRF4 +6 396200 G - 751 75040 55478 -0.02 0.6299 IRF4 +6 396200 G A 707 69441 53118 -0.05 0.1719 IRF4 +6 396200 G C 92 8149 5049 -0.31 0.00136 IRF4 +6 396200 G T 247 24407 20759 0.32 0 IRF4 +6 396201 G A 820 82551 62935 -0.01 0.74635 IRF4 +6 396201 G C 90 8394 7784 0.3 0.00209 IRF4 +6 396201 G T 581 59003 53565 0.29 0 IRF4 +6 396202 A - 100 12443 9722 0.19 0.0443 IRF4 +6 396202 A C 161 14353 10450 0.05 0.47214 IRF4 +6 396202 A G 2554 275566 244382 0.3 0 IRF4 +6 396202 A T 1344 127276 111152 0.22 0 IRF4 +6 396203 A C 285 28837 22127 -0.11 0.04162 IRF4 +6 396203 A G 2399 251997 199436 0.02 0.22299 IRF4 +6 396203 A T 1134 115240 84871 -0.1 0.00014 IRF4 +6 396204 G A 1782 180828 129669 -0.06 0.00593 IRF4 +6 396204 G C 474 43148 26011 -0.38 0 IRF4 +6 396204 G T 432 41919 27056 -0.26 0 IRF4 +6 396205 T A 1173 128375 79111 -0.25 0 IRF4 +6 396205 T C 1524 156237 131586 0.12 0 IRF4 +6 396205 T G 274 28668 17841 -0.23 5e-05 IRF4 +6 396206 G - 734 72402 40197 -0.44 0 IRF4 +6 396206 G A 849 88970 49709 -0.51 0 IRF4 +6 396206 G C 199 19397 9763 -0.7 0 IRF4 +6 396206 G T 376 38094 20915 -0.4 0 IRF4 +6 396207 G A 829 86797 58008 -0.23 0 IRF4 +6 396207 G C 198 22329 13587 -0.45 0 IRF4 +6 396207 G T 422 42640 25814 -0.43 0 IRF4 +6 396208 A - 56 6086 3951 -0.34 0.00563 IRF4 +6 396208 A C 114 10240 6112 -0.41 0 IRF4 +6 396208 A G 2491 258277 181797 -0.13 0 IRF4 +6 396208 A T 900 97456 69245 -0.11 0.00048 IRF4 +6 396209 A C 225 25667 16764 -0.22 0.00029 IRF4 +6 396209 A G 2620 272379 183912 -0.18 0 IRF4 +6 396209 A T 809 84851 63215 -0.04 0.2554 IRF4 +6 396210 G A 553 54365 59095 0.56 0 IRF4 +6 396210 G C 38 3062 1731 -0.1 0.48604 IRF4 +6 396210 G T 557 55681 53619 0.41 0 IRF4 +6 396211 A - 1 1 1 -0.06 0.9496 IRF4 +6 396211 A C 88 8871 6500 -0.16 0.10316 IRF4 +6 396211 A G 1609 168412 112375 -0.17 0 IRF4 +6 396211 A T 592 62550 47162 -0.06 0.1014 IRF4 +6 396212 T - 1208 132748 90327 -0.1 2e-04 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268141 187500 -0.13 0 IRF4 +6 396218 A T 1253 124602 80569 -0.24 0 IRF4 +6 396219 A C 333 33105 25435 0.19 0.00018 IRF4 +6 396219 A G 2379 246131 136511 -0.47 0 IRF4 +6 396219 A T 1222 127999 87648 -0.1 0.00025 IRF4 +6 396220 G A 1268 129058 92505 -0.1 0.00012 IRF4 +6 396220 G C 334 32886 28444 0.05 0.30046 IRF4 +6 396220 G T 630 69014 92028 0.87 0 IRF4 +6 396221 T A 1012 111248 72974 -0.17 0 IRF4 +6 396221 T C 1260 127346 107398 0.16 0 IRF4 +6 396221 T G 125 12971 9737 0.08 0.34704 IRF4 +6 396222 A - 3 42 43 0.35 0.50539 IRF4 +6 396222 A C 204 19991 18547 0.28 2e-05 IRF4 +6 396222 A G 1336 147308 123979 0.23 0 IRF4 +6 396222 A T 975 100097 81966 0.18 0 IRF4 +6 396223 G A 1482 150872 112137 -0.02 0.34904 IRF4 +6 396223 G C 268 26139 17751 -0.08 0.14183 IRF4 +6 396223 G T 629 61763 42946 -0.23 0 IRF4 +6 396224 T A 1359 142459 100863 -0.05 0.07072 IRF4 +6 396224 T C 1872 190844 124249 -0.13 0 IRF4 +6 396224 T G 419 43580 32042 -0.08 0.08256 IRF4 +6 396225 G A 1530 159609 81913 -0.63 0 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396232 C - 3 207 78 1.43 0.00781 IRF4 +6 396232 C A 171 18356 3867 -2.08 0 IRF4 +6 396232 C G 82 8765 6459 0.02 0.85148 IRF4 +6 396232 C T 769 79497 13964 -2.21 0 IRF4 +6 396233 A C 177 23717 4094 -2.19 0 IRF4 +6 396233 A G 1626 182482 31796 -2.14 0 IRF4 +6 396233 A T 1399 144615 30628 -1.84 0 IRF4 +6 396234 T A 812 96162 20217 -1.99 0 IRF4 +6 396234 T C 1999 211988 118408 -0.45 0 IRF4 +6 396234 T G 153 17723 2226 -2.49 0 IRF4 +6 396235 G A 1404 148466 51503 -1.23 0 IRF4 +6 396235 G C 334 34607 10049 -1.51 0 IRF4 +6 396235 G T 161 16908 4087 -2.03 0 IRF4 +6 396236 T A 1460 158621 45994 -1.32 0 IRF4 +6 396236 T C 2008 206722 102840 -0.64 0 IRF4 +6 396236 T G 311 37148 10052 -1.62 0 IRF4 +6 396237 G A 701 74264 16595 -1.72 0 IRF4 +6 396237 G C 35 3937 696 -1.93 0 IRF4 +6 396237 G T 197 24518 4764 -2.16 0 IRF4 +6 396238 A - 221 24742 7559 -1.23 0 IRF4 +6 396238 A C 177 17334 4766 -1.42 0 IRF4 +6 396238 A G 2399 250394 58568 -1.86 0 IRF4 +6 396238 A T 997 96744 31137 -1.4 0 IRF4 +6 396239 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396260 T C 2562 231600 230676 0.44 0 IRF4 +6 396260 T G 419 40381 42958 0.46 0 IRF4 +6 396261 T A 909 100485 64996 -0.22 0 IRF4 +6 396261 T C 2044 203627 158087 0.06 0.00279 IRF4 +6 396261 T G 188 19350 13194 -0.02 0.7758 IRF4 +6 396262 C - 5 1189 728 0.08 0.8407 IRF4 +6 396262 C A 217 25217 19612 0 0.9739 IRF4 +6 396262 C G 88 8912 8421 0.35 0.00038 IRF4 +6 396262 C T 958 93602 61184 -0.16 0 IRF4 +6 396263 A C 353 33914 44313 0.76 0 IRF4 +6 396263 A G 2338 243858 180033 -0.05 0.00771 IRF4 +6 396263 A T 1281 127323 99284 0.04 0.13858 IRF4 +6 396264 G - 71 8225 3849 -0.8 0 IRF4 +6 396264 G A 937 85764 58435 -0.18 0 IRF4 +6 396264 G C 147 13790 8632 -0.07 0.39284 IRF4 +6 396264 G T 986 101734 100537 0.34 0 IRF4 +6 396265 G A 1288 128181 96302 -0.01 0.80496 IRF4 +6 396265 G C 148 15795 11660 -0.08 0.27682 IRF4 +6 396265 G T 454 45697 29569 -0.19 1e-05 IRF4 +6 396266 C - 3 629 115 -1.46 0.00621 IRF4 +6 396266 C A 415 42906 26517 -0.42 0 IRF4 +6 396266 C G 172 17019 13040 0.04 0.60181 IRF4 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0.00683 IRF4 +6 396273 G C 232 23722 12430 -0.54 0 IRF4 +6 396273 G T 311 28241 23176 0.15 0.00556 IRF4 +6 396274 A C 157 15838 13097 0.12 0.10363 IRF4 +6 396274 A G 2238 231803 170333 -0.09 1e-05 IRF4 +6 396274 A T 1465 153582 129614 0.13 0 IRF4 +6 396275 T A 976 94152 67904 0 0.93834 IRF4 +6 396275 T C 2024 216170 137053 -0.21 0 IRF4 +6 396275 T G 282 30057 15530 -0.73 0 IRF4 +6 396276 G A 1334 131203 121651 0.37 0 IRF4 +6 396276 G C 382 38036 31477 0.16 0.00101 IRF4 +6 396276 G T 160 14655 10471 -0.39 0 IRF4 +6 396277 T A 1596 158494 79052 -0.7 0 IRF4 +6 396277 T C 1710 188740 35464 -2.18 0 IRF4 +6 396277 T G 285 35885 3334 -3.14 0 IRF4 +6 396278 G A 1056 104586 53205 -0.64 0 IRF4 +6 396278 G C 180 19458 15255 -0.07 0.33948 IRF4 +6 396278 G T 426 45209 16607 -1.13 0 IRF4 +6 396279 A - 140 18827 1993 -3.11 0 IRF4 +6 396279 A C 132 13746 1234 -2.79 0 IRF4 +6 396279 A G 1570 194237 19287 -3 0 IRF4 +6 396279 A T 941 97909 20857 -1.93 0 IRF4 +6 396280 A C 239 24760 4637 -2.26 0 IRF4 +6 396280 A G 1809 210079 26119 -2.68 0 IRF4 +6 396280 A T 270 32908 2443 -3.33 0 IRF4 +6 396281 T A 1496 153261 127713 0.11 0 IRF4 +6 396281 T C 1505 157615 59872 -1.06 0 IRF4 +6 396281 T G 173 17825 6670 -0.91 0 IRF4 +6 396282 G A 980 103459 80910 0.09 0.00216 IRF4 +6 396282 G C 67 5731 3113 -0.44 1e-04 IRF4 +6 396282 G T 185 19096 10044 -0.42 0 IRF4 +6 396283 A C 397 39648 30181 -0.08 0.07273 IRF4 +6 396283 A G 2445 239051 213238 0.32 0 IRF4 +6 396283 A T 1132 134344 90778 -0.17 0 IRF4 +6 396284 C - 3 61 33 -1.79 8e-04 IRF4 +6 396284 C A 92 9195 11316 0.48 0 IRF4 +6 396284 C G 413 46252 46878 0.38 0 IRF4 +6 396284 C T 1548 169550 131392 0.08 0.00141 IRF4 +6 396285 A C 336 31143 28438 0.4 0 IRF4 +6 396285 A G 2545 265402 226476 0.28 0 IRF4 +6 396285 A T 1077 112231 108937 0.43 0 IRF4 +6 396286 G A 1668 171637 85661 -0.65 0 IRF4 +6 396286 G C 317 35756 26649 -0.01 0.80351 IRF4 +6 396286 G T 749 71863 67315 0.25 0 IRF4 +6 396287 C - 10 1642 150 -3.56 0 IRF4 +6 396287 C A 753 74240 22398 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0.39776 IRF4 +6 396306 G T 319 28862 23757 0.17 0.00112 IRF4 +6 396307 T A 1101 114447 86967 0.09 0.00097 IRF4 +6 396307 T C 1549 163821 82173 -0.59 0 IRF4 +6 396307 T G 503 56109 45329 0.13 0.00136 IRF4 +6 396308 G - 757 85371 77811 0.36 0 IRF4 +6 396308 G A 1064 112901 40858 -1.01 0 IRF4 +6 396308 G C 284 30824 22671 -0.05 0.36588 IRF4 +6 396308 G T 378 37508 28633 0.11 0.02717 IRF4 +6 396309 G A 1581 150736 167234 0.58 0 IRF4 +6 396309 G C 343 34808 35062 0.31 0 IRF4 +6 396309 G T 886 95596 77690 0.17 0 IRF4 +6 396310 G A 1581 149311 138499 0.38 0 IRF4 +6 396310 G C 491 55335 43458 0.06 0.17717 IRF4 +6 396310 G T 175 21981 21012 0.47 0 IRF4 +6 396311 T - 3 563 324 -0.07 0.8998 IRF4 +6 396311 T A 830 85342 44012 -0.52 0 IRF4 +6 396311 T C 1089 117959 68289 -0.42 0 IRF4 +6 396311 T G 187 22324 14969 0.03 0.64399 IRF4 +6 396312 A - 1721 185892 176082 0.35 0 IRF4 +6 396312 A C 122 13423 14372 0.37 1e-05 IRF4 +6 396312 A G 1799 177296 171593 0.41 0 IRF4 +6 396312 A T 749 81857 72487 0.18 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3e-05 IRF4 +6 396485 T C 2272 228094 172919 -0.02 0.32451 IRF4 +6 396485 T G 264 27203 28412 0.4 0 IRF4 +6 396486 G A 1345 131320 97615 0.03 0.19467 IRF4 +6 396486 G C 410 34968 28473 0.07 0.1261 IRF4 +6 396486 G T 93 7975 8023 0.26 0.00679 IRF4 +6 396487 T A 1168 119199 100306 0.07 0.01235 IRF4 +6 396487 T C 1881 184067 151741 0.12 0 IRF4 +6 396487 T G 351 33076 22983 0.04 0.40426 IRF4 +6 396488 C - 3 189 146 -0.01 0.9893 IRF4 +6 396488 C A 181 19469 15209 0.13 0.06672 IRF4 +6 396488 C G 87 7856 7401 0.4 6e-05 IRF4 +6 396488 C T 1077 113453 107806 0.35 0 IRF4 +6 396489 A C 291 29251 22767 -0.06 0.2484 IRF4 +6 396489 A G 2403 255525 184577 -0.04 0.04457 IRF4 +6 396489 A T 1795 191574 153404 0.15 0 IRF4 +6 396490 G A 1436 150861 93744 -0.3 0 IRF4 +6 396490 G C 532 56744 37912 -0.13 0.00095 IRF4 +6 396490 G T 423 44891 30762 -0.05 0.29415 IRF4 +6 396491 T A 1144 122176 96737 0.14 0 IRF4 +6 396491 T C 1933 192430 179326 0.31 0 IRF4 +6 396491 T G 295 32415 25402 0.16 0.00247 IRF4 +6 396492 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--git a/the_code/Human/data/luciferase/EFS1_repressors.txt b/the_code/Human/data/luciferase/EFS1_repressors.txt new file mode 100644 index 0000000000000000000000000000000000000000..57472281f7b7477a55f92f4d1f9819379e02578e --- /dev/null +++ b/the_code/Human/data/luciferase/EFS1_repressors.txt @@ -0,0 +1,5 @@ +No_Repressor 42.37 56.79 40.11 +312G 58.46 63.22 37.72 +338C_339A 2.27 1.51 2.44 +365C_369T 44.72 50.00 30.88 +9_repressors 0.87 0.92 0.85 diff --git a/the_code/Human/data/luciferase/EFS1_steps.txt b/the_code/Human/data/luciferase/EFS1_steps.txt new file mode 100644 index 0000000000000000000000000000000000000000..b5ffe81e24a69bd573e61d3432010692b6b0ec5d --- /dev/null +++ b/the_code/Human/data/luciferase/EFS1_steps.txt @@ -0,0 +1,8 @@ +Mut-0 0.820187059 1.037598269 0.804012121 +Mut-1 0.684918483 1.067014208 0.693857835 +Mut-2 0.743464523 0.994484098 0.752360591 +Mut-5 0.87278354 1.153311815 0.952494899 +Mut-11 5.986208749 6.346623579 4.225500383 +Mut-12 4.87835354 6.654652737 4.709435639 +Mut-15 8.375062168 11.05385578 7.354815959 +Mut-15_Repr 0.727608717 0.980276068 0.766542455 diff --git a/the_code/Human/data/luciferase/EFS4_repressors.txt b/the_code/Human/data/luciferase/EFS4_repressors.txt new file mode 100644 index 0000000000000000000000000000000000000000..473f67c9fa65ebd5104b4d2d663564dd34ecb8bf --- /dev/null +++ b/the_code/Human/data/luciferase/EFS4_repressors.txt @@ -0,0 +1,12 @@ +No_Repressor 51.45 68.18 62.42 +113A 67.51 66.59 41.19 +164A 33.24 30.15 25.96 +210C 18.11 16.68 14.06 +216A 61.42 66.66 46.31 +215C_216A 40.17 46.29 40.03 +259G 14.23 9.69 10.86 +300T 32.76 37.20 30.76 +113A_164A 22.02 17.98 18.24 +113A_164A_210C 5.32 3.75 5.35 +113A_164A_210C_215C_216A 5.07 3.09 3.82 +113A_164A_210C_215C_216A_259G 1.41 1.38 1.35 diff --git a/the_code/Human/data/luciferase/EFS4_steps.txt b/the_code/Human/data/luciferase/EFS4_steps.txt new file mode 100644 index 0000000000000000000000000000000000000000..eff4321fa4125f82c58d5e7c9f2a71494920aff0 --- /dev/null +++ b/the_code/Human/data/luciferase/EFS4_steps.txt @@ -0,0 +1,8 @@ +Mut-0 0.874976474 1.182528286 0.846231715 +Mut-3 0.811199756 1.258049582 0.810866006 +Mut-4 0.949660847 1.347005002 1.013167839 +Mut-7 1.061614597 1.447136874 1.677659475 +Mut-8 1.856042861 2.212433284 2.350466665 +Mut-12 7.05733762 11.96334071 18.33612303 +Mut-15 16.96133354 18.99615911 28.6640379 +Mut-15_Repr 0.847878573 1.066388707 0.959500557 diff --git a/the_code/Human/data/luciferase/EFS8_repressors.txt b/the_code/Human/data/luciferase/EFS8_repressors.txt new file mode 100644 index 0000000000000000000000000000000000000000..7949aa4379a66d64372dbcdf95a3f843ccdc8eca --- /dev/null +++ b/the_code/Human/data/luciferase/EFS8_repressors.txt @@ -0,0 +1,5 @@ +No_Repressor 14.82 16.44 15.61 +184A 11.96 17.82 12.93 +184A_204T 10.14 9.27 9.92 +184A_204T_350C 6.66 6.74 7.13 +6_Repressors 0.78 0.76 0.77 diff --git a/the_code/Human/data/luciferase/EFS8_steps.txt b/the_code/Human/data/luciferase/EFS8_steps.txt new file mode 100644 index 0000000000000000000000000000000000000000..3b18256c2d6322cf09011c76263c8a72d99077d0 --- /dev/null +++ b/the_code/Human/data/luciferase/EFS8_steps.txt @@ -0,0 +1,10 @@ +Mut-0 0.803902262 0.964649584 0.878899462 +Mut-2 0.836664195 1.061538669 0.909332734 +Mut-7 3.782212988 3.419871087 1.906403063 +Mut-8 4.374756952 5.473840147 2.673457347 +Mut-9 4.627248154 4.991613407 2.053854499 +Mut-12 5.447537054 6.384976409 3.382273886 +Mut-13 4.32688307 5.649869409 5.317112298 +Mut-14 5.884621422 7.87163345 3.195820044 +Mut-15 5.748828336 8.103342557 11.76246363 +Mut-15_Repr 0.779400388 1.130507321 0.783376875 \ No newline at end of file diff --git a/the_code/Human/data/luciferase/EFSall_IRF4_TYR_MLANA.txt b/the_code/Human/data/luciferase/EFSall_IRF4_TYR_MLANA.txt new file mode 100644 index 0000000000000000000000000000000000000000..64c6fd0183f24719e900e46f36cbe6f06d5fa852 --- /dev/null +++ b/the_code/Human/data/luciferase/EFSall_IRF4_TYR_MLANA.txt @@ -0,0 +1,13 @@ +EFS-1 15.16 29.23 26.89 +EFS-2 4.56 9.33 30.20 +EFS-3 1.01 1.24 1.60 +EFS-4 23.06 24.48 33.96 +EFS-5 7.17 11.93 6.22 +EFS-6 1.44 1.70 1.83 +EFS-7 0.84 1.13 1.31 +EFS-8 11.77 18.55 8.59 +EFS-9 6.95 8.46 3.04 +EFS-10 4.47 6.74 4.67 +MLANA 124.9289666 59.56148702 37.85492237 +TYR 14.37348766 4.056166795 3.081931338 +IRF4 4.97563967 1.343298843 1.208126751 diff --git a/the_code/Human/data/luciferase/GANall_IRF4_TYR_MLANA.txt b/the_code/Human/data/luciferase/GANall_IRF4_TYR_MLANA.txt new file mode 100644 index 0000000000000000000000000000000000000000..76199daf78686bc572420cf8d6029060b5bb25ef --- /dev/null +++ b/the_code/Human/data/luciferase/GANall_IRF4_TYR_MLANA.txt @@ -0,0 +1,13 @@ +GG-1 26.22 35.84 23.84 +GG-2 0.83 0.95 1.47 +GG-3 15.25 16.79 15.14 +GG-4 124.57 153.21 95.54 +GG-5 1.79 1.94 1.81 +GG-6 1.01 0.99 1.37 +GG-7 1.29 0.95 1.46 +GG-8 8.27 0.93 4.87 +GG-9 1.06 1.20 1.46 +GG-10 2.08 1.21 11.17 +MLANA 124.9289666 59.56148702 37.85492237 +TYR 14.37348766 4.056166795 3.081931338 +IRF4 4.97563967 1.343298843 1.208126751 diff --git a/the_code/Human/data/luciferase/IRF4.txt b/the_code/Human/data/luciferase/IRF4.txt new file mode 100644 index 0000000000000000000000000000000000000000..ed8a1283bd41389eadc5b36195231f189c3bd7f4 --- /dev/null +++ b/the_code/Human/data/luciferase/IRF4.txt @@ -0,0 +1,5 @@ +WT 1.682871057 2.334252116 3.044411228 +Repr 0.88337328 1.250529185 0.888937795 +Mut-MITF 0.656437333 0.895013682 1.286511503 +Mut-SOX 0.484164347 0.907822905 1.32067221 +Mut-ZEB 6.443861642 11.1927444 16.67269371 \ No newline at end of file diff --git a/the_code/Human/data/motif_embedding/luciferase_ME.txt b/the_code/Human/data/motif_embedding/luciferase_ME.txt new file mode 100644 index 0000000000000000000000000000000000000000..caec430d4474cbe92865c3fbee0b2bb408986c96 --- /dev/null +++ b/the_code/Human/data/motif_embedding/luciferase_ME.txt @@ -0,0 +1,20 @@ +ME-1 1.41 1.18 1.01 0.98 0.94 +ME-2 6.84 4.89 4.71 1.00 1.00 +ME-3 2.52 1.99 1.66 0.96 1.01 +ME-4 12.46 9.21 5.33 1.02 0.98 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26.65 25.98 +ME-2 6.84 4.89 4.71 +ME-7 19.44 13.00 11.49 +ME-12 40.12 28.36 15.21 +ME-17 54.98 34.12 25.04 +MLANA 124.9289666 59.56148702 37.85492237 +TYR 14.37348766 4.056166795 3.081931338 +IRF4 4.97563967 1.343298843 1.208126751 \ No newline at end of file diff --git a/the_code/Human/data/motif_embedding/motif_embedding_smtr.pkl b/the_code/Human/data/motif_embedding/motif_embedding_smtr.pkl new file mode 100644 index 0000000000000000000000000000000000000000..785209c225addd74de7d104039ca3d6765137dc5 --- /dev/null +++ b/the_code/Human/data/motif_embedding/motif_embedding_smtr.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1104e4908a0b085775f8f2f87a6f937cdafa988ee2dd784c40bf26000c8f1ed4 +size 479271704 diff --git a/the_code/Human/data/tfmodisco/MMEFS_M4_results.hdf5 b/the_code/Human/data/tfmodisco/MMEFS_M4_results.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..ae048aa3fa5b6dc1ad5ea4603e1f6db0c2493005 --- /dev/null +++ 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0.14285714285714285 0.14285714285714285 0.4025974025974026 +0.3246753246753247 0.11688311688311688 0.09090909090909091 0.4675324675324675 diff --git a/the_code/Human/data/tomtom/motif-1.meme b/the_code/Human/data/tomtom/motif-1.meme new file mode 100644 index 0000000000000000000000000000000000000000..e25be88af62cc5340b34c7afd837036f99d0664b --- /dev/null +++ b/the_code/Human/data/tomtom/motif-1.meme @@ -0,0 +1,31 @@ +MEME version 4 + +ALPHABET= ACGT + +strands: + - + +Background letter frequencies (from unknown source): +A 0.250 C 0.250 G 0.250 T 0.250 + +MOTIF 1 NWNAADDVNNBYWTTGTNH + +letter-probability matrix: alength= 4 w= 19 nsites= 1 E= 0e+0 +0.458380 0.154106 0.138920 0.248594 +0.569741 0.084927 0.060742 0.284589 +0.278403 0.460630 0.125422 0.135546 +0.733971 0.146794 0.060742 0.058493 +0.788526 0.032058 0.134421 0.044994 +0.434196 0.052868 0.198538 0.314398 +0.316648 0.121485 0.411136 0.150731 +0.249719 0.200787 0.475253 0.074241 +0.249719 0.254218 0.343082 0.152981 +0.202475 0.280652 0.221597 0.295276 +0.053431 0.472441 0.232846 0.241282 +0.033183 0.677728 0.075928 0.213161 +0.545557 0.067492 0.045557 0.341395 +0.008436 0.086052 0.023622 0.881890 +0.003937 0.005062 0.004499 0.986502 +0.049494 0.020810 0.924634 0.005062 +0.030934 0.005062 0.003937 0.960067 +0.188414 0.181102 0.183352 0.447132 +0.163667 0.375141 0.089426 0.371766 diff --git a/the_code/Human/data/tomtom/motif-1/tomtom.html b/the_code/Human/data/tomtom/motif-1/tomtom.html new file mode 100644 index 0000000000000000000000000000000000000000..502f311f55db7e0676e7195cf8e4e15b0614256f --- /dev/null +++ b/the_code/Human/data/tomtom/motif-1/tomtom.html @@ -0,0 +1,21928 @@ + + + + + Tomtom Results + + + + + + + + + + + + + + + + +
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The motif preview. On supporting browsers this will display as a motif + logo, otherwise the consensus sequence will be displayed.

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The number motifs in the target database with a significant match to the query motif.

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Links to the (up to) twenty target motifs with the most significant matches to the query motif.

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The number of motifs read from the motif database minus the number that + had to be discarded due to conflicting IDs.

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The number of motifs in this database that have a significant match to at least one of the query motifs.

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The summary gives information about the target motif. Mouse over each + row to show further help buttons for each specific title.

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The ID of the target motif with the optional alternate ID shown in parentheses.

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The image shows the optimal alignment of the two motifs. The sequence logo + of the target motif is shown aligned above the logo for the query motif.

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By clicking the link "Create custom LOGO ↧" a form to make custom logos + will be displayed. The download button can then be clicked to generate a motif + matching the selected specifications.

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Strand Handling + Reverse complements are not possible so motifs are compared as they are provided. + Motifs are compared as they are provided. + Motifs may be reverse complemented before comparison to find a better match. +
Distance Measure + Average log-likelihood ratio + Euclidean distance + Kullback-Leibler divergence + Pearson correlation coefficient + Sandelin-Wasserman function + Bayesian Likelihood 2-Components score (from 1-component Dirichlet prior) + Bayesian Likelihood 2-Components score (from 5-component Dirichlet prior) + Log likelihood Ratio score (from 1-component Dirichlet prior) + Log likelihood Ratio score (from 5-component Dirichlet prior) +
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+ + + diff --git a/the_code/Human/data/tomtom/motif-1/tomtom.tsv b/the_code/Human/data/tomtom/motif-1/tomtom.tsv new file mode 100644 index 0000000000000000000000000000000000000000..7257b0c726de72bc602c3db862cecf774af8b4b1 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-1/tomtom.tsv @@ -0,0 +1,537 @@ +Query_ID Target_ID Optimal_offset p-value E-value q-value Overlap Query_consensus Target_consensus Orientation +1 hocomoco__SOX10_HUMAN.H11MO.0.B-Sox100B -2 3.30476e-18 8.08114e-14 1.59414e-13 16 AACAAAGGGTCCATTGTTC CAAAGGAGGCATTGTT + +1 hocomoco__SOX9_HUMAN.H11MO.0.B-Sox14-Sox100B-SoxN -3 1.50084e-16 3.67e-12 3.61984e-12 16 AACAAAGGGTCCATTGTTC AAAGGGGCCTTTGTTC + +1 transfac_pro__M08838-Sox100B -1 1.54198e-14 3.77061e-10 2.47938e-10 17 AACAAAGGGTCCATTGTTC AAAAAGGAGCCTTTGTG - +1 tfdimers__MD00293-Mad-Sox14 8 7.49383e-13 1.83247e-08 9.03711e-09 19 AACAAAGGGTCCATTGTTC TAAAACAAAACAAAGGATCCTTTGTTTTTTT - +1 taipale_cyt_meth__SOX10_AACAATNNNNNNATTGTT_FL_repr-Sox100B 0 3.37986e-12 8.26476e-08 3.24302e-08 18 AACAAAGGGTCCATTGTTC AACAATGGATCCATTGTT - +1 taipale_cyt_meth__SOX10_AACAATNNNNNNATTGTT_FL_meth-Sox100B 0 9.56763e-12 2.33957e-07 6.59313e-08 18 AACAAAGGGTCCATTGTTC AACAATGGATCCATTGTT + +1 transfac_pro__M08899-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -7 1.5285e-11 3.73764e-07 8.19235e-08 11 AACAAAGGGTCCATTGTTC GTCCCTTTGTT + +1 taipale_cyt_meth__SOX8_ACAATNNNNNNATTGT_FL-Sox100B -1 3.28127e-11 8.02369e-07 1.5828e-07 16 AACAAAGGGTCCATTGTTC ACAATGGGCCCATTGT - +1 taipale_cyt_meth__SOX8_ACAATNNNNNNATTGT_FL_meth-Sox100B -1 1.83409e-09 4.48489e-05 6.80553e-06 16 AACAAAGGGTCCATTGTTC ACAATGGATCCATTGT + +1 tfdimers__MD00034-SoxN -1 3.99214e-09 9.76197e-05 1.28381e-05 18 AACAAAGGGTCCATTGTTC GATTAAATTCCTTTGTTATGCTAATGAATTT + +1 transfac_pro__M08973-SoxN -8 1.60864e-08 0.000393361 4.84981e-05 10 AACAAAGGGTCCATTGTTC TTCTATTGTT - +1 transfac_pro__M08970-Sox100B-SoxN -9 2.00533e-08 0.000490364 5.69014e-05 10 AACAAAGGGTCCATTGTTC TCCATTGTTA - +1 tfdimers__MD00490-cad-SoxN -1 2.39575e-08 0.000585832 6.42028e-05 18 AACAAAGGGTCCATTGTTC AAATAAATCCCTTTGTTTTGTAAATAAAGTCA + +1 cisbp__M6124-Sox15-SoxN -8 2.5632e-08 0.000626779 6.5075e-05 11 AACAAAGGGTCCATTGTTC TTCCATTGTTT + +1 taipale_cyt_meth__SOX4_GAACAAAGRN_eDBD_meth-D-Mad-Sox100B-Sox14-SoxN -9 3.78982e-08 0.000926725 8.70532e-05 10 AACAAAGGGTCCATTGTTC TCCTTTGTTC - +1 homer__CCATTGTTNY_Sox6-D-Sox14-Sox102F-SoxN -10 3.78982e-08 0.000926725 8.70532e-05 9 AACAAAGGGTCCATTGTTC CCATTGTTCT + +1 tfdimers__MD00004 0 5.37968e-08 0.00131549 0.000117956 19 AACAAAGGGTCCATTGTTC TTTTTTTTTTCCTTTGTCATGCAAATAAATTT - +1 transfac_pro__M08974-Sox102F-Sox15 -9 5.68151e-08 0.0013893 0.000119158 10 AACAAAGGGTCCATTGTTC TCTATTGTTT - +1 transfac_pro__M07614-Sox14 -6 6.34485e-08 0.00155151 0.000123916 11 AACAAAGGGTCCATTGTTC GAACTCTTTGT - +1 tfdimers__MD00312 0 6.42219e-08 0.00157042 0.000123916 19 AACAAAGGGTCCATTGTTC ATTTTTTCTTCCTTTGTTATGCAAATGGCCCCTTTGT - +1 cisbp__M5846-D-Sox100B-Sox102F-Sox15-SoxN -10 7.24034e-08 0.00177048 0.000134329 9 AACAAAGGGTCCATTGTTC CCATTGTTC + +1 taipale_cyt_meth__SOX4_GAACAAAGRN_eDBD_repr-Mad-Sox100B-Sox14-SoxN -9 8.39473e-08 0.00205276 0.000149978 10 AACAAAGGGTCCATTGTTC CCCTTTGTTC - +1 taipale_tf_pairs__CUX1_SOX15_ATCRATNNNNNNNNSYATTGTT_CAP_repr-ct 4 1.02564e-07 0.002508 0.000176694 18 AACAAAGGGTCCATTGTTC ATCGATACATATGGCCATTGTT + +1 taipale__SOX9_DBD_NAACAATRN_repr-D-Sox100B-Sox102F-Sox15-SoxN -10 1.12338e-07 0.00274699 0.000186858 9 AACAAAGGGTCCATTGTTC CCATTGTTC - +1 transfac_pro__M08972-D-Sox100B-Sox102F-Sox15 -9 2.10202e-07 0.00514008 0.000337988 10 AACAAAGGGTCCATTGTTC TCCATTGTTT - +1 tfdimers__MD00246-vvl 0 2.28344e-07 0.00558369 0.000355315 19 AACAAAGGGTCCATTGTTC TTTTTTTTTTCCTTTGTTATTCTAATTCCTCTTATT - +1 transfac_pro__M08971-D-Mad-Sox14-Sox15-Sox21a-Sox21b -10 2.9708e-07 0.00726451 0.000434256 9 AACAAAGGGTCCATTGTTC CTATTGTTTT + +1 cisbp__M1604-D-Mad-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -11 3.11852e-07 0.00762571 0.00044244 8 AACAAAGGGTCCATTGTTC CATTGTTCT + +1 tfdimers__MD00320 0 3.60632e-07 0.00881853 0.000497028 19 AACAAAGGGTCCATTGTTC TTTTTTTTTTCCTTTGTTATGTAGAATAAT - +1 tfdimers__MD00502-Sox100B -3 3.74852e-07 0.00916625 0.000502276 16 AACAAAGGGTCCATTGTTC ATTTTTCCCATTGTGATTGATGTTTATT - +1 homer__CCWTTGTYYB_Sox10-Sox14-Sox102F-SoxN -10 4.15251e-07 0.0101541 0.00054137 9 AACAAAGGGTCCATTGTTC CCTTTGTTCG + +1 hocomoco__SOX9_HUMAN.H11MO.1.B-Sox100B-Sox102F -10 4.56224e-07 0.011156 0.000576861 9 AACAAAGGGTCCATTGTTC CCATTGTTT + +1 hocomoco__SOX2_MOUSE.H11MO.1.A-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN -8 5.58691e-07 0.0136617 0.000673747 11 AACAAAGGGTCCATTGTTC TTCCTTTGTTCTG + +1 idmmpmm__D-D-SoxN -8 5.74433e-07 0.0140466 0.000675835 10 AACAAAGGGTCCATTGTTC GTCCATTGTT + +1 hocomoco__SOX10_MOUSE.H11MO.1.A-Mad-Sox14-Sox100B-Sox102F-SoxN -9 6.75983e-07 0.0165298 0.000776376 10 AACAAAGGGTCCATTGTTC GCCTTTGTTCT + +1 homer__CCWTTGTY_Sox3-D-Mad-Sox14-Sox15-Sox102F-SoxN -10 7.44457e-07 0.0182042 0.000835134 8 AACAAAGGGTCCATTGTTC CCTTTGTT + +1 dbcorrdb__NANOG__ENCSR000BMT_1__m1-CG9650-Mad-nej-pan-SoxN -5 7.82337e-07 0.0191305 0.000857683 14 AACAAAGGGTCCATTGTTC GGAGGCCTTTGTTATGCAAA - +1 transfac_pro__M01247-D-Mad-pan-Sox100B-Sox14-Sox15-SoxN -5 1.03932e-06 0.0254144 0.00111409 14 AACAAAGGGTCCATTGTTC TGCTTCCTTTGTTTTTTAAA - +1 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNNNYMATTA_CAP_repr-pb 1 1.08122e-06 0.026439 0.00113381 17 AACAAAGGGTCCATTGTTC TAATTGCGTTGCCATTGT - +1 transfac_pro__M07269-Sox100B -5 1.17233e-06 0.028667 0.0012032 14 AACAAAGGGTCCATTGTTC TGGGGCCTTTGTTTAGG - +1 transfac_pro__M08975-Sox102F-Sox15 -9 1.24055e-06 0.0303351 0.00124669 10 AACAAAGGGTCCATTGTTC TCTATTGTTT - +1 transfac_pro__M01272-SoxN -6 1.3039e-06 0.0318844 0.00128362 13 AACAAAGGGTCCATTGTTC AACCCCATTGTTATGC + +1 transfac_pro__M08976-D-Sox100B-Sox102F-Sox15-SoxN -10 1.36122e-06 0.033286 0.00131324 8 AACAAAGGGTCCATTGTTC CTATTGTT - +1 taipale_tf_pairs__SOX6_TBX21_RGGTGTNNNNNNNNNYATTGT_CAP_repr-Sox102F 4 1.46506e-06 0.0358251 0.0013857 17 AACAAAGGGTCCATTGTTC AGGTGTTACTTTTTCCATTGT + +1 transfac_pro__M02116-Sox100B -11 1.61056e-06 0.039383 0.00146584 7 AACAAAGGGTCCATTGTTC CTTTGTT - +1 transfac_pro__M07307-Sox15 -6 1.76997e-06 0.043281 0.00154359 11 AACAAAGGGTCCATTGTTC ACGGCCATTGT - +1 hocomoco__SOX3_HUMAN.H11MO.0.B-Mad-Sox14-Sox100B-Sox102F-SoxN -9 1.76997e-06 0.043281 0.00154359 10 AACAAAGGGTCCATTGTTC GCCTTTGTCCC + +1 dbcorrdb__POU5F1__ENCSR000BMU_1__m2-Mad-pan -2 1.81265e-06 0.0443247 0.00154359 17 AACAAAGGGTCCATTGTTC CAAGGGGGCCTTTCTTATGC - +1 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNNYMATTA_CAP_repr-pb 0 1.8967e-06 0.04638 0.00154359 17 AACAAAGGGTCCATTGTTC TAATTGCGTTCCATTGT - +1 transfac_pro__M02902-D-Sox21a-Sox21b -7 1.90694e-06 0.0466303 0.00154359 12 AACAAAGGGTCCATTGTTC GCGCCATTGTGTGAG - +1 taipale_cyt_meth__SOX14_NGAACAATGN_eDBD_meth-D-Sox21a-Sox21b -10 1.91945e-06 0.0469364 0.00154359 9 AACAAAGGGTCCATTGTTC CCATTGTTAG - +1 transfac_pro__M03886-Mad-SoxN -8 1.91998e-06 0.0469492 0.00154359 11 AACAAAGGGTCCATTGTTC CTCCATTGTTATGG + +1 hocomoco__SOX2_HUMAN.H11MO.0.A-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN-pan -8 2.07631e-06 0.0507719 0.0016419 11 AACAAAGGGTCCATTGTTC TCCCTTTGTTCTC + +1 transfac_pro__M02807-Sox100B-Sox102F-Sox15 -3 2.14741e-06 0.0525106 0.00167074 16 AACAAAGGGTCCATTGTTC TGAAATTCTATTGTTCTTTATT - +1 transfac_pro__M01284-Sox100B-SoxN -8 2.29954e-06 0.0562307 0.0017607 11 AACAAAGGGTCCATTGTTC GTCCTTTGTTT - +1 tfdimers__MD00227-Mad -4 2.48394e-06 0.0607398 0.00187217 15 AACAAAGGGTCCATTGTTC TTTTTTCCTTTGTTTTGCTGACTCTGCTATTTTT + +1 transfac_pro__M02917-D-Sox21a-Sox21b -7 2.76238e-06 0.0675485 0.00205001 12 AACAAAGGGTCCATTGTTC CACCTATTGTTCCGTGA - +1 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNYMATTA_CAP_repr-pb -1 2.84929e-06 0.0696737 0.00208247 16 AACAAAGGGTCCATTGTTC TAATTGCGTCCATTGT - +1 transfac_pro__M07308-Mad-Sox14-SoxN -8 3.14341e-06 0.0768659 0.00226314 11 AACAAAGGGTCCATTGTTC TTCCTTTGTTTTGGA - +1 taipale_cyt_meth__SOX8_AGAACAATGN_eDBD_meth-D-Sox100B-SoxN -10 3.34652e-06 0.0818323 0.0022771 9 AACAAAGGGTCCATTGTTC CCATTGTTCT - +1 hocomoco__SOX3_MOUSE.H11MO.0.C-Mad-Sox14-Sox100B-Sox102F-SoxN -9 3.37146e-06 0.0824423 0.0022771 10 AACAAAGGGTCCATTGTTC GCCTTTGTTCC + +1 cisbp__M1904-D-Sox100B-Sox102F-Sox15-SoxN -10 3.40373e-06 0.0832314 0.0022771 9 AACAAAGGGTCCATTGTTC CCATTGTTC + +1 jaspar__MA0077.1-D-Sox15-Sox100B-Sox102F-SoxN -10 3.40373e-06 0.0832314 0.0022771 9 AACAAAGGGTCCATTGTTC CCATTGTTC + +1 scertf__fordyce.ROX1 -9 3.41138e-06 0.0834185 0.0022771 8 AACAAAGGGTCCATTGTTC GCTATTGT - +1 transfac_pro__M02804-Sox102F-Sox15 -6 3.44604e-06 0.0842659 0.0022771 13 AACAAAGGGTCCATTGTTC AATTCCATTGTTCAAT - +1 cisbp__M4920-D-Mad-Sox100B-Sox102F-Sox14-Sox15-SoxN-Ssrp -9 3.82039e-06 0.0934199 0.0024627 10 AACAAAGGGTCCATTGTTC TCCATTGTTCT - +1 taipale_cyt_meth__SOX3_NGAACAATGN_FL_meth_repr-D-Sox100B-SoxN -10 3.82902e-06 0.0936311 0.0024627 9 AACAAAGGGTCCATTGTTC CCATTGTTCT - +1 flyfactorsurvey__D_NAR_FBgn0000411-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN-Ssrp -9 4.32382e-06 0.10573 0.00274018 10 AACAAAGGGTCCATTGTTC TCCATTGTTCT - +1 homer__CCCATTGTTC_Sox2-D-Sox14-Sox100B-Sox102F-SoxN -9 4.37406e-06 0.106959 0.00274018 10 AACAAAGGGTCCATTGTTC CCCATTGTTC + +1 transfac_pro__M01590-D-Mad-pan-Sox100B-Sox102F-Sox14-SoxN -9 4.55359e-06 0.111349 0.00281608 10 AACAAAGGGTCCATTGTTC TCCTTTGTTTTT - +1 taipale_cyt_meth__SOX18_NACAATGN_eDBD_meth-Sox15 -10 4.79569e-06 0.117269 0.00292826 8 AACAAAGGGTCCATTGTTC GCATTGTT - +1 hocomoco__SOX13_HUMAN.H11MO.0.D-Sox102F -11 5.65662e-06 0.138321 0.00328749 8 AACAAAGGGTCCATTGTTC CATTGTTC + +1 flyfactorsurvey__Sox15_SANGER_5_FBgn0005613-Sox15-Sox21a-SoxN -11 5.65662e-06 0.138321 0.00328749 8 AACAAAGGGTCCATTGTTC CATTGTTT - +1 taipale_cyt_meth__SOX30_GAACAATN_eDBD-Sox102F -11 5.65662e-06 0.138321 0.00328749 8 AACAAAGGGTCCATTGTTC CATTGTTC - +1 transfac_pro__M07338-Sox100B -9 5.65662e-06 0.138321 0.00328749 8 AACAAAGGGTCCATTGTTC GTCATTGT - +1 hocomoco__SOX10_HUMAN.H11MO.1.A-Mad-Sox14-Sox100B-SoxN-pan -8 6.25426e-06 0.152935 0.00352518 11 AACAAAGGGTCCATTGTTC TTCCTTTGTTCTC + +1 tfdimers__MD00121-EcR-usp 0 6.27681e-06 0.153487 0.00352518 19 AACAAAGGGTCCATTGTTC TTTTCCCTGTCCTTTGTTTTCTTAAT - +1 taipale_cyt_meth__SOX8_AGAACAATGN_eDBD-D-Sox100B-Sox102F-Sox14-SoxN -10 6.46092e-06 0.157989 0.00352518 9 AACAAAGGGTCCATTGTTC CCATTGTTCT - +1 cisbp__M5208-Sox15-Sox21a-SoxN -11 6.65024e-06 0.162618 0.00352518 8 AACAAAGGGTCCATTGTTC CATTGTTT + +1 cisbp__M6471-D-Sox100B-Sox102F-Sox14-SoxN -11 6.65024e-06 0.162618 0.00352518 8 AACAAAGGGTCCATTGTTC CATTGTTC + +1 factorbook__SOX2-Sox14-Sox15-Sox100B-Sox102F-SoxN -10 6.65024e-06 0.162618 0.00352518 8 AACAAAGGGTCCATTGTTC CCTTTGTT - +1 transfac_pro__M01308-D-Mad-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -10 6.65024e-06 0.162618 0.00352518 8 AACAAAGGGTCCATTGTTC CCTTTGTT - +1 yetfasco__YPR065W_1396 -10 6.65024e-06 0.162618 0.00352518 8 AACAAAGGGTCCATTGTTC CTATTGTG - +1 dbcorrdb__TCF12__ENCSR000BIT_1__m2 -2 6.82161e-06 0.166809 0.00357671 17 AACAAAGGGTCCATTGTTC GCCGGGAGCCTTTGTTATGC - +1 tfdimers__MD00498-Mad-oc -4 7.30194e-06 0.178554 0.00378739 15 AACAAAGGGTCCATTGTTC TATATTCCTTTGTTTTAATCCTTTT - +1 jaspar__MA0445.1-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN -9 7.89081e-06 0.192954 0.00400667 10 AACAAAGGGTCCATTGTTC TCCATTGTTCT + +1 cisbp__M2249-D-Mad-Sox100B-Sox102F-Sox14-Sox15-SoxN -9 7.89081e-06 0.192954 0.00400667 10 AACAAAGGGTCCATTGTTC TCCATTGTTCT - +1 cisbp__M1594-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b -11 8.31966e-06 0.203441 0.00418042 8 AACAAAGGGTCCATTGTTC CATTGTTCTT + +1 cisbp__M6470-Sox100B -10 8.65801e-06 0.211714 0.00430558 7 AACAAAGGGTCCATTGTTC TCTTTGT + +1 cisbp__M1591-Sox100B-Sox102F-Sox14 -12 9.10638e-06 0.222678 0.00448234 7 AACAAAGGGTCCATTGTTC ATTGTTCT + +1 transfac_pro__M02866 -5 9.71621e-06 0.237591 0.00473421 14 AACAAAGGGTCCATTGTTC TGTTCCCATTGTGTACT + +1 cisbp__M6478-D-Sox100B-Sox102F-Sox14-SoxN -9 9.96097e-06 0.243576 0.00480493 10 AACAAAGGGTCCATTGTTC CCCATTGTTCT - +1 tfdimers__MD00074-pho-phol-Sox14 -5 1.03409e-05 0.252865 0.0049388 14 AACAAAGGGTCCATTGTTC TTTTCCCTTTGTTATGGAAATG - +1 taipale_tf_pairs__TEAD4_SOX15_NACAATRNNNNGAATGY_CAP_repr-sd -1 1.05947e-05 0.259073 0.00494228 17 AACAAAGGGTCCATTGTTC ACATTCCTTCTATTGTT - +1 cisbp__M2313-D-Mad-Sox100B-Sox102F-Sox14-SoxN -10 1.06555e-05 0.26056 0.00494228 9 AACAAAGGGTCCATTGTTC CCATTGTTTT + +1 jaspar__MA0515.1-D-Mad-Sox14-Sox100B-Sox102F-SoxN -10 1.06555e-05 0.26056 0.00494228 9 AACAAAGGGTCCATTGTTC CCATTGTTTT + +1 dbcorrdb__SP1__ENCSR000BJX_1__m2-btd-kay-Nf-YB-Spps -2 1.13099e-05 0.276562 0.00519584 17 AACAAAGGGTCCATTGTTC CCCCCCGGTCATTGGTTACC - +1 jaspar__MA0442.1-Sox100B -11 1.17126e-05 0.286407 0.00533005 6 AACAAAGGGTCCATTGTTC CTTTGT + +1 taipale_cyt_meth__IRX1_NACAYGNNNNNNCRTGTN_eDBD_repr-ara-caup-mirr 0 1.22145e-05 0.29868 0.00550511 18 AACAAAGGGTCCATTGTTC TACATGTTATTACATGTA + +1 taipale_cyt_meth__SOX30_GAACAATN_eDBD_meth-Sox102F -11 1.23255e-05 0.301395 0.00550511 8 AACAAAGGGTCCATTGTTC CATTGTTC - +1 transfac_pro__M02795-D-Mad-Sox100B-Sox14 -6 1.25815e-05 0.307655 0.00556789 13 AACAAAGGGTCCATTGTTC TAGTCCTTTGTTCTTAT - +1 cisbp__M1905-Sox15 -9 1.38104e-05 0.337706 0.00599516 9 AACAAAGGGTCCATTGTTC TTCATTGTC + +1 jaspar__MA0078.1-Sox15 -9 1.38104e-05 0.337706 0.00599516 9 AACAAAGGGTCCATTGTTC CTCATTGTC + +1 tfdimers__MD00356-fkh-Mad -4 1.39198e-05 0.340381 0.00599516 15 AACAAAGGGTCCATTGTTC TTTTTTTTTTTGTTTTTTTTTGTTTGTTTTTTTTTT + +1 taipale_cyt_meth__SOX14_NGAACAATGN_eDBD-D-Sox21a-Sox21b-SoxN -10 1.52987e-05 0.374099 0.00653072 9 AACAAAGGGTCCATTGTTC CCATTGTGCG - +1 hocomoco__SOX4_HUMAN.H11MO.0.B-Mad-Sox14-Sox100B-SoxN-pan -9 1.73038e-05 0.42313 0.00732187 10 AACAAAGGGTCCATTGTTC TCCTTTGTTCTC + +1 cisbp__M1601-D-Sox14-Sox15-Sox21a-Sox21b -12 1.78676e-05 0.436916 0.00749468 7 AACAAAGGGTCCATTGTTC ATTGTTTTC + +1 cisbp__M3916-D-Sox100B-SoxN -8 1.89742e-05 0.463976 0.00789024 11 AACAAAGGGTCCATTGTTC TCCCATTGTTCTTA - +1 transfac_public__M00410-D-Sox100B-Sox102F-SoxN -8 2.08175e-05 0.50905 0.00858277 11 AACAAAGGGTCCATTGTTC TCCCATTGTTCTTA - +1 transfac_public__M00160-Sox102F -9 2.13583e-05 0.522274 0.00873111 10 AACAAAGGGTCCATTGTTC TCTATTGTTTAC - +1 tfdimers__MD00169-pan-pho-phol -5 2.18154e-05 0.533451 0.00884303 14 AACAAAGGGTCCATTGTTC TTTTTCCTTTGTTATGCAAATGGCAGCTTTTT - +1 transfac_pro__M07432-Mad-Sox14-SoxN -10 2.34962e-05 0.574552 0.00944499 9 AACAAAGGGTCCATTGTTC CCTTTGTTATGGA - +1 cisbp__M3962-Sox102F -9 2.37009e-05 0.579557 0.00944853 10 AACAAAGGGTCCATTGTTC TCTATTGTTTAC - +1 tfdimers__MD00555-Sox100B -4 2.44178e-05 0.597088 0.00965455 15 AACAAAGGGTCCATTGTTC TTTTTTCTTTTGTTATACAAAGGAAATATT - +1 transfac_pro__M07268-Sox14 -10 2.47291e-05 0.604701 0.00969814 7 AACAAAGGGTCCATTGTTC TCTTTGT + +1 tfdimers__MD00205-GATAe-grn-pnr-srp -4 2.73483e-05 0.668749 0.0106388 15 AACAAAGGGTCCATTGTTC ATTTTTCTATTGTTATCTTTATT - +1 transfac_pro__M01505-Sox15 -4 2.7623e-05 0.675466 0.0106597 15 AACAAAGGGTCCATTGTTC GGAGGTCTATTGTTCTACAA - +1 dbcorrdb__EP300__ENCSR000EDV_1__m3-CG7786-gt-Myc-nej-Pdp1-slbo-Stat92E -3 2.98962e-05 0.731053 0.0113565 16 AACAAAGGGTCCATTGTTC CAGTTGGGTATTGCGTAATA - +1 hocomoco__SOX17_HUMAN.H11MO.0.C-D-Sox15 -9 3.0118e-05 0.736474 0.0113565 10 AACAAAGGGTCCATTGTTC GCCATTGTTTT + +1 taipale_cyt_meth__SOX9_MGAACAATRN_eDBD_meth-D-Sox100B-SoxN -10 3.0565e-05 0.747405 0.0114293 9 AACAAAGGGTCCATTGTTC CTATTGTTCT - +1 transfac_pro__M02799-Sox102F -6 3.14649e-05 0.76941 0.0115862 13 AACAAAGGGTCCATTGTTC AAATCTATTGTTCACTA - +1 transfac_pro__M02907-D-Sox21a-Sox21b -7 3.14649e-05 0.76941 0.0115862 12 AACAAAGGGTCCATTGTTC CATCAATTGTTCCGCTA + +1 cisbp__M5207-Sox14 -8 3.34763e-05 0.818597 0.0121415 11 AACAAAGGGTCCATTGTTC CTCCTTTGTCC + +1 flyfactorsurvey__Sox14_SANGER_10_FBgn0005612-Sox14 -8 3.34763e-05 0.818597 0.0121415 11 AACAAAGGGTCCATTGTTC CTCCTTTGTCC + +1 bergman__dsx-dsx -5 3.41201e-05 0.834338 0.0121916 14 AACAAAGGGTCCATTGTTC AAGATACATTGTGTTAC - +1 hocomoco__SOX9_MOUSE.H11MO.1.A-Sox14-Sox100B-SoxN -10 3.71783e-05 0.909121 0.0131867 9 AACAAAGGGTCCATTGTTC CCTTTGTTCTC + +1 cisbp__M1596-D-Sox21a-Sox21b -11 3.74654e-05 0.916141 0.0131915 8 AACAAAGGGTCCATTGTTC CATTGTTA - +1 taipale_cyt_meth__SOX9_MGAACAATRN_eDBD-D-Sox100B-Sox102F-SoxN -10 3.81684e-05 0.933332 0.0133417 9 AACAAAGGGTCCATTGTTC CCATTGTTCT - +1 tfdimers__MD00337-EcR 5 3.9083e-05 0.955697 0.0135631 19 AACAAAGGGTCCATTGTTC TTTCTCCCTCTGAACCCTTTGTTTTTCAAATTCTC + +1 transfac_pro__M01131-Sox100B -11 3.97528e-05 0.972075 0.013697 7 AACAAAGGGTCCATTGTTC CTTTGTG + +1 neph__UW.Motif.0259 -3 4.0576e-05 0.992205 0.0138815 15 AACAAAGGGTCCATTGTTC AGAAATTGCTGTGTG + +1 neph__UW.Motif.0471 -4 4.40415e-05 1.07695 0.0148956 15 AACAAAGGGTCCATTGTTC AGGAATGCTCTGTTTC + +1 neph__UW.Motif.0093 -3 4.41581e-05 1.0798 0.0148956 15 AACAAAGGGTCCATTGTTC AAAAAAAAATTTGGC + +1 transfac_pro__M02871 -5 5.11612e-05 1.25105 0.0171381 14 AACAAAGGGTCCATTGTTC TCGCACCTTTCTCC - +1 hocomoco__SOX15_HUMAN.H11MO.0.D -11 5.37122e-05 1.31342 0.0178686 7 AACAAAGGGTCCATTGTTC CATTGTT + +1 taipale_tf_pairs__GCM2_SOX15_ATRCGGGYNNNNNYWTTGTNN_CAP_repr-gcm-gcm2 2 5.44269e-05 1.3309 0.0179823 19 AACAAAGGGTCCATTGTTC ATGCGGGTATGTCCATTGTTT + +1 transfac_pro__M03803-Sox15 -13 5.87514e-05 1.43665 0.0192791 6 AACAAAGGGTCCATTGTTC TTGTTC + +1 swissregulon__hs__SOX17.p2-Sox15 -9 5.92872e-05 1.44975 0.0192965 9 AACAAAGGGTCCATTGTTC CTCATTGTC + +1 taipale_tf_pairs__ETV2_SOX15_RSCGGAANNNNNNNYWTTGT_CAP_repr-pnt 3 6.00045e-05 1.46729 0.0192965 17 AACAAAGGGTCCATTGTTC ACCGGAAGTGAGTCCATTGT + +1 dbcorrdb__NANOG__ENCSR000BMT_1__m4 -4 6.00045e-05 1.46729 0.0192965 15 AACAAAGGGTCCATTGTTC AGGGACCCATTGAAATGCAA + +1 tfdimers__MD00591-TfAP-2 -1 6.05728e-05 1.48119 0.0193502 18 AACAAAGGGTCCATTGTTC ACTAAAAGGCTTTTGTTTTCTAAAT - +1 hocomoco__SOX5_HUMAN.H11MO.0.C-Sox102F -11 6.21938e-05 1.52083 0.0194867 8 AACAAAGGGTCCATTGTTC TATTGTTA + +1 tfdimers__MD00316-pan -5 6.22119e-05 1.52127 0.0194867 14 AACAAAGGGTCCATTGTTC TATTTCCTTTGTTTTGCAAAACAAAGGAAATA + +1 transfac_public__M00276-Sox102F-Sox15 -9 6.53832e-05 1.59881 0.0203479 10 AACAAAGGGTCCATTGTTC TCCATTGTTT + +1 neph__UW.Motif.0442 -2 6.69856e-05 1.638 0.020713 15 AACAAAGGGTCCATTGTTC CATTTTTCTCTCTGT - +1 dbcorrdb__EP300__ENCSR000EDV_1__m1-btd-EcR-HDAC1-Hnf4-Hr78-nej-Spps-svp-usp -1 6.98008e-05 1.70684 0.021446 18 AACAAAGGGTCCATTGTTC TCAAACTGGACTTTGATCTC - +1 cisbp__M1129-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 7.93397e-05 1.94009 0.0241462 7 AACAAAGGGTCCATTGTTC ATTGTTTT - +1 tfdimers__MD00338-Sox100B -3 7.95903e-05 1.94622 0.0241462 16 AACAAAGGGTCCATTGTTC TTTTTTTCCTTTGTTTTGCACAATTATTTTT + +1 dbcorrdb__TCF7L2__ENCSR000EXL_1__m1-pan -2 8.10931e-05 1.98297 0.0244483 17 AACAAAGGGTCCATTGTTC CGGCGGTCCCTTTGATGTTC - +1 taipale_tf_pairs__ETV2_SOX15_RSCGGAANNNNNNYWTTGT_CAP_repr-pnt 2 8.50594e-05 2.07996 0.0253669 17 AACAAAGGGTCCATTGTTC GCCGGAAGTGGCCCATTGT + +1 tfdimers__MD00494-Sox100B-Tbp -3 8.51915e-05 2.08319 0.0253669 16 AACAAAGGGTCCATTGTTC TTTTATTCCTTTGTTTATATAATT - +1 transfac_pro__M02808-Sox100B-Sox102F -6 8.76826e-05 2.1441 0.0258267 13 AACAAAGGGTCCATTGTTC TTATCTATTGTTCTTTA + +1 cisbp__M2459-Sox15-Sox102F -9 8.9317e-05 2.18407 0.0258267 10 AACAAAGGGTCCATTGTTC TCCATTGTTT - +1 cisbp__M6473-Sox15 -1 8.93585e-05 2.18508 0.0258267 18 AACAAAGGGTCCATTGTTC CAACAATCTTCATTGTCC + +1 cisbp__M6477-Sox102F -11 8.9413e-05 2.18642 0.0258267 8 AACAAAGGGTCCATTGTTC TATTGTTA - +1 cisbp__M1600-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b -12 8.9413e-05 2.18642 0.0258267 7 AACAAAGGGTCCATTGTTC ATTGTTTT + +1 neph__UW.Motif.0514 0 9.04723e-05 2.21232 0.0259772 16 AACAAAGGGTCCATTGTTC TTAAAATTTCTTTTTG - +1 hocomoco__SRY_HUMAN.H11MO.0.B -11 9.24826e-05 2.26148 0.0260854 8 AACAAAGGGTCCATTGTTC TTTTGTTTT + +1 cisbp__M6490 -11 9.24826e-05 2.26148 0.0260854 8 AACAAAGGGTCCATTGTTC TTTTGTTTT - +1 tfdimers__MD00030 2 9.37944e-05 2.29355 0.0260854 19 AACAAAGGGTCCATTGTTC TTAAAAAAGAACACAGTGTTCTTATTAAA - +1 dbcorrdb__CEBPZ__ENCSR000EDO_1__m1-CG7839 0 9.40937e-05 2.30087 0.0260854 19 AACAAAGGGTCCATTGTTC ATCAAAAAGACCAATCATTA + +1 dbcorrdb__RFX5__ENCSR000ECX_1__m2-btd-CG7839-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps -1 9.40937e-05 2.30087 0.0260854 18 AACAAAGGGTCCATTGTTC GCCGGGTTCTGATTGGCTGA - +1 dbcorrdb__TCF7L2__ENCSR000EVF_1__m1-pan -1 9.40937e-05 2.30087 0.0260854 18 AACAAAGGGTCCATTGTTC GCGGCGTTTCCTTTGATGTT - +1 cisbp__M6472 -11 9.47647e-05 2.31728 0.0261212 7 AACAAAGGGTCCATTGTTC CATTGTT + +1 dbcorrdb__BCL11A__ENCSR000BIP_1__m3-CG9650 -5 0.000101308 2.4773 0.0277089 14 AACAAAGGGTCCATTGTTC AGGGCTCATTGTCATGCAAA + +1 transfac_pro__M03888-Sox102F -9 0.000101673 2.48622 0.0277089 10 AACAAAGGGTCCATTGTTC GCTTTTGTCTA - +1 hocomoco__SOX18_HUMAN.H11MO.0.D-Sox15 -6 0.00010627 2.59863 0.028799 13 AACAAAGGGTCCATTGTTC GCACCCATTGTTCTTTTCC + +1 transfac_public__M00380 11 0.000108811 2.66076 0.0290192 19 AACAAAGGGTCCATTGTTC GGGGTGAGGTTGGATTTTGGGTTAATTTTT - +1 dbcorrdb__TBP__ENCSR000EHA_1__m2-Tbp -1 0.000109043 2.66642 0.0290192 18 AACAAAGGGTCCATTGTTC TCAAAAGGTCGCGCGTTCGA - +1 cisbp__M2312-Mad-Sox100B-Sox102F-Sox14-SoxN -10 0.000109489 2.67734 0.0290192 9 AACAAAGGGTCCATTGTTC CCTTTGTTTT + +1 jaspar__MA0514.1-Mad-Sox14-Sox100B-Sox102F-SoxN -10 0.000109489 2.67734 0.0290192 9 AACAAAGGGTCCATTGTTC CCTTTGTTTT + +1 tfdimers__MD00327-pan -5 0.000112876 2.76016 0.0296499 14 AACAAAGGGTCCATTGTTC TAGTTCCTTTGTTATGCAAATTAACCCACCTTCCCTCCTCACCCCCTCTA + +1 cisbp__M1597-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b -12 0.000113098 2.76559 0.0296499 7 AACAAAGGGTCCATTGTTC ATTGTTTT + +1 transfac_pro__M00728-D-Sox100B-Sox102F-Sox15-SoxN -9 0.000114759 2.80619 0.0297617 9 AACAAAGGGTCCATTGTTC CCTATTGTT + +1 transfac_pro__M07309-Sox15 -9 0.000114759 2.80619 0.0297617 9 AACAAAGGGTCCATTGTTC TCTATTGTC - +1 cisbp__M3718 11 0.000117311 2.86861 0.030261 19 AACAAAGGGTCCATTGTTC GGGGTGAGGTTGGATTTTGGGTTAATTTTT + +1 transfac_pro__M04837-Mad-nej-pan-Sox100B-Sox102F-Sox14-SoxN -10 0.000119893 2.93173 0.0307624 9 AACAAAGGGTCCATTGTTC CCTTTGTTTTGCAA - +1 tfdimers__MD00282-Mad-sens-2 1 0.000124895 3.05407 0.0318765 19 AACAAAGGGTCCATTGTTC TTTATATAAATCCTTTCTTTTTTTTTT + +1 cisbp__M1578-Mad-Sox100B-Sox14-SoxN -10 0.000126957 3.10447 0.032232 8 AACAAAGGGTCCATTGTTC CCTTTGTT + +1 cisbp__M1595-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.000127638 3.12114 0.0322354 7 AACAAAGGGTCCATTGTTC ATTGTTTTG - +1 tfdimers__MD00543-Sox100B -6 0.00013557 3.31509 0.0338838 13 AACAAAGGGTCCATTGTTC TTTTTCTTTGTTTACTTATTTAT + +1 dbcorrdb__CBX3__ENCSR000BRT_1__m3-HP1b-HP1c-HP1e-Su(var)205 -3 0.000145905 3.56782 0.0362789 16 AACAAAGGGTCCATTGTTC CGTTTCTCCATTGTCTTCTG - +1 transfac_public__M00192 -3 0.000153066 3.74291 0.037671 16 AACAAAGGGTCCATTGTTC TGGGTACACTGTGTTCTAG + +1 cisbp__M6474-Sox15 -6 0.000153066 3.74291 0.037671 13 AACAAAGGGTCCATTGTTC GAACCCATTGTTCTTTTCC - +1 neph__UW.Motif.0589 -2 0.000155159 3.79411 0.0378318 16 AACAAAGGGTCCATTGTTC AAAAAGGAATTTTTTC + +1 tfdimers__MD00566 0 0.000155288 3.79725 0.0378318 19 AACAAAGGGTCCATTGTTC ATTTTTTAAATGATTTCTTAATTTTTTTTTAT - +1 taipale_cyt_meth__IRX1_NACGYGNNNNNNCRCGTN_eDBD_meth_repr-ara-caup-mirr 0 0.000161524 3.94974 0.0391533 18 AACAAAGGGTCCATTGTTC TACGCGCAGTAACGCGTT + +1 cisbp__M3359 -3 0.000164503 4.0226 0.0396762 16 AACAAAGGGTCCATTGTTC TGGGTACACTGTGTTCTTG + +1 neph__UW.Motif.0253 -1 0.000167353 4.09228 0.0398931 16 AACAAAGGGTCCATTGTTC CACATGGTGTCTCTGT - +1 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m8-RpII215 0 0.000168469 4.11958 0.0398931 19 AACAAAGGGTCCATTGTTC CAACATTCGGTCATTGGTAG - +1 dbcorrdb__TCF7L2__ENCSR000EUV_1__m3-pan -2 0.000168469 4.11958 0.0398931 17 AACAAAGGGTCCATTGTTC GCCGCCTCCCTTTGATGTGC - +1 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNNNNNYWTTGTNN_CAP_repr-gcm-gcm2 3 0.000168711 4.12548 0.0398931 19 AACAAAGGGTCCATTGTTC ATGCGGGTATATTTTATTGTTT + +1 taipale_tf_pairs__ETV2_SOX15_RSCGGAWNNNNNNNACAATRN_CAP_repr-pnt -10 0.000177424 4.33855 0.0417488 9 AACAAAGGGTCCATTGTTC CCATTGTTTTTGACTTCCGGT - +1 transfac_pro__M03847 -9 0.000178331 4.36074 0.0417586 8 AACAAAGGGTCCATTGTTC CCCTTTGT - +1 swissregulon__hs__SOX2.p2-SoxN -11 0.000181414 4.43611 0.0422751 7 AACAAAGGGTCCATTGTTC CATTGTT - +1 neph__UW.Motif.0372 -2 0.000195671 4.78473 0.0447331 14 AACAAAGGGTCCATTGTTC CAGAAAGTCATTTG - +1 neph__UW.Motif.0484 -7 0.000195671 4.78473 0.0447331 12 AACAAAGGGTCCATTGTTC AGTTCTTTCTTTCC + +1 tfdimers__MD00078-lab-pan -5 0.000202074 4.94132 0.0459791 14 AACAAAGGGTCCATTGTTC ATTTTCCTTTGTTATGCTAATTAGCTGTTTACTT + +1 neph__UW.Motif.0307 -3 0.000204045 4.9895 0.0462095 15 AACAAAGGGTCCATTGTTC AAAAACCACAGGGTG + +1 neph__UW.Motif.0398 -1 0.000209559 5.12434 0.0467991 16 AACAAAGGGTCCATTGTTC AGAGAAATTTTTTTCT - +1 transfac_pro__M02900-Sox14 -7 0.000209559 5.12434 0.0467991 12 AACAAAGGGTCCATTGTTC ATTCCTTTGTCTGTTT - +1 hocomoco__SOX2_HUMAN.H11MO.1.A-CG9650-Mad-SoxN-nej-pan -9 0.000209559 5.12434 0.0467991 10 AACAAAGGGTCCATTGTTC TCCTTTGTTATGCAAA + +1 swissregulon__hs__SOX_8_9_10_.p2-D-Sox100B-Sox102F-SoxN -10 0.000214139 5.23634 0.0476016 9 AACAAAGGGTCCATTGTTC CCATTGTTC - +1 cisbp__M1584-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b -12 0.000222453 5.43964 0.0491418 7 AACAAAGGGTCCATTGTTC ATTGTTTT + +1 dbcorrdb__ARID3A__ENCSR000EDP_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-GATAe-grn-HDAC1-nej-pnr -5 0.000223808 5.47278 0.0491418 14 AACAAAGGGTCCATTGTTC CTTAATCAATGTTTACTTAG - +1 tfdimers__MD00075-foxo 0 0.00022751 5.5633 0.0496585 19 AACAAAGGGTCCATTGTTC TTTTTTTTTTTTTTTGTTTGTTTTTTTTTT - +1 neph__UW.Motif.0244 -3 0.000229606 5.61455 0.0498805 14 AACAAAGGGTCCATTGTTC AAATTTCATTTTGT + +1 transfac_pro__M02909-Sox14 -6 0.000230595 5.63875 0.0498805 13 AACAAAGGGTCCATTGTTC GGAAAAATTGTTAGGAA + +1 cisbp__M6506-pan -8 0.000233894 5.7194 0.0501442 11 AACAAAGGGTCCATTGTTC GCGCTTTGTTCT + +1 swissregulon__sacCer__ROX1-D-Sox100B-Sox102F-SoxN -9 0.000233894 5.7194 0.0501442 10 AACAAAGGGTCCATTGTTC TCCATTGTTCTC + +1 cisbp__M1911 -12 0.000236842 5.7915 0.050329 7 AACAAAGGGTCCATTGTTC ATTGTTTAC - +1 jaspar__MA0084.1 -12 0.000236842 5.7915 0.050329 7 AACAAAGGGTCCATTGTTC ATTGTTTAC - +1 transfac_pro__M02801-Sox14-Sox15 -8 0.000243045 5.94318 0.0514206 11 AACAAAGGGTCCATTGTTC TTCAATTGTTCTAAAA + +1 cisbp__M1960-Mad-SoxN -10 0.000248059 6.0658 0.0516734 8 AACAAAGGGTCCATTGTTC CCTTTGTT + +1 taipale_cyt_meth__SOX18_NACAATGN_eDBD_repr-Sox15 -10 0.000248059 6.0658 0.0516734 8 AACAAAGGGTCCATTGTTC GCATTGTG - +1 transfac_pro__M01923-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.000248059 6.0658 0.0516734 7 AACAAAGGGTCCATTGTTC ATTGTTTT - +1 transfac_pro__M07750-SoxN -10 0.00025925 6.33943 0.0534426 9 AACAAAGGGTCCATTGTTC GCATTGTTCGT - +1 jaspar__MA0143.3-Mad-SoxN -10 0.000276323 6.75693 0.0567198 8 AACAAAGGGTCCATTGTTC CCTTTGTT + +1 neph__UW.Motif.0304 -4 0.000281507 6.88368 0.0572962 15 AACAAAGGGTCCATTGTTC AATTACACATTCTGTG + +1 hocomoco__DMRTB_MOUSE.H11MO.0.C-dmrt99B -5 0.000281507 6.88368 0.0572962 14 AACAAAGGGTCCATTGTTC TTGCTACATTGTATCC + +1 homer__YCTTTGTTCC_Sox4-Sox14-Sox100B-SoxN -10 0.000289081 7.06891 0.0585907 9 AACAAAGGGTCCATTGTTC CCTTTGTTCC + +1 dbcorrdb__JUN__ENCSR000ECA_1__m2-Jra 0 0.000295942 7.23667 0.059378 19 AACAAAGGGTCCATTGTTC AGACACGGCCGCATTCCTGA + +1 neph__UW.Motif.0620 -2 0.000298379 7.29626 0.059378 15 AACAAAGGGTCCATTGTTC CAAAGAAAACAGTGA + +1 tfdimers__MD00493-cnc 0 0.000301581 7.37456 0.059378 19 AACAAAGGGTCCATTGTTC ATAAACTAAATTAATGACTAACTGGCTAATA + +1 taipale_tf_pairs__TEAD4_RFX5_RCATTCNNNNNNNNNNNNNNNNNGCAACN_CAP_repr-sd 7 0.000302729 7.40262 0.059378 19 AACAAAGGGTCCATTGTTC CGTTGCCAAAAAAGGCCAGTTTGGAATGC - +1 neph__UW.Motif.0439 0 0.000302813 7.4047 0.059378 16 AACAAAGGGTCCATTGTTC TGGAAAAAAATCAGTG - +1 hocomoco__SOX2_MOUSE.H11MO.0.A-CG9650-Mad-SoxN-nej-pan -9 0.000302813 7.4047 0.059378 10 AACAAAGGGTCCATTGTTC TCCTTTGTTATGCAAA + +1 neph__UW.Motif.0077-Sox21a-SoxN -11 0.000307483 7.51887 0.0598073 8 AACAAAGGGTCCATTGTTC CATTGTTT - +1 transfac_pro__M07331-vvl -11 0.000307483 7.51887 0.0598073 8 AACAAAGGGTCCATTGTTC ATTTGTTA - +1 taipale_cyt_meth__SOX3_NGAACAATGN_FL_repr-D-Sox21a-Sox21b-SoxN -10 0.000317281 7.75846 0.0614652 9 AACAAAGGGTCCATTGTTC CCATTGTGAG - +1 cisbp__M1599-D-Sox100B-Sox14-Sox15-Sox21a-Sox21b -12 0.000318844 7.7967 0.0615211 7 AACAAAGGGTCCATTGTTC ATTGTTTTC + +1 flyfactorsurvey__br-PA_SOLEXA_FBgn0000210-br -3 0.000321597 7.864 0.0615597 15 AACAAAGGGTCCATTGTTC AAAAAATCAATAGTT - +1 transfac_pro__M08908 -5 0.000321597 7.864 0.0615597 14 AACAAAGGGTCCATTGTTC TTTTTGCCCTGTTCT - +1 yetfasco__YML076C_325 3 0.000324866 7.94395 0.0616959 19 AACAAAGGGTCCATTGTTC CCGAAAAAAAAAAAAAAAAAAAAAAACGG + +1 tfdimers__MD00478-Sox100B -6 0.000340627 8.32934 0.0644031 13 AACAAAGGGTCCATTGTTC AAAAACTTTGTGGGAATAAAAT + +1 cisbp__M1593-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.000341791 8.35782 0.0644031 7 AACAAAGGGTCCATTGTTC ATTGTTTT + +1 dbcorrdb__MYC__ENCSR000DOM_1__m3-Myc-nej-Stat92E -3 0.000363833 8.8968 0.0680248 16 AACAAAGGGTCCATTGTTC CAGCGGGTGATTGCATAATG + +1 dbcorrdb__POU5F1__ENCSR000BMU_1__m1-CG9650-D-Mad-nej-nub-pan-pdm2-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN-vvl -7 0.000363833 8.8968 0.0680248 12 AACAAAGGGTCCATTGTTC ATTCCTTTGTTATGCAAATT + +1 cisbp__M6129-CG9650-Mad-nej-pan-SoxN -10 0.000373201 9.12588 0.0695069 9 AACAAAGGGTCCATTGTTC CCATTGTTATGCAAA - +1 transfac_pro__M01183 1 0.000376173 9.19855 0.0695236 15 AACAAAGGGTCCATTGTTC TTTCTTGGAATTCTTT + +1 predrem__nrMotif276 -9 0.000381427 9.32702 0.0702255 10 AACAAAGGGTCCATTGTTC ACCTTTGTTT + +1 transfac_pro__M07431-Sox14 -8 0.000392571 9.59953 0.0720025 11 AACAAAGGGTCCATTGTTC GCTCTTTGTTTT + +1 tfdimers__MD00397 17 0.000399328 9.76477 0.0729645 19 AACAAAGGGTCCATTGTTC ACTGGGTCACAGTGGATACCAAGGAGTCAATAGTTGTTAACCACTGGGTCACAGTGGTTACCGAGGAG + +1 tfdimers__MD00353-Jra-kay-Sox14 -5 0.000429539 10.5035 0.0779768 14 AACAAAGGGTCCATTGTTC TTTTTCCTTTGTTGACTCATTGTTTTTAA + +1 neph__UW.Motif.0588 0 0.000432485 10.5756 0.0779768 15 AACAAAGGGTCCATTGTTC CAGAAATAATTCATT - +1 neph__UW.Motif.0509 -2 0.000434008 10.6128 0.0779768 16 AACAAAGGGTCCATTGTTC TCAATTTTTTTTTCTC - +1 taipale_tf_pairs__TEAD4_SOX15_NACAATRNNNNNGAATGY_CAP_repr-sd 0 0.000434126 10.6157 0.0779768 18 AACAAAGGGTCCATTGTTC ACATTCCTTTCCATTGTT - +1 taipale_cyt_meth__SOX10_AACAATNNNNNATTGTT_eDBD_repr-Sox100B -1 0.000436459 10.6727 0.0779768 17 AACAAAGGGTCCATTGTTC AACAATGGGCCATTGTT + +1 predrem__nrMotif286 -9 0.000457342 11.1834 0.0814061 10 AACAAAGGGTCCATTGTTC TTCATTGTTT - +1 transfac_pro__M02246-CG9650-nej-pan-SoxN -10 0.000465331 11.3788 0.0824103 9 AACAAAGGGTCCATTGTTC CCTTTGTTATGCAAA + +1 transfac_pro__M07319-fd59A -11 0.0004664 11.4049 0.0824103 8 AACAAAGGGTCCATTGTTC CTTTGTTT - +1 dbcorrdb__CEBPZ__ENCSR000EDO_1__m2-CG7839 0 0.000477298 11.6714 0.0837786 19 AACAAAGGGTCCATTGTTC TACCCTGCTTTGATTGGTTA - +1 cisbp__M1616 -9 0.00048122 11.7673 0.0837786 10 AACAAAGGGTCCATTGTTC ATTATTGTTTA - +1 tfdimers__MD00285-Mad -4 0.000482828 11.8066 0.0837786 15 AACAAAGGGTCCATTGTTC TTTTTTCCTTTGTTTAATGTTTTTTTT - +1 neph__UW.Motif.0193 -2 0.000498732 12.1955 0.0851423 14 AACAAAGGGTCCATTGTTC AAAAAAAGGCTCTG + +1 neph__UW.Motif.0431 -6 0.000500102 12.229 0.0851423 13 AACAAAGGGTCCATTGTTC GGAATCAGTTTTTTCA + +1 cisbp__M1609 -10 0.000500314 12.2342 0.0851423 9 AACAAAGGGTCCATTGTTC CTATTGTTTT - +1 cisbp__M1602-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.000500314 12.2342 0.0851423 7 AACAAAGGGTCCATTGTTC ATTGTTCTGC + +1 neph__UW.Motif.0273 -5 0.000500502 12.2388 0.0851423 14 AACAAAGGGTCCATTGTTC AGGAAGCTCTGCTTT - +1 hocomoco__GBX2_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG9876-CG18599-CG34367-Dll-Dr-E5-Lim3-OdsH-Pph13-Vsx1-Vsx2-ems-en-eve-ind-inv-lab-lbe-lms-pb-ro-unpg 0 0.000501278 12.2577 0.0851423 17 AACAAAGGGTCCATTGTTC AATTAAAGGCTAATTAG - +1 dbcorrdb__TCF12__ENCSR000BJG_1__m1-bin-croc-fkh-foxo-HDAC1-nej -5 0.00051046 12.4823 0.0861765 14 AACAAAGGGTCCATTGTTC CCAAGCCTCTGTTTACTTAG + +1 transfac_pro__M04664-foxo -6 0.000512107 12.5226 0.0861765 13 AACAAAGGGTCCATTGTTC GGTATTGTTGTTTTGGTGCTTA - +1 tfdimers__MD00516-Sox100B -6 0.000512726 12.5377 0.0861765 13 AACAAAGGGTCCATTGTTC ATTAAAATTGTGTAATTGTATAT + +1 dbcorrdb__SREBF2__ENCSR000DYT_1__m8-SREBP 3 0.000545775 13.3458 0.0906711 17 AACAAAGGGTCCATTGTTC GGGAAAAACTGAGACCTCGT + +1 dbcorrdb__TCF7L2__ENCSR000EWT_1__m1-pan -4 0.000545775 13.3458 0.0906711 15 AACAAAGGGTCCATTGTTC CCGGTTCCTTTGATGTTTCT + +1 predrem__nrMotif450 -10 0.000546986 13.3755 0.0906711 9 AACAAAGGGTCCATTGTTC GCATTGTTTT + +1 cisbp__M1589-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.000546986 13.3755 0.0906711 7 AACAAAGGGTCCATTGTTC ATTGTTCTGC - +1 tfdimers__MD00149-Hnf4-svp 2 0.000565252 13.8221 0.0930592 19 AACAAAGGGTCCATTGTTC AAAATTAAGGTCCATCTGTTCTTTTTTTT + +1 neph__UW.Motif.0516 -4 0.000578435 14.1445 0.0941158 15 AACAAAGGGTCCATTGTTC AAAACTTCCCTCTCC + +1 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m3-Spt20 0 0.000583375 14.2653 0.0941158 19 AACAAAGGGTCCATTGTTC CTCATTACGCTTCTTTTCTG + +1 dbcorrdb__TCF7L2__ENCSR000EUY_1__m1-pan -3 0.000583375 14.2653 0.0941158 16 AACAAAGGGTCCATTGTTC AGCGGTCCCTTTGATGTTTC - +1 dbcorrdb__NFIC__ENCSR000BQX_1__m2-HDAC1-Hnf4-nej-pan-svp-usp -4 0.000583375 14.2653 0.0941158 15 AACAAAGGGTCCATTGTTC AAATGGACTTTGATCTTTTT - +1 dbcorrdb__TCF7L2__ENCSR000EUV_1__m1-pan -4 0.000583375 14.2653 0.0941158 15 AACAAAGGGTCCATTGTTC CCGGTCCCTTTGATGTCGCC - +1 taipale_tf_pairs__ETV2_SOX15_RSCGGAWNNNNNNACAATRN_CAP_repr-pnt -10 0.000583375 14.2653 0.0941158 9 AACAAAGGGTCCATTGTTC CTATTGTTCTTACTTCCGGT - +1 neph__UW.Motif.0179 -3 0.000595744 14.5677 0.0957908 12 AACAAAGGGTCCATTGTTC AAAATTTCCTTT - +1 hocomoco__VENTX_HUMAN.H11MO.0.D-B-H1-B-H2-CG34367-Dr-en-exex-ind-inv-unpg 0 0.00061218 14.9696 0.0981066 19 AACAAAGGGTCCATTGTTC AATTAGAAACCAATTAGCG - +1 hocomoco__TCF7_MOUSE.H11MO.0.A-Sox14-Sox100B-SoxN-pan -6 0.000617139 15.0909 0.0985738 13 AACAAAGGGTCCATTGTTC GTTTCCTTTGATCTTT - +1 transfac_pro__M07332-vvl -12 0.00063017 15.4095 0.100323 7 AACAAAGGGTCCATTGTTC TTTGTTTA - +1 neph__UW.Motif.0636 -4 0.000642648 15.7147 0.101973 13 AACAAAGGGTCCATTGTTC CATTTCCCATTGG - +1 transfac_public__M00042-Sox102F -10 0.000652622 15.9586 0.102456 9 AACAAAGGGTCCATTGTTC GTATTGTTAA - +1 taipale_tf_pairs__SOX6_TBX21_RRGTGTNNNNNNNNACAATRN_CAP_repr-Sox102F -10 0.000654026 15.9929 0.102456 9 AACAAAGGGTCCATTGTTC CCATTGTTTTATTTAACACCT - +1 taipale_tf_pairs__TEAD4_SOX6_NNACAATNNNNNNGAATGY_CAP_repr-sd-Sox102F 0 0.000654186 15.9968 0.102456 19 AACAAAGGGTCCATTGTTC ACATTCCATTCCATTGTTC - +1 homer__VAGRACAKNCTGTBC_PR-Hsf-fkh -4 0.000667611 16.3251 0.103884 15 AACAAAGGGTCCATTGTTC CAGAACAGTCTGTTC + +1 tfdimers__MD00306 6 0.000694339 16.9787 0.107007 19 AACAAAGGGTCCATTGTTC AATAAAAAAAATTACGTAATTTTTTTTATA + +1 hocomoco__NANOG_MOUSE.H11MO.0.A-CG9650-Mad-SoxN-nej-nub-pan-pdm2 -9 0.000705003 17.2394 0.108304 10 AACAAAGGGTCCATTGTTC TCCTTTGTTATGCAAAT + +1 dbcorrdb__BCL11A__ENCSR000BHA_1__m2-Bgb-Bro-CG9650-ebi-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E -1 0.000711288 17.3931 0.108723 18 AACAAAGGGTCCATTGTTC AAATTTAGTCTGTGGTTTGT - +1 cisbp__M3913-Sox102F -10 0.000712237 17.4163 0.108723 9 AACAAAGGGTCCATTGTTC GTATTGTTAA - +1 neph__UW.Motif.0255 -2 0.000724574 17.718 0.110258 14 AACAAAGGGTCCATTGTTC CAGATGGATTCTTG - +1 taipale_tf_pairs__TEAD4_RFX5_RCATTCNNNNNNNNNNNNNNNNGCAACN_CAP_repr-sd 6 0.000734259 17.9548 0.11138 19 AACAAAGGGTCCATTGTTC CGTTGCCGAAATAGGGCATTTGGAATGT - +1 cisbp__M6475-CG9650-nej-nub-pdm2-SoxN -10 0.000759462 18.5711 0.113421 9 AACAAAGGGTCCATTGTTC CCATTGTTATGCAAAT - +1 dbcorrdb__MAFK__ENCSR000EDZ_1__m2-maf-S 0 0.000759472 18.5714 0.113421 19 AACAAAGGGTCCATTGTTC TACTACTGACCGTTTGCAAA + +1 dbcorrdb__CUX1__ENCSR000EFO_1__m5-CG7839-ct-CTCF 0 0.000759472 18.5714 0.113421 19 AACAAAGGGTCCATTGTTC AAAAAAAAATTTTTTTTTTT - +1 dbcorrdb__TBP__ENCSR000EEL_1__m4-Tbp 1 0.000759472 18.5714 0.113421 19 AACAAAGGGTCCATTGTTC GGCTATAAAAGGCTGCGCTC - +1 dbcorrdb__GTF2B__ENCSR000DOE_1__m1-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha -1 0.000759472 18.5714 0.113421 18 AACAAAGGGTCCATTGTTC GCGCCGCGCCTTTTATAGGC - +1 tfdimers__MD00244-Hsf 0 0.000791515 19.3549 0.117312 19 AACAAAGGGTCCATTGTTC TTTAATGGGAACCTTCTGTTCTTTTTATT - +1 tfdimers__MD00533-nub-pdm2 -3 0.000791515 19.3549 0.117312 16 AACAAAGGGTCCATTGTTC TAATTTCTGATTGATATGCAAATGAAATT + +1 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNCAATTN_FL_meth_repr-C15 5 0.000796299 19.4719 0.117312 16 AACAAAGGGTCCATTGTTC TAATTGGTTAAGATTCAATTA + +1 transfac_pro__M01737-SoxN -7 0.000800119 19.5653 0.117312 11 AACAAAGGGTCCATTGTTC TTCCTATTGTT + +1 taipale_cyt_meth__SOX12_ACCGAACAATN_eDBD_meth-Sox14 -11 0.000800119 19.5653 0.117312 8 AACAAAGGGTCCATTGTTC CATTGTTCGGT - +1 dbcorrdb__NR3C1__ENCSR000BJC_1__m2 -3 0.000810704 19.8241 0.11779 16 AACAAAGGGTCCATTGTTC AAGGCAAGGAATGTTCCCTG + +1 dbcorrdb__STAT3__ENCSR000DZV_1__m3-Bgb-Bro-CG9650-lz-run-RunxA-RunxB-Stat92E -4 0.000810704 19.8241 0.11779 15 AACAAAGGGTCCATTGTTC AATTCCACTCTGTGGTTTTT - +1 dbcorrdb__EP300__ENCSR000BKK_1__m2-nej-SoxN -6 0.000810704 19.8241 0.11779 13 AACAAAGGGTCCATTGTTC CCCCCCTTTGTCATGCAAAT - +1 transfac_pro__M04644-CHES-1-like-fd59A-FoxK-foxo-FoxP-slp2 -6 0.000813737 19.8983 0.117876 13 AACAAAGGGTCCATTGTTC AATGCAATTGTTTACAATATTC - +1 neph__UW.Motif.0104-Dif -3 0.000825766 20.1925 0.118904 15 AACAAAGGGTCCATTGTTC AAAAAATTATTTCCT + +1 transfac_pro__M07599-arm -11 0.000843154 20.6177 0.121047 8 AACAAAGGGTCCATTGTTC CTTTGATG + +1 cisbp__M1169 -9 0.000846871 20.7085 0.12122 10 AACAAAGGGTCCATTGTTC TTGATTGGTT - +1 cisbp__M6260-fkh-Hsf -3 0.000849676 20.7771 0.121261 16 AACAAAGGGTCCATTGTTC CCGGGACAGTCTGTTCTC + +1 dbcorrdb__SIN3A__ENCSR000BPB_1__m2-Sin3A 1 0.000865162 21.1558 0.122745 19 AACAAAGGGTCCATTGTTC CCGAAGTGATACCGCTGTCA - +1 dbcorrdb__SP1__ENCSR000BJX_1__m1-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp -3 0.000865162 21.1558 0.122745 16 AACAAAGGGTCCATTGTTC CCCCTGGACTTTGGCCTCTG - +1 taipale_tf_pairs__POU2F1_SOX15_NNNGMATAACAAWRRN_CAP_repr-nub-pdm2 -9 0.000870825 21.2943 0.123186 10 AACAAAGGGTCCATTGTTC TCCATTGTTATGCATG - +1 transfac_pro__M07035-arm -6 0.000885835 21.6613 0.124434 13 AACAAAGGGTCCATTGTTC GCTCTCTTTGATGAT + +1 transfac_pro__M02906-SoxN -7 0.000885835 21.6613 0.124434 12 AACAAAGGGTCCATTGTTC CTATAATTGTTATCG + +1 cisbp__M5169-brm-hb-jim-rn-sqz 0 0.000894582 21.8752 0.12508 19 AACAAAGGGTCCATTGTTC GGTTTTTGGTGTTTTTTTTGTGTGG - +1 hocomoco__DMRT1_HUMAN.H11MO.0.D-dmrt99B -5 0.000921378 22.5305 0.128314 14 AACAAAGGGTCCATTGTTC TTGCTACATTGTATCAA - +1 dbcorrdb__CBX3__ENCSR000BRT_1__m8-HP1b-HP1c-HP1e-Su(var)205 2 0.000923035 22.571 0.128314 18 AACAAAGGGTCCATTGTTC GAAAGGGCGGGTGGTCTGTG - +1 transfac_pro__M04666-FoxP -6 0.000928898 22.7143 0.128758 13 AACAAAGGGTCCATTGTTC TATGTTTTTGTTGTGACCATGAA - +1 tfdimers__MD00318-Hnf4-svp 18 0.000951981 23.2788 0.13158 19 AACAAAGGGTCCATTGTTC AATTTAAAAATTAACCTTACATCCAACCTCACCCCTTATT + +1 tfdimers__MD00104-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-Sox14 3 0.000984241 24.0676 0.13468 19 AACAAAGGGTCCATTGTTC TTTTTATTTCCTTCCTTTGTTTTTTT + +1 dbcorrdb__FOXA1__ENCSR000BPX_1__m1-fkh-Hsf 0 0.00098452 24.0745 0.13468 19 AACAAAGGGTCCATTGTTC TAAAAAGAACATACTGTTCT + +1 transfac_pro__M04647-jumu -2 0.000988374 24.1687 0.13468 17 AACAAAGGGTCCATTGTTC ACAATGATTGTTTGTTCGAGGC - +1 taipale_tf_pairs__MYBL1_MAX_YAACGGNNNNNNNNNNCACGTG_CAP_repr-Max-Myb 6 0.000988374 24.1687 0.13468 16 AACAAAGGGTCCATTGTTC CACGTGCTCCAGGCAACCGTTA - +1 hocomoco__SOX21_HUMAN.H11MO.0.D-D-Sox14-Sox15-Sox21a-Sox21b-Sox100B-Sox102F-SoxN-bbx-peng -3 0.000997326 24.3876 0.135517 16 AACAAAGGGTCCATTGTTC AACAATACCATTGTTT - +1 tfdimers__MD00549 -2 0.0010349 25.3063 0.140227 17 AACAAAGGGTCCATTGTTC TAAAAAAGATGCTGTTAATGATTAACTTTA + +1 dbcorrdb__SETDB1__ENCSR000EYD_1__m6-egg -3 0.00104983 25.6714 0.141852 16 AACAAAGGGTCCATTGTTC AAGAGAAACCTTATTAACCA + +1 cisbp__M1588-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN -12 0.00107172 26.2069 0.144406 7 AACAAAGGGTCCATTGTTC ATTGTTTTC + +1 flyfactorsurvey__rn_SOLEXA_5_FBgn0259172-brm-hb-jim-rn-sqz 0 0.00108691 26.5783 0.145639 19 AACAAAGGGTCCATTGTTC GGTTTTTGGTGTTTTTTTTGTGTGG - +1 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNNNNNCAATTN_eDBD_repr-C15 9 0.00108691 26.5783 0.145639 16 AACAAAGGGTCCATTGTTC TAATTGCTCTTAATAGCGGCAATTA - +1 taipale_tf_pairs__FLI1_DLX2_RSCGGAANNNNNYAATTAN_CAP -1 0.00110178 26.9419 0.146816 18 AACAAAGGGTCCATTGTTC TTAATTGCTCATTTCCGGT - +1 dbcorrdb__SETDB1__ENCSR000EWI_1__m6-egg -3 0.00111917 27.3671 0.147503 16 AACAAAGGGTCCATTGTTC GGTGCCTCCATTCTGCGGTG + +1 dbcorrdb__CEBPD__ENCSR000BQJ_1__m1-CG7786-CrebB-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 -6 0.00111917 27.3671 0.147503 13 AACAAAGGGTCCATTGTTC GCGGCGATTGCGCAACCGCC - +1 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNNNCAATTN_eDBD_meth_repr-C15-CG34367-gsb-gsb-n-prd-unpg 7 0.00112689 27.5558 0.147661 16 AACAAAGGGTCCATTGTTC TAATTGCTTTTTATAATCAATTA - +1 swissregulon__hs__HBP1_HMGB_SSRP1_UBTF.p2-D-Ssrp -12 0.00112955 27.6209 0.147661 6 AACAAAGGGTCCATTGTTC ATTGTT + +1 transfac_pro__M03854 -13 0.00112955 27.6209 0.147661 6 AACAAAGGGTCCATTGTTC TTGTTT + +1 hocomoco__SOX11_HUMAN.H11MO.0.D-D-Sox14-Sox15-Sox21a-Sox21b-Sox100B-Sox102F-SoxN -3 0.00114085 27.8973 0.148735 16 AACAAAGGGTCCATTGTTC AACAATGCAATTGTTC + +1 swissregulon__hs__SRY.p2 -12 0.00117077 28.6288 0.149448 7 AACAAAGGGTCCATTGTTC ATTGTTTAC - +1 tfdimers__MD00211-pho-phol 0 0.00117387 28.7047 0.149448 19 AACAAAGGGTCCATTGTTC CTGCTGTCAACATATGGTGACCAGCTGTTTGC - +1 tfdimers__MD00264-CG5846-Rfx 2 0.00117453 28.7208 0.149448 19 AACAAAGGGTCCATTGTTC ATTTCTGGGTAGCATCTGTTCTTGTTTTT + +1 hocomoco__BARH2_HUMAN.H11MO.0.D-B-H1-B-H2-CG34367-en-inv-unpg 0 0.00117652 28.7695 0.149448 18 AACAAAGGGTCCATTGTTC CAATTAGGACCAATTAGC - +1 taipale_tf_pairs__ERF_DLX3_RSCGGAANNNNNYAATTA_CAP-Ets21C -2 0.00117652 28.7695 0.149448 17 AACAAAGGGTCCATTGTTC TAATTGCCCATTTCCGGT - +1 transfac_pro__M01099-kni -4 0.00117652 28.7695 0.149448 15 AACAAAGGGTCCATTGTTC TGTGTTCCATTTTTTTAG - +1 transfac_pro__M07605-pan -9 0.00118281 28.9233 0.149448 10 AACAAAGGGTCCATTGTTC CCCTTTGATGCTG - +1 cisbp__M0891-bsh-C15-lab -1 0.00118959 29.0892 0.149448 10 AACAAAGGGTCCATTGTTC TTAATTGGTT + +1 cisbp__M1380 -9 0.00118959 29.0892 0.149448 10 AACAAAGGGTCCATTGTTC CTTATCGTTT - +1 transfac_pro__M01022-pan -9 0.00118959 29.0892 0.149448 10 AACAAAGGGTCCATTGTTC CCCTTTGATC - +1 cisbp__M1421 -10 0.00118959 29.0892 0.149448 9 AACAAAGGGTCCATTGTTC TTTTTGTGTC + +1 dbcorrdb__MYBL2__ENCSR000BRO_1__m3-Hnf4 -1 0.00119279 29.1673 0.149448 18 AACAAAGGGTCCATTGTTC CCCGTAGCTCAAAGGTCAAC - +1 yetfasco__YCL058C_1417 3 0.00119279 29.1673 0.149448 17 AACAAAGGGTCCATTGTTC TGTAAAAAAAAAAAAAATAT + +1 transfac_pro__M00955 1 0.00122217 29.8857 0.152545 19 AACAAAGGGTCCATTGTTC GTTTTGGGTACATAGTGTTCTAGGGTA + +1 cisbp__M6476-Sox14 -9 0.00122384 29.9265 0.152545 10 AACAAAGGGTCCATTGTTC CGCTTTGTTCTC - +1 jaspar__MA0087.1-Sox102F -12 0.00124464 30.4351 0.154627 7 AACAAAGGGTCCATTGTTC ATTGTTA + +1 transfac_pro__M01016-Sox15 -12 0.00124695 30.4917 0.154627 6 AACAAAGGGTCCATTGTTC ATTGTT - +1 dbcorrdb__CHD1__ENCSR000AQK_1__m3-Chd1 -4 0.00127092 31.0779 0.157196 15 AACAAAGGGTCCATTGTTC CAGTATCGTTTTTCGCGGTT - +1 transfac_pro__M07840-bs-bsh-CG9876-en-inv-Vsx2 -2 0.00129256 31.607 0.158753 14 AACAAAGGGTCCATTGTTC TAATTGGGTAATTG - +1 taipale_cyt_meth__SOX14_CCGAACAATN_FL_meth-D-Sox21a-Sox21b -11 0.00129339 31.6272 0.158753 8 AACAAAGGGTCCATTGTTC CATTGTTCGG - +1 jaspar__MA0371.1-D-Sox100B -9 0.00132268 32.3435 0.161526 10 AACAAAGGGTCCATTGTTC CCCATTGTTCTC + +1 hocomoco__DLX6_HUMAN.H11MO.0.D-CG34367-Dll-en-inv-unpg -1 0.00134099 32.7912 0.162747 15 AACAAAGGGTCCATTGTTC AAATTAAGGTAATTA - +1 cisbp__M1896 11 0.0013428 32.8354 0.162747 19 AACAAAGGGTCCATTGTTC GGGGGGGGAGTGGAGTATGGGAAATTTTTC + +1 dbcorrdb__TCF7L2__ENCSR000EWT_1__m2-foxo-pan -2 0.00135383 33.1051 0.16336 17 AACAAAGGGTCCATTGTTC CCGCGGCCTGTTTGCTCTGC - +1 tfdimers__MD00577-pan 0 0.00135838 33.2165 0.16336 19 AACAAAGGGTCCATTGTTC TTTTTTTTTTGCATTTTGATGTTTTT - +1 taipale_tf_pairs__GCM1_SOX2_RTRSGGGNNNATTGTKY_CAP_repr-gcm-gcm2-SoxN -2 0.00136511 33.3811 0.16336 17 AACAAAGGGTCCATTGTTC ATGCGGGTGCATTGTTC + +1 taipale_cyt_meth__POU3F1_TAATTNNNNNNNAATTA_eDBD_meth-vvl 1 0.00136511 33.3811 0.16336 16 AACAAAGGGTCCATTGTTC TAATTACCCGTTAATTA + +1 cisbp__M1914-Sox102F -12 0.00136818 33.456 0.16336 7 AACAAAGGGTCCATTGTTC ATTGTTT - +1 hocomoco__LEF1_HUMAN.H11MO.0.A-Mad-SoxN-pan -9 0.00138735 33.9248 0.164833 10 AACAAAGGGTCCATTGTTC TCCTTTGATTTGCT + +1 cisbp__M1590-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b -12 0.00139423 34.093 0.165243 7 AACAAAGGGTCCATTGTTC ATTGTTTTA + +1 transfac_pro__M08948-pan -8 0.00140552 34.3691 0.165767 10 AACAAAGGGTCCATTGTTC TTCCTTTGAT + +1 cisbp__M0985-ara-caup-mirr -10 0.00140552 34.3691 0.165767 9 AACAAAGGGTCCATTGTTC ATCATGTAAT + +1 tfdimers__MD00558-E(bx) -2 0.00142542 34.8558 0.167704 17 AACAAAGGGTCCATTGTTC TTTTTTTTTTGTTTTGTTTGCATTTTTTT - +1 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m2-RpII215 -3 0.00144177 35.2556 0.169215 16 AACAAAGGGTCCATTGTTC TATCTGCTCTTGGGTGGAAA - +1 tfdimers__MD00250-GATAe-grn-pho-phol-pnr-srp 0 0.00145177 35.5001 0.169975 19 AACAAAGGGTCCATTGTTC ATATAGTTAAAAAATGGAGATAAAAGATAAGAATTA - +1 transfac_pro__M07975-bbx-D-fd59A-fkh-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -2 0.00145615 35.6073 0.170075 17 AACAAAGGGTCCATTGTTC AAACAATAACATTGTTT - +1 neph__UW.Motif.0310 -2 0.00148764 36.3772 0.1725 16 AACAAAGGGTCCATTGTTC AGAAAATTTCCATCTG + +1 neph__UW.Motif.0392 0 0.00148764 36.3772 0.1725 16 AACAAAGGGTCCATTGTTC AAGTCTGGATTCTCTG + +1 neph__UW.Motif.0629 -1 0.00148764 36.3772 0.1725 16 AACAAAGGGTCCATTGTTC GAAAAGCAGCATCTGG - +1 swissregulon__hs__SOX5.p2-Sox15-Sox102F-SoxN -12 0.0015026 36.743 0.173401 7 AACAAAGGGTCCATTGTTC ATTGTTT - +1 transfac_pro__M03848-Sox15 -9 0.0015026 36.743 0.173401 7 AACAAAGGGTCCATTGTTC GCCATTG - +1 hocomoco__NKX61_HUMAN.H11MO.0.B-Dr-HGTX-ind 0 0.00151321 37.0026 0.173795 19 AACAAAGGGTCCATTGTTC CATTAAATTCCCATTAATC - +1 hocomoco__IRX2_HUMAN.H11MO.0.D-ara-caup-mirr -1 0.00151321 37.0026 0.173795 18 AACAAAGGGTCCATTGTTC ACATGGGTGGGCATGTTGG + +1 dbcorrdb__POLR3A__ENCSR000DOI_1__m5-CG17209 1 0.00153503 37.5361 0.174549 19 AACAAAGGGTCCATTGTTC AGCGCACGTCGGTTTAGCTC - +1 dbcorrdb__RFX5__ENCSR000EFD_1__m3-kay-Mes4-Nf-YA-Nf-YB-Nf-YC -2 0.00153503 37.5361 0.174549 17 AACAAAGGGTCCATTGTTC GAGGGTTCTGATTGGCTGGT - +1 dbcorrdb__POLR2A__ENCSR000AKZ_1__m1-ebi-GATAe-grn-pan-pnr-RpII215-srp -3 0.00153503 37.5361 0.174549 16 AACAAAGGGTCCATTGTTC GGCGCCGCCCTTATCTGCCC - +1 dbcorrdb__RAD21__ENCSR000EDE_1__m2-CTCF-SMC3-vtd -3 0.00153503 37.5361 0.174549 16 AACAAAGGGTCCATTGTTC AAAAGCGCCTTTTGGTGGTT - +1 tfdimers__MD00381-Sox100B -6 0.00154149 37.6941 0.174549 13 AACAAAGGGTCCATTGTTC TTTAACATTGTACAATGTTATA + +1 taipale_tf_pairs__ERF_PITX1_NSCGGANNNNNGGMTTA_CAP-Ets21C-Ptx1 -2 0.00155284 37.9716 0.175422 17 AACAAAGGGTCCATTGTTC TAATCCCCACTTCCGGT - +1 neph__UW.Motif.0644 0 0.00158855 38.8448 0.178277 16 AACAAAGGGTCCATTGTTC TGAAAACAAAAATTTG - +1 neph__UW.Motif.0260 -4 0.0015892 38.8608 0.178277 13 AACAAAGGGTCCATTGTTC CCAGATCCAGTGT - +1 dbcorrdb__CTCF__ENCSR000ALJ_1__m2-CTCF-SMC3-vtd 1 0.00163391 39.954 0.181684 19 AACAAAGGGTCCATTGTTC GGCCATATGGGGAACTGCAG - +1 dbcorrdb__SREBF2__ENCSR000DYT_1__m3-SREBP -2 0.00163391 39.954 0.181684 17 AACAAAGGGTCCATTGTTC AAGAGGTTTCACCGTGGTTC - +1 tfdimers__MD00291-foxo-pho-phol -5 0.00164084 40.1234 0.181684 14 AACAAAGGGTCCATTGTTC TTTTTCCATTGTTTTTTTTTTA - +1 cisbp__M0663 -8 0.00165724 40.5244 0.181684 10 AACAAAGGGTCCATTGTTC TCACTTTTTG - +1 cisbp__M0939-Antp-B-H1-B-H2-bsh-CG11085-Dfd-eve-ftz-pb-Scr-slou-Ubx-unpg-zen2 -8 0.00165724 40.5244 0.181684 10 AACAAAGGGTCCATTGTTC AGCAATTAGC - +1 jaspar__MA0987.1 -8 0.00165724 40.5244 0.181684 10 AACAAAGGGTCCATTGTTC TCACTTTTTG - +1 transfac_pro__M02033-pan -8 0.00165724 40.5244 0.181684 10 AACAAAGGGTCCATTGTTC GTCCTTTGAT - +1 neph__UW.Motif.0117 -3 0.00171197 41.8629 0.18726 14 AACAAAGGGTCCATTGTTC AGCCCTTCCTCTGG + +1 transfac_pro__M07896-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 7 0.00173465 42.4175 0.1889 19 AACAAAGGGTCCATTGTTC AGGTGTGAAATGTGGCGGGGAGGTGTGAAG + +1 dbcorrdb__BCL11A__ENCSR000BIP_1__m6-CG9650-SoxN -7 0.00173872 42.517 0.1889 12 AACAAAGGGTCCATTGTTC ACTCTTTTGTTATGCAGCTT + +1 cisbp__M2101-CHES-1-like-croc-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -7 0.00173872 42.517 0.1889 12 AACAAAGGGTCCATTGTTC TCCTCTTTGTTTACAATTCA - +1 taipale_tf_pairs__CUX1_SOX15_NATCRATNNNNNNNNAACAATRS_CAP_repr-ct -10 0.00175258 42.8559 0.189143 9 AACAAAGGGTCCATTGTTC CCATTGTTCTACGGGTATTGATC - +1 cisbp__M1592-Sox100B-SoxN -12 0.00175487 42.912 0.189143 7 AACAAAGGGTCCATTGTTC ATTGTTTT - +1 cisbp__M6134-CG9650-nej-pan-SoxN-vvl -10 0.00175697 42.9632 0.189143 9 AACAAAGGGTCCATTGTTC CCATTGTTATGCAAA - +1 hocomoco__GBX1_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG18599-CG34367-Dbx-Dll-Dr-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ems-en-eve-exex-gsb-gsb-n-ind-inv-lab-lbe-lms-otp-pdm3-prd-repo-ro-un 0 0.00176448 43.1469 0.189143 17 AACAAAGGGTCCATTGTTC AAATTTTAGCTAATTAG - +1 cisbp__M4509-CG9650-Mad-nej-nub-pan-pdm2-SoxN -9 0.00176448 43.1469 0.189143 10 AACAAAGGGTCCATTGTTC TCCTTTGTTATGCAAAT - +1 transfac_pro__M02855 -9 0.00176448 43.1469 0.189143 10 AACAAAGGGTCCATTGTTC TCCTTTGTTTTGGTGTT - +1 cisbp__M0659 -8 0.00179815 43.97 0.191475 10 AACAAAGGGTCCATTGTTC TTACTTTTTG - +1 jaspar__MA1022.1 -8 0.00179815 43.97 0.191475 10 AACAAAGGGTCCATTGTTC TCACTTTTTG - +1 taipale_cyt_meth__SOX14_CCGAACAATN_FL_repr-D-Sox21a-Sox21b -11 0.00179815 43.97 0.191475 8 AACAAAGGGTCCATTGTTC CATTGTTCGG - +1 tfdimers__MD00072-ara-caup-mirr 0 0.00181383 44.3537 0.19272 19 AACAAAGGGTCCATTGTTC TATTAATTTTTACATGTTTAGACATGTCTAAATA + +1 hocomoco__NKX61_MOUSE.H11MO.0.A-Dr-HGTX-ind 0 0.00182495 44.6254 0.193475 19 AACAAAGGGTCCATTGTTC ATTAATGGGATTTTAATTA + +1 transfac_pro__M01594-Mad-pan-SoxN -10 0.0018378 44.9397 0.194399 9 AACAAAGGGTCCATTGTTC CCTTTGTTTTGTT + +1 dbcorrdb__EP300__ENCSR000AQB_1__m8-nej -1 0.00184979 45.2329 0.194399 18 AACAAAGGGTCCATTGTTC AAAAAGCATGCGTAGCGAGG + +1 dbcorrdb__RAD21__ENCSR000BLY_1__m2-CTCF-vtd -2 0.00184979 45.2329 0.194399 17 AACAAAGGGTCCATTGTTC AAAGACACCTAGTGGTAAAA + +1 transfac_pro__M04669-bin-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -6 0.00185772 45.4269 0.194809 13 AACAAAGGGTCCATTGTTC TGTGTACTTGTTTACAGCTGGA - +1 transfac_pro__M02016-btd-EcR-eg-HDAC1-Hnf4-kni-knrl-nej-Spps-svp-usp -4 0.00187831 45.9303 0.19654 15 AACAAAGGGTCCATTGTTC AATTGAACTTTGGCC - +1 neph__UW.Motif.0210 -6 0.00193096 47.2178 0.200743 13 AACAAAGGGTCCATTGTTC CAGATTCTGGTGTTGA + +1 transfac_pro__M02797-Sox102F-Sox14 -7 0.00193096 47.2178 0.200743 12 AACAAAGGGTCCATTGTTC AATTTATTGTTCTTAA - +1 cisbp__M2176-D-Sox100B -9 0.00193745 47.3764 0.200984 10 AACAAAGGGTCCATTGTTC CCCATTGTTCTC - +1 cisbp__M1089-bsh-Dr-inv-lab-pb-Ubx-unpg -8 0.00195003 47.6841 0.201071 10 AACAAAGGGTCCATTGTTC ACCAATTAAC - +1 tfdimers__MD00462-Sox100B-zfh1 -6 0.00196363 48.0167 0.201071 13 AACAAAGGGTCCATTGTTC ATTTCCTTTGTGGTTTCTGTTTTT + +1 cisbp__M5393-bs-bsh-CG34367-CG9876-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg-Vsx2 -2 0.00196624 48.0805 0.201071 14 AACAAAGGGTCCATTGTTC TAATTGCTTAATTA - +1 dbcorrdb__HSF1__ENCSR000EET_1__m3-Hsf 1 0.00196746 48.1103 0.201071 19 AACAAAGGGTCCATTGTTC AAATTATGCTATGGCTGCGC - +1 dbcorrdb__PBX3__ENCSR000BGR_1__m2-bs-btd-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP -4 0.00196746 48.1103 0.201071 15 AACAAAGGGTCCATTGTTC CCCCTCTGATTGGCTGGGGC - +1 transfac_pro__M01507-CHES-1-like-croc-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -7 0.00196746 48.1103 0.201071 12 AACAAAGGGTCCATTGTTC TCCTCTTTGTTTACAATTCA - +1 cisbp__M1606 -7 0.00197519 48.2992 0.201434 12 AACAAAGGGTCCATTGTTC AATGTATTGTTAT - +1 transfac_pro__M02929 -4 0.00205962 50.3638 0.208283 15 AACAAAGGGTCCATTGTTC ATTCTGCCAGTGATTG - +1 neph__UW.Motif.0496 -5 0.00205962 50.3638 0.208283 14 AACAAAGGGTCCATTGTTC AGGATGCAGTGATCTG + +1 transfac_pro__M02750-croc-fd59A-FoxK-foxo-FoxP-slp2 -8 0.00205962 50.3638 0.208283 11 AACAAAGGGTCCATTGTTC AATTTTTGTTTACTAT - +1 taipale_tf_pairs__POU2F1_SOX2_ATTTGCATNACAATRN_CAP-nub-pdm2-SoxN -10 0.00205962 50.3638 0.208283 9 AACAAAGGGTCCATTGTTC CTATTGTTATGCAAAT - +1 dbcorrdb__CHD1__ENCSR000AQK_1__m4-Chd1 -2 0.00209209 51.1579 0.210016 17 AACAAAGGGTCCATTGTTC TTTTAAGCTCTTTTTCGGTT - +1 jaspar__MA0296.1-CHES-1-like-FoxK-FoxL1-FoxP-croc-fkh-foxo-slp1-slp2 -7 0.00209209 51.1579 0.210016 12 AACAAAGGGTCCATTGTTC TCCTCTTTGTTTACAATTCA - +1 hocomoco__CUX2_HUMAN.H11MO.0.D-ct -9 0.00209566 51.2452 0.210016 10 AACAAAGGGTCCATTGTTC TTCATTGATTT - +1 tfdimers__MD00540-Hand 0 0.00209852 51.3151 0.210016 19 AACAAAGGGTCCATTGTTC AAAATAATGGCATCTGGAATTAATTAAATAA + +1 taipale__EN1_full_TAATTRSNYAATTA-bs-bsh-CG34367-CG9876-Dr-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg-Vsx2 -2 0.00210615 51.5017 0.210343 14 AACAAAGGGTCCATTGTTC TAATTGCTTAATTA + +1 jaspar__MA0981.1 -8 0.00211365 51.6851 0.210656 10 AACAAAGGGTCCATTGTTC TAACTTTTTG - +1 cisbp__M1187-CG15696-en-inv -1 0.00213171 52.1266 0.212017 9 AACAAAGGGTCCATTGTTC TTAATTGGC + +1 tfdimers__MD00071-Sox100B -6 0.00215835 52.778 0.214225 13 AACAAAGGGTCCATTGTTC TTTTTCTTTGTTTGCATAATTTTTTTT + +1 tfdimers__MD00288 -4 0.00217463 53.1763 0.215399 15 AACAAAGGGTCCATTGTTC TCATATCTATTGTGTAATTTTTTAT - +1 tfdimers__MD00529 2 0.00221826 54.2431 0.2185 19 AACAAAGGGTCCATTGTTC CCCCCTGGCTTCCCTGTGTTCTTTCTCCT + +1 dbcorrdb__IRF3__ENCSR000DZX_1__m1 -1 0.00222406 54.385 0.2185 18 AACAAAGGGTCCATTGTTC ATAAATTGCCATTTATCATG + +1 dbcorrdb__CHD1__ENCSR000EBU_1__m1-Chd1-Jra-nej-SREBP -6 0.00222406 54.385 0.2185 13 AACAAAGGGTCCATTGTTC CCCCAATTGGTTCGGTCCGG - +1 tfdimers__MD00020 0 0.00223119 54.5594 0.218755 19 AACAAAGGGTCCATTGTTC AAATTAGAGTCAGTTAATAATTAACTAAAA + +1 neph__UW.Motif.0376 -9 0.00225026 55.0255 0.220176 10 AACAAAGGGTCCATTGTTC CTCATTTTTCAG + +1 neph__UW.Motif.0510 -5 0.00225526 55.148 0.220219 14 AACAAAGGGTCCATTGTTC GGATTTTTTTCTTC - +1 cisbp__M0647 -8 0.00228981 55.9927 0.221894 10 AACAAAGGGTCCATTGTTC TTACTTTTTG - +1 cisbp__M1125-abd-A-al-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-lms-NK7.1-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 -8 0.00228981 55.9927 0.221894 10 AACAAAGGGTCCATTGTTC GCCAATTAGC - +1 transfac_pro__M07563 -8 0.00228981 55.9927 0.221894 10 AACAAAGGGTCCATTGTTC CCCTCTTTTT - +1 homer__CCATTGTATGCAAAT_Oct4_Sox17-Sox15-nub-pdm2-vvl -10 0.00229081 56.0173 0.221894 9 AACAAAGGGTCCATTGTTC CCATTGTATGCAAAT + +1 hocomoco__HXC10_HUMAN.H11MO.0.D-Abd-B-CTCF-bab1-cad -1 0.00233447 57.0847 0.225669 18 AACAAAGGGTCCATTGTTC TTTTTAATTTTTTTATTAC + +1 dbcorrdb__CTCF__ENCSR000AQU_1__m2-CTCF-SMC3-vtd 1 0.00236377 57.8013 0.226685 19 AACAAAGGGTCCATTGTTC GGCCATATGGGGAACTGCAG + +1 transfac_pro__M01533-bin-CHES-1-like-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 -7 0.00236377 57.8013 0.226685 12 AACAAAGGGTCCATTGTTC TCATCTTTGTTTACTTTTAA - +1 transfac_pro__M04667-CHES-1-like-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 -7 0.00236377 57.8013 0.226685 12 AACAAAGGGTCCATTGTTC TCATCTTTGTTTACTTTTAA - +1 yetfasco__YNL068C_830-CHES-1-like-FoxK-FoxL1-FoxP-croc-fd59A-fkh-foxo-slp2 -7 0.00236377 57.8013 0.226685 12 AACAAAGGGTCCATTGTTC TCATCTTTGTTTACTTTTAA - +1 transfac_pro__M03850-Sox102F -13 0.00237052 57.9664 0.226771 6 AACAAAGGGTCCATTGTTC TTGTTTA + +1 transfac_pro__M04641-bin-CHES-1-like-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -6 0.00237407 58.0531 0.226771 13 AACAAAGGGTCCATTGTTC CACAAGTTTGTTTATCATAAAT - +1 taipale_cyt_meth__SOX10_AACAATNNNNNATTGTT_eDBD_meth-Sox100B -1 0.00241725 59.1091 0.230439 17 AACAAAGGGTCCATTGTTC AACAATGGGCCATTGTT + +1 predrem__nrMotif1 -8 0.0024236 59.2643 0.230589 11 AACAAAGGGTCCATTGTTC TGTTTTTGTTTT - +1 cisbp__M1585-pan -10 0.00247936 60.6279 0.234343 9 AACAAAGGGTCCATTGTTC CCTTTGATCT + +1 transfac_public__M00018-Antp-Scr-Ubx -4 0.00248114 60.6714 0.234343 15 AACAAAGGGTCCATTGTTC ACGAAGCCATTAAGCCCTC - +1 tfdimers__MD00602-Stat92E -2 0.00248332 60.7247 0.234343 17 AACAAAGGGTCCATTGTTC TTAATAGTCAGTTGTGATTTCCTTTTTT + +1 tfdimers__MD00358-fkh 6 0.00248886 60.86 0.234343 19 AACAAAGGGTCCATTGTTC TAATTATAAATGTTCTTTTTTGTTTACTTATATA - +1 dbcorrdb__CTCF__ENCSR000DTI_1__m2-CTCF-SMC3-vtd 1 0.00251164 61.4171 0.234343 19 AACAAAGGGTCCATTGTTC GGCCATATGGGGAACTGCAG + +1 dbcorrdb__CBX3__ENCSR000BRT_1__m5-HP1b-HP1c-HP1e-Su(var)205 2 0.00251164 61.4171 0.234343 18 AACAAAGGGTCCATTGTTC CCAGCAAAAATATCCTTCAA + +1 dbcorrdb__RFX5__ENCSR000ECX_1__m1 -2 0.00251164 61.4171 0.234343 17 AACAAAGGGTCCATTGTTC CTGTTCTGTCATTGGTTGCT - +1 dbcorrdb__TRIM28__ENCSR000EUZ_1__m7-bon -2 0.00251164 61.4171 0.234343 17 AACAAAGGGTCCATTGTTC CTATGACTCCATTCATTCTG - +1 dbcorrdb__GTF3C2__ENCSR000DOD_1__m4-Bdp1-Brf-Tbp -4 0.00251164 61.4171 0.234343 15 AACAAAGGGTCCATTGTTC CCGCCGGCGTAGCTTAGTGG - +1 dbcorrdb__STAT5A__ENCSR000BQZ_1__m2-CG9650-foxo-lz-MTA1-like-nej-NFAT-run-RunxA-RunxB-Stat92E -5 0.00251164 61.4171 0.234343 14 AACAAAGGGTCCATTGTTC GAGTCTTTTTGTGGTTTTTA - +1 tfdimers__MD00374-gsb-gsb-n-pho-phol-prd 1 0.00253976 62.1047 0.236509 19 AACAAAGGGTCCATTGTTC ATATTTTTTATTAATTAAATCCATTTTTAAAAAAATA + +1 transfac_pro__M07741-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -2 0.00257229 62.9003 0.23816 17 AACAAAGGGTCCATTGTTC AAACAATAGCATTGTTT - +1 hocomoco__NANOG_HUMAN.H11MO.0.A-CG9650-Mad-SoxN-nej-nub-pan-pdm2-vvl -9 0.00257229 62.9003 0.23816 10 AACAAAGGGTCCATTGTTC TCCTTTGTTATGCAAAT + +1 neph__UW.Motif.0397 -4 0.00258335 63.1708 0.238269 14 AACAAAGGGTCCATTGTTC AAAATGTTTTTTTG + +1 neph__UW.Motif.0196 -4 0.00260922 63.8034 0.239454 12 AACAAAGGGTCCATTGTTC AGGAAATTTTTG + +1 transfac_pro__M07746-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -3 0.0026111 63.8491 0.239454 15 AACAAAGGGTCCATTGTTC AACAATAACATTGTT - +1 stark__BYRHBACAAWGTDDB-dsx -7 0.0026111 63.8491 0.239454 12 AACAAAGGGTCCATTGTTC GTTACATTGTGTCAG - +1 neph__UW.Motif.0489 0 0.00265846 65.0073 0.241468 16 AACAAAGGGTCCATTGTTC GGAAATAATTTCTTTC - +1 neph__UW.Motif.0302 1 0.00265846 65.0073 0.241468 15 AACAAAGGGTCCATTGTTC TGGCATTTTTTTCATT - +1 dbcorrdb__CTCF__ENCSR000DUP_1__m2-CTCF-SMC3-vtd 1 0.0026681 65.243 0.241468 19 AACAAAGGGTCCATTGTTC GGCCATAGGGGGAACTGCAG + +1 dbcorrdb__MYC__ENCSR000DOM_1__m1-Max-Myc 1 0.0026681 65.243 0.241468 19 AACAAAGGGTCCATTGTTC TAAATACAAACCACATGGTT + +1 dbcorrdb__NFYB__ENCSR000DNR_1__m1-btd-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps 1 0.0026681 65.243 0.241468 19 AACAAAGGGTCCATTGTTC CCCCCGGCCTCTGATTGGCT + +1 taipale_tf_pairs__CUX1_SOX15_NATCRATNNNNNNNAACAATRS_CAP_repr-ct -10 0.00267976 65.5282 0.241928 9 AACAAAGGGTCCATTGTTC GCATTGTTGAAGGTTATCGATC - +1 cisbp__M1587-pan -10 0.00268321 65.6125 0.241928 9 AACAAAGGGTCCATTGTTC CCTTTGATCT + +1 transfac_pro__M07376-arm-pan -11 0.00270029 66.0303 0.243014 8 AACAAAGGGTCCATTGTTC CTTTGATG + +1 transfac_pro__M07697-dmrt93B-dmrt99B-dsx -5 0.00273657 66.9173 0.24582 14 AACAAAGGGTCCATTGTTC TTGATACATTGTAACAA - +1 neph__UW.Motif.0357 -2 0.00276353 67.5767 0.246863 14 AACAAAGGGTCCATTGTTC AAAAAGCAAATCTG + +1 transfac_pro__M09135 -4 0.00276353 67.5767 0.246863 14 AACAAAGGGTCCATTGTTC AAAGCTACTTTTTC - +1 tfdimers__MD00292 2 0.00277666 67.8976 0.247532 19 AACAAAGGGTCCATTGTTC AAAAAAATGCAAACATTTAAAAATA + +1 neph__UW.Motif.0366 -3 0.00278642 68.1363 0.247532 15 AACAAAGGGTCCATTGTTC AAAAAATGTTTTTTG + +1 transfac_pro__M01996-fkh -6 0.00278642 68.1363 0.247532 13 AACAAAGGGTCCATTGTTC GAACATTCTGTTCTT + +1 bergman__Ubx-Antp-Scr-Ubx -4 0.00280065 68.4842 0.248339 15 AACAAAGGGTCCATTGTTC ACGAAGCCATTAAGCCCTC - +1 hocomoco__DLX4_HUMAN.H11MO.0.D-CG34367-Dll-en-inv-unpg 0 0.00283166 69.2426 0.249884 16 AACAAAGGGTCCATTGTTC AAATTTAGGGTAATTA - +1 neph__UW.Motif.0624 0 0.00283166 69.2426 0.249884 16 AACAAAGGGTCCATTGTTC TGAAAAAAAAAAAATG - +1 dbcorrdb__STAT3__ENCSR000DOX_1__m2-Jra-Myc-nej-Stat92E -3 0.00283361 69.2903 0.249884 16 AACAAAGGGTCCATTGTTC CAGCTAGGTGTTGAGTCATA - +1 predrem__nrMotif943 -9 0.00290231 70.9702 0.25501 10 AACAAAGGGTCCATTGTTC TGCCTTGTTT - +1 taipale_tf_pairs__ERF_DLX3_RSCGGAANNNNYAATTA_CAP_repr-Ets21C -2 0.00291058 71.1723 0.255271 17 AACAAAGGGTCCATTGTTC TAATTGCCACTTCCGGT - +1 cisbp__M0716-FoxK-foxo-FoxP-slp2 -12 0.00295861 72.3468 0.259013 7 AACAAAGGGTCCATTGTTC GTTGTTTAC - +1 neph__UW.Motif.0621 -3 0.00297264 72.69 0.25977 15 AACAAAGGGTCCATTGTTC AAAAAAAATGCTGAC + +1 dbcorrdb__EZH2__ENCSR000ATC_1__m1-E(z) 2 0.00300865 73.5706 0.261025 18 AACAAAGGGTCCATTGTTC AGAAGACACCCGACATTTAG + +1 dbcorrdb__NR3C1__ENCSR000BHE_1__m1-fkh -1 0.00300865 73.5706 0.261025 18 AACAAAGGGTCCATTGTTC GGCGAGAACAGACTGTCCTT + +1 neph__UW.Motif.0314 -4 0.00301532 73.7337 0.261134 15 AACAAAGGGTCCATTGTTC GCAATTTCTCTGTCTC - +1 transfac_pro__M04670-bin-fd102C-fd19B-FoxK-FoxL1-slp1-slp2 -6 0.00303572 74.2325 0.26243 13 AACAAAGGGTCCATTGTTC GTTCAGGTTGTTTTGGTACGGAT - +1 elemento__ACAATGG -10 0.00308821 75.5159 0.266489 7 AACAAAGGGTCCATTGTTC CCATTGT - +1 transfac_pro__M02816-pan -6 0.00309485 75.6784 0.266586 13 AACAAAGGGTCCATTGTTC TTTTCCTTTGATCTATA - +1 tfdimers__MD00499-Taf7-Tbp 1 0.00313276 76.6054 0.26937 19 AACAAAGGGTCCATTGTTC ATAAAAATGCAAATTTATATATTTT + +1 neph__UW.Motif.0652 -4 0.00315939 77.2566 0.271177 14 AACAAAGGGTCCATTGTTC AAAATTGCTTTTTC + +1 hocomoco__NR2F6_HUMAN.H11MO.0.D-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp -2 0.00319027 78.0116 0.272668 17 AACAAAGGGTCCATTGTTC TCAATTGAACTTTGTCCT - +1 dbcorrdb__CTCF__ENCSR000DPY_1__m2-CTCF-SMC3-vtd 1 0.00319373 78.0963 0.272668 19 AACAAAGGGTCCATTGTTC GGCCATATGGGGAACTGCAG + +1 dbcorrdb__RXRA__ENCSR000BHU_1__m2-EcR-eg-ERR-ftz-f1-HDAC1-Hnf4-Hr38-Hr4-Hr51-Hr78-kni-knrl-nej-Nup133-svp-usp 0 0.00319373 78.0963 0.272668 19 AACAAAGGGTCCATTGTTC CCCACTCTGACCTTTGACCT - +1 neph__UW.Motif.0026 -12 0.00320631 78.4038 0.273093 7 AACAAAGGGTCCATTGTTC ATTGTGAAA + +1 neph__UW.Motif.0573 0 0.00321002 78.4946 0.273093 16 AACAAAGGGTCCATTGTTC CAAAATTTTTCATCTG - +1 tfdimers__MD00170-foxo-Sox100B -6 0.00322275 78.8059 0.273693 13 AACAAAGGGTCCATTGTTC AATTACTTTGTAAACAAAAAAAA + +1 tfdimers__MD00590-E(bx)-nej -1 0.00322898 78.9583 0.27374 18 AACAAAGGGTCCATTGTTC GGGGGGCAGGGAGTGTGTTGTGGTTTTTTT + +1 tfdimers__MD00108-fkh -4 0.00326011 79.7194 0.275411 15 AACAAAGGGTCCATTGTTC AATTTTTTTTTATTTACTTAGTAAATAAAAAAAAATA + +1 flyfactorsurvey__pdm3_SOLEXA_5_FBgn0033288-E5-pdm3-zen2 5 0.00332633 81.3387 0.280514 19 AACAAAGGGTCCATTGTTC TTAATTAGGTTGGTTGGGTGGGGGG + +1 neph__UW.Motif.0511 -1 0.00338029 82.6582 0.282459 15 AACAAAGGGTCCATTGTTC TGAAATTTTTCTTTG - +1 factorbook__SOX2-OCT4-CG9650-SoxN-nej-pan -10 0.00338029 82.6582 0.282459 9 AACAAAGGGTCCATTGTTC CCTTTGTTATGCAAA + +1 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNRNACAAWN_CAP_repr-gcm-gcm2 -11 0.00338819 82.8514 0.282459 8 AACAAAGGGTCCATTGTTC CATTGTTTTCGCCCGCAT - +1 dbcorrdb__CTCF__ENCSR000DWY_1__m2-CTCF-SMC3-vtd 1 0.00338937 82.8802 0.282459 19 AACAAAGGGTCCATTGTTC GGCCATTTGGGGAACTGCAG - +1 dbcorrdb__TBL1XR1__ENCSR000DYZ_1__m2-Bgb-Bro-CG9650-ebi-lz-MTA1-like-run-RunxA-RunxB -5 0.00338937 82.8802 0.282459 14 AACAAAGGGTCCATTGTTC AATATTTTCTGTGGTTTGTG - +1 dbcorrdb__ARID3A__ENCSR000EDP_1__m2 -6 0.00338937 82.8802 0.282459 13 AACAAAGGGTCCATTGTTC TTGCTCTTTGATCAGTCATG - +1 taipale_tf_pairs__SOX17_ACCGAACAAT_HT-Sox15 -12 0.00339038 82.9051 0.282459 7 AACAAAGGGTCCATTGTTC ATTGTTCGGT - +1 tfdimers__MD00562-GATAe-grn-pnr-srp 14 0.00339904 83.1168 0.282692 19 AACAAAGGGTCCATTGTTC CCATTCTTATCTTCTTTTCCCACTACTTCCTGTTCGCACAC - +1 tfdimers__MD00073-Ptx1 0 0.00340761 83.3262 0.282917 19 AACAAAGGGTCCATTGTTC AAAAAAAAAGGGATTAATCATTAACTAAT + +1 transfac_pro__M00794-scro -8 0.00349114 85.3688 0.288363 11 AACAAAGGGTCCATTGTTC GCCACTTGAGGG - +1 jaspar__MA0378.1-CG12054 -2 0.00353588 86.463 0.29156 17 AACAAAGGGTCCATTGTTC CCGTAGAAAATTTTTTTCAAT - +1 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNNRNACAAWN_CAP-gcm-gcm2 -11 0.00355791 87.0017 0.291655 8 AACAAAGGGTCCATTGTTC TATTGTTTTATACCCGCAT - +1 dbcorrdb__TAF7__ENCSR000BNM_1__m2-Taf7 1 0.00359612 87.9359 0.291655 19 AACAAAGGGTCCATTGTTC ACACCCAGATCCCAGTTGCA + +1 dbcorrdb__ATF3__ENCSR000BPS_1__m3 1 0.00359612 87.9359 0.291655 19 AACAAAGGGTCCATTGTTC GCCTCCACCGGGAATCGAAC - +1 dbcorrdb__SUPT20H__ENCSR000DNP_1__m1-Spt20 0 0.00359612 87.9359 0.291655 19 AACAAAGGGTCCATTGTTC AAAAATTTCATCTTTATTTC - +1 dbcorrdb__EP300__ENCSR000AQB_1__m4-nej -1 0.00359612 87.9359 0.291655 18 AACAAAGGGTCCATTGTTC GCCACTTTTCTCCTGTTGCA - +1 dbcorrdb__TAF7__ENCSR000BNM_1__m1-Taf7 -5 0.00359612 87.9359 0.291655 14 AACAAAGGGTCCATTGTTC GATATAGTTGGTTGCAGTGG - +1 dbcorrdb__CEBPB__ENCSR000EEE_1__m1-Irbp18-nej-slbo-Xrp1 -6 0.00359612 87.9359 0.291655 13 AACAAAGGGTCCATTGTTC GCAATTATTGCACAATATCT - +1 cisbp__M6392-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp -2 0.0035975 87.9696 0.291655 17 AACAAAGGGTCCATTGTTC 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/the_code/Human/data/tomtom/motif-2.meme b/the_code/Human/data/tomtom/motif-2.meme new file mode 100644 index 0000000000000000000000000000000000000000..35f3e66d8186ef2dbcb03d366c0b4832b72dc537 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-2.meme @@ -0,0 +1,22 @@ +MEME version 4 + +ALPHABET= ACGT + +strands: + - + +Background letter frequencies (from unknown source): +A 0.250 C 0.250 G 0.250 T 0.250 + +MOTIF 2 NNCDYGTGAY + +letter-probability matrix: alength= 4 w= 10 nsites= 1 E= 0e+0 +0.355996 0.156752 0.355052 0.132200 +0.152975 0.276676 0.166195 0.404155 +0.007554 0.983947 0.004721 0.003777 +0.457035 0.093484 0.200189 0.249292 +0.007554 0.721435 0.033050 0.237960 +0.208687 0.041549 0.740321 0.009443 +0.025496 0.019830 0.012276 0.942398 +0.000944 0.004721 0.986780 0.007554 +0.775260 0.080264 0.101983 0.042493 +0.082153 0.408876 0.101039 0.407932 diff --git a/the_code/Human/data/tomtom/motif-2/tomtom.html b/the_code/Human/data/tomtom/motif-2/tomtom.html new file mode 100644 index 0000000000000000000000000000000000000000..af8ee2d636429f6f135ec8c5dd84490da49e2494 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-2/tomtom.html @@ -0,0 +1,36997 @@ + + + + + Tomtom Results + + + + + + + + + + + + + + + + +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+

A link to more information about the query motif.

+
[close ]
+
+ +
+ +
[close ]
+
+ +
+

The motif preview. On supporting browsers this will display as a motif + logo, otherwise the consensus sequence will be displayed.

+
[close ]
+
+ +
+

The number motifs in the target database with a significant match to the query motif.

+
[close ]
+
+ +
+

Links to the (up to) twenty target motifs with the most significant matches to the query motif.

+
[close ]
+
+ +
+ +
[close ]
+
+ +
+

The number of motifs read from the motif database minus the number that + had to be discarded due to conflicting IDs.

+
[close ]
+
+ +
+

The number of motifs in this database that have a significant match to at least one of the query motifs.

+
[close ]
+
+ +
+

The summary gives information about the target motif. Mouse over each + row to show further help buttons for each specific title.

+
[close ]
+
+ +
+

The ID of the target motif with the optional alternate ID shown in parentheses.

+
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+ +
[close ]
+
+ +
+

The image shows the optimal alignment of the two motifs. The sequence logo + of the target motif is shown aligned above the logo for the query motif.

+
[close ]
+
+ +
+

By clicking the link "Create custom LOGO ↧" a form to make custom logos + will be displayed. The download button can then be clicked to generate a motif + matching the selected specifications.

+
[close ]
+
+ +
+

Two image formats, png and eps, are available. The pixel based portable + network graphic (png) format is commonly used on the Internet and the + Encapsulated PostScript (eps) format is more suitable for publications + that might require scaling.

+
[close ]
+
+ +
+

Toggle error bars indicating the confidence of a motif based on the + number of sites used in its creation.

+
[close ]
+
+ +
+

Toggle adding pseudocounts for Small Sample + Correction.

+
[close ]
+
+ +
+

Toggle a full reverse complement of the alignment.

+
[close ]
+
+ +
+

Specify the width of the generated logo.

+
[close ]
+
+ +
+

Specify the height of the generated logo.

+
[close ]
+
+ +
+ +
[close ]
+
+
+ +
[close ]
+
+ + + + +
+ +
+

+ For further information on how to interpret these results please access + https://meme-suite.org/meme/doc/tomtom-output-format.html.
+ To get a copy of the MEME software please access + https://meme-suite.org. +

+

+
+ Query Motifs  |  Target Databases  |  Matches  |  Settings  |  Program information  |  Results in TSV Format  +   |  Results in XML Format + +
+ +
+

Query Motifs

+ Next Top +
+
+ + + + + + + + + + + + + + + + + + + + + +
Database
ID
Alt. ID
Preview
Matches
List
+ +
+ +
+

Target Databases

+ Previous Next Top +
+
+ + + + + + + + + + + + + + + +
Database
Used
Matched
+ +
+ +
+
+
+

Matches to

+   Top +
+
+ + + + + + + + + + + + + +
Summary
Optimal Alignment
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Name
Database
p-value
E-value
q-value
Overlap
Offset
Orientation
+ Show logo download options + 		+
+ ⤒ + ↥ + ⇘ + ↧ + ⤓ +
+
+
+
+
+ + +
+

Settings

+ Previous Next Top +
+
+

Alphabet

+ + + +

Other Settings

+ + + + + + + + + + + + + +
Strand Handling + Reverse complements are not possible so motifs are compared as they are provided. + Motifs are compared as they are provided. + Motifs may be reverse complemented before comparison to find a better match. +
Distance Measure + Average log-likelihood ratio + Euclidean distance + Kullback-Leibler divergence + Pearson correlation coefficient + Sandelin-Wasserman function + Bayesian Likelihood 2-Components score (from 1-component Dirichlet prior) + Bayesian Likelihood 2-Components score (from 5-component Dirichlet prior) + Log likelihood Ratio score (from 1-component Dirichlet prior) + Log likelihood Ratio score (from 5-component Dirichlet prior) +
Match Threshold + Matches must have a E-valueq-value of or smaller. +
+ +
+ +
+ +
+
Tomtom version
+ (Release date: ) +
+
+
+
Command line
+
+
Result calculation took seconds
+
+
+ + + diff --git a/the_code/Human/data/tomtom/motif-2/tomtom.tsv b/the_code/Human/data/tomtom/motif-2/tomtom.tsv new file mode 100644 index 0000000000000000000000000000000000000000..bf4461518fd5b283a2e5ce06a8e5559f22a6ec39 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-2/tomtom.tsv @@ -0,0 +1,1168 @@ +Query_ID Target_ID Optimal_offset p-value E-value q-value Overlap Query_consensus Target_consensus Orientation +2 jaspar__MA0620.1-HLH3B-HLH4C-Hand-Max-Mitf-Myc-Usf-ac-ase-bigmax-cnc-l(1)sc-nau-sc -1 1.76475e-11 4.31534e-07 8.11924e-07 9 ATCACGTGAC CCACGTGACC - +2 cisbp__M0208-ac-ase-bigmax-cnc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf -1 3.41188e-11 8.34307e-07 8.11924e-07 9 ATCACGTGAC CCACGTGACC - +2 cisbp__M0233-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 0 8.70259e-11 2.12804e-06 1.03548e-06 10 ATCACGTGAC GTCACGTGAT + +2 cisbp__M0174-ac-ase-bigmax-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf -1 1.17359e-10 2.86977e-06 1.11711e-06 9 ATCACGTGAC CCACGTGACC - +2 cisbp__M0202-Max-Mitf-Usf -1 3.65557e-10 8.93896e-06 2.89971e-06 9 ATCACGTGAC CCACGTGACC - +2 homer__GTCACGTGGT_Usf2-Max-Mitf-Usf-cnc 0 8.0905e-10 1.97837e-05 5.50084e-06 10 ATCACGTGAC ACCACGTGAC - +2 taipale__TFE3_DBD_NNCACGTGNN-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 0 2.17946e-09 5.32943e-05 1.15255e-05 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5930-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 2.17946e-09 5.32943e-05 1.15255e-05 10 ATCACGTGAC ATCACGTGAC - +2 cisbp__M0201-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 0 4.37701e-09 0.000107031 1.89381e-05 10 ATCACGTGAC GTCACGTGAC + +2 cisbp__M5931-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 0 8.48555e-09 0.000207497 3.3655e-05 10 ATCACGTGAC ATCACGTGAC - +2 taipale__TFEB_full_RTCACGTGAY-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 0 1.05041e-08 0.000256858 3.84564e-05 10 ATCACGTGAC ATCACGTGAC + +2 taipale__TFEC_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 1.95273e-08 0.000477502 6.19589e-05 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5932-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 1.95273e-08 0.000477502 6.19589e-05 10 ATCACGTGAC ATCACGTGAC - +2 cisbp__M4081-bigmax-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 2.69129e-08 0.0006581 6.74152e-05 10 ATCACGTGAC ATATCACGTGATTT + +2 transfac_public__M00122-bigmax-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 2.69129e-08 0.0006581 6.74152e-05 10 ATCACGTGAC AAATCACGTGATAT + +2 homer__RTCATGTGAC_MITF-Mitf-SREBP-Usf-cnc-cyc 0 2.90619e-08 0.000710651 6.91585e-05 10 ATCACGTGAC GTCATGTGAC + +2 hocomoco__MITF_MOUSE.H11MO.0.A-HLH3B-HLH4C-Hand-Max-Mitf-Myc-Usf-ac-ase-cnc-cyc-l(1)sc-nau-sc -1 5.16325e-08 0.00126257 0.000117019 9 ATCACGTGAC CCACGTGACT + +2 taipale__USF1_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 0 6.2196e-08 0.00152088 0.000128702 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5943-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 7.47273e-08 0.00182731 0.000142263 10 ATCACGTGAC GTCACGTGAC - +2 cisbp__M0251-Clk-Max-Mitf-Mondo-SREBP-Sirt6-Usf-bigmax-cnc-cwo-cyc-tgo 0 8.95583e-08 0.00218997 0.000157868 10 ATCACGTGAC GTCACGTGAC + +2 swissregulon__sacCer__TYE7-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 0 1.07071e-07 0.00261821 0.000181998 10 ATCACGTGAC ATCACGTGAT - +2 jaspar__MA1011.1-Clk-Mitf-Mondo-SREBP-Sirt6-Usf-bigmax-cnc-cwo-cyc-tgo 0 1.27705e-07 0.00312278 0.000198935 10 ATCACGTGAC GTCACGTGAC + +2 cisbp__M0193-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tai-tgo-Usf -2 1.29575e-07 0.0031685 0.000198935 8 ATCACGTGAC CACGTGAC - +2 taipale_cyt_meth__ARNTL_RTCAYGTGMN_eDBD_meth-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 1.80425e-07 0.00441192 0.000268348 10 ATCACGTGAC GTCACATGAC - +2 cisbp__M0241 0 2.10573e-07 0.00514913 0.000303696 10 ATCACGTGAC AGCACGTGATTT + +2 transfac_pro__M08978-bigmax-Clk-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf -2 2.61485e-07 0.0063941 0.000366033 8 ATCACGTGAC CACGTGAC + +2 taipale_cyt_meth__SREBF1_NTCACGTGAN_eDBD-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 2.98074e-07 0.00728879 0.000389714 10 ATCACGTGAC ATCACGTGAC - +2 dbcorrdb__USF1__ENCSR000BHX_1__m1-ac-ase-bigmax-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf-zfh1 4 3.02968e-07 0.00740847 0.000389714 10 ATCACGTGAC CGGGGTCACGTGACCCGGGC + +2 scertf__spivak.TYE7-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 0 3.50907e-07 0.00858074 0.000417527 10 ATCACGTGAC GTCACGTGAT - +2 cisbp__M0197-Mitf-Usf 0 3.9738e-07 0.00971713 0.000461289 10 ATCACGTGAC CCCACGTGATA - +2 transfac_pro__M09006-bigmax-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf -2 6.19664e-07 0.0151526 0.000669256 8 ATCACGTGAC CACGTGAC + +2 dbcorrdb__USF1__ENCSR000BPV_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 1 7.53953e-07 0.0184364 0.000747575 10 ATCACGTGAC GGTCACGTGACCCGGGCCGG - +2 dbcorrdb__USF1__ENCSR000BJB_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 2 8.96726e-07 0.0219276 0.000820874 10 ATCACGTGAC GGGCCACGTGACCCGGGCCG + +2 cisbp__M0156-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-SREBP-Usf-bigmax-cnc-cwo-cyc-emc-h-mio-tgo 0 8.96867e-07 0.0219311 0.000820874 10 ATCACGTGAC GTCACGTGAT + +2 transfac_pro__M00796-Max-Usf 1 9.34529e-07 0.022852 0.000839206 10 ATCACGTGAC GACCACGTGACA + +2 transfac_pro__M03860-ac-ase-cnc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 2 1.05002e-06 0.0256762 0.000888062 10 ATCACGTGAC CGCCCACGTGACC + +2 dbcorrdb__USF1__ENCSR000BMF_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 2 1.06357e-06 0.0260075 0.000888062 10 ATCACGTGAC GGGCCACGTGACCCGGGCCG - +2 cisbp__M0182-bigmax-Max-Mitf-Mondo -1 1.20844e-06 0.02955 0.000974821 9 ATCACGTGAC CCACGTGATC + +2 cisbp__M0248-Mitf-SREBP-Usf -1 1.20844e-06 0.02955 0.000974821 9 ATCACGTGAC TCACGTGATG - +2 cisbp__M4709-Clk-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo -2 1.36238e-06 0.0333144 0.00107263 8 ATCACGTGAC CACGTGAC - +2 cisbp__M1917-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 0 1.37477e-06 0.0336172 0.00107263 10 ATCACGTGAC GCCACGTGACC - +2 taipale_cyt_meth__ARNTL_RTCACGTGMN_eDBD-Clk-cnc-cyc-Mitf-SREBP-tai-tgo 0 1.3991e-06 0.0342123 0.00107401 10 ATCACGTGAC GGCACGTGAC - +2 jaspar__MA0093.2-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Usf-ac-ase-cnc-cwo-cyc-l(1)sc-nau-sc-tgo 0 1.59147e-06 0.0389162 0.00113185 10 ATCACGTGAC GCCACGTGACC + +2 cisbp__M0200-Atf6-Clk-CrebA-Hey-Max-Met-Myc 0 1.61713e-06 0.0395436 0.00113185 10 ATCACGTGAC GCCACGTGGC + +2 swissregulon__hs__TFEB.p2-Max-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 0 1.61713e-06 0.0395436 0.00113185 10 ATCACGTGAC GTCACGTGAC + +2 jaspar__MA0964.1-Mitf-bigmax-cnc-cyc-tgo -1 1.61713e-06 0.0395436 0.00113185 9 ATCACGTGAC GCACGTGACC + +2 transfac_pro__M07643-bigmax-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 1.86604e-06 0.0456303 0.00126875 10 ATCACGTGAC ATCACGTGAT + +2 cisbp__M0235-Clk-Max-Mitf-SREBP-Usf-bigmax-cnc-cyc-tgo -2 1.96941e-06 0.0481581 0.00132017 8 ATCACGTGAC CACGTGAC - +2 dbcorrdb__USF1__ENCSR000BKT_1__m1-bigmax-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-SREBP-tgo-Usf 4 2.05009e-06 0.0501309 0.00132168 10 ATCACGTGAC CGTGGCCACGTGACCCGGGC + +2 dbcorrdb__USF2__ENCSR000DZU_1__m1-ac-ase-btd-cnc-CrebB-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-mor-Myc-nau-Sap30-sc-Sin3A-Spps-SREBP-tgo-Usf 1 2.05009e-06 0.0501309 0.00132168 10 ATCACGTGAC GGCCACGTGACCCGGGCCGG - +2 transfac_pro__M07067-ac-ase-cnc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 0 2.05497e-06 0.0502502 0.00132168 10 ATCACGTGAC CCCACGTGACCCCG - +2 cisbp__M6531-cnc-cyc-Max-Mitf-Myc-SREBP-tgo-Usf 1 2.12139e-06 0.0518744 0.00132879 10 ATCACGTGAC GCCCACGTGAC + +2 cisbp__M0225-Max-Mitf-Usf 0 2.14979e-06 0.0525687 0.00132879 10 ATCACGTGAC ACCACGTGAT - +2 cisbp__M0163-Max-Mitf-bigmax-cnc-cyc-tgo -1 2.14979e-06 0.0525687 0.00132879 9 ATCACGTGAC GCACGTGACG + +2 cisbp__M0223-E2f1-Max-Myc-Sap30 0 2.21248e-06 0.0541018 0.00135001 9 ATCACGTGAC ACCACGTGG + +2 cisbp__M4322 -1 2.35391e-06 0.0575601 0.00141812 8 ATCACGTGAC TCACGTGG - +2 transfac_public__M00187-Usf 0 2.47274e-06 0.060466 0.0014711 10 ATCACGTGAC GCCACGTGAC - +2 cisbp__M0221-Max-Myc -1 2.57277e-06 0.0629119 0.00147528 9 ATCACGTGAC CCACGTGGT + +2 cisbp__M0222-Max-Myc-Sap30 0 2.57277e-06 0.0629119 0.00147528 9 ATCACGTGAC ACCACGTGG + +2 yetfasco__YOR344C_397-Mitf-Mondo-SREBP-Usf-bigmax-tgo -1 2.57277e-06 0.0629119 0.00147528 9 ATCACGTGAC TCACGTGAT - +2 dbcorrdb__USF1__ENCSR000BGM_1__m1-ac-ase-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf-zfh1 4 2.80457e-06 0.0685803 0.00157159 10 ATCACGTGAC CGGGGCCACGTGACCCGGGC + +2 cisbp__M5633-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 2.83979e-06 0.0694414 0.00157159 10 ATCACGTGAC ATCACGTGAT - +2 taipale__MLXIPL_full_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 2.83979e-06 0.0694414 0.00157159 10 ATCACGTGAC ATCACGTGAT - +2 transfac_pro__M07633-bigmax-Mitf-Mondo-SREBP-tgo-Usf 1 3.03434e-06 0.0741987 0.00165996 10 ATCACGTGAC GATCACGTGATC - +2 cisbp__M0187-bigmax-Mitf-Mondo-SREBP-Usf 0 3.25634e-06 0.0796273 0.00172872 10 ATCACGTGAC ATCGCGTGAT + +2 transfac_pro__M08909-Clk-cnc-cyc-Mitf-tgo-Usf -1 3.25634e-06 0.0796273 0.00172872 9 ATCACGTGAC TCACGTGACA - +2 dbcorrdb__SIN3A__ENCSR000BRM_1__m1-Sin3A 3 3.26901e-06 0.0799372 0.00172872 10 ATCACGTGAC CCTGTCACGTGACTCATCGG + +2 cisbp__M0237-Mitf -2 3.72841e-06 0.0911708 0.00194569 8 ATCACGTGAC CACGTGATAA - +2 dbcorrdb__USF1__ENCSR000BIU_1__m1-bigmax-cnc-cwo-cyc-Max-Mitf-Myc-SREBP-tgo-Usf 9 3.80194e-06 0.0929689 0.00194569 10 ATCACGTGAC CCAGGCGTGGTCACGTGACC + +2 dbcorrdb__USF2__ENCSR000ECD_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Sin3A-Spps-SREBP-tgo-Usf 1 3.80194e-06 0.0929689 0.00194569 10 ATCACGTGAC GGTCACGTGACCCGGGCCGG + +2 cisbp__M4080-bigmax-Max-Mitf-Myc-SREBP-tgo-Usf 2 4.2302e-06 0.103441 0.00198898 10 ATCACGTGAC AGATCACGTGATCT + +2 hocomoco__CLOCK_HUMAN.H11MO.0.C-Clk 2 4.2302e-06 0.103441 0.00198898 10 ATCACGTGAC TGTTCACGTGTCTG + +2 transfac_public__M00121-bigmax-Max-Mitf-Myc-SREBP-tgo-Usf 2 4.2302e-06 0.103441 0.00198898 10 ATCACGTGAC AGATCACGTGATCT + +2 cisbp__M0154-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn-Sirt6-bigmax-cyc-dpn-h-tgo 0 4.26265e-06 0.104235 0.00198898 10 ATCACGTGAC GGCACGTGCC + +2 jaspar__MA0965.1-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-SREBP-Sidpn-Sirt6-bigmax-cyc-dpn-h-tgo 0 4.26265e-06 0.104235 0.00198898 10 ATCACGTGAC GGCACGTGCC + +2 yetfasco__YJR060W_1346 0 4.63119e-06 0.113246 0.0020992 8 ATCACGTGAC ACCACGTG + +2 cisbp__M0244-cnc-Mitf 0 4.82887e-06 0.11808 0.00214457 10 ATCACGTGAC TGCACGTGACT - +2 cisbp__M4550-ac-ase-bigmax-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 0 4.82887e-06 0.11808 0.00214457 10 ATCACGTGAC GTCACGTGACC - +2 taipale_cyt_meth__MAX_RNCACGTGYN_FL-Max-Mitf 0 4.86645e-06 0.118999 0.00214457 10 ATCACGTGAC CGCACGTGGC - +2 transfac_pro__M01558-bigmax-Mitf-Mondo-SREBP-Usf 5 5.10989e-06 0.124952 0.00221091 10 ATCACGTGAC GATGCATCACGTGATGCACT + +2 cisbp__M0212-h 0 5.54796e-06 0.135664 0.00226348 10 ATCACGTGAC GGCACGTGCC + +2 homer__KCCACGTGAC_NPAS2-Clk-Mitf-cnc-cyc 0 5.54796e-06 0.135664 0.00226348 10 ATCACGTGAC GCCACGTGAC + +2 jaspar__MA0632.1-h 0 5.54796e-06 0.135664 0.00226348 10 ATCACGTGAC GGCACGTGCC + +2 transfac_pro__M07636-bigmax-Clk-Max-Mitf-Mondo-SREBP-Usf 11 5.5643e-06 0.136064 0.00226348 10 ATCACGTGAC ATCACGTGATAATCACGTGAT + +2 dbcorrdb__SIRT6__ENCSR000DOH_1__m2-Sirt6 6 5.90582e-06 0.144415 0.00238204 10 ATCACGTGAC TCTCCAGGCACGTGACCCAG - +2 cisbp__M0204-Clk-cyc-tai-tgo-Usf -1 6.0905e-06 0.148931 0.00243589 9 ATCACGTGAC TCACGTGAC - +2 transfac_pro__M07601-Clk-E2f1-Max-Myc 0 6.27489e-06 0.15344 0.00246285 10 ATCACGTGAC GGCACGTGGCC - +2 cisbp__M0215-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 0 6.3162e-06 0.15445 0.00246285 10 ATCACGTGAC GGCACGTGCC + +2 cisbp__M4683-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf -2 6.3649e-06 0.155641 0.00246285 8 ATCACGTGAC CACGTGAC - +2 transfac_pro__M08872 2 6.81795e-06 0.166719 0.00258923 10 ATCACGTGAC TCGCCACGTGAG + +2 cisbp__M0206 -1 6.9847e-06 0.170797 0.00258923 9 ATCACGTGAC ACACGTGCC + +2 cisbp__M0234-Clk-E2f1-Max-Myc-gce -1 6.9847e-06 0.170797 0.00258923 9 ATCACGTGAC CCACGTGGC - +2 cisbp__M0160 0 7.18112e-06 0.1756 0.00258923 10 ATCACGTGAC CGCACGTGCT + +2 flyfactorsurvey__Usf_SANGER_5_FBgn0029711-Max-Mitf-Usf 0 7.18112e-06 0.1756 0.00258923 10 ATCACGTGAC ACCACGTGAC + +2 taipale_cyt_meth__ARNT2_RTCACGTGMN_eDBD-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf 0 7.18112e-06 0.1756 0.00258923 10 ATCACGTGAC GGCACGTGAC - +2 cisbp__M0220-Clk-cnc-cyc-Mitf-tai-tgo -1 7.18112e-06 0.1756 0.00258923 9 ATCACGTGAC GCACGTGACC - +2 cisbp__M0153-E2f1-Max-Myc 0 7.99623e-06 0.195532 0.00286144 9 ATCACGTGAC GCCACGTGC + +2 cisbp__M5263-Max-Mitf-Usf 0 8.1537e-06 0.199383 0.00287457 10 ATCACGTGAC ACCACGTGAC + +2 jaspar__MA0603.1-Clk-Mitf-cnc-cyc-tai-tgo -1 8.1537e-06 0.199383 0.00287457 9 ATCACGTGAC GCACGTGACC - +2 cisbp__M0245-Clk-cnc-cyc-Max-Mitf-SREBP-tai-tgo-Usf -2 8.6396e-06 0.211264 0.00302348 8 ATCACGTGAC CACGTGAC - +2 cisbp__M0188-SREBP -1 9.13875e-06 0.22347 0.00305594 9 ATCACGTGAC TCGCGTGAT - +2 cisbp__M0167-Clk-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 0 9.24604e-06 0.226093 0.00305594 10 ATCACGTGAC GGCACGTGCC + +2 cisbp__M0192-dpn-h-Hey-Sidpn 0 9.24604e-06 0.226093 0.00305594 10 ATCACGTGAC GACGCGTGCC + +2 cisbp__M0238-Max-Mitf-Mondo-SREBP-Usf-bigmax-tgo 0 9.24604e-06 0.226093 0.00305594 10 ATCACGTGAC ATCACGTGAT + +2 cisbp__M0191-dpn-E(spl)mbeta-HLH-h-Hey-Sidpn 0 9.24604e-06 0.226093 0.00305594 10 ATCACGTGAC GACGCGTGCC - +2 jaspar__MA1099.1-Hey-Sidpn-dpn-h 0 9.24604e-06 0.226093 0.00305594 10 ATCACGTGAC GACGCGTGCC - +2 cisbp__M0205 -1 1.00215e-05 0.245057 0.00323621 8 ATCACGTGAC TCACGTGC + +2 dbcorrdb__USF1__ENCSR000BGI_1__m1-ac-ase-btd-cnc-CrebB-cyc-E2f1-ERR-E(z)-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-Sap30-sc-Spps-SREBP-Stat92E-tgo-Usf-zfh1 4 1.03379e-05 0.252793 0.00323621 10 ATCACGTGAC CGGGGCCACGTGACCCGGGC + +2 hocomoco__BMAL1_HUMAN.H11MO.0.A-Clk-cyc 0 1.04199e-05 0.254798 0.00323621 10 ATCACGTGAC GCCACGTGACT - +2 taipale_cyt_meth__MYCN_NKCACGTGGN_eDBD-Clk-Max-Mnt-Myc 0 1.04714e-05 0.256058 0.00323621 10 ATCACGTGAC GGCACGTGGT + +2 taipale_cyt_meth__HES7_GGCACGTGYN_eDBD_meth-E(spl)mbeta-HLH-Hey 0 1.04714e-05 0.256058 0.00323621 10 ATCACGTGAC CGCACGTGCC - +2 homer__BCACGTGVDN_PIF5ox 1 1.04714e-05 0.256058 0.00323621 9 ATCACGTGAC CACCACGTGA - +2 cisbp__M5111-cnc-Mitf-SREBP-tgo-Usf -2 1.15728e-05 0.282989 0.00343736 7 ATCACGTGAC CACGTGA + +2 dbcorrdb__USF2__ENCSR000EEF_1__m1-bigmax-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf 7 1.18374e-05 0.289459 0.00343736 10 ATCACGTGAC CGGCGGGGTCACGTGACCCG + +2 dbcorrdb__USF2__ENCSR000ECW_1__m1-cnc-Max-Mitf-Usf -1 1.18374e-05 0.289459 0.00343736 9 ATCACGTGAC TCACGTGACCCGGGCCGGCC + +2 cisbp__M0161 0 1.18445e-05 0.289634 0.00343736 10 ATCACGTGAC AGCACGTGCT + +2 cisbp__M5993-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-Mitf-Mondo-Sirt6-SREBP-tai-tgo-Usf 0 1.18445e-05 0.289634 0.00343736 10 ATCACGTGAC GTCACGTGAC - +2 cisbp__M2322-cnc-cyc-Mitf-SREBP-tgo-Usf 0 1.33222e-05 0.325768 0.00370275 10 ATCACGTGAC GTCATGTGACC - +2 swissregulon__hs__SREBF1_2.p2-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 0 1.33222e-05 0.325768 0.00370275 10 ATCACGTGAC GTCACGTGACC - +2 cisbp__M0253-Sidpn-dpn-h 0 1.33814e-05 0.327215 0.00370275 10 ATCACGTGAC GGCGCGTGTC + +2 jaspar__MA0956.1 0 1.33814e-05 0.327215 0.00370275 10 ATCACGTGAC AGCACGTGCT + +2 taipale__Bhlhb2_DBD_NKCACGTGMN-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-Mitf-Mondo-Sirt6-SREBP-tai-tgo-Usf 0 1.33814e-05 0.327215 0.00370275 10 ATCACGTGAC GTCACGTGAC + +2 cisbp__M6053-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 1.33814e-05 0.327215 0.00370275 10 ATCACGTGAC ATCACGTGAT - +2 flyfactorsurvey__Mitf_SANGER_5_FBgn0263112-Mitf-Mondo-SREBP-Usf-bigmax-cnc-tgo -2 1.35715e-05 0.331863 0.00373364 7 ATCACGTGAC CACGTGA + +2 jaspar__MA0526.1-Mitf-SREBP-Usf-cnc-cyc-tgo 0 1.50356e-05 0.367667 0.0039925 10 ATCACGTGAC GTCATGTGACC + +2 swissregulon__hs__ARNT_ARNT2_BHLHB2_MAX_MYC_USF1.p2-Clk-Max-Myc-Usf-gce-tgo 1 1.50356e-05 0.367667 0.0039925 10 ATCACGTGAC GGCCACGTGGC + +2 cisbp__M0152-Max 0 1.50996e-05 0.369231 0.0039925 10 ATCACGTGAC CGCACGTGCG + +2 hocomoco__BHE40_HUMAN.H11MO.0.A-Sirt6 0 1.50996e-05 0.369231 0.0039925 10 ATCACGTGAC GGCACGTGAC + +2 taipale__Mlx_DBD_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 1.50996e-05 0.369231 0.0039925 10 ATCACGTGAC ATCACGTGAT + +2 homer__TCACGTGAYH_Cbf1-Clk-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo -1 1.50996e-05 0.369231 0.0039925 9 ATCACGTGAC TCACGTGACC + +2 taipale__BHLHB2_DBD_NKCACGTGMN-bigmax-Clk-cnc-cwo-cyc-mio-Mitf-Mondo-Sirt6-SREBP-tgo-Usf 0 1.70186e-05 0.416155 0.00437828 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5305-bigmax-Clk-cnc-cwo-cyc-mio-Mitf-Mondo-Sirt6-SREBP-tgo-Usf 0 1.70186e-05 0.416155 0.00437828 10 ATCACGTGAC ATCACGTGAC - +2 transfac_pro__M07635-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 1.70186e-05 0.416155 0.00437828 10 ATCACGTGAC GTCACGTGAC - +2 taipale_cyt_meth__MLX_NNCAYGTGMYN_FL_meth_repr-bigmax-Mitf 0 1.90833e-05 0.466643 0.0047742 10 ATCACGTGAC TCCACGTGATC + +2 cisbp__M0284-Atf6-CrebA-Xbp1 0 1.91594e-05 0.468505 0.0047742 10 ATCACGTGAC GCCACGTCAC - +2 cisbp__M6345-cyc-Mitf 0 1.91594e-05 0.468505 0.0047742 10 ATCACGTGAC GTCATGTGAT - +2 hocomoco__MITF_HUMAN.H11MO.0.A-Max-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo -1 1.91594e-05 0.468505 0.0047742 9 ATCACGTGAC TCACGTGACC + +2 transfac_pro__M07050-cyc-Mitf 1 2.14614e-05 0.524796 0.00528569 10 ATCACGTGAC AATCATGTGAC - +2 transfac_pro__M01585 0 2.15453e-05 0.526847 0.00528569 10 ATCACGTGAC GGCACGTGGG + +2 cisbp__M4680-Clk-cnc-cyc-Max-Mitf-SREBP-tgo-Usf -2 2.30975e-05 0.564804 0.00563745 8 ATCACGTGAC CACGTGAC - +2 transfac_pro__M01699-bigmax-Clk-cnc-Max-Mitf-Myc-Usf -2 2.37361e-05 0.580419 0.00576375 6 ATCACGTGAC CACGTG + +2 taipale_tf_pairs__RFX3_SREBF2_NNRGYAACNTCACGTGAY_CAP_repr-Rfx-SREBP 8 2.41001e-05 0.589319 0.00579508 10 ATCACGTGAC ATGGCAACATCACGTGAC + +2 factorbook__USF-Max-Mitf-Myc-SREBP-Usf-cnc-cwo-cyc-tgo 1 2.41087e-05 0.589529 0.00579508 10 ATCACGTGAC GGCCACGTGAC + +2 taipale_tf_pairs__ELK1_SREBF2_RWCACGTGNNCGGAANN_CAP_repr-SREBP 0 2.43877e-05 0.596353 0.0058327 10 ATCACGTGAC ATCACGTGACCGGAAGT + +2 dbcorrdb__USF2__ENCSR000EHG_1__m1-bigmax-btd-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf 8 2.57786e-05 0.630364 0.00606777 10 ATCACGTGAC CCGGCGGGGTCACGTGACCC + +2 dbcorrdb__MAX__ENCSR000ECN_1__m1-Brf-brm-btd-Clk-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-tgo-tna-Usf-vtd 0 2.57786e-05 0.630364 0.00606777 10 ATCACGTGAC GCCACGTGCCCCGGGGGGGG - +2 cisbp__M0179-Mitf-tgo 1 2.63219e-05 0.64365 0.00606777 10 ATCACGTGAC AAGCACGTGATT - +2 hocomoco__USF1_HUMAN.H11MO.0.A-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Usf-ac-ase-bigmax-cnc-cwo-cyc-l(1)sc-nau-sc-tgo 1 2.63219e-05 0.64365 0.00606777 10 ATCACGTGAC GGTCACGTGACC - +2 cisbp__M4465-cnc-Max-Mitf-Myc-tgo-Usf 1 2.66148e-05 0.65081 0.00606777 10 ATCACGTGAC GACCACGTGACTG - +2 transfac_public__M00220-bigmax-cnc-Mitf-Mondo-SREBP-tgo-Usf 0 2.70524e-05 0.661511 0.00606777 10 ATCACGTGAC GTCACGTGATC - +2 cisbp__M0164-bigmax-mio 0 2.71555e-05 0.664032 0.00606777 10 ATCACGTGAC AGCACGTGCT + +2 jaspar__MA0966.1-bigmax-mio 0 2.71555e-05 0.664032 0.00606777 10 ATCACGTGAC AGCACGTGCT + +2 transfac_pro__M00303-Clk-cnc-Mitf-tgo-Usf -1 2.71555e-05 0.664032 0.00606777 9 ATCACGTGAC TCACGTGACT - +2 dbcorrdb__MYC__ENCSR000DOS_1__m1-Clk-E2f1-gce-Max-Myc-Usf 1 2.91929e-05 0.713855 0.00649255 10 ATCACGTGAC AGCCACGTGCTCGGGGGGGG - +2 cisbp__M5107-bigmax-Mitf-Mondo -2 2.99412e-05 0.732151 0.0065254 8 ATCACGTGAC CACGTGAT - +2 flyfactorsurvey__Mio_bigmax_SANGER_5_FBgn0032940-Mitf-Mondo-bigmax -2 2.99412e-05 0.732151 0.0065254 8 ATCACGTGAC CACGTGAT - +2 taipale_cyt_meth__TFEC_RNCAYGTGAYN_eDBD_meth-Mitf-Usf 0 3.03225e-05 0.741476 0.0065254 10 ATCACGTGAC ACCATGTGACC + +2 cisbp__M3944-bigmax-cnc-Mitf-Mondo-SREBP-tgo-Usf 0 3.03225e-05 0.741476 0.0065254 10 ATCACGTGAC GTCACGTGATC - +2 cisbp__M5634-Max-Mnt-Myc 0 3.04374e-05 0.744287 0.0065254 10 ATCACGTGAC ACCACGTGCC + +2 taipale__MNT_DBD_NNCACGTGNN-Max-Mnt-Myc 0 3.04374e-05 0.744287 0.0065254 10 ATCACGTGAC ACCACGTGCC + +2 cisbp__M4637-ac-ase-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 2 3.24043e-05 0.792381 0.00675837 10 ATCACGTGAC CGGCCACGTGACCC - +2 homer__ACCACGTGGTCN_Max-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-cyc-emc 0 3.31176e-05 0.809825 0.00675837 10 ATCACGTGAC ACCACGTGGTCT + +2 transfac_pro__M01793-bigmax-Clk-cnc-cyc-Mitf-SREBP-tgo 1 3.31176e-05 0.809825 0.00675837 10 ATCACGTGAC AAGCACGTGACC - +2 transfac_public__M00123-Max-Myc 1 3.31176e-05 0.809825 0.00675837 10 ATCACGTGAC TGACACGTGGTA - +2 cisbp__M4451-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 0 3.39517e-05 0.83022 0.00675837 10 ATCACGTGAC GTCACGTGACC - +2 homer__GHCACGTG_CLOCK-Clk-Usf 0 3.39827e-05 0.83098 0.00675837 8 ATCACGTGAC GTCACGTG + +2 cisbp__M5614-Max-Mnt-Myc 0 3.40802e-05 0.833362 0.00675837 10 ATCACGTGAC ACCACGTGCT + +2 taipale__MLX_full_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 3.40802e-05 0.833362 0.00675837 10 ATCACGTGAC ATCACGTGAT + +2 taipale_cyt_meth__SREBF2_ATCACGTGAY_eDBD-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 3.40802e-05 0.833362 0.00675837 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5632-bigmax-Mitf-Mondo-SREBP-tgo-Usf 0 3.40802e-05 0.833362 0.00675837 10 ATCACGTGAC ATCACGTGAT - +2 cisbp__M2956-bigmax-Clk-Mitf-SREBP-tgo 3 3.48308e-05 0.851718 0.00687857 10 ATCACGTGAC GCGGGCACGTGACAAC - +2 transfac_pro__M01577-cyc-Mitf-tgo 5 3.58876e-05 0.877559 0.00705798 10 ATCACGTGAC GATCAGTCACGTGACTGATCG + +2 cisbp__M4610-Clk-E2f1-gce-Max-Myc-tgo-Usf 0 3.79754e-05 0.928612 0.00719938 10 ATCACGTGAC GCCACGTGGCC + +2 cisbp__M4578-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 0 3.79754e-05 0.928612 0.00719938 10 ATCACGTGAC GCCACGTGACC - +2 taipale__MAX_DBD_NNCACGTGNN_repr-Max-Mnt-Myc 0 3.81192e-05 0.932129 0.00719938 10 ATCACGTGAC ACCACGTGCT + +2 taipale__Srebf1_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 3.81192e-05 0.932129 0.00719938 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5994-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-mio-Mitf-Sirt6-SREBP-tai-tgo-Usf 0 3.81192e-05 0.932129 0.00719938 10 ATCACGTGAC AGCACGTGAC - +2 cisbp__M6097-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 3.81192e-05 0.932129 0.00719938 10 ATCACGTGAC ATCACGTGAC - +2 homer__GNCACGTG_BMAL1-Clk-Mitf-SREBP-Usf-cnc-cyc-tai-tgo 0 3.84935e-05 0.941281 0.00724133 8 ATCACGTGAC GTCACGTG + +2 transfac_public__M00236-bigmax-Clk-Mitf-tgo 3 3.91643e-05 0.957684 0.00733851 10 ATCACGTGAC GCGGGCACGTGACAAC - +2 transfac_pro__M03123-bigmax-Clk-cnc-Mitf-Mondo-SREBP-Usf 3 3.9439e-05 0.964402 0.00736101 10 ATCACGTGAC AGAATCACGTGACAATT + +2 hocomoco__BMAL1_MOUSE.H11MO.0.A-Clk-Mitf-Usf-cyc -1 4.03215e-05 0.985981 0.00749632 9 ATCACGTGAC CCACGTGAC - +2 transfac_pro__M08869-Clk-cyc 0 4.14854e-05 1.01444 0.00768186 10 ATCACGTGAC TCCACGTGAGCC - +2 cisbp__M2957-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 5 4.20434e-05 1.02809 0.00768186 10 ATCACGTGAC CAAAGGTCACGTGACCTTTG + +2 cisbp__M4638-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 2 4.21265e-05 1.03012 0.00768186 10 ATCACGTGAC GGGTCACGTGACC - +2 transfac_public__M00217-Usf -1 4.35199e-05 1.06419 0.00784577 8 ATCACGTGAC CCACGTGC + +2 dbcorrdb__MAX__ENCSR000EHS_1__m1-Clk-cnc-E2f1-E(z)-gce-Max-Myc-Sap30-SREBP-tgo-Usf 3 4.73524e-05 1.15791 0.00822851 10 ATCACGTGAC GCAGCCACGTGGTCCCCGCG + +2 transfac_public__M00539-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 5 4.73524e-05 1.15791 0.00822851 10 ATCACGTGAC CAAAGGTCACGTGACCTTTG + +2 cisbp__M4579-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 2 5.26483e-05 1.28741 0.00892613 10 ATCACGTGAC CGGTCACGTGACC - +2 transfac_pro__M04743-Max-Myc 0 5.30188e-05 1.29647 0.00892613 10 ATCACGTGAC ACCACGTGGC + +2 dbcorrdb__MAX__ENCSR000EFV_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-tgo-tna-Usf-vtd-zfh1 4 5.32635e-05 1.30245 0.00892613 10 ATCACGTGAC CGCGGCCACGTGGCCCGGGC + +2 transfac_public__M00615-Max-Myc 5 5.32635e-05 1.30245 0.00892613 10 ATCACGTGAC CAAGTGTCACGTGTTACTTG + +2 dbcorrdb__MAX__ENCSR000EUP_1__m1-btd-cnc-CrebB-E2f1-ERR-E(z)-Max-Myc-Spps-SREBP-Stat92E-Usf-vtd 6 5.32635e-05 1.30245 0.00892613 10 ATCACGTGAC GGCGGGGCCACGTGCTCGGG - +2 dbcorrdb__MYC__ENCSR000EGS_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-Max-Myc-pho-phol-RpII215-Sap30-Sin3A-Spps-SREBP-tgo-tna-Usf 3 5.32635e-05 1.30245 0.00892613 10 ATCACGTGAC GCGGCCACGTGGCCCGCGCG - +2 taipale_tf_pairs__ARNTL_PITX1_NNCACGTGNNNNRGMTTAN_CAP_repr-cyc-Ptx1 9 5.46692e-05 1.33683 0.00909763 10 ATCACGTGAC TTAATCCCTGTCACGTGCC - +2 cisbp__M6160-Clk-cyc-Sirt6-tgo -1 5.66816e-05 1.38604 0.00936702 9 ATCACGTGAC GCACGTGAC - +2 cisbp__M4596-ac-ase-cnc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-Sap30-sc-tgo-Usf 1 5.8764e-05 1.43695 0.00959434 10 ATCACGTGAC GGCCACGTGACCC - +2 homer__GGTCACGTGA_USF1-Max-Mitf-Myc-SREBP-Usf-cnc-cwo-tgo -1 5.90651e-05 1.44432 0.00959434 9 ATCACGTGAC TCACGTGACC - +2 dbcorrdb__MAX__ENCSR000DZF_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Snr1-Spps-Spt20-SREBP-Taf1-tgo-tna-Usf-vtd 9 5.98374e-05 1.46321 0.00963801 10 ATCACGTGAC CCCGCCCCGGCCACGTGCCC + +2 cisbp__M4481-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 4 6.0144e-05 1.4707 0.00963801 10 ATCACGTGAC CCGGGCCACGTGACC - +2 cisbp__M4514-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 4 6.0144e-05 1.4707 0.00963801 10 ATCACGTGAC CGCGGCCACGTGACC - +2 hocomoco__USF2_HUMAN.H11MO.0.A-CrebB-E2f1-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Spps-Usf-ac-ase-btd-cnc-cyc-l(1)sc-nau-sc 7 6.13513e-05 1.50022 0.00979848 10 ATCACGTGAC CGCCGCGGCCACGTGACCC - +2 transfac_pro__M01779-bigmax-Mitf -2 6.22215e-05 1.5215 0.00990424 8 ATCACGTGAC CACGTGAT - +2 cisbp__M0181-bigmax-Mondo-tgo 1 6.33404e-05 1.54886 0.0100154 8 ATCACGTGAC GATCACGTG + +2 hocomoco__USF1_MOUSE.H11MO.0.A-Max-Mitf-Myc-SREBP-Usf-cnc-cyc-tgo 1 6.55227e-05 1.60223 0.010258 10 ATCACGTGAC GGCCACGTGACCC - +2 taipale_cyt_meth__HEY1_NGCACGTGYN_eDBD-dpn-Hey-Sidpn 0 6.57372e-05 1.60747 0.010258 10 ATCACGTGAC GACACGTGCC - +2 dbcorrdb__BHLHE40__ENCSR000EGV_1__m1-bigmax-btd-cnc-CrebB-cwo-cyc-E2f1-ERR-ewg-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-Stat92E-tgo-Usf-zfh1 4 6.71406e-05 1.64179 0.0103749 10 ATCACGTGAC CCCGGGCACGTGCCCGGGCG + +2 dbcorrdb__MAX__ENCSR000EDS_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-cwo-E2f1-ERR-E(z)-gce-HDAC1-Hey-Max-Mitf-Mnt-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Stat92E-Taf1-tgo-tna-Usf-vtd-zfh1 4 6.71406e-05 1.64179 0.0103749 10 ATCACGTGAC CCGGGCCACGTGGCCCCGGC - +2 cisbp__M4086-Max-Usf -1 6.98619e-05 1.70833 0.0107605 8 ATCACGTGAC CCACGTGC + +2 cisbp__M5309-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 7.30929e-05 1.78734 0.0109741 10 ATCACGTGAC GTCACGTGAC - +2 taipale_cyt_meth__CLOCK_NMCAYGYGYN_eDBD_meth_repr-Clk 0 7.30929e-05 1.78734 0.0109741 10 ATCACGTGAC AACACATGTC - +2 taipale_cyt_meth__HEY2_NGCACGTGYN_eDBD-dpn-Hey-Sidpn 0 7.30929e-05 1.78734 0.0109741 10 ATCACGTGAC GACACGTGCC - +2 cisbp__M6517-Mitf-Usf -1 7.30929e-05 1.78734 0.0109741 9 ATCACGTGAC CCACATGACC - +2 dbcorrdb__MYC__ENCSR000EHR_1__m1-Brf-Clk-cnc-E2f1-Eip74EF-E(z)-gce-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-tna-Usf 8 7.52451e-05 1.83997 0.0112617 10 ATCACGTGAC CCCCGCCGGCCACGTGCTCC - +2 taipale_tf_pairs__TEAD4_HES7_RCATTCCNNCRCGYGYN_CAP_repr-sd 7 7.81612e-05 1.91127 0.0115542 10 ATCACGTGAC GCATTCCAGCACGTGCC + +2 hocomoco__BHE40_MOUSE.H11MO.0.A-Clk-cyc-tai-tgo -1 7.88173e-05 1.92732 0.0115542 9 ATCACGTGAC GCACGTGAC + +2 cisbp__M0175-Mnt -1 7.88173e-05 1.92732 0.0115542 9 ATCACGTGAC GCACGTGCA - +2 cisbp__M4609-Clk-E2f1-gce-Max-Mnt-Myc-tgo-Usf 0 8.08885e-05 1.97797 0.0115542 10 ATCACGTGAC GCCACGTGCTC + +2 hocomoco__MYC_HUMAN.H11MO.0.A-E2f1-Max-Myc 0 8.08885e-05 1.97797 0.0115542 10 ATCACGTGAC GCCACGTGCTC + +2 jaspar__MA0988.1 0 8.11949e-05 1.98546 0.0115542 10 ATCACGTGAC CGCACGTGCG + +2 taipale__BHLHE41_full_GTCACGTGAC-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 8.11949e-05 1.98546 0.0115542 10 ATCACGTGAC GTCACGTGAC + +2 taipale__SREBF2_DBD_RTCACGTGAY-bigmax-cnc-cwo-Mitf-Mondo-SREBP-tgo-Usf 0 8.11949e-05 1.98546 0.0115542 10 ATCACGTGAC ATCACGTGAC + +2 cisbp__M5866-bigmax-cnc-cwo-Mitf-Mondo-SREBP-tgo-Usf 0 8.11949e-05 1.98546 0.0115542 10 ATCACGTGAC ATCACGTGAC - +2 taipale_cyt_meth__BHLHE40_GTCACGTGAC_eDBD-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 8.11949e-05 1.98546 0.0115542 10 ATCACGTGAC GTCACGTGAC - +2 yetfasco__YFR034C_2222-E2f1-Max-Myc -1 8.11949e-05 1.98546 0.0115542 9 ATCACGTGAC CCACGTGCCT - +2 transfac_pro__M09510-bigmax 7 8.17222e-05 1.99835 0.0115542 10 ATCACGTGAC CGTGAAAAGCACGTGACACCT + +2 jaspar__MA0409.1-Clk-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cyc-tgo -2 8.18125e-05 2.00056 0.0115542 7 ATCACGTGAC CACGTGA + +2 transfac_pro__M01954-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf -2 8.18125e-05 2.00056 0.0115542 7 ATCACGTGAC CACGTGA - +2 cisbp__M4429-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 4 8.35756e-05 2.04367 0.0117683 10 ATCACGTGAC CCCGGTCACGTGACC - +2 cisbp__M4515-btd-cnc-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-Usf 4 8.6136e-05 2.10628 0.0120931 10 ATCACGTGAC CGCGGTCACGTGACCC - +2 cisbp__M4645-Max-Myc 1 8.97739e-05 2.19524 0.0123594 10 ATCACGTGAC GGCCACGTGCT + +2 cisbp__M0250 0 9.01107e-05 2.20348 0.0123594 10 ATCACGTGAC CGCACGTGCG + +2 taipale_cyt_meth__BHLHE41_GTCACGTGAC_eDBD_meth-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 9.01107e-05 2.20348 0.0123594 10 ATCACGTGAC GTCACGTGAC - +2 taipale_cyt_meth__HEY2_NGCACGTGYN_FL_meth-dpn-h-Hey-Sidpn 0 9.01107e-05 2.20348 0.0123594 10 ATCACGTGAC GACACGTGCC - +2 cisbp__M6530-ac-ase-cnc-cwo-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-Usf -1 9.01107e-05 2.20348 0.0123594 9 ATCACGTGAC CCACGTGACC - +2 dbcorrdb__MAX__ENCSR000EEZ_1__m1-Brf-brm-btd-cnc-CrebB-E2f1-ERR-E(z)-Max-Mitf-Myc-Nelf-E-RpII215-Sap30-Sin3A-Spps-SREBP-Stat92E-tgo-Usf-vtd-zfh1 6 9.4179e-05 2.30296 0.0128434 10 ATCACGTGAC GCCCGGCCCACGTGGCCGCC + +2 dbcorrdb__MYC__ENCSR000EZD_1__m1-Brf-brm-Clk-E2f1-E(z)-gce-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-SREBP-tgo-tna-Usf-vtd 1 9.4179e-05 2.30296 0.0128434 10 ATCACGTGAC GGCCACGTGCTCGCGGGGGG + +2 cisbp__M0230-Mitf-Mondo-SREBP-Usf-bigmax-cwo -1 9.76283e-05 2.3873 0.0131361 9 ATCACGTGAC TCACGTGAT - +2 transfac_pro__M03890-cnc-Mitf-Usf 0 9.80855e-05 2.39848 0.0131361 10 ATCACGTGAC GTCACGTGACTG + +2 taipale_cyt_meth__USF2_MNCAYGTGAYN_eDBD_meth_repr-Mitf-Usf 0 9.9545e-05 2.43417 0.0131361 10 ATCACGTGAC ACCATGTGACC + +2 cisbp__M4542-Max-Myc 1 9.9545e-05 2.43417 0.0131361 10 ATCACGTGAC GGCCACGTGCT - +2 hocomoco__MAX_MOUSE.H11MO.0.A-E2f1-Max-Myc 0 9.9545e-05 2.43417 0.0131361 10 ATCACGTGAC GCCACGTGCTC - +2 hocomoco__MXI1_HUMAN.H11MO.1.A-Max-Myc 1 9.9545e-05 2.43417 0.0131361 10 ATCACGTGAC GAGCACGTGGG - +2 hocomoco__MLX_HUMAN.H11MO.0.D-bigmax -1 9.9545e-05 2.43417 0.0131361 9 ATCACGTGAC GCACGTGATCA - +2 taipale_cyt_meth__HEY2_NGCACGTGYN_FL-dpn-E(spl)mbeta-HLH-h-Hey-Sidpn 0 9.99133e-05 2.44318 0.0131361 10 ATCACGTGAC GACACGTGCC - +2 transfac_pro__M03867-Max-Myc -2 0.000109371 2.67445 0.0138991 8 ATCACGTGAC CACGTGGC + +2 cisbp__M0231-Mitf-Mondo-SREBP-Usf-bigmax 0 0.000110681 2.70649 0.0138991 10 ATCACGTGAC ATCACGTGAT + +2 taipale_cyt_meth__BHLHE40_GTCACGTGAC_eDBD_meth_repr-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.000110681 2.70649 0.0138991 10 ATCACGTGAC GTCACGTGAC + +2 taipale_cyt_meth__BHLHE41_GTCACGTGAC_eDBD-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.000110681 2.70649 0.0138991 10 ATCACGTGAC GTCACGTGAC + +2 transfac_pro__M01034-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf -1 0.000110681 2.70649 0.0138991 9 ATCACGTGAC CCACGTGACC + +2 hocomoco__TFE3_HUMAN.H11MO.0.B-Clk-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo -1 0.000110681 2.70649 0.0138991 9 ATCACGTGAC TCACGTGACC - +2 swissregulon__sacCer__ABF1 3 0.000111272 2.72094 0.0139365 10 ATCACGTGAC CGTATATAGTGAT - +2 taipale_tf_pairs__ETV2_CLOCK_NNCACGTGNNNNNCCGGAWRY_CAP-Clk-pnt 11 0.000114195 2.7924 0.0142277 10 ATCACGTGAC GCATCCGGTGTGACACGTGTC - +2 swissregulon__sacCer__CBF1-Mitf-SREBP-Sirt6-Usf-bigmax-cnc-cyc-tgo -2 0.000117158 2.86487 0.0145588 7 ATCACGTGAC CACGTGA - +2 cisbp__M3642-Max-Mnt-Myc 1 0.000120482 2.94614 0.0146488 10 ATCACGTGAC TCCCACGTGTCG + +2 transfac_public__M00055-Myc 1 0.000120482 2.94614 0.0146488 10 ATCACGTGAC TCCCACGTGTCA + +2 cisbp__M4643-Myc 0 0.000121914 2.98117 0.0146488 8 ATCACGTGAC ACCACGTG + +2 taipale_cyt_meth__MLX_YNCACGTGMYN_FL-bigmax-Mitf 0 0.000122067 2.9849 0.0146488 10 ATCACGTGAC TGCACGTGACC + +2 transfac_pro__M07042-Sidpn 0 0.000122067 2.9849 0.0146488 10 ATCACGTGAC CTCGTGTGCCC + +2 cisbp__M6335-Max-Myc 0 0.000122067 2.9849 0.0146488 10 ATCACGTGAC ACCACGTGGCT - +2 hocomoco__ATF3_HUMAN.H11MO.0.A-Mitf-SREBP-Usf-cnc-cwo-tgo 0 0.000122067 2.9849 0.0146488 10 ATCACGTGAC ATCACGTCACC - +2 flyfactorsurvey__HLH106_SANGER_5_2_FBgn0015234-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-tgo 0 0.0001225 2.99548 0.0146488 10 ATCACGTGAC ATCACGTGAC + +2 taipale__BHLHB3_full_NKCACGTGMN_repr-bigmax-Clk-cyc-E(spl)m5-HLH-E(spl)mbeta-HLH-h-Mitf-Sirt6-SREBP-tgo-Usf 0 0.0001225 2.99548 0.0146488 10 ATCACGTGAC GGCACGTGAC + +2 cisbp__M5306-bigmax-Clk-cyc-E(spl)m5-HLH-E(spl)mbeta-HLH-h-Mitf-Sirt6-SREBP-tgo-Usf 0 0.0001225 2.99548 0.0146488 10 ATCACGTGAC GGCACGTGAC - +2 transfac_pro__M01843 -1 0.0001225 2.99548 0.0146488 9 ATCACGTGAC GCACGTGAAC - +2 transfac_pro__M00726-Usf -2 0.000128867 3.15118 0.0153716 6 ATCACGTGAC CACGTG - +2 dbcorrdb__MXI1__ENCSR000EIA_1__m1-E2f1-Max-Mnt-Myc-Sap30-Usf 8 0.000130784 3.19807 0.015484 10 ATCACGTGAC GCCCCGGCACCACGTGGCTG + +2 dbcorrdb__BHLHE40__ENCSR000DZJ_1__m1-bigmax-Brf-btd-Clk-cnc-cwo-cyc-E2f1-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-tgo-tna-Usf-zfh1 8 0.000130784 3.19807 0.015484 10 ATCACGTGAC CCCCCCCGGTCACGTGCCGG - +2 dbcorrdb__NFE2__ENCSR000DZY_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf-zfh1 6 0.000130784 3.19807 0.015484 10 ATCACGTGAC GGGCGGGTCACGTGACGGGG - +2 predrem__nrMotif2416-Max-Mitf-Usf-cnc -1 0.00013349 3.26423 0.0156026 9 ATCACGTGAC CCACGTGAC + +2 taipale_tf_pairs__ERF_SREBF2_NSCGGAARNCACGTGNN_CAP_repr-Ets21C-SREBP 0 0.000134088 3.27886 0.0156026 10 ATCACGTGAC ATCACGTGATTTCCGGC - +2 taipale_cyt_meth__TFEB_NNCACGTGAYN_eDBD-bigmax-cnc-Mitf-Usf 0 0.000134994 3.30102 0.0156026 10 ATCACGTGAC CGCACGTGACC + +2 taipale_cyt_meth__TFEC_MNCACGTGAYN_eDBD-cnc-cyc-Max-Mitf-Usf 0 0.000134994 3.30102 0.0156026 10 ATCACGTGAC CCCACGTGACC + +2 taipale_cyt_meth__CLOCK_NMCAYGTGYN_eDBD-Clk-Hey-Met-Myc-tai 0 0.000135459 3.31239 0.0156026 10 ATCACGTGAC GCCACGTGCC + +2 taipale_cyt_meth__HEY2_NGCACGTGYN_eDBD_meth-Hey-Sidpn 0 0.000135459 3.31239 0.0156026 10 ATCACGTGAC GACACGTGCC - +2 transfac_pro__M01807 -2 0.000135459 3.31239 0.0156026 8 ATCACGTGAC CATGTGAAAA - +2 dbcorrdb__MAX__ENCSR000BLP_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-tgo-tna-Usf-vtd 1 0.000145602 3.56041 0.0163744 10 ATCACGTGAC GGCCACGTGCGCGGGGCGGG - +2 dbcorrdb__MXI1__ENCSR000ECU_1__m1-Brf-brm-btd-Clk-CTCF-E2f1-ERR-E(z)-gce-Hcf-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf-vtd 9 0.000145602 3.56041 0.0163744 10 ATCACGTGAC CCCCCCGCCGCCACGTGGGC - +2 dbcorrdb__MYC__ENCSR000EZU_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf 7 0.000145602 3.56041 0.0163744 10 ATCACGTGAC CCCGGCGGCCACGTGGTCCG - +2 dbcorrdb__MYC__ENCSR000EZV_1__m1-Brf-btd-Clk-cnc-E2f1-Eip74EF-E(z)-gce-Max-Myc-pho-phol-RpII215-Sap30-Spps-tgo-Usf 2 0.000145602 3.56041 0.0163744 10 ATCACGTGAC CGACCACGTGGCCCCGGGGG - +2 dbcorrdb__MYC__ENCSR000FAZ_1__m1-btd-Clk-cnc-E2f1-E(z)-gce-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-tgo-tna-Usf 1 0.000145602 3.56041 0.0163744 10 ATCACGTGAC GGCCACGTGGTCCCCGGGGG - +2 hocomoco__MYCN_HUMAN.H11MO.0.A-Max-Myc-Sap30 1 0.000147467 3.60602 0.0163744 10 ATCACGTGAC GCCCACGTGGCC - +2 factorbook__MAX-Max-Mitf-Myc-Usf-tgo 1 0.000148624 3.63429 0.0163744 10 ATCACGTGAC GACCACGTGACCCC + +2 transfac_pro__M00985-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.000148624 3.63429 0.0163744 10 ATCACGTGAC CTGTCACGTGACCA + +2 transfac_pro__M02881-Max 2 0.000148624 3.63429 0.0163744 10 ATCACGTGAC CAGTCGCGTGGCAC - +2 cisbp__M0257-Myc 1 0.000149163 3.64748 0.0163744 10 ATCACGTGAC GGACACGTGGG + +2 taipale_cyt_meth__USF2_MNCACGTGAYN_eDBD-cnc-cyc-Max-Mitf-Usf 0 0.000149163 3.64748 0.0163744 10 ATCACGTGAC CCCACGTGACC + +2 transfac_pro__M09497-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf 8 0.000149363 3.65238 0.0163744 10 ATCACGTGAC ACGTGAATGTCACGTGAC + +2 hocomoco__MAX_HUMAN.H11MO.0.A-E2f1-Max-Myc -1 0.000149659 3.65961 0.0163744 9 ATCACGTGAC CCACGTGCTC - +2 homer__NCCACGTG_c-Myc-Max-Myc-Sap30-Usf-tgo 0 0.000150902 3.69001 0.0164349 8 ATCACGTGAC ACCACGTG + +2 dbcorrdb__MAX__ENCSR000DYG_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tgo-tna-Usf-vtd 9 0.000161932 3.95973 0.0172079 10 ATCACGTGAC CCCCCCGCGGCCACGTGCCC + +2 taipale_tf_pairs__TEAD4_HES7_RCATTCCNNNNNCRCGYGYN_CAP_repr-sd 10 0.000161932 3.95973 0.0172079 10 ATCACGTGAC ACATTCCACCGACACGTGCG + +2 taipale_tf_pairs__ERF_HES7_NNCACGTGNNNNCCGGAANN_CAP_repr-Ets21C 10 0.000161932 3.95973 0.0172079 10 ATCACGTGAC ACTTCCGGTGAGCACGTGAA - +2 taipale_tf_pairs__GCM2_HES7_RTRNKGGTNNNGCACGYGNN_CAP_repr-gcm-gcm2 0 0.000161932 3.95973 0.0172079 10 ATCACGTGAC GACACGTGCCATACCCGCAT - +2 taipale_tf_pairs__GCM2_MAX_NTRNGGGNNNCACGTG_CAP_repr-gcm-gcm2-Max 8 0.000162438 3.9721 0.0172079 8 ATCACGTGAC ATGCGGGTAACACGTG + +2 taipale_cyt_meth__USF1_MNCACGTGAYN_FL-cnc-cyc-Mitf-Usf 0 0.000164678 4.02688 0.0172079 10 ATCACGTGAC CCCACGTGACC + +2 transfac_pro__M07693-Atf6-CrebA-Xbp1 0 0.000165204 4.03972 0.0172079 10 ATCACGTGAC GCCACGTCAC + +2 taipale_cyt_meth__HEY1_NGCACGTGYN_FL_repr-dpn-Hey-Sidpn 0 0.000165204 4.03972 0.0172079 10 ATCACGTGAC GACACGTGCC - +2 taipale_cyt_meth__MAX_RNCATGTGYN_FL_meth_repr-Max 0 0.000165204 4.03972 0.0172079 10 ATCACGTGAC AGCACATGGT - +2 taipale_cyt_meth__NPAS2_NMCAYGYGYN_eDBD_meth-Clk 0 0.000165204 4.03972 0.0172079 10 ATCACGTGAC TACACATGTC - +2 transfac_pro__M02011-h-Sidpn 0 0.000165204 4.03972 0.0172079 10 ATCACGTGAC GGCGCGTGCC - +2 cisbp__M4628-ac-ase-bigmax-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-tgo-Usf -1 0.000165204 4.03972 0.0172079 9 ATCACGTGAC CCACGTGACC + +2 transfac_pro__M09504 0 0.000165232 4.04041 0.0172079 10 ATCACGTGAC ACCACGTGAAACACGTG - +2 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNNNNNNNNRTGCGGGYRN_CAP-gcm-gcm2-Max 18 0.00017725 4.33429 0.0184193 10 ATCACGTGAC CTACCCGCATCCCCCCCAAGCACGTGCC - +2 dbcorrdb__MXI1__ENCSR000DZI_1__m1-Brf-E2f1-E(z)-Max-Myc-RpII215-Sap30-Usf 7 0.000179913 4.39942 0.018451 10 ATCACGTGAC CCCCGGAACCACGTGGGCGG + +2 dbcorrdb__MYC__ENCSR000EGJ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-Hcf-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf 8 0.000179913 4.39942 0.018451 10 ATCACGTGAC CCCCGGCCGCCACGTGGGCG + +2 dbcorrdb__BHLHE40__ENCSR000EDT_1__m1-Brf-brm-btd-cnc-CrebB-CTCF-cyc-E2f1-E(z)-h-HDAC1-Max-Myc-Nelf-E-RpII215-Sin3A-Spps-tai-tgo-tna-Usf 1 0.000179913 4.39942 0.018451 10 ATCACGTGAC GGGCACGTGACCGGGGGGGG - +2 dbcorrdb__SIN3A__ENCSR000BLR_1__m1-Max-Myc-Sin3A 7 0.000179913 4.39942 0.018451 10 ATCACGTGAC GCGCGGTCCCACGTGCTGAC - +2 dbcorrdb__STAT1__ENCSR000EZK_1__m2-Stat92E 3 0.000179913 4.39942 0.018451 10 ATCACGTGAC GAAATCAGGTGACTTCCTGG - +2 transfac_pro__M04720-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf -1 0.000180832 4.42189 0.018451 9 ATCACGTGAC TCACGTGAC + +2 cisbp__M4500-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 0 0.000181655 4.44202 0.018451 10 ATCACGTGAC GTCACGTGACC - +2 hdpi__TFEB-Mitf -2 0.000184892 4.52117 0.0185863 7 ATCACGTGAC CACGTGG - +2 cisbp__M2355-Max -1 0.000185887 4.54549 0.0185863 8 ATCACGTGAC CCACGTGA + +2 cisbp__M0247-Mitf-Usf -2 0.000185887 4.54549 0.0185863 8 ATCACGTGAC CACGTGAT - +2 jaspar__MA0562.1-Max -1 0.000185887 4.54549 0.0185863 8 ATCACGTGAC CCACGTGA - +2 cisbp__M4480-ac-ase-btd-cnc-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-Usf 3 0.000192359 4.70376 0.0191932 10 ATCACGTGAC CCCGCCACGTGACCC - +2 cisbp__M0183-Clk-Hey-tai 0 0.000199692 4.88307 0.0194237 9 ATCACGTGAC GACACGTGC + +2 swissregulon__sacCer__RTG3-Clk-Mitf-bigmax-cyc-tgo -1 0.000199692 4.88307 0.0194237 9 ATCACGTGAC GCACGTGAC - +2 dbcorrdb__MYC__ENCSR000DLZ_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-cwo-E2f1-Eip74EF-ERR-E(z)-gce-HDAC1-Hey-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-Taf1-tgo-tna-Us 6 0.000199693 4.8831 0.0194237 10 ATCACGTGAC CCGGCGGCCACGTGGCCCCG - +2 dbcorrdb__MYC__ENCSR000DMJ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-SREBP-Stat92E-Taf1-tna-Usf-vtd-zfh1 6 0.000199693 4.8831 0.0194237 10 ATCACGTGAC CCCGCGGCCACGTGCGCCGC - +2 taipale_cyt_meth__USF1_RNCAYGTGACN_FL_meth-Mitf-Usf 0 0.000200217 4.89591 0.0194237 10 ATCACGTGAC ACCATGTGACC + +2 cisbp__M4552-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 0 0.000200217 4.89591 0.0194237 10 ATCACGTGAC GTCACGTGACC - +2 cisbp__M0258-Clk-CrebA 0 0.000200791 4.90995 0.0194237 10 ATCACGTGAC GCCACGTGTC + +2 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 13 0.000203248 4.97002 0.0195817 10 ATCACGTGAC GCCTGAGGCCATGGGCACGTGCC - +2 transfac_pro__M08802-Mondo 2 0.000203805 4.98365 0.0195957 10 ATCACGTGAC GTGTCACGTGCAC - +2 tfdimers__MD00500-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 4 0.000217675 5.32281 0.0205437 10 ATCACGTGAC TAGTTCCACCTGCCCAGGCATGCCTACTCT + +2 transfac_pro__M08950-Clk-cnc-Max-Mitf-Myc-Usf -2 0.000218549 5.34418 0.0205437 6 ATCACGTGAC CACGTG + +2 taipale_cyt_meth__HEY1_NGCACGTGYN_eDBD_meth-Hey-Sidpn 0 0.000221087 5.40625 0.0205437 10 ATCACGTGAC GACACGTGCA - +2 cisbp__M0165 -2 0.000221087 5.40625 0.0205437 8 ATCACGTGAC CACGTGCTTA + +2 dbcorrdb__ATF3__ENCSR000BKC_1__m1-btd-cnc-CrebB-cyc-E2f1-E(z)-FoxP-Jra-Max-Mitf-mor-Myc-Sap30-Spps-SREBP-Usf 3 0.000221434 5.41473 0.0205437 10 ATCACGTGAC CCGGTCACGTGACCCCCGCG + +2 taipale_tf_pairs__MYBL1_MAX_NCACGTGNNYAACSGNN_CAP_repr-Max-Myb -1 0.000224426 5.48789 0.0207808 9 ATCACGTGAC CCACGTGCCTAACGGTC + +2 taipale_cyt_meth__MLX_NCAYGTGN_eDBD_meth-bigmax-Mitf -1 0.000227957 5.57424 0.0209853 8 ATCACGTGAC TCATGTGA + +2 scertf__macisaac.CBF1-Clk-Mitf-SREBP-Usf-cnc-cyc-tgo -2 0.000227957 5.57424 0.0209853 8 ATCACGTGAC CACGTGAC - +2 jaspar__MA0583.1 0 0.000240808 5.88847 0.0220505 10 ATCACGTGAC ATCACCTGAGGC + +2 cisbp__M0198 0 0.000243235 5.94783 0.0220505 10 ATCACGTGAC AGCCCGTGCG + +2 taipale_cyt_meth__SREBF1_NTCACGCCAY_eDBD_repr-SREBP 0 0.000243235 5.94783 0.0220505 10 ATCACGTGAC GTGGCGTGAT - +2 transfac_pro__M00322-E2f1-Max-Myc 0 0.000243235 5.94783 0.0220505 10 ATCACGTGAC CGCGCGTGGC - +2 homer__KCACGTGMCN_bHLHE40-Sirt6-bigmax-cyc-mio-tgo 1 0.000243235 5.94783 0.0220505 9 ATCACGTGAC GGGCACGTGC - +2 dbcorrdb__BHLHE40__ENCSR000BID_1__m1-bigmax-btd-Clk-cnc-CrebB-cyc-E2f1-E(z)-h-Max-Myc-Spps-SREBP-tgo-Usf-zfh1 4 0.000245309 5.99854 0.0220703 10 ATCACGTGAC CCCGGTCACGTGCCGGCCCG + +2 dbcorrdb__E2F6__ENCSR000EWJ_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-FoxP-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-tna-Usf-vtd-zfh1 3 0.000245309 5.99854 0.0220703 10 ATCACGTGAC GCGGCCACGTGCGCCGCGCG - +2 dbcorrdb__MYC__ENCSR000DMP_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-E(z)-gce-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Taf1-tna-Usf-vtd 8 0.000245309 5.99854 0.0220703 10 ATCACGTGAC CCCCGGCGGCCACGTGCCCC - +2 hdpi__USF2-Max-Usf -2 0.000248113 6.06712 0.0221552 6 ATCACGTGAC CACGTG + +2 jaspar__MA0281.1-Sirt6-cyc-tgo -1 0.000252037 6.16307 0.0224214 8 ATCACGTGAC GCACGTGA + +2 cisbp__M0149 -2 0.000256665 6.27623 0.0227905 7 ATCACGTGAC CACGTGC + +2 cisbp__M2376 0 0.000264971 6.47933 0.0230145 10 ATCACGTGAC ATCACCTGAGGC + +2 hocomoco__MYC_MOUSE.H11MO.0.A-E2f1-Max-Myc 1 0.000264971 6.47933 0.0230145 10 ATCACGTGAC CGCCACGTGCGC + +2 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNCACGTGN_CAP_repr-Max-TfAP-2 -1 0.000266025 6.50512 0.0230145 9 ATCACGTGAC CCACGTGATCGCCTCAGGCCA - +2 cisbp__M2266 1 0.000266779 6.52354 0.0230145 10 ATCACGTGAC GTGCACGTGAG + +2 cisbp__M6351-E2f1-Max-Myc-tgo-Usf 0 0.000266779 6.52354 0.0230145 10 ATCACGTGAC GCCACGTGCTC + +2 taipale_cyt_meth__TFE3_NNCACGTGAYN_eDBD-bigmax-cnc-cyc-Max-Mitf-tai-tgo 0 0.000266779 6.52354 0.0230145 10 ATCACGTGAC CGCACGTGACG + +2 transfac_pro__M07078 1 0.000266779 6.52354 0.0230145 10 ATCACGTGAC GTGCACGTGAG - +2 cisbp__M0232-Mitf-Mondo-SREBP-Usf-bigmax 0 0.000267386 6.53839 0.0230145 10 ATCACGTGAC ATCACGTGAT + +2 transfac_pro__M02259-E2f1-Max-Myc 0 0.000267386 6.53839 0.0230145 10 ATCACGTGAC GCCACGTGCG - +2 cisbp__M4532-E2f1-Max-Myc-tgo-Usf -1 0.000267386 6.53839 0.0230145 9 ATCACGTGAC CCACGTGCTC + +2 cisbp__M4553-bigmax-cyc-Mitf-Sirt6-tgo -1 0.000267386 6.53839 0.0230145 9 ATCACGTGAC GCACGTGACC - +2 cisbp__M0255-Atf6-CrebA-Met -1 0.000267408 6.53894 0.0230145 9 ATCACGTGAC CCACGTGGC + +2 jaspar__MA0968.1-Atf6-CrebA-Met -1 0.000267408 6.53894 0.0230145 9 ATCACGTGAC CCACGTGGC + +2 dbcorrdb__MAX__ENCSR000FAE_1__m1-btd-Clk-cnc-E2f1-E(z)-gce-Max-Myc-RpII215-Sap30-Spps-tgo-Usf 9 0.000271505 6.6391 0.0231992 10 ATCACGTGAC CCCCGCCGGGGCACGTGGCC + +2 dbcorrdb__ATF3__ENCSR000BJY_1__m2-bs-cnc-CrebB-E2f1-Max-Myc-Sin3A-Usf 6 0.000271505 6.6391 0.0231992 10 ATCACGTGAC GCCGCGGCCACGTGACGCCA - +2 transfac_pro__M01580-bigmax-mio 5 0.000271505 6.6391 0.0231992 10 ATCACGTGAC GACTAAGCACGTGCTAATAT - +2 hocomoco__HES1_HUMAN.H11MO.0.D-Sidpn 1 0.000272663 6.66743 0.0232565 10 ATCACGTGAC GGGCTCGTGGCGG - +2 transfac_pro__M01911-cyc-Sirt6-tgo -1 0.000278378 6.80718 0.0236169 8 ATCACGTGAC GCACGTGA + +2 cisbp__M0578 -3 0.000278378 6.80718 0.0236169 7 ATCACGTGAC GTGTGACA - +2 transfac_pro__M03540-bigmax-cyc-Mitf-Mondo-Usf -2 0.000285643 6.98482 0.0241901 7 ATCACGTGAC CACGTGA + +2 transfac_pro__M07640-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 1 0.000291327 7.12382 0.0244376 10 ATCACGTGAC TGGCGCGTGCCA - +2 cisbp__M4558-Clk-E2f1-gce-Max-Mnt-Myc 0 0.000293099 7.16715 0.0244376 10 ATCACGTGAC GCCACGTGCTC + +2 transfac_pro__M03572-Mitf-Usf 1 0.000293099 7.16715 0.0244376 10 ATCACGTGAC GGTCACGTGCG - +2 transfac_pro__M02250-E2f1-Max-Myc 0 0.0002937 7.18185 0.0244376 10 ATCACGTGAC GCCACGTGCG - +2 cisbp__M0176-crp -1 0.000294212 7.19438 0.0244376 9 ATCACGTGAC CCAGCTGAT + +2 cisbp__M0209-nau -1 0.000294212 7.19438 0.0244376 9 ATCACGTGAC ACACCTGTC + +2 cisbp__M0243-Clk-cyc-E2f1-Max-Myc-tgo-Usf -2 0.000294212 7.19438 0.0244376 8 ATCACGTGAC CACGTGCTT - +2 neph__UW.Motif.0253 8 0.0002962 7.24297 0.0245598 8 ATCACGTGAC ACAGAGCCACCATGTG + +2 taipale_tf_pairs__ARNTL_BHLHA15_RKCACGTGNNNMCATATGKN_CAP_repr-cyc-dimm 10 0.000300223 7.34135 0.0247211 10 ATCACGTGAC ACCATATGGGTGCACGTGAC - +2 hocomoco__MXI1_MOUSE.H11MO.1.A-Max-Myc -1 0.000307169 7.5112 0.0252295 8 ATCACGTGAC CCACGTGG + +2 transfac_pro__M09511-bigmax-Clk-cyc-Mitf-tgo 5 0.000314508 7.69068 0.0256977 10 ATCACGTGAC GAGAGGTCACGTGCG + +2 taipale_cyt_meth__TFEB_RNCAYGTGAYN_eDBD_meth-Mitf-Usf 0 0.000321766 7.86815 0.0256977 10 ATCACGTGAC AACATGTGACC + +2 cisbp__M0196-Clk 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC GGCACGTGTA + +2 cisbp__M0361-Atf3-Atf6-Atf-2-CG7786-CG44247-CrebA-CrebB-Jra-Pdp1-REPTOR-BP-Xbp1-cnc-gt-kay-vri 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC ATGACGTAAT + +2 jaspar__MA0626.1-Clk 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC GGCACGTGTC + +2 taipale_cyt_meth__HEY1_NGCACGTGYN_FL_meth-Hey-Sidpn 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC GGCACGTGTC + +2 taipale_cyt_meth__TFAP4_ANCATATGNT_FL_meth-amos-ato-crp-Fer3-HLH54F-Oli-twi 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC AACATATGTT + +2 cisbp__M5321-Clk 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC AACACGTGTT - +2 flyfactorsurvey__HLH106_SANGER_10_FBgn0015234-Mitf-SREBP-Usf 0 0.000322352 7.88246 0.0256977 10 ATCACGTGAC GTCGCGTGAT - +2 cisbp__M0263-Atf6-CrebA-CrebB-Xbp1 -1 0.000322352 7.88246 0.0256977 9 ATCACGTGAC CCACGTCATC - +2 cisbp__M0266 -1 0.000323421 7.90862 0.0256977 9 ATCACGTGAC CCACGTGGC - +2 taipale_tf_pairs__ERF_HES7_NNCACGTGNNNNNCCGGAANN_CAP_repr-Ets21C 0 0.000325487 7.95914 0.0258187 10 ATCACGTGAC GACACGTGGTGGACCGGAAGT + +2 dbcorrdb__MYC__ENCSR000DLU_1__m1-Brf-brm-Clk-cnc-CrebB-E2f1-E(z)-gce-Max-Mnt-Myc-pho-phol-RpII215-Sap30-Sin3A-Taf1-tna-Usf-vtd 9 0.000331681 8.11058 0.0259212 10 ATCACGTGAC CCCCCGCCGGCCACGTGCTC + +2 dbcorrdb__MYC__ENCSR000FAG_1__m1-Brf-brm-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-lid-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-SREBP-Taf1-tgo-tna-Usf 8 0.000331681 8.11058 0.0259212 10 ATCACGTGAC CCGCGGCGGCCACGTGGGCC + +2 hocomoco__BHE41_HUMAN.H11MO.0.D 5 0.000331681 8.11058 0.0259212 10 ATCACGTGAC ACGGTGTCACGTGCAGAGGG + +2 yetfasco__YBL103C_870-bigmax-mio 5 0.000331681 8.11058 0.0259212 10 ATCACGTGAC GACTAAGCACGTGCTAATAT + +2 dbcorrdb__ATF3__ENCSR000BJY_1__m1-cnc-CrebB-cwo-cyc-E2f1-E(z)-Max-Mitf-Myc-Sin3A-SREBP-tna-Usf 0 0.000331681 8.11058 0.0259212 10 ATCACGTGAC GTCACGTGACCCGCCCGCGC - +2 dbcorrdb__MYC__ENCSR000EBY_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Max-Myc-RpII215-Sap30-Spps-SREBP-Stat92E-Taf1-tgo-tna-Usf-vtd-zfh1 6 0.000331681 8.11058 0.0259212 10 ATCACGTGAC CCGGCGGCCACGTGGCCGCG - +2 hocomoco__MYCN_MOUSE.H11MO.0.A-Max-Myc -1 0.000338613 8.28011 0.0264196 8 ATCACGTGAC CCACGTGG + +2 taipale_cyt_meth__SOHLH2_NGCACGTGCN_eDBD_meth 0 0.000353525 8.64474 0.027448 10 ATCACGTGAC TGCACGTGCT - +2 cisbp__M0180-tgo -1 0.000353525 8.64474 0.027448 9 ATCACGTGAC GCACATGAAT - +2 dbcorrdb__MYC__ENCSR000DLN_1__m1-Clk-cnc-E2f1-E(z)-gce-Max-Mnt-Myc-Sap30-Usf 2 0.000366111 8.95251 0.0281952 10 ATCACGTGAC CGGCCACGTGCTCCGGGCCG + +2 cisbp__M2181-bigmax-mio 5 0.000366111 8.95251 0.0281952 10 ATCACGTGAC GACTAAGCACGTGCTAATAT - +2 taipale_tf_pairs__CLOCK_BHLHA15_NCACGTGNNNNNCATATGN_CAP-Clk-dimm 10 0.000369967 9.04679 0.0284462 9 ATCACGTGAC CCATATGTTAGCCACGTGT - +2 taipale__CLOCK_DBD_NACACGTGTN_repr-Clk 0 0.000387418 9.47353 0.0293611 10 ATCACGTGAC AACACGTGTT - +2 cisbp__M2353 1 0.000387418 9.47353 0.0293611 9 ATCACGTGAC AGCCACGTGA + +2 jaspar__MA0560.1 1 0.000387418 9.47353 0.0293611 9 ATCACGTGAC AGCCACGTGA + +2 cisbp__M0297-Atf6-CrebB-kay -1 0.000389836 9.53267 0.0294974 9 ATCACGTGAC TTACGTCAT - +2 cisbp__M0151-Max-Myc -2 0.000391205 9.56613 0.0295539 7 ATCACGTGAC CACGTGG + +2 taipale_tf_pairs__E2F1_HES7_SRCRCGYGSYNNNNSGCGCSN_CAP_repr-E2f1 0 0.00039681 9.7032 0.0297909 10 ATCACGTGAC GGCACGTGCCGCAAGGCGCCC + +2 transfac_pro__M09506-Clk-E(spl)mgamma-HLH-Hey 6 0.00039681 9.7032 0.0297909 10 ATCACGTGAC GTGAATGCCACGTGCCACCTC - +2 transfac_pro__M08871 2 0.000397471 9.71935 0.0297909 10 ATCACGTGAC TCCGCACGTGAGC - +2 dbcorrdb__MXI1__ENCSR000EBR_1__m1-Max-Myc-Rfx 4 0.000403764 9.87325 0.0300731 10 ATCACGTGAC GCGGTCCACGTGGCGACGGG + +2 dbcorrdb__MXI1__ENCSR000EFE_1__m1-Clk-E2f1-ERR-E(z)-gce-Hcf-Max-Mnt-Myc-RpII215-Sap30-Sin3A-tna-Usf 3 0.000403764 9.87325 0.0300731 10 ATCACGTGAC GCGGCCACGTGGTCCGCGCG + +2 jaspar__MA0376.1-bigmax-mio 5 0.000403764 9.87325 0.0300731 10 ATCACGTGAC GACTAAGCACGTGCTAATAT - +2 hdpi__USF1-Usf -2 0.000404942 9.90205 0.0301137 6 ATCACGTGAC CACGTG - +2 transfac_pro__M01029-Mitf -1 0.000410354 10.0344 0.0304686 8 ATCACGTGAC TCACATGA - +2 transfac_pro__M00717-sv 4 0.000418243 10.2273 0.0309578 10 ATCACGTGAC CAGTTTTGCGTGAGT + +2 homer__CCGGTCACGTGA_E-box-Max-Mitf-SREBP-Usf-cnc -1 0.000422435 10.3298 0.031016 9 ATCACGTGAC TCACGTGACCGG - +2 transfac_pro__M01794-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 0.00042379 10.3629 0.031016 10 ATCACGTGAC ATCACGTGACA + +2 taipale_cyt_meth__HES1_GGCRCGTGNS_eDBD-dpn-E(spl)m5-HLH-h-Hey-Sidpn 0 0.000424243 10.374 0.031016 10 ATCACGTGAC GGCACGTGGC + +2 jaspar__MA1061.1 0 0.000427469 10.4529 0.0311084 9 ATCACGTGAC CCCACGTGC + +2 flyfactorsurvey__tgo_cyc_SANGER_5_FBgn0015014-Clk-Mitf-SREBP-Usf-bigmax-cnc-cyc-tgo -1 0.000427469 10.4529 0.0311084 9 ATCACGTGAC GCACGTGAC - +2 cisbp__M6162-cyc-Mitf-SREBP-Usf 2 0.000432975 10.5875 0.031461 10 ATCACGTGAC TGGACACGTGACCC - +2 cisbp__M6271-Sidpn 1 0.000435901 10.6591 0.0316254 10 ATCACGTGAC GGGCTCGTGGCGG + +2 cisbp__M6161 5 0.00044491 10.8794 0.0319382 10 ATCACGTGAC ACCGGGTCACGTGCAGAAGG + +2 dbcorrdb__MXI1__ENCSR000EDU_1__m1-Brf-brm-btd-CTCF-E2f1-E(z)-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf-vtd 9 0.00044491 10.8794 0.0319382 10 ATCACGTGAC CGCCCGCCGGCCACGTGGGC + +2 dbcorrdb__ATF3__ENCSR000BKE_1__m2-cnc-E2f1-Max-Myc-pho-phol-RpII215-Taf1-Usf 3 0.00044491 10.8794 0.0319382 10 ATCACGTGAC GCGGGCACGTGACGGCAGCG - +2 taipale_cyt_meth__MAX_NCACGTGNNNNNCACGTGN_eDBD_repr-Clk-cwo-gce-Hey-Max-Myc 10 0.000448981 10.9789 0.0321335 9 ATCACGTGAC GCACGTGGCGGGCACGTGC + +2 swissregulon__hs__bHLH_family.p2-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30-cyc-emc 0 0.000451137 11.0317 0.032191 8 ATCACGTGAC ACCACGTG + +2 taipale_cyt_meth__CREB1_NTGACGCGTCAN_eDBD_repr-CrebB 2 0.00046269 11.3142 0.0325395 10 ATCACGTGAC ATGACGCGTCAC - +2 idmmpmm__h-Sidpn-dpn-h 0 0.000464226 11.3517 0.0325395 10 ATCACGTGAC GGCGCGTGCC - +2 transfac_pro__M00943-Atf6-CrebA-Max-Myc-tgo-Usf 0 0.000464226 11.3517 0.0325395 10 ATCACGTGAC GCCACGTGGC - +2 factorbook__BHLHE40-bigmax-cyc-tgo -1 0.000464226 11.3517 0.0325395 9 ATCACGTGAC GCACGTGACC + +2 cisbp__M0291-Atf6-Xbp1 -1 0.000464226 11.3517 0.0325395 9 ATCACGTGAC ACACGTCATC - +2 cisbp__M0162 0 0.00046836 11.4528 0.0327329 9 ATCACGTGAC CCCACGTGC + +2 elemento__CACGTGA-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf -2 0.000480061 11.7389 0.0335015 7 ATCACGTGAC CACGTGA + +2 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 0 0.000488903 11.9551 0.0339844 10 ATCACGTGAC GGCACGTGCCGCATCGCCTGAGGC + +2 dbcorrdb__MYC__ENCSR000DLR_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-Max-Mnt-Myc-Nelf-E-RpII215-Sap30-Sin3A-Spps-SREBP-Taf1-tna-Usf 3 0.000489837 11.978 0.0339844 10 ATCACGTGAC GGGGCCACGTGCGCGCCGCG + +2 taipale_tf_pairs__PITX1_HES7_NNCRCGTGNNNNGGATTA_CAP_repr-Ptx1 0 0.00049384 12.0759 0.0341625 10 ATCACGTGAC GGCACGTGTTGGGGATTA + +2 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNGCGGGYN_CAP_repr-gcm-gcm2-Max 8 0.00049384 12.0759 0.0341625 10 ATCACGTGAC CACCCGCATCCACGTGCC - +2 transfac_pro__M09507-Clk-E(spl)m3-HLH-E(spl)mbeta-HLH-Hey-Sidpn 7 0.00050515 12.3524 0.0348942 10 ATCACGTGAC ACGTGTTGACACGTGTCATCCAC - +2 taipale_cyt_meth__HES5_GGCACGTGYY_eDBD_meth-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 0 0.00050761 12.4126 0.034912 10 ATCACGTGAC GACACGTGCC - +2 cisbp__M0346-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-cnc-crc-kay -1 0.000512764 12.5386 0.0351649 9 ATCACGTGAC TGACGTCAT - +2 cisbp__M5230-bigmax-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf -1 0.000512764 12.5386 0.0351649 9 ATCACGTGAC TCACGTGAC - +2 transfac_public__M00119-Max-Usf 2 0.000520451 12.7266 0.0355895 10 ATCACGTGAC AAACCACGTGGTTT + +2 taipale_tf_pairs__ETV2_SREBF2_RTMRCGTGACGGAWGN_CAP_repr-pnt-SREBP 0 0.000523943 12.812 0.0356745 10 ATCACGTGAC ATGACGTGACGGAAGT + +2 neph__UW.Motif.0596 3 0.000523943 12.812 0.0356745 10 ATCACGTGAC GGAAGCATCTGTCTCT - +2 neph__UW.Motif.0659 5 0.000523943 12.812 0.0356745 10 ATCACGTGAC TGATTATTCTGTGACT - +2 dbcorrdb__SAP30__ENCSR000AQJ_1__m2-Clk-cyc-E2f1-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-HDAC1-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30-Usf 7 0.000538856 13.1766 0.036407 10 ATCACGTGAC CTCCGGGACCACGTGGGGGC - +2 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNCACGTGN_HT-crp-Max 10 0.00054307 13.2797 0.036407 9 ATCACGTGAC TCAGCTGTTCGGCACGTGC + +2 cisbp__M2361-Hey-Max-Mnt-Myc -1 0.00054388 13.2995 0.036407 8 ATCACGTGAC GCACGTGC + +2 jaspar__MA0568.1-Hey-Max-Mnt-Myc -1 0.00054388 13.2995 0.036407 8 ATCACGTGAC GCACGTGC + +2 cisbp__M0170 -2 0.00054388 13.2995 0.036407 8 ATCACGTGAC CGCGTGTC - +2 cisbp__M4507-Max-Myc -1 0.000554498 13.5591 0.0365119 9 ATCACGTGAC CCACGTGCTCC - +2 neph__UW.Motif.0041 -2 0.000554498 13.5591 0.0365119 8 ATCACGTGAC CAAGTGAGTCA + +2 cisbp__M0178-ac-amos-ase-CoRest-dimm-Fer1-Fer3-HLH54F-l(1)sc-nau-sc 0 0.000554652 13.5629 0.0365119 10 ATCACGTGAC AACAGCTGTT + +2 taipale_tf_pairs__HES1_GNCACGTGNC_HT-Sidpn 0 0.000554652 13.5629 0.0365119 10 ATCACGTGAC GGCACGTGCC + +2 transfac_pro__M00945-Max-Myc-SREBP-Usf 0 0.000554652 13.5629 0.0365119 10 ATCACGTGAC GCCACGTGAT + +2 taipale_cyt_meth__HES7_GGCACGTGYN_eDBD-dpn-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 0 0.000554652 13.5629 0.0365119 10 ATCACGTGAC CGCACGTGCC - +2 transfac_pro__M07641-Fer1 0 0.000554652 13.5629 0.0365119 10 ATCACGTGAC GTCAGCTGAC - +2 transfac_pro__M09453-Clk 0 0.000588675 14.3949 0.0386447 10 ATCACGTGAC AACACGTGTTAAATTTG + +2 cisbp__M0190-SREBP -1 0.000596439 14.5847 0.0388861 8 ATCACGTGAC TCGCGTGA + +2 jaspar__MA1025.1 0 0.000605331 14.8022 0.0392167 10 ATCACGTGAC AGCACGTGCCCG - +2 cisbp__M4646-bigmax-Max-Mitf-Usf -1 0.000605623 14.8093 0.0392167 9 ATCACGTGAC CCACGTGATCC - +2 taipale_tf_pairs__CLOCK_EVX1_ATRATYANNNNCACGTG_CAP_repr-Clk-eve 9 0.000645409 15.7822 0.0416227 8 ATCACGTGAC ATAATCACCGACACGTG + +2 dbcorrdb__BHLHE40__ENCSR000DYJ_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-ERR-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-Stat92E-tai-TfIIFalpha-tgo-Usf-zfh1 4 0.000650519 15.9071 0.0416622 10 ATCACGTGAC GGCCGGCACGTGACCGGGCG + +2 taipale_tf_pairs__RFX3_HES7_NRGCAACNNNCRCGYGNN_CAP_repr-Rfx 0 0.000653404 15.9777 0.0416622 10 ATCACGTGAC CGCACGTGCCCGTTGCCA - +2 cisbp__M6352-E2f1-Max-Myc -1 0.000653558 15.9814 0.0416622 8 ATCACGTGAC CCACGTGG + +2 flyfactorsurvey__Clk_cyc_SANGER_5_FBgn0023076-Clk-Met-cyc -1 0.000653558 15.9814 0.0416622 8 ATCACGTGAC ACACGTGA + +2 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNCACGTGN_CAP-crp-Max 10 0.000654775 16.0112 0.0416622 9 ATCACGTGAC TCAGCTGACCGGCACGTGC + +2 taipale_cyt_meth__TFAP4_ANCATATGNT_eDBD_meth-crp 0 0.000660836 16.1594 0.0416758 10 ATCACGTGAC ATCATATGTT + +2 hocomoco__SRBP1_HUMAN.H11MO.0.A-SREBP 1 0.000661005 16.1636 0.0416758 10 ATCACGTGAC GGTGGGGTGAG + +2 transfac_pro__M03852-SREBP 1 0.000661005 16.1636 0.0416758 10 ATCACGTGAC CGTGGGGTGAG - +2 cisbp__M0155 0 0.000661119 16.1663 0.0416758 10 ATCACGTGAC AGCACGTGCCCG - +2 cisbp__M0203 -1 0.000669836 16.3795 0.0419476 9 ATCACGTGAC CCAGGTGGT + +2 transfac_pro__M04684-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf -1 0.000669836 16.3795 0.0419476 9 ATCACGTGAC TCACGTGAC - +2 cisbp__M0246-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf -2 0.000669836 16.3795 0.0419476 8 ATCACGTGAC CACGTGACC - +2 jaspar__MA0265.1 4 0.00068953 16.8611 0.0431241 10 ATCACGTGAC TCGTATAAAGTGATAA + +2 taipale_tf_pairs__E2F3_HES7_NNNNGCGCSNNNNNCACGTGNN_CAP-E2f1 12 0.000690745 16.8908 0.0431434 10 ATCACGTGAC TATGGCGCCATCGGCACGTGCC + +2 dbcorrdb__SREBF1__ENCSR000EEO_1__m3-cnc-CrebB-E2f1-Max-Myc-SREBP-Usf 3 0.000713899 17.457 0.0441407 10 ATCACGTGAC CCGATCGCGTGACCGCGGCG + +2 cisbp__M4893-Clk-cyc-Met -1 0.000715591 17.4984 0.0441407 8 ATCACGTGAC ACACGTGA + +2 taipale_cyt_meth__MLX_NCACGTGN_eDBD_repr-bigmax-cyc-mio-tgo -1 0.000715591 17.4984 0.0441407 8 ATCACGTGAC GCACGTGC + +2 homer__CCCACGTGCT_Pho2 0 0.000720586 17.6205 0.0441407 10 ATCACGTGAC CCCACGTGCT + +2 transfac_pro__M09560 0 0.000720586 17.6205 0.0441407 10 ATCACGTGAC AGCACGTGCC + +2 transfac_pro__M07642-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 0 0.000720586 17.6205 0.0441407 10 ATCACGTGAC GGCACGTGCC - +2 cisbp__M0327-Atf6-CrebA 1 0.000720961 17.6297 0.0441407 10 ATCACGTGAC TGCCACGTGTT + +2 hocomoco__MXI1_HUMAN.H11MO.0.A-Clk-E2f1-Max-Myc-Sap30-cyc-tgo 6 0.000724381 17.7133 0.0442569 9 ATCACGTGAC CCCGCCGCCACGTGC - +2 cisbp__M2343-CrebA 2 0.000745377 18.2267 0.0452492 10 ATCACGTGAC AAGCCACGTGTCCA + +2 jaspar__MA0550.1-CrebA 2 0.000745377 18.2267 0.0452492 10 ATCACGTGAC AAGCCACGTGTCCA + +2 cisbp__M6210-Myc 1 0.00074679 18.2613 0.0452773 10 ATCACGTGAC CACCACGTGGGCA - +2 transfac_pro__M01901 4 0.000754508 18.45 0.0455711 10 ATCACGTGAC TCGTATAAAGTGATAA + +2 cisbp__M2070 4 0.000754508 18.45 0.0455711 10 ATCACGTGAC TCGTATAAAGTGATAA - +2 taipale_tf_pairs__PITX1_HES7_NCRCGTGNNNGGATTA_CAP_repr-Ptx1 7 0.000754508 18.45 0.0455711 9 ATCACGTGAC TAATCCCCCCACGTGC - +2 dbcorrdb__MYC__ENCSR000DMQ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tna-Usf-vtd 8 0.000782848 19.143 0.0464605 10 ATCACGTGAC CCGCGGCGGCCACGTGCCCG + +2 dbcorrdb__MYC__ENCSR000DMM_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-Taf1-tna-Usf-vtd-zfh1 4 0.000782848 19.143 0.0464605 10 ATCACGTGAC CGCGGCCACGTGCGCCGCGG - +2 dbcorrdb__MYC__ENCSR000DYC_1__m1-Brf-brm-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-SREBP-Taf1-tna-Usf-vtd 8 0.000782848 19.143 0.0464605 10 ATCACGTGAC CCGCCGCGGCCACGTGGGCG - +2 yetfasco__YKL112W_1993 6 0.000784463 19.1825 0.0464605 10 ATCACGTGAC TGTCGTAGGAAGTGATCT - +2 cisbp__M2253-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 0 0.000785215 19.2009 0.0464605 10 ATCACGTGAC GGCACGTGCC + +2 cisbp__M5510-dpn-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mgamma-HLH-Hey-Sidpn 0 0.000785215 19.2009 0.0464605 10 ATCACGTGAC GGCACGTGTC + +2 jaspar__MA0449.1-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 0 0.000785215 19.2009 0.0464605 10 ATCACGTGAC GGCACGTGCC + +2 taipale__HEY2_DBD_NNCACGTGCC-dpn-E(spl)mbeta-HLH-Hey-Sidpn 0 0.000785215 19.2009 0.0464605 10 ATCACGTGAC GGCACGTGTC - +2 taipale_cyt_meth__TFAP4_ANCATATGNT_FL-amos-ato-crp-Fer3-HLH54F-Oli-twi 0 0.000785215 19.2009 0.0464605 10 ATCACGTGAC AACATATGTT - +2 taipale_cyt_meth__TFE3_RNCAYGTGAYN_eDBD_meth-Mitf 0 0.000785829 19.2159 0.0464605 10 ATCACGTGAC AGCATGTGACG + +2 taipale_tf_pairs__CLOCK_EVX1_YRATTANNNNNNNCACGTG_CAP_repr-Clk-eve 11 0.000787007 19.2447 0.0464724 8 ATCACGTGAC TAATTATTGCGTACACGTG + +2 hdpi__HES5 -2 0.000807593 19.7481 0.0476289 6 ATCACGTGAC CGCGTG + +2 tfdimers__MD00222-ac-ase-GATAe-grn-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-pnr-sc-srp-Usf 17 0.000843028 20.6146 0.0495312 10 ATCACGTGAC TATCCCTTATCTCTCTATCCACCTGTCCTTCTC - +2 transfac_pro__M00371-CrebA-cyc-Usf 0 0.000855079 20.9092 0.0495312 10 ATCACGTGAC GCCACGTGAC + +2 homer__GNCCACGTGG_c-Myc-Clk-E2f1-Max-Myc-Usf-gce-tgo 1 0.000855079 20.9092 0.0495312 9 ATCACGTGAC GGCCACGTGG + +2 taipale_cyt_meth__ATF2_NRTGAYGTMAYN_FL-Atf3-Atf6-CG7786-cnc-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 1 0.000857745 20.9744 0.0495312 10 ATCACGTGAC CGTTACGTCACG - +2 transfac_pro__M00794-scro 0 0.000857745 20.9744 0.0495312 10 ATCACGTGAC GCCACTTGAGGG - +2 taipale_tf_pairs__ERF_SREBF2_NNCACGTGACMGGAARNN_CAP_repr-Ets21C-SREBP 0 0.00085858 20.9949 0.0495312 10 ATCACGTGAC ATCACGTGACCGGAAGTG + +2 swissregulon__hs__HES1.p2-Max-Myc-Sidpn 2 0.000864839 21.1479 0.0497716 10 ATCACGTGAC AGGCCGCGTGGCCCG + +2 taipale_tf_pairs__CLOCK_FIGLA_NCASSTGKNNNNNNNNNCACGTGN_CAP_repr-Clk 15 0.000866372 21.1854 0.0497807 9 ATCACGTGAC CCAGCTGTTGCCACGTGCACGTGC + +2 transfac_pro__M00799-Max-Myc -1 0.000868136 21.2285 0.0497807 7 ATCACGTGAC GCACGTG - +2 factorbook__MYC-Clk-E2f1-Max-Mnt-Myc-Sap30-gce 1 0.00088823 21.7199 0.0508105 10 ATCACGTGAC GAGCACGTGGCTGC + +2 cisbp__M0242-Max-Myc 0 0.000930558 22.7549 0.0527319 10 ATCACGTGAC CCCACGTGCT + +2 taipale_tf_pairs__TCF15_NACAYATGNN_HT-CG33557 0 0.000930558 22.7549 0.0527319 10 ATCACGTGAC ACCATGTGTT - +2 cisbp__M4627-E2f1-Max-Myc -1 0.000930558 22.7549 0.0527319 9 ATCACGTGAC CCACGTGCTC + +2 homer__GNCCACGTGG_n-Myc-Max-Myc-Sap30-Usf-tgo 1 0.000930558 22.7549 0.0527319 9 ATCACGTGAC GACCACGTGG + +2 transfac_pro__M07247-Clk -1 0.000935112 22.8663 0.0527319 8 ATCACGTGAC CCACCTGT + +2 taipale_tf_pairs__ETV5_CLOCK_NCACGTGNNNNNSCGGAWRN_CAP_repr-Clk-Ets96B 11 0.000939218 22.9667 0.0527758 9 ATCACGTGAC ACTTCCGGCCCAACACGTGC - +2 taipale_tf_pairs__ERF_CLOCK_CACGTGNNNNNSRGGAARNN_CAP_repr-Clk-Ets21C 12 0.000939218 22.9667 0.0527758 8 ATCACGTGAC GACTTCCGGTCAGCCACGTG - +2 cisbp__M0219-zfh1 -1 0.000947063 23.1585 0.0531539 9 ATCACGTGAC CCAGGTGTG + +2 cisbp__M0256 0 0.000968284 23.6775 0.054172 10 ATCACGTGAC AACACGTGTCATG - +2 jaspar__MA0580.1-Usf 5 0.000968619 23.6856 0.054172 9 ATCACGTGAC CGTGAGTCACGTGA + +2 taipale_tf_pairs__CLOCK_FIGLA_NCASSTGKNNNNNNNNCACGTGN_CAP_repr-Clk 14 0.000976982 23.8902 0.0545756 9 ATCACGTGAC CCAGCTGGCACCAAGACACGTGT + +2 taipale_tf_pairs__ETV2_HES7_RSCGGAANNNNNNNCACGTGNN_CAP_repr-pnt 12 0.000999367 24.4375 0.0557606 10 ATCACGTGAC ACCGGAAGTGACGGCACGTGCC + +2 transfac_pro__M08930-Atf3-Atf6-CrebB-Jra-kay-REPTOR-BP-vri-Xbp1 0 0.00101206 24.7479 0.0561607 10 ATCACGTGAC ATTACGTCAT - +2 cisbp__M0185 1 0.00101206 24.7479 0.0561607 9 ATCACGTGAC GAACACCTGC + +2 cisbp__M0273-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-E2f1-Irbp18-Jra-Xbp1-crc-kay-maf-S -1 0.00101206 24.7479 0.0561607 9 ATCACGTGAC TGACGTCACC - +2 cisbp__M0363-Atf6-CrebA-Xbp1 1 0.00101362 24.786 0.0561607 10 ATCACGTGAC TGCCACGTCAT - +2 transfac_pro__M08870 1 0.00101695 24.8675 0.05628 10 ATCACGTGAC CCGCACGTGACC + +2 cisbp__M1927-Max-Myc-tgo-Usf 0 0.00102087 24.9634 0.0563452 8 ATCACGTGAC GCCACGTG + +2 jaspar__MA0104.3-Max-Myc-Usf-tgo 0 0.00102087 24.9634 0.0563452 8 ATCACGTGAC GCCACGTG + +2 dbcorrdb__EP300__ENCSR000BMA_1__m2-GATAe-grn-nej-pnr 0 0.0010276 25.128 0.0563452 10 ATCACGTGAC TCAAGATGACTCATGGCCTG + +2 dbcorrdb__MAX__ENCSR000EZF_1__m1-Max 6 0.0010276 25.128 0.0563452 10 ATCACGTGAC AATAATGACACATGGTATTA - +2 tfdimers__MD00334-Stat92E-Usf 3 0.00107014 26.1682 0.0584086 10 ATCACGTGAC CTAACCAGGTGATTTCCCTGGTG + +2 taipale_tf_pairs__ETV2_FIGLA_NNCAGGTGNNNNNMCGGAARYN_CAP_repr-pnt 0 0.00109395 26.7503 0.0594782 10 ATCACGTGAC AGCAGGTGGTAAACCGGAAGTG + +2 transfac_pro__M08868-Clk-cyc-tgo -2 0.00110001 26.8985 0.0594782 8 ATCACGTGAC CACGTGCCTG - +2 taipale__MAX_DBD_CACGTGNNNNNCACGTG_repr-Max 9 0.00110372 26.9893 0.0594782 8 ATCACGTGAC CACGTGCTAACCACGTG + +2 taipale_tf_pairs__ERF_HES7_NCCGGAANNNNNNCACGYGNN_CAP_repr-Ets21C 0 0.0011121 27.1942 0.0594782 10 ATCACGTGAC GGCACGTGCCGCACTTCCGGT - +2 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNNNCACGTGN_CAP_repr-crp-Max 12 0.0011121 27.1942 0.0594782 9 ATCACGTGAC TCAGCTGATAGGAGCACGTGC + +2 cisbp__M0189-emc -1 0.00111373 27.2339 0.0594782 8 ATCACGTGAC GCACGTGA + +2 jaspar__MA0617.1-emc -1 0.00111373 27.2339 0.0594782 8 ATCACGTGAC GCACGTGA + +2 transfac_pro__M07420-Sidpn -1 0.00111373 27.2339 0.0594782 8 ATCACGTGAC GCTTGTGC + +2 cisbp__M0240-Mitf-Mondo-SREBP-Usf-tgo -1 0.00111373 27.2339 0.0594782 8 ATCACGTGAC TCACGTGA - +2 jaspar__MA0067.1-sv -3 0.00111373 27.2339 0.0594782 7 ATCACGTGAC CCGTGACT - +2 cisbp__M6518-Clk-cnc-cwo-cyc-Max-Mitf-tgo-Usf -2 0.0011216 27.4266 0.0594782 8 ATCACGTGAC CACGTGACC - +2 hocomoco__TFEB_HUMAN.H11MO.0.C-Clk-Max-Mitf-Usf-cnc-cwo-cyc-tgo -2 0.0011216 27.4266 0.0594782 8 ATCACGTGAC CACGTGACC - +2 dbcorrdb__MYC__ENCSR000DOM_1__m1-Max-Myc 9 0.00112348 27.4725 0.0594782 10 ATCACGTGAC TAAATACAAACCACATGGTT + +2 transfac_pro__M01564-Max-Myc 5 0.00112348 27.4725 0.0594782 10 ATCACGTGAC GACCAAGCACGTGCCCGTAT + +2 jaspar__MA0941.1 0 0.00114753 28.0605 0.0606837 10 ATCACGTGAC AACACGTGTCATG - +2 cisbp__M0287-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-cnc-kay 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC ATGACGTCAT + +2 cisbp__M5509-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn-tai 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC GGCACGTGTC + +2 taipale__HEY1_DBD_NNCACGTGNN-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn-tai 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC GACACGTGCC + +2 cisbp__M5511-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC GGCACGTGTC - +2 flyfactorsurvey__dm_Max_SANGER_10_FBgn0000472-Max-Met-Myc 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC ACCACGTGTC - +2 taipale__HEY2_full_GNCACGTGYN-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 0 0.00119487 29.2181 0.0620056 10 ATCACGTGAC GGCACGTGTC - +2 cisbp__M0264-Atf6-CrebA-Xbp1 -1 0.00119487 29.2181 0.0620056 9 ATCACGTGAC TGACGTGGCA + +2 cisbp__M1464 -1 0.00119487 29.2181 0.0620056 9 ATCACGTGAC ATTTGTGTCC + +2 transfac_pro__M09568-CrebA-Xbp1 -1 0.00119487 29.2181 0.0620056 9 ATCACGTGAC TTACGTGGCA + +2 transfac_pro__M03834-E2f1-Max-Myc -1 0.00119487 29.2181 0.0620056 9 ATCACGTGAC GCACGTGCCC - +2 taipale_tf_pairs__CLOCK_NHLH1_NNCAGCTGNNNNNNCACGTGNN_CAP_repr-Clk-HLH4C 0 0.0011966 29.2603 0.0620056 10 ATCACGTGAC GACACGTGTTGGAGCAGCTGCG - +2 flyfactorsurvey__cwo_SANGER_5_FBgn0259938-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo 2 0.00120261 29.4075 0.0620793 10 ATCACGTGAC TGGTCACGTGAT - +2 transfac_pro__M03789-Mondo 4 0.00120261 29.4075 0.0620793 8 ATCACGTGAC CGGAGTCACGTG - +2 cisbp__M1895-sv -3 0.0012142 29.6908 0.0626094 7 ATCACGTGAC GCGTGACT + +2 flyfactorsurvey__tgo_tai_SANGER_5_FBgn0015014-Mitf-cyc-tai-tgo -1 0.00121942 29.8184 0.0627426 9 ATCACGTGAC GCACGTGAC + +2 transfac_pro__M04679-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf -1 0.00121942 29.8184 0.0627426 9 ATCACGTGAC TCACGTGAC - +2 dbcorrdb__SP4__ENCSR000BQV_1__m1-btd-cnc-E2f1-Max-Myc-Spps-Usf 6 0.00122742 30.0141 0.0628149 10 ATCACGTGAC CCCGGCGTCGCGTGACCGGA - +2 taipale_tf_pairs__ETV2_HES7_NNCACGTGNNNNNCGGAWRY_CAP_repr-pnt 10 0.00122742 30.0141 0.0628149 10 ATCACGTGAC ACTTCCGGTCGGCACGTGCC - +2 taipale_tf_pairs__ETV5_HES7_NNCACGTGNNNNCCGGAANN_CAP-Ets96B 10 0.00122742 30.0141 0.0628149 10 ATCACGTGAC CCTTCCGGTCGGCGCGTGCC - +2 taipale_tf_pairs__TEAD4_CLOCK_NCACGTGNNNNNNCATWCC_CAP_repr-Clk-sd 10 0.0012304 30.087 0.0628997 9 ATCACGTGAC GGAATGTTGGAACACGTGT - +2 transfac_pro__M03132 3 0.00127602 31.2026 0.0648835 10 ATCACGTGAC GTTAGCACGTGCTATA - +2 cisbp__M4918-Max-Met-Myc 0 0.00129712 31.7186 0.0654668 10 ATCACGTGAC ACCACGTGTC + +2 taipale_cyt_meth__HES2_GGCRCGTGYN_eDBD-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 0 0.00129712 31.7186 0.0654668 10 ATCACGTGAC GGCACGTGCC + +2 taipale_cyt_meth__SOHLH2_NGCACGTGCN_eDBD 0 0.00129712 31.7186 0.0654668 10 ATCACGTGAC CGCACGTGCA + +2 taipale_cyt_meth__TFAP4_ANCATATGNT_eDBD-amos-ato-crp-dimm-Fer3-HLH54F-Oli-twi 0 0.00129712 31.7186 0.0654668 10 ATCACGTGAC ACCATATGTT - +2 taipale_cyt_meth__CREB1_NRTGAYGCGTN_eDBD_meth_repr-CrebB 0 0.00130003 31.7897 0.0655441 10 ATCACGTGAC TACGCGTCACC - +2 cisbp__M5613-Max 9 0.00131243 32.0928 0.0660292 8 ATCACGTGAC CACGTGCTAACCACGTG - +2 cisbp__M0207-zfh1 0 0.00132494 32.3986 0.0664477 9 ATCACGTGAC CACACCTGG - +2 cisbp__M5238-cyc-Mitf-tai-tgo -1 0.00132494 32.3986 0.0664477 9 ATCACGTGAC GCACGTGAC - +2 dbcorrdb__MYC__ENCSR000DKU_1__m1-Brf-brm-btd-CG10431-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tna-Usf-vtd-zfh1 4 0.00134003 32.7676 0.0669927 10 ATCACGTGAC CGCGGCCACGTGCGCCGGGG - +2 taipale_tf_pairs__ETV2_SREBF2_RTCACGYSNCCGGAWN_CAP_repr-pnt-SREBP 6 0.00138948 33.977 0.0690553 10 ATCACGTGAC CTTCCGGTGGCGTGAT - +2 transfac_pro__M02099-Mitf -2 0.00138999 33.9894 0.0690553 7 ATCACGTGAC CATGTGA + +2 cisbp__M0341-Jra-REPTOR-BP-gt-kay-vri 0 0.00140729 34.4125 0.0692643 10 ATCACGTGAC ATTACGTAAT + +2 taipale_cyt_meth__SREBF2_ATCAGGTGAY_eDBD_meth-SREBP 0 0.00140729 34.4125 0.0692643 10 ATCACGTGAC ATCAGGTGAT + +2 taipale_cyt_meth__HES2_GGCRCGTGYN_eDBD_meth 0 0.00140729 34.4125 0.0692643 10 ATCACGTGAC CCCACGTACC - +2 cisbp__M0157 -1 0.00144028 35.2193 0.0703065 8 ATCACGTGAC GCACGTGG + +2 swissregulon__sacCer__PHO4-Max-Myc -1 0.00144028 35.2193 0.0703065 8 ATCACGTGAC GCACGTGC + +2 dbcorrdb__ATF3__ENCSR000BKE_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-E(z)-Jra-Max-Mitf-Myc-Sap30-Spps-SREBP-Usf-zfh1 5 0.00146193 35.7487 0.0709268 10 ATCACGTGAC CCGGGGTCACGTCACCGGCG + +2 dbcorrdb__RXRA__ENCSR000BHU_1__m2-EcR-eg-ERR-ftz-f1-HDAC1-Hnf4-Hr38-Hr4-Hr51-Hr78-kni-knrl-nej-Nup133-svp-usp 1 0.00146193 35.7487 0.0709268 10 ATCACGTGAC CCCACTCTGACCTTTGACCT - +2 taipale_tf_pairs__MEIS1_MAX_NTGACRNNNNNNCACGTGN_CAP_repr-Max 10 0.0014639 35.7966 0.0709496 9 ATCACGTGAC TTGACATGTCGGCACGTGC + +2 hocomoco__ID4_HUMAN.H11MO.0.D-emc-esg-sna-wor 0 0.00153 37.413 0.0734799 10 ATCACGTGAC GACAGGTGTAA + +2 cisbp__M2354-Clk-E2f1-Max-Myc-cyc 0 0.00156714 38.3212 0.0748106 8 ATCACGTGAC GCCACGTG + +2 jaspar__MA0962.1 -1 0.00156714 38.3212 0.0748106 8 ATCACGTGAC GCACGTGG + +2 jaspar__MA0561.1-Clk-E2f1-Max-Myc-cyc 0 0.00156714 38.3212 0.0748106 8 ATCACGTGAC GCCACGTG - +2 dbcorrdb__ATF3__ENCSR000BKC_1__m3-Brf-cnc-CTCF-E2f1-E(z)-lid-Max-Myc-pho-phol-RpII215-Sap30-Taf1-Taf7-tna-Usf-usp 3 0.00159383 38.974 0.075781 10 ATCACGTGAC GCGGCCACGTGGCGGCGGCG + +2 dbcorrdb__JUN__ENCSR000EGH_1__m2-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.00159383 38.974 0.075781 10 ATCACGTGAC ACAGGAGGTGACGTCATCGA + +2 cisbp__M2373-Usf 5 0.00160661 39.2864 0.0760844 9 ATCACGTGAC CGTGAGTCACGTGA + +2 jaspar__MA0552.1 -1 0.00160661 39.2864 0.0760844 9 ATCACGTGAC CCACGTGACCTTCT - +2 cisbp__M0279 0 0.0016536 40.4354 0.077768 10 ATCACGTGAC TACACGTGTA + +2 taipale_cyt_meth__SREBF1_RTCAGGTGAY_eDBD_meth-SREBP 0 0.0016536 40.4354 0.077768 10 ATCACGTGAC ATCAGGTGAT + +2 transfac_pro__M09569 -1 0.0016536 40.4354 0.077768 9 ATCACGTGAC TGACGTGTCA + +2 cisbp__M4900-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.00166937 40.8211 0.0782006 10 ATCACGTGAC ATCACGTGACCA + +2 taipale_cyt_meth__CREB3L4_YGCCACGTCAYN_eDBD_repr-Atf6-CrebA-Xbp1 1 0.00166937 40.8211 0.0782006 10 ATCACGTGAC TGCCACGTCACC + +2 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNNNNNNNNRTGCGGGYRN_CAP_repr-gcm-gcm2-Max 18 0.0017034 41.6533 0.0794359 10 ATCACGTGAC CTGCCCGCATCGCCCGTAACCACGTGCC - +2 transfac_pro__M01116-Clk-cyc -1 0.00170408 41.67 0.0794359 8 ATCACGTGAC ACACGTGG + +2 transfac_pro__M01009-Sidpn 2 0.00171 41.8147 0.0796338 10 ATCACGTGAC AAGGCTCGTGGCTCG + +2 transfac_pro__M00997 1 0.00173518 42.4302 0.0803933 10 ATCACGTGAC GCCCACGTGAAGG + +2 cisbp__M2345 -1 0.0017441 42.6485 0.0806691 9 ATCACGTGAC CCACGTGACCTTCC - +2 cisbp__M0611 0 0.00179094 43.7938 0.0823553 10 ATCACGTGAC TTTACGTAAT + +2 transfac_pro__M00369-Atf6-CrebA-Max-Myc-tgo-Usf 0 0.00179094 43.7938 0.0823553 10 ATCACGTGAC GCCACGTGGC + +2 transfac_pro__M07637-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.00179094 43.7938 0.0823553 10 ATCACGTGAC GTCACGTGAC + +2 taipale_cyt_meth__NPAS2_NMCACGTGYN_eDBD-Clk-Met 0 0.00179094 43.7938 0.0823553 10 ATCACGTGAC TACACGTGTC - +2 transfac_pro__M01177-SREBP 0 0.00180929 44.2426 0.0830388 10 ATCACGTGAC GTGGGGTGGCCT - +2 taipale_tf_pairs__MYBL1_MAX_YAACGGNNNNNNNNNNNCACGTG_CAP_repr-Max-Myb 15 0.00182002 44.505 0.0834508 8 ATCACGTGAC TAACGGTCGTCGCGGGGCACGTG + +2 taipale_tf_pairs__ETV2_HES7_RSCGGAANNNNNNCACGTGNN_CAP_repr-pnt 11 0.00187775 45.9165 0.0856028 10 ATCACGTGAC ACCGGAAGTGGGGCACGTGCC + +2 hocomoco__MLXPL_HUMAN.H11MO.0.D-Mondo 10 0.00189014 46.2195 0.0860217 9 ATCACGTGAC CCACGGGGGTGTCACATGC - +2 cisbp__M0293-CG7786-gt-Pdp1-vri -1 0.0019386 47.4045 0.0881236 9 ATCACGTGAC TTACGTAATA - +2 transfac_pro__M09019 2 0.00194091 47.4611 0.0881447 10 ATCACGTGAC AAATCACCTGAACAGG - +2 transfac_pro__M07034-CrebB 0 0.0019598 47.923 0.0885798 10 ATCACGTGAC CTCACGTCACTG - +2 transfac_pro__M09561-Atf6-Clk-CrebA-Met 1 0.0019598 47.923 0.0885798 10 ATCACGTGAC TGCCACGTGTCC - +2 transfac_pro__M01830-E2f1-Max-Myc 3 0.0019598 47.923 0.0885798 9 ATCACGTGAC CCGGCCACGTGC + +2 transfac_pro__M01036-btd-EcR-eg-Eip78C-ERR-ftz-f1-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-usp -1 0.00198354 48.5036 0.0895679 9 ATCACGTGAC TCCCCTGACCTTTGCCCTCTGCC + +2 cisbp__M0158-Usf -1 0.0020112 49.18 0.090303 8 ATCACGTGAC CCACGTGC + +2 elemento__CACGTGAC-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf -2 0.0020112 49.18 0.090303 8 ATCACGTGAC CACGTGAC + +2 jaspar__MA0566.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-Mnt -1 0.0020112 49.18 0.090303 8 ATCACGTGAC GCACGTGC + +2 taipale_tf_pairs__MYBL1_MAX_YAACGGNNNNNNNNNNCACGTG_CAP_repr-Max-Myb 14 0.00201903 49.3712 0.0903983 8 ATCACGTGAC TAACGGTTGCCTGGAGCACGTG + +2 neph__UW.Motif.0106 2 0.00205163 50.1685 0.09158 10 ATCACGTGAC CAGACAGCTGGAAA + +2 taipale_tf_pairs__TEAD4_MAX_RCATTCCNNNNNNCACGTG_CAP_repr-Max-sd 11 0.00205548 50.2626 0.09158 8 ATCACGTGAC ACATTCCATAAACCACGTG + +2 dbcorrdb__SIN3A__ENCSR000BOY_1__m1-CTCF-HDAC1-Myc-Sin3A 5 0.00205696 50.299 0.09158 10 ATCACGTGAC GCCGCCCCACGTGGTGCTGA - +2 taipale_tf_pairs__TEAD4_CLOCK_NCACGTGNNNNNNNCATWCC_CAP-Clk-sd 11 0.00205696 50.299 0.09158 9 ATCACGTGAC GGAATGTGGATTACACGTGT - +2 transfac_pro__M07660-crp-twi 0 0.00209727 51.2845 0.0929261 10 ATCACGTGAC AACATGTGTT + +2 cisbp__M0302-Atf3-Atf6-crc-CrebB-Irbp18-Jra-kay-Xbp1 -1 0.00209727 51.2845 0.0929261 9 ATCACGTGAC TTACGTCATC - +2 neph__UW.Motif.0229 3 0.00210444 51.46 0.0929261 8 ATCACGTGAC CAGCTCTCCTG - +2 neph__UW.Motif.0468 5 0.00210672 51.5157 0.0929261 10 ATCACGTGAC CTCCAGATATCTGGCA + +2 taipale_cyt_meth__ZNF174_NGNCRATCACTYGNCN_eDBD_repr 1 0.00210672 51.5157 0.0929261 10 ATCACGTGAC TGGCAAGTGATCGGCC - +2 taipale_cyt_meth__MSC_NRNCATATGNYN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 1 0.00212161 51.8797 0.0934095 10 ATCACGTGAC CACCATATGGTG - +2 taipale_tf_pairs__CLOCK_TBX3_GGTGTGNNNNNCACGTG_CAP_repr-bi-Clk 9 0.00217177 53.1063 0.0952264 8 ATCACGTGAC GGTGTGATCGGCACGTG + +2 transfac_pro__M01265 -4 0.00218213 53.3595 0.0952264 6 ATCACGTGAC AGTGATA - +2 jaspar__MA1074.1-Usf -1 0.00218296 53.3799 0.0952264 8 ATCACGTGAC CCACGTGC + +2 scertf__morozov.INO2 -1 0.00218296 53.3799 0.0952264 8 ATCACGTGAC GCATGTGA - +2 taipale_tf_pairs__FLI1_MAX_RSCGGAANCACGTGN_CAP-Max -1 0.00218488 53.427 0.0952264 9 ATCACGTGAC CCACGTGTTTCCGGT - +2 tfdimers__MD00439-CrebB 0 0.00219767 53.7397 0.0956961 10 ATCACGTGAC AAAATGTGACGTAAAAAATAAA + +2 transfac_pro__M09495-Clk-cnc-cyc-Mitf -2 0.00222317 54.3631 0.0965067 8 ATCACGTGAC CACGTGACATCCAC + +2 dbcorrdb__BCL3__ENCSR000BQH_1__m2-Jra-kay-mor 6 0.00223656 54.6907 0.0965067 10 ATCACGTGAC ATTGTTACGCGATGACTCAT - +2 cisbp__M0195-amos-ato-crp-da-dimm-Fer3-HLH3B-HLH54F-Oli-tap-twi-tx 0 0.00226769 55.4519 0.0974084 10 ATCACGTGAC ACCATATGGT + +2 cisbp__M0268-Atf6-CrebA-Xbp1 1 0.00226769 55.4519 0.0974084 9 ATCACGTGAC TGCCACGTCA - +2 cisbp__M0300-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-vri-Xbp1 -1 0.00226769 55.4519 0.0974084 9 ATCACGTGAC TGACGTCATT - +2 transfac_pro__M08951-nau 1 0.00227583 55.6508 0.0975816 10 ATCACGTGAC TAACAGTTGTT + +2 transfac_pro__M01289 6 0.00228529 55.8822 0.0978111 10 ATCACGTGAC TATCGTATAACATGAT + +2 homer__NNVVCAGCTGBN_Ascl1-Fer1-Fer3-HLH3B-HLH54F-ac-amos-ase-dimm-l(1)sc-nau-sc 0 0.00229547 56.1312 0.0980706 10 ATCACGTGAC AGCAGCTGCCGC - +2 homer__CGTRNAAARTGA_ABF1 3 0.00229547 56.1312 0.0980706 9 ATCACGTGAC CGTGCAAAATGA + +2 jaspar__MA0004.1-tgo -2 0.00231804 56.683 0.0989459 6 ATCACGTGAC CACGTG + +2 cisbp__M0252-Max-Usf -1 0.00236798 57.9042 0.10009 8 ATCACGTGAC CCACGTGC + +2 cisbp__M4679-Max-Myc-Sap30 -1 0.00236798 57.9042 0.10009 8 ATCACGTGAC CCACGTGG + +2 cisbp__M6151-tgo -1 0.00236798 57.9042 0.10009 8 ATCACGTGAC TCACGTGC + +2 hocomoco__ARNT_MOUSE.H11MO.0.B-tgo -1 0.00236798 57.9042 0.10009 8 ATCACGTGAC TCACGTGC + +2 jaspar__MA1021.1-Max-Usf -1 0.00236798 57.9042 0.10009 8 ATCACGTGAC CCACGTGC + +2 transfac_pro__M01168-SREBP 2 0.00236798 57.9042 0.10009 10 ATCACGTGAC CCCTGGGGTGAGCGG - +2 flyfactorsurvey__Met_SANGER_5_FBgn0002723-Clk-Max-Met-Myc-cyc -1 0.00238271 58.2645 0.100534 7 ATCACGTGAC CCACGTG - +2 taipale_tf_pairs__TEAD4_CLOCK_GGWATGNNNNNNCACGTGN_CAP_repr-Clk-sd 10 0.00242614 59.3263 0.102185 9 ATCACGTGAC GGAATGTGGGGGCACGTGT + +2 taipale_cyt_meth__CREB5_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 1 0.0024822 60.6972 0.103994 10 ATCACGTGAC GGTGACGTCATG + +2 predrem__nrMotif1641 -1 0.00251938 61.6063 0.105274 9 ATCACGTGAC ACACATGAT + +2 cisbp__M0362-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-kay -1 0.00251938 61.6063 0.105274 9 ATCACGTGAC TGACGTCAT - +2 cisbp__M1839-tgo -2 0.00256081 62.6196 0.106524 6 ATCACGTGAC CACGTG + +2 taipale_tf_pairs__PITX1_HES7_NCACGTGNNGGATTA_CAP_repr-Ptx1 -1 0.0025649 62.7194 0.106524 9 ATCACGTGAC ACACGTGGGGGATTA + +2 cisbp__M4274-Clk -1 0.00256719 62.7754 0.106524 8 ATCACGTGAC GCACGTGT + +2 cisbp__M0211-Mondo -1 0.00256719 62.7754 0.106524 8 ATCACGTGAC ACACGTGC - +2 jaspar__MA0622.1-Mondo -1 0.00256719 62.7754 0.106524 8 ATCACGTGAC ACACGTGC - +2 transfac_pro__M07384-sima -1 0.00256719 62.7754 0.106524 8 ATCACGTGAC CCACGTGC - +2 cisbp__M0306 1 0.00258466 63.2026 0.107155 10 ATCACGTGAC AGTTACGTAATTG - +2 cisbp__M5106-Clk-cyc-Max-Met-Myc -1 0.00259984 63.574 0.10766 7 ATCACGTGAC CCACGTG + +2 taipale_tf_pairs__GCM1_MAX_RTGCGGGNNNNNNNCACGTGN_CAP_repr-gcm-gcm2-Max 12 0.00262667 64.2299 0.108137 9 ATCACGTGAC ATGCGGGTGGGGAGCACGTGG + +2 dbcorrdb__BACH1__ENCSR000EBQ_1__m1-cnc-ewg-Jra-kay-maf-S 0 0.00263908 64.5334 0.108137 10 ATCACGTGAC CAAGGATGACTCAGCACTTT - +2 transfac_pro__M09500-Clk-Hey 10 0.00263908 64.5334 0.108137 10 ATCACGTGAC GCCCGGGGCTGACACGTGTC - +2 transfac_public__M00184-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.00264696 64.7262 0.108137 10 ATCACGTGAC AGCACCTGTC + +2 cisbp__M0839 0 0.00264696 64.7262 0.108137 10 ATCACGTGAC ATCATGTAAA - +2 cisbp__M5430-CG12605-da-scrt-tx 0 0.00264696 64.7262 0.108137 10 ATCACGTGAC AACAGGTGGT - +2 taipale__FIGLA_DBD_NNCACCTGNN-CG12605-da-scrt-tx 0 0.00264696 64.7262 0.108137 10 ATCACGTGAC AACAGGTGGT - +2 neph__UW.Motif.0150 1 0.00264696 64.7262 0.108137 9 ATCACGTGAC TTTCCCGAGA - +2 cisbp__M4543-Clk-cyc-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-HDAC1-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30 3 0.00265725 64.9778 0.108464 8 ATCACGTGAC GGAACCACGTG + +2 cisbp__M0359-Atf6-CrebA-Xbp1 1 0.00268263 65.5984 0.109219 10 ATCACGTGAC TGCCACGTCAGC - +2 scertf__morozov.PHO4-E2f1-Max-Myc -1 0.00278155 68.0173 0.112668 8 ATCACGTGAC CCACGTGC - +2 transfac_pro__M07353 0 0.00278155 68.0173 0.112668 8 ATCACGTGAC GCCACCTG - +2 taipale_tf_pairs__GCM1_MAX_RTGCGGGNNNNNNNCACGTGN_CAP-gcm-gcm2-Max -1 0.00285197 69.7393 0.114361 9 ATCACGTGAC CCACGTGCCCCCTACCCGCAT - +2 transfac_pro__M00370-CrebA-Usf 0 0.00285751 69.8746 0.114361 10 ATCACGTGAC GCCACGTGAC + +2 transfac_pro__M00944 0 0.00285751 69.8746 0.114361 10 ATCACGTGAC GTCACGTGAC + +2 transfac_pro__M08885-cwo-Hey-Max-Myc -2 0.00285751 69.8746 0.114361 8 ATCACGTGAC CACGTGCCGC - +2 taipale_tf_pairs__TEAD4_HES7_GGWATGYNNNNNNCRCGYGY_CAP-sd -1 0.00286402 70.0338 0.114361 9 ATCACGTGAC GCACGTGCCTCCCGCATTCC - +2 jaspar__MA0059.1-Max-Myc-Usf-tgo 1 0.00286901 70.1558 0.114361 10 ATCACGTGAC GAGCACGTGGT + +2 transfac_pro__M07435-twi 0 0.00286901 70.1558 0.114361 10 ATCACGTGAC TCCAGGTGTTT - +2 taipale_cyt_meth__XBP1_NKMCACRTCAYN_FL_meth-Atf6-CrebA-Xbp1 1 0.00289767 70.8567 0.115311 10 ATCACGTGAC CGCCACGTCACC + +2 scertf__macisaac.ABF1 4 0.00300395 73.4555 0.119057 10 ATCACGTGAC TCGTATATAGTGATA - +2 transfac_pro__M04632-SREBP 3 0.00301922 73.829 0.119057 10 ATCACGTGAC GCCGTGGGGTGAT + +2 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 22 0.00302202 73.8976 0.119065 9 ATCACGTGAC TGGCCTCAGGCGATATGGGGGGAGCACGTGC + +2 cisbp__M0236 0 0.00304749 74.5202 0.119969 10 ATCACGTGAC ATCACGTACGATGT + +2 taipale_tf_pairs__TEAD4_HES7_GGWATGYNNNNCRCGYGY_CAP_repr-sd 9 0.00306243 74.8857 0.120457 9 ATCACGTGAC GGAATGTGTGGCACGTGT + +2 cisbp__M0985-ara-caup-mirr 0 0.0030832 75.3936 0.120577 10 ATCACGTGAC ATCATGTAAT + +2 transfac_pro__M00376 0 0.0030832 75.3936 0.120577 10 ATCACGTGAC CTCACGTGAG + +2 transfac_pro__M01799 0 0.0030832 75.3936 0.120577 10 ATCACGTGAC GCCACATGCG - +2 flyfactorsurvey__tai_SANGER_5_FBgn0041092-tai 1 0.003096 75.7065 0.120899 10 ATCACGTGAC AAACACGTGTC + +2 cisbp__M6346-Mondo 10 0.00309653 75.7194 0.120899 9 ATCACGTGAC CCACGGCGGTGTCACATGC + +2 dbcorrdb__ATF3__ENCSR000DOG_1__m1-cnc-CrebB-cyc-E2f1-ERR-E(z)-Jra-Max-Myc-Sin3A-SREBP-tna-Usf 0 0.0031062 75.9559 0.120979 10 ATCACGTGAC GTCACGTCACCCGCGCGCGC + +2 taipale_tf_pairs__TEAD4_MAX_RCATTCCNNNNNNNCACGTG_CAP_repr-Max-sd 12 0.0031062 75.9559 0.120979 8 ATCACGTGAC ACATTCCACACGACCACGTG + +2 cisbp__M0272-Atf6-CrebA-Xbp1 0 0.00312826 76.4952 0.121738 10 ATCACGTGAC GCCACGTCAGCA - +2 cisbp__M0090 -1 0.00317671 77.6802 0.123322 9 ATCACGTGAC ACGCGTCAT - +2 flyfactorsurvey__HLHm3_SANGER_5_FBgn0002609-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 1 0.00317671 77.6802 0.123322 8 ATCACGTGAC TGGCACGTG - +2 cisbp__M2162-Max-Myc -1 0.00325995 79.7156 0.125448 8 ATCACGTGAC GCACGTGC + +2 flyfactorsurvey__gce_Clk_SANGER_5_FBgn0023076-Clk-E2f1-Max-Myc-Usf-gce-tgo 0 0.00325995 79.7156 0.125448 8 ATCACGTGAC GCCACGTG + +2 jaspar__MA0357.1-Max-Myc -1 0.00325995 79.7156 0.125448 8 ATCACGTGAC GCACGTGC + +2 jaspar__MA0957.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Mnt-Sidpn -1 0.00325995 79.7156 0.125448 8 ATCACGTGAC GCACGTGC + +2 swissregulon__hs__PAX2.p2-sv -3 0.00325995 79.7156 0.125448 7 ATCACGTGAC GCGTGACG - +2 neph__UW.Motif.0564 5 0.00326049 79.7287 0.125448 8 ATCACGTGAC CATTTTTCTCATG - +2 transfac_pro__M00929-esg-nau 4 0.00331644 81.0968 0.126906 10 ATCACGTGAC CTTCGCCACCTGCCGCGG - +2 cisbp__M5290-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.00332503 81.3069 0.126906 10 ATCACGTGAC GTCACGTGAC + +2 taipale_cyt_meth__HES1_GGCRCGTGNS_eDBD_meth-Sidpn 0 0.00332503 81.3069 0.126906 10 ATCACGTGAC GGCACGTGTG + +2 cisbp__M3591-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.00332503 81.3069 0.126906 10 ATCACGTGAC AGCACCTGTC - +2 cisbp__M0078 -1 0.00332503 81.3069 0.126906 9 ATCACGTGAC GCACCTGAAA + +2 cisbp__M0316-CG7786-CrebB-gt-Pdp1-vri -1 0.00332503 81.3069 0.126906 9 ATCACGTGAC TTACGTAATA - +2 cisbp__M4597-cnc-Mitf-SREBP-tgo-Usf -1 0.00332503 81.3069 0.126906 9 ATCACGTGAC TCACGTCACC - +2 flyfactorsurvey__HLHm5_FlyReg_FBgn0002631-E(spl)m5-HLH-dpn 1 0.00332503 81.3069 0.126906 9 ATCACGTGAC TGACACGTGC - +2 cisbp__M5225-tai 1 0.00333922 81.654 0.127243 10 ATCACGTGAC AAACACGTGTC + +2 dbcorrdb__GATA2__ENCSR000EVW_1__m3-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 1 0.00336679 82.3282 0.127905 10 ATCACGTGAC TAGAGTATGACTCATTGCTT + +2 taipale_cyt_meth__XBP1_NKMCACGTCAYN_FL-Atf6-CrebA-Xbp1 1 0.0033754 82.5386 0.127905 10 ATCACGTGAC GGCCACGTCACC + +2 hocomoco__HEY1_HUMAN.H11MO.0.D-Clk-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-Hey-Sidpn-dpn-tai 1 0.0033754 82.5386 0.127905 10 ATCACGTGAC CGACACGTGCCA - +2 transfac_pro__M03125-Max-Myc 3 0.00340185 83.1854 0.128702 10 ATCACGTGAC CGGACCACGTGGTCCG + +2 tfdimers__MD00453 1 0.00349039 85.3505 0.131842 10 ATCACGTGAC AATAATCTGATTTAATTAAATTTA - +2 neph__UW.Motif.0582 3 0.00351011 85.8326 0.132377 10 ATCACGTGAC CTGTCTCTCTGAGCT - +2 transfac_pro__M09496-cyc -2 0.00351011 85.8326 0.132377 8 ATCACGTGAC CACGTGACATTCACG + +2 hocomoco__CR3L2_HUMAN.H11MO.0.D-Atf6-CrebA-Xbp1 1 0.00351912 86.0531 0.132461 10 ATCACGTGAC TGCCACGTCATCA - +2 cisbp__M1148 0 0.00358401 87.6399 0.134102 10 ATCACGTGAC ATCACATCAT + +2 taipale__ARNTL_DBD_GTCACGTGAC-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.00358401 87.6399 0.134102 10 ATCACGTGAC GTCACGTGAC - +2 taipale_cyt_meth__CREM_NRTGACGTCAYN_eDBD-Atf3-Atf6-CG7786-cnc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 1 0.00364015 89.0125 0.135775 10 ATCACGTGAC CGTGACGTCACG - +2 dbcorrdb__RCOR1__ENCSR000EFG_1__m1-CoRest-Jra-kay-mor-Myc-pan 2 0.00364704 89.181 0.135819 10 ATCACGTGAC GTCGGCGGTGAGTCAGCCGT - +2 neph__UW.Motif.0288 8 0.00367716 89.9176 0.136834 8 ATCACGTGAC TCCCTGCTGCCAGCTG - +2 transfac_pro__M07043-sima -1 0.00369801 90.4274 0.137288 9 ATCACGTGAC GTACGTGCG + +2 cisbp__M5019-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 1 0.00369801 90.4274 0.137288 8 ATCACGTGAC TGGCACGTG + +2 transfac_pro__M01173-SREBP 2 0.00379113 92.7045 0.140635 10 ATCACGTGAC CCGTGGGGTGAGCGG - +2 cisbp__M0150-Mondo -1 0.00381219 93.2196 0.140868 8 ATCACGTGAC GCACGTGT + +2 transfac_pro__M03788-EcR-usp 0 0.003838 93.8507 0.141492 10 ATCACGTGAC CTTTTGTGAACTCT + +2 taipale_cyt_meth__BHLHA15_NMCATATGKN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.00386125 94.4191 0.14169 10 ATCACGTGAC ACCATATGGT + +2 taipale_cyt_meth__NEUROG2_RNCATATGNY_FL-amos-ato-HLH54F-Oli-tap 0 0.00386125 94.4191 0.14169 10 ATCACGTGAC GACATATGTC + +2 cisbp__M1501 -1 0.00386125 94.4191 0.14169 9 ATCACGTGAC ACGCGTGACG + +2 cisbp__M0269-Atf3-Atf6-CrebA-CrebB-E2f1-Irbp18-Jra-Xbp1-crc-kay -1 0.00386125 94.4191 0.14169 9 ATCACGTGAC TGACGTCACC - +2 transfac_pro__M00328-sv 5 0.00388252 94.9393 0.142142 10 ATCACGTGAC ACAGTCATGCGTGAGTTA + +2 neph__UW.Motif.0591 1 0.00392362 95.9443 0.143536 10 ATCACGTGAC AGCTGTGTGACT + +2 dbcorrdb__RCOR1__ENCSR000ECM_1__m1-cnc-CoRest-CrebB-Jra-kay-Mef2-mor-Myc-pan-Stat92E 1 0.00394824 96.5463 0.144105 10 ATCACGTGAC CCCGGGATGACTCATCCCCT + +2 dbcorrdb__ZNF143__ENCSR000EGP_1__m2-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.00394824 96.5463 0.144105 10 ATCACGTGAC CACAGCGCCGCCTAGTGGCC - +2 dbcorrdb__MXI1__ENCSR000EBR_1__m3-Chd1 -1 0.00394824 96.5463 0.144105 9 ATCACGTGAC GCTCGCGACAGCTCCGGCCG - +2 taipale_tf_pairs__TFAP4_ETV4_RCCGGAARCASSTGNN_CAP-crp-Ets96B 0 0.00397251 97.1397 0.144848 10 ATCACGTGAC CCCAGCTGCTTCCGGT - +2 cisbp__M0292-Xbp1 0 0.00398686 97.4908 0.144848 9 ATCACGTGAC GTGACGTGT + +2 predrem__nrMotif1935 0 0.00398686 97.4908 0.144848 9 ATCACGTGAC AACACTTGA + +2 predrem__nrMotif904 0 0.00398686 97.4908 0.144848 9 ATCACGTGAC TGCATGTGA + +2 transfac_pro__M09001-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.00409239 100.071 0.148568 10 ATCACGTGAC TGACCTTTTGACCTC - +2 taipale_cyt_meth__TCF12_NCACSTGN_eDBD-da-esg-sc-sna-wor -1 0.00411912 100.725 0.14897 8 ATCACGTGAC GCACCTGC + +2 cisbp__M0367 -1 0.00411912 100.725 0.14897 8 ATCACGTGAC TTACGTCA - +2 neph__UW.Motif.0372 6 0.00414019 101.24 0.149238 8 ATCACGTGAC CAGAAAGTCATTTG - +2 scertf__morozov.MET28-Atf6-CrebB-Jra 0 0.00415788 101.673 0.149238 10 ATCACGTGAC TTGACGTCAC + +2 taipale_cyt_meth__NEUROG2_RMCATATGYY_FL_meth-amos-ato-Oli-tap 0 0.00415788 101.673 0.149238 10 ATCACGTGAC GACATATGTC + +2 cisbp__M1137-achi-hth-vis -1 0.00415788 101.673 0.149238 9 ATCACGTGAC TTACATGTAA + +2 cisbp__M0309-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-vri-Xbp1 -1 0.00415788 101.673 0.149238 9 ATCACGTGAC TGACGTCATC - +2 cisbp__M0353 -2 0.00415788 101.673 0.149238 8 ATCACGTGAC TACGTGTCCT - +2 hocomoco__KAISO_HUMAN.H11MO.1.A-Chd1-CoRest 1 0.00417685 102.137 0.149356 10 ATCACGTGAC TCTCGCGAGAA + +2 jaspar__MA0549.1 0 0.00417685 102.137 0.149356 10 ATCACGTGAC CGCACGTGTGA + +2 cisbp__M2862 4 0.00419717 102.633 0.149857 10 ATCACGTGAC GTGGGACACGTGGCGACT + +2 transfac_public__M00434 4 0.00419717 102.633 0.149857 10 ATCACGTGAC GTGGGACACGTGGCGACT + +2 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 23 0.00422632 103.346 0.150583 8 ATCACGTGAC TGGCCTCAGGCGATGCGGGCCGAGGCACGTG + +2 dbcorrdb__TBL1XR1__ENCSR000EGB_1__m2-ebi-Jra 2 0.00427179 104.458 0.151952 10 ATCACGTGAC CCCGCAAATGACTTAACAGT + +2 cisbp__M4308 7 0.00428918 104.883 0.152456 9 ATCACGTGAC AATCAAAAAAAAATGA + +2 transfac_pro__M01938 -1 0.00432403 105.736 0.153466 7 ATCACGTGAC GCGCGTG + +2 transfac_pro__M04739-vtd -1 0.00432403 105.736 0.153466 7 ATCACGTGAC TCTAGTG + +2 cisbp__M0186-da-emc-GATAe-grn-pnr-sc-zfh1 -1 0.00444837 108.776 0.157526 8 ATCACGTGAC GCAGGTGC + +2 flyfactorsurvey__HLHmbeta_SANGER_10_FBgn0002733-E(spl)mbeta-HLH-Sidpn-dpn-h -2 0.00444837 108.776 0.157526 8 ATCACGTGAC CGCGTGCC + +2 yetfasco__YOR032C_1498 -1 0.00444837 108.776 0.157526 8 ATCACGTGAC CTACGTGT + +2 yetfasco__YDL056W_2138 -1 0.00447512 109.43 0.158121 9 ATCACGTGAC TTACGCGTCT + +2 cisbp__M2342 0 0.00449589 109.938 0.158619 10 ATCACGTGAC CGCACGTGTGA + +2 transfac_pro__M00440-Atf6-Clk-CrebA-gce 0 0.00449589 109.938 0.158619 10 ATCACGTGAC GCCACGTGGCA + +2 taipale_tf_pairs__CLOCK_EVX1_TAATTANNNNNNCACGTG_CAP_repr-Clk-eve 10 0.00453473 110.888 0.159634 8 ATCACGTGAC TAATTATTGACACACGTG + +2 taipale_tf_pairs__ETV5_HES7_CCGGAANNNNNNCACGTG_CAP-Ets96B 10 0.00453473 110.888 0.159634 8 ATCACGTGAC CCGGAAGCGCAGCGCGTG + +2 homer__AAGCACGTGBGD_Pho4 1 0.00455152 111.298 0.159989 10 ATCACGTGAC ACACACGTGCTT - +2 neph__UW.Motif.0232 3 0.00455152 111.298 0.159989 9 ATCACGTGAC AGCAGTTTGTGA + +2 taipale_tf_pairs__CLOCK_NHLH1_NRCAGCTGNNNNNCACGTGNN_CAP_repr-Clk-HLH4C 0 0.00461282 112.797 0.161267 10 ATCACGTGAC GACACGTGTGGCGCAGCTGCG - +2 dbcorrdb__ATF1__ENCSR000DNZ_1__m1-Atf-2-Atf3-Atf6-CG44247-cnc-CoRest-CrebA-CrebB-Jra-kay-Max-Myc-REPTOR-BP-SREBP-Usf-Xbp1 1 0.00461915 112.952 0.161267 10 ATCACGTGAC GCGGCGATGACGTCATCCGG + +2 dbcorrdb__FOS__ENCSR000DOT_1__m1-cnc-Jra-kay-maf-S-mor-Myc-nej-Stat92E-tj 0 0.00461915 112.952 0.161267 10 ATCACGTGAC AAATGATGACTCATCCTTTT + +2 dbcorrdb__ATF1__ENCSR000DNZ_1__m2-cnc-CoRest-CrebB-Jra-RpII215-Usf 2 0.00461915 112.952 0.161267 10 ATCACGTGAC CCCCCGGGTGACGCAACCGG - +2 dbcorrdb__FOS__ENCSR000DOO_1__m1-Jra-kay-maf-S-mor-Stat92E 6 0.00461915 112.952 0.161267 10 ATCACGTGAC ATAAAAAAATGATGACTCAT - +2 dbcorrdb__FOS__ENCSR000DOP_1__m1-cnc-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pnr-Stat92E 1 0.00461915 112.952 0.161267 10 ATCACGTGAC TAAAGGATGACTCATCCTTT - +2 dbcorrdb__RFX5__ENCSR000ECF_1__m4 2 0.00461915 112.952 0.161267 10 ATCACGTGAC GTGACACATGACGCAACCTG - +2 taipale_tf_pairs__TEAD4_CLOCK_GGWATGNNNNNNNCACGTGN_CAP_repr-Clk-sd 11 0.00461915 112.952 0.161267 9 ATCACGTGAC GGTATGCTGGTGACACGTGT + +2 cisbp__M0184-ac-da-Hand-sc 0 0.00462708 113.146 0.161267 9 ATCACGTGAC TGCAGGTGT + +2 transfac_pro__M08943-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 0 0.00462855 113.182 0.161267 10 ATCACGTGAC AAATGATGACGTCATC - +2 neph__UW.Motif.0629 7 0.00462855 113.182 0.161267 9 ATCACGTGAC GAAAAGCAGCATCTGG - +2 neph__UW.Motif.0236 5 0.00475055 116.165 0.165397 8 ATCACGTGAC ATTTTTTCATATG + +2 tfdimers__MD00161-Jra 1 0.004766 116.543 0.165692 10 ATCACGTGAC TTAAAGATGACTCAAAGTGAAACTAAAAAA + +2 transfac_pro__M02791-svp-usp -1 0.00478699 117.056 0.165915 9 ATCACGTGAC TGTCGTGACCCCTTAAT + +2 cisbp__M4984-Clk-E2f1-gce-Max-Myc-tgo-Usf 0 0.00480142 117.409 0.165915 8 ATCACGTGAC GCCACGTG + +2 cisbp__M0169 -2 0.00480142 117.409 0.165915 8 ATCACGTGAC CGCGTGTC - +2 bergman__h-h 2 0.00481013 117.622 0.165915 10 ATCACGTGAC ATGGCGCGTGCCGC - +2 neph__UW.Motif.0459 2 0.00481013 117.622 0.165915 10 ATCACGTGAC CAGCTCTGTGAATT - +2 transfac_public__M00067-h 2 0.00481013 117.622 0.165915 10 ATCACGTGAC ATGGCGCGTGCCGC - +2 cisbp__M1557 0 0.00481425 117.723 0.165915 10 ATCACGTGAC TTTTCGAAAA + +2 cisbp__M0331 -1 0.00481425 117.723 0.165915 9 ATCACGTGAC TTACGTAAGC - +2 transfac_pro__M00693-esg-nau-sna-wor 1 0.00483693 118.278 0.166456 10 ATCACGTGAC CGGCACCTGCC - +2 tfdimers__MD00117 2 0.00489519 119.702 0.168088 10 ATCACGTGAC AGGGGCAGTGACAGGTGGCGGGG + +2 taipale_cyt_meth__ATF2_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 1 0.0048985 119.783 0.168088 10 ATCACGTGAC GGTGACGTCACC + +2 hocomoco__ARNT_HUMAN.H11MO.0.B-sima-tgo -1 0.00498109 121.803 0.16995 9 ATCACGTGAC GTACGTGCC + +2 dbcorrdb__BACH1__ENCSR000EGD_1__m1-cnc-Jra-kay-maf-S-nej-tj 0 0.00499186 122.066 0.16995 10 ATCACGTGAC AAACCATGACTCAGCAATTT - +2 dbcorrdb__JUN__ENCSR000EGH_1__m3-CG9650-cnc-ewg-Jra-kay-maf-S 1 0.00499186 122.066 0.16995 10 ATCACGTGAC TCAGCAGTGACTCAGCAGGT - +2 transfac_pro__M01248 0 0.00499186 122.066 0.16995 10 ATCACGTGAC GGAAGGTGACCTTGCACTTC - +2 taipale_tf_pairs__ETV5_TCF3_RNCGGAAGNNNNNCASSTGN_CAP_repr-Ets96B 11 0.00499186 122.066 0.16995 9 ATCACGTGAC GGCGGAAGTGGGGCAGGTGG + +2 stark__TGACANNNNNNTGACA 5 0.00499204 122.07 0.16995 10 ATCACGTGAC TGACAAAAAAATGACA + +2 transfac_pro__M03820-EcR-eg-ERR-kni-knrl 2 0.00513088 125.465 0.174223 10 ATCACGTGAC GGTCACCGTGACCTG + +2 hocomoco__PO3F2_MOUSE.H11MO.1.A-nub-pdm2-vvl 0 0.00516441 126.285 0.174223 10 ATCACGTGAC GTCTCATGAATATTCAT + +2 transfac_pro__M02904-Sox15 0 0.00516441 126.285 0.174223 10 ATCACGTGAC ATTGTATGAATGTGGTC - +2 cisbp__M0288 0 0.0051766 126.583 0.174223 10 ATCACGTGAC ATGTCGACAT + +2 cisbp__M5902-da-Hand-sc 0 0.0051766 126.583 0.174223 10 ATCACGTGAC CACACCTGCA + +2 factorbook__SREBF1-SREBP 0 0.0051766 126.583 0.174223 10 ATCACGTGAC GTGGGGTGAT + +2 taipale__TCF4_full_NNCACCTGNN_repr-da-Hand-sc 0 0.0051766 126.583 0.174223 10 ATCACGTGAC CACACCTGCA + +2 cisbp__M0580 0 0.0051766 126.583 0.174223 10 ATCACGTGAC AATCCGCGGA - +2 hocomoco__HTF4_MOUSE.H11MO.0.A 0 0.0051766 126.583 0.174223 10 ATCACGTGAC CCCACCTGCT - +2 transfac_pro__M00366-Atf6-CrebA-Max-Mnt-Usf 0 0.0051766 126.583 0.174223 10 ATCACGTGAC GCCACGTGGC - +2 cisbp__M5023-dpn-E(spl)mbeta-HLH-h-Sidpn -2 0.00517978 126.661 0.174223 8 ATCACGTGAC CGCGTGCC + +2 jaspar__MA0569.1-Hey -1 0.00517978 126.661 0.174223 8 ATCACGTGAC ACACGTGC + +2 cisbp__M2362-Hey -1 0.00517978 126.661 0.174223 8 ATCACGTGAC ACACGTGC - +2 flyfactorsurvey__sna_F2-4_SOLEXA_5-esg-sna 0 0.00520132 127.188 0.174332 10 ATCACGTGAC CCCACCTGTCA + +2 hocomoco__FIGLA_HUMAN.H11MO.0.D 1 0.00520132 127.188 0.174332 10 ATCACGTGAC TAACAGGTGTT + +2 transfac_pro__M02108 0 0.00520132 127.188 0.174332 10 ATCACGTGAC CCCACTTGAAG + +2 cisbp__M2350 2 0.0052693 128.85 0.176362 10 ATCACGTGAC TGAGCGCGTGAG - +2 taipale_cyt_meth__MYF6_CGTCANNTGTYN_eDBD-Fer1-nau 1 0.0052693 128.85 0.176362 10 ATCACGTGAC CAACAGCTGACG - +2 cisbp__M1407 0 0.00535958 131.058 0.17863 9 ATCACGTGAC GTTGCGTGT - +2 flyfactorsurvey__HLHmdelta_SANGER_10_FBgn0002734-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey -2 0.00535958 131.058 0.17863 8 ATCACGTGAC CACGTGCCA - +2 homer__ANTTMRCASBNNNGTGYKAAN_Brachyury-H15-byn-mid-org-1 8 0.00538897 131.776 0.179069 10 ATCACGTGAC ATTTCACACCTAGGTGTTAAT + +2 dbcorrdb__FOSL2__ENCSR000BHP_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Snr1-Stat92E 0 0.00539156 131.84 0.179069 10 ATCACGTGAC AAGGGATGACTCATCCCTGA + +2 dbcorrdb__ATF2__ENCSR000BQU_1__m1-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.00539156 131.84 0.179069 10 ATCACGTGAC CCCTGGGGATGACGTCATCG - +2 transfac_pro__M02088-sc 2 0.00550244 134.551 0.182497 10 ATCACGTGAC CCAGCAGGTGGCC - +2 cisbp__M4526-cnc-ewg-Jra-kay-maf-S-mor-Myc-pan 0 0.00552672 135.145 0.182578 10 ATCACGTGAC GGGGGGTGACTCATC + +2 cisbp__M6407-sv -3 0.00552791 135.174 0.182578 7 ATCACGTGAC GCATGAC + +2 transfac_pro__M03582-twi -1 0.00552791 135.174 0.182578 7 ATCACGTGAC CCAGGTG - +2 transfac_pro__M00375-Usf 0 0.00556361 136.047 0.183502 10 ATCACGTGAC GCCACGTCAC + +2 taipale_cyt_meth__HES5_GGCACGTGYY_eDBD-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn 0 0.00556361 136.047 0.183502 10 ATCACGTGAC GACACGTGCC - +2 hocomoco__XBP1_HUMAN.H11MO.0.D-Atf6-CrebA-Xbp1 0 0.00559046 136.704 0.183878 10 ATCACGTGAC GCCACGTCAGC - +2 homer__HHCACGCGCBTN_FHY3 2 0.00566539 138.536 0.185957 10 ATCACGTGAC GAGGCGCGTGGA - +2 taipale_cyt_meth__MSGN1_NRCCAWWTGKYN_eDBD-amos-da-dimm-HLH54F-Oli-tap 1 0.00566539 138.536 0.185957 10 ATCACGTGAC GGACATATGGCG - +2 cisbp__M5024-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey -2 0.00576406 140.949 0.189066 8 ATCACGTGAC CACGTGCCA - +2 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNCACGTGN_CAP_repr-Max-TfAP-2 13 0.00578592 141.483 0.189205 9 ATCACGTGAC TGGCCTCAGGCCAAACACGTGC + +2 jaspar__MA0303.1-Jra-Mef2-Myc-Stat92E-kay 1 0.0058197 142.309 0.189205 10 ATCACGTGAC CAAGGGATGAGTCATACTTCA + +2 cisbp__M4501-Jra-kay 7 0.00581998 142.316 0.189205 10 ATCACGTGAC CATTCCTGAGGGATGACTTA + +2 dbcorrdb__FOS__ENCSR000DON_1__m1-Jra-kay-Mef2-Myc-nej-Stat92E 2 0.00581998 142.316 0.189205 10 ATCACGTGAC AAAAAGGATGACTCATACTT + +2 dbcorrdb__JUND__ENCSR000EBZ_1__m2-CoRest-CrebB-Jra-kay-mor-pan 1 0.00581998 142.316 0.189205 10 ATCACGTGAC CCCGGGGTGACTCAACCCGG + +2 dbcorrdb__STAT3__ENCSR000EDC_1__m1-Jra-kay-Myc-nej-Stat92E 4 0.00581998 142.316 0.189205 10 ATCACGTGAC AAAAAAAAGATGACTCATTT + +2 taipale_tf_pairs__E2F1_HES7_RRCRCGYGYNNNNSGCGCSN_CAP_repr-E2f1 0 0.00581998 142.316 0.189205 10 ATCACGTGAC GGCACGTGCCGTTGGCGCCC + +2 dbcorrdb__CEBPB__ENCSR000BRX_1__m3 0 0.00581998 142.316 0.189205 10 ATCACGTGAC CTGATGTGAGTCAGTTGTGG - +2 tfdimers__MD00600-EcR-usp 2 0.00584125 142.836 0.189766 10 ATCACGTGAC TGTCTCAGTGACAGATGGCCTTGGAG + +2 transfac_public__M00197 4 0.00594999 145.495 0.192852 10 ATCACGTGAC TCGTTTATAGTGATA - +2 taipale_tf_pairs__GCM1_MAX_CACGTGNNNGCGGGY_CAP-gcm-gcm2-Max 7 0.00594999 145.495 0.192852 8 ATCACGTGAC ACCCGCATCCACGTG - +2 cisbp__M0289 0 0.00597675 146.149 0.192852 10 ATCACGTGAC ATCGCGTCAT - +2 homer__NNCACCTGCN_E2A-da-sc 0 0.00597675 146.149 0.192852 10 ATCACGTGAC TGCAGGTGTG - +2 hocomoco__HEY2_HUMAN.H11MO.0.D-Hey 3 0.00600107 146.744 0.193244 10 ATCACGTGAC GGTGGCACGTGGCATTA + +2 stark__CNNNGCGYRTGANYNAT 3 0.00600107 146.744 0.193244 10 ATCACGTGAC CAAAGCGCATGAACAAT + +2 flyfactorsurvey__Met_Clk_SANGER_5_FBgn0002723-Clk-Met 0 0.00601904 147.184 0.1933 8 ATCACGTGAC GACACGTG + +2 taipale_cyt_meth__LHX1_NTCGTTAN_eDBD_meth-Lim1 -2 0.00601904 147.184 0.1933 8 ATCACGTGAC CTCGTTAC + +2 transfac_pro__M08800-tgo -2 0.00601904 147.184 0.1933 8 ATCACGTGAC TACGTGCC + +2 taipale_cyt_meth__MSGN1_NRCCAWWTGKYN_eDBD_meth-amos-da-dimm-Fer3-HLH54F-Oli-tap 1 0.00608828 148.877 0.194683 10 ATCACGTGAC CACCATATGTTA + +2 jaspar__MA0557.1 2 0.00608828 148.877 0.194683 10 ATCACGTGAC TGAGCGCGTGAG - +2 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_FL_meth-achi-amos-Fer3-HLH54F-nau-vis 1 0.00608828 148.877 0.194683 10 ATCACGTGAC CAACAGCTGTCG - +2 transfac_public__M00182-Atf6-CrebA-Max-Myc-tgo-Usf 1 0.00608828 148.877 0.194683 10 ATCACGTGAC TGCCACGTGGCC - +2 transfac_pro__M07469-HLH3B-HLH4C 3 0.00608828 148.877 0.194683 9 ATCACGTGAC GACACCACCTGC + +2 tfdimers__MD00238-cnc-E2f1-maf-S 0 0.00609077 148.938 0.194683 10 ATCACGTGAC TAAAAATGACTCAGAAACGAAAAA - +2 cisbp__M1162 -1 0.00619612 151.514 0.19752 9 ATCACGTGAC TCGTGTAAA - +2 cisbp__M4753-ato-da -1 0.00619612 151.514 0.19752 9 ATCACGTGAC CCACCTGCC - +2 transfac_pro__M09557 0 0.00619612 151.514 0.19752 9 ATCACGTGAC GCCACGTGA - +2 transfac_public__M00098-Poxm-sv 5 0.00623528 152.471 0.198476 10 ATCACGTGAC TCCATCATGCGTGACGAGG - +2 taipale_tf_pairs__ELK1_SREBF2_RSCGGAANTSRCGTGA_CAP_repr-SREBP 7 0.00624279 152.655 0.198476 9 ATCACGTGAC ACCGGAAGTGGCGTGA + +2 neph__UW.Motif.0547 -2 0.00624279 152.655 0.198476 8 ATCACGTGAC CACATGACGTCAGAGC + +2 dbcorrdb__CEBPB__ENCSR000EFM_1__m2-CoRest-Jra-kay-Myc-pan-Stat92E 4 0.00627891 153.538 0.198904 10 ATCACGTGAC GACTAAGGTATGACTCATTG + +2 dbcorrdb__FOS__ENCSR000EZE_1__m1-cnc-CoRest-Jra-kay-Mef2-mor-Myc-pan-Snr1-Stat92E 4 0.00627891 153.538 0.198904 10 ATCACGTGAC GCCGCAGGGATGAGTCATAC + +2 transfac_pro__M01555-Jra-kay-Mef2-Myc-Stat92E 1 0.00628131 153.597 0.198904 10 ATCACGTGAC CAAGGGATGAGTCATACTTCA + +2 cisbp__M0199 -1 0.00636055 155.535 0.201279 9 ATCACGTGAC GCACGTGTCGTTA - +2 neph__UW.Motif.0668 3 0.00640236 156.557 0.201427 10 ATCACGTGAC TCTGTCATTTTTTCA + +2 cisbp__M2398 4 0.00640236 156.557 0.201427 10 ATCACGTGAC TCGTTTATAGTGATA - +2 stark__CACNNRNNNNNNCAC 7 0.00640236 156.557 0.201427 8 ATCACGTGAC GTGAAAAAACAAGTG - +2 cisbp__M1203 0 0.0064176 156.93 0.201427 10 ATCACGTGAC AGCCCATTAC - +2 transfac_pro__M07861-CG7786-gt-hng1-Pdp1-vri 0 0.0064176 156.93 0.201427 10 ATCACGTGAC GTTACGTAAC - +2 taipale_cyt_meth__TCFL5_NCACGYGCAN_eDBD 1 0.0064176 156.93 0.201427 9 ATCACGTGAC GTGCGCGTGA - +2 cisbp__M1425 -2 0.0064176 156.93 0.201427 8 ATCACGTGAC ATTGTAACCT + +2 cisbp__M6487-SREBP 1 0.00644909 157.7 0.201427 10 ATCACGTGAC GGTGGGGTGAG + +2 transfac_pro__M02912-Sox100B 1 0.00645244 157.782 0.201427 10 ATCACGTGAC CGTGTCATGAATGT - +2 neph__UW.Motif.0255 6 0.00645244 157.782 0.201427 8 ATCACGTGAC CAAGATTCCATCTG + +2 tfdimers__MD00262-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 4 0.00645833 157.926 0.201427 10 ATCACGTGAC CATTGCCACCTGGCAGGTGGCAGAT + +2 cisbp__M4101-Atf6-CrebA-Xbp1 4 0.00646372 158.057 0.201463 10 ATCACGTGAC ATAGGACACGTCATCAT - +2 elemento__CGCGTGAC -2 0.00648346 158.54 0.201682 8 ATCACGTGAC CGCGTGAC + +2 taipale_cyt_meth__CREB3L1_TGCCACRTCAYN_eDBD_meth-Atf6-CrebA-Xbp1 1 0.00653958 159.912 0.202765 10 ATCACGTGAC TGCCACGTCACC + +2 flyfactorsurvey__Espl_FlyReg_FBgn0000591-E(spl)m8-HLH 3 0.00653958 159.912 0.202765 9 ATCACGTGAC TGTGCCACGTGC + +2 stark__CACNNNNNNACA 4 0.00653958 159.912 0.202765 8 ATCACGTGAC TGTAAAAAAGTG - +2 hdpi__CREB3L1-CrebA -4 0.00655577 160.308 0.203135 6 ATCACGTGAC CGTGGT - +2 tfdimers__MD00565 2 0.00665653 162.772 0.205348 10 ATCACGTGAC GAAGGCAGTGACAGATGGGGAGGTAGA + +2 cisbp__M0581 -1 0.00665742 162.794 0.205348 9 ATCACGTGAC CCGCGTTAC + +2 cisbp__M1208 -1 0.00665742 162.794 0.205348 9 ATCACGTGAC ACATGTCAA + +2 flyfactorsurvey__ato_da_SANGER_5_3_FBgn0000413-ato-da -1 0.00665742 162.794 0.205348 9 ATCACGTGAC CCACCTGCC + +2 transfac_pro__M01861-Atf6-CrebB -1 0.00665742 162.794 0.205348 9 ATCACGTGAC TCACGTCAC + +2 neph__UW.Motif.0496 3 0.00671874 164.293 0.206627 10 ATCACGTGAC AGGATGCAGTGATCTG + +2 neph__UW.Motif.0640 1 0.00671874 164.293 0.206627 10 ATCACGTGAC CTCCATCTGCCTGTCA + +2 neph__UW.Motif.0095-twi 8 0.00671874 164.293 0.206627 8 ATCACGTGAC TAATTAATAACATATG - +2 neph__UW.Motif.0573 8 0.00671874 164.293 0.206627 8 ATCACGTGAC CAAAATTTTTCATCTG - +2 taipale_cyt_meth__MAX_NCATGTGNNNNNCATGTGN_eDBD_meth-Max -1 0.00672058 164.338 0.206627 9 ATCACGTGAC GCACATGGTAAGCACATGG - +2 tfdimers__MD00257-CrebB-GATAe-grn-pnr-srp 0 0.00674242 164.872 0.207165 10 ATCACGTGAC TAAAAATGACAGATAAGAAATT + +2 dbcorrdb__TCF7L2__ENCSR000EUV_1__m2-cnc-CoRest-Jra-kay-Mef2-mor-Myc-pan-Snr1 0 0.00677028 165.554 0.207619 10 ATCACGTGAC CGGGGATGACTCATCGCCGC + +2 dbcorrdb__MYC__ENCSR000DOM_1__m2-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 1 0.00677028 165.554 0.207619 10 ATCACGTGAC TAAGGGATGACTCATCCCTT - +2 dbcorrdb__HDAC1__ENCSR000AQF_1__m1-HDAC1-Max-Myc-Sap30 11 0.00677028 165.554 0.207619 9 ATCACGTGAC GCCCGTCGGAAACCACGTGG + +2 tfdimers__MD00406 43 0.00681065 166.541 0.208454 10 ATCACGTGAC GCGCTCAGCTGAGCATCTGGGGGTGTGGCCACACCCCCAGATGCTCAGCTGAGCGC + +2 transfac_pro__M08955-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 0 0.0068335 167.1 0.208535 10 ATCACGTGAC GACCTTTGACCCC - +2 jaspar__MA0616.1 -1 0.0068335 167.1 0.208535 9 ATCACGTGAC GCACGTGTCGTTA - +2 flyfactorsurvey__disco-r-F1-2_SOLEXA_FBgn0042650-disco-disco-r 0 0.00688559 168.373 0.208535 10 ATCACGTGAC GTTGGGTGACATTTT + +2 neph__UW.Motif.0680 1 0.00688559 168.373 0.208535 10 ATCACGTGAC TGCCTCCTGGCCTTG - +2 cisbp__M1196 0 0.0068878 168.427 0.208535 10 ATCACGTGAC TGCATATCAA + +2 homer__RCCATMTGTT_Olig2-Fer3-HLH3B-HLH54F-Oli-amos-ato-da-dimm-tap 0 0.0068878 168.427 0.208535 10 ATCACGTGAC ACCATCTGTT + +2 taipale_cyt_meth__ASCL1_NRCAGCTGYN_eDBD-ac-ase-l(1)sc-sc 0 0.0068878 168.427 0.208535 10 ATCACGTGAC GGCAGCTGCC + +2 cisbp__M1277 0 0.0068878 168.427 0.208535 10 ATCACGTGAC CTCTGGTTAA - +2 cisbp__M1416 0 0.0068878 168.427 0.208535 10 ATCACGTGAC GTTGCGTAAA - +2 taipale_cyt_meth__SNAI1_NRCAGGTGYR_eDBD-ac-ase-da-esg-l(1)sc-sc-sna-wor 0 0.0068878 168.427 0.208535 10 ATCACGTGAC TGCACCTGCC - +2 cisbp__M5020-E(spl)m5-HLH 1 0.0068878 168.427 0.208535 9 ATCACGTGAC TGTCTCGTGC + +2 cisbp__M0335 -1 0.0068878 168.427 0.208535 9 ATCACGTGAC TTACGTAATC - +2 cisbp__M1408 1 0.0068878 168.427 0.208535 9 ATCACGTGAC GGTTGCGTGT - +2 cisbp__M1409 1 0.0068878 168.427 0.208535 9 ATCACGTGAC GGTTGCGTGT - +2 transfac_public__M00251-Atf6-CrebA-Xbp1 4 0.00695835 170.153 0.209998 10 ATCACGTGAC ATAGGACACGTCATCAT - +2 homer__GCCACGTG_E-box-Atf6-Clk-CrebA-Myc 0 0.00698024 170.688 0.209998 8 ATCACGTGAC GCCACGTG + +2 taipale_cyt_meth__TCF12_NCACSTGN_eDBD_meth-ac-ase-da-esg-sc-sna-wor -1 0.00698024 170.688 0.209998 8 ATCACGTGAC ACACCTGC + +2 stark__CACGAGNC-h 0 0.00698024 170.688 0.209998 8 ATCACGTGAC GACTCGTG - +2 flyfactorsurvey__Six4_SOLEXA_FBgn0027364-Optix-Six4 -3 0.00698024 170.688 0.209998 7 ATCACGTGAC AATTGATA + +2 transfac_public__M00001-esg-nau 1 0.00702098 171.684 0.210957 10 ATCACGTGAC CACCACCTGTTG - +2 cisbp__M0305-CrebA 0 0.00714972 174.832 0.21388 9 ATCACGTGAC GCCACGTGT + +2 jaspar__MA0970.1 -1 0.00714972 174.832 0.21388 9 ATCACGTGAC CCGCGTTAC + +2 hocomoco__EPAS1_HUMAN.H11MO.0.B-sima-tgo -1 0.00714972 174.832 0.21388 9 ATCACGTGAC GTACGTGCC - +2 cisbp__M0278-Xbp1 -2 0.00714972 174.832 0.21388 8 ATCACGTGAC CACGTCATC - +2 cisbp__M0867 -2 0.00714972 174.832 0.21388 8 ATCACGTGAC CGTGTCACT - +2 transfac_pro__M03812-tgo -2 0.00716322 175.162 0.214149 6 ATCACGTGAC TACGTG - +2 neph__UW.Motif.0074 5 0.00722723 176.728 0.215624 10 ATCACGTGAC CCAGGAGTTTCTGCCA + +2 neph__UW.Motif.0432 6 0.00722723 176.728 0.215624 10 ATCACGTGAC GCTTTTTCCTCTTTCT - +2 neph__UW.Motif.0129 8 0.00722723 176.728 0.215624 8 ATCACGTGAC AGAGAGGTGGCTGCTG + +2 cisbp__M3710-Poxm-sv 5 0.00723972 177.033 0.215624 10 ATCACGTGAC GCCATCATGCGTGACGAGG + +2 taipale_tf_pairs__RFX3_FIGLA_TRGYAACNNNNCASSTGNN_CAP_repr-Rfx 0 0.00723972 177.033 0.215624 10 ATCACGTGAC TCCACCTGTTCCGTTGCCA - +2 cisbp__M2108-Jra-kay-Mef2-Myc-Stat92E 1 0.00730499 178.629 0.21716 10 ATCACGTGAC CAAGGGATGAGTCATACTTCA - +2 neph__UW.Motif.0047 5 0.00733805 179.437 0.218007 8 ATCACGTGAC CAGAAACCATTTG - +2 cisbp__M0079 0 0.00738909 180.686 0.218432 10 ATCACGTGAC TCAACGTTGA + +2 transfac_pro__M00368-Atf6-Clk-CrebA-Met 0 0.00738909 180.686 0.218432 10 ATCACGTGAC GCCACGTGGC + +2 cisbp__M5029-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 0 0.00738909 180.686 0.218432 10 ATCACGTGAC GGCACGTGCC - +2 cisbp__M1964-Max-Myc -1 0.00738909 180.686 0.218432 9 ATCACGTGAC CCATGTGCTT + +2 jaspar__MA0147.2-Max-Myc -1 0.00738909 180.686 0.218432 9 ATCACGTGAC CCATGTGCTT + +2 cisbp__M1412 1 0.00738909 180.686 0.218432 9 ATCACGTGAC GGTTGCGTGT - +2 neph__UW.Motif.0360-amos 3 0.00740154 180.99 0.218664 10 ATCACGTGAC GAAGCCAGCTGGCTT - +2 flyfactorsurvey__Fer1_da_SANGER_10_FBgn0000413-Fer1-da 0 0.00742571 181.581 0.218835 10 ATCACGTGAC AACACCTGTCA + +2 hocomoco__SRBP1_MOUSE.H11MO.0.B-SREBP 1 0.00742571 181.581 0.218835 10 ATCACGTGAC GGTGGGGTGAG + +2 cisbp__M4965-da-Fer1 0 0.00742571 181.581 0.218835 10 ATCACGTGAC AACACCTGTCA - +2 transfac_pro__M01893 2 0.00742571 181.581 0.218835 9 ATCACGTGAC ATTCCACGTCA + +2 neph__UW.Motif.0168 6 0.0074506 182.19 0.219433 8 ATCACGTGAC CTGGGTTCCAGCTG - +2 cisbp__M5193-Optix-Six4 -3 0.0075114 183.676 0.220939 7 ATCACGTGAC AATTGATA + +2 tfdimers__MD00588-Jra-kay 2 0.00753042 184.141 0.220939 10 ATCACGTGAC CCCCTTGCTGACTCCTCCTCCCCCC - +2 hocomoco__BHE23_HUMAN.H11MO.0.D-Oli 0 0.00753425 184.235 0.220939 10 ATCACGTGAC AGCATATGGTGG + +2 bergman__esg-esg-sna-wor 1 0.00753425 184.235 0.220939 10 ATCACGTGAC CTGCACCTGTTA - +2 taipale_cyt_meth__CREB1_NRTGACGTCAYN_eDBD-Atf3-Atf6-CG7786-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 1 0.00753425 184.235 0.220939 10 ATCACGTGAC CGTGACGTCACG - +2 tfdimers__MD00496-lz-run-RunxA-RunxB 2 0.00756021 184.87 0.221564 10 ATCACGTGAC TTAAGCAGTGACAGATGGTGTGGGATAA + +2 jaspar__MA0608.1-CrebA 0 0.00767487 187.674 0.224234 9 ATCACGTGAC GCCACGTGT + +2 yetfasco__YDR123C_713 -1 0.00767487 187.674 0.224234 9 ATCACGTGAC GCATGTGAA - +2 taipale_cyt_meth__RARA_NRGGTCANNRGGTCAN_eDBD-EcR-eg-Hr78-kni-knrl-svp-usp 3 0.00777021 190.005 0.226741 10 ATCACGTGAC GTGACCTCTTGACCTC - +2 dbcorrdb__TCF12__ENCSR000BQQ_1__m2-cnc-Jra-kay-Myc-nej-Stat92E 3 0.00785847 192.163 0.228684 10 ATCACGTGAC ATTAATCAATGACTCATCAT + +2 dbcorrdb__JUND__ENCSR000BGK_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Snr1-Stat92E 1 0.00785847 192.163 0.228684 10 ATCACGTGAC GCCGGGATGACTCATCCCTG - +2 dbcorrdb__SMARCC2__ENCSR000EDL_1__m2-mor-Six4 3 0.00785847 192.163 0.228684 10 ATCACGTGAC GGGCCTCTGGGACTTGTAGT - +2 cisbp__M0304-CG7786-gt-hng1-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 0 0.00792329 193.748 0.228684 10 ATCACGTGAC ATTACGTAAT + +2 flyfactorsurvey__cato_da_SANGER_10_FBgn0000413-cato-da 0 0.00792329 193.748 0.228684 10 ATCACGTGAC CACAGCTGAC + +2 flyfactorsurvey__h_NAR_FBgn0001168-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 0 0.00792329 193.748 0.228684 10 ATCACGTGAC GGCACGTGCC + +2 taipale_cyt_meth__HES6_GGCACGTGTN_FL-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 0 0.00792329 193.748 0.228684 10 ATCACGTGAC GGCACGTGTT + +2 transfac_pro__M07574-Atf3-Atf6-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 0 0.00792329 193.748 0.228684 10 ATCACGTGAC GTGACGTCAC + +2 cisbp__M4793-cato-da 0 0.00792329 193.748 0.228684 10 ATCACGTGAC CACAGCTGAC - +2 taipale_cyt_meth__NEUROD2_RMCATATGYY_FL_meth-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.00792329 193.748 0.228684 10 ATCACGTGAC AACATATGGT - +2 cisbp__M0092 1 0.00792329 193.748 0.228684 9 ATCACGTGAC AGTGACGCGT - +2 jaspar__MA0931.1-Atf6-Clk-Met-Myc -1 0.00792329 193.748 0.228684 9 ATCACGTGAC CCACGTGTCA - +2 cisbp__M0364 2 0.00792329 193.748 0.228684 8 ATCACGTGAC TCGCCACGTG + +2 taipale_cyt_meth__NR3C2_NGNACRNNNYGTNCN_eDBD 5 0.00795215 194.454 0.229239 10 ATCACGTGAC GGTACACGGTGTACC - +2 tfdimers__MD00592-crp-Myc 5 0.00795764 194.588 0.229259 10 ATCACGTGAC ACGCGGCCAGATGCTCATCTGGGGGT + +2 transfac_pro__M07283-EcR-eg-ERR-kni-knrl 1 0.00800025 195.63 0.230347 10 ATCACGTGAC GTCACCGTGACCTC + +2 cisbp__M6273-Hey 3 0.00805142 196.881 0.2314 10 ATCACGTGAC GGGGGCACGTGGCATTA + +2 transfac_pro__M03127-Clk-Hey-tai 3 0.00805142 196.881 0.2314 10 ATCACGTGAC TATGGCACGTGTCCAAT + +2 transfac_pro__M03134-E(spl)m3-HLH-Hey-Sidpn 3 0.00805142 196.881 0.2314 10 ATCACGTGAC TAAGGCACGTGCCTTGA - +2 cisbp__M5104-Clk-Met 0 0.00807907 197.558 0.231419 8 ATCACGTGAC GACACGTG + +2 hdpi__MLX-bigmax -2 0.00807907 197.558 0.231419 8 ATCACGTGAC CACGTGCG - +2 neph__UW.Motif.0654 0 0.00808125 197.611 0.231419 10 ATCACGTGAC CCCAGGTGCCGG + +2 transfac_pro__M03544-Atf3-Atf6-CrebA-CrebB-E2f1-Jra-maf-S-Xbp1 1 0.00808125 197.611 0.231419 10 ATCACGTGAC GCTGACGTCACC + +2 tfdimers__MD00269 1 0.00812449 198.668 0.232517 10 ATCACGTGAC AATTTTATGATTGATTAATCATTAA - +2 flyfactorsurvey__Max_Mnt_SANGER_5_FBgn0017578-Atf6-CrebA-Max-Myc -1 0.00822575 201.144 0.235109 7 ATCACGTGAC CCACGTG + +2 c2h2_zfs__M0442 0 0.00823481 201.366 0.235109 9 ATCACGTGAC TGCCCCTGA - +2 cisbp__M0325 -1 0.00823481 201.366 0.235109 9 ATCACGTGAC CCACGTCAG - +2 swissregulon__sacCer__MBP1 0 0.00823481 201.366 0.235109 9 ATCACGTGAC GACGCGTCA - +2 tfdimers__MD00594 2 0.00829412 202.816 0.236661 10 ATCACGTGAC ATTGACAGTGACAGATGGGGAAAGGAAAAA + +2 neph__UW.Motif.0201 1 0.00834973 204.176 0.237962 10 ATCACGTGAC CAGCTGCTGTTTTTTT - +2 taipale_cyt_meth__ZNF174_NGNCRATCACTYGNCN_eDBD_meth 1 0.00834973 204.176 0.237962 10 ATCACGTGAC GGGCGAGTGATCGGCA - +2 neph__UW.Motif.0523 -1 0.00844944 206.614 0.239587 9 ATCACGTGAC CCCTGTGCCCTGC + +2 neph__UW.Motif.0198 5 0.00844944 206.614 0.239587 8 ATCACGTGAC GAAAATTCTTCTG - +2 dbcorrdb__JUND__ENCSR000EDH_1__m1-Jra-kay-maf-S-Myc-nej-Stat92E 2 0.00845964 206.864 0.239587 10 ATCACGTGAC AAAAATGATGACTCATCCTT + +2 dbcorrdb__ATF3__ENCSR000BPS_1__m3 4 0.00845964 206.864 0.239587 10 ATCACGTGAC GCCTCCACCGGGAATCGAAC - +2 dbcorrdb__JUND__ENCSR000EGN_1__m1-cnc-CoRest-CrebB-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 1 0.00845964 206.864 0.239587 10 ATCACGTGAC GGGGGGATGACTCATCCCTG - +2 dbcorrdb__SMARCC1__ENCSR000EDM_1__m1-cnc-CoRest-Jra-kay-maf-S-mor-Myc-pan-Snr1 3 0.00845964 206.864 0.239587 10 ATCACGTGAC CGCCGGGGGTGACTCATCCC - +2 dbcorrdb__TRIM28__ENCSR000EYC_1__m4-bon 1 0.00845964 206.864 0.239587 10 ATCACGTGAC AGCCATATGGCTTCTCACCA - +2 cisbp__M5627-da-Hand-sc 0 0.00849231 207.662 0.239587 10 ATCACGTGAC CACAGGTGTT + +2 taipale_cyt_meth__NKX2-5_NCCACTTRAN_FL_repr-scro-tin-vnd 0 0.00849231 207.662 0.239587 10 ATCACGTGAC ACCACTTGAG + +2 taipale__MESP1_DBD_NNCACCTGNN-Hand 0 0.00849231 207.662 0.239587 10 ATCACGTGAC CACAGGTGTT - +2 cisbp__M0261-Atf6-Clk-Met-Myc -1 0.00849231 207.662 0.239587 9 ATCACGTGAC ACACGTGTCA - +2 transfac_pro__M02012-sima -3 0.00852932 208.568 0.240346 6 ATCACGTGAC ACGTGC - +2 tfdimers__MD00582 2 0.00856013 209.321 0.241071 10 ATCACGTGAC TGGGCCAGTGACAGGTGCCCGGGGCGCCG + +2 cisbp__M2290-bon-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-NFAT-pnr-Stat92E 0 0.00858624 209.959 0.241378 10 ATCACGTGAC AGGAGATGACTCAT + +2 jaspar__MA0489.1-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-bon-grn-kay-mor-nej-pnr 0 0.00858624 209.959 0.241378 10 ATCACGTGAC AGGAGATGACTCAT + +2 cisbp__M6229-cnc-ewg-kay-maf-S -2 0.00858624 209.959 0.241378 8 ATCACGTGAC AACGTGACTCAGCA - +2 transfac_pro__M09536-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 0 0.00865404 211.617 0.243131 10 ATCACGTGAC AAAAGATGACGTCATCA - +2 taipale_cyt_meth__LHX4_NTCGTTAN_eDBD_meth_repr-Lim3 -2 0.00868549 212.386 0.243449 8 ATCACGTGAC CTCGTTAA + +2 transfac_pro__M00973-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.00868549 212.386 0.243449 8 ATCACGTGAC GGCAGGTG - +2 predrem__nrMotif2029-Myc-Sap30 0 0.00883159 215.959 0.247108 9 ATCACGTGAC CCCACGTGG + +2 predrem__nrMotif2488 -2 0.00883159 215.959 0.247108 8 ATCACGTGAC CACTTGACA + +2 transfac_pro__M08964-EcR-ERR-Hr3-Hr78-usp 5 0.00887493 217.019 0.248174 10 ATCACGTGAC TGACCTCTACATGACCTC - +2 neph__UW.Motif.0394 2 0.00896795 219.293 0.250628 10 ATCACGTGAC CAGATTTCTGGCATTT - +2 taipale_cyt_meth__YY1_NGCCATNTTTGNCNNNNYGTGCN_FL_repr-pho-phol-Taf1 13 0.00902063 220.582 0.251566 10 ATCACGTGAC CGCCATCTTTGGCAATTCGTGCT + +2 taipale_tf_pairs__HOXD12_FIGLA_SYMRTAAANNNNCASSTGN_CAP_repr 10 0.00902145 220.602 0.251566 9 ATCACGTGAC GTCGTAAAAAGCCAGCTGG + +2 transfac_public__M00285-cnc 3 0.00906028 221.551 0.251566 10 ATCACGTGAC CTTCCAAAATGAC - +2 cisbp__M5900-da-Hand-sc 0 0.00909815 222.477 0.251566 10 ATCACGTGAC AGCAGGTGTT + +2 taipale_cyt_meth__ASCL2_NRCAGCTGYN_eDBD_meth-ac-ase-dimm-l(1)sc-nau-sc 0 0.00909815 222.477 0.251566 10 ATCACGTGAC AGCAGCTGCT + +2 transfac_pro__M00367-Atf6-Clk-CrebA-Usf 0 0.00909815 222.477 0.251566 10 ATCACGTGAC GCCACGTGGC + +2 transfac_pro__M07631-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.00909815 222.477 0.251566 10 ATCACGTGAC AACATATGTT + +2 cisbp__M6374-scro-vnd 0 0.00909815 222.477 0.251566 10 ATCACGTGAC AGCACTTGAG - +2 transfac_pro__M07583 0 0.00909815 222.477 0.251566 10 ATCACGTGAC ATTGCGTGTC - +2 dbcorrdb__ARID3A__ENCSR000EFY_1__m2-CTCF-SMC3-usp-vtd 8 0.00910194 222.57 0.251566 10 ATCACGTGAC ATAGCGCCCTCTGGTGGTAA + +2 dbcorrdb__HSF1__ENCSR000EET_1__m5-Hsf 2 0.00910194 222.57 0.251566 10 ATCACGTGAC CGGACTCGTGAACAGGCGTT + +2 dbcorrdb__JUN__ENCSR000EDG_1__m1-GATAe-grn-Jra-kay-Myc-nej-pnr-Stat92E 2 0.00910194 222.57 0.251566 10 ATCACGTGAC TAAAAGGATGACTCATCCTT - +2 dbcorrdb__JUN__ENCSR000EFA_1__m1-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 1 0.00910194 222.57 0.251566 10 ATCACGTGAC TAAAAGATGACTCATTCTTT - +2 transfac_pro__M08935-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 1 0.00914339 223.583 0.252155 10 ATCACGTGAC GATGACGTCAT - +2 flyfactorsurvey__gsb-n_SOLEXA_5_FBgn0001147-gsb-n 2 0.00916562 224.127 0.252155 10 ATCACGTGAC CTAGAGCGTGACTAA + +2 bergman__mirr-mirr 2 0.00916562 224.127 0.252155 10 ATCACGTGAC TTAACACGTGTTTTC - +2 neph__UW.Motif.0676 4 0.00916562 224.127 0.252155 10 ATCACGTGAC TTTTTTTTCTTGGAA - +2 transfac_pro__M07248-Atf3-Atf6-CrebB-Xbp1 2 0.00916562 224.127 0.252155 10 ATCACGTGAC CGCTGACGTCACCGG - +2 transfac_pro__M01065 2 0.00921071 225.229 0.253249 10 ATCACGTGAC CTCCCACGTCAGCA - +2 cisbp__M3589-esg-nau 1 0.00928433 227.03 0.254538 10 ATCACGTGAC CAACACCTGTCC + +2 transfac_pro__M07659-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 1 0.00928433 227.03 0.254538 10 ATCACGTGAC TGGCACGTGCCA + +2 taipale_cyt_meth__CREB3L4_YGCCACGTGGCA_eDBD-Atf6-Clk-CrebA-Max-Mnt 1 0.00928433 227.03 0.254538 10 ATCACGTGAC TGCCACGTGGCG - +2 neph__UW.Motif.0003-CTCF-SMC3-usp-vtd 3 0.00928433 227.03 0.254538 9 ATCACGTGAC GCCACCTGCTGG - +2 transfac_pro__M01808-Myc -2 0.00929525 227.297 0.254544 6 ATCACGTGAC CATCTG + +2 hocomoco__AHR_HUMAN.H11MO.0.B-ss-tgo 0 0.00946735 231.505 0.258069 9 ATCACGTGAC GTTGCGTGC + +2 transfac_pro__M01689 -1 0.00946735 231.505 0.258069 9 ATCACGTGAC GCATGTGAA + +2 cisbp__M0974 -1 0.00946735 231.505 0.258069 9 ATCACGTGAC CCTGGTTAA - +2 transfac_pro__M07394-esg-sna-wor 1 0.00946735 231.505 0.258069 8 ATCACGTGAC CCGCAGGTG - +2 cisbp__M5100-Atf6-CrebA-Max-Myc -1 0.00960458 234.861 0.26166 7 ATCACGTGAC CCACGTG + +2 neph__UW.Motif.0644 2 0.00962712 235.412 0.261675 10 ATCACGTGAC CAAATTTTTGTTTTCA + +2 taipale_tf_pairs__TFAP4_ETV1_RSCGGAANCAGSTGNN_CAP-crp-Ets96B 0 0.00962712 235.412 0.261675 10 ATCACGTGAC CCCACCTGCTTCCGGC - +2 neph__UW.Motif.0082 8 0.00962712 235.412 0.261675 8 ATCACGTGAC CAGAAATTGCCATCTG - +2 neph__UW.Motif.0226 8 0.00962712 235.412 0.261675 8 ATCACGTGAC GAGTCAGTTTCTGCTG - +2 cisbp__M4030-cnc 3 0.00971072 237.456 0.262207 10 ATCACGTGAC CTTCCAAAATGAC + +2 cisbp__M0217-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.0097429 238.243 0.262207 10 ATCACGTGAC ACCATATGGT + +2 cisbp__M5571-emc-esg-sna-wor 0 0.0097429 238.243 0.262207 10 ATCACGTGAC GACAGGTGTA + +2 cisbp__M5652-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.0097429 238.243 0.262207 10 ATCACGTGAC GCCATATGGT + +2 taipale_cyt_meth__ASCL1_NRCAGCTGYN_eDBD_meth-ac-ase-dimm-l(1)sc-nau-sc 0 0.0097429 238.243 0.262207 10 ATCACGTGAC AGCAGCTGCT + +2 transfac_pro__M07593-Max-Myc 0 0.0097429 238.243 0.262207 10 ATCACGTGAC GCCACGTGGC + +2 taipale__ID4_DBD_NRCACCTGNN_repr-emc-esg-sna-wor 0 0.0097429 238.243 0.262207 10 ATCACGTGAC GACAGGTGTA - +2 taipale__NEUROD2_full_NNCATATGNN-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.0097429 238.243 0.262207 10 ATCACGTGAC ACCATATGGC - +2 taipale__TCF3_DBD_NNCACCTGNN-ac-da-Hand-sc 0 0.0097429 238.243 0.262207 10 ATCACGTGAC AGCAGGTGTT - +2 cisbp__M0317-CG7786-gt-Pdp1-vri -1 0.0097429 238.243 0.262207 9 ATCACGTGAC TTACGTAATA - +2 tfdimers__MD00403-cnc 8 0.00974671 238.336 0.262207 10 ATCACGTGAC GGGCACAGGCACCGTGACCACAGCGTCCCTCC - +2 tfdimers__MD00122 1 0.00975137 238.45 0.262207 10 ATCACGTGAC TTCTACCTGTTCTGACTTGCCTTTTTT - +2 dbcorrdb__FOSL2__ENCSR000BQO_1__m1-cnc-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 1 0.00978783 239.342 0.26239 10 ATCACGTGAC TAAAGAATGACTCAGCCTTA - +2 dbcorrdb__STAT3__ENCSR000DPB_1__m2-Jra-kay-Myc-nej-Stat92E 0 0.00978783 239.342 0.26239 10 ATCACGTGAC AAAGTATGACTCATCTTTTT - +2 yetfasco__YPR013C_859 0 0.00978783 239.342 0.26239 10 ATCACGTGAC CTAAAGTGATTTACGTTCAA - +2 taipale_cyt_meth__RARA_NRGGTCRTGACCYN_eDBD-EcR-eg-Hr3-Hr78-kni-knrl-usp 1 0.00987585 241.494 0.264062 10 ATCACGTGAC GAGGTCATGACCTT + +2 transfac_pro__M02034-scro 1 0.00987585 241.494 0.264062 10 ATCACGTGAC GAGCACTTGAGAGC + +2 homer__GTCACGCTCNCTGA_PAX5-sv 4 0.00987585 241.494 0.264062 10 ATCACGTGAC TCAGGGAGCGTGAC - +2 idmmpmm__twi-twi 2 0.0099446 243.175 0.265007 10 ATCACGTGAC CCCGCATATGTT + +2 neph__UW.Motif.0016 1 0.0099446 243.175 0.265007 10 ATCACGTGAC TTCCAGCTGCCA + +2 transfac_public__M00277-GATAe-grn-pnr 1 0.0099446 243.175 0.265007 10 ATCACGTGAC CGCCAGGTGCTG + +2 swissregulon__hs__MYOD1.p2-esg-nau-sna-wor 1 0.0099446 243.175 0.265007 10 ATCACGTGAC CACCACCTGCTC - +2 taipale_cyt_meth__CREB3_NGCCACGTGKMN_FL_repr-Atf6-Clk-CrebA-Max-Mnt 1 0.0099446 243.175 0.265007 10 ATCACGTGAC GGACACGTGGCA - +2 hocomoco__ZN134_HUMAN.H11MO.1.C 2 0.00998271 244.107 0.265725 10 ATCACGTGAC CCTTCACCTGATTAGGT + +2 jaspar__MA0958.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-Mnt -1 0.0100241 245.119 0.266083 8 ATCACGTGAC GCACGTGC + +2 taipale_cyt_meth__BSX_NTCGTTAN_eDBD-bsh-Dr -2 0.0100241 245.119 0.266083 8 ATCACGTGAC CTCGTTAA + +2 taipale_cyt_meth__MSX1_NTCGTTAN_FL_meth-bsh-CG34367-Dr-en-exex-ind-inv-lab-unpg -2 0.0100241 245.119 0.266083 8 ATCACGTGAC CTCGTTAA + +2 taipale_cyt_meth__MSX1_NTCGTTAN_eDBD_meth_repr-bsh-btn-Dr-lab -2 0.0100241 245.119 0.266083 8 ATCACGTGAC ATCGTTAT + +2 transfac_pro__M01671 -1 0.0101443 248.059 0.268675 9 ATCACGTGAC GCATGTGAA + +2 cisbp__M6139-ss-tgo 0 0.0101443 248.059 0.268675 9 ATCACGTGAC GTTGCGTGC - +2 taipale_cyt_meth__IRX1_NACAYGNNNNNNCRTGTN_eDBD_repr-ara-caup-mirr 8 0.0102434 250.482 0.271148 10 ATCACGTGAC TACATGTTATTACATGTA + +2 cisbp__M3996-EcR -1 0.0103296 252.59 0.273126 9 ATCACGTGAC TGGCGTGACCTCACTC + +2 transfac_public__M00239-EcR -1 0.0103296 252.59 0.273126 9 ATCACGTGAC TGGCGTGACCTCACTG - +2 elemento__CACGTGG-Max-Myc -1 0.0103696 253.567 0.27403 7 ATCACGTGAC CCACGTG - +2 taipale_cyt_meth__ASCL2_NRCAGCTGYN_eDBD-ac-ase-l(1)sc-nau-sc 0 0.0104288 255.015 0.274074 10 ATCACGTGAC GGCAGCTGCC + +2 cisbp__M1291 0 0.0104288 255.015 0.274074 10 ATCACGTGAC GTGGGGTTAA - +2 cisbp__M0828 -1 0.0104288 255.015 0.274074 9 ATCACGTGAC ACATGTCAAT + +2 cisbp__M0271-CrebB -1 0.0104288 255.015 0.274074 9 ATCACGTGAC TTACGTCAGC - +2 cisbp__M1889-Max-Myc -1 0.0104288 255.015 0.274074 9 ATCACGTGAC CCATGTGCTT - +2 transfac_pro__M07217-Max-Myc -1 0.0104288 255.015 0.274074 9 ATCACGTGAC CCATGTGCTT - +2 dbcorrdb__EP300__ENCSR000BPW_1__m1-cnc-ewg-Jra-kay-maf-S-Mef2-mor-Myc-nej-Stat92E-tj 0 0.0105199 257.243 0.274648 10 ATCACGTGAC AAATAATGACTCATCCTTTA + +2 dbcorrdb__MEF2A__ENCSR000BNV_1__m2-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Stat92E 0 0.0105199 257.243 0.274648 10 ATCACGTGAC GAAAGATGACTCATCGCTTA + +2 dbcorrdb__RFX5__ENCSR000EFD_1__m2 3 0.0105199 257.243 0.274648 10 ATCACGTGAC GTGCCCCCAGGATTAGTGAG + +2 transfac_pro__M03810-EcR-usp 7 0.0105199 257.243 0.274648 10 ATCACGTGAC AATTGAACTTTCATGACCTC + +2 dbcorrdb__MYC__ENCSR000DLI_1__m1-Myc 3 0.0105199 257.243 0.274648 10 ATCACGTGAC CGGGTCGCGTGGCTGGGGAG - +2 dbcorrdb__SIN3A__ENCSR000BOW_1__m3-Sin3A-Usf 1 0.0105199 257.243 0.274648 10 ATCACGTGAC CGACACGCAAGCGCCGCGGG - +2 dbcorrdb__SMARCC2__ENCSR000EDL_1__m4-mor 1 0.0105199 257.243 0.274648 10 ATCACGTGAC GATGGGATGACGCAAGGCGT - +2 hocomoco__ZN554_HUMAN.H11MO.0.C-Kr 5 0.0105199 257.243 0.274648 10 ATCACGTGAC AGCACCCCACATGGCTCAGC - +2 tfdimers__MD00033-CrebB-pho-phol 0 0.0105284 257.452 0.27472 10 ATCACGTGAC ACAAGCTGACAGATGGCAGCTG - +2 neph__UW.Motif.0112 7 0.0105436 257.822 0.274925 8 ATCACGTGAC CAGAAATATCATCTG - +2 transfac_pro__M00327-gsb-gsb-n-prd 2 0.0105536 258.068 0.274925 10 ATCACGTGAC AAATTTCGTCACGGTTGAGGT + +2 tfdimers__MD00218-CrebB-Eip74EF 0 0.0105536 258.068 0.274925 10 ATCACGTGAC AGAAAGTGACAGGAAGCGAAA - +2 transfac_pro__M01154-Clk-cyc-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-tgo-Usf 1 0.010647 260.351 0.276601 10 ATCACGTGAC GACCACGTGGTC + +2 cisbp__M3516-GATAe-grn-pnr 1 0.010647 260.351 0.276601 10 ATCACGTGAC CGCCAGGTGCAG - +2 taipale_cyt_meth__CREB3_NGCCACGTGKMN_FL_meth-Atf6-Clk-CrebA 1 0.010647 260.351 0.276601 10 ATCACGTGAC TGCCACGTGGCA - +2 taipale_tf_pairs__ETV5_TCF3_CASSTGNRNNGGAAGNN_CAP-Ets96B 9 0.0107136 261.98 0.278179 8 ATCACGTGAC CACTTCCGCCCCACCTG - +2 stark__WCACGTGC -1 0.0107614 263.149 0.278812 8 ATCACGTGAC GCACGTGA - +2 transfac_pro__M01054-E(spl)m3-HLH-E(spl)mdelta-HLH -1 0.0107614 263.149 0.278812 8 ATCACGTGAC GCACGTGC - +2 cisbp__M5115-CG12605-CG8319-da-Kah-net-scrt 0 0.0108649 265.68 0.280426 9 ATCACGTGAC ACCACCTGT + +2 flyfactorsurvey__net_da_SANGER_10_FBgn0000413-CG8319-CG12605-Kah-da-net-scrt 0 0.0108649 265.68 0.280426 9 ATCACGTGAC ACCACCTGT + +2 cisbp__M2126 -1 0.0108649 265.68 0.280426 9 ATCACGTGAC GCATGTGAA - +2 predrem__nrMotif1793 -1 0.0108649 265.68 0.280426 9 ATCACGTGAC CCTCATGAA - +2 transfac_pro__M07807-lbl -1 0.0108649 265.68 0.280426 9 ATCACGTGAC CCTCGTTAT - +2 tfdimers__MD00363 2 0.0110399 269.959 0.284788 10 ATCACGTGAC TGGAGCAGTGACAGATGGAAAAAGATAA + +2 transfac_pro__M03128-ac-amos-ase-dimm-hth-l(1)sc-sc 3 0.0110779 270.889 0.285304 10 ATCACGTGAC TTTAACAGCTGTTACA + +2 taipale_tf_pairs__ERF_FIGLA_RSCGGAANCASCTGNN_CAP_repr-Ets21C 0 0.0110779 270.889 0.285304 10 ATCACGTGAC ACCAGGTGTTTCCGGT - +2 taipale_tf_pairs__ETV2_FIGLA_NNCGGAANCAGGTGNN_CAP-pnt 0 0.0110779 270.889 0.285304 10 ATCACGTGAC ACCACCTGTTTCCGGT - +2 jaspar__MA0623.1-Fer3-HLH54F-Oli-amos-ato-da-dimm-tap-twi 0 0.0111581 272.849 0.285362 10 ATCACGTGAC ACCATATGGT + +2 transfac_pro__M00946-SREBP-Usf 0 0.0111581 272.849 0.285362 10 ATCACGTGAC GTGACGTGAC + +2 transfac_pro__M07580 0 0.0111581 272.849 0.285362 10 ATCACGTGAC AACACGTAAT + +2 transfac_pro__M08927-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 0 0.0111581 272.849 0.285362 10 ATCACGTGAC ATGACGTCAT + +2 taipale_cyt_meth__SREBF2_ATCACGCCAY_eDBD-SREBP 0 0.0111581 272.849 0.285362 10 ATCACGTGAC GTGGCGTGAT - +2 homer__TBGCACGCAA_Arnt_Ahr-ss-tgo -1 0.0111581 272.849 0.285362 9 ATCACGTGAC TTGCGTGCCA - +2 dbcorrdb__eGFP-JUNB__ENCSR000DJY_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 0 0.0113008 276.339 0.288083 10 ATCACGTGAC AAAGGATGACTCATCCCTTT + +2 dbcorrdb__CREB1__ENCSR000BRB_1__m1-Brf-brm-CrebB-CTCF-E2f1-ERR-E(z)-HDAC1-Jra-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Snr1-SREBP-Taf1-tna-Usf-vtd 7 0.0113008 276.339 0.288083 10 ATCACGTGAC CGGCGCCCGGCGGTGACGCC - +2 dbcorrdb__GTF2F1__ENCSR000EBP_1__m2-TfIIFalpha 4 0.0113008 276.339 0.288083 10 ATCACGTGAC GCGGAACGCGTTACGAACAC - +2 neph__UW.Motif.0623 5 0.0113375 277.236 0.288864 9 ATCACGTGAC AAACTGATATGTGA + +2 taipale_cyt_meth__CREB3_NGCCACGTCAYN_FL-Atf6-CrebA-Xbp1 1 0.0113938 278.614 0.289369 10 ATCACGTGAC TGCCACGTCACC + +2 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_eDBD_meth-achi-amos-Fer1-Fer3-HLH54F-hth-nau-vis 1 0.0113938 278.614 0.289369 10 ATCACGTGAC CGACAGCTGTTA + +2 homer__RACAGCTGTTBH_HLH-1-HLH54F-ac-amos-ase-dimm-l(1)sc-nau-sage-sc 2 0.0113938 278.614 0.289369 10 ATCACGTGAC ACAACAGCTGTT - +2 taipale_cyt_meth__MYF6_CGTCANNTGTYN_eDBD_meth-Fer1-nau 1 0.0113938 278.614 0.289369 10 ATCACGTGAC CAACAGCTGACG - +2 taipale_cyt_meth__NKX3-1_NTCGTTAN_eDBD_meth-bap-bsh-Dr-ind-Lim1-unpg -2 0.0115476 282.374 0.292495 8 ATCACGTGAC CTCGTTAA + +2 taipale_cyt_meth__NKX3-2_NTCGTTAN_eDBD_meth-bap-bsh-Dr-ind-unpg -2 0.0115476 282.374 0.292495 8 ATCACGTGAC CTCGTTAA + +2 taipale_cyt_meth__PRRX2_NTCGTTAN_eDBD_repr-OdsH-repo-unc-4 -2 0.0115476 282.374 0.292495 8 ATCACGTGAC AGCGTTAA + +2 cisbp__M0614 0 0.0115476 282.374 0.292495 8 ATCACGTGAC ATTACGCG - +2 cisbp__M2127 -1 0.0116316 284.428 0.293684 9 ATCACGTGAC GCATGTGAA + +2 jaspar__MA0321.1 -1 0.0116316 284.428 0.293684 9 ATCACGTGAC GCATGTGAA + +2 predrem__nrMotif1415 -2 0.0116316 284.428 0.293684 8 ATCACGTGAC CTTGTGAAA + +2 taipale_cyt_meth__ATOH7_ANCATATGNY_eDBD-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.0119333 291.804 0.298137 10 ATCACGTGAC AACATATGTC + +2 swissregulon__sacCer__PUT3 0 0.0119333 291.804 0.298137 10 ATCACGTGAC TTCCCGGGAT - +2 taipale_cyt_meth__NKX2-3_NCCACTTRAN_eDBD-bap-scro-vnd 0 0.0119333 291.804 0.298137 10 ATCACGTGAC GTCAAGTGGT - +2 cisbp__M1217-achi-hth-vis -1 0.0119333 291.804 0.298137 9 ATCACGTGAC TGCTGTCAAA + +2 transfac_pro__M07430-esg-sna-wor -1 0.0119333 291.804 0.298137 9 ATCACGTGAC CCACCTGCCA + +2 cisbp__M0294-CrebB -1 0.0119333 291.804 0.298137 9 ATCACGTGAC TTACGTCATC - +2 cisbp__M0872-achi-esg-sna-vis-wor -1 0.0119333 291.804 0.298137 9 ATCACGTGAC ACCTGTCAAT - +2 tfdimers__MD00090-foxo-Jra-slp2 1 0.0119529 292.283 0.29847 10 ATCACGTGAC AAATAACTGAGTAAACAAAAAAAA + +2 yetfasco__YCR039C_1364 -3 0.0119743 292.808 0.298813 6 ATCACGTGAC ACATGT - +2 cisbp__M4734-amos-da 1 0.0119917 293.233 0.298813 10 ATCACGTGAC CGGCAGATGGT - +2 cisbp__M0332-Jra -1 0.0119917 293.233 0.298813 9 ATCACGTGAC TGACGTCATTC - +2 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNNNNNNTGCGGG_CAP_repr-gcm-gcm2 11 0.0120091 293.659 0.298934 8 ATCACGTGAC CCCGCATCCCCACCACCTG - +2 taipale_cyt_meth__NANOG_TTAACGA_eDBD_meth-Lim1-Lim3 -3 0.0120666 295.064 0.299815 7 ATCACGTGAC TCGTTAA - +2 transfac_pro__M09530-Atf6-CrebA-Xbp1 1 0.0121053 296.011 0.299815 10 ATCACGTGAC TGCCACGTCATCATT - +2 dbcorrdb__JUND__ENCSR000EBZ_1__m1-CrebB-Jra-kay-mor-Snr1 5 0.0121335 296.699 0.299815 10 ATCACGTGAC TGCCGGGGGGATGACTCAAC + +2 dbcorrdb__RXRA__ENCSR000BJW_1__m1-EcR-usp 3 0.0121335 296.699 0.299815 10 ATCACGTGAC ACCCCCCCGTGACCTCTGCC + +2 dbcorrdb__ZBTB33__ENCSR000BNY_1__m1-Chd1-CoRest 2 0.0121335 296.699 0.299815 10 ATCACGTGAC AGATCTCGCGAGACCCGGCG + +2 dbcorrdb__eGFP-FOS__ENCSR000DKB_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Stat92E 0 0.0121335 296.699 0.299815 10 ATCACGTGAC GCGGGATGACTCATCCCTGT + +2 dbcorrdb__EP300__ENCSR000DZD_1__m3-ebi-foxo-Jra-kay-nej-NFAT-Stat92E 5 0.0121335 296.699 0.299815 10 ATCACGTGAC CAATCTCGATATGACTCATA - +2 dbcorrdb__NR2F2__ENCSR000BRS_1__m2-EcR-eg-ERR-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 2 0.0121335 296.699 0.299815 10 ATCACGTGAC TTGCCCTCTGACCTTTGACC - +2 transfac_pro__M01539 0 0.0121335 296.699 0.299815 10 ATCACGTGAC CTAAAGTGATTTACGTTCAA - +2 transfac_pro__M01549-achi-hth-vis 0 0.0121335 296.699 0.299815 10 ATCACGTGAC AAAATGTGACACATATGCAA - +2 flyfactorsurvey__prd_SOLEXA_5_FBgn0003145-Poxn-gsb-prd 1 0.012139 296.835 0.299815 10 ATCACGTGAC TGGAGCGTGACGGA - +2 taipale_tf_pairs__TEAD4_MAX_RGAATGYNNACGTG_CAP_repr-Max-sd 6 0.012139 296.835 0.299815 8 ATCACGTGAC GGAATGCGCACGTG + +2 neph__UW.Motif.0014 6 0.012139 296.835 0.299815 8 ATCACGTGAC CATGAATACACTTG - +2 neph__UW.Motif.0681 6 0.012139 296.835 0.299815 8 ATCACGTGAC GTTTTTCTCTTCTG - +2 jaspar__MA0278.1-Myb-Pbp95 0 0.0121815 297.874 0.299926 10 ATCACGTGAC TTGACTTGACTCTGGCTGTGC - +2 cisbp__M6358 1 0.0121876 298.024 0.299926 10 ATCACGTGAC GGCCATCTGCCG - + +# Tomtom (Motif Comparison Tool): Version 5.5.1 compiled on Mar 14 2023 at 10:55:24 +# The format of this file is described at https://meme-suite.org/meme/doc/tomtom-output-format.html. +# tomtom -thresh 0.3 -oc ./motif-2 motif-2.meme ./motif2gene_names.all.meme diff --git a/the_code/Human/data/tomtom/motif-2/tomtom.xml b/the_code/Human/data/tomtom/motif-2/tomtom.xml new file mode 100644 index 0000000000000000000000000000000000000000..d4776f763596c0e7a9b90f71ce320a6ea59e0ec9 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-2/tomtom.xml @@ -0,0 +1,18727 @@ + + + + tomtom -thresh 0.3 -oc ./motif-2 motif-2.meme ./motif2gene_names.all.meme + + 0.3 + + + + + + + + + + + + + + + + + + both + + i28g27 + Tue Oct 10 04:20:59 2023 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/the_code/Human/data/tomtom/motif-3.meme b/the_code/Human/data/tomtom/motif-3.meme new file mode 100644 index 0000000000000000000000000000000000000000..d416a33f6828f52b58b8145d31d29b546a2eb867 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-3.meme @@ -0,0 +1,21 @@ +MEME version 4 + +ALPHABET= ACGT + +strands: + - + +Background letter frequencies (from unknown source): +A 0.250 C 0.250 G 0.250 T 0.250 + +MOTIF 3 GCCBNRRGS + +letter-probability matrix: alength= 4 w= 9 nsites= 1 E= 0e+0 +0.009615 0.033654 0.947115 0.009615 +0.000000 0.985577 0.014423 0.000000 +0.000000 0.961538 0.000000 0.038462 +0.038462 0.355769 0.158654 0.447115 +0.177885 0.254808 0.307692 0.259615 +0.447115 0.100962 0.331731 0.120192 +0.298077 0.105769 0.567308 0.028846 +0.038462 0.014423 0.942308 0.004808 +0.038462 0.418269 0.461538 0.081731 diff --git a/the_code/Human/data/tomtom/motif-3/tomtom.html b/the_code/Human/data/tomtom/motif-3/tomtom.html new file mode 100644 index 0000000000000000000000000000000000000000..3dbeb40a7a2414f77282dd7b5abb3abd55de34d3 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-3/tomtom.html @@ -0,0 +1,10793 @@ + + + + + Tomtom Results + + + + + + + + + + + + + + + + +
+ +
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+

A link to more information about the query motif.

+
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+ +
+ +
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+ +
+

The motif preview. On supporting browsers this will display as a motif + logo, otherwise the consensus sequence will be displayed.

+
[close ]
+
+ +
+

The number motifs in the target database with a significant match to the query motif.

+
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+ +
+

Links to the (up to) twenty target motifs with the most significant matches to the query motif.

+
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+ +
+ +
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+ +
+

The number of motifs read from the motif database minus the number that + had to be discarded due to conflicting IDs.

+
[close ]
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+ +
+

The number of motifs in this database that have a significant match to at least one of the query motifs.

+
[close ]
+
+ +
+

The summary gives information about the target motif. Mouse over each + row to show further help buttons for each specific title.

+
[close ]
+
+ +
+

The ID of the target motif with the optional alternate ID shown in parentheses.

+
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+ +
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The image shows the optimal alignment of the two motifs. The sequence logo + of the target motif is shown aligned above the logo for the query motif.

+
[close ]
+
+ +
+

By clicking the link "Create custom LOGO ↧" a form to make custom logos + will be displayed. The download button can then be clicked to generate a motif + matching the selected specifications.

+
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+
+ +
+

Two image formats, png and eps, are available. The pixel based portable + network graphic (png) format is commonly used on the Internet and the + Encapsulated PostScript (eps) format is more suitable for publications + that might require scaling.

+
[close ]
+
+ +
+

Toggle error bars indicating the confidence of a motif based on the + number of sites used in its creation.

+
[close ]
+
+ +
+

Toggle adding pseudocounts for Small Sample + Correction.

+
[close ]
+
+ +
+

Toggle a full reverse complement of the alignment.

+
[close ]
+
+ +
+

Specify the width of the generated logo.

+
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+
+ +
+

Specify the height of the generated logo.

+
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+
+ +
+ +
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+
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+
+ + + + +
+ +
+

+ For further information on how to interpret these results please access + https://meme-suite.org/meme/doc/tomtom-output-format.html.
+ To get a copy of the MEME software please access + https://meme-suite.org. +

+

+
+ Query Motifs  |  Target Databases  |  Matches  |  Settings  |  Program information  |  Results in TSV Format  +   |  Results in XML Format + +
+ +
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Query Motifs

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Summary
Optimal Alignment
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Name
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p-value
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Settings

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+ + + + + + + + + + + + + +
Strand Handling + Reverse complements are not possible so motifs are compared as they are provided. + Motifs are compared as they are provided. + Motifs may be reverse complemented before comparison to find a better match. +
Distance Measure + Average log-likelihood ratio + Euclidean distance + Kullback-Leibler divergence + Pearson correlation coefficient + Sandelin-Wasserman function + Bayesian Likelihood 2-Components score (from 1-component Dirichlet prior) + Bayesian Likelihood 2-Components score (from 5-component Dirichlet prior) + Log likelihood Ratio score (from 1-component Dirichlet prior) + Log likelihood Ratio score (from 5-component Dirichlet prior) +
Match Threshold + Matches must have a E-valueq-value of or smaller. +
+ +
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Tomtom version
+ (Release date: ) +
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Result calculation took seconds
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+ + + diff --git a/the_code/Human/data/tomtom/motif-3/tomtom.tsv b/the_code/Human/data/tomtom/motif-3/tomtom.tsv new file mode 100644 index 0000000000000000000000000000000000000000..057fd8c197b8cf90133ef16f131ad1ef2524de5f --- /dev/null +++ b/the_code/Human/data/tomtom/motif-3/tomtom.tsv @@ -0,0 +1,181 @@ +Query_ID Target_ID Optimal_offset p-value E-value q-value Overlap Query_consensus Target_consensus Orientation +3 cisbp__M0082-TfAP-2 1 9.57139e-11 2.34049e-06 3.35423e-06 9 GCCTGAGGG CGCCTCAGGG + +3 transfac_public__M00469-TfAP-2 0 1.45401e-10 3.55549e-06 3.35423e-06 9 GCCTGAGGG GCCCGGGGG + +3 cisbp__M2934-TfAP-2 0 2.06381e-10 5.04663e-06 3.35423e-06 9 GCCTGAGGG GCCCGGGGG - +3 transfac_public__M00470-TfAP-2 0 2.90177e-10 7.0957e-06 3.5371e-06 9 GCCTGAGGG GCCCGGGGG + +3 cisbp__M2939-TfAP-2 0 4.04298e-10 9.88631e-06 3.94254e-06 9 GCCTGAGGG GCCCGGGGG - +3 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 14 9.49026e-08 0.00232065 0.000753947 9 GCCTGAGGG GATCGATCTGCTTGGCCTGAGGCGA + +3 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 14 1.08242e-07 0.00264683 0.000753947 9 GCCTGAGGG GGCACGTGCCCATGGCCTCAGGC + +3 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNCACGTGN_CAP_repr-Max-TfAP-2 10 1.53918e-07 0.00376376 0.000833549 9 GCCTGAGGG CCACGTGATCGCCTCAGGCCA - +3 swissregulon__hs__TFAP2_A_C_.p2-TfAP-2 0 1.55957e-07 0.00381362 0.000833549 9 GCCTGAGGG GCCCCGGGC + +3 transfac_pro__M08867-TfAP-2 0 1.70957e-07 0.00418041 0.000833549 9 GCCTGAGGG GCCTGGGGCC + +3 tfdimers__MD00178-TfAP-2 11 2.5556e-07 0.00624922 0.00109944 9 GCCTGAGGG GGGGCCAGCTGGCCCGGGGCCCGCC + +3 tfdimers__MD00333-Pur-alpha-TfAP-2 7 2.70589e-07 0.00661671 0.00109944 9 GCCTGAGGG GCCCCCTGCCTGGGGGCAGGGGGGGG + +3 taipale_cyt_meth__TFAP2C_NGCCYNRGGCN_eDBD_meth-TfAP-2 1 3.10716e-07 0.00759793 0.00116537 9 GCCTGAGGG TGCCTGAGGCA + +3 transfac_pro__M03811-TfAP-2 0 3.67939e-07 0.00899721 0.00124008 9 GCCTGAGGG GCCCGCAGGC + +3 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 0 3.81504e-07 0.00932891 0.00124008 9 GCCTGAGGG GCCTCAGGCGATGCGGCACGTGCC - +3 taipale_cyt_meth__TFAP2B_NGCCNNNGGCN_eDBD-TfAP-2 1 4.54941e-07 0.0111247 0.00130482 9 GCCTGAGGG TGCCTCAGGCA - +3 taipale_cyt_meth__TFAP2E_TGCCCNNNGGCN_FL_repr-TfAP-2 1 5.00709e-07 0.0122438 0.00133101 9 GCCTGAGGG CGCCTGAGGGCA - +3 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNYMATTA_CAP_repr-TfAP-2 1 5.1867e-07 0.012683 0.00133101 9 GCCTGAGGG CGCCTGAGGGCATGCGTAATTA + +3 transfac_pro__M07628-TfAP-2 1 6.04433e-07 0.0147802 0.00147354 9 GCCTGAGGG TGCCCTAGGGCA + +3 transfac_pro__M01857-TfAP-2 1 7.8444e-07 0.0191819 0.00157273 9 GCCTGAGGG AGCCCCCGGCC + +3 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNNTAATKR_CAP_repr-TfAP-2 1 8.46789e-07 0.0207065 0.00157273 9 GCCTGAGGG GGCCTGAGGGCACGCGGTAATTG + +3 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 2 8.51794e-07 0.0208289 0.00157273 9 GCCTGAGGG TGGCCTCAGGCGATGCGGGCCGAGGCACGTG + +3 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 20 8.51794e-07 0.0208289 0.00157273 9 GCCTGAGGG GCACGTGCTCCCCCCATATCGCCTGAGGCCA - +3 cisbp__M5915-TfAP-2 1 8.71173e-07 0.0213028 0.00157273 9 GCCTGAGGG TGCCCTGGGGCA + +3 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNCACGTGN_CAP_repr-Max-TfAP-2 2 9.69079e-07 0.0236969 0.00158435 9 GCCTGAGGG TGGCCTCAGGCCAAACACGTGC + +3 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 12 1.03819e-06 0.0253868 0.00158435 9 GCCTGAGGG AATCGATACTTAGCCTGAGGCGG + +3 cisbp__M5911-TfAP-2 1 1.04042e-06 0.0254413 0.00158435 9 GCCTGAGGG TGCCCGGGGGCA + +3 taipale__TFAP2A_DBD_NGCCNNNNGGCN-TfAP-2 1 1.04042e-06 0.0254413 0.00158435 9 GCCTGAGGG TGCCCGGGGGCA - +3 tfdimers__MD00477-TfAP-2 13 1.07231e-06 0.0262213 0.00158435 9 GCCTGAGGG CCCCTCCCCATCTGCCTCGGGCTCTCC + +3 taipale__TFAP2B_DBD_NGCCNNNNGGCN-TfAP-2 1 1.46931e-06 0.0359291 0.00196727 9 GCCTGAGGG TGCCCTGGGGCA - +3 taipale__TFAP2C_DBD_NGCCNNNNGGCN-TfAP-2 1 1.46931e-06 0.0359291 0.00196727 9 GCCTGAGGG TGCCCTGGGGCA - +3 taipale__Tcfap2a_DBD_NGCCNNNNGGCN_repr-TfAP-2 1 1.46931e-06 0.0359291 0.00196727 9 GCCTGAGGG TGCCCGGGGGCA - +3 taipale_tf_pairs__TFAP2C_ELK1_NGCCTNNGGSNNCGGAAGYN_CAP_repr-TfAP-2 1 1.49287e-06 0.0365051 0.00196727 9 GCCTGAGGG TGCCTCGGGCGGCGGAAGTG + +3 cisbp__M6100-TfAP-2 1 1.73786e-06 0.0424958 0.00206668 9 GCCTGAGGG TGCCCGGGGGCA + +3 neph__UW.Motif.0283 1 1.73786e-06 0.0424958 0.00206668 9 GCCTGAGGG GGCCTGGGGGGA + +3 cisbp__M5917-TfAP-2 1 1.73786e-06 0.0424958 0.00206668 9 GCCTGAGGG TGCCCTGGGGCA - +3 taipale_cyt_meth__TFAP2E_TGCCCNNNGGCN_FL_meth-TfAP-2 1 1.73786e-06 0.0424958 0.00206668 9 GCCTGAGGG TGCCTCAGGGCA - +3 transfac_pro__M01045-TfAP-2 3 1.80834e-06 0.0442193 0.00209536 9 GCCTGAGGG ACCGCCTGAGGGGAT + +3 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 15 1.84792e-06 0.0451872 0.00209536 9 GCCTGAGGG TATCGATCGGATGTTGCCTGAGGCGA + +3 cisbp__M5920-TfAP-2 1 2.0493e-06 0.0501114 0.00217215 9 GCCTGAGGG TGCCCTGGGGCA - +3 neph__UW.Motif.0651 4 2.0493e-06 0.0501114 0.00217215 8 GCCTGAGGG AAATGCCTGAGG + +3 transfac_pro__M07348-E(z)-TfAP-2 1 2.13969e-06 0.0523218 0.0021756 9 GCCTGAGGG CGCCTGCGGCC - +3 taipale_tf_pairs__TFAP2C_ETV7_SCCNNNGGSNNNGGAAGNNNTTCCNN_CAP_repr-aop-TfAP-2 0 2.23699e-06 0.0547011 0.0021756 9 GCCTGAGGG GCCCCGGGGCACGGAAGTACTTCCGC + +3 cisbp__M0085-TfAP-2 2 2.32488e-06 0.0568502 0.0021756 8 GCCTGAGGG TCGCCTGAGG + +3 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNNNTAATKR_CAP_repr-TfAP-2 13 2.39833e-06 0.0586464 0.0021756 9 GCCTGAGGG TAATTAGCCCCATGCCCCGGGGCG - +3 cisbp__M5923-TfAP-2 1 2.40951e-06 0.0589198 0.0021756 9 GCCTGAGGG TGCCCCAGGGCA + +3 taipale__TFAP2C_full_NGCCNNNNGGCN-TfAP-2 1 2.40951e-06 0.0589198 0.0021756 9 GCCTGAGGG TGCCCCAGGGCA + +3 taipale_cyt_meth__TFAP2C_NGCCYNMGGCN_eDBD-TfAP-2 1 2.50404e-06 0.0612313 0.00221985 9 GCCTGAGGG TGCCTCGGGCA - +3 cisbp__M0084-TfAP-2 1 3.13968e-06 0.0767746 0.00273364 9 GCCTGAGGG CGCCCGAGGC + +3 transfac_pro__M00915-E(z)-RpII215-TfAP-2-tna 1 5.55883e-06 0.13593 0.00444322 9 GCCTGAGGG GGCCTGGGGGCGG - +3 taipale_cyt_meth__TFAP2B_NGCCNNNGGCN_eDBD_meth-TfAP-2 1 6.10463e-06 0.149276 0.00465075 9 GCCTGAGGG TGCCTCAGGCA - +3 neph__UW.Motif.0321 6 6.63682e-06 0.16229 0.0048298 8 GCCTGAGGG AAAAAAGCCAGATG + +3 taipale_tf_pairs__TFAP2C_DRGX_SCCNNNGGCNNYAATTA_CAP_repr-CG11294-Drgx-TfAP-2 8 7.29931e-06 0.17849 0.00515794 9 GCCTGAGGG TAATTGTTGCCTCAGGG - +3 transfac_pro__M07627-TfAP-2 1 8.06781e-06 0.197282 0.0055404 9 GCCTGAGGG TGCCTCAGGCA - +3 taipale_tf_pairs__TFAP2C_ONECUT2_NATYGATNNNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 2 9.54529e-06 0.233411 0.00637544 9 GCCTGAGGG TCGCCTGAGGCAATGGAACGATCGATA - +3 transfac_pro__M02820-TfAP-2 2 1.18152e-05 0.288916 0.00768108 9 GCCTGAGGG TTGCCCTAGGGCAT + +3 taipale_tf_pairs__TFAP2C_E2F8_NNTCCCGCNNNCCNNNGGC_CAP_repr-TfAP-2 0 1.20267e-05 0.294089 0.00771574 9 GCCTGAGGG GCCTGGGGCGAGCGGGAAA - +3 dbcorrdb__GATA3__ENCSR000BMX_1__m4-GATAe-grn-pnr-TfAP-2 6 1.31047e-05 0.320449 0.00829813 9 GCCTGAGGG TAATTTGCCTGAGGGCATGT - +3 taipale__TFAP2C_DBD_NSCCNNNGGSN-TfAP-2 1 1.37536e-05 0.336316 0.00859735 9 GCCTGAGGG AGCCTCAGGCA + +3 cisbp__M5921-TfAP-2 1 1.56416e-05 0.382483 0.00904028 9 GCCTGAGGG AGCCTGAGGCA - +3 transfac_pro__M02819-TfAP-2 3 1.57524e-05 0.385193 0.00904028 9 GCCTGAGGG ATTCCCTGAGGGGAA + +3 transfac_pro__M02821-TfAP-2 3 1.57524e-05 0.385193 0.00904028 9 GCCTGAGGG ATTGCCTGAGGCGAA + +3 taipale_tf_pairs__TFAP2C_HOXB13_SCCNNNNGGCATNGTWAA_CAP_repr-TfAP-2 0 1.68926e-05 0.413074 0.00938855 9 GCCTGAGGG GCCTGAGGGCATCGTAAA + +3 cisbp__M6143-TfAP-2 0 1.69448e-05 0.414352 0.00938855 9 GCCTGAGGG GCCTGAGGC - +3 cisbp__M5912-TfAP-2 1 1.77571e-05 0.434213 0.00946279 9 GCCTGAGGG CGCCTCAGGCA + +3 taipale_cyt_meth__TFAP2E_NGCCNNNGGCN_FL_repr-TfAP-2 1 1.77571e-05 0.434213 0.00946279 9 GCCTGAGGG CGCCTCAGGCG + +3 transfac_pro__M07349-TfAP-2 5 1.79341e-05 0.438543 0.00946279 9 GCCTGAGGG CATCAGCCTGCAGGCC + +3 taipale__TFAP2A_DBD_NSCCNNNGGSN-TfAP-2 1 2.01238e-05 0.492088 0.0101704 9 GCCTGAGGG CGCCTCAGGCA + +3 transfac_pro__M02925-TfAP-2 2 2.0308e-05 0.496593 0.0101704 9 GCCTGAGGG CCGCCCAAGGGCAG + +3 cisbp__M4525-TfAP-2 1 2.35524e-05 0.575927 0.011042 9 GCCTGAGGG AGCCTCAGGGCATGG + +3 cisbp__M6101-TfAP-2 1 2.57169e-05 0.628856 0.0117187 9 GCCTGAGGG AGCCTGAGGCG - +3 taipale__Tcfap2a_DBD_NSCCNNNGGSN_repr-TfAP-2 1 2.57169e-05 0.628856 0.0117187 9 GCCTGAGGG TGCCTGAGGCG - +3 cisbp__M5925-TfAP-2 1 2.90022e-05 0.70919 0.0128308 9 GCCTGAGGG AGCCTCAGGCA - +3 cisbp__M4524-TfAP-2 3 3.04978e-05 0.745763 0.0128308 9 GCCTGAGGG ACTGCCTCAGGGCAC - +3 factorbook__AP2-TfAP-2 0 3.04978e-05 0.745763 0.0128308 9 GCCTGAGGG GCCTGAGGGCATGGG - +3 neph__UW.Motif.0612 5 3.05147e-05 0.746176 0.0128308 9 GCCTGAGGG TTCCTCCCTCTGGCCT - +3 transfac_pro__M00800-TfAP-2 6 3.05147e-05 0.746176 0.0128308 9 GCCTGAGGG CCCTCCGCCTGGGGGC - +3 dbcorrdb__TFAP2C__ENCSR000EVO_1__m1-GATAe-grn-pnr-TfAP-2 7 3.05258e-05 0.746448 0.0128308 9 GCCTGAGGG CCACATTGCCTCAGGGCATG + +3 cisbp__M0083-TfAP-2 2 3.26511e-05 0.798417 0.0136068 8 GCCTGAGGG TCGCCTCAGG + +3 cisbp__M6145-TfAP-2 0 3.38813e-05 0.8285 0.0137665 9 GCCTGAGGG GCCTGGGGC + +3 taipale__TFAP2C_full_NSCCNNNGGSN-TfAP-2 1 3.67169e-05 0.897838 0.014674 9 GCCTGAGGG AGCCTCAGGCA + +3 cisbp__M5914-TfAP-2 1 3.67169e-05 0.897838 0.014674 9 GCCTGAGGG TGCCTCAGGCT - +3 neph__UW.Motif.0680 4 3.92072e-05 0.958733 0.0155419 9 GCCTGAGGG CAAGGCCAGGAGGCA + +3 transfac_pro__M02924-TfAP-2 3 4.43403e-05 1.08425 0.0169775 9 GCCTGAGGG ATTGCCTCAGGCAAT + +3 taipale_cyt_meth__TFAP2A_NSCCYNRGGSN_FL-TfAP-2 1 4.62146e-05 1.13009 0.0174676 9 GCCTGAGGG TGCCTCAGGCA + +3 transfac_pro__M02822-GATAe-grn-pnr-TfAP-2 3 5.00631e-05 1.22419 0.0186504 9 GCCTGAGGG ATTGCCTGAGGCGAT + +3 cisbp__M5918-TfAP-2 1 5.17412e-05 1.26523 0.0186504 9 GCCTGAGGG TGCCTGAGGCT - +3 taipale__TFAP2B_DBD_NSCCNNNGGSN-TfAP-2 1 5.17412e-05 1.26523 0.0186504 9 GCCTGAGGG TGCCTGAGGCT - +3 neph__UW.Motif.0131 2 5.20214e-05 1.27208 0.0186504 9 GCCTGAGGG AGGCCCCGCGGCC + +3 tfdimers__MD00339-TfAP-2 7 5.79738e-05 1.41763 0.0203358 9 GCCTGAGGG TATTTTTGCCTTATGCAATTTTTTTTTTTTA + +3 cisbp__M1838-GATAe-grn-pnr-TfAP-2 4 6.3519e-05 1.55323 0.0218289 9 GCCTGAGGG CATTGCCTCAGGGCA + +3 transfac_pro__M07231-GATAe-grn-pnr-TfAP-2 4 6.3519e-05 1.55323 0.0218289 9 GCCTGAGGG CATTGCCTCAGGGCA + +3 neph__UW.Motif.0249 1 7.13857e-05 1.7456 0.0243399 9 GCCTGAGGG AGCAGCTGGCAGCCT + +3 taipale_cyt_meth__TFAP2A_NSCCYNRGGSN_FL_meth-TfAP-2 1 7.20483e-05 1.7618 0.0243952 9 GCCTGAGGG TGCCTCAGGCA + +3 homer__SCCTSAGGSCAW_AP-2gamma-GATAe-TfAP-2-grn-pnr 0 8.33799e-05 2.03889 0.0276559 9 GCCTGAGGG GCCTCAGGGCAT + +3 neph__UW.Motif.0202 1 8.6904e-05 2.12506 0.0284379 9 GCCTGAGGG TGCCAGTACCCACA + +3 neph__UW.Motif.0416 2 8.97743e-05 2.19525 0.0291813 9 GCCTGAGGG AAGCCATAATAATTT + +3 cisbp__M5919-TfAP-2 1 9.15907e-05 2.23967 0.0295746 9 GCCTGAGGG TGCCCTCAGGGCA - +3 cisbp__M5913-TfAP-2 1 0.000102158 2.49807 0.0321355 9 GCCTGAGGG TGCCCCGGGGGCA - +3 taipale__TFAP2A_DBD_NSCCNNNNNGGSN-TfAP-2 1 0.000102158 2.49807 0.0321355 9 GCCTGAGGG TGCCCCGGGGGCA - +3 taipale__TFAP2B_DBD_NSCCNNNNNGGSN-TfAP-2 1 0.000102158 2.49807 0.0321355 9 GCCTGAGGG TGCCCTCAGGGCA - +3 tfdimers__MD00038-TfAP-2 7 0.000117867 2.88221 0.035475 9 GCCTGAGGG GCCCATTGCCTGAGGCAATGGGC + +3 hocomoco__AP2A_MOUSE.H11MO.0.A-GATAe-TfAP-2-grn-pnr 0 0.000127739 3.12359 0.0382101 9 GCCTGAGGG GCCTCAGGCCAT - +3 neph__UW.Motif.0294 7 0.000142197 3.47713 0.0420194 9 GCCTGAGGG AGAGACAGCCTCCGGG + +3 taipale_cyt_meth__TFAP2E_NGCCNNNGGCN_FL_meth-TfAP-2 1 0.000149772 3.66238 0.0436677 9 GCCTGAGGG TGCCTCAGGCA + +3 dbcorrdb__EP300__ENCSR000BLM_1__m2-nej 5 0.000150462 3.67924 0.0436677 9 GCCTGAGGG TACATGCCTGAGGGGTTAGT + +3 taipale__TFAP2C_full_NGCCNNNNNGGCN-TfAP-2 1 0.000156238 3.82049 0.0448107 9 GCCTGAGGG TGCCCTGAGGGCA + +3 cisbp__M5924-TfAP-2 1 0.000156238 3.82049 0.0448107 9 GCCTGAGGG TGCCCTGAGGGCA - +3 tfdimers__MD00275-nub-pdm2-TfAP-2 6 0.000158434 3.87419 0.0451749 9 GCCTGAGGG AAAATAGCCTCAGGCAAATTAAAAAA - +3 homer__ATGCCCTGAGGC_AP-2alpha-GATAe-TfAP-2-grn-pnr 0 0.000173865 4.25152 0.0492864 9 GCCTGAGGG GCCTCAGGGCAT - +3 hocomoco__AP2C_MOUSE.H11MO.0.A-TfAP-2 2 0.000191929 4.69324 0.053882 9 GCCTGAGGG TGGCCTGAGGCCA - +3 neph__UW.Motif.0205 2 0.000226807 5.54612 0.0621271 9 GCCTGAGGG AAGCCTGTGTTCTG + +3 tfdimers__MD00591-TfAP-2 15 0.000236084 5.77297 0.064307 9 GCCTGAGGG ATTTAGAAAACAAAAGCCTTTTAGT + +3 swissregulon__hs__TFAP2B.p2-Brf-CTCF-E2f1-E(z)-HDAC1-Hcf-Nelf-E-RpII215-SREBP-TfAP-2-tna 6 0.000241731 5.91106 0.0654794 9 GCCTGAGGG CCCGCCGCCCGCGGCC - +3 cisbp__M4341 12 0.000252371 6.17123 0.0672408 9 GCCTGAGGG GGGGGTATCTCCGCCGGTGTG + +3 transfac_pro__M01518 12 0.000252371 6.17123 0.0672408 9 GCCTGAGGG GGGGGTATCTCCGCCGCTGTG + +3 transfac_pro__M07629-TfAP-2 1 0.000315402 7.71252 0.0817995 9 GCCTGAGGG TGCCCTCAGGGCA - +3 tfdimers__MD00112-CG7786-gt-Pdp1-TfAP-2 13 0.000322564 7.88766 0.0832144 9 GCCTGAGGG TTTTTTTGCATAAGCCTTTTTTT + +3 cisbp__M6144-TfAP-2 0 0.000342055 8.36427 0.0877546 9 GCCTGAGGG GCCCGGGGGC - +3 jaspar__MA0872.1-TfAP-2 1 0.000347363 8.49406 0.0877546 9 GCCTGAGGG TGCCCTGAGGGCA + +3 cisbp__M5916-TfAP-2 1 0.000347363 8.49406 0.0877546 9 GCCTGAGGG TGCCCTGAGGGCA - +3 neph__UW.Motif.0151 5 0.000347363 8.49406 0.0877546 8 GCCTGAGGG GGAAAGCCATCTG - +3 tfdimers__MD00445-TfAP-2 12 0.000372187 9.10109 0.0935413 9 GCCTGAGGG TTTAGGGGATTAGCCTTTGTTC + +3 taipale_tf_pairs__E2F1_HES7_SRCRCGYGSYNNNNSGCGCSN_CAP_repr-E2f1 4 0.000384204 9.39494 0.0955762 9 GCCTGAGGG GGGCGCCTTGCGGCACGTGCC - +3 cisbp__M6102-TfAP-2 1 0.000420216 10.2755 0.102444 9 GCCTGAGGG TGCCCTGAGGGCA + +3 taipale__Tcfap2a_DBD_NSCCNNNNNGGSN_repr-TfAP-2 1 0.000420216 10.2755 0.102444 9 GCCTGAGGG TGCCCTGAGGGCA + +3 tfdimers__MD00523-TfAP-2 7 0.000428001 10.4659 0.103823 9 GCCTGAGGG GGCCCATGCCTCTAGGGAAATGGGGC + +3 hocomoco__AP2B_HUMAN.H11MO.0.B-TfAP-2 0 0.000449041 10.9804 0.108203 9 GCCTGAGGG GCCCGGGGGC + +3 taipale__TFAP2C_DBD_NSCCNNNNNGGSN-TfAP-2 1 0.000461594 11.2874 0.108203 9 GCCTGAGGG TGCCCTGAGGGCA + +3 cisbp__M5922-TfAP-2 1 0.000461594 11.2874 0.108203 9 GCCTGAGGG TGCCCTGAGGGCA - +3 tfdimers__MD00444-Sirt6-TfAP-2 11 0.000470921 11.5154 0.109862 9 GCCTGAGGG AAAACAGATAAGCCTTTAATA + +3 neph__UW.Motif.0048 1 0.00053649 13.1188 0.123387 9 GCCTGAGGG TGCCCTGTGG - +3 hocomoco__AP2A_HUMAN.H11MO.0.A-GATAe-TfAP-2-grn-pnr 3 0.000570679 13.9548 0.130024 9 GCCTGAGGG ATGGCCTCAGGGCAT - +3 hocomoco__NR1H4_HUMAN.H11MO.0.B-EcR-svp-usp 10 0.000595751 14.5679 0.134257 9 GCCTGAGGG GGGGTCAATGACCCCGAGG + +3 jaspar__MA0146.2 3 0.000596985 14.5981 0.134257 9 GCCTGAGGG CAGGCCTCGGCCCC - +3 tfdimers__MD00147-TfAP-2 13 0.000597578 14.6126 0.134257 9 GCCTGAGGG CCCCCCACTTCCTGCCTCCCCCC - +3 neph__UW.Motif.0171 0 0.000600274 14.6785 0.134257 9 GCCTGAGGG GCCTTGGATTTT - +3 neph__UW.Motif.0290 0 0.000608823 14.8876 0.134321 9 GCCTGAGGG GCCAGGGAGCTCA + +3 transfac_pro__M01593-brm-CTCF-ERR-E(z)-RpII215-tna-vtd 6 0.000645902 15.7942 0.140593 9 GCCTGAGGG GGCCAGGCCGCGGCGC + +3 cisbp__M1963 3 0.000654502 16.0045 0.140998 9 GCCTGAGGG CAGGCCTCGGCCGC - +3 hocomoco__AP2C_HUMAN.H11MO.0.A-GATAe-TfAP-2-grn-pnr 2 0.000654502 16.0045 0.140998 9 GCCTGAGGG TGGCCTCAGGGCAT - +3 transfac_public__M00014-arg-HDAC1-HDAC3 8 0.00065644 16.0519 0.140998 9 GCCTGAGGG TACTAGCCGCCGAAGGC + +3 tfdimers__MD00446-TfAP-2 11 0.000698939 17.0912 0.148815 9 GCCTGAGGG TATTTCATTAAGCCTGTTTTT + +3 dbcorrdb__EP300__ENCSR000BLM_1__m4-nej 0 0.000712848 17.4313 0.150463 9 GCCTGAGGG GCCTCATGCCAAACTAAATA - +3 dbcorrdb__UBTF__ENCSR000EFZ_1__m1-Brf-brm-E(z)-RpII215-tna 5 0.000712848 17.4313 0.150463 9 GCCTGAGGG CGGCGGCCGGGCGGAGCCGG - +3 dbcorrdb__E2F6__ENCSR000BLI_1__m1-Brf-brm-btd-CTCF-E2f1-E2f2-Eip74EF-ERR-E(z)-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-TfAP-2-tna-usp-vtd 10 0.000784259 19.1775 0.162718 9 GCCTGAGGG CCCCCTTCCCGCCCGCCGCC - +3 dbcorrdb__HA-E2F1__ENCSR000EVM_1__m1-Brf-brm-CrebB-CTCF-E2f1-ERR-ewg-E(z)-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-SREBP-tna-vtd 6 0.000784259 19.1775 0.162718 9 GCCTGAGGG CCGCGCGCCAGCCCCGGGCG - +3 cisbp__M2493-arg-HDAC1-HDAC3 8 0.000791495 19.3544 0.163524 9 GCCTGAGGG TACTAGCCGCCGAAGGC - +3 neph__UW.Motif.0309 3 0.000797397 19.4988 0.164048 9 GCCTGAGGG AGAGCCAGGGAGT - +3 neph__UW.Motif.0557 5 0.000852277 20.8407 0.173146 9 GCCTGAGGG CAGCAGCAGGGAGATG + +3 transfac_pro__M01858-E(z)-RpII215-TfAP-2-tna 6 0.000852277 20.8407 0.173146 9 GCCTGAGGG GCGGCGGCCTGGGGGG + +3 dbcorrdb__HA-E2F1__ENCSR000EWX_1__m1-E2f1 10 0.000862054 21.0798 0.174406 9 GCCTGAGGG GGGCCTTCGCGCCAGCGGGG - +3 predrem__nrMotif2118-TfAP-2 0 0.000885328 21.6489 0.176912 9 GCCTGAGGG GCCGGAGGC - +3 tfdimers__MD00461-Pur-alpha 10 0.00091476 22.3686 0.181308 9 GCCTGAGGG CCCGTCCCTGCCCCTGGGGCAGGGCGGGG + +3 transfac_pro__M04896-TfAP-2 1 0.000938222 22.9423 0.184458 9 GCCTGAGGG GGCCCCAGGGCATG - +3 hocomoco__SP1_HUMAN.H11MO.0.A-Brf-CG3065-CG42741-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Max-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-Spt20-Stat92E-brm-btd-cbt-ct-dar1-klu-luna-sr-tna-vtd 10 0.000999107 24.4312 0.194081 9 GCCTGAGGG GGGGGGCGGGGCCGGGGGGGGG + +3 neph__UW.Motif.0574 4 0.00102119 24.9711 0.197583 9 GCCTGAGGG GCTGGCAGGGGGCAGC - +3 neph__UW.Motif.0488 2 0.0010375 25.3699 0.199158 9 GCCTGAGGG TTGGCATAAGAAA - +3 transfac_pro__M01047-TfAP-2 3 0.00107903 26.3854 0.205512 9 GCCTGAGGG ACCGCCTGAGGCGGT + +3 cisbp__M6547-Brf-brm-CTCF-ERR-E(z)-Myc-RpII215-SREBP-tna-vtd 6 0.00114887 28.0932 0.217962 9 GCCTGAGGG GCCGAGGCCTGGGGCCCCG - +3 neph__UW.Motif.0280 5 0.0012322 30.1309 0.232865 8 GCCTGAGGG GAGGGGCCCCAGG - +3 dbcorrdb__E2F6__ENCSR000EVK_1__m1-Brf-brm-CTCF-E2f1-E2f2-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-Spt20-SREBP-Taf1-vtd 8 0.00124771 30.5103 0.233087 9 GCCTGAGGG CCCTTCCCGCCCTCCCGCCC + +3 dbcorrdb__TFAP2A__ENCSR000EVP_1__m1-TfAP-2 5 0.00124771 30.5103 0.233087 9 GCCTGAGGG CCATGGCCTCAGGGCATGGG + +3 dbcorrdb__NELFE__ENCSR000DOF_1__m2-Nelf-E 8 0.00124771 30.5103 0.233087 9 GCCTGAGGG AGAGACCCGCCCCAGCCGCT - +3 hocomoco__ZFX_MOUSE.H11MO.0.B-Brf-CTCF-ERR-E(z)-Myc-RpII215-SREBP-brm-tna-vtd 6 0.00125764 30.753 0.234045 9 GCCTGAGGG GCCGAGGCCTGGGGCCCCC + +3 neph__UW.Motif.0512 4 0.00128554 31.4353 0.238328 9 GCCTGAGGG TGTGGCCTTAGGAAA + +3 tfdimers__MD00600-EcR-usp 17 0.00139782 34.1809 0.256221 9 GCCTGAGGG TGTCTCAGTGACAGATGGCCTTGGAG + +3 neph__UW.Motif.0399 1 0.0014255 34.8578 0.260316 9 GCCTGAGGG TGCTGTTAGGAA + +3 neph__UW.Motif.0433 8 0.00145276 35.5243 0.264303 8 GCCTGAGGG TGAGTTCTGGCTGTGG - +3 tfdimers__MD00582 16 0.00147864 36.1572 0.26702 9 GCCTGAGGG TGGGCCAGTGACAGGTGCCCGGGGCGCCG + +3 cisbp__M2320-TfAP-2 4 0.00152722 37.3452 0.274775 9 GCCTGAGGG CATGGCCCCAGGGCA - +3 neph__UW.Motif.0487 5 0.00158371 38.7264 0.28285 9 GCCTGAGGG CCAGTGCCTGCTCCTG - +3 neph__UW.Motif.0327 8 0.00158371 38.7264 0.28285 8 GCCTGAGGG CCCGGGCCGCCCGCAG + +3 tfdimers__MD00167 12 0.0015904 38.89 0.283008 9 GCCTGAGGG CCGGCCACAGCTGCCCGCGCCCCGG + +3 transfac_pro__M07137-TfAP-2 4 0.00166288 40.6625 0.293763 9 GCCTGAGGG CATGGCCCCAGGGCA + +3 neph__UW.Motif.0348 7 0.00166288 40.6625 0.293763 8 GCCTGAGGG CTGCCTTTCCTGCTG - + +# Tomtom (Motif Comparison Tool): Version 5.5.1 compiled on Mar 14 2023 at 10:55:24 +# The format of this file is described at https://meme-suite.org/meme/doc/tomtom-output-format.html. +# tomtom -thresh 0.3 -oc ./motif-3 motif-3.meme ./motif2gene_names.all.meme diff --git a/the_code/Human/data/tomtom/motif-3/tomtom.xml b/the_code/Human/data/tomtom/motif-3/tomtom.xml new file mode 100644 index 0000000000000000000000000000000000000000..099aed61f552a74a76214a4c1a9fbd4a030644f2 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-3/tomtom.xml @@ -0,0 +1,3361 @@ + + + + tomtom -thresh 0.3 -oc ./motif-3 motif-3.meme ./motif2gene_names.all.meme + + 0.3 + + + + + + + + + + + + + + + + + + both + + i28g27 + Tue Oct 10 04:20:59 2023 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/the_code/Human/data/tomtom/motif-4.meme b/the_code/Human/data/tomtom/motif-4.meme new file mode 100644 index 0000000000000000000000000000000000000000..c3173edda2f31adc0950e7beee7509d021026616 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-4.meme @@ -0,0 +1,18 @@ +MEME version 4 + +ALPHABET= ACGT + +strands: + - + +Background letter frequencies (from unknown source): +A 0.250 C 0.250 G 0.250 T 0.250 + +MOTIF 4 YACCTD + +letter-probability matrix: alength= 4 w= 6 nsites= 1 E= 0e+0 +0.138734 0.426443 0.049348 0.385475 +0.984171 0.009311 0.000000 0.006518 +0.004655 0.975791 0.005587 0.013966 +0.013035 0.967412 0.003724 0.015829 +0.008380 0.019553 0.020484 0.951583 +0.191806 0.096834 0.453445 0.257914 diff --git a/the_code/Human/data/tomtom/motif-4/tomtom.html b/the_code/Human/data/tomtom/motif-4/tomtom.html new file mode 100644 index 0000000000000000000000000000000000000000..08813f6deffdf07991398b3cab49aacd9752e344 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-4/tomtom.html @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3fdc9e69f739f976acbbfa7a798709300f26e1f9a294523d41e29ad00b6a58f0 +size 27592533 diff --git a/the_code/Human/data/tomtom/motif-4/tomtom.tsv b/the_code/Human/data/tomtom/motif-4/tomtom.tsv new file mode 100644 index 0000000000000000000000000000000000000000..7d1c622e739299297c7bf5df469b4ac0fb1d6684 --- /dev/null +++ b/the_code/Human/data/tomtom/motif-4/tomtom.tsv @@ -0,0 +1,24458 @@ +Query_ID Target_ID Optimal_offset p-value E-value q-value Overlap Query_consensus Target_consensus Orientation +4 cisbp__M6543-zfh1 0 0.000115581 2.8263 1 6 CACCTG CACCTGT - +4 transfac_pro__M09159 7 0.000151824 3.71255 1 6 CACCTG CAGATAACACCTGCACAA + +4 predrem__nrMotif1786 3 0.000171774 4.20039 1 6 CACCTG TCCCACCTG + +4 transfac_pro__M09007-zfh1 1 0.000195116 4.77118 1 6 CACCTG TCACCTGT + +4 transfac_public__M00073-zfh1 3 0.000223187 5.45759 1 6 CACCTG ACTCACCTGAA + +4 cisbp__M3114-zfh1 3 0.000223187 5.45759 1 6 CACCTG ACTCACCTGAA - +4 predrem__nrMotif1556 0 0.000331292 8.10107 1 6 CACCTG CACCTGAA - +4 hocomoco__ZEB1_HUMAN.H11MO.0.A-zfh1 2 0.000411987 10.0743 1 6 CACCTG CTCACCTGTC - +4 tfdimers__MD00194-NFAT-zfh1 11 0.000450183 11.0083 1 6 CACCTG AGATTGGAAAGCACCTGACCAATA + +4 stark__ACTNACCT 3 0.000784638 19.1868 1 5 CACCTG ACTAACCT + +4 predrem__nrMotif685 -1 0.000957387 23.411 1 5 CACCTG ACCTGCCAGG + +4 taipale__SNAI2_DBD_NRCAGGTGN-ac-ase-da-emc-esg-HLH54F-l(1)sc-nau-sc-sna-wor 1 0.000989282 24.1909 1 6 CACCTG ACACCTGTT - +4 transfac_pro__M03919-ac-ase-da-emc-esg-HLH54F-l(1)sc-nau-sc-sna-wor 1 0.000989282 24.1909 1 6 CACCTG ACACCTGTT - +4 cisbp__M0078 1 0.00107067 26.1811 1 6 CACCTG GCACCTGAAA + +4 cisbp__M5809-ac-ase-da-emc-esg-HLH54F-l(1)sc-nau-sc-sna-wor 1 0.00110177 26.9417 1 6 CACCTG ACACCTGTT - +4 hocomoco__ID4_HUMAN.H11MO.0.D-emc-esg-sna-wor 3 0.00112477 27.504 1 6 CACCTG TTACACCTGTC - +4 transfac_public__M00413-zfh1 3 0.00115583 28.2636 1 6 CACCTG ATTCACCTGTAC + +4 cisbp__M1627-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00119622 29.2511 1 5 CACCTG TCACACCT - +4 predrem__nrMotif1235 -1 0.00122339 29.9157 1 5 CACCTG ACCTGAGAG - +4 hocomoco__MESP1_HUMAN.H11MO.0.D 4 0.00125585 30.7093 1 6 CACCTG TGCACACCTGC - +4 cisbp__M2953-zfh1 3 0.00129213 31.5964 1 6 CACCTG ATTCACCTGTAC - +4 predrem__nrMotif1067 2 0.00132179 32.3216 1 5 CACCTG GGTACCT - +4 taipale_cyt_meth__SCRT2_NGCAACAGGTN_eDBD-CG12605-scrt 0 0.00139844 34.1962 1 6 CACCTG CACCTGTTGCT - +4 jaspar__MA0086.1-sna 0 0.00140197 34.2824 1 6 CACCTG CACCTG - +4 hdpi__ZNF313 1 0.00140197 34.2824 1 5 CACCTG TGACCT - +4 taipale__TCF4_full_NNCACCTGNN_repr-da-Hand-sc 2 0.00147197 35.994 1 6 CACCTG CACACCTGCA + +4 transfac_pro__M04785-vtd -1 0.00149668 36.5983 1 5 CACCTG ACCTGGTGG + +4 taipale_cyt_meth__SCRT1_NGCAACAGGTN_eDBD_repr-CG12605-scrt 0 0.00155309 37.9776 1 6 CACCTG CACCTGTTGCT - +4 taipale_cyt_meth__SCRT1_NGCRACAGGTN_eDBD_meth-CG12605-scrt 0 0.00155309 37.9776 1 6 CACCTG CACCTGTTGCA - +4 transfac_pro__M04831-zfh1 1 0.00158862 38.8466 1 6 CACCTG TCACCTG - +4 transfac_public__M00412-zfh1 4 0.00162611 39.7633 1 6 CACCTG TACTTACCTGTGT + +4 transfac_pro__M05300 4 0.00162819 39.8141 1 6 CACCTG TTGACACCTG + +4 cisbp__M1913-sna 0 0.00167151 40.8733 1 6 CACCTG CACCTG - +4 cisbp__M5902-da-Hand-sc 2 0.00179706 43.9434 1 6 CACCTG CACACCTGCA + +4 transfac_pro__M09321 2 0.00179706 43.9434 1 6 CACCTG TTTACCTAAC - +4 flyfactorsurvey__l_1_sc_da_SANGER_5_FBgn0000413-ac-da-esg-sna-wor 0 0.00189974 46.4544 1 6 CACCTG CACCTGC - +4 predrem__nrMotif1199 4 0.00190153 46.4982 1 6 CACCTG TCCCCACCTCC - +4 taipale_cyt_meth__SCRT2_NGCRACAGGTN_eDBD_meth-CG12605-scrt 0 0.00190153 46.4982 1 6 CACCTG CACCTGTTGCT - +4 jaspar__MA1036.1 0 0.00192408 47.0495 1 6 CACCTG TACCTACC - +4 transfac_pro__M09174 0 0.00199624 48.8139 1 6 CACCTG TACCTGGAGAACATA + +4 cisbp__M4818-CG12605-Kah-scrt 1 0.00200419 49.0085 1 6 CACCTG CCACCTGTTGCAC - +4 flyfactorsurvey__sna_F2-4_SOLEXA_5-esg-sna 2 0.00209734 51.2862 1 6 CACCTG CCCACCTGTCA + +4 cisbp__M4483-zfh1 2 0.00210648 51.5097 1 6 CACCTG CTCACCTG - +4 transfac_pro__M07371-zfh1 3 0.0021748 53.1805 1 6 CACCTG CCTCACCTGTGC - +4 cisbp__M2952-zfh1 4 0.00221732 54.2201 1 6 CACCTG TACTTACCTGTGT - +4 predrem__nrMotif2300-Hr78 -1 0.00226346 55.3485 1 5 CACCTG ACCTTTG - +4 transfac_pro__M05483 0 0.00229568 56.1362 1 6 CACCTG TACCTGACTACGCCAACA - +4 cisbp__M5274-nau-wor 1 0.00230351 56.3277 1 6 CACCTG CCACCTGC - +4 predrem__nrMotif2544 2 0.00230351 56.3277 1 6 CACCTG ATTACCTT - +4 cisbp__M1629-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00230351 56.3277 1 5 CACCTG TCACACCT - +4 hocomoco__TBX4_HUMAN.H11MO.0.D-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 14 0.00236334 57.7907 1 6 CACCTG GGTGTGAAATTTCACACCTT - +4 flyfactorsurvey__CG12605_SANGER_10_FBgn0035481-CG12605-scrt 0 0.00239782 58.6339 1 6 CACCTG CACCTGTTG + +4 idmmpmm__sna-esg-sna-wor 1 0.00239782 58.6339 1 6 CACCTG CCACCTGTT + +4 predrem__nrMotif1345 3 0.00239782 58.6339 1 6 CACCTG TCTCACCTT - +4 transfac_pro__M09019 4 0.00242062 59.1914 1 6 CACCTG AAATCACCTGAACAGG - +4 flyfactorsurvey__CG12605_SOLEXA_5_FBgn0035481-CG12605-Kah-scrt 1 0.002448 59.8609 1 6 CACCTG CCACCTGTTGCAC + +4 cisbp__M5063-ac-esg-sna-wor 0 0.00246805 60.3513 1 6 CACCTG CACCTGC - +4 predrem__nrMotif1850 1 0.00246805 60.3513 1 6 CACCTG CCACCTG - +4 flyfactorsurvey__wor_SOLEXA_2.5_FBgn0001983-ase-da-nau-wor 1 0.00251638 61.5331 1 6 CACCTG CCACCTGC + +4 jaspar__MA1040.1 0 0.00251638 61.5331 1 6 CACCTG TACCTAAC - +4 jaspar__MA1042.1 0 0.00251638 61.5331 1 6 CACCTG TACCTAAC - +4 hocomoco__ZN784_HUMAN.H11MO.0.D 1 0.00253826 62.068 1 6 CACCTG GTACCTACCTC - +4 transfac_pro__M05389-byn-Doc1-Doc2-Doc3-org-1 4 0.00262156 64.1049 1 6 CACCTG TTAACACCTA + +4 taipale__TBX21_DBD_NAGGTGTGAA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00262156 64.1049 1 6 CACCTG TTCACACCTT - +4 flyfactorsurvey__CG17181_SANGER_5_FBgn0035144-CG17802-Kah-da-net-scrt 2 0.00262406 64.1661 1 6 CACCTG ACCACCTGT + +4 predrem__nrMotif2146 2 0.00262406 64.1661 1 6 CACCTG CAGACCTGT + +4 predrem__nrMotif2638 3 0.00262406 64.1661 1 6 CACCTG TCCTACCTT + +4 transfac_pro__M07917-CG12605-scrt 1 0.00269764 65.9653 1 6 CACCTG CCACCTGTTGCAT - +4 cisbp__M4817-CG12605-scrt 0 0.00286852 70.144 1 6 CACCTG CACCTGTTG - +4 cisbp__M4831-CG12605-CG17802-da-Kah-net-scrt 2 0.00286852 70.144 1 6 CACCTG ACCACCTGT - +4 predrem__nrMotif1539 -1 0.00286852 70.144 1 5 CACCTG ACCTTCTTT + +4 transfac_pro__M05320 4 0.00287134 70.2128 1 6 CACCTG TTAACACCTA + +4 transfac_pro__M05321 4 0.00287134 70.2128 1 6 CACCTG TTAACACCTA + +4 cisbp__M5890-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00287134 70.2128 1 6 CACCTG TTCACACCTT - +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m2 5 0.00292094 71.4258 1 6 CACCTG GCTCACACCTTATTAAACAT + +4 transfac_pro__M02851 7 0.00296211 72.4325 1 6 CACCTG GAGGCGACACCTCCCC - +4 flyfactorsurvey__scrt_SOLEXA_2.5_1_FBgn0004880-CG12605-scrt 1 0.00296781 72.572 1 6 CACCTG CCACCTGTTGCAC + +4 cisbp__M5183-CG12605-scrt 1 0.00296781 72.572 1 6 CACCTG CCACCTGTTGCAC - +4 predrem__nrMotif1960 -1 0.00299515 73.2403 1 5 CACCTG ACCTGGAA + +4 cisbp__M5881-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00299515 73.2403 1 5 CACCTG TCACACCT - +4 stark__CAGGTG-sna 0 0.00301413 73.7044 1 6 CACCTG CACCTG - +4 hdpi__ZNF510 1 0.00301413 73.7044 1 5 CACCTG TAACCT - +4 cisbp__M5886-bi-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00305444 74.6902 1 6 CACCTG CTTCACACCTA - +4 transfac_pro__M00959-ERR 5 0.00305444 74.6902 1 6 CACCTG ACCGTGACCTG - +4 predrem__nrMotif1636 2 0.00313264 76.6026 1 6 CACCTG GGGACCTGA - +4 transfac_pro__M01044-org-1 4 0.00314138 76.8161 1 6 CACCTG CTCACACCTT + +4 taipale__TBX21_full_NAGGTGTGAA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00314138 76.8161 1 6 CACCTG TTCACACCTT - +4 swissregulon__hs__TBX4_5.p2-bi-org-1 5 0.00318162 77.8001 1 6 CACCTG CCTCACACCTTC - +4 swissregulon__hs__TCF4_dimer.p2 1 0.00318531 77.8903 1 6 CACCTG GCACCTG - +4 hocomoco__SCRT1_HUMAN.H11MO.0.D-CG12605-CG17802-Kah-scrt 3 0.00326028 79.7236 1 6 CACCTG AACCACCTGTTGC - +4 hocomoco__TBR1_HUMAN.H11MO.0.D-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 6 0.00326028 79.7236 1 6 CACCTG TTTTCACACCTTT - +4 taipale__SCRT2_DBD_NNGCAACAGGTGN-CG12605-scrt 1 0.00326028 79.7236 1 6 CACCTG CCACCTGTTGCAT - +4 taipale__TBX15_DBD_AGGTGTGA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00326396 79.8137 1 5 CACCTG TCACACCT - +4 transfac_pro__M09298 6 0.00329757 80.6355 1 6 CACCTG TTTGTTCACCTAACT + +4 hocomoco__FIGLA_HUMAN.H11MO.0.D 2 0.00334463 81.7862 1 6 CACCTG AACACCTGTTA - +4 taipale__TBX20_full_NAGGTGTGAAN-bi-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00334463 81.7862 1 6 CACCTG CTTCACACCTA - +4 c2h2_zfs__M0442 2 0.003418 83.5804 1 6 CACCTG TGCCCCTGA - +4 predrem__nrMotif753 2 0.003418 83.5804 1 6 CACCTG TGCACCTTC - +4 taipale__MESP1_DBD_NNCACCTGNN-Hand 2 0.00343322 83.9525 1 6 CACCTG AACACCTGTG + +4 transfac_pro__M05366-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00343322 83.9525 1 6 CACCTG TTAACACCTA + +4 cisbp__M5627-da-Hand-sc 2 0.00343322 83.9525 1 6 CACCTG AACACCTGTG - +4 cisbp__M5893-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00343322 83.9525 1 6 CACCTG TTCACACCTT - +4 transfac_pro__M07491 1 0.00343322 83.9525 1 6 CACCTG TTACCTAACT - +4 transfac_pro__M07492 1 0.00343322 83.9525 1 6 CACCTG CTACCTAACT - +4 transfac_pro__M07494 1 0.00343322 83.9525 1 6 CACCTG CTACCTACCA - +4 elemento__ACCTGCT -1 0.00346134 84.6401 1 5 CACCTG ACCTGCT + +4 transfac_pro__M05520 4 0.00348713 85.2708 1 6 CACCTG TAATTACCTGTC - +4 hdpi__FIP1L1-Fip1 0 0.00355427 86.9126 1 6 CACCTG CACCTTGA - +4 cisbp__M5805-CG12605-scrt 1 0.0035769 87.4659 1 6 CACCTG CCACCTGTTGCAT - +4 neph__UW.Motif.0583 4 0.0036211 88.5466 1 6 CACCTG TAAATTCCTTTCTG - +4 cisbp__M5874-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00365842 89.4594 1 6 CACCTG TTTCACACCTT - +4 taipale__TBR1_full_NAGGTGTGAAN-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00365842 89.4594 1 6 CACCTG TTTCACACCTT - +4 predrem__nrMotif1371 -1 0.00372629 91.119 1 5 CACCTG ACCTGTCAT - +4 flyfactorsurvey__esg_SANGER_2.5_FBgn0001981-esg 0 0.00375702 91.8705 1 6 CACCTG CACCTGT + +4 swissregulon__hs__SNAI1..3.p2-esg-sna-wor 0 0.00383271 93.7213 1 6 CACCTG CACCTG - +4 hdpi__ZNF655 1 0.00383271 93.7213 1 5 CACCTG TGACCT - +4 cisbp__M1623-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00386726 94.5661 1 5 CACCTG TCACACCT + +4 hocomoco__SCRT2_HUMAN.H11MO.0.D-CG12605-scrt 1 0.00391964 95.8469 1 6 CACCTG CCACCTGTTGCAT - +4 predrem__nrMotif283 0 0.00405924 99.2605 1 6 CACCTG CACCTGCTG - +4 flyfactorsurvey__wor_SANGER_2.5_FBgn0001983-esg-sna-wor 0 0.00407352 99.6098 1 6 CACCTG CACCTGC + +4 elemento__AGCACCT 2 0.00407352 99.6098 1 5 CACCTG AGCACCT + +4 elemento__ATCACCT 2 0.00407352 99.6098 1 5 CACCTG ATCACCT + +4 elemento__AGGTGAA 2 0.00407352 99.6098 1 5 CACCTG TTCACCT - +4 elemento__AGGTGAG 2 0.00407352 99.6098 1 5 CACCTG CTCACCT - +4 elemento__AGGTGCA 2 0.00407352 99.6098 1 5 CACCTG TGCACCT - +4 elemento__AGGTGCG 2 0.00407352 99.6098 1 5 CACCTG CGCACCT - +4 elemento__AGGTGTC 2 0.00407352 99.6098 1 5 CACCTG GACACCT - +4 cisbp__M6521-EcR 2 0.00408911 99.991 1 6 CACCTG CTGACCTGAG + +4 transfac_pro__M05345-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00408911 99.991 1 6 CACCTG TTCACACCTA + +4 transfac_pro__M05457 4 0.00408911 99.991 1 6 CACCTG TTAACACCTA + +4 transfac_pro__M05495 4 0.00408911 99.991 1 6 CACCTG TTAACACCTA + +4 transfac_pro__M07496 0 0.00408911 99.991 1 6 CACCTG TACCTACCGG + +4 cisbp__M1635-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.00408911 99.991 1 6 CACCTG TTCACACCTT - +4 c2h2_zfs__M3563 0 0.00415187 101.526 1 6 CACCTG TACCTA - +4 scertf__macisaac.MOT3 0 0.00415187 101.526 1 6 CACCTG TGCCTT - +4 cisbp__M0548 1 0.0042039 102.798 1 6 CACCTG CCACCTCA - +4 predrem__nrMotif1934 1 0.0042039 102.798 1 6 CACCTG CTACCTGC - +4 cisbp__M1640-bi 3 0.0042039 102.798 1 5 CACCTG TGACACCT + +4 cisbp__M5877-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0042039 102.798 1 5 CACCTG TCACACCT - +4 transfac_pro__M09316 3 0.00435195 106.418 1 6 CACCTG TTTTACCTAACTAA + +4 neph__UW.Motif.0348 6 0.00436699 106.786 1 6 CACCTG CTGCCTTTCCTGCTG - +4 elemento__ACACCTG 1 0.0044125 107.899 1 6 CACCTG ACACCTG + +4 elemento__CACCTGC 0 0.0044125 107.899 1 6 CACCTG CACCTGC + +4 elemento__CACCTGG 0 0.0044125 107.899 1 6 CACCTG CACCTGG + +4 elemento__ACAGGTG-scrt 0 0.0044125 107.899 1 6 CACCTG CACCTGT - +4 elemento__CAGGTGA 1 0.0044125 107.899 1 6 CACCTG TCACCTG - +4 elemento__CAGGTGC 1 0.0044125 107.899 1 6 CACCTG GCACCTG - +4 elemento__CAGGTGG 1 0.0044125 107.899 1 6 CACCTG CCACCTG - +4 predrem__nrMotif2178 3 0.00441848 108.045 1 6 CACCTG TCCAACCTC + +4 transfac_pro__M08831-bi 3 0.00441848 108.045 1 6 CACCTG TCACACCTG + +4 predrem__nrMotif1080 0 0.00441848 108.045 1 6 CACCTG GACCTGGGT - +4 hocomoco__THA_HUMAN.H11MO.1.D-EcR 2 0.0044569 108.985 1 6 CACCTG CTGACCTGAA - +4 taipale_cyt_meth__SNAI1_NRCAGGTGYR_eDBD-ac-ase-da-esg-l(1)sc-sc-sna-wor 2 0.0044569 108.985 1 6 CACCTG TGCACCTGCC - +4 cisbp__M0861 0 0.0045651 111.63 1 6 CACCTG TACCTTAA - +4 elemento__ACCTGTTG-CG12605-scrt -1 0.0045651 111.63 1 5 CACCTG ACCTGTTG + +4 taipale__TBX1_DBD_AGGTGTGA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0045651 111.63 1 5 CACCTG TCACACCT - +4 flyfactorsurvey__scrt_SOLEXA_2.5_2_FBgn0004880-CG12605-CG17802-Kah-da-net-scrt 2 0.00469171 114.726 1 6 CACCTG ACCACCTGTTGCA + +4 cisbp__M5184-CG12605-CG17802-da-Kah-net-scrt 2 0.00469171 114.726 1 6 CACCTG ACCACCTGTTGCA - +4 swissregulon__hs__T.p2-Doc1-Doc2-Doc3-H15-byn-mid-org-1 4 0.00475976 116.391 1 6 CACCTG TTCACACCTAG - +4 flyfactorsurvey__ase_da_SANGER_10_FBgn0000137-ac-ase-da-esg-sc-sna-wor 0 0.00477623 116.793 1 6 CACCTG CACCTGC + +4 cisbp__M4948-esg 0 0.00477623 116.793 1 6 CACCTG CACCTGT - +4 cisbp__M5273-esg-sna-wor 0 0.00477623 116.793 1 6 CACCTG CACCTGC - +4 predrem__nrMotif2067 2 0.00485388 118.692 1 6 CACCTG CTCACCTGTG + +4 predrem__nrMotif786 3 0.00485388 118.692 1 6 CACCTG GGACACCTGC + +4 taipale__ID4_DBD_NRCACCTGNN_repr-emc-esg-sna-wor 2 0.00485388 118.692 1 6 CACCTG TACACCTGTC + +4 taipale_cyt_meth__HAND2_AACACCTGYN_eDBD_meth_repr-Hand 2 0.00485388 118.692 1 6 CACCTG AACACCTGCA + +4 transfac_pro__M05322-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00485388 118.692 1 6 CACCTG TTCACACCTA + +4 cisbp__M5571-emc-esg-sna-wor 2 0.00485388 118.692 1 6 CACCTG TACACCTGTC - +4 transfac_pro__M01676 0 0.00487472 119.202 1 6 CACCTG TACCTG - +4 flyfactorsurvey__nau_da_SANGER_5_FBgn0000413-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.00495192 121.089 1 6 CACCTG CACCTGTC + +4 hocomoco__SNAI1_HUMAN.H11MO.0.C-esg-sna-wor 1 0.00495192 121.089 1 6 CACCTG CCACCTGG - +4 elemento__TACCTGC 0 0.00516732 126.357 1 6 CACCTG TACCTGC + +4 cisbp__M4745-ac-ase-da-esg-sc-sna-wor 0 0.00516732 126.357 1 6 CACCTG CACCTGC - +4 elemento__CAGGTAG 1 0.00516732 126.357 1 6 CACCTG CTACCTG - +4 jaspar__MA0103.2-zfh1 3 0.00522146 127.68 1 6 CACCTG CCTCACCTG + +4 predrem__nrMotif72 3 0.00522146 127.68 1 6 CACCTG TTCCACCTC + +4 cisbp__M1926-zfh1 3 0.00522146 127.68 1 6 CACCTG CCTCACCTG - +4 flyfactorsurvey__CG17181_SOLEXA_5_FBgn0035144-CG12605-CG17802-HLH54F-Kah-da-scrt-sna 3 0.00523555 128.025 1 6 CACCTG AACCACCTGTTGACC + +4 cisbp__M5885-bi-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.00523555 128.025 1 6 CACCTG CTTTCACACCTTTTC - +4 transfac_pro__M07430-esg-sna-wor 1 0.00528193 129.159 1 6 CACCTG CCACCTGCCA + +4 predrem__nrMotif2273 1 0.00528193 129.159 1 6 CACCTG TTACCTTGCA - +4 transfac_pro__M07900-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00528193 129.159 1 6 CACCTG TTCACACCTT - +4 flyfactorsurvey__ac_da_SANGER_5_FBgn0000022-ac-ase-da-esg-l(1)sc-sc-sna-wor 1 0.00536585 131.211 1 6 CACCTG ACACCTGC + +4 transfac_pro__M03565-esg-sna-wor 1 0.00536585 131.211 1 6 CACCTG GCACCTGC + +4 transfac_pro__M07919-CG12605-CG17802-da-HLH54F-Kah-net-scrt 3 0.00542997 132.779 1 6 CACCTG AACCACCTGTTA - +4 cisbp__M0458-scrt 0 0.00558884 136.664 1 6 CACCTG CACCTGT - +4 cisbp__M6469-esg-sna-wor 0 0.00558884 136.664 1 6 CACCTG CACCTGA - +4 transfac_public__M00060-esg-sna-wor 3 0.00559389 136.787 1 6 CACCTG GTGCACCTGTTTT - +4 flyfactorsurvey__HLH54F_da_SANGER_5_FBgn0000413-CG12605-HLH54F-Kah-da-esg-scrt-sna-wor 2 0.00564788 138.108 1 6 CACCTG AACACCTGTTG + +4 taipale_cyt_meth__ZNF784_STACYTACCKY_FL_meth 1 0.00564788 138.108 1 6 CACCTG GTACCTACCGT + +4 predrem__nrMotif2386 0 0.00566764 138.591 1 6 CACCTG AACCTTGGA + +4 hocomoco__TBX2_HUMAN.H11MO.0.D-bi 11 0.00572051 139.884 1 6 CACCTG GTCGCTTCTCACACCTCTGTTTGCA - +4 cisbp__M4832-CG12605-CG17802-da-HLH54F-Kah-scrt-sna 3 0.00572393 139.967 1 6 CACCTG AACCACCTGTTGACC - +4 cisbp__M5804-CG12605-CG17802-da-HLH54F-Kah-net-scrt 3 0.00572393 139.967 1 6 CACCTG AACCACCTGTTGCTC - +4 taipale__SCRT1_DBD_NNGCAACAGGTGGNN_repr-CG12605-CG17802-da-HLH54F-Kah-net-scrt 3 0.00572393 139.967 1 6 CACCTG AACCACCTGTTGCTC - +4 taipale__TBX20_DBD_HNHNAGGTGTGANHH-bi-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.00572393 139.967 1 6 CACCTG CTTTCACACCTTTTC - +4 cisbp__M0645 -1 0.00572584 140.014 1 5 CACCTG ACCTTT - +4 taipale_cyt_meth__SNAI1_NRCAGGTGCR_FL_repr-esg-sna-wor 2 0.00574279 140.428 1 6 CACCTG TGCACCTGCT - +4 taipale_cyt_meth__SREBF1_RTCAGGTGAY_eDBD_meth-SREBP 2 0.00574279 140.428 1 6 CACCTG ATCACCTGAT - +4 taipale_cyt_meth__SREBF2_ATCAGGTGAY_eDBD_meth-SREBP 2 0.00574279 140.428 1 6 CACCTG ATCACCTGAT - +4 dbcorrdb__ZEB1__ENCSR000BND_1__m1-Brf-brm-cnc-CTCF-CycT-E2f1-ebi-ERR-E(z)-HDAC1-Max-Myc-Nelf-E-RpII215-Spt20-SREBP-tna-Usf-zfh1 7 0.00578325 141.418 1 6 CACCTG CCGGCCTCACCTGGCCGCGC - +4 flyfactorsurvey__sc_da_SANGER_10_FBgn0000413-ac-ase-da-esg-sc-sna-wor 1 0.00580892 142.046 1 6 CACCTG ACACCTGC + +4 predrem__nrMotif1262 0 0.00580892 142.046 1 6 CACCTG CACCTGGT + +4 cisbp__M5112-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.00580892 142.046 1 6 CACCTG CACCTGTC - +4 elemento__CAGGTGAG-zfh1 2 0.00580892 142.046 1 6 CACCTG CTCACCTG - +4 elemento__CAGGTGGA 2 0.00580892 142.046 1 6 CACCTG TCCACCTG - +4 elemento__CAGGTGGC 2 0.00580892 142.046 1 6 CACCTG GCCACCTG - +4 transfac_pro__M04824-CTCF -1 0.00580892 142.046 1 5 CACCTG ACCTGCAG + +4 bergman__esg-esg-sna-wor 3 0.00591652 144.677 1 6 CACCTG CTGCACCTGTTA - +4 taipale_cyt_meth__TBX18_NRAGGTGTGAAN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00591652 144.677 1 6 CACCTG TTTCACACCTCC - +4 transfac_pro__M01019-bi-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00591652 144.677 1 6 CACCTG TTTGACACCTTT - +4 cisbp__M6443-EcR 1 0.00604388 147.791 1 6 CACCTG TGACCTC + +4 predrem__nrMotif1855 0 0.00604388 147.791 1 6 CACCTG AACCTCC + +4 predrem__nrMotif1346 1 0.00604388 147.791 1 6 CACCTG TCACCTT - +4 taipale_cyt_meth__TBX20_NAGGTGTGAAGGTGTGAN_eDBD_repr-bi-Doc1-Doc2-Doc3-H15-mid-org-1 12 0.00607935 148.658 1 6 CACCTG TTCACACCTTCACACCTC - +4 bergman__sna-esg-sna-wor 3 0.00609972 149.156 1 6 CACCTG GTGCACCTGTTTC - +4 cisbp__M2581-esg-sna-wor 3 0.00609972 149.156 1 6 CACCTG GTGCACCTGTTTC - +4 neph__UW.Motif.0123 0 0.00609972 149.156 1 6 CACCTG CACCTGGCATTCT - +4 transfac_pro__M07943-CG12605-scrt 1 0.00609972 149.156 1 6 CACCTG CCACCTGTTGCAC - +4 cisbp__M0680 5 0.00614464 150.255 1 6 CACCTG GAATGTACCTG + +4 transfac_pro__M07394-esg-sna-wor 0 0.00614539 150.273 1 6 CACCTG CACCTGCAG + +4 cisbp__M2851 3 0.00614539 150.273 1 6 CACCTG ACCTACCCG - +4 transfac_pro__M03566-esg-sna-wor 2 0.00620825 151.81 1 6 CACCTG GCCACCTGGCTGCA + +4 neph__UW.Motif.0400 1 0.00620825 151.81 1 6 CACCTG TCATCTCTGTTTTT - +4 cisbp__M6461-usp 3 0.00623797 152.537 1 6 CACCTG TGTGACCTCA + +4 transfac_pro__M08900-bi 4 0.00623797 152.537 1 6 CACCTG CTCACACCTG + +4 cisbp__M4685-zfh1 4 0.00623797 152.537 1 6 CACCTG CACACACCTG - +4 taipale_cyt_meth__TBX21_NAGGTGTGAN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00623797 152.537 1 6 CACCTG TTCACACCTC - +4 transfac_pro__M01020 3 0.00623797 152.537 1 6 CACCTG TAACACCTCA - +4 transfac_public__M00107 1 0.00623964 152.578 1 6 CACCTG GTACCGGTATCGGTGC - +4 cisbp__M5178-ac-ase-da-esg-sc-sna-wor 1 0.0062838 153.658 1 6 CACCTG ACACCTGC + +4 cisbp__M4724-ac-ase-da-esg-l(1)sc-sc-sna-wor 1 0.0062838 153.658 1 6 CACCTG ACACCTGC - +4 cisbp__M6503-bi 11 0.00629184 153.854 1 6 CACCTG GTCGCTTCTCACACCTCTGATGGCA + +4 cisbp__M6430-EcR-eg-ERR-ftz-f1-Hr3-Hr78-kni-knrl-svp-usp 1 0.00653561 159.815 1 6 CACCTG TGACCTT + +4 predrem__nrMotif2376 -1 0.00653561 159.815 1 5 CACCTG ACCTTTC + +4 transfac_pro__M04771-CTCF -1 0.00653561 159.815 1 5 CACCTG ACCTAGT + +4 taipale__EOMES_DBD_NAGGTGTGAAAWN_repr-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 7 0.00664552 162.503 1 6 CACCTG ATTTTCACACCTT - +4 transfac_public__M00226 3 0.0066565 162.771 1 6 CACCTG ACCTACCCG + +4 hocomoco__TBX3_MOUSE.H11MO.0.B-bi 3 0.0066565 162.771 1 6 CACCTG TAGCACCTT - +4 cisbp__M5017-CG12605-da-esg-HLH54F-Kah-scrt-sna-wor 2 0.00667922 163.327 1 6 CACCTG AACACCTGTTG - +4 cisbp__M2145 0 0.00672445 164.433 1 6 CACCTG TACCTA - +4 jaspar__MA0340.1 0 0.00672445 164.433 1 6 CACCTG TACCTA - +4 hocomoco__RXRB_HUMAN.H11MO.0.C-usp 3 0.00676896 165.521 1 6 CACCTG TGTGACCTCA - +4 transfac_pro__M03889-bi 5 0.00676896 165.521 1 5 CACCTG TCTCACACCT - +4 cisbp__M5896-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0067936 166.124 1 5 CACCTG TCACACCT - +4 taipale__TBX4_DBD_AGGTGTGA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0067936 166.124 1 5 CACCTG TCACACCT - +4 swissregulon__hs__MYOD1.p2-esg-nau-sna-wor 3 0.0070066 171.332 1 6 CACCTG CACCACCTGCTC - +4 stark__AWCAGGTGK-ato 1 0.00720338 176.144 1 6 CACCTG ACACCTGAT - +4 stark__RRCAGGTGB-HLH54F-ac-ase-da-emc-esg-l(1)sc-nau-sc-sna-wor 1 0.00720338 176.144 1 6 CACCTG GCACCTGCC - +4 transfac_pro__M05030 4 0.00720338 176.144 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M05160 4 0.00720338 176.144 1 5 CACCTG AGTCCACCT + +4 cisbp__M5396-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 7 0.007234 176.893 1 6 CACCTG ATTTTCACACCTT - +4 flyfactorsurvey__sna_SANGER_10_FBgn0003448-sna 1 0.00733742 179.422 1 6 CACCTG CCACCTGTTA + +4 taipale__ZNF784_full_GTACCTACCT_repr 1 0.00733742 179.422 1 6 CACCTG GTACCTACCT + +4 cisbp__M1631-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00733742 179.422 1 6 CACCTG TTCACACCTT - +4 cisbp__M5980 1 0.00733742 179.422 1 6 CACCTG GTACCTACCT - +4 taipale_cyt_meth__SNAI3_NRCAGGTGCR_FL_meth-esg-sna-wor 2 0.00733742 179.422 1 6 CACCTG TGCACCTGTT - +4 taipale_cyt_meth__TCF4_NCACSTGN_eDBD-ase-da-esg-l(1)sc-sc-sna-wor 1 0.00734188 179.531 1 6 CACCTG GCACCTGC + +4 cisbp__M6468-esg-sna-wor 1 0.00734188 179.531 1 6 CACCTG CCACCTGG - +4 flyfactorsurvey__vfl_SANGER_5_FBgn0259789-zld 1 0.00734188 179.531 1 6 CACCTG CTACCTGC - +4 taipale_cyt_meth__TBX20_NAGGTGTGANNNTCACACCTN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 15 0.00737293 180.29 1 6 CACCTG GAGGTGTGAATTTCACACCTC + +4 cisbp__M5202-esg-Kah-sna 1 0.00737399 180.316 1 6 CACCTG CCACCTGTTACCCC - +4 hocomoco__PPARD_HUMAN.H11MO.0.D-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 1 0.00737399 180.316 1 6 CACCTG TGACCTTTGTCCTA - +4 cisbp__M3131 1 0.00743583 181.828 1 6 CACCTG GTACCGGTATCGGTGC + +4 swissregulon__hs__ZEB1.p2-zfh1 3 0.00761478 186.204 1 6 CACCTG CCGCACCTGGGC + +4 transfac_pro__M03547 1 0.00764102 186.846 1 6 CACCTG TGACCTG + +4 cisbp__M6434-eg-kni-knrl 1 0.0077891 190.467 1 6 CACCTG TGACCTTTG + +4 cisbp__M0184-ac-da-Hand-sc 1 0.0077891 190.467 1 6 CACCTG ACACCTGCT - +4 swissregulon__hs__EOMES.p2-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.0077891 190.467 1 5 CACCTG TTCACACCT - +4 cisbp__M1319 2 0.00786906 192.422 1 6 CACCTG TCTACCTACCT - +4 cisbp__M5895-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00786906 192.422 1 6 CACCTG TTTCACACCTT - +4 hocomoco__TBX3_HUMAN.H11MO.0.C-bi 4 0.00786906 192.422 1 6 CACCTG TTCCCACCTCC - +4 jaspar__MA1038.1 2 0.00786906 192.422 1 6 CACCTG TCTACCTACCT - +4 neph__UW.Motif.0138 4 0.00786906 192.422 1 6 CACCTG TCAGCACCATG - +4 tfdimers__MD00062 12 0.00791465 193.537 1 6 CACCTG TTTACCAATTAACACCTTCTTTAA - +4 transfac_pro__M07477-ac-da-emc-esg-sc-sna-wor 1 0.0079323 193.969 1 6 CACCTG GCACCTGC - +4 hocomoco__TBX5_HUMAN.H11MO.0.D-bi-mid-org-1 3 0.0079323 193.969 1 5 CACCTG TCACACCT - +4 cisbp__M0185 3 0.00794548 194.291 1 6 CACCTG GAACACCTGC + +4 taipale_cyt_meth__HAND2_AACACCTGYN_eDBD-Hand 2 0.00794548 194.291 1 6 CACCTG AACACCTGCA + +4 cisbp__M5201-sna 1 0.00794548 194.291 1 6 CACCTG CCACCTGTTA - +4 taipale_cyt_meth__SNAI3_NRCAGGTGCR_FL-esg-sna-wor 2 0.00794548 194.291 1 6 CACCTG TGCACCTGTT - +4 cisbp__M6432-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 1 0.00802611 196.262 1 6 CACCTG TGACCTTTGTCCTA + +4 flyfactorsurvey__sna_SOLEXA_5_FBgn0003448-Kah-sna 1 0.00802611 196.262 1 6 CACCTG CCACCTGTTACCCC - +4 transfac_pro__M07859-ash2-Dlip3 3 0.00810193 198.116 1 6 CACCTG TATTACCTTATTATC - +4 transfac_pro__M03542-EcR-eg-ERR-ftz-f1-Hr78-kni-knrl-svp-usp 1 0.00826061 201.997 1 6 CACCTG TGACCTT + +4 transfac_pro__M04806-da-esg-HLH4C-sc-sna-wor-zfh1 1 0.00826061 201.997 1 6 CACCTG ACACCTG + +4 transfac_pro__M01270-eg-kni-knrl-svp 2 0.00826061 201.997 1 5 CACCTG CTGACCT - +4 hocomoco__EOMES_HUMAN.H11MO.0.D 4 0.00826789 202.175 1 6 CACCTG TTAACACCTCCT - +4 taipale_cyt_meth__FIGLA_NNCACCTGN_eDBD_repr 2 0.00841722 205.826 1 6 CACCTG ACCACCTGT + +4 transfac_pro__M05061 4 0.00841722 205.826 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M05065 4 0.00841722 205.826 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M05087 4 0.00841722 205.826 1 5 CACCTG TCTTAACCT + +4 predrem__nrMotif585 4 0.00852802 208.536 1 6 CACCTG GGAGGACCTGG + +4 taipale__TBX2_full_NAGGTGTGAWN-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00852802 208.536 1 6 CACCTG TTTCACACCTT - +4 transfac_pro__M09012-esg-sna-wor 3 0.00854946 209.06 1 6 CACCTG TTGCACCTGTTGC - +4 cisbp__M5265-zld 1 0.00856863 209.529 1 6 CACCTG CTACCTGC - +4 cisbp__M5898-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00856863 209.529 1 5 CACCTG TCACACCT - +4 cisbp__M6505-bi-byn-mid-org-1 3 0.00856863 209.529 1 5 CACCTG TCACACCT - +4 flyfactorsurvey__HLH4C_da_SANGER_5_3_FBgn0000413-HLH4C-da 0 0.00859588 210.195 1 6 CACCTG CACCTGCTCC + +4 cisbp__M1634-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00859588 210.195 1 6 CACCTG TTGACACCTT - +4 predrem__nrMotif471 4 0.00859588 210.195 1 6 CACCTG AGCCCACCTC - +4 taipale_cyt_meth__EOMES_NAGGTGTGAN_eDBD_repr-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00859588 210.195 1 6 CACCTG TTCACACCTC - +4 taipale_cyt_meth__SNAI2_NRCAGGTGCR_FL_meth-esg-sna-wor 2 0.00859588 210.195 1 6 CACCTG CGCACCTGTC - +4 taipale_cyt_meth__TBX21_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.00859588 210.195 1 6 CACCTG TTCACACCTT - +4 flyfactorsurvey__HLH4C_da_SANGER_5_FBgn0000413-HLH4C-da 5 0.00881758 215.616 1 6 CACCTG CAAAACACCTGCGCC + +4 predrem__nrMotif1537 1 0.00892887 218.338 1 6 CACCTG AAACCTT - +4 elemento__ACCTTCA -1 0.00892887 218.338 1 5 CACCTG ACCTTCA + +4 elemento__ACCTTGA -1 0.00892887 218.338 1 5 CACCTG ACCTTGA + +4 transfac_pro__M06332 0 0.00896794 219.293 1 6 CACCTG CACCTGGCTAAC + +4 taipale_cyt_meth__FIGLA_NMCACCTGN_eDBD_meth-CG8319 2 0.00909183 222.323 1 6 CACCTG ACCACCTGT + +4 cisbp__M6316-esg-sna-wor-zfh1 2 0.00909183 222.323 1 6 CACCTG TGCACCTGG - +4 hocomoco__ITF2_MOUSE.H11MO.0.B-esg-sna-wor-zfh1 2 0.00909183 222.323 1 6 CACCTG TGCACCTGG - +4 taipale_cyt_meth__TCF4_NCACCTGN_eDBD_meth-ac-ase-da-esg-sc-sna-wor 1 0.00925445 226.299 1 6 CACCTG GCACCTGC + +4 cisbp__M2889 3 0.00925445 226.299 1 5 CACCTG ATGTACCT + +4 transfac_public__M00502 3 0.00925445 226.299 1 5 CACCTG ATGTACCT + +4 homer__AGGTGTCA_Tbx5-bi 3 0.00925445 226.299 1 5 CACCTG TGACACCT - +4 taipale__TBX5_DBD_AGGTGTGA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.00925445 226.299 1 5 CACCTG TCACACCT - +4 flyfactorsurvey__sna_FlyReg_FBgn0003448-sna 1 0.00929211 227.22 1 6 CACCTG CCACCTGCTT + +4 taipale__TCF3_DBD_NNCACCTGNN-ac-da-Hand-sc 2 0.00929211 227.22 1 6 CACCTG AACACCTGCT + +4 taipale__TCF4_DBD_NNCACCTGNN 2 0.00929211 227.22 1 6 CACCTG CGCACCTGCT + +4 cisbp__M5200-sna 1 0.00929211 227.22 1 6 CACCTG CCACCTGCTA - +4 cisbp__M5900-da-Hand-sc 2 0.00929211 227.22 1 6 CACCTG AACACCTGCT - +4 cisbp__M5873-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00929211 227.22 1 5 CACCTG TTTCACACCT - +4 taipale__TBR1_DBD_AGGTGTGANN-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.00929211 227.22 1 5 CACCTG TTTCACACCT - +4 transfac_pro__M03856-bi 8 0.00958799 234.455 1 6 CACCTG CATTCTCACACCTGT + +4 transfac_public__M00414-zfh1 3 0.0097172 237.615 1 6 CACCTG CTGCACCTGTGC + +4 predrem__nrMotif993 2 0.00981713 240.058 1 6 CACCTG ACCACCTTT + +4 predrem__nrMotif1032 0 0.00981713 240.058 1 6 CACCTG CACCTTCCC - +4 predrem__nrMotif444 0 0.00981713 240.058 1 6 CACCTG AACCTCAAA - +4 transfac_pro__M05063 4 0.00981713 240.058 1 5 CACCTG TCTTAACCT + +4 tfdimers__MD00294-Hnf4-Ing5-svp 6 0.00984212 240.669 1 6 CACCTG CCCCCCCACCTGGCCCTTCCCCC - +4 flyfactorsurvey__scrt_SANGER_2.5_FBgn0004880-CG12605-HLH54F-Kah-da-net-scrt-tx 2 0.00998643 244.198 1 6 CACCTG ACCACCTGTTG + +4 cisbp__M1305 1 0.0100382 245.464 1 6 CACCTG TTACCTACCG + +4 taipale__FIGLA_DBD_NNCACCTGNN-CG12605-da-scrt-tx 2 0.0100382 245.464 1 6 CACCTG ACCACCTGTT + +4 cisbp__M5901 2 0.0100382 245.464 1 6 CACCTG CGCACCTGCT - +4 taipale_cyt_meth__SNAI1_NRCAGGTGCR_FL_meth-esg-sna-wor 2 0.0100382 245.464 1 6 CACCTG CGCACCTGCT - +4 taipale_cyt_meth__SNAI1_NRCAGGTGYR_eDBD_meth-ac-ase-esg-l(1)sc-sc-sna-wor 2 0.0100382 245.464 1 6 CACCTG TGCACCTGCC - +4 taipale_cyt_meth__SNAI2_NRCAGGTGCA_FL-esg-sna-wor 2 0.0100382 245.464 1 6 CACCTG TGCACCTGTT - +4 taipale_cyt_meth__SNAI2_NRCAGGTGCR_eDBD_meth-esg-sna-wor 2 0.0100382 245.464 1 6 CACCTG TGCACCTGTT - +4 taipale_cyt_meth__TBX3_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0100382 245.464 1 6 CACCTG TTCACACCTC - +4 cisbp__M5894-org-1 3 0.0101088 247.19 1 6 CACCTG TCACACCTTTTAGGTGTGA + +4 taipale__TBX21_full_TNACACCTNNNAGGTGTNA-org-1 3 0.0101088 247.19 1 6 CACCTG TCACACCTTTTAGGTGTGA - +4 taipale__TBX15_DBD_AGGTGTGAANTTCACACCT_repr-bi-byn-Doc2-H15-mid-org-1 14 0.0101088 247.19 1 5 CACCTG AGGTGTGAATTTCACACCT - +4 cisbp__M5014-da-HLH4C 5 0.0104162 254.707 1 6 CACCTG AAAAACACCTGCGCC + +4 transfac_pro__M07474-H15-mid-org-1 8 0.0104162 254.707 1 6 CACCTG TCGCCTCACACCTCC - +4 transfac_public__M00181 1 0.010447 255.46 1 6 CACCTG GCACCGGTTTCGGTTC - +4 neph__UW.Motif.0090 3 0.0105184 257.207 1 6 CACCTG AGCTTCCTGCCT + +4 tiffin__TIFDMEM0000088 2 0.0105184 257.207 1 6 CACCTG GTCAGCTGAGCT + +4 transfac_pro__M06593 2 0.0105184 257.207 1 6 CACCTG TGTACCTGGTCT + +4 cisbp__M2954-zfh1 3 0.0105184 257.207 1 6 CACCTG CTGCACCTGTGC - +4 swissregulon__hs__LMO2.p2-GATAe-grn-pnr 3 0.0105184 257.207 1 6 CACCTG CAGCACCTGCCG - +4 cisbp__M1447-ERR-ftz-f1-Hr3-Hr39-Hr78 2 0.0105975 259.14 1 6 CACCTG ATGACCTTG + +4 cisbp__M0207-zfh1 2 0.0105975 259.14 1 6 CACCTG CACACCTGG - +4 transfac_pro__M04781-EcR-eg-Hr78-kni-knrl-svp-usp -1 0.0105975 259.14 1 5 CACCTG ACCTTTGAC + +4 transfac_pro__M05091 4 0.0105975 259.14 1 5 CACCTG TCTTAACCT + +4 predrem__nrMotif1015 0 0.0107889 263.822 1 6 CACCTG CACCTTTT - +4 transfac_pro__M02000-ERR 1 0.0107889 263.822 1 6 CACCTG TGACCTTG - +4 transfac_pro__M05347-Hr78 2 0.0107889 263.822 1 6 CACCTG TTGACCTT - +4 hdpi__AGGF1-CG8079 -1 0.0107889 263.822 1 5 CACCTG ACCTCCCC - +4 transfac_pro__M05323-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG CTTTCACACCT - +4 transfac_pro__M05324-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG CTTTCACACCT - +4 transfac_pro__M05325-bi-byn-Doc2-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG ATTTCACACCT - +4 transfac_pro__M05346-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG CTTTCACACCT - +4 transfac_pro__M05365-bi-byn-Doc2-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG ATTTCACACCT - +4 transfac_pro__M05416-bi-byn-Doc2-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG ATTTCACACCT - +4 transfac_pro__M05443-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG TTTTCACACCT - +4 transfac_pro__M05458-bi-byn-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG ATTTCACACCT - +4 transfac_pro__M05497-bi-byn-H15-mid-org-1 6 0.0107929 263.918 1 5 CACCTG ATTTAACACCT - +4 cisbp__M5430-CG12605-da-scrt-tx 2 0.0108387 265.039 1 6 CACCTG AACACCTGTT + +4 homer__NNCACCTGCN_E2A-da-sc 2 0.0108387 265.039 1 6 CACCTG CACACCTGCA + +4 cisbp__M5010-da-HLH4C 0 0.0108387 265.039 1 6 CACCTG CACCTGCGCC - +4 hocomoco__HTF4_MOUSE.H11MO.0.A 2 0.0108387 265.039 1 6 CACCTG CCCACCTGCT - +4 hocomoco__SNAI2_HUMAN.H11MO.0.A-ac-ase-emc-esg-l(1)sc-sc-sna-wor 2 0.0108387 265.039 1 6 CACCTG TGCACCTGCC - +4 taipale_cyt_meth__SNAI2_NRCAGGTGCR_eDBD-esg-sna-wor 2 0.0108387 265.039 1 6 CACCTG TGCACCTGTT - +4 transfac_pro__M03879 4 0.0109049 266.659 1 6 CACCTG CTTCCACCTACCC + +4 cisbp__M5880-bi-byn-Doc2-H15-mid-org-1 14 0.0110083 269.187 1 5 CACCTG AGGTGTGAATTTCACACCT - +4 transfac_pro__M03582-twi 0 0.0112597 275.334 1 6 CACCTG CACCTGG + +4 elemento__AAGGTGA 1 0.0112597 275.334 1 6 CACCTG TCACCTT - +4 elemento__CAAGGTG 0 0.0112597 275.334 1 6 CACCTG CACCTTG - +4 predrem__nrMotif2453 3 0.0112597 275.334 1 4 CACCTG TGACACC - +4 hocomoco__ZIC2_HUMAN.H11MO.0.D-CG9650-HDAC1-opa 3 0.011305 276.441 1 6 CACCTG GGCCCCCTGCTGTGA + +4 flyfactorsurvey__esg-F3-5_SOLEXA_FBgn0001981-esg 8 0.011305 276.441 1 6 CACCTG ACCCCATGCACCTGC - +4 cisbp__M2376 2 0.011375 278.154 1 6 CACCTG ATCACCTGAGGC + +4 jaspar__MA0583.1 2 0.011375 278.154 1 6 CACCTG ATCACCTGAGGC + +4 transfac_pro__M05496-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 6 0.011375 278.154 1 6 CACCTG ATTTCACACCTA + +4 taipale_cyt_meth__TBX1_NWAGGTGTGARN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.011375 278.154 1 6 CACCTG TTTCACACCTTC - +4 cisbp__M0219-zfh1 2 0.0114371 279.671 1 6 CACCTG CACACCTGG - +4 cisbp__M4702-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 1 0.0116449 284.752 1 6 CACCTG TGACCTTT + +4 flyfactorsurvey__Hr78_SANGER_5_FBgn0015239-EcR-Hr78-eg-kni-knrl-svp-usp 1 0.0116449 284.752 1 6 CACCTG TGACCTCT - +4 elemento__ACCTTGGC -1 0.0116449 284.752 1 5 CACCTG ACCTTGGC + +4 elemento__AAGAAGGT -1 0.0116449 284.752 1 5 CACCTG ACCTTCTT - +4 hdpi__PTCD1-CG4611 -1 0.0116449 284.752 1 5 CACCTG ACATTACC - +4 idmmpmm__Med-Med 3 0.0116565 285.036 1 6 CACCTG TTTCGCCTGTT - +4 predrem__nrMotif206 4 0.0116984 286.061 1 6 CACCTG TGCATTCCTG - +4 taipale__TBX1_DBD_TYTCACACCTNNNAGGTGTGARA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.0117204 286.6 1 6 CACCTG TTTCACACCTCAGAGGTGTGAGA + +4 cisbp__M5878-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.0117204 286.6 1 6 CACCTG TTTCACACCTCAGAGGTGTGAGA - +4 yetfasco__YMR037C_1380-CG10348-CG13296-ham 1 0.012158 297.3 1 6 CACCTG ACCCCTT - +4 transfac_pro__M06347 12 0.0121627 297.414 1 6 CACCTG GTAGTAGGAGTAGACCTC + +4 taipale_cyt_meth__TBX20_NAGGTGTGAASGYGTGAN_eDBD_meth-bi-Doc1-Doc2-Doc3-H15-mid-org-1 12 0.0121627 297.414 1 6 CACCTG TTCACGCGTTCACACCTT - +4 transfac_pro__M03855-bi 8 0.0122573 299.727 1 6 CACCTG TATTCTCACACCTGC + +4 neph__UW.Motif.0307 0 0.0122573 299.727 1 6 CACCTG CACCATGTGGTTTTT - +4 transfac_pro__M09000-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 0 0.0122573 299.727 1 6 CACCTG GACCTTTGACCTACT - +4 neph__UW.Motif.0345 5 0.0122913 300.56 1 6 CACCTG ACTTCTTCCTCT - +4 transfac_pro__M05722-Aef1 1 0.0122913 300.56 1 6 CACCTG ATACCTTAACCC - +4 hocomoco__ERR3_HUMAN.H11MO.0.B-ERR-EcR-Hr39-ftz-f1-usp 1 0.0123401 301.753 1 6 CACCTG TGACCTTGA - +4 transfac_pro__M04987 4 0.0123401 301.753 1 5 CACCTG ACTTAACCT + +4 taipale_cyt_meth__TBX19_NANGTGTKANNNTNACACCTN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 15 0.0124583 304.644 1 6 CACCTG GACGTGTGAAATTCACACCTT + +4 cisbp__M5036-EcR-eg-Hr78-kni-knrl-svp-usp 1 0.0125651 307.253 1 6 CACCTG TGACCTCT + +4 taipale_cyt_meth__TCF12_NCACSTGN_eDBD_meth-ac-ase-da-esg-sc-sna-wor 1 0.0125651 307.253 1 6 CACCTG ACACCTGC + +4 transfac_pro__M09551 0 0.0125651 307.253 1 6 CACCTG CACCTACC + +4 cisbp__M1335 0 0.0125651 307.253 1 6 CACCTG CACCTACC - +4 cisbp__M4513-zfh1 1 0.0125651 307.253 1 6 CACCTG ACACCTGG - +4 taipale__MGA_DBD_AGGTGTGA-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0125651 307.253 1 5 CACCTG TCACACCT - +4 taipale_cyt_meth__ZNF784_STACYTACCKY_FL_repr 1 0.0125825 307.679 1 6 CACCTG GTACCTACCGC + +4 cisbp__M5182-CG12605-da-HLH54F-Kah-net-scrt-tx 2 0.0125825 307.679 1 6 CACCTG ACCACCTGTTG - +4 hocomoco__SNAI2_MOUSE.H11MO.0.A-esg-sna-wor 3 0.0125825 307.679 1 6 CACCTG ATGCACCTGCC - +4 hocomoco__ESR1_HUMAN.H11MO.1.A-ERR 3 0.0126222 308.651 1 6 CACCTG GGTGACCTTG - +4 hocomoco__THB_HUMAN.H11MO.1.D-EcR 1 0.0126222 308.651 1 6 CACCTG TGACCTGACC - +4 predrem__nrMotif470 0 0.0126222 308.651 1 6 CACCTG CAGCTGCTCC - +4 stark__RRNNNMCACCTGC-ac 6 0.0127617 312.061 1 6 CACCTG AAAAAACACCTGC + +4 transfac_pro__M07952-esg-sna-wor 3 0.0127617 312.061 1 6 CACCTG ATACACCTGTTAC - +4 transfac_pro__M09286 3 0.0130847 319.96 1 6 CACCTG TTATACCTAACTTT - +4 taipale_cyt_meth__T_NANGTGTGANNNNTNACACCTN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 16 0.0131825 322.353 1 6 CACCTG GAGGTGTGAAATTTCACACCTT + +4 transfac_pro__M07947-esg-sna-wor 2 0.0132722 324.544 1 6 CACCTG TGCACCTGTTGC - +4 taipale_tf_pairs__ALX4_TBX21_RGGTGYTAATWR_CAP 7 0.0132722 324.544 1 5 CACCTG TAATTAACACCT - +4 taipale_tf_pairs__MGA_DLX3_AGGTGNTAATKR_CAP 7 0.0132722 324.544 1 5 CACCTG CAATTAACACCT - +4 hocomoco__ZIC2_MOUSE.H11MO.0.C-CG9650-HDAC1-opa 3 0.0132762 324.642 1 6 CACCTG GGCCCCCTGCTGAGA + +4 hocomoco__ZIC3_HUMAN.H11MO.0.B-CG9650-HDAC1-opa 3 0.0132762 324.642 1 6 CACCTG GGCCCCCTGCTGTGA + +4 cisbp__M6216-EcR-ERR-ftz-f1-Hr39-usp 1 0.0133108 325.489 1 6 CACCTG TGACCTTGA + +4 predrem__nrMotif1177 0 0.0133108 325.489 1 6 CACCTG TTCCTGCTA + +4 predrem__nrMotif1292 1 0.0133108 325.489 1 6 CACCTG CAACCTGCA + +4 predrem__nrMotif1300 2 0.0133108 325.489 1 6 CACCTG AAAACCTGG + +4 predrem__nrMotif556 3 0.0133108 325.489 1 6 CACCTG TGGCACCTG + +4 transfac_pro__M05062 4 0.0133108 325.489 1 5 CACCTG ACTTAACCT + +4 transfac_pro__M05128 4 0.0133108 325.489 1 5 CACCTG ACTTAACCT + +4 cisbp__M3153 1 0.0133513 326.48 1 6 CACCTG GCACCGGTTTCGGTTC + +4 taipale_tf_pairs__MGA_DLX2_SYAATTANWGGTGYGA_CAP 3 0.0133513 326.48 1 6 CACCTG TCACACCTTTAATTGC - +4 cisbp__M5883-H15-mid-org-1 11 0.0133513 326.48 1 5 CACCTG TCACACCTTCACACCT + +4 taipale__TBX20_DBD_AGGTGTGAAGGTGTGA_repr-Doc2-H15-mid-org-1 11 0.0133513 326.48 1 5 CACCTG TCACACCTTCACACCT - +4 factorbook__ZEB1-zfh1 1 0.0135537 331.429 1 6 CACCTG ACACCTGG + +4 cisbp__M0186-da-emc-GATAe-grn-pnr-sc-zfh1 1 0.0135537 331.429 1 6 CACCTG GCACCTGC - +4 jaspar__MA1039.1 0 0.0135537 331.429 1 6 CACCTG CACCTACC - +4 cisbp__M5628-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 3 0.0135537 331.429 1 5 CACCTG TCACACCT - +4 cisbp__M6524-EcR 1 0.0136149 332.925 1 6 CACCTG TGACCTGACC + +4 predrem__nrMotif1462 4 0.0136149 332.925 1 6 CACCTG CAGGGACCTG + +4 predrem__nrMotif1815 0 0.0136149 332.925 1 6 CACCTG TTCCTTCTTA - +4 taipale_cyt_meth__TBX6_NAGGTGTGAN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0136149 332.925 1 6 CACCTG TTCACACCTC - +4 cisbp__M6431-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 1 0.0137875 337.146 1 6 CACCTG TGACCTTTGACCT + +4 jaspar__MA0574.1 1 0.0137875 337.146 1 6 CACCTG CCACCTACCGTCG - +4 transfac_pro__M07953-emc-sna-wor 3 0.0137875 337.146 1 6 CACCTG ATACACCTGTCGC - +4 taipale_cyt_meth__NFKB2_NGGGGAWNYMCCN_eDBD_meth_repr-Rel 8 0.0137875 337.146 1 5 CACCTG AGGGGAAGCACCT + +4 cisbp__M5891-org-1 3 0.0141391 345.742 1 6 CACCTG TCACACCTTAAAGGTGTGA + +4 taipale__TBX21_DBD_TNACACCTNNNAGGTGTNA_repr-org-1 3 0.0141391 345.742 1 6 CACCTG TCACACCTTAAAGGTGTGA + +4 taipale_cyt_meth__THRB_NYGACCTNNNNYGACCTYN_FL-EcR-ERR 2 0.0141391 345.742 1 6 CACCTG GTGACCTTACGTGACCTTA + +4 cisbp__M5876-bi-byn-Doc2-H15-mid-org-1 14 0.0141391 345.742 1 5 CACCTG AGGTGTGAAATTCACACCT + +4 taipale__TBX1_DBD_AGGTGTGAAWTTCACACCT-bi-byn-Doc2-H15-mid-org-1 14 0.0141391 345.742 1 5 CACCTG AGGTGTGAAATTCACACCT - +4 transfac_pro__M07920-CG12605-CG17802-Kah-scrt 4 0.0141464 345.922 1 6 CACCTG CAACCACCTGTTAC - +4 transfac_pro__M09292 3 0.0141464 345.922 1 6 CACCTG TTTCACCTAATTTT - +4 predrem__nrMotif708 2 0.0141608 346.273 1 5 CACCTG AGCACCT + +4 taipale_cyt_meth__TBX18_NRAGGTGTGAAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.0143232 350.245 1 6 CACCTG TTTCACACCTTT - +4 taipale_cyt_meth__TBX1_NNAGGTGTGANN_eDBD_meth-bi-Doc1-Doc2-Doc3-org-1 5 0.0143232 350.245 1 6 CACCTG ATTCACACCTCC - +4 cisbp__M1431-EcR-Hr3-Hr78-svp-usp 2 0.0143534 350.984 1 6 CACCTG GTGACCTCT + +4 predrem__nrMotif1422 1 0.0143534 350.984 1 6 CACCTG TCACCTGTC + +4 predrem__nrMotif817 1 0.0143534 350.984 1 6 CACCTG AAACCTGTG - +4 taipale_cyt_meth__GCM2_RTGNKGGTN_FL_meth_repr-gcm-gcm2 0 0.0143534 350.984 1 6 CACCTG TACCCGCAT - +4 transfac_pro__M05064 4 0.0143534 350.984 1 5 CACCTG ACTTAACCT + +4 transfac_pro__M09276 3 0.0143653 351.275 1 6 CACCTG TTTCACCTAATTTTT - +4 transfac_pro__M02747-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 8 0.0144441 353.202 1 6 CACCTG AATTTTCACACCTTTTC - +4 transfac_pro__M01488-achi-esg-hth-sna-vis-wor 3 0.0144597 353.582 1 6 CACCTG AAGGACCTGTCAATAC + +4 elemento__ACAAGGTG 0 0.0146152 357.385 1 6 CACCTG CACCTTGT - +4 predrem__nrMotif318 3 0.0146152 357.385 1 5 CACCTG TCAGACCT + +4 predrem__nrMotif352 5 0.0146428 358.059 1 6 CACCTG CTGCCCACCTC - +4 transfac_pro__M08820-ac-ase-l(1)sc-sc 3 0.0146813 359.002 1 6 CACCTG CTACACCTGC + +4 hocomoco__RARA_HUMAN.H11MO.1.A-EcR-Hr78-svp-usp 4 0.0146813 359.002 1 6 CACCTG CCCTGACCTT - +4 transfac_pro__M07899-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0146813 359.002 1 6 CACCTG TTCACACCTC - +4 homer__ATTAACACCT_Eomes-byn 5 0.0146813 359.002 1 5 CACCTG ATTAACACCT + +4 tfdimers__MD00076-eg-kni-knrl 17 0.0147695 361.16 1 6 CACCTG ATATTTGGTTAATTATTAACCTATTTTT + +4 factorbook__ESR1-ERR-EcR 10 0.0150676 368.448 1 6 CACCTG AGGTCAGGGTGACCTGGAAC - +4 transfac_pro__M02018 0 0.0152731 373.474 1 6 CACCTG CACCTGC + +4 transfac_pro__M07367-esg-sna-wor 7 0.0152814 373.677 1 6 CACCTG CGCGGCGCACCTGC + +4 neph__UW.Motif.0599 5 0.0152814 373.677 1 6 CACCTG CCTGCCACTTCCTG - +4 transfac_pro__M06502 9 0.0152814 373.677 1 5 CACCTG GTCCGAGGGAACCT + +4 transfac_pro__M01263-bi-byn-Doc2-H15-mid-org-1 14 0.01534 375.109 1 5 CACCTG AGGTGTGAATTTCACACCT + +4 hocomoco__PPARA_MOUSE.H11MO.1.A-ERR-EcR-Hnf4-Hr3-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0154725 378.348 1 6 CACCTG TGACCTTTG - +4 predrem__nrMotif1937 1 0.0154725 378.348 1 6 CACCTG CAACCTCTG - +4 transfac_pro__M05072 4 0.0154725 378.348 1 5 CACCTG ACTCAACCT + +4 cisbp__M5266-zld 4 0.0155291 379.734 1 6 CACCTG CGCCTACCTGCCACA - +4 taipale_cyt_meth__NR2F1_NRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0155291 379.734 1 6 CACCTG TTGACCTTTGACCTT - +4 transfac_pro__M08896-zfh1 5 0.0155291 379.734 1 6 CACCTG GGTGACACCTGGTTG - +4 taipale__MGA_DBD_AGGTGTKANNTMACACCT_repr-bi-byn-org-1 13 0.0155357 379.895 1 5 CACCTG AGGTGTGACTTCACACCT - +4 hocomoco__THA_HUMAN.H11MO.0.C-EcR-usp 2 0.0156417 382.487 1 6 CACCTG CTGACCTGAAGTGACCC - +4 neph__UW.Motif.0201 0 0.0156443 382.55 1 6 CACCTG CAGCTGCTGTTTTTTT - +4 cisbp__M1492 2 0.0157541 385.235 1 6 CACCTG TTGACCTG + +4 transfac_pro__M00973-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 0 0.0157541 385.235 1 6 CACCTG CACCTGTC + +4 hocomoco__RARG_HUMAN.H11MO.1.B-EcR 2 0.0157541 385.235 1 6 CACCTG CTGACCTC - +4 scertf__fordyce.AFT2 2 0.0157541 385.235 1 6 CACCTG CACACCCC - +4 hocomoco__RARB_HUMAN.H11MO.0.D-EcR 5 0.0157879 386.062 1 6 CACCTG GCCCTGACCTC - +4 predrem__nrMotif368 4 0.0157879 386.062 1 6 CACCTG TGGGGACCTGG - +4 neph__UW.Motif.0143 6 0.0157879 386.062 1 5 CACCTG ACTGAAAACAT + +4 predrem__nrMotif647 1 0.0158262 386.999 1 6 CACCTG AAACCTGCCT + +4 transfac_pro__M07905-YL-1 2 0.0158262 386.999 1 6 CACCTG ACCACCTCAC - +4 predrem__nrMotif1792 5 0.0158262 386.999 1 5 CACCTG TTTTTAACCT - +4 cisbp__M6504-bi 7 0.0159125 389.108 1 6 CACCTG TTTTTAACACCTAATTCTCTTCCT - +4 taipale_cyt_meth__TBX19_NANGTGTKANNNTNACACCTN_eDBD_meth_repr-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 15 0.0159952 391.132 1 6 CACCTG AACGTGTGAAATTCACACCTT + +4 cisbp__M5879-org-1 4 0.0163462 399.713 1 6 CACCTG TTCACACCTAGAGGTGTGAA + +4 dbcorrdb__ZNF274__ENCSR000EVR_1__m5 1 0.0163462 399.713 1 6 CACCTG ATACCTTATTAAACATCAGA - +4 hocomoco__ZN708_HUMAN.H11MO.0.C 4 0.0163462 399.713 1 6 CACCTG GCTGTACCTGCTTATTAGGC - +4 taipale__TBX1_DBD_YTCACACCTNNAGGTGTGAR_repr-Doc2-org-1 4 0.0163462 399.713 1 6 CACCTG TTCACACCTAGAGGTGTGAA - +4 tfdimers__MD00117 6 0.0164389 401.981 1 6 CACCTG CCCCGCCACCTGTCACTGCCCCT - +4 cisbp__M1422-Hr3-Hr78 1 0.0164641 402.596 1 6 CACCTG TGACCTC + +4 predrem__nrMotif795 0 0.0164641 402.596 1 6 CACCTG AACCTTT - +4 yetfasco__YGL071W_658 2 0.0164641 402.596 1 5 CACCTG TGCACCC + +4 elemento__AGGTCAC 2 0.0164641 402.596 1 5 CACCTG GTGACCT - +4 neph__UW.Motif.0014 8 0.0164956 403.367 1 6 CACCTG CATGAATACACTTG - +4 taipale_tf_pairs__MYBL1_TBX21_AGGTGTGNCSGTTR_CAP_repr-Myb 9 0.0164956 403.367 1 5 CACCTG CAACGGTCACACCT - +4 transfac_pro__M09308 10 0.0166261 406.558 1 6 CACCTG CATTTCCAACCACCTTTTC + +4 cisbp__M5884-bi-byn-Doc2-H15-mid-org-1 14 0.0166261 406.558 1 5 CACCTG AGGTGTGAATTTCACACCT + +4 taipale__TBX20_DBD_AGGTGTGAWWWTCACACCT-bi-byn-Doc2-H15-mid-org-1 14 0.0166261 406.558 1 5 CACCTG AGGTGTGAATTTCACACCT - +4 neph__UW.Motif.0218 3 0.0166592 407.367 1 6 CACCTG AAGCAGCTTTGC + +4 hocomoco__PPARA_HUMAN.H11MO.1.B-ERR-EcR-Hr78-eg-kni-knrl-svp-usp 2 0.0166728 407.699 1 6 CACCTG CTGACCTTT + +4 transfac_pro__M05159 4 0.0166728 407.699 1 5 CACCTG ACTTAACCT + +4 predrem__nrMotif621 -1 0.0166728 407.699 1 5 CACCTG ACCTCTTCC - +4 neph__UW.Motif.0405 4 0.0167731 410.153 1 6 CACCTG AGCTTCCCTGTCCTG + +4 transfac_pro__M09301 5 0.0167731 410.153 1 6 CACCTG TTGTTCACCTACCTT + +4 flyfactorsurvey__vfl_SOLEXA_5_FBgn0259789-zld 4 0.0167731 410.153 1 6 CACCTG CGCCTACCTGCCACA - +4 transfac_pro__M07972-ash2-Dlip3 3 0.0167731 410.153 1 6 CACCTG TATTACCTTATTATC - +4 cisbp__M5629-bi-byn-org-1 13 0.0168224 411.357 1 5 CACCTG AGGTGTGACTTCACACCT - +4 transfac_pro__M01264-bi-Doc1-Doc2-Doc3-H15-mid-org-1 13 0.0168224 411.357 1 5 CACCTG TTTCACACCTTAACACCT - +4 neph__UW.Motif.0554 4 0.01691 413.5 1 6 CACCTG GCCCCACCATCTGCCA + +4 transfac_public__M00125-bs 1 0.01691 413.5 1 6 CACCTG TTACCTGATTAGGAAA - +4 cisbp__M6522-EcR-usp 2 0.0169216 413.784 1 6 CACCTG CTGACCTGAAGTGACCC + +4 transfac_pro__M01374-Six4 8 0.0169216 413.784 1 6 CACCTG ATAAATGACACCTATCA + +4 cisbp__M6541 2 0.0169216 413.784 1 6 CACCTG CCCACCTGCCATCTAGG - +4 taipale_tf_pairs__GCM2_TBX21_NNNCGGGNNNGGTGTNN_CAP_repr-gcm-gcm2 3 0.0169216 413.784 1 6 CACCTG TCACACCTAGCCCGCAT - +4 cisbp__M1449-ERR-ftz-f1-Hr39-srl 1 0.0169752 415.096 1 6 CACCTG TGACCTTG + +4 cisbp__M0538-CG6769 1 0.0169752 415.096 1 6 CACCTG GCCCCTGA - +4 cisbp__M0683 5 0.017017 416.116 1 6 CACCTG GAATGTATCTG + +4 transfac_pro__M08839 1 0.017017 416.116 1 6 CACCTG GTACCTAACTT - +4 homer__GTGACCTTGA_Esrrb-ERR-Hr4-ftz-f1 2 0.0170545 417.035 1 6 CACCTG GTGACCTTGA + +4 predrem__nrMotif1625 0 0.0170545 417.035 1 6 CACCTG AACCTCTGAG + +4 cisbp__M0814-gcm-gcm2 0 0.0170545 417.035 1 6 CACCTG TACCCGCATC - +4 neph__UW.Motif.0109 3 0.0170545 417.035 1 6 CACCTG GAAGTCCTGG - +4 hdpi__RPS10-RpS10a 1 0.0171342 418.983 1 5 CACCTG TGACCT - +4 transfac_pro__M09326 3 0.0173207 423.544 1 6 CACCTG TCTCACCTACCTC + +4 transfac_pro__M09299 3 0.0173207 423.544 1 6 CACCTG CTTCACCTACCTT - +4 transfac_pro__M08963-EcR-eg-ERR-ftz-f1-Hr3-Hr4-Hr78-kni-knrl-svp-usp 1 0.0177366 433.714 1 6 CACCTG TGACCTT - +4 homer__CACAGCAGGGGG_Unknown-ESC-element-CG9650-HDAC1-opa 1 0.0179562 439.082 1 6 CACCTG CCCCCTGCTGTG - +4 neph__UW.Motif.0655 6 0.0179562 439.082 1 6 CACCTG CAGCCCTTCCTT - +4 neph__UW.Motif.0591 -1 0.0179562 439.082 1 5 CACCTG AGCTGTGTGACT + +4 transfac_pro__M06589 7 0.0179562 439.082 1 5 CACCTG GCCCTCCTACCT - +4 cisbp__M6214-ERR-ftz-f1-Hr4-srl 1 0.0179592 439.157 1 6 CACCTG TGACCTTGA + +4 flyfactorsurvey__net_da_SANGER_10_FBgn0000413-CG8319-CG12605-Kah-da-net-scrt 2 0.0179592 439.157 1 6 CACCTG ACCACCTGT + +4 predrem__nrMotif1116 0 0.0179592 439.157 1 6 CACCTG TACCTCACA + +4 predrem__nrMotif430 0 0.0179592 439.157 1 6 CACCTG CACTTTCTC + +4 predrem__nrMotif2004 0 0.0179592 439.157 1 6 CACCTG GACCTGCTG - +4 taipale_cyt_meth__RARG_NRGGTCAYN_FL_meth_repr-EcR-Hr78-usp 3 0.0179592 439.157 1 6 CACCTG CGTGACCTT - +4 predrem__nrMotif1478 4 0.0179592 439.157 1 5 CACCTG CCAAGACCT - +4 transfac_pro__M09323 10 0.0180016 440.193 1 6 CACCTG ATTTCCCAACTACCTTCTA - +4 neph__UW.Motif.0470 4 0.0181034 442.681 1 6 CACCTG TGAAAAGCTGCTTAA + +4 taipale_cyt_meth__NR2F1_NRGGTCAAAGGTCAN_FL_meth-EcR-eg-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0181034 442.681 1 6 CACCTG GTGACCTTTGACCTC - +4 taipale_cyt_meth__TBX20_NTNACRCCTANGTGTGAN_FL-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0181973 444.977 1 6 CACCTG TTCACACCTAGGTGTGAA + +4 cisbp__M3155 5 0.0182625 446.573 1 6 CACCTG GTGAACACCTGTTAAT + +4 cisbp__M2464-bs 1 0.0182625 446.573 1 6 CACCTG TTACCTGATTAGGAAA - +4 transfac_public__M00071 5 0.0182625 446.573 1 6 CACCTG GTGAACACCTGTTAAT - +4 neph__UW.Motif.0062-ERR-Hr4-ftz-f1-srl-usp 1 0.0182832 447.079 1 6 CACCTG TGACCTTG - +4 predrem__nrMotif1894 4 0.0182832 447.079 1 4 CACCTG ATTTCACC - +4 transfac_pro__M03129-ase-da 5 0.0182889 447.217 1 6 CACCTG AATACCACCTGCTCATT + +4 hocomoco__ZBTB4_HUMAN.H11MO.0.D 2 0.0182889 447.217 1 6 CACCTG CCCACCTGCCATCTAGG - +4 cisbp__M6445-EcR 5 0.0183352 448.352 1 6 CACCTG GCCCTGACCTC + +4 flyfactorsurvey__CG8319-F5-7_SOLEXA_5-CG8319 5 0.0183352 448.352 1 6 CACCTG GAGGTCACCAC + +4 transfac_pro__M00693-esg-nau-sna-wor 3 0.0183352 448.352 1 6 CACCTG CGGCACCTGCC - +4 transfac_pro__M00754 -1 0.0183352 448.352 1 5 CACCTG ACCTTTAGGGT - +4 cisbp__M1899-Hr3 1 0.0183713 449.234 1 6 CACCTG TGACCTTGAT + +4 cisbp__M0486 3 0.0183713 449.234 1 6 CACCTG AGATGCCTTA - +4 cisbp__M6527-twi 1 0.0183713 449.234 1 6 CACCTG CCACCTGGGT - +4 jaspar__MA0071.1-Hr3 1 0.0183713 449.234 1 6 CACCTG TGACCTTGAT - +4 transfac_pro__M07898-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0183713 449.234 1 6 CACCTG TTCACACCTC - +4 cisbp__M4938-Eip78C-ftz-f1-Hr78-svp-usp 1 0.0184225 450.486 1 5 CACCTG TGACCT + +4 flyfactorsurvey__Eip78C_SANGER_5_FBgn0004865-Eip78C-Hr78-ftz-f1-svp-usp 1 0.0184225 450.486 1 5 CACCTG TGACCT - +4 taipale_tf_pairs__HOXB2_TBX21_NAGGTGNTAATKR_CAP-pb 7 0.0186715 456.574 1 6 CACCTG CCATTAACACCTC - +4 elemento__CCACCTC 1 0.0190931 466.883 1 6 CACCTG CCACCTC + +4 elemento__TCACCTC 1 0.0190931 466.883 1 6 CACCTG TCACCTC + +4 predrem__nrMotif2346 1 0.0190931 466.883 1 6 CACCTG TAACCTT - +4 cisbp__M1934-EcR-ERR 10 0.0191794 468.994 1 6 CACCTG AGGTCAGGGTGACCTGGGCC + +4 taipale__TBX1_DBD_AGGTGTGAAAAAAGGTGTGA_repr-byn-org-1 3 0.0191794 468.994 1 6 CACCTG TCACACCTTTTTTCACACCT - +4 predrem__nrMotif1628 2 0.0193371 472.851 1 6 CACCTG CATCCCTGT - +4 cisbp__M6049-achi-hth-vis 3 0.0193471 473.094 1 6 CACCTG TGACACCTGTCA + +4 scertf__foat.UPC2 3 0.0193471 473.094 1 6 CACCTG ATTGACCTGGTC + +4 taipale__Meis2_DBD_TGACAGSTGTCA_repr-achi-hth-vis 3 0.0193471 473.094 1 6 CACCTG TGACACCTGTCA - +4 neph__UW.Motif.0643 6 0.0195269 477.492 1 6 CACCTG ATTTATTTCCTGGCT - +4 taipale_cyt_meth__NR2F1_NRGGTCAAAGGTCAN_eDBD-btd-EcR-eg-ERR-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 2 0.0195269 477.492 1 6 CACCTG CTGACCTTTGACCCC - +4 neph__UW.Motif.0273 10 0.0195269 477.492 1 5 CACCTG AAAGCAGAGCTTCCT + +4 taipale_cyt_meth__NR2C2_NRGGTCAN_eDBD-EcR-ERR-ftz-f1-Hr78-svp-usp 2 0.0196825 481.296 1 6 CACCTG ATGACCTC - +4 jaspar__MA1041.1 -1 0.0196825 481.296 1 5 CACCTG ACCTACCG + +4 transfac_pro__M01395-achi-esg-hth-sna-vis-wor 3 0.0197085 481.932 1 6 CACCTG AATTACCTGTCAATAC + +4 taipale_tf_pairs__MGA_DLX3_YNATTANRGGTGTGAN_CAP_repr 4 0.0197085 481.932 1 6 CACCTG TTCACACCTTTAATCG - +4 taipale_cyt_meth__XPA_NCACCTCACAN_FL_meth_repr-Xpac 1 0.0197483 482.904 1 6 CACCTG CCACCTCACAC + +4 cisbp__M5403-EcR-eg-ERR-Hr38-kni-knrl-svp 11 0.0197497 482.938 1 6 CACCTG AAGGTCACGGTGACCTG + +4 taipale__ESR1_DBD_NAGGTCAMSRTGACCTN_repr-EcR-eg-ERR-Hr38-kni-knrl 11 0.0197497 482.938 1 6 CACCTG AAGGTCACGGTGACCTG + +4 cisbp__M0847 3 0.0197819 483.728 1 6 CACCTG CTAAACCACT + +4 hocomoco__NR1H3_HUMAN.H11MO.1.B-EcR-Hr38-Hr78 3 0.0197819 483.728 1 6 CACCTG TCTGACCTTT - +4 cisbp__M2364 2 0.0203558 497.76 1 6 CACCTG TTCACCTCGGGAACTGTGCCC - +4 jaspar__MA0571.1 2 0.0203558 497.76 1 6 CACCTG TTCACCTCGGGAACTGTGCCC - +4 transfac_pro__M01282-eg-kni-knrl 1 0.0205353 502.15 1 6 CACCTG TGACCTT + +4 transfac_pro__M03569-EcR 1 0.0205353 502.15 1 6 CACCTG TGACCCC - +4 predrem__nrMotif2157 -1 0.0205353 502.15 1 5 CACCTG ACCTGAA + +4 hdpi__TIMM44-CG11779 -1 0.0205353 502.15 1 5 CACCTG ACCCTAC - +4 cisbp__M5875-byn-org-1 3 0.0207436 507.243 1 6 CACCTG TCACACCTTTTTTCACACCT - +4 swissregulon__hs__ESR1.p3-ERR-EcR 10 0.0207436 507.243 1 6 CACCTG AGGTCAGGGTGACCTGGGCC - +4 cisbp__M5115-CG12605-CG8319-da-Kah-net-scrt 2 0.0208118 508.91 1 6 CACCTG ACCACCTGT + +4 predrem__nrMotif1705 3 0.0208118 508.91 1 6 CACCTG CTCCATCTC + +4 transfac_pro__M03568-EcR-eg-ERR-Hr38-Hr78-kni-knrl-svp-usp 2 0.0208118 508.91 1 6 CACCTG CTGACCTTT + +4 hocomoco__NR4A2_HUMAN.H11MO.0.C-Hr38-svp 2 0.0208118 508.91 1 6 CACCTG GTGACCTTT - +4 predrem__nrMotif85 -1 0.0208118 508.91 1 5 CACCTG ACCTTGGGG + +4 transfac_pro__M05127 4 0.0208118 508.91 1 5 CACCTG TCTTAACCT + +4 hocomoco__ZN708_HUMAN.H11MO.1.D 4 0.0208118 508.91 1 5 CACCTG GCTGTACCT - +4 transfac_pro__M06424 1 0.0208379 509.549 1 6 CACCTG AAACCTGCCCCA - +4 transfac_pro__M01262-bi-byn-H15-mid-org-1 14 0.0210408 514.512 1 5 CACCTG AGGTGTGAAATTCGCACCT + +4 transfac_pro__M01195-bi-byn-Doc2-H15-mid-org-1 14 0.0210408 514.512 1 5 CACCTG AGGTGACAATTTCACACCT - +4 transfac_pro__M09190 7 0.0210512 514.764 1 6 CACCTG TACGGTGCACCACCA + +4 taipale_cyt_meth__NR2F1_NRGGTCRNYGACCYN_FL_meth-EcR-svp-usp 9 0.0210512 514.764 1 6 CACCTG AAGGTCAGTGACCTT - +4 taipale_cyt_meth__NR2F6_NRGGTCAAAGGTCAN_FL_meth-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0210512 514.764 1 6 CACCTG CTGACCTTTGACCCC - +4 taipale_tf_pairs__ETV5_FIGLA_RSCGGAARCAGGTGN_CAP-Ets96B 1 0.0210512 514.764 1 6 CACCTG CCACCTGCTTCCGCC - +4 predrem__nrMotif566 -1 0.0211771 517.844 1 5 CACCTG ACCTCCTT + +4 predrem__nrMotif2073 3 0.0211771 517.844 1 5 CACCTG CTCTACCT - +4 transfac_pro__M08960-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0212346 519.248 1 6 CACCTG ATGACCTTTGACCTACAT - +4 predrem__nrMotif435 4 0.0212919 520.652 1 6 CACCTG CAGCCACCCC + +4 transfac_pro__M07957-ERR-ftz-f1-Hr39 2 0.0212919 520.652 1 6 CACCTG ATGACCTTGA - +4 cisbp__M6007-EcR-ERR-ftz-f1 11 0.021311 521.118 1 6 CACCTG TGACCTTGACTGACCTA + +4 taipale__Esrra_DBD_RAGGTCANTCAAGGTCA_repr-EcR-ERR-ftz-f1 11 0.021311 521.118 1 6 CACCTG TGACCTTGACTGACCTA - +4 transfac_pro__M02823 6 0.021311 521.118 1 6 CACCTG TTTTCGCACCTGTGGAT - +4 tfdimers__MD00224-pho-phol 12 0.0215308 526.492 1 6 CACCTG CACCCCCATTCACACCTTCTTC + +4 transfac_pro__M01583 6 0.0216717 529.938 1 6 CACCTG TCACTCGACCTCA - +4 neph__UW.Motif.0343 5 0.0222783 544.772 1 6 CACCTG CAGATTCCCTCTGG - +4 cisbp__M1385 1 0.0223884 547.463 1 6 CACCTG TCACCCATT + +4 predrem__nrMotif2536 0 0.0223884 547.463 1 6 CACCTG TACCTCTTT + +4 predrem__nrMotif1651 4 0.0223884 547.463 1 5 CACCTG GGGTCACCT - +4 predrem__nrMotif2663 4 0.0223884 547.463 1 5 CACCTG CTACCACCT - +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m5 0 0.0224139 548.088 1 6 CACCTG CACCTTATTAAACATCAGAG - +4 transfac_public__M00001-esg-nau 3 0.0224346 548.593 1 6 CACCTG CACCACCTGTTG - +4 transfac_pro__M06314-CG2120 7 0.0224346 548.593 1 5 CACCTG TCCGCCGAACCG - +4 transfac_pro__M06555 7 0.0224346 548.593 1 5 CACCTG GCACCCACACCC - +4 taipale_cyt_meth__NR2F1_NRGGTCRNTGACCYN_eDBD_meth-EcR-eg-kni-knrl-svp-usp 9 0.0226837 554.686 1 6 CACCTG AAGGTCGTTGACCTT + +4 taipale_cyt_meth__NR2F6_NRGGTCRNTGACCYN_FL_meth_repr-EcR-eg-kni-knrl-svp-usp 9 0.0226837 554.686 1 6 CACCTG AAGGTCGGTGACCTT + +4 taipale_cyt_meth__NR2F6_NRGGTCAAAGGTCAN_FL-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0226837 554.686 1 6 CACCTG CTGACCTTTGACCCC - +4 stark__CAGSTG-ase 0 0.0227585 556.513 1 6 CACCTG CACCTG - +4 cisbp__M1448-ERR-ftz-f1-Hr39 1 0.0227707 556.813 1 6 CACCTG TGACCTTG + +4 cisbp__M1454-EcR-Hr78-svp-usp 2 0.0227707 556.813 1 6 CACCTG GTGACCTT + +4 cisbp__M1491-EcR-eg-ERR-Hr4-Hr78-kni-knrl-svp-usp 2 0.0227707 556.813 1 6 CACCTG TTGACCTT + +4 flyfactorsurvey__EcR_SANGER_5_FBgn0000546-EcR-Hr78-usp 2 0.0227707 556.813 1 6 CACCTG ATGACCTT + +4 taipale_cyt_meth__TCF12_NCACSTGN_eDBD-da-esg-sc-sna-wor 1 0.0227707 556.813 1 6 CACCTG GCACCTGC + +4 flyfactorsurvey__CG8319_SOLEXA_2.5_FBgn0037722-CG8319-svp 5 0.0228813 559.517 1 6 CACCTG GGGGTCACCAC + +4 cisbp__M4884-CG8319-svp 5 0.0228813 559.517 1 6 CACCTG GGGGTCACCAC - +4 cisbp__M4316 -1 0.0228813 559.517 1 5 CACCTG ACCTTTAGGGT + +4 cisbp__M0811-gcm-gcm2 1 0.0229071 560.147 1 6 CACCTG GTACCCGCAT - +4 cisbp__M1622-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.0229071 560.147 1 6 CACCTG TTCACACCTC - +4 hocomoco__PPARG_MOUSE.H11MO.1.A-EcR-Hnf4-eg-kni-knrl-svp-usp 1 0.0229071 560.147 1 6 CACCTG TGACCTTTGC - +4 taipale_cyt_meth__EOMES_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0229071 560.147 1 6 CACCTG TTCACACCTT - +4 taipale_cyt_meth__RARB_NAAAGGTCAN_FL-EcR-eg-Hr78-kni-knrl-svp-usp 2 0.0229071 560.147 1 6 CACCTG TTGACCTTTT - +4 predrem__nrMotif2325-CTCF 5 0.0229071 560.147 1 5 CACCTG GGCGCCACCT - +4 neph__UW.Motif.0576-ERR-E(z) 2 0.0229111 560.244 1 6 CACCTG GCGGCCTGGCCCCGCC + +4 transfac_pro__M01459-achi-esg-hth-sna-vis-wor 3 0.0229111 560.244 1 6 CACCTG AAAGACCTGTCAATCC + +4 neph__UW.Motif.0520 11 0.0229111 560.244 1 5 CACCTG CAGCAGCCTGCTTCCT - +4 cisbp__M6523-EcR 1 0.0229808 561.95 1 6 CACCTG TGACCTGACCTGACCTC + +4 taipale_cyt_meth__ESR1_NAGGTCANNNYGACCTN_eDBD_meth-eg-ERR-kni-knrl 11 0.0229808 561.95 1 6 CACCTG GAGGTCACCGCGACCTT + +4 transfac_pro__M03120 5 0.0229808 561.95 1 6 CACCTG AGTAACACCTGCTAATC + +4 transfac_pro__M09297 2 0.0233341 570.589 1 6 CACCTG TTTACCTACCTTT + +4 hocomoco__NR2C2_MOUSE.H11MO.0.A-EcR-HDAC1-Hnf4-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0233341 570.589 1 6 CACCTG TGACCTTTGACCT - +4 hocomoco__ZN335_HUMAN.H11MO.1.A 0 0.023685 579.169 1 6 CACCTG TGCCTGA + +4 transfac_pro__M02109 0 0.023685 579.169 1 6 CACCTG CACTTGA + +4 transfac_pro__M00660 0 0.023685 579.169 1 6 CACCTG CACGTGA - +4 transfac_pro__M08968-EcR-eg-ERR-ftz-f1-Hr4-Hr78-kni-knrl-svp-usp 1 0.023685 579.169 1 6 CACCTG TGACCTT - +4 taipale_tf_pairs__ETV2_TBX21_RCCGGANNNNNNNNNNNACACCTN_CAP-pnt 18 0.0238765 583.853 1 6 CACCTG ACCGGAAGCACGATTTCACACCTT + +4 cisbp__M5682-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-nej-Spps-svp-tll-usp 1 0.0239908 586.646 1 6 CACCTG TGACCTTTGACCTC + +4 taipale_cyt_meth__RARB_NRGGTCRTGACCYN_FL-EcR-eg-ftz-f1-Hr78-kni-knrl-svp-usp 8 0.0239908 586.646 1 6 CACCTG AAGGTCATGACCTT + +4 transfac_pro__M07256-EcR-svp-usp 8 0.0239908 586.646 1 6 CACCTG AGGTCAATGACCTC + +4 taipale__NR2F6_full_RRGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0239908 586.646 1 6 CACCTG TGACCTTTGACCTC - +4 cisbp__M0325 2 0.0240721 588.635 1 6 CACCTG CTGACGTGG + +4 predrem__nrMotif1762 0 0.0240721 588.635 1 6 CACCTG TTCCTTTGC + +4 predrem__nrMotif2431 0 0.0240721 588.635 1 6 CACCTG TTCCTTCAT + +4 predrem__nrMotif433 0 0.0240721 588.635 1 6 CACCTG CACCCACCA + +4 transfac_pro__M00963-EcR-usp 3 0.0240721 588.635 1 6 CACCTG CCTGTCCTT + +4 predrem__nrMotif892 0 0.0240721 588.635 1 6 CACCTG AACCTCTCT - +4 predrem__nrMotif944 0 0.0240721 588.635 1 6 CACCTG AACCAGGAC - +4 cisbp__M1075 4 0.0240721 588.635 1 5 CACCTG ATTACACCT + +4 predrem__nrMotif2645 -1 0.0240721 588.635 1 5 CACCTG ACCTGACTG + +4 predrem__nrMotif2186 4 0.0240721 588.635 1 5 CACCTG TCTGAACCT - +4 predrem__nrMotif707 4 0.0240721 588.635 1 5 CACCTG CAGAAACCT - +4 cisbp__M5622-achi-hth-nau-vis 3 0.0241435 590.38 1 6 CACCTG TGACACCTGTCA + +4 flyfactorsurvey__HLH4C_da_SANGER_5_4_FBgn0000413-HLH4C-da 1 0.0241435 590.38 1 6 CACCTG CCACCTGCGCCC + +4 hocomoco__RARA_MOUSE.H11MO.3.A-EcR-svp-usp 4 0.0241435 590.38 1 6 CACCTG CCCTGACCTCGG - +4 transfac_pro__M05846 6 0.0241435 590.38 1 6 CACCTG GCACTTAACCCC - +4 dbcorrdb__eGFP-NR4A1__ENCSR000DJW_1__m4 4 0.0241976 591.704 1 6 CACCTG TTATCACCTGTATCTACTGA + +4 transfac_pro__M03820-EcR-eg-ERR-kni-knrl 9 0.0244323 597.442 1 6 CACCTG GGTCACCGTGACCTG + +4 transfac_pro__M01841-ERR 4 0.0244323 597.442 1 6 CACCTG CCGTGACCTTGGAGA - +4 taipale_tf_pairs__GCM2_TBX21_AGGTGTNNNGSGGGN_CAP_repr-gcm-gcm2 10 0.0244323 597.442 1 5 CACCTG ACCCCCATGACACCT - +4 cisbp__M1430-EcR-Hr78-svp-usp 2 0.0244664 598.277 1 6 CACCTG TTGACCTC + +4 cisbp__M1465-EcR-Hr4-Hr78-eg-kni-knrl-svp-usp 2 0.0244664 598.277 1 6 CACCTG TTGACCTC + +4 cisbp__M4933-EcR-Hr78-usp 2 0.0244664 598.277 1 6 CACCTG ATGACCTC + +4 cisbp__M0480 0 0.0244664 598.277 1 6 CACCTG TGCCTTAT - +4 taipale_cyt_meth__XPA_NCACCTCACAN_FL-Xpac 1 0.0246133 601.87 1 6 CACCTG CCACCTCACAC + +4 transfac_pro__M03877-ac-ase-l(1)sc-sc 3 0.0246133 601.87 1 6 CACCTG CAACACCTGCC + +4 transfac_pro__M01724-EcR-svp-usp 2 0.0246133 601.87 1 6 CACCTG CTGACCTCAAC - +4 cisbp__M0003 4 0.0246333 602.358 1 6 CACCTG TTCACACCCC + +4 cisbp__M1438-EcR-eg-ftz-f1-Hr78-kni-knrl-svp-usp 3 0.0246333 602.358 1 6 CACCTG CGTGACCTCT + +4 cisbp__M0816-gcm-gcm2 0 0.0246333 602.358 1 6 CACCTG TACCCGCATA - +4 taipale_cyt_meth__TBX15_NAGGTGTGAN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0246333 602.358 1 6 CACCTG TTCACACCTT - +4 predrem__nrMotif79 5 0.0246333 602.358 1 5 CACCTG TTCCTCACCT - +4 transfac_pro__M01419-achi-esg-hth-sna-vis-wor 3 0.0246837 603.591 1 6 CACCTG AAGGAGCTGTCAATAC + +4 taipale__ZNF435_full_AGTGTTAACAGARCACCT_repr 13 0.0247032 604.067 1 5 CACCTG AGTGTTAACAGAACACCT + +4 c2h2_zfs__M5117 13 0.0247032 604.067 1 5 CACCTG AGTGTTAACAGAACACCT - +4 hocomoco__PPARA_MOUSE.H11MO.0.A-EcR-Hnf4-Hr3-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0247674 605.638 1 6 CACCTG TGACCTTTGACCTAGTT - +4 cisbp__M6390-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.0251136 614.103 1 6 CACCTG TGACCTTTGACCT + +4 scertf__foat.ADR1 4 0.0251136 614.103 1 6 CACCTG ATGCAACCTGTCA + +4 hocomoco__COT2_MOUSE.H11MO.0.A-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 4 0.0251136 614.103 1 6 CACCTG CTCTGACCTTTGG - +4 neph__UW.Motif.0289 4 0.0251136 614.103 1 6 CACCTG GGCCTGCCTGCCT - +4 taipale_cyt_meth__NFKB2_NGGGGAWNYMCCN_eDBD-Rel 8 0.0251136 614.103 1 5 CACCTG AGGGGAAGCACCG + +4 neph__UW.Motif.0220 8 0.0251136 614.103 1 5 CACCTG GAAATCCTGTCCT - +4 taipale_cyt_meth__T_NANGTGTGANNNNTNACACCTN_eDBD_meth_repr-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 16 0.0251543 615.099 1 6 CACCTG AACGTGTGAAATTTCACACCTC + +4 flyfactorsurvey__svp_SANGER_5_FBgn0003651-svp 1 0.0253985 621.068 1 6 CACCTG TGACCTT - +4 tfdimers__MD00092-Pur-alpha 9 0.0258165 631.291 1 6 CACCTG CCCCTTCCCCATCTGCCCCCCCCC + +4 cisbp__M6394-Hr38-svp 2 0.0258676 632.54 1 6 CACCTG GTGACCTTT + +4 hocomoco__PPARG_HUMAN.H11MO.1.A-ERR-EcR-Hnf4-Hr3-Hr38-Hr78-eg-kni-knrl-svp-usp 1 0.0258676 632.54 1 6 CACCTG TGACCTTTG - +4 predrem__nrMotif1577 1 0.0258676 632.54 1 6 CACCTG ACACCTGCT - +4 taipale_cyt_meth__GCM1_RTRNGGGTN_eDBD_meth-gcm-gcm2 0 0.0258676 632.54 1 6 CACCTG TACCCCCAT - +4 taipale_cyt_meth__RARG_NRGGTCAYN_FL-EcR-Hr78-svp-usp 3 0.0258676 632.54 1 6 CACCTG CGTGACCTC - +4 transfac_pro__M05149 4 0.0258676 632.54 1 5 CACCTG ACTTAACCT + +4 cisbp__M5012-da-HLH4C 1 0.0259709 635.066 1 6 CACCTG CCACCTGAGCCC + +4 cisbp__M5722-achi-hth-nau-vis 3 0.0259709 635.066 1 6 CACCTG TGACACCTGTCA + +4 transfac_pro__M06290 5 0.0259709 635.066 1 6 CACCTG AGGTCCTCCTGA + +4 taipale__MEIS3_DBD_TGACAGSTGTCA-achi-hth-vis 3 0.0259709 635.066 1 6 CACCTG TGACACCTGTCA - +4 taipale__PKNOX2_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.0259709 635.066 1 6 CACCTG TGACACCTGTCA - +4 transfac_pro__M05981-CG2120 6 0.0259709 635.066 1 6 CACCTG TCGTTTCACCGC - +4 hdpi__NUP133-EcR-Nup133-eg-kni-knrl-svp-usp 1 0.0260905 637.99 1 5 CACCTG TGACCT - +4 dbcorrdb__REST__ENCSR000BHM_1__m2-CTCF 14 0.0261028 638.292 1 6 CACCTG GGCGCCGTGTTCAGCACCAT - +4 taipale__TBX5_DBD_AGGTGTNANWWNTNACACCT-bi-byn-Doc2-H15-mid-org-1 15 0.0261028 638.292 1 5 CACCTG AGGTGTGAAATTTCACACCT - +4 cisbp__M1450-eg-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 1 0.0262667 642.299 1 6 CACCTG TGACCTTT + +4 cisbp__M1451-EcR-Hnf4-Hr3-Hr78-svp-usp 2 0.0262667 642.299 1 6 CACCTG TTGACCTC + +4 cisbp__M1469-Hr3-svp 2 0.0262667 642.299 1 6 CACCTG GTGACCTC + +4 swissregulon__hs__NR4A2.p2-Hr38 2 0.0262667 642.299 1 6 CACCTG GTGACCTT - +4 transfac_pro__M06145 9 0.0263043 643.22 1 6 CACCTG GTGGCAGGGCACCTT - +4 cisbp__M4663-EcR-ERR 12 0.0264225 646.11 1 6 CACCTG CAAGGTCAGGGTGACCTGG + +4 neph__UW.Motif.0041 5 0.0264641 647.126 1 6 CACCTG TGACTCACTTG - +4 transfac_pro__M06801-salm-salr 5 0.0264641 647.126 1 6 CACCTG GGTTCTACCAA - +4 transfac_pro__M08966-Hr3 2 0.0264641 647.126 1 6 CACCTG GTGACCTAATT - +4 transfac_pro__M07894-bi-byn-Doc2-Doc3-H15-mid-org-1 6 0.0264641 647.126 1 5 CACCTG ATTTCACACCT - +4 cisbp__M1446-ERR-Hr39 2 0.0264764 647.427 1 6 CACCTG ATGACCTTGA + +4 cisbp__M4697-ERR 2 0.0264764 647.427 1 6 CACCTG GTGACCTTGG + +4 cisbp__M5033-Eip75B-Hr3 1 0.0264764 647.427 1 6 CACCTG TGACCTATTT + +4 flyfactorsurvey__Hr46_SANGER_5_FBgn0000448-Eip75B-Hr3 1 0.0264764 647.427 1 6 CACCTG TGACCTACTT + +4 taipale_tf_pairs__ETV2_FIGLA_NNCGGAANCAGGTGNN_CAP-pnt 2 0.0265815 649.997 1 6 CACCTG ACCACCTGTTTCCGGT - +4 cisbp__M5887-H15-mid-org-1 11 0.0265815 649.997 1 5 CACCTG TCACACCTTCACACCT + +4 taipale__TBX20_full_AGGTGTKANGGTGTSA-H15-mid-org-1 11 0.0265815 649.997 1 5 CACCTG TCACACCTTCACACCT - +4 taipale_cyt_meth__ESR1_NAGGTCANNNYGACCTN_FL_meth-EcR-eg-ERR-kni-knrl 11 0.0266796 652.396 1 6 CACCTG GAGGTCACCGTGACCTT + +4 transfac_pro__M03135-da-HLH54F 5 0.0266796 652.396 1 6 CACCTG TAGACCACCTGTTCCGG - +4 transfac_public__M00528-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 1 0.0266796 652.396 1 6 CACCTG TGACCTTTGCCCTAGTT - +4 cisbp__M3837-ERR-Hr3 2 0.0270168 660.641 1 6 CACCTG ATGACCTTGATAT + +4 transfac_public__M00156-ERR-Hr3 2 0.0270168 660.641 1 6 CACCTG ATGACCTTGATAT - +4 cisbp__M5221-svp 1 0.02721 665.366 1 6 CACCTG TGACCTT + +4 hocomoco__ESR2_HUMAN.H11MO.1.A-ERR-EcR-svp 2 0.02721 665.366 1 5 CACCTG GTGACCT - +4 predrem__nrMotif2188 0 0.0277791 679.282 1 6 CACCTG TCCCTGTTA - +4 transfac_pro__M08956-Hr38 1 0.0277791 679.282 1 6 CACCTG TGACCTTTA - +4 transfac_pro__M05086 4 0.0277791 679.282 1 5 CACCTG ACTTAACCT + +4 predrem__nrMotif833 -1 0.0277791 679.282 1 5 CACCTG ACCTGAAGT - +4 transfac_pro__M09304 7 0.0277852 679.432 1 6 CACCTG CCTCAACCACCACC + +4 homer__GAGGTCAAAGGTCA_TR4-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-svp-tll-usp 1 0.0277852 679.432 1 6 CACCTG TGACCTTTGACCTC - +4 cisbp__M3589-esg-nau 3 0.0279235 682.812 1 6 CACCTG CAACACCTGTCC + +4 transfac_pro__M05986 2 0.0279235 682.812 1 6 CACCTG CTTACCTTAACC - +4 taipale_tf_pairs__MGA_DLX2_AGGTGNTAATTR_CAP 7 0.0279235 682.812 1 5 CACCTG CAATTAACACCT - +4 transfac_pro__M05932 7 0.0279235 682.812 1 5 CACCTG GCGTCCCCACCG - +4 transfac_pro__M06723 7 0.0279235 682.812 1 5 CACCTG TCTTCCTTACCA - +4 dbcorrdb__ESR1__ENCSR000BQR_1__m1 7 0.0281388 688.079 1 6 CACCTG TCACGGTGACCTGGCACCGG + +4 taipale__EOMES_DBD_TCACACCTNNNNAGGTGTGA_repr-org-1 3 0.0281388 688.079 1 6 CACCTG TCACACCTTCTAAGGTGTGA + +4 dbcorrdb__REST__ENCSR000BJP_1__m2-CTCF 14 0.0281388 688.079 1 6 CACCTG GGCGCGGTGTTCAGCACCAT - +4 cisbp__M5899-bi-byn-Doc2-H15-mid-org-1 15 0.0281388 688.079 1 5 CACCTG AGGTGTGAAATTTCACACCT + +4 swissregulon__hs__NR5A1_2.p2-ERR-Hr4-ftz-f1-usp 1 0.0281742 688.944 1 6 CACCTG TGACCTTG + +4 taipale_tf_pairs__TBX3_AGGTGTNR_HT-bi 3 0.0281742 688.944 1 5 CACCTG TCACACCT - +4 neph__UW.Motif.0516 6 0.0283075 692.204 1 6 CACCTG AAAACTTCCCTCTCC + +4 transfac_public__M00002 5 0.0283075 692.204 1 6 CACCTG GGGGACACCTGCCGT - +4 neph__UW.Motif.0645 10 0.0283075 692.204 1 5 CACCTG AGGCTGAAGGCAGCT - +4 taipale_cyt_meth__ZNF276_NTTAAGGNNGWANNNWCSNCCTTAAN_eDBD_meth 17 0.0283431 693.073 1 6 CACCTG CTTAAGGTGGACTATACCACCTTAAT - +4 cisbp__M5407-ERR-ftz-f1-Hr39 2 0.0284399 695.442 1 6 CACCTG TTGACCTTGAA + +4 cisbp__M1843-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0284399 695.442 1 6 CACCTG TTCACACCTAG - +4 hocomoco__MEIS3_HUMAN.H11MO.0.D-achi-esg-hth-sna-vis-wor 0 0.0284399 695.442 1 6 CACCTG CACCTGTCAAA - +4 cisbp__M6178-EcR-eg-Hnf4-Hr3-kni-knrl-svp-usp 2 0.0284421 695.494 1 6 CACCTG TTGACCTTTG + +4 cisbp__M1624-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.0284421 695.494 1 6 CACCTG TTCACACCTT - +4 hocomoco__NR4A3_HUMAN.H11MO.0.D-ERR-EcR-Hnf4-Hr38-Hr78-eg-kni-knrl-svp-usp 2 0.0284421 695.494 1 6 CACCTG CTGACCTTTG - +4 taipale_cyt_meth__RARA_NRRGGTCANN_eDBD_meth-EcR-Hnf4-Hr78-svp-usp 3 0.0284421 695.494 1 6 CACCTG CGTGACCTTT - +4 taipale_cyt_meth__RARB_NAAAGGTCRN_FL_meth-EcR-Hr78-usp 2 0.0284421 695.494 1 6 CACCTG GTGACCTTTT - +4 transfac_pro__M02110-EcR-Hr38-svp-usp 3 0.0284421 695.494 1 6 CACCTG TTTGACCTTT - +4 homer__AGGTGTGAAM_Tbet-Doc2-H15-bi-byn-mid-org-1 5 0.0284421 695.494 1 5 CACCTG TTTCACACCT - +4 transfac_pro__M01171 -1 0.0284421 695.494 1 5 CACCTG TCCTAGAACC - +4 cisbp__M5677-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.0286124 699.66 1 6 CACCTG TTGACCTTTTGACCTC + +4 transfac_pro__M00928 2 0.0286124 699.66 1 6 CACCTG TGTACCGTTTTCGGTG + +4 transfac_pro__M09278 2 0.0286124 699.66 1 6 CACCTG TTCACCTACCACAATA - +4 cisbp__M4696-EcR-ERR 10 0.0286714 701.102 1 6 CACCTG AGGTCAGGGTGACCTGGA - +4 transfac_pro__M00929-esg-nau 6 0.0286714 701.102 1 6 CACCTG CTTCGCCACCTGCCGCGG - +4 taipale_tf_pairs__HOXB13_TBX21_ARGTGNNANNNMWTAAAN_CAP_repr 13 0.0286714 701.102 1 5 CACCTG GTTTATGCAATCACACCT - +4 cisbp__M3785-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 1 0.0287259 702.435 1 6 CACCTG TGACCTTTGCCCTAGTT + +4 cisbp__M5770-EcR-eg-ERR-Hr78-kni-knrl-svp-usp 11 0.0287259 702.435 1 6 CACCTG TGACCTCTGTTGACCTT + +4 hdpi__NR4A1-Hr38 0 0.0287651 703.393 1 5 CACCTG GACAT - +4 predrem__nrMotif53 -2 0.0291251 712.196 1 4 CACCTG CCTTCAA + +4 predrem__nrMotif157-CTCF-SMC3-usp-vtd 2 0.0298103 728.951 1 6 CACCTG GCCACCTGG + +4 cisbp__M1552 1 0.0298103 728.951 1 6 CACCTG TTCCCTGGG - +4 transfac_pro__M04976 4 0.0298103 728.951 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M04995 4 0.0298103 728.951 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M05173 4 0.0298103 728.951 1 5 CACCTG TCTTAACCT + +4 stark__GGTNTAAAW 5 0.0298103 728.951 1 4 CACCTG ATTTAAACC - +4 transfac_pro__M00511-ERR 3 0.0298816 730.696 1 6 CACCTG TATGACCTTGATCT - +4 transfac_pro__M06556 3 0.0300081 733.788 1 6 CACCTG GCTTACCTTCCA - +4 transfac_pro__M06168 7 0.0300081 733.788 1 5 CACCTG TCCCTCGTACCA - +4 transfac_pro__M06863 7 0.0300081 733.788 1 5 CACCTG TCCGCCTCACCT - +4 cisbp__M1434-EcR-eg-Hr78-kni-knrl-svp-usp 1 0.0301921 738.287 1 6 CACCTG TGACCCCT + +4 transfac_pro__M00727-ftz-f1-Hr4 1 0.0301921 738.287 1 6 CACCTG TGACCTTG + +4 taipale_cyt_meth__NR2C2_NRGGTCAN_eDBD_meth-EcR-Hr78-svp-usp 2 0.0301921 738.287 1 6 CACCTG TTGACCTC - +4 transfac_pro__M07353 2 0.0301921 738.287 1 6 CACCTG GCCACCTG - +4 predrem__nrMotif1514 -1 0.0301921 738.287 1 5 CACCTG AACTGCCT + +4 predrem__nrMotif1536 3 0.0301921 738.287 1 5 CACCTG GCCAACCT + +4 dbcorrdb__ESR1__ENCSR000BKL_1__m1 5 0.0303154 741.303 1 6 CACCTG ACGGTGACCTGGCACAGTGC + +4 dbcorrdb__TCF12__ENCSR000BIT_1__m1-zfh1 3 0.0303154 741.303 1 6 CACCTG CCACACCTGGTGTTGCTAAG + +4 cisbp__M5397-org-1 3 0.0303154 741.303 1 6 CACCTG TCACACCTTCTAAGGTGTGA - +4 yetfasco__TBP-TFIIA-TFIIB_1330-Tbp-TfIIA-S-TfIIA-S-2-TfIIB-Trf-Trf2 13 0.0303154 741.303 1 6 CACCTG CCTTTTATAGGCGCCCCTTC - +4 taipale_cyt_meth__NR2F6_NRGGTCRNYGACCYN_eDBD_meth-EcR-svp-usp 9 0.0304495 744.583 1 6 CACCTG AAGGTCAGTGACCTT + +4 transfac_pro__M09309 6 0.0304495 744.583 1 6 CACCTG TCCACCTACCACCAC + +4 taipale_cyt_meth__RXRB_NRGGTCAAAGGTCAN_eDBD_meth_repr-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0304495 744.583 1 6 CACCTG ATGACCTTTGACCCC - +4 taipale_tf_pairs__TEAD4_TCF3_NCAGGTGNGWATGYN_CAP_repr-sd 8 0.0304495 744.583 1 6 CACCTG CACATTCTCACCTGC - +4 cisbp__M0353 4 0.0305355 746.686 1 6 CACCTG AGGACACGTA + +4 predrem__nrMotif1868 0 0.0305355 746.686 1 6 CACCTG TGCCTTTGGT + +4 cisbp__M1626-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0305355 746.686 1 6 CACCTG TTCACACCTT - +4 cisbp__M1630-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0305355 746.686 1 6 CACCTG TTGACACCTT - +4 transfac_pro__M05060 5 0.0305355 746.686 1 5 CACCTG CACTTAACCT + +4 taipale_cyt_meth__ESRRG_NYCAAGGTCAN_FL-ERR-ftz-f1-Hr39 2 0.0305473 746.973 1 6 CACCTG GTGACCTTGAC - +4 transfac_pro__M06833 0 0.0306591 749.708 1 6 CACCTG TACCTCGAAGCTCGTCCCA - +4 transfac_pro__M07902-byn-H15-mid-org-1 3 0.0307847 752.779 1 6 CACCTG TCACACCTAGGTGTTA + +4 hocomoco__THB_HUMAN.H11MO.0.C-EcR 1 0.0309151 755.966 1 6 CACCTG TGACCTGACCTGACCTC - +4 taipale__RARG_full_RRGGTCANNNRRGGTCA-EcR-ERR-Hr78-svp-usp 11 0.0309151 755.966 1 6 CACCTG TGACCTCTGTTGACCTT - +4 cisbp__M5034-EcR-ERR-Hr4-usp 1 0.0311494 761.697 1 6 CACCTG TGACCTT + +4 predrem__nrMotif168 0 0.0311494 761.697 1 6 CACCTG CACCAGG + +4 flyfactorsurvey__Hr4_SANGER_5_FBgn0023546-ERR-EcR-Hr4-usp 1 0.0311494 761.697 1 6 CACCTG TGACCTT - +4 transfac_pro__M02094-ERR-ftz-f1 3 0.0312224 763.48 1 6 CACCTG AGTGACCTTGAAT - +4 transfac_pro__M09544-Myb 0 0.0319645 781.628 1 6 CACCTG TAACGGTCA - +4 transfac_pro__M05085 4 0.0319645 781.628 1 5 CACCTG ACTTAACCT + +4 cisbp__M5673-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-nej-Spps-svp-tll-usp 1 0.0321207 785.448 1 6 CACCTG TGACCTTTGACCTC + +4 neph__UW.Motif.0538 2 0.0321207 785.448 1 6 CACCTG AAAACCATGTGAAC + +4 homer__TAGGGCAAAGGTCA_RXR-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 1 0.0321207 785.448 1 6 CACCTG TGACCTTTGCCCTA - +4 taipale__NR2C2_DBD_RRGGTCAAAGGTCA_repr-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-nej-Spps-svp-tll-usp 1 0.0321207 785.448 1 6 CACCTG TGACCTTTGACCTC - +4 neph__UW.Motif.0286 -2 0.0321207 785.448 1 4 CACCTG CCTGTGCCTTCCTG - +4 neph__UW.Motif.0339 6 0.0322317 788.162 1 6 CACCTG AGATGCTTCCTC + +4 transfac_pro__M06251 6 0.0322317 788.162 1 6 CACCTG GCGTTTTGCCTG - +4 predrem__nrMotif1085 2 0.0323248 790.438 1 6 CACCTG AAGACCTT + +4 predrem__nrMotif885 2 0.0323248 790.438 1 6 CACCTG GAAACCTG - +4 transfac_pro__M04926-CTCF 2 0.0323248 790.438 1 6 CACCTG AGCACCTT - +4 taipale_tf_pairs__ETV2_EOMES_RCCGGANNNNNNNNNNNACACCTN_CAP_repr-pnt 18 0.0324554 793.633 1 6 CACCTG ACCGGAAGCAACACCTCACACCTT + +4 cisbp__M3154 5 0.0327381 800.544 1 6 CACCTG GGGGACACCTGCCGT + +4 homer__AAGGTCACNGTGACC_ERE-ERR-EcR-eg-kni-knrl 9 0.0327381 800.544 1 6 CACCTG GGTCACGGTGACCTT - +4 taipale_cyt_meth__RXRG_NRGGTCAAAGGTCAN_FL-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0327381 800.544 1 6 CACCTG TTGACCTTTGACCCC - +4 transfac_pro__M07475 8 0.0327381 800.544 1 6 CACCTG CCCCCTCACACCTCG - +4 cisbp__M1378 1 0.0327617 801.123 1 6 CACCTG TAACCTTAAA + +4 cisbp__M1387 3 0.0327617 801.123 1 6 CACCTG GTGTACCCAT - +4 taipale_cyt_meth__HES1_GGCRCGTGNS_eDBD_meth-Sidpn 2 0.0327617 801.123 1 6 CACCTG CACACGTGCC - +4 cisbp__M4703-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp -1 0.0327617 801.123 1 5 CACCTG ACCTTTGACC + +4 cisbp__M5918-TfAP-2 0 0.0327925 801.874 1 6 CACCTG TGCCTGAGGCT - +4 taipale__TFAP2B_DBD_NSCCNNNGGSN-TfAP-2 0 0.0327925 801.874 1 6 CACCTG TGCCTGAGGCT - +4 taipale_cyt_meth__ESRRG_NYCAAGGTCAN_FL_meth-ERR-ftz-f1-Hr39 2 0.0327925 801.874 1 6 CACCTG GTGACCTTGAC - +4 transfac_pro__M02093-ERR 4 0.0327925 801.874 1 6 CACCTG GCGTGACCTTG - +4 neph__UW.Motif.0571 7 0.0331066 809.555 1 6 CACCTG AAATTCCTTCCTCCTG + +4 homer__GGGTTACTANAGGTCA_LXRE-EcR-svp-usp 1 0.0331066 809.555 1 6 CACCTG TGACCTGTAGTAACCC - +4 neph__UW.Motif.0210 4 0.0331066 809.555 1 6 CACCTG TCAGAACCAGAATCAG - +4 neph__UW.Motif.0675 9 0.0331066 809.555 1 6 CACCTG CCTGCCCCCTGCCTTG - +4 taipale__NR2F1_DBD_RRGGTCANNNGGTCAN_repr-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.0331066 809.555 1 6 CACCTG TTGACCTTTTGACCTC - +4 taipale_tf_pairs__GCM2_MAX_NTRNGGGNNNCACGTG_CAP_repr-gcm-gcm2-Max 7 0.0331066 809.555 1 6 CACCTG CACGTGTTACCCGCAT - +4 hocomoco__MGAP_HUMAN.H11MO.0.D-Doc2-bi-byn-org-1 11 0.0331066 809.555 1 5 CACCTG GTGAAAATTCACACCT - +4 predrem__nrMotif2213 0 0.0332889 814.012 1 6 CACCTG CAACTTG + +4 transfac_pro__M03831-nau-sc 0 0.0332889 814.012 1 6 CACCTG CACCTGC + +4 predrem__nrMotif2341 -1 0.0332889 814.012 1 5 CACCTG TCCTGCA + +4 hocomoco__COT2_HUMAN.H11MO.0.A-ERR-EcR-HDAC1-Hnf4-eg-kni-knrl-svp-usp 5 0.0335392 820.134 1 6 CACCTG CCTCTGACCTTTG - +4 neph__UW.Motif.0199 4 0.0335392 820.134 1 6 CACCTG TGGCTTCCTGGCC - +4 transfac_pro__M01081 6 0.0335392 820.134 1 6 CACCTG GCAACCAACCTTG - +4 hocomoco__TBX19_HUMAN.H11MO.0.D-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 6 0.0339965 831.317 1 6 CACCTG ATTTCACACCTACGTGTGAAAT - +4 cisbp__M1394 2 0.0342451 837.395 1 6 CACCTG TAACCCTAG + +4 cisbp__M1494-EcR-Hr38-Hr78-svp-usp 2 0.0342451 837.395 1 6 CACCTG GTGACCTCT + +4 predrem__nrMotif1096 2 0.0342451 837.395 1 6 CACCTG GCCGCCTGG + +4 predrem__nrMotif1725 3 0.0342451 837.395 1 6 CACCTG TGATCCCTG + +4 transfac_pro__M01132-ERR-ftz-f1-Hr4-usp 1 0.0342451 837.395 1 6 CACCTG TGACCTTGA + +4 hocomoco__COT1_MOUSE.H11MO.0.B-ERR-EcR-HDAC1-Hnf4-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0342451 837.395 1 6 CACCTG TGACCTTTG - +4 transfac_pro__M09577-Myb 0 0.0342451 837.395 1 6 CACCTG TAACGGTCA - +4 transfac_pro__M05055 4 0.0342451 837.395 1 5 CACCTG TCTTAACCT + +4 transfac_pro__M05088 4 0.0342451 837.395 1 5 CACCTG ACTTAACCT + +4 transfac_pro__M05113 4 0.0342451 837.395 1 5 CACCTG TCTTAACCT + +4 predrem__nrMotif1916 -1 0.0342451 837.395 1 5 CACCTG CCCTTCAGA - +4 tfdimers__MD00025 16 0.0344978 843.575 1 6 CACCTG AAAACCAGGTCACCGTGACCTGTTTTT + +4 homer__TGACCTTTGCCCCA_PPARE-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 1 0.0345101 843.874 1 6 CACCTG TGACCTTTGCCCCA + +4 cisbp__M1452-Hr3 1 0.0345776 845.525 1 6 CACCTG TGACCTAG + +4 cisbp__M4947-ERR-ftz-f1-srl 1 0.0345776 845.525 1 6 CACCTG TGACCTTG + +4 flyfactorsurvey__ERR_SANGER_5_FBgn0035849-ERR-srl 1 0.0345776 845.525 1 6 CACCTG TGACCTTG - +4 flyfactorsurvey__Vnd_SOLEXA_FBgn0003986-tin-vnd 0 0.0345776 845.525 1 6 CACCTG CACTTGAA - +4 predrem__nrMotif1620 -2 0.0345776 845.525 1 4 CACCTG CCTGCATT + +4 predrem__nrMotif2065 -2 0.0345776 845.525 1 4 CACCTG CCTGCCTA + +4 transfac_pro__M05505 1 0.0346012 846.103 1 6 CACCTG TCGCCTGCAACA - +4 transfac_pro__M06809-crol -1 0.0346012 846.103 1 5 CACCTG CCCTGCGACAGC + +4 cisbp__M0085-TfAP-2 1 0.0351249 858.91 1 6 CACCTG TCGCCTGAGG + +4 predrem__nrMotif2591 4 0.0351249 858.91 1 6 CACCTG AAGCAACCTA + +4 transfac_public__M00184-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 2 0.0351249 858.91 1 6 CACCTG AGCACCTGTC + +4 hocomoco__RXRA_HUMAN.H11MO.1.A-ERR-EcR-Hr78-eg-kni-knrl-svp-usp 2 0.0351249 858.91 1 6 CACCTG CTGACCTCTG - +4 transfac_pro__M04636-Usf 4 0.0351249 858.91 1 6 CACCTG TCACTTCCTT - +4 transfac_pro__M07427-EcR-Hnf4-Hr38 3 0.0351249 858.91 1 6 CACCTG CTTGACCTTT - +4 dbcorrdb__ESR1__ENCSR000BIY_1__m1 5 0.035131 859.058 1 6 CACCTG ACGGTGACCTGGCCCCGTGG + +4 dbcorrdb__STAT1__ENCSR000EZK_1__m2-Stat92E 9 0.035131 859.058 1 6 CACCTG CCAGGAAGTCACCTGATTTC + +4 dbcorrdb__ZNF274__ENCSR000EUK_1__m5 5 0.035131 859.058 1 6 CACCTG GCTCACACCTTATTCAACAT - +4 transfac_pro__M05791 2 0.035131 859.058 1 6 CACCTG AGTACCTTTTTTCCGCACCA - +4 taipale_cyt_meth__NR2F1_NRGGTCRNTGACCYN_eDBD-EcR-svp-usp 9 0.0351811 860.283 1 6 CACCTG GAGGTCAGTGACCTT + +4 transfac_pro__M08988 5 0.0351811 860.283 1 6 CACCTG GGCTCGACCTCAAAG + +4 jaspar__MA0531.1-CTCF-SMC3-usp-vtd 5 0.0351811 860.283 1 6 CACCTG GGCGCCATCTAGCGG - +4 neph__UW.Motif.0528 9 0.0351811 860.283 1 6 CACCTG TGCCTTTTTTTCCTT - +4 taipale_cyt_meth__NR2F1_NRGGTCAAAGGTCAN_FL-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0351811 860.283 1 6 CACCTG GTGACCTTTGACCTC - +4 taipale_cyt_meth__NR2F1_NRGGTCRNTGACCYN_FL-EcR-svp-usp 9 0.0351811 860.283 1 6 CACCTG AAGGTCAATGACCTT - +4 transfac_pro__M01725-EcR-eg-ERR-Hr78-kni-knrl-svp-usp 3 0.0351812 860.285 1 6 CACCTG CCTGACCTTTG + +4 flyfactorsurvey__da_SANGER_10_FBgn0000413-da 3 0.0351812 860.285 1 6 CACCTG GCACACCTGCG - +4 taipale_cyt_meth__ESRRG_NYCAAGGTCAN_eDBD_meth_repr-ERR-ftz-f1-Hr39 2 0.0351812 860.285 1 6 CACCTG GTGACCTTGAC - +4 taipale_cyt_meth__TFAP2B_NGCCNNNGGCN_eDBD_meth-TfAP-2 0 0.0351812 860.285 1 6 CACCTG TGCCTCAGGCA - +4 transfac_pro__M00518-eg-kni-knrl-usp 12 0.035504 868.178 1 6 CACCTG CCTGACCCCAATGACCCGA - +4 stark__CASGTAR-sim 1 0.0355494 869.289 1 6 CACCTG CTACCTG - +4 transfac_pro__M01268-EcR-usp 2 0.0355494 869.289 1 5 CACCTG ATGACCT - +4 transfac_pro__M07280-EcR-Hr3-svp-usp 2 0.0355494 869.289 1 5 CACCTG CTGACCT - +4 transfac_pro__M05398-bowl-drm-odd-sob 3 0.0355861 870.187 1 6 CACCTG CCCAACCTGTCGGCCT - +4 transfac_pro__M02930 8 0.0357563 874.349 1 6 CACCTG CATAAGACCACCATTAC + +4 transfac_pro__M01699-bigmax-Clk-cnc-Max-Mitf-Myc-Usf 0 0.0362647 886.78 1 6 CACCTG CACGTG + +4 cisbp__M6450-btd-CTCF-HDAC1-Sin3A-Spps 5 0.0365979 894.929 1 6 CACCTG TTCAGCACCATGGACAGCGCCC + +4 hocomoco__REST_HUMAN.H11MO.0.A-CTCF-HDAC1-Sin3A-Spps-btd 5 0.0365979 894.929 1 6 CACCTG TTCAGCACCATGGACAGCGCCC + +4 transfac_pro__M01256-btd-CTCF-HDAC1-Sin3A-Spps 2 0.0365979 894.929 1 6 CACCTG AGCACCATGGACAGCGCCCAGC - +4 cisbp__M1453-EcR-Hr3 3 0.0366558 896.344 1 6 CACCTG GGTGACCTA + +4 cisbp__M6177-EcR-eg-ERR-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 1 0.0366558 896.344 1 6 CACCTG TGACCTTTG + +4 cisbp__M6215-ERR-ftz-f1-Hr39-Hr4-usp 1 0.0366558 896.344 1 6 CACCTG TGACCTTGA + +4 predrem__nrMotif2209 2 0.0366558 896.344 1 6 CACCTG CCAACCTGG + +4 transfac_pro__M07638-da 1 0.0366558 896.344 1 6 CACCTG ACACCTGCA + +4 hocomoco__ERR2_HUMAN.H11MO.0.A-ERR-EcR-Hr4-Hr39-ftz-f1-usp 1 0.0366558 896.344 1 6 CACCTG TGACCTTGA - +4 predrem__nrMotif793 3 0.0366558 896.344 1 6 CACCTG TGCAACTTT - +4 predrem__nrMotif890 0 0.0366558 896.344 1 6 CACCTG CAGCTGCAT - +4 predrem__nrMotif634 4 0.0366558 896.344 1 5 CACCTG ACACCACCC + +4 predrem__nrMotif642 4 0.0366558 896.344 1 5 CACCTG AAAACACCC + +4 cisbp__M4719-ERR 1 0.0369566 903.7 1 6 CACCTG TGACCTTG + +4 cisbp__M5271-tin-vnd 0 0.0369566 903.7 1 6 CACCTG CACTTGAA - +4 hocomoco__ASCL1_HUMAN.H11MO.0.A-ac-ase-esg-l(1)sc-nau-sc-sna-wor 3 0.0370575 906.166 1 6 CACCTG CTGCACCTGCTCCC + +4 neph__UW.Motif.0176 8 0.0370575 906.166 1 6 CACCTG GCAAACCCTGCCTC + +4 transfac_pro__M00804-esg-nau 1 0.0370575 906.166 1 6 CACCTG CCACCTGTCTCAGG + +4 transfac_pro__M07283-EcR-eg-ERR-kni-knrl 8 0.0370575 906.166 1 6 CACCTG GTCACCGTGACCTC + +4 taipale__Rxra_DBD_GGGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0370575 906.166 1 6 CACCTG TGACCTTTGACCCC - +4 neph__UW.Motif.0171 3 0.0371234 907.778 1 6 CACCTG AAAGTCCAAGGC + +4 transfac_pro__M09313 2 0.0372566 911.036 1 6 CACCTG TCCACCTAACATTACCACAAC - +4 cisbp__M4701-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 1 0.037629 920.142 1 6 CACCTG TGACCTCTGA + +4 predrem__nrMotif831 4 0.037629 920.142 1 6 CACCTG CTGTGACCTT + +4 transfac_public__M00183 2 0.037629 920.142 1 6 CACCTG CTCAACTGGC + +4 cisbp__M3585 2 0.037629 920.142 1 6 CACCTG CTCAACTGGC - +4 cisbp__M3591-ac-ase-da-esg-l(1)sc-nau-sc-sna-wor 2 0.037629 920.142 1 6 CACCTG AGCACCTGTC - +4 predrem__nrMotif511 0 0.037629 920.142 1 6 CACCTG TTCCTTTTTG - +4 swissregulon__hs__NKX2-1_4.p2-scro 1 0.037629 920.142 1 6 CACCTG ACACTTGAGT - +4 taipale_cyt_meth__TBX6_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.037629 920.142 1 6 CACCTG TTCACACCTT - +4 cisbp__M4903-da 3 0.0377189 922.339 1 6 CACCTG GCACACCTGCG + +4 taipale_cyt_meth__TFAP2A_NSCCYNRGGSN_FL_meth-TfAP-2 0 0.0377189 922.339 1 6 CACCTG TGCCTCAGGCA + +4 transfac_pro__M02108 2 0.0377189 922.339 1 6 CACCTG CCCACTTGAAG + +4 transfac_pro__M03562-EcR 1 0.0377189 922.339 1 6 CACCTG TGACCTTCGGT + +4 taipale_cyt_meth__DPF1_NCTATAGGTGN_eDBD_repr-d4-tth 1 0.0377189 922.339 1 6 CACCTG TCACCTATAGA - +4 factorbook__GATA3-GATAe-grn-pnr 7 0.0377866 923.996 1 6 CACCTG CTGATAACATCTCTG + +4 taipale_cyt_meth__NR2F6_NRGGTCRNTGACCYN_FL-EcR-svp-usp 9 0.0377866 923.996 1 6 CACCTG GAGGTCAGTGACCTT + +4 factorbook__NR2C2-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-svp-usp 1 0.0377866 923.996 1 6 CACCTG TGACCTTTGACCCCT - +4 taipale_cyt_meth__THRB_NRGGTCAAAGGTCAN_eDBD-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0377866 923.996 1 6 CACCTG ATGACCTTTGACCCC - +4 transfac_pro__M03543-EcR-eg-kni-knrl-svp-usp 5 0.0377866 923.996 1 6 CACCTG CCCTTGACCTTTGCC - +4 transfac_pro__M09289 2 0.0377866 923.996 1 6 CACCTG TTTACCTAATTTTTT - +4 transfac_pro__M01801-EcR-eg-ERR-kni-knrl 10 0.0377866 923.996 1 5 CACCTG AGGTCACTGTGACCT - +4 dbcorrdb__NANOG__ENCSR000BMT_1__m2-CG9650-HDAC1-opa 1 0.0377903 924.085 1 6 CACCTG CCCCCTGCTGAGATCTAAAT + +4 taipale_tf_pairs__ETV5_TCF3_RNCGGAAGNNNNNCASSTGN_CAP_repr-Ets96B 1 0.0377903 924.085 1 6 CACCTG CCACCTGCCCCACTTCCGCC - +4 cisbp__M6447-EcR-Hr78-usp 1 0.0379369 927.672 1 6 CACCTG TGACCTC + +4 flyfactorsurvey__ftz-f1_SANGER_5_FBgn0001078-ERR-EcR-ftz-f1-usp 1 0.0379369 927.672 1 6 CACCTG TGACCTT - +4 predrem__nrMotif623 1 0.0379369 927.672 1 6 CACCTG TTATCTG - +4 taipale_tf_pairs__GCM1_FIGLA_CAGCTGNNNNNNCCCGCAY_CAP_repr-gcm-gcm2 10 0.0381785 933.58 1 6 CACCTG CACGTGTAACTACCCGCAT + +4 taipale__THRB_DBD_NTGACCTNNNNNAGGTCAN_repr-EcR 2 0.0381785 933.58 1 6 CACCTG GTGACCTTAATAAGGTCAC - +4 taipale__GCM1_full_ATGCGGGYRCCCGCAT_repr-gcm-gcm2 7 0.0382317 934.881 1 6 CACCTG ATGCGGGTACCCGCAT - +4 transfac_pro__M06878 4 0.0383988 938.965 1 6 CACCTG CCCCCACCTACCGCATCC - +4 taipale_cyt_meth__ESR1_NAGGTCANNNYGACCTN_FL-EcR-eg-ERR-kni-knrl-svp 11 0.0384257 939.624 1 6 CACCTG AAGGTCACCGTGACCTT + +4 taipale_cyt_meth__ESR1_NAGGTCANNNYGACCTN_eDBD_repr-EcR-eg-ERR-kni-knrl-usp 11 0.0384257 939.624 1 6 CACCTG AAGGTCACGGTGACCTT + +4 transfac_pro__M07422-ac-ase-l(1)sc-sc 5 0.0386381 944.818 1 6 CACCTG CCTCACACCTGCC + +4 hocomoco__RXRG_HUMAN.H11MO.0.B-EcR-Hnf4-Hr51-Hr78-eg-kni-knrl-svp-usp 2 0.0386381 944.818 1 6 CACCTG GTGACCTTTGACC - +4 predrem__nrMotif866 1 0.0392019 958.604 1 6 CACCTG GGACCTTGG + +4 cisbp__M0203 2 0.0392019 958.604 1 6 CACCTG ACCACCTGG - +4 taipale_cyt_meth__GCM1_RTGCGGGTN_eDBD-gcm-gcm2 0 0.0392019 958.604 1 6 CACCTG CACCCGCAT - +4 predrem__nrMotif2377 -1 0.0392019 958.604 1 5 CACCTG ACCTTGAGA + +4 predrem__nrMotif2394 4 0.0392019 958.604 1 5 CACCTG TGAACACTT + +4 transfac_pro__M07901-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0392019 958.604 1 5 CACCTG TTCACACCT - +4 cisbp__M1457-CG8319-EcR-eg-Hr78-kni-knrl-svp-usp 2 0.0394683 965.118 1 6 CACCTG GTGACCTC + +4 predrem__nrMotif1821 0 0.0394683 965.118 1 6 CACCTG CACCTTGG + +4 yetfasco__YOR032C_1498 1 0.0394683 965.118 1 6 CACCTG CTACGTGT + +4 stark__GCAGSTGK-nau-sc 1 0.0394683 965.118 1 6 CACCTG ACACCTGC - +4 transfac_pro__M09583 -1 0.0394683 965.118 1 5 CACCTG ACCTAACT + +4 taipale_cyt_meth__ZNF276_NTTAAGGNNGTANNNWCSNCCTTAN_eDBD_repr 17 0.039492 965.698 1 6 CACCTG GTTAAGGTAGTATAGTCCACCTTAA + +4 cisbp__M2582-sna 2 0.0397709 972.518 1 6 CACCTG ACCACCTGTTTGCA + +4 cisbp__M6059-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 8 0.0397709 972.518 1 6 CACCTG TGACCTTTGACCTC + +4 cisbp__M6079-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0397709 972.518 1 6 CACCTG TGACCTTTGACCCC + +4 taipale_cyt_meth__RARB_NRGGTCRTGACCYN_FL_meth-EcR-eg-ftz-f1-Hr78-kni-knrl-usp 8 0.0397709 972.518 1 6 CACCTG AAGGTCGTGACCTT + +4 transfac_public__M00044-sna 2 0.0397709 972.518 1 6 CACCTG ACCACCTGTTTGCA + +4 cisbp__M3516-GATAe-grn-pnr 3 0.0398045 973.34 1 6 CACCTG CTGCACCTGGCG + +4 cisbp__M6062-achi-hth-nau-vis 3 0.0398045 973.34 1 6 CACCTG TGACACCTGTCA + +4 neph__UW.Motif.0435 2 0.0398045 973.34 1 6 CACCTG GAGGCCTGGCCA + +4 neph__UW.Motif.0181 3 0.0398045 973.34 1 6 CACCTG GAGAAGCTTCTG - +4 neph__UW.Motif.0654 4 0.0398045 973.34 1 6 CACCTG CCGGCACCTGGG - +4 transfac_pro__M05863 1 0.0398045 973.34 1 6 CACCTG GAACCTGGAACA - +4 transfac_public__M00277-GATAe-grn-pnr 3 0.0398045 973.34 1 6 CACCTG CTGCACCTGGCG - +4 taipale_tf_pairs__HOXB2_TBX3_AGGTGTTAATKN_CAP-bi-pb 7 0.0398045 973.34 1 5 CACCTG CCATTAACACCT - +4 taipale_tf_pairs__MGA_EVX1_AGGTGNTAATKW_CAP-eve 7 0.0398045 973.34 1 5 CACCTG TCATTAACACCT - +4 transfac_pro__M06685 7 0.0398045 973.34 1 5 CACCTG TATCATTTACCG - +4 cisbp__M1432-tll 3 0.040278 984.919 1 6 CACCTG ATTGACCTCT + +4 cisbp__M0537 3 0.040278 984.919 1 6 CACCTG CCACACCTCC - +4 cisbp__M1639-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.040278 984.919 1 6 CACCTG TTGACACCTT - +4 hocomoco__ERR3_MOUSE.H11MO.0.C-ERR-Hr4-ftz-f1 2 0.040278 984.919 1 6 CACCTG GTGACCTTGA - +4 taipale__ESRRG_full_TSAAGGTCAN-ERR-ftz-f1-Hr39 2 0.040278 984.919 1 6 CACCTG ATGACCTTGA - +4 taipale_cyt_meth__SOHLH2_NGCACGTGCN_eDBD_meth 2 0.040278 984.919 1 6 CACCTG TGCACGTGCT - +4 transfac_pro__M04622-Hnf4-Hr38 3 0.040278 984.919 1 6 CACCTG CTTGACCTTT - +4 taipale_cyt_meth__ESRRA_NYCAAGGTCAN_eDBD_meth-ERR-ftz-f1-Hr39 2 0.0404104 988.156 1 6 CACCTG GTGACCTTGAC - +4 predrem__nrMotif2288 1 0.0404574 989.305 1 6 CACCTG GCACTTT + +4 elemento__AAGGTCA-EcR-ERR-usp 1 0.0404574 989.305 1 6 CACCTG TGACCTT - +4 elemento__CAAGGTC 0 0.0404574 989.305 1 6 CACCTG GACCTTG - +4 hocomoco__MYF6_HUMAN.H11MO.0.C-ac-ase-l(1)sc-nau-sc 0 0.0404574 989.305 1 6 CACCTG CAGCTGC - +4 predrem__nrMotif1988 1 0.0404574 989.305 1 6 CACCTG ACACTTT - +4 cisbp__M6058-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.0405629 991.885 1 6 CACCTG TGACCTTTTGACCTC + +4 cisbp__M2326-CTCF-SMC3-usp-vtd 5 0.0405629 991.885 1 6 CACCTG GGCGCCATCTAGCGG - +4 neph__UW.Motif.0469 7 0.0405629 991.885 1 6 CACCTG TGCCCCCCCCCTCCC - +4 taipale__Nr2f6_DBD_RRGGTCAAAAGGTCA-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.0405629 991.885 1 6 CACCTG TGACCTTTTGACCTC - +4 taipale_cyt_meth__RXRG_NRGGTCAAAGGTCAN_FL_meth-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0405629 991.885 1 6 CACCTG TTGACCTTTGACCCC - +4 transfac_pro__M08969-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 3 0.0405629 991.885 1 6 CACCTG TTTGACCTTTGACCT - +4 transfac_pro__M09296 2 0.0405629 991.885 1 6 CACCTG TTTACCAAACTTATT - +4 cisbp__M5938-EcR 2 0.041034 1003.4 1 6 CACCTG GTGACCTTAATAAGGTCAC - +4 taipale_cyt_meth__THRB_NTGACCTNNNNNAGGTCAN_FL_meth-EcR 2 0.041034 1003.4 1 6 CACCTG GTGACCTCATTGAGGTCAC - +4 neph__UW.Motif.0215 7 0.041052 1003.84 1 6 CACCTG AGGCAGATGCCATCTG + +4 cisbp__M5485-gcm-gcm2 7 0.041052 1003.84 1 6 CACCTG ATGCGGGTACCCGCAT - +4 taipale_tf_pairs__GCM2_EOMES_RTGCGGGNAGGTGNNN_CAP_repr-gcm-gcm2 3 0.041052 1003.84 1 6 CACCTG TCACACCTACCCGCAT - +4 neph__UW.Motif.0639 -2 0.041052 1003.84 1 4 CACCTG CCTGCTCTGCCAGCTG - +4 hdpi__CBX7-Pc-svp 1 0.0411963 1007.37 1 5 CACCTG TGACCT - +4 taipale__THRB_DBD_NTGACCTNATNAGGTCAN-EcR 2 0.041257 1008.86 1 6 CACCTG GTGACCTTATAAGGTCAC + +4 transfac_pro__M06879 4 0.041257 1008.86 1 6 CACCTG CCCCCACCTACCGCATTC - +4 taipale_tf_pairs__ETV5_TCF3_CASSTGNRNNGGAAGNN_CAP-Ets96B 11 0.0412728 1009.24 1 6 CACCTG CACTTCCGCCCCACCTG - +4 cisbp__M6462-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0414349 1013.21 1 6 CACCTG GTGACCTTTGACC + +4 cisbp__M0292-Xbp1 2 0.0418893 1024.32 1 6 CACCTG GTGACGTGT + +4 predrem__nrMotif912 -1 0.0418893 1024.32 1 5 CACCTG TCCTTTCAT - +4 cisbp__M1495-Hr78-svp-usp 2 0.0421194 1029.94 1 6 CACCTG GTGACCCC + +4 cisbp__M0500-CG6769 1 0.0421194 1029.94 1 6 CACCTG GCCCCTGA - +4 transfac_pro__M00712-ac-ase-l(1)sc-nau-sc 0 0.0421194 1029.94 1 6 CACCTG CACCTGCC - +4 predrem__nrMotif1889 3 0.0421194 1029.94 1 5 CACCTG GCTCACAT - +4 predrem__nrMotif701 3 0.0421194 1029.94 1 5 CACCTG TGTTACTT - +4 taipale_cyt_meth__CREB3L1_TGCCACGTGGCA_FL-Atf6-Clk-CrebA-Max-Mnt 3 0.0426506 1042.93 1 6 CACCTG TGCCACGTGGCA + +4 taipale_cyt_meth__CREB3L4_YGCCACGTGGCA_eDBD-Atf6-Clk-CrebA-Max-Mnt 3 0.0426506 1042.93 1 6 CACCTG CGCCACGTGGCA + +4 taipale_cyt_meth__ZNF524_NYTCGNACCCKN_FL_repr 5 0.0426506 1042.93 1 6 CACCTG ACTCGAACCCGT + +4 neph__UW.Motif.0267 1 0.0426506 1042.93 1 6 CACCTG TCAATTCCCACC - +4 taipale__Meis3_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.0426506 1042.93 1 6 CACCTG TGACACCTGTCA - +4 taipale__Pknox2_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.0426506 1042.93 1 6 CACCTG TGACACCTGTCA - +4 taipale_cyt_meth__TFAP2E_TGCCCNNNGGCN_FL_meth-TfAP-2 0 0.0426506 1042.93 1 6 CACCTG TGCCTCAGGGCA - +4 transfac_pro__M07464 0 0.0426506 1042.93 1 6 CACCTG CATCTGTCACCC - +4 yetfasco__YDL020C_1700 5 0.0426506 1042.93 1 6 CACCTG TTTGCCACCGTG - +4 transfac_pro__M05915 7 0.0426506 1042.93 1 5 CACCTG CCCGCTTTACCA - +4 neph__UW.Motif.0600 1 0.0426582 1043.12 1 6 CACCTG CTGCCCGCCCTGAG + +4 scertf__harbison.ZAP1 2 0.0426582 1043.12 1 6 CACCTG ACAACCTTGAGGGT - +4 taipale__Nr2f6_DBD_RRGGTCAAAGGTCA-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 8 0.0426582 1043.12 1 6 CACCTG TGACCTTTGACCTC - +4 cisbp__M1956-btd-CTCF-HDAC1-Sin3A-Spps 5 0.0430764 1053.35 1 6 CACCTG TTCAGCACCATGGACAGCGCC + +4 jaspar__MA0138.2-CTCF-HDAC1-Sin3A-Spps-btd 5 0.0430764 1053.35 1 6 CACCTG TTCAGCACCATGGACAGCGCC + +4 transfac_pro__M09302 12 0.0430764 1053.35 1 6 CACCTG CTTCAAAATTTTCACCTACCT + +4 cisbp__M0082-TfAP-2 0 0.0430764 1053.35 1 6 CACCTG CGCCTCAGGG + +4 cisbp__M0161 2 0.0430764 1053.35 1 6 CACCTG AGCACGTGCT + +4 cisbp__M1291 2 0.0430764 1053.35 1 6 CACCTG TTAACCCCAG + +4 cisbp__M1437-EcR-Hnf4-Hr78-svp-usp 3 0.0430764 1053.35 1 6 CACCTG CTTGACCTTT + +4 cisbp__M5413-ERR-ftz-f1-Hr39 2 0.0430764 1053.35 1 6 CACCTG ATGACCTTGA + +4 predrem__nrMotif2468-Usf-cnc 4 0.0430764 1053.35 1 6 CACCTG GGGTCACTTG - +4 transfac_pro__M01859-TfAP-2 1 0.0431168 1054.34 1 6 CACCTG TAGCCTG + +4 cisbp__M0149 1 0.0431168 1054.34 1 6 CACCTG GCACGTG - +4 cisbp__M0151-Max-Myc 1 0.0431168 1054.34 1 6 CACCTG CCACGTG - +4 cisbp__M6376-vnd 0 0.0431168 1054.34 1 6 CACCTG CACTTGA - +4 cisbp__M6219-EcR-ERR 2 0.0431168 1054.34 1 5 CACCTG GTGACCT + +4 cisbp__M5921-TfAP-2 0 0.0432604 1057.85 1 6 CACCTG TGCCTGAGGCT + +4 taipale__TFAP2C_DBD_NSCCNNNGGSN-TfAP-2 0 0.0432604 1057.85 1 6 CACCTG TGCCTGAGGCT - +4 neph__UW.Motif.0665 3 0.0435185 1064.16 1 6 CACCTG AGATACTTTTCAAAT + +4 taipale_tf_pairs__FLI1_TCF3_NCCGGANNCASSTGY_CAP 8 0.0435185 1064.16 1 6 CACCTG ACCGGAAGCAGCTGC + +4 cisbp__M4441-CTCF-SMC3-usp-vtd 2 0.0435185 1064.16 1 6 CACCTG GCCCCCTGGTGGCCG - +4 cisbp__M4589-btd-CTCF-HDAC1-Sin3A-Spps 4 0.0435185 1064.16 1 6 CACCTG TCAGCACCATGGACA - +4 taipale_cyt_meth__NR2F6_NRGGTCAAAGGTCAN_eDBD-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 9 0.0435185 1064.16 1 6 CACCTG TTGACCTTTGACCTT - +4 taipale_cyt_meth__THRB_NRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0435185 1064.16 1 6 CACCTG CTGACCTTTGACCCC - +4 dbcorrdb__ESR1__ENCSR000BIY_1__m2-EcR-ERR 14 0.043662 1067.67 1 6 CACCTG CACCAGGGCAGGGTGACCTG + +4 taipale__THRB_DBD_NTGACCTYANNTRAGGTCAN_repr-EcR 2 0.043662 1067.67 1 6 CACCTG GTGACCTTACATAAGGTCAC + +4 neph__UW.Motif.0460 0 0.0440556 1077.29 1 6 CACCTG AAGCTGTGGCTCCCAG + +4 cisbp__M4630-btd-CTCF-HDAC1-Sin3A-Spps 4 0.0440556 1077.29 1 6 CACCTG TCAGCACCATGGACAG - +4 neph__UW.Motif.0015 9 0.0440556 1077.29 1 6 CACCTG GAGCCAGCGTGCCCGG - +4 neph__UW.Motif.0457 3 0.0440556 1077.29 1 6 CACCTG AAGTCCCAGCCTCTCT - +4 neph__UW.Motif.0677 8 0.0440556 1077.29 1 6 CACCTG TCTGCTTTTTTCTGCT - +4 transfac_pro__M06922 13 0.0440799 1077.89 1 6 CACCTG AACAACACGGCAGTCCCTT - +4 cisbp__M5936-EcR 2 0.0443042 1083.37 1 6 CACCTG GTGACCTTATGAGGTCAC + +4 cisbp__M5937-EcR 2 0.0443042 1083.37 1 6 CACCTG GTGACCTTATAAGGTCAC + +4 taipale__THRA_FL_NTGACCTNATNAGGTCAN_repr-EcR 2 0.0443042 1083.37 1 6 CACCTG GTGACCTTATGAGGTCAC + +4 taipale_cyt_meth__TBX20_NAGGTGTKARGGYGTKAN_FL-bi-Doc3-H15-mid-org-1 12 0.0443042 1083.37 1 6 CACCTG TTCACACCCTCACACCTT - +4 taipale_cyt_meth__TBX20_NAGGTGTKARGGYGTKAN_FL_meth-H15-mid-org-1 12 0.0443042 1083.37 1 6 CACCTG ATCACACCCTCACACCTT - +4 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNGCGGGYN_CAP_repr-gcm-gcm2-Max 0 0.0443042 1083.37 1 6 CACCTG CACCCGCATCCACGTGCC - +4 hocomoco__ERR2_MOUSE.H11MO.0.A-ERR-EcR-Hr4-Hr39-ftz-f1 5 0.0443064 1083.42 1 6 CACCTG AGGATGACCTTGAACTT - +4 cisbp__M5685-Hr38 12 0.0443064 1083.42 1 5 CACCTG AGGTCACAGTTTGACCT + +4 taipale__NR4A2_full_AGGTCANNNNNTGACCT_repr-Hr38 12 0.0443064 1083.42 1 5 CACCTG AGGTCACAGTTTGACCT - +4 jaspar__MA0576.1 1 0.0444057 1085.85 1 6 CACCTG CCACCTACCCCCC + +4 transfac_pro__M08871 3 0.0444057 1085.85 1 6 CACCTG GGTCACGTGCGGA + +4 transfac_pro__M03883-CTCF-HDAC1 5 0.0444057 1085.85 1 6 CACCTG TTCAGCACCACGG - +4 cisbp__M1396 1 0.0447249 1093.66 1 6 CACCTG AACCCTAAT + +4 predrem__nrMotif1956 3 0.0447249 1093.66 1 6 CACCTG ATGCCCCTG + +4 predrem__nrMotif641 3 0.0447249 1093.66 1 6 CACCTG AGGACCCTG + +4 transfac_pro__M01692-Tsf1-Tsf2-Tsf3 2 0.0447249 1093.66 1 6 CACCTG GGCACTTGC + +4 cisbp__M0463 1 0.0447249 1093.66 1 6 CACCTG GTGCCCAAC - +4 cisbp__M6288-ac-ase-l(1)sc-nau-sc 1 0.0447249 1093.66 1 6 CACCTG ACACCTGCT - +4 cisbp__M0282 4 0.0447249 1093.66 1 5 CACCTG GTGCCACGT + +4 predrem__nrMotif2585 4 0.0447249 1093.66 1 5 CACCTG TGGCCAACT - +4 cisbp__M1086-bap-scro-vnd 1 0.0449165 1098.34 1 6 CACCTG GCACTTAA + +4 transfac_pro__M07247-Clk 1 0.0449165 1098.34 1 6 CACCTG CCACCTGT + +4 cisbp__M0527-CG10348-CG13296-ham 1 0.0449165 1098.34 1 6 CACCTG ACCCCTTA - +4 cisbp__M5243-tin-vnd 0 0.0449165 1098.34 1 6 CACCTG CACTTAAA - +4 cisbp__M0071 3 0.0449165 1098.34 1 5 CACCTG GTGCACCC + +4 tfdimers__MD00586-eg-Jra-kay-kni-knrl 7 0.0449562 1099.31 1 6 CACCTG TTTCCCTGACCTTAGCTGACTCATATTT - +4 cisbp__M6051-achi-hth-nau-vis 3 0.045667 1116.69 1 6 CACCTG TGACACCTGTCA + +4 transfac_pro__M01589-ERR-ftz-f1 4 0.045667 1116.69 1 6 CACCTG GGGTGACCTTGA - +4 transfac_pro__M06929-Mad 7 0.045667 1116.69 1 5 CACCTG AGGTCTAGACCT + +4 transfac_pro__M06973-Mad 7 0.045667 1116.69 1 5 CACCTG AGGTCTAGACCT + +4 taipale_cyt_meth__RARG_NRGGTCRTGACCYN_eDBD-EcR-eg-ftz-f1-Hr78-kni-knrl-usp 8 0.0457271 1118.17 1 6 CACCTG AAGGTCATGACCTT + +4 neph__UW.Motif.0545 3 0.0457271 1118.17 1 6 CACCTG TGAAAACTTTTCTG - +4 cisbp__M4979-EcR-ERR-ftz-f1-usp 1 0.0459218 1122.93 1 6 CACCTG TGACCTT + +4 predrem__nrMotif211 2 0.0459218 1122.93 1 5 CACCTG TTTATCT - +4 transfac_pro__M04883 2 0.0459218 1122.93 1 5 CACCTG CGCACCT - +4 predrem__nrMotif2037 3 0.0459218 1122.93 1 4 CACCTG CTTGACC + +4 cisbp__M1459 3 0.0460301 1125.58 1 6 CACCTG ACTGACCTCT + +4 jaspar__MA0956.1 2 0.0460301 1125.58 1 6 CACCTG AGCACGTGCT + +4 predrem__nrMotif1253 3 0.0460301 1125.58 1 6 CACCTG TCTGACCTTC + +4 yetfasco__YPR009W_2236 2 0.0460301 1125.58 1 6 CACCTG GGGACCTGGG + +4 predrem__nrMotif1092 1 0.0460301 1125.58 1 6 CACCTG CCAGCTGACC - +4 taipale_cyt_meth__RARA_NRRGGTCANN_eDBD-EcR-Hnf4-Hr78-svp-usp 3 0.0460301 1125.58 1 6 CACCTG CGTGACCTTT - +4 transfac_pro__M02009-EcR-Hr4-usp 3 0.0460301 1125.58 1 6 CACCTG CTTGACCTTG - +4 taipale_cyt_meth__TFAP2E_NGCCNNNGGCN_FL_meth-TfAP-2 0 0.0462733 1131.52 1 6 CACCTG TGCCTCAGGCA + +4 transfac_pro__M07435-twi 3 0.0462733 1131.52 1 6 CACCTG AAACACCTGGA + +4 cisbp__M5914-TfAP-2 0 0.0462733 1131.52 1 6 CACCTG TGCCTCAGGCT - +4 taipale_cyt_meth__ESRRA_NYCAAGGTCAN_FL_meth-EcR-ERR-ftz-f1-Hr39 2 0.0462733 1131.52 1 6 CACCTG ATGACCTTGAC - +4 transfac_pro__M07426-EcR-Hr38-usp 4 0.0462733 1131.52 1 6 CACCTG CTGTGACCTTT - +4 transfac_pro__M09195 10 0.0462828 1131.75 1 6 CACCTG AGATACAATGAACCTAGACAC - +4 cisbp__M5680-EcR-eg-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 1 0.0466615 1141.01 1 6 CACCTG TGACCTTTTGACCTC + +4 cisbp__M6068-EcR-eg-Hnf4-kni-knrl-svp-usp 9 0.0466615 1141.01 1 6 CACCTG TGACCTTTTGACCTT + +4 neph__UW.Motif.0503 7 0.0466615 1141.01 1 6 CACCTG AAAATCCAGCCTGTG + +4 neph__UW.Motif.0617 3 0.0466615 1141.01 1 6 CACCTG CACATCCTGCTTCCA + +4 taipale_cyt_meth__NR2F6_NRGGTCRNTGACCYN_eDBD-EcR-eg-kni-knrl-svp-usp 9 0.0466615 1141.01 1 6 CACCTG AAGGTCACTGACCTT + +4 taipale__NR2F6_DBD_RRGGTCAAAAGGTCA-EcR-eg-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 1 0.0466615 1141.01 1 6 CACCTG TGACCTTTTGACCTC - +4 taipale__Rara_DBD_RRGGTCAAAAGGTCA-EcR-eg-Hnf4-kni-knrl-svp-usp 9 0.0466615 1141.01 1 6 CACCTG TGACCTTTTGACCTT - +4 taipale_cyt_meth__RXRB_NRGGTCAAAGGTCAN_eDBD-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0466615 1141.01 1 6 CACCTG GTGACCTTTGACCTC - +4 transfac_pro__M09001-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 9 0.0466615 1141.01 1 6 CACCTG TGACCTTTTGACCTC - +4 hdpi__NCBP2-Cbp20 0 0.0467083 1142.16 1 6 CACCTG GACGTG + +4 cisbp__M5939-EcR 2 0.0468945 1146.71 1 6 CACCTG GTGACCTTACATAAGGTCAC - +4 taipale_tf_pairs__GCM2_HES7_RTRNKGGTNNNGCACGYGNN_CAP_repr-gcm-gcm2 11 0.0468945 1146.71 1 6 CACCTG GACACGTGCCATACCCGCAT - +4 neph__UW.Motif.0129 7 0.0472514 1155.44 1 6 CACCTG AGAGAGGTGGCTGCTG + +4 transfac_pro__M01407-achi-esg-hth-sna-vis-wor 3 0.0472514 1155.44 1 6 CACCTG AACTAGCTGTCAATAC + +4 neph__UW.Motif.0611 8 0.0472514 1155.44 1 6 CACCTG CAGGCCTCCTCCTCCT - +4 taipale_cyt_meth__PPARD_NRRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.0472514 1155.44 1 6 CACCTG ATGACCTTTGACCCCT - +4 taipale_tf_pairs__PITX1_EOMES_GGATTANNARGTGTKN_CAP_repr-Ptx1 3 0.0472514 1155.44 1 6 CACCTG TCACACCTGCTAATCC - +4 taipale_tf_pairs__PITX1_TBX21_AGGTGNGAARGGATTA_CAP_repr-Ptx1 11 0.0472514 1155.44 1 5 CACCTG TAATCCCTTCACACCT - +4 cisbp__M3206-EcR-ERR 12 0.047326 1157.26 1 6 CACCTG ACAGGTCACTGTGACCTGA + +4 transfac_public__M00191-EcR-ERR 12 0.047326 1157.26 1 6 CACCTG ACAGGTCACTGTGACCTGA + +4 taipale_tf_pairs__HOXB2_ESRRB_TAATKRNNNNNNAAGGTCA_CAP_repr-ERR-pb 1 0.047326 1157.26 1 6 CACCTG TGACCTTGAAACGTAATTA - +4 cisbp__M5769-EcR-ERR-Hr3-usp 12 0.0475497 1162.73 1 6 CACCTG TGACCTTTGCTTGACCTT + +4 cisbp__M6217-EcR-eg-ERR-kni-knrl 10 0.0475497 1162.73 1 6 CACCTG AGGTCACGGTGACCTGGG + +4 taipale__RARG_DBD_RRGGTCANNNARAGGTCA-EcR-eg-ERR-Hr3-Hr78-kni-knrl-svp-usp 1 0.0475497 1162.73 1 6 CACCTG TGACCTTTAGTTGACCTT - +4 taipale__RARG_full_RRGGTCANNNARAGGTCA-EcR-ERR-Hr3-usp 12 0.0475497 1162.73 1 6 CACCTG TGACCTTTGCTTGACCTT - +4 transfac_pro__M05823-Kr 12 0.0475497 1162.73 1 6 CACCTG GCACTACCGATTTACCTC - +4 transfac_pro__M07965-Hr96 12 0.0475497 1162.73 1 6 CACCTG TAAGTGCACGTGTACCCA - +4 transfac_pro__M00763-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 1 0.047557 1162.91 1 6 CACCTG TGACCTTTGACCC + +4 transfac_pro__M01198-btd-EcR-eg-ftz-f1-HDAC1-Hnf4-Hr4-Hr51-Hr78-kni-knrl-Spps-svp-usp 8 0.047557 1162.91 1 5 CACCTG TGACCTTTGACCT - +4 cisbp__M6498-ERR-ftz-f1-Hr4-usp 1 0.0477158 1166.79 1 6 CACCTG TGACCTTGA + +4 stark__RACASCTGY-ac-ase-l(1)sc-sc 2 0.0477158 1166.79 1 6 CACCTG AACACCTGC + +4 predrem__nrMotif2207 2 0.0477158 1166.79 1 6 CACCTG CAGACCTGC - +4 transfac_pro__M07962-EcR-Hr38 1 0.0477158 1166.79 1 6 CACCTG TGACCTTTA - +4 predrem__nrMotif199 4 0.0477158 1166.79 1 5 CACCTG TTTCCACCA + +4 cisbp__M4921-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0477158 1166.79 1 5 CACCTG TTCACACCT - +4 predrem__nrMotif1834 5 0.0477158 1166.79 1 4 CACCTG TTCTTTACC + +4 cisbp__M0539 1 0.0478662 1170.47 1 6 CACCTG GCCCCTGA - +4 flyfactorsurvey__Tin_SOLEXA_FBgn0004110-tin-vnd 0 0.0478662 1170.47 1 6 CACCTG CACTTAAG - +4 cisbp__M0058 3 0.0478662 1170.47 1 5 CACCTG TGCCACCA + +4 hocomoco__ZN431_MOUSE.H11MO.0.C 7 0.0479492 1172.5 1 6 CACCTG AGATACCAACCTAAGACAGGCAC + +4 cisbp__M1958-EcR-ERR-ftz-f1-Hr4-srl-usp 1 0.0488588 1194.74 1 6 CACCTG TGACCTTGAGCT + +4 transfac_pro__M06629 2 0.0488588 1194.74 1 6 CACCTG TGAACCTTCCGA + +4 yetfasco__YJL056C_2097 0 0.0488588 1194.74 1 6 CACCTG AACCCTTAGGGT + +4 stark__TAACCTC 1 0.0488795 1195.25 1 6 CACCTG TAACCTC + +4 cisbp__M6353-ac-ase-l(1)sc-nau-sc 0 0.0488795 1195.25 1 6 CACCTG CAGCTGC - +4 predrem__nrMotif2106 -2 0.0488795 1195.25 1 4 CACCTG CCTAACA + +4 neph__UW.Motif.0255 5 0.0489849 1197.83 1 6 CACCTG CAAGATTCCATCTG + +4 neph__UW.Motif.0364 7 0.0489849 1197.83 1 6 CACCTG CTGTGGGTTTCTGA + +4 transfac_pro__M04695-CTCF-HDAC1-Sin3A 5 0.0489849 1197.83 1 6 CACCTG TTCAGCACCACGGA + +4 neph__UW.Motif.0168 5 0.0489849 1197.83 1 6 CACCTG CTGGGTTCCAGCTG - +4 taipale_cyt_meth__RXRG_NRGGTCAYGACCYN_FL_meth-EcR-eg-Hr78-kni-knrl-usp 8 0.0489849 1197.83 1 6 CACCTG GAGGTCGTGACCTC - +4 taipale_tf_pairs__GCM1_HOXA13_RKRNGGGNNATAAA_CAP-gcm-gcm2 5 0.0489849 1197.83 1 6 CACCTG TTTATTACCCGCAT - +4 cisbp__M1292 2 0.0491457 1201.76 1 6 CACCTG TTAACCACAG + +4 cisbp__M1461 4 0.0491457 1201.76 1 6 CACCTG TTTGCACTTT + +4 predrem__nrMotif2388 4 0.0491457 1201.76 1 6 CACCTG GGAGACCCTG + +4 transfac_pro__M09566 4 0.0491457 1201.76 1 6 CACCTG ATTGCACCAC + +4 cisbp__M1347 1 0.0491457 1201.76 1 6 CACCTG TTAACGGCCC - +4 cisbp__M1633-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0491457 1201.76 1 6 CACCTG TTCACACCTC - +4 taipale_cyt_meth__TBX3_NAGGTGTGAN_eDBD-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0491457 1201.76 1 6 CACCTG TTCACACCTC - +4 cisbp__M1632-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.0491457 1201.76 1 5 CACCTG TTTCACACCT - +4 predrem__nrMotif2516 4 0.0494543 1209.31 1 6 CACCTG CACACCCCTCC + +4 taipale_cyt_meth__ZBTB45_NCACCTATAKN_eDBD-d4-tth 1 0.0494543 1209.31 1 6 CACCTG TCACCTATAGA + +4 transfac_pro__M07627-TfAP-2 0 0.0494543 1209.31 1 6 CACCTG TGCCTGAGGCA + +4 factorbook__ESRRA-ERR-srl 1 0.0494543 1209.31 1 6 CACCTG TGACCTTGGGC - +4 predrem__nrMotif2089 5 0.0494543 1209.31 1 6 CACCTG TCACTGACCTC - +4 taipale_cyt_meth__DPF1_NCTATAGGTGN_eDBD_meth-d4-tth 1 0.0494543 1209.31 1 6 CACCTG TCACCTATAGC - +4 taipale_cyt_meth__ESRRA_NYCAAGGTCAN_eDBD-ERR-ftz-f1-Hr39 2 0.0494543 1209.31 1 6 CACCTG ATGACCTTGAC - +4 taipale_cyt_meth__ESRRB_NYCAAGGTCAN_eDBD_meth-ERR-ftz-f1-Hr39 2 0.0494543 1209.31 1 6 CACCTG ATGACCTTGAA - +4 taipale_cyt_meth__ESRRG_NYCAAGGTCAN_eDBD-ERR-ftz-f1-Hr39 2 0.0494543 1209.31 1 6 CACCTG GTGACCTTGAC - +4 yetfasco__YPL202C_389 1 0.0496955 1215.2 1 5 CACCTG GCACCC + +4 taipale_cyt_meth__TBX20_NAGGTGTGANNNTCACACCTN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 15 0.0497009 1215.34 1 6 CACCTG AAGGTGTGAAATTCACACCTT + +4 hocomoco__TF2LX_HUMAN.H11MO.0.D-achi-hth-vis 7 0.0500001 1222.65 1 6 CACCTG ACTATGACAGCTGTC - +4 jaspar__MA0065.2-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 1 0.0500001 1222.65 1 6 CACCTG TGACCTTTGCCCTAC - +4 taipale_tf_pairs__GCM1_HOXB13_RTRNGGGTNNTAAAN_CAP-gcm-gcm2 6 0.0500001 1222.65 1 6 CACCTG TTTTATTACCCGCAT - +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m1-CG9650 0 0.0503383 1230.92 1 6 CACCTG CTCCTGCTGTGTAGCTATTT + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m8-E(z) 9 0.0503383 1230.92 1 6 CACCTG GTTCACCCCAACCTCAAGGA + +4 cisbp__M4544-btd-CTCF-HDAC1-Sin3A-Spps 2 0.050648 1238.49 1 6 CACCTG AGCACCATGGACAGCG + +4 neph__UW.Motif.0331 7 0.050648 1238.49 1 6 CACCTG GGCCTGGCTTCTGCCA + +4 transfac_pro__M02934 2 0.050648 1238.49 1 6 CACCTG GAGCCCTTGTCCCTTG + +4 transfac_pro__M05423-peb 5 0.050648 1238.49 1 6 CACCTG GCGTTTACCCGCCACA - +4 transfac_public__M00239-EcR 6 0.050648 1238.49 1 6 CACCTG TGGCGTGACCTCACTG - +4 cisbp__M5409-EcR-ERR-usp 1 0.0507819 1241.77 1 6 CACCTG TGACCTTGAAATGACCTTG + +4 taipale_cyt_meth__THRB_NTGACCTNNNNNAGGTCAN_FL_repr-EcR 2 0.0507819 1241.77 1 6 CACCTG GTGACCTCAATGAGGTCAC - +4 cisbp__M0014 0 0.0508692 1243.9 1 6 CACCTG CACCGACCA + +4 cisbp__M0015 1 0.0508692 1243.9 1 6 CACCTG CCACCGACA + +4 transfac_pro__M02100-achi-hth-nau-vis 0 0.0508692 1243.9 1 6 CACCTG CAGCTGTCA + +4 cisbp__M1352 2 0.0508692 1243.9 1 6 CACCTG TAAATCTCG - +4 cisbp__M2060-vnd 0 0.0508692 1243.9 1 6 CACCTG CACTTGAAA - +4 flyfactorsurvey__Vnd_Cell_FBgn0003986-vnd 0 0.0508692 1243.9 1 6 CACCTG CACTTGAAA - +4 predrem__nrMotif1134 0 0.0508692 1243.9 1 6 CACCTG CACCGGCCC - +4 predrem__nrMotif198 0 0.0508692 1243.9 1 6 CACCTG CATCTCTGC - +4 flyfactorsurvey__Doc2_SANGER_5_FBgn0035956-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.0508692 1243.9 1 5 CACCTG TTCACACCT + +4 predrem__nrMotif2408 -1 0.0508692 1243.9 1 5 CACCTG CCCTGTTGT - +4 cisbp__M6389-EcR-Hr78-svp 2 0.0508947 1244.53 1 6 CACCTG CTGACCTCTGGCC + +4 hocomoco__NR2C1_HUMAN.H11MO.0.C-EcR-Hr78-svp 2 0.0508947 1244.53 1 6 CACCTG CTGACCTCTGGCC - +4 taipale_tf_pairs__HOXB2_TCF3_NCACCTGNNNNNMATTA_CAP_repr-pb 1 0.0509697 1246.36 1 6 CACCTG GCACCTGCACCCCATTA + +4 jaspar__MA0159.1-EcR-usp 1 0.0509697 1246.36 1 6 CACCTG TGACCTCTCCATGACCT - +4 predrem__nrMotif2113 1 0.0509754 1246.5 1 6 CACCTG CCACCTAG + +4 cisbp__M0534-CG6769 1 0.0509754 1246.5 1 6 CACCTG GCCCCTGA - +4 elemento__AAGGTCAC-EcR-ERR 2 0.0509754 1246.5 1 6 CACCTG GTGACCTT - +4 elemento__CAAGGTCA-ERR-ftz-f1-Hr4-srl 1 0.0509754 1246.5 1 6 CACCTG TGACCTTG - +4 elemento__CCAAGGTC 0 0.0509754 1246.5 1 6 CACCTG GACCTTGG - +4 predrem__nrMotif1022 3 0.0509754 1246.5 1 5 CACCTG CTGTACTT + +4 cisbp__M5411-EcR-ERR-usp 12 0.0510029 1247.17 1 6 CACCTG TGACCTTGAAATGACCTT + +4 cisbp__M5766-EcR-eg-ERR-Hr3-Hr78-kni-knrl-svp-usp 1 0.0510029 1247.17 1 6 CACCTG TGACCTTTAGTTGACCTT + +4 taipale_cyt_meth__ZNF580_CCTACCCTNNCCTACCCY_eDBD_repr 8 0.0510029 1247.17 1 6 CACCTG CCTACCCTCACCTACCCT + +4 taipale__ESRRG_full_AAGGTCANNNNAAGGTCA-EcR-ERR-usp 12 0.0510029 1247.17 1 6 CACCTG TGACCTTGAAATGACCTT - +4 predrem__nrMotif2650 1 0.0519981 1271.51 1 6 CACCTG CCATCTT + +4 hdpi__ESRRA-ERR 0 0.0519981 1271.51 1 6 CACCTG GACCTTG - +4 predrem__nrMotif1370 1 0.0519981 1271.51 1 6 CACCTG TGACCTG - +4 taipale_cyt_meth__CREB3L4_YGCCACGTGGCA_eDBD_meth-Atf6-Clk-CrebA-Max-Mnt 3 0.0522311 1277.21 1 6 CACCTG CGCCACGTGGCA + +4 neph__UW.Motif.0003-CTCF-SMC3-usp-vtd 2 0.0522311 1277.21 1 6 CACCTG GCCACCTGCTGG - +4 taipale_cyt_meth__TFAP2E_TGCCCNNNGGCN_FL_repr-TfAP-2 0 0.0522311 1277.21 1 6 CACCTG CGCCTGAGGGCA - +4 neph__UW.Motif.0543 -1 0.0522311 1277.21 1 5 CACCTG ATCTGTCTGTGG + +4 neph__UW.Motif.0196 7 0.0522311 1277.21 1 5 CACCTG CAAAAATTTCCT - +4 cisbp__M1458 3 0.0524306 1282.08 1 6 CACCTG ACTGACCTCG + +4 predrem__nrMotif1508 0 0.0524306 1282.08 1 6 CACCTG CACCTTCACC + +4 predrem__nrMotif1949 0 0.0524306 1282.08 1 6 CACCTG TTCCTGTACC + +4 predrem__nrMotif2232 0 0.0524306 1282.08 1 6 CACCTG CACCAGAAAA + +4 transfac_pro__M01034-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 1 0.0524306 1282.08 1 6 CACCTG CCACGTGACC + +4 cisbp__M0464 2 0.0524306 1282.08 1 6 CACCTG TACCCCTGAC - +4 predrem__nrMotif214 0 0.0524306 1282.08 1 6 CACCTG CACCTCCATC - +4 taipale_cyt_meth__NR4A1_NAAAGGTCAN_eDBD_meth-Hr38-Hr78 2 0.0524306 1282.08 1 6 CACCTG TTGACCTTTA - +4 taipale_cyt_meth__NR4A1_NAAAGGTCRN_eDBD_meth-Hr38-Hr78 2 0.0524306 1282.08 1 6 CACCTG GTGACCTTTA - +4 taipale_cyt_meth__TBX15_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.0524306 1282.08 1 6 CACCTG TTCACACCTT - +4 transfac_pro__M00943-Atf6-CrebA-Max-Myc-tgo-Usf 2 0.0524306 1282.08 1 6 CACCTG GCCACGTGGC - +4 taipale_cyt_meth__RXRB_NRGGTCRTGACCYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-svp-usp 8 0.0524383 1282.27 1 6 CACCTG GAGGTCGTGACCTC + +4 bergman__vnd-scro-tin-vnd 4 0.0524383 1282.27 1 6 CACCTG CAACCACTTAACAC - +4 cisbp__M4469-CTCF-HDAC1 5 0.0524383 1282.27 1 6 CACCTG TTCAGCACCATGGA - +4 hocomoco__TF65_HUMAN.H11MO.0.A-Dif-Rel-dl 8 0.0524383 1282.27 1 6 CACCTG CTGGAAATTCCCTG - +4 taipale_tf_pairs__GCM1_FOXO1_RTMAATAMGGGYRN_CAP-foxo-gcm-gcm2 1 0.0524383 1282.27 1 6 CACCTG CTACCCTTATTGAC - +4 transfac_pro__M04756-btd-CTCF-HDAC1-Sin3A-Spps 3 0.0524383 1282.27 1 6 CACCTG CAGCACCACGGACA - +4 tfdimers__MD00093-SREBP 10 0.0527973 1291.05 1 6 CACCTG CCCCCCCCCCCACCTGCCCTCTCCC + +4 cisbp__M5404-ERR-ftz-f1-Hr39 2 0.0528099 1291.36 1 6 CACCTG ATGACCTTGAA + +4 cisbp__M5687-Hr38 1 0.0528099 1291.36 1 6 CACCTG TGACCTTTAAA + +4 predrem__nrMotif1582 5 0.0528099 1291.36 1 6 CACCTG ACACACACCAG + +4 predrem__nrMotif175-CG7368-klu-l(3)neo38-sr 4 0.0528099 1291.36 1 6 CACCTG CCCCCACCCCC + +4 taipale_cyt_meth__ZBTB45_NCACCTATAKN_eDBD_meth-d4-tth 1 0.0528099 1291.36 1 6 CACCTG TCACCTATAGC + +4 transfac_pro__M06504 5 0.0528099 1291.36 1 6 CACCTG TTGAAAACCTC + +4 hocomoco__MYF5_MOUSE.H11MO.0.D-nau 1 0.0528099 1291.36 1 6 CACCTG GCAGCTGTTCC - +4 taipale__ESRRA_DBD_NTCAAGGTCAN-ERR-ftz-f1-Hr39 2 0.0528099 1291.36 1 6 CACCTG ATGACCTTGAA - +4 taipale__NR4A2_full_TTTAAAGGTCA_repr-Hr38 1 0.0528099 1291.36 1 6 CACCTG TGACCTTTAAA - +4 transfac_pro__M04624 6 0.0528099 1291.36 1 5 CACCTG TTTTTCCACCT + +4 swissregulon__hs__REST.p3-CTCF-HDAC1-Sin3A-Spps-btd 5 0.053341 1304.35 1 6 CACCTG TTCAGCACCATGGACAGCGCC + +4 cisbp__M4508-btd-CTCF-HDAC1-Sin3A-Spps 2 0.0535421 1309.26 1 6 CACCTG AGCACCATGGACAGC + +4 neph__UW.Motif.0358 1 0.0535421 1309.26 1 6 CACCTG TGAGCAAAGATGAGC - +4 transfac_pro__M01675 3 0.0535421 1309.26 1 6 CACCTG CATGACCTTTAAGGT - +4 transfac_pro__M09310 1 0.0535421 1309.26 1 6 CACCTG CTACCTAACTTTTTT - +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m5-CG9650-opa 2 0.0540033 1320.54 1 6 CACCTG GACTCCTGCTGAGATACTTA + +4 dbcorrdb__ESR1__ENCSR000BQD_1__m1-EcR-Eip78C-ERR 12 0.0540033 1320.54 1 6 CACCTG CAAGGTCACCGTGACCTGGA - +4 taipale__TBX4_DBD_AGGTGTNANWWNTNACACCT-bi-byn-Doc2-H15-mid-org-1 15 0.0540033 1320.54 1 5 CACCTG AGGTGTGAAATTTCACACCT - +4 predrem__nrMotif1987 3 0.0541926 1325.17 1 6 CACCTG GGTTTCCTG + +4 cisbp__M6354-nau 1 0.0541926 1325.17 1 6 CACCTG GCAGCTGTC - +4 predrem__nrMotif1070 -1 0.0541926 1325.17 1 5 CACCTG TCCTGAATC + +4 predrem__nrMotif2512 4 0.0541926 1325.17 1 5 CACCTG CATTTACCA - +4 predrem__nrMotif2665 -1 0.0541926 1325.17 1 5 CACCTG TCCTGTAAT - +4 neph__UW.Motif.0007-opa -2 0.0541926 1325.17 1 4 CACCTG CCTGCTGGG - +4 predrem__nrMotif2613 -2 0.0541926 1325.17 1 4 CACCTG CCTGCGGAG - +4 taipale_tf_pairs__ELK1_TBX21_RAGGTSRNNNNNNNNNNNNNNNNCGGAAGYN_CAP 25 0.0541969 1325.28 1 6 CACCTG CACTTCCGGTGTTAACGCCACTTCACACCTT - +4 cisbp__M1439-EcR-ftz-f1-Hr78-svp-usp 2 0.0542506 1326.59 1 6 CACCTG TTGACCTC + +4 cisbp__M4511-EcR-eg-Hr78-kni-knrl-svp-usp 1 0.0542506 1326.59 1 6 CACCTG TGACCTCT + +4 homer__TACGTGCV_HIF-1a-sima 0 0.0542506 1326.59 1 6 CACCTG TACGTGCC + +4 fantom__motif144_AAKCMSGT -1 0.0542506 1326.59 1 5 CACCTG ACCTGATT - +4 cisbp__M3996-EcR 6 0.054254 1326.67 1 6 CACCTG TGGCGTGACCTCACTC + +4 neph__UW.Motif.0418 6 0.054254 1326.67 1 6 CACCTG CAGCACCTCCTGTGCA + +4 neph__UW.Motif.0354 9 0.054254 1326.67 1 6 CACCTG TTGGCTTTTTTCCTCC - +4 taipale_cyt_meth__PPARD_NRRGGTCAAAGGTCAN_eDBD-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.054254 1326.67 1 6 CACCTG TTGACCTTTGACCCCT - +4 taipale_cyt_meth__RARB_NRGGTCANNRGGTCAN_FL_meth-EcR-eg-ftz-f1-Hnf4-Hr78-kni-knrl-svp-usp 10 0.054254 1326.67 1 6 CACCTG GTGACCTTTTGACCTT - +4 neph__UW.Motif.0198 4 0.0544244 1330.84 1 6 CACCTG GAAAATTCTTCTG - +4 neph__UW.Motif.0248 6 0.0544244 1330.84 1 6 CACCTG TGCCCAGTTCTCA - +4 neph__UW.Motif.0318 2 0.0544244 1330.84 1 6 CACCTG CAGTTCTGCTGTG - +4 taipale_tf_pairs__HOXB2_TBX21_TAATKRGGTGYKA_CAP-pb 3 0.0544244 1330.84 1 6 CACCTG TAACACCTCATTA - +4 transfac_pro__M00319 3 0.0544244 1330.84 1 6 CACCTG TGAAACCTGACCC - +4 hocomoco__COT2_HUMAN.H11MO.1.A-ERR-EcR-Hnf4-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 4 0.0546178 1335.57 1 6 CACCTG CCCTGACCTTTGACCCC - +4 hocomoco__PPARG_HUMAN.H11MO.0.A-EcR-Hnf4-Hr3-Hr78-eg-kni-knrl-svp-usp 1 0.0546178 1335.57 1 6 CACCTG TGACCTTTGCCCCACTT - +4 transfac_pro__M04613 1 0.0546178 1335.57 1 6 CACCTG GCAGCTGCTTTTTGGCT - +4 cisbp__M6071-EcR-eg-ERR-Hr3-Hr38-Hr78-kni-knrl-svp-usp 12 0.0546178 1335.57 1 5 CACCTG TGACCTTTAGTTGACCT + +4 taipale__Rarb_DBD_RGGTCANNNARRGGTCA-EcR-eg-ERR-Hr3-Hr38-kni-knrl-svp-usp 12 0.0546178 1335.57 1 5 CACCTG TGACCTTTAGTTGACCT - +4 predrem__nrMotif609 1 0.0552862 1351.91 1 6 CACCTG TTCCCTG + +4 cisbp__M0773 1 0.0552862 1351.91 1 6 CACCTG GGATCTG - +4 predrem__nrMotif1776 3 0.0552862 1351.91 1 4 CACCTG GAACACC + +4 predrem__nrMotif39 3 0.0552862 1351.91 1 4 CACCTG GGACACC + +4 predrem__nrMotif829 3 0.0552862 1351.91 1 4 CACCTG TGTCACC + +4 taipale_cyt_meth__CREB3_NGCCACGTGKMN_FL_repr-Atf6-Clk-CrebA-Max-Mnt 3 0.0557896 1364.22 1 6 CACCTG TGCCACGTGTCC + +4 cisbp__M4457-CTCF-lmd-SMC3-usp-vtd 3 0.0557896 1364.22 1 6 CACCTG CGCCCCCTGGTG - +4 transfac_pro__M06947-Mad 7 0.0557896 1364.22 1 5 CACCTG ATGTCTAGACCT + +4 transfac_pro__M06194 7 0.0557896 1364.22 1 5 CACCTG TCGGCTTTACCT - +4 transfac_pro__M06343 7 0.0557896 1364.22 1 5 CACCTG GCTGTCCAACCT - +4 transfac_pro__M06521 7 0.0557896 1364.22 1 5 CACCTG CCGGCTGCACCC - +4 cisbp__M1293 2 0.0558924 1366.74 1 6 CACCTG TTAACCAGAG + +4 cisbp__M1441-EcR-eg-ERR-Hr78-kni-knrl-svp-usp 3 0.0558924 1366.74 1 6 CACCTG CGTGACCCCT + +4 cisbp__M1442-EcR-Hr78-svp-usp 3 0.0558924 1366.74 1 6 CACCTG GGTGACCTCT + +4 cisbp__M6395-EcR-eg-ERR-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 2 0.0558924 1366.74 1 6 CACCTG CTGACCTTTG + +4 predrem__nrMotif1387 4 0.0558924 1366.74 1 6 CACCTG TTTCATCCTC + +4 cisbp__M0494 0 0.0558924 1366.74 1 6 CACCTG TTGCTGAAAC - +4 cisbp__M1029-bap-scro-vnd 3 0.0558924 1366.74 1 6 CACCTG AACCACTTAA - +4 cisbp__M1353-Myb 0 0.0558924 1366.74 1 6 CACCTG TAACGGCCAT - +4 hocomoco__ITF2_HUMAN.H11MO.0.C-sc 2 0.0558924 1366.74 1 6 CACCTG CCCAGCTGCC - +4 predrem__nrMotif1426 4 0.0558924 1366.74 1 6 CACCTG AGCCCACGTG - +4 swissregulon__hs__NKX2-2_8.p2-bap-scro-vnd 3 0.0558924 1366.74 1 6 CACCTG AAGCACTTAA - +4 taipale_cyt_meth__NR4A1_NAAAGGTCAN_eDBD_2-Hr38-Hr78 2 0.0558924 1366.74 1 6 CACCTG TTGACCTTTA - +4 predrem__nrMotif31 -1 0.0558924 1366.74 1 5 CACCTG TCCTGCACAG + +4 neph__UW.Motif.0351 2 0.0560939 1371.66 1 6 CACCTG CAGCCCAGCCAGCA + +4 transfac_public__M00476-FoxL1-foxo-FoxP 8 0.0560939 1371.66 1 6 CACCTG ATGTTGTTTACGTT + +4 cisbp__M3283-FoxL1-foxo-FoxP 8 0.0560939 1371.66 1 6 CACCTG ATGTTGTTTACGTT - +4 taipale__NR2F6_DBD_RRGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 8 0.0560939 1371.66 1 6 CACCTG TGACCTTTGACCTC - +4 transfac_pro__M02006-srp 0 0.0561287 1372.51 1 6 CACCTG TATCTG + +4 fantom__motif97_TTCCCT 1 0.0561287 1372.51 1 5 CACCTG TTCCCT + +4 hdpi__MSRB3-SelR 1 0.0561287 1372.51 1 5 CACCTG TGACAT - +4 hocomoco__REST_MOUSE.H11MO.0.A-CTCF-HDAC1-Sin3A-Spps-btd 5 0.0563343 1377.54 1 6 CACCTG TTCAGCACCATGGACAGCGCCC + +4 transfac_pro__M08805 5 0.0563471 1377.86 1 6 CACCTG ACTTTGACCTT + +4 cisbp__M6101-TfAP-2 0 0.0563471 1377.86 1 6 CACCTG AGCCTGAGGCG - +4 taipale__Tcfap2a_DBD_NSCCNNNGGSN_repr-TfAP-2 0 0.0563471 1377.86 1 6 CACCTG TGCCTGAGGCG - +4 taipale_cyt_meth__ESRRB_NYCAAGGTCAN_eDBD-ERR-ftz-f1-Hr39 2 0.0563471 1377.86 1 6 CACCTG ATGACCTTGAC - +4 yetfasco__YGR044C_273 1 0.0563471 1377.86 1 6 CACCTG GTACCTCAAAA - +4 cisbp__M5676-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0572946 1401.02 1 6 CACCTG TTGACCTTTGACCTC + +4 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNCCCGCAY_CAP_repr-gcm-gcm2 6 0.0572946 1401.02 1 6 CACCTG CACCTGGACCCGCAT + +4 cisbp__M2245 3 0.0572946 1401.02 1 6 CACCTG CATGACCTTTAAGGT - +4 cisbp__M4574-btd-CTCF-HDAC1-Sin3A-Spps 4 0.0572946 1401.02 1 6 CACCTG TCAGCACCATGGACA - +4 taipale__NR2F1_DBD_NRGGTCANNGGTCAN-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0572946 1401.02 1 6 CACCTG TTGACCTTTGACCTC - +4 transfac_pro__M02939-opa 1 0.0572946 1401.02 1 6 CACCTG TCTCCTGCTGTGTGG - +4 transfac_pro__M09003-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0572946 1401.02 1 6 CACCTG TTGACCTTTGACCTC - +4 scertf__spivak.RPH1-Kdm4A-Kdm4B 2 0.0576931 1410.77 1 6 CACCTG CACCCCTGA + +4 cisbp__M0153-E2f1-Max-Myc 1 0.0576931 1410.77 1 6 CACCTG GCACGTGGC - +4 taipale_cyt_meth__NR2C1_NRAGGTCAN_eDBD_meth_repr-EcR-eg-Eip78C-Hnf4-Hr3-Hr38-Hr78-kni-knrl-svp-usp 2 0.0576931 1410.77 1 6 CACCTG TTGACCTTT - +4 transfac_pro__M06847-salm-salr 0 0.0576931 1410.77 1 6 CACCTG AAACTGTTA - +4 predrem__nrMotif140 -1 0.0576931 1410.77 1 5 CACCTG TCCTGCTGC + +4 predrem__nrMotif2418 -2 0.0576931 1410.77 1 4 CACCTG CCTGATAAA + +4 cisbp__M1470-EcR-eg-Eip78C-ERR-ftz-f1-Hr78-kni-knrl-svp-usp 2 0.0576993 1410.92 1 6 CACCTG ATGACCTT + +4 predrem__nrMotif2326 -1 0.0576993 1410.92 1 5 CACCTG ACCGAGGC + +4 predrem__nrMotif1222 -2 0.0576993 1410.92 1 4 CACCTG CCTAGCAT - +4 cisbp__M5786-EcR-eg-ERR-Hr3-Hr78-kni-knrl-svp-usp 1 0.0578997 1415.82 1 6 CACCTG TGACCTCAATTTGACCTTTG + +4 dbcorrdb__ESRRA__ENCSR000DYQ_1__m1-ERR-ftz-f1-srl 5 0.0578997 1415.82 1 6 CACCTG ACCGTGACCTTGAGCCCGCG - +4 hocomoco__TBX1_HUMAN.H11MO.0.D-org-1 7 0.0578997 1415.82 1 6 CACCTG CCGCCCACCCCTGCCCACCC - +4 taipale__RORA_DBD_NRAAGGTCAANNNNRGGTCA-EcR-eg-ERR-Hr3-Hr78-kni-knrl-svp-usp 1 0.0578997 1415.82 1 6 CACCTG TGACCTCAATTTGACCTTTG - +4 taipale_tf_pairs__GCM1_CEBPB_ATRSGGGNNNNTTRCGYAAN_CAP_repr-gcm-gcm2 11 0.0578997 1415.82 1 6 CACCTG ATTGCGCAATATACCCGCAT - +4 cisbp__M5897-bi-byn-Doc2-H15-mid-org-1 15 0.0578997 1415.82 1 5 CACCTG AGGTGTGAAATTTCACACCT + +4 neph__UW.Motif.0327 7 0.0580774 1420.17 1 6 CACCTG CCCGGGCCGCCCGCAG + +4 neph__UW.Motif.0226 7 0.0580774 1420.17 1 6 CACCTG GAGTCAGTTTCTGCTG - +4 neph__UW.Motif.0563 2 0.0580774 1420.17 1 6 CACCTG GACACATTCATTTGGT - +4 neph__UW.Motif.0572 8 0.0580774 1420.17 1 6 CACCTG AGTTCCTCTTCCTCTT - +4 taipale_tf_pairs__HOXB13_TBX21_ARGTGNNNNNNATAAA_CAP_repr 11 0.0580774 1420.17 1 5 CACCTG TTTATTGTTCACACCT - +4 cisbp__M5408-EcR-ERR-ftz-f1 11 0.0584888 1430.23 1 6 CACCTG TGACCTTGAATGACCTT + +4 cisbp__M5758-EcR-eg-ERR-ftz-f1-kni-knrl-svp-usp 11 0.058571 1432.24 1 6 CACCTG TGACCTCAAATGACCTTT + +4 cisbp__M6070-EcR-eg-Hr78-kni-knrl-svp-usp 11 0.058571 1432.24 1 6 CACCTG TGACCTCTGGTGACCTTT + +4 taipale__RARA_DBD_ARRGGTCANNNRRGGTCA_repr-EcR-eg-ERR-ftz-f1-kni-knrl-svp-usp 11 0.058571 1432.24 1 6 CACCTG TGACCTCAAATGACCTTT - +4 predrem__nrMotif2190 1 0.0587526 1436.68 1 6 CACCTG ATACTTT + +4 hdpi__ZNF695 1 0.0587526 1436.68 1 6 CACCTG TAACCCT - +4 predrem__nrMotif1468 1 0.0587526 1436.68 1 6 CACCTG GCACCTC - +4 transfac_pro__M00308-CG10348-CG13296-ham 1 0.0587526 1436.68 1 6 CACCTG TCCCCTG - +4 transfac_public__M00240-tin-vnd 0 0.0587526 1436.68 1 6 CACCTG CACTTGA - +4 hdpi__HSPA5-Hsc70-3 3 0.0587526 1436.68 1 4 CACCTG CGTCACC - +4 cisbp__M1286 2 0.0595391 1455.91 1 6 CACCTG TTAACCAGAG + +4 yetfasco__YDR043C_2148 2 0.0595391 1455.91 1 6 CACCTG GGACCCTGAT + +4 predrem__nrMotif276 -1 0.0595391 1455.91 1 5 CACCTG ACCTTTGTTT + +4 cisbp__M5721-achi-hth-nau-vis 3 0.0595414 1455.97 1 6 CACCTG TGACACCTGTCA + +4 homer__TGACCTTTNCNT_Nur77-Hr38 1 0.0595414 1455.97 1 6 CACCTG TGACCTTTACCT + +4 neph__UW.Motif.0284 6 0.0595414 1455.97 1 6 CACCTG AAAAGAAACTTG + +4 taipale_tf_pairs__CUX1_TBX21_TMACACCYAATA_CAP_repr-ct 3 0.0595414 1455.97 1 6 CACCTG TCACACCCAATA + +4 tiffin__TIFDMEM0000060 4 0.0595414 1455.97 1 6 CACCTG TAATCAACTTAT + +4 hocomoco__ERR1_MOUSE.H11MO.0.A-ERR-EcR-Hr4-ftz-f1-srl-usp 1 0.0595414 1455.97 1 6 CACCTG TGACCTTGACCT - +4 swissregulon__hs__RXRG_dimer.p3-EcR-HDAC1-Hnf4-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0595414 1455.97 1 6 CACCTG TGACCTTTGACC - +4 taipale__PKNOX1_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.0595414 1455.97 1 6 CACCTG TGACACCTGTCA - +4 transfac_pro__M07904-YL-1 1 0.0595414 1455.97 1 6 CACCTG ACACCGAACACA - +4 transfac_pro__M05792 7 0.0595414 1455.97 1 5 CACCTG TATCCCACACCA - +4 hdpi__PAXIP1-Ptip 0 0.0595665 1456.58 1 6 CACCTG CAGCTT - +4 cisbp__M5681-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 8 0.0599575 1466.14 1 6 CACCTG TGACCTTTGACCTC + +4 neph__UW.Motif.0116 3 0.0599575 1466.14 1 6 CACCTG CCCCGCCCCCAGGG + +4 taipale_cyt_meth__RARG_NRGGTCRTGACCYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-usp 8 0.0599575 1466.14 1 6 CACCTG AAGGTCGTGACCTT + +4 transfac_pro__M09306 2 0.0599575 1466.14 1 6 CACCTG TTTACCTAACTTTT + +4 cisbp__M6384-EcR-svp-usp 9 0.0599575 1466.14 1 5 CACCTG AGGGTCAATGACCT - +4 taipale_cyt_meth__TFAP2C_NGCCYNRGGCN_eDBD_meth-TfAP-2 0 0.060074 1468.99 1 6 CACCTG TGCCTGAGGCA + +4 cisbp__M5912-TfAP-2 0 0.060074 1468.99 1 6 CACCTG TGCCTGAGGCG - +4 hocomoco__ATF3_HUMAN.H11MO.0.A-Mitf-SREBP-Usf-cnc-cwo-tgo 2 0.060074 1468.99 1 6 CACCTG ATCACGTCACC - +4 predrem__nrMotif496 1 0.060074 1468.99 1 6 CACCTG TTTCCTTTCTA - +4 taipale__TFAP2A_DBD_NSCCNNNGGSN-TfAP-2 0 0.060074 1468.99 1 6 CACCTG TGCCTGAGGCG - +4 taipale_cyt_meth__ESRRA_NYCAAGGTCAN_FL-ERR-ftz-f1-Hr39 2 0.060074 1468.99 1 6 CACCTG ATGACCTTGAC - +4 cisbp__M1628-byn-Doc2-org-1 6 0.060074 1468.99 1 5 CACCTG TTTTCACACCT - +4 transfac_pro__M00653 -1 0.0605277 1480.08 1 5 CACCTG ACGTG - +4 cisbp__M4576-EcR-eg-ERR-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 4 0.0612645 1498.1 1 6 CACCTG CCCTGACCTTTGCCC + +4 neph__UW.Motif.0096 8 0.0612645 1498.1 1 6 CACCTG AAAACTGGCATCTGG + +4 hocomoco__ERR1_HUMAN.H11MO.0.A-ERR-Hr4-ftz-f1 6 0.0612645 1498.1 1 6 CACCTG CTGTGTGACCTTGAG - +4 jaspar__MA0440.1 3 0.0612645 1498.1 1 6 CACCTG CATGACCTTTAAGGT - +4 cisbp__M4274-Clk 1 0.0613293 1499.69 1 6 CACCTG GCACGTGT + +4 idmmpmm__vnd-scro-vnd 1 0.0613293 1499.69 1 6 CACCTG GCACTTGA + +4 predrem__nrMotif997 1 0.0613293 1499.69 1 6 CACCTG GCACATGC - +4 transfac_pro__M06855 9 0.0613293 1499.69 1 6 CACCTG GAGGCGTTAAACCTTACTTCG - +4 predrem__nrMotif2059 0 0.0613781 1500.88 1 6 CACCTG AACATGGGA + +4 predrem__nrMotif418 3 0.0613781 1500.88 1 6 CACCTG ACAGACCCC + +4 predrem__nrMotif516 3 0.0613781 1500.88 1 6 CACCTG GGCCCCCTG + +4 cisbp__M0584 2 0.0613781 1500.88 1 6 CACCTG TCTATCCTA - +4 cisbp__M1388 3 0.0613781 1500.88 1 6 CACCTG CCTTATCCG - +4 flyfactorsurvey__usp_SANGER_5_FBgn0003964-EcR-Hr78-svp-usp 2 0.0613781 1500.88 1 6 CACCTG TTGACCTCT - +4 predrem__nrMotif987 3 0.0613781 1500.88 1 6 CACCTG ACAACCCTG - +4 predrem__nrMotif1087 -1 0.0613781 1500.88 1 5 CACCTG ACCTTGGCC + +4 predrem__nrMotif2082 -1 0.0613781 1500.88 1 5 CACCTG CCCTGAGGG + +4 predrem__nrMotif1592 4 0.0613781 1500.88 1 5 CACCTG TCTCAACCT - +4 predrem__nrMotif2268 4 0.0613781 1500.88 1 5 CACCTG AATGCACCA - +4 predrem__nrMotif394 -1 0.0613781 1500.88 1 5 CACCTG TCCTGCAGA - +4 dbcorrdb__ESR1__ENCSR000BJS_1__m1-EcR-eg-ERR-kni-knrl 10 0.062038 1517.01 1 6 CACCTG AGGTCACGGTGACCTGGAAT - +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m3-brm 3 0.062038 1517.01 1 6 CACCTG TCTTTCCTGCAGATTATCAA - +4 hocomoco__RARG_HUMAN.H11MO.2.D-EcR-usp 2 0.062038 1517.01 1 6 CACCTG GTGACCTTTGGGTGACCCCC - +4 taipale_tf_pairs__GCM1_FOXI1_RTAAATANGGGNN_CAP_repr-gcm-gcm2 0 0.0620827 1518.11 1 6 CACCTG TACCCGTATTTAC - +4 neph__UW.Motif.0224 8 0.0620827 1518.11 1 5 CACCTG TTTTCTGCCAGCT - +4 transfac_pro__M01782-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 8 0.0620827 1518.11 1 5 CACCTG TGACCTTTGACCT - +4 taipale_cyt_meth__THRB_NRRGGTCRTGACCYYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-usp 9 0.062126 1519.17 1 6 CACCTG AGAGGTCGTGACCTTT + +4 transfac_pro__M02888-bowl-drm-odd-sob 6 0.062126 1519.17 1 6 CACCTG ACATGCTACCTAATAC + +4 neph__UW.Motif.0254 6 0.062126 1519.17 1 6 CACCTG TGACTCATTCTTCCTG - +4 transfac_pro__M02787-EcR-eg-Hr78-kni-knrl-svp 5 0.062126 1519.17 1 6 CACCTG CAGGTGACCTTTGAGA - +4 elemento__TGACCTC 1 0.0624045 1525.98 1 6 CACCTG TGACCTC + +4 predrem__nrMotif1664 1 0.0624045 1525.98 1 6 CACCTG ACTCCTG + +4 transfac_pro__M01835 1 0.0624045 1525.98 1 6 CACCTG CCTCCTT + +4 predrem__nrMotif2081 0 0.0624045 1525.98 1 6 CACCTG CATCTTG - +4 transfac_pro__M03804-HLH3B 1 0.0624045 1525.98 1 6 CACCTG CCATCTG - +4 fantom__motif44_TGAAGST -1 0.0624045 1525.98 1 5 CACCTG ACCTTCA - +4 predrem__nrMotif2053 -2 0.0624045 1525.98 1 4 CACCTG CCTCAAG + +4 predrem__nrMotif956 -2 0.0624045 1525.98 1 4 CACCTG CCTGAAA + +4 predrem__nrMotif2463 -2 0.0624045 1525.98 1 4 CACCTG CCTGAGT - +4 taipale_cyt_meth__ZNF580_MCTACCCYNNNMCTACCCY_FL_repr 2 0.0625078 1528.5 1 6 CACCTG CCTACCCTCCACCTACCCT + +4 taipale__ESRRA_DBD_SAAGGTCANNTSAAGGTCA_repr-EcR-ERR-ftz-f1-Hr3 12 0.0625078 1528.5 1 6 CACCTG TGACCTTGAAATGACCTTG - +4 transfac_pro__M05928 4 0.0625078 1528.5 1 6 CACCTG CAGAAACCTACCCACCTAC - +4 cisbp__M5405-EcR-ERR-ftz-f1 11 0.0625911 1530.54 1 6 CACCTG TGACCTTGAATGACCTT + +4 cisbp__M5763-EcR-Hr3-Hr78-usp 1 0.0625911 1530.54 1 6 CACCTG TGACCTTTAGTTGACCT + +4 hocomoco__PPARA_HUMAN.H11MO.0.B-EcR-Hnf4-Hr3-Hr38-Hr51-Hr78-eg-kni-knrl-svp-usp 1 0.0625911 1530.54 1 6 CACCTG TGACCTTTGCCCCAGTT - +4 taipale__ESRRA_DBD_RAGGTCANTCAAGGTCA_repr-EcR-ERR-ftz-f1 11 0.0625911 1530.54 1 6 CACCTG TGACCTTGAATGACCTT - +4 taipale__RARA_full_RGGTCANNNARRGGTCA-EcR-Hr3-Hr78-usp 1 0.0625911 1530.54 1 6 CACCTG TGACCTTTAGTTGACCT - +4 transfac_pro__M08962-EcR-eg-Hnf4-Hr3-kni-knrl-svp 2 0.0625911 1530.54 1 6 CACCTG GTGACCTTTTGACCTTT - +4 taipale__Rara_DBD_RGGTCANNNARRGGTCA-EcR-ERR-svp-usp 12 0.0625911 1530.54 1 5 CACCTG TGACCTTTGAGTGACCT - +4 cisbp__M6073-EcR-eg-ERR-Hr3-kni-knrl-svp-usp 12 0.0627047 1533.32 1 6 CACCTG TGACCTTTAGATGACCTT + +4 taipale__Rara_DBD_ARRGGTCANNNRRGGTCA-EcR-eg-ERR-Hr78-kni-knrl-svp 11 0.0627047 1533.32 1 6 CACCTG TGACCTCTCTTGACCTTT - +4 taipale__Rarb_DBD_ARRGGTCANNNRRGGTCA-EcR-eg-Hr78-kni-knrl-svp-usp 11 0.0627047 1533.32 1 6 CACCTG TGACCTCTGGTGACCTTT - +4 taipale__Rarg_DBD_RRGGTCANNNARAGGTCA-EcR-eg-ERR-Hr3-kni-knrl-svp-usp 12 0.0627047 1533.32 1 6 CACCTG TGACCTTTAGATGACCTT - +4 taipale_tf_pairs__TEAD4_ESRRB_RCATWCNNNNNNAGGTCA_CAP_repr-ERR-sd 1 0.0627047 1533.32 1 6 CACCTG TGACCTTGAGAGGAATGC - +4 taipale_tf_pairs__MGA_EVX1_AGGTGNTAATKWNNNNTN_CAP_repr-eve 13 0.0627047 1533.32 1 5 CACCTG TAATGTTCATTATCACCT - +4 hdpi__NR2F1-Hr78-svp-usp 1 0.0631536 1544.29 1 5 CACCTG TGACCT - +4 cisbp__M0164-bigmax-mio 2 0.0633786 1549.8 1 6 CACCTG AGCACGTGCT + +4 predrem__nrMotif2336 0 0.0633786 1549.8 1 6 CACCTG TTCCTGATCT + +4 taipale_cyt_meth__NR4A2_NAAAGGTCRN_eDBD_meth-Hr38 2 0.0633786 1549.8 1 6 CACCTG ATGACCTTTC - +4 transfac_pro__M00372 2 0.0633786 1549.8 1 6 CACCTG TCCACGTGGA - +4 predrem__nrMotif989 5 0.0633786 1549.8 1 5 CACCTG AAATTCACCA + +4 transfac_pro__M07536 -1 0.0633786 1549.8 1 5 CACCTG ACCTCGTACT + +4 cisbp__M0501 5 0.0633786 1549.8 1 5 CACCTG TTCGCCACCG - +4 taipale__ZBTB7A_DBD_NGCGACCACCNN_repr 6 0.063494 1552.62 1 6 CACCTG GGCGACCACCGA + +4 cisbp__M5960 6 0.063494 1552.62 1 6 CACCTG GGCGACCACCGA - +4 hocomoco__TBX21_MOUSE.H11MO.0.A 5 0.063494 1552.62 1 6 CACCTG TCTCACACCTCC - +4 transfac_pro__M06056 2 0.063494 1552.62 1 6 CACCTG GCAACCTCAACT - +4 transfac_pro__M06641 6 0.063494 1552.62 1 6 CACCTG TCGGATTACCAG - +4 stark__RWWNTNRCACYT-byn 7 0.063494 1552.62 1 5 CACCTG AAAATAACACCT + +4 transfac_pro__M05582 7 0.063494 1552.62 1 5 CACCTG TCGGTACCACCG - +4 taipale_cyt_meth__TFAP2E_NGCCNNNGGCN_FL_repr-TfAP-2 0 0.0639988 1564.96 1 6 CACCTG CGCCTCAGGCG + +4 transfac_pro__M03839-sv 2 0.0639988 1564.96 1 6 CACCTG CACGCCTGAGT + +4 transfac_pro__M08906-EcR-Hr78 5 0.0639988 1564.96 1 6 CACCTG ACCCTGACCTC + +4 transfac_pro__M07402-ERR-ftz-f1 3 0.0639988 1564.96 1 6 CACCTG TGTGACCTTGG - +4 transfac_pro__M08809-ERR-ftz-f1 2 0.0639988 1564.96 1 6 CACCTG CTGACCTTGAA - +4 cisbp__M4564-ERR-srl 3 0.0640353 1565.86 1 6 CACCTG TGTGACCTTGGGCC + +4 cisbp__M6382-Eip75B-Hr3 3 0.0640353 1565.86 1 6 CACCTG TTTGACCTACTTTT + +4 neph__UW.Motif.0117 5 0.0640353 1565.86 1 6 CACCTG AGCCCTTCCTCTGG + +4 cisbp__M0236 6 0.0640353 1565.86 1 6 CACCTG ACATCGTACGTGAT - +4 neph__UW.Motif.0186 4 0.0640353 1565.86 1 6 CACCTG TGCCTTCCTCTGCT - +4 swissregulon__hs__NR1H4.p2-EcR-usp 7 0.0640353 1565.86 1 6 CACCTG GGTCACTGACCCTG - +4 transfac_pro__M07040 7 0.0640353 1565.86 1 6 CACCTG CCGCCCCCCCCTTG - +4 cisbp__M0205 1 0.0651494 1593.1 1 6 CACCTG GCACGTGA - +4 cisbp__M6222-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Rpn5 2 0.0651494 1593.1 1 6 CACCTG ACTTCCTG - +4 jaspar__MA0310.1-Clk 0 0.0651494 1593.1 1 6 CACCTG CACGTGTC - +4 transfac_pro__M01610-Clk 0 0.0651494 1593.1 1 6 CACCTG CACGTGTC - +4 transfac_pro__M03892-EcR-usp 2 0.0651494 1593.1 1 6 CACCTG ATGACCTC - +4 yetfasco__YBR066C_1383 2 0.0651494 1593.1 1 6 CACCTG GGACCCTT - +4 predrem__nrMotif1873 -1 0.0651494 1593.1 1 5 CACCTG ACCTCTGT + +4 flyfactorsurvey__CG8319_SANGER_2.5_FBgn0037722-CG8319 4 0.0651494 1593.1 1 4 CACCTG GGGTCACC + +4 cisbp__M5264-EcR-eg-Hr78-kni-knrl-svp-usp 2 0.0652549 1595.68 1 6 CACCTG TTGACCTCT + +4 cisbp__M6393-Hr38 2 0.0652549 1595.68 1 6 CACCTG GTGACCTTT + +4 hocomoco__ASCL2_HUMAN.H11MO.0.D-Fer1-ac-ase-l(1)sc-nau-sc 1 0.0652549 1595.68 1 6 CACCTG CCAGCTGCT + +4 predrem__nrMotif1593 2 0.0652549 1595.68 1 6 CACCTG CAGACCTCC + +4 predrem__nrMotif2086 0 0.0652549 1595.68 1 6 CACCTG TACCAGATT + +4 predrem__nrMotif2117 0 0.0652549 1595.68 1 6 CACCTG AAGCTGTTG + +4 transfac_pro__M07267-ERR-ftz-f1-Hr4 1 0.0652549 1595.68 1 6 CACCTG TGACCTTGA + +4 transfac_pro__M09557 1 0.0652549 1595.68 1 6 CACCTG TCACGTGGC + +4 cisbp__M0505 2 0.0652549 1595.68 1 6 CACCTG GGACCCTGA - +4 taipale_cyt_meth__GCM2_RTGCGGGTN_FL-gcm-gcm2 0 0.0652549 1595.68 1 6 CACCTG CACCCGCAT - +4 predrem__nrMotif366 -1 0.0652549 1595.68 1 5 CACCTG TCCTGTTTT + +4 transfac_pro__M05031 4 0.0652549 1595.68 1 5 CACCTG TCTTAACCT + +4 predrem__nrMotif409 4 0.0652549 1595.68 1 5 CACCTG CAGTGACCT - +4 predrem__nrMotif2049 -2 0.0652549 1595.68 1 4 CACCTG CCTTAACCC + +4 cisbp__M6164-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 9 0.0652573 1595.74 1 6 CACCTG ACATAGTGACACCTAGGTGTGAAAT + +4 neph__UW.Motif.0614 1 0.0654582 1600.65 1 6 CACCTG AAAACTTCCCAGGAG + +4 transfac_pro__M08954-EcR-svp-usp 9 0.0654582 1600.65 1 6 CACCTG GAGGTCATTGACCTT + +4 transfac_pro__M02021-usp 8 0.0654582 1600.65 1 6 CACCTG CCACCAGTGACCTCA - +4 neph__UW.Motif.0506 10 0.0654582 1600.65 1 5 CACCTG TTAAAAAATCCACAT - +4 transfac_pro__M01522 10 0.0656986 1606.53 1 6 CACCTG TTACATATTGCACCCGATTGG + +4 cisbp__M0199 1 0.0662251 1619.4 1 6 CACCTG GCACGTGTCGTTA - +4 cisbp__M0256 2 0.0662251 1619.4 1 6 CACCTG AACACGTGTCATG - +4 hocomoco__BCL6_MOUSE.H11MO.0.A 0 0.0662251 1619.4 1 6 CACCTG TTCCTGGAAAGCA - +4 jaspar__MA0616.1 1 0.0662251 1619.4 1 6 CACCTG GCACGTGTCGTTA - +4 transfac_pro__M01895 -1 0.0662251 1619.4 1 5 CACCTG ACCTTTAGGGTTT - +4 flyfactorsurvey__lola-PA_SANGER_5_FBgn0005630-lola 2 0.0662461 1619.92 1 5 CACCTG GAAACCC - +4 tfdimers__MD00361-fkh-GATAe-grn-pnr-srp 7 0.0663662 1622.85 1 6 CACCTG ATTTTTTTATCTGTTTGTTTATTTATT - +4 taipale_cyt_meth__PPARD_NRRGGTCRTGACCYYN_eDBD-EcR-eg-ftz-f1-Hr78-kni-knrl-usp 9 0.0664068 1623.85 1 6 CACCTG AGAGGTCATGACCTTT + +4 neph__UW.Motif.0589 7 0.0664068 1623.85 1 6 CACCTG GAAAAAATTCCTTTTT - +4 taipale_cyt_meth__RARG_NRGGTCAAAAGGTCAN_eDBD-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 10 0.0664068 1623.85 1 6 CACCTG TTGACCTTTTGACCTT - +4 taipale_tf_pairs__TEAD4_EOMES_GGWATGNRAGGTGNNR_CAP_repr-sd 3 0.0664068 1623.85 1 6 CACCTG TCACACCTCGCATTCC - +4 neph__UW.Motif.0650 11 0.0664068 1623.85 1 5 CACCTG CCTCCCCCTGCCAGCT - +4 dbcorrdb__SREBF1__ENCSR000DYU_1__m1-Chd1-CTCF-SREBP 8 0.066428 1624.36 1 6 CACCTG CCGGGCAGCACCACGGGCGG + +4 dbcorrdb__ESR1__ENCSR000BKN_1__m1-EcR-eg-Eip78C-ERR-kni-knrl 10 0.066428 1624.36 1 6 CACCTG AGGTCACGGTGACCTAGAAT - +4 hocomoco__ZN768_HUMAN.H11MO.0.C-CG12299-CG31365-dati 4 0.066428 1624.36 1 6 CACCTG ACTTAACCTCTCTGAGCCTC - +4 transfac_pro__M01248 7 0.066428 1624.36 1 6 CACCTG GGAAGGTGACCTTGCACTTC - +4 cisbp__M5406-EcR-ERR-ftz-f1-Hr3 12 0.0669016 1635.95 1 6 CACCTG TGACCTTGAAATGACCTTG + +4 taipale_cyt_meth__THRB_NYGACCTNNNNYGACCTYN_FL_meth-EcR 2 0.0669016 1635.95 1 6 CACCTG GTGACCTCACGTGACCTCA + +4 hocomoco__NR1H3_HUMAN.H11MO.0.B-EcR-svp-usp 1 0.0669016 1635.95 1 6 CACCTG TGACCTGCAGTGACCTCTG - +4 transfac_pro__M09171 6 0.0669016 1635.95 1 6 CACCTG AGGTTTTATCTGGGGAAGG - +4 cisbp__M5412-EcR-ERR-ftz-f1 11 0.0669326 1636.7 1 6 CACCTG TGACCTTGACTGACCTT + +4 jaspar__MA0115.1-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-svp-usp 10 0.0669326 1636.7 1 6 CACCTG GTTGACCTTTGACCTTT - +4 taipale__ESRRG_full_RAGGTCANTCAAGGTCA-EcR-ERR-ftz-f1 11 0.0669326 1636.7 1 6 CACCTG TGACCTTGACTGACCTT - +4 taipale__RARG_DBD_RRGGTCANNNRRGGTCA-EcR-eg-ERR-Hr78-kni-knrl-svp-usp 11 0.0669326 1636.7 1 6 CACCTG TGACCTCTGGTGACCTT - +4 transfac_pro__M02748-ERR-ftz-f1-Hr39 6 0.0669326 1636.7 1 6 CACCTG TCGCATGACCTTGAATA - +4 cisbp__M6067-EcR-ERR-svp-usp 12 0.0669326 1636.7 1 5 CACCTG TGACCTTTGAGTGACCT + +4 taipale_cyt_meth__NR5A2_NCAAGGTCRNGACCTTGN_eDBD_repr-EcR-eg-ERR-ftz-f1-Hr39-Hr78-kni-knrl-usp 10 0.0670831 1640.38 1 6 CACCTG TCAAGGTCATGACCTTGA + +4 transfac_pro__M07974-CG14860 11 0.0670831 1640.38 1 6 CACCTG TTACGTGTAATTACGTGT + +4 transfac_pro__M07956-eg-Eip75B-Hr3-kni-knrl 9 0.0670831 1640.38 1 6 CACCTG TGACCTACTGACCTACAT - +4 transfac_pro__M09281 8 0.0670831 1640.38 1 6 CACCTG AATTAGTTCACCTACCTT - +4 cisbp__M0083-TfAP-2 1 0.0674185 1648.58 1 6 CACCTG TCGCCTCAGG + +4 cisbp__M0264-Atf6-CrebA-Xbp1 1 0.0674185 1648.58 1 6 CACCTG TGACGTGGCA + +4 cisbp__M0279 2 0.0674185 1648.58 1 6 CACCTG TACACGTGTA + +4 flyfactorsurvey__Fer3_da_SANGER_5_FBgn0000413-Fer3-da 0 0.0674185 1648.58 1 6 CACCTG CAGCTGTTAC + +4 predrem__nrMotif1012 4 0.0674185 1648.58 1 6 CACCTG GGCACAGCTG + +4 predrem__nrMotif2210 4 0.0674185 1648.58 1 6 CACCTG AAAGCACCAG + +4 transfac_pro__M07253-ERR 2 0.0674185 1648.58 1 6 CACCTG CTGACCTTGA + +4 cisbp__M0258-Clk-CrebA 2 0.0674185 1648.58 1 6 CACCTG GACACGTGGC - +4 cisbp__M0468 3 0.0674185 1648.58 1 6 CACCTG TGGGCCCTTC - +4 cisbp__M0774 1 0.0674185 1648.58 1 6 CACCTG AGATCTGTAA - +4 predrem__nrMotif1655 0 0.0674185 1648.58 1 6 CACCTG AAACTGAAAT - +4 predrem__nrMotif2407 4 0.0674185 1648.58 1 6 CACCTG CACTTCCCTG - +4 predrem__nrMotif686 4 0.0674185 1648.58 1 6 CACCTG GGGAGAGCTG - +4 transfac_pro__M05454 5 0.0674185 1648.58 1 5 CACCTG GTTGACACCA - +4 homer__KCCGGGTAAYRR_REB1 4 0.0676559 1654.39 1 6 CACCTG TTGTTACCCGGC - +4 taipale__TGIF2LX_full_TGACAGSTGTCA-achi-hth-nau-vis 3 0.0676559 1654.39 1 6 CACCTG TGACAGCTGTCA - +4 bergman__byn-byn 7 0.0676559 1654.39 1 5 CACCTG AAAATAACACCT + +4 transfac_pro__M06151-crol -1 0.0676559 1654.39 1 5 CACCTG CCCTACGGCAGA + +4 transfac_pro__M06211 7 0.0676559 1654.39 1 5 CACCTG TCTGCTTTACCA - +4 transfac_pro__M06212 7 0.0676559 1654.39 1 5 CACCTG TCTGCTTTACCA - +4 transfac_pro__M06649 7 0.0676559 1654.39 1 5 CACCTG AATAATTAACCA - +4 transfac_pro__M06751 7 0.0676559 1654.39 1 5 CACCTG TATCATTTACCG - +4 swissregulon__sacCer__RGM1 0 0.0680323 1663.59 1 5 CACCTG CCCCT - +4 yetfasco__YMR182C_531 0 0.0680323 1663.59 1 5 CACCTG CCCCT - +4 cisbp__M0257-Myc 3 0.0681298 1665.98 1 6 CACCTG GGACACGTGGG + +4 cisbp__M2384-ERR 3 0.0681298 1665.98 1 6 CACCTG TGTGACCTTGG + +4 flyfactorsurvey__lola-PK_SOLEXA_FBgn0005630-lola 2 0.0681298 1665.98 1 6 CACCTG GGCCCCTACAT - +4 taipale_cyt_meth__TFAP2B_NGCCNNNGGCN_eDBD-TfAP-2 0 0.0681298 1665.98 1 6 CACCTG TGCCTCAGGCA - +4 transfac_pro__M07466-Six4-so 3 0.0681298 1665.98 1 6 CACCTG TGAAACCTGAG - +4 cisbp__M6081-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 1 0.0683339 1670.97 1 6 CACCTG TGACCTTTGACCCC + +4 neph__UW.Motif.0277 7 0.0683339 1670.97 1 6 CACCTG AGGAAATTATCTGA + +4 neph__UW.Motif.0630 7 0.0683339 1670.97 1 6 CACCTG GAAGCCAGCGCTGC + +4 taipale_cyt_meth__NR2C1_NRGGTCRYGACCYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-usp 8 0.0683339 1670.97 1 6 CACCTG GAGGTCATGACCTC + +4 taipale_cyt_meth__RORC_NRGGTCRTGACCYN_eDBD-EcR-Hr3-usp 8 0.0683339 1670.97 1 6 CACCTG TAGGTCATGACCTA + +4 taipale_tf_pairs__HOXD12_TBX21_YNRCACSTCGTWAA_CAP 3 0.0683339 1670.97 1 6 CACCTG TAGCACCTCGTAAA + +4 hocomoco__NR1D1_HUMAN.H11MO.1.D-Eip75B-Hr3 3 0.0683339 1670.97 1 6 CACCTG TTTGACCTACTTTT - +4 neph__UW.Motif.0382 3 0.0683339 1670.97 1 6 CACCTG CATCAATTTCACTT - +4 neph__UW.Motif.0505 5 0.0683339 1670.97 1 6 CACCTG GGGCTGCCCTGGGT - +4 taipale__RXRA_DBD_GGGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0683339 1670.97 1 6 CACCTG TGACCTTTGACCCC - +4 taipale__Rxrb_DBD_GGGGTCAAAGGTCA-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 1 0.0683339 1670.97 1 6 CACCTG TGACCTTTGACCCC - +4 neph__UW.Motif.0320 9 0.0683339 1670.97 1 5 CACCTG AAGAAAAAACAGCT + +4 cisbp__M1455-EcR-Hr78-svp-usp 2 0.0691689 1691.39 1 6 CACCTG GTGACCCC + +4 cisbp__M5241-tin-vnd 0 0.0691689 1691.39 1 6 CACCTG CACTTGAG - +4 flyfactorsurvey__Tin_Cell_FBgn0004110-tin-vnd 0 0.0691689 1691.39 1 6 CACCTG CACTTGAG - +4 hocomoco__ETV4_MOUSE.H11MO.0.B-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Rpn5-aop-bs-pnt 2 0.0691689 1691.39 1 6 CACCTG ACTTCCTG - +4 predrem__nrMotif1000 0 0.0691689 1691.39 1 6 CACCTG CTCCTAGA - +4 stark__GTCACGTD 0 0.0691689 1691.39 1 6 CACCTG TACGTGAC - +4 predrem__nrMotif468 -2 0.0691689 1691.39 1 4 CACCTG CCTTGTAA + +4 cisbp__M4883-CG8319 4 0.0691689 1691.39 1 4 CACCTG GGGTCACC - +4 predrem__nrMotif567 4 0.0691689 1691.39 1 4 CACCTG GTCCCACC - +4 predrem__nrMotif581 4 0.0691689 1691.39 1 4 CACCTG AAACCACC - +4 flyfactorsurvey__lola-PY_SANGER_2.5_FBgn0005630-lola 0 0.0693314 1695.36 1 6 CACCTG AACCCTAAC + +4 predrem__nrMotif2075 0 0.0693314 1695.36 1 6 CACCTG AACCTTGTT + +4 cisbp__M6550-ci-opa 3 0.0693314 1695.36 1 6 CACCTG GACCACCCA - +4 hdpi__MRPL2-mRpL2 1 0.0693314 1695.36 1 6 CACCTG TTTCCTGTC - +4 predrem__nrMotif2505 0 0.0693314 1695.36 1 6 CACCTG TTCCTTACA - +4 predrem__nrMotif799 3 0.0693314 1695.36 1 6 CACCTG ACATGCCTG - +4 taipale_cyt_meth__NR2C1_NRRGGTCAN_eDBD_repr-EcR-eg-Hr78-kni-knrl-svp-usp 2 0.0693314 1695.36 1 6 CACCTG GTGACCTCG - +4 predrem__nrMotif2364 -1 0.0693314 1695.36 1 5 CACCTG CCCTGAGCC - +4 cisbp__M2303-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 1 0.0698821 1708.83 1 6 CACCTG TGACCTCTGACCCCT + +4 bergman__EcR_usp-EcR-svp-usp 9 0.0698821 1708.83 1 6 CACCTG GAGGTCATTGACCTC - +4 cisbp__M4657-btd-CTCF-HDAC1-Sin3A-Spps-SREBP 3 0.0698821 1708.83 1 6 CACCTG CAGCACCATGGACAG - +4 jaspar__MA0504.1-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-svp-usp 1 0.0698821 1708.83 1 6 CACCTG TGACCTCTGACCCCT - +4 taipale_cyt_meth__NR2F6_NRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0698821 1708.83 1 6 CACCTG ATGACCTTTGACCTC - +4 taipale_tf_pairs__GCM1_FOXI1_NNGTMAATANGGGYR_CAP-gcm-gcm2 0 0.0698821 1708.83 1 6 CACCTG TACCCTTATTTACAT - +4 taipale_tf_pairs__GCM1_HOXB13_RTGCGGGTAATAAAN_CAP-gcm-gcm2 6 0.0698821 1708.83 1 6 CACCTG TTTTATTACCCGCAT - +4 cisbp__M3632-tin-vnd 0 0.0702767 1718.48 1 6 CACCTG CACTTGA - +4 predrem__nrMotif331 1 0.0702767 1718.48 1 6 CACCTG ACACCTC - +4 predrem__nrMotif546 1 0.0702767 1718.48 1 6 CACCTG CCACATT - +4 scertf__harbison.MSN4-CG10348-CG13296-ham 1 0.0702767 1718.48 1 6 CACCTG ACCCCTT - +4 predrem__nrMotif1961 2 0.0702767 1718.48 1 5 CACCTG GAGAACT - +4 transfac_pro__M04875 -2 0.0702767 1718.48 1 4 CACCTG CCTGCTG + +4 cisbp__M2074 10 0.0703319 1719.83 1 6 CACCTG TTACATATTGCACCCGATTGG + +4 jaspar__MA0269.1 10 0.0703319 1719.83 1 6 CACCTG TTACATATTGCACCCGATTGG + +4 transfac_pro__M00765-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.0705867 1726.06 1 6 CACCTG TGACCTTTGACCC + +4 transfac_pro__M03884-Eip75B-Hr3 3 0.0705867 1726.06 1 6 CACCTG ACTGACCTATTTA + +4 transfac_pro__M00767-EcR-svp-usp 8 0.0705867 1726.06 1 5 CACCTG GGGTTAATGACCT + +4 transfac_pro__M00986 0 0.07081 1731.52 1 6 CACCTG CCCCCG - +4 transfac_pro__M02101-ac-ase-HLH4C-HLH54F-l(1)sc-nau-sc 0 0.07081 1731.52 1 6 CACCTG CAGCTG - +4 transfac_pro__M03790-EcR 1 0.07081 1731.52 1 5 CACCTG TGACCT + +4 fantom__motif27_CCTGCA -2 0.07081 1731.52 1 4 CACCTG CCTGCA + +4 cisbp__M5764-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.0709267 1734.37 1 6 CACCTG TGACCTTTTGACCTTT + +4 cisbp__M6519-achi-vis 7 0.0709267 1734.37 1 6 CACCTG CAGGTGACACCTGACA + +4 neph__UW.Motif.0311 6 0.0709267 1734.37 1 6 CACCTG GCTGGGTTCCAGCAGA + +4 neph__UW.Motif.0436 5 0.0709267 1734.37 1 6 CACCTG AATCACAGCAACAGTG + +4 taipale__T_full_TCACACCTAGGTGTGA-byn-H15-mid-org-1 3 0.0709267 1734.37 1 6 CACCTG TCACACCTAGGTGTGA + +4 transfac_pro__M01411-achi-esg-hth-sna-vis-wor 3 0.0709267 1734.37 1 6 CACCTG AAGCACCTGTCAATAT + +4 transfac_pro__M02889-bowl-drm-odd-sob 6 0.0709267 1734.37 1 6 CACCTG ACTTGCTACCTACATC + +4 neph__UW.Motif.0314 4 0.0709267 1734.37 1 6 CACCTG GCAATTTCTCTGTCTC - +4 neph__UW.Motif.0573 8 0.0709267 1734.37 1 6 CACCTG CAAAATTTTTCATCTG - +4 neph__UW.Motif.0596 2 0.0709267 1734.37 1 6 CACCTG GGAAGCATCTGTCTCT - +4 neph__UW.Motif.0628 2 0.0709267 1734.37 1 6 CACCTG GACAATTTCCTTTTTC - +4 taipale__RARB_full_AARGGTCAAAAGGTCA-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.0709267 1734.37 1 6 CACCTG TGACCTTTTGACCTTT - +4 taipale_cyt_meth__RARA_NRGGTCANNRGGTCAN_eDBD_meth-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.0709267 1734.37 1 6 CACCTG GTGACCTCTTGACCTC - +4 taipale_cyt_meth__RARB_NRGGTCANNRGGTCAN_FL_repr-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 10 0.0709267 1734.37 1 6 CACCTG GTGACCTTTTGACCTT - +4 cisbp__M6446-EcR-usp 2 0.0710798 1738.11 1 6 CACCTG GTGACCTCTGGCTGACCCCC + +4 hocomoco__ZN329_HUMAN.H11MO.0.C 13 0.0710798 1738.11 1 6 CACCTG CTGGATCCAGCCATGCCTGA + +4 homer__GGAGCTGTCCATGGTGCTGA_REST-NRSF-CTCF-HDAC1-Sin3A-Spps-btd 4 0.0710798 1738.11 1 6 CACCTG TCAGCACCATGGACAGCTCC - +4 cisbp__M5767-EcR-eg-ERR-Hr78-kni-knrl-svp-usp 11 0.071521 1748.9 1 6 CACCTG TGACCTCTGGTGACCTT + +4 jaspar__MA0494.1-EcR-usp 11 0.0715535 1749.7 1 6 CACCTG TGACCTAAAGTAACCTCTG + +4 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNNNNNNTGCGGG_CAP_repr-gcm-gcm2 13 0.0715535 1749.7 1 6 CACCTG CCCGCATCCCCACCACCTG - +4 cisbp__M0084-TfAP-2 0 0.0716667 1752.47 1 6 CACCTG CGCCCGAGGC + +4 cisbp__M0268-Atf6-CrebA-Xbp1 1 0.0716667 1752.47 1 6 CACCTG TGACGTGGCA + +4 cisbp__M0284-Atf6-CrebA-Xbp1 2 0.0716667 1752.47 1 6 CACCTG GTGACGTGGC + +4 cisbp__M1197-scro-vnd 3 0.0716667 1752.47 1 6 CACCTG AAGCACTTGA + +4 cisbp__M1625-bi-byn-Doc1-Doc2-Doc3-H15-mid 4 0.0716667 1752.47 1 6 CACCTG TTGACACCTC + +4 transfac_pro__M08868-Clk-cyc-tgo 4 0.0716667 1752.47 1 6 CACCTG CAGGCACGTG + +4 cisbp__M0180-tgo 1 0.0716667 1752.47 1 6 CACCTG GCACATGAAT - +4 cisbp__M0260-nau 1 0.0716667 1752.47 1 6 CACCTG ACAGCTGTCA - +4 cisbp__M1923 1 0.0716667 1752.47 1 6 CACCTG CCAACTGCCA - +4 cisbp__M4970-da-Fer3 0 0.0716667 1752.47 1 6 CACCTG CAGCTGTTAC - +4 homer__AAYTAGGTCA_RORgt-Hr3 1 0.0716667 1752.47 1 6 CACCTG TGACCTAGTT - +4 taipale__GCM1_DBD_NATGCGGGTA_repr-gcm-gcm2 0 0.0716667 1752.47 1 6 CACCTG TACCCGCATG - +4 transfac_pro__M09569 3 0.0716667 1752.47 1 6 CACCTG TGACACGTGT - +4 predrem__nrMotif5 -1 0.0716667 1752.47 1 5 CACCTG GCCTGGGGCC - +4 transfac_pro__M03186 -1 0.0716667 1752.47 1 5 CACCTG ACCTCGGTCG - +4 cisbp__M5759-EcR-eg-Hnf4-kni-knrl-svp-tll-usp 12 0.0717146 1753.64 1 6 CACCTG CATTGACCTTTTGACCTC + +4 cisbp__M6066-EcR-eg-ERR-Hr78-kni-knrl-svp 11 0.0717146 1753.64 1 6 CACCTG TGACCTCTCTTGACCTTT + +4 taipale_cyt_meth__TBX20_NTNACRCCTANGTGTGAN_FL_meth-byn-Doc2-H15-mid-org-1 4 0.0717146 1753.64 1 6 CACCTG TTCACACCTAAGTGTGAA + +4 cisbp__M5935-achi-hth-nau-vis 3 0.0720357 1761.49 1 6 CACCTG TGACAGCTGTCA + +4 hocomoco__SMAD3_HUMAN.H11MO.0.B-Smox 6 0.0720357 1761.49 1 6 CACCTG CTCTGTCACCTG + +4 transfac_public__M00182-Atf6-CrebA-Max-Myc-tgo-Usf 3 0.0720357 1761.49 1 6 CACCTG GGCCACGTGGCA + +4 cisbp__M0571 6 0.0720357 1761.49 1 6 CACCTG ATTCCCCACCGG - +4 transfac_pro__M06253 6 0.0720357 1761.49 1 6 CACCTG TCGGCTTACCCG - +4 transfac_pro__M05565 7 0.0720357 1761.49 1 5 CACCTG TATGGCATACCA - +4 transfac_pro__M06174 7 0.0720357 1761.49 1 5 CACCTG TCTTTAGTACCT - +4 transfac_pro__M06397 7 0.0720357 1761.49 1 5 CACCTG TATGCCCAACCA - +4 flyfactorsurvey__Side_SANGER_5_FBgn0032741-Sidpn-da-sage 4 0.0724753 1772.24 1 6 CACCTG AAAACACCTGT + +4 taipale_cyt_meth__TFAP2A_NSCCYNRGGSN_FL-TfAP-2 0 0.0724753 1772.24 1 6 CACCTG TGCCTCAGGCA + +4 predrem__nrMotif2042 1 0.0724753 1772.24 1 6 CACCTG CCTCCTCCCCA - +4 transfac_pro__M08951-nau 2 0.0724753 1772.24 1 6 CACCTG AACAACTGTTA - +4 cisbp__M5795-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0728613 1781.68 1 6 CACCTG TGACCTTTGACCCC + +4 homer__AGGTCANTGACCTN_FXR-EcR-Hr78-svp-usp 8 0.0728613 1781.68 1 6 CACCTG AGGTCATTGACCTC + +4 transfac_pro__M01802 7 0.0728613 1781.68 1 6 CACCTG AAGGGTGCACCCAT + +4 transfac_pro__M03821 5 0.0728613 1781.68 1 6 CACCTG ACAGTGACCCGGAA + +4 taipale_tf_pairs__CUX1_SRF_NCCATAYWNGGWNNNNATCRATN_CAP_repr-bs-ct 10 0.0729771 1784.51 1 6 CACCTG AATTGATCATGACCTTGTATGGT - +4 tfdimers__MD00596-eg-kni-knrl 7 0.0729771 1784.51 1 6 CACCTG ATTTTCTGACCTATAAAAAAAAA - +4 tfdimers__MD00528 9 0.0731029 1787.58 1 6 CACCTG CCCCCTCCCCACCTGCTGTCCTCCTG + +4 cisbp__M1440-Hr78-svp-usp 2 0.0733974 1794.79 1 6 CACCTG GTGACCCC + +4 cisbp__M4709-Clk-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo 2 0.0733974 1794.79 1 6 CACCTG GTCACGTG + +4 predrem__nrMotif1978 1 0.0733974 1794.79 1 6 CACCTG TTACCATT + +4 predrem__nrMotif872 0 0.0733974 1794.79 1 6 CACCTG AACCTGAT + +4 transfac_pro__M08890-Myb 1 0.0733974 1794.79 1 6 CACCTG CCAACTGC + +4 jaspar__MA0977.1 0 0.0733974 1794.79 1 6 CACCTG CACTTTTT - +4 predrem__nrMotif1572 1 0.0733974 1794.79 1 6 CACCTG TTAACTGA - +4 predrem__nrMotif696 2 0.0733974 1794.79 1 6 CACCTG GGCAACTG - +4 scertf__fordyce.MATA2 0 0.0733974 1794.79 1 6 CACCTG TACATGAT - +4 transfac_public__M00154 1 0.0733974 1794.79 1 6 CACCTG CCCCCTGA - +4 predrem__nrMotif2033 -1 0.0733974 1794.79 1 5 CACCTG ACCCCGAG + +4 cisbp__M4787-byn 3 0.0733974 1794.79 1 5 CACCTG TCGCACTT - +4 predrem__nrMotif1071 -1 0.0733974 1794.79 1 5 CACCTG ATCTTACT - +4 predrem__nrMotif1076 0 0.0736161 1800.13 1 6 CACCTG CACCCCCCT + +4 predrem__nrMotif1972 0 0.0736161 1800.13 1 6 CACCTG CACCCGGGC + +4 predrem__nrMotif224 3 0.0736161 1800.13 1 6 CACCTG CCTCACTTT + +4 predrem__nrMotif333 0 0.0736161 1800.13 1 6 CACCTG AACTTGGAA + +4 transfac_pro__M00913 0 0.0736161 1800.13 1 6 CACCTG CAACTGCCA + +4 predrem__nrMotif1917 2 0.0736161 1800.13 1 6 CACCTG TGCACATGT - +4 transfac_pro__M04881 3 0.0736161 1800.13 1 6 CACCTG GGTCACCTT - +4 scertf__foat.AFT1 4 0.0736161 1800.13 1 5 CACCTG TTTGCACCC + +4 transfac_pro__M05059 4 0.0736161 1800.13 1 5 CACCTG ACTTAACCT + +4 transfac_pro__M05126 4 0.0736161 1800.13 1 5 CACCTG ACTTAACCT + +4 jaspar__MA0193.1-schlank 1 0.0744944 1821.61 1 6 CACCTG CTACCAA + +4 transfac_pro__M01269-Hr38 1 0.0744944 1821.61 1 6 CACCTG TGGCCTT + +4 fantom__motif77_TCCTTGG -1 0.0744944 1821.61 1 5 CACCTG TCCTTGG + +4 predrem__nrMotif2156 -1 0.0744944 1821.61 1 5 CACCTG TCCTGCT + +4 cisbp__M5081-lola 2 0.0744944 1821.61 1 5 CACCTG GAAACCC - +4 predrem__nrMotif2476 -1 0.0744944 1821.61 1 5 CACCTG TCCTGGA - +4 elemento__ACTCACC 3 0.0744944 1821.61 1 4 CACCTG ACTCACC + +4 elemento__CCCCACC 3 0.0744944 1821.61 1 4 CACCTG CCCCACC + +4 elemento__CTCCACC 3 0.0744944 1821.61 1 4 CACCTG CTCCACC + +4 elemento__GGCCACC 3 0.0744944 1821.61 1 4 CACCTG GGCCACC + +4 elemento__GGTCACC 3 0.0744944 1821.61 1 4 CACCTG GGTCACC + +4 cisbp__M4502-CTCF-SMC3-usp-vtd 4 0.0745434 1822.81 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4534-CTCF-SMC3-usp-vtd 4 0.0745434 1822.81 1 6 CACCTG GTGCCCCCTGGTGGC - +4 factorbook__RXRA-ERR-EcR-Eip78C-Hnf4-Hr78-eg-kni-knrl-svp-usp 4 0.0745434 1822.81 1 6 CACCTG CCCTGACCTTTGCCC - +4 flyfactorsurvey__disco-r-F1-2_SOLEXA_FBgn0042650-disco-disco-r 7 0.0745434 1822.81 1 6 CACCTG AAAATGTCACCCAAC - +4 flyfactorsurvey__lola-PA_SOLEXA_FBgn0005630-lola 2 0.0745434 1822.81 1 6 CACCTG GGAACCCTCTGGGTT - +4 neph__UW.Motif.0323 5 0.0745434 1822.81 1 6 CACCTG GCCTTTGCCTCTGCT - +4 neph__UW.Motif.0590 3 0.0745434 1822.81 1 6 CACCTG GAAATTCTGTTTCTG - +4 taipale_cyt_meth__RXRA_NRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.0745434 1822.81 1 6 CACCTG TTGACCTTTGACCTC - +4 taipale_tf_pairs__HOXD12_EOMES_AGGYGYGANNNNNNNNNNNNNNNTCRTWAA_CAP_repr 19 0.074589 1823.92 1 6 CACCTG AGGCGTGAAGATACATTCACACCTCGTAAA + +4 tfdimers__MD00594 13 0.074589 1823.92 1 6 CACCTG TTTTTCCTTTCCCCATCTGTCACTGTCATT - +4 scertf__badis.GIS1-Kdm4A-Kdm4B 0 0.0749127 1831.84 1 6 CACCTG CCCCTA + +4 transfac_pro__M01808-Myc 0 0.0749127 1831.84 1 6 CACCTG CATCTG + +4 hdpi__NAP1L1-CG3708-Nap1-mil -1 0.0749127 1831.84 1 5 CACCTG GCCTGG - +4 hdpi__RXRA-usp 1 0.0749127 1831.84 1 5 CACCTG TGACCC - +4 transfac_pro__M01995 1 0.0749127 1831.84 1 5 CACCTG CCACGT - +4 cisbp__M6460-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 1 0.0751766 1838.29 1 6 CACCTG TGACCTTTGACCT + +4 hocomoco__MEIS2_HUMAN.H11MO.0.B-achi-hth-nau-vis 3 0.0751766 1838.29 1 6 CACCTG TGACAGCTGTCAA - +4 hocomoco__TBX21_HUMAN.H11MO.0.A-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 4 0.0751766 1838.29 1 6 CACCTG TTCACACCTCCAC - +4 jaspar__MA0941.1 2 0.0751766 1838.29 1 6 CACCTG AACACGTGTCATG - +4 jaspar__MA0513.1-Med-Smox 8 0.0751766 1838.29 1 5 CACCTG CTGTCTGTCACCT + +4 neph__UW.Motif.0414 3 0.0756925 1850.91 1 6 CACCTG AAAAAATTGTGGTTTG + +4 neph__UW.Motif.0500 2 0.0756925 1850.91 1 6 CACCTG AAATCCATTTTCCTCT + +4 neph__UW.Motif.0517 3 0.0756925 1850.91 1 6 CACCTG AAAAAAATTATTCATG + +4 taipale_cyt_meth__THRB_NRRGGTCRTGACCYYN_eDBD-EcR-eg-Hr78-kni-knrl-usp 9 0.0756925 1850.91 1 6 CACCTG AGAGGTCATGACCTCT + +4 taipale__Rarb_DBD_AARGGTCAAAAGGTCA-EcR-eg-Hnf4-kni-knrl-svp 9 0.0756925 1850.91 1 6 CACCTG TGACCTTTTGACCTTT - +4 transfac_pro__M02783-EcR-eg-Hr78-kni-knrl-svp 5 0.0756925 1850.91 1 6 CACCTG CTCGTGACCTTTGAGA - +4 neph__UW.Motif.0597 11 0.0756925 1850.91 1 5 CACCTG AAATGTTTTTCCAGCT - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BPL_1__m1-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.0760026 1858.49 1 6 CACCTG CTATAGCGCCCCCTGGTGGC + +4 dbcorrdb__REST__ENCSR000BMN_1__m2-CTCF-Sin3A 9 0.0760026 1858.49 1 6 CACCTG AGGATTCAGCACCAAGGACA + +4 taipale_tf_pairs__TEAD4_TBX21_ARGTGTKRNNNNNRGWATGY_CAP-sd 15 0.0760026 1858.49 1 5 CACCTG ACATTCCATTGGTAACACCT - +4 cisbp__M1361 1 0.0761311 1861.63 1 6 CACCTG AACCCTAGCT + +4 jaspar__MA0100.2 1 0.0761311 1861.63 1 6 CACCTG CCAACTGCCA + +4 jaspar__MA0966.1-bigmax-mio 2 0.0761311 1861.63 1 6 CACCTG AGCACGTGCT + +4 jaspar__MA1030.1 1 0.0761311 1861.63 1 6 CACCTG AACCCTAGAT + +4 predrem__nrMotif1024 1 0.0761311 1861.63 1 6 CACCTG TCCCCTGGCC + +4 taipale__NKX2-3_DBD_NCCACTTRAN-scro-tin-vnd 2 0.0761311 1861.63 1 6 CACCTG ACCACTTGAA + +4 taipale_cyt_meth__NKX2-3_NNCACTTRAN_FL-scro-vnd 2 0.0761311 1861.63 1 6 CACCTG CCCACTTGAC + +4 transfac_pro__M00376 2 0.0761311 1861.63 1 6 CACCTG CTCACGTGAG + +4 transfac_pro__M07833-tin-vnd 2 0.0761311 1861.63 1 6 CACCTG ACCACTTGAG + +4 transfac_pro__M09568-CrebA-Xbp1 1 0.0761311 1861.63 1 6 CACCTG TTACGTGGCA + +4 cisbp__M5484-gcm-gcm2 0 0.0761311 1861.63 1 6 CACCTG TACCCGCATG - +4 cisbp__M5487-gcm-gcm2 0 0.0761311 1861.63 1 6 CACCTG TACCCGCATA - +4 hocomoco__HTF4_HUMAN.H11MO.0.A 2 0.0761311 1861.63 1 6 CACCTG CACAGCTGCA - +4 predrem__nrMotif458 3 0.0761311 1861.63 1 6 CACCTG TGTCACCTCT - +4 taipale__GCM2_DBD_NATGCGGGTN-gcm-gcm2 0 0.0761311 1861.63 1 6 CACCTG TACCCGCATA - +4 taipale_cyt_meth__HES2_GGCRCGTGYN_eDBD_meth 2 0.0761311 1861.63 1 6 CACCTG CCCACGTACC - +4 taipale_cyt_meth__NR4A1_NAAAGGTCAN_eDBD_1-Hr38-Hr78 2 0.0761311 1861.63 1 6 CACCTG GTGACCTTTA - +4 transfac_pro__M01691 0 0.0761311 1861.63 1 6 CACCTG TTCCTTTGGA - +4 cisbp__M5760-EcR-eg-ERR-kni-knrl-svp-usp 1 0.0763632 1867.31 1 6 CACCTG TGACCTTTGCATGACCT + +4 cisbp__M6074-EcR-usp 1 0.0763632 1867.31 1 6 CACCTG TGACCTTTCGTGACCTT + +4 transfac_pro__M06304 11 0.0763632 1867.31 1 6 CACCTG TTAACCGGGAATACCTA + +4 hocomoco__PPARG_MOUSE.H11MO.0.A-EcR-Hnf4-Hr3-Hr78-eg-kni-knrl-svp-usp 1 0.0763632 1867.31 1 6 CACCTG TGACCTTTGCCCCACTT - +4 taipale__RARA_DBD_RGGTCANNNARRGGTCA_repr-EcR-eg-ERR-kni-knrl-svp-usp 1 0.0763632 1867.31 1 6 CACCTG TGACCTTTGCATGACCT - +4 taipale__Rarg_DBD_RRGGTCANNNRRGGTCA-EcR-Hr4-usp 1 0.0763632 1867.31 1 6 CACCTG TGACCTTTCGTGACCTT - +4 transfac_pro__M02119-EcR 2 0.0763632 1867.31 1 6 CACCTG CTGACCTCAGCTCACCC - +4 taipale_tf_pairs__CUX1_TBX3_AGGTGTGNNNNATCRAT_CAP_repr-bi-ct 12 0.0763632 1867.31 1 5 CACCTG ATTGATCATCCACACCT - +4 hocomoco__ZKSC1_HUMAN.H11MO.0.B 4 0.0764721 1869.97 1 6 CACCTG TGAGGACCTACTGTGTGCC + +4 cisbp__M3004-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 7 0.076595 1872.98 1 6 CACCTG AATTTCACACCTAGGTGTCACTAG - +4 transfac_public__M00150-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 7 0.076595 1872.98 1 6 CACCTG AATTTCACACCTAGGTGTCACTAG - +4 taipale__RARA_DBD_RAGGTCAAAAGGTCAAKN_repr-EcR-eg-Hnf4-kni-knrl-svp-tll-usp 12 0.0766071 1873.27 1 6 CACCTG CATTGACCTTTTGACCTC - +4 taipale_cyt_meth__CREB3_NGCCACGTGKMN_FL_meth-Atf6-Clk-CrebA 3 0.0766421 1874.13 1 6 CACCTG TGCCACGTGGCA + +4 transfac_pro__M04873-ERR-ftz-f1-srl 2 0.0766421 1874.13 1 6 CACCTG GTGACCTTGGGC + +4 transfac_pro__M05852 5 0.0766421 1874.13 1 6 CACCTG GGGGCAACCTTC + +4 swissregulon__hs__GTF2A1_2.p2-TfIIA-L-TfIIA-S 1 0.0766421 1874.13 1 6 CACCTG GCCCCTTTCAGA - +4 transfac_pro__M06363 6 0.0766421 1874.13 1 6 CACCTG GCGGTCCACCGG - +4 transfac_pro__M06981 3 0.0766421 1874.13 1 6 CACCTG GGTCAACTGTCG - +4 neph__UW.Motif.0458 7 0.0766421 1874.13 1 5 CACCTG AGATTTTAATCT + +4 transfac_pro__M05696 7 0.0766421 1874.13 1 5 CACCTG TCCCTCGGACCT - +4 transfac_pro__M05704-CG4360-jim 7 0.0766421 1874.13 1 5 CACCTG GCGGTTTAACCA - +4 transfac_pro__M05715 7 0.0766421 1874.13 1 5 CACCTG TTTTTTTTACCA - +4 transfac_pro__M05827-CG2120 7 0.0766421 1874.13 1 5 CACCTG TCTCCTTTACCT - +4 transfac_pro__M06341 7 0.0766421 1874.13 1 5 CACCTG TCATTTGCACCT - +4 cisbp__M5176-da-sage-Sidpn 4 0.0770435 1883.95 1 6 CACCTG AAAACACCTGT + +4 flyfactorsurvey__lola_PK_SANGER_5_FBgn0005630-lola 5 0.0770435 1883.95 1 6 CACCTG GATCCTACTTT + +4 cisbp__M0244-cnc-Mitf 2 0.0770435 1883.95 1 6 CACCTG TGCACGTGACT - +4 predrem__nrMotif1153 5 0.0770435 1883.95 1 6 CACCTG CAGAGAACCAG - +4 taipale__Esrra_DBD_TTCAAGGTCAN_repr-ERR-ftz-f1-Hr39 2 0.0770435 1883.95 1 6 CACCTG ATGACCTTGAA - +4 taipale_tf_pairs__FOXJ3_TBX21_WAACAACACMY_CAP_repr 6 0.0770435 1883.95 1 5 CACCTG TAACAACACCT + +4 cisbp__M5799-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 1 0.0776258 1898.18 1 6 CACCTG TGACCTTTGACCCC + +4 taipale_cyt_meth__RXRG_NRGGTCAYGACCYN_FL-EcR-eg-Hr78-kni-knrl-usp 8 0.0776258 1898.18 1 6 CACCTG GAGGTCATGACCTC + +4 transfac_pro__M00979-ey-toy 2 0.0776258 1898.18 1 6 CACCTG CTGACCTGGAACTC + +4 transfac_pro__M08889 3 0.0776258 1898.18 1 6 CACCTG AATTACATCATAAG + +4 swissregulon__hs__ESRRA.p2-ERR-ftz-f1 3 0.0776258 1898.18 1 6 CACCTG TGTGACCTTGAGCA - +4 taipale_tf_pairs__GCM2_DRGX_RTRSGGGNAATTAN_CAP_repr-CG11294-Drgx-gcm-gcm2 5 0.0776258 1898.18 1 6 CACCTG CTAATTACCCGCAT - +4 stark__ATCTNATC -1 0.0778423 1903.48 1 5 CACCTG ATCTAATC + +4 flyfactorsurvey__byn_FlyReg_FBgn0011723-byn 3 0.0778423 1903.48 1 5 CACCTG TCGCACTT - +4 hocomoco__ESR2_MOUSE.H11MO.1.A-EcR-svp 3 0.0778423 1903.48 1 5 CACCTG CCTGACCT - +4 predrem__nrMotif2489 -1 0.0778423 1903.48 1 5 CACCTG ACCAAAAG - +4 predrem__nrMotif14 -2 0.0778423 1903.48 1 4 CACCTG CCTGAGGA - +4 flyfactorsurvey__ato_da_SANGER_5_3_FBgn0000413-ato-da 1 0.0781183 1910.23 1 6 CACCTG CCACCTGCC + +4 taipale__NKX2-8_full_NCACTTNAN-scro-tin-vnd 1 0.0781183 1910.23 1 6 CACCTG CCACTTGAA + +4 cisbp__M1339 3 0.0781183 1910.23 1 6 CACCTG CCTTATCCA - +4 cisbp__M4147-opa 3 0.0781183 1910.23 1 6 CACCTG GACCACCCA - +4 hocomoco__TGIF1_MOUSE.H11MO.0.A-achi-hth-vis 0 0.0781183 1910.23 1 6 CACCTG CAGCTGTCA - +4 hocomoco__THA_MOUSE.H11MO.1.C-EcR 2 0.0781183 1910.23 1 6 CACCTG GTGACCTCA - +4 predrem__nrMotif2173 0 0.0781183 1910.23 1 6 CACCTG TAACTGCCC - +4 predrem__nrMotif850 -1 0.0781183 1910.23 1 5 CACCTG TCCTCCTTT - +4 cisbp__M2002-schlank 1 0.0788949 1929.22 1 6 CACCTG CTACCAA + +4 transfac_pro__M01207-aop 1 0.0788949 1929.22 1 6 CACCTG CTTCCTG + +4 cisbp__M0760 1 0.0788949 1929.22 1 6 CACCTG AGATCTT - +4 predrem__nrMotif2583 1 0.0788949 1929.22 1 6 CACCTG TGACCAG - +4 transfac_pro__M04794-Taf1 -1 0.0788949 1929.22 1 5 CACCTG ACCGGAA + +4 transfac_pro__M04826-nej -1 0.0788949 1929.22 1 5 CACCTG ACTTCCG + +4 elemento__CCTGCAG -2 0.0788949 1929.22 1 4 CACCTG CCTGCAG + +4 elemento__CCTGCCC -2 0.0788949 1929.22 1 4 CACCTG CCTGCCC + +4 elemento__CCTGGCA -2 0.0788949 1929.22 1 4 CACCTG CCTGGCA + +4 transfac_pro__M04912-fkh -2 0.0788949 1929.22 1 4 CACCTG CCTGCTG + +4 cisbp__M0450 -2 0.0788949 1929.22 1 4 CACCTG CCTGTTG - +4 elemento__CAGCAGG -2 0.0788949 1929.22 1 4 CACCTG CCTGCTG - +4 elemento__CCCCAGG -2 0.0788949 1929.22 1 4 CACCTG CCTGGGG - +4 neph__UW.Motif.0259 5 0.0794503 1942.8 1 6 CACCTG AGAAATTGCTGTGTG + +4 cisbp__M4613-CTCF-SMC3-usp-vtd 4 0.0794503 1942.8 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4658-CTCF-SMC3-Stat92E-usp-vtd 3 0.0794503 1942.8 1 6 CACCTG CGCCCCCTGGTGGCC - +4 hocomoco__TAL1_HUMAN.H11MO.1.A-HLH3B 2 0.0794503 1942.8 1 6 CACCTG CACATCTGCTTCCTG - +4 neph__UW.Motif.0580 4 0.0794503 1942.8 1 6 CACCTG GAGAGGCCAGGGGGG - +4 taipale_cyt_meth__RXRA_NRGGTCAAAGGTCAN_eDBD-EcR-eg-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 2 0.0794503 1942.8 1 6 CACCTG GTGACCTTTGACCCC - +4 cisbp__M2065-EcR-eg-ERR-kni-knrl 10 0.0794503 1942.8 1 5 CACCTG AGGTCAGGGTGACCT + +4 neph__UW.Motif.0444 10 0.0794503 1942.8 1 5 CACCTG AAAAAAATCTCATCT + +4 transfac_pro__M07896-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.079942 1954.82 1 6 CACCTG CTTCACACCTCCCCGCCACATTTCACACCT - +4 cisbp__M0340 5 0.0800035 1956.33 1 6 CACCTG TAGATTACGTGTA + +4 cisbp__M6344-achi-hth-nau-vis 3 0.0800035 1956.33 1 6 CACCTG TGACAGCTGTCAA + +4 taipale_tf_pairs__MGA_PITX1_RGGTGNTAAKCCN_CAP_repr-Ptx1 8 0.0800035 1956.33 1 5 CACCTG CGGATTAGCACCT - +4 factorbook__REST-CTCF-HDAC1-Sin3A-Spps-btd 5 0.0804303 1966.76 1 6 CACCTG TTCAGCACCATGGACAGCGCC - +4 taipale_tf_pairs__GCM1_CEBPB_MTRSGGGNNNNNTTRCGYAAN_CAP-gcm-gcm2 12 0.0804303 1966.76 1 6 CACCTG ATTGCGCAACACCACCCGCAT - +4 cisbp__M6069-EcR-eg-Hnf4-kni-knrl-svp 9 0.0807115 1973.64 1 6 CACCTG TGACCTTTTGACCTTT + +4 taipale_cyt_meth__RARG_NRGGTCAAAAGGTCAN_eDBD_meth-EcR-eg-Hnf4-kni-knrl-svp-usp 10 0.0807115 1973.64 1 6 CACCTG ATGACCTTTTGACCTC - +4 transfac_pro__M07306-Hr3 2 0.0807115 1973.64 1 6 CACCTG CTGACCTAGTTTCTAT - +4 transfac_public__M00110-grh 6 0.0807115 1973.64 1 6 CACCTG ATTCAAAACCGTTCCA - +4 taipale_tf_pairs__GCM1_TBX21_AGGTGTNRTRCGGGNN_CAP_repr-gcm-gcm2 11 0.0807115 1973.64 1 5 CACCTG AACCCGCATGACACCT - +4 cisbp__M0364 4 0.0808199 1976.29 1 6 CACCTG TCGCCACGTG + +4 cisbp__M1389 2 0.0808199 1976.29 1 6 CACCTG ATACCCTAAT + +4 cisbp__M1444-EcR-Hr78-svp 4 0.0808199 1976.29 1 6 CACCTG GCATGACCTC + +4 predrem__nrMotif1305 0 0.0808199 1976.29 1 6 CACCTG TTCCTCATTA + +4 taipale_cyt_meth__NKX2-8_NNCACTTSAN_FL_meth-scro-tin-vnd 2 0.0808199 1976.29 1 6 CACCTG ACCACTTGAG + +4 transfac_pro__M07744-Sox14 0 0.0808199 1976.29 1 6 CACCTG CACCGAACAC + +4 transfac_pro__M09550 4 0.0808199 1976.29 1 6 CACCTG AAAATATCTA + +4 cisbp__M0165 4 0.0808199 1976.29 1 6 CACCTG TACGCACGTG - +4 cisbp__M0379 2 0.0808199 1976.29 1 6 CACCTG TTTACCTCAA - +4 cisbp__M1425 4 0.0808199 1976.29 1 6 CACCTG AGGTCACAAT - +4 cisbp__M2175 0 0.0808199 1976.29 1 6 CACCTG TTCCTTTGGA - +4 cisbp__M4670-CTCF-vtd 4 0.0808199 1976.29 1 6 CACCTG GCGCCATCTA - +4 homer__BTCAAGGTCA_Nr5a2-ERR-EcR-Hr4-ftz-f1-usp 1 0.0808199 1976.29 1 6 CACCTG TGACCTTGAA - +4 jaspar__MA0370.1 0 0.0808199 1976.29 1 6 CACCTG TTCCTTTGGA - +4 neph__UW.Motif.0048 1 0.0808199 1976.29 1 6 CACCTG TGCCCTGTGG - +4 predrem__nrMotif1479 1 0.0808199 1976.29 1 6 CACCTG AAACCAGACA - +4 predrem__nrMotif1866 3 0.0808199 1976.29 1 6 CACCTG CTCCAGCTGC - +4 predrem__nrMotif2260 4 0.0808199 1976.29 1 6 CACCTG AGGCCAGCTG - +4 taipale_cyt_meth__NR4A2_NAAAGGTCRN_eDBD-Hr38 2 0.0808199 1976.29 1 6 CACCTG GTGACCTTTC - +4 transfac_pro__M08885-cwo-Hey-Max-Myc 0 0.0808199 1976.29 1 6 CACCTG CACGTGCCGC - +4 transfac_public__M00031 3 0.0808199 1976.29 1 6 CACCTG TTTTACATGA - +4 predrem__nrMotif1757 -1 0.0808199 1976.29 1 5 CACCTG GCCTGGAACA + +4 predrem__nrMotif1597 -1 0.0808199 1976.29 1 5 CACCTG GCCTGGGTTC - +4 transfac_pro__M08192-bs 8 0.0812052 1985.71 1 6 CACCTG GTGTAAGTTACCTAATTAGG + +4 dbcorrdb__RAD21__ENCSR000EHX_1__m3-vtd 2 0.0812052 1985.71 1 6 CACCTG TTTACCTCTAAATGCTTTTT - +4 dbcorrdb__REST__ENCSR000BMW_1__m1-CTCF-Sin3A 11 0.0812052 1985.71 1 6 CACCTG ACCCTGGACAGCACCATGGA - +4 hocomoco__ZSC16_HUMAN.H11MO.0.D 14 0.0812052 1985.71 1 6 CACCTG TAGTGTTAACAGAACACCTC - +4 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNNNNNNNTGCGGG_CAP_repr-gcm-gcm2 14 0.0812052 1985.71 1 6 CACCTG CCCGCATCCCACACCACCTG - +4 taipale_tf_pairs__TEAD4_ESRRB_RCATTCYNNNNCAAGGTCAN_CAP_repr-ERR-sd 2 0.0812052 1985.71 1 6 CACCTG TTGACCTTGCAAAGGAATGC - +4 transfac_pro__M01462-pdm3 2 0.0814665 1992.1 1 6 CACCTG GCAACCTCATTATGTTT - +4 cisbp__M6176-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Nup133-Pc-svp-usp 1 0.0814838 1992.52 1 6 CACCTG TGACCTTTGACC + +4 cisbp__M6375-bap-scro-vnd 4 0.0814838 1992.52 1 6 CACCTG AAACCACTTAAA + +4 neph__UW.Motif.0454 0 0.0814838 1992.52 1 6 CACCTG CTTCTGTGTTTA + +4 hocomoco__COT1_MOUSE.H11MO.1.C-EcR-HDAC1-Hnf4-Hr4-Hr51-Hr78-Nup133-Pc-eg-kni-knrl-svp-usp 1 0.0814838 1992.52 1 6 CACCTG TGACCTTTGACC - +4 transfac_pro__M05889 2 0.0814838 1992.52 1 6 CACCTG GCAGCCTGCACA - +4 transfac_pro__M05643 7 0.0814838 1992.52 1 5 CACCTG TCTAAACGACCG - +4 transfac_pro__M05895 7 0.0814838 1992.52 1 5 CACCTG GATTATGTACCA - +4 transfac_pro__M06773 7 0.0814838 1992.52 1 5 CACCTG GCGCTAGCACCA - +4 transfac_pro__M06832 7 0.0814838 1992.52 1 5 CACCTG TTGGTCTCACCA - +4 transfac_pro__M08191-bs-bsh-E5-ems-en-inv-Vsx2 7 0.0816654 1996.96 1 6 CACCTG ATGTAATTACCTAATTAGG + +4 transfac_pro__M04697-Chd1-CTCF-SMC3-usp-vtd 7 0.0816654 1996.96 1 6 CACCTG ATAGTGCCATCTGGTGGCC - +4 transfac_pro__M02377-EcR-eg-ERR-kni-knrl 12 0.0817679 1999.47 1 6 CACCTG CAAGGTCACGGTGACCTG + +4 taipale_tf_pairs__GCM2_DLX3_RTRCGGGNNNNNTAATKR_CAP-gcm-gcm2 9 0.0817679 1999.47 1 6 CACCTG CAATTATCTAACCCGCAT - +4 transfac_pro__M05377 8 0.0817679 1999.47 1 6 CACCTG ACAATGCTGACCTCACCC - +4 cisbp__M6008-ERR-ftz-f1-Hr39 2 0.0818426 2001.3 1 6 CACCTG ATGACCTTGAA + +4 flyfactorsurvey__Fer1_da_SANGER_10_FBgn0000413-Fer1-da 2 0.0818426 2001.3 1 6 CACCTG AACACCTGTCA + +4 predrem__nrMotif311 5 0.0818426 2001.3 1 6 CACCTG ACCACCACCAC + +4 cisbp__M5087-lola 5 0.0818426 2001.3 1 6 CACCTG GAACCTACTTT - +4 taipale__ESRRB_DBD_TCAAGGTCAWN-ERR-ftz-f1-Hr39 3 0.0818426 2001.3 1 6 CACCTG TATGACCTTGA - +4 transfac_pro__M06698 6 0.0818426 2001.3 1 5 CACCTG ATTTCGCACCG - +4 cisbp__M1558 1 0.0825084 2017.58 1 6 CACCTG GTACGTCA + +4 cisbp__M1809 0 0.0825084 2017.58 1 6 CACCTG CTCCGGAC + +4 predrem__nrMotif1376 2 0.0825084 2017.58 1 6 CACCTG AACACCCA + +4 predrem__nrMotif2285 0 0.0825084 2017.58 1 6 CACCTG TGCCTAAA + +4 jaspar__MA0128.1 1 0.0825084 2017.58 1 6 CACCTG CCACGTGT - +4 fantom__motif66_ACCGRTCA -1 0.0825084 2017.58 1 5 CACCTG ACCGATCA + +4 neph__UW.Motif.0373 -2 0.0825084 2017.58 1 4 CACCTG CCTTGAAC + +4 predrem__nrMotif1227 -2 0.0825084 2017.58 1 4 CACCTG CCTTGGGA + +4 cisbp__M5797-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0826366 2020.71 1 6 CACCTG TGACCTTTGACCCC + +4 cisbp__M5800-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0826366 2020.71 1 6 CACCTG TGACCTTTGACCCC + +4 neph__UW.Motif.0421 7 0.0826366 2020.71 1 6 CACCTG TGCGCAGCTGCTGC - +4 taipale__RXRA_full_GGGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0826366 2020.71 1 6 CACCTG TGACCTTTGACCCC - +4 taipale__RXRG_DBD_GGGGTCAAAGGTCA-btd-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 1 0.0826366 2020.71 1 6 CACCTG TGACCTTTGACCCC - +4 taipale_tf_pairs__GCM2_PITX1_RTRCGGGNNGATTA_CAP_repr-gcm-gcm2-Ptx1 5 0.0826366 2020.71 1 6 CACCTG TAATCCACCCGCAT - +4 cisbp__M1813 2 0.0828477 2025.88 1 6 CACCTG AACGCCGGT + +4 predrem__nrMotif1999 3 0.0828477 2025.88 1 6 CACCTG TGTCACCAA + +4 predrem__nrMotif2226 1 0.0828477 2025.88 1 6 CACCTG TTAACTGCA + +4 transfac_pro__M00700 2 0.0828477 2025.88 1 6 CACCTG GCCACCTCA + +4 cisbp__M4149-ci-lmd-opa-sug 3 0.0828477 2025.88 1 6 CACCTG GACCACCCA - +4 cisbp__M4753-ato-da 1 0.0828477 2025.88 1 6 CACCTG CCACCTGCC - +4 cisbp__M5094-lola 0 0.0828477 2025.88 1 6 CACCTG AACCCTAAC - +4 hocomoco__ETV6_HUMAN.H11MO.0.D-Ets21C-Ets65A-Ets96B-Ets97D-aop-pnt 2 0.0828477 2025.88 1 6 CACCTG ACTTCCTGT - +4 predrem__nrMotif1589 3 0.0828477 2025.88 1 6 CACCTG AGACACCAA - +4 predrem__nrMotif917 0 0.0828477 2025.88 1 6 CACCTG AACCTGGCA - +4 transfac_public__M00448-opa 3 0.0828477 2025.88 1 6 CACCTG GACCACCCA - +4 transfac_public__M00450-ci-lmd-opa-sug 3 0.0828477 2025.88 1 6 CACCTG GACCACCCA - +4 predrem__nrMotif824 4 0.0828477 2025.88 1 5 CACCTG TTTGCAGCT + +4 cisbp__M1343 -1 0.0828477 2025.88 1 5 CACCTG ACCTAACTT - +4 transfac_pro__M05176 4 0.0828477 2025.88 1 5 CACCTG TCGACCCCT - +4 predrem__nrMotif1418 5 0.0828477 2025.88 1 4 CACCTG AAAATCACC + +4 predrem__nrMotif1695 -2 0.0828477 2025.88 1 4 CACCTG CCTCTGACC + +4 predrem__nrMotif1975 5 0.0828477 2025.88 1 4 CACCTG CCTCACACC + +4 predrem__nrMotif236 5 0.0828477 2025.88 1 4 CACCTG TTCTCCACC + +4 predrem__nrMotif589 5 0.0828477 2025.88 1 4 CACCTG ACCAACACC + +4 predrem__nrMotif1166 5 0.0828477 2025.88 1 4 CACCTG CTGAGCACC - +4 predrem__nrMotif2087 5 0.0828477 2025.88 1 4 CACCTG AGAATCACC - +4 predrem__nrMotif2504 5 0.0828477 2025.88 1 4 CACCTG CCCGGCACC - +4 predrem__nrMotif900 5 0.0828477 2025.88 1 4 CACCTG TGCCACACC - +4 predrem__nrMotif384 0 0.0834823 2041.39 1 6 CACCTG CACATCT - +4 predrem__nrMotif479 2 0.0834823 2041.39 1 5 CACCTG AATTCCT + +4 predrem__nrMotif518 2 0.0834823 2041.39 1 5 CACCTG TTCACTT - +4 tfdimers__MD00455 13 0.0835024 2041.89 1 6 CACCTG CCCCCCTCCCCACTTCCTGCCCC - +4 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 14 0.0837886 2048.88 1 6 CACCTG TATCGATCGGATGTTGCCTGAGGCGA + +4 cisbp__M4442-CTCF-SMC3-usp-vtd 5 0.0846115 2069 1 6 CACCTG GGCGCCCCCTGGTGG - +4 taipale_cyt_meth__HNF4A_NRGTCCAAAGGTCRN_eDBD-EcR-eg-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 2 0.0846115 2069 1 6 CACCTG GTGACCTTTGGACCC - +4 transfac_pro__M02940-opa 1 0.0846115 2069 1 6 CACCTG TCTCCTGCTGTGTGG - +4 transfac_pro__M08957-EcR-Hr78-svp-usp 9 0.0846115 2069 1 6 CACCTG GGGGTCAATGACCTC - +4 jaspar__MA0258.2-ERR-EcR-eg-kni-knrl 10 0.0846115 2069 1 5 CACCTG AGGTCAGGGTGACCT - +4 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNNNNNYWTTGTNN_CAP_repr-gcm-gcm2 13 0.0848368 2074.52 1 6 CACCTG AAACAATAAAATATACCCGCAT - +4 transfac_pro__M02088-sc 3 0.0850766 2080.38 1 6 CACCTG GGACACCTGCCGG + +4 cisbp__M4659-CTCF-SMC3-usp-vtd 3 0.0850766 2080.38 1 6 CACCTG CGCCCCCTGGTGG - +4 cisbp__M0839 2 0.0857421 2096.65 1 6 CACCTG TTTACATGAT + +4 cisbp__M1277 2 0.0857421 2096.65 1 6 CACCTG TTAACCAGAG + +4 cisbp__M2462 3 0.0857421 2096.65 1 6 CACCTG TTTTACATGA + +4 scertf__spivak.TYE7-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.0857421 2096.65 1 6 CACCTG ATCACGTGAC + +4 transfac_pro__M07391-bap-scro-vnd 3 0.0857421 2096.65 1 6 CACCTG AACCACTTAA + +4 hocomoco__RXRG_MOUSE.H11MO.1.B-EcR-usp 4 0.0857421 2096.65 1 6 CACCTG CCTTGACCTC - +4 homer__CAAAGGTCAG_Erra-ERR-EcR-HDAC1-Hnf4-Hr38-Hr78-eg-kni-knrl-svp-usp 2 0.0857421 2096.65 1 6 CACCTG CTGACCTTTG - +4 transfac_pro__M00432-scro 1 0.0857421 2096.65 1 6 CACCTG ACACTTGAGT - +4 transfac_pro__M01584 3 0.0857421 2096.65 1 6 CACCTG CGCCACGTCA - +4 transfac_public__M00485-bap-scro-vnd 3 0.0857421 2096.65 1 6 CACCTG AACCACTTAA - +4 predrem__nrMotif356 -1 0.0857421 2096.65 1 5 CACCTG CCCTGCCCTG + +4 cisbp__M4655-btd-CTCF-HDAC1-Sin3A-Spps 5 0.0859141 2100.86 1 6 CACCTG TTCAGCACCATGGACAGCGCC - +4 transfac_pro__M01373-abd-A-Abd-B-cad-eve-Ubx 9 0.0859925 2102.77 1 6 CACCTG TAATTTTATTACCTTA - +4 transfac_pro__M02781-nau 4 0.0859925 2102.77 1 6 CACCTG CGGACACCTGTTCTTC - +4 cisbp__M6454-Eip75B-Hr3 1 0.0865692 2116.88 1 6 CACCTG TGACCTAGTTTT + +4 hocomoco__GRHL1_HUMAN.H11MO.0.D-grh 0 0.0865692 2116.88 1 6 CACCTG AACCTGTTTTTC + +4 taipale_cyt_meth__ZNF524_NYTCGNACCCRN_FL_meth 5 0.0865692 2116.88 1 6 CACCTG CCTCGAACCCGC + +4 transfac_pro__M00964-EcR-usp 6 0.0865692 2116.88 1 6 CACCTG GTTATTAACCCT - +4 transfac_pro__M05829 6 0.0865692 2116.88 1 6 CACCTG CCTTATGACCTT - +4 transfac_pro__M06714 -1 0.0865692 2116.88 1 5 CACCTG TCCTAAGTCAGA + +4 transfac_pro__M05967 7 0.0865692 2116.88 1 5 CACCTG TTTGGTATACCC - +4 transfac_pro__M06016 7 0.0865692 2116.88 1 5 CACCTG TATTCCACACCC - +4 transfac_pro__M06123-CG10321-CG8089 7 0.0865692 2116.88 1 5 CACCTG TCCCCTTAACCA - +4 transfac_pro__M06130 7 0.0865692 2116.88 1 5 CACCTG GCCTTAGAACCA - +4 transfac_pro__M06325 7 0.0865692 2116.88 1 5 CACCTG GATTTTAAACAT - +4 transfac_pro__M06547 7 0.0865692 2116.88 1 5 CACCTG GCTGCCCCACCA - +4 transfac_pro__M06654 7 0.0865692 2116.88 1 5 CACCTG TCGTCCCCACCA - +4 dbcorrdb__CTCF__ENCSR000DUU_1__m3-CTCF-SMC3-usp-vtd 6 0.0866959 2119.98 1 6 CACCTG GGGGGCCCCCTAGCGGCAAC + +4 dbcorrdb__NR2F2__ENCSR000BRS_1__m2-EcR-eg-ERR-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 9 0.0866959 2119.98 1 6 CACCTG TTGCCCTCTGACCTTTGACC - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BPL_1__m2-CTCF-SMC3-usp-vtd 8 0.0866959 2119.98 1 6 CACCTG TTCAGCGCCCCCTTGCGGCA - +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m3 10 0.0866959 2119.98 1 6 CACCTG AATGTTATAAAACCTTTTAC - +4 hocomoco__RARA_MOUSE.H11MO.0.A-ERR-EcR-Hr4-svp-usp 1 0.0866959 2119.98 1 6 CACCTG TGACCTTGAACTTCTGACCC - +4 hocomoco__ZN134_HUMAN.H11MO.1.C 4 0.0868386 2123.46 1 6 CACCTG CCTTCACCTGATTAGGT + +4 transfac_pro__M08980-EcR-usp 11 0.0868386 2123.46 1 6 CACCTG GTGAACCTGGTGACCTG - +4 cisbp__M2311-EcR-eg-ERR-Hnf4-Hr78-kni-knrl-svp-usp 3 0.0868807 2124.49 1 6 CACCTG TCTGACCTTTG + +4 cisbp__M4965-da-Fer1 2 0.0868807 2124.49 1 6 CACCTG AACACCTGTCA - +4 hocomoco__TGIF2_HUMAN.H11MO.0.D-achi-hth-nau-vis 1 0.0868807 2124.49 1 6 CACCTG ACAGCTGTCAT - +4 hocomoco__NR1H2_HUMAN.H11MO.0.D-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-svp-usp 11 0.0871409 2130.86 1 6 CACCTG CGTTGACCTTTGACCTTTA - +4 yetfasco__YMR016C_404 0 0.0873957 2137.09 1 6 CACCTG TTCCTGCA + +4 cisbp__M0554 0 0.0873957 2137.09 1 6 CACCTG CACCGCAC - +4 cisbp__M1948 1 0.0873957 2137.09 1 6 CACCTG CCACGTGT - +4 scertf__morozov.PHO4-E2f1-Max-Myc 1 0.0873957 2137.09 1 6 CACCTG CCACGTGC - +4 transfac_pro__M03867-Max-Myc 2 0.0873957 2137.09 1 6 CACCTG GCCACGTG - +4 yetfasco__YOL028C_1414 1 0.0873957 2137.09 1 6 CACCTG TTACGTAA - +4 cisbp__M1435-EcR-Hr3-Hr78 3 0.0873957 2137.09 1 5 CACCTG GGTGACCT + +4 cisbp__M1497-EcR-Hr78 3 0.0873957 2137.09 1 5 CACCTG CGTGACCT + +4 transfac_pro__M01678 -1 0.0873957 2137.09 1 5 CACCTG AACTGTGG + +4 transfac_pro__M01686 -1 0.0873957 2137.09 1 5 CACCTG ACTTGAAT + +4 cisbp__M0681 3 0.0878143 2147.32 1 6 CACCTG ATGTATCTA + +4 predrem__nrMotif1223 1 0.0878143 2147.32 1 6 CACCTG AAACCTTCC + +4 predrem__nrMotif502 3 0.0878143 2147.32 1 6 CACCTG TCCCACTTG + +4 predrem__nrMotif942 1 0.0878143 2147.32 1 6 CACCTG GGACCTGCC + +4 transfac_pro__M08919-gcm-gcm2 0 0.0878143 2147.32 1 6 CACCTG TACCCGCAT + +4 predrem__nrMotif1754 2 0.0878143 2147.32 1 6 CACCTG AGTAACTGC - +4 predrem__nrMotif835 0 0.0878143 2147.32 1 6 CACCTG TCCCTGTGT - +4 yetfasco__YMR070W_2080 2 0.0878143 2147.32 1 6 CACCTG CGTGCCTGC - +4 jaspar__MA1037.1 -1 0.0878143 2147.32 1 5 CACCTG ACCTAACTT - +4 taipale_cyt_meth__RARA_NRGGTCRTGACCYN_eDBD-EcR-eg-Hr3-Hr78-kni-knrl-usp 8 0.0879029 2149.49 1 6 CACCTG GAGGTCATGACCTT + +4 neph__UW.Motif.0413 5 0.0879029 2149.49 1 6 CACCTG TGTTTTTCCTGTCT - +4 taipale__RXRB_DBD_GGGGTCAAAGGTCA-EcR-eg-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 1 0.0879029 2149.49 1 6 CACCTG TGACCTTTGACCCC - +4 taipale_cyt_meth__RXRB_NRGGTCRTGACCYN_eDBD-EcR-eg-Hr78-kni-knrl-usp 8 0.0879029 2149.49 1 6 CACCTG GAGGTCATGACCTC - +4 yetfasco__YDR174W_2249 3 0.0879029 2149.49 1 6 CACCTG TTCTGCCTAGAGAA - +4 hocomoco__PRRX1_HUMAN.H11MO.0.D 1 0.0882628 2158.29 1 6 CACCTG TAACCTG + +4 predrem__nrMotif1563 1 0.0882628 2158.29 1 6 CACCTG GAATCTG + +4 flyfactorsurvey__Met_SANGER_5_FBgn0002723-Clk-Max-Met-Myc-cyc 1 0.0882628 2158.29 1 6 CACCTG CCACGTG - +4 predrem__nrMotif718 2 0.0882628 2158.29 1 5 CACCTG AGCACAT + +4 predrem__nrMotif1761 -1 0.0882628 2158.29 1 5 CACCTG GCCTAGG - +4 predrem__nrMotif1992 2 0.0882628 2158.29 1 5 CACCTG CACACTT - +4 transfac_pro__M04844-Max -1 0.0882628 2158.29 1 5 CACCTG ACGTGTT - +4 predrem__nrMotif187 -2 0.0882628 2158.29 1 4 CACCTG CCTCAAA - +4 cisbp__M1839-tgo 0 0.0885078 2164.28 1 6 CACCTG CACGTG - +4 jaspar__MA0004.1-tgo 0 0.0885078 2164.28 1 6 CACCTG CACGTG - +4 transfac_pro__M01743-Ing5 1 0.0885078 2164.28 1 5 CACCTG CCACCA + +4 hdpi__CREB1-CrebB 1 0.0885078 2164.28 1 5 CACCTG TGACGT - +4 cisbp__M6126-EcR-ERR-ftz-f1-Hr4 4 0.0900364 2201.66 1 6 CACCTG GGGTGACCTTGACCT + +4 transfac_pro__M02821-TfAP-2 2 0.0900364 2201.66 1 6 CACCTG ATTGCCTGAGGCGAA + +4 transfac_pro__M02822-GATAe-grn-pnr-TfAP-2 2 0.0900364 2201.66 1 6 CACCTG ATTGCCTGAGGCGAT + +4 cisbp__M4575-CG9727-Rfx 2 0.0900364 2201.66 1 6 CACCTG TCTGCCTAGCAACAG - +4 taipale_cyt_meth__HNF4A_NRGTCCAAAGGTCRN_eDBD_meth_repr-EcR-eg-Hnf4-Hr38-Hr78-kni-knrl-svp-usp 2 0.0900364 2201.66 1 6 CACCTG GTGACCTTTGGACCC - +4 cisbp__M5679-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 5 0.0904047 2210.67 1 6 CACCTG CCCTTGACCTTTG + +4 taipale_tf_pairs__ETV5_FOXO1_RTMAACAGGAWRN_CAP-Ets96B-foxo 2 0.0904047 2210.67 1 6 CACCTG ACTTCCTGTTTAC - +4 hocomoco__ZN134_HUMAN.H11MO.0.C 4 0.0905988 2215.41 1 6 CACCTG CCTTCAACTGATTAGGTGAGGC - +4 cisbp__M1294 2 0.0909072 2222.95 1 6 CACCTG TTAACCAGAG + +4 cisbp__M3631-bap-scro-vnd 3 0.0909072 2222.95 1 6 CACCTG AACCACTTAA + +4 cisbp__M4597-cnc-Mitf-SREBP-tgo-Usf 3 0.0909072 2222.95 1 6 CACCTG GGTGACGTGA + +4 flyfactorsurvey__Hr39_SANGER_5_FBgn0010229-ERR-Hr39-ftz-f1 2 0.0909072 2222.95 1 6 CACCTG ATGACCTTGA + +4 neph__UW.Motif.0110 4 0.0909072 2222.95 1 6 CACCTG AAATGCCCTG + +4 predrem__nrMotif1083 4 0.0909072 2222.95 1 6 CACCTG GTGGTCCCTG + +4 predrem__nrMotif910 2 0.0909072 2222.95 1 6 CACCTG GGCGCCTGGG + +4 transfac_pro__M01119 0 0.0909072 2222.95 1 6 CACCTG TTCCTGCTAA + +4 yetfasco__YLR013W_2128 3 0.0909072 2222.95 1 6 CACCTG TCGGATCTAC + +4 cisbp__M0985-ara-caup-mirr 2 0.0909072 2222.95 1 6 CACCTG ATTACATGAT - +4 predrem__nrMotif2428 1 0.0909072 2222.95 1 6 CACCTG GCACCAGCGG - +4 transfac_pro__M01799 2 0.0909072 2222.95 1 6 CACCTG GCCACATGCG - +4 swissregulon__sacCer__AFT1 5 0.0909072 2222.95 1 5 CACCTG TATTGCACCC + +4 neph__UW.Motif.0380 8 0.0915443 2238.53 1 6 CACCTG AATTTTGTAATTTTTG + +4 neph__UW.Motif.0612 1 0.0915443 2238.53 1 6 CACCTG AGGCCAGAGGAAGGAA + +4 taipale_cyt_meth__PPARD_NRRGGTCRTGACCYYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-svp-usp 9 0.0915443 2238.53 1 6 CACCTG AGAGGTCGTGACCTCT + +4 taipale_tf_pairs__GCM1_ELF1_NRCCCRNNCGGAAGNN_CAP_repr-Eip74EF-gcm-gcm2 0 0.0915443 2238.53 1 6 CACCTG CACCCGCACGGAAGTG + +4 transfac_pro__M03133-nau 4 0.0915443 2238.53 1 6 CACCTG TTAACACCTGTCAATA + +4 cisbp__M2555-grh 6 0.0915443 2238.53 1 6 CACCTG ATACAAAACCATAACA - +4 jaspar__MA0383.1-Mef2 1 0.0916989 2242.31 1 6 CACCTG TTACCTATAATTAAATTAGCA + +4 yetfasco__YBR182C_864-Mef2 1 0.0916989 2242.31 1 6 CACCTG TTACCTATAATTAAATTAGCA - +4 transfac_pro__M05710 16 0.0916989 2242.31 1 5 CACCTG AGCCTTCGGCAGACTGTACCA - +4 taipale_cyt_meth__DMRT1_NNTYGNWACATN_FL_meth-dmrt93B-dsx 6 0.0919069 2247.4 1 6 CACCTG AATTGCTACATT + +4 cisbp__M6358 3 0.0919069 2247.4 1 6 CACCTG GGCCATCTGCCG - +4 hocomoco__NR2C2_HUMAN.H11MO.0.B-Hr78 1 0.0919069 2247.4 1 6 CACCTG TGACCCGGAACC - +4 neph__UW.Motif.0067 6 0.0919069 2247.4 1 6 CACCTG CTCAGCCTCCTG - +4 neph__UW.Motif.0170 6 0.0919069 2247.4 1 6 CACCTG TTTCCTTTTCTG - +4 transfac_pro__M05516 6 0.0919069 2247.4 1 6 CACCTG GAAGCCTGCCTA - +4 transfac_pro__M05639 6 0.0919069 2247.4 1 6 CACCTG TATGCCCACCAA - +4 transfac_pro__M06295 6 0.0919069 2247.4 1 6 CACCTG TACCATAACCAG - +4 transfac_pro__M07955-Eip75B-Hr3 3 0.0919069 2247.4 1 6 CACCTG CTTGACCTACAT - +4 transfac_pro__M08961-eg-Eip75B-Hr3-kni-knrl 3 0.0919069 2247.4 1 6 CACCTG AGTGACCTACTT - +4 homer__AGGTCAAGGTCA_RARg-ERR-EcR-Hr4-usp 7 0.0919069 2247.4 1 5 CACCTG TGACCTTGACCT - +4 transfac_pro__M05754-CG10321-CG8089 7 0.0919069 2247.4 1 5 CACCTG TCCCCTTAACCA - +4 transfac_pro__M06118-crol 7 0.0919069 2247.4 1 5 CACCTG TAACCTTTACCA - +4 transfac_pro__M06529 7 0.0919069 2247.4 1 5 CACCTG TTTTCCCGACCT - +4 neph__UW.Motif.0169 -2 0.0919069 2247.4 1 4 CACCTG CCTGGGGCTGGG - +4 cisbp__M5410-ERR-ftz-f1-Hr39 3 0.0921666 2253.75 1 6 CACCTG TATGACCTTGA + +4 flyfactorsurvey__ato_da_SANGER_10_FBgn0000413-ato-da 1 0.0921666 2253.75 1 6 CACCTG CCACCTGTCAC + +4 flyfactorsurvey__chinmo_SOLEXA_FBgn0086758-chinmo 4 0.0921666 2253.75 1 6 CACCTG GATGCACTTCG + +4 flyfactorsurvey__CG31782-F9-11_SOLEXA_FBgn0051782-CR43670 2 0.0921666 2253.75 1 6 CACCTG CTCACCACCAA - +4 hocomoco__ETV4_HUMAN.H11MO.0.B-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-aop-bs-grn-pnr-pnt 3 0.0921666 2253.75 1 6 CACCTG CCCTTCCTGTT - +4 taipale_cyt_meth__NR5A1_NYCAAGGTCAN_FL-ERR-ftz-f1-Hr39-Hr4 2 0.0921666 2253.75 1 6 CACCTG GTGACCTTGAC - +4 transfac_pro__M00773 0 0.0921666 2253.75 1 6 CACCTG CAACTGGCCCT - +4 transfac_pro__M07125-EcR-eg-ERR-Hnf4-Hr78-kni-knrl-svp-usp 3 0.0921666 2253.75 1 6 CACCTG TCTGACCTTTG - +4 tiffin__TIFDMEM0000055 6 0.0921666 2253.75 1 5 CACCTG TATTTATATCT + +4 dbcorrdb__MYBL2__ENCSR000BRO_1__m3-Hnf4 3 0.0924826 2261.48 1 6 CACCTG GTTGACCTTTGAGCTACGGG + +4 dbcorrdb__SIN3A__ENCSR000EBO_1__m2-CrebB-Sin3A 6 0.0924826 2261.48 1 6 CACCTG TGCCGTCACCAGGGCGCCGC - +4 dbcorrdb__REST__ENCSR000BOT_1__m2-CTCF 16 0.0924826 2261.48 1 4 CACCTG GGGGCGGCGGCTTCAGCACC - +4 cisbp__M4683-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf 2 0.0925029 2261.97 1 6 CACCTG GTCACGTG + +4 flyfactorsurvey__br-Z3_FlyReg_FBgn0000210-br 0 0.0925029 2261.97 1 6 CACCTG AAACTAGT + +4 hdpi__MEIS3-achi-nau-vis 2 0.0925029 2261.97 1 6 CACCTG GACAGCTG + +4 homer__RTACGTGC_HIF-1b-tgo 1 0.0925029 2261.97 1 6 CACCTG ATACGTGC + +4 cisbp__M0513-CG10348-CG13296-ham 1 0.0925029 2261.97 1 6 CACCTG CCCCCTAT - +4 cisbp__M4778-br 0 0.0925029 2261.97 1 6 CACCTG AAACTAGT - +4 scertf__harbison.SOK2 0 0.0925029 2261.97 1 6 CACCTG TTCCTGCA - +4 predrem__nrMotif2141 -1 0.0925029 2261.97 1 5 CACCTG ACATGATG + +4 predrem__nrMotif2646 -1 0.0925029 2261.97 1 5 CACCTG ACTTAATG + +4 hocomoco__NR1H4_HUMAN.H11MO.1.B-EcR 3 0.0925029 2261.97 1 5 CACCTG ACTGACCT - +4 predrem__nrMotif1548 -1 0.0925029 2261.97 1 5 CACCTG AACTTGAG - +4 neph__UW.Motif.0044-srp -2 0.0925029 2261.97 1 4 CACCTG CCTTATCT - +4 taipale_cyt_meth__ZNF580_CCTACCCTNNCCTACCCT_eDBD_meth 8 0.0929247 2272.29 1 6 CACCTG CCTACCCTCGCCTACCCT + +4 predrem__nrMotif2123 2 0.0930259 2274.76 1 6 CACCTG AATATCTTC + +4 cisbp__M0255-Atf6-CrebA-Met 2 0.0930259 2274.76 1 6 CACCTG GCCACGTGG - +4 cisbp__M1369 1 0.0930259 2274.76 1 6 CACCTG GTATCCTAA - +4 jaspar__MA0968.1-Atf6-CrebA-Met 2 0.0930259 2274.76 1 6 CACCTG GCCACGTGG - +4 predrem__nrMotif2387 0 0.0930259 2274.76 1 6 CACCTG CTCCTGCGG - +4 predrem__nrMotif2171 4 0.0930259 2274.76 1 5 CACCTG TTCTTACCA - +4 predrem__nrMotif2396 4 0.0930259 2274.76 1 5 CACCTG GTGCCACCT - +4 predrem__nrMotif2030 -2 0.0930259 2274.76 1 4 CACCTG CCTGCCGCC + +4 predrem__nrMotif275 -2 0.0930259 2274.76 1 4 CACCTG CCTGACATG + +4 predrem__nrMotif1273 -2 0.0930259 2274.76 1 4 CACCTG CCTGACTCT - +4 predrem__nrMotif574 -2 0.0930259 2274.76 1 4 CACCTG CCTGTCCAC - +4 predrem__nrMotif957 -2 0.0930259 2274.76 1 4 CACCTG CCTGGATCC - +4 predrem__nrMotif2224 0 0.0932551 2280.37 1 6 CACCTG CCCCTTA + +4 transfac_pro__M00799-Max-Myc 0 0.0932551 2280.37 1 6 CACCTG CACGTGG + +4 cisbp__M6350 1 0.0932551 2280.37 1 6 CACCTG CCAACTG - +4 hocomoco__ETV7_HUMAN.H11MO.0.D-Ets96B-Ets97D-aop 1 0.0932551 2280.37 1 6 CACCTG CTTCCTG - +4 transfac_pro__M04859-SMC3 2 0.0932551 2280.37 1 5 CACCTG GCCACCA + +4 tfdimers__MD00179-eg-kni-knrl 17 0.0934146 2284.27 1 6 CACCTG CCCCCCTGACCTCACCTGACCTCTCCC - +4 cisbp__M4520-CTCF-SMC3-usp-vtd 3 0.093434 2284.74 1 6 CACCTG CGCCCCCTGGTGGC - +4 transfac_pro__M03802-ftz-f1-svp 5 0.093434 2284.74 1 6 CACCTG TCCCTGACCTTGAC - +4 transfac_pro__M04708-CTCF-SMC3-usp-vtd 3 0.093434 2284.74 1 6 CACCTG CGCCCCCTGGTGGC - +4 fantom__motif34_GANCCT 1 0.0935121 2286.65 1 5 CACCTG GAACCT + +4 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 11 0.0952595 2329.38 1 6 CACCTG AATCGATACTTAGCCTGAGGCGG + +4 neph__UW.Motif.0447 8 0.0957345 2341 1 6 CACCTG AATGCCATCTCCATG + +4 transfac_pro__M02893 1 0.0957345 2341 1 6 CACCTG TACCCTAGTTACCGA + +4 transfac_pro__M09290 8 0.0957345 2341 1 6 CACCTG TTCCCAACCACCAAC + +4 cisbp__M4612-CTCF-SMC3-usp-vtd 5 0.0957345 2341 1 6 CACCTG GGCGCCCCCTGGCGG - +4 cisbp__M4644-CTCF-SMC3-usp-vtd 4 0.0957345 2341 1 6 CACCTG GCGCCCCCTGGTGGC - +4 neph__UW.Motif.0051 1 0.0957345 2341 1 6 CACCTG CTTCCTGCCACCCTG - +4 taipale_cyt_meth__HNF4A_NRGGTCAAAGGTCAN_eDBD-EcR-eg-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 2 0.0957345 2341 1 6 CACCTG TTGACCTTTGACCCC - +4 cisbp__M4667-btd-CTCF-HDAC1-Sin3A-Spps -1 0.0957345 2341 1 5 CACCTG ACCATGGACAGCGCC + +4 cisbp__M6210-Myc 4 0.0959966 2347.41 1 6 CACCTG TGCCCACGTGGTG + +4 cisbp__M4584-CTCF-SMC3-usp-vtd 3 0.0959966 2347.41 1 6 CACCTG CGCCCCCTGGTGG - +4 taipale__NR2F1_DBD_DNNNGGTCANNNH_repr-EcR-eg-Hr78-kni-knrl-svp-usp 5 0.0959966 2347.41 1 6 CACCTG CCCTTGACCTTTG - +4 transfac_pro__M08955-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 7 0.0959966 2347.41 1 6 CACCTG GACCTTTGACCCC - +4 cisbp__M0250 2 0.0963255 2355.45 1 6 CACCTG CGCACGTGCG + +4 cisbp__M1436-EcR-Hr78-svp-usp 3 0.0963255 2355.45 1 6 CACCTG GGTGACCTCT + +4 taipale_cyt_meth__NKX2-5_NCCACTTRAN_FL_repr-scro-tin-vnd 2 0.0963255 2355.45 1 6 CACCTG ACCACTTGAG + +4 transfac_pro__M00371-CrebA-cyc-Usf 2 0.0963255 2355.45 1 6 CACCTG GCCACGTGAC + +4 transfac_pro__M00945-Max-Myc-SREBP-Usf 2 0.0963255 2355.45 1 6 CACCTG GCCACGTGAT + +4 cisbp__M1395 4 0.0963255 2355.45 1 6 CACCTG ACCTTATCCA - +4 transfac_pro__M07505 4 0.0963255 2355.45 1 6 CACCTG AGCGTATCTT - +4 yetfasco__YLR451W_2135 2 0.0963255 2355.45 1 6 CACCTG AACGCCGGTA - +4 transfac_pro__M02763 8 0.0973766 2381.15 1 6 CACCTG ACTATGCCAACCTACC + +4 cisbp__M5686-Hr38 1 0.0973766 2381.15 1 6 CACCTG TGACCTTTAAAGGTCA - +4 neph__UW.Motif.0375 7 0.0973766 2381.15 1 6 CACCTG TGACAGTCCCCCGGGG - +4 transfac_pro__M02895-usp 5 0.0973766 2381.15 1 6 CACCTG AGTACAACCTTCGCGA - +4 cisbp__M4897-Atf6-CrebA-Xbp1 3 0.0975053 2384.3 1 6 CACCTG GATTACGTGGCA + +4 taipale_cyt_meth__DMRTC2_WWTTGNTACATN_FL_meth-dmrt11E-dmrt93B-dsx 6 0.0975053 2384.3 1 6 CACCTG AATTGATACATT + +4 transfac_pro__M06481 0 0.0975053 2384.3 1 6 CACCTG AAACTGATGACA + +4 transfac_pro__M08870 3 0.0975053 2384.3 1 6 CACCTG CCGCACGTGACC + +4 cisbp__M1666 0 0.0975053 2384.3 1 6 CACCTG TACCGGCGGGAT - +4 flyfactorsurvey__CrebA_SANGER_5_FBgn0004396-Atf6-CrebA-Xbp1 3 0.0975053 2384.3 1 6 CACCTG GATTACGTGGCA - +4 transfac_pro__M05975 6 0.0975053 2384.3 1 6 CACCTG TGGTTTTACCCG - +4 transfac_pro__M06897 6 0.0975053 2384.3 1 6 CACCTG GCTGCAAACCCG - +4 transfac_pro__M05441 7 0.0975053 2384.3 1 5 CACCTG TCTTCCTCACCA - +4 transfac_pro__M06129-CG6654-CG7372 7 0.0975053 2384.3 1 5 CACCTG GTTTTCTCACCA - +4 transfac_pro__M06414 7 0.0975053 2384.3 1 5 CACCTG AATGCCTTACCC - +4 transfac_pro__M06538 7 0.0975053 2384.3 1 5 CACCTG AATTTTTTACCA - +4 transfac_pro__M06552 7 0.0975053 2384.3 1 5 CACCTG TCCTACTTACCA - +4 cisbp__M5925-TfAP-2 0 0.0977093 2389.29 1 6 CACCTG TGCCTGAGGCT + +4 taipale__TFAP2C_full_NSCCNNNGGSN-TfAP-2 0 0.0977093 2389.29 1 6 CACCTG AGCCTCAGGCA + +4 cisbp__M4749-ato-da 1 0.0977093 2389.29 1 6 CACCTG CCACCTGTCAC - +4 taipale_cyt_meth__NR5A1_NYCAAGGTCAN_FL_meth-ERR-ftz-f1-Hr39 2 0.0977093 2389.29 1 6 CACCTG GTGACCTTGAC - +4 transfac_pro__M02098-EcR-ERR-ftz-f1-Hr4-usp 1 0.0977093 2389.29 1 6 CACCTG TGACCTTGAAC - +4 transfac_pro__M09166 0 0.0977093 2389.29 1 6 CACCTG TAACTGAAAGT - +4 factorbook__UA9-CG9650-opa -1 0.0977093 2389.29 1 5 CACCTG TCCTGCTGTGC - +4 swissregulon__hs__EN1_2.p2-en-inv 6 0.0977093 2389.29 1 5 CACCTG GAACACTACTT - +4 predrem__nrMotif1817 1 0.097826 2392.14 1 6 CACCTG GCACCGGG + +4 scertf__spivak.NRG1 2 0.097826 2392.14 1 6 CACCTG GGACCCTG + +4 predrem__nrMotif2061 0 0.097826 2392.14 1 6 CACCTG TACATACA - +4 cisbp__M2140 -1 0.097826 2392.14 1 5 CACCTG AACTGTGG + +4 jaspar__MA0274.1 -1 0.097826 2392.14 1 5 CACCTG ACTTGAAT + +4 jaspar__MA0335.1 -1 0.097826 2392.14 1 5 CACCTG AACTGTGG + +4 transfac_pro__M01814-lz-run-RunxA-RunxB 3 0.097826 2392.14 1 5 CACCTG CCACACCA + +4 hdpi__SSBP3-Ssdp -1 0.097826 2392.14 1 5 CACCTG ACATTTCC - +4 elemento__CCTGCCTC -2 0.097826 2392.14 1 4 CACCTG CCTGCCTC + +4 elemento__CCTGTTGC -2 0.097826 2392.14 1 4 CACCTG CCTGTTGC + +4 elemento__CCAGCAGG -2 0.097826 2392.14 1 4 CACCTG CCTGCTGG - +4 taipale_tf_pairs__TFAP2C_DRGX_SCCNNNGGCNNYAATTA_CAP_repr-CG11294-Drgx-TfAP-2 7 0.0984246 2406.78 1 6 CACCTG TAATTGTTGCCTCAGGG - +4 predrem__nrMotif2163 0 0.0984747 2408 1 6 CACCTG TACATGA + +4 transfac_pro__M01822-luna 0 0.0984747 2408 1 6 CACCTG GCCCCTT + +4 transfac_pro__M07252-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 1 0.0984747 2408 1 6 CACCTG CTTCCTG + +4 predrem__nrMotif638 0 0.0984747 2408 1 6 CACCTG CAACTTT - +4 transfac_pro__M02099-Mitf 1 0.0984747 2408 1 6 CACCTG TCACATG - +4 fantom__motif102_GCAAMGT -1 0.0984747 2408 1 5 CACCTG ACGTTGC - +4 predrem__nrMotif1867 2 0.0984747 2408 1 5 CACCTG ATTACTT - +4 cisbp__M0162 2 0.0984876 2408.32 1 6 CACCTG CCCACGTGC + +4 cisbp__M1379 2 0.0984876 2408.32 1 6 CACCTG TAAACCCTT + +4 jaspar__MA1061.1 2 0.0984876 2408.32 1 6 CACCTG CCCACGTGC + +4 predrem__nrMotif1398 0 0.0984876 2408.32 1 6 CACCTG CAGCTGCCG + +4 predrem__nrMotif1748 3 0.0984876 2408.32 1 6 CACCTG GTTCACATT + +4 predrem__nrMotif207 2 0.0984876 2408.32 1 6 CACCTG TGTATCTTT + +4 predrem__nrMotif2530 0 0.0984876 2408.32 1 6 CACCTG CCCCTAGTG + +4 predrem__nrMotif416 2 0.0984876 2408.32 1 6 CACCTG CAAACCTCC + +4 predrem__nrMotif776 1 0.0984876 2408.32 1 6 CACCTG TTTCCTGGG + +4 scertf__badis.REB1 2 0.0984876 2408.32 1 6 CACCTG GTTACCCGG + +4 transfac_pro__M07827-scro 1 0.0984876 2408.32 1 6 CACCTG CCACTTCAC + +4 predrem__nrMotif1206 3 0.0984876 2408.32 1 6 CACCTG TTCAAACTG - +4 predrem__nrMotif1844 0 0.0984876 2408.32 1 6 CACCTG AAACTGTCA - +4 predrem__nrMotif2338 0 0.0984876 2408.32 1 6 CACCTG TCCCTGTCA - +4 predrem__nrMotif1552 4 0.0984876 2408.32 1 5 CACCTG ACCAGACCA - +4 predrem__nrMotif1726 4 0.0984876 2408.32 1 5 CACCTG TGAGAACCA - +4 predrem__nrMotif646 4 0.0984876 2408.32 1 5 CACCTG TGCAAACCA - +4 dbcorrdb__RAD21__ENCSR000BLY_1__m2-CTCF-vtd 5 0.0985731 2410.41 1 6 CACCTG AAAGACACCTAGTGGTAAAA + +4 dbcorrdb__RXRA__ENCSR000BHU_1__m1-EcR-eg-Hnf4-Hr38-kni-knrl-svp-usp 10 0.0985731 2410.41 1 6 CACCTG GACCGCCTTTGACCTTTGCC + +4 taipale_cyt_meth__RORB_NAWNTRGGTCANTRGGTCAN_eDBD_repr-eg-Eip75B-Hr3-kni-knrl 10 0.0985731 2410.41 1 6 CACCTG GTGACCTACTGACCTACTTA - +4 taipale_tf_pairs__GCM2_E2F8_NTRYGGGNNNTGGCGGGARN_CAP_repr-gcm-gcm2 11 0.0985731 2410.41 1 6 CACCTG TTTCCCGCCATTACCCGCAT - +4 transfac_pro__M08964-EcR-ERR-Hr3-Hr78-usp 12 0.0989377 2419.32 1 6 CACCTG TGACCTCTACATGACCTC - +4 cisbp__M6383-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 11 0.0989703 2420.12 1 6 CACCTG CGTTGACCTTTGACCTTTA + +4 cisbp__M6183-CTCF-SMC3-usp-vtd 6 0.0989703 2420.12 1 6 CACCTG TAGCGCCCCCTGGTGGCCA - +4 flyfactorsurvey__lola-PL_SOLEXA_FBgn0005630-lola 5 0.099239 2426.69 1 6 CACCTG TGCACCACCGGGGG + +4 hocomoco__SP7_MOUSE.H11MO.0.A-Sp1 2 0.099239 2426.69 1 6 CACCTG CAAACCTGTAATTA + +4 taipale_cyt_meth__RORC_NRGGTCRTGACCYN_eDBD_meth-Hr3-usp 8 0.099239 2426.69 1 6 CACCTG TAGGTCATGACCTA + +4 transfac_pro__M07964-eg-Eip75B-Hr3-kni-knrl 9 0.099239 2426.69 1 5 CACCTG TGACCTACTGACCT - +4 transfac_pro__M01045-TfAP-2 2 0.101715 2487.24 1 6 CACCTG ACCGCCTGAGGGGAT + +4 transfac_pro__M01047-TfAP-2 2 0.101715 2487.24 1 6 CACCTG ACCGCCTGAGGCGGT + +4 transfac_pro__M09273 0 0.101715 2487.24 1 6 CACCTG CAACTACCAACTACC + +4 cisbp__M4649-CTCF-SMC3-usp-vtd 4 0.101715 2487.24 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4668-CTCF-SMC3-usp-vtd 5 0.101715 2487.24 1 6 CACCTG GGCGCCCCCTGGTGG - +4 taipale_cyt_meth__HNF4A_NRGGTCAAAGGTCAN_eDBD_meth-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 2 0.101715 2487.24 1 6 CACCTG TTGACCTTTGACCCC - +4 taipale_cyt_meth__NR3C2_NGNACRNNNYGTNCN_eDBD 2 0.101715 2487.24 1 6 CACCTG GGTACACGGTGTACC - +4 cisbp__M6343 4 0.101861 2490.81 1 6 CACCTG CATAAAACTGTCA + +4 neph__UW.Motif.0235 0 0.101861 2490.81 1 6 CACCTG CAGTTGCCAGAGT - +4 transfac_pro__M07360-ERR-ftz-f1 2 0.101861 2490.81 1 6 CACCTG TTGACCTTGAACG - +4 transfac_pro__M06987 8 0.101861 2490.81 1 5 CACCTG GATGTATAGACCT - +4 cisbp__M0233-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.102007 2494.37 1 6 CACCTG GTCACGTGAT + +4 cisbp__M0262 3 0.102007 2494.37 1 6 CACCTG TGACAGCTGG + +4 cisbp__M1324 4 0.102007 2494.37 1 6 CACCTG AGCGAATCTT + +4 jaspar__MA0988.1 2 0.102007 2494.37 1 6 CACCTG CGCACGTGCG + +4 predrem__nrMotif1610 0 0.102007 2494.37 1 6 CACCTG AGCCTGTCTT + +4 predrem__nrMotif1741 4 0.102007 2494.37 1 6 CACCTG AAATAACATT + +4 taipale_cyt_meth__NKX2-3_NNCACTTRAN_FL_meth-scro 2 0.102007 2494.37 1 6 CACCTG CCCACTTGAC + +4 transfac_pro__M01217-Hr38 2 0.102007 2494.37 1 6 CACCTG TTGACCTTTG + +4 transfac_pro__M07861-CG7786-gt-hng1-Pdp1-vri 2 0.102007 2494.37 1 6 CACCTG GTTACGTAAC + +4 cisbp__M0263-Atf6-CrebA-CrebB-Xbp1 1 0.102007 2494.37 1 6 CACCTG CCACGTCATC - +4 cisbp__M0804 3 0.102007 2494.37 1 6 CACCTG TCAGATCTAC - +4 flyfactorsurvey__Kr_FlyReg_FBgn0001325-Kr 2 0.102007 2494.37 1 6 CACCTG TTAACCCTTT - +4 hocomoco__PRD16_MOUSE.H11MO.0.B-ham-kn 1 0.102007 2494.37 1 6 CACCTG TCCCCTGGGG - +4 predrem__nrMotif2588 4 0.102007 2494.37 1 6 CACCTG GGAATGCCTG - +4 transfac_pro__M07562 1 0.102007 2494.37 1 6 CACCTG TCACTTTTTG - +4 predrem__nrMotif810 5 0.102007 2494.37 1 5 CACCTG AGAGAGACCA + +4 swissregulon__hs__TLX2.p2-C15 5 0.102007 2494.37 1 5 CACCTG CCACTTACCG - +4 scertf__macisaac.ASH1 -2 0.102007 2494.37 1 4 CACCTG CCTGATTCGG - +4 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNNNNNNNNNTGCGGG_CAP_repr-gcm-gcm2 16 0.103072 2520.43 1 6 CACCTG CCCGCATCCCCCCCCCCACCTG - +4 cisbp__M4249-CG7786-gt-Pdp1-vri 1 0.10337 2527.7 1 6 CACCTG TTACGTAA + +4 cisbp__M4322 1 0.10337 2527.7 1 6 CACCTG CCACGTGA + +4 cisbp__M5678-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.10337 2527.7 1 6 CACCTG TTGACCCC + +4 scertf__macisaac.ACE2-CG9609 0 0.10337 2527.7 1 6 CACCTG AACCAGCA + +4 transfac_pro__M07251 1 0.10337 2527.7 1 6 CACCTG TTTCCTGC + +4 taipale__NR2F1_full_RRGGTCAN_repr-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.10337 2527.7 1 6 CACCTG TTGACCCC - +4 cisbp__M2079 -1 0.10337 2527.7 1 5 CACCTG ACTTGAAT + +4 predrem__nrMotif1082 -1 0.10337 2527.7 1 5 CACCTG ACTTATCA + +4 predrem__nrMotif1197 -1 0.10337 2527.7 1 5 CACCTG CCCTGATG + +4 predrem__nrMotif1201 -1 0.10337 2527.7 1 5 CACCTG ACATGAGT + +4 predrem__nrMotif880 -1 0.10337 2527.7 1 5 CACCTG ACTTGAAT + +4 transfac_pro__M01048 -1 0.10337 2527.7 1 5 CACCTG ACCTCCCA - +4 transfac_pro__M06727 4 0.10337 2527.7 1 4 CACCTG GTGGTACC - +4 cisbp__M6175-kn 1 0.103373 2527.79 1 6 CACCTG GTCCCTGGGGAC + +4 taipale__IRX2_DBD_NWACAYRACAWN_repr-ara-caup-mirr 1 0.103373 2527.79 1 6 CACCTG TTACATGACATG + +4 transfac_pro__M06132 2 0.103373 2527.79 1 6 CACCTG CTCACCAGCCCT + +4 transfac_pro__M07628-TfAP-2 0 0.103373 2527.79 1 6 CACCTG TGCCCTAGGGCA + +4 hocomoco__ZBT48_HUMAN.H11MO.0.C 5 0.103373 2527.79 1 6 CACCTG CACGGTCCCTAA - +4 neph__UW.Motif.0250 5 0.103373 2527.79 1 6 CACCTG TTTGAAAACTGC - +4 transfac_pro__M05871 6 0.103373 2527.79 1 6 CACCTG TCCGGCTACCCA - +4 transfac_pro__M05902 6 0.103373 2527.79 1 6 CACCTG TCATCGGACCTC - +4 transfac_pro__M06396 6 0.103373 2527.79 1 6 CACCTG TGGTTTTACCCG - +4 transfac_pro__M06449 6 0.103373 2527.79 1 6 CACCTG TCCGATTGCCTA - +4 fantom__motif156_ACTGTAGGACMT 7 0.103373 2527.79 1 5 CACCTG ACTGTAGGACCT + +4 homer__AGGTCTCTAACC_PRDM14 7 0.103373 2527.79 1 5 CACCTG GGTTAGAGACCT - +4 transfac_pro__M05921 7 0.103373 2527.79 1 5 CACCTG TATTTTTCACCC - +4 transfac_pro__M05929-CG3281-CG4360-jim 7 0.103373 2527.79 1 5 CACCTG TCGGTTTAACCA - +4 transfac_pro__M06052 7 0.103373 2527.79 1 5 CACCTG TCTTCACCACCT - +4 transfac_pro__M06701-CG3281-CG4360-jim 7 0.103373 2527.79 1 5 CACCTG TCGGTTTAACCA - +4 transfac_pro__M06850 7 0.103373 2527.79 1 5 CACCTG TCCTCCGCTCCG - +4 cisbp__M6072-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 10 0.103499 2530.86 1 6 CACCTG TTGACCTTTTGACCTT + +4 taipale__NR4A2_full_TGACCTTTAAAGGTCA_repr-Hr38 1 0.103499 2530.86 1 6 CACCTG TGACCTTTAAAGGTCA - +4 taipale__Rarg_DBD_GRGGTCAAAAGKTCAC-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 10 0.103499 2530.86 1 6 CACCTG TTGACCTTTTGACCTT - +4 hocomoco__FOXF2_HUMAN.H11MO.0.D-FoxK-FoxL1-FoxP-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr 4 0.103519 2531.34 1 6 CACCTG TGTTTACTTAT + +4 neph__UW.Motif.0035 5 0.103519 2531.34 1 6 CACCTG CAGAGAAGCTG + +4 neph__UW.Motif.0120 2 0.103519 2531.34 1 6 CACCTG AAAATCTGCTT + +4 neph__UW.Motif.0229 5 0.103519 2531.34 1 6 CACCTG CAGGAGAGCTG + +4 predrem__nrMotif1803 1 0.103519 2531.34 1 6 CACCTG TTCCCTTGACT + +4 transfac_pro__M01854-lz-run-RunxA-RunxB 3 0.103519 2531.34 1 6 CACCTG CCACACCATGG + +4 hocomoco__NKX23_HUMAN.H11MO.0.D-bap-scro-vnd 3 0.103519 2531.34 1 6 CACCTG AACCACTTAAC - +4 taipale_cyt_meth__NR5A2_NYCAAGGTCAN_eDBD-ERR-ftz-f1-Hr39-Hr4 2 0.103519 2531.34 1 6 CACCTG GTGACCTTGAA - +4 transfac_pro__M01736 4 0.103519 2531.34 1 6 CACCTG TTGTTACCCGG - +4 transfac_pro__M07348-E(z)-TfAP-2 0 0.103519 2531.34 1 6 CACCTG CGCCTGCGGCC - +4 cisbp__M1751 0 0.103939 2541.63 1 6 CACCTG TGCATGG + +4 predrem__nrMotif2276 1 0.103939 2541.63 1 6 CACCTG ACACCCA + +4 cisbp__M1949 0 0.103939 2541.63 1 6 CACCTG TACGTCA - +4 predrem__nrMotif1268 0 0.1042 2547.99 1 6 CACCTG TTCCTTGAG + +4 predrem__nrMotif2121 3 0.1042 2547.99 1 6 CACCTG GTCTGCCTG + +4 predrem__nrMotif2158 0 0.1042 2547.99 1 6 CACCTG TTCCTTATT + +4 taipale__NKX2-8_DBD_NCACTTNAN-scro-tin-vnd 1 0.1042 2547.99 1 6 CACCTG CCACTTGAG + +4 cisbp__M0794 2 0.1042 2547.99 1 6 CACCTG GGGATCTAC - +4 neph__UW.Motif.0004-amos-tap 1 0.1042 2547.99 1 6 CACCTG CCATCTGCT - +4 predrem__nrMotif1311 3 0.1042 2547.99 1 6 CACCTG AAACACATG - +4 scertf__harbison.MSN2-CG10348-CG13296-ham 3 0.1042 2547.99 1 6 CACCTG CCGCCCCTT - +4 swissregulon__hs__ZIC1..3.p2-ci-lmd-opa-sug 3 0.1042 2547.99 1 6 CACCTG GACCACCCA - +4 transfac_pro__M00967-Hnf4-svp 3 0.1042 2547.99 1 6 CACCTG TTGGACTTT - +4 predrem__nrMotif1400 -1 0.1042 2547.99 1 5 CACCTG TCCTTCACA + +4 taipale_cyt_meth__IRF6_ACCGAWACY_FL_meth 5 0.1042 2547.99 1 4 CACCTG ACCGATACC + +4 transfac_pro__M01553-Mef2 1 0.104204 2548.1 1 6 CACCTG TTACCTATAATTAAATTAGCA + +4 transfac_pro__M05644 16 0.104204 2548.1 1 5 CACCTG AGCCTTCGGCAGACTGTACCA - +4 transfac_pro__M08950-Clk-cnc-Max-Mitf-Myc-Usf 0 0.10431 2550.68 1 6 CACCTG CACGTG - +4 fantom__motif30_AGNTCC 1 0.10431 2550.68 1 5 CACCTG GGAACT - +4 transfac_pro__M07694-lin-28 6 0.104658 2559.19 1 6 CACCTG ACCACCGACCTACACGA + +4 transfac_pro__M01479-pdm3 2 0.104658 2559.19 1 6 CACCTG GCAACCTCATTATCGTC - +4 dbcorrdb__CTCF__ENCSR000APF_1__m2-CTCF-vtd 5 0.104976 2566.97 1 6 CACCTG GATGACAGCTACCGGTAAAA - +4 taipale_cyt_meth__RORB_NAWNTRGGTCANTRGGTCAN_eDBD_meth-eg-Eip75B-Hr3-kni-knrl 10 0.104976 2566.97 1 6 CACCTG GTGACCTACTGACCTACTTA - +4 transfac_pro__M01259-CTCF-SMC3-usp-vtd 4 0.104976 2566.97 1 6 CACCTG GCGCCCCCTGGTGGCCATTT - +4 transfac_public__M00242-EcR-eg-Hnf4-Hr78-kni-knrl-Nup133-svp-usp 1 0.104976 2566.97 1 6 CACCTG TGACCTTTGACCTAGTTTTG - +4 taipale_cyt_meth__NR5A2_NCAAGGTCRNGACCTTGN_eDBD_meth-EcR-ERR-Hr39-Hr78-usp 10 0.105253 2573.75 1 6 CACCTG TCAAGGTCGCGACCTTGA + +4 transfac_pro__M09324 0 0.105253 2573.75 1 6 CACCTG CAACTACCAACTACCTTA - +4 transfac_pro__M05910 13 0.105253 2573.75 1 5 CACCTG GAGGCCACCGTGCCACCT - +4 taipale_cyt_meth__RARA_NRGGTCRTGACCYN_eDBD_meth-EcR-eg-Hr78-kni-knrl-usp 8 0.105327 2575.55 1 6 CACCTG AAGGTCGTGACCTT + +4 taipale_tf_pairs__HOXC10_EOMES_TMACACYYMRTWAA_CAP 3 0.105327 2575.55 1 6 CACCTG TCACACCTCATAAA + +4 taipale_tf_pairs__HOXD12_EOMES_TMRCACCTCRTWAA_CAP_repr 3 0.105327 2575.55 1 6 CACCTG TCACACCTCGTAAA + +4 transfac_pro__M05655 0 0.105327 2575.55 1 6 CACCTG GACCTTCTCGTCTA - +4 transfac_pro__M03795-EcR-svp-usp 12 0.105341 2575.91 1 6 CACCTG TTGACCTCCAGTGACCCCG + +4 transfac_public__M00056-C15-NfI 0 0.107852 2637.29 1 6 CACCTG CACCTGTTTTATTTGGCACGGTGCCAACT + +4 cisbp__M0016 0 0.107959 2639.93 1 6 CACCTG CACCGACCAT + +4 cisbp__M0160 2 0.107959 2639.93 1 6 CACCTG CGCACGTGCT + +4 cisbp__M0291-Atf6-Xbp1 3 0.107959 2639.93 1 6 CACCTG GATGACGTGT + +4 cisbp__M0789 4 0.107959 2639.93 1 6 CACCTG TGTATACTTT + +4 transfac_pro__M00993-amos-HLH3B 2 0.107959 2639.93 1 6 CACCTG TCCATCTGCT + +4 transfac_pro__M01716-amos 1 0.107959 2639.93 1 6 CACCTG GCAGCTGGTG + +4 transfac_pro__M07500 4 0.107959 2639.93 1 6 CACCTG AAAATATCTT + +4 transfac_pro__M07595 0 0.107959 2639.93 1 6 CACCTG CCCCTAGGGT + +4 transfac_pro__M09549 4 0.107959 2639.93 1 6 CACCTG AAAATATCTT + +4 cisbp__M0805 3 0.107959 2639.93 1 6 CACCTG TCGGATCTAC - +4 cisbp__M1312 2 0.107959 2639.93 1 6 CACCTG CTTATCCTTA - +4 cisbp__M5060-Kr 2 0.107959 2639.93 1 6 CACCTG TTAACCCTTT - +4 transfac_pro__M05168 -2 0.107959 2639.93 1 4 CACCTG CCTACGGACG - +4 neph__UW.Motif.0295 9 0.107988 2640.62 1 6 CACCTG AAAATTTTCTTTCTG + +4 taipale_cyt_meth__NR3C2_NGNACRNNNYGTNCN_eDBD_meth_repr 2 0.107988 2640.62 1 6 CACCTG GGTACATGATGTACC + +4 cisbp__M4495-Dif-dl-Rel-shn 9 0.107988 2640.62 1 6 CACCTG CTTGGAAATCCCCTT - +4 cisbp__M4496-Dif-dl-Rel 9 0.107988 2640.62 1 6 CACCTG TCTGGAAATCCCCTT - +4 cisbp__M4533-CTCF-SMC3-usp-vtd 5 0.107988 2640.62 1 6 CACCTG AGCGCCCCCTGGTGG - +4 cisbp__M4560-CTCF-SMC3-usp-vtd 5 0.107988 2640.62 1 6 CACCTG AGCGCCCCCTGGTGG - +4 cisbp__M4561-CTCF-SMC3-usp-vtd 5 0.107988 2640.62 1 6 CACCTG AGTGCCACCTAGTGG - +4 cisbp__M4662-CTCF-SMC3-usp-vtd 5 0.107988 2640.62 1 6 CACCTG GGCGCCCCCTGGTGG - +4 transfac_pro__M02819-TfAP-2 2 0.107988 2640.62 1 6 CACCTG TTCCCCTCAGGGAAT - +4 transfac_pro__M09287 6 0.107988 2640.62 1 6 CACCTG TTCACCAACCACTAC - +4 neph__UW.Motif.0047 7 0.108006 2641.08 1 6 CACCTG CAGATGGTTTCTG + +4 neph__UW.Motif.0145 2 0.108006 2641.08 1 6 CACCTG AATTCCTTGCCTC + +4 hocomoco__COT1_HUMAN.H11MO.1.C-EcR-Hr78-eg-kni-knrl-svp-usp 4 0.108006 2641.08 1 6 CACCTG CCCTGACCTCTGC - +4 taipale_tf_pairs__GCM2_FOXI1_RTAAATANGGGNN_CAP-gcm-gcm2 0 0.108006 2641.08 1 6 CACCTG TACCCTTATTTAC - +4 taipale_tf_pairs__HOXA3_EOMES_TAATKAGGTGNKA_CAP_repr 3 0.108006 2641.08 1 6 CACCTG TAACACCTCATTA - +4 cisbp__M5035-Hr51 -1 0.108006 2641.08 1 5 CACCTG ACCTTTGATTTTT + +4 flyfactorsurvey__Hr51_SANGER_5_FBgn0034012-Hr51 -1 0.108006 2641.08 1 5 CACCTG ACCTTTGATTTTT - +4 transfac_pro__M08952-CG12018-Dif-dl-Rel 8 0.108006 2641.08 1 5 CACCTG GGGGGAAGCCCCC - +4 cisbp__M0945 2 0.109141 2668.83 1 6 CACCTG TTAACTAG + +4 yetfasco__YJR060W_1346 2 0.109141 2668.83 1 6 CACCTG ACCACGTG + +4 cisbp__M6254-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 2 0.109141 2668.83 1 6 CACCTG CTTATCTG - +4 predrem__nrMotif1421 0 0.109141 2668.83 1 6 CACCTG CAACTGTT - +4 predrem__nrMotif624 0 0.109141 2668.83 1 6 CACCTG TACCAACT - +4 transfac_pro__M01153-usp 1 0.109141 2668.83 1 6 CACCTG TGAACTCC - +4 yetfasco__YHL009C_1411 1 0.109141 2668.83 1 6 CACCTG TTACGTAA - +4 transfac_pro__M04948-Hnf4 -1 0.109141 2668.83 1 5 CACCTG CCCTTTGT - +4 neph__UW.Motif.0040 -2 0.109141 2668.83 1 4 CACCTG CCTCCCAC + +4 transfac_public__M00378 6 0.10952 2678.09 1 6 CACCTG AATCCCCACCCC + +4 transfac_pro__M05919 4 0.10952 2678.09 1 6 CACCTG CCTCTACCTAAT - +4 transfac_pro__M06017 1 0.10952 2678.09 1 6 CACCTG TCACCGTGCAGG - +4 transfac_pro__M06072-wdn 1 0.10952 2678.09 1 6 CACCTG GCATCTTCCCCA - +4 transfac_pro__M06775-CG6654-CG7372 6 0.10952 2678.09 1 6 CACCTG GACCCTCACCCG - +4 transfac_pro__M08967-Eip75B-Hr3 1 0.10952 2678.09 1 6 CACCTG TGACCTACTTAT - +4 transfac_pro__M05471 7 0.10952 2678.09 1 5 CACCTG GCCCCCCCACCT - +4 transfac_pro__M05647-CG31612 7 0.10952 2678.09 1 5 CACCTG GCTTTTTCACCA - +4 transfac_pro__M05825 7 0.10952 2678.09 1 5 CACCTG GCTTCCCTACCA - +4 transfac_pro__M06102-crol 7 0.10952 2678.09 1 5 CACCTG GCGGTCGTACCT - +4 transfac_pro__M06138-crol 7 0.10952 2678.09 1 5 CACCTG AAGCCCGTACCA - +4 transfac_pro__M06165 7 0.10952 2678.09 1 5 CACCTG TCCTTCCCACCA - +4 transfac_pro__M06267 7 0.10952 2678.09 1 5 CACCTG AACGCCCTACCC - +4 transfac_pro__M06574 7 0.10952 2678.09 1 5 CACCTG TGTATCGAACCG - +4 transfac_pro__M06676 7 0.10952 2678.09 1 5 CACCTG GCATTTTTACCT - +4 transfac_pro__M06696 7 0.10952 2678.09 1 5 CACCTG TGTATCGAACCG - +4 taipale_cyt_meth__TFAP2C_NGCCYNMGGCN_eDBD-TfAP-2 0 0.109605 2680.18 1 6 CACCTG TGCCCGAGGCA + +4 taipale_cyt_meth__ZBTB7A_NCGACCMCCGN_eDBD_meth_repr 5 0.109605 2680.18 1 6 CACCTG GCGACCACCGA + +4 cisbp__M4479-ac-ase-dimm-l(1)sc-nau-sc 1 0.109605 2680.18 1 6 CACCTG ACAGCTGCTGC - +4 cisbp__M5486-gcm-gcm2 1 0.109605 2680.18 1 6 CACCTG GTACCCGCATG - +4 cisbp__M6239-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-GATAe-grn-HDAC1-nej-pnr 4 0.109605 2680.18 1 6 CACCTG TGTTTACTTTT - +4 hocomoco__SRBP1_HUMAN.H11MO.0.A-SREBP 2 0.109605 2680.18 1 6 CACCTG CTCACCCCACC - +4 hocomoco__STF1_HUMAN.H11MO.0.B-ERR-ftz-f1 1 0.109605 2680.18 1 6 CACCTG TGGCCTTGAGC - +4 taipale__GCM1_full_NATGCGGGTAN-gcm-gcm2 1 0.109605 2680.18 1 6 CACCTG GTACCCGCATG - +4 transfac_pro__M08953-EcR-Hr78 5 0.109605 2680.18 1 6 CACCTG CATTTGACCTC - +4 cisbp__M1547 0 0.109662 2681.56 1 6 CACCTG TACGTAA + +4 cisbp__M1762 1 0.109662 2681.56 1 6 CACCTG TTGCCGG + +4 cisbp__M5106-Clk-cyc-Max-Met-Myc 1 0.109662 2681.56 1 6 CACCTG CCACGTG + +4 cisbp__M6439 1 0.109662 2681.56 1 6 CACCTG TAATCTG + +4 jaspar__MA0129.1 0 0.109662 2681.56 1 6 CACCTG TACGTCA + +4 predrem__nrMotif1998 0 0.109662 2681.56 1 6 CACCTG CACTTGT + +4 scertf__badis.REI1-CG6769 0 0.109662 2681.56 1 6 CACCTG CCCCTGA + +4 scertf__badis.YER130C-CG10348-CG13296-ham 0 0.109662 2681.56 1 6 CACCTG CCCCTAT + +4 predrem__nrMotif272 -1 0.109662 2681.56 1 5 CACCTG ACTTCCA + +4 predrem__nrMotif1124 2 0.109662 2681.56 1 5 CACCTG CAAAACT - +4 hocomoco__ZN335_HUMAN.H11MO.0.A 15 0.1098 2684.94 1 6 CACCTG GGCTGTCCTCGGCGCTGCCTGA + +4 neph__UW.Motif.0640 0 0.109921 2687.89 1 6 CACCTG CTCCATCTGCCTGTCA + +4 homer__GTAGGTCACTGGGTCA_Reverb-Eip75B-Hr3 9 0.109921 2687.89 1 6 CACCTG TGACCCAGTGACCTAC - +4 neph__UW.Motif.0553 10 0.109921 2687.89 1 6 CACCTG CTCAGCCCAGCAGCTG - +4 taipale_cyt_meth__RARA_NRGGTCANNRGGTCAN_eDBD-EcR-eg-Hr78-kni-knrl-svp-usp 10 0.109921 2687.89 1 6 CACCTG GTGACCTCTTGACCTC - +4 hdpi__ZBTB25 -2 0.110125 2692.88 1 4 CACCTG CCTTTG - +4 cisbp__M0243-Clk-cyc-E2f1-Max-Myc-tgo-Usf 3 0.110161 2693.76 1 6 CACCTG GGGCACGTG + +4 predrem__nrMotif1715 3 0.110161 2693.76 1 6 CACCTG TTCCACTTT + +4 predrem__nrMotif2427 3 0.110161 2693.76 1 6 CACCTG AATTATCTT + +4 transfac_pro__M07437 2 0.110161 2693.76 1 6 CACCTG TCCTCCTGA + +4 yetfasco__YOR344C_397-Mitf-Mondo-SREBP-Usf-bigmax-tgo 2 0.110161 2693.76 1 6 CACCTG ATCACGTGA + +4 hdpi__SPAG7-CG2608 0 0.110161 2693.76 1 6 CACCTG GACGTGGCC - +4 hocomoco__PTF1A_HUMAN.H11MO.1.B-Fer1-ac-ase-l(1)sc-sc 1 0.110161 2693.76 1 6 CACCTG CCAGCTGCT - +4 neph__UW.Motif.0056-Hnf4-Spps-btd 2 0.110161 2693.76 1 6 CACCTG TGCACTTTG - +4 cisbp__M0810-gcm-gcm2 -1 0.110161 2693.76 1 5 CACCTG ACCCGCATC - +4 predrem__nrMotif1665 -1 0.110161 2693.76 1 5 CACCTG AACTGAGCT - +4 predrem__nrMotif401 4 0.110161 2693.76 1 5 CACCTG ACCCAACCC - +4 predrem__nrMotif667 4 0.110161 2693.76 1 5 CACCTG AGCATGCCT - +4 fantom__motif157_AAACTWACC 5 0.110161 2693.76 1 4 CACCTG AAACTAACC + +4 predrem__nrMotif2233 -2 0.110161 2693.76 1 4 CACCTG CCTTAAAAA + +4 predrem__nrMotif431 5 0.110161 2693.76 1 4 CACCTG AGCAAAACC - +4 cisbp__M4648-Chd1-CTCF-SMC3-usp-vtd 6 0.111197 2719.09 1 6 CACCTG TAGTGCCATCTGGTGGC - +4 hocomoco__CTCFL_HUMAN.H11MO.0.A-CTCF-SMC3-usp-vtd 6 0.111197 2719.09 1 6 CACCTG CGGCGCCCCCTGGCGGC - +4 taipale_tf_pairs__HOXB2_TCF3_NCAGGTGNNNNNMATTA_CAP-pb 10 0.111197 2719.09 1 6 CACCTG TAATGACCTGCACCTGC - +4 taipale_tf_pairs__HOXD12_TBX21_AGGTGTKAAGTCGTAAA_CAP_repr 12 0.111197 2719.09 1 5 CACCTG TTTACGACTTCACACCT - +4 taipale_tf_pairs__TFAP2C_ONECUT2_NATCGATNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 13 0.111438 2725 1 6 CACCTG GATCGATCTGCTTGGCCTGAGGCGA + +4 taipale_tf_pairs__ALX4_TBX21_RGGTGNTAATNNNNNNNNNCASYNN_CAP 20 0.111438 2725 1 5 CACCTG TAGGTGTGAATTTTAATTAACACCT - +4 cisbp__M3781-EcR-eg-Hnf4-Hr78-kni-knrl-Nup133-svp-usp 1 0.1117 2731.39 1 6 CACCTG TGACCTTTGACCTAGTTTTG + +4 dbcorrdb__CTCF__ENCSR000DMC_1__m1-CTCF-SMC3-usp-vtd 6 0.1117 2731.39 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__REST__ENCSR000BJL_1__m2-CTCF 11 0.1117 2731.39 1 6 CACCTG GCCGGGTTCAGCACCACGGA + +4 dbcorrdb__SMC3__ENCSR000EHW_1__m1-CTCF-SMC3-usp-vtd 7 0.1117 2731.39 1 6 CACCTG ATAGTGCCCCCTGGTGGCCA + +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m6 2 0.1117 2731.39 1 6 CACCTG CACACCTTATTCAGCATCAG + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m4-RpII215 11 0.1117 2731.39 1 6 CACCTG TAAGGGATAAGGACCTACCA - +4 taipale_cyt_meth__RORC_NWWNNRGGTCANNRGGTCAN_eDBD-eg-Eip75B-Hr3-kni-knrl 10 0.1117 2731.39 1 6 CACCTG GTGACCTACTGACCTACTTT - +4 cisbp__M4468-Dif-dl-Rel-shn 8 0.111706 2731.54 1 6 CACCTG TTGGAAATCCCCTT - +4 cisbp__M4562-CTCF-SMC3-usp-vtd 3 0.111706 2731.54 1 6 CACCTG CGCCCCCTGGTGGC - +4 cisbp__M4650-CTCF-SMC3-usp-vtd 4 0.111706 2731.54 1 6 CACCTG GCGCCCCCTGGTGG - +4 cisbp__M6259-gcm-gcm2 2 0.111706 2731.54 1 6 CACCTG AATACCCGCATGTG - +4 hocomoco__ETV5_HUMAN.H11MO.0.C-CG9650-Eip74EF-Ets96B-Ets97D-GATAe-aop-grn-pnr-pnt 5 0.111706 2731.54 1 6 CACCTG CTCACTTCCTGCTC - +4 hocomoco__GCM1_HUMAN.H11MO.0.D-gcm-gcm2 2 0.111706 2731.54 1 6 CACCTG AGTACCCGCATGTT - +4 taipale__RXRA_full_RRGGTCATGACCYY-EcR-eg-Hr78-kni-knrl-usp 8 0.111706 2731.54 1 6 CACCTG GGGGTCATGACCTC - +4 taipale__RXRG_full_GGGGTCAAAGGTCA-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.111706 2731.54 1 6 CACCTG TGACCTTTGACCCC - +4 transfac_pro__M04738-EcR-eg-ERR-kni-knrl 9 0.111706 2731.54 1 5 CACCTG GGTCAGGGTGACCT - +4 neph__UW.Motif.0098 -2 0.111706 2731.54 1 4 CACCTG CCTGGGGCTGGGCA + +4 cisbp__M4611-CTCF-SMC3-usp-vtd 5 0.11188 2735.79 1 6 CACCTG GGCGCCCCCTGGTGGCCA - +4 taipale_tf_pairs__RORB_AANTAGGTCAGTAGGTCA_HT-Hr3 9 0.11188 2735.79 1 6 CACCTG TGACCTACTGACCTACTT - +4 transfac_pro__M01059-bs-Mef2 2 0.11188 2735.79 1 6 CACCTG CTTACCTAATTTGGAAAC - +4 cisbp__M1957-CTCF-SMC3-usp-vtd 6 0.112029 2739.45 1 6 CACCTG TAGCGCCCCCTGGTGGCCA - +4 fantom__motif16_ACCAG -1 0.114107 2790.25 1 5 CACCTG ACCAG + +4 cisbp__M0361-Atf3-Atf6-Atf-2-CG7786-CG44247-CrebA-CrebB-Jra-Pdp1-REPTOR-BP-Xbp1-cnc-gt-kay-vri 2 0.114188 2792.25 1 6 CACCTG ATGACGTAAT + +4 cisbp__M0684 4 0.114188 2792.25 1 6 CACCTG AATGTATCTA + +4 fantom__motif79_ACATCTACAA 1 0.114188 2792.25 1 6 CACCTG ACATCTACAA + +4 swissregulon__sacCer__TYE7-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.114188 2792.25 1 6 CACCTG ATCACGTGAT + +4 transfac_pro__M00369-Atf6-CrebA-Max-Myc-tgo-Usf 2 0.114188 2792.25 1 6 CACCTG GCCACGTGGC + +4 transfac_pro__M04864-Ets96B-GATAe-grn-pnr 4 0.114188 2792.25 1 6 CACCTG TCATTTCCTG + +4 transfac_pro__M06818 0 0.114188 2792.25 1 6 CACCTG CACCGGATGC + +4 c2h2_zfs__M0400-opa 3 0.114188 2792.25 1 6 CACCTG GACCCCCCGG - +4 hocomoco__MYBB_HUMAN.H11MO.0.D 2 0.114188 2792.25 1 6 CACCTG TCAACCTGCA - +4 predrem__nrMotif3 0 0.114188 2792.25 1 6 CACCTG TTCCTTTCCT - +4 taipale_cyt_meth__TBX2_NAGGTGTGAN_eDBD_repr-bi 4 0.114188 2792.25 1 6 CACCTG CCCACACCTC - +4 transfac_pro__M04727-CTCF-SMC3-usp-vtd 2 0.114188 2792.25 1 6 CACCTG GCCCCCTGGT - +4 yetfasco__YCR018C_2232 1 0.114188 2792.25 1 6 CACCTG GGATCTACAC - +4 taipale_cyt_meth__ZBTB7B_NCGACCMCCN_eDBD_meth 5 0.114188 2792.25 1 5 CACCTG ACGACCACCG + +4 transfac_pro__M07930-ci 5 0.114188 2792.25 1 5 CACCTG GCGACCACCC + +4 predrem__nrMotif2110 5 0.114188 2792.25 1 5 CACCTG AAAGAAACCA - +4 cisbp__M6455-Eip75B-Hr3 2 0.114441 2798.44 1 6 CACCTG CTGACCTACTTTT + +4 neph__UW.Motif.0128 1 0.114441 2798.44 1 6 CACCTG AAAACTGTTTTTT + +4 cisbp__M1345 4 0.114441 2798.44 1 6 CACCTG ATCGTATCTTGAT - +4 jaspar__MA0948.1 4 0.114441 2798.44 1 6 CACCTG ATCGTATCTTGAT - +4 neph__UW.Motif.0142 3 0.114441 2798.44 1 6 CACCTG AGAGCCCTGTCCT - +4 neph__UW.Motif.0241 5 0.114441 2798.44 1 6 CACCTG TTTTTTTTCTGGC - +4 neph__UW.Motif.0306 3 0.114441 2798.44 1 6 CACCTG AGCCATTTTCTTT - +4 transfac_pro__M07289 5 0.114441 2798.44 1 6 CACCTG GCCCACCCCCTCC - +4 transfac_pro__M05352 -1 0.114441 2798.44 1 5 CACCTG ACCTTTAAAGGCC + +4 neph__UW.Motif.0160 8 0.114441 2798.44 1 5 CACCTG CACAGAGCTGCCT - +4 hocomoco__AP2A_HUMAN.H11MO.0.A-GATAe-TfAP-2-grn-pnr 2 0.114561 2801.35 1 6 CACCTG ATGCCCTGAGGCCAT + +4 transfac_pro__M09179 9 0.114561 2801.35 1 6 CACCTG TTTTTTTTTTACCGT + +4 cisbp__M4448-CTCF-SMC3-usp-vtd 5 0.114561 2801.35 1 6 CACCTG GGCGCCCCCTGGTGG - +4 taipale_tf_pairs__GCM2_FIGLA_RTRCGGGNNCASSTG_CAP-gcm-gcm2 0 0.114561 2801.35 1 6 CACCTG CACCTGGACCCGCAT - +4 swissregulon__hs__NFIX.p2-C15-Nf1-NfI-tll 0 0.115097 2814.46 1 6 CACCTG CACCTGTTCTGTTTGGCACGCTGCCAGCT + +4 cisbp__M0934 2 0.115158 2815.96 1 6 CACCTG TTAACCAG + +4 cisbp__M2162-Max-Myc 1 0.115158 2815.96 1 6 CACCTG GCACGTGC + +4 jaspar__MA0357.1-Max-Myc 1 0.115158 2815.96 1 6 CACCTG GCACGTGC + +4 jaspar__MA0957.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Mnt-Sidpn 1 0.115158 2815.96 1 6 CACCTG GCACGTGC + +4 transfac_pro__M09548 1 0.115158 2815.96 1 6 CACCTG AGCCCTAG + +4 cisbp__M0490 0 0.115158 2815.96 1 6 CACCTG CACCAATG - +4 jaspar__MA0946.1 2 0.115158 2815.96 1 6 CACCTG CGTATCTT - +4 predrem__nrMotif2449 3 0.115158 2815.96 1 5 CACCTG GGCTACTT + +4 predrem__nrMotif2622 3 0.115158 2815.96 1 5 CACCTG AAGTAACT + +4 jaspar__MA0947.1 3 0.115158 2815.96 1 5 CACCTG GCGTATCT - +4 predrem__nrMotif1295 3 0.115158 2815.96 1 5 CACCTG ATTCATCT - +4 predrem__nrMotif2039 3 0.115158 2815.96 1 5 CACCTG AACAACCC - +4 taipale_tf_pairs__GCM1_FIGLA_CASSTGNNNNNNNNNNNTGCGGG_CAP_repr-gcm-gcm2 17 0.115361 2820.92 1 6 CACCTG CCCGCATCCCCCCCCCCCACCTG - +4 cisbp__M6258-srp 1 0.115655 2828.1 1 6 CACCTG TTATCTT - +4 predrem__nrMotif146 -1 0.115655 2828.1 1 5 CACCTG AGCTTCC + +4 predrem__nrMotif2302 -1 0.115655 2828.1 1 5 CACCTG ACATAAT + +4 predrem__nrMotif1139 -1 0.115655 2828.1 1 5 CACCTG ACCAACC - +4 predrem__nrMotif2542 -2 0.115655 2828.1 1 4 CACCTG CCTTTAC + +4 predrem__nrMotif1441 -2 0.115655 2828.1 1 4 CACCTG CCTTGGA - +4 predrem__nrMotif2266 -2 0.115655 2828.1 1 4 CACCTG CCTTGAA - +4 cisbp__M1126 0 0.115955 2835.46 1 6 CACCTG GAGCTGTCATTT + +4 cisbp__M5934-achi-hth-nau-vis 3 0.115955 2835.46 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M01142-ftz-f1 2 0.115955 2835.46 1 6 CACCTG CTGGCCTTGAAC + +4 cisbp__M3717 6 0.115955 2835.46 1 6 CACCTG AATCCCCACCCC - +4 cisbp__M5581-ara-caup-mirr 1 0.115955 2835.46 1 6 CACCTG GTACATGACATG - +4 cisbp__M6451-CG9727-Rfx 1 0.115955 2835.46 1 6 CACCTG TTCCCTAGCAAC - +4 taipale__TGIF2_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.115955 2835.46 1 6 CACCTG TGACAGCTGTCA - +4 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_eDBD-amos-Fer3-HLH54F-nau 3 0.115955 2835.46 1 6 CACCTG CAACAGCTGTCG - +4 transfac_pro__M06076 6 0.115955 2835.46 1 6 CACCTG AACCATCACCCG - +4 transfac_pro__M06240 6 0.115955 2835.46 1 6 CACCTG GCGTTCCACCCT - +4 transfac_pro__M06604 0 0.115955 2835.46 1 6 CACCTG TCCCTAAAGCAA - +4 transfac_pro__M06758 1 0.115955 2835.46 1 6 CACCTG GCACTTTTACAC - +4 transfac_pro__M06166 7 0.115955 2835.46 1 5 CACCTG TGTTTTTTACCA - +4 transfac_pro__M06544 7 0.115955 2835.46 1 5 CACCTG GCGGCAGGACCG - +4 transfac_pro__M06572 7 0.115955 2835.46 1 5 CACCTG TCTCAATTACCC - +4 transfac_pro__M06633 7 0.115955 2835.46 1 5 CACCTG TCTTCCTCACCC - +4 taipale_cyt_meth__NR5A2_NYCAAGGTCAN_eDBD_meth-ERR-ftz-f1-Hr39 2 0.115979 2836.03 1 6 CACCTG GTGACCTTGAG - +4 transfac_pro__M00726-Usf 0 0.116229 2842.14 1 6 CACCTG CACGTG - +4 swissregulon__hs__GATA1..3.p2-GATAe-grn-pnr 1 0.116229 2842.14 1 5 CACCTG CCATCT - +4 hdpi__GTF3C5-l(2)37Cd 2 0.116229 2842.14 1 4 CACCTG GTGACC + +4 cisbp__M0266 2 0.116368 2845.55 1 6 CACCTG GCCACGTGG + +4 idmmpmm__usp-usp 3 0.116368 2845.55 1 6 CACCTG CGTGACCTA + +4 predrem__nrMotif1985 3 0.116368 2845.55 1 6 CACCTG ATATTCCTT + +4 predrem__nrMotif2384 3 0.116368 2845.55 1 6 CACCTG GCCCACCGC + +4 predrem__nrMotif278 0 0.116368 2845.55 1 6 CACCTG CACTTTGAA + +4 hocomoco__BHE40_MOUSE.H11MO.0.A-Clk-cyc-tai-tgo 2 0.116368 2845.55 1 6 CACCTG GTCACGTGC - +4 predrem__nrMotif1181 3 0.116368 2845.55 1 6 CACCTG ACTAAACTT - +4 predrem__nrMotif1684 3 0.116368 2845.55 1 6 CACCTG GCTGCCCTG - +4 predrem__nrMotif1771 3 0.116368 2845.55 1 6 CACCTG AGCCACTTG - +4 predrem__nrMotif2498 0 0.116368 2845.55 1 6 CACCTG AAACTAAAG - +4 predrem__nrMotif1310 4 0.116368 2845.55 1 5 CACCTG ATGTCACTT + +4 predrem__nrMotif2375 -1 0.116368 2845.55 1 5 CACCTG AACTCCCCA + +4 predrem__nrMotif2400 4 0.116368 2845.55 1 5 CACCTG ATGACACCT + +4 cisbp__M0812-gcm-gcm2 -1 0.116368 2845.55 1 5 CACCTG ACCCGCATG - +4 neph__UW.Motif.0024 4 0.116368 2845.55 1 5 CACCTG CTGCTTCCT - +4 predrem__nrMotif1490 4 0.116368 2845.55 1 5 CACCTG GAAACAACT - +4 predrem__nrMotif1560 -2 0.116368 2845.55 1 4 CACCTG CCTGTGGCC + +4 predrem__nrMotif465 5 0.116368 2845.55 1 4 CACCTG TTTTGCACA - +4 cisbp__M5768-EcR-eg-Hnf4-kni-knrl-svp 10 0.116651 2852.47 1 6 CACCTG GTGACCTTTTGACCTC + +4 neph__UW.Motif.0565 10 0.116651 2852.47 1 6 CACCTG TTATCAAAGCTTTCTG - +4 taipale__RARG_full_GRGGTCAAAAGKTCAC-EcR-eg-Hnf4-kni-knrl-svp 10 0.116651 2852.47 1 6 CACCTG GTGACCTTTTGACCTC - +4 taipale_tf_pairs__TFAP4_ETV1_RSCGGAANCAGSTGNN_CAP-crp-Ets96B 2 0.116651 2852.47 1 6 CACCTG CCCACCTGCTTCCGGC - +4 taipale_tf_pairs__GCM1_MAX_RTGCGGGNNNNNNNCACGTGN_CAP-gcm-gcm2-Max 12 0.118013 2885.76 1 6 CACCTG CCACGTGCCCCCTACCCGCAT - +4 taipale_tf_pairs__GCM1_MAX_RTGCGGGNNNNNNNCACGTGN_CAP_repr-gcm-gcm2-Max 12 0.118013 2885.76 1 6 CACCTG CCACGTGCTCCCCACCCGCAT - +4 transfac_pro__M09438 8 0.118013 2885.76 1 6 CACCTG GTGGGTCCCACCTTCTTTTTA - +4 taipale_cyt_meth__ZBTB37_NYACCGCRNNYACCGYR_eDBD_meth_repr 10 0.118051 2886.7 1 6 CACCTG TCACCGCGCTCACCGCG + +4 taipale__RARG_DBD_GRGGTCAAAAGGTCANA-EcR-eg-Hnf4-kni-knrl-svp 3 0.118051 2886.7 1 6 CACCTG TGTGACCTTTTGACCTC - +4 cisbp__M5798-EcR-eg-Hr78-kni-knrl-usp 8 0.118385 2894.87 1 6 CACCTG GGGGTCATGACCCC + +4 cisbp__M5802-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.118385 2894.87 1 6 CACCTG TGACCTTTGACCCC + +4 hocomoco__ASCL1_MOUSE.H11MO.0.A-ac-ase-l(1)sc-nau-sc 3 0.118385 2894.87 1 6 CACCTG CTGCAGCTGCCCCC + +4 neph__UW.Motif.0353 6 0.118385 2894.87 1 6 CACCTG AAGAACCAGTTTCT + +4 hocomoco__RFX6_MOUSE.H11MO.1.C-Rfx 2 0.118385 2894.87 1 6 CACCTG GTTTCCTAGCAACC - +4 neph__UW.Motif.0356-Jra 6 0.118385 2894.87 1 6 CACCTG TGAGTCTTCCTTCC - +4 dbcorrdb__CTCF__ENCSR000DKP_1__m1-Chd1-CTCF-SMC3-usp-vtd 9 0.118754 2903.9 1 6 CACCTG CTCTAGCGCCCCCTGGTGGC + +4 dbcorrdb__CTCF__ENCSR000DKV_1__m1-CTCF-SMC3-usp-vtd 6 0.118754 2903.9 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DML_1__m1-CTCF-SMC3-usp-vtd 5 0.118754 2903.9 1 6 CACCTG GGCGCCCCCTGGTGGCCGCG + +4 dbcorrdb__CTCF__ENCSR000DMS_1__m1-CTCF-SMC3-usp-vtd 7 0.118754 2903.9 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DNI_1__m1-CTCF-SMC3-usp-vtd 5 0.118754 2903.9 1 6 CACCTG AGCGCCCCCTGGTGGCCACA + +4 dbcorrdb__SMC3__ENCSR000DZP_1__m1-CTCF-SMC3-usp-vtd 6 0.118754 2903.9 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__SMC3__ENCSR000EGW_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.118754 2903.9 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DKX_1__m1-CTCF-SMC3-usp-vtd 6 0.118754 2903.9 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__CTCF__ENCSR000DKY_1__m1-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.118754 2903.9 1 6 CACCTG CTCTGGCGCCCCCTGGTGGC - +4 dbcorrdb__CTCF__ENCSR000DLD_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.118754 2903.9 1 6 CACCTG TCTGGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DNC_1__m1-CTCF-SMC3-usp-vtd 6 0.118754 2903.9 1 6 CACCTG TAGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__RELA__ENCSR000EAQ_1__m1-Dif-dl-Rel-shn 8 0.118754 2903.9 1 6 CACCTG CGGGAAATCCCCTGCGCCCC - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m9-SREBP 0 0.118754 2903.9 1 6 CACCTG CCCCTTCTTTTAGCAGGGAG - +4 transfac_pro__M01200-Chd1-CTCF-SMC3-usp-vtd 6 0.118754 2903.9 1 6 CACCTG CGGCGCCCCCTGGTGGCCAC - +4 cisbp__M5762-EcR-ERR-ftz-f1-Hr78-usp 1 0.118828 2905.7 1 6 CACCTG TGACCTCACATGACCTTT + +4 taipale__RARA_full_ARRGGTCANNNRRGGTCA-EcR-ERR-ftz-f1-Hr78-svp-usp 11 0.118828 2905.7 1 6 CACCTG TGACCTCACATGACCTTT - +4 taipale_cyt_meth__ZNF580_MCTACCCYNNNMCTACCCY_FL_meth 13 0.119044 2910.98 1 6 CACCTG CCTACCCTCCCCCTACCCT + +4 c2h2_zfs__M5111 7 0.119044 2910.98 1 6 CACCTG CTTAATCTACATTTAACAT - +4 jaspar__MA0139.1-CTCF-SMC3-usp-vtd 6 0.119044 2910.98 1 6 CACCTG TAGCGCCCCCTGGTGGCCA - +4 cisbp__M0152-Max 2 0.120694 2951.33 1 6 CACCTG CGCACGTGCG + +4 cisbp__M0216-HLH4C 2 0.120694 2951.33 1 6 CACCTG CGCAGCTGTG + +4 cisbp__M1306 4 0.120694 2951.33 1 6 CACCTG AAAATATCTT + +4 cisbp__M1327 4 0.120694 2951.33 1 6 CACCTG AGCGAATCTT + +4 flyfactorsurvey__dei_da_SANGER_5_FBgn0000413-CG8319-HLH54F-da-scrt-tx 2 0.120694 2951.33 1 6 CACCTG ACCACCTGTT + +4 homer__AYTAAACCGG_Unknown3 4 0.120694 2951.33 1 6 CACCTG ATTAAACCGG + +4 jaspar__MA0945.1 4 0.120694 2951.33 1 6 CACCTG AGCGAATCTT + +4 taipale__NKX2-3_full_NCCACTTRAN_repr-scro-tin-vnd 2 0.120694 2951.33 1 6 CACCTG ACCACTTGAA + +4 taipale_cyt_meth__NKX2-3_NCCACTTRAN_eDBD-bap-scro-vnd 2 0.120694 2951.33 1 6 CACCTG ACCACTTGAC + +4 transfac_pro__M00375-Usf 2 0.120694 2951.33 1 6 CACCTG GCCACGTCAC + +4 transfac_pro__M08909-Clk-cnc-cyc-Mitf-tgo-Usf 3 0.120694 2951.33 1 6 CACCTG TGTCACGTGA + +4 cisbp__M0946-bap-scro-vnd 3 0.120694 2951.33 1 6 CACCTG AGCCACTTAA - +4 cisbp__M1366 1 0.120694 2951.33 1 6 CACCTG TTACCGGTGT - +4 hocomoco__RXRA_MOUSE.H11MO.2.A-EcR-usp 4 0.120694 2951.33 1 6 CACCTG CCTTGACCTC - +4 taipale_cyt_meth__ARNTL_RTCAYGTGMN_eDBD_meth-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.120694 2951.33 1 6 CACCTG GTCACATGAC - +4 tiffin__TIFDMEM0000067 2 0.120694 2951.33 1 6 CACCTG AAAACCCTTT - +4 scertf__badis.USV1 0 0.120712 2951.77 1 5 CACCTG CCCCT - +4 cisbp__M4521-CTCF-SMC3-usp-vtd 3 0.121176 2963.11 1 6 CACCTG CGCCCTCTGGTGG - +4 cisbp__M6223-Ets96B 5 0.121176 2963.11 1 6 CACCTG GTTACTTCCTGTC - +4 neph__UW.Motif.0386 7 0.121176 2963.11 1 6 CACCTG GAAAAATCACTTG - +4 transfac_pro__M00762-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.121176 2963.11 1 6 CACCTG TGACCTTTGACCC - +4 transfac_pro__M07958-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.121176 2963.11 1 6 CACCTG TGACCTTTGACCC - +4 neph__UW.Motif.0107 8 0.121176 2963.11 1 5 CACCTG CTGAGCCCTTCCT - +4 neph__UW.Motif.0019 0 0.121436 2969.49 1 6 CACCTG CACATTCC + +4 transfac_pro__M01779-bigmax-Mitf 2 0.121436 2969.49 1 6 CACCTG ATCACGTG + +4 cisbp__M0551 1 0.121436 2969.49 1 6 CACCTG CCACCGCA - +4 hocomoco__HIF1A_HUMAN.H11MO.0.C-sima 1 0.121436 2969.49 1 6 CACCTG GCACGTCC - +4 predrem__nrMotif1260 2 0.121436 2969.49 1 6 CACCTG CCCATCTG - +4 transfac_pro__M01806-Xbp1 1 0.121436 2969.49 1 6 CACCTG ACACGTCA - +4 jaspar__MA0121.1 3 0.121436 2969.49 1 5 CACCTG GCGGATCT - +4 cisbp__M0050 4 0.121436 2969.49 1 4 CACCTG AGTGCACC + +4 hocomoco__FOXD1_HUMAN.H11MO.0.D-croc-fd59A-fkh-foxo-nej 7 0.121443 2969.64 1 6 CACCTG CTTTGTTTACTTAAG + +4 taipale_tf_pairs__HOXB2_RFX5_TAATKRNNNNGCAAC_CAP_repr-pb 4 0.121443 2969.64 1 6 CACCTG TAATTACCTAGCAAC + +4 transfac_pro__M01791 5 0.121443 2969.64 1 6 CACCTG CTCTCTGCCTAGAGC + +4 cisbp__M4431-CTCF-SMC3-usp-vtd 5 0.121443 2969.64 1 6 CACCTG AGCGCCCCCTGGTGG - +4 cisbp__M4456-CTCF-SMC3-Stat92E-usp-vtd 3 0.121443 2969.64 1 6 CACCTG CGCCCCCTGGTGGCC - +4 cisbp__M4651-CTCF-SMC3-usp-vtd 5 0.121443 2969.64 1 6 CACCTG AGCGCCCCCTGGTGG - +4 transfac_pro__M09283 0 0.121443 2969.64 1 6 CACCTG TGCCTAACTTTTTTT - +4 hocomoco__ESR1_HUMAN.H11MO.0.A-ERR-EcR-eg-kni-knrl 10 0.121443 2969.64 1 5 CACCTG AGGTCAGGGTGACCT - +4 hdpi__HSF1-Hsf 1 0.121931 2981.58 1 6 CACCTG GCACTTT + +4 stark__CACTTRA-tin-vnd 0 0.121931 2981.58 1 6 CACCTG CACTTAA + +4 transfac_pro__M02111-EcR 2 0.121931 2981.58 1 5 CACCTG GTGACCC + +4 transfac_pro__M00635 4 0.121931 2981.58 1 3 CACCTG TATTCAC - +4 hdpi__DR-1-NC2beta 0 0.122627 2998.61 1 6 CACCTG GACCTC - +4 cisbp__M6209-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.122647 2999.09 1 6 CACCTG CACCGGAAGTA + +4 cisbp__M6531-cnc-cyc-Max-Mitf-Myc-SREBP-tgo-Usf 3 0.122647 2999.09 1 6 CACCTG GCCCACGTGAC + +4 transfac_pro__M00798 3 0.122647 2999.09 1 6 CACCTG CCCCAACGGCC + +4 transfac_pro__M01821 2 0.122647 2999.09 1 6 CACCTG CCCAACTGGCG + +4 transfac_pro__M08812 5 0.122647 2999.09 1 6 CACCTG TATGCCACGTG + +4 cisbp__M1337 4 0.122647 2999.09 1 6 CACCTG TCCGAATCTAT - +4 neph__UW.Motif.0649 5 0.122647 2999.09 1 6 CACCTG GTTTTCACATG - +4 hocomoco__SMAD1_HUMAN.H11MO.0.D-Mad 0 0.12269 3000.13 1 6 CACCTG ACCCTGTCTGCC + +4 jaspar__MA0918.1 0 0.12269 3000.13 1 6 CACCTG GAGCTGTCATTT + +4 neph__UW.Motif.0493 2 0.12269 3000.13 1 6 CACCTG AATTCCAAGAAG + +4 cisbp__M0179-Mitf-tgo 3 0.12269 3000.13 1 6 CACCTG AAGCACGTGATT - +4 hocomoco__MYB_HUMAN.H11MO.0.A 1 0.12269 3000.13 1 6 CACCTG CCAACTGCCACC - +4 homer__ACAGGATGTGGT_ETS_RUNX-Ets96B-Ets97D-RunxA-RunxB-lz-run 5 0.12269 3000.13 1 6 CACCTG ACCACATCCTGT - +4 neph__UW.Motif.0370 4 0.12269 3000.13 1 6 CACCTG TCATTATCTTTG - +4 taipale_cyt_meth__CREB3L1_TGCCACGTGGCA_eDBD-Atf6-Clk-CrebA-Max-Mnt 3 0.12269 3000.13 1 6 CACCTG TGCCACGTGGCA - +4 transfac_pro__M06095 1 0.12269 3000.13 1 6 CACCTG GCACTTTTACAC - +4 transfac_pro__M06635-crol -1 0.12269 3000.13 1 5 CACCTG CCCTTGAAGGGC + +4 tiffin__TIFDMEM0000081 -1 0.12269 3000.13 1 5 CACCTG ATCTAGTTAAAA - +4 transfac_pro__M05764 7 0.12269 3000.13 1 5 CACCTG TTTGCTTCACCC - +4 transfac_pro__M05794 7 0.12269 3000.13 1 5 CACCTG TACGTCGAACCG - +4 transfac_pro__M05856 7 0.12269 3000.13 1 5 CACCTG TCTTACGCACCA - +4 transfac_pro__M05979-CG2120 7 0.12269 3000.13 1 5 CACCTG TATCTAGAACCT - +4 transfac_pro__M06601-CG6654-CG7372 7 0.12269 3000.13 1 5 CACCTG AATTCTTGACCA - +4 cisbp__M0230-Mitf-Mondo-SREBP-Usf-bigmax-cwo 2 0.122826 3003.46 1 6 CACCTG ATCACGTGA + +4 cisbp__M0909-ara-caup-mirr 2 0.122826 3003.46 1 6 CACCTG ATTACATGA + +4 cisbp__M0974 2 0.122826 3003.46 1 6 CACCTG TTAACCAGG + +4 hocomoco__BMAL1_MOUSE.H11MO.0.A-Clk-Mitf-Usf-cyc 2 0.122826 3003.46 1 6 CACCTG GTCACGTGG + +4 predrem__nrMotif689 0 0.122826 3003.46 1 6 CACCTG CTCCTGAAG + +4 predrem__nrMotif841 0 0.122826 3003.46 1 6 CACCTG CACTTTGTT + +4 predrem__nrMotif966 3 0.122826 3003.46 1 6 CACCTG GAATCCCTT + +4 yetfasco__YDR423C_2098-CG7786-Pdp1-gt-vri 1 0.122826 3003.46 1 6 CACCTG TTACGTAAT + +4 cisbp__M0175-Mnt 1 0.122826 3003.46 1 6 CACCTG GCACGTGCA - +4 cisbp__M0514-CG10348-CG13296-ham 0 0.122826 3003.46 1 6 CACCTG CCCCTATTT - +4 cisbp__M1365 3 0.122826 3003.46 1 6 CACCTG AAATATCTT - +4 hocomoco__EPAS1_HUMAN.H11MO.0.B-sima-tgo 1 0.122826 3003.46 1 6 CACCTG GTACGTGCC - +4 predrem__nrMotif363 0 0.122826 3003.46 1 6 CACCTG TCCCTTCCA - +4 predrem__nrMotif706 3 0.122826 3003.46 1 6 CACCTG TCTGACCTT - +4 predrem__nrMotif995-CTCF-SMC3-usp-vtd 3 0.122826 3003.46 1 6 CACCTG GGCCACCAG - +4 predrem__nrMotif180 4 0.122826 3003.46 1 5 CACCTG TTCTCACCA + +4 predrem__nrMotif1364 5 0.122826 3003.46 1 4 CACCTG GGTGGCACC - +4 scertf__spivak.RPN4 5 0.122826 3003.46 1 4 CACCTG TTTGCCACC - +4 transfac_pro__M03131 4 0.123699 3024.81 1 6 CACCTG GGACCAGCTGGGCCCT + +4 cisbp__M4430-CTCF-SMC3-usp-vtd 6 0.123699 3024.81 1 6 CACCTG CAGCGCCCCCTGGTGG - +4 transfac_pro__M05363-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 10 0.123699 3024.81 1 6 CACCTG GTTGAACTTTGACCTT - +4 cisbp__M5765-EcR-eg-Hnf4-kni-knrl-svp 3 0.12523 3062.26 1 6 CACCTG TGTGACCTTTTGACCTC + +4 transfac_pro__M02890 9 0.12523 3062.26 1 6 CACCTG GCTGGGGGGTACCCCTT + +4 hocomoco__COT1_HUMAN.H11MO.0.C-ERR-EcR-Hnf4-Hr51-Hr78-eg-kni-knrl-svp-usp 4 0.12523 3062.26 1 6 CACCTG CCCTGACCTCTGACCCC - +4 transfac_pro__M05422-fd59A 12 0.12523 3062.26 1 5 CACCTG ATTCCCTTGATTTACCG - +4 cisbp__M5803-EcR-eg-ham-Hr78-kni-knrl-usp 8 0.125373 3065.75 1 6 CACCTG GGGGTCATGACCCC + +4 neph__UW.Motif.0139 1 0.125373 3065.75 1 6 CACCTG CCAGCTCCTTCCCA + +4 neph__UW.Motif.0584 8 0.125373 3065.75 1 6 CACCTG TCTGAAAATTTCTG - +4 taipale_tf_pairs__FOXO1_ELF1_RWMAACAGGAAGTN_CAP_repr-Eip74EF-foxo 3 0.125373 3065.75 1 6 CACCTG TACTTCCTGTTTAC - +4 transfac_pro__M06923 1 0.125373 3065.75 1 6 CACCTG TACCCTAATTCCAC - +4 transfac_pro__M06618 9 0.125373 3065.75 1 5 CACCTG GTCCGAGGGAACCA + +4 tfdimers__MD00599-Stat92E-usp 6 0.125429 3067.11 1 6 CACCTG AAATCTGACCTTTCCCTTTAT + +4 tfdimers__MD00245-GATAe-grn-pnr-srp 11 0.125429 3067.11 1 6 CACCTG TTCTACTTCCTTATCTTTTCT - +4 transfac_pro__M09322 5 0.125429 3067.11 1 6 CACCTG TTGTTCACCTACCTTAACCAA - +4 taipale_tf_pairs__TEAD4_EOMES_RGGTGTNNNNNNNNGAATGYN_CAP_repr-sd 16 0.125429 3067.11 1 5 CACCTG CGCATTCCACCGCTCACACCT - +4 cisbp__M6433-EcR-eg-Hnf4-Hr3-Hr78-kni-knrl-svp-usp 9 0.126107 3083.7 1 6 CACCTG GTGACCTTTGACCTACTT + +4 taipale_cyt_meth__IRX3_NACGYRNNNNNNYGCGTN_eDBD_meth-ara-caup-mirr 0 0.126107 3083.7 1 6 CACCTG TACGTGATTTAACGCGTA + +4 cisbp__M4587-CTCF-SMC3-usp-vtd 8 0.126107 3083.7 1 6 CACCTG TATAGCGCCCTCTGGTGG - +4 cisbp__M4588-Chd1-CTCF-SMC3-usp-vtd 6 0.126107 3083.7 1 6 CACCTG TAGCGCCCCCTGGTGGCC - +4 taipale_cyt_meth__T_NTCACACNTANGTGTGAN_eDBD-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.126107 3083.7 1 6 CACCTG TTCACACCTAGGTGTGAA - +4 transfac_pro__M06197-crol 12 0.126107 3083.7 1 6 CACCTG CACATTCCGATCCAACTC - +4 transfac_pro__M06899 2 0.126107 3083.7 1 6 CACCTG CCCACCTCGTCCCACCCC - +4 dbcorrdb__ARID3A__ENCSR000EFY_1__m2-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCTCTGGTGGTAA + +4 dbcorrdb__CTCF__ENCSR000DKZ_1__m1-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.12615 3084.74 1 6 CACCTG CTCTAGCGCCCCCTGGTGGC + +4 dbcorrdb__CTCF__ENCSR000DMO_1__m1-CTCF-SMC3-usp-vtd 6 0.12615 3084.74 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC + +4 dbcorrdb__CTCF__ENCSR000DRF_2__m1-CTCF-SMC3-usp-vtd 5 0.12615 3084.74 1 6 CACCTG GGCGCCCCCTGGTGGCCGCG + +4 dbcorrdb__CTCF__ENCSR000DRI_1__m1-Chd1-CTCF-SMC3-usp-vtd 9 0.12615 3084.74 1 6 CACCTG CTCTAGCGCCCCCTGGTGGC + +4 dbcorrdb__CTCF__ENCSR000DRK_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DYD_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m2-RpII215 4 0.12615 3084.74 1 6 CACCTG TTTCCACCCAAGAGCAGATA + +4 dbcorrdb__RAD21__ENCSR000BKV_1__m1-CTCF-SMC3-usp-vtd 12 0.12615 3084.74 1 6 CACCTG GGCCTATGGCGCCCCCTGGT + +4 dbcorrdb__RAD21__ENCSR000DYE_1__m1-CTCF-SMC3-usp-vtd 6 0.12615 3084.74 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__RELA__ENCSR000EAG_1__m1-Dif-dl-Rel-shn 11 0.12615 3084.74 1 6 CACCTG ACCTTGGAAATCCCCTAATT + +4 dbcorrdb__RELA__ENCSR000EBD_1__m1-Dif-dl-Rel-shn 10 0.12615 3084.74 1 6 CACCTG CCTGGGAAATCCCCTACCCC + +4 cisbp__M5882-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.12615 3084.74 1 6 CACCTG TTTCACACCTAGGTGTGAAA - +4 dbcorrdb__CTCF__ENCSR000AKO_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DLE_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ACGGCGCCCCCTGGTGGCCG - +4 dbcorrdb__CTCF__ENCSR000DLF_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.12615 3084.74 1 6 CACCTG TCTGGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DLK_1__m1-CTCF-SMC3-usp-vtd 6 0.12615 3084.74 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__CTCF__ENCSR000DMH_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DMV_1__m1-CTCF-SMC3-usp-vtd 6 0.12615 3084.74 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__CTCF__ENCSR000DND_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.12615 3084.74 1 6 CACCTG TATAGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DRF_1__m1-CTCF-SMC3-usp-vtd 5 0.12615 3084.74 1 6 CACCTG AGCGCCCCCTGGTGGCCACA - +4 dbcorrdb__CTCF__ENCSR000DRJ_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DRL_2__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.12615 3084.74 1 6 CACCTG CTAGCGCCCCCTGGTGGCCG - +4 dbcorrdb__SMC3__ENCSR000EDW_1__m1-CTCF-SMC3-usp-vtd 6 0.12615 3084.74 1 6 CACCTG TAGTGCCCCCTGGTGGCCAA - +4 taipale__TBX19_DBD_NNTCRCACNTANGTGYGANN_repr-byn-Doc1-Doc2-Doc3-H15-mid-org-1 5 0.12615 3084.74 1 6 CACCTG TTTCACACCTAGGTGTGAAA - +4 taipale_tf_pairs__GCM1_NHLH1_NCAGCTGNNNNNNNTRCGGG_CAP_repr-gcm-gcm2-HLH4C 13 0.12615 3084.74 1 6 CACCTG CCCGCATGGGCCGCAGCTGC - +4 taipale_tf_pairs__HOXB2_ESRRB_TAATKNNNNNNNNAAGGTCA_CAP_repr-ERR-pb 1 0.12615 3084.74 1 6 CACCTG TGACCTTGAAATCGTAATTA - +4 taipale__ZNF232_full_RTGTTAAAYGTAGATTAAG_repr 7 0.126394 3090.72 1 6 CACCTG CTTAATCTACATTTAACAT - +4 cisbp__M0154-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn-Sirt6-bigmax-cyc-dpn-h-tgo 2 0.127475 3117.15 1 6 CACCTG GGCACGTGCC + +4 cisbp__M4905-CG8319-da-HLH54F-tx 2 0.127475 3117.15 1 6 CACCTG ACCACCTGTT + +4 cisbp__M6349 2 0.127475 3117.15 1 6 CACCTG TCAACCTGCA + +4 flyfactorsurvey__Lag1_Cell_FBgn0040918-schlank 1 0.127475 3117.15 1 6 CACCTG CTACCAAAAT + +4 hocomoco__TFE3_HUMAN.H11MO.0.B-Clk-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo 3 0.127475 3117.15 1 6 CACCTG GGTCACGTGA + +4 jaspar__MA0965.1-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-SREBP-Sidpn-Sirt6-bigmax-cyc-dpn-h-tgo 2 0.127475 3117.15 1 6 CACCTG GGCACGTGCC + +4 predrem__nrMotif1788 4 0.127475 3117.15 1 6 CACCTG TTCAAACATT + +4 predrem__nrMotif2159 4 0.127475 3117.15 1 6 CACCTG TGCTCACCCA + +4 predrem__nrMotif2401 3 0.127475 3117.15 1 6 CACCTG TATCACTTTA + +4 taipale_cyt_meth__NKX2-3_NCCACTTRAN_eDBD_meth-bap-scro-vnd 2 0.127475 3117.15 1 6 CACCTG ACCACTTGAC + +4 transfac_pro__M00367-Atf6-Clk-CrebA-Usf 2 0.127475 3117.15 1 6 CACCTG GCCACGTGGC + +4 transfac_pro__M07375-Stat92E 0 0.127475 3117.15 1 6 CACCTG TTCCTAGAAA + +4 cisbp__M0435 2 0.127475 3117.15 1 6 CACCTG TTCACTTCCT - +4 cisbp__M0470 3 0.127475 3117.15 1 6 CACCTG TGGACCCTTA - +4 cisbp__M0783-GATAd-GATAe-grn-pnr-srp 2 0.127475 3117.15 1 6 CACCTG CTTATCTCTT - +4 cisbp__M0947-bap-scro-vnd 3 0.127475 3117.15 1 6 CACCTG AACCACTTAA - +4 swissregulon__hs__HMX1.p2-Hmx 4 0.127475 3117.15 1 6 CACCTG CACGCACTTG - +4 predrem__nrMotif150 5 0.127475 3117.15 1 5 CACCTG CTGCTGACCC + +4 taipale_cyt_meth__DPRX_NGMTAATCCN_eDBD_meth 5 0.127475 3117.15 1 5 CACCTG GGGATTATCT - +4 transfac_pro__M05155 6 0.127475 3117.15 1 4 CACCTG TTTTAACACC + +4 swissregulon__sacCer__RPN4 6 0.127475 3117.15 1 4 CACCTG TTTTGCCACC - +4 cisbp__M0245-Clk-cnc-cyc-Max-Mitf-SREBP-tai-tgo-Usf 2 0.127994 3129.83 1 6 CACCTG GTCACGTG + +4 cisbp__M0973 2 0.127994 3129.83 1 6 CACCTG TTAACTAG + +4 cisbp__M2361-Hey-Max-Mnt-Myc 1 0.127994 3129.83 1 6 CACCTG GCACGTGC + +4 jaspar__MA0270.1 2 0.127994 3129.83 1 6 CACCTG CACACCCC + +4 jaspar__MA0566.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-Mnt 1 0.127994 3129.83 1 6 CACCTG GCACGTGC + +4 jaspar__MA0568.1-Hey-Max-Mnt-Myc 1 0.127994 3129.83 1 6 CACCTG GCACGTGC + +4 predrem__nrMotif798 1 0.127994 3129.83 1 6 CACCTG AGCCCTTG + +4 transfac_pro__M00971-aop-Atac3-Dif-dl-Eip74EF-Ets96B-Ets97D-Rpn5 2 0.127994 3129.83 1 6 CACCTG ACTTCCTC + +4 transfac_pro__M07384-sima 1 0.127994 3129.83 1 6 CACCTG GCACGTGG + +4 cisbp__M0986-ara-caup-mirr 2 0.127994 3129.83 1 6 CACCTG ATTACATG - +4 transfac_pro__M01152-usp 1 0.127994 3129.83 1 6 CACCTG TGAACTTT - +4 transfac_pro__M08979-EcR 2 0.127994 3129.83 1 6 CACCTG TGAACTCA - +4 predrem__nrMotif215 3 0.127994 3129.83 1 5 CACCTG TTGTGCCT + +4 hdpi__RPP25-CG9422 -1 0.127994 3129.83 1 5 CACCTG AGCTGCCA - +4 neph__UW.Motif.0194 7 0.128219 3135.35 1 6 CACCTG TGAGAAATTTCTG - +4 neph__UW.Motif.0388 8 0.128219 3135.35 1 5 CACCTG AACATGCCTTTCT + +4 bergman__tin-tin-vnd 0 0.128504 3142.3 1 6 CACCTG CACTTAA + +4 jaspar__MA0409.1-Clk-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cyc-tgo 0 0.128504 3142.3 1 6 CACCTG CACGTGA + +4 predrem__nrMotif42 1 0.128504 3142.3 1 6 CACCTG AAGCCTG + +4 swissregulon__sacCer__GIS1-Kdm4A-Kdm4B 0 0.128504 3142.3 1 6 CACCTG CCCCTAA + +4 predrem__nrMotif1259 0 0.128504 3142.3 1 6 CACCTG GACCTCC - +4 predrem__nrMotif231 0 0.128504 3142.3 1 6 CACCTG TTCCTCT - +4 stark__ACATGTK-twi 0 0.128504 3142.3 1 6 CACCTG AACATGT - +4 transfac_pro__M01954-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 0.128504 3142.3 1 6 CACCTG CACGTGA - +4 predrem__nrMotif1213 2 0.128504 3142.3 1 5 CACCTG ATGAACT - +4 predrem__nrMotif1613 3 0.128504 3142.3 1 4 CACCTG TTAAACC + +4 predrem__nrMotif845 3 0.128504 3142.3 1 4 CACCTG AAAAACC - +4 cisbp__M2320-TfAP-2 1 0.128643 3145.71 1 6 CACCTG TGCCCTGGGGCCATG + +4 cisbp__M5761-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.128643 3145.71 1 6 CACCTG TGACCTTTTGACCCT + +4 neph__UW.Motif.0238 6 0.128643 3145.71 1 6 CACCTG CTGAAAATCCTGGCC + +4 cisbp__M4437-CTCF-SMC3-usp-vtd 4 0.128643 3145.71 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4446-CTCF-SMC3-usp-vtd 4 0.128643 3145.71 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4447-CTCF-SMC3-usp-vtd 4 0.128643 3145.71 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4455-CTCF-SMC3-usp-vtd 2 0.128643 3145.71 1 6 CACCTG GCCCCCTGGTGGCCA - +4 homer__GGTCANYTGAGGWCA_THRa-EcR 1 0.128643 3145.71 1 6 CACCTG TGACCTCAGATGACC - +4 neph__UW.Motif.0058 9 0.128643 3145.71 1 6 CACCTG CTGCAGGGGCCGCTG - +4 taipale__RARA_full_ARGGTCAAAAGGTCA-EcR-eg-Hnf4-kni-knrl-svp-usp 1 0.128643 3145.71 1 6 CACCTG TGACCTTTTGACCCT - +4 transfac_pro__M07137-TfAP-2 1 0.128643 3145.71 1 6 CACCTG TGCCCTGGGGCCATG - +4 transfac_pro__M07970-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 8 0.128643 3145.71 1 6 CACCTG TGACCTTTGACCTTT - +4 transfac_pro__M01181 0 0.12933 3162.51 1 6 CACCTG CACTTA - +4 cisbp__M0867 3 0.129541 3167.67 1 6 CACCTG AGTGACACG + +4 predrem__nrMotif2644 1 0.129541 3167.67 1 6 CACCTG TTACCATAA + +4 predrem__nrMotif596 2 0.129541 3167.67 1 6 CACCTG TTTACTTTG + +4 stark__MACMDGTTK 0 0.129541 3167.67 1 6 CACCTG AACATGTTG + +4 transfac_pro__M01838-CrebA 0 0.129541 3167.67 1 6 CACCTG GACGTGGCA + +4 transfac_pro__M07925-CG4424 0 0.129541 3167.67 1 6 CACCTG CACCCACCC + +4 cisbp__M0785-GATAd-GATAe-grn-pnr-srp 3 0.129541 3167.67 1 6 CACCTG CCTTATCTG - +4 predrem__nrMotif1983 1 0.129541 3167.67 1 6 CACCTG GAACCTCAG - +4 predrem__nrMotif2337 0 0.129541 3167.67 1 6 CACCTG CACCATGCC - +4 predrem__nrMotif476 2 0.129541 3167.67 1 6 CACCTG CCCACCACA - +4 transfac_pro__M07963-ERR-Hr39 2 0.129541 3167.67 1 6 CACCTG ATGACCTTG - +4 predrem__nrMotif1966 -1 0.129541 3167.67 1 5 CACCTG TCCTGGTTG + +4 predrem__nrMotif2614 -1 0.129541 3167.67 1 5 CACCTG ATCTGGGAA + +4 predrem__nrMotif1054 4 0.129541 3167.67 1 5 CACCTG TGGAATCCT - +4 transfac_pro__M07696-dmrt93B 5 0.129616 3169.49 1 6 CACCTG AATGATACATT + +4 transfac_pro__M08813-CrebA 3 0.129616 3169.49 1 6 CACCTG GTACACGTGGC + +4 cisbp__M1489 5 0.129733 3172.36 1 6 CACCTG ATGTGTACTTTC + +4 cisbp__M5911-TfAP-2 0 0.129733 3172.36 1 6 CACCTG TGCCCGGGGGCA + +4 homer__ATGCCCTGAGGC_AP-2alpha-GATAe-TfAP-2-grn-pnr 2 0.129733 3172.36 1 6 CACCTG ATGCCCTGAGGC + +4 taipale__ZBTB7C_full_NCGACCACCNAN 5 0.129733 3172.36 1 6 CACCTG GCGACCACCGAA + +4 taipale_cyt_meth__DMRTC2_WWTTGNTACATN_FL-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.129733 3172.36 1 6 CACCTG AATTGATACATT + +4 cisbp__M5962 5 0.129733 3172.36 1 6 CACCTG GCGACCACCGAA - +4 neph__UW.Motif.0140 5 0.129733 3172.36 1 6 CACCTG GGGAGGGGCTGC - +4 predrem__nrMotif2529 6 0.129733 3172.36 1 6 CACCTG GGGTGGGACCTG - +4 taipale__TFAP2A_DBD_NGCCNNNNGGCN-TfAP-2 0 0.129733 3172.36 1 6 CACCTG TGCCCGGGGGCA - +4 transfac_pro__M06393 1 0.129733 3172.36 1 6 CACCTG TCCCCTTGCCAG - +4 neph__UW.Motif.0409 7 0.129733 3172.36 1 5 CACCTG AGTTTTCTTCTT - +4 transfac_pro__M05506 7 0.129733 3172.36 1 5 CACCTG TTTCTTGTACCA - +4 transfac_pro__M05776 7 0.129733 3172.36 1 5 CACCTG TTTTCTTCACCA - +4 transfac_pro__M05892-CG12299-CG31365-dati 7 0.129733 3172.36 1 5 CACCTG TCCGCCGTACCA - +4 transfac_pro__M06386 7 0.129733 3172.36 1 5 CACCTG CTGGCTTCACCA - +4 transfac_pro__M06554 7 0.129733 3172.36 1 5 CACCTG TCGGAAGCACCA - +4 transfac_pro__M06978-salm-salr -2 0.129733 3172.36 1 4 CACCTG CCTTTTATCAGC + +4 tfdimers__MD00514-pho-phol-scro 14 0.130749 3197.2 1 6 CACCTG CTTCTGCCATCTGGCTCTTGAGGGCTTCT + +4 neph__UW.Motif.0166 3 0.131073 3205.13 1 6 CACCTG AAATTTCTGCCTTTCT + +4 neph__UW.Motif.0363 2 0.131073 3205.13 1 6 CACCTG AAAGCCTGGATTTTCA + +4 taipale_cyt_meth__GMEB1_NKACGTNNNNACGTMN_FL_meth_repr 1 0.131073 3205.13 1 6 CACCTG TTACGTAATTACGTAA + +4 taipale_tf_pairs__PITX1_FIGLA_TAATCCNNNNCASSTG_CAP_repr-Ptx1 10 0.131073 3205.13 1 6 CACCTG TAATCCCTTACACCTG + +4 transfac_pro__M01392-abd-A-Antp-bsh-btn-lab-pb-Scr-Ubx 8 0.131073 3205.13 1 6 CACCTG AAGGTAATTACCTAAT + +4 neph__UW.Motif.0278 6 0.131073 3205.13 1 6 CACCTG TGCCTCTCCCTGGCCT - +4 neph__UW.Motif.0300 0 0.131073 3205.13 1 6 CACCTG TATCTTTATATTTCAG - +4 tfdimers__MD00493-cnc 18 0.131695 3220.35 1 6 CACCTG ATAAACTAAATTAATGACTAACTGGCTAATA + +4 taipale_cyt_meth__RORB_NAWNTRGGTCRTGACCYANWTN_eDBD_meth-Hr3-usp 12 0.132052 3229.08 1 6 CACCTG TAAGTAGGTCGTGACCTAGTTA + +4 hocomoco__ETV3_HUMAN.H11MO.0.D-Ets21C 8 0.132679 3244.41 1 6 CACCTG TACGTTTGCACTTC + +4 neph__UW.Motif.0205 1 0.132679 3244.41 1 6 CACCTG AAGCCTGTGTTCTG + +4 neph__UW.Motif.0462 5 0.132679 3244.41 1 6 CACCTG CTTTCCATTTGTCA + +4 neph__UW.Motif.0613 2 0.132679 3244.41 1 6 CACCTG CAGAACTGTCTTCC + +4 taipale__ZNF524_full_CTCGRACCCGTGCN_repr 4 0.132679 3244.41 1 6 CACCTG CTCGAACCCGTGCC + +4 cisbp__M5975 4 0.132679 3244.41 1 6 CACCTG CTCGAACCCGTGCC - +4 flyfactorsurvey__CG8319-F3-5-SOLEXA_5-CG8319-Oli-ato-da-net-tx 5 0.132679 3244.41 1 6 CACCTG ACGACCATCTGGCA - +4 neph__UW.Motif.0322 5 0.132679 3244.41 1 6 CACCTG TTTTCTCCTTTCTG - +4 taipale_tf_pairs__GCM1_FOXO1_GTMAATAAGGGYRN_CAP-foxo-gcm-gcm2 1 0.132679 3244.41 1 6 CACCTG GTACCCTTATTGAC - +4 cisbp__M6444-EcR-usp 1 0.132743 3245.97 1 6 CACCTG TGACCTCTCGGTGACCT + +4 cisbp__M6321-Klf15 5 0.132743 3245.97 1 6 CACCTG GCCCCCACCTCCCCGCC - +4 hocomoco__RARA_HUMAN.H11MO.2.A-EcR-usp 1 0.132743 3245.97 1 6 CACCTG TGACCTCTCGGTGACCT - +4 transfac_pro__M01346-achi-esg-sna-vis-wor 3 0.132743 3245.97 1 6 CACCTG ACGCAGCTGTCAATATA - +4 cisbp__M4518-CTCF-SMC3-usp-vtd 5 0.133726 3270.01 1 6 CACCTG GGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000AQU_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000BHW_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.133895 3274.14 1 6 CACCTG TATAGCGCCCCCTGGTGGCC + +4 dbcorrdb__CTCF__ENCSR000BNO_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DMR_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DMY_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DNA_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATGGCGCCCCCTGGTGGCCG + +4 dbcorrdb__CTCF__ENCSR000DQD_1__m1-CTCF-SMC3-usp-vtd 6 0.133895 3274.14 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__CTCF__ENCSR000DRH_2__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG CTAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DUS_1__m1-CTCF-SMC3-usp-vtd 6 0.133895 3274.14 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DXI_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DZN_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__RAD21__ENCSR000BLS_1__m1-CTCF-SMC3-usp-vtd 6 0.133895 3274.14 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__REST__ENCSR000BJO_1__m2-CTCF-Sin3A 9 0.133895 3274.14 1 6 CACCTG CTGGTTCAGCACCACGGACA + +4 dbcorrdb__TCF7L2__ENCSR000EVF_1__m2-pan 5 0.133895 3274.14 1 6 CACCTG TGCAGTTCCTTTCATCTGGC + +4 cisbp__M4580-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCFL__ENCSR000BNK_1__m1-Chd1-CTCF-Hcf-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG CCGGCGCCCCCTGGTGGCCG - +4 dbcorrdb__CTCF__ENCSR000ALJ_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000BPJ_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DLG_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.133895 3274.14 1 6 CACCTG TCTAGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DMA_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DMF_1__m1-CTCF-SMC3-usp-vtd 6 0.133895 3274.14 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DRH_1__m1-CTCF-SMC3-usp-vtd 5 0.133895 3274.14 1 6 CACCTG AGCGCCCCCTGGTGGCCACA - +4 dbcorrdb__CTCF__ENCSR000DRL_1__m1-CTCF-SMC3-usp-vtd 5 0.133895 3274.14 1 6 CACCTG AGCGCCCCCTGGTGGCCACA - +4 dbcorrdb__CTCF__ENCSR000DRP_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DUG_1__m1-CTCF-SMC3-usp-vtd 6 0.133895 3274.14 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DWX_1__m1-Chd1-CTCF-SMC3-usp-vtd 9 0.133895 3274.14 1 6 CACCTG CTATAGCGCCCCCTGGTGGC - +4 dbcorrdb__CTCF__ENCSR000EIC_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__HSF1__ENCSR000EET_1__m1-Brf-CG17209-Hsf-SREBP 8 0.133895 3274.14 1 6 CACCTG GGGTCTCGAACCTTCGACCC - +4 dbcorrdb__RAD21__ENCSR000ECE_1__m1-CTCF-SMC3-usp-vtd 12 0.133895 3274.14 1 6 CACCTG GGCCTATAGTGCCCCCTGGT - +4 dbcorrdb__RAD21__ENCSR000FAD_1__m1-CTCF-SMC3-usp-vtd 7 0.133895 3274.14 1 6 CACCTG ATAGTGCCCCCTGGTGGCCA - +4 hocomoco__RXRA_HUMAN.H11MO.0.A-EcR-eg-kni-knrl-svp-usp 4 0.133895 3274.14 1 6 CACCTG CTCTGACCTCTGCCTCCCCC - +4 hocomoco__PRDM9_MOUSE.H11MO.0.C 10 0.13409 3278.9 1 6 CACCTG AAGATGGCAGCAGCATCTG + +4 cisbp__M4510-CG9727-Rfx 2 0.13409 3278.9 1 6 CACCTG TCTGCCTAGCAACAGGTGA - +4 hocomoco__CTCF_HUMAN.H11MO.0.A-CTCF-Chd1-SMC3-usp-vtd 6 0.13409 3278.9 1 6 CACCTG TGGCGCCCCCTGGTGGCCA - +4 taipale_tf_pairs__GCM1_FIGLA_CAGCTGNNNNNNNTGCGGG_CAP-gcm-gcm2 13 0.13409 3278.9 1 6 CACCTG CCCGCATTAGCGCCACCTG - +4 transfac_pro__M06086 13 0.13409 3278.9 1 6 CACCTG GAGGATGCGAACTCACCAC - +4 tfdimers__MD00602-Stat92E 14 0.134106 3279.28 1 6 CACCTG AAAAAAGGAAATCACAACTGCCTATTAA - +4 tfdimers__MD00332-Pur-alpha 10 0.134407 3286.66 1 6 CACCTG CCCCCCCGCGCCCCTGCCCCCCCCC - +4 cisbp__M0231-Mitf-Mondo-SREBP-Usf-bigmax 2 0.134529 3289.64 1 6 CACCTG ATCACGTGAT + +4 cisbp__M0248-Mitf-SREBP-Usf 3 0.134529 3289.64 1 6 CACCTG CATCACGTGA + +4 cisbp__M1834 4 0.134529 3289.64 1 6 CACCTG ATTTCTCCGA + +4 cisbp__M6396-ERR-ftz-f1-Hr4 1 0.134529 3289.64 1 6 CACCTG TGGCCTTGAA + +4 hocomoco__BHE40_HUMAN.H11MO.0.A-Sirt6 2 0.134529 3289.64 1 6 CACCTG GGCACGTGAC + +4 predrem__nrMotif1186 3 0.134529 3289.64 1 6 CACCTG AGTGCCCTCT + +4 predrem__nrMotif1826 4 0.134529 3289.64 1 6 CACCTG CTGGAGCCTG + +4 transfac_pro__M01874-CG42741 3 0.134529 3289.64 1 6 CACCTG CCACACCCTG + +4 cisbp__M0476 2 0.134529 3289.64 1 6 CACCTG TTGGCCTCCC - +4 cisbp__M0636-dmrt11E-dmrt93B-dmrt99B-dsx 4 0.134529 3289.64 1 6 CACCTG TTGATACATT - +4 cisbp__M1314 3 0.134529 3289.64 1 6 CACCTG CCTTATCCAT - +4 cisbp__M5069-schlank 1 0.134529 3289.64 1 6 CACCTG CTACCAAAAT - +4 jaspar__MA0931.1-Atf6-Clk-Met-Myc 1 0.134529 3289.64 1 6 CACCTG CCACGTGTCA - +4 transfac_pro__M02267-kn 0 0.134529 3289.64 1 6 CACCTG TCCCTTGGGT - +4 transfac_pro__M07550 4 0.134529 3289.64 1 6 CACCTG GCTTGACCGA - +4 taipale_cyt_meth__ZBTB7B_NCGACCMCCN_eDBD 5 0.134529 3289.64 1 5 CACCTG GCGACCACCG + +4 predrem__nrMotif2354 -2 0.134529 3289.64 1 4 CACCTG CCTCGGTCCC - +4 cisbp__M0871-ara-caup-mirr 2 0.134842 3297.29 1 6 CACCTG ATTACAAG + +4 cisbp__M1130 2 0.134842 3297.29 1 6 CACCTG TTTACACG + +4 cisbp__M1764 0 0.134842 3297.29 1 6 CACCTG CTCCGGAC + +4 cisbp__M1793 2 0.134842 3297.29 1 6 CACCTG ATATCCGG + +4 homer__GHCACGTG_CLOCK-Clk-Usf 2 0.134842 3297.29 1 6 CACCTG GTCACGTG + +4 predrem__nrMotif1098 0 0.134842 3297.29 1 6 CACCTG CACTTAAA + +4 swissregulon__sacCer__YAP3 2 0.134842 3297.29 1 6 CACCTG ATTACGTA + +4 transfac_pro__M01611 2 0.134842 3297.29 1 6 CACCTG CACACCCC + +4 transfac_pro__M09553 2 0.134842 3297.29 1 6 CACCTG AATATCTT + +4 cisbp__M0533-CG10348-CG13296-ham 2 0.134842 3297.29 1 6 CACCTG TACCCCTT - +4 cisbp__M1864-croc 0 0.134842 3297.29 1 6 CACCTG TACTTACC - +4 flyfactorsurvey__Kr_SANGER_5_FBgn0001325-Kr 0 0.134842 3297.29 1 6 CACCTG TACCCTTC - +4 predrem__nrMotif1277 2 0.134842 3297.29 1 6 CACCTG TGGAACTG - +4 predrem__nrMotif2677 1 0.134842 3297.29 1 6 CACCTG AAACCTAA - +4 predrem__nrMotif500 1 0.134842 3297.29 1 6 CACCTG GCTCCTTG - +4 transfac_pro__M09582 0 0.134842 3297.29 1 6 CACCTG CGCCGGCA - +4 predrem__nrMotif1236 -1 0.134842 3297.29 1 5 CACCTG CCCTGTTG + +4 predrem__nrMotif1648 3 0.134842 3297.29 1 5 CACCTG CCCAACTT + +4 cisbp__M1941 3 0.134842 3297.29 1 5 CACCTG GCGGATCT - +4 predrem__nrMotif2329 3 0.134842 3297.29 1 5 CACCTG GCTCATCT - +4 predrem__nrMotif796 -1 0.134842 3297.29 1 5 CACCTG AGCTCAAG - +4 transfac_pro__M01049-ci -1 0.134842 3297.29 1 5 CACCTG ACCACCCA - +4 transfac_pro__M05545 3 0.134842 3297.29 1 5 CACCTG GATAACCA - +4 jaspar__MA0342.1-CG10348-CG13296-ham 0 0.135006 3301.29 1 5 CACCTG CCCCT - +4 transfac_pro__M01952-CG10348-CG13296-ham 0 0.135006 3301.29 1 5 CACCTG CCCCT - +4 yetfasco__YKL062W_518-CG10348-CG13296-ham 0 0.135006 3301.29 1 5 CACCTG CCCCT - +4 predrem__nrMotif2172 1 0.135385 3310.56 1 6 CACCTG ATTCCTT - +4 transfac_pro__M06203-CG9609 0 0.135385 3310.56 1 6 CACCTG CACCCTG - +4 predrem__nrMotif2162 -1 0.135385 3310.56 1 5 CACCTG ACATGGA + +4 predrem__nrMotif2197 2 0.135385 3310.56 1 5 CACCTG ATCACCA - +4 predrem__nrMotif1603 -2 0.135385 3310.56 1 4 CACCTG CCTAAAA - +4 predrem__nrMotif2026 -2 0.135385 3310.56 1 4 CACCTG CCTAAAG - +4 hocomoco__BCL6_HUMAN.H11MO.0.A 0 0.135582 3315.39 1 6 CACCTG TTCCTAGAAAGCA - +4 neph__UW.Motif.0550 4 0.135582 3315.39 1 6 CACCTG TTTTTCCTTTTCA - +4 transfac_pro__M00443 2 0.135582 3315.39 1 6 CACCTG TCCACGTCAACTG - +4 tfdimers__MD00157-C15 20 0.136097 3327.97 1 6 CACCTG ATAAATAATTAATTAATAACTAACTGGTTTATAA + +4 neph__UW.Motif.0112 9 0.13617 3329.76 1 6 CACCTG CAGATGATATTTCTG + +4 neph__UW.Motif.0319 8 0.13617 3329.76 1 6 CACCTG AGAAAAAACAGTTTC + +4 neph__UW.Motif.0668 5 0.13617 3329.76 1 6 CACCTG TCTGTCATTTTTTCA + +4 taipale_cyt_meth__ZFP1_NTTTTATACCCAGCN_eDBD-CG4730-CG7101 6 0.13617 3329.76 1 6 CACCTG CTTTTATACCCAGCT + +4 cisbp__M4435-Chd1-CTCF-SMC3-usp-vtd 4 0.13617 3329.76 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4436-CTCF-SMC3-usp-vtd 4 0.13617 3329.76 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4485-CG12018-Dif-dl-Rel-shn 9 0.13617 3329.76 1 6 CACCTG CTGGGAAATCCCCTA - +4 cisbp__M4503-CTCF-SMC3-usp-vtd 4 0.13617 3329.76 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4517-CTCF-SMC3-usp-vtd 4 0.13617 3329.76 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M6125-CTCF-SMC3-usp-vtd 5 0.13617 3329.76 1 6 CACCTG AGCGCCCCCTGGTGG - +4 neph__UW.Motif.0242 0 0.13617 3329.76 1 6 CACCTG TCCCCGGGCCCCAGC - +4 yetfasco__YCR039C_1364 -1 0.136347 3334.09 1 5 CACCTG ACATGT + +4 transfac_pro__M01701 1 0.136347 3334.09 1 5 CACCTG TTACGT - +4 predrem__nrMotif1004 1 0.136532 3338.62 1 6 CACCTG TGAACTGCA + +4 predrem__nrMotif1291 3 0.136532 3338.62 1 6 CACCTG TGTAACATT + +4 predrem__nrMotif2013 1 0.136532 3338.62 1 6 CACCTG TCAACTGAA + +4 predrem__nrMotif2097 2 0.136532 3338.62 1 6 CACCTG TTTAGCTGG + +4 predrem__nrMotif2417 1 0.136532 3338.62 1 6 CACCTG TGACTTTCA + +4 transfac_pro__M09546-Myb 0 0.136532 3338.62 1 6 CACCTG TAACGGACA + +4 cisbp__M1303 3 0.136532 3338.62 1 6 CACCTG AAATATCTA - +4 predrem__nrMotif1319 0 0.136532 3338.62 1 6 CACCTG TATCTGTAA - +4 predrem__nrMotif1919 0 0.136532 3338.62 1 6 CACCTG CTCCTGGAA - +4 predrem__nrMotif1938 0 0.136532 3338.62 1 6 CACCTG TTCCTAGAA - +4 predrem__nrMotif2424 2 0.136532 3338.62 1 6 CACCTG AGCAACTGG - +4 scertf__harbison.GLN3-GATAd-GATAe-grn-pnr-srp 0 0.136532 3338.62 1 6 CACCTG TATCTTATC - +4 transfac_public__M00449-opa 3 0.136532 3338.62 1 6 CACCTG GACCACCCC - +4 predrem__nrMotif250 4 0.136532 3338.62 1 5 CACCTG CCTGGACCC + +4 predrem__nrMotif2551 4 0.136532 3338.62 1 5 CACCTG CGCGCACCC + +4 predrem__nrMotif945 -1 0.136532 3338.62 1 5 CACCTG ACTTGGCTT + +4 predrem__nrMotif1898 4 0.136532 3338.62 1 5 CACCTG AAGTTACCT - +4 predrem__nrMotif246 -1 0.136532 3338.62 1 5 CACCTG TCCTGCAGC - +4 predrem__nrMotif507 5 0.136532 3338.62 1 4 CACCTG GAGGGCACC - +4 cisbp__M0002 4 0.136885 3347.24 1 6 CACCTG ATTGCACCCGG + +4 cisbp__M4552-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 3 0.136885 3347.24 1 6 CACCTG GGTCACGTGAC + +4 hocomoco__BMAL1_HUMAN.H11MO.0.A-Clk-cyc 3 0.136885 3347.24 1 6 CACCTG AGTCACGTGGC + +4 predrem__nrMotif2499 0 0.136885 3347.24 1 6 CACCTG AAACTGTATTT + +4 cisbp__M4582-CTCF-SMC3-usp-vtd 1 0.136885 3347.24 1 6 CACCTG CCCTCTAGTGG - +4 factorbook__TCF12-ac-ase-dimm-l(1)sc-nau-sc 1 0.136885 3347.24 1 6 CACCTG ACAGCTGCTGT - +4 hocomoco__GCM2_HUMAN.H11MO.0.D-gcm-gcm2 1 0.136885 3347.24 1 6 CACCTG ATACCCGCATC - +4 transfac_pro__M07335-so 3 0.136885 3347.24 1 6 CACCTG AGAAACCTGAG - +4 cisbp__M5923-TfAP-2 0 0.137093 3352.34 1 6 CACCTG TGCCCCAGGGCA + +4 hocomoco__GRHL2_HUMAN.H11MO.0.A-grh 0 0.137093 3352.34 1 6 CACCTG AACCTGTTTGAC + +4 taipale__IRX5_DBD_NWACAYRACAWN-ara-caup-mirr 1 0.137093 3352.34 1 6 CACCTG TTACATGACATG + +4 taipale__TFAP2C_full_NGCCNNNNGGCN-TfAP-2 0 0.137093 3352.34 1 6 CACCTG TGCCCCAGGGCA + +4 taipale_cyt_meth__CREB3L1_TGCCACGTGGCA_FL_meth-Atf6-Clk-CrebA 3 0.137093 3352.34 1 6 CACCTG TGCCACGTGGCA + +4 taipale_cyt_meth__CREB3L1_TGCCACGTGGCA_eDBD_meth-Atf6-Clk-CrebA 3 0.137093 3352.34 1 6 CACCTG TGCCACGTGGCA + +4 transfac_pro__M05884 2 0.137093 3352.34 1 6 CACCTG ATAACCTTTTCT + +4 cisbp__M4586-CTCF-SMC3-usp-vtd 3 0.137093 3352.34 1 6 CACCTG CGCCCCCTGGTG - +4 cisbp__M5582-ara-caup-mirr 1 0.137093 3352.34 1 6 CACCTG TTACATGACATG - +4 hocomoco__MYB_MOUSE.H11MO.0.A-Myb 1 0.137093 3352.34 1 6 CACCTG CCAACTGCCACC - +4 neph__UW.Motif.0043 6 0.137093 3352.34 1 6 CACCTG CAGATCTTCCTG - +4 transfac_pro__M00794-scro 2 0.137093 3352.34 1 6 CACCTG GCCACTTGAGGG - +4 transfac_pro__M00796-Max-Usf 3 0.137093 3352.34 1 6 CACCTG GGTCACGTGGTC - +4 transfac_pro__M05973 6 0.137093 3352.34 1 6 CACCTG TCCTTTAACCAT - +4 transfac_pro__M06057 6 0.137093 3352.34 1 6 CACCTG TCTAATAACCGA - +4 transfac_pro__M06429 6 0.137093 3352.34 1 6 CACCTG GCGGCTTTCCTC - +4 transfac_pro__M07299-Myb 2 0.137093 3352.34 1 6 CACCTG CCCAACTGCCTG - +4 yetfasco__YFL031W_1788 2 0.137093 3352.34 1 6 CACCTG CATACGTGTCCT - +4 predrem__nrMotif1334 7 0.137093 3352.34 1 5 CACCTG AAAAAAAAACCA + +4 tiffin__TIFDMEM0000020 7 0.137093 3352.34 1 5 CACCTG TTTCCGATAGCT + +4 transfac_pro__M05613-CG12071 7 0.137093 3352.34 1 5 CACCTG TCTGATATACCA - +4 transfac_pro__M05939-crol 7 0.137093 3352.34 1 5 CACCTG CATAATATACCA - +4 transfac_pro__M06309 7 0.137093 3352.34 1 5 CACCTG TGTTTCTTACCA - +4 transfac_pro__M06441 7 0.137093 3352.34 1 5 CACCTG TATCCCGCACCA - +4 transfac_pro__M06496-CG3281-CG4360-jim 7 0.137093 3352.34 1 5 CACCTG TCGGTTTTACCA - +4 transfac_pro__M06546 7 0.137093 3352.34 1 5 CACCTG TCCCCCATACCA - +4 transfac_pro__M05865 8 0.137093 3352.34 1 4 CACCTG CGCTCCAACACC + +4 transfac_pro__M06370 -2 0.137093 3352.34 1 4 CACCTG CCTTTAGAAAGT - +4 taipale_cyt_meth__ZNF580_NRTTATGTTAAAWWNYTACCNYN_FL_repr 16 0.138626 3389.82 1 6 CACCTG TGTTATGTTAAATAATTACCCTA + +4 neph__UW.Motif.0637 7 0.138782 3393.63 1 6 CACCTG GGAAAGGCAGCAGGCA + +4 taipale_tf_pairs__ERF_FIGLA_RSCGGAANCASCTGNN_CAP_repr-Ets21C 8 0.138782 3393.63 1 6 CACCTG ACCGGAAACACCTGGT + +4 cisbp__M4432-Chd1-CTCF-SMC3-usp-vtd 7 0.138782 3393.63 1 6 CACCTG CTGGCGCCCCCTGGTG - +4 neph__UW.Motif.0137 9 0.138782 3393.63 1 6 CACCTG GCCTGCCTCCTCCTGT - +4 neph__UW.Motif.0299 3 0.138782 3393.63 1 6 CACCTG AGATTTCTGTCTTCTT - +4 neph__UW.Motif.0432 8 0.138782 3393.63 1 6 CACCTG GCTTTTTCCTCTTTCT - +4 taipale_cyt_meth__RORB_NAWNTRGGTCRTGACCYANWTN_eDBD-Hr3-usp 12 0.140191 3428.08 1 6 CACCTG TAACTAGGTCATGACCTAGTTA + +4 hocomoco__RXRG_MOUSE.H11MO.0.B-ERR-EcR-Hr4-ftz-f1-svp-usp 1 0.140191 3428.08 1 6 CACCTG TGACCTTGAACTCCTGACCCTC - +4 cisbp__M5796-EcR-eg-ham-Hr78-kni-knrl-usp 8 0.140313 3431.08 1 6 CACCTG GGGGTCATGACCCC + +4 fantom__motif163_GARTCGCCCTGTNA 5 0.140313 3431.08 1 6 CACCTG GAGTCGCCCTGTTA + +4 neph__UW.Motif.0335 4 0.140313 3431.08 1 6 CACCTG AGGGCTCCCGCCCC + +4 taipale__RXRA_DBD_RRGGTCATGACCYY-EcR-eg-ham-Hr78-kni-knrl-usp 8 0.140313 3431.08 1 6 CACCTG GGGGTCATGACCCC + +4 taipale_tf_pairs__HOXC10_TBX21_TMRCACYTMATWAA_CAP_repr 3 0.140313 3431.08 1 6 CACCTG TAACACCTCATAAA + +4 transfac_pro__M09452 5 0.140313 3431.08 1 6 CACCTG TTTTTTACCGTTTT + +4 flyfactorsurvey__dsx-F_FlyReg_FBgn0000504-dsx 4 0.140313 3431.08 1 6 CACCTG TAATAACTTTGTAG - +4 neph__UW.Motif.0183 8 0.140313 3431.08 1 6 CACCTG TTTCAGAATTTCTG - +4 neph__UW.Motif.0357 5 0.140313 3431.08 1 6 CACCTG CAGATTTGCTTTTT - +4 neph__UW.Motif.0662 8 0.140313 3431.08 1 6 CACCTG TGTTTACTCACCCA - +4 taipale_tf_pairs__TEAD4_FIGLA_GGAATKNNCASSTG_CAP-sd 0 0.140313 3431.08 1 6 CACCTG CACCTGCACATTCC - +4 transfac_pro__M02871 3 0.140313 3431.08 1 6 CACCTG TCGCACCTTTCTCC - +4 hocomoco__THA_MOUSE.H11MO.0.C-ERR-EcR 1 0.140598 3438.04 1 6 CACCTG TGTCCTCAGATGACCTC - +4 transfac_pro__M01313-Optix-so 8 0.140598 3438.04 1 6 CACCTG AAAAATGATACCCCATC - +4 transfac_pro__M07949-bowl-sob 2 0.140598 3438.04 1 6 CACCTG GCTACCGGTGTTACGCA - +4 transfac_pro__M09414 11 0.140598 3438.04 1 6 CACCTG ACAACAGAAATTATCTG - +4 transfac_pro__M08986 1 0.141694 3464.84 1 6 CACCTG CCACCTTTAGCTATATCT + +4 cisbp__M1840-Mef2-bs 2 0.141694 3464.84 1 6 CACCTG ATTACCCAATTTGGTAAT - +4 jaspar__MA0005.2-Mef2-bs 2 0.141694 3464.84 1 6 CACCTG ATTTCCCAATTTGGTAAT - +4 cisbp__M0178-ac-amos-ase-CoRest-dimm-Fer1-Fer3-HLH54F-l(1)sc-nau-sc 2 0.14186 3468.9 1 6 CACCTG AACAGCTGTT + +4 cisbp__M0237-Mitf 4 0.14186 3468.9 1 6 CACCTG TTATCACGTG + +4 cisbp__M0276-Atf6-CrebA 3 0.14186 3468.9 1 6 CACCTG TGCCACGTGT + +4 cisbp__M1377 3 0.14186 3468.9 1 6 CACCTG CAAACCCTAA + +4 cisbp__M1391 1 0.14186 3468.9 1 6 CACCTG ACCCCTAGTT + +4 cisbp__M1443-Hnf4 4 0.14186 3468.9 1 6 CACCTG TTTGAACCCT + +4 cisbp__M6345-cyc-Mitf 2 0.14186 3468.9 1 6 CACCTG ATCACATGAC + +4 predrem__nrMotif1005 0 0.14186 3468.9 1 6 CACCTG CCCCTTCCCG + +4 scertf__spivak.LEU3 4 0.14186 3468.9 1 6 CACCTG CCGGTACCGG + +4 taipale_cyt_meth__NKX2-5_NCCACTTRAN_FL_meth-tin-vnd 2 0.14186 3468.9 1 6 CACCTG ACCACTTGAC + +4 taipale_cyt_meth__NKX2-8_NNCACTTSAN_FL-tin-vnd 2 0.14186 3468.9 1 6 CACCTG ACCACTTGAG + +4 transfac_pro__M01843 3 0.14186 3468.9 1 6 CACCTG GTTCACGTGC + +4 transfac_pro__M04625 4 0.14186 3468.9 1 6 CACCTG ACTGTATTTA + +4 yetfasco__YPL128C_2178 3 0.14186 3468.9 1 6 CACCTG TAAACCCTAA + +4 cisbp__M0261-Atf6-Clk-Met-Myc 1 0.14186 3468.9 1 6 CACCTG ACACGTGTCA - +4 cisbp__M0630-dmrt11E-dmrt93B-dmrt99B-dsx 4 0.14186 3468.9 1 6 CACCTG TTGATACATT - +4 cisbp__M1338 0 0.14186 3468.9 1 6 CACCTG TAACGGCCTA - +4 cisbp__M1362 1 0.14186 3468.9 1 6 CACCTG ATACCGGTCT - +4 homer__CCCACGTGCT_Pho2 2 0.14186 3468.9 1 6 CACCTG AGCACGTGGG - +4 homer__NAHCAGCTGD_Ap4-crp 1 0.14186 3468.9 1 6 CACCTG ACAGCTGTTT - +4 predrem__nrMotif100 2 0.14186 3468.9 1 6 CACCTG TTCTCCTTCT - +4 predrem__nrMotif2107 4 0.14186 3468.9 1 6 CACCTG TTTGAACTTT - +4 predrem__nrMotif344 4 0.14186 3468.9 1 6 CACCTG AGAAGACATT - +4 predrem__nrMotif541 3 0.14186 3468.9 1 6 CACCTG AAACACCAGA - +4 predrem__nrMotif780 4 0.14186 3468.9 1 6 CACCTG TGCCTCCCTG - +4 predrem__nrMotif1191 5 0.14186 3468.9 1 5 CACCTG CTGGAGACCA + +4 cisbp__M1516 5 0.14186 3468.9 1 5 CACCTG CCGTACACCC - +4 cisbp__M0908-bap-scro-vnd 1 0.141993 3472.15 1 6 CACCTG CCACTTAA + +4 cisbp__M1307 2 0.141993 3472.15 1 6 CACCTG GGAATCTT + +4 cisbp__M1553 1 0.141993 3472.15 1 6 CACCTG GTACGTCA + +4 jaspar__MA0403.1 1 0.141993 3472.15 1 6 CACCTG AACCCTAA + +4 jaspar__MA0416.1 2 0.141993 3472.15 1 6 CACCTG ATTACGTA + +4 jaspar__MA0959.1-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn 1 0.141993 3472.15 1 6 CACCTG GCACGTGC + +4 predrem__nrMotif1256 1 0.141993 3472.15 1 6 CACCTG GGACTTTC + +4 transfac_pro__M01913 1 0.141993 3472.15 1 6 CACCTG AACCCTAA + +4 cisbp__M0792-GATAd-GATAe-grn-pnr-srp 2 0.141993 3472.15 1 6 CACCTG GTTATCTG - +4 cisbp__M5062-Kr 0 0.141993 3472.15 1 6 CACCTG TACCCTTC - +4 fantom__motif61_KAYMGMTN 0 0.141993 3472.15 1 6 CACCTG GAGCGATC - +4 hdpi__PRKRIR 1 0.141993 3472.15 1 6 CACCTG TGGCCTTT - +4 neph__UW.Motif.0046 0 0.141993 3472.15 1 6 CACCTG TTCCTTCC - +4 neph__UW.Motif.0006 3 0.141993 3472.15 1 5 CACCTG CATTTCCT - +4 predrem__nrMotif2445 -2 0.141993 3472.15 1 4 CACCTG CCTTAATT + +4 predrem__nrMotif832 -2 0.141993 3472.15 1 4 CACCTG CCTTTGAT - +4 cisbp__M1894-eg-ERR-kni-knrl 13 0.142 3472.32 1 6 CACCTG AGTAGGTCACCGTGACCTAC + +4 dbcorrdb__CTCF__ENCSR000ALA_1__m1-CTCF-SMC3-usp-vtd 5 0.142 3472.32 1 6 CACCTG AGCGCCCCCTGGTGGCCACA + +4 dbcorrdb__CTCF__ENCSR000AMF_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAG + +4 dbcorrdb__CTCF__ENCSR000AOO_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__CTCF__ENCSR000BNH_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.142 3472.32 1 6 CACCTG TATAGCGCCCCCTGGTGGCC + +4 dbcorrdb__CTCF__ENCSR000DKR_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DLB_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DME_1__m1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DPF_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DUB_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DWH_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAG + +4 dbcorrdb__CTCF__ENCSR000DXW_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000EGM_1__m1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__RAD21__ENCSR000EEG_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGTGCCCCCTGGTGGCCAA + +4 dbcorrdb__RFX5__ENCSR000EFD_1__m1-CG9727-Rfx 3 0.142 3472.32 1 6 CACCTG TTCTGCCTAGCAACAGATGA + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m6-brm 5 0.142 3472.32 1 6 CACCTG CTTCCCAACTCACTCAACAA + +4 dbcorrdb__SMC3__ENCSR000ECS_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGTGCCCCCTGGTGGCCAC + +4 dbcorrdb__ZNF384__ENCSR000EFP_1__m3-rn-sqz 3 0.142 3472.32 1 6 CACCTG TGCAACCTCAGCCTCCCGGG + +4 homer__ATAGTGCCACCTGGTGGCCA_CTCF-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGTGCCACCTGGTGGCCA + +4 homer__CNNBRGCGCCCCCTGSTGGC_BORIS-CTCF-Chd1-Hcf-SMC3-usp-vtd 9 0.142 3472.32 1 6 CACCTG CTCCGGCGCCCCCTGGTGGC + +4 taipale_tf_pairs__RORB_AWNTAGGTCATGACCTANWT_HT-Hr3 11 0.142 3472.32 1 6 CACCTG AACTAGGTCATGACCTAGTT + +4 dbcorrdb__CTCF__ENCSR000AKB_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000AOA_1__m1-CTCF-SMC3-usp-vtd 9 0.142 3472.32 1 6 CACCTG CTATAGCGCCCCCTGGTGGC - +4 dbcorrdb__CTCF__ENCSR000BIE_1__m1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DKL_1__m1-Chd1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__CTCF__ENCSR000DKN_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DLO_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAG - +4 dbcorrdb__CTCF__ENCSR000DNG_1__m1-CTCF-SMC3-usp-vtd 5 0.142 3472.32 1 6 CACCTG AGCGCCCCCTGGTGGCCACA - +4 dbcorrdb__CTCF__ENCSR000DPG_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DQN_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DQW_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DRI_2__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DRJ_2__m1-Chd1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC - +4 dbcorrdb__CTCF__ENCSR000DRN_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DTR_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA - +4 dbcorrdb__CTCF__ENCSR000DTW_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DXQ_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000EFI_1__m1-CTCF-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__IKZF1__ENCSR000EUJ_1__m4 5 0.142 3472.32 1 6 CACCTG GATTCCTCCTGTGAGTGAGC - +4 dbcorrdb__RAD21__ENCSR000BMY_1__m1-CTCF-SMC3-usp-vtd 12 0.142 3472.32 1 6 CACCTG GGGCTATAGTGCCCCCTGGT - +4 dbcorrdb__RAD21__ENCSR000EAC_1__m1-CTCF-SMC3-usp-vtd 6 0.142 3472.32 1 6 CACCTG TAGTGCCCCCTGGTGGCCAA - +4 dbcorrdb__RAD21__ENCSR000EDE_1__m1-CTCF-SMC3-usp-vtd 2 0.142 3472.32 1 6 CACCTG GCCACCTGGTGGCCAAATGG - +4 dbcorrdb__RAD21__ENCSR000EFJ_1__m1-CTCF-SMC3-usp-vtd 12 0.142 3472.32 1 6 CACCTG GGGCTATAGTGCCCCCTGGT - +4 dbcorrdb__RXRA__ENCSR000BHU_1__m2-EcR-eg-ERR-ftz-f1-HDAC1-Hnf4-Hr38-Hr4-Hr51-Hr78-kni-knrl-nej-Nup133-svp-usp 8 0.142 3472.32 1 6 CACCTG CCCACTCTGACCTTTGACCT - +4 dbcorrdb__ZNF143__ENCSR000EGP_1__m1-CTCF-Hcf-SMC3-usp-vtd 7 0.142 3472.32 1 6 CACCTG GCCGCGCCGCCTGCTGGGAA - +4 homer__NGAGGTCANNGAGTTCANNN_VDR-EcR-usp 13 0.142 3472.32 1 6 CACCTG CCATGAACTCAGTGACCTCT - +4 jaspar__MA0066.1-ERR-EcR-eg-kni-knrl 13 0.142 3472.32 1 6 CACCTG AGTAGGTCACCGTGACCTAC - +4 transfac_pro__M01573 9 0.142 3472.32 1 6 CACCTG ATACCCGTACACCCTAACCC - +4 transfac_pro__M05673 8 0.142 3472.32 1 6 CACCTG AGGCTTGAAACCTCTGCCGT - +4 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNCACGTGN_HT-crp-Max 1 0.14214 3475.75 1 6 CACCTG TCAGCTGTTCGGCACGTGC + +4 transfac_pro__M06094 7 0.14214 3475.75 1 6 CACCTG GGGACGCGACCTCTAAGGC + +4 taipale__RORA_DBD_WAWNTRGGTYAGTAGGTCA_repr-eg-Eip75B-Hr3-kni-knrl 9 0.14214 3475.75 1 6 CACCTG TGACCTACTAACCTAGTTA - +4 taipale_tf_pairs__GCM2_DLX3_RTRCGGGNNNNNNTAATKR_CAP_repr-gcm-gcm2 10 0.14214 3475.75 1 6 CACCTG CAATTAAGTATACCCGCAT - +4 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNNRNACAAWN_CAP-gcm-gcm2 10 0.14214 3475.75 1 6 CACCTG TATTGTTTTATACCCGCAT - +4 transfac_pro__M04955 0 0.142582 3486.55 1 6 CACCTG AACCTCG + +4 predrem__nrMotif1424 1 0.142582 3486.55 1 6 CACCTG CCACTTC - +4 transfac_pro__M03540-bigmax-cyc-Mitf-Mondo-Usf 1 0.142582 3486.55 1 6 CACCTG TCACGTG - +4 transfac_pro__M04822 0 0.142582 3486.55 1 6 CACCTG CAACTCC - +4 predrem__nrMotif1112 -1 0.142582 3486.55 1 5 CACCTG ATCTCTG + +4 predrem__nrMotif2531 2 0.142582 3486.55 1 5 CACCTG AGCACAT - +4 transfac_pro__M01050 2 0.142582 3486.55 1 5 CACCTG CGGATCT - +4 jaspar__MA0373.1 3 0.142582 3486.55 1 4 CACCTG CGCCACC - +4 transfac_pro__M01925 3 0.142582 3486.55 1 4 CACCTG CGCCACC - +4 transfac_pro__M01860-crp 1 0.143273 3503.47 1 6 CACCTG CCAGCTGCGGCCA + +4 cisbp__M0635 5 0.143273 3503.47 1 6 CACCTG TTTTATACATGTT - +4 neph__UW.Motif.0515 7 0.143273 3503.47 1 6 CACCTG CCTGCAGGACCTG - +4 taipale_tf_pairs__HOXB2_EOMES_TAATKRGGTGYKA_CAP-pb 3 0.143273 3503.47 1 6 CACCTG TCACACCTCATTA - +4 flyfactorsurvey__disco_SOLEXA_5_FBgn0000459-disco-disco-r 8 0.143273 3503.47 1 5 CACCTG AAAATTGTCACCT + +4 cisbp__M4915-disco-disco-r 8 0.143273 3503.47 1 5 CACCTG AAAATTGTCACCT - +4 cisbp__M2925-lz-run-RunxA-RunxB -1 0.14369 3513.66 1 5 CACCTG ACCACA + +4 transfac_pro__M01878-GATAe-grn-pnr 1 0.14369 3513.66 1 5 CACCTG TTATCT - +4 transfac_public__M00271-lz-run-RunxA-RunxB -1 0.14369 3513.66 1 5 CACCTG ACCACA - +4 cisbp__M2389-CG10431 1 0.143813 3516.67 1 6 CACCTG CTGCCCGCA + +4 predrem__nrMotif2218 2 0.143813 3516.67 1 6 CACCTG CACACGTGT + +4 predrem__nrMotif38 1 0.143813 3516.67 1 6 CACCTG CTCCCTTCT + +4 predrem__nrMotif951 1 0.143813 3516.67 1 6 CACCTG CCACTTGCT + +4 yetfasco__YDR123C_713 2 0.143813 3516.67 1 6 CACCTG TTCACATGC + +4 bergman__sd-sd 1 0.143813 3516.67 1 6 CACCTG AAAAATACA - +4 c2h2_zfs__M3383-opa 3 0.143813 3516.67 1 6 CACCTG GACCACCCC - +4 cisbp__M0181-bigmax-Mondo-tgo 0 0.143813 3516.67 1 6 CACCTG CACGTGATC - +4 jaspar__MA0321.1 2 0.143813 3516.67 1 6 CACCTG TTCACATGC - +4 predrem__nrMotif181 1 0.143813 3516.67 1 6 CACCTG ATGCCTGGA - +4 predrem__nrMotif2416-Max-Mitf-Usf-cnc 2 0.143813 3516.67 1 6 CACCTG GTCACGTGG - +4 predrem__nrMotif2575 3 0.143813 3516.67 1 6 CACCTG CTGTACCCT - +4 predrem__nrMotif752 0 0.143813 3516.67 1 6 CACCTG CACATGCCA - +4 transfac_public__M00077-GATAe-grn-pnr 3 0.143813 3516.67 1 6 CACCTG CCCTATCTC - +4 predrem__nrMotif1837 4 0.143813 3516.67 1 5 CACCTG AAGACATCT + +4 predrem__nrMotif724 4 0.143813 3516.67 1 5 CACCTG AGAACAGCT + +4 transfac_pro__M00706 -2 0.143813 3516.67 1 4 CACCTG CCTCCCTCT - +4 homer__ADGGYAGYAGCATCT_PRDM9 7 0.144032 3522.02 1 6 CACCTG ATGGTAGCAGCATCT + +4 transfac_pro__M02924-TfAP-2 2 0.144032 3522.02 1 6 CACCTG ATTGCCTCAGGCAAT + +4 cisbp__M4433-CTCF-SMC3-usp-vtd 4 0.144032 3522.02 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4450-CTCF-SMC3-usp-vtd 4 0.144032 3522.02 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4661-CTCF-SMC3-Stat92E-usp-vtd 3 0.144032 3522.02 1 6 CACCTG CGCCCCCTGGTGGCC - +4 cisbp__M6366-NFAT 9 0.144032 3522.02 1 6 CACCTG GTGGAAAAATCCATG - +4 factorbook__NR3C1-Hsf-fkh 2 0.144032 3522.02 1 6 CACCTG AGGACATTCTGTTCC - +4 neph__UW.Motif.0676 6 0.144032 3522.02 1 6 CACCTG TTTTTTTTCTTGGAA - +4 taipale_tf_pairs__GCM2_HOXA13_RTRCGGGTAATAAAN_CAP_repr-gcm-gcm2 6 0.144032 3522.02 1 6 CACCTG TTTTATTACCCGCAT - +4 taipale_tf_pairs__NR1D2_TRGGTYASTAGGTCA_HT-Eip75B 9 0.144032 3522.02 1 6 CACCTG TGACCTACTAACCCA - +4 neph__UW.Motif.0491 10 0.144032 3522.02 1 5 CACCTG CTCAGTCTGTTTTCT - +4 taipale_cyt_meth__ZNF32_NYGTAACNYGAYACN_FL_meth_repr-CG4730-CG7101 11 0.144032 3522.02 1 4 CACCTG ACGTAACCCGATACC + +4 cisbp__M2069-scro-tin-vnd 2 0.144453 3532.3 1 6 CACCTG ACCACTTGAAA + +4 cisbp__M4500-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 3 0.144453 3532.3 1 6 CACCTG GGTCACGTGAC + +4 cisbp__M6516-amos-HLH3B-HLH54F 3 0.144453 3532.3 1 6 CACCTG GACCATCTGGT + +4 jaspar__MA0264.1-scro-tin-vnd 2 0.144453 3532.3 1 6 CACCTG ACCACTTGAAA + +4 predrem__nrMotif484 5 0.144453 3532.3 1 6 CACCTG CAGGGCCCCTC + +4 transfac_pro__M00439 1 0.144453 3532.3 1 6 CACCTG CCAACTACCCG + +4 transfac_pro__M03572-Mitf-Usf 2 0.144453 3532.3 1 6 CACCTG CGCACGTGACC + +4 cisbp__M1684 5 0.144453 3532.3 1 6 CACCTG ACGTTGACCGG - +4 jaspar__MA1090.1 5 0.144453 3532.3 1 6 CACCTG ACGTTGACCGG - +4 tiffin__TIFDMEM0000082 4 0.144453 3532.3 1 6 CACCTG TTTTCACTTTA - +4 neph__UW.Motif.0080 -1 0.144453 3532.3 1 5 CACCTG TCCTGGCCTCA + +4 cisbp__M6463-Mad 0 0.144774 3540.17 1 6 CACCTG AGCCTGTCTGCC + +4 neph__UW.Motif.0057 6 0.144774 3540.17 1 6 CACCTG AGCAATTTCCTG + +4 neph__UW.Motif.0606 3 0.144774 3540.17 1 6 CACCTG AGCTCCATCATC + +4 neph__UW.Motif.0609 6 0.144774 3540.17 1 6 CACCTG AAATTGAAACTC + +4 c2h2_zfs__M0489-CG2120 6 0.144774 3540.17 1 6 CACCTG AGGCTGCGCCTC - +4 hocomoco__NKX31_HUMAN.H11MO.0.C-bap-vnd 4 0.144774 3540.17 1 6 CACCTG AAAGCACTTAAC - +4 homer__NNVVCAGCTGBN_Ascl1-Fer1-Fer3-HLH3B-HLH54F-ac-amos-ase-dimm-l(1)sc-nau-sc 2 0.144774 3540.17 1 6 CACCTG AGCAGCTGCCGC - +4 homer__SCCTSAGGSCAW_AP-2gamma-GATAe-TfAP-2-grn-pnr 2 0.144774 3540.17 1 6 CACCTG ATGCCCTGAGGC - +4 neph__UW.Motif.0560 4 0.144774 3540.17 1 6 CACCTG TAAAACCATTTG - +4 taipale_cyt_meth__TGIF2_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.144774 3540.17 1 6 CACCTG TGACAGCTGTCA - +4 taipale_cyt_meth__ZBTB2_NTTTMCGGTWAN_eDBD 2 0.144774 3540.17 1 6 CACCTG GTTACCGGAAAC - +4 transfac_pro__M05681-CG3281-CG4360-jim 7 0.144774 3540.17 1 5 CACCTG TCGGTTTTACCC - +4 transfac_pro__M05773-Meics 7 0.144774 3540.17 1 5 CACCTG GCCCTCGTACCA - +4 transfac_pro__M05774-Meics 7 0.144774 3540.17 1 5 CACCTG GCCCTCGTACCA - +4 transfac_pro__M06417-CG6654-CG7372 7 0.144774 3540.17 1 5 CACCTG TGGTTTTTACCA - +4 transfac_pro__M06472-CG6654-CG7372 7 0.144774 3540.17 1 5 CACCTG TGGTTTTTACCA - +4 transfac_pro__M06595 7 0.144774 3540.17 1 5 CACCTG AGATCTTTACCA - +4 transfac_pro__M06653 7 0.144774 3540.17 1 5 CACCTG GCTTTATTACCA - +4 transfac_pro__M06780 7 0.144774 3540.17 1 5 CACCTG AGATCTTTACCA - +4 neph__UW.Motif.0403 1 0.146833 3590.51 1 6 CACCTG AGTCCTGGCCTCCTGC + +4 hocomoco__VDR_HUMAN.H11MO.0.A-EcR-usp 10 0.146833 3590.51 1 6 CACCTG TGAACCCACTGACCCC - +4 neph__UW.Motif.0074 9 0.146833 3590.51 1 6 CACCTG TGGCAGCTGTTCCTGG - +4 neph__UW.Motif.0487 4 0.146833 3590.51 1 6 CACCTG CCAGTGCCTGCTCCTG - +4 hocomoco__LYL1_HUMAN.H11MO.0.A-Fer1-HLH3B 1 0.148285 3626.01 1 6 CACCTG CCAGCTGTTTCCTG + +4 cisbp__M4881-ZIPIC 8 0.148285 3626.01 1 6 CACCTG TTTTTGCATCCCTG - +4 flyfactorsurvey__CG7928_SOLEXA_5_FBgn0039740-ZIPIC 8 0.148285 3626.01 1 6 CACCTG TTTTTGCATCCCTG - +4 taipale_cyt_meth__NR2C1_NRGGTCRYGACCYN_eDBD_repr-EcR-eg-Hr78-kni-knrl-usp 8 0.148285 3626.01 1 6 CACCTG GAGGTCATGACCTC - +4 neph__UW.Motif.0420 9 0.148285 3626.01 1 5 CACCTG AGCTTCCTTTTTCT - +4 transfac_pro__M01342-ct 10 0.148802 3638.66 1 6 CACCTG ACCGGTTGATCACCTGA + +4 cisbp__M4581-Chd1-CTCF-Hcf-SMC3-usp-vtd 7 0.148802 3638.66 1 6 CACCTG CTGGCGCCCCCTGGTGG - +4 transfac_pro__M01398-Optix-Six4-so 8 0.148802 3638.66 1 6 CACCTG ATAATTGATACCCTATT - +4 cisbp__M0898 1 0.149459 3654.72 1 6 CACCTG TTACGTAA + +4 cisbp__M5496-CG7786-gt-Pdp1-vri 1 0.149459 3654.72 1 6 CACCTG TTACGTAA + +4 hdpi__JDP2 2 0.149459 3654.72 1 6 CACCTG GACAGCTG + +4 homer__GNCACGTG_BMAL1-Clk-Mitf-SREBP-Usf-cnc-cyc-tai-tgo 2 0.149459 3654.72 1 6 CACCTG GTCACGTG + +4 jaspar__MA0259.1-sima-tgo 1 0.149459 3654.72 1 6 CACCTG GGACGTGC + +4 predrem__nrMotif1784 1 0.149459 3654.72 1 6 CACCTG GGATCTGG + +4 swissregulon__hs__ATF2.p2-CG7786-Pdp1-gt-vri 1 0.149459 3654.72 1 6 CACCTG TTACATAA + +4 taipale__GMEB2_DBD_TTACGTAA-CG7786-vri 1 0.149459 3654.72 1 6 CACCTG TTACGTAA + +4 yetfasco__YDR259C_599-CG7786-Pdp1-gt-vri 1 0.149459 3654.72 1 6 CACCTG TTACATAA + +4 c2h2_zfs__M0436 2 0.149459 3654.72 1 6 CACCTG CCTCCCTT - +4 cisbp__M0643 2 0.149459 3654.72 1 6 CACCTG GAAACATT - +4 jaspar__MA0937.1 1 0.149459 3654.72 1 6 CACCTG TTACGTGT - +4 predrem__nrMotif2203 2 0.149459 3654.72 1 6 CACCTG CTAACCTC - +4 predrem__nrMotif876 0 0.149459 3654.72 1 6 CACCTG GACCTCAC - +4 stark__TYAAGTGS-scro-vnd 1 0.149459 3654.72 1 6 CACCTG CCACTTAA - +4 cisbp__M1417 3 0.149459 3654.72 1 5 CACCTG TGGTACCA + +4 transfac_pro__M04843-SMC3 -1 0.149459 3654.72 1 5 CACCTG ACCAGCAG + +4 transfac_pro__M04959-Stat92E -1 0.149459 3654.72 1 5 CACCTG TCCTGCCT - +4 fantom__motif2_GCTGGAGG -2 0.149459 3654.72 1 4 CACCTG CCTCCAGC - +4 predrem__nrMotif1075 4 0.149459 3654.72 1 4 CACCTG TGCTGACC - +4 c2h2_zfs__M0523 4 0.149474 3655.09 1 6 CACCTG ATCCCACATT + +4 cisbp__M0331 3 0.149474 3655.09 1 6 CACCTG GCTTACGTAA + +4 cisbp__M1791 4 0.149474 3655.09 1 6 CACCTG ATAACACCGC + +4 flyfactorsurvey__cato_da_SANGER_10_FBgn0000413-cato-da 2 0.149474 3655.09 1 6 CACCTG CACAGCTGAC + +4 transfac_pro__M00366-Atf6-CrebA-Max-Mnt-Usf 2 0.149474 3655.09 1 6 CACCTG GCCACGTGGC + +4 transfac_pro__M00370-CrebA-Usf 2 0.149474 3655.09 1 6 CACCTG GCCACGTGAC + +4 transfac_pro__M00788 2 0.149474 3655.09 1 6 CACCTG TACACGTGGA + +4 transfac_pro__M03179 1 0.149474 3655.09 1 6 CACCTG CTACCGATGT + +4 transfac_pro__M07641-Fer1 2 0.149474 3655.09 1 6 CACCTG GTCAGCTGAC + +4 cisbp__M0421-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 4 0.149474 3655.09 1 6 CACCTG GCCACGCCCA - +4 cisbp__M1399 4 0.149474 3655.09 1 6 CACCTG ACTGTATCTT - +4 cisbp__M1683 4 0.149474 3655.09 1 6 CACCTG CGTTGACTTT - +4 cisbp__M1702 4 0.149474 3655.09 1 6 CACCTG CGTTGACCTT - +4 predrem__nrMotif1605 4 0.149474 3655.09 1 6 CACCTG CCTAGCCCTG - +4 predrem__nrMotif1809 0 0.149474 3655.09 1 6 CACCTG AACATGCTTT - +4 predrem__nrMotif34 0 0.149474 3655.09 1 6 CACCTG CCCCTGCCAA - +4 scertf__macisaac.RME1 0 0.149474 3655.09 1 6 CACCTG TTCCTTTAAA - +4 taipale_cyt_meth__TBX2_NAGGTGTGAN_eDBD_meth-bi-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.149474 3655.09 1 6 CACCTG TTCACACCTT - +4 transfac_pro__M07490 1 0.149474 3655.09 1 6 CACCTG GCAACTAACG - +4 transfac_pro__M07502 3 0.149474 3655.09 1 6 CACCTG CCGTATCTTT - +4 cisbp__M1336 -1 0.149474 3655.09 1 5 CACCTG ACCTTATCTG - +4 predrem__nrMotif1576 5 0.149474 3655.09 1 5 CACCTG GCAGCCACTT - +4 cisbp__M4592-Chd1-CTCF-Hcf-SMC3-usp-vtd 8 0.149837 3663.97 1 6 CACCTG CCCGGCGCCCCCTGGTGGCCG - +4 hocomoco__CTCFL_MOUSE.H11MO.0.A-CTCF-Hcf-SMC3-Stat92E-usp-vtd 7 0.150018 3668.39 1 6 CACCTG GCAGCGCCCCCTGGCGGC - +4 transfac_pro__M06637 3 0.150018 3668.39 1 6 CACCTG CCGACCCTGGCTGCCGCT - +4 taipale_tf_pairs__PITX1_EOMES_RGGTGTKANNNNGGATTA_CAP_repr-Ptx1 13 0.150018 3668.39 1 5 CACCTG TAATCCCATTTAACACCC - +4 transfac_pro__M05998-CTCF 13 0.150018 3668.39 1 5 CACCTG TGGTGCCTTCTCCCACCG - +4 cisbp__M1350 0 0.150102 3670.44 1 6 CACCTG GCCCGGT + +4 predrem__nrMotif390 1 0.150102 3670.44 1 6 CACCTG TCATCTG + +4 flyfactorsurvey__tll_FlyReg_FBgn0003720-tll 1 0.150102 3670.44 1 6 CACCTG TGACTTT - +4 hdpi__PIR 0 0.150102 3670.44 1 6 CACCTG CGCCTGC - +4 predrem__nrMotif2627 -1 0.150102 3670.44 1 5 CACCTG AACTGTT + +4 predrem__nrMotif940 -1 0.150102 3670.44 1 5 CACCTG GCCTGCT + +4 transfac_pro__M03579-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5 2 0.150102 3670.44 1 5 CACCTG ACTTCCT - +4 elemento__CCTTATC -2 0.150102 3670.44 1 4 CACCTG CCTTATC + +4 elemento__CCTTGAC -2 0.150102 3670.44 1 4 CACCTG CCTTGAC + +4 elemento__CCTTGCG -2 0.150102 3670.44 1 4 CACCTG CCTTGCG + +4 elemento__CCTTGGC -2 0.150102 3670.44 1 4 CACCTG CCTTGGC + +4 elemento__CCCAAGG -2 0.150102 3670.44 1 4 CACCTG CCTTGGG - +4 dbcorrdb__CTCF__ENCSR000BLX_1__m1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DPM_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DPY_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DRB_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DSU_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DSZ_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DVI_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DWE_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__CTCF__ENCSR000DWY_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__HDAC2__ENCSR000BNR_1__m1-HDAC1-opa 3 0.150472 3679.49 1 6 CACCTG GCCCTCCTGCTGAGATGGAC + +4 dbcorrdb__RFX5__ENCSR000ECF_1__m1-CG9727-Rfx 2 0.150472 3679.49 1 6 CACCTG TCTGCCTAGCAACAGGTGAC + +4 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m1-Spt20 6 0.150472 3679.49 1 6 CACCTG TGACTGTTCCTTGAAGTGAA + +4 tfdimers__MD00486-Stat92E 6 0.150472 3679.49 1 6 CACCTG CCCCCCCACCTTCCCCCCCC + +4 transfac_pro__M01559 9 0.150472 3679.49 1 6 CACCTG ACGTAACGCCACCCTAATCG + +4 transfac_pro__M03809-EcR-svp-usp 3 0.150472 3679.49 1 6 CACCTG TTTGACCTCCAGTGACCCCC + +4 dbcorrdb__CTCF__ENCSR000APF_1__m1-CTCF-SMC3-usp-vtd 9 0.150472 3679.49 1 6 CACCTG CTATAGCGCCCCCTGGTGGC - +4 dbcorrdb__CTCF__ENCSR000APM_1__m1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000BHV_1__m1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000BQE_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.150472 3679.49 1 6 CACCTG TATAGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DLS_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA - +4 dbcorrdb__CTCF__ENCSR000DPS_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DRE_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DRK_2__m1-CTCF-SMC3-usp-vtd 5 0.150472 3679.49 1 6 CACCTG AGCGCCCCCTGGTGGCCACA - +4 dbcorrdb__CTCF__ENCSR000DRR_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DRU_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DRZ_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DTA_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DTF_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DTL_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DUM_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DUU_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.150472 3679.49 1 6 CACCTG TATAGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DVP_1__m1-CTCF-SMC3-usp-vtd 6 0.150472 3679.49 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DVQ_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DWN_1__m1-CTCF-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DXD_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.150472 3679.49 1 6 CACCTG TATAGCGCCCCCTGGTGGCC - +4 dbcorrdb__RAD21__ENCSR000EHX_1__m1-CTCF-SMC3-vtd 12 0.150472 3679.49 1 6 CACCTG GGGCTATAGTGCCCTCTAGT - +4 dbcorrdb__RELA__ENCSR000EAI_1__m1-CG12018-Dif-dl-Rel-shn 11 0.150472 3679.49 1 6 CACCTG GCCTGGGAAATCCCCTACTC - +4 dbcorrdb__RELA__ENCSR000EAN_1__m1-CG12018-Dif-dl-Rel-shn 11 0.150472 3679.49 1 6 CACCTG GCCTGGGAAATCCCCTGCTC - +4 hocomoco__BRAC_HUMAN.H11MO.0.A-Doc1-Doc2-Doc3-H15-bi-byn-mid-org-1 6 0.150472 3679.49 1 6 CACCTG ATTTCACACCTCCCTGCTAA - +4 hocomoco__CTCF_MOUSE.H11MO.0.A-CTCF-Chd1-SMC3-usp-vtd 7 0.150472 3679.49 1 6 CACCTG CCAGCGCCCCCTGGTGGCCA - +4 hocomoco__RFX5_HUMAN.H11MO.0.A-CG9727-Rfx 2 0.150472 3679.49 1 6 CACCTG TCTGCCTAGCAACAGCTGAC - +4 taipale_cyt_meth__RORC_NWWNNRGGTCANNRGGTCAN_eDBD_meth-eg-Eip75B-Hr3-kni-knrl 10 0.150472 3679.49 1 6 CACCTG TTGACCTACTGACCTACTTA - +4 cisbp__M5787-eg-Eip75B-Hr3-kni-knrl 9 0.150552 3681.46 1 6 CACCTG TGACCTACTAACCTAGTTA + +4 transfac_pro__M09152 9 0.150552 3681.46 1 6 CACCTG CAATAATTTCACCAACCTT + +4 hocomoco__IRX2_HUMAN.H11MO.0.D-ara-caup-mirr 2 0.150552 3681.46 1 6 CACCTG CCAACATGCCCACCCATGT - +4 transfac_pro__M01161 -1 0.150789 3687.25 1 5 CACCTG ACCCA + +4 neph__UW.Motif.0371 5 0.151301 3699.76 1 6 CACCTG TCCAATCCCAGCA + +4 transfac_pro__M01591-ebi-GATAe-grn-HLH3B-Jra-pnr-sd-Sirt6-srp 1 0.151301 3699.76 1 6 CACCTG CTTCCTTATCTCT + +4 cisbp__M4434-CTCF-SMC3-usp-vtd 2 0.151301 3699.76 1 6 CACCTG GCCCTCTAGTGGC - +4 hocomoco__GATA3_MOUSE.H11MO.0.A-GATAe-Jra-Snr1-grn-pnr-srp 6 0.151301 3699.76 1 6 CACCTG GATTCTTATCTGT - +4 predrem__nrMotif2217 5 0.151301 3699.76 1 6 CACCTG GGCGGAGCCTGGG - +4 swissregulon__sacCer__SMP1-Mef2 -1 0.151301 3699.76 1 5 CACCTG ACCTATAATTAAA + +4 stark__AACTGA-ovo -1 0.151376 3701.59 1 5 CACCTG AACTGA + +4 yetfasco__YDR026C_696 -1 0.151376 3701.59 1 5 CACCTG ACCCGG + +4 hdpi__THRA-EcR 3 0.151376 3701.59 1 3 CACCTG GGCCAC + +4 cisbp__M1803 2 0.151402 3702.24 1 6 CACCTG ATTTCCGTT + +4 cisbp__M2126 2 0.151402 3702.24 1 6 CACCTG TTCACATGC + +4 jaspar__MA0597.1-CG10431 1 0.151402 3702.24 1 6 CACCTG CTGCCCGCA + +4 predrem__nrMotif1870 3 0.151402 3702.24 1 6 CACCTG ATTTGCCTT + +4 predrem__nrMotif254 3 0.151402 3702.24 1 6 CACCTG AAAGCCCTG + +4 transfac_pro__M00307 2 0.151402 3702.24 1 6 CACCTG ATTACCCGG + +4 transfac_pro__M07043-sima 1 0.151402 3702.24 1 6 CACCTG GTACGTGCG + +4 cisbp__M0543 3 0.151402 3702.24 1 6 CACCTG CCCCACGCT - +4 cisbp__M0790 3 0.151402 3702.24 1 6 CACCTG CCAGATCTT - +4 cisbp__M3326-GATAe-grn-pnr 3 0.151402 3702.24 1 6 CACCTG CCCTATCTC - +4 hocomoco__ATOH1_HUMAN.H11MO.0.B-HLH3B-amos-tap 1 0.151402 3702.24 1 6 CACCTG CCATCTGCT - +4 hocomoco__NDF2_HUMAN.H11MO.0.B-amos-tap 1 0.151402 3702.24 1 6 CACCTG CCATCTGTT - +4 hocomoco__NR4A1_HUMAN.H11MO.0.A-Hr38-Hr78-svp 2 0.151402 3702.24 1 6 CACCTG CTGACCTTT - +4 jaspar__MA0363.1 2 0.151402 3702.24 1 6 CACCTG GTTACCCGG - +4 predrem__nrMotif898 2 0.151402 3702.24 1 6 CACCTG AGGACCTCA - +4 transfac_pro__M04720-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.151402 3702.24 1 6 CACCTG GTCACGTGA - +4 cisbp__M6143-TfAP-2 -1 0.151402 3702.24 1 5 CACCTG GCCTGAGGC - +4 predrem__nrMotif1645 4 0.151402 3702.24 1 5 CACCTG TCCACACAT - +4 predrem__nrMotif2471 4 0.151402 3702.24 1 5 CACCTG TTTACATCT - +4 predrem__nrMotif265 -1 0.151402 3702.24 1 5 CACCTG CCCTACCCC - +4 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNNNNNNNNRTGCGGGYRN_CAP-gcm-gcm2-Max 1 0.151599 3707.06 1 6 CACCTG CTACCCGCATCCCCCCCAAGCACGTGCC - +4 hocomoco__NFAT5_MOUSE.H11MO.0.D-NFAT 9 0.152239 3722.71 1 6 CACCTG GTGGAAAAATCCATT + +4 neph__UW.Motif.0456 0 0.152239 3722.71 1 6 CACCTG TCCCTCCCAGCCCCA + +4 transfac_pro__M00447-fkh 2 0.152239 3722.71 1 6 CACCTG AGTACATGTTGTTCT + +4 transfac_pro__M07123-CG9727-Rfx 1 0.152239 3722.71 1 6 CACCTG CTCCCTGGCAACAGC + +4 cisbp__M4449-CTCF-SMC3-usp-vtd 4 0.152239 3722.71 1 6 CACCTG GCGCCCCCTGGTGGC - +4 cisbp__M4585-CTCF-SMC3-usp-vtd 4 0.152239 3722.71 1 6 CACCTG GCGCCCCCTGGTGGC - +4 neph__UW.Motif.0366 7 0.152239 3722.71 1 6 CACCTG CAAAAATCATTTTTT - +4 taipale_cyt_meth__NR3C1_NGWACANNNYGTWCN_eDBD_meth-fkh 2 0.152239 3722.71 1 6 CACCTG AGTACATAATGTACT - +4 transfac_pro__M00479-btd-Spps 6 0.152239 3722.71 1 6 CACCTG CGGCCCCACCTCTTT - +4 predrem__nrMotif1412 4 0.152317 3724.6 1 6 CACCTG CCTCCTCCTCC + +4 transfac_pro__M03852-SREBP 2 0.152317 3724.6 1 6 CACCTG CTCACCCCACG + +4 cisbp__M1691 5 0.152317 3724.6 1 6 CACCTG GCGTTGACTTT - +4 fantom__motif160_AGCCGGTAACG 3 0.152317 3724.6 1 6 CACCTG CGTTACCGGCT - +4 hocomoco__NR5A2_MOUSE.H11MO.0.A-ERR-EcR-Hr4-ftz-f1-srl-usp 1 0.152317 3724.6 1 6 CACCTG TGACCTTGAAC - +4 hocomoco__ZN652_HUMAN.H11MO.0.D 3 0.152317 3724.6 1 6 CACCTG ATTAACCCTTT - +4 neph__UW.Motif.0279 2 0.152317 3724.6 1 6 CACCTG TCCACTTCCAG - +4 transfac_pro__M05485 5 0.152317 3724.6 1 6 CACCTG GCATTTACCCG - +4 transfac_pro__M09529 3 0.152317 3724.6 1 6 CACCTG TGACAGCTGGT - +4 cisbp__M0098 -1 0.152317 3724.6 1 5 CACCTG ACCTGCAGGCA - +4 cisbp__M1471-tll 5 0.152777 3735.86 1 6 CACCTG AAATTGACCTCA + +4 cisbp__M5375-aop-Eip74EF-Ets21C 0 0.152777 3735.86 1 6 CACCTG AACCCGGAAGTA + +4 flyfactorsurvey__nau_SANGER_5_FBgn0002922-Fer1-nau 2 0.152777 3735.86 1 6 CACCTG AACAGCTGACGC + +4 cisbp__M3562 0 0.152777 3735.86 1 6 CACCTG GACCTGTCACTG - +4 neph__UW.Motif.0179 5 0.152777 3735.86 1 6 CACCTG AAAATTTCCTTT - +4 neph__UW.Motif.0232 1 0.152777 3735.86 1 6 CACCTG TCACAATCTGCT - +4 transfac_pro__M05880 6 0.152777 3735.86 1 6 CACCTG TCACCCTACCCT - +4 transfac_pro__M05893 5 0.152777 3735.86 1 6 CACCTG ACCGCCCCCTCT - +4 transfac_pro__M06335 6 0.152777 3735.86 1 6 CACCTG TTTGCCTACCCT - +4 transfac_pro__M06699-CG2120 6 0.152777 3735.86 1 6 CACCTG TCTTTCCACTTG - +4 transfac_pro__M06706 6 0.152777 3735.86 1 6 CACCTG GCGTCATACCCT - +4 transfac_pro__M06495 7 0.152777 3735.86 1 5 CACCTG TGTAACAGACCG + +4 homer__AGGTGHCAGACA_Tbox_Smad-Med-Smox 7 0.152777 3735.86 1 5 CACCTG TGTCTGGCACCT - +4 transfac_pro__M05626 7 0.152777 3735.86 1 5 CACCTG CAAGCTGTACCC - +4 transfac_pro__M05790 7 0.152777 3735.86 1 5 CACCTG CCGGATTAACCT - +4 transfac_pro__M05797 7 0.152777 3735.86 1 5 CACCTG TATTTTTAACCA - +4 transfac_pro__M05812 7 0.152777 3735.86 1 5 CACCTG CAAGCCTTACCA - +4 transfac_pro__M05854 7 0.152777 3735.86 1 5 CACCTG GCGGCTTTACCA - +4 transfac_pro__M05960-crol 7 0.152777 3735.86 1 5 CACCTG TCTCTTTTACCG - +4 transfac_pro__M06565 7 0.152777 3735.86 1 5 CACCTG CCGCATTAACCT - +4 neph__UW.Motif.0082 10 0.155236 3796 1 6 CACCTG CAGATGGCAATTTCTG + +4 neph__UW.Motif.0406 9 0.155236 3796 1 6 CACCTG GGCCTCTGCCGCCAGC + +4 neph__UW.Motif.0474 1 0.155236 3796 1 6 CACCTG CCAGCACAAAGAAAAA + +4 neph__UW.Motif.0384 9 0.155236 3796 1 6 CACCTG AGCCAGATACATTTTT - +4 neph__UW.Motif.0610 8 0.155236 3796 1 6 CACCTG TCTGCCATTTTCTGAA - +4 neph__UW.Motif.0633 -1 0.155236 3796 1 5 CACCTG AATTGGATTCCAAATT + +4 taipale_tf_pairs__HOXB13_TBX3_NNNRTAAATCACACNN_CAP_repr-bi 11 0.155236 3796 1 5 CACCTG CTCATAAATCACACCT + +4 neph__UW.Motif.0496 11 0.155236 3796 1 5 CACCTG CAGTTCACTGCATCCT - +4 cisbp__M3784-eg-ERR-kni-knrl 14 0.156014 3815.02 1 6 CACCTG AAGTAGGTCACCGTGACCTACTT + +4 transfac_public__M00515-eg-ERR-kni-knrl 14 0.156014 3815.02 1 6 CACCTG AAGTAGGTCACCGTGACCTACTT - +4 neph__UW.Motif.0365 4 0.156603 3829.42 1 6 CACCTG AGCAGGGCTGGCTG + +4 neph__UW.Motif.0660 4 0.156603 3829.42 1 6 CACCTG AAAAACCCAGCTCT + +4 transfac_pro__M02820-TfAP-2 1 0.156603 3829.42 1 6 CACCTG TTGCCCTAGGGCAT + +4 swissregulon__hs__RORA.p2-EcR-Eip75B-Hr3-svp-usp 2 0.156603 3829.42 1 6 CACCTG CTGACCTAGTTTTC - +4 taipale__MEIS2_DBD_TTGACAGSTGTCAA-achi-hth-nau-vis 4 0.156603 3829.42 1 6 CACCTG TTGACAGCTGTCAA - +4 taipale_tf_pairs__FOXO1_ETV4_RWMAACAGGAARNN_CAP-Ets96B-foxo 3 0.156603 3829.42 1 6 CACCTG TACTTCCTGTTTAC - +4 cisbp__M0235-Clk-Max-Mitf-SREBP-Usf-bigmax-cnc-cyc-tgo 2 0.157252 3845.28 1 6 CACCTG GTCACGTG + +4 cisbp__M0307 1 0.157252 3845.28 1 6 CACCTG AAACGTAG + +4 hocomoco__MXI1_MOUSE.H11MO.1.A-Max-Myc 1 0.157252 3845.28 1 6 CACCTG CCACGTGG + +4 predrem__nrMotif1066 2 0.157252 3845.28 1 6 CACCTG ATGACCTT + +4 predrem__nrMotif1574 1 0.157252 3845.28 1 6 CACCTG TCAACTCT + +4 predrem__nrMotif2634 0 0.157252 3845.28 1 6 CACCTG GACCCGAG + +4 scertf__macisaac.SKO1 0 0.157252 3845.28 1 6 CACCTG TACGTCAT + +4 scertf__morozov.INO2 1 0.157252 3845.28 1 6 CACCTG TCACATGC + +4 yetfasco__YCL067C_2102 2 0.157252 3845.28 1 6 CACCTG TCAACATG + +4 cisbp__M0491 0 0.157252 3845.28 1 6 CACCTG CCCCTGCT - +4 cisbp__M1329 0 0.157252 3845.28 1 6 CACCTG AACCGGTA - +4 cisbp__M4353-CG7786-gt-Pdp1-vri 1 0.157252 3845.28 1 6 CACCTG TTACGTAA - +4 cisbp__M6255-brm-CoRest-CycT-ebi-GATAe-grn-HLH3B-nej-pnr-RpII215-Snr1-srp-svp 2 0.157252 3845.28 1 6 CACCTG CTTATCTC - +4 hocomoco__NR1I3_HUMAN.H11MO.1.D-EcR-Hnf4-usp 2 0.157252 3845.28 1 6 CACCTG CTGAACTT - +4 stark__GCANGTCC 1 0.157252 3845.28 1 6 CACCTG GGACATGC - +4 taipale_cyt_meth__MLX_NCAYGTGN_eDBD_meth-bigmax-Mitf 1 0.157252 3845.28 1 6 CACCTG TCACATGA - +4 transfac_pro__M01029-Mitf 1 0.157252 3845.28 1 6 CACCTG TCACATGA - +4 transfac_pro__M07284-Ets97D 1 0.157252 3845.28 1 6 CACCTG TTTCCTGT - +4 predrem__nrMotif1053 -1 0.157252 3845.28 1 5 CACCTG ATCTACAA + +4 transfac_pro__M04802-kay 3 0.157252 3845.28 1 5 CACCTG ACTCACCA + +4 yetfasco__YOL067C_1494 3 0.157252 3845.28 1 5 CACCTG AGTGACCG + +4 cisbp__M0809-gcm-gcm2 -1 0.157252 3845.28 1 5 CACCTG ACCCGCAT - +4 hdpi__SMAD4-Med 3 0.157252 3845.28 1 5 CACCTG GCAAACCC - +4 predrem__nrMotif1205 -1 0.157252 3845.28 1 5 CACCTG AACTTAGA - +4 predrem__nrMotif432 -1 0.157252 3845.28 1 5 CACCTG AACTGGCA - +4 tfdimers__MD00582 12 0.157254 3845.33 1 6 CACCTG CGGCGCCCCGGGCACCTGTCACTGGCCCA - +4 taipale_cyt_meth__GMEB2_NKACGTNNNNTACGTMN_eDBD_meth_repr 1 0.157365 3848.05 1 6 CACCTG TTACGTACCGTACGTAA + +4 taipale_tf_pairs__ERF_SREBF2_NSCGGAARNCACGTGNN_CAP_repr-Ets21C-SREBP 9 0.157365 3848.05 1 6 CACCTG GCCGGAAATCACGTGAT + +4 transfac_pro__M00965-EcR-svp-usp 1 0.157365 3848.05 1 6 CACCTG TGACCTCTACTGACCCC + +4 transfac_pro__M02958-ct 10 0.157365 3848.05 1 6 CACCTG ACCGGTTGATCACCTGA + +4 transfac_pro__M01345-Optix-so 8 0.157365 3848.05 1 6 CACCTG AATATTGATACCCTATT - +4 cisbp__M0357-gt 3 0.15739 3848.65 1 6 CACCTG GCTTACGTAA + +4 flyfactorsurvey__D19B-F10-12_SOLEXA_FBgn0022699-D19B 1 0.15739 3848.65 1 6 CACCTG ATACCCTGTA + +4 hocomoco__OLIG2_HUMAN.H11MO.1.B-HLH3B-amos 1 0.15739 3848.65 1 6 CACCTG CCATCTGTTT + +4 predrem__nrMotif12 4 0.15739 3848.65 1 6 CACCTG TTCCCAGCTC + +4 taipale__MSC_full_AACAGCTGTT_repr-ac-amos-ase-crp-dimm-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.15739 3848.65 1 6 CACCTG AACAGCTGTT + +4 taipale__NHLH1_DBD_CGCAGCTGCG-HLH4C 2 0.15739 3848.65 1 6 CACCTG CGCAGCTGCG + +4 taipale__TFEB_full_RTCACGTGAY-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.15739 3848.65 1 6 CACCTG ATCACGTGAC + +4 cisbp__M0506-Kdm4A-Kdm4B 1 0.15739 3848.65 1 6 CACCTG ACCCCTAATT - +4 cisbp__M0634-dmrt11E-dmrt93B-dmrt99B-dsx 4 0.15739 3848.65 1 6 CACCTG TTGATACATT - +4 cisbp__M1514 1 0.15739 3848.65 1 6 CACCTG ATTTCTTGAA - +4 cisbp__M3311-GATAe-grn-pnr 3 0.15739 3848.65 1 6 CACCTG CCCCATCACG - +4 cisbp__M5670-HLH4C 2 0.15739 3848.65 1 6 CACCTG CGCAGCTGCG - +4 predrem__nrMotif1144 4 0.15739 3848.65 1 6 CACCTG TTAGCACTTT - +4 predrem__nrMotif1774 4 0.15739 3848.65 1 6 CACCTG AGCCATCCTG - +4 predrem__nrMotif422 1 0.15739 3848.65 1 6 CACCTG TTTCCTTTAT - +4 taipale_cyt_meth__ASCL1_NRCAGCTGYN_eDBD-ac-ase-l(1)sc-sc 2 0.15739 3848.65 1 6 CACCTG GGCAGCTGCC - +4 transfac_public__M00075-GATAe-grn-pnr 3 0.15739 3848.65 1 6 CACCTG CCCTATCACG - +4 yetfasco__YLR228C_2122 0 0.15739 3848.65 1 6 CACCTG TTCCGGACTT - +4 predrem__nrMotif2526 5 0.15739 3848.65 1 5 CACCTG AAACTGACAT + +4 cisbp__M0813-gcm-gcm2 -1 0.15739 3848.65 1 5 CACCTG ACCCGCATGT - +4 neph__UW.Motif.0072 5 0.15739 3848.65 1 5 CACCTG CAGCCTTCCT - +4 taipale_cyt_meth__ZNF449_MAGCCCAACC_eDBD_meth_repr 6 0.15739 3848.65 1 4 CACCTG ACGCCCAACC + +4 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNYMATTA_CAP_repr-TfAP-2 0 0.157603 3853.87 1 6 CACCTG CGCCTGAGGGCATGCGTAATTA + +4 taipale_tf_pairs__GCM2_FIGLA_NCASSTGNNNNNNNNRTRCGGG_CAP_repr-gcm-gcm2 15 0.157603 3853.87 1 6 CACCTG CCCGCATCAAGAAAACACCTGG - +4 taipale_tf_pairs__HOXB2_TBX21_NGGTGTGNNNNNTMATTWGCRN_CAP_repr-pb 17 0.157603 3853.87 1 5 CACCTG GTGCTAATTACTCTCCACACCT - +4 predrem__nrMotif1878 1 0.15795 3862.35 1 6 CACCTG GCTCCTG + +4 predrem__nrMotif1973 0 0.15795 3862.35 1 6 CACCTG TATCTCA + +4 predrem__nrMotif2443 1 0.15795 3862.35 1 6 CACCTG TGAGCTG + +4 swissregulon__sacCer__CBF1-Mitf-SREBP-Sirt6-Usf-bigmax-cnc-cyc-tgo 1 0.15795 3862.35 1 6 CACCTG TCACGTG + +4 cisbp__M5245-tll 1 0.15795 3862.35 1 6 CACCTG TGACTTT - +4 yetfasco__YBR267W_489-CG6769 0 0.15795 3862.35 1 6 CACCTG CCCCTGA - +4 predrem__nrMotif1396 2 0.15795 3862.35 1 5 CACCTG GCCAACT + +4 predrem__nrMotif1416 2 0.15795 3862.35 1 5 CACCTG TCTACCC + +4 predrem__nrMotif259 2 0.15795 3862.35 1 5 CACCTG GTCTCCT + +4 hdpi__LASS4-schlank -1 0.15795 3862.35 1 5 CACCTG ACCGTCA - +4 predrem__nrMotif2672 -1 0.15795 3862.35 1 5 CACCTG TCCTAAT - +4 predrem__nrMotif865 2 0.15795 3862.35 1 5 CACCTG TTCAACT - +4 hocomoco__SRF_HUMAN.H11MO.0.A-bs 1 0.158706 3880.85 1 6 CACCTG TTGCCTTATATGGGCATG + +4 cisbp__M4559-Chd1-CTCF-SMC3-usp-vtd 7 0.158706 3880.85 1 6 CACCTG ATAGCGCCCCCTGGTGGC - +4 cisbp__M3783-btd-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 5 0.158723 3881.25 1 6 CACCTG CGGGTGACCTTTGACCCCTGA + +4 cisbp__M4427-Chd1-CTCF-SMC3-usp-vtd 7 0.158723 3881.25 1 6 CACCTG ACAGCGCCCCCTGGTGGCCAC - +4 cisbp__M4647-CTCF-SMC3-usp-vtd 6 0.158723 3881.25 1 6 CACCTG TAGTGCCCCCTAGTGGCCAAA - +4 transfac_public__M00512-btd-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 5 0.158723 3881.25 1 6 CACCTG CGGATGACCTTTGACCCCTGA - +4 cisbp__M0222-Max-Myc-Sap30 2 0.15931 3895.6 1 6 CACCTG ACCACGTGG + +4 cisbp__M1087-bap-scro-vnd 2 0.15931 3895.6 1 6 CACCTG ACCACTTAA + +4 flyfactorsurvey__tgo_sima_SANGER_5_FBgn0015014-sima-tgo 1 0.15931 3895.6 1 6 CACCTG GTACGTGAC + +4 jaspar__MA1058.1 2 0.15931 3895.6 1 6 CACCTG CGTACGGTT + +4 predrem__nrMotif1927 2 0.15931 3895.6 1 6 CACCTG GGAACCTCC + +4 predrem__nrMotif2182 0 0.15931 3895.6 1 6 CACCTG TACTTGTTT + +4 predrem__nrMotif488 3 0.15931 3895.6 1 6 CACCTG CTCTCCCTT + +4 predrem__nrMotif683 3 0.15931 3895.6 1 6 CACCTG CTTGGCCTG + +4 cisbp__M0987-ara-caup-mirr 3 0.15931 3895.6 1 6 CACCTG AATAACATG - +4 predrem__nrMotif1118 3 0.15931 3895.6 1 6 CACCTG TCAGACCCA - +4 predrem__nrMotif1569 3 0.15931 3895.6 1 6 CACCTG GGGCACTTC - +4 predrem__nrMotif1989 1 0.15931 3895.6 1 6 CACCTG TCATCTCTG - +4 predrem__nrMotif51 0 0.15931 3895.6 1 6 CACCTG CCCCTCCCC - +4 predrem__nrMotif955 0 0.15931 3895.6 1 6 CACCTG CACCCTGGA - +4 transfac_pro__M00927-crp 1 0.15931 3895.6 1 6 CACCTG GCAGCTGGT - +4 predrem__nrMotif2118-TfAP-2 -1 0.15931 3895.6 1 5 CACCTG GCCTCCGGC + +4 transfac_pro__M04845-CTCF-SMC3-usp-vtd 4 0.15931 3895.6 1 5 CACCTG GCGCCCCCT - +4 dbcorrdb__CTCF__ENCSR000AMA_1__m1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DPP_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DTO_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__CTCF__ENCSR000DUX_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__CTCF__ENCSR000DVH_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__RAD21__ENCSR000BLD_1__m1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA + +4 dbcorrdb__RAD21__ENCSR000BLY_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.15932 3895.84 1 6 CACCTG TATAGTGCCCCCTGGTGGCC + +4 dbcorrdb__RELA__ENCSR000EAW_1__m1-Dif-dl-Rel-shn 11 0.15932 3895.84 1 6 CACCTG ACCTGGGAAATCCCCTACTC + +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m6-egg 5 0.15932 3895.84 1 6 CACCTG GGTGCCTCCATTCTGCGGTG + +4 hocomoco__ZN322_HUMAN.H11MO.0.B 1 0.15932 3895.84 1 6 CACCTG GAGCCTGGTACAGAGCCTGG + +4 dbcorrdb__CTCF__ENCSR000ALV_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA - +4 dbcorrdb__CTCF__ENCSR000ANO_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000ANS_1__m1-CTCF-SMC3-usp-vtd 7 0.15932 3895.84 1 6 CACCTG ATAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__CTCF__ENCSR000DQI_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DTI_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DUP_1__m1-Chd1-CTCF-SMC3-usp-vtd 8 0.15932 3895.84 1 6 CACCTG TATAGCGCCCCCTGGTGGCC - +4 dbcorrdb__CTCF__ENCSR000DVA_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC - +4 dbcorrdb__CTCF__ENCSR000DWQ_1__m1-CTCF-SMC3-usp-vtd 6 0.15932 3895.84 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA - +4 dbcorrdb__ESRRA__ENCSR000EEW_1__m1-ERR-srl 4 0.15932 3895.84 1 6 CACCTG CTGTGACCTTGGGCCGGCCC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m6-RpII215 1 0.15932 3895.84 1 6 CACCTG ACACATGGTCGCATGCGGAA - +4 dbcorrdb__REST__ENCSR000BQS_1__m2-CTCF 16 0.15932 3895.84 1 4 CACCTG GCGGCGGCGGGTTCAGCACC - +4 swissregulon__sacCer__AFT2 1 0.159416 3898.21 1 5 CACCTG ACACCC + +4 transfac_pro__M02012-sima 1 0.159416 3898.21 1 5 CACCTG GCACGT + +4 transfac_pro__M09508 -1 0.159416 3898.21 1 5 CACCTG ACCAGT + +4 fantom__motif39_CCAAGT -1 0.159416 3898.21 1 5 CACCTG ACTTGG - +4 transfac_pro__M01032-EcR-Hnf4 1 0.159416 3898.21 1 5 CACCTG TGAACT - +4 transfac_pro__M02031 1 0.159416 3898.21 1 5 CACCTG CTTCCT - +4 cisbp__M2013-Six4 3 0.159416 3898.21 1 3 CACCTG TGATAC + +4 jaspar__MA0204.1-Six4 3 0.159416 3898.21 1 3 CACCTG TGATAC + +4 cisbp__M6397-EcR-ERR-Hr4-usp 1 0.159669 3904.39 1 6 CACCTG TGACCTTGAACTT + +4 transfac_pro__M03860-ac-ase-cnc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 4 0.159669 3904.39 1 6 CACCTG CGCCCACGTGACC + +4 transfac_pro__M07926-ZIPIC 4 0.159669 3904.39 1 6 CACCTG TCCATCCCTGGTA + +4 cisbp__M0074 4 0.159669 3904.39 1 6 CACCTG TTTTTACCGACAA - +4 hocomoco__NR6A1_HUMAN.H11MO.0.B-ERR-EcR-Hr4-usp 1 0.159669 3904.39 1 6 CACCTG TGACCTTGAACTT - +4 jaspar__MA1010.1 4 0.159669 3904.39 1 6 CACCTG TTTATACCGACAA - +4 transfac_pro__M07467-Six4-so 3 0.159669 3904.39 1 6 CACCTG TGAAACCTGAGCC - +4 transfac_pro__M08891-CG12018-Dif-dl-Rel 7 0.159669 3904.39 1 6 CACCTG GGGGAAGTCCCCC - +4 taipale_tf_pairs__POU2F1_ETV4_NCCGGATATGCAN_CAP_1-Ets96B-nub-pdm2 -1 0.159669 3904.39 1 5 CACCTG ACCGGATATGCAA + +4 neph__UW.Motif.0313 8 0.159669 3904.39 1 5 CACCTG CAGGAATGTTTCT - +4 transfac_pro__M07960-EcR-Hnf4-svp 9 0.159669 3904.39 1 4 CACCTG TGACCTTTGGACC - +4 factorbook__ETS1-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-aop-bs-grn-pnr-pnt 3 0.160481 3924.24 1 6 CACCTG CATTTCCTGTT + +4 hocomoco__MXI1_HUMAN.H11MO.1.A-Max-Myc 2 0.160481 3924.24 1 6 CACCTG CCCACGTGCTC + +4 predrem__nrMotif1872 4 0.160481 3924.24 1 6 CACCTG CAGCCGCCTGC + +4 swissregulon__sacCer__PBF2 0 0.160481 3924.24 1 6 CACCTG CACCTCATCGC + +4 transfac_pro__M07050-cyc-Mitf 2 0.160481 3924.24 1 6 CACCTG GTCACATGATT + +4 hocomoco__GATA2_HUMAN.H11MO.1.A-CoRest-CycT-GATAe-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.160481 3924.24 1 6 CACCTG TTCTTATCTGT - +4 hocomoco__MYC_HUMAN.H11MO.0.A-E2f1-Max-Myc 3 0.160481 3924.24 1 6 CACCTG GAGCACGTGGC - +4 predrem__nrMotif376 4 0.160481 3924.24 1 6 CACCTG CCTCCACCCCC - +4 tiffin__TIFDMEM0000062 0 0.160481 3924.24 1 6 CACCTG TACATATTTAT - +4 transfac_pro__M07714-croc-FoxL1-foxo-slp1-slp2 5 0.160481 3924.24 1 6 CACCTG GTGTTTACGTA - +4 hocomoco__BRAC_HUMAN.H11MO.1.B-H15-bi-byn-mid-org-1 6 0.160481 3924.24 1 5 CACCTG ATTTCACACCT - +4 factorbook__CTCF-CTCF-SMC3-usp-vtd 4 0.160801 3932.07 1 6 CACCTG GCGCCCCCTGGTGGC + +4 homer__NAGATWNBNATCTNN_GATA-GATAe-grn-pnr 8 0.160801 3932.07 1 6 CACCTG CAGATAATTATCTGT + +4 neph__UW.Motif.0089 9 0.160801 3932.07 1 6 CACCTG AGGAAATAAATGCTG + +4 neph__UW.Motif.0377 6 0.160801 3932.07 1 6 CACCTG AAAAAGAAGCTGAAG + +4 neph__UW.Motif.0390 2 0.160801 3932.07 1 6 CACCTG AGCACTTTGCAAGGC + +4 cisbp__M2309-CG9727-Rfx 1 0.160801 3932.07 1 6 CACCTG CTCCCTGGCAACAGC - +4 cisbp__M4445-CTCF-SMC3-usp-vtd 5 0.160801 3932.07 1 6 CACCTG GGCGCCCCCTGGTGG - +4 cisbp__M4583-CTCF-SMC3-usp-vtd 5 0.160801 3932.07 1 6 CACCTG AGCGCCCCCTGGTGG - +4 cisbp__M4614-CTCF-SMC3-usp-vtd 4 0.160801 3932.07 1 6 CACCTG GCGCCCCCTGGTGGC - +4 neph__UW.Motif.0162 3 0.160801 3932.07 1 6 CACCTG AGGAATCTGGGTTTT - +4 neph__UW.Motif.0239 10 0.160801 3932.07 1 5 CACCTG AAAAACATCATTTCT + +4 hocomoco__PRDM5_MOUSE.H11MO.0.A-CG1233-CG11456-CG32767-CG43347 -1 0.160801 3932.07 1 5 CACCTG ACCCTGCTCTCCAGG - +4 neph__UW.Motif.0582 10 0.160801 3932.07 1 5 CACCTG CTGTCTCTCTGAGCT - +4 taipale_tf_pairs__GCM1_ELF1_NNMGGAARTGCKGGN_CAP_repr-Eip74EF-gcm-gcm2 -1 0.160801 3932.07 1 5 CACCTG ACCCGCATTTCCGCA - +4 taipale_tf_pairs__GCM1_MAX_CACGTGNNNGCGGGY_CAP-gcm-gcm2-Max -1 0.160801 3932.07 1 5 CACCTG ACCCGCATCCACGTG - +4 transfac_pro__M05749 11 0.160801 3932.07 1 4 CACCTG ATGGATGTCATCACC - +4 c2h2_zfs__M4012-CG4854 11 0.16083 3932.78 1 6 CACCTG GTGTTGCCAACCACCTTCACCCCAT - +4 cisbp__M0366 5 0.1611 3939.38 1 6 CACCTG ATGCTGACGTGT + +4 homer__AGGAAACAGCTG_ETS_E-box-HLH3B 6 0.1611 3939.38 1 6 CACCTG AGGAAACAGCTG + +4 neph__UW.Motif.0251 5 0.1611 3939.38 1 6 CACCTG CAAGTTACTTCA + +4 neph__UW.Motif.0296 6 0.1611 3939.38 1 6 CACCTG CAGTCTCATCTC + +4 taipale__ELF3_DBD_WACCCGGAAGTA-aop-Eip74EF-Ets21C 0 0.1611 3939.38 1 6 CACCTG AACCCGGAAGTA + +4 cisbp__M5114-Fer1-nau 2 0.1611 3939.38 1 6 CACCTG AACAGCTGACGC - +4 cisbp__M6154 5 0.1611 3939.38 1 6 CACCTG CCTTCTTCCTTA - +4 neph__UW.Motif.0125 5 0.1611 3939.38 1 6 CACCTG GCCAGCTCCTTC - +4 predrem__nrMotif878 1 0.1611 3939.38 1 6 CACCTG CTGCCTGACACC - +4 taipale__ELF4_full_AACCCGGAAGTR_repr-aop-Eip74EF-Ets21C 0 0.1611 3939.38 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__ATF2_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 3 0.1611 3939.38 1 6 CACCTG GGTGACGTCACC - +4 taipale_cyt_meth__CREB5_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 3 0.1611 3939.38 1 6 CACCTG CATGACGTCACC - +4 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_FL-amos-Fer1-Fer3-HLH54F-nau 3 0.1611 3939.38 1 6 CACCTG CAACAGCTGTCG - +4 transfac_public__M00419 0 0.1611 3939.38 1 6 CACCTG GACCTGTCACTG - +4 transfac_pro__M05659 7 0.1611 3939.38 1 5 CACCTG TCTTATAAACCG - +4 transfac_pro__M06422 7 0.1611 3939.38 1 5 CACCTG TCTCTTGCACCA - +4 transfac_pro__M06525 7 0.1611 3939.38 1 5 CACCTG TCTGCCCAACCA - +4 transfac_pro__M06530 7 0.1611 3939.38 1 5 CACCTG GCGGCGGCACCA - +4 transfac_pro__M06588 7 0.1611 3939.38 1 5 CACCTG TCAGACTAACCA - +4 neph__UW.Motif.0445 4 0.164 4010.3 1 6 CACCTG AAAATTTCTGAGTCTT + +4 neph__UW.Motif.0608 7 0.164 4010.3 1 6 CACCTG AACAAAACAACAAAAA + +4 neph__UW.Motif.0197 10 0.164 4010.3 1 6 CACCTG GGAAGGGAGGGGGCTG - +4 neph__UW.Motif.0529 1 0.164 4010.3 1 6 CACCTG TTTCCTGGGAATTTGA - +4 neph__UW.Motif.0557 7 0.164 4010.3 1 6 CACCTG CATCTCGCGGCTGCTG - +4 transfac_pro__M03128-ac-amos-ase-dimm-hth-l(1)sc-sc 5 0.164 4010.3 1 6 CACCTG TGTAACAGCTGTTAAA - +4 transfac_pro__M05828 11 0.164 4010.3 1 5 CACCTG GCGTCCATTATCACTT - +4 cisbp__M5619-achi-hth-nau-vis 4 0.165275 4041.47 1 6 CACCTG TTGACAGCTGTCAA + +4 neph__UW.Motif.0480 5 0.165275 4041.47 1 6 CACCTG GAAAGATGCTGGGA + +4 taipale_cyt_meth__CREB3L1_NTGCCACGTGTACN_eDBD-CrebA 4 0.165275 4041.47 1 6 CACCTG GTGCCACGTGTACA + +4 transfac_pro__M05560-jing 6 0.165275 4041.47 1 6 CACCTG GGGGTGGACCTCAT + +4 transfac_pro__M09442 6 0.165275 4041.47 1 6 CACCTG AAACAAAACCGGAA + +4 yetfasco__YMR280C_33 0 0.165275 4041.47 1 6 CACCTG TTCCGTTCGTCCGA + +4 neph__UW.Motif.0349 3 0.165275 4041.47 1 6 CACCTG GAGACACTTCCTCT - +4 taipale_cyt_meth__ETV5_NCAGGAAGGAAGTN_eDBD_meth-Ets96B 7 0.165275 4041.47 1 6 CACCTG CACTTCCTTCCTGT - +4 transfac_pro__M07756-Abd-B 9 0.165275 4041.47 1 5 CACCTG GGCAGTAACGACCT + +4 taipale_tf_pairs__GCM1_FOXI1_RTMAACATRNGGGN_CAP_repr-gcm-gcm2 -1 0.165275 4041.47 1 5 CACCTG ACCCGCATGTTTAC - +4 taipale_tf_pairs__RFX3_SRF_NRGYAACNNNNNCCTWWWNNGGN_CAP_repr-bs-Rfx 10 0.165298 4042.03 1 6 CACCTG TGGCAACGATTACCTTATAAGGT + +4 cisbp__M0880-bap 0 0.165382 4044.08 1 6 CACCTG CACTTAAG + +4 cisbp__M4086-Max-Usf 1 0.165382 4044.08 1 6 CACCTG CCACGTGC + +4 cisbp__M4679-Max-Myc-Sap30 1 0.165382 4044.08 1 6 CACCTG CCACGTGG + +4 cisbp__M6388-EcR-Hnf4-usp 2 0.165382 4044.08 1 6 CACCTG ATGAACTT + +4 swissregulon__sacCer__PHO4-Max-Myc 1 0.165382 4044.08 1 6 CACCTG GCACGTGC + +4 cisbp__M0328 1 0.165382 4044.08 1 6 CACCTG CCACGTCA - +4 cisbp__M0628-dmrt11E-dmrt93B-dsx 2 0.165382 4044.08 1 6 CACCTG GATACATT - +4 cisbp__M1372 2 0.165382 4044.08 1 6 CACCTG GTTACCCG - +4 hdpi__ZNF71-EcR-Hr78-eg-kni-knrl-svp-usp 1 0.165382 4044.08 1 6 CACCTG TGACCCCT - +4 neph__UW.Motif.0258 2 0.165382 4044.08 1 6 CACCTG GTCACTTC - +4 swissregulon__hs__FOX_C1_C2_.p2-croc 0 0.165382 4044.08 1 6 CACCTG TACTTACC - +4 predrem__nrMotif1579 3 0.165382 4044.08 1 5 CACCTG GCACACCC + +4 predrem__nrMotif2143 -1 0.165382 4044.08 1 5 CACCTG ACATATGT + +4 predrem__nrMotif483 3 0.165382 4044.08 1 5 CACCTG AGTCACCA + +4 transfac_pro__M04870-HDAC1 3 0.165382 4044.08 1 5 CACCTG CTGGACTT + +4 predrem__nrMotif1401 -1 0.165382 4044.08 1 5 CACCTG ACATGCCA - +4 transfac_pro__M02083 -1 0.165382 4044.08 1 5 CACCTG TCCTGTCA - +4 cisbp__M0557 4 0.165382 4044.08 1 4 CACCTG GCAGCACC - +4 cisbp__M0238-Max-Mitf-Mondo-SREBP-Usf-bigmax-tgo 2 0.16562 4049.92 1 6 CACCTG ATCACGTGAT + +4 cisbp__M1384 4 0.16562 4049.92 1 6 CACCTG AGCGAATCTT + +4 cisbp__M1409 1 0.16562 4049.92 1 6 CACCTG ACACGCAACC + +4 idmmpmm__ttk-ttk 3 0.16562 4049.92 1 6 CACCTG ATTATCCTGG + +4 jaspar__MA0109.1 1 0.16562 4049.92 1 6 CACCTG AACCTTATAT + +4 jaspar__MA0359.1 0 0.16562 4049.92 1 6 CACCTG CACCCATACA + +4 jaspar__MA1011.1-Clk-Mitf-Mondo-SREBP-Sirt6-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.16562 4049.92 1 6 CACCTG GTCACGTGAC + +4 predrem__nrMotif0 0 0.16562 4049.92 1 6 CACCTG GGCCTGGCTT + +4 predrem__nrMotif2126 3 0.16562 4049.92 1 6 CACCTG CGGCCCCTCC + +4 stark__TYRACACTTK 4 0.16562 4049.92 1 6 CACCTG TCAACACTTG + +4 transfac_pro__M00944 2 0.16562 4049.92 1 6 CACCTG GTCACGTGAC + +4 transfac_pro__M07856-BtbVII 4 0.16562 4049.92 1 6 CACCTG AGAGTACATA + +4 cisbp__M1342 4 0.16562 4049.92 1 6 CACCTG AGGGAATCTT - +4 cisbp__M1572 3 0.16562 4049.92 1 6 CACCTG CCGTACCCCC - +4 cisbp__M1694 4 0.16562 4049.92 1 6 CACCTG CGTTGACCAT - +4 homer__KCCACGTGAC_NPAS2-Clk-Mitf-cnc-cyc 2 0.16562 4049.92 1 6 CACCTG GTCACGTGGC - +4 jaspar__MA1077.1 4 0.16562 4049.92 1 6 CACCTG CGTTGACCAT - +4 taipale__GABPA_full_ACCGGAAGTN_repr-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.16562 4049.92 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M01637 0 0.16562 4049.92 1 6 CACCTG CACCCATACA - +4 transfac_pro__M05304 1 0.16562 4049.92 1 6 CACCTG GAAGCTTCCT - +4 transfac_pro__M07513 3 0.16562 4049.92 1 6 CACCTG ATTTACCGTG - +4 transfac_pro__M07703-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.16562 4049.92 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M09545 4 0.16562 4049.92 1 6 CACCTG AAAATATCTT - +4 transfac_pro__M09558 3 0.16562 4049.92 1 6 CACCTG CCTTATCCTG - +4 yetfasco__YIL130W_2116 3 0.16562 4049.92 1 6 CACCTG CATATCCGGG - +4 cisbp__M1285 5 0.16562 4049.92 1 5 CACCTG ATATTTACCG + +4 predrem__nrMotif1588 5 0.16562 4049.92 1 5 CACCTG CCCCCTACCC + +4 transfac_pro__M06537-CTCF 5 0.16562 4049.92 1 5 CACCTG CCGCCCACCC - +4 cisbp__M2081 -2 0.16562 4049.92 1 4 CACCTG CCCGATCCGG + +4 jaspar__MA0276.1 -2 0.16562 4049.92 1 4 CACCTG CCCGATCCGG - +4 transfac_pro__M01672 -2 0.16562 4049.92 1 4 CACCTG CCCGATCCGG - +4 cisbp__M1548 0 0.166133 4062.46 1 6 CACCTG TACGTCA + +4 predrem__nrMotif1977 0 0.166133 4062.46 1 6 CACCTG CCCCTTG + +4 swissregulon__sacCer__REI1-CG6769 0 0.166133 4062.46 1 6 CACCTG CCCCTGA + +4 jaspar__MA0211.1-bap 0 0.166133 4062.46 1 6 CACCTG CACTTAA - +4 predrem__nrMotif1029 0 0.166133 4062.46 1 6 CACCTG AACTTTG - +4 predrem__nrMotif2582 1 0.166133 4062.46 1 6 CACCTG TTACTTG - +4 elemento__ACCCGGA -1 0.166133 4062.46 1 5 CACCTG ACCCGGA + +4 elemento__ACCGGAA-aop-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.166133 4062.46 1 5 CACCTG ACCGGAA + +4 jaspar__MA0173.1-CG11617 2 0.166133 4062.46 1 5 CACCTG TTAACAT + +4 predrem__nrMotif1285 -1 0.166133 4062.46 1 5 CACCTG GCCTTAG + +4 predrem__nrMotif1760 2 0.166133 4062.46 1 5 CACCTG TGAAGCT + +4 cisbp__M4231 2 0.166133 4062.46 1 5 CACCTG TGTGCCT - +4 hdpi__PDCD11-CG5728 -1 0.166133 4062.46 1 5 CACCTG ACCGCTG - +4 predrem__nrMotif938 -2 0.166133 4062.46 1 4 CACCTG CCTGCTA - +4 cisbp__M5985 3 0.166294 4066.39 1 6 CACCTG GGGTACACGGTGTACCG + +4 taipale__Ar_DBD_RRGNACANNNTGTNCYY_repr 3 0.166294 4066.39 1 6 CACCTG GGGTACACGGTGTACCG + +4 taipale_tf_pairs__ETV2_TCF3_CASSTGNNCCGGAWRYN_CAP_repr-pnt 0 0.166294 4066.39 1 6 CACCTG CACGTGAACCGGAAGTG + +4 transfac_pro__M02828-Aef1 9 0.166294 4066.39 1 6 CACCTG TCTTTGGCGTACCCTAA + +4 transfac_public__M00280-Rfx 4 0.166294 4066.39 1 6 CACCTG TAGTAGCCTGGCAACAA + +4 cisbp__M4458-Chd1-CTCF-Hcf-SMC3-usp-vtd 6 0.166294 4066.39 1 6 CACCTG TGGCGCCCCCTGGTGGC - +4 cisbp__M0209-nau 1 0.167547 4097.02 1 6 CACCTG ACACCTGTC + +4 cisbp__M1030-bap-scro-vnd 2 0.167547 4097.02 1 6 CACCTG GCCACTTAA + +4 cisbp__M1407 1 0.167547 4097.02 1 6 CACCTG ACACGCAAC + +4 cisbp__M1543 2 0.167547 4097.02 1 6 CACCTG CTTACGTCA + +4 cisbp__M1563 2 0.167547 4097.02 1 6 CACCTG CGTACGGTT + +4 cisbp__M6160-Clk-cyc-Sirt6-tgo 2 0.167547 4097.02 1 6 CACCTG GTCACGTGC + +4 predrem__nrMotif1202 0 0.167547 4097.02 1 6 CACCTG TATCTGTTT + +4 predrem__nrMotif1280 3 0.167547 4097.02 1 6 CACCTG TTCACCCTC + +4 predrem__nrMotif1358 2 0.167547 4097.02 1 6 CACCTG TGAATCTTT + +4 predrem__nrMotif1403 0 0.167547 4097.02 1 6 CACCTG GCCCTGAAA + +4 swissregulon__sacCer__NRG1 3 0.167547 4097.02 1 6 CACCTG AGGACCCTG + +4 transfac_pro__M04731-Blimp-1 0 0.167547 4097.02 1 6 CACCTG CACTTTCAC + +4 cisbp__M0431-bowl-drm-odd-sob 3 0.167547 4097.02 1 6 CACCTG TGCTACCGT - +4 cisbp__M0660 0 0.167547 4097.02 1 6 CACCTG CACTTTTTG - +4 cisbp__M1393 3 0.167547 4097.02 1 6 CACCTG GCGTATCCT - +4 cisbp__M5232-sima-tgo 1 0.167547 4097.02 1 6 CACCTG GTACGTGAC - +4 flyfactorsurvey__ato_da_SANGER_5_2_FBgn0000413-CG8319-Oli-ato-da 1 0.167547 4097.02 1 6 CACCTG ACATCTGTC - +4 hocomoco__PRDM5_MOUSE.H11MO.1.A-CG1233-CG11456-CG32767-CG43347 2 0.167547 4097.02 1 6 CACCTG TTCTCCAGG - +4 predrem__nrMotif2429 1 0.167547 4097.02 1 6 CACCTG CCACCGCCT - +4 predrem__nrMotif2466 2 0.167547 4097.02 1 6 CACCTG AGCACTTCC - +4 predrem__nrMotif2562 0 0.167547 4097.02 1 6 CACCTG AAACTTGGG - +4 transfac_pro__M00633 0 0.167547 4097.02 1 6 CACCTG CACCCCCAA - +4 transfac_pro__M04966-nej 1 0.167547 4097.02 1 6 CACCTG CTTCCTGTT - +4 transfac_pro__M06491 0 0.167547 4097.02 1 6 CACCTG CTCCTACCC - +4 transfac_pro__M07285-Ets97D-GATAe-grn-pnr-pnt 3 0.167547 4097.02 1 6 CACCTG CATTTCCTG - +4 predrem__nrMotif1390 4 0.167547 4097.02 1 5 CACCTG TGTGTCCCT + +4 predrem__nrMotif874 4 0.167547 4097.02 1 5 CACCTG TGTTTGCCT + +4 predrem__nrMotif451 -2 0.167547 4097.02 1 4 CACCTG CCTTTAAAA + +4 predrem__nrMotif330 -2 0.167547 4097.02 1 4 CACCTG CCTTGCTCC - +4 transfac_pro__M05158 5 0.167547 4097.02 1 4 CACCTG GAGTTTACC - +4 transfac_pro__M09411 3 0.167767 4102.4 1 6 CACCTG TCCCAACTACCAACTACC + +4 cisbp__M2378-bs 2 0.167767 4102.4 1 6 CACCTG CTTACCCAATTTGGCAAT - +4 cisbp__M4654-CTCF-SMC3-usp-vtd 5 0.167767 4102.4 1 6 CACCTG AGCGCCCCCTGGTGGCCA - +4 jaspar__MA0585.1-bs 2 0.167767 4102.4 1 6 CACCTG CTTACCCAATTTGGCAAT - +4 taipale_tf_pairs__GCM2_DLX2_RTRCGGGNNNNNTAATTR_CAP_repr-gcm-gcm2 9 0.167767 4102.4 1 6 CACCTG CAATTAATTAGCCCGCAT - +4 transfac_pro__M06476 3 0.167767 4102.4 1 6 CACCTG AAGAACCTTTTCCGACAA - +4 cisbp__M4886-hng1 1 0.167828 4103.9 1 5 CACCTG TTACGT + +4 flyfactorsurvey__CG9437_SANGER_5_FBgn0034599-hng1 1 0.167828 4103.9 1 5 CACCTG TTACGT + +4 transfac_pro__M09156 1 0.167828 4103.9 1 5 CACCTG TCACCA + +4 transfac_pro__M09268 1 0.167828 4103.9 1 5 CACCTG TCACCA + +4 transfac_pro__M09271 1 0.167828 4103.9 1 5 CACCTG TCACCA - +4 transfac_pro__M07734-gcm-gcm2 11 0.167996 4108.01 1 6 CACCTG TATGCGGGTAGTACCCGCATA - +4 taipale_tf_pairs__ETV7_TBX21_NSCGGAARNNNNNTCACACNN_CAP_repr-aop 16 0.167996 4108.01 1 5 CACCTG CCCGGAAGTACCATCACACCT + +4 yetfasco__YPL230W_509 0 0.167998 4108.06 1 5 CACCTG CCCCT - +4 neph__UW.Motif.0252 4 0.168377 4117.33 1 6 CACCTG CCAGCCCCAGCCA + +4 neph__UW.Motif.0451 5 0.168377 4117.33 1 6 CACCTG GAAGCCACATCCC + +4 transfac_pro__M06807-salm-salr 7 0.168377 4117.33 1 6 CACCTG AGGAATGTAACTG + +4 cisbp__M2839 5 0.168377 4117.33 1 6 CACCTG GTAACTAACTTTT - +4 cisbp__M6452-Rfx 1 0.168377 4117.33 1 6 CACCTG TTCCCTAGCAACA - +4 neph__UW.Motif.0115 7 0.168377 4117.33 1 6 CACCTG TGTGGGTTTGCTG - +4 transfac_public__M00219 5 0.168377 4117.33 1 6 CACCTG GTAACTAACTTTT - +4 transfac_pro__M06937 8 0.168377 4117.33 1 5 CACCTG GATGGACGGACCT - +4 transfac_pro__M06941 9 0.168377 4117.33 1 4 CACCTG GGATAGGTTAACC + +4 taipale_cyt_meth__NR5A2_YGACCTTGNNNCAAGGTCR_eDBD_repr-ERR-ftz-f1 1 0.168495 4120.22 1 6 CACCTG TGACCTTGACTCAAGGTCA + +4 transfac_pro__M06869 13 0.168495 4120.22 1 6 CACCTG TGTCGTTAATCGGGACTTA + +4 transfac_pro__M09133-brm-CG7839-maf-S-orb-SREBP-vtd 5 0.168495 4120.22 1 6 CACCTG TTTTTTGCCTTTTTTTTTT - +4 dbcorrdb__CTCF__ENCSR000DLW_1__m1-CTCF-SMC3-usp-vtd 8 0.16855 4121.55 1 6 CACCTG TATAGTGCCCCCTAGTGGCC + +4 dbcorrdb__CTCF__ENCSR000DPV_1__m1-CTCF-SMC3-usp-vtd 6 0.16855 4121.55 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA + +4 dbcorrdb__CTCF__ENCSR000DUH_1__m1-CTCF-SMC3-usp-vtd 6 0.16855 4121.55 1 6 CACCTG TAGCGCCCCCTGGTGGCCAC + +4 dbcorrdb__ELK4__ENCSR000EVB_1__m3 0 0.16855 4121.55 1 6 CACCTG TCCCTGCCGTCGCCTCGGCG + +4 dbcorrdb__POLR3A__ENCSR000DNU_1__m1-CG17209-usp 14 0.16855 4121.55 1 6 CACCTG GGTCTCGAACTCCTGACCTC + +4 taipale_tf_pairs__TFAP2C_ELK1_NGCCTNNGGSNNCGGAAGYN_CAP_repr-TfAP-2 0 0.16855 4121.55 1 6 CACCTG TGCCTCGGGCGGCGGAAGTG + +4 transfac_pro__M04787-Chd1-CTCF-Hcf-SMC3-usp-vtd 8 0.16855 4121.55 1 6 CACCTG TCCGGCGCCCCCTGGTGGCC + +4 transfac_pro__M06872 14 0.16855 4121.55 1 6 CACCTG GAGTACTCAAGGGGGACCTT + +4 cisbp__M4594-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.16855 4121.55 1 6 CACCTG CTCCGGCGCCCCCTGGTGGC - +4 dbcorrdb__CTCF__ENCSR000ANE_1__m1-CTCF-SMC3-usp-vtd 6 0.16855 4121.55 1 6 CACCTG TAGCGCCCCCTGGTGGCCAA - +4 dbcorrdb__RELA__ENCSR000DYM_1__m1-Dif-dl-Rel-shn 13 0.16855 4121.55 1 6 CACCTG CGCCCTGGGAAATCCCCTAC - +4 homer__ACTYKNATTCGTGNTACTTC_Mouse_Recombination_Hotspot 4 0.16855 4121.55 1 6 CACCTG GAAGTAGCACGAATTAGAGT - +4 swissregulon__hs__PPARG.p2-ERR-eg-kni-knrl 13 0.16855 4121.55 1 6 CACCTG AGTGGGTCACCGTGACCCAG - +4 transfac_pro__M09435 8 0.16855 4121.55 1 6 CACCTG GTGGGTCCCACATCCTCTGT - +4 cisbp__M3944-bigmax-cnc-Mitf-Mondo-SREBP-tgo-Usf 3 0.168951 4131.35 1 6 CACCTG GATCACGTGAC + +4 hocomoco__TFE2_HUMAN.H11MO.0.A 2 0.168951 4131.35 1 6 CACCTG CACAGCTGCAG + +4 predrem__nrMotif1895 4 0.168951 4131.35 1 6 CACCTG CCCGCGCCTCC + +4 taipale_cyt_meth__ZBTB7A_NCGACCMCCGN_eDBD 5 0.168951 4131.35 1 6 CACCTG GCGACCACCGA + +4 transfac_pro__M03833-bap 1 0.168951 4131.35 1 6 CACCTG CCACTTAGTCA + +4 transfac_pro__M04631-peb 1 0.168951 4131.35 1 6 CACCTG GCACCCCGACC + +4 transfac_public__M00220-bigmax-cnc-Mitf-Mondo-SREBP-tgo-Usf 3 0.168951 4131.35 1 6 CACCTG GATCACGTGAC + +4 cisbp__M5437-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK 5 0.168951 4131.35 1 6 CACCTG ATATTTACATA - +4 hocomoco__IRX3_HUMAN.H11MO.0.D-ara-caup-mirr 2 0.168951 4131.35 1 6 CACCTG ATTACATGAAA - +4 taipale__FOXB1_DBD_WRWGTMAAYAN_repr-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK 5 0.168951 4131.35 1 6 CACCTG ATATTTACATA - +4 flyfactorsurvey__shn-F1-2_SANGER_5_FBgn0003396-Rel-shn 6 0.168951 4131.35 1 5 CACCTG GGGAATCCCCT + +4 tfdimers__MD00085 7 0.169095 4134.89 1 6 CACCTG TTAAACCCAACTGGCTTAGCCAGTTGGGTTTCA + +4 taipale_cyt_meth__IRX5_NCRTGTNNNACAYGN_eDBD_repr-ara-caup-mirr 8 0.169725 4150.3 1 6 CACCTG ACATGTATTACATGT + +4 taipale_cyt_meth__ZFP1_NTTTTATACCCAGCN_eDBD_meth_repr-CG4730-CG7101 6 0.169725 4150.3 1 6 CACCTG CTTTTATACCCAGCT + +4 taipale_cyt_meth__ZIC1_NRCCMCCYGCTGTGN_FL_meth-HDAC1-opa 3 0.169725 4150.3 1 6 CACCTG GACCCCCTGCTGTGC + +4 cisbp__M4524-TfAP-2 2 0.169725 4150.3 1 6 CACCTG ACTGCCTCAGGGCAC - +4 cisbp__M6323-CG42741-dar1 5 0.169725 4150.3 1 6 CACCTG AGCCACACCCAGGCA - +4 transfac_pro__M09307 4 0.169725 4150.3 1 6 CACCTG GTTTCACCAACCACA - +4 cisbp__M4438-EcR-eg-ERR-kni-knrl 10 0.169725 4150.3 1 5 CACCTG AGGTCACGGTGACCT + +4 transfac_pro__M07817-nub-pdm2-vvl -1 0.169725 4150.3 1 5 CACCTG AGCTAATTTGCATAT - +4 cisbp__M5917-TfAP-2 0 0.169739 4150.62 1 6 CACCTG TGCCCCAGGGCA + +4 cisbp__M5920-TfAP-2 0 0.169739 4150.62 1 6 CACCTG TGCCCCAGGGCA + +4 hocomoco__GRHL2_MOUSE.H11MO.0.A-grh 0 0.169739 4150.62 1 6 CACCTG AACCTGTTTTTC + +4 predrem__nrMotif2640 3 0.169739 4150.62 1 6 CACCTG CCCCACCACGCC + +4 taipale__TFAP2B_DBD_NGCCNNNNGGCN-TfAP-2 0 0.169739 4150.62 1 6 CACCTG TGCCCCAGGGCA + +4 taipale__TFAP2C_DBD_NGCCNNNNGGCN-TfAP-2 0 0.169739 4150.62 1 6 CACCTG TGCCCCAGGGCA + +4 taipale_cyt_meth__TGIF1_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.169739 4150.62 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M00771-aop-Eip74EF-Ets21C-Ets96B-Ets97D 6 0.169739 4150.62 1 6 CACCTG AACCACTTCCTG + +4 transfac_pro__M05701 5 0.169739 4150.62 1 6 CACCTG TGTGGGACCCGC + +4 transfac_pro__M06133 2 0.169739 4150.62 1 6 CACCTG AGCTCCTGGAGC + +4 transfac_pro__M07469-HLH3B-HLH4C 5 0.169739 4150.62 1 6 CACCTG GACACCACCTGC + +4 transfac_pro__M09581 0 0.169739 4150.62 1 6 CACCTG GACCGGTCGACC + +4 cisbp__M5377-aop-Eip74EF-Ets21C 0 0.169739 4150.62 1 6 CACCTG CACTTCCGGGTT - +4 hocomoco__RORG_HUMAN.H11MO.0.C-Eip75B-Hr3 5 0.169739 4150.62 1 6 CACCTG TGACCCACTTTC - +4 transfac_pro__M05896 6 0.169739 4150.62 1 6 CACCTG GATTTTAACCCA - +4 transfac_pro__M06131 6 0.169739 4150.62 1 6 CACCTG GCCTTTTACCCT - +4 transfac_pro__M06517 6 0.169739 4150.62 1 6 CACCTG GCGTCCTACCCT - +4 transfac_pro__M08903-sd 5 0.169739 4150.62 1 6 CACCTG AAAAATACCTCA - +4 transfac_pro__M05788 7 0.169739 4150.62 1 5 CACCTG TTTTTTTAACCG - +4 transfac_pro__M06199 7 0.169739 4150.62 1 5 CACCTG GATTATTGACCG - +4 transfac_pro__M06320 7 0.169739 4150.62 1 5 CACCTG TCTTCATAACCG - +4 transfac_pro__M06402-CG3281 7 0.169739 4150.62 1 5 CACCTG TCTTTTTGACCT - +4 flyfactorsurvey__CG4854_SOLEXA_5_FBgn0038766-CG4854 11 0.170446 4167.9 1 6 CACCTG GTGTTGCCAACCACCTTCACCCCAT - +4 cisbp__M3721-sv 7 0.170754 4175.45 1 6 CACCTG AAACAGATACCTGAAGCGTGACCATACA + +4 jaspar__MA0540.1 2 0.173133 4233.63 1 6 CACCTG TGTCCCTGCGCGATAA + +4 cisbp__M2333 2 0.173133 4233.63 1 6 CACCTG TCTCCCTGCGCGATAA - +4 neph__UW.Motif.0471 11 0.173133 4233.63 1 5 CACCTG GAAACAGATCATTTCT - +4 yetfasco__TBP-TFIIA_1328-Tbp-TfIIA-S-TfIIA-S-2-Trf-Trf2 -2 0.173133 4233.63 1 4 CACCTG CCTGAAGGGGCGCCCT - +4 cisbp__M1705 0 0.173855 4251.27 1 6 CACCTG CTCCGAGG + +4 cisbp__M4693-Six4 1 0.173855 4251.27 1 6 CACCTG ACAACTCC + +4 flyfactorsurvey__Mio_bigmax_SANGER_5_FBgn0032940-Mitf-Mondo-bigmax 2 0.173855 4251.27 1 6 CACCTG ATCACGTG + +4 predrem__nrMotif419 1 0.173855 4251.27 1 6 CACCTG GAACCCTC + +4 taipale_cyt_meth__LHX4_NTCGTTAN_eDBD_meth_repr-Lim3 0 0.173855 4251.27 1 6 CACCTG CTCGTTAA + +4 transfac_public__M00217-Usf 1 0.173855 4251.27 1 6 CACCTG CCACGTGC + +4 cisbp__M0782-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 2 0.173855 4251.27 1 6 CACCTG CTTATCTG - +4 cisbp__M0798-GATAd-GATAe-grn-pnr-srp 2 0.173855 4251.27 1 6 CACCTG CTTATCGG - +4 cisbp__M0824 2 0.173855 4251.27 1 6 CACCTG ATGACATG - +4 fantom__motif143_ATGATGTG 0 0.173855 4251.27 1 6 CACCTG CACATCAT - +4 homer__NCCACGTG_c-Myc-Max-Myc-Sap30-Usf-tgo 0 0.173855 4251.27 1 6 CACCTG CACGTGGT - +4 swissregulon__hs__FEV.p2-Ets65A-Ets97D-pnt 2 0.173855 4251.27 1 6 CACCTG ATTTCCTG - +4 swissregulon__hs__bHLH_family.p2-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30-cyc-emc 0 0.173855 4251.27 1 6 CACCTG CACGTGGT - +4 transfac_pro__M05150 3 0.173855 4251.27 1 5 CACCTG ATAAACAT + +4 predrem__nrMotif149 -1 0.173855 4251.27 1 5 CACCTG ATCTGCAT - +4 predrem__nrMotif778 3 0.173855 4251.27 1 5 CACCTG TGTCACAT - +4 predrem__nrMotif1189 4 0.173855 4251.27 1 4 CACCTG GGAGCACC + +4 cisbp__M0467 4 0.173855 4251.27 1 4 CACCTG TCGCCACC - +4 cisbp__M0156-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-SREBP-Usf-bigmax-cnc-cwo-cyc-emc-h-mio-tgo 2 0.174182 4259.28 1 6 CACCTG GTCACGTGAT + +4 cisbp__M0271-CrebB 3 0.174182 4259.28 1 6 CACCTG GCTGACGTAA + +4 cisbp__M1060-bap-scro-vnd 3 0.174182 4259.28 1 6 CACCTG AAGCACTTAA + +4 cisbp__M1931 1 0.174182 4259.28 1 6 CACCTG AACCTTATAT + +4 cisbp__M5511-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 2 0.174182 4259.28 1 6 CACCTG GACACGTGCC + +4 cisbp__M5636-ac-amos-ase-crp-dimm-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.174182 4259.28 1 6 CACCTG AACAGCTGTT + +4 hocomoco__FOXA1_MOUSE.H11MO.0.A-FoxK-FoxL1-FoxP-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.174182 4259.28 1 6 CACCTG TGTTTACATA + +4 homer__ANACAGCTGC_E2A 3 0.174182 4259.28 1 6 CACCTG ACACAGCTGC + +4 predrem__nrMotif1847 3 0.174182 4259.28 1 6 CACCTG ACACACCAAA + +4 predrem__nrMotif2247 3 0.174182 4259.28 1 6 CACCTG GGGCACCCAG + +4 transfac_pro__M00946-SREBP-Usf 2 0.174182 4259.28 1 6 CACCTG GTGACGTGAC + +4 transfac_pro__M01128 2 0.174182 4259.28 1 6 CACCTG GTACCCTTTT + +4 transfac_pro__M01249-sima 1 0.174182 4259.28 1 6 CACCTG GTACGTGCTT + +4 transfac_pro__M07498 4 0.174182 4259.28 1 6 CACCTG AAAATATCTT + +4 transfac_pro__M07509 3 0.174182 4259.28 1 6 CACCTG GAGAATCTGT + +4 transfac_pro__M07578 4 0.174182 4259.28 1 6 CACCTG GCTACATCAA + +4 transfac_pro__M07643-bigmax-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.174182 4259.28 1 6 CACCTG ATCACGTGAT + +4 transfac_pro__M07667-Atf3-Atf6-CG44247-CG7786-cnc-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 2 0.174182 4259.28 1 6 CACCTG GTGACGTCAT + +4 transfac_pro__M07693-Atf6-CrebA-Xbp1 2 0.174182 4259.28 1 6 CACCTG GCCACGTCAC + +4 transfac_pro__M08881-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.174182 4259.28 1 6 CACCTG CACTTCCTGT + +4 cisbp__M0163-Max-Mitf-bigmax-cnc-cyc-tgo 3 0.174182 4259.28 1 6 CACCTG TGTCACGTGC - +4 cisbp__M0447 3 0.174182 4259.28 1 6 CACCTG ATTGACCACT - +4 cisbp__M1420 4 0.174182 4259.28 1 6 CACCTG ATGCAACCCT - +4 cisbp__M1686 4 0.174182 4259.28 1 6 CACCTG CGTTGACCTT - +4 cisbp__M1692 4 0.174182 4259.28 1 6 CACCTG CGTTGACCTT - +4 cisbp__M5070-schlank 1 0.174182 4259.28 1 6 CACCTG CTACCAAATT - +4 cisbp__M5475-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.174182 4259.28 1 6 CACCTG TACTTCCGGT - +4 hdpi__STAU2-stau 3 0.174182 4259.28 1 6 CACCTG AGTTAACTTT - +4 jaspar__MA0028.2-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Taf1-aop-bs-pnt 0 0.174182 4259.28 1 6 CACCTG CACTTCCGGT - +4 taipale__HEY2_full_GNCACGTGYN-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 2 0.174182 4259.28 1 6 CACCTG GGCACGTGTC - +4 taipale_cyt_meth__HES6_GGCACGTGTN_FL-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 2 0.174182 4259.28 1 6 CACCTG AACACGTGCC - +4 transfac_pro__M04854-CTCF-SMC3-usp-vtd 3 0.174182 4259.28 1 6 CACCTG CGCCCCCTGG - +4 yetfasco__YKL222C_2192 3 0.174182 4259.28 1 6 CACCTG TATTTCCGTT - +4 predrem__nrMotif1549 -1 0.174182 4259.28 1 5 CACCTG ACCTTTTGAA + +4 cisbp__M1419-CG3328 5 0.174182 4259.28 1 5 CACCTG GGTGGTACGG - +4 hocomoco__AP2C_HUMAN.H11MO.0.A-GATAe-TfAP-2-grn-pnr 2 0.174304 4262.27 1 6 CACCTG ATGCCCTGAGGCCA + +4 jaspar__MA0463.1-Stat92E 1 0.174304 4262.27 1 6 CACCTG TTTCCTAGAAAGCA + +4 neph__UW.Motif.0211 0 0.174304 4262.27 1 6 CACCTG TGTCTGTGGCTTCA + +4 neph__UW.Motif.0396 2 0.174304 4262.27 1 6 CACCTG GAAACCAGATCTTC + +4 swissregulon__hs__HIF1A.p2-sima-tgo 3 0.174304 4262.27 1 6 CACCTG GCGGACGTGCGGCC + +4 cisbp__M2265-Stat92E 1 0.174304 4262.27 1 6 CACCTG TTTCCTAGAAAGCA - +4 neph__UW.Motif.0055 4 0.174304 4262.27 1 6 CACCTG TTTTTTCCAGCTGG - +4 neph__UW.Motif.0264 7 0.174304 4262.27 1 6 CACCTG TGCCAGCTTCCTTC - +4 stark__TCCTNNNNNNNGGA -1 0.174304 4262.27 1 5 CACCTG TCCTAAAAAAAGGA + +4 predrem__nrMotif1633 0 0.17466 4270.96 1 6 CACCTG GAACTTG + +4 cisbp__M2020-bap 0 0.17466 4270.96 1 6 CACCTG CACTTAA - +4 flyfactorsurvey__pnr_SANGER_5_FBgn0003117-pnr-srp 1 0.17466 4270.96 1 6 CACCTG TTATCTG - +4 cisbp__M1982-CG11617 2 0.17466 4270.96 1 5 CACCTG TTAACAT + +4 jaspar__MA0349.1 2 0.17466 4270.96 1 5 CACCTG CGAACCG + +4 predrem__nrMotif48 2 0.17466 4270.96 1 5 CACCTG AAAAACT + +4 hdpi__CHES1-CHES-1-like -1 0.17466 4270.96 1 5 CACCTG CCCTGGA - +4 predrem__nrMotif1856 -1 0.17466 4270.96 1 5 CACCTG ACCAAGC - +4 transfac_pro__M04595-nom-salm-salr 2 0.17466 4270.96 1 5 CACCTG CCCACCC - +4 predrem__nrMotif25 -2 0.17466 4270.96 1 4 CACCTG CCTCTGC + +4 predrem__nrMotif2360 -2 0.17466 4270.96 1 4 CACCTG CCTCTAC - +4 transfac_pro__M01410-ara-caup-mirr 4 0.175598 4293.89 1 6 CACCTG AATATACATGTAAAACA + +4 transfac_pro__M02894-CG9727 9 0.175598 4293.89 1 6 CACCTG CTACTTGGATACGGAAT + +4 transfac_pro__M05327-klu 11 0.175598 4293.89 1 6 CACCTG TGCGGGGGGGTCACCTT + +4 bergman__dsx-dsx 4 0.175598 4293.89 1 6 CACCTG AAGATACATTGTGTTAC - +4 cisbp__M4535-Chd1-CTCF-Hcf-SMC3-usp-vtd 7 0.175598 4293.89 1 6 CACCTG CCGGCGCCCCCTGGTGG - +4 transfac_pro__M01832 6 0.175598 4293.89 1 6 CACCTG GGAAATTACATCATTGG - +4 transfac_pro__M07973-CG14860 1 0.175598 4293.89 1 6 CACCTG TTACGTGTTCCACGTAA - +4 cisbp__M0183-Clk-Hey-tai 2 0.176124 4306.76 1 6 CACCTG GACACGTGC + +4 cisbp__M0204-Clk-cyc-tai-tgo-Usf 2 0.176124 4306.76 1 6 CACCTG GTCACGTGA + +4 cisbp__M0380 3 0.176124 4306.76 1 6 CACCTG AATAAGCCT + +4 cisbp__M5233-sima-tgo 1 0.176124 4306.76 1 6 CACCTG GTACGTGAC + +4 jaspar__MA0306.1-Kdm4A-Kdm4B 1 0.176124 4306.76 1 6 CACCTG ACCCCTAAA + +4 predrem__nrMotif2076 1 0.176124 4306.76 1 6 CACCTG ACAACTTGA + +4 predrem__nrMotif2330 3 0.176124 4306.76 1 6 CACCTG TTAACCCTG + +4 predrem__nrMotif2475 3 0.176124 4306.76 1 6 CACCTG AGAGACTTG + +4 transfac_pro__M02241 3 0.176124 4306.76 1 6 CACCTG TACTTCCTT + +4 transfac_public__M00111-usp 3 0.176124 4306.76 1 6 CACCTG CGTGACCCC + +4 cisbp__M0206 2 0.176124 4306.76 1 6 CACCTG GGCACGTGT - +4 cisbp__M0234-Clk-E2f1-Max-Myc-gce 1 0.176124 4306.76 1 6 CACCTG CCACGTGGC - +4 cisbp__M4751-ato-CG8319-da-Oli 1 0.176124 4306.76 1 6 CACCTG ACATCTGTC - +4 flyfactorsurvey__ttk_NAR_FBgn0003870-ttk 3 0.176124 4306.76 1 6 CACCTG ATTATCCTT - +4 jaspar__MA0989.1 0 0.176124 4306.76 1 6 CACCTG CACTTTTTG - +4 predrem__nrMotif1320 2 0.176124 4306.76 1 6 CACCTG AGGATCTGA - +4 swissregulon__sacCer__RTG3-Clk-Mitf-bigmax-cyc-tgo 1 0.176124 4306.76 1 6 CACCTG GCACGTGAC - +4 transfac_pro__M01626-Kdm4A-Kdm4B 1 0.176124 4306.76 1 6 CACCTG ACCCCTAAA - +4 transfac_pro__M01885-CG10348-CG13296-ham 3 0.176124 4306.76 1 6 CACCTG CAGCCCCTT - +4 yetfasco__YDR096W_562-Kdm4A-Kdm4B 1 0.176124 4306.76 1 6 CACCTG ACCCCTAAA - +4 cisbp__M6145-TfAP-2 -1 0.176124 4306.76 1 5 CACCTG GCCTGGGGC + +4 predrem__nrMotif364 5 0.176124 4306.76 1 4 CACCTG AGCACCACC - +4 tfdimers__MD00537-nej-Pur-alpha 4 0.177035 4329.03 1 6 CACCTG CCCCCCCCTGCCCCCACTCCCTCCCCCCC - +4 taipale_tf_pairs__CUX1_TBX21_NTCACACMNNNATCRATN_CAP_repr-ct 4 0.177207 4333.24 1 6 CACCTG GTCACACATTAATCGATA + +4 taipale_tf_pairs__CLOCK_EVX1_TAATTANNNNNNCACGTG_CAP_repr-Clk-eve 0 0.177207 4333.24 1 6 CACCTG CACGTGTGTCAATAATTA - +4 transfac_pro__M05596 4 0.177207 4333.24 1 6 CACCTG AAAGTACCTTGGAAACGC - +4 cisbp__M3838-Eip75B-Hr3 2 0.177423 4338.53 1 6 CACCTG TTGACCTACTTAT + +4 neph__UW.Motif.0473 6 0.177423 4338.53 1 6 CACCTG TTCAAATTTCTGA - +4 transfac_pro__M08987 1 0.177423 4338.53 1 6 CACCTG AGACCTACTATGC - +4 transfac_public__M00157-Eip75B-Hr3 2 0.177423 4338.53 1 6 CACCTG TTGACCTACTTAT - +4 hocomoco__SMAD4_HUMAN.H11MO.0.B-Med-Smox 8 0.177423 4338.53 1 5 CACCTG CTGTCTGGCACCT + +4 neph__UW.Motif.0395 8 0.177423 4338.53 1 5 CACCTG CCAGAGAAATTCT - +4 tfdimers__MD00059-scro 11 0.177568 4342.08 1 6 CACCTG ATTTTTTAATCCTCTTGAGTGATTTT - +4 taipale_tf_pairs__GCM2_SOX15_ATRCGGGYNNNNNYWTTGTNN_CAP_repr-gcm-gcm2 12 0.177664 4344.42 1 6 CACCTG AAACAATGGACATACCCGCAT - +4 taipale_tf_pairs__TFAP4_DLX3_NCAGSTGNNNNNNNGTAATKR_CAP_repr-crp 14 0.177664 4344.42 1 6 CACCTG CAATTACCTCCCCCCAGCTGA - +4 cisbp__M2318 2 0.177743 4346.36 1 6 CACCTG CACAGCTGCAG + +4 cisbp__M1867-brm-CoRest-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Sirt6-Snr1-srp-svp 4 0.177743 4346.36 1 6 CACCTG TTCTTATCTGT - +4 fantom__motif167_TTGGGTAGGAG 0 0.177743 4346.36 1 6 CACCTG CTCCTACCCAA - +4 hocomoco__XBP1_HUMAN.H11MO.0.D-Atf6-CrebA-Xbp1 2 0.177743 4346.36 1 6 CACCTG GCCACGTCAGC - +4 hocomoco__ZBT18_HUMAN.H11MO.0.C 3 0.177743 4346.36 1 6 CACCTG CCACATCTGGA - +4 neph__UW.Motif.0061 5 0.177743 4346.36 1 6 CACCTG GAAAACATATG - +4 predrem__nrMotif2422 1 0.177743 4346.36 1 6 CACCTG TTACTTTTGTT - +4 transfac_pro__M09134 4 0.177743 4346.36 1 6 CACCTG AAAGTAGCTTT - +4 cisbp__M5189-Rel-shn 6 0.177743 4346.36 1 5 CACCTG GGGAATCCCCT - +4 taipale_tf_pairs__TEAD4_CLOCK_NCACGTGNNNNNNCATWCC_CAP_repr-Clk-sd 1 0.17804 4353.62 1 6 CACCTG ACACGTGTTCCAACATTCC + +4 transfac_pro__M05934-CTCF 14 0.17804 4353.62 1 5 CACCTG GTGGAGCCGTCTCCCACCG - +4 dbcorrdb__CTCF__ENCSR000DYB_1__m1-CTCF-SMC3-vtd 0 0.17817 4356.8 1 6 CACCTG CCCCTGGTGGCCACAGGGGG + +4 dbcorrdb__HDAC2__ENCSR000BNR_1__m3-CoRest-HDAC1 7 0.17817 4356.8 1 6 CACCTG TGGAAAGCGCCCGCGGGGGT + +4 dbcorrdb__PPARGC1A__ENCSR000EEQ_1__m3-srl 5 0.17817 4356.8 1 6 CACCTG CTAGGCCACTCTGCATGTGG + +4 dbcorrdb__TBL1XR1__ENCSR000EGA_1__m3-ebi 4 0.17817 4356.8 1 6 CACCTG CAACAGTCTGCTGTTTCCTC + +4 dbcorrdb__TFAP2C__ENCSR000EVO_1__m1-GATAe-grn-pnr-TfAP-2 6 0.17817 4356.8 1 6 CACCTG CCACATTGCCTCAGGGCATG + +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m4-CG9650 14 0.17817 4356.8 1 6 CACCTG TTTGAAATGCTGAGTGCCCT - +4 dbcorrdb__CTCF__ENCSR000DQY_1__m1-Chd1-CTCF-SMC3-usp-vtd 7 0.17817 4356.8 1 6 CACCTG CTAGCGCCCCCTGGTGGCCA - +4 dbcorrdb__EP300__ENCSR000BHB_1__m4-nej 6 0.17817 4356.8 1 6 CACCTG CGTCACCACCCGCTTCGGTG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m1-RpII215 7 0.17817 4356.8 1 6 CACCTG CAACATATACCAGTTGCGCA - +4 dbcorrdb__RFX5__ENCSR000EGO_1__m1-Rfx 2 0.17817 4356.8 1 6 CACCTG TCTGCCTAGCAACAGGTGAC - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m2-CTCF-SMC3-usp-vtd 1 0.17817 4356.8 1 6 CACCTG TTACCGCCAGGGGGCGCGAG - +4 transfac_pro__M06471 15 0.17817 4356.8 1 5 CACCTG AGGGCCCCCATATTCCACCA - +4 cisbp__M6100-TfAP-2 0 0.178698 4369.69 1 6 CACCTG TGCCCGGGGGCA + +4 neph__UW.Motif.0340 5 0.178698 4369.69 1 6 CACCTG CATTTTTCCAAA + +4 stark__ACACNNNNRCAC 1 0.178698 4369.69 1 6 CACCTG ACACAAAAACAC + +4 stark__CACNNNNNNACA 0 0.178698 4369.69 1 6 CACCTG CACAAAAAAACA + +4 taipale_cyt_meth__CREM_NRTGACGTCAYN_eDBD-Atf3-Atf6-CG7786-cnc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.178698 4369.69 1 6 CACCTG CGTGACGTCACG + +4 taipale_cyt_meth__DMRT1_NNTYGNTACATN_FL-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.178698 4369.69 1 6 CACCTG AATTGATACATT + +4 transfac_pro__M00634-gcm-gcm2 2 0.178698 4369.69 1 6 CACCTG CACGCCCGCATT + +4 transfac_pro__M07681-Atf6-Clk-CrebA-Max-Mnt 3 0.178698 4369.69 1 6 CACCTG TGCCACGTGGCA + +4 cisbp__M6037-ara-caup-mirr 1 0.178698 4369.69 1 6 CACCTG CTACATGACAAA - +4 taipale__Tcfap2a_DBD_NGCCNNNNGGCN_repr-TfAP-2 0 0.178698 4369.69 1 6 CACCTG TGCCCGGGGGCA - +4 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_FL_meth-achi-amos-Fer3-HLH54F-nau-vis 3 0.178698 4369.69 1 6 CACCTG CAACAGCTGTCG - +4 tiffin__TIFDMEM0000074 0 0.178698 4369.69 1 6 CACCTG TAACTATCGATT - +4 transfac_pro__M05350 1 0.178698 4369.69 1 6 CACCTG TTTCCTTTAACA - +4 transfac_pro__M06082 5 0.178698 4369.69 1 6 CACCTG TCCGCTGCCTGA - +4 transfac_pro__M06107 1 0.178698 4369.69 1 6 CACCTG GCATCTTTCCCT - +4 transfac_pro__M06378 6 0.178698 4369.69 1 6 CACCTG GCTTATGACCAG - +4 transfac_pro__M06524 5 0.178698 4369.69 1 6 CACCTG GATGGTACCAAG - +4 transfac_pro__M06549 5 0.178698 4369.69 1 6 CACCTG CACCCCACCTCT - +4 transfac_pro__M06093 7 0.178698 4369.69 1 5 CACCTG AATGTTGGACCA - +4 transfac_pro__M06419-CG3281 7 0.178698 4369.69 1 5 CACCTG TCGCCAATACCT - +4 transfac_pro__M06487 -1 0.178698 4369.69 1 5 CACCTG ATCTCCTTACAA - +4 transfac_pro__M06512 7 0.178698 4369.69 1 5 CACCTG TTTTTACAACCA - +4 transfac_pro__M06581 7 0.178698 4369.69 1 5 CACCTG GCGGTTGCTCCT - +4 tfdimers__MD00317 7 0.178727 4370.41 1 6 CACCTG TTTATCTCAACTGGCAAGACTTGTCTTACTT + +4 neph__UW.Motif.0005-Fer1-Su(H) 0 0.179019 4377.55 1 6 CACCTG CAGCTGGTTTTTCTC + +4 neph__UW.Motif.0671 8 0.179019 4377.55 1 6 CACCTG GAAAAAAATTCCATC + +4 cisbp__M4519-Chd1-CTCF-SMC3-Stat92E-usp-vtd 3 0.179019 4377.55 1 6 CACCTG CGCCCCCTGGTGGCC - +4 hocomoco__COT2_MOUSE.H11MO.1.B-EcR-HDAC1-Hnf4-Hr51-Hr78-eg-kni-knrl-svp-tll-usp 2 0.179019 4377.55 1 6 CACCTG TTGACCTTTGACCTT - +4 neph__UW.Motif.0249 4 0.179019 4377.55 1 6 CACCTG AGGCTGCCAGGTGCT - +4 stark__BYRHBACAAWGTDDB-dsx 2 0.179019 4377.55 1 6 CACCTG GTTACATTGTGTCAG - +4 stark__VRGKTYAWTGAMMYY-EcR-svp-usp 9 0.179019 4377.55 1 6 CACCTG AAGGTCAATAAACCT - +4 taipale_tf_pairs__TFAP4_FLI1_RSCGGAWRCASSTGN_CAP-crp 1 0.179019 4377.55 1 6 CACCTG CCAGCTGCTTCCGGT - +4 transfac_pro__M09196 6 0.179019 4377.55 1 6 CACCTG TCAATGAATCTAGAC - +4 neph__UW.Motif.0144 10 0.179019 4377.55 1 5 CACCTG AGACCTGGCTTTTCT - +4 transfac_public__M00144-sv 7 0.180974 4425.36 1 6 CACCTG GACGTGATTTCTGAAGCGTGACGATAGC + +4 cisbp__M6142-fkh-Hsf 3 0.182644 4466.18 1 6 CACCTG AAGAACATCCTGTTCC + +4 hocomoco__PRGR_HUMAN.H11MO.0.A-Hsf-fkh 2 0.182644 4466.18 1 6 CACCTG AGAACATTCTGTTCTT + +4 neph__UW.Motif.0624 0 0.182644 4466.18 1 6 CACCTG CATTTTTTTTTTTTCA + +4 neph__UW.Motif.0658 5 0.182644 4466.18 1 6 CACCTG GAGAAGCGCTGGGGCC + +4 transfac_pro__M01350-scro-tin-vnd 5 0.182644 4466.18 1 6 CACCTG TAAGCCACTTGAAATT + +4 transfac_pro__M01414-scro 5 0.182644 4466.18 1 6 CACCTG TAAGCCACTTGAATTT + +4 transfac_pro__M02883-Myb 4 0.182644 4466.18 1 6 CACCTG CGACCAACTGCCATGC + +4 cisbp__M0166-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 1 0.182677 4467 1 6 CACCTG GCACGTGC + +4 cisbp__M0267 1 0.182677 4467 1 6 CACCTG ACACGTGT + +4 cisbp__M5107-bigmax-Mitf-Mondo 2 0.182677 4467 1 6 CACCTG ATCACGTG + +4 jaspar__MA0930.1 1 0.182677 4467 1 6 CACCTG ACACGTGT + +4 jaspar__MA0963.1-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 1 0.182677 4467 1 6 CACCTG GCACGTGC + +4 predrem__nrMotif436 1 0.182677 4467 1 6 CACCTG GGTCCTGC + +4 predrem__nrMotif734 2 0.182677 4467 1 6 CACCTG CAAACCCT + +4 hdpi__ZNF238 1 0.182677 4467 1 6 CACCTG ACATCTGG - +4 predrem__nrMotif1724 -1 0.182677 4467 1 5 CACCTG AACTGACT + +4 predrem__nrMotif239 -1 0.182677 4467 1 5 CACCTG TCCTGACT + +4 predrem__nrMotif64 3 0.182677 4467 1 5 CACCTG CTGCATCT + +4 cisbp__M1515 3 0.182677 4467 1 5 CACCTG GTACACCC - +4 predrem__nrMotif104 -1 0.182677 4467 1 5 CACCTG AACTGGGG - +4 elemento__CCTTGTAG -2 0.182677 4467 1 4 CACCTG CCTTGTAG + +4 elemento__CCTTTAAG -2 0.182677 4467 1 4 CACCTG CCTTTAAG + +4 elemento__CAAGAAGG -2 0.182677 4467 1 4 CACCTG CCTTCTTG - +4 elemento__CATCAAGG -2 0.182677 4467 1 4 CACCTG CCTTGATG - +4 cisbp__M0251-Clk-Max-Mitf-Mondo-SREBP-Sirt6-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.183086 4476.99 1 6 CACCTG GTCACGTGAC + +4 cisbp__M0930-bap-scro-tin-vnd 2 0.183086 4476.99 1 6 CACCTG GCCACTTAAG + +4 cisbp__M1052-bap-scro-vnd 3 0.183086 4476.99 1 6 CACCTG AACCACTTAA + +4 cisbp__M1408 1 0.183086 4476.99 1 6 CACCTG ACACGCAACC + +4 cisbp__M1412 1 0.183086 4476.99 1 6 CACCTG ACACGCAACC + +4 cisbp__M1414 3 0.183086 4476.99 1 6 CACCTG TTACACGCAA + +4 cisbp__M4553-bigmax-cyc-Mitf-Sirt6-tgo 3 0.183086 4476.99 1 6 CACCTG GGTCACGTGC + +4 flyfactorsurvey__CG5180_SANGER_5_FBgn0043457-CG5180 4 0.183086 4476.99 1 6 CACCTG ATCGAACATC + +4 flyfactorsurvey__Lag1_SOLEXA_FBgn0040918-schlank 1 0.183086 4476.99 1 6 CACCTG CTACCAAATT + +4 homer__GCCATCTGTT_NeuroD1-HLH54F-amos-tap 2 0.183086 4476.99 1 6 CACCTG GCCATCTGTT + +4 predrem__nrMotif2127 1 0.183086 4476.99 1 6 CACCTG CCTCCTCCGG + +4 taipale_cyt_meth__SOHLH2_NGCACGTGCN_eDBD 2 0.183086 4476.99 1 6 CACCTG CGCACGTGCA + +4 cisbp__M0404 2 0.183086 4476.99 1 6 CACCTG TGCCCCCCTT - +4 cisbp__M0525 2 0.183086 4476.99 1 6 CACCTG GGTGCCGTAC - +4 cisbp__M0826 3 0.183086 4476.99 1 6 CACCTG TTTGACATGT - +4 cisbp__M1320 4 0.183086 4476.99 1 6 CACCTG AGGGAATCTT - +4 cisbp__M1323 4 0.183086 4476.99 1 6 CACCTG AGGGAATCTT - +4 cisbp__M3319-GATAe-grn-pnr 3 0.183086 4476.99 1 6 CACCTG CGCTATCCCC - +4 cisbp__M4660-brm-CoRest-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 4 0.183086 4476.99 1 6 CACCTG TTCTTATCTG - +4 cisbp__M4793-cato-da 2 0.183086 4476.99 1 6 CACCTG CACAGCTGAC - +4 cisbp__M4869-CG5180 4 0.183086 4476.99 1 6 CACCTG ATCGAACATC - +4 cisbp__M5383-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.183086 4476.99 1 6 CACCTG CACTTCCGGT - +4 cisbp__M5931-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.183086 4476.99 1 6 CACCTG ATCACGTGAC - +4 flyfactorsurvey__Fer2_da_SANGER_5_FBgn0000413-Fer2-da 3 0.183086 4476.99 1 6 CACCTG CGTCAGCTGG - +4 homer__GCACGTACCC_HIF2a-sima 3 0.183086 4476.99 1 6 CACCTG GGGTACGTGC - +4 jaspar__MA0964.1-Mitf-bigmax-cnc-cyc-tgo 3 0.183086 4476.99 1 6 CACCTG GGTCACGTGC - +4 jaspar__MA1079.1 4 0.183086 4476.99 1 6 CACCTG CGTTGACCTT - +4 taipale_cyt_meth__ASCL1_NRCAGCTGYN_eDBD_meth-ac-ase-dimm-l(1)sc-nau-sc 2 0.183086 4476.99 1 6 CACCTG AGCAGCTGCT - +4 taipale_cyt_meth__MYCN_NKCACGTGGN_eDBD-Clk-Max-Mnt-Myc 2 0.183086 4476.99 1 6 CACCTG ACCACGTGCC - +4 transfac_pro__M04850-CTCF-lmd-SMC3-usp-vtd 3 0.183086 4476.99 1 6 CACCTG TGCCCCCTGG - +4 transfac_pro__M09454 4 0.183086 4476.99 1 6 CACCTG TTTTTACCGT - +4 transfac_public__M00076-GATAe-grn-pnr 3 0.183086 4476.99 1 6 CACCTG CGCTATCCGC - +4 transfac_public__M00347-GATAe-grn-pnr-srp 3 0.183086 4476.99 1 6 CACCTG TCTTATCTAT - +4 predrem__nrMotif1629 -1 0.183086 4476.99 1 5 CACCTG TCCTCTCACC + +4 predrem__nrMotif89 5 0.183086 4476.99 1 5 CACCTG TCTTTCACTT + +4 taipale__POU6F2_DBD_NSCTMATTAN_repr-pdm3 -1 0.183086 4476.99 1 5 CACCTG AGCTCATTAT + +4 transfac_pro__M01234 -1 0.183086 4476.99 1 5 CACCTG ACCTAATGAG + +4 transfac_pro__M07551 5 0.183086 4476.99 1 5 CACCTG CCGTTGACCG + +4 cisbp__M4691-GATAe-grn-pnr 5 0.183086 4476.99 1 5 CACCTG GATAATATCT - +4 cisbp__M5746-pdm3 -1 0.183086 4476.99 1 5 CACCTG AGCTCATTAT - +4 cisbp__M6532-EcR 1 0.18354 4488.11 1 6 CACCTG TGACCTC + +4 predrem__nrMotif1444 0 0.18354 4488.11 1 6 CACCTG AGCCTTG + +4 transfac_pro__M01722-Hr3 1 0.18354 4488.11 1 6 CACCTG TGACCCA + +4 cisbp__M5156-pnr-srp 1 0.18354 4488.11 1 6 CACCTG TTATCTG - +4 predrem__nrMotif1195 0 0.18354 4488.11 1 6 CACCTG CATCTCA - +4 transfac_pro__M06202-CG9609 1 0.18354 4488.11 1 6 CACCTG CACCCTG - +4 elemento__ACATGAC -1 0.18354 4488.11 1 5 CACCTG ACATGAC + +4 elemento__ACATGCG -1 0.18354 4488.11 1 5 CACCTG ACATGCG + +4 elemento__ACATGCT -1 0.18354 4488.11 1 5 CACCTG ACATGCT + +4 elemento__ACATGGC -1 0.18354 4488.11 1 5 CACCTG ACATGGC + +4 elemento__ACATGTC -1 0.18354 4488.11 1 5 CACCTG ACATGTC + +4 elemento__ACGTGAC -1 0.18354 4488.11 1 5 CACCTG ACGTGAC + +4 elemento__ACGTGCA -1 0.18354 4488.11 1 5 CACCTG ACGTGCA + +4 elemento__ACGTGCC -1 0.18354 4488.11 1 5 CACCTG ACGTGCC + +4 elemento__ACGTGCG -1 0.18354 4488.11 1 5 CACCTG ACGTGCG + +4 elemento__ACGTGCT -1 0.18354 4488.11 1 5 CACCTG ACGTGCT + +4 elemento__ACGTGGC-CrebA -1 0.18354 4488.11 1 5 CACCTG ACGTGGC + +4 elemento__ACGTGGG -1 0.18354 4488.11 1 5 CACCTG ACGTGGG + +4 elemento__ACTTGAC -1 0.18354 4488.11 1 5 CACCTG ACTTGAC + +4 elemento__ACTTGTC -1 0.18354 4488.11 1 5 CACCTG ACTTGTC + +4 elemento__CCCACCC 2 0.18354 4488.11 1 5 CACCTG CCCACCC + +4 elemento__CGCACCA 2 0.18354 4488.11 1 5 CACCTG CGCACCA + +4 predrem__nrMotif749 2 0.18354 4488.11 1 5 CACCTG TTTAGCT + +4 transfac_pro__M01681 2 0.18354 4488.11 1 5 CACCTG CGAACCG + +4 cisbp__M2154 2 0.18354 4488.11 1 5 CACCTG CGAACCG - +4 elemento__TGGTGCC 2 0.18354 4488.11 1 5 CACCTG GGCACCA - +4 predrem__nrMotif115 2 0.18354 4488.11 1 5 CACCTG TCTTCCT - +4 predrem__nrMotif1670 2 0.18354 4488.11 1 5 CACCTG TGGAGCT - +4 predrem__nrMotif2316 2 0.18354 4488.11 1 5 CACCTG GTTAACT - +4 predrem__nrMotif2573 2 0.18354 4488.11 1 5 CACCTG TGTCCCT - +4 predrem__nrMotif60 2 0.18354 4488.11 1 5 CACCTG TTTTCCT - +4 stark__CACATGT-twi -1 0.18354 4488.11 1 5 CACCTG ACATGTG - +4 hocomoco__PRD14_HUMAN.H11MO.0.A 8 0.18369 4491.77 1 6 CACCTG AGGTTAGAGACCTA + +4 neph__UW.Motif.0383 5 0.18369 4491.77 1 6 CACCTG AGTAATTCTTTCTG + +4 neph__UW.Motif.0619 7 0.18369 4491.77 1 6 CACCTG GAAACATTTCCAGC + +4 taipale_cyt_meth__SKOR2_NWNNKKTAATTAAN_eDBD_meth-fuss 0 0.18369 4491.77 1 6 CACCTG TAACTGTAATTAAG + +4 transfac_pro__M04896-TfAP-2 3 0.18369 4491.77 1 6 CACCTG CATGCCCTGGGGCC + +4 neph__UW.Motif.0106 1 0.18369 4491.77 1 6 CACCTG TTTCCAGCTGTCTG - +4 neph__UW.Motif.0193 3 0.18369 4491.77 1 6 CACCTG CAGAGCCTTTTTTT - +4 transfac_pro__M00305 8 0.18369 4491.77 1 6 CACCTG TCCGTTATCTCCGT - +4 transfac_pro__M00631-EcR-usp 7 0.18369 4491.77 1 6 CACCTG GGTTAATCACCTTG - +4 neph__UW.Motif.0657-Hrb87F-Hrb98DE-Rb97D 9 0.18369 4491.77 1 5 CACCTG AAGGAAAATTTTCT - +4 cisbp__M0188-SREBP 2 0.185051 4525.06 1 6 CACCTG ATCACGCGA + +4 cisbp__M0305-CrebA 2 0.185051 4525.06 1 6 CACCTG GCCACGTGT + +4 jaspar__MA0608.1-CrebA 2 0.185051 4525.06 1 6 CACCTG GCCACGTGT + +4 predrem__nrMotif1028 3 0.185051 4525.06 1 6 CACCTG AACCACCAG + +4 predrem__nrMotif2044 3 0.185051 4525.06 1 6 CACCTG TTCCACCAG + +4 predrem__nrMotif2657 0 0.185051 4525.06 1 6 CACCTG CACATCCTC + +4 predrem__nrMotif949 2 0.185051 4525.06 1 6 CACCTG TTTAACTTC + +4 stark__MACTTGTYR 0 0.185051 4525.06 1 6 CACCTG AACTTGTCA + +4 transfac_pro__M04713-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.185051 4525.06 1 6 CACCTG CCTTATCTG + +4 cisbp__M0781 2 0.185051 4525.06 1 6 CACCTG TAGATCTGA - +4 cisbp__M1355-Myb 0 0.185051 4525.06 1 6 CACCTG TAACGGTCG - +4 cisbp__M2263-ttk 3 0.185051 4525.06 1 6 CACCTG ATTATCCTT - +4 cisbp__M6256-brm-CoRest-GATAe-grn-HLH3B-nej-pnr-Snr1-srp-svp 2 0.185051 4525.06 1 6 CACCTG GTTATCTGT - +4 cisbp__M6548-opa 3 0.185051 4525.06 1 6 CACCTG GACCACCCC - +4 flyfactorsurvey__pad_SANGER_5_FBgn0038418-pad 2 0.185051 4525.06 1 6 CACCTG TACCCCTTC - +4 predrem__nrMotif854 3 0.185051 4525.06 1 6 CACCTG ACTCCCCTC - +4 taipale_cyt_meth__NR2E1_NAAAGTCAN_FL_repr-dsf-tll 2 0.185051 4525.06 1 6 CACCTG TTGACTTTT - +4 tfdimers__MD00268-eg-kni-knrl-Ptx1 7 0.185081 4525.8 1 6 CACCTG TTTCCCTGCCCTAATCCTTATAT - +4 cisbp__M3829-Rfx 4 0.185284 4530.76 1 6 CACCTG TAGTAGCCTGGCAACAA + +4 transfac_pro__M02749-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-FoxP-slp1 9 0.185284 4530.76 1 6 CACCTG GTCTTTGTTTACTTTTT - +4 transfac_pro__M04649-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 9 0.185284 4530.76 1 6 CACCTG GTCTTTGTTTACTTTTT - +4 transfac_pro__M01160 1 0.186541 4561.48 1 4 CACCTG CCACG + +4 neph__UW.Motif.0330 5 0.186803 4567.89 1 6 CACCTG TGAAAAACCAGAA + +4 neph__UW.Motif.0581 6 0.186803 4567.89 1 6 CACCTG CACAGAAGCCTGC + +4 transfac_pro__M09219 0 0.186803 4567.89 1 6 CACCTG AACCTTATCCATT + +4 hocomoco__RORA_HUMAN.H11MO.0.C-Eip75B-Hr3-eg-kni-knrl 4 0.186803 4567.89 1 6 CACCTG CCCTGACCTAGTT - +4 neph__UW.Motif.0124 2 0.186803 4567.89 1 6 CACCTG CAGGCCTTGCCTT - +4 taipale_cyt_meth__CREB3L1_TGCCACGTGTACR_FL-CrebA 4 0.186803 4567.89 1 6 CACCTG CGCACACGTGGCA - +4 transfac_pro__M04745-CTCF-SMC3-vtd 4 0.186803 4567.89 1 6 CACCTG CTGCCATCTAGTG - +4 transfac_pro__M07893-Blimp-1 2 0.186803 4567.89 1 6 CACCTG TTCACTTTCACTT - +4 yetfasco__YNL216W_254 7 0.186803 4567.89 1 6 CACCTG ACACCCATACACC - +4 transfac_pro__M00619 -2 0.186803 4567.89 1 4 CACCTG CCTGAGAATAATC + +4 hocomoco__TWST1_MOUSE.H11MO.1.B-da-twi 2 0.186872 4569.58 1 6 CACCTG AACATCTGGTT + +4 jaspar__MA0035.3-CoRest-GATAe-HLH3B-Jra-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.186872 4569.58 1 6 CACCTG TTCTTATCTGT + +4 predrem__nrMotif2007 1 0.186872 4569.58 1 6 CACCTG GGGCCTGGGCC + +4 swissregulon__sacCer__RAP1 0 0.186872 4569.58 1 6 CACCTG CACCCATACAT + +4 taipale_cyt_meth__ETV1_NACCGKAWGTN_FL-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.186872 4569.58 1 6 CACCTG GACCGGAAGTA + +4 transfac_pro__M01167-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.186872 4569.58 1 6 CACCTG CACCGGAAGTA + +4 hocomoco__WT1_HUMAN.H11MO.1.B-klu-sr 1 0.186872 4569.58 1 6 CACCTG CCTCCTCCCAC - +4 predrem__nrMotif1150 0 0.186872 4569.58 1 6 CACCTG GCCCTGCCTCC - +4 taipale_cyt_meth__FOXK1_NWYGTAAAYAN_eDBD-bin-bs-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.186872 4569.58 1 6 CACCTG TTGTTTACATT - +4 transfac_pro__M07809-B-H1-B-H2-NK7.1 0 0.186872 4569.58 1 6 CACCTG AACCGTTTAAC - +4 transfac_pro__M08935-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.186872 4569.58 1 6 CACCTG GATGACGTCAT - +4 cisbp__M6370-Rel 6 0.186872 4569.58 1 5 CACCTG GGAATCTCCCT + +4 cisbp__M4523-CTCF-SMC3-usp-vtd 5 0.187034 4573.55 1 6 CACCTG GGCGCCCCCTGGTGGCCA - +4 hocomoco__AIRE_HUMAN.H11MO.0.C 11 0.187034 4573.55 1 6 CACCTG TTAACCAATATAACCAAT - +4 jaspar__MA0350.1 5 0.187733 4590.63 1 6 CACCTG AGGCACAGCTCATCGCGTTTT + +4 transfac_pro__M01542 5 0.187733 4590.63 1 6 CACCTG AGGCACAGCTCATCGCGTTAT + +4 cisbp__M2155 5 0.187733 4590.63 1 6 CACCTG AGGCACAGCTCATCGCGTTAT - +4 hocomoco__RXRA_MOUSE.H11MO.0.A-CG17209-ERR-EcR-Hr4-ftz-f1-svp-usp 1 0.187733 4590.63 1 6 CACCTG TGACCTTGAACTCCTGACCCT - +4 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNCACGTGN_CAP_repr-Max-TfAP-2 9 0.187733 4590.63 1 6 CACCTG CCACGTGATCGCCTCAGGCCA - +4 yetfasco__YBL054W_852 5 0.187733 4590.63 1 6 CACCTG AGGCACAGCTCATCGCGTTAT - +4 taipale_cyt_meth__NR5A2_YGACCTTGNNNCAAGGTCR_eDBD_meth-ERR-ftz-f1 1 0.187977 4596.6 1 6 CACCTG TGACCTTGAGTCAAGGTCA + +4 cisbp__M5326-Atf6-Clk-CrebA-Max-Mnt 3 0.187981 4596.71 1 6 CACCTG TGCCACGTGGCA + +4 cisbp__M5915-TfAP-2 0 0.187981 4596.71 1 6 CACCTG TGCCCTGGGGCA + +4 taipale_cyt_meth__DMRTC2_WWTYGNTACATN_eDBD_meth_repr-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.187981 4596.71 1 6 CACCTG AATTGATACATT + +4 transfac_pro__M07699-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 1 0.187981 4596.71 1 6 CACCTG AAACCGGAAGTA + +4 transfac_public__M00064 3 0.187981 4596.71 1 6 CACCTG TAGCACGTGGGA + +4 hocomoco__INSM1_HUMAN.H11MO.0.C-nerfin-1-nerfin-2 3 0.187981 4596.71 1 6 CACCTG TGCCCCCTGACA - +4 homer__MYGGTCACACTG_Unknown1 6 0.187981 4596.71 1 6 CACCTG CAGTGTGACCGT - +4 taipale__CREB3L1_DBD_TGCCACGTGGCA_repr-Atf6-Clk-CrebA 3 0.187981 4596.71 1 6 CACCTG TGCCACGTGGCA - +4 taipale_cyt_meth__MYF6_CGTCANNTGTYN_eDBD-Fer1-nau 3 0.187981 4596.71 1 6 CACCTG CAACAGCTGACG - +4 transfac_pro__M05504 6 0.187981 4596.71 1 6 CACCTG GCCCCCCCCCTC - +4 transfac_pro__M05614 7 0.187981 4596.71 1 5 CACCTG GATTTCAGACCG - +4 transfac_pro__M05702 7 0.187981 4596.71 1 5 CACCTG TGATTTGTACCA - +4 transfac_pro__M06059 7 0.187981 4596.71 1 5 CACCTG GCATTTGGACCT - +4 transfac_pro__M06141 -1 0.187981 4596.71 1 5 CACCTG TCCTTTTCCCCT - +4 transfac_pro__M06152-crol 7 0.187981 4596.71 1 5 CACCTG TCCCTTTGACCG - +4 transfac_pro__M06338 7 0.187981 4596.71 1 5 CACCTG TCTGCCCAACCA - +4 transfac_pro__M06585 7 0.187981 4596.71 1 5 CACCTG AAGGCAGTACCA - +4 transfac_pro__M05742 -2 0.187981 4596.71 1 4 CACCTG CCTGCCCTTTCA - +4 dbcorrdb__HSF1__ENCSR000EET_1__m6-Hsf 5 0.188187 4601.73 1 6 CACCTG TCTTCTACCACTACGCGACG + +4 dbcorrdb__RELA__ENCSR000EBA_1__m1-Dif-dl-Rel-shn 8 0.188187 4601.73 1 6 CACCTG TTGGAAATCCCCTTCCCCCC + +4 dbcorrdb__RELA__ENCSR000EBI_1__m1-Dif-dl-Rel-shn 11 0.188187 4601.73 1 6 CACCTG CCCTTGGAAATCCCCTTCCC + +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m1-bon-egg 11 0.188187 4601.73 1 6 CACCTG CACTGGAGAGAAACCTTTTA + +4 dbcorrdb__NR3C1__ENCSR000BHE_1__m4 3 0.188187 4601.73 1 6 CACCTG TCCCACCCGCCTTTGTTCTC - +4 dbcorrdb__RFX5__ENCSR000EHY_1__m2 9 0.188187 4601.73 1 6 CACCTG CCCAATCAGCGCCTGCCCAG - +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m8-brm 9 0.188187 4601.73 1 6 CACCTG TGCATCCTTGATCTGACTGC - +4 dbcorrdb__SRF__ENCSR000BLK_1__m1-bs 2 0.188187 4601.73 1 6 CACCTG GTCGCCATATATGGGCGGGC - +4 dbcorrdb__SUPT20H__ENCSR000DNP_1__m1-Spt20 8 0.188187 4601.73 1 6 CACCTG AAAAATTTCATCTTTATTTC - +4 dbcorrdb__ZKSCAN1__ENCSR000ECJ_1__m1 4 0.188187 4601.73 1 6 CACCTG TGAGCACCTACTGTGTGCCA - +4 cisbp__M4525-TfAP-2 0 0.188685 4613.91 1 6 CACCTG AGCCTCAGGGCATGG + +4 cisbp__M6179-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 2 0.188685 4613.91 1 6 CACCTG TTGACCTTTGACCTT + +4 transfac_pro__M06158 9 0.188685 4613.91 1 6 CACCTG GTGGTCCTTTACCAC + +4 transfac_pro__M08998-fkh 2 0.188685 4613.91 1 6 CACCTG AGTACATTTTGTTCT + +4 cisbp__M3942 8 0.188685 4613.91 1 6 CACCTG GCCATACCCTCCTGC - +4 transfac_pro__M08911-CTCF-SMC3-usp-vtd 4 0.188685 4613.91 1 6 CACCTG GCGCCCCCTAGCGGC - +4 transfac_pro__M09259 0 0.188685 4613.91 1 6 CACCTG CTCCGGATTTTCCGG - +4 transfac_public__M00446 8 0.188685 4613.91 1 6 CACCTG GCCATACCCTCCTGC - +4 tfdimers__MD00588-Jra-kay 14 0.190933 4668.88 1 6 CACCTG CCCCTTGCTGACTCCTCCTCCCCCC - +4 cisbp__M1346 1 0.19185 4691.32 1 6 CACCTG TGCCCTAA + +4 cisbp__M1821 2 0.19185 4691.32 1 6 CACCTG ATTTCCGC + +4 cisbp__M4847-ab 0 0.19185 4691.32 1 6 CACCTG TACTTCCT + +4 homer__GCCACGTG_E-box-Atf6-Clk-CrebA-Myc 2 0.19185 4691.32 1 6 CACCTG GCCACGTG + +4 jaspar__MA0562.1-Max 1 0.19185 4691.32 1 6 CACCTG TCACGTGG + +4 jaspar__MA0569.1-Hey 1 0.19185 4691.32 1 6 CACCTG ACACGTGC + +4 jaspar__MA1073.1 1 0.19185 4691.32 1 6 CACCTG TGCCCTAA + +4 scertf__fordyce.MSN1 2 0.19185 4691.32 1 6 CACCTG AGGACATT + +4 taipale_cyt_meth__PRRX2_NTCGTTAN_eDBD_repr-OdsH-repo-unc-4 0 0.19185 4691.32 1 6 CACCTG AGCGTTAA + +4 transfac_pro__M07282-Ets21C-Ets96B-Ets97D-pnt 1 0.19185 4691.32 1 6 CACCTG CTTCCTGT + +4 cisbp__M0270-CrebB-Jra-REPTOR-BP-kay 0 0.19185 4691.32 1 6 CACCTG TACGTCAT - +4 cisbp__M0330-gt 0 0.19185 4691.32 1 6 CACCTG TACGTAAT - +4 cisbp__M0568 0 0.19185 4691.32 1 6 CACCTG GCCCTCCC - +4 cisbp__M0574 2 0.19185 4691.32 1 6 CACCTG CAAACTTT - +4 cisbp__M2355-Max 1 0.19185 4691.32 1 6 CACCTG TCACGTGG - +4 cisbp__M2362-Hey 1 0.19185 4691.32 1 6 CACCTG ACACGTGC - +4 flyfactorsurvey__CG32830_SANGER_10_FBgn0052830-ab 0 0.19185 4691.32 1 6 CACCTG TACTTCCT - +4 hocomoco__ZFX_MOUSE.H11MO.1.B 1 0.19185 4691.32 1 6 CACCTG GGGCCTGG - +4 jaspar__MA0958.1-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-Mnt 1 0.19185 4691.32 1 6 CACCTG GCACGTGC - +4 transfac_pro__M08866-Bgb-Bro-CG9650-ebi-lz-nej-run-RunxA-RunxB 1 0.19185 4691.32 1 6 CACCTG TAACCACA - +4 cisbp__M1276 3 0.19185 4691.32 1 5 CACCTG GTTAACCA + +4 cisbp__M1418-CG3328 3 0.19185 4691.32 1 5 CACCTG TGGTACCA + +4 jaspar__MA1020.1 3 0.19185 4691.32 1 5 CACCTG GTTAACCA + +4 predrem__nrMotif1510 3 0.19185 4691.32 1 5 CACCTG TTTTACCA + +4 cisbp__M1679 3 0.19185 4691.32 1 5 CACCTG GTTGACCG - +4 predrem__nrMotif1864 -1 0.19185 4691.32 1 5 CACCTG ATCTTGTG - +4 predrem__nrMotif2289 3 0.19185 4691.32 1 5 CACCTG CTCTACCA - +4 cisbp__M1287 4 0.19185 4691.32 1 4 CACCTG GGTTAACC + +4 predrem__nrMotif732 4 0.19185 4691.32 1 4 CACCTG CAGGGACC + +4 predrem__nrMotif1366 4 0.19185 4691.32 1 4 CACCTG CCGGGACC - +4 predrem__nrMotif1432 4 0.19185 4691.32 1 4 CACCTG CGCAGACC - +4 predrem__nrMotif554 -2 0.19185 4691.32 1 4 CACCTG CCTAAGAG - +4 scertf__fordyce.NRG2 4 0.19185 4691.32 1 4 CACCTG CTTGGACC - +4 cisbp__M0182-bigmax-Max-Mitf-Mondo 1 0.192339 4703.27 1 6 CACCTG CCACGTGATC + +4 cisbp__M0220-Clk-cnc-cyc-Mitf-tai-tgo 3 0.192339 4703.27 1 6 CACCTG TGTCACGTGC + +4 cisbp__M4968-da-Fer2 3 0.192339 4703.27 1 6 CACCTG CGTCAGCTGG + +4 neph__UW.Motif.0013-kn 0 0.192339 4703.27 1 6 CACCTG TCCCCGGGGA + +4 predrem__nrMotif1819 1 0.192339 4703.27 1 6 CACCTG AATCCTGGCA + +4 predrem__nrMotif2235 4 0.192339 4703.27 1 6 CACCTG CGGCCACCCC + +4 taipale__MYF6_full_AACAVBTGTT-amos-dimm-HLH54F-nau-sage 2 0.192339 4703.27 1 6 CACCTG AACAGCTGTT + +4 taipale__NHLH1_full_CGCAGCTGCG-HLH4C-nau 2 0.192339 4703.27 1 6 CACCTG CGCAGCTGCG + +4 taipale__Srebf1_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.192339 4703.27 1 6 CACCTG ATCACGTGAC + +4 transfac_pro__M05016 3 0.192339 4703.27 1 6 CACCTG CGTTACCTCT + +4 transfac_pro__M08927-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.192339 4703.27 1 6 CACCTG ATGACGTCAT + +4 yetfasco__YFR034C_2222-E2f1-Max-Myc 3 0.192339 4703.27 1 6 CACCTG GGGCACGTGG + +4 cisbp__M0487 1 0.192339 4703.27 1 6 CACCTG AATCCAGAAA - +4 cisbp__M0544-klu-sr 0 0.192339 4703.27 1 6 CACCTG CGCCCACGCA - +4 cisbp__M0620 3 0.192339 4703.27 1 6 CACCTG TGAAACATTT - +4 cisbp__M0663 1 0.192339 4703.27 1 6 CACCTG TCACTTTTTG - +4 cisbp__M1334 4 0.192339 4703.27 1 6 CACCTG AGGGAATCTT - +4 cisbp__M1680 4 0.192339 4703.27 1 6 CACCTG CGTTGACTTT - +4 cisbp__M5426-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.192339 4703.27 1 6 CACCTG CACTTCCGCT - +4 cisbp__M6517-Mitf-Usf 1 0.192339 4703.27 1 6 CACCTG CCACATGACC - +4 factorbook__BHLHE40-bigmax-cyc-tgo 3 0.192339 4703.27 1 6 CACCTG GGTCACGTGC - +4 homer__CCWGGAATGY_TEAD4-sd 3 0.192339 4703.27 1 6 CACCTG GCATTCCAGG - +4 homer__TTCAAGGTCA_Nr5a2-ERR-EcR-Hr4-ftz-f1-usp 1 0.192339 4703.27 1 6 CACCTG TGACCTTGAA - +4 predrem__nrMotif320 1 0.192339 4703.27 1 6 CACCTG CTGCCTTTGC - +4 taipale_cyt_meth__ASCL2_NRCAGCTGYN_FL-ac-ase-l(1)sc-nau-sc 2 0.192339 4703.27 1 6 CACCTG GGCAGCTGCT - +4 transfac_pro__M07580 2 0.192339 4703.27 1 6 CACCTG ATTACGTGTT - +4 transfac_pro__M07493 5 0.192339 4703.27 1 5 CACCTG TCAACCACCG + +4 homer__GCGATGAGMT_TOD6_ -1 0.192339 4703.27 1 5 CACCTG AGCTCATCGC - +4 transfac_pro__M07906-YL-1 6 0.192339 4703.27 1 4 CACCTG CGCGACCACC - +4 neph__UW.Motif.0659 3 0.192537 4708.1 1 6 CACCTG AGTCACATAATATTCA + +4 transfac_pro__M01312-scro-vnd 5 0.192537 4708.1 1 6 CACCTG TAAGCCACTTGAAATT + +4 transfac_pro__M02758-gcm-gcm2 3 0.192537 4708.1 1 6 CACCTG TCGTACCCGCATCATT + +4 transfac_pro__M01416-abd-A-Antp-Dfd-ftz-Scr-Ubx 9 0.192537 4708.1 1 6 CACCTG ATAATTAATGACCTCC - +4 transfac_pro__M03130-HLH54F-Oli 2 0.192537 4708.1 1 6 CACCTG GATACCAGATGTTTAT - +4 taipale_tf_pairs__HOXB13_TBX21_ARGTGTKANTTTATNN_CAP 11 0.192537 4708.1 1 5 CACCTG CCATAAATTCACACCT - +4 cisbp__M5892 12 0.192537 4708.1 1 4 CACCTG GGTGTGATATCACACC + +4 taipale__TBX21_full_GGTGTGAWATCACACC 12 0.192537 4708.1 1 4 CACCTG GGTGTGATATCACACC + +4 cisbp__M5111-cnc-Mitf-SREBP-tgo-Usf 1 0.192786 4714.2 1 6 CACCTG TCACGTG - +4 flyfactorsurvey__Mitf_SANGER_5_FBgn0263112-Mitf-Mondo-SREBP-Usf-bigmax-cnc-tgo 1 0.192786 4714.2 1 6 CACCTG TCACGTG - +4 transfac_pro__M02082-tup 0 0.192786 4714.2 1 6 CACCTG CACTTAA - +4 elemento__AGCTGCC -1 0.192786 4714.2 1 5 CACCTG AGCTGCC + +4 elemento__AGCTGCG -1 0.192786 4714.2 1 5 CACCTG AGCTGCG + +4 elemento__CCCTGCC -1 0.192786 4714.2 1 5 CACCTG CCCTGCC + +4 elemento__TCCTGCA -1 0.192786 4714.2 1 5 CACCTG TCCTGCA + +4 elemento__TCCTGGC -1 0.192786 4714.2 1 5 CACCTG TCCTGGC + +4 predrem__nrMotif837 2 0.192786 4714.2 1 5 CACCTG AAAGCCT + +4 elemento__AGCAGCT -1 0.192786 4714.2 1 5 CACCTG AGCTGCT - +4 elemento__AGCAGGC -1 0.192786 4714.2 1 5 CACCTG GCCTGCT - +4 elemento__CGCAGGA -1 0.192786 4714.2 1 5 CACCTG TCCTGCG - +4 elemento__TCCAGGA -1 0.192786 4714.2 1 5 CACCTG TCCTGGA - +4 elemento__TCCAGGC -1 0.192786 4714.2 1 5 CACCTG GCCTGGA - +4 elemento__CATGACC-usp 3 0.192786 4714.2 1 4 CACCTG CATGACC + +4 elemento__CTTGACC 3 0.192786 4714.2 1 4 CACCTG CTTGACC + +4 elemento__GCTGACC 3 0.192786 4714.2 1 4 CACCTG GCTGACC + +4 cisbp__M1900-Eip75B-Hr3 2 0.193429 4729.92 1 6 CACCTG TTGACCTACTTATA + +4 cisbp__M4512-bs 2 0.193429 4729.92 1 6 CACCTG TTTGCCTTATATGG + +4 cisbp__M5801-EcR-eg-ham-Hr78-kni-knrl-usp 8 0.193429 4729.92 1 6 CACCTG GGGGTCATGACCTC + +4 factorbook__SRF-bs 2 0.193429 4729.92 1 6 CACCTG TTTGCCTTATATGG + +4 swissregulon__hs__TAL1_TCF_3_4_12_.p2-HLH3B-HLH54F 4 0.193429 4729.92 1 6 CACCTG AGAACATCTGGTAT + +4 transfac_public__M00477-croc-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp1 8 0.193429 4729.92 1 6 CACCTG TTGTTGTTTACATA + +4 cisbp__M4927-dsx 4 0.193429 4729.92 1 6 CACCTG TAATAACTTTGTAG - +4 jaspar__MA0072.1-Eip75B-Hr3 2 0.193429 4729.92 1 6 CACCTG TTGACCTACTTATA - +4 taipale__RXRG_DBD_RRGGTCATGACCYY-EcR-eg-ham-Hr78-kni-knrl-usp 8 0.193429 4729.92 1 6 CACCTG GGGGTCATGACCTC - +4 transfac_pro__M02830 7 0.193429 4729.92 1 6 CACCTG TTATTAGTACATAA - +4 transfac_pro__M07067-ac-ase-cnc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 2 0.193429 4729.92 1 6 CACCTG CCCACGTGACCCCG - +4 transfac_public__M00420 5 0.193429 4729.92 1 6 CACCTG TCGTAAAACTGTCA - +4 hocomoco__TBX20_HUMAN.H11MO.0.D-H15-mid -1 0.193429 4729.92 1 5 CACCTG ACCTGTCAGCACCT - +4 cisbp__M6556 10 0.193492 4731.46 1 6 CACCTG GGGCAACAAATCCCTGCGCCCCGT + +4 cisbp__M0221-Max-Myc 1 0.194338 4752.14 1 6 CACCTG CCACGTGGT + +4 cisbp__M0966-bap-scro-tin-vnd 1 0.194338 4752.14 1 6 CACCTG CCACTTAAA + +4 cisbp__M1773 2 0.194338 4752.14 1 6 CACCTG TGTTCCGAT + +4 cisbp__M4676-Myb 3 0.194338 4752.14 1 6 CACCTG CTGCAACTG + +4 predrem__nrMotif1279 3 0.194338 4752.14 1 6 CACCTG TTTCACCAG + +4 predrem__nrMotif1413 1 0.194338 4752.14 1 6 CACCTG CCACCGGCC + +4 predrem__nrMotif2202 1 0.194338 4752.14 1 6 CACCTG GGTCCTGAG + +4 predrem__nrMotif2333 2 0.194338 4752.14 1 6 CACCTG AGCCCCTAG + +4 predrem__nrMotif268 0 0.194338 4752.14 1 6 CACCTG CTCCTCTGA + +4 predrem__nrMotif600 2 0.194338 4752.14 1 6 CACCTG GGCACCAGC + +4 predrem__nrMotif958 0 0.194338 4752.14 1 6 CACCTG TCCCTTGGT + +4 taipale__NKX3-1_full_NCCACTTAA-bap 2 0.194338 4752.14 1 6 CACCTG ACCACTTAA + +4 taipale_cyt_meth__TEAD1_NRCATWCCN_FL-sd 0 0.194338 4752.14 1 6 CACCTG CGCATTCCA + +4 cisbp__M2127 2 0.194338 4752.14 1 6 CACCTG TTCACATGC - +4 cisbp__M5142-pad 2 0.194338 4752.14 1 6 CACCTG TACCCCTTC - +4 hocomoco__ZIC1_HUMAN.H11MO.0.B-opa 3 0.194338 4752.14 1 6 CACCTG GACCACCCC - +4 predrem__nrMotif1272 1 0.194338 4752.14 1 6 CACCTG CCACCAGTC - +4 predrem__nrMotif1355 0 0.194338 4752.14 1 6 CACCTG AACTTGCTC - +4 predrem__nrMotif174 2 0.194338 4752.14 1 6 CACCTG CCCACCAGG - +4 predrem__nrMotif2365 0 0.194338 4752.14 1 6 CACCTG GAGCTGACA - +4 transfac_pro__M01671 2 0.194338 4752.14 1 6 CACCTG TTCACATGC - +4 transfac_pro__M03845-Mad 0 0.194338 4752.14 1 6 CACCTG TGTCTGCCC - +4 transfac_pro__M07372-lz-run-RunxA-RunxB 2 0.194338 4752.14 1 6 CACCTG CTCACCACA - +4 cisbp__M1123 -1 0.194338 4752.14 1 5 CACCTG ACCTGTCAT + +4 cisbp__M4359 4 0.194338 4752.14 1 5 CACCTG CCGATACCG + +4 predrem__nrMotif2078 -1 0.194338 4752.14 1 5 CACCTG ACATGGAGA + +4 predrem__nrMotif1207 4 0.194338 4752.14 1 5 CACCTG AGCCAACAT - +4 predrem__nrMotif1787 -1 0.194338 4752.14 1 5 CACCTG ACATGAGAA - +4 predrem__nrMotif2494 -1 0.194338 4752.14 1 5 CACCTG AACTTGCCT - +4 yetfasco__YML099C_1506 4 0.194338 4752.14 1 5 CACCTG CCGATACCG - +4 swissregulon__hs__GTF2I.p2 -2 0.194338 4752.14 1 4 CACCTG CCTCCCTCC - +4 transfac_pro__M02824 9 0.195361 4777.16 1 6 CACCTG GTGATCTAGAACCTTAG - +4 transfac_pro__M02860-srp 7 0.195361 4777.16 1 6 CACCTG ACACTGATATCTCTGTC - +4 transfac_pro__M07485 8 0.195381 4777.66 1 6 CACCTG TATCATAGTACCAACCCTACAGAGTAA + +4 taipale_cyt_meth__ZNF580_NRTTATGTTAAAWWNYTACCNYN_FL_meth 16 0.195593 4782.84 1 6 CACCTG CATTATGTTAAATTATTACCCTA + +4 cisbp__M1917-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.196351 4801.37 1 6 CACCTG GGTCACGTGGC + +4 cisbp__M2322-cnc-cyc-Mitf-SREBP-tgo-Usf 3 0.196351 4801.37 1 6 CACCTG GGTCACATGAC + +4 flyfactorsurvey__sens2_SOLEXA_F4-6-sens-2 4 0.196351 4801.37 1 6 CACCTG AATAAATCTGA + +4 transfac_pro__M07922-CG31388 5 0.196351 4801.37 1 6 CACCTG GCCGTCACTTT + +4 cisbp__M6322-CG42741-dar1 4 0.196351 4801.37 1 6 CACCTG GCCACACCCTG - +4 hocomoco__NR5A2_HUMAN.H11MO.0.B-ERR-Hr4-ftz-f1-usp 1 0.196351 4801.37 1 6 CACCTG TGGCCTTGAAC - +4 jaspar__MA0111.1 5 0.196351 4801.37 1 6 CACCTG GCTGTTACCCT - +4 predrem__nrMotif1853 5 0.196351 4801.37 1 6 CACCTG TGCCCCACCCC - +4 predrem__nrMotif2131 2 0.196351 4801.37 1 6 CACCTG CCCACCCATCC - +4 swissregulon__sacCer__REB1 3 0.196351 4801.37 1 6 CACCTG TGTTACCCGGA - +4 transfac_pro__M01138-Eip75B-Hr3 1 0.196351 4801.37 1 6 CACCTG TGACCCAATTA - +4 transfac_pro__M05305 5 0.196351 4801.37 1 6 CACCTG GGTAAAACTTA - +4 transfac_pro__M09115 1 0.196351 4801.37 1 6 CACCTG TTACTTTTTCT - +4 hocomoco__DLX5_HUMAN.H11MO.0.D-Sp1 -1 0.196351 4801.37 1 5 CACCTG ACCTATAATTA + +4 neph__UW.Motif.0477 4 0.196519 4805.48 1 6 CACCTG GCTTTGCCAGTCA + +4 hocomoco__HNF1B_MOUSE.H11MO.1.A 7 0.196519 4805.48 1 6 CACCTG AATCATTAACTAA - +4 transfac_pro__M05420-ovo 2 0.196519 4805.48 1 6 CACCTG GGTACCGGCCGTC - +4 neph__UW.Motif.0502 8 0.196519 4805.48 1 5 CACCTG TTTTCTTTCACTT - +4 taipale_tf_pairs__MYBL1_MAX_YAACGGNNNNNNNNNNCACGTG_CAP_repr-Max-Myb 0 0.197184 4821.73 1 6 CACCTG TAACGGTTGCCTGGAGCACGTG + +4 taipale_tf_pairs__TEAD4_EOMES_NGYGNNAMATWCYNNTMRCRCN_CAP_repr-sd 5 0.197184 4821.73 1 6 CACCTG GGTGCCACATTCCTTTCACACC + +4 taipale_tf_pairs__CLOCK_NHLH1_NNCAGCTGNNNNNNCACGTGNN_CAP_repr-Clk-HLH4C 14 0.197184 4821.73 1 6 CACCTG GACACGTGTTGGAGCAGCTGCG - +4 taipale_tf_pairs__ETV2_FIGLA_NNCAGGTGNNNNNMCGGAARYN_CAP_repr-pnt 14 0.197184 4821.73 1 6 CACCTG CACTTCCGGTTTACCACCTGCT - +4 transfac_pro__M07738-gcm-gcm2 8 0.197257 4823.52 1 6 CACCTG TATGCTGGTACCAGCATG + +4 transfac_pro__M06900 2 0.197257 4823.52 1 6 CACCTG CCCACCTCGTCCCACCAC - +4 transfac_pro__M09362 0 0.197257 4823.52 1 6 CACCTG TACTTGTTCCACACGTAA - +4 bergman__Dip3-Dlip3 3 0.197606 4832.05 1 6 CACCTG CCACACCTTGCC + +4 cisbp__M0360 5 0.197606 4832.05 1 6 CACCTG GTAATGACGTGA + +4 hocomoco__AP2A_MOUSE.H11MO.0.A-GATAe-TfAP-2-grn-pnr 2 0.197606 4832.05 1 6 CACCTG ATGGCCTGAGGC + +4 scertf__macisaac.YRR1 6 0.197606 4832.05 1 6 CACCTG TTTTGTTACCCG + +4 taipale__Irx3_DBD_NWACATGAMAWN_repr-ara-caup-mirr 1 0.197606 4832.05 1 6 CACCTG CTACATGACAAA + +4 taipale_cyt_meth__MBNL2_NYGCTTYGCTTN_FL_meth-mbl 1 0.197606 4832.05 1 6 CACCTG TTGCTTCGCTTC + +4 taipale_cyt_meth__MEIS3_TGACANNTGTCA_eDBD-achi-Fer1-hth-nau-vis 3 0.197606 4832.05 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M05686 5 0.197606 4832.05 1 6 CACCTG AGGGAAAACTTC + +4 transfac_pro__M07649-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.197606 4832.05 1 6 CACCTG TGGCACGTGCCA + +4 transfac_pro__M09561-Atf6-Clk-CrebA-Met 3 0.197606 4832.05 1 6 CACCTG GGACACGTGGCA + +4 cisbp__M0241 4 0.197606 4832.05 1 6 CACCTG AAATCACGTGCT - +4 cisbp__M5374-aop-Eip74EF-Ets21C 0 0.197606 4832.05 1 6 CACCTG CACTTCCGGGTT - +4 cisbp__M6306-nerfin-1-nerfin-2 3 0.197606 4832.05 1 6 CACCTG TGCCCCCTGACA - +4 taipale__ELF1_full_AACCCGGAAGTR-aop-Eip74EF-Ets21C 0 0.197606 4832.05 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__ELF2_NATGCGGAAGTN_FL-Eip74EF 0 0.197606 4832.05 1 6 CACCTG CACTTCCGCATT - +4 taipale_cyt_meth__ELF2_NATGCGGAAGTN_FL_meth-Eip74EF 0 0.197606 4832.05 1 6 CACCTG TACTTCCGGATT - +4 taipale_cyt_meth__MYOD1_YGTCANNTGTYN_eDBD_meth-achi-amos-Fer1-Fer3-HLH54F-hth-nau-vis 3 0.197606 4832.05 1 6 CACCTG TAACAGCTGTCG - +4 taipale_cyt_meth__MYOG_CGTCANNTGTYN_eDBD-amos-HLH54F-nau 3 0.197606 4832.05 1 6 CACCTG CAACAGCTGTCG - +4 transfac_pro__M05718 1 0.197606 4832.05 1 6 CACCTG GCATCTTAACCA - +4 transfac_pro__M06420-CG3281 6 0.197606 4832.05 1 6 CACCTG TCTGCCGACCAG - +4 transfac_pro__M06623 4 0.197606 4832.05 1 6 CACCTG GCGCAATCTTAA - +4 hocomoco__SMAD2_HUMAN.H11MO.0.A-Med-Smox 7 0.197606 4832.05 1 5 CACCTG TGTCTGTCACCT + +4 transfac_pro__M05367 7 0.197606 4832.05 1 5 CACCTG TCTGTTTTATCT - +4 transfac_pro__M05526 7 0.197606 4832.05 1 5 CACCTG AAACGCCAACCG - +4 transfac_pro__M05875 7 0.197606 4832.05 1 5 CACCTG AAACGCCAACCG - +4 transfac_pro__M06013 7 0.197606 4832.05 1 5 CACCTG GCTACCAAACCG - +4 transfac_pro__M06499 7 0.197606 4832.05 1 5 CACCTG TCCTATCCACCG - +4 transfac_pro__M06792-CG2120 7 0.197606 4832.05 1 5 CACCTG TCTTTTGGACCT - +4 neph__UW.Motif.0651 -2 0.197606 4832.05 1 4 CACCTG CCTCAGGCATTT - +4 taipale_tf_pairs__GCM1_NHLH1_NCAGCTGNNNNNNNNTRCGGG_CAP_repr-gcm-gcm2-HLH4C 1 0.198208 4846.78 1 6 CACCTG GCAGCTGCGTCCCGATGCGGG + +4 cisbp__M2324-btd-CoRest-ct-CTCF-Dif-dl-Klf15-klu-Spps-sr 11 0.198208 4846.78 1 6 CACCTG TCCTCCTCCCCCTCCTCCTCC - +4 cisbp__M4443-Chd1-CTCF-Hcf-SMC3-usp-vtd 9 0.198208 4846.78 1 6 CACCTG CTCGGGCGCCCCCTGGTGGCC - +4 jaspar__MA0528.1-CTCF-CoRest-Dif-Klf15-Spps-btd-ct-dl-klu-sr 11 0.198208 4846.78 1 6 CACCTG TCCTCCTCCCCCTCCTCCTCC - +4 transfac_pro__M05795 -1 0.198208 4846.78 1 5 CACCTG ACATACTCCTTTCCCGCCACG - +4 transfac_pro__M05796 -1 0.198208 4846.78 1 5 CACCTG ACATACTCCTTTCCCGCCACG - +4 taipale_tf_pairs__RFX3_FIGLA_TRGYAACNNNNCASSTGNN_CAP_repr-Rfx 2 0.198312 4849.33 1 6 CACCTG TCCACCTGTTCCGTTGCCA - +4 transfac_pro__M06894 12 0.198312 4849.33 1 6 CACCTG CCGCTACCGATTACCCTTA - +4 transfac_pro__M09300-Myb 0 0.198312 4849.33 1 6 CACCTG TAACGGAAATAACCGTAAA - +4 transfac_pro__M09393 0 0.198312 4849.33 1 6 CACCTG TACTTGAAGATGAAGAAAC - +4 dbcorrdb__RELA__ENCSR000EBM_1__m1-CG12018-Dif-dl-Rel-shn 11 0.198606 4856.51 1 6 CACCTG GCCTGGGAAATCCCCTACCC + +4 dbcorrdb__TCF12__ENCSR000BGZ_1__m1-ac-ase-dimm-l(1)sc-nau-sc 11 0.198606 4856.51 1 6 CACCTG CGCCCCAACAGCAGCTGCTG + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m3-E(z) 2 0.198606 4856.51 1 6 CACCTG CAAACCTTCTGTTGACGAGA - +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m3-egg 5 0.198606 4856.51 1 6 CACCTG TTTATTACTTACATAGGTTT - +4 hocomoco__ZN680_HUMAN.H11MO.0.C-Iswi -2 0.198606 4856.51 1 4 CACCTG CCTCATTCTTCTTGGACATG - +4 hocomoco__MYOD1_MOUSE.H11MO.0.A-Fer1-nau 1 0.198721 4859.31 1 6 CACCTG GCAGCTGTTCCTGTC + +4 taipale_cyt_meth__ZIC4_NRCCMCCYGYNGTGN_eDBD_meth_repr-HDAC1-opa 3 0.198721 4859.31 1 6 CACCTG GACCCCCTGCTGTGC + +4 taipale_tf_pairs__FLI1_FIGLA_RSCGGAANCASSTGN_CAP 8 0.198721 4859.31 1 6 CACCTG ACCGGAAACAGCTGG + +4 transfac_pro__M01201-fkh 2 0.198721 4859.31 1 6 CACCTG GGTACAGGGTGTTCT + +4 taipale_tf_pairs__GCM1_HOXA2_RTRSGGGNNTAATKR_CAP_repr-gcm-gcm2-pb 6 0.198721 4859.31 1 6 CACCTG TAATTACGCCCGCAT - +4 transfac_pro__M02941-opa 1 0.198721 4859.31 1 6 CACCTG TGTCCTGCTGTGCTC - +4 transfac_pro__M06800 9 0.198721 4859.31 1 6 CACCTG CTTACCAGACACCAG - +4 neph__UW.Motif.0219 10 0.198721 4859.31 1 5 CACCTG TGGCAGTTTTTTTCT - +4 neph__UW.Motif.0012 1 0.201381 4924.36 1 6 CACCTG CAGCCTGG + +4 predrem__nrMotif2256 0 0.201381 4924.36 1 6 CACCTG AAACTAGA + +4 predrem__nrMotif2632 1 0.201381 4924.36 1 6 CACCTG CAACTTAA + +4 taipale_cyt_meth__ALX4_NTCGTTAN_eDBD_meth-Lim3-OdsH-repo-unc-4 0 0.201381 4924.36 1 6 CACCTG CTCGTTAA + +4 hocomoco__NR1I2_HUMAN.H11MO.1.D-EcR 2 0.201381 4924.36 1 6 CACCTG GTGAACTT - +4 jaspar__MA1047.1-CrebB-Jra-REPTOR-BP-kay 0 0.201381 4924.36 1 6 CACCTG TACGTCAT - +4 predrem__nrMotif1304 2 0.201381 4924.36 1 6 CACCTG GTCAGCTT - +4 predrem__nrMotif1375 0 0.201381 4924.36 1 6 CACCTG CACCCCTT - +4 transfac_pro__M09559 1 0.201381 4924.36 1 6 CACCTG TGCCCTAG - +4 fantom__motif169_GCCTGGCC -1 0.201381 4924.36 1 5 CACCTG GCCTGGCC + +4 predrem__nrMotif1521 -1 0.201381 4924.36 1 5 CACCTG CCCTCCTT + +4 predrem__nrMotif1646 3 0.201381 4924.36 1 5 CACCTG ATGTACAT + +4 cisbp__M0621 3 0.201381 4924.36 1 5 CACCTG TGAAACAT - +4 jaspar__MA1092.1 3 0.201381 4924.36 1 5 CACCTG GTTGACCG - +4 predrem__nrMotif1350 -2 0.201381 4924.36 1 4 CACCTG CCTGTCTA + +4 tfdimers__MD00222-ac-ase-GATAe-grn-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-pnr-sc-srp-Usf 19 0.201684 4931.78 1 6 CACCTG TATCCCTTATCTCTCTATCCACCTGTCCTTCTC - +4 cisbp__M1728 0 0.201953 4938.35 1 6 CACCTG CCCCGACCCC + +4 cisbp__M1796 4 0.201953 4938.35 1 6 CACCTG TTATCTCCGG + +4 cisbp__M5321-Clk 2 0.201953 4938.35 1 6 CACCTG AACACGTGTT + +4 cisbp__M5904-sd 0 0.201953 4938.35 1 6 CACCTG CACATTCCAT + +4 homer__NRYTTCCGGH_Fli1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-Hcf-RpII215-Taf1-aop-bs-grn-pnr-pnt 3 0.201953 4938.35 1 6 CACCTG CACTTCCGGT + +4 jaspar__MA0603.1-Clk-Mitf-cnc-cyc-tai-tgo 3 0.201953 4938.35 1 6 CACCTG GGTCACGTGC + +4 predrem__nrMotif2120 3 0.201953 4938.35 1 6 CACCTG TTGGGCCTGG + +4 swissregulon__sacCer__YPR196W 4 0.201953 4938.35 1 6 CACCTG ATTTCTCCGA + +4 taipale__CLOCK_DBD_NACACGTGTN_repr-Clk 2 0.201953 4938.35 1 6 CACCTG AACACGTGTT + +4 taipale_cyt_meth__ARNTL_RTCACGTGMN_eDBD-Clk-cnc-cyc-Mitf-SREBP-tai-tgo 2 0.201953 4938.35 1 6 CACCTG GTCACGTGCC + +4 taipale_cyt_meth__ASCL2_NRCAGCTGYN_eDBD-ac-ase-l(1)sc-nau-sc 2 0.201953 4938.35 1 6 CACCTG GGCAGCTGCC + +4 taipale_cyt_meth__CLOCK_NMCAYGTGYN_eDBD-Clk-Hey-Met-Myc-tai 2 0.201953 4938.35 1 6 CACCTG GCCACGTGCC + +4 transfac_pro__M01043 3 0.201953 4938.35 1 6 CACCTG TGCCACTTGA + +4 transfac_pro__M04621 2 0.201953 4938.35 1 6 CACCTG CTCACCAAAT + +4 transfac_pro__M09571 4 0.201953 4938.35 1 6 CACCTG AGGGAATCTT + +4 yetfasco__YHR006W_2174 2 0.201953 4938.35 1 6 CACCTG GGTGCCGTAC + +4 cisbp__M0026 1 0.201953 4938.35 1 6 CACCTG CCACCGACAC - +4 cisbp__M0417-klu-sr 0 0.201953 4938.35 1 6 CACCTG CGCCCCCGCA - +4 cisbp__M0446 4 0.201953 4938.35 1 6 CACCTG CCTGAAACAA - +4 cisbp__M1364 4 0.201953 4938.35 1 6 CACCTG AGGGAATCTT - +4 cisbp__M1690 4 0.201953 4938.35 1 6 CACCTG CGTTGACTTT - +4 cisbp__M1699 4 0.201953 4938.35 1 6 CACCTG CGTTGACCTT - +4 cisbp__M3316-GATAe-grn-pnr-srp 3 0.201953 4938.35 1 6 CACCTG TCTTATCTAT - +4 cisbp__M3328-GATAe-grn-pnr 3 0.201953 4938.35 1 6 CACCTG TAAGATCTTT - +4 cisbp__M4710-Blimp-1 0 0.201953 4938.35 1 6 CACCTG CACTTTCACT - +4 cisbp__M5422-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.201953 4938.35 1 6 CACCTG CACTTCCGGT - +4 cisbp__M5651-amos-dimm-HLH54F-nau-sage 2 0.201953 4938.35 1 6 CACCTG AACAGCTGTT - +4 cisbp__M5671-HLH4C 2 0.201953 4938.35 1 6 CACCTG CGCAGCTGCG - +4 cisbp__M6097-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.201953 4938.35 1 6 CACCTG ATCACGTGAC - +4 hocomoco__GATA4_HUMAN.H11MO.0.A-CoRest-GATAe-HDAC1-HLH3B-Jra-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.201953 4938.35 1 6 CACCTG TCTTATCTGT - +4 hocomoco__MITF_HUMAN.H11MO.0.A-Max-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo 3 0.201953 4938.35 1 6 CACCTG GGTCACGTGA - +4 hocomoco__NDF1_HUMAN.H11MO.0.A-HLH54F-Oli-amos-da-tap 2 0.201953 4938.35 1 6 CACCTG ACCATCTGTC - +4 hocomoco__NDF2_MOUSE.H11MO.0.A-amos-tap 2 0.201953 4938.35 1 6 CACCTG GCCATCTGTT - +4 homer__TGGCAGTTGG_AMYB-Myb 1 0.201953 4938.35 1 6 CACCTG CCAACTGCCA - +4 jaspar__MA1022.1 1 0.201953 4938.35 1 6 CACCTG TCACTTTTTG - +4 jaspar__MA1088.1 4 0.201953 4938.35 1 6 CACCTG CGTTGACCTC - +4 jaspar__MA1089.1 4 0.201953 4938.35 1 6 CACCTG CGTTGACTTT - +4 predrem__nrMotif1669 2 0.201953 4938.35 1 6 CACCTG AAAACCAGTT - +4 predrem__nrMotif2361 0 0.201953 4938.35 1 6 CACCTG TACTTTCCTT - +4 predrem__nrMotif480 3 0.201953 4938.35 1 6 CACCTG AAACATCTCC - +4 swissregulon__hs__GATA6.p2-CoRest-GATAe-HLH3B-Jra-Sirt6-Snr1-brm-ebi-grn-nej-pnr-srp-svp 3 0.201953 4938.35 1 6 CACCTG CCTTATCTGT - +4 taipale__ETV6_full_KSYGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.201953 4938.35 1 6 CACCTG CACTTCCGCT - +4 taipale__Elk3_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.201953 4938.35 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M01818 4 0.201953 4938.35 1 6 CACCTG GTGCCACGTC - +4 transfac_pro__M05303 3 0.201953 4938.35 1 6 CACCTG TAGCACCTGC - +4 transfac_public__M00351-GATAe-grn-pnr 3 0.201953 4938.35 1 6 CACCTG TAAGATCTTT - +4 flyfactorsurvey__disco_SANGER_5_FBgn0000459-disco-disco-r 6 0.201953 4938.35 1 4 CACCTG AAGTGTCACC + +4 taipale_cyt_meth__ZNF449_RCGCCCAACC_eDBD_repr 6 0.201953 4938.35 1 4 CACCTG GCGCCCAACC + +4 cisbp__M4914-disco-disco-r 6 0.201953 4938.35 1 4 CACCTG AAGTGTCACC - +4 transfac_pro__M04935-btd-Spps 0 0.202409 4949.5 1 6 CACCTG CCCCTTT - +4 bergman__pros-pros 2 0.202409 4949.5 1 5 CACCTG CATGTCT + +4 predrem__nrMotif1959 2 0.202409 4949.5 1 5 CACCTG TGTATCT + +4 predrem__nrMotif2104 -1 0.202409 4949.5 1 5 CACCTG CCCTCCA + +4 predrem__nrMotif2630 2 0.202409 4949.5 1 5 CACCTG CAATCCT + +4 elemento__ATGTGGA 2 0.202409 4949.5 1 5 CACCTG TCCACAT - +4 stark__ATGTGAT 2 0.202409 4949.5 1 5 CACCTG ATCACAT - +4 swissregulon__sacCer__HAC1 -1 0.202409 4949.5 1 5 CACCTG ACGTGTC - +4 transfac_pro__M03216-GATAe-grn-pnr-srp 2 0.202409 4949.5 1 5 CACCTG CTTATCT - +4 predrem__nrMotif1051 -2 0.202409 4949.5 1 4 CACCTG CCTGTTC + +4 predrem__nrMotif801 -3 0.202409 4949.5 1 3 CACCTG CTGACAA + +4 hocomoco__DMRTB_MOUSE.H11MO.0.C-dmrt99B 4 0.202815 4959.43 1 6 CACCTG TTGCTACATTGTATCC + +4 neph__UW.Motif.0641 7 0.202815 4959.43 1 6 CACCTG AGAAAAGATTCTGTGT - +4 scertf__morozov.MCM1-bs 1 0.202815 4959.43 1 6 CACCTG TTTCCCGATTAGGAAA - +4 neph__UW.Motif.0661 -1 0.202815 4959.43 1 5 CACCTG AGCATCTTTCTTCCCA + +4 taipale_tf_pairs__GCM1_HOXB13_NCCCGCANNNMRTAAA_CAP_repr-gcm-gcm2 -1 0.202815 4959.43 1 5 CACCTG ACCCGCACCCCATAAA + +4 neph__UW.Motif.0347 -1 0.202815 4959.43 1 5 CACCTG AATTTAATATCAGCTT - +4 cisbp__M5527-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 1 0.203516 4976.58 1 6 CACCTG TGACCTTTGACCCC + +4 hocomoco__SIX4_MOUSE.H11MO.0.C-Six4-so 3 0.203516 4976.58 1 6 CACCTG TGAAACCTGAGACC + +4 neph__UW.Motif.0158 5 0.203516 4976.58 1 6 CACCTG AAACAGACCAGCTG + +4 transfac_pro__M05189 0 0.203516 4976.58 1 6 CACCTG GACCTCGTTTAGGG + +4 transfac_pro__M07274 4 0.203516 4976.58 1 6 CACCTG CTGACACGTGTCTT + +4 transfac_pro__M07275-Hey 5 0.203516 4976.58 1 6 CACCTG ACCGACACGTGTCC + +4 cisbp__M3280-croc-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp1 8 0.203516 4976.58 1 6 CACCTG TTGTTGTTTACATA - +4 taipale__HNF4A_full_RRGGTCAAAGGTCA_repr-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-usp 1 0.203516 4976.58 1 6 CACCTG TGACCTTTGACCCC - +4 cisbp__M1162 2 0.203987 4988.1 1 6 CACCTG ATTACACGA + +4 cisbp__M1715 2 0.203987 4988.1 1 6 CACCTG TTTGCCGAG + +4 hocomoco__E4F1_HUMAN.H11MO.0.D-CrebB 3 0.203987 4988.1 1 6 CACCTG CGTGACGTC + +4 predrem__nrMotif1524 3 0.203987 4988.1 1 6 CACCTG TCTGACTTT + +4 predrem__nrMotif1888 3 0.203987 4988.1 1 6 CACCTG TTGCACATG + +4 predrem__nrMotif1893 3 0.203987 4988.1 1 6 CACCTG GTGCACCAG + +4 predrem__nrMotif1935 2 0.203987 4988.1 1 6 CACCTG AACACTTGA + +4 predrem__nrMotif304 2 0.203987 4988.1 1 6 CACCTG AAGACATGA + +4 taipale_cyt_meth__TEAD1_NRCATWCCN_FL_meth_repr-sd 0 0.203987 4988.1 1 6 CACCTG CGCATTCCA + +4 transfac_pro__M08819 3 0.203987 4988.1 1 6 CACCTG CCCCACCCC + +4 cisbp__M0765 3 0.203987 4988.1 1 6 CACCTG CTAGATCTG - +4 cisbp__M1042-bap-scro-vnd 2 0.203987 4988.1 1 6 CACCTG ACCACTTAA - +4 cisbp__M1561 3 0.203987 4988.1 1 6 CACCTG CCGTACCCC - +4 cisbp__M6549-opa 3 0.203987 4988.1 1 6 CACCTG GACCACCCC - +4 jaspar__MA0322.1 2 0.203987 4988.1 1 6 CACCTG TTCACATGC - +4 predrem__nrMotif1208 2 0.203987 4988.1 1 6 CACCTG AACAACTCA - +4 predrem__nrMotif1240 0 0.203987 4988.1 1 6 CACCTG TGCCTTTTG - +4 predrem__nrMotif1484 3 0.203987 4988.1 1 6 CACCTG AGCAAACTT - +4 predrem__nrMotif2518 3 0.203987 4988.1 1 6 CACCTG AGAAACATA - +4 predrem__nrMotif904 1 0.203987 4988.1 1 6 CACCTG TCACATGCA - +4 taipale_cyt_meth__NR2E1_NAAAGTCAN_FL_meth-tll 2 0.203987 4988.1 1 6 CACCTG TTGACTTTT - +4 transfac_pro__M04684-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 1 0.203987 4988.1 1 6 CACCTG TCACGTGAC - +4 predrem__nrMotif1904 4 0.203987 4988.1 1 5 CACCTG TAAAGAGCT + +4 predrem__nrMotif2129 -1 0.203987 4988.1 1 5 CACCTG ATCTGGCCT + +4 predrem__nrMotif2223 4 0.203987 4988.1 1 5 CACCTG CAACCACAT + +4 predrem__nrMotif934 4 0.203987 4988.1 1 5 CACCTG AAATCACAT + +4 swissregulon__sacCer__SOK2 -1 0.203987 4988.1 1 5 CACCTG ACCTGCAGG + +4 transfac_pro__M04814-Dif-dl 4 0.203987 4988.1 1 5 CACCTG AAATCCCCT + +4 predrem__nrMotif1117 4 0.203987 4988.1 1 5 CACCTG AGAGGACCC - +4 predrem__nrMotif2272 -1 0.203987 4988.1 1 5 CACCTG ATCTGAGAA - +4 predrem__nrMotif677 -1 0.203987 4988.1 1 5 CACCTG ATCTGGAAA - +4 transfac_pro__M00630-foxo 4 0.203987 4988.1 1 5 CACCTG AGTCCATCT - +4 transfac_pro__M01721-Pur-alpha -1 0.203987 4988.1 1 5 CACCTG CACTGGCCC - +4 predrem__nrMotif1065 5 0.203987 4988.1 1 4 CACCTG TTGGGAACC - +4 fantom__motif57_AGGCAT 1 0.205385 5022.28 1 5 CACCTG ATGCCT - +4 fantom__motif63_GTNCCA 3 0.205385 5022.28 1 3 CACCTG TGGAAC - +4 cisbp__M6338 6 0.205832 5033.21 1 6 CACCTG TACAACAACCTGTTCTT + +4 transfac_pro__M01359 8 0.205832 5033.21 1 6 CACCTG TAAATAGATACCCCATA + +4 hocomoco__MCR_HUMAN.H11MO.0.D 6 0.205832 5033.21 1 6 CACCTG TACAACAACCTGTTCTA - +4 transfac_pro__M01383-bap-vnd 8 0.205832 5033.21 1 6 CACCTG CATTTAAGTACTTAGTA - +4 taipale_tf_pairs__E2F3_TBX21_NGGTGTGNNNGGCGCSN_CAP_repr-E2f1 12 0.205832 5033.21 1 5 CACCTG ACGCGCGATTCACACCT - +4 cisbp__M0327-Atf6-CrebA 3 0.206189 5041.94 1 6 CACCTG TGCCACGTGTT + +4 cisbp__M1933 5 0.206189 5041.94 1 6 CACCTG GCTGTTACCCT + +4 cisbp__M4451-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.206189 5041.94 1 6 CACCTG GGTCACGTGAC + +4 scertf__spivak.CIN5-CG7786-Pdp1-gt 2 0.206189 5041.94 1 6 CACCTG ATTACGTAAGC + +4 taipale__ETV2_DBD_AACCGGAARTR-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.206189 5041.94 1 6 CACCTG AACCGGAAATA + +4 transfac_pro__M01295 4 0.206189 5041.94 1 6 CACCTG CCTCTTCCTTA + +4 cisbp__M6351-E2f1-Max-Myc-tgo-Usf 3 0.206189 5041.94 1 6 CACCTG GAGCACGTGGC - +4 hocomoco__BHA15_HUMAN.H11MO.0.B-Fer1-dimm 1 0.206189 5041.94 1 6 CACCTG CCAGCTGCTGC - +4 hocomoco__GATA3_HUMAN.H11MO.0.A-GATAe-HLH3B-Jra-Snr1-ebi-grn-nej-pnr-sd-srp 4 0.206189 5041.94 1 6 CACCTG TTCTTATCTTT - +4 jaspar__MA0526.1-Mitf-SREBP-Usf-cnc-cyc-tgo 3 0.206189 5041.94 1 6 CACCTG GGTCACATGAC - +4 swissregulon__hs__TGIF1.p2-achi-vis -1 0.206189 5041.94 1 5 CACCTG AGCTGTCAGAA + +4 hocomoco__PO6F2_HUMAN.H11MO.0.D-pdm3 -1 0.206189 5041.94 1 5 CACCTG AGCTAATTAAC - +4 tfdimers__MD00321-Ing5 12 0.206525 5050.15 1 6 CACCTG TCCCTCCACCACTTCCTGTCCCC - +4 taipale_tf_pairs__TFAP2C_ONECUT2_NATYGATNNNNNNNNNGCCTNNGGSNN_CAP_repr-onecut-TfAP-2 1 0.206572 5051.31 1 6 CACCTG TCGCCTGAGGCAATGGAACGATCGATA - +4 hocomoco__FOXA3_HUMAN.H11MO.0.B-FoxK-FoxP-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-slp2 6 0.206576 5051.4 1 6 CACCTG CTTGTTTACTTTG + +4 hocomoco__ERG_HUMAN.H11MO.0.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-RpII215-Rpn5-aop-bs-pnt 4 0.206576 5051.4 1 6 CACCTG CCACTTCCTGCCC - +4 neph__UW.Motif.0173 6 0.206576 5051.4 1 6 CACCTG TGCCAGTCACTCA - +4 neph__UW.Motif.0309 2 0.206576 5051.4 1 6 CACCTG AGAGCCAGGGAGT - +4 neph__UW.Motif.0328 1 0.206576 5051.4 1 6 CACCTG GAACAGACTGTTC - +4 taipale_cyt_meth__ZBTB18_NWTCCAGATGTKN_eDBD_meth_repr 3 0.206576 5051.4 1 6 CACCTG GCACATCTGGAAT - +4 neph__UW.Motif.0523 -2 0.206576 5051.4 1 4 CACCTG CCCTGTGCCCTGC + +4 cisbp__M1669 1 0.207582 5076.01 1 6 CACCTG GTCCCGGGCTTT + +4 cisbp__M2786 1 0.207582 5076.01 1 6 CACCTG CCACCAAACCCT + +4 cisbp__M6275-sima-tgo 3 0.207582 5076.01 1 6 CACCTG GCGTACGTGCGG + +4 hocomoco__PAX6_HUMAN.H11MO.0.C-Poxm-ey-sv-toy 3 0.207582 5076.01 1 6 CACCTG TTCCGCTTGACT + +4 taipale_cyt_meth__DMRTC2_WWTTGNTACATN_eDBD-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.207582 5076.01 1 6 CACCTG AATTGATACATT + +4 taipale_cyt_meth__MBNL2_NYGCTTYGCTTN_FL_repr-mbl 1 0.207582 5076.01 1 6 CACCTG TCGCTTCGCTTC + +4 taipale_cyt_meth__TGIF2LX_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.207582 5076.01 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M00466-sima-tgo 2 0.207582 5076.01 1 6 CACCTG CGTACGTGCGGT + +4 transfac_pro__M07465 5 0.207582 5076.01 1 6 CACCTG CCCCACAGCTGG + +4 transfac_pro__M08869-Clk-cyc 4 0.207582 5076.01 1 6 CACCTG GGCTCACGTGGA + +4 transfac_pro__M08872 4 0.207582 5076.01 1 6 CACCTG TCGCCACGTGAG + +4 transfac_public__M00506 1 0.207582 5076.01 1 6 CACCTG CCACCAAACCCT + +4 cisbp__M2482 3 0.207582 5076.01 1 6 CACCTG TACCACGTGGGA - +4 neph__UW.Motif.0368 2 0.207582 5076.01 1 6 CACCTG TTTCCCACAGCC - +4 taipale_cyt_meth__CREB1_NRTGACGTCAYN_eDBD-Atf3-Atf6-CG7786-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.207582 5076.01 1 6 CACCTG CGTGACGTCACG - +4 taipale_cyt_meth__ELF5_NANNAGGAAGTN_eDBD_meth-Eip74EF 3 0.207582 5076.01 1 6 CACCTG TACTTCCTCGTT - +4 taipale_cyt_meth__FOXI1_NANGTAAACAAN_FL_repr-bin-CHES-1-like-croc-FoxK-FoxL1-foxo-FoxP-slp1-slp2 6 0.207582 5076.01 1 6 CACCTG ATTGTTTACATT - +4 transfac_pro__M01862-Atf-2-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-Xbp1 2 0.207582 5076.01 1 6 CACCTG ATGACGTCAGCG - +4 transfac_pro__M06461 5 0.207582 5076.01 1 6 CACCTG GCGGCAGCCTGA - +4 transfac_pro__M06474 6 0.207582 5076.01 1 6 CACCTG TCCGCCCACCAG - +4 transfac_pro__M06656 6 0.207582 5076.01 1 6 CACCTG TCCGCCCACCAG - +4 transfac_pro__M06479 -1 0.207582 5076.01 1 5 CACCTG TCCTCCGGATGA + +4 transfac_pro__M05615 7 0.207582 5076.01 1 5 CACCTG TATGCCACACCA - +4 transfac_pro__M05674-CG2120 7 0.207582 5076.01 1 5 CACCTG TATCTTTAACCG - +4 transfac_pro__M06116 7 0.207582 5076.01 1 5 CACCTG GCGGCTTCACCC - +4 transfac_pro__M06319 7 0.207582 5076.01 1 5 CACCTG GCGAATAAACCC - +4 transfac_pro__M06599 7 0.207582 5076.01 1 5 CACCTG TCTTCAGAACCC - +4 transfac_pro__M06694 7 0.207582 5076.01 1 5 CACCTG GCTGGCTGACCG - +4 taipale_cyt_meth__T_NTCACACNTANGTGTGAN_eDBD_meth_repr-byn-Doc1-Doc2-Doc3-H15-mid-org-1 4 0.20788 5083.29 1 6 CACCTG TTCACACCTAGGTGTGAA + +4 cisbp__M6140 11 0.20788 5083.29 1 6 CACCTG TTAACCAATATAACCAAT - +4 hocomoco__FLI1_HUMAN.H11MO.0.A-Ets96B-Ets97D-pnt 7 0.20788 5083.29 1 6 CACCTG TCCCTCCTTCCTTCCTCC - +4 transfac_pro__M06825 11 0.20788 5083.29 1 6 CACCTG GCGGTCTTCGTGAACTAC - +4 transfac_pro__M05636 8 0.209053 5111.98 1 6 CACCTG ATGAAGAAGACCGGTGGCT + +4 transfac_pro__M07737-gcm-gcm2 11 0.209096 5113.02 1 6 CACCTG CATGCGGGTACTACCCGCATG + +4 tfdimers__MD00081-ovo 10 0.209096 5113.02 1 6 CACCTG CCCCCCCCACTTCCTGCCCCC - +4 cisbp__M4665-GATAe-grn-pnr-srp 8 0.209123 5113.69 1 6 CACCTG CAGATAAGAATCTGT + +4 cisbp__M4545-Blimp-1 1 0.209123 5113.69 1 6 CACCTG TCACTTTCACTTTCT - +4 taipale__HNF4A_full_RRGTCCAAAGGTCAA-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.209123 5113.69 1 6 CACCTG TTGACCTTTGGACCC - +4 yetfasco__YJL127C_1880 4 0.209123 5113.69 1 6 CACCTG CGATCAGCAGATAGA - +4 dbcorrdb__ATF3__ENCSR000BJY_1__m1-cnc-CrebB-cwo-cyc-E2f1-E(z)-Max-Mitf-Myc-Sin3A-SREBP-tna-Usf 12 0.209434 5121.29 1 6 CACCTG GCGCGGGCGGGTCACGTGAC + +4 dbcorrdb__RFX5__ENCSR000EEA_1__m1-CG9727-Rfx 2 0.209434 5121.29 1 6 CACCTG TCTGCCTGGCAACAGCTGAC + +4 dbcorrdb__SIN3A__ENCSR000BLR_1__m1-Max-Myc-Sin3A 5 0.209434 5121.29 1 6 CACCTG GTCAGCACGTGGGACCGCGC + +4 hocomoco__ZN322_MOUSE.H11MO.0.B 1 0.209434 5121.29 1 6 CACCTG GAGCCTGGTACAGAGCCTGG + +4 homer__NNNNNBAGATAWYATCTVHN_GATA-GATAe-grn-pnr 12 0.209434 5121.29 1 6 CACCTG AAGAACAGATATTATCTGAT + +4 taipale_cyt_meth__NR1D1_NAWNTRGGTCANTRGGTCAN_eDBD-eg-Eip75B-Hr3-kni-knrl 10 0.209434 5121.29 1 6 CACCTG CTGACCTACTGACCCACATC - +4 taipale_cyt_meth__NR1D1_NAWNTRGGTCANTRGGTCAN_eDBD_meth-eg-Eip75B-Hr3-kni-knrl 10 0.209434 5121.29 1 6 CACCTG CTGACCTACTGACCCACATC - +4 transfac_pro__M04744-CrebB-Max-Usf 1 0.209434 5121.29 1 6 CACCTG TCACGTCACCGCCGCGCGCC - +4 tfdimers__MD00600-EcR-usp 9 0.210054 5136.45 1 6 CACCTG CTCCAAGGCCATCTGTCACTGAGACT - +4 cisbp__M1729 0 0.211273 5166.26 1 6 CACCTG CTCCGAGG + +4 cisbp__M5493 1 0.211273 5166.26 1 6 CACCTG GTACGTAA + +4 cisbp__M6386-EcR 2 0.211273 5166.26 1 6 CACCTG GTGAACTT + +4 jaspar__MA0935.1 0 0.211273 5166.26 1 6 CACCTG TACGTAAC + +4 jaspar__MA0986.1 0 0.211273 5166.26 1 6 CACCTG CACCGACA + +4 predrem__nrMotif491 2 0.211273 5166.26 1 6 CACCTG TCCATCTT + +4 taipale__GMEB2_DBD_TTACGYAM 1 0.211273 5166.26 1 6 CACCTG TTACGTAC + +4 transfac_pro__M01759-lz-run-RunxA-RunxB 0 0.211273 5166.26 1 6 CACCTG AACCACAA + +4 cisbp__M0355-CrebB-Jra-kay-REPTOR-BP 0 0.211273 5166.26 1 6 CACCTG TACGTCAT - +4 cisbp__M0638-dmrt93B-dsx 2 0.211273 5166.26 1 6 CACCTG GATACATT - +4 cisbp__M0778 2 0.211273 5166.26 1 6 CACCTG GAGATCTA - +4 predrem__nrMotif1706 2 0.211273 5166.26 1 6 CACCTG GCAACATG - +4 transfac_pro__M00951-grh 1 0.211273 5166.26 1 6 CACCTG AAACCAGT - +4 yetfasco__YOL116W_1378 2 0.211273 5166.26 1 6 CACCTG AGGACATT - +4 cisbp__M0578 3 0.211273 5166.26 1 5 CACCTG CGTCACAC + +4 predrem__nrMotif2625 -1 0.211273 5166.26 1 5 CACCTG GCCTAGCC - +4 cisbp__M5192-Six4 4 0.211273 5166.26 1 4 CACCTG ATGATACC + +4 flyfactorsurvey__Six4_SOLEXA_2_FBgn0027364-Six4 4 0.211273 5166.26 1 4 CACCTG ATGATACC + +4 predrem__nrMotif1172 -2 0.211273 5166.26 1 4 CACCTG CCTCATGG - +4 cisbp__M0200-Atf6-Clk-CrebA-Hey-Max-Met-Myc 2 0.211934 5182.43 1 6 CACCTG GCCACGTGGC + +4 cisbp__M1331 3 0.211934 5182.43 1 6 CACCTG GCGAATCTTT + +4 cisbp__M1410 1 0.211934 5182.43 1 6 CACCTG ACACGCAACC + +4 cisbp__M1456 4 0.211934 5182.43 1 6 CACCTG TATGTTCCTA + +4 cisbp__M1570 4 0.211934 5182.43 1 6 CACCTG TCCGTACGGT + +4 cisbp__M1812 2 0.211934 5182.43 1 6 CACCTG ATCTCCGATA + +4 cisbp__M1818 3 0.211934 5182.43 1 6 CACCTG AATCTCCGAA + +4 cisbp__M1822 4 0.211934 5182.43 1 6 CACCTG TTATTTCCGC + +4 fantom__motif115_CATCAACTAC 3 0.211934 5182.43 1 6 CACCTG CATCAACTAC + +4 flyfactorsurvey__tgo_sim_SANGER_5_FBgn0004666-sim-tgo 1 0.211934 5182.43 1 6 CACCTG GTACGTGACC + +4 jaspar__MA0949.1 3 0.211934 5182.43 1 6 CACCTG GCGAATCTTT + +4 predrem__nrMotif1595 1 0.211934 5182.43 1 6 CACCTG CAACCTCTTC + +4 predrem__nrMotif1980 1 0.211934 5182.43 1 6 CACCTG GGACCTCAGA + +4 predrem__nrMotif2399 0 0.211934 5182.43 1 6 CACCTG TGCCTGTTCT + +4 taipale__TEAD1_full_NRMATWCCWN_repr-sd 0 0.211934 5182.43 1 6 CACCTG CACATTCCAT + +4 taipale_cyt_meth__ASCL2_NRCAGCTGYN_eDBD_meth-ac-ase-dimm-l(1)sc-nau-sc 2 0.211934 5182.43 1 6 CACCTG AGCAGCTGCT + +4 taipale_cyt_meth__HES5_GGCACGTGYY_eDBD_meth-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 2 0.211934 5182.43 1 6 CACCTG GGCACGTGTC + +4 taipale_cyt_meth__NKX3-2_NCCACTTAAN_eDBD_meth-bap-Hmx 2 0.211934 5182.43 1 6 CACCTG ACCACTTAAC + +4 cisbp__M0653 1 0.211934 5182.43 1 6 CACCTG TCACTTTTTT - +4 cisbp__M0689-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 2 0.211934 5182.43 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1302 2 0.211934 5182.43 1 6 CACCTG CTTATCCATT - +4 cisbp__M1526-CG9727-Rfx 2 0.211934 5182.43 1 6 CACCTG GTTGCCAGGG - +4 cisbp__M4532-E2f1-Max-Myc-tgo-Usf 3 0.211934 5182.43 1 6 CACCTG GAGCACGTGG - +4 cisbp__M6005-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.211934 5182.43 1 6 CACCTG TACTTCCGGT - +4 hocomoco__MAX_HUMAN.H11MO.0.A-E2f1-Max-Myc 1 0.211934 5182.43 1 6 CACCTG CCACGTGCTC - +4 homer__AACAGGAAGT_Ets1-distal-bs-Dif-dl-Ets96B-Ets97D-pnt 2 0.211934 5182.43 1 6 CACCTG ACTTCCTGTT - +4 jaspar__MA0973.1 1 0.211934 5182.43 1 6 CACCTG TCACTTTTTT - +4 predrem__nrMotif998 0 0.211934 5182.43 1 6 CACCTG GACCCGGCCC - +4 taipale__ELK1_full_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.211934 5182.43 1 6 CACCTG TACTTCCGGT - +4 taipale__ETV3_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.211934 5182.43 1 6 CACCTG CACTTCCGGT - +4 taipale_cyt_meth__ASCL2_NRCAGCTGYN_FL_meth-ac-ase-dimm-l(1)sc-nau-sc 2 0.211934 5182.43 1 6 CACCTG AGCAGCTGCT - +4 transfac_pro__M05529 1 0.211934 5182.43 1 6 CACCTG GCTCCTTCTG - +4 predrem__nrMotif1094 5 0.211934 5182.43 1 5 CACCTG TTTGTCACCA + +4 transfac_pro__M07716-fd102C 5 0.211934 5182.43 1 5 CACCTG CGAAGGACCG - +4 elemento__ACACGTG 1 0.212419 5194.29 1 6 CACCTG ACACGTG + +4 elemento__CACATGC 0 0.212419 5194.29 1 6 CACCTG CACATGC + +4 elemento__CACGTGA-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 0 0.212419 5194.29 1 6 CACCTG CACGTGA + +4 elemento__CACGTGC-E(spl)m3-HLH 0 0.212419 5194.29 1 6 CACCTG CACGTGC + +4 elemento__CACGTGG-Max-Myc 0 0.212419 5194.29 1 6 CACCTG CACGTGG + +4 elemento__CACTTGA 0 0.212419 5194.29 1 6 CACCTG CACTTGA + +4 transfac_pro__M01709 1 0.212419 5194.29 1 6 CACCTG TCAGCAG + +4 c2h2_zfs__M3425 1 0.212419 5194.29 1 6 CACCTG GGACCCT - +4 elemento__CATGTGC 1 0.212419 5194.29 1 6 CACCTG GCACATG - +4 hdpi__MXD4 1 0.212419 5194.29 1 6 CACCTG AAACCGG - +4 elemento__AGCTCCT 2 0.212419 5194.29 1 5 CACCTG AGCTCCT + +4 predrem__nrMotif1509 2 0.212419 5194.29 1 5 CACCTG CCAAGCT + +4 transfac_pro__M09176 2 0.212419 5194.29 1 5 CACCTG ATCACCA + +4 elemento__AGGAGCG 2 0.212419 5194.29 1 5 CACCTG CGCTCCT - +4 elemento__AGGAGGA 2 0.212419 5194.29 1 5 CACCTG TCCTCCT - +4 elemento__AGGCGCG 2 0.212419 5194.29 1 5 CACCTG CGCGCCT - +4 elemento__AGGGGAG 2 0.212419 5194.29 1 5 CACCTG CTCCCCT - +4 elemento__AGGGGCG 2 0.212419 5194.29 1 5 CACCTG CGCCCCT - +4 elemento__AGGGGGC-CTCF 2 0.212419 5194.29 1 5 CACCTG GCCCCCT - +4 transfac_pro__M02278-Ets97D 2 0.212419 5194.29 1 5 CACCTG ACTTCCT - +4 elemento__CCTCCAG -2 0.212419 5194.29 1 4 CACCTG CCTCCAG + +4 elemento__CCTCCGC -2 0.212419 5194.29 1 4 CACCTG CCTCCGC + +4 elemento__CCTCGCC -2 0.212419 5194.29 1 4 CACCTG CCTCGCC + +4 elemento__CCTCGCG -2 0.212419 5194.29 1 4 CACCTG CCTCGCG + +4 elemento__AAGGAGG -2 0.212419 5194.29 1 4 CACCTG CCTCCTT - +4 elemento__CACGAGG -2 0.212419 5194.29 1 4 CACCTG CCTCGTG - +4 elemento__CAGGAGG -2 0.212419 5194.29 1 4 CACCTG CCTCCTG - +4 transfac_pro__M01457 7 0.213475 5220.09 1 6 CACCTG CTTTAAGTACTTAATG + +4 taipale_tf_pairs__ETV2_SREBF2_RTMRCGTGACGGAWGN_CAP_repr-pnt-SREBP 8 0.213475 5220.09 1 6 CACCTG ACTTCCGTCACGTCAT - +4 neph__UW.Motif.0551 11 0.213475 5220.09 1 5 CACCTG CCTGGAGAGAATTGCT - +4 transfac_pro__M06942 -1 0.213475 5220.09 1 5 CACCTG TCCTTTTTTATTAAAA - +4 neph__UW.Motif.0092 0 0.213954 5231.81 1 6 CACCTG CTCCTGGCCTCCAG + +4 transfac_pro__M03788-EcR-usp 7 0.213954 5231.81 1 6 CACCTG CTTTTGTGAACTCT + +4 transfac_public__M00194-CG12018-Dif-dl-Rel 8 0.213954 5231.81 1 6 CACCTG TGGGGAATTTCCTC + +4 transfac_public__M00474-foxo-FoxP 8 0.213954 5231.81 1 6 CACCTG GTGTTGTTTACATT + +4 hocomoco__ELF3_HUMAN.H11MO.0.A-Eip74EF-Ets96B-aop-pnt 4 0.213954 5231.81 1 6 CACCTG CCACTTCCTGGTTC - +4 neph__UW.Motif.0246 7 0.213954 5231.81 1 6 CACCTG CTGCCGCCTCCCTG - +4 neph__UW.Motif.0448 8 0.213954 5231.81 1 6 CACCTG CAGAGAGATTTCTT - +4 taipale_cyt_meth__ETV4_NCAGGAAGGAAGTN_eDBD_meth_repr-Ets96B 7 0.213954 5231.81 1 6 CACCTG CACTTCCTTCCTGT - +4 cisbp__M1093-Optix-so 3 0.214003 5233.02 1 6 CACCTG TGATACCCC + +4 cisbp__M1571 3 0.214003 5233.02 1 6 CACCTG GGGTACGGC + +4 cisbp__M1799 2 0.214003 5233.02 1 6 CACCTG TTTCCCGAT + +4 hdpi__ZNF323 2 0.214003 5233.02 1 6 CACCTG CGGACATGA + +4 jaspar__MA0423.1-CG10348-CG13296-ham 1 0.214003 5233.02 1 6 CACCTG ACCCCTATT + +4 predrem__nrMotif332 3 0.214003 5233.02 1 6 CACCTG ATTGTCCTT + +4 predrem__nrMotif98 1 0.214003 5233.02 1 6 CACCTG ACATCTGGA + +4 taipale__NKX3-2_DBD_NCCACTTAA-bap-scro-vnd 2 0.214003 5233.02 1 6 CACCTG ACCACTTAA + +4 cisbp__M1554 1 0.214003 5233.02 1 6 CACCTG TGACGTACG - +4 cisbp__M2228-CG10348-CG13296-ham 1 0.214003 5233.02 1 6 CACCTG ACCCCTATT - +4 cisbp__M6220-aop-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.214003 5233.02 1 6 CACCTG ACTTCCTGT - +4 jaspar__MA1017.1 3 0.214003 5233.02 1 6 CACCTG CTAGATCTG - +4 yetfasco__YER130C_534-CG10348-CG13296-ham 1 0.214003 5233.02 1 6 CACCTG ACCCCTATT - +4 cisbp__M5157-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.214003 5233.02 1 5 CACCTG ACCGGAAAT + +4 flyfactorsurvey__pnt_SANGER_5_FBgn0003118-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-pnt -1 0.214003 5233.02 1 5 CACCTG ACCGGAAGT + +4 predrem__nrMotif2056 -1 0.214003 5233.02 1 5 CACCTG AACTGTTCT + +4 predrem__nrMotif730 -1 0.214003 5233.02 1 5 CACCTG AGCTGCTTT + +4 predrem__nrMotif2077 4 0.214003 5233.02 1 5 CACCTG CTGAGACCC - +4 predrem__nrMotif663 -2 0.214003 5233.02 1 4 CACCTG CCTGTTTGA - +4 cisbp__M1152 1 0.216394 5291.47 1 6 CACCTG AAACATGTACA + +4 cisbp__M1968-kn 0 0.216394 5291.47 1 6 CACCTG TCCCTGGGGAC + +4 cisbp__M5421-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.216394 5291.47 1 6 CACCTG AACCGGAAATA + +4 hocomoco__MYOD1_HUMAN.H11MO.1.A-ac-ase-l(1)sc-nau-sc 3 0.216394 5291.47 1 6 CACCTG CTGCAGCTGTC + +4 predrem__nrMotif2519 4 0.216394 5291.47 1 6 CACCTG CACCCATCTCC + +4 swissregulon__hs__SPZ1.p2 5 0.216394 5291.47 1 6 CACCTG GCTGTTACCCT - +4 taipale_cyt_meth__ELK1_NACCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.216394 5291.47 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__ETV1_NACMGKAWGTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.216394 5291.47 1 6 CACCTG TACTTCCGGTC - +4 taipale_cyt_meth__MLX_NNCAYGTGMYN_FL_meth_repr-bigmax-Mitf 3 0.216394 5291.47 1 6 CACCTG GATCACGTGGA - +4 taipale_tf_pairs__TEAD4_EOMES_RGAATGYGTGA_CAP_repr-sd 3 0.216394 5291.47 1 6 CACCTG TCACACATTCC - +4 transfac_pro__M07207-kn 0 0.216394 5291.47 1 6 CACCTG TCCCTGGGGAC - +4 cisbp__M6526-C15-NfI 4 0.216699 5298.93 1 6 CACCTG CTGGCAACTTGCCAAGG + +4 taipale_tf_pairs__CUX1_HOXA13_ATCRATNNNNYCRTAAA_CAP_repr-ct 6 0.216699 5298.93 1 6 CACCTG ATCGATTACCTCATAAA + +4 transfac_pro__M01448-ap-Awh-C15-CG18599-CG9876-E5-ems-en-eve-inv-lab-Lim3-OdsH-otp-pb-ro-unpg-zfh2 9 0.216699 5298.93 1 6 CACCTG TAAACTAATTAGCTGTA + +4 jaspar__MA0631.1-Optix-so 8 0.216699 5298.93 1 6 CACCTG ATTAGTGATACCCTATC - +4 taipale_cyt_meth__NR6A1_NTCAAGKTCAAGKTCAN_eDBD_meth-EcR-ERR-Hr4 2 0.216699 5298.93 1 6 CACCTG TTGACCTTGAACTTGAC - +4 transfac_pro__M01358-Optix-so 8 0.216699 5298.93 1 6 CACCTG ATAAGTGATACCCTATC - +4 transfac_pro__M01433-Optix-so 8 0.216699 5298.93 1 6 CACCTG AAACGTGATACCCCATT - +4 transfac_pro__M08837 12 0.216699 5298.93 1 5 CACCTG TTGCGTGTGCCACACGT - +4 transfac_pro__M05369 13 0.216699 5298.93 1 4 CACCTG AGTTATTAGCTTAAACC + +4 taipale_tf_pairs__MYBL1_EOMES_RSGTGNNNAACGK_CAP_repr-Myb 7 0.216988 5306.01 1 6 CACCTG AGGTGTCTAACGG + +4 hocomoco__AP2C_MOUSE.H11MO.0.A-TfAP-2 1 0.216988 5306.01 1 6 CACCTG TGGCCTGAGGCCA - +4 hocomoco__FLI1_HUMAN.H11MO.1.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-RpII215-Rpn5-aop-bs-pnt 4 0.216988 5306.01 1 6 CACCTG CCACTTCCTGCCT - +4 neph__UW.Motif.0105 4 0.216988 5306.01 1 6 CACCTG TGATTTTCTTGGC - +4 transfac_pro__M01865 4 0.216988 5306.01 1 6 CACCTG ACTCCTCCCTCAC - +4 transfac_pro__M07265-cnc-ewg-Jra-kay-maf-S-mor 0 0.216988 5306.01 1 6 CACCTG CTGCTGAGTCACG - +4 neph__UW.Motif.0281 -2 0.216988 5306.01 1 4 CACCTG CCATCTGTTCTTT - +4 tfdimers__MD00500-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 6 0.21723 5311.93 1 6 CACCTG TAGTTCCACCTGCCCAGGCATGCCTACTCT + +4 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 13 0.217881 5327.85 1 6 CACCTG GGCACGTGCCCATGGCCTCAGGC + +4 transfac_pro__M02892-Rfx 5 0.217881 5327.85 1 6 CACCTG ACTGACGCTTGGTTACCACAAAG + +4 tfdimers__MD00119-ac-ase-CrebB-l(1)sc-nau-sc 10 0.217881 5327.85 1 6 CACCTG TGACACTGACCATCTGCCCAATC - +4 cisbp__M0272-Atf6-CrebA-Xbp1 4 0.217925 5328.91 1 6 CACCTG TGCTGACGTGGC + +4 cisbp__M5933-achi-hth-nau-vis 3 0.217925 5328.91 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__CREB3L1_TGCCACRTCAYN_eDBD_meth-Atf6-CrebA-Xbp1 3 0.217925 5328.91 1 6 CACCTG TGCCACGTCACC + +4 taipale_cyt_meth__PKNOX1_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.217925 5328.91 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__PTF1A_NYGTCAGCTGNY_eDBD_meth_repr-Fer1-nau 4 0.217925 5328.91 1 6 CACCTG GCGTCAGCTGTT + +4 cisbp__M0359-Atf6-CrebA-Xbp1 3 0.217925 5328.91 1 6 CACCTG TGCCACGTCAGC - +4 flyfactorsurvey__tin_FlyReg_FBgn0004110-tin 3 0.217925 5328.91 1 6 CACCTG GGCCACTTGAGA - +4 homer__ACATCAAAGGGA_Tcf4-pan 0 0.217925 5328.91 1 6 CACCTG TCCCTTTGATGT - +4 taipale__TGIF1_DBD_TGACAGSTGTCA-achi-hth-nau-vis 3 0.217925 5328.91 1 6 CACCTG TGACAGCTGTCA - +4 taipale_cyt_meth__ATF2_NRTGAYGTMAYN_FL-Atf3-Atf6-CG7786-cnc-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-vri-Xbp1 3 0.217925 5328.91 1 6 CACCTG CGTTACGTCACG - +4 taipale_cyt_meth__ELF4_NATGCGGAAGTN_eDBD-Eip74EF 0 0.217925 5328.91 1 6 CACCTG CACTTCCGCATC - +4 taipale_cyt_meth__MSC_NRACAGCTGTYN_eDBD-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.217925 5328.91 1 6 CACCTG TAACAGCTGTTG - +4 taipale_cyt_meth__TGIF2LY_TGACANNTGTCA_eDBD_meth_repr-achi-hth-nau-vis 3 0.217925 5328.91 1 6 CACCTG TGACAGCTGTCA - +4 transfac_pro__M06224 6 0.217925 5328.91 1 6 CACCTG TCGTTTCACCCA - +4 transfac_pro__M05604 -1 0.217925 5328.91 1 5 CACCTG CCCTCGTGGTTT + +4 transfac_pro__M05912 7 0.217925 5328.91 1 5 CACCTG TCTTTAGCACCC - +4 transfac_pro__M06271-CG2120 7 0.217925 5328.91 1 5 CACCTG TCTTACCGACCA - +4 transfac_pro__M06278 7 0.217925 5328.91 1 5 CACCTG TGTATCGGACCG - +4 transfac_pro__M05984 -2 0.217925 5328.91 1 4 CACCTG CCTTATCATGCG - +4 tfdimers__MD00536-eg-kn-kni-knrl 17 0.218207 5335.81 1 6 CACCTG CACTGCAGGTCCCCAGGGACCCCGTGG - +4 transfac_pro__M00647-EcR-svp-usp 6 0.218908 5352.96 1 6 CACCTG TGGGGTCACTGGCGGTCA + +4 transfac_pro__M06820 7 0.218908 5352.96 1 6 CACCTG TCGGCATTACCTAAACTC - +4 cisbp__M6103 -1 0.218908 5352.96 1 5 CACCTG ACATGTCCATGGACATGT + +4 taipale__Tp53_DBD_ACAWGTCNNNNRACAWGT_repr -1 0.218908 5352.96 1 5 CACCTG ACATGTCCATGGACATGT - +4 tfdimers__MD00313-Ing5-NFAT 12 0.219448 5366.17 1 6 CACCTG AACACAGGAAACCACCATAAGA - +4 transfac_pro__M02859-GATAe-grn-pnr 11 0.219448 5366.17 1 6 CACCTG TAAGTCGATAAAATCTACAAAA - +4 transfac_pro__M04863 15 0.219448 5366.17 1 6 CACCTG CTCCTCCAGGAAGCCCTCCGGG - +4 cisbp__M1838-GATAe-grn-pnr-TfAP-2 3 0.219886 5376.87 1 6 CACCTG CATTGCCTCAGGGCA + +4 cisbp__M5529-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 2 0.219886 5376.87 1 6 CACCTG TTGACCTTTGGACCC + +4 factorbook__PRDM1-Blimp-1 1 0.219886 5376.87 1 6 CACCTG TCACTTTCACTTTCT + +4 taipale__GMEB2_DBD_YACGTAACNKACGTA_repr 0 0.219886 5376.87 1 6 CACCTG TACGTAACTGACGTA + +4 cisbp__M5749-Blimp-1 1 0.219886 5376.87 1 6 CACCTG TCACTTTCACTTTCT - +4 hocomoco__NR1H3_MOUSE.H11MO.0.A-ERR-EcR-HDAC1-Hnf4-Hr38-Hr51-Hr78-Nup133-Spps-btd-eg-kni-knrl-nej-svp-usp 2 0.219886 5376.87 1 6 CACCTG CTGACCTTTGACCTC - +4 neph__UW.Motif.0511 7 0.219886 5376.87 1 6 CACCTG TGAAATTTTTCTTTG - +4 neph__UW.Motif.0539 4 0.219886 5376.87 1 6 CACCTG CAGTTTCTTTCCTTT - +4 taipale__PRDM1_full_NRAAAGTGAAAGTGN_repr-Blimp-1 1 0.219886 5376.87 1 6 CACCTG TCACTTTCACTTTCT - +4 transfac_pro__M00339-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 8 0.219886 5376.87 1 6 CACCTG GCAATCACTTCCTGC - +4 transfac_pro__M08984-CG4730-CG7101 6 0.219886 5376.87 1 6 CACCTG GTATTATACCCAGCT - +4 transfac_pro__M05872 11 0.219886 5376.87 1 4 CACCTG CACCCCTCGGTCACC - +4 cisbp__M4477-bs 1 0.220205 5384.66 1 6 CACCTG TTGCCTTATATGGCCATAG - +4 predrem__nrMotif2527-Brf-CTCF-Clp-CoRest-HDAC1-Nelf-E-Rbbp5-SREBP-Spps-Spt20-brm-btd-cbt-crol-ct-l(3)neo38-peb 12 0.220205 5384.66 1 6 CACCTG CCCCCCCCACCCCACCCCC - +4 transfac_pro__M01028-btd-CTCF-HDAC1-Sin3A-Spps 4 0.220205 5384.66 1 6 CACCTG TCAGCACCACGGACAGCGC - +4 transfac_pro__M09085 1 0.220205 5384.66 1 6 CACCTG TTTCCTCGGGATCCGTGCC - +4 transfac_pro__M09274 12 0.220401 5389.47 1 6 CACCTG CTCCAAAATCTCCACCAACCA + +4 taipale_tf_pairs__FOXO1_ETV7_RWMAACAGGNNNNNNTTCCNN_CAP_repr-aop-foxo 10 0.220401 5389.47 1 6 CACCTG GCGGAAGTGTTTCCTGTTGAC - +4 taipale_tf_pairs__SOX6_TBX21_RGGTGTNNNNNNNNNYATTGT_CAP_repr-Sox102F 16 0.220401 5389.47 1 5 CACCTG ACAATGGAAAAAGTAACACCT - +4 dbcorrdb__CHD1__ENCSR000DZE_1__m1-Chd1-Jra-nej 9 0.220676 5396.2 1 6 CACCTG GGCGGGCGGAACCACTTCGG + +4 dbcorrdb__EP300__ENCSR000BMA_1__m4-nej 4 0.220676 5396.2 1 6 CACCTG TGGCCAGCTGACAAATCTAA + +4 dbcorrdb__GATA3__ENCSR000BMX_1__m2-GATAe-grn-pnr-srp 6 0.220676 5396.2 1 6 CACCTG GGATCTTATCTGCTTCTTCA + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m4-RpII215 3 0.220676 5396.2 1 6 CACCTG TTCCACCAGAGCTACTCAGC + +4 dbcorrdb__RXRA__ENCSR000BJW_1__m1-EcR-usp 10 0.220676 5396.2 1 6 CACCTG ACCCCCCCGTGACCTCTGCC + +4 dbcorrdb__TBP__ENCSR000EHA_1__m5-Tbp 5 0.220676 5396.2 1 6 CACCTG GGCGACAATTGTAACGCTAA + +4 transfac_pro__M03810-EcR-usp 14 0.220676 5396.2 1 6 CACCTG AATTGAACTTTCATGACCTC + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m4-E(z) 9 0.220676 5396.2 1 6 CACCTG GGCTGCCTCTCCCTGTGCCA - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m3-Snr1 5 0.220676 5396.2 1 6 CACCTG CCACAGAGCTGACTAATGCT - +4 dbcorrdb__TAF7__ENCSR000BNM_1__m1-Taf7 4 0.220676 5396.2 1 6 CACCTG GATATAGTTGGTTGCAGTGG - +4 dbcorrdb__TFAP2A__ENCSR000EVP_1__m1-TfAP-2 5 0.220676 5396.2 1 6 CACCTG CCCATGCCCTGAGGCCATGG - +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m9-bon 0 0.220676 5396.2 1 6 CACCTG CGCCTGCAGTCAGAGCTCAG - +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m2 4 0.220676 5396.2 1 6 CACCTG GTGTTCTCTGATTTAAATTA - +4 swissregulon__hs__CTCF.p2-CTCF-SMC3-usp-vtd 6 0.220676 5396.2 1 6 CACCTG TAGTGCCCCCTGGTGGCCAA - +4 taipale_tf_pairs__TFAP4_DLX3_NCAGSTGNNNNNNGTAATKR_CAP_repr-crp 13 0.220676 5396.2 1 6 CACCTG CAATTACGCCCCTCAGCTGA - +4 yetfasco__MATA1-MATALPHA2-dimer_1436 13 0.220676 5396.2 1 6 CACCTG TGATGTAAATTTTTACATGA - +4 transfac_pro__M06536 15 0.220676 5396.2 1 5 CACCTG AGGGCGATACCATTATACCA - +4 dbcorrdb__CTCF__ENCSR000DLD_1__m2-CTCF -2 0.220676 5396.2 1 4 CACCTG CCTGGTGGCCACAGGGGGCA - +4 cisbp__M1400 0 0.221536 5417.21 1 6 CACCTG TACGTAAC + +4 jaspar__MA0281.1-Sirt6-cyc-tgo 1 0.221536 5417.21 1 6 CACCTG GCACGTGA + +4 jaspar__MA0561.1-Clk-E2f1-Max-Myc-cyc 0 0.221536 5417.21 1 6 CACCTG CACGTGGC + +4 transfac_pro__M01911-cyc-Sirt6-tgo 1 0.221536 5417.21 1 6 CACCTG GCACGTGA + +4 transfac_pro__M08800-tgo 0 0.221536 5417.21 1 6 CACCTG TACGTGCC + +4 cisbp__M0478 0 0.221536 5417.21 1 6 CACCTG CCCCCACG - +4 cisbp__M0802-GATAd-GATAe-grn-pnr-srp 2 0.221536 5417.21 1 6 CACCTG CTTATCAG - +4 cisbp__M2354-Clk-E2f1-Max-Myc-cyc 0 0.221536 5417.21 1 6 CACCTG CACGTGGC - +4 cisbp__M4680-Clk-cnc-cyc-Max-Mitf-SREBP-tgo-Usf 0 0.221536 5417.21 1 6 CACCTG CACGTGAC - +4 predrem__nrMotif1091 2 0.221536 5417.21 1 6 CACCTG AATAACTG - +4 predrem__nrMotif1689 1 0.221536 5417.21 1 6 CACCTG ATAGCTTT - +4 jaspar__MA0972.1 3 0.221536 5417.21 1 5 CACCTG AAATATCT + +4 predrem__nrMotif1691 3 0.221536 5417.21 1 5 CACCTG CCTTAGCT + +4 yetfasco__YNL167C_1401 3 0.221536 5417.21 1 5 CACCTG AATGACGT + +4 yetfasco__YPR199C_603 -1 0.221536 5417.21 1 5 CACCTG ATTTGAAT + +4 predrem__nrMotif1394 3 0.221536 5417.21 1 5 CACCTG AACCACTT - +4 hdpi__EIF5A2 -2 0.221536 5417.21 1 4 CACCTG CCTGTGAC - +4 predrem__nrMotif222 5 0.221536 5417.21 1 3 CACCTG ACAGTCAC - +4 tfdimers__MD00275-nub-pdm2-TfAP-2 10 0.221757 5422.61 1 6 CACCTG TTTTTTAATTTGCCTGAGGCTATTTT + +4 tfdimers__MD00333-Pur-alpha-TfAP-2 4 0.221757 5422.61 1 6 CACCTG CCCCCCCCTGCCCCCAGGCAGGGGGC - +4 transfac_pro__M00999 13 0.221757 5422.61 1 6 CACCTG ATTTAACCATTATAACCAATTAATAA - +4 cisbp__M0167-Clk-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 2 0.222289 5435.64 1 6 CACCTG GGCACGTGCC + +4 cisbp__M0309-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-vri-Xbp1 3 0.222289 5435.64 1 6 CACCTG GATGACGTCA + +4 cisbp__M1059-bap-scro-tin-vnd 2 0.222289 5435.64 1 6 CACCTG AGCACTTAAG + +4 cisbp__M1321 4 0.222289 5435.64 1 6 CACCTG ATAGAATCTT + +4 cisbp__M1739 3 0.222289 5435.64 1 6 CACCTG TTGTTCCGAT + +4 cisbp__M5634-Max-Mnt-Myc 2 0.222289 5435.64 1 6 CACCTG ACCACGTGCC + +4 cisbp__M5987-ac-ase-dimm-l(1)sc-nau-sc 2 0.222289 5435.64 1 6 CACCTG AGCAGCTGCT + +4 predrem__nrMotif746 4 0.222289 5435.64 1 6 CACCTG CTGCACCCTG + +4 scertf__macisaac.MET32 0 0.222289 5435.64 1 6 CACCTG AAACTGTGGC + +4 taipale__Ascl2_DBD_RRCAGCTGYY_repr-ac-ase-dimm-l(1)sc-nau-sc 2 0.222289 5435.64 1 6 CACCTG AGCAGCTGCT + +4 taipale__SREBF2_DBD_RTCACGTGAY-bigmax-cnc-cwo-Mitf-Mondo-SREBP-tgo-Usf 2 0.222289 5435.64 1 6 CACCTG ATCACGTGAC + +4 transfac_pro__M07281-CG42741-dar1 4 0.222289 5435.64 1 6 CACCTG GCCACACCCT + +4 yetfasco__YML081W_2194-klu-sr 1 0.222289 5435.64 1 6 CACCTG TACCCCGCAC + +4 cisbp__M0461-ci-lmd-opa 4 0.222289 5435.64 1 6 CACCTG AGACCACCCA - +4 cisbp__M0532-klu-sr 1 0.222289 5435.64 1 6 CACCTG TACCCCGCAC - +4 cisbp__M0701-aop-Eip74EF-Ets21C-Ets98B 2 0.222289 5435.64 1 6 CACCTG ACATCCGGGT - +4 cisbp__M0787-CoRest-CycT-GATAd-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.222289 5435.64 1 6 CACCTG CCTTATCGGT - +4 cisbp__M1363 4 0.222289 5435.64 1 6 CACCTG GGGGAATCTA - +4 cisbp__M5381-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.222289 5435.64 1 6 CACCTG TACTTCCGGT - +4 fantom__motif165_AAAGTTACTG 3 0.222289 5435.64 1 6 CACCTG CAGTAACTTT - +4 homer__AAAGTAAACA_FOXA1_GSE27824-FoxK-FoxL1-FoxP-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.222289 5435.64 1 6 CACCTG TGTTTACTTA - +4 jaspar__MA0995.1 1 0.222289 5435.64 1 6 CACCTG CCACCGACAC - +4 predrem__nrMotif131 4 0.222289 5435.64 1 6 CACCTG GGAGGCCCTG - +4 predrem__nrMotif1915 0 0.222289 5435.64 1 6 CACCTG CATCTCCTGG - +4 taipale_cyt_meth__GRHL1_NAACCGGTTN_eDBD-gem-grh 1 0.222289 5435.64 1 6 CACCTG AAACCGGTTT - +4 transfac_pro__M05500-TfIIA-L 0 0.222289 5435.64 1 6 CACCTG CTCCAAGTAC - +4 transfac_pro__M05622 4 0.222289 5435.64 1 6 CACCTG TCCGCACCTC - +4 transfac_pro__M09013-ttk 2 0.222289 5435.64 1 6 CACCTG GTATCCTTGA - +4 yetfasco__YBR239C_2188 2 0.222289 5435.64 1 6 CACCTG TGTTCCGATG - +4 cisbp__M1284 5 0.222289 5435.64 1 5 CACCTG ATATTTACCG + +4 predrem__nrMotif648 5 0.222289 5435.64 1 5 CACCTG TGTCACTCCT - +4 jaspar__MA0324.1 -2 0.222289 5435.64 1 4 CACCTG CCGTTACCGG + +4 transfac_pro__M01629 -2 0.222289 5435.64 1 4 CACCTG CCGTTACCGG + +4 cisbp__M0603 1 0.222828 5448.82 1 6 CACCTG TTAGCGG + +4 cisbp__M1820 1 0.222828 5448.82 1 6 CACCTG TTTCCGT + +4 elemento__CAGCTGC-HLH4C 0 0.222828 5448.82 1 6 CACCTG CAGCTGC + +4 elemento__CAGCTGG 0 0.222828 5448.82 1 6 CACCTG CAGCTGG + +4 flyfactorsurvey__Max_Mnt_SANGER_5_FBgn0017578-Atf6-CrebA-Max-Myc 1 0.222828 5448.82 1 6 CACCTG CCACGTG + +4 predrem__nrMotif1529 1 0.222828 5448.82 1 6 CACCTG TCTCCTA + +4 elemento__CAGGAGC 1 0.222828 5448.82 1 6 CACCTG GCTCCTG - +4 elemento__CAGGCGC 1 0.222828 5448.82 1 6 CACCTG GCGCCTG - +4 elemento__CCAGGGG 0 0.222828 5448.82 1 6 CACCTG CCCCTGG - +4 predrem__nrMotif1979 0 0.222828 5448.82 1 6 CACCTG GACCCGC - +4 predrem__nrMotif2534 1 0.222828 5448.82 1 6 CACCTG TTACCAA - +4 elemento__AGATAAG-GATAe-grn-pnr 2 0.222828 5448.82 1 5 CACCTG CTTATCT - +4 fantom__motif45_GCTCNGG -2 0.222828 5448.82 1 4 CACCTG CCTGAGC - +4 cisbp__M0229 2 0.224386 5486.91 1 6 CACCTG GCCACTTGC + +4 cisbp__M1546 2 0.224386 5486.91 1 6 CACCTG TGTACGTCA + +4 cisbp__M1621 3 0.224386 5486.91 1 6 CACCTG TCCGACCCG + +4 cisbp__M1754 3 0.224386 5486.91 1 6 CACCTG ATTTATCCG + +4 cisbp__M6197-CrebB 3 0.224386 5486.91 1 6 CACCTG CGTGACGTC + +4 hocomoco__ARNT_HUMAN.H11MO.0.B-sima-tgo 1 0.224386 5486.91 1 6 CACCTG GTACGTGCC + +4 jaspar__MA0961.1 2 0.224386 5486.91 1 6 CACCTG GCCACTTGC + +4 predrem__nrMotif1362 2 0.224386 5486.91 1 6 CACCTG TTTAGCTTC + +4 predrem__nrMotif1414 0 0.224386 5486.91 1 6 CACCTG CAGCTGAAG + +4 predrem__nrMotif2674 3 0.224386 5486.91 1 6 CACCTG TATAACATT + +4 cisbp__M1208 2 0.224386 5486.91 1 6 CACCTG TTGACATGT - +4 cisbp__M1357-Myb 0 0.224386 5486.91 1 6 CACCTG TAACGGTCA - +4 cisbp__M1939-lmd 3 0.224386 5486.91 1 6 CACCTG GACCCCCCA - +4 jaspar__MA0118.1-lmd 3 0.224386 5486.91 1 6 CACCTG GACCCCCCA - +4 predrem__nrMotif314 0 0.224386 5486.91 1 6 CACCTG CCCCTGACC - +4 swissregulon__sacCer__CUP9-achi-hth-vis 3 0.224386 5486.91 1 6 CACCTG TGACACATT - +4 transfac_pro__M01689 2 0.224386 5486.91 1 6 CACCTG TTCACATGC - +4 transfac_pro__M01815 0 0.224386 5486.91 1 6 CACCTG CACGTCAGC - +4 predrem__nrMotif138 4 0.224386 5486.91 1 5 CACCTG CCACCCCCT + +4 predrem__nrMotif59 4 0.224386 5486.91 1 5 CACCTG GGAGCCCCT + +4 predrem__nrMotif164 -1 0.224386 5486.91 1 5 CACCTG CCCTTGTCC - +4 predrem__nrMotif260 4 0.224386 5486.91 1 5 CACCTG TTTGCTCCT - +4 predrem__nrMotif632 4 0.224386 5486.91 1 5 CACCTG CCCACCCCT - +4 predrem__nrMotif80 4 0.224386 5486.91 1 5 CACCTG ATTTCCCCT - +4 predrem__nrMotif97 4 0.224386 5486.91 1 5 CACCTG CCATCCCCT - +4 neph__UW.Motif.0310 8 0.224512 5489.99 1 6 CACCTG AGAAAATTTCCATCTG + +4 neph__UW.Motif.0498 10 0.224512 5489.99 1 6 CACCTG GCCATCATTCTTCCTC + +4 taipale_tf_pairs__TFAP4_ETV4_RCCGGAARCASSTGNN_CAP-crp-Ets96B 2 0.224512 5489.99 1 6 CACCTG CCCAGCTGCTTCCGGT - +4 cisbp__M6533-EcR-usp 11 0.224512 5489.99 1 5 CACCTG GTGAACTCCTTGACCC + +4 neph__UW.Motif.0294 -2 0.224512 5489.99 1 4 CACCTG CCCGGAGGCTGTCTCT - +4 cisbp__M3625-CG12018-Dif-dl-Rel 8 0.224745 5495.69 1 6 CACCTG AGGGGACTTTCCCC + +4 flyfactorsurvey__D19B-F1-2-CG4360_F3_SOLEXA_2.5-D19B 1 0.224745 5495.69 1 6 CACCTG ATACCCTGTAATGG + +4 neph__UW.Motif.0605 7 0.224745 5495.69 1 6 CACCTG CCAGAGACAATTTC + +4 neph__UW.Motif.0664 1 0.224745 5495.69 1 6 CACCTG CCAGCCTGCCGCTG + +4 transfac_pro__M01728-EcR-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-usp 1 0.224745 5495.69 1 6 CACCTG TGACCTTTGCCCTT + +4 transfac_pro__M04750-fkh-Hsf 2 0.224745 5495.69 1 6 CACCTG AGAACATTCTGTTC + +4 scertf__badis.CST6-Atf3-CrebB-Jra-Xbp1-kay 1 0.22645 5537.39 1 5 CACCTG TGACGT + +4 transfac_pro__M01130 -2 0.22645 5537.39 1 4 CACCTG CCTTTT - +4 fantom__motif162_AGTTACCGTCA 3 0.226972 5550.15 1 6 CACCTG AGTTACCGTCA + +4 fantom__motif166_TAMAACTTTGS 2 0.226972 5550.15 1 6 CACCTG TACAACTTTGC + +4 predrem__nrMotif2169 4 0.226972 5550.15 1 6 CACCTG GAGGCCCCTCC + +4 predrem__nrMotif559 0 0.226972 5550.15 1 6 CACCTG CACATCTGTTT + +4 transfac_pro__M01621 0 0.226972 5550.15 1 6 CACCTG TGCCTGCAGGT + +4 transfac_pro__M07601-Clk-E2f1-Max-Myc 3 0.226972 5550.15 1 6 CACCTG GGCCACGTGCC + +4 transfac_pro__M07929-CG8319-Mettl14 5 0.226972 5550.15 1 6 CACCTG CCCGTCACTTT + +4 cisbp__M2276-aop-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 4 0.226972 5550.15 1 6 CACCTG CCACTTCCTGT - +4 cisbp__M6335-Max-Myc 2 0.226972 5550.15 1 6 CACCTG ACCACGTGGCT - +4 jaspar__MA0093.2-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Usf-ac-ase-cnc-cwo-cyc-l(1)sc-nau-sc-tgo 3 0.226972 5550.15 1 6 CACCTG GGTCACGTGGC - +4 jaspar__MA0385.1 0 0.226972 5550.15 1 6 CACCTG TGCCTGCAGGT - +4 transfac_pro__M01004 3 0.226972 5550.15 1 6 CACCTG TTTTTCCTTAT - +4 transfac_pro__M01163-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.226972 5550.15 1 6 CACCTG TACTTCCGGTT - +4 transfac_pro__M01165-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.226972 5550.15 1 6 CACCTG TACTTCCGGTT - +4 transfac_pro__M07088-aop-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 4 0.226972 5550.15 1 6 CACCTG CCACTTCCTGT - +4 cisbp__M4064-achi-vis -1 0.226972 5550.15 1 5 CACCTG AGCTGTCAGAA + +4 transfac_public__M00418-achi-vis -1 0.226972 5550.15 1 5 CACCTG AGCTGTCAGAA + +4 transfac_pro__M06179 -1 0.226972 5550.15 1 5 CACCTG TCCTTTATCCA - +4 scertf__badis.ECM23 0 0.227543 5564.11 1 5 CACCTG GATCT - +4 hocomoco__FOXA2_MOUSE.H11MO.0.A-FoxK-FoxP-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-slp2 7 0.227765 5569.54 1 6 CACCTG CCTTGTTTACTTT + +4 hocomoco__SOX10_HUMAN.H11MO.1.A-Mad-Sox14-Sox100B-SoxN-pan 0 0.227765 5569.54 1 6 CACCTG TTCCTTTGTTCTC + +4 jaspar__MA0499.1-ac-ase-l(1)sc-nau-sc 2 0.227765 5569.54 1 6 CACCTG TGCAGCTGTCCCT + +4 neph__UW.Motif.0236 7 0.227765 5569.54 1 6 CACCTG ATTTTTTCATATG + +4 cisbp__M2299-ac-ase-l(1)sc-nau-sc 2 0.227765 5569.54 1 6 CACCTG TGCAGCTGTCCCT - +4 neph__UW.Motif.0519 6 0.227765 5569.54 1 6 CACCTG TGTGTTTTTCTTC - +4 taipale_tf_pairs__ETV5_FOXI1_GTMAACAGGAWRN_CAP-Ets96B 2 0.227765 5569.54 1 6 CACCTG ACTTCCTGTTTAC - +4 transfac_pro__M07959-HDAC1-Hnf4-Hr78-nej-svp-usp 2 0.227765 5569.54 1 6 CACCTG TGGACTTTGCCCC - +4 taipale_tf_pairs__ERF_NHLH1_NNCAGCTGCCGGAWRYN_CAP_repr-Ets21C-HLH4C 2 0.227957 5574.23 1 6 CACCTG AGCAGCTGCCGGAAGTA + +4 transfac_pro__M01472-ara-caup-mirr 4 0.227957 5574.23 1 6 CACCTG TATATACATGTAAAATT + +4 transfac_pro__M02838 9 0.227957 5574.23 1 6 CACCTG TTTTATGTGCACATGTA - +4 cisbp__M5329-Atf6-Clk-CrebA-Max-Mnt 3 0.228639 5590.91 1 6 CACCTG TGCCACGTGGCA + +4 neph__UW.Motif.0016 3 0.228639 5590.91 1 6 CACCTG TTCCAGCTGCCA + +4 neph__UW.Motif.0378 0 0.228639 5590.91 1 6 CACCTG AGCCACTTTCCA + +4 taipale_cyt_meth__CREB3L4_YGCCACGTCAYN_eDBD_repr-Atf6-CrebA-Xbp1 3 0.228639 5590.91 1 6 CACCTG TGCCACGTCACC + +4 taipale_cyt_meth__MEIS2_TGACANNTGTCA_FL-achi-hth-nau-vis 3 0.228639 5590.91 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__MYF6_NAACANNTGWYN_eDBD-amos-Fer1-HLH54F-nau 3 0.228639 5590.91 1 6 CACCTG GAACAGCTGTCG + +4 taipale_cyt_meth__TGIF1_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.228639 5590.91 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__TGIF2LX_TGACANNTGTCA_FL-achi-hth-nau-vis 3 0.228639 5590.91 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__XBP1_NKMCACRTCAYN_FL_meth-Atf6-CrebA-Xbp1 3 0.228639 5590.91 1 6 CACCTG CGCCACGTCACC + +4 transfac_pro__M00441-Atf6-Clk-CrebA-Max-Mnt 3 0.228639 5590.91 1 6 CACCTG TGCCACGTGGCA + +4 transfac_public__M00123-Max-Myc 3 0.228639 5590.91 1 6 CACCTG TACCACGTGTCA + +4 cisbp__M0743-fd59A-fkh-FoxP 6 0.228639 5590.91 1 6 CACCTG TTTGTTTACAAT - +4 cisbp__M5242-tin 3 0.228639 5590.91 1 6 CACCTG AGCCACTTGAGA - +4 homer__CCATATATGGNA_CArG-bs-Mef2 0 0.228639 5590.91 1 6 CACCTG TGCCATATATGG - +4 jaspar__MA0929.1-FoxP-fd59A-fkh 6 0.228639 5590.91 1 6 CACCTG TTTGTTTACAAT - +4 taipale_cyt_meth__ATF2_NRTGAYGTMAYN_FL_meth-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-gt-Irbp18-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.228639 5590.91 1 6 CACCTG CATGACGTCATC - +4 taipale_cyt_meth__ATF6B_YGCCACGTGGCA_eDBD-Atf6-Clk-CrebA 3 0.228639 5590.91 1 6 CACCTG TGCCACGTGGCA - +4 taipale_cyt_meth__ELF2_NATGCGGAAGTN_eDBD-Eip74EF 0 0.228639 5590.91 1 6 CACCTG CACTTCCGCATC - +4 taipale_cyt_meth__ELF2_NATGCGGAAGTN_eDBD_meth-Eip74EF 0 0.228639 5590.91 1 6 CACCTG CACTTCCGCATT - +4 taipale_cyt_meth__ELF4_NACCCGGAAGTN_eDBD-aop-Eip74EF-Ets96B-nej 0 0.228639 5590.91 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__JDP2_NRTGAYGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Irbp18-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.228639 5590.91 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__MYF6_CGTCANNTGTYN_eDBD_meth-Fer1-nau 3 0.228639 5590.91 1 6 CACCTG CAACAGCTGACG - +4 taipale_cyt_meth__PKNOX1_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.228639 5590.91 1 6 CACCTG TGACAGCTGTCA - +4 taipale_cyt_meth__PKNOX2_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.228639 5590.91 1 6 CACCTG TGACAGCTGTCA - +4 taipale_cyt_meth__SPIB_RWWGRGGAAGTN_eDBD_meth-CG9650-nej 0 0.228639 5590.91 1 6 CACCTG CACTTCCTCATT - +4 transfac_pro__M00707-TfIIA-L-TfIIA-S 1 0.228639 5590.91 1 6 CACCTG GGTCCTTTTATA - +4 transfac_pro__M05937 6 0.228639 5590.91 1 6 CACCTG TCTTCATACCAC - +4 transfac_pro__M06048 1 0.228639 5590.91 1 6 CACCTG GCAACTTCCCCT - +4 transfac_pro__M06061 6 0.228639 5590.91 1 6 CACCTG GATTTTTACCCA - +4 transfac_pro__M06784 6 0.228639 5590.91 1 6 CACCTG GCTTCTTACCAC - +4 transfac_pro__M07701-Eip74EF 0 0.228639 5590.91 1 6 CACCTG TACTTCCGCATT - +4 transfac_pro__M09527-achi-vis 2 0.228639 5590.91 1 6 CACCTG TACAGCTGTCAA - +4 taipale_tf_pairs__TEAD4_ETV4_RCCGGAAATRCC_CAP-Ets96B-sd -1 0.228639 5590.91 1 5 CACCTG ACCGGAAATACC + +4 transfac_pro__M05650 7 0.228639 5590.91 1 5 CACCTG TATTTCTAACCC + +4 transfac_pro__M05687 7 0.228639 5590.91 1 5 CACCTG TGTATAGGACCG - +4 transfac_pro__M06031 7 0.228639 5590.91 1 5 CACCTG TGTATCGGACCG - +4 transfac_pro__M06144 7 0.228639 5590.91 1 5 CACCTG GCGTTATTACCT - +4 transfac_pro__M06443 7 0.228639 5590.91 1 5 CACCTG GCGTTATTACCT - +4 transfac_pro__M06568-CG6654-CG7372 7 0.228639 5590.91 1 5 CACCTG TCCTTAAAACCT - +4 transfac_pro__M06667 7 0.228639 5590.91 1 5 CACCTG GCTCCTGAACCA - +4 transfac_pro__M06682 7 0.228639 5590.91 1 5 CACCTG GCGAATAAACCC - +4 transfac_pro__M00957 8 0.230287 5631.22 1 6 CACCTG GGGGGGGGGACATGGTGTTCTTGGGGG + +4 hocomoco__ZN350_HUMAN.H11MO.0.C 12 0.230341 5632.52 1 6 CACCTG CAGTCCTTTTATGACCTA + +4 taipale_cyt_meth__ZNF660_NYTGATNNCCCAYCCTRN_FL_meth_repr-CG12071 11 0.230341 5632.52 1 6 CACCTG ATTGATTACCCACCCTAC + +4 swissregulon__hs__NR6A1.p2-ERR-EcR-Hr4-ftz-f1 3 0.230341 5632.52 1 6 CACCTG GGTGACCTTGAACTTGAG - +4 transfac_pro__M01257-bs 4 0.230341 5632.52 1 6 CACCTG CCCTTGCCTTATATGGGC - +4 cisbp__M5495 9 0.23101 5648.9 1 6 CACCTG TACGTCAGTTACGTA + +4 stark__RCACNNNNNNNCACA 1 0.23101 5648.9 1 6 CACCTG ACACAAAAAAACACA + +4 transfac_pro__M07231-GATAe-grn-pnr-TfAP-2 3 0.23101 5648.9 1 6 CACCTG CATTGCCTCAGGGCA + +4 transfac_pro__M07434-GATAd 9 0.23101 5648.9 1 6 CACCTG TGTTTCTATCTCCTT + +4 transfac_pro__M09335 3 0.23101 5648.9 1 6 CACCTG ATTAACCTTATCCTC + +4 neph__UW.Motif.0285 8 0.23101 5648.9 1 6 CACCTG TGATTGATTTCATTT - +4 taipale_cyt_meth__NR3C1_NGWACANNNYGTWCN_eDBD-fkh 2 0.23101 5648.9 1 6 CACCTG AGTACATAATGTACT - +4 transfac_pro__M09256 0 0.23101 5648.9 1 6 CACCTG CTCCGGATTTTCCGG - +4 taipale_tf_pairs__CUX1_RFX5_RATCRATNNNNNNNNNRGYAAC_CAP_repr-ct 11 0.231216 5653.93 1 6 CACCTG AATCGATAACGTGCCTAGTAAC + +4 tfdimers__MD00055 11 0.231216 5653.93 1 6 CACCTG ATTAGATAATCCTCCTTCATTT + +4 taipale_cyt_meth__ZSCAN23_NYCATGTGCTAATTACAMN_eDBD 11 0.231769 5667.45 1 6 CACCTG TTTGTAATTAGCACATGAG - +4 taipale_tf_pairs__HOXB2_NHLH1_NYMATTANNNNNNCAGCTGNN_CAP_repr-HLH4C-pb 13 0.232129 5676.24 1 6 CACCTG ATCATTAGGGCCGCAGCTGCG + +4 flyfactorsurvey__ab_SANGER_10_FBgn0259750-ab 10 0.232129 5676.24 1 6 CACCTG CTCTTAATGGGTCCTGGCCTC - +4 transfac_pro__M05254 3 0.232129 5676.24 1 6 CACCTG ACCCACCCGCAAGGAACACAA - +4 cisbp__M1927-Max-Myc-tgo-Usf 2 0.232176 5677.41 1 6 CACCTG GCCACGTG + +4 cisbp__M6151-tgo 1 0.232176 5677.41 1 6 CACCTG TCACGTGC + +4 hocomoco__ARNT_MOUSE.H11MO.0.B-tgo 1 0.232176 5677.41 1 6 CACCTG TCACGTGC + +4 homer__AGGCCTGG_ZFX 1 0.232176 5677.41 1 6 CACCTG AGGCCTGG + +4 jaspar__MA0104.3-Max-Myc-Usf-tgo 2 0.232176 5677.41 1 6 CACCTG GCCACGTG + +4 predrem__nrMotif1374 1 0.232176 5677.41 1 6 CACCTG GAACCAAG + +4 scertf__macisaac.CBF1-Clk-Mitf-SREBP-Usf-cnc-cyc-tgo 2 0.232176 5677.41 1 6 CACCTG GTCACGTG + +4 transfac_pro__M01856-lz-run-RunxA-RunxB 0 0.232176 5677.41 1 6 CACCTG AACCACAA + +4 cisbp__M0488 2 0.232176 5677.41 1 6 CACCTG GACCCCCC - +4 cisbp__M0637 1 0.232176 5677.41 1 6 CACCTG TTACATTT - +4 cisbp__M2390 2 0.232176 5677.41 1 6 CACCTG CCTTCCTC - +4 cisbp__M4643-Myc 0 0.232176 5677.41 1 6 CACCTG CACGTGGT - +4 jaspar__MA1021.1-Max-Usf 1 0.232176 5677.41 1 6 CACCTG GCACGTGG - +4 predrem__nrMotif2673 2 0.232176 5677.41 1 6 CACCTG GCTACCCA - +4 scertf__badis.HMRA2 2 0.232176 5677.41 1 6 CACCTG ATTACATG - +4 cisbp__M0334 3 0.232176 5677.41 1 5 CACCTG GCTTACGT + +4 elemento__AGCTGTCA-achi-hth-vis -1 0.232176 5677.41 1 5 CACCTG AGCTGTCA + +4 yetfasco__YHR178W_1405 3 0.232176 5677.41 1 5 CACCTG TAACACCG + +4 cisbp__M0646 -1 0.232176 5677.41 1 5 CACCTG ACGTTATC - +4 elemento__ATGCAGGC -1 0.232176 5677.41 1 5 CACCTG GCCTGCAT - +4 elemento__GTGTGACC 4 0.232176 5677.41 1 4 CACCTG GTGTGACC + +4 cisbp__M0096 -2 0.232176 5677.41 1 4 CACCTG CCTGCAGC - +4 predrem__nrMotif2041 5 0.232176 5677.41 1 3 CACCTG AGTGCCAC + +4 predrem__nrMotif897 5 0.232176 5677.41 1 3 CACCTG TTCATCAC + +4 dbcorrdb__EP300__ENCSR000BKK_1__m1-Chd1-Jra-nej 12 0.232337 5681.34 1 6 CACCTG GCGAATGGTACGTTCCAGCC + +4 dbcorrdb__EP300__ENCSR000BLM_1__m2-nej 0 0.232337 5681.34 1 6 CACCTG TACATGCCTGAGGGGTTAGT + +4 dbcorrdb__RAD21__ENCSR000ECE_1__m2-CTCF-SMC3-usp-vtd 6 0.232337 5681.34 1 6 CACCTG GGGTGCCCCCTAGTGGCAAA + +4 dbcorrdb__RFX5__ENCSR000DZW_1__m1-CG9727-Rfx 2 0.232337 5681.34 1 6 CACCTG TCTGCCTAGCAACAGGTGAC + +4 dbcorrdb__ZC3H11A__ENCSR000EFR_1__m1-Brf-CTCF-E(z)-RpII215-tna 6 0.232337 5681.34 1 6 CACCTG GGCCGCCCCCTGGAGGGGGC + +4 transfac_pro__M09503 10 0.232337 5681.34 1 6 CACCTG ACAAATTGAACACGTCTCTT + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m4 9 0.232337 5681.34 1 6 CACCTG CCACACCTCTTTCTGCAAAC - +4 dbcorrdb__POLR3G__ENCSR000EHQ_1__m1-AMPKalpha-Bdp1-Brf-CG17209-CG43143-ebi-Hsf-SREBP-Tbp 11 0.232337 5681.34 1 6 CACCTG GCCGGGATTCGAACCCGGGA - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m6-CTCF-SMC3-usp-vtd 9 0.232337 5681.34 1 6 CACCTG CTGGCGCGCCCCCTTGCGGC - +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m7-egg 12 0.232337 5681.34 1 6 CACCTG TGAATGTGAGAAAACATTCA - +4 dbcorrdb__SIN3A__ENCSR000BOY_1__m1-CTCF-HDAC1-Myc-Sin3A 7 0.232337 5681.34 1 6 CACCTG GCCGCCCCACGTGGTGCTGA - +4 dbcorrdb__eGFP-NR4A1__ENCSR000DJW_1__m1 14 0.232337 5681.34 1 6 CACCTG AACATGAGTGACTCCATCTT - +4 taipale_tf_pairs__GCM2_ONECUT2_RTRCGGGNNNNNNATCRATN_CAP_repr-gcm-gcm2-onecut 11 0.232337 5681.34 1 6 CACCTG TATCGATTTTTTGCCCGCAT - +4 tfdimers__MD00358-fkh 20 0.232393 5682.71 1 6 CACCTG TATATAAGTAAACAAAAAAGAACATTTTTAATTA + +4 cisbp__M0196-Clk 2 0.233021 5698.05 1 6 CACCTG GGCACGTGTA + +4 cisbp__M0232-Mitf-Mondo-SREBP-Usf-bigmax 2 0.233021 5698.05 1 6 CACCTG ATCACGTGAT + +4 cisbp__M1801 4 0.233021 5698.05 1 6 CACCTG ATTTTTCCGG + +4 factorbook__GATA1-CoRest-CycT-GATAd-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.233021 5698.05 1 6 CACCTG TCTTATCTGT + +4 homer__ACAGCTGCTG_Tcf12-HLH3B-HLH54F-ac-ase-l(1)sc-nau-sc 1 0.233021 5698.05 1 6 CACCTG ACAGCTGCTG + +4 jaspar__MA0626.1-Clk 2 0.233021 5698.05 1 6 CACCTG GGCACGTGTC + +4 predrem__nrMotif133 3 0.233021 5698.05 1 6 CACCTG GTGGGCCTGG + +4 predrem__nrMotif1869 0 0.233021 5698.05 1 6 CACCTG TCCCTTTCTT + +4 predrem__nrMotif2036 3 0.233021 5698.05 1 6 CACCTG CTTAACATTT + +4 predrem__nrMotif273 1 0.233021 5698.05 1 6 CACCTG CAGCCTAGGG + +4 predrem__nrMotif896 0 0.233021 5698.05 1 6 CACCTG CACCACACAC + +4 taipale_cyt_meth__GRHL1_NAACCGGTTN_eDBD_meth_repr-gem-grh 1 0.233021 5698.05 1 6 CACCTG AAACCGGTTT + +4 taipale_cyt_meth__NKX3-1_NCCACTTAAN_eDBD_meth-bap-Hmx 2 0.233021 5698.05 1 6 CACCTG ACCACTTAAC + +4 taipale_cyt_meth__OLIG2_AACAGCTGTY_eDBD-amos-dimm-Fer3-HLH54F-nau-sage 2 0.233021 5698.05 1 6 CACCTG AACAGCTGTT + +4 transfac_pro__M00303-Clk-cnc-Mitf-tgo-Usf 3 0.233021 5698.05 1 6 CACCTG AGTCACGTGA + +4 transfac_pro__M02250-E2f1-Max-Myc 2 0.233021 5698.05 1 6 CACCTG CGCACGTGGC + +4 cisbp__M0031 4 0.233021 5698.05 1 6 CACCTG TGCCGACATA - +4 cisbp__M0640 3 0.233021 5698.05 1 6 CACCTG TGTAACATTT - +4 cisbp__M0647 0 0.233021 5698.05 1 6 CACCTG TTACTTTTTG - +4 cisbp__M0714-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 2 0.233021 5698.05 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1310 4 0.233021 5698.05 1 6 CACCTG GGGGAATCTT - +4 cisbp__M1326 3 0.233021 5698.05 1 6 CACCTG GGGAATCTTC - +4 cisbp__M1464 3 0.233021 5698.05 1 6 CACCTG GGACACAGTT - +4 cisbp__M1964-Max-Myc 3 0.233021 5698.05 1 6 CACCTG AAGCACATGG - +4 cisbp__M3334-GATAd-GATAe-grn-pnr-srp 3 0.233021 5698.05 1 6 CACCTG GCTTATCTTT - +4 cisbp__M4622-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.233021 5698.05 1 6 CACCTG TCTTATCTGT - +4 cisbp__M5234-sim-tgo 1 0.233021 5698.05 1 6 CACCTG GTACGTGACC - +4 cisbp__M5498-gem-grh 1 0.233021 5698.05 1 6 CACCTG AAACCGGTTT - +4 cisbp__M5866-bigmax-cnc-cwo-Mitf-Mondo-SREBP-tgo-Usf 2 0.233021 5698.05 1 6 CACCTG ATCACGTGAC - +4 jaspar__MA0147.2-Max-Myc 3 0.233021 5698.05 1 6 CACCTG AAGCACATGG - +4 predrem__nrMotif618 3 0.233021 5698.05 1 6 CACCTG AGGCACATTT - +4 predrem__nrMotif927 0 0.233021 5698.05 1 6 CACCTG TTCCTCTTGG - +4 taipale_cyt_meth__BHLHA15_NMCAGCTGKN_eDBD-ac-amos-ase-CoRest-dimm-Fer1-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.233021 5698.05 1 6 CACCTG AACAGCTGTT - +4 taipale_cyt_meth__ELK3_ACCGGAAGTN_FL-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.233021 5698.05 1 6 CACCTG CACTTCCGGT - +4 taipale_cyt_meth__MAX_RNCACGTGYN_FL-Max-Mitf 2 0.233021 5698.05 1 6 CACCTG CGCACGTGGC - +4 transfac_pro__M05557-btd-cbt-luna-Sp1-Spps 0 0.233021 5698.05 1 6 CACCTG CACCCGCCCT - +4 transfac_public__M00008-btd-Spps 4 0.233021 5698.05 1 6 CACCTG ACCCCGCCCC - +4 transfac_public__M00462-GATAd-GATAe-grn-pnr-srp 3 0.233021 5698.05 1 6 CACCTG GCTTATCTTT - +4 fantom__motif129_CTCGTAATCT 5 0.233021 5698.05 1 5 CACCTG CTCGTAATCT + +4 transfac_pro__M08867-TfAP-2 -1 0.233021 5698.05 1 5 CACCTG GCCTGGGGCC + +4 cisbp__M0412-opa -1 0.233021 5698.05 1 5 CACCTG CCCCGCTGTG - +4 predrem__nrMotif19 -1 0.233021 5698.05 1 5 CACCTG ATCTGTGTTT - +4 predrem__nrMotif954 5 0.233021 5698.05 1 5 CACCTG CCACCCACCC - +4 taipale_cyt_meth__DPRX_NGMTAATCCN_eDBD_repr 5 0.233021 5698.05 1 5 CACCTG GGGATTATCT - +4 transfac_pro__M09570 -1 0.233021 5698.05 1 5 CACCTG TCCGGAATTC - +4 transfac_pro__M05154 6 0.233021 5698.05 1 4 CACCTG GGGAGTCACC - +4 cisbp__M5100-Atf6-CrebA-Max-Myc 1 0.233643 5713.26 1 6 CACCTG CCACGTG + +4 stark__GTACGTG-sim 1 0.233643 5713.26 1 6 CACCTG GTACGTG + +4 elemento__CAAGTAC 1 0.233643 5713.26 1 6 CACCTG GTACTTG - +4 predrem__nrMotif2532 0 0.233643 5713.26 1 6 CACCTG CAGCTAC - +4 predrem__nrMotif475 1 0.233643 5713.26 1 6 CACCTG CCACATG - +4 transfac_pro__M00644 1 0.233643 5713.26 1 6 CACCTG GCAGCTG - +4 transfac_pro__M01870-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.233643 5713.26 1 5 CACCTG ACTTCCT - +4 tfdimers__MD00424-ac-ase-Hnf4-l(1)sc-nau-sc-svp-usp 16 0.234261 5728.39 1 6 CACCTG CCCCCTGACCTTTGACCATCTGCCCCCCG - +4 cisbp__M0019 1 0.235138 5749.83 1 6 CACCTG CTGCCGACA + +4 cisbp__M1545 2 0.235138 5749.83 1 6 CACCTG CGTACGTCA + +4 cisbp__M1783 2 0.235138 5749.83 1 6 CACCTG ATTGCCGAG + +4 cisbp__M1942 2 0.235138 5749.83 1 6 CACCTG TCCACTTAA + +4 cisbp__M5674-dsf-tll 2 0.235138 5749.83 1 6 CACCTG TTGACTTTT + +4 predrem__nrMotif2071 0 0.235138 5749.83 1 6 CACCTG AATCTCCCA + +4 predrem__nrMotif775 3 0.235138 5749.83 1 6 CACCTG GCAGAACTT + +4 predrem__nrMotif915 0 0.235138 5749.83 1 6 CACCTG TACTTTTGT + +4 stark__YGACMTTGA 1 0.235138 5749.83 1 6 CACCTG CGACATTGA + +4 cisbp__M0791 2 0.235138 5749.83 1 6 CACCTG CGGATCGGG - +4 flyfactorsurvey__D19B_F10-12_SANGER_5_FBgn0022699-D19B 1 0.235138 5749.83 1 6 CACCTG TACCCTGTA - +4 neph__UW.Motif.0030 1 0.235138 5749.83 1 6 CACCTG TGACTTCAT - +4 predrem__nrMotif1043 0 0.235138 5749.83 1 6 CACCTG AATCTGGAA - +4 predrem__nrMotif1420 3 0.235138 5749.83 1 6 CACCTG AGTGACATG - +4 predrem__nrMotif1497 3 0.235138 5749.83 1 6 CACCTG TCTAACCCT - +4 predrem__nrMotif195 0 0.235138 5749.83 1 6 CACCTG TTCCTTCTG - +4 predrem__nrMotif354 1 0.235138 5749.83 1 6 CACCTG GTGCCTTCC - +4 predrem__nrMotif980 2 0.235138 5749.83 1 6 CACCTG GGACCCTGA - +4 transfac_pro__M02447 3 0.235138 5749.83 1 6 CACCTG AATTACATG - +4 predrem__nrMotif2324 -1 0.235138 5749.83 1 5 CACCTG TCCTGTGAA + +4 transfac_pro__M04707-CG9727-Rfx -1 0.235138 5749.83 1 5 CACCTG CCCTAGCAA + +4 predrem__nrMotif1337 -1 0.235138 5749.83 1 5 CACCTG GCCTCTGAT - +4 predrem__nrMotif2185 -1 0.235138 5749.83 1 5 CACCTG TCCTTGTGT - +4 predrem__nrMotif990 -1 0.235138 5749.83 1 5 CACCTG TCCTCAGCT - +4 predrem__nrMotif1522 -2 0.235138 5749.83 1 4 CACCTG CCTGTGACA + +4 cisbp__M4428-fkh-Hsf 2 0.235902 5768.51 1 6 CACCTG AGAACATTCTGTTC + +4 neph__UW.Motif.0108 4 0.235902 5768.51 1 6 CACCTG CTGCCCCCTCCCAG + +4 transfac_public__M00213 8 0.235902 5768.51 1 6 CACCTG AAAACCCATACATC + +4 neph__UW.Motif.0485 4 0.235902 5768.51 1 6 CACCTG CAGCCACCATGTTG - +4 swissregulon__hs__HOXA9_MEIS1.p2 5 0.235902 5768.51 1 6 CACCTG TCATAAAACTGTCA - +4 taipale_cyt_meth__ETV4_NCAGGAAGGAAGTN_FL_meth-Ets96B 0 0.235902 5768.51 1 6 CACCTG CACTTCCTTCCTGT - +4 taipale_tf_pairs__ETV2_FOXI1_RNCGGAANNAAACA_CAP_repr-pnt 4 0.235902 5768.51 1 6 CACCTG TGTTTACTTCCGGT - +4 transfac_pro__M01650-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-Spps-svp-tll-usp 8 0.235902 5768.51 1 6 CACCTG TGACCTTTGACCTC - +4 taipale_cyt_meth__ZBTB14_NTGCRCGTGCACGYGN_FL_meth_repr 9 0.235919 5768.94 1 6 CACCTG GTGCGCGTGCACGTGA + +4 transfac_pro__M03121-amos 5 0.235919 5768.94 1 6 CACCTG AGGAACAGCTGTCTAA + +4 neph__UW.Motif.0547 8 0.235919 5768.94 1 6 CACCTG GCTCTGTTGTCATGTG - +4 neph__UW.Motif.0635 2 0.235919 5768.94 1 6 CACCTG CTCACACCTCTGTTTG - +4 taipale_cyt_meth__BCL6_NTGCTTTCGAGGAAYN_eDBD_repr 2 0.235919 5768.94 1 6 CACCTG AATTCCTCGAAAGCAT - +4 taipale_cyt_meth__BCL6_NYGTAATCTAGGAATN_eDBD_meth 2 0.235919 5768.94 1 6 CACCTG AATTCCTAGATTACGT - +4 transfac_pro__M09443 10 0.235919 5768.94 1 6 CACCTG TTTAATTTTTTACCGT - +4 hdpi__AFF4-lilli -1 0.237508 5807.78 1 5 CACCTG CCCTCC - +4 hdpi__ETS1 -1 0.237508 5807.78 1 5 CACCTG ACTTCC - +4 transfac_pro__M01266-Eip74EF-Ets96B 1 0.237508 5807.78 1 5 CACCTG CTTCCT - +4 transfac_pro__M02084-Bgb-Bro-lz-run-RunxA-RunxB -1 0.237508 5807.78 1 5 CACCTG ACCACA - +4 fantom__motif1_TCGNAG -3 0.237508 5807.78 1 3 CACCTG CTACGA - +4 flyfactorsurvey__amos_da_SANGER_10_FBgn0000413-amos-da 2 0.23793 5818.1 1 6 CACCTG ACCATCTGCCG + +4 predrem__nrMotif2669 1 0.23793 5818.1 1 6 CACCTG CCGCCGTCGCC + +4 taipale_cyt_meth__FLI1_NACCGGAARTN_FL-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.23793 5818.1 1 6 CACCTG GACCGGAAGTG + +4 transfac_pro__M01833 4 0.23793 5818.1 1 6 CACCTG CCGGGACCGGC + +4 transfac_pro__M07078 2 0.23793 5818.1 1 6 CACCTG CTCACGTGCAC + +4 cisbp__M0825 2 0.23793 5818.1 1 6 CACCTG TGTACATGTCG - +4 cisbp__M2266 2 0.23793 5818.1 1 6 CACCTG CTCACGTGCAC - +4 cisbp__M6206 3 0.23793 5818.1 1 6 CACCTG TACTTCCTTAT - +4 hocomoco__ZKSC3_HUMAN.H11MO.0.D 2 0.23793 5818.1 1 6 CACCTG CTAGCCTCGAA - +4 taipale_cyt_meth__USF2_MNCAYGTGAYN_eDBD_meth_repr-Mitf-Usf 3 0.23793 5818.1 1 6 CACCTG GGTCACATGGT - +4 transfac_pro__M01893 1 0.23793 5818.1 1 6 CACCTG TGACATGGAAT - +4 transfac_pro__M05316-ind-pb -1 0.23793 5818.1 1 5 CACCTG TCCTTATTAAA + +4 predrem__nrMotif402 -1 0.23793 5818.1 1 5 CACCTG TCCTCTTTCCC - +4 transfac_pro__M09492-Awh 6 0.23793 5818.1 1 5 CACCTG ATTAATTACGT - +4 transfac_pro__M08193 1 0.238619 5834.94 1 4 CACCTG TTACA - +4 cisbp__M5376-aop-Eip74EF-Ets21C 0 0.238919 5842.29 1 6 CACCTG AACCCGGAAGTAA + +4 hocomoco__COE1_MOUSE.H11MO.0.A-kn 2 0.238919 5842.29 1 6 CACCTG AGTCCCTGGGGAC + +4 taipale__ELF3_full_NACCCGGAAGTAN-aop-Eip74EF-Ets21C 0 0.238919 5842.29 1 6 CACCTG AACCCGGAAGTAA + +4 hocomoco__GATA6_HUMAN.H11MO.0.A-GATAd-GATAe-Jra-grn-ham-pnr-sd-srp 1 0.238919 5842.29 1 6 CACCTG TTATCTTATCTGT - +4 hocomoco__NR6A1_MOUSE.H11MO.0.D-ERR-EcR-Hr4-ftz-f1-usp 1 0.238919 5842.29 1 6 CACCTG TGACCTTGACCTT - +4 predrem__nrMotif2368 6 0.238919 5842.29 1 6 CACCTG CCCTTCCACCCCC - +4 transfac_pro__M00915-E(z)-RpII215-TfAP-2-tna 0 0.238919 5842.29 1 6 CACCTG GGCCTGGGGGCGG - +4 transfac_pro__M01149-dmrt11E-dmrt93B-dmrt99B-dsx 7 0.238919 5842.29 1 6 CACCTG AAATTGTTACATT - +4 transfac_pro__M05567-ovo 2 0.238919 5842.29 1 6 CACCTG GCGACATGACTCT - +4 transfac_pro__M07362 0 0.238919 5842.29 1 6 CACCTG AACCTTTTAATGG - +4 hocomoco__TLX1_HUMAN.H11MO.0.D-C15-NfI 4 0.239601 5858.97 1 6 CACCTG CTGGCAACTTGCCAAGG + +4 taipale_tf_pairs__MYBL1_MAX_NCACGTGNNYAACSGNN_CAP_repr-Max-Myb 9 0.239601 5858.97 1 6 CACCTG CCACGTGCCTAACGGTC + +4 transfac_pro__M02737-ac-ase-HLH54F-l(1)sc-nau-sc 5 0.239601 5858.97 1 6 CACCTG CTCAGCAGCTGCTACTG + +4 transfac_pro__M08989 2 0.239601 5858.97 1 6 CACCTG ACAAACTGTAGAGTGCT + +4 transfac_pro__M01437-Abd-B 10 0.239601 5858.97 1 6 CACCTG GAAATTTTACGACCTAA - +4 transfac_pro__M04653-croc-fd59A-fkh-FoxK-foxo-FoxP-slp2 9 0.239601 5858.97 1 6 CACCTG GTGTTTGTTTACTTTTT - +4 transfac_pro__M05425 9 0.239601 5858.97 1 6 CACCTG ATTCGAATTCACCTTAT - +4 transfac_pro__M07697-dmrt93B-dmrt99B-dsx 4 0.239601 5858.97 1 6 CACCTG TTGATACATTGTAACAA - +4 transfac_pro__M07760-achi-vis 8 0.239601 5858.97 1 6 CACCTG TGACAATTCAGCTGTCA - +4 transfac_pro__M08995-CTCF-vtd 11 0.239601 5858.97 1 6 CACCTG CCCAATAGCGCCCCCTA - +4 cisbp__M5997-Atf6-Clk-CrebA 3 0.239732 5862.16 1 6 CACCTG TGCCACGTGGCA + +4 hocomoco__HEY1_HUMAN.H11MO.0.D-Clk-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-Hey-Sidpn-dpn-tai 3 0.239732 5862.16 1 6 CACCTG TGGCACGTGTCG + +4 neph__UW.Motif.0401 1 0.239732 5862.16 1 6 CACCTG AAACTGTTTTTG + +4 taipale_cyt_meth__DMRTA2_NNTTGWTACATT_eDBD_meth-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.239732 5862.16 1 6 CACCTG AATTGTTACATT + +4 taipale_cyt_meth__MEIS2_TGACANNYGTCA_eDBD-achi-hth-nau-vis 3 0.239732 5862.16 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__MYF6_NAACANNTGWYN_eDBD_meth-amos-Fer1-HLH54F-nau 3 0.239732 5862.16 1 6 CACCTG CAACAGCTGTCG + +4 taipale_cyt_meth__PKNOX2_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.239732 5862.16 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M05524-rn-sqz 6 0.239732 5862.16 1 6 CACCTG GTGTCATACCGA + +4 transfac_pro__M07034-CrebB 4 0.239732 5862.16 1 6 CACCTG CAGTGACGTGAG + +4 hocomoco__VEZF1_HUMAN.H11MO.1.C-Spps-btd-klu-sr 1 0.239732 5862.16 1 6 CACCTG CCCCCTCCCCCT - +4 swissregulon__hs__PRDM1.p3-Blimp-1 0 0.239732 5862.16 1 6 CACCTG CACTTTCACTTT - +4 taipale__Creb3l2_DBD_TGCCACGTGGCA-Atf6-Clk-CrebA 3 0.239732 5862.16 1 6 CACCTG TGCCACGTGGCA - +4 taipale_cyt_meth__ELF1_NATGMGGAAGTN_FL_meth-Eip74EF 0 0.239732 5862.16 1 6 CACCTG CACTTCCGCATT - +4 taipale_cyt_meth__MSC_NNACAGCTGTNN_FL_repr-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.239732 5862.16 1 6 CACCTG CAACAGCTGTTG - +4 taipale_cyt_meth__PRDM1_NRGNGAAAGTGN_eDBD_repr-Blimp-1 1 0.239732 5862.16 1 6 CACCTG ACACTTTCCCTT - +4 taipale_cyt_meth__ZBTB20_NYAAYGTATRKN_eDBD_repr 4 0.239732 5862.16 1 6 CACCTG TCTATACATTAA - +4 transfac_pro__M07759-achi-hth-nau-vis 3 0.239732 5862.16 1 6 CACCTG TGACAGCTGTCA - +4 transfac_public__M00113-CrebB 6 0.239732 5862.16 1 6 CACCTG GGACGTCACCCG - +4 taipale_tf_pairs__TEAD4_FLI1_RCCGGAAATRSY_CAP-sd -1 0.239732 5862.16 1 5 CACCTG ACCGGAAATGCC + +4 taipale__Rxra_DBD_RGGTCATGACCY_repr-EcR-eg-ham-Hr3-Hr78-kni-knrl-usp 7 0.239732 5862.16 1 5 CACCTG GGGTCATGACCC - +4 transfac_pro__M05058 7 0.239732 5862.16 1 5 CACCTG CTTTTACTACCT - +4 transfac_pro__M05836 7 0.239732 5862.16 1 5 CACCTG GCGCCTTAACCA - +4 transfac_pro__M06153 7 0.239732 5862.16 1 5 CACCTG TCCCACAGACCG - +4 transfac_pro__M06315-CG2120 7 0.239732 5862.16 1 5 CACCTG TCTTTTGGACCG - +4 transfac_pro__M06652 7 0.239732 5862.16 1 5 CACCTG TCTTTCTGACCA - +4 tfdimers__MD00114-foxo-ftz-f1-slp2 11 0.239749 5862.58 1 6 CACCTG TTTTTTTTGTTTACCTTGGATTTT + +4 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNNTAATKR_CAP_repr-TfAP-2 0 0.241881 5914.73 1 6 CACCTG GGCCTGAGGGCACGCGGTAATTG + +4 tfdimers__MD00182-crp 7 0.241881 5914.73 1 6 CACCTG TCTTGACTTCCTGCTGTGTTCTT - +4 cisbp__M6138-ct-CTCF-Dif-dl-Klf15-klu 23 0.242164 5921.64 1 6 CACCTG CTCTTCCTCCCTCCTCTTCTCCTCTCCTCT + +4 taipale_cyt_meth__ZNF660_NYTGATNNCCCAYCCTRN_FL-CG12071 11 0.242173 5921.85 1 6 CACCTG ATTGATTACCCACCCTAC + +4 transfac_pro__M07736-gcm-gcm2 8 0.242173 5921.85 1 6 CACCTG TATGCTGGTACCCGCATA - +4 flyfactorsurvey__ci_F3-5_SOLEXA_5-ci-opa 6 0.242498 5929.8 1 6 CACCTG CAAGACCACCCAGAC + +4 hocomoco__REL_HUMAN.H11MO.0.B-Dif-dl 7 0.242498 5929.8 1 6 CACCTG TGGAATTTCCCTTCA + +4 taipale_cyt_meth__ZIC4_NRCCMCCYGYNGYGN_eDBD_repr-lmd-opa 3 0.242498 5929.8 1 6 CACCTG CACCCCCCGCTGCGC + +4 transfac_pro__M06455 9 0.242498 5929.8 1 6 CACCTG GGAGTTGACCACCGG + +4 transfac_pro__M09332 0 0.242498 5929.8 1 6 CACCTG AACCTTATCCATAAA + +4 cisbp__M2307-Blimp-1 1 0.242498 5929.8 1 6 CACCTG TCACTTTCACTTTCT - +4 cisbp__M4593-CTCF-SMC3-usp-vtd 5 0.242498 5929.8 1 6 CACCTG AGTGCCATCTAGTGG - +4 hocomoco__GCR_HUMAN.H11MO.0.A-Hsf-fkh 2 0.242498 5929.8 1 6 CACCTG AGAACATTCTGTTCT - +4 jaspar__MA0508.1-Blimp-1 1 0.242498 5929.8 1 6 CACCTG TCACTTTCACTTTCT - +4 jaspar__MA0534.1-EcR-svp-usp 9 0.242498 5929.8 1 6 CACCTG AAGGTCAATGAACTC - +4 transfac_pro__M02914-btd-Spps 7 0.242498 5929.8 1 6 CACCTG CTGGCCACGCCTTTG - +4 neph__UW.Motif.0428 10 0.242498 5929.8 1 5 CACCTG AGAAAATACAGTCTT + +4 taipale_tf_pairs__GCM1_HOXB13_NCCCGCANNMATAAA_CAP_repr-gcm-gcm2 -1 0.242498 5929.8 1 5 CACCTG ACCCGCACCAATAAA + +4 hocomoco__ESR2_HUMAN.H11MO.0.A-ERR-EcR-eg-kni-knrl 10 0.242498 5929.8 1 5 CACCTG AGGTCAGGGTGACCT - +4 neph__UW.Motif.0577 10 0.242498 5929.8 1 5 CACCTG TTCTCTGGCAATTCT - +4 transfac_pro__M09275 -1 0.242498 5929.8 1 5 CACCTG ACCTAACTTTACCAA - +4 cisbp__M0172-HLH54F 2 0.243202 5947.02 1 6 CACCTG AACATCTG + +4 cisbp__M0329-Met 1 0.243202 5947.02 1 6 CACCTG ACACGTGG + +4 cisbp__M1551 1 0.243202 5947.02 1 6 CACCTG GTACGTCA + +4 cisbp__M1734 2 0.243202 5947.02 1 6 CACCTG AATACGAG + +4 cisbp__M1756 1 0.243202 5947.02 1 6 CACCTG GCTCCGAT + +4 cisbp__M2264-amos 2 0.243202 5947.02 1 6 CACCTG GCCATCTG + +4 flyfactorsurvey__gce_Clk_SANGER_5_FBgn0023076-Clk-E2f1-Max-Myc-Usf-gce-tgo 2 0.243202 5947.02 1 6 CACCTG GCCACGTG + +4 taipale__ISL2_DBD_GCACTTAA_repr-tup 1 0.243202 5947.02 1 6 CACCTG GCACTTAA + +4 taipale_cyt_meth__HES5_NCACACKY_eDBD_meth_repr 1 0.243202 5947.02 1 6 CACCTG GCACACTT + +4 taipale_cyt_meth__LMX1A_CTCGTTAN_eDBD_meth-CG4328-Lmx1a 0 0.243202 5947.02 1 6 CACCTG CTCGTTAA + +4 transfac_pro__M01116-Clk-cyc 1 0.243202 5947.02 1 6 CACCTG ACACGTGG + +4 transfac_pro__M01919-Kdm4A-Kdm4B 1 0.243202 5947.02 1 6 CACCTG ACCCCTAA + +4 homer__AACAGCTG_MyoG-Fer1-Fer3-HLH54F-ac-amos-ase-crp-dimm-l(1)sc-nau-sc 0 0.243202 5947.02 1 6 CACCTG CAGCTGTT - +4 transfac_pro__M07075-amos 2 0.243202 5947.02 1 6 CACCTG GCCATCTG - +4 yetfasco__YER169W_547-Kdm4A-Kdm4B 1 0.243202 5947.02 1 6 CACCTG ACCCCTAA - +4 yetfasco__YOR028C_409-CG7786-Pdp1-gt-vri 1 0.243202 5947.02 1 6 CACCTG TTACGTAA - +4 cisbp__M1315 3 0.243202 5947.02 1 5 CACCTG TGGAATCT + +4 hdpi__DTL-l(2)dtl -1 0.243202 5947.02 1 5 CACCTG AACTGAAA + +4 predrem__nrMotif1465 -1 0.243202 5947.02 1 5 CACCTG ACCACAGT + +4 cisbp__M4686-Blimp-1 -1 0.243202 5947.02 1 5 CACCTG ACTTTCAC - +4 elemento__AAGTGCGT 3 0.243202 5947.02 1 5 CACCTG ACGCACTT - +4 elemento__AAGTGCTG 3 0.243202 5947.02 1 5 CACCTG CAGCACTT - +4 predrem__nrMotif2103 3 0.243202 5947.02 1 5 CACCTG CTAAATCT - +4 predrem__nrMotif723 3 0.243202 5947.02 1 5 CACCTG TATCTCCT - +4 jaspar__MA1075.1 4 0.243202 5947.02 1 4 CACCTG CGTTGACC + +4 transfac_pro__M04937 -2 0.243202 5947.02 1 4 CACCTG CCTGGAAT - +4 tfdimers__MD00107-TfAP-2 11 0.243413 5952.17 1 6 CACCTG TTTAAAAATAAAGCCTGTTTAT + +4 hocomoco__RXRA_MOUSE.H11MO.1.A-EcR-Hr4-svp-usp 6 0.243413 5952.17 1 6 CACCTG GACCTTGACCTTTTGATCCCCC - +4 taipale_tf_pairs__MYBL1_FIGLA_NCASSTGNNNNNNNNNCSGTTR_CAP_repr-Myb 15 0.243413 5952.17 1 6 CACCTG TAACGGTCACTGTGCCAGCTGG - +4 tfdimers__MD00172-EcR-usp 11 0.243413 5952.17 1 6 CACCTG AGTTAATTATTAACCCTTAAGA - +4 transfac_pro__M04839-btd-CTCF-HDAC1-Sin3A-Spps 4 0.243745 5960.3 1 6 CACCTG TCAGCACCACGGACAGCAC + +4 cisbp__M1618 1 0.244129 5969.68 1 6 CACCTG TTACCGGCAA + +4 cisbp__M1712 3 0.244129 5969.68 1 6 CACCTG ATTAGCCGAG + +4 cisbp__M1713 0 0.244129 5969.68 1 6 CACCTG CTCCGATCTC + +4 cisbp__M1750 3 0.244129 5969.68 1 6 CACCTG TTCATCCGGA + +4 homer__ACAGCTGTTN_Ptf1a-Fer1-ac-ase-dimm-l(1)sc-nau-sc 1 0.244129 5969.68 1 6 CACCTG ACAGCTGTTC + +4 swissregulon__hs__TFEB.p2-Max-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.244129 5969.68 1 6 CACCTG GTCACGTGAC + +4 swissregulon__sacCer__GSM1 0 0.244129 5969.68 1 6 CACCTG AAACTCCGGA + +4 taipale__GRHL1_DBD_NAACCGGTTN_repr-gem-grh 1 0.244129 5969.68 1 6 CACCTG AAACCGGTTT + +4 taipale__MNT_DBD_NNCACGTGNN-Max-Mnt-Myc 2 0.244129 5969.68 1 6 CACCTG ACCACGTGCC + +4 taipale_cyt_meth__MAFG_TGCTGACGYN_FL-maf-S 4 0.244129 5969.68 1 6 CACCTG TGCTGACGTG + +4 tiffin__TIFDMEM0000033 0 0.244129 5969.68 1 6 CACCTG AACCAATTTG + +4 transfac_pro__M07317-CtBP 0 0.244129 5969.68 1 6 CACCTG CGCCTGGGCT + +4 transfac_pro__M07766-bap-Hmx 2 0.244129 5969.68 1 6 CACCTG ACCACTTAAC + +4 cisbp__M0300-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-vri-Xbp1 1 0.244129 5969.68 1 6 CACCTG TGACGTCATT - +4 cisbp__M0396-bowl-drm-odd-sob 3 0.244129 5969.68 1 6 CACCTG TGCTACCGTT - +4 cisbp__M0704-aop-Atac3-Eip74EF-Ets96B-Ets97D-Ets98B-Rpn5 2 0.244129 5969.68 1 6 CACCTG ACTTCCGGGT - +4 cisbp__M0788-CoRest-GATAd-GATAe-HLH3B-Jra-grn-nej-pnr-srp-svp 3 0.244129 5969.68 1 6 CACCTG TCTTATCTCT - +4 cisbp__M0828 3 0.244129 5969.68 1 6 CACCTG ATTGACATGT - +4 cisbp__M1687 4 0.244129 5969.68 1 6 CACCTG CGTTGACCAT - +4 cisbp__M6226-Ets65A 4 0.244129 5969.68 1 6 CACCTG TTATTTCCTG - +4 hocomoco__GATA6_MOUSE.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.244129 5969.68 1 6 CACCTG CCTTATCTCC - +4 jaspar__MA0981.1 0 0.244129 5969.68 1 6 CACCTG TAACTTTTTG - +4 predrem__nrMotif2472 3 0.244129 5969.68 1 6 CACCTG AAATGCCTAA - +4 transfac_pro__M01585 2 0.244129 5969.68 1 6 CACCTG CCCACGTGCC - +4 transfac_pro__M05438-btd-cbt-Sp1-Spps 0 0.244129 5969.68 1 6 CACCTG GACCCGCCCT - +4 transfac_pro__M07292-ci-lmd-opa-sug 3 0.244129 5969.68 1 6 CACCTG GACCACCCAC - +4 predrem__nrMotif193 -1 0.244129 5969.68 1 5 CACCTG GCCTGAACCC + +4 predrem__nrMotif498 -1 0.244129 5969.68 1 5 CACCTG TCCTGTTTCT - +4 taipale_tf_pairs__MYBL1_FIGLA_NCASSTGNNNNNNYAACSGYN_CAP_repr-Myb 1 0.244281 5973.41 1 6 CACCTG CCACCTGGTCCAGTAACCGTC + +4 transfac_pro__M01011 14 0.244281 5973.41 1 6 CACCTG AGCAGTTAATAATTAACCATA + +4 transfac_pro__M06779 0 0.244281 5973.41 1 6 CACCTG TACCGGATGGTGGCGTGCTTT + +4 dbcorrdb__ATF3__ENCSR000BJY_1__m2-bs-cnc-CrebB-E2f1-Max-Myc-Sin3A-Usf 6 0.244418 5976.76 1 6 CACCTG TGGCGTCACGTGGCCGCGGC + +4 dbcorrdb__GATA3__ENCSR000EWV_1__m1-GATAe-grn-pnr-srp 7 0.244418 5976.76 1 6 CACCTG AGATTCTTATCTGACCCATC + +4 dbcorrdb__JUND__ENCSR000BKP_1__m2-Jra 5 0.244418 5976.76 1 6 CACCTG GGCAAAACCTGGAGCGGGGA + +4 dbcorrdb__JUND__ENCSR000DYS_1__m1-Chd1-Jra-nej 9 0.244418 5976.76 1 6 CACCTG CCCGGGCGGTACCAATGCCG + +4 dbcorrdb__MXI1__ENCSR000EGZ_1__m1-CG9727-Max-Myc-Rfx-SREBP 10 0.244418 5976.76 1 6 CACCTG TTGCCATGGCAACGTGGGCC + +4 dbcorrdb__CTCF__ENCSR000DQW_1__m2-CTCF-vtd 12 0.244418 5976.76 1 6 CACCTG GGGCTGCAGCGCCCCCTGGC - +4 dbcorrdb__GTF3C2__ENCSR000DOD_1__m1-Bdp1-CG17209 14 0.244418 5976.76 1 6 CACCTG GGTCTCGAACTCCTGACCTC - +4 dbcorrdb__HDAC2__ENCSR000AQG_1__m3-btd-CTCF-HDAC1-Sin3A-Spps 7 0.244418 5976.76 1 6 CACCTG GGCGCTGTGCGTGGTGCTGA - +4 dbcorrdb__SMARCC2__ENCSR000EDL_1__m1-mor-Six4-Usf 4 0.244418 5976.76 1 6 CACCTG GGACTACGTCACCCAGCAGG - +4 dbcorrdb__ZNF143__ENCSR000DZL_1__m1-Brf-CTCF-Hcf-RpII215-Six4 8 0.244418 5976.76 1 6 CACCTG CGCCGCGCCGCCTGCTGGGA - +4 dbcorrdb__ZNF217__ENCSR000EWU_1__m2 8 0.244418 5976.76 1 6 CACCTG CTCAGGGTAATCTGACCTGG - +4 hocomoco__RARA_HUMAN.H11MO.0.A-EcR-svp-usp 4 0.244418 5976.76 1 6 CACCTG CCTTGACCTCTTGATCCCCC - +4 cisbp__M1832 0 0.24486 5987.55 1 6 CACCTG CTCCGAA + +4 hocomoco__HAND1_HUMAN.H11MO.1.D-Hand 0 0.24486 5987.55 1 6 CACCTG GGCCTGG + +4 predrem__nrMotif2250 0 0.24486 5987.55 1 6 CACCTG GACATGT + +4 flyfactorsurvey__ttk-PF_SANGER_5_FBgn0003870-ttk 1 0.24486 5987.55 1 6 CACCTG TGTCCTT - +4 transfac_pro__M01658-lz-run-RunxA-RunxB 0 0.24486 5987.55 1 6 CACCTG AACCACA - +4 transfac_pro__M04913 1 0.24486 5987.55 1 6 CACCTG GCCCCTT - +4 predrem__nrMotif1265 -1 0.24486 5987.55 1 5 CACCTG ATCTTTG - +4 cisbp__M0297-Atf6-CrebB-kay 2 0.246262 6021.85 1 6 CACCTG GTGACGTAA + +4 cisbp__M0362-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-kay 2 0.246262 6021.85 1 6 CACCTG ATGACGTCA + +4 cisbp__M1423 3 0.246262 6021.85 1 6 CACCTG AGTGACCTG + +4 predrem__nrMotif1090 3 0.246262 6021.85 1 6 CACCTG TGACACATA + +4 predrem__nrMotif614 0 0.246262 6021.85 1 6 CACCTG GCCCTGTGA + +4 swissregulon__sacCer__YDR026c 2 0.246262 6021.85 1 6 CACCTG TTTACCCGG + +4 cisbp__M0176-crp 2 0.246262 6021.85 1 6 CACCTG ATCAGCTGG - +4 cisbp__M0210-amos-nau 1 0.246262 6021.85 1 6 CACCTG ACAGCTGTT - +4 predrem__nrMotif361 3 0.246262 6021.85 1 6 CACCTG CAGAACCCA - +4 predrem__nrMotif493 2 0.246262 6021.85 1 6 CACCTG TGAAACTTT - +4 predrem__nrMotif631 0 0.246262 6021.85 1 6 CACCTG AAACTCTTG - +4 taipale__NR2E1_full_AAAAGTCAA-dsf-tll 2 0.246262 6021.85 1 6 CACCTG TTGACTTTT - +4 transfac_pro__M09572 0 0.246262 6021.85 1 6 CACCTG TCACTTTTT - +4 flyfactorsurvey__Ets97D_SANGER_10_FBgn0004510-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt -1 0.246262 6021.85 1 5 CACCTG ACCGGAAGT + +4 predrem__nrMotif191 4 0.246262 6021.85 1 5 CACCTG AACATTCCT + +4 predrem__nrMotif2281 4 0.246262 6021.85 1 5 CACCTG ATTGTTCCT + +4 predrem__nrMotif848 5 0.246262 6021.85 1 4 CACCTG ATTCCCACC + +4 tfdimers__MD00104-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-Sox14 7 0.246489 6027.4 1 6 CACCTG TTTTTATTTCCTTCCTTTGTTTTTTT + +4 cisbp__M6294 5 0.247434 6050.5 1 6 CACCTG TCATAAAACTGTCA + +4 hocomoco__CLOCK_HUMAN.H11MO.0.C-Clk 4 0.247434 6050.5 1 6 CACCTG TGTTCACGTGTCTG + +4 neph__UW.Motif.0324 3 0.247434 6050.5 1 6 CACCTG GAAATCCAGATACA + +4 neph__UW.Motif.0484 2 0.247434 6050.5 1 6 CACCTG AGTTCTTTCTTTCC + +4 swissregulon__hs__HNF4A_NR2F1_2.p2-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-nej-svp-tll-usp 1 0.247434 6050.5 1 6 CACCTG TGACCTTTGACCCT + +4 cisbp__M2488 8 0.247434 6050.5 1 6 CACCTG AAAACCCATACATC - +4 cisbp__M3276-foxo-FoxP 8 0.247434 6050.5 1 6 CACCTG GTGTTGTTTACGTT - +4 hocomoco__TEF_HUMAN.H11MO.0.D-CG7786-Pdp1-gt 4 0.247434 6050.5 1 6 CACCTG CATTTACATAAACA - +4 hocomoco__ZN816_HUMAN.H11MO.1.C 0 0.247434 6050.5 1 6 CACCTG TGCATGTCCCCCTT - +4 neph__UW.Motif.0626 1 0.247434 6050.5 1 6 CACCTG TGGCCTCTGCCTTC - +4 taipale_cyt_meth__SKOR1_NWNNKKTAATTAAN_eDBD-fuss 6 0.247434 6050.5 1 6 CACCTG CTTAATTACCGTTT - +4 transfac_pro__M01717 3 0.247434 6050.5 1 6 CACCTG CGGTGCCTATATTC - +4 neph__UW.Motif.0337 6 0.247697 6056.93 1 6 CACCTG CAGTGGGTTCTGGTGG + +4 neph__UW.Motif.0672 7 0.247697 6056.93 1 6 CACCTG AAGAAAAAACATTTCA + +4 predrem__nrMotif1871-Brf-CTCF-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-vtd 3 0.247697 6056.93 1 6 CACCTG GCGCCCCTCCCCCCCC + +4 hdpi__USF1-Usf 0 0.248898 6086.3 1 6 CACCTG CACGTG + +4 transfac_pro__M03812-tgo 0 0.248898 6086.3 1 6 CACCTG TACGTG - +4 cisbp__M0285 4 0.249271 6095.43 1 6 CACCTG CAAATACGTAT + +4 cisbp__M4507-Max-Myc 4 0.249271 6095.43 1 6 CACCTG AGAGCACGTGG + +4 cisbp__M4542-Max-Myc 2 0.249271 6095.43 1 6 CACCTG AGCACGTGGCC + +4 cisbp__M4734-amos-da 2 0.249271 6095.43 1 6 CACCTG ACCATCTGCCG + +4 hocomoco__MYOD1_MOUSE.H11MO.1.A-Fer1-ac-ase-l(1)sc-nau-sc 1 0.249271 6095.43 1 6 CACCTG GCAGCTGTTCC + +4 idmmpmm__Kr-Kr-Kr-h2 1 0.249271 6095.43 1 6 CACCTG TAACCCTTTTG + +4 jaspar__MA0059.1-Max-Myc-Usf-tgo 3 0.249271 6095.43 1 6 CACCTG GAGCACGTGGT + +4 transfac_pro__M07379-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.249271 6095.43 1 6 CACCTG CACTTCCTGTT + +4 transfac_pro__M09303 3 0.249271 6095.43 1 6 CACCTG CATTACCGTTA + +4 c2h2_zfs__M4205-Kr-Kr-h2 1 0.249271 6095.43 1 6 CACCTG TAACCCTTTTG - +4 cisbp__M0363-Atf6-CrebA-Xbp1 3 0.249271 6095.43 1 6 CACCTG TGCCACGTCAT - +4 cisbp__M1136-achi-CrebB-hth-vis 4 0.249271 6095.43 1 6 CACCTG ATTTGACGTCA - +4 flyfactorsurvey__Kr_NAR_FBgn0001325-Kr-Kr-h2 1 0.249271 6095.43 1 6 CACCTG TAACCCTTTTG - +4 hocomoco__GATA1_HUMAN.H11MO.1.A-CoRest-CycT-GATAd-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.249271 6095.43 1 6 CACCTG TTCTTATCTGT - +4 hocomoco__GSC2_HUMAN.H11MO.0.D-Gsc 3 0.249271 6095.43 1 6 CACCTG CCTAATCCGCT - +4 taipale_cyt_meth__USF1_RNCAYGTGACN_FL_meth-Mitf-Usf 3 0.249271 6095.43 1 6 CACCTG GGTCACATGGT - +4 transfac_pro__M01284-Sox100B-SoxN 0 0.249271 6095.43 1 6 CACCTG GTCCTTTGTTT - +4 cisbp__M4713 6 0.249271 6095.43 1 5 CACCTG GATAAGCATCT + +4 transfac_pro__M06492 -2 0.249271 6095.43 1 4 CACCTG CCTGGCCAATC - +4 tfdimers__MD00234-cad-TfAP-2 14 0.2497 6105.92 1 6 CACCTG ATTTATTTTTTATTAGCCTTTTAAT - +4 cisbp__M6212-sima 2 0.250454 6124.36 1 6 CACCTG CCCACGTACGCAC + +4 scertf__harbison.NDD1-bs 1 0.250454 6124.36 1 6 CACCTG TTTCCCAATTGGG + +4 neph__UW.Motif.0184 3 0.250454 6124.36 1 6 CACCTG TGCTTTCTCTGCC - +4 neph__UW.Motif.0190 9 0.250454 6124.36 1 4 CACCTG AAAAAAAGCTTCC + +4 cisbp__M5248-ttk 5 0.251207 6142.76 1 6 CACCTG GCCAGGACCTCG + +4 cisbp__M6405 2 0.251207 6142.76 1 6 CACCTG CAGACATGCCCC + +4 flyfactorsurvey__ttk_FlyReg_FBgn0003870-ttk 5 0.251207 6142.76 1 6 CACCTG GCCAGGACCTTG + +4 homer__AAAAATACCRMA_Unknown4 5 0.251207 6142.76 1 6 CACCTG AAAAATACCAAA + +4 homer__SCCTAGCAACAG_Rfx5-CG9727-Rfx 6 0.251207 6142.76 1 6 CACCTG CCCTAGCAACAG + +4 swissregulon__hs__FOXA2.p3-FoxK-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.251207 6142.76 1 6 CACCTG TGTTTACTTAGG + +4 taipale_cyt_meth__MEIS2_TGACANNTGTCA_FL_meth-achi-hth-nau-vis 3 0.251207 6142.76 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__TGIF2LX_TGACANNTGTCA_FL_meth-achi-hth-nau-vis 3 0.251207 6142.76 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M06518 2 0.251207 6142.76 1 6 CACCTG TAATCCTGGAGA + +4 transfac_pro__M07325 6 0.251207 6142.76 1 6 CACCTG TCTGCTGACCTC + +4 transfac_pro__M09346 5 0.251207 6142.76 1 6 CACCTG AAAAATATCTTA + +4 cisbp__M1637 1 0.251207 6142.76 1 6 CACCTG TAACTTGGTACA - +4 cisbp__M1879-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-GATAe-grn-HDAC1-nej-pnr-slp2 4 0.251207 6142.76 1 6 CACCTG TGTTTACTTAGG - +4 cisbp__M3084-CrebB 6 0.251207 6142.76 1 6 CACCTG GGACGTCACCAA - +4 homer__AACAGCTGTTHN_E-box-HLH54F-amos-crp-dimm-nau 4 0.251207 6142.76 1 6 CACCTG CAAACAGCTGTT - +4 neph__UW.Motif.0078 5 0.251207 6142.76 1 6 CACCTG GAGAAATGCTTG - +4 neph__UW.Motif.0135 5 0.251207 6142.76 1 6 CACCTG AGCCCCGCCTCT - +4 taipale_cyt_meth__ELF2_NACCAGGAAGTN_FL_meth-aop-Eip74EF 0 0.251207 6142.76 1 6 CACCTG TACTTCCTGGTT - +4 taipale_cyt_meth__XBP1_NKMCACGTCAYN_FL-Atf6-CrebA-Xbp1 3 0.251207 6142.76 1 6 CACCTG GGTGACGTGGCC - +4 taipale_tf_pairs__ELF2_NATGCGGAAGTR_HT-Eip74EF 0 0.251207 6142.76 1 6 CACCTG CACTTCCGCATT - +4 tiffin__TIFDMEM0000015 6 0.251207 6142.76 1 6 CACCTG TAATCACAGCTG - +4 transfac_pro__M00632-srp 0 0.251207 6142.76 1 6 CACCTG TCCCTTTTATCT - +4 transfac_pro__M05446 6 0.251207 6142.76 1 6 CACCTG TCGGATAACCCA - +4 transfac_pro__M05638 1 0.251207 6142.76 1 6 CACCTG TCAACTGGACCA - +4 transfac_pro__M05806 6 0.251207 6142.76 1 6 CACCTG TCTTATTACCCA - +4 cisbp__M6080-EcR-eg-ham-Hr3-Hr78-kni-knrl-usp 7 0.251207 6142.76 1 5 CACCTG GGGTCATGACCC - +4 transfac_pro__M05512 7 0.251207 6142.76 1 5 CACCTG GCCCCCCCACCT - +4 transfac_pro__M05563 7 0.251207 6142.76 1 5 CACCTG GCCGCCGGACCA - +4 transfac_pro__M05651 7 0.251207 6142.76 1 5 CACCTG TCGCCACAACCA - +4 transfac_pro__M05916-CG31612 7 0.251207 6142.76 1 5 CACCTG GCTCTTTCACCA - +4 transfac_pro__M06200 7 0.251207 6142.76 1 5 CACCTG GCTTTCGGACCA - +4 transfac_pro__M06323 7 0.251207 6142.76 1 5 CACCTG GATTCTTAACCC - +4 transfac_pro__M08884-gcm-gcm2 -1 0.251207 6142.76 1 5 CACCTG ACCCGCATGAAC - +4 transfac_pro__M06765 8 0.251207 6142.76 1 4 CACCTG TCGCTTATTACC - +4 hocomoco__PO3F2_HUMAN.H11MO.0.A-vvl 0 0.251623 6152.94 1 6 CACCTG TTCATGCATATTCATTC + +4 taipale_tf_pairs__TEAD4_DLX2_NRCATTCNNNNYAATTN_CAP_repr-sd 0 0.251623 6152.94 1 6 CACCTG CACATTCCACCCAATTA + +4 transfac_pro__M01352-bap-vnd 7 0.251623 6152.94 1 6 CACCTG TTTTAAGTACTTAAATT + +4 transfac_pro__M01372-scro-tin-vnd 5 0.251623 6152.94 1 6 CACCTG ATAACCACTTGAAAATT + +4 transfac_pro__M01440-Awh-CG18599-E5-ems-en-eve-inv-pb-unpg 1 0.251623 6152.94 1 6 CACCTG ACCCCTAATTAGCGGTG + +4 transfac_pro__M05599-klu 11 0.251623 6152.94 1 6 CACCTG TGCGGGGGGGTCACCTA + +4 cisbp__M4633-bs 3 0.251623 6152.94 1 6 CACCTG AGTTGCCTTATATGGTC - +4 hocomoco__THB_MOUSE.H11MO.0.D-ERR-EcR 1 0.251623 6152.94 1 6 CACCTG TGTCCTCAACTGACCTT - +4 jaspar__MA0851.1-FoxK-FoxP-croc-fd59A-fkh-foxo-slp2 9 0.251623 6152.94 1 6 CACCTG GTGTTTGTTTACTTTTT - +4 cisbp__M6104 -1 0.251623 6152.94 1 5 CACCTG ACATGTCATAGACATGT + +4 tfdimers__MD00144 15 0.251625 6153 1 6 CACCTG TTATCAGACATGTCTCAACTTGCCTTTT + +4 tfdimers__MD00427-ct-Pur-alpha 9 0.252399 6171.9 1 6 CACCTG TACTTCATCGATCTGCCCCTTTTT + +4 tfdimers__MD00070-Pur-alpha 9 0.252399 6171.9 1 6 CACCTG TTTTTGTTTTATCTGTCCCTTTCA - +4 tfdimers__MD00163-EcR-usp 8 0.252399 6171.9 1 6 CACCTG TTTTCCCTGTCCTTATCTGTTTTC - +4 hocomoco__MYOD1_HUMAN.H11MO.0.A-Fer1-nau 1 0.254359 6219.85 1 6 CACCTG GCAGCTGTTCCTGCC + +4 neph__UW.Motif.0360-amos 4 0.254359 6219.85 1 6 CACCTG AAGCCAGCTGGCTTC + +4 transfac_pro__M00481 2 0.254359 6219.85 1 6 CACCTG GGTACAGGGTGTTCT + +4 transfac_pro__M02884-Myb 4 0.254359 6219.85 1 6 CACCTG CGACCAACTGCCGTG + +4 transfac_pro__M09341 0 0.254359 6219.85 1 6 CACCTG AACCTTATCTTCATC + +4 hocomoco__COE1_HUMAN.H11MO.0.A-kn 2 0.254359 6219.85 1 6 CACCTG GGTCCCTGGGGACTT - +4 swissregulon__sacCer__YAP6 2 0.254359 6219.85 1 6 CACCTG CTTACGTAATCAGAC - +4 taipale_tf_pairs__GCM2_ELK1_NNRNGGGCGGAARTN_CAP-gcm-gcm2 0 0.254359 6219.85 1 6 CACCTG CACTTCCGCCCGCAT - +4 cisbp__M6218-EcR-eg-ERR-kni-knrl 10 0.254359 6219.85 1 5 CACCTG AGGTCACCGTGACCC + +4 flyfactorsurvey__ftz-f1_FlyReg_FBgn0001078-ftz-f1 5 0.254397 6220.77 1 6 CACCTG GCGGTGACCTTCGGACTG + +4 hocomoco__OLIG2_HUMAN.H11MO.0.B-Fer1-HLH3B-amos 1 0.254397 6220.77 1 6 CACCTG CCAGCTGTTTCCCTTCTG + +4 hocomoco__PTF1A_HUMAN.H11MO.0.B-Fer1-HLH3B-Su(H)-dimm-nau 1 0.254397 6220.77 1 6 CACCTG CCAGCTGCCCCCTTTCCC + +4 swissregulon__hs__TFAP4.p2-crp 5 0.254397 6220.77 1 6 CACCTG AGAGCCAGCTGCGGCCAG + +4 cisbp__M4569-Bdp1-Brf-CG17209-Hsf-SREBP-Tbp 8 0.254397 6220.77 1 6 CACCTG GGGATTCGAACCCGGGAC - +4 taipale_tf_pairs__HOXB13_TBX3_NNNRTAAANNTNACACYN_CAP_repr-bi 13 0.254397 6220.77 1 5 CACCTG CCAATAAAAGTCACACCT + +4 hocomoco__RARG_HUMAN.H11MO.0.B-ERR-EcR-eg-kni-knrl 13 0.254397 6220.77 1 5 CACCTG CCCAGGTCACTCTGACCT - +4 taipale_tf_pairs__MYBL1_MAX_YAACGGNNNNNNNNNNNCACGTG_CAP_repr-Max-Myb 0 0.254531 6224.04 1 6 CACCTG TAACGGTCGTCGCGGGGCACGTG + +4 cisbp__M0239-Clk 1 0.254621 6226.26 1 6 CACCTG GCACGTGT + +4 cisbp__M0252-Max-Usf 1 0.254621 6226.26 1 6 CACCTG CCACGTGC + +4 cisbp__M1278 2 0.254621 6226.26 1 6 CACCTG ATTACCGC + +4 cisbp__M4984-Clk-E2f1-gce-Max-Myc-tgo-Usf 2 0.254621 6226.26 1 6 CACCTG GCCACGTG + +4 elemento__CACACGTG 2 0.254621 6226.26 1 6 CACCTG CACACGTG + +4 elemento__CACGTGAC-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 0 0.254621 6226.26 1 6 CACCTG CACGTGAC + +4 elemento__CACTTGGC 0 0.254621 6226.26 1 6 CACCTG CACTTGGC + +4 jaspar__MA0372.1-Kdm4A-Kdm4B 1 0.254621 6226.26 1 6 CACCTG ACCCCTAA + +4 jaspar__MA1033.1-Met 1 0.254621 6226.26 1 6 CACCTG ACACGTGT + +4 stark__WCACGTGC 1 0.254621 6226.26 1 6 CACCTG ACACGTGC + +4 taipale_cyt_meth__LHX1_NTCGTTAN_eDBD_meth-Lim1 0 0.254621 6226.26 1 6 CACCTG CTCGTTAC + +4 transfac_pro__M01054-E(spl)m3-HLH-E(spl)mdelta-HLH 1 0.254621 6226.26 1 6 CACCTG GCACGTGC + +4 transfac_pro__M09574 0 0.254621 6226.26 1 6 CACCTG CACCGACA + +4 cisbp__M0072 0 0.254621 6226.26 1 6 CACCTG CACCGACA - +4 cisbp__M1131 2 0.254621 6226.26 1 6 CACCTG TTTACATG - +4 cisbp__M1207 1 0.254621 6226.26 1 6 CACCTG TGACATGT - +4 cisbp__M2177-Kdm4A-Kdm4B 1 0.254621 6226.26 1 6 CACCTG ACCCCTAA - +4 cisbp__M5583-tup 1 0.254621 6226.26 1 6 CACCTG GCACTTAA - +4 elemento__AACATGTG 0 0.254621 6226.26 1 6 CACCTG CACATGTT - +4 elemento__CAAGTGCA 2 0.254621 6226.26 1 6 CACCTG TGCACTTG - +4 elemento__CATGTGCA 2 0.254621 6226.26 1 6 CACCTG TGCACATG - +4 flyfactorsurvey__Clk_cyc_SANGER_5_FBgn0023076-Clk-Met-cyc 1 0.254621 6226.26 1 6 CACCTG TCACGTGG - +4 homer__NTCAGTYG_Initiator 0 0.254621 6226.26 1 6 CACCTG CGACTGAA - +4 jaspar__MA1007.1 0 0.254621 6226.26 1 6 CACCTG CACCGACA - +4 predrem__nrMotif2578 1 0.254621 6226.26 1 6 CACCTG ACACTTAG - +4 cisbp__M2187 3 0.254621 6226.26 1 5 CACCTG CATTACGT + +4 hdpi__SNRPB2 3 0.254621 6226.26 1 5 CACCTG CAGCACAA + +4 predrem__nrMotif234 -1 0.254621 6226.26 1 5 CACCTG TCCTCATT + +4 predrem__nrMotif769 -1 0.254621 6226.26 1 5 CACCTG AACTTCAG + +4 cisbp__M0817-gcm-gcm2 -1 0.254621 6226.26 1 5 CACCTG ACCCGCAT - +4 elemento__AGGAGCTG 3 0.254621 6226.26 1 5 CACCTG CAGCTCCT - +4 elemento__AGGAGGAG 3 0.254621 6226.26 1 5 CACCTG CTCCTCCT - +4 jaspar__MA0382.1 3 0.254621 6226.26 1 5 CACCTG CATTACGT - +4 jaspar__MA0917.1-gcm-gcm2 -1 0.254621 6226.26 1 5 CACCTG ACCCGCAT - +4 swissregulon__sacCer__SKO1 3 0.254621 6226.26 1 5 CACCTG CATTACGT - +4 elemento__CCTCCCAA -2 0.254621 6226.26 1 4 CACCTG CCTCCCAA + +4 elemento__CCTCCCTC -2 0.254621 6226.26 1 4 CACCTG CCTCCCTC + +4 elemento__CCTCCTCC -2 0.254621 6226.26 1 4 CACCTG CCTCCTCC + +4 elemento__CATGGAGG -2 0.254621 6226.26 1 4 CACCTG CCTCCATG - +4 tfdimers__MD00020 14 0.255322 6243.4 1 6 CACCTG TTTTAGTTAATTATTAACTGACACTAATAT - +4 cisbp__M0316-CG7786-CrebB-gt-Pdp1-vri 3 0.255612 6250.47 1 6 CACCTG TATTACGTAA + +4 cisbp__M1279 1 0.255612 6250.47 1 6 CACCTG TGTCCGGTCA + +4 cisbp__M1707 3 0.255612 6250.47 1 6 CACCTG TTCATCCGGA + +4 cisbp__M5614-Max-Mnt-Myc 2 0.255612 6250.47 1 6 CACCTG ACCACGTGCT + +4 cisbp__M6457-Bgb-Bro-CG9650-lz-MTA1-like-nej-run-RunxA-RunxB 1 0.255612 6250.47 1 6 CACCTG TAACCACAGA + +4 fantom__motif29_TAGCTCGGCT 0 0.255612 6250.47 1 6 CACCTG TAGCTCGGCT + +4 flyfactorsurvey__tgo_trh_SANGER_5_FBgn0015014-sim-tgo 1 0.255612 6250.47 1 6 CACCTG GTACGTGACC + +4 homer__ATTTCCTGTN_EWS_ERG-fusion-Ets97D 2 0.255612 6250.47 1 6 CACCTG ATTTCCTGTG + +4 homer__TCACGTGAYH_Cbf1-Clk-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 1 0.255612 6250.47 1 6 CACCTG TCACGTGACC + +4 predrem__nrMotif2135 2 0.255612 6250.47 1 6 CACCTG TCCAGCTGTT + +4 scertf__spivak.YAP6-gt 1 0.255612 6250.47 1 6 CACCTG TTACGTAAAC + +4 taipale__TFEC_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.255612 6250.47 1 6 CACCTG ATCACGTGAC + +4 taipale_cyt_meth__NKX3-1_NCCACTTAAN_eDBD-bap-Hmx 2 0.255612 6250.47 1 6 CACCTG ACCACTTAAC + +4 transfac_pro__M07927-nom-salm-salr 3 0.255612 6250.47 1 6 CACCTG ACCCACCCGA + +4 transfac_pro__M08948-pan 0 0.255612 6250.47 1 6 CACCTG TTCCTTTGAT + +4 transfac_public__M00176-crp 2 0.255612 6250.47 1 6 CACCTG CTCAGCTGGT + +4 transfac_public__M00187-Usf 2 0.255612 6250.47 1 6 CACCTG GTCACGTGGC + +4 cisbp__M0187-bigmax-Mitf-Mondo-SREBP-Usf 2 0.255612 6250.47 1 6 CACCTG ATCACGCGAT - +4 cisbp__M0414-klu-sr 1 0.255612 6250.47 1 6 CACCTG CCGCCCACGC - +4 cisbp__M0659 0 0.255612 6250.47 1 6 CACCTG TTACTTTTTG - +4 cisbp__M0737-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-nej-slp1-slp2 4 0.255612 6250.47 1 6 CACCTG TGTTTACATA - +4 hocomoco__ZFX_HUMAN.H11MO.0.A 3 0.255612 6250.47 1 6 CACCTG CGGGGCCTGG - +4 homer__AAAGTAAACA_FOXA1_GSE26831-FoxK-FoxP-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.255612 6250.47 1 6 CACCTG TGTTTACTTA - +4 homer__BAACAGCTGT_Myf5-Fer3-HLH54F-nau 1 0.255612 6250.47 1 6 CACCTG ACAGCTGTTA - +4 predrem__nrMotif2315 1 0.255612 6250.47 1 6 CACCTG CCTCCTGACC - +4 taipale__MAX_DBD_NNCACGTGNN_repr-Max-Mnt-Myc 2 0.255612 6250.47 1 6 CACCTG AGCACGTGGT - +4 transfac_pro__M03868-gem 0 0.255612 6250.47 1 6 CACCTG TCCCAGTCAA - +4 transfac_pro__M05554-btd-cbt-Sp1-Spps 0 0.255612 6250.47 1 6 CACCTG GACCCGCCCT - +4 transfac_pro__M07526 4 0.255612 6250.47 1 6 CACCTG GGCCGACATG - +4 transfac_pro__M07864-CG8319-Mettl14 4 0.255612 6250.47 1 6 CACCTG CCGTCACTTT - +4 yetfasco__YKL015W_2223 2 0.255612 6250.47 1 6 CACCTG TTTCCCGAGG - +4 predrem__nrMotif2204 -1 0.255612 6250.47 1 5 CACCTG CCCTGCCCAA + +4 taipale_cyt_meth__FOXJ3_NYGTAAACAN_eDBD_meth-croc-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.255612 6250.47 1 5 CACCTG TTGTTTACGT - +4 predrem__nrMotif991 -2 0.255612 6250.47 1 4 CACCTG GCTGTCAGCA + +4 tfdimers__MD00335-scro 7 0.255791 6254.86 1 6 CACCTG TTTTTTGTTCTTGTTTGTTTATTTTTT - +4 taipale_tf_pairs__GCM1_CEBPB_MTRSGGGNNNNNNTTRCGYAAN_CAP-gcm-gcm2 13 0.256039 6260.93 1 6 CACCTG ATTGCGCAATACCCGCCCGCAT - +4 taipale_tf_pairs__ETV7_TBX21_NSCGGAARNNNNNNTCACACNN_CAP_repr-aop 17 0.256039 6260.93 1 5 CACCTG CCCGGAAACAGACTTCACACCT + +4 transfac_pro__M01007-bs 3 0.256126 6263.06 1 6 CACCTG CATCTCCTTATATGGCCAT + +4 cisbp__M2185 0 0.256471 6271.49 1 6 CACCTG CTCCGGA + +4 jaspar__MA0380.1 0 0.256471 6271.49 1 6 CACCTG CTCCGGA + +4 predrem__nrMotif1348 0 0.256471 6271.49 1 6 CACCTG CATCTTT + +4 predrem__nrMotif1622 0 0.256471 6271.49 1 6 CACCTG GAACTGT + +4 predrem__nrMotif1747 0 0.256471 6271.49 1 6 CACCTG GTCCTGA + +4 predrem__nrMotif2643 0 0.256471 6271.49 1 6 CACCTG TCCCTAT + +4 transfac_pro__M01958 0 0.256471 6271.49 1 6 CACCTG CTCCGGA + +4 yetfasco__YJL089W_573 0 0.256471 6271.49 1 6 CACCTG CTCCGGA + +4 cisbp__M0499 1 0.256471 6271.49 1 6 CACCTG CCCCCCC - +4 swissregulon__sacCer__MSN4-CG10348-CG13296-ham 0 0.256471 6271.49 1 6 CACCTG CCCCTTA - +4 predrem__nrMotif1717 -1 0.256471 6271.49 1 5 CACCTG ACATGAC + +4 predrem__nrMotif279 2 0.256471 6271.49 1 5 CACCTG CTGTCCT + +4 predrem__nrMotif389 -1 0.256471 6271.49 1 5 CACCTG TCCTTTT + +4 predrem__nrMotif238 -1 0.256471 6271.49 1 5 CACCTG AACTTTT - +4 scertf__badis.SWI5-CG9609 -1 0.256471 6271.49 1 5 CACCTG ACCAGCA - +4 predrem__nrMotif158 -2 0.256471 6271.49 1 4 CACCTG CCTGGAG + +4 hocomoco__TGIF1_HUMAN.H11MO.0.A-achi-hth-vis -2 0.256471 6271.49 1 4 CACCTG GCTGTCA - +4 predrem__nrMotif1274 3 0.256471 6271.49 1 4 CACCTG AAGAACC - +4 transfac_pro__M09311 9 0.256859 6280.97 1 6 CACCTG CAACTACTCCACCAACCCCCA + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m5 7 0.256916 6282.37 1 6 CACCTG TGGCTGTTATCTGCCCAGGC + +4 dbcorrdb__BRF1__ENCSR000DNW_1__m1-Bdp1-Brf-CG17209-Hsf-SREBP-Tbp 8 0.256916 6282.37 1 6 CACCTG GGGATTCGAACCCGGGACCT + +4 dbcorrdb__CHD1__ENCSR000EBU_1__m1-Chd1-Jra-nej-SREBP 8 0.256916 6282.37 1 6 CACCTG CCGGACCGAACCAATTGGGG + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m7-brm 9 0.256916 6282.37 1 6 CACCTG CTGGAGAATGTCCTTGAGGC + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m10-Taf7 3 0.256916 6282.37 1 6 CACCTG GAGCAACTGCTACCAAAAAG + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m8-Taf7 0 0.256916 6282.37 1 6 CACCTG CAACTAACTAAAGAAAACCG + +4 taipale_tf_pairs__TEAD4_CLOCK_NCACGTGNNNNNNNCATWCC_CAP-Clk-sd 1 0.256916 6282.37 1 6 CACCTG ACACGTGTAATCCACATTCC + +4 dbcorrdb__RFX5__ENCSR000ECF_1__m4 14 0.256916 6282.37 1 6 CACCTG GTGACACATGACGCAACCTG - +4 taipale_tf_pairs__ETV5_CLOCK_NCACGTGNNNNNSCGGAWRN_CAP_repr-Clk-Ets96B 13 0.256916 6282.37 1 6 CACCTG ACTTCCGGCCCAACACGTGC - +4 taipale_tf_pairs__GCM1_FIGLA_CAGCTGNNNNNNNNTGCGGG_CAP-gcm-gcm2 14 0.256916 6282.37 1 6 CACCTG CCCGCATACCCCACCACCTG - +4 cisbp__M0223-E2f1-Max-Myc-Sap30 2 0.257763 6303.07 1 6 CACCTG ACCACGTGG + +4 cisbp__M1722 2 0.257763 6303.07 1 6 CACCTG GTTTCCGGG + +4 cisbp__M6056-dsf-tll 2 0.257763 6303.07 1 6 CACCTG TTGACTTTT + +4 cisbp__M6402-ovo 2 0.257763 6303.07 1 6 CACCTG TGTAACTGT + +4 flyfactorsurvey__HLHm3_SANGER_5_FBgn0002609-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 0 0.257763 6303.07 1 6 CACCTG CACGTGCCA + +4 hocomoco__OVOL1_HUMAN.H11MO.0.C-ovo 2 0.257763 6303.07 1 6 CACCTG TGTAACTGT + +4 jaspar__MA0054.1 0 0.257763 6303.07 1 6 CACCTG TAACCGTTT + +4 predrem__nrMotif1008 3 0.257763 6303.07 1 6 CACCTG CACAACCCA + +4 predrem__nrMotif1604 3 0.257763 6303.07 1 6 CACCTG CAGGACTTG + +4 predrem__nrMotif2009 0 0.257763 6303.07 1 6 CACCTG GAGCTCAAA + +4 predrem__nrMotif2183 2 0.257763 6303.07 1 6 CACCTG CTCACCACT + +4 predrem__nrMotif355 1 0.257763 6303.07 1 6 CACCTG ATTCCTGAA + +4 predrem__nrMotif438 0 0.257763 6303.07 1 6 CACCTG TTCCTTAAA + +4 predrem__nrMotif467 1 0.257763 6303.07 1 6 CACCTG TTCCCTGGT + +4 predrem__nrMotif682 3 0.257763 6303.07 1 6 CACCTG CTGTGCCTG + +4 predrem__nrMotif800 1 0.257763 6303.07 1 6 CACCTG ATCCCTGGG + +4 transfac_pro__M04698-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Sin3A-Taf1 0 0.257763 6303.07 1 6 CACCTG CACTTCCGG + +4 cisbp__M2133 3 0.257763 6303.07 1 6 CACCTG AATTACATG - +4 predrem__nrMotif1239 1 0.257763 6303.07 1 6 CACCTG TTTCCTGTT - +4 predrem__nrMotif1313 0 0.257763 6303.07 1 6 CACCTG AAACTGCAT - +4 predrem__nrMotif1399 1 0.257763 6303.07 1 6 CACCTG AAACCATGA - +4 predrem__nrMotif2019 3 0.257763 6303.07 1 6 CACCTG AGACATCTT - +4 predrem__nrMotif2605 1 0.257763 6303.07 1 6 CACCTG TCCCCTAAG - +4 predrem__nrMotif486 3 0.257763 6303.07 1 6 CACCTG CTGAACTTC - +4 predrem__nrMotif539 0 0.257763 6303.07 1 6 CACCTG AATCTCCCT - +4 predrem__nrMotif629 0 0.257763 6303.07 1 6 CACCTG TTCCTGTCT - +4 predrem__nrMotif863 1 0.257763 6303.07 1 6 CACCTG TTGCCTGAT - +4 transfac_pro__M01657-ci-lmd-opa-sug 2 0.257763 6303.07 1 6 CACCTG ACCACCCAC - +4 cisbp__M4953-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.257763 6303.07 1 5 CACCTG ACCGGAAGT + +4 predrem__nrMotif1104 4 0.257763 6303.07 1 5 CACCTG CATTTCCCT + +4 predrem__nrMotif2500 4 0.257763 6303.07 1 5 CACCTG TCATTTCCT + +4 predrem__nrMotif345 4 0.257763 6303.07 1 5 CACCTG CTGCTTCCT + +4 predrem__nrMotif584 4 0.257763 6303.07 1 5 CACCTG CAAGGACCA + +4 predrem__nrMotif684 4 0.257763 6303.07 1 5 CACCTG TCTGTAGCT + +4 cisbp__M1700 4 0.257763 6303.07 1 5 CACCTG CGTTGACCT - +4 predrem__nrMotif608 4 0.257763 6303.07 1 5 CACCTG CACTCTCCC - +4 transfac_pro__M05240 5 0.257763 6303.07 1 4 CACCTG GGTTAAACC - +4 tfdimers__MD00289-ara-caup-mirr 17 0.258968 6332.55 1 6 CACCTG ATATTTGGTTAATGATTAACATGTTAATTAATTT + +4 cisbp__M5494 0 0.25935 6341.88 1 6 CACCTG TACGTGGTTACGTT + +4 taipale_cyt_meth__SKOR1_NWNNKKTAATTAAN_eDBD_meth-fuss 0 0.25935 6341.88 1 6 CACCTG TAACTGTAATTAAC + +4 taipale_tf_pairs__TEAD4_FIGLA_GGAATKNNCASSTG_CAP_repr-sd 8 0.25935 6341.88 1 6 CACCTG GGAATGTACAGCTG + +4 transfac_pro__M00797-sima-tgo 3 0.25935 6341.88 1 6 CACCTG GCGTACGTGCGGCA + +4 transfac_pro__M01065 4 0.25935 6341.88 1 6 CACCTG TGCTGACGTGGGAG + +4 taipale__GMEB2_DBD_WRCGTAACCACGYN_repr 0 0.25935 6341.88 1 6 CACCTG TACGTGGTTACGTT - +4 taipale_tf_pairs__FLI1_FOXI1_RTAAACMGGAARYN_CAP 3 0.25935 6341.88 1 6 CACCTG CACTTCCTGTTTAC - +4 tfdimers__MD00121-EcR-usp 8 0.259521 6346.08 1 6 CACCTG TTTTCCCTGTCCTTTGTTTTCTTAAT - +4 factorbook__B-Box-Bdp1-Brf-CG17209-Hsf-SREBP 8 0.259844 6353.97 1 6 CACCTG GGGATTCGAACCCGCG + +4 neph__UW.Motif.0548 8 0.259844 6353.97 1 6 CACCTG AAAACTGAAAAATTTC + +4 neph__UW.Motif.0669 1 0.259844 6353.97 1 6 CACCTG AAGCCCGGGGGCTGGG + +4 transfac_pro__M03119-crp 6 0.259844 6353.97 1 6 CACCTG TTTGATCAGCTGATCG + +4 swissregulon__hs__HAND1_2.p2-Hand 9 0.259844 6353.97 1 6 CACCTG AATGCCAGACACCAAT - +4 swissregulon__hs__ZNF148.p2-CG42741 3 0.259844 6353.97 1 6 CACCTG CCCCACCCAGGGGCTG - +4 taipale__POU6F2_DBD_WTAATKAGCTMATTAW-CG34367-E5-ems-en-gsb-gsb-n-inv-pdm3-prd-unpg 5 0.259844 6353.97 1 6 CACCTG TTAATTAGCTCATTAA - +4 taipale_cyt_meth__MAFA_NYGCTGAYGTCAGCRN_eDBD-CrebA-CrebB-maf-S 5 0.259844 6353.97 1 6 CACCTG TTGCTGACGTCAGCAA - +4 taipale_cyt_meth__MAF_NYGCTGAYGTCAGCRN_FL-CrebA-maf-S 5 0.259844 6353.97 1 6 CACCTG ATGCTGACGTCAGCAA - +4 transfac_pro__M07249-CTCF-SMC3-usp-vtd 6 0.259844 6353.97 1 6 CACCTG CACTGCCCCCTAGTGG - +4 transfac_pro__M07851-Dll-dve-nub-pdm2-pdm3-vvl -1 0.259844 6353.97 1 5 CACCTG ACCTAATTTGCATAAT - +4 hdpi__MYF6-nau 0 0.260618 6372.89 1 6 CACCTG CATCTG - +4 hdpi__USF2-Max-Usf 0 0.260618 6372.89 1 6 CACCTG CACGTG - +4 transfac_pro__M02050 0 0.260618 6372.89 1 6 CACCTG TGCCAA - +4 hdpi__HHAT-rasp 1 0.260618 6372.89 1 5 CACCTG CAATCT - +4 fantom__motif149_CAAGCTGTACA 1 0.260995 6382.11 1 6 CACCTG CAAGCTGTACA + +4 predrem__nrMotif1338 0 0.260995 6382.11 1 6 CACCTG TTCCTTCATCT + +4 predrem__nrMotif2147 4 0.260995 6382.11 1 6 CACCTG GGCCGGCCTGG + +4 swissregulon__sacCer__USV1 3 0.260995 6382.11 1 6 CACCTG TTCCCCCTGAA + +4 transfac_pro__M07297 3 0.260995 6382.11 1 6 CACCTG CCCTCCCTCCC + +4 transfac_pro__M09502 3 0.260995 6382.11 1 6 CACCTG AGCAACTTGCA + +4 cisbp__M2300-ac-ase-l(1)sc-nau-sc 3 0.260995 6382.11 1 6 CACCTG CTGCAGCTGTC - +4 cisbp__M2317-ac-ase-l(1)sc-nau-sc 3 0.260995 6382.11 1 6 CACCTG CTGCAGCTGTT - +4 cisbp__M6221-Eip74EF-Ets97D 4 0.260995 6382.11 1 6 CACCTG CCACTTCCCGC - +4 hocomoco__CR3L1_HUMAN.H11MO.0.D-Atf6-Clk-CrebA 3 0.260995 6382.11 1 6 CACCTG TGCCACGTGGC - +4 hocomoco__GATA1_MOUSE.H11MO.1.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.260995 6382.11 1 6 CACCTG CTCTTATCTGC - +4 jaspar__MA0500.1-ac-ase-l(1)sc-nau-sc 3 0.260995 6382.11 1 6 CACCTG CTGCAGCTGTC - +4 jaspar__MA0521.1-ac-ase-l(1)sc-nau-sc 3 0.260995 6382.11 1 6 CACCTG CTGCAGCTGTT - +4 neph__UW.Motif.0157 3 0.260995 6382.11 1 6 CACCTG GAAAAAATTCT - +4 scertf__pachkov.INO4 4 0.260995 6382.11 1 6 CACCTG TTTTCACATGC - +4 swissregulon__sacCer__INO2 4 0.260995 6382.11 1 6 CACCTG TTTTCACATGC - +4 transfac_pro__M01197 3 0.260995 6382.11 1 6 CACCTG TACTTCCTTAT - +4 transfac_pro__M09288 5 0.260995 6382.11 1 6 CACCTG CCAACAAACTT - +4 transfac_pro__M09319 1 0.260995 6382.11 1 6 CACCTG CCACCAACCAC - +4 transfac_pro__M05339-ind-pb -1 0.260995 6382.11 1 5 CACCTG TCCTTATTAAA + +4 cisbp__M1859-en-inv 6 0.260995 6382.11 1 5 CACCTG GAACACTACTT - +4 flyfactorsurvey__Fer1_SANGER_5_FBgn0037475-Fer1-nau 4 0.262374 6415.84 1 6 CACCTG ACGACAGCTGACG + +4 neph__UW.Motif.0312 0 0.262374 6415.84 1 6 CACCTG AGCATCTGCTGTG + +4 taipale_tf_pairs__GCM1_FOXI1_TGTTGANGCGGGN_CAP-gcm-gcm2 -1 0.262374 6415.84 1 5 CACCTG ACCCGCATCAACA - +4 taipale_tf_pairs__TEAD4_TBX21_ANGTGTGAATWCY_CAP_repr-sd 8 0.262374 6415.84 1 5 CACCTG GGAATTCACACCT - +4 tfdimers__MD00574-Stat92E 12 0.26277 6425.51 1 6 CACCTG TCTATCATTTCCCATCTGTCCCCTT + +4 cisbp__M0349-CG7786-Pdp1-gt-vri 5 0.263068 6432.81 1 6 CACCTG ATTATTACGTAA + +4 homer__CTTGTTTACATA_Foxa2-FoxK-FoxP-bin-croc-fd96Ca-fd96Cb-fkh-foxo 6 0.263068 6432.81 1 6 CACCTG CTTGTTTACATA + +4 neph__UW.Motif.0076 0 0.263068 6432.81 1 6 CACCTG TTCCTGGCAGCA + +4 neph__UW.Motif.0326 2 0.263068 6432.81 1 6 CACCTG CTGCCCTGTGCC + +4 neph__UW.Motif.0499 5 0.263068 6432.81 1 6 CACCTG TCATTTTTCTCA + +4 taipale_cyt_meth__TGIF2LX_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.263068 6432.81 1 6 CACCTG TGACAGCTGTCA + +4 flyfactorsurvey__her_SOLEXA_F2-4-her 4 0.263068 6432.81 1 6 CACCTG CTCATAATTGCG - +4 hocomoco__NGN2_HUMAN.H11MO.0.D-amos-tap 2 0.263068 6432.81 1 6 CACCTG GCCATCTGCTCC - +4 taipale__ELF1_DBD_AACCCGGAAGTN-aop-Eip74EF-Ets21C 0 0.263068 6432.81 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__ATF7_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.263068 6432.81 1 6 CACCTG GATGACATCATC - +4 taipale_cyt_meth__ELF2_NACCCGGAAGTN_eDBD-aop-Eip74EF-Ets96B-nej 0 0.263068 6432.81 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__ELF5_NANNAGGAAGTN_FL_meth-Eip74EF 0 0.263068 6432.81 1 6 CACCTG CACTTCCTCCTT - +4 taipale_cyt_meth__FOXA1_NWRTGTAMAYAN_eDBD_repr-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxP-slp2 5 0.263068 6432.81 1 6 CACCTG TTGTTTACACAA - +4 taipale_cyt_meth__MSC_NRACAGCTGTYN_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.263068 6432.81 1 6 CACCTG CAACAGCTGTTA - +4 taipale_cyt_meth__MYOG_CGTCANNTGTYN_FL-amos-Fer1-HLH54F-nau 3 0.263068 6432.81 1 6 CACCTG CAACAGCTGTCG - +4 taipale_cyt_meth__PRDM1_NRGNGAAAGTGN_eDBD_meth-Blimp-1 1 0.263068 6432.81 1 6 CACCTG CCACTTTCACTT - +4 taipale_cyt_meth__SPIB_RWWGSGGAAGTN_eDBD_repr-Eip74EF 0 0.263068 6432.81 1 6 CACCTG CACTTCCGCATT - +4 tiffin__TIFDMEM0000116 6 0.263068 6432.81 1 6 CACCTG CAGTGTGACCGT - +4 transfac_pro__M04924-kn 3 0.263068 6432.81 1 6 CACCTG AGCTCCCCAGGG - +4 transfac_pro__M06077 5 0.263068 6432.81 1 6 CACCTG GGTTCTGCCTGC - +4 transfac_pro__M06119 6 0.263068 6432.81 1 6 CACCTG TATACTTTCCTG - +4 transfac_pro__M06195 6 0.263068 6432.81 1 6 CACCTG GCGTCTCGCCTC - +4 transfac_pro__M06366 6 0.263068 6432.81 1 6 CACCTG TCCTCTAACCAG - +4 transfac_pro__M06713-opa 6 0.263068 6432.81 1 6 CACCTG GATGACCACCCA - +4 transfac_pro__M06729 0 0.263068 6432.81 1 6 CACCTG CAACTTCCCCAG - +4 transfac_pro__M05631 7 0.263068 6432.81 1 5 CACCTG TCTGCCCTACCG - +4 transfac_pro__M05633 7 0.263068 6432.81 1 5 CACCTG TCGGCATGACCA - +4 transfac_pro__M05950 7 0.263068 6432.81 1 5 CACCTG GGAACTACACCG - +4 transfac_pro__M06091 7 0.263068 6432.81 1 5 CACCTG TCTTTTTTATCG - +4 transfac_pro__M06394 7 0.263068 6432.81 1 5 CACCTG TCCGATCAACCA - +4 transfac_pro__M06486 7 0.263068 6432.81 1 5 CACCTG GCCTTAGAACCC - +4 taipale__CTCF_full_NGCGCCMYCTAGYGGTN_repr-CTCF-SMC3-usp-vtd 5 0.264021 6456.11 1 6 CACCTG AGCGCCACCTAGTGGTA + +4 transfac_pro__M01377-ara-caup-mirr 4 0.264021 6456.11 1 6 CACCTG AAAATACATGTAAAAAT + +4 transfac_pro__M01485-ara-caup-mirr 4 0.264021 6456.11 1 6 CACCTG AATATACATGTAATACT + +4 cisbp__M5331-CTCF-SMC3-usp-vtd 5 0.264021 6456.11 1 6 CACCTG AGCGCCACCTAGTGGTA - +4 transfac_pro__M05453 0 0.264021 6456.11 1 6 CACCTG ATCCTGTTTTCAACCAC - +4 taipale__Tp53_DBD_ACAWGTCNNNRRCAWGT_repr -1 0.264021 6456.11 1 5 CACCTG ACATGTCATAGACATGT - +4 tfdimers__MD00487-EcR-usp 17 0.264978 6479.5 1 6 CACCTG TTAATAAATAAAACATTAACCCTTTTAT - +4 taipale_tf_pairs__TFAP2C_HES7_NNCRCGYGNNNNNNNSCCNNNGGS_CAP_repr-TfAP-2 14 0.265486 6491.92 1 6 CACCTG GGCACGTGCCGCATCGCCTGAGGC + +4 taipale_tf_pairs__CLOCK_FIGLA_NCASSTGKNNNNNNNNNCACGTGN_CAP_repr-Clk 17 0.265486 6491.92 1 6 CACCTG GCACGTGCACGTGGCAACAGCTGG - +4 taipale_tf_pairs__TFAP2C_DLX3_NSCCNNNRGGCANNNNNNTAATKR_CAP_repr-TfAP-2 12 0.265486 6491.92 1 6 CACCTG TAATTAGCCCCATGCCCCGGGGCG - +4 elemento__AACAGCTG-amos-dimm-HLH54F-nau 2 0.26644 6515.25 1 6 CACCTG AACAGCTG + +4 elemento__ATCAGCTG 2 0.26644 6515.25 1 6 CACCTG ATCAGCTG + +4 elemento__CAGCTGCA 0 0.26644 6515.25 1 6 CACCTG CAGCTGCA + +4 flyfactorsurvey__Met_Clk_SANGER_5_FBgn0002723-Clk-Met 2 0.26644 6515.25 1 6 CACCTG GACACGTG + +4 hdpi__PURG-Pur-alpha 1 0.26644 6515.25 1 6 CACCTG AAATCTGG + +4 predrem__nrMotif1385 1 0.26644 6515.25 1 6 CACCTG CCATCTGA + +4 cisbp__M0112 1 0.26644 6515.25 1 6 CACCTG ATATCAGG - +4 cisbp__M0295-CrebB-kay 0 0.26644 6515.25 1 6 CACCTG TACGTCAT - +4 cisbp__M4893-Clk-cyc-Met 1 0.26644 6515.25 1 6 CACCTG TCACGTGG - +4 factorbook__TAL1-HLH3B 1 0.26644 6515.25 1 6 CACCTG TTATCTCT - +4 jaspar__MA0604.1-CrebB-kay 0 0.26644 6515.25 1 6 CACCTG TACGTCAT - +4 jaspar__MA0938.1 1 0.26644 6515.25 1 6 CACCTG TTGCGTGT - +4 predrem__nrMotif1410 2 0.26644 6515.25 1 6 CACCTG AGAGCCTT - +4 transfac_pro__M08978-bigmax-Clk-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.26644 6515.25 1 6 CACCTG GTCACGTG - +4 transfac_pro__M09006-bigmax-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 2 0.26644 6515.25 1 6 CACCTG GTCACGTG - +4 yetfasco__YER045C_8-Atf6-CrebB-Jra-REPTOR-BP-kay 1 0.26644 6515.25 1 6 CACCTG TTACGTCA - +4 transfac_pro__M00698 -1 0.26644 6515.25 1 5 CACCTG GCCAGCTG + +4 transfac_pro__M03824-gcm-gcm2 -1 0.26644 6515.25 1 5 CACCTG GCCCGCAT + +4 homer__VAGRACAKWCTGTYC_GRE-Hsf-fkh 3 0.266602 6519.21 1 6 CACCTG CAGAACATTCTGTTC + +4 jaspar__MA0116.1 2 0.266602 6519.21 1 6 CACCTG GGCACCCAGGGGTGC + +4 neph__UW.Motif.0552 7 0.266602 6519.21 1 6 CACCTG GAGAAAATGCCAGAC + +4 neph__UW.Motif.0556 6 0.266602 6519.21 1 6 CACCTG CTGTTTTTCTTTTCA + +4 transfac_pro__M02790-CG9727-Rfx 1 0.266602 6519.21 1 6 CACCTG CCGCATAGCAACGGA + +4 transfac_pro__M07211-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 5 0.266602 6519.21 1 6 CACCTG CCCACTTCCTGTCTC + +4 cisbp__M1937 2 0.266602 6519.21 1 6 CACCTG GGCACCCAGGGGTGC - +4 hocomoco__KLF4_MOUSE.H11MO.0.A-CG42741-Sp1-Spps-btd-cbt-dar1-luna 4 0.266602 6519.21 1 6 CACCTG GCCACACCCACTCCA - +4 homer__ACVAKCTGGCAGCGC_Unknown3 7 0.266602 6519.21 1 6 CACCTG GCGCTGCCAGCTTGT - +4 taipale_cyt_meth__HNF4A_NRGGTCAAAGTCCRN_eDBD_meth_repr-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 9 0.266602 6519.21 1 6 CACCTG GTGGACTTTGACCCC - +4 transfac_pro__M00444-EcR 1 0.266602 6519.21 1 6 CACCTG TCACCCCCTTGACCC - +4 cisbp__M4577-bs 1 0.267004 6529.06 1 6 CACCTG TTGCCTTATATGGGCATG - +4 cisbp__M5436-croc-fd59A-fd96Ca-fd96Cb-fkh 12 0.267004 6529.06 1 6 CACCTG TATGTCAATATTTACATA - +4 taipale__FOXB1_DBD_WNWGTMAATATTRACWNW-croc-fd59A-fd96Ca-fd96Cb-fkh 12 0.267004 6529.06 1 6 CACCTG TATGTCAATATTTACATA - +4 cisbp__M0201-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.267469 6540.41 1 6 CACCTG GTCACGTGAC + +4 cisbp__M0808 1 0.267469 6540.41 1 6 CACCTG AGATCTCTAA + +4 cisbp__M1049-Optix-so 4 0.267469 6540.41 1 6 CACCTG ATGATACCCC + +4 fantom__motif125_TTTAACTCGT 2 0.267469 6540.41 1 6 CACCTG TTTAACTCGT + +4 flyfactorsurvey__Eip74EF_FlyReg_FBgn0000567-Eip74EF 2 0.267469 6540.41 1 6 CACCTG ACTTCCTGTT + +4 hocomoco__TWST1_HUMAN.H11MO.1.A-twi 2 0.267469 6540.41 1 6 CACCTG CACATCTGGT + +4 homer__GNCCACGTGG_c-Myc-Clk-E2f1-Max-Myc-Usf-gce-tgo 3 0.267469 6540.41 1 6 CACCTG GGCCACGTGG + +4 homer__GTCACGTGGT_Usf2-Max-Mitf-Usf-cnc 2 0.267469 6540.41 1 6 CACCTG GTCACGTGGT + +4 predrem__nrMotif1286 0 0.267469 6540.41 1 6 CACCTG CACATGAAAA + +4 taipale__USF1_DBD_RTCACGTGAY-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.267469 6540.41 1 6 CACCTG ATCACGTGAC + +4 taipale_cyt_meth__KLF5_NMCACGCCCN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.267469 6540.41 1 6 CACCTG ACCACGCCCC + +4 transfac_pro__M01640-CG7786-gt-Pdp1 3 0.267469 6540.41 1 6 CACCTG GATTACGTAA + +4 transfac_pro__M03180 3 0.267469 6540.41 1 6 CACCTG CGTTACATCC + +4 cisbp__M0177-amos-ato-crp-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.267469 6540.41 1 6 CACCTG AACATATGGC - +4 cisbp__M0632-dmrt11E-dmrt93B-dmrt99B-dsx 4 0.267469 6540.41 1 6 CACCTG TTGATACATT - +4 cisbp__M0702-Ets98B 1 0.267469 6540.41 1 6 CACCTG CATCCGGTTT - +4 cisbp__M0708-aop-Eip74EF-Ets21C-Ets96B-Ets97D-Ets98B-pnt 2 0.267469 6540.41 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1175-scro-vnd 3 0.267469 6540.41 1 6 CACCTG AAGTACTTAA - +4 cisbp__M1318 2 0.267469 6540.41 1 6 CACCTG CTTATCCATA - +4 cisbp__M2353 1 0.267469 6540.41 1 6 CACCTG TCACGTGGCT - +4 cisbp__M3919-btd-Spps 4 0.267469 6540.41 1 6 CACCTG ACCCCGCCCC - +4 cisbp__M4935-Eip74EF 2 0.267469 6540.41 1 6 CACCTG ACTTCCTGTT - +4 cisbp__M5240-sim-tgo 1 0.267469 6540.41 1 6 CACCTG GTACGTGACC - +4 cisbp__M5510-dpn-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mgamma-HLH-Hey-Sidpn 2 0.267469 6540.41 1 6 CACCTG GACACGTGCC - +4 cisbp__M5932-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.267469 6540.41 1 6 CACCTG ATCACGTGAC - +4 cisbp__M6253-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.267469 6540.41 1 6 CACCTG CCTTATCTGT - +4 fantom__motif105_KTNGNAGWMG 0 0.267469 6540.41 1 6 CACCTG CTACTACCAC - +4 flyfactorsurvey__Bap_Cell_FBgn0004862-bap 1 0.267469 6540.41 1 6 CACCTG CCACTTAAGA - +4 homer__ACAGGAAGTG_ETS1-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-bs-dl-grn-pnr-pnt 3 0.267469 6540.41 1 6 CACCTG CACTTCCTGT - +4 jaspar__MA0284.1-CG7786-Pdp1-gt 3 0.267469 6540.41 1 6 CACCTG GATTACGTAA - +4 jaspar__MA0560.1 1 0.267469 6540.41 1 6 CACCTG TCACGTGGCT - +4 jaspar__MA0633.1-Fer3-HLH54F-Oli-amos-ato-crp-dimm-tap-twi 0 0.267469 6540.41 1 6 CACCTG AACATATGGT - +4 predrem__nrMotif1783 1 0.267469 6540.41 1 6 CACCTG TTTCCTCTAA - +4 predrem__nrMotif864 4 0.267469 6540.41 1 6 CACCTG CTCCCACATT - +4 taipale_tf_pairs__ETS2_RCCGGAAGTG_HT 0 0.267469 6540.41 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M06796-btd-cbt-Sp1-Spps 0 0.267469 6540.41 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M07294-CG42741 1 0.267469 6540.41 1 6 CACCTG ACACCCCCTT - +4 transfac_public__M00349-GATAe-grn-pnr-srp 3 0.267469 6540.41 1 6 CACCTG TCTTATCTCT - +4 yetfasco__YOR162C_2245 4 0.267469 6540.41 1 6 CACCTG TTATTTCCGC - +4 cisbp__M5433-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.267469 6540.41 1 5 CACCTG ACCGGAAGTG + +4 taipale__FLI1_full_ACCGGAARYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.267469 6540.41 1 5 CACCTG ACCGGAAGTG + +4 transfac_pro__M04799-Sin3A -1 0.267469 6540.41 1 5 CACCTG ACCATGGACA + +4 taipale_cyt_meth__FOXJ3_NYGTAAACAN_eDBD-croc-FoxK-FoxL1-foxo-FoxP-slp1 5 0.267469 6540.41 1 5 CACCTG TTGTTTACGT - +4 taipale_tf_pairs__CLOCK_FIGLA_NCASSTGKNNNNNNNNCACGTGN_CAP_repr-Clk 1 0.267615 6543.98 1 6 CACCTG CCAGCTGGCACCAAGACACGTGT + +4 predrem__nrMotif63 0 0.268455 6564.54 1 6 CACCTG CACCCAG + +4 cisbp__M0376 1 0.268455 6564.54 1 6 CACCTG ATAACTT - +4 cisbp__M0466 0 0.268455 6564.54 1 6 CACCTG CCCCCAC - +4 predrem__nrMotif2301 1 0.268455 6564.54 1 6 CACCTG GGACATT - +4 swissregulon__sacCer__ACE2-CG9609 0 0.268455 6564.54 1 6 CACCTG AACCAGC - +4 cisbp__M0762 2 0.268455 6564.54 1 5 CACCTG TTGATCT - +4 cisbp__M6185-Cfp1-CG17440-CG3347 2 0.268455 6564.54 1 5 CACCTG GCCAACG - +4 predrem__nrMotif1283 -1 0.268455 6564.54 1 5 CACCTG ACCCACA - +4 predrem__nrMotif742 -2 0.268455 6564.54 1 4 CACCTG CCTGGCT + +4 jaspar__MA0955.1 3 0.268455 6564.54 1 4 CACCTG CCGTACC - +4 predrem__nrMotif2072 3 0.268455 6564.54 1 4 CACCTG TGCCAAC - +4 predrem__nrMotif2317 3 0.268455 6564.54 1 4 CACCTG CCACACA - +4 hdpi__NKX2-3 -3 0.268455 6564.54 1 3 CACCTG CTGTAAT - +4 taipale_tf_pairs__TFAP2C_E2F8_NNTCCCGCNNNCCNNNGGC_CAP_repr-TfAP-2 9 0.268905 6575.53 1 6 CACCTG TTTCCCGCTCGCCCCAGGC + +4 taipale_tf_pairs__CLOCK_BHLHA15_NCACGTGNNNNNCATATGN_CAP-Clk-dimm 12 0.268905 6575.53 1 6 CACCTG CCATATGTTAGCCACGTGT - +4 transfac_pro__M06364 3 0.268905 6575.53 1 6 CACCTG TCGCATCTGTAGACACCAT - +4 tfdimers__MD00252-EcR 19 0.268939 6576.38 1 6 CACCTG ACACTCTGTCTGAACCCACTTCCTGTGTCT + +4 hocomoco__ZN770_HUMAN.H11MO.0.C 8 0.269095 6580.18 1 6 CACCTG GATCCTCCCGCCTCAGCCTCCC - +4 cisbp__M0278-Xbp1 3 0.269644 6593.61 1 6 CACCTG GATGACGTG + +4 cisbp__M0756-FoxK-foxo 3 0.269644 6593.61 1 6 CACCTG GTAAACAAA + +4 cisbp__M1732 0 0.269644 6593.61 1 6 CACCTG TTCCGATCC + +4 cisbp__M1807 2 0.269644 6593.61 1 6 CACCTG ATTTCCGCC + +4 transfac_pro__M01118-klu 2 0.269644 6593.61 1 6 CACCTG CCCTCCCCC + +4 transfac_pro__M01861-Atf6-CrebB 1 0.269644 6593.61 1 6 CACCTG TCACGTCAC + +4 transfac_pro__M04679-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.269644 6593.61 1 6 CACCTG GTCACGTGA + +4 transfac_pro__M05538 0 0.269644 6593.61 1 6 CACCTG GACGTTTTA + +4 transfac_pro__M07242-lz-run-RunxA-RunxB 1 0.269644 6593.61 1 6 CACCTG AAACCACAG + +4 cisbp__M0784-brm-CoRest-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 2 0.269644 6593.61 1 6 CACCTG CTTATCTGT - +4 cisbp__M4902-D19B 1 0.269644 6593.61 1 6 CACCTG TACCCTGTA - +4 cisbp__M5019-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 0 0.269644 6593.61 1 6 CACCTG CACGTGCCA - +4 predrem__nrMotif1566 1 0.269644 6593.61 1 6 CACCTG ACAGCTTCA - +4 predrem__nrMotif1667 0 0.269644 6593.61 1 6 CACCTG AACATCATC - +4 predrem__nrMotif216 1 0.269644 6593.61 1 6 CACCTG ACACCAAAG - +4 predrem__nrMotif551 2 0.269644 6593.61 1 6 CACCTG ACTTCCTCT - +4 taipale__Nr2e1_DBD_AAAAGTCAA_repr-dsf-tll 2 0.269644 6593.61 1 6 CACCTG TTGACTTTT - +4 taipale_cyt_meth__CREB1_NRTGACGTN_eDBD_repr-CrebB 0 0.269644 6593.61 1 6 CACCTG TACGTCACC - +4 taipale_cyt_meth__GATA2_NWGATAASN_eDBD_meth_repr-CoRest-GATAd-GATAe-grn-pnr-srp 3 0.269644 6593.61 1 6 CACCTG CGTTATCTC - +4 predrem__nrMotif1454 -1 0.269644 6593.61 1 5 CACCTG TCCTAGCCC + +4 predrem__nrMotif1526 -1 0.269644 6593.61 1 5 CACCTG ACTTTCATT + +4 predrem__nrMotif1515 -2 0.269644 6593.61 1 4 CACCTG CCTGGCGCC + +4 predrem__nrMotif1953 -2 0.269644 6593.61 1 4 CACCTG CCTGCACAC - +4 transfac_pro__M05120 -2 0.269644 6593.61 1 4 CACCTG CCTCGGTCG - +4 dbcorrdb__ATF3__ENCSR000BKC_1__m1-btd-cnc-CrebB-cyc-E2f1-E(z)-FoxP-Jra-Max-Mitf-mor-Myc-Sap30-Spps-SREBP-Usf 5 0.269823 6597.99 1 6 CACCTG CCGGTCACGTGACCCCCGCG + +4 dbcorrdb__ATF3__ENCSR000BKE_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-E(z)-Jra-Max-Mitf-Myc-Sap30-Spps-SREBP-Usf-zfh1 7 0.269823 6597.99 1 6 CACCTG CCGGGGTCACGTCACCGGCG + +4 dbcorrdb__BDP1__ENCSR000DOK_1__m1-Bdp1-Brf-CG17209-ebi-Tbp 10 0.269823 6597.99 1 6 CACCTG ACCACTGAGCCACCGAGCCA + +4 dbcorrdb__IRF3__ENCSR000DZX_1__m3 6 0.269823 6597.99 1 6 CACCTG TTAGTATATCTAATTGACAT + +4 transfac_pro__M07897-byn-H15-mid-org-1 5 0.269823 6597.99 1 6 CACCTG TTTCACACCTAGGTGTGAAA + +4 dbcorrdb__EP300__ENCSR000BMA_1__m1-nej-twi 3 0.269823 6597.99 1 6 CACCTG AGACATCTGGTATTAATCAG - +4 dbcorrdb__EZH2__ENCSR000ARO_1__m2-E(z) 11 0.269823 6597.99 1 6 CACCTG GCGCCGCCGTGTCCGTGCGC - +4 dbcorrdb__POLR3G__ENCSR000EYU_1__m2-Bdp1-Brf-CG17209-Tbp 14 0.269823 6597.99 1 6 CACCTG CTTAACCACTGCGCCACCGA - +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m6-egg 7 0.269823 6597.99 1 6 CACCTG CATTCATTACATTTATACGG - +4 dbcorrdb__SREBF1__ENCSR000EEO_1__m1-CG5846-Rfx-SREBP 3 0.269823 6597.99 1 6 CACCTG GGTCGCCCCAGCGACGGGCG - +4 dbcorrdb__ZNF143__ENCSR000EBW_1__m1-egg-Hcf-Six4 4 0.269823 6597.99 1 6 CACCTG GCGCCGCCTGCTGGGAAATG - +4 dbcorrdb__eGFP-NR4A1__ENCSR000DJW_1__m3 2 0.269823 6597.99 1 6 CACCTG CTGCCCTTCTGAGGATGCAG - +4 cisbp__M4722-ab 10 0.269858 6598.83 1 6 CACCTG CTCTTAATGGGTCCTGGCCTC + +4 hocomoco__ZN563_HUMAN.H11MO.0.C 14 0.269858 6598.83 1 6 CACCTG GGGATCCTCACTGGCAGCTGC + +4 transfac_pro__M01546 5 0.269858 6598.83 1 6 CACCTG TCAAATACCGGCGAAATCTAA + +4 taipale_tf_pairs__CLOCK_NHLH1_NRCAGCTGNNNNNCACGTGNN_CAP_repr-Clk-HLH4C 13 0.269858 6598.83 1 6 CACCTG GACACGTGTGGCGCAGCTGCG - +4 neph__UW.Motif.0379 5 0.271652 6642.72 1 6 CACCTG AAACCTTTCTCTGC + +4 neph__UW.Motif.0595 5 0.271652 6642.72 1 6 CACCTG AGAAAAAGCTCCTT + +4 swissregulon__hs__FOXO1_3_4.p2-CHES-1-like-FoxK-FoxP-croc-fkh-foxo-slp1-slp2 8 0.271652 6642.72 1 6 CACCTG GTTTTGTTTACATT + +4 taipale_tf_pairs__TEAD4_EOMES_WNGTGYKAMATWCY_CAP-sd 6 0.271652 6642.72 1 6 CACCTG AGGTGTGACATTCC + +4 transfac_public__M00122-bigmax-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 4 0.271652 6642.72 1 6 CACCTG AAATCACGTGATAT + +4 taipale_tf_pairs__ELK1_FOXI1_WGTTKMCGGAWRTN_CAP 0 0.271652 6642.72 1 6 CACCTG CACTTCCGTAAACA - +4 taipale_tf_pairs__ERF_FOXO1_RTMAACAGGAARNN_CAP-Ets21C-foxo 3 0.271652 6642.72 1 6 CACCTG CACTTCCTGTTTAC - +4 transfac_pro__M01185 1 0.271652 6642.72 1 6 CACCTG ATTCCTAGAAAGCA - +4 transfac_pro__M08879-Eip74EF-Ets21C-Ets65A-Ets97D-GATAe-grn-pnr-pnt 3 0.271652 6642.72 1 6 CACCTG CACTTCCTGTTGTT - +4 transfac_pro__M09334 0 0.271652 6642.72 1 6 CACCTG AACCTTATCCATTT - +4 neph__UW.Motif.0317 9 0.271652 6642.72 1 5 CACCTG AGAAACTGCCTTCT + +4 neph__UW.Motif.0544 10 0.271652 6642.72 1 4 CACCTG GCCTGGCATTTTCC + +4 cisbp__M5747-CG34367-E5-ems-en-gsb-gsb-n-inv-pb-pdm3-prd-unpg 5 0.272371 6660.28 1 6 CACCTG TTAATTAGCTCATTAA + +4 hocomoco__PRD14_MOUSE.H11MO.0.A 9 0.272371 6660.28 1 6 CACCTG AGGGTTAGAGACCTTG + +4 taipale_tf_pairs__ETV2_SREBF2_RTCACGYSNCCGGAWN_CAP_repr-pnt-SREBP 7 0.272371 6660.28 1 6 CACCTG ATCACGCCACCGGAAG + +4 transfac_pro__M01460-abd-A-Ubx 10 0.272371 6660.28 1 6 CACCTG TATTGGTAATTACCTT + +4 transfac_pro__M03137-nau 4 0.272371 6660.28 1 6 CACCTG TGGACAGCTGTCGAGG + +4 cisbp__M2371 7 0.272371 6660.28 1 6 CACCTG TTTTATGTACCTTATT - +4 neph__UW.Motif.0253 0 0.272371 6660.28 1 6 CACCTG CACATGGTGTCTCTGT - +4 taipale_cyt_meth__ERG_NACCGGATATCCGGTN_eDBD_meth-Ets21C-Ets97D 0 0.272371 6660.28 1 6 CACCTG AACCGGATATCCGGTT - +4 taipale_cyt_meth__MAFA_NTGCTGAYGTCAGCAN_eDBD_meth-CrebA-maf-S 5 0.272371 6660.28 1 6 CACCTG TTGCTGACGTCAGCAA - +4 taipale_tf_pairs__ELK1_FOXI1_RSCGGAANRWMAACAN_CAP_repr 5 0.272371 6660.28 1 6 CACCTG ATGTTTACCTTCCGGC - +4 transfac_pro__M02891-EcR 5 0.272371 6660.28 1 6 CACCTG TACTTGACCCCGCTCT - +4 transfac_pro__M09371 1 0.272371 6660.28 1 6 CACCTG TTACGTGTTGCACAAG - +4 taipale_tf_pairs__E2F3_TBX21_NGGTGTGNNGGCGCSN_CAP_repr-E2f1 11 0.272371 6660.28 1 5 CACCTG ACGCGCCTTCACACCT - +4 cisbp__M5889 12 0.272371 6660.28 1 4 CACCTG GGTGTGAATTCACACC - +4 yetfasco__YPR008W_1425 0 0.272663 6667.44 1 6 CACCTG CCCCGC - +4 hdpi__CREB3L1-CrebA -1 0.272663 6667.44 1 5 CACCTG ACCACG + +4 hdpi__ZNF160 1 0.272663 6667.44 1 5 CACCTG ATCCCT - +4 hdpi__CEBPG -3 0.272663 6667.44 1 3 CACCTG CTGTGA + +4 hdpi__UGP2-UGP -3 0.272663 6667.44 1 3 CACCTG CTGGAG + +4 cisbp__M0197-Mitf-Usf 3 0.2731 6678.11 1 6 CACCTG TATCACGTGGG + +4 cisbp__M0768 4 0.2731 6678.11 1 6 CACCTG TCTAGATCTGA + +4 cisbp__M4937-Eip75B-Hr3 1 0.2731 6678.11 1 6 CACCTG TGACCCACATA + +4 hocomoco__GMEB2_HUMAN.H11MO.0.D 3 0.2731 6678.11 1 6 CACCTG GGTTACGTAAT + +4 jaspar__MA1018.1 4 0.2731 6678.11 1 6 CACCTG TCTAGATCTGT + +4 predrem__nrMotif628 2 0.2731 6678.11 1 6 CACCTG CCTCCCTGCAC + +4 cisbp__M0629-dmrt11E-dmrt93B-dsx 5 0.2731 6678.11 1 6 CACCTG ATTGATACATT - +4 cisbp__M4558-Clk-E2f1-gce-Max-Mnt-Myc 3 0.2731 6678.11 1 6 CACCTG GAGCACGTGGC - +4 cisbp__M4645-Max-Myc 2 0.2731 6678.11 1 6 CACCTG AGCACGTGGCC - +4 cisbp__M5441-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxP 5 0.2731 6678.11 1 6 CACCTG ATATTTACATA - +4 hocomoco__ATF7_MOUSE.H11MO.0.D-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 2 0.2731 6678.11 1 6 CACCTG ATGACATCATC - +4 hocomoco__RFX6_MOUSE.H11MO.0.C-CG9727-Rfx 5 0.2731 6678.11 1 6 CACCTG CCTGGCAACAG - +4 jaspar__MA0610.1-dmrt11E-dmrt93B-dsx 5 0.2731 6678.11 1 6 CACCTG ATTGATACATT - +4 predrem__nrMotif690 0 0.2731 6678.11 1 6 CACCTG GGCCTGGTCTC - +4 swissregulon__hs__SREBF1_2.p2-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-cyc-tgo 2 0.2731 6678.11 1 6 CACCTG GTCACGTGACC - +4 taipale__FOXC1_DBD_WRWRTMAAYAW-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxP 5 0.2731 6678.11 1 6 CACCTG ATATTTACATA - +4 taipale_cyt_meth__TFEC_RNCAYGTGAYN_eDBD_meth-Mitf-Usf 3 0.2731 6678.11 1 6 CACCTG GGTCACATGGT - +4 taipale_tf_pairs__ETV5_HOXA2_RSCGGWAATKR_CAP-Ets96B-pb 4 0.2731 6678.11 1 6 CACCTG TCATTTCCGGT - +4 tiffin__TIFDMEM0000064 5 0.2731 6678.11 1 6 CACCTG TAAAAAACATT - +4 transfac_pro__M06846-zfh2 4 0.2731 6678.11 1 6 CACCTG GGGGGACCACA - +4 stark__CCTTTGATCTT-pan -2 0.2731 6678.11 1 4 CACCTG CCTTTGATCTT + +4 jaspar__MA0341.1-CG10348-CG13296-ham 0 0.273778 6694.69 1 5 CACCTG CCCCT - +4 transfac_pro__M01915-CG10348-CG13296-ham 0 0.273778 6694.69 1 5 CACCTG CCCCT - +4 taipale_tf_pairs__ELK1_TBX21_ANGTGNNANNNNNNNNNNNCNNMGGAWNN_CAP_repr 24 0.274051 6701.37 1 5 CACCTG ACTTCCGGTGTTAAATATATTTCACACCT - +4 cisbp__M6328 0 0.274682 6716.8 1 6 CACCTG CACTTTTAATTAG + +4 cisbp__M6355-nau 3 0.274682 6716.8 1 6 CACCTG TGACAGCTGCTGC + +4 hocomoco__TEAD4_HUMAN.H11MO.0.A-nej-sd 3 0.274682 6716.8 1 6 CACCTG ACATTCCTGGCAT + +4 transfac_pro__M07610-cnc-ewg-kay-maf-S 0 0.274682 6716.8 1 6 CACCTG CTGCTGAGTCACG + +4 cisbp__M4967-Fer1-nau 4 0.274682 6716.8 1 6 CACCTG ACGACAGCTGACG - +4 hocomoco__SPIC_HUMAN.H11MO.0.D 3 0.274682 6716.8 1 6 CACCTG CCTCCCCTTCCTC - +4 neph__UW.Motif.0263 4 0.274682 6716.8 1 6 CACCTG TGCAAAATTTCTC - +4 taipale_cyt_meth__SPIB_RAWWGRGGAAGTN_FL_meth-CG9650-nej 0 0.274682 6716.8 1 6 CACCTG CACTTCCCCTTTC - +4 taipale_tf_pairs__HOXB2_ELF1_SMGGAAGTMRTTA_CAP-Eip74EF-pb 4 0.274682 6716.8 1 6 CACCTG TAATGACTTCCGG - +4 taipale_tf_pairs__TEAD4_DLX2_RGWATGYTAATKR_CAP_repr-sd 5 0.274682 6716.8 1 6 CACCTG CAATTAACATTCC - +4 transfac_pro__M02220-btd-EcR-eg-ERR-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 1 0.274682 6716.8 1 6 CACCTG TGACCTTTGGCCT - +4 cisbp__M6542 8 0.274682 6716.8 1 5 CACCTG GGCTCTATCATCT - +4 cisbp__M5327-Atf6-Clk-CrebA 3 0.275317 6732.32 1 6 CACCTG TGCCACGTGGCA + +4 homer__GTCCCCAGGGGA_EBF1-ham-kn 2 0.275317 6732.32 1 6 CACCTG GTCCCCAGGGGA + +4 taipale__CREB3L1_full_TGCCACGTGGCA-Atf6-Clk-CrebA 3 0.275317 6732.32 1 6 CACCTG TGCCACGTGGCA + +4 taipale_cyt_meth__DMRTA2_NNTTGWTACATT_eDBD-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.275317 6732.32 1 6 CACCTG AATTGTTACATT + +4 taipale_cyt_meth__MYOD1_NAACANNTGTYN_FL_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.275317 6732.32 1 6 CACCTG CAACAGCTGTTG + +4 taipale_cyt_meth__TGIF2LY_TGACANNTGTCA_eDBD-achi-hth-nau-vis 3 0.275317 6732.32 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__TGIF2_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.275317 6732.32 1 6 CACCTG TGACAGCTGTCA + +4 transfac_pro__M02105 1 0.275317 6732.32 1 6 CACCTG CTCCCTCGCCAG + +4 transfac_pro__M05530 6 0.275317 6732.32 1 6 CACCTG TCGTGTAACCTC + +4 transfac_pro__M05714-ham 6 0.275317 6732.32 1 6 CACCTG TGGTCCCAACTC + +4 cisbp__M5373-aop-Eip74EF-Ets21C 0 0.275317 6732.32 1 6 CACCTG CACTTCCGGGTT - +4 hdpi__NME1-awd 2 0.275317 6732.32 1 6 CACCTG ATTTGCTTTTGA - +4 neph__UW.Motif.0256 3 0.275317 6732.32 1 6 CACCTG ATTAACTTTTTT - +4 taipale_cyt_meth__ELF2_NACCMGGAAGTN_eDBD_meth_repr-aop-bs-Eip74EF-Ets96B-Ets97D-pnt 0 0.275317 6732.32 1 6 CACCTG TACTTCCTGTTT - +4 taipale_cyt_meth__ELF4_NATGCGGAAGTN_eDBD_meth-Eip74EF 0 0.275317 6732.32 1 6 CACCTG CACTTCCGCATT - +4 taipale_cyt_meth__TCF21_NAACAGCTGYYN_eDBD-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.275317 6732.32 1 6 CACCTG TAACAGCTGTTG - +4 taipale_cyt_meth__ZBTB20_NYAAYGTATRKN_eDBD_meth 4 0.275317 6732.32 1 6 CACCTG TCTATACATTAA - +4 transfac_pro__M01830-E2f1-Max-Myc 1 0.275317 6732.32 1 6 CACCTG GCACGTGGCCGG - +4 transfac_pro__M05417 6 0.275317 6732.32 1 6 CACCTG GCCCCCCCCCTC - +4 transfac_pro__M06275-CG2120 4 0.275317 6732.32 1 6 CACCTG TCACCACCCCCC - +4 transfac_pro__M06410 6 0.275317 6732.32 1 6 CACCTG GCTTTTTACCCG - +4 transfac_pro__M06722-CG11456-CG1233-CG32767-CG43347 0 0.275317 6732.32 1 6 CACCTG AAACTTGCCCCA - +4 transfac_pro__M06859-CG2120 6 0.275317 6732.32 1 6 CACCTG TGCTTTAAACTT - +4 transfac_pro__M05946-ham 7 0.275317 6732.32 1 5 CACCTG TGGTCATGACCA + +4 transfac_pro__M05903 7 0.275317 6732.32 1 5 CACCTG TCCTTTTGACCA - +4 transfac_pro__M06104-crol 7 0.275317 6732.32 1 5 CACCTG GCGTTTTTACCG - +4 transfac_pro__M06725 7 0.275317 6732.32 1 5 CACCTG TCATATTGACCA - +4 hocomoco__ZNF18_HUMAN.H11MO.0.C 8 0.275317 6732.32 1 4 CACCTG CCAGTTCACACC - +4 transfac_pro__M05913 8 0.275317 6732.32 1 4 CACCTG CTTGGTGATACC - +4 taipale_tf_pairs__ETV2_NHLH1_NGCAGCTGCCGGAWRYN_CAP_repr-HLH4C-pnt 2 0.276793 6768.43 1 6 CACCTG AGCAGCTGCCGGAAGTT + +4 transfac_pro__M02770 8 0.276793 6768.43 1 6 CACCTG CTGATCGAAACCAAAGT + +4 transfac_pro__M08190 7 0.276793 6768.43 1 6 CACCTG GGAACGGAACATGTTCT + +4 cisbp__M6336-Brf-btd-CoRest-crol-ct-CTCF-Dif-dl-HDAC1-Klf15-klu-l(3)neo38-Rbbp5-Spps-Spt20-sr-SREBP 3 0.276793 6768.43 1 6 CACCTG CCCTCCCTCCCCCCCCC - +4 hocomoco__DMRT1_HUMAN.H11MO.0.D-dmrt99B 4 0.276793 6768.43 1 6 CACCTG TTGCTACATTGTATCAA - +4 jaspar__MA0852.1-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd59A-fkh-foxo-slp1-slp2 9 0.276793 6768.43 1 6 CACCTG CTGTTTGTTTACATTTT - +4 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 19 0.277446 6784.38 1 6 CACCTG CACGTGCCTCGGCCCGCATCGCCTGAGGCCA - +4 cisbp__M0150-Mondo 1 0.278659 6814.05 1 6 CACCTG GCACGTGT + +4 cisbp__M0158-Usf 1 0.278659 6814.05 1 6 CACCTG CCACGTGC + +4 cisbp__M0189-emc 1 0.278659 6814.05 1 6 CACCTG GCACGTGA + +4 cisbp__M0211-Mondo 1 0.278659 6814.05 1 6 CACCTG GCACGTGT + +4 cisbp__M0227 1 0.278659 6814.05 1 6 CACCTG CCACGTGT + +4 cisbp__M0240-Mitf-Mondo-SREBP-Usf-tgo 1 0.278659 6814.05 1 6 CACCTG TCACGTGA + +4 cisbp__M0247-Mitf-Usf 2 0.278659 6814.05 1 6 CACCTG ATCACGTG + +4 cisbp__M1048 2 0.278659 6814.05 1 6 CACCTG ATTACAGC + +4 cisbp__M1376 1 0.278659 6814.05 1 6 CACCTG AACCCTAA + +4 cisbp__M3087-CG7786-gt-hng1-Pdp1-vri 1 0.278659 6814.05 1 6 CACCTG TTACGTAA + +4 cisbp__M5104-Clk-Met 2 0.278659 6814.05 1 6 CACCTG GACACGTG + +4 elemento__TACGTGAC 0 0.278659 6814.05 1 6 CACCTG TACGTGAC + +4 jaspar__MA0617.1-emc 1 0.278659 6814.05 1 6 CACCTG GCACGTGA + +4 jaspar__MA0622.1-Mondo 1 0.278659 6814.05 1 6 CACCTG GCACGTGT + +4 jaspar__MA1015.1 2 0.278659 6814.05 1 6 CACCTG TAGATCTA + +4 jaspar__MA1074.1-Usf 1 0.278659 6814.05 1 6 CACCTG CCACGTGC + +4 predrem__nrMotif2339 2 0.278659 6814.05 1 6 CACCTG TCTACATT + +4 predrem__nrMotif2667 0 0.278659 6814.05 1 6 CACCTG CACTTATT + +4 taipale_cyt_meth__LHX4_YTCGTTAN_FL_meth-CG4328-Lim3-Lmx1a-Vsx1-Vsx2 0 0.278659 6814.05 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__MLX_NCACGTGN_eDBD_repr-bigmax-cyc-mio-tgo 1 0.278659 6814.05 1 6 CACCTG GCACGTGC + +4 taipale_tf_pairs__MYCL2_SCACGTGS_HT 1 0.278659 6814.05 1 6 CACCTG GCACGTGC + +4 transfac_public__M00040-CG7786-gt-hng1-Pdp1-vri 1 0.278659 6814.05 1 6 CACCTG TTACGTAA + +4 cisbp__M0193-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tai-tgo-Usf 0 0.278659 6814.05 1 6 CACCTG CACGTGAC - +4 cisbp__M0367 1 0.278659 6814.05 1 6 CACCTG TTACGTCA - +4 cisbp__M0780 1 0.278659 6814.05 1 6 CACCTG CGATCGGG - +4 cisbp__M4760-bap 0 0.278659 6814.05 1 6 CACCTG CACTTAAG - +4 flyfactorsurvey__Bap_SOLEXA_FBgn0004862-bap 0 0.278659 6814.05 1 6 CACCTG CACTTAAG - +4 jaspar__MA0402.1-CG9609 0 0.278659 6814.05 1 6 CACCTG AACCAGCA - +4 predrem__nrMotif185 1 0.278659 6814.05 1 6 CACCTG GGAGCTTT - +4 stark__WCYGGTTT-grh 1 0.278659 6814.05 1 6 CACCTG AAACCAGA - +4 swissregulon__sacCer__HMRA2 2 0.278659 6814.05 1 6 CACCTG ATTACATG - +4 transfac_pro__M01240 2 0.278659 6814.05 1 6 CACCTG GGTCGCTG - +4 yetfasco__YDR146C_569-CG9609 0 0.278659 6814.05 1 6 CACCTG AACCAGCA - +4 predrem__nrMotif1407 3 0.278659 6814.05 1 5 CACCTG TGATTCCT + +4 transfac_pro__M04626-CG32532 -1 0.278659 6814.05 1 5 CACCTG AGCTTATT + +4 predrem__nrMotif160 -1 0.278659 6814.05 1 5 CACCTG ACTTTTCA - +4 predrem__nrMotif2560 -1 0.278659 6814.05 1 5 CACCTG ACATTTAG - +4 transfac_pro__M04840-Mef2 3 0.278659 6814.05 1 5 CACCTG CATTTCCT - +4 predrem__nrMotif1994 -2 0.278659 6814.05 1 4 CACCTG CCTTATTC + +4 hocomoco__ZN350_HUMAN.H11MO.1.D 10 0.27901 6822.62 1 6 CACCTG GGGCAACAAACCCCTGCGCCCCGT - +4 tfdimers__MD00162-cnc-maf-S-Pur-alpha 9 0.27901 6822.62 1 6 CACCTG CCCCCCTGCCTCCTCCCCCCCCCC - +4 taipale_tf_pairs__POU2F1_EOMES_ARGTGTNNNAATATKYNNNCRCNN_CAP_repr-nub-pdm2 19 0.27901 6822.62 1 5 CACCTG CAGTGTGGGAATATTCCAACACCT - +4 hocomoco__MXI1_HUMAN.H11MO.0.A-Clk-E2f1-Max-Myc-Sap30-cyc-tgo 1 0.279232 6828.07 1 6 CACCTG GCACGTGGCGGCGGG + +4 homer__CCGACAYYTYACGGG_GEI-11 4 0.279232 6828.07 1 6 CACCTG CCGACACCTCACGGG + +4 jaspar__MA0316.1-Mes4-Nf-YB-Nf-YC-kay 3 0.279232 6828.07 1 6 CACCTG TGGGATCTGATTGGT + +4 scertf__pachkov.HAP5-Mes4-Nf-YB-Nf-YC-kay 3 0.279232 6828.07 1 6 CACCTG TGGGATCTGATTGGT + +4 taipale_cyt_meth__ZNF32_NYGTAACNYGAYACN_FL-CG4730-CG7101-so 4 0.279232 6828.07 1 6 CACCTG ATGTAACCTGATACC + +4 transfac_pro__M01787 1 0.279232 6828.07 1 6 CACCTG ACACCCATACATCTC + +4 transfac_pro__M09405 7 0.279232 6828.07 1 6 CACCTG TCATCATCACCATCA + +4 cisbp__M1922-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 5 0.279232 6828.07 1 6 CACCTG CCCACTTCCTGTCTC - +4 homer__AGATGKDGAGATAAG_GATA3-GATAe-grn-pnr 2 0.279232 6828.07 1 6 CACCTG CTTATCTCCACATCT - +4 homer__NNNCTTTCCAGGAAA_Bcl6-Stat92E 1 0.279232 6828.07 1 6 CACCTG TTTCCTGGAAAGCAA - +4 transfac_pro__M09345 2 0.279232 6828.07 1 6 CACCTG ATAACCTTATCCAAA - +4 factorbook__AP2-TfAP-2 -1 0.279232 6828.07 1 5 CACCTG GCCTGAGGGCATGGG - +4 hocomoco__ESR1_MOUSE.H11MO.0.A-ERR-EcR-eg-kni-knrl 10 0.279232 6828.07 1 5 CACCTG AGGTCAGGGTGACCT - +4 neph__UW.Motif.0342 10 0.279232 6828.07 1 5 CACCTG GCCAGCCTCCCTTCT - +4 swissregulon__hs__RXRA_VDR_dimer_.p2-EcR-usp 10 0.279232 6828.07 1 5 CACCTG TGAACTCCGTGACCC - +4 flyfactorsurvey__br-PLPA_SOLEXA_10-br -2 0.279232 6828.07 1 4 CACCTG CCTGGTTAGTTTTGG - +4 cisbp__M0198 2 0.279699 6839.49 1 6 CACCTG AGCCCGTGCG + +4 cisbp__M0273-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-E2f1-Irbp18-Jra-Xbp1-crc-kay-maf-S 3 0.279699 6839.49 1 6 CACCTG GATGACGTCA + +4 cisbp__M1819 3 0.279699 6839.49 1 6 CACCTG TATCTCCGAA + +4 cisbp__M1889-Max-Myc 3 0.279699 6839.49 1 6 CACCTG AAGCACATGG + +4 cisbp__M5305-bigmax-Clk-cnc-cwo-cyc-mio-Mitf-Mondo-Sirt6-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG GTCACGTGAT + +4 cisbp__M6530-ac-ase-cnc-cwo-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-Usf 3 0.279699 6839.49 1 6 CACCTG GGTCACGTGG + +4 flyfactorsurvey__Usf_SANGER_5_FBgn0029711-Max-Mitf-Usf 2 0.279699 6839.49 1 6 CACCTG ACCACGTGAC + +4 homer__GNCCACGTGG_n-Myc-Max-Myc-Sap30-Usf-tgo 3 0.279699 6839.49 1 6 CACCTG GACCACGTGG + +4 homer__KCACGTGMCN_bHLHE40-Sirt6-bigmax-cyc-mio-tgo 1 0.279699 6839.49 1 6 CACCTG GCACGTGCCT + +4 taipale__HEY2_DBD_NNCACGTGCC-dpn-E(spl)mbeta-HLH-Hey-Sidpn 2 0.279699 6839.49 1 6 CACCTG GACACGTGCC + +4 taipale__TFE3_DBD_NNCACGTGNN-bigmax-cnc-cwo-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG ATCACGTGAC + +4 taipale_cyt_meth__ARNT2_RTCACGTGMN_eDBD-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG GTCACGTGCC + +4 taipale_cyt_meth__OLIG3_ANCAGCTGTT_eDBD-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.279699 6839.49 1 6 CACCTG AACAGCTGTT + +4 taipale_cyt_meth__TFAP4_AWCAGCTGWT_FL-crp 2 0.279699 6839.49 1 6 CACCTG ATCAGCTGAT + +4 taipale_cyt_meth__TFAP4_AWCAGCTGWT_eDBD-crp 2 0.279699 6839.49 1 6 CACCTG ATCAGCTGAT + +4 transfac_pro__M00952 4 0.279699 6839.49 1 6 CACCTG GTGGTCCCGC + +4 transfac_pro__M02259-E2f1-Max-Myc 2 0.279699 6839.49 1 6 CACCTG CGCACGTGGC + +4 transfac_pro__M07217-Max-Myc 3 0.279699 6839.49 1 6 CACCTG AAGCACATGG + +4 transfac_pro__M07637-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG GTCACGTGAC + +4 transfac_pro__M09552 2 0.279699 6839.49 1 6 CACCTG CTTATCCATA + +4 cisbp__M0319-CrebB-Jra-kay-REPTOR-BP-vri 1 0.279699 6839.49 1 6 CACCTG TTACGTCATA - +4 cisbp__M0840-achi-esg-sna-vis-wor 3 0.279699 6839.49 1 6 CACCTG TTTGACAGCT - +4 cisbp__M4759-bap 1 0.279699 6839.49 1 6 CACCTG CCACTTAAGA - +4 cisbp__M5509-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn-tai 2 0.279699 6839.49 1 6 CACCTG GACACGTGCC - +4 cisbp__M5633-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG ATCACGTGAT - +4 cisbp__M5930-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG ATCACGTGAC - +4 jaspar__MA0609.1-CrebB-Jra-REPTOR-BP-kay-vri 1 0.279699 6839.49 1 6 CACCTG TTACGTCATA - +4 jaspar__MA0987.1 0 0.279699 6839.49 1 6 CACCTG TCACTTTTTG - +4 predrem__nrMotif562 0 0.279699 6839.49 1 6 CACCTG AACATTTCAT - +4 swissregulon__sacCer__RPH1-Kdm4A-Kdm4B 1 0.279699 6839.49 1 6 CACCTG ACCCCTAATT - +4 taipale__MLXIPL_full_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.279699 6839.49 1 6 CACCTG ATCACGTGAT - +4 taipale_cyt_meth__ATOH1_ANCAGCTGNY_eDBD-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 2 0.279699 6839.49 1 6 CACCTG GACAGCTGTT - +4 taipale_tf_pairs__FOXA1_TRNGTAAACA_HT-fkh 4 0.279699 6839.49 1 6 CACCTG TGTTTACATA - +4 transfac_pro__M01006 3 0.279699 6839.49 1 6 CACCTG ATAGATCTGA - +4 transfac_pro__M05755 1 0.279699 6839.49 1 6 CACCTG TTTCCTTAAC - +4 transfac_pro__M08939-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.279699 6839.49 1 6 CACCTG ATGACGTCAT - +4 transfac_public__M00433-Hmx 4 0.279699 6839.49 1 6 CACCTG CACGCACTTG - +4 yetfasco__YOL089C_2134 2 0.279699 6839.49 1 6 CACCTG ATTTCCGCTG - +4 cisbp__M1647 5 0.279699 6839.49 1 5 CACCTG GGGCCCACCA + +4 jaspar__MA1065.1 5 0.279699 6839.49 1 5 CACCTG GGGCCCACCA + +4 neph__UW.Motif.0063 -1 0.279699 6839.49 1 5 CACCTG CACTCTGGGA + +4 predrem__nrMotif1940 5 0.279699 6839.49 1 5 CACCTG TTCTGGAACT + +4 predrem__nrMotif93 5 0.279699 6839.49 1 5 CACCTG CTGTGTTCCT + +4 scertf__zhu.TOD6 -1 0.279699 6839.49 1 5 CACCTG AGCTCATCGC + +4 cisbp__M0441-opa -1 0.279699 6839.49 1 5 CACCTG CCCCGCTGTG - +4 taipale_cyt_meth__FOXO4_NYGTAAACAN_eDBD_meth-croc-FoxL1-foxo-slp1-slp2 5 0.279699 6839.49 1 5 CACCTG GTGTTTACGT - +4 taipale_cyt_meth__MEF2B_CCWWATWWRG_eDBD-bs-Mef2 -2 0.279699 6839.49 1 4 CACCTG CCATATTTGG + +4 cisbp__M6387-EcR-svp-usp 12 0.279991 6846.62 1 6 CACCTG CTGAACTTTCCTGACCCC + +4 hocomoco__NR1I3_HUMAN.H11MO.0.C-EcR-svp-usp 12 0.279991 6846.62 1 6 CACCTG CTGAACTTTCCTGACCCC - +4 hocomoco__ZN524_HUMAN.H11MO.0.D 5 0.279991 6846.62 1 6 CACCTG ACTCGAACCCTCGAACCC - +4 transfac_pro__M06643 14 0.279991 6846.62 1 4 CACCTG GGCCGCGGGCAAGGCACC + +4 cisbp__M1944-bap 1 0.280796 6866.29 1 6 CACCTG ATACTTA - +4 cisbp__M5251-ttk 1 0.280796 6866.29 1 6 CACCTG TGTCCTT - +4 hdpi__LOC653972 0 0.280796 6866.29 1 6 CACCTG AACCGTC - +4 hocomoco__NFAC2_MOUSE.H11MO.1.C-NFAT 1 0.280796 6866.29 1 6 CACCTG TTTCCAT - +4 predrem__nrMotif1995 1 0.280796 6866.29 1 6 CACCTG TAACCAG - +4 cisbp__M0377 2 0.280796 6866.29 1 5 CACCTG TTCACTC - +4 hocomoco__CXXC1_HUMAN.H11MO.0.D-CG3347-CG17440-Cfp1 2 0.280796 6866.29 1 5 CACCTG GCCAACG - +4 predrem__nrMotif1169 2 0.280796 6866.29 1 5 CACCTG AAAACCA - +4 transfac_pro__M03549-srp 2 0.280796 6866.29 1 5 CACCTG TTTATCT - +4 cisbp__M1568 3 0.280796 6866.29 1 4 CACCTG CCGTACC - +4 cisbp__M0837-Gsc-Ptx1 3 0.281909 6893.53 1 6 CACCTG GTTAATCCG + +4 cisbp__M1550 2 0.281909 6893.53 1 6 CACCTG TGTACGTCA + +4 cisbp__M1714 3 0.281909 6893.53 1 6 CACCTG AATTGCCGA + +4 predrem__nrMotif2554 0 0.281909 6893.53 1 6 CACCTG GACCCAGTG + +4 predrem__nrMotif349 0 0.281909 6893.53 1 6 CACCTG CAGCTTGCT + +4 predrem__nrMotif714 0 0.281909 6893.53 1 6 CACCTG CACATGGCC + +4 taipale_cyt_meth__NR1I3_NTGAACTWW_FL_repr-EcR 2 0.281909 6893.53 1 6 CACCTG ATGAACTTT + +4 yetfasco__YIL036W_585-Atf3-Atf6-CrebB-Jra-REPTOR-BP-kay 1 0.281909 6893.53 1 6 CACCTG TTACGTCAT + +4 cisbp__M2091-Atf3-Atf6-CrebB-Jra-kay-REPTOR-BP 1 0.281909 6893.53 1 6 CACCTG TTACGTCAT - +4 cisbp__M4307-Atf3-Atf6-CrebB-Jra-kay-REPTOR-BP 1 0.281909 6893.53 1 6 CACCTG TTACGTCAT - +4 flyfactorsurvey__tai_Clk_SANGER_5_FBgn0023076-Clk-Hey-tai 2 0.281909 6893.53 1 6 CACCTG GACACGTGC - +4 jaspar__MA0286.1-Atf3-Atf6-CrebB-Jra-REPTOR-BP-kay 1 0.281909 6893.53 1 6 CACCTG TTACGTCAT - +4 predrem__nrMotif1456 0 0.281909 6893.53 1 6 CACCTG AAACTGAGT - +4 predrem__nrMotif1470 3 0.281909 6893.53 1 6 CACCTG AAGGAACTG - +4 predrem__nrMotif165 0 0.281909 6893.53 1 6 CACCTG GTCCTGGGA - +4 transfac_pro__M01615-Atf3-Atf6-CrebB-Jra-kay-REPTOR-BP 1 0.281909 6893.53 1 6 CACCTG TTACGTCAT - +4 transfac_pro__M04909-Klf15 0 0.281909 6893.53 1 6 CACCTG CTCCTCCCC - +4 transfac_pro__M06791-disco 1 0.281909 6893.53 1 6 CACCTG CCACCATCA - +4 predrem__nrMotif1578 4 0.281909 6893.53 1 5 CACCTG GTGACCCCA + +4 predrem__nrMotif953 -1 0.281909 6893.53 1 5 CACCTG TTCTTCTCA + +4 transfac_pro__M00651 4 0.281909 6893.53 1 5 CACCTG CGGCCATCT + +4 tiffin__TIFDMEM0000050 4 0.281909 6893.53 1 5 CACCTG AGTTCACTT - +4 flyfactorsurvey__lola-PL_SANGER_2.5_FBgn0005630-lola 5 0.281909 6893.53 1 4 CACCTG TGCCCCACC - +4 cisbp__M5191-Six4 6 0.281909 6893.53 1 3 CACCTG ATTTGATAC + +4 flyfactorsurvey__Six4_Cell_FBgn0027364-Six4 6 0.281909 6893.53 1 3 CACCTG ATTTGATAC + +4 tfdimers__MD00349-pho-phol 9 0.282069 6897.44 1 6 CACCTG AAAACCCATTTCCTGTCCT + +4 hocomoco__NR1D1_HUMAN.H11MO.0.B-Eip75B-Hr3 1 0.282069 6897.44 1 6 CACCTG CCTTCTGACCCACTTCCCT - +4 hocomoco__NR1H4_HUMAN.H11MO.0.B-EcR-svp-usp 13 0.282069 6897.44 1 6 CACCTG CCTCGGGGTCATTGACCCC - +4 taipale_tf_pairs__TEAD4_CLOCK_GGWATGNNNNNNCACGTGN_CAP_repr-Clk-sd 1 0.282069 6897.44 1 6 CACCTG ACACGTGCCCCCACATTCC - +4 transfac_pro__M06339 15 0.282069 6897.44 1 4 CACCTG GGATCTAGTCGCGGCCACC + +4 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNCACGTGN_CAP_repr-Max-TfAP-2 1 0.282574 6909.78 1 6 CACCTG TGGCCTCAGGCCAAACACGTGC + +4 tfdimers__MD00366-MTF-1-ovo 6 0.282574 6909.78 1 6 CACCTG CCCCCCCCCCTCCCCACCCCCC - +4 taipale_tf_pairs__HOXD12_TBX21_NGGTGTNNNNNNNNNNNNNCACNTNNTWAN_CAP_repr 19 0.283012 6920.5 1 6 CACCTG AGGTGTGTGGCGGTGTTAACACCTCATAAA + +4 tfdimers__MD00565 10 0.283083 6922.22 1 6 CACCTG TCTCCCTCCCCATCTGTCACTGCCTTC - +4 dbcorrdb__ARID3A__ENCSR000EFY_1__m4 4 0.283131 6923.39 1 6 CACCTG ATGATATCAGTCAGTCGGCT + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m1-brm-bs-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-srp-Stat92E-svp 5 0.283131 6923.39 1 6 CACCTG GTCCTTATCTGGGCCAACCA + +4 dbcorrdb__POLR3A__ENCSR000DNU_1__m3-CG17209 4 0.283131 6923.39 1 6 CACCTG TCGAGACCAGCCTGGGCCAC + +4 dbcorrdb__RBBP5__ENCSR000AQC_1__m4-Rbbp5 9 0.283131 6923.39 1 6 CACCTG CGCGTCCGTCCGCTGCGGCG + +4 dbcorrdb__RCOR1__ENCSR000EFG_1__m2-CoRest 4 0.283131 6923.39 1 6 CACCTG TCCGCAGCTGTCCAATGTGC + +4 dbcorrdb__RFX5__ENCSR000EHY_1__m1-CG9727-Rfx 2 0.283131 6923.39 1 6 CACCTG TCTGCCTAGCAACAGCTGAC + +4 dbcorrdb__SRF__ENCSR000BGE_1__m1-bs-Mef2 4 0.283131 6923.39 1 6 CACCTG CCATGGCCATATATGGCCAG + +4 dbcorrdb__SRF__ENCSR000BIV_1__m1-bs 7 0.283131 6923.39 1 6 CACCTG CGGACATTTCCTTATATGGT + +4 dbcorrdb__BDP1__ENCSR000DNX_1__m1-Bdp1-Brf-CG17209-Hsf-SREBP 10 0.283131 6923.39 1 6 CACCTG GCGGGATTCGCACCCTGGTC - +4 dbcorrdb__GATA2__ENCSR000EVW_1__m2-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 7 0.283131 6923.39 1 6 CACCTG AAGTCATTTCCTGTTTTTGA - +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m1-egg 3 0.283131 6923.39 1 6 CACCTG CGGGACCTTCATGCAGAAGT - +4 dbcorrdb__STAT5A__ENCSR000BRR_1__m2-CoRest-CycT-ebi-GATAe-grn-Jra-pnr-srp-Stat92E-svp 5 0.283131 6923.39 1 6 CACCTG TATCTTATCTGCCTGACCCA - +4 hocomoco__ZN554_HUMAN.H11MO.0.C-Kr 7 0.283131 6923.39 1 6 CACCTG AGCACCCCACATGGCTCAGC - +4 taipale_cyt_meth__NR1D2_NAWNTRGGTCANTRGGTCAN_eDBD_meth-eg-Eip75B-Hr3-kni-knrl 10 0.283131 6923.39 1 6 CACCTG CTGACCCACTGACCCACATC - +4 taipale_tf_pairs__MYBL1_FIGLA_NCASSTGNNNNNYAACSGYN_CAP_repr-Myb 13 0.283131 6923.39 1 6 CACCTG GACCGTTACCTCCCAGCTGT - +4 cisbp__M4440-fkh-Hsf 6 0.283268 6926.76 1 6 CACCTG GCCCAGAACATTCTGTTCCCT + +4 taipale_cyt_meth__ETV3_NNAGGAANNNNNNNTTCCTNN_eDBD_meth-Eip74EF-Ets21C-Ets65A-Ets97D-pnt 14 0.283268 6926.76 1 6 CACCTG ACAGGAAGTGGCACTTCCTGT - +4 taipale_tf_pairs__GCM1_FIGLA_CAGCTGNNNNNNNNNTGCGGG_CAP-gcm-gcm2 15 0.283268 6926.76 1 6 CACCTG CCCGCATCCTACGAACAGCTG - +4 transfac_pro__M01562 13 0.283268 6926.76 1 6 CACCTG TCGGCTTCAGCCGCACGAGTG - +4 cisbp__M4081-bigmax-cyc-Max-Mitf-Mondo-SREBP-tgo-Usf 4 0.284343 6953.04 1 6 CACCTG ATATCACGTGATTT + +4 neph__UW.Motif.0381 1 0.284343 6953.04 1 6 CACCTG AAACATATTTTCTG + +4 swissregulon__sacCer__HAP5-Mes4-Nf-YA-Nf-YB-Nf-YC-kay 2 0.284343 6953.04 1 6 CACCTG GGGATCTGATTGGT + +4 taipale_tf_pairs__TEAD4_MAX_RGAATGYNNACGTG_CAP_repr-Max-sd 8 0.284343 6953.04 1 6 CACCTG GGAATGCGCACGTG + +4 transfac_public__M00158-btd-EcR-eg-fkh-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 1 0.284343 6953.04 1 6 CACCTG TGACCTTTGAACCT + +4 transfac_pro__M00340-aop-Ets96B-Ets97D-pnt 6 0.284343 6953.04 1 6 CACCTG ACTTACTTCCTGTC - +4 transfac_pro__M01245 3 0.284343 6953.04 1 6 CACCTG ACCAACTTTTACCA - +4 transfac_pro__M09537 4 0.284343 6953.04 1 6 CACCTG TGACCAGCTGTCAA - +4 transfac_public__M00033-nej 7 0.284343 6953.04 1 6 CACCTG CACTCACTCCCTGA - +4 neph__UW.Motif.0429 10 0.284343 6953.04 1 4 CACCTG GAGTTTTTTTTTCC + +4 scertf__macisaac.GTS1 0 0.285032 6969.88 1 6 CACCTG TACCAA + +4 swissregulon__sacCer__CST6-Atf3-CrebB-Jra-Xbp1-kay -1 0.285032 6969.88 1 5 CACCTG ACGTCA - +4 cisbp__M6486 7 0.285281 6975.99 1 6 CACCTG CGGCTGTTACCCTGGG + +4 jaspar__MA0578.1 7 0.285281 6975.99 1 6 CACCTG TTTTATGTACCTTATT + +4 neph__UW.Motif.0288 10 0.285281 6975.99 1 6 CACCTG TCCCTGCTGCCAGCTG - +4 neph__UW.Motif.0483 9 0.285281 6975.99 1 6 CACCTG CAGAATTCAGATTTTT - +4 neph__UW.Motif.0489 9 0.285281 6975.99 1 6 CACCTG GGAAATAATTTCTTTC - +4 transfac_pro__M01402-abd-A-Antp-bsh-btn-eve-exex-ind-lab-Lim3-pb-Scr-slou-Ubx 10 0.285281 6975.99 1 6 CACCTG TTGAGCTAATTACCTT - +4 transfac_pro__M01438-abd-A-Antp-Awh-bsh-E5-ems-eve-exex-lab-Lim3-pb-Scr-slou-Ubx 10 0.285281 6975.99 1 6 CACCTG ATGAGCTAATTACCTT - +4 transfac_pro__M01449-abd-A-Abd-B-cad-eve-Ubx 9 0.285281 6975.99 1 6 CACCTG AAATTTTATTACCCTT - +4 taipale__TBX21_DBD_GGTGTGANNTCACACC 12 0.285281 6975.99 1 4 CACCTG GGTGTGAATTCACACC - +4 cisbp__M4550-ac-ase-bigmax-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.28558 6983.29 1 6 CACCTG GGTCACGTGAC + +4 fantom__motif127_TTTTTACCCTC 4 0.28558 6983.29 1 6 CACCTG TTTTTACCCTC + +4 taipale_cyt_meth__FLI1_NACCGGAARTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.28558 6983.29 1 6 CACCTG AACCGGAAGTC + +4 cisbp__M4595-brm-CoRest-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Sirt6-Snr1-srp-svp 4 0.28558 6983.29 1 6 CACCTG TTCTTATCTGT - +4 cisbp__M6379 2 0.28558 6983.29 1 6 CACCTG TCCACTTAACT - +4 flyfactorsurvey__Eip75B_SANGER_5_FBgn0000568-Eip75B-Hr3 1 0.28558 6983.29 1 6 CACCTG TGACCCACATA - +4 swissregulon__sacCer__YPR013C 5 0.28558 6983.29 1 6 CACCTG TGATTTACGTT - +4 taipale_cyt_meth__ETV4_NRCCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.28558 6983.29 1 6 CACCTG CACTTCCGGTC - +4 transfac_pro__M07702-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.28558 6983.29 1 6 CACCTG CACTTCCGGTC - +4 hocomoco__ZN449_HUMAN.H11MO.0.C 6 0.28558 6983.29 1 5 CACCTG AAGCCCAACCA - +4 transfac_pro__M08990 7 0.28558 6983.29 1 4 CACCTG CATCCCACACC - +4 tfdimers__MD00135-EcR-usp 8 0.286915 7015.93 1 6 CACCTG ATTTAACTGTCCTTATAAAACTTTAT + +4 predrem__nrMotif1340 2 0.287378 7027.24 1 6 CACCTG CCCACCCCATCCC + +4 transfac_pro__M05449 0 0.287378 7027.24 1 6 CACCTG AATCTGCTAGCAC + +4 transfac_pro__M09207 1 0.287378 7027.24 1 6 CACCTG GAATCTTTGATTC - +4 hocomoco__FOXO6_HUMAN.H11MO.0.D-fd59A-foxo-slp2 8 0.287378 7027.24 1 5 CACCTG AACTTGTTTACGT + +4 cisbp__M1880-HLH4C 3 0.287949 7041.22 1 6 CACCTG ACGCAGCTGCGC + +4 flyfactorsurvey__cwo_SANGER_5_FBgn0259938-Mitf-SREBP-Usf-cnc-cwo-cyc-tgo 2 0.287949 7041.22 1 6 CACCTG GTCACGTGACCA + +4 hocomoco__MYCN_HUMAN.H11MO.0.A-Max-Myc-Sap30 3 0.287949 7041.22 1 6 CACCTG GGCCACGTGGGC + +4 stark__AATNNNNCATNR 5 0.287949 7041.22 1 6 CACCTG AATAAAACATAA + +4 taipale_cyt_meth__MYOD1_NAACANNTGTYN_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.287949 7041.22 1 6 CACCTG CAACAGCTGTTG + +4 transfac_pro__M03878-shn 6 0.287949 7041.22 1 6 CACCTG ACACCCCAGCTG + +4 transfac_pro__M05737 5 0.287949 7041.22 1 6 CACCTG TGTGGCACGTGC + +4 cisbp__M1969-nerfin-1-nerfin-2 3 0.287949 7041.22 1 6 CACCTG CGCCCCCTGACA - +4 cisbp__M5444-bin-br-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-Nf1-slp1-slp2 6 0.287949 7041.22 1 6 CACCTG TTTGTTTACTTA - +4 hocomoco__BHE23_HUMAN.H11MO.0.D-Oli 1 0.287949 7041.22 1 6 CACCTG CCACCATATGCT - +4 neph__UW.Motif.0122 5 0.287949 7041.22 1 6 CACCTG TGTGTTTTCTCA - +4 neph__UW.Motif.0293 5 0.287949 7041.22 1 6 CACCTG AAAGTGACTTTT - +4 stark__TNATGNNTGACA 5 0.287949 7041.22 1 6 CACCTG TGTCAAACATAA - +4 swissregulon__hs__NHLH1_2.p2-HLH4C 3 0.287949 7041.22 1 6 CACCTG GCGCAGCTGCGG - +4 taipale_cyt_meth__ELF2_NACCCGGAAGTN_FL-aop-Eip74EF-Ets21C-Ets96B 0 0.287949 7041.22 1 6 CACCTG TACTTCCGGGTT - +4 taipale_cyt_meth__ELF4_NACCMGGAAGTN_eDBD_meth-aop-Eip74EF-Ets96B 0 0.287949 7041.22 1 6 CACCTG TACTTCCTGGTT - +4 taipale_cyt_meth__JDP2_NRTGAYGTCAYN_FL_meth-Atf3-Atf6-cnc-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.287949 7041.22 1 6 CACCTG CATGACATCACC - +4 taipale_cyt_meth__PKNOX1_TGACANNTGTCA_FL_meth-achi-hth-nau-vis 3 0.287949 7041.22 1 6 CACCTG TGACAGCTGTCA - +4 transfac_pro__M05881 1 0.287949 7041.22 1 6 CACCTG TCACCCAAATCT - +4 transfac_pro__M06066 6 0.287949 7041.22 1 6 CACCTG TCCTCATACCCG - +4 transfac_pro__M06650 6 0.287949 7041.22 1 6 CACCTG GCGGGTTACAAG - +4 transfac_pro__M06670 3 0.287949 7041.22 1 6 CACCTG TCGTCCCTCATG - +4 transfac_pro__M05713-ham-usp 7 0.287949 7041.22 1 5 CACCTG GGGTCATGACCA - +4 transfac_pro__M06050 7 0.287949 7041.22 1 5 CACCTG TCTTTCGGACCA - +4 transfac_pro__M06111 7 0.287949 7041.22 1 5 CACCTG GCGTCCGCACCG - +4 transfac_pro__M06146 7 0.287949 7041.22 1 5 CACCTG TATGACCGACCG - +4 transfac_pro__M06264 7 0.287949 7041.22 1 5 CACCTG TTTGTAAAACCC - +4 transfac_pro__M06812 7 0.287949 7041.22 1 5 CACCTG GGAAATGCACCA - +4 transfac_pro__M06861 7 0.287949 7041.22 1 5 CACCTG TTTCCCCTACCT - +4 transfac_pro__M06610 8 0.287949 7041.22 1 4 CACCTG GAGTGCTATACC + +4 hocomoco__SRF_MOUSE.H11MO.0.A-bs 1 0.289947 7090.08 1 6 CACCTG TTTCCTTATTTGGCCAT + +4 transfac_pro__M01318-ara-caup-mirr 4 0.289947 7090.08 1 6 CACCTG AATATACATGTAATATT + +4 transfac_pro__M02774-pan 2 0.289947 7090.08 1 6 CACCTG GATCCCTTTGATCTATC + +4 taipale_tf_pairs__GCM1_SOX2_RTRSGGGNNNATTGTKY_CAP_repr-gcm-gcm2-SoxN 8 0.289947 7090.08 1 6 CACCTG GAACAATGCACCCGCAT - +4 transfac_pro__M01434-Abd-B 10 0.289947 7090.08 1 6 CACCTG AGGATTTTACGACCTTA - +4 tfdimers__MD00148 6 0.290228 7096.93 1 6 CACCTG CCCCGGTCCCTGGGGGCCCCGGGGC - +4 cisbp__M0168-achi-hth-nau-vis 2 0.291274 7122.53 1 6 CACCTG GACAGCTG + +4 neph__UW.Motif.0031 1 0.291274 7122.53 1 6 CACCTG AAACATTT + +4 transfac_public__M00009-ttk 1 0.291274 7122.53 1 6 CACCTG GGTCCTGC + +4 cisbp__M0034 0 0.291274 7122.53 1 6 CACCTG CACCGACA - +4 cisbp__M0795-GATAd-GATAe-grn-pnr-srp 2 0.291274 7122.53 1 6 CACCTG CTTATCTA - +4 cisbp__M6352-E2f1-Max-Myc 1 0.291274 7122.53 1 6 CACCTG CCACGTGG - +4 hdpi__HCLS1-Cortactin 0 0.291274 7122.53 1 6 CACCTG GACGTGGC - +4 jaspar__MA0318.1 2 0.291274 7122.53 1 6 CACCTG ATTACATG - +4 jaspar__MA0996.1 0 0.291274 7122.53 1 6 CACCTG CACCGACA - +4 swissregulon__sacCer__GAT4 2 0.291274 7122.53 1 6 CACCTG TAGATCTA - +4 yetfasco__YCR096C_558 2 0.291274 7122.53 1 6 CACCTG ATTACATG - +4 cisbp__M0052 3 0.291274 7122.53 1 5 CACCTG AGCTAGCT + +4 neph__UW.Motif.0083-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt -1 0.291274 7122.53 1 5 CACCTG ACTTCCGG + +4 cisbp__M0497 -1 0.291274 7122.53 1 5 CACCTG AACTGCAA - +4 cisbp__M1869-GATAe-grn-pnr-srp 3 0.291274 7122.53 1 5 CACCTG TCTTATCT - +4 homer__AGATAASR_GATA3-CoRest-GATAe-Jra-Snr1-Stat92E-ebi-grn-pnr-srp 3 0.291274 7122.53 1 5 CACCTG TGTTATCT - +4 jaspar__MA0037.2-GATAe-grn-pnr-srp 3 0.291274 7122.53 1 5 CACCTG TCTTATCT - +4 predrem__nrMotif501 4 0.291274 7122.53 1 4 CACCTG CCATCAGC + +4 taipale_tf_pairs__TFAP2C_MAX_TNSCCNNNGGSNNNNNNNNNNNNNCACGTGN_CAP_repr-Max-TfAP-2 19 0.291863 7136.93 1 6 CACCTG GCACGTGCTCCCCCCATATCGCCTGAGGCCA - +4 cisbp__M1935-fkh-Hsf 2 0.292251 7146.42 1 6 CACCTG AGAACATTCTGTTCT + +4 cisbp__M2121-kay-Mes4-Nf-YB-Nf-YC 3 0.292251 7146.42 1 6 CACCTG TGGGATCTGATTGGT + +4 neph__UW.Motif.0272 8 0.292251 7146.42 1 6 CACCTG GAAATCAGTGGCTCA + +4 neph__UW.Motif.0346 3 0.292251 7146.42 1 6 CACCTG CATCATTTTTCCCAG + +4 jaspar__MA0505.1-ERR-EcR-Hr4-ey-ftz-f1-toy-usp 3 0.292251 7146.42 1 6 CACCTG GCTGACCTTGAACTT - +4 neph__UW.Motif.0434 6 0.292251 7146.42 1 6 CACCTG TCTGGCTGCTGGGAG - +4 taipale_cyt_meth__HNF4A_NRGGTCAAAGTCCRN_eDBD-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 9 0.292251 7146.42 1 6 CACCTG TTGGACTTTGACCCC - +4 taipale_tf_pairs__FLI1_MAX_RSCGGAANCACGTGN_CAP-Max 1 0.292251 7146.42 1 6 CACCTG CCACGTGTTTCCGGT - +4 taipale_tf_pairs__GCM1_ELK3_RTGCGGGCGGAAGTN_CAP_repr-gcm-gcm2 0 0.292251 7146.42 1 6 CACCTG CACTTCCGCCCGCAT - +4 cisbp__M1398 4 0.292304 7147.71 1 6 CACCTG TCAGTTCCTA + +4 cisbp__M1564 4 0.292304 7147.71 1 6 CACCTG ACCGTACGGT + +4 cisbp__M1648 4 0.292304 7147.71 1 6 CACCTG GTGGGCCCAC + +4 cisbp__M1706 2 0.292304 7147.71 1 6 CACCTG TTTGCCGAGG + +4 cisbp__M1718 3 0.292304 7147.71 1 6 CACCTG TTATGCCGAG + +4 cisbp__M1749 3 0.292304 7147.71 1 6 CACCTG TTTTTCCGGA + +4 cisbp__M5263-Max-Mitf-Usf 2 0.292304 7147.71 1 6 CACCTG ACCACGTGAC + +4 flyfactorsurvey__lola-PF_SANGER_5_FBgn0005630-lola 0 0.292304 7147.71 1 6 CACCTG CAACTCCACT + +4 homer__GGTCACGTGA_USF1-Max-Mitf-Myc-SREBP-Usf-cnc-cwo-tgo 3 0.292304 7147.71 1 6 CACCTG GGTCACGTGA + +4 homer__NCCTTATCTC_Gata2-CoRest-CycT-GATAe-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.292304 7147.71 1 6 CACCTG TCCTTATCTG + +4 jaspar__MA1064.1 4 0.292304 7147.71 1 6 CACCTG GTGGGCCCAC + +4 predrem__nrMotif103 1 0.292304 7147.71 1 6 CACCTG TTCCCTGAGG + +4 predrem__nrMotif1068 1 0.292304 7147.71 1 6 CACCTG CCCCCTCCAT + +4 predrem__nrMotif2060 1 0.292304 7147.71 1 6 CACCTG AAACCACACT + +4 predrem__nrMotif2280 3 0.292304 7147.71 1 6 CACCTG TGTTATCTTT + +4 taipale__HEY1_DBD_NNCACGTGNN-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn-tai 2 0.292304 7147.71 1 6 CACCTG GACACGTGCC + +4 taipale__TFAP4_DBD_AWCAGCTGWT-crp 2 0.292304 7147.71 1 6 CACCTG AACAGCTGAT + +4 taipale_cyt_meth__MAFG_TGCTGACGYN_FL_meth-maf-S 4 0.292304 7147.71 1 6 CACCTG TGCTGACATG + +4 taipale_cyt_meth__SREBF2_ATCACGTGAY_eDBD-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.292304 7147.71 1 6 CACCTG ATCACGTGAC + +4 transfac_pro__M00735 2 0.292304 7147.71 1 6 CACCTG TTGACCGAGC + +4 transfac_pro__M05101 4 0.292304 7147.71 1 6 CACCTG GCTCCCCCTT + +4 transfac_pro__M07593-Max-Myc 2 0.292304 7147.71 1 6 CACCTG GCCACGTGGC + +4 transfac_pro__M07634-crp-nau 2 0.292304 7147.71 1 6 CACCTG ATCAGCTGTT + +4 transfac_pro__M07642-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 2 0.292304 7147.71 1 6 CACCTG GGCACGTGCC + +4 transfac_public__M00175-crp 2 0.292304 7147.71 1 6 CACCTG CTCAGCTGGT + +4 c2h2_zfs__M0462-klu-sr 0 0.292304 7147.71 1 6 CACCTG TACCCCACAC - +4 cisbp__M0269-Atf3-Atf6-CrebA-CrebB-E2f1-Irbp18-Jra-Xbp1-crc-kay 1 0.292304 7147.71 1 6 CACCTG TGACGTCACC - +4 cisbp__M0427-CG2790 1 0.292304 7147.71 1 6 CACCTG CCACCACCCC - +4 cisbp__M0699-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 2 0.292304 7147.71 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M0709-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.292304 7147.71 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M0855-achi-esg-hth-sna-vis-wor 3 0.292304 7147.71 1 6 CACCTG TGTGACAGGT - +4 cisbp__M3321-GATAe-grn-pnr-srp 3 0.292304 7147.71 1 6 CACCTG TCTTATCTCT - +4 cisbp__M4627-E2f1-Max-Myc 3 0.292304 7147.71 1 6 CACCTG GAGCACGTGG - +4 cisbp__M5255-da-twi 0 0.292304 7147.71 1 6 CACCTG AACATCTGGT - +4 cisbp__M5632-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.292304 7147.71 1 6 CACCTG ATCACGTGAT - +4 flyfactorsurvey__twi_da_SANGER_5_FBgn0000413-da-twi 0 0.292304 7147.71 1 6 CACCTG AACATCTGGT - +4 homer__ACVAGGAAGT_ELF5-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-aop 2 0.292304 7147.71 1 6 CACCTG ACTTCCTCGT - +4 neph__UW.Motif.0018-Rfx 2 0.292304 7147.71 1 6 CACCTG GTTTCCAGGG - +4 neph__UW.Motif.0025 1 0.292304 7147.71 1 6 CACCTG GGGCCTGCGC - +4 predrem__nrMotif1224 3 0.292304 7147.71 1 6 CACCTG AGATGCCTGG - +4 predrem__nrMotif1481 4 0.292304 7147.71 1 6 CACCTG ATGAAAACTT - +4 predrem__nrMotif2379 4 0.292304 7147.71 1 6 CACCTG GGGCCTCCTG - +4 predrem__nrMotif2604 2 0.292304 7147.71 1 6 CACCTG CCGGCCTGCC - +4 taipale__BHLHB2_DBD_NKCACGTGMN-bigmax-Clk-cnc-cwo-cyc-mio-Mitf-Mondo-Sirt6-SREBP-tgo-Usf 2 0.292304 7147.71 1 6 CACCTG GTCACGTGAT - +4 taipale_cyt_meth__SREBF1_NTCACGTGAN_eDBD-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.292304 7147.71 1 6 CACCTG ATCACGTGAC - +4 transfac_pro__M05553-btd-cbt-Sp1-Spps 0 0.292304 7147.71 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M07632-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.292304 7147.71 1 6 CACCTG AACAGCTGTT - +4 transfac_pro__M08921-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.292304 7147.71 1 6 CACCTG ATGACGTCAT - +4 flyfactorsurvey__Eip74EF_SANGER_5_FBgn0000567-Eip74EF-Ets21C -1 0.292304 7147.71 1 5 CACCTG ACCCGGAAGT + +4 predrem__nrMotif1125 5 0.292304 7147.71 1 5 CACCTG CCCCGTCCCT + +4 flyfactorsurvey__nub_FlyReg_FBgn0085424-nub -1 0.292304 7147.71 1 5 CACCTG GCTTGCATAA - +4 transfac_pro__M07565 6 0.292304 7147.71 1 4 CACCTG GGGGCCCACC + +4 transfac_pro__M09565 -2 0.292304 7147.71 1 4 CACCTG CCGGAATTTC + +4 predrem__nrMotif62 6 0.292304 7147.71 1 4 CACCTG CTTCCCCACC - +4 neph__UW.Motif.0020 7 0.292304 7147.71 1 3 CACCTG AATGATTCAC + +4 tfdimers__MD00203-pho-phol 8 0.293028 7165.42 1 6 CACCTG GAACATAACACCAGATGGTGTCCAATTG - +4 transfac_public__M00212 12 0.293354 7173.39 1 6 CACCTG CAATAAAACCTCTCTCTG + +4 cisbp__M1910-bs 1 0.293354 7173.39 1 6 CACCTG TTGCCTTATTTGGGCATG - +4 flyfactorsurvey__CG7928_SANGER_10_FBgn0039740-ZIPIC 12 0.293354 7173.39 1 6 CACCTG GGGTGTTATGCAGCCCTG - +4 taipale_tf_pairs__ERF_SREBF2_NNCACGTGACMGGAARNN_CAP_repr-Ets21C-SREBP 10 0.293354 7173.39 1 6 CACCTG CACTTCCGGTCACGTGAT - +4 taipale_tf_pairs__ETV5_HES7_CCGGAANNNNNNCACGTG_CAP-Ets96B 12 0.293354 7173.39 1 6 CACCTG CACGCGCTGCGCTTCCGG - +4 transfac_pro__M07227-bs 1 0.293354 7173.39 1 6 CACCTG TTGCCTTATTTGGGCATG - +4 swissregulon__hs__EWSR1-FLI1.p2 -2 0.293354 7173.39 1 4 CACCTG CCTTCCTTCCTTCCTTCC - +4 cisbp__M1804 0 0.293474 7176.33 1 6 CACCTG ATCCGAG + +4 jaspar__MA0292.1 0 0.293474 7176.33 1 6 CACCTG CTCCGGA + +4 predrem__nrMotif664 0 0.293474 7176.33 1 6 CACCTG TCCCTCA + +4 predrem__nrMotif781 1 0.293474 7176.33 1 6 CACCTG TCATCTA - +4 elemento__ACCGTTA -1 0.293474 7176.33 1 5 CACCTG ACCGTTA + +4 predrem__nrMotif790 -1 0.293474 7176.33 1 5 CACCTG CCCTAAA + +4 cisbp__M1810 3 0.294562 7202.92 1 6 CACCTG TATCTCCGA + +4 cisbp__M5223-Clk-Hey-tai 2 0.294562 7202.92 1 6 CACCTG GACACGTGC + +4 cisbp__M6518-Clk-cnc-cwo-cyc-Max-Mitf-tgo-Usf 3 0.294562 7202.92 1 6 CACCTG GGTCACGTG + +4 flyfactorsurvey__Oli_da_SANGER_5_3_FBgn0000413-CG8319-Oli-ato-da 1 0.294562 7202.92 1 6 CACCTG ACATCTGTC + +4 hocomoco__TFEB_HUMAN.H11MO.0.C-Clk-Max-Mitf-Usf-cnc-cwo-cyc-tgo 3 0.294562 7202.92 1 6 CACCTG GGTCACGTG + +4 predrem__nrMotif1046 0 0.294562 7202.92 1 6 CACCTG GTCCTCTCC + +4 predrem__nrMotif2680 1 0.294562 7202.92 1 6 CACCTG AGACCAAGA + +4 predrem__nrMotif359 3 0.294562 7202.92 1 6 CACCTG TTTGCCCTT + +4 predrem__nrMotif558 2 0.294562 7202.92 1 6 CACCTG AGAACCCAC + +4 predrem__nrMotif899 1 0.294562 7202.92 1 6 CACCTG AAATCTGCT + +4 swissregulon__sacCer__MATALPHA2 3 0.294562 7202.92 1 6 CACCTG AATTACATG + +4 taipale__Nkx3-1_DBD_NCCACTTAA-bap 2 0.294562 7202.92 1 6 CACCTG ACCACTTAA + +4 transfac_pro__M04748-aop-bs-Eip74EF-Ets21C-Ets96B-Ets97D 0 0.294562 7202.92 1 6 CACCTG AACCGGAAG + +4 cisbp__M0651 1 0.294562 7202.92 1 6 CACCTG GCACTTTTT - +4 cisbp__M1886 0 0.294562 7202.92 1 6 CACCTG TAACCGTTT - +4 elemento__CAACAAGTG 0 0.294562 7202.92 1 6 CACCTG CACTTGTTG - +4 jaspar__MA0974.1 1 0.294562 7202.92 1 6 CACCTG GCACTTTTT - +4 predrem__nrMotif1040 1 0.294562 7202.92 1 6 CACCTG ATTCCTTGA - +4 predrem__nrMotif1516 1 0.294562 7202.92 1 6 CACCTG ACATCTACT - +4 predrem__nrMotif351 3 0.294562 7202.92 1 6 CACCTG AATGACTTT - +4 swissregulon__sacCer__YER130C-CG10348-CG13296-ham 0 0.294562 7202.92 1 6 CACCTG CCCCTATTT - +4 transfac_pro__M00975-CG5846-Rfx 3 0.294562 7202.92 1 6 CACCTG TGGCAACAG - +4 transfac_pro__M04737-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 3 0.294562 7202.92 1 6 CACCTG GTTTACTTA - +4 transfac_pro__M06766 0 0.294562 7202.92 1 6 CACCTG AATCTTAGT - +4 transfac_pro__M07041-HDAC1 0 0.294562 7202.92 1 6 CACCTG GACCCTGCC - +4 transfac_pro__M08825-NfI 1 0.294562 7202.92 1 6 CACCTG ATGTCTGGC - +4 cisbp__M0933-achi-esg-hth-sna-vis-wor -1 0.294562 7202.92 1 5 CACCTG AGCTGTCAA + +4 predrem__nrMotif2109 4 0.294562 7202.92 1 5 CACCTG AGAACATCT - +4 predrem__nrMotif244 4 0.294562 7202.92 1 5 CACCTG CAGACCCCA - +4 stark__WTGACANBT -1 0.294562 7202.92 1 5 CACCTG AGATGTCAA - +4 predrem__nrMotif1745 5 0.294562 7202.92 1 4 CACCTG AATCCCACC + +4 predrem__nrMotif1925 5 0.294562 7202.92 1 4 CACCTG CCCAAAACA + +4 cisbp__M5088-lola 5 0.294562 7202.92 1 4 CACCTG TGCCCCACC - +4 taipale_tf_pairs__GCM1_FIGLA_CAGCTGNNNNNNNNNNNTGCGGG_CAP-gcm-gcm2 17 0.295069 7215.31 1 6 CACCTG CCCGCATGCGTCGCGCCCACCTG - +4 tfdimers__MD00102-lz-pho-phol-run-RunxA-RunxB 8 0.295069 7215.31 1 6 CACCTG ATAACCCACACCAGATGGCAGCT - +4 tfdimers__MD00436-lz-run-RunxA-RunxB 13 0.295069 7215.31 1 6 CACCTG CTTCTTTAATCCACACCACTTTT - +4 cisbp__M3415-EcR-eg-fkh-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 12 0.295615 7228.67 1 6 CACCTG TCGTGACCTTTGACCCTGT + +4 cisbp__M6385-EcR-usp 12 0.295615 7228.67 1 6 CACCTG CTGAACTTTTTTGACCTCA + +4 transfac_pro__M06557 12 0.295615 7228.67 1 6 CACCTG CGGAAGGGGTCAAAACTTC + +4 hocomoco__NR1I2_HUMAN.H11MO.0.C-EcR-usp 2 0.295615 7228.67 1 6 CACCTG CTGAACTTTTTTGACCCCA - +4 taipale_tf_pairs__HOXD12_FIGLA_SYMRTAAANNNNCASSTGN_CAP_repr 1 0.295615 7228.67 1 6 CACCTG CCAGCTGGCTTTTTACGAC - +4 transfac_public__M00134-EcR-eg-fkh-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-svp-usp 12 0.295615 7228.67 1 6 CACCTG TCGTGACCTTTGACCCTGT - +4 transfac_pro__M09361 -2 0.295615 7228.67 1 4 CACCTG CCTGTTTTACACGGCATCT + +4 tfdimers__MD00014 11 0.296465 7249.47 1 6 CACCTG TTTTTTTAATCCTCCTTTTTTC - +4 tfdimers__MD00053 9 0.296465 7249.47 1 6 CACCTG CCCCCCCACCATCTGCCCCCTC - +4 dbcorrdb__ATF3__ENCSR000DOG_1__m1-cnc-CrebB-cyc-E2f1-ERR-E(z)-Jra-Max-Myc-Sin3A-SREBP-tna-Usf 7 0.296825 7258.26 1 6 CACCTG GTCACGTCACCCGCGCGCGC + +4 dbcorrdb__EP300__ENCSR000DZG_1__m3-foxo-nej 7 0.296825 7258.26 1 6 CACCTG CTGATGTCACTTCCTGTTTT + +4 dbcorrdb__POLR3A__ENCSR000DNU_1__m2-Bdp1-Brf-CG17209-ebi-Tbp 11 0.296825 7258.26 1 6 CACCTG AACCACTGAGCCACCGCGCC + +4 dbcorrdb__ZNF274__ENCSR000EVG_1__m5 5 0.296825 7258.26 1 6 CACCTG AGTCAGAGCTCATAACTCAT + +4 transfac_pro__M01558-bigmax-Mitf-Mondo-SREBP-Usf 7 0.296825 7258.26 1 6 CACCTG GATGCATCACGTGATGCACT + +4 dbcorrdb__EP300__ENCSR000AQB_1__m4-nej 2 0.296825 7258.26 1 6 CACCTG GCCACTTTTCTCCTGTTGCA - +4 dbcorrdb__JUN__ENCSR000EGH_1__m3-CG9650-cnc-ewg-Jra-kay-maf-S 12 0.296825 7258.26 1 6 CACCTG TCAGCAGTGACTCAGCAGGT - +4 dbcorrdb__NR3C1__ENCSR000BHE_1__m1-fkh 3 0.296825 7258.26 1 6 CACCTG AAGGACAGTCTGTTCTCGCC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m7-RpII215 14 0.296825 7258.26 1 6 CACCTG TTACTCGGTGGGAATAACTT - +4 dbcorrdb__POLR3G__ENCSR000EYU_1__m1-AMPKalpha-Bdp1-Brf-CG17209-CG43143-Hsf-SREBP 14 0.296825 7258.26 1 6 CACCTG CCGGCCGGGATTCGAACCCG - +4 dbcorrdb__SIN3A__ENCSR000BOW_1__m1-CrebB-E2f1-ERR-Max-Myc-Rfx-Sin3A 5 0.296825 7258.26 1 6 CACCTG GCCGTCGCCAGGGCCCCGCG - +4 dbcorrdb__SP2__ENCSR000BOU_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 3 0.296825 7258.26 1 6 CACCTG CAGCACCATGGACAGCGCCC - +4 dbcorrdb__TBL1XR1__ENCSR000EGA_1__m4-CG17209-ebi 10 0.296825 7258.26 1 6 CACCTG CCGGGACTCGAAGCAGCAGC - +4 dbcorrdb__YY1__ENCSR000EUM_1__m2-CG10431-pho-phol 1 0.296825 7258.26 1 6 CACCTG CATCTTGGCTGCGGGCAGGC - +4 transfac_pro__M07895-bi-byn-Doc2 15 0.296825 7258.26 1 5 CACCTG AGGTGTGAAATTTCACACCT + +4 transfac_pro__M05232 13 0.297079 7264.48 1 6 CACCTG GTGGTTGTCCGGCTTCCTGGC + +4 tfdimers__MD00380-Ing5 11 0.297079 7264.48 1 6 CACCTG TTTTTTTAATCCACCACAATT - +4 transfac_pro__M07636-bigmax-Clk-Max-Mitf-Mondo-SREBP-Usf 13 0.297079 7264.48 1 6 CACCTG ATCACGTGATTATCACGTGAT - +4 cisbp__M2319-pan 0 0.297421 7272.84 1 6 CACCTG TTCCTTTGATCTTT + +4 neph__UW.Motif.0495 8 0.297421 7272.84 1 6 CACCTG CACTGAGTAATTTC + +4 transfac_pro__M00306 6 0.297421 7272.84 1 6 CACCTG TGCCGGTACCGGCT + +4 transfac_pro__M07651-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 4 0.297421 7272.84 1 6 CACCTG TTGGCACGTGCCAA + +4 cisbp__M3695-nej 7 0.297421 7272.84 1 6 CACCTG CACTCACTCCCTGA - +4 cisbp__M5864-aop-Eip74EF 0 0.297421 7272.84 1 6 CACCTG TACTTCCGCTTTTT - +4 hocomoco__PRDM1_HUMAN.H11MO.0.A-Blimp-1-Dif-dl-foxo 1 0.297421 7272.84 1 6 CACCTG TCACTTTCACTTTC - +4 jaspar__MA0523.1-pan 0 0.297421 7272.84 1 6 CACCTG TTCCTTTGATCTTT - +4 taipale_cyt_meth__POU6F1_NTAATGAKATGYRN_FL-pdm3-vvl 3 0.297421 7272.84 1 6 CACCTG GTGCATCTCATTAT - +4 taipale_tf_pairs__FOXO1_ELK3_RTMAACAGGAAGTN_CAP-foxo 3 0.297421 7272.84 1 6 CACCTG CACTTCCTGTTTAC - +4 yetfasco__YGL181W_694 0 0.297719 7280.12 1 6 CACCTG TACCAA - +4 scertf__zhao.YML081W -1 0.297719 7280.12 1 5 CACCTG CCCCGC + +4 hdpi__VIL2-Moe -2 0.297719 7280.12 1 4 CACCTG CCTCCG - +4 cisbp__M2381-CrebB 4 0.298433 7297.58 1 6 CACCTG TGGTGACGTGA + +4 cisbp__M5225-tai 3 0.298433 7297.58 1 6 CACCTG AAACACGTGTC + +4 flyfactorsurvey__tai_SANGER_5_FBgn0041092-tai 3 0.298433 7297.58 1 6 CACCTG AAACACGTGTC + +4 hocomoco__HXC13_HUMAN.H11MO.0.D 5 0.298433 7297.58 1 6 CACCTG ATTTTTACGAG + +4 jaspar__MA0482.1-CoRest-CycT-GATAe-HLH3B-Jra-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.298433 7297.58 1 6 CACCTG TCTTATCTCCC + +4 jaspar__MA0588.1-CrebB 4 0.298433 7297.58 1 6 CACCTG TGGTGACGTAA + +4 neph__UW.Motif.0042 2 0.298433 7297.58 1 6 CACCTG CAGGGCTCTGG + +4 transfac_pro__M07340-sd 3 0.298433 7297.58 1 6 CACCTG ACATTCCTCAG + +4 cisbp__M1095-bap-scro-vnd 3 0.298433 7297.58 1 6 CACCTG AACCACTTAAG - +4 hocomoco__ATF2_HUMAN.H11MO.0.B-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Irbp18-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 2 0.298433 7297.58 1 6 CACCTG ATGACGTCATC - +4 jaspar__MA0293.1 4 0.298433 7297.58 1 6 CACCTG TTTAGATCTTT - +4 jaspar__MA0302.1 4 0.298433 7297.58 1 6 CACCTG TTTAGATCTTT - +4 taipale_cyt_meth__ERG_NACAGGAARTN_eDBD_meth-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.298433 7297.58 1 6 CACCTG CATTTCCTGTT - +4 taipale_cyt_meth__ETV1_NACMGGAWGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-RpII215-Rpn5-run-RunxA-RunxB 3 0.298433 7297.58 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__TFEB_RNCAYGTGAYN_eDBD_meth-Mitf-Usf 3 0.298433 7297.58 1 6 CACCTG GGTCACATGTT - +4 transfac_pro__M01614 4 0.298433 7297.58 1 6 CACCTG TTTAGATCTTT - +4 transfac_pro__M01945 4 0.298433 7297.58 1 6 CACCTG TTTAGATCTTT - +4 transfac_pro__M09459 4 0.298433 7297.58 1 6 CACCTG CGTTGACTTTT - +4 yetfasco__YPL021W_578 4 0.298433 7297.58 1 6 CACCTG TTTAGATCTTT - +4 stark__MATTRRCACNY 6 0.298433 7297.58 1 5 CACCTG AATTAACACAC + +4 transfac_pro__M05315-ind-pb -1 0.298433 7297.58 1 5 CACCTG TCCTTATTAAA + +4 bergman__pan-pan -2 0.298433 7297.58 1 4 CACCTG CCTTTGATCTT + +4 transfac_public__M00362-pan -2 0.298433 7297.58 1 4 CACCTG CCTTTGATCTT + +4 hocomoco__PO3F2_MOUSE.H11MO.0.A-nub-pdm2-vvl 0 0.298581 7301.2 1 6 CACCTG CTCATGCATATGCATA + +4 hocomoco__SPZ1_HUMAN.H11MO.0.D 7 0.298581 7301.2 1 6 CACCTG CGGCTGTTACCCTGGG + +4 taipale_cyt_meth__FLI1_NACCGGATATCCGGTN_FL-Ets21C-Ets97D 0 0.298581 7301.2 1 6 CACCTG GACCGGATATCCGGTC + +4 transfac_pro__M01343-oc-Ptx1 8 0.298581 7301.2 1 6 CACCTG AGGGGGATTAGCTGCC + +4 transfac_pro__M07349-TfAP-2 4 0.298581 7301.2 1 6 CACCTG CATCAGCCTGCAGGCC + +4 neph__UW.Motif.0634 1 0.298581 7301.2 1 6 CACCTG TGTTCTGGGGACAGAG - +4 taipale_cyt_meth__BCL6_NYGTAATCGAGGAATN_eDBD_repr 2 0.298581 7301.2 1 6 CACCTG AATTCCTCGATTACGT - +4 taipale_cyt_meth__MAFF_NYGCTGAYRTCAGCRN_FL-CrebA-CrebB-maf-S 5 0.298581 7301.2 1 6 CACCTG ATGCTGACGTCAGCAT - +4 transfac_pro__M07948-bowl-sob 2 0.298581 7301.2 1 6 CACCTG GCTACCGTGTTACGCA - +4 transfac_public__M00292-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-HDAC1-nej 8 0.298581 7301.2 1 6 CACCTG CCATTGTTTACTTAAG - +4 hdpi__MCTP2-Mctp 0 0.298786 7306.22 1 5 CACCTG TTCCC - +4 hdpi__BRUNOL6-bru3 1 0.298786 7306.22 1 4 CACCTG TGACC - +4 hdpi__LOC51035-CG8209 1 0.298786 7306.22 1 4 CACCTG TTACT - +4 cisbp__M5594 3 0.300459 7347.12 1 6 CACCTG CTCGACCTAATTA + +4 hocomoco__SIX2_HUMAN.H11MO.0.A-Six4-so 3 0.300459 7347.12 1 6 CACCTG TGAAACCTGAGAC + +4 taipale__LBX2_DBD_AATTGGCCAATTA_repr 3 0.300459 7347.12 1 6 CACCTG CTCGACCTAATTA + +4 transfac_pro__M00764-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 1 0.300459 7347.12 1 6 CACCTG TGACCTTTGACCC + +4 transfac_pro__M03880-nau 3 0.300459 7347.12 1 6 CACCTG TGACAGCTGCAGT + +4 cisbp__M1703 7 0.300459 7347.12 1 6 CACCTG TACCGTTGACCAT - +4 cisbp__M5913-TfAP-2 0 0.300459 7347.12 1 6 CACCTG TGCCCCGGGGGCA - +4 taipale__TFAP2A_DBD_NSCCNNNNNGGSN-TfAP-2 0 0.300459 7347.12 1 6 CACCTG TGCCCCGGGGGCA - +4 taipale_cyt_meth__FOXD2_NYWANGTAAACAN_eDBD_meth_repr-croc-fd59A-fkh 5 0.300459 7347.12 1 6 CACCTG ATGTTTACGTAAC - +4 taipale_cyt_meth__FOXI1_NWWNYGTAAACAN_eDBD-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.300459 7347.12 1 6 CACCTG TTGTTTACATTAC - +4 transfac_pro__M00997 4 0.300459 7347.12 1 6 CACCTG CCTTCACTTGGGG - +4 taipale_tf_pairs__POU2F1_ELK1_NCCGGATATGCAN_CAP-nub-pdm2 -1 0.300459 7347.12 1 5 CACCTG ACCGGATATGCAA + +4 cisbp__M4498-Dif-dl-Rel 8 0.300459 7347.12 1 5 CACCTG CTGGAAATCCCCT - +4 taipale_tf_pairs__GCM2_FOXI1_TGTTKATRCGGGN_CAP-gcm-gcm2 -1 0.300459 7347.12 1 5 CACCTG ACCCGCATCAACA - +4 cisbp__M0155 4 0.30096 7359.39 1 6 CACCTG CGGGCACGTGCT + +4 cisbp__M5372-aop-Eip74EF-Ets21C 0 0.30096 7359.39 1 6 CACCTG AACCCGGAAGTA + +4 hocomoco__P73_HUMAN.H11MO.1.A 5 0.30096 7359.39 1 6 CACCTG GAACATGCCTGG + +4 jaspar__MA1025.1 4 0.30096 7359.39 1 6 CACCTG CGGGCACGTGCT + +4 neph__UW.Motif.0494 3 0.30096 7359.39 1 6 CACCTG CTTTTTCTGAAA + +4 predrem__nrMotif503-klu-sr 4 0.30096 7359.39 1 6 CACCTG CCCCCTCCTCCC + +4 taipale_cyt_meth__CREB1_NRTGACGTCAYN_FL-Atf3-Atf6-CG7786-cnc-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.30096 7359.39 1 6 CACCTG CGTGACGTCACG + +4 taipale_cyt_meth__PKNOX1_TGACANNTGTCA_FL-achi-hth-nau-vis 3 0.30096 7359.39 1 6 CACCTG TGACAGCTGTCA + +4 tiffin__TIFDMEM0000047 4 0.30096 7359.39 1 6 CACCTG TTAATAACTTAA + +4 transfac_pro__M01177-SREBP 4 0.30096 7359.39 1 6 CACCTG AGGCCACCCGAC + +4 transfac_pro__M01288 0 0.30096 7359.39 1 6 CACCTG CTGCTGCTGTGC + +4 transfac_pro__M01305-sd 0 0.30096 7359.39 1 6 CACCTG CACATTCCTCCG + +4 transfac_pro__M03890-cnc-Mitf-Usf 2 0.30096 7359.39 1 6 CACCTG GTCACGTGACTG + +4 transfac_pro__M07671-Atf6-Clk-CrebA-Max-Mnt 3 0.30096 7359.39 1 6 CACCTG TGCCACGTGGCA + +4 cisbp__M0338 3 0.30096 7359.39 1 6 CACCTG ACTTACGTCATC - +4 hocomoco__ZN219_HUMAN.H11MO.0.D 6 0.30096 7359.39 1 6 CACCTG TCCGCCCCCCTC - +4 neph__UW.Motif.0399 0 0.30096 7359.39 1 6 CACCTG TTCCTGACAGCA - +4 taipale__EHF_full_NACCCGGAAGTA-aop-Eip74EF-Ets21C 0 0.30096 7359.39 1 6 CACCTG TACTTCCGGGTT - +4 taipale_cyt_meth__ELF1_NATGCGGAAGTN_FL-Eip74EF 0 0.30096 7359.39 1 6 CACCTG TACTTCCGCATT - +4 taipale_cyt_meth__ELF1_NATGMGGAAGTN_eDBD_meth-Eip74EF 0 0.30096 7359.39 1 6 CACCTG CACTTCCGCATC - +4 taipale_cyt_meth__MYOD1_NAACANNTGTYN_FL-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.30096 7359.39 1 6 CACCTG CGACAGCTGTTC - +4 taipale_cyt_meth__MYOD1_NAACANNTGTYN_eDBD-ac-amos-ase-crp-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.30096 7359.39 1 6 CACCTG TAACAGCTGTTG - +4 taipale_cyt_meth__MYOG_CGTCANNTGTYN_FL_meth-amos-HLH54F-nau 3 0.30096 7359.39 1 6 CACCTG CAACAGCTGTCG - +4 taipale_cyt_meth__MYOG_CGTCANNTGTYN_eDBD_meth-amos-Fer3-HLH54F-nau 3 0.30096 7359.39 1 6 CACCTG CAACAGCTGTCG - +4 taipale_tf_pairs__FOXO1_ELK3_RCCGGAWGTKKW_CAP-foxo 2 0.30096 7359.39 1 6 CACCTG AAAACTTCCGGT - +4 tiffin__TIFDMEM0000099 5 0.30096 7359.39 1 6 CACCTG ATGGCCAACTGG - +4 transfac_pro__M03876 5 0.30096 7359.39 1 6 CACCTG CCTGCCCCCGGC - +4 transfac_pro__M05782-CG10321-CG8089 6 0.30096 7359.39 1 6 CACCTG GCCCATTGCATG - +4 transfac_pro__M05820-opa 6 0.30096 7359.39 1 6 CACCTG GATGACCACCCA - +4 transfac_pro__M06003 6 0.30096 7359.39 1 6 CACCTG GCTGCCCACCAG - +4 transfac_pro__M06454 1 0.30096 7359.39 1 6 CACCTG TCCCCTAATCCC - +4 transfac_pro__M07633-bigmax-Mitf-Mondo-SREBP-tgo-Usf 3 0.30096 7359.39 1 6 CACCTG GATCACGTGATC - +4 taipale__ZNF524_full_ACCCTTGAACCC_repr -1 0.30096 7359.39 1 5 CACCTG ACCCTCGAACCC + +4 taipale_tf_pairs__HOXB2_EOMES_RGGTGTTAATKN_CAP_repr-pb 7 0.30096 7359.39 1 5 CACCTG CCATTAACACCT - +4 transfac_pro__M00961-EcR 7 0.30096 7359.39 1 5 CACCTG CCGGGTGAACCC - +4 transfac_pro__M05467-salm-salr 7 0.30096 7359.39 1 5 CACCTG TCCCCAGGACCC - +4 transfac_pro__M05763 7 0.30096 7359.39 1 5 CACCTG TCTACTTGACCA - +4 transfac_pro__M05968 7 0.30096 7359.39 1 5 CACCTG GCCCCCGGACCA - +4 transfac_pro__M06368 7 0.30096 7359.39 1 5 CACCTG TCTACTTGACCA - +4 transfac_pro__M06655 7 0.30096 7359.39 1 5 CACCTG GCATATTTACCA - +4 transfac_pro__M06707 7 0.30096 7359.39 1 5 CACCTG TCGTTTGGACCA - +4 transfac_pro__M06842-salm-salr 7 0.30096 7359.39 1 5 CACCTG TTCCCCGGACCC - +4 transfac_pro__M06856 7 0.30096 7359.39 1 5 CACCTG GCTGACGGACCC - +4 transfac_pro__M06374 -2 0.30096 7359.39 1 4 CACCTG CCTGCTGAAGGA + +4 transfac_pro__M07618-bs -2 0.30096 7359.39 1 4 CACCTG CCTTATATGGGC + +4 tfdimers__MD00094-EcR-usp 15 0.301271 7366.98 1 6 CACCTG AATTAATTAATCATTAACCCTTAAAT + +4 tfdimers__MD00137 16 0.301271 7366.98 1 6 CACCTG GGGGGAGTGGGGAATTCCCCAGGTCA - +4 cisbp__M5497-grh 0 0.303485 7421.13 1 6 CACCTG AACCGGTTTAACCGGTT + +4 taipale__AR_DBD_RRGWACANNNTGTWCYY 3 0.303485 7421.13 1 6 CACCTG AGGTACACGGTGTACCC + +4 taipale_cyt_meth__GMEB2_NYACGTANNNTACGTRN_eDBD 1 0.303485 7421.13 1 6 CACCTG CTACGTACGGTACGTAG + +4 taipale_cyt_meth__NR6A1_NTCAAGKTCAAGKTCAN_eDBD_repr-EcR-ERR-Hr4 2 0.303485 7421.13 1 6 CACCTG TTGACCTTGAACTTGAC - +4 transfac_pro__M02760 9 0.303485 7421.13 1 6 CACCTG ACGTATGTGCACATCTG - +4 transfac_pro__M03835-cnc-ewg-kay-maf-S 2 0.303485 7421.13 1 6 CACCTG TTCTGCTGAGTCATGGT - +4 transfac_pro__M07909-bowl-sob 3 0.303485 7421.13 1 6 CACCTG TGCTACCGGTGTTACGC - +4 cisbp__M0080 2 0.304273 7440.38 1 6 CACCTG GCAACATA + +4 hocomoco__MYCN_MOUSE.H11MO.0.A-Max-Myc 1 0.304273 7440.38 1 6 CACCTG CCACGTGG + +4 jaspar__MA0312.1 0 0.304273 7440.38 1 6 CACCTG TATCTCCG + +4 jaspar__MA0389.1 1 0.304273 7440.38 1 6 CACCTG AGATCTAC + +4 neph__UW.Motif.0021 1 0.304273 7440.38 1 6 CACCTG CAGCCTCC + +4 transfac_pro__M01964 1 0.304273 7440.38 1 6 CACCTG AGATCTAC + +4 cisbp__M0157 1 0.304273 7440.38 1 6 CACCTG CCACGTGC - +4 cisbp__M0606 2 0.304273 7440.38 1 6 CACCTG CGTACGTA - +4 cisbp__M0614 2 0.304273 7440.38 1 6 CACCTG ATTACGCG - +4 cisbp__M1330 0 0.304273 7440.38 1 6 CACCTG TAACCGCC - +4 hdpi__SRP9-Srp9 2 0.304273 7440.38 1 6 CACCTG GCCACCTT - +4 homer__ANCAGCTG_SCL-HLH3B-ac-ase-l(1)sc-sc 0 0.304273 7440.38 1 6 CACCTG CAGCTGCT - +4 jaspar__MA0962.1 1 0.304273 7440.38 1 6 CACCTG CCACGTGC - +4 predrem__nrMotif365 1 0.304273 7440.38 1 6 CACCTG CCCCCTCA - +4 scertf__macisaac.STB2 2 0.304273 7440.38 1 6 CACCTG TTTACCCG - +4 transfac_pro__M00921 2 0.304273 7440.38 1 6 CACCTG AGAACAGA - +4 yetfasco__YLR131C_1332-CG9609 0 0.304273 7440.38 1 6 CACCTG GACCAGCA - +4 yetfasco__YMR053C_710 2 0.304273 7440.38 1 6 CACCTG TTTACCCG - +4 cisbp__M0048 3 0.304273 7440.38 1 5 CACCTG GTCGACCC + +4 predrem__nrMotif2066 -1 0.304273 7440.38 1 5 CACCTG CCCTTACC + +4 transfac_pro__M01620 3 0.304273 7440.38 1 5 CACCTG TAACACCG + +4 yetfasco__YBL103C_1446 3 0.304273 7440.38 1 5 CACCTG CGTGACCG + +4 jaspar__MA0392.1 3 0.304273 7440.38 1 5 CACCTG TAACACCG - +4 predrem__nrMotif342 -1 0.304273 7440.38 1 5 CACCTG AGCTTTGC - +4 jaspar__MA1084.1 4 0.304273 7440.38 1 4 CACCTG CGTTGACC + +4 tfdimers__MD00042-nub-pdm2 14 0.304607 7448.57 1 6 CACCTG TTTAGTTAATCATTTACATTTTATT + +4 tfdimers__MD00124-Hnf4-svp 14 0.304607 7448.57 1 6 CACCTG TTTAGTTAATGTTTAACTTTTTTTT - +4 cisbp__M0335 3 0.305284 7465.1 1 6 CACCTG GATTACGTAA + +4 cisbp__M1127 4 0.305284 7465.1 1 6 CACCTG TAGATCCCCT + +4 cisbp__M1332 4 0.305284 7465.1 1 6 CACCTG ACGAAATCTA + +4 cisbp__M5943-bigmax-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.305284 7465.1 1 6 CACCTG GTCACGTGAT + +4 cisbp__M5994-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-mio-Mitf-Sirt6-SREBP-tai-tgo-Usf 2 0.305284 7465.1 1 6 CACCTG GTCACGTGCC + +4 homer__AAGCACTTAA_Nkx3.1-bap-vnd 3 0.305284 7465.1 1 6 CACCTG AAGCACTTAA + +4 homer__BCACGTGVDN_PIF5ox 1 0.305284 7465.1 1 6 CACCTG TCACGTGGTT + +4 jaspar__MA0421.1 2 0.305284 7465.1 1 6 CACCTG TTTACCCGGC + +4 predrem__nrMotif1267 1 0.305284 7465.1 1 6 CACCTG AGATCTTTCT + +4 predrem__nrMotif2164 2 0.305284 7465.1 1 6 CACCTG GGGACCTCCC + +4 scertf__pachkov.YDR026C 2 0.305284 7465.1 1 6 CACCTG TTTACCCGGC + +4 taipale__ARNTL_DBD_GTCACGTGAC-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.305284 7465.1 1 6 CACCTG GTCACGTGAC + +4 taipale__MLX_full_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.305284 7465.1 1 6 CACCTG ATCACGTGAT + +4 taipale_cyt_meth__HES5_GGCACGTGYY_eDBD-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn 2 0.305284 7465.1 1 6 CACCTG GGCACGTGTC + +4 taipale_cyt_meth__TFAP4_AWCAGCTGWT_eDBD_meth-crp 2 0.305284 7465.1 1 6 CACCTG ATCAGCTGAT + +4 transfac_pro__M00942-Atf6-Clk-CrebA-Met 2 0.305284 7465.1 1 6 CACCTG TCCACGTGTC + +4 transfac_pro__M07528 1 0.305284 7465.1 1 6 CACCTG CCACCGACAT + +4 transfac_pro__M07971-CG4956 2 0.305284 7465.1 1 6 CACCTG AGTACATAAG + +4 cisbp__M0707-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 2 0.305284 7465.1 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1217-achi-hth-vis 3 0.305284 7465.1 1 6 CACCTG TTTGACAGCA - +4 cisbp__M1274 1 0.305284 7465.1 1 6 CACCTG TCCCCGGGTT - +4 cisbp__M1888 3 0.305284 7465.1 1 6 CACCTG TTCCCCCTCC - +4 cisbp__M2226 2 0.305284 7465.1 1 6 CACCTG TTTACCCGGC - +4 cisbp__M2944-crp 2 0.305284 7465.1 1 6 CACCTG CTCAGCTGGT - +4 cisbp__M2947-crp 2 0.305284 7465.1 1 6 CACCTG CACAGCTGGT - +4 cisbp__M3401-Hmx 4 0.305284 7465.1 1 6 CACCTG CACGCACTTG - +4 cisbp__M5084-lola 0 0.305284 7465.1 1 6 CACCTG AAACTCCACC - +4 homer__CAGATAAGGN_Gata1-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.305284 7465.1 1 6 CACCTG TCCTTATCTG - +4 homer__NBWGATAAGR_Gata4-CoRest-CycT-GATAd-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 3 0.305284 7465.1 1 6 CACCTG TCTTATCTGC - +4 predrem__nrMotif1429 1 0.305284 7465.1 1 6 CACCTG TTTCCTACAT - +4 predrem__nrMotif18 1 0.305284 7465.1 1 6 CACCTG CTTCCTCCCT - +4 predrem__nrMotif2683 4 0.305284 7465.1 1 6 CACCTG TTAGGACATA - +4 taipale_cyt_meth__HES7_GGCACGTGYN_eDBD_meth-E(spl)mbeta-HLH-Hey 2 0.305284 7465.1 1 6 CACCTG CGCACGTGCC - +4 taipale_cyt_meth__HEY1_NGCACGTGYN_eDBD-dpn-Hey-Sidpn 2 0.305284 7465.1 1 6 CACCTG GACACGTGCC - +4 taipale_cyt_meth__HEY2_NGCACGTGYN_FL_meth-dpn-h-Hey-Sidpn 2 0.305284 7465.1 1 6 CACCTG GACACGTGCC - +4 transfac_pro__M05353-btd-cbt-Sp1-Spps 0 0.305284 7465.1 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M05493-btd-cbt-Sp1-Spps 0 0.305284 7465.1 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M05535-hb-her 4 0.305284 7465.1 1 6 CACCTG TATTTACCCC - +4 transfac_pro__M06078 4 0.305284 7465.1 1 6 CACCTG AAATCTCCCA - +4 transfac_pro__M07277-btd-CG42741-dar1-luna-Spps 4 0.305284 7465.1 1 6 CACCTG GCCCCGCCCC - +4 transfac_pro__M07660-crp-twi 2 0.305284 7465.1 1 6 CACCTG AACACATGTT - +4 transfac_public__M00021-Kr 2 0.305284 7465.1 1 6 CACCTG TTAACCCGTT - +4 yetfasco__YDR421W_2115 2 0.305284 7465.1 1 6 CACCTG TTTGCCGAGG - +4 yetfasco__YJL110C_2133-CoRest-GATAd-GATAe-HLH3B-grn-nej-pnr-srp-svp 3 0.305284 7465.1 1 6 CACCTG CCTTATCAGT - +4 swissregulon__sacCer__PBF1 -1 0.305284 7465.1 1 5 CACCTG AGCTCATCGC + +4 cisbp__M0496 5 0.305284 7465.1 1 5 CACCTG GCGCCCACCG - +4 scertf__harbison.STB5 5 0.305284 7465.1 1 5 CACCTG TATAACACCG - +4 transfac_pro__M06576 5 0.305284 7465.1 1 5 CACCTG GCGGCCACCC - +4 transfac_pro__M09347 5 0.305284 7465.1 1 5 CACCTG AAAAATATCT - +4 cisbp__M1531-CG9727-Rfx 6 0.305284 7465.1 1 4 CACCTG CTTAGCAACG + +4 cisbp__M1535-CG9727-Rfx 6 0.305284 7465.1 1 4 CACCTG CTTAGCAACC + +4 taipale_cyt_meth__MEF2B_CCWWATWWRG_eDBD_meth-bs-Mef2 -2 0.305284 7465.1 1 4 CACCTG CCAAATTTGG + +4 scertf__morozov.UGA3 -2 0.305284 7465.1 1 4 CACCTG CCGCTTCCGG - +4 cisbp__M2304-EcR-ERR-ey-ftz-f1-Hr4-toy-usp 3 0.305657 7474.23 1 6 CACCTG GCTGACCTTGAACTT + +4 cisbp__M5596-pan 1 0.305657 7474.23 1 6 CACCTG AACCCTTTGATCTTT + +4 neph__UW.Motif.0245 4 0.305657 7474.23 1 6 CACCTG AAAGAAATTGATTCA + +4 neph__UW.Motif.0512 3 0.305657 7474.23 1 6 CACCTG TGTGGCCTTAGGAAA + +4 taipale_cyt_meth__KLF17_NMCCACGCWCCCMYY_eDBD_meth_repr-CG3065-hkb 7 0.305657 7474.23 1 6 CACCTG CACCACGCACCCCTT + +4 taipale_cyt_meth__ZIC3_NRCCCCCYGCTGTGN_FL_meth-opa 3 0.305657 7474.23 1 6 CACCTG GACCCCCTGCTGTGC + +4 cisbp__M2120-kay-Mes4-Nf-YB-Nf-YC-Ubx 3 0.305657 7474.23 1 6 CACCTG TCGCCTCTGATTGGT - +4 neph__UW.Motif.0426 8 0.305657 7474.23 1 6 CACCTG GAAACCAGATCCCTG - +4 taipale_tf_pairs__ETV2_FOXI1_NRTMAACMGGAARYN_CAP-pnt 3 0.305657 7474.23 1 6 CACCTG CACTTCCTGTTTACG - +4 neph__UW.Motif.0104-Dif 10 0.305657 7474.23 1 5 CACCTG AAAAAATTATTTCCT + +4 taipale_cyt_meth__ZNF787_TGCCTCMGTTTMCCY_FL-zfh1 10 0.305657 7474.23 1 5 CACCTG TGCCTCAGTTTACCC + +4 cisbp__M4491-CG12018-Dif-dl-Rel-shn 10 0.305657 7474.23 1 5 CACCTG CCTTGGAAATCCCCT - +4 neph__UW.Motif.0642 11 0.305657 7474.23 1 4 CACCTG GGCTGATTTTTTTCC - +4 transfac_pro__M01639 0 0.306475 7494.23 1 6 CACCTG CTCCGGA + +4 cisbp__M2097 0 0.306475 7494.23 1 6 CACCTG CTCCGGA - +4 hdpi__COBRA1-NELF-B 1 0.306475 7494.23 1 6 CACCTG TTACCAT - +4 hdpi__NUP107-Nup107 1 0.306475 7494.23 1 6 CACCTG GCATCTT - +4 hdpi__THRAP6-MED30 1 0.306475 7494.23 1 6 CACCTG CCACCTC - +4 transfac_pro__M02080-tup 0 0.306475 7494.23 1 6 CACCTG CACTTAG - +4 cisbp__M0374 2 0.306475 7494.23 1 5 CACCTG CACACTC - +4 cisbp__M0626 2 0.306475 7494.23 1 5 CACCTG GAAACAT - +4 hdpi__JARID1A-lid -1 0.306475 7494.23 1 5 CACCTG ACCCCTG - +4 predrem__nrMotif329 -2 0.306475 7494.23 1 4 CACCTG CCTTTGG - +4 taipale_tf_pairs__GCM2_SOX15_RTRCGGGNNNRNACAAWN_CAP_repr-gcm-gcm2 9 0.307099 7509.49 1 6 CACCTG CATTGTTTTCGCCCGCAT - +4 transfac_pro__M00810-bs 5 0.307099 7509.49 1 6 CACCTG GCCATCTCCTTATATGGG - +4 transfac_pro__M02219-fkh 4 0.307099 7509.49 1 6 CACCTG TCAGGACATAATGTTCCC - +4 tfdimers__MD00567 11 0.307346 7515.53 1 6 CACCTG ATTTTCAATTATTCCTTATATTTT - +4 cisbp__M1753 1 0.307603 7521.83 1 6 CACCTG CTGCCGAGA + +4 elemento__CGCCTGCGC-ewg 0 0.307603 7521.83 1 6 CACCTG CGCCTGCGC + +4 fantom__motif59_NCWCCARNR 1 0.307603 7521.83 1 6 CACCTG TCACCAAGG + +4 flyfactorsurvey__tgo_cyc_SANGER_5_FBgn0015014-Clk-Mitf-SREBP-Usf-bigmax-cnc-cyc-tgo 2 0.307603 7521.83 1 6 CACCTG GTCACGTGA + +4 predrem__nrMotif2511 1 0.307603 7521.83 1 6 CACCTG GGCCCTGCC + +4 scertf__pachkov.MATALPHA2 3 0.307603 7521.83 1 6 CACCTG AATTACATG + +4 transfac_pro__M01864 0 0.307603 7521.83 1 6 CACCTG TACGTCATG + +4 cisbp__M0389 2 0.307603 7521.83 1 6 CACCTG CCCACTTCC - +4 cisbp__M3517-CycT-GATAe-grn-pnr 3 0.307603 7521.83 1 6 CACCTG CCCTATCTG - +4 elemento__CGCAGGCGC-ewg 1 0.307603 7521.83 1 6 CACCTG GCGCCTGCG - +4 flyfactorsurvey__tgo_tai_SANGER_5_FBgn0015014-Mitf-cyc-tai-tgo 2 0.307603 7521.83 1 6 CACCTG GTCACGTGC - +4 hocomoco__NR4A1_MOUSE.H11MO.0.B-Hr38 1 0.307603 7521.83 1 6 CACCTG TGACCTTTT - +4 predrem__nrMotif1692 3 0.307603 7521.83 1 6 CACCTG AAGAACTTT - +4 stark__GRGGTCAYS-usp 3 0.307603 7521.83 1 6 CACCTG CATGACCCC - +4 transfac_public__M00278-CycT-GATAe-grn-pnr 3 0.307603 7521.83 1 6 CACCTG CCCTATCTG - +4 cisbp__M1317 4 0.307603 7521.83 1 5 CACCTG AAAATATCT - +4 cisbp__M1704 4 0.307603 7521.83 1 5 CACCTG CGTTGACCA - +4 predrem__nrMotif10 4 0.307603 7521.83 1 5 CACCTG AAGGCTCCT - +4 taipale_tf_pairs__TEAD4_FIGLA_RATTCCNNNNNNNNNNCASSTGN_CAP_repr-sd 16 0.30942 7566.24 1 6 CACCTG CATTCCACGCAATGCCCACCTGG + +4 tfdimers__MD00334-Stat92E-Usf 12 0.30942 7566.24 1 6 CACCTG CACCTGGGAAATCACCTGGTTAT - +4 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNCACGTGN_CAP-crp-Max 1 0.309536 7569.08 1 6 CACCTG TCAGCTGACCGGCACGTGC + +4 hocomoco__FLI1_MOUSE.H11MO.1.A-Eip74EF-Ets96B-Ets97D-RpII215-aop-klu-pnt 7 0.309536 7569.08 1 6 CACCTG CCCCCCCTTCCTGCCTCCC - +4 transfac_pro__M06342 0 0.309536 7569.08 1 6 CACCTG CCCCTGCCATACGACTCCC - +4 transfac_pro__M03576-gem 1 0.310718 7597.99 1 5 CACCTG CCAGCG + +4 transfac_pro__M04985 -2 0.310718 7597.99 1 4 CACCTG ACTATT + +4 transfac_pro__M05079 -2 0.310718 7597.99 1 4 CACCTG ACTACA + +4 transfac_pro__M05123 -2 0.310718 7597.99 1 4 CACCTG CCGGCG + +4 hdpi__BRUNOL5-bru3 3 0.310718 7597.99 1 3 CACCTG ATACAC - +4 tfdimers__MD00438-E2f1 12 0.310757 7598.93 1 6 CACCTG AAAAGGAAGTGAAACCTGTATA + +4 transfac_pro__M00937 14 0.310757 7598.93 1 6 CACCTG TTGATGACTTATACTACGTCTC + +4 tfdimers__MD00095-Eip74EF 12 0.310757 7598.93 1 6 CACCTG AAATACAGCTGTTTCCTGTTCA - +4 tfdimers__MD00375-Ptx1 6 0.310757 7598.93 1 6 CACCTG TTAACCTTCCTAATCCTCTTTT - +4 cisbp__M1851-btd-EcR-eg-fkh-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 1 0.310885 7602.07 1 6 CACCTG TGACCTTTGAACCT + +4 cisbp__M4637-ac-ase-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 4 0.310885 7602.07 1 6 CACCTG GGGTCACGTGGCCG + +4 hocomoco__SIX2_MOUSE.H11MO.0.A-Six4-so 3 0.310885 7602.07 1 6 CACCTG TGAAACCTGATACC + +4 cisbp__M4103-croc 8 0.310885 7602.07 1 6 CACCTG GCATTATTTACATG - +4 cisbp__M6205 2 0.310885 7602.07 1 6 CACCTG ATTTCCTGTTTGCC - +4 cisbp__M6435-Blimp-1 1 0.310885 7602.07 1 6 CACCTG TCACTTTCACTTTC - +4 cisbp__M6510-CG7786-gt-Pdp1 4 0.310885 7602.07 1 6 CACCTG CATTTACATAAACA - +4 neph__UW.Motif.0161 8 0.310885 7602.07 1 6 CACCTG TGGAAAAATTTCTG - +4 neph__UW.Motif.0247 3 0.310885 7602.07 1 6 CACCTG TTCTTCATACAGAG - +4 neph__UW.Motif.0408 4 0.310885 7602.07 1 6 CACCTG CTCTGTTCTTTCTG - +4 taipale__SPIB_DBD_AAAAAGMGGAAGTN-aop-Eip74EF 0 0.310885 7602.07 1 6 CACCTG TACTTCCGCTTTTT - +4 taipale_tf_pairs__ELK1_HOXA1_RCCGGAAGTAATTA_HT-lab 4 0.310885 7602.07 1 6 CACCTG TAATTACTTCCGGT - +4 cisbp__M4444-CG12018-Dif-dl-Rel-shn 9 0.310885 7602.07 1 5 CACCTG CTGGGAAATCCCCT - +4 dbcorrdb__ATF3__ENCSR000BPS_1__m2 6 0.310899 7602.42 1 6 CACCTG GGTTAGAACCCGGGACTTCT + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m3 5 0.310899 7602.42 1 6 CACCTG ATCACAACCCCTCCACAAGA + +4 dbcorrdb__MAZ__ENCSR000EFX_1__m1-Brf-CTCF-HDAC1-Max-Myc-Nelf-E-RpII215-SMC3-SREBP-Stat92E-TfAP-2-usp-vtd 6 0.310899 7602.42 1 6 CACCTG CGGCGCCCCCTGGTGGCCGC + +4 dbcorrdb__STAT1__ENCSR000FAV_1__m3-Stat92E 4 0.310899 7602.42 1 6 CACCTG GAAGCTCCTCCCCCATTTCC + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m5-Taf7 7 0.310899 7602.42 1 6 CACCTG ACGAATCAGCCTTTTTTGAA + +4 homer__CGGCTGCNGNNNNCAGATAA_GATA_SCL-CoRest-CycT-GATAe-HDAC1-HLH3B-RpII215-Snr1-brm-ebi-grn-nej-pnr-svp 0 0.310899 7602.42 1 6 CACCTG CGGCTGCGGGGCACAGATAA + +4 dbcorrdb__EZH2__ENCSR000ATC_1__m2-E(z) 1 0.310899 7602.42 1 6 CACCTG GTGCCGTTTGGTTGCAGAGG - +4 dbcorrdb__ZNF143__ENCSR000EGP_1__m2-Chd1-CTCF-Hcf-SMC3-usp-vtd 8 0.310899 7602.42 1 6 CACCTG CACAGCGCCGCCTAGTGGCC - +4 hocomoco__ZN528_HUMAN.H11MO.0.C 12 0.310899 7602.42 1 6 CACCTG TCAGAAATGGCTTCCCTGGG - +4 taipale_tf_pairs__TEAD4_CLOCK_GGWATGNNNNNNNCACGTGN_CAP_repr-Clk-sd 1 0.310899 7602.42 1 6 CACCTG ACACGTGTCACCAGCATACC - +4 jaspar__MA0351.1 5 0.311277 7611.65 1 6 CACCTG TTCTGCACCTCATCGCATCCT + +4 taipale_tf_pairs__ETV2_CLOCK_NNCACGTGNNNNNCCGGAWRY_CAP-Clk-pnt 2 0.311277 7611.65 1 6 CACCTG GACACGTGTCACACCGGATGC + +4 transfac_pro__M00966-EcR-usp 4 0.311277 7611.65 1 6 CACCTG GATGAACTTCCTGACCCGTTT + +4 cisbp__M2156 5 0.311277 7611.65 1 6 CACCTG TTCTGCACCTCATCGCATCCT - +4 cisbp__M4262 5 0.311277 7611.65 1 6 CACCTG TTCTGCACCTCATCGCATCCT - +4 transfac_pro__M06187 2 0.311277 7611.65 1 6 CACCTG ATGACCTTTAAGTCGAAAACG - +4 cisbp__M2338-amos-HLH54F-nau 2 0.311653 7620.85 1 6 CACCTG GACAGCTGTTC + +4 cisbp__M4578-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.311653 7620.85 1 6 CACCTG GGTCACGTGGC + +4 hocomoco__P63_HUMAN.H11MO.1.A 5 0.311653 7620.85 1 6 CACCTG GAGCATGCCTG + +4 transfac_pro__M00440-Atf6-Clk-CrebA-gce 2 0.311653 7620.85 1 6 CACCTG GCCACGTGGCA + +4 transfac_pro__M01857-TfAP-2 0 0.311653 7620.85 1 6 CACCTG AGCCCCCGGCC + +4 cisbp__M2284-brm-CoRest-CycT-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.311653 7620.85 1 6 CACCTG TCTTATCTCTC - +4 fantom__motif40_ATGCGGAGGAG 0 0.311653 7620.85 1 6 CACCTG CTCCTCCGCAT - +4 fantom__motif95_AGCGAGCTAGC 2 0.311653 7620.85 1 6 CACCTG GCTAGCTCGCT - +4 hocomoco__E2F3_HUMAN.H11MO.0.A-Dp-E2f1-E2f2 5 0.311653 7620.85 1 6 CACCTG TTTCCCGCCCT - +4 jaspar__MA0545.1-HLH54F-amos-nau 2 0.311653 7620.85 1 6 CACCTG GACAGCTGTTC - +4 predrem__nrMotif1152 4 0.311653 7620.85 1 6 CACCTG CTGGGACCCTG - +4 scertf__harbison.SPT2 5 0.311653 7620.85 1 6 CACCTG TTAAATACAGG - +4 taipale_cyt_meth__ETV2_NRCAGGAAGTN_eDBD_meth_repr-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.311653 7620.85 1 6 CACCTG CACTTCCTGTC - +4 transfac_pro__M09118 1 0.311653 7620.85 1 6 CACCTG TTAACTTTTTG - +4 transfac_pro__M09391 4 0.311653 7620.85 1 6 CACCTG AAGTTACGTGT - +4 transfac_pro__M09512 3 0.311653 7620.85 1 6 CACCTG TGCAACTTGCA - +4 yetfasco__YIR013C_565 4 0.311653 7620.85 1 6 CACCTG TTTAGATCTTT - +4 transfac_pro__M09340 6 0.311653 7620.85 1 5 CACCTG AAAAAATATCT - +4 tfdimers__MD00535-crp-foxo-slp2 6 0.312142 7632.81 1 6 CACCTG ATAAAACAGCTGTGCAAACAAACATAT + +4 neph__UW.Motif.0164 7 0.312267 7635.87 1 6 CACCTG CTTCTGGTTTCTTTCA + +4 neph__UW.Motif.0175 1 0.312267 7635.87 1 6 CACCTG AGCCCTCCCTCCTCTG + +4 taipale_cyt_meth__ZBTB14_NYGCRCGTGCACGYGN_eDBD_meth_repr 9 0.312267 7635.87 1 6 CACCTG ATGCGCGTGCACGTGC + +4 transfac_pro__M07388 0 0.312267 7635.87 1 6 CACCTG GAGCTTTTTTAGCACG + +4 cisbp__M3295-croc-fkh 8 0.312267 7635.87 1 6 CACCTG TGTTTATTTACTTACC - +4 cisbp__M3296-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-HDAC1-nej 8 0.312267 7635.87 1 6 CACCTG CCATTGTTTACTTAAG - +4 hocomoco__TCF7_HUMAN.H11MO.0.A-pan 0 0.312267 7635.87 1 6 CACCTG TTCCTTTGATGTGGTT - +4 neph__UW.Motif.0297 6 0.312267 7635.87 1 6 CACCTG CTCCAGATTCTGCCAG - +4 neph__UW.Motif.0549 4 0.312267 7635.87 1 6 CACCTG TTTCTTTTTTTCTCAG - +4 taipale__Vdr_DBD_RRGTTCANNRRGTTCA_repr-EcR-usp 2 0.312267 7635.87 1 6 CACCTG TGAACCCGATGAACTC - +4 taipale_cyt_meth__BCL6_NTGCTTTCTAGGAATN_eDBD_meth-Stat92E 2 0.312267 7635.87 1 6 CACCTG AATTCCTAGAAAGCAT - +4 transfac_pro__M09360 1 0.312267 7635.87 1 6 CACCTG TTACTTGTAGAACAAG - +4 transfac_public__M00291-croc-fkh 8 0.312267 7635.87 1 6 CACCTG TGTTTATTTACTTACC - +4 hocomoco__MYOG_HUMAN.H11MO.0.B-ac-ase-l(1)sc-nau-sc 3 0.31392 7676.29 1 6 CACCTG CCGCAGCTGTCCC - +4 neph__UW.Motif.0579 3 0.31392 7676.29 1 6 CACCTG GGCCAGATGCTGC - +4 swissregulon__sacCer__FKH2-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd59A-fkh-foxo-slp1-slp2 6 0.31392 7676.29 1 6 CACCTG TTTGTTTACTTTT - +4 taipale_tf_pairs__GCM1_SPDEF_RTGNKGGCGGAWG_CAP_repr-Ets98B-gcm-gcm2 4 0.31392 7676.29 1 6 CACCTG CATCCGCCCGCAT - +4 transfac_pro__M09429 8 0.31392 7676.29 1 5 CACCTG GTGGGGCCCACCA - +4 cisbp__M1916-sd 0 0.314342 7686.61 1 6 CACCTG CACATTCCTCCG + +4 cisbp__M4900-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.314342 7686.61 1 6 CACCTG ATCACGTGACCA + +4 hocomoco__USF1_HUMAN.H11MO.0.A-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Usf-ac-ase-bigmax-cnc-cwo-cyc-l(1)sc-nau-sc-tgo 3 0.314342 7686.61 1 6 CACCTG GGTCACGTGACC + +4 homer__CCGGTCACGTGA_E-box-Max-Mitf-SREBP-Usf-cnc 5 0.314342 7686.61 1 6 CACCTG CCGGTCACGTGA + +4 neph__UW.Motif.0504 6 0.314342 7686.61 1 6 CACCTG AGCAGATTTCTG + +4 taipale__ZBTB7B_full_NCGACCACCGAN 5 0.314342 7686.61 1 6 CACCTG GCGACCACCGAA + +4 taipale_cyt_meth__DMRTA1_WWTTGWTACATT_FL_meth-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.314342 7686.61 1 6 CACCTG AATTGTTACATT + +4 taipale_cyt_meth__TCF21_NACCATATGKYN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.314342 7686.61 1 6 CACCTG CACCATATGGCG + +4 tiffin__TIFDMEM0000008 5 0.314342 7686.61 1 6 CACCTG AAATGAAACTGG + +4 transfac_pro__M06039-Max-Myc 2 0.314342 7686.61 1 6 CACCTG ACCACGTGGTCC + +4 cisbp__M5961 5 0.314342 7686.61 1 6 CACCTG GCGACCACCGAA - +4 cisbp__M6320 2 0.314342 7686.61 1 6 CACCTG TCTTCCTGCGAG - +4 cisbp__M6553 6 0.314342 7686.61 1 6 CACCTG TCCGCCCCCCTC - +4 hocomoco__E2F8_HUMAN.H11MO.0.D-E2f2 1 0.314342 7686.61 1 6 CACCTG TTTCCCGCCAAA - +4 hocomoco__KAISO_HUMAN.H11MO.2.A 2 0.314342 7686.61 1 6 CACCTG TCTTCCTGCGAG - +4 jaspar__MA0155.1-nerfin-1-nerfin-2 3 0.314342 7686.61 1 6 CACCTG CGCCCCCTGACA - +4 neph__UW.Motif.0274 0 0.314342 7686.61 1 6 CACCTG TTCCTTTTTTTG - +4 neph__UW.Motif.0283 0 0.314342 7686.61 1 6 CACCTG TCCCCCCAGGCC - +4 taipale__FOXC2_DBD_WAWRTAAAYAWW-bin-br-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-Nf1-slp1-slp2 6 0.314342 7686.61 1 6 CACCTG TTTGTTTACTTA - +4 taipale_cyt_meth__ATF2_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-gt-Irbp18-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.314342 7686.61 1 6 CACCTG GATGACATCATC - +4 transfac_pro__M01784 5 0.314342 7686.61 1 6 CACCTG TTTTATACGAGA - +4 transfac_pro__M06045 5 0.314342 7686.61 1 6 CACCTG GCTCCAACCTCT - +4 transfac_pro__M06235 6 0.314342 7686.61 1 6 CACCTG GCGTTAGACCCG - +4 transfac_pro__M06411 6 0.314342 7686.61 1 6 CACCTG TCATTTTACCCA - +4 transfac_pro__M06645 5 0.314342 7686.61 1 6 CACCTG AAGGCATCCTGA - +4 transfac_pro__M06693 6 0.314342 7686.61 1 6 CACCTG AAAGATAACCCC - +4 transfac_pro__M06705 6 0.314342 7686.61 1 6 CACCTG TCCCACTGCCTG - +4 transfac_pro__M06728-CG11456-CG1233-CG32767-CG43347 6 0.314342 7686.61 1 6 CACCTG ATAACCCGCCTA - +4 transfac_pro__M06736 6 0.314342 7686.61 1 6 CACCTG GATTAAGCCCTC - +4 transfac_pro__M06752 6 0.314342 7686.61 1 6 CACCTG TCTTCCTACCCA - +4 transfac_pro__M06911-CG2120 6 0.314342 7686.61 1 6 CACCTG AGATTAATCCTT - +4 c2h2_zfs__M5118 -1 0.314342 7686.61 1 5 CACCTG ACCCTCGAACCC - +4 transfac_pro__M05393 7 0.314342 7686.61 1 5 CACCTG CGTTTATTAACT - +4 transfac_pro__M05778 7 0.314342 7686.61 1 5 CACCTG TCTTTCATACTC - +4 transfac_pro__M05848 7 0.314342 7686.61 1 5 CACCTG TCGCTTGTACCG - +4 transfac_pro__M05874 7 0.314342 7686.61 1 5 CACCTG GGTTCACTTCCA - +4 transfac_pro__M06047 7 0.314342 7686.61 1 5 CACCTG GCGTCCCTAGCG - +4 transfac_pro__M06162 7 0.314342 7686.61 1 5 CACCTG TCGTCAGTTCCT - +4 transfac_pro__M06170 7 0.314342 7686.61 1 5 CACCTG TCCTTCGTACCG - +4 transfac_pro__M06284 7 0.314342 7686.61 1 5 CACCTG GCTTTACCACAA - +4 transfac_pro__M06326 7 0.314342 7686.61 1 5 CACCTG TTTTCTTGACCC - +4 transfac_pro__M06817-crol 7 0.314342 7686.61 1 5 CACCTG TATGCTTTACCG - +4 jaspar__MA0331.1-bs -2 0.314342 7686.61 1 4 CACCTG CCCAATTAGGAA + +4 cisbp__M2136-bs -2 0.314342 7686.61 1 4 CACCTG CCCAATTAGGAA - +4 neph__UW.Motif.0059 -3 0.314342 7686.61 1 3 CACCTG CTTGTGGGAAAA + +4 taipale_tf_pairs__TFAP2C_ETV7_SCCNNNGGSNNNGGAAGNNNTTCCNN_CAP_repr-aop-TfAP-2 16 0.316057 7728.55 1 6 CACCTG GCGGAAGTACTTCCGTGCCCCGGGGC - +4 tfdimers__MD00354-Pur-alpha 4 0.316057 7728.55 1 6 CACCTG CCCGGCCCTGTCCCTGGGGAGGGGGG - +4 hocomoco__FOXB1_HUMAN.H11MO.0.D-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 9 0.31741 7761.63 1 6 CACCTG GTCAATATTTACATAAC + +4 hocomoco__TWST1_HUMAN.H11MO.0.A-nej-twi 1 0.31741 7761.63 1 6 CACCTG ACATCTGGTTTTAATTA + +4 taipale__GRHL1_DBD_AACCGGWNNNWCCGGTT_repr-grh 0 0.31741 7761.63 1 6 CACCTG AACCGGTTTAACCGGTT + +4 taipale_tf_pairs__CLOCK_TBX3_GGTGTGNNNNNCACGTG_CAP_repr-bi-Clk 11 0.31741 7761.63 1 6 CACCTG GGTGTGATCGGCACGTG + +4 taipale_tf_pairs__TEAD4_PITX1_RCATTCNNNNNTAATCC_CAP-Ptx1-sd 3 0.31741 7761.63 1 6 CACCTG ACATTCCGTACTAATCC + +4 transfac_pro__M01405-ara-caup-mirr 4 0.31741 7761.63 1 6 CACCTG TAAATACATGTAAAATT + +4 hocomoco__ZFX_HUMAN.H11MO.1.A 4 0.31741 7761.63 1 6 CACCTG CCCCGGCCTCCGCCCCC - +4 taipale_tf_pairs__ERF_PITX1_NSCGGANNNNNGGMTTA_CAP-Ets21C-Ptx1 10 0.31741 7761.63 1 6 CACCTG TAATCCCCACTTCCGGT - +4 transfac_pro__M02927 6 0.31741 7761.63 1 6 CACCTG CCGGACCATCTGGCCTT - +4 cisbp__M0010 1 0.317629 7766.98 1 6 CACCTG GCGCCGGC + +4 cisbp__M0759 2 0.317629 7766.98 1 6 CACCTG TAGATCTG + +4 flyfactorsurvey__bcd_FlyReg_FBgn0000166-Gsc-bcd-oc 2 0.317629 7766.98 1 6 CACCTG TTAATCCG + +4 jaspar__MA1014.1 2 0.317629 7766.98 1 6 CACCTG TAGATCTG + +4 cisbp__M1371 1 0.317629 7766.98 1 6 CACCTG CCATCGCG - +4 jaspar__MA0984.1 0 0.317629 7766.98 1 6 CACCTG CCTCTTTT - +4 yetfasco__YKR034W_1355-GATAd-GATAe-grn-pnr-srp 1 0.317629 7766.98 1 6 CACCTG ATATCGGG - +4 predrem__nrMotif2546 -1 0.317629 7766.98 1 5 CACCTG ACATAACA + +4 bergman__gcm-gcm-gcm2 -1 0.317629 7766.98 1 5 CACCTG ACCCGCAT - +4 cisbp__M0815-gcm-gcm2 -1 0.317629 7766.98 1 5 CACCTG ACCCGCAT - +4 cisbp__M1351 3 0.317629 7766.98 1 5 CACCTG AAATATCT - +4 cisbp__M5477-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.317629 7766.98 1 5 CACCTG CCTTATCT - +4 transfac_pro__M07356-sima 3 0.317629 7766.98 1 5 CACCTG GCGCACGT - +4 transfac_pro__M07345-lmd -2 0.317629 7766.98 1 4 CACCTG CCTGCTGT + +4 transfac_pro__M07420-Sidpn -2 0.317629 7766.98 1 4 CACCTG GCTTGTGC + +4 predrem__nrMotif82 -3 0.317629 7766.98 1 3 CACCTG CTTTGTTA + +4 cisbp__M1473 3 0.318637 7791.62 1 6 CACCTG ATTGATCTTT + +4 cisbp__M1823 4 0.318637 7791.62 1 6 CACCTG TTATTTCCGT + +4 cisbp__M5290-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GTCACGTGAC + +4 cisbp__M5306-bigmax-Clk-cyc-E(spl)m5-HLH-E(spl)mbeta-HLH-h-Mitf-Sirt6-SREBP-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GTCACGTGCC + +4 cisbp__M5926-crp 2 0.318637 7791.62 1 6 CACCTG ATCAGCTGTT + +4 cisbp__M5993-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-Mitf-Mondo-Sirt6-SREBP-tai-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GTCACGTGAC + +4 jaspar__MA0034.1 2 0.318637 7791.62 1 6 CACCTG GACAACCGCC + +4 jaspar__MA0595.1-SREBP 2 0.318637 7791.62 1 6 CACCTG ATCACCCCAC + +4 swissregulon__sacCer__CIN5-CG7786-Pdp1-gt-vri 1 0.318637 7791.62 1 6 CACCTG TTACGTAATC + +4 taipale__BHLHB3_full_NKCACGTGMN_repr-bigmax-Clk-cyc-E(spl)m5-HLH-E(spl)mbeta-HLH-h-Mitf-Sirt6-SREBP-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GGCACGTGAC + +4 taipale__Bhlhb2_DBD_NKCACGTGMN-bigmax-Clk-cnc-cwo-cyc-E(spl)m5-HLH-h-Mitf-Mondo-Sirt6-SREBP-tai-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GTCACGTGAC + +4 taipale_cyt_meth__ATOH1_ANCAGCTGNY_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 2 0.318637 7791.62 1 6 CACCTG AACAGCTGTC + +4 taipale_cyt_meth__HEY2_NGCACGTGYN_eDBD_meth-Hey-Sidpn 2 0.318637 7791.62 1 6 CACCTG GGCACGTGTC + +4 taipale_cyt_meth__TFAP4_AWCAGCTGWT_FL_meth-crp 2 0.318637 7791.62 1 6 CACCTG ATCAGCTGAT + +4 transfac_pro__M00368-Atf6-Clk-CrebA-Met 2 0.318637 7791.62 1 6 CACCTG GCCACGTGGC + +4 transfac_pro__M03212 2 0.318637 7791.62 1 6 CACCTG CGTACATTCT + +4 transfac_pro__M07460-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna 4 0.318637 7791.62 1 6 CACCTG CCCCACCCTG + +4 transfac_pro__M07530 0 0.318637 7791.62 1 6 CACCTG CACCGACCAA + +4 transfac_pro__M07594 0 0.318637 7791.62 1 6 CACCTG TTCCGGAAAA + +4 yetfasco__YDR520C_553 4 0.318637 7791.62 1 6 CACCTG TTATCTCCGG + +4 cisbp__M0797-GATAd-GATAe-grn-pnr-srp 2 0.318637 7791.62 1 6 CACCTG CTTATCGGTA - +4 cisbp__M1356-Myb 0 0.318637 7791.62 1 6 CACCTG TAACGGTCAA - +4 cisbp__M1866 2 0.318637 7791.62 1 6 CACCTG GACAACCGCC - +4 cisbp__M3327-GATAe-grn-pnr 3 0.318637 7791.62 1 6 CACCTG TCTTATCTCT - +4 cisbp__M4628-ac-ase-bigmax-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-tgo-Usf 3 0.318637 7791.62 1 6 CACCTG GGTCACGTGG - +4 cisbp__M5384-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.318637 7791.62 1 6 CACCTG TACTTCCGGT - +4 cisbp__M6374-scro-vnd 2 0.318637 7791.62 1 6 CACCTG AGCACTTGAG - +4 flyfactorsurvey__dm_Max_SANGER_10_FBgn0000472-Max-Met-Myc 2 0.318637 7791.62 1 6 CACCTG ACCACGTGTC - +4 flyfactorsurvey__lola-PW_SOLEXA_FBgn0005630-lola 0 0.318637 7791.62 1 6 CACCTG CGTCTGCAAA - +4 flyfactorsurvey__tap_da_SANGER_5_2_FBgn0000413-da-tap 1 0.318637 7791.62 1 6 CACCTG TGACATCTGG - +4 jaspar__MA0057.1 3 0.318637 7791.62 1 6 CACCTG TTCCCCCTAC - +4 predrem__nrMotif2098 3 0.318637 7791.62 1 6 CACCTG CAGCACCAAA - +4 taipale__ELK3_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.318637 7791.62 1 6 CACCTG TACTTCCGGT - +4 taipale__ERF_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.318637 7791.62 1 6 CACCTG CACTTCCGGT - +4 taipale_cyt_meth__BHLHA15_NMCAGCTGKN_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sage-sc 2 0.318637 7791.62 1 6 CACCTG AACAGCTGTT - +4 taipale_cyt_meth__HEY1_NGCACGTGYN_FL_repr-dpn-Hey-Sidpn 2 0.318637 7791.62 1 6 CACCTG GACACGTGCC - +4 taipale_cyt_meth__MAX_RNCATGTGYN_FL_meth_repr-Max 2 0.318637 7791.62 1 6 CACCTG AGCACATGGT - +4 taipale_cyt_meth__ZNF250_NTAGGCCYAN_eDBD 3 0.318637 7791.62 1 6 CACCTG GTAGGCCTAG - +4 transfac_pro__M07635-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.318637 7791.62 1 6 CACCTG GTCACGTGAC - +4 transfac_public__M00350-GATAe-grn-pnr 3 0.318637 7791.62 1 6 CACCTG TCTTATCTCT - +4 cisbp__M1525-CG9727-Rfx -1 0.318637 7791.62 1 5 CACCTG CCTTAGCAAC + +4 cisbp__M4936-Eip74EF-Ets21C -1 0.318637 7791.62 1 5 CACCTG ACCCGGAAGT + +4 cisbp__M5398-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.318637 7791.62 1 5 CACCTG ACCGGAAGTG + +4 swissregulon__sacCer__STB5 5 0.318637 7791.62 1 5 CACCTG TATAACACCG + +4 transfac_pro__M06377 5 0.318637 7791.62 1 5 CACCTG GCGGCCACCC - +4 cisbp__M1527-CG9727-Rfx 6 0.318637 7791.62 1 4 CACCTG CTTAGCAACG + +4 cisbp__M1660 6 0.318637 7791.62 1 4 CACCTG GGGGCCCACC + +4 homer__ACWTCAAAGG_TCFL2-pan -2 0.318637 7791.62 1 4 CACCTG CCTTTGAAGT - +4 taipale_cyt_meth__ZNF263_NGTGCTCCCN_eDBD_meth 6 0.318637 7791.62 1 4 CACCTG GGGGAGCACG - +4 tfdimers__MD00027-foxo-slp2 11 0.319409 7810.51 1 6 CACCTG TTTTATTTGTTTACTTTTTTATTTT + +4 tfdimers__MD00368-EcR-usp 8 0.319409 7810.51 1 6 CACCTG CCCCCCCTCTCCTCCACCCCCCCCC + +4 transfac_pro__M02768 8 0.319447 7811.45 1 6 CACCTG CGTATCGAAACCAAA + +4 transfac_pro__M09449 9 0.319447 7811.45 1 6 CACCTG TTTTTTTTTTACCGT + +4 neph__UW.Motif.0449 5 0.319447 7811.45 1 6 CACCTG GCCAGATTCTGACTC - +4 neph__UW.Motif.0507 8 0.319447 7811.45 1 6 CACCTG GAGGCCAGGAGCTGG - +4 neph__UW.Motif.0663 7 0.319447 7811.45 1 6 CACCTG TGTGAATTATTTTCT - +4 swissregulon__hs__ZNF423.p2 3 0.319447 7811.45 1 6 CACCTG GCCCCCCTGGGGGCC - +4 taipale__LEF1_DBD_AAAGATCAAAGGRWW_repr-pan 1 0.319447 7811.45 1 6 CACCTG AACCCTTTGATCTTT - +4 transfac_pro__M01789 8 0.319447 7811.45 1 6 CACCTG TACATCCGTACATTT - +4 transfac_pro__M02004-GATAe-grn-pnr-Sirt6-Snr1-srp 5 0.319447 7811.45 1 6 CACCTG GTCCTTATCTGCTAC - +4 transfac_pro__M09002-CG5846-CG9727-Max-Rfx-SREBP 2 0.319447 7811.45 1 6 CACCTG GTTACCATGGCAACC - +4 predrem__nrMotif2093 0 0.319789 7819.8 1 6 CACCTG ATCCTGA + +4 predrem__nrMotif807 1 0.319789 7819.8 1 6 CACCTG CATCCTG + +4 hdpi__HIST2H2AB 1 0.319789 7819.8 1 6 CACCTG ACATCTG - +4 predrem__nrMotif2440 1 0.319789 7819.8 1 6 CACCTG TAGCCTG - +4 predrem__nrMotif1496 2 0.319789 7819.8 1 5 CACCTG GAACCCT + +4 transfac_pro__M00655-Ets96B 2 0.319789 7819.8 1 5 CACCTG ACTTCCT + +4 transfac_pro__M04918 -1 0.319789 7819.8 1 5 CACCTG ACCGCCC + +4 predrem__nrMotif1356 2 0.319789 7819.8 1 5 CACCTG CCAAACT - +4 predrem__nrMotif1780 3 0.319789 7819.8 1 4 CACCTG ATTCCCC + +4 hdpi__MAP4K2-hppy -3 0.319789 7819.8 1 3 CACCTG CTGTCAA - +4 cisbp__M0171 2 0.321032 7850.19 1 6 CACCTG AACACGTGC + +4 cisbp__M0246-Clk-cnc-cwo-cyc-Max-Mitf-SREBP-tgo-Usf 3 0.321032 7850.19 1 6 CACCTG GGTCACGTG + +4 cisbp__M1771 3 0.321032 7850.19 1 6 CACCTG CGGATCCGC + +4 cisbp__M5230-bigmax-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf 2 0.321032 7850.19 1 6 CACCTG GTCACGTGC + +4 cisbp__M5238-cyc-Mitf-tai-tgo 2 0.321032 7850.19 1 6 CACCTG GTCACGTGC + +4 flyfactorsurvey__odd_NBT_2.5_FBgn0002985-bowl-drm-odd-sob 2 0.321032 7850.19 1 6 CACCTG GCTACTGTA + +4 predrem__nrMotif1309 3 0.321032 7850.19 1 6 CACCTG ACAGAACTT + +4 predrem__nrMotif235 3 0.321032 7850.19 1 6 CACCTG TGCTGCCTT + +4 predrem__nrMotif2487 2 0.321032 7850.19 1 6 CACCTG AGCACCATT + +4 predrem__nrMotif547 0 0.321032 7850.19 1 6 CACCTG CGCCTCTCC + +4 predrem__nrMotif757 2 0.321032 7850.19 1 6 CACCTG GAGACCAGA + +4 swissregulon__sacCer__TBF1 2 0.321032 7850.19 1 6 CACCTG TAACCCTAA + +4 cisbp__M5131-ato-CG8319-da-Oli 1 0.321032 7850.19 1 6 CACCTG ACATCTGTC - +4 predrem__nrMotif1329 1 0.321032 7850.19 1 6 CACCTG CATCCTTGA - +4 predrem__nrMotif284 1 0.321032 7850.19 1 6 CACCTG CCACCCTTC - +4 predrem__nrMotif736 3 0.321032 7850.19 1 6 CACCTG TGGGTCCTT - +4 stark__YRAAMGTGM 1 0.321032 7850.19 1 6 CACCTG GCACGTTCA - +4 transfac_pro__M01817-sd 3 0.321032 7850.19 1 6 CACCTG ACATTCCTC - +4 predrem__nrMotif1228 -1 0.321032 7850.19 1 5 CACCTG ACTTGGAGT + +4 predrem__nrMotif1264 -1 0.321032 7850.19 1 5 CACCTG TCCTGGCAT + +4 predrem__nrMotif1391 -1 0.321032 7850.19 1 5 CACCTG ACATTAAAA + +4 predrem__nrMotif1679 -1 0.321032 7850.19 1 5 CACCTG ACTTTTTCT + +4 predrem__nrMotif2287 -1 0.321032 7850.19 1 5 CACCTG TCCTTGAAC + +4 predrem__nrMotif2598 -1 0.321032 7850.19 1 5 CACCTG TCCTCAGTA + +4 scertf__badis.YPR196W 4 0.321032 7850.19 1 5 CACCTG ATTTCTCCG + +4 cisbp__M1433 4 0.321032 7850.19 1 5 CACCTG TGGGTACAT - +4 predrem__nrMotif1142 -1 0.321032 7850.19 1 5 CACCTG ACATTGTGT - +4 transfac_pro__M04818 4 0.321032 7850.19 1 5 CACCTG TCACTTCCT - +4 hdpi__ZC3H7A 5 0.321032 7850.19 1 4 CACCTG GGGCTTTCC - +4 predrem__nrMotif637 -2 0.321032 7850.19 1 4 CACCTG CCTGCATTC - +4 cisbp__M6392-EcR-eg-Hnf4-Hr78-kni-knrl-svp-usp 11 0.321225 7854.93 1 6 CACCTG AGGACAAAGTTCATTTGA - +4 taipale_cyt_meth__IRX1_NACAYGNNNNNNCRTGTN_eDBD_repr-ara-caup-mirr 0 0.321225 7854.93 1 6 CACCTG TACATGTAATAACATGTA - +4 taipale_cyt_meth__TFCP2_AWCCGGWTNNAWCCGGWT_FL-gem 10 0.321225 7854.93 1 6 CACCTG AACCGGTTTAAACCGGTT - +4 transfac_public__M00139-ss 8 0.321225 7854.93 1 6 CACCTG TCTCACGCTAGCCGGGGG - +4 transfac_public__M00279-Rfx 5 0.321225 7854.93 1 6 CACCTG CCCGTTACCTAGCAACTG - +4 tfdimers__MD00091-scro 16 0.322045 7874.96 1 6 CACCTG AGAATAGACATGTCCGGACTTGACTGTTTTT + +4 hocomoco__MNX1_HUMAN.H11MO.0.D-exex 10 0.323836 7918.77 1 6 CACCTG CTATTTTAATAACCCTTTA + +4 transfac_pro__M05119 13 0.323836 7918.77 1 6 CACCTG TGTCCAATGAAGTTCCCTG + +4 hocomoco__NR1D2_MOUSE.H11MO.0.A-Eip75B-Hr3 10 0.323836 7918.77 1 6 CACCTG CCCTCTGACCCACTTCCCC - +4 taipale_tf_pairs__GCM2_TEF_RTRCGGGNNNNTTACGTAA_CAP_repr-CG7786-gcm-gcm2-gt-Pdp1 10 0.323836 7918.77 1 6 CACCTG TTACGTAACCAACCCGCAT - +4 transfac_public__M00142 0 0.324021 7923.28 1 6 CACCTG TATCTA + +4 hdpi__AKR1A1-CG6083-noc -1 0.324021 7923.28 1 5 CACCTG CCCACC - +4 transfac_pro__M00751-lz-run-RunxA-RunxB -1 0.324021 7923.28 1 5 CACCTG ACCACA - +4 transfac_pro__M03818-sr 3 0.324021 7923.28 1 3 CACCTG ACCCAC - +4 cisbp__M2308-CG5846-CG9727-Max-Rfx-SREBP 2 0.324729 7940.59 1 6 CACCTG GTTGCCATGGCAAC + +4 factorbook__MYC-Clk-E2f1-Max-Mnt-Myc-Sap30-gce 3 0.324729 7940.59 1 6 CACCTG GAGCACGTGGCTGC + +4 jaspar__MA0509.1-CG5846-CG9727-Max-Rfx-SREBP 2 0.324729 7940.59 1 6 CACCTG GTTGCCATGGCAAC + +4 neph__UW.Motif.0369 3 0.324729 7940.59 1 6 CACCTG AAGTCCCAGCCCCC + +4 swissregulon__sacCer__LEU3 4 0.324729 7940.59 1 6 CACCTG CCGGTACCGGCGAA + +4 taipale_cyt_meth__SKOR2_NWNNKKTAATTAAN_eDBD-fuss 0 0.324729 7940.59 1 6 CACCTG TAACTGTAATTAAG + +4 transfac_pro__M07655-Fer3-nau 4 0.324729 7940.59 1 6 CACCTG GCGACAGCTGTCGC + +4 transfac_pro__M07945-seq-ttk 5 0.324729 7940.59 1 6 CACCTG AAACCCACCCCTAA + +4 transfac_pro__M09349 7 0.324729 7940.59 1 6 CACCTG AAAAAAATATCTTA + +4 hocomoco__KLF5_HUMAN.H11MO.0.A-CG42741-dar1-luna 8 0.324729 7940.59 1 6 CACCTG CCCAGCCCCACCCT - +4 taipale_tf_pairs__ERF_FOXI1_RTAAACMGGAARYN_CAP-Ets21C 3 0.324729 7940.59 1 6 CACCTG CACTTCCTGTTTAC - +4 taipale_tf_pairs__ETV5_HOXA2_RNCGGAWGTMATTA_CAP-Ets96B-pb 4 0.324729 7940.59 1 6 CACCTG TAATTACTTCCGCT - +4 taipale_tf_pairs__FOXO1_ELK1_RWYAACAGGAAGYN_CAP-foxo 3 0.324729 7940.59 1 6 CACCTG CACTTCCTGTTGAT - +4 taipale_tf_pairs__FOXO1_FLI1_RTMAACAGGAAGTN_CAP-foxo 3 0.324729 7940.59 1 6 CACCTG CACTTCCTGTTTAC - +4 transfac_pro__M00626-Rfx 2 0.324729 7940.59 1 6 CACCTG GTTGCCTAGTAACG - +4 transfac_pro__M01831-bs 2 0.324729 7940.59 1 6 CACCTG ATTTCCTAATTGGG - +4 transfac_public__M00267-croc 8 0.324729 7940.59 1 6 CACCTG GCATTATTTACATG - +4 neph__UW.Motif.0334 9 0.324729 7940.59 1 5 CACCTG AAAAAGCTCCAGCT + +4 cisbp__M4494-CG12018-Dif-dl-Rel-shn 9 0.324729 7940.59 1 5 CACCTG CCTGGAAATCCCCT - +4 flyfactorsurvey__ttk-PF_SOLEXA_FBgn0003870-ttk 5 0.325238 7953.04 1 6 CACCTG AAGGACACCCC + +4 predrem__nrMotif142 3 0.325238 7953.04 1 6 CACCTG CCCTCCCTGTC + +4 predrem__nrMotif1428 5 0.325238 7953.04 1 6 CACCTG AAGGACAGCAG + +4 predrem__nrMotif717-CTCF 4 0.325238 7953.04 1 6 CACCTG GCGCCCCCTGC + +4 swissregulon__hs__ARNT_ARNT2_BHLHB2_MAX_MYC_USF1.p2-Clk-Max-Myc-Usf-gce-tgo 3 0.325238 7953.04 1 6 CACCTG GGCCACGTGGC + +4 taipale_cyt_meth__ETV4_NRCCGGAAGTN_FL-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.325238 7953.04 1 6 CACCTG GACCGGAAGTG + +4 taipale_cyt_meth__FEV_NACCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.325238 7953.04 1 6 CACCTG GACCGGAAGTG + +4 cisbp__M0507-CG9609 1 0.325238 7953.04 1 6 CACCTG TAACCAGCATT - +4 cisbp__M2342 3 0.325238 7953.04 1 6 CACCTG TCACACGTGCG - +4 cisbp__M4543-Clk-cyc-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-HDAC1-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30 0 0.325238 7953.04 1 6 CACCTG CACGTGGTTCC - +4 cisbp__M4600-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 4 0.325238 7953.04 1 6 CACCTG TCCTTATCTGC - +4 cisbp__M5347 5 0.325238 7953.04 1 6 CACCTG GGGATTATCCC - +4 cisbp__M6201-sr 0 0.325238 7953.04 1 6 CACCTG GCCCTGCCGCC - +4 factorbook__USF-Max-Mitf-Myc-SREBP-Usf-cnc-cwo-cyc-tgo 2 0.325238 7953.04 1 6 CACCTG GTCACGTGGCC - +4 flyfactorsurvey__crp_SANGER_10_FBgn0001994-crp 2 0.325238 7953.04 1 6 CACCTG ATCAGCTGGTT - +4 hocomoco__EGR4_HUMAN.H11MO.0.D-sr 0 0.325238 7953.04 1 6 CACCTG TCCCCGCCGCC - +4 jaspar__MA0549.1 3 0.325238 7953.04 1 6 CACCTG TCACACGTGCG - +4 swissregulon__hs__IKZF2.p2 3 0.325238 7953.04 1 6 CACCTG TTTTTCCTTTT - +4 taipale__DPRX_DBD_NRGATAATCYN 5 0.325238 7953.04 1 6 CACCTG GGGATTATCCC - +4 taipale_cyt_meth__FOXG1_NAYRTAAACAN_eDBD_meth_repr-croc-FoxL1-foxo-slp1-slp2 5 0.325238 7953.04 1 6 CACCTG GTGTTTACGTT - +4 transfac_pro__M01303-btd-CTCF-Spps 1 0.325238 7953.04 1 6 CACCTG CCCCCCGCCCC - +4 transfac_pro__M09421 3 0.325238 7953.04 1 6 CACCTG TTGTACTTTTT - +4 fantom__motif138_CTTTWANNYCC 7 0.325238 7953.04 1 4 CACCTG CTTTTAACCCC + +4 predrem__nrMotif969 7 0.325238 7953.04 1 4 CACCTG CTGCCCACACC + +4 dbcorrdb__BDP1__ENCSR000DOK_1__m2-AMPKalpha-Bdp1-Brf-CG17209-CG43143-Hsf-SREBP 13 0.325347 7955.72 1 6 CACCTG CGGCCGGGATTCGAACCCGG + +4 dbcorrdb__EZH2__ENCSR000ARD_1__m2-E(z) 8 0.325347 7955.72 1 6 CACCTG GACCCAAAAACCGGCTCCGG + +4 dbcorrdb__GATA3__ENCSR000EWS_1__m1-GATAe-grn-pnr-srp 9 0.325347 7955.72 1 6 CACCTG CCAGGTTCTTATCTGCTCCG + +4 dbcorrdb__TCF3__ENCSR000BQT_1__m1-Max-Myc 10 0.325347 7955.72 1 6 CACCTG GCGCCGAGAACAGCTGCCGC + +4 transfac_pro__M07941-pita 14 0.325347 7955.72 1 6 CACCTG TTAGCCAAGACACGAACCAT + +4 cisbp__M2223-gt 6 0.325347 7955.72 1 6 CACCTG GTCGCTTACGTAATCAGACC - +4 dbcorrdb__ELK4__ENCSR000EVB_1__m2 3 0.325347 7955.72 1 6 CACCTG CGGCCCCTCATTGGGCGAGC - +4 dbcorrdb__NR3C1__ENCSR000BJR_1__m1 2 0.325347 7955.72 1 6 CACCTG GGGACAGTCTGTTCTGGGCC - +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m2-brm 4 0.325347 7955.72 1 6 CACCTG AGAAAGCCTGGTGATGTGGG - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m5-Snr1 13 0.325347 7955.72 1 6 CACCTG GGCTGACAGGGATGATCTGA - +4 jaspar__MA0418.1-gt 6 0.325347 7955.72 1 6 CACCTG GTCGCTTACGTAATCAGACC - +4 taipale_cyt_meth__NR1D2_NAWNTRGGTCANTRGGTCAN_eDBD-Eip75B-Hr3 10 0.325347 7955.72 1 6 CACCTG ATGACCCACTAACCCACATA - +4 taipale_tf_pairs__ERF_CLOCK_CACGTGNNNNNSRGGAARNN_CAP_repr-Clk-Ets21C 14 0.325347 7955.72 1 6 CACCTG GACTTCCGGTCAGCCACGTG - +4 transfac_pro__M01537 5 0.325852 7968.06 1 6 CACCTG TTCTGCACCTCATCGCATCCT + +4 transfac_pro__M05271 16 0.325852 7968.06 1 5 CACCTG GGGTGTGCCCGGCCGGTCCCT + +4 transfac_pro__M05245 17 0.325852 7968.06 1 4 CACCTG GCGGGGAGGCGGGGCACCACC - +4 transfac_pro__M05253 17 0.325852 7968.06 1 4 CACCTG GGGGGGCGACGGGAACCCACC - +4 hocomoco__OSR2_HUMAN.H11MO.0.C-bowl-drm-odd-sob 4 0.326337 7979.91 1 6 CACCTG GCTGCTGCTTCTGCTG + +4 neph__UW.Motif.0518 5 0.326337 7979.91 1 6 CACCTG AAGAAAACCAAATACC + +4 neph__UW.Motif.0569 9 0.326337 7979.91 1 6 CACCTG AGAGGCTGGCATTTTC + +4 taipale_cyt_meth__ERG_NACCGGATATCCGGTN_FL-Ets21C-Ets97D 0 0.326337 7979.91 1 6 CACCTG GACCGGATATCCGGTC + +4 taipale_cyt_meth__FLI1_NACCGGATATCCGGTN_FL_meth-Ets21C-Ets97D 0 0.326337 7979.91 1 6 CACCTG GACCGGATATCCGGTC + +4 transfac_pro__M00766-EcR-svp-usp 1 0.326337 7979.91 1 6 CACCTG TGACCGGCAGTAACCC + +4 cisbp__M2956-bigmax-Clk-Mitf-SREBP-tgo 5 0.326337 7979.91 1 6 CACCTG GCGGGCACGTGACAAC - +4 hocomoco__TAF1_HUMAN.H11MO.0.A-RpII215-Taf1-Taf7-lid-pho-phol 7 0.326337 7979.91 1 6 CACCTG CCGCCGCCGCCATCTT - +4 neph__UW.Motif.0214 3 0.326337 7979.91 1 6 CACCTG TGATTTCTTGTCTCTG - +4 neph__UW.Motif.0586 6 0.326337 7979.91 1 6 CACCTG CTGTTTTTTCTTTCTG - +4 transfac_public__M00236-bigmax-Clk-Mitf-tgo 5 0.326337 7979.91 1 6 CACCTG GCGGGCACGTGACAAC - +4 yetfasco__YMR042W_1483-bs 1 0.326337 7979.91 1 6 CACCTG CGGCCTAGTGCGGAAA - +4 tfdimers__MD00077-Myc-SREBP 5 0.327319 8003.92 1 6 CACCTG CCCCCCAGCTGTCACCCCAGGCCCCCC + +4 transfac_pro__M01051-bs-croc-fd59A-fkh-FoxK-foxo-FoxP 12 0.327319 8003.92 1 6 CACCTG TTGTTTACATTTTTCCTATTTGGGAAA - +4 cisbp__M4638-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.327753 8014.55 1 6 CACCTG GGTCACGTGACCC + +4 cisbp__M2560-gcm-gcm2 1 0.327753 8014.55 1 6 CACCTG AAACCCGCATATT - +4 neph__UW.Motif.0359 6 0.327753 8014.55 1 6 CACCTG GAAAAAATCCCTT - +4 neph__UW.Motif.0391 6 0.327753 8014.55 1 6 CACCTG GTTTCATTTTTTC - +4 neph__UW.Motif.0443 6 0.327753 8014.55 1 6 CACCTG CTGACATTCCAGG - +4 neph__UW.Motif.0631 5 0.327753 8014.55 1 6 CACCTG CTCTGGAATTGTG - +4 neph__UW.Motif.0290 -1 0.327753 8014.55 1 5 CACCTG GCCAGGGAGCTCA + +4 taipale_cyt_meth__NFAT5_NYGGAAANNTACN_eDBD_meth_repr-NFAT 9 0.327753 8014.55 1 4 CACCTG ACGGAAAAGTACG + +4 tfdimers__MD00431 17 0.327916 8018.52 1 6 CACCTG TCCCTAAGCGCGCCCACTTCCTGTTCCCAC - +4 neph__UW.Motif.0159 4 0.328088 8022.73 1 6 CACCTG CTGCCAGCCCCA + +4 neph__UW.Motif.0481 5 0.328088 8022.73 1 6 CACCTG AGAATTCTCTGA + +4 taipale_cyt_meth__DMRTA1_WWTTGWTACATT_FL-dmrt11E-dmrt93B-dmrt99B-dsx 6 0.328088 8022.73 1 6 CACCTG AATTGTTACATT + +4 taipale_cyt_meth__MEIS3_TGACANNTGTCA_eDBD_meth-achi-hth-nau-vis 3 0.328088 8022.73 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__PTF1A_NYGTCAGCTGNY_eDBD-Fer1-nau 4 0.328088 8022.73 1 6 CACCTG GCGTCAGCTGTT + +4 transfac_pro__M05723 5 0.328088 8022.73 1 6 CACCTG CTGGGAAACTGC + +4 homer__NNTGTGGATTSS_Foxh1 6 0.328088 8022.73 1 6 CACCTG CCAATCCACAGC - +4 homer__NTGGGTGTGGCC_EKLF-CG42741-dar1-luna 5 0.328088 8022.73 1 6 CACCTG GGCCACACCCAG - +4 neph__UW.Motif.0240 5 0.328088 8022.73 1 6 CACCTG GCAGTGACTTGC - +4 predrem__nrMotif893 6 0.328088 8022.73 1 6 CACCTG GGCCCCAACTCC - +4 taipale_cyt_meth__SPDEF_NAMCAGGATGTN_FL_meth_repr-Eip74EF-Ets98B 0 0.328088 8022.73 1 6 CACCTG TACATCCGGTTC - +4 taipale_cyt_meth__ZBTB2_NTTTCCGGTAMN_eDBD_meth_repr 2 0.328088 8022.73 1 6 CACCTG ATTACCGGAAAC - +4 transfac_pro__M06294 6 0.328088 8022.73 1 6 CACCTG TCCTCATACCCG - +4 transfac_pro__M06776-CG2120 2 0.328088 8022.73 1 6 CACCTG TCCGCCTGAATG - +4 transfac_pro__M05976-CG2120 7 0.328088 8022.73 1 5 CACCTG TCCGAATTACGC - +4 transfac_pro__M06600 7 0.328088 8022.73 1 5 CACCTG GCATTATTAACT - +4 transfac_pro__M06642 -1 0.328088 8022.73 1 5 CACCTG TCCTTTCACACG - +4 neph__UW.Motif.0189 -3 0.328088 8022.73 1 3 CACCTG CTGTGGCTGAGT - +4 neph__UW.Motif.0376 -3 0.328088 8022.73 1 3 CACCTG CTGAAAAATGAG - +4 tfdimers__MD00411-pho-phol 8 0.331262 8100.36 1 6 CACCTG TTATTTATTTCCTTCCATTTTTTTTT + +4 tfdimers__MD00421 14 0.331262 8100.36 1 6 CACCTG TTTTTTTTTTGTATTTCCTGTTTTAT + +4 tfdimers__MD00393-Sox100B 11 0.331262 8100.36 1 6 CACCTG TTTATTACAATTTCCTGTATTTAATT - +4 cisbp__M4762-bcd-Gsc-oc 2 0.331323 8101.84 1 6 CACCTG TTAATCCG + +4 jaspar__MA0936.1 1 0.331323 8101.84 1 6 CACCTG ACACGCAA + +4 predrem__nrMotif1405 1 0.331323 8101.84 1 6 CACCTG AGACATAA + +4 cisbp__M0827 2 0.331323 8101.84 1 6 CACCTG ATGACATG - +4 jaspar__MA1023.1 0 0.331323 8101.84 1 6 CACCTG CACCGACA - +4 stark__CAGNNGCA 2 0.331323 8101.84 1 6 CACCTG TGCAACTG - +4 transfac_pro__M09573 3 0.331323 8101.84 1 5 CACCTG GTTGACCT + +4 cisbp__M0390 3 0.331323 8101.84 1 5 CACCTG GTGCACAT - +4 cisbp__M1701 3 0.331323 8101.84 1 5 CACCTG GTTGACCG - +4 predrem__nrMotif1111 3 0.331323 8101.84 1 5 CACCTG CACAACCA - +4 predrem__nrMotif2678 3 0.331323 8101.84 1 5 CACCTG TGTAACCA - +4 taipale__GATA3_full_AGATAANN-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.331323 8101.84 1 5 CACCTG CCTTATCT - +4 predrem__nrMotif1230 -2 0.331323 8101.84 1 4 CACCTG CCTTCTTG + +4 scertf__foat.ACA1 11 0.331717 8111.48 1 6 CACCTG ACTAGTGGATTCACCGA + +4 taipale__MAX_DBD_CACGTGNNNNNCACGTG_repr-Max 11 0.331717 8111.48 1 6 CACCTG CACGTGCTAACCACGTG + +4 cisbp__M5288 3 0.331717 8111.48 1 6 CACCTG AGGTACACGGTGTACCC - +4 cisbp__M6227-aop-Atac3-Eip74EF-Ets96B-Ets97D 7 0.331717 8111.48 1 6 CACCTG TCCTCACTTCCTGTGGC - +4 cisbp__M6420 0 0.331717 8111.48 1 6 CACCTG CCCCTCCTGATGCCCCC - +4 taipale_tf_pairs__ELK1_EOMES_RSCGGAANNAGGYGYNA_CAP_repr 3 0.331717 8111.48 1 6 CACCTG TCACACCTACTTCCGGT - +4 taipale_tf_pairs__ELK1_EVX1_RSCGGWANNNNYMATTA_CAP_repr-eve 10 0.331717 8111.48 1 6 CACCTG TAATTACCATTTCCGGT - +4 transfac_pro__M09504 11 0.331717 8111.48 1 6 CACCTG ACCACGTGAAACACGTG - +4 cisbp__M0159-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 2 0.332362 8127.26 1 6 CACCTG GGCACGTGCC + +4 cisbp__M1445-tll 4 0.332362 8127.26 1 6 CACCTG ATTTGACTTT + +4 cisbp__M1697 4 0.332362 8127.26 1 6 CACCTG GGTCAACGCT + +4 cisbp__M1716 4 0.332362 8127.26 1 6 CACCTG TAATCCCCGA + +4 cisbp__M1717 2 0.332362 8127.26 1 6 CACCTG TTAGCCGATA + +4 cisbp__M1752 1 0.332362 8127.26 1 6 CACCTG ATACCGGTAT + +4 cisbp__M4918-Max-Met-Myc 2 0.332362 8127.26 1 6 CACCTG ACCACGTGTC + +4 cisbp__M5927-crp-HLH54F-nau 2 0.332362 8127.26 1 6 CACCTG AACAGCTGAT + +4 fantom__motif32_TRGNMCTNNT 2 0.332362 8127.26 1 6 CACCTG TGGTCCTACT + +4 hocomoco__TFAP4_HUMAN.H11MO.0.A-crp 1 0.332362 8127.26 1 6 CACCTG CCAGCTGTTT + +4 jaspar__MA1083.1 4 0.332362 8127.26 1 6 CACCTG GGTCAACGCT + +4 jaspar__MA1099.1-Hey-Sidpn-dpn-h 2 0.332362 8127.26 1 6 CACCTG GGCACGCGTC + +4 predrem__nrMotif1122 3 0.332362 8127.26 1 6 CACCTG AGAAACCTCA + +4 predrem__nrMotif1127 2 0.332362 8127.26 1 6 CACCTG AAAATCTGTT + +4 taipale__TFAP4_full_AWCAGCTGWT-crp-HLH54F-nau 2 0.332362 8127.26 1 6 CACCTG AACAGCTGAT + +4 taipale_cyt_meth__BHLHE40_GTCACGTGAC_eDBD-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.332362 8127.26 1 6 CACCTG GTCACGTGAC + +4 transfac_pro__M01807 4 0.332362 8127.26 1 6 CACCTG TTATCACATG + +4 transfac_pro__M01920 4 0.332362 8127.26 1 6 CACCTG TTATCTCCGG + +4 transfac_pro__M07060-acj6 3 0.332362 8127.26 1 6 CACCTG TATTAATTAC + +4 transfac_pro__M07504 3 0.332362 8127.26 1 6 CACCTG AAAGATCTTG + +4 cisbp__M0764 4 0.332362 8127.26 1 6 CACCTG TTTAGATCTA - +4 cisbp__M1195 0 0.332362 8127.26 1 6 CACCTG CCAATGATTG - +4 cisbp__M1476 2 0.332362 8127.26 1 6 CACCTG GTGACCAATA - +4 cisbp__M2387-SREBP 2 0.332362 8127.26 1 6 CACCTG ATCACCCCAC - +4 cisbp__M2572-Kr 2 0.332362 8127.26 1 6 CACCTG TTAACCCGTT - +4 cisbp__M5226-da-tap 1 0.332362 8127.26 1 6 CACCTG TGACATCTGG - +4 cisbp__M5380-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.332362 8127.26 1 6 CACCTG TACTTCCGGT - +4 hocomoco__FEV_HUMAN.H11MO.0.B-Atac3-Eip74EF-Ets65A 3 0.332362 8127.26 1 6 CACCTG CGCTTCCCGC - +4 homer__ACAGGAAGTG_ERG-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-aop-bs-dl-grn-pnr-pnt 3 0.332362 8127.26 1 6 CACCTG CACTTCCTGT - +4 homer__CCAGGAACAG_AR-halfsite 3 0.332362 8127.26 1 6 CACCTG CTGTTCCTGG - +4 jaspar__MA0422.1 4 0.332362 8127.26 1 6 CACCTG TTATCTCCGG - +4 predrem__nrMotif1621 3 0.332362 8127.26 1 6 CACCTG GGGGACCCGG - +4 taipale__ELK1_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.332362 8127.26 1 6 CACCTG TACTTCCGGT - +4 taipale_cyt_meth__BHLHE40_GTCACGTGAC_eDBD_meth_repr-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.332362 8127.26 1 6 CACCTG GTCACGTGAC - +4 taipale_cyt_meth__GATA4_NWGATAASRN_eDBD_meth-CoRest-ebi-GATAd-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Snr1-srp-Stat92E-svp 4 0.332362 8127.26 1 6 CACCTG TTCTTATCTG - +4 taipale_cyt_meth__HEY1_NGCACGTGYN_FL_meth-Hey-Sidpn 2 0.332362 8127.26 1 6 CACCTG GACACGTGCC - +4 transfac_pro__M05552-btd-cbt-Sp1-Spps 0 0.332362 8127.26 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M05555-cbt-luna-Sp1 0 0.332362 8127.26 1 6 CACCTG GACCCGCCCT - +4 transfac_pro__M08880-Ets97D 1 0.332362 8127.26 1 6 CACCTG CTTCCTGCCT - +4 cisbp__M1273 5 0.332362 8127.26 1 5 CACCTG ACCGAAACTA + +4 transfac_pro__M03811-TfAP-2 -1 0.332362 8127.26 1 5 CACCTG GCCCGCAGGC + +4 transfac_pro__M07553 5 0.332362 8127.26 1 5 CACCTG CCGTTGACCA + +4 predrem__nrMotif1699 -1 0.332362 8127.26 1 5 CACCTG TTCTTTCATA - +4 transfac_pro__M01169 -1 0.332362 8127.26 1 5 CACCTG CCCTCCCAAC - +4 transfac_pro__M03196 -1 0.332362 8127.26 1 5 CACCTG ATCTCGGTCG - +4 transfac_pro__M05431-CG9650 5 0.332362 8127.26 1 5 CACCTG TCGTTTCCCT - +4 transfac_pro__M06597 -1 0.332362 8127.26 1 5 CACCTG CCCTTAAACA - +4 predrem__nrMotif1164 6 0.332362 8127.26 1 4 CACCTG GCTGGCCACC + +4 predrem__nrMotif2051 6 0.332362 8127.26 1 4 CACCTG CAGCACCACC + +4 predrem__nrMotif1671 6 0.332362 8127.26 1 4 CACCTG TGTCACCACC - +4 taipale_cyt_meth__ZNF263_NGTGCTCCCN_eDBD_repr 6 0.332362 8127.26 1 4 CACCTG GGGGAGCACG - +4 tfdimers__MD00461-Pur-alpha 4 0.33338 8152.15 1 6 CACCTG CCCGTCCCTGCCCCTGGGGCAGGGCGGGG + +4 stark__YGYGGTY-run 0 0.333407 8152.8 1 6 CACCTG AACCACA - +4 swissregulon__sacCer__MSN2-CG10348-CG13296-ham 0 0.333407 8152.8 1 6 CACCTG CCCCTTA - +4 elemento__CCCTTCC -1 0.333407 8152.8 1 5 CACCTG CCCTTCC + +4 elemento__TCCTTGC -1 0.333407 8152.8 1 5 CACCTG TCCTTGC + +4 predrem__nrMotif2241 -1 0.333407 8152.8 1 5 CACCTG ACATCAA + +4 elemento__TCAAGGA -1 0.333407 8152.8 1 5 CACCTG TCCTTGA - +4 hdpi__NXPH3 2 0.333407 8152.8 1 5 CACCTG CCACGCT - +4 stark__AAAAGCT -1 0.333407 8152.8 1 5 CACCTG AGCTTTT - +4 swissregulon__sacCer__SWI5-CG9609 -1 0.333407 8152.8 1 5 CACCTG ACCAGCA - +4 transfac_pro__M07382-Ets96B 2 0.333407 8152.8 1 5 CACCTG ACTTCCT - +4 predrem__nrMotif1119 -2 0.333407 8152.8 1 4 CACCTG CCTTCTC + +4 transfac_pro__M03794-pan -2 0.333407 8152.8 1 4 CACCTG CCTTTGA - +4 factorbook__EBF1-kn 2 0.333617 8157.93 1 6 CACCTG AGTCCCTGGGGACTT + +4 neph__UW.Motif.0680 3 0.333617 8157.93 1 6 CACCTG CAAGGCCAGGAGGCA + +4 taipale_cyt_meth__GLI2_RGACCACCCACGWWG_eDBD_meth-ci-lmd-opa-sug 8 0.333617 8157.93 1 6 CACCTG AGACCACCCACGTTG + +4 cisbp__M5053-ken 7 0.333617 8157.93 1 6 CACCTG CTACTTTCACCGGGG - +4 flyfactorsurvey__ken_SOLEXA_5_FBgn0011236-ken 7 0.333617 8157.93 1 6 CACCTG CTACTTTCACCGGGG - +4 transfac_pro__M07663-brk 3 0.333617 8157.93 1 6 CACCTG TGGCGCCTGGCGCCA - +4 transfac_pro__M07111 -1 0.333617 8157.93 1 5 CACCTG AGCTGTCACTCACCT + +4 cisbp__M2298 -1 0.333617 8157.93 1 5 CACCTG AGCTGTCACTCACCT - +4 jaspar__MA0074.1-EcR-usp 10 0.333617 8157.93 1 5 CACCTG TGAACTCGTTGACCC - +4 cisbp__M0228-crp 2 0.334836 8187.75 1 6 CACCTG ATCAGCTGA + +4 cisbp__M1281 2 0.334836 8187.75 1 6 CACCTG CTTACGCAA + +4 cisbp__M2138 3 0.334836 8187.75 1 6 CACCTG CGCCACACT + +4 predrem__nrMotif1298 3 0.334836 8187.75 1 6 CACCTG GGGGACCGG + +4 predrem__nrMotif1507 3 0.334836 8187.75 1 6 CACCTG TCTCACATA + +4 predrem__nrMotif2101 0 0.334836 8187.75 1 6 CACCTG CACATTGCT + +4 predrem__nrMotif726 3 0.334836 8187.75 1 6 CACCTG TTGGCCCTT + +4 predrem__nrMotif901 2 0.334836 8187.75 1 6 CACCTG CTTATCTCT + +4 cisbp__M5123-bowl-drm-odd-sob 2 0.334836 8187.75 1 6 CACCTG GCTACCGTA - +4 cisbp__M6377-vnd 1 0.334836 8187.75 1 6 CACCTG GTCCTTGAA - +4 hocomoco__ZN394_HUMAN.H11MO.1.D 1 0.334836 8187.75 1 6 CACCTG ATTCCATTC - +4 jaspar__MA0333.1 3 0.334836 8187.75 1 6 CACCTG CGCCACACC - +4 predrem__nrMotif1380 2 0.334836 8187.75 1 6 CACCTG GCCATCTCT - +4 predrem__nrMotif1683 1 0.334836 8187.75 1 6 CACCTG TGACCAAGG - +4 predrem__nrMotif241 2 0.334836 8187.75 1 6 CACCTG TTCACATTC - +4 predrem__nrMotif248 3 0.334836 8187.75 1 6 CACCTG TGTGACTTT - +4 transfac_pro__M01962 3 0.334836 8187.75 1 6 CACCTG CGCCACACC - +4 cisbp__M0994-Optix-Six4 4 0.334836 8187.75 1 5 CACCTG ATGATACCC + +4 predrem__nrMotif1009 -1 0.334836 8187.75 1 5 CACCTG GCCTCGGAG + +4 predrem__nrMotif1608 -1 0.334836 8187.75 1 5 CACCTG ATCTTCTGA + +4 predrem__nrMotif1766 -1 0.334836 8187.75 1 5 CACCTG ATCTTCATT + +4 predrem__nrMotif1805 4 0.334836 8187.75 1 5 CACCTG TGTGACCCT + +4 transfac_pro__M02049 4 0.334836 8187.75 1 5 CACCTG AACACACAT + +4 predrem__nrMotif1555 -1 0.334836 8187.75 1 5 CACCTG ACCATTTTG - +4 predrem__nrMotif1860 -1 0.334836 8187.75 1 5 CACCTG ATCTTGTCT - +4 predrem__nrMotif1924 -1 0.334836 8187.75 1 5 CACCTG AACTGGATG - +4 predrem__nrMotif1993 -1 0.334836 8187.75 1 5 CACCTG AACTGGAGA - +4 predrem__nrMotif41 -2 0.334836 8187.75 1 4 CACCTG CCTGCCCCC + +4 taipale_cyt_meth__YBX1_YGTWCCAYC_eDBD_meth-yps 5 0.334836 8187.75 1 4 CACCTG TGTACCATC + +4 cisbp__M2917-ss 8 0.335734 8209.7 1 6 CACCTG TCTCACGCTAGCCGGGGG + +4 hocomoco__NR2F6_HUMAN.H11MO.0.D-EcR-Hnf4-Hr78-eg-kni-knrl-svp-usp 11 0.335734 8209.7 1 6 CACCTG AGGACAAAGTTCATTTGA + +4 cisbp__M4621-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Snr1-srp-Stat92E-svp 2 0.335734 8209.7 1 6 CACCTG CTTATCTGCCCCCACCAG - +4 cisbp__M4880-ZIPIC 12 0.335734 8209.7 1 6 CACCTG GGGTGTTATGCAGCCCTG - +4 taipale_tf_pairs__ETV2_EVX1_RSCGGWAATNNNYATTAN_CAP-eve-pnt 11 0.335734 8209.7 1 6 CACCTG GTAATGGCCATTTCCGGT - +4 transfac_pro__M05349-esg-sna-wor 5 0.335734 8209.7 1 6 CACCTG CCCTTCCCCTTTTCCCAC - +4 transfac_pro__M06127 12 0.335734 8209.7 1 6 CACCTG ACCACGACGATTAACCCC - +4 transfac_pro__M06140 2 0.335734 8209.7 1 6 CACCTG GCCACCTCAGTCCCCCCC - +4 transfac_pro__M06571 8 0.335734 8209.7 1 6 CACCTG GATAGCATGGCCTACCCC - +4 tfdimers__MD00239 11 0.337318 8248.44 1 6 CACCTG AAATTGCCAGTTAACTGGCAATTA + +4 taipale_tf_pairs__RFX3_FIGLA_GTTGCYNNNNNNNNNNNNCASSTG_CAP_repr-Rfx 0 0.337318 8248.44 1 6 CACCTG CAGCTGGGGCGTTGCCATGGCAAC - +4 tfdimers__MD00049-oc 8 0.337318 8248.44 1 6 CACCTG AAAAGGATTAACTGCCACTAATTA - +4 cisbp__M2478 0 0.337609 8255.56 1 6 CACCTG TATCTA - +4 swissregulon__hs__ATF5_CREB3.p2-CrebB-Jra-kay 1 0.337609 8255.56 1 5 CACCTG TGACGT + +4 stark__GGGTCA-Hr3 1 0.337609 8255.56 1 5 CACCTG TGACCC - +4 swissregulon__sacCer__ECM23 1 0.337609 8255.56 1 5 CACCTG AGATCT - +4 cisbp__M2383 4 0.338514 8277.68 1 6 CACCTG TATTGACCGCCGGTCAATA + +4 jaspar__MA0590.1 4 0.338514 8277.68 1 6 CACCTG TATTGACCGCCGGTCAATA + +4 transfac_pro__M06310 13 0.338514 8277.68 1 6 CACCTG AAGAATAAAAAACAGCCTG + +4 transfac_pro__M06638 10 0.338514 8277.68 1 6 CACCTG AAGGGGCAATTACCAGCGG + +4 transfac_pro__M09173-Dif-dl-Klf15-klu-sr 10 0.338514 8277.68 1 6 CACCTG CCTCCTCCTCCTCCTCCTC + +4 transfac_pro__M09218 0 0.338514 8277.68 1 6 CACCTG AACCTTATCCATATCTTAT + +4 transfac_pro__M09258 4 0.338514 8277.68 1 6 CACCTG TTTCCTCCGGATTTTCCGG + +4 transfac_public__M00214 8 0.338514 8277.68 1 6 CACCTG AACACGGATATCTGTGGTC + +4 hocomoco__ZN232_HUMAN.H11MO.0.D 8 0.338514 8277.68 1 6 CACCTG ACTTAATCTACATTTAACA - +4 taipale_cyt_meth__ZSCAN23_NYCATGTGCTAATTACAMN_eDBD_meth_repr 11 0.338514 8277.68 1 6 CACCTG TTTGTAATTAGCACATGAT - +4 neph__UW.Motif.0674 0 0.338944 8288.2 1 6 CACCTG AAACATTTTTCTGA + +4 cisbp__M1862-bin-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 6 0.338944 8288.2 1 6 CACCTG ATTGTTTACGTTTG - +4 flyfactorsurvey__CG7928-F5-7_SOLEXA_5-ZIPIC 2 0.338944 8288.2 1 6 CACCTG TGTCCCTGAAAGGG - +4 jaspar__MA0030.1-FoxK-FoxL1-FoxP-bin-fd19B-fd59A-fd102C-foxo-slp1-slp2 6 0.338944 8288.2 1 6 CACCTG ATTGTTTACGTTTG - +4 neph__UW.Motif.0282 6 0.338944 8288.2 1 6 CACCTG TGCTGAATTTTTCA - +4 neph__UW.Motif.0422 7 0.338944 8288.2 1 6 CACCTG CTGGAAAATCCATG - +4 predrem__nrMotif1215-l(3)neo38 4 0.338944 8288.2 1 6 CACCTG CCCCCACCCCCACT - +4 swissregulon__hs__FOX_F1_F2_J1_.p2-FoxK-FoxL1-FoxP-bin-fd19B-fd59A-fd102C-foxo-slp1-slp2 6 0.338944 8288.2 1 6 CACCTG TTTGTTTACCTTGG - +4 cisbp__M4899-crp 2 0.339184 8294.07 1 6 CACCTG ATCAGCTGGTC + +4 flyfactorsurvey__HLHm7_SANGER_5_FBgn0002633-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 1 0.339184 8294.07 1 6 CACCTG GCACGTGCCAA + +4 neph__UW.Motif.0119 3 0.339184 8294.07 1 6 CACCTG TGAAAAATGCA + +4 stark__TGTCAMNTGCA 3 0.339184 8294.07 1 6 CACCTG TGTCAAATGCA + +4 taipale_cyt_meth__ERG_NACCGGAARTN_FL-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.339184 8294.07 1 6 CACCTG GACCGGAAGTG + +4 taipale_cyt_meth__TFEC_MNCACGTGAYN_eDBD-cnc-cyc-Max-Mitf-Usf 2 0.339184 8294.07 1 6 CACCTG CCCACGTGACC + +4 cisbp__M4609-Clk-E2f1-gce-Max-Mnt-Myc-tgo-Usf 3 0.339184 8294.07 1 6 CACCTG GAGCACGTGGC - +4 hocomoco__MAX_MOUSE.H11MO.0.A-E2f1-Max-Myc 2 0.339184 8294.07 1 6 CACCTG GCCACGTGCTC - +4 scertf__zhu.YPR013C 5 0.339184 8294.07 1 6 CACCTG TGATTTACGTT - +4 swissregulon__hs__XBP1.p3-Xbp1 0 0.339184 8294.07 1 6 CACCTG GACGTGGCATT - +4 transfac_pro__M04811-Dif-dl 4 0.339184 8294.07 1 6 CACCTG AAATCCCCAGC - +4 transfac_pro__M05005 5 0.339184 8294.07 1 6 CACCTG TTTGTCCGCTA - +4 transfac_pro__M06359 5 0.339184 8294.07 1 6 CACCTG TCCTCCCCCTA - +4 transfac_pro__M07387 3 0.339184 8294.07 1 6 CACCTG CGCGACCCACT - +4 hocomoco__RFX5_HUMAN.H11MO.1.A -2 0.339184 8294.07 1 4 CACCTG CCTAGCAACAG - +4 predrem__nrMotif994 7 0.339184 8294.07 1 4 CACCTG CAGGCCCCACC - +4 dbcorrdb__ATF2__ENCSR000BQU_1__m2 10 0.34017 8318.17 1 6 CACCTG CGCGTTGCGTTAGCAAGGGG + +4 dbcorrdb__CUX1__ENCSR000EFO_1__m2-ct 0 0.34017 8318.17 1 6 CACCTG CCCCTGAGCGATCACTGAGC + +4 dbcorrdb__EZH2__ENCSR000ARD_1__m1-Bgb-Bro-E(z) 2 0.34017 8318.17 1 6 CACCTG AAAACCACAAAAAGCAAACA + +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m8-RpII215 4 0.34017 8318.17 1 6 CACCTG AAAGAACCAACACAATCCTC + +4 dbcorrdb__RELA__ENCSR000EAI_1__m2-Dif-dl 8 0.34017 8318.17 1 6 CACCTG CCGGAAATCCCCCACAGAGA + +4 dbcorrdb__RELA__ENCSR000EAN_1__m2-Dif-dl 1 0.34017 8318.17 1 6 CACCTG CCAGCTGACTCAGATGGGGA + +4 dbcorrdb__RELA__ENCSR000EAW_1__m3-Dif-dl 8 0.34017 8318.17 1 6 CACCTG TCAGAATTCCCCCACTGGGA + +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m6 13 0.34017 8318.17 1 6 CACCTG ATTAATGTGCTAAAACTTTT + +4 transfac_pro__M01564-Max-Myc 7 0.34017 8318.17 1 6 CACCTG GACCAAGCACGTGCCCGTAT + +4 dbcorrdb__CTCF__ENCSR000DUG_1__m2-CTCF-vtd 12 0.34017 8318.17 1 6 CACCTG GGGCAGCAGCGCCCCCTGCC - +4 dbcorrdb__FOXA1__ENCSR000BPX_1__m1-fkh-Hsf 2 0.34017 8318.17 1 6 CACCTG AGAACAGTATGTTCTTTTTA - +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m1 7 0.34017 8318.17 1 6 CACCTG GCCTATGTACCTAATCATCC - +4 dbcorrdb__NR3C1__ENCSR000BHG_1__m1-fkh-Hsf 3 0.34017 8318.17 1 6 CACCTG AAGAACAGAATGTTCTTGGC - +4 hocomoco__WT1_HUMAN.H11MO.0.C-Brf-CG42741-CTCF-CoRest-Dif-HDAC1-Klf15-Nelf-E-Rbbp5-SREBP-Spps-Spt20-btd-crol-ct-dl-klu-sr 6 0.34017 8318.17 1 6 CACCTG CCCCCCCTCCTCCCCCGCCC - +4 transfac_pro__M01548-gt 6 0.34017 8318.17 1 6 CACCTG GTCGCTTACGTAATCAGACC - +4 tfdimers__MD00050-CG5641-NFAT-Pur-alpha 7 0.340481 8325.77 1 6 CACCTG TTTTTTTTTCCTGCCCCTTTTT - +4 neph__UW.Motif.0398 9 0.340783 8333.17 1 6 CACCTG AGAAAAAAATTTCTCT + +4 neph__UW.Motif.0455 7 0.340783 8333.17 1 6 CACCTG GAAATGAAATTTGCCA + +4 neph__UW.Motif.0541 6 0.340783 8333.17 1 6 CACCTG GCTCCCAGCCTCCCCA + +4 transfac_pro__M01322-scro 5 0.340783 8333.17 1 6 CACCTG TAAGCCACTTAACATT + +4 cisbp__M2370 7 0.340783 8333.17 1 6 CACCTG ATAGCCGTACTTTTTC - +4 cisbp__M6109-EcR-usp 2 0.340783 8333.17 1 6 CACCTG TGAACCCGATGAACTC - +4 jaspar__MA0904.1-Antp-Lim3-Scr-Ubx-abd-A-bsh-btn-ind-lab-pb 10 0.340783 8333.17 1 6 CACCTG ATGAGCTAATTACCGT - +4 neph__UW.Motif.0262 9 0.340783 8333.17 1 6 CACCTG CCAGATATCCAGATGG - +4 neph__UW.Motif.0298 8 0.340783 8333.17 1 6 CACCTG TGGAGCAGTGCCAGCT - +4 neph__UW.Motif.0466 5 0.340783 8333.17 1 6 CACCTG TGAAATTCACTGCCTC - +4 neph__UW.Motif.0508 2 0.340783 8333.17 1 6 CACCTG TGGCTCTGCTGCTCCC - +4 neph__UW.Motif.0593 1 0.340783 8333.17 1 6 CACCTG CAGTCTGCTTTCTGCT - +4 transfac_pro__M00800-TfAP-2 5 0.340783 8333.17 1 6 CACCTG CCCTCCGCCTGGGGGC - +4 transfac_pro__M01319-abd-A-Antp-bsh-btn-ind-lab-Lim3-pb-Scr-Ubx 10 0.340783 8333.17 1 6 CACCTG ATGAGCTAATTACCGT - +4 transfac_pro__M07609-tap 4 0.340783 8333.17 1 6 CACCTG AAGCCATCTGACTGCC - +4 cisbp__M5526-Hnf4 11 0.340783 8333.17 1 5 CACCTG ATTGGACTTTGGACCC + +4 transfac_pro__M07857-BtbVII 11 0.340783 8333.17 1 5 CACCTG ATGTACTATAGTACAT + +4 taipale__HNF4A_full_NRGTCCAAAGTCCANY-Hnf4 11 0.340783 8333.17 1 5 CACCTG ATTGGACTTTGGACCC - +4 neph__UW.Motif.0433 -2 0.340783 8333.17 1 4 CACCTG CCACAGCCAGATCTCA + +4 yetfasco__YLR176C_1478-CG5846-CG9727-Max-Rfx-SREBP 12 0.340783 8333.17 1 4 CACCTG CGTTGCCATGGCAACC - +4 taipale_tf_pairs__TFAP4_MAX_NCAGCTGNNNNNNNCACGTGN_CAP_repr-crp-Max 1 0.340796 8333.49 1 6 CACCTG TCAGCTGATAGGAGCACGTGC + +4 transfac_pro__M04689-CTCF-SMC3-usp-vtd 11 0.340796 8333.49 1 6 CACCTG TGCTATAGTGCCATCTAGTGG + +4 cisbp__M0318-CG7786-gt-Pdp1 3 0.341946 8361.62 1 6 CACCTG TATTACATAAATT + +4 neph__UW.Motif.0208 3 0.341946 8361.62 1 6 CACCTG AAAATACTCAGAA + +4 predrem__nrMotif171 0 0.341946 8361.62 1 6 CACCTG CCCCTGCCCCGCT + +4 scertf__morozov.RAP1 1 0.341946 8361.62 1 6 CACCTG ACACCCATACATC + +4 transfac_public__M00270-gcm-gcm2 1 0.341946 8361.62 1 6 CACCTG AAACCCGCATATT + +4 cisbp__M1249 6 0.341946 8361.62 1 6 CACCTG ATATAGAACATTC - +4 hocomoco__ETS1_HUMAN.H11MO.0.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-RpII215-RunxA-RunxB-bs-lz-pnt-run 4 0.341946 8361.62 1 6 CACCTG CCACTTCCTGTCT - +4 taipale_tf_pairs__ERF_FOXI1_RSCGGATGTTKWN_CAP_repr-Ets21C 3 0.341946 8361.62 1 6 CACCTG GTAAACATCCGGT - +4 transfac_pro__M04632-SREBP 7 0.341946 8361.62 1 6 CACCTG ATCACCCCACGCC - +4 transfac_pro__M07305-CG9727-Rfx 0 0.341946 8361.62 1 6 CACCTG TCCATGGCAACGC - +4 neph__UW.Motif.0412 -1 0.341946 8361.62 1 5 CACCTG AAATTCCAGAGCC + +4 transfac_pro__M05517 -1 0.341946 8361.62 1 5 CACCTG AACTGAACGAATC + +4 swissregulon__hs__IKZF1.p2 9 0.341946 8361.62 1 4 CACCTG GTTTGGGAATACC + +4 fantom__motif159_ACACATACTACA 1 0.342189 8367.55 1 6 CACCTG ACACATACTACA + +4 hocomoco__TEAD1_HUMAN.H11MO.0.A-sd 3 0.342189 8367.55 1 6 CACCTG ACATTCCAGCCA + +4 neph__UW.Motif.0101 5 0.342189 8367.55 1 6 CACCTG AAAAATTTCTGG + +4 neph__UW.Motif.0682 5 0.342189 8367.55 1 6 CACCTG AGTTTTTTCTTC + +4 taipale_cyt_meth__CREB3L4_NRTGACGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.342189 8367.55 1 6 CACCTG GGTGACGTCACC + +4 taipale_cyt_meth__MEIS2_TGACANNYGTCA_eDBD_meth-achi-hth-nau-vis 3 0.342189 8367.55 1 6 CACCTG TGACAGCTGTCA + +4 taipale_cyt_meth__XBP1_NRTGACGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.342189 8367.55 1 6 CACCTG GATGACGTCACC + +4 taipale_tf_pairs__ERF_TBX21_TMACACCGGAAG_CAP-Ets21C 3 0.342189 8367.55 1 6 CACCTG TCACACCGGAAG + +4 transfac_pro__M06029 2 0.342189 8367.55 1 6 CACCTG TATACCACCATA + +4 transfac_pro__M06285 3 0.342189 8367.55 1 6 CACCTG GGGTACTTGGGA + +4 transfac_pro__M06470 6 0.342189 8367.55 1 6 CACCTG TGAGGCTTCCTT + +4 swissregulon__hs__CREB1.p2-CrebB 5 0.342189 8367.55 1 6 CACCTG GACGTCACCCCG - +4 swissregulon__hs__NKX3-1.p2-bap 3 0.342189 8367.55 1 6 CACCTG ATATACTTATTT - +4 taipale_cyt_meth__ELF1_NACCMGGAAGTN_eDBD_meth-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.342189 8367.55 1 6 CACCTG CACTTCCTGGTT - +4 taipale_cyt_meth__ELF1_NATGCGGAAGTN_eDBD-Eip74EF 0 0.342189 8367.55 1 6 CACCTG CACTTCCGCATT - +4 taipale_cyt_meth__FOXD3_NYWAYRTAAACN_eDBD_meth-croc-fd59A-fkh 4 0.342189 8367.55 1 6 CACCTG TGTTTACGTAGG - +4 tiffin__TIFDMEM0000051 5 0.342189 8367.55 1 6 CACCTG TTTAAAAGCTTT - +4 transfac_pro__M06432 2 0.342189 8367.55 1 6 CACCTG TCCGCCTAATCT - +4 transfac_public__M00055-Myc 3 0.342189 8367.55 1 6 CACCTG CGACACGTGGGA - +4 transfac_pro__M06401 7 0.342189 8367.55 1 5 CACCTG TATTTAGGACCA - +4 transfac_pro__M06428-CG2120 7 0.342189 8367.55 1 5 CACCTG TGTTTTTTACCG - +4 transfac_pro__M06753 7 0.342189 8367.55 1 5 CACCTG TCCCAAGCACCG - +4 transfac_pro__M06843-salm-salr 7 0.342189 8367.55 1 5 CACCTG TCCCCAGGACCC - +4 transfac_pro__M00953 8 0.342909 8385.16 1 6 CACCTG CGGGAGGGTACATTGTGTTCTTGTGCG + +4 transfac_pro__M00956 8 0.342909 8385.16 1 6 CACCTG AGGTGAGGTACACGGTGTTCTTTTGGG + +4 cisbp__M0758 2 0.345333 8444.43 1 6 CACCTG TAGATCTG + +4 cisbp__M1082 0 0.345333 8444.43 1 6 CACCTG CACATCAA + +4 predrem__nrMotif525 1 0.345333 8444.43 1 6 CACCTG CAACCCCC + +4 taipale_cyt_meth__ALX3_NTCGTTAN_FL_meth-CG34367-Dr-en-eve-ind-inv-unpg 0 0.345333 8444.43 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__MEOX1_NTCGTTAN_FL-Antp-bsh-btn-Dr-lab-Scr 0 0.345333 8444.43 1 6 CACCTG ATCATTAA + +4 cisbp__M0075 0 0.345333 8444.43 1 6 CACCTG CACCGACA - +4 hdpi__MLX-bigmax 0 0.345333 8444.43 1 6 CACCTG CACGTGCG - +4 predrem__nrMotif2290 0 0.345333 8444.43 1 6 CACCTG CATCTAAA - +4 stark__TTAYGTAA-CG7786-Pdp1-gt-vri 1 0.345333 8444.43 1 6 CACCTG TTACATAA - +4 transfac_pro__M04930-fkh-Hnf4-svp 1 0.345333 8444.43 1 6 CACCTG TGACCTTT - +4 cisbp__M1140-achi-hth-vis 3 0.345333 8444.43 1 5 CACCTG TGACACAT + +4 elemento__ACCATGGC -1 0.345333 8444.43 1 5 CACCTG ACCATGGC + +4 fantom__motif100_GCYTNCTC -1 0.345333 8444.43 1 5 CACCTG GCCTCCTC + +4 fantom__motif88_CCCTCTTT -1 0.345333 8444.43 1 5 CACCTG CCCTCTTT + +4 jaspar__MA1048.1 3 0.345333 8444.43 1 5 CACCTG ACCGACCA + +4 predrem__nrMotif2014 3 0.345333 8444.43 1 5 CACCTG AAATACCA + +4 transfac_pro__M01740 3 0.345333 8444.43 1 5 CACCTG GTTGACCA + +4 transfac_pro__M04841 -1 0.345333 8444.43 1 5 CACCTG AACTGATG + +4 hdpi__GPD1-CG3215-CG43343-Gpdh -1 0.345333 8444.43 1 5 CACCTG CCCTCCCC - +4 jaspar__MA1078.1 3 0.345333 8444.43 1 5 CACCTG GTTGACCG - +4 cisbp__M5620-hth -2 0.345333 8444.43 1 4 CACCTG GCTGTCAA + +4 yetfasco__YKL043W_393 -2 0.345333 8444.43 1 4 CACCTG CCTGCAGC - +4 c2h2_zfs__M0406 5 0.345333 8444.43 1 3 CACCTG AGGAGCAC + +4 predrem__nrMotif2284 -3 0.345333 8444.43 1 3 CACCTG CTGCATGA + +4 cisbp__M5289 3 0.3464 8470.52 1 6 CACCTG GGGAACACGGTGTACCC + +4 cisbp__M5683-fkh 3 0.3464 8470.52 1 6 CACCTG GGGTACATAATGTTCCC + +4 taipale__ELK1_full_NACTTCCGSCGGAARMN_repr-Atac3 0 0.3464 8470.52 1 6 CACCTG CACTTCCGGCGGAAGTG + +4 transfac_public__M00206 11 0.3464 8470.52 1 6 CACCTG AGTTAATTATTAACCAA + +4 cisbp__M5382-Atac3 0 0.3464 8470.52 1 6 CACCTG CACTTCCGGCGGAAGTG - +4 hocomoco__PLAG1_HUMAN.H11MO.0.D 0 0.3464 8470.52 1 6 CACCTG CCCCTCCTGATGCCCCC - +4 transfac_pro__M01380-Abd-B 10 0.3464 8470.52 1 6 CACCTG AAGATTTTACGACCTTG - +4 cisbp__M0087 0 0.346457 8471.92 1 6 CACCTG TATATGCAGG + +4 cisbp__M0191-dpn-E(spl)mbeta-HLH-h-Hey-Sidpn 2 0.346457 8471.92 1 6 CACCTG GGCACGCGTC + +4 cisbp__M0866 3 0.346457 8471.92 1 6 CACCTG ATTGACACGT + +4 cisbp__M1416 2 0.346457 8471.92 1 6 CACCTG TTTACGCAAC + +4 cisbp__M1767 3 0.346457 8471.92 1 6 CACCTG TATCTCCGAT + +4 flyfactorsurvey__E_spl__SANGER_5_FBgn0000591-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn-dpn 1 0.346457 8471.92 1 6 CACCTG GCACGTGCCA + +4 flyfactorsurvey__HLH106_SANGER_5_2_FBgn0015234-Mitf-Mondo-SREBP-Usf-bigmax-cnc-cwo-tgo 2 0.346457 8471.92 1 6 CACCTG ATCACGTGAC + +4 flyfactorsurvey__vnd_FlyReg_FBgn0003986-vnd 1 0.346457 8471.92 1 6 CACCTG GCACTTGAGC + +4 jaspar__MA0960.1-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 2 0.346457 8471.92 1 6 CACCTG GGCACGTGCC + +4 neph__UW.Motif.0086 1 0.346457 8471.92 1 6 CACCTG TCATTTTTCA + +4 predrem__nrMotif1445 1 0.346457 8471.92 1 6 CACCTG AGCCCTTTTG + +4 predrem__nrMotif1640 4 0.346457 8471.92 1 6 CACCTG ATGTCATCTT + +4 predrem__nrMotif565 0 0.346457 8471.92 1 6 CACCTG AGCCTCTTTT + +4 taipale_cyt_meth__NKX3-2_NCCACTTAAN_eDBD-bap-Hmx 2 0.346457 8471.92 1 6 CACCTG ACCACTTAAC + +4 transfac_pro__M08930-Atf3-Atf6-CrebB-Jra-kay-REPTOR-BP-vri-Xbp1 2 0.346457 8471.92 1 6 CACCTG ATGACGTAAC + +4 cisbp__M0639-dmrt93B-dmrt99B-dsx 4 0.346457 8471.92 1 6 CACCTG TTGATACAGT - +4 cisbp__M0705-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 2 0.346457 8471.92 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1255 4 0.346457 8471.92 1 6 CACCTG TTATGGCCAG - +4 hocomoco__NKX32_HUMAN.H11MO.0.C-vnd 3 0.346457 8471.92 1 6 CACCTG AAACACTTAA - +4 homer__AVCAGGAAGT_EHF-Atac3-Eip74EF-Ets65A-Ets96B-Ets97D-Rpn5-aop 2 0.346457 8471.92 1 6 CACCTG ACTTCCTGGT - +4 predrem__nrMotif1734 0 0.346457 8471.92 1 6 CACCTG TACATGCTCC - +4 taipale_cyt_meth__CLOCK_NMCAYGYGYN_eDBD_meth_repr-Clk 2 0.346457 8471.92 1 6 CACCTG AACACATGTC - +4 taipale_cyt_meth__GATA5_NWGATAASRN_FL_meth-CoRest-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Sirt6-Snr1-srp 4 0.346457 8471.92 1 6 CACCTG TTCTTATCTG - +4 taipale_cyt_meth__GATA5_NWGATAASRN_eDBD_meth-CoRest-ebi-GATAe-grn-HLH3B-Jra-nej-pnr-sd-Sirt6-Snr1-srp 4 0.346457 8471.92 1 6 CACCTG TTCTTATCTG - +4 tiffin__TIFDMEM0000079-HLH54F-crp-nau 2 0.346457 8471.92 1 6 CACCTG AACAGCTGTT - +4 yetfasco__YLR098C_2120 2 0.346457 8471.92 1 6 CACCTG ATTTCCGCCG - +4 cisbp__M1301 5 0.346457 8471.92 1 5 CACCTG ATTGACACTT + +4 homer__ACTGAAACCA_IRF4 5 0.346457 8471.92 1 5 CACCTG ACTGAAACCA + +4 taipale_cyt_meth__OLIG3_AMCAGCTGTT_eDBD_meth-amos-ato-crp-dimm-Fer3-HLH3B-HLH54F-Oli-tap-twi -1 0.346457 8471.92 1 5 CACCTG ACCATATGTT + +4 transfac_pro__M02073-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.346457 8471.92 1 5 CACCTG ACCGGAAGTA + +4 transfac_pro__M05427 5 0.346457 8471.92 1 5 CACCTG CGTAAAGCCT + +4 cisbp__M0622-dmrt11E 5 0.346457 8471.92 1 5 CACCTG ATTGATACAT - +4 cisbp__M1678 5 0.346457 8471.92 1 5 CACCTG GCGTTGACCT - +4 jaspar__MA1086.1 5 0.346457 8471.92 1 5 CACCTG GTGTTGACTT - +4 transfac_pro__M07918-CG12769 -1 0.346457 8471.92 1 5 CACCTG TCCTGTGGGA - +4 transfac_pro__M09348 5 0.346457 8471.92 1 5 CACCTG AAAAATATCT - +4 cisbp__M1534-CG9727-Rfx 6 0.346457 8471.92 1 4 CACCTG CATAGCAACC + +4 tfdimers__MD00518 13 0.346869 8481.98 1 6 CACCTG ATATTTTTTTGCATAACTGCCTTTTT + +4 tfdimers__MD00598-Taf7-Tbp 5 0.346869 8481.98 1 6 CACCTG ATTTTCACTTCTTTTTTATATTTTAT + +4 predrem__nrMotif385 0 0.347321 8493.03 1 6 CACCTG TTCCTAG - +4 predrem__nrMotif1615 2 0.347321 8493.03 1 5 CACCTG AAGACAT + +4 cisbp__M0627 2 0.347321 8493.03 1 5 CACCTG GAAACAT - +4 transfac_pro__M03574-gcm-gcm2 -2 0.347321 8493.03 1 4 CACCTG CCCGCAT + +4 flyfactorsurvey__HLH4C_SANGER_5_FBgn0011277-HLH4C 4 0.348157 8513.47 1 6 CACCTG AGCGCAGCTGAGGCC + +4 homer__VAGRACAKNCTGTBC_PR-Hsf-fkh 3 0.348157 8513.47 1 6 CACCTG CAGAACAGTCTGTTC + +4 neph__UW.Motif.0536 2 0.348157 8513.47 1 6 CACCTG AAAACATTTTTTTCT + +4 stark__CACNNRNNNNNNCAC 0 0.348157 8513.47 1 6 CACCTG CACAAAAAAAAACAC + +4 taipale_cyt_meth__ZNF787_TGCCTCMGTTTMCCY_FL_meth_repr-zfh1 0 0.348157 8513.47 1 6 CACCTG TGCCTCAGTTTACCC + +4 transfac_pro__M01086-byn 8 0.348157 8513.47 1 6 CACCTG AAAAATCGCACTTAT + +4 transfac_pro__M01996-fkh 1 0.348157 8513.47 1 6 CACCTG GAACATTCTGTTCTT + +4 transfac_pro__M02769 9 0.348157 8513.47 1 6 CACCTG ATAAACCGAAACCAA + +4 transfac_pro__M09374 0 0.348157 8513.47 1 6 CACCTG TACTTGAAGATGAAG + +4 yetfasco__YKL109W_695 3 0.348157 8513.47 1 6 CACCTG TCGAATCTGATTGGT + +4 hocomoco__KLF5_MOUSE.H11MO.0.A-CG3065-CG42741-Klf15-Spps-btd-cbt-dar1-hkb-luna 5 0.348157 8513.47 1 6 CACCTG GCCCCACCCTGCCCC - +4 neph__UW.Motif.0154 2 0.348157 8513.47 1 6 CACCTG TGTTTTTTCCATGTG - +4 neph__UW.Motif.0530 5 0.348157 8513.47 1 6 CACCTG CACAGTCTCTGCCTG - +4 neph__UW.Motif.0620 7 0.348157 8513.47 1 6 CACCTG TCACTGTTTTTTTTG - +4 transfac_pro__M00922-bs 3 0.348157 8513.47 1 6 CACCTG CATCTCCTTATATGG - +4 transfac_pro__M06257 9 0.348157 8513.47 1 6 CACCTG TGGCATCCCCACCAT - +4 transfac_pro__M09515-Atf6-CrebA-Xbp1 3 0.348157 8513.47 1 6 CACCTG TGCCACGTGTCCATT - +4 transfac_pro__M09528-Atf6-CrebA-Usf-Xbp1 3 0.348157 8513.47 1 6 CACCTG TGCCACGTGACCATT - +4 transfac_pro__M09539-Atf6-CrebA-Xbp1 6 0.348157 8513.47 1 6 CACCTG GATGCTGACGTGGCA - +4 transfac_public__M00411-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-svp-usp 2 0.348157 8513.47 1 6 CACCTG GTGACCTTTGACCCC - +4 taipale_tf_pairs__HOXB13_EOMES_ANGTGTSNNATAAAN_CAP_repr 10 0.348157 8513.47 1 5 CACCTG TTTTATGACACACCT - +4 cisbp__M4555-bon-egg 11 0.348157 8513.47 1 4 CACCTG TACTGGAGAGAAACC + +4 cisbp__M1711 2 0.349001 8534.13 1 6 CACCTG GTTTCCGGG + +4 cisbp__M1811 2 0.349001 8534.13 1 6 CACCTG ATCTCCGTC + +4 predrem__nrMotif1352 1 0.349001 8534.13 1 6 CACCTG TCATCTTCT + +4 predrem__nrMotif2555 1 0.349001 8534.13 1 6 CACCTG TGATCTGCT + +4 predrem__nrMotif820 3 0.349001 8534.13 1 6 CACCTG AGGGACTTC + +4 cisbp__M0434 3 0.349001 8534.13 1 6 CACCTG GTGCACACA - +4 cisbp__M0771 3 0.349001 8534.13 1 6 CACCTG TTTGATCGG - +4 cisbp__M6326-CG42741 3 0.349001 8534.13 1 6 CACCTG CACCCCCTG - +4 predrem__nrMotif1368 2 0.349001 8534.13 1 6 CACCTG TGAACATCA - +4 predrem__nrMotif1528 3 0.349001 8534.13 1 6 CACCTG GGGGAACTG - +4 predrem__nrMotif2459 1 0.349001 8534.13 1 6 CACCTG CCTCCTCGG - +4 predrem__nrMotif615 1 0.349001 8534.13 1 6 CACCTG TCATCTTCC - +4 predrem__nrMotif838 1 0.349001 8534.13 1 6 CACCTG TGCCCTGTG - +4 transfac_pro__M07940-ovo 1 0.349001 8534.13 1 6 CACCTG GTACCGTTA - +4 predrem__nrMotif1743 4 0.349001 8534.13 1 5 CACCTG AAGGCATCT + +4 predrem__nrMotif656 -1 0.349001 8534.13 1 5 CACCTG ACCCAGACC + +4 predrem__nrMotif825 -1 0.349001 8534.13 1 5 CACCTG TTCTGCTGT + +4 predrem__nrMotif858 -1 0.349001 8534.13 1 5 CACCTG GCCTTCTCC + +4 predrem__nrMotif992 4 0.349001 8534.13 1 5 CACCTG CAGTTTCCT - +4 taipale__RHOXF1_DBD_GGMTNAKCC 4 0.349001 8534.13 1 5 CACCTG GGATTATCC - +4 cisbp__M6415-Antp-ap-E5-ems-en-eve-ind-inv-lab-Lim3-pb-Scr-slou-Ubx-zen2 5 0.349001 8534.13 1 4 CACCTG CTAATTACC + +4 predrem__nrMotif495 -2 0.349001 8534.13 1 4 CACCTG TCTTCTCTC + +4 predrem__nrMotif860 -2 0.349001 8534.13 1 4 CACCTG TCTTCATTA + +4 hdpi__VAX2-mRpL1 -3 0.349001 8534.13 1 3 CACCTG CTGTGAAAT + +4 tfdimers__MD00292 11 0.350213 8563.75 1 6 CACCTG AAAAAAATGCAAACATTTAAAAATA + +4 tfdimers__MD00345 9 0.350213 8563.75 1 6 CACCTG GCGCGCTGTCCCCCTGGGACATAGG - +4 cisbp__M4978-ftz-f1 5 0.350617 8573.64 1 6 CACCTG GCGGTGACCTTCGGACTG + +4 transfac_pro__M05864 4 0.350617 8573.64 1 6 CACCTG GGGGAACCGGCCAACGAC - +4 transfac_pro__M06858-CG2120 13 0.350617 8573.64 1 5 CACCTG GACCCCTCGTCAACACCC - +4 hdpi__GTF2H3-Tfb4 1 0.351477 8594.67 1 5 CACCTG ATTTCT - +4 fantom__motif67_GNTAAC 2 0.351477 8594.67 1 4 CACCTG GTTAAC - +4 transfac_pro__M01227 2 0.351477 8594.67 1 4 CACCTG GTCAGC - +4 hocomoco__ZNF41_HUMAN.H11MO.0.C 15 0.352875 8628.86 1 6 CACCTG CACAAGGGAGTAAGGCACCATGAG + +4 tfdimers__MD00348 9 0.352875 8628.86 1 6 CACCTG ATAATGTTTTATCTCCACAACCTA + +4 hocomoco__ZN436_HUMAN.H11MO.0.C 16 0.352875 8628.86 1 6 CACCTG CCTCCTCCAGGAAGCCTTCCCTGA - +4 hdpi__CANX-CG1924-Cnx14D-Cnx99A 2 0.352875 8628.86 1 3 CACCTG AGCAC - +4 hdpi__HLCS-Hcs -3 0.352875 8628.86 1 3 CACCTG CTGCC - +4 cisbp__M0068 5 0.353486 8643.78 1 6 CACCTG TGGTGTACACA + +4 cisbp__M5127-amos-ato-da-dimm-HLH54F-Oli-tap 0 0.353486 8643.78 1 6 CACCTG CACCATATGGC + +4 flyfactorsurvey__Oli_da_SANGER_5_1_FBgn0000413-HLH54F-Oli-amos-ato-da-dimm-tap 0 0.353486 8643.78 1 6 CACCTG CACCATATGGC + +4 predrem__nrMotif205 1 0.353486 8643.78 1 6 CACCTG CTTCCTCCTCT + +4 taipale_cyt_meth__ELK3_NACCGGAAGTN_FL_meth_repr-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.353486 8643.78 1 6 CACCTG AACCGGAAGTG + +4 taipale_cyt_meth__GABPA_NACMGGAAGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.353486 8643.78 1 6 CACCTG AACCGGAAGTG + +4 transfac_pro__M01792 1 0.353486 8643.78 1 6 CACCTG CCACCACCACC + +4 cisbp__M2277-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 4 0.353486 8643.78 1 6 CACCTG CCACTTCCTGT - +4 cisbp__M4646-bigmax-Max-Mitf-Usf 1 0.353486 8643.78 1 6 CACCTG CCACGTGATCC - +4 cisbp__M5022-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH 1 0.353486 8643.78 1 6 CACCTG GCACGTGCCAA - +4 cisbp__M5378-aop-Eip74EF-Ets96B-Ets98B-Hr78 0 0.353486 8643.78 1 6 CACCTG TACTTCCGGGT - +4 flyfactorsurvey__CG12029_SANGER_10_FBgn0035454-CG3065-CG42741-Spps-btd-cbt-dar1-luna 4 0.353486 8643.78 1 6 CACCTG GCCACACCCAC - +4 flyfactorsurvey__klu_SANGER_10_FBgn0013469-klu-sr 1 0.353486 8643.78 1 6 CACCTG CCACCCACGCA - +4 taipale_cyt_meth__ETV5_NRCMGGAAGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.353486 8643.78 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__TFE3_RNCAYGTGAYN_eDBD_meth-Mitf 3 0.353486 8643.78 1 6 CACCTG CGTCACATGCT - +4 transfac_pro__M05970 2 0.353486 8643.78 1 6 CACCTG TCCTCCTTCAC - +4 transfac_pro__M09158 0 0.353486 8643.78 1 6 CACCTG CAACTTCACTA - +4 transfac_pro__M09427 5 0.353486 8643.78 1 6 CACCTG ATCCGTACAAT - +4 transfac_pro__M06434-zfh1 6 0.353486 8643.78 1 5 CACCTG AATACAGACCA - +4 transfac_pro__M09344 6 0.353486 8643.78 1 5 CACCTG AAAAAATATCT - +4 neph__UW.Motif.0355 2 0.353519 8644.6 1 6 CACCTG AAGAACACTGTTTT + +4 transfac_pro__M09501 5 0.353519 8644.6 1 6 CACCTG TTAGCAACTTGCAT + +4 transfac_public__M00121-bigmax-Max-Mitf-Myc-SREBP-tgo-Usf 4 0.353519 8644.6 1 6 CACCTG AGATCACGTGATCT + +4 swissregulon__hs__ETS1_2.p2-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 6 0.353519 8644.6 1 6 CACCTG AGTCACTTCCTGTC - +4 transfac_pro__M04803-Jra 1 0.353519 8644.6 1 6 CACCTG AAACCCGGAGCGGA - +4 transfac_pro__M07653-ac-amos-ase-crp-dimm-Fer3-HLH54F-l(1)sc-nau-sc 4 0.353519 8644.6 1 6 CACCTG GCAACAGCTGTTGC - +4 transfac_pro__M09131 4 0.353519 8644.6 1 6 CACCTG TTTTTAACTTTTTG - +4 neph__UW.Motif.0546 9 0.353519 8644.6 1 5 CACCTG GTTTTTTTTCTTCT - +4 transfac_pro__M06962 9 0.353519 8644.6 1 5 CACCTG GTTGCCTCCTGCCT - +4 neph__UW.Motif.0510 10 0.353519 8644.6 1 4 CACCTG GAAGAAAAAAATCC + +4 yetfasco__YPR054W_1875 1 0.353566 8645.75 1 6 CACCTG TCAACTCTGAGGCTTGCTA + +4 dbcorrdb__ATF3__ENCSR000BPS_1__m1-Bdp1-Brf-CG17209-ebi-Tbp 10 0.355362 8689.66 1 6 CACCTG ACCACTGAGCCACCGAGGCT + +4 dbcorrdb__EP300__ENCSR000BHB_1__m1-Chd1-Jra-nej 9 0.355362 8689.66 1 6 CACCTG CTCGGACTAAACCACTTGCT + +4 dbcorrdb__ESRRA__ENCSR000DYQ_1__m3-ERR 5 0.355362 8689.66 1 6 CACCTG CCCGACACCACATGGCCCTT + +4 dbcorrdb__HCFC1__ENCSR000ECH_1__m1-Hcf-mor-Six4 12 0.355362 8689.66 1 6 CACCTG CGGGGACTACAACTCCCGGG + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EGF_1__m4-RpII215 14 0.355362 8689.66 1 6 CACCTG AACCCCGCCACGGCAACTGG + +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m3-bon 3 0.355362 8689.66 1 6 CACCTG TCTGTCCTGTATGCTTGCTG + +4 dbcorrdb__ZNF217__ENCSR000EWU_1__m1-GATAe-grh-grn-nej-pnr 9 0.355362 8689.66 1 6 CACCTG AACCTGTCAAACCTGTTTTG + +4 taipale_tf_pairs__ETV2_RFX5_NNNTTCCGSNNNNGCAACNN_CAP_repr-pnt 14 0.355362 8689.66 1 6 CACCTG CACTTCCGGTACGGCAACGG + +4 transfac_pro__M01502 11 0.355362 8689.66 1 6 CACCTG TAAATGAGATCTACAAGCTG + +4 transfac_pro__M01580-bigmax-mio 7 0.355362 8689.66 1 6 CACCTG ATATTAGCACGTGCTTAGTC + +4 dbcorrdb__GTF3C2__ENCSR000DOD_1__m5 0 0.355362 8689.66 1 6 CACCTG CACCTTCTAAGAGCGCCCGT - +4 dbcorrdb__HNF4A__ENCSR000BLF_1__m2-btd-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-Spps-svp-usp 14 0.355362 8689.66 1 6 CACCTG CACTCTGGACTTTGAACTCT - +4 dbcorrdb__IRF1__ENCSR000EGU_1__m2 5 0.355362 8689.66 1 6 CACCTG AAGGCCACTTTCTTTTTAGC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DZK_1__m1-RpII215 2 0.355362 8689.66 1 6 CACCTG GCCTCTTGCGCCATTTCCTC - +4 dbcorrdb__RAD21__ENCSR000EDE_1__m2-CTCF-SMC3-vtd 8 0.355362 8689.66 1 6 CACCTG AAAAGCGCCTTTTGGTGGTT - +4 dbcorrdb__SIRT6__ENCSR000DOH_1__m2-Sirt6 8 0.355362 8689.66 1 6 CACCTG TCTCCAGGCACGTGACCCAG - +4 dbcorrdb__SRF__ENCSR000BLV_1__m2-bs 6 0.355362 8689.66 1 6 CACCTG GGCGCTCGCCGATTGCGGGC - +4 dbcorrdb__TEAD4__ENCSR000BRY_1__m2-sd 8 0.355362 8689.66 1 6 CACCTG TCCCCGCATTCCTGCCACTC - +4 dbcorrdb__ZNF274__ENCSR000EVX_1__m2-bon 2 0.355362 8689.66 1 6 CACCTG ATTACATTTATAGGGTTTCT - +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m7-HP1b-HP1c-HP1e-Su(var)205 7 0.355362 8689.66 1 6 CACCTG TGAGTTACAGCTGAAGGCTT - +4 hocomoco__ZN263_HUMAN.H11MO.0.A-CTCF-CoRest-Dif-Klf15-Spps-Spt20-btd-ct-dl-klu-sr 9 0.355362 8689.66 1 6 CACCTG CTCCTCCTCTCCCTCCTCCC - +4 taipale_tf_pairs__MYBL1_FIGLA_NCASSTGNNNNNNNCSGTTR_CAP_repr-Myb 13 0.355362 8689.66 1 6 CACCTG TAACGGTCCTTCCCAGCTGG - +4 cisbp__M6159 0 0.355599 8695.45 1 6 CACCTG TTCCTAGAAAGCTTTT + +4 hocomoco__ANDR_HUMAN.H11MO.1.A-Hsf-fkh 2 0.355599 8695.45 1 6 CACCTG GGAACAGTGTGTTCTT + +4 jaspar__MA0577.1 7 0.355599 8695.45 1 6 CACCTG ATTGCCGTACTTTTTC + +4 neph__UW.Motif.0095-twi 0 0.355599 8695.45 1 6 CACCTG CATATGTTATTAATTA + +4 neph__UW.Motif.0603 8 0.355599 8695.45 1 6 CACCTG CACACTGCTTTCATCA + +4 taipale_tf_pairs__TEAD4_DLX3_RCATTCCNNNYMATTA_CAP-sd 3 0.355599 8695.45 1 6 CACCTG ACATTCCACGCAATTA + +4 transfac_pro__M02844 7 0.355599 8695.45 1 6 CACCTG ATCCCCGCCCCTAAAA + +4 transfac_pro__M07646-HLH4C 5 0.355599 8695.45 1 6 CACCTG GGCACCAGCTGGTGCC + +4 neph__UW.Motif.0153 1 0.355599 8695.45 1 6 CACCTG TGACCACCCTGGGGAA - +4 neph__UW.Motif.0482 7 0.355599 8695.45 1 6 CACCTG CAGCAAATATTTTTTT - +4 neph__UW.Motif.0667 5 0.355599 8695.45 1 6 CACCTG GGAAATTGCTGTGCTT - +4 taipale__Hnf4a_DBD_RRGGTCAAAGTCCRNN-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-svp-usp 10 0.355599 8695.45 1 6 CACCTG ATTGGACTTTGACCCC - +4 transfac_pro__M01487-abd-A-Antp-bsh-btn-E5-ems-ind-lab-Lim3-pb-Scr-slou-Ubx 8 0.355599 8695.45 1 6 CACCTG ACGGTAATTAGCTCAG - +4 taipale_tf_pairs__FLI1_HOXB13_NCCGGAANTNRTAAAN_HT -1 0.355599 8695.45 1 5 CACCTG ACCGGAAGTCGTAAAA + +4 swissregulon__hs__AR.p2-fkh 14 0.355892 8702.62 1 6 CACCTG CAAAGAACACCCTGTCCCTGCC + +4 taipale_tf_pairs__ETV2_RFX5_RNCGGAANNNNNNNNNGCAACN_CAP_repr-pnt 10 0.355892 8702.62 1 6 CACCTG ACCGGAAGTGCGCCTAGCAACG + +4 tfdimers__MD00473-lz-run-RunxA-RunxB 11 0.355892 8702.62 1 6 CACCTG GTCGCTGTGGTCAGCAGGGTTC + +4 hocomoco__RFX1_HUMAN.H11MO.0.B-CG5846-CG9727-Max-Rfx-SREBP-Sin3A-Taf1 4 0.355892 8702.62 1 6 CACCTG CCGTCGCCATGGCAACCGGGGC - +4 cisbp__M6441-Fer1 15 0.356108 8707.91 1 6 CACCTG GGACAGCTGTTCTGTTTCCTG + +4 jaspar__MA0533.1-su(Hw) 10 0.356108 8707.91 1 6 CACCTG ATTTGTTGCATACTTTTGGGC - +4 tfdimers__MD00132-Myc-ovo 10 0.356108 8707.91 1 6 CACCTG CCCCCCTCACCATCTGCCCCC - +4 transfac_pro__M06247-CG2120 16 0.356108 8707.91 1 5 CACCTG CACTCCTCCGCCGCTTAACCA - +4 transfac_pro__M07742-Sox102F 2 0.356489 8717.24 1 6 CACCTG ACCACCGAACAAT + +4 hocomoco__GLIS1_HUMAN.H11MO.0.D-lmd-sug 1 0.356489 8717.24 1 6 CACCTG AGACCCCCCACGA - +4 taipale_cyt_meth__FOXD2_NYWANGTAAACAN_eDBD_repr-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-slp2 5 0.356489 8717.24 1 6 CACCTG TTGTTTACTTAAC - +4 taipale_cyt_meth__FOXI1_NWWNYGTAAACAN_eDBD_meth-bin-bs-CHES-1-like-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.356489 8717.24 1 6 CACCTG TTGTTTACATTAT - +4 taipale_cyt_meth__ZBTB18_NWTCCAGATGTKN_eDBD 3 0.356489 8717.24 1 6 CACCTG GAACATCTGGAAT - +4 transfac_pro__M09051 6 0.356489 8717.24 1 6 CACCTG TTCGCCGACATCA - +4 transfac_pro__M01747-Bdp1-Brf-CG17209-Hsf-SREBP 8 0.356489 8717.24 1 5 CACCTG GGGATTCGAACCC - +4 neph__UW.Motif.0156 -3 0.356489 8717.24 1 3 CACCTG CTGAGAAATGCAG - +4 homer__RACAGCTGTTBH_HLH-1-HLH54F-ac-amos-ase-dimm-l(1)sc-nau-sage-sc 2 0.356639 8720.9 1 6 CACCTG AACAGCTGTTGT + +4 swissregulon__hs__TEAD1.p2-sd 4 0.356639 8720.9 1 6 CACCTG CACATTCCTCGG + +4 taipale_cyt_meth__ATF6B_TGCCACGTCAYN_eDBD_meth_repr-Atf6-CrebA-Xbp1 3 0.356639 8720.9 1 6 CACCTG TGCCACGTCACC + +4 taipale_cyt_meth__JUND_NRTGACGTCATN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.356639 8720.9 1 6 CACCTG GGTGACGTCATC + +4 taipale_cyt_meth__MYOG_NAACANNTGTYN_eDBD-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.356639 8720.9 1 6 CACCTG GAACAGCTGTTG + +4 taipale_cyt_meth__MYOG_NAACANNTGTYN_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.356639 8720.9 1 6 CACCTG GAACAGCTGTTG + +4 transfac_pro__M05826 5 0.356639 8720.9 1 6 CACCTG GTCTTCAACTAA + +4 cisbp__M3642-Max-Mnt-Myc 3 0.356639 8720.9 1 6 CACCTG GGACACGTGGGA - +4 cisbp__M5663-CG7786-crc-gt-hng1-Irbp18-Pdp1-slbo-vri 3 0.356639 8720.9 1 6 CACCTG TATTACATAACA - +4 fantom__motif120_TTSMTGNNGKTG 4 0.356639 8720.9 1 6 CACCTG CAACATCATCAA - +4 homer__ACCACGTGGTCN_Max-Clk-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-cyc-emc 4 0.356639 8720.9 1 6 CACCTG AGACCACGTGGT - +4 homer__GKVTCADRTTWC_Six1-CG4730-CG7101-Six4-so 2 0.356639 8720.9 1 6 CACCTG GTAACCTGATCC - +4 taipale_cyt_meth__ZNF704_NRCCGGCCGGYN_FL_meth_repr-Glut4EF 0 0.356639 8720.9 1 6 CACCTG CGCCGGCCGGCG - +4 taipale_tf_pairs__ETV5_FOXI1_RSCGGATGTTGN_CAP-Ets96B 2 0.356639 8720.9 1 6 CACCTG ACAACATCCGGC - +4 transfac_pro__M05606 6 0.356639 8720.9 1 6 CACCTG GCGGCTGGCCTG - +4 transfac_pro__M06044 4 0.356639 8720.9 1 6 CACCTG TCATTACCCCCG - +4 transfac_pro__M06298 6 0.356639 8720.9 1 6 CACCTG TATGCCCACCAA - +4 transfac_pro__M06692 5 0.356639 8720.9 1 6 CACCTG CCGGAAACCCAA - +4 transfac_pro__M07417-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 4 0.356639 8720.9 1 6 CACCTG CCACTTCCTGCC - +4 transfac_pro__M07700-aop-Eip74EF-Ets21C-Ets96B 0 0.356639 8720.9 1 6 CACCTG TACTTCCGGGTT - +4 transfac_pro__M05657 -1 0.356639 8720.9 1 5 CACCTG TCCTCGGGGATA + +4 hocomoco__MEIS1_MOUSE.H11MO.1.A-H15-mid -1 0.356639 8720.9 1 5 CACCTG AGCTGTCAGCAC - +4 transfac_pro__M05618-CG2120 7 0.356639 8720.9 1 5 CACCTG TATTTTTTACCG - +4 transfac_pro__M05987 7 0.356639 8720.9 1 5 CACCTG TCTTATCGACCA - +4 transfac_pro__M06054 7 0.356639 8720.9 1 5 CACCTG TGGTCCTCACCA - +4 transfac_pro__M06084 -1 0.356639 8720.9 1 5 CACCTG ACCCCTTCCCCG - +4 transfac_pro__M06218 7 0.356639 8720.9 1 5 CACCTG TATTCTGAACCC - +4 transfac_pro__M06228 7 0.356639 8720.9 1 5 CACCTG TCCCACATACCA - +4 yetfasco__YIL131C_2002-FoxK-FoxP-fd59A-fkh-foxo-slp2 7 0.356639 8720.9 1 5 CACCTG GCTTGTTTACAT - +4 transfac_pro__M05907 -2 0.356639 8720.9 1 4 CACCTG CCTACGTCTCTC - +4 tfdimers__MD00554-ct-nej 21 0.357112 8732.46 1 6 CACCTG TTCTTCACTCAATCCCTTAATCACCTGAAATTT - +4 cisbp__M1368 1 0.359638 8794.23 1 6 CACCTG AGCCCTAA + +4 cisbp__M1737 2 0.359638 8794.23 1 6 CACCTG TTTTCCGG + +4 jaspar__MA1013.1 2 0.359638 8794.23 1 6 CACCTG TAGATCTG + +4 predrem__nrMotif2426 2 0.359638 8794.23 1 6 CACCTG ATCACTTG + +4 predrem__nrMotif2609 2 0.359638 8794.23 1 6 CACCTG CCTAACTC + +4 taipale_cyt_meth__PRRX2_NTCGTTAN_eDBD_meth 0 0.359638 8794.23 1 6 CACCTG CTCGTTAG + +4 transfac_pro__M01182-CG17829 2 0.359638 8794.23 1 6 CACCTG CGGACGTT + +4 cisbp__M2589-ttk 1 0.359638 8794.23 1 6 CACCTG GGTCCTGC - +4 homer__GGCVGTTR_MYB 0 0.359638 8794.23 1 6 CACCTG TAACCGCC - +4 jaspar__MA0018.2-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-crc-kay 1 0.359638 8794.23 1 6 CACCTG TGACGTCA - +4 predrem__nrMotif774 0 0.359638 8794.23 1 6 CACCTG TGCCTTTA - +4 transfac_pro__M00743-bs-Ets96B-Ets97D 2 0.359638 8794.23 1 6 CACCTG GCTTCCTG - +4 transfac_pro__M03847 0 0.359638 8794.23 1 6 CACCTG CCCTTTGT - +4 predrem__nrMotif2321 3 0.359638 8794.23 1 5 CACCTG TCCAATCT + +4 predrem__nrMotif298 3 0.359638 8794.23 1 5 CACCTG AAGCAATT + +4 predrem__nrMotif695 3 0.359638 8794.23 1 5 CACCTG AAACACCC + +4 transfac_pro__M08803-Atf6-CrebA-CrebB-Jra-kay-Xbp1 3 0.359638 8794.23 1 5 CACCTG GATGACGT + +4 transfac_pro__M01251-E2f1 -1 0.359638 8794.23 1 5 CACCTG ACGTTTCG - +4 transfac_pro__M04808-Hnf4 3 0.359638 8794.23 1 5 CACCTG CTGGACTT - +4 taipale__MEIS2_DBD_TTGACAGS_repr-hth -2 0.359638 8794.23 1 4 CACCTG GCTGTCAA - +4 cisbp__M0225-Max-Mitf-Usf 2 0.360915 8825.46 1 6 CACCTG ATCACGTGGT + +4 cisbp__M0242-Max-Myc 2 0.360915 8825.46 1 6 CACCTG CCCACGTGCT + +4 cisbp__M0280 3 0.360915 8825.46 1 6 CACCTG GCTTACGTAA + +4 cisbp__M0859-Optix-so 4 0.360915 8825.46 1 6 CACCTG TTGATACCCT + +4 cisbp__M0872-achi-esg-sna-vis-wor 3 0.360915 8825.46 1 6 CACCTG TTTGACAGGT + +4 cisbp__M1137-achi-hth-vis 1 0.360915 8825.46 1 6 CACCTG TTACATGTAA + +4 cisbp__M1785 3 0.360915 8825.46 1 6 CACCTG TATCTCCGTT + +4 cisbp__M1798 4 0.360915 8825.46 1 6 CACCTG ATTTTCCCGA + +4 cisbp__M1951-CG17829 3 0.360915 8825.46 1 6 CACCTG GCGGACGTTA + +4 cisbp__M5309-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG GTCACGTGAC + +4 cisbp__M6053-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG ATCACGTGAT + +4 fantom__motif114_AAACCCGCTC 1 0.360915 8825.46 1 6 CACCTG AAACCCGCTC + +4 predrem__nrMotif509 3 0.360915 8825.46 1 6 CACCTG TTTGACTTAA + +4 taipale__BHLHE41_full_GTCACGTGAC-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG GTCACGTGAC + +4 taipale__Mlx_DBD_ATCACGTGAT-bigmax-Mitf-Mondo-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG ATCACGTGAT + +4 taipale_cyt_meth__BHLHE41_GTCACGTGAC_eDBD-bigmax-Clk-cnc-cwo-cyc-Mitf-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG GTCACGTGAC + +4 taipale_cyt_meth__BHLHE41_GTCACGTGAC_eDBD_meth-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.360915 8825.46 1 6 CACCTG GTCACGTGAC + +4 taipale_cyt_meth__NPAS2_NMCACGTGYN_eDBD-Clk-Met 2 0.360915 8825.46 1 6 CACCTG GACACGTGTA + +4 transfac_pro__M07559 3 0.360915 8825.46 1 6 CACCTG TTAGATCTAC + +4 transfac_pro__M07692-CG7786-gt-hng1-kay-Pdp1-REPTOR-BP-vri 2 0.360915 8825.46 1 6 CACCTG GTTACGTAAC + +4 transfac_pro__M09560 2 0.360915 8825.46 1 6 CACCTG AGCACGTGCC + +4 transfac_public__M00228-CG7786-gt-Pdp1-REPTOR-BP-vri 2 0.360915 8825.46 1 6 CACCTG GTTACGTAAT + +4 cisbp__M0136 3 0.360915 8825.46 1 6 CACCTG TTTTTCCTGT - +4 cisbp__M0275-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-crc-kay 1 0.360915 8825.46 1 6 CACCTG TGACGTCATC - +4 cisbp__M0430 3 0.360915 8825.46 1 6 CACCTG CCCCCCCACG - +4 cisbp__M0523 0 0.360915 8825.46 1 6 CACCTG CCCCCACTTT - +4 cisbp__M0687-aop-Atac3-Eip74EF-Ets65A-Ets96B-Ets97D-Ets98B-Rpn5 2 0.360915 8825.46 1 6 CACCTG ACTTCCGGGT - +4 cisbp__M0690-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.360915 8825.46 1 6 CACCTG ACTTCCGGTC - +4 cisbp__M0769 2 0.360915 8825.46 1 6 CACCTG CAGATCTAGA - +4 cisbp__M1328 4 0.360915 8825.46 1 6 CACCTG GGGGAATCTA - +4 cisbp__M4088-CG7786-gt-Pdp1-REPTOR-BP-vri 2 0.360915 8825.46 1 6 CACCTG GTTACGTAAT - +4 cisbp__M4949-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn 1 0.360915 8825.46 1 6 CACCTG GCACGTGCCA - +4 cisbp__M6267-lmd-sug 0 0.360915 8825.46 1 6 CACCTG GACCCCCCAC - +4 predrem__nrMotif1885 4 0.360915 8825.46 1 6 CACCTG AGACCAGCAG - +4 predrem__nrMotif524 2 0.360915 8825.46 1 6 CACCTG TTCACCATCA - +4 scertf__macisaac.HAC1 0 0.360915 8825.46 1 6 CACCTG TACGTGTCCT - +4 scertf__morozov.MET28-Atf6-CrebB-Jra 2 0.360915 8825.46 1 6 CACCTG GTGACGTCAA - +4 taipale_cyt_meth__GATA5_NWGATAASRN_FL_repr-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp 4 0.360915 8825.46 1 6 CACCTG TCCTTATCTG - +4 transfac_pro__M05311-btd-cbt-Sp1-Spps 0 0.360915 8825.46 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M07583 2 0.360915 8825.46 1 6 CACCTG ATTGCGTGTC - +4 yetfasco__YPL248C_2206 4 0.360915 8825.46 1 6 CACCTG AGACCTCCGA - +4 cisbp__M5401-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.360915 8825.46 1 5 CACCTG ACCGGAAGTG + +4 taipale__ERG_full_ACCGGAARTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.360915 8825.46 1 5 CACCTG ACCGGAAGTG + +4 cisbp__M1300-bs -1 0.360915 8825.46 1 5 CACCTG TCCCTATTCG - +4 cisbp__M1688 5 0.360915 8825.46 1 5 CACCTG GTGTTGACTT - +4 jaspar__MA1076.1 5 0.360915 8825.46 1 5 CACCTG GCGTTGACCT - +4 predrem__nrMotif2307 -1 0.360915 8825.46 1 5 CACCTG TGCTGGCCAC - +4 taipale_cyt_meth__SIX4_NCGTATCATN_eDBD-Optix-Six4-so 5 0.360915 8825.46 1 5 CACCTG AATGATACGG - +4 transfac_pro__M03178 -1 0.360915 8825.46 1 5 CACCTG ACCTCGGTCG - +4 cisbp__M1266 6 0.360915 8825.46 1 4 CACCTG GACCGAAACC + +4 cisbp__M1532-CG9727-Rfx 6 0.360915 8825.46 1 4 CACCTG CTTAGCAACG + +4 predrem__nrMotif1064 6 0.360915 8825.46 1 4 CACCTG TCTGTGCACT + +4 predrem__nrMotif1324 -2 0.360915 8825.46 1 4 CACCTG CCTGGGTCAG + +4 taipale__AR_full_RRGWACANNNTGTWCYY 3 0.36145 8838.54 1 6 CACCTG GGGAACACGGTGTACCC + +4 taipale__NR3C1_DBD_NRGWACANNNTGTWCYN-fkh 3 0.36145 8838.54 1 6 CACCTG GGGTACATAATGTTCCC + +4 taipale_cyt_meth__GMEB1_NKACGTANNNTACGTMN_FL 10 0.36145 8838.54 1 6 CACCTG TTACGTAAATTACGTAA + +4 taipale_tf_pairs__TEAD4_DLX3_RCATTCCNNNNTAATKR_CAP-sd 3 0.36145 8838.54 1 6 CACCTG GCATTCCACGGTAATTG + +4 cisbp__M5613-Max 0 0.36145 8838.54 1 6 CACCTG CACGTGCTAACCACGTG - +4 cisbp__M6224-aop 4 0.36145 8838.54 1 6 CACCTG GTGTTACTTCCTGTGGC - +4 homer__GGGRAARRGRMCAGMTG_RBPJ_Ebox-Fer1-Su(H) 0 0.36145 8838.54 1 6 CACCTG CAGCTGGCCCTTTTCCC - +4 taipale_cyt_meth__POU3F2_TAATKANNNNNTAATKA_eDBD_meth_repr-vvl 7 0.36145 8838.54 1 6 CACCTG TAATTAGCACCTCATTA - +4 transfac_pro__M00442-cnc-CrebA-Max-Myc-Usf 6 0.36145 8838.54 1 6 CACCTG TCGTGCCACGTGTCCCC - +4 transfac_pro__M02852-ERR-usp 8 0.36145 8838.54 1 6 CACCTG GCCCTTGACCCCTCGCC - +4 yetfasco__YMR075W_1066-bon 0 0.361519 8840.23 1 6 CACCTG AATTTGT + +4 cisbp__M1908 0 0.361519 8840.23 1 6 CACCTG TTCCTCT - +4 elemento__AACGTGA 1 0.361519 8840.23 1 6 CACCTG TCACGTT - +4 elemento__AACGTGC 1 0.361519 8840.23 1 6 CACCTG GCACGTT - +4 jaspar__MA0081.1 0 0.361519 8840.23 1 6 CACCTG TTCCTCT - +4 transfac_pro__M01776-Hr78 0 0.361519 8840.23 1 6 CACCTG TTCCTGG - +4 elemento__ACATATG-amos-Oli-tap -1 0.361519 8840.23 1 5 CACCTG ACATATG + +4 predrem__nrMotif1086 -1 0.361519 8840.23 1 5 CACCTG AACTCAG + +4 predrem__nrMotif582 -1 0.361519 8840.23 1 5 CACCTG GCCTCAG + +4 transfac_pro__M07355 2 0.361519 8840.23 1 5 CACCTG AGAACAG + +4 predrem__nrMotif1482 4 0.361519 8840.23 1 3 CACCTG TGTTTAC + +4 taipale_tf_pairs__E2F1_NHLH1_SGCGCCNNNNNNNNNNNNCAGCTGNN_CAP_repr-E2f1-HLH4C 18 0.362856 8872.92 1 6 CACCTG GGCGCCATAACGGGGCCGCAGCTGCG + +4 cisbp__M4514-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 3 0.363055 8877.79 1 6 CACCTG GGTCACGTGGCCGCG + +4 neph__UW.Motif.0385 2 0.363055 8877.79 1 6 CACCTG AGTGCCTGGGAGGAG + +4 taipale_cyt_meth__GLIS1_NACCCCCCACGWMGN_eDBD-ci-lmd-sug 0 0.363055 8877.79 1 6 CACCTG CACCCCCCACGACGC + +4 taipale_cyt_meth__ZNF449_NTCGCGNGCMARCAN_eDBD 9 0.363055 8877.79 1 6 CACCTG GTCGCGAGCCAGCAG + +4 hocomoco__EHF_HUMAN.H11MO.0.B-Eip74EF-Ets96B-pnt 5 0.363055 8877.79 1 6 CACCTG GCCACTTCCTGGTTC - +4 jaspar__MA0484.1-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-nej-svp-usp 9 0.363055 8877.79 1 6 CACCTG TGGACTTTGGACTCT - +4 neph__UW.Motif.0522 5 0.363055 8877.79 1 6 CACCTG AAAATTTCCACATTT - +4 taipale_tf_pairs__ELK1_FOXI1_RSCGGAANRTMAAYA_CAP_repr 8 0.363055 8877.79 1 6 CACCTG TGTTTACGTTCCGGT - +4 factorbook__NFKB1-CG12018-Dif-Rel-dl-shn 10 0.363055 8877.79 1 5 CACCTG CCTTGGAAATCCCCT - +4 transfac_pro__M05287 -1 0.363055 8877.79 1 5 CACCTG ACGTCCCGCTGTTAA - +4 neph__UW.Motif.0136 11 0.363055 8877.79 1 4 CACCTG ATGGGGACGGGGGCC + +4 neph__UW.Motif.0555 11 0.363055 8877.79 1 4 CACCTG GCTCTGGCTCACAGC + +4 factorbook__RFX5 -2 0.363055 8877.79 1 4 CACCTG CCTAGCAACAGGTGA - +4 neph__UW.Motif.0568 -3 0.363055 8877.79 1 3 CACCTG CTGGGCTTTTTTTTC + +4 c2h2_zfs__M0522 0 0.363497 8888.6 1 6 CACCTG TCCCGAAAC + +4 cisbp__M1778 3 0.363497 8888.6 1 6 CACCTG AAATTCCGT + +4 cisbp__M1817 0 0.363497 8888.6 1 6 CACCTG TTCCGGGCA + +4 flyfactorsurvey__ttk-PA_SANGER_5_FBgn0003870-ttk 1 0.363497 8888.6 1 6 CACCTG CAACCCCTA + +4 predrem__nrMotif1077 1 0.363497 8888.6 1 6 CACCTG CCAGCTTTG + +4 predrem__nrMotif1343 2 0.363497 8888.6 1 6 CACCTG GTCCCCTGC + +4 predrem__nrMotif2151 2 0.363497 8888.6 1 6 CACCTG AAATCCTCT + +4 predrem__nrMotif577 3 0.363497 8888.6 1 6 CACCTG CAAGACCCA + +4 predrem__nrMotif611 0 0.363497 8888.6 1 6 CACCTG CAACTTCCC + +4 stark__GNMCTTGAA 1 0.363497 8888.6 1 6 CACCTG GAACTTGAA + +4 swissregulon__hs__MYBL2.p2 0 0.363497 8888.6 1 6 CACCTG TAACTGTTT + +4 transfac_pro__M04729-kn 0 0.363497 8888.6 1 6 CACCTG TCCCCGGGG + +4 transfac_pro__M05961-CG31612 1 0.363497 8888.6 1 6 CACCTG CAACATGGA + +4 fantom__motif36_AAGGAGRAN 3 0.363497 8888.6 1 6 CACCTG CTTCTCCTT - +4 predrem__nrMotif1877 2 0.363497 8888.6 1 6 CACCTG GTGACATCA - +4 predrem__nrMotif2579 0 0.363497 8888.6 1 6 CACCTG CACCCTCAT - +4 predrem__nrMotif675 2 0.363497 8888.6 1 6 CACCTG TTCAGCTTT - +4 predrem__nrMotif700 0 0.363497 8888.6 1 6 CACCTG TTCCTTGCA - +4 predrem__nrMotif852 2 0.363497 8888.6 1 6 CACCTG CGCTCCTCC - +4 transfac_pro__M09543 3 0.363497 8888.6 1 6 CACCTG CCTTATCCT - +4 predrem__nrMotif2206 -1 0.363497 8888.6 1 5 CACCTG ATCTGCCCA + +4 transfac_pro__M04763-CTCF-SMC3-usp-vtd 4 0.363497 8888.6 1 5 CACCTG GCGCCCCCT + +4 cisbp__M1559 4 0.363497 8888.6 1 5 CACCTG TCCGTACAA - +4 cisbp__M5782 4 0.363497 8888.6 1 5 CACCTG GGATTATCC - +4 fantom__motif132_TCRCCAGWY -1 0.363497 8888.6 1 5 CACCTG GACTGGTGA - +4 predrem__nrMotif661 -1 0.363497 8888.6 1 5 CACCTG ACATAGAAA - +4 predrem__nrMotif1712 -2 0.363497 8888.6 1 4 CACCTG CCTGAAGCA + +4 predrem__nrMotif622 5 0.363497 8888.6 1 4 CACCTG TTTGCCACA + +4 predrem__nrMotif856 5 0.363497 8888.6 1 4 CACCTG TTGTCCACA + +4 predrem__nrMotif1750 -2 0.363497 8888.6 1 4 CACCTG CCTTGGGGG - +4 predrem__nrMotif602 5 0.363497 8888.6 1 4 CACCTG CTGACCACA - +4 bergman__Hr46-Hr3 1 0.365612 8940.31 1 5 CACCTG TGACCC - +4 transfac_pro__M06528 0 0.365866 8946.53 1 6 CACCTG GACCTAACGATCACACCC - +4 tfdimers__MD00501-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Tsf1-Tsf2-Tsf3-Usf 6 0.366175 8954.09 1 6 CACCTG AGCTGCCACCTGTCACTTGCTCTCT + +4 tfdimers__MD00405 11 0.366175 8954.09 1 6 CACCTG AAAAAAAGTGAAACTTTTATATAAT - +4 tfdimers__MD00072-ara-caup-mirr 16 0.366559 8963.47 1 6 CACCTG AATTTAGACATGTCTGAACATGTAAAAAATAATA - +4 hdpi__RBM7-CG11454 0 0.367293 8981.41 1 5 CACCTG CTCCT - +4 hdpi__BAD 2 0.367293 8981.41 1 3 CACCTG GCAAC + +4 cisbp__M0342-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-crc-kay 4 0.368137 9002.06 1 6 CACCTG GGATGACGTCA + +4 cisbp__M6464-Smox 5 0.368137 9002.06 1 6 CACCTG GTGTCCGTCTG + +4 tiffin__TIFDMEM0000056 3 0.368137 9002.06 1 6 CACCTG AATAAACATAT + +4 cisbp__M4811-btd-cbt-CG3065-CG42741-dar1-luna-Spps 4 0.368137 9002.06 1 6 CACCTG GCCACACCCAC - +4 flyfactorsurvey__HLHm5_SANGER_5_FBgn0002631-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 3 0.368137 9002.06 1 6 CACCTG TGGCACGTGCC - +4 taipale__ELF5_DBD_ACCCGGAAGTN-aop-Eip74EF-Ets96B-Ets98B-Hr78 0 0.368137 9002.06 1 6 CACCTG TACTTCCGGGT - +4 taipale_cyt_meth__TFEB_NNCACGTGAYN_eDBD-bigmax-cnc-Mitf-Usf 3 0.368137 9002.06 1 6 CACCTG GGTCACGTGCG - +4 transfac_pro__M05501 5 0.368137 9002.06 1 6 CACCTG CCTATCCCCTG - +4 transfac_pro__M06390-CG2120 0 0.368137 9002.06 1 6 CACCTG TATCTCAGAAT - +4 transfac_pro__M07089-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-lz-pnt-run-RunxA-RunxB 4 0.368137 9002.06 1 6 CACCTG CCACTTCCTGT - +4 transfac_pro__M09199 1 0.368137 9002.06 1 6 CACCTG GAATCTTTGAT - +4 transfac_pro__M09540-achi-hth-vis 3 0.368137 9002.06 1 6 CACCTG TGCCAGCTGTA - +4 cisbp__M4346 7 0.368137 9002.06 1 4 CACCTG CCGATATTTCC + +4 scertf__spivak.HAP1 7 0.368137 9002.06 1 4 CACCTG CCGATATTTCC - +4 transfac_pro__M07907-YL-1 7 0.368137 9002.06 1 4 CACCTG CGGCGACCACC - +4 cisbp__M2343-CrebA 4 0.368439 9009.45 1 6 CACCTG AAGCCACGTGTCCA + +4 cisbp__M4080-bigmax-Max-Mitf-Myc-SREBP-tgo-Usf 4 0.368439 9009.45 1 6 CACCTG AGATCACGTGATCT + +4 cisbp__M6057-tll 1 0.368439 9009.45 1 6 CACCTG TGACTTATTGACTT + +4 cisbp__M6229-cnc-ewg-kay-maf-S 8 0.368439 9009.45 1 6 CACCTG TGCTGAGTCACGTT + +4 cisbp__M6391-Hr51-svp-tll-usp 8 0.368439 9009.45 1 6 CACCTG TGACTTTTGACTTT + +4 jaspar__MA0550.1-CrebA 4 0.368439 9009.45 1 6 CACCTG AAGCCACGTGTCCA + +4 neph__UW.Motif.0372 8 0.368439 9009.45 1 6 CACCTG CAAATGACTTTCTG + +4 neph__UW.Motif.0562 3 0.368439 9009.45 1 6 CACCTG AATTCCTTTTTCTG + +4 neph__UW.Motif.0653 6 0.368439 9009.45 1 6 CACCTG AAATTTTTCATTCA + +4 taipale_cyt_meth__ZNF282_NTTCCCMYNACACN_eDBD 8 0.368439 9009.45 1 6 CACCTG TTTCCCACAACACG + +4 transfac_pro__M02925-TfAP-2 1 0.368439 9009.45 1 6 CACCTG CCGCCCAAGGGCAG + +4 hocomoco__NR2E3_HUMAN.H11MO.0.C-Hr51-svp-tll 8 0.368439 9009.45 1 6 CACCTG TGACTTTTGACTTT - +4 neph__UW.Motif.0291 1 0.368439 9009.45 1 6 CACCTG TCAGCAGAGATCTG - +4 swissregulon__hs__EP300.p2-nej 7 0.368439 9009.45 1 6 CACCTG CGCTCACTCCCTGC - +4 transfac_pro__M07654-Fer1-HLH54F-nau 4 0.368439 9009.45 1 6 CACCTG ACAACAGCTGACGC - +4 transfac_public__M00467 1 0.368439 9009.45 1 6 CACCTG GCACCCTTGGGTGC - +4 transfac_pro__M06936-maf-S 9 0.368439 9009.45 1 5 CACCTG CGATACTTAAACCA + +4 transfac_pro__M06991-maf-S 9 0.368439 9009.45 1 5 CACCTG GGTTTATTAAACCA + +4 neph__UW.Motif.0203 9 0.368439 9009.45 1 5 CACCTG GAAGCCAGTTTTCT - +4 tfdimers__MD00408-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-sens-2 13 0.368792 9018.07 1 6 CACCTG ATTATTCAAATCCTTCCTCATCCC + +4 tfdimers__MD00425-Med 8 0.368792 9018.07 1 6 CACCTG TTTCCTACTTCCTGTCTGTTTTTT - +4 tfdimers__MD00571 7 0.37054 9060.81 1 6 CACCTG TTTTTACTTCCTCATTTTATTATATTTTTTT - +4 taipale_tf_pairs__CUX1_RFX5_RATCRATNNNNNNNNNNRGYAAC_CAP_repr-ct 12 0.370641 9063.29 1 6 CACCTG GATCGATAGGCGTGCATAGCAAC + +4 taipale_tf_pairs__ETV2_TEF_TTACGTNNNNNNNNNCCGGAANN_CAP_repr-CG7786-gt-Pdp1-pnt 13 0.370641 9063.29 1 6 CACCTG TTACGTAACCACGTACCGGAAGT + +4 tfdimers__MD00039-GATAe-grn-pnr-srp 11 0.370641 9063.29 1 6 CACCTG AAAAAAGATAAGATCTTTTAATA - +4 tfdimers__MD00521-Taf7-Tbp 13 0.370641 9063.29 1 6 CACCTG AAAAAAAAAAAATTCCCAAAAAT - +4 transfac_pro__M00312-Fer1-nau 0 0.370699 9064.71 1 6 CACCTG AAACTGCTGACGCTGCGGGTACTTCCCA + +4 tfdimers__MD00401-ci 14 0.370699 9064.71 1 6 CACCTG TCCACACCACCCACTTCCTGTCCCCCTT - +4 tfdimers__MD00496-lz-run-RunxA-RunxB 11 0.370699 9064.71 1 6 CACCTG TTTTCCCACACCATCTGTCACTGCTTCA - +4 homer__AGAACAGNCTGTTCTT_ARE-fkh 2 0.370772 9066.48 1 6 CACCTG AGAACAGTCTGTTCTT + +4 homer__NAGAACAGNCTGTTCT_GRE-Hsf-fkh 3 0.370772 9066.48 1 6 CACCTG GAGAACAGTCTGTTCT + +4 neph__UW.Motif.0632 3 0.370772 9066.48 1 6 CACCTG AAAAAGCACAGTCTGG + +4 neph__UW.Motif.0673 4 0.370772 9066.48 1 6 CACCTG CATGATTCATTTTTTC + +4 taipale_cyt_meth__MAFF_NYGCTGAYRTCAGCRN_eDBD_repr-CrebA-CrebB-maf-S 5 0.370772 9066.48 1 6 CACCTG TTGCTGACGTCAGCAA + +4 transfac_pro__M07647-HLH4C 5 0.370772 9066.48 1 6 CACCTG GGCATCAGCTGCGTCC + +4 cisbp__M3294-bin-fd59A-FoxL1-foxo-FoxP-slp1-slp2 8 0.370772 9066.48 1 6 CACCTG GGATTGTTTACGTTTG - +4 neph__UW.Motif.0450 7 0.370772 9066.48 1 6 CACCTG GCTGCCTTTTCTCTCT - +4 transfac_pro__M01329-Abd-B 9 0.370772 9066.48 1 6 CACCTG CTATTTTACGACTTTA - +4 transfac_pro__M01378-Abd-B 9 0.370772 9066.48 1 6 CACCTG ATGTTTTACGACTTTA - +4 transfac_pro__M01464-cad 10 0.370772 9066.48 1 6 CACCTG TGAATTTTATTACCTA - +4 transfac_pro__M03814-Brf-brm-btd-CG42741-CTCF-dar1-ERR-kay-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-Sp1-Spps-Stat92E 9 0.370772 9066.48 1 6 CACCTG CGGCCCCGCCCCCTGC - +4 transfac_public__M00010 0 0.370772 9066.48 1 6 CACCTG TATCTACGTGGAATGA - +4 transfac_public__M00290-bin-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 8 0.370772 9066.48 1 6 CACCTG GGATTGTTTACGTTTG - +4 neph__UW.Motif.0646 11 0.370772 9066.48 1 5 CACCTG AAAAATTTTGCCATTT + +4 neph__UW.Motif.0431 12 0.370772 9066.48 1 4 CACCTG TGGAAAAACTGATTCC - +4 dbcorrdb__BRCA1__ENCSR000EDB_1__m1-Chd1-CoRest-CrebB 12 0.370919 9070.08 1 6 CACCTG CAGCTCTCGCGTCACCTGGG + +4 dbcorrdb__BRF2__ENCSR000DNV_1__m3 12 0.370919 9070.08 1 6 CACCTG TCTCTTTCGTTCAAACTGTA + +4 dbcorrdb__HDAC1__ENCSR000AQF_1__m1-HDAC1-Max-Myc-Sap30 13 0.370919 9070.08 1 6 CACCTG GCCCGTCGGAAACCACGTGG + +4 dbcorrdb__MXI1__ENCSR000EIA_1__m1-E2f1-Max-Mnt-Myc-Sap30-Usf 10 0.370919 9070.08 1 6 CACCTG GCCCCGGCACCACGTGGCTG + +4 dbcorrdb__PRDM1__ENCSR000ECY_1__m1-Blimp-1-Stat92E 0 0.370919 9070.08 1 6 CACCTG CACTTTCACTTTTTTTTTTT + +4 dbcorrdb__SAP30__ENCSR000AQJ_1__m2-Clk-cyc-E2f1-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-HDAC1-Hey-Max-Mitf-Mnt-Mondo-Myc-Sap30-Usf 5 0.370919 9070.08 1 6 CACCTG GCCCCCACGTGGTCCCGGAG + +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m5-egg 0 0.370919 9070.08 1 6 CACCTG CTGCTTTGCCCTTGCAGAGC + +4 dbcorrdb__TAF7__ENCSR000BLU_1__m1-lid-pho-phol-RpII215-Taf1-Taf7 11 0.370919 9070.08 1 6 CACCTG CGCGCCGCCGCCATCTTGCG + +4 hocomoco__HEN1_HUMAN.H11MO.0.C-HLH4C 7 0.370919 9070.08 1 6 CACCTG TGGGGAGCAGCTGCGTCCCT + +4 transfac_pro__M01570-GATAd-GATAe-grn-pnr-srp 4 0.370919 9070.08 1 6 CACCTG CCATTTCCTTATCGGGTTTA + +4 dbcorrdb__BRF1__ENCSR000DOJ_1__m1-Bdp1-Brf-CG17209-ebi-Tbp 11 0.370919 9070.08 1 6 CACCTG AACCACTGGGCCACCGAGCC - +4 dbcorrdb__EP300__ENCSR000AQB_1__m2-nej 6 0.370919 9070.08 1 6 CACCTG GAGAGAGACCAGCGCGTAGT - +4 dbcorrdb__HNF4A__ENCSR000EEU_1__m2-btd-EcR-HDAC1-Hnf4-nej-Spps-svp 13 0.370919 9070.08 1 6 CACCTG CACCTGGACTTTGGACTCTG - +4 dbcorrdb__NR3C1__ENCSR000BHE_1__m2 6 0.370919 9070.08 1 6 CACCTG CCTTCGGTCCTGTTTGCAAA - +4 dbcorrdb__NR3C1__ENCSR000BJC_1__m2 5 0.370919 9070.08 1 6 CACCTG CAGGGAACATTCCTTGCCTT - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m1-RpII215 2 0.370919 9070.08 1 6 CACCTG GTTCCCTTGGGAGTTGAGGA - +4 dbcorrdb__TCF7L2__ENCSR000EUV_1__m1-pan 4 0.370919 9070.08 1 6 CACCTG CCGGTCCCTTTGATGTCGCC - +4 dbcorrdb__TCF7L2__ENCSR000EVF_1__m1-pan 7 0.370919 9070.08 1 6 CACCTG GCGGCGTTTCCTTTGATGTT - +4 taipale_cyt_meth__ETS2_NACCGGANNNNNNTCCGGTN_FL-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.370919 9070.08 1 6 CACCTG GACCGGAAGTACTTCCGGTC - +4 taipale_tf_pairs__ETV5_HES7_NNCACGTGNNNNCCGGAANN_CAP-Ets96B 2 0.370919 9070.08 1 6 CACCTG CCTTCCGGTCGGCGCGTGCC - +4 tfdimers__MD00407-EcR-pho-phol-usp 10 0.370919 9070.08 1 6 CACCTG TATTCCCATTGACCTTACCC - +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m6-egg 15 0.370919 9070.08 1 5 CACCTG TAATGAATGTGGGAAAGCCT + +4 hocomoco__USF1_MOUSE.H11MO.0.A-Max-Mitf-Myc-SREBP-Usf-cnc-cyc-tgo 4 0.371371 9081.13 1 6 CACCTG GGGTCACGTGACC + +4 neph__UW.Motif.0261 4 0.371371 9081.13 1 6 CACCTG ATTTTTCCTTTCA + +4 taipale_cyt_meth__DMRT3_NWWTTGNTACATT_eDBD-dmrt11E-dmrt93B-dmrt99B-dsx 7 0.371371 9081.13 1 6 CACCTG AAATTGATACATT + +4 transfac_pro__M09460 6 0.371371 9081.13 1 6 CACCTG AACGTTGACTATT + +4 cisbp__M4465-cnc-Max-Mitf-Myc-tgo-Usf 3 0.371371 9081.13 1 6 CACCTG GACCACGTGACTG - +4 cisbp__M5969 3 0.371371 9081.13 1 6 CACCTG GAACATCTGGATG - +4 neph__UW.Motif.0333 3 0.371371 9081.13 1 6 CACCTG TGTGTTTTTTGCA - +4 predrem__nrMotif2580-CTCF-SMC3-vtd 3 0.371371 9081.13 1 6 CACCTG TGCCATCTAGTGG - +4 scertf__zhu.ECM22 6 0.371371 9081.13 1 6 CACCTG TCCGGCCACCCGG - +4 stark__YSAAGGWCRCHRM-ftz-f1 5 0.371371 9081.13 1 6 CACCTG GCTGCGACCTTCA - +4 yetfasco__YBR049C_907 2 0.371371 9081.13 1 6 CACCTG GTTACCCGGATTG - +4 transfac_pro__M09440 8 0.371371 9081.13 1 5 CACCTG GTTGGGACCACAT + +4 cisbp__M5499-gem-grh 2 0.37143 9082.58 1 6 CACCTG AAAACCGGTTTT + +4 neph__UW.Motif.0100 6 0.37143 9082.58 1 6 CACCTG AGAAAATGCCAG + +4 taipale__NFIL3_DBD_NRTTACRTAAYN_repr-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.37143 9082.58 1 6 CACCTG TATTACATAACA + +4 taipale_cyt_meth__CREB3L4_YGCCACRTCAYN_eDBD_meth-Atf6-CrebA-Xbp1 3 0.37143 9082.58 1 6 CACCTG CGCCACGTCACC + +4 taipale_cyt_meth__KLF17_NGCCACRCCCWN_eDBD_meth-CG3065-CG42741-dar1-hkb-luna 6 0.37143 9082.58 1 6 CACCTG TGCCACGCCCTT + +4 taipale_cyt_meth__MYOG_NAACANNTGTYN_FL_meth-amos-dimm-Fer3-HLH54F-nau 3 0.37143 9082.58 1 6 CACCTG GAACAGCTGTTG + +4 transfac_pro__M00819 0 0.37143 9082.58 1 6 CACCTG CATGTGACAGGT + +4 transfac_pro__M01793-bigmax-Clk-cnc-cyc-Mitf-SREBP-tgo 3 0.37143 9082.58 1 6 CACCTG GGTCACGTGCTT + +4 transfac_pro__M06473 0 0.37143 9082.58 1 6 CACCTG AACTTGTAGTCA + +4 transfac_pro__M06482 2 0.37143 9082.58 1 6 CACCTG TGTTCCTGGCGA + +4 transfac_pro__M06757 2 0.37143 9082.58 1 6 CACCTG TGGGCATGCATC + +4 transfac_pro__M09480 6 0.37143 9082.58 1 6 CACCTG AGCGTTGACTTT + +4 hocomoco__ZNF41_HUMAN.H11MO.1.C 3 0.37143 9082.58 1 6 CACCTG TTCTCCCTTGTG - +4 idmmpmm__twi-twi 0 0.37143 9082.58 1 6 CACCTG AACATATGCGGG - +4 taipale__GRHL1_full_NAAACCGGTTTN-gem-grh 2 0.37143 9082.58 1 6 CACCTG AAAACCGGTTTT - +4 taipale_cyt_meth__CREM_NRTGAYGTCAYN_eDBD_meth-Atf3-Atf6-CrebB-Jra-Xbp1 3 0.37143 9082.58 1 6 CACCTG CGTGACATCACG - +4 taipale_cyt_meth__FOXD3_NYWAYRTAAACN_eDBD_repr-croc-fd59A-fkh 4 0.37143 9082.58 1 6 CACCTG TGTTTACGTAGG - +4 taipale_cyt_meth__FOXQ1_NTAYRTAAACAN_eDBD_meth-CHES-1-like-croc-fd59A-FoxK-foxo-FoxP-slp1 5 0.37143 9082.58 1 6 CACCTG TTGTTTACATAA - +4 taipale_cyt_meth__MSC_NRNCATATGNYN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.37143 9082.58 1 6 CACCTG CACCATATGGTG - +4 transfac_pro__M05619 6 0.37143 9082.58 1 6 CACCTG CATGTTAAACTA - +4 transfac_pro__M05920 2 0.37143 9082.58 1 6 CACCTG TCGACCGGATCG - +4 transfac_pro__M06176 6 0.37143 9082.58 1 6 CACCTG TCTTTATTCCTC - +4 transfac_pro__M06227 3 0.37143 9082.58 1 6 CACCTG AACCCCCTCCCA - +4 transfac_pro__M06439 1 0.37143 9082.58 1 6 CACCTG GTAGCTAACACG - +4 transfac_pro__M07455-ci-lmd-opa-sug 5 0.37143 9082.58 1 6 CACCTG ACGACCACCCAC - +4 transfac_pro__M05645 7 0.37143 9082.58 1 5 CACCTG TCTGCAGCATCT - +4 transfac_pro__M05938 7 0.37143 9082.58 1 5 CACCTG GCGGCCCAACCC - +4 transfac_pro__M06248 7 0.37143 9082.58 1 5 CACCTG TCTTTCTCACAG - +4 transfac_pro__M06388 7 0.37143 9082.58 1 5 CACCTG TCCCCTGTACCA - +4 transfac_pro__M06721 7 0.37143 9082.58 1 5 CACCTG GCGGCCCTACAT - +4 transfac_pro__M06896 7 0.37143 9082.58 1 5 CACCTG GCGTTTGCACCA - +4 cisbp__M5903-pan -2 0.37143 9082.58 1 4 CACCTG CCTTTGATCTTT - +4 taipale_tf_pairs__HOXB2_NHLH1_NYMATTANNNNNNNCAGCTGNN_CAP_repr-HLH4C-pb 2 0.371662 9088.25 1 6 CACCTG CGCAGCTGCGCCCGATAATTAA - +4 tfdimers__MD00257-CrebB-GATAe-grn-pnr-srp 7 0.371662 9088.25 1 6 CACCTG TATTTCTTATCTGTCATTTTTT - +4 taipale_tf_pairs__ETV2_RFX5_NCCGGAAGYNNCNTAGCAACS_CAP_repr-pnt 9 0.371781 9091.15 1 6 CACCTG ACCGGAAGCAGCATAGCAACG + +4 transfac_public__M00256-btd-CTCF-HDAC1-Sin3A-Spps 5 0.371781 9091.15 1 6 CACCTG TTCAGCACCACGGACAGCGCC + +4 cisbp__M3666-btd-CTCF-HDAC1-Sin3A-Spps 5 0.371781 9091.15 1 6 CACCTG TTCAGCACCACGGACAGCGCC - +4 transfac_pro__M09376 2 0.371781 9091.15 1 6 CACCTG GTTACTTGTTCTACACGTAAC - +4 cisbp__M1022-bcd-Gsc-oc-Ptx1 2 0.374225 9150.92 1 6 CACCTG TTAATCCC + +4 cisbp__M1755 1 0.374225 9150.92 1 6 CACCTG TTGCCGAA + +4 homer__AGGCCTAG_ZNF711 1 0.374225 9150.92 1 6 CACCTG AGGCCTAG + +4 taipale_cyt_meth__MEOX2_NTCGTTAN_FL-Antp-bsh-btn-Dfd-Dll-Dr-en-eve-exex-HGTX-ind-inv-lab-pb-Scr 0 0.374225 9150.92 1 6 CACCTG GTCATTAA + +4 transfac_public__M00345 0 0.374225 9150.92 1 6 CACCTG CAACCGCC + +4 cisbp__M0013 2 0.374225 9150.92 1 6 CACCTG GCAACATA - +4 cisbp__M0901 2 0.374225 9150.92 1 6 CACCTG TTGACAAG - +4 cisbp__M2763 0 0.374225 9150.92 1 6 CACCTG CAACCGAC - +4 hdpi__TRIM69 0 0.374225 9150.92 1 6 CACCTG CGCCTGCG - +4 transfac_pro__M00722-Bgb-Bro-CG9650-lz-nej-run-RunxA-RunxB 1 0.374225 9150.92 1 6 CACCTG AAACCACA - +4 transfac_public__M00039-achi-Atf3-Atf6-CrebA-CrebB-hth-Jra-kay-maf-S-REPTOR-BP-vis-Xbp1 1 0.374225 9150.92 1 6 CACCTG TGACGTCA - +4 elemento__ATCTTATC-ham -1 0.374225 9150.92 1 5 CACCTG ATCTTATC + +4 predrem__nrMotif2187 3 0.374225 9150.92 1 5 CACCTG CTGATCCT + +4 transfac_pro__M04933-Stat92E 3 0.374225 9150.92 1 5 CACCTG AAATTCCT + +4 cisbp__M0545 -1 0.374225 9150.92 1 5 CACCTG ACATGTCA - +4 cisbp__M1681 3 0.374225 9150.92 1 5 CACCTG GTTGACCA - +4 cisbp__M5478-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.374225 9150.92 1 5 CACCTG TCTTATCT - +4 jaspar__MA1085.1 3 0.374225 9150.92 1 5 CACCTG CTTGACCA - +4 predrem__nrMotif1007 -1 0.374225 9150.92 1 5 CACCTG ACCCCGCA - +4 predrem__nrMotif1694 -1 0.374225 9150.92 1 5 CACCTG ACCGCAGC - +4 cisbp__M0462 -2 0.374225 9150.92 1 4 CACCTG TCTTGGCG + +4 hdpi__SND1-Tudor-SN 4 0.374225 9150.92 1 4 CACCTG CCCAAACC - +4 homer__GGGGGGGG_Maz-Brf-CG7368-CTCF-CoRest-Klf15-Spps-Spt20-bon-btd-ct 4 0.374225 9150.92 1 4 CACCTG CCCCCCCC - +4 tfdimers__MD00568-GATAe-grn-Ing5-pnr-srp 17 0.375254 9176.08 1 6 CACCTG TCTTCCTTATCTCCATCCACCAGACCC - +4 cisbp__M0053 0 0.375721 9187.5 1 6 CACCTG TAGCTAGCTA + +4 cisbp__M0763 3 0.375721 9187.5 1 6 CACCTG TCAGATCTGA + +4 cisbp__M1046 3 0.375721 9187.5 1 6 CACCTG AATTACAGCG + +4 cisbp__M1348 4 0.375721 9187.5 1 6 CACCTG ACTACCCCTC + +4 cisbp__M1777 2 0.375721 9187.5 1 6 CACCTG AATTCCGGCG + +4 cisbp__M1795 0 0.375721 9187.5 1 6 CACCTG TTCCGATGAT + +4 cisbp__M1831 2 0.375721 9187.5 1 6 CACCTG ATTCCCGATG + +4 cisbp__M2251-CG7786-gt-hng1-Pdp1-vri 2 0.375721 9187.5 1 6 CACCTG ATTACGTAAT + +4 jaspar__MA0447.1-CG7786-Pdp1-gt-hng1-vri 2 0.375721 9187.5 1 6 CACCTG ATTACGTAAT + +4 predrem__nrMotif1332 3 0.375721 9187.5 1 6 CACCTG AGACACTTTT + +4 predrem__nrMotif1732 0 0.375721 9187.5 1 6 CACCTG TTTCTGCACT + +4 predrem__nrMotif2016 3 0.375721 9187.5 1 6 CACCTG CAAAACCCCA + +4 predrem__nrMotif2611 4 0.375721 9187.5 1 6 CACCTG CCGCAGCCTC + +4 predrem__nrMotif633 0 0.375721 9187.5 1 6 CACCTG AGCCTCTGGA + +4 predrem__nrMotif923 3 0.375721 9187.5 1 6 CACCTG GAGCTCCAGG + +4 predrem__nrMotif982 3 0.375721 9187.5 1 6 CACCTG GGACTCCAGG + +4 taipale_cyt_meth__NEUROG2_RMCATATGYY_FL_meth-amos-ato-Oli-tap 0 0.375721 9187.5 1 6 CACCTG GACATATGTC + +4 transfac_pro__M03832-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.375721 9187.5 1 6 CACCTG CACTTCCGGT + +4 transfac_pro__M04743-Max-Myc 2 0.375721 9187.5 1 6 CACCTG ACCACGTGGC + +4 transfac_pro__M07573-Atf6-CrebA-CrebB 0 0.375721 9187.5 1 6 CACCTG TACGTCATCA + +4 transfac_pro__M07704-Ets98B 0 0.375721 9187.5 1 6 CACCTG TACCGTATGC + +4 cisbp__M0073 1 0.375721 9187.5 1 6 CACCTG TCACCGACAA - +4 cisbp__M0482 1 0.375721 9187.5 1 6 CACCTG TACCCCGCCC - +4 cisbp__M0706-aop-bs-Eip74EF-Ets21C-Ets96B-Ets97D-Ets98B-nej-pnt 2 0.375721 9187.5 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M0799 3 0.375721 9187.5 1 6 CACCTG CTAGATCTCT - +4 cisbp__M3320-CoRest-GATAd-GATAe-grn-HLH3B-Jra-nej-pnr-srp-svp 3 0.375721 9187.5 1 6 CACCTG TCTTATCTCT - +4 hocomoco__GLIS3_HUMAN.H11MO.0.D-lmd-sug 0 0.375721 9187.5 1 6 CACCTG GACCCCCCAC - +4 hocomoco__SALL4_HUMAN.H11MO.0.B-salm-salr 3 0.375721 9187.5 1 6 CACCTG CCCACCCTCC - +4 jaspar__MA1008.1 1 0.375721 9187.5 1 6 CACCTG TCACCGACAA - +4 neph__UW.Motif.0064 1 0.375721 9187.5 1 6 CACCTG CATTCTGTTT - +4 predrem__nrMotif1217 4 0.375721 9187.5 1 6 CACCTG AGGGGACCAG - +4 predrem__nrMotif1930 0 0.375721 9187.5 1 6 CACCTG TTTCTGTGTA - +4 transfac_pro__M00948 4 0.375721 9187.5 1 6 CACCTG GTGGGCCCCA - +4 transfac_pro__M02043 3 0.375721 9187.5 1 6 CACCTG TACTTCCTCT - +4 transfac_pro__M05513 4 0.375721 9187.5 1 6 CACCTG TTCCCACCCC - +4 transfac_pro__M05551-CG42741 4 0.375721 9187.5 1 6 CACCTG GGCCCGCCTG - +4 transfac_public__M00348-CoRest-GATAd-GATAe-grn-HLH3B-Jra-pnr-srp-svp 3 0.375721 9187.5 1 6 CACCTG TCTTATCTCT - +4 yetfasco__YGR067C_2191 1 0.375721 9187.5 1 6 CACCTG TACCCCACTT - +4 cisbp__M5385-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.375721 9187.5 1 5 CACCTG ACCGGAAGTG + +4 neph__UW.Motif.0052 5 0.375721 9187.5 1 5 CACCTG GGAAAATCCC + +4 scertf__zhu.DOT6 -1 0.375721 9187.5 1 5 CACCTG ACCTCATCGC + +4 swissregulon__hs__EHF.p2-Eip74EF-Ets21C -1 0.375721 9187.5 1 5 CACCTG ACCCGGAAGT + +4 swissregulon__sacCer__MET31 -1 0.375721 9187.5 1 5 CACCTG AACTGTGGCG + +4 taipale__ELK4_DBD_ACCGGAARTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.375721 9187.5 1 5 CACCTG ACCGGAAGTG + +4 transfac_pro__M09407 5 0.375721 9187.5 1 5 CACCTG AAAAATATCT + +4 cisbp__M0439-opa -1 0.375721 9187.5 1 5 CACCTG CCCCGCTGTG - +4 cisbp__M1693 5 0.375721 9187.5 1 5 CACCTG CCGTTGACTT - +4 predrem__nrMotif2308 5 0.375721 9187.5 1 5 CACCTG TGACTTTCCT - +4 predrem__nrMotif1902 -2 0.375721 9187.5 1 4 CACCTG TCTTTCCATT + +4 predrem__nrMotif814 -2 0.375721 9187.5 1 4 CACCTG CCTGGACCCC - +4 elemento__CACCCAC 0 0.37599 9194.09 1 6 CACCTG CACCCAC + +4 elemento__CAGCTTC 0 0.37599 9194.09 1 6 CACCTG CAGCTTC + +4 elemento__AAGCTGG 1 0.37599 9194.09 1 6 CACCTG CCAGCTT - +4 elemento__AAGGAGC 1 0.37599 9194.09 1 6 CACCTG GCTCCTT - +4 elemento__CAAGCTG 0 0.37599 9194.09 1 6 CACCTG CAGCTTG - +4 elemento__CAAGGAG 0 0.37599 9194.09 1 6 CACCTG CTCCTTG - +4 transfac_pro__M03841-Bgb-Bro 0 0.37599 9194.09 1 6 CACCTG GACCACA - +4 predrem__nrMotif2540 2 0.37599 9194.09 1 5 CACCTG TAGAACT + +4 predrem__nrMotif1570 2 0.37599 9194.09 1 5 CACCTG CTGAACT - +4 jaspar__MA0436.1 3 0.37599 9194.09 1 4 CACCTG CCCCACG + +4 predrem__nrMotif2132 -2 0.37599 9194.09 1 4 CACCTG ACTGTCA + +4 transfac_pro__M05548 3 0.37599 9194.09 1 4 CACCTG AAGGACC + +4 hdpi__TAGLN2-CG5023-Mp20 -2 0.37599 9194.09 1 4 CACCTG CCGGACC - +4 transfac_pro__M01647 3 0.37599 9194.09 1 4 CACCTG CCCCACG - +4 transfac_pro__M05541 -2 0.37599 9194.09 1 4 CACCTG CCTCCGG - +4 yetfasco__YPR022C_588 3 0.37599 9194.09 1 4 CACCTG CCCCACG - +4 predrem__nrMotif1179 4 0.37599 9194.09 1 3 CACCTG CTGGCAC - +4 hocomoco__TWST1_MOUSE.H11MO.0.B-nej-twi 1 0.376855 9215.25 1 6 CACCTG ACATCTGGTTTTAATTA + +4 taipale_tf_pairs__CUX1_PITX1_GGATTANNNNATCRATN_CAP_repr-ct-Ptx1 4 0.376855 9215.25 1 6 CACCTG GGATTAAGTGATCGATA + +4 transfac_pro__M01133-bs 3 0.376855 9215.25 1 6 CACCTG ATTTTCCATTTTTGGTA + +4 transfac_pro__M09453-Clk 9 0.376855 9215.25 1 6 CACCTG CAAATTTAACACGTGTT - +4 cisbp__M1841-fkh-Hsf 1 0.378297 9250.51 1 6 CACCTG GAACATTCTGTTCTT + +4 cisbp__M2286-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 9 0.378297 9250.51 1 6 CACCTG TGGACTTTGAACTCT + +4 cisbp__M3414-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-svp-usp 2 0.378297 9250.51 1 6 CACCTG GTGACCTTTGCCCCC + +4 flyfactorsurvey__br-PAPE_SOLEXA_2.5-br 5 0.378297 9250.51 1 6 CACCTG AAAACCATCTAACGC + +4 flyfactorsurvey__pad_SOLEXA_F2-4-pad 2 0.378297 9250.51 1 6 CACCTG TTCCCCTCCTGGTTT + +4 hocomoco__TEAD4_MOUSE.H11MO.0.A-sd 3 0.378297 9250.51 1 6 CACCTG ACATTCCTGGCATTC + +4 neph__UW.Motif.0490 3 0.378297 9250.51 1 6 CACCTG CAGAAGCACAGAGAG + +4 neph__UW.Motif.0598 7 0.378297 9250.51 1 6 CACCTG AAAAATTTCTCTGTG + +4 taipale_cyt_meth__ZIC1_NMCCMCCYGCYGWGN_eDBD_meth-opa 3 0.378297 9250.51 1 6 CACCTG GACCCCCTGCTGTGC + +4 transfac_pro__M01875-EcR 8 0.378297 9250.51 1 6 CACCTG GTCAGAGTGACCCAG + +4 transfac_pro__M02928 9 0.378297 9250.51 1 6 CACCTG TATCATTAGAACGCT + +4 transfac_pro__M07035-arm 2 0.378297 9250.51 1 6 CACCTG GCTCTCTTTGATGAT + +4 transfac_pro__M09343 2 0.378297 9250.51 1 6 CACCTG ATAACCTTATCCATA + +4 cisbp__M2283-bin-croc-fd59A-fkh-FoxK-FoxL1-FoxP 7 0.378297 9250.51 1 6 CACCTG CTTTGTTTACTTTTG - +4 cisbp__M4546 5 0.378297 9250.51 1 6 CACCTG CCTAGCAACAGATGA - +4 flyfactorsurvey__lola-PF_SOLEXA_FBgn0005630-lola 2 0.378297 9250.51 1 6 CACCTG CCCAACTCCACCAAC - +4 hocomoco__MYBA_HUMAN.H11MO.0.D-Myb 4 0.378297 9250.51 1 6 CACCTG TCTCCAACTGCCACT - +4 hocomoco__PRGR_MOUSE.H11MO.0.A-Hsf-fkh 2 0.378297 9250.51 1 6 CACCTG AGAACATTCTGTTCT - +4 jaspar__MA0481.1-FoxK-FoxL1-FoxP-bin-croc-fd59A-fkh 7 0.378297 9250.51 1 6 CACCTG CTTTGTTTACTTTTG - +4 neph__UW.Motif.0270 9 0.378297 9250.51 1 6 CACCTG TGAAAAGAAATCTTC - +4 neph__UW.Motif.0532 2 0.378297 9250.51 1 6 CACCTG TGAAGCAGAGAGATG - +4 taipale_tf_pairs__ETV5_HOXA13_NNCGGAWGTNRTWAA_CAP-Ets96B 8 0.378297 9250.51 1 6 CACCTG TTTACGACTTCCGGT - +4 transfac_pro__M01072-E(z)-Myc-tna 7 0.378297 9250.51 1 6 CACCTG CCCCGGGCACCCGGG - +4 transfac_pro__M01109 7 0.378297 9250.51 1 6 CACCTG CGGCTGATACCCTGG - +4 transfac_public__M00258-Blimp-1-ebi-Stat92E 9 0.378297 9250.51 1 6 CACCTG GGGAAAGTGAAACTG - +4 transfac_pro__M06756 10 0.378297 9250.51 1 5 CACCTG ACGAAACTCGCACCA - +4 cisbp__M0610-Tet 2 0.378301 9250.59 1 6 CACCTG ATCGCGTTA + +4 cisbp__M1047 2 0.378301 9250.59 1 6 CACCTG ATTACAGCG + +4 cisbp__M4339 1 0.378301 9250.59 1 6 CACCTG AGATCTACA + +4 flyfactorsurvey__odd_NBT_1.5_FBgn0002985-bowl-odd 2 0.378301 9250.59 1 6 CACCTG GCTACTGGA + +4 jaspar__MA0301.1 1 0.378301 9250.59 1 6 CACCTG AGATCTACA + +4 predrem__nrMotif788 0 0.378301 9250.59 1 6 CACCTG ATCCTCCCA + +4 transfac_pro__M01921 1 0.378301 9250.59 1 6 CACCTG AGATCTACA + +4 cisbp__M0457 3 0.378301 9250.59 1 6 CACCTG TGTCACCTA - +4 cisbp__M0512-klu-sr 0 0.378301 9250.59 1 6 CACCTG CCCCGCATT - +4 predrem__nrMotif738 1 0.378301 9250.59 1 6 CACCTG CCCCCTCGG - +4 swissregulon__hs__NKX3-2.p2 2 0.378301 9250.59 1 6 CACCTG TCCACTTAA - +4 transfac_pro__M07272 0 0.378301 9250.59 1 6 CACCTG TAACTTGAC - +4 jaspar__MA0437.1 4 0.378301 9250.59 1 5 CACCTG ATTTCTCCG + +4 predrem__nrMotif598 4 0.378301 9250.59 1 5 CACCTG AAAACATCA + +4 transfac_pro__M01950 4 0.378301 9250.59 1 5 CACCTG ATTTCTCCG + +4 predrem__nrMotif1997 4 0.378301 9250.59 1 5 CACCTG AAGCTACTT - +4 predrem__nrMotif2297 4 0.378301 9250.59 1 5 CACCTG TTAAAACCA - +4 predrem__nrMotif871 4 0.378301 9250.59 1 5 CACCTG TGGATTCCT - +4 predrem__nrMotif91 -1 0.378301 9250.59 1 5 CACCTG TGCTGGGCT - +4 stark__RKGTCAAGK 4 0.378301 9250.59 1 5 CACCTG ACTTGACAC - +4 transfac_public__M00470-TfAP-2 -1 0.378301 9250.59 1 5 CACCTG CCCCCGGGC - +4 cisbp__M1296-bs -2 0.378301 9250.59 1 4 CACCTG CCTTATATG + +4 predrem__nrMotif929 5 0.378301 9250.59 1 4 CACCTG TCTGTCACA + +4 predrem__nrMotif457 5 0.378301 9250.59 1 4 CACCTG AAAAGCACA - +4 transfac_pro__M07807-lbl -2 0.378301 9250.59 1 4 CACCTG CCTCGTTAT - +4 transfac_pro__M05402 6 0.379202 9272.63 1 6 CACCTG TATAAATACGGGGGAACTTCATTCAT + +4 scertf__badis.CAT8 0 0.380009 9292.36 1 6 CACCTG TTCCGG - +4 scertf__zhao.YGR067C 0 0.380009 9292.36 1 6 CACCTG CCCCAC - +4 transfac_pro__M01829 -2 0.380009 9292.36 1 4 CACCTG CCTTTT + +4 hdpi__CSNK2B-CkIIbeta -2 0.380009 9292.36 1 4 CACCTG CCTTTC - +4 hdpi__RBBP5-Rbbp5 -2 0.380009 9292.36 1 4 CACCTG CATACT - +4 cisbp__M2377-Mef2-bs 2 0.381469 9328.06 1 6 CACCTG TTTACCATATATAGAAAT + +4 cisbp__M3339-ERR-Hr4 3 0.381469 9328.06 1 6 CACCTG GGTGAACTTGAACTTGAG + +4 jaspar__MA0584.1-Mef2-bs 2 0.381469 9328.06 1 6 CACCTG TTTACCATATATAGAAAT + +4 transfac_pro__M09444 10 0.381469 9328.06 1 6 CACCTG TAAAAAATATACCCTAAA + +4 cisbp__M5940 0 0.381469 9328.06 1 6 CACCTG GACATGTCCCAACATGTT - +4 swissregulon__hs__NR3C1.p2-fkh 4 0.381469 9328.06 1 6 CACCTG CTAGGACATAATGTTCCC - +4 taipale__TP63_DBD_RACATGTYNNRACATGTC 0 0.381469 9328.06 1 6 CACCTG GACATGTCCCAACATGTT - +4 taipale_tf_pairs__TEAD4_CEBPD_RGWATGYNNTTRCGYAAN_CAP-sd 10 0.381469 9328.06 1 6 CACCTG GTTGCGCAATCACATTCC - +4 taipale_tf_pairs__TEAD4_HES7_GGWATGYNNNNCRCGYGY_CAP_repr-sd 10 0.381469 9328.06 1 6 CACCTG ACACGTGCCACACATTCC - +4 transfac_pro__M05399-CG12605-scrt 0 0.381469 9328.06 1 6 CACCTG GACCAACAACAATGCCGC - +4 transfac_pro__M05877 10 0.381469 9328.06 1 6 CACCTG CCCAACCCGTCCCCTGCC - +4 transfac_pro__M06906 4 0.381469 9328.06 1 6 CACCTG ACCCTTCCTTTTGATTAC - +4 transfac_pro__M07735-gcm-gcm2 8 0.381469 9328.06 1 6 CACCTG CATGCGGGCACCCGCATG - +4 transfac_public__M00526-ERR-Hr4 3 0.381469 9328.06 1 6 CACCTG GGTGAACTTGAACTTGAG - +4 tfdimers__MD00459-nej 15 0.382287 9348.06 1 6 CACCTG TCTCTCACTCACTACTTCCTGTTTTTCCT - +4 cisbp__M1149 2 0.383131 9368.7 1 6 CACCTG GACACATCAAA + +4 cisbp__M6513-crp 2 0.383131 9368.7 1 6 CACCTG GCCAGCTGCGG + +4 jaspar__MA0493.1-CG42741-dar1-luna 5 0.383131 9368.7 1 6 CACCTG GGCCACACCCA + +4 predrem__nrMotif974 0 0.383131 9368.7 1 6 CACCTG TTACTTCTTGA + +4 taipale_cyt_meth__ETV2_NRCCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.383131 9368.7 1 6 CACCTG GACCGGAAGTG + +4 taipale_cyt_meth__USF2_MNCACGTGAYN_eDBD-cnc-cyc-Max-Mitf-Usf 2 0.383131 9368.7 1 6 CACCTG CCCACGTGACC + +4 tiffin__TIFDMEM0000087 3 0.383131 9368.7 1 6 CACCTG GACTACTTTCT + +4 transfac_pro__M01219-btd-kay-Nf-YB-Spps 4 0.383131 9368.7 1 6 CACCTG CCGCCCCCTCC + +4 transfac_pro__M05162 2 0.383131 9368.7 1 6 CACCTG AGTACCGCGCG + +4 transfac_pro__M09423 4 0.383131 9368.7 1 6 CACCTG TCCGTACAATT + +4 cisbp__M2294-CG42741-dar1-luna 5 0.383131 9368.7 1 6 CACCTG GGCCACACCCA - +4 cisbp__M5021-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.383131 9368.7 1 6 CACCTG TGGCACGTGCC - +4 cisbp__M5054-klu-sr 1 0.383131 9368.7 1 6 CACCTG CCACCCACGCA - +4 jaspar__MA0025.1-CG7786-Pdp1-gt-vri 4 0.383131 9368.7 1 6 CACCTG ACGTTACATAA - +4 taipale_cyt_meth__ELK1_NACCGGAAGTN_eDBD_meth-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-GATAe-grn-nej-pnr-pnt-RpII215 0 0.383131 9368.7 1 6 CACCTG CACTTCCGGTT - +4 taipale_cyt_meth__ELK3_NACCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.383131 9368.7 1 6 CACCTG CACTTCCGGTT - +4 taipale_tf_pairs__ETV5_EVX1_RSCGGWAATKR_CAP-Ets96B-eve 4 0.383131 9368.7 1 6 CACCTG TCATTTCCGGT - +4 transfac_pro__M05581 5 0.383131 9368.7 1 6 CACCTG CCTTCCAACCC - +4 transfac_pro__M07291-ci-lmd 5 0.383131 9368.7 1 6 CACCTG CCGACCACCCA - +4 transfac_pro__M07295 1 0.383131 9368.7 1 6 CACCTG ACACATTGGGT - +4 transfac_pro__M09128 1 0.383131 9368.7 1 6 CACCTG TTTACTTTTTG - +4 transfac_pro__M09420 4 0.383131 9368.7 1 6 CACCTG TCCGTACAATT - +4 transfac_pro__M05999 6 0.383131 9368.7 1 5 CACCTG TGTTTAAACCC + +4 transfac_pro__M06024 -1 0.383131 9368.7 1 5 CACCTG GCCGGACGACT + +4 cisbp__M3227-ham-pnr-srp 6 0.383131 9368.7 1 5 CACCTG TTATCTTATCT - +4 hocomoco__NOTO_HUMAN.H11MO.0.D-Awh-CG11294-CG18599-CG32532-CG34367-E5-Lim1-Lim3-OdsH-Pph13-Vsx1-ap-ems-eve-ind-lab-otp-repo-unc-4-unpg-zen2-zfh2 -1 0.383131 9368.7 1 5 CACCTG ACCTAATTAAC - +4 hocomoco__NFKB2_HUMAN.H11MO.0.B-CG12018-Dif-Rel-dl 7 0.383131 9368.7 1 4 CACCTG GGGAAAGCCCC + +4 predrem__nrMotif512 7 0.383131 9368.7 1 4 CACCTG CTGCCACCACC + +4 taipale_cyt_meth__HOXA10_NGYAATAAAAN_eDBD-abd-A-Abd-B-cad-eve-Ubx 7 0.383131 9368.7 1 4 CACCTG GTTTTATTACC - +4 cisbp__M3836 1 0.383691 9382.39 1 6 CACCTG GCACCCTTGGGTGC + +4 cisbp__M5364-kn 2 0.383691 9382.39 1 6 CACCTG ATTCCCTTGGGAAT + +4 cisbp__M6507-sd 0 0.383691 9382.39 1 6 CACCTG CACATTCCTGCGCC + +4 hocomoco__SIX1_HUMAN.H11MO.0.A-CG4730-CG7101-Six4-so 3 0.383691 9382.39 1 6 CACCTG TGAAACCTGATACC + +4 neph__UW.Motif.0202 0 0.383691 9382.39 1 6 CACCTG TGCCAGTACCCACA + +4 neph__UW.Motif.0417 5 0.383691 9382.39 1 6 CACCTG TTTAGCAACAGAAA + +4 taipale_cyt_meth__FERD3L_GYNNCAGCTGNNAC_FL_repr-ac-amos-ase-da-dimm-Fer3-HLH54F-l(1)sc-nau-sc 4 0.383691 9382.39 1 6 CACCTG GCAACAGCTGTTAC + +4 taipale_cyt_meth__OVOL1_NRWACCGTTATNYN_FL_meth_repr-ovo 2 0.383691 9382.39 1 6 CACCTG AAAACCGTTATTTG + +4 taipale_tf_pairs__ELK1_TBX21_TNRCACCGGAAGNN_CAP_repr 3 0.383691 9382.39 1 6 CACCTG TCACACCGGAAGTG + +4 taipale_tf_pairs__HOX13_MEIS1_NNNRTAAANCTGTN_ChIP_Exo 6 0.383691 9382.39 1 6 CACCTG ACCATAAAACTGTC + +4 transfac_pro__M07658-ac-ase-HLH3B-l(1)sc-sc 4 0.383691 9382.39 1 6 CACCTG ATAGCAGCTGCTAT + +4 transfac_pro__M09339 0 0.383691 9382.39 1 6 CACCTG ATCCTTATCTTAAT + +4 taipale__EBF1_full_NNTCCCNNGGGANN_repr-kn 2 0.383691 9382.39 1 6 CACCTG ATTCCCTTGGGAAT - +4 taipale__Nr2e1_DBD_RAGTCAANAAGTCA_repr-tll 1 0.383691 9382.39 1 6 CACCTG TGACTTATTGACTT - +4 taipale__SPIC_full_AAAAAGNGGAAGTN 0 0.383691 9382.39 1 6 CACCTG TACTTCCTCTTTTT - +4 taipale_tf_pairs__GCM2_PITX1_RTRCGGGSGATTAN_CAP_repr-gcm-gcm2-Ptx1 5 0.383691 9382.39 1 6 CACCTG CTAATCGCCCGCAT - +4 taipale_tf_pairs__TEAD4_ELF1_RGAATGCGGAAGTR_CAP-Eip74EF-sd 0 0.383691 9382.39 1 6 CACCTG CACTTCCGCATTCC - +4 taipale_tf_pairs__TEAD4_GSC2_RGWATGTTAATCCS_CAP_repr-Gsc-sd 6 0.383691 9382.39 1 6 CACCTG CGGATTAACATTCC - +4 taipale_tf_pairs__TEAD4_SPIB_RGAATGCGGAAGTN_CAP_2-sd 0 0.383691 9382.39 1 6 CACCTG TACTTCCGCATTCC - +4 transfac_pro__M02896 2 0.383691 9382.39 1 6 CACCTG GGTTCCGGAATTTG - +4 transfac_public__M00186-bs 0 0.383691 9382.39 1 6 CACCTG GTCCTTATATGGCC - +4 hocomoco__FOXD2_HUMAN.H11MO.0.D-croc-fd59A-fd96Ca-fd96Cb-fkh 13 0.384752 9408.35 1 6 CACCTG TTAAATAAATATTTACATA - +4 hocomoco__GATA1_HUMAN.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-srp-svp 3 0.384752 9408.35 1 6 CACCTG TCTTATCTGTCCCCGCCAG - +4 hocomoco__GATA1_MOUSE.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-srp-svp 4 0.384752 9408.35 1 6 CACCTG CCCTTATCTGCCCCCCCCA - +4 hocomoco__GATA2_HUMAN.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-srp-svp 3 0.384752 9408.35 1 6 CACCTG CCTTATCTCCACCCCCCAG - +4 hocomoco__TBX15_HUMAN.H11MO.0.D-Brf-CG7368-CTCF-Clp-CoRest-HDAC1-Klf15-Nelf-E-Rbbp5-SREBP-Spps-Spt20-brm-btd-crol-ct-klu-luna-l(3)neo38-peb-sr-vtd 4 0.384752 9408.35 1 6 CACCTG CCCCCACCCCCCCCCCCCC - +4 transfac_pro__M09377 1 0.384752 9408.35 1 6 CACCTG TTACGTGTAAAACACGTAA - +4 scertf__zhu.TEA1 15 0.384752 9408.35 1 4 CACCTG TCTGCGGAAATTAAATACC + +4 swissregulon__sacCer__TEA1 15 0.384752 9408.35 1 4 CACCTG TCTGCGGAAATTAAATACC + +4 tfdimers__MD00553-foxo-lz-run-RunxA-RunxB-slp2 3 0.385053 9415.71 1 6 CACCTG TAATTCCAAAACAAACAAAAAAAA + +4 cisbp__M6025-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-svp-usp 10 0.386287 9445.87 1 6 CACCTG ATTGGACTTTGACCCC + +4 stark__AATTAANNNNNCATNA-Antp 9 0.386287 9445.87 1 6 CACCTG AATTAAAAAAACATAA + +4 taipale_cyt_meth__ERG_NACCGGATATCCGGTN_FL_meth-Ets21C-Ets97D 0 0.386287 9445.87 1 6 CACCTG AACCGGATATCCGGTC + +4 taipale_cyt_meth__FLI1_NACCGGATATCCGGTN_eDBD-Ets21C-Ets97D 0 0.386287 9445.87 1 6 CACCTG AACCGGATATCCGGTT + +4 taipale_tf_pairs__ETV7_NNGGAAGTGCTTCCNN_HT-aop 10 0.386287 9445.87 1 6 CACCTG GCGGAAGTGCTTCCGC + +4 taipale_tf_pairs__FOXO1_HOXB13_RWMAACASYMRTWAAA_CAP_repr-foxo 5 0.386287 9445.87 1 6 CACCTG GTCAACACCCATAAAA + +4 taipale_tf_pairs__TEAD4_DLX3_RCATTCCNNNYAATTA_CAP-sd 3 0.386287 9445.87 1 6 CACCTG GCATTCCACGCAATTA + +4 transfac_pro__M01430 1 0.386287 9445.87 1 6 CACCTG AAAGCTCGTAAAATTT + +4 taipale_cyt_meth__HSF5_NRCGTTCTAGAAYGYN_eDBD_repr-Hsf 10 0.386287 9445.87 1 6 CACCTG AACGTTCTAGAACGTT - +4 taipale_cyt_meth__MAFG_NYGCTGAYRTCAGCRN_eDBD_meth-CrebA-CrebB-maf-S 5 0.386287 9445.87 1 6 CACCTG ATGCTGACGTCAGCAA - +4 transfac_pro__M00950-bs-Mef2 1 0.386287 9445.87 1 6 CACCTG TTTCCATATTTGGTAA - +4 transfac_pro__M01361-Abd-B 9 0.386287 9445.87 1 6 CACCTG ACGTTTTACGACTTTA - +4 transfac_pro__M07645-HLH4C 5 0.386287 9445.87 1 6 CACCTG GGACGCAGCTGCGTCC - +4 transfac_pro__M09367 1 0.386287 9445.87 1 6 CACCTG TTACTTGTGACACAAG - +4 transfac_pro__M09386 1 0.386287 9445.87 1 6 CACCTG TTACTTGTTCAACACG - +4 cisbp__M5929-gem -1 0.386287 9445.87 1 5 CACCTG ACCGGTTTAAACCGGT + +4 hocomoco__MYC_MOUSE.H11MO.0.A-E2f1-Max-Myc 3 0.386552 9452.36 1 6 CACCTG CGCCACGTGCGC + +4 hocomoco__SMAD4_MOUSE.H11MO.0.A-Med-Smox 1 0.386552 9452.36 1 6 CACCTG CTGTCTGGCACC + +4 homer__AGCAGCTGCTGC_MyoD-Fer3-HLH54F-ac-ase-dimm-l(1)sc-nau-sc 2 0.386552 9452.36 1 6 CACCTG AGCAGCTGCTGC + +4 homer__GGTCCCTAGGGA_EBF-kn 2 0.386552 9452.36 1 6 CACCTG GGTCCCTAGGGA + +4 scertf__foat.DAL81 5 0.386552 9452.36 1 6 CACCTG TATCTTATCTCC + +4 swissregulon__hs__ZNF238.p2 4 0.386552 9452.36 1 6 CACCTG GGAACATCTGGA + +4 taipale_cyt_meth__ZNF704_NRCCGGCCGGYN_FL-Glut4EF 0 0.386552 9452.36 1 6 CACCTG CGCCGGCCGGCG + +4 transfac_pro__M05690 6 0.386552 9452.36 1 6 CACCTG CGAATTTACCGA + +4 transfac_pro__M05943 6 0.386552 9452.36 1 6 CACCTG TGGGGTTGCCTC + +4 transfac_pro__M06615 6 0.386552 9452.36 1 6 CACCTG CTGTCCTACCGA + +4 transfac_pro__M06669 6 0.386552 9452.36 1 6 CACCTG CGAAGCTACCGC + +4 transfac_pro__M07639-amos-ato-da-dimm-HLH54F-Oli-tap 0 0.386552 9452.36 1 6 CACCTG CACCATATGGTG + +4 transfac_pro__M07661-twi 1 0.386552 9452.36 1 6 CACCTG CCACACGACGCA + +4 cisbp__M3638-bap 3 0.386552 9452.36 1 6 CACCTG ATATACTTATTT - +4 neph__UW.Motif.0073 6 0.386552 9452.36 1 6 CACCTG GAAAAAAGCCAG - +4 neph__UW.Motif.0081 3 0.386552 9452.36 1 6 CACCTG TTCCATTTTGGC - +4 taipale_cyt_meth__CREB3_NGCCACGTCAYN_FL-Atf6-CrebA-Xbp1 3 0.386552 9452.36 1 6 CACCTG GGTGACGTGGCA - +4 taipale_cyt_meth__TCF21_NAACAGCTGYYN_eDBD_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.386552 9452.36 1 6 CACCTG CAACAGCTGTTG - +4 taipale_cyt_meth__XBP1_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.386552 9452.36 1 6 CACCTG GATGACGTCATC - +4 taipale_tf_pairs__FOXO1_ETV4_RCCGGAWGTKKN_CAP-Ets96B-foxo 2 0.386552 9452.36 1 6 CACCTG TAAACATCCGGT - +4 tiffin__TIFDMEM0000091 5 0.386552 9452.36 1 6 CACCTG AAAAATACCAAA - +4 transfac_pro__M04617 1 0.386552 9452.36 1 6 CACCTG GGACCCACTGCT - +4 transfac_pro__M06027 1 0.386552 9452.36 1 6 CACCTG TTGCCTTGTGAA - +4 transfac_pro__M06255 6 0.386552 9452.36 1 6 CACCTG GCGTATTGCCCG - +4 transfac_pro__M06704-CG2120 6 0.386552 9452.36 1 6 CACCTG TCTTATTACCCG - +4 transfac_pro__M07415-aop-Eip74EF-Ets21C-Ets96B 0 0.386552 9452.36 1 6 CACCTG TACTTCCGGGTT - +4 transfac_pro__M07602-gem 1 0.386552 9452.36 1 6 CACCTG GTGGCTGGGAAG - +4 transfac_pro__M07666-Atf-2-Atf3-Atf6-CG44247-CG7786-cnc-crc-CrebA-CrebB-E2f1-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.386552 9452.36 1 6 CACCTG GGTGACGTCACC - +4 transfac_public__M00451-bap 3 0.386552 9452.36 1 6 CACCTG ATATACTTATAT - +4 transfac_pro__M05930-CG6654-CG7372 7 0.386552 9452.36 1 5 CACCTG TTTTTCGCAACT - +4 transfac_pro__M05985 7 0.386552 9452.36 1 5 CACCTG GCTAGATCACCC - +4 transfac_pro__M06995-cnc -1 0.386552 9452.36 1 5 CACCTG TCCTTGCTAATA - +4 scertf__foat.WAR1 8 0.386552 9452.36 1 4 CACCTG TTGACTTGAACC + +4 transfac_pro__M06782-CG3281 8 0.386552 9452.36 1 4 CACCTG CCCATAATAACC + +4 taipale__TCF7L1_full_NAASATCAAAGN-pan -2 0.386552 9452.36 1 4 CACCTG CCTTTGATCTTT - +4 transfac_pro__M05698 -2 0.386552 9452.36 1 4 CACCTG CCTGTACTCACT - +4 transfac_pro__M06787 8 0.386552 9452.36 1 4 CACCTG GCTTTTTCCACA - +4 cisbp__M4579-ac-ase-cnc-cwo-cyc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-SREBP-tgo-Usf 3 0.386579 9453.02 1 6 CACCTG GGTCACGTGACCC + +4 neph__UW.Motif.0647 5 0.386579 9453.02 1 6 CACCTG GGCTTCATTTTCC + +4 taipale_cyt_meth__EGR1_NMCGCCCACGCMN_eDBD_meth-klu-sr 2 0.386579 9453.02 1 6 CACCTG CCCGCCCACGCAC + +4 taipale_tf_pairs__ELK1_EOMES_TNRCACCGGAAGN_CAP 3 0.386579 9453.02 1 6 CACCTG TCACACCGGAAGT + +4 transfac_pro__M07351-kn 2 0.386579 9453.02 1 6 CACCTG ATTCCCTTGGGGC + +4 taipale__ZNF238_full_NNTCCAGATGTKN 3 0.386579 9453.02 1 6 CACCTG GAACATCTGGATG - +4 neph__UW.Motif.0180 8 0.386579 9453.02 1 5 CACCTG AAGTAATTTTCCT + +4 neph__UW.Motif.0191 -1 0.386579 9453.02 1 5 CACCTG CCCTCTGGCTTTC + +4 neph__UW.Motif.0131 8 0.386579 9453.02 1 5 CACCTG GGCCGCGGGGCCT - +4 transfac_pro__M09430 8 0.386579 9453.02 1 5 CACCTG GTGGGGCCCACAT - +4 neph__UW.Motif.0670 -3 0.386579 9453.02 1 3 CACCTG CTTTCCAGTGACA + +4 cisbp__M2181-bigmax-mio 7 0.386829 9459.12 1 6 CACCTG ATATTAGCACGTGCTTAGTC + +4 dbcorrdb__ARID3A__ENCSR000EFY_1__m3-cnc-Jra-kay-nej-Stat92E 9 0.386829 9459.12 1 6 CACCTG AGAATGACTCATCATTTTAT + +4 dbcorrdb__EBF1__ENCSR000DZQ_1__m1-kn 3 0.386829 9459.12 1 6 CACCTG AAGTCCCTGGGGACTTGAGG + +4 dbcorrdb__EP300__ENCSR000DZT_1__m1-nej 10 0.386829 9459.12 1 6 CACCTG AAGATAATAATACATTATAA + +4 dbcorrdb__REST__ENCSR000BQS_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 3 0.386829 9459.12 1 6 CACCTG CAGCACCATGGACAGCGCCC + +4 dbcorrdb__SIN3A__ENCSR000BOW_1__m3-Sin3A-Usf 11 0.386829 9459.12 1 6 CACCTG CCCGCGGCGCTTGCGTGTCG + +4 dbcorrdb__SRF__ENCSR000BLV_1__m1-bs-Mef2 7 0.386829 9459.12 1 6 CACCTG CGCCCATTGCCATATAAGGC + +4 dbcorrdb__STAT2__ENCSR000FBC_1__m2-Stat92E 10 0.386829 9459.12 1 6 CACCTG ATAAGGAAACTGCCTGCAGA + +4 dbcorrdb__TCF7L2__ENCSR000EWT_1__m1-pan 4 0.386829 9459.12 1 6 CACCTG CCGGTTCCTTTGATGTTTCT + +4 yetfasco__YBL103C_870-bigmax-mio 7 0.386829 9459.12 1 6 CACCTG GACTAAGCACGTGCTAATAT + +4 cisbp__M6270-HLH4C 7 0.386829 9459.12 1 6 CACCTG TGGGGAGCAGCTGCGTCCCT - +4 dbcorrdb__CHD1__ENCSR000AQK_1__m1-Chd1 3 0.386829 9459.12 1 6 CACCTG GTTGCCCTGAAAACCGCCTT - +4 dbcorrdb__CTCF__ENCSR000DTI_1__m3-CTCF-vtd 12 0.386829 9459.12 1 6 CACCTG GGGCAAGAGCGCCCCCTGGT - +4 dbcorrdb__NR3C1__ENCSR000BHF_1__m1-fkh-Hsf 2 0.386829 9459.12 1 6 CACCTG AGAACAGAATGTTCTTTGCC - +4 dbcorrdb__RCOR1__ENCSR000EFG_1__m4-ac-ase-CoRest-dimm-l(1)sc-sc 2 0.386829 9459.12 1 6 CACCTG AACAGCTGTCTGAGGCATGA - +4 dbcorrdb__REST__ENCSR000BQS_1__m3-CTCF 11 0.386829 9459.12 1 6 CACCTG CACCAAGGCAGCTCCTGGTG - +4 dbcorrdb__eGFP-NR4A1__ENCSR000DJW_1__m2 6 0.386829 9459.12 1 6 CACCTG TGTGCTGGCATCCTATCTCA - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m3-RpII215 15 0.386829 9459.12 1 5 CACCTG ATCGCCCTTCGCGCTCCCCT - +4 hocomoco__Z324A_HUMAN.H11MO.0.C-CG8089-CG10321 9 0.38684 9459.39 1 6 CACCTG TATCAAACCATCCTTTGCTGCCA + +4 tfdimers__MD00543-Sox100B 12 0.38684 9459.39 1 6 CACCTG TTTTTCTTTGTTTACTTATTTAT + +4 taipale_cyt_meth__ELF3_ACCAGGAAGNNNNNNNNNWWWWW_eDBD_meth_repr 15 0.38684 9459.39 1 6 CACCTG TTTTTTTTTTTTTACTTCCTGGT - +4 taipale_cyt_meth__ELF3_ACMAGGAAGNNNNNNNNNWWWWW_FL_meth 15 0.38684 9459.39 1 6 CACCTG TTTTTTTGAATCTACTTCCTGGT - +4 taipale_tf_pairs__GCM1_MAX_NNCACGTGNNNNNNNNNNRTGCGGGYRN_CAP_repr-gcm-gcm2-Max 1 0.38741 9473.34 1 6 CACCTG CTGCCCGCATCGCCCGTAACCACGTGCC - +4 tfdimers__MD00082-GATAe-grn-pnr-srp 14 0.387781 9482.42 1 6 CACCTG TCAACAGATAATCCTACAAAAA + +4 tfdimers__MD00419-pho-phol 10 0.387781 9482.42 1 6 CACCTG TCTCTCCATTCACATGCAAATT + +4 cisbp__M2328-su(Hw) 10 0.387806 9483.03 1 6 CACCTG ATTTGTTGCATACTTTTGGGC - +4 hocomoco__ZBT7B_HUMAN.H11MO.0.D-CG5846-CG9727-Max-Rfx-SREBP-Sin3A 5 0.387806 9483.03 1 6 CACCTG CCCGTTGCCATGGCAACGGCG - +4 tfdimers__MD00083-Ing5-pho-phol 6 0.387806 9483.03 1 6 CACCTG AAAAGCCACCAGATGGCGTAG - +4 cisbp__M0944-bcd-Gsc-oc-Ptx1 2 0.389078 9514.12 1 6 CACCTG TTAATCCC + +4 cisbp__M1566 2 0.389078 9514.12 1 6 CACCTG TGTACGGT + +4 cisbp__M1615 1 0.389078 9514.12 1 6 CACCTG CCACTAAA + +4 cisbp__M3083-achi-Atf3-Atf6-CrebA-CrebB-hth-Jra-kay-maf-S-REPTOR-BP-vis-Xbp1 1 0.389078 9514.12 1 6 CACCTG TGACGTCA + +4 homer__CTGTCTGG_Smad2-Med-Smox 1 0.389078 9514.12 1 6 CACCTG CTGTCTGG + +4 neph__UW.Motif.0008-RunxA-RunxB-lz-run 1 0.389078 9514.12 1 6 CACCTG AAACCACA + +4 cisbp__M1313 0 0.389078 9514.12 1 6 CACCTG TAACGGTC - +4 elemento__ATGGTGGC 2 0.389078 9514.12 1 6 CACCTG GCCACCAT - +4 taipale_cyt_meth__NKX3-1_NTCGTTAN_eDBD_meth-bap-bsh-Dr-ind-Lim1-unpg 2 0.389078 9514.12 1 6 CACCTG TTAACGAG - +4 elemento__CCCTTTAA -1 0.389078 9514.12 1 5 CACCTG CCCTTTAA + +4 elemento__TCCTTGCC -1 0.389078 9514.12 1 5 CACCTG TCCTTGCC + +4 elemento__TCCTTGTC -1 0.389078 9514.12 1 5 CACCTG TCCTTGTC + +4 predrem__nrMotif1690 3 0.389078 9514.12 1 5 CACCTG TGAGACCA + +4 scertf__spivak.TEC1-sd -1 0.389078 9514.12 1 5 CACCTG ACATTCTT + +4 cisbp__M1685 3 0.389078 9514.12 1 5 CACCTG GTTGACCG - +4 elemento__AAGAAGGC -1 0.389078 9514.12 1 5 CACCTG GCCTTCTT - +4 elemento__GCCAAGGC -1 0.389078 9514.12 1 5 CACCTG GCCTTGGC - +4 predrem__nrMotif1312 3 0.389078 9514.12 1 5 CACCTG TGTGACCA - +4 taipale__GATA4_DBD_AGATAANN-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.389078 9514.12 1 5 CACCTG TCTTATCT - +4 transfac_pro__M07461-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Spps 3 0.389078 9514.12 1 5 CACCTG CCCCACCC - +4 yetfasco__YOR028C_1349 4 0.389078 9514.12 1 4 CACCTG TAATTACG + +4 cisbp__M0070 4 0.389078 9514.12 1 4 CACCTG ACGACATC - +4 transfac_pro__M01688 4 0.389078 9514.12 1 4 CACCTG GCCACACC - +4 predrem__nrMotif844 -3 0.389078 9514.12 1 3 CACCTG CTTTAAGA + +4 cisbp__M4878-CG7386-D19A 5 0.389078 9514.12 1 3 CACCTG TCATTCAC - +4 predrem__nrMotif2456 5 0.389078 9514.12 1 3 CACCTG GCGGGCAC - +4 elemento__CATGTTC 1 0.390718 9554.23 1 6 CACCTG GAACATG - +4 transfac_pro__M01238-Deaf1 0 0.390718 9554.23 1 6 CACCTG AGCCGAA - +4 elemento__ACATCCT 2 0.390718 9554.23 1 5 CACCTG ACATCCT + +4 elemento__ACCCCGC -1 0.390718 9554.23 1 5 CACCTG ACCCCGC + +4 elemento__AGATCCT 2 0.390718 9554.23 1 5 CACCTG AGATCCT + +4 cisbp__M0370 2 0.390718 9554.23 1 5 CACCTG TACACTC - +4 elemento__AGGATGC 2 0.390718 9554.23 1 5 CACCTG GCATCCT - +4 transfac_pro__M00789-GATAe-grn-pnr-srp 2 0.390718 9554.23 1 5 CACCTG CTTATCT - +4 hdpi__IVD-CG6638 3 0.390718 9554.23 1 4 CACCTG AATCAGC + +4 transfac_pro__M02019-pan -2 0.390718 9554.23 1 4 CACCTG CCTTTGA - +4 cisbp__M0341-Jra-REPTOR-BP-gt-kay-vri 2 0.390854 9557.55 1 6 CACCTG ATTACGTAAT + +4 cisbp__M1174 2 0.390854 9557.55 1 6 CACCTG TATATCCGCT + +4 cisbp__M1501 1 0.390854 9557.55 1 6 CACCTG ACGCGTGACG + +4 cisbp__M1533-CG5846-CG9727-Rfx-SREBP 2 0.390854 9557.55 1 6 CACCTG GTTGCCATGG + +4 cisbp__M1544 3 0.390854 9557.55 1 6 CACCTG ATTGACGTCA + +4 homer__NHAACBGYYV_BMYB 1 0.390854 9557.55 1 6 CACCTG CTAACTGCCA + +4 predrem__nrMotif1325 1 0.390854 9557.55 1 6 CACCTG CCACCCGGCC + +4 predrem__nrMotif2248 0 0.390854 9557.55 1 6 CACCTG TTTCTTCATG + +4 predrem__nrMotif2589 4 0.390854 9557.55 1 6 CACCTG TTAGTTCCTT + +4 predrem__nrMotif961 3 0.390854 9557.55 1 6 CACCTG GACCACCCCC + +4 taipale_cyt_meth__HEY2_NGCACGTGYN_FL-dpn-E(spl)mbeta-HLH-h-Hey-Sidpn 2 0.390854 9557.55 1 6 CACCTG GGCACGTGTC + +4 taipale_cyt_meth__KLF5_NMCACGCCCN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-hkb-luna-Sp1-Spps 4 0.390854 9557.55 1 6 CACCTG GCCACGCCCT + +4 taipale_cyt_meth__SREBF2_ATCACMCCAY_eDBD_meth-SREBP 4 0.390854 9557.55 1 6 CACCTG ATCACACCAT + +4 transfac_pro__M00936-Xbp1 2 0.390854 9557.55 1 6 CACCTG GCCACGTCAC + +4 transfac_pro__M07688-CG7786-gt-hng1-Pdp1-vri 2 0.390854 9557.55 1 6 CACCTG GTTACGTAAC + +4 transfac_pro__M08915-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.390854 9557.55 1 6 CACCTG ATGACGTCAT + +4 cisbp__M0308-cic-maf-S-tj 2 0.390854 9557.55 1 6 CACCTG AATTGCTGAC - +4 cisbp__M0343 4 0.390854 9557.55 1 6 CACCTG TTGTCATCAT - +4 cisbp__M0617 1 0.390854 9557.55 1 6 CACCTG TCCCGCACTT - +4 cisbp__M1367 3 0.390854 9557.55 1 6 CACCTG ACGAACTATT - +4 cisbp__M1424 2 0.390854 9557.55 1 6 CACCTG GGCACCAATT - +4 cisbp__M1539-CG5846-CG9727-Max-Rfx-SREBP 2 0.390854 9557.55 1 6 CACCTG GTTGCCATGG - +4 factorbook__SREBF1-SREBP 2 0.390854 9557.55 1 6 CACCTG ATCACCCCAC - +4 fantom__motif98_GCCGAAGATT 0 0.390854 9557.55 1 6 CACCTG AATCTTCGGC - +4 hdpi__H2AFZ-His2Av 2 0.390854 9557.55 1 6 CACCTG TTTCCCATTG - +4 homer__AACCGGAAGT_GABPA-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-dl-pnt 2 0.390854 9557.55 1 6 CACCTG ACTTCCGGTT - +4 predrem__nrMotif1258 4 0.390854 9557.55 1 6 CACCTG ACTTTGCCTT - +4 predrem__nrMotif1955 3 0.390854 9557.55 1 6 CACCTG TCACATCTCT - +4 taipale_cyt_meth__GATA5_NWGATAASRN_eDBD-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp 4 0.390854 9557.55 1 6 CACCTG CCCTTATCTG - +4 tiffin__TIFDMEM0000028 4 0.390854 9557.55 1 6 CACCTG TGGCTAAATT - +4 transfac_pro__M02041 3 0.390854 9557.55 1 6 CACCTG TACTTCCGCT - +4 transfac_pro__M08806-klu-sr 2 0.390854 9557.55 1 6 CACCTG CCCACCCACA - +4 transfac_pro__M08818-CG42741 3 0.390854 9557.55 1 6 CACCTG CCACACCCCC - +4 cisbp__M0682 5 0.390854 9557.55 1 5 CACCTG GGATGCATCC + +4 predrem__nrMotif745 5 0.390854 9557.55 1 5 CACCTG GGAGGGACCC + +4 transfac_pro__M09584 5 0.390854 9557.55 1 5 CACCTG GTCCGTACAA + +4 cisbp__M1261 6 0.390854 9557.55 1 4 CACCTG GACCGAAACT + +4 cisbp__M1272 6 0.390854 9557.55 1 4 CACCTG AACCGAAACT + +4 taipale_cyt_meth__MEF2D_CCWWATWWRG_eDBD_meth-bs-Mef2 -2 0.390854 9557.55 1 4 CACCTG CCAAATTTGG + +4 taipale_tf_pairs__TEAD4_HES7_RCATTCCNNCRCGYGYN_CAP_repr-sd 3 0.392602 9600.3 1 6 CACCTG GCATTCCAGCACGTGCC + +4 transfac_pro__M07727-GATAe-grn-pnr 7 0.392602 9600.3 1 6 CACCTG CGATAAGGACCTTATCG + +4 taipale_tf_pairs__ELK1_SREBF2_RWCACGTGNNCGGAANN_CAP_repr-SREBP 9 0.392602 9600.3 1 6 CACCTG ACTTCCGGTCACGTGAT - +4 transfac_pro__M01324-vvl 11 0.392602 9600.3 1 6 CACCTG TTTATTATGCATATCTT - +4 transfac_pro__M03090-vvl 11 0.392602 9600.3 1 6 CACCTG TTTATTATGCATATCTT - +4 transfac_pro__M06823 12 0.392602 9600.3 1 5 CACCTG TGCTTGTGGGCATCCCT + +4 cisbp__M0727-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 3 0.393385 9619.45 1 6 CACCTG GTAAACAAA + +4 cisbp__M1723 1 0.393385 9619.45 1 6 CACCTG TTCCCGCGC + +4 cisbp__M1805 2 0.393385 9619.45 1 6 CACCTG ATATCCGTT + +4 jaspar__MA0288.1-achi-hth-vis 3 0.393385 9619.45 1 6 CACCTG TGACACATT + +4 predrem__nrMotif1156 1 0.393385 9619.45 1 6 CACCTG TGCCCTTGA + +4 predrem__nrMotif597 0 0.393385 9619.45 1 6 CACCTG AACCCTCCC + +4 predrem__nrMotif606 3 0.393385 9619.45 1 6 CACCTG GGCCACCCC + +4 taipale_cyt_meth__HMX1_NCAMTTAAN_eDBD_meth_repr-bap-Hmx-tup 1 0.393385 9619.45 1 6 CACCTG CCACTTAAC + +4 transfac_pro__M00793-CG10431-pho-phol 2 0.393385 9619.45 1 6 CACCTG GCCATCTTG + +4 cisbp__M4410-achi-hth-vis 3 0.393385 9619.45 1 6 CACCTG TGACACATT - +4 cisbp__M5122-bowl-odd 2 0.393385 9619.45 1 6 CACCTG GCTACTGGA - +4 fantom__motif113_YGAGCTRTG 2 0.393385 9619.45 1 6 CACCTG CACAGCTCA - +4 fantom__motif121_TGCAWTGTA 0 0.393385 9619.45 1 6 CACCTG TACATTGCA - +4 predrem__nrMotif2115 1 0.393385 9619.45 1 6 CACCTG TAACCCTTT - +4 predrem__nrMotif2347 2 0.393385 9619.45 1 6 CACCTG TGAACATGA - +4 transfac_pro__M01953-achi-hth-vis 3 0.393385 9619.45 1 6 CACCTG TGACACATT - +4 cisbp__M1021-achi-esg-hth-sna-vis-wor -1 0.393385 9619.45 1 5 CACCTG ACCTGTCAA + +4 cisbp__M2939-TfAP-2 -1 0.393385 9619.45 1 5 CACCTG CCCCCGGGC + +4 predrem__nrMotif2234 -1 0.393385 9619.45 1 5 CACCTG TCCTAAGCT + +4 transfac_pro__M05157 4 0.393385 9619.45 1 5 CACCTG TATTTAGCT + +4 cisbp__M1401 4 0.393385 9619.45 1 5 CACCTG CGTTGACCA - +4 cisbp__M1698 4 0.393385 9619.45 1 5 CACCTG CGTTGACCT - +4 predrem__nrMotif948 4 0.393385 9619.45 1 5 CACCTG TCATTGCCT - +4 predrem__nrMotif1436 5 0.393385 9619.45 1 4 CACCTG GTCCACACC + +4 predrem__nrMotif310 5 0.393385 9619.45 1 4 CACCTG TGAGAAACA + +4 predrem__nrMotif763 5 0.393385 9619.45 1 4 CACCTG AAATTCACT + +4 transfac_pro__M04680-bs -2 0.393385 9619.45 1 4 CACCTG CCTTATAAG + +4 flyfactorsurvey__Kr_SOLEXA_FBgn0001325-Kr 3 0.393865 9631.19 1 6 CACCTG GTTAACCCTTTCGCT + +4 jaspar__MA0148.3-FoxK-FoxP-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-nej 8 0.393865 9631.19 1 6 CACCTG TCCATGTTTACTTTG + +4 taipale_cyt_meth__GLI3_RGACCACCCACRWYG_eDBD_repr-ci-lmd-opa 8 0.393865 9631.19 1 6 CACCTG AGACCACCCACGTCG + +4 taipale_tf_pairs__HOXB2_ELK1_TAATKRCCGGAAGNN_CAP_repr-pb 4 0.393865 9631.19 1 6 CACCTG TAATTACCGGAAGTG + +4 taipale_tf_pairs__MYBL1_ONECUT2_NAACGGNNATYGANN_CAP_repr-Myb-onecut 0 0.393865 9631.19 1 6 CACCTG CAACGGTTATCGATC + +4 transfac_pro__M02789-CG9727-Rfx 1 0.393865 9631.19 1 6 CACCTG TACCATAGCAACGGT + +4 transfac_pro__M02831-btd-CG7368-CoRest-crol-ct-CTCF-klu-l(3)neo38-Rbbp5-Spps-Spt20 1 0.393865 9631.19 1 6 CACCTG TCCCCCCCCCCCCCC + +4 transfac_pro__M09052 7 0.393865 9631.19 1 6 CACCTG CCACCTCCACCGACA + +4 transfac_pro__M09366 4 0.393865 9631.19 1 6 CACCTG AAGTTACGTGTAAAA + +4 cisbp__M1965-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-slp2 8 0.393865 9631.19 1 6 CACCTG TCCATGTTTACTTTG - +4 cisbp__M5016-HLH4C 4 0.393865 9631.19 1 6 CACCTG AGCGCAGCTGAGGCC - +4 flyfactorsurvey__lola-PY_SOLEXA_FBgn0005630-lola 3 0.393865 9631.19 1 6 CACCTG CCAAACCCTCACAAA - +4 neph__UW.Motif.0185 4 0.393865 9631.19 1 6 CACCTG TGTCTTTCTGGGTTT - +4 transfac_pro__M07204-fkh-Hsf 1 0.393865 9631.19 1 6 CACCTG GAACATTCTGTTCTT - +4 transfac_pro__M09530-Atf6-CrebA-Xbp1 3 0.393865 9631.19 1 6 CACCTG TGCCACGTCATCATT - +4 transfac_pro__M09394 -1 0.393865 9631.19 1 5 CACCTG ACTTGTTCAATAAGT + +4 fantom__motif24_AGAACT 1 0.39467 9650.87 1 5 CACCTG AGAACT + +4 fantom__motif43_CCCWGT -1 0.39467 9650.87 1 5 CACCTG CCCTGT + +4 hdpi__CFL2 1 0.39467 9650.87 1 5 CACCTG ACCCCG - +4 hdpi__MTHFD1-pug -2 0.39467 9650.87 1 4 CACCTG CCCAGC - +4 flyfactorsurvey__ab_SOLEXA_5_FBgn0259750-ab 12 0.395888 9680.65 1 6 CACCTG TTTTTTTAATGGGTCCTGGCGTGGGG - +4 tfdimers__MD00066-Eip74EF 15 0.395888 9680.65 1 6 CACCTG CTCTACAACAACCACTTCCTGCCTCT - +4 tfdimers__MD00592-crp-Myc 13 0.395888 9680.65 1 6 CACCTG GCCCCCAGATGAGCATCTGGCCGCGT - +4 hdpi__ZDHHC5-CG34449 -1 0.396853 9704.24 1 5 CACCTG CCCTC - +4 hdpi__ZMAT2-CG11586 -1 0.396853 9704.24 1 5 CACCTG CCCTC - +4 taipale_cyt_meth__NHLH1_NKGNMKCAGCTGCGYCMN_FL-HLH4C 6 0.397411 9717.89 1 6 CACCTG GGGGCGCAGCTGCGTCCC + +4 taipale_tf_pairs__ERF_DLX3_RSCGGAANNNNNYAATTA_CAP-Ets21C 11 0.397411 9717.89 1 6 CACCTG TAATTGCCCATTTCCGGT - +4 transfac_pro__M05298-ovo 13 0.397411 9717.89 1 5 CACCTG GGGGGCCGATCCCGACCC - +4 cisbp__M1857-CG7786-gt-Pdp1-vri 4 0.398456 9743.44 1 6 CACCTG ATGTTACATAA + +4 hocomoco__MLX_HUMAN.H11MO.0.D-bigmax 4 0.398456 9743.44 1 6 CACCTG TGATCACGTGC + +4 predrem__nrMotif16 0 0.398456 9743.44 1 6 CACCTG TTTCTTTTACT + +4 scertf__zhu.MIG3-klu-sr 0 0.398456 9743.44 1 6 CACCTG TACCCCGCATT + +4 taipale_cyt_meth__MLX_YNCACGTGMYN_FL-bigmax-Mitf 2 0.398456 9743.44 1 6 CACCTG TGCACGTGACC + +4 taipale_cyt_meth__USF1_MNCACGTGAYN_FL-cnc-cyc-Mitf-Usf 2 0.398456 9743.44 1 6 CACCTG CCCACGTGACC + +4 transfac_pro__M01794-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 2 0.398456 9743.44 1 6 CACCTG ATCACGTGACA + +4 transfac_pro__M07312-Atf3-Atf6-cnc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.398456 9743.44 1 6 CACCTG CGTGACGTCAT + +4 transfac_pro__M07913-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.398456 9743.44 1 6 CACCTG GCCACGCCCCC + +4 transfac_pro__M08937-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.398456 9743.44 1 6 CACCTG GATGACGTCAT + +4 transfac_pro__M09108 2 0.398456 9743.44 1 6 CACCTG CGCACGTGTGG + +4 transfac_pro__M09109 2 0.398456 9743.44 1 6 CACCTG CGCACGTGTGA + +4 transfac_pro__M09110 3 0.398456 9743.44 1 6 CACCTG TCACACGTGCG + +4 cisbp__M0351 2 0.398456 9743.44 1 6 CACCTG GTTTCCTCCTC - +4 cisbp__M0656 1 0.398456 9743.44 1 6 CACCTG AAACGTTATCG - +4 cisbp__M1638 0 0.398456 9743.44 1 6 CACCTG AACTTGGTACA - +4 taipale_cyt_meth__ETV4_NRCMGGAAGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.398456 9743.44 1 6 CACCTG TACTTCCGGTC - +4 transfac_pro__M05676 2 0.398456 9743.44 1 6 CACCTG TCCTCCTTCAC - +4 transfac_pro__M09175 2 0.398456 9743.44 1 6 CACCTG TTAACTTTTTC - +4 cisbp__M1498 -1 0.398456 9743.44 1 5 CACCTG ACCGTGACCAC + +4 transfac_pro__M05724 -1 0.398456 9743.44 1 5 CACCTG GCCTGACGACT + +4 transfac_public__M00080-ham-pnr-srp 6 0.398456 9743.44 1 5 CACCTG TTATCTTATCT - +4 cisbp__M6487-SREBP 7 0.398456 9743.44 1 4 CACCTG CTCACCCCACC - +4 taipale_cyt_meth__HOXC12_GGTAATAAAAN_eDBD-Abd-B-cad 7 0.398456 9743.44 1 4 CACCTG ATTTTATTACC - +4 tfdimers__MD00482-lz-run-RunxA-RunxB 15 0.399135 9760.05 1 6 CACCTG AAAAAAATGCAACCACACCAACAAC + +4 tfdimers__MD00118-nej 9 0.399135 9760.05 1 6 CACCTG ATTAATAATTAACTCCCTGTTTTAT - +4 cisbp__M1962-gem 7 0.399258 9763.05 1 6 CACCTG CTGGTTTGAACTGG + +4 cisbp__M2345 7 0.399258 9763.05 1 6 CACCTG AGAAGGTCACGTGG + +4 jaspar__MA0552.1 7 0.399258 9763.05 1 6 CACCTG GGAAGGTCACGTGG + +4 taipale_cyt_meth__ZNF282_NTTCCCMYNACACN_eDBD_meth_repr 8 0.399258 9763.05 1 6 CACCTG TTTCCCACAACACT + +4 transfac_pro__M07650-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 4 0.399258 9763.05 1 6 CACCTG TTGGCACGTGCCAA + +4 cisbp__M3960-bs 0 0.399258 9763.05 1 6 CACCTG GTCCTTATATGGAC - +4 cisbp__M5865 0 0.399258 9763.05 1 6 CACCTG TACTTCCTCTTTTT - +4 hocomoco__ZN282_HUMAN.H11MO.0.D 8 0.399258 9763.05 1 6 CACCTG TTTCCCATAACCCG - +4 neph__UW.Motif.0623 1 0.399258 9763.05 1 6 CACCTG TCACATTTCAGTTT - +4 taipale__NR2E1_full_RAGTCAANAAGTCA-tll 1 0.399258 9763.05 1 6 CACCTG TGACTTATTGACTT - +4 taipale_tf_pairs__TEAD4_SPIB_RGAATGCGGAAGTN_CAP_1-sd 0 0.399258 9763.05 1 6 CACCTG TACTTCCGCATTCC - +4 transfac_pro__M01103-twi 8 0.399258 9763.05 1 6 CACCTG GTGCACAACACATG - +4 transfac_pro__M01828 5 0.399258 9763.05 1 6 CACCTG ACCCATACATCAGT - +4 transfac_pro__M04627-CG9727-Rfx-SREBP 2 0.399258 9763.05 1 6 CACCTG GTTTCCCTAGCAAC - +4 neph__UW.Motif.0200 -2 0.399258 9763.05 1 4 CACCTG CCTGCCCAGACCCA + +4 transfac_pro__M06409 12 0.40086 9802.24 1 6 CACCTG TGAAGGGGACAGCACTTGT + +4 transfac_pro__M09378 1 0.40086 9802.24 1 6 CACCTG TAACGTGTAGAACAAGTAA + +4 hocomoco__KLF6_HUMAN.H11MO.0.A-CG3065-CG42741-Klf15-Nf-YA-Nf-YB-Pur-alpha-Spps-btd-cbt-dar1-hkb-luna-sr 1 0.40086 9802.24 1 6 CACCTG CCCCCGGCCCCGCCCTTCC - +4 tfdimers__MD00228-crp 11 0.401651 9821.57 1 6 CACCTG TTTTTCATTAGCAGCTGGTTAGAA - +4 hocomoco__HES7_HUMAN.H11MO.0.D-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 3 0.401995 9829.99 1 6 CACCTG TGGCACGTGCCG + +4 hocomoco__TEAD2_HUMAN.H11MO.0.D-sd 1 0.401995 9829.99 1 6 CACCTG CCACATTCCAGG + +4 hocomoco__TEAD2_MOUSE.H11MO.0.C-sd 1 0.401995 9829.99 1 6 CACCTG CCACATTCCAGG + +4 jaspar__MA0091.1-CG8319-HLH3B-HLH54F-amos 4 0.401995 9829.99 1 6 CACCTG CGACCATCTGTT + +4 scertf__foat.MIG1-klu-sr 2 0.401995 9829.99 1 6 CACCTG CTTACCCCACGG + +4 stark__TGGCACGTGYYA-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn 3 0.401995 9829.99 1 6 CACCTG TGGCACGTGCCA + +4 stark__TWTKACKTAANA-gt 3 0.401995 9829.99 1 6 CACCTG TATGACGTAAAA + +4 taipale_cyt_meth__MSC_NRACAGCTGTYN_FL_meth-ac-amos-ase-dimm-Fer3-HLH54F-l(1)sc-nau-sc 3 0.401995 9829.99 1 6 CACCTG CAACAGCTGTTG + +4 taipale_cyt_meth__MYOG_NAACANNTGTYN_FL-amos-dimm-Fer3-HLH54F-nau 3 0.401995 9829.99 1 6 CACCTG GAACAGCTGTCG + +4 taipale_cyt_meth__TCF21_NACCATATGKYN_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.401995 9829.99 1 6 CACCTG CACCATATGGCG + +4 transfac_pro__M01089-Kr-Kr-h2 2 0.401995 9829.99 1 6 CACCTG ATAACCCTTTTA + +4 transfac_pro__M01598-CG13775 6 0.401995 9829.99 1 6 CACCTG CAGGCTCGCCTG + +4 transfac_pro__M05834 6 0.401995 9829.99 1 6 CACCTG CGAAGCTACCGC + +4 transfac_pro__M06242 2 0.401995 9829.99 1 6 CACCTG CGAAGCTTGAGC + +4 neph__UW.Motif.0604 6 0.401995 9829.99 1 6 CACCTG TTCAGTTTCTTT - +4 taipale_cyt_meth__ELF1_NACCMGGAAGTN_FL_meth-aop-Eip74EF-Ets21C-Ets96B-Ets98B-Hr78 0 0.401995 9829.99 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__FOSB_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.401995 9829.99 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__FOXA1_NWRTGTAMAYAN_eDBD_meth-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxP-nej 5 0.401995 9829.99 1 6 CACCTG ATGTTTACATAA - +4 taipale_cyt_meth__MSC_NRNCATATGNYN_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.401995 9829.99 1 6 CACCTG CACCATATGGTG - +4 transfac_pro__M00746-Eip74EF 2 0.401995 9829.99 1 6 CACCTG ACTTCCTCTTAC - +4 transfac_pro__M03544-Atf3-Atf6-CrebA-CrebB-E2f1-Jra-maf-S-Xbp1 3 0.401995 9829.99 1 6 CACCTG GGTGACGTCAGC - +4 transfac_pro__M03789-Mondo 6 0.401995 9829.99 1 6 CACCTG CGGAGTCACGTG - +4 transfac_pro__M05663-CG10321-CG8089 6 0.401995 9829.99 1 6 CACCTG GAGCGGGCCCTG - +4 transfac_pro__M05711 2 0.401995 9829.99 1 6 CACCTG TGTACCGGAACG - +4 transfac_pro__M05760 6 0.401995 9829.99 1 6 CACCTG TCAGCAAACCCA - +4 transfac_pro__M06063 4 0.401995 9829.99 1 6 CACCTG TTTACACCAACT - +4 transfac_pro__M06108 5 0.401995 9829.99 1 6 CACCTG TCACCAACCAGG - +4 transfac_pro__M06241 5 0.401995 9829.99 1 6 CACCTG GCACCAACCCCG - +4 transfac_public__M00189-TfAP-2 0 0.401995 9829.99 1 6 CACCTG CGCCGGCGGGCG - +4 homer__NYYTGTTTACHN_FOXP1-FoxP-foxo-slp2 7 0.401995 9829.99 1 5 CACCTG TCCTGTTTACCA + +4 taipale_cyt_meth__GATA5_WGATAACGATCT_eDBD_meth-GATAe-grn-pnr-srp 7 0.401995 9829.99 1 5 CACCTG AGATAACGATCT + +4 taipale_tf_pairs__TEAD4_ERG_RSCGGAAATRCC_CAP_repr-Ets97D-sd -1 0.401995 9829.99 1 5 CACCTG ACCGGAAATGCC + +4 transfac_pro__M05519-erm 7 0.401995 9829.99 1 5 CACCTG GCTGCCAAACCG - +4 transfac_pro__M05666-CG6654-CG7372 7 0.401995 9829.99 1 5 CACCTG GCTTTCTCAACA - +4 transfac_pro__M05772 7 0.401995 9829.99 1 5 CACCTG TCAGCTTGACCG - +4 transfac_pro__M05963-CG6654-CG7372 7 0.401995 9829.99 1 5 CACCTG GCGTTCTCAACA - +4 transfac_pro__M06702-CG2120 8 0.401995 9829.99 1 4 CACCTG CAGACGAGGACC + +4 transfac_pro__M06155 8 0.401995 9829.99 1 4 CACCTG GATTACACCACG - +4 hocomoco__TF7L1_HUMAN.H11MO.0.B-pan 0 0.402103 9832.62 1 6 CACCTG TGCCTTTGATGTT + +4 neph__UW.Motif.0564 7 0.402103 9832.62 1 6 CACCTG CATGTGAAAAATG + +4 transfac_pro__M01279 7 0.402103 9832.62 1 6 CACCTG TTATTTTCGCTTT + +4 cisbp__M5968 3 0.402103 9832.62 1 6 CACCTG AAACATCTGGATT - +4 swissregulon__sacCer__FKH1-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd59A-fkh-foxo-slp1-slp2 6 0.402103 9832.62 1 6 CACCTG TTTGTTTACATTT - +4 taipale__ZNF238_DBD_NNTCCAGATGTKN_repr 3 0.402103 9832.62 1 6 CACCTG CAACATCTGGATT - +4 taipale_tf_pairs__FOXO1_ELK1_RSCGGATGTTRTN_CAP-foxo 3 0.402103 9832.62 1 6 CACCTG CACAACATCCGGC - +4 taipale_cyt_meth__NFAT5_NYGGAAANNTACN_eDBD-NFAT 9 0.402103 9832.62 1 4 CACCTG GTGGAAAGGTACG + +4 cisbp__M5525-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 10 0.402126 9833.19 1 6 CACCTG AATGGACTTTGACCCC + +4 neph__UW.Motif.0392 8 0.402126 9833.19 1 6 CACCTG AAGTCTGGATTCTCTG + +4 scertf__macisaac.THI2 2 0.402126 9833.19 1 6 CACCTG GGAAACTCTAAGAACT + +4 transfac_pro__M01443-abd-A-Antp-bsh-btn-lab-pb-Scr-Ubx 8 0.402126 9833.19 1 6 CACCTG GAGGTAATTACCTCAG + +4 transfac_pro__M02915-Ets98B 6 0.402126 9833.19 1 6 CACCTG GATAACATCCTAGTAG + +4 transfac_pro__M03125-Max-Myc 5 0.402126 9833.19 1 6 CACCTG CGGACCACGTGGTCCG + +4 transfac_public__M00205 2 0.402126 9833.19 1 6 CACCTG GGTACAAAATGTTCTG + +4 cisbp__M5862-Ets98B 3 0.402126 9833.19 1 6 CACCTG TGTTACTTCTTTCTGC - +4 neph__UW.Motif.0233 9 0.402126 9833.19 1 6 CACCTG AAATTTTTTCAACTTT - +4 neph__UW.Motif.0275 10 0.402126 9833.19 1 6 CACCTG GAAGGCAGGGCAGCTG - +4 neph__UW.Motif.0361 0 0.402126 9833.19 1 6 CACCTG TGCCTGTGGCCTCGGC - +4 taipale__HNF4A_DBD_RRGGTCAAAGTCCRNN-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 10 0.402126 9833.19 1 6 CACCTG AATGGACTTTGACCCC - +4 taipale_cyt_meth__MAF_NYGCTGAYGTCAGCRN_FL_meth-maf-S 5 0.402126 9833.19 1 6 CACCTG ATGCTGACATCAGCAA - +4 transfac_public__M00066-HLH3B 5 0.402126 9833.19 1 6 CACCTG GTCACCATCTGTTCGA - +4 transfac_public__M00288-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC 0 0.402126 9833.19 1 6 CACCTG TCTGTGATTGGTGGAT - +4 cisbp__M6403 1 0.403076 9856.42 1 6 CACCTG AGACATGCCCGGGCATGTCC + +4 dbcorrdb__EBF1__ENCSR000BGU_1__m1-kn 3 0.403076 9856.42 1 6 CACCTG AAGTCCCTGGGGACTTGAGG + +4 dbcorrdb__GTF3C2__ENCSR000DNY_1__m1-CG17209 13 0.403076 9856.42 1 6 CACCTG GTCAGGAGTTCGAGACCAGC + +4 dbcorrdb__POLR2A__ENCSR000AKZ_1__m2-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-svp 2 0.403076 9856.42 1 6 CACCTG CTTATCTGCCCCCGCCAGGG + +4 dbcorrdb__REST__ENCSR000BQP_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 2 0.403076 9856.42 1 6 CACCTG GGGCGCTGTCCATGGTGCTG + +4 dbcorrdb__SRF__ENCSR000BLK_1__m5-bs 10 0.403076 9856.42 1 6 CACCTG ACGCGCGGCGCCCCTGTTTA + +4 dbcorrdb__STAT5A__ENCSR000BQZ_1__m3-Stat92E 13 0.403076 9856.42 1 6 CACCTG AGAGAAGTCTCACTACCACA + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m7-Taf7 5 0.403076 9856.42 1 6 CACCTG GTTCTGTCCTGTTTTTCAAC + +4 dbcorrdb__ZNF143__ENCSR000EBW_1__m2-Hcf-Six4 13 0.403076 9856.42 1 6 CACCTG CGGGGGACTACACTTCCCAG + +4 homer__GGYAGCAYDTGCTDCCCNNN_EBNA1 5 0.403076 9856.42 1 6 CACCTG GGCAGCATATGCTACCCAGG + +4 jaspar__MA0376.1-bigmax-mio 7 0.403076 9856.42 1 6 CACCTG ATATTAGCACGTGCTTAGTC + +4 taipale_tf_pairs__HOXD12_EOMES_NNNACGANNNNNNTCGTNNN_CAP_repr 9 0.403076 9856.42 1 6 CACCTG TTTACGAGGAACCTCGTAAA + +4 dbcorrdb__CHD1__ENCSR000EBU_1__m3-Chd1 9 0.403076 9856.42 1 6 CACCTG TGCCGTCCTCCCCTTCTGCG - +4 dbcorrdb__EP300__ENCSR000AQB_1__m8-nej 8 0.403076 9856.42 1 6 CACCTG CCTCGCTACGCATGCTTTTT - +4 dbcorrdb__GTF2B__ENCSR000DOE_1__m2-TfIIB 9 0.403076 9856.42 1 6 CACCTG GTCGCCTTTTGCTTGGCGTC - +4 dbcorrdb__MYC__ENCSR000DLI_1__m2-Myc 6 0.403076 9856.42 1 6 CACCTG ACACCCTACCCCCCAGCACA - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m8-RpII215 10 0.403076 9856.42 1 6 CACCTG TACCCCTCTCAGCCTCCAAA - +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m5-egg 0 0.403076 9856.42 1 6 CACCTG ACCCTTTGACTGTGTTCAAT - +4 dbcorrdb__SMARCC2__ENCSR000EDL_1__m3-mor 3 0.403076 9856.42 1 6 CACCTG CTCTTGCGGGGTACGGCGTC - +4 dbcorrdb__TAF7__ENCSR000BNM_1__m4-Taf7 9 0.403076 9856.42 1 6 CACCTG CGGCTTCTCTACAAGGCAAT - +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m4-bon 7 0.403076 9856.42 1 6 CACCTG GTGGGAAACCCTTTAGCCGT - +4 transfac_pro__M01549-achi-hth-vis 9 0.403076 9856.42 1 6 CACCTG AAAATGTGACACATATGCAA - +4 transfac_pro__M04667-CHES-1-like-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 11 0.403076 9856.42 1 6 CACCTG TCATCTTTGTTTACTTTTAA - +4 yetfasco__YNL068C_830-CHES-1-like-FoxK-FoxL1-FoxP-croc-fd59A-fkh-foxo-slp2 11 0.403076 9856.42 1 6 CACCTG TCATCTTTGTTTACTTTTAA - +4 transfac_pro__M01497 16 0.403076 9856.42 1 4 CACCTG ATCTGCGGAAATTAAATACC + +4 transfac_pro__M00325-btd-CTCF-HDAC1-Sin3A-Spps 5 0.40417 9883.17 1 6 CACCTG TTCAGCACCTCGGAGAGCGCC + +4 taipale_tf_pairs__MYBL1_FIGLA_NCASSTGNNNNNNNNCSGTTR_CAP_repr-Myb 14 0.40417 9883.17 1 6 CACCTG TAACGGTCGCCCACCAGCTGT - +4 transfac_pro__M05255 16 0.40417 9883.17 1 5 CACCTG ACGCAACGGGGAGAACCACCA - +4 transfac_pro__M05991-CTCF 16 0.40417 9883.17 1 5 CACCTG TGGTTGTGGACTCCCCCACCA - +4 cisbp__M0793 1 0.404183 9883.48 1 6 CACCTG AGATCTAC + +4 cisbp__M0806 2 0.404183 9883.48 1 6 CACCTG AAGATCTG + +4 cisbp__M0978-ct 2 0.404183 9883.48 1 6 CACCTG TTGATCAC + +4 cisbp__M1663 2 0.404183 9883.48 1 6 CACCTG GGGACCAC + +4 jaspar__MA0979.1 0 0.404183 9883.48 1 6 CACCTG CGCCGCCC + +4 jaspar__MA1057.1 2 0.404183 9883.48 1 6 CACCTG TGTACGGT + +4 predrem__nrMotif2252 2 0.404183 9883.48 1 6 CACCTG ATATCCTT + +4 scertf__macisaac.GAT3 2 0.404183 9883.48 1 6 CACCTG ATAACATG + +4 scertf__zhu.TBF1 1 0.404183 9883.48 1 6 CACCTG AACCCTAA + +4 swissregulon__sacCer__GAT3 1 0.404183 9883.48 1 6 CACCTG AGATCTAC + +4 taipale_cyt_meth__MEOX2_NTCGTTAN_FL_meth-abd-A-Antp-bsh-btn-Dfd-Dll-en-eve-exex-ind-inv-lab-pb-Scr-Ubx-unpg 0 0.404183 9883.48 1 6 CACCTG GTCATTAA + +4 transfac_pro__M04868-nej 2 0.404183 9883.48 1 6 CACCTG ATTACATC + +4 transfac_pro__M09213 2 0.404183 9883.48 1 6 CACCTG AGAATCTG + +4 transfac_public__M00041-Jra 1 0.404183 9883.48 1 6 CACCTG TGACGTCA + +4 cisbp__M0190-SREBP 1 0.404183 9883.48 1 6 CACCTG TCACGCGA - +4 hdpi__SOCS4-Socs36E 2 0.404183 9883.48 1 6 CACCTG TCATCCCA - +4 predrem__nrMotif1820 2 0.404183 9883.48 1 6 CACCTG ATTCCCTA - +4 cisbp__M0049 -1 0.404183 9883.48 1 5 CACCTG ATCTTGCC + +4 cisbp__M0952-Optix-so 3 0.404183 9883.48 1 5 CACCTG TGATACCC + +4 jaspar__MA1081.1 3 0.404183 9883.48 1 5 CACCTG GTTGACCG - +4 predrem__nrMotif2480 4 0.404183 9883.48 1 4 CACCTG TTAGCACT + +4 cisbp__M0397 5 0.404183 9883.48 1 3 CACCTG GGGAGCAC + +4 tfdimers__MD00193-Eip74EF-Stat92E 12 0.40424 9884.89 1 6 CACCTG TTATTCATTTCCTTCCTTTTTT + +4 hocomoco__MAZ_HUMAN.H11MO.0.A-Brf-CG7368-CTCF-CoRest-Dif-Klf15-Rbbp5-SREBP-Spps-Spt20-btd-crol-ct-dl-klu-l(3)neo38-peb-sr-usp 12 0.40424 9884.89 1 6 CACCTG CCCCCCCCCCCCCCCCTCCCCC - +4 transfac_pro__M09385 16 0.40424 9884.89 1 6 CACCTG AAGAAGACAAATTCTACACGTA - +4 elemento__CATCCTG 1 0.40568 9920.1 1 6 CACCTG CATCCTG + +4 hdpi__TFEB-Mitf 1 0.40568 9920.1 1 6 CACCTG TCACGTG + +4 predrem__nrMotif1816 0 0.40568 9920.1 1 6 CACCTG AATCTTT + +4 transfac_pro__M05725-GATAe-grn-pnr-srp 1 0.40568 9920.1 1 6 CACCTG TTAACAG + +4 flyfactorsurvey__lola-PG_SANGER_2.5_FBgn0005630-lola 1 0.40568 9920.1 1 6 CACCTG TGAGCTT - +4 elemento__GGGACCC 2 0.40568 9920.1 1 5 CACCTG GGGACCC + +4 jaspar__MA0267.1-CG9609 -1 0.40568 9920.1 1 5 CACCTG ACCAGCA + +4 transfac_pro__M01616-CG9609 -1 0.40568 9920.1 1 5 CACCTG ACCAGCA + +4 cisbp__M0375 2 0.40568 9920.1 1 5 CACCTG TTCACTC - +4 cisbp__M2072-CG9609 -1 0.40568 9920.1 1 5 CACCTG ACCAGCA - +4 elemento__TGGTCAC 2 0.40568 9920.1 1 5 CACCTG GTGACCA - +4 transfac_pro__M04855 2 0.40568 9920.1 1 5 CACCTG GAAACTT - +4 hdpi__C1orf176 3 0.40568 9920.1 1 4 CACCTG AAATAGC + +4 predrem__nrMotif2378 3 0.40568 9920.1 1 4 CACCTG GGACATC + +4 predrem__nrMotif1544 -3 0.40568 9920.1 1 3 CACCTG CTTTCAA + +4 predrem__nrMotif533 -3 0.40568 9920.1 1 3 CACCTG CTGAACA + +4 cisbp__M0079 2 0.406283 9934.83 1 6 CACCTG TCAACGTTGA + +4 cisbp__M0293-CG7786-gt-Pdp1-vri 3 0.406283 9934.83 1 6 CACCTG TATTACGTAA + +4 cisbp__M1521-NFAT 3 0.406283 9934.83 1 6 CACCTG ATTTTCCATT + +4 flyfactorsurvey__HLHmgamma_SANGER_10_FBgn0002735-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn-dpn 1 0.406283 9934.83 1 6 CACCTG GCACGTGCCA + +4 homer__GCCACACCCA_Klf4-CG42741-cbt-dar1-luna 4 0.406283 9934.83 1 6 CACCTG GCCACACCCA + +4 jaspar__MA1070.1-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-E2f1-Jra-Xbp1-crc-kay 3 0.406283 9934.83 1 6 CACCTG GGTGACGTCA + +4 predrem__nrMotif102 2 0.406283 9934.83 1 6 CACCTG CTCCCCTTTG + +4 predrem__nrMotif2211 1 0.406283 9934.83 1 6 CACCTG AGAACTGTGA + +4 predrem__nrMotif2421 1 0.406283 9934.83 1 6 CACCTG TGTCCTCTTT + +4 predrem__nrMotif2568 2 0.406283 9934.83 1 6 CACCTG CCCACCCAAA + +4 predrem__nrMotif859 4 0.406283 9934.83 1 6 CACCTG TTGCTGCCTT + +4 taipale_cyt_meth__HEY2_NGCACGTGYN_eDBD-dpn-Hey-Sidpn 2 0.406283 9934.83 1 6 CACCTG GGCACGTGTC + +4 taipale_cyt_meth__SIX6_NYRTATCRYN_eDBD_meth-Optix-so 3 0.406283 9934.83 1 6 CACCTG GCGTATCACG + +4 taipale_cyt_meth__TEAD2_NRCATTCCWN_FL-sd 0 0.406283 9934.83 1 6 CACCTG CACATTCCAT + +4 transfac_pro__M00678-aop 1 0.406283 9934.83 1 6 CACCTG TTACTTCCTG + +4 transfac_public__M00484-C15 3 0.406283 9934.83 1 6 CACCTG CGGTAATTGG + +4 yetfasco__YBR150C_2179 3 0.406283 9934.83 1 6 CACCTG CGGATCCGCG + +4 cisbp__M0208-ac-ase-bigmax-cnc-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 1 0.406283 9934.83 1 6 CACCTG CCACGTGACC - +4 cisbp__M0253-Sidpn-dpn-h 2 0.406283 9934.83 1 6 CACCTG GACACGCGCC - +4 cisbp__M0365 1 0.406283 9934.83 1 6 CACCTG CACGCTGGCA - +4 cisbp__M0455 3 0.406283 9934.83 1 6 CACCTG AACTACCGTA - +4 cisbp__M0498 0 0.406283 9934.83 1 6 CACCTG AGGCTTTAAC - +4 cisbp__M0685-CG9650-ebi-nej 2 0.406283 9934.83 1 6 CACCTG ACTTCCTCTT - +4 cisbp__M0734-bin-bs-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-nej-slp1-slp2 4 0.406283 9934.83 1 6 CACCTG TGTTTACATA - +4 cisbp__M0818 3 0.406283 9934.83 1 6 CACCTG TGCGACATTT - +4 cisbp__M1794 3 0.406283 9934.83 1 6 CACCTG TATTTCCGGA - +4 fantom__motif150_AGCACAGGCG 0 0.406283 9934.83 1 6 CACCTG CGCCTGTGCT - +4 homer__AGAGGAAGTG_PU.1-CG9650-Dif-Stat92E-dl-nej-sv 0 0.406283 9934.83 1 6 CACCTG CACTTCCTCT - +4 homer__DGGGYGKGGC_KLF5-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-hkb-luna 4 0.406283 9934.83 1 6 CACCTG GCCACACCCT - +4 homer__GATGACGTCA_Atf1-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 1 0.406283 9934.83 1 6 CACCTG TGACGTCATC - +4 jaspar__MA0620.1-HLH3B-HLH4C-Hand-Max-Mitf-Myc-Usf-ac-ase-bigmax-cnc-l(1)sc-nau-sc 1 0.406283 9934.83 1 6 CACCTG CCACGTGACC - +4 neph__UW.Motif.0023 4 0.406283 9934.83 1 6 CACCTG CTGGGGGCTG - +4 predrem__nrMotif2043 2 0.406283 9934.83 1 6 CACCTG TTGCCCTGAG - +4 predrem__nrMotif2063 4 0.406283 9934.83 1 6 CACCTG GTGGGGCCTG - +4 predrem__nrMotif2552 4 0.406283 9934.83 1 6 CACCTG AGAGTACAAA - +4 taipale__ETV1_DBD_ACCGGAARYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.406283 9934.83 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M01231-lmd 0 0.406283 9934.83 1 6 CACCTG GACCCCCCAC - +4 transfac_pro__M05360-btd-cbt-Sp1-Spps 0 0.406283 9934.83 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M07261 1 0.406283 9934.83 1 6 CACCTG CCCCCACCCC - +4 transfac_pro__M07276-Bgb-Bro-lz-NFAT-run-RunxA-RunxB 1 0.406283 9934.83 1 6 CACCTG AAACCACAGA - +4 transfac_pro__M07454-ci-lmd-opa 1 0.406283 9934.83 1 6 CACCTG AGACCACCCA - +4 transfac_pro__M07563 1 0.406283 9934.83 1 6 CACCTG CCCTCTTTTT - +4 transfac_public__M00346-GATAe-grn-pnr 3 0.406283 9934.83 1 6 CACCTG TGTTATCTGC - +4 cisbp__M1784 5 0.406283 9934.83 1 5 CACCTG ATTATCTCCG + +4 predrem__nrMotif627 5 0.406283 9934.83 1 5 CACCTG CTGAAACCCA + +4 taipale__ETS1_DBD_ACCGGAARYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.406283 9934.83 1 5 CACCTG ACCGGAAGTG + +4 cisbp__M1560 5 0.406283 9934.83 1 5 CACCTG GTCCGTACAC - +4 cisbp__M1644 5 0.406283 9934.83 1 5 CACCTG GGGGGCACCA - +4 cisbp__M1682 5 0.406283 9934.83 1 5 CACCTG GCGTTGACCT - +4 cisbp__M1924-Dif-dl-Rel 5 0.406283 9934.83 1 5 CACCTG GGAAATCCCC - +4 cisbp__M3091-Dif-dl-Rel 5 0.406283 9934.83 1 5 CACCTG GGAAATCCCC - +4 jaspar__MA0101.1-Dif-Rel-dl 5 0.406283 9934.83 1 5 CACCTG GGAAATCCCC - +4 predrem__nrMotif2194 -1 0.406283 9934.83 1 5 CACCTG TTCTTCTTTT - +4 taipale_cyt_meth__FOXO4_NYGTAAACAN_eDBD-croc-FoxL1-foxo-slp2 5 0.406283 9934.83 1 5 CACCTG GTGTTTACGT - +4 taipale_cyt_meth__SIX2_MCGTATCAYN_FL-Optix-so 5 0.406283 9934.83 1 5 CACCTG GGTGATACGG - +4 taipale_cyt_meth__SIX2_NCGTATCRYN_eDBD_meth-Optix-so 5 0.406283 9934.83 1 5 CACCTG CACGATACGC - +4 transfac_public__M00053-Dif-dl-Rel 5 0.406283 9934.83 1 5 CACCTG GGAAATCCCC - +4 predrem__nrMotif2025 6 0.406283 9934.83 1 4 CACCTG TCACTTCACA + +4 taipale_cyt_meth__MEF2C_CCWWATWWRG_FL-bs-Mef2 -2 0.406283 9934.83 1 4 CACCTG CCAAATTTGG + +4 hocomoco__RFX3_MOUSE.H11MO.1.C-CG5846-CG9727-Max-Rfx -2 0.406283 9934.83 1 4 CACCTG CATGGCAACC - +4 predrem__nrMotif909 -2 0.406283 9934.83 1 4 CACCTG CCTTCCCGGC - +4 cisbp__M4101-Atf6-CrebA-Xbp1 5 0.408671 9993.23 1 6 CACCTG ATGATGACGTGTCCTAT + +4 transfac_pro__M03123-bigmax-Clk-cnc-Mitf-Mondo-SREBP-Usf 5 0.408671 9993.23 1 6 CACCTG AGAATCACGTGACAATT + +4 transfac_pro__M09370 0 0.408671 9993.23 1 6 CACCTG TACGTGTGGAACAAGCA + +4 transfac_public__M00251-Atf6-CrebA-Xbp1 5 0.408671 9993.23 1 6 CACCTG ATGATGACGTGTCCTAT + +4 hocomoco__ELF5_MOUSE.H11MO.0.A-Dif-Ets96B-dl 6 0.408671 9993.23 1 6 CACCTG TTCTTCTTCCTTCTTCC - +4 taipale_tf_pairs__HOXB13_EOMES_NNMRTAAANTMACACNN_CAP_repr 12 0.408671 9993.23 1 5 CACCTG CCAATAAAATCACACCT + +4 cisbp__M0041-Taf1 1 0.408726 9994.58 1 6 CACCTG CCGCCGCCA + +4 cisbp__M0346-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-cnc-crc-kay 2 0.408726 9994.58 1 6 CACCTG ATGACGTCA + +4 cisbp__M1770 2 0.408726 9994.58 1 6 CACCTG GGATCCGCG + +4 cisbp__M1830 2 0.408726 9994.58 1 6 CACCTG ATTCCCGAG + +4 fantom__motif148_NTCSYSTYT 0 0.408726 9994.58 1 6 CACCTG TTCGTGTTT + +4 predrem__nrMotif1439 0 0.408726 9994.58 1 6 CACCTG CTCCTTGTC + +4 predrem__nrMotif2599 0 0.408726 9994.58 1 6 CACCTG TTCCTAATG + +4 predrem__nrMotif460 2 0.408726 9994.58 1 6 CACCTG GCTTCCTTG + +4 transfac_pro__M02002-ham 0 0.408726 9994.58 1 6 CACCTG TATCTTGTC + +4 transfac_pro__M07058-acj6-nub-pdm2-SoxN-Tbp-vvl 3 0.408726 9994.58 1 6 CACCTG ATTTGCATA + +4 transfac_pro__M07341 1 0.408726 9994.58 1 6 CACCTG TGGGCTGGT + +4 cisbp__M5250-ttk 1 0.408726 9994.58 1 6 CACCTG CAACCCCTA - +4 hocomoco__PATZ1_HUMAN.H11MO.1.C 0 0.408726 9994.58 1 6 CACCTG CCCCTCCCT - +4 predrem__nrMotif1247 0 0.408726 9994.58 1 6 CACCTG AACATGGCA - +4 predrem__nrMotif1547 3 0.408726 9994.58 1 6 CACCTG TTGCACAAA - +4 predrem__nrMotif1607 3 0.408726 9994.58 1 6 CACCTG TCAAAGCTC - +4 predrem__nrMotif1696 0 0.408726 9994.58 1 6 CACCTG GAGCCGCGC - +4 predrem__nrMotif2024 0 0.408726 9994.58 1 6 CACCTG CTCCTATTT - +4 predrem__nrMotif2038 0 0.408726 9994.58 1 6 CACCTG CAACTGCCT - +4 predrem__nrMotif543 1 0.408726 9994.58 1 6 CACCTG GAACTTTCT - +4 predrem__nrMotif919 1 0.408726 9994.58 1 6 CACCTG TTATCTCAT - +4 taipale_cyt_meth__NKX2-3_NTCGTTGAN_eDBD_meth 2 0.408726 9994.58 1 6 CACCTG CTCAACGAC - +4 transfac_pro__M04819-bin-croc-fd59A-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 3 0.408726 9994.58 1 6 CACCTG GTTTACTTA - +4 transfac_pro__M05842-CG30020 1 0.408726 9994.58 1 6 CACCTG ACCCCTTCC - +4 transfac_pro__M04774-mor-Six4 4 0.408726 9994.58 1 5 CACCTG ACTACAACT + +4 cisbp__M5784 4 0.408726 9994.58 1 5 CACCTG GGATTATCC - +4 jaspar__MA1094.1 4 0.408726 9994.58 1 5 CACCTG CGTTGACCT - +4 predrem__nrMotif1081 4 0.408726 9994.58 1 5 CACCTG AGAAAATCT - +4 taipale__RHOXF1_full_GGMTNAKCC_repr 4 0.408726 9994.58 1 5 CACCTG GGATTATCC - +4 cisbp__M1118 5 0.408726 9994.58 1 4 CACCTG CTTAAAACC + +4 taipale_cyt_meth__YBX1_YGTWCCAYC_eDBD_repr-yps 5 0.408726 9994.58 1 4 CACCTG TGTACCATC + +4 predrem__nrMotif1037 5 0.408726 9994.58 1 4 CACCTG AAAATAACA - +4 hdpi__MRPL1-mRpL1 -3 0.408726 9994.58 1 3 CACCTG CTGTGAAAT + +4 predrem__nrMotif1151 -3 0.408726 9994.58 1 3 CACCTG CTGTTCCCT - +4 jaspar__MA0161.1-NfI 0 0.409606 10016.1 1 6 CACCTG TGCCAA - +4 yetfasco__YBL005W_1387 -1 0.409606 10016.1 1 5 CACCTG TCCGCG + +4 fantom__motif14_TCNACG 2 0.409606 10016.1 1 4 CACCTG TCAACG + +4 fantom__motif28_CGTNCA 2 0.409606 10016.1 1 4 CACCTG TGAACG - +4 scertf__badis.YPR022C 3 0.409606 10016.1 1 3 CACCTG CCCCAC + +4 cisbp__M4678-CG5846-CG9727-Max-Rfx-SREBP 2 0.409742 10019.4 1 6 CACCTG GTCGCCATGGCAACC + +4 neph__UW.Motif.0527 4 0.409742 10019.4 1 6 CACCTG GAAATTCCTTTTCCA + +4 swissregulon__sacCer__THI2 2 0.409742 10019.4 1 6 CACCTG GGAAACTGTAAGAAC + +4 taipale_tf_pairs__E2F3_FOXI1_NNMCACCGCGCCCMN_CAP_repr-E2f1 3 0.409742 10019.4 1 6 CACCTG TGACACCGCGCCCAC + +4 transfac_pro__M01168-SREBP 5 0.409742 10019.4 1 6 CACCTG CCGCTCACCCCACGG + +4 transfac_pro__M08865-Bgb-Bro-lz-run-RunxA-RunxB 4 0.409742 10019.4 1 6 CACCTG CGCAAACCACAGAGG + +4 transfac_pro__M09049 8 0.409742 10019.4 1 6 CACCTG TCTTTGCCGACATCA + +4 cisbp__M4666-Klf15-klu 4 0.409742 10019.4 1 6 CACCTG CCTCTCCCTCCTCCC - +4 cisbp__M6117 9 0.409742 10019.4 1 6 CACCTG GCATGTCCCGACATG - +4 neph__UW.Motif.0621 2 0.409742 10019.4 1 6 CACCTG GTCAGCATTTTTTTT - +4 taipale_tf_pairs__ERF_MAX_RSCGGAANCACGTGN_CAP_repr-Ets21C-Max 1 0.409742 10019.4 1 6 CACCTG CCACGTGTTTCCGGT - +4 transfac_pro__M01788-bs 0 0.409742 10019.4 1 6 CACCTG TTCCTATTTGGGAAA - +4 transfac_pro__M02827-CG12071 0 0.409742 10019.4 1 6 CACCTG CTCTTGTTGTTTGTT - +4 transfac_pro__M07830-so 3 0.409742 10019.4 1 6 CACCTG TGATACCTATGATAC - +4 transfac_pro__M09325 7 0.409742 10019.4 1 6 CACCTG TATCCGTTACATTTT - +4 transfac_pro__M09379 0 0.409742 10019.4 1 6 CACCTG TGCTTGTTTTACACG - +4 cisbp__M4499-Dif-dl-Rel-shn 10 0.409742 10019.4 1 5 CACCTG CCTTGGAAATCCCCT - +4 cisbp__M6489-bs -1 0.409742 10019.4 1 5 CACCTG TCCATATATGGGCAT - +4 neph__UW.Motif.0648 10 0.409742 10019.4 1 5 CACCTG TAAGAAAAAATTGCT - +4 cisbp__M4476 -2 0.409742 10019.4 1 4 CACCTG CCTAGCAACAGGTGA - +4 cisbp__M4723-ab 12 0.412895 10096.5 1 6 CACCTG TTTTTTGAATGGGTCCTGGCGTGGGG + +4 c2h2_zfs__M3867-ab 12 0.412895 10096.5 1 6 CACCTG TTTTTTGAATGGGTCCTGGCGTGGGG - +4 tfdimers__MD00138 5 0.412895 10096.5 1 6 CACCTG AAAAAGAACTGAAAGTGAAAGAAAAA - +4 taipale_tf_pairs__RFX3_HES7_NRGCAACNNNCRCGYGNN_CAP_repr-Rfx 4 0.413675 10115.6 1 6 CACCTG TGGCAACGGGCACGTGCG + +4 transfac_pro__M01061-Mef2 2 0.413675 10115.6 1 6 CACCTG GTTACCATAAATGGAAAG + +4 transfac_pro__M09513-Atf6-CrebA-Xbp1 8 0.413675 10115.6 1 6 CACCTG AAAAATGCCACGTGACCA + +4 transfac_public__M00281-CG5846-CG9727-Max-Rfx-SREBP 12 0.413675 10115.6 1 6 CACCTG TAGTAGCCATGGCAACAA + +4 cisbp__M4601-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-svp 3 0.413675 10115.6 1 6 CACCTG CCTTATCTGCCCCCCCCA - +4 cisbp__M5888-bi-byn 14 0.413675 10115.6 1 4 CACCTG GGTGTGAAATTTCACACC - +4 taipale__TBX2_full_GGTGTNANWWNTNACACC-bi-byn 14 0.413675 10115.6 1 4 CACCTG GGTGTGAAATTTCACACC - +4 flyfactorsurvey__Sox14_SANGER_10_FBgn0005612-Sox14 0 0.414092 10125.8 1 6 CACCTG CTCCTTTGTCC + +4 jaspar__MA0589.1 2 0.414092 10125.8 1 6 CACCTG TTGACCGAGCC + +4 neph__UW.Motif.0028 2 0.414092 10125.8 1 6 CACCTG CAGCCCTGGCA + +4 predrem__nrMotif1711 3 0.414092 10125.8 1 6 CACCTG CGCTCCCTCCC + +4 transfac_pro__M00930-acj6-nub-pdm2-vvl 5 0.414092 10125.8 1 6 CACCTG TGATTTGCATA + +4 transfac_pro__M08873 1 0.414092 10125.8 1 6 CACCTG ACGCCTGACGG + +4 transfac_pro__M08941-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.414092 10125.8 1 6 CACCTG GATGACGTCAT + +4 transfac_pro__M09580-Atf3-Atf6-CrebA-CrebB-Jra-kay-maf-S-Xbp1 1 0.414092 10125.8 1 6 CACCTG TTACGTCACCA + +4 cisbp__M2382 2 0.414092 10125.8 1 6 CACCTG TTGACCGAGCC - +4 cisbp__M5857-Ets96B-Ets98B 0 0.414092 10125.8 1 6 CACCTG TACATCCGGGT - +4 cisbp__M6120-ci-lmd-opa-sug 4 0.414092 10125.8 1 6 CACCTG GGACCACCCAG - +4 cisbp__M6416-Bgb-Bro-CG9650-ebi-E(z)-foxo-lz-MTA1-like-NFAT-run-RunxA-RunxB-Stat92E 2 0.414092 10125.8 1 6 CACCTG CAAACCACAGA - +4 hocomoco__PEBB_HUMAN.H11MO.0.C-Bgb-Bro-CG9650-E(z)-MTA1-like-NFAT-RunxA-RunxB-Stat92E-ebi-foxo-lz-run 2 0.414092 10125.8 1 6 CACCTG CTAACCACAGA - +4 taipale__SPDEF_DBD_AMCCGGATGTN_repr-Ets96B-Ets98B 0 0.414092 10125.8 1 6 CACCTG TACATCCGGGT - +4 taipale_cyt_meth__ETV4_NRCMGGAAGTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.414092 10125.8 1 6 CACCTG TACTTCCGGTC - +4 taipale_cyt_meth__FOXL2_NAYRTMAACAN_FL-bin-croc-FoxK-FoxL1-foxo-slp1-slp2 5 0.414092 10125.8 1 6 CACCTG TTGTTTACGTT - +4 transfac_pro__M05587 5 0.414092 10125.8 1 6 CACCTG GCTTTAGCCCG - +4 transfac_pro__M09470 5 0.414092 10125.8 1 6 CACCTG GCGTTGACTTT - +4 taipale_cyt_meth__GATA3_NGATAAGATCW_FL_repr-GATAd-GATAe-grn-pnr-srp 6 0.414092 10125.8 1 5 CACCTG AGATAAGATCT + +4 cisbp__M4506-bon-cnc-Jra-kay-Mef2-mor-Myc-nej-pan 6 0.414092 10125.8 1 5 CACCTG ATGACTCACCC - +4 cisbp__M4619-bon-CoRest-Jra-kay-Mef2-mor-Myc-pan 6 0.414092 10125.8 1 5 CACCTG ATGAGTCACCC - +4 transfac_public__M00043-Dif-dl 6 0.414092 10125.8 1 5 CACCTG GGGAAAAACCC - +4 hocomoco__NFKB1_MOUSE.H11MO.0.A-CG12018-Dif-Rel-dl-shn 7 0.414092 10125.8 1 4 CACCTG GGGAAATTCCC + +4 hocomoco__SRBP1_MOUSE.H11MO.0.B-SREBP 7 0.414092 10125.8 1 4 CACCTG CTCACCCCACC - +4 cisbp__M5037-Hr83 8 0.415126 10151.1 1 6 CACCTG GCTACTGTGACTTT + +4 cisbp__M5675-tll 1 0.415126 10151.1 1 6 CACCTG TGACTTATTGACTT + +4 cisbp__M6459-lz-run-RunxA-RunxB 0 0.415126 10151.1 1 6 CACCTG AACCACAAACCCCC + +4 jaspar__MA0580.1-Usf 7 0.415126 10151.1 1 6 CACCTG CGTGAGTCACGTGA + +4 neph__UW.Motif.0437 8 0.415126 10151.1 1 6 CACCTG AAGAAAAGGACTTG + +4 taipale_cyt_meth__FERD3L_GYNNCAGCTGNNAC_FL_meth-ac-amos-ase-da-dimm-Fer3-HLH54F-l(1)sc-nau-sc 4 0.415126 10151.1 1 6 CACCTG GCAACAGCTGTTAC + +4 transfac_pro__M02034-scro 3 0.415126 10151.1 1 6 CACCTG GAGCACTTGAGAGC + +4 cisbp__M6096-aop 0 0.415126 10151.1 1 6 CACCTG TACTTCCGCTTTTT - +4 flyfactorsurvey__Hr83_SANGER_5_FBgn0037436-Hr83 8 0.415126 10151.1 1 6 CACCTG GCTACTGTGACTTT - +4 neph__UW.Motif.0618 0 0.415126 10151.1 1 6 CACCTG CATCTTCCCACTGG - +4 taipale_tf_pairs__ELK1_TBX21_TNRCACCGGAAGNN_CAP 3 0.415126 10151.1 1 6 CACCTG CACTTCCGGTGTGA - +4 taipale_tf_pairs__ETV2_FOXI1_TGTTKMCGGAWRTN_CAP-pnt 0 0.415126 10151.1 1 6 CACCTG CACTTCCGTCAACA - +4 taipale_tf_pairs__NR1I2_RGTTCRNNNRGTTC_HT-EcR 1 0.415126 10151.1 1 6 CACCTG GAACTCGATGAACT - +4 transfac_pro__M04741-CG5846-CG9727-Max-Rfx-SREBP 2 0.415126 10151.1 1 6 CACCTG GTCGCCATGGCAAC - +4 transfac_pro__M09034 4 0.415126 10151.1 1 6 CACCTG CCTCCACCGTCCAT - +4 transfac_pro__M09036 4 0.415126 10151.1 1 6 CACCTG CCTCCACCGACCAT - +4 neph__UW.Motif.0237 9 0.415126 10151.1 1 5 CACCTG TTCCAGATTTCCCA - +4 taipale_tf_pairs__GCM1_FOXI1_NTGTTGATRNGGGN_CAP_repr-gcm-gcm2 -1 0.415126 10151.1 1 5 CACCTG GCCCGCATCAACAC - +4 neph__UW.Motif.0627 -3 0.415126 10151.1 1 3 CACCTG CTGCAGAAAAAAAG + +4 transfac_public__M00200 6 0.416104 10175 1 6 CACCTG ACCAATCAACTCGCTTCTCGCTTCT + +4 transfac_pro__M01001-Deaf1 12 0.416104 10175 1 6 CACCTG CTACTCCGGAAATACCCGAGGGCGG - +4 taipale_tf_pairs__ERF_EOMES_RRGTGTKNNNNNNNNNNNNNNCMGGANNN_CAP-Ets21C 24 0.416698 10189.5 1 5 CACCTG ACTTCCGGTGACAAATCGTTTTCACACCT - +4 cisbp__M3710-Poxm-sv 7 0.417289 10204 1 6 CACCTG GCCATCATGCGTGACGAGG + +4 cisbp__M5909-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.417747 10215.2 1 6 CACCTG TATTACGTAACA + +4 cisbp__M6500-HLH3B 3 0.417747 10215.2 1 6 CACCTG GACCATCTGTTC + +4 flyfactorsurvey__br-PAPL_SOLEXA_5-br 3 0.417747 10215.2 1 6 CACCTG ACCATCCTAGTG + +4 hocomoco__FOXO1_HUMAN.H11MO.0.A-fkh-foxo 0 0.417747 10215.2 1 6 CACCTG TTCCTGTTTACT + +4 homer__ACTTTCACTTTC_PRDM1-Blimp-1 5 0.417747 10215.2 1 6 CACCTG ACTTTCACTTTC + +4 predrem__nrMotif379 0 0.417747 10215.2 1 6 CACCTG TTTCTTCCATTT + +4 swissregulon__sacCer__MET32 0 0.417747 10215.2 1 6 CACCTG AAACTGTGGCGC + +4 taipale__MYBL1_DBD_ACNGTTAAACNG_repr-Myb 6 0.417747 10215.2 1 6 CACCTG ACCGTTAAACGG + +4 taipale__TEF_DBD_NRTTACRTAAYN-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.417747 10215.2 1 6 CACCTG TATTACGTAACA + +4 taipale_cyt_meth__CREB3L1_TGCCACGTCAYN_eDBD-Atf6-CrebA-Xbp1 3 0.417747 10215.2 1 6 CACCTG TGCCACGTCACC + +4 tiffin__TIFDMEM0000029 3 0.417747 10215.2 1 6 CACCTG ATTTTTCTAAAA + +4 transfac_pro__M01145-Max-Myc 3 0.417747 10215.2 1 6 CACCTG AACCACGTGCTC + +4 transfac_pro__M01154-Clk-cyc-emc-E(spl)m3-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Max-Mitf-Mnt-Mondo-Myc-tgo-Usf 3 0.417747 10215.2 1 6 CACCTG GACCACGTGGTC + +4 transfac_pro__M01224-Dif-dl-Rel 6 0.417747 10215.2 1 6 CACCTG GGAATTTCCCAC + +4 transfac_pro__M05621 6 0.417747 10215.2 1 6 CACCTG GGTTACAACCGA + +4 transfac_pro__M06288 5 0.417747 10215.2 1 6 CACCTG GTGTACACCAGA + +4 cisbp__M4985-gl 2 0.417747 10215.2 1 6 CACCTG AATCCTTCAAAT - +4 cisbp__M6449-Dif-dl-Rel-shn 6 0.417747 10215.2 1 6 CACCTG GGGAAATCCCCA - +4 flyfactorsurvey__gl_FlyReg_FBgn0004618-gl 2 0.417747 10215.2 1 6 CACCTG TATCCTTGAAAT - +4 hocomoco__GLI1_HUMAN.H11MO.0.D-ci-lmd-opa-sug 4 0.417747 10215.2 1 6 CACCTG AGACCACCCAGG - +4 hocomoco__HES5_HUMAN.H11MO.0.D-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 3 0.417747 10215.2 1 6 CACCTG CGGCACGTGCCA - +4 swissregulon__hs__GLI1..3.p2-ci-lmd-opa-sug 4 0.417747 10215.2 1 6 CACCTG GGACCACCCAGA - +4 swissregulon__sacCer__YPR015C 6 0.417747 10215.2 1 6 CACCTG AGGATTTACGTC - +4 taipale_cyt_meth__CREB3L1_TGCCACGTCAYN_FL-Atf6-CrebA-Xbp1 3 0.417747 10215.2 1 6 CACCTG GGTGACGTGGCA - +4 taipale_cyt_meth__FOSL1_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.417747 10215.2 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__POU3F4_NTATGCGCATAN_eDBD-nub-pdm2-vvl 5 0.417747 10215.2 1 6 CACCTG TTATGCGCATAC - +4 taipale_tf_pairs__ELK1_FOXI1_RSCGGATGTKKN_CAP 1 0.417747 10215.2 1 6 CACCTG TAAACTTCCGGT - +4 tiffin__TIFDMEM0000117 1 0.417747 10215.2 1 6 CACCTG TCCACTTCAAAT - +4 transfac_pro__M06160 2 0.417747 10215.2 1 6 CACCTG GCAACCTCATCT - +4 transfac_pro__M06238-CG2120 6 0.417747 10215.2 1 6 CACCTG TATGACCACATG - +4 transfac_pro__M06477 5 0.417747 10215.2 1 6 CACCTG GGGGCAACCGGC - +4 transfac_pro__M06680 6 0.417747 10215.2 1 6 CACCTG TCCGATTACCCG - +4 transfac_public__M00532 4 0.417747 10215.2 1 6 CACCTG GAAACATCTGGA - +4 hocomoco__HXC12_HUMAN.H11MO.0.D-Abd-B-cad-eve 7 0.417747 10215.2 1 5 CACCTG TTTTTATGACCT + +4 transfac_pro__M05364 7 0.417747 10215.2 1 5 CACCTG GATTCTTGACCC - +4 transfac_pro__M05628 7 0.417747 10215.2 1 5 CACCTG GGGGCCGGACCG - +4 transfac_pro__M05727 7 0.417747 10215.2 1 5 CACCTG TATTTTTTAACT - +4 transfac_pro__M06189 7 0.417747 10215.2 1 5 CACCTG TCTGCCCTACCA - +4 transfac_pro__M06324 7 0.417747 10215.2 1 5 CACCTG AATCCGGCAACA - +4 transfac_pro__M06375 7 0.417747 10215.2 1 5 CACCTG GGTTTCGTATCT - +4 transfac_pro__M06513 7 0.417747 10215.2 1 5 CACCTG GCGGCCCAACCC - +4 transfac_pro__M06748 7 0.417747 10215.2 1 5 CACCTG TCGGACTTACCA - +4 transfac_pro__M05432 8 0.417747 10215.2 1 4 CACCTG TGGCGGCGTACC + +4 transfac_pro__M05558-CG11456-CG1233-CG32767-CG43347 8 0.417747 10215.2 1 4 CACCTG TTGGGCAAGACC + +4 cisbp__M2681-Atf6-CrebA-CrebB-Xbp1 8 0.417747 10215.2 1 4 CACCTG GGCCACGTCACC - +4 transfac_pro__M05789 -2 0.417747 10215.2 1 4 CACCTG CCTCATTAAACT - +4 transfac_public__M00358-Atf6-CrebA-CrebB-Xbp1 8 0.417747 10215.2 1 4 CACCTG GGCCACGTCACC - +4 neph__UW.Motif.0182 -3 0.417747 10215.2 1 3 CACCTG CTCTGTTTTCTT - +4 taipale_tf_pairs__TEAD4_ELK1_RMATWCCGGAWRN_CAP_repr-sd 3 0.417927 10219.6 1 6 CACCTG ACATACCGGAAGT + +4 yetfasco__YLR256W_2078 7 0.417927 10219.6 1 6 CACCTG CCGATAACTCCGG + +4 taipale_tf_pairs__ETV5_FOXO1_RNCGGATGTTKWN_CAP-Ets96B-foxo 3 0.417927 10219.6 1 6 CACCTG GACAACATCCGCT - +4 transfac_pro__M07604-ham 1 0.417927 10219.6 1 6 CACCTG TTATCTTGTCATT - +4 transfac_pro__M09145 7 0.417927 10219.6 1 6 CACCTG AGATCTAGATCTA - +4 idmmpmm__slp1-slp1 8 0.417927 10219.6 1 5 CACCTG GGTGTGTTTACAT + +4 taipale_tf_pairs__POU2F1_ELK1_NCCGGATATGCAN_CAP_repr-nub-pdm2 -1 0.417927 10219.6 1 5 CACCTG ACCGGATATGCAA + +4 neph__UW.Motif.0225 8 0.417927 10219.6 1 5 CACCTG GATGAATTATTCT - +4 cisbp__M3452 9 0.417927 10219.6 1 4 CACCTG TACTGGGAATACC + +4 transfac_public__M00088 9 0.417927 10219.6 1 4 CACCTG TCCTGGGAATACC + +4 cisbp__M2344-Atf6-Clk-CrebA-Met 5 0.418268 10227.9 1 6 CACCTG AATGCCACGTGGCATT + +4 cisbp__M5528-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 10 0.418268 10227.9 1 6 CACCTG ATTGGACTTTGACCCC + +4 taipale_cyt_meth__FLI1_NACCGGATATCCGGTN_eDBD_meth-Ets21C-Ets97D 0 0.418268 10227.9 1 6 CACCTG AACCGGATATCCGGTT + +4 taipale_cyt_meth__MAFG_NYGCTGAYRTCAGCRN_eDBD-CrebA-CrebB-maf-S 5 0.418268 10227.9 1 6 CACCTG TTGCTGACGTCAGCAA + +4 taipale_tf_pairs__CLOCK_EVX1_CACGTGNNNTAATKAT_CAP_repr-Clk-eve 0 0.418268 10227.9 1 6 CACCTG CACGTGTGGTAATGAT + +4 transfac_pro__M01317 1 0.418268 10227.9 1 6 CACCTG TAAGCTCGTAAAATTT + +4 bergman__grh-grh 6 0.418268 10227.9 1 6 CACCTG CCGCAAAACCAGTTAA - +4 hocomoco__ETV2_HUMAN.H11MO.0.B-Eip74EF-Ets65A-Ets96B-Ets97D-pnt 5 0.418268 10227.9 1 6 CACCTG CCCACTTCCTGTTTCC - +4 neph__UW.Motif.0204 9 0.418268 10227.9 1 6 CACCTG TGGCTTTTGTCTCTGC - +4 neph__UW.Motif.0315 4 0.418268 10227.9 1 6 CACCTG TTAGCAGCAGAGGCAG - +4 taipale__SPDEF_DBD_NCAGNAAGAMGTAWMM_repr-Ets98B 3 0.418268 10227.9 1 6 CACCTG GTATACTTCTTACTGC - +4 taipale__SPDEF_full_NCAGNAAGAMGTAWMM-Ets98B 3 0.418268 10227.9 1 6 CACCTG TGTTACTTCTTTCTGC - +4 taipale_tf_pairs__GCM1_ONECUT2_RTGCGGGNNNTCGATR_CAP-gcm-gcm2-onecut 7 0.418268 10227.9 1 6 CACCTG TATCGATTTCCCGCAT - +4 transfac_public__M00065-HLH3B 5 0.418268 10227.9 1 6 CACCTG CCGACCATCTGTTCAG - +4 taipale__TFCP2_full_NCCGGNNNNNNCCGGN_repr-gem -1 0.418268 10227.9 1 5 CACCTG ACCGGTTTAAACCGGT - +4 taipale_tf_pairs__FOXJ3_TBX21_NNGYGNNNNNNNNWAACAACACNN_CAP_repr 19 0.418571 10235.3 1 5 CACCTG AAGTGTTAATAAATAACAACACCT + +4 cisbp__M0919-bcd-Gsc-oc-Ptx1 2 0.419524 10258.6 1 6 CACCTG TTAATCCC + +4 elemento__AACCGGTT-grh 0 0.419524 10258.6 1 6 CACCTG AACCGGTT + +4 jaspar__MA0967.1-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay-maf-S 1 0.419524 10258.6 1 6 CACCTG TGACGTCA + +4 neph__UW.Motif.0087 0 0.419524 10258.6 1 6 CACCTG GCCCTCTA + +4 predrem__nrMotif1835 0 0.419524 10258.6 1 6 CACCTG CTCCTTAG + +4 predrem__nrMotif733 1 0.419524 10258.6 1 6 CACCTG GGATCTGC + +4 predrem__nrMotif932 2 0.419524 10258.6 1 6 CACCTG TCCATCTC + +4 taipale_cyt_meth__VSX1_NTCGTTAN_eDBD_meth-CG4328-Lim3-Lmx1a-Vsx1-Vsx2 0 0.419524 10258.6 1 6 CACCTG CTCGTTAA + +4 cisbp__M0347-Atf6-CrebB-Jra-REPTOR-BP-kay 1 0.419524 10258.6 1 6 CACCTG TTACGTCA - +4 jaspar__MA0328.2 2 0.419524 10258.6 1 6 CACCTG ATTACACG - +4 predrem__nrMotif2212 0 0.419524 10258.6 1 6 CACCTG AACTTACA - +4 transfac_pro__M01710 1 0.419524 10258.6 1 6 CACCTG TTAGCTGA - +4 transfac_pro__M09157 1 0.419524 10258.6 1 6 CACCTG CTACTACT - +4 fantom__motif108_AACKSARM -1 0.419524 10258.6 1 5 CACCTG AACGGAGA + +4 jaspar__MA1068.1-CrebB-Xbp1 -1 0.419524 10258.6 1 5 CACCTG ACGTCATC + +4 predrem__nrMotif33 -1 0.419524 10258.6 1 5 CACCTG ACCACCCT + +4 transfac_pro__M05028 3 0.419524 10258.6 1 5 CACCTG ATCAACCA + +4 cisbp__M1696 3 0.419524 10258.6 1 5 CACCTG GTTGACTT - +4 cisbp__M5476-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.419524 10258.6 1 5 CACCTG TCTTATCT - +4 predrem__nrMotif2225 -1 0.419524 10258.6 1 5 CACCTG AGCTCTAA - +4 taipale__GATA3_DBD_AGATAANN_repr-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.419524 10258.6 1 5 CACCTG TCTTATCT - +4 predrem__nrMotif1721 -2 0.419524 10258.6 1 4 CACCTG CCTAAGCC + +4 predrem__nrMotif1900 4 0.419524 10258.6 1 4 CACCTG GATTTACT - +4 transfac_pro__M04734-CTCF -2 0.419524 10258.6 1 4 CACCTG CCTCTAGT - +4 predrem__nrMotif2549 -3 0.419524 10258.6 1 3 CACCTG CTACATAA - +4 dbcorrdb__BCL3__ENCSR000BNQ_1__m2 14 0.419644 10261.5 1 6 CACCTG CACAGACACTCACACACATG + +4 dbcorrdb__BHLHE40__ENCSR000EDT_1__m1-Brf-brm-btd-cnc-CrebB-CTCF-cyc-E2f1-E(z)-h-HDAC1-Max-Myc-Nelf-E-RpII215-Sin3A-Spps-tai-tgo-tna-Usf 11 0.419644 10261.5 1 6 CACCTG CCCCCCCCGGTCACGTGCCC + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m4 4 0.419644 10261.5 1 6 CACCTG CCCCCACATTTGGGAAAAGC + +4 dbcorrdb__EZH2__ENCSR000ATA_1__m3-E(z) 11 0.419644 10261.5 1 6 CACCTG CAGCGCCTCGCGACCCGCGG + +4 dbcorrdb__JUN__ENCSR000ECA_1__m2-Jra 13 0.419644 10261.5 1 6 CACCTG AGACACGGCCGCATTCCTGA + +4 dbcorrdb__MYC__ENCSR000DOM_1__m1-Max-Myc 11 0.419644 10261.5 1 6 CACCTG TAAATACAAACCACATGGTT + +4 dbcorrdb__SUZ12__ENCSR000EUQ_1__m1-Su(z)12 1 0.419644 10261.5 1 6 CACCTG CCACATGCACGCGCAGAAGC + +4 dbcorrdb__TBP__ENCSR000EHA_1__m3-Bdp1-Brf-CG17209-ebi-Tbp 10 0.419644 10261.5 1 6 CACCTG ACCACTCCGCCACCGGGCCG + +4 dbcorrdb__ZNF143__ENCSR000DZL_1__m2-Hcf-mor-Six4 13 0.419644 10261.5 1 6 CACCTG GGGGGGACTACAATTCCCAG + +4 homer__AGTAAACAAAAAAGAACANA_FOXA1_AR-fkh 14 0.419644 10261.5 1 6 CACCTG AGTAAACAAAAAAGAACATA + +4 dbcorrdb__CBX3__ENCSR000BRT_1__m4-HP1b-HP1c-HP1e-Su(var)205 5 0.419644 10261.5 1 6 CACCTG ATTGTCCTCTTGTGGCTGCT - +4 dbcorrdb__CHD1__ENCSR000EFC_1__m1-Chd1-CTCF-SMC3-usp-vtd 4 0.419644 10261.5 1 6 CACCTG GGGCCACCCGACGGCGGCGG - +4 dbcorrdb__EP300__ENCSR000AQB_1__m3-nej 10 0.419644 10261.5 1 6 CACCTG GCGGAGTGTCCGCCTTAGAG - +4 dbcorrdb__EP300__ENCSR000BLM_1__m3-GATAe-grh-grn-nej-pnr 9 0.419644 10261.5 1 6 CACCTG AACCTGCCAAACCTGTTTGC - +4 dbcorrdb__EZH2__ENCSR000ARH_1__m9-E(z)-RpII215 5 0.419644 10261.5 1 6 CACCTG GTCTGCGCTTGCGCGGCGTC - +4 dbcorrdb__MXI1__ENCSR000EFE_1__m1-Clk-E2f1-ERR-E(z)-gce-Hcf-Max-Mnt-Myc-RpII215-Sap30-Sin3A-tna-Usf 9 0.419644 10261.5 1 6 CACCTG CGCGCGGACCACGTGGCCGC - +4 dbcorrdb__RFX5__ENCSR000EFD_1__m2 7 0.419644 10261.5 1 6 CACCTG CTCACTAATCCTGGGGGCAC - +4 dbcorrdb__SIRT6__ENCSR000DOH_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 7 0.419644 10261.5 1 6 CACCTG GCGCCCTTATCTGTCGCGCC - +4 dbcorrdb__SP4__ENCSR000BQV_1__m1-btd-cnc-E2f1-Max-Myc-Spps-Usf 8 0.419644 10261.5 1 6 CACCTG CCCGGCGTCGCGTGACCGGA - +4 dbcorrdb__TCF7L2__ENCSR000EUY_1__m1-pan 5 0.419644 10261.5 1 6 CACCTG AGCGGTCCCTTTGATGTTTC - +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m5-bon 11 0.419644 10261.5 1 6 CACCTG GCTAGAGGTCATGCCTGAGT - +4 dbcorrdb__TRIM28__ENCSR000EYC_1__m1-bon-Jra-kay 8 0.419644 10261.5 1 6 CACCTG GTATGAGTCATCTGCTGTCA - +4 taipale_cyt_meth__PRDM4_YRRCRGTTTCRAGKSYNCCC_eDBD_meth_repr 4 0.419644 10261.5 1 6 CACCTG GGGGAGCCTTGAAACCGCCG - +4 transfac_pro__M01533-bin-CHES-1-like-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 11 0.419644 10261.5 1 6 CACCTG TCATCTTTGTTTACTTTTAA - +4 yetfasco__YOR337W_817 16 0.419644 10261.5 1 4 CACCTG ATCTGCGGAAATTAAATACC - +4 taipale_tf_pairs__GCM1_ETV7_NTRNGGGCGGAAGNNNTTCCNNN_CAP_repr-aop-gcm-gcm2 16 0.420233 10276 1 6 CACCTG ATACGGGCGGAAGTGTTTCCCGC + +4 tfdimers__MD00589-E2f1 12 0.420233 10276 1 6 CACCTG CTTTTCCTTTCTCAGCAGCTCCT + +4 tfdimers__MD00151 6 0.420233 10276 1 6 CACCTG CCCCCCCCCCCCCCCCCCCCCCC - +4 cisbp__M3802 2 0.420854 10291.1 1 6 CACCTG TGCACCACGATTCGCGGCCAA + +4 factorbook__A-Box-Bdp1-Brf-CG17209-Tbp-ebi 12 0.420854 10291.1 1 6 CACCTG TAACCACTGAGCCACCGAGCC + +4 transfac_pro__M09365 1 0.420854 10291.1 1 6 CACCTG TAACGTGTAGAACAAGTAACC + +4 tfdimers__MD00515 6 0.420854 10291.1 1 6 CACCTG TTTTTCTTCCTTTTTTTTTTT - +4 transfac_public__M00273 2 0.420854 10291.1 1 6 CACCTG TGCACCACGATTCGCGGCCAA - +4 taipale_tf_pairs__SOX6_TBX21_RRGTGTNNNNNNNNACAATRN_CAP_repr-Sox102F 16 0.420854 10291.1 1 5 CACCTG CCATTGTTTTATTTAACACCT - +4 cisbp__M5085-lola 1 0.420863 10291.4 1 6 CACCTG TGAGCTT + +4 predrem__nrMotif92 0 0.420863 10291.4 1 6 CACCTG AAACTCC + +4 transfac_pro__M05445-GATAe-grn-pnr-srp 1 0.420863 10291.4 1 6 CACCTG TTAACAG + +4 elemento__CCGGGTC 0 0.420863 10291.4 1 6 CACCTG GACCCGG - +4 elemento__ACGTCAC -1 0.420863 10291.4 1 5 CACCTG ACGTCAC + +4 elemento__ACGTCAG -1 0.420863 10291.4 1 5 CACCTG ACGTCAG + +4 elemento__ACTTCCG-Eip74EF -1 0.420863 10291.4 1 5 CACCTG ACTTCCG + +4 transfac_pro__M04934-Hr78 -1 0.420863 10291.4 1 5 CACCTG ACCCCGG + +4 predrem__nrMotif517 -2 0.420863 10291.4 1 4 CACCTG CTTTGCA + +4 stark__CWYBDCY-pros 3 0.420863 10291.4 1 4 CACCTG CACTTCC + +4 predrem__nrMotif1453 -2 0.420863 10291.4 1 4 CACCTG TCTTGAT - +4 hdpi__GRHPR-CG1236-CG9331-CG31673-CG31674 -3 0.420863 10291.4 1 3 CACCTG CTGCCCC - +4 taipale_tf_pairs__E2F1_EOMES_NGGTGTGNNNGGCGCSNNNCRC_CAP_repr-E2f1 17 0.421021 10295.2 1 5 CACCTG GTGATACGCGCCATTCACACCT - +4 cisbp__M0077 4 0.421978 10318.6 1 6 CACCTG TAGCAACATA + +4 cisbp__M0259-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-E2f1-Jra-Xbp1-crc-kay 3 0.421978 10318.6 1 6 CACCTG GGTGACGTCA + +4 cisbp__M0609 0 0.421978 10318.6 1 6 CACCTG CCCCGCTGCC + +4 cisbp__M0693-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.421978 10318.6 1 6 CACCTG AACCGGAAGT + +4 cisbp__M1074-Optix-so 4 0.421978 10318.6 1 6 CACCTG ATGATACCCC + +4 cisbp__M1860 1 0.421978 10318.6 1 6 CACCTG GAGCCGGAAG + +4 cisbp__M3602-C15 3 0.421978 10318.6 1 6 CACCTG CGGTAATTGG + +4 cisbp__M5794-Bgb-lz-run-RunxA-RunxB 1 0.421978 10318.6 1 6 CACCTG AAACCGCAAA + +4 cisbp__M5908-sd 0 0.421978 10318.6 1 6 CACCTG CACATTCCAT + +4 hocomoco__FOXK1_HUMAN.H11MO.0.A-FoxK-FoxL1-FoxP-bin-croc-fkh-foxo-slp2 4 0.421978 10318.6 1 6 CACCTG TGTTTACTTT + +4 hocomoco__TF2L1_MOUSE.H11MO.1.C-gem 0 0.421978 10318.6 1 6 CACCTG AAACTGGTTT + +4 homer__RCCATMTGTT_Olig2-Fer3-HLH3B-HLH54F-Oli-amos-ato-da-dimm-tap 2 0.421978 10318.6 1 6 CACCTG ACCATCTGTT + +4 jaspar__MA0092.1-Hand 0 0.421978 10318.6 1 6 CACCTG GGTCTGGCAT + +4 predrem__nrMotif2409 2 0.421978 10318.6 1 6 CACCTG TTTACATTTT + +4 taipale__RUNX3_full_NAACCRCAAN-Bgb-lz-run-RunxA-RunxB 1 0.421978 10318.6 1 6 CACCTG AAACCGCAAA + +4 taipale__TEAD4_DBD_NRCATTCCWN-sd 0 0.421978 10318.6 1 6 CACCTG CACATTCCAT + +4 taipale_cyt_meth__HES2_GGCRCGTGYN_eDBD-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 2 0.421978 10318.6 1 6 CACCTG GGCACGTGCC + +4 transfac_pro__M03553-CG42741 3 0.421978 10318.6 1 6 CACCTG CCCCACCCCG + +4 transfac_pro__M03834-E2f1-Max-Myc 3 0.421978 10318.6 1 6 CACCTG GGGCACGTGC + +4 transfac_pro__M07582 2 0.421978 10318.6 1 6 CACCTG TACACGCAAC + +4 yetfasco__YER028C_2144-klu-sr 0 0.421978 10318.6 1 6 CACCTG CCCCGCATTT + +4 yetfasco__YGL035C_2142-klu-sr 1 0.421978 10318.6 1 6 CACCTG CCCCCGCATT + +4 cisbp__M0224-amos-ato-crp-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.421978 10318.6 1 6 CACCTG AACATATGGC - +4 cisbp__M0453 1 0.421978 10318.6 1 6 CACCTG CTACCGTATT - +4 cisbp__M0518-klu-sr 1 0.421978 10318.6 1 6 CACCTG ACCCCGCATT - +4 cisbp__M0519-klu-sr 1 0.421978 10318.6 1 6 CACCTG TACCCCGCAC - +4 cisbp__M1100-Optix 1 0.421978 10318.6 1 6 CACCTG TTATCCCCTA - +4 cisbp__M5025-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Sidpn 1 0.421978 10318.6 1 6 CACCTG GCACGTGCCA - +4 cisbp__M5420-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.421978 10318.6 1 6 CACCTG TACTTCCGGT - +4 homer__RTCATGTGAC_MITF-Mitf-SREBP-Usf-cnc-cyc 2 0.421978 10318.6 1 6 CACCTG GTCACATGAC - +4 swissregulon__hs__HSF1_2.p2-Hsf 2 0.421978 10318.6 1 6 CACCTG AGAACATTCT - +4 taipale_cyt_meth__HEY1_NGCACGTGYN_eDBD_meth-Hey-Sidpn 2 0.421978 10318.6 1 6 CACCTG GACACGTGCA - +4 transfac_pro__M02059-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.421978 10318.6 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M08792-ham-pnr-srp 1 0.421978 10318.6 1 6 CACCTG TTATCTTATC - +4 yetfasco__YLL054C_2242 1 0.421978 10318.6 1 6 CACCTG TATCCGTTCT - +4 cisbp__M1524-CG9727-Rfx -1 0.421978 10318.6 1 5 CACCTG CCTTAGCAAC + +4 cisbp__M5416-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.421978 10318.6 1 5 CACCTG ACCGGAAGTG + +4 predrem__nrMotif2481 -1 0.421978 10318.6 1 5 CACCTG CCCTGCCCGC + +4 transfac_pro__M03822 5 0.421978 10318.6 1 5 CACCTG CAATACACAT + +4 transfac_pro__M03870-Jra-kay-Stat92E 5 0.421978 10318.6 1 5 CACCTG TGACTCATCT + +4 transfac_pro__M07533 5 0.421978 10318.6 1 5 CACCTG GGCGCCGCCT + +4 cisbp__M0521-CG3065-hkb -1 0.421978 10318.6 1 5 CACCTG CCCTATCAAC - +4 cisbp__M1275 -1 0.421978 10318.6 1 5 CACCTG TCCGCAATTT - +4 neph__UW.Motif.0152 5 0.421978 10318.6 1 5 CACCTG TGAGAAATCT - +4 taipale_cyt_meth__SIX2_MCGTATCRYN_FL_meth-Optix-so 5 0.421978 10318.6 1 5 CACCTG CATGATACGT - +4 transfac_pro__M01261-croc-fd59A-fkh-nej 5 0.421978 10318.6 1 5 CACCTG ATGTTTACTT - +4 transfac_pro__M06080 5 0.421978 10318.6 1 5 CACCTG TCTCACCCCA - +4 predrem__nrMotif1469 6 0.421978 10318.6 1 4 CACCTG CTGCCTCACT + +4 predrem__nrMotif1828 6 0.421978 10318.6 1 4 CACCTG CTGGGACACA + +4 taipale_cyt_meth__MEF2C_CCWWATWWRG_FL_meth_repr-bs-Mef2 -2 0.421978 10318.6 1 4 CACCTG CCAAATTTAG + +4 yetfasco__YLR451W_781 -2 0.421978 10318.6 1 4 CACCTG CCGGTACCGG + +4 cisbp__M1565 3 0.424304 10375.5 1 6 CACCTG TTGTACGGC + +4 jaspar__MA1059.1 3 0.424304 10375.5 1 6 CACCTG TTGTACGGC + +4 predrem__nrMotif1033 1 0.424304 10375.5 1 6 CACCTG AAAACTGTT + +4 predrem__nrMotif1042 3 0.424304 10375.5 1 6 CACCTG TGCAACCCA + +4 predrem__nrMotif1430 3 0.424304 10375.5 1 6 CACCTG CCATGCCTC + +4 predrem__nrMotif1458 0 0.424304 10375.5 1 6 CACCTG TGCCTTCTG + +4 predrem__nrMotif2181 0 0.424304 10375.5 1 6 CACCTG GACTTAGCT + +4 predrem__nrMotif346 3 0.424304 10375.5 1 6 CACCTG TGGCATCCT + +4 predrem__nrMotif720 0 0.424304 10375.5 1 6 CACCTG ATCCTGTGA + +4 swissregulon__sacCer__SRD1 1 0.424304 10375.5 1 6 CACCTG AGATCTACA + +4 transfac_pro__M01175 0 0.424304 10375.5 1 6 CACCTG GCCCTCCCC + +4 hocomoco__NKX28_HUMAN.H11MO.0.C-vnd 0 0.424304 10375.5 1 6 CACCTG GTCCTTGAA - +4 predrem__nrMotif155 2 0.424304 10375.5 1 6 CACCTG AGAAACTGG - +4 predrem__nrMotif21 3 0.424304 10375.5 1 6 CACCTG TGAGAGCTT - +4 predrem__nrMotif2372 0 0.424304 10375.5 1 6 CACCTG TTCCTAAGA - +4 predrem__nrMotif2535 0 0.424304 10375.5 1 6 CACCTG TTCCAATTC - +4 predrem__nrMotif538 3 0.424304 10375.5 1 6 CACCTG CAGAGCCTG - +4 predrem__nrMotif679 0 0.424304 10375.5 1 6 CACCTG AACATGTTT - +4 predrem__nrMotif748 3 0.424304 10375.5 1 6 CACCTG TGGGAACTC - +4 transfac_pro__M00309 1 0.424304 10375.5 1 6 CACCTG CCACCAATG - +4 transfac_pro__M07486 3 0.424304 10375.5 1 6 CACCTG CGCCCCCTG - +4 transfac_pro__M07732-GATAd-GATAe-grn-pnr-srp 3 0.424304 10375.5 1 6 CACCTG TCTTATCTT - +4 transfac_public__M00011-ham 1 0.424304 10375.5 1 6 CACCTG TTATCTTGT - +4 cisbp__M0965-achi-esg-hth-sna-vis-wor -1 0.424304 10375.5 1 5 CACCTG ACCTGTCAA + +4 cisbp__M1765 4 0.424304 10375.5 1 5 CACCTG GTTTAGCCG + +4 predrem__nrMotif1518 -1 0.424304 10375.5 1 5 CACCTG AACTTCTTT + +4 transfac_pro__M01752-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.424304 10375.5 1 5 CACCTG ACCGGAAGT + +4 predrem__nrMotif139 -1 0.424304 10375.5 1 5 CACCTG CCCTAGGGA - +4 predrem__nrMotif1722 4 0.424304 10375.5 1 5 CACCTG CAGACACCC - +4 predrem__nrMotif2344 5 0.424304 10375.5 1 4 CACCTG TCTAACACA + +4 predrem__nrMotif296 5 0.424304 10375.5 1 4 CACCTG AAATCCAGC + +4 predrem__nrMotif750 -2 0.424304 10375.5 1 4 CACCTG CCTTCCAAA + +4 transfac_pro__M04996 -2 0.424304 10375.5 1 4 CACCTG CCTCGGTCG - +4 jaspar__MA0021.1 0 0.424825 10388.2 1 6 CACCTG CGCTTT - +4 stark__CHGGAW 0 0.424825 10388.2 1 6 CACCTG ATCCTG - +4 hdpi__FEZ1-Unc-76 -1 0.424825 10388.2 1 5 CACCTG ATTTGC - +4 fantom__motif20_TGNAGC 2 0.424825 10388.2 1 4 CACCTG TGAAGC + +4 fantom__motif7_CGNATC 2 0.424825 10388.2 1 4 CACCTG CGAATC + +4 taipale_tf_pairs__HOXD12_ELK3_NTTTAYNNCCGGAARNN_CAP_repr 6 0.425041 10393.5 1 6 CACCTG TTTTATGACCGGAAGTT + +4 taipale_tf_pairs__TEAD4_DLX3_RCATTCNNNNNTAATKR_CAP-sd 3 0.425041 10393.5 1 6 CACCTG GCATTCCTCGGTAATTG + +4 transfac_pro__M01348-al-Antp-ap-Awh-C15-CG18599-CG32532-CG34367-E5-ems-en-eve-inv-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-Rx-Scr-unc-4-unpg-Vsx1-zfh2 9 0.425041 10393.5 1 6 CACCTG GTAACTAATTAACTACT + +4 transfac_pro__M01379 7 0.425041 10393.5 1 6 CACCTG CCTTGGTTAACTAAAAT + +4 transfac_pro__M09392 1 0.425041 10393.5 1 6 CACCTG TAACGTAAAATTCAAGC + +4 cisbp__M5684-fkh 3 0.425041 10393.5 1 6 CACCTG GGGAACATTGTGTTCCC - +4 flyfactorsurvey__Blimp-1_SOLEXA_FBgn0035625-Blimp-1-Dif-dl-ebi 7 0.425041 10393.5 1 6 CACCTG TTACTTTCACTTTCATT - +4 hocomoco__SALL1_MOUSE.H11MO.0.D-CG42741-CTCF-CoRest-Spps-btd-ct-dar1-klu-luna-salm-salr-sr 9 0.425041 10393.5 1 6 CACCTG CCCTGCCCCACCCTCCC - +4 taipale__NR3C2_DBD_NRGNACANNNTGTNCYN-fkh 3 0.425041 10393.5 1 6 CACCTG GGGAACATTGTGTTCCC - +4 transfac_pro__M02843-bbx 1 0.425041 10393.5 1 6 CACCTG CCAACTGTTAACAATCA - +4 transfac_pro__M07710-CHES-1-like-croc-FoxK-foxo-FoxP-slp1-slp2 6 0.425041 10393.5 1 6 CACCTG TTTGTTTACATAGACGC - +4 transfac_pro__M06886 12 0.425041 10393.5 1 5 CACCTG TGCTTGTGGGCATCCCT + +4 transfac_pro__M05302 -2 0.425041 10393.5 1 4 CACCTG ACTGGTTGCCCCCGCCC + +4 cisbp__M4429-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 3 0.425908 10414.7 1 6 CACCTG GGTCACGTGACCGGG + +4 neph__UW.Motif.0588 9 0.425908 10414.7 1 6 CACCTG AATGAATTATTTCTG + +4 taipale_cyt_meth__GLI2_NGACCACCCACGWYG_eDBD-ci-lmd-opa-sug 8 0.425908 10414.7 1 6 CACCTG AGACCACCCACGTCG + +4 transfac_pro__M01582 0 0.425908 10414.7 1 6 CACCTG TTCCAAAAATGGAAA + +4 transfac_pro__M02854 6 0.425908 10414.7 1 6 CACCTG ATGTCACAACAACAC + +4 transfac_pro__M09265-bs 1 0.425908 10414.7 1 6 CACCTG TTTCCTTTTTTGGAA + +4 cisbp__M4812-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 7 0.425908 10414.7 1 6 CACCTG CCAGCCACACCCACC - +4 flyfactorsurvey__CG12029_SOLEXA_5_FBgn0035454-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 7 0.425908 10414.7 1 6 CACCTG CCAGCCACACCCACC - +4 taipale_tf_pairs__GCM1_ELF1_GTGCGGGCGGAAGTN_CAP_repr-Eip74EF-gcm-gcm2 0 0.425908 10414.7 1 6 CACCTG CACTTCCGCCCGCAT - +4 taipale_tf_pairs__GCM2_DRGX_RTRSGGGNNAATTAN_CAP_repr-CG11294-Drgx-gcm-gcm2 6 0.425908 10414.7 1 6 CACCTG CTAATTAGCCCGCAT - +4 transfac_pro__M01105 3 0.425908 10414.7 1 6 CACCTG AAAGGGCTGCGCCCC - +4 transfac_public__M00238 4 0.425908 10414.7 1 6 CACCTG CCTCCAGCTTTTGAT - +4 cisbp__M5129-amos-da-HLH54F-Oli -1 0.425908 10414.7 1 5 CACCTG ACCGCACCATCTGTC + +4 flyfactorsurvey__Oli_da_SANGER_5_2_FBgn0000413-HLH54F-Oli-amos-da -1 0.425908 10414.7 1 5 CACCTG ACCGCACCATCTGTC + +4 tfdimers__MD00422 13 0.426541 10430.2 1 6 CACCTG CTCCTGCCCTAGCCTCCATCTGTTCTTGCCCCC + +4 hdpi__ESX1 -2 0.426853 10437.8 1 4 CACCTG ACTTC - +4 tfdimers__MD00503-kn 5 0.428686 10482.7 1 6 CACCTG CTCGCCCCCAGGGGACTTCCCCACCCCCCC - +4 cisbp__M5207-Sox14 0 0.430016 10515.2 1 6 CACCTG CTCCTTTGTCC + +4 cisbp__M6458-CG9650-ebi-lz-MTA1-like-run-RunxA-RunxB 3 0.430016 10515.2 1 6 CACCTG ACAAACCACAG + +4 neph__UW.Motif.0070 4 0.430016 10515.2 1 6 CACCTG AAAAAACATTT + +4 predrem__nrMotif1565 5 0.430016 10515.2 1 6 CACCTG AGGCCCACAGC + +4 taipale_tf_pairs__SOX6_CACCGAACAAT_HT-Sox102F 0 0.430016 10515.2 1 6 CACCTG CACCGAACAAT + +4 transfac_pro__M09575 0 0.430016 10515.2 1 6 CACCTG TACATGCAGGT + +4 cisbp__M4566-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-pnr-slp2 4 0.430016 10515.2 1 6 CACCTG TGTTTACTTAG - +4 cisbp__M4664-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-pnr-slp2 4 0.430016 10515.2 1 6 CACCTG TGTTTACACAG - +4 flyfactorsurvey__br-PL_SOLEXA_FBgn0000210-br 1 0.430016 10515.2 1 6 CACCTG CCTCCTAGATC - +4 hocomoco__STAT6_HUMAN.H11MO.0.B-Stat92E 1 0.430016 10515.2 1 6 CACCTG TTTCCTGAGAA - +4 idmmpmm__Eip74EF-Eip74EF-aop 2 0.430016 10515.2 1 6 CACCTG ACTTCCTGGTT - +4 taipale_cyt_meth__TFE3_NNCACGTGAYN_eDBD-bigmax-cnc-cyc-Max-Mitf-tai-tgo 3 0.430016 10515.2 1 6 CACCTG CGTCACGTGCG - +4 transfac_pro__M01208-bs 5 0.430016 10515.2 1 6 CACCTG GTCACTTCCGG - +4 transfac_pro__M09457-tll 4 0.430016 10515.2 1 6 CACCTG CGTTGACTTTT - +4 transfac_pro__M09483-tll 4 0.430016 10515.2 1 6 CACCTG CGTTGACTTTT - +4 bergman__dl-A-Dif-dl 6 0.430016 10515.2 1 5 CACCTG GGGAAAAACCC - +4 cisbp__M2385-croc-fd59A-fkh-foxo-FoxP-slp2 6 0.430016 10515.2 1 5 CACCTG TTTGTTTACTT - +4 transfac_pro__M07966-kni-knrl 6 0.430016 10515.2 1 5 CACCTG GTGCTCTAGTT - +4 transfac_pro__M06124 7 0.430016 10515.2 1 4 CACCTG TCGTTTTAACC - +4 cisbp__M3830-CG5846-CG9727-Max-Rfx-SREBP 12 0.430239 10520.6 1 6 CACCTG TAGTAGCCATGGCAACAA + +4 cisbp__M5333-ct 6 0.430239 10520.6 1 6 CACCTG ATCGATCAGGTTATCGAT + +4 cisbp__M6106 10 0.430239 10520.6 1 6 CACCTG GGCATGTCCAGACATGTC + +4 taipale__Tp53_DBD_RACATGYCNNGRCATGTY_repr 0 0.430239 10520.6 1 6 CACCTG AACATGCCCGGGCATGTC + +4 taipale_cyt_meth__IRX3_NACATGNNNNNNCATGTN_eDBD-ara-caup-mirr 0 0.430239 10520.6 1 6 CACCTG TACATGAATATTCATGTA + +4 taipale_cyt_meth__NHLH2_NKGNMGCAGCTGCGYCMN_FL-HLH4C 6 0.430239 10520.6 1 6 CACCTG GGGCCGCAGCTGCGTCCC + +4 cisbp__M3952-bs 2 0.430239 10520.6 1 6 CACCTG ATTACCATATATGGGCAT - +4 taipale__CUX1_DBD_ATCRATNNNNNNATCRAT_repr-ct 6 0.430239 10520.6 1 6 CACCTG ATCGATCAGGTTATCGAT - +4 taipale__Tp73_DBD_NRCATGYYNNRRCAYGYN 10 0.430239 10520.6 1 6 CACCTG GACATGTCCAGACATGTC - +4 transfac_pro__M05901 4 0.430239 10520.6 1 6 CACCTG CGACGACCGGCCCCTATC - +4 transfac_pro__M06340 12 0.430239 10520.6 1 6 CACCTG TCCCGAGCGCCGCACCAA - +4 transfac_public__M00152-bs 2 0.430239 10520.6 1 6 CACCTG ATTACCATATATGGGCAT - +4 taipale_tf_pairs__TFAP2C_HOXB13_SCCNNNNGGCATNGTWAA_CAP_repr-TfAP-2 -1 0.430239 10520.6 1 5 CACCTG GCCTGAGGGCATCGTAAA + +4 jaspar__MA0146.2 8 0.431279 10546.1 1 6 CACCTG GGGGCCGAGGCCTG + +4 transfac_pro__M00697 6 0.431279 10546.1 1 6 CACCTG TTCTGTCACGTCAC + +4 transfac_pro__M08877-sr 7 0.431279 10546.1 1 6 CACCTG TCACGCCCACTTCT + +4 cisbp__M5863-aop-Eip74EF 0 0.431279 10546.1 1 6 CACCTG TACTTCCGCTTTTT - +4 hocomoco__NF2L2_MOUSE.H11MO.0.A-Jra-cnc-kay-maf-S 2 0.431279 10546.1 1 6 CACCTG AATTGCTGAGTCAT - +4 neph__UW.Motif.0585 4 0.431279 10546.1 1 6 CACCTG TCTTTCCCTTCCCA - +4 taipale__SPI1_full_AAAAAGCGGAAGTN_repr-aop-Eip74EF 0 0.431279 10546.1 1 6 CACCTG TACTTCCGCTTTTT - +4 taipale_tf_pairs__HOXB2_ELK3_RSCGGAAGTMRTTA_CAP-pb 4 0.431279 10546.1 1 6 CACCTG TAATGACTTCCGGT - +4 transfac_pro__M07961-Hnf4 3 0.431279 10546.1 1 6 CACCTG GTGGACTTTGGACC - +4 transfac_pro__M07968-eg-Hnf4-Hr51-Hr78-kni-knrl-svp-tll-usp 1 0.431279 10546.1 1 6 CACCTG TGACTTTTGACTTC - +4 transfac_pro__M09135 4 0.431279 10546.1 1 6 CACCTG AAAGCTACTTTTTC - +4 neph__UW.Motif.0244 -1 0.431279 10546.1 1 5 CACCTG AAATTTCATTTTGT + +4 transfac_pro__M09353 -1 0.431279 10546.1 1 5 CACCTG ACTTGTAGAAGAAG - +4 tfdimers__MD00116 13 0.43338 10597.4 1 6 CACCTG TTCTTGCTAATCCCTCCTCCCCCCC - +4 cisbp__M5337-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.433791 10607.5 1 6 CACCTG CATTACGTAACA + +4 cisbp__M5504-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.433791 10607.5 1 6 CACCTG TGGCACGTGCCG + +4 cisbp__M5505-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.433791 10607.5 1 6 CACCTG CGGCACGTGCCG + +4 cisbp__M5506-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.433791 10607.5 1 6 CACCTG TGGCACGTGCCA + +4 homer__AAGCACGTGBGD_Pho4 3 0.433791 10607.5 1 6 CACCTG AAGCACGTGTGT + +4 jaspar__MA0120.1 3 0.433791 10607.5 1 6 CACCTG TTTTCCTTTTCG + +4 predrem__nrMotif2462 2 0.433791 10607.5 1 6 CACCTG CTCACCCTCCCC + +4 predrem__nrMotif709 4 0.433791 10607.5 1 6 CACCTG CCCCCACCCTGC + +4 taipale__HES5_DBD_NGGCACGTGCCN-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.433791 10607.5 1 6 CACCTG CGGCACGTGCCA + +4 taipale__HES7_DBD_NGGCACGTGCCN-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.433791 10607.5 1 6 CACCTG TGGCACGTGCCA + +4 transfac_pro__M05573 2 0.433791 10607.5 1 6 CACCTG TATGCCTACCGC + +4 transfac_pro__M07337 1 0.433791 10607.5 1 6 CACCTG TAAAGTGCTGAT + +4 cisbp__M1940 3 0.433791 10607.5 1 6 CACCTG TTTTCCTTTTCG - +4 cisbp__M6233-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-Nf1 5 0.433791 10607.5 1 6 CACCTG TTGTTTACTTAG - +4 taipale_cyt_meth__CREB5_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.433791 10607.5 1 6 CACCTG GATGACATCATC - +4 transfac_pro__M05406 0 0.433791 10607.5 1 6 CACCTG AACCAAATCCCA - +4 transfac_pro__M05527 6 0.433791 10607.5 1 6 CACCTG GTGCCACACCCA - +4 transfac_pro__M05876 1 0.433791 10607.5 1 6 CACCTG GTACCCCACCCA - +4 transfac_pro__M06292 1 0.433791 10607.5 1 6 CACCTG TTTCCTTCACGT - +4 transfac_pro__M06389 2 0.433791 10607.5 1 6 CACCTG AATCCCTGCAAT - +4 transfac_pro__M05502 7 0.433791 10607.5 1 5 CACCTG AATCCGGCAACA - +4 transfac_pro__M06014 7 0.433791 10607.5 1 5 CACCTG CATCTAGTCCCA - +4 transfac_pro__M06033 7 0.433791 10607.5 1 5 CACCTG GGAGTAAAACCG - +4 transfac_pro__M06553 -1 0.433791 10607.5 1 5 CACCTG TCCTACTTCCCA - +4 transfac_pro__M06708 7 0.433791 10607.5 1 5 CACCTG TCGGTTCCACGA - +4 transfac_pro__M09338 7 0.433791 10607.5 1 5 CACCTG AAAAAAATATCT - +4 homer__GGTGYTGACAGS_Tbx20-H15-mid -2 0.433791 10607.5 1 4 CACCTG CCTGTCAACACC - +4 transfac_pro__M05964 8 0.433791 10607.5 1 4 CACCTG TCAGCCGCCACA - +4 taipale_tf_pairs__MEIS1_MAX_NTGACRNNNNNNCACGTGN_CAP_repr-Max 12 0.434017 10613 1 6 CACCTG TTGACATGTCGGCACGTGC + +4 transfac_pro__M06908 10 0.434017 10613 1 6 CACCTG ATGTGGCAATAAACTGACC + +4 transfac_public__M00098-Poxm-sv 7 0.434017 10613 1 6 CACCTG TCCATCATGCGTGACGAGG - +4 taipale_cyt_meth__DMRT3_NWWTTGNTACATT_eDBD_meth-dmrt11E-dmrt93B-dmrt99B-dsx 7 0.434039 10613.5 1 6 CACCTG AAATTGATACATT + +4 taipale_cyt_meth__EGR1_NMCGCCCACGCMN_eDBD-klu-sr 2 0.434039 10613.5 1 6 CACCTG CCCGCCCACGCAC + +4 cisbp__M3050-Ets21C-Ets96B-Ets97D-pnt 4 0.434039 10613.5 1 6 CACCTG TAACTTCCGGTGG - +4 cisbp__M3595 3 0.434039 10613.5 1 6 CACCTG TTCCCCCTCACCC - +4 cisbp__M4596-ac-ase-cnc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-Sap30-sc-tgo-Usf 3 0.434039 10613.5 1 6 CACCTG GGCCACGTGACCC - +4 swissregulon__sacCer__ECM22 6 0.434039 10613.5 1 6 CACCTG TCCGGAGACCCGG - +4 transfac_pro__M00333 7 0.434039 10613.5 1 6 CACCTG AAGCGCGCCCCCG - +4 transfac_public__M00074-Ets21C-Ets96B-Ets97D-pnt 4 0.434039 10613.5 1 6 CACCTG TAATTTCCGGTGG - +4 transfac_public__M00084 3 0.434039 10613.5 1 6 CACCTG TTCCCCCTCACCC - +4 transfac_public__M00128-GATAe-grn-pnr-srp 5 0.434039 10613.5 1 6 CACCTG CCCCTTATCTGAT - +4 yetfasco__YDR421W_1509 8 0.434039 10613.5 1 5 CACCTG CCGATAATTACCG + +4 cisbp__M3356 2 0.434692 10629.5 1 6 CACCTG GGTACAATCTGTTCTG + +4 cisbp__M4515-btd-cnc-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-Usf 4 0.434692 10629.5 1 6 CACCTG GGGTCACGTGACCGCG + +4 cisbp__M6272 4 0.434692 10629.5 1 6 CACCTG AGGCCACGTGCCGGAT + +4 jaspar__MA0551.1-Atf6-Clk-CrebA 5 0.434692 10629.5 1 6 CACCTG AATGCCACGTGGCATT + +4 neph__UW.Motif.0467 4 0.434692 10629.5 1 6 CACCTG GCAAACCATACCCACA + +4 neph__UW.Motif.0521 7 0.434692 10629.5 1 6 CACCTG CAGGAAGGGCAGAGAG + +4 transfac_pro__M03124-ac-amos-ase-dimm-Fer1-HLH54F-l(1)sc-sc 5 0.434692 10629.5 1 6 CACCTG CAGAACAGCTGTTCTC + +4 cisbp__M5859-Ets98B 3 0.434692 10629.5 1 6 CACCTG GTATACTTCTTTCTGC - +4 hocomoco__HESX1_HUMAN.H11MO.0.D 4 0.434692 10629.5 1 6 CACCTG ATGCCACGTGCCGCCT - +4 hocomoco__RFX3_MOUSE.H11MO.0.C-CG5846-CG9727-Max-Rfx-SREBP 2 0.434692 10629.5 1 6 CACCTG GTTGCCATGGCAACCG - +4 swissregulon__sacCer__MCM1-bs 1 0.434692 10629.5 1 6 CACCTG TTTCCCAATTCGGAAA - +4 taipale__HNF4A_full_RRGGTCAAAGTCCRNN_repr-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 10 0.434692 10629.5 1 6 CACCTG ATTGGACTTTGACCCC - +4 taipale_tf_pairs__ELK1_SREBF2_RSCGGAANTSRCGTGA_CAP_repr-SREBP 6 0.434692 10629.5 1 6 CACCTG TCACGCCACTTCCGGT - +4 taipale_tf_pairs__GCM1_ELK3_ACCCGCANCCGGAAGN_CAP_repr-gcm-gcm2 -1 0.434692 10629.5 1 5 CACCTG ACCCGCAGCCGGAAGT + +4 neph__UW.Motif.0601 11 0.434692 10629.5 1 5 CACCTG CAGAAATGAATTTGCT - +4 cisbp__M0841 2 0.435081 10639 1 6 CACCTG TGTTCATA + +4 cisbp__M1829 2 0.435081 10639 1 6 CACCTG TTTTCCGC + +4 predrem__nrMotif1073 2 0.435081 10639 1 6 CACCTG AGAACCTC + +4 predrem__nrMotif2116 2 0.435081 10639 1 6 CACCTG TGGACTTT + +4 predrem__nrMotif2383 1 0.435081 10639 1 6 CACCTG ATGGCTGA + +4 taipale_cyt_meth__BSX_NTCGTTAN_eDBD-bsh-Dr 0 0.435081 10639 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__NKX3-2_NTCGTTAN_eDBD_meth-bap-bsh-Dr-ind-unpg 0 0.435081 10639 1 6 CACCTG CTCGTTAA + +4 transfac_pro__M03844-Ets96B 1 0.435081 10639 1 6 CACCTG CTTCCTGT + +4 cisbp__M0008 2 0.435081 10639 1 6 CACCTG GCAACATA - +4 cisbp__M1161 2 0.435081 10639 1 6 CACCTG ATTACACG - +4 elemento__AAAGGCGC 1 0.435081 10639 1 6 CACCTG GCGCCTTT - +4 elemento__CCAAGGAG 0 0.435081 10639 1 6 CACCTG CTCCTTGG - +4 elemento__GAAGGGGC 1 0.435081 10639 1 6 CACCTG GCCCCTTC - +4 predrem__nrMotif2154 0 0.435081 10639 1 6 CACCTG AATCTAAT - +4 predrem__nrMotif2238 2 0.435081 10639 1 6 CACCTG ATAATCTT - +4 predrem__nrMotif404 1 0.435081 10639 1 6 CACCTG ACACATGC - +4 predrem__nrMotif973 0 0.435081 10639 1 6 CACCTG CAACTCCT - +4 swissregulon__hs__ATF6.p2-Atf6-CrebA 1 0.435081 10639 1 6 CACCTG CCACGTCA - +4 cisbp__M0831 -1 0.435081 10639 1 5 CACCTG ACCAATCA + +4 predrem__nrMotif968 -1 0.435081 10639 1 5 CACCTG GCCTGCGC + +4 transfac_pro__M01113-cbt-CG42741-dar1-luna 3 0.435081 10639 1 5 CACCTG CCACACCC + +4 elemento__ATGTTGCA 3 0.435081 10639 1 5 CACCTG TGCAACAT - +4 jaspar__MA0983.1 -1 0.435081 10639 1 5 CACCTG ACTTTTTC - +4 jaspar__MA1093.1 3 0.435081 10639 1 5 CACCTG GTTGACTT - +4 predrem__nrMotif1477 4 0.435081 10639 1 4 CACCTG AGACTCCC - +4 transfac_pro__M05354-CG10979 -2 0.435081 10639 1 4 CACCTG CCTATTTA - +4 hdpi__CYB5R1-CG5946 5 0.435081 10639 1 3 CACCTG TCCGATAC + +4 tfdimers__MD00037-Pur-alpha 9 0.435797 10656.5 1 6 CACCTG GGGCGGGGGCAGCTGCCCCCGCGC + +4 tfdimers__MD00273-GATAe-grn-pnr-srp 14 0.435797 10656.5 1 6 CACCTG TTTAAAGTGGGGATTATCTGTTTA + +4 tfdimers__MD00223-sd-Sox100B 5 0.435797 10656.5 1 6 CACCTG TCCCCTTCCTTTGCATTTCTAACC - +4 elemento__CCACCCC 1 0.436248 10667.6 1 6 CACCTG CCACCCC + +4 hdpi__ARFGAP1-ArfGAP1 1 0.436248 10667.6 1 6 CACCTG GTCCATG - +4 swissregulon__hs__SPIB.p2 0 0.436248 10667.6 1 6 CACCTG TTCCTCT - +4 elemento__CCCTCCG -1 0.436248 10667.6 1 5 CACCTG CCCTCCG + +4 elemento__GCCTCCC -1 0.436248 10667.6 1 5 CACCTG GCCTCCC + +4 elemento__GCCTCGC -1 0.436248 10667.6 1 5 CACCTG GCCTCGC + +4 elemento__TCCTCCA -1 0.436248 10667.6 1 5 CACCTG TCCTCCA + +4 elemento__TCCTCGC -1 0.436248 10667.6 1 5 CACCTG TCCTCGC + +4 cisbp__M0796-CycT-GATAd-GATAe-grn-pnr-srp 2 0.436248 10667.6 1 5 CACCTG CTTATCT - +4 cisbp__M1920-CrebB -1 0.436248 10667.6 1 5 CACCTG ACGTCAG - +4 elemento__ATGTCCT 2 0.436248 10667.6 1 5 CACCTG AGGACAT - +4 elemento__CCGAGGA -1 0.436248 10667.6 1 5 CACCTG TCCTCGG - +4 hdpi__TOB2-Tob 2 0.436248 10667.6 1 5 CACCTG GCCCCCA - +4 jaspar__MA0096.1-CrebB -1 0.436248 10667.6 1 5 CACCTG ACGTCAG - +4 predrem__nrMotif1089 2 0.436248 10667.6 1 5 CACCTG GCCGCCT - +4 transfac_public__M00468-CG42741 2 0.436248 10667.6 1 5 CACCTG CCCACTG - +4 hdpi__SCC-112-pds5 3 0.436248 10667.6 1 4 CACCTG CTTGCCC - +4 predrem__nrMotif1129 3 0.436248 10667.6 1 4 CACCTG GGATCCC - +4 predrem__nrMotif1804 -2 0.436248 10667.6 1 4 CACCTG TCTGAGT - +4 transfac_pro__M01968-foxo 4 0.436248 10667.6 1 3 CACCTG TGTTGAC + +4 cisbp__M4501-Jra-kay 2 0.436511 10674 1 6 CACCTG CATTCCTGAGGGATGACTTA + +4 dbcorrdb__CEBPB__ENCSR000BRX_1__m3 3 0.436511 10674 1 6 CACCTG CCACAACTGACTCACATCAG + +4 dbcorrdb__EZH2__ENCSR000ARR_1__m4-E(z) 7 0.436511 10674 1 6 CACCTG CGGCCGGTCCCGAACCGCGG + +4 dbcorrdb__HNF4A__ENCSR000BLF_1__m1-btd-EcR-HDAC1-Hnf4-Hr78-nej-Spps-svp-usp 12 0.436511 10674 1 6 CACCTG ATCTGGACTTTGGACTCTGG + +4 dbcorrdb__JUN__ENCSR000EZW_1__m2-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Snr1-srp-Stat92E-svp 5 0.436511 10674 1 6 CACCTG TTTCTTATCTGTGTAACCCA + +4 dbcorrdb__MXI1__ENCSR000EBR_1__m1-Max-Myc-Rfx 6 0.436511 10674 1 6 CACCTG GCGGTCCACGTGGCGACGGG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BKR_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp-zfh1 4 0.436511 10674 1 6 CACCTG CCCTTATCTGCCCCCCCCAG + +4 dbcorrdb__SAP30__ENCSR000AQJ_1__m3-Sap30-Sin3A 9 0.436511 10674 1 6 CACCTG CCGGTACAGCACCGCCGCCA + +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m6-egg 6 0.436511 10674 1 6 CACCTG AAGAGAAACCTTATTAACCA + +4 dbcorrdb__TBL1XR1__ENCSR000EGA_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-pan-pnr-RpII215-Sirt6-srp-zfh1 7 0.436511 10674 1 6 CACCTG GCCGCCTTATCTCCCCCGCC + +4 transfac_pro__M06976-exd 5 0.436511 10674 1 6 CACCTG TCCGTTTCCTCTGGAAAGCC + +4 dbcorrdb__EZH2__ENCSR000ASY_1__m6-E(z) 3 0.436511 10674 1 6 CACCTG CCGGGCCTTCGGCGGCAGGG - +4 dbcorrdb__EZH2__ENCSR000ASY_1__m7-E(z) 12 0.436511 10674 1 6 CACCTG GGCCTTCTTCCGCAGCGCCG - +4 dbcorrdb__GATA1__ENCSR000EFT_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.436511 10674 1 6 CACCTG TCTTATCTGTCCCCCCCAGC - +4 dbcorrdb__HNF4G__ENCSR000BNJ_1__m2-btd-EcR-eg-ERR-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 13 0.436511 10674 1 6 CACCTG ACTCTGGACTTTGAACTCTG - +4 dbcorrdb__HSF1__ENCSR000EET_1__m2-Hsf 14 0.436511 10674 1 6 CACCTG GCAGCCCAGTGGTCTAGCGG - +4 dbcorrdb__POLR2A__ENCSR000ALT_1__m3-RpII215 4 0.436511 10674 1 6 CACCTG GCAACACGTAACACGCCACC - +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m4-CG17209 6 0.436511 10674 1 6 CACCTG ACCCGGGACCTCCCGATTGT - +4 dbcorrdb__RELA__ENCSR000EBA_1__m3-Dif-dl 11 0.436511 10674 1 6 CACCTG CTCTGGAAATTCCCCTGGCT - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m1-AMPKalpha-Bdp1-Brf-CG17209-CG43143-Hsf-SREBP-Tbp 9 0.436511 10674 1 6 CACCTG CGGGATTCGAACCCGGGGCC - +4 dbcorrdb__TBL1XR1__ENCSR000EGB_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 5 0.436511 10674 1 6 CACCTG TTCCTTATCTGTGCCCGCCA - +4 factorbook__GATA1-ext-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.436511 10674 1 6 CACCTG TCCTTATCTGCACCCACCAG - +4 homer__AGATSTNDNNDSAGATAASN_GATA3-GATAe-grn-pnr-srp 3 0.436511 10674 1 6 CACCTG TCTTATCTGTGTTGACATCT - +4 dbcorrdb__BRF2__ENCSR000DNV_1__m4 -2 0.436511 10674 1 4 CACCTG CTTGGTCTCAGTGTAGTGTT + +4 tfdimers__MD00038-TfAP-2 6 0.437395 10695.6 1 6 CACCTG GCCCATTGCCTGAGGCAATGGGC + +4 tfdimers__MD00208-Tsf1-Tsf2-Tsf3 7 0.437395 10695.6 1 6 CACCTG TATTTTTCACTTTCACTTTCTTT + +4 transfac_pro__M02845 8 0.437395 10695.6 1 6 CACCTG TGTCGTTACACGTGGAAGGCGGT + +4 transfac_pro__M04670-bin-fd102C-fd19B-FoxK-FoxL1-slp1-slp2 14 0.437395 10695.6 1 6 CACCTG ATCCGTACCAAAACAACCTGAAC + +4 taipale_tf_pairs__ETV5_HOXA2_RSCGGWAATKNNNNNNNNMATTA_CAP_repr-Ets96B-pb 16 0.437395 10695.6 1 6 CACCTG TAATGACCTAACCCATTTCCGGC - +4 factorbook__UA7-Jra 4 0.437838 10706.5 1 6 CACCTG GGAAAACCCGGAGCGGAGTTC + +4 transfac_pro__M01565 10 0.437838 10706.5 1 6 CACCTG ATCTCAATTTCTCCGATGATT + +4 yetfasco__YPR196W_861 10 0.437838 10706.5 1 6 CACCTG ATCTCAATTTCTCCGATGATT + +4 tfdimers__MD00433 10 0.437838 10706.5 1 6 CACCTG TTTTTTTTCCCACTTACTTTT - +4 cisbp__M0302-Atf3-Atf6-crc-CrebB-Irbp18-Jra-kay-Xbp1 3 0.437911 10708.2 1 6 CACCTG GATGACGTAA + +4 cisbp__M0770 3 0.437911 10708.2 1 6 CACCTG ACAGATCTGT + +4 cisbp__M0800 3 0.437911 10708.2 1 6 CACCTG AAAGATCTAT + +4 cisbp__M1721 3 0.437911 10708.2 1 6 CACCTG AAATGCCGAG + +4 cisbp__M1797 1 0.437911 10708.2 1 6 CACCTG ACTCCGGAGT + +4 cisbp__M2054-scro-tin-vnd 1 0.437911 10708.2 1 6 CACCTG CCACTTGAAA + +4 cisbp__M5270-vnd 1 0.437911 10708.2 1 6 CACCTG GCACTTGAGC + +4 cisbp__M6152-CrebA-CrebB-Jra-Xbp1 2 0.437911 10708.2 1 6 CACCTG CTGACGTCAC + +4 hocomoco__ATF1_MOUSE.H11MO.0.B-CrebA-CrebB-Jra-Xbp1 2 0.437911 10708.2 1 6 CACCTG CTGACGTCAC + +4 homer__ACATCCTGGT_SPDEF-Ets98B 2 0.437911 10708.2 1 6 CACCTG ACATCCTGGT + +4 predrem__nrMotif90 2 0.437911 10708.2 1 6 CACCTG TGTTCCTTTT + +4 swissregulon__sacCer__TEC1-sd 0 0.437911 10708.2 1 6 CACCTG AACATTCCCG + +4 taipale_cyt_meth__SREBF1_NTCACGCCAY_eDBD_repr-SREBP 2 0.437911 10708.2 1 6 CACCTG ATCACGCCAC + +4 transfac_pro__M07507 3 0.437911 10708.2 1 6 CACCTG GAAGATCTTC + +4 yetfasco__YPL133C_2226 2 0.437911 10708.2 1 6 CACCTG ATTCCCGAGG + +4 cisbp__M0202-Max-Mitf-Usf 1 0.437911 10708.2 1 6 CACCTG CCACGTGACC - +4 cisbp__M0420 1 0.437911 10708.2 1 6 CACCTG CCACCCCCCC - +4 cisbp__M0697-aop-Eip74EF-Ets21C-Ets98B 2 0.437911 10708.2 1 6 CACCTG ACTTCCGGGT - +4 cisbp__M0767 4 0.437911 10708.2 1 6 CACCTG TTTTGATCGG - +4 cisbp__M1411 1 0.437911 10708.2 1 6 CACCTG TTGCGTAAAA - +4 cisbp__M3315-GATAe-grn-pnr 3 0.437911 10708.2 1 6 CACCTG TGTTATCAGC - +4 cisbp__M5429-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.437911 10708.2 1 6 CACCTG CACTTCCGGT - +4 hocomoco__MITF_MOUSE.H11MO.0.A-HLH3B-HLH4C-Hand-Max-Mitf-Myc-Usf-ac-ase-cnc-cyc-l(1)sc-nau-sc 3 0.437911 10708.2 1 6 CACCTG AGTCACGTGG - +4 homer__NCTGGAATGC_TEAD-Jra-sd 3 0.437911 10708.2 1 6 CACCTG GCATTCCAGG - +4 idmmpmm__tll-dsf-tll 3 0.437911 10708.2 1 6 CACCTG TTTGACTTTT - +4 predrem__nrMotif1532 4 0.437911 10708.2 1 6 CACCTG TGCTGTCTTT - +4 predrem__nrMotif1663 1 0.437911 10708.2 1 6 CACCTG AAACATGCAT - +4 predrem__nrMotif2008 0 0.437911 10708.2 1 6 CACCTG CTCCTCGGCC - +4 taipale__FEV_DBD_ACCGGAAGTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.437911 10708.2 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M01823-Stat92E 1 0.437911 10708.2 1 6 CACCTG TTTCCCGGAA - +4 transfac_pro__M01977-aop-Eip74EF-Ets21C-Ets96B-pnt 3 0.437911 10708.2 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M02057-aop-Eip74EF 3 0.437911 10708.2 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M05312-btd-cbt-Sp1-Spps 0 0.437911 10708.2 1 6 CACCTG CACCCGCCCT - +4 transfac_pro__M06527 1 0.437911 10708.2 1 6 CACCTG TCCCCTTTCA - +4 cisbp__M1061-achi-esg-hth-sna-vis-wor -1 0.437911 10708.2 1 5 CACCTG ACCTGTCAAT + +4 cisbp__M4688-Eip74EF-Ets21C-Hr78 -1 0.437911 10708.2 1 5 CACCTG ACCCGGAAGT + +4 cisbp__M5399-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.437911 10708.2 1 5 CACCTG ACCGGAAGTG + +4 cisbp__M5418-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.437911 10708.2 1 5 CACCTG ACCGGAAGTG + +4 predrem__nrMotif2006-bin-foxo 5 0.437911 10708.2 1 5 CACCTG AAATAAACAT + +4 stark__ACGNNAATTG -1 0.437911 10708.2 1 5 CACCTG ACGAAAATTG + +4 taipale__ERG_DBD_ACCGGAARTN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.437911 10708.2 1 5 CACCTG ACCGGAAGTG + +4 taipale__ETS1_full_ACCGGAARYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.437911 10708.2 1 5 CACCTG ACCGGAAGTG + +4 cisbp__M0492 5 0.437911 10708.2 1 5 CACCTG TATTACACTA - +4 cisbp__M0541 5 0.437911 10708.2 1 5 CACCTG TGATCTACGC - +4 predrem__nrMotif2430 -1 0.437911 10708.2 1 5 CACCTG ACATGTGAGA - +4 predrem__nrMotif302 5 0.437911 10708.2 1 5 CACCTG AAAGAAATCT - +4 cisbp__M1530-CG5846-CG9727-Rfx 6 0.437911 10708.2 1 4 CACCTG CCTAGCAACG + +4 predrem__nrMotif2201 6 0.437911 10708.2 1 4 CACCTG AGAAAGTACA - +4 taipale_cyt_meth__ZNF345_TTGCAACNNNNNCAACYGKACN_eDBD 4 0.438103 10712.9 1 6 CACCTG TTGCAACATGGACAACCGTACC + +4 tfdimers__MD00318-Hnf4-svp 12 0.438997 10734.8 1 6 CACCTG AATTTAAAAATTAACCTTACATCCAACCTCACCCCTTATT + +4 taipale_tf_pairs__GCM1_TBX21_RGGTGWKNNNNNNNNNTNNCRTRNGGGN_CAP_repr-gcm-gcm2 23 0.439476 10746.5 1 5 CACCTG GCCCGTATGTTAAATGGAATTCACACCT - +4 cisbp__M0503 1 0.440099 10761.7 1 6 CACCTG AACTCTAGA + +4 cisbp__M5790-Bgb-lz-run-RunxA-RunxB 1 0.440099 10761.7 1 6 CACCTG AAACCGCAA + +4 cisbp__M6423-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.440099 10761.7 1 6 CACCTG ATTTGCATA + +4 predrem__nrMotif1460 2 0.440099 10761.7 1 6 CACCTG TAAGCCTTT + +4 predrem__nrMotif1644 2 0.440099 10761.7 1 6 CACCTG ATGACCAGT + +4 predrem__nrMotif184 0 0.440099 10761.7 1 6 CACCTG AAGCTTCTT + +4 predrem__nrMotif2023 1 0.440099 10761.7 1 6 CACCTG TAAGCTTCT + +4 predrem__nrMotif2136 1 0.440099 10761.7 1 6 CACCTG GGACCCGGG + +4 predrem__nrMotif481 2 0.440099 10761.7 1 6 CACCTG TAAAGCTTT + +4 taipale__RUNX2_DBD_WAACCRCAN_repr-Bgb-lz-run-RunxA-RunxB 1 0.440099 10761.7 1 6 CACCTG AAACCGCAA + +4 taipale_cyt_meth__NR1I3_NYGAACTWW_FL_meth_repr-EcR 2 0.440099 10761.7 1 6 CACCTG ACGAACTTT + +4 transfac_public__M00394-Dr 3 0.440099 10761.7 1 6 CACCTG CCGTAATTG + +4 cisbp__M0384-bowl-drm-odd-sob 3 0.440099 10761.7 1 6 CACCTG TGCTACCGT - +4 hocomoco__ZBT7A_HUMAN.H11MO.0.A 3 0.440099 10761.7 1 6 CACCTG GAGACCCCC - +4 predrem__nrMotif135 0 0.440099 10761.7 1 6 CACCTG TGGCTGTGA - +4 predrem__nrMotif2128 0 0.440099 10761.7 1 6 CACCTG ATCCTTTTT - +4 predrem__nrMotif73 3 0.440099 10761.7 1 6 CACCTG CATCCTCTG - +4 taipale_cyt_meth__CREB1_NRTGAYGTN_eDBD_meth-CrebB 0 0.440099 10761.7 1 6 CACCTG TACGTCACC - +4 cisbp__M1490 4 0.440099 10761.7 1 5 CACCTG AATTGACAT + +4 cisbp__M1636 -1 0.440099 10761.7 1 5 CACCTG ATCTTCACA + +4 predrem__nrMotif1675 4 0.440099 10761.7 1 5 CACCTG GCTGCGCCC + +4 predrem__nrMotif2085 -1 0.440099 10761.7 1 5 CACCTG ACTTCTTAA + +4 cisbp__M1569 4 0.440099 10761.7 1 5 CACCTG ACCGTACAA - +4 cisbp__M6274 4 0.440099 10761.7 1 5 CACCTG GGGCAACCC - +4 predrem__nrMotif520 4 0.440099 10761.7 1 5 CACCTG GTTCTGCCT - +4 predrem__nrMotif96 4 0.440099 10761.7 1 5 CACCTG AAGAGAGCA - +4 transfac_pro__M08894-ovo 4 0.440099 10761.7 1 5 CACCTG CCGTTATGT - +4 cisbp__M1537-CG9727-Rfx -2 0.440099 10761.7 1 4 CACCTG CTTAGCAAC + +4 predrem__nrMotif1114-Hnf4-eg-kni-knrl-usp -2 0.440099 10761.7 1 4 CACCTG CCTTTGCCC + +4 predrem__nrMotif1687 5 0.440099 10761.7 1 4 CACCTG CTAAGCACA + +4 predrem__nrMotif1541 -2 0.440099 10761.7 1 4 CACCTG CCTTTTCCT - +4 predrem__nrMotif1799 5 0.440099 10761.7 1 4 CACCTG AGAGCAACA - +4 cisbp__M1970 0 0.440316 10767 1 6 CACCTG TGCCAA + +4 fantom__motif52_CGNATG -2 0.440316 10767 1 4 CACCTG CATACG - +4 transfac_pro__M03858-pan -3 0.440316 10767 1 3 CACCTG CTTTGA + +4 hdpi__BRUNOL4-bru3 3 0.440316 10767 1 3 CACCTG ATACAC - +4 tfdimers__MD00339-TfAP-2 6 0.440428 10769.8 1 6 CACCTG TATTTTTGCCTTATGCAATTTTTTTTTTTTA + +4 homer__NNNVCTGWGYAAACASN_Fox_Ebox-HDAC1-fkh-foxo-nej 1 0.441688 10800.6 1 6 CACCTG GAGCCTGTGTAAACAGA + +4 transfac_pro__M01456 2 0.441688 10800.6 1 6 CACCTG GAAAACTAGTTAACATC + +4 hocomoco__GATA5_HUMAN.H11MO.0.D-srp 8 0.441688 10800.6 1 6 CACCTG CTCTAAGTTATCTTTTA - +4 predrem__nrMotif1495-Brf-CTCF-CoRest-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-ct-kay-klu-l(3)neo38-sr-vtd 4 0.441688 10800.6 1 6 CACCTG CCCCCACCCCCTCCCCC - +4 taipale_tf_pairs__MEIS1_SOX2_TGACAKNNNAACAATGN_CAP_repr-SoxN 8 0.441688 10800.6 1 6 CACCTG ACATTGTTAACATGTCA - +4 cisbp__M4481-ac-ase-btd-cnc-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf 3 0.442344 10816.6 1 6 CACCTG GGTCACGTGGCCCGG + +4 flyfactorsurvey__CG11071_SOLEXA_FBgn0030532-mamo 3 0.442344 10816.6 1 6 CACCTG CCAAGCCTATAGCCA + +4 hocomoco__FOXC1_HUMAN.H11MO.0.C-FoxK-FoxP-HDAC1-bin-croc-fd59A-fkh-foxo-nej-slp2 7 0.442344 10816.6 1 6 CACCTG CGTTGTTTACTTAAG + +4 hocomoco__ZN423_HUMAN.H11MO.0.D 2 0.442344 10816.6 1 6 CACCTG GGCACCCAAGGGTGC + +4 taipale_cyt_meth__KLF17_NMCCACGCWCCCMYY_eDBD-CG3065-hkb 7 0.442344 10816.6 1 6 CACCTG CACCACGCACCCCTT + +4 taipale_tf_pairs__MEIS2_HOXA13_CYCATAAANNTGTCA_HT-hth 6 0.442344 10816.6 1 6 CACCTG CTCGTAAAACTGTCA + +4 transfac_pro__M00947-gem 8 0.442344 10816.6 1 6 CACCTG GCTGGTTTGAGCTGG + +4 transfac_pro__M04724-CG5846-CG9727-Rfx-SREBP 4 0.442344 10816.6 1 6 CACCTG CGGTCGCCATGGCAA + +4 cisbp__M0411 6 0.442344 10816.6 1 6 CACCTG TAAGTATACACAAGT - +4 cisbp__M6235-bin-croc-fd59A-fkh-FoxK-foxo-FoxP-HDAC1-nej-slp2 7 0.442344 10816.6 1 6 CACCTG CATTGTTTACTTAAG - +4 flyfactorsurvey__br-PE_SOLEXA_FBgn0000210-br 4 0.442344 10816.6 1 6 CACCTG AAACCATCTAACGCT - +4 hocomoco__ELF2_MOUSE.H11MO.0.C-Eip74EF-Ets96B-pnt 6 0.442344 10816.6 1 6 CACCTG AGTCACTTCCTGCTA - +4 hocomoco__RFX4_HUMAN.H11MO.0.D-CG5846-CG9727-Max-Rfx-SREBP 2 0.442344 10816.6 1 6 CACCTG GTTACCATGGCAACG - +4 transfac_pro__M07969-tll 1 0.442344 10816.6 1 6 CACCTG TGACTTATTGACTTT - +4 transfac_pro__M09035 2 0.442344 10816.6 1 6 CACCTG TCCACCGCCACCGCC - +4 transfac_pro__M09217 5 0.442344 10816.6 1 6 CACCTG TGTATTTTCTGACAA - +4 tfdimers__MD00192 17 0.443972 10856.5 1 6 CACCTG AAAAAAGAAAGTGAAAGTCCCAAATTT - +4 tfdimers__MD00295-kn-Stat92E 12 0.443972 10856.5 1 6 CACCTG AAGTTGGGAAATTCCCCTGGGAATTCA - +4 cisbp__M4610-Clk-E2f1-gce-Max-Myc-tgo-Usf 2 0.446192 10910.7 1 6 CACCTG GCCACGTGGCC + +4 jaspar__MA0367.1 5 0.446192 10910.7 1 6 CACCTG AATTTTTCCGG + +4 neph__UW.Motif.0265 3 0.446192 10910.7 1 6 CACCTG GATGACATTTC + +4 predrem__nrMotif1573 1 0.446192 10910.7 1 6 CACCTG CCGCCGGCTCC + +4 transfac_pro__M01706-ci-lmd-opa-sug 3 0.446192 10910.7 1 6 CACCTG GACCACCCACG + +4 transfac_pro__M01965 5 0.446192 10910.7 1 6 CACCTG AATTTTTCCGG + +4 c2h2_zfs__M0469-Kdm4A-Kdm4B 1 0.446192 10910.7 1 6 CACCTG GTACCCCTAAA - +4 hocomoco__ELK1_MOUSE.H11MO.0.B-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Taf1-aop-bs-pnt 1 0.446192 10910.7 1 6 CACCTG CCACTTCCGGT - +4 hocomoco__MAZ_HUMAN.H11MO.1.A-Spps-btd-dar1-klu 5 0.446192 10910.7 1 6 CACCTG CCCCCTCCCTC - +4 predrem__nrMotif2596 5 0.446192 10910.7 1 6 CACCTG CCCCCCACCAA - +4 swissregulon__sacCer__GLN3-GATAd-GATAe-grn-pnr-srp 5 0.446192 10910.7 1 6 CACCTG GGCCTTATCAG - +4 taipale_cyt_meth__FOXL2_NAYRTMAACAN_FL_meth-croc-FoxL1-foxo-slp2 5 0.446192 10910.7 1 6 CACCTG GTGTTGACGTT - +4 taipale_tf_pairs__ELK1_HOXA3_RSCGGTAATKR_CAP_repr 4 0.446192 10910.7 1 6 CACCTG CAATTTCCGGC - +4 tiffin__TIFDMEM0000069 0 0.446192 10910.7 1 6 CACCTG AACCATTTTTC - +4 transfac_pro__M01136 0 0.446192 10910.7 1 6 CACCTG TTTCTTTTTTT - +4 transfac_pro__M02048-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.446192 10910.7 1 6 CACCTG ATGACGTCATC - +4 transfac_pro__M05705-CG2120 1 0.446192 10910.7 1 6 CACCTG TCTCCTTTACC - +4 transfac_pro__M06516 5 0.446192 10910.7 1 6 CACCTG ACGGCTCCCCG - +4 transfac_pro__M09542 4 0.446192 10910.7 1 6 CACCTG CGTTGACTTTT - +4 cisbp__M1333 6 0.446192 10910.7 1 5 CACCTG ATCCGTTACAG + +4 stark__GGGGAMWWCCM-shn 6 0.446192 10910.7 1 5 CACCTG GGGGAAAACCA + +4 cisbp__M6137-CG12018-Dif-dl-Rel 6 0.446192 10910.7 1 5 CACCTG GGGAAATTCCC - +4 jaspar__MA0593.1-FoxP-croc-fd59A-fkh-foxo-slp2 6 0.446192 10910.7 1 5 CACCTG TTTGTTTACTT - +4 taipale_tf_pairs__Hoxa10_TTCTGG40NTGC_HT_2 7 0.446192 10910.7 1 4 CACCTG ATTTTATTACC - +4 cisbp__M2620-Mef2-bs 2 0.447078 10932.4 1 6 CACCTG ATTACCATATATAGTAAT + +4 cisbp__M6105 0 0.447078 10932.4 1 6 CACCTG AACATGCCCGGGCATGTC + +4 taipale__Hic1_DBD_RTGCCANCYNRTGCCMNC_repr 4 0.447078 10932.4 1 6 CACCTG GTGCCAGCCTATGCCAAC + +4 taipale__RUNX2_DBD_WAACCRCAAWAACCRCAN_repr-lz-run-RunxA-RunxB 10 0.447078 10932.4 1 6 CACCTG TAACCGCAAAAACCGCAA + +4 taipale_cyt_meth__NHLH1_NKGNMKCAGCTGCGYCMN_FL_meth-HLH4C 6 0.447078 10932.4 1 6 CACCTG GGGGAGCAGCTGCGTCCC + +4 taipale_tf_pairs__TEAD4_PITX1_RCATWCYNNNNNTAATCC_CAP_repr-Ptx1-sd 3 0.447078 10932.4 1 6 CACCTG GCATTCCTGCGCTAATCC + +4 transfac_public__M00393-bs-Mef2 2 0.447078 10932.4 1 6 CACCTG ATTACCATATATAGTAAT + +4 cisbp__M6022 4 0.447078 10932.4 1 6 CACCTG GTGCCAGCCTATGCCAAC - +4 cisbp__M6047-CrebA-CrebB-maf-S 6 0.447078 10932.4 1 6 CACCTG AATGCTTACGTCAGCACT - +4 taipale__Mafb_DBD_NNYGCTGACGTMAGCANN_repr-CrebA-CrebB-maf-S 6 0.447078 10932.4 1 6 CACCTG AATGCTTACGTCAGCACT - +4 taipale_cyt_meth__NHLH1_NKGNMKCAGCTGCGYCMN_eDBD_meth-HLH4C 6 0.447078 10932.4 1 6 CACCTG GGGACGCAGCTGATCCCC - +4 taipale_tf_pairs__ETV5_EVX1_RSCGGWAATNNNNATTAN_CAP-Ets96B-eve 11 0.447078 10932.4 1 6 CACCTG CTAATGGCCATTTCCGCT - +4 transfac_pro__M00531-Eip74EF 2 0.447078 10932.4 1 6 CACCTG GTGACCCACTTCCTGGCA - +4 transfac_pro__M06893 0 0.447078 10932.4 1 6 CACCTG GACCCGTCGACCCATTCC - +4 transfac_pro__M09514-Atf6-CrebA-Xbp1 5 0.447078 10932.4 1 6 CACCTG ACTGCCACGTCACCATTT - +4 taipale_tf_pairs__FLI1_DLX2_ACCGGAARTNNNYAATTA_HT -1 0.447078 10932.4 1 5 CACCTG ACCGGAAGTGGGCAATTA + +4 cisbp__M1963 8 0.447698 10947.6 1 6 CACCTG GGGGCCGAGGCCTG + +4 cisbp__M2373-Usf 7 0.447698 10947.6 1 6 CACCTG CGTGAGTCACGTGA + +4 cisbp__M3036-Irbp18-Xrp1 8 0.447698 10947.6 1 6 CACCTG ATATTGCGCAACTG + +4 cisbp__M6162-cyc-Mitf-SREBP-Usf 4 0.447698 10947.6 1 6 CACCTG GGGTCACGTGTCCA + +4 factorbook__MAX-Max-Mitf-Myc-Usf-tgo 3 0.447698 10947.6 1 6 CACCTG GACCACGTGACCCC + +4 jaspar__MA0036.2-GATAe-Jra-grn-pnr-srp 7 0.447698 10947.6 1 6 CACCTG AGATTCTTATCTGT + +4 neph__UW.Motif.0459 4 0.447698 10947.6 1 6 CACCTG AATTCACAGAGCAG + +4 neph__UW.Motif.0464 8 0.447698 10947.6 1 6 CACCTG CAGAAAGAAACATG + +4 neph__UW.Motif.0479 4 0.447698 10947.6 1 6 CACCTG AGATCAGTTTCCTG + +4 taipale_cyt_meth__CREB3L1_NTGCCACGYGTACN_eDBD_meth-CrebA 4 0.447698 10947.6 1 6 CACCTG GTGCCACGTGTACA + +4 taipale_cyt_meth__IRF5_NYGAAACCGAAACY_eDBD 4 0.447698 10947.6 1 6 CACCTG CCGAAACCGAAACC + +4 transfac_pro__M00985-cwo-cyc-Mitf-SREBP-tgo-Usf 4 0.447698 10947.6 1 6 CACCTG CTGTCACGTGACCA + +4 transfac_pro__M04749-nej 8 0.447698 10947.6 1 6 CACCTG TATTGCATCATCTT + +4 transfac_pro__M07840-bs-bsh-CG9876-en-inv-Vsx2 4 0.447698 10947.6 1 6 CACCTG CAATTACCCAATTA + +4 transfac_pro__M07939-opa 0 0.447698 10947.6 1 6 CACCTG GACCCCCCGCTGCG + +4 transfac_public__M00117-Irbp18-Xrp1 8 0.447698 10947.6 1 6 CACCTG ATATTGCGCAACTG + +4 cisbp__M1868-GATAe-grn-Jra-pnr-srp 7 0.447698 10947.6 1 6 CACCTG AGATTCTTATCTGT - +4 hocomoco__ETS1_MOUSE.H11MO.0.A-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-RunxA-RunxB-Sin3A-Taf1-aop-bs-dl-lz-pnt-run 4 0.447698 10947.6 1 6 CACCTG CCACTTCCTGTCCC - +4 neph__UW.Motif.0397 8 0.447698 10947.6 1 6 CACCTG CAAAAAAACATTTT - +4 neph__UW.Motif.0533 1 0.447698 10947.6 1 6 CACCTG TTTCCTTTTTTTCA - +4 taipale__Spic_DBD_AAAAAGMGGAAGTA-aop 0 0.447698 10947.6 1 6 CACCTG TACTTCCGCTTTTT - +4 transfac_pro__M04888-Taf1 7 0.447698 10947.6 1 6 CACCTG CTTCCGCTTCCTTC - +4 cisbp__M4842-CR43670 9 0.447698 10947.6 1 5 CACCTG TTTGGTGGTGACCT + +4 transfac_pro__M09432 9 0.447698 10947.6 1 5 CACCTG TGTGGGCCCCACTT + +4 transfac_pro__M02162 10 0.447698 10947.6 1 4 CACCTG GTTAATTATTAACC - +4 neph__UW.Motif.0174 -3 0.447698 10947.6 1 3 CACCTG CTGAGTCAGTCCCA + +4 cisbp__M3156-CG7786-gt-hng1-Pdp1-vri 3 0.450105 11006.4 1 6 CACCTG CGTTACATAACG + +4 cisbp__M5643-Myb 6 0.450105 11006.4 1 6 CACCTG ACCGTTAAACGG + +4 fantom__motif93_TANTMTCTRWAT 3 0.450105 11006.4 1 6 CACCTG TAATCTCTATAT + +4 hocomoco__FOXA1_HUMAN.H11MO.0.A-FoxK-GATAe-HDAC1-Nf1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.450105 11006.4 1 6 CACCTG TGTTTACTTTGG + +4 hocomoco__VSX2_HUMAN.H11MO.0.D-Awh-CG18599-CG34367-E5-Lim3-Pph13-Rx-Ubx-Vsx1-Vsx2-al-ap-ems-ind-otp-unpg 5 0.450105 11006.4 1 6 CACCTG TTAATTAGCTTC + +4 neph__UW.Motif.0336 4 0.450105 11006.4 1 6 CACCTG CAAAAAACTGCA + +4 neph__UW.Motif.0486 5 0.450105 11006.4 1 6 CACCTG GAAAATATTTTC + +4 taipale__DBP_DBD_NRTTACGTAAYN-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.450105 11006.4 1 6 CACCTG CATTACGTAACA + +4 taipale_cyt_meth__CREB3L1_TGCCACRTCAYN_FL_meth-Atf6-CrebA-Xbp1 3 0.450105 11006.4 1 6 CACCTG TGCCACATCATC + +4 transfac_pro__M01302-ac-ase-l(1)sc-nau-sc 3 0.450105 11006.4 1 6 CACCTG CAGCAGCTGCTG + +4 transfac_pro__M05810 6 0.450105 11006.4 1 6 CACCTG CGGGGTTACCGC + +4 cisbp__M0516-Kdm4A-Kdm4B 3 0.450105 11006.4 1 6 CACCTG CCCCCCCTAAAT - +4 homer__CGTGGGTGGTCC_GLI3-ci-lmd-opa-sug 4 0.450105 11006.4 1 6 CACCTG GGACCACCCACG - +4 homer__VNAVCAGCTGGC_Atoh1-HLH54F-ac-amos-ase-dimm-l(1)sc-sc-tap 2 0.450105 11006.4 1 6 CACCTG GCCAGCTGGTAC - +4 neph__UW.Motif.0195 6 0.450105 11006.4 1 6 CACCTG GAGCAGGGCCAG - +4 taipale_cyt_meth__ELF5_NANNMGGAAGTN_eDBD_repr-Eip74EF 0 0.450105 11006.4 1 6 CACCTG CACTTCCGCGTT - +4 taipale_cyt_meth__FOXC2_NWANRTAAACAN_eDBD_meth-croc-fd59A-FoxL1-foxo-slp1-slp2 5 0.450105 11006.4 1 6 CACCTG TTGTTTACGTAG - +4 taipale_cyt_meth__POU2F2_NTMATTATGCAN_eDBD-nub-pdm2 1 0.450105 11006.4 1 6 CACCTG ATGCATAATTAG - +4 taipale_cyt_meth__POU3F2_NTATGCGCATAN_eDBD-nub-pdm2-vvl 5 0.450105 11006.4 1 6 CACCTG TTATGCGCATAA - +4 taipale_tf_pairs__ELF2_NAMCCGGAAGTR_HT-Eip74EF 0 0.450105 11006.4 1 6 CACCTG TACTTCCGGGTT - +4 transfac_pro__M05909-CG4360-jim 1 0.450105 11006.4 1 6 CACCTG GAGCCTTTATAA - +4 transfac_pro__M06011-CG3407 1 0.450105 11006.4 1 6 CACCTG TTACCAGTCCCT - +4 transfac_pro__M06272 4 0.450105 11006.4 1 6 CACCTG TATCCACCCCCA - +4 transfac_pro__M06276 0 0.450105 11006.4 1 6 CACCTG CATCTCACTACA - +4 transfac_pro__M06612 1 0.450105 11006.4 1 6 CACCTG TCATCTTTAACA - +4 transfac_pro__M06689-CG4360-jim 1 0.450105 11006.4 1 6 CACCTG GAGCCTTTATAA - +4 transfac_public__M00045-CG7786-gt-hng1-Pdp1-vri 3 0.450105 11006.4 1 6 CACCTG CGTTACATAACG - +4 taipale_cyt_meth__GATA5_WGATAACGATCT_FL_meth-GATAe-grn-pnr-srp 7 0.450105 11006.4 1 5 CACCTG AGATAACGATCT + +4 scertf__harbison.MOT2-Cnot4 7 0.450105 11006.4 1 5 CACCTG TTTTTGTTTCCT - +4 transfac_pro__M05745 7 0.450105 11006.4 1 5 CACCTG GCGCAATCCCCT - +4 transfac_pro__M06282 -1 0.450105 11006.4 1 5 CACCTG TCCTTTTTCACG - +4 transfac_pro__M06485-CG3281 7 0.450105 11006.4 1 5 CACCTG TCTATTTCCCCT - +4 transfac_pro__M05750 8 0.450105 11006.4 1 4 CACCTG TTAACGACCACC + +4 swissregulon__hs__SRF.p3-bs -2 0.450105 11006.4 1 4 CACCTG CCTTATTTGGGC - +4 transfac_pro__M05648 8 0.450105 11006.4 1 4 CACCTG GAGGCAGCCACA - +4 transfac_pro__M06062-wdn 8 0.450105 11006.4 1 4 CACCTG TCCCCTTTCACA - +4 transfac_pro__M06125 -2 0.450105 11006.4 1 4 CACCTG CCTCCTCCCCCG - +4 cisbp__M6488-SREBP 5 0.45042 11014.1 1 6 CACCTG CCTCACCCCACCC + +4 factorbook__UA2 0 0.45042 11014.1 1 6 CACCTG CGCCTGTCAATCA + +4 neph__UW.Motif.0113 5 0.45042 11014.1 1 6 CACCTG ATGTTTCCCAGCA + +4 neph__UW.Motif.0221 7 0.45042 11014.1 1 6 CACCTG AAAAAACCACTTG + +4 transfac_pro__M09280 5 0.45042 11014.1 1 6 CACCTG TTAATTACCGTTA + +4 cisbp__M3314-GATAe-grn-pnr-srp 5 0.45042 11014.1 1 6 CACCTG CCCCTTATCTGAT - +4 cisbp__M6378-bap 5 0.45042 11014.1 1 6 CACCTG TTATATACTTATT - +4 hocomoco__SRBP2_HUMAN.H11MO.0.B-SREBP 5 0.45042 11014.1 1 6 CACCTG CCTCACCCCACCC - +4 neph__UW.Motif.0111 3 0.45042 11014.1 1 6 CACCTG CAGATTCTGTTTT - +4 neph__UW.Motif.0217 0 0.45042 11014.1 1 6 CACCTG TCCCAGATTGCTC - +4 neph__UW.Motif.0636 4 0.45042 11014.1 1 6 CACCTG CATTTCCCATTGG - +4 swissregulon__hs__MZF1.p2-Spps-btd-klu 3 0.45042 11014.1 1 6 CACCTG TTCCCCCTCCCCC - +4 taipale_tf_pairs__TEAD4_DRGX_RGWATGYTAATKN_CAP-CG11294-Drgx-sd 5 0.45042 11014.1 1 6 CACCTG TAATTAACATTCC - +4 transfac_pro__M00753 4 0.45042 11014.1 1 6 CACCTG AATGCACCCATTT - +4 hocomoco__TF7L2_HUMAN.H11MO.0.A-pan -1 0.45042 11014.1 1 5 CACCTG CCCTTTGATGTGG + +4 stark__ACGYNGCGTATGM -1 0.45042 11014.1 1 5 CACCTG ACGCAGCGTATGA + +4 scertf__morozov.ARO80 8 0.45042 11014.1 1 5 CACCTG CCGATAATTACCG - +4 hocomoco__P53_MOUSE.H11MO.1.A -2 0.45042 11014.1 1 4 CACCTG CCCGGGCATGTCC - +4 elemento__CAAGTTCA 2 0.450835 11024.3 1 6 CACCTG TGAACTTG - +4 elemento__CATGTTGC 2 0.450835 11024.3 1 6 CACCTG GCAACATG - +4 predrem__nrMotif1681 0 0.450835 11024.3 1 6 CACCTG CACCGGGG - +4 transfac_pro__M01082-Usf 0 0.450835 11024.3 1 6 CACCTG CAACAGAA - +4 cisbp__M0369 3 0.450835 11024.3 1 5 CACCTG TTTGAACT + +4 cisbp__M1283 3 0.450835 11024.3 1 5 CACCTG GTTAACCA + +4 cisbp__M1397 3 0.450835 11024.3 1 5 CACCTG GCGAATCT + +4 transfac_pro__M00731-lz-run-RunxA-RunxB -1 0.450835 11024.3 1 5 CACCTG ACCACAAA + +4 cisbp__M0657 -1 0.450835 11024.3 1 5 CACCTG ACTTTTTG - +4 cisbp__M5479-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.450835 11024.3 1 5 CACCTG TCTTATCT - +4 hdpi__ZNF503-CG6083-CG12116-Sptr-noc -1 0.450835 11024.3 1 5 CACCTG CCCACCAC - +4 taipale__GATA5_DBD_AGATAANN-brm-CoRest-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.450835 11024.3 1 5 CACCTG TCTTATCT - +4 cisbp__M1578-Mad-Sox100B-Sox14-SoxN -2 0.450835 11024.3 1 4 CACCTG CCTTTGTT + +4 predrem__nrMotif1226 -2 0.450835 11024.3 1 4 CACCTG TCTGTTAA + +4 swissregulon__sacCer__GAT1-CycT-GATAd-GATAe-grn-pnr-srp -2 0.450835 11024.3 1 4 CACCTG CCTTATCG + +4 neph__UW.Motif.0032 -3 0.450835 11024.3 1 3 CACCTG CTGGGCTG - +4 neph__UW.Motif.0088-Chrac-14-Nf-YA-Nf-YB-Nf-YC -3 0.450835 11024.3 1 3 CACCTG CTGATTGG - +4 tfdimers__MD00262-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 6 0.450943 11026.9 1 6 CACCTG CATTGCCACCTGGCAGGTGGCAGAT + +4 tfdimers__MD00296-zfh1 7 0.450943 11026.9 1 6 CACCTG ACTAGCACAACTGGTTTCTCAAATT + +4 cisbp__M5143-pad 3 0.450943 11026.9 1 6 CACCTG GTTCCCCTCCTTGTTTTGTGGGGGG - +4 flyfactorsurvey__pad_SOLEXA_5_FBgn0038418-pad 3 0.450943 11026.9 1 6 CACCTG GTTCCCCTCCTTGTTTTGTGGGGGG - +4 transfac_pro__M06198 13 0.45102 11028.8 1 6 CACCTG TGAGTTACTCCTGGAAATG + +4 cisbp__M2363-CrebA-Max-Myc-Usf 10 0.45102 11028.8 1 6 CACCTG CCCGTCGTGCCACGTGTCC - +4 jaspar__MA0570.1-CrebA-Max-Myc-Usf 10 0.45102 11028.8 1 6 CACCTG CCCGTCGTGCCACGTGTCC - +4 taipale_cyt_meth__MAX_NCACGTGNNNNNCACGTGN_eDBD_repr-Clk-cwo-gce-Hey-Max-Myc 12 0.45102 11028.8 1 6 CACCTG GCACGTGCCCGCCACGTGC - +4 transfac_pro__M09354 1 0.45102 11028.8 1 6 CACCTG AAACTTGTAAAAGAAGTAA - +4 cisbp__M2843 0 0.451375 11037.5 1 6 CACCTG TATCTACGTGGAATGA + +4 neph__UW.Motif.0509 9 0.451375 11037.5 1 6 CACCTG GAGAAAAAAAAATTGA + +4 transfac_pro__M02865 5 0.451375 11037.5 1 6 CACCTG TGGGCGACGTCGTTAA + +4 neph__UW.Motif.0629 7 0.451375 11037.5 1 6 CACCTG GAAAAGCAGCATCTGG - +4 taipale_cyt_meth__FOXA3_NSYTAWGTAAACAAAN_FL_meth-bin-croc-fd59A-fkh-foxo-FoxP-nej 7 0.451375 11037.5 1 6 CACCTG GTTTGTTTACTTAAGG - +4 taipale_tf_pairs__ELK1_FOXI1_RSCGGAANNRTMAAYA_CAP_repr 9 0.451375 11037.5 1 6 CACCTG TGTTTATATTTCCGGT - +4 taipale_tf_pairs__GCM1_ONECUT2_RTGCGGGNNATCGATR_CAP_repr-gcm-gcm2-onecut 7 0.451375 11037.5 1 6 CACCTG TATCGATTTCCCGCAT - +4 transfac_pro__M00774-CG12018-Dif-dl-Rel 10 0.451375 11037.5 1 6 CACCTG GGCGGGGAAATTCCCC - +4 transfac_pro__M01321-abd-A-Antp-Dll-pb-Scr-Ubx 8 0.451375 11037.5 1 6 CACCTG ACGTTAATTACCCCAA - +4 transfac_pro__M02900-Sox14 1 0.451375 11037.5 1 6 CACCTG ATTCCTTTGTCTGTTT - +4 neph__UW.Motif.0257 -1 0.451375 11037.5 1 5 CACCTG CCCTCTGGCTTCTGCA + +4 elemento__GACATGC 0 0.451823 11048.4 1 6 CACCTG GACATGC + +4 elemento__GATCTGC 0 0.451823 11048.4 1 6 CACCTG GATCTGC + +4 transfac_pro__M03554-NfI 0 0.451823 11048.4 1 6 CACCTG TGCCAAG + +4 elemento__CATGTCG 1 0.451823 11048.4 1 6 CACCTG CGACATG - +4 elemento__CCATGTC 0 0.451823 11048.4 1 6 CACCTG GACATGG - +4 elemento__TCATGTC 0 0.451823 11048.4 1 6 CACCTG GACATGA - +4 elemento__ACGCCCT 2 0.451823 11048.4 1 5 CACCTG ACGCCCT + +4 elemento__ATGAACT 2 0.451823 11048.4 1 5 CACCTG ATGAACT + +4 c2h2_zfs__M2430-CG42741 2 0.451823 11048.4 1 5 CACCTG CCCACTG - +4 cisbp__M0648 -1 0.451823 11048.4 1 5 CACCTG ACTTTTT - +4 cisbp__M0988-ara-caup-mirr 2 0.451823 11048.4 1 5 CACCTG ATTACAA - +4 elemento__AGGACAA 2 0.451823 11048.4 1 5 CACCTG TTGTCCT - +4 elemento__AGGACAC 2 0.451823 11048.4 1 5 CACCTG GTGTCCT - +4 elemento__AGGACGA 2 0.451823 11048.4 1 5 CACCTG TCGTCCT - +4 elemento__AGGCCCC 2 0.451823 11048.4 1 5 CACCTG GGGGCCT - +4 elemento__AGGCCGC 2 0.451823 11048.4 1 5 CACCTG GCGGCCT - +4 elemento__AGGGCGG 2 0.451823 11048.4 1 5 CACCTG CCGCCCT - +4 jaspar__MA0982.1 -1 0.451823 11048.4 1 5 CACCTG ACTTTTT - +4 scertf__badis.PDR8 -1 0.451823 11048.4 1 5 CACCTG ATCTCCG - +4 scertf__badis.YLR278C -1 0.451823 11048.4 1 5 CACCTG AACTCCG - +4 transfac_pro__M04739-vtd -2 0.451823 11048.4 1 4 CACCTG TCTAGTG + +4 taipale_tf_pairs__MYBL1_EOMES_NNSYGNCNAACNNNNNNCACRCNN_CAP_repr-Myb 7 0.453307 11084.7 1 6 CACCTG ACGCGACCAACGGTCTTCACACCC + +4 dbcorrdb__ATF2__ENCSR000BQU_1__m1-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 9 0.453653 11093.2 1 6 CACCTG CGATGACGTCATCCCCAGGG + +4 dbcorrdb__CHD1__ENCSR000EFC_1__m5-Chd1 3 0.453653 11093.2 1 6 CACCTG CCGGCGCTTCCAGGCGGTAT + +4 dbcorrdb__EZH2__ENCSR000ARD_1__m4-E(z) 10 0.453653 11093.2 1 6 CACCTG GCGACAGATTAACGCGAACA + +4 dbcorrdb__MAX__ENCSR000EUP_1__m1-btd-cnc-CrebB-E2f1-ERR-E(z)-Max-Myc-Spps-SREBP-Stat92E-Usf-vtd 6 0.453653 11093.2 1 6 CACCTG CCCGAGCACGTGGCCCCGCC + +4 dbcorrdb__MAZ__ENCSR000EDN_1__m1-bon-Brf-brm-btd-CoRest-ct-CTCF-E(z)-HDAC1-kay-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-vtd 8 0.453653 11093.2 1 6 CACCTG TCTGCCCCCCCCCCCGGGCG + +4 dbcorrdb__POLR2A__ENCSR000EZL_1__m2-RpII215 3 0.453653 11093.2 1 6 CACCTG CCGTTGCTTCCGCCATTTCG + +4 dbcorrdb__REST__ENCSR000BJO_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 4 0.453653 11093.2 1 6 CACCTG TCAGCACCATGGACAGCGCC + +4 dbcorrdb__SMARCA4__ENCSR000EHO_1__m2-brm 7 0.453653 11093.2 1 6 CACCTG AAGAGGCCTGCTGTCTGTGG + +4 dbcorrdb__STAT5A__ENCSR000BRR_1__m1-brm-CoRest-ebi-GATAe-grn-HDAC1-HLH3B-Jra-pnr-srp-Stat92E-svp 3 0.453653 11093.2 1 6 CACCTG TCTTATCTGGGAAAGCCAGG + +4 dbcorrdb__TEAD4__ENCSR000BRP_1__m1-sd 11 0.453653 11093.2 1 6 CACCTG CATACTCCACATTCCTGCCA + +4 dbcorrdb__USF1__ENCSR000BMF_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 10 0.453653 11093.2 1 6 CACCTG CGGCCCGGGTCACGTGGCCC + +4 dbcorrdb__USF2__ENCSR000DZU_1__m1-ac-ase-btd-cnc-CrebB-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-mor-Myc-nau-Sap30-sc-Sin3A-Spps-SREBP-tgo-Usf 11 0.453653 11093.2 1 6 CACCTG CCGGCCCGGGTCACGTGGCC + +4 dbcorrdb__ZNF274__ENCSR000EVX_1__m1-bon 3 0.453653 11093.2 1 6 CACCTG CTAAACATCAGAGAATTCAT + +4 taipale_tf_pairs__HOXB2_NHLH1_NYMATTANNNNNCAGCTGNN_CAP_repr-HLH4C-pb 12 0.453653 11093.2 1 6 CACCTG GTCATTAGGCAGCAGCTGCG + +4 taipale_tf_pairs__TEAD4_HES7_RCATTCCNNNNNCRCGYGYN_CAP_repr-sd 3 0.453653 11093.2 1 6 CACCTG ACATTCCACCGACACGTGCG + +4 transfac_pro__M07928-nom 3 0.453653 11093.2 1 6 CACCTG ACCCACCCGAAACCCACCCC + +4 cisbp__M2152 8 0.453653 11093.2 1 6 CACCTG TGCAATGGACCCTGATTTAG - +4 dbcorrdb__CCNT2__ENCSR000DOA_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Sin3A-Sirt6-srp-svp-zfh1 4 0.453653 11093.2 1 6 CACCTG GCCTTATCTGCCGCCCCCAG - +4 dbcorrdb__EP300__ENCSR000AQB_1__m1-nej 11 0.453653 11093.2 1 6 CACCTG GTCTTTTTTCCGCCCTTATC - +4 dbcorrdb__EZH2__ENCSR000AQE_1__m6-E(z) 2 0.453653 11093.2 1 6 CACCTG TGACACTGCACATTGTCTTT - +4 dbcorrdb__HDAC2__ENCSR000BNR_1__m2-HDAC1 13 0.453653 11093.2 1 6 CACCTG TCCCGTGCAGCGCCCCCTGG - +4 dbcorrdb__HNF4G__ENCSR000BNJ_1__m1-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 11 0.453653 11093.2 1 6 CACCTG CCTGGACTTTGGACTCTGGC - +4 dbcorrdb__PML__ENCSR000BQY_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.453653 11093.2 1 6 CACCTG CCTTATCTGTCCCCACCAGA - +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m1-AMPKalpha-Bdp1-Brf-CG17209-CG43143-ebi-Hsf-SREBP 10 0.453653 11093.2 1 6 CACCTG CCGGGGTTCGAACCCGGGAC - +4 dbcorrdb__POLR3G__ENCSR000EHQ_1__m2-Bdp1-Brf-CG17209-ebi-Tbp 11 0.453653 11093.2 1 6 CACCTG AACCACTGAGCCACCGAGCC - +4 dbcorrdb__RBBP5__ENCSR000AQC_1__m2-Rbbp5 1 0.453653 11093.2 1 6 CACCTG CCCGCTTCGGCTGCGCTCTC - +4 dbcorrdb__REST__ENCSR000BJL_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 3 0.453653 11093.2 1 6 CACCTG CAGCACCATGGACAGCGCCC - +4 dbcorrdb__SIN3A__ENCSR000BRM_1__m1-Sin3A 9 0.453653 11093.2 1 6 CACCTG CCGATGAGTCACGTGACAGG - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-svp 4 0.453653 11093.2 1 6 CACCTG TTCTTATCTGTTCCCCCCAC - +4 dbcorrdb__STAT2__ENCSR000FAT_1__m2-Stat92E 3 0.453653 11093.2 1 6 CACCTG AAAGCCCTGCCCTTTTCTGG - +4 dbcorrdb__TCF7L2__ENCSR000EUV_1__m3-pan 6 0.453653 11093.2 1 6 CACCTG GCCGCCTCCCTTTGATGTGC - +4 dbcorrdb__USF1__ENCSR000BGM_1__m1-ac-ase-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf-zfh1 8 0.453653 11093.2 1 6 CACCTG GCCCGGGTCACGTGGCCCCG - +4 dbcorrdb__USF1__ENCSR000BJB_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 10 0.453653 11093.2 1 6 CACCTG CGGCCCGGGTCACGTGGCCC - +4 dbcorrdb__eGFP-HDAC8__ENCSR000DJZ_1__m3 3 0.453653 11093.2 1 6 CACCTG GGCTGCATGCACACGCAGGC - +4 jaspar__MA0347.1 8 0.453653 11093.2 1 6 CACCTG TGCGATGGACCCTGATCTAG - +4 taipale_tf_pairs__ARNTL_BHLHA15_RKCACGTGNNNMCATATGKN_CAP_repr-cyc-dimm 12 0.453653 11093.2 1 6 CACCTG ACCATATGGGTGCACGTGAC - +4 taipale_tf_pairs__TEAD4_ELK3_NCCGGAANNNNNNNMATWCC_CAP_repr-sd 10 0.453653 11093.2 1 6 CACCTG GGAATGCGTTCACTTCCGGT - +4 taipale_tf_pairs__TEAD4_MAX_RCATTCCNNNNNNNCACGTG_CAP_repr-Max-sd 0 0.453653 11093.2 1 6 CACCTG CACGTGGTCGTGTGGAATGT - +4 tfdimers__MD00352-CG5641-Myc-NFAT 5 0.453653 11093.2 1 6 CACCTG TTTGCCATCTGTTCCTTTTT - +4 transfac_public__M00047 13 0.453653 11093.2 1 6 CACCTG GCGGATAAGTGTTTATCCGG - +4 dbcorrdb__CHD1__ENCSR000EBU_1__m4-Chd1 15 0.453653 11093.2 1 5 CACCTG CCTGGCCCTTGGCGTCACCC - +4 dbcorrdb__RAD21__ENCSR000EHX_1__m2-CTCF-vtd -2 0.453653 11093.2 1 4 CACCTG TCTAGTGGCCAAATTGAGAA - +4 cisbp__M0710-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.454051 11102.9 1 6 CACCTG GACCGGAAGT + +4 cisbp__M0766 3 0.454051 11102.9 1 6 CACCTG ATAGATCTAT + +4 cisbp__M0803-GATAd-GATAe-grn-pnr-srp 4 0.454051 11102.9 1 6 CACCTG ACGATATCGT + +4 cisbp__M1228 2 0.454051 11102.9 1 6 CACCTG TATGCATTAT + +4 cisbp__M1573-Smox 0 0.454051 11102.9 1 6 CACCTG TGTCTGGAAT + +4 cisbp__M1709 2 0.454051 11102.9 1 6 CACCTG TTTCCCGCAA + +4 cisbp__M1769 4 0.454051 11102.9 1 6 CACCTG ATTTTTCCGG + +4 cisbp__M5792-Bgb-lz-run-RunxA-RunxB 1 0.454051 11102.9 1 6 CACCTG AAACCGCAAA + +4 neph__UW.Motif.0079 1 0.454051 11102.9 1 6 CACCTG CCCTCTGCTG + +4 predrem__nrMotif1543 1 0.454051 11102.9 1 6 CACCTG CTCCCTTTCC + +4 predrem__nrMotif2508 2 0.454051 11102.9 1 6 CACCTG TTTCCCTTGT + +4 predrem__nrMotif809 3 0.454051 11102.9 1 6 CACCTG AAAAATCTGA + +4 predrem__nrMotif99 3 0.454051 11102.9 1 6 CACCTG TTGTTCCTCA + +4 taipale_cyt_meth__ZNF250_NTAGGCCTAN_eDBD_meth_repr 3 0.454051 11102.9 1 6 CACCTG ATAGGCCTAT + +4 transfac_pro__M01849 4 0.454051 11102.9 1 6 CACCTG GTGGGGCCGG + +4 transfac_pro__M07529 1 0.454051 11102.9 1 6 CACCTG CCACCGACAC + +4 transfac_pro__M09547 4 0.454051 11102.9 1 6 CACCTG AGGGAATCTT + +4 transfac_public__M00003 2 0.454051 11102.9 1 6 CACCTG AATAACGGAA + +4 yetfasco__YOR380W_2158 2 0.454051 11102.9 1 6 CACCTG TTTTCCGCAG + +4 cisbp__M0174-ac-ase-bigmax-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Usf 1 0.454051 11102.9 1 6 CACCTG CCACGTGACC - +4 cisbp__M0394 4 0.454051 11102.9 1 6 CACCTG GGGGCCCCCC - +4 cisbp__M0615 4 0.454051 11102.9 1 6 CACCTG AATTTACGGA - +4 cisbp__M0696-aop-Eip74EF-Ets21C-Ets98B 2 0.454051 11102.9 1 6 CACCTG ACTTCCGGGT - +4 cisbp__M1344 3 0.454051 11102.9 1 6 CACCTG CCTTATCCAT - +4 cisbp__M1479 4 0.454051 11102.9 1 6 CACCTG ACTACACAAT - +4 cisbp__M1656 4 0.454051 11102.9 1 6 CACCTG GTGGGCCCCA - +4 cisbp__M4094 2 0.454051 11102.9 1 6 CACCTG AATAACGGAA - +4 cisbp__M5928-gem-grh 1 0.454051 11102.9 1 6 CACCTG AAACCGGTTT - +4 flyfactorsurvey__BtbVII_SANGER_5_FBgn0012049-BtbVII 2 0.454051 11102.9 1 6 CACCTG TATACATAAG - +4 jaspar__MA0247.2-tin-vnd 1 0.454051 11102.9 1 6 CACCTG CCACTTGAAA - +4 scertf__morozov.HMS1 4 0.454051 11102.9 1 6 CACCTG ATCACCCCAC - +4 tiffin__TIFDMEM0000036 2 0.454051 11102.9 1 6 CACCTG TCGAACTGAA - +4 transfac_pro__M01980-aop-Eip74EF-Ets96B 3 0.454051 11102.9 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M02091-Atf6-CrebB-kay 2 0.454051 11102.9 1 6 CACCTG GTTACGTCAC - +4 yetfasco__YDR253C_2140 4 0.454051 11102.9 1 6 CACCTG GCGCCACAGT - +4 cisbp__M5431-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.454051 11102.9 1 5 CACCTG ACCGGAAGTG + +4 fantom__motif164_AGCCGATTTG -1 0.454051 11102.9 1 5 CACCTG AGCCGATTTG + +4 taipale__FLI1_DBD_ACCGGAARYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.454051 11102.9 1 5 CACCTG ACCGGAAGTG + +4 transfac_pro__M01981-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt -1 0.454051 11102.9 1 5 CACCTG ACCGGAAGTA + +4 cisbp__M0336 5 0.454051 11102.9 1 5 CACCTG TTGCTTACTT - +4 neph__UW.Motif.0127 5 0.454051 11102.9 1 5 CACCTG CTGAAATTCT - +4 predrem__nrMotif408 5 0.454051 11102.9 1 5 CACCTG GGAGTCAGCC - +4 taipale_cyt_meth__SIX1_NSRTATCRYN_FL_meth-Optix-so 5 0.454051 11102.9 1 5 CACCTG CATGATACGC - +4 transfac_pro__M06497 5 0.454051 11102.9 1 5 CACCTG ATCCCCCCCC - +4 tfdimers__MD00106-Pur-alpha 8 0.454838 11122.1 1 6 CACCTG TTTTTCTAATCCTGCCCCTTCTT + +4 tfdimers__MD00180 12 0.454838 11122.1 1 6 CACCTG GGCCGCTGCTGACAGCAGCGGCC + +4 transfac_pro__M01036-btd-EcR-eg-Eip78C-ERR-ftz-f1-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-usp 6 0.454838 11122.1 1 6 CACCTG TCCCCTGACCTTTGCCCTCTGCC + +4 transfac_pro__M02788-CG9727-Rfx 5 0.454838 11122.1 1 6 CACCTG TGTGACCCTTAGCAACCGATTAA + +4 taipale_tf_pairs__CUX1_NHLH1_NNCAGCTGNNNNNNNNATCGATN_CAP_repr-ct-HLH4C 15 0.454838 11122.1 1 6 CACCTG GATCGATTGTGGGCGCAGCTGCG - +4 taipale_tf_pairs__ALX4_EOMES_NGYGYTAAYNNNNNNTNACACNN_CAP 18 0.454838 11122.1 1 5 CACCTG GGTGCTAATTATATTTAACACCT + +4 tfdimers__MD00446-TfAP-2 10 0.455098 11128.5 1 6 CACCTG TATTTCATTAAGCCTGTTTTT + +4 transfac_pro__M01577-cyc-Mitf-tgo 7 0.455098 11128.5 1 6 CACCTG GATCAGTCACGTGACTGATCG + +4 factorbook__UA12-nej 14 0.455098 11128.5 1 6 CACCTG GGGGGGGCGGGCGGTACCATT - +4 transfac_pro__M09359 3 0.455098 11128.5 1 6 CACCTG GGTAACGTGTAGAACAAGCAA - +4 tfdimers__MD00445-TfAP-2 11 0.455462 11137.4 1 6 CACCTG TTTAGGGGATTAGCCTTTGTTC + +4 taipale_tf_pairs__HOXB2_ELF1_NYMATTANNNNNNNNGGAAGNN_CAP_repr-Eip74EF-pb 11 0.455462 11137.4 1 6 CACCTG CACTTCCGGATTCCCTAATGAC - +4 transfac_public__M00068-HLH4C 8 0.455462 11137.4 1 6 CACCTG GAGGGGCGCAGCTGCGCCCCAA - +4 cisbp__M1853 0 0.456055 11151.9 1 6 CACCTG CGCTTT - +4 transfac_pro__M04983 -2 0.456055 11151.9 1 4 CACCTG CCGGGG + +4 fantom__motif46_CGNAGT -2 0.456055 11151.9 1 4 CACCTG ACTACG - +4 transfac_pro__M08840-CG9766 -2 0.456055 11151.9 1 4 CACCTG CTTTTT - +4 jaspar__MA0130.1 3 0.456055 11151.9 1 3 CACCTG ATCCAC + +4 c2h2_zfs__M1843 3 0.456055 11151.9 1 3 CACCTG ATCCAC - +4 hdpi__ZNF671 -3 0.456055 11151.9 1 3 CACCTG CTGCCA - +4 cisbp__M0820-grh 1 0.456091 11152.8 1 6 CACCTG TAACCGGTT + +4 cisbp__M1295 1 0.456091 11152.8 1 6 CACCTG TTACGCAAA + +4 cisbp__M3576-Dr 3 0.456091 11152.8 1 6 CACCTG CCGTAATTG + +4 flyfactorsurvey__HLHmdelta_SANGER_10_FBgn0002734-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 3 0.456091 11152.8 1 6 CACCTG TGGCACGTG + +4 flyfactorsurvey__br-PLPE_SOLEXA_10-br 0 0.456091 11152.8 1 6 CACCTG CTTCTAATG + +4 predrem__nrMotif2029-Myc-Sap30 2 0.456091 11152.8 1 6 CACCTG CCCACGTGG + +4 predrem__nrMotif2357 0 0.456091 11152.8 1 6 CACCTG TGCCTATTT + +4 predrem__nrMotif292 2 0.456091 11152.8 1 6 CACCTG TCAAACTTT + +4 predrem__nrMotif925 1 0.456091 11152.8 1 6 CACCTG TGACTTGCT + +4 predrem__nrMotif983 2 0.456091 11152.8 1 6 CACCTG TTCACTTCA + +4 transfac_pro__M00976-sima-ss-tgo 0 0.456091 11152.8 1 6 CACCTG TGCGTGCGG + +4 cisbp__M3230-ham 1 0.456091 11152.8 1 6 CACCTG TTATCTTGT - +4 hocomoco__HMBX1_HUMAN.H11MO.0.D 1 0.456091 11152.8 1 6 CACCTG TAACTAGCT - +4 predrem__nrMotif2000-Ets21C 2 0.456091 11152.8 1 6 CACCTG GCCACTTCC - +4 predrem__nrMotif911 1 0.456091 11152.8 1 6 CACCTG TGTCCTTGA - +4 taipale_cyt_meth__NKX2-3_NTCGTTGAN_FL_meth 3 0.456091 11152.8 1 6 CACCTG CTCAACGAC - +4 transfac_pro__M00981-Atf3-Atf6-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 1 0.456091 11152.8 1 6 CACCTG TGACGTCAC - +4 predrem__nrMotif2412 4 0.456091 11152.8 1 5 CACCTG CCAGGACAT + +4 predrem__nrMotif2666 4 0.456091 11152.8 1 5 CACCTG TGTGTACTT + +4 transfac_public__M00469-TfAP-2 -1 0.456091 11152.8 1 5 CACCTG GCCCGGGGG + +4 cisbp__M2934-TfAP-2 -1 0.456091 11152.8 1 5 CACCTG GCCCGGGGG - +4 cisbp__M6331 4 0.456091 11152.8 1 5 CACCTG CCGTCAGCA - +4 hocomoco__HIC1_HUMAN.H11MO.0.C 4 0.456091 11152.8 1 5 CACCTG GGGCAACCC - +4 predrem__nrMotif971 5 0.456091 11152.8 1 4 CACCTG TCAACCACA + +4 cisbp__M4901-CG7386-D19A 5 0.456091 11152.8 1 4 CACCTG TCATTCACA - +4 flyfactorsurvey__D19A_F10-12_SANGER_5_FBgn0022935-CG7386-D19A 5 0.456091 11152.8 1 4 CACCTG TCATTCACA - +4 predrem__nrMotif1393 -2 0.456091 11152.8 1 4 CACCTG CCTAGCTCC - +4 predrem__nrMotif1435 5 0.456091 11152.8 1 4 CACCTG ATGGGAACA - +4 predrem__nrMotif1768 5 0.456091 11152.8 1 4 CACCTG TGACTCACA - +4 predrem__nrMotif603 -2 0.456091 11152.8 1 4 CACCTG CCTTTCTCC - +4 scertf__badis.GSM1 -2 0.457242 11180.9 1 4 CACCTG CCGGA + +4 transfac_pro__M01700 -2 0.457242 11180.9 1 4 CACCTG CCGAC + +4 tfdimers__MD00058-pho-phol-Smox 10 0.457404 11184.9 1 6 CACCTG TTTCTCCCGCCATCTGTCTGTCTTTCTT + +4 cisbp__M3407 11 0.458587 11213.8 1 6 CACCTG AGTTAATTATTAACCAA + +4 transfac_pro__M01489-abd-A-Antp-CG32532-Dfd-HGTX-Scr-Ubx 10 0.458587 11213.8 1 6 CACCTG GAAAATTAATTACTTCG + +4 transfac_pro__M09060 6 0.458587 11213.8 1 6 CACCTG CACCTCCACCGACATTA + +4 transfac_pro__M03127-Clk-Hey-tai 6 0.458587 11213.8 1 6 CACCTG ATTGGACACGTGCCATA - +4 transfac_pro__M05331-ci-lmd-sug 9 0.458587 11213.8 1 6 CACCTG GGGCCACCCTACTTTAA - +4 transfac_pro__M05414-opa 4 0.458587 11213.8 1 6 CACCTG GGGTGACCCGACTTTAA - +4 tfdimers__MD00168-GATAe-grn-pnr-srp 7 0.458648 11215.3 1 6 CACCTG CTTTCCTTATCTCCCACCCCCACCCCCTCCC + +4 flyfactorsurvey__shn-F1-2_SOLEXA_FBgn0003396-shn 5 0.459031 11224.7 1 6 CACCTG GGGGATTCCCTGGGG + +4 homer__GTCATGCHTGRCTGS_Pax8-Poxm-ey-sv-toy 4 0.459031 11224.7 1 6 CACCTG GTCATGCCTGACTGC + +4 taipale_tf_pairs__MEIS1_HOXA13_SYNRTAAANNTGTCA_CAP 6 0.459031 11224.7 1 6 CACCTG CTAATAAAACTGTCA + +4 taipale_tf_pairs__TEAD4_EOMES_NNGYGYSACATTCCN_CAP_repr-sd 6 0.459031 11224.7 1 6 CACCTG AGGTGTGACATTCCG + +4 transfac_pro__M02839 5 0.459031 11224.7 1 6 CACCTG ACCCGTATCAAATTT + +4 transfac_pro__M07248-Atf3-Atf6-CrebB-Xbp1 5 0.459031 11224.7 1 6 CACCTG CCGGTGACGTCAGCG + +4 transfac_pro__M07916-CG12219 2 0.459031 11224.7 1 6 CACCTG CACACCCCTTACACA + +4 transfac_pro__M09027 7 0.459031 11224.7 1 6 CACCTG CCACCTCCACCGCCA + +4 transfac_pro__M09137 7 0.459031 11224.7 1 6 CACCTG AGATCTAGATCTGAA + +4 transfac_pro__M09329 8 0.459031 11224.7 1 6 CACCTG TAAAAAAATATCTTA + +4 transfac_pro__M09498 8 0.459031 11224.7 1 6 CACCTG GTGAATGCCACGTGG + +4 transfac_pro__M09516-Atf6-CrebA-Xbp1 3 0.459031 11224.7 1 6 CACCTG TGCCACGTCAGCATT + +4 cisbp__M4480-ac-ase-btd-cnc-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-Usf 5 0.459031 11224.7 1 6 CACCTG CCCGCCACGTGACCC - +4 cisbp__M6204-Eip74EF-Ets96B-pnt 6 0.459031 11224.7 1 6 CACCTG ACTCACTTCCTGCTA - +4 cisbp__M6558 2 0.459031 11224.7 1 6 CACCTG GGCACCCAAGGGTGC - +4 neph__UW.Motif.0594 9 0.459031 11224.7 1 6 CACCTG GGCTTCCTTTCCCAG - +4 taipale_tf_pairs__FLI1_HOXB13_RSCGGAANYNRTAAA_CAP 8 0.459031 11224.7 1 6 CACCTG TTTATTACTTCCGGT - +4 transfac_pro__M08983-CG4730-CG7101 6 0.459031 11224.7 1 6 CACCTG CCAGCACAACTAACC - +4 transfac_pro__M09055 8 0.459031 11224.7 1 6 CACCTG TCGTCGCCGACATCA - +4 neph__UW.Motif.0463 -1 0.459031 11224.7 1 5 CACCTG AAATTCTTTCTGTCT + +4 cisbp__M4838-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 10 0.459031 11224.7 1 5 CACCTG CAGCCACGCCCACCT - +4 flyfactorsurvey__CG3065_F1-3_SOLEXA_2.5_FBgn0034946-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 10 0.459031 11224.7 1 5 CACCTG CAGCCACGCCCACCT - +4 factorbook__UA4-CG10431-pho-phol -2 0.459031 11224.7 1 4 CACCTG CCTCAACCAAGATGG - +4 tfdimers__MD00043-Hand-Hnf4-svp 11 0.461876 11294.2 1 6 CACCTG GTAACAAAGGCCATCTGGCATTTTTTT + +4 tfdimers__MD00311-NfI-Usf 10 0.461876 11294.2 1 6 CACCTG TTCCCCTGGCCACCTGCCAAGCCCTAC + +4 cisbp__M5575 0 0.462587 11311.6 1 6 CACCTG AACCGAAACCA + +4 hocomoco__CREM_HUMAN.H11MO.0.C-Atf-2-CG44247-CrebB-Jra 4 0.462587 11311.6 1 6 CACCTG CACTGACGTCA + +4 hocomoco__PO2F2_HUMAN.H11MO.0.A-nub-pdm2 5 0.462587 11311.6 1 6 CACCTG ATATGCAAATG + +4 predrem__nrMotif1739 1 0.462587 11311.6 1 6 CACCTG TTTCCCCATTG + +4 taipale__IRF5_full_NACCGAAACYN_repr 0 0.462587 11311.6 1 6 CACCTG AACCGAAACCA + +4 taipale__MYBL1_DBD_NNAACCGTTNN_repr-Myb 2 0.462587 11311.6 1 6 CACCTG AAAACCGTTAA + +4 taipale_cyt_meth__GABPA_NACCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.462587 11311.6 1 6 CACCTG GACCGGAAGTG + +4 taipale_cyt_meth__KLF4_NRCCMCGCCCN_eDBD_meth-btd-cbt-CG42741-dar1-luna-Sp1-Spps 0 0.462587 11311.6 1 6 CACCTG CGCCACGCCCA + +4 cisbp__M3229-ham-srp 1 0.462587 11311.6 1 6 CACCTG TTATCTTATCT - +4 cisbp__M5860-Eip74EF-Ets96B-Ets98B 0 0.462587 11311.6 1 6 CACCTG TACATCCGGGT - +4 cisbp__M6534-CG34367-E5-ems-unpg-Vsx1-Vsx2 4 0.462587 11311.6 1 6 CACCTG TAATTAGCTAA - +4 factorbook__ELF1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-aop-bs-pnt 1 0.462587 11311.6 1 6 CACCTG CCACTTCCGGT - +4 taipale__SPDEF_full_AMCCGGATGTN-Eip74EF-Ets96B-Ets98B 0 0.462587 11311.6 1 6 CACCTG TACATCCGGGT - +4 transfac_pro__M01903 2 0.462587 11311.6 1 6 CACCTG AGCTCCGGAGA - +4 transfac_pro__M05404 0 0.462587 11311.6 1 6 CACCTG TCCCTTGTCCA - +4 transfac_pro__M09464 4 0.462587 11311.6 1 6 CACCTG CGTTGACTTTT - +4 transfac_public__M00082-ham-srp 1 0.462587 11311.6 1 6 CACCTG TTATCTTATCT - +4 hocomoco__HIC2_HUMAN.H11MO.0.D -1 0.462587 11311.6 1 5 CACCTG GCCTGGCATGT - +4 hocomoco__RFX1_HUMAN.H11MO.1.B-CG5846-CG9727-Max-Rfx-SREBP -1 0.462587 11311.6 1 5 CACCTG CCATGGCAACC - +4 transfac_pro__M06665 6 0.462587 11311.6 1 5 CACCTG TTTTATCACGA - +4 cisbp__M5789-lz-run-RunxA-RunxB 10 0.464165 11350.2 1 6 CACCTG TAACCGCAAAAACCGCAA + +4 taipale_tf_pairs__RFX3_SREBF2_NNRGYAACNTCACGTGAY_CAP_repr-Rfx-SREBP 10 0.464165 11350.2 1 6 CACCTG ATGGCAACATCACGTGAC + +4 transfac_pro__M06469 12 0.464165 11350.2 1 6 CACCTG GTAGTACGGGATTACGTT + +4 transfac_public__M00005-crp 5 0.464165 11350.2 1 6 CACCTG AGAGTCAGCTGTGGTCAG + +4 yetfasco__YKL112W_1993 11 0.464165 11350.2 1 6 CACCTG AGATCACTTCCTACGACA + +4 cisbp__M4656-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-svp 2 0.464165 11350.2 1 6 CACCTG CTTATCTGCCCCCCCCAG - +4 hocomoco__EGR2_MOUSE.H11MO.1.A-CTCF-CoRest-Klf15-Spps-btd-ct-klu-peb-sr 4 0.464165 11350.2 1 6 CACCTG CCCCCCCCTCCCACGCCC - +4 taipale_cyt_meth__NHLH1_NKGNMKCAGCTGCGYCMN_eDBD-HLH4C 6 0.464165 11350.2 1 6 CACCTG GGGACGCAGCTGCGCCCC - +4 transfac_pro__M05401 4 0.464165 11350.2 1 6 CACCTG TTGGCTCCTATTAACCCA - +4 transfac_pro__M09183 11 0.464165 11350.2 1 6 CACCTG AACGCGTTTTTTACACGG - +4 flyfactorsurvey__suHw_FlyReg_FBgn0003567-su(Hw) 13 0.464165 11350.2 1 5 CACCTG AAAATACATTGCATACCC - +4 cisbp__M4624-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.464365 11355.1 1 6 CACCTG GATGACGTCACCCC + +4 cisbp__M6368-CG7786-gt-Pdp1-vri 6 0.464365 11355.1 1 6 CACCTG ATGCATTACATAAC + +4 swissregulon__sacCer__SKN7 8 0.464365 11355.1 1 6 CACCTG TATGGCCATAACTG - +4 taipale_cyt_meth__PAX4_NAATTANNTAATTN_eDBD_meth_repr-ap-bs-bsh-CG34367-CG9876-E5-ems-en-gsb-gsb-n-inv-OdsH-pdm3-prd-unpg-Vsx1-Vsx2 4 0.464365 11355.1 1 6 CACCTG TAATTAGCTAATTA - +4 taipale_tf_pairs__TEAD4_ELF1_GGAATGCGGAAGTN_CAP_repr-Eip74EF-sd 0 0.464365 11355.1 1 6 CACCTG TACTTCCGCATTCC - +4 transfac_pro__M01337-Awh-C15-CG18599-CG9876-Dll-E5-ems-en-eve-ind-inv-lab-Lim3-OdsH-otp-pb-ro-slou-zen2-zfh2 6 0.464365 11355.1 1 6 CACCTG ACTAATTACCTCAA - +4 transfac_pro__M01871-kn 4 0.464365 11355.1 1 6 CACCTG CAATTCCCCTGGGA - +4 yetfasco__YLR014C_2064 8 0.464365 11355.1 1 6 CACCTG TCGGAGAATGCCGA - +4 neph__UW.Motif.0271 9 0.464365 11355.1 1 5 CACCTG GAAATCTGATTCCA + +4 transfac_pro__M00654 -1 0.464365 11355.1 1 5 CACCTG ACGTGTCGCCATTC + +4 flyfactorsurvey__CG31782_F9-11_SANGER_5_FBgn0051782-CR43670 9 0.464365 11355.1 1 5 CACCTG TTTGGTGGTGACCT - +4 cisbp__M1878 10 0.464365 11355.1 1 4 CACCTG GTTAATTATTAACC + +4 yetfasco__YPR186C_1321-CG42726 10 0.464365 11355.1 1 4 CACCTG TGTAGTGGGTGACC + +4 cisbp__M2631 -2 0.464365 11355.1 1 4 CACCTG CCTCGGGATCTGTG - +4 transfac_public__M00501 -2 0.464365 11355.1 1 4 CACCTG CCTCGGGAACTGTG - +4 cisbp__M6509-sd 5 0.46666 11411.2 1 6 CACCTG AAAAATAGCCCT + +4 flyfactorsurvey__twi_FlyReg_FBgn0003900-twi 1 0.46666 11411.2 1 6 CACCTG TCGCATATGTTG + +4 transfac_pro__M03556-NFAT 6 0.46666 11411.2 1 6 CACCTG GGAAAACTCCAT + +4 transfac_pro__M08945-Atf-2-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.46666 11411.2 1 6 CACCTG TGTGACGTCATT + +4 transfac_pro__M09048 6 0.46666 11411.2 1 6 CACCTG TTCGCCGACATC + +4 yetfasco__YNL139C_786-tho2 6 0.46666 11411.2 1 6 CACCTG ATTTTCTTCTTT + +4 cisbp__M1562 5 0.46666 11411.2 1 6 CACCTG ATCCGTACGATA - +4 jaspar__MA1056.1 5 0.46666 11411.2 1 6 CACCTG ATCCGTACGATA - +4 scertf__foat.SKN7 6 0.46666 11411.2 1 6 CACCTG GGTCGGGGCCTT - +4 taipale_cyt_meth__CREB1_NRTGAYGTCAYN_FL_meth-Atf3-Atf6-CG44247-CG7786-cnc-CrebA-CrebB-gt-Jra-kay-Pdp1-REPTOR-BP-Xbp1 3 0.46666 11411.2 1 6 CACCTG GATGACGTCACG - +4 taipale_cyt_meth__POU2F2_NTAATNTATGCN_eDBD_repr-nub-pdm2 0 0.46666 11411.2 1 6 CACCTG TGCATACATTAC - +4 transfac_pro__M01186-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-maf-S-Xbp1 3 0.46666 11411.2 1 6 CACCTG GCTGACGTCATC - +4 transfac_pro__M05484 1 0.46666 11411.2 1 6 CACCTG TAACATGCACAG - +4 transfac_pro__M06002 6 0.46666 11411.2 1 6 CACCTG TCTGCCCACCCT - +4 transfac_pro__M06021 6 0.46666 11411.2 1 6 CACCTG TCTTCTTTCCAG - +4 transfac_pro__M06037 6 0.46666 11411.2 1 6 CACCTG GCTTATTGCCTG - +4 transfac_pro__M06109 6 0.46666 11411.2 1 6 CACCTG GCGTCTTACCCT - +4 transfac_pro__M06418-zfh1 1 0.46666 11411.2 1 6 CACCTG GATCCTTTTCAG - +4 transfac_pro__M06459 4 0.46666 11411.2 1 6 CACCTG TACTCACCACTA - +4 transfac_pro__M06541-crol 3 0.46666 11411.2 1 6 CACCTG GATTCCCTAACG - +4 homer__GSCTGTCACTCA_PBX1 -1 0.46666 11411.2 1 5 CACCTG GCCTGTCACTCA + +4 predrem__nrMotif847 -1 0.46666 11411.2 1 5 CACCTG AACTTTAAAAAA + +4 transfac_pro__M03545-CG12018-Dif-dl-Rel 7 0.46666 11411.2 1 5 CACCTG GGGGAATTTCCC + +4 transfac_pro__M05847 -1 0.46666 11411.2 1 5 CACCTG GCCACATAAAGC + +4 homer__AGGGGATTTCCC_NFkB-p65-Dif-Rel-dl-shn 7 0.46666 11411.2 1 5 CACCTG GGGAAATCCCCT - +4 taipale_tf_pairs__MEIS1_EOMES_AGGTGTTGACAN_CAP_repr 7 0.46666 11411.2 1 5 CACCTG CTGTCAACACGT - +4 transfac_pro__M05905 7 0.46666 11411.2 1 5 CACCTG TCCGTTTTACCA - +4 transfac_pro__M06687 7 0.46666 11411.2 1 5 CACCTG TATGGAATCCCT - +4 transfac_pro__M06703 7 0.46666 11411.2 1 5 CACCTG TCATTTTTCCCA - +4 cisbp__M6099-pan -2 0.46666 11411.2 1 4 CACCTG CCTTTGATCTTT - +4 jaspar__MA0097.1-Atf6-CrebA-CrebB-Xbp1 8 0.46666 11411.2 1 4 CACCTG GGCCACGTCATC - +4 taipale__Tcf7_DBD_NAAGATCAAAGG-pan -2 0.46666 11411.2 1 4 CACCTG CCTTTGATCTTT - +4 transfac_pro__M06520 8 0.46666 11411.2 1 4 CACCTG TCCCCCGCAACT - +4 cisbp__M1472 2 0.466756 11413.6 1 6 CACCTG TTGATCTC + +4 cisbp__M2978-Atf6-CrebA 1 0.466756 11413.6 1 6 CACCTG TGACGTGG + +4 taipale_cyt_meth__BSX_NTCGTTAN_eDBD_meth-bap-bsh-btn-Dll-Dr-en-eve-exex-ind-inv-lab-Lim1-unpg 0 0.466756 11413.6 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__ISL2_SCACTTAN_eDBD-tup 1 0.466756 11413.6 1 6 CACCTG GCACTTAA + +4 transfac_pro__M04906-Sin3A 1 0.466756 11413.6 1 6 CACCTG ACAGCTCC + +4 transfac_public__M00483-Atf6-CrebA 1 0.466756 11413.6 1 6 CACCTG TGACGTGG + +4 predrem__nrMotif1639 1 0.466756 11413.6 1 6 CACCTG TGTCCTTG - +4 transfac_pro__M04856 2 0.466756 11413.6 1 6 CACCTG TGAAACTT - +4 cisbp__M0658 -1 0.466756 11413.6 1 5 CACCTG ACTTTTTG - +4 hocomoco__NFKB1_HUMAN.H11MO.0.A-Rel 3 0.466756 11413.6 1 5 CACCTG ATTTCCCT - +4 jaspar__MA0978.1 3 0.466756 11413.6 1 5 CACCTG GCCGACAT - +4 predrem__nrMotif903 3 0.466756 11413.6 1 5 CACCTG CTTCACCA - +4 swissregulon__hs__DMAP1_NCOR_1_2__SMARC.p2-DMAP1-Iswi-Smr-mor -1 0.466756 11413.6 1 5 CACCTG AACCGACA - +4 predrem__nrMotif340 4 0.466756 11413.6 1 4 CACCTG GGGAAACC + +4 transfac_pro__M00671-pan -2 0.466756 11413.6 1 4 CACCTG CCTTTGAA + +4 transfac_pro__M07805-lbe -2 0.466756 11413.6 1 4 CACCTG CCTTATTA - +4 taipale_cyt_meth__OVOL2_NWWCCGTTAYNYN_FL_meth-ovo 1 0.467051 11420.8 1 6 CACCTG ATACCGTTATTTG + +4 taipale_cyt_meth__OVOL2_NWWCCGTTAYNYN_eDBD_meth-ovo 1 0.467051 11420.8 1 6 CACCTG ATACCGTTATTTA + +4 transfac_pro__M01135 6 0.467051 11420.8 1 6 CACCTG TTCCAACAACAGA + +4 transfac_pro__M01304-bs 0 0.467051 11420.8 1 6 CACCTG GACCATATAAGGC + +4 taipale_tf_pairs__TEAD4_HOXB13_CTCGTAAAATGYN_CAP_repr-sd 7 0.467051 11420.8 1 6 CACCTG CGCATTTTACGAG - +4 predrem__nrMotif937 -1 0.467051 11420.8 1 5 CACCTG ACTTTTTTTTTTT + +4 cisbp__M1032-al-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-en-inv-Lim1-Lim3-Lmx1a-OdsH-otp-repo-unc-4-Vsx2 1 0.467582 11433.8 1 6 CACCTG CTAATTA + +4 cisbp__M1828 1 0.467582 11433.8 1 6 CACCTG TTTCCGC + +4 elemento__CACTTCC-Eip74EF 0 0.467582 11433.8 1 6 CACCTG CACTTCC + +4 flyfactorsurvey__lola_SANGER_5_FBgn0005630-lola 1 0.467582 11433.8 1 6 CACCTG AAAGCTC + +4 taipale_cyt_meth__NANOG_TTAACGA_eDBD_meth-Lim1-Lim3 1 0.467582 11433.8 1 6 CACCTG TTAACGA + +4 elemento__CAGGACA 1 0.467582 11433.8 1 6 CACCTG TGTCCTG - +4 elemento__CAGGCCC 1 0.467582 11433.8 1 6 CACCTG GGGCCTG - +4 elemento__CCAGGCC 0 0.467582 11433.8 1 6 CACCTG GGCCTGG - +4 elemento__GCAGGAC 0 0.467582 11433.8 1 6 CACCTG GTCCTGC - +4 transfac_pro__M07429-Smox 1 0.467582 11433.8 1 6 CACCTG CTGTCTG - +4 predrem__nrMotif735 2 0.467582 11433.8 1 5 CACCTG CACTCCT + +4 predrem__nrMotif367 2 0.467582 11433.8 1 5 CACCTG CTTGCCT - +4 stark__ACANACA 3 0.467582 11433.8 1 4 CACCTG ACAAACA + +4 hdpi__EBF1-kn -2 0.467582 11433.8 1 4 CACCTG CCCTTTT - +4 hdpi__FAM127B 4 0.467582 11433.8 1 3 CACCTG TGGCAAC + +4 taipale_tf_pairs__ARNTL_PITX1_NNCACGTGNNNNRGMTTAN_CAP_repr-cyc-Ptx1 2 0.468271 11450.6 1 6 CACCTG GGCACGTGACAGGGATTAA + +4 transfac_pro__M09390 1 0.468271 11450.6 1 6 CACCTG TTACGTGTTTTACACGTAA + +4 taipale_tf_pairs__CLOCK_EVX1_YRATTANNNNNNNCACGTG_CAP_repr-Clk-eve 0 0.468271 11450.6 1 6 CACCTG CACGTGTACGCAATAATTA - +4 transfac_pro__M09387 4 0.468271 11450.6 1 6 CACCTG AGGTTACTTGTTCCACACG - +4 neph__UW.Motif.0666 9 0.468295 11451.2 1 6 CACCTG AACATTTCTCATCTTC + +4 taipale__RUNX3_DBD_NAACCGCAAACCRCAN-Bgb-lz-run-RunxA-RunxB 8 0.468295 11451.2 1 6 CACCTG TAACCGCAAACCGCAA + +4 taipale_cyt_meth__ERG_NACCGGATATCCGGTN_eDBD-Ets21C-Ets97D 0 0.468295 11451.2 1 6 CACCTG AACCGGATATCCGGTT + +4 taipale_cyt_meth__POU6F1_TYATTANNNNTYATTA_FL_meth_repr-ems-pdm3 6 0.468295 11451.2 1 6 CACCTG TCATTACACCTCATTA + +4 taipale_tf_pairs__ARNTL_PITX1_CACGTGNNNRGATTAN_CAP_repr-cyc-Ptx1 0 0.468295 11451.2 1 6 CACCTG CACGTGCTCGGATTAT + +4 transfac_pro__M01452-abd-A-Antp-bsh-btn-Dfd-ind-lab-Lim3-pb-Scr-slou-Ubx 8 0.468295 11451.2 1 6 CACCTG ACGGTAATTAGCTCAG + +4 transfac_pro__M06821-salm-salr 5 0.468295 11451.2 1 6 CACCTG TGCGTGCCCTTTAAAC + +4 neph__UW.Motif.0301 5 0.468295 11451.2 1 6 CACCTG TGGCAGATTTTCACAG - +4 neph__UW.Motif.0622 10 0.468295 11451.2 1 6 CACCTG TTTGAATTTTTTCCAG - +4 taipale_cyt_meth__FOXA1_NSYTAWGTAAACAAAN_FL_meth-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxP-HDAC1-nej 7 0.468295 11451.2 1 6 CACCTG GTTTGTTTACTTAACG - +4 taipale_tf_pairs__HOXD12_ELK3_RSCGGAAGTAATAAAN_CAP 6 0.468295 11451.2 1 6 CACCTG CTTTATTACTTCCGCT - +4 transfac_pro__M00721 3 0.468295 11451.2 1 6 CACCTG CCACACCCAAGGGATG - +4 transfac_pro__M02740 4 0.468295 11451.2 1 6 CACCTG CAAATTCCTCGAAAGA - +4 transfac_pro__M02887-svp 5 0.468295 11451.2 1 6 CACCTG TACGTGACCCGGCGCG - +4 transfac_public__M00222-Hand 9 0.468295 11451.2 1 6 CACCTG AATGCCAGACGCCATT - +4 transfac_pro__M01798-Bdp1-CG17209 12 0.468295 11451.2 1 4 CACCTG TCAGGAGTTCGAGACC + +4 cisbp__M0356 3 0.470376 11502.1 1 6 CACCTG GATTACTAAT + +4 cisbp__M1203 2 0.470376 11502.1 1 6 CACCTG GTAATGGGTT + +4 cisbp__M1779 0 0.470376 11502.1 1 6 CACCTG AACCGCGGTT + +4 cisbp__M2253-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 2 0.470376 11502.1 1 6 CACCTG GGCACGTGCC + +4 cisbp__M2460 3 0.470376 11502.1 1 6 CACCTG ATTTACATCA + +4 homer__AACCGGAAGT_ETS-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-nej-pnt 0 0.470376 11502.1 1 6 CACCTG AACCGGAAGT + +4 homer__RSCACTYRAG_Nkx2.1-bap-scro-vnd 2 0.470376 11502.1 1 6 CACCTG GGCACTCAAG + +4 homer__TTCCKNAGAA_STAT6-Stat92E 0 0.470376 11502.1 1 6 CACCTG TTCCTTAGAA + +4 jaspar__MA0449.1-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 2 0.470376 11502.1 1 6 CACCTG GGCACGTGCC + +4 predrem__nrMotif1827 0 0.470376 11502.1 1 6 CACCTG CTCCATGGCC + +4 predrem__nrMotif2150 2 0.470376 11502.1 1 6 CACCTG TGAGCCTGAG + +4 predrem__nrMotif2425 2 0.470376 11502.1 1 6 CACCTG CCACCCTCTC + +4 predrem__nrMotif2559 3 0.470376 11502.1 1 6 CACCTG GCATGCCAGG + +4 taipale__RUNX3_DBD_NAACCGCAAN-Bgb-lz-run-RunxA-RunxB 1 0.470376 11502.1 1 6 CACCTG AAACCGCAAA + +4 taipale__TFCP2_full_NAACCGGTTN-gem-grh 1 0.470376 11502.1 1 6 CACCTG AAACCGGTTT + +4 taipale_cyt_meth__TEAD2_NRCATTCCWN_FL_meth-sd 0 0.470376 11502.1 1 6 CACCTG CGCATTCCAT + +4 taipale_tf_pairs__POU5F1_WATGCGCATW_HT 4 0.470376 11502.1 1 6 CACCTG TATGCGCATA + +4 transfac_pro__M01042-ci-lmd-opa-sug 3 0.470376 11502.1 1 6 CACCTG GACCACCCAG + +4 yetfasco__YJR147W_992 2 0.470376 11502.1 1 6 CACCTG ATTTCCTTCA + +4 cisbp__M0294-CrebB 1 0.470376 11502.1 1 6 CACCTG TTACGTCATC - +4 cisbp__M0747-bin-bs-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.470376 11502.1 1 6 CACCTG TGTTTACATT - +4 cisbp__M1141-achi-hth-vis 4 0.470376 11502.1 1 6 CACCTG ATGACACATT - +4 cisbp__M5423-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.470376 11502.1 1 6 CACCTG TACTTCCGGT - +4 cisbp__M6324-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 4 0.470376 11502.1 1 6 CACCTG GCCCCGCCCA - +4 homer__AACAGGAAAT_EWS_FLI1-fusion-Ets21C-Ets97D-GATAe-aop-bs-grn-pnr-pnt 2 0.470376 11502.1 1 6 CACCTG ATTTCCTGTT - +4 predrem__nrMotif1818 2 0.470376 11502.1 1 6 CACCTG AAAAACTGCC - +4 transfac_pro__M00761 1 0.470376 11502.1 1 6 CACCTG GGACTTGTCT - +4 transfac_pro__M01983-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 0 0.470376 11502.1 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02069-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 0 0.470376 11502.1 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02077 3 0.470376 11502.1 1 6 CACCTG CACTTCCTCT - +4 transfac_pro__M06142 2 0.470376 11502.1 1 6 CACCTG TTTACTTTCC - +4 transfac_pro__M06379 4 0.470376 11502.1 1 6 CACCTG CTCGCCCCAC - +4 cisbp__M1800 5 0.470376 11502.1 1 5 CACCTG AATTTTTCCG + +4 predrem__nrMotif1442 5 0.470376 11502.1 1 5 CACCTG TACTGAACAT + +4 predrem__nrMotif86 -1 0.470376 11502.1 1 5 CACCTG AACTGAAAAT + +4 cisbp__M0032 5 0.470376 11502.1 1 5 CACCTG CTGCCGACAT - +4 jaspar__MA0971.1 5 0.470376 11502.1 1 5 CACCTG TTGCCGACAT - +4 predrem__nrMotif1703 5 0.470376 11502.1 1 5 CACCTG AAACAGGCCT - +4 predrem__nrMotif2352 5 0.470376 11502.1 1 5 CACCTG AAAATAAACT - +4 stark__RAGTGAAAGT-Blimp-1 -1 0.470376 11502.1 1 5 CACCTG ACTTTCACTC - +4 cisbp__M2312-Mad-Sox100B-Sox102F-Sox14-SoxN -2 0.470376 11502.1 1 4 CACCTG CCTTTGTTTT + +4 jaspar__MA0514.1-Mad-Sox14-Sox100B-Sox102F-SoxN -2 0.470376 11502.1 1 4 CACCTG CCTTTGTTTT + +4 taipale_cyt_meth__BATF_NMATGACACN_FL_meth 6 0.470376 11502.1 1 4 CACCTG CCATGACACG + +4 predrem__nrMotif1736 -2 0.470376 11502.1 1 4 CACCTG TCTGTTCTCT - +4 taipale_cyt_meth__HOXB7_NGTAATTANN_FL-abd-A-Antp-ap-Awh-CG18599-CG32532-CG4328-Dfd-E5-ems-en-eve-hbn-ind-lab-lbl-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-Scr-Ubx-unpg-Vsx1-zen2 6 0.470376 11502.1 1 4 CACCTG GTTAATTACC - +4 tfdimers__MD00286 14 0.47051 11505.4 1 6 CACCTG GCATATAATGGGATTAACTAAAATTATAA + +4 tfdimers__MD00471-E(bx) 18 0.47051 11505.4 1 6 CACCTG CCCAAAACCACAACCCACATCCTGTCTCC + +4 tfdimers__MD00248-lz-run-RunxA-RunxB 17 0.47051 11505.4 1 6 CACCTG TATATTAGTTAATAATTAACCACATTTTT - +4 cisbp__M2485 13 0.471043 11518.4 1 6 CACCTG GCGGATAAGTGTTTACCCGG + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m3 2 0.471043 11518.4 1 6 CACCTG AGCAACACAAATTGGCCAGC + +4 dbcorrdb__EP300__ENCSR000AQB_1__m7-nej 0 0.471043 11518.4 1 6 CACCTG AAACTGGGCTTACTGAAAGA + +4 dbcorrdb__EP300__ENCSR000BPW_1__m3-nej-sd 9 0.471043 11518.4 1 6 CACCTG GATGACACATTCCTGAGAGA + +4 dbcorrdb__HMGN3__ENCSR000DOB_1__m1-CoRest-CrebB-CycT-ebi-E(z)-GATAd-GATAe-grn-HDAC1-HLH3B-pnr-RpII215-srp-svp 2 0.471043 11518.4 1 6 CACCTG CTTATCGGCCGCCCCCGGGC + +4 dbcorrdb__POLR2A__ENCSR000EHL_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-svp 4 0.471043 11518.4 1 6 CACCTG TCCTTATCTGCCCCCCCCAG + +4 dbcorrdb__RCOR1__ENCSR000EGG_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.471043 11518.4 1 6 CACCTG TCTTATCTGCGCCCCCCAGC + +4 dbcorrdb__TAF1__ENCSR000BQN_1__m1-CG10431-lid-pho-phol-Rbbp5-RpII215-Taf1-Taf7 8 0.471043 11518.4 1 6 CACCTG GCCGCCGGCATCTTGGCGGG + +4 taipale_cyt_meth__ETS2_NACAGGANNNNNNTCCTGTN_FL_meth_repr-aop-Ets96B-Ets97D-pnt 12 0.471043 11518.4 1 6 CACCTG AACAGGAAGTACTTCCTGTT + +4 dbcorrdb__ATF3__ENCSR000BJY_1__m3-CrebB-Usf 2 0.471043 11518.4 1 6 CACCTG GCTCCCTAGTGGCGTCGCCG - +4 dbcorrdb__BHLHE40__ENCSR000BID_1__m1-bigmax-btd-Clk-cnc-CrebB-cyc-E2f1-E(z)-h-Max-Myc-Spps-SREBP-tgo-Usf-zfh1 8 0.471043 11518.4 1 6 CACCTG CGGGCCGGCACGTGACCGGG - +4 dbcorrdb__JUN__ENCSR000EGH_1__m2-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 10 0.471043 11518.4 1 6 CACCTG TCGATGACGTCACCTCCTGT - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m6-RpII215 11 0.471043 11518.4 1 6 CACCTG GACTGTTTACCAACCTCCGC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m5-RpII215 4 0.471043 11518.4 1 6 CACCTG CCATCCGCTTCCAGCTTATG - +4 dbcorrdb__SIX5__ENCSR000BRL_1__m2-Six4 14 0.471043 11518.4 1 6 CACCTG GGGGGCTGCCGCACTGCATT - +4 dbcorrdb__TBL1XR1__ENCSR000EGA_1__m2-Bdp1-Brf-CG17209-ebi-Tbp 0 0.471043 11518.4 1 6 CACCTG TGGCTCTGTGGCTTAGTGGT - +4 dbcorrdb__TCF7L2__ENCSR000EVQ_1__m1-pan 3 0.471043 11518.4 1 6 CACCTG ATTTTCCTTTGATCTTTTTT - +4 dbcorrdb__TCF7L2__ENCSR000EXL_1__m1-pan 6 0.471043 11518.4 1 6 CACCTG CGGCGGTCCCTTTGATGTTC - +4 dbcorrdb__USF2__ENCSR000ECD_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Sin3A-Spps-SREBP-tgo-Usf 11 0.471043 11518.4 1 6 CACCTG CCGGCCCGGGTCACGTGACC - +4 hocomoco__ZN274_HUMAN.H11MO.0.A-bon-egg 10 0.471043 11518.4 1 6 CACCTG TAGGGTTTCTCTCCAGTATG - +4 hocomoco__ZN331_HUMAN.H11MO.0.C 1 0.471043 11518.4 1 6 CACCTG CCACCCAGCTGAGCCCAGCC - +4 transfac_pro__M09352 15 0.471043 11518.4 1 5 CACCTG AAACCCTAAACCCTAAACCC + +4 swissregulon__hs__TP53.p2-egg -1 0.471043 11518.4 1 5 CACCTG ACATGCCCGGGCATGCCCCG - +4 tfdimers__MD00520-Myc 5 0.471074 11519.2 1 6 CACCTG CCCGCCATCTGTCCCCACCCCCCC - +4 transfac_pro__M05405 1 0.471954 11540.7 1 5 CACCTG TCACAG - +4 transfac_pro__M05121 2 0.471954 11540.7 1 4 CACCTG ATTTCC - +4 hdpi__TCEAL6 -3 0.471954 11540.7 1 3 CACCTG CTTCCC - +4 cisbp__M0028 1 0.472258 11548.1 1 6 CACCTG CCGCCGCCC + +4 cisbp__M1023-oc 2 0.472258 11548.1 1 6 CACCTG ATAATCCCC + +4 cisbp__M1181 3 0.472258 11548.1 1 6 CACCTG ACCAATCAA + +4 cisbp__M5024-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey 3 0.472258 11548.1 1 6 CACCTG TGGCACGTG + +4 predrem__nrMotif1059 3 0.472258 11548.1 1 6 CACCTG ACAGTCATG + +4 predrem__nrMotif1243 1 0.472258 11548.1 1 6 CACCTG CCATCTCCA + +4 predrem__nrMotif1811 3 0.472258 11548.1 1 6 CACCTG TCTCACTTG + +4 predrem__nrMotif2222 0 0.472258 11548.1 1 6 CACCTG GGCCTGTTG + +4 predrem__nrMotif747 3 0.472258 11548.1 1 6 CACCTG GAATCCCAG + +4 transfac_pro__M04832-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Taf1 0 0.472258 11548.1 1 6 CACCTG CACTTCCGG + +4 cisbp__M0437-CG4730-CG7101 3 0.472258 11548.1 1 6 CACCTG ATATATATA - +4 cisbp__M1112 2 0.472258 11548.1 1 6 CACCTG TATATTGGC - +4 elemento__AAGATGGCG-CG10431-pho-phol-Taf1 3 0.472258 11548.1 1 6 CACCTG CGCCATCTT - +4 flyfactorsurvey__Ct_SOLEXA_FBgn0004198-ct 3 0.472258 11548.1 1 6 CACCTG GTTTAAGAA - +4 predrem__nrMotif1045 1 0.472258 11548.1 1 6 CACCTG TCATCTCCA - +4 predrem__nrMotif1779 0 0.472258 11548.1 1 6 CACCTG CAGCCGCTG - +4 predrem__nrMotif2671 0 0.472258 11548.1 1 6 CACCTG AGCCAGTAA - +4 predrem__nrMotif916 1 0.472258 11548.1 1 6 CACCTG CCATCTCTC - +4 stark__AAAGTGANA 3 0.472258 11548.1 1 6 CACCTG TATCACTTT - +4 swissregulon__hs__RUNX1..3.p2-Bgb-Bro-RunxA-RunxB-lz-run 0 0.472258 11548.1 1 6 CACCTG AACCACAAA - +4 flyfactorsurvey__CG3838_SANGER_5_FBgn0032130-CG3838 4 0.472258 11548.1 1 5 CACCTG AAGCAACAT + +4 predrem__nrMotif1914 4 0.472258 11548.1 1 5 CACCTG AAATCATCT + +4 transfac_pro__M04747-egg-mor-Six4 4 0.472258 11548.1 1 5 CACCTG ACTACAATT + +4 cisbp__M4859-CG3838 4 0.472258 11548.1 1 5 CACCTG AAGCAACAT - +4 neph__UW.Motif.0425 4 0.472258 11548.1 1 5 CACCTG GAAGCACTT - +4 predrem__nrMotif2095 4 0.472258 11548.1 1 5 CACCTG TCTTTCCCT - +4 predrem__nrMotif2282 -1 0.472258 11548.1 1 5 CACCTG CTCTGGCAG - +4 predrem__nrMotif2452 4 0.472258 11548.1 1 5 CACCTG AGAGTACTT - +4 predrem__nrMotif571 -1 0.472258 11548.1 1 5 CACCTG AGCTCATTT - +4 neph__UW.Motif.0102 -2 0.472258 11548.1 1 4 CACCTG TCTCTGCCA + +4 predrem__nrMotif2390 5 0.472258 11548.1 1 4 CACCTG CATTCCACA + +4 transfac_pro__M04594-opa -2 0.472258 11548.1 1 4 CACCTG CCCGCTGGG + +4 predrem__nrMotif1606 5 0.472258 11548.1 1 4 CACCTG CAGCACACA - +4 predrem__nrMotif1707 5 0.472258 11548.1 1 4 CACCTG TTAAACACA - +4 transfac_pro__M07270-sd 5 0.472258 11548.1 1 4 CACCTG AAAAATAGC - +4 neph__UW.Motif.0045 -3 0.472258 11548.1 1 3 CACCTG CTGCCCACA + +4 tfdimers__MD00279 6 0.472608 11556.7 1 6 CACCTG CCGCCTCAGCTGTTCTCTCGC + +4 transfac_pro__M09061 7 0.472608 11556.7 1 6 CACCTG CCACCTCCACCGACATAACCA - +4 transfac_pro__M05256 16 0.472608 11556.7 1 5 CACCTG CGGCCCCGGGGGGGACAACCC - +4 hdpi__ZRSR2-CG3294 -1 0.472724 11559.5 1 5 CACCTG AAATT + +4 cisbp__M3375-HLH4C 8 0.473073 11568.1 1 6 CACCTG GAGGGGCGCAGCTGCGCCCCAT + +4 tfdimers__MD00466 18 0.474226 11596.3 1 6 CACCTG AAAGAAAAAGAGGAAGTGAAACTGACACTAATAA - +4 cisbp__M5646-Myb 9 0.475713 11632.6 1 6 CACCTG TAACGGTTATAACGGCC - +4 cisbp__M6257-srp 8 0.475713 11632.6 1 6 CACCTG ATCTAAGTTATCTCTTA - +4 taipale__MYBL1_DBD_NNCNGTTNNNACNGTTN_repr-Myb 9 0.475713 11632.6 1 6 CACCTG TAACGGTTATAACGGCC - +4 taipale_tf_pairs__HOXD12_HOXA3_NTAATNRSNYMRTAAAN_CAP_repr 6 0.475713 11632.6 1 6 CACCTG TTTTATGACGTGATTAA - +4 transfac_pro__M01421-Awh-E5-ems-en-inv-lab-Lim3-unpg 2 0.475713 11632.6 1 6 CACCTG CAAAGCTAATTAGTTTA - +4 transfac_pro__M02816-pan 2 0.475713 11632.6 1 6 CACCTG TTTTCCTTTGATCTATA - +4 transfac_public__M00480-Topors 8 0.475713 11632.6 1 6 CACCTG TCCCAAAGTAGCTGGGA - +4 transfac_pro__M05448 12 0.475713 11632.6 1 5 CACCTG TGCAGGGAAATAGACCA + +4 factorbook__ZNF263-klu 3 0.475946 11638.3 1 6 CACCTG CTCTCCCTCCTCCCC + +4 flyfactorsurvey__peb-F5-7_SOLEXA_FBgn0003053-peb 2 0.475946 11638.3 1 6 CACCTG TTTATCTCATACTTT + +4 neph__UW.Motif.0132 6 0.475946 11638.3 1 6 CACCTG GAAAACTGGCTGACA + +4 taipale_cyt_meth__GLI3_RGACCACCCACRWWG_eDBD_meth-ci-lmd-opa-sug 8 0.475946 11638.3 1 6 CACCTG AGACCACCCACGTAG + +4 taipale_tf_pairs__MEIS1_HOXB13_SYMRTAAANCTGTCA_CAP_repr 6 0.475946 11638.3 1 6 CACCTG CCAATAAAACTGTCA + +4 transfac_pro__M09057 7 0.475946 11638.3 1 6 CACCTG CCACCGCCACCGACA + +4 transfac_pro__M09106 3 0.475946 11638.3 1 6 CACCTG TCACACGTGTGAACT + +4 transfac_pro__M09509-Max 9 0.475946 11638.3 1 6 CACCTG CGTGTTTGGCACGTG + +4 transfac_pro__M09525-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 8 0.475946 11638.3 1 6 CACCTG AATGACGTCATCATT + +4 bergman__mirr-mirr 4 0.475946 11638.3 1 6 CACCTG TTAACACGTGTTTTC - +4 cisbp__M5055-Clp-klu-peb-sr 5 0.475946 11638.3 1 6 CACCTG CCCCCCACCCACGCA - +4 flyfactorsurvey__klu_SOLEXA_5_FBgn0013469-Clp-klu-l(3)neo38-peb-sr 5 0.475946 11638.3 1 6 CACCTG CCCCCCACCCACGCA - +4 flyfactorsurvey__lmd-F3-5_SOLEXA_5-lmd-sug 6 0.475946 11638.3 1 6 CACCTG AGAGACCCCCTGGAC - +4 hocomoco__GCR_MOUSE.H11MO.0.A-Hsf-fkh 2 0.475946 11638.3 1 6 CACCTG AGAACATTCTGTTCT - +4 transfac_pro__M07481-sd 2 0.475946 11638.3 1 6 CACCTG CATTCCATGCATTCC - +4 transfac_pro__M09136 0 0.475946 11638.3 1 6 CACCTG CATCATCATCACCAT - +4 transfac_pro__M09490-CG34367-unpg 8 0.475946 11638.3 1 6 CACCTG TAATTAATTACATTT - +4 transfac_pro__M09511-bigmax-Clk-cyc-Mitf-tgo 2 0.475946 11638.3 1 6 CACCTG CGCACGTGACCTCTC - +4 transfac_pro__M09531-Atf6-CrebA-Xbp1 8 0.475946 11638.3 1 6 CACCTG TGCCACGTCAGCATC - +4 neph__UW.Motif.0416 -1 0.475946 11638.3 1 5 CACCTG AAATTATTATGGCTT - +4 cisbp__M3402 11 0.475946 11638.3 1 4 CACCTG TGGTAATCATTAACC + +4 transfac_public__M00132 11 0.475946 11638.3 1 4 CACCTG TGGTAATTATTAACC - +4 cisbp__M4505-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-nej-pnt-RpII215-Sin3A-Taf1 0 0.479168 11717.1 1 6 CACCTG AACCGGAAGTG + +4 cisbp__M4747-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.479168 11717.1 1 6 CACCTG GATGACGTCAT + +4 cisbp__M5645-Myb 2 0.479168 11717.1 1 6 CACCTG AAAACCGTTAA + +4 cisbp__M6181-Atf-2-CG44247-CrebB-Jra 4 0.479168 11717.1 1 6 CACCTG CACTGACGTCA + +4 cisbp__M6404 1 0.479168 11717.1 1 6 CACCTG GGACATGTCTC + +4 scertf__zhu.MIG2-klu-sr 0 0.479168 11717.1 1 6 CACCTG TACCCCGCAAT + +4 taipale_cyt_meth__ERG_NACCGGAARYN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt-RpII215 0 0.479168 11717.1 1 6 CACCTG AACCGGAAATG + +4 tiffin__TIFDMEM0000073 3 0.479168 11717.1 1 6 CACCTG AAATACCAAAC + +4 transfac_pro__M00616 2 0.479168 11717.1 1 6 CACCTG ATTAACTACAC + +4 transfac_pro__M01703-ci-opa 3 0.479168 11717.1 1 6 CACCTG GACCACCCAAG + +4 transfac_pro__M07290-ci-lmd-opa-sug 1 0.479168 11717.1 1 6 CACCTG AGACCACCCAG + +4 transfac_pro__M09523-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-maf-S-Xbp1 1 0.479168 11717.1 1 6 CACCTG TGACGTCATCA + +4 cisbp__M0332-Jra 1 0.479168 11717.1 1 6 CACCTG TGACGTCATTC - +4 cisbp__M6266-ci-lmd-opa-sug 4 0.479168 11717.1 1 6 CACCTG GGACCACCCAA - +4 flyfactorsurvey__Atf-2_SANGER_5_FBgn0050420-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 3 0.479168 11717.1 1 6 CACCTG GATGACGTCAT - +4 hocomoco__ELK1_HUMAN.H11MO.0.B-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Taf1-aop-bs-nej-pnt 1 0.479168 11717.1 1 6 CACCTG CCACTTCCGGT - +4 hocomoco__GLI3_HUMAN.H11MO.0.B-ci-lmd-opa-sug 4 0.479168 11717.1 1 6 CACCTG AGACCACCCAG - +4 hocomoco__NFIL3_HUMAN.H11MO.0.D-CG7786-Pdp1-gt-vri 2 0.479168 11717.1 1 6 CACCTG ATTACATAACT - +4 predrem__nrMotif1884 5 0.479168 11717.1 1 6 CACCTG CCTCTGACCCC - +4 taipale_cyt_meth__ELK3_NACCGGAAGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.479168 11717.1 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__ELK4_NRCMGGAWGTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-nej-pnt-RpII215-Taf1 3 0.479168 11717.1 1 6 CACCTG CACTTCCGGTC - +4 transfac_pro__M01596-ci-lmd-opa-sug 4 0.479168 11717.1 1 6 CACCTG AGACCACCCAG - +4 transfac_pro__M05341-lbe-lbl 0 0.479168 11717.1 1 6 CACCTG ACTCTTATTTA - +4 transfac_pro__M09469-dsf-tll 4 0.479168 11717.1 1 6 CACCTG CGTTGACTTTT - +4 cisbp__M1747 -1 0.479168 11717.1 1 5 CACCTG AACTGCCGGAG + +4 cisbp__M6213-aop-Atac3-Ets21C-Ets96B-Ets97D-pnt -1 0.479168 11717.1 1 5 CACCTG ACCGGAAATCC + +4 taipale_cyt_meth__GATA3_WGATAAGATCW_FL_meth-GATAe-grn-pnr-srp 6 0.479168 11717.1 1 5 CACCTG AGATAAGATCT + +4 transfac_pro__M07911-btd-Klf15-Sp1-Spps 6 0.479168 11717.1 1 5 CACCTG CACGCCCACCC + +4 transfac_pro__M05310 7 0.479168 11717.1 1 4 CACCTG CTCAGAAGACC + +4 cisbp__M4497-CG12018-Dif-dl-Rel-shn 7 0.479168 11717.1 1 4 CACCTG TGGAAATCCCC - +4 factorbook__TCF7L2-pan -2 0.479168 11717.1 1 4 CACCTG CCTTTGATCTT - +4 tfdimers__MD00216-EcR 17 0.480025 11738.1 1 6 CACCTG TTTTTTTAATCCCTTTGAACCCTATTT + +4 tfdimers__MD00364-klu 7 0.480025 11738.1 1 6 CACCTG CCCCGGCCCCCTGCGGTCCCCCCCGCC + +4 tfdimers__MD00441-Dif-dl-ovo-Rel 16 0.480025 11738.1 1 6 CACCTG GGGGGGTGGGGGAATTTCCCACACCCC + +4 transfac_pro__M00955 17 0.480025 11738.1 1 6 CACCTG TTCCCTAGAACACTCTGTACCCGCAAC - +4 cisbp__M5387-ap-Awh-bs-bsh-CG34367-CG9876-Dll-E5-ems-en-eve-exex-gsb-gsb-n-ind-inv-lbl-OdsH-otp-pdm3-prd-Rx-unpg 4 0.48126 11768.2 1 6 CACCTG TAATTAGCTAATTA + +4 cisbp__M6453-CG5846-CG9727-Max-Rfx-SREBP 1 0.48126 11768.2 1 6 CACCTG TTACCATGGCAACC + +4 jaspar__MA0119.1-C15-NfI 3 0.48126 11768.2 1 6 CACCTG TGGCACCATGCCAA + +4 neph__UW.Motif.0525 5 0.48126 11768.2 1 6 CACCTG TTCAAAATCTGGAA + +4 predrem__nrMotif947-CG7368-l(3)neo38 4 0.48126 11768.2 1 6 CACCTG CCCCCACCCCCAAC + +4 taipale_cyt_meth__OVOL1_NRWACCGTTATNYN_FL-ovo 2 0.48126 11768.2 1 6 CACCTG AAAACCGTTATTTG + +4 transfac_pro__M07938-odd 3 0.48126 11768.2 1 6 CACCTG TGCTACCGGTAGCA + +4 cisbp__M6554 6 0.48126 11768.2 1 6 CACCTG CCGAAACATCTGGA - +4 hocomoco__RFX3_HUMAN.H11MO.0.B-CG5846-CG9727-Max-Rfx-SREBP 1 0.48126 11768.2 1 6 CACCTG TTACCATGGCAACC - +4 neph__UW.Motif.0002-C15-NfI-tll 8 0.48126 11768.2 1 6 CACCTG TGGCAGGGTGCCAG - +4 scertf__foat.PPR1 6 0.48126 11768.2 1 6 CACCTG CACGAGTACTTTAA - +4 taipale__Tcf21_DBD_NNAACAGCTGTTNN-amos-dimm-Fer3-HLH54F-nau 4 0.48126 11768.2 1 6 CACCTG ACAACAGCTGTTGC - +4 transfac_pro__M04953-btd-CG42741-kay-Nf-YA-Nf-YB-Spps-sr 6 0.48126 11768.2 1 6 CACCTG CCCCGCCCCCTCCC - +4 transfac_pro__M06154 2 0.48126 11768.2 1 6 CACCTG TAAACATTTCTAAC - +4 transfac_public__M00421 5 0.48126 11768.2 1 6 CACCTG CCATAAAACTGTCA - +4 yetfasco__YLR228C_849 9 0.481473 11773.5 1 6 CACCTG ATTTCCGGCCACCCGGAA + +4 transfac_pro__M01541 9 0.481473 11773.5 1 6 CACCTG ATTTCCGGCCACCCGGAA - +4 transfac_pro__M05941-crol 8 0.481473 11773.5 1 6 CACCTG CCCGTCACAATCTCAATC - +4 transfac_pro__M06839 0 0.481473 11773.5 1 6 CACCTG CGCCTCCCTTATTCCAAC - +4 cisbp__M0650 2 0.482826 11806.5 1 6 CACCTG GATAACGT + +4 cisbp__M0862-Gsc-Ptx1-bcd-oc 2 0.482826 11806.5 1 6 CACCTG TTAATCCC + +4 cisbp__M1076 1 0.482826 11806.5 1 6 CACCTG TTACGTCA + +4 cisbp__M1475 2 0.482826 11806.5 1 6 CACCTG ATGAACTC + +4 cisbp__M6061-bcd-oc 2 0.482826 11806.5 1 6 CACCTG TTAATCCG + +4 homer__TAATCCCN_Pitx1 2 0.482826 11806.5 1 6 CACCTG TAATCCCG + +4 predrem__nrMotif830 0 0.482826 11806.5 1 6 CACCTG AACCATGA + +4 taipale_cyt_meth__MSX1_NTCGTTAN_FL_meth-bsh-CG34367-Dr-en-exex-ind-inv-lab-unpg 0 0.482826 11806.5 1 6 CACCTG CTCGTTAA + +4 cisbp__M0563 2 0.482826 11806.5 1 6 CACCTG CTACCCTA - +4 cisbp__M0922-achi-esg-hth-sna-vis-wor 1 0.482826 11806.5 1 6 CACCTG TGACAGGT - +4 cisbp__M1677 1 0.482826 11806.5 1 6 CACCTG TTTTCAGA - +4 transfac_pro__M08829-Mad 2 0.482826 11806.5 1 6 CACCTG TCAGTCTG - +4 elemento__ACATCCGG -1 0.482826 11806.5 1 5 CACCTG ACATCCGG + +4 elemento__ACTTCCTC -1 0.482826 11806.5 1 5 CACCTG ACTTCCTC + +4 elemento__ATCTCCTC -1 0.482826 11806.5 1 5 CACCTG ATCTCCTC + +4 hocomoco__PRGR_MOUSE.H11MO.1.A 3 0.482826 11806.5 1 5 CACCTG AAGAACAG + +4 cisbp__M0030 3 0.482826 11806.5 1 5 CACCTG ACCGACAT - +4 cisbp__M1482 3 0.482826 11806.5 1 5 CACCTG GGCTACAC - +4 cisbp__M1695 3 0.482826 11806.5 1 5 CACCTG GTTGACCA - +4 cisbp__M6409-sv -1 0.482826 11806.5 1 5 CACCTG GGCTGAGG - +4 jaspar__MA0985.1 3 0.482826 11806.5 1 5 CACCTG GCCGACAT - +4 jaspar__MA1091.1 3 0.482826 11806.5 1 5 CACCTG GTTGACCA - +4 predrem__nrMotif1746 -1 0.482826 11806.5 1 5 CACCTG ACATTAGA - +4 cisbp__M1150 -2 0.482826 11806.5 1 4 CACCTG CCTGTCAT + +4 cisbp__M1960-Mad-SoxN -2 0.482826 11806.5 1 4 CACCTG CCTTTGTT + +4 jaspar__MA0143.3-Mad-SoxN -2 0.482826 11806.5 1 4 CACCTG CCTTTGTT + +4 jaspar__MA0553.1 -2 0.482826 11806.5 1 4 CACCTG CCTCGTAC + +4 fantom__motif35_CGCCYAGA -2 0.482826 11806.5 1 4 CACCTG TCTGGGCG - +4 cisbp__M4712-foxo-slp2 -3 0.482826 11806.5 1 3 CACCTG CTGTTTAC - +4 cisbp__M2056-twi 1 0.483418 11821 1 6 CACCTG TCGCATATGTTG + +4 fantom__motif111_WWAATYCGCTCC 5 0.483418 11821 1 6 CACCTG AAAATCCGCTCC + +4 hocomoco__CDX2_MOUSE.H11MO.0.A-Abd-B-cad-eve 6 0.483418 11821 1 6 CACCTG TTTTATGGCCTT + +4 hocomoco__ZN257_HUMAN.H11MO.0.C 5 0.483418 11821 1 6 CACCTG GCTCTTGCCTCT + +4 neph__UW.Motif.0410 4 0.483418 11821 1 6 CACCTG TGAAATCATTCA + +4 predrem__nrMotif194 6 0.483418 11821 1 6 CACCTG CATCCCCATCCC + +4 tiffin__TIFDMEM0000035 6 0.483418 11821 1 6 CACCTG ATATATTTTCTA + +4 transfac_pro__M00699-ebi-Stat92E 6 0.483418 11821 1 6 CACCTG AAAGTGAAACTG + +4 transfac_pro__M00924-Jra-kay 5 0.483418 11821 1 6 CACCTG TGACTCAAGGTG + +4 transfac_pro__M03874 6 0.483418 11821 1 6 CACCTG ATTAATTACATC + +4 transfac_pro__M06020 2 0.483418 11821 1 6 CACCTG CGGTCCTGGTCC + +4 transfac_pro__M06617 3 0.483418 11821 1 6 CACCTG TGTGACCAGGGC + +4 transfac_pro__M06664-CG3281 6 0.483418 11821 1 6 CACCTG TGGGAAAACCGA + +4 transfac_pro__M06891-CG3281 6 0.483418 11821 1 6 CACCTG TGGGAAAACCGA + +4 transfac_pro__M07903-sd 1 0.483418 11821 1 6 CACCTG CCGCATTCCATT + +4 cisbp__M0746-bin-CHES-1-like-croc-FoxK-foxo-FoxP-slp1-slp2 6 0.483418 11821 1 6 CACCTG TATGTTTACATT - +4 taipale_cyt_meth__CREB5_NRTGAYGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.483418 11821 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__MSC_NRNCATATGNYN_FL-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.483418 11821 1 6 CACCTG CACCATATGGTG - +4 taipale_tf_pairs__FOXO1_ETV1_RCCGGAWGTKKN_CAP-Ets96B-foxo 2 0.483418 11821 1 6 CACCTG AAAACATCCGGT - +4 transfac_pro__M01037-ci-lmd-opa-sug 4 0.483418 11821 1 6 CACCTG GGACCACCCAAA - +4 transfac_pro__M05451-CG16779 1 0.483418 11821 1 6 CACCTG GTACCAACCAAG - +4 transfac_pro__M05487 2 0.483418 11821 1 6 CACCTG ACTACCCTCATG - +4 transfac_pro__M05738 6 0.483418 11821 1 6 CACCTG GATATTCAACAG - +4 transfac_pro__M06150 6 0.483418 11821 1 6 CACCTG TCGTTTAACCAC - +4 transfac_pro__M06358-zfh1 6 0.483418 11821 1 6 CACCTG GAGCCTTATCAG - +4 transfac_pro__M06406 1 0.483418 11821 1 6 CACCTG GCAGCTTGACAG - +4 transfac_pro__M06803 6 0.483418 11821 1 6 CACCTG TGTGCCCACCCT - +4 transfac_pro__M09481-dsf-tll 4 0.483418 11821 1 6 CACCTG CTTTGACTTTTT - +4 transfac_pro__M05677 -1 0.483418 11821 1 5 CACCTG TCCTTTTTCCCA - +4 transfac_pro__M06149 7 0.483418 11821 1 5 CACCTG TTTGCCAGTCCA - +4 transfac_pro__M06169 -1 0.483418 11821 1 5 CACCTG TCCTTCTCACAG - +4 transfac_pro__M06299 7 0.483418 11821 1 5 CACCTG TCCCCAGCAACA - +4 transfac_pro__M06336 7 0.483418 11821 1 5 CACCTG TCTTTTTGATCG - +4 transfac_pro__M06836-crol 7 0.483418 11821 1 5 CACCTG TTTGTTTTAGCT - +4 transfac_pro__M07644-SREBP 8 0.483418 11821 1 4 CACCTG CATCACGCCACC + +4 transfac_pro__M09439 8 0.483418 11821 1 4 CACCTG GTTGGGACCACA + +4 cisbp__M1921-Atf6-CrebA-CrebB-Xbp1 8 0.483418 11821 1 4 CACCTG GGCCACGTCATC - +4 transfac_pro__M05668 8 0.483418 11821 1 4 CACCTG TCTGATTTCACG - +4 transfac_pro__M05728 -2 0.483418 11821 1 4 CACCTG CCTTTTTCACGA - +4 transfac_pro__M06268 -2 0.483418 11821 1 4 CACCTG CCTTTTTCACGA - +4 cisbp__M5095-lola 0 0.483526 11823.7 1 6 CACCTG GAGCTTT + +4 elemento__CCCCCTC 1 0.483526 11823.7 1 6 CACCTG CCCCCTC + +4 elemento__CCGCCTC 1 0.483526 11823.7 1 6 CACCTG CCGCCTC + +4 elemento__CGCCTCC 0 0.483526 11823.7 1 6 CACCTG CGCCTCC + +4 elemento__CTCCTCG 0 0.483526 11823.7 1 6 CACCTG CTCCTCG + +4 predrem__nrMotif2018 1 0.483526 11823.7 1 6 CACCTG AATCCTT + +4 transfac_pro__M01889-Med 0 0.483526 11823.7 1 6 CACCTG TGTCTGC + +4 elemento__GAGGAGC 1 0.483526 11823.7 1 6 CACCTG GCTCCTC - +4 elemento__GAGGCGC 1 0.483526 11823.7 1 6 CACCTG GCGCCTC - +4 elemento__GAGGGGC 1 0.483526 11823.7 1 6 CACCTG GCCCCTC - +4 predrem__nrMotif55 1 0.483526 11823.7 1 6 CACCTG GGGCCTG - +4 transfac_pro__M03848-Sox15 0 0.483526 11823.7 1 6 CACCTG GCCATTG - +4 cisbp__M1792 2 0.483526 11823.7 1 5 CACCTG TTTTCCG + +4 predrem__nrMotif772 -1 0.483526 11823.7 1 5 CACCTG ATCTGTT + +4 scertf__macisaac.GCR2 2 0.483526 11823.7 1 5 CACCTG GCTTCCT + +4 yetfasco__YPL075W_2071 2 0.483526 11823.7 1 5 CACCTG GCTTCCT + +4 cisbp__M0372 2 0.483526 11823.7 1 5 CACCTG TACACTC - +4 predrem__nrMotif2493 2 0.483526 11823.7 1 5 CACCTG CTTACAA - +4 jaspar__MA0334.1 3 0.483526 11823.7 1 4 CACCTG CGCCACA + +4 hdpi__ZBED1-CG13775 -2 0.483526 11823.7 1 4 CACCTG CCATTGA - +4 transfac_pro__M01935 3 0.483526 11823.7 1 4 CACCTG CGCCACA - +4 predrem__nrMotif1203 4 0.483526 11823.7 1 3 CACCTG CATGCAC + +4 predrem__nrMotif2084 4 0.483526 11823.7 1 3 CACCTG CTAGCAC + +4 predrem__nrMotif2391 4 0.483526 11823.7 1 3 CACCTG ATTGCAC + +4 predrem__nrMotif2543 4 0.483526 11823.7 1 3 CACCTG TCAGCAC + +4 predrem__nrMotif269-CTCF 4 0.483526 11823.7 1 3 CACCTG TCAGCAC + +4 predrem__nrMotif454 -3 0.483526 11823.7 1 3 CACCTG CTTGAAG + +4 predrem__nrMotif979 4 0.483526 11823.7 1 3 CACCTG GGGGCAC + +4 cisbp__M5451-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 4 0.483526 11823.7 1 3 CACCTG TGTTTAC - +4 predrem__nrMotif1271 4 0.483526 11823.7 1 3 CACCTG GAGCCAC - +4 predrem__nrMotif2484 4 0.483526 11823.7 1 3 CACCTG ATTCCAC - +4 predrem__nrMotif2595 4 0.483526 11823.7 1 3 CACCTG AGAGCAC - +4 predrem__nrMotif440 4 0.483526 11823.7 1 3 CACCTG GACCCAC - +4 predrem__nrMotif754 4 0.483526 11823.7 1 3 CACCTG TCATCAC - +4 taipale__FOXI1_full_GTAAACA-croc-fd59A-fkh-FoxK-foxo-FoxP-slp2 4 0.483526 11823.7 1 3 CACCTG TGTTTAC - +4 tfdimers__MD00319-EcR-usp 12 0.483792 11830.2 1 6 CACCTG CCCCCCCTGTCCTTCCTGTTCCCGCC - +4 cisbp__M6427-Dfd-Lim3-Scr 0 0.483905 11832.9 1 6 CACCTG CAGCTCATTAATA + +4 hocomoco__CR3L2_HUMAN.H11MO.0.D-Atf6-CrebA-Xbp1 4 0.483905 11832.9 1 6 CACCTG TGATGACGTGGCA + +4 neph__UW.Motif.0424 0 0.483905 11832.9 1 6 CACCTG CATTTTTCAAAAC + +4 swissregulon__sacCer__YGR067C 6 0.483905 11832.9 1 6 CACCTG GCGGGGTACTGTA + +4 neph__UW.Motif.0155 4 0.483905 11832.9 1 6 CACCTG TTCTTTTCTTTTG - +4 transfac_pro__M07731-GATAe-grn-ham-pnr-srp 3 0.483905 11832.9 1 6 CACCTG CCTTATCTTATCT - +4 transfac_pro__M08802-Mondo 4 0.483905 11832.9 1 6 CACCTG GTGTCACGTGCAC - +4 taipale_tf_pairs__POU2F1_ETV1_NCCGGATATGCAN_CAP_repr-Ets96B-nub-pdm2 -1 0.483905 11832.9 1 5 CACCTG ACCGGATATGCAT + +4 cisbp__M5788-Bgb-lz-run-RunxA-RunxB 8 0.485429 11870.2 1 6 CACCTG TAACCGCAAACCGCAA + +4 cisbp__M5791-Bgb-lz-run-RunxA-RunxB 8 0.485429 11870.2 1 6 CACCTG TAACCGCAAACCGCAA + +4 taipale__RUNX2_DBD_NAACCGCAAACCRCAN_repr-Bgb-lz-run-RunxA-RunxB 8 0.485429 11870.2 1 6 CACCTG TAACCGCAAACCGCAA + +4 transfac_pro__M02104-cnc-maf-S 7 0.485429 11870.2 1 6 CACCTG CATGACTCAGCACACC + +4 transfac_pro__M02841-ac-ase-l(1)sc-sc 7 0.485429 11870.2 1 6 CACCTG CTATCCCCGCCCTATT + +4 hocomoco__TCF7_MOUSE.H11MO.0.A-Sox14-Sox100B-SoxN-pan 2 0.485429 11870.2 1 6 CACCTG GTTTCCTTTGATCTTT - +4 neph__UW.Motif.0243 4 0.485429 11870.2 1 6 CACCTG GAAATGGCTGTTTCTG - +4 neph__UW.Motif.0578 5 0.485429 11870.2 1 6 CACCTG GGCAGTGGCTGGGTTT - +4 scertf__zhu.YPR015C 6 0.485429 11870.2 1 6 CACCTG AGGATTTACGTCTTCA - +4 taipale_cyt_meth__HSF5_AACRTTCTAGAAYGYT_eDBD_meth-Hsf 0 0.485429 11870.2 1 6 CACCTG AACATTCTAGAATGTT - +4 taipale_tf_pairs__PITX1_HES7_NCRCGTGNNNGGATTA_CAP_repr-Ptx1 9 0.485429 11870.2 1 6 CACCTG TAATCCCCCCACGTGC - +4 transfac_pro__M02867 9 0.485429 11870.2 1 6 CACCTG CCTTTTGGGCACACCC - +4 transfac_pro__M02929 0 0.485429 11870.2 1 6 CACCTG ATTCTGCCAGTGATTG - +4 transfac_public__M00007-aop-Atac3-Eip74EF-Ets21C-Ets96B-Ets97D-pnt 3 0.485429 11870.2 1 6 CACCTG ACGAACTTCCGGTTTA - +4 cisbp__M5524-Hnf4 11 0.485429 11870.2 1 5 CACCTG GATGGACTTTGGACTC + +4 neph__UW.Motif.0592 11 0.485429 11870.2 1 5 CACCTG TGGAAATGTGATTTCT - +4 taipale__HNF4A_DBD_NRGTCCAAAGTCCANY_repr-Hnf4 11 0.485429 11870.2 1 5 CACCTG GATGGACTTTGGACTC - +4 hocomoco__USF2_HUMAN.H11MO.0.A-CrebB-E2f1-HLH3B-HLH4C-Hand-Max-Mitf-Myc-SREBP-Spps-Usf-ac-ase-btd-cnc-cyc-l(1)sc-nau-sc 4 0.485738 11877.7 1 6 CACCTG GGGTCACGTGGCCGCGGCG + +4 transfac_pro__M05429 3 0.485738 11877.7 1 6 CACCTG CGCTACCGGAGACGGTGGG + +4 hocomoco__KLF15_HUMAN.H11MO.0.A-CTCF-CoRest-Dif-Klf15-Rbbp5-Spps-Spt20-btd-crol-ct-dl-klu-luna-sr 4 0.485738 11877.7 1 6 CACCTG CCCCCCCCTGCTCCTCCCC - +4 tfdimers__MD00178-TfAP-2 14 0.486827 11904.4 1 6 CACCTG GGCGGCCCCCGGGCCAGCTGGCCCC - +4 tfdimers__MD00480-HLH3B 5 0.486827 11904.4 1 6 CACCTG TTTCCCACTTCCTTTTCTCCTTTCT - +4 cisbp__M0695-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.48686 11905.2 1 6 CACCTG AACCGGAAGT + +4 cisbp__M1651 4 0.48686 11905.2 1 6 CACCTG ATGGGCCCAT + +4 cisbp__M1730 3 0.48686 11905.2 1 6 CACCTG TTTTTCCGAT + +4 cisbp__M1735 3 0.48686 11905.2 1 6 CACCTG TATTCCCGAT + +4 cisbp__M3439-Hsf 2 0.48686 11905.2 1 6 CACCTG CGAACATTCT + +4 fantom__motif107_CGTCTGCGTA 0 0.48686 11905.2 1 6 CACCTG CGTCTGCGTA + +4 hocomoco__STAT4_MOUSE.H11MO.0.A-Stat92E 1 0.48686 11905.2 1 6 CACCTG TTTCCCGGAA + +4 predrem__nrMotif1242 4 0.48686 11905.2 1 6 CACCTG CTAGGCCCTG + +4 predrem__nrMotif144 0 0.48686 11905.2 1 6 CACCTG AAAATGGCCT + +4 predrem__nrMotif70 3 0.48686 11905.2 1 6 CACCTG CAGCACCCCA + +4 taipale_cyt_meth__ASCL2_ACACGACGCN_FL_repr-ac-ase-l(1)sc-sc 4 0.48686 11905.2 1 6 CACCTG ACACGACGCG + +4 yetfasco__YML007W_2186 3 0.48686 11905.2 1 6 CACCTG GATTACTAAA + +4 cisbp__M0192-dpn-h-Hey-Sidpn 2 0.48686 11905.2 1 6 CACCTG GGCACGCGTC - +4 cisbp__M0686-CG9650-ebi-nej 2 0.48686 11905.2 1 6 CACCTG ACTTCCCCTT - +4 hocomoco__RUNX3_HUMAN.H11MO.0.A-Bgb-Bro-CG9650-MTA1-like-NFAT-RunxA-RunxB-Stat92E-ebi-foxo-lz-nej-run 1 0.48686 11905.2 1 6 CACCTG AAACCACAAA - +4 predrem__nrMotif1049 4 0.48686 11905.2 1 6 CACCTG CCTCGCCCTC - +4 predrem__nrMotif1599 3 0.48686 11905.2 1 6 CACCTG TTCCACCCCA - +4 transfac_pro__M07508 4 0.48686 11905.2 1 6 CACCTG TGGATATCCG - +4 transfac_public__M00030 3 0.48686 11905.2 1 6 CACCTG ATTTACATCA - +4 yetfasco__YPL177C_2121-achi-hth-vis 4 0.48686 11905.2 1 6 CACCTG ATGACACATT - +4 predrem__nrMotif2503 5 0.48686 11905.2 1 5 CACCTG AGCAGCATCA - +4 taipale_cyt_meth__SIX1_NSRTATCRYN_FL-Optix-so 5 0.48686 11905.2 1 5 CACCTG CATGATACGC - +4 taipale_cyt_meth__SIX2_NCGTATCRYN_eDBD-Optix-so 5 0.48686 11905.2 1 5 CACCTG GATGATACGG - +4 transfac_pro__M01022-pan -1 0.48686 11905.2 1 5 CACCTG CCCTTTGATC - +4 predrem__nrMotif1011 6 0.48686 11905.2 1 4 CACCTG CACAGCCACA + +4 taipale_cyt_meth__MEF2D_CCWWATWWRG_eDBD-bs-Mef2 -2 0.48686 11905.2 1 4 CACCTG CCAAATTTGG + +4 transfac_pro__M07753-abd-A-Antp-ap-Awh-btn-CG32532-Dfd-Dll-E5-ems-en-eve-HGTX-ind-lab-pb-repo-Scr-slou-Ubx-unpg-Vsx1-zen2 6 0.48686 11905.2 1 4 CACCTG GTTAATTACC + +4 taipale_cyt_meth__SRF_CCWTGTWNGG_eDBD_repr-bs -2 0.48686 11905.2 1 4 CACCTG CCATACATGG - +4 hdpi__C19orf25 -1 0.487958 11932 1 5 CACCTG ACTTTG - +4 hdpi__PCK2-CG10924-Pepck -1 0.487958 11932 1 5 CACCTG ACGCCG - +4 hdpi__RARA-EcR -1 0.487958 11932 1 5 CACCTG AGCGTC - +4 hdpi__P4HB-Pdi 2 0.487958 11932 1 4 CACCTG GGCAGC + +4 swissregulon__sacCer__YPR022C 3 0.487958 11932 1 3 CACCTG CCCCAC + +4 hdpi__HSPA1L-Hsc70-1-Hsc70-4 -3 0.487958 11932 1 3 CACCTG CTGCCA - +4 c2h2_zfs__M0415-CG4730-CG7101 3 0.488577 11947.2 1 6 CACCTG ATATATATA + +4 cisbp__M0856 2 0.488577 11947.2 1 6 CACCTG ATAACTCTA + +4 jaspar__MA0126.1-Poxn-ovo 2 0.488577 11947.2 1 6 CACCTG AGTAACAGT + +4 predrem__nrMotif145 1 0.488577 11947.2 1 6 CACCTG TGTCCTGCT + +4 predrem__nrMotif152 2 0.488577 11947.2 1 6 CACCTG ATGCCCTTT + +4 predrem__nrMotif1538 0 0.488577 11947.2 1 6 CACCTG CAACTGTGT + +4 predrem__nrMotif1825 2 0.488577 11947.2 1 6 CACCTG GTGGCCTGC + +4 predrem__nrMotif209 2 0.488577 11947.2 1 6 CACCTG AACAGCTCA + +4 predrem__nrMotif515 2 0.488577 11947.2 1 6 CACCTG AGCAGCTCT + +4 predrem__nrMotif594 0 0.488577 11947.2 1 6 CACCTG CAGCATGGC + +4 cisbp__M0567 3 0.488577 11947.2 1 6 CACCTG CGGCATCCT - +4 cisbp__M0712-Ets21C-Ets65A-Ets96B-Ets97D-aop-pnt 2 0.488577 11947.2 1 6 CACCTG ACTTCCGGT - +4 cisbp__M1484 3 0.488577 11947.2 1 6 CACCTG AGTCACAAA - +4 cisbp__M4687-Blimp-1 3 0.488577 11947.2 1 6 CACCTG AATCACTTT - +4 cisbp__M6207-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.488577 11947.2 1 6 CACCTG ACTTCCGGT - +4 predrem__nrMotif1680 3 0.488577 11947.2 1 6 CACCTG GGGCCCCAG - +4 predrem__nrMotif1698 0 0.488577 11947.2 1 6 CACCTG TACCCCAGG - +4 predrem__nrMotif2149 2 0.488577 11947.2 1 6 CACCTG CAGCCCTTT - +4 predrem__nrMotif755 0 0.488577 11947.2 1 6 CACCTG CTCCTCATT - +4 predrem__nrMotif768 1 0.488577 11947.2 1 6 CACCTG AGAACTGCT - +4 predrem__nrMotif81 0 0.488577 11947.2 1 6 CACCTG AGCCTTGAA - +4 taipale_cyt_meth__MAF_NYGCTGACN_eDBD-maf-S-tj 3 0.488577 11947.2 1 6 CACCTG CGTCAGCAC - +4 transfac_pro__M04893-Taf1 0 0.488577 11947.2 1 6 CACCTG CGACTTCCG - +4 cisbp__M4857-CG3407 4 0.488577 11947.2 1 5 CACCTG GGTTGACAT + +4 hocomoco__NFIB_HUMAN.H11MO.0.D-NfI -1 0.488577 11947.2 1 5 CACCTG CCCTGGCAG + +4 predrem__nrMotif2314 4 0.488577 11947.2 1 5 CACCTG AGATCACTT + +4 predrem__nrMotif317 4 0.488577 11947.2 1 5 CACCTG ATGCCAACA + +4 predrem__nrMotif713 -1 0.488577 11947.2 1 5 CACCTG ACCCCCAGA + +4 yetfasco__YER184C_2095 -1 0.488577 11947.2 1 5 CACCTG ACCGGCCGG + +4 cisbp__M0298-Atf6-CrebA-Jra 4 0.488577 11947.2 1 5 CACCTG ACGTCATCA - +4 flyfactorsurvey__CG3407_SANGER_2.5_FBgn0031573-CG3407 4 0.488577 11947.2 1 5 CACCTG GGTTGACTT - +4 flyfactorsurvey__Ets21c_SANGER_5_FBgn0005660-Ets21C-Ets65A-Ets96B-Ets97D-aop-pnt -1 0.488577 11947.2 1 5 CACCTG ACCGGAAAT - +4 hocomoco__ZN341_HUMAN.H11MO.1.C -1 0.488577 11947.2 1 5 CACCTG GGCTGTTCC - +4 predrem__nrMotif1062 -1 0.488577 11947.2 1 5 CACCTG AGCTCTTCT - +4 predrem__nrMotif1794 4 0.488577 11947.2 1 5 CACCTG ATCATCCCT - +4 predrem__nrMotif941 4 0.488577 11947.2 1 5 CACCTG CCAAAAGCA - +4 predrem__nrMotif1101 5 0.488577 11947.2 1 4 CACCTG GTCACAACC + +4 predrem__nrMotif1131 5 0.488577 11947.2 1 4 CACCTG AGTGTCACT + +4 predrem__nrMotif1619 5 0.488577 11947.2 1 4 CACCTG ACTGCTACT + +4 predrem__nrMotif1649 5 0.488577 11947.2 1 4 CACCTG AGCATCACT + +4 predrem__nrMotif2094 5 0.488577 11947.2 1 4 CACCTG TCTCACACA + +4 predrem__nrMotif2332 5 0.488577 11947.2 1 4 CACCTG TTGGGGACT + +4 scertf__zhu.GAT1-GATAd-GATAe-grn-pnr-srp -2 0.488577 11947.2 1 4 CACCTG CCTTATCGG + +4 predrem__nrMotif1954 5 0.488577 11947.2 1 4 CACCTG TTGGATACA - +4 dbcorrdb__ATF3__ENCSR000BNU_1__m1-cnc-CoRest-CrebB-Jra-kay-mor-Myc-pan-Snr1-SREBP-Usf 14 0.488651 11949 1 6 CACCTG CCCGGCGGTTGAGTCACCCG + +4 dbcorrdb__BHLHE40__ENCSR000DYJ_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-ERR-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-Stat92E-tai-TfIIFalpha-tgo-Usf-zfh1 6 0.488651 11949 1 6 CACCTG GGCCGGCACGTGACCGGGCG + +4 dbcorrdb__CHD1__ENCSR000EFC_1__m2-Chd1 7 0.488651 11949 1 6 CACCTG AGGTGGGAACCGGAAAAGCG + +4 dbcorrdb__EP300__ENCSR000EGE_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 4 0.488651 11949 1 6 CACCTG TTCTTATCTGTACCCACCAG + +4 dbcorrdb__EZH2__ENCSR000ASW_1__m4-Brf-brm-btd-CTCF-ERR-E(z)-Spps-SREBP-vtd 11 0.488651 11949 1 6 CACCTG GCGGGGCCGCTCCCCGGCCA + +4 dbcorrdb__GTF2F1__ENCSR000ECZ_1__m4-TfIIFalpha 4 0.488651 11949 1 6 CACCTG CTACCAGCCAGAAGGCGCTG + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m1-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 6 0.488651 11949 1 6 CACCTG CGCGGCTGCTTTTATAGGCC + +4 dbcorrdb__PPARGC1A__ENCSR000EEQ_1__m1-Hsf-srl 2 0.488651 11949 1 6 CACCTG CCCACCTTCTGGAATATTCT + +4 dbcorrdb__SIN3A__ENCSR000BOY_1__m2-Sin3A 5 0.488651 11949 1 6 CACCTG AGAAACAGCTGCGAGGGGGC + +4 dbcorrdb__SREBF1__ENCSR000EEO_1__m3-cnc-CrebB-E2f1-Max-Myc-SREBP-Usf 10 0.488651 11949 1 6 CACCTG CCGATCGCGTGACCGCGGCG + +4 dbcorrdb__TBP__ENCSR000EHA_1__m4-Tbp 7 0.488651 11949 1 6 CACCTG CTTTCGCCACCTAAGAGTGA + +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m4 0 0.488651 11949 1 6 CACCTG TTCCTTCAGTCAGTACACTC + +4 dbcorrdb__ZNF274__ENCSR000EVR_1__m2-bon 3 0.488651 11949 1 6 CACCTG CTCTGGCTAAAGGCTTTCCC + +4 dbcorrdb__eGFP-GATA2__ENCSR000DKA_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.488651 11949 1 6 CACCTG TCTTATCTGTCCCCCCCAGC + +4 jaspar__MA0413.1 6 0.488651 11949 1 6 CACCTG AAATTCCCCCTGAATTTGTG + +4 transfac_pro__M01540 6 0.488651 11949 1 6 CACCTG AAATTCCCCCTGAATTTGTG + +4 transfac_pro__M04782-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 5 0.488651 11949 1 6 CACCTG TGCCTTATCTGCCCCCCCCA + +4 transfac_pro__M06854 12 0.488651 11949 1 6 CACCTG AGGGGAGTAAATTACCCTAC + +4 cisbp__M2218 6 0.488651 11949 1 6 CACCTG AAATTCCCCCTGAATTTGTG - +4 cisbp__M4478-aop-Stat92E 14 0.488651 11949 1 6 CACCTG CATTTCCCGGAAATCACCTG - +4 cisbp__M4690-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 4 0.488651 11949 1 6 CACCTG TCCTTATCTGCCCCCACCAG - +4 dbcorrdb__GATA3__ENCSR000BMX_1__m4-GATAe-grn-pnr-TfAP-2 5 0.488651 11949 1 6 CACCTG TAATTTGCCTGAGGGCATGT - +4 dbcorrdb__GTF2F1__ENCSR000EBP_1__m3-TfIIFalpha 11 0.488651 11949 1 6 CACCTG TCCGGCGTCGTCTCATGTCG - +4 dbcorrdb__NR3C1__ENCSR000BJC_1__m1-fkh-Hsf 2 0.488651 11949 1 6 CACCTG GGAACAGAATGTTCTTGGCA - +4 dbcorrdb__POLR2A__ENCSR000AKZ_1__m1-ebi-GATAe-grn-pan-pnr-RpII215-srp 11 0.488651 11949 1 6 CACCTG GGCGCCGCCCTTATCTGCCC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EGF_1__m1-RpII215 7 0.488651 11949 1 6 CACCTG CGGACGGCATTTCCGCAGCG - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BPA_1__m2 6 0.488651 11949 1 6 CACCTG TCATATCGCTTCCGCCATTT - +4 dbcorrdb__SIN3A__ENCSR000BRM_1__m4-foxo-Sin3A 8 0.488651 11949 1 6 CACCTG TTGCTGTTTACGTAATTCTG - +4 dbcorrdb__SRF__ENCSR000BLK_1__m2-bs 6 0.488651 11949 1 6 CACCTG TGGCGACGGCTGGGCGCGCC - +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m2-bon 1 0.488651 11949 1 6 CACCTG ATGCATGACACAGATAGGGT - +4 dbcorrdb__USF1__ENCSR000BGI_1__m1-ac-ase-btd-cnc-CrebB-cyc-E2f1-ERR-E(z)-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-Sap30-sc-Spps-SREBP-Stat92E-tgo-Usf-zfh1 8 0.488651 11949 1 6 CACCTG GCCCGGGTCACGTGGCCCCG - +4 dbcorrdb__USF1__ENCSR000BKT_1__m1-bigmax-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-SREBP-tgo-Usf 8 0.488651 11949 1 6 CACCTG GCCCGGGTCACGTGGCCACG - +4 dbcorrdb__USF2__ENCSR000EHG_1__m1-bigmax-btd-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf 4 0.488651 11949 1 6 CACCTG GGGTCACGTGACCCCGCCGG - +4 taipale_tf_pairs__MYBL1_HOXA13_CTCRTAAAWNNNNRMCGTTR_CAP_repr-Myb 0 0.488651 11949 1 6 CACCTG CAACGGTCATTTTTTACGAG - +4 taipale_tf_pairs__TEAD4_HES7_GGWATGYNNNNNNCRCGYGY_CAP-sd 12 0.488651 11949 1 6 CACCTG GCACGTGCCTCCCGCATTCC - +4 tfdimers__MD00080-ovo 5 0.488651 11949 1 6 CACCTG CCCGCCCCCTGCTGAGCCCC - +4 transfac_pro__M01545 8 0.488651 11949 1 6 CACCTG TGCAATGGACCCTGATTTAG - +4 transfac_pro__M01550 2 0.488651 11949 1 6 CACCTG TGCATCTGACGCGTCGCCCA - +4 transfac_pro__M01568-CG10348-CG13296-ham 0 0.488651 11949 1 6 CACCTG TACCTACCCCTATTTCATAG - +4 dbcorrdb__eGFP-NR4A1__ENCSR000DJW_1__m5 -1 0.488651 11949 1 5 CACCTG ACCTTCTTTGTCACAGGACC + +4 tfdimers__MD00031-zfh1 7 0.48907 11959.2 1 6 CACCTG AAAAAAGAAACTGAAACAAAAAAA - +4 tfdimers__MD00507-EcR-usp 9 0.48907 11959.2 1 6 CACCTG CCCTGTCCCCACCTGCCCTCTCCC - +4 taipale_tf_pairs__E2F1_EOMES_RGGTGTNNNGGCGSNNTNNCRSNN_CAP-E2f1 19 0.48907 11959.2 1 5 CACCTG CCGTGTCATGGCGCCATCACACCT - +4 cisbp__M2113 6 0.490336 11990.2 1 6 CACCTG ATTAAAAAACTCCGGAGTATA + +4 transfac_pro__M09396 3 0.490336 11990.2 1 6 CACCTG GGTAGCGTGAAATTCAAGCAA + +4 yetfasco__YJL103C_856 6 0.490336 11990.2 1 6 CACCTG ATTAAAAAACTCCGGAGTATA + +4 transfac_pro__M09113 0 0.490336 11990.2 1 6 CACCTG AATCTCAACCGTCCATTTTAT - +4 transfac_pro__M09127-Blimp-1-brm-CG7839-maf-S-orb-SREBP-vtd 4 0.490336 11990.2 1 6 CACCTG TTTTCACTTTTTCTTTTTTTT - +4 taipale_tf_pairs__GCM1_ETV7_NTNNNGGCGGAAGNNNTTCCNNN_CAP_repr-aop-gcm-gcm2 16 0.490455 11993.1 1 6 CACCTG ATGCGGGCGGAAGTACTTCCGGT + +4 tfdimers__MD00187-GATAe-grn-pnr-srp 12 0.490905 12004.1 1 6 CACCTG ATTTAAGATAATTATCTTAAAT + +4 cisbp__M3376-HLH4C 8 0.490905 12004.1 1 6 CACCTG AGGGGACGCAGCTGCGCCCCCT - +4 tfdimers__MD00410 11 0.490905 12004.1 1 6 CACCTG TTTTTAATTTCCTCCTTTTTTT - +4 transfac_public__M00058-HLH4C 8 0.490905 12004.1 1 6 CACCTG AGGGGACGCAGCTGCGCCCCCT - +4 hocomoco__NR2E1_HUMAN.H11MO.0.D-EcR-tll 4 0.493039 12056.3 1 6 CACCTG AATTGACTTTTTGACTT + +4 taipale_tf_pairs__TEAD4_HOXA3_RCATTCNNNNNNCATTA_CAP-sd 3 0.493039 12056.3 1 6 CACCTG ACATTCCACACCCATTA + +4 taipale_tf_pairs__TEAD4_PITX1_RCATWCYNNNNTAATCC_CAP_repr-Ptx1-sd 3 0.493039 12056.3 1 6 CACCTG ACATACCTCCCTAATCC + +4 transfac_pro__M01592-gem-grh 10 0.493039 12056.3 1 6 CACCTG AAACCGGTTCAAACTGG - +4 transfac_pro__M02764-Hnf4 8 0.493039 12056.3 1 6 CACCTG TCAATTGACCCCTGAAG - +4 transfac_pro__M07269-Sox100B 3 0.493039 12056.3 1 6 CACCTG TGGGGCCTTTGTTTAGG - +4 transfac_pro__M05435-opa 12 0.493039 12056.3 1 5 CACCTG TTAAAGTCGGGTCACCC + +4 factorbook__MYOG-Nf1-nau 9 0.493067 12057 1 6 CACCTG CTGGCTCTTTGCCAG + +4 jaspar__MA0407.1 2 0.493067 12057 1 6 CACCTG GGAAACTCTAAGAAC + +4 taipale_cyt_meth__GLIS1_KACCCCCCACGWWGN_eDBD_meth-ci-lmd-sug 0 0.493067 12057 1 6 CACCTG GACCCCCCACGGAGC + +4 transfac_pro__M00984-Bgb-Bro-lz-run-RunxA-RunxB 3 0.493067 12057 1 6 CACCTG GCTAACCACAAACGT + +4 transfac_pro__M01173-SREBP 5 0.493067 12057 1 6 CACCTG CCGCTCACCCCACGG + +4 transfac_pro__M09398 0 0.493067 12057 1 6 CACCTG AGCGTGTGGAACAAG + +4 cisbp__M2212 2 0.493067 12057 1 6 CACCTG GGAAACTCTAAGAAC - +4 cisbp__M5003-her 6 0.493067 12057 1 6 CACCTG TACTCATAATTGCGT - +4 hocomoco__ELF5_HUMAN.H11MO.0.A-Eip74EF-Ets96B-Ets97D-RpII215-pnt 4 0.493067 12057 1 6 CACCTG CCACTTCCTCCTTCC - +4 hocomoco__NFAC1_HUMAN.H11MO.0.B-CG5641-NFAT 9 0.493067 12057 1 6 CACCTG TTTCTTTTTTTCCAT - +4 transfac_pro__M07598 2 0.493067 12057 1 6 CACCTG AACTCCACAATTCTG - +4 taipale_cyt_meth__HNF4A_NRGTCCAAAGTCCRN_eDBD-Hnf4 10 0.493067 12057 1 5 CACCTG TTGGACTTTGGACTC - +4 tfdimers__MD00540-Hand 10 0.495782 12123.4 1 6 CACCTG AAAATAATGGCATCTGGAATTAATTAAATAA + +4 tfdimers__MD00046-GATAe-grn-Med-pnr-srp 7 0.495782 12123.4 1 6 CACCTG ATATTCTTATCTTTAAACTACAGACATATAT - +4 cisbp__M0213 1 0.495902 12126.3 1 6 CACCTG CTACCATATGG + +4 predrem__nrMotif170 0 0.495902 12126.3 1 6 CACCTG TTTCTGCCAAA + +4 tiffin__TIFDMEM0000042 5 0.495902 12126.3 1 6 CACCTG TGGCAACACTG + +4 transfac_pro__M01702-ci-lmd-opa-sug 3 0.495902 12126.3 1 6 CACCTG GACCACCCACG + +4 cisbp__M5689-maf-S-tj 2 0.495902 12126.3 1 6 CACCTG GTCAGCAAATT - +4 cisbp__M6264-ci-lmd-opa-sug 4 0.495902 12126.3 1 6 CACCTG AGACCACCCAG - +4 hocomoco__NFAT5_HUMAN.H11MO.0.D-NFAT 4 0.495902 12126.3 1 6 CACCTG CCTTTTCCTCT - +4 swissregulon__hs__NFIL3.p2-vri 4 0.495902 12126.3 1 6 CACCTG AGGTTACATAA - +4 taipale__NRL_DBD_NNNNTGCTGAN-maf-S-tj 2 0.495902 12126.3 1 6 CACCTG GTCAGCAAATT - +4 transfac_pro__M07042-Sidpn 3 0.495902 12126.3 1 6 CACCTG GGGCACGCGAG - +4 transfac_pro__M09422 5 0.495902 12126.3 1 6 CACCTG ATCCGTACAAT - +4 transfac_pro__M09468-dsf-tll 4 0.495902 12126.3 1 6 CACCTG CGTTGACTTTT - +4 transfac_pro__M09472-dsf-tll 4 0.495902 12126.3 1 6 CACCTG CGTTGACTTTT - +4 transfac_pro__M07709-bin-CHES-1-like-croc-fd59A-fkh-FoxK-foxo-FoxP-slp1-slp2 6 0.495902 12126.3 1 5 CACCTG TTTGTTTACAT - +4 taipale_cyt_meth__HOXD10_NGYAATAAAAN_FL_meth-Abd-B-cad-eve 7 0.495902 12126.3 1 4 CACCTG GTTTTATTACC - +4 cisbp__M6098-amos-crp-dimm-Fer3-HLH54F-nau 4 0.498357 12186.3 1 6 CACCTG GCAACAGCTGTTGT + +4 neph__UW.Motif.0222 0 0.498357 12186.3 1 6 CACCTG AGGCTGGAGTCAGA + +4 neph__UW.Motif.0652 4 0.498357 12186.3 1 6 CACCTG AAAATTGCTTTTTC + +4 taipale__EMX1_DBD_YMATTARYTAATKR_repr-ap-Awh-bs-bsh-CG34367-CG9876-Dll-E5-ems-en-eve-gsb-gsb-n-ind-inv-lbl-OdsH-otp-pdm3-prd-Rx-unpg 4 0.498357 12186.3 1 6 CACCTG TAATTAGCTAATTA + +4 taipale__GLI2_DBD_GACCACMCACNNNG_repr-ci-lmd-opa-sug 7 0.498357 12186.3 1 6 CACCTG GACCACCCACGACG + +4 transfac_pro__M07648-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m7-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 4 0.498357 12186.3 1 6 CACCTG ATGGCACGTGCCAA + +4 transfac_pro__M07652-Max-Myc 4 0.498357 12186.3 1 6 CACCTG AAACCACGTGGTTT + +4 transfac_pro__M07757-Abd-B 4 0.498357 12186.3 1 6 CACCTG AAAACACATAAAAC + +4 transfac_pro__M09050 7 0.498357 12186.3 1 6 CACCTG CTTCACCGACATAA + +4 transfac_pro__M09495-Clk-cnc-cyc-Mitf 0 0.498357 12186.3 1 6 CACCTG CACGTGACATCCAC + +4 transfac_pro__M09522-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 8 0.498357 12186.3 1 6 CACCTG GATGACGTCATCAT + +4 transfac_public__M00118-Max-Myc 4 0.498357 12186.3 1 6 CACCTG CGACCACGTGGTCA + +4 transfac_public__M00119-Max-Usf 4 0.498357 12186.3 1 6 CACCTG AAACCACGTGGTTT + +4 cisbp__M5471-fd59A-FoxK-foxo-slp2 3 0.498357 12186.3 1 6 CACCTG GTAAACATGTTTAC - +4 cisbp__M5488-ci-lmd-opa-sug 7 0.498357 12186.3 1 6 CACCTG GACCACCCACGACG - +4 neph__UW.Motif.0321 4 0.498357 12186.3 1 6 CACCTG CATCTGGCTGTTTT - +4 transfac_pro__M07657-ac-amos-dimm-HLH54F-nau-sage 4 0.498357 12186.3 1 6 CACCTG AAAACAGCTGTTTT - +4 neph__UW.Motif.0147 9 0.498357 12186.3 1 5 CACCTG TGGAAATTTTTCTT - +4 transfac_pro__M06353 9 0.498357 12186.3 1 5 CACCTG ATATTGCCCCCCCT - +4 homer__GGTTGCCATGGCAA_X-box-CG5846-CG9727-Max-Rfx-SREBP 10 0.498357 12186.3 1 4 CACCTG TTGCCATGGCAACC - +4 taipale_tf_pairs__PITX1_HES7_NNCRCGTGNNNNGGATTA_CAP_repr-Ptx1 10 0.498971 12201.3 1 6 CACCTG TAATCCCCAACACGTGCC - +4 transfac_pro__M05945 3 0.498971 12201.3 1 6 CACCTG CCCAACTTGATTGAAACC - +4 transfac_pro__M07931-gl 3 0.498971 12201.3 1 6 CACCTG GTGCACTTGTATGGTAAT - +4 transfac_pro__M09388 2 0.498971 12201.3 1 6 CACCTG GTTGCTTGTTTTACACGT - +4 transfac_pro__M00790 13 0.498971 12201.3 1 5 CACCTG ACTGTTAATTATTAACCA - +4 cisbp__M1068-oc-Ptx1 2 0.49902 12202.5 1 6 CACCTG TTAATCCC + +4 flyfactorsurvey__CG16778_SANGER_5_FBgn0003715-lov 0 0.49902 12202.5 1 6 CACCTG CACATATG + +4 jaspar__MA1060.1 2 0.49902 12202.5 1 6 CACCTG CGTACGGC + +4 predrem__nrMotif2319 0 0.49902 12202.5 1 6 CACCTG CATCTCTA + +4 predrem__nrMotif2628 1 0.49902 12202.5 1 6 CACCTG ATACCATG + +4 taipale__Otx1_DBD_NTAATCCN-bcd-oc 2 0.49902 12202.5 1 6 CACCTG TTAATCCG + +4 taipale_cyt_meth__DLX3_NTCGTTAN_FL_meth-abd-A-Antp-bsh-btn-Dll-Dr-HGTX-lab-Scr-Ubx 0 0.49902 12202.5 1 6 CACCTG GTCATTAA + +4 transfac_pro__M00640-Dfd 1 0.49902 12202.5 1 6 CACCTG ATAATTAG + +4 c2h2_zfs__M0435 0 0.49902 12202.5 1 6 CACCTG GATCGGCG - +4 cisbp__M0065 0 0.49902 12202.5 1 6 CACCTG GATCTAGA - +4 jaspar__MA0300.1-GATAd-GATAe-grn-pnr-srp 2 0.49902 12202.5 1 6 CACCTG CTTATCGG - +4 predrem__nrMotif1069 1 0.49902 12202.5 1 6 CACCTG TAACCACA - +4 transfac_pro__M01910-GATAd-GATAe-grn-pnr-srp 2 0.49902 12202.5 1 6 CACCTG CTTATCGG - +4 transfac_pro__M07368-Med 1 0.49902 12202.5 1 6 CACCTG CTGTCTGG - +4 yetfasco__YPL038W_1370 1 0.49902 12202.5 1 6 CACCTG CCACAGTG - +4 cisbp__M0299-CG44247-CrebA-CrebB-Jra-kay-Xbp1 3 0.49902 12202.5 1 5 CACCTG GATGACGT + +4 cisbp__M1740 -1 0.49902 12202.5 1 5 CACCTG TCCGGAGC + +4 elemento__AGCTCCTC -1 0.49902 12202.5 1 5 CACCTG AGCTCCTC + +4 elemento__CCCTCCCC -1 0.49902 12202.5 1 5 CACCTG CCCTCCCC + +4 elemento__CCCTCCTC -1 0.49902 12202.5 1 5 CACCTG CCCTCCTC + +4 elemento__TCCTCCTC -1 0.49902 12202.5 1 5 CACCTG TCCTCCTC + +4 elemento__TCCTCGGC -1 0.49902 12202.5 1 5 CACCTG TCCTCGGC + +4 elemento__TCCTCGTC -1 0.49902 12202.5 1 5 CACCTG TCCTCGTC + +4 jaspar__MA0605.1-CG44247-CrebA-CrebB-Jra-Xbp1-kay 3 0.49902 12202.5 1 5 CACCTG GATGACGT + +4 predrem__nrMotif861 3 0.49902 12202.5 1 5 CACCTG ACACTCCT + +4 c2h2_zfs__M0464 3 0.49902 12202.5 1 5 CACCTG CGCCACAG - +4 cisbp__M0649 -1 0.49902 12202.5 1 5 CACCTG ACTTTATC - +4 cisbp__M0942-ara-caup-mirr 3 0.49902 12202.5 1 5 CACCTG CATTACAA - +4 elemento__AGATCATG 3 0.49902 12202.5 1 5 CACCTG CATGATCT - +4 elemento__ATGTCCAC 3 0.49902 12202.5 1 5 CACCTG GTGGACAT - +4 elemento__TACGAGGA -1 0.49902 12202.5 1 5 CACCTG TCCTCGTA - +4 predrem__nrMotif636 -1 0.49902 12202.5 1 5 CACCTG ATCAGAAG - +4 swissregulon__hs__MAZ.p2 -1 0.49902 12202.5 1 5 CACCTG CCCTCCCC - +4 cisbp__M2346 -2 0.49902 12202.5 1 4 CACCTG CCTCGTAC + +4 predrem__nrMotif1561 4 0.49902 12202.5 1 4 CACCTG GGCTCACC - +4 predrem__nrMotif2411 -2 0.49902 12202.5 1 4 CACCTG CATTATGA - +4 taipale__MEIS3_DBD_NTGACAGN-achi-hth-vis -2 0.49902 12202.5 1 4 CACCTG CCTGTCAA - +4 neph__UW.Motif.0050 -3 0.49902 12202.5 1 3 CACCTG CTGGCTTC + +4 transfac_pro__M01718-NFAT 1 0.499652 12218 1 6 CACCTG TTTCCAC + +4 predrem__nrMotif134 1 0.499652 12218 1 6 CACCTG TTTCCTG - +4 predrem__nrMotif2521 2 0.499652 12218 1 5 CACCTG TTTACCC + +4 hdpi__ETFB-CG7834 -2 0.499652 12218 1 4 CACCTG CGTCGTC - +4 cisbp__M5513-CG17829 5 0.500342 12234.9 1 6 CACCTG CCGCGGACGTTG + +4 cisbp__M6024-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.500342 12234.9 1 6 CACCTG GATTACGTAACA + +4 scertf__harbison.THO2-tho2 6 0.500342 12234.9 1 6 CACCTG ATTTTCTTCTTT + +4 taipale__Dbp_DBD_NRTTACGTAAYN-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.500342 12234.9 1 6 CACCTG TATTACGTAACA + +4 taipale__Hlf_DBD_NRTTACGTAAYN-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.500342 12234.9 1 6 CACCTG GATTACGTAACC + +4 taipale_cyt_meth__CREB3_NGCCACRTCAYN_FL_meth-Atf6-CrebA-Xbp1 3 0.500342 12234.9 1 6 CACCTG CGCCACGTCACC + +4 taipale_cyt_meth__MSGN1_NRCCAWWTGKYN_eDBD-amos-da-dimm-HLH54F-Oli-tap 0 0.500342 12234.9 1 6 CACCTG CGCCATATGTCC + +4 taipale_cyt_meth__ZNF281_NCCCCTCCCCCN_eDBD_meth-btd-Spps 1 0.500342 12234.9 1 6 CACCTG GCCCCTCCCCCG + +4 transfac_pro__M06333 2 0.500342 12234.9 1 6 CACCTG TATTCCTAAAGA + +4 transfac_pro__M06786 4 0.500342 12234.9 1 6 CACCTG TTTCCGCCTGGG + +4 transfac_pro__M07674-CG7786-gt-hng1-nej-Pdp1-slbo-vri 3 0.500342 12234.9 1 6 CACCTG TATTACGTAATA + +4 transfac_pro__M07831-so 3 0.500342 12234.9 1 6 CACCTG TGATACGTATCA + +4 cisbp__M5999-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.500342 12234.9 1 6 CACCTG TATTACGTAACA - +4 hocomoco__GLI3_MOUSE.H11MO.0.D-ci-lmd-opa-sug 4 0.500342 12234.9 1 6 CACCTG AGACCACCCAGG - +4 neph__UW.Motif.0054 6 0.500342 12234.9 1 6 CACCTG CTGTGGGTTCTG - +4 taipale__HINFP1_full_CAACGTCCGCNN_repr-CG17829 5 0.500342 12234.9 1 6 CACCTG CCGCGGACGTTG - +4 taipale_cyt_meth__ELF1_NACCCGGAAGTN_FL-aop-Eip74EF-Ets21C-Ets96B-Ets97D-Ets98B-Hr78-nej-pnt 0 0.500342 12234.9 1 6 CACCTG TACTTCCGGGTT - +4 taipale_cyt_meth__FOS_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-Xbp1 3 0.500342 12234.9 1 6 CACCTG GATGACGTCATC - +4 tiffin__TIFDMEM0000045 0 0.500342 12234.9 1 6 CACCTG CTGCTGTTAACT - +4 transfac_pro__M05675 0 0.500342 12234.9 1 6 CACCTG TCCCTTTTACGG - +4 transfac_pro__M05869 6 0.500342 12234.9 1 6 CACCTG GATTTCAACCAA - +4 transfac_pro__M06548 5 0.500342 12234.9 1 6 CACCTG TTTACAACCGCG - +4 transfac_pro__M09505 5 0.500342 12234.9 1 6 CACCTG GTCCGTACAATT - +4 cisbp__M5867-bs -1 0.500342 12234.9 1 5 CACCTG ACCATATATGGC + +4 taipale__SRF_DBD_MCCATATAWGGN_repr-bs -1 0.500342 12234.9 1 5 CACCTG ACCATATATGGC + +4 transfac_pro__M05709 7 0.500342 12234.9 1 5 CACCTG TCTCTTCGACCC - +4 transfac_pro__M05850-CG12299-CG31365-dati 7 0.500342 12234.9 1 5 CACCTG TCTTCTTGACCG - +4 transfac_pro__M05917-CG12299-CG31365-dati 7 0.500342 12234.9 1 5 CACCTG TCTTCTTGACCG - +4 transfac_pro__M06019 7 0.500342 12234.9 1 5 CACCTG TCCCTCTTAACT - +4 transfac_pro__M06088 7 0.500342 12234.9 1 5 CACCTG TCTGATTGACCT - +4 transfac_pro__M06185 7 0.500342 12234.9 1 5 CACCTG GCCTCCATAACT - +4 transfac_pro__M06330 7 0.500342 12234.9 1 5 CACCTG TCTGATTGACCT - +4 transfac_pro__M06451 7 0.500342 12234.9 1 5 CACCTG TCGGCTGGACCT - +4 transfac_pro__M06762-CG2120 7 0.500342 12234.9 1 5 CACCTG TCGTTTTGACCC - +4 transfac_pro__M06924 7 0.500342 12234.9 1 5 CACCTG AGAATTACCCCT - +4 flyfactorsurvey__disco-r-Cl1_SANGER_5_FBgn0042650-disco-r 8 0.500342 12234.9 1 4 CACCTG AAGAATGTCACC + +4 homer__CGTRNAAARTGA_ABF1 8 0.500342 12234.9 1 4 CACCTG TCATTTTGCACG - +4 transfac_pro__M01796-Bdp1-Brf-CG17209-Hsf 8 0.500342 12234.9 1 4 CACCTG GGGTTCGAATCC - +4 transfac_pro__M06117-crol -2 0.500342 12234.9 1 4 CACCTG CCTCCCCACCCA - +4 transfac_pro__M06744-CG2120 -2 0.500342 12234.9 1 4 CACCTG CCTGCTTTAGTT - +4 cisbp__M0323-CG7786-gt-Pdp1 7 0.500949 12249.7 1 6 CACCTG TGTTACGCAAATA + +4 flyfactorsurvey__ci_SOLEXA_FBgn0004859-ci-lmd-opa-sug 3 0.500949 12249.7 1 6 CACCTG GACCACCCACGAC + +4 taipale_cyt_meth__OVOL2_NWWCCGTTAYNYN_eDBD-ovo 1 0.500949 12249.7 1 6 CACCTG ATACCGTTATTTG + +4 transfac_pro__M07884-Dif-dl-Rel 7 0.500949 12249.7 1 6 CACCTG TGGGAAAATCCCA + +4 transfac_pro__M08835-CTCF-lmd-vtd 4 0.500949 12249.7 1 6 CACCTG ATCCCCCCTGCTG + +4 cisbp__M2289-Jra-kay-Xbp1 2 0.500949 12249.7 1 6 CACCTG ATGACATCATCTT - +4 cisbp__M4689-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1 6 0.500949 12249.7 1 6 CACCTG CTTGTTTACTTAG - +4 cisbp__M4825-Asciz 7 0.500949 12249.7 1 6 CACCTG GTGTTTCAACTTT - +4 flyfactorsurvey__CG14962_SOLEXA_5_FBgn0035407-Asciz 7 0.500949 12249.7 1 6 CACCTG GTGTTTCAACTTT - +4 jaspar__MA0488.1-Jra-Xbp1-kay 2 0.500949 12249.7 1 6 CACCTG ATGACATCATCTT - +4 stark__MKSCMAGGACVHH-ttk 3 0.500949 12249.7 1 6 CACCTG TTTGTCCTGGCAG - +4 transfac_pro__M01836 4 0.500949 12249.7 1 6 CACCTG GAAGAACAGATTG - +4 transfac_pro__M07087-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.500949 12249.7 1 6 CACCTG CACTTCCTGGTTC - +4 transfac_public__M00159 4 0.500949 12249.7 1 6 CACCTG GCCTTACCAAATA - +4 taipale_tf_pairs__TEAD4_HOXA13_CYCRTAAATWCCN_CAP_repr-sd 8 0.500949 12249.7 1 5 CACCTG CTCGTAAATACCA + +4 transfac_pro__M09433 8 0.500949 12249.7 1 5 CACCTG GTGGGGACCACAA + +4 tfdimers__MD00350-nub-pdm2 7 0.501955 12274.3 1 6 CACCTG TTTATTTAATCTGATTTGCATTTTTTTTTT - +4 tfdimers__MD00437-klu-pho-phol 7 0.502111 12278.1 1 6 CACCTG CCCCTGCCATCTGCCTCCTCCCCCCC + +4 tfdimers__MD00538 6 0.502111 12278.1 1 6 CACCTG TAAACTCAGCAGATTGCACAAGATTT + +4 cisbp__M6276-CG17829 9 0.502749 12293.7 1 6 CACCTG GCGCTAGCGGACGTTA + +4 hocomoco__HINFP_HUMAN.H11MO.0.C-CG17829 9 0.502749 12293.7 1 6 CACCTG GCGCTAGCGGACGTTA + +4 neph__UW.Motif.0531 2 0.502749 12293.7 1 6 CACCTG AAAACATTTTTTCTCA + +4 taipale_cyt_meth__ETV3_NACCGGATATCCGGTN_eDBD_repr-Ets21C-Ets97D 0 0.502749 12293.7 1 6 CACCTG AACCGGATATCCGGTT + +4 transfac_pro__M03132 5 0.502749 12293.7 1 6 CACCTG TATACCACGTGCTAAC + +4 transfac_pro__M07630-ac-ase-l(1)sc-sage-sc 5 0.502749 12293.7 1 6 CACCTG AAAAGCAGCTGCTTTT + +4 transfac_pro__M08943-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.502749 12293.7 1 6 CACCTG GATGACGTCATCATTT + +4 homer__CAGAGGNCAAAGTCCA_HNF4a-EcR-HDAC1-Hnf4-Hr51-Hr78-Spps-btd-eg-kni-knrl-nej-svp-usp 9 0.502749 12293.7 1 6 CACCTG TGGACTTTGACCTCTG - +4 taipale_cyt_meth__ETV3_NACCGGATATCCGGTN_eDBD_meth-Ets21C-Ets97D 0 0.502749 12293.7 1 6 CACCTG AACCGGATATCCGGTT - +4 transfac_public__M00070-HLH3B 5 0.502749 12293.7 1 6 CACCTG GAGACCATCTGTTCCC - +4 hocomoco__P73_HUMAN.H11MO.0.A 11 0.503391 12309.4 1 6 CACCTG AGACATGCCCAGACATGCC + +4 hocomoco__TF2L1_MOUSE.H11MO.0.C-gem 9 0.503391 12309.4 1 6 CACCTG AACCGGTTCAAGCCGGTTC + +4 hocomoco__ZFX_MOUSE.H11MO.0.B-Brf-CTCF-ERR-E(z)-Myc-RpII215-SREBP-brm-tna-vtd 5 0.503391 12309.4 1 6 CACCTG GCCGAGGCCTGGGGCCCCC + +4 swissregulon__sacCer__YOX1-CG4328-CG11294-Lim1-Lim3-Lmx1a-otp 11 0.503391 12309.4 1 6 CACCTG ATTAATTAATTTTCCTAAA + +4 taipale_tf_pairs__TEAD4_MAX_RCATTCCNNNNNNCACGTG_CAP_repr-Max-sd 13 0.503391 12309.4 1 6 CACCTG ACATTCCATAAACCACGTG + +4 transfac_pro__M07729-GATAe-grn-pnr 8 0.503391 12309.4 1 6 CACCTG ATGATAAGGACCTTATCAT + +4 cisbp__M6547-Brf-brm-CTCF-ERR-E(z)-Myc-RpII215-SREBP-tna-vtd 5 0.503391 12309.4 1 6 CACCTG GCCGAGGCCTGGGGCCCCG - +4 hocomoco__KLF16_HUMAN.H11MO.0.D-Brf-CTCF-Clp-CoRest-E(z)-HDAC1-Klf15-Nelf-E-Rbbp5-SREBP-Spps-Spt20-brm-btd-cbt-crol-ct-klu-l(3)neo38-peb-sr-vtd 3 0.503391 12309.4 1 6 CACCTG CCCCCCCCCCCCCGCCCCC - +4 hocomoco__MAF_HUMAN.H11MO.0.A-cnc-maf-S-tj 0 0.503391 12309.4 1 6 CACCTG TTGCTGAGTCAGCAGATTC - +4 hocomoco__MLXPL_HUMAN.H11MO.0.D-Mondo 12 0.503391 12309.4 1 6 CACCTG CCACGGGGGTGTCACATGC - +4 cisbp__M0101 0 0.503477 12311.5 1 6 CACCTG ATTTTGATTA + +4 cisbp__M0215-Clk-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-tai 2 0.503477 12311.5 1 6 CACCTG GGCACGTGCC + +4 cisbp__M0354 3 0.503477 12311.5 1 6 CACCTG CATTACGTAA + +4 cisbp__M0611 2 0.503477 12311.5 1 6 CACCTG TTTACGTAAT + +4 cisbp__M1512 4 0.503477 12311.5 1 6 CACCTG TTGTTACGCT + +4 cisbp__M1549 3 0.503477 12311.5 1 6 CACCTG ATTTTACGAC + +4 cisbp__M1827 4 0.503477 12311.5 1 6 CACCTG TAATGTCCGC + +4 cisbp__M3699 1 0.503477 12311.5 1 6 CACCTG AGACATGCCT + +4 jaspar__MA0587.1 3 0.503477 12311.5 1 6 CACCTG GTGGACCCGG + +4 predrem__nrMotif217 1 0.503477 12311.5 1 6 CACCTG GGACTTGGGG + +4 predrem__nrMotif2261 3 0.503477 12311.5 1 6 CACCTG CCGCGCCTGG + +4 predrem__nrMotif94 0 0.503477 12311.5 1 6 CACCTG TTCCTCCAGA + +4 transfac_pro__M07534 1 0.503477 12311.5 1 6 CACCTG GCGCCGCCCA + +4 transfac_pro__M07574-Atf3-Atf6-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.503477 12311.5 1 6 CACCTG GTGACGTCAC + +4 transfac_public__M00272 1 0.503477 12311.5 1 6 CACCTG AGACATGTCT + +4 c2h2_zfs__M0448 2 0.503477 12311.5 1 6 CACCTG CCAGCCACCC - +4 cisbp__M0443-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 4 0.503477 12311.5 1 6 CACCTG GCCACGCCCA - +4 cisbp__M0472 2 0.503477 12311.5 1 6 CACCTG TTCAGCCGCA - +4 cisbp__M0489 4 0.503477 12311.5 1 6 CACCTG GGCTCATCCT - +4 cisbp__M0644 4 0.503477 12311.5 1 6 CACCTG TCGCAACATT - +4 cisbp__M0732-bin-bs-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-HDAC1-nej-slp1-slp2 4 0.503477 12311.5 1 6 CACCTG TGTTTACATA - +4 cisbp__M1041-Abd-B-cad 3 0.503477 12311.5 1 6 CACCTG TTTTATGAGC - +4 cisbp__M1215 0 0.503477 12311.5 1 6 CACCTG GGACTAATGG - +4 cisbp__M1349 2 0.503477 12311.5 1 6 CACCTG TTTATCTGTA - +4 cisbp__M1528-CG5846-CG9727-Max-Rfx-SREBP 2 0.503477 12311.5 1 6 CACCTG GTTGCCATGG - +4 cisbp__M2380 4 0.503477 12311.5 1 6 CACCTG GTGGACCCGG - +4 cisbp__M4677-kni 4 0.503477 12311.5 1 6 CACCTG GGCAACCCTG - +4 cisbp__M4988-grh 4 0.503477 12311.5 1 6 CACCTG ACAAAACCAG - +4 cisbp__M5424-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-Taf1 0 0.503477 12311.5 1 6 CACCTG CACTTCCGGT - +4 flyfactorsurvey__grh_FlyReg_FBgn0259211-grh 4 0.503477 12311.5 1 6 CACCTG ATAAAACCAG - +4 homer__GCTGTGGTTT_RUNX-AML-lz-run-RunxA-RunxB 1 0.503477 12311.5 1 6 CACCTG AAACCACAGC - +4 predrem__nrMotif1108 2 0.503477 12311.5 1 6 CACCTG AACACTTCTT - +4 predrem__nrMotif1173 1 0.503477 12311.5 1 6 CACCTG TGACTTGAAT - +4 predrem__nrMotif1951 4 0.503477 12311.5 1 6 CACCTG TTGGGAGCTG - +4 taipale__ETV4_DBD_ACCGGAAGTN-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.503477 12311.5 1 6 CACCTG TACTTCCGGT - +4 taipale__ETV5_DBD_ACCGGAWGYN-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-Taf1 0 0.503477 12311.5 1 6 CACCTG CACTTCCGGT - +4 taipale_cyt_meth__GATA4_NWGATAASRN_eDBD-GATAe-grn-pnr-srp 4 0.503477 12311.5 1 6 CACCTG GCGTTATCTC - +4 transfac_pro__M02033-pan 0 0.503477 12311.5 1 6 CACCTG GTCCTTTGAT - +4 transfac_pro__M07564 4 0.503477 12311.5 1 6 CACCTG CGTTAACGTT - +4 transfac_pro__M07706-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.503477 12311.5 1 6 CACCTG CACTTCCGGT - +4 transfac_public__M00146-Hsf 2 0.503477 12311.5 1 6 CACCTG CGAACATTCT - +4 cisbp__M1536-CG9727-Rfx 5 0.503477 12311.5 1 5 CACCTG GTAGCAACCA + +4 cisbp__M4329 -1 0.503477 12311.5 1 5 CACCTG ACCTGCAGCA + +4 transfac_pro__M01941 -1 0.503477 12311.5 1 5 CACCTG ACCTGCAGCA + +4 cisbp__M0925-pdm3 -1 0.503477 12311.5 1 5 CACCTG AGCTCATTAT - +4 predrem__nrMotif2125 6 0.503477 12311.5 1 4 CACCTG AGACAAGACA + +4 homer__ACATCAAAGG_Tcf3-pan -2 0.503477 12311.5 1 4 CACCTG CCTTTGATGT - +4 scertf__harbison.SUT1-Brf-ERR-E(z)-RpII215-SREBP-brm-tna -2 0.503477 12311.5 1 4 CACCTG CCGGCCCCGC - +4 transfac_pro__M03173 6 0.503477 12311.5 1 4 CACCTG GGGGGACACG - +4 transfac_pro__M03187 6 0.503477 12311.5 1 4 CACCTG GGGGGACACG - +4 jaspar__MA0280.1 0 0.503947 12323 1 6 CACCTG TTCCGG + +4 hdpi__HES5 0 0.503947 12323 1 6 CACCTG CACGCG - +4 stark__YGATAC-so 3 0.503947 12323 1 3 CACCTG CGATAC + +4 transfac_pro__M01674 -3 0.503947 12323 1 3 CACCTG CTGTGG + +4 hdpi__ZCCHC17 -3 0.503947 12323 1 3 CACCTG CTGCCA - +4 predrem__nrMotif1641 1 0.50502 12349.2 1 6 CACCTG ACACATGAT + +4 predrem__nrMotif1653 2 0.50502 12349.2 1 6 CACCTG AGAATCTCT + +4 predrem__nrMotif1896 1 0.50502 12349.2 1 6 CACCTG ATAACTGTT + +4 taipale_cyt_meth__HMX2_NCAMTTAAN_eDBD-Hmx 1 0.50502 12349.2 1 6 CACCTG GCACTTAAC + +4 cisbp__M1474 3 0.50502 12349.2 1 6 CACCTG CGAGATCAA - +4 cisbp__M2047-ovo-Poxn 2 0.50502 12349.2 1 6 CACCTG AGTAACAGT - +4 cisbp__M6180-Atf3-Atf6-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 1 0.50502 12349.2 1 6 CACCTG TGACGTCAC - +4 jaspar__MA1046.1 2 0.50502 12349.2 1 6 CACCTG ATTACTTAA - +4 predrem__nrMotif2553 1 0.50502 12349.2 1 6 CACCTG CTACTTCCT - +4 predrem__nrMotif26 3 0.50502 12349.2 1 6 CACCTG TGAGGCCTT - +4 predrem__nrMotif513 0 0.50502 12349.2 1 6 CACCTG GACTTTTCT - +4 transfac_pro__M07472 2 0.50502 12349.2 1 6 CACCTG CAAACATGC - +4 predrem__nrMotif1700 4 0.50502 12349.2 1 5 CACCTG AGAACTCCT + +4 predrem__nrMotif392 -1 0.50502 12349.2 1 5 CACCTG ATCTCTGAA + +4 predrem__nrMotif691 4 0.50502 12349.2 1 5 CACCTG TTCTGAGCC + +4 predrem__nrMotif702 4 0.50502 12349.2 1 5 CACCTG TGCAGAACA + +4 predrem__nrMotif784 4 0.50502 12349.2 1 5 CACCTG CTGTGTCCA + +4 cisbp__M1325 4 0.50502 12349.2 1 5 CACCTG AGGGAATCT - +4 flyfactorsurvey__lola-PQ_SANGER_5_FBgn0005630-lola 5 0.50502 12349.2 1 4 CACCTG AGAAACAAC + +4 predrem__nrMotif1167 -2 0.50502 12349.2 1 4 CACCTG CCTCTAGCC + +4 predrem__nrMotif2367 -2 0.50502 12349.2 1 4 CACCTG CTTGCCATT + +4 cisbp__M5090-lola 5 0.50502 12349.2 1 4 CACCTG AGAAACAAC - +4 predrem__nrMotif1341 -2 0.50502 12349.2 1 4 CACCTG TCTCTCCCA - +4 predrem__nrMotif1452 5 0.50502 12349.2 1 4 CACCTG TTTTACACA - +4 predrem__nrMotif2345 5 0.50502 12349.2 1 4 CACCTG AGAGTGACT - +4 predrem__nrMotif676 -2 0.50502 12349.2 1 4 CACCTG TCTGAAGCT - +4 predrem__nrMotif711 5 0.50502 12349.2 1 4 CACCTG GTGAGAACA - +4 predrem__nrMotif1584 -3 0.50502 12349.2 1 3 CACCTG CTGCGGCAG - +4 predrem__nrMotif71 -3 0.50502 12349.2 1 3 CACCTG CTGTCTTCT - +4 tfdimers__MD00249 14 0.505088 12350.9 1 6 CACCTG AGAAAACACAGGATCAGCAGATGTT + +4 tfdimers__MD00591-TfAP-2 14 0.505088 12350.9 1 6 CACCTG ATTTAGAAAACAAAAGCCTTTTAGT + +4 flyfactorsurvey__pdm3_SOLEXA_5_FBgn0033288-E5-pdm3-zen2 14 0.505088 12350.9 1 6 CACCTG CCCCCCACCCAACCAACCTAATTAA - +4 tfdimers__MD00562-GATAe-grn-pnr-srp 26 0.505766 12367.5 1 6 CACCTG CCATTCTTATCTTCTTTTCCCACTACTTCCTGTTCGCACAC - +4 dbcorrdb__FOSL1__ENCSR000BNS_1__m1-kay 8 0.506442 12384 1 6 CACCTG GGCGCTAGGACCCCGCGGCC + +4 dbcorrdb__GATA2__ENCSR000BKM_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.506442 12384 1 6 CACCTG TCTTATCTGTACCCCCCAGC + +4 dbcorrdb__GATA3__ENCSR000EXZ_1__m1-GATAe-grn-Jra-pnr-Snr1-srp 8 0.506442 12384 1 6 CACCTG TAGATTCTTATCTGCTCACC + +4 dbcorrdb__GTF3C2__ENCSR000DOD_1__m4-Bdp1-Brf-Tbp 9 0.506442 12384 1 6 CACCTG CCACTAAGCTACGCCGGCGG + +4 dbcorrdb__HDAC2__ENCSR000BMC_1__m2-btd-EcR-eg-ERR-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 12 0.506442 12384 1 6 CACCTG AACTGGACTTTGAACTTTGG + +4 dbcorrdb__HSF1__ENCSR000EET_1__m5-Hsf 4 0.506442 12384 1 6 CACCTG CGGACTCGTGAACAGGCGTT + +4 dbcorrdb__MAFK__ENCSR000EEB_1__m3-cic-cnc-maf-S-tj 0 0.506442 12384 1 6 CACCTG AAGCTGAGTCAGCAATTTTG + +4 dbcorrdb__MAX__ENCSR000EHS_1__m1-Clk-cnc-E2f1-E(z)-gce-Max-Myc-Sap30-SREBP-tgo-Usf 5 0.506442 12384 1 6 CACCTG GCAGCCACGTGGTCCCCGCG + +4 dbcorrdb__POLR2A__ENCSR000EUU_1__m4-RpII215 3 0.506442 12384 1 6 CACCTG GCGCAGCGACGGCCGCGCGT + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m9-RpII215 3 0.506442 12384 1 6 CACCTG TCCTACCCCGTGATGCACAC + +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m3-Bdp1-Brf-CG17209-Tbp 3 0.506442 12384 1 6 CACCTG CCTTAACCACTGAGCCACTG + +4 dbcorrdb__RBBP5__ENCSR000AQI_1__m1-E2f1-Eip74EF-E(z)-Hcf-lid-Myc-pho-phol-Rbbp5-RpII215-Sin3A-Taf1-tna 4 0.506442 12384 1 6 CACCTG GGCGACGCTTCCGGCGCCGG + +4 dbcorrdb__RELA__ENCSR000EBI_1__m3-Dif-dl 1 0.506442 12384 1 6 CACCTG TCCCCCCAAGGGGAAGTTCG + +4 dbcorrdb__RFX5__ENCSR000EHY_1__m5 4 0.506442 12384 1 6 CACCTG TGACAACCACTGATGCCAGA + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m1-brm-Jra-kay 11 0.506442 12384 1 6 CACCTG CCGTAGGGACTCACCCTGTG + +4 dbcorrdb__USF1__ENCSR000BPV_1__m1-bigmax-btd-cnc-cwo-cyc-E2f1-Max-Mitf-mor-Myc-Spps-SREBP-tgo-Usf 11 0.506442 12384 1 6 CACCTG CCGGCCCGGGTCACGTGACC + +4 homer__AAACYKGTTWDACMRGTTTB_GRHL2-GATAe-gem-grh-grn-nej-pnr 0 0.506442 12384 1 6 CACCTG AAACCGGTTTAACCAGTTTT + +4 predrem__nrMotif1138-Brf-CTCF-CoRest-ERR-Eip74EF-E(z)-HDAC1-Klf15-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-crol-ct-klu-l(3)neo38-peb-sr-tna-vtd 7 0.506442 12384 1 6 CACCTG CCCCCCCCACCCCCGCCCCC + +4 swissregulon__hs__RREB1.p2-Brf-CTCF-CoRest-Rbbp5-SREBP-Spt20-ct-klu-l(3)neo38-peb-sr 8 0.506442 12384 1 6 CACCTG CCCCCACCCACCCCCACCCC + +4 transfac_pro__M09028-Adf1 12 0.506442 12384 1 6 CACCTG CACCGCCGCCGCCACCGCCA + +4 dbcorrdb__BRF2__ENCSR000DNV_1__m1 3 0.506442 12384 1 6 CACCTG CTCTTCCTCACTTCCCCAGC - +4 dbcorrdb__CHD1__ENCSR000EBU_1__m2-bon-Chd1 5 0.506442 12384 1 6 CACCTG CCCCCCCCCGGGGGGGCAGT - +4 dbcorrdb__EZH2__ENCSR000ARE_1__m3-E(z) 9 0.506442 12384 1 6 CACCTG GTCTCCGTTCGCCGGCGCGT - +4 dbcorrdb__EZH2__ENCSR000ARI_1__m3-E(z)-RpII215 5 0.506442 12384 1 6 CACCTG GCCTGAGTCTCCGGCGTTTT - +4 dbcorrdb__GATA2__ENCSR000EYB_1__m1-GATAe-grn-pnr-srp 11 0.506442 12384 1 6 CACCTG GCCCAGGTTCTTATCTGCCC - +4 dbcorrdb__MAX__ENCSR000EZF_1__m1-Max 8 0.506442 12384 1 6 CACCTG AATAATGACACATGGTATTA - +4 dbcorrdb__MXI1__ENCSR000EBR_1__m3-Chd1 11 0.506442 12384 1 6 CACCTG GCTCGCGACAGCTCCGGCCG - +4 dbcorrdb__MYC__ENCSR000DLN_1__m1-Clk-cnc-E2f1-E(z)-gce-Max-Mnt-Myc-Sap30-Usf 10 0.506442 12384 1 6 CACCTG CGGCCCGGAGCACGTGGCCG - +4 dbcorrdb__NR2F2__ENCSR000BRS_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.506442 12384 1 6 CACCTG TCTTATCTGTCCCCCCCAGG - +4 dbcorrdb__POLR2A__ENCSR000EUU_1__m2-RpII215 5 0.506442 12384 1 6 CACCTG GGTATCGCTTGCCGCAGTGG - +4 dbcorrdb__POU5F1__ENCSR000BMU_1__m2-Mad-pan 6 0.506442 12384 1 6 CACCTG CAAGGGGGCCTTTCTTATGC - +4 dbcorrdb__RCOR1__ENCSR000EGC_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 5 0.506442 12384 1 6 CACCTG CTCCTTATCTGCGCCCCCCA - +4 dbcorrdb__RELA__ENCSR000EAG_1__m2-Dif-dl-Jra 1 0.506442 12384 1 6 CACCTG CGAACTGACTCATATGGGGA - +4 dbcorrdb__REST__ENCSR000BJJ_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 3 0.506442 12384 1 6 CACCTG GGGGCGCTGTCCATGGTGCT - +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m6-bon-egg 0 0.506442 12384 1 6 CACCTG CACAGGAGAGAAACCACACA - +4 dbcorrdb__USF1__ENCSR000BHX_1__m1-ac-ase-bigmax-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-Myc-nau-sc-Spps-SREBP-tgo-Usf-zfh1 8 0.506442 12384 1 6 CACCTG GCCCGGGTCACGTGACCCCG - +4 dbcorrdb__USF1__ENCSR000BIU_1__m1-bigmax-cnc-cwo-cyc-Max-Mitf-Myc-SREBP-tgo-Usf 3 0.506442 12384 1 6 CACCTG GGTCACGTGACCACGCCTGG - +4 dbcorrdb__ZKSCAN1__ENCSR000ECJ_1__m2 1 0.506442 12384 1 6 CACCTG TCACCAACTGTGTGTTGAGC - +4 hocomoco__TAL1_MOUSE.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-sd-srp-svp 4 0.506442 12384 1 6 CACCTG TTCTTATCTGTCTCCCCCAG - +4 taipale_cyt_meth__FOXA3_NWNWGTMAATATTKRYNYWN_FL-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.506442 12384 1 6 CACCTG TTAAGCAAATATTTACATAA - +4 taipale_cyt_meth__PRDM4_YRRCNGTTTCAAGKCYCCCC_eDBD 4 0.506442 12384 1 6 CACCTG GGGGGGCCTTGAAACTGTTG - +4 transfac_pro__M01498-GATAd-GATAe-grn-pnr-srp 3 0.506442 12384 1 6 CACCTG TTATCCCTTATCAGCCGGAA - +4 taipale_cyt_meth__PRDM4_YRRCRGTTTCRAGGGTTACC_eDBD_meth 16 0.506442 12384 1 4 CACCTG CGGCGGTTTCGAGGGTTACC + +4 tfdimers__MD00028-GATAe-grn-pnr-srp 14 0.507263 12404.1 1 6 CACCTG TTATTAAACAGGATTATCTTTTTT + +4 jaspar__MA0308.1 6 0.50825 12428.2 1 6 CACCTG ATTAAAAAACTCCGGAGTATA + +4 transfac_pro__M01499 6 0.50825 12428.2 1 6 CACCTG ATTAAAAAACTCCGGAGTAGA + +4 cisbp__M4604-btd-CoRest-ct-CTCF-Dif-dl-Klf15-klu-Spps-Spt20-sr 9 0.50825 12428.2 1 6 CACCTG CTCCTCCCCTCCCTCCTCCCC - +4 homer__ANTTMRCASBNNNGTGYKAAN_Brachyury-H15-byn-mid-org-1 5 0.50825 12428.2 1 6 CACCTG TTTAACACCTAGGTGTGAAAT - +4 taipale_tf_pairs__GCM1_PITX1_GGATTANNNNNNNNNTGCGGG_CAP_repr-gcm-gcm2-Ptx1 11 0.50825 12428.2 1 6 CACCTG CCCGCATAACCCCCCTAATCC - +4 tfdimers__MD00045-Stat92E 12 0.50825 12428.2 1 6 CACCTG AGAAAAGGAAACCACAGAAAC - +4 transfac_pro__M05207 17 0.50825 12428.2 1 4 CACCTG GGGCCGCGGCGGGGACCAACC - +4 tfdimers__MD00539-Myc-pho-phol 5 0.508568 12436 1 6 CACCTG GCCGGCAGCTGCCATCTTCCGCT + +4 tfdimers__MD00033-CrebB-pho-phol 7 0.508925 12444.8 1 6 CACCTG CAGCTGCCATCTGTCAGCTTGT + +4 tfdimers__MD00485-Myc 11 0.508925 12444.8 1 6 CACCTG GAATGCAGCTGCAGCTGCCTTC + +4 cisbp__M2395 3 0.508925 12444.8 1 6 CACCTG AGTTTCGTATATAATGATATGA - +4 hocomoco__VEZF1_HUMAN.H11MO.0.C-CTCF-CoRest-Dif-Klf15-Spps-Spt20-btd-ct-dl-klu-sr 6 0.508925 12444.8 1 6 CACCTG CCCCTCCCCCTCCCCCCTCCCC - +4 hocomoco__ZN467_HUMAN.H11MO.0.C-CTCF-CoRest-Dif-Klf15-Rbbp5-Spps-Spt20-btd-crol-ct-dl-klu-sr 13 0.508925 12444.8 1 6 CACCTG CCCCCCCCCCCCTCCCCTCCCC - +4 tfdimers__MD00259 11 0.508925 12444.8 1 6 CACCTG TTTTTTTTTATCAGCAGATTTA - +4 transfac_public__M00015 3 0.508925 12444.8 1 6 CACCTG AGTTTCGTATATAATGATATGT - +4 flyfactorsurvey__herF1-ZifF1_herF34_SOLEXA_5-her 6 0.510369 12480.1 1 6 CACCTG TACTCATAATTGCGT + +4 taipale_cyt_meth__ZNF771_NRCGCTAACCATTRN_FL-CG6654-CG7372 6 0.510369 12480.1 1 6 CACCTG AGCGCTAACCATTGT + +4 transfac_pro__M02771 8 0.510369 12480.1 1 6 CACCTG CAAAATCGAAACTAA + +4 transfac_pro__M09395 0 0.510369 12480.1 1 6 CACCTG TACTTCTTCAATAAG + +4 transfac_pro__M09496-cyc 0 0.510369 12480.1 1 6 CACCTG CACGTGACATTCACG + +4 factorbook__STAT2-Stat92E 8 0.510369 12480.1 1 6 CACCTG GGAAAATGAAACTGA - +4 flyfactorsurvey__her_SANGER_10_FBgn0001185-her 6 0.510369 12480.1 1 6 CACCTG TACTCATAATTGCGT - +4 taipale_cyt_meth__HSF2_NGAANNTTCYRGAAN_FL_meth-Hsf-pb-srl 7 0.510369 12480.1 1 6 CACCTG CTTCCAGAACGTTCC - +4 taipale_tf_pairs__ETV5_HOXB13_NNCGGANGNNNTWAA_CAP-Ets96B 5 0.510369 12480.1 1 6 CACCTG TTTACTACTTCCGCT - +4 transfac_pro__M09409 2 0.510369 12480.1 1 6 CACCTG TGCTGCTGCTGCTGC - +4 transfac_pro__M09517-Atf6-CrebA-Xbp1 8 0.510369 12480.1 1 6 CACCTG TGCCACGTCAGCATT - +4 transfac_pro__M09520-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 8 0.510369 12480.1 1 6 CACCTG AGTGACGTCATCATC - +4 transfac_public__M00215-bs -1 0.510369 12480.1 1 5 CACCTG GCCATATATGGCCAG + +4 c2h2_zfs__M5103 1 0.510538 12484.2 1 6 CACCTG TGACGTGCCAGGCGAAA + +4 taipale_tf_pairs__ETV5_ETV7_NNGGAMGGATKTCCGSN_CAP-aop-Ets96B 10 0.510538 12484.2 1 6 CACCTG GGGGAAGGATGTCCGGG + +4 transfac_pro__M01482-bap 6 0.510538 12484.2 1 6 CACCTG CATAACCACTTAACAAC + +4 transfac_pro__M01819 9 0.510538 12484.2 1 6 CACCTG CATAAAAAATATCTAAG + +4 transfac_pro__M02782-bap 6 0.510538 12484.2 1 6 CACCTG CTTAACCACTTAAGGAT + +4 transfac_pro__M07726-GATAe-grn-pnr 4 0.510538 12484.2 1 6 CACCTG AGATAACGACGTTATCT + +4 flyfactorsurvey__Hey_SANGER_5_FBgn0027788-Hey 4 0.510538 12484.2 1 6 CACCTG GGGGCACGTGTCGGCTG - +4 jaspar__MA0629.1 8 0.510538 12484.2 1 6 CACCTG TCGCTTTACAGCGTCTT - +4 taipale__ZBTB49_DBD_TTTCGCNTGGCNNGTCA_repr 1 0.510538 12484.2 1 6 CACCTG TGACGTGCCAGGCGAAA - +4 transfac_pro__M01384 8 0.510538 12484.2 1 6 CACCTG TCGCTTTACAGCGTCTT - +4 transfac_pro__M03134-E(spl)m3-HLH-Hey-Sidpn 5 0.510538 12484.2 1 6 CACCTG TAAGGCACGTGCCTTGA - +4 transfac_pro__M06498 11 0.510538 12484.2 1 6 CACCTG TCCATCGAAAGAAACTT - +4 transfac_pro__M08985 8 0.510538 12484.2 1 6 CACCTG CGTTCCGGTGCCTCCAT - +4 tfdimers__MD00142-gem-pho-phol 16 0.512577 12534 1 6 CACCTG ATTGGCCATCTGGCTTGCGCTGGCCTTG + +4 tfdimers__MD00363 11 0.512577 12534 1 6 CACCTG TTATCTTTTTCCATCTGTCACTGCTCCT - +4 cisbp__M1961-Stat92E 0 0.512761 12538.5 1 6 CACCTG CTTCTGGGAAA + +4 hocomoco__TEAD1_MOUSE.H11MO.0.A-sd 3 0.512761 12538.5 1 6 CACCTG ACATTCCAGGG + +4 predrem__nrMotif1016 2 0.512761 12538.5 1 6 CACCTG AAAGCCTTCCT + +4 predrem__nrMotif192 2 0.512761 12538.5 1 6 CACCTG CAGCCCTCCCC + +4 predrem__nrMotif604 0 0.512761 12538.5 1 6 CACCTG CCCCGGCCCTG + +4 predrem__nrMotif964 4 0.512761 12538.5 1 6 CACCTG CTGGCCCCGCC + +4 transfac_pro__M01704-ci-lmd-opa-sug 3 0.512761 12538.5 1 6 CACCTG GACCACCCACG + +4 transfac_pro__M07889-Bgb-lz-run-RunxA-RunxB 1 0.512761 12538.5 1 6 CACCTG TAACCGCAAAA + +4 cisbp__M1955-Stat92E 1 0.512761 12538.5 1 6 CACCTG TTTCCTGGAAA - +4 flyfactorsurvey__lola-PC_SOLEXA_FBgn0005630-lola 5 0.512761 12538.5 1 6 CACCTG GGATTTTCCCG - +4 jaspar__MA0137.3-Stat92E 1 0.512761 12538.5 1 6 CACCTG TTTCCTGGAAA - +4 swissregulon__hs__SPI1.p2-CG9650 1 0.512761 12538.5 1 6 CACCTG CCACTTCCTCT - +4 swissregulon__sacCer__CUP2 5 0.512761 12538.5 1 6 CACCTG CATTTCTGCTG - +4 taipale_tf_pairs__ETV7_NNGCGGAAGTG_HT-aop 0 0.512761 12538.5 1 6 CACCTG CACTTCCGCCT - +4 transfac_pro__M01003 3 0.512761 12538.5 1 6 CACCTG TTATCCCTATA - +4 transfac_pro__M05588 5 0.512761 12538.5 1 6 CACCTG GCTTTAGCCCG - +4 transfac_pro__M09282 1 0.512761 12538.5 1 6 CACCTG ATAACTGACTT - +4 flyfactorsurvey__Ets96B_SANGER_5_FBgn0039225-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt -1 0.512761 12538.5 1 5 CACCTG ACCGGAAGTGC + +4 transfac_pro__M05579 -1 0.512761 12538.5 1 5 CACCTG ACCCGCCAGAC + +4 cisbp__M1928-CG12018-Dif-dl-Rel-shn 6 0.512761 12538.5 1 5 CACCTG GGGAAATTCCC - +4 hocomoco__TF65_MOUSE.H11MO.0.A-CG12018-Dif-Rel-dl-shn 6 0.512761 12538.5 1 5 CACCTG GGGAAATTCCC - +4 transfac_pro__M07221-CG12018-Dif-dl-Rel-shn 6 0.512761 12538.5 1 5 CACCTG GGGAAATTCCC - +4 transfac_pro__M00978-arm-pan -2 0.512761 12538.5 1 4 CACCTG CCTTTGATGTT + +4 cisbp__M0998-al-ap-Awh-CG34367-E5-ems-en-ey-ind-inv-lbe-lbl-OdsH-repo-toy-Ubx-unc-4-unpg-Vsx2 1 0.51532 12601.1 1 6 CACCTG TTAATTAG + +4 cisbp__M1165 2 0.51532 12601.1 1 6 CACCTG TTAATCCC + +4 cisbp__M1241-nub-pdm2-vvl 0 0.51532 12601.1 1 6 CACCTG TTCATTAT + +4 predrem__nrMotif1738 2 0.51532 12601.1 1 6 CACCTG TCTTACTG + +4 predrem__nrMotif972 0 0.51532 12601.1 1 6 CACCTG CACACGGC + +4 taipale_cyt_meth__ALX3_NTCGTTAN_eDBD_meth-CG34367 0 0.51532 12601.1 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__DLX5_NTCGTTAN_FL_meth-abd-A-bsh-btn-Dll-Dr-eve-ind-Ubx 0 0.51532 12601.1 1 6 CACCTG GTCATTAT + +4 taipale_cyt_meth__ISL2_SCACTTAN_eDBD_meth-tup 1 0.51532 12601.1 1 6 CACCTG GCACTTAA + +4 taipale_cyt_meth__MSX1_NTCGTTAN_eDBD_meth_repr-bsh-btn-Dr-lab 0 0.51532 12601.1 1 6 CACCTG ATCGTTAT + +4 transfac_pro__M05550-Pbp95 0 0.51532 12601.1 1 6 CACCTG TACCGATT + +4 transfac_public__M00253 1 0.51532 12601.1 1 6 CACCTG TCAGTCTT + +4 cisbp__M0419-sr 0 0.51532 12601.1 1 6 CACCTG CGCCCACG - +4 elemento__ACACGTCA 1 0.51532 12601.1 1 6 CACCTG TGACGTGT - +4 elemento__CCACGTCA-Atf6-CrebA 1 0.51532 12601.1 1 6 CACCTG TGACGTGG - +4 elemento__TCCATGTC 0 0.51532 12601.1 1 6 CACCTG GACATGGA - +4 hdpi__MGC10433-CG2931 0 0.51532 12601.1 1 6 CACCTG TTCATTTT - +4 swissregulon__hs__HOX_A4_D4_.p2-Dfd 1 0.51532 12601.1 1 6 CACCTG CCAATTTT - +4 yetfasco__YER184C_512 0 0.51532 12601.1 1 6 CACCTG TTCCGGAG - +4 cisbp__M4207 3 0.51532 12601.1 1 5 CACCTG CGGATCCG + +4 transfac_pro__M01936 3 0.51532 12601.1 1 5 CACCTG CGGATCCG + +4 cisbp__M0410 3 0.51532 12601.1 1 5 CACCTG GATCCCCA - +4 cisbp__M0415 -1 0.51532 12601.1 1 5 CACCTG ACCGTTAT - +4 jaspar__MA0404.1 3 0.51532 12601.1 1 5 CACCTG CGGATCCG - +4 transfac_pro__M08918-brm-CoRest-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 3 0.51532 12601.1 1 5 CACCTG TCTTATCT - +4 yetfasco__YBR150C_552 3 0.51532 12601.1 1 5 CACCTG CGGATCCG - +4 cisbp__M5621-achi-hth-vis -2 0.51532 12601.1 1 4 CACCTG CCTGTCAA + +4 predrem__nrMotif2600 -2 0.51532 12601.1 1 4 CACCTG CCTCGAGG + +4 cisbp__M5214-CoRest-ebi-GATAd-GATAe-grn-HLH3B-Jra-pnr-Snr1-srp -2 0.51532 12601.1 1 4 CACCTG CCTTATCA - +4 hdpi__DUSP26-CG7378 -2 0.51532 12601.1 1 4 CACCTG CCTTTGGC - +4 predrem__nrMotif1231 4 0.51532 12601.1 1 4 CACCTG CCAGAACT - +4 transfac_pro__M00646 4 0.51532 12601.1 1 4 CACCTG CTGACCCC - +4 neph__UW.Motif.0287 4 0.515626 12608.6 1 6 CACCTG CAAATTCATTTTTC + +4 neph__UW.Motif.0540 1 0.515626 12608.6 1 6 CACCTG TTTCCAGAAAGAAA + +4 swissregulon__hs__PAX6.p2-ey-toy 4 0.515626 12608.6 1 6 CACCTG TTCACGCTTGATTT + +4 taipale__FOXO6_DBD_GTAAACATGTTTAC-fd59A-foxo-slp2 3 0.515626 12608.6 1 6 CACCTG GTAAACATGTTTAC + +4 transfac_pro__M02767 8 0.515626 12608.6 1 6 CACCTG GAGAACCGAAACTG + +4 transfac_pro__M02919-dve 1 0.515626 12608.6 1 6 CACCTG TTGCCCGGATTAGG + +4 transfac_pro__M09524-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 8 0.515626 12608.6 1 6 CACCTG AATGACGTCATCAT + +4 hocomoco__ZEP2_HUMAN.H11MO.0.D-shn 5 0.515626 12608.6 1 6 CACCTG GGGGTTTCCCTACC - +4 transfac_pro__M01031-btd-EcR-eg-fkh-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 2 0.515626 12608.6 1 6 CACCTG TTGAACTTTGCCCC - +4 transfac_pro__M07707-bin-CHES-1-like-croc-fd59A-fkh-FoxK-foxo-FoxP-slp1-slp2 6 0.515626 12608.6 1 6 CACCTG TTTGTTTACATTAT - +4 neph__UW.Motif.0430 9 0.515626 12608.6 1 5 CACCTG AAAAATGAATTCCA + +4 hocomoco__HNF4G_HUMAN.H11MO.0.B-EcR-HDAC1-Hnf4-Hr78-Spps-btd-eg-kni-knrl-nej-svp-usp 9 0.515626 12608.6 1 5 CACCTG TGGACTTTGGACTC - +4 swissregulon__hs__HNF1A.p2 10 0.515626 12608.6 1 4 CACCTG GTTAATCATTAACC - +4 cisbp__M1493 2 0.515942 12616.3 1 5 CACCTG ATGAACC + +4 cisbp__M0378 2 0.515942 12616.3 1 5 CACCTG CACACTC - +4 hdpi__CCDC16-CG11839 2 0.515942 12616.3 1 5 CACCTG TTCATTT - +4 transfac_pro__M08888 -1 0.515942 12616.3 1 5 CACCTG TGCTGAA - +4 predrem__nrMotif1316 3 0.515942 12616.3 1 4 CACCTG CATGTCC - +4 predrem__nrMotif2523 -2 0.515942 12616.3 1 4 CACCTG CCTCAAA - +4 predrem__nrMotif426 -2 0.515942 12616.3 1 4 CACCTG CCTCTCC - +4 fantom__motif104_GTWSGMT 4 0.515942 12616.3 1 3 CACCTG ATCCTAC - +4 transfac_public__M00396-en-inv 4 0.515942 12616.3 1 3 CACCTG CAATTAC - +4 cisbp__M6260-fkh-Hsf 4 0.516632 12633.2 1 6 CACCTG CCGGGACAGTCTGTTCTC + +4 transfac_pro__M05815 8 0.516632 12633.2 1 6 CACCTG CCCGTGCATTCCTACGAC - +4 transfac_pro__M09497-Clk-cnc-cyc-Mitf-SREBP-tgo-Usf -1 0.516632 12633.2 1 5 CACCTG ACGTGAATGTCACGTGAC + +4 tfdimers__MD00176-E2f1 16 0.516939 12640.7 1 6 CACCTG TTTTTCCTTTCACTTTCCCTTTTTTTT + +4 tfdimers__MD00122 13 0.516939 12640.7 1 6 CACCTG TTCTACCTGTTCTGACTTGCCTTTTTT - +4 tfdimers__MD00595-SREBP-Tbp 12 0.516939 12640.7 1 6 CACCTG TATATAATTTATCACCTCACGCATACT - +4 flyfactorsurvey__CG11071_SANGER_5_FBgn0030532-mamo 2 0.517397 12651.9 1 6 CACCTG TAAGCCTATTGA + +4 hocomoco__ZN563_HUMAN.H11MO.1.C 4 0.517397 12651.9 1 6 CACCTG CAGGCAGCACAG + +4 predrem__nrMotif2491-Spps-btd 0 0.517397 12651.9 1 6 CACCTG CCCCTTCCCCGC + +4 taipale_cyt_meth__ZNF281_GCCCCTCCCCCM_eDBD_repr-btd-Spps 1 0.517397 12651.9 1 6 CACCTG GCCCCTCCCCCA + +4 transfac_pro__M00776-SREBP 5 0.517397 12651.9 1 6 CACCTG GCGATCACCCCA + +4 transfac_pro__M03561-acj6-nub-pdm2-vvl 5 0.517397 12651.9 1 6 CACCTG TAATTTGCATAT + +4 transfac_pro__M06113 5 0.517397 12651.9 1 6 CACCTG CCCGGCTCCTGA + +4 transfac_pro__M06675 2 0.517397 12651.9 1 6 CACCTG CGAAGCTAAACA + +4 transfac_pro__M06726 2 0.517397 12651.9 1 6 CACCTG GGCTCCTAATGA + +4 transfac_pro__M08924-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.517397 12651.9 1 6 CACCTG GATGACGTCATC + +4 hocomoco__ELK3_HUMAN.H11MO.0.D-Eip74EF-Ets97D 4 0.517397 12651.9 1 6 CACCTG GCACTTCCTGTG - +4 stark__AATTWWNAYGCR 0 0.517397 12651.9 1 6 CACCTG CGCATAAAAATT - +4 taipale_cyt_meth__PROX1_NAAGRCGTCTTN_eDBD-pros 5 0.517397 12651.9 1 6 CACCTG CAAGACGCCTTA - +4 taipale_cyt_meth__PROX1_NAAGRYGTCTTN_eDBD_meth_repr-pros 5 0.517397 12651.9 1 6 CACCTG CAAGACGTCTTA - +4 transfac_pro__M05153 1 0.517397 12651.9 1 6 CACCTG CTACTTCAAGCG - +4 transfac_pro__M05867 2 0.517397 12651.9 1 6 CACCTG TCTACCGACACT - +4 transfac_pro__M05878 6 0.517397 12651.9 1 6 CACCTG TCCGCCCTCCAG - +4 transfac_pro__M06049 1 0.517397 12651.9 1 6 CACCTG GGAACTCCCCCT - +4 transfac_pro__M06296 6 0.517397 12651.9 1 6 CACCTG TCTTTTCCCCAG - +4 transfac_pro__M06862 6 0.517397 12651.9 1 6 CACCTG TTGTCTGACCTT - +4 transfac_pro__M09585-Atf6-crc-CrebA-CrebB-Jra-kay-maf-S-Xbp1 5 0.517397 12651.9 1 6 CACCTG TTGATGACGTCA - +4 cisbp__M6512-pan -1 0.517397 12651.9 1 5 CACCTG CCCTTTGATCTT + +4 swissregulon__sacCer__HAP1 7 0.517397 12651.9 1 5 CACCTG CCGATATCTCCG + +4 taipale_tf_pairs__TEAD4_ETV1_RSCGGAAATRCM_CAP-Ets96B-sd -1 0.517397 12651.9 1 5 CACCTG ACCGGAAATACC + +4 transfac_pro__M05883 7 0.517397 12651.9 1 5 CACCTG CGGACCAAACCC + +4 cisbp__M6448-CG12018-Dif-dl-Rab18-Rel 7 0.517397 12651.9 1 5 CACCTG GGGAAATCCCCC - +4 hocomoco__RELB_HUMAN.H11MO.0.C-CG12018-Dif-Rab18-Rel-dl 7 0.517397 12651.9 1 5 CACCTG GGGAAATCCCCC - +4 transfac_pro__M05376 7 0.517397 12651.9 1 5 CACCTG ACCCCGGCACCA - +4 transfac_pro__M06318 7 0.517397 12651.9 1 5 CACCTG GATTTTTTACAG - +4 transfac_pro__M06331 7 0.517397 12651.9 1 5 CACCTG TCGGCCGGACCA - +4 transfac_pro__M06350 -1 0.517397 12651.9 1 5 CACCTG TCCTACGCCCAG - +4 transfac_pro__M06440-CG3281 -1 0.517397 12651.9 1 5 CACCTG TCCTTCTTCCCC - +4 cisbp__M4913-disco-r 8 0.517397 12651.9 1 4 CACCTG AAGAATGTCACC + +4 taipale_cyt_meth__CREB3L4_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 8 0.517397 12651.9 1 4 CACCTG GATGACGTCACC - +4 transfac_pro__M05658 8 0.517397 12651.9 1 4 CACCTG GCCTAATCCACA - +4 transfac_pro__M06188 8 0.517397 12651.9 1 4 CACCTG GCGTTAGCCACG - +4 transfac_pro__M06811 8 0.517397 12651.9 1 4 CACCTG TCGGCCTTAACA - +4 neph__UW.Motif.0534 9 0.517397 12651.9 1 3 CACCTG CAGAAAAGAAAC + +4 cisbp__M1282 6 0.518142 12670.1 1 6 CACCTG GGTTAACCCCCTT + +4 cisbp__M3031 4 0.518142 12670.1 1 6 CACCTG AACTTACCAAACA + +4 neph__UW.Motif.0206 2 0.518142 12670.1 1 6 CACCTG AAACCATTTTTTC + +4 swissregulon__sacCer__MIG3-klu-sr 2 0.518142 12670.1 1 6 CACCTG GTTACCCCGCATT + +4 taipale__ZBED1_DBD_NTATCGCGAYATR_repr-CG13775 7 0.518142 12670.1 1 6 CACCTG CTATCGCGACATA + +4 taipale_cyt_meth__OVOL2_NWWCCGTTAYNYN_FL-ovo 1 0.518142 12670.1 1 6 CACCTG GTACCGTTATGTG + +4 transfac_pro__M09467-dsf-tll 6 0.518142 12670.1 1 6 CACCTG ATCGTTGACTTTT + +4 cisbp__M2275-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.518142 12670.1 1 6 CACCTG CACTTCCTGGTTC - +4 cisbp__M4620-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-pnt-Rbbp5-RpII215-Sin3A-Taf1 0 0.518142 12670.1 1 6 CACCTG CACTTCCGGTGCC - +4 hocomoco__E2F6_HUMAN.H11MO.0.A-Dp-E2f1-E2f2 3 0.518142 12670.1 1 6 CACCTG CCCTTCCCGCCCC - +4 hocomoco__PO4F2_HUMAN.H11MO.0.D-Dfd-Lim3-Scr 0 0.518142 12670.1 1 6 CACCTG AAGCTCATTAATA - +4 neph__UW.Motif.0234 3 0.518142 12670.1 1 6 CACCTG TGTTTGCTTTTCA - +4 stark__VSNKTDATKRCNV-Abd-B 7 0.518142 12670.1 1 6 CACCTG TAGCAATTAAACT - +4 transfac_pro__M07629-TfAP-2 0 0.518142 12670.1 1 6 CACCTG TGCCCTCAGGGCA - +4 transfac_pro__M09138 3 0.518142 12670.1 1 6 CACCTG TTAGATCTGGATC - +4 cisbp__M5669-Dif-dl-Rel-shn 8 0.518142 12670.1 1 5 CACCTG AGGGGAATCCCCT - +4 neph__UW.Motif.0501 8 0.518142 12670.1 1 5 CACCTG TTGCAAAAATCCA - +4 hdpi__RPL6-RpL6 0 0.519919 12713.6 1 6 CACCTG CATTTG - +4 transfac_public__M00048 1 0.519919 12713.6 1 5 CACCTG ACCCCA - +4 cisbp__M1269 4 0.520202 12720.5 1 6 CACCTG ATCGAAACTA + +4 cisbp__M1619 1 0.520202 12720.5 1 6 CACCTG TGGCCGGCCC + +4 cisbp__M1645 3 0.520202 12720.5 1 6 CACCTG GGGGACCACC + +4 taipale_cyt_meth__HMX2_NCCAMTTAAN_FL_meth-bap-Hmx 2 0.520202 12720.5 1 6 CACCTG ACCACTTAAC + +4 taipale_cyt_meth__NEUROG2_RNCATATGNY_FL-amos-ato-HLH54F-Oli-tap 0 0.520202 12720.5 1 6 CACCTG GACATATGTC + +4 transfac_pro__M06081 0 0.520202 12720.5 1 6 CACCTG TAGCTGGACA + +4 transfac_pro__M07350-cyc 3 0.520202 12720.5 1 6 CACCTG AGCCACGTGA + +4 transfac_pro__M07489 3 0.520202 12720.5 1 6 CACCTG AACTAACGGA + +4 transfac_pro__M09563 3 0.520202 12720.5 1 6 CACCTG TTTTGGCGGC + +4 cisbp__M1556 1 0.520202 12720.5 1 6 CACCTG TTACGAAAAA - +4 homer__CCWGGAATGY_TEAD2-sd 3 0.520202 12720.5 1 6 CACCTG ACATTCCAGG - +4 homer__CWGGCGGGAA_E2F1-E2f1 4 0.520202 12720.5 1 6 CACCTG TTCCCGCCAG - +4 transfac_pro__M01974-aop-Eip74EF-Ets21C-Ets96B-pnt 3 0.520202 12720.5 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M01992-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 0 0.520202 12720.5 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02042-Ets21C-Ets96B-pnt 3 0.520202 12720.5 1 6 CACCTG TACTTCCGCT - +4 transfac_pro__M02063-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-Taf1 0 0.520202 12720.5 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M02065-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-nej-pnt-RpII215-Taf1 3 0.520202 12720.5 1 6 CACCTG CACTTCCGGT - +4 jaspar__MA0355.1 -1 0.520202 12720.5 1 5 CACCTG ACCTGCAGCA + +4 predrem__nrMotif137 -1 0.520202 12720.5 1 5 CACCTG TCCTCTCTTC + +4 predrem__nrMotif1446 -1 0.520202 12720.5 1 5 CACCTG GCCTGCCGGG + +4 transfac_pro__M01816 -1 0.520202 12720.5 1 5 CACCTG CCCTCCCCCA + +4 transfac_pro__M02062-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.520202 12720.5 1 5 CACCTG ACCGGAAGTG + +4 predrem__nrMotif1339 5 0.520202 12720.5 1 5 CACCTG AAATGCACTT - +4 taipale_cyt_meth__POU6F1_NTAATKAGSN_FL_repr-pdm3 -1 0.520202 12720.5 1 5 CACCTG ACCTCATTAT - +4 transfac_pro__M05769 5 0.520202 12720.5 1 5 CACCTG TGCCGTATCT - +4 transfac_pro__M05954 5 0.520202 12720.5 1 5 CACCTG TGCCGTATCT - +4 yetfasco__YKL043W_2153 -1 0.520202 12720.5 1 5 CACCTG ACGTGCATCA - +4 taipale_cyt_meth__BATF_NMATGACACN_FL_repr 6 0.520202 12720.5 1 4 CACCTG GAATGACACG + +4 transfac_pro__M07296-cnc-ewg-Jra-kay-maf-S-mor-nej -2 0.520202 12720.5 1 4 CACCTG GCTGAGTCAC + +4 cisbp__M1506 6 0.520202 12720.5 1 4 CACCTG AACCGAAACT - +4 scertf__foat.OPI1-Brf-CG17209-Hsf-SREBP 6 0.520202 12720.5 1 4 CACCTG GATTCGAACC - +4 jaspar__MA0085.1-Su(H) 7 0.520231 12721.2 1 6 CACCTG TTGTGGGAACCGAGAT + +4 neph__UW.Motif.0468 7 0.520231 12721.2 1 6 CACCTG CTCCAGATATCTGGCA + +4 transfac_pro__M03826 10 0.520231 12721.2 1 6 CACCTG CGTTAATCATTAACTA + +4 transfac_public__M00145-vvl 0 0.520231 12721.2 1 6 CACCTG GCCATCCAAAATGAGC + +4 cisbp__M3009-vvl 0 0.520231 12721.2 1 6 CACCTG GCCATCCAAAATGAAC - +4 cisbp__M6559 7 0.520231 12721.2 1 6 CACCTG CGGCAGTAACCGTGGG - +4 taipale_tf_pairs__ELK1_HOXB13_RSCGGAAGNNGTAAAN_CAP_repr 6 0.520231 12721.2 1 6 CACCTG TTTTACAACTTCCGGT - +4 taipale_tf_pairs__HOXB13_ELK1_RSMGGAARTNNTAAAN_CAP 9 0.520231 12721.2 1 6 CACCTG TTTTATGACTTCCGGT - +4 transfac_pro__M01922 0 0.520363 12724.4 1 5 CACCTG CATCG - +4 tfdimers__MD00542-E2f1-kn 5 0.520604 12730.3 1 6 CACCTG TGAGTTCCCAGGGGGTTTCCCTTCTT + +4 tfdimers__MD00041 7 0.520787 12734.8 1 6 CACCTG AATAAGAAAACTAGTTAATGATTAATTAAT + +4 cisbp__M6346-Mondo 12 0.521198 12744.9 1 6 CACCTG CCACGGCGGTGTCACATGC + +4 cisbp__M2366 12 0.521198 12744.9 1 6 CACCTG GCGAGTAATCATTACGATT - +4 hocomoco__TAL1_HUMAN.H11MO.0.A-CoRest-CycT-GATAe-HDAC1-HLH3B-Jra-RpII215-Sirt6-Snr1-Stat92E-brm-ebi-grn-nej-pnr-srp-svp 3 0.521198 12744.9 1 6 CACCTG CCTTATCTGCCCCCCCCAG - +4 jaspar__MA0573.1 12 0.521198 12744.9 1 6 CACCTG GCGAGTAATCATTACGATT - +4 taipale_cyt_meth__MAX_NCATGTGNNNNNCATGTGN_eDBD_meth-Max 12 0.521198 12744.9 1 6 CACCTG GCACATGGTAAGCACATGG - +4 taipale_tf_pairs__TEAD4_SOX6_NNACAATNNNNNNGAATGY_CAP_repr-sd-Sox102F 3 0.521198 12744.9 1 6 CACCTG ACATTCCATTCCATTGTTC - +4 transfac_pro__M01780 7 0.521198 12744.9 1 6 CACCTG ACATCCAAACACCAATACA - +4 transfac_pro__M09126-Blimp-1-CG9650 4 0.521198 12744.9 1 6 CACCTG TTTTCACTTTTTCTTTTTT - +4 transfac_pro__M06356 -1 0.521198 12744.9 1 5 CACCTG ACCATCCCAACCCCCCCAT - +4 transfac_pro__M06445 -1 0.521198 12744.9 1 5 CACCTG CCCTTTCTTTACTCACAAA - +4 cisbp__M0358-CG7786-gt-Pdp1-vri 2 0.521555 12753.6 1 6 CACCTG ATTACATAA + +4 cisbp__M1426 2 0.521555 12753.6 1 6 CACCTG TTGATCTTT + +4 cisbp__M1946-ovo-Poxn 2 0.521555 12753.6 1 6 CACCTG AGTAACAGT + +4 elemento__CCAGCCTGG 2 0.521555 12753.6 1 6 CACCTG CCAGCCTGG + +4 neph__UW.Motif.0039-maf-S 3 0.521555 12753.6 1 6 CACCTG AAAATGCTG + +4 predrem__nrMotif963 2 0.521555 12753.6 1 6 CACCTG AAAACCAAA + +4 scertf__spivak.GCR1 3 0.521555 12753.6 1 6 CACCTG GGCTTCCAC + +4 transfac_pro__M04718-Hr78 1 0.521555 12753.6 1 6 CACCTG TGACCCGGA + +4 transfac_pro__M09555 3 0.521555 12753.6 1 6 CACCTG TGAAAACGT + +4 bergman__Cf2-Cf2 0 0.521555 12753.6 1 6 CACCTG TATATATAC - +4 cisbp__M0479 2 0.521555 12753.6 1 6 CACCTG TGGCCCCAC - +4 cisbp__M0605 3 0.521555 12753.6 1 6 CACCTG TATTTCCGC - +4 cisbp__M0761 2 0.521555 12753.6 1 6 CACCTG CTGATCATA - +4 cisbp__M1006-Abd-B 3 0.521555 12753.6 1 6 CACCTG TTTTATGAG - +4 cisbp__M1370 2 0.521555 12753.6 1 6 CACCTG CTCATCGCG - +4 cisbp__M1467 3 0.521555 12753.6 1 6 CACCTG AAAGATCAA - +4 fantom__motif13_GAGGATGCK 2 0.521555 12753.6 1 6 CACCTG AGCATCCTC - +4 jaspar__MA1016.1 2 0.521555 12753.6 1 6 CACCTG CTGATCATA - +4 predrem__nrMotif1321 1 0.521555 12753.6 1 6 CACCTG AAACATAAA - +4 predrem__nrMotif1685 3 0.521555 12753.6 1 6 CACCTG AGAGGCTTG - +4 predrem__nrMotif271 2 0.521555 12753.6 1 6 CACCTG TGTCCCTGT - +4 transfac_pro__M01746 3 0.521555 12753.6 1 6 CACCTG CCAACCCTA - +4 transfac_pro__M04932-btd-Spps 3 0.521555 12753.6 1 6 CACCTG CCGCCCCTT - +4 transfac_pro__M07608-CG5641-Jra-kay-NFAT 3 0.521555 12753.6 1 6 CACCTG TTTTTCCAT - +4 cisbp__M4954-Ets98B -1 0.521555 12753.6 1 5 CACCTG ACCCGGATC + +4 flyfactorsurvey__aop_SANGER_10_FBgn0000097-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Taf1-aop-bs-pnt -1 0.521555 12753.6 1 5 CACCTG ACCGGAAGT + +4 predrem__nrMotif1378 -1 0.521555 12753.6 1 5 CACCTG ATCTGGGCT + +4 predrem__nrMotif1624 -1 0.521555 12753.6 1 5 CACCTG ACCACATCT + +4 predrem__nrMotif2294 -1 0.521555 12753.6 1 5 CACCTG TTCTGTAAC + +4 predrem__nrMotif530 4 0.521555 12753.6 1 5 CACCTG CTATCCCCT + +4 taipale_cyt_meth__IRF6_ACCGAWACY_FL_repr 4 0.521555 12753.6 1 5 CACCTG ACCGAAACT + +4 transfac_pro__M00962 -1 0.521555 12753.6 1 5 CACCTG ACGTGCTCA - +4 transfac_pro__M04637 -1 0.521555 12753.6 1 5 CACCTG AACTAACAG - +4 hdpi__RFX3-CG5846-Max-Rfx-SREBP -2 0.521555 12753.6 1 4 CACCTG CATGGCAAC + +4 predrem__nrMotif1650 5 0.521555 12753.6 1 4 CACCTG TGTCTCACT + +4 predrem__nrMotif2528 5 0.521555 12753.6 1 4 CACCTG ACTCAGACA + +4 predrem__nrMotif499 5 0.521555 12753.6 1 4 CACCTG GTGGAAACA + +4 predrem__nrMotif792 5 0.521555 12753.6 1 4 CACCTG GGAACCACA + +4 cisbp__M0821 5 0.521555 12753.6 1 4 CACCTG TTCCGTACA - +4 predrem__nrMotif1241 -2 0.521555 12753.6 1 4 CACCTG CCTCCGCGC - +4 predrem__nrMotif413 -2 0.521555 12753.6 1 4 CACCTG TCTGAAACT - +4 predrem__nrMotif2485 -3 0.521555 12753.6 1 3 CACCTG CTCATGACT + +4 predrem__nrMotif2664 6 0.521555 12753.6 1 3 CACCTG TGCACTGAC + +4 predrem__nrMotif447 -3 0.521555 12753.6 1 3 CACCTG CTGTTGCTG + +4 taipale_cyt_meth__CPSF4_MCCNCCNCCNCCCCNCCCCCNCCAN_FL_repr-btd-Clp-klu-Spps 19 0.523517 12801.6 1 6 CACCTG CCCACCACCACCCCACCCCCACCAA + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m10-E(z) 4 0.524383 12822.7 1 6 CACCTG GACAGACCTTCAACCCCCAG + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m5-E(z) 7 0.524383 12822.7 1 6 CACCTG ACGGTTGAACGTTATCTGGC + +4 dbcorrdb__GATA1__ENCSR000EXR_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 4 0.524383 12822.7 1 6 CACCTG TCCTTATCTGTCCCCCCCAG + +4 dbcorrdb__MAFK__ENCSR000EDZ_1__m2-maf-S 7 0.524383 12822.7 1 6 CACCTG TACTACTGACCGTTTGCAAA + +4 dbcorrdb__MXI1__ENCSR000EBR_1__m2-CG5846-CG9727-Rfx-Sin3A-SREBP 4 0.524383 12822.7 1 6 CACCTG CGTTCCCCTGGCAACGGCCG + +4 dbcorrdb__MYC__ENCSR000DLI_1__m3-Myc 9 0.524383 12822.7 1 6 CACCTG CCCCCACGTCACCAGCGAAC + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m2-RpII215 1 0.524383 12822.7 1 6 CACCTG GCATCTTGGTAATGCTACCC + +4 dbcorrdb__REST__ENCSR000BHM_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 3 0.524383 12822.7 1 6 CACCTG CAGCACCATGGACAGCGCCC + +4 dbcorrdb__RFX5__ENCSR000EFD_1__m5 3 0.524383 12822.7 1 6 CACCTG ACCCACCAGGACAGAGCGGA + +4 dbcorrdb__TAF1__ENCSR000BHT_1__m1-lid-pho-phol-Rbbp5-RpII215-Sin3A-Taf1-Taf7 9 0.524383 12822.7 1 6 CACCTG CGCCGCCGCAATCTTGGGGC + +4 dbcorrdb__TAF1__ENCSR000BQF_1__m1-Hcf-lid-Myc-pho-phol-Rbbp5-RpII215-Sin3A-Taf1-Taf7 9 0.524383 12822.7 1 6 CACCTG CGCCGCCGGCATCTTGGGGC + +4 dbcorrdb__TBP__ENCSR000ECB_1__m3-Tbp 8 0.524383 12822.7 1 6 CACCTG AGTTCCGCCACCTGCCAGTT + +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m5 5 0.524383 12822.7 1 6 CACCTG TAACATATTTATAGGGTTCC + +4 dbcorrdb__eGFP-HDAC8__ENCSR000DJZ_1__m4 12 0.524383 12822.7 1 6 CACCTG CTCGGACACACAGGCCTGTG + +4 transfac_pro__M09062 13 0.524383 12822.7 1 6 CACCTG CCACCACCACCTCCACCGAC + +4 cisbp__M6161 7 0.524383 12822.7 1 6 CACCTG CCCTCTGCACGTGACCCGGT - +4 dbcorrdb__BCL3__ENCSR000BKG_1__m7 2 0.524383 12822.7 1 6 CACCTG GCCTGCTGTCTGTTCTTATC - +4 dbcorrdb__FOXA1__ENCSR000BKY_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-FoxP-GATAe-grn-HDAC1-nej-pnr-slp2 10 0.524383 12822.7 1 6 CACCTG ATTCCTTGTTTACTTAGGGA - +4 dbcorrdb__FOXA1__ENCSR000BMO_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-GATAe-grn-HDAC1-nej-Nf1-pnr-slp2 10 0.524383 12822.7 1 6 CACCTG AGTCTTTGTTTACTTAGCGA - +4 dbcorrdb__GATA1__ENCSR000EXP_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 5 0.524383 12822.7 1 6 CACCTG TTCCTTATCTGTCCCCCCCA - +4 dbcorrdb__JUND__ENCSR000EBZ_1__m2-CoRest-CrebB-Jra-kay-mor-pan 11 0.524383 12822.7 1 6 CACCTG CCGGGTTGAGTCACCCCGGG - +4 dbcorrdb__JUN__ENCSR000ECA_1__m1-Jra-kay 2 0.524383 12822.7 1 6 CACCTG CATTCCTGAGGGATGACTCA - +4 dbcorrdb__KDM5A__ENCSR000AQL_1__m2-Hcf-Hr78-lid-Sin3A 5 0.524383 12822.7 1 6 CACCTG GCGACCGCGTCCGGCGCCGC - +4 dbcorrdb__MYBL2__ENCSR000BRO_1__m1-btd-EcR-HDAC1-Hnf4-nej-Spps-svp 10 0.524383 12822.7 1 6 CACCTG CTGGACTTTGAACTCTGGAC - +4 dbcorrdb__MYC__ENCSR000DLR_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-Max-Mnt-Myc-Nelf-E-RpII215-Sap30-Sin3A-Spps-SREBP-Taf1-tna-Usf 9 0.524383 12822.7 1 6 CACCTG CGCGGCGCGCACGTGGCCCC - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m9-RpII215 11 0.524383 12822.7 1 6 CACCTG CACTGCCGCCCCGCCAAAAA - +4 dbcorrdb__RCOR1__ENCSR000ECM_1__m3-CoRest 5 0.524383 12822.7 1 6 CACCTG GCAGCTGCCTGAGTGATGCC - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m4-usp 13 0.524383 12822.7 1 6 CACCTG CGGCACCAAGCGACTACTGC - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m7-usp 5 0.524383 12822.7 1 6 CACCTG ACCCCCACCGAATGACGGCT - +4 dbcorrdb__SMARCA4__ENCSR000EHO_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 5 0.524383 12822.7 1 6 CACCTG TTCCTTATCTGTCCCCCCCA - +4 dbcorrdb__TAL1__ENCSR000EHB_1__m1-brm-CoRest-CycT-ebi-GATAd-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-Stat92E-svp 4 0.524383 12822.7 1 6 CACCTG TTCTTATCTGTACCCACCAG - +4 dbcorrdb__TEAD4__ENCSR000BRK_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HLH3B-nej-pnr-sd-Sirt6-srp 10 0.524383 12822.7 1 6 CACCTG CCTATTTTCTTATCTGTCCC - +4 dbcorrdb__USF2__ENCSR000ECW_1__m1-cnc-Max-Mitf-Usf 13 0.524383 12822.7 1 6 CACCTG GGCCGGCCCGGGTCACGTGA - +4 dbcorrdb__USF2__ENCSR000EEF_1__m1-bigmax-btd-Clk-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf 5 0.524383 12822.7 1 6 CACCTG CGGGTCACGTGACCCCGCCG - +4 dbcorrdb__ZNF274__ENCSR000EWE_1__m3 10 0.524383 12822.7 1 6 CACCTG CCACATTCATTACATTCAAA - +4 dbcorrdb__eGFP-JUNB__ENCSR000DJY_1__m2-CoRest-ebi-GATAe-grn-HDAC1-HLH3B-Jra-pnr-sd-srp 8 0.524383 12822.7 1 6 CACCTG CATTTTCTTATCTGCGGCAA - +4 hocomoco__BHE41_HUMAN.H11MO.0.D 7 0.524383 12822.7 1 6 CACCTG GCTTCTGCACGTGGCCCTGT - +4 taipale_cyt_meth__FOXA2_NWNWGTMAATATTKRYNYWN_eDBD-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.524383 12822.7 1 6 CACCTG CTATGTAAATATTGACATAG - +4 taipale_cyt_meth__FOXA2_NWNWGTMAATATTKRYNYWN_eDBD_meth_repr-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.524383 12822.7 1 6 CACCTG CTATGTAAATATTGACATAG - +4 transfac_pro__M09038 2 0.526312 12869.9 1 6 CACCTG TCCACCGACACCACCACCACC - +4 transfac_pro__M09403 3 0.526312 12869.9 1 6 CACCTG GGTTGCGTAAAATACAAGCAA - +4 taipale_tf_pairs__TEAD4_PAX5_RCATWCCNNNNNNNNNNNNRWGCGTGACN_CAP_repr-sd-sv 3 0.526362 12871.1 1 6 CACCTG ACATACCTCGTGGGCAGTCATGCGTGACG + +4 taipale_tf_pairs__ERF_TBX21_NRGTGTNANNNNNNNNNNNNNCCGGAANN_CAP-Ets21C 24 0.526362 12871.1 1 5 CACCTG ACTTCCGGTGTGACCCGTACTTCACACCT - +4 transfac_pro__M04639-jumu 15 0.527098 12889.1 1 6 CACCTG GTGTCCAGACGCCATTAACAGA - +4 transfac_pro__M08795 10 0.527098 12889.1 1 6 CACCTG AGGCATCGCCGACATCACCCCC - +4 cisbp__M3020-ct 9 0.527824 12906.9 1 6 CACCTG TATATCGATTATTTT + +4 cisbp__M4635-MTA1-like-Stat92E 7 0.527824 12906.9 1 6 CACCTG GAAAATGAAACTGAA + +4 cisbp__M6115 8 0.527824 12906.9 1 6 CACCTG CATGTCTGGGCATGT + +4 cisbp__M6494-Stat92E 8 0.527824 12906.9 1 6 CACCTG GGAAAACGAAACTGA + +4 hocomoco__NFIA_HUMAN.H11MO.0.C-C15-Nf1-NfI 9 0.527824 12906.9 1 6 CACCTG TTGGCACGGTGCCAA + +4 taipale_cyt_meth__MEF2B_TGTTACCATATNNGG_FL_repr-Mef2 3 0.527824 12906.9 1 6 CACCTG TGTTACCATATTTGG + +4 transfac_pro__M08932-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 4 0.527824 12906.9 1 6 CACCTG TGATGACGTCATCGC + +4 transfac_pro__M09132 6 0.527824 12906.9 1 6 CACCTG TTTTTTTACTTTTTG + +4 transfac_pro__M09272 3 0.527824 12906.9 1 6 CACCTG ACTTTCCTTTTTTGG + +4 transfac_pro__M09473 6 0.527824 12906.9 1 6 CACCTG AACGTTGACTTTTTT + +4 transfac_pro__M09491-Awh 8 0.527824 12906.9 1 6 CACCTG TAATTAATTAAGTTT + +4 transfac_pro__M09518-Atf6-CrebA-Xbp1 8 0.527824 12906.9 1 6 CACCTG TGCCACGTCAGCATC + +4 transfac_public__M00102-ct 9 0.527824 12906.9 1 6 CACCTG TATATCGATTATTTT + +4 transfac_public__M00105-ct 0 0.527824 12906.9 1 6 CACCTG CACCAATATGTATGG + +4 c2h2_zfs__M4131-gl 9 0.527824 12906.9 1 6 CACCTG GAAGCCATACAAATG - +4 cisbp__M4729-Adf1 0 0.527824 12906.9 1 6 CACCTG CACCGGCAGAGAAAA - +4 cisbp__M5425-aop-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Taf1 0 0.527824 12906.9 1 6 CACCTG CACTTCCGCTTCCGG - +4 cisbp__M5778-CG9727-Rfx 3 0.527824 12906.9 1 6 CACCTG CGTTGCCTAGCAACG - +4 cisbp__M6123-btd-CG7368-CoRest-ct-CTCF-Spps-sr 9 0.527824 12906.9 1 6 CACCTG CCCCTCCCCCACCCC - +4 neph__UW.Motif.0526 8 0.527824 12906.9 1 6 CACCTG GTATCTGTTTTCTTT - +4 taipale_tf_pairs__GCM1_ETV4_RTGCGGGCGGAAGTR_CAP-Ets96B-gcm-gcm2 0 0.527824 12906.9 1 6 CACCTG CACTTCCGCCCGCAT - +4 transfac_pro__M02016-btd-EcR-eg-HDAC1-Hnf4-kni-knrl-nej-Spps-svp-usp 4 0.527824 12906.9 1 6 CACCTG AATTGAACTTTGGCC - +4 transfac_pro__M09294-Myb 8 0.527824 12906.9 1 6 CACCTG CCAACGGTTATATTT - +4 transfac_pro__M09333 0 0.527824 12906.9 1 6 CACCTG AATCTTATCCAAAAT - +4 transfac_pro__M09519-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 8 0.527824 12906.9 1 6 CACCTG GATGACGTCATCATT - +4 transfac_pro__M00733-Dad-Mad-Med-Smox 10 0.527824 12906.9 1 5 CACCTG GTGGGGCAGCCAGCT + +4 cisbp__M3524-Topors 8 0.528182 12915.6 1 6 CACCTG TCCCAAAGTAGCTGGGA + +4 cisbp__M5905-sd 3 0.528182 12915.6 1 6 CACCTG ACATTCCTGACATTCCA + +4 taipale__TEAD1_full_RCATTCCNNRCATWCCN_repr-sd 3 0.528182 12915.6 1 6 CACCTG ACATTCCTGACATTCCA + +4 taipale_tf_pairs__TEAD4_HOXA2_RCATTCNNNNNNCATTA_CAP-pb-sd 3 0.528182 12915.6 1 6 CACCTG ACATTCCAAACTCATTA + +4 transfac_pro__M02815 7 0.528182 12915.6 1 6 CACCTG ACTTAGTTAACTAAAAA + +4 hocomoco__PROX1_HUMAN.H11MO.0.D-pros 7 0.528182 12915.6 1 6 CACCTG CCCAACCCGCCTTACCC - +4 transfac_pro__M01463-oc-Ptx1 9 0.528182 12915.6 1 6 CACCTG GATAATTAATCCCTTCC - +4 transfac_pro__M02817-pan 2 0.528182 12915.6 1 6 CACCTG TATTCCTTTGATCTATA - +4 transfac_pro__M05603-ci-lmd-sug 4 0.528182 12915.6 1 6 CACCTG GGGCCACCCTACTTTAA - +4 cisbp__M4462-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-nej-pnt-RpII215-Sin3A-Taf1 0 0.529715 12953.1 1 6 CACCTG CGCCGGAAGTG + +4 cisbp__M6495-aop-Stat92E 1 0.529715 12953.1 1 6 CACCTG CTTCCTGGAAG + +4 flyfactorsurvey__vri_SANGER_5_FBgn0016076-CG7786-Pdp1-REPTOR-BP-gt-hng1-vri 2 0.529715 12953.1 1 6 CACCTG ATTACGTAACA + +4 jaspar__MA0144.2-Stat92E 0 0.529715 12953.1 1 6 CACCTG CTTCTGGGAAA + +4 predrem__nrMotif2064 4 0.529715 12953.1 1 6 CACCTG CCCCCACCGCC + +4 taipale_cyt_meth__KLF2_NRCCACRCCCN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 5 0.529715 12953.1 1 6 CACCTG CACCACGCCCA + +4 transfac_pro__M02022-cnc-maf-S 5 0.529715 12953.1 1 6 CACCTG TGACTCAGCAC + +4 cisbp__M0393-sug 1 0.529715 12953.1 1 6 CACCTG AGACCCCCCAC - +4 cisbp__M2092 5 0.529715 12953.1 1 6 CACCTG CATTTCTGCTG - +4 cisbp__M5272-CG7786-gt-hng1-Pdp1-REPTOR-BP-vri 2 0.529715 12953.1 1 6 CACCTG ATTACGTAACA - +4 cisbp__M5379-aop-Eip74EF-Ets21C-Ets96B-Ets98B-Hr78 0 0.529715 12953.1 1 6 CACCTG TACTTCCGGGT - +4 cisbp__M6004-aop-Eip74EF-Ets96B-Ets98B-Hr78 3 0.529715 12953.1 1 6 CACCTG TACTTCCGGGT - +4 predrem__nrMotif2374 5 0.529715 12953.1 1 6 CACCTG CCCGGGCCCTG - +4 scertf__pachkov.CUP2 5 0.529715 12953.1 1 6 CACCTG CATTTTTGCTG - +4 taipale_cyt_meth__ELK1_NACCGGAAGTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 3 0.529715 12953.1 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__FEV_NACMGGAAGTN_eDBD_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.529715 12953.1 1 6 CACCTG CACTTCCGGTC - +4 hocomoco__TF7L1_MOUSE.H11MO.0.A-pan -1 0.529715 12953.1 1 5 CACCTG GCCTTTGATGT + +4 tiffin__TIFDMEM0000001 6 0.529715 12953.1 1 5 CACCTG CCAAAAAACTT + +4 hocomoco__ATF1_HUMAN.H11MO.0.B-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-kay 6 0.529715 12953.1 1 5 CACCTG TGACGTCACCG - +4 cisbp__M6369-CG12018-Dif-dl-Rel-shn 7 0.529715 12953.1 1 4 CACCTG GGGGAATCCCC - +4 tiffin__TIFDMEM0000103 7 0.529715 12953.1 1 4 CACCTG TTAAAATTAAC - +4 transfac_public__M00072-gem -3 0.529715 12953.1 1 3 CACCTG CTGGGTTGTGC - +4 cisbp__M0807 1 0.531712 13002 1 6 CACCTG AGATCTAT + +4 cisbp__M0956-Gsc-oc-Ptx1 2 0.531712 13002 1 6 CACCTG TTAATCCC + +4 cisbp__M2229 0 0.531712 13002 1 6 CACCTG TTCCGGAG + +4 cisbp__M4269 0 0.531712 13002 1 6 CACCTG TTCCGGAG + +4 jaspar__MA0999.1 1 0.531712 13002 1 6 CACCTG CCGCCGCC + +4 swissregulon__hs__JUN.p2-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-cnc-crc-kay 1 0.531712 13002 1 6 CACCTG TGACGTCA + +4 taipale_cyt_meth__GSC2_YTAATCCN_eDBD_meth_repr-Gsc-oc 2 0.531712 13002 1 6 CACCTG CTAATCCC + +4 taipale_cyt_meth__ISL1_SCACTTAN_FL-tup 1 0.531712 13002 1 6 CACCTG GCACTTAA + +4 taipale_cyt_meth__ISL1_SCACTTAN_eDBD-tup 1 0.531712 13002 1 6 CACCTG GCACTTAA + +4 taipale_cyt_meth__ISX_CTCGTTAN_eDBD_meth-CG34367-ind-Lim3-unpg-Vsx1-Vsx2 0 0.531712 13002 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__LHX5_NTCGTTAN_FL_meth-bap-bsh-Dr-ind-Lim1-unpg 0 0.531712 13002 1 6 CACCTG CTCGTTAA + +4 cisbp__M0400 1 0.531712 13002 1 6 CACCTG ACTCCCCC - +4 cisbp__M0522-lmd 0 0.531712 13002 1 6 CACCTG CCCCCCAC - +4 cisbp__M0623 1 0.531712 13002 1 6 CACCTG ACAAAATT - +4 elemento__TCCAGCTC 0 0.531712 13002 1 6 CACCTG GAGCTGGA - +4 hdpi__LUZP1-CG10915 1 0.531712 13002 1 6 CACCTG CTTCCCCC - +4 hdpi__LUZP2 0 0.531712 13002 1 6 CACCTG GATTTTCA - +4 jaspar__MA0424.1 0 0.531712 13002 1 6 CACCTG TTCCGGAG - +4 predrem__nrMotif2068 0 0.531712 13002 1 6 CACCTG TCCCTTCA - +4 predrem__nrMotif626 2 0.531712 13002 1 6 CACCTG GAGACCCC - +4 swissregulon__sacCer__ARO80 1 0.531712 13002 1 6 CACCTG TTGCCGAG - +4 transfac_pro__M01634 0 0.531712 13002 1 6 CACCTG TTCCGGAG - +4 c2h2_zfs__M0393 -1 0.531712 13002 1 5 CACCTG ACCGTTAT + +4 cisbp__M5907-sd -1 0.531712 13002 1 5 CACCTG ACATTCCA + +4 taipale__TEAD3_DBD_RMATWCCA-sd -1 0.531712 13002 1 5 CACCTG ACATTCCA + +4 cisbp__M0664 -1 0.531712 13002 1 5 CACCTG ACTTTTTC - +4 flyfactorsurvey__Cf2-II_FlyReg_FBgn0000286-Cf2 3 0.531712 13002 1 5 CACCTG TTATACAC - +4 hocomoco__NKX22_HUMAN.H11MO.0.D -1 0.531712 13002 1 5 CACCTG GCCACTCA - +4 transfac_pro__M00649 -1 0.531712 13002 1 5 CACCTG CCCTCCCC - +4 cisbp__M0438-Aef1 4 0.531712 13002 1 4 CACCTG GGCGTACG + +4 flyfactorsurvey__srp_SANGER_5_FBgn0003507-CoRest-GATAd-GATAe-HLH3B-Jra-Snr1-brm-ebi-grn-pnr-srp -2 0.531712 13002 1 4 CACCTG CCTTATCA + +4 predrem__nrMotif873 -2 0.531712 13002 1 4 CACCTG CCAGACAA + +4 stark__GATNTCAT 4 0.531712 13002 1 4 CACCTG ATGAAATC - +4 transfac_pro__M07484 4 0.531712 13002 1 4 CACCTG CATGCAAC - +4 yetfasco__YLR176C_496-CG9727-Rfx 4 0.531712 13002 1 4 CACCTG TAGCAACC - +4 jaspar__MA1066.1 5 0.531712 13002 1 3 CACCTG GGGCCCAC + +4 predrem__nrMotif2447 5 0.531712 13002 1 3 CACCTG CCCATGAC + +4 transfac_pro__M01306 5 0.531712 13002 1 3 CACCTG ATTCCGAC + +4 cisbp__M0618 1 0.532365 13017.9 1 6 CACCTG TTAGCGG + +4 cisbp__M0937-Optix-Six4-so 1 0.532365 13017.9 1 6 CACCTG TGATACC + +4 cisbp__M1953 1 0.532365 13017.9 1 6 CACCTG ACAACAC + +4 predrem__nrMotif2660 1 0.532365 13017.9 1 6 CACCTG ACTACTG + +4 cisbp__M1540-Cnot4 1 0.532365 13017.9 1 6 CACCTG TTATATA - +4 predrem__nrMotif1502 2 0.532365 13017.9 1 5 CACCTG GACAGCC + +4 predrem__nrMotif2343 2 0.532365 13017.9 1 5 CACCTG AACAGCA + +4 hdpi__SF3B1-Sf3b1 -1 0.532365 13017.9 1 5 CACCTG ATCTGGC - +4 swissregulon__sacCer__PDR8 -1 0.532365 13017.9 1 5 CACCTG ATCTCCG - +4 transfac_pro__M01665 2 0.532365 13017.9 1 5 CACCTG TGAAACT - +4 transfac_pro__M05114 3 0.532365 13017.9 1 4 CACCTG TCACATC + +4 predrem__nrMotif2474 -2 0.532365 13017.9 1 4 CACCTG TCTTGAA - +4 predrem__nrMotif1198 -3 0.532365 13017.9 1 3 CACCTG CTGATGT + +4 predrem__nrMotif30 -3 0.532365 13017.9 1 3 CACCTG CTGTGGG + +4 predrem__nrMotif372 -3 0.532365 13017.9 1 3 CACCTG CTGTAAA + +4 predrem__nrMotif545 -3 0.532365 13017.9 1 3 CACCTG CTGCAGA + +4 predrem__nrMotif884 -3 0.532365 13017.9 1 3 CACCTG CTGATTT + +4 transfac_pro__M03891-scro -3 0.532365 13017.9 1 3 CACCTG CTTGAGT + +4 cisbp__M3191-en-inv 4 0.532365 13017.9 1 3 CACCTG CAATTAC - +4 hdpi__FGF19 -3 0.532365 13017.9 1 3 CACCTG CTGCCAC - +4 predrem__nrMotif22 -3 0.532365 13017.9 1 3 CACCTG CTGCTTC - +4 predrem__nrMotif2455 -3 0.532365 13017.9 1 3 CACCTG CTGCTAA - +4 predrem__nrMotif2606 -3 0.532365 13017.9 1 3 CACCTG CTGTAGT - +4 predrem__nrMotif36 -3 0.532365 13017.9 1 3 CACCTG CTGGAAT - +4 predrem__nrMotif619 -3 0.532365 13017.9 1 3 CACCTG CTGGAGT - +4 cisbp__M4815-CG12236 7 0.533033 13034.3 1 6 CACCTG ACGAATGAACCCCC + +4 neph__UW.Motif.0575 6 0.533033 13034.3 1 6 CACCTG TGCACAGACATGCA + +4 transfac_public__M00454-htk 8 0.533033 13034.3 1 6 CACCTG AACCACAATACCAA + +4 cisbp__M3312-GATAe-grn-pnr 5 0.533033 13034.3 1 6 CACCTG ACCCCTATCTATAC - +4 cisbp__M3574-htk 8 0.533033 13034.3 1 6 CACCTG AACCACAATACCAA - +4 flyfactorsurvey__CG12236_SANGER_10_FBgn0029822-CG12236 7 0.533033 13034.3 1 6 CACCTG ACGAATGAACTCCC - +4 neph__UW.Motif.0223 4 0.533033 13034.3 1 6 CACCTG CACAGCCCTGGCTT - +4 neph__UW.Motif.0338 4 0.533033 13034.3 1 6 CACCTG AAACAGCCTTTTTT - +4 neph__UW.Motif.0407 7 0.533033 13034.3 1 6 CACCTG TGGGCTGGGTCTGC - +4 neph__UW.Motif.0446 8 0.533033 13034.3 1 6 CACCTG TTTTGAAAAATCTG - +4 taipale_cyt_meth__POU3F1_NTAATKAKATGCRN_eDBD_repr-pdm3-vvl 3 0.533033 13034.3 1 6 CACCTG ATGCATCTCATTAT - +4 taipale_tf_pairs__ETV5_DRGX_RSMGGAWGYAATTA_CAP-CG11294-Drgx-Ets96B 7 0.533033 13034.3 1 6 CACCTG TAATTACTTCCGGT - +4 taipale_tf_pairs__HOXB2_ELK1_RSCGGAAGTMRTTA_CAP-pb 4 0.533033 13034.3 1 6 CACCTG TAATGACTTCCGGT - +4 transfac_pro__M02912-Sox100B 3 0.533033 13034.3 1 6 CACCTG CGTGTCATGAATGT - +4 transfac_pro__M09030 3 0.533033 13034.3 1 6 CACCTG CTCCACCGACAATA - +4 transfac_public__M00126-GATAe-grn-pnr 5 0.533033 13034.3 1 6 CACCTG ACCCCTATCTATAC - +4 transfac_pro__M03872 10 0.533033 13034.3 1 4 CACCTG GTTAATCATTAACC + +4 cisbp__M6545-shn 10 0.533033 13034.3 1 4 CACCTG GGGGTTTCCCTACC - +4 cisbp__M2943-crp 5 0.534423 13068.2 1 6 CACCTG AGAACCAGCTGCGGTCAG + +4 jaspar__MA0140.2-GATAe-HLH3B-Stat92E-grn-pnr-srp 2 0.534423 13068.2 1 6 CACCTG CTTATCTGTGAGGAGCAG + +4 taipale_cyt_meth__NHLH2_NKGNMKCAGCTGCGYCMN_FL_meth_repr-HLH4C 6 0.534423 13068.2 1 6 CACCTG GGGGAGCAGCTGCGTCCC + +4 taipale_tf_pairs__ERF_ETV7_NSMGGACGGAYNTCCKSN_CAP_repr-aop-Ets21C 11 0.534423 13068.2 1 6 CACCTG ACCGGACGGATGTCCGGG + +4 transfac_pro__M05766 -1 0.534423 13068.2 1 5 CACCTG ACCCTATTTATTCAACTC - +4 cisbp__M6150-tgo 6 0.534544 13071.2 1 6 CACCTG GCCTCCCACGCC + +4 cisbp__M6506-pan 0 0.534544 13071.2 1 6 CACCTG GCGCTTTGTTCT + +4 flyfactorsurvey__CG12768_SANGER_5_FBgn0037206-CG12768 3 0.534544 13071.2 1 6 CACCTG TTTTACCAACAA + +4 hocomoco__FOXA2_HUMAN.H11MO.0.A-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr-slp2 4 0.534544 13071.2 1 6 CACCTG TGTTTACTTAGC + +4 taipale_cyt_meth__MESP2_NAMCATATGKYN_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.534544 13071.2 1 6 CACCTG CAACATATGTCG + +4 taipale_cyt_meth__MSGN1_NRCCAWWTGKYN_eDBD_meth-amos-da-dimm-Fer3-HLH54F-Oli-tap 0 0.534544 13071.2 1 6 CACCTG CACCATATGTTA + +4 transfac_pro__M01588-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 5 0.534544 13071.2 1 6 CACCTG GCCACGCCCAGC + +4 transfac_pro__M03550 0 0.534544 13071.2 1 6 CACCTG AACATTTTAACT + +4 transfac_pro__M04719-btd-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-Spps-svp-usp 2 0.534544 13071.2 1 6 CACCTG TGGACTTTGACC + +4 transfac_pro__M06087 2 0.534544 13071.2 1 6 CACCTG TATTCCTAAAGA + +4 transfac_pro__M06584 0 0.534544 13071.2 1 6 CACCTG GGCCTCTAGAAG + +4 transfac_pro__M07397-btd-CTCF-Spps 0 0.534544 13071.2 1 6 CACCTG CCCCTCCCCCCC + +4 transfac_pro__M07659-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.534544 13071.2 1 6 CACCTG TGGCACGTGCCA + +4 cisbp__M1854-dl 6 0.534544 13071.2 1 6 CACCTG CGGAAAAACCCC - +4 cisbp__M6268-Hand 1 0.534544 13071.2 1 6 CACCTG GCGTCTGGCATT - +4 hocomoco__ARNT2_HUMAN.H11MO.0.D-tgo 6 0.534544 13071.2 1 6 CACCTG GCCTCCCACGCC - +4 hocomoco__GCR_HUMAN.H11MO.1.A 6 0.534544 13071.2 1 6 CACCTG ATTCTGTTCTTT - +4 jaspar__MA0022.1-dl 6 0.534544 13071.2 1 6 CACCTG GGGAAAAACCCC - +4 taipale_cyt_meth__CREB5_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.534544 13071.2 1 6 CACCTG GATGACATCATC - +4 taipale_cyt_meth__DBP_NRTTAYGTAAYN_FL_meth-CG7786-gt-hng1-Pdp1-vri 3 0.534544 13071.2 1 6 CACCTG CGTTACGTAACG - +4 taipale_cyt_meth__DBP_NRTTAYGTAAYN_eDBD_meth-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.534544 13071.2 1 6 CACCTG CGTTACATAACA - +4 taipale_cyt_meth__ELF5_NAMCCGGAAGTN_FL-aop-Eip74EF-Ets21C-Ets96B-Ets97D-Ets98B-Hr78 0 0.534544 13071.2 1 6 CACCTG CACTTCCGGGTC - +4 taipale_cyt_meth__HLF_NRTTRYGYAAYN_FL-CG7786-CrebB-gt-hng1-Pdp1-vri 3 0.534544 13071.2 1 6 CACCTG CGTTACGTAACG - +4 taipale_cyt_meth__SPDEF_NAMCAGGATGTN_eDBD_meth-Ets98B 3 0.534544 13071.2 1 6 CACCTG CACATCCTGTTC - +4 transfac_pro__M01187-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-Xbp1 3 0.534544 13071.2 1 6 CACCTG GGTGACGTCATC - +4 transfac_pro__M05957 6 0.534544 13071.2 1 6 CACCTG GCGTCTTACCCC - +4 transfac_pro__M06280 6 0.534544 13071.2 1 6 CACCTG GCAAATTACCAT - +4 transfac_pro__M06483 2 0.534544 13071.2 1 6 CACCTG GCTTCCTCCACA - +4 transfac_pro__M06717 6 0.534544 13071.2 1 6 CACCTG TATCCGGCCCTA - +4 transfac_public__M00302-CG5641-NFAT 4 0.534544 13071.2 1 6 CACCTG ATTTTTCCTCTG - +4 homer__ACTTTCGTTTCT_T1ISRE -1 0.534544 13071.2 1 5 CACCTG ACTTTCGTTTCT + +4 transfac_pro__M03563-CG12018-Dif-dl-Rel 7 0.534544 13071.2 1 5 CACCTG TGGGAAATTCCC - +4 transfac_pro__M05739-CG2120 7 0.534544 13071.2 1 5 CACCTG GCGGATTGAACG - +4 transfac_pro__M05897 7 0.534544 13071.2 1 5 CACCTG GAATATTAACCG - +4 transfac_pro__M05936 7 0.534544 13071.2 1 5 CACCTG TCCCCGGCAACA - +4 transfac_pro__M06042 7 0.534544 13071.2 1 5 CACCTG TCGTTCAAAACT - +4 transfac_pro__M06083 7 0.534544 13071.2 1 5 CACCTG TGTTATGCCCCG - +4 transfac_pro__M06262 7 0.534544 13071.2 1 5 CACCTG TCTGATTCCCCA - +4 transfac_pro__M06592 7 0.534544 13071.2 1 5 CACCTG GCATCCCAATCT - +4 transfac_pro__M06666 7 0.534544 13071.2 1 5 CACCTG TCGGCACAACCA - +4 transfac_pro__M01122-btd-Spps 8 0.534544 13071.2 1 4 CACCTG CGCCCCCCCCCC + +4 hdpi__RUVBL1-pont -2 0.534544 13071.2 1 4 CACCTG CTTAAATGAAAA - +4 transfac_pro__M05430-peb 8 0.534544 13071.2 1 4 CACCTG TGATTGGCCACA - +4 cisbp__M0306 4 0.535446 13093.3 1 6 CACCTG CAATTACGTAAAT + +4 cisbp__M4317 7 0.535446 13093.3 1 6 CACCTG TCCATTAAGCCGA + +4 hocomoco__ETS2_HUMAN.H11MO.0.B 5 0.535446 13093.3 1 6 CACCTG TCCTCTTCCTTCC + +4 predrem__nrMotif1742 6 0.535446 13093.3 1 6 CACCTG CCCCCCAACCCGC + +4 taipale_cyt_meth__BBX_TGAWCNNNGWTCA_eDBD_meth_repr-bbx 2 0.535446 13093.3 1 6 CACCTG TGAACGTTGTTCA + +4 transfac_public__M00085 6 0.535446 13093.3 1 6 CACCTG CGGCTCTATCATC + +4 cisbp__M5958-CG13775 7 0.535446 13093.3 1 6 CACCTG CTATCGCGACATA - +4 cisbp__M6252-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-pnt-RpII215-Sin3A-Taf1 1 0.535446 13093.3 1 6 CACCTG CCACTTCCGGTTC - +4 hocomoco__SP5_MOUSE.H11MO.1.C-Nf-YB-Spps-btd-kay-klu-sr 0 0.535446 13093.3 1 6 CACCTG CTCCTCCCCCTCC - +4 neph__UW.Motif.0478 1 0.535446 13093.3 1 6 CACCTG GCAGCTCTGTCTG - +4 taipale_tf_pairs__ETV2_FOXO6_RCCGGATGTTKWN_CAP-foxo-pnt 3 0.535446 13093.3 1 6 CACCTG GAAAACATCCGGT - +4 yetfasco__YJL089W_2067 7 0.535446 13093.3 1 6 CACCTG TCCATTAAGCCGA - +4 cisbp__M5668-Dif-dl-Rel 8 0.535446 13093.3 1 5 CACCTG AGGGGATTCCCCT + +4 transfac_pro__M07310 -1 0.535446 13093.3 1 5 CACCTG ACCGCGCCGCCCC + +4 taipale__NFKB1_DBD_NGGGGAWTCCCCN_repr-Dif-dl-Rel 8 0.535446 13093.3 1 5 CACCTG AGGGGATTCCCCT - +4 taipale__NFKB2_DBD_NGGGGAWTCCCCN-Dif-dl-Rel-shn 8 0.535446 13093.3 1 5 CACCTG AGGGGAATCCCCT - +4 hocomoco__ZBTB6_HUMAN.H11MO.0.C 9 0.535446 13093.3 1 4 CACCTG CGGCTCCAGCACC - +4 tfdimers__MD00477-TfAP-2 6 0.535633 13097.8 1 6 CACCTG CCCCTCCCCATCTGCCTCGGGCTCTCC + +4 transfac_pro__M01855-ss 0 0.53586 13103.4 1 6 CACCTG TGCGTG - +4 cisbp__M2399 1 0.53586 13103.4 1 5 CACCTG ACCCCA - +4 hdpi__ZNF766 -2 0.53586 13103.4 1 4 CACCTG CCGCTT - +4 cisbp__M2137 -3 0.53586 13103.4 1 3 CACCTG CTGTGG + +4 factorbook__MEIS1 -3 0.53586 13103.4 1 3 CACCTG CTGTCA + +4 jaspar__MA0332.1 -3 0.53586 13103.4 1 3 CACCTG CTGTGG + +4 fantom__motif18_CATCAG -3 0.53586 13103.4 1 3 CACCTG CTGATG - +4 hdpi__TAF9-e(y)1 1 0.536647 13122.6 1 4 CACCTG CCACG - +4 cisbp__M0579 0 0.537006 13131.4 1 6 CACCTG AACTTGCACC + +4 jaspar__MA0998.1-Taf1-lid-pho-phol 4 0.537006 13131.4 1 6 CACCTG CCGCCGCCAT + +4 neph__UW.Motif.0011 0 0.537006 13131.4 1 6 CACCTG CACACACACA + +4 predrem__nrMotif128 3 0.537006 13131.4 1 6 CACCTG TGAATCCTTT + +4 predrem__nrMotif2359 0 0.537006 13131.4 1 6 CACCTG TTCCAATAAA + +4 predrem__nrMotif290 2 0.537006 13131.4 1 6 CACCTG CTCCCCTCCC + +4 predrem__nrMotif49 2 0.537006 13131.4 1 6 CACCTG CCCAGCTCCT + +4 predrem__nrMotif572 3 0.537006 13131.4 1 6 CACCTG CCCCGCCTGC + +4 predrem__nrMotif805 2 0.537006 13131.4 1 6 CACCTG GGGCCCTGGG + +4 taipale_cyt_meth__OSR2_NGCTACYGTN_eDBD-bowl-drm-odd-sob 3 0.537006 13131.4 1 6 CACCTG TGCTACTGTT + +4 transfac_pro__M00694-CrebB 2 0.537006 13131.4 1 6 CACCTG GTTACGTCAC + +4 transfac_pro__M01848 4 0.537006 13131.4 1 6 CACCTG GTGGGACCCA + +4 transfac_pro__M03192 1 0.537006 13131.4 1 6 CACCTG CTACCGAGAC + +4 transfac_pro__M05106 1 0.537006 13131.4 1 6 CACCTG ACACCGACCA + +4 transfac_pro__M07568-Hsf 2 0.537006 13131.4 1 6 CACCTG GGAACGTTCC + +4 yetfasco__YHR124W_1464 3 0.537006 13131.4 1 6 CACCTG CGACACAAAA + +4 cisbp__M0451 2 0.537006 13131.4 1 6 CACCTG TAAATCACGG - +4 cisbp__M1354-Myb 0 0.537006 13131.4 1 6 CACCTG TAACGGTTAT - +4 cisbp__M1649 4 0.537006 13131.4 1 6 CACCTG GTGGGCCCCA - +4 cisbp__M1849-Cf2 1 0.537006 13131.4 1 6 CACCTG GTATATATAC - +4 cisbp__M1871-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 4 0.537006 13131.4 1 6 CACCTG GCCCCACCCA - +4 cisbp__M4302 3 0.537006 13131.4 1 6 CACCTG CGACACAAAA - +4 flyfactorsurvey__Hr46_FlyReg_FBgn0000448-Hr3 1 0.537006 13131.4 1 6 CACCTG TGACCCAATT - +4 hocomoco__KLF4_HUMAN.H11MO.0.A-CG3065-CG42741-Klf15-Spps-btd-cbt-dar1-hkb-luna 4 0.537006 13131.4 1 6 CACCTG GCCACACCCT - +4 homer__AACCGGAAGT_ETV1-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-dl-pnt 2 0.537006 13131.4 1 6 CACCTG ACTTCCGGTT - +4 jaspar__MA0015.1-Cf2 1 0.537006 13131.4 1 6 CACCTG GTATATATAC - +4 neph__UW.Motif.0303 3 0.537006 13131.4 1 6 CACCTG GCGGGGCTTC - +4 predrem__nrMotif2369 2 0.537006 13131.4 1 6 CACCTG CCTACCCCCA - +4 predrem__nrMotif29 0 0.537006 13131.4 1 6 CACCTG CCCCTCTTCC - +4 swissregulon__hs__KLF4.p3-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-hkb-luna 4 0.537006 13131.4 1 6 CACCTG GCCCCACCCA - +4 swissregulon__sacCer__YRM1 4 0.537006 13131.4 1 6 CACCTG TTATTTCCGT - +4 transfac_pro__M02060-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.537006 13131.4 1 6 CACCTG TACTTCCGGT - +4 cisbp__M0433 -1 0.537006 13131.4 1 5 CACCTG ATCTAGAACA + +4 cisbp__M1341 5 0.537006 13131.4 1 5 CACCTG GGGGGAATCT + +4 predrem__nrMotif1168 5 0.537006 13131.4 1 5 CACCTG CCACAGCCCT + +4 cisbp__M0424-achi-esg-hth-sna-vis-wor -1 0.537006 13131.4 1 5 CACCTG AGCTGTCAAA - +4 homer__CNGTCCTCCC_Znf263 5 0.537006 13131.4 1 5 CACCTG GGGAGGACTG - +4 predrem__nrMotif2435 5 0.537006 13131.4 1 5 CACCTG TGCTGAATCA - +4 stark__RAGTKCAANG 5 0.537006 13131.4 1 5 CACCTG CATTGAACTC - +4 taipale_cyt_meth__SIX4_NCGTATCATN_eDBD_meth-Optix-Six4-so 5 0.537006 13131.4 1 5 CACCTG AATGATACGG - +4 transfac_public__M00051-Rel 6 0.537006 13131.4 1 4 CACCTG GGGGATTCCC + +4 predrem__nrMotif978 6 0.537006 13131.4 1 4 CACCTG AGAAAATACT - +4 cisbp__M1912-Su(H) 7 0.537845 13151.9 1 6 CACCTG CTGTGGGAAACGAGAT + +4 neph__UW.Motif.0149 9 0.537845 13151.9 1 6 CACCTG CCAGATTTTTTCATTC + +4 neph__UW.Motif.0574 9 0.537845 13151.9 1 6 CACCTG GCTGCCCGCTGCCAGC + +4 neph__UW.Motif.0679 8 0.537845 13151.9 1 6 CACCTG TGACTGTGTTTCAGAA + +4 taipale_cyt_meth__ETV7_NMGGAARNNYTTCCKN_FL_meth-aop-Ets96B 10 0.537845 13151.9 1 6 CACCTG CAGGAAGTACTTCCTG + +4 taipale_tf_pairs__TFAP4_FLI1_ACCGGAAACAGCTGNN_HT-crp 8 0.537845 13151.9 1 6 CACCTG ACCGGAAACAGCTGAT + +4 transfac_pro__M02876-Jra-kay-Mef2-nej 10 0.537845 13151.9 1 6 CACCTG ATTGATGAGTCACCAA + +4 transfac_pro__M09383 1 0.537845 13151.9 1 6 CACCTG TAACTTGGGGCGCAAG + +4 cisbp__M2549-Dfd 8 0.537845 13151.9 1 6 CACCTG CAAGGAATTACTTGGT - +4 homer__CGGTTGCCATGGCAAC_RFX-CG5846-CG9727-Max-Rfx-SREBP 10 0.537845 13151.9 1 6 CACCTG GTTGCCATGGCAACCG - +4 taipale_cyt_meth__FOXA1_NMYTAWGTAAACAAAN_FL-bin-croc-fd59A-fkh-FoxP-nej 7 0.537845 13151.9 1 6 CACCTG GTTTGTTTACTTAAGG - +4 transfac_pro__M01745 5 0.537845 13151.9 1 6 CACCTG GGTAGCATATGCTATC - +4 transfac_public__M00078-ham 1 0.537845 13151.9 1 6 CACCTG TTATCTTATCTTATCT - +4 hocomoco__ZSC22_HUMAN.H11MO.0.C -2 0.537845 13151.9 1 4 CACCTG CCTCCTCCCTCAGACC - +4 cisbp__M0721-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 3 0.538159 13159.6 1 6 CACCTG GTAAACAAA + +4 cisbp__M0970-bcd-Gsc-oc-Ptx1 2 0.538159 13159.6 1 6 CACCTG TTAATCCCC + +4 cisbp__M1567 2 0.538159 13159.6 1 6 CACCTG TGTACGACA + +4 cisbp__M2153 0 0.538159 13159.6 1 6 CACCTG TATCTCCGA + +4 jaspar__MA0922.1-CG7786-Pdp1-gt-vri 2 0.538159 13159.6 1 6 CACCTG ATTACGTAA + +4 predrem__nrMotif118 3 0.538159 13159.6 1 6 CACCTG TTTTCCCTC + +4 predrem__nrMotif1550 3 0.538159 13159.6 1 6 CACCTG AGAAACCAC + +4 predrem__nrMotif1901 1 0.538159 13159.6 1 6 CACCTG TTGCCTCAT + +4 predrem__nrMotif2482 1 0.538159 13159.6 1 6 CACCTG CTAGCTCAG + +4 scertf__foat.FKH1-FoxK-FoxP-fd59A-fkh-foxo-slp2 3 0.538159 13159.6 1 6 CACCTG GTAAACAAG + +4 transfac_pro__M00792-Mad-Med-Smox 1 0.538159 13159.6 1 6 CACCTG AGACACCCT + +4 transfac_pro__M06797 3 0.538159 13159.6 1 6 CACCTG TTATACCCC + +4 cisbp__M0147 3 0.538159 13159.6 1 6 CACCTG GCCGACAAA - +4 cisbp__M1403 2 0.538159 13159.6 1 6 CACCTG ATTACTTAA - +4 jaspar__MA0348.1 0 0.538159 13159.6 1 6 CACCTG TATCTCCGA - +4 jaspar__MA0944.1 3 0.538159 13159.6 1 6 CACCTG GCCGACAAA - +4 predrem__nrMotif1905 1 0.538159 13159.6 1 6 CACCTG ACACATGGA - +4 predrem__nrMotif37 2 0.538159 13159.6 1 6 CACCTG CCTCCCTCC - +4 predrem__nrMotif398 0 0.538159 13159.6 1 6 CACCTG CTGCTCAGA - +4 transfac_pro__M00720 3 0.538159 13159.6 1 6 CACCTG CCCACCCTC - +4 transfac_pro__M01914 0 0.538159 13159.6 1 6 CACCTG TATCTCCGA - +4 transfac_pro__M07733-CycT-GATAd-GATAe-grn-pnr-srp 3 0.538159 13159.6 1 6 CACCTG CCTTATCAC - +4 cisbp__M4950-aop-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.538159 13159.6 1 5 CACCTG ACCGGAAAT + +4 flyfactorsurvey__Ets98B_SANGER_10_FBgn0005659-Ets98B -1 0.538159 13159.6 1 5 CACCTG ACCCGGATC + +4 neph__UW.Motif.0009 -1 0.538159 13159.6 1 5 CACCTG CCCCTCCCC + +4 predrem__nrMotif1397 -1 0.538159 13159.6 1 5 CACCTG TTCTCAGAA + +4 predrem__nrMotif1467 -1 0.538159 13159.6 1 5 CACCTG TTCTGCTCA + +4 predrem__nrMotif2312 4 0.538159 13159.6 1 5 CACCTG TCTATCCCA + +4 predrem__nrMotif264 4 0.538159 13159.6 1 5 CACCTG TCAGTGCCT + +4 predrem__nrMotif816 -1 0.538159 13159.6 1 5 CACCTG ACTGGGACA + +4 transfac_pro__M04711-sv -1 0.538159 13159.6 1 5 CACCTG ACTTCCTCT + +4 predrem__nrMotif2406 4 0.538159 13159.6 1 5 CACCTG AAATTACTT - +4 predrem__nrMotif678 4 0.538159 13159.6 1 5 CACCTG TTTCTGCCT - +4 transfac_pro__M07059-nub-pdm2-vvl 4 0.538159 13159.6 1 5 CACCTG AATTTGCAT - +4 transfac_public__M00415-zfh1 4 0.538159 13159.6 1 5 CACCTG CTGAAACAG - +4 cisbp__M3433 -2 0.538159 13159.6 1 4 CACCTG CGTAATTGT + +4 predrem__nrMotif2292 5 0.538159 13159.6 1 4 CACCTG ACATCCACA + +4 predrem__nrMotif2295 5 0.538159 13159.6 1 4 CACCTG TGCAACACA + +4 predrem__nrMotif2545 5 0.538159 13159.6 1 4 CACCTG AGAATTACA + +4 transfac_public__M00395 -2 0.538159 13159.6 1 4 CACCTG CGTAATTGT + +4 hocomoco__MEIS1_HUMAN.H11MO.1.B -2 0.538159 13159.6 1 4 CACCTG GCTGTCAGC - +4 predrem__nrMotif1845 -2 0.538159 13159.6 1 4 CACCTG CCTGGCAAA - +4 taipale_cyt_meth__BCL11B_GTGAACRNNNNNNYTACAC_eDBD_meth-CG9650 10 0.539126 13183.2 1 6 CACCTG GTGAACGCTAACGCTACAC + +4 taipale_tf_pairs__TEAD4_DLX2_NRCATTCNNNNNTAATTRN_CAP-sd 0 0.539126 13183.2 1 6 CACCTG CGCATTCCGCGCTAATTGC + +4 cisbp__M5065-CoRest-ct-CTCF-klu-l(3)neo38 1 0.539126 13183.2 1 6 CACCTG ACACGTCCCCCCCCCCCCC - +4 flyfactorsurvey__l_3_neo38_SANGER_2.5_FBgn0086910-CTCF-CoRest-ct-klu-l(3)neo38 1 0.539126 13183.2 1 6 CACCTG ACACGTCCCCCCCCCCCCC - +4 transfac_pro__M06759 1 0.539126 13183.2 1 6 CACCTG TCGCCTGATCATCAGCCCT - +4 tfdimers__MD00103 12 0.539235 13185.9 1 6 CACCTG AATTAAATAATCCACTTAAAACTTTA - +4 tfdimers__MD00583 15 0.539235 13185.9 1 6 CACCTG TTTTTGTTAATTATTCACTTATTTAA - +4 tfdimers__MD00305 8 0.539757 13198.7 1 6 CACCTG TTACTCCTTATCTGTAAAGAACAGACACTT - +4 tfdimers__MD00457-SREBP 7 0.542076 13255.4 1 6 CACCTG CCCCCCCCACCACCCCCCCCCCCCC + +4 cisbp__M2348-bs 2 0.542438 13264.2 1 6 CACCTG ATTACCAAAAATGGAAAGAA + +4 dbcorrdb__GATA2__ENCSR000EWG_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-sd-Sirt6-Snr1-srp-svp 5 0.542438 13264.2 1 6 CACCTG GTCCTTATCTGCCCCCCCCA + +4 dbcorrdb__IRF1__ENCSR000EGK_1__m1-aop-Blimp-1-Dif-dl-ebi-Eip74EF-RpII215-Stat92E 5 0.542438 13264.2 1 6 CACCTG CGCTTCACTTTCGCTTTCGC + +4 dbcorrdb__MXI1__ENCSR000DZI_1__m1-Brf-E2f1-E(z)-Max-Myc-RpII215-Sap30-Usf 9 0.542438 13264.2 1 6 CACCTG CCCCGGAACCACGTGGGCGG + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m3-RpII215 10 0.542438 13264.2 1 6 CACCTG CTGGGTAATGCACCCAGTCA + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m3-RpII215 13 0.542438 13264.2 1 6 CACCTG TGGCATGTGTAGATATCTCA + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m5-RpII215 14 0.542438 13264.2 1 6 CACCTG ATGTGATAGTACCACCCATT + +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m3-egg 2 0.542438 13264.2 1 6 CACCTG TCCGCGTGGTGTTGCTCTGG + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m4-brm 11 0.542438 13264.2 1 6 CACCTG GGACAGAGTCATCACTGCCA + +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m3-SREBP 14 0.542438 13264.2 1 6 CACCTG GAACCACGGTGGAACCTCTT + +4 dbcorrdb__SRF__ENCSR000BLK_1__m4-bs 0 0.542438 13264.2 1 6 CACCTG CGCCTGATCAATCGGCGCCC + +4 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m2-Spt20 6 0.542438 13264.2 1 6 CACCTG CTTTACCGCCGCTTTTTAAA + +4 dbcorrdb__TBP__ENCSR000ECB_1__m4-Tbp 14 0.542438 13264.2 1 6 CACCTG CCCTACCGCGACGCCATCGG + +4 dbcorrdb__eGFP-FOS__ENCSR000DKB_1__m2 1 0.542438 13264.2 1 6 CACCTG TCATCCCCGGGGCAGGGGGA + +4 jaspar__MA0555.1-bs 2 0.542438 13264.2 1 6 CACCTG ATTACCAAAAAAGGAAAGAA + +4 taipale_cyt_meth__ZNF787_RATGCMNNNNNNNTGCCTCR_FL_repr-zfh1 4 0.542438 13264.2 1 6 CACCTG GATGCACCTACCGTGCCTCG + +4 dbcorrdb__CEBPD__ENCSR000BQJ_1__m1-CG7786-CrebB-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 13 0.542438 13264.2 1 6 CACCTG GCGGCGATTGCGCAACCGCC - +4 dbcorrdb__GTF2F1__ENCSR000ECZ_1__m3-TfIIFalpha 4 0.542438 13264.2 1 6 CACCTG AAAACACTTCCGCCCTGTGG - +4 dbcorrdb__NFIC__ENCSR000BQX_1__m2-HDAC1-Hnf4-nej-pan-svp-usp 4 0.542438 13264.2 1 6 CACCTG AAATGGACTTTGATCTTTTT - +4 dbcorrdb__REST__ENCSR000BOZ_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 2 0.542438 13264.2 1 6 CACCTG GGGCGCTGTCCATGGTGCTG - +4 dbcorrdb__ZBTB7A__ENCSR000BQA_1__m1-Brf-brm-SREBP-vtd 14 0.542438 13264.2 1 6 CACCTG GCCCCGGAGACCCCTGCCCG - +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m1-egg 13 0.542438 13264.2 1 6 CACCTG ATCAGAGAACTCATACTGGA - +4 taipale_cyt_meth__FOXA3_NWNWGTMAATATTKRYNYWN_FL_meth-croc-fd59A-fd96Ca-fd96Cb-fkh 13 0.542438 13264.2 1 6 CACCTG TTAAGCAAATATTTACATAA - +4 taipale_tf_pairs__HOXB2_ETV7_NSCGGAARNNNNNNMATTAN_CAP_repr-aop-pb 10 0.542438 13264.2 1 6 CACCTG CTAATGACCTTACTTCCGGC - +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m7-egg 15 0.542438 13264.2 1 5 CACCTG TTTTTCAACATTCAGCACAT + +4 taipale_tf_pairs__CUX1_NHLH1_NNCAGCTGNNNNNNNNNATYGATN_CAP_repr-ct-HLH4C 2 0.544095 13304.7 1 6 CACCTG CGCAGCTGCTCCCACTTATCGATC + +4 tfdimers__MD00155-Hnf4-svp 13 0.544095 13304.7 1 6 CACCTG TTATTTTTTTATGGACTTTTTATT - +4 transfac_public__M00057 0 0.544095 13304.7 1 6 CACCTG CACCTCTTGTTGTCAATCAAAACA - +4 taipale_tf_pairs__ETV2_RFX5_NACTTCCGGYNNNNGCAACSN_CAP_repr-pnt 15 0.544487 13314.3 1 6 CACCTG CACTTCCGGCGCAGGCAACCC + +4 tfdimers__MD00001-pho-phol-Pur-alpha 6 0.544487 13314.3 1 6 CACCTG CTTTGCCATCTGCCCCCTCCT + +4 tfdimers__MD00021-NFAT 11 0.544487 13314.3 1 6 CACCTG AAATGGGAAAGCCCCAAAACT + +4 transfac_pro__M05215 15 0.544487 13314.3 1 6 CACCTG GTGGGTGCCCGGCCGCCCCTC + +4 transfac_pro__M05222-ERR 9 0.544487 13314.3 1 6 CACCTG GGGGGGGTCCGCCTGCCTGGC + +4 transfac_pro__M09355 2 0.544487 13314.3 1 6 CACCTG GTTACTTGTAGCAGAAGCAAC + +4 transfac_pro__M09373 3 0.544487 13314.3 1 6 CACCTG GGTAACGTAAAATTCAAGCAA + +4 transfac_pro__M05258 17 0.544487 13314.3 1 4 CACCTG GGGGGAAAGCAGGGACCAACC - +4 tfdimers__MD00158-CG7786-gt-Pdp1 14 0.545223 13332.3 1 6 CACCTG AATATTTGCAAAACCACATACCA + +4 tfdimers__MD00147-TfAP-2 8 0.545223 13332.3 1 6 CACCTG CCCCCCACTTCCTGCCTCCCCCC - +4 taipale_tf_pairs__E2F3_TBX21_NGGTGTGNNGGCGCSNNNNCRMN_CAP-E2f1 18 0.545223 13332.3 1 5 CACCTG CGCGCCAACGCGCCATCACACCT - +4 taipale_tf_pairs__TEAD4_RFX5_RCATTCNNNNNNNNNNNNNNNNNGCAACN_CAP_repr-sd 3 0.545284 13333.8 1 6 CACCTG GCATTCCAAACTGGCCTTTTTTGGCAACG + +4 tfdimers__MD00047 11 0.545284 13333.8 1 6 CACCTG ACCTAGGCAGCCATCTGTTCTCTCCTCCC - +4 tfdimers__MD00036-CG5641-Jra-kay-NFAT 13 0.545382 13336.2 1 6 CACCTG AATATTGAGTCATTTCCTTTTT + +4 tfdimers__MD00603-pho-phol 5 0.545382 13336.2 1 6 CACCTG ATTATCACTTCCATTTTTTTTT + +4 hocomoco__RREB1_HUMAN.H11MO.0.D-l(3)neo38-peb 9 0.545382 13336.2 1 6 CACCTG ACCCCAAACCACCCCCCCCCCC - +4 taipale_tf_pairs__HOXB2_ELF1_NNYMATTANNNNNNNGGAAGNN_CAP_repr-Eip74EF-pb 10 0.545382 13336.2 1 6 CACCTG CACTTCCGCATTCCTAATTACC - +4 tfdimers__MD00492-zfh1 13 0.545382 13336.2 1 6 CACCTG CACACAACAAACCCACATCCAC - +4 taipale_cyt_meth__ZNF345_TYGCAACNNNNNCAACTGKACN_eDBD_meth_repr 18 0.545382 13336.2 1 4 CACCTG TTGCAACACGAACAACTGTACC + +4 cisbp__M4571-Atf3-Atf6-CrebA-CrebB-Jra-kay-nej-REPTOR-BP-Stat92E-Xbp1 9 0.545399 13336.6 1 6 CACCTG TGATGACGTCACCTT + +4 flyfactorsurvey__Adf1_SANGER_5_FBgn0000054-Adf1 0 0.545399 13336.6 1 6 CACCTG CACCGGCAGAGACAA + +4 flyfactorsurvey__gl_SOLEXA_5_FBgn0004618-gl 9 0.545399 13336.6 1 6 CACCTG GAAGCCATACAAATG + +4 neph__UW.Motif.0566 6 0.545399 13336.6 1 6 CACCTG AAAAAACATTTCTCA + +4 taipale__ZIC4_DBD_GACCCCCYGYTGNGN-lmd-opa 3 0.545399 13336.6 1 6 CACCTG GACCCCCCGCTGTGC + +4 taipale_cyt_meth__MEF2B_TGTTACCATATNNGG_FL_meth-bs-Mef2 3 0.545399 13336.6 1 6 CACCTG TGTTACCATATTTGG + +4 transfac_pro__M07936-ci-lmd-opa-sug 0 0.545399 13336.6 1 6 CACCTG GACCCCCCACGACGC + +4 transfac_pro__M09046-Taf1 1 0.545399 13336.6 1 6 CACCTG CCACCGCCGCCGCCA + +4 transfac_pro__M09087-Taf1 1 0.545399 13336.6 1 6 CACCTG CCACCGCCGCCGCCA + +4 cisbp__M3022-ct 0 0.545399 13336.6 1 6 CACCTG CACCAATATGTATGG - +4 cisbp__M5861-Ets98B 9 0.545399 13336.6 1 6 CACCTG ATGATCCGGGACCAC - +4 cisbp__M6299-abd-A-Ubx 9 0.545399 13336.6 1 6 CACCTG ATGATTTATTACTTT - +4 jaspar__MA0517.1-Stat92E 8 0.545399 13336.6 1 6 CACCTG GGAAAATGAAACTGA - +4 neph__UW.Motif.0344 6 0.545399 13336.6 1 6 CACCTG TGGAAAATGCTGTCT - +4 taipale__ETV6_full_CCGGAASCGGAAGTN_repr-aop-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Taf1 0 0.545399 13336.6 1 6 CACCTG CACTTCCGCTTCCGG - +4 taipale__RFX4_DBD_SGTTGCYARGCAACS-CG9727-Rfx 3 0.545399 13336.6 1 6 CACCTG CGTTGCCTAGCAACG - +4 taipale__SPDEF_full_GTGGTCCCGGATYAT-Ets98B 9 0.545399 13336.6 1 6 CACCTG ATGATCCGGGACCAC - +4 taipale_cyt_meth__IRF7_NNGAAANYGAAANYN_eDBD_meth_repr-Blimp-1 0 0.545399 13336.6 1 6 CACCTG CACTTTCACTTTCCT - +4 transfac_pro__M05855-erm 8 0.545399 13336.6 1 6 CACCTG GTTTCATTTCCCTTC - +4 transfac_pro__M09534-Atf6-CrebA-Xbp1 8 0.545399 13336.6 1 6 CACCTG TGCCACGTCAGCATC - +4 taipale_cyt_meth__HNF4A_NRGTCCAAAGTCCRN_eDBD_meth_repr-Hnf4 10 0.545399 13336.6 1 5 CACCTG GTGGACTTTGGACTC - +4 hocomoco__HAND1_HUMAN.H11MO.0.D-Hand 1 0.545939 13349.8 1 6 CACCTG GGGTCTGGTTTTTGTCA + +4 taipale_tf_pairs__TEAD4_HOXA2_RCATTCNNNNNNCATTA_CAP_repr-pb-sd 3 0.545939 13349.8 1 6 CACCTG ACATTCCAATCTCATTA + +4 transfac_pro__M01355-al-ap-Awh-CG18599-CG34367-CG9876-E5-ems-en-eve-inv-lab-Lim3-OdsH-otp-pdm3-Pph13-repo-Rx-unc-4-Vsx1-vvl-zfh2 9 0.545939 13349.8 1 6 CACCTG TAAACTAATTAGCTGAG + +4 transfac_pro__M02810-btd-E2f2-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 8 0.545939 13349.8 1 6 CACCTG GGTCCCGCCCCCTTCTC + +4 cisbp__M6011-fkh-slp2 6 0.545939 13349.8 1 6 CACCTG TGTTTACACTTGTTTAT - +4 taipale__Foxg1_DBD_ATAAACAAGTRTAAACA_repr-fkh-slp2 6 0.545939 13349.8 1 6 CACCTG TGTTTACACTTGTTTAT - +4 taipale_tf_pairs__ETV2_CEBPD_RSCGGANNTTGCGYAAN_CAP_repr-pnt 10 0.545939 13349.8 1 6 CACCTG GTTGCGCAACTTCCGGT - +4 taipale_tf_pairs__FLI1_CEBPD_RNCGGANNTTGCGCAAN_CAP 10 0.545939 13349.8 1 6 CACCTG ATTGCGCAATTTCCGGT - +4 transfac_pro__M01347 8 0.545939 13349.8 1 6 CACCTG TCCCTTTACAGCGTCCT - +4 transfac_pro__M02757-GATAe-grn-pnr-srp 7 0.545939 13349.8 1 6 CACCTG CAATTCTTATCTATATA - +4 transfac_pro__M05375 2 0.545939 13349.8 1 6 CACCTG ATCGCCAGCGTTCGAAC - +4 cisbp__M1741 1 0.546735 13369.3 1 6 CACCTG GTTCCGGCCGG + +4 flyfactorsurvey__Crc_CG6272_SANGER_5_FBgn0000370-Irbp18-crc-kay-vri 2 0.546735 13369.3 1 6 CACCTG ATTACGTCAGC + +4 predrem__nrMotif1363 5 0.546735 13369.3 1 6 CACCTG ATGCACACACA + +4 predrem__nrMotif429 4 0.546735 13369.3 1 6 CACCTG GGGGGCCCTGG + +4 cisbp__M4634-Stat92E 1 0.546735 13369.3 1 6 CACCTG TTTCCCGGAAA - +4 cisbp__M4895-crc-Irbp18-kay-vri 2 0.546735 13369.3 1 6 CACCTG ATTACGTCAGC - +4 cisbp__M6130-Stat92E 1 0.546735 13369.3 1 6 CACCTG CTTCCTGGAAG - +4 cisbp__M6410-ey-Poxm-sv-toy 4 0.546735 13369.3 1 6 CACCTG TTCACGCTTGA - +4 factorbook__UA13 5 0.546735 13369.3 1 6 CACCTG GCTGGGAGCTG - +4 flyfactorsurvey__Cf2-PB_SOLEXA_FBgn0000286-Cf2 2 0.546735 13369.3 1 6 CACCTG TGTACATATAT - +4 flyfactorsurvey__dpn_SANGER_10_FBgn0010109-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 3 0.546735 13369.3 1 6 CACCTG TGGCACGTGCC - +4 flyfactorsurvey__knrl_SANGER_5_FBgn0001323-kni-knrl 5 0.546735 13369.3 1 6 CACCTG TGCCCTAGTTT - +4 predrem__nrMotif2092 3 0.546735 13369.3 1 6 CACCTG TATTTCCTATT - +4 taipale__ELF5_full_ACCCGGAAGTN-aop-Eip74EF-Ets21C-Ets96B-Ets98B-Hr78 0 0.546735 13369.3 1 6 CACCTG TACTTCCGGGT - +4 taipale__Elf5_DBD_ACCCGGAAGTN-aop-Eip74EF-Ets96B-Ets98B-Hr78 3 0.546735 13369.3 1 6 CACCTG TACTTCCGGGT - +4 taipale_cyt_meth__ELK1_NACCGGAAGTN_FL-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.546735 13369.3 1 6 CACCTG TACTTCCGGTT - +4 taipale_cyt_meth__FLI1_NACMGGAARTN_eDBD_meth-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 3 0.546735 13369.3 1 6 CACCTG GATTTCCGGTC - +4 transfac_pro__M01112-Su(H) 5 0.546735 13369.3 1 6 CACCTG TTTCCCACGGT - +4 transfac_pro__M03799 2 0.546735 13369.3 1 6 CACCTG AGAACAGAATG - +4 transfac_pro__M03843-acj6-vvl 4 0.546735 13369.3 1 6 CACCTG TGCATAAATTA - +4 transfac_pro__M05719 4 0.546735 13369.3 1 6 CACCTG GGCAAACATCC - +4 transfac_pro__M09461-tll 4 0.546735 13369.3 1 6 CACCTG CGTTGACTTTT - +4 cisbp__M4952-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.546735 13369.3 1 5 CACCTG ACCGGAAGTGC + +4 taipale_tf_pairs__Hoxa10_TTCTGG40NTGC_HT_1 7 0.546735 13369.3 1 4 CACCTG ATTTTACGACC - +4 transfac_pro__M06398 7 0.546735 13369.3 1 4 CACCTG TCTGATTTCCC - +4 cisbp__M0024 1 0.54819 13404.9 1 6 CACCTG CCGCCGCC + +4 elemento__CCCCTCCC 0 0.54819 13404.9 1 6 CACCTG CCCCTCCC + +4 elemento__CTCCTCCC 0 0.54819 13404.9 1 6 CACCTG CTCCTCCC + +4 flyfactorsurvey__Hnf4_SANGER_5_FBgn0004914-Hnf4 2 0.54819 13404.9 1 6 CACCTG TTGACCCC + +4 taipale_cyt_meth__ISL1_SCACTTAN_eDBD_meth-tup 1 0.54819 13404.9 1 6 CACCTG GCACTTAA + +4 taipale_cyt_meth__RAX_CTCGTTAN_eDBD_meth-CG34367-ind-unpg 0 0.54819 13404.9 1 6 CACCTG CTCGTTAA + +4 yetfasco__YGL192W_1000-Ime4 2 0.54819 13404.9 1 6 CACCTG TTTTCCTT + +4 yetfasco__YOR140W_605 1 0.54819 13404.9 1 6 CACCTG GAAGCTTC + +4 cisbp__M1374 2 0.54819 13404.9 1 6 CACCTG CTCATCGC - +4 hocomoco__NKX25_HUMAN.H11MO.0.B 0 0.54819 13404.9 1 6 CACCTG CCTCTCCA - +4 predrem__nrMotif2362 2 0.54819 13404.9 1 6 CACCTG GTTGCCTA - +4 cisbp__M4349 -1 0.54819 13404.9 1 5 CACCTG AACTCCGG + +4 jaspar__MA0942.1 -1 0.54819 13404.9 1 5 CACCTG ACCGACAT + +4 predrem__nrMotif2570 -1 0.54819 13404.9 1 5 CACCTG CCCTGAAG + +4 transfac_pro__M01648 -1 0.54819 13404.9 1 5 CACCTG AACTCCGG + +4 flyfactorsurvey__Optix_Cell_FBgn0025360-Optix 3 0.54819 13404.9 1 5 CACCTG TATCACTT - +4 jaspar__MA0430.1 -1 0.54819 13404.9 1 5 CACCTG AACTCCGG - +4 swissregulon__sacCer__YLR278C -1 0.54819 13404.9 1 5 CACCTG AACTCCGG - +4 flyfactorsurvey__CG15601_SANGER_5_FBgn0030673-CG15601 4 0.54819 13404.9 1 4 CACCTG TTTCAATC + +4 flyfactorsurvey__GATAd_SANGER_5_FBgn0032223-GATAd -2 0.54819 13404.9 1 4 CACCTG CCTTATCA + +4 flyfactorsurvey__prd_FlyReg_FBgn0003145-prd 4 0.54819 13404.9 1 4 CACCTG CAATTACG + +4 jaspar__MA1087.1 4 0.54819 13404.9 1 4 CACCTG CGTTGACC + +4 transfac_pro__M09425 4 0.54819 13404.9 1 4 CACCTG TCCGTACA + +4 jaspar__MA1062.1 5 0.54819 13404.9 1 3 CACCTG GGGCCCAC + +4 predrem__nrMotif586 5 0.54819 13404.9 1 3 CACCTG CAGTCCAC + +4 predrem__nrMotif612 5 0.54819 13404.9 1 3 CACCTG AGAATCAC + +4 predrem__nrMotif1874 -3 0.54819 13404.9 1 3 CACCTG CTTCACAC - +4 cisbp__M0662 1 0.548836 13420.7 1 6 CACCTG GTAACGT + +4 cisbp__M1018-H2.0 1 0.548836 13420.7 1 6 CACCTG TAATTAA + +4 predrem__nrMotif1480 1 0.548836 13420.7 1 6 CACCTG GTTCCTG + +4 predrem__nrMotif2608 0 0.548836 13420.7 1 6 CACCTG GACCAAG + +4 scertf__spivak.CRZ1-CG2120 1 0.548836 13420.7 1 6 CACCTG GTGGCTG + +4 transfac_pro__M01894-pho-phol 1 0.548836 13420.7 1 6 CACCTG CCATTTT + +4 cisbp__M0604 1 0.548836 13420.7 1 6 CACCTG ATTACGC - +4 predrem__nrMotif1229 0 0.548836 13420.7 1 6 CACCTG TGCCTGC - +4 transfac_pro__M04895-E2f1 0 0.548836 13420.7 1 6 CACCTG CGCCTTT - +4 cisbp__M0885 2 0.548836 13420.7 1 5 CACCTG CTGATCC + +4 cisbp__M4763-bcd 2 0.548836 13420.7 1 5 CACCTG TTAATCT + +4 flyfactorsurvey__bcd_NAR_FBgn0000166-bcd 2 0.548836 13420.7 1 5 CACCTG TTAATCT + +4 predrem__nrMotif1464 -1 0.548836 13420.7 1 5 CACCTG GCCTTCA + +4 hdpi__TPI1-Tpi -1 0.548836 13420.7 1 5 CACCTG CCCTTTC - +4 predrem__nrMotif1074 -1 0.548836 13420.7 1 5 CACCTG ACTTCAT - +4 predrem__nrMotif1328 3 0.548836 13420.7 1 4 CACCTG TCTCACA + +4 transfac_pro__M06840 -2 0.548836 13420.7 1 4 CACCTG CATCCGG - +4 elemento__AGTGCAC 4 0.548836 13420.7 1 3 CACCTG AGTGCAC + +4 elemento__CACGCAC 4 0.548836 13420.7 1 3 CACCTG CACGCAC + +4 elemento__CCCGCAC 4 0.548836 13420.7 1 3 CACCTG CCCGCAC + +4 elemento__CGCCCAC-sr 4 0.548836 13420.7 1 3 CACCTG CGCCCAC + +4 elemento__CGCGCAC 4 0.548836 13420.7 1 3 CACCTG CGCGCAC + +4 elemento__GCGTCAC 4 0.548836 13420.7 1 3 CACCTG GCGTCAC + +4 elemento__TGCCCAC 4 0.548836 13420.7 1 3 CACCTG TGCCCAC + +4 elemento__TGCGCAC 4 0.548836 13420.7 1 3 CACCTG TGCGCAC + +4 elemento__TGGACAC 4 0.548836 13420.7 1 3 CACCTG TGGACAC + +4 elemento__TGGCCAC 4 0.548836 13420.7 1 3 CACCTG TGGCCAC + +4 elemento__TTGACAC 4 0.548836 13420.7 1 3 CACCTG TTGACAC + +4 predrem__nrMotif1165 -3 0.548836 13420.7 1 3 CACCTG CTTGTTA + +4 stark__CACRCAC 4 0.548836 13420.7 1 3 CACCTG CACACAC + +4 transfac_pro__M01286 -3 0.548836 13420.7 1 3 CACCTG CTTTGAA + +4 cisbp__M5469-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp2 4 0.548836 13420.7 1 3 CACCTG TGTTTAC - +4 cisbp__M5472-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 4 0.548836 13420.7 1 3 CACCTG TGTTTAC - +4 taipale__FOXO4_DBD_GTAAACA-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp2 4 0.548836 13420.7 1 3 CACCTG TGTTTAC - +4 taipale__FOXO6_DBD_GTAAACA-croc-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp2 4 0.548836 13420.7 1 3 CACCTG TGTTTAC - +4 tfdimers__MD00541-NFAT 6 0.550191 13453.8 1 6 CACCTG TTTTATTTCCTGCAATTTTTTTTTTTTT + +4 cisbp__M5574 4 0.550532 13462.2 1 6 CACCTG CCGAAACCGAAACT + +4 factorbook__CEBPB-CG7786-Irbp18-Pdp1-Xrp1-gt-nej-slbo 8 0.550532 13462.2 1 6 CACCTG TATTGCACAATCCC + +4 neph__UW.Motif.0461 3 0.550532 13462.2 1 6 CACCTG GAAAAAATGACAAA + +4 swissregulon__sacCer__HSF1-Hsf-pb 2 0.550532 13462.2 1 6 CACCTG AGAACCTTATGGAA + +4 taipale__IRF5_full_CCGAAACCGAAACY 4 0.550532 13462.2 1 6 CACCTG CCGAAACCGAAACT + +4 transfac_pro__M02835-bon-opa 2 0.550532 13462.2 1 6 CACCTG CACCCCCGGGGGGG + +4 transfac_pro__M09535-Atf6-CrebA-Xbp1 7 0.550532 13462.2 1 6 CACCTG GCCACGTCAGCATC + +4 cisbp__M6190-Dp-E2f1-E2f2 6 0.550532 13462.2 1 6 CACCTG CTTTCCCGCCAATT - +4 cisbp__M6373-btd-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps 0 0.550532 13462.2 1 6 CACCTG GCGCTGATTGGCTG - +4 factorbook__HNF4-EcR-HDAC1-Hnf4-Spps-btd-nej-svp-usp 3 0.550532 13462.2 1 6 CACCTG CTGGACTTTGGACT - +4 taipale__CREB3L1_DBD_NTGCCACGTCANCA-Atf6-CrebA-CrebB-Xbp1 4 0.550532 13462.2 1 6 CACCTG TGATGACGTGGCAT - +4 taipale_tf_pairs__MEIS1_DLX3_TGACANSNTAATTG_CAP 5 0.550532 13462.2 1 6 CACCTG CAATTAACCTGTCA - +4 taipale_tf_pairs__TEAD4_ELK1_RGAATSCGGAAGYN_CAP_repr-sd 0 0.550532 13462.2 1 6 CACCTG AACTTCCGCATTCC - +4 transfac_pro__M02023-ct-CTCF-Klf15-klu-l(3)neo38-sr 4 0.550532 13462.2 1 6 CACCTG CCCTCCCCTCCCCC - +4 transfac_pro__M06955 4 0.550532 13462.2 1 6 CACCTG GGGCCAACTTATCC - +4 taipale_cyt_meth__ZBTB12_NGCTGNNCCGCGYN_eDBD_meth 9 0.550532 13462.2 1 5 CACCTG GACGCGGCCCAGCT - +4 homer__GGTTGCCATGGCAA_Rfx1-CG5846-CG9727-Max-Rfx-SREBP 10 0.550532 13462.2 1 4 CACCTG TTGCCATGGCAACC - +4 tfdimers__MD00078-lab-pan 21 0.55079 13468.5 1 6 CACCTG ATTTTCCTTTGTTATGCTAATTAGCTGTTTACTT + +4 neph__UW.Motif.0091 2 0.551753 13492 1 6 CACCTG AAAACCAGACTG + +4 taipale_cyt_meth__CREB3_NRTGACGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.551753 13492 1 6 CACCTG GGTGACGTCACC + +4 transfac_pro__M05421 2 0.551753 13492 1 6 CACCTG AGTTCCTTCCGC + +4 transfac_pro__M05575 6 0.551753 13492 1 6 CACCTG CAATGTTTCCTC + +4 transfac_pro__M05807 6 0.551753 13492 1 6 CACCTG GATGAATACCGC + +4 cisbp__M4803-mamo 2 0.551753 13492 1 6 CACCTG TAAGCCTATAGA - +4 hocomoco__ATF6A_HUMAN.H11MO.0.B-Atf6 1 0.551753 13492 1 6 CACCTG CCACGTCACCAC - +4 hocomoco__EMX1_HUMAN.H11MO.0.D-CG34367-E5-Vsx1-Vsx2-ap-ems-en-inv-otp-pdm3-ro-unpg 2 0.551753 13492 1 6 CACCTG ATTAGCTAATTA - +4 neph__UW.Motif.0065 6 0.551753 13492 1 6 CACCTG TGGAATGTTCTG - +4 neph__UW.Motif.0188 3 0.551753 13492 1 6 CACCTG GAAATTCTTCTG - +4 taipale_cyt_meth__CREB1_NRTGAYGTCAYN_eDBD_meth-Atf3-Atf6-CrebB-Jra-Xbp1 3 0.551753 13492 1 6 CACCTG CGTGACATCACG - +4 taipale_cyt_meth__DBP_NRTTAYGTAAYN_eDBD-CG7786-CrebB-gt-hng1-Pdp1-vri 3 0.551753 13492 1 6 CACCTG CGTTACGTAACG - +4 taipale_cyt_meth__ELF1_NACCCGGAAGTN_eDBD-aop-Eip74EF-Ets21C-Ets96B-Hr78-nej 0 0.551753 13492 1 6 CACCTG CACTTCCGGGTT - +4 taipale_cyt_meth__FOXI1_NANGTAAACAAN_FL_meth-bin-CHES-1-like-croc-FoxK-FoxL1-foxo-FoxP-slp1-slp2 6 0.551753 13492 1 6 CACCTG ATTGTTTACGTT - +4 taipale_tf_pairs__TEAD4_HOXB13_NTCGTAAAATGC_CAP-sd 6 0.551753 13492 1 6 CACCTG GCATTTTACGAG - +4 transfac_pro__M05578 6 0.551753 13492 1 6 CACCTG GAGGCCCGCCCT - +4 transfac_pro__M01301-Mef2-rump 7 0.551753 13492 1 5 CACCTG TTAAAAATAGCT + +4 transfac_pro__M05691 7 0.551753 13492 1 5 CACCTG TCGTTTTCACAG - +4 transfac_pro__M06137 -1 0.551753 13492 1 5 CACCTG TCCTATTCTCGC - +4 transfac_pro__M06607-htk 7 0.551753 13492 1 5 CACCTG TCGGCAATATCG - +4 homer__CCTGTCAATCAN_Pbx3 -2 0.551753 13492 1 4 CACCTG CCTGTCAATCAA + +4 homer__CCTTTTATAGCC_TATA-Box-Nelf-E-Tbp-TfIIB-TfIIFalpha -2 0.551753 13492 1 4 CACCTG CCTTTTATAGCC + +4 transfac_pro__M06097 8 0.551753 13492 1 4 CACCTG TGTTAGAGGACA + +4 transfac_pro__M06206-CG2120 -2 0.551753 13492 1 4 CACCTG TCTGCTTTAGTC - +4 transfac_pro__M06570 8 0.551753 13492 1 4 CACCTG GATGTCTACACA - +4 cisbp__M4867-CG4854 9 0.551753 13492 1 3 CACCTG GTTGCCAACCAC - +4 jaspar__MA0006.1-tgo 0 0.551835 13494 1 6 CACCTG TGCGTG + +4 hdpi__YWHAZ-14-3-3zeta 0 0.551835 13494 1 6 CACCTG AACCCA - +4 transfac_pro__M01660-Atac3-bs-Eip74EF 1 0.551835 13494 1 5 CACCTG CTTCCG + +4 jaspar__MA0056.1 1 0.551835 13494 1 5 CACCTG TCCCCA - +4 transfac_pro__M01033-Hnf4 1 0.551835 13494 1 5 CACCTG TGCCCC - +4 transfac_pro__M05131 -3 0.551835 13494 1 3 CACCTG CTATAT - +4 hocomoco__MAFF_HUMAN.H11MO.0.B-cnc-maf-S-tj 8 0.552313 13505.7 1 6 CACCTG TGCTGAGTCAGCATTTTT + +4 swissregulon__hs__RFX1..5_RFXANK_RFXAP.p2-CG5846-CG9727-Max-Rfx-SREBP 4 0.552313 13505.7 1 6 CACCTG CGGTCGCCATGGCAACCG + +4 taipale_tf_pairs__RFX3_BHLHA15_NRGYAACNNNCATATGKN_CAP_repr-dimm-Rfx 4 0.552313 13505.7 1 6 CACCTG TGGCAACGACCATATGGT + +4 transfac_pro__M06164 12 0.552313 13505.7 1 6 CACCTG GGATTCCGTTCCTACCCT + +4 taipale_tf_pairs__HOXB2_ELK3_TAATGNNNNNCGGAAGTN_CAP-pb 0 0.552313 13505.7 1 6 CACCTG CACTTCCGGTTCACATTA - +4 transfac_pro__M05779 0 0.552313 13505.7 1 6 CACCTG CCCCAGCAGTCTGCACCC - +4 tfdimers__MD00099-GATAe-grn-Myc-pnr-srp 7 0.552774 13517 1 6 CACCTG ATTTTCTTATCTGTTTTTTACAGCTGGTAAT - +4 cisbp__M1825 6 0.55282 13518.1 1 6 CACCTG CTTTATTTCCGTT + +4 hocomoco__EVX2_HUMAN.H11MO.0.A-Abd-B-cad-eve 7 0.55282 13518.1 1 6 CACCTG GTTTTATGGCCTT + +4 hocomoco__MAFA_MOUSE.H11MO.0.D-cnc-maf-S-tj 0 0.55282 13518.1 1 6 CACCTG CTGCTGACTCTGC + +4 hocomoco__ZNF85_HUMAN.H11MO.1.C 6 0.55282 13518.1 1 6 CACCTG TGAAGTAATCTTT + +4 neph__UW.Motif.0280 7 0.55282 13518.1 1 6 CACCTG CCTGGGGCCCCTC + +4 neph__UW.Motif.0441 1 0.55282 13518.1 1 6 CACCTG TTTCCATTTTTCA + +4 transfac_pro__M07883-Dif-dl 7 0.55282 13518.1 1 6 CACCTG TGGGAAAAACCCA + +4 hocomoco__E2F7_HUMAN.H11MO.0.B-Dp-E2f1-E2f2 7 0.55282 13518.1 1 6 CACCTG CCTTTCCCGCCCC - +4 stark__WTGGNNNNNTAAY 7 0.55282 13518.1 1 6 CACCTG ATTAAAAAACCAA - +4 taipale__Tcfap2a_DBD_NSCCNNNNNGGSN_repr-TfAP-2 0 0.55282 13518.1 1 6 CACCTG TGCCCTCAGGGCA - +4 taipale_cyt_meth__POU3F1_NTAATTWATGCNN_eDBD-dve-vvl 1 0.55282 13518.1 1 6 CACCTG TTGCATAAATTAG - +4 transfac_pro__M00821-cnc-Jra-kay-maf-S 7 0.55282 13518.1 1 6 CACCTG CATGACTCAGCAG - +4 stark__RBYGTGRGAAMCB-Su(H) 8 0.55282 13518.1 1 5 CACCTG ATCGTGAGAAACT + +4 transfac_pro__M07605-pan -1 0.55282 13518.1 1 5 CACCTG CCCTTTGATGCTG - +4 swissregulon__hs__ZBTB6.p2 9 0.55282 13518.1 1 4 CACCTG CGGCTCCATCACC + +4 hdpi__KIAA0907 -2 0.553149 13526.2 1 4 CACCTG CTTTC - +4 yetfasco__YER040W_539-GATAd-GATAe-grn-pnr-srp 1 0.553149 13526.2 1 4 CACCTG TTATC - +4 cisbp__M0037-Taf1-lid-pho-phol 4 0.553858 13543.5 1 6 CACCTG CCGCCGCCAT + +4 cisbp__M0277 3 0.553858 13543.5 1 6 CACCTG GCTTACTAAT + +4 cisbp__M0290-cnc-maf-S-tj 0 0.553858 13543.5 1 6 CACCTG ATTTTGCTGA + +4 cisbp__M0449 4 0.553858 13543.5 1 6 CACCTG GATGAAGCCT + +4 cisbp__M1240-nub-pdm2-vvl 4 0.553858 13543.5 1 6 CACCTG AATTTGCATA + +4 cisbp__M1665-sd 3 0.553858 13543.5 1 6 CACCTG ACATTCCCGA + +4 cisbp__M1814 3 0.553858 13543.5 1 6 CACCTG TTTTTCCGAG + +4 idmmpmm__h-Sidpn-dpn-h 2 0.553858 13543.5 1 6 CACCTG GGCACGCGCC + +4 predrem__nrMotif381 4 0.553858 13543.5 1 6 CACCTG TTGGCACAGA + +4 taipale_cyt_meth__OLIG2_AACAGCTGTY_eDBD_meth-amos-ato-crp-dimm-HLH54F 2 0.553858 13543.5 1 6 CACCTG AACATCTGTT + +4 transfac_pro__M01785 3 0.553858 13543.5 1 6 CACCTG TTAGCCCTAA + +4 yetfasco__YGL209W_2143-klu-sr 0 0.553858 13543.5 1 6 CACCTG ACCCCGCATT + +4 c2h2_zfs__M0482-CG9609 1 0.553858 13543.5 1 6 CACCTG TAACCAGCAC - +4 cisbp__M0217-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.553858 13543.5 1 6 CACCTG ACCATATGGT - +4 cisbp__M0526 0 0.553858 13543.5 1 6 CACCTG TACCCCGCAC - +4 cisbp__M0688-aop-Eip74EF-Ets98B 2 0.553858 13543.5 1 6 CACCTG ATTTCCGGGT - +4 cisbp__M0703-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.553858 13543.5 1 6 CACCTG ACTTCCGGTT - +4 cisbp__M1402 2 0.553858 13543.5 1 6 CACCTG TTTACGTAAT - +4 cisbp__M1427 3 0.553858 13543.5 1 6 CACCTG GAGAACAATT - +4 jaspar__MA1045.1 2 0.553858 13543.5 1 6 CACCTG TTTACGTAAT - +4 jaspar__MA1063.1 4 0.553858 13543.5 1 6 CACCTG GTGGGCCCCA - +4 predrem__nrMotif1003 3 0.553858 13543.5 1 6 CACCTG TTTGATCTTA - +4 predrem__nrMotif1021 3 0.553858 13543.5 1 6 CACCTG CTGAACCCCA - +4 predrem__nrMotif821 4 0.553858 13543.5 1 6 CACCTG CCAAGCCCAG - +4 taipale_cyt_meth__ATOH7_ANCATATGNY_eDBD_meth-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.553858 13543.5 1 6 CACCTG GACATATGTT - +4 taipale_cyt_meth__TFAP4_ANCATATGNT_FL-amos-ato-crp-Fer3-HLH54F-Oli-twi 2 0.553858 13543.5 1 6 CACCTG AACATATGTT - +4 taipale_cyt_meth__TFAP4_ANCATATGNT_FL_meth-amos-ato-crp-Fer3-HLH54F-Oli-twi 2 0.553858 13543.5 1 6 CACCTG AACATATGTT - +4 transfac_pro__M01214-aop-Eip74EF-Ets96B 3 0.553858 13543.5 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M01991-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.553858 13543.5 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M02052-aop-Eip74EF-Ets96B 3 0.553858 13543.5 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M02064-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 0 0.553858 13543.5 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02067-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 3 0.553858 13543.5 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M03577-sv 4 0.553858 13543.5 1 6 CACCTG CTGCTTCTCC - +4 transfac_pro__M07064-Stat92E 1 0.553858 13543.5 1 6 CACCTG TTTCCCGGAA - +4 transfac_pro__M07967-knrl 3 0.553858 13543.5 1 6 CACCTG TGTTACAGTT - +4 cisbp__M1035-achi-esg-hth-sna-vis-wor -1 0.553858 13543.5 1 5 CACCTG AGCTGTCAAT + +4 transfac_public__M00108-Atac3-Eip74EF -1 0.553858 13543.5 1 5 CACCTG ACCGGAAGAG + +4 cisbp__M0524 -2 0.553858 13543.5 1 4 CACCTG TCTTGGCGAG + +4 cisbp__M3622-Rel 6 0.553858 13543.5 1 4 CACCTG GGGGATTCCC + +4 hocomoco__FOXO3_HUMAN.H11MO.0.B-FoxK-FoxP-fkh-foxo-slp2 6 0.553858 13543.5 1 4 CACCTG CTTGTTTACA + +4 predrem__nrMotif659 6 0.553858 13543.5 1 4 CACCTG AAAGAACACA + +4 transfac_pro__M00732 6 0.553858 13543.5 1 4 CACCTG CCATTCGTCC + +4 yetfasco__YIL056W_2091-Jra-Myc-bon-cnc-kay-mor-pan 6 0.553858 13543.5 1 4 CACCTG GTGAGTCACC - +4 transfac_pro__M06214 7 0.553858 13543.5 1 3 CACCTG TCCGCTTTAC - +4 tfdimers__MD00488-Eip74EF 6 0.554434 13557.6 1 6 CACCTG TTTTACTTCCTGATTTCTCCTTCTTTT - +4 cisbp__M0607-Kdm2 3 0.554802 13566.6 1 6 CACCTG ACGTAAATA + +4 cisbp__M1050 2 0.554802 13566.6 1 6 CACCTG CCCATCAAA + +4 cisbp__M1204 2 0.554802 13566.6 1 6 CACCTG CTTAATTGG + +4 jaspar__MA0441.1 1 0.554802 13566.6 1 6 CACCTG TTCCCCGCA + +4 neph__UW.Motif.0329 1 0.554802 13566.6 1 6 CACCTG CCAAATTTC + +4 predrem__nrMotif186 1 0.554802 13566.6 1 6 CACCTG TGACCCCCT + +4 predrem__nrMotif2192 2 0.554802 13566.6 1 6 CACCTG TTTGCCTTG + +4 predrem__nrMotif417 0 0.554802 13566.6 1 6 CACCTG TCCCATTTC + +4 stark__TRACRYGCA 1 0.554802 13566.6 1 6 CACCTG TAACACGCA + +4 swissregulon__sacCer__ZMS1 1 0.554802 13566.6 1 6 CACCTG TTCCCCGCA + +4 transfac_pro__M04858-CG10431 0 0.554802 13566.6 1 6 CACCTG AACATGGCG + +4 transfac_pro__M04908-pho-phol 1 0.554802 13566.6 1 6 CACCTG AAACATGGC + +4 transfac_pro__M08897-Dad-Mad-Med-Smox 0 0.554802 13566.6 1 6 CACCTG TGTCTGGCC + +4 cisbp__M0121 2 0.554802 13566.6 1 6 CACCTG TTATTTTGC - +4 cisbp__M0432 3 0.554802 13566.6 1 6 CACCTG GTGCGCGCG - +4 cisbp__M0989-nub-pdm2 0 0.554802 13566.6 1 6 CACCTG CTCATTATC - +4 predrem__nrMotif1372 3 0.554802 13566.6 1 6 CACCTG AAAGATCTA - +4 predrem__nrMotif1854 2 0.554802 13566.6 1 6 CACCTG AAATCCTCT - +4 predrem__nrMotif672 3 0.554802 13566.6 1 6 CACCTG TTCTGCCTT - +4 swissregulon__sacCer__YDR520C 1 0.554802 13566.6 1 6 CACCTG TTATCTCCG - +4 taipale_cyt_meth__MAF_NYGCTGACN_eDBD_meth-maf-S-tj 3 0.554802 13566.6 1 6 CACCTG CGTCAGCAT - +4 transfac_pro__M01617 1 0.554802 13566.6 1 6 CACCTG TTCCCCGCA - +4 transfac_pro__M04891 0 0.554802 13566.6 1 6 CACCTG CTGCTGTGG - +4 transfac_pro__M04960-nub-pdm2 0 0.554802 13566.6 1 6 CACCTG CATATTCAT - +4 transfac_pro__M09576 3 0.554802 13566.6 1 6 CACCTG AGTCAACGC - +4 cisbp__M4739-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 -1 0.554802 13566.6 1 5 CACCTG ACCGGAAGT + +4 elemento__CCCTCCCCC -1 0.554802 13566.6 1 5 CACCTG CCCTCCCCC + +4 predrem__nrMotif1145 4 0.554802 13566.6 1 5 CACCTG TGCATCCCA + +4 predrem__nrMotif1795 -1 0.554802 13566.6 1 5 CACCTG ATCTTGGAA + +4 cisbp__M0564 -1 0.554802 13566.6 1 5 CACCTG ACGTCCTCT - +4 cisbp__M5052-ken -1 0.554802 13566.6 1 5 CACCTG ACTTTCTCC - +4 flyfactorsurvey__ken_SANGER_10_FBgn0011236-ken -1 0.554802 13566.6 1 5 CACCTG ACTTTCTCC - +4 transfac_pro__M04704-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-Taf1 -1 0.554802 13566.6 1 5 CACCTG ACTTCCGGC - +4 predrem__nrMotif1293 5 0.554802 13566.6 1 4 CACCTG TAAAACACA + +4 predrem__nrMotif1517 5 0.554802 13566.6 1 4 CACCTG GCTCTGACT + +4 predrem__nrMotif1759 5 0.554802 13566.6 1 4 CACCTG TTATTCACA + +4 predrem__nrMotif2176 -2 0.554802 13566.6 1 4 CACCTG TCTGTTATT + +4 taipale_cyt_meth__HMBOX1_NCTAGTTAN_eDBD_meth -2 0.554802 13566.6 1 4 CACCTG ACTAGTTAA + +4 taipale_cyt_meth__HMBOX1_NCTAGTTAN_eDBD_repr -2 0.554802 13566.6 1 4 CACCTG ACTAGTTAC + +4 transfac_pro__M04775-pan -2 0.554802 13566.6 1 4 CACCTG CCTTTGATG + +4 hocomoco__FOXH1_HUMAN.H11MO.0.A 5 0.554802 13566.6 1 4 CACCTG CAATCCACA - +4 taipale_cyt_meth__ZBTB14_NYGCRCGTGCACGYGN_eDBD 9 0.55556 13585.1 1 6 CACCTG ATGCGCGTGCACGTGA + +4 transfac_pro__M02738-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 10 0.55556 13585.1 1 6 CACCTG ACGATGACGTCATCGA + +4 hocomoco__ZN589_HUMAN.H11MO.0.D 7 0.55556 13585.1 1 6 CACCTG CGGCAGTAACCCTGGG - +4 neph__UW.Motif.0302 10 0.55556 13585.1 1 6 CACCTG TGGCATTTTTTTCATT - +4 taipale_cyt_meth__BCL6B_NYGCTTTCKAGGAATN_eDBD 2 0.55556 13585.1 1 6 CACCTG AATTCCTCGAAAGCAC - +4 taipale_cyt_meth__MAFF_NYGCTGAYRTCAGCRN_eDBD_meth-CrebA-CrebB-maf-S 5 0.55556 13585.1 1 6 CACCTG TTGCTGACGTCAGCAT - +4 taipale_tf_pairs__ERF_HOXB13_NNMGGAARNNRTAAAN_CAP_repr-Ets21C 9 0.55556 13585.1 1 6 CACCTG TTTTACGACTTCCGGT - +4 transfac_pro__M01354-ap-Awh-CG32532-E5-Lim3-nub-otp-pdm2-Pph13-ro-Rx-Vsx1-vvl-zfh2 0 0.55556 13585.1 1 6 CACCTG TACTTAATTAATACAT - +4 transfac_pro__M02772-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 10 0.55556 13585.1 1 6 CACCTG ACGATGACGTCATCGG - +4 taipale__RFX4_DBD_NGTTNCCATGGNAACN-CG5846-CG9727-Max-Rfx-SREBP 12 0.55556 13585.1 1 4 CACCTG CGTTGCCATGGCAACG + +4 hocomoco__ZN667_HUMAN.H11MO.0.C 2 0.557142 13623.8 1 6 CACCTG GTGGCCTTAAAAGCTCAGC + +4 hocomoco__ZBT17_HUMAN.H11MO.0.A-CTCF-CoRest-Klf15-Spps-btd-ct-klu-sr 12 0.557142 13623.8 1 6 CACCTG CTTCCCCTCCCCCACCCTC - +4 hocomoco__ZIM3_HUMAN.H11MO.0.C 12 0.557142 13623.8 1 6 CACCTG GCAAGCAACAGAAACCCAA - +4 transfac_pro__M06917 2 0.557142 13623.8 1 6 CACCTG CCCACCATTTCTTTGTTTA - +4 taipale_cyt_meth__RFX5_NGTTGCYRNNNGTTGCYRN_eDBD_meth-CG9727-Rfx 15 0.557142 13623.8 1 4 CACCTG CTAGCAACGCCTAGCAACC - +4 tfdimers__MD00243-ct 16 0.557963 13643.9 1 6 CACCTG AAAATTAATTAATGATCAATAAAAAT - +4 tfdimers__MD00555-Sox100B 5 0.558827 13665 1 6 CACCTG ATTATTTCCTTTGTATAACAAAAGAAAAAA + +4 tfdimers__MD00590-E(bx)-nej 18 0.558827 13665 1 6 CACCTG AAAAAAACCACAACACACTCCCTGCCCCCC - +4 cisbp__M4210 14 0.560574 13707.7 1 6 CACCTG GCGGGTTTTTTGGACGCCGT + +4 dbcorrdb__ARID3A__ENCSR000EFY_1__m1-brm-CoRest-ebi-GATAe-grn-HDAC1-HLH3B-nej-pnr-RpII215-Snr1-srp-Stat92E-svp 3 0.560574 13707.7 1 6 CACCTG TCTTATCTGTACCAACCAGG + +4 dbcorrdb__ATF3__ENCSR000BNU_1__m2-Bdp1-Brf-CG17209-ebi-Tbp 3 0.560574 13707.7 1 6 CACCTG TAACCACTGAGCCACCGCGC + +4 dbcorrdb__CBX3__ENCSR000BRT_1__m1-HP1b-HP1c-HP1e-Su(var)205 3 0.560574 13707.7 1 6 CACCTG GAATTTCAGCAGAATGCTCA + +4 dbcorrdb__EP300__ENCSR000DZD_1__m4-nej 13 0.560574 13707.7 1 6 CACCTG TTCTTCTCAGTCATAACAAG + +4 dbcorrdb__EZH2__ENCSR000ATA_1__m4-E(z) 13 0.560574 13707.7 1 6 CACCTG CCCGGGGCCGAGCGTCCGGT + +4 dbcorrdb__EZH2__ENCSR000ATC_1__m5-E(z) 0 0.560574 13707.7 1 6 CACCTG CTCCTGGTCTCCAAACAGAC + +4 dbcorrdb__FOXA1__ENCSR000BLE_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-GATAe-grn-HDAC1-nej-Nf1-pnr-slp2 9 0.560574 13707.7 1 6 CACCTG TTCTTTGTTTACTTAGCGAA + +4 dbcorrdb__GATA1__ENCSR000EFT_1__m2-GATAe-grn-pnr 1 0.560574 13707.7 1 6 CACCTG ACAGCAGCTGGCAAGCTGCC + +4 dbcorrdb__HDAC2__ENCSR000BMG_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 3 0.560574 13707.7 1 6 CACCTG TCTTATCTGCGCCCCCCAGC + +4 dbcorrdb__MAX__ENCSR000EDS_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-cwo-E2f1-ERR-E(z)-gce-HDAC1-Hey-Max-Mitf-Mnt-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Stat92E-Taf1-tgo-tna-Usf-vtd-zfh1 8 0.560574 13707.7 1 6 CACCTG GCCGGGGCCACGTGGCCCGG + +4 dbcorrdb__NFE2__ENCSR000DZY_1__m1-btd-cnc-CrebB-cwo-cyc-E2f1-Max-Mitf-Myc-Spps-SREBP-tgo-Usf-zfh1 6 0.560574 13707.7 1 6 CACCTG CCCCGTCACGTGACCCGCCC + +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m11-RpII215 13 0.560574 13707.7 1 6 CACCTG CAGACGAACATGCCGCCTAC + +4 dbcorrdb__POLR2A__ENCSR000DMT_1__m1-CG10431-RpII215-Taf1 12 0.560574 13707.7 1 6 CACCTG CGGCGCTTCCGCCATGTGCC + +4 dbcorrdb__POLR2A__ENCSR000EYW_1__m2-RpII215 9 0.560574 13707.7 1 6 CACCTG CCGTGGCGCTATATCAGCGG + +4 dbcorrdb__REST__ENCSR000BMN_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 1 0.560574 13707.7 1 6 CACCTG GGAGCTGTCCATGGTGCTGA + +4 dbcorrdb__STAT1__ENCSR000DZM_1__m1-btd-Spps-Stat92E 7 0.560574 13707.7 1 6 CACCTG GGGGCGGGACTTCGGGTCGG + +4 dbcorrdb__TBP__ENCSR000EDD_1__m2-Brf-Hsf-SREBP-Tbp 6 0.560574 13707.7 1 6 CACCTG GAATCGAACCCGCGACGTTT + +4 dbcorrdb__TBP__ENCSR000EEL_1__m3-Bdp1-Brf-CG17209-ebi-Tbp 13 0.560574 13707.7 1 6 CACCTG CTAACCGCTACGCCACCGCG + +4 dbcorrdb__THAP1__ENCSR000BNN_1__m1-CG10431-pho-phol 1 0.560574 13707.7 1 6 CACCTG CTGCCCGAAGCCAAGATGGC + +4 transfac_pro__M07138 11 0.560574 13707.7 1 6 CACCTG AGACATGCCCAGACATGCCC + +4 transfac_pro__M09500-Clk-Hey 2 0.560574 13707.7 1 6 CACCTG GACACGTGGCAGCCCCGGGC + +4 transfac_public__M00615-Max-Myc 14 0.560574 13707.7 1 6 CACCTG CAAGTGTCACGTGTTACTTG + +4 dbcorrdb__CBX3__ENCSR000BRT_1__m2-HP1b-HP1c-HP1e-Su(var)205 0 0.560574 13707.7 1 6 CACCTG CACCTCTCAGCAGAAACAAT - +4 dbcorrdb__CBX3__ENCSR000BRT_1__m3-HP1b-HP1c-HP1e-Su(var)205 5 0.560574 13707.7 1 6 CACCTG CGTTTCTCCATTGTCTTCTG - +4 dbcorrdb__EP300__ENCSR000AQB_1__m6-nej 3 0.560574 13707.7 1 6 CACCTG CAACGCTTGTTCTGATGCCG - +4 dbcorrdb__EP300__ENCSR000BLM_1__m1-bin-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 1 0.560574 13707.7 1 6 CACCTG GGAACTGTTTGCTCAGCCAC - +4 dbcorrdb__EP300__ENCSR000BMA_1__m3-nej 8 0.560574 13707.7 1 6 CACCTG ATTAATTACAGCTGACAGGA - +4 dbcorrdb__MAX__ENCSR000EEZ_1__m1-Brf-brm-btd-cnc-CrebB-E2f1-ERR-E(z)-Max-Mitf-Myc-Nelf-E-RpII215-Sap30-Sin3A-Spps-SREBP-Stat92E-tgo-Usf-vtd-zfh1 6 0.560574 13707.7 1 6 CACCTG GGCGGCCACGTGGGCCGGGC - +4 dbcorrdb__POLR2A__ENCSR000BQB_1__m2-pho-phol-RpII215-Taf1 3 0.560574 13707.7 1 6 CACCTG GCCTTCCGGCCGCCGTTTTG - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIL_1__m2 10 0.560574 13707.7 1 6 CACCTG TCTCGTGCGCCATCTTAGCT - +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m4-egg 0 0.560574 13707.7 1 6 CACCTG TGCCGCACTGGGAACATACT - +4 dbcorrdb__SIX5__ENCSR000BRL_1__m1-bi-egg-Hcf-mor-Six4 8 0.560574 13707.7 1 6 CACCTG GACTACAATTCCCAGAAGGC - +4 dbcorrdb__ZNF274__ENCSR000EVX_1__m5-bon 6 0.560574 13707.7 1 6 CACCTG GTTTCTCACCAGTGTGAGTT - +4 homer__NNNGCATGTCCNGACATGCC_p63 10 0.560574 13707.7 1 6 CACCTG GGCATGTCCGGACATGCCTT - +4 yetfasco__YBR240C_1449 14 0.560574 13707.7 1 6 CACCTG GCGGGTTTTTTGGACGCCGT - +4 dbcorrdb__HDAC2__ENCSR000AQG_1__m2-HDAC1 15 0.560574 13707.7 1 5 CACCTG GAGCCTCAGCTTGCGCATCT - +4 taipale_cyt_meth__ZBTB43_NGTGCCNNNNNNNYAGCACN_eDBD_meth 16 0.560574 13707.7 1 4 CACCTG AGTGCCATAAAGGCAGCACT + +4 transfac_pro__M06903-CG9609 5 0.560723 13711.4 1 6 CACCTG GTGGTAACGGTTTGAATGGGGATCC + +4 hocomoco__ZN140_HUMAN.H11MO.0.C 18 0.562654 13758.6 1 6 CACCTG TATGACCCAGCAATTCCGCTCCTA + +4 tfdimers__MD00362 8 0.562654 13758.6 1 6 CACCTG AGATTTTAATCCTAGAAACATATA - +4 jaspar__MA0386.1-Tbp-Trf-Trf2 12 0.562736 13760.6 1 6 CACCTG ATCGAATATATATATCTAGTC - +4 transfac_pro__M01524-Tbp-Trf-Trf2 12 0.562736 13760.6 1 6 CACCTG ATCGAATATATATATCTAGTC - +4 transfac_pro__M09431 9 0.562736 13760.6 1 6 CACCTG GGTGGGACCCACGGCAAATGG - +4 transfac_pro__M05262 17 0.562736 13760.6 1 4 CACCTG CCCCGGCGACAGGAACCAACC - +4 factorbook__NFY-CG7839-Chd1-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay-yps 0 0.563055 13768.4 1 6 CACCTG CCTCTGATTGGCTGG + +4 jaspar__MA0527.1-Chd1-CoRest 9 0.563055 13768.4 1 6 CACCTG CTCTCGCGAGATCTG + +4 neph__UW.Motif.0374 3 0.563055 13768.4 1 6 CACCTG CCAGATCTGTTTTCA + +4 taipale__ZIC3_full_GACCCCCYGYTGNGN-lmd-opa 0 0.563055 13768.4 1 6 CACCTG GACCCCCCGCTGCGC + +4 taipale_cyt_meth__ZIC1_NMCCMCCYGCTGYGN_FL-lmd-opa 0 0.563055 13768.4 1 6 CACCTG GACCCCCCGCTGTGC + +4 taipale_cyt_meth__ZNF771_NRCGCTAACCATTRN_FL_meth-CG6654-CG7372 6 0.563055 13768.4 1 6 CACCTG TGCGCTAACCACTGC + +4 taipale_tf_pairs__FOXJ2_HOXB13_RTAAACAYNRTAAAN_CAP 3 0.563055 13768.4 1 6 CACCTG GTAAACATCATAAAA + +4 transfac_pro__M07669-Atf6-CrebA-CrebB-Xbp1 9 0.563055 13768.4 1 6 CACCTG TTGCCACGTCATCAC + +4 cisbp__M2293-Atf6-crc-CrebA-Jra-kay-Xbp1 3 0.563055 13768.4 1 6 CACCTG GATGACATCATCTTT - +4 cisbp__M2323-Chd1-CoRest 9 0.563055 13768.4 1 6 CACCTG CTCTCGCGAGATCTG - +4 cisbp__M5964-lmd-opa 0 0.563055 13768.4 1 6 CACCTG GACCCCCCGCTGCGC - +4 cisbp__M5965-lmd-opa 3 0.563055 13768.4 1 6 CACCTG GACCCCCCGCTGTGC - +4 jaspar__MA0492.1-Atf3-Atf6-CrebA-Jra-Xbp1-crc-kay 3 0.563055 13768.4 1 6 CACCTG GATGACATCATCTTT - +4 transfac_pro__M09073 7 0.563055 13768.4 1 6 CACCTG CCACCTCCACCGACA - +4 transfac_pro__M09293-Myb 8 0.563055 13768.4 1 6 CACCTG CTAACGGTCATATTT - +4 transfac_pro__M09357 0 0.563055 13768.4 1 6 CACCTG TGCTTGTTCTGCAAG - +4 transfac_pro__M09397 0 0.563055 13768.4 1 6 CACCTG AGCGTGAAGAAGAAG - +4 transfac_pro__M09400 0 0.563055 13768.4 1 6 CACCTG TGCTTGTGTTTCAAG - +4 transfac_pro__M09538-Atf6-CrebA-Xbp1 8 0.563055 13768.4 1 6 CACCTG TGCCACGTCAGCATC - +4 neph__UW.Motif.0442 -1 0.563055 13768.4 1 5 CACCTG ACAGAGAGAAAAATG + +4 neph__UW.Motif.0558 10 0.563055 13768.4 1 5 CACCTG AAGAAAAAAAAACCA + +4 homer__GTTGCCATGGCAACM_Rfx2-CG5846-CG9727-Max-Rfx-SREBP 11 0.563055 13768.4 1 4 CACCTG GTTGCCATGGCAACC + +4 taipale_tf_pairs__TEAD4_SPDEF_RGWATSCGGATGNNNNTCCKNNN_CAP_repr-Ets98B-sd 9 0.563685 13783.8 1 6 CACCTG AACCGGATACACATCCGCATTCC - +4 tfdimers__MD00115-E2f1-usp 6 0.563741 13785.2 1 6 CACCTG AAATCTGAACTGAAACTAAAAT - +4 tfdimers__MD00547-foxo-TfAP-2 6 0.563741 13785.2 1 6 CACCTG CTCACAGTCCATCTGGCTTATC - +4 transfac_pro__M09112 5 0.563741 13785.2 1 6 CACCTG GAATAAATCTCAACCGTTGATT - +4 cisbp__M5906-sd 3 0.563779 13786.1 1 6 CACCTG ACATTCCTCGCATTCCA + +4 cisbp__M6538 11 0.563779 13786.1 1 6 CACCTG AGCAGTGGGTCCCCCAG + +4 hocomoco__NFIC_HUMAN.H11MO.0.A-C15-Nf1-NfI-tll 10 0.563779 13786.1 1 6 CACCTG CTTGGCTCCCTGCCAAG + +4 transfac_pro__M01422-al-Awh-CG18599-E5-ems-en-eve-inv-lab-unpg-zfh2 1 0.563779 13786.1 1 6 CACCTG TCCACTAATTAGCGGTT + +4 transfac_pro__M02937 7 0.563779 13786.1 1 6 CACCTG TACGAGACTCCTCTAAC + +4 cisbp__M5006-Hey 4 0.563779 13786.1 1 6 CACCTG GGGGCACGTGTCGGCGG - +4 taipale_tf_pairs__TEAD4_GATA3_NGATAASNNNRGWATGY_CAP_repr-GATAe-grn-pnr-sd 3 0.563779 13786.1 1 6 CACCTG ACATTCCTTCCTTATCT - +4 transfac_pro__M02756-GATAd-GATAe-grn-pnr-srp 2 0.563779 13786.1 1 6 CACCTG ATCTTCTTATCAGTTTA - +4 transfac_pro__M05400 12 0.563779 13786.1 1 5 CACCTG TTTCGAACGACAAACTT - +4 cisbp__M6442-luna-Pur-alpha 13 0.563779 13786.1 1 4 CACCTG CCCTGCCCCCCCCTTCC + +4 hocomoco__PURA_HUMAN.H11MO.0.D-Pur-alpha-luna 13 0.563779 13786.1 1 4 CACCTG CCCTGCCCCCCCCTTCC - +4 cisbp__M4395 5 0.563791 13786.4 1 6 CACCTG CTTATCTCCGC + +4 cisbp__M5649-Myb 2 0.563791 13786.4 1 6 CACCTG ATAACCGTTAA + +4 hocomoco__NRL_HUMAN.H11MO.0.D-maf-S-tj 4 0.563791 13786.4 1 6 CACCTG TGCTGACGCAG + +4 jaspar__MA0439.1 5 0.563791 13786.4 1 6 CACCTG CTTATCTCCGC + +4 predrem__nrMotif2652 4 0.563791 13786.4 1 6 CACCTG TAGGGAGCTGG + +4 taipale_cyt_meth__FOXO3_NTCCCCACACN_eDBD_meth_repr-foxo 5 0.563791 13786.4 1 6 CACCTG TTCCCCACACG + +4 taipale_cyt_meth__KLF2_NRCCACRCCCN_eDBD-btd-cbt-CG3065-CG42741-dar1-luna-Sp1-Spps 5 0.563791 13786.4 1 6 CACCTG CACCACGCCCA + +4 transfac_pro__M01957 5 0.563791 13786.4 1 6 CACCTG CTTATCTCCGC + +4 transfac_pro__M09477 4 0.563791 13786.4 1 6 CACCTG CGTTGACTTTG + +4 c2h2_zfs__M0404 5 0.563791 13786.4 1 6 CACCTG TAGCGCACACT - +4 cisbp__M1308 4 0.563791 13786.4 1 6 CACCTG ACGGAATCTAC - +4 cisbp__M4922-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)m8-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.563791 13786.4 1 6 CACCTG TGGCACGTGCC - +4 cisbp__M5059-kni-knrl 0 0.563791 13786.4 1 6 CACCTG AAACTAGGGCA - +4 cisbp__M6127-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 5 0.563791 13786.4 1 6 CACCTG GGCCCCACCCA - +4 jaspar__MA0062.2-Atac3-Eip74EF-Ets21C-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-bs-pnt 2 0.563791 13786.4 1 6 CACCTG GCCACTTCCGG - +4 taipale_cyt_meth__ERG_NACMGGAARTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.563791 13786.4 1 6 CACCTG CATTTCCGGTC - +4 hocomoco__BACH2_MOUSE.H11MO.0.A-Jra-cnc-ewg-kay-maf-S-nej -1 0.563791 13786.4 1 5 CACCTG TGCTGAGTCAT + +4 hocomoco__SOX10_MOUSE.H11MO.1.A-Mad-Sox14-Sox100B-Sox102F-SoxN -1 0.563791 13786.4 1 5 CACCTG GCCTTTGTTCT + +4 transfac_pro__M05186 -1 0.563791 13786.4 1 5 CACCTG ACATCGCATAC - +4 hocomoco__SOX9_MOUSE.H11MO.1.A-Sox14-Sox100B-SoxN -2 0.563791 13786.4 1 4 CACCTG CCTTTGTTCTC + +4 taipale_cyt_meth__HOXA10_NGYAATAAAAN_eDBD_meth-abd-A-Abd-B-cad-eve-Ubx 7 0.563791 13786.4 1 4 CACCTG GTTTTATTACC - +4 transfac_pro__M05597 7 0.563791 13786.4 1 4 CACCTG TCCGCTTTACA - +4 cisbp__M3079-gem -3 0.563791 13786.4 1 3 CACCTG CTGGGTTGTGC + +4 tfdimers__MD00258-nub-pdm2 18 0.564293 13798.7 1 6 CACCTG GGAAAAAAAATGCAAATCCTCCTTTTATT + +4 tfdimers__MD00529 10 0.564293 13798.7 1 6 CACCTG CCCCCTGGCTTCCCTGTGTTCTTTCTCCT + +4 cisbp__M1173-CG34367-OdsH-Vsx2-al-repo-unc-4 1 0.564744 13809.7 1 6 CACCTG TTAATTGG + +4 taipale_cyt_meth__EN1_NTCGTTAN_eDBD_meth_repr-en-inv 0 0.564744 13809.7 1 6 CACCTG CTCGTTAG + +4 taipale_cyt_meth__HESX1_CTAATTAN_FL_meth 1 0.564744 13809.7 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__PRRX2_MTCGTTAN_FL_meth-CG4328-Lim3-Lmx1a-Vsx1-Vsx2 0 0.564744 13809.7 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__UNCX_NTCGTTAN_eDBD_meth-OdsH-repo-unc-4 0 0.564744 13809.7 1 6 CACCTG CGCGTTAA + +4 transfac_pro__M01909 0 0.564744 13809.7 1 6 CACCTG TTCCCGGG + +4 yetfasco__YCL067C_2079 2 0.564744 13809.7 1 6 CACCTG ATTACACG + +4 cisbp__M0624 2 0.564744 13809.7 1 6 CACCTG GAAACATT - +4 cisbp__M1485 2 0.564744 13809.7 1 6 CACCTG GACACAAA - +4 jaspar__MA0358.1 0 0.564744 13809.7 1 6 CACCTG TTCCCGGG - +4 transfac_pro__M00658 1 0.564744 13809.7 1 6 CACCTG CTTCCTCT - +4 transfac_pro__M07826-abd-A-Antp-bsh-btn-Dfd-Dr-E5-ems-eve-ftz-ind-lab-pb-Scr-Ubx-zen-zen2 1 0.564744 13809.7 1 6 CACCTG TTAATTAC - +4 cisbp__M1725 3 0.564744 13809.7 1 5 CACCTG AACTTCCG + +4 cisbp__M5135-Optix 3 0.564744 13809.7 1 5 CACCTG TATCACTT - +4 hdpi__ZFP3 3 0.564744 13809.7 1 5 CACCTG AAATTACT - +4 predrem__nrMotif739 3 0.564744 13809.7 1 5 CACCTG ACTCAGCA - +4 transfac_pro__M01797-brm-CoRest-GATAe-grn-HLH3B-pnr-Sirt6-srp 3 0.564744 13809.7 1 5 CACCTG CCTTATCT - +4 cisbp__M4826-CG15601 4 0.564744 13809.7 1 4 CACCTG TTTCAATC + +4 predrem__nrMotif2080 4 0.564744 13809.7 1 4 CACCTG ACTCACCC + +4 predrem__nrMotif2111 -2 0.564744 13809.7 1 4 CACCTG CTTTTGTA + +4 cisbp__M4982-GATAd -2 0.564744 13809.7 1 4 CACCTG CCTTATCA - +4 predrem__nrMotif2441 -3 0.564744 13809.7 1 3 CACCTG CTGCAGTA + +4 jaspar__MA0337.1-klu-sr 0 0.565301 13823.3 1 6 CACCTG CCCCCGC + +4 predrem__nrMotif1383 1 0.565301 13823.3 1 6 CACCTG GAGCTTG + +4 predrem__nrMotif380 1 0.565301 13823.3 1 6 CACCTG ACCCCAC + +4 hdpi__OLIG1 0 0.565301 13823.3 1 6 CACCTG CATCTGG - +4 predrem__nrMotif1542 1 0.565301 13823.3 1 6 CACCTG AAACCCC - +4 predrem__nrMotif654 1 0.565301 13823.3 1 6 CACCTG AGTCCTC - +4 transfac_pro__M01961-klu-sr 0 0.565301 13823.3 1 6 CACCTG CCCCCGC - +4 jaspar__MA0305.1 2 0.565301 13823.3 1 5 CACCTG GCTTCCT + +4 predrem__nrMotif1487 2 0.565301 13823.3 1 5 CACCTG CTTAACA + +4 tiffin__TIFDMEM0000090 -1 0.565301 13823.3 1 5 CACCTG ACATTTT + +4 transfac_pro__M01108-abd-A-Ubx 2 0.565301 13823.3 1 5 CACCTG CCAATCT + +4 transfac_pro__M01669 2 0.565301 13823.3 1 5 CACCTG GCTTCCT + +4 predrem__nrMotif1282 2 0.565301 13823.3 1 5 CACCTG TTTAACA - +4 predrem__nrMotif2490 2 0.565301 13823.3 1 5 CACCTG CATAGCA - +4 transfac_pro__M01884 2 0.565301 13823.3 1 5 CACCTG TTCACTT - +4 transfac_pro__M06190-CG9609 2 0.565301 13823.3 1 5 CACCTG GACCCCT - +4 transfac_pro__M01265 3 0.565301 13823.3 1 4 CACCTG TATCACT + +4 fantom__motif84_GGKTTYT 3 0.565301 13823.3 1 4 CACCTG AGAACCC - +4 predrem__nrMotif1581 3 0.565301 13823.3 1 4 CACCTG GGGAACA - +4 scertf__badis.FKH2-FoxP-bin-croc-fd59A-fkh-foxo-slp2 4 0.565301 13823.3 1 3 CACCTG TGTTTAC - +4 hdpi__ANXA11 0 0.567871 13886.1 1 6 CACCTG CTCCTC - +4 cisbp__M1887 1 0.567871 13886.1 1 5 CACCTG TCCCCA - +4 hdpi__BAX 2 0.567871 13886.1 1 4 CACCTG GACATC + +4 cisbp__M5325-Atf6-CrebA-CrebB-Xbp1 4 0.568083 13891.3 1 6 CACCTG TGATGACGTGGCAT + +4 cisbp__M5389-ap-Awh-bs-bsh-CG18599-CG34367-CG9876-E5-ems-en-eve-gsb-gsb-n-ind-inv-lbl-OdsH-otp-pdm3-Pph13-prd-ro-Rx-unpg-Vsx1-Vsx2 4 0.568083 13891.3 1 6 CACCTG TAATTAGCTAATTA + +4 cisbp__M5647-Myb 6 0.568083 13891.3 1 6 CACCTG AACGGTTAACGGTT + +4 taipale_cyt_meth__IRF5_NYGAAACCGAAACY_FL 4 0.568083 13891.3 1 6 CACCTG CCGAAACCGAAACT + +4 transfac_pro__M00916-Atf3-Atf6-CrebB-Jra-kay-Xbp1 8 0.568083 13891.3 1 6 CACCTG GGTTACGTCAGCGC + +4 transfac_pro__M09314-Myb 0 0.568083 13891.3 1 6 CACCTG TAACCGTAATAACC + +4 transfac_pro__M09475-tll 6 0.568083 13891.3 1 6 CACCTG GTCGTTGACTTTTT + +4 transfac_public__M00475-foxo-FoxP-slp2 8 0.568083 13891.3 1 6 CACCTG GTGTTGTTTACAAC + +4 cisbp__M2595-FoxP-foxo-slp2 8 0.568083 13891.3 1 6 CACCTG GTGTTGTTTACAAC - +4 cisbp__M6287-Hsf-pb 6 0.568083 13891.3 1 6 CACCTG TTCTAGAACATTCT - +4 hocomoco__GABPA_HUMAN.H11MO.0.A-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-RpII215-Sin3A-Taf1-aop-bs-dl-pnt 1 0.568083 13891.3 1 6 CACCTG CCACTTCCGGTTCC - +4 taipale__EMX2_DBD_YMATTARYTAATKR-ap-Awh-bs-bsh-CG18599-CG34367-CG9876-E5-ems-en-eve-gsb-gsb-n-ind-inv-lbl-Lim3-OdsH-otp-pdm3-Pph13-prd-ro-Rx-unpg-Vsx1-Vsx2 4 0.568083 13891.3 1 6 CACCTG TAATTAGCTAATTA - +4 taipale_tf_pairs__ETV2_HOXA2_NCCGGAAGTMATTA_CAP_repr-pb-pnt 4 0.568083 13891.3 1 6 CACCTG TAATTACTTCCGGT - +4 transfac_pro__M02881-Max 4 0.568083 13891.3 1 6 CACCTG CAGTCGCGTGGCAC - +4 transfac_pro__M09032 1 0.568083 13891.3 1 6 CACCTG CCACCGACAAAATT - +4 hocomoco__LEF1_HUMAN.H11MO.0.A-Mad-SoxN-pan -1 0.568083 13891.3 1 5 CACCTG TCCTTTGATTTGCT + +4 transfac_pro__M00488-Dref -1 0.568083 13891.3 1 5 CACCTG AGCTATCGATATAT + +4 hocomoco__HNF4A_HUMAN.H11MO.0.A-EcR-HDAC1-Hnf4-Hr78-Spps-btd-eg-kni-knrl-nej-svp-usp 9 0.568083 13891.3 1 5 CACCTG TGGACTTTGGACTC - +4 cisbp__M4819-CG12768 3 0.568991 13913.5 1 6 CACCTG TTTTACCAACAT + +4 cisbp__M6155-Atf6 5 0.568991 13913.5 1 6 CACCTG GTGGTGACGTGG + +4 predrem__nrMotif230 0 0.568991 13913.5 1 6 CACCTG TGCTTGCTTTTT + +4 scertf__morozov.ARG80-bs 1 0.568991 13913.5 1 6 CACCTG TTTCCGCACGAG + +4 taipale__FOXO4_DBD_TTTCCCCACACG-foxo 6 0.568991 13913.5 1 6 CACCTG TTTCCCCACACG + +4 taipale__TEF_FL_NRTTACRTAAYN-CG7786-gt-hng1-Pdp1-vri 3 0.568991 13913.5 1 6 CACCTG TATTACATAACA + +4 taipale_cyt_meth__KLF15_NCCMCGCCCMYN_FL-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.568991 13913.5 1 6 CACCTG GCCACGCCCCCC + +4 taipale_tf_pairs__E2F3_DRGX_SGCGCTAATTKN_CAP_repr-CG11294-Drgx-E2f1 5 0.568991 13913.5 1 6 CACCTG GGCGCTAATTGC + +4 tiffin__TIFDMEM0000111 5 0.568991 13913.5 1 6 CACCTG AAAAATACTAAA + +4 transfac_pro__M05274 3 0.568991 13913.5 1 6 CACCTG TGACACGTGGCT + +4 transfac_pro__M06503 6 0.568991 13913.5 1 6 CACCTG ATGGCACGCCTC + +4 transfac_pro__M07459-Hsf 4 0.568991 13913.5 1 6 CACCTG GAACCTTCTGGA + +4 homer__NGCGTGGGCGGR_Egr2-klu-sr 6 0.568991 13913.5 1 6 CACCTG CCCGCCCACGCA - +4 homer__NGRTGACGTCAY_Atf7-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 2 0.568991 13913.5 1 6 CACCTG ATGACGTCATCG - +4 jaspar__MA0940.1 0 0.568991 13913.5 1 6 CACCTG TTCCATTTTTGG - +4 predrem__nrMotif2676 4 0.568991 13913.5 1 6 CACCTG CGGAGACCCGGG - +4 predrem__nrMotif455 4 0.568991 13913.5 1 6 CACCTG CCCCCACCCCCG - +4 taipale_cyt_meth__FOXQ1_NTAYRTAAACAN_eDBD-croc-fd59A-fkh-FoxK-FoxP-slp1-slp2 5 0.568991 13913.5 1 6 CACCTG TTGTTTATATAA - +4 taipale_cyt_meth__TEF_NRTTAYGTAAYN_eDBD_meth-CG7786-gt-hng1-Pdp1-slbo-vri 3 0.568991 13913.5 1 6 CACCTG CGTTACATAACA - +4 taipale_tf_pairs__ETV5_EOMES_TNRCACCGGAWN_CAP-Ets96B 1 0.568991 13913.5 1 6 CACCTG CTTCCGGTGTGA - +4 transfac_pro__M05752 6 0.568991 13913.5 1 6 CACCTG TCACCACCCCGA - +4 transfac_pro__M06387 6 0.568991 13913.5 1 6 CACCTG GCGTTTTTCCCG - +4 transfac_pro__M06533 1 0.568991 13913.5 1 6 CACCTG TCACCGGCAACA - +4 transfac_pro__M06616 6 0.568991 13913.5 1 6 CACCTG TCCGTGGCCCTG - +4 transfac_pro__M06795 2 0.568991 13913.5 1 6 CACCTG GCTTCCTTCCCG - +4 transfac_pro__M06834 6 0.568991 13913.5 1 6 CACCTG TCGGAAAAACAA - +4 cisbp__M1874 7 0.568991 13913.5 1 5 CACCTG AAACAAACATCC + +4 swissregulon__hs__LEF1_TCF7_TCF7L1_2.p2-pan -1 0.568991 13913.5 1 5 CACCTG CCCTTTGATCTT + +4 taipale_cyt_meth__GATA3_NGATAACGATCW_FL-GATAe-grn-pnr-srp 7 0.568991 13913.5 1 5 CACCTG AGATAACGATCT + +4 taipale_cyt_meth__GATA5_WGATAACGATCT_eDBD-GATAe-grn-pnr-srp 7 0.568991 13913.5 1 5 CACCTG AGATAACGATCT + +4 tiffin__TIFDMEM0000119 -1 0.568991 13913.5 1 5 CACCTG AACTTAAAAATA + +4 transfac_pro__M06719 -1 0.568991 13913.5 1 5 CACCTG TCGTAAAAAAGA + +4 transfac_pro__M01587-klu -1 0.568991 13913.5 1 5 CACCTG CCCTCCTCCCCC - +4 transfac_pro__M05860 7 0.568991 13913.5 1 5 CACCTG GCGGTAGTAACA - +4 transfac_pro__M06065 7 0.568991 13913.5 1 5 CACCTG TCTTTTTTAACA - +4 transfac_pro__M06408 7 0.568991 13913.5 1 5 CACCTG TCCGTTTTACGC - +4 transfac_pro__M06523 7 0.568991 13913.5 1 5 CACCTG TCGCATTCTCCA - +4 transfac_pro__M06611 7 0.568991 13913.5 1 5 CACCTG GCTGACCCACTC - +4 transfac_pro__M06848-crol 7 0.568991 13913.5 1 5 CACCTG GCTTTCGCAGCT - +4 transfac_pro__M06421 8 0.568991 13913.5 1 4 CACCTG GGGGAGAAAACC + +4 transfac_pro__M06902 8 0.568991 13913.5 1 4 CACCTG TTTATAAAAAAC + +4 transfac_pro__M01850 8 0.568991 13913.5 1 4 CACCTG TGGGGGCCCACA - +4 transfac_pro__M06143-crol 8 0.568991 13913.5 1 4 CACCTG TCTTAAGCAACG - +4 transfac_pro__M06183 8 0.568991 13913.5 1 4 CACCTG GCTCCTTGCACG - +4 transfac_pro__M06534 -2 0.568991 13913.5 1 4 CACCTG CCGCCGGCCCCA - +4 transfac_pro__M06640 8 0.568991 13913.5 1 4 CACCTG TCCGATTTCACG - +4 transfac_pro__M06986 -2 0.568991 13913.5 1 4 CACCTG CCTTTTAGAAGG - +4 tfdimers__MD00173-Dbx 14 0.569132 13917 1 6 CACCTG TTTAATTAATAATTAACTTTTTAATTTA + +4 scertf__zhao.RDS2 -1 0.56985 13934.5 1 5 CACCTG TCCGA + +4 cisbp__M5919-TfAP-2 1 0.570224 13943.7 1 6 CACCTG TGCCCTGAGGGCA + +4 cisbp__M6419 0 0.570224 13943.7 1 6 CACCTG CATCAATCAAGCT + +4 hocomoco__P53_HUMAN.H11MO.1.A 5 0.570224 13943.7 1 6 CACCTG GGACATGCCTGGG + +4 hocomoco__SOX2_HUMAN.H11MO.0.A-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN-pan 0 0.570224 13943.7 1 6 CACCTG TCCCTTTGTTCTC + +4 neph__UW.Motif.0260 6 0.570224 13943.7 1 6 CACCTG ACAGTGTATCTGG + +4 swissregulon__hs__NFE2L2.p2-Jra-cnc-kay-maf-S 0 0.570224 13943.7 1 6 CACCTG CTGCTGAGTCATG + +4 taipale__TFAP2C_full_NGCCNNNNNGGCN-TfAP-2 0 0.570224 13943.7 1 6 CACCTG TGCCCTGAGGGCA + +4 taipale_cyt_meth__ZNF460_NRMCGCCCCCCGN_eDBD_meth 7 0.570224 13943.7 1 6 CACCTG CAACGCCCCCCGC + +4 transfac_pro__M05410 3 0.570224 13943.7 1 6 CACCTG GGGGACACGAGGC + +4 transfac_pro__M07951-lmd-sug 0 0.570224 13943.7 1 6 CACCTG GACCCCCCACGAA + +4 cisbp__M4151 6 0.570224 13943.7 1 6 CACCTG CGGCTCTATCATC - +4 cisbp__M5924-TfAP-2 0 0.570224 13943.7 1 6 CACCTG TGCCCTGAGGGCA - +4 cisbp__M6102-TfAP-2 0 0.570224 13943.7 1 6 CACCTG TGCCCTCAGGGCA - +4 hocomoco__ELF2_HUMAN.H11MO.0.C-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-Hcf-Hr78-RpII215-Sin3A-aop-bs-dl-nej-pnt 0 0.570224 13943.7 1 6 CACCTG CCACTTCCGGGTT - +4 taipale__TFAP2B_DBD_NSCCNNNNNGGSN-TfAP-2 0 0.570224 13943.7 1 6 CACCTG TGCCCTCAGGGCA - +4 taipale_tf_pairs__ERF_FOXI1_TGTTKMCGGAWRN_CAP_repr-Ets21C 2 0.570224 13943.7 1 6 CACCTG ACTTCCGTAAACA - +4 taipale_tf_pairs__FOXO1_SPDEF_WMSCGGATGTKNW_CAP_repr-Ets98B-foxo 2 0.570224 13943.7 1 6 CACCTG AAAACATCCGGGT - +4 transfac_pro__M09487-tll 6 0.570224 13943.7 1 6 CACCTG GTCGTTGACTTTT - +4 taipale_tf_pairs__ETV2_ETV7_NSMGGACGGAYNTCCKSN_CAP-aop-pnt 11 0.570269 13944.8 1 6 CACCTG ACCGGACGGATTTCCGCG + +4 transfac_pro__M05888 8 0.570269 13944.8 1 6 CACCTG CCATTGTTCACCCACTCT - +4 transfac_pro__M06193 0 0.570269 13944.8 1 6 CACCTG TCCCTACTTTTTTACTTC - +4 transfac_pro__M06427 8 0.570269 13944.8 1 6 CACCTG CCATTGTTCACCCACTCT - +4 transfac_pro__M09380 0 0.570269 13944.8 1 6 CACCTG AACGTGGAGATCACGGCA - +4 taipale__MGA_DBD_GGYGTGANNNNTCACRCC_repr-bi-byn 14 0.570269 13944.8 1 4 CACCTG GGTGTGAAATTTCACACC + +4 cisbp__M5630-bi-byn 14 0.570269 13944.8 1 4 CACCTG GGTGTGAAATTTCACACC - +4 cisbp__M0317-CG7786-gt-Pdp1-vri 3 0.570723 13955.9 1 6 CACCTG TATTACGTAA + +4 cisbp__M0473 1 0.570723 13955.9 1 6 CACCTG GCGCACGGAC + +4 cisbp__M0700-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215 0 0.570723 13955.9 1 6 CACCTG GACCGGAAGT + +4 cisbp__M1612 2 0.570723 13955.9 1 6 CACCTG CCCACTAAAA + +4 hdpi__DDEFL1-Asap 2 0.570723 13955.9 1 6 CACCTG GTAAATTACT + +4 jaspar__MA1001.1-Taf1-lid 1 0.570723 13955.9 1 6 CACCTG GCGCCGCCAT + +4 predrem__nrMotif2366 3 0.570723 13955.9 1 6 CACCTG ACAGATCTCT + +4 taipale_cyt_meth__KLF16_NCCACRCCCN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.570723 13955.9 1 6 CACCTG GCCACGCCCC + +4 taipale_cyt_meth__NPAS2_NMCAYGYGYN_eDBD_meth-Clk 0 0.570723 13955.9 1 6 CACCTG GACATGTGTA + +4 taipale_tf_pairs__TCF15_NACAYATGNN_HT-CG33557 2 0.570723 13955.9 1 6 CACCTG AACACATGGT + +4 cisbp__M0409 4 0.570723 13955.9 1 6 CACCTG TAATCCCCAC - +4 cisbp__M1263 2 0.570723 13955.9 1 6 CACCTG GTTTCCGTTT - +4 cisbp__M1381 1 0.570723 13955.9 1 6 CACCTG CCAGCGGTAA - +4 cisbp__M1511 4 0.570723 13955.9 1 6 CACCTG GGGGGGCCTA - +4 cisbp__M5517 2 0.570723 13955.9 1 6 CACCTG GTTAACTAGT - +4 jaspar__MA0623.1-Fer3-HLH54F-Oli-amos-ato-da-dimm-tap-twi 0 0.570723 13955.9 1 6 CACCTG ACCATATGGT - +4 predrem__nrMotif1596 0 0.570723 13955.9 1 6 CACCTG TTCCATGACA - +4 stark__VVVBTAATCC-bcd 4 0.570723 13955.9 1 6 CACCTG GGATTAGTTT - +4 transfac_pro__M01845 0 0.570723 13955.9 1 6 CACCTG TATCTCCAAT - +4 transfac_pro__M01976-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-Hr78-pnt 0 0.570723 13955.9 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M01984-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.570723 13955.9 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02053-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.570723 13955.9 1 6 CACCTG TATTTCCGGG - +4 transfac_pro__M02078 3 0.570723 13955.9 1 6 CACCTG CACTTCCTCT - +4 transfac_pro__M04931 0 0.570723 13955.9 1 6 CACCTG CAGCTGCCCC - +4 transfac_pro__M07063-btd-CG42741-CTCF-dar1-kay-luna-Nf-YA-Nf-YB-Spps-Stat92E 0 0.570723 13955.9 1 6 CACCTG GCCCCGCCCC - +4 cisbp__M1529-CG9727-Rfx -1 0.570723 13955.9 1 5 CACCTG CCATAGCAAC + +4 predrem__nrMotif1708 5 0.570723 13955.9 1 5 CACCTG TTGTCCACTT + +4 cisbp__M0924-pdm3 -1 0.570723 13955.9 1 5 CACCTG AGCTCATTAT - +4 predrem__nrMotif113 -1 0.570723 13955.9 1 5 CACCTG CCCTCACTCA - +4 predrem__nrMotif2647 5 0.570723 13955.9 1 5 CACCTG AACTACATCT - +4 transfac_pro__M05492-CG11085-slou -1 0.570723 13955.9 1 5 CACCTG TCCTTATTAT - +4 transfac_pro__M06279 5 0.570723 13955.9 1 5 CACCTG TCTGACGCCT - +4 cisbp__M1267 6 0.570723 13955.9 1 4 CACCTG AACCGAAACT + +4 hocomoco__FOXO3_MOUSE.H11MO.0.B-FoxK-FoxP-fd59A-fkh-foxo-slp2 6 0.570723 13955.9 1 4 CACCTG CCTGTTTACA + +4 predrem__nrMotif1088 6 0.570723 13955.9 1 4 CACCTG AAAGAATACA + +4 transfac_pro__M00684 6 0.570723 13955.9 1 4 CACCTG TCTGAGGAAC + +4 predrem__nrMotif125 -2 0.570723 13955.9 1 4 CACCTG GCTGTGGAAA - +4 predrem__nrMotif1473 6 0.570723 13955.9 1 4 CACCTG TTCATTTACT - +4 cisbp__M0887-ind-pb-Ubx 2 0.571461 13973.9 1 6 CACCTG CCTAATGAG + +4 cisbp__M1031-Gsc-oc-Ptx1 2 0.571461 13973.9 1 6 CACCTG TTAATCCCC + +4 cisbp__M1768 3 0.571461 13973.9 1 6 CACCTG TAACTCCGA + +4 cisbp__M5172-Bgb-lz-run-RunxA-RunxB 1 0.571461 13973.9 1 6 CACCTG TAACCGCAA + +4 flyfactorsurvey__run_Bgb_NBT_FBgn0003300-Bgb-RunxA-RunxB-lz-run 1 0.571461 13973.9 1 6 CACCTG TAACCGCAA + +4 predrem__nrMotif1109 1 0.571461 13973.9 1 6 CACCTG CCATCTGCA + +4 predrem__nrMotif1540 2 0.571461 13973.9 1 6 CACCTG CTGACTTCA + +4 predrem__nrMotif1673 1 0.571461 13973.9 1 6 CACCTG TAACATCAT + +4 predrem__nrMotif1676 2 0.571461 13973.9 1 6 CACCTG AGAAACTCA + +4 predrem__nrMotif2488 0 0.571461 13973.9 1 6 CACCTG CACTTGACA + +4 transfac_pro__M05004 2 0.571461 13973.9 1 6 CACCTG TTTACCCCC + +4 yetfasco__YJR127C_575 1 0.571461 13973.9 1 6 CACCTG TTCCCCGCA + +4 cisbp__M0456-btd-cbt-CG3065-CG42741-dar1-hkb-luna-Sp1-Spps 3 0.571461 13973.9 1 6 CACCTG CCACGCCCA - +4 cisbp__M0917-Abd-B 3 0.571461 13973.9 1 6 CACCTG TTTTATGAG - +4 cisbp__M4323 1 0.571461 13973.9 1 6 CACCTG TTCCCCGCA - +4 elemento__CATGTCCAG 3 0.571461 13973.9 1 6 CACCTG CTGGACATG - +4 hocomoco__KLF8_HUMAN.H11MO.0.C-CG42741 0 0.571461 13973.9 1 6 CACCTG CACCCCCTG - +4 predrem__nrMotif505 1 0.571461 13973.9 1 6 CACCTG GAGCCTTCT - +4 predrem__nrMotif719 2 0.571461 13973.9 1 6 CACCTG CAGTCCTGA - +4 transfac_pro__M08824-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-pnr-pnt 3 0.571461 13973.9 1 6 CACCTG CACTTCCTG - +4 flyfactorsurvey__CG11504_SANGER_5_FBgn0039733-CG11504 4 0.571461 13973.9 1 5 CACCTG CAGCAACAT + +4 predrem__nrMotif116 4 0.571461 13973.9 1 5 CACCTG TTTCCAGCT + +4 predrem__nrMotif2334 -1 0.571461 13973.9 1 5 CACCTG ACCCTTGCC + +4 predrem__nrMotif2572 4 0.571461 13973.9 1 5 CACCTG ATTGCTCCT + +4 predrem__nrMotif2602 4 0.571461 13973.9 1 5 CACCTG TTTCCAACT + +4 predrem__nrMotif280 4 0.571461 13973.9 1 5 CACCTG ATTCAAACA + +4 predrem__nrMotif681 4 0.571461 13973.9 1 5 CACCTG AAATCCCCT + +4 predrem__nrMotif908 -1 0.571461 13973.9 1 5 CACCTG ACATGCTTT + +4 transfac_pro__M04923 -1 0.571461 13973.9 1 5 CACCTG AACTCTCGC + +4 transfac_pro__M05133 -1 0.571461 13973.9 1 5 CACCTG ACCGCCAGC + +4 cisbp__M0371 4 0.571461 13973.9 1 5 CACCTG ACTTGAACT - +4 cisbp__M4808-CG11504 4 0.571461 13973.9 1 5 CACCTG CAGCAACAT - +4 neph__UW.Motif.0037 4 0.571461 13973.9 1 5 CACCTG TGGCTGCCT - +4 predrem__nrMotif2322 -1 0.571461 13973.9 1 5 CACCTG ATCTTATTT - +4 predrem__nrMotif357 4 0.571461 13973.9 1 5 CACCTG CAGTGTCCT - +4 predrem__nrMotif725 4 0.571461 13973.9 1 5 CACCTG GGATTTCCT - +4 scertf__zhu.SRD1 4 0.571461 13973.9 1 5 CACCTG TGTAGATCT - +4 transfac_pro__M07051-NfI -1 0.571461 13973.9 1 5 CACCTG TCCTGCCAG - +4 fantom__motif158_SRCGWYACA 5 0.571461 13973.9 1 4 CACCTG CACGACACA + +4 hocomoco__FOXP2_HUMAN.H11MO.0.C-FoxP-fkh-foxo-slp2 5 0.571461 13973.9 1 4 CACCTG CTGTTTACA + +4 predrem__nrMotif147 5 0.571461 13973.9 1 4 CACCTG CCAAGAACA + +4 predrem__nrMotif1303 -2 0.571461 13973.9 1 4 CACCTG CCTCCCAAC - +4 predrem__nrMotif183 5 0.571461 13973.9 1 4 CACCTG CTGGAGACC - +4 predrem__nrMotif396 -2 0.571461 13973.9 1 4 CACCTG GCTGCGGGA - +4 tfdimers__MD00449-Dif-dl-pho-phol 17 0.573299 14018.9 1 6 CACCTG ATAAAAAGATGGGGAAATCCCCAATTT - +4 taipale_cyt_meth__ZIC5_NGACCCCCYGCTGTGM_eDBD_meth-opa 4 0.573341 14019.9 1 6 CACCTG AGACCCCCTGCTGTGA + +4 taipale_tf_pairs__MEIS1_EVX1_TGACANNNNNTCATTA_CAP_repr-eve 3 0.573341 14019.9 1 6 CACCTG TGACATCTAATCATTA + +4 transfac_pro__M00949-Mef2 1 0.573341 14019.9 1 6 CACCTG TTACTATATATAGTAA + +4 cisbp__M3225-ham 1 0.573341 14019.9 1 6 CACCTG TTATCTTATCTTATCT - +4 cisbp__M4718 5 0.573341 14019.9 1 6 CACCTG AAATTTTACTGTTTCA - +4 neph__UW.Motif.0440 8 0.573341 14019.9 1 6 CACCTG CTGGCGGCCTCCGCTG - +4 transfac_pro__M01593-brm-CTCF-ERR-E(z)-RpII215-tna-vtd 7 0.573341 14019.9 1 6 CACCTG GCGCCGCGGCCTGGGC - +4 transfac_pro__M02750-croc-fd59A-FoxK-foxo-FoxP-slp2 10 0.573341 14019.9 1 6 CACCTG AATTTTTGTTTACTAT - +4 transfac_pro__M07715-fd102C 6 0.573341 14019.9 1 6 CACCTG GCGAAGGACCGCAAGC - +4 cisbp__M5777-CG5846-CG9727-Max-Rfx-SREBP 12 0.573341 14019.9 1 4 CACCTG CGTTGCCATGGCAACG + +4 taipale_cyt_meth__RFX2_NGTTRCCATGGYAACN_eDBD_repr-CG5846-CG9727-Max-Rfx-SREBP 12 0.573341 14019.9 1 4 CACCTG CGTTGCCATGGCAACG - +4 tfdimers__MD00250-GATAe-grn-pho-phol-pnr-srp 7 0.573381 14020.9 1 6 CACCTG TTATTCTTATCTTTTATCTCCATTTTTTAACTTTAT + +4 cisbp__M2392-CG5846-CG9727-Max-Rfx-SREBP 2 0.57521 14065.6 1 6 CACCTG GTTGCCATGGCAACCGCGG + +4 taipale_tf_pairs__CUX1_FOXI1_RTAAACANNNNNATCRATN_CAP-ct 5 0.57521 14065.6 1 6 CACCTG GTAAACACGATAATCGATT + +4 transfac_pro__M01561 13 0.57521 14065.6 1 6 CACCTG TCGGGAAAAAAAAAACCGA + +4 transfac_pro__M05759 10 0.57521 14065.6 1 6 CACCTG GTCCGAAAGCAACCCGCGC + +4 transfac_pro__M07410-CG5846-CG9727-Max-Rfx-SREBP 2 0.57521 14065.6 1 6 CACCTG GTTGCCATGGCAACCGCGG + +4 taipale_tf_pairs__ETV5_EVX1_RSCGGWAATNNNNNATTAN_CAP_repr-Ets96B-eve 12 0.57521 14065.6 1 6 CACCTG CTAATGACCCATTTCCGCT - +4 transfac_pro__M09122-brm-CG7839-maf-S-orb-SREBP-vtd 3 0.57521 14065.6 1 6 CACCTG TTTTAACTTTTTTTTTTTT - +4 tfdimers__MD00341 16 0.577953 14132.7 1 6 CACCTG TCCGTAAGCATGCCCAGACATGCCCATCCT + +4 dbcorrdb__ATF3__ENCSR000BKC_1__m3-Brf-cnc-CTCF-E2f1-E(z)-lid-Max-Myc-pho-phol-RpII215-Sap30-Taf1-Taf7-tna-Usf-usp 5 0.578752 14152.2 1 6 CACCTG GCGGCCACGTGGCGGCGGCG + +4 dbcorrdb__CHD1__ENCSR000AQD_1__m1-Chd1 0 0.578752 14152.2 1 6 CACCTG CCCCTAAGGCTCGTTTCCGG + +4 dbcorrdb__EP300__ENCSR000DZD_1__m1-MTA1-like-nej 9 0.578752 14152.2 1 6 CACCTG AGGAAATGAAACTAGCAATT + +4 dbcorrdb__GATA2__ENCSR000EVW_1__m1-GATAe-grn-Jra-pnr-srp 7 0.578752 14152.2 1 6 CACCTG AGATTCTTATCTGATTTATC + +4 dbcorrdb__GTF3C2__ENCSR000DOD_1__m2-Tbp 7 0.578752 14152.2 1 6 CACCTG GGCGCTCTACCCACTAGGCC + +4 dbcorrdb__POLR2A__ENCSR000EEM_1__m2-RpII215 13 0.578752 14152.2 1 6 CACCTG TGACAGCTGCCGCTACGGGC + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EDX_1__m2-RpII215-Taf1 9 0.578752 14152.2 1 6 CACCTG CGGCTGCGCCATCGGGTCGT + +4 dbcorrdb__SIX5__ENCSR000BIQ_1__m3-Six4 1 0.578752 14152.2 1 6 CACCTG CCGCCTTCTGGCCGCCGGAA + +4 dbcorrdb__ZNF274__ENCSR000EVX_1__m3-bon 13 0.578752 14152.2 1 6 CACCTG TTCCCACATTCATTACATTC + +4 transfac_pro__M01516 12 0.578752 14152.2 1 6 CACCTG AGAATTTTCCGGAACAAACG + +4 dbcorrdb__BCL3__ENCSR000BQH_1__m1-fkh-HDAC1-nej 13 0.578752 14152.2 1 6 CACCTG CTCACTGAGTAAACACTGAC - +4 dbcorrdb__BRF2__ENCSR000DOC_1__m5 11 0.578752 14152.2 1 6 CACCTG TCTGTAGCGATCAAATTTAA - +4 dbcorrdb__NR3C1__ENCSR000BHE_1__m5 5 0.578752 14152.2 1 6 CACCTG TCGTGTCCTTGGCACCGTCA - +4 dbcorrdb__REST__ENCSR000BJP_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 1 0.578752 14152.2 1 6 CACCTG GGCGCTGTCCAGGGTGCTGA - +4 dbcorrdb__SIN3A__ENCSR000BRM_1__m3-Sin3A 6 0.578752 14152.2 1 6 CACCTG TCCTAGCTGTTGCGTCATCC - +4 dbcorrdb__SIX5__ENCSR000BGX_1__m3-Six4 5 0.578752 14152.2 1 6 CACCTG CGTGCTGCCCACCGGGAACT - +4 dbcorrdb__SP1__ENCSR000BJX_1__m1-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 0 0.578752 14152.2 1 6 CACCTG CCCCTGGACTTTGGCCTCTG - +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m4-bon 10 0.578752 14152.2 1 6 CACCTG AATGACTGCACGCTTAACAA - +4 taipale_cyt_meth__FOXA1_NWRWGTMAATATTKRYNYWN_FL_meth-croc-fd59A-fd96Ca-fd96Cb-fkh 13 0.578752 14152.2 1 6 CACCTG TTAAGCAAATATTTACATAA - +4 dbcorrdb__EP300__ENCSR000BLM_1__m4-nej -1 0.578752 14152.2 1 5 CACCTG GCCTCATGCCAAACTAAATA - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m8-SREBP 15 0.578752 14152.2 1 5 CACCTG ACGAGGTCTCAGTTTTTCCC - +4 dbcorrdb__ZNF274__ENCSR000EUN_1__m4 15 0.578752 14152.2 1 5 CACCTG ACTCAGGTCTTATTATACAT - +4 taipale_cyt_meth__CPSF4_MCCNCCNCCNCCCCNCCCCCNCCAN_FL_meth-Clp 2 0.579416 14168.5 1 6 CACCTG CCCTCCACCACCCCTCCCCCACCAA + +4 tfdimers__MD00018-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-Taf7-Tbp 7 0.579416 14168.5 1 6 CACCTG TTTTTACTTCCTCTTTTTTTTTTTT + +4 tfdimers__MD00023-pho-phol 10 0.579416 14168.5 1 6 CACCTG TCTCTCCCGCCATCTGCTGAGTTTT + +4 tfdimers__MD00260 12 0.579416 14168.5 1 6 CACCTG AATAAGGGATTATCCCTATTACTCT - +4 tfdimers__MD00559-sens-2 5 0.579416 14168.5 1 6 CACCTG TAAATCACTTAATCACTTGTAAATA - +4 transfac_pro__M00310 6 0.580745 14201 1 6 CACCTG AATAAACGCCAATTT + +4 transfac_pro__M02836-bon-opa 2 0.580745 14201 1 6 CACCTG CCCCCCCGGGGGGGT + +4 transfac_pro__M09018 3 0.580745 14201 1 6 CACCTG ATATACATGCATGCA + +4 transfac_pro__M09067 1 0.580745 14201 1 6 CACCTG CCACCGCCGCCGCCA + +4 flyfactorsurvey__BCl6-F4-6_SOLEXA_5 4 0.580745 14201 1 6 CACCTG AAAATTCCTCGAACA - +4 flyfactorsurvey__BCl6-F5_CG4360F2-3_SOLEXA_2.5 8 0.580745 14201 1 6 CACCTG CCCCACAACAACTCC - +4 flyfactorsurvey__Cf2-PB_SANGER_5_FBgn0000286-Cf2 6 0.580745 14201 1 6 CACCTG TATATGTATCCACCG - +4 transfac_pro__M09024 2 0.580745 14201 1 6 CACCTG ACCACCGACAATATC - +4 transfac_pro__M09040 4 0.580745 14201 1 6 CACCTG ACTCCACCGACAATT - +4 transfac_pro__M09260 0 0.580745 14201 1 6 CACCTG CTCCGATTTTTTCGG - +4 neph__UW.Motif.0415 -1 0.580745 14201 1 5 CACCTG AATTTTCTCAATTTC + +4 flyfactorsurvey__CG10267-F1-3_SOLEXA_5-Zif 10 0.580745 14201 1 5 CACCTG AATGTAAATACACCT - +4 cisbp__M6236-croc -2 0.580745 14201 1 4 CACCTG TCTGGCAAAACAAAC + +4 predrem__nrMotif771-Spps-btd 2 0.58085 14203.5 1 6 CACCTG GCCCCCTCCCC + +4 scertf__morozov.YAP5 2 0.58085 14203.5 1 6 CACCTG CTTGGCTAAGC + +4 scertf__zhu.GAT4 2 0.58085 14203.5 1 6 CACCTG TAGATCTATTC + +4 taipale__MYBL2_DBD_NNAACCGTTNN-Myb 2 0.58085 14203.5 1 6 CACCTG ATAACCGTTAA + +4 taipale_cyt_meth__ELK4_NRCCGGAWGTN_FL-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Taf1 0 0.58085 14203.5 1 6 CACCTG CACCGGAAGTG + +4 transfac_pro__M07053 5 0.58085 14203.5 1 6 CACCTG GGACATGCCCC + +4 transfac_pro__M09172 0 0.58085 14203.5 1 6 CACCTG CACTTTCACTA + +4 transfac_pro__M09240-Hsf 4 0.58085 14203.5 1 6 CACCTG CTAGAAGCTTC + +4 cisbp__M1891-Atac3-bs-Eip74EF-Ets21C-Ets96B-Ets97D-Hcf-pnt-RpII215-Sin3A-Taf1 2 0.58085 14203.5 1 6 CACCTG GCCACTTCCGG - +4 cisbp__M2711 0 0.58085 14203.5 1 6 CACCTG TTGCTTTAATG - +4 hocomoco__DUX4_HUMAN.H11MO.0.A 1 0.58085 14203.5 1 6 CACCTG TAACCTAATCA - +4 hocomoco__ETV1_HUMAN.H11MO.0.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Taf1-aop-bs-pnt 0 0.58085 14203.5 1 6 CACCTG CACTTCCGGCC - +4 hocomoco__RHXF1_HUMAN.H11MO.0.D-Ptx1 5 0.58085 14203.5 1 6 CACCTG GTTAATCCCCG - +4 predrem__nrMotif1443 3 0.58085 14203.5 1 6 CACCTG TTTCCCCTCAA - +4 predrem__nrMotif221 2 0.58085 14203.5 1 6 CACCTG CAGCCCTGGGC - +4 taipale_cyt_meth__ETV5_NRCCGGAAGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.58085 14203.5 1 6 CACCTG CACTTCCGGTC - +4 transfac_pro__M00917-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-E2f1-Jra-kay-Xbp1 1 0.58085 14203.5 1 6 CACCTG TGACGTCATCG - +4 transfac_pro__M07395-btd-CG42741-CTCF-dar1-E(z)-kay-Klf15-klu-Nf-YA-Nf-YB-sd-Sp1-Spps-Stat92E 0 0.58085 14203.5 1 6 CACCTG GCCCCGCCCCC - +4 transfac_pro__M09486-dsf-tll 4 0.58085 14203.5 1 6 CACCTG CGTTGACTTTT - +4 transfac_public__M00353 0 0.58085 14203.5 1 6 CACCTG TTGCTTTATTT - +4 jaspar__MA0579.1 -1 0.58085 14203.5 1 5 CACCTG GGCTCAGCGCG + +4 taipale_tf_pairs__HOXB2_ETV1_ACCGGAAATGA_CAP-Ets96B-pb -1 0.58085 14203.5 1 5 CACCTG ACCGGAAATGA + +4 cisbp__M2372 -1 0.58085 14203.5 1 5 CACCTG GGCTCAGCGCG - +4 hocomoco__RFX2_MOUSE.H11MO.1.A-CG5846-CG9727-Max-Rfx-SREBP -1 0.58085 14203.5 1 5 CACCTG CCATGGCAACC - +4 transfac_pro__M02013 6 0.58085 14203.5 1 5 CACCTG AATTATTAACT - +4 transfac_pro__M08822-Dr 6 0.58085 14203.5 1 5 CACCTG CCTAATTACAT - +4 taipale_cyt_meth__FOXO3_NTCCCCACACN_eDBD-foxo 7 0.58085 14203.5 1 4 CACCTG TTCCCCACACG + +4 hocomoco__HNF1B_HUMAN.H11MO.1.A 7 0.58085 14203.5 1 4 CACCTG AATCATTAACT - +4 hocomoco__PBX1_MOUSE.H11MO.0.A -2 0.58085 14203.5 1 4 CACCTG CCTGTCAATCA - +4 flyfactorsurvey__CG33557_da_SANGER_5_FBgn0000413-CG33557-da 14 0.581023 14207.8 1 6 CACCTG TGTTGTGTCCGTGCCATCTGG - +4 hocomoco__ZN816_HUMAN.H11MO.0.C 3 0.581023 14207.8 1 6 CACCTG CCCTGCATGTCCCCCTTTTTT - +4 transfac_pro__M09369 3 0.581023 14207.8 1 6 CACCTG AGTTACGTGTAAAATTTGAAA - +4 transfac_pro__M05228 16 0.581023 14207.8 1 5 CACCTG GGAGCGAGAGGGGGAACACCC - +4 transfac_pro__M05243 16 0.581023 14207.8 1 5 CACCTG AGGGGGAGGGGGGGACCACCA - +4 tfdimers__MD00136-E2f1-GATAe-grn-pnr 12 0.581251 14213.3 1 6 CACCTG TTTTTTTTTTCTTATCTTTTTTTT - +4 cisbp__M5031-Hnf4 2 0.581348 14215.7 1 6 CACCTG TTGACCCC + +4 cisbp__M5783 2 0.581348 14215.7 1 6 CACCTG ATAATCCC + +4 cisbp__M6182-bcd-Gsc-oc-Ptx1 2 0.581348 14215.7 1 6 CACCTG CTAATCCC + +4 cisbp__M6332-maf-S 0 0.581348 14215.7 1 6 CACCTG TTGCTGAC + +4 elemento__CTCCCTCC 1 0.581348 14215.7 1 6 CACCTG CTCCCTCC + +4 predrem__nrMotif2651 1 0.581348 14215.7 1 6 CACCTG ACAACTAA + +4 taipale__RHOXF1_DBD_NTRAKCCN 2 0.581348 14215.7 1 6 CACCTG ATAATCCC + +4 taipale_cyt_meth__EVX1_RTCGTTAN_eDBD_meth-btn-Dfd-Dll-eve-exex-ind-pb-unpg 0 0.581348 14215.7 1 6 CACCTG GTCATTAG + +4 taipale_cyt_meth__GSX1_MTCGTTAN_eDBD_meth-bap-bsh-btn-CG34367-Dll-Dr-en-eve-exex-ind-inv-lab-Lim1-pb-unpg 0 0.581348 14215.7 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__HOXB1_MTCGTTAN_eDBD_meth-Dr-lab 0 0.581348 14215.7 1 6 CACCTG ATCGTTAC + +4 taipale_cyt_meth__HOXD1_RTCGTTAN_eDBD_meth-Dr-lab 0 0.581348 14215.7 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__ISX_MTCGTTAN_FL_meth-bsh-CG34367-Dr-ind-Lim3-unpg-Vsx1-Vsx2 0 0.581348 14215.7 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__SHOX_STCGTTAN_eDBD_meth-CG34367-Dr-eve-ind-unpg 0 0.581348 14215.7 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__VSX2_YTCGTTAN_eDBD_meth-CG4328-Lim3-Lmx1a-Vsx1-Vsx2 0 0.581348 14215.7 1 6 CACCTG CTCGTTAA + +4 cisbp__M1033-vvl 1 0.581348 14215.7 1 6 CACCTG TTGCATAA - +4 predrem__nrMotif2062 0 0.581348 14215.7 1 6 CACCTG CACTAGAG - +4 stark__GAGGAAGC-pnt 2 0.581348 14215.7 1 6 CACCTG GCTTCCTC - +4 transfac_pro__M07344-opa 2 0.581348 14215.7 1 6 CACCTG GCTCCCCG - +4 cisbp__M1664-sd -1 0.581348 14215.7 1 5 CACCTG ACATTCCC + +4 cisbp__M2159 -1 0.581348 14215.7 1 5 CACCTG ATCTCCGT + +4 cisbp__M0218-dimm-Fer3 -1 0.581348 14215.7 1 5 CACCTG ACATATGG - +4 hocomoco__CDX1_HUMAN.H11MO.0.C-cad -1 0.581348 14215.7 1 5 CACCTG ACATAAAT - +4 jaspar__MA0354.1 -1 0.581348 14215.7 1 5 CACCTG ATCTCCGC - +4 predrem__nrMotif1564 -1 0.581348 14215.7 1 5 CACCTG ACTTTGGG - +4 predrem__nrMotif2153 3 0.581348 14215.7 1 5 CACCTG TATCAGCA - +4 stark__ATGCGGGY-gcm-gcm2 -1 0.581348 14215.7 1 5 CACCTG ACCCGCAT - +4 transfac_pro__M01015 -1 0.581348 14215.7 1 5 CACCTG ACTTCTTA - +4 yetfasco__YLR266C_528 -1 0.581348 14215.7 1 5 CACCTG ATCTCCGC - +4 cisbp__M0550 -2 0.581348 14215.7 1 4 CACCTG CCATTCCA - +4 cisbp__M4240 4 0.581348 14215.7 1 4 CACCTG GTGCCACA - +4 scertf__spivak.MET31 4 0.581348 14215.7 1 4 CACCTG GCGCCACA - +4 cisbp__M1658 5 0.581348 14215.7 1 3 CACCTG GGGCCCAC + +4 jaspar__MA1050.1 5 0.581348 14215.7 1 3 CACCTG GGGCCCAC + +4 cisbp__M5466-croc-fd59A-fkh-foxo-FoxP-slp2 5 0.581348 14215.7 1 3 CACCTG TTGTTTAC - +4 cisbp__M1973-Hr51 1 0.58165 14223.1 1 6 CACCTG CAAGCTT + +4 fantom__motif94_CATYTSA 0 0.58165 14223.1 1 6 CACCTG CATTTCA + +4 jaspar__MA0164.1-Hr51 1 0.58165 14223.1 1 6 CACCTG CAAGCTT + +4 cisbp__M0777 1 0.58165 14223.1 1 6 CACCTG AGATCGG - +4 transfac_pro__M07260 1 0.58165 14223.1 1 6 CACCTG CCTCCCA - +4 cisbp__M2110 2 0.58165 14223.1 1 5 CACCTG GCTTCCT + +4 scertf__badis.RSF2 -1 0.58165 14223.1 1 5 CACCTG CCCCGCA + +4 predrem__nrMotif1120 -1 0.58165 14223.1 1 5 CACCTG ACCCAAG - +4 predrem__nrMotif1531 2 0.58165 14223.1 1 5 CACCTG CATCCCC - +4 transfac_pro__M06191-CG9609 2 0.58165 14223.1 1 5 CACCTG GACCCCT - +4 transfac_pro__M09579 3 0.58165 14223.1 1 4 CACCTG CGTCAGC + +4 predrem__nrMotif965 -2 0.58165 14223.1 1 4 CACCTG TCTAGAG - +4 elemento__CAATTAC 4 0.58165 14223.1 1 3 CACCTG CAATTAC + +4 elemento__CTGCAGC -3 0.58165 14223.1 1 3 CACCTG CTGCAGC + +4 elemento__CTGCCCC -3 0.58165 14223.1 1 3 CACCTG CTGCCCC + +4 elemento__CTGCCGC -3 0.58165 14223.1 1 3 CACCTG CTGCCGC + +4 elemento__CTGCGCA -3 0.58165 14223.1 1 3 CACCTG CTGCGCA + +4 elemento__CTGCGCC -3 0.58165 14223.1 1 3 CACCTG CTGCGCC + +4 elemento__CTGCGGC -3 0.58165 14223.1 1 3 CACCTG CTGCGGC + +4 elemento__CTGCTGC -3 0.58165 14223.1 1 3 CACCTG CTGCTGC + +4 elemento__CTGGAGC -3 0.58165 14223.1 1 3 CACCTG CTGGAGC + +4 elemento__CTGGCCA -3 0.58165 14223.1 1 3 CACCTG CTGGCCA + +4 elemento__CTGGCCC -3 0.58165 14223.1 1 3 CACCTG CTGGCCC + +4 elemento__CTGGGCC -3 0.58165 14223.1 1 3 CACCTG CTGGGCC + +4 elemento__CTGTCAA-hth -3 0.58165 14223.1 1 3 CACCTG CTGTCAA + +4 elemento__TAATTAC 4 0.58165 14223.1 1 3 CACCTG TAATTAC + +4 elemento__TGTTTAC-fd59A-foxo 4 0.58165 14223.1 1 3 CACCTG TGTTTAC + +4 transfac_pro__M07061 -3 0.58165 14223.1 1 3 CACCTG CTAATTT + +4 cisbp__M2863-Myc 6 0.581667 14223.5 1 6 CACCTG ACGTCCCACGTGGCCCT + +4 taipale__TEAD3_DBD_RCATTCCNNRCATTCCN-sd 3 0.581667 14223.5 1 6 CACCTG ACATTCCTCGCATTCCA + +4 taipale_tf_pairs__CLOCK_EVX1_ATRATYANNNNCACGTG_CAP_repr-Clk-eve 11 0.581667 14223.5 1 6 CACCTG ATAATCACCGACACGTG + +4 transfac_pro__M01330-Awh-CG11085-CG18599-E5-ems-en-eve-inv-lab-slou-unpg 1 0.581667 14223.5 1 6 CACCTG TGAGCTAATTAGTTGGA + +4 transfac_pro__M02904-Sox15 3 0.581667 14223.5 1 6 CACCTG GACCACATTCATACAAT + +4 transfac_pro__M05521 0 0.581667 14223.5 1 6 CACCTG GGCCTCAAACGAAAAGG + +4 transfac_pro__M05861 7 0.581667 14223.5 1 6 CACCTG GGATTCGTCCCTAGTAC + +4 transfac_pro__M07879-toy 4 0.581667 14223.5 1 6 CACCTG TTCAAGCGTGAGTAATG + +4 transfac_pro__M08947-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 6 0.581667 14223.5 1 6 CACCTG ATGGATGACGTCATCCT + +4 transfac_public__M00435-Myc 5 0.581667 14223.5 1 6 CACCTG AGGGCCACGTGGGACGT + +4 yetfasco__YOR230W_1148 10 0.581667 14223.5 1 6 CACCTG ATAATAATATTACCAAT + +4 scertf__morozov.CHA4 12 0.581667 14223.5 1 5 CACCTG TCGGCTTCTTATAACCG - +4 taipale_tf_pairs__TEAD4_ALX4_RCATWCYNNNNTAATYRNATTA_CAP_repr-sd 3 0.582134 14234.9 1 6 CACCTG GCATTCCTTCCTAATCGAATTA + +4 transfac_pro__M09327 13 0.582134 14234.9 1 6 CACCTG CAACATCATCAACAACATCACC + +4 cisbp__M6456-CoRest-l(3)neo38-peb 9 0.582134 14234.9 1 6 CACCTG ACCCCAAACCACCCCCCCCCCC - +4 taipale_tf_pairs__TEAD4_CEBPB_NTTRCGYAANNNNNNGGAATGY_CAP_repr-sd 3 0.582134 14234.9 1 6 CACCTG GCATTCCTAGGTATTGCGCAAT - +4 tfdimers__MD00029 5 0.582134 14234.9 1 6 CACCTG TTTTTCACTTCCCTTTTTTTTT - +4 tfdimers__MD00439-CrebB 9 0.582134 14234.9 1 6 CACCTG ATTATTTTTTACGTCACATTTT - +4 transfac_pro__M04644-CHES-1-like-fd59A-FoxK-foxo-FoxP-slp2 12 0.582134 14234.9 1 6 CACCTG AATGCAATTGTTTACAATATTC - +4 transfac_pro__M01055 14 0.582182 14236.1 1 6 CACCTG GGAGGCGTATGGGATACGTAACC + +4 transfac_pro__M09507-Clk-E(spl)m3-HLH-E(spl)mbeta-HLH-Hey-Sidpn 8 0.582182 14236.1 1 6 CACCTG GTGGATGACACGTGTCAACACGT + +4 tfdimers__MD00205-GATAe-grn-pnr-srp 13 0.582182 14236.1 1 6 CACCTG ATTTTTCTATTGTTATCTTTATT - +4 tfdimers__MD00581 5 0.582182 14236.1 1 6 CACCTG TTTCTCACTTCTCCCTTTTTTTT - +4 tfdimers__MD00149-Hnf4-svp 12 0.583345 14264.5 1 6 CACCTG AAAATTAAGGTCCATCTGTTCTTTTTTTT + +4 hdpi__TRIM21 -1 0.583953 14279.4 1 5 CACCTG GGCTGG + +4 hdpi__VPS4B 1 0.583953 14279.4 1 5 CACCTG GCGCCC - +4 jaspar__MA0020.1 -1 0.583953 14279.4 1 5 CACCTG TGCTTT - +4 transfac_pro__M08794-ham -1 0.583953 14279.4 1 5 CACCTG ATCTTC - +4 transfac_pro__M03819-Dif-dl-Ets96B 2 0.583953 14279.4 1 4 CACCTG ACTTCC - +4 jaspar__MA0298.1-CG3065-hkb -3 0.583953 14279.4 1 3 CACCTG CTATCA + +4 transfac_pro__M03857-pan -3 0.583953 14279.4 1 3 CACCTG CTTTGT + +4 hdpi__PLAGL1 -3 0.583953 14279.4 1 3 CACCTG CTAATT - +4 cisbp__M5204-bowl-drm-odd-sob 8 0.585643 14320.7 1 6 CACCTG AAAAACAGTAGCCG + +4 flyfactorsurvey__CG8765_SANGER_5_FBgn0036900-CG8765 4 0.585643 14320.7 1 6 CACCTG AAGCGACATACATA + +4 flyfactorsurvey__SuH_FlyReg_FBgn0004837-Su(H) 7 0.585643 14320.7 1 6 CACCTG TAGTTCTCACATTC + +4 jaspar__MA0425.1 4 0.585643 14320.7 1 6 CACCTG ACCCCACTTTTTTG + +4 taipale__ZNF306_full_TGGKCTARCCTCGA_repr 6 0.585643 14320.7 1 6 CACCTG TGGTCTAGCCTCGA + +4 transfac_pro__M01942 4 0.585643 14320.7 1 6 CACCTG ACCCCACTTTTTTG + +4 transfac_public__M00456-E(bx) 8 0.585643 14320.7 1 6 CACCTG ACCCACAACACATA + +4 cisbp__M2230 4 0.585643 14320.7 1 6 CACCTG ACCCCACTTTTTTA - +4 cisbp__M3234-E(bx) 8 0.585643 14320.7 1 6 CACCTG AACCACAACACATA - +4 cisbp__M4294 4 0.585643 14320.7 1 6 CACCTG ACCCCACTTTTTTG - +4 cisbp__M4529-Irbp18-nej-slbo-Xrp1 8 0.585643 14320.7 1 6 CACCTG TATTGCACAATCCT - +4 cisbp__M4975-fru 3 0.585643 14320.7 1 6 CACCTG TATTACTTTGGGGG - +4 cisbp__M5971 6 0.585643 14320.7 1 6 CACCTG TGGGCTAGCCTCGA - +4 flyfactorsurvey__fru_SANGER_10_FBgn0004652-fru 3 0.585643 14320.7 1 6 CACCTG TATTACTTTGGGGG - +4 flyfactorsurvey__sob_SOLEXA_5_FBgn0004892-bowl-drm-odd-sob 8 0.585643 14320.7 1 6 CACCTG AAAAACAGTAGCCG - +4 hocomoco__HSF2_HUMAN.H11MO.0.A-Hsf-pb 6 0.585643 14320.7 1 6 CACCTG TTCTAGAACATTCT - +4 hocomoco__TAF1_MOUSE.H11MO.0.A-RpII215-Taf1-Taf7-lid-pho-phol 4 0.585643 14320.7 1 6 CACCTG CCGCCGCCATCTTG - +4 swissregulon__hs__EVI1.p2-ham 3 0.585643 14320.7 1 6 CACCTG TTTTATCTTGTCTT - +4 transfac_pro__M05408 8 0.585643 14320.7 1 6 CACCTG ACAATACGATCGTG - +4 transfac_pro__M09499 1 0.585643 14320.7 1 6 CACCTG CCACCGACACATTC - +4 cisbp__M5434-Ets21C-Ets97D-pnt -1 0.585643 14320.7 1 5 CACCTG ACCGGATTTCCGGT - +4 transfac_public__M00127-GATAe-grn-pnr 9 0.585643 14320.7 1 5 CACCTG GCGGTAATCTTCCT - +4 transfac_pro__M05285 10 0.585643 14320.7 1 4 CACCTG TCTTAAATTTAACC + +4 cisbp__M5058-eg-kni-knrl 5 0.586224 14334.9 1 6 CACCTG TGCTCTACTTTT + +4 cisbp__M5338-CG7786-gt-hng1-nej-Pdp1-slbo-vri 3 0.586224 14334.9 1 6 CACCTG TATTACGTAACA + +4 cisbp__M5470-foxo 6 0.586224 14334.9 1 6 CACCTG TTTCCCCACACG + +4 hocomoco__ANDR_MOUSE.H11MO.1.A 6 0.586224 14334.9 1 6 CACCTG ACTGTGTTCTTT + +4 homer__CGGTGACGTCAC_CRE-Atf3-Atf6-CrebA-CrebB-E2f1-Jra-Xbp1 4 0.586224 14334.9 1 6 CACCTG CGGTGACGTCAC + +4 swissregulon__hs__FOSL2.p2-kay 5 0.586224 14334.9 1 6 CACCTG TGACTCACGGTC + +4 taipale_cyt_meth__ATF7_NRTGACGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.586224 14334.9 1 6 CACCTG GATGACGTCATC + +4 transfac_pro__M05706 2 0.586224 14334.9 1 6 CACCTG TGGACCAGAATT + +4 cisbp__M5910-CG7786-gt-hng1-Pdp1-vri 3 0.586224 14334.9 1 6 CACCTG TATTACATAATA - +4 cisbp__M6284-Hnf4 2 0.586224 14334.9 1 6 CACCTG TGGACTTTGGCC - +4 cisbp__M6485 1 0.586224 14334.9 1 6 CACCTG CTTCCTCTTTTT - +4 fantom__motif151_GCCYGTGCMKCW 5 0.586224 14334.9 1 6 CACCTG AGATGCACAGGC - +4 flyfactorsurvey__kni_SANGER_5_FBgn0001320-eg-kni-knrl 5 0.586224 14334.9 1 6 CACCTG TGCTCTACTTTT - +4 hocomoco__RUNX3_MOUSE.H11MO.0.A-Bgb-Bro-RunxA-RunxB-lz-run 2 0.586224 14334.9 1 6 CACCTG CAAACCACAGCC - +4 neph__UW.Motif.0452 4 0.586224 14334.9 1 6 CACCTG TGGAAATCTGGA - +4 transfac_pro__M01137-FoxK-foxo-FoxP-slp1 0 0.586224 14334.9 1 6 CACCTG AATTTGTTTACA - +4 transfac_pro__M05368 4 0.586224 14334.9 1 6 CACCTG GTCCCACCCACT - +4 transfac_pro__M05966 5 0.586224 14334.9 1 6 CACCTG TTTTATTCCTCA - +4 transfac_pro__M06171 1 0.586224 14334.9 1 6 CACCTG TCTCTTGCCAGT - +4 transfac_pro__M06277 2 0.586224 14334.9 1 6 CACCTG TCTACCCCAACG - +4 transfac_pro__M06425-CG2120 3 0.586224 14334.9 1 6 CACCTG TTTCACCCTTCG - +4 transfac_pro__M09233-Hsf 5 0.586224 14334.9 1 6 CACCTG TCTAGAAGCTTC - +4 taipale_cyt_meth__GATA6_WGATAACGATCW_eDBD_meth-GATAe-grn-pnr-srp 7 0.586224 14334.9 1 5 CACCTG AGATAACGATCT + +4 transfac_pro__M06156 -1 0.586224 14334.9 1 5 CACCTG CCATCCGGCTGC + +4 transfac_pro__M05623 7 0.586224 14334.9 1 5 CACCTG TCTGTACCATCT - +4 transfac_pro__M06009 7 0.586224 14334.9 1 5 CACCTG CATTCTTGACCC - +4 transfac_pro__M06101 7 0.586224 14334.9 1 5 CACCTG GCGGCAAAACCA - +4 transfac_pro__M05732 -2 0.586224 14334.9 1 4 CACCTG CCTGGAATAATA + +4 transfac_pro__M06139-CG10321-CG8089 -2 0.586224 14334.9 1 4 CACCTG CCTGGAATGGGC + +4 transfac_pro__M06273 8 0.586224 14334.9 1 4 CACCTG TCGGCCCGCACA - +4 transfac_pro__M06435-crol 8 0.586224 14334.9 1 4 CACCTG TCCGCTGCCACA - +4 transfac_pro__M08902-pan -2 0.586224 14334.9 1 4 CACCTG CCTTTGATGCTT - +4 flyfactorsurvey__CG4854_SANGER_10_FBgn0038766-CG4854 9 0.586224 14334.9 1 3 CACCTG GTTGCCAACCAC - +4 cisbp__M2118-Nf-YA -1 0.586714 14346.9 1 5 CACCTG ACCAA - +4 jaspar__MA0313.1-Nf-YA -1 0.586714 14346.9 1 5 CACCTG ACCAA - +4 scertf__harbison.DAL80-GATAd-GATAe-grn-pnr-srp 1 0.586714 14346.9 1 4 CACCTG TTATC - +4 cisbp__M0006 1 0.587572 14367.9 1 6 CACCTG CCGCCGCCGT + +4 cisbp__M0009-Taf1 1 0.587572 14367.9 1 6 CACCTG GCGCCGCCAT + +4 cisbp__M0039 2 0.587572 14367.9 1 6 CACCTG CGCGCCGCCA + +4 cisbp__M0452 4 0.587572 14367.9 1 6 CACCTG GGTGAAGCTT + +4 cisbp__M0692-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.587572 14367.9 1 6 CACCTG AACCGGAAGT + +4 cisbp__M0822 1 0.587572 14367.9 1 6 CACCTG TGACATGTCA + +4 cisbp__M1155-Gsc-bcd-oc 3 0.587572 14367.9 1 6 CACCTG CCTAATCCGC + +4 cisbp__M1542 2 0.587572 14367.9 1 6 CACCTG TTAATATTAA + +4 cisbp__M4926-dsf-tll 3 0.587572 14367.9 1 6 CACCTG TTTGACTTTT + +4 cisbp__M5345-bcd-Gsc-oc-Ptx1 3 0.587572 14367.9 1 6 CACCTG GTTAATCCGC + +4 jaspar__MA1031.1 4 0.587572 14367.9 1 6 CACCTG GTGGGCCCAC + +4 predrem__nrMotif578 0 0.587572 14367.9 1 6 CACCTG TTCCCAAATC + +4 predrem__nrMotif811 3 0.587572 14367.9 1 6 CACCTG CAGTGCCTCT + +4 swissregulon__sacCer__OAF1 4 0.587572 14367.9 1 6 CACCTG TTATCTCCGA + +4 taipale_cyt_meth__OSR2_NGCTACYGTN_eDBD_meth_repr-bowl-drm-odd-sob 3 0.587572 14367.9 1 6 CACCTG TGCTACTGTG + +4 transfac_pro__M06798 4 0.587572 14367.9 1 6 CACCTG TCGGGACTTT + +4 transfac_pro__M08913-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.587572 14367.9 1 6 CACCTG CACTTCCGGT + +4 bergman__Kr-Kr 2 0.587572 14367.9 1 6 CACCTG TTAACCCGTT - +4 cisbp__M0265-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 1 0.587572 14367.9 1 6 CACCTG TGACGTCATC - +4 cisbp__M0536-CG17328 3 0.587572 14367.9 1 6 CACCTG TTCCTTTTTC - +4 cisbp__M0835 0 0.587572 14367.9 1 6 CACCTG TATATTAACC - +4 cisbp__M1555 0 0.587572 14367.9 1 6 CACCTG TTCCGTAACT - +4 flyfactorsurvey__HLH106_SANGER_10_FBgn0015234-Mitf-SREBP-Usf 2 0.587572 14367.9 1 6 CACCTG GTCGCGTGAT - +4 flyfactorsurvey__dsf_SANGER_5_FBgn0015381-dsf-tll 3 0.587572 14367.9 1 6 CACCTG TTTGACTTTT - +4 hocomoco__PLAL1_HUMAN.H11MO.0.D 4 0.587572 14367.9 1 6 CACCTG GGGCCCCCCG - +4 hocomoco__PO5F1_HUMAN.H11MO.1.A-SoxN-nub-pdm2 3 0.587572 14367.9 1 6 CACCTG ATTTGCATAT - +4 hocomoco__STA5A_HUMAN.H11MO.0.A-Stat92E 1 0.587572 14367.9 1 6 CACCTG TTTCCTAGAA - +4 jaspar__MA0546.1-FoxK-FoxP-GATAe-HDAC1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-grn-nej-pnr 4 0.587572 14367.9 1 6 CACCTG TGTTTACTTT - +4 jaspar__MA1054.1 4 0.587572 14367.9 1 6 CACCTG GTGGTCCCCA - +4 jaspar__MA1069.1-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 1 0.587572 14367.9 1 6 CACCTG TGACGTCATC - +4 predrem__nrMotif1137 4 0.587572 14367.9 1 6 CACCTG TGGGAGCCAG - +4 taipale__HMBOX1_DBD_NYTAGTTAMN_repr 2 0.587572 14367.9 1 6 CACCTG GTTAACTAGT - +4 transfac_pro__M01975-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.587572 14367.9 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M01990-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 3 0.587572 14367.9 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M02072-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 0 0.587572 14367.9 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M07739-Chrac-14-Myb 1 0.587572 14367.9 1 6 CACCTG TGACCGTTAC - +4 cisbp__M4705-sv 5 0.587572 14367.9 1 5 CACCTG AGCGTGACCG + +4 homer__VGCTGWCAVB_Meis1 -1 0.587572 14367.9 1 5 CACCTG GGCTGTCAGC + +4 predrem__nrMotif1807 5 0.587572 14367.9 1 5 CACCTG AGAGCAAACA + +4 predrem__nrMotif200 -1 0.587572 14367.9 1 5 CACCTG ATCTTGCAAA + +4 predrem__nrMotif54 5 0.587572 14367.9 1 5 CACCTG AATCACACAT + +4 transfac_pro__M00334 -1 0.587572 14367.9 1 5 CACCTG ACCATTAAAC + +4 transfac_pro__M07056-Ptx1 5 0.587572 14367.9 1 5 CACCTG TGTAATCCCA + +4 jaspar__MA0107.1-CG12018-Dif-Rel-dl 5 0.587572 14367.9 1 5 CACCTG GGAAATTCCC - +4 predrem__nrMotif2576 6 0.587572 14367.9 1 4 CACCTG TAATTTTACA + +4 transfac_pro__M06475 6 0.587572 14367.9 1 4 CACCTG CTTGAAAATC + +4 yetfasco__YDL170W_651 -2 0.587572 14367.9 1 4 CACCTG CCGAAAACGG + +4 predrem__nrMotif141 -2 0.587572 14367.9 1 4 CACCTG CCTTCCCAAA - +4 taipale_cyt_meth__HOXB7_NGTAATTANN_FL_meth-abd-A-Antp-ap-Awh-btn-CG18599-CG32532-CG9876-Dfd-E5-ems-en-eve-ind-inv-lab-lbl-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 6 0.587572 14367.9 1 4 CACCTG GTTAATTACC - +4 predrem__nrMotif1451-RpII215 1 0.587625 14369.2 1 6 CACCTG CCCCCTCCGCCCG + +4 swissregulon__sacCer__ABF1 2 0.587625 14369.2 1 6 CACCTG ATCACTATATACG + +4 taipale__HSF1_DBD_TTCTAGAANNTTC_repr-Hsf-pb 6 0.587625 14369.2 1 6 CACCTG TTCTAGAACGTTC + +4 taipale_cyt_meth__MAFG_TGCTGANNNTGCR_FL-maf-S 4 0.587625 14369.2 1 6 CACCTG TGCTGACTGTGCA + +4 taipale_cyt_meth__PAX4_NYACGCTAATTAN_eDBD-ap-Awh-CG18599-E5-ems-gsb-gsb-n-ind-lab-Lim3-prd 1 0.587625 14369.2 1 6 CACCTG TCACGCTAATTAG + +4 transfac_pro__M07617-Brf-brm-btd-CTCF-ERR-E(z)-HDAC1-klu-Nelf-E-Rbbp5-RpII215-sd-Spps-SREBP-vtd 0 0.587625 14369.2 1 6 CACCTG GCCCCGCCCCCGC + +4 cisbp__M5564-Hsf-pb 6 0.587625 14369.2 1 6 CACCTG TTCTAGAACGTTC - +4 cisbp__M6173 7 0.587625 14369.2 1 6 CACCTG ATTTTGCAATCTG - +4 neph__UW.Motif.0475 5 0.587625 14369.2 1 6 CACCTG GGCCACTGCCCCC - +4 taipale_cyt_meth__SPIB_RAWWGMGGAAGTN_FL-CG9650-Eip74EF-nej 0 0.587625 14369.2 1 6 CACCTG TACTTCCGCTTTT - +4 taipale_tf_pairs__TEAD4_DRGX_GGAATGTTAATTR_CAP-CG11294-Drgx-sd 5 0.587625 14369.2 1 6 CACCTG CAATTAACATTCC - +4 transfac_pro__M04904-CG17209 3 0.587625 14369.2 1 6 CACCTG CCACAGCCTCGTC - +4 transfac_pro__M07717-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-nej-slp1-slp2 6 0.587625 14369.2 1 6 CACCTG ATTGTTTATTTAA - +4 transfac_pro__M09456-tll 6 0.587625 14369.2 1 6 CACCTG ATCGTTGACTTTT - +4 transfac_pro__M09465 6 0.587625 14369.2 1 6 CACCTG ACCGTTGACTTTT - +4 tfdimers__MD00460-nau 7 0.588103 14380.9 1 6 CACCTG ACCCCGGCAGCTGCCACACCGTAAACCC + +4 bergman__br-Z3-br 2 0.588118 14381.2 1 6 CACCTG AAAACAAAA + +4 cisbp__M0333-Jra-Stat92E-kay-nej 3 0.588118 14381.2 1 6 CACCTG TATGACTCA + +4 cisbp__M1099-bcd-Gsc-oc-Ptx1 2 0.588118 14381.2 1 6 CACCTG TTAATCCCT + +4 elemento__CGTCACTTC 3 0.588118 14381.2 1 6 CACCTG CGTCACTTC + +4 flyfactorsurvey__Hand_da_SANGER_5_FBgn0000413-Hand-da 0 0.588118 14381.2 1 6 CACCTG CACATGGCC + +4 hocomoco__SMAD2_MOUSE.H11MO.0.A-Smox 2 0.588118 14381.2 1 6 CACCTG TCTGTCTGG + +4 jaspar__MA0431.1 0 0.588118 14381.2 1 6 CACCTG ACCCCGCAC + +4 predrem__nrMotif1287 1 0.588118 14381.2 1 6 CACCTG TGACTTCCT + +4 predrem__nrMotif1586 2 0.588118 14381.2 1 6 CACCTG TTCACTTCT + +4 predrem__nrMotif2191 0 0.588118 14381.2 1 6 CACCTG TTCTTTTTG + +4 predrem__nrMotif23 3 0.588118 14381.2 1 6 CACCTG TTGTCCCAG + +4 transfac_pro__M03575-HLH4C 0 0.588118 14381.2 1 6 CACCTG CATTTGTGC + +4 cisbp__M0122 2 0.588118 14381.2 1 6 CACCTG TTTTTTCGG - +4 cisbp__M0691-nej 1 0.588118 14381.2 1 6 CACCTG CTTCCGCTT - +4 cisbp__M0698-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.588118 14381.2 1 6 CACCTG ACTTCCGGT - +4 elemento__CGGAAGTGA-nej 1 0.588118 14381.2 1 6 CACCTG TCACTTCCG - +4 hocomoco__MAF_MOUSE.H11MO.1.A-bon 3 0.588118 14381.2 1 6 CACCTG AGTCAGCAG - +4 hocomoco__VDR_HUMAN.H11MO.1.A-EcR 2 0.588118 14381.2 1 6 CACCTG CTGAACCCA - +4 predrem__nrMotif1632 2 0.588118 14381.2 1 6 CACCTG ATGACCACA - +4 predrem__nrMotif2293 2 0.588118 14381.2 1 6 CACCTG AGAATCTTG - +4 predrem__nrMotif2467 2 0.588118 14381.2 1 6 CACCTG CACGCCTGG - +4 predrem__nrMotif291 2 0.588118 14381.2 1 6 CACCTG GAAATCTTT - +4 predrem__nrMotif653 1 0.588118 14381.2 1 6 CACCTG TTACTTGAA - +4 taipale_cyt_meth__NKX2-5_NTCGTTGAN_FL_meth-vnd 3 0.588118 14381.2 1 6 CACCTG CTCAACGAG - +4 taipale_cyt_meth__NKX2-8_NTCGTTSAN_FL_meth_repr-vnd 3 0.588118 14381.2 1 6 CACCTG TTCAACGAG - +4 transfac_pro__M01905 0 0.588118 14381.2 1 6 CACCTG ACCCCGCAC - +4 transfac_public__M00141 1 0.588118 14381.2 1 6 CACCTG TCTCCCAAA - +4 predrem__nrMotif1031 4 0.588118 14381.2 1 5 CACCTG CAGACCCCT + +4 predrem__nrMotif1751 -1 0.588118 14381.2 1 5 CACCTG TGCTTCTAA + +4 predrem__nrMotif2520 4 0.588118 14381.2 1 5 CACCTG TTCATGCCA + +4 predrem__nrMotif740 -1 0.588118 14381.2 1 5 CACCTG AGCTCTGGG + +4 predrem__nrMotif826 4 0.588118 14381.2 1 5 CACCTG AATTCTCCC + +4 cisbp__M0652 -1 0.588118 14381.2 1 5 CACCTG ACTTTTTCT - +4 cisbp__M2955-zfh1 4 0.588118 14381.2 1 5 CACCTG CAGAAACAG - +4 predrem__nrMotif2045 4 0.588118 14381.2 1 5 CACCTG TTCAGACTT - +4 predrem__nrMotif2434 -1 0.588118 14381.2 1 5 CACCTG AACTGTACA - +4 predrem__nrMotif704 -1 0.588118 14381.2 1 5 CACCTG CCATGGACA - +4 swissregulon__hs__TFAP2_A_C_.p2-TfAP-2 -1 0.588118 14381.2 1 5 CACCTG GCCCGGGGC - +4 predrem__nrMotif1192 -2 0.588118 14381.2 1 4 CACCTG TCTGTTGTG + +4 predrem__nrMotif1212 -2 0.588118 14381.2 1 4 CACCTG CCAGGATTT + +4 predrem__nrMotif2168 -2 0.588118 14381.2 1 4 CACCTG GCTGGACAT + +4 predrem__nrMotif411 -2 0.588118 14381.2 1 4 CACCTG GCTGGGAAT - +4 transfac_pro__M04685-cnc-Jra-kay-maf-S -3 0.588118 14381.2 1 3 CACCTG CTGAGTCAT - +4 jaspar__MA0060.2-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-kay-yps 3 0.588257 14384.7 1 6 CACCTG AGAGTGCTGATTGGTCCA + +4 scertf__foat.PIP2 11 0.588257 14384.7 1 6 CACCTG GCCAATACGCCGGCCTAT + +4 taipale_cyt_meth__TFCP2_AWCCGGWTNNAWCCGGWT_eDBD-gem 0 0.588257 14384.7 1 6 CACCTG AACCGGTTCAAACCGGTT + +4 taipale_cyt_meth__ZSCAN5A_NYGTCCCYCCCCAAANMN_eDBD_repr 3 0.588257 14384.7 1 6 CACCTG CTGTCCCCCCCCAAATCC + +4 hocomoco__PAX2_HUMAN.H11MO.0.D-Poxm-ey-sv-toy 5 0.588257 14384.7 1 6 CACCTG TGTCACGCATGACTGATC - +4 swissregulon__hs__PAX8.p2-sv 7 0.588257 14384.7 1 6 CACCTG TAACTCACGCATGACTGT - +4 taipale_tf_pairs__ERF_DLX2_RSCGGAANNNNNYMATTA_CAP_repr_2-Ets21C 11 0.588257 14384.7 1 6 CACCTG TAATTAGCCACTTCCGGT - +4 transfac_pro__M06873 12 0.588257 14384.7 1 6 CACCTG CCCTTGGCCTTCCACCCC - +4 transfac_pro__M06874 12 0.588257 14384.7 1 6 CACCTG CCCTTGGCCTTCCACCCC - +4 neph__UW.Motif.0394 10 0.591146 14455.3 1 6 CACCTG AAATGCCAGATATCTG + +4 taipale_cyt_meth__TFCP2L1_NCCGGNNNNNNCCGGN_eDBD_meth-gem 9 0.591146 14455.3 1 6 CACCTG ACCGGTTCGAACCGGT + +4 taipale_cyt_meth__ZIC3_NGACCCCCTGCTGTGM_eDBD_meth-opa 4 0.591146 14455.3 1 6 CACCTG AGACCCCCTGCTGTGC + +4 taipale_tf_pairs__POU2F1_HOXB13_NRMATATACCAATAAA_CAP_repr-nub-pdm2 6 0.591146 14455.3 1 6 CACCTG TGAATATACCAATAAA + +4 taipale_tf_pairs__TEAD4_PITX1_RCATWCNNNNGGATTA_CAP_repr-Ptx1-sd 3 0.591146 14455.3 1 6 CACCTG GCATACTTAAGGATTA + +4 transfac_pro__M00406-Mef2-rump 10 0.591146 14455.3 1 6 CACCTG CTCTAAAAATAACCCT + +4 transfac_pro__M01326-al-Antp-Awh-C15-CG18599-CG34367-E5-ems-en-ind-lab-Lim3-OdsH-otp-pb-repo-Scr-unc-4-unpg-zfh2 8 0.591146 14455.3 1 6 CACCTG AGGTTAATTAGCTGAT + +4 hocomoco__EVI1_HUMAN.H11MO.0.B-ham 5 0.591146 14455.3 1 6 CACCTG TATCTTATCTTATCTT - +4 neph__UW.Motif.0316 10 0.591146 14455.3 1 6 CACCTG CACGGAGCCAGGGCTG - +4 neph__UW.Motif.0644 10 0.591146 14455.3 1 6 CACCTG TGAAAACAAAAATTTG - +4 taipale_tf_pairs__ELK1_HOXB13_RNCGGAANYNRTWAAN_CAP 9 0.591146 14455.3 1 6 CACCTG TTTTATTACTTCCGGT - +4 transfac_pro__M01408-Antp-Scr 0 0.591146 14455.3 1 6 CACCTG GACCTCATTAATAACT - +4 transfac_pro__M09356 1 0.591146 14455.3 1 6 CACCTG TTACTTGTTCCCCAAG - +4 transfac_pro__M05450 -1 0.591146 14455.3 1 5 CACCTG ACCATCATTATAGACA - +4 tfdimers__MD00166-pho-phol-SREBP 18 0.591184 14456.2 1 6 CACCTG CTCCTGCACTCCATCTGCCACCTCCCATCTC + +4 taipale_cyt_meth__HSF5_YNGAANNNNNNNNNNNNNAACRTTCNR_eDBD_repr 18 0.592183 14480.6 1 6 CACCTG TCGAACGTTGCGGCCCCCAACGTTCCA + +4 transfac_pro__M00954 8 0.592183 14480.6 1 6 CACCTG GGGGTGGGGACATGGTGTTCTTGGTGG + +4 transfac_pro__M05853 8 0.593296 14507.9 1 6 CACCTG TCCGATAAGAACTCGGAAG - +4 transfac_pro__M06881 12 0.593296 14507.9 1 6 CACCTG AGGGCCGCAACCCACCCAC - +4 transfac_pro__M05933 15 0.593296 14507.9 1 4 CACCTG CACTTCTACACTGATCACC - +4 tfdimers__MD00215-pan-Stat92E 10 0.595536 14562.7 1 6 CACCTG TTTTTCACTTCCCCTTTGATCTTTTT + +4 tfdimers__MD00026 10 0.595536 14562.7 1 6 CACCTG AAAGAAAGTGAAACTGACACTTAAAA - +4 tfdimers__MD00175-nej 14 0.595536 14562.7 1 6 CACCTG CTTATGGGATTAACTCCCTGCTATAT - +4 cisbp__M2321 11 0.596937 14596.9 1 6 CACCTG AGACATGCCCAGACATGCCC + +4 dbcorrdb__ATF3__ENCSR000BPS_1__m3 6 0.596937 14596.9 1 6 CACCTG GTTCGATTCCCGGTGGAGGC + +4 dbcorrdb__ATF3__ENCSR000BPS_1__m4 0 0.596937 14596.9 1 6 CACCTG CACTTATGACGCAAAAGGTG + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m6 1 0.596937 14596.9 1 6 CACCTG CCCGCAGCGAACAGACACCA + +4 dbcorrdb__CHD1__ENCSR000AQK_1__m3-Chd1 14 0.596937 14596.9 1 6 CACCTG AACCGCGAAAAACGATACTG + +4 dbcorrdb__ETS1__ENCSR000BPU_1__m3-Hcf-Six4 11 0.596937 14596.9 1 6 CACCTG GGCCGTCGCGGGGCCTTCTG + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m2-E(z) 14 0.596937 14596.9 1 6 CACCTG CAGGAAAGAACGATCTCATG + +4 dbcorrdb__EZH2__ENCSR000ASZ_1__m2-E(z)-Myc-pho-phol 12 0.596937 14596.9 1 6 CACCTG CGGAAAAAGCCGGTCCGGCG + +4 dbcorrdb__FOXM1__ENCSR000BRU_1__m1-CG9650-ebi-foxo-Jra-kay-Mef2-MTA1-like-nej-NFAT-Stat92E 14 0.596937 14596.9 1 6 CACCTG GTCTCGATATGACTCATCAG + +4 dbcorrdb__GATA1__ENCSR000EWM_1__m1-brm-CoRest-CycT-ebi-GATAe-grn-HDAC1-HLH3B-Jra-nej-pnr-RpII215-Sirt6-Snr1-srp-Stat92E-svp 4 0.596937 14596.9 1 6 CACCTG TCCTTATCTGCCCCCCCCAG + +4 dbcorrdb__MAZ__ENCSR000DZA_1__m1-Brf-brm-btd-CG42741-CoRest-CTCF-ERR-E(z)-HDAC1-luna-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-tna-vtd 13 0.596937 14596.9 1 6 CACCTG GCCCTCCGGCCCCGCCCTCC + +4 dbcorrdb__MYC__ENCSR000DLI_1__m1-Myc 14 0.596937 14596.9 1 6 CACCTG CTCCCCAGCCACGCGACCCG + +4 dbcorrdb__POLR2A__ENCSR000EAJ_1__m1-Ets96B-RpII215-Taf1 1 0.596937 14596.9 1 6 CACCTG GCGCTTCCGCCCTGGGAGGC + +4 dbcorrdb__REST__ENCSR000BJQ_1__m1-btd-CTCF-HDAC1-Sin3A-Spps 14 0.596937 14596.9 1 6 CACCTG AGCACCATGGACAGCGCCCG + +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m2-egg 12 0.596937 14596.9 1 6 CACCTG TCAGAGAATTCATAATAGAG + +4 dbcorrdb__TBL1XR1__ENCSR000EGB_1__m2-ebi-Jra 13 0.596937 14596.9 1 6 CACCTG CCCGCAAATGACTTAACAGT + +4 dbcorrdb__TEAD4__ENCSR000BRY_1__m1-sd 9 0.596937 14596.9 1 6 CACCTG TTCCCCACATTCCTGGCATT + +4 hocomoco__MAFK_MOUSE.H11MO.0.A-cnc-maf-S-tj 13 0.596937 14596.9 1 6 CACCTG AAAACTGCTGAGTCAGCATT + +4 hocomoco__ZN250_HUMAN.H11MO.0.C 0 0.596937 14596.9 1 6 CACCTG TACCATGCTGTTTTGATTAC + +4 dbcorrdb__BHLHE40__ENCSR000EGV_1__m1-bigmax-btd-cnc-CrebB-cwo-cyc-E2f1-ERR-ewg-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-Stat92E-tgo-Usf-zfh1 8 0.596937 14596.9 1 6 CACCTG CGCCCGGGCACGTGCCCGGG - +4 dbcorrdb__EZH2__ENCSR000ARR_1__m3-E(z)-RpII215-SREBP-tna 0 0.596937 14596.9 1 6 CACCTG GCCCAGCCGCGGCGCGGGGG - +4 dbcorrdb__FOXM1__ENCSR000BRU_1__m3-Blimp-1-CG9650-foxo-nej-Stat92E 8 0.596937 14596.9 1 6 CACCTG TAAAAGTGAAACTGACAAAT - +4 dbcorrdb__GATA3__ENCSR000BMX_1__m3-GATAe-grh-grn-nej-pnr 0 0.596937 14596.9 1 6 CACCTG AACCTGATTAGCAAGTTTCC - +4 dbcorrdb__MAFK__ENCSR000ECK_1__m1-cic-cnc-maf-S-tj 0 0.596937 14596.9 1 6 CACCTG TTGCTGAGTCAGCAATTTTT - +4 dbcorrdb__MAX__ENCSR000DZF_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Snr1-Spps-Spt20-SREBP-Taf1-tgo-tna-Usf-vtd 3 0.596937 14596.9 1 6 CACCTG GGGCACGTGGCCGGGGCGGG - +4 dbcorrdb__MAX__ENCSR000FAE_1__m1-btd-Clk-cnc-E2f1-E(z)-gce-Max-Myc-RpII215-Sap30-Spps-tgo-Usf 3 0.596937 14596.9 1 6 CACCTG GGCCACGTGCCCCGGCGGGG - +4 dbcorrdb__MXI1__ENCSR000EDU_1__m1-Brf-brm-btd-CTCF-E2f1-E(z)-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf-vtd 3 0.596937 14596.9 1 6 CACCTG GCCCACGTGGCCGGCGGGCG - +4 dbcorrdb__MYC__ENCSR000DLU_1__m1-Brf-brm-Clk-cnc-CrebB-E2f1-E(z)-gce-Max-Mnt-Myc-pho-phol-RpII215-Sap30-Sin3A-Taf1-tna-Usf-vtd 3 0.596937 14596.9 1 6 CACCTG GAGCACGTGGCCGGCGGGGG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m6-RpII215 9 0.596937 14596.9 1 6 CACCTG CACTTTCTGCACATGCCATT - +4 dbcorrdb__TAF1__ENCSR000BKS_1__m2-aop-Atac3-Eip74EF-E(z)-Hcf-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha 3 0.596937 14596.9 1 6 CACCTG CCGCCGCTTCCGCCGCGGGC - +4 dbcorrdb__WRNIP1__ENCSR000EAA_1__m1 14 0.596937 14596.9 1 6 CACCTG GCTGAGCGCTTCCGCACCTG - +4 transfac_pro__M03828-btd-EcR-eg-ERR-fkh-HDAC1-Hnf4-Hr38-Hr51-Hr78-kni-knrl-Spps-svp-usp 9 0.596937 14596.9 1 6 CACCTG CTGAACTTTGCCCTTCCCTC - +4 transfac_pro__M06403 11 0.596937 14596.9 1 6 CACCTG GATGTCAAAGAAAACTAAAT - +4 transfac_pro__M09111 11 0.596937 14596.9 1 6 CACCTG AAAAAGAGTCGCACGTGTGG - +4 tfdimers__MD00145-aop-Eip74EF-Ets21C-Ets97D-pan 11 0.597089 14600.6 1 6 CACCTG TATATATTCACTTCCTCCTTTGATGTTTTT + +4 tfdimers__MD00320 3 0.597089 14600.6 1 6 CACCTG ATTATTCTACATAACAAAGGAAAAAAAAAA + +4 stark__TGGAGGDGGWAHTMATBVRTGWDDDRKKMW-toy 22 0.597089 14600.6 1 6 CACCTG AGAACTTTACACTGATGATTACCTCCTCCA - +4 cisbp__M1019-al-bsh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Drgx-en-exex-inv-lab-lbe-Lim3-Lmx1a-OdsH-Pph13-repo-unc-4-unpg-Vsx2 0 0.597874 14619.8 1 6 CACCTG TAATTAG + +4 predrem__nrMotif2246 1 0.597874 14619.8 1 6 CACCTG GAATCTC + +4 cisbp__M0995-C15-Dr-en-exex-inv-Rx-unpg 0 0.597874 14619.8 1 6 CACCTG CAATTAG - +4 cisbp__M1576 1 0.597874 14619.8 1 6 CACCTG ATGATTA - +4 cisbp__M1858-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 1 0.597874 14619.8 1 6 CACCTG CTTCCGG - +4 jaspar__MA0026.1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt 1 0.597874 14619.8 1 6 CACCTG CTTCCGG - +4 predrem__nrMotif1906 1 0.597874 14619.8 1 6 CACCTG TCACACT - +4 stark__CMGGAAR-Eip74EF-Ets97D 1 0.597874 14619.8 1 6 CACCTG CTTCCGG - +4 transfac_pro__M00695-sd 1 0.597874 14619.8 1 6 CACCTG CCGCCGC - +4 transfac_pro__M00624-CG7786-gt-Pdp1 -1 0.597874 14619.8 1 5 CACCTG AGCAAAC + +4 hdpi__FLI1-Eip74EF-Ets21C-Ets96B-aop -1 0.597874 14619.8 1 5 CACCTG ACTTCCG - +4 predrem__nrMotif635 -1 0.597874 14619.8 1 5 CACCTG TTCTGGC - +4 taipale_tf_pairs__GATA1_AGATAAN_HT-GATAe-grn-pnr 2 0.597874 14619.8 1 5 CACCTG CTTATCT - +4 transfac_pro__M05775-CG9609 2 0.597874 14619.8 1 5 CACCTG GTCCCCT - +4 predrem__nrMotif1887 -2 0.597874 14619.8 1 4 CACCTG TCTTAAC + +4 predrem__nrMotif1897 3 0.597874 14619.8 1 4 CACCTG TGAGACT + +4 predrem__nrMotif1476 3 0.597874 14619.8 1 4 CACCTG CTCCAAC - +4 predrem__nrMotif2397 -2 0.597874 14619.8 1 4 CACCTG CTTAAAC - +4 predrem__nrMotif514 -2 0.597874 14619.8 1 4 CACCTG CCAAGCA - +4 transfac_pro__M04949-GATAe-grn-pnr -2 0.597874 14619.8 1 4 CACCTG GCTGACT - +4 cisbp__M6013-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.597874 14619.8 1 3 CACCTG TGTTTAC - +4 jaspar__MA0297.1-FoxP-bin-croc-fd59A-fkh-foxo-slp2 4 0.597874 14619.8 1 3 CACCTG TGTTTAC - +4 taipale__Foxg1_DBD_RTAAAYA-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.597874 14619.8 1 3 CACCTG TGTTTAC - +4 transfac_pro__M01906-bin-croc-fd59A-fkh-foxo-FoxP-slp2 4 0.597874 14619.8 1 3 CACCTG TGTTTAC - +4 hocomoco__FOXL2_MOUSE.H11MO.0.C-FoxK-FoxL1-FoxP-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-slp2 4 0.597878 14619.9 1 6 CACCTG TGTTTACATTT + +4 hocomoco__MEOX2_HUMAN.H11MO.0.D-CG18599-Dfd-E5-abd-A-ap-btn-ftz-lab-pb-zen2 5 0.597878 14619.9 1 6 CACCTG TTAATTATGAT + +4 scertf__morozov.CUP9-achi-hth-vis 5 0.597878 14619.9 1 6 CACCTG CCATACATCAC + +4 taipale__SP3_DBD_GCCMCGCCCMC-btd-cbt-CG3065-CG42741-dar1-Klf15-klu-luna-Sp1-Spps 4 0.597878 14619.9 1 6 CACCTG GCCACGCCCCC + +4 taipale_cyt_meth__FLI1_NACMGGAARTN_FL_meth-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.597878 14619.9 1 6 CACCTG GACCGGAAGTC + +4 transfac_pro__M00795-acj6-nub-pdm2-vvl 1 0.597878 14619.9 1 6 CACCTG TGATTTGCATA + +4 transfac_pro__M03862-yps 2 0.597878 14619.9 1 6 CACCTG GCTGCCAATCA + +4 transfac_pro__M07039-btd-klu-sd-Spps 3 0.597878 14619.9 1 6 CACCTG CCCCGCCCCCG + +4 cisbp__M2261-bin-croc-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.597878 14619.9 1 6 CACCTG TTGTTTACATT - +4 hocomoco__DUXA_HUMAN.H11MO.0.D-Traf4 1 0.597878 14619.9 1 6 CACCTG TAATTTAATCA - +4 scertf__zhu.YKL222C 4 0.597878 14619.9 1 6 CACCTG TTATTTCCGTT - +4 taipale_cyt_meth__CREB1_NRTGAYGCGTN_eDBD_meth_repr-CrebB 0 0.597878 14619.9 1 6 CACCTG TACGCGTCACC - +4 transfac_pro__M01742-E2f1-ewg 1 0.597878 14619.9 1 6 CACCTG GCGCATGCGCA - +4 transfac_pro__M09587 5 0.597878 14619.9 1 6 CACCTG TGTGGGCCCCA - +4 yetfasco__YBR033W_2093 5 0.597878 14619.9 1 6 CACCTG AGTTTTTCCGG - +4 hocomoco__FOXK1_MOUSE.H11MO.0.A-FoxK-FoxP-fkh-foxo 6 0.597878 14619.9 1 5 CACCTG CTTGTTTACAT + +4 jaspar__MA0480.1-FoxP-fkh-foxo -1 0.597878 14619.9 1 5 CACCTG TCCTGTTTACA + +4 neph__UW.Motif.0099 -1 0.597878 14619.9 1 5 CACCTG AAATGAAAACA + +4 predrem__nrMotif2105 -1 0.597878 14619.9 1 5 CACCTG GGCTGTGGTTT + +4 cisbp__M0938-Optix 6 0.597878 14619.9 1 5 CACCTG GAATGATATCC - +4 cisbp__M2282-fkh-foxo-FoxP -1 0.597878 14619.9 1 5 CACCTG TCCTGTTTACA - +4 flyfactorsurvey__kay_Jra_SANGER_5_FBgn0001291-CoRest-Jra-Mef2-Myc-bon-cnc-kay-nej-pan 7 0.597878 14619.9 1 4 CACCTG GATGAGTCACC + +4 cisbp__M5050-bon-cnc-CoRest-Jra-kay-Mef2-Myc-nej-pan 7 0.597878 14619.9 1 4 CACCTG GATGAGTCACC - +4 taipale_cyt_meth__HOXC12_GGTAATAAAAN_eDBD_meth-Abd-B-cad-eve 7 0.597878 14619.9 1 4 CACCTG TTTTTATTACC - +4 tiffin__TIFDMEM0000003 7 0.597878 14619.9 1 4 CACCTG AGTTAATTAGC - +4 transfac_pro__M05962-ham 7 0.597878 14619.9 1 4 CACCTG ATGCCGGCACA - +4 transfac_pro__M00808-ey-gsb-gsb-n-Poxm-prd-sv-toy 8 0.597878 14619.9 1 3 CACCTG CTGGAACTCAC + +4 cisbp__M0312-Jra 1 0.597969 14622.1 1 6 CACCTG TGACTCAA + +4 factorbook__RUNX1-Bgb-Bro-CG9650-MTA1-like-NFAT-RunxA-RunxB-Stat92E-ebi-foxo-lz-nej-run 1 0.597969 14622.1 1 6 CACCTG AAACCACA + +4 taipale_cyt_meth__GSC2_YTAATCCN_eDBD-bcd-Gsc-oc 2 0.597969 14622.1 1 6 CACCTG CTAATCCG + +4 taipale_cyt_meth__ISL1_SCACTTAN_FL_meth-Hmx-tup 1 0.597969 14622.1 1 6 CACCTG GCACTTAA + +4 cisbp__M0625 2 0.597969 14622.1 1 6 CACCTG GAAACATT - +4 cisbp__M1051-nub-pdm2-vvl 0 0.597969 14622.1 1 6 CACCTG CTCATTAA - +4 predrem__nrMotif2112 0 0.597969 14622.1 1 6 CACCTG CCACTGTG - +4 cisbp__M6167-cad -1 0.597969 14622.1 1 5 CACCTG ACATAAAT + +4 cisbp__M0562 -1 0.597969 14622.1 1 5 CACCTG ATCTATAT - +4 cisbp__M0711-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.597969 14622.1 1 5 CACCTG ACTTCCGG - +4 cisbp__M4797-Cf2 3 0.597969 14622.1 1 5 CACCTG TTATACAC - +4 jaspar__MA0607.1-Fer3-dimm -1 0.597969 14622.1 1 5 CACCTG ACATATGG - +4 predrem__nrMotif2594 -2 0.597969 14622.1 1 4 CACCTG CATAGACT + +4 cisbp__M0387 4 0.597969 14622.1 1 4 CACCTG CACACACA - +4 predrem__nrMotif2432 4 0.597969 14622.1 1 4 CACCTG TGCTTACT - +4 transfac_pro__M07829-Optix-so 4 0.597969 14622.1 1 4 CACCTG ATGATACG - +4 cisbp__M1653 5 0.597969 14622.1 1 3 CACCTG GGGCCCAC + +4 predrem__nrMotif1939 -3 0.597969 14622.1 1 3 CACCTG CTGGCTTA + +4 predrem__nrMotif2659 -3 0.597969 14622.1 1 3 CACCTG CTGTAGGC + +4 predrem__nrMotif377 -3 0.597969 14622.1 1 3 CACCTG CTGCCTCA + +4 predrem__nrMotif870 -3 0.597969 14622.1 1 3 CACCTG CTGCTTAA + +4 cisbp__M1863-croc-fd59A-fkh-foxo-slp2 5 0.597969 14622.1 1 3 CACCTG ATGTTTAC - +4 jaspar__MA0031.1-croc-fd59A-fkh-foxo-slp2 5 0.597969 14622.1 1 3 CACCTG ATGTTTAC - +4 predrem__nrMotif1060 -3 0.597969 14622.1 1 3 CACCTG CTGTGATG - +4 predrem__nrMotif108 -3 0.597969 14622.1 1 3 CACCTG CTTCTAAA - +4 predrem__nrMotif1503 -3 0.597969 14622.1 1 3 CACCTG CTTAATTC - +4 predrem__nrMotif2561 -3 0.597969 14622.1 1 3 CACCTG CTGTTAGA - +4 predrem__nrMotif2670 -3 0.597969 14622.1 1 3 CACCTG CTGATCAA - +4 taipale__FOXO3_full_GTAAACAW-croc-fd59A-fkh-foxo-FoxP-slp2 5 0.597969 14622.1 1 3 CACCTG TTGTTTAC - +4 hocomoco__BRAC_MOUSE.H11MO.0.B-byn 5 0.598109 14625.6 1 6 CACCTG TTTTCCATATGTCTGTCAATTCATG + +4 tfdimers__MD00253 10 0.598109 14625.6 1 6 CACCTG TTTCTCCATCAATCTGTTCTTTTTT + +4 transfac_pro__M06606-CG9609 5 0.598109 14625.6 1 6 CACCTG AGGGGAACGGTTTGAATGGGGCTCC + +4 transfac_pro__M06838-CG9609 5 0.598109 14625.6 1 6 CACCTG AGGGGAACGGTTTGTATGGGGCTCC + +4 flyfactorsurvey__lola-PO_SOLEXA_FBgn0005630-lola 8 0.598427 14633.3 1 6 CACCTG TTTGGGCGGCCCTTT + +4 hdpi__KCNIP1-CG5890-CG44422 5 0.598427 14633.3 1 6 CACCTG CCGGGGACTTCACTG + +4 transfac_pro__M06888-CG9609 1 0.598427 14633.3 1 6 CACCTG TAGCCTACTTAACAG + +4 transfac_pro__M09037 1 0.598427 14633.3 1 6 CACCTG CCACCTCCACCGCCA + +4 transfac_pro__M09039-Taf1 1 0.598427 14633.3 1 6 CACCTG CCGCCGCCGCCGCCA + +4 transfac_pro__M09070-RpII215 0 0.598427 14633.3 1 6 CACCTG CGCCTCCGCCGCCGC + +4 transfac_public__M00103-ct 9 0.598427 14633.3 1 6 CACCTG TATATCGATTATTTT + +4 cisbp__M4439-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-GATAe-grn-HDAC1-nej-Nf1-pnr-slp2 6 0.598427 14633.3 1 6 CACCTG TTTGTTTACTTAGGG - +4 cisbp__M4526-cnc-ewg-Jra-kay-maf-S-mor-Myc-pan 7 0.598427 14633.3 1 6 CACCTG GATGAGTCACCCCCC - +4 cisbp__M6438-CG32532 6 0.598427 14633.3 1 6 CACCTG TTATATTAATTACTC - +4 factorbook__CTCF-ext-CTCF-SMC3-vtd 8 0.598427 14633.3 1 6 CACCTG GGCTGCAGTTCCCCA - +4 flyfactorsurvey__sob-F3-5_SOLEXA_5-sob 7 0.598427 14633.3 1 6 CACCTG AATGCGTAACGGAAA - +4 homer__RGGGTAWWWTHGTAA_Unknown1 9 0.598427 14633.3 1 6 CACCTG TTACGAAAATACCCT - +4 neph__UW.Motif.0492 7 0.598427 14633.3 1 6 CACCTG TGAAAAAAAACTGAG - +4 neph__UW.Motif.0607 8 0.598427 14633.3 1 6 CACCTG TGTGAAAAAATCTGG - +4 taipale_tf_pairs__GCM1_ETV1_RTRNNGGCGGAAGTN_CAP-Ets96B-gcm-gcm2 0 0.598427 14633.3 1 6 CACCTG CACTTCCGCCCCCAT - +4 transfac_pro__M04978 1 0.598427 14633.3 1 6 CACCTG GCCCCTATGTCGTAA - +4 transfac_pro__M09026-Taf1 1 0.598427 14633.3 1 6 CACCTG CCACCGCCGCCGCCA - +4 transfac_pro__M09072-Taf1 1 0.598427 14633.3 1 6 CACCTG CCACCGCCGCCGCCA - +4 transfac_pro__M09330 0 0.598427 14633.3 1 6 CACCTG AACCTTATCCTAATT - +4 transfac_pro__M09412 7 0.598427 14633.3 1 6 CACCTG TTTTTTTTACTTTTT - +4 yetfasco__YGL131C_612 9 0.598427 14633.3 1 6 CACCTG GTGCGGCGCTATCAT - +4 scertf__macisaac.ABF1 10 0.598427 14633.3 1 5 CACCTG TATCACTATATACGA + +4 hocomoco__SMCA5_MOUSE.H11MO.0.C-Iswi-crol 10 0.598427 14633.3 1 5 CACCTG TTCCATTCCATTCCA - +4 transfac_pro__M09086 -2 0.598427 14633.3 1 4 CACCTG CCTCGGGATTCGTGC + +4 transfac_pro__M09506-Clk-E(spl)mgamma-HLH-Hey 7 0.599308 14654.9 1 6 CACCTG GAGGTGGCACGTGGCAATCAC + +4 cisbp__M2191-Tbp-Trf-Trf2 12 0.599308 14654.9 1 6 CACCTG ATCGAATATATATATCTAGTC - +4 transfac_pro__M01574-Kdm4A-Kdm4B 4 0.599308 14654.9 1 6 CACCTG ATTCCACCCCTAATTTTTCTT - +4 transfac_pro__M09510-bigmax 6 0.599308 14654.9 1 6 CACCTG AGGTGTCACGTGCTATTCACG - +4 yetfasco__YER148W_798-Tbp-Trf-Trf2 12 0.599308 14654.9 1 6 CACCTG ATCGAATATATATATCTAGTC - +4 transfac_pro__M05261-Brf-brm-btd-ERR-E(z)-kay-Nf-YB-Spps 16 0.599308 14654.9 1 5 CACCTG GGGGAGGGGGCGGGCCCACCC - +4 taipale_cyt_meth__NR1I2_NYGAACYNNNYGAACYN_eDBD_meth-EcR 3 0.599566 14661.2 1 6 CACCTG ACGAACTCAATGAACTC + +4 transfac_pro__M02775-cic-maf-S-tj 9 0.599566 14661.2 1 6 CACCTG AAATTTGCTGACTTAGA + +4 transfac_pro__M02855 2 0.599566 14661.2 1 6 CACCTG AACACCAAAACAAAGGA + +4 transfac_pro__M09536-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 9 0.599566 14661.2 1 6 CACCTG TGATGACGTCATCTTTT + +4 transfac_pro__M01386-Awh-CG11085-CG18599-E5-ems-en-eve-inv-lab-slou-unpg 9 0.599566 14661.2 1 6 CACCTG ACCGCTAATTAGCGGTG - +4 transfac_public__M00247 5 0.599566 14661.2 1 6 CACCTG AGGTCCGCTTGGCCGTT - +4 tfdimers__MD00197 11 0.599843 14668 1 6 CACCTG GAGGAAATGGGGAACTGGCAAAAG + +4 hdpi__ING3-Ing3 0 0.600067 14673.4 1 6 CACCTG GACATC - +4 cisbp__M1852 -1 0.600067 14673.4 1 5 CACCTG TGCTTT - +4 fantom__motif8_CCATGN -1 0.600067 14673.4 1 5 CACCTG ACATGG - +4 transfac_pro__M04984 -2 0.600067 14673.4 1 4 CACCTG CCAAAA + +4 transfac_pro__M05124 -2 0.600067 14673.4 1 4 CACCTG CCAACG + +4 hdpi__RBM8A-tsu 2 0.600067 14673.4 1 4 CACCTG TACACA - +4 transfac_pro__M05959-CTCF -2 0.600067 14673.4 1 4 CACCTG CCGTAT - +4 cisbp__M2016-achi -3 0.600067 14673.4 1 3 CACCTG CTGTCA + +4 jaspar__MA0207.1 -3 0.600067 14673.4 1 3 CACCTG CTGTCA - +4 tfdimers__MD00329-EcR-Sox100B 2 0.600521 14684.5 1 6 CACCTG CTCCCCTGACCCCAAAGCCCGC - +4 tfdimers__MD00264-CG5846-Rfx 12 0.602393 14730.3 1 6 CACCTG ATTTCTGGGTAGCATCTGTTCTTGTTTTT + +4 cisbp__M6286-Hsf-pb 6 0.60317 14749.3 1 6 CACCTG TTCTAGAACTTTCT + +4 taipale__MYBL2_DBD_AACCGTTAACGGNN-Myb 6 0.60317 14749.3 1 6 CACCTG AACGGTTAACGGTT + +4 taipale_tf_pairs__FOXJ2_HOXB13_RTAAACWNATWAAA_CAP_repr 3 0.60317 14749.3 1 6 CACCTG GTAAACAAATAAAA + +4 taipale_tf_pairs__HOXB13_Fox_NNMAACAYNRTAAA_ChIP_Exo 3 0.60317 14749.3 1 6 CACCTG GTAAACATCATAAA + +4 cisbp__M4528-Chd1-CoRest 8 0.60317 14749.3 1 6 CACCTG TCTCGCGAGATTTG - +4 cisbp__M4540-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-pnt-RpII215-Sin3A-Taf1 2 0.60317 14749.3 1 6 CACCTG GCCACTTCCGGTTC - +4 cisbp__M4885-CG8765 4 0.60317 14749.3 1 6 CACCTG AAGCGACATAAATA - +4 flyfactorsurvey__prd_SOLEXA_5_FBgn0003145-Poxn-gsb-prd 8 0.60317 14749.3 1 6 CACCTG TGGAGCGTGACGGA - +4 flyfactorsurvey__sr_SOLEXA_5_FBgn0003499-Spps-btd-cbt-klu-sr 7 0.60317 14749.3 1 6 CACCTG CCCCGCCCACGCAC - +4 taipale_cyt_meth__POU1F1_NTAATGAKATGCRN_eDBD-pdm3-vvl 3 0.60317 14749.3 1 6 CACCTG ATGCATCTCATTAA - +4 taipale_cyt_meth__POU3F2_NTAATKAKATGCAN_eDBD-pdm3-vvl 3 0.60317 14749.3 1 6 CACCTG ATGCATCTCATTAT - +4 taipale_tf_pairs__TEAD4_FOXI1_GGWATGYGTMAACA_CAP_repr-sd 6 0.60317 14749.3 1 6 CACCTG TGTTGACGCATTCC - +4 transfac_pro__M05746 0 0.60317 14749.3 1 6 CACCTG GACATGCCTATTTG - +4 cisbp__M6156-cnc-Jra-kay-maf-S -1 0.60317 14749.3 1 5 CACCTG ACCATGACTCAGCA + +4 taipale__CREB3_full_NNRTGACGTCAYCN-Atf-2-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 9 0.60317 14749.3 1 5 CACCTG CGATGACGTCATCA + +4 cisbp__M5323-Atf-2-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 9 0.60317 14749.3 1 5 CACCTG CGATGACGTCATCA - +4 hocomoco__BACH1_MOUSE.H11MO.0.C-cnc-kay-maf-S -1 0.60317 14749.3 1 5 CACCTG ACCATGACTCAGCA - +4 taipale_cyt_meth__ZBTB12_NGCTGNNCCGCGYN_eDBD_repr 9 0.60317 14749.3 1 5 CACCTG GGCGCGGTTCAGCT - +4 cisbp__M0772 6 0.603419 14755.4 1 6 CACCTG TCTGATAACGAT + +4 flyfactorsurvey__Sug_F3-5-2_SOLEXA_5-lmd-sug 4 0.603419 14755.4 1 6 CACCTG AGACCCCCTGGA + +4 taipale__DBP_full_NRTTACGTAAYN-CG7786-gt-hng1-nej-Pdp1-slbo-vri 3 0.603419 14755.4 1 6 CACCTG TATTACGTAACA + +4 taipale__GLI2_DBD_GCGACCACNCTG_repr-ci 5 0.603419 14755.4 1 6 CACCTG GCGACCACACTG + +4 cisbp__M1483 5 0.603419 14755.4 1 6 CACCTG GAACACAAATTT - +4 cisbp__M5489-ci 5 0.603419 14755.4 1 6 CACCTG GCGACCACACTG - +4 flyfactorsurvey__Blimp-1_NAR_FBgn0035625-Blimp-1 5 0.603419 14755.4 1 6 CACCTG ACTTTCACTTTC - +4 flyfactorsurvey__CG9895_SANGER_10_FBgn0034810-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 4 0.603419 14755.4 1 6 CACCTG GCCACGCCCATT - +4 hocomoco__HSFY1_HUMAN.H11MO.0.D 1 0.603419 14755.4 1 6 CACCTG ATACGTTCGAAT - +4 idmmpmm__gt-CG7786-Pdp1-gt-vri 4 0.603419 14755.4 1 6 CACCTG TTATTACGTAAT - +4 taipale_cyt_meth__BATF3_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Irbp18-Jra-kay-REPTOR-BP-Xbp1 3 0.603419 14755.4 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__FOSL1_NRTGAYGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.603419 14755.4 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__HLF_NRTTRYGYAAYN_FL_meth_repr-CG7786-CrebB-gt-hng1-Pdp1-vri 3 0.603419 14755.4 1 6 CACCTG CGTTACGTAACG - +4 taipale_tf_pairs__ETV2_FOXI1_RSCGGATGTTKW_CAP-pnt 2 0.603419 14755.4 1 6 CACCTG TCAACATCCGGT - +4 transfac_pro__M05670 4 0.603419 14755.4 1 6 CACCTG TTTTTACCCCCA - +4 transfac_pro__M06025 1 0.603419 14755.4 1 6 CACCTG GCAGCTTACACT - +4 transfac_pro__M06079 6 0.603419 14755.4 1 6 CACCTG GCGTCTTTCCTG - +4 transfac_pro__M06603 4 0.603419 14755.4 1 6 CACCTG GTAGCACTTGGA - +4 transfac_pro__M07390-cnc 3 0.603419 14755.4 1 6 CACCTG AATGACTAAGCA - +4 taipale_tf_pairs__TEAD4_ERG_RSCGGAAATRCC_CAP-Ets97D-sd -1 0.603419 14755.4 1 5 CACCTG ACCGGAAATGCC + +4 transfac_pro__M05837 -1 0.603419 14755.4 1 5 CACCTG TCCACGGGGATA + +4 transfac_pro__M05667-CG12071 -1 0.603419 14755.4 1 5 CACCTG GCCTTTTTACAC - +4 transfac_pro__M06192 7 0.603419 14755.4 1 5 CACCTG TCTGGACCACAC - +4 transfac_pro__M06266-CG2120 7 0.603419 14755.4 1 5 CACCTG GCTTTTGCTCCA - +4 transfac_pro__M06627 7 0.603419 14755.4 1 5 CACCTG TATGCTTAACAG - +4 transfac_pro__M07447 -1 0.603419 14755.4 1 5 CACCTG GCCTCGTTTTGG - +4 transfac_pro__M00514-CrebB-Xbp1 -2 0.603419 14755.4 1 4 CACCTG CCTGACGCAATG + +4 transfac_pro__M05652 8 0.603419 14755.4 1 4 CACCTG TGGGGCTGCAGC + +4 flyfactorsurvey__tj_SANGER_5_FBgn0000964-cnc-maf-S-tj -2 0.603419 14755.4 1 4 CACCTG GCTAAGTCAGCA - +4 transfac_pro__M06313 8 0.603419 14755.4 1 4 CACCTG TCTCTTTTAACA - +4 transfac_pro__M06399 8 0.603419 14755.4 1 4 CACCTG TATGATGGCACA - +4 swissregulon__sacCer__HAP2-Nf-YA -1 0.603661 14761.3 1 5 CACCTG ACCAA - +4 hdpi__CBFB-Bgb-Bro -2 0.603661 14761.3 1 4 CACCTG CATTT - +4 cisbp__M0195-amos-ato-crp-da-dimm-Fer3-HLH3B-HLH54F-Oli-tap-twi-tx 2 0.604373 14778.7 1 6 CACCTG ACCATATGGT + +4 cisbp__M0303-Atf3-Atf6-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.604373 14778.7 1 6 CACCTG GATGACGTAA + +4 cisbp__M0889-Awh-C15-CG11085-CG18599-CG9876-E5-ems-en-ind-inv-Lim3-OdsH-repo-slou-unc-4 3 0.604373 14778.7 1 6 CACCTG TACTAATTAG + +4 cisbp__M0897-Abd-B-cad 3 0.604373 14778.7 1 6 CACCTG TTTTATGGGG + +4 cisbp__M1259 1 0.604373 14778.7 1 6 CACCTG CGACCAAATA + +4 cisbp__M1657 4 0.604373 14778.7 1 6 CACCTG GTGGGCCCAC + +4 cisbp__M1808 2 0.604373 14778.7 1 6 CACCTG TTTTTCGGAG + +4 fantom__motif155_AATARSTCCC 2 0.604373 14778.7 1 6 CACCTG AATAACTCCC + +4 homer__CTTCCGGGAA_Stat3-Stat92E-aop 1 0.604373 14778.7 1 6 CACCTG CTTCCGGGAA + +4 scertf__zhu.SUT2 0 0.604373 14778.7 1 6 CACCTG AAACTCCGAA + +4 stark__ACACNNACAC 1 0.604373 14778.7 1 6 CACCTG ACACAAACAC + +4 taipale_cyt_meth__SREBF1_RTCACMCCAY_eDBD_meth-SREBP 4 0.604373 14778.7 1 6 CACCTG ATCACCCCAC + +4 transfac_pro__M01176 4 0.604373 14778.7 1 6 CACCTG ATTTTTCCGA + +4 transfac_pro__M07038-CG7786-gt-Pdp1-vri 1 0.604373 14778.7 1 6 CACCTG TTACATAATC + +4 transfac_pro__M07549 3 0.604373 14778.7 1 6 CACCTG CCGTACGGCA + +4 transfac_pro__M07937-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.604373 14778.7 1 6 CACCTG GCCACGCCCA + +4 cisbp__M0405-btd-cbt-CG3065-CG42741-dar1-hkb-Klf15-luna-Sp1-Spps 4 0.604373 14778.7 1 6 CACCTG GCCACGCCCA - +4 cisbp__M0416-klu-sr 4 0.604373 14778.7 1 6 CACCTG CGCCCACGCA - +4 cisbp__M0912-Abd-B 3 0.604373 14778.7 1 6 CACCTG TTTTATGAGC - +4 cisbp__M1001-achi-esg-hth-sna-vis-wor 3 0.604373 14778.7 1 6 CACCTG TTTGACAGGT - +4 cisbp__M1659 4 0.604373 14778.7 1 6 CACCTG GTGGTCCCCA - +4 cisbp__M2339-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-GATAe-grn-HDAC1-nej-pnr 4 0.604373 14778.7 1 6 CACCTG TGTTTACTTT - +4 cisbp__M6203-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-GATAe-grn-Hcf-nej-pnr-pnt-RpII215-Taf1 3 0.604373 14778.7 1 6 CACCTG CACTTCCGGT - +4 hocomoco__AP2B_HUMAN.H11MO.0.B-TfAP-2 0 0.604373 14778.7 1 6 CACCTG GCCCCCGGGC - +4 homer__GGCGGGAARN_E2F6-E2f1 2 0.604373 14778.7 1 6 CACCTG CTTTCCCGCC - +4 predrem__nrMotif301 4 0.604373 14778.7 1 6 CACCTG CTCAGCCCTG - +4 stark__RTATATRTRB-Cf2 1 0.604373 14778.7 1 6 CACCTG GCACATATAC - +4 taipale__DMBX1_DBD_NNGGATTANN-bcd-Gsc-oc-Ptx1 3 0.604373 14778.7 1 6 CACCTG GTTAATCCGC - +4 transfac_pro__M00935-CG5641-NFAT 4 0.604373 14778.7 1 6 CACCTG AATTTTCCAC - +4 transfac_pro__M01982-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.604373 14778.7 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M01987-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-RpII215-Taf1 0 0.604373 14778.7 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M01993-aop-Eip74EF-Hr78-Stat92E 3 0.604373 14778.7 1 6 CACCTG CACTTCCGGG - +4 transfac_pro__M02037-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.604373 14778.7 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M02068-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 0 0.604373 14778.7 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M01985-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 -1 0.604373 14778.7 1 5 CACCTG ACCGGAAGTG + +4 transfac_pro__M05003 5 0.604373 14778.7 1 5 CACCTG TGGCCGACCC + +4 cisbp__M1930-CG12018-Dif-dl-Rel 5 0.604373 14778.7 1 5 CACCTG GGAAATTCCC - +4 homer__CCAAAAAGGG_SEP3 -1 0.604373 14778.7 1 5 CACCTG CCCTTTTTGG - +4 taipale_cyt_meth__SIX6_NSRTATCRYN_eDBD_repr-Optix-Six4-so 5 0.604373 14778.7 1 5 CACCTG AATGATACGC - +4 fantom__motif99_GYGTSANACG 6 0.604373 14778.7 1 4 CACCTG GTGTCATACG + +4 taipale__POU6F2_full_SCTMATTANN-Awh-CG18599-E5-ems-ind-Lim3-pdm3-ro -2 0.604373 14778.7 1 4 CACCTG GCTAATTAGA + +4 cisbp__M5748-Awh-CG18599-E5-ems-ind-Lim3-pdm3-ro -2 0.604373 14778.7 1 4 CACCTG GCTAATTAGA - +4 transfac_pro__M05498-salm-salr 6 0.604373 14778.7 1 4 CACCTG GCTGACTACA - +4 bergman__ovo-Poxn-ovo 2 0.604759 14788.2 1 6 CACCTG AGTAACAGT + +4 cisbp__M0936-bcd-Gsc-oc-Ptx1 3 0.604759 14788.2 1 6 CACCTG GCTAATCCC + +4 cisbp__M1238-nub-pdm2-vvl 0 0.604759 14788.2 1 6 CACCTG TTAATTAAT + +4 cisbp__M1876 3 0.604759 14788.2 1 6 CACCTG GAGTACAAC + +4 cisbp__M6165-Usf 1 0.604759 14788.2 1 6 CACCTG CAACCCAAA + +4 flyfactorsurvey__Cf2-PA_SANGER_2.5_FBgn0000286-Cf2 0 0.604759 14788.2 1 6 CACCTG TATCTGAAA + +4 jaspar__MA0242.1-Bgb-RunxA-RunxB-lz-run 1 0.604759 14788.2 1 6 CACCTG TAACCGCAA + +4 predrem__nrMotif1567 3 0.604759 14788.2 1 6 CACCTG CTCTTCATT + +4 predrem__nrMotif163 1 0.604759 14788.2 1 6 CACCTG AAAACTTCT + +4 predrem__nrMotif1635 0 0.604759 14788.2 1 6 CACCTG CTCCCGCCA + +4 predrem__nrMotif2271 3 0.604759 14788.2 1 6 CACCTG GCATTCCAG + +4 predrem__nrMotif300 3 0.604759 14788.2 1 6 CACCTG TGCCATCTA + +4 predrem__nrMotif446 3 0.604759 14788.2 1 6 CACCTG ACAAACCCA + +4 swissregulon__sacCer__YML081W 0 0.604759 14788.2 1 6 CACCTG TACCCCGCA + +4 taipale_cyt_meth__EN2_MTCGTTANY_eDBD_meth-bsh-btn-Dr-en-eve-exex-ind-inv-unpg 0 0.604759 14788.2 1 6 CACCTG ATCGTTAAT + +4 taipale_cyt_meth__HMX2_NCAMTTAAN_eDBD_meth-Hmx-tup 1 0.604759 14788.2 1 6 CACCTG CCACTTAAC + +4 transfac_pro__M04950 0 0.604759 14788.2 1 6 CACCTG TGCGTGCGT + +4 transfac_public__M00046 3 0.604759 14788.2 1 6 CACCTG GGCTTCCAC + +4 cisbp__M0484 3 0.604759 14788.2 1 6 CACCTG CTGAGCCAC - +4 cisbp__M1505 3 0.604759 14788.2 1 6 CACCTG CCCAAAATT - +4 cisbp__M4995-da-Hand 0 0.604759 14788.2 1 6 CACCTG CACATGGCC - +4 hocomoco__BRCA1_HUMAN.H11MO.0.D-Usf 1 0.604759 14788.2 1 6 CACCTG CAACCCAAA - +4 jaspar__MA0044.1 3 0.604759 14788.2 1 6 CACCTG GAGTACAAC - +4 predrem__nrMotif2239 0 0.604759 14788.2 1 6 CACCTG ATCCTTTAA - +4 predrem__nrMotif2291 1 0.604759 14788.2 1 6 CACCTG AAACCAATT - +4 predrem__nrMotif256 3 0.604759 14788.2 1 6 CACCTG CTGGCCCTG - +4 predrem__nrMotif643 3 0.604759 14788.2 1 6 CACCTG CAAAGCCTA - +4 predrem__nrMotif928 2 0.604759 14788.2 1 6 CACCTG AGCAGCTTG - +4 taipale_cyt_meth__GATA2_NYGATAASN_eDBD_repr-GATAe-grn-pnr 3 0.604759 14788.2 1 6 CACCTG CGTTATCGC - +4 transfac_pro__M04678-bi-egg-mor-Six4 1 0.604759 14788.2 1 6 CACCTG CTACAATTC - +4 transfac_pro__M05956-CG9650 3 0.604759 14788.2 1 6 CACCTG TTGTACGAC - +4 cisbp__M4773-br 4 0.604759 14788.2 1 5 CACCTG CATAGACCA + +4 neph__UW.Motif.0069 4 0.604759 14788.2 1 5 CACCTG AGAATGACT + +4 predrem__nrMotif121 4 0.604759 14788.2 1 5 CACCTG CAGCCAGCA + +4 predrem__nrMotif2035 4 0.604759 14788.2 1 5 CACCTG CTACTGCCC + +4 predrem__nrMotif2567 4 0.604759 14788.2 1 5 CACCTG GTCCTTCCC + +4 predrem__nrMotif2682 4 0.604759 14788.2 1 5 CACCTG CTAAAGCCA + +4 predrem__nrMotif802 4 0.604759 14788.2 1 5 CACCTG CTCTGTCCT + +4 predrem__nrMotif867 4 0.604759 14788.2 1 5 CACCTG GCTGTTCCT + +4 taipale__Rhox11_DBD_NGCTGTWAN_repr 4 0.604759 14788.2 1 5 CACCTG TTAACAGCG - +4 transfac_pro__M04682-bi-egg-mor-Six4 -1 0.604759 14788.2 1 5 CACCTG ACAATTCCC - +4 hocomoco__LHX6_MOUSE.H11MO.0.C-Awh -2 0.604759 14788.2 1 4 CACCTG GCTGATTAC + +4 predrem__nrMotif1553 -2 0.604759 14788.2 1 4 CACCTG TCTGCTTTA + +4 transfac_public__M00112-usp 5 0.604759 14788.2 1 4 CACCTG GGGGTCACG + +4 cisbp__M2541-usp 5 0.604759 14788.2 1 4 CACCTG GGGGTCACG - +4 predrem__nrMotif1404 -2 0.604759 14788.2 1 4 CACCTG CTTGTGCCT - +4 predrem__nrMotif1793 -2 0.604759 14788.2 1 4 CACCTG CCTCATGAA - +4 predrem__nrMotif905 5 0.604759 14788.2 1 4 CACCTG CAACACACA - +4 stark__GCTNMTTAA 5 0.604759 14788.2 1 4 CACCTG TTAAGAAGC - +4 predrem__nrMotif1221 -3 0.604759 14788.2 1 3 CACCTG CTTGTGGCT + +4 predrem__nrMotif1301 6 0.604759 14788.2 1 3 CACCTG AGCAGTCAC + +4 predrem__nrMotif1836 6 0.604759 14788.2 1 3 CACCTG TGGCACCAC + +4 predrem__nrMotif2228 6 0.604759 14788.2 1 3 CACCTG CTGGAACAC + +4 predrem__nrMotif266 6 0.604759 14788.2 1 3 CACCTG TCCCATCAC + +4 predrem__nrMotif761 6 0.604759 14788.2 1 3 CACCTG AAATGCCAC + +4 predrem__nrMotif827 -3 0.604759 14788.2 1 3 CACCTG CTTGAGAGA + +4 predrem__nrMotif101 6 0.604759 14788.2 1 3 CACCTG TCTCTTCAC - +4 predrem__nrMotif1411 6 0.604759 14788.2 1 3 CACCTG CTCAGGCAC - +4 predrem__nrMotif1519 6 0.604759 14788.2 1 3 CACCTG TCCATTCAC - +4 predrem__nrMotif179 6 0.604759 14788.2 1 3 CACCTG AGCAGACAC - +4 predrem__nrMotif1806 6 0.604759 14788.2 1 3 CACCTG AAAGCTCAC - +4 predrem__nrMotif2114 6 0.604759 14788.2 1 3 CACCTG TGACATCAC - +4 predrem__nrMotif625 6 0.604759 14788.2 1 3 CACCTG TGGACACAC - +4 predrem__nrMotif669 6 0.604759 14788.2 1 3 CACCTG CTGAGACAC - +4 hocomoco__SOX2_MOUSE.H11MO.1.A-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN 0 0.604987 14793.7 1 6 CACCTG TTCCTTTGTTCTG + +4 idmmpmm__ovo-ovo 5 0.604987 14793.7 1 6 CACCTG ACTGTTACTTTTA + +4 neph__UW.Motif.0094 4 0.604987 14793.7 1 6 CACCTG TCCCAGCCACCCA + +4 transfac_pro__M00638-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-svp-usp 2 0.604987 14793.7 1 6 CACCTG CTGAACTTTGACC + +4 transfac_pro__M09485-tll 6 0.604987 14793.7 1 6 CACCTG AGCGTTGACTTTT + +4 cisbp__M6149-htk 5 0.604987 14793.7 1 6 CACCTG CACAATACCAACC - +4 jaspar__MA0575.1 1 0.604987 14793.7 1 6 CACCTG GTAACCGTCACTT - +4 swissregulon__sacCer__SIP4 0 0.604987 14793.7 1 6 CACCTG CTCCATTCATCCG - +4 transfac_pro__M01223-CG12018-Dif-dl-Rel-shn 7 0.604987 14793.7 1 6 CACCTG GGGGAATTCCCCC - +4 transfac_pro__M09088 4 0.604987 14793.7 1 6 CACCTG CCACCACCGACAC - +4 transfac_pro__M09462-tll 6 0.604987 14793.7 1 6 CACCTG ATCGTTGACTTTT - +4 bergman__ems-ems -1 0.604987 14793.7 1 5 CACCTG AAATATAATGACA + +4 cisbp__M0321-maf-S-tj 8 0.604987 14793.7 1 5 CACCTG AAATTGCTGACGT + +4 stark__AANTNTAATGACA-ems -1 0.604987 14793.7 1 5 CACCTG AAATATAATGACA + +4 transfac_pro__M07679-Atf6-CrebA-CrebB-Xbp1 8 0.604987 14793.7 1 5 CACCTG TGCCACGTCATCA + +4 transfac_public__M00289-croc-fd59A-foxo 8 0.604987 14793.7 1 5 CACCTG TAAACAAACATCC + +4 taipale_cyt_meth__ELF3_NTGTGCGGATGCN_FL_repr 8 0.604987 14793.7 1 5 CACCTG CGCATCCGCACAC - +4 transfac_pro__M06380-zfh1 9 0.604987 14793.7 1 4 CACCTG GATCAGTACCACG - +4 cisbp__M2619-Mef2 1 0.60624 14824.4 1 6 CACCTG CTTTCTATATATGGAAAC + +4 cisbp__M2862 6 0.60624 14824.4 1 6 CACCTG GTGGGACACGTGGCGACT + +4 taipale__RUNX3_DBD_WAACCRCAAWAACCRCAN-Bgb-lz-run-RunxA-RunxB 10 0.60624 14824.4 1 6 CACCTG TAACCGCAAAAACCGCAA + +4 taipale_cyt_meth__UBP1_NNCCGGNNNNNNCCGGNN_eDBD-gem 0 0.60624 14824.4 1 6 CACCTG AACCGGTTCGAACCGGTT + +4 taipale_tf_pairs__TFAP4_DLX3_NNCAGCTGNNNNTAATKR_HT-crp 2 0.60624 14824.4 1 6 CACCTG ATCAGCTGATTTTAATTG + +4 tfdimers__MD00113-Myc 5 0.60624 14824.4 1 6 CACCTG AAATACACATGTGTATTT + +4 transfac_pro__M00403-Mef2-rump 11 0.60624 14824.4 1 6 CACCTG CGGTTTAAAAATAACCCA + +4 transfac_public__M00434 6 0.60624 14824.4 1 6 CACCTG GTGGGACACGTGGCGACT + +4 cisbp__M6406-ey-Poxm-sv-toy 5 0.60624 14824.4 1 6 CACCTG TGTCACGCATGACTGAAC - +4 hocomoco__EGR2_HUMAN.H11MO.0.A-CG42741-CTCF-CoRest-Spps-btd-ct-klu-luna-peb-sr 0 0.60624 14824.4 1 6 CACCTG CCCCTCCCACACCCCCCC - +4 taipale_tf_pairs__ERF_DLX2_RSCGGAANNNNNYMATTA_CAP_repr_1-Ets21C 11 0.60624 14824.4 1 6 CACCTG TAATTGGCCACTTCCGGT - +4 transfac_pro__M05862 12 0.60624 14824.4 1 6 CACCTG TCCACCAACCGCAAGCTT - +4 neph__UW.Motif.0419 3 0.608927 14890.1 1 6 CACCTG AAAAAAATTTCATATT + +4 swissregulon__hs__RBPJ.p2-Su(H) 7 0.608927 14890.1 1 6 CACCTG CTGTGGGAAACGGGGT + +4 taipale_tf_pairs__TEAD4_ONECUT2_RCATTCCNNATCGAYN_CAP_repr-onecut-sd 3 0.608927 14890.1 1 6 CACCTG ACATTCCGCATCGATC + +4 transfac_pro__M02773-btd-CG42741-dar1-luna-Spps 2 0.608927 14890.1 1 6 CACCTG TCGACCCCGCCCCTAT + +4 cisbp__M6225-ham 5 0.608927 14890.1 1 6 CACCTG TATCTTATCTTATCTT - +4 hocomoco__EGR2_HUMAN.H11MO.1.A-klu-luna-sr 1 0.608927 14890.1 1 6 CACCTG CCCCCGCCCACGCCCC - +4 taipale_cyt_meth__BCL6B_NYGCTTTCTAGGAATN_eDBD_meth 2 0.608927 14890.1 1 6 CACCTG AATTCCTAGAAAGCAA - +4 taipale_cyt_meth__FOXA3_NSYTAWGTAAACAAAN_FL-croc-fd59A-fkh-FoxP-nej 7 0.608927 14890.1 1 6 CACCTG GTTTGTTTACTTAAGG - +4 cisbp__M5780-CG5846-CG9727-Max-Rfx-SREBP 11 0.608927 14890.1 1 5 CACCTG CGTTGCCATGGTAACG + +4 taipale__RFX5_DBD_SGTTRCCATRGCAACS-CG5846-CG9727-Max-Rfx-SREBP 11 0.608927 14890.1 1 5 CACCTG CGTTGCCATGGTAACG - +4 transfac_pro__M06918 11 0.608927 14890.1 1 5 CACCTG CATATGATTCACACGT - +4 cisbp__M6075-CG5846-CG9727-Max-Rfx-SREBP 12 0.608927 14890.1 1 4 CACCTG CGTTGCCATGGCAACC + +4 taipale__Rfx2_DBD_NGTTRCCATGGYAACN-CG5846-CG9727-Max-Rfx-SREBP 12 0.608927 14890.1 1 4 CACCTG CGTTGCCATGGCAACC + +4 taipale__RFX3_DBD_NGTTNCCATGGNAACN-CG5846-CG9727-Max-Rfx-SREBP 12 0.608927 14890.1 1 4 CACCTG CGTTGCCATGGCAACG - +4 tfdimers__MD00084-scro 11 0.611039 14941.7 1 6 CACCTG TTTTTTTAATCCACTTAAAATTCTATA + +4 transfac_pro__M09116-Blimp-1-brm-CG17328-CG7839-HDAC1-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 4 0.611039 14941.7 1 6 CACCTG TTTTCACTTTTTCTTTTTTTTTTTTTT + +4 transfac_pro__M09123 1 0.611362 14949.6 1 6 CACCTG TTTACTTTTTGCTTTTTTT + +4 transfac_pro__M09418 9 0.611362 14949.6 1 6 CACCTG GTGACGTTTCATCTTCCTC + +4 transfac_pro__M09451 4 0.611362 14949.6 1 6 CACCTG AATTAACCATGGTTAAAAC + +4 cisbp__M0903-abd-A-Antp-Scr-Ubx 0 0.613956 15013.1 1 6 CACCTG TAATGGC + +4 cisbp__M1058-al-Awh-C15-CG11085-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-en-inv-lab-lbe-Lim3-lms-Lmx1a-Pph13-Rx-slou-unpg-Vsx1-Vsx2 1 0.613956 15013.1 1 6 CACCTG CTAATTA + +4 cisbp__M1892 1 0.613956 15013.1 1 6 CACCTG TTAATTG + +4 cisbp__M6339 0 0.613956 15013.1 1 6 CACCTG CTCCGGG + +4 jaspar__MA0063.1 1 0.613956 15013.1 1 6 CACCTG TTAATTG + +4 predrem__nrMotif8 0 0.613956 15013.1 1 6 CACCTG AGCCTCC + +4 transfac_pro__M00749-SREBP 0 0.613956 15013.1 1 6 CACCTG CACCCCA + +4 cisbp__M0928-al-Awh-bsh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-en-inv-lab-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-repo-ro-Traf4-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.613956 15013.1 1 6 CACCTG CTAATTA - +4 cisbp__M0991-tup 0 0.613956 15013.1 1 6 CACCTG CAATTAG - +4 cisbp__M0996 1 0.613956 15013.1 1 6 CACCTG TGATTTC - +4 hocomoco__MECP2_HUMAN.H11MO.0.C 0 0.613956 15013.1 1 6 CACCTG CTCCGGG - +4 predrem__nrMotif2184 2 0.613956 15013.1 1 5 CACCTG GATCCCA + +4 cisbp__M6437 2 0.613956 15013.1 1 5 CACCTG AGAACAG - +4 flyfactorsurvey__GATAe_SANGER_5_FBgn0038391-GATAd-GATAe-HDAC1-Jra-Snr1-grn-pnr-srp 2 0.613956 15013.1 1 5 CACCTG CTTATCA - +4 transfac_pro__M08826 -1 0.613956 15013.1 1 5 CACCTG GCCTCAC - +4 predrem__nrMotif1079 3 0.613956 15013.1 1 4 CACCTG CTTTATC + +4 predrem__nrMotif1281 -2 0.613956 15013.1 1 4 CACCTG TCTGGCA + +4 hdpi__HCFC2-Hcf 3 0.613956 15013.1 1 4 CACCTG GAAACCC - +4 fantom__motif71_CTCCGCW -3 0.613956 15013.1 1 3 CACCTG CTCCGCT + +4 swissregulon__hs__DBP.p2-CG7786-Pdp1-gt 4 0.613956 15013.1 1 3 CACCTG AGCAAAC + +4 cisbp__M1104-CG34031 1 0.614525 15027 1 6 CACCTG TTAATTGC + +4 cisbp__M1107 1 0.614525 15027 1 6 CACCTG CTGTCAAG + +4 jaspar__MA1067.1 2 0.614525 15027 1 6 CACCTG GGGACCAC + +4 predrem__nrMotif1232 2 0.614525 15027 1 6 CACCTG CAGACCAA + +4 predrem__nrMotif382 1 0.614525 15027 1 6 CACCTG AGAACTGA + +4 swissregulon__hs__FOXL1.p2 2 0.614525 15027 1 6 CACCTG TATACATA + +4 cisbp__M1496 2 0.614525 15027 1 6 CACCTG AGGACATC - +4 hdpi__GRHL1-grh 2 0.614525 15027 1 6 CACCTG TTAAACTT - +4 predrem__nrMotif1770 1 0.614525 15027 1 6 CACCTG TGAGCTTC - +4 transfac_pro__M07725-GATAe-grn-pnr 2 0.614525 15027 1 6 CACCTG CTTATCGC - +4 yetfasco__YER161C_1114 0 0.614525 15027 1 6 CACCTG GAAATGAA - +4 swissregulon__sacCer__SUT2 -1 0.614525 15027 1 5 CACCTG AACTCCGA + +4 cisbp__M5136-Optix 3 0.614525 15027 1 5 CACCTG TATCACTT - +4 flyfactorsurvey__Optix_SOLEXA_FBgn0025360-Optix 3 0.614525 15027 1 5 CACCTG TATCACTT - +4 transfac_pro__M07386-CG4328-Lmx1a 3 0.614525 15027 1 5 CACCTG AATTAGTC - +4 hdpi__FHL2-CG30178-CG31624-CG31988-CG34325 -2 0.614525 15027 1 4 CACCTG GCTAGGGA + +4 predrem__nrMotif1612 4 0.614525 15027 1 4 CACCTG TCATTACA + +4 predrem__nrMotif2031 -2 0.614525 15027 1 4 CACCTG CTTTAATC + +4 predrem__nrMotif2122 -2 0.614525 15027 1 4 CACCTG CTTGGTGT - +4 cisbp__M0059 5 0.614525 15027 1 3 CACCTG GCACACAC + +4 cisbp__M1652 5 0.614525 15027 1 3 CACCTG GGCCCCAC + +4 cisbp__M1655 5 0.614525 15027 1 3 CACCTG GGGACCAC + +4 elemento__ACACACAC 5 0.614525 15027 1 3 CACCTG ACACACAC + +4 elemento__ACGCACAC 5 0.614525 15027 1 3 CACCTG ACGCACAC + +4 elemento__ACGCCCAC-Sp1 5 0.614525 15027 1 3 CACCTG ACGCCCAC + +4 elemento__GACATCAC 5 0.614525 15027 1 3 CACCTG GACATCAC + +4 elemento__GACGTCAC 5 0.614525 15027 1 3 CACCTG GACGTCAC + +4 elemento__GCACACAC 5 0.614525 15027 1 3 CACCTG GCACACAC + +4 elemento__TGACACAC 5 0.614525 15027 1 3 CACCTG TGACACAC + +4 elemento__TGAGCCAC 5 0.614525 15027 1 3 CACCTG TGAGCCAC + +4 jaspar__MA1095.1 5 0.614525 15027 1 3 CACCTG GGGCCCAC + +4 jaspar__MA1096.1 5 0.614525 15027 1 3 CACCTG GGGACCAC + +4 jaspar__MA1097.1 5 0.614525 15027 1 3 CACCTG GGGCCCAC + +4 neph__UW.Motif.0163 -3 0.614525 15027 1 3 CACCTG CTTCAAAG + +4 cisbp__M0729-bs-croc-fd59A-fkh-FoxK-foxo-FoxP-slp2 5 0.614525 15027 1 3 CACCTG TTGTTTAC - +4 cisbp__M4232 1 0.614838 15034.6 1 6 CACCTG ATACATATATA + +4 cisbp__M4384 3 0.614838 15034.6 1 6 CACCTG TATCACTCATG + +4 flyfactorsurvey__slp1_NAR_FBgn0003430-FoxK-FoxL1-FoxP-bin-croc-foxo-slp1-slp2 5 0.614838 15034.6 1 6 CACCTG TTGTTTACATT + +4 taipale_cyt_meth__JUND_NRTGACTCATN_eDBD_meth-cnc-Jra-kay 5 0.614838 15034.6 1 6 CACCTG GATGACTCATC + +4 taipale_cyt_meth__KLF4_NRCCMCGCCCN_eDBD-btd-cbt-CG42741-dar1-luna-Sp1-Spps 5 0.614838 15034.6 1 6 CACCTG CACCACGCCCA + +4 transfac_pro__M01820-Atf6-CrebB-Jra 1 0.614838 15034.6 1 6 CACCTG TGACGTCACCG + +4 cisbp__M4599-Dp-E2f1-E2f2 5 0.614838 15034.6 1 6 CACCTG TTTCCCGCCCC - +4 cisbp__M6525-C15 1 0.614838 15034.6 1 6 CACCTG GCTCCTTGGCG - +4 hocomoco__RUNX1_HUMAN.H11MO.0.A-Bgb-Bro-MTA1-like-RunxA-RunxB-lz-run 2 0.614838 15034.6 1 6 CACCTG GAAACCACAGA - +4 predrem__nrMotif208-RpII215 0 0.614838 15034.6 1 6 CACCTG CCCCGGGCCGG - +4 transfac_pro__M04612 0 0.614838 15034.6 1 6 CACCTG TGCATGCATGC - +4 transfac_pro__M05540 3 0.614838 15034.6 1 6 CACCTG ATATCCCTATC - +4 transfac_pro__M06135 1 0.614838 15034.6 1 6 CACCTG TTTCCTTTAGC - +4 transfac_pro__M08917-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-Taf1 1 0.614838 15034.6 1 6 CACCTG CTACTTCCGGT - +4 transfac_public__M00354 0 0.614838 15034.6 1 6 CACCTG TCGCTTTTCTC - +4 yetfasco__YDR081C_1050 1 0.614838 15034.6 1 6 CACCTG ATACATATAAA - +4 yetfasco__YOL067C_1493 3 0.614838 15034.6 1 6 CACCTG TATCACTCATG - +4 hocomoco__SOX3_MOUSE.H11MO.0.C-Mad-Sox14-Sox100B-Sox102F-SoxN -1 0.614838 15034.6 1 5 CACCTG GCCTTTGTTCC + +4 transfac_pro__M07915-CG12219 6 0.614838 15034.6 1 5 CACCTG CACACACACTC + +4 cisbp__M6511-CG12018-Dif-dl-Rel-shn 6 0.614838 15034.6 1 5 CACCTG GGGAAATTCCC - +4 hocomoco__CEBPD_HUMAN.H11MO.0.C-Irbp18-Xrp1-nej 7 0.614838 15034.6 1 4 CACCTG ATTGCACAACC + +4 cisbp__M2240 10 0.615089 15040.8 1 6 CACCTG GGTAAGGATTTACGTCTTCA + +4 dbcorrdb__ATF3__ENCSR000BKC_1__m2-CrebB-E(z)-Max-RpII215-Usf 5 0.615089 15040.8 1 6 CACCTG GACGTCACTGGCGCGCGCCC + +4 dbcorrdb__BHLHE40__ENCSR000DZJ_1__m1-bigmax-Brf-btd-Clk-cnc-cwo-cyc-E2f1-E(z)-h-Hey-Max-Myc-RpII215-Spps-SREBP-tgo-tna-Usf-zfh1 4 0.615089 15040.8 1 6 CACCTG CCGGCACGTGACCGGGGGGG + +4 dbcorrdb__EZH2__ENCSR000ARD_1__m5-E(z) 9 0.615089 15040.8 1 6 CACCTG CCGACAAACTACCGCAAGAG + +4 dbcorrdb__HDAC6__ENCSR000ATJ_1__m1-HDAC6 7 0.615089 15040.8 1 6 CACCTG CGCGCGGCACCGCCCCGAGC + +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m3 6 0.615089 15040.8 1 6 CACCTG CAGTTAAACCTGACAAGCTC + +4 dbcorrdb__NR3C1__ENCSR000BHE_1__m3 5 0.615089 15040.8 1 6 CACCTG GTTTGTCCCTCGCAGAGGGG + +4 dbcorrdb__POLR2A__ENCSR000BJM_1__m1-Eip74EF-ERR-ewg-E(z)-Hcf-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha 4 0.615089 15040.8 1 6 CACCTG GCTGCGCTTCCGCCGTGGGC + +4 dbcorrdb__RFX5__ENCSR000EFD_1__m4 4 0.615089 15040.8 1 6 CACCTG TGTGCAACTGTTTCTCCCCG + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m2-Taf7 9 0.615089 15040.8 1 6 CACCTG ACACCCAGATCCCAGTTGCA + +4 dbcorrdb__TAF7__ENCSR000BNM_1__m3-Taf7 8 0.615089 15040.8 1 6 CACCTG CAAACAACCACAACCAAGAA + +4 homer__TGCAGTTCCAANAGTGGCCA_CTCF-SatelliteElement-CTCF 5 0.615089 15040.8 1 6 CACCTG TGCAGTTCCAACAGTGGCCA + +4 taipale_cyt_meth__ZNF787_RATGCMNNNNNNNTGCCTCR_FL_meth_repr-zfh1 4 0.615089 15040.8 1 6 CACCTG GATGCACGTACCGTGCCTCA + +4 taipale_tf_pairs__HOXB2_RFX5_SYMATTANNNNNNRGCAACN_CAP_repr-pb 8 0.615089 15040.8 1 6 CACCTG GTCATTACCGCATAGCAACG + +4 transfac_pro__M09043 1 0.615089 15040.8 1 6 CACCTG CCACCGACAAAACCACCACC + +4 yetfasco__YPR015C_871 10 0.615089 15040.8 1 6 CACCTG GGTAAGGATTTACGTCTTCA + +4 dbcorrdb__HDAC1__ENCSR000AQF_1__m4-HDAC1 7 0.615089 15040.8 1 6 CACCTG CCTTCCGCACCGGGGCCCGC - +4 dbcorrdb__PBX3__ENCSR000BGR_1__m1-btd-E2f2-kay-mor-Nf-YA-Spps-SREBP 3 0.615089 15040.8 1 6 CACCTG CCCCGCCTGTCAATCAGCGC - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m5-RpII215 5 0.615089 15040.8 1 6 CACCTG GCTCTCGCTTCTTGTGGTAG - +4 dbcorrdb__POLR2A__ENCSR000DLM_1__m1-pho-phol-RpII215-Taf1 10 0.615089 15040.8 1 6 CACCTG CCGCTTCCGCCATTTCCGGG - +4 dbcorrdb__POLR2A__ENCSR000FAY_1__m2-RpII215 6 0.615089 15040.8 1 6 CACCTG TTCTTTTAGTTTCCGCTACT - +4 dbcorrdb__RCOR1__ENCSR000ECM_1__m5-CoRest 10 0.615089 15040.8 1 6 CACCTG GCCCTGATGCCAGATGCTGG - +4 dbcorrdb__SREBF1__ENCSR000DYU_1__m2-CoRest-SREBP 6 0.615089 15040.8 1 6 CACCTG GGACAGCACCGGGGCGGGCG - +4 dbcorrdb__STAT3__ENCSR000DPB_1__m1-aop-Stat92E 0 0.615089 15040.8 1 6 CACCTG TCACTTCCGGGAAATGATTT - +4 dbcorrdb__TAF1__ENCSR000BHO_1__m1-lid-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 10 0.615089 15040.8 1 6 CACCTG CCGCCGCCGCCATCTTGGGG - +4 dbcorrdb__TAF1__ENCSR000BPF_1__m3-Taf1 7 0.615089 15040.8 1 6 CACCTG GGGCCCATATATGGCGGAGC - +4 dbcorrdb__TAF7__ENCSR000BNM_1__m9-Taf7 3 0.615089 15040.8 1 6 CACCTG TGTGGCTTTCCTATTGTGGT - +4 dbcorrdb__TBP__ENCSR000DZZ_1__m1-Bdp1-Brf-CG17209-Tbp 3 0.615089 15040.8 1 6 CACCTG CCCTAACCGCTGCGCCACCC - +4 dbcorrdb__eGFP-HDAC8__ENCSR000DJZ_1__m2 0 0.615089 15040.8 1 6 CACCTG CGCACATGCAAGTGGGAGCA - +4 homer__NAAACCGGTTCAAACCGGTT_Tcfcp2l1-gem 9 0.615089 15040.8 1 6 CACCTG AACCGGTTTGAACCGGTTTG - +4 taipale_cyt_meth__FOXA1_NWRWGTMAATATTKRYNYWN_FL-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.615089 15040.8 1 6 CACCTG CTAAGCAAATATTTACATAA - +4 transfac_pro__M01508 10 0.615089 15040.8 1 6 CACCTG GGTAAGGATTTACGTCTTCA - +4 transfac_pro__M01531 0 0.615089 15040.8 1 6 CACCTG TCCCCTTCGGCCGAAGGACG - +4 transfac_pro__M05280-Brf-brm-ERR-E(z)-SREBP-vtd 13 0.615089 15040.8 1 6 CACCTG GGCGGGGGCCCCCCACCCCC - +4 dbcorrdb__NANOG__ENCSR000BMT_1__m4 15 0.615089 15040.8 1 5 CACCTG TTGCATTTCAATGGGTCCCT - +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m3-egg 15 0.615089 15040.8 1 5 CACCTG TTTCGCCAGTGTTCTTTTGT - +4 cisbp__M6076-CG9727-Rfx 3 0.616056 15064.4 1 6 CACCTG CGTTGCCTAGCAACG + +4 flyfactorsurvey__CG3919_SANGER_5_FBgn0036423-CG3919 2 0.616056 15064.4 1 6 CACCTG CCAACGTGCAACACC + +4 flyfactorsurvey__ttk-PA_SOLEXA_FBgn0003870-seq-ttk 5 0.616056 15064.4 1 6 CACCTG AAAACAACCCCCAAA + +4 stark__RWWWASWBDYSKNMW-mirr 7 0.616056 15064.4 1 6 CACCTG AAAAACATTCCGAAA + +4 taipale_cyt_meth__HSF4_NGAANNTTCYRGAAN_eDBD_meth-Hsf-pb 2 0.616056 15064.4 1 6 CACCTG GGAACGTTCTAGAAC + +4 taipale_cyt_meth__IRX5_NCGCGWNNNWCGCGN_eDBD_meth_repr-ara-caup-mirr 8 0.616056 15064.4 1 6 CACCTG ACGCGTACAACGCGT + +4 taipale_cyt_meth__ZIC1_NMCCMCCCGCYGYGN_eDBD-lmd-opa 0 0.616056 15064.4 1 6 CACCTG GACCCCCCGCTGCGC + +4 taipale_tf_pairs__GLI3_NGACCACMCACGWNG_HT-ci 8 0.616056 15064.4 1 6 CACCTG GGACCACCCACGTCG + +4 transfac_pro__M09095 3 0.616056 15064.4 1 6 CACCTG CTCCACCGACAAAAT + +4 transfac_pro__M09139 4 0.616056 15064.4 1 6 CACCTG TTTAGATCTGATTTT + +4 cisbp__M4799-Cf2 6 0.616056 15064.4 1 6 CACCTG TATATGTATCCACCG - +4 cisbp__M4860-CG3919 2 0.616056 15064.4 1 6 CACCTG CCAACGTGCAACACC - +4 cisbp__M5066-btd-CG7368-CoRest-crol-ct-CTCF-l(3)neo38-peb-Rbbp5-Spps-Spt20-sr 8 0.616056 15064.4 1 6 CACCTG CCCCCCCCCCCCCCC - +4 homer__HWWGTCAGCAWWTTT_MafF-cic-maf-S-tj 9 0.616056 15064.4 1 6 CACCTG AAAATTGCTGACTTG - +4 scertf__macisaac.SNT2 9 0.616056 15064.4 1 6 CACCTG GTACGGCGCTATCAT - +4 taipale__Rfx2_DBD_SGTTGCYARGCAACS_repr-CG9727-Rfx 3 0.616056 15064.4 1 6 CACCTG CGTTGCCTAGCAACG - +4 taipale_cyt_meth__HSF1_NGAANNTTCNNGAAN_eDBD-Hsf-pb-srl 7 0.616056 15064.4 1 6 CACCTG CTTCTAGAACGTTCC - +4 taipale_cyt_meth__HSF4_NGAANNTTCNNGAAN_eDBD-Hsf-pb-srl 7 0.616056 15064.4 1 6 CACCTG CTTCTAGAACGTTCT - +4 transfac_pro__M01344-ct 7 0.616056 15064.4 1 6 CACCTG TAGTGATCATCATTA - +4 transfac_pro__M02959-ct 7 0.616056 15064.4 1 6 CACCTG TAGTGATCATCATTA - +4 transfac_pro__M05569-erm 8 0.616056 15064.4 1 6 CACCTG GTTTCATTTCCCTTC - +4 transfac_pro__M09056 8 0.616056 15064.4 1 6 CACCTG TCTTCGCCGACATCA - +4 transfac_pro__M09402 0 0.616056 15064.4 1 6 CACCTG TGCTTGTTTTTTACG - +4 tfdimers__MD00210-cad 7 0.616188 15067.6 1 6 CACCTG AATTAAAAATCTAGTTAATAATTAACTAAT + +4 c2h2_zfs__M5280-Dif-dl 2 0.616188 15067.6 1 6 CACCTG TCTCCCTTTCTTCCCTTCCCCTTCTCTCCT - +4 cisbp__M4310 0 0.616205 15068.1 1 6 CACCTG TTCCGG + +4 hdpi__MORN1 1 0.616205 15068.1 1 5 CACCTG ATTTCT - +4 hdpi__ZCCHC14 1 0.616205 15068.1 1 5 CACCTG GCTCCC - +4 scertf__badis.YER184C -1 0.616205 15068.1 1 5 CACCTG TCCGGA - +4 transfac_pro__M03546 1 0.616205 15068.1 1 5 CACCTG TTAATT - +4 flyfactorsurvey__Caup_SOLEXA_FBgn0015919-caup-mirr 2 0.616205 15068.1 1 4 CACCTG ATAACA + +4 cisbp__M4796-caup-mirr 2 0.616205 15068.1 1 4 CACCTG ATAACA - +4 cisbp__M2053-so 3 0.616205 15068.1 1 3 CACCTG TGATAC + +4 jaspar__MA0246.1-so 3 0.616205 15068.1 1 3 CACCTG TGATAC + +4 hdpi__RARB-EcR -3 0.616205 15068.1 1 3 CACCTG CTTATA - +4 cisbp__M6501-HLH3B 17 0.616758 15081.6 1 6 CACCTG TCCAGTGGTTGGGCGACCATCTGTT + +4 tfdimers__MD00167 12 0.616758 15081.6 1 6 CACCTG CGGGGGCGCGGGCAGCTGTGGCCGG - +4 factorbook__v-Maf-cic-cnc-maf-S-tj 0 0.617431 15098 1 6 CACCTG TTGCTGAGTCAGCAATT + +4 taipale_tf_pairs__TEAD4_DLX2_RCATTCYNNNNCAATTA_CAP-sd 3 0.617431 15098 1 6 CACCTG ACATTCCACAGTAATTA + +4 hocomoco__BC11A_HUMAN.H11MO.0.A-CG9650-Dif-Ets96B-MTA1-like-Stat92E-dl-ebi-foxo-nej-sv 7 0.617431 15098 1 6 CACCTG TTTTCACTTCCTCTTTT - +4 taipale_tf_pairs__ERF_DLX3_RSCGGAANNNNYAATTA_CAP_repr-Ets21C 10 0.617431 15098 1 6 CACCTG TAATTGCCACTTCCGGT - +4 transfac_pro__M00992 8 0.617431 15098 1 6 CACCTG GTCTGAAACAACATTTC - +4 transfac_pro__M06844-ci-lmd-sug 4 0.617431 15098 1 6 CACCTG GGGCCACCCTACTTTAA - +4 transfac_pro__M07910-bowl-sob 3 0.617431 15098 1 6 CACCTG TGCTACCGTGTTACGCA - +4 transfac_pro__M08838-Sox100B 7 0.617431 15098 1 6 CACCTG AAAAAGGAGCCTTTGTG - +4 cisbp__M4849-CG33557-da 14 0.617552 15101 1 6 CACCTG TGTTGTGTCCGTGCCATCTGG + +4 cisbp__M6131-gem 7 0.617552 15101 1 6 CACCTG CCGGTTCAAACCGGTTCTGGC + +4 taipale_tf_pairs__ERF_HES7_NCCGGAANNNNNNCACGYGNN_CAP_repr-Ets21C 13 0.617552 15101 1 6 CACCTG ACCGGAAGTGCGGCACGTGCC + +4 taipale_tf_pairs__ETV2_NHLH1_NCCGGAANNNNNNCAGCTGNN_CAP_repr-HLH4C-pnt 13 0.617552 15101 1 6 CACCTG ACCGGAAGGGACGCAGCTGCG + +4 tfdimers__MD00068-Hsf-Myc 10 0.617552 15101 1 6 CACCTG ATTTAAGAACCATCTGTTCTT - +4 transfac_pro__M00323 2 0.617552 15101 1 6 CACCTG GGCCCCTGCGTGGGGGCGGGG - +4 transfac_pro__M09230-Taf1 3 0.617552 15101 1 6 CACCTG CTCCGCCGCCTCCTCCGCCGT - +4 transfac_pro__M05206 16 0.617552 15101 1 5 CACCTG ACGGAGCGGCGGGGCACACCC - +4 transfac_pro__M05208 16 0.617552 15101 1 5 CACCTG GGGGCCCGCCAAGGCCCACCA - +4 transfac_pro__M05265-ERR-E(z) 16 0.617552 15101 1 5 CACCTG GGGGGGCAGCGGGGCCCACCC - +4 transfac_pro__M05275 16 0.617552 15101 1 5 CACCTG GGGGCACGACGGGGACCACCA - +4 cisbp__M3986-Stat92E 15 0.618386 15121.4 1 6 CACCTG TTCCCAGAATTGCGTTTCCTAGAG + +4 tfdimers__MD00217-Tsf1-Tsf2-Tsf3 7 0.618386 15121.4 1 6 CACCTG TTAATGTCACTTCCCCATTTCCCC - +4 tfdimers__MD00226 11 0.618861 15133 1 6 CACCTG TAAAAGCCAGTTTCCTTTTTTT - +4 tfdimers__MD00548-Myc 4 0.618861 15133 1 6 CACCTG AAAAAACATTTGGCAATTATTA - +4 transfac_pro__M08797 10 0.618861 15133 1 6 CACCTG TATCCTCGCCGACATCACCACA - +4 tfdimers__MD00524-Med 7 0.619111 15139.1 1 6 CACCTG ATGTAAGAACATGTCTGGGCATG - +4 cisbp__M0619 6 0.620542 15174.1 1 6 CACCTG TTCGCGTAAACG + +4 cisbp__M5644-Myb 6 0.620542 15174.1 1 6 CACCTG ACCGTTAACGGT + +4 homer__NWAACCACADNN_RUNX2-Bgb-Bro-CG9650-MTA1-like-NFAT-RunxA-RunxB-ebi-lz-run 2 0.620542 15174.1 1 6 CACCTG CAAACCACAAAC + +4 predrem__nrMotif132 3 0.620542 15174.1 1 6 CACCTG CCTCCCCTCCCC + +4 predrem__nrMotif2393 3 0.620542 15174.1 1 6 CACCTG CAACCCCTCCCC + +4 swissregulon__hs__MYFfamily.p2-ac-ase-l(1)sc-nau-sc 3 0.620542 15174.1 1 6 CACCTG CAGCAGCAGCAG + +4 taipale__HLF_full_NRTTACGTAAYN-CG7786-gt-hng1-Pdp1-vri 3 0.620542 15174.1 1 6 CACCTG CATTACGTAACC + +4 taipale__MYBL1_DBD_NCCGTTAACGGN_repr-Myb 6 0.620542 15174.1 1 6 CACCTG ACCGTTAACGGT + +4 transfac_pro__M01258-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-pnt-Rbbp5-RpII215-Sin3A-Taf1 0 0.620542 15174.1 1 6 CACCTG CACTTCCGGCGC + +4 transfac_pro__M07246-Atf3-Atf6-crc-CrebA-CrebB-Irbp18-Jra-kay-Xbp1 3 0.620542 15174.1 1 6 CACCTG GATTACGTCATC + +4 transfac_pro__M07603-ind 0 0.620542 15174.1 1 6 CACCTG CACCTAATTAAT + +4 transfac_pro__M07683-CG7786-gt-hng1-nej-Pdp1-slbo-vri 3 0.620542 15174.1 1 6 CACCTG TATTACGTAATA + +4 c2h2_zfs__M3911-Blimp-1 5 0.620542 15174.1 1 6 CACCTG ACTTTCACTTTC - +4 cisbp__M4889-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.620542 15174.1 1 6 CACCTG GCCACGCCCATC - +4 cisbp__M6195-E2f1-E2f2 2 0.620542 15174.1 1 6 CACCTG CCTTCCCGCCCA - +4 cisbp__M6208-Eip74EF-Ets97D 4 0.620542 15174.1 1 6 CACCTG GCACTTCCTGGG - +4 predrem__nrMotif7 2 0.620542 15174.1 1 6 CACCTG CAGCCCTGTCCC - +4 taipale_cyt_meth__JDP2_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.620542 15174.1 1 6 CACCTG GATGACGTCATC - +4 transfac_pro__M06068 6 0.620542 15174.1 1 6 CACCTG TCGGCACCCCCG - +4 transfac_pro__M06354 0 0.620542 15174.1 1 6 CACCTG GCCCTATTAAAC - +4 transfac_pro__M06431 4 0.620542 15174.1 1 6 CACCTG GGACCACTTCTC - +4 transfac_pro__M06678 0 0.620542 15174.1 1 6 CACCTG TATCTTCGACAG - +4 transfac_pro__M06720 6 0.620542 15174.1 1 6 CACCTG TCTGCCCTCCAG - +4 transfac_pro__M07314-Blimp-1-ebi 4 0.620542 15174.1 1 6 CACCTG CTTTCACTTCCT - +4 transfac_pro__M09426 5 0.620542 15174.1 1 6 CACCTG GTCCGTACAATT - +4 cisbp__M1668 -1 0.620542 15174.1 1 5 CACCTG TCCAAACGAGAT + +4 hocomoco__SOX4_HUMAN.H11MO.0.B-Mad-Sox14-Sox100B-SoxN-pan -1 0.620542 15174.1 1 5 CACCTG TCCTTTGTTCTC + +4 taipale_tf_pairs__HOXB2_ETV4_ACCGGAAATGAN_CAP-Ets96B-pb -1 0.620542 15174.1 1 5 CACCTG ACCGGAAATGAC + +4 tiffin__TIFDMEM0000052 7 0.620542 15174.1 1 5 CACCTG TTAAAATTACTT + +4 cisbp__M6251-Psi 7 0.620542 15174.1 1 5 CACCTG AAAAAAACACAA - +4 neph__UW.Motif.0438 -1 0.620542 15174.1 1 5 CACCTG TTCTGTTTTTCA - +4 taipale_cyt_meth__GATA3_WGATAACGATCW_FL_meth-GATAe-grn-pnr-srp 7 0.620542 15174.1 1 5 CACCTG AGATCGTTATCT - +4 tiffin__TIFDMEM0000024 7 0.620542 15174.1 1 5 CACCTG TAAATATAATTT - +4 tiffin__TIFDMEM0000112 7 0.620542 15174.1 1 5 CACCTG TCGATTGTATTT - +4 transfac_pro__M05641 7 0.620542 15174.1 1 5 CACCTG TCTCTTCGACCC - +4 transfac_pro__M05735 7 0.620542 15174.1 1 5 CACCTG GATGTTACACGA - +4 transfac_pro__M05816 7 0.620542 15174.1 1 5 CACCTG CCCGTTGAACAG - +4 transfac_pro__M05822 7 0.620542 15174.1 1 5 CACCTG TTTCTGGACCCT - +4 transfac_pro__M06121-CG6654-CG7372 7 0.620542 15174.1 1 5 CACCTG GCTTTTTGACAG - +4 transfac_pro__M06219 7 0.620542 15174.1 1 5 CACCTG GCGGACTTTCCG - +4 transfac_pro__M06244 7 0.620542 15174.1 1 5 CACCTG TCGGCTCGACCG - +4 transfac_pro__M06644 7 0.620542 15174.1 1 5 CACCTG CCCTTTGAACAG - +4 transfac_pro__M06657-CG6654-CG7372 7 0.620542 15174.1 1 5 CACCTG GCTTTTTGACAG - +4 transfac_pro__M06716 -1 0.620542 15174.1 1 5 CACCTG ACCGACTATAAC - +4 transfac_pro__M06777-CG2120 7 0.620542 15174.1 1 5 CACCTG TCTCTATGAACG - +4 cisbp__M5244-cnc-maf-S-tj -2 0.620542 15174.1 1 4 CACCTG GCTGAGTCAGCA - +4 transfac_pro__M05424-CG9650 8 0.620542 15174.1 1 4 CACCTG GCGTTTCCCACT - +4 transfac_pro__M05894 8 0.620542 15174.1 1 4 CACCTG TCCGTTTTCACT - +4 transfac_pro__M05996 -2 0.620542 15174.1 1 4 CACCTG GCTGCCCCCCCA - +4 transfac_pro__M06231 8 0.620542 15174.1 1 4 CACCTG GCGTCTTCCACT - +4 transfac_pro__M06700 8 0.620542 15174.1 1 4 CACCTG TCAGCCGCAACG - +4 transfac_pro__M06760 8 0.620542 15174.1 1 4 CACCTG TCAACGGGCACA - +4 transfac_public__M00359-CrebB-Xbp1 8 0.620542 15174.1 1 4 CACCTG GTACACGTCATC - +4 cisbp__M2019-ara 1 0.620625 15176.1 1 4 CACCTG TAACA + +4 jaspar__MA0210.1-ara 1 0.620625 15176.1 1 4 CACCTG TAACA + +4 cisbp__M5324-Atf6-CrebA-CrebB-Xbp1 4 0.620627 15176.2 1 6 CACCTG TGATGACGTGGCAC + +4 cisbp__M5463-fd59A-FoxK-foxo-slp2 3 0.620627 15176.2 1 6 CACCTG GTAAACATGTTTAC + +4 cisbp__M5953-Atf6-CrebA-CrebB-Xbp1 3 0.620627 15176.2 1 6 CACCTG GATGACGTGGCATT + +4 homer__GTCACGCTCNCTGA_PAX5-sv 7 0.620627 15176.2 1 6 CACCTG GTCACGCTCCCTGA + +4 taipale__FOXO1_DBD_GTAAACATGTTTAC_repr-fd59A-FoxK-foxo-slp2 3 0.620627 15176.2 1 6 CACCTG GTAAACATGTTTAC + +4 taipale__FOXO4_DBD_GTAAACATGTTTAC-foxo 3 0.620627 15176.2 1 6 CACCTG GTAAACATGTTTAC + +4 taipale__XBP1_DBD_NNNGMCACGTCATC-Atf6-CrebA-CrebB-Xbp1 5 0.620627 15176.2 1 6 CACCTG AATGCCACGTCATC + +4 transfac_pro__M07865-Myb 4 0.620627 15176.2 1 6 CACCTG AAAAAACCGTTACA + +4 cisbp__M5842-Sox100B 6 0.620627 15176.2 1 6 CACCTG TGACTGCACATTCA - +4 cisbp__M6411-sv 2 0.620627 15176.2 1 6 CACCTG CCCGCTTCAGTGAC - +4 factorbook__AP1-CoRest-GATAe-Jra-Mef2-Myc-Stat92E-brm-cnc-grn-kay-mor-nej-pan-pnr 6 0.620627 15176.2 1 6 CACCTG ATGACTCACCCTCT - +4 hocomoco__ELF1_HUMAN.H11MO.0.A-Eip74EF-Hr78-RpII215-aop 1 0.620627 15176.2 1 6 CACCTG CCACTTCCGGGTTC - +4 hocomoco__HNF4A_MOUSE.H11MO.0.A-EcR-HDAC1-Hnf4-Spps-btd-nej-svp 2 0.620627 15176.2 1 6 CACCTG TGGACTTTGGCCTT - +4 neph__UW.Motif.0524 6 0.620627 15176.2 1 6 CACCTG TGCTGAAACCAGCC - +4 taipale__CREB3_full_NTGCCACGTCAYCN_repr-Atf6-CrebA-CrebB-Xbp1 4 0.620627 15176.2 1 6 CACCTG TGATGACGTGGCAC - +4 taipale__SOX8_DBD_TGAATRTKCAGWCA-Sox100B 6 0.620627 15176.2 1 6 CACCTG TGACTGCACATTCA - +4 taipale_tf_pairs__FLI1_FOXI1_TGTTKMCGGAWRNN_CAP 0 0.620627 15176.2 1 6 CACCTG CACTTCCGTAAACA - +4 transfac_pro__M07321-btd-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-Spps-svp-usp 2 0.620627 15176.2 1 6 CACCTG CTGAACTTTGCCCT - +4 transfac_pro__M09107-Hsf-pb 6 0.620627 15176.2 1 6 CACCTG TTCTAGAAGCTTCT - +4 taipale__FLI1_full_ACCGGAWATCCGGT-Ets21C-Ets97D-pnt -1 0.620627 15176.2 1 5 CACCTG ACCGGAAATCCGGT + +4 cisbp__M3313-GATAe-grn-pnr 9 0.620627 15176.2 1 5 CACCTG CCGCTAATCTGCCT - +4 cisbp__M0012 0 0.621099 15187.7 1 6 CACCTG CGCCGCCATT + +4 cisbp__M0036-Taf1 1 0.621099 15187.7 1 6 CACCTG CCGCCGCCAT + +4 cisbp__M0891-bsh-C15-lab 1 0.621099 15187.7 1 6 CACCTG TTAATTGGTT + +4 cisbp__M1260 0 0.621099 15187.7 1 6 CACCTG TTCCAAAATT + +4 cisbp__M1290 4 0.621099 15187.7 1 6 CACCTG GGGTTAACCC + +4 cisbp__M1775 3 0.621099 15187.7 1 6 CACCTG TTCACCCGCC + +4 cisbp__M1833 3 0.621099 15187.7 1 6 CACCTG AAACTCCGAA + +4 cisbp__M6144-TfAP-2 0 0.621099 15187.7 1 6 CACCTG GCCCCCGGGC + +4 jaspar__MA0993.1 0 0.621099 15187.7 1 6 CACCTG CGCCGCCATT + +4 predrem__nrMotif13 4 0.621099 15187.7 1 6 CACCTG CCCTCACCCC + +4 predrem__nrMotif1886 3 0.621099 15187.7 1 6 CACCTG AGAAACATTT + +4 taipale_cyt_meth__HMX2_NCCAMTTAAN_FL-bap-Hmx 2 0.621099 15187.7 1 6 CACCTG ACCACTTAAC + +4 tiffin__TIFDMEM0000058 2 0.621099 15187.7 1 6 CACCTG GCCAACTAAA + +4 transfac_pro__M00629-eve 3 0.621099 15187.7 1 6 CACCTG TCAGCTCTGC + +4 transfac_pro__M02011-h-Sidpn 2 0.621099 15187.7 1 6 CACCTG GGCACGAGCC + +4 transfac_pro__M02281-btd-kay-klu-Nf-YB-Pglym78-Pglym87-sd-Spps 3 0.621099 15187.7 1 6 CACCTG CCCCGCCCCC + +4 transfac_pro__M07572-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.621099 15187.7 1 6 CACCTG ATGACGTCAC + +4 transfac_pro__M09097 4 0.621099 15187.7 1 6 CACCTG ATCCGACAAA + +4 cisbp__M0381 4 0.621099 15187.7 1 6 CACCTG GCGCATCCTT - +4 predrem__nrMotif119 2 0.621099 15187.7 1 6 CACCTG CACAGCTGTG - +4 predrem__nrMotif2229 4 0.621099 15187.7 1 6 CACCTG CAGCAGCCTC - +4 predrem__nrMotif975 2 0.621099 15187.7 1 6 CACCTG TAAACATTTA - +4 taipale_cyt_meth__SRF_CCWTGTWNGG_eDBD_meth-bs 3 0.621099 15187.7 1 6 CACCTG CCATACATGG - +4 taipale_cyt_meth__TFAP4_ANCATATGNT_eDBD-amos-ato-crp-dimm-Fer3-HLH54F-Oli-twi 2 0.621099 15187.7 1 6 CACCTG ACCATATGTT - +4 transfac_pro__M01307 4 0.621099 15187.7 1 6 CACCTG TTTTTGCATT - +4 transfac_public__M00032-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.621099 15187.7 1 6 CACCTG TACTTCCGGT - +4 predrem__nrMotif76 -1 0.621099 15187.7 1 5 CACCTG TTCTGAGCTT + +4 transfac_pro__M01734-NFAT 5 0.621099 15187.7 1 5 CACCTG AGATTTTCCT + +4 fantom__motif55_CGTTATAGCC -1 0.621099 15187.7 1 5 CACCTG GGCTATAACG - +4 predrem__nrMotif2385 -1 0.621099 15187.7 1 5 CACCTG ACATTTGTCT - +4 taipale_cyt_meth__POU6F1_NTAATKAGSN_FL_meth-pdm3 -1 0.621099 15187.7 1 5 CACCTG ATCTCATTAA - +4 transfac_pro__M08916-fd59A-fkh-FoxK-foxo-FoxP-slp2 5 0.621099 15187.7 1 5 CACCTG GTAAACAAAT - +4 predrem__nrMotif414 6 0.621099 15187.7 1 4 CACCTG AGACAGAACA + +4 yetfasco__YPR086W_1327-TfIIB 6 0.621099 15187.7 1 4 CACCTG ATAGCGCCCC + +4 predrem__nrMotif1737 6 0.621099 15187.7 1 4 CACCTG AAATAAAACT - +4 predrem__nrMotif373 6 0.621099 15187.7 1 4 CACCTG CCCCAAGACC - +4 transfac_pro__M05640 -2 0.621099 15187.7 1 4 CACCTG TCTGCTGCCA - +4 transfac_pro__M05868 6 0.621099 15187.7 1 4 CACCTG ACTGCCCACA - +4 transfac_pro__M07266-nej-Rrp1 -3 0.621099 15187.7 1 3 CACCTG CTGTCTCCAT + +4 transfac_pro__M05768 7 0.621099 15187.7 1 3 CACCTG GCGTTTTAAC - +4 cisbp__M0035 0 0.621368 15194.3 1 6 CACCTG TGGCGGCCT + +4 cisbp__M0598 3 0.621368 15194.3 1 6 CACCTG ATTTGAATT + +4 cisbp__M0834 3 0.621368 15194.3 1 6 CACCTG CCTAATCAA + +4 cisbp__M1187-CG15696-en-inv 1 0.621368 15194.3 1 6 CACCTG TTAATTGGC + +4 cisbp__M1358 2 0.621368 15194.3 1 6 CACCTG TAACCCTAG + +4 cisbp__M5096-lola 0 0.621368 15194.3 1 6 CACCTG GAGCTTTCA + +4 predrem__nrMotif1863 1 0.621368 15194.3 1 6 CACCTG CCGCCTCCA + +4 predrem__nrMotif1996 0 0.621368 15194.3 1 6 CACCTG CAGCAGTGT + +4 predrem__nrMotif2538 3 0.621368 15194.3 1 6 CACCTG ACTGTCATT + +4 stark__HSWAACHGH-Poxn-ovo 2 0.621368 15194.3 1 6 CACCTG TCAAACTGT + +4 taipale_cyt_meth__HMX1_NCAMTTAAN_eDBD-Hmx-tup 1 0.621368 15194.3 1 6 CACCTG GCACTTAAC + +4 transfac_pro__M06008 0 0.621368 15194.3 1 6 CACCTG TTCGTATTT + +4 cisbp__M0425 1 0.621368 15194.3 1 6 CACCTG GTGCCAACC - +4 cisbp__M3525 1 0.621368 15194.3 1 6 CACCTG TCTCCCAAA - +4 flyfactorsurvey__lola_SOLEXA_5_FBgn0005630-lola 0 0.621368 15194.3 1 6 CACCTG GAGCTTTCA - +4 hdpi__HIST1H2BN-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG33886-His2B:CG33888-His2B:CG33890-Hi 0 0.621368 15194.3 1 6 CACCTG CGCATGCGC - +4 predrem__nrMotif2054 0 0.621368 15194.3 1 6 CACCTG CACATATTT - +4 predrem__nrMotif2514 0 0.621368 15194.3 1 6 CACCTG TATTTGAGA - +4 predrem__nrMotif261 2 0.621368 15194.3 1 6 CACCTG AATCCCTTT - +4 transfac_pro__M04879-Jra 3 0.621368 15194.3 1 6 CACCTG CATTTCCTT - +4 cisbp__M0694-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.621368 15194.3 1 5 CACCTG ACCGGAAGT + +4 cisbp__M6078 4 0.621368 15194.3 1 5 CACCTG TTAACAGCG + +4 flyfactorsurvey__br-PL_SANGER_5_FBgn0000210-br 4 0.621368 15194.3 1 5 CACCTG CATAGACCA + +4 predrem__nrMotif1402 4 0.621368 15194.3 1 5 CACCTG CCGCTTCCC + +4 predrem__nrMotif2620 4 0.621368 15194.3 1 5 CACCTG TTAATTCCT + +4 predrem__nrMotif729 -1 0.621368 15194.3 1 5 CACCTG ACCACTGCC + +4 transfac_pro__M05089 -1 0.621368 15194.3 1 5 CACCTG ACCGCACCG + +4 hdpi__H2AFY 4 0.621368 15194.3 1 5 CACCTG CAGCAATCT - +4 predrem__nrMotif1590 -1 0.621368 15194.3 1 5 CACCTG AACTGGGAT - +4 predrem__nrMotif169 4 0.621368 15194.3 1 5 CACCTG GTGTCTCCA - +4 predrem__nrMotif405 4 0.621368 15194.3 1 5 CACCTG TTCTTCCCT - +4 yetfasco__YHR206W_380 -1 0.621368 15194.3 1 5 CACCTG GCCTGGGCC - +4 bergman__usp-usp 5 0.621368 15194.3 1 4 CACCTG GGGGTCACG + +4 hocomoco__NFIB_MOUSE.H11MO.0.C-NfI -2 0.621368 15194.3 1 4 CACCTG CCTGGCAGC + +4 predrem__nrMotif262 5 0.621368 15194.3 1 4 CACCTG GTGCCCACA + +4 predrem__nrMotif445 -2 0.621368 15194.3 1 4 CACCTG CCTCCCCCA + +4 stark__CTTNNATAC -2 0.621368 15194.3 1 4 CACCTG CTTAAATAC + +4 cisbp__M5438-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp2 5 0.621368 15194.3 1 4 CACCTG TTGTTTACA - +4 predrem__nrMotif2533 5 0.621368 15194.3 1 4 CACCTG TCTCTAAAC - +4 predrem__nrMotif281 5 0.621368 15194.3 1 4 CACCTG TGAAAAACA - +4 taipale__FOXB1_full_WGTAAAYAN_repr-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp2 5 0.621368 15194.3 1 4 CACCTG TTGTTTACA - +4 taipale_cyt_meth__RFX7_NGTTGCYAN_eDBD_meth_repr-CG9727 5 0.621368 15194.3 1 4 CACCTG ATAGCAACG - +4 cisbp__M1661 6 0.621368 15194.3 1 3 CACCTG GGGGCCCAC + +4 jaspar__MA1019.1 6 0.621368 15194.3 1 3 CACCTG GGGGCCCAC + +4 predrem__nrMotif759 -3 0.621368 15194.3 1 3 CACCTG CTACTGACT - +4 tfdimers__MD00544-pho-phol-sd 18 0.621389 15194.8 1 6 CACCTG CCCTTCCCGCCATTTGCATTCCTCTCCCT + +4 taipale_tf_pairs__ETV5_EOMES_RNGTGNNNNNNNNNNNNNRCRCCGGAWSN_CAP-Ets96B 24 0.621389 15194.8 1 5 CACCTG ACATCCGGTGTGACCCCCCCTTCACACCT - +4 cisbp__M6202-aop-Eip74EF 1 0.622273 15216.4 1 6 CACCTG AAACCCGGAAGTA + +4 cisbp__M6277-CG7786-gt-Pdp1-vri 4 0.622273 15216.4 1 6 CACCTG CTGTTACGTAATC + +4 cisbp__M6497-Stat92E 3 0.622273 15216.4 1 6 CACCTG AAATTCCTGGGAA - +4 hocomoco__ARI5B_HUMAN.H11MO.0.C-htk 5 0.622273 15216.4 1 6 CACCTG CACAATACCAACA - +4 hocomoco__HLF_HUMAN.H11MO.0.C-CG7786-Pdp1-gt-vri 4 0.622273 15216.4 1 6 CACCTG CTGTTACATAATC - +4 neph__UW.Motif.0151 4 0.622273 15216.4 1 6 CACCTG GGAAAGCCATCTG - +4 taipale_cyt_meth__CREB3L1_TGCCACRYGTACR_FL_meth_repr-CrebA 2 0.622273 15216.4 1 6 CACCTG TGTACGCGTGGCA - +4 taipale_tf_pairs__ETV2_TBX21_TMACACMGGAARN_CAP-pnt 2 0.622273 15216.4 1 6 CACCTG GCTTCCGGTGTGA - +4 taipale_tf_pairs__FLI1_FOXI1_RCCGGATGTTKWY_CAP 3 0.622273 15216.4 1 6 CACCTG GTAAACATCCGGT - +4 transfac_pro__M05426 6 0.622273 15216.4 1 6 CACCTG AAGTTTTATCTAC - +4 cisbp__M3677-nub-pdm2 -1 0.622273 15216.4 1 5 CACCTG ACCTCATTACGAG + +4 transfac_public__M00137-nub-pdm2 -1 0.622273 15216.4 1 5 CACCTG ACCTCATTACGAG - +4 homer__GGTTAAACATTAAC_Hnf1 9 0.622273 15216.4 1 4 CACCTG TTAATGTTTAACC - +4 cisbp__M1836-Mef2 1 0.624178 15263 1 6 CACCTG CTTTCTATATATGGAAAC + +4 cisbp__M1890-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-yps 3 0.624178 15263 1 6 CACCTG AGAGTGCTGATTGGTCCA + +4 cisbp__M5793-Bgb-lz-run-RunxA-RunxB 1 0.624178 15263 1 6 CACCTG TAACCGCAAAAACCGCAA + +4 taipale_cyt_meth__UBP1_AWCCGGNNNNNNCCGGWT_eDBD_meth-gem 10 0.624178 15263 1 6 CACCTG AACCGGTTTAAACCGGTT + +4 taipale_cyt_meth__ZNF684_NYACAGTCCWCCCCTTKN_FL_repr 10 0.624178 15263 1 6 CACCTG ATACAGTCCACCCCTTTA + +4 transfac_pro__M07719-croc-fd59A-fd96Ca-fd96Cb-fkh 12 0.624178 15263 1 6 CACCTG TATGTAAATATTTACATA + +4 jaspar__MA0001.2-Mef2 1 0.624178 15263 1 6 CACCTG CTTTCTATATATGGAAAC - +4 taipale_cyt_meth__TFCP2_AWCCGGWTNNAWCCGGWT_eDBD_meth_repr-gem 0 0.624178 15263 1 6 CACCTG AACCGGTTTAAACCGGTT - +4 taipale_tf_pairs__ERF_PITX1_NSCGGANNNNNNGGMTTA_CAP-Ets21C-Ptx1 11 0.624178 15263 1 6 CACCTG TAATCCCCCACTTCCGGC - +4 taipale_tf_pairs__GCM1_PITX1_GGATTANNNNNNTGCGGG_CAP_repr-gcm-gcm2-Ptx1 4 0.624178 15263 1 6 CACCTG CCCGCATCCCCATAATCC - +4 hocomoco__VAX2_HUMAN.H11MO.0.D-Antp-CG34367-Dll-E5-Lim3-Scr-ap-ems-en-eve-ind-inv-pb-ro-slou-unpg 7 0.626639 15323.2 1 6 CACCTG CACTAATTACCCTAAA + +4 neph__UW.Motif.0402 5 0.626639 15323.2 1 6 CACCTG AAATTTGCCAAAAAAA + +4 neph__UW.Motif.0656 0 0.626639 15323.2 1 6 CACCTG TCCCTGCCTTTTCCCA + +4 taipale_cyt_meth__TFCP2L1_NCCGGNNNNNNCCGGN_eDBD-gem 9 0.626639 15323.2 1 6 CACCTG ACCGGTTCGAACCGGT + +4 transfac_pro__M01289 8 0.626639 15323.2 1 6 CACCTG TATCGTATAACATGAT + +4 transfac_pro__M01397-abd-A-Antp-Awh-CG18599-ind-lab-Lim3-pb-repo-Scr-Ubx-zfh2 8 0.626639 15323.2 1 6 CACCTG ACGTTAATTAACCCAG + +4 transfac_pro__M02878-pan 10 0.626639 15323.2 1 6 CACCTG GAAGATCAATCACTTA + +4 cisbp__M5946-EcR-usp 2 0.626639 15323.2 1 6 CACCTG TGAACTCAATGAACTC - +4 neph__UW.Motif.0427 2 0.626639 15323.2 1 6 CACCTG TGGCTCTGGCTTCTTG - +4 taipale_tf_pairs__HOXB13_ETV1_RSCGGAARYNNTAAAN_CAP_repr-Ets96B 6 0.626639 15323.2 1 6 CACCTG TTTTATTACTTCCGGT - +4 taipale_tf_pairs__HOXD12_ELK3_RSCGGAAGTCGTAAAN_CAP 6 0.626639 15323.2 1 6 CACCTG TTTTACGACTTCCGCC - +4 cisbp__M5775-CG5846-CG9727-Max-Rfx-SREBP 12 0.626639 15323.2 1 4 CACCTG CGTTGCCATGGCAACG - +4 transfac_pro__M07880-CG5846-CG9727-Max-Rfx-SREBP 12 0.626639 15323.2 1 4 CACCTG CGTTGCCATGGCAACG - +4 transfac_pro__M09269-bs 1 0.62937 15390 1 6 CACCTG TTTCCAAAAAAGGAAAAAA + +4 transfac_pro__M06737-CG2120 8 0.62937 15390 1 6 CACCTG CATATATCGACATACTCAT - +4 transfac_pro__M09083-Taf1 14 0.62937 15390 1 5 CACCTG TCCTCCGCCGCCACCGCCG - +4 tfdimers__MD00013-pho-phol 11 0.629818 15400.9 1 6 CACCTG TAACTTGTCACCATCTGTTGTCTTTTT + +4 cisbp__M0981-Antp-B-H1-B-H2-bsh-CG11085-CG32532-Dll-Dr-Drgx-en-exex-inv-lab-Lim1-lms-Scr-slou-Ubx-unpg 0 0.629942 15404 1 6 CACCTG TAATTGC + +4 hdpi__MAGEA8 1 0.629942 15404 1 6 CACCTG TTTCCAG - +4 hocomoco__UBIP1_HUMAN.H11MO.0.D-gem 0 0.629942 15404 1 6 CACCTG TTTCTGG - +4 transfac_pro__M01883 0 0.629942 15404 1 6 CACCTG TATTTTC - +4 transfac_pro__M07364-NfI 1 0.629942 15404 1 6 CACCTG CTGCCAA - +4 yetfasco__YGL162W_673 0 0.629942 15404 1 6 CACCTG CGCGGGG - +4 cisbp__M4771-br -1 0.629942 15404 1 5 CACCTG AACTATT + +4 transfac_pro__M00747 2 0.629942 15404 1 5 CACCTG TTCACTT + +4 cisbp__M4983-GATAd-GATAe-grn-HDAC1-Jra-pnr-Snr1-srp 2 0.629942 15404 1 5 CACCTG CTTATCA - +4 cisbp__M6261 2 0.629942 15404 1 5 CACCTG AGAACAG - +4 flyfactorsurvey__br-PA_SANGER_5_FBgn0000210-br -1 0.629942 15404 1 5 CACCTG AACTATT - +4 fantom__motif72_CAGAAMC 3 0.629942 15404 1 4 CACCTG CAGAAAC + +4 hdpi__SMUG1-CG5285 -2 0.629942 15404 1 4 CACCTG CGTGGAA + +4 hdpi__DIABLO 3 0.629942 15404 1 4 CACCTG TGGCAGC - +4 predrem__nrMotif1525 3 0.629942 15404 1 4 CACCTG TTGCCCC - +4 transfac_pro__M01243-MTF-1 4 0.629942 15404 1 3 CACCTG TGCGCAC + +4 cisbp__M0953 1 0.630962 15428.9 1 6 CACCTG ATTAATTA + +4 cisbp__M1580 0 0.630962 15428.9 1 6 CACCTG TCATTCAG + +4 predrem__nrMotif2220 0 0.630962 15428.9 1 6 CACCTG TGCCTACT + +4 taipale_cyt_meth__HOXA5_RTCGTTAN_eDBD_meth-Antp-btn-Dfd-exex-lab-pb-Scr 0 0.630962 15428.9 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__MSX2_NTCGTTAN_eDBD_meth-bap-bsh-btn-Dll-Dr-en-ind-inv-lab-Lim1-unpg 0 0.630962 15428.9 1 6 CACCTG CTCGTTAA + +4 transfac_pro__M01030 0 0.630962 15428.9 1 6 CACCTG TTTCTTGG - +4 cisbp__M1743 3 0.630962 15428.9 1 5 CACCTG TATTCCCG + +4 predrem__nrMotif1123 -1 0.630962 15428.9 1 5 CACCTG CCCAGATC + +4 swissregulon__sacCer__YNR063W -1 0.630962 15428.9 1 5 CACCTG ATCTCCGA + +4 cisbp__M0067 3 0.630962 15428.9 1 5 CACCTG GTGTACGC - +4 flyfactorsurvey__CG11617_SOLEXA_FBgn0031232-CG11617 3 0.630962 15428.9 1 5 CACCTG TGTTAAAA - +4 hdpi__RAN-Ran -1 0.630962 15428.9 1 5 CACCTG TCCTTTTG - +4 flyfactorsurvey__Aef1_FlyReg_FBgn0005694-Aef1 4 0.630962 15428.9 1 4 CACCTG CAACAACA + +4 neph__UW.Motif.0118 -2 0.630962 15428.9 1 4 CACCTG GCTGATAA + +4 predrem__nrMotif1132 4 0.630962 15428.9 1 4 CACCTG TTTGAACT + +4 scertf__spivak.PHD1 -2 0.630962 15428.9 1 4 CACCTG CATGCATC + +4 cisbp__M0801-GATAd-GATAe-grn-pnr-srp -2 0.630962 15428.9 1 4 CACCTG TCTTATCG - +4 predrem__nrMotif338 -2 0.630962 15428.9 1 4 CACCTG CCCGCGGG - +4 cisbp__M1646 5 0.630962 15428.9 1 3 CACCTG GGGACCAC + +4 cisbp__M1662 5 0.630962 15428.9 1 3 CACCTG GGGCCCAC + +4 homer__CTGTTTAC_Foxo1-foxo-FoxP-Sin3A 5 0.630962 15428.9 1 3 CACCTG CTGTTTAC + +4 jaspar__MA1035.1 5 0.630962 15428.9 1 3 CACCTG GGGACCAC + +4 taipale_cyt_meth__HOXB1_GTAATTAN_eDBD_meth-Antp-btn-Dfd-E5-ems-eve-exex-lab-Lim3-pb-Scr-slou 5 0.630962 15428.9 1 3 CACCTG CTAATTAC - +4 cisbp__M1837-Bgb-Bro-ebi-lz-MTA1-like-run-RunxA-RunxB 1 0.631698 15446.9 1 6 CACCTG AAACCACAGAC + +4 flyfactorsurvey__lola-PG_SOLEXA_FBgn0005630-lola 0 0.631698 15446.9 1 6 CACCTG GAGCTTTCGGG + +4 taipale_cyt_meth__FOXG1_NAYRYAAACAN_eDBD-slp2 0 0.631698 15446.9 1 6 CACCTG CACGCAAACAC + +4 transfac_pro__M00977-kn 1 0.631698 15446.9 1 6 CACCTG TTCCCTTGGGA + +4 transfac_pro__M03806 1 0.631698 15446.9 1 6 CACCTG GGCCCGGGCGG + +4 transfac_pro__M09010-CG7786-gt-hng1-Pdp1-REPTOR-BP-slbo-vri 2 0.631698 15446.9 1 6 CACCTG ATTACGTAACA + +4 transfac_pro__M09318 1 0.631698 15446.9 1 6 CACCTG GTAACCGAATT + +4 transfac_public__M00221-SREBP 3 0.631698 15446.9 1 6 CACCTG TATCACCCCAC + +4 cisbp__M1719 0 0.631698 15446.9 1 6 CACCTG CACCGGCGGAG - +4 cisbp__M2710 0 0.631698 15446.9 1 6 CACCTG GGGCTTTAGTT - +4 cisbp__M2712 0 0.631698 15446.9 1 6 CACCTG TCGCTTTTCTC - +4 cisbp__M4617-aop-Atac3-bs-Eip74EF-Ets21C-Hr78-RpII215-Sin3A 0 0.631698 15446.9 1 6 CACCTG CACTTCCGGGT - +4 cisbp__M5854-btd-cbt-CG3065-CG42741-dar1-Klf15-klu-luna-Sp1-Spps 4 0.631698 15446.9 1 6 CACCTG GCCACGCCCCC - +4 cisbp__M6265-ci-lmd-opa-sug 4 0.631698 15446.9 1 6 CACCTG AGACCACCCAC - +4 hocomoco__CREB1_HUMAN.H11MO.0.A-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-kay 1 0.631698 15446.9 1 6 CACCTG TGACGTCATCG - +4 hocomoco__GLI2_HUMAN.H11MO.0.D-ci-lmd-opa-sug 4 0.631698 15446.9 1 6 CACCTG AGACCACCCAC - +4 stark__YGCGTHAATTR 0 0.631698 15446.9 1 6 CACCTG CAATTTACGCA - +4 taipale_cyt_meth__POU2F3_NTATGCWAATN_eDBD_meth-nub-pdm2-vvl 4 0.631698 15446.9 1 6 CACCTG CATTTGCATAT - +4 transfac_pro__M06073 1 0.631698 15446.9 1 6 CACCTG AAACCAGCCAA - +4 transfac_pro__M06561-crol 5 0.631698 15446.9 1 6 CACCTG AGTCTTTCCCC - +4 transfac_pro__M06605 4 0.631698 15446.9 1 6 CACCTG GCTTTACCCCC - +4 transfac_public__M00352 0 0.631698 15446.9 1 6 CACCTG GTGCTTTAGTT - +4 predrem__nrMotif362 6 0.631698 15446.9 1 5 CACCTG TTTTCTCATCT + +4 fantom__motif134_ATAAGAGAGGC -1 0.631698 15446.9 1 5 CACCTG GCCTCTCTTAT - +4 transfac_pro__M05433-pan -1 0.631698 15446.9 1 5 CACCTG AACTCACTCCG - +4 transfac_pro__M05489-pan -1 0.631698 15446.9 1 5 CACCTG AACTCACTCCG - +4 cisbp__M5535 -2 0.631698 15446.9 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M5540 -2 0.631698 15446.9 1 4 CACCTG GCTCGTAAAAA + +4 flyfactorsurvey__ovo_SANGER_5_FBgn0003028-ovo 7 0.631698 15446.9 1 4 CACCTG ATAACGGTACT + +4 taipale__HOXB13_DBD_NCTCGTAAAAN -2 0.631698 15446.9 1 4 CACCTG GCTCGTAAAAA + +4 taipale_cyt_meth__HOXC10_NGYAATAAAAN_FL-abd-A-Abd-B-cad-eve-Ubx 7 0.631698 15446.9 1 4 CACCTG GTTTTATTACC - +4 transfac_pro__M05523 -2 0.631698 15446.9 1 4 CACCTG CCTATCCCCCA - +4 transfac_pro__M09441 8 0.631698 15446.9 1 3 CACCTG GTGGGTCCCAC - +4 transfac_pro__M01908 0 0.632362 15463.1 1 6 CACCTG TTCCGG + +4 transfac_pro__M04620 0 0.632362 15463.1 1 6 CACCTG TAACAA + +4 fantom__motif54_CGNGTA 0 0.632362 15463.1 1 6 CACCTG TACACG - +4 jaspar__MA0275.1 0 0.632362 15463.1 1 6 CACCTG TTCCGG - +4 jaspar__MA0417.1 1 0.632362 15463.1 1 5 CACCTG AAGCAT + +4 transfac_pro__M01680 1 0.632362 15463.1 1 5 CACCTG AAGCAT + +4 cisbp__M2222 1 0.632362 15463.1 1 5 CACCTG AAGCAT - +4 fantom__motif31_AGNCGT 1 0.632362 15463.1 1 5 CACCTG ACGACT - +4 fantom__motif58_CGGNAT 1 0.632362 15463.1 1 5 CACCTG ATACCG - +4 transfac_pro__M03580-Smox 1 0.632362 15463.1 1 5 CACCTG CTGTCT - +4 cisbp__M5110-ara-caup-mirr 2 0.632362 15463.1 1 4 CACCTG ATAACA + +4 jaspar__MA0260.1 2 0.632362 15463.1 1 4 CACCTG GAAACC + +4 c2h2_zfs__M1962 2 0.632362 15463.1 1 4 CACCTG GAAACC - +4 hdpi__PDLIM5-Zasp52 2 0.632362 15463.1 1 4 CACCTG CTCCCC - +4 transfac_pro__M08189 2 0.632362 15463.1 1 4 CACCTG GGAACA - +4 cisbp__M4320-GATAd-GATAe-grn-pnr-srp -3 0.632362 15463.1 1 3 CACCTG CTTATC - +4 tfdimers__MD00056-nej-zfh1 16 0.632957 15477.7 1 6 CACCTG AAAAAAAAGGAAGTGAAACAAAAATT + +4 tfdimers__MD00523-TfAP-2 6 0.632957 15477.7 1 6 CACCTG GGCCCATGCCTCTAGGGAAATGGGGC + +4 tfdimers__MD00451-scro-sens-2 11 0.632957 15477.7 1 6 CACCTG ATTAAAAAAATCACTTGAGTGTTATT - +4 transfac_pro__M00390 4 0.632957 15477.7 1 6 CACCTG AAAGCTCCGCGAAAGAGCGGATAGAG - +4 dbcorrdb__BDP1__ENCSR000DNX_1__m3-Bdp1 6 0.633171 15482.9 1 6 CACCTG GCTTAGCACCCGCGCCTTCC + +4 dbcorrdb__CHD2__ENCSR000ECP_1__m1-Chd1-CoRest 9 0.633171 15482.9 1 6 CACCTG ATCTCGCGAGACTTGGCGGG + +4 dbcorrdb__EP300__ENCSR000BHB_1__m2-nej 13 0.633171 15482.9 1 6 CACCTG GCCGGTAATGACGCAAATGG + +4 dbcorrdb__EP300__ENCSR000EHV_1__m3-CTCF-hbn-nej-OdsH 0 0.633171 15482.9 1 6 CACCTG TAATTGAATTAAATTAATTT + +4 dbcorrdb__ETS1__ENCSR000BKQ_1__m1-bi-egg-mor-Six4 7 0.633171 15482.9 1 6 CACCTG CTACAACTCCCGGCAGGCCC + +4 dbcorrdb__FOXP2__ENCSR000BGA_1__m1-E2f1-Eip74EF-E(z)-FoxP-Hcf-RpII215-Sin3A 9 0.633171 15482.9 1 6 CACCTG CGGCCTGTTTACGCCCCGGC + +4 dbcorrdb__IRF3__ENCSR000DZX_1__m2 7 0.633171 15482.9 1 6 CACCTG TTTTTTATAACAGAGACAAT + +4 dbcorrdb__MAFK__ENCSR000DYV_1__m2-maf-S 5 0.633171 15482.9 1 6 CACCTG TTATGCAGCAGTCATTTCTT + +4 dbcorrdb__MAFK__ENCSR000EBS_1__m1-cnc-maf-S-tj 0 0.633171 15482.9 1 6 CACCTG TTGCTGAGTCAGCAATTTTT + +4 dbcorrdb__RFX5__ENCSR000ECX_1__m1 2 0.633171 15482.9 1 6 CACCTG AGCAACCAATGACAGAACAG + +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m8-egg 9 0.633171 15482.9 1 6 CACCTG CTCACAGAATTCATTGGAGA + +4 dbcorrdb__SIN3A__ENCSR000BRM_1__m5-Sin3A 8 0.633171 15482.9 1 6 CACCTG TGTGTCAGCACCCGGTGGGC + +4 dbcorrdb__STAT3__ENCSR000DOZ_1__m1-aop-Stat92E 1 0.633171 15482.9 1 6 CACCTG GTCACTTCCGGGAAATGGGT + +4 dbcorrdb__STAT3__ENCSR000DZV_1__m3-Bgb-Bro-CG9650-lz-run-RunxA-RunxB-Stat92E 6 0.633171 15482.9 1 6 CACCTG AAAAACCACAGAGTGGATTT + +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m7-bon 3 0.633171 15482.9 1 6 CACCTG TTATACATAGGAGGATTCAC + +4 transfac_pro__M01503 12 0.633171 15482.9 1 6 CACCTG CTTTTCGGCGGCTATTTCTA + +4 transfac_public__M00069-CG10431-pho-phol-Taf1 7 0.633171 15482.9 1 6 CACCTG CCGCGGCCATCTTGGCTGCT + +4 yetfasco__YBR083W_815-sd 5 0.633171 15482.9 1 6 CACCTG CAACCAACATTCTTGATATA + +4 dbcorrdb__CTCF__ENCSR000DXW_1__m2-CTCF 13 0.633171 15482.9 1 6 CACCTG CGAGGCGCTGCACTGCCCCC - +4 dbcorrdb__EP300__ENCSR000DZG_1__m2-CG9650-ebi-foxo-Jra-kay-MTA1-like-nej-NFAT-Stat92E 13 0.633171 15482.9 1 6 CACCTG TCTCGAAATGACTCAGAATA - +4 dbcorrdb__EP300__ENCSR000EDV_1__m1-btd-EcR-HDAC1-Hnf4-Hr78-nej-Spps-svp-usp 2 0.633171 15482.9 1 6 CACCTG TCAAACTGGACTTTGATCTC - +4 dbcorrdb__ETS1__ENCSR000BPU_1__m1-bi-egg-mor-Six4 7 0.633171 15482.9 1 6 CACCTG ACTACAATTCCGAGAAGGCC - +4 dbcorrdb__FOXA2__ENCSR000BNI_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-GATAe-grn-HDAC1-nej-Nf1-pnr-slp2 7 0.633171 15482.9 1 6 CACCTG CTTTGTTTACTTAGGGAATA - +4 dbcorrdb__GATA3__ENCSR000EWV_1__m2-GATAe-grn-pnr 5 0.633171 15482.9 1 6 CACCTG AATTTTATCTGATCACAGAT - +4 dbcorrdb__MXI1__ENCSR000EIA_1__m2 14 0.633171 15482.9 1 6 CACCTG ATGGCAGCCGTTAGCACGTG - +4 dbcorrdb__POLR2A__ENCSR000EXX_1__m1-Eip74EF-ewg-Hcf-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha 4 0.633171 15482.9 1 6 CACCTG GCTGCGCTTCCGCCGTGGGG - +4 dbcorrdb__POLR2A__ENCSR000FAL_1__m1-E2f1-Eip74EF-E(z)-Hcf-Hr78-Max-RpII215-Sin3A-Taf1-TfIIFalpha 2 0.633171 15482.9 1 6 CACCTG GGCGCTTCCGCCGCGGGGCG - +4 dbcorrdb__TAF1__ENCSR000BKS_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sin3A-Taf1 7 0.633171 15482.9 1 6 CACCTG GGCGCCCAAGCTTCCGGCGG - +4 jaspar__MA0435.1 10 0.633171 15482.9 1 6 CACCTG TGTAAGGATTTACGTCTTCA - +4 taipale_tf_pairs__ERF_HES7_NNCACGTGNNNNCCGGAANN_CAP_repr-Ets21C 2 0.633171 15482.9 1 6 CACCTG ACTTCCGGTGAGCACGTGAA - +4 yetfasco__YPR013C_859 11 0.633171 15482.9 1 6 CACCTG CTAAAGTGATTTACGTTCAA - +4 dbcorrdb__CBX3__ENCSR000BRT_1__m6-HP1b-HP1c-HP1e-Su(var)205 -1 0.633171 15482.9 1 5 CACCTG ACCGGTCAGTCAAGACGTTT + +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m6-Snr1 15 0.633171 15482.9 1 5 CACCTG CCATGCTTCTTCTGTTATCT - +4 hocomoco__ZN121_HUMAN.H11MO.0.C-sv 16 0.633171 15482.9 1 4 CACCTG CTGGGCAACATAGCAAGACC + +4 factorbook__UA1-Chd1-CoRest 9 0.633589 15493.2 1 6 CACCTG CTCTCGCGAGATTTG + +4 scertf__pachkov.HSF1-Hsf-pb 2 0.633589 15493.2 1 6 CACCTG AGAACCTTCTAGAAA + +4 transfac_pro__M01009-Sidpn 1 0.633589 15493.2 1 6 CACCTG AAGGCTCGTGGCTCG + +4 transfac_pro__M02837-bon-opa 2 0.633589 15493.2 1 6 CACCTG CCCCCCCGGGGGGGT + +4 transfac_pro__M02885-nau 2 0.633589 15493.2 1 6 CACCTG AGCAACAGCCGCACC + +4 transfac_pro__M09041 6 0.633589 15493.2 1 6 CACCTG CACCGCCACCGACAC + +4 transfac_pro__M09320 8 0.633589 15493.2 1 6 CACCTG ACCACACGCGCCTCC + +4 cisbp__M4567-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-HDAC1-nej 7 0.633589 15493.2 1 6 CACCTG CTCTGTTTACTTTGC - +4 cisbp__M6122-CG9650-nej-Stat92E 4 0.633589 15493.2 1 6 CACCTG TCACTTCCTCTTTTT - +4 jaspar__MA0543.1 0 0.633589 15493.2 1 6 CACCTG TCTCTGCGTCTCTCT - +4 transfac_pro__M00769-Bgb-Bro-lz-run-RunxA-RunxB 3 0.633589 15493.2 1 6 CACCTG GCTAACCACAGACTT - +4 transfac_pro__M09047 9 0.633589 15493.2 1 6 CACCTG CCGCCGCCGCAACAG - +4 transfac_pro__M09295-Myb 7 0.633589 15493.2 1 6 CACCTG CAACGGTCATATTTT - +4 neph__UW.Motif.0010 10 0.633589 15493.2 1 5 CACCTG CTGGGCATGGTGCCA + +4 cisbp__M3956-bs -1 0.633589 15493.2 1 5 CACCTG GCCATATATGGCCAG - +4 cisbp__M6281 11 0.633589 15493.2 1 4 CACCTG GGTTAATTATTAACC + +4 hocomoco__HNF1A_MOUSE.H11MO.0.A 11 0.633589 15493.2 1 4 CACCTG GGTTAATTATTAACC - +4 hocomoco__HEY2_HUMAN.H11MO.0.D-Hey 5 0.635215 15532.9 1 6 CACCTG GGTGGCACGTGGCATTA + +4 hocomoco__ZN418_HUMAN.H11MO.0.C 10 0.635215 15532.9 1 6 CACCTG TGCTTTTAGCCTCTTCC + +4 taipale_cyt_meth__NR1I2_NYGAACYNNNYGAACYN_eDBD_repr-EcR-usp 11 0.635215 15532.9 1 6 CACCTG ATGAACTCGATGAACTC + +4 transfac_pro__M01466-Ptx1 10 0.635215 15532.9 1 6 CACCTG TGAGGGGGATTAACTAT + +4 transfac_pro__M09284-Myb 11 0.635215 15532.9 1 6 CACCTG AAAATAACCGTTACAAA + +4 taipale_tf_pairs__ERF_CEBPD_RSMGGAANTTGCGYAAN_CAP-Ets21C 10 0.635215 15532.9 1 6 CACCTG ATTGCGCAATTTCCGCT - +4 transfac_pro__M02753-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 9 0.635215 15532.9 1 6 CACCTG ACCTTTGTTTACATTTA - +4 transfac_pro__M05460-fd59A 2 0.635215 15532.9 1 6 CACCTG TTAAACTTGCTTTAACT - +4 tfdimers__MD00154-SREBP 10 0.635315 15535.4 1 6 CACCTG CCCCCTCCCCCACCCCCCCCCCCCC - +4 transfac_pro__M09129-brm-CG7839-maf-S-SREBP-vtd 12 0.635714 15545.1 1 6 CACCTG TTTTTTTTTTTTTTACTTTTT + +4 taipale_tf_pairs__ERF_HES7_NNCACGTGNNNNNCCGGAANN_CAP_repr-Ets21C 13 0.635714 15545.1 1 6 CACCTG ACTTCCGGTCCACCACGTGTC - +4 transfac_pro__M09075 14 0.635714 15545.1 1 6 CACCTG TCCACCGCCACCACCACCGCC - +4 transfac_pro__M09382 1 0.635714 15545.1 1 6 CACCTG TAACTTGTTCAGCAAGTTACC - +4 transfac_pro__M05293 16 0.635714 15545.1 1 5 CACCTG GGAGGGCGGCGGGGCACACCC - +4 tfdimers__MD00423 13 0.636837 15572.6 1 6 CACCTG TTTTTTTAATTCCCACCCCTTTTA + +4 tfdimers__MD00464-nub-pdm2 13 0.636837 15572.6 1 6 CACCTG TTATTTTAATATTTGCATTTATAT + +4 transfac_public__M00460-Stat92E 15 0.636837 15572.6 1 6 CACCTG TTCCCAGAATTGCGTTTCCTAGAG + +4 tfdimers__MD00304 3 0.637112 15579.3 1 6 CACCTG TCCTCTCTGTCCTCCTTCCCCC + +4 cisbp__M3552-Mef2-rump 15 0.637112 15579.3 1 6 CACCTG TTATTCTATTTTTAGAACCACA - +4 transfac_pro__M08798 10 0.637112 15579.3 1 6 CACCTG AATCCTCGCCGACATCACTCCA - +4 transfac_public__M00232-Mef2-rump 15 0.637112 15579.3 1 6 CACCTG TTATTCTATTTTTAGAACCACA - +4 tfdimers__MD00112-CG7786-gt-Pdp1-TfAP-2 2 0.637459 15587.8 1 6 CACCTG TTTTTTTGCATAAGCCTTTTTTT + +4 tfdimers__MD00130-eg-kni-knrl-pho-phol 7 0.637459 15587.8 1 6 CACCTG CCTCAGCCATCTGGCCTCTCTTT + +4 taipale_cyt_meth__ELF3_ACCCGGAAGNNNNNNNNNWWWWW_FL-Eip74EF-Ets21C-Hr78 12 0.637459 15587.8 1 6 CACCTG TTTTTTTCCGTTTACTTCCGGGT - +4 tfdimers__MD00376 12 0.637459 15587.8 1 6 CACCTG TTCATTTTTTACTTCCTCTTTTT - +4 transfac_pro__M03557-CG12018-Dif-dl-Rel 6 0.637555 15590.1 1 6 CACCTG GGGAATTCCCCC + +4 transfac_pro__M04618 4 0.637555 15590.1 1 6 CACCTG TCTCTATCTCTA + +4 transfac_pro__M05084 6 0.637555 15590.1 1 6 CACCTG AGTAACGGCCTC + +4 transfac_pro__M05664-Cf2 2 0.637555 15590.1 1 6 CACCTG TGGTCCTAAAGC + +4 transfac_pro__M06128-CG6654-CG7372 6 0.637555 15590.1 1 6 CACCTG TGGGCCAACCGC + +4 transfac_pro__M06742 5 0.637555 15590.1 1 6 CACCTG ATCAAAACGTTC + +4 cisbp__M5516-CG7786-gt-hng1-Pdp1-vri 3 0.637555 15590.1 1 6 CACCTG CATTACGTAACC - +4 flyfactorsurvey__Espl_FlyReg_FBgn0000591-E(spl)m8-HLH 1 0.637555 15590.1 1 6 CACCTG GCACGAGGCACA - +4 hocomoco__E2F6_MOUSE.H11MO.0.A-E2f1-E2f2 2 0.637555 15590.1 1 6 CACCTG CCTTCCCGCCCA - +4 neph__UW.Motif.0192 5 0.637555 15590.1 1 6 CACCTG TGATTCACATTT - +4 taipale_cyt_meth__ATF6B_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.637555 15590.1 1 6 CACCTG GATGACGTCACC - +4 taipale_cyt_meth__DBP_NRTTAYGTAAYN_FL-CG7786-CrebB-gt-hng1-Pdp1-vri 3 0.637555 15590.1 1 6 CACCTG CGTTACGTAACG - +4 tiffin__TIFDMEM0000038 5 0.637555 15590.1 1 6 CACCTG TTTATTACAAAT - +4 transfac_pro__M05924 6 0.637555 15590.1 1 6 CACCTG AAACCCGGCCTA - +4 transfac_pro__M06460-CG3281 2 0.637555 15590.1 1 6 CACCTG TCTACTTCCCCA - +4 transfac_pro__M06622 6 0.637555 15590.1 1 6 CACCTG TCGTTTTCCCAG - +4 transfac_pro__M09232-Hsf 5 0.637555 15590.1 1 6 CACCTG TCTAGAAGCTTC - +4 transfac_pro__M06672 7 0.637555 15590.1 1 5 CACCTG CGGGGCAAACCC + +4 transfac_pro__M06789 7 0.637555 15590.1 1 5 CACCTG ACGGGGGAACCC + +4 hocomoco__FUBP1_HUMAN.H11MO.0.D-Psi 7 0.637555 15590.1 1 5 CACCTG AAAAAAACACAA - +4 transfac_pro__M05661-CG12071-CG6654-CG7372 7 0.637555 15590.1 1 5 CACCTG GATTTTTTATCA - +4 transfac_pro__M05803 7 0.637555 15590.1 1 5 CACCTG TCTCCCATAACA - +4 transfac_pro__M06535 7 0.637555 15590.1 1 5 CACCTG TCGGCAGCCCCA - +4 transfac_pro__M06590 7 0.637555 15590.1 1 5 CACCTG GATTTTTTACAT - +4 transfac_pro__M05688 8 0.637555 15590.1 1 4 CACCTG TGGAAAAAAATC + +4 transfac_pro__M06256 -2 0.637555 15590.1 1 4 CACCTG TCTGGCGGATCC + +4 transfac_pro__M06895 8 0.637555 15590.1 1 4 CACCTG GTGGCCTACAAC + +4 cisbp__M2682-CrebB-Xbp1 8 0.637555 15590.1 1 4 CACCTG GTACACGTCATC - +4 transfac_pro__M01928 0 0.637573 15590.6 1 5 CACCTG TTCCG + +4 jaspar__MA0311.1 0 0.637573 15590.6 1 5 CACCTG TTCCG - +4 jaspar__MA0233.1 1 0.637573 15590.6 1 4 CACCTG AAACA + +4 hdpi__MGC10334-CG30392 -2 0.637573 15590.6 1 4 CACCTG GCTCC - +4 jaspar__MA0064.1 -2 0.637573 15590.6 1 4 CACCTG GCTTT - +4 hdpi__KIF22 -3 0.637573 15590.6 1 3 CACCTG CTCAT - +4 cisbp__M0023 0 0.637729 15594.4 1 6 CACCTG CGCCGCCATT + +4 cisbp__M0130 2 0.637729 15594.4 1 6 CACCTG CGCAATTTCG + +4 cisbp__M0580 1 0.637729 15594.4 1 6 CACCTG TCCGCGGTTT + +4 cisbp__M0641-dmrt11E-dmrt93B-dmrt99B-dsx 2 0.637729 15594.4 1 6 CACCTG TGTATCAATT + +4 cisbp__M0852 2 0.637729 15594.4 1 6 CACCTG AATTAATGCG + +4 cisbp__M1522-NFAT 3 0.637729 15594.4 1 6 CACCTG ATTTTCCATT + +4 cisbp__M1673 3 0.637729 15594.4 1 6 CACCTG ACCCCCACTT + +4 cisbp__M2594-CG7786-gt-hng1-Pdp1-REPTOR-BP-vri 2 0.637729 15594.4 1 6 CACCTG ATTACGTAAC + +4 cisbp__M5346-bcd-Gsc-oc 3 0.637729 15594.4 1 6 CACCTG GCTAATCCGT + +4 homer__AAACCACAAA_RUNX1-Bgb-Bro-MTA1-like-RunxA-RunxB-Stat92E-lz-run 4 0.637729 15594.4 1 6 CACCTG AAACCACAAC + +4 homer__AACCGGAAGT_ELF1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-nej 0 0.637729 15594.4 1 6 CACCTG AACCGGAAGT + +4 homer__CAAACCACAG_RUNX-Bgb-Bro-RunxA-RunxB-ebi-lz-run 2 0.637729 15594.4 1 6 CACCTG CAAACCACAG + +4 predrem__nrMotif1594 1 0.637729 15594.4 1 6 CACCTG GCGCCGGCTC + +4 transfac_pro__M04968 2 0.637729 15594.4 1 6 CACCTG AAAACCGATC + +4 transfac_pro__M05008 4 0.637729 15594.4 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M05021 4 0.637729 15594.4 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M07682-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.637729 15594.4 1 6 CACCTG ATGACGTCAT + +4 transfac_public__M00398-CG7786-gt-hng1-Pdp1-REPTOR-BP-vri 2 0.637729 15594.4 1 6 CACCTG ATTACGTAAC + +4 cisbp__M0123 4 0.637729 15594.4 1 6 CACCTG TTTTTGCCTC - +4 cisbp__M0474-klu-sr 0 0.637729 15594.4 1 6 CACCTG TACCCCACAT - +4 cisbp__M0819 3 0.637729 15594.4 1 6 CACCTG TCCGACACTG - +4 cisbp__M1044-abd-A-Abd-B-cad-Dbx-eve-Ubx 3 0.637729 15594.4 1 6 CACCTG TTTTATGACC - +4 cisbp__M1463 3 0.637729 15594.4 1 6 CACCTG GGACACAAAA - +4 cisbp__M1504 0 0.637729 15594.4 1 6 CACCTG TGCCAAAATT - +4 cisbp__M3049-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 0 0.637729 15594.4 1 6 CACCTG TACTTCCGGT - +4 predrem__nrMotif2370 4 0.637729 15594.4 1 6 CACCTG CTGTCGCCCC - +4 taipale__DPRX_DBD_NNGGATTANN-Gsc-oc 3 0.637729 15594.4 1 6 CACCTG GCTAATCCGT - +4 taipale_cyt_meth__NEUROD2_RMCATATGYY_FL-amos-ato-crp-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.637729 15594.4 1 6 CACCTG AACATATGGT - +4 taipale_cyt_meth__TFAP4_ANCATATGNT_eDBD_meth-crp 2 0.637729 15594.4 1 6 CACCTG AACATATGAT - +4 transfac_pro__M01989-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-Taf1 0 0.637729 15594.4 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M05858 1 0.637729 15594.4 1 6 CACCTG CCACTCGAAC - +4 cisbp__M0408 5 0.637729 15594.4 1 5 CACCTG ATGTGCACAT + +4 hocomoco__LHX6_HUMAN.H11MO.0.D-Awh -1 0.637729 15594.4 1 5 CACCTG CTCTGATTAC + +4 cisbp__M3623-CG12018-Dif-dl-Rel 5 0.637729 15594.4 1 5 CACCTG GGAAATTCCC - +4 swissregulon__sacCer__SNT2 5 0.637729 15594.4 1 5 CACCTG GGCGCTACCA - +4 taipale_cyt_meth__SIX1_NSRTATCRYN_eDBD_meth-Optix-Six4-so 5 0.637729 15594.4 1 5 CACCTG CATGATACGT - +4 transfac_public__M00052-CG12018-Dif-dl-Rel 5 0.637729 15594.4 1 5 CACCTG GGAAATTCCC - +4 transfac_pro__M07836-Antp-B-H1-B-H2-bsh-btn-Dfd-Dll-Dr-en-exex-inv-Lim1-Scr-unpg 6 0.637729 15594.4 1 4 CACCTG CGCAATTACG + +4 flyfactorsurvey__dl_NBT_FBgn0000462-Dif-dl 6 0.637729 15594.4 1 4 CACCTG GGGAATTCCC - +4 hdpi__FOXP4 6 0.637729 15594.4 1 4 CACCTG GTGCTTTTCC - +4 neph__UW.Motif.0638 -2 0.637729 15594.4 1 4 CACCTG CCCCAAAATG - +4 predrem__nrMotif2517 -2 0.637729 15594.4 1 4 CACCTG CCTCCTCCGC - +4 flyfactorsurvey__HLH106_SANGER_5_3_FBgn0015234-SREBP 7 0.637729 15594.4 1 3 CACCTG GTCACGCCAC + +4 transfac_pro__M04972 7 0.637729 15594.4 1 3 CACCTG ATGCCGCCAC + +4 cisbp__M0311-Jra 2 0.637917 15599 1 6 CACCTG ATGACGCAA + +4 cisbp__M0444 3 0.637917 15599 1 6 CACCTG TGTGGCCTA + +4 cisbp__M1236-nub-pdm2 0 0.637917 15599 1 6 CACCTG TTAATTATC + +4 cisbp__M4798-Cf2 0 0.637917 15599 1 6 CACCTG TATCTGAAA + +4 hocomoco__HSF1_MOUSE.H11MO.1.A-Hsf 0 0.637917 15599 1 6 CACCTG GTTCTGGAA + +4 predrem__nrMotif2200 3 0.637917 15599 1 6 CACCTG AGACAACAG + +4 predrem__nrMotif2392 0 0.637917 15599 1 6 CACCTG TTCCATTTA + +4 predrem__nrMotif478 0 0.637917 15599 1 6 CACCTG CTTCTGGCT + +4 transfac_pro__M04681-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 2 0.637917 15599 1 6 CACCTG ATGACGTCA + +4 transfac_pro__M07257 3 0.637917 15599 1 6 CACCTG TTATAACTT + +4 cisbp__M0475 2 0.637917 15599 1 6 CACCTG AGGGCCTCC - +4 hocomoco__FOXP3_HUMAN.H11MO.0.D 3 0.637917 15599 1 6 CACCTG AAACAAATT - +4 hocomoco__ISL1_HUMAN.H11MO.0.A-tup 0 0.637917 15599 1 6 CACCTG TCCATTAGC - +4 predrem__nrMotif1113 2 0.637917 15599 1 6 CACCTG GGCGCCTCC - +4 predrem__nrMotif1361 1 0.637917 15599 1 6 CACCTG CCACATCCC - +4 predrem__nrMotif1882 3 0.637917 15599 1 6 CACCTG AAACACCAT - +4 predrem__nrMotif2309 2 0.637917 15599 1 6 CACCTG TGTGCATGC - +4 hocomoco__HSF1_HUMAN.H11MO.1.A-Hsf -1 0.637917 15599 1 5 CACCTG TTCTGGAAA + +4 predrem__nrMotif1175 4 0.637917 15599 1 5 CACCTG CTCATCCCT + +4 predrem__nrMotif1587 4 0.637917 15599 1 5 CACCTG CACCCATCC + +4 predrem__nrMotif167 4 0.637917 15599 1 5 CACCTG ACAGCATCA + +4 predrem__nrMotif1800 4 0.637917 15599 1 5 CACCTG ACAGAACAG + +4 predrem__nrMotif698 4 0.637917 15599 1 5 CACCTG TTGTAAACA + +4 taipale__Hic1_DBD_RTGCCMNCN_repr 4 0.637917 15599 1 5 CACCTG ATGCCAACC + +4 cisbp__M6023 4 0.637917 15599 1 5 CACCTG ATGCCAACC - +4 predrem__nrMotif1798 4 0.637917 15599 1 5 CACCTG GAAATTCCT - +4 predrem__nrMotif843 4 0.637917 15599 1 5 CACCTG ATAAAGCCA - +4 taipale_cyt_meth__BARHL2_NTAAACGNY_eDBD-B-H1-B-H2 -1 0.637917 15599 1 5 CACCTG ACCGTTTAG - +4 taipale_cyt_meth__RFX7_NGTTGCYAN_eDBD-CG9727 4 0.637917 15599 1 5 CACCTG ATAGCAACG - +4 cisbp__M0969-Awh-CG11085-E5-ems-en-inv-lab-slou-unpg 5 0.637917 15599 1 4 CACCTG CCAATCAGC + +4 predrem__nrMotif1072 -2 0.637917 15599 1 4 CACCTG CCTCCCATG + +4 predrem__nrMotif1447 5 0.637917 15599 1 4 CACCTG GGAATTCCC + +4 predrem__nrMotif1591 -2 0.637917 15599 1 4 CACCTG CCTCAGACT + +4 taipale_cyt_meth__FOSL1_RATGAYACG_FL-kay 5 0.637917 15599 1 4 CACCTG AATGACACG + +4 predrem__nrMotif1677 -2 0.637917 15599 1 4 CACCTG CCATTTGAA - +4 predrem__nrMotif2251 5 0.637917 15599 1 4 CACCTG TCCATTAAC - +4 predrem__nrMotif560 -2 0.637917 15599 1 4 CACCTG CCTCCAACA - +4 transfac_pro__M04702-CTCF -2 0.637917 15599 1 4 CACCTG CCATGGACA - +4 transfac_pro__M04746-Atf3-Atf6-CrebB-E2f1-Jra-Xbp1 5 0.637917 15599 1 4 CACCTG GACGTCACC - +4 cisbp__M3257 7 0.637976 15600.4 1 6 CACCTG ATAATAATATTTTT + +4 cisbp__M5330-Atf6-CrebA-CrebB-Xbp1 4 0.637976 15600.4 1 6 CACCTG TGATGACGTGGCAT + +4 cisbp__M5468-foxo 3 0.637976 15600.4 1 6 CACCTG GTAAACATGTTTAC + +4 hocomoco__BSH_HUMAN.H11MO.0.D-CG9876-E5-Vsx2-bsh-ems-en-inv 4 0.637976 15600.4 1 6 CACCTG CAATTAACTCATTA + +4 transfac_pro__M09029 1 0.637976 15600.4 1 6 CACCTG CCACCGACAAATTC + +4 transfac_pro__M09455-tll 6 0.637976 15600.4 1 6 CACCTG AGCGTTGACTTTTT + +4 transfac_public__M00423 7 0.637976 15600.4 1 6 CACCTG ATAATAATATTTTT + +4 cisbp__M1861-ham 3 0.637976 15600.4 1 6 CACCTG TGTTATCTTATCTT - +4 cisbp__M4563-aop-Atac3-Eip74EF-Ets21C-Hcf-RpII215-Sin3A 1 0.637976 15600.4 1 6 CACCTG CCACTTCCGGGTTC - +4 cisbp__M5216-btd-cbt-klu-Spps-sr 7 0.637976 15600.4 1 6 CACCTG CCCCGCCCACGCAC - +4 hocomoco__EGR2_MOUSE.H11MO.0.A-klu-luna-sr 0 0.637976 15600.4 1 6 CACCTG CCCCCGCCCACGCC - +4 hocomoco__GABPA_MOUSE.H11MO.0.A-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-RpII215-Sin3A-Taf1-aop-bs-dl-pnt 1 0.637976 15600.4 1 6 CACCTG CCACTTCCGGTTCC - +4 hocomoco__PAX8_HUMAN.H11MO.0.D-sv 2 0.637976 15600.4 1 6 CACCTG CCCGCTTCAGTGAC - +4 hocomoco__ZN740_HUMAN.H11MO.0.D-Spps-btd-l(3)neo38-peb 2 0.637976 15600.4 1 6 CACCTG CCCACCCCCCCCCC - +4 jaspar__MA0029.1-ham 3 0.637976 15600.4 1 6 CACCTG TGTTATCTTATCTT - +4 jaspar__MA0069.1-Poxm-ey-sv-toy 6 0.637976 15600.4 1 6 CACCTG AACTCATGCGTGAA - +4 taipale_cyt_meth__POU6F1_NTAATGAKATGCRN_FL_meth-pdm3-vvl 1 0.637976 15600.4 1 6 CACCTG ACGCATATCATTAT - +4 transfac_pro__M01714-Klf15 5 0.637976 15600.4 1 6 CACCTG CCACTCCCCTCCTC - +4 transfac_public__M00269-croc-fd59A-fkh-foxo 8 0.637976 15600.4 1 6 CACCTG TTTTTGTTTACTCA - +4 taipale__FLI1_DBD_ACCGGAWATCCGGN-Ets21C-Ets97D -1 0.637976 15600.4 1 5 CACCTG ACCGGAAATCCGGT + +4 cisbp__M3035-nej 9 0.637976 15600.4 1 5 CACCTG ACATTGCACAATCT - +4 transfac_public__M00109-nej 9 0.637976 15600.4 1 5 CACCTG ACATTGCACAATCT - +4 taipale_cyt_meth__IRF5_NYGAAACCGAAACY_eDBD_meth 10 0.637976 15600.4 1 4 CACCTG CCGAAACCGAAACT + +4 cisbp__M5922-TfAP-2 1 0.639448 15636.4 1 6 CACCTG TGCCCTGAGGGCA + +4 jaspar__MA0872.1-TfAP-2 1 0.639448 15636.4 1 6 CACCTG TGCCCTGAGGGCA + +4 taipale__TFAP2C_DBD_NSCCNNNNNGGSN-TfAP-2 1 0.639448 15636.4 1 6 CACCTG TGCCCTGAGGGCA + +4 taipale_cyt_meth__MAFG_TGCTGANNNTGCR_FL_meth-maf-S 4 0.639448 15636.4 1 6 CACCTG TGCTGACTGTGCA + +4 transfac_pro__M08977-pan 6 0.639448 15636.4 1 6 CACCTG TCCTTTGATCTTT + +4 cisbp__M1078 0 0.639448 15636.4 1 6 CACCTG AACCAATTAATAT - +4 cisbp__M4824-Asciz 7 0.639448 15636.4 1 6 CACCTG GTGTTTCAACTTT - +4 cisbp__M5916-TfAP-2 1 0.639448 15636.4 1 6 CACCTG TGCCCTGAGGGCA - +4 flyfactorsurvey__CG14962_SANGER_5_FBgn0035407-Asciz 7 0.639448 15636.4 1 6 CACCTG GTGTTTCAACTTT - +4 transfac_pro__M07912-Klf15 7 0.639448 15636.4 1 6 CACCTG GATACGCCCCCTT - +4 neph__UW.Motif.0133 -1 0.639448 15636.4 1 5 CACCTG AAATGCTTATTCA + +4 neph__UW.Motif.0213 8 0.639448 15636.4 1 5 CACCTG CTGTTTTTCATTT - +4 transfac_pro__M09399 -2 0.639448 15636.4 1 4 CACCTG CTTGTATTTCACG + +4 transfac_pro__M09342 -2 0.639448 15636.4 1 4 CACCTG CCTTATCCATATT - +4 transfac_pro__M09331 24 0.640283 15656.9 1 5 CACCTG CTAAACCCTAAACCCTAAACCCTAAACCC + +4 transfac_pro__M04754-ey-Poxm-sv-toy 4 0.642027 15699.5 1 6 CACCTG GTCACGCTTGGCTGCCCC + +4 transfac_pro__M06880 2 0.642027 15699.5 1 6 CACCTG GACAGCCGTCATATTGCT + +4 transfac_pro__M07890-Bgb-lz-run-RunxA-RunxB 1 0.642027 15699.5 1 6 CACCTG TAACCGCAAAAACCGCAA + +4 transfac_public__M00422-bin-croc-fd59A-fkh-foxo 11 0.642027 15699.5 1 6 CACCTG TTATAAATAAACATTCAA + +4 hocomoco__RFX2_HUMAN.H11MO.0.A-CG5846-CG9727-Max-Rfx-SREBP 4 0.642027 15699.5 1 6 CACCTG CCGTTGCCATGGCAACCG - +4 taipale_cyt_meth__IRX1_NACGYGNNNNNNCRCGTN_eDBD_meth_repr-ara-caup-mirr 0 0.642027 15699.5 1 6 CACCTG AACGCGTCACTGCGCGTA - +4 transfac_pro__M06816 3 0.642027 15699.5 1 6 CACCTG CGTGACCCTTCTTCCGTT - +4 transfac_pro__M07887-kn 4 0.642027 15699.5 1 6 CACCTG GAATTCCCTAGGGAATTG - +4 taipale_tf_pairs__TEAD4_ELK1_RCCGGANRNNCGGWATKN_CAP_repr-sd -1 0.642027 15699.5 1 5 CACCTG ACCGGATGTCCGGTATGC + +4 cisbp__M6514-gem 9 0.644238 15753.5 1 6 CACCTG GCCTGAACTGGCCAGA + +4 hocomoco__SOX9_HUMAN.H11MO.0.B-Sox14-Sox100B-SoxN 5 0.644238 15753.5 1 6 CACCTG AAAGGGGCCTTTGTTC + +4 transfac_pro__M01272-SoxN 2 0.644238 15753.5 1 6 CACCTG AACCCCATTGTTATGC + +4 transfac_public__M00019-Dfd 8 0.644238 15753.5 1 6 CACCTG AAAAAAATTACTAAAA + +4 neph__UW.Motif.0097 4 0.644238 15753.5 1 6 CACCTG TTTGTTTTTGGCAGAA - +4 swissregulon__hs__TFAP2B.p2-Brf-CTCF-E2f1-E(z)-HDAC1-Hcf-Nelf-E-RpII215-SREBP-TfAP-2-tna 5 0.644238 15753.5 1 6 CACCTG CCCGCCGCCCGCGGCC - +4 taipale__VDR_full_GRGTTCANNRRGTTCA-EcR-usp 2 0.644238 15753.5 1 6 CACCTG TGAACTCAATGAACTC - +4 taipale_tf_pairs__ETV2_HOXB13_NCCGGAAGTYRTAAAN_CAP-pnt 9 0.644238 15753.5 1 6 CACCTG GTTTACGACTTCCGGC - +4 taipale_tf_pairs__MEIS1_ONECUT2_TGACAGNWAATCRATR_CAP_repr-onecut 7 0.644238 15753.5 1 6 CACCTG CATCGATTTTCTGTCA - +4 transfac_pro__M01183 6 0.644238 15753.5 1 6 CACCTG AAAGTATTACTAGAAA - +4 transfac_pro__M01331-Awh-E5-ems-en-inv-unpg 1 0.644238 15753.5 1 6 CACCTG ACGACTAATTAGGAGT - +4 transfac_pro__M01442-abd-A-Antp-bsh-btn-lab-pb-Scr-Ubx 10 0.644238 15753.5 1 6 CACCTG CTGAGGTAATTACCTG - +4 transfac_pro__M01778 0 0.644238 15753.5 1 6 CACCTG CCCCCTCTAATGCCCC - +4 transfac_pro__M07062-CTCF-peb 6 0.644238 15753.5 1 6 CACCTG CCCCCCAACCCCTCCC - +4 transfac_pro__M09364 1 0.644238 15753.5 1 6 CACCTG TTGCTTGTTCTACAAG - +4 tfdimers__MD00504-Eip74EF-NfI 11 0.644721 15765.4 1 6 CACCTG TGAGCCTTGGCTTCCTGCCAACACCATC - +4 cisbp__M1015-CG32532-CG4328-Lim1-Lim3-Lmx1a-OdsH-repo-unc-4 1 0.645849 15792.9 1 6 CACCTG TTAATTA + +4 hdpi__POU3F2-vvl 1 0.645849 15792.9 1 6 CACCTG CTAATTG + +4 scertf__morozov.YAP3 1 0.645849 15792.9 1 6 CACCTG TTACTAA + +4 transfac_pro__M01096-brk 1 0.645849 15792.9 1 6 CACCTG GCGCCAG + +4 elemento__AAGATCA 1 0.645849 15792.9 1 6 CACCTG TGATCTT - +4 predrem__nrMotif2327 -1 0.645849 15792.9 1 5 CACCTG AGCTTAG - +4 transfac_pro__M05439-peb 2 0.645849 15792.9 1 5 CACCTG TCGACCC - +4 hdpi__TAF1A 3 0.645849 15792.9 1 4 CACCTG AAATGCC + +4 predrem__nrMotif303 -2 0.645849 15792.9 1 4 CACCTG TCTTTTG + +4 yetfasco__YHR084W_400 3 0.645849 15792.9 1 4 CACCTG TGAAACA + +4 hdpi__SMPX -2 0.645849 15792.9 1 4 CACCTG CCGGGCC - +4 hdpi__ZNF76 -2 0.645849 15792.9 1 4 CACCTG CCATTGA - +4 predrem__nrMotif1829 3 0.645849 15792.9 1 4 CACCTG ATGACCC - +4 predrem__nrMotif712 3 0.645849 15792.9 1 4 CACCTG GAAAGCC - +4 scertf__badis.EDS1 3 0.645849 15792.9 1 4 CACCTG TTTTTCC - +4 hdpi__H1FX -3 0.645849 15792.9 1 3 CACCTG CTGGAAA + +4 cisbp__M0017-tna 0 0.647181 15825.5 1 6 CACCTG CGCCGGCC + +4 cisbp__M0021 1 0.647181 15825.5 1 6 CACCTG TTGCCGCC + +4 cisbp__M0858-Gsc-Ptx1-bcd-oc 2 0.647181 15825.5 1 6 CACCTG TTAATCCC + +4 cisbp__M1045-abd-A-Abd-B-cad-Dbx-eve-Ubx 2 0.647181 15825.5 1 6 CACCTG TTTATGAC + +4 cisbp__M1096-bcd-Gsc-oc-Ptx1 2 0.647181 15825.5 1 6 CACCTG TTAATCCC + +4 cisbp__M1650 2 0.647181 15825.5 1 6 CACCTG GGGACCAC + +4 cisbp__M5701-bcd-Gsc-oc 2 0.647181 15825.5 1 6 CACCTG TTAATCCT + +4 flyfactorsurvey__CG1621_SANGER_5_FBgn0033182-Coop 0 0.647181 15825.5 1 6 CACCTG ACCCGGAA + +4 homer__TWGTCTGV_Smad3-Smox 1 0.647181 15825.5 1 6 CACCTG TTGTCTGG + +4 jaspar__MA1027.1 1 0.647181 15825.5 1 6 CACCTG AGATATTC + +4 predrem__nrMotif1327 0 0.647181 15825.5 1 6 CACCTG CACTTTTG + +4 predrem__nrMotif249 2 0.647181 15825.5 1 6 CACCTG TCAGCCTG + +4 taipale_cyt_meth__MEOX1_NTCGTTAN_FL_meth-Antp-btn-Dfd-Dll-eve-exex-ind-lab-pb-Scr 0 0.647181 15825.5 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__MNX1_NTCGTTAN_eDBD_meth-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-en-eve-exex-ind-inv-lab-pb-Scr-Ubx-unpg 0 0.647181 15825.5 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__SOX18_NACAATGN_eDBD_repr-Sox15 0 0.647181 15825.5 1 6 CACCTG CACAATGC + +4 transfac_pro__M01101-ovo 0 0.647181 15825.5 1 6 CACCTG TAACAGTA + +4 transfac_pro__M03791-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 1 0.647181 15825.5 1 6 CACCTG CTTCCGGT + +4 transfac_pro__M07612-nonA-nonA-l 1 0.647181 15825.5 1 6 CACCTG GTATCCGC + +4 cisbp__M0517-klu-sr 0 0.647181 15825.5 1 6 CACCTG ACCCCGCA - +4 cisbp__M5023-dpn-E(spl)mbeta-HLH-h-Sidpn 2 0.647181 15825.5 1 6 CACCTG GGCACGCG - +4 cisbp__M6305 1 0.647181 15825.5 1 6 CACCTG TCTCCCAA - +4 flyfactorsurvey__HLHmbeta_SANGER_10_FBgn0002733-E(spl)mbeta-HLH-Sidpn-dpn-h 2 0.647181 15825.5 1 6 CACCTG GGCACGCG - +4 hdpi__SSX2 0 0.647181 15825.5 1 6 CACCTG TGCATTTT - +4 taipale_cyt_meth__NANOG_TTAAKTGN_eDBD_meth_repr-Antp-Scr 1 0.647181 15825.5 1 6 CACCTG GCAATTAA - +4 cisbp__M4810-CG11617 3 0.647181 15825.5 1 5 CACCTG TGTTAAAA + +4 factorbook__TEAD1-sd -1 0.647181 15825.5 1 5 CACCTG ACATTCCA + +4 stark__RCGYRCGY 3 0.647181 15825.5 1 5 CACCTG ACGCACGC + +4 cisbp__M5193-Optix-Six4 3 0.647181 15825.5 1 5 CACCTG TATCAATT - +4 cisbp__M6325-luna 3 0.647181 15825.5 1 5 CACCTG CCGCCCCC - +4 swissregulon__hs__PAX2.p2-sv -1 0.647181 15825.5 1 5 CACCTG GCGTGACG - +4 transfac_pro__M03573-bin 3 0.647181 15825.5 1 5 CACCTG ATAAACAT - +4 cisbp__M1466 4 0.647181 15825.5 1 4 CACCTG TTGTGACT + +4 hdpi__LARP4-CG11505 -2 0.647181 15825.5 1 4 CACCTG CTTGGGAA + +4 predrem__nrMotif1976 -2 0.647181 15825.5 1 4 CACCTG CTTTATTG + +4 predrem__nrMotif2458 4 0.647181 15825.5 1 4 CACCTG CTCTCGCC + +4 neph__UW.Motif.0146 -2 0.647181 15825.5 1 4 CACCTG CCAGAAAT - +4 elemento__CTGCAGCA -3 0.647181 15825.5 1 3 CACCTG CTGCAGCA + +4 elemento__CTGCTGGA -3 0.647181 15825.5 1 3 CACCTG CTGCTGGA + +4 elemento__TTGTTTAC-bin-CHES-1-like-croc-fkh-FoxK-foxo-FoxP-slp2 5 0.647181 15825.5 1 3 CACCTG TTGTTTAC + +4 elemento__CCAATCAG-Chrac-14-Nf-YA-Nf-YB-Nf-YC -3 0.647181 15825.5 1 3 CACCTG CTGATTGG - +4 elemento__CTTATCAG -3 0.647181 15825.5 1 3 CACCTG CTGATAAG - +4 swissregulon__hs__FOX_D1_D2_.p2-FoxP-croc-fd59A-fkh-foxo-slp2 5 0.647181 15825.5 1 3 CACCTG TTGTTTAC - +4 jaspar__MA0586.1 9 0.647278 15827.9 1 6 CACCTG TCGCGTCCGTACAGGAGGG + +4 swissregulon__sacCer__GAL4 13 0.647278 15827.9 1 6 CACCTG TCGGGCAACAGTACTCCGA + +4 transfac_pro__M09482 4 0.647278 15827.9 1 6 CACCTG CGTTGACTTTTTTTAACAT + +4 cisbp__M2379 9 0.647278 15827.9 1 6 CACCTG TCGCGTCCGTACAGGAGGG - +4 cisbp__M5515-CG17829 3 0.647278 15827.9 1 6 CACCTG GCGGACGTTCAACGTCCGC - +4 hocomoco__P63_HUMAN.H11MO.0.A 11 0.647278 15827.9 1 6 CACCTG GGGCATGCCTGGACATGCC - +4 fantom__motif124_AATNCANCACT 4 0.648424 15855.9 1 6 CACCTG AATGCAGCACT + +4 hocomoco__STAT4_HUMAN.H11MO.0.A-Stat92E-aop 1 0.648424 15855.9 1 6 CACCTG TTTCCTGGAAG + +4 jaspar__MA0506.1-ewg 1 0.648424 15855.9 1 6 CACCTG GCGCCTGCGCA + +4 jaspar__MA0581.1 0 0.648424 15855.9 1 6 CACCTG TGCATGCACAT + +4 predrem__nrMotif490 5 0.648424 15855.9 1 6 CACCTG GCTCCCGCCCC + +4 transfac_pro__M07329-Sp1 3 0.648424 15855.9 1 6 CACCTG CCGCCCCCTCG + +4 cisbp__M2305-E2f1-ewg 1 0.648424 15855.9 1 6 CACCTG GCGCCTGCGCA - +4 cisbp__M2374 0 0.648424 15855.9 1 6 CACCTG TGCATGCACAT - +4 fantom__motif154_GRWGGCAARCG 4 0.648424 15855.9 1 6 CACCTG CGTTTGCCTCC - +4 hocomoco__CREB5_HUMAN.H11MO.0.D-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Irbp18-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 2 0.648424 15855.9 1 6 CACCTG ATGACGTCATC - +4 jaspar__MA0002.2-Bgb-Bro-MTA1-like-RunxA-RunxB-ebi-lz-run 1 0.648424 15855.9 1 6 CACCTG AAACCACAGAC - +4 predrem__nrMotif95-CTCF-E(z)-HDAC1-SREBP-brm 4 0.648424 15855.9 1 6 CACCTG CCCGCGCCCCC - +4 taipale_cyt_meth__ETV1_NACCGGAWGTN_eDBD-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 3 0.648424 15855.9 1 6 CACCTG CACTTCCGGTC - +4 taipale_cyt_meth__FOXK1_NWYGTAAAYAN_eDBD_meth_repr-fd59A-FoxK-foxo 5 0.648424 15855.9 1 6 CACCTG TTGTTTACGAC - +4 transfac_pro__M06910-CG2120 5 0.648424 15855.9 1 6 CACCTG GGACTGACTCT - +4 transfac_pro__M09203 2 0.648424 15855.9 1 6 CACCTG GGAATCTTTTT - +4 cisbp__M4590-Jra-kay-mor-Myc 6 0.648424 15855.9 1 5 CACCTG ATGACTCACTC + +4 transfac_pro__M07258 6 0.648424 15855.9 1 5 CACCTG TTATTATTCCT - +4 taipale__HOXA13_DBD_NCTCGTAAAAN -2 0.648424 15855.9 1 4 CACCTG GCTCGTAAAAC + +4 hocomoco__HXA2_HUMAN.H11MO.0.D-Antp-Awh-CG18599-Dfd-E5-Lim3-Pph13-Rx-Scr-al-ap-ems-en-eve-ind-inv-lbl-otp-pb-unpg-zen2 7 0.648424 15855.9 1 4 CACCTG CGCTAATTACC - +4 tfdimers__MD00512-pho-phol 16 0.648472 15857.1 1 6 CACCTG TCATGCCATCTGCGCGCCCCCGGCCCC - +4 fantom__motif51_CGGNTA 0 0.648534 15858.6 1 6 CACCTG TAACCG - +4 hdpi__HNRPH3-glo 0 0.648534 15858.6 1 6 CACCTG TTCCAG - +4 jaspar__MA0261.1 1 0.648534 15858.6 1 5 CACCTG GAACAC + +4 cisbp__M2067 1 0.648534 15858.6 1 5 CACCTG GAACAC - +4 flyfactorsurvey__Mirr_SOLEXA_FBgn0014343-ara-caup-mirr 2 0.648534 15858.6 1 4 CACCTG ATAACA + +4 c2h2_zfs__M3800 9 0.650987 15918.6 1 6 CACCTG GAGAATTCATACTGG + +4 cisbp__M2288-Hsf-pb 2 0.650987 15918.6 1 6 CACCTG AGAACCTTCTAGAAG + +4 factorbook__HSF1-Hsf-pb 2 0.650987 15918.6 1 6 CACCTG AGAACCTTCTAGAAG + +4 neph__UW.Motif.0266 7 0.650987 15918.6 1 6 CACCTG TTTTTTATGCCAAAA + +4 taipale_tf_pairs__PITX1_HES7_NCACGTGNNGGATTA_CAP_repr-Ptx1 1 0.650987 15918.6 1 6 CACCTG ACACGTGGGGGATTA + +4 transfac_pro__M02856-FoxK 7 0.650987 15918.6 1 6 CACCTG CAAACAACAACACCT + +4 transfac_pro__M02910-Sox102F 1 0.650987 15918.6 1 6 CACCTG TATCATAATTAAGGA + +4 cisbp__M1929 9 0.650987 15918.6 1 6 CACCTG ACATGCCCAGACATG - +4 cisbp__M2336 0 0.650987 15918.6 1 6 CACCTG TCTCTGCGTCTCTCT - +4 cisbp__M4568-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-lid-pnt-Rbbp5-RpII215-Sin3A-Taf1 1 0.650987 15918.6 1 6 CACCTG CCACTTCCGGTTCCG - +4 flyfactorsurvey__l_3_neo38_SOLEXA_2.5_FBgn0086910-CG7368-CTCF-CoRest-Rbbp5-Spps-Spt20-btd-crol-ct-l(3)neo38-peb 8 0.650987 15918.6 1 6 CACCTG CCCCCCCCCCCCCCC - +4 flyfactorsurvey__lola-PQ_SOLEXA_FBgn0005630-lola 7 0.650987 15918.6 1 6 CACCTG AAACGAACAACGCAA - +4 hocomoco__HSF1_HUMAN.H11MO.0.A-Hsf-pb 6 0.650987 15918.6 1 6 CACCTG TTCTAGAACCTTCCA - +4 neph__UW.Motif.0165 7 0.650987 15918.6 1 6 CACCTG GGAAGGGGATCTGGC - +4 neph__UW.Motif.0559 0 0.650987 15918.6 1 6 CACCTG AGCCAAATCAGTTTT - +4 swissregulon__hs__POU5F1_SOX2_dimer_.p2-CG9650-SoxN-nej-nub-pdm2-vvl 3 0.650987 15918.6 1 6 CACCTG ATTTGCATAACAATA - +4 taipale_cyt_meth__MAFF_NYGCTGASTCAGCRN_eDBD-cnc-maf-S-tj 9 0.650987 15918.6 1 6 CACCTG TTGCTGAGTCAGCAT - +4 transfac_pro__M09091-Taf1 1 0.650987 15918.6 1 6 CACCTG CCTCCGCCGCCGCCA - +4 swissregulon__hs__SMAD1..7_9.p2-Dad-Mad-Med-Smox 10 0.650987 15918.6 1 5 CACCTG GGCGGGCAGACAGCC + +4 cisbp__M2957-bigmax-Clk-cnc-cwo-cyc-Mitf-Mondo-SREBP-tgo-Usf 7 0.651142 15922.4 1 6 CACCTG CAAAGGTCACGTGACCTTTG + +4 dbcorrdb__ATF3__ENCSR000BKE_1__m2-cnc-E2f1-Max-Myc-pho-phol-RpII215-Taf1-Usf 9 0.651142 15922.4 1 6 CACCTG CGCTGCCGTCACGTGCCCGC + +4 dbcorrdb__EZH2__ENCSR000ARE_1__m4-E(z) 4 0.651142 15922.4 1 6 CACCTG CACGCACCGCGAGGCAGACA + +4 dbcorrdb__GATA3__ENCSR000BMX_1__m1-bin-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 3 0.651142 15922.4 1 6 CACCTG CAATGACTGTTTGCTTAGGG + +4 dbcorrdb__HDAC1__ENCSR000AQF_1__m2-CTCF-HDAC1 14 0.651142 15922.4 1 6 CACCTG GTCCGCACCGCGGCCACCGC + +4 dbcorrdb__PAX5__ENCSR000BHJ_1__m1-ey-Poxm-sv-toy 13 0.651142 15922.4 1 6 CACCTG AGCAGCCAAGCGTGACCGAG + +4 dbcorrdb__POLR2A__ENCSR000BHN_1__m1-Myc-pho-phol-RpII215-Taf1 4 0.651142 15922.4 1 6 CACCTG CCCCGAAATGGCGGCAGCGG + +4 dbcorrdb__POLR2A__ENCSR000EXO_1__m1-Eip74EF-Hcf-RpII215-Taf1 13 0.651142 15922.4 1 6 CACCTG GCCGCGCTTCCGCCACGCGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BKR_1__m2 7 0.651142 15922.4 1 6 CACCTG CAGCCGCCAGCTGTTTCTCT + +4 dbcorrdb__SIX5__ENCSR000BGX_1__m1-bi-egg-Hcf-mor-Six4 9 0.651142 15922.4 1 6 CACCTG GACTACAATTCCCAGCATGC + +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m8-bon 2 0.651142 15922.4 1 6 CACCTG GTTTCTTGCTGTTTGCGGAT + +4 dbcorrdb__YY1__ENCSR000EXG_1__m2-pho-phol-RpII215 9 0.651142 15922.4 1 6 CACCTG CGGTTCCGTCACTTCGGCGG + +4 taipale_cyt_meth__RUNX2_NWAACCGCANNNACCGCAAN_eDBD-Bgb-lz-run-RunxA-RunxB 2 0.651142 15922.4 1 6 CACCTG CTAACCGCAAAAACCGCAAC + +4 transfac_pro__M01534-sd 5 0.651142 15922.4 1 6 CACCTG CAACCAACATTCTTGATATA + +4 transfac_pro__M09521-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.651142 15922.4 1 6 CACCTG AATGACGTCATCATTTTTGT + +4 transfac_public__M00539-bigmax-Clk-cnc-cyc-Mitf-Mondo-SREBP-tgo-Usf 7 0.651142 15922.4 1 6 CACCTG CAAAGGTCACGTGACCTTTG + +4 cisbp__M4110-CG10431-pho-phol-Taf1 7 0.651142 15922.4 1 6 CACCTG CCGCGGCCATCTTGGCTGCT - +4 dbcorrdb__CHD1__ENCSR000DZE_1__m2-Chd1 5 0.651142 15922.4 1 6 CACCTG CCCCCCGCGTATCGGAATGG - +4 dbcorrdb__EP300__ENCSR000EDV_1__m2-fd59A-fkh-HDAC1-nej 13 0.651142 15922.4 1 6 CACCTG TCTGTTGAGCAAACAGTGGC - +4 dbcorrdb__ETS1__ENCSR000BPU_1__m2-Six4 14 0.651142 15922.4 1 6 CACCTG CGCGGCGGGGGGACTACAAC - +4 dbcorrdb__FOXA1__ENCSR000BKW_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-FoxP-HDAC1-nej-Nf1-slp2 10 0.651142 15922.4 1 6 CACCTG AGTCTTTGTTTACTTAGGGA - +4 dbcorrdb__MAX__ENCSR000ECN_1__m1-Brf-brm-btd-Clk-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-tgo-tna-Usf-vtd 2 0.651142 15922.4 1 6 CACCTG GCCACGTGCCCCGGGGGGGG - +4 dbcorrdb__MBD4__ENCSR000BQW_1__m2-pan 0 0.651142 15922.4 1 6 CACCTG TCTCTTTGATCTTTTATGAC - +4 dbcorrdb__MEF2A__ENCSR000BNV_1__m2-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Stat92E 12 0.651142 15922.4 1 6 CACCTG TAAGCGATGAGTCATCTTTC - +4 dbcorrdb__MYC__ENCSR000DMJ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-SREBP-Stat92E-Taf1-tna-Usf-vtd-zfh1 8 0.651142 15922.4 1 6 CACCTG CCCGCGGCCACGTGCGCCGC - +4 dbcorrdb__POLR2A__ENCSR000DMZ_1__m1-Eip74EF-Hcf-RpII215-Taf1 14 0.651142 15922.4 1 6 CACCTG CCGGCGGCTGCCGCTACGCG - +4 dbcorrdb__POLR2A__ENCSR000EFB_1__m1-RpII215-Taf1 14 0.651142 15922.4 1 6 CACCTG TGCGTCCGTTCCGCTATCTT - +4 dbcorrdb__POLR2A__ENCSR000EYW_1__m1-pho-phol-RpII215-Taf1 10 0.651142 15922.4 1 6 CACCTG GCGCTTCCGCTATCAGCCGC - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIL_1__m1-RpII215 6 0.651142 15922.4 1 6 CACCTG TCACGTCACTTCCGCCATCG - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BML_1__m2 10 0.651142 15922.4 1 6 CACCTG GTCGTTGCGGCATCTGAGAC - +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m6-CG17209 14 0.651142 15922.4 1 6 CACCTG AAAACGAAAGCGAGAACCAC - +4 dbcorrdb__RFX5__ENCSR000ECF_1__m3 10 0.651142 15922.4 1 6 CACCTG GGGATGTCATTGGCTGCCGC - +4 dbcorrdb__SIN3A__ENCSR000EBO_1__m1-CTCF-HDAC1-Sin3A 14 0.651142 15922.4 1 6 CACCTG TTCCGTACCCCTGACAGCGC - +4 dbcorrdb__TAF7__ENCSR000BLU_1__m2-Taf7 9 0.651142 15922.4 1 6 CACCTG GTCTTCCGCCGCGATGGCGA - +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m4-bon 5 0.651142 15922.4 1 6 CACCTG TTTCCTACATTCATAAGATT - +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m5-bon 3 0.651142 15922.4 1 6 CACCTG TTACAACTGTAGGCTTTCCC - +4 hocomoco__ZN586_HUMAN.H11MO.0.C 9 0.651142 15922.4 1 6 CACCTG CATTTTTTCCTCCTAGGCCT - +4 homer__AACATGCCCAGACATGCCCN_p53 12 0.651142 15922.4 1 6 CACCTG GGGACATGTCTGGACATGTC - +4 jaspar__MA0296.1-CHES-1-like-FoxK-FoxL1-FoxP-croc-fkh-foxo-slp1-slp2 11 0.651142 15922.4 1 6 CACCTG TCCTCTTTGTTTACAATTCA - +4 transfac_pro__M01507-CHES-1-like-croc-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 11 0.651142 15922.4 1 6 CACCTG TCCTCTTTGTTTACAATTCA - +4 transfac_pro__M01539 11 0.651142 15922.4 1 6 CACCTG CTAAAGTGATTTACGTTCAA - +4 transfac_pro__M09042 13 0.651142 15922.4 1 6 CACCTG CCACCACCGCCTCCACCGCC - +4 dbcorrdb__CTCF__ENCSR000DXQ_1__m2-CTCF 16 0.651142 15922.4 1 4 CACCTG CGGCAAAGCGCTGCAGCGCC + +4 dbcorrdb__RAD21__ENCSR000BLY_1__m3-Brf-brm-btd-CTCF-ERR-E(z)-HDAC1-Max-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-tna-vtd 16 0.651142 15922.4 1 4 CACCTG GGCGCCCCCCCGACGGCCCC + +4 factorbook__FOXA-FoxK-FoxP-HDAC1-Nf1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-nej-slp2 0 0.65287 15964.6 1 6 CACCTG TCCCTAAGTAAACAAAG + +4 taipale_cyt_meth__FOXR2_NYRTAWACATAAATNNN_FL-jumu 5 0.65287 15964.6 1 6 CACCTG ATATAAACATAAATAAA + +4 transfac_pro__M01370-abd-A-Antp-Awh-CG18599-CG32532-Dfd-HGTX-OdsH-otp-repo-Scr-Ubx-unc-4-vvl-zfh2 10 0.65287 15964.6 1 6 CACCTG GATTATTAATTAACTTG + +4 transfac_pro__M01425 10 0.65287 15964.6 1 6 CACCTG AGCTGTTAACTAGCCGT + +4 transfac_pro__M07853-Hsf-pb 3 0.65287 15964.6 1 6 CACCTG TCGAACATTCTAGAACA + +4 taipale_tf_pairs__TEAD4_SOX15_NACAATRNNNNGAATGY_CAP_repr-sd 3 0.65287 15964.6 1 6 CACCTG ACATTCCTTCTATTGTT - +4 transfac_pro__M02862-gcm-gcm2 5 0.65287 15964.6 1 6 CACCTG CTCCTCCCCTATGCGCA - +4 transfac_pro__M03126 7 0.65287 15964.6 1 6 CACCTG TTGGCCACGCGTGGCAG - +4 transfac_pro__M07298-Dr 10 0.65287 15964.6 1 6 CACCTG CTAATTGGATCAATTTT - +4 tfdimers__MD00067 15 0.653737 15985.8 1 6 CACCTG CGCGCCTTTGGGAAACCCCCAAACC + +4 tfdimers__MD00141-Jra-kay 1 0.653737 15985.8 1 6 CACCTG TTTTATGAGTCACTGACTCATAAAA + +4 swissregulon__hs__AIRE.p2 10 0.653737 15985.8 1 6 CACCTG TAACCAATATAACCAATTAATAATC - +4 taipale_tf_pairs__ETV2_GSC2_RCCGGANNNNNNNNTAATCCN_CAP_repr-Gsc-pnt 10 0.653755 15986.3 1 6 CACCTG ACCGGAAATGCCCCTAATCCA + +4 transfac_pro__M09064-Adf1 2 0.653755 15986.3 1 6 CACCTG TCCACCGCCTCCGCCGCCGCC + +4 transfac_pro__M09078 1 0.653755 15986.3 1 6 CACCTG CCACCGCCTCCGCCGCCGCCA + +4 tfdimers__MD00550-Ptx1-sd 8 0.654071 15994 1 6 CACCTG TAAAAACATTCCTCAAAGGATTAAAAAATT + +4 transfac_pro__M09434 9 0.654071 15994 1 6 CACCTG TGTGGGCCCCACCTCCTCTCTTGGGCCTAT + +4 taipale_tf_pairs__ETV2_EOMES_NGGTGTNNNNNNNNNNNNNNNCCGGAWNNN_CAP_repr-pnt 25 0.654071 15994 1 5 CACCTG CACTTCCGGTGTGAACGCCACTTCACACCT - +4 cisbp__M0086 3 0.654244 15998.2 1 6 CACCTG TTATGCATAA + +4 cisbp__M0775 3 0.654244 15998.2 1 6 CACCTG GTCGATCACA + +4 cisbp__M1037 4 0.654244 15998.2 1 6 CACCTG ATCCAATCAA + +4 cisbp__M1196 0 0.654244 15998.2 1 6 CACCTG TGCATATCAA + +4 cisbp__M1257 2 0.654244 15998.2 1 6 CACCTG CCGGCCACCT + +4 cisbp__M1298-bs-Mef2 3 0.654244 15998.2 1 6 CACCTG CCAAATTTGG + +4 cisbp__M1518-CG5641-NFAT 3 0.654244 15998.2 1 6 CACCTG ATTTTCCATT + +4 homer__HACTTCCGGY_Elk1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-RpII215-Taf1-aop-bs-pnt 3 0.654244 15998.2 1 6 CACCTG CACTTCCGGT + +4 jaspar__MA0994.1 0 0.654244 15998.2 1 6 CACCTG CGCCGCCATT + +4 predrem__nrMotif1471 1 0.654244 15998.2 1 6 CACCTG TGACCAGAAA + +4 predrem__nrMotif688 4 0.654244 15998.2 1 6 CACCTG TCCCCAGCCC + +4 swissregulon__sacCer__PUT3 0 0.654244 15998.2 1 6 CACCTG ATCCCGGGAA + +4 taipale_cyt_meth__BHLHA15_NMCATATGKN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.654244 15998.2 1 6 CACCTG ACCATATGGT + +4 transfac_pro__M03559 1 0.654244 15998.2 1 6 CACCTG ATATATTCAT + +4 transfac_pro__M05357 1 0.654244 15998.2 1 6 CACCTG AAACATAAGA + +4 cisbp__M0520-klu-sr 1 0.654244 15998.2 1 6 CACCTG TACCCCGCAT - +4 cisbp__M1190 0 0.654244 15998.2 1 6 CACCTG TTTATTGGGC - +4 cisbp__M1499-ey-Poxm-sv-toy 0 0.654244 15998.2 1 6 CACCTG CGCTTGACTG - +4 cisbp__M5653-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.654244 15998.2 1 6 CACCTG AACATATGTC - +4 cisbp__M6422 4 0.654244 15998.2 1 6 CACCTG GGGCCCCCCG - +4 hocomoco__FOXO1_MOUSE.H11MO.0.A-FoxP-foxo 3 0.654244 15998.2 1 6 CACCTG GTAAACAGGC - +4 jaspar__MA0596.1-SREBP 2 0.654244 15998.2 1 6 CACCTG ATCACCCCAT - +4 predrem__nrMotif2323 0 0.654244 15998.2 1 6 CACCTG TTCCAGCAGC - +4 predrem__nrMotif75 0 0.654244 15998.2 1 6 CACCTG TCTCTTGGCT - +4 swissregulon__hs__ELK1_4_GABP_A_B1_.p3-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-TfIIFalpha-aop-bs-pnt 0 0.654244 15998.2 1 6 CACCTG CACTTCCGGC - +4 taipale_cyt_meth__NEUROD2_RMCATATGYY_FL_meth-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.654244 15998.2 1 6 CACCTG AACATATGGT - +4 transfac_pro__M01837-cbt 4 0.654244 15998.2 1 6 CACCTG CGCCCACCCC - +4 transfac_pro__M01979-aop-Eip74EF-Ets21C 0 0.654244 15998.2 1 6 CACCTG CACTTCCGGG - +4 transfac_pro__M01988-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 3 0.654244 15998.2 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02058-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-RpII215-Taf1 0 0.654244 15998.2 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M02061-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 3 0.654244 15998.2 1 6 CACCTG TACTTCCGGT - +4 transfac_pro__M02071-aop-Eip74EF-Ets96B-Hr78-pnt 3 0.654244 15998.2 1 6 CACCTG CGTTTCCGGG - +4 transfac_pro__M02074-aop-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 3 0.654244 15998.2 1 6 CACCTG TATTTCCGGT - +4 transfac_pro__M05015 0 0.654244 15998.2 1 6 CACCTG GTTCAATAAT - +4 transfac_pro__M05387 1 0.654244 15998.2 1 6 CACCTG GCACCCCAAC - +4 transfac_pro__M06508 1 0.654244 15998.2 1 6 CACCTG TTAGCCGGCC - +4 yetfasco__YER088C_2221 4 0.654244 15998.2 1 6 CACCTG AGCTCATCGC - +4 cisbp__M1478 5 0.654244 15998.2 1 5 CACCTG TTTGTGACTA + +4 jaspar__MA0016.1-usp 5 0.654244 15998.2 1 5 CACCTG GGGGTCACGG + +4 neph__UW.Motif.0393 -1 0.654244 15998.2 1 5 CACCTG CCCAGAATGC + +4 predrem__nrMotif1017 -1 0.654244 15998.2 1 5 CACCTG TCTTCAGTCA + +4 predrem__nrMotif151 5 0.654244 15998.2 1 5 CACCTG GTGTGCACAC + +4 stark__AWNTGGGTCA-Hr3 -1 0.654244 15998.2 1 5 CACCTG AAATGGGTCA + +4 transfac_pro__M00933-btd-CTCF-dar1-kay-Klf15-klu-Nf-YA-Nf-YB-sd-Sp1-Spps-sr-Stat92E -1 0.654244 15998.2 1 5 CACCTG CCCCGCCCCC + +4 transfac_pro__M01986-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt-Taf1 -1 0.654244 15998.2 1 5 CACCTG ACCGGAAGTA + +4 cisbp__M1386 -1 0.654244 15998.2 1 5 CACCTG AACTGACTCT - +4 cisbp__M1850-usp 5 0.654244 15998.2 1 5 CACCTG GGGGTCACGG - +4 predrem__nrMotif1483 5 0.654244 15998.2 1 5 CACCTG CTGGGCACTG - +4 predrem__nrMotif1583 5 0.654244 15998.2 1 5 CACCTG CTGCATGCCT - +4 cisbp__M1264 6 0.654244 15998.2 1 4 CACCTG AACCGAAACT + +4 stark__GTCANTNAAC-EcR 6 0.654244 15998.2 1 4 CACCTG GTCAATAAAC + +4 taipale_cyt_meth__HIC1_NRTGCCAMCN_eDBD_meth 6 0.654244 15998.2 1 4 CACCTG CATGCCAACC + +4 cisbp__M1297 -2 0.654244 15998.2 1 4 CACCTG CCCGATTTGG - +4 predrem__nrMotif255 6 0.654244 15998.2 1 4 CACCTG CTGGGAGACC - +4 transfac_pro__M05381 -2 0.654244 15998.2 1 4 CACCTG GCTGCAGCCC - +4 swissregulon__sacCer__STP4 7 0.654244 15998.2 1 3 CACCTG TCAGCCGCAC - +4 cisbp__M0941-Gsc-oc-Ptx1 2 0.65437 16001.3 1 6 CACCTG TTAATCCCC + +4 cisbp__M1038 3 0.65437 16001.3 1 6 CACCTG CCCAATCAA + +4 cisbp__M1288 2 0.65437 16001.3 1 6 CACCTG CTTACGTAA + +4 cisbp__M1790 1 0.65437 16001.3 1 6 CACCTG TGCCCGCGT + +4 cisbp__M2431 3 0.65437 16001.3 1 6 CACCTG GGCTTCCAC + +4 cisbp__M6249 3 0.65437 16001.3 1 6 CACCTG AAACAAATT + +4 neph__UW.Motif.0268 1 0.65437 16001.3 1 6 CACCTG AATTCTGTG + +4 predrem__nrMotif1048 1 0.65437 16001.3 1 6 CACCTG AGACATTCT + +4 predrem__nrMotif1408 3 0.65437 16001.3 1 6 CACCTG ATGGCCCAG + +4 predrem__nrMotif1491 0 0.65437 16001.3 1 6 CACCTG TGGCTGAAT + +4 predrem__nrMotif913 3 0.65437 16001.3 1 6 CACCTG ACAAACCCA + +4 predrem__nrMotif1147 0 0.65437 16001.3 1 6 CACCTG CTCCAACCA - +4 predrem__nrMotif1459 3 0.65437 16001.3 1 6 CACCTG AAATAGCAG - +4 predrem__nrMotif2028 3 0.65437 16001.3 1 6 CACCTG TTCTAAATG - +4 predrem__nrMotif815 3 0.65437 16001.3 1 6 CACCTG AGTCACTCA - +4 transfac_pro__M04795-CG9650-ebi-MTA1-like-nej-Stat92E 2 0.65437 16001.3 1 6 CACCTG TTCACTTCC - +4 predrem__nrMotif370 4 0.65437 16001.3 1 5 CACCTG AAATGTCCT + +4 taipale_cyt_meth__VENTX_CGATTATCG_FL_repr 4 0.65437 16001.3 1 5 CACCTG CGATTATCG + +4 transfac_pro__M04714-aop-Eip74EF-Ets21C-Ets96B -1 0.65437 16001.3 1 5 CACCTG ACTTCCGGG + +4 predrem__nrMotif1643 4 0.65437 16001.3 1 5 CACCTG CCAGCAACA - +4 cisbp__M1160-Awh-CG11085-Dr-E5-ems-en-inv-slou-unpg 5 0.65437 16001.3 1 4 CACCTG CTAATCAGC + +4 predrem__nrMotif420 -2 0.65437 16001.3 1 4 CACCTG CTTGAAAAA + +4 predrem__nrMotif1126 5 0.65437 16001.3 1 4 CACCTG AATGGCACT - +4 predrem__nrMotif2199 5 0.65437 16001.3 1 4 CACCTG GGGAGAACA - +4 transfac_pro__M04816-Dif-dl-Rel 5 0.65437 16001.3 1 4 CACCTG GGCTTTCCC - +4 predrem__nrMotif1637 -3 0.65437 16001.3 1 3 CACCTG CTGAGATTT + +4 predrem__nrMotif1865 -3 0.65437 16001.3 1 3 CACCTG CTGATTGCA + +4 predrem__nrMotif424 -3 0.65437 16001.3 1 3 CACCTG CTGTTGGAA + +4 transfac_pro__M04789-croc-fd59A-fd96Ca-fd96Cb-fkh 6 0.65437 16001.3 1 3 CACCTG AATATTGAC + +4 predrem__nrMotif1545 -3 0.65437 16001.3 1 3 CACCTG CTGCAAGCT - +4 predrem__nrMotif1846 -3 0.65437 16001.3 1 3 CACCTG CTGGATGCA - +4 predrem__nrMotif24 -3 0.65437 16001.3 1 3 CACCTG CTGTGGCTG - +4 cisbp__M4309 1 0.654419 16002.5 1 6 CACCTG TCGCCTCGAGGC + +4 cisbp__M5998-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.654419 16002.5 1 6 CACCTG GGTGACGTCATT + +4 cisbp__M6398-E2f1-ewg 3 0.654419 16002.5 1 6 CACCTG CTGCGCATGCGC + +4 hocomoco__ELK4_HUMAN.H11MO.0.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-aop-bs-pnt 0 0.654419 16002.5 1 6 CACCTG GACCGGAAGTGG + +4 hocomoco__PAX4_HUMAN.H11MO.0.D-CG34367 0 0.654419 16002.5 1 6 CACCTG TAACTAATTCGC + +4 predrem__nrMotif69 6 0.654419 16002.5 1 6 CACCTG CACACACACACA + +4 taipale_cyt_meth__MSC_NRNCATATGNYN_FL_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.654419 16002.5 1 6 CACCTG CACCATATGGTG + +4 transfac_pro__M06444 5 0.654419 16002.5 1 6 CACCTG TCCGCGTCCTGC + +4 transfac_pro__M06660 6 0.654419 16002.5 1 6 CACCTG AGAAATTACCGC + +4 cisbp__M4939-Eip93F 1 0.654419 16002.5 1 6 CACCTG ACTCCCGAAAAT - +4 flyfactorsurvey__srp_FlyReg_FBgn0003507-srp 3 0.654419 16002.5 1 6 CACCTG ATCAACCGATAG - +4 hocomoco__RFX2_HUMAN.H11MO.1.A-CG5846-CG9727-Max-Rfx 6 0.654419 16002.5 1 6 CACCTG CCATGGCAACCG - +4 hocomoco__RUNX1_MOUSE.H11MO.0.A-Bgb-Bro-MTA1-like-RunxA-RunxB-ebi-lz-run 2 0.654419 16002.5 1 6 CACCTG CAAACCACAGAC - +4 taipale_cyt_meth__SPDEF_NAMCCGGATGTN_FL-Eip74EF-Ets96B-Ets98B 0 0.654419 16002.5 1 6 CACCTG CACATCCGGGTC - +4 taipale_tf_pairs__FOXJ2_PITX1_TAAACAGGATTA_CAP_repr-Ptx1 2 0.654419 16002.5 1 6 CACCTG TAATCCTGTTTA - +4 tiffin__TIFDMEM0000031 1 0.654419 16002.5 1 6 CACCTG AAACATTTTTAA - +4 transfac_pro__M05798 2 0.654419 16002.5 1 6 CACCTG GCCGCCTTCCCT - +4 transfac_pro__M05805 5 0.654419 16002.5 1 6 CACCTG GTCAGCGCCTTT - +4 transfac_pro__M05843 4 0.654419 16002.5 1 6 CACCTG TGTTTAGCTTCG - +4 transfac_pro__M05952 6 0.654419 16002.5 1 6 CACCTG TCGTTACGCCAG - +4 transfac_pro__M05972 4 0.654419 16002.5 1 6 CACCTG TCTTCACCCCAC - +4 transfac_pro__M06293 0 0.654419 16002.5 1 6 CACCTG GGCCTCGTCCCG - +4 transfac_pro__M06488 3 0.654419 16002.5 1 6 CACCTG GATTCCCTCCCA - +4 transfac_pro__M07259-Hsf 4 0.654419 16002.5 1 6 CACCTG GAAGCTTCTGGA - +4 transfac_pro__M07436-Brf-brm-btd-E(z)-HDAC1-klu-l(3)neo38-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-vtd 5 0.654419 16002.5 1 6 CACCTG CCCCCCACCCCC - +4 yetfasco__YIL101C_2039 1 0.654419 16002.5 1 6 CACCTG TCGCCTCGAGGC - +4 taipale_cyt_meth__GATA5_WGATAACGATCT_FL_repr-GATAe-grn-pnr-srp 7 0.654419 16002.5 1 5 CACCTG AGATAACGATCT + +4 transfac_pro__M05707-CG2120 -1 0.654419 16002.5 1 5 CACCTG CCCTCAAAAAGA + +4 transfac_pro__M06436 7 0.654419 16002.5 1 5 CACCTG CTGGGCAAACTT + +4 transfac_pro__M05632-CG6654-CG7372 7 0.654419 16002.5 1 5 CACCTG TTTTTCAAAGCT - +4 transfac_pro__M05761 7 0.654419 16002.5 1 5 CACCTG TCTGCCGCAACT - +4 transfac_pro__M05886 7 0.654419 16002.5 1 5 CACCTG TCCGTTCGAACG - +4 transfac_pro__M06022 7 0.654419 16002.5 1 5 CACCTG TCTTCTTGACAG - +4 transfac_pro__M06221 7 0.654419 16002.5 1 5 CACCTG TATACTATAACT - +4 transfac_pro__M06405 7 0.654419 16002.5 1 5 CACCTG TAGGCAGTACAC - +4 transfac_pro__M06741 7 0.654419 16002.5 1 5 CACCTG GCTTTTTGTCCG - +4 transfac_pro__M07862-bs -1 0.654419 16002.5 1 5 CACCTG ACCATATATGGT - +4 taipale_cyt_meth__CREB3_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.654419 16002.5 1 4 CACCTG GATGACGTCACC - +4 transfac_pro__M05786 8 0.654419 16002.5 1 4 CACCTG TCTGCCTGCACA - +4 transfac_pro__M06182 8 0.654419 16002.5 1 4 CACCTG TTTCCATGCACG - +4 transfac_pro__M06232-CG2120 8 0.654419 16002.5 1 4 CACCTG CAGTTTTGCACG - +4 transfac_pro__M06263 8 0.654419 16002.5 1 4 CACCTG GGCTTTGTCACG - +4 transfac_pro__M06287 8 0.654419 16002.5 1 4 CACCTG TCTCATGCAACA - +4 neph__UW.Motif.0231 9 0.654419 16002.5 1 3 CACCTG TGTGAAAATCAC - +4 cisbp__M2564-Hsf 0 0.654455 16003.4 1 5 CACCTG TTTCT + +4 transfac_public__M00028-Hsf 0 0.654455 16003.4 1 5 CACCTG TTTCT - +4 cisbp__M2041-mirr 1 0.654455 16003.4 1 4 CACCTG AAACA + +4 cisbp__M1893 -2 0.654455 16003.4 1 4 CACCTG GCTTT - +4 tfdimers__MD00300 9 0.655151 16020.4 1 6 CACCTG TTCAAAGAACATATGTTCTTTGTA + +4 tfdimers__MD00331 13 0.655151 16020.4 1 6 CACCTG CAGCGGACTGGGACAGCTGGGCCG + +4 tfdimers__MD00552-Usf 13 0.655151 16020.4 1 6 CACCTG GCCCCCAGCGCGCCCCCTGCCGCC - +4 flyfactorsurvey__bowl_SOLEXA_FBgn0004893-bowl-drm-odd-sob 8 0.655181 16021.1 1 6 CACCTG ACAAACAGTAGCCC + +4 flyfactorsurvey__gt_NAR_FBgn0001150-CG7786-Pdp1-gt-hng1-vri 6 0.655181 16021.1 1 6 CACCTG CGGTGTTACGTAAT + +4 neph__UW.Motif.0325 2 0.655181 16021.1 1 6 CACCTG TTACTCAGCCAGCA + +4 swissregulon__hs__ARID5B.p2-htk 8 0.655181 16021.1 1 6 CACCTG AACCACAATACCAA + +4 taipale_tf_pairs__FOXO1_HOXA10_RWMAACAYCRTWAA_CAP_repr-foxo 3 0.655181 16021.1 1 6 CACCTG GTAAACATCGTAAA + +4 transfac_pro__M02017-Hsf 4 0.655181 16021.1 1 6 CACCTG GAACTTTCTGGAAC + +4 transfac_pro__M09463-tll 5 0.655181 16021.1 1 6 CACCTG TCGTTGACTTTTTT + +4 transfac_public__M00257-peb 8 0.655181 16021.1 1 6 CACCTG CCCCAAACCACCCC + +4 cisbp__M1972 1 0.655181 16021.1 1 6 CACCTG CCCCCTTGGGCCCC - +4 cisbp__M2290-bon-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-NFAT-pnr-Stat92E 6 0.655181 16021.1 1 6 CACCTG ATGAGTCATCTCCT - +4 cisbp__M3843-peb 8 0.655181 16021.1 1 6 CACCTG CCCCAAACCACCCC - +4 hocomoco__NF2L2_HUMAN.H11MO.0.A-Jra-cnc-kay-maf-S 2 0.655181 16021.1 1 6 CACCTG AACTGCTGAGTCAT - +4 hocomoco__TFDP1_HUMAN.H11MO.0.C-Dp-E2f1-E2f2-Spps-btd 6 0.655181 16021.1 1 6 CACCTG TTTTCCCGCCCCCC - +4 jaspar__MA0163.1 1 0.655181 16021.1 1 6 CACCTG CCCCCTTGGGCCCC - +4 jaspar__MA0489.1-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-bon-grn-kay-mor-nej-pnr 6 0.655181 16021.1 1 6 CACCTG ATGAGTCATCTCCT - +4 neph__UW.Motif.0681 6 0.655181 16021.1 1 6 CACCTG GTTTTTCTCTTCTG - +4 taipale_tf_pairs__ELK1_HOXA1_RCCGGAAGTAATTA_CAP-lab 4 0.655181 16021.1 1 6 CACCTG TAATTACTTCCGGT - +4 taipale_tf_pairs__FOXJ2_ELF1_NWAAACAGGAAGNN_CAP-Eip74EF 3 0.655181 16021.1 1 6 CACCTG TACTTCCTGTTTAT - +4 transfac_pro__M01439-Dfd-Dll 6 0.655181 16021.1 1 6 CACCTG ATTAATTACCTCAG - +4 transfac_pro__M02106-btd-CG7839-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps 0 0.655181 16021.1 1 6 CACCTG GCTCTGATTGGCTG - +4 cisbp__M5402-Ets21C-Ets97D-pnt -1 0.655181 16021.1 1 5 CACCTG ACCGGAAATCCGGT + +4 cisbp__M5432-Ets21C-Ets97D -1 0.655181 16021.1 1 5 CACCTG ACCGGAAATCCGGT + +4 neph__UW.Motif.0207 -1 0.655181 16021.1 1 5 CACCTG AAATGACTTTCCCA + +4 taipale__ERG_full_ACCGGAWATCCGGT-Ets21C-Ets97D -1 0.655181 16021.1 1 5 CACCTG ACCGGAAATCCGGT + +4 transfac_pro__M03881-NFAT 10 0.655181 16021.1 1 4 CACCTG ACTGGAAAATTCCC + +4 hocomoco__THAP1_HUMAN.H11MO.0.C-CG10431-CTCF-Myc-Taf1-lid-pho-phol 3 0.655234 16022.4 1 6 CACCTG CGCCGCCATCTTGGCTGCGGGC + +4 hocomoco__RFX2_MOUSE.H11MO.0.A-CG5846-CG9727-Max-Rfx-SREBP 6 0.655234 16022.4 1 6 CACCTG TCCCGTTGCCATGGCAACCGCC - +4 hocomoco__ZN341_HUMAN.H11MO.0.C-CTCF-CoRest-Dif-Klf15-Spps-Spt20-btd-ct-dl-klu-usp 4 0.655234 16022.4 1 6 CACCTG GCTCTTCCCTCCCCCCCCCCCC - +4 tfdimers__MD00221-foxo-slp2 6 0.655234 16022.4 1 6 CACCTG TTTTATTTCCTGTTTTTTTTTT - +4 transfac_pro__M08799 10 0.655234 16022.4 1 6 CACCTG TATCCTCGCCGACATCACCACC - +4 transfac_pro__M09428 15 0.655673 16033.2 1 6 CACCTG AAACCCTAAACCCTAAACCCTAA + +4 taipale_cyt_meth__ELF3_ACCCGGAAGNNNNNNNNNWWWWW_eDBD-Eip74EF 12 0.655673 16033.2 1 6 CACCTG ATTTTTGGGCGTTACTTCCGGGT - +4 taipale_cyt_meth__YY1_NGCCATNTTTGNCNNNNYGTGCN_FL_repr-pho-phol-Taf1 2 0.655673 16033.2 1 6 CACCTG AGCACGAATTGCCAAAGATGGCG - +4 cisbp__M6283-btd-EcR-eg-HDAC1-Hnf4-Hr78-kni-knrl-nej-Spps-svp-usp 2 0.656475 16052.8 1 6 CACCTG TGGACTTTGGCCT + +4 hocomoco__CREB3_HUMAN.H11MO.0.D-Atf6-CrebA-Xbp1 4 0.656475 16052.8 1 6 CACCTG TGGTGACGTGGCA + +4 neph__UW.Motif.0066 3 0.656475 16052.8 1 6 CACCTG CTGAGTCAGCCAG + +4 neph__UW.Motif.0352 5 0.656475 16052.8 1 6 CACCTG TCTGTTTTTTTCA + +4 neph__UW.Motif.0362 5 0.656475 16052.8 1 6 CACCTG TCAAAGATTTTAA + +4 swissregulon__sacCer__MIG2-klu-sr 2 0.656475 16052.8 1 6 CACCTG GTTACCCCGCAAT + +4 taipale_cyt_meth__EGR2_NMCGCCCACGCAN_FL-klu-sr 6 0.656475 16052.8 1 6 CACCTG CCCGCCCACGCAC + +4 transfac_pro__M00711 0 0.656475 16052.8 1 6 CACCTG TCACTGTGACTCA + +4 hocomoco__BARH1_HUMAN.H11MO.0.D-B-H1-B-H2-unpg 4 0.656475 16052.8 1 6 CACCTG TTAAGAGCATTTA - +4 neph__UW.Motif.0141 7 0.656475 16052.8 1 6 CACCTG TGTGAGTCAGCAG - +4 taipale_cyt_meth__POU3F1_NTATGCWAATNNN_eDBD-Dll-dve-nub-pdm2-pdm3-vvl 6 0.656475 16052.8 1 6 CACCTG CTCATTAGCATAA - +4 transfac_pro__M01581 1 0.656475 16052.8 1 6 CACCTG TTTCCCTTTTTGG - +4 taipale_tf_pairs__ETV5_FOXI1_TGTTGNCGGAWRN_CAP-Ets96B -1 0.656475 16052.8 1 5 CACCTG ACTTCCGTCAACA - +4 tfdimers__MD00585-kn-Stat92E 10 0.659024 16115.1 1 6 CACCTG GTTCTCATTTCCCCAGGGGAATTGGTCCC + +4 cisbp__M3256-bin-croc-fd59A-fkh-foxo 11 0.659735 16132.5 1 6 CACCTG TTATAAATAAACATTCAA + +4 factorbook__CREB-ext-CrebB 3 0.659735 16132.5 1 6 CACCTG CGTCATCAGCGCGCGCCG + +4 taipale_cyt_meth__ZNF684_NYACAGTCCRCCCCTTKN_FL_meth 10 0.659735 16132.5 1 6 CACCTG ATACAGTCCACCCCTTTA + +4 taipale_tf_pairs__FLI1_ETV7_NSMGGACGGAYNTCCKSN_CAP-aop 11 0.659735 16132.5 1 6 CACCTG ACCGGACGGATTTCCGGT + +4 bergman__pnr-pnr-srp 2 0.659735 16132.5 1 6 CACCTG ACCCCCTTATCACAAAAT - +4 hocomoco__ZSC31_HUMAN.H11MO.0.C 2 0.659735 16132.5 1 6 CACCTG CATAACTGCCCTGCTGCC - +4 taipale_tf_pairs__MEIS2_ONECUT2_NTGACAGNTAATCRATAN_CAP-hth-onecut 8 0.659735 16132.5 1 6 CACCTG GTATCGATTAGCTGTCAA - +4 transfac_pro__M06819 0 0.659735 16132.5 1 6 CACCTG AAGCTTTTGTCTTCTTCT - +4 tfdimers__MD00211-pho-phol 5 0.661325 16171.4 1 6 CACCTG TCAAACAGCTGGTCACCATATGTTGATAGCGT + +4 cisbp__M3961 0 0.661655 16179.4 1 6 CACCTG AAACAAA + +4 elemento__TGACCCA 1 0.661655 16179.4 1 6 CACCTG TGACCCA + +4 predrem__nrMotif1638 0 0.661655 16179.4 1 6 CACCTG GATCTCA + +4 transfac_pro__M02116-Sox100B 0 0.661655 16179.4 1 6 CACCTG TACAATG + +4 transfac_public__M00148 0 0.661655 16179.4 1 6 CACCTG AAACAAA + +4 yetfasco__YDR477W_1110-AMPKalpha-CG43143 1 0.661655 16179.4 1 6 CACCTG TTTCTTT + +4 elemento__AAGGACA 1 0.661655 16179.4 1 6 CACCTG TGTCCTT - +4 elemento__AAGGACG 1 0.661655 16179.4 1 6 CACCTG CGTCCTT - +4 elemento__AAGGCCA 1 0.661655 16179.4 1 6 CACCTG TGGCCTT - +4 elemento__CAAGGAC 0 0.661655 16179.4 1 6 CACCTG GTCCTTG - +4 hocomoco__NFIA_HUMAN.H11MO.1.D-NfI 0 0.661655 16179.4 1 6 CACCTG TGCCAAG - +4 transfac_pro__M01104-ovo 1 0.661655 16179.4 1 6 CACCTG CCCCCGC - +4 predrem__nrMotif1958 2 0.661655 16179.4 1 5 CACCTG CATGCCA - +4 predrem__nrMotif1353 -2 0.661655 16179.4 1 4 CACCTG GCTCACA + +4 hdpi__MAGEF1 -2 0.661655 16179.4 1 4 CACCTG CCATTAA - +4 predrem__nrMotif1406 -2 0.661655 16179.4 1 4 CACCTG TCTCATT - +4 predrem__nrMotif212 -2 0.661655 16179.4 1 4 CACCTG TCTCTGG - +4 predrem__nrMotif588 -2 0.661655 16179.4 1 4 CACCTG ACTGCCA - +4 predrem__nrMotif528 4 0.661655 16179.4 1 3 CACCTG GAAACAC + +4 swissregulon__sacCer__DAL80-GATAd-GATAe-grn-pnr-srp -3 0.661655 16179.4 1 3 CACCTG CTTATCG + +4 transfac_pro__M07322-Hsf -3 0.661655 16179.4 1 3 CACCTG CTGCCGG + +4 hocomoco__TFCP2_HUMAN.H11MO.0.D-gem 9 0.661677 16180 1 6 CACCTG GCCTGACCTGGCCAGA + +4 taipale_cyt_meth__ZBTB14_NTGCRCGTGCACGYGN_FL 9 0.661677 16180 1 6 CACCTG ATGCGCGTGCACGTGA + +4 transfac_pro__M01338-abd-A-Antp-bsh-btn-ind-lab-Lim3-pb-Scr-Ubx 10 0.661677 16180 1 6 CACCTG TTGAGTTAATTACCCT + +4 transfac_pro__M01469-Antp-HGTX-lab-Scr 10 0.661677 16180 1 6 CACCTG AGTAATTAATTACTTC + +4 transfac_pro__M07358-Hsf 6 0.661677 16180 1 6 CACCTG GGGAATCTTCTAGAGG + +4 transfac_pro__M09044 3 0.661677 16180 1 6 CACCTG CTCCACCGACAATTTC + +4 cisbp__M3298 0 0.661677 16180 1 6 CACCTG ATCTTGTTTATGTATA - +4 cisbp__M5849-Sox100B 7 0.661677 16180 1 6 CACCTG ATGACTGCACATTCAT - +4 hocomoco__ANDR_MOUSE.H11MO.0.A-Hsf-fkh 3 0.661677 16180 1 6 CACCTG AGGAACAGAGTGTTCC - +4 hocomoco__ZF64A_HUMAN.H11MO.0.D-CTCF 4 0.661677 16180 1 6 CACCTG CAGGTTCCCGGGCCCC - +4 homer__GCAGCCAAGCGTGACC_PAX5-Poxm-ey-sv-toy 5 0.661677 16180 1 6 CACCTG GGTCACGCTTGGCTGC - +4 taipale__SOX9_full_ATGAATRTKCAGWCAT_repr-Sox100B 7 0.661677 16180 1 6 CACCTG ATGACTGCACATTCAT - +4 transfac_public__M00287-btd-CG7839-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-TfIIB-yps 0 0.661677 16180 1 6 CACCTG GCTCTGATTGGCTGAT - +4 cisbp__M4325 11 0.661677 16180 1 5 CACCTG CGGGAAGCCAATCCCG + +4 taipale__RFX5_DBD_NGTTRCCATGGYAACN-CG5846-CG9727-Max-Rfx-SREBP 11 0.661677 16180 1 5 CACCTG CGTTGCCATGGCAACG + +4 transfac_pro__M05447-nerfin-1-nerfin-2 -1 0.661677 16180 1 5 CACCTG ACTGATTCGATTGCCA - +4 cisbp__M0890-Awh 2 0.663171 16216.5 1 6 CACCTG GTAATCAA + +4 cisbp__M0940-bsh-CG34367-Dll-Dr-E5-ems-en-eve-exex-inv-lab-slou-unpg 2 0.663171 16216.5 1 6 CACCTG GCCAATTA + +4 cisbp__M1017-al-Awh-CG11085-CG15696-CG18599-CG32532-CG34367-Dr-dve-E5-ems-en-exex-inv-lab-Lim3-otp-repo-ro-slou-unpg-Vsx1-Vsx2-zfh2 2 0.663171 16216.5 1 6 CACCTG GCTAATTA + +4 cisbp__M1026-Abd-B-cad 2 0.663171 16216.5 1 6 CACCTG TTTATGAC + +4 taipale__OTX2_DBD_NTAATCCN-bcd-Gsc-oc 2 0.663171 16216.5 1 6 CACCTG TTAATCCT + +4 taipale_cyt_meth__HOXB5_RTCGTTAN_eDBD_meth-abd-A-Antp-btn-Dfd-Dll-eve-exex-ind-lab-pb-Scr-Ubx 0 0.663171 16216.5 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__RAX_YTAATTAN_eDBD_meth-Antp-CG11294-CG4328-Drgx-E5-ems-en-eve-ind-inv-Lim3-Lmx1a-OdsH-pb-Rx-Scr-Ubx-unpg-Vsx1-Vsx2-zen2 1 0.663171 16216.5 1 6 CACCTG CTAATTAC + +4 cisbp__M0124 2 0.663171 16216.5 1 6 CACCTG ATTTTTAT - +4 cisbp__M0125 2 0.663171 16216.5 1 6 CACCTG TTTATTTT - +4 cisbp__M0144 2 0.663171 16216.5 1 6 CACCTG ATTTTTAT - +4 cisbp__M0485 1 0.663171 16216.5 1 6 CACCTG AGCCCTAC - +4 cisbp__M0786-srp 2 0.663171 16216.5 1 6 CACCTG CTTATCAG - +4 cisbp__M0935-Dll-HGTX 1 0.663171 16216.5 1 6 CACCTG GCAATTAT - +4 cisbp__M0976-abd-A-Antp-btn-CG11085-Dfd-Dr-E5-ems-eve-exex-ftz-HGTX-ind-lab-lms-pb-Scr-slou-tup-Ubx-unpg-zen-zen2 0 0.663171 16216.5 1 6 CACCTG GCCATTAG - +4 cisbp__M4829-Coop 0 0.663171 16216.5 1 6 CACCTG ACCCGGAA - +4 hocomoco__IKZF1_HUMAN.H11MO.0.C 2 0.663171 16216.5 1 6 CACCTG TCTCCCAA - +4 predrem__nrMotif143 2 0.663171 16216.5 1 6 CACCTG CCCACTGG - +4 swissregulon__hs__MYB.p2 0 0.663171 16216.5 1 6 CACCTG CAACCGCC - +4 transfac_pro__M00679-tll 2 0.663171 16216.5 1 6 CACCTG TTTGACTT - +4 transfac_pro__M07487 2 0.663171 16216.5 1 6 CACCTG ACTGCCAC - +4 yetfasco__YDR451C_716 0 0.663171 16216.5 1 6 CACCTG TAATTACA - +4 cisbp__M0062 3 0.663171 16216.5 1 5 CACCTG TTACACAC + +4 flyfactorsurvey__Ct_Cell_FBgn0004198-ct -1 0.663171 16216.5 1 5 CACCTG TCTTGAAC + +4 homer__CCCCGCGC_SUT1_ -1 0.663171 16216.5 1 5 CACCTG CCCCGCGC + +4 jaspar__MA0406.1-sd -1 0.663171 16216.5 1 5 CACCTG ACATTCCC + +4 predrem__nrMotif1911 3 0.663171 16216.5 1 5 CACCTG TTGAACCA + +4 flyfactorsurvey__Six4_SOLEXA_FBgn0027364-Optix-Six4 3 0.663171 16216.5 1 5 CACCTG TATCAATT - +4 hocomoco__OTX1_HUMAN.H11MO.0.D 3 0.663171 16216.5 1 5 CACCTG CTAATCCT - +4 predrem__nrMotif1237 -1 0.663171 16216.5 1 5 CACCTG ACAAATTG - +4 transfac_pro__M05544-CG9650 -1 0.663171 16216.5 1 5 CACCTG TCCTTACG - +4 predrem__nrMotif1107 4 0.663171 16216.5 1 4 CACCTG TTCCCCCC + +4 cisbp__M0558 -2 0.663171 16216.5 1 4 CACCTG TCTTCTCC - +4 cisbp__M0061 5 0.663171 16216.5 1 3 CACCTG ACACACAC + +4 predrem__nrMotif1964 -3 0.663171 16216.5 1 3 CACCTG CTCTTGCA - +4 tfdimers__MD00265-sens-2 14 0.663331 16220.4 1 6 CACCTG AAAAAAGCAGTGATTTCCTTAATTTTTA - +4 tfdimers__MD00418-MTF-1 1 0.663331 16220.4 1 6 CACCTG CCCCCTGCCCTCCCCCCTCCCCCCCCCC - +4 cisbp__M4925-al-bsh-CG32532-CG34367-Dll-Dr-lms-OdsH-repo-unc-4-unpg 0 0.664696 16253.8 1 6 CACCTG TAATTG + +4 flyfactorsurvey__Dr_SOLEXA_FBgn0000492-CG32532-CG34367-Dll-Dr-OdsH-al-bsh-en-inv-lms-repo-unc-4-unpg 0 0.664696 16253.8 1 6 CACCTG TAATTG + +4 fantom__motif49_ACAGRG -1 0.664696 16253.8 1 5 CACCTG CTCTGT - +4 hdpi__TMSL3 1 0.664696 16253.8 1 5 CACCTG CGTCAT - +4 hdpi__PLG -2 0.664696 16253.8 1 4 CACCTG TCTGTC - +4 transfac_pro__M01886-NFAT 2 0.664696 16253.8 1 4 CACCTG TTTTCC - +4 hdpi__CYCS-Cyt-c-d 2 0.664988 16260.9 1 6 CACCTG CAAACCCCCGC + +4 taipale__SP1_DBD_GCCMCGCCCMC-btd-cbt-CG3065-CG42741-Clp-dar1-hkb-kay-Klf15-klu-luna-Nf-YB-sd-Sp1-Spps-sr-Stat92E 4 0.664988 16260.9 1 6 CACCTG ACCCCGCCCCC + +4 taipale_cyt_meth__PROP1_TAATTNNATTA_eDBD-al-CG11294-CG32532-CG9876-Dr-Drgx-en-inv-OdsH-Optix-Traf4 0 0.664988 16260.9 1 6 CACCTG TAATTGGATTA + +4 taipale_cyt_meth__PROP1_TAAYNTCGTTA_eDBD_meth-CG32532 4 0.664988 16260.9 1 6 CACCTG TAATCTCGTTA + +4 tiffin__TIFDMEM0000032 2 0.664988 16260.9 1 6 CACCTG AAAACTTTATT + +4 transfac_pro__M00507 1 0.664988 16260.9 1 6 CACCTG GGACGCGTGGC + +4 transfac_pro__M02102-E2f1-ewg 2 0.664988 16260.9 1 6 CACCTG TGCGCATGCGC + +4 transfac_pro__M03830 4 0.664988 16260.9 1 6 CACCTG CGCTGACCACA + +4 transfac_pro__M07052-E2f1-ewg-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG33886-His2B:CG33888-Hi 1 0.664988 16260.9 1 6 CACCTG GCGCATGCGCG + +4 cisbp__M4775-br 0 0.664988 16260.9 1 6 CACCTG TTTCTAATCAC - +4 factorbook__ZNF281-Spps-btd-klu 1 0.664988 16260.9 1 6 CACCTG TCCCCTCCCCC - +4 hocomoco__HMX2_HUMAN.H11MO.0.D 0 0.664988 16260.9 1 6 CACCTG AACCAATTAAA - +4 hocomoco__ZN263_HUMAN.H11MO.1.A-klu 1 0.664988 16260.9 1 6 CACCTG CCTCCTCCCTC - +4 tiffin__TIFDMEM0000085 2 0.664988 16260.9 1 6 CACCTG TTTACTTATTT - +4 transfac_public__M00079-ham-srp 1 0.664988 16260.9 1 6 CACCTG TTATCTTGTCT - +4 bergman__shn-ZFP2-CG12018-Dif-Rel-dl-shn 6 0.664988 16260.9 1 5 CACCTG GGGGAATTCCC + +4 cisbp__M1614 -1 0.664988 16260.9 1 5 CACCTG CGCTCTAGACT - +4 cisbp__M2291-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan 6 0.664988 16260.9 1 5 CACCTG ATGAGTCATCC - +4 hocomoco__HXD3_HUMAN.H11MO.0.D-Awh-E5-Lim3-al-ind-pb-unpg 6 0.664988 16260.9 1 5 CACCTG CCTAATTAACC - +4 jaspar__MA0490.1-CoRest-Jra-Mef2-Myc-bon-cnc-kay-mor-nej-pan 6 0.664988 16260.9 1 5 CACCTG ATGAGTCATCC - +4 bergman__Rel-Dif-Rel 7 0.664988 16260.9 1 4 CACCTG GGGGAATCCCC + +4 cisbp__M5140-ovo 7 0.664988 16260.9 1 4 CACCTG ATAACGGTACT + +4 taipale_cyt_meth__HOXC10_NGYAATAAAAN_eDBD_meth-Abd-B-cad-eve 7 0.664988 16260.9 1 4 CACCTG GTTTTATTACC - +4 cisbp__M4489-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E-sv 13 0.665041 16262.2 1 6 CACCTG AAAGAGGAAGTGAAACTAG + +4 hocomoco__STAT2_HUMAN.H11MO.0.A-Stat92E 9 0.665041 16262.2 1 6 CACCTG AGGAAAATGAAACTGAAAG + +4 taipale__HINFP1_full_GCGGACSNNSNNSGTCCGC_repr-CG17829 3 0.665041 16262.2 1 6 CACCTG GCGGACGTTCAACGTCCGC + +4 transfac_pro__M07691-cnc-kay-maf-S-nej-tj 11 0.665041 16262.2 1 6 CACCTG AATTGCTGACTCAGCATTT + +4 cisbp__M6408-ey-Poxm-sv-toy 4 0.665041 16262.2 1 6 CACCTG GTCACGCTTCACTGCCCTC - +4 taipale_tf_pairs__FLI1_DLX2_RSCGGAANNNNNYAATTAN_CAP 12 0.665041 16262.2 1 6 CACCTG TTAATTGCTCATTTCCGGT - +4 transfac_pro__M09471 4 0.665041 16262.2 1 6 CACCTG CGTTGACTTTTTTTTATCC - +4 tfdimers__MD00509-Atac3-lz-run-RunxA-RunxB 3 0.666954 16309 1 6 CACCTG ACCCTCCACACCCACTTCCTGTCTCCC + +4 tfdimers__MD00338-Sox100B 5 0.667329 16318.2 1 6 CACCTG TTTTTTTCCTTTGTTTTGCACAATTATTTTT + +4 cisbp__M2349-Mef2 0 0.668211 16339.8 1 6 CACCTG TTCCAAAAATGGAAA + +4 cisbp__M4816-CG12236 9 0.668211 16339.8 1 6 CACCTG CACCGGATGAACACC + +4 jaspar__MA0556.1-Mef2 0 0.668211 16339.8 1 6 CACCTG TTCCAAAAATGGAAA + +4 neph__UW.Motif.0177 4 0.668211 16339.8 1 6 CACCTG TTTCAGCATTTTTCA + +4 swissregulon__hs__CUX2.p2-ct-onecut 9 0.668211 16339.8 1 6 CACCTG ATTATTGATTATTTT + +4 taipale_cyt_meth__GATA1_GATAANNNNNTTATC_eDBD_meth-GATAe-grn-pnr 6 0.668211 16339.8 1 6 CACCTG GATAAGGACCTTATC + +4 taipale_cyt_meth__MAFF_NYGCTGASTCAGCRN_FL-cnc-maf-S-tj 9 0.668211 16339.8 1 6 CACCTG ATGCTGAGTCAGCAT + +4 taipale_cyt_meth__ZNF449_NTCGCGNGCMARCAN_eDBD_meth_repr 9 0.668211 16339.8 1 6 CACCTG GTCGCGAGCCAGCAT + +4 transfac_pro__M09228 8 0.668211 16339.8 1 6 CACCTG GTAATCATTACTTTT + +4 transfac_pro__M09279 6 0.668211 16339.8 1 6 CACCTG AACCGTAACCGAATT + +4 transfac_pro__M09448 3 0.668211 16339.8 1 6 CACCTG TTTCTCCGGCGATGA + +4 cisbp__M1907-CG9650-Dif-dl-Eip74EF-nej-pnt-Stat92E-sv 4 0.668211 16339.8 1 6 CACCTG TCACTTCCTCTTTTT - +4 cisbp__M4605 9 0.668211 16339.8 1 6 CACCTG GAGAATTCATACTGG - +4 cisbp__M4631-CG9650-nej-pnt 1 0.668211 16339.8 1 6 CACCTG CCACTTCCTCTTTTT - +4 cisbp__M6493-aop-Stat92E 3 0.668211 16339.8 1 6 CACCTG CATTTCCCGGAAATG - +4 flyfactorsurvey__CG12236_SOLEXA_5_FBgn0029822-CG12236 9 0.668211 16339.8 1 6 CACCTG CACCGGATGAACACC - +4 neph__UW.Motif.0404 8 0.668211 16339.8 1 6 CACCTG TGTCTTTTTTCCCAT - +4 transfac_pro__M02874 2 0.668211 16339.8 1 6 CACCTG GTGACCGAGAGTGGT - +4 transfac_pro__M07224-CG9650-Dif-dl-nej-pnt-Stat92E-sv 4 0.668211 16339.8 1 6 CACCTG TCACTTCCTCTTTTT - +4 transfac_pro__M09144 6 0.668211 16339.8 1 6 CACCTG GATTCAGATCTGAAA - +4 transfac_pro__M09221 8 0.668211 16339.8 1 6 CACCTG GTAATCATTACTTTT - +4 transfac_pro__M09317-Myb 9 0.668211 16339.8 1 6 CACCTG TAACCGTTATAACCG - +4 dbcorrdb__CBX3__ENCSR000BRT_1__m8-HP1b-HP1c-HP1e-Su(var)205 7 0.668958 16358 1 6 CACCTG CACAGACCACCCGCCCTTTC + +4 dbcorrdb__CEBPZ__ENCSR000EDO_1__m1-CG7839 8 0.668958 16358 1 6 CACCTG ATCAAAAAGACCAATCATTA + +4 dbcorrdb__CHD1__ENCSR000AQK_1__m6-Chd1 5 0.668958 16358 1 6 CACCTG AACGAAAACGGAAAAACCTA + +4 dbcorrdb__FOXA1__ENCSR000BPX_1__m2-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-HDAC1-nej-slp2 9 0.668958 16358 1 6 CACCTG TTCCTTGTTTACTTAGCGAT + +4 dbcorrdb__KDM5B__ENCSR000AQA_1__m1-lid-Rbbp5-RpII215 3 0.668958 16358 1 6 CACCTG TCGGCACTTGCGCCCGCGGG + +4 dbcorrdb__MAFF__ENCSR000EGI_1__m1-cnc-maf-S-tj 0 0.668958 16358 1 6 CACCTG TTGCTGACTCAGCAATTTTT + +4 dbcorrdb__MYC__ENCSR000DYC_1__m1-Brf-brm-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-SREBP-Taf1-tna-Usf-vtd 4 0.668958 16358 1 6 CACCTG CGCCCACGTGGCCGCGGCGG + +4 dbcorrdb__MYC__ENCSR000EZD_1__m1-Brf-brm-Clk-E2f1-E(z)-gce-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-SREBP-tgo-tna-Usf-vtd 3 0.668958 16358 1 6 CACCTG GGCCACGTGCTCGCGGGGGG + +4 dbcorrdb__MYC__ENCSR000FAZ_1__m1-btd-Clk-cnc-E2f1-E(z)-gce-HDAC1-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-tgo-tna-Usf 11 0.668958 16358 1 6 CACCTG CCCCCGGGGACCACGTGGCC + +4 dbcorrdb__POLR2A__ENCSR000DYO_1__m1-RpII215 11 0.668958 16358 1 6 CACCTG CGTCGCCGCGGCGCTTGCGC + +4 dbcorrdb__RBBP5__ENCSR000AQC_1__m1-Rbbp5 3 0.668958 16358 1 6 CACCTG CCGCGGCTTCCGTCCGCGAG + +4 dbcorrdb__SIX5__ENCSR000BIQ_1__m1-bi-egg-mor-Six4 2 0.668958 16358 1 6 CACCTG ACTACATTTCCCAGCATGCC + +4 dbcorrdb__STAT3__ENCSR000DOX_1__m1-aop-Stat92E 0 0.668958 16358 1 6 CACCTG TCACTTCCAGGAAATGATTT + +4 dbcorrdb__TAF1__ENCSR000BGS_1__m1-CG10431-lid-pho-phol-RpII215-Taf1-Taf7 3 0.668958 16358 1 6 CACCTG CCGCCGCTGCCGCCATCTTG + +4 dbcorrdb__TAF7__ENCSR000BLU_1__m3-Taf7 12 0.668958 16358 1 6 CACCTG CACGGCGCGCAACAGCGCCG + +4 dbcorrdb__TBP__ENCSR000EHA_1__m2-Tbp 3 0.668958 16358 1 6 CACCTG TCGAACGCGCGACCTTTTGA + +4 transfac_pro__M01510-bs 3 0.668958 16358 1 6 CACCTG TGTTTCCCAATTCGGAAATG + +4 transfac_pro__M01656 11 0.668958 16358 1 6 CACCTG GGACATGTCCGGACATGTCC + +4 transfac_pro__M07695-gem-grh 0 0.668958 16358 1 6 CACCTG AAACCGGTTTAAACCGGTTT + +4 yetfasco__YMR043W_831-bs 3 0.668958 16358 1 6 CACCTG TGTTTCCCAATTCGGAAATG + +4 cisbp__M2101-CHES-1-like-croc-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 11 0.668958 16358 1 6 CACCTG TCCTCTTTGTTTACAATTCA - +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m3-CG9650 2 0.668958 16358 1 6 CACCTG TTTGCATGACAATGAGCCCT - +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m6-CG9650-SoxN 0 0.668958 16358 1 6 CACCTG AAGCTGCATAACAAAAGAGT - +4 dbcorrdb__CEBPB__ENCSR000EEX_1__m1-Irbp18-nej-Xrp1 12 0.668958 16358 1 6 CACCTG CCGAGATTGCACAACCGCCC - +4 dbcorrdb__EP300__ENCSR000AQB_1__m5-nej 10 0.668958 16358 1 6 CACCTG TTTCTCACGCCCGCTTTTTC - +4 dbcorrdb__EZH2__ENCSR000ARK_1__m1-E(z) 5 0.668958 16358 1 6 CACCTG GCCTGCCAGTCCGCGTCGCT - +4 dbcorrdb__EZH2__ENCSR000ASZ_1__m1-E(z) 13 0.668958 16358 1 6 CACCTG GCGGCCGGTTTGCGCCCCGC - +4 dbcorrdb__GATA3__ENCSR000EWS_1__m2-GATAe-grn-pnr 5 0.668958 16358 1 6 CACCTG CTGGCAGGCAGGCCAGAGAT - +4 dbcorrdb__JUN__ENCSR000EZX_1__m1-cnc-CoRest-Jra-kay-maf-S-Mef2-mor-Myc-pan-Stat92E 14 0.668958 16358 1 6 CACCTG AAGCAAGGATGACTCACCCC - +4 dbcorrdb__MXI1__ENCSR000EFE_1__m2-Eip74EF-Hcf-RpII215-Taf1 13 0.668958 16358 1 6 CACCTG GGGGCGCTTGCGGCGCCATG - +4 dbcorrdb__NFE2__ENCSR000FAF_1__m2-cnc-ewg-maf-S 3 0.668958 16358 1 6 CACCTG GCCAATCTGCTGAGTCACGT - +4 dbcorrdb__NFYB__ENCSR000EGQ_1__m1-btd-kay-Nf-YA-Nf-YB-Nf-YC-Spps-yps 4 0.668958 16358 1 6 CACCTG CCCCCTCCCTCTGATTGGCC - +4 dbcorrdb__POLR2A__ENCSR000FAJ_1__m2-aop-Dif-dl-Eip74EF-Hcf-RpII215-Sin3A-Taf1 4 0.668958 16358 1 6 CACCTG TGCGCCACTTCCGCTTCCGG - +4 dbcorrdb__RCOR1__ENCSR000ECM_1__m1-cnc-CoRest-CrebB-Jra-kay-Mef2-mor-Myc-pan-Stat92E 11 0.668958 16358 1 6 CACCTG AGGGGATGAGTCATCCCGGG - +4 dbcorrdb__RFX5__ENCSR000EHY_1__m4 1 0.668958 16358 1 6 CACCTG TTGGTTGTCCATTGTGAGTT - +4 dbcorrdb__SIN3A__ENCSR000BGL_1__m2-Sin3A 7 0.668958 16358 1 6 CACCTG ACACCACCCAATGGCGGCTG - +4 dbcorrdb__STAT3__ENCSR000DZV_1__m1-CG9650-ebi-foxo-MTA1-like-nej-Stat92E-sv 14 0.668958 16358 1 6 CACCTG AAAAGAGGAAGTGAAACTAT - +4 dbcorrdb__TCF7L2__ENCSR000EWT_1__m2-foxo-pan 4 0.668958 16358 1 6 CACCTG CCGCGGCCTGTTTGCTCTGC - +4 dbcorrdb__ZNF263__ENCSR000EWN_1__m1-Brf-vtd 13 0.668958 16358 1 6 CACCTG GGCGGGGAGGGAGGACTGCG - +4 taipale_tf_pairs__ETV2_SOX15_RSCGGAANNNNNNNYWTTGT_CAP_repr-pnt 10 0.668958 16358 1 6 CACCTG ACAATGGACTCACTTCCGGT - +4 transfac_pro__M06877-CG2120 15 0.668958 16358 1 5 CACCTG CACACGGCCGCCCAATACCG - +4 dbcorrdb__CTCF__ENCSR000DTL_1__m2-CTCF 16 0.668958 16358 1 4 CACCTG CCATGCGCTGCACTGCCGCC + +4 tfdimers__MD00391 17 0.669851 16379.9 1 6 CACCTG CCCCCCCCCCACCCCCCCCCCCCCCC + +4 transfac_pro__M00388 4 0.669851 16379.9 1 6 CACCTG CTCTCTCCCTTCCTGCGGGGAGTTAT + +4 tfdimers__MD00188-EcR-usp 8 0.669851 16379.9 1 6 CACCTG TGTTATTTTCCCTAGGGACAGAGCGA - +4 tfdimers__MD00570 9 0.669851 16379.9 1 6 CACCTG TGCACAGGACAGCTGCTGCCCTGGGG - +4 cisbp__M6273-Hey 5 0.67035 16392.1 1 6 CACCTG GGGGGCACGTGGCATTA + +4 taipale_cyt_meth__FOXR2_NYRTAWACATAAATNNN_FL_meth_repr-jumu 5 0.67035 16392.1 1 6 CACCTG ACATAAACATAAATATA + +4 transfac_pro__M02840-htk 7 0.67035 16392.1 1 6 CACCTG CATACAATACGAAATAA + +4 taipale_tf_pairs__ETV5_CEBPD_NSCGGANNTTRCGYAAN_CAP-Ets96B 10 0.67035 16392.1 1 6 CACCTG ATTGCGCAACATCCGGC - +4 taipale_tf_pairs__HOXB2_ELF1_TAATKRNNNNGGAAGTN_CAP_repr-Eip74EF-pb 0 0.67035 16392.1 1 6 CACCTG CACTTCCGCAATCATTA - +4 transfac_pro__M01381-oc-Ptx1 9 0.67035 16392.1 1 6 CACCTG GATAATTAATCCCTCTT - +4 transfac_pro__M01406-abd-A-Antp-Dfd-Scr-Ubx 10 0.67035 16392.1 1 6 CACCTG TTTTATTAATTAATTTG - +4 transfac_pro__M07852-Hsf-pb 8 0.67035 16392.1 1 6 CACCTG CGTTCTAGAACATTCCA - +4 cisbp__M1468 3 0.670626 16398.8 1 6 CACCTG TTTGATCTTT + +4 cisbp__M1605-Sox15 3 0.670626 16398.8 1 6 CACCTG ATTCATCTTT + +4 cisbp__M1943 3 0.670626 16398.8 1 6 CACCTG CGGTGCCCCC + +4 homer__NYTAATCCYB_Otx2-Gsc-Ptx1-oc 4 0.670626 16398.8 1 6 CACCTG GTTAATCCCT + +4 jaspar__MA0123.1 3 0.670626 16398.8 1 6 CACCTG CGGTGCCCCC + +4 predrem__nrMotif2355 4 0.670626 16398.8 1 6 CACCTG GGGGGAGCTG + +4 predrem__nrMotif823 3 0.670626 16398.8 1 6 CACCTG TGCCACATTT + +4 taipale__NEUROG2_DBD_RACATATGTY-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.670626 16398.8 1 6 CACCTG AACATATGTC + +4 taipale_tf_pairs__JUN_ATGACGTCAT_HT-Jra 2 0.670626 16398.8 1 6 CACCTG ATGACGTCAT + +4 transfac_public__M00260-CG7786-gt-hng1-Pdp1-REPTOR-BP-vri 2 0.670626 16398.8 1 6 CACCTG GTTACGTAAT + +4 yetfasco__YHR056C_2164 2 0.670626 16398.8 1 6 CACCTG TTGCCCGCGT + +4 cisbp__M0289 2 0.670626 16398.8 1 6 CACCTG ATCGCGTCAT - +4 cisbp__M0388 4 0.670626 16398.8 1 6 CACCTG GGAAGCCCTA - +4 cisbp__M0406 3 0.670626 16398.8 1 6 CACCTG AGCCCCCCAA - +4 cisbp__M0608-trx 1 0.670626 16398.8 1 6 CACCTG TTACGCCCCC - +4 cisbp__M0633-dmrt11E 3 0.670626 16398.8 1 6 CACCTG TAATACATTA - +4 cisbp__M1043-Hmx 0 0.670626 16398.8 1 6 CACCTG AACCAATTAA - +4 cisbp__M1248 4 0.670626 16398.8 1 6 CACCTG ATGGAATCTT - +4 cisbp__M2388-SREBP 2 0.670626 16398.8 1 6 CACCTG ATCACCCCAT - +4 cisbp__M5032-Hr3 1 0.670626 16398.8 1 6 CACCTG TGACCCAATT - +4 fantom__motif137_MAACAGAAGY 1 0.670626 16398.8 1 6 CACCTG GCTTCTGTTT - +4 fantom__motif147_ATATCCAGTG 0 0.670626 16398.8 1 6 CACCTG CACTGGATAT - +4 flyfactorsurvey__h_NAR_FBgn0001168-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-Hey-Sidpn-dpn-h 2 0.670626 16398.8 1 6 CACCTG GGCACGTGCC - +4 flyfactorsurvey__tll_NAR_FBgn0003720-dsf-tll 3 0.670626 16398.8 1 6 CACCTG TTTGACTTTT - +4 hocomoco__NKX25_MOUSE.H11MO.0.A-scro-vnd 1 0.670626 16398.8 1 6 CACCTG CCACTCCAGA - +4 neph__UW.Motif.0178 0 0.670626 16398.8 1 6 CACCTG TAATTTTATT - +4 predrem__nrMotif1099 4 0.670626 16398.8 1 6 CACCTG CTGGGAAGTG - +4 predrem__nrMotif534 0 0.670626 16398.8 1 6 CACCTG TTGCTTCTTC - +4 predrem__nrMotif888 0 0.670626 16398.8 1 6 CACCTG CACTCTGTCC - +4 predrem__nrMotif950 4 0.670626 16398.8 1 6 CACCTG TGGCTCTCTG - +4 scertf__foat.XBP1 0 0.670626 16398.8 1 6 CACCTG ATCCTCGAGC - +4 transfac_pro__M00931-btd-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 0 0.670626 16398.8 1 6 CACCTG GCCCCGCCCC - +4 transfac_pro__M02076 3 0.670626 16398.8 1 6 CACCTG CACTTCCTCT - +4 yetfasco__YDL056W_2138 3 0.670626 16398.8 1 6 CACCTG GGACGCGTAA - +4 cisbp__M0099 -1 0.670626 16398.8 1 5 CACCTG TTATGCATAA + +4 predrem__nrMotif1858 5 0.670626 16398.8 1 5 CACCTG AAAACCATCA + +4 predrem__nrMotif2373 5 0.670626 16398.8 1 5 CACCTG CAGTGCAGCC + +4 predrem__nrMotif984 5 0.670626 16398.8 1 5 CACCTG AAAAAGACAA + +4 transfac_pro__M01970 -1 0.670626 16398.8 1 5 CACCTG GCCTCGAGGC + +4 cisbp__M0750-bin-bs-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp1-slp2 5 0.670626 16398.8 1 5 CACCTG TTGTTTACAT - +4 hocomoco__HXB1_HUMAN.H11MO.0.D-lab 5 0.670626 16398.8 1 5 CACCTG CCATCCATCA - +4 predrem__nrMotif924 5 0.670626 16398.8 1 5 CACCTG CTTGGCCCCA - +4 taipale__EN2_full_NNYAATTANN-B-H2-bsh-C15-CG11085-CG18599-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 6 0.670626 16398.8 1 4 CACCTG CCCAATTAGC + +4 transfac_public__M00054-CG12018-Dif-dl-Rel-shn 6 0.670626 16398.8 1 4 CACCTG GGGAATTTCC + +4 cisbp__M0386-opa -2 0.670626 16398.8 1 4 CACCTG CCCGCTGTGA - +4 cisbp__M5395-B-H2-bsh-C15-CG11085-CG18599-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 6 0.670626 16398.8 1 4 CACCTG CCCAATTAGC - +4 stark__CTATNNNAAG -2 0.670626 16398.8 1 4 CACCTG CTTAAAATAG - +4 cisbp__M6228-Jra-kay -3 0.670626 16398.8 1 3 CACCTG CTGACTCATC + +4 cisbp__M1007-abd-A-Abd-B-cad-Ubx 2 0.67065 16399.4 1 6 CACCTG TTTATGACC + +4 predrem__nrMotif1948 3 0.67065 16399.4 1 6 CACCTG TCACATCAG + +4 predrem__nrMotif2161 1 0.67065 16399.4 1 6 CACCTG AGGCCTTCA + +4 predrem__nrMotif575 2 0.67065 16399.4 1 6 CACCTG CAGTCCTTT + +4 cisbp__M0120 2 0.67065 16399.4 1 6 CACCTG TTTATTCGT - +4 cisbp__M1156-Hmx 2 0.67065 16399.4 1 6 CACCTG AGCAATTAA - +4 cisbp__M1579-pan 0 0.67065 16399.4 1 6 CACCTG AACATCAAA - +4 cisbp__M4682-cnc 1 0.67065 16399.4 1 6 CACCTG TCAGCATTT - +4 predrem__nrMotif1336 1 0.67065 16399.4 1 6 CACCTG AGACCAGAG - +4 predrem__nrMotif1381 3 0.67065 16399.4 1 6 CACCTG TGGCAGCTT - +4 predrem__nrMotif1562 1 0.67065 16399.4 1 6 CACCTG TTATCTGCA - +4 predrem__nrMotif1474 -1 0.67065 16399.4 1 5 CACCTG CCCTCATCC + +4 predrem__nrMotif2144 4 0.67065 16399.4 1 5 CACCTG TGTTTATCA + +4 predrem__nrMotif219 -1 0.67065 16399.4 1 5 CACCTG ACATTCCCA + +4 yetfasco__YLR278C_2112 4 0.67065 16399.4 1 5 CACCTG CGGACTCCG + +4 cisbp__M0442 -1 0.67065 16399.4 1 5 CACCTG CACTGCATT - +4 transfac_pro__M01783-btd-Nf-YA-Spps 4 0.67065 16399.4 1 5 CACCTG GTCCCGCCC - +4 transfac_pro__M04732-egg-mor-Six4 -1 0.67065 16399.4 1 5 CACCTG ACAATTCCC - +4 predrem__nrMotif1941 -2 0.67065 16399.4 1 4 CACCTG CTTGTTCCT + +4 predrem__nrMotif1981 -2 0.67065 16399.4 1 4 CACCTG ACTGTCAAA + +4 cisbp__M0540 5 0.67065 16399.4 1 4 CACCTG GGATTTACA - +4 fantom__motif146_AGACGAAGA -2 0.67065 16399.4 1 4 CACCTG TCTTCGTCT - +4 elemento__TCCCAGCAC 6 0.67065 16399.4 1 3 CACCTG TCCCAGCAC + +4 predrem__nrMotif2569 6 0.67065 16399.4 1 3 CACCTG TGCAGAAAC + +4 transfac_pro__M04804 -3 0.67065 16399.4 1 3 CACCTG CTGTCACTC + +4 cisbp__M1256 1 0.671103 16410.5 1 6 CACCTG GTTTCTTCTATT + +4 cisbp__M2255-kni-knrl 6 0.671103 16410.5 1 6 CACCTG GTGCTCTAGTTT + +4 cisbp__M5464-foxo 6 0.671103 16410.5 1 6 CACCTG TTTCCCCACACG + +4 flyfactorsurvey__Atf6_SANGER_5_FBgn0033010-Atf6-CrebA-Xbp1 3 0.671103 16410.5 1 6 CACCTG GCTGACGTGGCA + +4 flyfactorsurvey__Eip93F_SANGER_10_FBgn0013948-Eip93F 1 0.671103 16410.5 1 6 CACCTG ACTCCCGAAAAT + +4 flyfactorsurvey__br-PE_SANGER_5_FBgn0000210-br 3 0.671103 16410.5 1 6 CACCTG GTTCGTCTAACG + +4 hocomoco__CEBPE_HUMAN.H11MO.0.A 6 0.671103 16410.5 1 6 CACCTG TTGCGCAATCTT + +4 hocomoco__EVX2_MOUSE.H11MO.0.A-Abd-B-cad-eve 6 0.671103 16410.5 1 6 CACCTG TTTTATTGCTTT + +4 hocomoco__STAT3_MOUSE.H11MO.0.A-Stat92E 0 0.671103 16410.5 1 6 CACCTG CACTTCCCGGAA + +4 stark__YYWVNYYWDNYS-Dlip3 3 0.671103 16410.5 1 6 CACCTG CCAGACCATACC + +4 taipale__Creb5_DBD_NATGACGTCAYN-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.671103 16410.5 1 6 CACCTG AATGACGTCACC + +4 taipale_tf_pairs__FLI1_FOXI1_GAAAACCGAAAN_CAP_repr 3 0.671103 16410.5 1 6 CACCTG GAAAACCGAAAC + +4 transfac_pro__M06510 6 0.671103 16410.5 1 6 CACCTG CGGAACTACCGC + +4 transfac_pro__M09533-Atf6-CrebA-Xbp1 2 0.671103 16410.5 1 6 CACCTG GCCACGTCAGCA + +4 cisbp__M3088-Atf6-CrebB 3 0.671103 16410.5 1 6 CACCTG AGTTACGTCACC - +4 cisbp__M6172 6 0.671103 16410.5 1 6 CACCTG TTGCGCAATCTT - +4 flyfactorsurvey__kni_NAR_FBgn0001320-kni-knrl 6 0.671103 16410.5 1 6 CACCTG GTGCTCTAGTTT - +4 hocomoco__EMX2_HUMAN.H11MO.0.D-CG9876-CG34367-E5-Lim3-OdsH-Vsx1-Vsx2-ap-ems-en-inv-otp-ro-unpg 2 0.671103 16410.5 1 6 CACCTG ATTAGCTAATTA - +4 neph__UW.Motif.0121 2 0.671103 16410.5 1 6 CACCTG TGTATTTTCCCA - +4 taipale_cyt_meth__FOXC2_NWANRTAAACAN_eDBD-croc-fd59A-FoxL1-foxo-slp2 5 0.671103 16410.5 1 6 CACCTG TTGTTTACGTTA - +4 taipale_cyt_meth__ZBTB26_NMTCYAGAAAAN_FL_meth_repr 2 0.671103 16410.5 1 6 CACCTG TTTTTCTAGATC - +4 transfac_pro__M05574 2 0.671103 16410.5 1 6 CACCTG GACGCCTTCCCT - +4 transfac_pro__M05729 3 0.671103 16410.5 1 6 CACCTG TCTGACATGGGG - +4 transfac_pro__M05733-Meics 0 0.671103 16410.5 1 6 CACCTG TCCCTCGCCCAG - +4 transfac_pro__M05885 6 0.671103 16410.5 1 6 CACCTG TCTGCCCGCCAG - +4 transfac_pro__M06051 2 0.671103 16410.5 1 6 CACCTG TCCACCCCCCCG - +4 transfac_pro__M06217 2 0.671103 16410.5 1 6 CACCTG TATACTTAAACA - +4 transfac_pro__M06237 6 0.671103 16410.5 1 6 CACCTG GATTTTTGCCCC - +4 transfac_pro__M06250 4 0.671103 16410.5 1 6 CACCTG GCAACACCCCGG - +4 transfac_pro__M06423 6 0.671103 16410.5 1 6 CACCTG GCAGCCCACCCC - +4 transfac_pro__M06531 5 0.671103 16410.5 1 6 CACCTG GGACAAACACGA - +4 transfac_pro__M06738-CG2120 2 0.671103 16410.5 1 6 CACCTG GTAATCTGCCAG - +4 transfac_public__M00179-Atf6-CrebB 3 0.671103 16410.5 1 6 CACCTG AGTTACGTCACC - +4 transfac_public__M00229 5 0.671103 16410.5 1 6 CACCTG TGGATGACATTA - +4 transfac_pro__M07049 7 0.671103 16410.5 1 5 CACCTG GGTTATAAAGCT + +4 swissregulon__hs__FOX_I1_J2_.p2 7 0.671103 16410.5 1 5 CACCTG AAATAAACAACC - +4 taipale_cyt_meth__ZNF385D_NCGTCGCGACGN_eDBD_repr 7 0.671103 16410.5 1 5 CACCTG CCGTCGCGACGG - +4 taipale_cyt_meth__ATF6B_TGCCACGTCAYN_eDBD-Atf6-CrebA-Xbp1 8 0.671103 16410.5 1 4 CACCTG TGCCACGTCACC + +4 transfac_pro__M05032 -2 0.671103 16410.5 1 4 CACCTG CCTTTCGTGTTT + +4 transfac_pro__M05802 -2 0.671103 16410.5 1 4 CACCTG CCTTGAATAATA + +4 transfac_pro__M06438-CG2120 8 0.671103 16410.5 1 4 CACCTG GACTGGAAAACC + +4 transfac_pro__M05653 8 0.671103 16410.5 1 4 CACCTG GGGGATGCCACT - +4 transfac_pro__M05716 8 0.671103 16410.5 1 4 CACCTG GGGGATGCCACT - +4 transfac_pro__M05753 8 0.671103 16410.5 1 4 CACCTG TTTCTTGACACT - +4 jaspar__MA0217.1-caup 1 0.671273 16414.6 1 4 CACCTG TAACA + +4 swissregulon__sacCer__CAT8 -2 0.671273 16414.6 1 4 CACCTG CCGGA + +4 cisbp__M4636-CG10431-pho-phol 1 0.671634 16423.5 1 6 CACCTG CTGCCCTCAACAAAGATGGCG + +4 cisbp__M6135-bi-egg-mor-Six4-Stat92E 4 0.671634 16423.5 1 6 CACCTG AAACTACAATTCCCAGAATGC + +4 taipale_tf_pairs__TFAP4_DLX3_NNCAGCTGNNNNNNNTAATTN_HT-crp 2 0.671634 16423.5 1 6 CACCTG ATCAGCTGATCGGCGTAATTA + +4 tfdimers__MD00307 6 0.671634 16423.5 1 6 CACCTG AAACCTCAGCAGCTGAGGTTT + +4 transfac_pro__M05267 15 0.671634 16423.5 1 6 CACCTG GGGGGGCGACAGGGCCACCCA - +4 cisbp__M4527-bi-egg-Hcf-mor-Six4 -1 0.671634 16423.5 1 5 CACCTG GCCTGCTGGGAGTTGTAGTCC - +4 transfac_pro__M05078 4 0.671978 16431.9 1 6 CACCTG ATAATACCAAAAGAATTCGCGTTTG + +4 taipale_tf_pairs__RFX3_ETV7_NNNMGGAANNNNNTCCNNNRCAACN_CAP_repr-aop-Rfx 17 0.671978 16431.9 1 6 CACCTG CGTTGCTAAGGAAGTACTTCCGGGT - +4 tfdimers__MD00472-nej 13 0.671978 16431.9 1 6 CACCTG ATTTTGGTTTAACTCCCTGCCTATC - +4 cisbp__M3059-Awh-CG18599-E5-ems-en-eve-inv-lab-Lim3-unpg-Vsx1-Vsx2 7 0.672203 16437.4 1 6 CACCTG GGCTAATTAGCGCA + +4 cisbp__M4992-CG7786-gt-hng1-Pdp1-vri 6 0.672203 16437.4 1 6 CACCTG CGGTGTTACGTAAT + +4 hocomoco__HXB3_HUMAN.H11MO.0.D-Antp-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Dr-E5-HGTX-Hmx-Lim1-Lim3-Lmx1a-Pph13-Rx-Scr-Vsx1-abd-A-ap-ems-en-eve-exex-ind-lab-lbl-otp-pb-repo-ro-slou-unpg-zen2 5 0.672203 16437.4 1 6 CACCTG TTAATTAGTTTTTA + +4 jaspar__MA0237.2-pan 4 0.672203 16437.4 1 6 CACCTG TCGGCTCCTTTGAT + +4 swissregulon__hs__MTF1.p2-MTF-1 4 0.672203 16437.4 1 6 CACCTG TCTGCACCCGGCCC + +4 taipale_tf_pairs__FOXO1_HOXB13_GWMAACAYMRTAAA_CAP-foxo 3 0.672203 16437.4 1 6 CACCTG GTAAACATCGTAAA + +4 taipale_tf_pairs__MYBL1_ELF1_NMCCGGAACCGTTR_CAP_repr-Eip74EF-Myb 0 0.672203 16437.4 1 6 CACCTG AACCGGAACCGTTA + +4 transfac_pro__M07866-Chrac-14-Myb 4 0.672203 16437.4 1 6 CACCTG AAATGACCGTTACA + +4 transfac_public__M00437-Awh-CG18599-E5-ems-en-eve-inv-lab-Lim3-unpg-Vsx1-Vsx2 7 0.672203 16437.4 1 6 CACCTG GGCTAATTAGCGAA + +4 yetfasco__YPL133C_757 0 0.672203 16437.4 1 6 CACCTG ACCCTTTAAGCCGA + +4 c2h2_zfs__M3928-Klf15-Spps-btd 7 0.672203 16437.4 1 6 CACCTG GATACGCCCCCTAA - +4 cisbp__M4105-croc-fd59A-fkh-foxo 8 0.672203 16437.4 1 6 CACCTG TTTTTGTTTACTCA - +4 flyfactorsurvey__Bteb2_SOLEXA_2.5_FBgn0025679-Klf15-Spps-btd 7 0.672203 16437.4 1 6 CACCTG GATACGCCCCCTAA - +4 hocomoco__ELF1_MOUSE.H11MO.0.A-Eip74EF-Hcf-Hr78-RpII215-Sin3A-aop 1 0.672203 16437.4 1 6 CACCTG CCACTTCCGGGTTC - +4 hocomoco__ERG_MOUSE.H11MO.0.A-Atac3-Dif-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-aop-bs-dl-pnt 5 0.672203 16437.4 1 6 CACCTG CCCACTTCCGGTCC - +4 hocomoco__NFE2_MOUSE.H11MO.0.A-Jra-cnc-kay-maf-S 2 0.672203 16437.4 1 6 CACCTG AACTGCTGAGTCAT - +4 swissregulon__hs__TLX1..3_NFIC_dimer_.p2-C15-NfI 5 0.672203 16437.4 1 6 CACCTG TTGGCTTGCTGCCA - +4 transfac_pro__M09458-tll 6 0.672203 16437.4 1 6 CACCTG GGCGTTGACTTTTT - +4 transfac_public__M00255-btd-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 6 0.672203 16437.4 1 6 CACCTG CAGCCCCGCCCCCT - +4 taipale__CREB3L1_full_NTGCCACGTCANCA-Atf6-CrebA-CrebB-Xbp1 9 0.672203 16437.4 1 5 CACCTG ATGCCACGTCATCA + +4 taipale_cyt_meth__ZNF75A_NGCTTTTCCCACMN_eDBD_meth 9 0.672203 16437.4 1 5 CACCTG CGCTTTTCCCACAC + +4 transfac_pro__M09478 -1 0.672203 16437.4 1 5 CACCTG ACCGGCGTTGACTT + +4 cisbp__M5328-Atf6-CrebA-CrebB-Xbp1 9 0.672203 16437.4 1 5 CACCTG ATGCCACGTCATCA - +4 taipale_cyt_meth__FERD3L_GYNNCATATGNNAC_FL-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 11 0.672203 16437.4 1 3 CACCTG GCACCATATGTTAC + +4 taipale_cyt_meth__FERD3L_GYNNCATATGNNAC_FL_meth-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 11 0.672203 16437.4 1 3 CACCTG GCACCATATGTTAC + +4 tfdimers__MD00005-pan 6 0.673185 16461.4 1 6 CACCTG AAAAACCACATCAAAGAAAAAA + +4 tfdimers__MD00051-Stat92E 2 0.673185 16461.4 1 6 CACCTG TTCCACTTCCTCTTCCTCTTTC + +4 cisbp__M3553-Mef2 15 0.673185 16461.4 1 6 CACCTG AGTTTCTATTTTTAGTAACAGT - +4 transfac_public__M00233-Mef2 15 0.673185 16461.4 1 6 CACCTG AGTTTCTATTTTTAGTAACAGT - +4 cisbp__M4195 18 0.673283 16463.8 1 6 CACCTG TCGGCGCCTTCTCGCCCGCACCGA + +4 tfdimers__MD00392-E2f1-scro 14 0.673283 16463.8 1 6 CACCTG ATAAACACTCAGGAAATGTTAAAT + +4 tfdimers__MD00429 11 0.673283 16463.8 1 6 CACCTG AAAAAAATTAATCCCTTTAATTTT - +4 tfdimers__MD00463-CG7786-gt-Pdp1 16 0.673283 16463.8 1 6 CACCTG TTAATTTCCCTTTTTGCAAATTTA - +4 yetfasco__YAL051W_2060 18 0.673283 16463.8 1 6 CACCTG TCGGCGCCTTCTCGCCCGCACCGA - +4 neph__UW.Motif.0488 1 0.673316 16464.6 1 6 CACCTG TTTCTTATGCCAA + +4 predrem__nrMotif657 7 0.673316 16464.6 1 6 CACCTG CCGCGCGCCCCGC + +4 swissregulon__sacCer__GZF3-GATAd-GATAe-grn-pnr-srp 1 0.673316 16464.6 1 6 CACCTG ATCGCTTATCAGC + +4 transfac_pro__M01888-Smox 7 0.673316 16464.6 1 6 CACCTG GGACAGACAGACT + +4 transfac_pro__M03837-nub-pdm2-SoxN-vvl 7 0.673316 16464.6 1 6 CACCTG TGATATGCAAATT + +4 cisbp__M4570-brm-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 6 0.673316 16464.6 1 6 CACCTG ATGACTCATCCTC - +4 fantom__motif133_TWTAWAGTWGRAG 3 0.673316 16464.6 1 6 CACCTG CTCCTACTTTATA - +4 hocomoco__ELK4_MOUSE.H11MO.0.B-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-RpII215-Sin3A-Taf1-aop-bs-pnt 4 0.673316 16464.6 1 6 CACCTG CCGCTTCCGGCCC - +4 transfac_pro__M09235-Hsf 5 0.673316 16464.6 1 6 CACCTG TCTAGAAGCTTCT - +4 transfac_pro__M04692-bi-egg-Hcf-mor-Six4 -1 0.673316 16464.6 1 5 CACCTG AACTACAACTCCC + +4 neph__UW.Motif.0616 9 0.673316 16464.6 1 4 CACCTG TTTCATTTTCACT - +4 transfac_pro__M01087-slbo 1 0.673708 16474.2 1 6 CACCTG AGATCTGTGTGATCATTTTTGCG + +4 transfac_pro__M04661-CHES-1-like-jumu 14 0.673708 16474.2 1 6 CACCTG AATCGAAACGACGCTATAATGCG + +4 taipale_tf_pairs__HOXB2_ETV7_TAATKNNNNGNNNNNNCTTCCNN_CAP_repr-aop-pb 10 0.673708 16474.2 1 6 CACCTG GCGGAAGTACTTCCGGGTCATTA - +4 tfdimers__MD00009 9 0.673708 16474.2 1 6 CACCTG CAAAACCACATCCTGTCCTCCTC - +4 tfdimers__MD00303-oc 12 0.673708 16474.2 1 6 CACCTG TTTTTATTTAATCTCCTTTTTTT - +4 factorbook__UA11-egg 8 0.677257 16561 1 6 CACCTG GGCTTTCCCACATTCATT + +4 taipale_cyt_meth__TFCP2_AWCCGGWTNNAWCCGGWT_FL_meth-gem 0 0.677257 16561 1 6 CACCTG AACCGGTTTAAACCGGTT + +4 taipale_cyt_meth__ZSCAN5A_NYGTCCCYCCCCAAANMN_eDBD_meth 3 0.677257 16561 1 6 CACCTG CTGTCCCCCCCCAAATCC + +4 taipale_tf_pairs__HOXB2_ELF1_TAATKRNNNNNGGAAGTN_CAP-Eip74EF-pb 3 0.677257 16561 1 6 CACCTG CACTTCCGCTTGCCATTA - +4 cisbp__M6347-Dr 0 0.677342 16563.1 1 6 CACCTG TAATTGT + +4 hocomoco__MSX2_HUMAN.H11MO.0.D-Dr 0 0.677342 16563.1 1 6 CACCTG TAATTGT + +4 predrem__nrMotif1333 0 0.677342 16563.1 1 6 CACCTG CCCCACA + +4 predrem__nrMotif56 0 0.677342 16563.1 1 6 CACCTG CCCGTGG - +4 transfac_pro__M01131-Sox100B 0 0.677342 16563.1 1 6 CACCTG GACAAAG - +4 transfac_pro__M04889-Chd1 0 0.677342 16563.1 1 6 CACCTG CGCCTTT - +4 predrem__nrMotif1193 2 0.677342 16563.1 1 5 CACCTG CCAACAT - +4 transfac_pro__M05665-btd-Sp1-Spps 2 0.677342 16563.1 1 5 CACCTG CCGCCCT - +4 predrem__nrMotif2165 -2 0.677342 16563.1 1 4 CACCTG GCTGTGG + +4 transfac_pro__M04897-kay -2 0.677342 16563.1 1 4 CACCTG CATGAGT - +4 cisbp__M5448-bs-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxP-slp2 4 0.677342 16563.1 1 3 CACCTG TGTTTAC - +4 tfdimers__MD00242 18 0.677562 16568.4 1 6 CACCTG CCCCCCCCCCCCACCCCCCACCCCCCCCC + +4 tfdimers__MD00379-pho-phol 16 0.677562 16568.4 1 6 CACCTG CCCCAGCCGCCAGGTGCAGCCGGCACCGG + +4 transfac_pro__M01075 15 0.677562 16568.4 1 6 CACCTG GAACAGATCAAACTTTAGCTTCAAAACAA - +4 cisbp__M0547 1 0.678911 16601.4 1 6 CACCTG GTACAGTA + +4 cisbp__M0971-gsb-gsb-n-prd 2 0.678911 16601.4 1 6 CACCTG ATAATTGG + +4 cisbp__M5699-bcd-Gsc-oc 2 0.678911 16601.4 1 6 CACCTG TTAATCCG + +4 jaspar__MA0438.1 2 0.678911 16601.4 1 6 CACCTG ATTTCCGT + +4 predrem__nrMotif2419 0 0.678911 16601.4 1 6 CACCTG TAGCTAAG + +4 predrem__nrMotif399 2 0.678911 16601.4 1 6 CACCTG GTCTCTTG + +4 taipale__OTX1_DBD_NTAATCCN_repr-bcd-Gsc-oc 2 0.678911 16601.4 1 6 CACCTG TTAATCCG + +4 taipale_cyt_meth__BARHL1_NTAAACGN_eDBD_repr-B-H1-B-H2 2 0.678911 16601.4 1 6 CACCTG CTAAACGG + +4 transfac_public__M00083 1 0.678911 16601.4 1 6 CACCTG TCCCCACT - +4 cisbp__M0348 3 0.678911 16601.4 1 5 CACCTG TATTACGT + +4 cisbp__M1895-sv -1 0.678911 16601.4 1 5 CACCTG GCGTGACT + +4 flyfactorsurvey__CG5953_SANGER_5_FBgn0032587-CG5953 3 0.678911 16601.4 1 5 CACCTG ACAAACAT + +4 hdpi__SOX14-D-Sox21a-Sox21b -1 0.678911 16601.4 1 5 CACCTG AACTGAAA + +4 cisbp__M0565 -1 0.678911 16601.4 1 5 CACCTG TCCCGCTC - +4 cisbp__M4872-CG5953 3 0.678911 16601.4 1 5 CACCTG ACAAACAT - +4 jaspar__MA0067.1-sv -1 0.678911 16601.4 1 5 CACCTG CCGTGACT - +4 predrem__nrMotif765 3 0.678911 16601.4 1 5 CACCTG TCAGGCCA - +4 scertf__badis.YNR063W -1 0.678911 16601.4 1 5 CACCTG ATCTCCGA - +4 stark__GCGCATGH -1 0.678911 16601.4 1 5 CACCTG TCATGCGC - +4 transfac_pro__M04810-Usf 3 0.678911 16601.4 1 5 CACCTG CGTGACTT - +4 transfac_pro__M09588 3 0.678911 16601.4 1 5 CACCTG TGACATCT - +4 predrem__nrMotif2237 4 0.678911 16601.4 1 4 CACCTG AGCCAAGC + +4 predrem__nrMotif839 4 0.678911 16601.4 1 4 CACCTG ATAACACA + +4 predrem__nrMotif2274 -2 0.678911 16601.4 1 4 CACCTG CCAGCGAG - +4 transfac_pro__M07399-HGTX 5 0.678911 16601.4 1 3 CACCTG TTAATTAC + +4 transfac_pro__M07816-Antp-Dfd-pb-Scr 5 0.678911 16601.4 1 3 CACCTG GTCATTAC + +4 cisbp__M0440 5 0.678911 16601.4 1 3 CACCTG GTCTACAC - +4 hdpi__INSM1-nerfin-1-nerfin-2 5 0.678911 16601.4 1 3 CACCTG GAACACAC - +4 hocomoco__SOX8_HUMAN.H11MO.0.D-Sox14-Sox15-Sox100B 0 0.678918 16601.6 1 6 CACCTG TCACTGCAATTGATGC + +4 transfac_pro__M00317 0 0.678918 16601.6 1 6 CACCTG CGCGTGTGTTCTCATC + +4 transfac_pro__M07054 8 0.678918 16601.6 1 6 CACCTG CCGAGACATGCCCGGG + +4 transfac_public__M00155-EcR-svp 2 0.678918 16601.6 1 6 CACCTG TGAACCCTTGACCCCT + +4 transfac_public__M00293 10 0.678918 16601.6 1 6 CACCTG TATACATAAACAAGAT + +4 taipale_tf_pairs__HOXD12_ETV4_RSCGGAAGTAATAAAN_CAP-Ets96B 6 0.678918 16601.6 1 6 CACCTG TTTTATTACTTCCGGT - +4 transfac_pro__M00648 4 0.678918 16601.6 1 6 CACCTG AGGCAACTTCCCTCTA - +4 scertf__morozov.PUT3 11 0.678918 16601.6 1 5 CACCTG CGGGAAGCCAATCCCG + +4 taipale_cyt_meth__RFX3_NGTTGCCATGGCAACN_eDBD-CG5846-CG9727-Max-Rfx-SREBP 11 0.678918 16601.6 1 5 CACCTG CGTTGCCATGGCAACG + +4 cisbp__M5779-CG5846-CG9727-Max-Rfx-SREBP 11 0.678918 16601.6 1 5 CACCTG CGTTGCCATGGCAACG - +4 yetfasco__YKL015W_2065 11 0.678918 16601.6 1 5 CACCTG CGGGAAGCCAATCCCG - +4 transfac_pro__M05572 12 0.678918 16601.6 1 4 CACCTG GGAGGCGGGCTATACA - +4 tfdimers__MD00385-nub-pdm2 13 0.68008 16630 1 6 CACCTG TGGTTGTGATTTGCATATGCAAATCACCACCA + +4 swissregulon__hs__AHR_ARNT_ARNT2.p2-ss-tgo 0 0.68081 16647.8 1 6 CACCTG TGCGTG + +4 transfac_pro__M01162-al-CG32532-CG34367-Dr-en-inv-lms-OdsH-repo-unc-4-unpg 0 0.68081 16647.8 1 6 CACCTG TAATTG + +4 transfac_pro__M01188 0 0.68081 16647.8 1 6 CACCTG TTGCTT + +4 fantom__motif9_ANGGCT -1 0.68081 16647.8 1 5 CACCTG AGCCAT - +4 transfac_pro__M05187 1 0.68081 16647.8 1 5 CACCTG GTGCCC - +4 flyfactorsurvey__Ara_SOLEXA_FBgn0015904-ara-mirr 2 0.68081 16647.8 1 4 CACCTG ATAACA + +4 hdpi__TGIF2LX-achi-vis 2 0.68081 16647.8 1 4 CACCTG GACAGC + +4 transfac_pro__M05125 2 0.68081 16647.8 1 4 CACCTG CCGCCC + +4 transfac_pro__M08997-GATAd-GATAe-grn-HDAC1-pnr-srp 2 0.68081 16647.8 1 4 CACCTG CTTATC + +4 cisbp__M4744-ara-mirr 2 0.68081 16647.8 1 4 CACCTG ATAACA - +4 hdpi__PKNOX2 -2 0.68081 16647.8 1 4 CACCTG GCTGTC - +4 scertf__badis.FZF1-CG3065-hkb -3 0.68081 16647.8 1 3 CACCTG CTATCA + +4 hdpi__RARG-EcR -3 0.68081 16647.8 1 3 CACCTG CTTCCG - +4 bergman__bcd-bcd-oc 0 0.681365 16661.4 1 6 CACCTG CCCCTAATCCC + +4 cisbp__M1541-Bgb-RunxA-RunxB-lz-run 2 0.681365 16661.4 1 6 CACCTG ATAACCGCAAT + +4 fantom__motif128_NNGNATRCGWN 5 0.681365 16661.4 1 6 CACCTG CCGAATGCGTG + +4 flyfactorsurvey__Ci_SANGER_5_FBgn0004859-ci-lmd-opa-sug 4 0.681365 16661.4 1 6 CACCTG AGACCACCCAC + +4 predrem__nrMotif2193 0 0.681365 16661.4 1 6 CACCTG TTTCTCTGCTA + +4 predrem__nrMotif251 4 0.681365 16661.4 1 6 CACCTG CCCCGCCCTCC + +4 predrem__nrMotif660 0 0.681365 16661.4 1 6 CACCTG TTCCATTTTTA + +4 transfac_pro__M01035-pho-phol 2 0.681365 16661.4 1 6 CACCTG GCCGCCATTTT + +4 transfac_pro__M05278 1 0.681365 16661.4 1 6 CACCTG GAACCTTGTAC + +4 cisbp__M3945-SREBP 3 0.681365 16661.4 1 6 CACCTG GATCACCCCAC - +4 cisbp__M4538-Dp-E2f1-E2f2 5 0.681365 16661.4 1 6 CACCTG TTTCCCGCCCT - +4 cisbp__M5853-btd-cbt-CG3065-CG42741-Clp-dar1-hkb-kay-Klf15-klu-luna-Nf-YB-sd-Sp1-Spps-sr-Stat92E 4 0.681365 16661.4 1 6 CACCTG ACCCCGCCCCC - +4 flyfactorsurvey__br_SOLEXA_10_FBgn0000210-br 0 0.681365 16661.4 1 6 CACCTG TTTCTAATCAC - +4 transfac_pro__M03581-Tbp 5 0.681365 16661.4 1 6 CACCTG TTTTATACCCC - +4 scertf__pachkov.YAP1 -1 0.681365 16661.4 1 5 CACCTG TGCTTACTAAT + +4 taipale_cyt_meth__SOX12_ACCGAACAATN_eDBD-Sox14 -1 0.681365 16661.4 1 5 CACCTG ACCGAACAATG + +4 cisbp__M2189 6 0.681365 16661.4 1 5 CACCTG CGGCGCTACCA - +4 hocomoco__JUND_MOUSE.H11MO.0.A-CoRest-Jra-Myc-Stat92E-brm-cnc-kay-mor-nej-pan 6 0.681365 16661.4 1 5 CACCTG ATGACTCACCC - +4 hocomoco__KLF13_HUMAN.H11MO.0.D-CG3065-Klf15-Sp1-Spps-btd-hkb 6 0.681365 16661.4 1 5 CACCTG CACGCCCCCCT - +4 hocomoco__LBX2_HUMAN.H11MO.0.D-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Dll-E5-OdsH-Pph13-Rx-Ubx-Vsx1-al-ap-dve-ems-en-eve-ey-ind-inv-lbe-lbl-lms-otp-pb-pdm3-repo-ro-slou-toy-unc-4-unpg-zfh2 -1 0.681365 16661.4 1 5 CACCTG ACCTAATTAAC - +4 jaspar__MA0384.1 6 0.681365 16661.4 1 5 CACCTG CGGCGCTACCA - +4 taipale_cyt_meth__FOSL1_NATGASTCAYN_FL_meth-bon-cnc-CoRest-Jra-kay-Mef2-mor-pan 7 0.681365 16661.4 1 4 CACCTG GATGAGTCATC + +4 cisbp__M2279-Jra-kay-mor-nej 7 0.681365 16661.4 1 4 CACCTG CATGAGTCACC - +4 hocomoco__PKNX1_HUMAN.H11MO.0.B -2 0.681365 16661.4 1 4 CACCTG CCTGTCAATCA - +4 jaspar__MA0477.1-Jra-kay-mor-nej 7 0.681365 16661.4 1 4 CACCTG CATGAGTCACC - +4 taipale_cyt_meth__CDX4_NGTCGTAAANN_FL_meth-cad 7 0.681365 16661.4 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M05181 7 0.681365 16661.4 1 4 CACCTG TAGCCGTTACT - +4 transfac_pro__M07046-arm-pan -2 0.681365 16661.4 1 4 CACCTG CCTTTGATGTT - +4 fantom__motif131_CTGCTTAAATA -3 0.681365 16661.4 1 3 CACCTG CTGCTTAAATA + +4 transfac_pro__M09437 8 0.681365 16661.4 1 3 CACCTG GTGGTCCCCAC + +4 taipale_tf_pairs__TEAD4_RFX5_RCATTCNNNNNNNNNNNNNNNNGCAACN_CAP_repr-sd 3 0.681728 16670.3 1 6 CACCTG ACATTCCAAATGCCCTATTTCGGCAACG + +4 tfdimers__MD00283-nub-pdm2 17 0.681728 16670.3 1 6 CACCTG ATTAAAATGCAAATATTTGCATTTTAAT + +4 tfdimers__MD00369-rn-sqz 14 0.681728 16670.3 1 6 CACCTG TTTTTTATTTTTTCCACTGTGTTTTAAA - +4 taipale_cyt_meth__BCL11B_GTGAACRNNNNNNYTACAC_eDBD_repr-CG9650 10 0.682607 16691.8 1 6 CACCTG GTGAACGCTGAAGCTACAC + +4 transfac_pro__M09277 0 0.682607 16691.8 1 6 CACCTG TAACAAATTTAACGGTAAC - +4 tfdimers__MD00344 13 0.685215 16755.6 1 6 CACCTG ATATAAAATAAACCACATCAAAAAAAA - +4 cisbp__M4602-aop-Eip74EF-Hr78 2 0.685222 16755.7 1 6 CACCTG AGTACTTCCGGGTCA + +4 hocomoco__HXC6_HUMAN.H11MO.0.D-Ubx-abd-A 9 0.685222 16755.7 1 6 CACCTG ATGATTTATTACTTT + +4 taipale_cyt_meth__LIN28B_CGCGANNNNNCAGCG_FL_meth-lin-28 7 0.685222 16755.7 1 6 CACCTG CGCGATATAACAGCG + +4 taipale_cyt_meth__ZNF771_NRCGCTAACCATTRN_eDBD-CG6654-CG7372 6 0.685222 16755.7 1 6 CACCTG TGCGCTAACCATTGT + +4 taipale_cyt_meth__ZNF771_NRCGCTAACCATTRN_eDBD_meth_repr-CG6654-CG7372 6 0.685222 16755.7 1 6 CACCTG TGCGCTAACCATTGC + +4 transfac_pro__M00717-sv 6 0.685222 16755.7 1 6 CACCTG CAGTTTTGCGTGAGT + +4 transfac_pro__M07232 9 0.685222 16755.7 1 6 CACCTG ACATGCCCAGACATG + +4 transfac_pro__M09053-Adf1-Taf1 1 0.685222 16755.7 1 6 CACCTG CCGCCGCCGCCGCCA + +4 cisbp__M5005-her 6 0.685222 16755.7 1 6 CACCTG TGCTCATAATTGCGT - +4 cisbp__M5612-cnc-maf-S-tj 0 0.685222 16755.7 1 6 CACCTG TCGCTGACTCAGCAT - +4 factorbook__STAT1-Stat92E-aop 3 0.685222 16755.7 1 6 CACCTG CATTTCCCGGAAATC - +4 hocomoco__GSX1_HUMAN.H11MO.0.D-CG34367-Dr-HGTX-ind-unpg 5 0.685222 16755.7 1 6 CACCTG ATTAAAAACTAATTA - +4 hocomoco__HSF1_MOUSE.H11MO.0.A-Hsf-pb 6 0.685222 16755.7 1 6 CACCTG TTCTAGAACTTTCTA - +4 hocomoco__ZN281_MOUSE.H11MO.0.A-CG7368-CTCF-CoRest-Spps-Spt20-btd-crol-ct-sr 9 0.685222 16755.7 1 6 CACCTG CCCCTCCCCCACCCC - +4 neph__UW.Motif.0567 6 0.685222 16755.7 1 6 CACCTG TTTTTTTTCCAAAGC - +4 taipale__NFIX_full_YTGGCNNNNTGCCAA-C15-Nf1-NfI 9 0.685222 16755.7 1 6 CACCTG TTGGCACCGTGCCAA - +4 transfac_pro__M07100-Hsf-pb 2 0.685222 16755.7 1 6 CACCTG AGAACCTTCTAGAAG - +4 transfac_pro__M08908 5 0.685222 16755.7 1 6 CACCTG TTTTTGCCCTGTTCT - +4 transfac_pro__M09404-Hsf-pb 7 0.685222 16755.7 1 6 CACCTG CTTCTAGAAGCTTCT - +4 transfac_public__M00081-ham 0 0.685222 16755.7 1 6 CACCTG TATCTTATCTTATCT - +4 neph__UW.Motif.0678 10 0.685222 16755.7 1 5 CACCTG TGGAGAATCTGGTCT - +4 transfac_pro__M05610-pho-phol -1 0.685222 16755.7 1 5 CACCTG AACTAAATGGTGATC - +4 hocomoco__FOXC2_HUMAN.H11MO.0.D-croc -2 0.685222 16755.7 1 4 CACCTG TCTGGCAAAACAAAC - +4 transfac_pro__M09045 11 0.685222 16755.7 1 4 CACCTG TCCACCGCCTCCACC - +4 tfdimers__MD00415-vvl 5 0.685927 16773 1 6 CACCTG ATTAATTCATGGTTAATCATTAAATTAAATT + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m6 5 0.686575 16788.8 1 6 CACCTG TGCTGGCTCTTCATGCCCAT + +4 dbcorrdb__CHD2__ENCSR000DZR_1__m1-Chd1-CoRest 11 0.686575 16788.8 1 6 CACCTG GGCTCTCGCGAGACTTGGCG + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m7-E(z) 9 0.686575 16788.8 1 6 CACCTG TATGTGTGCGTCCAGAAGCC + +4 dbcorrdb__GTF3C2__ENCSR000DNY_1__m2 12 0.686575 16788.8 1 6 CACCTG GGGCGCTCGGTTAACACGAG + +4 dbcorrdb__HSF1__ENCSR000EET_1__m4-Hsf 5 0.686575 16788.8 1 6 CACCTG GACGGCTCCCAAGCCTACCG + +4 dbcorrdb__JUND__ENCSR000BGK_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Snr1-Stat92E 11 0.686575 16788.8 1 6 CACCTG CAGGGATGAGTCATCCCGGC + +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m4 13 0.686575 16788.8 1 6 CACCTG GAGACTACTATGCCACAAGA + +4 dbcorrdb__MAFK__ENCSR000EEB_1__m1-cic-cnc-maf-S-tj 1 0.686575 16788.8 1 6 CACCTG TTTGCTGAGTCAGCAATTTT + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m5-Nelf-E 8 0.686575 16788.8 1 6 CACCTG GCGGACCGCAACAGCAACTC + +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m3-RpII215 10 0.686575 16788.8 1 6 CACCTG AAAACAGCGCAAGCTGCCCC + +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m10-RpII215 5 0.686575 16788.8 1 6 CACCTG GAGGAGAGCAGCGGATGATC + +4 dbcorrdb__POLR2A__ENCSR000BHI_1__m1-Brf-E2f1-ewg-E(z)-Myc-RpII215 1 0.686575 16788.8 1 6 CACCTG CCCGCTGCGCGGGCGCGGCG + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EHF_1__m7-RpII215 10 0.686575 16788.8 1 6 CACCTG CACAAAGCAGTACCGTACTT + +4 dbcorrdb__PPARGC1A__ENCSR000EEQ_1__m2-slbo-srl 10 0.686575 16788.8 1 6 CACCTG GGTATTGCGCAACCGGCGGG + +4 dbcorrdb__RCOR1__ENCSR000EFG_1__m1-CoRest-Jra-kay-mor-Myc-pan 12 0.686575 16788.8 1 6 CACCTG ACGGCTGACTCACCGCCGAC + +4 dbcorrdb__REST__ENCSR000BOT_1__m1-btd-CG10431-CTCF-pho-phol-Spps 2 0.686575 16788.8 1 6 CACCTG AGCACCCAGGACAGCGGCCG + +4 dbcorrdb__RFX5__ENCSR000EFD_1__m3-kay-Mes4-Nf-YA-Nf-YB-Nf-YC 13 0.686575 16788.8 1 6 CACCTG ACCAGCCAATCAGAACCCTC + +4 dbcorrdb__RFX5__ENCSR000EFD_1__m6 9 0.686575 16788.8 1 6 CACCTG CCTGCCAGCCTCCTCAGTCT + +4 dbcorrdb__SIN3A__ENCSR000BOY_1__m3-Sin3A 7 0.686575 16788.8 1 6 CACCTG TTGCTTACAGCAGTCGCGGC + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m5-brm 10 0.686575 16788.8 1 6 CACCTG AGCGCTGCTTCAAATTCCAC + +4 dbcorrdb__STAT1__ENCSR000DZM_1__m6-Max-Myc-Stat92E-Usf 8 0.686575 16788.8 1 6 CACCTG GGCGAGGCATCGTGAGGGGG + +4 dbcorrdb__STAT3__ENCSR000DOQ_1__m1-aop-Stat92E 0 0.686575 16788.8 1 6 CACCTG TCACTTCCAGGAAATGATTT + +4 dbcorrdb__TBP__ENCSR000EHA_1__m1-Tbp 11 0.686575 16788.8 1 6 CACCTG GGCCGGCGCCCTACCCGCTG + +4 dbcorrdb__CHD1__ENCSR000EFC_1__m6-Chd1 3 0.686575 16788.8 1 6 CACCTG GGCATCCTACGGCCAGGCCC - +4 dbcorrdb__EZH2__ENCSR000ATC_1__m4-E(z) 14 0.686575 16788.8 1 6 CACCTG AACGCTCTGCAAAGTTCCCG - +4 dbcorrdb__FOXP2__ENCSR000BGB_1__m1-foxo-FoxP 10 0.686575 16788.8 1 6 CACCTG GCTGGCTGTTTACTGCGCCG - +4 dbcorrdb__HDAC2__ENCSR000BMC_1__m1-bin-croc-fd59A-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 2 0.686575 16788.8 1 6 CACCTG AGCCACTGTTTACTCAGCGC - +4 dbcorrdb__IKZF1__ENCSR000EUJ_1__m1-CG9650-Dif-dl-ebi-Eip74EF-Ets96B-MTA1-like-nej-Stat92E-sv 8 0.686575 16788.8 1 6 CACCTG AGTTTCACTTCCTCTTTCAG - +4 dbcorrdb__IRF3__ENCSR000DZX_1__m1 5 0.686575 16788.8 1 6 CACCTG CATGATAAATGGCAATTTAT - +4 dbcorrdb__JUN__ENCSR000EZT_1__m1-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 14 0.686575 16788.8 1 6 CACCTG AAAAAGGGATGACTCATCCC - +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m8 7 0.686575 16788.8 1 6 CACCTG GTAAGTTTTTCTGGTTAAAG - +4 dbcorrdb__MAFK__ENCSR000EDZ_1__m1-cic-cnc-maf-S-tj 0 0.686575 16788.8 1 6 CACCTG TTGCTGAGTCAGCAATTTTT - +4 dbcorrdb__MAZ__ENCSR000ECL_1__m1-Brf-brm-btd-CG42741-CTCF-dar1-E2f1-E(z)-HDAC1-kay-luna-Myc-Nelf-E-Nf-YA-Nf-YB-Pglym78-Pglym87-Rbbp5-RpII215-Spps-Spt20-SREBP-Stat92E-Taf1-tna-vtd 9 0.686575 16788.8 1 6 CACCTG CCCGGCCCCGCCCTCCGGCG - +4 dbcorrdb__MXI1__ENCSR000ECU_1__m1-Brf-brm-btd-Clk-CTCF-E2f1-ERR-E(z)-gce-Hcf-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf-vtd 11 0.686575 16788.8 1 6 CACCTG CCCCCCGCCGCCACGTGGGC - +4 dbcorrdb__MYC__ENCSR000DOS_1__m1-Clk-E2f1-gce-Max-Myc-Usf 3 0.686575 16788.8 1 6 CACCTG AGCCACGTGCTCGGGGGGGG - +4 dbcorrdb__MYC__ENCSR000EBY_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Max-Myc-RpII215-Sap30-Spps-SREBP-Stat92E-Taf1-tgo-tna-Usf-vtd-zfh1 8 0.686575 16788.8 1 6 CACCTG CCGGCGGCCACGTGGCCGCG - +4 dbcorrdb__MYC__ENCSR000EHR_1__m1-Brf-Clk-cnc-E2f1-Eip74EF-E(z)-gce-Max-Mnt-Myc-Nelf-E-pho-phol-RpII215-Sap30-tna-Usf 10 0.686575 16788.8 1 6 CACCTG CCCCGCCGGCCACGTGCTCC - +4 dbcorrdb__MYC__ENCSR000EZV_1__m1-Brf-btd-Clk-cnc-E2f1-Eip74EF-E(z)-gce-Max-Myc-pho-phol-RpII215-Sap30-Spps-tgo-Usf 4 0.686575 16788.8 1 6 CACCTG CGACCACGTGGCCCCGGGGG - +4 dbcorrdb__NELFE__ENCSR000DOF_1__m2-Nelf-E 7 0.686575 16788.8 1 6 CACCTG AGAGACCCGCCCCAGCCGCT - +4 dbcorrdb__SAP30__ENCSR000AQJ_1__m4-Sap30 7 0.686575 16788.8 1 6 CACCTG GCAGCGCGACCGGCGGCCGG - +4 dbcorrdb__STAT3__ENCSR000DZV_1__m2-CG9650-Dif-dl-Jra-kay-nej-Stat92E 2 0.686575 16788.8 1 6 CACCTG ATACGATGACTCATTTCTGG - +4 dbcorrdb__TBL1XR1__ENCSR000DYZ_1__m2-Bgb-Bro-CG9650-ebi-lz-MTA1-like-run-RunxA-RunxB 5 0.686575 16788.8 1 6 CACCTG AATATTTTCTGTGGTTTGTG - +4 dbcorrdb__TCF12__ENCSR000BJG_1__m2-btd-EcR-HDAC1-Hnf4-Hr78-nej-Spps-svp-usp 4 0.686575 16788.8 1 6 CACCTG AGCTGGACTTTGAACTCTGC - +4 dbcorrdb__TCF7L2__ENCSR000EUV_1__m2-cnc-CoRest-Jra-kay-Mef2-mor-Myc-pan-Snr1 12 0.686575 16788.8 1 6 CACCTG GCGGCGATGAGTCATCCCCG - +4 dbcorrdb__TCF7L2__ENCSR000EUY_1__m2-ebi-pan 11 0.686575 16788.8 1 6 CACCTG GGCGGTTTTATCGCCCCTTG - +4 tfdimers__MD00185-TfAP-2 9 0.686575 16788.8 1 6 CACCTG TTTCTTTAATCCCTGTATTA - +4 transfac_pro__M05744-CG9609 5 0.686575 16788.8 1 6 CACCTG GGTGTTACCAATTCCCAGCT - +4 dbcorrdb__RCOR1__ENCSR000ECM_1__m2-CoRest -1 0.686575 16788.8 1 5 CACCTG CTCTGGCAGCATCCCTGACA + +4 taipale_cyt_meth__ZSCAN29_MMGYGTAGMCGKCTACACNN_eDBD_meth 15 0.686575 16788.8 1 5 CACCTG CCGTGTAGACGTCTACACAG + +4 dbcorrdb__RELA__ENCSR000EBM_1__m2-Dif-dl -1 0.686575 16788.8 1 5 CACCTG CCCAAACAGCCACAGGGGGG - +4 cisbp__M0007-Taf1 1 0.686705 16792 1 6 CACCTG GCGCCGCCA + +4 cisbp__M0716-FoxK-foxo-FoxP-slp2 3 0.686705 16792 1 6 CACCTG GTAAACAAC + +4 cisbp__M0830 0 0.686705 16792 1 6 CACCTG AACCAATCA + +4 cisbp__M1010-abd-A-Abd-B-Antp-bsh-btn-C15-cad-CG32532-Dfd-en-eve-exex-ftz-HGTX-ind-lab-lms-pb-Scr-slou-tup-Ubx-zen2 0 0.686705 16792 1 6 CACCTG TTAATTACC + +4 cisbp__M1188-CG15696 3 0.686705 16792 1 6 CACCTG GCCAATAAA + +4 fantom__motif141_TTAAACGGC 2 0.686705 16792 1 6 CACCTG TTAAACGGC + +4 jaspar__MA0997.1-Taf1 1 0.686705 16792 1 6 CACCTG GCGCCGCCA + +4 predrem__nrMotif1802 3 0.686705 16792 1 6 CACCTG TGGGACTAT + +4 predrem__nrMotif285 3 0.686705 16792 1 6 CACCTG GCAAACACA + +4 scertf__zhu.OAF1 3 0.686705 16792 1 6 CACCTG TAAATCCGA + +4 hocomoco__PITX1_HUMAN.H11MO.0.D-Ptx1-oc 3 0.686705 16792 1 6 CACCTG TTAATCCCT - +4 predrem__nrMotif1505 3 0.686705 16792 1 6 CACCTG GGGCTCCAT - +4 predrem__nrMotif1654 0 0.686705 16792 1 6 CACCTG CTGCTTCAA - +4 predrem__nrMotif1765 2 0.686705 16792 1 6 CACCTG CCCACCATC - +4 predrem__nrMotif2214 0 0.686705 16792 1 6 CACCTG AACCCCACC - +4 predrem__nrMotif2442 0 0.686705 16792 1 6 CACCTG TGGCTTCTA - +4 predrem__nrMotif485 0 0.686705 16792 1 6 CACCTG TAACAGAAA - +4 predrem__nrMotif758 3 0.686705 16792 1 6 CACCTG AGTCTCCCA - +4 predrem__nrMotif959 0 0.686705 16792 1 6 CACCTG CCCCGGCGG - +4 tiffin__TIFDMEM0000093 0 0.686705 16792 1 6 CACCTG TATTTTCAA - +4 transfac_pro__M04726-btd-CTCF-Spps 0 0.686705 16792 1 6 CACCTG GCGCTGTCC - +4 cisbp__M5280-eve-zen -1 0.686705 16792 1 5 CACCTG CCCTAATGA + +4 predrem__nrMotif1427 4 0.686705 16792 1 5 CACCTG GGGGTCCCC + +4 predrem__nrMotif1932 4 0.686705 16792 1 5 CACCTG AGAGAATCT + +4 predrem__nrMotif2461 -1 0.686705 16792 1 5 CACCTG CTCTGTAGC + +4 predrem__nrMotif789 4 0.686705 16792 1 5 CACCTG TATTTCCCA + +4 hocomoco__PRGR_HUMAN.H11MO.1.A -1 0.686705 16792 1 5 CACCTG TTCTGTTCT - +4 predrem__nrMotif129 4 0.686705 16792 1 5 CACCTG CCCACTCCC - +4 predrem__nrMotif2254 -1 0.686705 16792 1 5 CACCTG ACATTGCCA - +4 transfac_pro__M04721-Stat92E -1 0.686705 16792 1 5 CACCTG TCCAGGAAA - +4 transfac_pro__M07607-NFAT 4 0.686705 16792 1 5 CACCTG ATTTTTCCA - +4 predrem__nrMotif1658 -2 0.686705 16792 1 4 CACCTG TCTGAATTG + +4 predrem__nrMotif1723 5 0.686705 16792 1 4 CACCTG GGAGCAACA + +4 predrem__nrMotif2001 -2 0.686705 16792 1 4 CACCTG GCTTGATGA + +4 cisbp__M0725-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.686705 16792 1 4 CACCTG TTGTTTACA - +4 jaspar__MA0434.1 5 0.686705 16792 1 4 CACCTG TGATCTACA - +4 neph__UW.Motif.0022 -2 0.686705 16792 1 4 CACCTG GCTGGGATT - +4 predrem__nrMotif1284 5 0.686705 16792 1 4 CACCTG CTGGCTCCC - +4 transfac_pro__M01139 5 0.686705 16792 1 4 CACCTG CTGCTGACC - +4 transfac_pro__M01929 5 0.686705 16792 1 4 CACCTG TGATCTACA - +4 transfac_pro__M04759-CG5846-CG9727-Max-Rfx-SREBP 5 0.686705 16792 1 4 CACCTG CATGGCAAC - +4 predrem__nrMotif1851 6 0.686705 16792 1 3 CACCTG TTCTAAAAC - +4 cisbp__M0287-Atf-2-CG44247-CrebA-CrebB-Jra-Xbp1-cnc-kay 2 0.686843 16795.4 1 6 CACCTG ATGACGTCAT + +4 cisbp__M0324-CG7786-Irbp18-Pdp1-Xrp1-gt-hng1-slbo-vri 2 0.686843 16795.4 1 6 CACCTG ATTACGTAAT + +4 cisbp__M0655 4 0.686843 16795.4 1 6 CACCTG AGATAACGTC + +4 cisbp__M0857-Antp-B-H1-B-H2-CG9876-CG11085-Dll-Dr-E5-HGTX-Lim1-NK7.1-OdsH-Scr-Ubx-Vsx2-bsh-btn-ems-en-eve-ftz-inv-lab-lms-pb-slou-unpg-zen2 2 0.686843 16795.4 1 6 CACCTG AGTAATTAAG + +4 cisbp__M1116 3 0.686843 16795.4 1 6 CACCTG CCTAATCACG + +4 cisbp__M2262-dsf-tll 3 0.686843 16795.4 1 6 CACCTG TTTGACTTTT + +4 cisbp__M3393-CG7786-gt-hng1-Pdp1-REPTOR-BP-vri 2 0.686843 16795.4 1 6 CACCTG GTTACGTAAT + +4 cisbp__M6465-Dad-Mad-Med-Smox 1 0.686843 16795.4 1 6 CACCTG GTGTCTGGCC + +4 flyfactorsurvey__Trl_FlyReg_FBgn0013263-Trl 0 0.686843 16795.4 1 6 CACCTG TTGCTCTCTC + +4 jaspar__MA0599.1-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-hkb-luna 4 0.686843 16795.4 1 6 CACCTG GCCCCGCCCC + +4 predrem__nrMotif1710 4 0.686843 16795.4 1 6 CACCTG GTCCAGCCCC + +4 predrem__nrMotif2496 1 0.686843 16795.4 1 6 CACCTG GGACTTCCCA + +4 taipale_cyt_meth__ATOH7_ANCATATGNY_eDBD-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.686843 16795.4 1 6 CACCTG AACATATGTC + +4 taipale_cyt_meth__HES7_GGCACGTGYN_eDBD-dpn-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 2 0.686843 16795.4 1 6 CACCTG GGCACGTGCG + +4 transfac_pro__M01834 1 0.686843 16795.4 1 6 CACCTG ACACATAAAA + +4 cisbp__M0399 2 0.686843 16795.4 1 6 CACCTG CATTCCCCCT - +4 cisbp__M1224 4 0.686843 16795.4 1 6 CACCTG GGTGGTCATG - +4 cisbp__M1488 4 0.686843 16795.4 1 6 CACCTG AGGCTACAAA - +4 cisbp__M2014-Trl 0 0.686843 16795.4 1 6 CACCTG TTGCTCTCTC - +4 cisbp__M2391-btd-cbt-CG3065-CG42741-dar1-hkb-kay-Klf15-luna-Sp1-Spps 4 0.686843 16795.4 1 6 CACCTG GCCCCGCCCC - +4 cisbp__M4669-cnc-maf-S 1 0.686843 16795.4 1 6 CACCTG TGACTCGGCA - +4 cisbp__M4708-nub-pdm2-Tbp-vvl 0 0.686843 16795.4 1 6 CACCTG TATTTGCATA - +4 hocomoco__E2F3_MOUSE.H11MO.0.A-E2f1-E2f2 1 0.686843 16795.4 1 6 CACCTG CCTCCCGCCC - +4 homer__GCTGATAASV_Unknown5 3 0.686843 16795.4 1 6 CACCTG GGTTATCAGC - +4 predrem__nrMotif252 4 0.686843 16795.4 1 6 CACCTG TAAGAAACAA - +4 transfac_pro__M02038-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 0 0.686843 16795.4 1 6 CACCTG CACTTCCGGT - +4 transfac_pro__M07762-B-H1-B-H2 0 0.686843 16795.4 1 6 CACCTG ACCGTTTAGG - +4 cisbp__M6365-NFAT 5 0.686843 16795.4 1 5 CACCTG AAATTTTCCT + +4 predrem__nrMotif828 5 0.686843 16795.4 1 5 CACCTG AGTGACAGCA + +4 swissregulon__sacCer__BAS1-Myb-Pbp95 -1 0.686843 16795.4 1 5 CACCTG GCCAGAGTCA + +4 taipale_tf_pairs__SOX17_ACCGAACAAT_HT-Sox15 -1 0.686843 16795.4 1 5 CACCTG ACCGAACAAT + +4 transfac_pro__M07552 5 0.686843 16795.4 1 5 CACCTG GCGTTGACCA + +4 hocomoco__NFAC4_HUMAN.H11MO.0.C-NFAT 5 0.686843 16795.4 1 5 CACCTG AAATTTTCCT - +4 predrem__nrMotif1659 -1 0.686843 16795.4 1 5 CACCTG CTCTGGCCCT - +4 cisbp__M6426-vvl -2 0.686843 16795.4 1 4 CACCTG CATAAATAAT + +4 predrem__nrMotif307 6 0.686843 16795.4 1 4 CACCTG AATGAAAACT + +4 taipale_cyt_meth__HIC1_NRTGCCAMCN_eDBD_repr 6 0.686843 16795.4 1 4 CACCTG CGTGCCAACC + +4 taipale_tf_pairs__HOXD4_NNYMATTANN_HT-Dfd 6 0.686843 16795.4 1 4 CACCTG GGCCATTACC + +4 transfac_pro__M07566 6 0.686843 16795.4 1 4 CACCTG GGGGCCCACA + +4 cisbp__M0469 6 0.686843 16795.4 1 4 CACCTG CTGCGCCACA - +4 cisbp__M5414-al-Awh-bsh-C15-CG18599-CG34367-CG9876-Dr-E5-ems-en-ind-inv-lab-lbe-Lim3-OdsH-pb-Pph13-repo-slou-Ubx-unc-4-unpg-zfh2 6 0.686843 16795.4 1 4 CACCTG ACCAATTAAC - +4 predrem__nrMotif1842 -2 0.686843 16795.4 1 4 CACCTG CCTGGCCGCC - +4 predrem__nrMotif315 -2 0.686843 16795.4 1 4 CACCTG CTTTTTTCTT - +4 transfac_pro__M01239-Dif-dl-Rel 6 0.686843 16795.4 1 4 CACCTG GGAAATCCCC - +4 transfac_pro__M06060 6 0.686843 16795.4 1 4 CACCTG TCTTCTCAAC - +4 transfac_pro__M05462 7 0.686843 16795.4 1 3 CACCTG TTGTGGGCAC + +4 transfac_pro__M05770 7 0.686843 16795.4 1 3 CACCTG TCGAAAATAC - +4 transfac_pro__M06260 7 0.686843 16795.4 1 3 CACCTG GCGGCTTAAC - +4 tfdimers__MD00406 13 0.687183 16803.7 1 6 CACCTG GCGCTCAGCTGAGCATCTGGGGGTGTGGCCACACCCCCAGATGCTCAGCTGAGCGC + +4 cisbp__M0141-Xrp1 5 0.687571 16813.2 1 6 CACCTG ATAAATAATTAA + +4 cisbp__M1763 2 0.687571 16813.2 1 6 CACCTG TTTACCGAGCAC + +4 cisbp__M2596 5 0.687571 16813.2 1 6 CACCTG TGGATGACATTA + +4 cisbp__M4772-br 3 0.687571 16813.2 1 6 CACCTG ATTCATCTAACG + +4 hocomoco__ANDR_HUMAN.H11MO.2.A 5 0.687571 16813.2 1 6 CACCTG CTCTGTTCTTTT + +4 stark__TGACANNTTGAC 3 0.687571 16813.2 1 6 CACCTG TGACAAATTGAC + +4 taipale__FOXO1_DBD_TTTCCCCACACG_repr-foxo 6 0.687571 16813.2 1 6 CACCTG TTTCCCCACACG + +4 taipale_cyt_meth__FOS_NRTGACGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.687571 16813.2 1 6 CACCTG GATGACGTCATC + +4 tiffin__TIFDMEM0000092 3 0.687571 16813.2 1 6 CACCTG TATTAACAATTT + +4 transfac_pro__M00338-CrebB 2 0.687571 16813.2 1 6 CACCTG GTGACGTCAGCG + +4 transfac_pro__M01017 5 0.687571 16813.2 1 6 CACCTG ACATCAATCAAA + +4 transfac_pro__M07684-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.687571 16813.2 1 6 CACCTG GATGACGTCATC + +4 hocomoco__RUNX2_MOUSE.H11MO.0.A-Bgb-Bro-MTA1-like-RunxA-RunxB-ebi-lz-run 2 0.687571 16813.2 1 6 CACCTG CAAACCACAGAC - +4 hocomoco__SMCA1_HUMAN.H11MO.0.C-Iswi 5 0.687571 16813.2 1 6 CACCTG CATTCTTCTTGG - +4 swissregulon__hs__NFATC1..3.p2-CG5641-NFAT 4 0.687571 16813.2 1 6 CACCTG AATTTTCCACTG - +4 taipale_cyt_meth__ATF3_NRTGAYGTCAYN_FL_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-Xbp1 3 0.687571 16813.2 1 6 CACCTG GATGACATCATC - +4 taipale_cyt_meth__BATF3_NRTGAYGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 3 0.687571 16813.2 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__BATF3_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.687571 16813.2 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__ZBTB26_NMTCYAGAAAAN_FL 2 0.687571 16813.2 1 6 CACCTG TTTTTCTAGATT - +4 taipale_tf_pairs__MEIS1_ELF1_NTGCCGGAAGTN_CAP_repr-Eip74EF 0 0.687571 16813.2 1 6 CACCTG CACTTCCGGCAG - +4 transfac_pro__M05576 6 0.687571 16813.2 1 6 CACCTG GCATTTTATCGC - +4 transfac_pro__M05887 2 0.687571 16813.2 1 6 CACCTG GCGGCCTTCCCA - +4 transfac_pro__M05949 2 0.687571 16813.2 1 6 CACCTG GCTTCCTTCCCT - +4 transfac_pro__M06005 3 0.687571 16813.2 1 6 CACCTG TCTTTCCTCGAG - +4 transfac_pro__M06220-CG2120 6 0.687571 16813.2 1 6 CACCTG TCAGTTAATCAC - +4 transfac_pro__M06506 4 0.687571 16813.2 1 6 CACCTG GAATAATCTCCA - +4 transfac_pro__M06562 2 0.687571 16813.2 1 6 CACCTG TCTGCCTTAACT - +4 transfac_pro__M06586 6 0.687571 16813.2 1 6 CACCTG GCGTTTTGCCCC - +4 transfac_pro__M06634 1 0.687571 16813.2 1 6 CACCTG GTACGTTGCTCT - +4 transfac_pro__M06865 4 0.687571 16813.2 1 6 CACCTG CCCCCACCCCAG - +4 transfac_pro__M06866 4 0.687571 16813.2 1 6 CACCTG CCCCCACCCCAG - +4 homer__ATGACGTCATCC_c-Jun-CRE-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 7 0.687571 16813.2 1 5 CACCTG ATGACGTCATCC + +4 transfac_public__M00208-CG12018-Dif-dl-Rel 7 0.687571 16813.2 1 5 CACCTG GGGGACTTTCCA + +4 cisbp__M2680 -1 0.687571 16813.2 1 5 CACCTG ACGTCAGCACCC - +4 jaspar__MA0019.1 7 0.687571 16813.2 1 5 CACCTG GGGATTGCATCT - +4 transfac_pro__M05730 7 0.687571 16813.2 1 5 CACCTG TTTCTTTTATCG - +4 transfac_pro__M06034 7 0.687571 16813.2 1 5 CACCTG TCTATACCCCCA - +4 transfac_pro__M06371 7 0.687571 16813.2 1 5 CACCTG TGGGCCAAACAC - +4 transfac_pro__M06430 7 0.687571 16813.2 1 5 CACCTG TGGGCCAAACAC - +4 transfac_pro__M06453 7 0.687571 16813.2 1 5 CACCTG TCCCCAAATCCA - +4 transfac_public__M00357 -1 0.687571 16813.2 1 5 CACCTG ACGTCAGCACCC - +4 transfac_pro__M06269 8 0.687571 16813.2 1 4 CACCTG TTTTTTAACACC - +4 transfac_pro__M06582 8 0.687571 16813.2 1 4 CACCTG GCTTTTTTCACA - +4 transfac_pro__M07433-pan -2 0.687571 16813.2 1 4 CACCTG GCTTTGAACTCA - +4 transfac_pro__M00725 -3 0.687571 16813.2 1 3 CACCTG CTGTTGAATATT - +4 taipale_tf_pairs__ELK1_TEF_NSCGGAWNTTACGTAAN_CAP-CG7786-gt-Pdp1 9 0.687612 16814.2 1 6 CACCTG ACCGGAAGTTACGTAAC + +4 taipale_tf_pairs__ETV2_TEF_RSCGGAWNTTRCGYAAN_CAP-CG7786-gt-Pdp1-pnt 9 0.687612 16814.2 1 6 CACCTG ACCGGAAGTTACGTAAC + +4 taipale_tf_pairs__TEAD4_HOXA3_RCATTCYNNNNNCATTA_CAP-sd 3 0.687612 16814.2 1 6 CACCTG ACATTCCAAACTCATTA + +4 transfac_pro__M03067-oc-Ptx1 9 0.687612 16814.2 1 6 CACCTG GATAATTAATCCCTCTT + +4 transfac_pro__M07892-Bgb-lz-run-RunxA-RunxB 1 0.687612 16814.2 1 6 CACCTG TAACCGCAAAACCGCAA + +4 hocomoco__CENPB_HUMAN.H11MO.0.D 0 0.687612 16814.2 1 6 CACCTG AACCCGCATCGTACGAA - +4 hocomoco__EGR1_HUMAN.H11MO.0.A-CG42741-Spps-btd-klu-luna-sd-sr 1 0.687612 16814.2 1 6 CACCTG CCCCCGCCCACGCCCTC - +4 hocomoco__NANOG_HUMAN.H11MO.0.A-CG9650-Mad-SoxN-nej-nub-pan-pdm2-vvl 3 0.687612 16814.2 1 6 CACCTG ATTTGCATAACAAAGGA - +4 swissregulon__hs__FOXP3.p2 11 0.687612 16814.2 1 6 CACCTG GTCTGAAACAACACTTC - +4 taipale_cyt_meth__PAX6_NYACGCNTSANYGNNYN_FL-ey-Poxm-sv-toy 10 0.687612 16814.2 1 6 CACCTG TGCGCAGTCATGCGTGA - +4 taipale_cyt_meth__ZNF343_NYGCTTCACCNCGGYMN_eDBD 1 0.687612 16814.2 1 6 CACCTG GTGCCGTGGTGAAGCGG - +4 transfac_pro__M05359 4 0.687612 16814.2 1 6 CACCTG GGACCACTTAAGCTCAA - +4 transfac_pro__M07855-Hsf-pb 8 0.687612 16814.2 1 6 CACCTG CGTTCTAGAACATTCCA - +4 taipale__FOXI1_full_NTGTTTACRGTAAAYAN_repr 12 0.687612 16814.2 1 5 CACCTG TTGTTTACCGTAAACAT - +4 tfdimers__MD00088 12 0.687985 16823.3 1 6 CACCTG AAAAAGGAAAACCACAGACAACTAAA + +4 tfdimers__MD00057-CG7786-gt-Pdp1 2 0.687985 16823.3 1 6 CACCTG TTTTTTTGCATAATCCCCACCTTTCT - +4 tfdimers__MD00399-NFAT 8 0.687985 16823.3 1 6 CACCTG TATTTTACTTCCTCTTTTTCCTTTTT - +4 tfdimers__MD00428-nej-Sirt6 14 0.687985 16823.3 1 6 CACCTG TTTTTCCTTCTCACTCCCTTTTTTTT - +4 hdpi__PTPMT1-PTPMT1 -1 0.688001 16823.7 1 5 CACCTG TCCCC - +4 cisbp__M2026-caup 1 0.688001 16823.7 1 4 CACCTG TAACA + +4 jaspar__MA0053.1 -2 0.688001 16823.7 1 4 CACCTG GCTTT - +4 cisbp__M1897-ey-Poxm-sv-toy 6 0.689005 16848.2 1 6 CACCTG AACTCATGCGTGAA + +4 cisbp__M2045-pan 4 0.689005 16848.2 1 6 CACCTG TCGGCTCCTTTGAT + +4 fantom__motif86_CGCACAGACCGCGC 6 0.689005 16848.2 1 6 CACCTG CGCACAGACCGCGC + +4 flyfactorsurvey__CG4404_SANGER_5_FBgn0030432-CG4404 4 0.689005 16848.2 1 6 CACCTG GCAGTAATTACAGC + +4 hocomoco__MEF2B_HUMAN.H11MO.0.A-Mef2 1 0.689005 16848.2 1 6 CACCTG GTTGCTATTTTTGG + +4 homer__ACATGCCCGGGCAT_p53 3 0.689005 16848.2 1 6 CACCTG ACATGCCCGGGCAT + +4 jaspar__MA0162.2-CTCF-Spps-btd-klu-luna-sd-sr 0 0.689005 16848.2 1 6 CACCTG CCCCCGCCCCCGCC + +4 taipale_cyt_meth__ZBTB12_NGGCCTGCCGTCNN_eDBD_meth_repr 1 0.689005 16848.2 1 6 CACCTG TGGCCTGCCGTCGC + +4 cisbp__M1971-btd-CTCF-klu-luna-sd-Spps-sr 0 0.689005 16848.2 1 6 CACCTG CCCCCGCCCCCGCC - +4 cisbp__M2315-Stat92E 4 0.689005 16848.2 1 6 CACCTG CCATTTCCTGGAAA - +4 cisbp__M3680-nub-pdm2 0 0.689005 16848.2 1 6 CACCTG AACATGTAATTATG - +4 hocomoco__GLIS2_HUMAN.H11MO.0.D-ci-lmd-sug 0 0.689005 16848.2 1 6 CACCTG GACCCCCCGCGAAG - +4 hocomoco__KLF1_MOUSE.H11MO.0.A-CG3065-CG42741-Klf15-Spps-btd-cbt-dar1-hkb-luna-sr 8 0.689005 16848.2 1 6 CACCTG CCCGGCCCCACCCT - +4 homer__CTGGCAGGCTGCCA_Tlx_-NfI-tll 8 0.689005 16848.2 1 6 CACCTG TGGCAGCCTGCCAG - +4 jaspar__MA0518.1-Stat92E 4 0.689005 16848.2 1 6 CACCTG CCATTTCCTGGAAA - +4 taipale_cyt_meth__NKX2-8_NATGTCGTTAYTGN_FL_meth_repr-vnd 8 0.689005 16848.2 1 6 CACCTG GCAATAACGACATC - +4 taipale_tf_pairs__ETV2_DRGX_RSCGGAANYAATTA_CAP-CG11294-Drgx-pnt 7 0.689005 16848.2 1 6 CACCTG TAATTACTTCCGGT - +4 transfac_public__M00162-nub-pdm2 0 0.689005 16848.2 1 6 CACCTG TACATGTAATTTTG - +4 taipale_cyt_meth__ZNF75A_NGCTTTTCCCACMN_eDBD 9 0.689005 16848.2 1 5 CACCTG CGCTTTTCCCACAC + +4 transfac_pro__M07680-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 9 0.689005 16848.2 1 5 CACCTG TGATGACGTCATCA + +4 neph__UW.Motif.0134 9 0.689005 16848.2 1 5 CACCTG TGAAAATGAAATTT - +4 transfac_pro__M00665-btd-Spps -1 0.689005 16848.2 1 5 CACCTG CCCTCCCCAAGGCT - +4 transfac_pro__M05277 9 0.689005 16848.2 1 5 CACCTG GGGTTAAATTATCC - +4 taipale_cyt_meth__IRF5_NYGAAACCGAAACY_FL_meth 10 0.689005 16848.2 1 4 CACCTG CCGAAACCGAAACT + +4 taipale_cyt_meth__POU1F1_NTATGCWAATKAGN_eDBD_meth-nub-pdm2-pdm3-vvl -2 0.689005 16848.2 1 4 CACCTG GCTAATTTGCATAT - +4 transfac_pro__M09198 1 0.689306 16855.6 1 6 CACCTG TAACGTGTTCTACACGCTACC + +4 taipale_cyt_meth__ETV3_NNAGGAANNNNNNNTTCCTNN_eDBD_repr-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 11 0.689306 16855.6 1 6 CACCTG ACCGGAAGTGCCACTTCCGGT - +4 tfdimers__MD00206-zfh1 1 0.689306 16855.6 1 6 CACCTG TTACCTCAGCAAACATTTAAT - +4 transfac_pro__M01535 14 0.689306 16855.6 1 6 CACCTG AGGAGATATGGCCATAACTGG - +4 transfac_pro__M09054-Adf1-Taf1 16 0.689306 16855.6 1 5 CACCTG CCTCCGCCGCCGCCGCCGCCG + +4 flyfactorsurvey__CG6276_SANGER_5_FBgn0038316-CG6276 6 0.689933 16870.9 1 6 CACCTG CCATAAAACAAAA + +4 neph__UW.Motif.0423 4 0.689933 16870.9 1 6 CACCTG CCAATTTCTCTGA + +4 taipale_cyt_meth__KLF14_NRCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.689933 16870.9 1 6 CACCTG CGCCACGCCCCCC + +4 taipale_cyt_meth__POU6F1_TATGCNNNGCATA_FL_repr-pdm3 7 0.689933 16870.9 1 6 CACCTG TATGCAAGGCATA + +4 taipale_cyt_meth__ZNF740_NYGCCCCCCCCAC_FL_repr 1 0.689933 16870.9 1 6 CACCTG CCGCCCCCCCCAC + +4 transfac_pro__M06956-oc 2 0.689933 16870.9 1 6 CACCTG TTAATCTGATTAT + +4 cisbp__M0876 3 0.689933 16870.9 1 6 CACCTG AAGGGCATGTTAT - +4 cisbp__M4548-Stat92E 3 0.689933 16870.9 1 6 CACCTG CATTTCCCGGAAG - +4 cisbp__M4873-CG6276 6 0.689933 16870.9 1 6 CACCTG CCATAAAACAAAA - +4 hocomoco__BRAC_MOUSE.H11MO.1.C-byn 5 0.689933 16870.9 1 6 CACCTG GAATTCACAGACA - +4 taipale_tf_pairs__FOXO1_ELK1_TGTTGCCGGANNN_CAP-foxo 2 0.689933 16870.9 1 6 CACCTG ACTTCCGGCAACA - +4 transfac_pro__M08994 5 0.689933 16870.9 1 6 CACCTG GCACACACTGACA - +4 transfac_pro__M09466-tll 6 0.689933 16870.9 1 6 CACCTG AAAAGTCAACGAT - +4 flyfactorsurvey__Opa_SANGER_5_FBgn0003002-opa 8 0.689933 16870.9 1 5 CACCTG ATCCCCCCCACCG + +4 transfac_public__M00234-Su(H) 8 0.689933 16870.9 1 5 CACCTG ATTGTGGGAACCG + +4 cisbp__M5134-opa 8 0.689933 16870.9 1 5 CACCTG AGCCCCCCCACCG - +4 cisbp__M3450 9 0.689933 16870.9 1 4 CACCTG GTTTGGGAATACC + +4 transfac_public__M00086 9 0.689933 16870.9 1 4 CACCTG GTTTGGGAATACC + +4 neph__UW.Motif.0114 -3 0.689933 16870.9 1 3 CACCTG CTGGGATTTTTTT - +4 taipale_tf_pairs__TEAD4_FOXI1_RCATWCCNNNNNNNNNNNRTMAACA_CAP_repr-sd 8 0.689994 16872.4 1 6 CACCTG ACATTCCACACTGGCAGCGAAAACA + +4 taipale_tf_pairs__TEAD4_HOXA13_RCATWCCNNNNNNNNYNNTAAA_CAP_repr-sd 3 0.690923 16895.1 1 6 CACCTG ACATTCCACACCCGCTCATAAA + +4 hocomoco__ZN143_HUMAN.H11MO.0.A-Hcf-Six4-Stat92E-bi-egg-mor 4 0.690923 16895.1 1 6 CACCTG GAACTACAATTCCCAGAATGCC - +4 hocomoco__ZNF76_HUMAN.H11MO.0.C-Six4-bi-egg-mor 2 0.690923 16895.1 1 6 CACCTG ACTACAATTCCCAGAATGCCCC - +4 transfac_pro__M04696-CG10431-pho-phol-Taf1 0 0.690923 16895.1 1 6 CACCTG TGCCCGTACCCAAGATGGCGGC - +4 cisbp__M3447-Atf6-CrebA-CrebB-Xbp1 9 0.691192 16901.7 1 6 CACCTG CTGAAAGATGACGTGTCATTTAAT + +4 transfac_public__M00538-Atf6-CrebA-CrebB-Xbp1 9 0.691192 16901.7 1 6 CACCTG CTGAAAGATGACGTGTCATTTAAT - +4 transfac_public__M00049 15 0.691524 16909.8 1 6 CACCTG GTTCGGAGGACAGTGCTCCGATG - +4 transfac_pro__M04887 0 0.692896 16943.4 1 6 CACCTG AACCGAA + +4 cisbp__M1016-Optix 1 0.692896 16943.4 1 6 CACCTG GTATCAC - +4 cisbp__M1139-CG4328-Lmx1a 0 0.692896 16943.4 1 6 CACCTG TAATTAA - +4 hdpi__CAT-CG9314-Cat 1 0.692896 16943.4 1 6 CACCTG ATTTCTG - +4 hdpi__HP1BP3 1 0.692896 16943.4 1 6 CACCTG TTTCCAG - +4 predrem__nrMotif2249 2 0.692896 16943.4 1 5 CACCTG GTCCCCA + +4 predrem__nrMotif2381 2 0.692896 16943.4 1 5 CACCTG TTAAACT + +4 hdpi__SLC18A1-Vmat -1 0.692896 16943.4 1 5 CACCTG ACCAATT - +4 predrem__nrMotif922 2 0.692896 16943.4 1 5 CACCTG AGAACAT - +4 jaspar__MA0393.1 3 0.692896 16943.4 1 4 CACCTG TGAAACA + +4 stark__RATTAMY-Dfd 3 0.692896 16943.4 1 4 CACCTG AATTAAC + +4 hdpi__YWHAE-14-3-3epsilon 3 0.692896 16943.4 1 4 CACCTG ATCGTCC - +4 predrem__nrMotif78 3 0.692896 16943.4 1 4 CACCTG TGGGCCC - +4 cisbp__M0542 -3 0.692896 16943.4 1 3 CACCTG CTCCCCC - +4 taipale__FOXD3_DBD_RTAAAYA-bs-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-slp2 4 0.692896 16943.4 1 3 CACCTG TGTTTAC - +4 cisbp__M0927-al-ap-Awh-CG11085-CG18599-CG9876-E5-ems-en-eve-exex-inv-lab-lbl-Lim3-OdsH-otp-repo-ro-Rx-slou-unpg-vvl 2 0.694437 16981.1 1 6 CACCTG GCTAATTA + +4 cisbp__M0968-bcd-Gsc-oc-Ptx1 2 0.694437 16981.1 1 6 CACCTG TTAATCCC + +4 cisbp__M1772 1 0.694437 16981.1 1 6 CACCTG GTTCCGGT + +4 cisbp__M1824 2 0.694437 16981.1 1 6 CACCTG ATTTCCGT + +4 cisbp__M1865 2 0.694437 16981.1 1 6 CACCTG TATACATA + +4 fantom__motif91_TTCTTTCG 0 0.694437 16981.1 1 6 CACCTG TTCTTTCG + +4 hdpi__TRIP10-Cip4 2 0.694437 16981.1 1 6 CACCTG TGTAAATG + +4 predrem__nrMotif2269 2 0.694437 16981.1 1 6 CACCTG ACAATCTG + +4 predrem__nrMotif794 0 0.694437 16981.1 1 6 CACCTG GACCCCGG + +4 taipale__DLX5_FL_NYAATTAN_repr-Dll 1 0.694437 16981.1 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__DMBX1_NTAATCCN_eDBD 2 0.694437 16981.1 1 6 CACCTG CTAATCCG + +4 taipale_cyt_meth__HOXD4_RTCGTTAN_eDBD_meth-Antp-btn-Dfd-eve-exex-pb-Scr 0 0.694437 16981.1 1 6 CACCTG ATCATTAG + +4 taipale_cyt_meth__TGIF2_NTGACAGN_FL_meth_repr-achi-vis 2 0.694437 16981.1 1 6 CACCTG GTGACAGC + +4 taipale_cyt_meth__VSX1_NTCGTTAN_FL_meth-bsh-CG34367-CG4328-ind-Lim3-Lmx1a-unpg-Vsx1-Vsx2 0 0.694437 16981.1 1 6 CACCTG CTCGTTAA + +4 cisbp__M0129 1 0.694437 16981.1 1 6 CACCTG ATTTTTTT - +4 cisbp__M0569 0 0.694437 16981.1 1 6 CACCTG TGCATCCC - +4 cisbp__M0600 2 0.694437 16981.1 1 6 CACCTG TTCAAATT - +4 cisbp__M1014-abd-A-Antp-bsh-cad-Dfd-ftz-HGTX-Scr-Ubx 0 0.694437 16981.1 1 6 CACCTG GCCATTAA - +4 cisbp__M3594 1 0.694437 16981.1 1 6 CACCTG TCCCCACT - +4 cisbp__M5343-Dll 1 0.694437 16981.1 1 6 CACCTG GTAATTAT - +4 flyfactorsurvey__ovo_FlyReg_FBgn0003028-ovo 2 0.694437 16981.1 1 6 CACCTG TGTAACGG - +4 hdpi__PDE6H 0 0.694437 16981.1 1 6 CACCTG CTCATTAA - +4 hdpi__PGAM2-Pglym78-Pglym87-Spps-btd 0 0.694437 16981.1 1 6 CACCTG CCCCGCCC - +4 cisbp__M0301-Jra-kay 3 0.694437 16981.1 1 5 CACCTG GATGACGT + +4 predrem__nrMotif1140 3 0.694437 16981.1 1 5 CACCTG CATCCCCC + +4 predrem__nrMotif2607 -1 0.694437 16981.1 1 5 CACCTG AGCTTAAT + +4 transfac_pro__M00710-zen-zen2 -1 0.694437 16981.1 1 5 CACCTG ACATTAAA + +4 hdpi__RKHD2-CG11360 3 0.694437 16981.1 1 5 CACCTG TTTCATTT - +4 cisbp__M4695-Mef2 4 0.694437 16981.1 1 4 CACCTG AAAATAGC + +4 flyfactorsurvey__bowl_SANGER_5_FBgn0004893-bowl-odd -2 0.694437 16981.1 1 4 CACCTG GCTACTGG - +4 hdpi__TSC22D4-bun -2 0.694437 16981.1 1 4 CACCTG CCCAAAAG - +4 predrem__nrMotif1266 4 0.694437 16981.1 1 4 CACCTG TTTTTAGC - +4 predrem__nrMotif1693 4 0.694437 16981.1 1 4 CACCTG CAAATATC - +4 predrem__nrMotif2541 4 0.694437 16981.1 1 4 CACCTG TTAGCCCC - +4 transfac_pro__M01308-D-Mad-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN -2 0.694437 16981.1 1 4 CACCTG CCTTTGTT - +4 cisbp__M1205-ap-CG18599-E5-ems-eve-ind-lbl-pb-Ubx-zen2 5 0.694437 16981.1 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXD3_YTAATTAN_FL_meth-Antp-ap-Dfd-E5-ems-en-eve-exex-ind-inv-lbl-Lim3-pb-Scr-slou-Ubx-zen2 5 0.694437 16981.1 1 3 CACCTG CTAATTAC + +4 transfac_pro__M07376-arm-pan -3 0.694437 16981.1 1 3 CACCTG CTTTGATG + +4 cisbp__M5419-aop-Ets21C-Ets96B-Ets97D-pnt 8 0.694547 16983.7 1 6 CACCTG ACCGGAAGTACATCCGGC + +4 cisbp__M3068 4 0.694547 16983.7 1 6 CACCTG CCCCCAACCGCCATTGGG - +4 transfac_pro__M05831 11 0.694547 16983.7 1 6 CACCTG CCGTTGCTGACCCCCTTC - +4 transfac_public__M00004 4 0.694547 16983.7 1 6 CACCTG CCCCCAACCGCCGTTGGG - +4 stark__ANHDDBHGATAASSDNNB-GATAd-GATAe-grn-pnr-srp -1 0.694547 16983.7 1 5 CACCTG AATTTTTGATAACCTAAT + +4 tfdimers__MD00164 9 0.695847 17015.5 1 6 CACCTG CCCCCTGGGTCCCATCTGTTCTTCGCCCC + +4 tfdimers__MD00353-Jra-kay-Sox14 3 0.695847 17015.5 1 6 CACCTG TTTTTCCTTTGTTGACTCATTGTTTTTAA + +4 tfdimers__MD00434-Myc-pho-phol 5 0.695847 17015.5 1 6 CACCTG TTAGCCAGCTGTCCATTTTTGCACTTATT + +4 tfdimers__MD00576-Smox 5 0.695847 17015.5 1 6 CACCTG GCAAGAGCCTGTCTGGACATGCCTCCTCT + +4 cisbp__M2960-EcR-svp 2 0.69592 17017.3 1 6 CACCTG TGAACCCTTGACCCCT + +4 cisbp__M5648-Myb 8 0.69592 17017.3 1 6 CACCTG ACCGTTAAAACCGTTA + +4 jaspar__MA0912.1-Antp-Lim3-Scr-Ubx-abd-A-bsh-btn-ind-lab-pb 10 0.69592 17017.3 1 6 CACCTG TTGAGTTAATTAACCT + +4 taipale__MYBL2_DBD_ACCGTTARRACCGTTA_repr-Myb 8 0.69592 17017.3 1 6 CACCTG ACCGTTAAAACCGTTA + +4 taipale_tf_pairs__HOXB2_RFX5_TAATKRNNNNNGCAAC_CAP_repr-pb 4 0.69592 17017.3 1 6 CACCTG TAATTACCCTAGCAAC + +4 transfac_pro__M03882-Dif-dl 6 0.69592 17017.3 1 6 CACCTG GGAAAGTCCCCTTTGC + +4 transfac_pro__M07677-Atf3-Atf6-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.69592 17017.3 1 6 CACCTG GTCATCATGACGTCAT + +4 taipale_tf_pairs__HOXD12_ETV1_RSCGGAAGTAATAAAN_CAP-Ets96B 6 0.69592 17017.3 1 6 CACCTG TTTTATTACTTCCGGT - +4 swissregulon__sacCer__CRZ1-CG2120 0 0.696801 17038.9 1 6 CACCTG AGCCAC + +4 fantom__motif3_CGCTNA 1 0.696801 17038.9 1 5 CACCTG TAAGCG - +4 jaspar__MA0442.1-Sox100B -1 0.696801 17038.9 1 5 CACCTG ACAAAG - +4 transfac_pro__M07480-sd 2 0.696801 17038.9 1 4 CACCTG CATTCC - +4 transfac_pro__M00805-pan -3 0.696801 17038.9 1 3 CACCTG CTTTGA - +4 cisbp__M1413 5 0.697534 17056.8 1 6 CACCTG ACACGCAACTA + +4 flyfactorsurvey__l_3_neo38_SOLEXA_F2-4-CG7368-CTCF-klu-l(3)neo38 5 0.697534 17056.8 1 6 CACCTG CCCCCACCCCC + +4 jaspar__MA0076.2-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-aop-bs-pnt 1 0.697534 17056.8 1 6 CACCTG CCACTTCCGGC + +4 transfac_pro__M01273-brm-btd-CG42741-CTCF-dar1-ERR-E(z)-kay-Klf15-klu-Nf-YB-RpII215-Spps 0 0.697534 17056.8 1 6 CACCTG GCCCCGCCCCC + +4 transfac_pro__M06824-nerfin-1-nerfin-2 5 0.697534 17056.8 1 6 CACCTG AGAATTCCCCG + +4 transfac_pro__M09315 0 0.697534 17056.8 1 6 CACCTG TAACCGTAATA + +4 cisbp__M0398 3 0.697534 17056.8 1 6 CACCTG TTGCACTTCCT - +4 cisbp__M4892-ci-lmd-opa-sug 4 0.697534 17056.8 1 6 CACCTG AGACCACCCAC - +4 hocomoco__ZBT49_HUMAN.H11MO.0.D-Awh-C15-CG9876-CG11085-CG18599-CG34367-Dr-E5-Lim3-OdsH-Pph13-Rx-al-ems-en-exex-inv-lbe-lms-repo-slou-unc-4-unpg 5 0.697534 17056.8 1 6 CACCTG CCAATTAGCGC - +4 predrem__nrMotif410 0 0.697534 17056.8 1 6 CACCTG TTTCTTCTTTC - +4 tiffin__TIFDMEM0000023 3 0.697534 17056.8 1 6 CACCTG GTATTAGTTTT - +4 transfac_pro__M01876-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-nej-pnt 0 0.697534 17056.8 1 6 CACCTG GCACTTCCGGT - +4 jaspar__MA0563.1 -1 0.697534 17056.8 1 5 CACCTG TCCATTTTTGG + +4 cisbp__M2356 -1 0.697534 17056.8 1 5 CACCTG TCCATTTTTGG - +4 hocomoco__HLF_MOUSE.H11MO.0.C-CG7786-Hsf-Pdp1-gt 6 0.697534 17056.8 1 5 CACCTG GTTATGCAACA - +4 predrem__nrMotif57 6 0.697534 17056.8 1 5 CACCTG CTTGGAAACAT - +4 hocomoco__HXA13_HUMAN.H11MO.0.C 7 0.697534 17056.8 1 4 CACCTG CCAATAAAATC - +4 taipale_cyt_meth__HOXC10_NGYAATAAAAN_FL_meth-abd-A-Abd-B-cad-eve-Ubx 7 0.697534 17056.8 1 4 CACCTG GTTTTATTACC - +4 transfac_pro__M01892 -2 0.697534 17056.8 1 4 CACCTG TCTTAAAAAGG - +4 transfac_pro__M09526-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 7 0.697534 17056.8 1 4 CACCTG ATGACGTCATC - +4 tfdimers__MD00526 8 0.699864 17113.8 1 6 CACCTG CCCCCTTCCCCCTCATCCCAGACCCCTC - +4 transfac_pro__M09065-Adf1-Taf1 3 0.699931 17115.4 1 6 CACCTG CGCCGCCGCCGCCGCCGCC + +4 transfac_pro__M06490-CG2120 -2 0.699931 17115.4 1 4 CACCTG CCGGCATTGATTAAATTCT - +4 cisbp__M5650-Myb 7 0.701983 17165.6 1 6 CACCTG AACCGTTAAACGGTC + +4 cisbp__M5664-C15-Nf1-NfI 9 0.701983 17165.6 1 6 CACCTG TTGGCACCGTGCCAA + +4 flyfactorsurvey__br-PA_SOLEXA_FBgn0000210-br 7 0.701983 17165.6 1 6 CACCTG AACTATTGATTTTTT + +4 homer__TTCTAGAABNTTCTA_HRE-Hsf-pb 6 0.701983 17165.6 1 6 CACCTG TTCTAGAACGTTCTA + +4 taipale__MAFK_full_NTGCTGANTCAGCRN-cnc-maf-S-tj 9 0.701983 17165.6 1 6 CACCTG ATGCTGAGTCAGCGA + +4 taipale__MYBL2_DBD_RACCGTTAAACNGYY-Myb 7 0.701983 17165.6 1 6 CACCTG AACCGTTAAACGGTC + +4 taipale_cyt_meth__LIN28B_CGCGANNNNNCAGCG_FL_repr-lin-28 7 0.701983 17165.6 1 6 CACCTG CGCGATATAACAGCG + +4 taipale_cyt_meth__ZIC3_NRCCCCCYGCTGYGN_FL-lmd-opa 0 0.701983 17165.6 1 6 CACCTG GACCCCCCGCTGTGC + +4 transfac_pro__M01148-dmrt11E-dmrt93B-dmrt99B-dsx 7 0.701983 17165.6 1 6 CACCTG AATTTGATACATTTT + +4 transfac_pro__M05602 3 0.701983 17165.6 1 6 CACCTG TGTCACCATTTTGCT + +4 transfac_pro__M07411-nau-Nf1-NfI 9 0.701983 17165.6 1 6 CACCTG TTGGCAATGAGCCAA + +4 cisbp__M3228-ham 0 0.701983 17165.6 1 6 CACCTG TATCTTATCATATCC - +4 cisbp__M4453-CG9650-Dif-dl-ebi-MTA1-like-nej-Stat92E-sv 7 0.701983 17165.6 1 6 CACCTG GTTTCACTTCCTCTT - +4 cisbp__M4472-ey-Poxm-sv-toy 8 0.701983 17165.6 1 6 CACCTG GTCACGCTTGGCTGC - +4 cisbp__M4591-cnc-Jra-kay-Mef2-mor-Myc-NFAT-Stat92E 9 0.701983 17165.6 1 6 CACCTG ATGAGTCATCCCTTT - +4 cisbp__M4641-aop-Stat92E 3 0.701983 17165.6 1 6 CACCTG CATTTCCCGGAAGTG - +4 flyfactorsurvey__her_SOLEXA_10_FBgn0001185-her 6 0.701983 17165.6 1 6 CACCTG TGCTCATAATTGCGT - +4 flyfactorsurvey__lola-PQPJ_SOLEXA_5-lola 5 0.701983 17165.6 1 6 CACCTG CACCAAACATAAAAC - +4 hocomoco__ZN281_HUMAN.H11MO.0.A-Spps-btd-klu-sr 0 0.701983 17165.6 1 6 CACCTG TCCCCTCCCCCACCC - +4 taipale_cyt_meth__HSF2_NGAANNTTCYRGAAN_eDBD_meth-Hsf-pb 7 0.701983 17165.6 1 6 CACCTG GTTCTAGAACGTTCC - +4 taipale_cyt_meth__MAFA_NYGCTGASTCAGCRN_eDBD-cnc-maf-S-tj 9 0.701983 17165.6 1 6 CACCTG TTGCTGACTCAGCAA - +4 taipale_cyt_meth__MAF_NYGCTGASTCAGCRN_FL-cnc-maf-S-tj 9 0.701983 17165.6 1 6 CACCTG TTGCTGACTCAGCAT - +4 transfac_pro__M02745-Eip74EF-Ets21C 1 0.701983 17165.6 1 6 CACCTG TTACTTCCGGGTCCT - +4 transfac_pro__M07308-Mad-Sox14-SoxN 0 0.701983 17165.6 1 6 CACCTG TTCCTTTGTTTTGGA - +4 transfac_pro__M09419-Hsf-pb 7 0.701983 17165.6 1 6 CACCTG CTTCTAGAAGCTTCT - +4 transfac_pro__M07215-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 10 0.701983 17165.6 1 5 CACCTG CTGGACTTTGGACTC + +4 transfac_pro__M09068-Adf1-Taf1 10 0.701983 17165.6 1 5 CACCTG CCGCCGCCACCGCCG + +4 taipale_cyt_meth__ZFP42_NGRCRGCCATMTTGN_eDBD_meth-pho-phol 10 0.701983 17165.6 1 5 CACCTG CCAATATGGCCGCCA - +4 cisbp__M0214-amos-ato-crp-da-Fer3-HLH54F-Oli-tap 2 0.702447 17176.9 1 6 CACCTG AACATATGG + +4 cisbp__M1786 0 0.702447 17176.9 1 6 CACCTG TTCCGGAAA + +4 predrem__nrMotif1190 3 0.702447 17176.9 1 6 CACCTG TGCTGCCTC + +4 predrem__nrMotif2557 2 0.702447 17176.9 1 6 CACCTG TTTACATTA + +4 predrem__nrMotif674 1 0.702447 17176.9 1 6 CACCTG CAGCCTTCC + +4 stark__MAAMNNCAA 0 0.702447 17176.9 1 6 CACCTG AAAAAACAA + +4 taipale__Hoxd9_DBD_CCCATAAAN 0 0.702447 17176.9 1 6 CACCTG CCCATAAAA + +4 cisbp__M0581 2 0.702447 17176.9 1 6 CACCTG GTAACGCGG - +4 cisbp__M6034 0 0.702447 17176.9 1 6 CACCTG CCCATAAAA - +4 fantom__motif103_CGGCTAWWT 3 0.702447 17176.9 1 6 CACCTG AATTAGCCG - +4 jaspar__MA0970.1 2 0.702447 17176.9 1 6 CACCTG GTAACGCGG - +4 predrem__nrMotif1360 0 0.702447 17176.9 1 6 CACCTG AAACAGAAG - +4 predrem__nrMotif1716 2 0.702447 17176.9 1 6 CACCTG AGTCCCTCC - +4 predrem__nrMotif2140 0 0.702447 17176.9 1 6 CACCTG CACTGTCCC - +4 predrem__nrMotif378 1 0.702447 17176.9 1 6 CACCTG ACACTTTCT - +4 predrem__nrMotif935 3 0.702447 17176.9 1 6 CACCTG GAACCCCAG - +4 transfac_pro__M09586-lid-Taf1 1 0.702447 17176.9 1 6 CACCTG CCGCCGCCA - +4 flyfactorsurvey__Zen_Cell_FBgn0004053-eve-zen -1 0.702447 17176.9 1 5 CACCTG CCCTAATGA + +4 predrem__nrMotif1039 4 0.702447 17176.9 1 5 CACCTG ATTTCACAG + +4 predrem__nrMotif1095 4 0.702447 17176.9 1 5 CACCTG TGAACAGCA + +4 predrem__nrMotif2231 -1 0.702447 17176.9 1 5 CACCTG CCCCGTCTC + +4 predrem__nrMotif2262 4 0.702447 17176.9 1 5 CACCTG TCCACAACA + +4 predrem__nrMotif2436 4 0.702447 17176.9 1 5 CACCTG CTCTGATCT + +4 predrem__nrMotif77 4 0.702447 17176.9 1 5 CACCTG ACAGGACTG + +4 swissregulon__sacCer__CHA4 -1 0.702447 17176.9 1 5 CACCTG ATCTCCGCC + +4 hdpi__SEMA4A 4 0.702447 17176.9 1 5 CACCTG CCGCAATCT - +4 predrem__nrMotif1023 4 0.702447 17176.9 1 5 CACCTG ATGTCTCCA - +4 predrem__nrMotif65 4 0.702447 17176.9 1 5 CACCTG TCCAGAGCC - +4 transfac_pro__M03838 4 0.702447 17176.9 1 5 CACCTG GGATTACTT - +4 cisbp__M1271 5 0.702447 17176.9 1 4 CACCTG AACGAAACT + +4 swissregulon__sacCer__PHD1 -2 0.702447 17176.9 1 4 CACCTG CATGCATCA + +4 taipale_cyt_meth__FOSL1_RATGAYACG_FL_meth-kay 5 0.702447 17176.9 1 4 CACCTG AATGACACG + +4 transfac_pro__M01705-pan -2 0.702447 17176.9 1 4 CACCTG CCTTTGATG + +4 hdpi__THAP5 -2 0.702447 17176.9 1 4 CACCTG CCATTCATT - +4 predrem__nrMotif2196 5 0.702447 17176.9 1 4 CACCTG TCAAATACT - +4 predrem__nrMotif2230 5 0.702447 17176.9 1 4 CACCTG TTTATGACA - +4 elemento__CTGGGATTA -3 0.702447 17176.9 1 3 CACCTG CTGGGATTA + +4 predrem__nrMotif1718 6 0.702447 17176.9 1 3 CACCTG AGAGCCAAC + +4 predrem__nrMotif2296 -3 0.702447 17176.9 1 3 CACCTG CTCTAAAAT - +4 stark__GTATNWATA 6 0.702447 17176.9 1 3 CACCTG TATAAATAC - +4 cisbp__M0038 2 0.702858 17187 1 6 CACCTG TGCGCCGCCA + +4 cisbp__M0138 3 0.702858 17187 1 6 CACCTG AAATATTTAT + +4 cisbp__M1148 2 0.702858 17187 1 6 CACCTG ATCACATCAT + +4 cisbp__M1233-vvl 2 0.702858 17187 1 6 CACCTG TATTAATTAT + +4 cisbp__M1557 1 0.702858 17187 1 6 CACCTG TTTTCGAAAA + +4 cisbp__M1577-Sox14-Sox102F-SoxN 3 0.702858 17187 1 6 CACCTG GGAAACAATG + +4 cisbp__M1611-pan 0 0.702858 17187 1 6 CACCTG CCTTTGATGT + +4 cisbp__M5029-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 2 0.702858 17187 1 6 CACCTG GGCACGTGCC + +4 flyfactorsurvey__HLHm5_FlyReg_FBgn0002631-E(spl)m5-HLH-dpn 1 0.702858 17187 1 6 CACCTG GCACGAGACA + +4 homer__AASCACTCAA_Nkx2.5-bap-scro-vnd 3 0.702858 17187 1 6 CACCTG AACCACTCAA + +4 predrem__nrMotif1342 0 0.702858 17187 1 6 CACCTG TTCCCATTTG + +4 predrem__nrMotif1379 0 0.702858 17187 1 6 CACCTG CCCATGCCCC + +4 predrem__nrMotif2027 2 0.702858 17187 1 6 CACCTG CCGGCCTCAC + +4 taipale_cyt_meth__NEUROG2_RNCATATGNY_eDBD-amos-ato-dimm-Fer3-HLH54F-Oli-tap 0 0.702858 17187 1 6 CACCTG AACATATGTT + +4 taipale_cyt_meth__NEUROG2_RNCATATGNY_eDBD_meth-amos-ato-HLH54F-Oli-tap 0 0.702858 17187 1 6 CACCTG GACATATGTC + +4 transfac_pro__M07363-NfI 2 0.702858 17187 1 6 CACCTG GCAGCCAAGA + +4 cisbp__M0531 0 0.702858 17187 1 6 CACCTG TACCCCGCAC - +4 cisbp__M1502 0 0.702858 17187 1 6 CACCTG TGCCGAAATT - +4 cisbp__M1855-Dif-dl 4 0.702858 17187 1 6 CACCTG GGAAAACCCC - +4 cisbp__M4522-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-pnt-RpII215-Sin3A-Taf1 1 0.702858 17187 1 6 CACCTG CCACTTCCGG - +4 fantom__motif145_GMAGWCGMAW 3 0.702858 17187 1 6 CACCTG ATGCGTCTGC - +4 homer__VBSYGTCTGG_Smad4-Med-Smox 3 0.702858 17187 1 6 CACCTG CCAGACGGCC - +4 predrem__nrMotif1642 0 0.702858 17187 1 6 CACCTG TTTCTTTCCA - +4 predrem__nrMotif1823 2 0.702858 17187 1 6 CACCTG CTGGCCTCAT - +4 predrem__nrMotif1971 0 0.702858 17187 1 6 CACCTG CCCCATGAAG - +4 stark__RAAMGGRTTA-Kr 1 0.702858 17187 1 6 CACCTG TAACCCGTTC - +4 swissregulon__sacCer__YRR1 4 0.702858 17187 1 6 CACCTG TTATTTCCGC - +4 taipale_tf_pairs__HES1_GNCACGTGNC_HT-Sidpn 2 0.702858 17187 1 6 CACCTG GGCACGTGCC - +4 transfac_pro__M02040-Ets96B-Ets98B-pnt 0 0.702858 17187 1 6 CACCTG TACATCCGGG - +4 transfac_pro__M04986 0 0.702858 17187 1 6 CACCTG TGCCCGAATG - +4 predrem__nrMotif544 5 0.702858 17187 1 5 CACCTG TTCTTCAGCA + +4 transfac_pro__M00960 5 0.702858 17187 1 5 CACCTG GAAAGAACAG + +4 transfac_pro__M02039-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Taf1 -1 0.702858 17187 1 5 CACCTG ACCGGAAGTG + +4 yetfasco__YKL038W_2227 5 0.702858 17187 1 5 CACCTG CGGAAAAATT + +4 cisbp__M0445 -1 0.702858 17187 1 5 CACCTG TTCTGGGAAA - +4 cisbp__M0718-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.702858 17187 1 5 CACCTG TTGTTTACAT - +4 homer__ADBTAATTAR_Lhx3-Awh-C15-CG4328-CG9876-CG18599-CG34367-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-al-ems-en-eve-ind-inv-lab-lbe-otp-repo-ro-unc-4-unpg-vvl 5 0.702858 17187 1 5 CACCTG CTAATTAATT - +4 predrem__nrMotif1233 5 0.702858 17187 1 5 CACCTG TCTGTCCCCA - +4 predrem__nrMotif358 5 0.702858 17187 1 5 CACCTG AGCAGCACTG - +4 taipale_cyt_meth__SIX3_NSRTATCRYN_eDBD_meth-Optix-so 5 0.702858 17187 1 5 CACCTG CGTGATACGC - +4 transfac_pro__M05845 -1 0.702858 17187 1 5 CACCTG TCCGTCCCCC - +4 cisbp__M5427-Antp-btn-E5-ems-en-eve-inv-pb-Scr-slou-Vsx1-Vsx2 6 0.702858 17187 1 4 CACCTG GCTAATTACC + +4 cisbp__M5428-Antp-E5-ems-en-eve-ind-inv-lab-pb-Scr-slou-Ubx 6 0.702858 17187 1 4 CACCTG GCTAATTACC + +4 taipale__ESX1_DBD_NNYAATTANN-al-Awh-bsh-C15-CG18599-CG34367-CG9876-Dr-E5-ems-en-inv-lab-lbe-Lim3-OdsH-pb-Pph13-repo-slou-Ubx-unc-4-unpg-zfh2 6 0.702858 17187 1 4 CACCTG ACCAATTAAC + +4 transfac_pro__M07665-Trl -2 0.702858 17187 1 4 CACCTG CCTCTCTCCC + +4 cisbp__M0385 6 0.702858 17187 1 4 CACCTG ATTTATACCC - +4 cisbp__M1003-abd-A-Antp-CG4328-Dfd-HGTX-lab-Scr-Ubx 6 0.702858 17187 1 4 CACCTG ATTAATTACC - +4 predrem__nrMotif127 6 0.702858 17187 1 4 CACCTG TATCCAAACA - +4 taipale__EVX1_DBD_NNTNATTANN-Antp-btn-E5-ems-en-eve-inv-pb-Scr-slou 6 0.702858 17187 1 4 CACCTG GCTAATTACC - +4 transfac_pro__M08901-pan -2 0.702858 17187 1 4 CACCTG CCTTTGATGC - +4 transfac_pro__M08905-cbt 6 0.702858 17187 1 4 CACCTG GTACACCCCC - +4 transfac_pro__M05000 7 0.702858 17187 1 3 CACCTG AGGCCGCCAC + +4 taipale_tf_pairs__TEAD4_FOXI1_RCATWCCNNNNNNNNNNNNNRTMAACA_CAP_repr-sd 3 0.70321 17195.6 1 6 CACCTG GCATTCCACGCCCTGCCAACGTAAACA + +4 swissregulon__hs__STAT5_A_B_.p2-Stat92E-bi 0 0.70321 17195.6 1 6 CACCTG CTCTCGGAACTACATTTCCTGGAAATC - +4 tfdimers__MD00476-cnc-foxo-maf-S-slp2 2 0.70321 17195.6 1 6 CACCTG AATAAATGACTCAGCAAACAAAAAAAT - +4 cisbp__M5213-srp 3 0.703793 17209.8 1 6 CACCTG ATCAACCGATAG + +4 flyfactorsurvey__opa_NAR_FBgn0003002-opa 3 0.703793 17209.8 1 6 CACCTG GACCCCCCGCTG + +4 homer__HHCACGCGCBTN_FHY3 2 0.703793 17209.8 1 6 CACCTG TCCACGCGCCTC + +4 swissregulon__hs__HLF.p2-CG7786-Pdp1-gt-vri 3 0.703793 17209.8 1 6 CACCTG GGTTACATAATC + +4 swissregulon__sacCer__YAP1 4 0.703793 17209.8 1 6 CACCTG TGCTTACGAAAG + +4 taipale_cyt_meth__SPDEF_NAMCCGGATGTN_eDBD-Eip74EF-Ets96B-Ets98B 0 0.703793 17209.8 1 6 CACCTG GAACCGGATGTA + +4 tiffin__TIFDMEM0000097 4 0.703793 17209.8 1 6 CACCTG AACAATTCTATT + +4 transfac_pro__M06563 6 0.703793 17209.8 1 6 CACCTG AGGATCGGCCTT + +4 transfac_pro__M06965 1 0.703793 17209.8 1 6 CACCTG AGACGTTAGTCA + +4 cisbp__M2375 0 0.703793 17209.8 1 6 CACCTG TTTCTGTTGCTG - +4 fantom__motif123_TTGATGCAGTGA 0 0.703793 17209.8 1 6 CACCTG TCACTGCATCAA - +4 jaspar__MA0582.1 0 0.703793 17209.8 1 6 CACCTG TTTCTGTTGCTG - +4 neph__UW.Motif.0513 0 0.703793 17209.8 1 6 CACCTG TAGCATTTTTTA - +4 predrem__nrMotif2654 0 0.703793 17209.8 1 6 CACCTG CCCCTCGCTCCC - +4 transfac_pro__M05678 5 0.703793 17209.8 1 6 CACCTG TATTATTCCAGA - +4 transfac_pro__M06167 6 0.703793 17209.8 1 6 CACCTG TCTTCTTCCCCG - +4 transfac_pro__M06181-Jra 4 0.703793 17209.8 1 6 CACCTG GCGTCACCCCGG - +4 transfac_pro__M06302 2 0.703793 17209.8 1 6 CACCTG GCAGCCTTCTCT - +4 transfac_pro__M06322 6 0.703793 17209.8 1 6 CACCTG GCGTCTTTCCGG - +4 transfac_pro__M06395 6 0.703793 17209.8 1 6 CACCTG TCGGACAACCCA - +4 transfac_pro__M06545 6 0.703793 17209.8 1 6 CACCTG TCCCCCCTCCCG - +4 transfac_pro__M06889 6 0.703793 17209.8 1 6 CACCTG GCTCTTCCCCAG - +4 transfac_pro__M06890 6 0.703793 17209.8 1 6 CACCTG GCTCTTCCCCAG - +4 transfac_pro__M09532-Atf6-CrebA-Xbp1 2 0.703793 17209.8 1 6 CACCTG GCCACGTCAGCA - +4 cisbp__M3624-CG12018-Dif-dl-Rel 7 0.703793 17209.8 1 5 CACCTG GGGGACTTTCCA + +4 homer__NRRTGACGTCAT_Atf2-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 7 0.703793 17209.8 1 5 CACCTG ATGACGTCATCG - +4 transfac_pro__M05409 7 0.703793 17209.8 1 5 CACCTG AGTTTAGCAACA - +4 transfac_pro__M05777 7 0.703793 17209.8 1 5 CACCTG GCGTTTGCACAC - +4 transfac_pro__M05977 7 0.703793 17209.8 1 5 CACCTG TCCGCCGCACAG - +4 transfac_pro__M06626 7 0.703793 17209.8 1 5 CACCTG TCTTTTAGTCCC - +4 transfac_pro__M06674 7 0.703793 17209.8 1 5 CACCTG TCATCAGTCCCA - +4 homer__ACTACAATTCCC_GFY-Hcf-Six4-bi-egg-mor 8 0.703793 17209.8 1 4 CACCTG ACTACAATTCCC + +4 transfac_pro__M05743 -2 0.703793 17209.8 1 4 CACCTG TCTGCCCTAACG - +4 transfac_pro__M06613 -2 0.703793 17209.8 1 4 CACCTG TCTGAATCAACC - +4 transfac_pro__M06346 9 0.703793 17209.8 1 3 CACCTG TAATTACGGCAC - +4 cisbp__M2220 7 0.703942 17213.5 1 6 CACCTG ATTTGCTTACGTAAGCTCGT + +4 dbcorrdb__ATF1__ENCSR000DNZ_1__m1-Atf-2-Atf3-Atf6-CG44247-cnc-CoRest-CrebA-CrebB-Jra-kay-Max-Myc-REPTOR-BP-SREBP-Usf-Xbp1 13 0.703942 17213.5 1 6 CACCTG GCGGCGATGACGTCATCCGG + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m1 2 0.703942 17213.5 1 6 CACCTG CGCTCCCGGAATTTCCCCCT + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m2 7 0.703942 17213.5 1 6 CACCTG ACCAGCCAAACTGCATTCTC + +4 dbcorrdb__CREB1__ENCSR000BRB_1__m1-Brf-brm-CrebB-CTCF-E2f1-ERR-E(z)-HDAC1-Jra-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Snr1-SREBP-Taf1-tna-Usf-vtd 5 0.703942 17213.5 1 6 CACCTG GGCGTCACCGCCGGGCGCCG + +4 dbcorrdb__CTCF__ENCSR000DXD_1__m2-CTCF 5 0.703942 17213.5 1 6 CACCTG TGCTGCCCCTTTCCAGCACA + +4 dbcorrdb__ESRRA__ENCSR000DYQ_1__m2-ERR 3 0.703942 17213.5 1 6 CACCTG CTGTGTCTGGAGGACCCACC + +4 dbcorrdb__EZH2__ENCSR000ARE_1__m1-E(z) 2 0.703942 17213.5 1 6 CACCTG CTCCGCTTCGTACACTCGCA + +4 dbcorrdb__GTF2B__ENCSR000DOE_1__m4-Nf-YB-TfIIB 9 0.703942 17213.5 1 6 CACCTG ACGCTAACCAATCGGCGCGC + +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m9 13 0.703942 17213.5 1 6 CACCTG AAGAAAGATCAAATACATGA + +4 dbcorrdb__POLR2A__ENCSR000DKT_1__m1-aop-Atac3-Dif-dl-Eip74EF-RpII215-Sin3A-Su(z)12-Taf1-Taf7-TfIIFalpha 2 0.703942 17213.5 1 6 CACCTG GCCACTTCCGCCTTCGCCGG + +4 dbcorrdb__POLR2A__ENCSR000EZA_1__m1-RpII215 3 0.703942 17213.5 1 6 CACCTG GTGCGCCTGCGCCGTTCGCC + +4 dbcorrdb__RAD21__ENCSR000EHX_1__m5-vtd 13 0.703942 17213.5 1 6 CACCTG ACTGTGCATGGCTCCCCAGG + +4 dbcorrdb__SMARCC1__ENCSR000EDM_1__m1-cnc-CoRest-Jra-kay-maf-S-mor-Myc-pan-Snr1 9 0.703942 17213.5 1 6 CACCTG GGGATGAGTCACCCCCGGCG + +4 dbcorrdb__TAF1__ENCSR000BPF_1__m1-RpII215-Taf1 9 0.703942 17213.5 1 6 CACCTG CGCTTCCGCCGTCGGCGGGG + +4 jaspar__MA0073.1-CTCF-CoRest-ct-peb 8 0.703942 17213.5 1 6 CACCTG CCCCAAACCACCCCCCCCCC + +4 taipale_cyt_meth__FOXB1_NWNWGTMAATATTRACWYWN_eDBD-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.703942 17213.5 1 6 CACCTG TTATGTAAATATTGACATAA + +4 taipale_cyt_meth__FOXB1_NWNWGTMAATATTRACWYWN_eDBD_meth-croc-fd59A-fd96Ca-fd96Cb-fkh-nej 13 0.703942 17213.5 1 6 CACCTG TTATGTAAATATTGACATAA + +4 taipale_tf_pairs__E2F1_HES7_RRCRCGYGYNNNNSGCGCSN_CAP_repr-E2f1 2 0.703942 17213.5 1 6 CACCTG GGCACGTGCCGTTGGCGCCC + +4 transfac_pro__M01492 5 0.703942 17213.5 1 6 CACCTG CCTTAAATCTCCGAGGCCGC + +4 transfac_pro__M01496 7 0.703942 17213.5 1 6 CACCTG ATTTGCTTACGTAAGCTCGT + +4 cisbp__M1901-CoRest-ct-CTCF-peb 8 0.703942 17213.5 1 6 CACCTG CCCCAAACCACCCCCCCCCA - +4 dbcorrdb__ATF3__ENCSR000BPS_1__m5 14 0.703942 17213.5 1 6 CACCTG GATTCGAAATCAGAATCTTT - +4 dbcorrdb__CEBPB__ENCSR000BRQ_1__m1-Irbp18-nej-Xrp1 13 0.703942 17213.5 1 6 CACCTG GCAGAGATTGCACAATCCCA - +4 dbcorrdb__CEBPZ__ENCSR000EDO_1__m3-CG7839 4 0.703942 17213.5 1 6 CACCTG ATTTGTCCTTAATATCCTTA - +4 dbcorrdb__ETS1__ENCSR000BKA_1__m1-CoRest-mor-Six4 3 0.703942 17213.5 1 6 CACCTG GGCCTTCTCGCGAGAGTAGT - +4 dbcorrdb__EZH2__ENCSR000ARI_1__m4-E(z)-Hcf-RpII215 10 0.703942 17213.5 1 6 CACCTG CGGCGGCGGAAACCCGGGCG - +4 dbcorrdb__EZH2__ENCSR000ATA_1__m1-E(z) 14 0.703942 17213.5 1 6 CACCTG CGACGTGCGGCGCGCGCCGC - +4 dbcorrdb__JUND__ENCSR000EGN_1__m1-cnc-CoRest-CrebB-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 12 0.703942 17213.5 1 6 CACCTG GGGGGGATGACTCATCCCTG - +4 dbcorrdb__JUN__ENCSR000EFS_1__m1-cnc-CoRest-CrebB-Jra-kay-maf-S-mor-Myc-pan-Snr1 14 0.703942 17213.5 1 6 CACCTG CCGCGGGGATGACTCATCCC - +4 dbcorrdb__MAX__ENCSR000DYG_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tgo-tna-Usf-vtd 3 0.703942 17213.5 1 6 CACCTG GGGCACGTGGCCGCGGGGGG - +4 dbcorrdb__MYBL2__ENCSR000BRO_1__m2-fd59A-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 3 0.703942 17213.5 1 6 CACCTG AGGTCACTGTTTGCTCAGCG - +4 dbcorrdb__MYC__ENCSR000EGS_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-Max-Myc-pho-phol-RpII215-Sap30-Sin3A-Spps-SREBP-tgo-tna-Usf 5 0.703942 17213.5 1 6 CACCTG GCGGCCACGTGGCCCGCGCG - +4 dbcorrdb__NFATC1__ENCSR000BQL_1__m3-Bgb-Bro-lz-NFAT-run-RunxA-RunxB-Stat92E 4 0.703942 17213.5 1 6 CACCTG TGTGTATTTGTGGTTTTGTG - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m7-RpII215 0 0.703942 17213.5 1 6 CACCTG CACCTCGCCACAAAGGCGGA - +4 dbcorrdb__POLR2A__ENCSR000FAY_1__m1-RpII215-Taf1 1 0.703942 17213.5 1 6 CACCTG GCGCTTCCGCCGTGTGCGCG - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIA_1__m2 11 0.703942 17213.5 1 6 CACCTG CAGCATCGCGGCGGCTGCGA - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BML_1__m1-aop-Atac3-CG10431-CrebB-Dif-dl-E2f1-Eip74EF-ERR-Ets96B-Ets97D-E(z)-FoxP-Hcf-lid-Max-Rbbp5-RpII215-Sin3A-Taf1 4 0.703942 17213.5 1 6 CACCTG GCGGCGCTTCCGCTGCCGGC - +4 dbcorrdb__RCOR1__ENCSR000ECM_1__m4-CoRest 8 0.703942 17213.5 1 6 CACCTG CCGCATGGCAGCTCCCAGAG - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m4-Snr1 3 0.703942 17213.5 1 6 CACCTG AGCATCCTGCACAGAGTCAG - +4 dbcorrdb__SREBF1__ENCSR000DYU_1__m3-SREBP 9 0.703942 17213.5 1 6 CACCTG CTGGGGGCGGTCCGCGCTGC - +4 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m4-Spt20 12 0.703942 17213.5 1 6 CACCTG GGGATATGTTTTCGACCCTT - +4 dbcorrdb__TAF7__ENCSR000BNM_1__m6-Taf7 12 0.703942 17213.5 1 6 CACCTG AGCAGCATGCTGTTACTTAC - +4 dbcorrdb__TBL1XR1__ENCSR000DYZ_1__m4-ebi-MTA1-like-Stat92E 11 0.703942 17213.5 1 6 CACCTG ACCAGAACTGAAACTAGCCA - +4 dbcorrdb__ZC3H11A__ENCSR000EFR_1__m3-Brf-brm-CTCF-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-SREBP-tna-usp-vtd 7 0.703942 17213.5 1 6 CACCTG CCGGCGCCCCCCTGCGGCCG - +4 dbcorrdb__ZNF274__ENCSR000EVX_1__m4 8 0.703942 17213.5 1 6 CACCTG AAAGCCTTTAGCCAGAGCTC - +4 dbcorrdb__ZNF274__ENCSR000EWE_1__m2 7 0.703942 17213.5 1 6 CACCTG GTGGGAAAGCCTTCAGTCAG - +4 hocomoco__ZN547_HUMAN.H11MO.0.C 3 0.703942 17213.5 1 6 CACCTG GTATGCCTGCTGCATTAGCA - +4 transfac_pro__M04807 9 0.703942 17213.5 1 6 CACCTG TGGCCGGCGGGCCTGTCACT - +4 dbcorrdb__ZNF274__ENCSR000EVR_1__m4-egg -1 0.703942 17213.5 1 5 CACCTG CCCTATGAATGCAATGAATG + +4 taipale_cyt_meth__ZBTB43_NGTGCCNNNNNNNYAGCACN_eDBD_repr 16 0.703942 17213.5 1 4 CACCTG AGTGCCATAAAGGCAGCACT + +4 dbcorrdb__CTCF__ENCSR000DLK_1__m2-CTCF 16 0.703942 17213.5 1 4 CACCTG GGCAGTGCAGCACCGCCCCC - +4 taipale_cyt_meth__IRF6_RGTWTCGNNNNNNYGAWACY_eDBD_repr 16 0.703942 17213.5 1 4 CACCTG AGTATCGCTTTACCGAAACT - +4 dbcorrdb__ZNF274__ENCSR000EVG_1__m1 17 0.703942 17213.5 1 3 CACCTG AGACATCAGAGAACTCATAC - +4 transfac_pro__M01400-Dll 10 0.704614 17229.9 1 6 CACCTG TCGCTATAATTACCGAC + +4 transfac_pro__M01470-abd-A-Antp-CG32532-CG4328-Dbx-Dfd-HGTX-lab-Lim3-Lmx1a-Scr-Ubx-vvl 10 0.704614 17229.9 1 6 CACCTG GAAAATTAATTACTTTG + +4 transfac_pro__M02791-svp-usp 6 0.704614 17229.9 1 6 CACCTG TGTCGTGACCCCTTAAT + +4 taipale_cyt_meth__ZNF343_NYGCTTCACCNCGGYMN_eDBD_meth_repr 1 0.704614 17229.9 1 6 CACCTG CTGCCGCGGTGAAGCGG - +4 taipale_tf_pairs__ETV2_FOXI1_RSCGGAANNRYMAACAN_CAP-pnt 10 0.704614 17229.9 1 6 CACCTG ATGTTTACACTTCCGGT - +4 transfac_pro__M01480-Ptx1 9 0.704614 17229.9 1 6 CACCTG GAAATTTAATCCCTCTA - +4 transfac_pro__M09368 -1 0.704614 17229.9 1 5 CACCTG ACTTGTTCCACAAGAAA - +4 hdpi__UBB-CG11700 -1 0.704682 17231.6 1 5 CACCTG TCCCA - +4 cisbp__M1885 -2 0.704682 17231.6 1 4 CACCTG GCTTT - +4 hdpi__DDX53-CG7878 1 0.704682 17231.6 1 4 CACCTG ACACA - +4 hocomoco__STAT6_MOUSE.H11MO.0.A-Stat92E 1 0.705549 17252.8 1 6 CACCTG TTTCCTGAGAACTG + +4 neph__UW.Motif.0269 2 0.705549 17252.8 1 6 CACCTG GAATCCAAAAAAAA + +4 transfac_pro__M09216 1 0.705549 17252.8 1 6 CACCTG GTAAATGTGTCAGA + +4 transfac_pro__M09234-Hsf-pb 6 0.705549 17252.8 1 6 CACCTG TTCTAGAAGCTTCT + +4 cisbp__M4866-CG4404 4 0.705549 17252.8 1 6 CACCTG GCAGTAATTACAGC - +4 hocomoco__AP2D_HUMAN.H11MO.0.D-TfAP-2 3 0.705549 17252.8 1 6 CACCTG ACGCGCCTCGGGCG - +4 hocomoco__RUNX2_HUMAN.H11MO.0.A-Bgb-Bro-CG9650-MTA1-like-RunxA-RunxB-ebi-lz-run 3 0.705549 17252.8 1 6 CACCTG AAAAACCACAGACA - +4 taipale__SOX10_full_TGAATRTKCAGTCA_repr-Sox100B 6 0.705549 17252.8 1 6 CACCTG TGACTGAACATTCA - +4 taipale_cyt_meth__POU3F4_NTAATKAKATGCRN_eDBD-pdm3-vvl 3 0.705549 17252.8 1 6 CACCTG ATGCATCTCATTAA - +4 taipale_tf_pairs__TEAD4_ELK1_RGAATSCGGAAGYN_CAP-sd 0 0.705549 17252.8 1 6 CACCTG CACTTCCGGATTCC - +4 neph__UW.Motif.0625 -1 0.705549 17252.8 1 5 CACCTG TTCTGAGTTACTCA + +4 scertf__spivak.HAP3-CG7839-Chrac-14-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay -2 0.705549 17252.8 1 4 CACCTG TCTGATTGGTTCAG + +4 taipale_cyt_meth__POU1F1_NTATGCWAATKAGN_eDBD_repr-nub-pdm2-pdm3-vvl -2 0.705549 17252.8 1 4 CACCTG CCTCATTTGCATAA - +4 tfdimers__MD00003-pho-phol 7 0.705849 17260.1 1 6 CACCTG TATCTGCTGCCATATGGCGGCAGATA + +4 yetfasco__YDR421W_725 1 0.705849 17260.1 1 6 CACCTG TAACCGAAAATAACCGAAAATAACCG + +4 transfac_pro__M06926-al-oc-Traf4 2 0.706292 17271 1 6 CACCTG TTAATCTGATTAA + +4 transfac_pro__M06934 2 0.706292 17271 1 6 CACCTG ATAATCTGATTAT + +4 transfac_pro__M09312 5 0.706292 17271 1 6 CACCTG ACCGTAACCGTAA + +4 cisbp__M3546 7 0.706292 17271 1 6 CACCTG TGGCCCCCCCCCC - +4 cisbp__M6417 0 0.706292 17271 1 6 CACCTG CTCATGAATATAT - +4 idmmpmm__kni-eg-kni 6 0.706292 17271 1 6 CACCTG TTGCTCTAGTTTT - +4 jaspar__MA0262.1 7 0.706292 17271 1 6 CACCTG AATTCGCAACATT - +4 transfac_pro__M09011-opa 2 0.706292 17271 1 6 CACCTG ACCCCCCGCTGTG - +4 cisbp__M2585-Su(H) 8 0.706292 17271 1 5 CACCTG ACTGTGGGAAACG + +4 cisbp__M5439-croc-fkh-foxo-slp1 8 0.706292 17271 1 5 CACCTG TGTTTATTTACTT - +4 taipale__FOXC1_DBD_ANRTAAAYAAACA-croc-fkh-foxo-slp1 8 0.706292 17271 1 5 CACCTG TGTTTATTTACTT - +4 tfdimers__MD00481-ovo 6 0.706725 17281.6 1 6 CACCTG CCCAGCTCCCTGGGGACAGGG + +4 transfac_pro__M01536-klu-sr 6 0.706725 17281.6 1 6 CACCTG ATGTACTACCCCGCACTTGTG + +4 transfac_pro__M05241-E(z) 10 0.706725 17281.6 1 6 CACCTG GGGGGGGTCCGCCCTGCTCCC + +4 transfac_pro__M09071-Adf1-Taf1 4 0.706725 17281.6 1 6 CACCTG CCGCCGCCTCCGCCGCCGCCG + +4 cisbp__M4295 12 0.706725 17281.6 1 6 CACCTG AGGACTATAGAACACTCTAAA - +4 cisbp__M4358-klu-sr 6 0.706725 17281.6 1 6 CACCTG ATGTACTACCCCGCACTTGTG - +4 taipale_tf_pairs__E2F1_HES7_SRCRCGYGSYNNNNSGCGCSN_CAP_repr-E2f1 13 0.706725 17281.6 1 6 CACCTG GGGCGCCTTGCGGCACGTGCC - +4 tfdimers__MD00444-Sirt6-TfAP-2 11 0.706725 17281.6 1 6 CACCTG TATTAAAGGCTTATCTTTTTT - +4 cisbp__M4618-bi-egg-Hcf-mor-Six4 -2 0.706725 17281.6 1 4 CACCTG CCTGCTGGGAGTTGTAGTTCC + +4 transfac_pro__M00400-Max-Myc-tgo-Usf 10 0.707739 17306.4 1 6 CACCTG CTGCGTCGGCCACGTGGCCCCGACA + +4 transfac_pro__M06733 6 0.707739 17306.4 1 6 CACCTG ATGATAAACTACGATGAAATCGCCG + +4 cisbp__M1034-Dbx 0 0.708304 17320.2 1 6 CACCTG GCAATTA + +4 cisbp__M1036-al-C15-CG11085-CG34367-CG9876-Dr-en-lbe-lms-OdsH-Pph13-repo-Rx-slou-Ubx-unc-4-unpg 1 0.708304 17320.2 1 6 CACCTG CTAATTG + +4 cisbp__M1641-Tbp-Trf-Trf2 1 0.708304 17320.2 1 6 CACCTG ATATAAA + +4 elemento__GATCCTC 1 0.708304 17320.2 1 6 CACCTG GATCCTC + +4 transfac_pro__M09254 0 0.708304 17320.2 1 6 CACCTG GATTTGA - +4 cisbp__M1062-oc 2 0.708304 17320.2 1 5 CACCTG TTAATCC + +4 predrem__nrMotif2610 -1 0.708304 17320.2 1 5 CACCTG ACCAAAA + +4 predrem__nrMotif862 -1 0.708304 17320.2 1 5 CACCTG TTCTTGC + +4 transfac_pro__M09151 2 0.708304 17320.2 1 5 CACCTG GAAATCT + +4 hdpi__TIA1-CG34354-Rox8-trv 2 0.708304 17320.2 1 5 CACCTG TTTGCTT - +4 scertf__badis.GZF3-GATAd-GATAe-grn-pnr-srp 2 0.708304 17320.2 1 5 CACCTG CTTATCA - +4 transfac_pro__M04715-nub-pdm2 2 0.708304 17320.2 1 5 CACCTG TGCAAAT - +4 cisbp__M2198 3 0.708304 17320.2 1 4 CACCTG TGAAACA + +4 hocomoco__SOX15_HUMAN.H11MO.0.D -2 0.708304 17320.2 1 4 CACCTG CATTGTT + +4 predrem__nrMotif1210 3 0.708304 17320.2 1 4 CACCTG TAGCACA + +4 predrem__nrMotif1299 3 0.708304 17320.2 1 4 CACCTG TTTGACA + +4 transfac_pro__M01057-Hcf 3 0.708304 17320.2 1 4 CACCTG CGCCGCC + +4 hdpi__MSI2-Rbp6 -2 0.708304 17320.2 1 4 CACCTG GCTATTT - +4 predrem__nrMotif84 3 0.708304 17320.2 1 4 CACCTG GCTCACA - +4 predrem__nrMotif2020 -3 0.708304 17320.2 1 3 CACCTG CTTTAGC + +4 predrem__nrMotif785 -3 0.708304 17320.2 1 3 CACCTG CTTTGGA + +4 transfac_pro__M04901-nej 4 0.708304 17320.2 1 3 CACCTG ATGACAC + +4 yetfasco__YHL027W_600 -3 0.708304 17320.2 1 3 CACCTG CTTGGCA + +4 predrem__nrMotif777 -3 0.708304 17320.2 1 3 CACCTG CTCTTAA - +4 scertf__harbison.RIM101 -3 0.708304 17320.2 1 3 CACCTG CTTGGCA - +4 cisbp__M2426 5 0.708403 17322.6 1 6 CACCTG TCGGAGCACTGTCCTCCGAACG + +4 transfac_public__M00262 2 0.708403 17322.6 1 6 CACCTG TTTACCCACAATGCATTGCGCC + +4 hocomoco__MAFF_MOUSE.H11MO.0.A-cnc-maf-S-tj 3 0.708403 17322.6 1 6 CACCTG TTTTTGCTGAGTCAGCATTTTT - +4 hocomoco__PATZ1_HUMAN.H11MO.0.C-Brf-CTCF-CoRest-Dif-HDAC1-Klf15-Rbbp5-SREBP-Spps-Spt20-brm-btd-ct-dl-klu-luna-sr 1 0.708403 17322.6 1 6 CACCTG CCTCCCCCCCCGCCCCCTCCCC - +4 tfdimers__MD00545-Sox100B 3 0.708403 17322.6 1 6 CACCTG TTTTTACTTCCCCAAAGTTTAC - +4 tfdimers__MD00146-kn 5 0.708834 17333.1 1 6 CACCTG CTTATTCCCAAGGGATTAAAAGAC + +4 transfac_pro__M00399 10 0.708834 17333.1 1 6 CACCTG GTCGAGGGGACACGTGGCACGACA + +4 hocomoco__ZN264_HUMAN.H11MO.0.C 12 0.708834 17333.1 1 6 CACCTG AATGGGATTAGTGCCCTTATAAGA - +4 taipale_tf_pairs__ELK1_HOXA3_NCCGGWNNNNNNNNNNNSCATTAN_CAP_repr 17 0.708834 17333.1 1 6 CACCTG GTAATGGGTGATACAATTTCCGGT - +4 tfdimers__MD00165-Jra-kay 2 0.708834 17333.1 1 6 CACCTG TATTAATGAATCATTAATCAAAAA - +4 tfdimers__MD00238-cnc-E2f1-maf-S 2 0.708834 17333.1 1 6 CACCTG TAAAAATGACTCAGAAACGAAAAA - +4 tfdimers__MD00494-Sox100B-Tbp 5 0.708834 17333.1 1 6 CACCTG TTTTATTCCTTTGTTTATATAATT - +4 taipale_tf_pairs__E2F3_EOMES_NNGYGNNNNGGCGCSNNNNCRCNN_CAP_repr-E2f1 19 0.708834 17333.1 1 5 CACCTG AGGTGCTAACGCGCCATAACACTT - +4 cisbp__M2425 15 0.709078 17339.1 1 6 CACCTG GTTCGGAGGACAGTCCTCCGATG - +4 tfdimers__MD00299 9 0.70934 17345.5 1 6 CACCTG TATTTTTACTTCCTCTTTTGTTTTCTTTTT - +4 cisbp__M0957-B-H1-B-H2-bsh-CG34367-Dr-en-inv-lab-unpg-Vsx2 0 0.709756 17355.7 1 6 CACCTG TAATTGGT + +4 cisbp__M0964-abd-A-Antp-cad-ftz-Scr-Ubx 1 0.709756 17355.7 1 6 CACCTG TTAATGGC + +4 predrem__nrMotif1449 1 0.709756 17355.7 1 6 CACCTG GCAATTTT + +4 taipale_cyt_meth__GSX1_CTAATTAC_eDBD-abd-A-Antp-ap-CG4328-Dfd-E5-ems-en-eve-ind-Lmx1a-Scr-Ubx 0 0.709756 17355.7 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXA6_RTCGTTAN_eDBD_meth_repr-abd-A-btn-Dfd-Dll-exex-Ubx 0 0.709756 17355.7 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__PITX2_NTAATCCN_eDBD-Ptx1 2 0.709756 17355.7 1 6 CACCTG CTAATCCC + +4 taipale_cyt_meth__TGIF2_NTGACAGN_FL-achi-vis 2 0.709756 17355.7 1 6 CACCTG GTGACAGC + +4 transfac_pro__M00315 0 0.709756 17355.7 1 6 CACCTG CCTCATTC + +4 transfac_public__M00499-Stat92E 2 0.709756 17355.7 1 6 CACCTG CATTTCTT + +4 cisbp__M0170 0 0.709756 17355.7 1 6 CACCTG CGCGTGTC - +4 cisbp__M0546-cbt-klu-sr 0 0.709756 17355.7 1 6 CACCTG CGCCCACG - +4 cisbp__M1211-achi-vis 2 0.709756 17355.7 1 6 CACCTG GTGACAGC - +4 cisbp__M3988-Stat92E 2 0.709756 17355.7 1 6 CACCTG CATTTCTT - +4 elemento__AATGTCAA 2 0.709756 17355.7 1 6 CACCTG TTGACATT - +4 elemento__CAAGATCA 1 0.709756 17355.7 1 6 CACCTG TGATCTTG - +4 elemento__CAATGTCA 1 0.709756 17355.7 1 6 CACCTG TGACATTG - +4 flyfactorsurvey__brk_FlyReg_FBgn0024250-brk 2 0.709756 17355.7 1 6 CACCTG GGCGCCAG - +4 cisbp__M0005 3 0.709756 17355.7 1 5 CACCTG CGCCGCCG + +4 jaspar__MA0011.1-br -1 0.709756 17355.7 1 5 CACCTG TACTATTT + +4 jaspar__MA1049.1 3 0.709756 17355.7 1 5 CACCTG CGCCGCCG + +4 transfac_pro__M00493-Stat92E 3 0.709756 17355.7 1 5 CACCTG TATTTCCT + +4 transfac_pro__M01810-sd -1 0.709756 17355.7 1 5 CACCTG ACATTCTC + +4 cisbp__M1845-br -1 0.709756 17355.7 1 5 CACCTG TACTATTT - +4 cisbp__M3975-Stat92E 3 0.709756 17355.7 1 5 CACCTG GGATTCCC - +4 flyfactorsurvey__So_SOLEXA_FBgn0003460-so 3 0.709756 17355.7 1 5 CACCTG TATCATAT - +4 hocomoco__MAFG_HUMAN.H11MO.1.A-cnc-maf-S 3 0.709756 17355.7 1 5 CACCTG ACTCAGCA - +4 jaspar__MA0405.1 3 0.709756 17355.7 1 5 CACCTG GCGGACAT - +4 predrem__nrMotif43 3 0.709756 17355.7 1 5 CACCTG ATTCAGCA - +4 transfac_pro__M07728-ebi-GATAd-GATAe-grn-pnr-srp 3 0.709756 17355.7 1 5 CACCTG CCTTATCA - +4 c2h2_zfs__M3913-bowl-odd -2 0.709756 17355.7 1 4 CACCTG GCTACTGG - +4 cisbp__M1938 4 0.709756 17355.7 1 4 CACCTG CCGTCAGC - +4 cisbp__M4730-Aef1 4 0.709756 17355.7 1 4 CACCTG CAACAACA - +4 neph__UW.Motif.0148 4 0.709756 17355.7 1 4 CACCTG TAATCCCC - +4 scertf__badis.STP4 4 0.709756 17355.7 1 4 CACCTG GCGCTATC - +4 factorbook__GFI1-sens-2 -3 0.709756 17355.7 1 3 CACCTG CTGTGATT - +4 neph__UW.Motif.0053 -3 0.709756 17355.7 1 3 CACCTG CTCTCTCT - +4 taipale_tf_pairs__TEAD4_ALX4_GGAATGNNNNNYTAATTA_CAP_repr-sd 10 0.711558 17399.7 1 6 CACCTG TAATTAGTTTAACATTCC - +4 transfac_pro__M06835-CG4730-CG7101 8 0.711558 17399.7 1 6 CACCTG CCATAATCTTCCTACTCC - +4 fantom__motif47_CGAGTN 0 0.712611 17425.5 1 6 CACCTG AACTCG - +4 hdpi__ASCC1-CG12129 0 0.712611 17425.5 1 6 CACCTG CTCCCC - +4 hdpi__ACO1-Irp-1A-Irp-1B 1 0.712611 17425.5 1 5 CACCTG AAAACG + +4 cisbp__M2027-ct 2 0.712611 17425.5 1 4 CACCTG TTGAAC + +4 jaspar__MA0218.1-ct 2 0.712611 17425.5 1 4 CACCTG TTGAAC + +4 fantom__motif12_ACTAAG -3 0.712611 17425.5 1 3 CACCTG CTTAGT - +4 hdpi__ECSIT-ECSIT -3 0.712611 17425.5 1 3 CACCTG CTATTC - +4 hocomoco__PRDM4_HUMAN.H11MO.0.D 6 0.712646 17426.3 1 6 CACCTG GGGGGGGGCCTTGAAA + +4 homer__CTTGGCACNGTGCCAA_NF1-Nf1-NfI-nau 10 0.712646 17426.3 1 6 CACCTG CTTGGCACTGTGCCAA + +4 transfac_pro__M02834-CG7368-CTCF 10 0.712646 17426.3 1 6 CACCTG CCCCCCCCCCCACTTG + +4 transfac_pro__M02849 10 0.712646 17426.3 1 6 CACCTG TAGTATTTCCGATCTT + +4 transfac_pro__M05395 9 0.712646 17426.3 1 6 CACCTG GGATTTGTCCAACTGA + +4 cisbp__M5848-D-Sox100B-Sox21a-Sox21b 7 0.712646 17426.3 1 6 CACCTG ATCACTGCACATTGAT - +4 taipale_cyt_meth__BCL6B_RYGTAATCGAGGAATW_eDBD 2 0.712646 17426.3 1 6 CACCTG AATTCCTCGATTACGC - +4 transfac_pro__M09381 6 0.712646 17426.3 1 6 CACCTG TTGCTTCATCTTCAAG - +4 taipale_cyt_meth__PAX7_NSGTCACGSNWRTTAN_eDBD_meth_repr-gsb-gsb-n-prd-sv 11 0.712646 17426.3 1 5 CACCTG TTAATAACCGTGACGA - +4 cisbp__M4539-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Sin3A-Taf1 0 0.713475 17446.6 1 6 CACCTG GGCCGGAAGTG + +4 cisbp__M6186-CG7786-gt-Pdp1-vri 3 0.713475 17446.6 1 6 CACCTG TGTTACATAAC + +4 hocomoco__HXD8_HUMAN.H11MO.0.D-acj6-nub-pdm2-vvl 5 0.713475 17446.6 1 6 CACCTG TAATTTGCATA + +4 predrem__nrMotif1616 0 0.713475 17446.6 1 6 CACCTG AAACTCTGTGT + +4 predrem__nrMotif2537 5 0.713475 17446.6 1 6 CACCTG CCCGGCTCCGG + +4 taipale_cyt_meth__KLF3_NRCCRCGCCCN_FL-btd-CG3065-CG42741-dar1-luna-Spps 0 0.713475 17446.6 1 6 CACCTG GACCACGCCCA + +4 taipale_cyt_meth__PROP1_TAATTNNATTA_eDBD_meth-al-CG11294-CG32532-CG9876-Dr-Drgx-en-inv-OdsH-Optix-repo-Traf4-unc-4 0 0.713475 17446.6 1 6 CACCTG TAATTGGATTA + +4 tiffin__TIFDMEM0000075 1 0.713475 17446.6 1 6 CACCTG TAAAATTAAAA + +4 transfac_pro__M09291 1 0.713475 17446.6 1 6 CACCTG ATAACCGAATT + +4 cisbp__M0368 4 0.713475 17446.6 1 6 CACCTG CGTGCACGGGC - +4 cisbp__M1574 5 0.713475 17446.6 1 6 CACCTG GTCCAGACACT - +4 cisbp__M1903-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Sin3A-Taf1 1 0.713475 17446.6 1 6 CACCTG CCACTTCCGGC - +4 cisbp__M3226-ham-srp 1 0.713475 17446.6 1 6 CACCTG TTATCTTATCT - +4 cisbp__M4890-btd-cbt-CG3065-CG42741-dar1-luna-Sp1-Spps 5 0.713475 17446.6 1 6 CACCTG GGCCACGCCCA - +4 flyfactorsurvey__CG9895_SOLEXA_5_FBgn0034810-CG3065-CG42741-Sp1-Spps-btd-cbt-dar1-luna 5 0.713475 17446.6 1 6 CACCTG GGCCACGCCCA - +4 flyfactorsurvey__klu_SOLEXA_F2-4-Spps-btd-cbt-klu-sr 2 0.713475 17446.6 1 6 CACCTG CCCGCCCACAC - +4 hocomoco__DBP_HUMAN.H11MO.0.B-CG7786-Pdp1-gt-vri 3 0.713475 17446.6 1 6 CACCTG TGTTACATAAC - +4 predrem__nrMotif437 0 0.713475 17446.6 1 6 CACCTG TTGCTTTCAAA - +4 tiffin__TIFDMEM0000100 5 0.713475 17446.6 1 6 CACCTG TTGAATACTTT - +4 transfac_pro__M07821-Ptx1 5 0.713475 17446.6 1 6 CACCTG GGGATTAACGT - +4 transfac_pro__M09244 1 0.713475 17446.6 1 6 CACCTG ATAAATGATTG - +4 cisbp__M1322 6 0.713475 17446.6 1 5 CACCTG TCCGGATATCC + +4 taipale_cyt_meth__SOX12_ACCGAACAATN_eDBD_meth-Sox14 -1 0.713475 17446.6 1 5 CACCTG ACCGAACAATG + +4 stark__CATNANTYAAA -2 0.713475 17446.6 1 4 CACCTG CATAAATCAAA + +4 stark__CATNNNNCGCG -2 0.713475 17446.6 1 4 CACCTG CATAAAACGCG + +4 taipale_cyt_meth__HOXB13_NCTCGTAAAAN_eDBD -2 0.713475 17446.6 1 4 CACCTG CCTCGTAAAAC + +4 neph__UW.Motif.0085 -2 0.713475 17446.6 1 4 CACCTG GCTGTGTTTTC - +4 swissregulon__hs__NFKB1_REL_RELA.p2-Dif-Rel-dl 7 0.713475 17446.6 1 4 CACCTG GGGAAAGCCCC - +4 taipale_cyt_meth__HOXA11_NRTCGTAAAAN_eDBD-Abd-B-cad 7 0.713475 17446.6 1 4 CACCTG ATTTTACGACC - +4 transfac_pro__M06837 8 0.713475 17446.6 1 3 CACCTG TGCTGTCCCAC + +4 tfdimers__MD00443-klu-SREBP 16 0.713832 17455.3 1 6 CACCTG CCCCCCCCCCCCCCCCCACCCCCCCCCCC + +4 transfac_pro__M05440 -1 0.716967 17532 1 5 CACCTG ACGGGAGGCATCATCTTTA - +4 tfdimers__MD00506-GATAe-grn-pnr-Pur-alpha 13 0.717693 17549.7 1 6 CACCTG ATTTTCCTCTAATCCCCTTCCCCTTTCT - +4 cisbp__M0895-ap-Awh-CG11085-CG18599-E5-ems-en-inv-lbl-Lim1-slou 2 0.717864 17553.9 1 6 CACCTG CTAATTAGT + +4 cisbp__M0926-Antp-bsh-Scr 2 0.717864 17553.9 1 6 CACCTG TTAATTGCT + +4 cisbp__M1168 3 0.717864 17553.9 1 6 CACCTG ACCAATCAA + +4 cisbp__M1586-Sox15 3 0.717864 17553.9 1 6 CACCTG ATTCATCCT + +4 predrem__nrMotif1058 3 0.717864 17553.9 1 6 CACCTG TGGCACAAA + +4 predrem__nrMotif2303 1 0.717864 17553.9 1 6 CACCTG AGACATTCT + +4 swissregulon__hs__MSX1_2.p2-Dr 3 0.717864 17553.9 1 6 CACCTG CTGTAATTG + +4 transfac_pro__M00666-Sry-beta 2 0.717864 17553.9 1 6 CACCTG CGCATCTCT + +4 transfac_pro__M00701-Smox 0 0.717864 17553.9 1 6 CACCTG TGTCTGTCT + +4 transfac_public__M00227 2 0.717864 17553.9 1 6 CACCTG TCTAACGGC + +4 cisbp__M1009-abd-A-Antp-bsh-btn-cad-Dfd-ftz-HGTX-lab-pb-Scr-Ubx-zen2 1 0.717864 17553.9 1 6 CACCTG GGCCATTAA - +4 cisbp__M4095 2 0.717864 17553.9 1 6 CACCTG TCTAACGGC - +4 predrem__nrMotif1749 2 0.717864 17553.9 1 6 CACCTG AACTCCTTA - +4 predrem__nrMotif423 3 0.717864 17553.9 1 6 CACCTG TGTCACAAA - +4 predrem__nrMotif453 0 0.717864 17553.9 1 6 CACCTG CACAAGAAA - +4 predrem__nrMotif469 0 0.717864 17553.9 1 6 CACCTG AATCTCTCT - +4 predrem__nrMotif576 1 0.717864 17553.9 1 6 CACCTG AGACCAGCC - +4 predrem__nrMotif1626 -1 0.717864 17553.9 1 5 CACCTG CCCACTCCA + +4 predrem__nrMotif1657 -1 0.717864 17553.9 1 5 CACCTG CACTGGGCA + +4 predrem__nrMotif1903 -1 0.717864 17553.9 1 5 CACCTG CCCAGTGCT + +4 predrem__nrMotif2179 4 0.717864 17553.9 1 5 CACCTG ATATCCCCA + +4 predrem__nrMotif2621 -1 0.717864 17553.9 1 5 CACCTG ATCTTTGCA + +4 predrem__nrMotif2635 -1 0.717864 17553.9 1 5 CACCTG GCCCGAGCC + +4 predrem__nrMotif123 -1 0.717864 17553.9 1 5 CACCTG GACTGATTT - +4 predrem__nrMotif210 4 0.717864 17553.9 1 5 CACCTG TGAAAACAT - +4 stark__YAATKAAGY -1 0.717864 17553.9 1 5 CACCTG ACTTAATTA - +4 taipale_cyt_meth__TCF7L1_ASATCAAAS_eDBD_meth_repr-pan 4 0.717864 17553.9 1 5 CACCTG CTTTGATCT - +4 predrem__nrMotif2444 -2 0.717864 17553.9 1 4 CACCTG ACTTGTGCA + +4 predrem__nrMotif371 5 0.717864 17553.9 1 4 CACCTG TTTTCCCCC + +4 cisbp__M0097 -2 0.717864 17553.9 1 4 CACCTG CCTGCATCA - +4 predrem__nrMotif1306 5 0.717864 17553.9 1 4 CACCTG TTTCTTACA - +4 predrem__nrMotif297 -2 0.717864 17553.9 1 4 CACCTG GCTCTGCTC - +4 predrem__nrMotif325 -2 0.717864 17553.9 1 4 CACCTG TCTTGCAGA - +4 predrem__nrMotif655 5 0.717864 17553.9 1 4 CACCTG GGGAACTCC - +4 transfac_public__M00211 5 0.717864 17553.9 1 4 CACCTG GAGACCACA - +4 flyfactorsurvey__opa_SOLEXA_FBgn0003002-lmd-opa-sug 6 0.718455 17568.4 1 6 CACCTG CCAGACCCCCCGCGG + +4 hocomoco__HXB2_HUMAN.H11MO.0.D-Hsf-pb 3 0.718455 17568.4 1 6 CACCTG TAGAACATTCTAGAA + +4 neph__UW.Motif.0615 2 0.718455 17568.4 1 6 CACCTG GAATTCTCAGCCCCA + +4 taipale_cyt_meth__MAFA_NTGCTGANTCAGCAN_eDBD_meth-cnc-maf-S-tj 9 0.718455 17568.4 1 6 CACCTG TTGCTGAGTCAGCAT + +4 transfac_pro__M07799-Gsc 9 0.718455 17568.4 1 6 CACCTG TAATCCTTTAATCCC + +4 transfac_pro__M09076-Adf1-Taf1 1 0.718455 17568.4 1 6 CACCTG CCACCGCCGCCGCCA + +4 transfac_pro__M09375 0 0.718455 17568.4 1 6 CACCTG AGCGTGAAGAAGAAG + +4 cisbp__M5080-lmd-opa-sug 2 0.718455 17568.4 1 6 CACCTG CAGACCCCCCACAGA - +4 cisbp__M6540 4 0.718455 17568.4 1 6 CACCTG CCACCACCGCTATTG - +4 flyfactorsurvey__lmd_SOLEXA_5_FBgn0039039-lmd-opa-sug 2 0.718455 17568.4 1 6 CACCTG CAGACCCCCCACAGA - +4 hocomoco__PBX2_HUMAN.H11MO.0.C 8 0.718455 17568.4 1 6 CACCTG CCATCAATCAATTTA - +4 hocomoco__ZBTB4_HUMAN.H11MO.1.D 4 0.718455 17568.4 1 6 CACCTG CCACCACCGCTATTG - +4 swissregulon__hs__BACH2.p2-CoRest-Jra-Myc-Snr1-cnc-kay-maf-S-mor-pan 9 0.718455 17568.4 1 6 CACCTG GCCATGACTCACCGT - +4 taipale_cyt_meth__HSF1_NGAANNTTCNNGAAN_FL_repr-Hsf-pb-srl 7 0.718455 17568.4 1 6 CACCTG GTTCTAGAACGTTCC - +4 taipale_cyt_meth__HSF1_NGAANNTTCYRGAAN_FL_meth-Hsf-pb 7 0.718455 17568.4 1 6 CACCTG GTTCTAGAACGTTCC - +4 taipale_cyt_meth__HSF2_NGAANNTTCNNGAAN_eDBD-Hsf-pb 7 0.718455 17568.4 1 6 CACCTG GTTCTAGAACGTTCG - +4 taipale_tf_pairs__GCM1_ELK1_RTGCGGGCGGAAGTN_CAP_2-gcm-gcm2 0 0.718455 17568.4 1 6 CACCTG CACTTCCGCCCGCAT - +4 transfac_pro__M02879 9 0.718455 17568.4 1 6 CACCTG ATATTTTTGCAATTG - +4 transfac_pro__M09239-Hsf-pb 7 0.718455 17568.4 1 6 CACCTG CTTCTAGAAGCTTCT - +4 transfac_public__M00195-acj6-nub-pdm2-vvl 6 0.718455 17568.4 1 6 CACCTG GTGATTTGCATATTT - +4 yetfasco__YDR034C_133 2 0.718455 17568.4 1 6 CACCTG AATTCCGCCGGAATT - +4 cisbp__M1936-btd-EcR-eg-HDAC1-Hnf4-Hr51-Hr78-kni-knrl-nej-Spps-svp-usp 10 0.718455 17568.4 1 5 CACCTG CTGGACTTTGAACTC + +4 cisbp__M2398 10 0.718455 17568.4 1 5 CACCTG TATCACTATAAACGA + +4 taipale_cyt_meth__IRF4_NYGAAASYGAAASYN_FL 10 0.718455 17568.4 1 5 CACCTG CCGAAACCGAAACTA + +4 taipale_cyt_meth__IRF8_NYGAAASYGAAASYN_eDBD_meth 10 0.718455 17568.4 1 5 CACCTG ACGAAACCGAAACTA + +4 taipale_cyt_meth__ZNF821_NRGACRGACRGACRN_FL-peb 10 0.718455 17568.4 1 5 CACCTG CGGACAGACAGACAT + +4 cisbp__M4625-bon-cnc-CoRest-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-Stat92E 10 0.718455 17568.4 1 5 CACCTG AAGTATGAGTCATCA - +4 taipale__HNF1B_full_NRTTAATNATTAACN 11 0.718455 17568.4 1 4 CACCTG AGTTAATGATTAACT + +4 taipale__RFX3_DBD_SGTTGCYARGCAACS-CG9727-Rfx 11 0.718455 17568.4 1 4 CACCTG CGTTGCTAGGCAACC + +4 cisbp__M5523 11 0.718455 17568.4 1 4 CACCTG AGTTAATGATTAACT - +4 cisbp__M1121-CG4328-Lmx1a 1 0.718602 17572 1 6 CACCTG ATTAATTAAT + +4 cisbp__M1169 4 0.718602 17572 1 6 CACCTG AACCAATCAG + +4 cisbp__M1189-Antp-Awh-CG4328-CG11085-CG18599-CG32532-CG34367-Dfd-Dr-Lim3-Lmx1a-OdsH-Scr-al-en-ey-gsb-gsb-n-inv-otp-pdm3-prd-repo-slou-toy-unc-4-vvl-zfh2 1 0.718602 17572 1 6 CACCTG ATTAATTAAT + +4 cisbp__M1230-vvl 2 0.718602 17572 1 6 CACCTG TATGAATTAT + +4 cisbp__M1247-vvl 2 0.718602 17572 1 6 CACCTG TATGAATTAT + +4 cisbp__M1520-NFAT 3 0.718602 17572 1 6 CACCTG ATTTTCCATT + +4 cisbp__M1672-bab1 4 0.718602 17572 1 6 CACCTG AAATTAATTT + +4 cisbp__M5281-zen 4 0.718602 17572 1 6 CACCTG CATTAAAATT + +4 flyfactorsurvey__zen_FlyReg_FBgn0004053-zen 4 0.718602 17572 1 6 CACCTG CATTAAAATT + +4 homer__ATCACCCCAT_Srebp1a-SREBP 4 0.718602 17572 1 6 CACCTG ATCACCCCAT + +4 jaspar__MA0624.1-NFAT 3 0.718602 17572 1 6 CACCTG ATTTTCCATT + +4 predrem__nrMotif1763 0 0.718602 17572 1 6 CACCTG TGTCTTTGGA + +4 taipale_cyt_meth__HOXA9_RTCGTAAANN_FL-cad 0 0.718602 17572 1 6 CACCTG GTCGTAAACG + +4 taipale_cyt_meth__SIX1_NSRTATCRYN_eDBD-Optix-Six4-so 3 0.718602 17572 1 6 CACCTG CCGTATCATT + +4 transfac_pro__M06841 3 0.718602 17572 1 6 CACCTG GTTATCCTCA + +4 cisbp__M0119 4 0.718602 17572 1 6 CACCTG TAATTATATA - +4 cisbp__M0678 4 0.718602 17572 1 6 CACCTG TGCGCGCCAA - +4 cisbp__M1158-abd-A-Abd-B-cad-Dbx-eve-Ubx 3 0.718602 17572 1 6 CACCTG TTTTATGACC - +4 cisbp__M1245-dve-nub-pdm2-vvl 3 0.718602 17572 1 6 CACCTG ATGCTAATTA - +4 cisbp__M1507 0 0.718602 17572 1 6 CACCTG AGCCAAAATT - +4 cisbp__M1766 4 0.718602 17572 1 6 CACCTG CTCGGATTTT - +4 cisbp__M1782 0 0.718602 17572 1 6 CACCTG CTCGCGTTGT - +4 cisbp__M5652-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.718602 17572 1 6 CACCTG ACCATATGGC - +4 cisbp__M5989-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.718602 17572 1 6 CACCTG AACATATGTT - +4 hocomoco__STA5A_MOUSE.H11MO.0.A-Stat92E 1 0.718602 17572 1 6 CACCTG TTTCTTGGAA - +4 homer__TGCGTGGGYG_Egr1-klu-sr 0 0.718602 17572 1 6 CACCTG CACCCACGCA - +4 jaspar__MA0023.1-Dif-dl 4 0.718602 17572 1 6 CACCTG GGAAAACCCC - +4 predrem__nrMotif1027 3 0.718602 17572 1 6 CACCTG GGCGCCCTCC - +4 predrem__nrMotif1128 0 0.718602 17572 1 6 CACCTG TGACTGCTCT - +4 predrem__nrMotif2679 1 0.718602 17572 1 6 CACCTG TGACCCAAAA - +4 predrem__nrMotif943 0 0.718602 17572 1 6 CACCTG TGCCTTGTTT - +4 taipale__NEUROD2_full_NNCATATGNN-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.718602 17572 1 6 CACCTG ACCATATGGC - +4 transfac_pro__M02075-Eip74EF-Ets65A-Ets96B-Ets98B-pnt 0 0.718602 17572 1 6 CACCTG TACATCCGGT - +4 transfac_pro__M07065-Stat92E 2 0.718602 17572 1 6 CACCTG TTTCCCGGAA - +4 predrem__nrMotif403 5 0.718602 17572 1 5 CACCTG CTGTGCCCCA + +4 predrem__nrMotif448 5 0.718602 17572 1 5 CACCTG GAGCCCACTC + +4 predrem__nrMotif487 5 0.718602 17572 1 5 CACCTG CTTCACTCCC + +4 taipale_cyt_meth__HOXA9_GYAATAAANN_FL_meth-abd-A-Abd-B-cad-Ubx 5 0.718602 17572 1 5 CACCTG GCCATTAACG + +4 taipale_cyt_meth__HOXA9_GYAATAAANN_FL_repr-abd-A-Abd-B-cad-Ubx 5 0.718602 17572 1 5 CACCTG GCCATTAACC + +4 transfac_pro__M05299 -1 0.718602 17572 1 5 CACCTG ACCGTTTTGT + +4 cisbp__M0509 5 0.718602 17572 1 5 CACCTG GGCGCCACAG - +4 cisbp__M0752-bin-bs-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.718602 17572 1 5 CACCTG TTGTTTACAT - +4 predrem__nrMotif1180 -1 0.718602 17572 1 5 CACCTG CCCAGCTCTG - +4 predrem__nrMotif1485 -1 0.718602 17572 1 5 CACCTG TCTTGGGTTT - +4 predrem__nrMotif1546 5 0.718602 17572 1 5 CACCTG CATGCCCCCA - +4 predrem__nrMotif521 5 0.718602 17572 1 5 CACCTG TTAAAGACAA - +4 predrem__nrMotif703 5 0.718602 17572 1 5 CACCTG CCCAGCACAC - +4 taipale_cyt_meth__SIX3_NSSTATCRYN_eDBD-Optix-so 5 0.718602 17572 1 5 CACCTG GATGATACGG - +4 homer__YCTTTGTTCC_Sox4-Sox14-Sox100B-SoxN -2 0.718602 17572 1 4 CACCTG CCTTTGTTCC + +4 neph__UW.Motif.0537 6 0.718602 17572 1 4 CACCTG TGGAAACACA + +4 taipale__HOXA2_DBD_NNYMATTANN-Antp-Awh-btn-CG18599-E5-ems-en-eve-inv-lab-lbl-Lim3-pb-ro-Scr-slou-Ubx-unpg 6 0.718602 17572 1 4 CACCTG CCTAATTACC + +4 cisbp__M1153-Antp-Awh-E5-Lim3-Scr-ems-eve-ind-lab-pb-unpg-zen2 -2 0.718602 17572 1 4 CACCTG CTTAATTAGT - +4 hocomoco__JUN_MOUSE.H11MO.0.A-Jra-Mef2-Myc-brm-cnc-kay-mor-nej-pan 6 0.718602 17572 1 4 CACCTG GTGACTCACC - +4 taipale__EVX2_DBD_NNTNATTANN-Antp-E5-ems-en-eve-ind-inv-lab-pb-Scr-slou-Ubx-unpg 6 0.718602 17572 1 4 CACCTG GCTAATTACC - +4 transfac_pro__M04633-arm-pan -2 0.718602 17572 1 4 CACCTG TCTTTGATGT - +4 cisbp__M4748-Atf6-CrebA-Xbp1 3 0.719745 17599.9 1 6 CACCTG GCTGACGTGGCA + +4 cisbp__M6536-Xbp1 0 0.719745 17599.9 1 6 CACCTG GACGTGTCATTA + +4 hocomoco__XBP1_MOUSE.H11MO.0.C-Xbp1 0 0.719745 17599.9 1 6 CACCTG GACGTGTCATTA + +4 taipale_cyt_meth__JUN_NATGACGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.719745 17599.9 1 6 CACCTG GATGACGTCATC + +4 taipale_cyt_meth__MESP2_NAMCATATGKYN_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.719745 17599.9 1 6 CACCTG CAACATATGGCG + +4 taipale_cyt_meth__POU2F2_NTGCATATGCAN_eDBD_repr-nub-pdm2-vvl 3 0.719745 17599.9 1 6 CACCTG ATGCATATGCAT + +4 transfac_pro__M06222 6 0.719745 17599.9 1 6 CACCTG TGGGGCTACCGA + +4 transfac_pro__M06384 4 0.719745 17599.9 1 6 CACCTG TGTTAACCCGCA + +4 transfac_pro__M06763-CG3281 6 0.719745 17599.9 1 6 CACCTG TGGGAAAACCGG + +4 transfac_pro__M06968 3 0.719745 17599.9 1 6 CACCTG TGGGAGCTCCCC + +4 transfac_public__M00356-Atf6-CrebA-Xbp1 3 0.719745 17599.9 1 6 CACCTG GATGACGTGGCA + +4 cisbp__M2259-opa 3 0.719745 17599.9 1 6 CACCTG GACCCCCCGCTG - +4 cisbp__M6491-Stat92E 2 0.719745 17599.9 1 6 CACCTG AATTCCTGGAAA - +4 hocomoco__OTX2_MOUSE.H11MO.0.A-Ptx1-bcd-oc 3 0.719745 17599.9 1 6 CACCTG TTAATCCTCTTA - +4 homer__CTATAAAAGCSV_TATA-box-RpII215-Taf1-Tbp 0 0.719745 17599.9 1 6 CACCTG CGGCTTTTATAG - +4 homer__GAAASYGAAASY_IRF2-Blimp-1-Stat92E-ebi 5 0.719745 17599.9 1 6 CACCTG ACTTTCACTTTC - +4 tiffin__TIFDMEM0000016 3 0.719745 17599.9 1 6 CACCTG TTTTAAATTTCG - +4 transfac_pro__M05478 5 0.719745 17599.9 1 6 CACCTG GTTGCTACCCAC - +4 transfac_pro__M05731-CG12071 6 0.719745 17599.9 1 6 CACCTG GCGTTCCCCCCA - +4 transfac_pro__M06074 6 0.719745 17599.9 1 6 CACCTG GCGTCCTTCCCA - +4 transfac_pro__M06542-crol 6 0.719745 17599.9 1 6 CACCTG GATTATCAACAT - +4 transfac_pro__M06767 7 0.719745 17599.9 1 5 CACCTG CTGTGAAGACGT + +4 transfac_pro__M00941-Mef2-rump 7 0.719745 17599.9 1 5 CACCTG TTAAAAATAGCC - +4 transfac_pro__M05629 7 0.719745 17599.9 1 5 CACCTG GGGGCTCGATCA - +4 transfac_pro__M05682 7 0.719745 17599.9 1 5 CACCTG GTAGCCGTACAG - +4 transfac_pro__M05700 7 0.719745 17599.9 1 5 CACCTG GCAGCAGCCCCA - +4 transfac_pro__M05978-CG2120 -1 0.719745 17599.9 1 5 CACCTG AACTCCAAAGCT - +4 transfac_pro__M06055 7 0.719745 17599.9 1 5 CACCTG TGGTCTTCCCCA - +4 transfac_pro__M06064 7 0.719745 17599.9 1 5 CACCTG GCTTTCCCAACT - +4 transfac_pro__M06234 7 0.719745 17599.9 1 5 CACCTG GCGGCATCCCCT - +4 transfac_pro__M06783 7 0.719745 17599.9 1 5 CACCTG CCGCCAGAACCA - +4 transfac_pro__M06915 7 0.719745 17599.9 1 5 CACCTG TGCGCACAATCA - +4 cisbp__M5952-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.719745 17599.9 1 4 CACCTG GATGACGTCATC + +4 transfac_pro__M06964-salm-salr -2 0.719745 17599.9 1 4 CACCTG TCTGTTATCAGC + +4 homer__GCTGASTCAGCA_MafK-cnc-maf-S-tj 8 0.719745 17599.9 1 4 CACCTG TGCTGAGTCAGC - +4 swissregulon__hs__ATF4.p2-Atf3-Atf6-CG7786-CrebB-E2f1-Jra-Pdp1-Xbp1-gt 8 0.719745 17599.9 1 4 CACCTG CGTGACGTCACC - +4 transfac_pro__M05475-CG30020 -2 0.719745 17599.9 1 4 CACCTG TCTACCCCCCAC - +4 transfac_pro__M05804-CG30020 8 0.719745 17599.9 1 4 CACCTG TTCCCCCCAACC - +4 transfac_pro__M06032 8 0.719745 17599.9 1 4 CACCTG TTAGTCGCCACG - +4 dbcorrdb__ATF2__ENCSR000BQK_1__m1-Jra-Myc 12 0.721013 17630.9 1 6 CACCTG CTGGAAATGACTCAATCTTT + +4 dbcorrdb__BCL3__ENCSR000BNQ_1__m1 10 0.721013 17630.9 1 6 CACCTG GAATTTCTCACAGGCGCACA + +4 dbcorrdb__BRF2__ENCSR000DOC_1__m7 5 0.721013 17630.9 1 6 CACCTG GGGTTCAATTCGGGGGCTTT + +4 dbcorrdb__CHD1__ENCSR000EFC_1__m8-Chd1 4 0.721013 17630.9 1 6 CACCTG CGTCTCCCTCTTCCGTTTCC + +4 dbcorrdb__CTBP2__ENCSR000EUO_1__m1-CtBP 1 0.721013 17630.9 1 6 CACCTG CCCCCCGCCTGCACTCTCCC + +4 dbcorrdb__EP300__ENCSR000BMA_1__m2-GATAe-grn-nej-pnr 14 0.721013 17630.9 1 6 CACCTG TCAAGATGACTCATGGCCTG + +4 dbcorrdb__EP300__ENCSR000EHV_1__m2-nej 5 0.721013 17630.9 1 6 CACCTG CTGAAGGCCAGATCTAATTG + +4 dbcorrdb__EZH2__ENCSR000ARE_1__m2-E(z) 14 0.721013 17630.9 1 6 CACCTG CGTTCGCCGACGAGCACACG + +4 dbcorrdb__GTF2F1__ENCSR000EBP_1__m2-TfIIFalpha 8 0.721013 17630.9 1 6 CACCTG GTGTTCGTAACGCGTTCCGC + +4 dbcorrdb__GTF2F1__ENCSR000ECZ_1__m1-Atac3-RpII215-Taf1-TfIIFalpha 10 0.721013 17630.9 1 6 CACCTG GCACTTCCGGCACTGGGCGT + +4 dbcorrdb__HCFC1__ENCSR000ECH_1__m2-egg-Hcf-Six4 0 0.721013 17630.9 1 6 CACCTG TTCCCAGAAGGCCCCGCGCC + +4 dbcorrdb__HDAC2__ENCSR000AQG_1__m1-CTCF-HDAC1 4 0.721013 17630.9 1 6 CACCTG GCTGCCCATGGTGCTGATGG + +4 dbcorrdb__JUN__ENCSR000EZX_1__m2-Jra-kay 6 0.721013 17630.9 1 6 CACCTG TTGAGTCATCCCTGGGTGAG + +4 dbcorrdb__MYC__ENCSR000DKU_1__m1-Brf-brm-btd-CG10431-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tna-Usf-vtd-zfh1 8 0.721013 17630.9 1 6 CACCTG CCCCGGCGCACGTGGCCGCG + +4 dbcorrdb__MYC__ENCSR000EGJ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-Hcf-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf 10 0.721013 17630.9 1 6 CACCTG CCCCGGCCGCCACGTGGGCG + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m4-Nelf-E 2 0.721013 17630.9 1 6 CACCTG CCCGCCGCCGTCCCCTCCGA + +4 dbcorrdb__NFIC__ENCSR000BQX_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 11 0.721013 17630.9 1 6 CACCTG CGCAAAGTAAACATTGACTT + +4 dbcorrdb__POLR2A__ENCSR000BHH_1__m1-Brf-brm-CG10431-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-FoxP-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Spt20-SREBP-Taf1-tna 5 0.721013 17630.9 1 6 CACCTG CGCGGCGCTTCCGCCGCGGG + +4 dbcorrdb__POLR2A__ENCSR000BIK_1__m1-RpII215-Taf1 0 0.721013 17630.9 1 6 CACCTG CGCTTCCGCCATCGTCGGGC + +4 dbcorrdb__POLR2A__ENCSR000FAW_1__m1-bs-Eip74EF-ewg-Hcf-Myc-RpII215-Sin3A-Taf1 8 0.721013 17630.9 1 6 CACCTG CGCCACGGCGCTTCCGCCGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIC_1__m1-RpII215 6 0.721013 17630.9 1 6 CACCTG CCGCCGCCCTTACGCCGCGT + +4 dbcorrdb__STAT1__ENCSR000FAU_1__m1-Blimp-1-ebi-nej-Stat92E 14 0.721013 17630.9 1 6 CACCTG ATAAAAGGAAAATGAAACTG + +4 dbcorrdb__STAT3__ENCSR000DOQ_1__m2-aop-Jra-Stat92E 8 0.721013 17630.9 1 6 CACCTG TGAGTCATTTCCTGGAAGTG + +4 dbcorrdb__STAT3__ENCSR000DOX_1__m2-Jra-Myc-nej-Stat92E 10 0.721013 17630.9 1 6 CACCTG TATGACTCAACACCTAGCTG + +4 dbcorrdb__TBL1XR1__ENCSR000DYZ_1__m1-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E-sv 13 0.721013 17630.9 1 6 CACCTG AAAGAGGAAGTGAAACTGGA + +4 dbcorrdb__eGFP-HDAC8__ENCSR000DJZ_1__m1 10 0.721013 17630.9 1 6 CACCTG TGGCCCTGAGTGACTGCACA + +4 scertf__zhu.CEP3 12 0.721013 17630.9 1 6 CACCTG GGCGACTTCGGAAATATGAG + +4 transfac_pro__M01544 12 0.721013 17630.9 1 6 CACCTG GGCGACTTCGGAAATATGAG + +4 transfac_pro__M01552 11 0.721013 17630.9 1 6 CACCTG CAAATGAGATCTACAAACTG + +4 yetfasco__YNR063W_804 5 0.721013 17630.9 1 6 CACCTG CCTTAAATCTCCGAGGCCGC + +4 dbcorrdb__EP300__ENCSR000DZD_1__m2-Bgb-Bro-CG9650-foxo-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 8 0.721013 17630.9 1 6 CACCTG ATATAAACCACAGAGAAAAT - +4 dbcorrdb__FOS__ENCSR000EZE_1__m1-cnc-CoRest-Jra-kay-Mef2-mor-Myc-pan-Snr1-Stat92E 8 0.721013 17630.9 1 6 CACCTG GTATGACTCATCCCTGCGGC - +4 dbcorrdb__IKZF1__ENCSR000EUJ_1__m2-Bgb-Bro-ebi-lz-MTA1-like-run-RunxA-RunxB 4 0.721013 17630.9 1 6 CACCTG ATTCAGTCTGTGGTTTGTGT - +4 dbcorrdb__JUN__ENCSR000EGH_1__m1-cnc-CoRest-Jra-kay-mor-Myc-pan-Snr1-Stat92E 8 0.721013 17630.9 1 6 CACCTG GGATGACTCATCCCTGCGCC - +4 dbcorrdb__MYC__ENCSR000DMQ_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-Taf1-tna-Usf-vtd 4 0.721013 17630.9 1 6 CACCTG CGGGCACGTGGCCGCCGCGG - +4 dbcorrdb__POLR2A__ENCSR000EAD_1__m1-CG10431-Eip74EF-E(z)-Hcf-Rbbp5-RpII215-Sin3A-Taf1 6 0.721013 17630.9 1 6 CACCTG CCGCGGCGCTTCCGCCGTGG - +4 dbcorrdb__POLR2A__ENCSR000EBC_1__m1-Brf-CG10431-CTCF-E2f1-Eip74EF-ewg-E(z)-FoxP-Hcf-HDAC1-Max-Myc-Rbbp5-RpII215-Sin3A-Taf1 6 0.721013 17630.9 1 6 CACCTG CCGCGGCGCTTCCGCCGCGG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m11-RpII215 0 0.721013 17630.9 1 6 CACCTG CCCCTACCCGCCCGGATGGG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EGF_1__m2-RpII215 3 0.721013 17630.9 1 6 CACCTG CACGGCTTCCGCGCTGCGAC - +4 dbcorrdb__SAP30__ENCSR000AQJ_1__m1-lid-pho-phol-Sap30-Taf1 4 0.721013 17630.9 1 6 CACCTG TGCGAACATGGCGGCGCCCG - +4 dbcorrdb__SETDB1__ENCSR000EWI_1__m2-egg 8 0.721013 17630.9 1 6 CACCTG GAGGGCTTCTCCCTTCTGCA - +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m5-egg 9 0.721013 17630.9 1 6 CACCTG ATTCTTTACAACATTTCTTA - +4 dbcorrdb__SIX5__ENCSR000BJE_1__m1-bi-Hcf-mor-Six4 14 0.721013 17630.9 1 6 CACCTG CGCGGGGACTACAATTCCCA - +4 dbcorrdb__STAT1__ENCSR000DZM_1__m4-Stat92E 14 0.721013 17630.9 1 6 CACCTG AGCGGGGCGGAACCAACCCG - +4 dbcorrdb__UBTF__ENCSR000EFZ_1__m1-Brf-brm-E(z)-RpII215-tna 4 0.721013 17630.9 1 6 CACCTG CGGCGGCCGGGCGGAGCCGG - +4 taipale_cyt_meth__PAX2_NSGTCACGCWTSANYGNNYN_eDBD-ey-Poxm-sv-toy 10 0.721013 17630.9 1 6 CACCTG TGGGCGGTCATGCGTGACGG - +4 transfac_pro__M01513 4 0.721013 17630.9 1 6 CACCTG CGCATCTCTCGAGATGCGAG - +4 dbcorrdb__SIN3A__ENCSR000BPB_1__m1-Sin3A -1 0.721013 17630.9 1 5 CACCTG ACCTGCCGCCAGATTTGAAC + +4 dbcorrdb__EZH2__ENCSR000ARH_1__m3-E(z) 15 0.721013 17630.9 1 5 CACCTG TCTCTTCTCCGCAGCCCCCT - +4 jaspar__MA0615.1 5 0.721316 17638.3 1 6 CACCTG GAGTGTACGTAAGATGG + +4 taipale_tf_pairs__TEAD4_PITX1_RCATWCNNNNNGGATTA_CAP_repr-Ptx1-sd 3 0.721316 17638.3 1 6 CACCTG GCATTCCATAGGGATTA + +4 transfac_pro__M01357 3 0.721316 17638.3 1 6 CACCTG TCACCCATCAATAATCA + +4 transfac_pro__M02935 4 0.721316 17638.3 1 6 CACCTG AGGAGACCCCCAATTTG + +4 transfac_pro__M07854-Hsf-pb 3 0.721316 17638.3 1 6 CACCTG TAGAACATTCTAGAACG + +4 cisbp__M5452 5 0.721316 17638.3 1 6 CACCTG TTGTTTACCGTAAACAT - +4 transfac_pro__M00806-NfI 11 0.721316 17638.3 1 6 CACCTG TCTTGGCAAGTATCCAA - +4 transfac_pro__M01387-oc-Ptx1 9 0.721316 17638.3 1 6 CACCTG GACAATTAATCCCTACA - +4 transfac_pro__M01415-al-ap-Awh-CG18599-CG34367-Dfd-E5-ems-eve-Lim3-OdsH-otp-Pph13-repo-Rx-unc-4-Vsx1-vvl-zfh2 2 0.721316 17638.3 1 6 CACCTG CACAATTAATTAACGCG - +4 transfac_pro__M09257 0 0.721316 17638.3 1 6 CACCTG CGCCGCAATTTCCGCCG - +4 jaspar__MA0452.2-Kr-Kr-h2 4 0.721797 17650.1 1 6 CACCTG TTTAACCCTTTTTC + +4 neph__UW.Motif.0602 5 0.721797 17650.1 1 6 CACCTG AAAAAAAACATTTC + +4 swissregulon__hs__VSX1_2.p2-Vsx1-Vsx2 7 0.721797 17650.1 1 6 CACCTG AAATAATTAGCACA + +4 taipale__GLIS2_DBD_GACCCCCCGCGNNG_repr-ci-lmd-sug 0 0.721797 17650.1 1 6 CACCTG GACCCCCCGCGAAG + +4 taipale_cyt_meth__ATF6_NGRTGACGTGGCAN_eDBD_meth-Atf6-CrebA-CrebB-Xbp1 4 0.721797 17650.1 1 6 CACCTG TGATGACGTGGCAG + +4 taipale_tf_pairs__ETV5_DRGX_TAATKRSCGGAWGN_CAP_repr-CG11294-Drgx-Ets96B 4 0.721797 17650.1 1 6 CACCTG TAATTACCGGAAGT + +4 transfac_pro__M01151 4 0.721797 17650.1 1 6 CACCTG TTGTTACATTGTTG + +4 transfac_public__M00017-CrebB 4 0.721797 17650.1 1 6 CACCTG CTGTGACGTCAGCC + +4 cisbp__M2256-Kr-Kr-h2 4 0.721797 17650.1 1 6 CACCTG TTTAACCCTTTTTC - +4 cisbp__M5814-Sox100B 6 0.721797 17650.1 1 6 CACCTG TGACTGAACATTCA - +4 taipale_tf_pairs__TEAD4_HOXB13_GGWATGNNNRTAAA_CAP-sd 2 0.721797 17650.1 1 6 CACCTG TTTATGAGCATTCC - +4 transfac_pro__M02899-Sox14 0 0.721797 17650.1 1 6 CACCTG TTCATAACAATTTT - +4 transfac_pro__M05951 10 0.721797 17650.1 1 4 CACCTG GGGGGCGGGCCTCC + +4 tfdimers__MD00343 10 0.722234 17660.8 1 6 CACCTG TGGCAGGGCATGCCCGGGCAGGCGCGCGTTT + +4 tfdimers__MD00416 24 0.722353 17663.7 1 6 CACCTG ATATTTGGTTAATAATTAATTATTAACCAAATAT + +4 cisbp__M6436 0 0.722358 17663.8 1 6 CACCTG TACAGACTGTTCT + +4 hocomoco__PIT1_HUMAN.H11MO.0.C-vvl 0 0.722358 17663.8 1 6 CACCTG CTCATGAATATAT + +4 predrem__nrMotif1141 5 0.722358 17663.8 1 6 CACCTG CCGTCCCCATCCC + +4 transfac_pro__M00777-Stat92E 4 0.722358 17663.8 1 6 CACCTG GACTTTTCTGGGA + +4 transfac_pro__M01866-nej 0 0.722358 17663.8 1 6 CACCTG GAGTTGTGCAATT + +4 transfac_pro__M06935-CG32532 2 0.722358 17663.8 1 6 CACCTG CTAATCTGATTAC + +4 transfac_pro__M06980-oc 2 0.722358 17663.8 1 6 CACCTG TTAATCTGATTAT + +4 transfac_public__M00360-gsb-gsb-n-prd 6 0.722358 17663.8 1 6 CACCTG TCGTCACGCTTCA + +4 yetfasco__YGL073W_411-Hsf-pb 6 0.722358 17663.8 1 6 CACCTG TTCTATAATATTC + +4 cisbp__M1390 4 0.722358 17663.8 1 6 CACCTG AAGTTATCCGGAT - +4 cisbp__M6111 3 0.722358 17663.8 1 6 CACCTG ATTAACCCTTTCT - +4 stark__MATTAAWNATGCR-acj6 0 0.722358 17663.8 1 6 CACCTG CGCATAATTAATG - +4 taipale__Zfp652_DBD_NNAAAGGGTTAAW_repr 3 0.722358 17663.8 1 6 CACCTG ATTAACCCTTTCT - +4 transfac_pro__M08959-gsb-gsb-n-prd 6 0.722358 17663.8 1 6 CACCTG ATTAGTCACGGTT - +4 transfac_public__M00491 7 0.722358 17663.8 1 6 CACCTG TGGCCCCCCCCCC - +4 transfac_public__M00249 8 0.722358 17663.8 1 5 CACCTG GGGGATTGCATCT - +4 tfdimers__MD00181-CG7786-E2f1-gt-Pdp1 18 0.7234 17689.3 1 6 CACCTG TTTTTCTTTTCTTTTTTGCAAATTAT + +4 cisbp__M0088 1 0.723558 17693.2 1 6 CACCTG TGACGCG + +4 predrem__nrMotif1701 1 0.723558 17693.2 1 6 CACCTG GCTCTTT + +4 transfac_pro__M04853-CTCF 1 0.723558 17693.2 1 6 CACCTG ACAGCGT + +4 cisbp__M1720 1 0.723558 17693.2 1 6 CACCTG TTCGCGC - +4 hdpi__ETV4-Eip74EF-Ets21C-Ets65A-Ets96B-aop-pnt 1 0.723558 17693.2 1 6 CACCTG CTTCCGG - +4 cisbp__M6470-Sox100B -1 0.723558 17693.2 1 5 CACCTG TCTTTGT + +4 predrem__nrMotif130 -1 0.723558 17693.2 1 5 CACCTG GCTTTCC + +4 predrem__nrMotif651 2 0.723558 17693.2 1 5 CACCTG TATTTCT + +4 cisbp__M0616 -1 0.723558 17693.2 1 5 CACCTG TCCGCAA - +4 hdpi__NONO-nonA-nonA-l 2 0.723558 17693.2 1 5 CACCTG CAAACCC - +4 transfac_pro__M04922-usp 2 0.723558 17693.2 1 5 CACCTG GCCCTCT - +4 transfac_pro__M05455-btd-cbt-Sp1-Spps 2 0.723558 17693.2 1 5 CACCTG CCGCCCT - +4 hdpi__ANXA1 3 0.723558 17693.2 1 4 CACCTG TGCCAAC + +4 predrem__nrMotif1263 -2 0.723558 17693.2 1 4 CACCTG CCAGACT + +4 predrem__nrMotif1923 3 0.723558 17693.2 1 4 CACCTG AAGCATC + +4 stark__AATKACA 3 0.723558 17693.2 1 4 CACCTG AATGACA + +4 transfac_pro__M01180 3 0.723558 17693.2 1 4 CACCTG CCGTACA + +4 cisbp__M0654 -2 0.723558 17693.2 1 4 CACCTG CTTTTTC - +4 jaspar__MA1071.1 -2 0.723558 17693.2 1 4 CACCTG CTTTTTC - +4 transfac_pro__M01877-GATAe-grn-pnr 3 0.723558 17693.2 1 4 CACCTG GCTTATC - +4 predrem__nrMotif1302-CG5846-CG9727-Rfx-SREBP 4 0.723558 17693.2 1 3 CACCTG TGGCAAC + +4 predrem__nrMotif1822 4 0.723558 17693.2 1 3 CACCTG AGAGCAC + +4 predrem__nrMotif1986 4 0.723558 17693.2 1 3 CACCTG TTTCAAC + +4 transfac_pro__M01494-klu-sr 6 0.723843 17700.1 1 6 CACCTG ACGTGTTACCCCGCATTTAAT + +4 transfac_pro__M01547 12 0.723843 17700.1 1 6 CACCTG AGGACTATAGAACACTCTAAA + +4 transfac_pro__M09079-RpII215-Taf1 1 0.723843 17700.1 1 6 CACCTG CCACCGCCGCCGCCATTTCCG + +4 transfac_pro__M09474 14 0.723843 17700.1 1 6 CACCTG TTTTAATTAGCGTTGACTTTT + +4 cisbp__M2141 12 0.723843 17700.1 1 6 CACCTG AGGACTATAGAACACTCTAAA - +4 transfac_pro__M01554-Myb-Pbp95 2 0.723843 17700.1 1 6 CACCTG TTGACTTGACTCTGGCTGTGC - +4 transfac_pro__M05237 14 0.723843 17700.1 1 6 CACCTG GCGGAACAGCCGGGCACCCCC - +4 transfac_pro__M09125-brm-CG7839-maf-S-orb-SREBP-vtd 3 0.723843 17700.1 1 6 CACCTG TTTTTACTTTTTCTTTTTTTT - +4 yetfasco__TBP-TFIIB_1329-Tbp-TfIIA-S-TfIIA-S-2-TfIIB-Trf-Trf2 12 0.723843 17700.1 1 6 CACCTG CTTTTATAGGCCCCCCTTCAG - +4 cisbp__M0283-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 1 0.724845 17724.6 1 6 CACCTG TGACGTCA + +4 cisbp__M0923-al-ap-CG11085-CG9876-Dr-E5-ems-en-eve-inv-lab-lbl-OdsH-otp-repo-ro-Rx-slou-unpg 2 0.724845 17724.6 1 6 CACCTG GCTAATTA + +4 cisbp__M0979 2 0.724845 17724.6 1 6 CACCTG CTAATTCG + +4 cisbp__M1008-abd-A-Abd-B-Antp-cad-Dbx-eve-ftz-Scr-Ubx 2 0.724845 17724.6 1 6 CACCTG TTTATGGC + +4 cisbp__M1025-Antp-Awh-bsh-btn-C15-CG11085-CG15696-CG34367-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim3-pb-repo-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.724845 17724.6 1 6 CACCTG GCTAATTA + +4 cisbp__M5120-bcd-Gsc-oc-Ptx1 2 0.724845 17724.6 1 6 CACCTG TTAATCCC + +4 cisbp__M5139-ovo 2 0.724845 17724.6 1 6 CACCTG TGTAACGG + +4 elemento__GACCAATC 0 0.724845 17724.6 1 6 CACCTG GACCAATC + +4 elemento__TTGACCCA 2 0.724845 17724.6 1 6 CACCTG TTGACCCA + +4 flyfactorsurvey__Oc_SOLEXA_FBgn0004102-Gsc-Ptx1-bcd-oc 2 0.724845 17724.6 1 6 CACCTG TTAATCCC + +4 homer__CATCMCTA_Unknown2 2 0.724845 17724.6 1 6 CACCTG CATCACTA + +4 predrem__nrMotif1433 1 0.724845 17724.6 1 6 CACCTG GTGCTTGC + +4 predrem__nrMotif2102 2 0.724845 17724.6 1 6 CACCTG GCTACCAT + +4 taipale_cyt_meth__HOXA5_RTCGTTAN_FL_meth-Antp-btn-Dfd-Dll-eve-exex-lab-pb-Scr 0 0.724845 17724.6 1 6 CACCTG ATCATTAA + +4 cisbp__M0585 1 0.724845 17724.6 1 6 CACCTG TGATCGGT - +4 cisbp__M0823-CG9876-CG11294-CG32532-Rx-Vsx1-en-lms-repo-slou-unpg 0 0.724845 17724.6 1 6 CACCTG TAATTAAT - +4 cisbp__M1138 0 0.724845 17724.6 1 6 CACCTG TAATTAAT - +4 elemento__AGAAGGCC 0 0.724845 17724.6 1 6 CACCTG GGCCTTCT - +4 hdpi__TPPP-ringer 2 0.724845 17724.6 1 6 CACCTG TTTACCAA - +4 homer__RGGATTAR_GSC-Gsc-Ptx1-bcd-oc 2 0.724845 17724.6 1 6 CACCTG CTAATCCC - +4 taipale_cyt_meth__VSX2_NTCGTTAN_FL_meth-eve-unpg-Vsx1-Vsx2 2 0.724845 17724.6 1 6 CACCTG CTAACGAG - +4 transfac_pro__M01872-CG7786-gt-Pdp1 1 0.724845 17724.6 1 6 CACCTG TTGCATAA - +4 transfac_pro__M07456 0 0.724845 17724.6 1 6 CACCTG CTCATAAA - +4 cisbp__M6400 3 0.724845 17724.6 1 5 CACCTG CTAATCCT + +4 predrem__nrMotif1135 -1 0.724845 17724.6 1 5 CACCTG TGCTGTAA + +4 transfac_pro__M01917 -1 0.724845 17724.6 1 5 CACCTG ATCTCCGA + +4 transfac_public__M00497-Stat92E 3 0.724845 17724.6 1 5 CACCTG GGATTCCC + +4 cisbp__M5206-so 3 0.724845 17724.6 1 5 CACCTG TATCATAT - +4 jaspar__MA0432.1 -1 0.724845 17724.6 1 5 CACCTG ATCTCCGA - +4 predrem__nrMotif1832 -1 0.724845 17724.6 1 5 CACCTG TCCTTACA - +4 predrem__nrMotif2513 3 0.724845 17724.6 1 5 CACCTG TGCTATAT - +4 scertf__foat.DIG1-sd -1 0.724845 17724.6 1 5 CACCTG ACATTCTT - +4 transfac_pro__M04616-Lim3-tup 3 0.724845 17724.6 1 5 CACCTG CATTAGCC - +4 transfac_pro__M07301-NFAT 3 0.724845 17724.6 1 5 CACCTG ATTTTCCC - +4 predrem__nrMotif2259 -2 0.724845 17724.6 1 4 CACCTG CTTGAGAC + +4 swissregulon__sacCer__ADR1 4 0.724845 17724.6 1 4 CACCTG ACCCCAAC + +4 predrem__nrMotif2637 4 0.724845 17724.6 1 4 CACCTG ATAGAAAC - +4 transfac_pro__M01653 4 0.724845 17724.6 1 4 CACCTG AAATAACC - +4 transfac_pro__M02270-foxo 4 0.724845 17724.6 1 4 CACCTG TGTTTACA - +4 neph__UW.Motif.0292 -3 0.724845 17724.6 1 3 CACCTG CTTTAAGA + +4 tfdimers__MD00551 14 0.725173 17732.7 1 6 CACCTG TATTTTTTTATTTTTTCCTGATTAT + +4 taipale_cyt_meth__KLF10_RMCACRCCCMYNMCACRCCCMC_eDBD_repr-btd-cbt-CG42741-dar1-Klf15-luna-Spps 4 0.72558 17742.6 1 6 CACCTG GCCACACCCCCGCCACACCCCC + +4 tfdimers__MD00593-Ptx1 12 0.72558 17742.6 1 6 CACCTG AACATTCTAATCTTCCTTATTT + +4 c2h2_zfs__M3269 2 0.72558 17742.6 1 6 CACCTG TTTACCCACAATGCATTGCGCC - +4 cisbp__M3690-kn 6 0.72558 17742.6 1 6 CACCTG ACAAACTCCCTGGGGAATAGTG - +4 hocomoco__ZNF8_HUMAN.H11MO.0.C-Aef1 15 0.72558 17742.6 1 6 CACCTG TCCATTGTATGGATATACCACA - +4 swissregulon__hs__EBF1.p2-kn 6 0.72558 17742.6 1 6 CACCTG ACCCGTTCCCTGGGGAGTTGCG - +4 tfdimers__MD00074-pho-phol-Sox14 3 0.72558 17742.6 1 6 CACCTG TTTTCCCTTTGTTATGGAAATG - +4 tfdimers__MD00497-abd-A-lab-Ubx 7 0.72558 17742.6 1 6 CACCTG CAGTACCCACATCAATCATACT - +4 tfdimers__MD00351-CG5846-Rfx 8 0.726167 17757 1 6 CACCTG AAAAATGGCAACTGAAACTAAAAA - +4 transfac_pro__M04723-CG10431-pho-phol 3 0.726167 17757 1 6 CACCTG CTCTGCCCTTAACCAAGATGGCGG - +4 taipale_tf_pairs__TEAD4_CEBPD_NTTRCGYAANNNNNNNRGWATGY_CAP_repr-sd 9 0.726326 17760.8 1 6 CACCTG ATTGCGCAATAACTTTGGAATGT + +4 tfdimers__MD00220 13 0.726326 17760.8 1 6 CACCTG AAAAACATGCAAACCCCCAACAC + +4 tfdimers__MD00432-CG7786-gt-Pdp1-Stat92E 14 0.726326 17760.8 1 6 CACCTG TTTATTTACATAATTCCCTTTTA + +4 tfdimers__MD00125-Jra-kay 2 0.726326 17760.8 1 6 CACCTG AATTATTGAGTCAATAAAAAAAA - +4 fantom__motif22_GGMCTG 0 0.728208 17806.9 1 6 CACCTG GGACTG + +4 hdpi__HOXB9 0 0.728208 17806.9 1 6 CACCTG TAATTG + +4 scertf__macisaac.SWI6 0 0.728208 17806.9 1 6 CACCTG GACGCG + +4 transfac_pro__M05092 0 0.728208 17806.9 1 6 CACCTG TATTTG - +4 hdpi__NNT 1 0.728208 17806.9 1 5 CACCTG GCGCCG + +4 hdpi__SMAP1L-CG8243 -1 0.728208 17806.9 1 5 CACCTG GGCTGG + +4 transfac_pro__M03541-Jra 1 0.728208 17806.9 1 5 CACCTG TGACTC + +4 fantom__motif56_GANCGT -1 0.728208 17806.9 1 5 CACCTG ACGATC - +4 swissregulon__sacCer__YER184C -1 0.728208 17806.9 1 5 CACCTG TCCGGA - +4 swissregulon__hs__TFDP1.p2-Dp 2 0.728208 17806.9 1 4 CACCTG CGCGCC - +4 transfac_pro__M00704-sd -2 0.728208 17806.9 1 4 CACCTG CATTCC - +4 scertf__macisaac.AZF1-CG17328 8 0.728253 17808 1 6 CACCTG TTTTTCTTTTTCTGTTTC + +4 taipale__ETS1_full_NCCGGAWRYRYWTCCGGN-aop-Ets21C-Ets96B-Ets97D-pnt 8 0.728253 17808 1 6 CACCTG ACCGGAAGTACATCCGGC - +4 taipale_tf_pairs__ELK1_SPDEF_NSMGGACGGAYNTCCKSN_CAP-Ets98B 11 0.728253 17808 1 6 CACCTG CCCGGATATCCGTCCGGT - +4 transfac_pro__M00328-sv 7 0.728253 17808 1 6 CACCTG GAACTCACGCATGACTGT - +4 transfac_pro__M06885 3 0.728253 17808 1 6 CACCTG GCTGACCCTAACTCCCCC - +4 neph__UW.Motif.0304 8 0.729057 17827.6 1 6 CACCTG AATTACACATTCTGTG + +4 taipale_tf_pairs__POU2F1_SOX2_ATTTGCATNACAATRN_CAP-nub-pdm2-SoxN 3 0.729057 17827.6 1 6 CACCTG ATTTGCATAACAATAG + +4 taipale_tf_pairs__TEAD4_DLX2_RCATTCYNNNCAATTA_CAP-sd 3 0.729057 17827.6 1 6 CACCTG ACATTCCAAGCAATTA + +4 transfac_pro__M01365-al-ap-Awh-CG11294-CG32532-CG34367-CG9876-E5-ems-en-inv-Lim1-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-zfh2 2 0.729057 17827.6 1 6 CACCTG GCGAACTAATTAATGC + +4 transfac_pro__M01436-Gsc-oc 10 0.729057 17827.6 1 6 CACCTG CGTTGGGGATTAGCCT + +4 transfac_pro__M01973 1 0.729057 17827.6 1 6 CACCTG CCCCCTAAGAGGCCCC + +4 transfac_pro__M06543 7 0.729057 17827.6 1 6 CACCTG CGGGAAGCACCCAATG + +4 cisbp__M5299-B-H1-B-H2 7 0.729057 17827.6 1 6 CACCTG CAATTAGCACCAATTA - +4 hocomoco__SOX10_HUMAN.H11MO.0.B-Sox100B 8 0.729057 17827.6 1 6 CACCTG AACAATGCCTCCTTTG - +4 neph__UW.Motif.0126 0 0.729057 17827.6 1 6 CACCTG TTTCTCTGCCAAATTC - +4 neph__UW.Motif.0514 6 0.729057 17827.6 1 6 CACCTG TTAAAATTTCTTTTTG - +4 taipale__BARHL2_full_TAAWYGNNNNTAAWYG-B-H1-B-H2 7 0.729057 17827.6 1 6 CACCTG CAATTAGCACCAATTA - +4 taipale__SOX9_full_ATCAATRTKCAGWGAT_repr-D-Sox100B-Sox21a-Sox21b 7 0.729057 17827.6 1 6 CACCTG ATCACTGCACATTGAT - +4 transfac_pro__M01451-abd-A-Antp-Scr-Ubx 9 0.729057 17827.6 1 6 CACCTG TTTATTAATTGCCGGT - +4 transfac_pro__M08991 1 0.729057 17827.6 1 6 CACCTG CTACACGATTAATATC - +4 taipale_cyt_meth__PAX3_NSGTCACGSNNATTAN_eDBD_meth-gsb-gsb-n-ind-prd 11 0.729057 17827.6 1 5 CACCTG TTAATTAGCGTGACGA - +4 cisbp__M5367-klu-sr 0 0.729157 17830.1 1 6 CACCTG TGCGTGGGCGT + +4 cisbp__M5950-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-inv-lab-lbe-OdsH-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 3 0.729157 17830.1 1 6 CACCTG AGCTAATTAGC + +4 taipale__PRRX1_full_TAATYTAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-PHDP-repo-ro-Traf4-unc-4 1 0.729157 17830.1 1 6 CACCTG TAATCTAATTA + +4 taipale_cyt_meth__KLF3_NRCCACGCCCN_FL_meth-btd-CG3065-CG42741-dar1-luna-Sp1-Spps 0 0.729157 17830.1 1 6 CACCTG GGCCACGCCCA + +4 taipale_cyt_meth__MIXL1_TAAYNKCGTTA_FL_meth-CG32532-Drgx 4 0.729157 17830.1 1 6 CACCTG TAATTGCGTTA + +4 transfac_pro__M00958 3 0.729157 17830.1 1 6 CACCTG AAGCACCGCCC + +4 transfac_pro__M01209 4 0.729157 17830.1 1 6 CACCTG CATATTCCCGT + +4 transfac_pro__M03816 1 0.729157 17830.1 1 6 CACCTG CATGCTCAGCA + +4 cisbp__M1147 0 0.729157 17830.1 1 6 CACCTG CATCTCAATCA - +4 cisbp__M1906-btd-CG42741-dar1-E2f2-kay-Klf15-klu-luna-Nf-YA-Nf-YB-sd-Sp1-Spps-Stat92E 0 0.729157 17830.1 1 6 CACCTG GCCCCGCCCCC - +4 flyfactorsurvey__tap_da_SANGER_5_FBgn0000413-Fer3-HLH54F-amos-da-tap 1 0.729157 17830.1 1 6 CACCTG CCATATGTCAC - +4 hocomoco__EGR3_HUMAN.H11MO.0.D-sr 1 0.729157 17830.1 1 6 CACCTG ACACCCACTCT - +4 hocomoco__NFAC1_MOUSE.H11MO.1.A-CG5641-Jra-NFAT-kay 3 0.729157 17830.1 1 6 CACCTG TTTTTCCATTC - +4 hocomoco__ZN770_HUMAN.H11MO.1.C 3 0.729157 17830.1 1 6 CACCTG CTCAGCCTCCC - +4 jaspar__MA0925.1 5 0.729157 17830.1 1 6 CACCTG GTCCAGACACT - +4 predrem__nrMotif1013 0 0.729157 17830.1 1 6 CACCTG TTGCTTTCATT - +4 predrem__nrMotif1674 4 0.729157 17830.1 1 6 CACCTG CATGGGCCAGG - +4 taipale_cyt_meth__JUND_NATGASTCATN_eDBD_meth-cnc-Jra-kay-Mef2 5 0.729157 17830.1 1 6 CACCTG GATGACTCATC - +4 taipale_cyt_meth__POU2F2_NTATGCWAATN_eDBD-nub-pdm2-vvl 4 0.729157 17830.1 1 6 CACCTG CATTTGCATAC - +4 transfac_pro__M01597-btd-Clp-Spps 0 0.729157 17830.1 1 6 CACCTG CCCCTCCCCCA - +4 transfac_pro__M07614-Sox14 0 0.729157 17830.1 1 6 CACCTG GAACTCTTTGT - +4 transfac_pro__M09142 5 0.729157 17830.1 1 6 CACCTG AATCCGATCTG - +4 fantom__motif75_AGCCGAGCGCT -1 0.729157 17830.1 1 5 CACCTG AGCCGAGCGCT + +4 hocomoco__BACH2_HUMAN.H11MO.0.A-Jra-cnc-ewg-kay-maf-S-nej -1 0.729157 17830.1 1 5 CACCTG TGCTGAGTCAT + +4 cisbp__M6032 -2 0.729157 17830.1 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M6290 7 0.729157 17830.1 1 4 CACCTG CCAATAAAACC + +4 taipale__Hoxd13_DBD_NCTCRTAAAAN -2 0.729157 17830.1 1 4 CACCTG GCTCGTAAAAC + +4 taipale_cyt_meth__HOXD10_NGTCGTAAAAN_FL-Abd-B-cad 7 0.729157 17830.1 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXD10_NGYAATAAAAN_FL-abd-A-Abd-B-cad-eve-Ubx 7 0.729157 17830.1 1 4 CACCTG TTTTTATTACC - +4 taipale_cyt_meth__JUND_NRTGACGCATN_eDBD_repr-Jra 7 0.729157 17830.1 1 4 CACCTG GATGCGTCATC - +4 transfac_public__M00172-Jra-kay 7 0.729157 17830.1 1 4 CACCTG ACTGAGTCACC - +4 cisbp__M0582 1 0.732937 17922.5 1 6 CACCTG AAACCGCGT + +4 cisbp__M0904-abd-A-Abd-B-Antp-cad-Dbx-Dfd-eve-ftz-H2.0-Scr-Ubx 2 0.732937 17922.5 1 6 CACCTG TTTATGACC + +4 cisbp__M0990-abd-A-Antp-B-H1-B-H2-bsh-Dfd-eve-exex-ftz-Hmx-pb-Scr-tup-Ubx-zen2 1 0.732937 17922.5 1 6 CACCTG TTAATTGCT + +4 cisbp__M1232-vvl 1 0.732937 17922.5 1 6 CACCTG ATTAATTAT + +4 cisbp__M2096 3 0.732937 17922.5 1 6 CACCTG GCGCACATT + +4 hdpi__RBM22-CG14641 3 0.732937 17922.5 1 6 CACCTG TGGTAAATG + +4 jaspar__MA0969.1 1 0.732937 17922.5 1 6 CACCTG AAACCGCGT + +4 predrem__nrMotif1269 2 0.732937 17922.5 1 6 CACCTG AGAGCCTTT + +4 predrem__nrMotif1367 0 0.732937 17922.5 1 6 CACCTG GCCCCGGGA + +4 predrem__nrMotif1455 3 0.732937 17922.5 1 6 CACCTG GATTTCCAG + +4 predrem__nrMotif1492 1 0.732937 17922.5 1 6 CACCTG CATCCTCTC + +4 transfac_pro__M04861-Six4 1 0.732937 17922.5 1 6 CACCTG AAAACTACA + +4 transfac_public__M00223-Stat92E 0 0.732937 17922.5 1 6 CACCTG TTCCCGGAA + +4 cisbp__M0418 2 0.732937 17922.5 1 6 CACCTG CCCACGCAT - +4 cisbp__M0980-al-Antp-bsh-CG15696-CG34367-Dr-E5-ems-en-ind-inv-lab-lms-NK7.1-OdsH-repo-Scr-slou-Ubx-unc-4-unpg-Vsx2 2 0.732937 17922.5 1 6 CACCTG GCCAATTAA - +4 cisbp__M1055-abd-A-Abd-B-Antp-cad-Dfd-eve-ftz-Scr-Ubx 1 0.732937 17922.5 1 6 CACCTG GGCCATTAA - +4 neph__UW.Motif.0068-Taf1-pho-phol 3 0.732937 17922.5 1 6 CACCTG CGCCATTTT - +4 predrem__nrMotif1704 3 0.732937 17922.5 1 6 CACCTG TGTCACTTT - +4 predrem__nrMotif1908 3 0.732937 17922.5 1 6 CACCTG ATTCCCCAG - +4 predrem__nrMotif2069 3 0.732937 17922.5 1 6 CACCTG AGAAACTTG - +4 predrem__nrMotif2091 3 0.732937 17922.5 1 6 CACCTG TGCTCCCAG - +4 predrem__nrMotif68 3 0.732937 17922.5 1 6 CACCTG CAAAACTGG - +4 transfac_pro__M01735-Ptx1 3 0.732937 17922.5 1 6 CACCTG TCTAATCCA - +4 transfac_pro__M04898 1 0.732937 17922.5 1 6 CACCTG TGATATGCA - +4 predrem__nrMotif162 -1 0.732937 17922.5 1 5 CACCTG CCCATTCCC + +4 predrem__nrMotif610 4 0.732937 17922.5 1 5 CACCTG AATTTCCCA + +4 predrem__nrMotif855 4 0.732937 17922.5 1 5 CACCTG GGGACCCCC + +4 cisbp__M1186 -1 0.732937 17922.5 1 5 CACCTG ACCGATTAT - +4 predrem__nrMotif1025 4 0.732937 17922.5 1 5 CACCTG TGAAAGCCA - +4 predrem__nrMotif2137 4 0.732937 17922.5 1 5 CACCTG TGTTTATCA - +4 predrem__nrMotif2227 4 0.732937 17922.5 1 5 CACCTG TCCTTAGCA - +4 predrem__nrMotif2414 -1 0.732937 17922.5 1 5 CACCTG TTCTTTGAT - +4 predrem__nrMotif2469 4 0.732937 17922.5 1 5 CACCTG TCATTAGCA - +4 predrem__nrMotif2619 -1 0.732937 17922.5 1 5 CACCTG ACAGTATTT - +4 predrem__nrMotif999 -1 0.732937 17922.5 1 5 CACCTG ACTTTTTGG - +4 transfac_pro__M01100 4 0.732937 17922.5 1 5 CACCTG GGGGCCCCC - +4 predrem__nrMotif1219 5 0.732937 17922.5 1 4 CACCTG TGGCAAACA - +4 predrem__nrMotif201 -2 0.732937 17922.5 1 4 CACCTG ACTGAGCCT - +4 predrem__nrMotif61 5 0.732937 17922.5 1 4 CACCTG ATGCAGACA - +4 transfac_pro__M04706-Dif-dl-Rel 5 0.732937 17922.5 1 4 CACCTG GAAATTCCC - +4 fantom__motif68_CTTTTAAAC 6 0.732937 17922.5 1 3 CACCTG CTTTTAAAC + +4 predrem__nrMotif1812 -3 0.732937 17922.5 1 3 CACCTG CTGATGCCA + +4 transfac_pro__M09231-Hsf-pb 5 0.733669 17940.4 1 6 CACCTG TCTAGAAGCTTCTAGAAGC + +4 transfac_pro__M07730-GATAe-grn 13 0.733669 17940.4 1 6 CACCTG AAGATAACGCCGTTATCTT - +4 taipale_cyt_meth__RFX5_NGTTGCYRNNNGTTGCYRN_eDBD_repr-CG9727-Rfx 15 0.733669 17940.4 1 4 CACCTG ATAGCAACGCATAGCAACG - +4 cisbp__M0115 3 0.734027 17949.2 1 6 CACCTG TGCAATAGCA + +4 cisbp__M1057 1 0.734027 17949.2 1 6 CACCTG AAATCGATTT + +4 cisbp__M1110 4 0.734027 17949.2 1 6 CACCTG GGGCAATAGA + +4 cisbp__M1380 4 0.734027 17949.2 1 6 CACCTG AAACGATAAG + +4 cisbp__M1676 3 0.734027 17949.2 1 6 CACCTG TCCGACCACA + +4 cisbp__M4692-egg-Hcf-mor-Six4 4 0.734027 17949.2 1 6 CACCTG ACTACAACTC + +4 jaspar__MA1043.1 1 0.734027 17949.2 1 6 CACCTG ATACGCAACC + +4 predrem__nrMotif1110 0 0.734027 17949.2 1 6 CACCTG TATGTGCTTT + +4 taipale__Atoh1_DBD_RNCATATGNY_repr-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.734027 17949.2 1 6 CACCTG AACATATGTT + +4 transfac_pro__M03206 4 0.734027 17949.2 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M07822-al-ap-Awh-CG18599-CG34367-CG4328-dve-E5-ems-en-ind-inv-lab-Lim3-Lmx1a-OdsH-otp-repo-Rx-unc-4-unpg-zfh2 2 0.734027 17949.2 1 6 CACCTG GCTAATTAAC + +4 transfac_pro__M08904-TfIIB 1 0.734027 17949.2 1 6 CACCTG TTTTCTGCCA + +4 cisbp__M0869-Antp-HGTX-Scr-Ubx-abd-A-bsh 2 0.734027 17949.2 1 6 CACCTG AGCCCATTAA - +4 cisbp__M5654-amos-ato-HLH54F-Oli-tap 0 0.734027 17949.2 1 6 CACCTG AACATATGTC - +4 cisbp__M6114-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-FoxP-GATAe-grn-HDAC1-nej-Nf1-pnr 4 0.734027 17949.2 1 6 CACCTG TGTTTGCTTT - +4 hocomoco__DDIT3_HUMAN.H11MO.0.D-nej 4 0.734027 17949.2 1 6 CACCTG ATTGCATCAT - +4 homer__NATGTTGCAA_CEBP_AP1-Jra 4 0.734027 17949.2 1 6 CACCTG TTGCAACATC - +4 predrem__nrMotif337 0 0.734027 17949.2 1 6 CACCTG CTCCAGTCCC - +4 stark__MAATTNAATT 4 0.734027 17949.2 1 6 CACCTG AATTAAATTG - +4 taipale_cyt_meth__PBX1_KTGATTGAYR_FL 0 0.734027 17949.2 1 6 CACCTG CATCAATCAA - +4 taipale_cyt_meth__PBX1_KTGATTGAYR_eDBD_meth 4 0.734027 17949.2 1 6 CACCTG CGTCAATCAC - +4 transfac_pro__M02056-aop-Eip74EF-Ets21C-Ets65A-Ets96B-pnt 3 0.734027 17949.2 1 6 CACCTG TATTTCCGGG - +4 transfac_pro__M04619-MTF-1 3 0.734027 17949.2 1 6 CACCTG CTGCACACGG - +4 transfac_pro__M04997 4 0.734027 17949.2 1 6 CACCTG GGGGGACATG - +4 cisbp__M1270 5 0.734027 17949.2 1 5 CACCTG AACGAAACTA + +4 cisbp__M1406 5 0.734027 17949.2 1 5 CACCTG ATACGCAACC + +4 cisbp__M6295-lab 5 0.734027 17949.2 1 5 CACCTG CCATCCATCA + +4 predrem__nrMotif744 -1 0.734027 17949.2 1 5 CACCTG TTCTGACAGT + +4 taipale_cyt_meth__OLIG2_ANCATATGNY_eDBD-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.734027 17949.2 1 5 CACCTG ACCATATGGT + +4 cisbp__M0337 5 0.734027 17949.2 1 5 CACCTG TGAATCATAA - +4 predrem__nrMotif449 5 0.734027 17949.2 1 5 CACCTG GGGGCCACTG - +4 transfac_pro__M01235-Antp-btn-E5-ems-eve-exex-lab-pb-Scr-slou 5 0.734027 17949.2 1 5 CACCTG GTAATTAGCT - +4 transfac_pro__M02085 -1 0.734027 17949.2 1 5 CACCTG TTCTAGAAAG - +4 transfac_pro__M07764-B-H1-B-H2-CG11085 -1 0.734027 17949.2 1 5 CACCTG ACCGTTTAGC - +4 transfac_pro__M08981-al-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ind-lab-lbe-Lim1-Lim3-OdsH-otp-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 5 0.734027 17949.2 1 5 CACCTG TTAATTAGCT - +4 cisbp__M1587-pan -2 0.734027 17949.2 1 4 CACCTG CCTTTGATCT + +4 predrem__nrMotif47 6 0.734027 17949.2 1 4 CACCTG AAAGAAAACA + +4 predrem__nrMotif649 -2 0.734027 17949.2 1 4 CACCTG TCTTTGCTCT + +4 cisbp__M5538-Antp-Awh-btn-CG18599-E5-ems-en-eve-inv-lab-lbl-Lim3-pb-ro-Scr-slou-Ubx-unpg 6 0.734027 17949.2 1 4 CACCTG CCTAATTACC - +4 cisbp__M5624-abd-A-Antp-btn-HGTX-inv-lab-pb-Scr-Ubx 6 0.734027 17949.2 1 4 CACCTG GTTAATTACT - +4 predrem__nrMotif2318 -2 0.734027 17949.2 1 4 CACCTG TCTTTGATTT - +4 taipale__MEOX2_DBD_NSTAATTANN-abd-A-Antp-btn-HGTX-inv-lab-pb-Scr-Ubx 6 0.734027 17949.2 1 4 CACCTG GTTAATTACT - +4 transfac_pro__M06361 -2 0.734027 17949.2 1 4 CACCTG GCTTTTCAAT - +4 transfac_pro__M01851 7 0.734027 17949.2 1 3 CACCTG AGGGGCCCAC - +4 cisbp__M3684-acj6-nub-pdm2-vvl 6 0.734602 17963.2 1 6 CACCTG GTGATTTGCATATTT + +4 cisbp__M4557-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.734602 17963.2 1 6 CACCTG GATGACGTCATCCCC + +4 cisbp__M6413 8 0.734602 17963.2 1 6 CACCTG CCATCAATCAATTTA + +4 hocomoco__FOXD3_HUMAN.H11MO.0.D-FoxK-FoxP-HDAC1-Nf1-bin-croc-fd59A-fkh-foxo-slp2 6 0.734602 17963.2 1 6 CACCTG TTTGTTTACTTAGCA + +4 neph__UW.Motif.0476 5 0.734602 17963.2 1 6 CACCTG AATGAAAAATTCCAG + +4 scertf__zhu.ASG1 9 0.734602 17963.2 1 6 CACCTG CCGGCCGAGTTCCGG + +4 taipale_cyt_meth__MAFG_NYGCTGASTCAGCRN_eDBD_meth-cnc-maf-S-tj 0 0.734602 17963.2 1 6 CACCTG TTGCTGACTCAGCAA + +4 taipale_cyt_meth__ZFP41_NGCTAACTCTCCRCR_FL_repr-CG6654-CG7372 3 0.734602 17963.2 1 6 CACCTG CGCTAACTCTCCGCA + +4 taipale_tf_pairs__FLI1_BHLHA15_NCCGGAANCATATGN_CAP-dimm 6 0.734602 17963.2 1 6 CACCTG ACCGGAAACATATGT + +4 transfac_pro__M01150-dmrt93B-dsx 6 0.734602 17963.2 1 6 CACCTG TTTTGTTACAGTTTC + +4 transfac_pro__M09089-Adf1 1 0.734602 17963.2 1 6 CACCTG CCGCCGCCGCCGGCG + +4 cisbp__M2316-Stat92E 3 0.734602 17963.2 1 6 CACCTG CATTTCCTGAGAAAT - +4 cisbp__M4484-bi-egg-Hcf-mor-Six4 3 0.734602 17963.2 1 6 CACCTG GACTACAATTCCCAG - +4 cisbp__M5222-ey-Poxm-sv 4 0.734602 17963.2 1 6 CACCTG CCGTCACGCACCAAT - +4 flyfactorsurvey__NFAT_SANGER_5_FBgn0030505-NFAT 9 0.734602 17963.2 1 6 CACCTG TGGGAATTTTCCGTT - +4 flyfactorsurvey__sv_SOLEXA_5_FBgn0005561-Poxm-ey-sv 4 0.734602 17963.2 1 6 CACCTG CCGTCACGCACCAAT - +4 swissregulon__sacCer__SFL1 5 0.734602 17963.2 1 6 CACCTG TTTTATTTCTTCTAT - +4 taipale_cyt_meth__HSF1_NGAANNTTCYRGAAN_eDBD_meth-Hsf-pb 7 0.734602 17963.2 1 6 CACCTG GTTCTAGAACGTTCT - +4 taipale_cyt_meth__HSF2_NGAANNTTCNNGAAN_FL-Hsf-pb-srl 7 0.734602 17963.2 1 6 CACCTG CTTCTAGAACGTTCT - +4 taipale_cyt_meth__PAX7_NNATTMGTCACGSTN_eDBD_meth-foxo-gsb-gsb-n-prd 0 0.734602 17963.2 1 6 CACCTG AACCGTGACTAATCG - +4 taipale_tf_pairs__PBX4_HOXA10_YNNRTAAATCAATCA_CAP_repr-exd 9 0.734602 17963.2 1 6 CACCTG TGATTGATTTATGGG - +4 transfac_public__M00197 10 0.734602 17963.2 1 5 CACCTG TATCACTATAAACGA + +4 jaspar__MA0314.1-Chrac-14-Nf-YA-Nf-YB-Nf-YC-Spps-btd-kay -2 0.734602 17963.2 1 4 CACCTG TCTGATTGGTTCAGA + +4 cisbp__M5776-CG9727-Rfx 11 0.734602 17963.2 1 4 CACCTG CGTTGCTAGGCAACC - +4 hocomoco__HNF1A_HUMAN.H11MO.0.C 11 0.734602 17963.2 1 4 CACCTG AGTTAATCATTAACC - +4 hocomoco__HNF1B_HUMAN.H11MO.0.A 11 0.734602 17963.2 1 4 CACCTG GGTTAATCATTAACC - +4 tfdimers__MD00098-Jra-kay 2 0.735169 17977.1 1 6 CACCTG AATTTTTGAGTCATAATGAAACTAAAAA - +4 tfdimers__MD00384-Stat92E 15 0.735169 17977.1 1 6 CACCTG TTTCCTTTCCCATAATCCCTTTATCTTA - +4 tfdimers__MD00479-Jra-kay-tup 2 0.735169 17977.1 1 6 CACCTG TTTTATTGAGTCATTCATTAACTAATAA - +4 taipale_tf_pairs__ETV2_TBX21_RGTGTKRNNNNNNNNNNNCNCMGGAARN_CAP-pnt 24 0.735169 17977.1 1 4 CACCTG ACTTCCGGTGTGAACCCGCTTTCACACC - +4 cisbp__M2679-Atf6-CrebA-Xbp1 3 0.735404 17982.8 1 6 CACCTG GATGACGTGGCA + +4 taipale__XBP1_DBD_GATGACGTCATC-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.735404 17982.8 1 6 CACCTG GATGACGTCATC + +4 transfac_pro__M00912-nej 6 0.735404 17982.8 1 6 CACCTG ATTGCACAATTT + +4 transfac_pro__M05765 6 0.735404 17982.8 1 6 CACCTG TGGAATTGCCTC + +4 transfac_pro__M06106 2 0.735404 17982.8 1 6 CACCTG TGGACCATCAGT + +4 transfac_pro__M09476-dsf-tll 4 0.735404 17982.8 1 6 CACCTG CGTTGACTTTTT + +4 cisbp__M1392 5 0.735404 17982.8 1 6 CACCTG GAATATTCCGCG - +4 cisbp__M6045-maf-S-tj 3 0.735404 17982.8 1 6 CACCTG AGTCAGCATTTT - +4 fantom__motif76_GGAGCAGCCAAT 2 0.735404 17982.8 1 6 CACCTG ATTGGCTGCTCC - +4 hocomoco__E2F1_MOUSE.H11MO.0.A-Dp-E2f1-E2f2 1 0.735404 17982.8 1 6 CACCTG TTTCCCGCCCTC - +4 taipale__Mafb_DBD_NNNNTGCTGACN_repr-maf-S-tj 3 0.735404 17982.8 1 6 CACCTG AGTCAGCATTTT - +4 taipale_cyt_meth__TEF_NRTTAYGTAAYN_eDBD-Atf3-CG7786-CrebB-gt-hng1-Pdp1-vri-Xbp1 3 0.735404 17982.8 1 6 CACCTG CGTTACGTAACC - +4 transfac_pro__M01880 6 0.735404 17982.8 1 6 CACCTG GCATGATGCATG - +4 transfac_pro__M05342-Hr38 2 0.735404 17982.8 1 6 CACCTG GTGATCTAAACA - +4 transfac_pro__M05464-salm-salr 6 0.735404 17982.8 1 6 CACCTG CCTTTACGCCTC - +4 transfac_pro__M05511 1 0.735404 17982.8 1 6 CACCTG CCCCCTCCCCAG - +4 transfac_pro__M05762 6 0.735404 17982.8 1 6 CACCTG TATGTTGACAAG - +4 transfac_pro__M06265 6 0.735404 17982.8 1 6 CACCTG GATCTATGCATG - +4 transfac_pro__M06919 2 0.735404 17982.8 1 6 CACCTG TAAGCCTCAAAA - +4 transfac_public__M00178-Atf3-Atf6-CG7786-CrebB-gt-Jra-Pdp1-Xbp1 3 0.735404 17982.8 1 6 CACCTG GATTACGTCACC - +4 fantom__motif130_TTTCAAACNCCC 7 0.735404 17982.8 1 5 CACCTG TTTCAAACCCCC + +4 homer__NATGASTCABNN_Fosl2-CoRest-GATAe-Jra-Mef2-Myc-Stat92E-bon-brm-cnc-grn-kay-mor-nej-pan-pnr 7 0.735404 17982.8 1 5 CACCTG GATGAGTCATCC + +4 predrem__nrMotif1 7 0.735404 17982.8 1 5 CACCTG AAAACAAAAACA + +4 taipale_cyt_meth__GATA6_NGATAACGATCW_eDBD-GATAe-grn-pnr-srp 7 0.735404 17982.8 1 5 CACCTG CGATAACGATCT + +4 transfac_pro__M06400 -1 0.735404 17982.8 1 5 CACCTG TCGTCCGTCGGA + +4 cisbp__M5957-pho-phol -1 0.735404 17982.8 1 5 CACCTG CCATGCCGCCAT - +4 predrem__nrMotif1609 7 0.735404 17982.8 1 5 CACCTG CCGGGCTCCCCG - +4 transfac_pro__M05813 7 0.735404 17982.8 1 5 CACCTG TCGTTTTCACAG - +4 transfac_pro__M06036 7 0.735404 17982.8 1 5 CACCTG TCTGATGAACCA - +4 transfac_pro__M06673 7 0.735404 17982.8 1 5 CACCTG CGCGTTGGCCCT - +4 taipale_cyt_meth__ATF6_NRTGACGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.735404 17982.8 1 4 CACCTG GATGACGTCATC + +4 cisbp__M1875-CG7786-gt-Pdp1-vri 8 0.735404 17982.8 1 4 CACCTG TATTACGTAACC - +4 predrem__nrMotif2088 -2 0.735404 17982.8 1 4 CACCTG CCCGCCGTCCCC - +4 transfac_pro__M06177 8 0.735404 17982.8 1 4 CACCTG GTTTCTTGCACA - +4 transfac_pro__M06519 -2 0.735404 17982.8 1 4 CACCTG TCTTATCCCCGC - +4 transfac_pro__M06594 8 0.735404 17982.8 1 4 CACCTG TCCGATTGTACA - +4 transfac_pro__M06876 8 0.735404 17982.8 1 4 CACCTG GCTTAAAACACG - +4 tfdimers__MD00309-pho-phol-svp 10 0.736866 18018.6 1 6 CACCTG CCCCTCCCGCCATCTGGCCTTTGCCCCCTGCCCTCCC + +4 transfac_pro__M01475-al-Awh-CG11085-CG18599-E5-ems-en-eve-inv-lab-Lim3-slou-unpg 1 0.73768 18038.5 1 6 CACCTG AGAACTAATTAGTGGAC + +4 c2h2_zfs__M4447 4 0.73768 18038.5 1 6 CACCTG TGAATTCCTAGAAAGCA - +4 taipale_cyt_meth__RFX5_NYRRCAACSGTTGCYAN_eDBD_repr 4 0.73768 18038.5 1 6 CACCTG ATAGCAACGGTTGCTAT - +4 taipale_tf_pairs__ETV2_ONECUT2_NRTCRATANCGGAARYN_CAP_repr-onecut-pnt 3 0.73768 18038.5 1 6 CACCTG CACTTCCGGTATTGATT - +4 transfac_pro__M06712 7 0.73768 18038.5 1 6 CACCTG ATCCTTTAGCCTAATCC - +4 transfac_pro__M09033-Adf1-Taf1 2 0.73768 18038.5 1 6 CACCTG GCCGCCGCCGCCGCCGC - +4 taipale_cyt_meth__PAX1_NSGTCACGCWTSANYGN_eDBD_meth_repr-ey-Poxm-sv-toy 12 0.73768 18038.5 1 5 CACCTG GCAGTCAAGCGTGACGG - +4 hocomoco__VSX1_HUMAN.H11MO.0.D-CG34367-Dll-E5-Vsx1-Vsx2-ems-en-gsb-gsb-n-inv-pdm3-prd-ro-unpg 4 0.737716 18039.4 1 6 CACCTG TAATTAGCTAATTT + +4 taipale__GLIS3_DBD_GACCCCCCGCGNNG-ci-lmd-sug 0 0.737716 18039.4 1 6 CACCTG GACCCCCCACGAAG + +4 taipale_cyt_meth__GLIS2_RCCCCCCRCGWWGN_eDBD_meth-lmd-sug 6 0.737716 18039.4 1 6 CACCTG ACCCCCCACGAAGC + +4 transfac_pro__M07908-Aef1 8 0.737716 18039.4 1 6 CACCTG GCAACAACAACAAT + +4 cisbp__M5098-btd-CG3065-CG42741-dar1-luna-Sp1-Spps 6 0.737716 18039.4 1 6 CACCTG GGCCACGCCCATTT - +4 cisbp__M5491-ci-lmd-sug 0 0.737716 18039.4 1 6 CACCTG GACCCCCCGCGAAG - +4 cisbp__M5492-ci-lmd-sug 0 0.737716 18039.4 1 6 CACCTG GACCCCCCACGAAG - +4 fantom__motif142_TCATATAGAGAAGC 7 0.737716 18039.4 1 6 CACCTG GCTTCTCTATATGA - +4 fantom__motif33_AGAGCATGAGACGG 4 0.737716 18039.4 1 6 CACCTG CCGTCTCATGCTCT - +4 hocomoco__PO2F3_HUMAN.H11MO.0.D-nub-pdm2-vvl 0 0.737716 18039.4 1 6 CACCTG CAAATTTGCATAAC - +4 taipale__FOXO3_full_GTAAACATGTTTAC-foxo 3 0.737716 18039.4 1 6 CACCTG GTAAACATGTTTAC - +4 taipale_tf_pairs__TEAD4_HOXA13_GGWATGNNNRTAAA_CAP_repr-sd 2 0.737716 18039.4 1 6 CACCTG TTTACGAGCATTCC - +4 transfac_pro__M00513-Atf-2-Atf3-Atf6-CG44247-CrebA-CrebB-Jra-kay-Xbp1 4 0.737716 18039.4 1 6 CACCTG CGATGACGTCAGAG - +4 transfac_pro__M07769-bs-bsh-CG15696-CG34367-CG9876-E5-ems-en-gsb-gsb-n-inv-prd 4 0.737716 18039.4 1 6 CACCTG TAATTAACTAATTA - +4 dbcorrdb__CTCF__ENCSR000DTF_1__m2-CTCF 6 0.737741 18040 1 6 CACCTG GGTGGCCACACGGGGAACTG + +4 dbcorrdb__CUX1__ENCSR000EFO_1__m3-ct 14 0.737741 18040 1 6 CACCTG GGCAGCAGGGCCTGCCCCTT + +4 dbcorrdb__EP300__ENCSR000BKK_1__m2-nej-SoxN 3 0.737741 18040 1 6 CACCTG ATTTGCATGACAAAGGGGGG + +4 dbcorrdb__ETS1__ENCSR000BKQ_1__m2-Six4 13 0.737741 18040 1 6 CACCTG CCGGCGGGGGGACTACAACT + +4 dbcorrdb__FOXM1__ENCSR000BRU_1__m2-Bgb-Bro-foxo-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 1 0.737741 18040 1 6 CACCTG TTTTTTGTGGTTTTTATTTT + +4 dbcorrdb__HSF1__ENCSR000EET_1__m3-Hsf 9 0.737741 18040 1 6 CACCTG GCGCAGCCATAGCATAATTT + +4 dbcorrdb__JUN__ENCSR000EZW_1__m1-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 12 0.737741 18040 1 6 CACCTG AAAAGGATGACTCATCCCTT + +4 dbcorrdb__MYC__ENCSR000DMP_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-E(z)-gce-HDAC1-lid-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Spps-SREBP-Taf1-tna-Usf-vtd 4 0.737741 18040 1 6 CACCTG GGGGCACGTGGCCGCCGGGG + +4 dbcorrdb__NR3C1__ENCSR000BHG_1__m2 10 0.737741 18040 1 6 CACCTG CCTGGCTAAGAACACACTGT + +4 dbcorrdb__POLR2A__ENCSR000EAR_1__m1-Brf-CrebB-E2f1-Eip74EF-E(z)-Hcf-Max-RpII215-Sin3A-SREBP-Taf1-TfIIFalpha-tna 2 0.737741 18040 1 6 CACCTG GGCGCTTCCGCCGTGGGCCG + +4 dbcorrdb__RAD21__ENCSR000EAC_1__m2-CTCF-vtd 0 0.737741 18040 1 6 CACCTG TTTGTGGGGCTATAGTGCCA + +4 dbcorrdb__SIN3A__ENCSR000BIS_1__m1-CTCF-Sin3A 6 0.737741 18040 1 6 CACCTG GCCCGGGAGCTGTCAGTGGT + +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m2-SREBP 2 0.737741 18040 1 6 CACCTG AGCGCGTTAGCCATTTGGGA + +4 dbcorrdb__TBP__ENCSR000DZZ_1__m2-Tbp 4 0.737741 18040 1 6 CACCTG TATGAATCCGGCGCCCTAAC + +4 dbcorrdb__TBP__ENCSR000EEL_1__m5-Tbp 3 0.737741 18040 1 6 CACCTG TAACGCCTTCCGAAACGGCA + +4 dbcorrdb__TCF12__ENCSR000BJG_1__m1-bin-croc-fkh-foxo-HDAC1-nej 13 0.737741 18040 1 6 CACCTG CCAAGCCTCTGTTTACTTAG + +4 dbcorrdb__TCF12__ENCSR000BQQ_1__m1-bin-croc-fd59A-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 4 0.737741 18040 1 6 CACCTG GTAGTCGCTGAGTAAACATT + +4 dbcorrdb__TRIM28__ENCSR000EYC_1__m2-bon 4 0.737741 18040 1 6 CACCTG TTTTCTGCTGAGTGATTTCA + +4 jaspar__MA0395.1 12 0.737741 18040 1 6 CACCTG TGATCGGCGCCGCACGACGA + +4 jaspar__MA0415.1 7 0.737741 18040 1 6 CACCTG ATTTGCTTACGTAAGCTCGT + +4 transfac_pro__M01560 12 0.737741 18040 1 6 CACCTG TGATCGGCGCCGCACGACGA + +4 transfac_pro__M06969-kn 5 0.737741 18040 1 6 CACCTG CGGATAACCCTTGTTATCAG + +4 cisbp__M2200 12 0.737741 18040 1 6 CACCTG TGATCGGCGCCGCACGACGA - +4 cisbp__M4299 12 0.737741 18040 1 6 CACCTG TGATCGGCGCCGCACGACGA - +4 dbcorrdb__CHD1__ENCSR000AQD_1__m4-Chd1 13 0.737741 18040 1 6 CACCTG GGTTTTCTCGTAGCTCCTGG - +4 dbcorrdb__CTCF__ENCSR000DUP_1__m2-CTCF-SMC3-vtd 9 0.737741 18040 1 6 CACCTG CTGCAGTTCCCCCTATGGCC - +4 dbcorrdb__EZH2__ENCSR000ATC_1__m3-E(z) 6 0.737741 18040 1 6 CACCTG GGAAGCGCTCTCTGACTGAA - +4 dbcorrdb__FOSL1__ENCSR000BMV_1__m1-cnc-CoRest-Jra-kay-Mef2-mor-Myc-pan-Stat92E 12 0.737741 18040 1 6 CACCTG ACAGGGATGAGTCACCGCGC - +4 dbcorrdb__HCFC1__ENCSR000EFN_1__m1-Brf-brm-CTCF-ERR-E(z)-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-SREBP-Taf1-TfAP-2-tna-usp-vtd 9 0.737741 18040 1 6 CACCTG CCCGGGCGCCGCCGGCTGGC - +4 dbcorrdb__JUN__ENCSR000FAH_1__m1-cnc-CoRest-CrebB-Jra-kay-mor-Myc-pan-Snr1 8 0.737741 18040 1 6 CACCTG GGATGAGTCATCCCCGCGGG - +4 dbcorrdb__NANOG__ENCSR000BMT_1__m3-Antp-B-H1-B-H2-Dfd-eve-lab-pb-Scr-tup-unpg-zen2 12 0.737741 18040 1 6 CACCTG AAAGAGAGCAATTAACATCT - +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m7-RpII215 7 0.737741 18040 1 6 CACCTG GAGCCGCCCGCTGAGTTGCG - +4 dbcorrdb__POLR2A__ENCSR000DYO_1__m2-RpII215 0 0.737741 18040 1 6 CACCTG CGCTTGGCGCTTCCGCTGCG - +4 dbcorrdb__POLR2A__ENCSR000EAY_1__m1-Atac3-Brf-brm-E2f1-Eip74EF-Ets96B-Ets97D-E(z)-Hcf-Hr78-Max-RpII215-Sin3A-Taf1-TfIIFalpha-tna 1 0.737741 18040 1 6 CACCTG GCGCTTCCGCCCCGCGCCGG - +4 dbcorrdb__RBBP5__ENCSR000AQC_1__m3-Rbbp5 8 0.737741 18040 1 6 CACCTG GACCGCGGCCGCGTCGCTCC - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m1-usp 6 0.737741 18040 1 6 CACCTG GCGTGCGCCTTCCGCTTAGG - +4 dbcorrdb__SIN3A__ENCSR000BLR_1__m2-Atac3-Brf-bs-Dif-dl-E2f1-E2f2-Eip74EF-Ets97D-E(z)-FoxP-Hcf-Myc-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 4 0.737741 18040 1 6 CACCTG CGCGCCACTTCCGGCTCCGG - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m7-Snr1 0 0.737741 18040 1 6 CACCTG CTCTTCTGCACACTGTCTTA - +4 hocomoco__P53_MOUSE.H11MO.0.A 1 0.737741 18040 1 6 CACCTG GGGCATGCCTGGGCATGTCC - +4 dbcorrdb__CTCF__ENCSR000DPM_1__m2-CTCF 15 0.737741 18040 1 5 CACCTG TGCAGTTCCCCATATTGCCA + +4 dbcorrdb__TCF7L2__ENCSR000EVE_1__m1-pan -2 0.737741 18040 1 4 CACCTG CCTTTGATGTTTCCGCCGCC - +4 dbcorrdb__ZNF274__ENCSR000EVR_1__m1 17 0.737741 18040 1 3 CACCTG CAACATCAGAGAACTCATAC - +4 cisbp__M5458-fd59A-foxo-slp2 3 0.738103 18048.8 1 6 CACCTG GTAAACATAAACA + +4 taipale__HSF4_DBD_TTCTAGAANNTTC-Hsf-pb 6 0.738103 18048.8 1 6 CACCTG TTCTAGAACGTTC + +4 taipale_cyt_meth__ZNF740_NYGCCCCCCCCAC_FL_meth 1 0.738103 18048.8 1 6 CACCTG CCGCCCCCCCCAC + +4 transfac_pro__M06932-oc 2 0.738103 18048.8 1 6 CACCTG TTAATCTGATTAT + +4 transfac_pro__M06946 2 0.738103 18048.8 1 6 CACCTG ATAATCTGATTAT + +4 transfac_pro__M06974 2 0.738103 18048.8 1 6 CACCTG ATAATCTGATTAT + +4 bergman__ftz-Antp-Dfd-Scr-ftz 7 0.738103 18048.8 1 6 CACCTG AGGTCATTAACGC - +4 cisbp__M3713-gsb-gsb-n-prd 6 0.738103 18048.8 1 6 CACCTG TCGTCACGCTTCA - +4 cisbp__M5567-Hsf-pb 6 0.738103 18048.8 1 6 CACCTG TTCTAGAACGTTC - +4 taipale_cyt_meth__ETV7_NYTTCCNGGAARN_FL_meth-aop-Stat92E 2 0.738103 18048.8 1 6 CACCTG ACTTCCCGGAAGT - +4 taipale_tf_pairs__ETV2_EOMES_TCACACCGGAWRY_CAP-pnt 2 0.738103 18048.8 1 6 CACCTG ACTTCCGGTGTGA - +4 taipale_tf_pairs__HOXB2_PITX1_TAATKRNGGATTA_CAP_repr-pb-Ptx1 3 0.738103 18048.8 1 6 CACCTG TAATCCCTAATTA - +4 transfac_pro__M00932-btd-CG3065-CG42741-dar1-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 1 0.738103 18048.8 1 6 CACCTG GGCCCCGCCCCCT - +4 cisbp__M3467 9 0.738103 18048.8 1 4 CACCTG GAAAAGTGAAACC + +4 tfdimers__MD00519-cad-Jra 3 0.738221 18051.7 1 6 CACCTG TAATAATTGAGTCATTTATTAAATAAT - +4 predrem__nrMotif2320 1 0.73863 18061.7 1 6 CACCTG CCACAAG + +4 swissregulon__hs__NKX2-3_NKX2-5.p2 1 0.73863 18061.7 1 6 CACCTG TTAATTG + +4 scertf__spivak.ERT1 1 0.73863 18061.7 1 6 CACCTG GTTCCGG - +4 stark__ATCWATG -1 0.73863 18061.7 1 5 CACCTG ATCAATG + +4 predrem__nrMotif1801 -1 0.73863 18061.7 1 5 CACCTG ACACAAT - +4 cisbp__M6472 -2 0.73863 18061.7 1 4 CACCTG CATTGTT + +4 hdpi__BOLL-bol 3 0.73863 18061.7 1 4 CACCTG CACAACA + +4 predrem__nrMotif32 -2 0.73863 18061.7 1 4 CACCTG CATGAAA + +4 predrem__nrMotif721 3 0.73863 18061.7 1 4 CACCTG GTCCCCC - +4 cisbp__M6327-pan -3 0.73863 18061.7 1 3 CACCTG CTTTGAT + +4 transfac_pro__M05122 4 0.73863 18061.7 1 3 CACCTG GGGATAC - +4 cisbp__M0943-al-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-ind-inv-lab-lbl-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-unpg-Vsx1-zfh2 2 0.739686 18087.6 1 6 CACCTG GCTAATTA + +4 cisbp__M1610 0 0.739686 18087.6 1 6 CACCTG TCATTCAT + +4 cisbp__M2022-brk 2 0.739686 18087.6 1 6 CACCTG GGCGCCAG + +4 cisbp__M4716 0 0.739686 18087.6 1 6 CACCTG CATCAATC + +4 cisbp__M5785 2 0.739686 18087.6 1 6 CACCTG TTAATCCC + +4 predrem__nrMotif159 2 0.739686 18087.6 1 6 CACCTG AAGACTTT + +4 predrem__nrMotif2047 1 0.739686 18087.6 1 6 CACCTG AGAACTAA + +4 predrem__nrMotif313 2 0.739686 18087.6 1 6 CACCTG CAAACATG + +4 taipale__RHOXF1_full_NTRAKCCN 2 0.739686 18087.6 1 6 CACCTG TTAATCCC + +4 taipale_cyt_meth__DLX3_NTCGTTAN_eDBD_meth-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-en-eve-exex-HGTX-ind-inv-lab-pb-Scr-Ubx 0 0.739686 18087.6 1 6 CACCTG ATCATTAA + +4 taipale_cyt_meth__EVX2_STCGTTAN_eDBD_meth-Antp-bsh-btn-CG34367-Dfd-Dll-en-eve-exex-ind-inv-lab-pb-Scr-unpg-Vsx1-Vsx2 0 0.739686 18087.6 1 6 CACCTG CTCATTAG + +4 taipale_cyt_meth__GSX2_STCGTTAN_eDBD_meth-Antp-Awh-bap-bsh-btn-CG34367-Dfd-Dll-Dr-en-eve-exex-ind-inv-lab-Lim1-pb-Scr-unpg 0 0.739686 18087.6 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__HOXA1_RTCGTTAN_FL_meth-Antp-bsh-btn-Dfd-Dll-Dr-eve-exex-ind-lab-pb-Scr 0 0.739686 18087.6 1 6 CACCTG ATCATTAA + +4 taipale_cyt_meth__VSX2_YTAATTAN_eDBD_meth-CG11294-Drgx-E5-ems-en-eve-exex-ind-inv-Lim3-pb-slou-Ubx-unpg-Vsx1-Vsx2 1 0.739686 18087.6 1 6 CACCTG CTAATTAC + +4 transfac_pro__M00492-Stat92E 0 0.739686 18087.6 1 6 CACCTG CATTTCCG + +4 transfac_pro__M01946 2 0.739686 18087.6 1 6 CACCTG AATTCCGG + +4 cisbp__M0045 0 0.739686 18087.6 1 6 CACCTG CGCATGCA - +4 cisbp__M0114-retn 1 0.739686 18087.6 1 6 CACCTG TAATTAAA - +4 cisbp__M0465 1 0.739686 18087.6 1 6 CACCTG AGGCCTCC - +4 hdpi__XRCC1-XRCC1 2 0.739686 18087.6 1 6 CACCTG AGCAAATT - +4 jaspar__MA0325.1 2 0.739686 18087.6 1 6 CACCTG AATTCCGG - +4 predrem__nrMotif245 3 0.739686 18087.6 1 5 CACCTG GCCAGACT + +4 cisbp__M0559 3 0.739686 18087.6 1 5 CACCTG GCAGCCCA - +4 cisbp__M0570 -1 0.739686 18087.6 1 5 CACCTG ACCGCTTC - +4 predrem__nrMotif2363 3 0.739686 18087.6 1 5 CACCTG GAGCGCCC - +4 predrem__nrMotif494 -1 0.739686 18087.6 1 5 CACCTG AACTCAGA - +4 predrem__nrMotif2267 4 0.739686 18087.6 1 4 CACCTG TTAGGGCC + +4 transfac_pro__M02092-sr 4 0.739686 18087.6 1 4 CACCTG CCCACACC + +4 hdpi__CD59-Rel 4 0.739686 18087.6 1 4 CACCTG GACTTCCC - +4 predrem__nrMotif1020 -2 0.739686 18087.6 1 4 CACCTG ACTCACTG - +4 cisbp__M0057 -3 0.739686 18087.6 1 3 CACCTG CTTTTAGA + +4 predrem__nrMotif462 5 0.739686 18087.6 1 3 CACCTG CAAACCAC + +4 taipale_cyt_meth__LBX2_CTCGTTAN_eDBD-ind -3 0.739686 18087.6 1 3 CACCTG CTCGTTAA + +4 taipale_cyt_meth__MEOX2_NYAATTAN_FL-abd-A-Antp-bsh-btn-CG32532-Dfd-Dll-lab-Lim1-Lim3-pb-Scr-Ubx-unpg 5 0.739686 18087.6 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__MEOX2_NYAATTAN_FL_meth-abd-A-Antp-bsh-btn-Dfd-Dll-en-exex-inv-lab-Lim1-Lim3-pb-Scr-Ubx-unpg 5 0.739686 18087.6 1 3 CACCTG GTAATTAC + +4 transfac_pro__M07599-arm -3 0.739686 18087.6 1 3 CACCTG CTTTGATG + +4 transfac_pro__M07806-al-ap-Awh-bsh-CG18599-CG34367-E5-ems-ind-lbe-lbl-pb-Ubx-unpg-Vsx2-zen2 -3 0.739686 18087.6 1 3 CACCTG CTAATTAA + +4 cisbp__M0717-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.739686 18087.6 1 3 CACCTG TTGTTTAC - +4 predrem__nrMotif2015 -3 0.739686 18087.6 1 3 CACCTG CTGCGCTC - +4 swissregulon__hs__FOS_FOS_B_L1__JUN_B_D_.p2-CoRest-Jra-cnc-kay-mor 5 0.739686 18087.6 1 3 CACCTG TGACTCAC - +4 tfdimers__MD00328-Nf-YA-Nf-YB-Nf-YC 21 0.739847 18091.5 1 6 CACCTG TTTAGTCATTGGTTAATGATTAACCAAATAA - +4 tfdimers__MD00587-E2f1 3 0.740595 18109.8 1 6 CACCTG CCCCCCGTTTCCCACTCCGCCCCCCC - +4 hocomoco__MAFA_HUMAN.H11MO.0.D 12 0.740613 18110.2 1 6 CACCTG CTGCTGACGCCGCAGCCTTCC + +4 jaspar__MA0336.1 12 0.740613 18110.2 1 6 CACCTG AGGACTATAGAACACTCTAAA + +4 taipale__MAFK_DBD_NNNNTGCTGASTCAGCANNNN-cic-cnc-Jra-kay-maf-S-nej-tj 12 0.740613 18110.2 1 6 CACCTG AAAATGCTGACTCAGCATTTT + +4 tfdimers__MD00218-CrebB-Eip74EF 6 0.740613 18110.2 1 6 CACCTG TTTCACTTCCTGTCACCTTCT + +4 transfac_pro__M01523 4 0.740613 18110.2 1 6 CACCTG GGGGAGCATGCATCAAGGAGG + +4 cisbp__M2083-Myb-Pbp95 2 0.740613 18110.2 1 6 CACCTG TTGACTTGACTCTGGCTGTGC - +4 cisbp__M5610-cic-cnc-Jra-kay-maf-S-nej-tj 12 0.740613 18110.2 1 6 CACCTG AAAATGCTGACTCAGCATTTT - +4 jaspar__MA0278.1-Myb-Pbp95 2 0.740613 18110.2 1 6 CACCTG TTGACTTGACTCTGGCTGTGC - +4 taipale_tf_pairs__GCM1_ELK1_RKRNRGGCGGAARCGGAAGNN_CAP_repr-gcm-gcm2 0 0.740613 18110.2 1 6 CACCTG TACTTCCGTTTCCGCCCGTAT - +4 transfac_pro__M00324 2 0.740613 18110.2 1 6 CACCTG TGCACCTGCGTGGGGCCGGAA - +4 hocomoco__THA11_HUMAN.H11MO.0.B-Hcf-Six4-bi-egg-mor 0 0.742406 18154.1 1 6 CACCTG GGCATGCTGGGAGTTGTAGTTC + +4 tfdimers__MD00064-E2f1-Tsf1-Tsf2-Tsf3 13 0.742406 18154.1 1 6 CACCTG TTTTTAGTTTCAGTTCCTTTTT + +4 tfdimers__MD00510 15 0.742406 18154.1 1 6 CACCTG ATAAATATTATATAATATTTAT + +4 transfac_public__M00207 16 0.742406 18154.1 1 6 CACCTG CTATCGGAATACTTTACTCCGA + +4 transfac_pro__M04663-foxo 11 0.742406 18154.1 1 6 CACCTG ATCGCATGATGCATCTTGAAAT - +4 transfac_public__M00198 16 0.742406 18154.1 1 6 CACCTG CGTTCGGAGGACAGTGCTCCGA - +4 transfac_public__M00261-kn 6 0.742406 18154.1 1 6 CACCTG ACAACCTCCCTGGGGAGTTGTG - +4 cisbp__M6483-Brf-brm-btd-cbt-CG42741-CoRest-ct-CTCF-dar1-E2f1-ERR-E(z)-HDAC1-kay-Klf15-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-tna-vtd 13 0.743147 18172.2 1 6 CACCTG CGGCCCCGCCCCCCCCCTGGCCCC - +4 taipale_cyt_meth__YY1_NGCCATYTTTGRCNNWNYGTGCT_FL_meth-pho-phol 2 0.743223 18174 1 6 CACCTG AGCACAAATTGCCAAAAATGGCG - +4 flyfactorsurvey__Ubx_FlyReg_FBgn0003944-Ubx 0 0.743545 18181.9 1 6 CACCTG TAATTG - +4 hdpi__NOLA1-CG4038 1 0.743545 18181.9 1 5 CACCTG ATTTCT - +4 transfac_pro__M01156 2 0.743545 18181.9 1 4 CACCTG CGCACG - +4 cisbp__M5756-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-PHDP-repo-ro-Traf4-unc-4 1 0.744544 18206.3 1 6 CACCTG TAATCTAATTA + +4 jaspar__MA0079.3-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-klu-luna-sd 0 0.744544 18206.3 1 6 CACCTG GCCCCGCCCCC + +4 predrem__nrMotif1758 3 0.744544 18206.3 1 6 CACCTG TGTTCCCTCTC + +4 taipale_cyt_meth__DUXA_TRAYNTAATCA_eDBD 1 0.744544 18206.3 1 6 CACCTG TAATCTAATCA + +4 transfac_pro__M07392-bcd-Ptx1 4 0.744544 18206.3 1 6 CACCTG GGATTAAAAGC + +4 transfac_pro__M09031 4 0.744544 18206.3 1 6 CACCTG CCGCCACCGCC + +4 transfac_public__M00185-Nf-YA-Nf-YB-Nf-YC 1 0.744544 18206.3 1 6 CACCTG TAACCAATCAC + +4 yetfasco__YBL103C_1445-Jra-Mef2-Myc-Stat92E-kay-nej-pan 3 0.744544 18206.3 1 6 CACCTG GATGACTCATC + +4 cisbp__M2273-Dp-E2f1-E2f2 2 0.744544 18206.3 1 6 CACCTG CCTTCCCGCCC - +4 cisbp__M6200-sr 1 0.744544 18206.3 1 6 CACCTG ACACCCACTCT - +4 cisbp__M6479-btd-CG42741-CTCF-dar1-E(z)-kay-Klf15-klu-Nf-YA-Nf-YB-sd-Sp1-Spps-Stat92E 0 0.744544 18206.3 1 6 CACCTG GCCCCGCCCCC - +4 hocomoco__SP1_MOUSE.H11MO.1.A-CG42741-CTCF-E(z)-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-klu-sd 0 0.744544 18206.3 1 6 CACCTG GCCCCGCCCCC - +4 predrem__nrMotif665 5 0.744544 18206.3 1 6 CACCTG AATGCCAGCCT - +4 hocomoco__SUH_MOUSE.H11MO.0.A-Su(H) -1 0.744544 18206.3 1 5 CACCTG GCGTGGGAAAA + +4 transfac_pro__M01826-Ptx1 6 0.744544 18206.3 1 5 CACCTG GACACTAATCT + +4 transfac_pro__M06826 6 0.744544 18206.3 1 5 CACCTG GGAAAGGACTG + +4 stark__RCGTGYYAAAT 6 0.744544 18206.3 1 5 CACCTG ATTTAACACGC - +4 transfac_pro__M02263-cnc-Jra-maf-S-nej -1 0.744544 18206.3 1 5 CACCTG TGCTGAGTCAT - +4 transfac_public__M00203-GATAe-grn-pnr 6 0.744544 18206.3 1 5 CACCTG AGGCCTTATCT - +4 fantom__motif153_ACTYNYYATYG -2 0.744544 18206.3 1 4 CACCTG ACTTATTATTG + +4 cisbp__M5552-Abd-B 7 0.744544 18206.3 1 4 CACCTG TTTTTACGACC - +4 predrem__nrMotif226 7 0.744544 18206.3 1 4 CACCTG AAAACAAAACA - +4 taipale__HOXC12_DBD_NGTCGTAAAAN-Abd-B 7 0.744544 18206.3 1 4 CACCTG TTTTTACGACC - +4 transfac_pro__M05115 7 0.744544 18206.3 1 4 CACCTG GAGCCGTTACT - +4 transfac_pro__M01099-kni 5 0.74459 18207.5 1 6 CACCTG CTAAAAAACTGGAACACA + +4 transfac_pro__M07891-lz-run-RunxA-RunxB 1 0.74459 18207.5 1 6 CACCTG TAACCGCATTAACCGCAA + +4 hocomoco__BARH2_HUMAN.H11MO.0.D-B-H1-B-H2-CG34367-en-inv-unpg 7 0.74459 18207.5 1 6 CACCTG CAATTAGGACCAATTAGC - +4 taipale_tf_pairs__ETV5_DLX2_RSCGGAANNNNNYAATTA_CAP-Ets96B 11 0.74459 18207.5 1 6 CACCTG TAATTGCCCACTTCCGGT - +4 taipale_tf_pairs__TEAD4_SOX15_NACAATRNNNNNGAATGY_CAP_repr-sd 3 0.74459 18207.5 1 6 CACCTG ACATTCCTTTCCATTGTT - +4 transfac_pro__M06500 6 0.74459 18207.5 1 6 CACCTG GCGCTTGACTGCTATTCA - +4 transfac_pro__M06884 3 0.74459 18207.5 1 6 CACCTG AATGACCCTAACTCCCCC - +4 hocomoco__PO3F1_MOUSE.H11MO.0.C-nub-pdm2-vvl 0 0.745116 18220.3 1 6 CACCTG CTCATGAATATTCAAG + +4 neph__UW.Motif.0439 7 0.745116 18220.3 1 6 CACCTG CACTGTTTTTTTTTCA + +4 transfac_pro__M01080 1 0.745116 18220.3 1 6 CACCTG AGGCCTGCGGTTAAAT + +4 yetfasco__YIL130W_807 10 0.745116 18220.3 1 6 CACCTG CCCGGCCGAGTTCCGG + +4 cisbp__M5992-B-H1-B-H2 7 0.745116 18220.3 1 6 CACCTG CATTTAGCAGCAATTA - +4 neph__UW.Motif.0341 8 0.745116 18220.3 1 6 CACCTG TGCTCTGGTGCCATCT - +4 taipale__Barhl1_DBD_TAAWYGNNNNTAAWYG_repr-B-H1-B-H2 7 0.745116 18220.3 1 6 CACCTG CATTTAGCAGCAATTA - +4 taipale__SOX9_full_AACAATRTKCAGWGTT-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.745116 18220.3 1 6 CACCTG AACACTGCACATTGTT - +4 taipale_cyt_meth__BCL6B_RYGTAATCTAGGAATW_eDBD_meth 2 0.745116 18220.3 1 6 CACCTG AATTCCTAGATTACGT - +4 transfac_pro__M01388-slou 10 0.745116 18220.3 1 6 CACCTG CAGAGCTAATTACCCC - +4 transfac_pro__M01595-Stat92E 5 0.745116 18220.3 1 6 CACCTG CCCCCTTCCCGGAAGC - +4 transfac_pro__M02848 7 0.745116 18220.3 1 6 CACCTG CCAGTCCCACTCCGCA - +4 transfac_pro__M02905-Sox15 0 0.745116 18220.3 1 6 CACCTG GGCATGAATTCAGTCC - +4 transfac_pro__M09236-Hsf 9 0.745116 18220.3 1 6 CACCTG AGCTTCTAGAATCTTC - +4 transfac_pro__M07044 11 0.745116 18220.3 1 5 CACCTG TGTTAATGATTAACTA + +4 cisbp__M1510 0 0.747691 18283.3 1 6 CACCTG AATTTTGGG + +4 cisbp__M5665-NfI 2 0.747691 18283.3 1 6 CACCTG GGTGCCAAG + +4 cisbp__M5744-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.747691 18283.3 1 6 CACCTG ATTTGCATA + +4 hocomoco__AHR_HUMAN.H11MO.0.B-ss-tgo 2 0.747691 18283.3 1 6 CACCTG GTTGCGTGC + +4 jaspar__MA0671.1-NfI 2 0.747691 18283.3 1 6 CACCTG CGTGCCAAG + +4 predrem__nrMotif936 3 0.747691 18283.3 1 6 CACCTG GGACACCCC + +4 taipale__HIC2_DBD_RTGCCMNNN_repr 1 0.747691 18283.3 1 6 CACCTG ATGCCCACC + +4 transfac_pro__M04784-Myc 3 0.747691 18283.3 1 6 CACCTG TTGCATCAG + +4 cisbp__M0109 1 0.747691 18283.3 1 6 CACCTG TAATTAAAA - +4 cisbp__M0992-al-Awh-CG18599-CG32532-CG34367-Dll-en-inv-lbl-Lim1-Lim3-OdsH-repo-Rx-unc-4 1 0.747691 18283.3 1 6 CACCTG CTAATTATC - +4 cisbp__M1070-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-pb-Scr-slou-tup-Ubx-zen2 1 0.747691 18283.3 1 6 CACCTG GGTCATTAA - +4 cisbp__M1079-Antp-B-H1-B-H2-CG11085-Dfd-Dr-E5-Hmx-NK7.1-Scr-Ubx-abd-A-bsh-btn-ems-eve-exex-ftz-ind-lab-pb-tup-unpg-zen2 1 0.747691 18283.3 1 6 CACCTG AGCAATTAA - +4 cisbp__M1122-Antp-Awh-B-H1-B-H2-C15-CG9876-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-Dr-E5-HGTX-Lim3-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-al-bsh-dve-ems-en-hbn-ind-inv-lab-lbe-lms-otp-pdm3 2 0.747691 18283.3 1 6 CACCTG ACCAATTAA - +4 cisbp__M5159-gsb-gsb-n-Poxn-prd 3 0.747691 18283.3 1 6 CACCTG CGTCACGCT - +4 jaspar__MA0291.1 3 0.747691 18283.3 1 6 CACCTG GCGCACATT - +4 predrem__nrMotif1148 1 0.747691 18283.3 1 6 CACCTG TCCCCATGA - +4 predrem__nrMotif1933-CTCF 2 0.747691 18283.3 1 6 CACCTG GCCCTCTGG - +4 predrem__nrMotif2245 2 0.747691 18283.3 1 6 CACCTG CAAATCTGT - +4 predrem__nrMotif2286 0 0.747691 18283.3 1 6 CACCTG TGCCATAAT - +4 predrem__nrMotif583 3 0.747691 18283.3 1 6 CACCTG CGGCGCCGC - +4 predrem__nrMotif791 3 0.747691 18283.3 1 6 CACCTG GAAGCCCTT - +4 predrem__nrMotif875 2 0.747691 18283.3 1 6 CACCTG CTCATCAGT - +4 taipale_tf_pairs__MEIS1_DRGX_TGTCAATTA_CAP_repr-CG11294-Drgx 0 0.747691 18283.3 1 6 CACCTG TAATTGACA - +4 transfac_pro__M01608 3 0.747691 18283.3 1 6 CACCTG GCGCACATT - +4 predrem__nrMotif2311 4 0.747691 18283.3 1 5 CACCTG AGATTCCCA + +4 predrem__nrMotif2335 4 0.747691 18283.3 1 5 CACCTG TGAGTATGT + +4 predrem__nrMotif287 4 0.747691 18283.3 1 5 CACCTG AAATTTCCA + +4 predrem__nrMotif722 4 0.747691 18283.3 1 5 CACCTG AGAGAAACT + +4 predrem__nrMotif1103 4 0.747691 18283.3 1 5 CACCTG ATCACACAA - +4 predrem__nrMotif2590-Dll 4 0.747691 18283.3 1 5 CACCTG TAATTAGCA - +4 predrem__nrMotif930 4 0.747691 18283.3 1 5 CACCTG GGGCCGCCC - +4 hocomoco__FOXP2_MOUSE.H11MO.0.A-FoxP-fkh-foxo 5 0.747691 18283.3 1 4 CACCTG TTGTTTACT + +4 predrem__nrMotif2216 -2 0.747691 18283.3 1 4 CACCTG CTTTGTGCT + +4 predrem__nrMotif2618 5 0.747691 18283.3 1 4 CACCTG AGAATGACT + +4 predrem__nrMotif529 -2 0.747691 18283.3 1 4 CACCTG GCTGCAGTC + +4 predrem__nrMotif537 5 0.747691 18283.3 1 4 CACCTG CTCTGAACA + +4 cisbp__M6248-fkh-foxo-FoxP-slp2 5 0.747691 18283.3 1 4 CACCTG CTGTTTACT - +4 cisbp__M6499-Su(H) 5 0.747691 18283.3 1 4 CACCTG TTTCCCACG - +4 transfac_pro__M04761-CG7786-gt-Hsf-Pdp1 5 0.747691 18283.3 1 4 CACCTG TTATGCAAC - +4 cisbp__M5560-Abd-B-cad 6 0.747691 18283.3 1 3 CACCTG TTTTATTAC + +4 tfdimers__MD00412-E2f1 9 0.748714 18308.3 1 6 CACCTG AAATAAAAGAACATTTTCTTCTTATTTTT - +4 cisbp__M0025 4 0.749057 18316.7 1 6 CACCTG CCGCCGCCGT + +4 cisbp__M0592 4 0.749057 18316.7 1 6 CACCTG AATTTAAATT + +4 cisbp__M0735-bin-CHES-1-like-fd102C-fd19B-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.749057 18316.7 1 6 CACCTG TTGTAAACAA + +4 cisbp__M0740-bin-CHES-1-like-fd59A-FoxK-foxo-FoxP-slp1-slp2 4 0.749057 18316.7 1 6 CACCTG TGTAAACAAA + +4 cisbp__M1221 2 0.749057 18316.7 1 6 CACCTG CGTAATTACG + +4 cisbp__M1575 3 0.749057 18316.7 1 6 CACCTG TTATAATTAA + +4 flyfactorsurvey__kni_FlyReg_FBgn0001320-kni 4 0.749057 18316.7 1 6 CACCTG GATCTCATTT + +4 homer__BBHWTATATA_TATA-box 0 0.749057 18316.7 1 6 CACCTG CCTTTATATA + +4 homer__NRYTTCCGGY_Elk4-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Taf1-aop-bs-pnt 3 0.749057 18316.7 1 6 CACCTG CACTTCCGGT + +4 predrem__nrMotif840 4 0.749057 18316.7 1 6 CACCTG CTGCCACAAA + +4 taipale__NEUROG2_full_RACATATGTY-amos-ato-HLH54F-Oli-tap 0 0.749057 18316.7 1 6 CACCTG AACATATGTC + +4 taipale_cyt_meth__HES1_GGCRCGTGNS_eDBD-dpn-E(spl)m5-HLH-h-Hey-Sidpn 2 0.749057 18316.7 1 6 CACCTG GGCACGTGGC + +4 transfac_pro__M07512 2 0.749057 18316.7 1 6 CACCTG GAGATATTCG + +4 cisbp__M1415 2 0.749057 18316.7 1 6 CACCTG ATTGCGTATT - +4 cisbp__M5056-kni 4 0.749057 18316.7 1 6 CACCTG GATCTCATTT - +4 fantom__motif126_AATGCAGTCG 0 0.749057 18316.7 1 6 CACCTG CGACTGCATT - +4 hocomoco__GFI1B_HUMAN.H11MO.0.A-sens-sens-2 1 0.749057 18316.7 1 6 CACCTG AAATCACAGC - +4 hocomoco__GFI1B_MOUSE.H11MO.0.A-sens-sens-2 1 0.749057 18316.7 1 6 CACCTG AAATCACAGC - +4 homer__ATGMATATDC_Pit1-nub-pdm2-vvl 1 0.749057 18316.7 1 6 CACCTG GCATATGCAT - +4 homer__CGGTTTCAAA_CHR 4 0.749057 18316.7 1 6 CACCTG TTTGAAACCG - +4 transfac_pro__M01299 4 0.749057 18316.7 1 6 CACCTG TAAATTCCGG - +4 transfac_pro__M07439-CG7786-gt-hng1-Irbp18-Pdp1-REPTOR-BP-vri-Xrp1 2 0.749057 18316.7 1 6 CACCTG ATTACGTAAC - +4 transfac_pro__M07590-nej 4 0.749057 18316.7 1 6 CACCTG TAATTAATTT - +4 cisbp__M6304-cad 5 0.749057 18316.7 1 5 CACCTG TAATAAAACT + +4 predrem__nrMotif1322 5 0.749057 18316.7 1 5 CACCTG AAAAGCAGCA + +4 predrem__nrMotif1425 5 0.749057 18316.7 1 5 CACCTG AACAACAGCA + +4 bergman__srp-GATAd-GATAe-grn-pnr-srp -1 0.749057 18316.7 1 5 CACCTG GTCTTATCGC - +4 cisbp__M1513 -1 0.749057 18316.7 1 5 CACCTG GCCGAAATTT - +4 taipale_cyt_meth__BHLHE23_ANCATATGNT_FL_meth-amos-ato-da-dimm-HLH54F-Oli-tap -1 0.749057 18316.7 1 5 CACCTG ACCATATGGT - +4 cisbp__M5623-Antp-btn-lab-pb-Scr-slou 6 0.749057 18316.7 1 4 CACCTG GCTAATTAAC + +4 taipale_cyt_meth__HOXA6_NGYAATTANN_eDBD-abd-A-Antp-ap-btn-cad-CG32532-Dfd-Dll-E5-ems-en-eve-ftz-HGTX-ind-lab-lms-OdsH-pb-Scr-slou-Ubx-unpg-Vsx1-zen2 6 0.749057 18316.7 1 4 CACCTG GTTAATTACC - +4 transfac_pro__M05380-tll -2 0.749057 18316.7 1 4 CACCTG CCTGATTTTT - +4 transfac_pro__M07792-ap-CG18599-E5-ems-en-eve-ind-inv-lab-lbl-pb-ro-slou-Ubx-unpg-Vsx1-Vsx2 6 0.749057 18316.7 1 4 CACCTG GCTAATTAGC - +4 transfac_pro__M03197 7 0.749057 18316.7 1 3 CACCTG ATGCCGCCAC + +4 hocomoco__ZN713_HUMAN.H11MO.0.D 12 0.75 18339.8 1 6 CACCTG TTTCGTGTCTTTTTTCTAT - +4 transfac_pro__M07611-nonA-nonA-l 8 0.75 18339.8 1 6 CACCTG TCCGCTGCCATCCGCCGTC - +4 transfac_public__M00035-cnc-maf-S-tj 11 0.75 18339.8 1 6 CACCTG TTGTGCTGAGTCAGCATTT - +4 taipale_tf_pairs__HOXB2_SPDEF_ANCCGGATNNNNNNMATTA_CAP_repr-Ets98B-pb -1 0.75 18339.8 1 5 CACCTG ACCCGGATGTACGTAATTA + +4 flyfactorsurvey__Hnf4_SANGER_10_FBgn0004914-Hnf4 3 0.750387 18349.2 1 6 CACCTG TGACCCCGCCAAAAA + +4 hocomoco__MEF2C_MOUSE.H11MO.0.A-Mef2-rump 0 0.750387 18349.2 1 6 CACCTG GTTCTATTTTTAGCT + +4 jaspar__MA0520.1-Stat92E 3 0.750387 18349.2 1 6 CACCTG CATTTCCTGAGAAAT + +4 taipale_cyt_meth__ZNF501_NSSCSACGCGAACAM_FL_meth_repr-CG6654-CG7372 4 0.750387 18349.2 1 6 CACCTG CGGCGACGCGAACAC + +4 transfac_pro__M06977 9 0.750387 18349.2 1 6 CACCTG CGTCCGCGCCCCCTT + +4 transfac_pro__M09080 2 0.750387 18349.2 1 6 CACCTG TCCTCCGCCGCCGCC + +4 c2h2_zfs__M3835-E(z)-Nf-YB-RpII215-Spps-btd-kay-vtd 5 0.750387 18349.2 1 6 CACCTG CCGAGACCCCTGCCC - +4 cisbp__M4549-aop-Eip74EF-Hr78 1 0.750387 18349.2 1 6 CACCTG TGACCCGGAAGTGGT - +4 cisbp__M6119-CG9650-nej 1 0.750387 18349.2 1 6 CACCTG CCACTTCCTCTTTTT - +4 factorbook__v-JUN-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 3 0.750387 18349.2 1 6 CACCTG GATGACGTCATCCTC - +4 flyfactorsurvey__gsb-n_SOLEXA_5_FBgn0001147-gsb-n 5 0.750387 18349.2 1 6 CACCTG TTAGTCACGCTCTAG - +4 hocomoco__NFAC1_MOUSE.H11MO.0.A-Jra-NFAT-kay 4 0.750387 18349.2 1 6 CACCTG GACTCATATTTTCCA - +4 hocomoco__SPI1_MOUSE.H11MO.0.A-CG9650-Dif-Stat92E-dl-nej-pnt 1 0.750387 18349.2 1 6 CACCTG TCACTTCCTCTTTTT - +4 scertf__harbison.MET4 7 0.750387 18349.2 1 6 CACCTG GGCACCACATTTTTT - +4 scertf__zhu.SFL1 5 0.750387 18349.2 1 6 CACCTG TTTTATTTCTTCTAT - +4 transfac_pro__M05531 5 0.750387 18349.2 1 6 CACCTG ACTAATACCGTTTCC - +4 transfac_pro__M08907 2 0.750387 18349.2 1 6 CACCTG AGAACAGGCTGTTCT - +4 transfac_pro__M09015 8 0.750387 18349.2 1 6 CACCTG CTTTTCTTCATCATC - +4 transfac_pro__M09413-Hsf-pb 7 0.750387 18349.2 1 6 CACCTG CTTCTAGAAGCTTCT - +4 flyfactorsurvey__crol_F7-16_SANGER_5_FBgn0020309-CG7368-CTCF-CoRest-Klf15-Rbbp5-SREBP-Spt20-crol-ct-l(3)neo38 -1 0.750387 18349.2 1 5 CACCTG ACCCCCCCCCTCCCC + +4 neph__UW.Motif.0130 -1 0.750387 18349.2 1 5 CACCTG AATTTTTTCCTTTTC + +4 taipale_cyt_meth__IRF8_NYGAAASYGAAASYN_eDBD 10 0.750387 18349.2 1 5 CACCTG ACGAAACCGAAACTA + +4 taipale_cyt_meth__IRF9_NYGAAASYGAAACYN_FL_meth 10 0.750387 18349.2 1 5 CACCTG ACGAAACTGAAACTA + +4 taipale_cyt_meth__LEF1_WCATCGRGRCGCTGW_FL_meth-pan -1 0.750387 18349.2 1 5 CACCTG ACATCGGGGCGCTGA + +4 cisbp__M4898-CG7368-CoRest-crol-ct-CTCF-Klf15-l(3)neo38-Rbbp5-Spt20-SREBP -1 0.750387 18349.2 1 5 CACCTG ACCCCCCCCCTCCCC - +4 transfac_pro__M07263 -2 0.750387 18349.2 1 4 CACCTG CCTTGGAGAGCAAGA + +4 cisbp__M2119-btd-Chrac-14-kay-Nf-YA-Nf-YB-Nf-YC-Spps -2 0.750387 18349.2 1 4 CACCTG TCTGATTGGTTCAGA - +4 flyfactorsurvey__nub_NAR_FBgn0085424-nub-pdm2-vvl 4 0.75075 18358.1 1 6 CACCTG TATGCAAATTAG + +4 homer__NTTTCCAGGAAA_STAT4-Stat92E 2 0.75075 18358.1 1 6 CACCTG GTTTCCAGGAAA + +4 taipale_cyt_meth__KLF15_NCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.75075 18358.1 1 6 CACCTG GCCACGCCCCCC + +4 taipale_cyt_meth__POU2F2_NTGCATATGCAN_eDBD_meth-nub-pdm2-vvl 3 0.75075 18358.1 1 6 CACCTG TTGCATATGCAA + +4 tiffin__TIFDMEM0000070 4 0.75075 18358.1 1 6 CACCTG AAATAAAATATA + +4 transfac_pro__M06252 2 0.75075 18358.1 1 6 CACCTG GGGGCCTGAACA + +4 transfac_pro__M07431-Sox14 1 0.75075 18358.1 1 6 CACCTG GCTCTTTGTTTT + +4 transfac_public__M00478-Cdc5 5 0.75075 18358.1 1 6 CACCTG GATTTAACATAA + +4 cisbp__M1404 3 0.75075 18358.1 1 6 CACCTG TGTGGCGTGTTA - +4 cisbp__M2257-nub-pdm2-vvl 4 0.75075 18358.1 1 6 CACCTG TATGCAAATTAG - +4 cisbp__M3018-Cdc5 5 0.75075 18358.1 1 6 CACCTG GATTTAACATAA - +4 cisbp__M3090-Atf3-Atf6-CG7786-CrebB-gt-Jra-Pdp1-Xbp1 3 0.75075 18358.1 1 6 CACCTG GATTACGTCACC - +4 jaspar__MA1044.1 3 0.75075 18358.1 1 6 CACCTG TGTGGCGTGTTA - +4 taipale_cyt_meth__BATF3_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.75075 18358.1 1 6 CACCTG GATGACGTCATC - +4 transfac_pro__M06764-CG2120 -1 0.75075 18358.1 1 5 CACCTG TCCGCCGAACCC + +4 neph__UW.Motif.0075 7 0.75075 18358.1 1 5 CACCTG GAAAAACTGTCT - +4 transfac_pro__M05637-crol 7 0.75075 18358.1 1 5 CACCTG AATCCCCCAACA - +4 transfac_pro__M05849 7 0.75075 18358.1 1 5 CACCTG TCGTTAGAAACT - +4 transfac_pro__M06249 7 0.75075 18358.1 1 5 CACCTG TCCCCCCCACGA - +4 transfac_pro__M06551 7 0.75075 18358.1 1 5 CACCTG TCATCAGCCCCA - +4 transfac_pro__M06577 7 0.75075 18358.1 1 5 CACCTG TATTCTGCACAG - +4 taipale__JDP2_full_NATGACGTCAYN-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.75075 18358.1 1 4 CACCTG GATGACGTCATC + +4 cisbp__M5590-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.75075 18358.1 1 4 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__ATF6B_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-E2f1-Jra-kay-REPTOR-BP-Xbp1 8 0.75075 18358.1 1 4 CACCTG GATGACGTCATC - +4 transfac_pro__M06509-CTCF -2 0.75075 18358.1 1 4 CACCTG TCTGTAGCAACA - +4 transfac_pro__M06360 -3 0.75075 18358.1 1 3 CACCTG CTGGCGAAAGTA + +4 tfdimers__MD00169-pan-pho-phol 3 0.751953 18387.5 1 6 CACCTG TTTTTCCTTTGTTATGCAAATGGCAGCTTTTT - +4 tfdimers__MD00365-E(bx)-nej 8 0.751953 18387.5 1 6 CACCTG TTTTTCTCTCACTTCCTTTTTTTGTTTTTTTT - +4 tfdimers__MD00198-HLH3B-Ptx1 16 0.752249 18394.7 1 6 CACCTG TTATTTCTAATCCTCTTCTCTCCTTTAC + +4 tfdimers__MD00235-CG7786-gt-Pdp1-Stat92E 20 0.752249 18394.7 1 6 CACCTG ATTTTCACTTCCCCTTTTTGCAAATTTA + +4 tfdimers__MD00346-CG7786-gt-ind-Pdp1 2 0.752249 18394.7 1 6 CACCTG CTTAAATGAGCTAATTAGCATTTCAAAA + +4 tfdimers__MD00569-btd-Spps 15 0.752249 18394.7 1 6 CACCTG CCCCCCCGCGCCCCCCGCCCCCCCCCCC - +4 cisbp__M5465-foxo 3 0.753272 18419.8 1 6 CACCTG GTAAACATGTTTAC + +4 cisbp__M6146-TfAP-2 3 0.753272 18419.8 1 6 CACCTG ACGCGCCTCGGGCG + +4 transfac_pro__M03886-Mad-SoxN 0 0.753272 18419.8 1 6 CACCTG CTCCATTGTTATGG + +4 transfac_pro__M07668-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-Xbp1 4 0.753272 18419.8 1 6 CACCTG CGATGACGTCATCG + +4 cisbp__M5141-ovo 8 0.753272 18419.8 1 6 CACCTG AGTACCGTTATTTG - +4 hocomoco__SP1_HUMAN.H11MO.1.A-Brf-CG3065-CG42741-CTCF-ERR-E(z)-Klf15-Nelf-E-Nf-YA-Nf-YB-RpII215-Sp1-Spps-Stat92E-brm-btd-dar1-kay-luna 8 0.753272 18419.8 1 6 CACCTG CGGCCCCGCCCCCC - +4 stark__TAATKRNGTCATTA 4 0.753272 18419.8 1 6 CACCTG TAATGACACAATTA - +4 transfac_pro__M09424 6 0.753272 18419.8 1 6 CACCTG TGTCCGTACAATTT - +4 yetfasco__YGL073W_615-Hsf-pb 2 0.753272 18419.8 1 6 CACCTG AGAATGTTCTAGAA - +4 elemento__TGATCTC 1 0.753482 18424.9 1 6 CACCTG TGATCTC + +4 predrem__nrMotif580 0 0.753482 18424.9 1 6 CACCTG CACAGCC + +4 elemento__GATGTCC 1 0.753482 18424.9 1 6 CACCTG GGACATC - +4 hdpi__NUCB1-NUCB1 1 0.753482 18424.9 1 6 CACCTG TTCCCAT - +4 hdpi__RFC3-RfC38 0 0.753482 18424.9 1 6 CACCTG TGCATTT - +4 predrem__nrMotif1251 -1 0.753482 18424.9 1 5 CACCTG TTCTGGC + +4 predrem__nrMotif1713 2 0.753482 18424.9 1 5 CACCTG GTCACAA + +4 hdpi__DNMT3A -1 0.753482 18424.9 1 5 CACCTG GCTTGCG - +4 hdpi__RAB14-Rab14 -1 0.753482 18424.9 1 5 CACCTG ACCACGC - +4 predrem__nrMotif595 2 0.753482 18424.9 1 5 CACCTG TGAATCA - +4 transfac_pro__M05361-btd-cbt-luna-Sp1-Spps 2 0.753482 18424.9 1 5 CACCTG CCGCCCT - +4 predrem__nrMotif1909 3 0.753482 18424.9 1 4 CACCTG AATTACA + +4 predrem__nrMotif2174 3 0.753482 18424.9 1 4 CACCTG TTTTACT + +4 predrem__nrMotif2205 -2 0.753482 18424.9 1 4 CACCTG TCTGATG + +4 hdpi__TSNAX-Trax -2 0.753482 18424.9 1 4 CACCTG CATTTCT - +4 swissregulon__hs__KLF12.p2-CG42741 -2 0.753482 18424.9 1 4 CACCTG CCCACTG - +4 predrem__nrMotif1551 -3 0.753482 18424.9 1 3 CACCTG CTAATTT + +4 predrem__nrMotif1627 -3 0.753482 18424.9 1 3 CACCTG CTAAGAA + +4 transfac_pro__M00664 4 0.753482 18424.9 1 3 CACCTG ATGAAAC + +4 flyfactorsurvey__HLHmgamma_SANGER_5_2_FBgn0002735-E(spl)mgamma-HLH -3 0.753482 18424.9 1 3 CACCTG CTTGACA - +4 hdpi__SMAD2-Smox 4 0.753482 18424.9 1 3 CACCTG CATATAA - +4 predrem__nrMotif229 -3 0.753482 18424.9 1 3 CACCTG CTAGAAA - +4 cisbp__M1606 7 0.753501 18425.4 1 6 CACCTG ATAACAATACATT + +4 cisbp__M5349-al-CG11294-Drgx-OdsH-repo-Traf4-unc-4 2 0.753501 18425.4 1 6 CACCTG CTAATTTAATCAA + +4 taipale__DUXA_DBD_NTRAYNTAATCAN_repr-al-CG11294-Drgx-OdsH-repo-Traf4-unc-4 2 0.753501 18425.4 1 6 CACCTG CTAATTTAATCAA + +4 taipale__FOXJ3_DBD_RTAAACATAAACA-fd59A-foxo-slp2 3 0.753501 18425.4 1 6 CACCTG GTAAACATAAACA + +4 taipale__HSF2_DBD_TTCTAGAANNTTC-Hsf-pb 6 0.753501 18425.4 1 6 CACCTG TTCTAGAACGTTC + +4 taipale_cyt_meth__PAX4_NYACGCTAATTAN_eDBD_meth_repr-ap-Awh-C15-CG34367-E5-ems-gsb-gsb-n-ind-Lim3-prd-ro-vvl 1 0.753501 18425.4 1 6 CACCTG TTACGCTAATTAG + +4 transfac_pro__M07670-Atf-2-Atf3-Atf6-CG44247-cnc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 7 0.753501 18425.4 1 6 CACCTG ATGACGTCATCAC + +4 transfac_pro__M09479-dsf-tll 4 0.753501 18425.4 1 6 CACCTG CTTTGACTTTTTT + +4 cisbp__M5566-Hsf-pb 6 0.753501 18425.4 1 6 CACCTG TTCTAGAACGTTC - +4 cisbp__M6246-FoxK-foxo-slp1 0 0.753501 18425.4 1 6 CACCTG TGTTTGTTTACCT - +4 cisbp__M6496-Stat92E 2 0.753501 18425.4 1 6 CACCTG CTTTTCTGGGAAA - +4 cisbp__M6535-brm-btd-CTCF-ERR-klu-Spps-sr 4 0.753501 18425.4 1 6 CACCTG CCCCCGCCCCCGC - +4 swissregulon__sacCer__RGT1 3 0.753501 18425.4 1 6 CACCTG TTTTTCCGGAAAA - +4 taipale_cyt_meth__POU3F4_NTAATTWATGCRN_eDBD-dve-vvl 1 0.753501 18425.4 1 6 CACCTG ATGCATAAATTAC - +4 taipale_tf_pairs__TEAD4_HOXB13_CYAATAAAATGYN_CAP_repr-sd 0 0.753501 18425.4 1 6 CACCTG CGCATTTTATTGC - +4 transfac_public__M00285-cnc 1 0.753501 18425.4 1 6 CACCTG CTTCCAAAATGAC - +4 transfac_pro__M01594-Mad-pan-SoxN -2 0.753501 18425.4 1 4 CACCTG CCTTTGTTTTGTT + +4 transfac_public__M00062 9 0.753501 18425.4 1 4 CACCTG GAAAAGTGAAACC + +4 transfac_pro__M07328-NFAT 9 0.753501 18425.4 1 4 CACCTG CTGGAAAATTCCA - +4 hocomoco__FOXG1_HUMAN.H11MO.0.D-CHES-1-like-FoxK-FoxL1-FoxP-croc-fd59A-slp1-slp2 8 0.753671 18429.5 1 6 CACCTG ATTGTTTATATTTTTTT + +4 hocomoco__PO3F2_MOUSE.H11MO.1.A-nub-pdm2-vvl 2 0.753671 18429.5 1 6 CACCTG GTCTCATGAATATTCAT + +4 taipale__ZNF282_DBD_CTTTCCCMYAACACKNN_repr 11 0.753671 18429.5 1 6 CACCTG CTTTCCCACAACACGAC + +4 transfac_pro__M01450-Ptx1 10 0.753671 18429.5 1 6 CACCTG TTAAGGGGATTAACTAC + +4 yetfasco__YPL248C_1510 4 0.753671 18429.5 1 6 CACCTG CGGAGGACTCTCGTCCG + +4 c2h2_zfs__M5114 11 0.753671 18429.5 1 6 CACCTG CTTTCCCACAACACGAC - +4 cisbp__M4413 4 0.753671 18429.5 1 6 CACCTG CGGAGGACTCTCGTCCG - +4 taipale__BCL6B_DBD_TGCTTTCTAGGAATTMM_repr 4 0.753671 18429.5 1 6 CACCTG TGAATTCCTAGAAAGCA - +4 taipale_cyt_meth__PAX6_NYACGCNTSANYGNNYN_eDBD-ey-Poxm-sv-toy 10 0.753671 18429.5 1 6 CACCTG TGTGCAGTCATGCGTGA - +4 taipale_cyt_meth__PAX9_NSGTCACGCWTSANYGN_eDBD-ey-Poxm-sv-toy 7 0.753671 18429.5 1 6 CACCTG GCAGTCATGCGTGACGG - +4 taipale_tf_pairs__TEAD4_DLX2_RCATTCYNNNNTAATTR_CAP_repr-sd 4 0.753671 18429.5 1 6 CACCTG CAATTACGGAGGAATGT - +4 transfac_pro__M01333 11 0.753671 18429.5 1 6 CACCTG TGCGATGATTTCGCCTT - +4 transfac_pro__M02795-D-Mad-Sox100B-Sox14 2 0.753671 18429.5 1 6 CACCTG TAGTCCTTTGTTCTTAT - +4 transfac_pro__M02861-srp 8 0.753671 18429.5 1 6 CACCTG CGCTGCGATATCGCCGC - +4 taipale_cyt_meth__PAX9_NSGTCRCGCWTSANYGN_eDBD_meth-ey-Poxm-sv-toy 12 0.753671 18429.5 1 5 CACCTG GCGCTCAAGCGTGACGA - +4 dbcorrdb__CEBPB__ENCSR000BRX_1__m2-Bgb-Bro-CG9650-ebi-foxo-lz-MTA1-like-nej-NFAT-run-RunxA-RunxB-Stat92E 8 0.754085 18439.6 1 6 CACCTG AAACAAACCACAGAAGAAAT + +4 dbcorrdb__CEBPB__ENCSR000EHE_1__m1-CG7786-gt-Irbp18-nej-Pdp1-Xrp1 11 0.754085 18439.6 1 6 CACCTG AAAGATTGCACAATAGCACT + +4 dbcorrdb__EP300__ENCSR000BPW_1__m2-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-pnr 14 0.754085 18439.6 1 6 CACCTG AGTCGTTAAGTAAACAGTGA + +4 dbcorrdb__EP300__ENCSR000EHV_1__m1-nej 2 0.754085 18439.6 1 6 CACCTG GCTGTCTGGATTATGTCAGC + +4 dbcorrdb__IRF1__ENCSR000EGK_1__m2 7 0.754085 18439.6 1 6 CACCTG TTTCCGCTTCTGGCTCAGCG + +4 dbcorrdb__MYC__ENCSR000DOM_1__m2-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 11 0.754085 18439.6 1 6 CACCTG AAGGGATGAGTCATCCCTTA + +4 dbcorrdb__MYC__ENCSR000FAG_1__m1-Brf-brm-Clk-cnc-CTCF-E2f1-Eip74EF-E(z)-gce-lid-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-SREBP-Taf1-tgo-tna-Usf 10 0.754085 18439.6 1 6 CACCTG CCGCGGCGGCCACGTGGGCC + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m3-Nelf-E 5 0.754085 18439.6 1 6 CACCTG GCTGCGAACCGCGCAGAGCA + +4 dbcorrdb__NFIC__ENCSR000BRN_1__m2-Bgb-Bro-CG9650-ebi-foxo-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 8 0.754085 18439.6 1 6 CACCTG TAAAAAACCACAAAAATTAT + +4 dbcorrdb__NFYB__ENCSR000DNM_1__m1-btd-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 3 0.754085 18439.6 1 6 CACCTG CGGCCTCTGATTGGCTGGGG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIA_1__m1-aop-Atac3-bs-Dif-dl-Eip74EF-Ets97D-Hcf-lid-Rbbp5-RpII215-Sin3A-Taf1 4 0.754085 18439.6 1 6 CACCTG CGCGCCACTTCCGCCTTCGG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIF_1__m1-aop-Atac3-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Hr78-lid-Max-pnt-Rbbp5-RpII215-Sin3A-Taf1 1 0.754085 18439.6 1 6 CACCTG GTCACTTCCGGCTGCGGTGC + +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m4-egg 11 0.754085 18439.6 1 6 CACCTG GAGAAGCCTTTTTTCTGTAG + +4 dbcorrdb__SIN3A__ENCSR000EBO_1__m3-CoRest-Sin3A 4 0.754085 18439.6 1 6 CACCTG CTGACAGCTGCCCGCCGGGG + +4 dbcorrdb__STAT1__ENCSR000FAV_1__m2-Stat92E 3 0.754085 18439.6 1 6 CACCTG GGCTGACTTCTGGGAAAGGG + +4 dbcorrdb__TAF1__ENCSR000BHT_1__m2-aop-Atac3-CG10431-Eip74EF-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1 3 0.754085 18439.6 1 6 CACCTG CCGCCACTTCCGCCATCTTT + +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m1-bon 7 0.754085 18439.6 1 6 CACCTG GTGGAGAAACCATGTGATTG + +4 dbcorrdb__ZBTB33__ENCSR000BPZ_1__m1-Chd1 6 0.754085 18439.6 1 6 CACCTG TCGCGAGAGTTGGGGGGGCC + +4 tfdimers__MD00388-pan 5 0.754085 18439.6 1 6 CACCTG TTTACCACTTCAAAGAAATT + +4 transfac_pro__M01655 1 0.754085 18439.6 1 6 CACCTG GGACATGTCCGGACATGTCC + +4 transfac_pro__M03558 11 0.754085 18439.6 1 6 CACCTG GTCAAGGCCTGCCCCTGACT + +4 transfac_pro__M06975-kn 5 0.754085 18439.6 1 6 CACCTG CGGATAACCCTTGTTATCAG + +4 dbcorrdb__BCL11A__ENCSR000BHA_1__m1-CG9650-Dif-dl-foxo-Jra-MTA1-like-nej-Stat92E 13 0.754085 18439.6 1 6 CACCTG CCTGATGACTCATTTCCGCA - +4 dbcorrdb__CBX3__ENCSR000BRT_1__m5-HP1b-HP1c-HP1e-Su(var)205 8 0.754085 18439.6 1 6 CACCTG TTGAAGGATATTTTTGCTGG - +4 dbcorrdb__CEBPB__ENCSR000BQI_1__m1-Irbp18-Xrp1 13 0.754085 18439.6 1 6 CACCTG GCCGAGATTGCACAACTGCA - +4 dbcorrdb__CEBPB__ENCSR000EDA_1__m1-CG7786-gt-Irbp18-nej-Pdp1-vri-Xrp1 13 0.754085 18439.6 1 6 CACCTG CCAAATATTGCATAATACCT - +4 dbcorrdb__CEBPZ__ENCSR000EDO_1__m2-CG7839 6 0.754085 18439.6 1 6 CACCTG TACCCTGCTTTGATTGGTTA - +4 dbcorrdb__CTCF__ENCSR000ANE_1__m2-CTCF-vtd 13 0.754085 18439.6 1 6 CACCTG AGTGGGGCTATAGTGCCCTC - +4 dbcorrdb__CTCF__ENCSR000DVA_1__m2-CTCF-vtd 13 0.754085 18439.6 1 6 CACCTG AGTGGGGCTATAGTGCCCCC - +4 dbcorrdb__EP300__ENCSR000BLW_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-Nf1-pnr 1 0.754085 18439.6 1 6 CACCTG GCCACTGTTTACTTAGCGTC - +4 dbcorrdb__EP300__ENCSR000EGY_1__m2-CTCF-nej 8 0.754085 18439.6 1 6 CACCTG TAATAAATTATATTAAATAT - +4 dbcorrdb__FOSL1__ENCSR000BNS_1__m2-kay 4 0.754085 18439.6 1 6 CACCTG CGGCCGCCGAGCGGACGGCG - +4 dbcorrdb__FOSL2__ENCSR000BHP_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Snr1-Stat92E 12 0.754085 18439.6 1 6 CACCTG TCAGGGATGAGTCATCCCTT - +4 dbcorrdb__HA-E2F1__ENCSR000EWX_1__m1-E2f1 9 0.754085 18439.6 1 6 CACCTG GGGCCTTCGCGCCAGCGGGG - +4 dbcorrdb__HSF1__ENCSR000EET_1__m7-Hsf 9 0.754085 18439.6 1 6 CACCTG AAAACCCTAGAACGGCCGGG - +4 dbcorrdb__JUN__ENCSR000EZT_1__m2-CrebB-ebi-Jra 14 0.754085 18439.6 1 6 CACCTG CCCGGTGATGACTTAATCCT - +4 dbcorrdb__MAFK__ENCSR000DYV_1__m1-cic-cnc-maf-S-nej-tj 2 0.754085 18439.6 1 6 CACCTG ATTTGCTGAGTCAGCAATTT - +4 dbcorrdb__NR2C2__ENCSR000EVN_1__m1-Eip74EF-Hcf-Hr78-lid-RpII215 3 0.754085 18439.6 1 6 CACCTG CGACCGCTTCCGGGTCGGGG - +4 dbcorrdb__POLR2A__ENCSR000EAM_1__m1-Brf-brm-CrebB-E2f1-Eip74EF-ERR-E(z)-Hcf-Hr78-Max-Myc-Rbbp5-RpII215-Sin3A-SREBP-Taf1-TfIIFalpha-tna 2 0.754085 18439.6 1 6 CACCTG GGCGCTTCCGCCGCGGGCCG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m8-RpII215 9 0.754085 18439.6 1 6 CACCTG CAACATTCGGTCATTGGTAG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EGF_1__m3-RpII215 14 0.754085 18439.6 1 6 CACCTG CCAAGCGGCCGCGTCGTTTG - +4 dbcorrdb__POU5F1__ENCSR000BMU_1__m1-CG9650-D-Mad-nej-nub-pan-pdm2-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN-vvl 0 0.754085 18439.6 1 6 CACCTG AATTTGCATAACAAAGGAAT - +4 dbcorrdb__RELA__ENCSR000EAW_1__m2-CG9650-Dif-dl-MTA1-like-Stat92E 11 0.754085 18439.6 1 6 CACCTG CACTGCTGTTTCACTTCCAG - +4 dbcorrdb__SREBF1__ENCSR000EEO_1__m2-btd-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 5 0.754085 18439.6 1 6 CACCTG CCCGGCCCCGGCCAATCAGA - +4 dbcorrdb__STAT2__ENCSR000FAT_1__m1-Stat92E 12 0.754085 18439.6 1 6 CACCTG TTCAGTTTCCGTTTCCCGCC - +4 dbcorrdb__STAT2__ENCSR000FBC_1__m1-ebi-MTA1-like-Stat92E 11 0.754085 18439.6 1 6 CACCTG AAAGGAAAATGAAACTGAAA - +4 dbcorrdb__STAT3__ENCSR000EDC_1__m2-aop-Stat92E 3 0.754085 18439.6 1 6 CACCTG AAATCATTTCCAGGAAATGA - +4 dbcorrdb__TRIM28__ENCSR000EYC_1__m3-bon-egg 7 0.754085 18439.6 1 6 CACCTG TGCAGTCTTACTGCTGAGAG - +4 dbcorrdb__ZNF274__ENCSR000EUK_1__m4 7 0.754085 18439.6 1 6 CACCTG CTTATTGAACATCAGAGAAC - +4 dbcorrdb__CTCF__ENCSR000ANS_1__m2-CTCF 15 0.754085 18439.6 1 5 CACCTG TGCAGTTCCCCATATTGCCA + +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m2 -1 0.754085 18439.6 1 5 CACCTG AGCAAATACCAAAATTAATA + +4 dbcorrdb__CTCF__ENCSR000AQU_1__m2-CTCF-SMC3-vtd 16 0.754085 18439.6 1 4 CACCTG CTGCAGTTCCCCATATGGCC - +4 taipale_cyt_meth__IRF6_RGTWTCGNNNNNNYGAWACY_eDBD_meth 16 0.754085 18439.6 1 4 CACCTG AGTATCACATAACCGATACT - +4 yetfasco__YKL185W_28 -1 0.754186 18442.1 1 5 CACCTG ATCAA + +4 bergman__TFAM-TFAM 1 0.754186 18442.1 1 4 CACCTG TTATC + +4 cisbp__M0960-CG4328-H2.0-Lmx1a-OdsH-repo-unc-4 2 0.754262 18444 1 6 CACCTG TTAATTAA + +4 cisbp__M0984-al-Awh-B-H1-B-H2-CG11085-Dr-E5-ems-en-inv-lab-OdsH-otp-repo-Rx-slou-unpg 2 0.754262 18444 1 6 CACCTG GCTAATTG + +4 predrem__nrMotif1149 2 0.754262 18444 1 6 CACCTG TCAGCATG + +4 predrem__nrMotif2661 0 0.754262 18444 1 6 CACCTG AATCTATT + +4 predrem__nrMotif760 0 0.754262 18444 1 6 CACCTG AGCCTGAA + +4 taipale__PRRX1_full_NYAATTAN-al-ap-Awh-B-H1-B-H2-bsh-C15-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ey-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh 1 0.754262 18444 1 6 CACCTG CCAATTAA + +4 taipale__Vsx1_DBD_NYAATTAN-al-Awh-bsh-C15-CG32532-CG34367-CG4328-CG9876-Dll-Dr-en-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-Pph13-repo-Ubx-unc-4-unpg-Vsx2 1 0.754262 18444 1 6 CACCTG CCAATTAA + +4 taipale_cyt_meth__GBX2_NTCGTTAN_FL_meth-Awh-CG34367-Dr-en-eve-exex-ind-inv-unpg-Vsx1-Vsx2 0 0.754262 18444 1 6 CACCTG CTCGTTAG + +4 taipale_cyt_meth__GBX2_NTCGTTAN_eDBD_meth-Awh-bap-bsh-btn-CG34367-Dll-Dr-en-eve-exex-ind-inv-Lim1-unpg-Vsx1-Vsx2 0 0.754262 18444 1 6 CACCTG CTCGTTAA + +4 taipale_cyt_meth__HOXD8_RTCGTTAN_eDBD_meth-abd-A-Dll-Ubx 0 0.754262 18444 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__UNCX_KTAATTAN_eDBD-al-Awh-en-Lim3-OdsH-repo-unc-4 1 0.754262 18444 1 6 CACCTG TTAATTAG + +4 taipale_cyt_meth__VSX1_YTAATTAN_eDBD-CG11294-CG9876-Drgx-E5-ems-en-eve-exex-ind-inv-Lim3-OdsH-pb-ro-Rx-Ubx-Vsx1-Vsx2 1 0.754262 18444 1 6 CACCTG CTAATTAC + +4 transfac_pro__M07788-Antp-bsh-E5-Scr 0 0.754262 18444 1 6 CACCTG GCCATTAC + +4 transfac_pro__M09004-Med 0 0.754262 18444 1 6 CACCTG TGTCTAGA + +4 cisbp__M0454 0 0.754262 18444 1 6 CACCTG CCCCATAG - +4 cisbp__M0561 1 0.754262 18444 1 6 CACCTG GAGCATCC - +4 cisbp__M0612 2 0.754262 18444 1 6 CACCTG TCCCCCCC - +4 cisbp__M1064-al-Awh-CG11085-E5-ems-en-exex-inv-lab-OdsH-otp-repo-Rx-slou-unpg 0 0.754262 18444 1 6 CACCTG TAATTAGC - +4 cisbp__M1429 2 0.754262 18444 1 6 CACCTG GACACGGA - +4 cisbp__M5755-al-Awh-B-H1-B-H2-bsh-C15-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ey-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.754262 18444 1 6 CACCTG CCAATTAA - +4 cisbp__M5772-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ey-gsb-gsb-n-ind-inv-lbe-lbl-Lim3-lms-Lmx1a-OdsH-otp-Pph13-prd-repo-Rx-slou-toy-Traf4-Ubx-unc-4-un 1 0.754262 18444 1 6 CACCTG CTAATTAA - +4 cisbp__M6110-al-Awh-bsh-C15-CG34367-CG4328-CG9876-Dll-Dr-en-ey-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-Pph13-repo-toy-unc-4-unpg-Vsx2 1 0.754262 18444 1 6 CACCTG CCAATTAA - +4 hdpi__ZNF3-CG6654-CG7372 1 0.754262 18444 1 6 CACCTG CCATTTTA - +4 jaspar__MA0939.1 1 0.754262 18444 1 6 CACCTG TTGCGTGT - +4 predrem__nrMotif1611 1 0.754262 18444 1 6 CACCTG GGATATGA - +4 cisbp__M1114 3 0.754262 18444 1 5 CACCTG TGTAATTT + +4 cisbp__M1835 3 0.754262 18444 1 5 CACCTG TTTCTCCG + +4 cisbp__M2360 3 0.754262 18444 1 5 CACCTG CGCCGCCA + +4 jaspar__MA0567.1 3 0.754262 18444 1 5 CACCTG CGCCGCCA + +4 neph__UW.Motif.0049-SoxN-acj6-nub-pdm2-vvl 3 0.754262 18444 1 5 CACCTG ATGCAAAT + +4 transfac_pro__M09143 -1 0.754262 18444 1 5 CACCTG ATCGGATC + +4 hdpi__ZNF124 -1 0.754262 18444 1 5 CACCTG TCATTTGA - +4 predrem__nrMotif148 -1 0.754262 18444 1 5 CACCTG TCTTTAGA - +4 predrem__nrMotif731 -1 0.754262 18444 1 5 CACCTG CTCTTGGA - +4 cisbp__M0046 4 0.754262 18444 1 4 CACCTG TGCACACA + +4 cisbp__M0560 -2 0.754262 18444 1 4 CACCTG CATGCAGC + +4 predrem__nrMotif1044 -2 0.754262 18444 1 4 CACCTG CATTCTCT + +4 predrem__nrMotif2478 4 0.754262 18444 1 4 CACCTG TGTCTACA + +4 cisbp__M0051 4 0.754262 18444 1 4 CACCTG GGAATACA - +4 c2h2_zfs__M0373 5 0.754262 18444 1 3 CACCTG ATTAGTAC + +4 cisbp__M0879-Dfd-Ubx-abd-A-cad 5 0.754262 18444 1 3 CACCTG TTAATTAC + +4 taipale_cyt_meth__LHX6_CTAATTAN_FL-Antp-Awh-btn-C15-E5-ems-en-eve-exex-inv-lab-Lim3-lms-OdsH-pb-Scr-slou -3 0.754262 18444 1 3 CACCTG CTAATTAC + +4 cisbp__M0751-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.754262 18444 1 3 CACCTG TTGTTTAC - +4 taipale_cyt_meth__HOXB1_STAATTAN_eDBD-abd-A-Antp-btn-CG32532-Dfd-lab-Lim3-Scr-Ubx 5 0.754262 18444 1 3 CACCTG TTAATTAC - +4 taipale_cyt_meth__HSF5_YNGAANNNNNNNNNNNNNAACRTTCYR_eDBD_meth 18 0.755152 18465.7 1 6 CACCTG TGGAATGTTGCGGACCCCAACATTCCA + +4 tfdimers__MD00475-Jra-kay 15 0.755152 18465.7 1 6 CACCTG ATTTTATTATTGACTCATAGTTTTTAA + +4 tfdimers__MD00284-Myc 16 0.755152 18465.7 1 6 CACCTG CCATTCAAGTGCTAATTACTTTATTAA - +4 transfac_pro__M05210 6 0.756991 18510.7 1 6 CACCTG TTGGGTTCCCTGCCGCTCCCC + +4 transfac_pro__M05291 6 0.756991 18510.7 1 6 CACCTG TGGTTTGCCCTGTTGGCCTCG + +4 transfac_pro__M07482-Cfp1-CG17440-CG3347 12 0.756991 18510.7 1 6 CACCTG CACAAATAAAAATAACAACCG + +4 transfac_pro__M09077-Taf1 1 0.756991 18510.7 1 6 CACCTG CCGCCGCCGCCGCCGCCACCG + +4 transfac_pro__M09117-brm-CG7839-maf-S-RpII215-SREBP-vtd 11 0.756991 18510.7 1 6 CACCTG TTTTTTTTTTTTTACTTTTTT + +4 flyfactorsurvey__acj6_SOLEXA_5_FBgn0000028-acj6 0 0.756991 18510.7 1 6 CACCTG CTCATTAAATATGCACACCAC - +4 transfac_pro__M00327-gsb-gsb-n-prd 11 0.756991 18510.7 1 6 CACCTG ACCTTAACCGTGACGAAATTT - +4 tfdimers__MD00160 18 0.757037 18511.8 1 6 CACCTG ATATACTAGTTAATTAGTAATCTCATATATT + +4 yetfasco__MATALPHA1-MCM1-dimer_1442-bs 3 0.757393 18520.5 1 6 CACCTG ACTTTCCTAATTAGGCCATCAATGAC - +4 cisbp__M5259-Ubx 0 0.758621 18550.5 1 6 CACCTG TAATTG + +4 swissregulon__sacCer__UPC2 1 0.758621 18550.5 1 5 CACCTG ATACGA + +4 hdpi__PRDX5-Prx5 1 0.758621 18550.5 1 5 CACCTG CGTCCT - +4 hdpi__ZNF304 1 0.758621 18550.5 1 5 CACCTG CGGCCT - +4 transfac_pro__M01126 1 0.758621 18550.5 1 5 CACCTG CTTTCT - +4 hdpi__BCL11A-CG9650 -2 0.758621 18550.5 1 4 CACCTG CATTTC - +4 transfac_pro__M03555-CG5641-NFAT 2 0.758621 18550.5 1 4 CACCTG TTTTCC - +4 transfac_pro__M08793-ham 2 0.758621 18550.5 1 4 CACCTG CTCATC - +4 swissregulon__hs__NFE2L1.p2-cnc 3 0.758621 18550.5 1 3 CACCTG GATGAC + +4 swissregulon__sacCer__FZF1-CG3065-hkb -3 0.758621 18550.5 1 3 CACCTG CTATCA + +4 jaspar__MA0227.1-hth -3 0.758621 18550.5 1 3 CACCTG CTGTCA - +4 transfac_pro__M01904-CG3065-hkb -3 0.758621 18550.5 1 3 CACCTG CTATCA - +4 transfac_pro__M07837-achi-hth-vis -3 0.758621 18550.5 1 3 CACCTG CTGTCA - +4 hdpi__RBM3-tra2 4 0.758621 18550.5 1 2 CACCTG CATATA + +4 hocomoco__SP1_HUMAN.H11MO.0.A-Brf-CG3065-CG42741-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Max-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-Spt20-Stat92E-brm-btd-cbt-ct-dar1-klu-luna-sr-tna-vtd 4 0.758836 18555.8 1 6 CACCTG CCCCCCCCCGGCCCCGCCCCCC - +4 hocomoco__ZN143_MOUSE.H11MO.0.A-Hcf-Six4-Stat92E-bi-egg-mor 4 0.758836 18555.8 1 6 CACCTG GGACTACAATTCCCAGCATGCC - +4 taipale_tf_pairs__TEAD4_CEBPD_NTTRCGYAANNNNNNRGWATGY_CAP-sd 3 0.758836 18555.8 1 6 CACCTG GCATTCCAATGTATTGCGCAAT - +4 tfdimers__MD00035-Stat92E 12 0.758836 18555.8 1 6 CACCTG AATTTGGGAAATCCCCATAGCT - +4 tfdimers__MD00269 3 0.758935 18558.2 1 6 CACCTG AATTTTATGATTGATTAATCATTAA - +4 tfdimers__MD00426-Med-sens-2 16 0.758935 18558.2 1 6 CACCTG AGTTTAGCAGGGATTAGACATAGAG - +4 tfdimers__MD00447-CG7786-gt-Pdp1-Taf7-Tbp 17 0.758935 18558.2 1 6 CACCTG AAAAAATATAAATTATGCAAAATAA - +4 tfdimers__MD00505-pan 4 0.758935 18558.2 1 6 CACCTG CTTTTCCTTTTATCCTGTGCATTCT - +4 predrem__nrMotif319 3 0.759573 18573.8 1 6 CACCTG CCTGGCCTTCT + +4 taipale__VSX1_full_NNYTAATTANN-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-inv-lab-lbe-OdsH-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 3 0.759573 18573.8 1 6 CACCTG GGCTAATTAGC + +4 taipale_cyt_meth__KLF6_NRCCACGCCCN_eDBD_meth-btd-cbt-CG42741-dar1-luna-Spps 0 0.759573 18573.8 1 6 CACCTG TGCCACGCCCA + +4 transfac_pro__M01749-NFAT 0 0.759573 18573.8 1 6 CACCTG TTCCATGGAAA + +4 transfac_public__M00487-TFAM 4 0.759573 18573.8 1 6 CACCTG TCCTTATCAGT + +4 cisbp__M5228-amos-da-Fer3-HLH54F-tap 1 0.759573 18573.8 1 6 CACCTG CCATATGTCAC - +4 jaspar__MA0471.1-Dp-E2f1-E2f2 2 0.759573 18573.8 1 6 CACCTG CCTTCCCGCCC - +4 swissregulon__sacCer__YKL222C 4 0.759573 18573.8 1 6 CACCTG TTATTTCCGTT - +4 taipale__EGR2_DBD_MCGCCCACGCA-klu-sr 0 0.759573 18573.8 1 6 CACCTG TGCGTGGGCGT - +4 taipale_cyt_meth__ZNF296_NASTGGWCASN_eDBD_meth_repr-CG9650 3 0.759573 18573.8 1 6 CACCTG ACTGTCCACTA - +4 transfac_pro__M01972-klu-sr 5 0.759573 18573.8 1 6 CACCTG CCGCCCACGCA - +4 transfac_pro__M05330-E5-ems 0 0.759573 18573.8 1 6 CACCTG TTCATATTAAC - +4 transfac_public__M00355 0 0.759573 18573.8 1 6 CACCTG TCGCTTTTATT - +4 hocomoco__SOX3_HUMAN.H11MO.0.B-Mad-Sox14-Sox100B-Sox102F-SoxN -1 0.759573 18573.8 1 5 CACCTG GCCTTTGTCCC + +4 idmmpmm__nub-nub-pdm2-vvl -1 0.759573 18573.8 1 5 CACCTG ATTTGCATATT + +4 transfac_pro__M06684-CG12299-CG31365-dati 6 0.759573 18573.8 1 5 CACCTG CATAGTAGCCT + +4 cisbp__M2280-cnc-CoRest-Jra-kay-maf-S-mor-Myc-nej-pan 6 0.759573 18573.8 1 5 CACCTG CTGAGTCATCC - +4 jaspar__MA0478.1-CoRest-Jra-Myc-kay-maf-S-mor-nej-pan 6 0.759573 18573.8 1 5 CACCTG ATGAGTCATCC - +4 cisbp__M2980-cnc-Jra-kay 7 0.759573 18573.8 1 4 CACCTG CGTGAGTCATC - +4 hocomoco__MIXL1_HUMAN.H11MO.0.D-Awh-C15-CG11294-CG32532-CG34367-E5-Lim3-OdsH-Pph13-Rx-Traf4-Vsx1-Vsx2-al-ap-ems-en-eve-inv-otp-repo-unc-4-unpg 7 0.759573 18573.8 1 4 CACCTG ATCTAATTAAC - +4 hocomoco__NKX22_MOUSE.H11MO.0.A-scro -3 0.759573 18573.8 1 3 CACCTG CTGGAGTGGCT + +4 tfdimers__MD00086-pho-phol 11 0.759721 18577.5 1 6 CACCTG ATTTTTTAATCCATCTTTTTTTT + +4 tfdimers__MD00383-pan-Stat92E 3 0.759721 18577.5 1 6 CACCTG TTTTTACTTTCATTTCCCTTTTT + +4 transfac_pro__M04668-FoxP 0 0.759721 18577.5 1 6 CACCTG AACTGGCACAACAACACAACAAA + +4 tfdimers__MD00271-Ptx1 8 0.759721 18577.5 1 6 CACCTG TTTATTCTAATCTGCTGAAATAA - +4 taipale_tf_pairs__GCM1_SPDEF_RTGNKGGCGGAWGNNNNTCCGGNN_CAP-Ets98B-gcm-gcm2 16 0.759731 18577.7 1 6 CACCTG ATGCGGGCGGATGCGTTTCCGGGT + +4 tfdimers__MD00190-klu 12 0.759731 18577.7 1 6 CACCTG TTTTCTTAATCCCTCCCCCTCTTC + +4 hocomoco__SP5_MOUSE.H11MO.0.C-CTCF-CoRest-Dif-Klf15-SREBP-Spps-Spt20-btd-ct-dl-klu-l(3)neo38-sr-usp 3 0.759731 18577.7 1 6 CACCTG CTCCTCCCCCTCCCCCTCCCCCCC - +4 hocomoco__ANDR_HUMAN.H11MO.0.A-fkh 6 0.760534 18597.3 1 6 CACCTG TGTTCTTTTTTGTTTGCT + +4 swissregulon__hs__HIC1.p2-Brf-CTCF-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-SREBP-brm-tna-vtd 10 0.760534 18597.3 1 6 CACCTG GGCCCGCGGGCACCCCCG - +4 taipale_tf_pairs__ETV2_DLX2_RCCGGAANNNNNYAATTA_CAP-pnt 11 0.760534 18597.3 1 6 CACCTG TAATTGCTCACTTCCGGT - +4 c2h2_zfs__M2164-br 13 0.760534 18597.3 1 5 CACCTG TAGATTTGTTTATTACTT + +4 cisbp__M2533-br 13 0.760534 18597.3 1 5 CACCTG GAGATTTGTCTATTACAT - +4 transfac_pro__M06355 15 0.760534 18597.3 1 3 CACCTG ACGCTCCCGTCGTCACAC - +4 transfac_pro__M01500 10 0.760789 18603.6 1 6 CACCTG CCCGGCCGAGTTCCGG + +4 transfac_pro__M02785-bowl-drm-odd-sob 8 0.760789 18603.6 1 6 CACCTG TTGTACAGTAGCAAAG + +4 transfac_pro__M02786 8 0.760789 18603.6 1 6 CACCTG TTGGGGGCGCCCCTAG + +4 transfac_pro__M02864 7 0.760789 18603.6 1 6 CACCTG AGCGGCACACACGCAA + +4 transfac_pro__M02922-pan 10 0.760789 18603.6 1 6 CACCTG GAAGATCAATCACTAA + +4 cisbp__M5296-B-H1-B-H2 7 0.760789 18603.6 1 6 CACCTG CATTTAACAGCAATTA - +4 cisbp__M5847-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.760789 18603.6 1 6 CACCTG AACACTGCACATTGTT - +4 taipale__BARHL2_DBD_TAAWYGNNNNTAAWYG-B-H1-B-H2 7 0.760789 18603.6 1 6 CACCTG CATTTAACACCAATTA - +4 taipale__POU4F3_DBD_NTGMATAATTAATGAN-acj6-vvl 0 0.760789 18603.6 1 6 CACCTG CTCATTAATTATGCAT - +4 taipale_cyt_meth__PAX3_NYRATTMGTCACGSTN_eDBD_meth-C15-foxo-gsb-gsb-n-prd 0 0.760789 18603.6 1 6 CACCTG AACCGTGACTAATTGA - +4 transfac_pro__M01098-vvl 4 0.760789 18603.6 1 6 CACCTG TTTTGAATTAATTAAA - +4 transfac_pro__M01901 4 0.760789 18603.6 1 6 CACCTG ATATCACTTTATACGA - +4 transfac_pro__M00405-Mef2-rump 11 0.760789 18603.6 1 5 CACCTG CTGTTTAAAAATACCC + +4 transfac_pro__M00938-E2f1-E2f2-eve -1 0.760789 18603.6 1 5 CACCTG GCCCGTTTCGCGCCAA - +4 taipale_cyt_meth__RFX2_NGTTRCCATGGYAACN_eDBD_meth-CG5846-CG9727-Max-Rfx-SREBP 12 0.760789 18603.6 1 4 CACCTG CGTTGCCATGGCAACG + +4 taipale_cyt_meth__RFX4_NGTTRCCATGGYAACN_eDBD_meth-CG5846-CG9727-Max-Rfx-SREBP 12 0.760789 18603.6 1 4 CACCTG CGTTGCCATGGCAACG + +4 cisbp__M0914-abd-A-Antp-bsh-btn-C15-cad-CG15696-Dbx-Dfd-en-ftz-H2.0-HGTX-Scr-slou-Ubx 1 0.76213 18636.4 1 6 CACCTG TTAATTGCC + +4 cisbp__M1013-abd-A-Antp-ap-bsh-btn-cad-Dfd-Dr-E5-ems-eve-exex-ftz-HGTX-ind-lab-lms-pb-Scr-slou-tup-Ubx-zen2 0 0.76213 18636.4 1 6 CACCTG TTAATGACC + +4 cisbp__M1102-al-CG15696-CG34367-en-inv-lab-OdsH-repo-unc-4 3 0.76213 18636.4 1 6 CACCTG GCCAATTAA + +4 cisbp__M2357 1 0.76213 18636.4 1 6 CACCTG CTGCATGCA + +4 flyfactorsurvey__Poxn_SOLEXA_5_FBgn0003130-Poxn-gsb-gsb-n-prd 3 0.76213 18636.4 1 6 CACCTG CGTCACGCT + +4 jaspar__MA0564.1 1 0.76213 18636.4 1 6 CACCTG CTGCATGCA + +4 predrem__nrMotif1323 2 0.76213 18636.4 1 6 CACCTG TTCATTTGC + +4 predrem__nrMotif2119 1 0.76213 18636.4 1 6 CACCTG TGACATCCT + +4 predrem__nrMotif83 3 0.76213 18636.4 1 6 CACCTG ACCAGCCTT + +4 swissregulon__hs__STAT2_4_6.p2-Stat92E 0 0.76213 18636.4 1 6 CACCTG TTCCCGGAA + +4 transfac_pro__M01960 2 0.76213 18636.4 1 6 CACCTG ATTTCCGTT + +4 cisbp__M0135-Xrp1 2 0.76213 18636.4 1 6 CACCTG ATTATTTAT - +4 cisbp__M5512 1 0.76213 18636.4 1 6 CACCTG ATGCCCACC - +4 cisbp__M6139-ss-tgo 2 0.76213 18636.4 1 6 CACCTG GTTGCGTGC - +4 jaspar__MA0428.1 2 0.76213 18636.4 1 6 CACCTG ATTTCCGTT - +4 predrem__nrMotif1001 0 0.76213 18636.4 1 6 CACCTG TGTCTGCTT - +4 predrem__nrMotif1652 1 0.76213 18636.4 1 6 CACCTG TGACTTGCT - +4 predrem__nrMotif918 0 0.76213 18636.4 1 6 CACCTG TGCTTCTGT - +4 taipale__POU5F1P1_DBD_TATGCWAAT-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.76213 18636.4 1 6 CACCTG ATTTGCATA - +4 hocomoco__NFIC_HUMAN.H11MO.1.A -1 0.76213 18636.4 1 5 CACCTG TCTTGGCAG + +4 predrem__nrMotif1769 4 0.76213 18636.4 1 5 CACCTG GTCTTTCCT + +4 predrem__nrMotif2208 4 0.76213 18636.4 1 5 CACCTG ACAATTCCA + +4 predrem__nrMotif425 4 0.76213 18636.4 1 5 CACCTG TCAGAGCCA + +4 predrem__nrMotif2052 4 0.76213 18636.4 1 5 CACCTG AACCCACAC - +4 transfac_pro__M01127-tup 4 0.76213 18636.4 1 5 CACCTG CTATTACGC - +4 predrem__nrMotif15 -2 0.76213 18636.4 1 4 CACCTG TCTTTTAAC + +4 predrem__nrMotif1755 5 0.76213 18636.4 1 4 CACCTG TGGAGGACA + +4 predrem__nrMotif2577 -2 0.76213 18636.4 1 4 CACCTG CATCATAAA - +4 predrem__nrMotif327 5 0.76213 18636.4 1 4 CACCTG AGCAAGACA - +4 cisbp__M0288 4 0.763677 18674.2 1 6 CACCTG ATGTCGACAT + +4 cisbp__M0913-abd-A-Abd-B-cad-Dbx-eve-Ubx 3 0.763677 18674.2 1 6 CACCTG TTTTATGACC + +4 cisbp__M1185 4 0.763677 18674.2 1 6 CACCTG CTTAATCCTA + +4 cisbp__M1258 3 0.763677 18674.2 1 6 CACCTG TGCGGCCAAA + +4 cisbp__M1460 4 0.763677 18674.2 1 6 CACCTG TTTGCTTCCG + +4 cisbp__M5501-bcd-Gsc-oc 3 0.763677 18674.2 1 6 CACCTG CCTAATCCGC + +4 hdpi__VSX1 3 0.763677 18674.2 1 6 CACCTG GGGAAACTGA + +4 predrem__nrMotif1419 0 0.763677 18674.2 1 6 CACCTG TGGCTTTTGA + +4 predrem__nrMotif1777 4 0.763677 18674.2 1 6 CACCTG GATGCCCCAG + +4 taipale_cyt_meth__KLF16_NCCACRCCCN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.763677 18674.2 1 6 CACCTG GCCACGCCCC + +4 taipale_cyt_meth__OSR1_NGCTACYGTN_eDBD-bowl-drm-odd-sob 3 0.763677 18674.2 1 6 CACCTG TGCTACTGTT + +4 transfac_pro__M03190 4 0.763677 18674.2 1 6 CACCTG ATGCCGCCCG + +4 transfac_pro__M03825-sens-2 3 0.763677 18674.2 1 6 CACCTG TTCAATCAGA + +4 transfac_pro__M06526 0 0.763677 18674.2 1 6 CACCTG GAGCCGGCCC + +4 cisbp__M0194-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.763677 18674.2 1 6 CACCTG AACATATGGT - +4 cisbp__M0402-btd-CG3065-Dp-E2f1-E2f2-hkb-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 2 0.763677 18674.2 1 6 CACCTG CCCGCCCCCT - +4 cisbp__M1134 4 0.763677 18674.2 1 6 CACCTG GATATATTAC - +4 homer__TBGCACGCAA_Arnt_Ahr-ss-tgo 1 0.763677 18674.2 1 6 CACCTG TTGCGTGCCA - +4 predrem__nrMotif443 0 0.763677 18674.2 1 6 CACCTG GGACTGGCCT - +4 transfac_pro__M00322-E2f1-Max-Myc 2 0.763677 18674.2 1 6 CACCTG CGCGCGTGGC - +4 transfac_pro__M04614-Antp-Awh-E5-ems-en-eve-Scr-zen2 4 0.763677 18674.2 1 6 CACCTG TAATTAGCCT - +4 transfac_pro__M07796-ey-eyg-gsb-gsb-n-prd-toe 0 0.763677 18674.2 1 6 CACCTG TAATCGATTA - +4 yetfasco__YNL314W_690 3 0.763677 18674.2 1 6 CACCTG GCGCAATTTT - +4 bergman__eve-eve-zen 5 0.763677 18674.2 1 5 CACCTG TCAATTAAAT + +4 cisbp__M0757-bin-CHES-1-like-croc-fd102C-fd19B-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.763677 18674.2 1 5 CACCTG ATGTAAACAA + +4 cisbp__M5304-amos-ato-crp-da-dimm-HLH54F-Oli-tap -1 0.763677 18674.2 1 5 CACCTG ACCATATGGT + +4 fantom__motif140_WTAAATAACG 5 0.763677 18674.2 1 5 CACCTG TTAAATAACG + +4 predrem__nrMotif2057 -1 0.763677 18674.2 1 5 CACCTG TTCTGTGACT + +4 stark__TCAWTTAAMT-eve-zen 5 0.763677 18674.2 1 5 CACCTG TCAATTAAAT + +4 taipale__BHLHA15_DBD_NNCATATGNN-amos-ato-crp-da-dimm-HLH54F-Oli-tap -1 0.763677 18674.2 1 5 CACCTG ACCATATGGT + +4 taipale_cyt_meth__BHLHE23_ANCATATGNY_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.763677 18674.2 1 5 CACCTG ACCATATGGT + +4 taipale_cyt_meth__OLIG3_ACCATATGKT_FL_meth_repr-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.763677 18674.2 1 5 CACCTG ACCATATGTT + +4 cisbp__M0748-CHES-1-like-FoxK-FoxL1-FoxP-bin-fd19B-fd59A-fd102C-fkh-foxo-slp1-slp2 5 0.763677 18674.2 1 5 CACCTG TTGTTTACAA - +4 predrem__nrMotif122 -1 0.763677 18674.2 1 5 CACCTG CTCTGGGTCT - +4 taipale_cyt_meth__BHLHE23_ANCATATGNT_FL-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.763677 18674.2 1 5 CACCTG ACCATATGGT - +4 taipale_cyt_meth__SOX4_GAACAAAGRN_eDBD_repr-Mad-Sox100B-Sox14-SoxN -1 0.763677 18674.2 1 5 CACCTG CCCTTTGTTC - +4 cisbp__M1585-pan -2 0.763677 18674.2 1 4 CACCTG CCTTTGATCT + +4 cisbp__M4011-Taf7-Tbp -2 0.763677 18674.2 1 4 CACCTG TCTATAAAAG + +4 taipale__MEOX1_full_NSTAATTANN-Antp-btn-lab-pb-Scr-slou 6 0.763677 18674.2 1 4 CACCTG GCTAATTAAC + +4 transfac_pro__M03805-Nf-YA-Nf-YB-Nf-YC-yps -2 0.763677 18674.2 1 4 CACCTG CCAATCAGAA + +4 transfac_public__M00216-Taf7-Tbp -2 0.763677 18674.2 1 4 CACCTG TCTATAAAAG + +4 cisbp__M4250 6 0.763677 18674.2 1 4 CACCTG ATTAGTAAGC - +4 predrem__nrMotif1423 6 0.763677 18674.2 1 4 CACCTG TTAGAAAACA - +4 transfac_pro__M05879 6 0.763677 18674.2 1 4 CACCTG GATTATCAAC - +4 yetfasco__YER064C_2094-CoRest-Jra-Mef2-Myc-bon-cnc-kay-mor-nej-pan 6 0.763677 18674.2 1 4 CACCTG ATGAGTCATC - +4 tfdimers__MD00030 9 0.765524 18719.4 1 6 CACCTG TTTAATAAGAACACTGTGTTCTTTTTAAA + +4 tfdimers__MD00096-E2f1-nub-pdm2 21 0.765524 18719.4 1 6 CACCTG TATTTCCTTTCACATGCAAATCAGTAAAT + +4 tfdimers__MD00470 15 0.765524 18719.4 1 6 CACCTG TAGAAAAACATGTCAGACATGTCTTACTA + +4 tfdimers__MD00196-E2f1-nej 8 0.765524 18719.4 1 6 CACCTG TATTACTCTCACTTCCTTTTTTTTTTTTT - +4 predrem__nrMotif2681 6 0.765754 18725 1 6 CACCTG TTTAAAAATCTA + +4 tiffin__TIFDMEM0000106 2 0.765754 18725 1 6 CACCTG ATTATTTTATTT + +4 transfac_pro__M05914 3 0.765754 18725 1 6 CACCTG TTTTACTTTAAG + +4 transfac_pro__M06349 5 0.765754 18725 1 6 CACCTG TGTTTCATCCGC + +4 transfac_pro__M06639 6 0.765754 18725 1 6 CACCTG TGTGCCGACCGC + +4 hocomoco__HLTF_HUMAN.H11MO.0.D 6 0.765754 18725 1 6 CACCTG TTTGCAGCCTTC - +4 taipale_cyt_meth__ATF3_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.765754 18725 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__FOSB_NRTGACGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.765754 18725 1 6 CACCTG GATGACGTCATC - +4 taipale_cyt_meth__JDP2_NRTGAYGTCAYN_eDBD_meth-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.765754 18725 1 6 CACCTG GATGACGTCATC - +4 tiffin__TIFDMEM0000039 5 0.765754 18725 1 6 CACCTG ATTAAAAAATTT - +4 tiffin__TIFDMEM0000102 0 0.765754 18725 1 6 CACCTG TGGCTGCGATTG - +4 transfac_pro__M05662 6 0.765754 18725 1 6 CACCTG GCTCCATCCCAG - +4 transfac_pro__M05756 6 0.765754 18725 1 6 CACCTG TTTAATAAACAG - +4 transfac_pro__M05801 6 0.765754 18725 1 6 CACCTG TTTTTTAACACC - +4 transfac_pro__M05870 6 0.765754 18725 1 6 CACCTG TCGATCCATTTT - +4 transfac_pro__M06058 0 0.765754 18725 1 6 CACCTG GGCCTCTTACAG - +4 transfac_pro__M06226 1 0.765754 18725 1 6 CACCTG TCCGCTGTCCCA - +4 transfac_pro__M06233 4 0.765754 18725 1 6 CACCTG TCGGCACCCCCG - +4 transfac_pro__M06478 2 0.765754 18725 1 6 CACCTG GTAATCTGGACT - +4 transfac_pro__M06940 4 0.765754 18725 1 6 CACCTG AGATTACATAGA - +4 transfac_pro__M07954-Kr-Kr-h2 3 0.765754 18725 1 6 CACCTG TTTAACCCTTTC - +4 cisbp__M6231-btd-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-Tbp -1 0.765754 18725 1 5 CACCTG TTCTGATTGGTC + +4 tiffin__TIFDMEM0000022 7 0.765754 18725 1 5 CACCTG ATAAATCTATTT - +4 transfac_pro__M05669 7 0.765754 18725 1 5 CACCTG GATGATTGAGCT - +4 transfac_pro__M06122 7 0.765754 18725 1 5 CACCTG GCGTTCCCATCT - +4 transfac_pro__M06493 7 0.765754 18725 1 5 CACCTG GCCGATATTCCA - +4 transfac_pro__M06587-rn-sqz 7 0.765754 18725 1 5 CACCTG GCGGATTTACTA - +4 transfac_pro__M06718 7 0.765754 18725 1 5 CACCTG GGATCCATACAG - +4 transfac_pro__M06749-CG2120 7 0.765754 18725 1 5 CACCTG TCGGAATTACGC - +4 transfac_pro__M07869-gsb-gsb-n-prd 7 0.765754 18725 1 5 CACCTG GATTCGTCACGC - +4 transfac_pro__M05783 8 0.765754 18725 1 4 CACCTG TGGGGCATTATC + +4 transfac_pro__M06018-CG2120 8 0.765754 18725 1 4 CACCTG CGATAAAAAACA + +4 transfac_pro__M06085 -2 0.765754 18725 1 4 CACCTG TCTTAAATACGA + +4 transfac_pro__M05607-Myb 8 0.765754 18725 1 4 CACCTG AAATCCGTTACT - +4 cisbp__M4653-bon 3 0.765778 18725.6 1 6 CACCTG TCATACTGGAGAGAA + +4 cisbp__M4698-btd-EcR-HDAC1-Hnf4-Hr78-nej-Spps-svp-usp 3 0.765778 18725.6 1 6 CACCTG CTGGACTTTGGCCTC + +4 flyfactorsurvey__CG14962_SOLEXA_F2-4-Asciz 6 0.765778 18725.6 1 6 CACCTG GTGTTTCAACTTTTG + +4 neph__UW.Motif.0332 4 0.765778 18725.6 1 6 CACCTG TGAATTTTTTCTTCA + +4 taipale_cyt_meth__IRF8_NYGAAASYGAAASYN_FL 9 0.765778 18725.6 1 6 CACCTG TCGAAACCGAAACTA + +4 cisbp__M0281 9 0.765778 18725.6 1 6 CACCTG TATATTTCATAAATT - +4 cisbp__M4406 5 0.765778 18725.6 1 6 CACCTG GACCAACCCTAACGG - +4 cisbp__M5030-Hnf4 3 0.765778 18725.6 1 6 CACCTG TGACCCCGCCAAAAA - +4 hocomoco__HXA7_HUMAN.H11MO.0.D-Ubx-abd-A 3 0.765778 18725.6 1 6 CACCTG TCCAATCTATTGATC - +4 hocomoco__KAISO_HUMAN.H11MO.0.A-Chd1-CoRest 9 0.765778 18725.6 1 6 CACCTG TTCTCGCGAGATTTG - +4 jaspar__MA0501.1-Jra-cnc-kay-maf-S-nej 3 0.765778 18725.6 1 6 CACCTG AAATTGCTGAGTCAT - +4 jaspar__MA0548.1-Mef2 0 0.765778 18725.6 1 6 CACCTG TTCCAAAAATGGAAA - +4 taipale_tf_pairs__FLI1_DRGX_NNCGGAWGYMATTAN_CAP-CG11294-Drgx 5 0.765778 18725.6 1 6 CACCTG ATAATTACTTCCGGT - +4 taipale_tf_pairs__FOXO1_ELF1_NTGTTGNCGGAARNN_CAP-Eip74EF-foxo 0 0.765778 18725.6 1 6 CACCTG CACTTCCGGCAACAC - +4 transfac_pro__M01179 2 0.765778 18725.6 1 6 CACCTG CGCACAAAACGCGTA - +4 transfac_pro__M02739-bbx 0 0.765778 18725.6 1 6 CACCTG CACTTCATTGAATTA - +4 transfac_pro__M09238-Hsf 2 0.765778 18725.6 1 6 CACCTG AGAAGCTTCTAGAAG - +4 hocomoco__NFIC_MOUSE.H11MO.1.A-Nf1-NfI-tll -2 0.765778 18725.6 1 4 CACCTG CCTGGCACCCTGCCA + +4 swissregulon__sacCer__HAP3-Chrac-14-Nf-YA-Nf-YB-Nf-YC-Spps-btd-kay -2 0.765778 18725.6 1 4 CACCTG TCTGATTGGTTCAGA + +4 transfac_pro__M05465-esg-sna-wor 11 0.765778 18725.6 1 4 CACCTG TTGCGACGACAAACT + +4 transfac_pro__M07924-Aef1-CG4360 11 0.765778 18725.6 1 4 CACCTG ATTACAACAACAACC + +4 hocomoco__HNF1B_MOUSE.H11MO.0.A 11 0.765778 18725.6 1 4 CACCTG AGTTAATCATTAACT - +4 transfac_pro__M01172-CG9650-ebi-Eip74EF-nej-Stat92E-sv 0 0.765921 18729.1 1 6 CACCTG AACTTTCACTTCCTCTTTT + +4 cisbp__M4093-cnc-maf-S-tj 11 0.765921 18729.1 1 6 CACCTG TTGTGCTGAGTCAGCATAT - +4 transfac_pro__M06028 0 0.765921 18729.1 1 6 CACCTG GCCCTCAAACACTCATAAT - +4 transfac_pro__M09264-bs 3 0.765921 18729.1 1 6 CACCTG ACTTTCCAAAAAAGGAAAG - +4 elemento__CGCCCTC 1 0.768053 18781.2 1 6 CACCTG CGCCCTC + +4 elemento__TGCCCTC 1 0.768053 18781.2 1 6 CACCTG TGCCCTC + +4 elemento__TGGCCTC 1 0.768053 18781.2 1 6 CACCTG TGGCCTC + +4 predrem__nrMotif1568 1 0.768053 18781.2 1 6 CACCTG TCAACAG + +4 predrem__nrMotif1662 0 0.768053 18781.2 1 6 CACCTG CACTGGC + +4 predrem__nrMotif2257 0 0.768053 18781.2 1 6 CACCTG GACATTG + +4 transfac_pro__M01938 1 0.768053 18781.2 1 6 CACCTG GCGCGTG + +4 hocomoco__NKX61_HUMAN.H11MO.1.B-HGTX 0 0.768053 18781.2 1 6 CACCTG TTCATTA - +4 predrem__nrMotif2597 1 0.768053 18781.2 1 6 CACCTG ATGGCTA - +4 yetfasco__YDR216W_576 0 0.768053 18781.2 1 6 CACCTG ACCCCAC - +4 predrem__nrMotif2457 -1 0.768053 18781.2 1 5 CACCTG TTCTTGT + +4 predrem__nrMotif2134 2 0.768053 18781.2 1 5 CACCTG CAAGCTT - +4 predrem__nrMotif2420 -1 0.768053 18781.2 1 5 CACCTG TCCTCAA - +4 transfac_pro__M01839 2 0.768053 18781.2 1 5 CACCTG CCCGCCA - +4 transfac_pro__M05332-btd-cbt-luna-Sp1-Spps 2 0.768053 18781.2 1 5 CACCTG CCGCCCT - +4 hdpi__TIMM8A -2 0.768053 18781.2 1 4 CACCTG CGTGCCC - +4 elemento__CCGGAAC 4 0.768053 18781.2 1 3 CACCTG CCGGAAC + +4 elemento__CTTATCA -3 0.768053 18781.2 1 3 CACCTG CTTATCA + +4 elemento__CTTATCG -3 0.768053 18781.2 1 3 CACCTG CTTATCG + +4 elemento__CTTCATC -3 0.768053 18781.2 1 3 CACCTG CTTCATC + +4 elemento__CTTCCGC -3 0.768053 18781.2 1 3 CACCTG CTTCCGC + +4 elemento__CTTGGCC -3 0.768053 18781.2 1 3 CACCTG CTTGGCC + +4 elemento__CTTGTCC -3 0.768053 18781.2 1 3 CACCTG CTTGTCC + +4 elemento__TGGCAAC-CG5846-CG9727-Rfx-SREBP 4 0.768053 18781.2 1 3 CACCTG TGGCAAC + +4 elemento__TGTCAAC 4 0.768053 18781.2 1 3 CACCTG TGTCAAC + +4 elemento__CATGAAG -3 0.768053 18781.2 1 3 CACCTG CTTCATG - +4 elemento__CCGGAAG-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-pnt -3 0.768053 18781.2 1 3 CACCTG CTTCCGG - +4 hocomoco__SPDEF_HUMAN.H11MO.0.D-Ets98B 0 0.768439 18790.6 1 6 CACCTG AACCCGGATGAAGT + +4 idmmpmm__brk-brk 7 0.768439 18790.6 1 6 CACCTG GTAGCGCCACCCAA + +4 taipale__ZIC1_full_GACCMCCYRMTGNG_repr-opa 0 0.768439 18790.6 1 6 CACCTG GACCCCCCGCTGTG + +4 taipale_cyt_meth__ATF6_NGRTGACGTGGCAN_eDBD-Atf6-CrebA-CrebB-Xbp1 4 0.768439 18790.6 1 6 CACCTG TGATGACGTGGCAG + +4 cisbp__M6184-ct 8 0.768439 18790.6 1 6 CACCTG CCATCGATCCCCCT - +4 flyfactorsurvey__luna_SOLEXA_5_FBgn0040765-CG3065-CG42741-Sp1-Spps-btd-dar1-luna 6 0.768439 18790.6 1 6 CACCTG GGCCACGCCCATTT - +4 flyfactorsurvey__ovo_SOLEXA_5_FBgn0003028-ovo 8 0.768439 18790.6 1 6 CACCTG AGTACCGTTATTTG - +4 hocomoco__CUX1_HUMAN.H11MO.0.C-ct 8 0.768439 18790.6 1 6 CACCTG CCATCGATCCCCCT - +4 idmmpmm__shn-shn 5 0.768439 18790.6 1 6 CACCTG TGATTTTCTTGGTT - +4 neph__UW.Motif.0497 -1 0.768439 18790.6 1 5 CACCTG ACTAAAAATCACAG + +4 taipale__NFAT5_DBD_RTGGAAAANTMCNN_repr-NFAT 9 0.768439 18790.6 1 5 CACCTG ATGGAAAATTACAG + +4 cisbp__M5655-NFAT 9 0.768439 18790.6 1 5 CACCTG ATGGAAAATTACAG - +4 taipale_cyt_meth__POU6F1_NTATGYTAATKAGN_FL_meth-ems-pb-pdm3-Scr-vvl -2 0.768439 18790.6 1 4 CACCTG CCTCATTAACATAA - +4 transfac_pro__M01068-btd-Clp-Spps-sr 10 0.768439 18790.6 1 4 CACCTG GCCCCTCCCCCACC - +4 cisbp__M4030-cnc 1 0.768533 18792.9 1 6 CACCTG CTTCCAAAATGAC + +4 cisbp__M5996-Atf6-CrebA-CrebB-Xbp1 4 0.768533 18792.9 1 6 CACCTG TGATGACGTGGCA + +4 taipale__Creb3l2_DBD_TGCCACGTCATCA-Atf6-CrebA-CrebB-Xbp1 3 0.768533 18792.9 1 6 CACCTG TGCCACGTCATCA + +4 taipale_cyt_meth__KLF14_NRCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.768533 18792.9 1 6 CACCTG GACCACGCCCCCC + +4 transfac_pro__M06984-hbn-oc 2 0.768533 18792.9 1 6 CACCTG TTAATCTGATTAT + +4 cisbp__M1759 3 0.768533 18792.9 1 6 CACCTG CGGATCCGGAATA - +4 neph__UW.Motif.0172 2 0.768533 18792.9 1 6 CACCTG CATTCTTTTTTCT - +4 taipale_cyt_meth__NRL_NWWWNTGCTGACN_eDBD_repr-maf-S-tj 3 0.768533 18792.9 1 6 CACCTG CGTCAGCACATTC - +4 hocomoco__MAFK_HUMAN.H11MO.1.A-cnc-maf-S-tj 8 0.768533 18792.9 1 5 CACCTG TGCTGAGTCAGCA + +4 cisbp__M0056 2 0.76856 18793.6 1 6 CACCTG GGCCCCGT + +4 cisbp__M0107-htk 1 0.76856 18793.6 1 6 CACCTG CGATATTG + +4 cisbp__M0776 2 0.76856 18793.6 1 6 CACCTG TCGATCGG + +4 cisbp__M1004-al-C15-CG11294-CG15696-CG32532-CG34367-CG9876-Dll-Dr-en-ey-hbn-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-toy-Traf4-unc-4-unpg-Vsx1-Vsx2 1 0.76856 18793.6 1 6 CACCTG TTAATTAG + +4 taipale__RAXL1_DBD_NYAATTAN-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ey-ind-inv-lab-lbe-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-repo-Rx-slou-toy-Traf4-U 1 0.76856 18793.6 1 6 CACCTG CCAATTAA + +4 taipale__Uncx_DBD_YTAATTAN-al-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Drgx-E5-ems-en-ind-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.76856 18793.6 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__HOXA2_RTCGTTAN_eDBD_meth-Antp-btn-Dfd-Dll-eve-exex-ind-lab-pb-Scr 0 0.76856 18793.6 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__HOXA7_RTCGTTAN_eDBD_meth-abd-A-Antp-btn-Dfd-Dll-exex-Scr-Ubx 0 0.76856 18793.6 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__PITX1_NTAATCCN_eDBD_meth-bcd-Ptx1 2 0.76856 18793.6 1 6 CACCTG CTAATCCG + +4 taipale_cyt_meth__SHOX_CYAATTAN_eDBD-al-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-E5-en-ey-hbn-ind-inv-lab-Lim3-lms-Lmx1a-OdsH-otp-repo-Rx-slou-toy-Traf4-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.76856 18793.6 1 6 CACCTG CTAATTAA + +4 cisbp__M0900-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm3-PH 1 0.76856 18793.6 1 6 CACCTG CCAATTAA - +4 cisbp__M1071-abd-A-Antp-ap-Awh-bsh-btn-CG18599-CG4328-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-HGTX-ind-lab-Lim3-lms-Lmx1a-otp-pb-Scr-slou-tup-Ubx-unpg-Vsx1-zen-zen2 0 0.76856 18793.6 1 6 CACCTG GTCATTAA - +4 cisbp__M1193-al-B-H1-B-H2-C15-CG11085-CG15696-CG32532-CG34367-CG9876-Dr-E5-ems-en-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.76856 18793.6 1 6 CACCTG CCAATTAA - +4 cisbp__M5342-Dll-Dr 1 0.76856 18793.6 1 6 CACCTG CCAATTAC - +4 cisbp__M6000-Dll-Dr 1 0.76856 18793.6 1 6 CACCTG CCAATTAC - +4 jaspar__MA0630.1-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-Dll-Dr-Drgx-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Traf4-Ubx-Vsx1-Vsx2-al-ap-bsh-ems-en-ey-gsb-gsb 1 0.76856 18793.6 1 6 CACCTG CCAATTAA - +4 taipale_cyt_meth__MSX1_NCAATTAN_FL_meth-bsh-Dll-Dr-slou 1 0.76856 18793.6 1 6 CACCTG GTAATTGG - +4 transfac_pro__M07819-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-inv-lbe-Lim3-lms-OdsH-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.76856 18793.6 1 6 CACCTG CTAATTGG - +4 cisbp__M0131-CG14215 3 0.76856 18793.6 1 5 CACCTG AAATAAAT + +4 cisbp__M2109 3 0.76856 18793.6 1 5 CACCTG GGCTTCCA + +4 hdpi__OLIG3 -1 0.76856 18793.6 1 5 CACCTG GCATTTCA - +4 jaspar__MA0304.1 3 0.76856 18793.6 1 5 CACCTG GGCTTCCA - +4 yetfasco__YHR178W_2068 -1 0.76856 18793.6 1 5 CACCTG CCCGCGGA - +4 cisbp__M0001 4 0.76856 18793.6 1 4 CACCTG TTATCACT + +4 cisbp__M1608 -2 0.76856 18793.6 1 4 CACCTG TCTTTGTT + +4 predrem__nrMotif161 4 0.76856 18793.6 1 4 CACCTG ATTCTTCC + +4 predrem__nrMotif1918 4 0.76856 18793.6 1 4 CACCTG GAGACACT + +4 predrem__nrMotif1926 4 0.76856 18793.6 1 4 CACCTG ACTGCACT + +4 predrem__nrMotif2079 4 0.76856 18793.6 1 4 CACCTG TTATCACT + +4 predrem__nrMotif834 4 0.76856 18793.6 1 4 CACCTG AAGACACA + +4 predrem__nrMotif902 4 0.76856 18793.6 1 4 CACCTG GCAAATCC + +4 homer__TAATTAGN_Lhx2-Awh-CG9876-CG18599-E5-Lim3-OdsH-Rx-al-ap-ems-en-eve-exex-inv-lab-lbl-otp-pdm3-repo-ro-unpg -2 0.76856 18793.6 1 4 CACCTG GCTAATTA - +4 predrem__nrMotif1790 4 0.76856 18793.6 1 4 CACCTG CTAGCACT - +4 predrem__nrMotif662 4 0.76856 18793.6 1 4 CACCTG TGCTCACT - +4 predrem__nrMotif687 4 0.76856 18793.6 1 4 CACCTG TAAACACA - +4 transfac_pro__M03846-Mad -2 0.76856 18793.6 1 4 CACCTG TCTGCCCC - +4 predrem__nrMotif1656 -3 0.76856 18793.6 1 3 CACCTG CTTATTCA + +4 predrem__nrMotif550 -3 0.76856 18793.6 1 3 CACCTG CTTGTGGG + +4 taipale_cyt_meth__HOXD3_YTAATTAN_FL-Antp-ap-Awh-E5-ems-en-eve-exex-ind-inv-lbl-Lim3-OdsH-pb-ro-Scr-slou-Ubx-Vsx1-Vsx2-zen2 5 0.76856 18793.6 1 3 CACCTG CTAATTAC + +4 cisbp__M5462-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.76856 18793.6 1 3 CACCTG TTGTTTAC - +4 homer__KTGTTTGC_PHA-4 5 0.76856 18793.6 1 3 CACCTG GCAAACAC - +4 taipale__FOXO1_DBD_GTAAACAA-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.76856 18793.6 1 3 CACCTG TTGTTTAC - +4 tfdimers__MD00266-vvl 17 0.768891 18801.7 1 6 CACCTG TTTTACCATTTTAAATCCTCCTTCCTTT - +4 tfdimers__MD00403-cnc 18 0.768893 18801.7 1 6 CACCTG GGGCACAGGCACCGTGACCACAGCGTCCCTCC - +4 cisbp__M5723-acj6-nub-pdm2-vvl 0 0.769252 18810.5 1 6 CACCTG CTCATGCATAATTAATG + +4 taipale__POU1F1_DBD_NNYATGMATAATTAATN-acj6-nub-pdm2-vvl 0 0.769252 18810.5 1 6 CACCTG CTCATGCATAATTAATG + +4 transfac_pro__M01461-al-Awh-CG11085-CG18599-E5-ems-en-eve-inv-otp-pdm3-ro-slou-unpg-zfh2 1 0.769252 18810.5 1 6 CACCTG ACCACTAATTAGTGGAC + +4 transfac_pro__M01486-Dll 10 0.769252 18810.5 1 6 CACCTG GCGCTATAATTACCGAC + +4 transfac_pro__M02794-Smox 8 0.769252 18810.5 1 6 CACCTG CAAATCCAGACATCAGA + +4 transfac_pro__M02825 10 0.769252 18810.5 1 6 CACCTG AATCGCACTGCATTCCG + +4 transfac_pro__M09410-Hsf-pb 6 0.769252 18810.5 1 6 CACCTG TTCTAGAAGCTTCTATA + +4 transfac_public__M00059-pho-phol 4 0.769252 18810.5 1 6 CACCTG GAACACCATTTTTGAAC + +4 cisbp__M4109-pho-phol 4 0.769252 18810.5 1 6 CACCTG GAACACCATTTTTGAAC - +4 taipale_cyt_meth__NFIB_NTTGGCNNNNTGCCARN_FL-C15-Nf1-NfI 10 0.769252 18810.5 1 6 CACCTG CTTGGCACCGTGCCAAC - +4 transfac_pro__M01376-ap-Awh-CG18599-CG9876-E5-ems-en-eve-inv-lab-otp-ro-Rx-unpg-zfh2 10 0.769252 18810.5 1 6 CACCTG TTTCGCTAATTAGCTTT - +4 transfac_pro__M01382-Awh-CG11085-E5-ems-en-eve-exex-inv-slou-unpg 2 0.769252 18810.5 1 6 CACCTG AATCGCTAATTAGCGCT - +4 transfac_pro__M09058 6 0.769252 18810.5 1 6 CACCTG TGCCACCACCGACAATT - +4 dbcorrdb__CTCF__ENCSR000DLW_1__m2-CTCF-vtd 11 0.770007 18829 1 6 CACCTG TTTCTAAATTTTGCCACTAG + +4 dbcorrdb__CTCF__ENCSR000EFI_1__m2-CTCF-vtd 7 0.770007 18829 1 6 CACCTG ATTTCCCCATTTGGCCACCA + +4 dbcorrdb__E2F6__ENCSR000EWJ_1__m2-E2f1-E(z)-Max-Myc-Usf 0 0.770007 18829 1 6 CACCTG CGCGCGCGCGCCACGCGGCC + +4 dbcorrdb__EP300__ENCSR000BPW_1__m1-cnc-ewg-Jra-kay-maf-S-Mef2-mor-Myc-nej-Stat92E-tj 11 0.770007 18829 1 6 CACCTG AAATAATGACTCATCCTTTA + +4 dbcorrdb__EP300__ENCSR000DZD_1__m3-ebi-foxo-Jra-kay-nej-NFAT-Stat92E 7 0.770007 18829 1 6 CACCTG TATGAGTCATATCGAGATTG + +4 dbcorrdb__EZH2__ENCSR000ARH_1__m6-E(z) 6 0.770007 18829 1 6 CACCTG GGGACAAACCGGCGCGTGCA + +4 dbcorrdb__GABPA__ENCSR000BIW_1__m2-E2f1-Eip74EF-Hcf-RpII215-Sin3A-Taf1 8 0.770007 18829 1 6 CACCTG GGCGCCGGAAGCGGAGGGGG + +4 dbcorrdb__MAX__ENCSR000BLP_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-tgo-tna-Usf-vtd 11 0.770007 18829 1 6 CACCTG CCCGCCCCGCGCACGTGGCC + +4 dbcorrdb__MAX__ENCSR000EFV_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-tgo-tna-Usf-vtd-zfh1 6 0.770007 18829 1 6 CACCTG CGCGGCCACGTGGCCCGGGC + +4 dbcorrdb__NFYB__ENCSR000DNR_1__m1-btd-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps 7 0.770007 18829 1 6 CACCTG CCCCCGGCCTCTGATTGGCT + +4 dbcorrdb__NR2C2__ENCSR000EUL_1__m1-Brf-brm-ERR-E(z)-Hr78-RpII215-SREBP-tna 5 0.770007 18829 1 6 CACCTG CGGCCGACCGCCGCCCCGGC + +4 dbcorrdb__POLR2A__ENCSR000BHZ_1__m1-CG10431-lid-pho-phol-RpII215-Taf1-Taf7-TfIIFalpha 0 0.770007 18829 1 6 CACCTG TCGCTTCCGCCATCTGGCGG + +4 dbcorrdb__POLR2A__ENCSR000EAU_1__m1-aop-Atac3-Eip74EF-E(z)-Hcf-Hr78-Myc-RpII215-Sin3A-Taf1-TfIIFalpha 0 0.770007 18829 1 6 CACCTG CGCTTCCGCCTCCGGCGGGG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIC_1__m2-ewg-RpII215-Six4 11 0.770007 18829 1 6 CACCTG CCGAGTTGCGCCAGCGCAAG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BKR_1__m3 2 0.770007 18829 1 6 CACCTG GGTACCGGAAGCGGCCTGCG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOA_1__m1-aop-Atac3-Eip74EF-Ets96B-RpII215-Taf1 0 0.770007 18829 1 6 CACCTG CGCTTCCGCTTTGTGCCGGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BQC_1__m1-aop-Atac3-Dif-dl-E2f1-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Hr78-Max-Myc-pnt-RpII215-Sin3A-Taf1-TfIIFalpha-tna 5 0.770007 18829 1 6 CACCTG GCCGCTTCCGGTCCGGGCGG + +4 dbcorrdb__RCOR1__ENCSR000EDQ_1__m1-CoRest 3 0.770007 18829 1 6 CACCTG CGCCGTCTCTCGCGATGACG + +4 dbcorrdb__RFX5__ENCSR000DZW_1__m3-CrebB 12 0.770007 18829 1 6 CACCTG GGAGTGAGCAGTGACGTCAC + +4 dbcorrdb__RXRA__ENCSR000BJD_1__m3-E2f1-usp 12 0.770007 18829 1 6 CACCTG CGGCTGGCGGGAAACCGGAG + +4 dbcorrdb__SIN3A__ENCSR000BGL_1__m1-Atac3-Brf-brm-bs-Dif-dl-E2f1-E2f2-Eip74EF-Ets97D-E(z)-FoxP-Hcf-Hr78-lid-Max-Myc-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 4 0.770007 18829 1 6 CACCTG CCCGCCGCTTCCGGCGCCGG + +4 dbcorrdb__STAT3__ENCSR000DPB_1__m2-Jra-kay-Myc-nej-Stat92E 12 0.770007 18829 1 6 CACCTG AAAAAGATGAGTCATACTTT + +4 dbcorrdb__TCF12__ENCSR000BIT_1__m2 12 0.770007 18829 1 6 CACCTG GCATAACAAAGGCTCCCGGC + +4 dbcorrdb__ZBTB33__ENCSR000BKF_1__m1-Chd1-CoRest 9 0.770007 18829 1 6 CACCTG CTCTCGCGAGAACTGCGGGG + +4 dbcorrdb__eGFP-JUND__ENCSR000DJX_1__m1-CoRest-Jra-kay-mor-Myc-pan 7 0.770007 18829 1 6 CACCTG GATGAGTCATCCTTTCTGGC + +4 transfac_pro__M09541-Adf1-Taf1 3 0.770007 18829 1 6 CACCTG CGCCGCCGCCACCGCCGCCG + +4 transfac_public__M00034 1 0.770007 18829 1 6 CACCTG GGACATGCCCGGGCATGTCC + +4 dbcorrdb__ATF3__ENCSR000BNU_1__m3 0 0.770007 18829 1 6 CACCTG TGACAGCCGCACGCGCTACG - +4 dbcorrdb__JUND__ENCSR000EBZ_1__m1-CrebB-Jra-kay-mor-Snr1 7 0.770007 18829 1 6 CACCTG GTTGAGTCATCCCCCCGGCA - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m2-RpII215 14 0.770007 18829 1 6 CACCTG ACTTCCGGTTTGCGCAGCGA - +4 dbcorrdb__POLR2A__ENCSR000BKI_1__m1-CG10431-E2f1-Eip74EF-E(z)-FoxP-Hcf-Rbbp5-RpII215-Sin3A-Taf1 14 0.770007 18829 1 6 CACCTG CGCGGCGCTTCCGCCATCGG - +4 dbcorrdb__POLR2A__ENCSR000DNF_1__m2-RpII215 9 0.770007 18829 1 6 CACCTG CTGTTGGCGCTGCTGCGGCG - +4 dbcorrdb__POLR2A__ENCSR000EBG_1__m1-Atac3-Brf-CTCF-E2f1-Eip74EF-E(z)-Hcf-HDAC1-Hr78-lid-Max-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha-tna 3 0.770007 18829 1 6 CACCTG CGGCGCTTCCGCCGCCGGGC - +4 dbcorrdb__POLR2A__ENCSR000EZL_1__m1-aop-Atac3-Brf-E2f1-Eip74EF-Ets96B-E(z)-Hcf-Hr78-Max-RpII215-Sin3A-Taf1-TfIIFalpha 1 0.770007 18829 1 6 CACCTG CCGCTTCCGCCGTGGCCCGG - +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m2-egg 9 0.770007 18829 1 6 CACCTG AGGCTTTTCCGCATTAATTA - +4 dbcorrdb__STAT5A__ENCSR000BQZ_1__m2-CG9650-foxo-lz-MTA1-like-nej-NFAT-run-RunxA-RunxB-Stat92E 5 0.770007 18829 1 6 CACCTG GAGTCTTTTTGTGGTTTTTA - +4 dbcorrdb__TCF7L2__ENCSR000EWT_1__m3-pan 12 0.770007 18829 1 6 CACCTG GTTCAAAGCAGCCGCCAGGC - +4 dbcorrdb__eGFP-FOS__ENCSR000DKB_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Stat92E 12 0.770007 18829 1 6 CACCTG ACAGGGATGAGTCATCCCGC - +4 transfac_pro__M06781 9 0.770007 18829 1 6 CACCTG AGAATTTGTCACATTCCCCT - +4 taipale_tf_pairs__ELK1_PAX5_RSCGGAACYACGCWYSANTG_CAP_repr-sv -1 0.770007 18829 1 5 CACCTG ACCGGAACTACGCATCACTG + +4 taipale_tf_pairs__ETV2_PAX5_ACCGGANNTACGCNNNNNYR_CAP-pnt-sv -1 0.770007 18829 1 5 CACCTG ACCGGAACTACGCTTCACTG + +4 dbcorrdb__HNF4A__ENCSR000EEU_1__m1-btd-EcR-HDAC1-Hnf4-nej-Spps-svp-usp 15 0.770007 18829 1 5 CACCTG GGACCCTGGACTTTGGACTC - +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m2-CG17209 16 0.770007 18829 1 4 CACCTG CACTAGTCTAACGCGCTAAC + +4 hdpi__GPAM-mino -2 0.770341 18837.1 1 4 CACCTG CCCAT - +4 cisbp__M2195 13 0.772936 18900.6 1 6 CACCTG GTCCAAAATTTTTCACTCAGG + +4 cisbp__M4236 13 0.772936 18900.6 1 6 CACCTG GTCCAAAATTTTTCACTCAGG + +4 jaspar__MA0390.1 13 0.772936 18900.6 1 6 CACCTG GTCCAAAATTTTTCACTCTGG + +4 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNCAATTN_FL_meth_repr-C15 0 0.772936 18900.6 1 6 CACCTG TAATTGGTTAAGATTCAATTA + +4 transfac_pro__M01514 13 0.772936 18900.6 1 6 CACCTG GTCCAAAATTTTTCACTCAGG + +4 transfac_pro__M05224-brm-ERR-E(z) 13 0.772936 18900.6 1 6 CACCTG GGGGGGGCCCGGCCGCCTGCT + +4 transfac_pro__M06075 10 0.772936 18900.6 1 6 CACCTG CGAATCAGCGGACCGGACCGC + +4 transfac_pro__M09025-Adf1 12 0.772936 18900.6 1 6 CACCTG CGCCGCCGCCTTCGCCGACAA + +4 transfac_pro__M09084-Adf1-Taf1 14 0.772936 18900.6 1 6 CACCTG TCCGCCGCCGCCACCGCCGCC + +4 transfac_pro__M09130-brm-CG7839-HDAC1-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 2 0.772936 18900.6 1 6 CACCTG TTTACTTTTTTTTTTTTTTTT + +4 transfac_pro__M09255-RpII215-Taf1 13 0.772936 18900.6 1 6 CACCTG TCTCCGCCGCCTTCTCCGCCG + +4 yetfasco__YOR172W_813 10 0.772936 18900.6 1 6 CACCTG ACCGTCTTATTTCCGCGAATG + +4 jaspar__MA0303.1-Jra-Mef2-Myc-Stat92E-kay 12 0.772936 18900.6 1 6 CACCTG TGAAGTATGACTCATCCCTTG - +4 scertf__zhu.YRM1 10 0.772936 18900.6 1 6 CACCTG ACCGTCTTATTTCCGCGTATG - +4 transfac_pro__M01501 10 0.772936 18900.6 1 6 CACCTG ACCGTCTTATTTCCGCGAATG - +4 transfac_pro__M05559 3 0.772936 18900.6 1 6 CACCTG GCCAATCTAATTTCGGCTGCG - +4 jaspar__MA0089.1 0 0.773408 18912.1 1 6 CACCTG GTCATG - +4 scertf__badis.ABF2-Hsf -2 0.773408 18912.1 1 4 CACCTG TCTAGA + +4 transfac_pro__M01281-CG5641-NFAT 2 0.773408 18912.1 1 4 CACCTG TTTTCC - +4 cisbp__M2035-esg-hth-sna-wor -3 0.773408 18912.1 1 3 CACCTG CTGTCA + +4 hdpi__HTATIP2 3 0.773408 18912.1 1 3 CACCTG GCGCAA + +4 fantom__motif50_GTCCNA 3 0.773408 18912.1 1 3 CACCTG TAGGAC - +4 hdpi__RAB7A-Rab7 -3 0.773408 18912.1 1 3 CACCTG CTGAGC - +4 tfdimers__MD00382-nub-pdm2 17 0.773752 18920.6 1 6 CACCTG AAGGAGAAAATGCAAACCACAGAAAA + +4 tfdimers__MD00274-Myc 5 0.773752 18920.6 1 6 CACCTG ATTAACATCTGTAATCAATTAAATTA - +4 tfdimers__MD00563-CG7786-gt-Pdp1 7 0.773761 18920.8 1 6 CACCTG ATAAAATTTGCTGAGTCAGCAAATTTAATAT - +4 cisbp__M2575-TFAM 4 0.774202 18931.6 1 6 CACCTG TCCTTATCAGT + +4 flyfactorsurvey__dimm_da_SANGER_5_FBgn0000413-HLH54F-Oli-amos-ato-da-dimm-tap 0 0.774202 18931.6 1 6 CACCTG CGCCATATGGT + +4 predrem__nrMotif316 4 0.774202 18931.6 1 6 CACCTG CTCCCGGCTGC + +4 transfac_pro__M08899-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.774202 18931.6 1 6 CACCTG GTCCCTTTGTT + +4 transfac_pro__M09100 0 0.774202 18931.6 1 6 CACCTG AAATTTAATTT + +4 cisbp__M2852 0 0.774202 18931.6 1 6 CACCTG TCGCTTTTATT - +4 cisbp__M4490-CG10431-lid-pho-phol-RpII215-Taf1 5 0.774202 18931.6 1 6 CACCTG GCCGCCATCTT - +4 cisbp__M6232-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-Nf1-pnr 4 0.774202 18931.6 1 6 CACCTG TGTTTACTTTG - +4 flyfactorsurvey__CG31670_SANGER_5_FBgn0031375-erm 4 0.774202 18931.6 1 6 CACCTG GTTGCTCATTT - +4 predrem__nrMotif177 5 0.774202 18931.6 1 6 CACCTG AGAAAAACAAA - +4 transfac_pro__M05601 5 0.774202 18931.6 1 6 CACCTG AGGCCGACCCC - +4 transfac_pro__M09149 4 0.774202 18931.6 1 6 CACCTG TCGTCATCGTT - +4 taipale__HMX2_DBD_NNCAMTTAANN-Hmx -1 0.774202 18931.6 1 5 CACCTG ACCAATTAAAA + +4 taipale_cyt_meth__ZNF296_NASTGGWCASN_eDBD-CG9650 6 0.774202 18931.6 1 5 CACCTG AGTGTCCACTA - +4 transfac_pro__M01998 6 0.774202 18931.6 1 5 CACCTG GCATTTCCGCT - +4 transfac_pro__M07385-ap-CG32532-CG9876-hbn-inv-Lim1-otp-pb-Pph13-ro-Rx-Vsx2 -1 0.774202 18931.6 1 5 CACCTG AACTAATTAAA - +4 cisbp__M5554 -2 0.774202 18931.6 1 4 CACCTG GCTCGTAAAAA + +4 factorbook__CREB-CrebB-Jra-kay 7 0.774202 18931.6 1 4 CACCTG ATTGCGTCATC + +4 taipale__HOXC13_DBD_NCTCGTAAAAN_repr -2 0.774202 18931.6 1 4 CACCTG GCTCGTAAAAA + +4 taipale_cyt_meth__HOXA13_NCTCGTAAAAN_FL -2 0.774202 18931.6 1 4 CACCTG GCTCGTAAAAC + +4 transfac_public__M00490-cnc-Jra-kay 7 0.774202 18931.6 1 4 CACCTG CGTGAGTCATC + +4 cisbp__M5559-Abd-B 7 0.774202 18931.6 1 4 CACCTG ATTTTACGACC - +4 hocomoco__ATF2_HUMAN.H11MO.2.C-Atf3-Atf6-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-kay 7 0.774202 18931.6 1 4 CACCTG GTGACGTCATC - +4 hocomoco__JUND_HUMAN.H11MO.0.A-CoRest-Jra-Mef2-Myc-bon-cnc-kay-mor-nej-pan 7 0.774202 18931.6 1 4 CACCTG GATGACTCATC - +4 hocomoco__PBX3_HUMAN.H11MO.0.A -2 0.774202 18931.6 1 4 CACCTG CCTGTCAATCA - +4 taipale_cyt_meth__CDX1_NGTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.774202 18931.6 1 4 CACCTG GTTTTACGACC - +4 transfac_public__M00188-Jra-kay 7 0.774202 18931.6 1 4 CACCTG ACTTAGTCACC - +4 transfac_pro__M09436 8 0.774202 18931.6 1 3 CACCTG GTGGGGTCCAC + +4 hocomoco__THA11_MOUSE.H11MO.0.B-Hcf-Six4-Stat92E-bi-egg-mor 0 0.774828 18946.9 1 6 CACCTG GGCATGCTGGGAGTTGTAGTTC + +4 cisbp__M6551-egg-Hcf-mor-Six4 2 0.774828 18946.9 1 6 CACCTG TACACTTCCCAGAATGCCTTGC - +4 transfac_pro__M04641-bin-CHES-1-like-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 12 0.774828 18946.9 1 6 CACCTG CACAAGTTTGTTTATCATAAAT - +4 transfac_public__M00284-cnc-kay-maf-S 2 0.774828 18946.9 1 6 CACCTG CATAATTGCTGAGTCATTTTAG - +4 tfdimers__MD00143 15 0.775178 18955.4 1 6 CACCTG GGCCTCTTTGGGAATCCCCTGCCCC + +4 flyfactorsurvey__ey_SOLEXA_5_FBgn0005558-ey-sv-toy 18 0.775178 18955.4 1 6 CACCTG CCTTCACACTTCAATGCACACCATG - +4 transfac_pro__M09351 1 0.775779 18970.1 1 6 CACCTG AAACCCTAAACCCTAAACCCTAA + +4 cisbp__M2070 4 0.776039 18976.5 1 6 CACCTG ATATCACTTTATACGA + +4 cisbp__M4308 3 0.776039 18976.5 1 6 CACCTG AATCAAAAAAAAATGA + +4 cisbp__M5868-bs 1 0.776039 18976.5 1 6 CACCTG TGACCATATATGGTCA + +4 stark__TGACANNNNNNTGACA 3 0.776039 18976.5 1 6 CACCTG TGACAAAAAAATGACA + +4 taipale__ZNF143_DBD_TWCCCAYAATGCATTG_repr 0 0.776039 18976.5 1 6 CACCTG TACCCACAATGCATTG + +4 taipale_cyt_meth__ZIC5_NGACCCCCYGCTGYGM_eDBD-lmd-opa 1 0.776039 18976.5 1 6 CACCTG CGACCCCCCGCTGTGC + +4 transfac_pro__M06814 8 0.776039 18976.5 1 6 CACCTG TGGTGGATCACAGGAC + +4 transfac_pro__M07676-cnc 3 0.776039 18976.5 1 6 CACCTG CATGACGAGCATGACG + +4 cisbp__M5743-acj6-vvl 0 0.776039 18976.5 1 6 CACCTG CTCATTAATTATGCAT - +4 cisbp__M5838-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.776039 18976.5 1 6 CACCTG AACACTGCACATTGTT - +4 cisbp__M5966 0 0.776039 18976.5 1 6 CACCTG TACCCACAATGCATTG - +4 hocomoco__PO5F1_MOUSE.H11MO.0.A-CG9650-SoxN-nej-nub-pan-pdm2-vvl 3 0.776039 18976.5 1 6 CACCTG ATTTGCATAACAATGG - +4 jaspar__MA0265.1 4 0.776039 18976.5 1 6 CACCTG ATATCACTTTATACGA - +4 taipale__SOX8_DBD_AACAATRTKCAGWGTT-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.776039 18976.5 1 6 CACCTG AACACTGCACATTGTT - +4 taipale__SRF_full_NNMCCATATAWGGKNN-bs 1 0.776039 18976.5 1 6 CACCTG TGACCATATATGGTCA - +4 taipale_tf_pairs__HOXD12_ELK1_RSCGGAAGTAATAAAN_CAP 6 0.776039 18976.5 1 6 CACCTG TTTTATTACTTCCGGT - +4 transfac_pro__M01078-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 6 0.776039 18976.5 1 6 CACCTG ACCCACTTCCGGTAGA - +4 transfac_pro__M01189 2 0.776039 18976.5 1 6 CACCTG CTTAGCAATTAAGCAA - +4 transfac_pro__M05263 3 0.776039 18976.5 1 6 CACCTG GATTACCATGGTAATC - +4 transfac_pro__M05474 11 0.776039 18976.5 1 5 CACCTG GCCTCCGTTGGCATCT - +4 taipale_cyt_meth__RFX1_NGTTRCCATGGYAACN_eDBD_meth-CG5846-CG9727-Max-Rfx-SREBP 12 0.776039 18976.5 1 4 CACCTG CGTTGCCATGGCAACG + +4 taipale_cyt_meth__RFX4_NGTTRCCATGGYAACN_eDBD-CG5846-CG9727-Max-Rfx-SREBP 12 0.776039 18976.5 1 4 CACCTG CGTTGCCATGGCAACG + +4 cisbp__M6077-CG5846-CG9727-Max-Rfx-SREBP 12 0.776039 18976.5 1 4 CACCTG CGTTGCCATGGCAACC - +4 taipale__Rfx3_DBD_NGTTNCCATGGNAACN-CG5846-CG9727-Max-Rfx-SREBP 12 0.776039 18976.5 1 4 CACCTG CGTTGCCATGGCAACC - +4 cisbp__M5707-ey-Poxm-sv-toy 9 0.77605 18976.7 1 6 CACCTG GAGCACTCATGCGTGACG + +4 scertf__macisaac.GAL4 12 0.77605 18976.7 1 6 CACCTG CGGACTACACTGCCCCGA + +4 taipale__Lhx8_DBD_NTAATTANNNNTAATTAN-Awh-CG34367-ems-en-inv-Lim3-repo-ro-unpg-zfh2 5 0.77605 18976.7 1 6 CACCTG CTAATTAGCGCTAATTAA + +4 transfac_pro__M00991-cad 0 0.77605 18976.7 1 6 CACCTG TACAAACAAAGTAATAAA + +4 transfac_pro__M01309 5 0.77605 18976.7 1 6 CACCTG AGTGAATCGTCGATGAAT + +4 transfac_pro__M09263-bs-Mef2 1 0.77605 18976.7 1 6 CACCTG TTACCAAAAATGGAAAAA + +4 cisbp__M4463-CG9650-Dif-dl-ebi-MTA1-like-Stat92E 9 0.77605 18976.7 1 6 CACCTG CTGACTCATTTCCACATT - +4 taipale_tf_pairs__ETV2_DLX3_RSCGGAANNNNNYAATTA_CAP-pnt 11 0.77605 18976.7 1 6 CACCTG TAATTGCCCACTTCCGGT - +4 taipale_tf_pairs__ETV2_GSC2_RSCGGAANNNNNGGATTA_CAP_repr-Gsc-pnt 11 0.77605 18976.7 1 6 CACCTG TAATCCCTAACTTCCGGC - +4 taipale_tf_pairs__HOXB2_SOX15_NYMATTANNNNNACAATR_CAP_repr-pb 7 0.77605 18976.7 1 6 CACCTG CATTGTTTTGCTAATTAG - +4 taipale_tf_pairs__MEIS2_ONECUT2_NTGACAGNTAATCRATAN_HT-hth-onecut 8 0.77605 18976.7 1 6 CACCTG TTATCGATTTTCTGTCAA - +4 transfac_pro__M05935 3 0.77605 18976.7 1 6 CACCTG TCCAATCTTATTTCCTCC - +4 transfac_pro__M06365 12 0.77605 18976.7 1 6 CACCTG ACCCCCATGATCTACGTC - +4 transfac_public__M00091-br 13 0.77605 18976.7 1 5 CACCTG TAGATTTGTCTATTACTT - +4 cisbp__M0731-bin-CHES-1-like-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 3 0.776234 18981.2 1 6 CACCTG TGTAAACAA + +4 cisbp__M0993-B-H1-B-H2-CG11085-unpg 1 0.776234 18981.2 1 6 CACCTG CTAATTGGT + +4 cisbp__M1480 0 0.776234 18981.2 1 6 CACCTG GTTCTGACC + +4 cisbp__M1826 0 0.776234 18981.2 1 6 CACCTG AATTTCCGC + +4 cisbp__M5729-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.776234 18981.2 1 6 CACCTG ATTTGCATA + +4 predrem__nrMotif2581 2 0.776234 18981.2 1 6 CACCTG ACAAACTGT + +4 transfac_pro__M04886 1 0.776234 18981.2 1 6 CACCTG AAATCTCGC + +4 cisbp__M0910-bsh-btn-Dll-Dr-lab 2 0.776234 18981.2 1 6 CACCTG GGCAATTAT - +4 cisbp__M1012-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-lab-pb-Scr-slou-tup-Ubx-zen2 1 0.776234 18981.2 1 6 CACCTG GGTCATTAA - +4 cisbp__M1024-bsh-btn-Dll-Dr-lab 2 0.776234 18981.2 1 6 CACCTG GGCAATTAT - +4 cisbp__M1214 1 0.776234 18981.2 1 6 CACCTG ATATATTAA - +4 predrem__nrMotif1234 1 0.776234 18981.2 1 6 CACCTG GAATCTGTT - +4 predrem__nrMotif2423 0 0.776234 18981.2 1 6 CACCTG TTACTGCTT - +4 predrem__nrMotif328 0 0.776234 18981.2 1 6 CACCTG AAACAGAGT - +4 taipale__POU2F3_DBD_TATGCWAAT-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.776234 18981.2 1 6 CACCTG ATTTGCATA - +4 hdpi__VAMP3 4 0.776234 18981.2 1 5 CACCTG TGAGAAACA + +4 predrem__nrMotif172 4 0.776234 18981.2 1 5 CACCTG TTCAAAACA + +4 predrem__nrMotif2509 -1 0.776234 18981.2 1 5 CACCTG TCATTCATT + +4 taipale__VENTX_DBD_NMCRATTAR_repr -1 0.776234 18981.2 1 5 CACCTG ACCGATTAG + +4 cisbp__M1085 -1 0.776234 18981.2 1 5 CACCTG ACCAATTAA - +4 cisbp__M5947 -1 0.776234 18981.2 1 5 CACCTG ACCGATTAG - +4 predrem__nrMotif20 -1 0.776234 18981.2 1 5 CACCTG CACTGCTCT - +4 predrem__nrMotif312 4 0.776234 18981.2 1 5 CACCTG AACAAGCCT - +4 predrem__nrMotif1559 -2 0.776234 18981.2 1 4 CACCTG TCTCCTCTA + +4 predrem__nrMotif2510 -2 0.776234 18981.2 1 4 CACCTG CCTCGCAGC + +4 predrem__nrMotif819 5 0.776234 18981.2 1 4 CACCTG TTTTGGACA + +4 transfac_pro__M04877 5 0.776234 18981.2 1 4 CACCTG GTTCGAATC + +4 cisbp__M0843 -2 0.776234 18981.2 1 4 CACCTG AATTATTGC - +4 cisbp__M1225 5 0.776234 18981.2 1 4 CACCTG CCAATTATC - +4 predrem__nrMotif1100 -2 0.776234 18981.2 1 4 CACCTG TCTCTCAAA - +4 predrem__nrMotif1890 -2 0.776234 18981.2 1 4 CACCTG CTTTTGGCA - +4 cisbp__M0018-Taf1-lid-pho-phol 2 0.777872 19021.3 1 6 CACCTG GCCGCCGCCA + +4 cisbp__M0110-htk 4 0.777872 19021.3 1 6 CACCTG TCGATATTGT + +4 cisbp__M0128-bab1-CTCF-Dif-maf-S-Tbp 0 0.777872 19021.3 1 6 CACCTG TAATATATTA + +4 cisbp__M0313-CG7786-gt-Irbp18-Myc-nej-Pdp1-slbo-vri-Xrp1 3 0.777872 19021.3 1 6 CACCTG GATTGCGTAA + +4 cisbp__M1517-NFAT 3 0.777872 19021.3 1 6 CACCTG ATTTTCCATT + +4 cisbp__M1523-NFAT 3 0.777872 19021.3 1 6 CACCTG ATTTTCCATT + +4 jaspar__MA0625.1-NFAT 3 0.777872 19021.3 1 6 CACCTG ATTTTCCATT + +4 predrem__nrMotif1317 4 0.777872 19021.3 1 6 CACCTG AGGCCAGCAG + +4 predrem__nrMotif1344 0 0.777872 19021.3 1 6 CACCTG TGCCCAGAAT + +4 predrem__nrMotif202 3 0.777872 19021.3 1 6 CACCTG CAAAACAAAA + +4 predrem__nrMotif506 3 0.777872 19021.3 1 6 CACCTG ACAAAACTCA + +4 predrem__nrMotif639 1 0.777872 19021.3 1 6 CACCTG CAGCCTCTTC + +4 predrem__nrMotif699 3 0.777872 19021.3 1 6 CACCTG TGGAAACTCT + +4 scertf__morozov.ARR1 1 0.777872 19021.3 1 6 CACCTG GTTACTAATC + +4 taipale__GSC2_DBD_NNTAATCCNN-bcd-Gsc-oc 3 0.777872 19021.3 1 6 CACCTG CCTAATCCGC + +4 transfac_pro__M05105 4 0.777872 19021.3 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M08970-Sox100B-SoxN 1 0.777872 19021.3 1 6 CACCTG TAACAATGGA + +4 cisbp__M0429 3 0.777872 19021.3 1 6 CACCTG CCCCCCCACA - +4 cisbp__M1063-Hmx 3 0.777872 19021.3 1 6 CACCTG AAGCAATTAA - +4 cisbp__M1067 4 0.777872 19021.3 1 6 CACCTG TGATTGGATC - +4 cisbp__M1421 2 0.777872 19021.3 1 6 CACCTG GACACAAAAA - +4 cisbp__M1675 0 0.777872 19021.3 1 6 CACCTG AAAATTGCGC - +4 flyfactorsurvey__z_FlyReg_FBgn0004050-z 2 0.777872 19021.3 1 6 CACCTG AATCACTCAA - +4 hocomoco__HXA1_HUMAN.H11MO.0.C-lab 4 0.777872 19021.3 1 6 CACCTG CATCCATCAA - +4 homer__ATTTAATGGG_EGL-5 0 0.777872 19021.3 1 6 CACCTG CCCATTAAAT - +4 neph__UW.Motif.0150 1 0.777872 19021.3 1 6 CACCTG TTTCCCGAGA - +4 predrem__nrMotif981 1 0.777872 19021.3 1 6 CACCTG CAGCCTCAAG - +4 transfac_pro__M09554 3 0.777872 19021.3 1 6 CACCTG AAGGACAAAA - +4 predrem__nrMotif1389 -1 0.777872 19021.3 1 5 CACCTG TTCTGTTCTT + +4 predrem__nrMotif1554 -1 0.777872 19021.3 1 5 CACCTG TTCTTTGTCT + +4 predrem__nrMotif1600 5 0.777872 19021.3 1 5 CACCTG CTGCTCCCCA + +4 transfac_pro__M05111 5 0.777872 19021.3 1 5 CACCTG AGGCCGCCCA + +4 homer__TGCTGAGTCA_Bach2-Jra-cnc-kay-maf-S-tj 5 0.777872 19021.3 1 5 CACCTG TGACTCAGCA - +4 homer__GGAAATTCCC_NFkB-p65-Rel-CG12018-Dif-Rel-dl 6 0.777872 19021.3 1 4 CACCTG GGAAATTCCC + +4 taipale__ESX1_full_NNYAATTANN-al-Awh-bsh-C15-CG18599-CG32532-CG34367-CG9876-Dr-dve-E5-ems-en-ftz-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx2-zfh2 6 0.777872 19021.3 1 4 CACCTG ACCAATTAAC + +4 taipale_cyt_meth__DMRTC2_GAACGATACA_FL 6 0.777872 19021.3 1 4 CACCTG GAACGATACA + +4 transfac_pro__M01809-Mef2 -2 0.777872 19021.3 1 4 CACCTG CCAAAAATAG + +4 transfac_pro__M03214 6 0.777872 19021.3 1 4 CACCTG ACGCCGACCC + +4 transfac_pro__M07828-Antp-Awh-bsh-btn-CG11294-CG18599-Dll-Dr-Drgx-E5-ems-en-eve-exex-inv-lab-Lim3-pb-Scr-slou-Ubx-unpg-Vsx1-Vsx2 6 0.777872 19021.3 1 4 CACCTG GCTAATTACC + +4 cisbp__M5415-al-Awh-C15-CG18599-CG32532-CG34367-CG9876-Dr-dve-E5-ems-en-ftz-hbn-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx2-zfh2 6 0.777872 19021.3 1 4 CACCTG ACCAATTAAC - +4 homer__HTTTCCCASG_Rbpj1-Su(H) -2 0.777872 19021.3 1 4 CACCTG CGTGGGAAAA - +4 swissregulon__sacCer__SPT15-Tbp-Trf-Trf2 6 0.777872 19021.3 1 4 CACCTG TATATATATC - +4 transfac_pro__M03207 7 0.777872 19021.3 1 3 CACCTG AGGCCGCCAC + +4 transfac_pro__M04971 7 0.777872 19021.3 1 3 CACCTG ATGCCGCCAC + +4 transfac_pro__M05093 -3 0.777872 19021.3 1 3 CACCTG CTGGCGGGGG - +4 taipale_cyt_meth__CREB1_NTGACGCGTCAN_eDBD_repr-CrebB 2 0.780382 19082.7 1 6 CACCTG GTGACGCGTCAT + +4 transfac_pro__M01732-klu-sr 0 0.780382 19082.7 1 6 CACCTG ACCCCGCATTTT + +4 transfac_pro__M06567 2 0.780382 19082.7 1 6 CACCTG GACTCCTAAAGA + +4 transfac_pro__M07313-CrebB-Xbp1 3 0.780382 19082.7 1 6 CACCTG GCTGACGTAATG + +4 transfac_pro__M07640-dpn-E(spl)m3-HLH-E(spl)m5-HLH-E(spl)mbeta-HLH-E(spl)mdelta-HLH-E(spl)mgamma-HLH-h-Hey-Sidpn 3 0.780382 19082.7 1 6 CACCTG TGGCACGCGCCA + +4 transfac_pro__M08958-Dll-dve-nub-pdm2-vvl 4 0.780382 19082.7 1 6 CACCTG AATTTGCATAAT + +4 cisbp__M3089-Atf3-CrebB-Xbp1 3 0.780382 19082.7 1 6 CACCTG CCTTACGTCACC - +4 homer__CAAGATGGCGGC_YY1-CG10431-RpII215-Taf1-Taf7-lid-pho-phol 5 0.780382 19082.7 1 6 CACCTG GCCGCCATCTTG - +4 transfac_pro__M00770 2 0.780382 19082.7 1 6 CACCTG TTTGCCAAATTC - +4 transfac_pro__M06205 6 0.780382 19082.7 1 6 CACCTG GCGTTTTTCCCG - +4 transfac_pro__M06480 6 0.780382 19082.7 1 6 CACCTG ATAGCCCCCCGG - +4 transfac_public__M00177-Atf3-CrebB-Xbp1 3 0.780382 19082.7 1 6 CACCTG CCTTACGTCACC - +4 tiffin__TIFDMEM0000071 -1 0.780382 19082.7 1 5 CACCTG AACCGAAACGGA + +4 transfac_pro__M06035 -1 0.780382 19082.7 1 5 CACCTG TCGTGCGGCCGC + +4 transfac_pro__M06114 -1 0.780382 19082.7 1 5 CACCTG TCGTCATCGCGC + +4 cisbp__M4956-eve 7 0.780382 19082.7 1 5 CACCTG AAATAATTAACG - +4 cisbp__M6360-cnc-ewg-Jra-kay-maf-S -1 0.780382 19082.7 1 5 CACCTG TGCTGAGTCATG - +4 homer__NNATGASTCATH_Fra1-CoRest-Jra-Mef2-Myc-Stat92E-bon-cnc-kay-mor-nej-pan 7 0.780382 19082.7 1 5 CACCTG GATGACTCATCC - +4 tiffin__TIFDMEM0000053 -1 0.780382 19082.7 1 5 CACCTG ACTTTGATTTTC - +4 transfac_pro__M04982 7 0.780382 19082.7 1 5 CACCTG CTTTTTCTAACC - +4 transfac_pro__M05906 7 0.780382 19082.7 1 5 CACCTG TCCGCCAATCCA - +4 transfac_pro__M05982 7 0.780382 19082.7 1 5 CACCTG GCTTATATACAC - +4 transfac_pro__M06184 7 0.780382 19082.7 1 5 CACCTG GCTTCCATCCCA - +4 transfac_pro__M06216 7 0.780382 19082.7 1 5 CACCTG TCCTTTGCACAC - +4 idmmpmm__fkh-fkh -2 0.780382 19082.7 1 4 CACCTG CTTTTGTAAATA + +4 taipale_cyt_meth__ATF6_NRTGACGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.780382 19082.7 1 4 CACCTG GATGACGTCATC + +4 taipale_cyt_meth__JUNB_NATGACGTCAYN_eDBD_repr-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.780382 19082.7 1 4 CACCTG GATGACGTCATC + +4 transfac_pro__M00621 8 0.780382 19082.7 1 4 CACCTG AATTGCGTCACT + +4 transfac_pro__M01827 8 0.780382 19082.7 1 4 CACCTG TTTTTTTTTAAC + +4 transfac_pro__M05844 8 0.780382 19082.7 1 4 CACCTG TGTTTATTAACA - +4 transfac_pro__M05995 -2 0.780382 19082.7 1 4 CACCTG GCTGCCCCCCCA - +4 cisbp__M1959-CG9650-nej-nub-pdm2-SoxN-vvl 3 0.780744 19091.5 1 6 CACCTG ATTTGCATAACAAAG + +4 cisbp__M2341-Mef2 0 0.780744 19091.5 1 6 CACCTG TTCCAAAAATGGAAA + +4 cisbp__M2442-fkh-Hsf 2 0.780744 19091.5 1 6 CACCTG AGAACGTTCTGTTCT + +4 cisbp__M2443-Hsf-pb 2 0.780744 19091.5 1 6 CACCTG AGAACGTTCTAGAAC + +4 cisbp__M4554-aop-Eip74EF-Hr78 2 0.780744 19091.5 1 6 CACCTG AACCGCTTCCGGGTC + +4 cisbp__M6134-CG9650-nej-pan-SoxN-vvl 2 0.780744 19091.5 1 6 CACCTG TTTGCATAACAATGG + +4 factorbook__UA3-E(z)-RpII215-Spps-btd-kay-vtd 5 0.780744 19091.5 1 6 CACCTG CCGAGACCCCCGCCC + +4 hocomoco__DLX6_HUMAN.H11MO.0.D-CG34367-Dll-en-inv-unpg 4 0.780744 19091.5 1 6 CACCTG TAATTACCTTAATTT + +4 scertf__macisaac.IXR1 1 0.780744 19091.5 1 6 CACCTG AAACCGGAAGCGGTG + +4 swissregulon__sacCer__ASG1 9 0.780744 19091.5 1 6 CACCTG CCGGCCGAGTTCCGG + +4 taipale_cyt_meth__IRF8_NYGAAASYGAAASYN_FL_meth 9 0.780744 19091.5 1 6 CACCTG ACGAAACTGAAACTA + +4 taipale_cyt_meth__MAFG_NYGCTGASTCAGCRN_eDBD-cnc-maf-S-tj 0 0.780744 19091.5 1 6 CACCTG TTGCTGAGTCAGCAA + +4 taipale_tf_pairs__ETV2_BHLHA15_RSCGGANNCATATGK_CAP_repr-dimm-pnt 6 0.780744 19091.5 1 6 CACCTG ACCGGAAACATATGG + +4 transfac_pro__M02903 1 0.780744 19091.5 1 6 CACCTG TTGAATGAAATTCGA + +4 transfac_pro__M09488-tll 9 0.780744 19091.5 1 6 CACCTG AAAAAAGTCAACGAT + +4 transfac_public__M00168-fkh-Hsf 7 0.780744 19091.5 1 6 CACCTG AGAACAGAACGTTCT + +4 transfac_public__M00169-Hsf-pb 2 0.780744 19091.5 1 6 CACCTG AGAACGTTCTAGAAC + +4 cisbp__M4012-CrebB 8 0.780744 19091.5 1 6 CACCTG TCTACGTCAACCCCC - +4 cisbp__M4487-ey-Poxm-sv-toy 5 0.780744 19091.5 1 6 CACCTG GGTCACGCTTGGCTG - +4 cisbp__M4492-ey-Poxm-sv-toy 8 0.780744 19091.5 1 6 CACCTG GTCACGCTTGGCTGC - +4 cisbp__M4572-cnc-maf-S-tj 1 0.780744 19091.5 1 6 CACCTG TTTGCTGAGTCAGCA - +4 neph__UW.Motif.0472 8 0.780744 19091.5 1 6 CACCTG TTTCTGTCTTTTTTC - +4 swissregulon__hs__TBP.p2-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 3 0.780744 19091.5 1 6 CACCTG CCGCCCCTTTTATAG - +4 taipale_tf_pairs__ERF_EOMES_TNTCACACCGGAAAT_CAP-Ets21C 2 0.780744 19091.5 1 6 CACCTG GCTTCCGGTGTGATA - +4 transfac_pro__M09237-Hsf-pb 7 0.780744 19091.5 1 6 CACCTG CTTCTAGAAGCTTCT - +4 transfac_public__M00114-CrebB 8 0.780744 19091.5 1 6 CACCTG TCTGCGTCAACCCCC - +4 taipale_cyt_meth__LEF1_WCATCGRGRCGCTGW_FL-pan -1 0.780744 19091.5 1 5 CACCTG ACATCGGGGCGCTGA + +4 cisbp__M6552-btd-CoRest-crol-ct-CTCF-Spps-sr -1 0.780744 19091.5 1 5 CACCTG CCCCTCCCCCACCCC - +4 transfac_pro__M09059 9 0.781397 19107.5 1 6 CACCTG CTTCATCACCACCGACAAT + +4 transfac_public__M00192 13 0.781397 19107.5 1 6 CACCTG CAAGAACACAGTGTACCCA - +4 tfdimers__MD00040-nub-pdm2 16 0.78186 19118.8 1 6 CACCTG AAAAAAAAAATGCAAATCCCTTTAGTTTA + +4 transfac_pro__M09200 17 0.78186 19118.8 1 6 CACCTG CGAATATTCCTTTATTTCATCTGTATAAT + +4 tfdimers__MD00315-oc 13 0.78186 19118.8 1 6 CACCTG TAATTATCTAATCCACTTAAAAATAATAT - +4 predrem__nrMotif2283 0 0.782293 19129.4 1 6 CACCTG GACCATG + +4 cisbp__M0949-abd-A-Antp-ap-Awh-bsh-btn-C15-CG18599-CG32532-Dbx-Dfd-E5-ems-en-eve-ftz-HGTX-ind-lab-lms-NK7.1-pb-Scr-slou-tup-Ubx-unpg-zen-zen2 0 0.782293 19129.4 1 6 CACCTG TCATTAA - +4 hdpi__PQBP1 1 0.782293 19129.4 1 6 CACCTG CCAAATT - +4 jaspar__MA0338.1-klu-sr -1 0.782293 19129.4 1 5 CACCTG CCCCGCA + +4 cisbp__M4256-klu-sr -1 0.782293 19129.4 1 5 CACCTG CCCCGCA - +4 cisbp__M4291-klu-sr -1 0.782293 19129.4 1 5 CACCTG CCCCGCA - +4 idmmpmm__bcd-Gsc-Ptx1-bcd 2 0.782293 19129.4 1 5 CACCTG CTAATCC - +4 transfac_pro__M01966-klu-sr -1 0.782293 19129.4 1 5 CACCTG CCCCGCA - +4 elemento__CCAGCGC -2 0.782293 19129.4 1 4 CACCTG CCAGCGC + +4 elemento__CCCGCCC-kay -2 0.782293 19129.4 1 4 CACCTG CCCGCCC + +4 elemento__CCCGCCG -2 0.782293 19129.4 1 4 CACCTG CCCGCCG + +4 elemento__CCCGCGC -2 0.782293 19129.4 1 4 CACCTG CCCGCGC + +4 elemento__CCCGCGG -2 0.782293 19129.4 1 4 CACCTG CCCGCGG + +4 elemento__CCCGCTC -2 0.782293 19129.4 1 4 CACCTG CCCGCTC + +4 elemento__CCCGGAA-Eip74EF -2 0.782293 19129.4 1 4 CACCTG CCCGGAA + +4 elemento__CCCGGAG -2 0.782293 19129.4 1 4 CACCTG CCCGGAG + +4 elemento__CCCGGCC -2 0.782293 19129.4 1 4 CACCTG CCCGGCC + +4 elemento__CCCGGCG -2 0.782293 19129.4 1 4 CACCTG CCCGGCG + +4 elemento__CCCGGGC -2 0.782293 19129.4 1 4 CACCTG CCCGGGC + +4 elemento__CCGGAAA -2 0.782293 19129.4 1 4 CACCTG CCGGAAA + +4 elemento__CCGGAGC -2 0.782293 19129.4 1 4 CACCTG CCGGAGC + +4 elemento__CCGGCCC -2 0.782293 19129.4 1 4 CACCTG CCGGCCC + +4 elemento__CCGGCCG -2 0.782293 19129.4 1 4 CACCTG CCGGCCG + +4 elemento__CCGGCGC -2 0.782293 19129.4 1 4 CACCTG CCGGCGC + +4 elemento__CCGGCTC -2 0.782293 19129.4 1 4 CACCTG CCGGCTC + +4 elemento__CCGGGCC -2 0.782293 19129.4 1 4 CACCTG CCGGGCC + +4 elemento__CCGGGGC -2 0.782293 19129.4 1 4 CACCTG CCGGGGC + +4 predrem__nrMotif2142 -2 0.782293 19129.4 1 4 CACCTG TCTTTAT + +4 predrem__nrMotif482 3 0.782293 19129.4 1 4 CACCTG TGTTCCC + +4 elemento__ATGCTGG -2 0.782293 19129.4 1 4 CACCTG CCAGCAT - +4 elemento__CCCCGGG -2 0.782293 19129.4 1 4 CACCTG CCCGGGG - +4 elemento__CCGCCGG -2 0.782293 19129.4 1 4 CACCTG CCGGCGG - +4 fantom__motif19_GYTGGMC 3 0.782293 19129.4 1 4 CACCTG GTCCAGC - +4 predrem__nrMotif1767 3 0.782293 19129.4 1 4 CACCTG CATTTCC - +4 predrem__nrMotif228 3 0.782293 19129.4 1 4 CACCTG TTTTGCC - +4 predrem__nrMotif2298 3 0.782293 19129.4 1 4 CACCTG TTTTAGC - +4 cisbp__M5026-E(spl)mgamma-HLH -3 0.782293 19129.4 1 3 CACCTG CTTGACA + +4 jaspar__MA0368.1 -3 0.782293 19129.4 1 3 CACCTG CTTGGCG + +4 predrem__nrMotif1354 4 0.782293 19129.4 1 3 CACCTG TGCAGAC + +4 predrem__nrMotif1457 4 0.782293 19129.4 1 3 CACCTG CAAAGAC + +4 predrem__nrMotif1957 4 0.782293 19129.4 1 3 CACCTG AGAAGAC + +4 predrem__nrMotif2100 4 0.782293 19129.4 1 3 CACCTG CAATGAC + +4 hdpi__HOXD3 4 0.782293 19129.4 1 3 CACCTG AAATTAC - +4 swissregulon__sacCer__RIM101 -3 0.782293 19129.4 1 3 CACCTG CTTGGCG - +4 cisbp__M0972-al-ap-Awh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-E5-ems-en-ey-gsb-gsb-n-ind-inv-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm3-PHDP-Pph13-prd-repo-ro-Rx-slo 1 0.782568 19136.1 1 6 CACCTG CTAATTGA + +4 cisbp__M1405 1 0.782568 19136.1 1 6 CACCTG ACACGCAA + +4 cisbp__M6108-al-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Drgx-E5-ems-en-ind-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-zfh2 1 0.782568 19136.1 1 6 CACCTG CTAATTAA + +4 taipale__DLX2_DBD_NYAATTAN-Dll-Dr 1 0.782568 19136.1 1 6 CACCTG CCAATTAC + +4 taipale__DLX3_DBD_NYAATTAN-Dll-Dr 1 0.782568 19136.1 1 6 CACCTG CCAATTAC + +4 taipale__Dlx1_DBD_NYAATTAN_repr-Dll-Dr 1 0.782568 19136.1 1 6 CACCTG CCAATTAC + +4 taipale__SHOX2_DBD_NYAATTAN-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2-z 1 0.782568 19136.1 1 6 CACCTG CCAATTAA + +4 taipale__UNCX_DBD_NYAATTAN-al-ap-Awh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm3-Pph13- 1 0.782568 19136.1 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__HOXB5_RTCGTTAN_FL_meth-Antp-btn-Dfd-eve-exex-lab-pb-Scr 0 0.782568 19136.1 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__VSX1_YTAATTAN_eDBD_meth_repr-CG11294-CG4328-Drgx-E5-ems-en-eve-ind-inv-Lim3-Lmx1a-pb-Ubx-Vsx1-Vsx2 1 0.782568 19136.1 1 6 CACCTG CTAATTAC + +4 tiffin__TIFDMEM0000059 1 0.782568 19136.1 1 6 CACCTG TTATCGAA + +4 transfac_pro__M00313 0 0.782568 19136.1 1 6 CACCTG CCTCATTT + +4 transfac_pro__M00314 0 0.782568 19136.1 1 6 CACCTG CCTCATTC + +4 cisbp__M0383-sr 0 0.782568 19136.1 1 6 CACCTG CGCCCACG - +4 cisbp__M5341-Dll-Dr 1 0.782568 19136.1 1 6 CACCTG CCAATTAC - +4 cisbp__M5806-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm 1 0.782568 19136.1 1 6 CACCTG CTAATTAA - +4 cisbp__M0577 3 0.782568 19136.1 1 5 CACCTG TGTCACAC + +4 jaspar__MA0943.1 3 0.782568 19136.1 1 5 CACCTG GCCGACAA + +4 predrem__nrMotif1019 -1 0.782568 19136.1 1 5 CACCTG CTCTGACA + +4 predrem__nrMotif1249 3 0.782568 19136.1 1 5 CACCTG TTAGTCCT + +4 stark__WCATTWMM-zen-zen2 -1 0.782568 19136.1 1 5 CACCTG ACATTAAA + +4 cisbp__M0055 3 0.782568 19136.1 1 5 CACCTG TTTGAGCT - +4 predrem__nrMotif762 -1 0.782568 19136.1 1 5 CACCTG ACTCTGAC - +4 swissregulon__sacCer__GCR1 3 0.782568 19136.1 1 5 CACCTG GGCTTCCA - +4 cisbp__M1671 -2 0.782568 19136.1 1 4 CACCTG CCCGCGGG + +4 homer__CCWTTGTY_Sox3-D-Mad-Sox14-Sox15-Sox102F-SoxN -2 0.782568 19136.1 1 4 CACCTG CCTTTGTT + +4 predrem__nrMotif1666 4 0.782568 19136.1 1 4 CACCTG ACAAGCCC + +4 predrem__nrMotif1791 4 0.782568 19136.1 1 4 CACCTG GGATGCCC + +4 cisbp__M0916-ems-eve 4 0.782568 19136.1 1 4 CACCTG TCATTAGC - +4 predrem__nrMotif1238 4 0.782568 19136.1 1 4 CACCTG TGCCCATC - +4 predrem__nrMotif2593 -2 0.782568 19136.1 1 4 CACCTG CCCGAGAG - +4 transfac_pro__M08949-al-Antp-ap-Awh-CG11294-CG32532-CG7745-CG9876-E5-ems-en-gsb-gsb-n-ind-inv-Lim1-Lim3-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-unpg-Vsx1-vvl-zfh2 4 0.782568 19136.1 1 4 CACCTG TAATTAAT - +4 cisbp__M1077-Antp-Awh-HGTX-Scr-al-ap-ind-lab-zen2 -3 0.782568 19136.1 1 3 CACCTG CTAATTAA + +4 cisbp__M1159-abd-A-Antp-cad-Dfd-ftz-HGTX-lab-Scr-Ubx 5 0.782568 19136.1 1 3 CACCTG TTAATTAC + +4 hdpi__RPS4X-RpS4 -3 0.782568 19136.1 1 3 CACCTG CTTGTGAA + +4 predrem__nrMotif2331 5 0.782568 19136.1 1 3 CACCTG TCTGCAAC + +4 predrem__nrMotif783 5 0.782568 19136.1 1 3 CACCTG AAGACAAC + +4 taipale_cyt_meth__LHX1_NYAATTAN_eDBD-Antp-bsh-btn-Dfd-Dll-Dr-en-exex-inv-lab-Lim1-pb-Scr-unpg 5 0.782568 19136.1 1 3 CACCTG GCAATTAC + +4 predrem__nrMotif323 5 0.782568 19136.1 1 3 CACCTG AAATGAAC - +4 cisbp__M4530-Jra-kay-Mef2 7 0.783176 19151 1 6 CACCTG GATGACTCACACA + +4 cisbp__M5750 3 0.783176 19151 1 6 CACCTG GGGGGCCTTGAAA + +4 taipale_cyt_meth__KLF13_NRCCACGCCCMYN_FL_repr-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.783176 19151 1 6 CACCTG CGCCACGCCCCCC + +4 transfac_pro__M04610-ct 0 0.783176 19151 1 6 CACCTG CGTTTGACCAATG + +4 transfac_pro__M06994-hbn-oc 2 0.783176 19151 1 6 CACCTG ATAATCTGATTAT + +4 transfac_pro__M07934-klu-sr 2 0.783176 19151 1 6 CACCTG CCCACCCACGCAC + +4 cisbp__M0373 5 0.783176 19151 1 6 CACCTG CAGTACACTAGTG - +4 cisbp__M2306-nub-pdm2-vvl 5 0.783176 19151 1 6 CACCTG ATATGCAAATGAA - +4 cisbp__M5203-sob 2 0.783176 19151 1 6 CACCTG GCTACTGTGTTTA - +4 taipale__UNCX_DBD_NTAATYTAATTAN-al-bsh-C15-CG11294-CG32532-CG34367-CG9876-Drgx-eve-Lim3-OdsH-Optix-repo-Rx-Traf4-unc-4 5 0.783176 19151 1 6 CACCTG CTAATTAAATTAG - +4 transfac_pro__M07751-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.783176 19151 1 6 CACCTG ACAATAACATTGT - +4 hocomoco__MAFK_MOUSE.H11MO.1.A-cnc-maf-S-tj 8 0.783176 19151 1 5 CACCTG TGCTGAGTCAGCA + +4 transfac_pro__M08922-bon-Jra-kay-nej 8 0.783176 19151 1 5 CACCTG TGATGACTCATAC + +4 transfac_pro__M07287-croc-foxo -1 0.783176 19151 1 5 CACCTG GCTTGTTTATTTT - +4 idmmpmm__prd-prd 0 0.783192 19151.4 1 6 CACCTG CCAATTCGTCACGC + +4 taipale_cyt_meth__FOXD2_NWACAATAAYAWWN_eDBD_meth_repr-fd59A-fkh 7 0.783192 19151.4 1 6 CACCTG CAACAATAACATTA + +4 taipale_cyt_meth__MAF_NYGCTGACNNNGCR_FL-maf-S-tj 5 0.783192 19151.4 1 6 CACCTG ATGCTGACAATGCA + +4 transfac_pro__M01967 7 0.783192 19151.4 1 6 CACCTG ATTGATTGACAGGG + +4 transfac_pro__M02809 3 0.783192 19151.4 1 6 CACCTG ATTTTACGGAAAAT + +4 c2h2_zfs__M5107-opa 0 0.783192 19151.4 1 6 CACCTG GACCCCCCGCTGTG - +4 cisbp__M4565-brm-cnc-CoRest-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-pnr-Stat92E 7 0.783192 19151.4 1 6 CACCTG GGTGACTCATCCTG - +4 taipale_tf_pairs__FLI1_DLX2_RSCGGAARYAATTA_CAP 7 0.783192 19151.4 1 6 CACCTG TAATTATTTCCGGT - +4 taipale_tf_pairs__HOXB2_PITX1_TAATKANNGGATTA_CAP_repr-pb-Ptx1 2 0.783192 19151.4 1 6 CACCTG TAATCCCGTAATTA - +4 transfac_pro__M01478 8 0.783192 19151.4 1 6 CACCTG TTTGATTCGATCAT - +4 transfac_pro__M07687-maf-S-tj 6 0.783192 19151.4 1 6 CACCTG TGTCAGCACTTTTT - +4 transfac_pro__M09484-tll 8 0.783192 19151.4 1 6 CACCTG AAAAAGTCAACGAT - +4 factorbook__UA8-nej -2 0.783192 19151.4 1 4 CACCTG TCTGGTTTCTATCA - +4 transfac_pro__M00657 -2 0.783192 19151.4 1 4 CACCTG CCTGTGGTTTTCCC - +4 taipale__Mafb_DBD_NNTGCTGASTCAGCANN_repr-cnc-maf-S-nej-tj 10 0.784391 19180.7 1 6 CACCTG TGTGCTGAGTCAGCATT + +4 taipale_tf_pairs__FOXO1_HOXB13_GWMAACANNSYMRTAAA_CAP_repr-foxo 3 0.784391 19180.7 1 6 CACCTG AACAACAAACCCATAAA + +4 hocomoco__SPI1_HUMAN.H11MO.0.A-CG9650-Dif-Ets96B-MTA1-like-Stat92E-dl-ebi-nej-sv 6 0.784391 19180.7 1 6 CACCTG TTTCACTTCCTCTTTTT - +4 taipale_cyt_meth__NFIX_NTTGGCNNNNTGCCARN_FL_meth-C15-Nf1-NfI 5 0.784391 19180.7 1 6 CACCTG CTTGGCACCGTGCCAAC - +4 taipale_cyt_meth__NFIX_NTTGGCNNNNTGCCARN_FL_repr-C15-Nf1-NfI 5 0.784391 19180.7 1 6 CACCTG CCTGGCACCGTGCCAAC - +4 taipale_tf_pairs__ELK1_FOXI1_RSCGGAANNRTMAAYAN_CAP_repr 7 0.784391 19180.7 1 6 CACCTG ATGTTTACACTTCCGGT - +4 transfac_pro__M01203 3 0.784391 19180.7 1 6 CACCTG CCCTACTTCCGCTTTTT - +4 transfac_pro__M01441-al-Antp-Awh-C15-CG18599-CG32532-CG34367-CG9876-Dfd-E5-ems-en-inv-lbe-Lim3-OdsH-otp-repo-ro-Rx-Scr-unc-4-vvl-zfh2 2 0.784391 19180.7 1 6 CACCTG GATACCTAATTAGCGCG - +4 transfac_pro__M01477-Antp-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-Dbx-Dfd-HGTX-Lim1-Lim3-Lmx1a-nub-OdsH-otp-pdm2-pdm3-repo-Scr-unc-4-vvl 1 0.784391 19180.7 1 6 CACCTG CAAACTAATTAATTATC - +4 hocomoco__MAF_MOUSE.H11MO.0.A-cnc-maf-S-tj -1 0.784391 19180.7 1 5 CACCTG TGCTGAGTCAGCAAATT - +4 hocomoco__PAX1_HUMAN.H11MO.0.D-Poxm-ey-sv-toy 12 0.784391 19180.7 1 5 CACCTG TCAGTCAAGCGTGACGA - +4 tfdimers__MD00578 11 0.785058 19197 1 6 CACCTG CTCTCTTCTCCCATCTGTCACTGGCTTC - +4 tfdimers__MD00316-pan 3 0.785332 19203.7 1 6 CACCTG TATTTCCTTTGTTTTGCAAAACAAAGGAAATA + +4 dbcorrdb__BCL11A__ENCSR000BHA_1__m2-Bgb-Bro-CG9650-ebi-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 6 0.78547 19207.1 1 6 CACCTG ACAAACCACAGACTAAATTT + +4 dbcorrdb__BDP1__ENCSR000DNX_1__m2-Bdp1 4 0.78547 19207.1 1 6 CACCTG CCCCCACCGGGACTGGAACG + +4 dbcorrdb__CEBPB__ENCSR000EBV_1__m1-Irbp18-nej-slbo-Xrp1 13 0.78547 19207.1 1 6 CACCTG GCTGAGATTGCGTAATCGCA + +4 dbcorrdb__EP300__ENCSR000EDV_1__m3-CG7786-gt-Myc-nej-Pdp1-slbo-Stat92E 10 0.78547 19207.1 1 6 CACCTG TATTACGCAATACCCAACTG + +4 dbcorrdb__EZH2__ENCSR000ARO_1__m1-E(z) 3 0.78547 19207.1 1 6 CACCTG TCGTGCGTGTCGGTGTTGCC + +4 dbcorrdb__EZH2__ENCSR000ATC_1__m1-E(z) 11 0.78547 19207.1 1 6 CACCTG AGAAGACACCCGACATTTAG + +4 dbcorrdb__HDAC1__ENCSR000AQF_1__m3-HDAC1 9 0.78547 19207.1 1 6 CACCTG CAGGCGCGGTACGGTCGCCA + +4 dbcorrdb__MTA3__ENCSR000BRH_1__m2-Bgb-Bro-CG9650-ebi-foxo-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 7 0.78547 19207.1 1 6 CACCTG AACAAACCACAGAAATTATT + +4 dbcorrdb__NRF1__ENCSR000DZO_1__m1-Brf-E2f1-ewg-E(z)-Myc-RpII215 5 0.78547 19207.1 1 6 CACCTG CCCTGCGCCTGCGCAGGGGG + +4 dbcorrdb__POLR2A__ENCSR000EHL_1__m2-RpII215 13 0.78547 19207.1 1 6 CACCTG GCTCCCCACAGGCTCCTTGT + +4 dbcorrdb__RUNX3__ENCSR000BRI_1__m1-Bgb-Bro-CG9650-foxo-lz-MTA1-like-nej-run-RunxA-RunxB-Stat92E 9 0.78547 19207.1 1 6 CACCTG AAAAATACAAACCACAAAAA + +4 dbcorrdb__SIN3A__ENCSR000BOW_1__m4-CrebB-Sin3A 1 0.78547 19207.1 1 6 CACCTG GCAACAGCGCCGGCCCGCGC + +4 dbcorrdb__SMARCC2__ENCSR000EDL_1__m4-mor 11 0.78547 19207.1 1 6 CACCTG ACGCCTTGCGTCATCCCATC + +4 dbcorrdb__STAT1__ENCSR000EHK_1__m1-aop-Stat92E 5 0.78547 19207.1 1 6 CACCTG GCCATTTCCCGGAAATGACG + +4 dbcorrdb__STAT3__ENCSR000DOU_1__m2-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 10 0.78547 19207.1 1 6 CACCTG AAGTATGACTCATCTTTTCT + +4 dbcorrdb__TAF1__ENCSR000BIB_1__m1-CG10431-E(z)-lid-pho-phol-RpII215-Taf1-Taf7 14 0.78547 19207.1 1 6 CACCTG GCCGCCGCCGCCGCCATCTT + +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m1-bon 11 0.78547 19207.1 1 6 CACCTG CCTGCTGACTTATCCTATAA + +4 factorbook__TBP-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 8 0.78547 19207.1 1 6 CACCTG CCGCGCCGCGGCTTTTATAG + +4 homer__NNTTCTGGAANNTTCTAGAA_HRE-Hsf-pb 8 0.78547 19207.1 1 6 CACCTG CCTTCTGGAAGCTTCCAGAA + +4 transfac_pro__M09363 11 0.78547 19207.1 1 6 CACCTG TGCCGTGATATCTACGCTAC + +4 cisbp__M3698 1 0.78547 19207.1 1 6 CACCTG GGACATGCCCGGGCATGTCT - +4 dbcorrdb__ATF1__ENCSR000DNZ_1__m2-cnc-CoRest-CrebB-Jra-RpII215-Usf 13 0.78547 19207.1 1 6 CACCTG CCCCCGGGTGACGCAACCGG - +4 dbcorrdb__BACH1__ENCSR000EBQ_1__m1-cnc-ewg-Jra-kay-maf-S 11 0.78547 19207.1 1 6 CACCTG CAAGGATGACTCAGCACTTT - +4 dbcorrdb__CEBPB__ENCSR000EFM_1__m2-CoRest-Jra-kay-Myc-pan-Stat92E 8 0.78547 19207.1 1 6 CACCTG CAATGAGTCATACCTTAGTC - +4 dbcorrdb__CTCF__ENCSR000AOO_1__m2-CTCF 11 0.78547 19207.1 1 6 CACCTG GGGCAAAACTGCAGTTTCCC - +4 dbcorrdb__CTCF__ENCSR000DWY_1__m2-CTCF-SMC3-vtd 3 0.78547 19207.1 1 6 CACCTG GGCCATTTGGGGAACTGCAG - +4 dbcorrdb__ELK1__ENCSR000EFU_1__m1-aop-Atac3-bs-CTCF-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-Max-Myc-pho-phol-pnt-Rbbp5-RpII215-Sin3A-Taf1 9 0.78547 19207.1 1 6 CACCTG CGCGGGCGCCACTTCCGGCC - +4 dbcorrdb__EP300__ENCSR000BHB_1__m3-Atac3-CG9650-ebi-Eip74EF-Ets96B-MTA1-like-nej-Stat92E 8 0.78547 19207.1 1 6 CACCTG GCCACTTTCACTTCCGGTTT - +4 dbcorrdb__ESRRA__ENCSR000DYQ_1__m4-ERR 8 0.78547 19207.1 1 6 CACCTG TCTGTCCTTTCCGTGGGACA - +4 dbcorrdb__EZH2__ENCSR000ASW_1__m1-E(z)-Myc-vtd 4 0.78547 19207.1 1 6 CACCTG CCCGCAGCCGCTTCCCCGCC - +4 dbcorrdb__GTF2F1__ENCSR000EHC_1__m2-TfIIFalpha 9 0.78547 19207.1 1 6 CACCTG TGGCGCCGTCGCGTGCCGCG - +4 dbcorrdb__IRF1__ENCSR000EGL_1__m1-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E 1 0.78547 19207.1 1 6 CACCTG TCACTTTCACTTTCACTTTC - +4 dbcorrdb__JUN__ENCSR000EFA_1__m1-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 12 0.78547 19207.1 1 6 CACCTG TAAAAGATGACTCATTCTTT - +4 dbcorrdb__MYC__ENCSR000DLZ_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-cwo-E2f1-Eip74EF-ERR-E(z)-gce-HDAC1-Hey-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-Taf1-tgo-tna-Us 8 0.78547 19207.1 1 6 CACCTG CCGGCGGCCACGTGGCCCCG - +4 dbcorrdb__MYC__ENCSR000EZU_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-ERR-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-RpII215-Sap30-Spps-SREBP-Taf1-tgo-tna-Usf 9 0.78547 19207.1 1 6 CACCTG CCCGGCGGCCACGTGGTCCG - +4 dbcorrdb__POLR2A__ENCSR000EZQ_1__m1-btd-E2f2-Nf-YA-RpII215-Spps 6 0.78547 19207.1 1 6 CACCTG CGCCGCGGCCTATAAGCGCC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000ECT_1__m1-CrebB-Eip74EF-Hcf-RpII215-Sin3A-Taf1-TfIIFalpha 1 0.78547 19207.1 1 6 CACCTG GCGCTTCCGCCGCGGGGGGG - +4 dbcorrdb__RXRA__ENCSR000BJD_1__m5-usp 10 0.78547 19207.1 1 6 CACCTG AGTAACGCACTGCCCCACGA - +4 dbcorrdb__SPI1__ENCSR000BGW_1__m1-CG9650-Ets96B-nej-pnt-Stat92E-sv 4 0.78547 19207.1 1 6 CACCTG CTCCCACTTCCTCTTTTTCT - +4 dbcorrdb__STAT1__ENCSR000DZM_1__m5-Stat92E 4 0.78547 19207.1 1 6 CACCTG CTGCCCCCTTCGCGGTTTCG - +4 dbcorrdb__STAT3__ENCSR000EDC_1__m1-Jra-kay-Myc-nej-Stat92E 8 0.78547 19207.1 1 6 CACCTG AAATGAGTCATCTTTTTTTT - +4 dbcorrdb__TAF1__ENCSR000BIM_1__m1-lid-pho-phol-Rbbp5-RpII215-Taf1-Taf7 9 0.78547 19207.1 1 6 CACCTG CGCCGCCGCCATCTTGCGGC - +4 dbcorrdb__ZC3H11A__ENCSR000EFR_1__m2-Brf-brm-CTCF-ERR-E(z)-Nelf-E-RpII215-SREBP-tna 2 0.78547 19207.1 1 6 CACCTG GGGGCCCGGCCCGGCGCCCT - +4 hocomoco__SP4_HUMAN.H11MO.0.A-CG42741-E2f2-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-luna-sr 8 0.78547 19207.1 1 6 CACCTG CCCGGCCCCGCCCCCTTCCC - +4 taipale_tf_pairs__ELK1_PAX1_RSCGGAACYACGCWYSANTG_CAP-Poxm -1 0.78547 19207.1 1 5 CACCTG ACCGGAACTACGCTTCACTG + +4 dbcorrdb__SRF__ENCSR000BGE_1__m3-bs-Nf-YA 15 0.78547 19207.1 1 5 CACCTG TTCCGTGATTGGCTACGCCT - +4 dbcorrdb__JUN__ENCSR000EFS_1__m2-Jra -2 0.78547 19207.1 1 4 CACCTG CCTCTCTGAGCACTGAGAAG - +4 dbcorrdb__RFX5__ENCSR000EHY_1__m3 -2 0.78547 19207.1 1 4 CACCTG GCTTCCCTCATGGCCATTCT - +4 transfac_pro__M01228 1 0.786093 19222.3 1 4 CACCTG TGACT + +4 tfdimers__MD00153-CG7786-gt-Pdp1 19 0.787658 19260.6 1 6 CACCTG TTAATTTAATTTAATTATGTAAATAAA + +4 fantom__motif53_ANGCTG 0 0.787934 19267.3 1 6 CACCTG CAGCAT - +4 hdpi__FAM119B 1 0.787934 19267.3 1 5 CACCTG TTATTT - +4 fantom__motif15_ACTGTG -2 0.787934 19267.3 1 4 CACCTG ACTGTG + +4 hdpi__MSI1-Rbp6 2 0.787934 19267.3 1 4 CACCTG TACACA - +4 hdpi__CLK1 -3 0.787934 19267.3 1 3 CACCTG CTTTCA - +4 c2h2_zfs__M1734-br 1 0.788365 19277.9 1 6 CACCTG TAAACTAAAAG + +4 cisbp__M5727-nub-pdm2-vvl 4 0.788365 19277.9 1 6 CACCTG AATTTGCATAT + +4 cisbp__M6302 0 0.788365 19277.9 1 6 CACCTG TCCCTAATAAA + +4 jaspar__MA0012.1-br 1 0.788365 19277.9 1 6 CACCTG TAAACTAAAAG + +4 scertf__macisaac.PDR1 1 0.788365 19277.9 1 6 CACCTG CCGCCGAATAA + +4 taipale_cyt_meth__KLF6_NRCCACGCCCN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 5 0.788365 19277.9 1 6 CACCTG GGCCACGCCCA + +4 transfac_pro__M05284 1 0.788365 19277.9 1 6 CACCTG TTAACTTTAAT + +4 transfac_pro__M07750-SoxN 3 0.788365 19277.9 1 6 CACCTG ACGAACAATGC + +4 cisbp__M4615-Dp-E2f1-E2f2 5 0.788365 19277.9 1 6 CACCTG CTTCCCGCCCC - +4 hocomoco__KLF12_HUMAN.H11MO.0.C-CG42741-Spps-Stat92E-btd-dar1-luna 5 0.788365 19277.9 1 6 CACCTG GCCCCGCCCCT - +4 idmmpmm__dl-Dif-Rel-dl 5 0.788365 19277.9 1 6 CACCTG GGGAAAACCCC - +4 predrem__nrMotif2617 5 0.788365 19277.9 1 6 CACCTG CTGCTCAGCAC - +4 transfac_pro__M07066-Stat92E 1 0.788365 19277.9 1 6 CACCTG TTTCCTGGGAA - +4 cisbp__M6230-cnc-CoRest-Jra-kay-mor-Myc-nej-pan-Stat92E 6 0.788365 19277.9 1 5 CACCTG ATGACTCATCC + +4 stark__GGGGAWTCCCY-Dif-Rel 6 0.788365 19277.9 1 5 CACCTG GGGGAATCCCC + +4 cisbp__M0742-CHES-1-like-croc-fd59A-fkh-FoxK-foxo-FoxP-slp1-slp2 6 0.788365 19277.9 1 5 CACCTG TTTGTTTACAT - +4 cisbp__M5519-Hmx -1 0.788365 19277.9 1 5 CACCTG ACCAATTAAAA - +4 jaspar__MA0483.1-sens-sens-2 -1 0.788365 19277.9 1 5 CACCTG TGCTGTGATTT - +4 predrem__nrMotif1194 6 0.788365 19277.9 1 5 CACCTG CCTCCATCCCC - +4 transfac_pro__M06790 7 0.788365 19277.9 1 4 CACCTG TGGACTAAACC + +4 transfac_pro__M09285 7 0.788365 19277.9 1 4 CACCTG TAACCGTTACA + +4 cisbp__M4608-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 7 0.788365 19277.9 1 4 CACCTG GATGAGTCATC - +4 taipale_cyt_meth__HOXA10_NGTCGTAAAAN_eDBD-Abd-B-cad 7 0.788365 19277.9 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC11_RGYAATAAAAN_eDBD-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.788365 19277.9 1 4 CACCTG GTTTTATGACC - +4 transfac_pro__M05074 8 0.788365 19277.9 1 3 CACCTG AACGCCGTTAC - +4 cisbp__M2108-Jra-kay-Mef2-Myc-Stat92E 12 0.788413 19279.1 1 6 CACCTG TGAAGTATGACTCATCCCTTG + +4 cisbp__M2150-Tbp 2 0.788413 19279.1 1 6 CACCTG ATGACCTATATATAAAAATGA + +4 cisbp__M6330 12 0.788413 19279.1 1 6 CACCTG GTGCTGACCCCGCAGCCTTCC + +4 jaspar__MA0378.1-CG12054 15 0.788413 19279.1 1 6 CACCTG ATTGAAAAAAATTTTCTACGG + +4 taipale_tf_pairs__TEAD4_HOXA13_RCATWCCNNNNNNTTTAYNNN_CAP_repr-sd 3 0.788413 19279.1 1 6 CACCTG GCATTCCACACAATTTACGAG + +4 yetfasco__YPR052C_879-Tbp 2 0.788413 19279.1 1 6 CACCTG ATGACCTATATATAAAAATGA + +4 transfac_pro__M01555-Jra-kay-Mef2-Myc-Stat92E 12 0.788413 19279.1 1 6 CACCTG TGAAGTATGACTCATCCCTTG - +4 taipale_cyt_meth__ZNF12_GGKSMTRYTTGTTWYAGCANN_eDBD_repr 17 0.788413 19279.1 1 4 CACCTG TATGCTATAACAAGCAGCCCC - +4 tfdimers__MD00281-cad-Hnf4-svp 15 0.789632 19308.9 1 6 CACCTG ATTTTTTATTTATTGGACTTTTAATT - +4 cisbp__M0829-CG4328-Lmx1a 1 0.789984 19317.5 1 6 CACCTG CTAATTTAT + +4 cisbp__M1039-al-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-ind-inv-lab-lbe-lms-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 2 0.789984 19317.5 1 6 CACCTG GCTAATTGG + +4 cisbp__M1239-nub-pdm2-pdm3 0 0.789984 19317.5 1 6 CACCTG CTAATTAAC + +4 cisbp__M1246-nub-pdm2-pdm3 0 0.789984 19317.5 1 6 CACCTG CTAATTAAC + +4 fantom__motif118_AATCCGGCT 0 0.789984 19317.5 1 6 CACCTG AATCCGGCT + +4 neph__UW.Motif.0036 2 0.789984 19317.5 1 6 CACCTG ATTTCATCA + +4 predrem__nrMotif1513 0 0.789984 19317.5 1 6 CACCTG CACTTCTCT + +4 predrem__nrMotif2571 0 0.789984 19317.5 1 6 CACCTG CTCCGGGGG + +4 predrem__nrMotif52 3 0.789984 19317.5 1 6 CACCTG CCACAGCTT + +4 predrem__nrMotif697 0 0.789984 19317.5 1 6 CACCTG TCACTGACA + +4 predrem__nrMotif764 0 0.789984 19317.5 1 6 CACCTG TCTCTGTGT + +4 predrem__nrMotif846 1 0.789984 19317.5 1 6 CACCTG AGAGCTCTG + +4 predrem__nrMotif891 1 0.789984 19317.5 1 6 CACCTG ACCCCGGGC + +4 transfac_pro__M07352-Gsc-oc-Ptx1 3 0.789984 19317.5 1 6 CACCTG CCTAATCCC + +4 cisbp__M0950-Antp-bsh-Dll-Dr-lab-Scr 2 0.789984 19317.5 1 6 CACCTG GGCAATTAT - +4 cisbp__M0997-abd-A-al-Antp-ap-Awh-B-H1-B-H2-bsh-btn-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-gsb-gsb-n-HGTX-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lm 1 0.789984 19317.5 1 6 CACCTG GGTAATTAA - +4 cisbp__M1191-Antp-Awh-CG4328-CG9876-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-dve-ems-en-eve-ftz-inv-lab-lbl-lms- 1 0.789984 19317.5 1 6 CACCTG GTTAATTAA - +4 cisbp__M6036-Abd-B-cad 3 0.789984 19317.5 1 6 CACCTG TTTTACGAC - +4 predrem__nrMotif1830 0 0.789984 19317.5 1 6 CACCTG TTCCCATTA - +4 predrem__nrMotif1969 2 0.789984 19317.5 1 6 CACCTG TGTTCTTGA - +4 predrem__nrMotif321 1 0.789984 19317.5 1 6 CACCTG AGCCCTCAG - +4 predrem__nrMotif879 0 0.789984 19317.5 1 6 CACCTG GGCCAGTGT - +4 tiffin__TIFDMEM0000040-srp 3 0.789984 19317.5 1 6 CACCTG TCTTATCAG - +4 transfac_pro__M09562-Taf1 1 0.789984 19317.5 1 6 CACCTG GCGCCGCCA - +4 predrem__nrMotif17 -1 0.789984 19317.5 1 5 CACCTG CCCAGCCCC + +4 predrem__nrMotif1984 4 0.789984 19317.5 1 5 CACCTG TTTCAATCT + +4 predrem__nrMotif2306 -1 0.789984 19317.5 1 5 CACCTG CCCAGGGCG + +4 taipale_cyt_meth__TCF7_ASATCAAAS_eDBD-pan -1 0.789984 19317.5 1 5 CACCTG ACATCAAAG + +4 tiffin__TIFDMEM0000019 -1 0.789984 19317.5 1 5 CACCTG ATTTGTATT + +4 cisbp__M0100-retn 4 0.789984 19317.5 1 5 CACCTG TAATTAAAA - +4 predrem__nrMotif1307 4 0.789984 19317.5 1 5 CACCTG CACTCAGCA - +4 predrem__nrMotif1731 -1 0.789984 19317.5 1 5 CACCTG ATCCAGTCT - +4 predrem__nrMotif579 4 0.789984 19317.5 1 5 CACCTG TGAAGACCA - +4 cisbp__M1090-abd-A-Antp-ap-Awh-btn-CG11294-CG18599-CG4328-CG9876-Drgx-E5-ems-en-eve-exex-ftz-ind-inv-lab-lbl-Lim3-lms-Lmx1a-OdsH-otp-pb-pdm3-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 5 0.789984 19317.5 1 4 CACCTG CTAATTACC + +4 hocomoco__LHX3_MOUSE.H11MO.0.C-Lim3 -2 0.789984 19317.5 1 4 CACCTG GCTAATTAA + +4 yetfasco__YDL048C_559 5 0.789984 19317.5 1 4 CACCTG TGCGCTATC + +4 cisbp__M2202 5 0.789984 19317.5 1 4 CACCTG TGCGCTATC - +4 cisbp__M4222 5 0.789984 19317.5 1 4 CACCTG TGCGCTATC - +4 jaspar__MA0397.1 5 0.789984 19317.5 1 4 CACCTG TGCGCTATC - +4 jaspar__MA0953.1 -2 0.789984 19317.5 1 4 CACCTG AATTATTGC - +4 scertf__zhu.STP2 5 0.789984 19317.5 1 4 CACCTG TGCGGCGCC - +4 transfac_pro__M01635 5 0.789984 19317.5 1 4 CACCTG TGCGCTATC - +4 cisbp__M5557-Abd-B-cad 6 0.789984 19317.5 1 3 CACCTG TTTTATTAC - +4 taipale__HOXD12_DBD_GTAATAAAA-Abd-B-cad 6 0.789984 19317.5 1 3 CACCTG TTTTATTAC - +4 transfac_public__M00013-Cf2 6 0.789984 19317.5 1 3 CACCTG TATATATAC - +4 cisbp__M3551-Mef2-rump 4 0.790342 19326.2 1 6 CACCTG TCCGGTGCTAAAAATAGCACCT + +4 taipale_tf_pairs__CUX1_SOX15_ATCRATNNNNNNNNSYATTGTT_CAP_repr-ct 7 0.790342 19326.2 1 6 CACCTG ATCGATACATATGGCCATTGTT + +4 tfdimers__MD00573-Med 5 0.790342 19326.2 1 6 CACCTG CGCGCTGTCTGCAGACAGGGCG + +4 transfac_pro__M07932-her 11 0.790342 19326.2 1 6 CACCTG ACTCATAAACGCACTTATGAGC + +4 transfac_public__M00231-Mef2-rump 4 0.790342 19326.2 1 6 CACCTG TCCGGTGCTAAAAATAGCACCT + +4 tfdimers__MD00448 5 0.790342 19326.2 1 6 CACCTG ATATATACTTATAAAAATTAAT - +4 cisbp__M2546-croc 9 0.790838 19338.4 1 6 CACCTG AAAAATAAATATAATG + +4 hocomoco__DLX4_HUMAN.H11MO.0.D-CG34367-Dll-en-inv-unpg 4 0.790838 19338.4 1 6 CACCTG TAATTACCCTAAATTT + +4 transfac_pro__M01467 0 0.790838 19338.4 1 6 CACCTG AACCCAATAAAATTCG + +4 transfac_pro__M02784-bowl-drm-odd-sob 8 0.790838 19338.4 1 6 CACCTG TTTTACAGTAGCAAAA + +4 transfac_pro__M07339-Six4 3 0.790838 19338.4 1 6 CACCTG ACTTCCCAGAATGCCT + +4 cisbp__M5811-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.790838 19338.4 1 6 CACCTG AACACTGAACATTGTT - +4 factorbook__PAX5-Poxm-sv 8 0.790838 19338.4 1 6 CACCTG GTCACGCTCGGCTGCC - +4 jaspar__MA0045.1 7 0.790838 19338.4 1 6 CACCTG GTTTTTCCATTTGTTG - +4 neph__UW.Motif.0389 8 0.790838 19338.4 1 6 CACCTG TGGGGATGGTTTTTCC - +4 taipale__SOX10_full_AACAATRTKCAGWGTT_repr-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.790838 19338.4 1 6 CACCTG AACACTGAACATTGTT - +4 taipale_tf_pairs__HOXD12_HOXA3_NTAATKRSNMRTAAAN_CAP_repr 6 0.790838 19338.4 1 6 CACCTG TTTTATTACCAATTAG - +4 transfac_pro__M01066-Blimp-1-ebi 1 0.790838 19338.4 1 6 CACCTG TTACTTTCACTTCCTG - +4 transfac_pro__M02778-MTF-1 8 0.790838 19338.4 1 6 CACCTG TTTTTGCACACGGCCC - +4 transfac_pro__M09401 1 0.790838 19338.4 1 6 CACCTG TTGCTTGTTTTTCAAG - +4 transfac_public__M00026-Mef2-rump 0 0.790838 19338.4 1 6 CACCTG AAGCTATAAATAGACT - +4 taipale__RFX2_DBD_NGTTRCCATGGYAACN_repr-CG5846-CG9727-Max-Rfx-SREBP 11 0.790838 19338.4 1 5 CACCTG CGTTGCCATGGCAACG + +4 taipale_cyt_meth__RFX1_NGTTRCCATGGYAACN_eDBD-CG5846-CG9727-Max-Rfx-SREBP 12 0.790838 19338.4 1 4 CACCTG CGTTGCCATGGCAACG + +4 cisbp__M5773-CG5846-CG9727-Max-Rfx-SREBP 12 0.790838 19338.4 1 4 CACCTG CGTTGCCATGGCAACG - +4 cisbp__M5417-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 8 0.791103 19344.8 1 6 CACCTG ACCGGAAGTACATCCGGT + +4 cisbp__M6042-Awh-CG34367-ems-en-inv-Lim3-repo-ro-Rx-zfh2 5 0.791103 19344.8 1 6 CACCTG CTAATTAGCGCTAATTAA + +4 hocomoco__LMX1B_HUMAN.H11MO.0.D-CG4328-CG34367-Lmx1a-unpg 4 0.791103 19344.8 1 6 CACCTG TAATTAATTGATTTATTT + +4 taipale_tf_pairs__E2F3_FOXO6_NMATGACACNGCGCCMNN_CAP-E2f1-foxo 6 0.791103 19344.8 1 6 CACCTG GAATGACACCGCGCCCAC + +4 taipale__PAX5_DBD_NGTCACGCWTSRNTGNNY-ey-Poxm-sv-toy 9 0.791103 19344.8 1 6 CACCTG GAGCACTCATGCGTGACG - +4 taipale_tf_pairs__CEBPG_ELF1_TTGCGYAANNSCGGAAGN_CAP_repr-Eip74EF 2 0.791103 19344.8 1 6 CACCTG ACTTCCGCTATTGCGCAA - +4 transfac_pro__M05518-hb-her 4 0.791103 19344.8 1 6 CACCTG AACCCTCCTCTCCCTTCA - +4 transfac_pro__M06466 1 0.791103 19344.8 1 6 CACCTG TATCCTTTCTCGACGAAG - +4 taipale_tf_pairs__GCM1_SPDEF_RTRSKGGCGGANNNNNATCCNNN_CAP_repr-Ets98B-gcm-gcm2 16 0.791355 19351 1 6 CACCTG GTGCGGGCGGATGTACTTCCGGG + +4 tfdimers__MD00230-Jra-kay-Stat92E 14 0.791355 19351 1 6 CACCTG TATTCTGACTCATTTCCCTTTTT + +4 tfdimers__MD00231-lz-run-RunxA-RunxB 8 0.791355 19351 1 6 CACCTG AAAAAAACCACATAAAACAAAAA + +4 transfac_pro__M04666-FoxP 0 0.791355 19351 1 6 CACCTG CTCATGGTCACAACAAAAACATA + +4 transfac_pro__M00331 10 0.791355 19351 1 6 CACCTG TCTTGCGGTTAGCCTTCTTTCTT - +4 transfac_pro__M04648-jumu 3 0.791355 19351 1 6 CACCTG CGTCATTTGGCGTCCTAAGTGGG - +4 tfdimers__MD00435 8 0.791531 19355.3 1 6 CACCTG CCCCCTTATCCCTCAGCCCCTCCC + +4 tfdimers__MD00171 10 0.791531 19355.3 1 6 CACCTG TAATTCAATTATCCTTTTTTTTTT - +4 tfdimers__MD00409-pho-phol 9 0.791531 19355.3 1 6 CACCTG AATTTTATTTTCCAGATGGTAAAA - +4 cisbp__M0132 3 0.791664 19358.6 1 6 CACCTG GCGCAATAAA + +4 cisbp__M0661 4 0.791664 19358.6 1 6 CACCTG ACTTTAAAGT + +4 cisbp__M0726-bin-br-CHES-1-like-croc-fd59A-fkh-FoxK-foxo-FoxP-slp1-slp2 4 0.791664 19358.6 1 6 CACCTG TGTAAACAAA + +4 cisbp__M1092-al-Awh-en-inv-Lim3 0 0.791664 19358.6 1 6 CACCTG CTAATTACGC + +4 cisbp__M2062-z 2 0.791664 19358.6 1 6 CACCTG AATCACTCAA + +4 cisbp__M5339-Dll 2 0.791664 19358.6 1 6 CACCTG GATAATTAGG + +4 jaspar__MA1002.1-Taf1-lid-pho-phol 2 0.791664 19358.6 1 6 CACCTG GCCGCCGCCA + +4 predrem__nrMotif1733 0 0.791664 19358.6 1 6 CACCTG TGACTGTGAT + +4 predrem__nrMotif2130 4 0.791664 19358.6 1 6 CACCTG CCCCGACCCC + +4 predrem__nrMotif907 0 0.791664 19358.6 1 6 CACCTG GACTGGGGGA + +4 transfac_pro__M01164-Mef2 1 0.791664 19358.6 1 6 CACCTG CCATTTTTGG + +4 transfac_pro__M02114-Ptx1 4 0.791664 19358.6 1 6 CACCTG TGTAATCCCA + +4 cisbp__M0511-klu-sr 0 0.791664 19358.6 1 6 CACCTG AACCCCGCAC - +4 cisbp__M0670-E2f1 3 0.791664 19358.6 1 6 CACCTG ACGCGCCAAA - +4 cisbp__M0868-CG4328-Lim1-Lmx1a-OdsH-repo-unc-4 3 0.791664 19358.6 1 6 CACCTG TATTAATTAA - +4 cisbp__M1509 3 0.791664 19358.6 1 6 CACCTG CCCAAATTTG - +4 hdpi__ZHX3 2 0.791664 19358.6 1 6 CACCTG AGCCCTTTTG - +4 homer__ACTGATAAGA_PQM-1-GATAd-GATAe-grn-pnr-srp 3 0.791664 19358.6 1 6 CACCTG TCTTATCAGT - +4 predrem__nrMotif1781 0 0.791664 19358.6 1 6 CACCTG TTTCTCTTTG - +4 transfac_pro__M07631-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.791664 19358.6 1 6 CACCTG AACATATGTT - +4 predrem__nrMotif2145 -1 0.791664 19358.6 1 5 CACCTG ACCCCAAGCC + +4 taipale_cyt_meth__OLIG3_ACCATATGKT_eDBD_meth-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.791664 19358.6 1 5 CACCTG ACCATATGTT + +4 fantom__motif110_AGTCGCAGCG -1 0.791664 19358.6 1 5 CACCTG CGCTGCGACT - +4 predrem__nrMotif1308 -1 0.791664 19358.6 1 5 CACCTG CTCTGTGTCT - +4 predrem__nrMotif519 -1 0.791664 19358.6 1 5 CACCTG ATTTTTGCTT - +4 taipale_cyt_meth__OSR1_NGCTACYGTN_eDBD_meth-bowl-drm-odd-sob 5 0.791664 19358.6 1 5 CACCTG CACAGTAGCA - +4 transfac_pro__M05528 5 0.791664 19358.6 1 5 CACCTG ATCCCCAACC - +4 taipale__HOXA1_DBD_NNYAATTANN-abd-A-Antp-Awh-B-H1-B-H2-btn-C15-CG11085-CG18599-CG34367-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-NK7.1-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg- 6 0.791664 19358.6 1 4 CACCTG GGTAATTAAC + +4 taipale_cyt_meth__DMRTC2_GAACGATACA_FL_meth 6 0.791664 19358.6 1 4 CACCTG GAACGATACA + +4 cisbp__M5533-abd-A-al-Antp-Awh-B-H1-B-H2-btn-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-NK7.1-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg 6 0.791664 19358.6 1 4 CACCTG GGTAATTAAC - +4 hocomoco__DLX3_HUMAN.H11MO.0.C 6 0.791664 19358.6 1 4 CACCTG TGTAATTATC - +4 transfac_pro__M07421 -2 0.791664 19358.6 1 4 CACCTG ACTGTTATTC - +4 tfdimers__MD00530-cnc-maf-S 13 0.794101 19418.2 1 6 CACCTG GGCTTTGCTGAGCCATCTGTTCTTGTATGT + +4 transfac_public__M00380 24 0.794101 19418.2 1 6 CACCTG AAAAATTAACCCAAAATCCAACCTCACCCC + +4 tfdimers__MD00251 19 0.794101 19418.2 1 6 CACCTG TTATTAATAATTTTATGAGAACATAATATA - +4 tfdimers__MD00287-cnc-crp 14 0.794101 19418.2 1 6 CACCTG CCTTCAGCAGCTGTCATTTTGGCACCATCT - +4 transfac_pro__M05882 2 0.794579 19429.8 1 6 CACCTG CGGTCCATAAGA + +4 transfac_pro__M07690-maf-S-tj 3 0.794579 19429.8 1 6 CACCTG AAATTGCTGACG + +4 cisbp__M3451 3 0.794579 19429.8 1 6 CACCTG GTATTCCCAAAC - +4 cisbp__M6528-CG10431-lid-pho-phol-Taf1-Taf7 5 0.794579 19429.8 1 6 CACCTG GCCGCCATCTTG - +4 tiffin__TIFDMEM0000026 5 0.794579 19429.8 1 6 CACCTG AGAGTTGCCAGA - +4 transfac_pro__M00489-HGTX 6 0.794579 19429.8 1 6 CACCTG AATAATTATTTC - +4 transfac_pro__M01744-CG10431-lid-pho-phol-Taf1 6 0.794579 19429.8 1 6 CACCTG GGCAGCCATCTT - +4 transfac_pro__M05595-hb-her 0 0.794579 19429.8 1 6 CACCTG TACCATCGTCAT - +4 transfac_pro__M05617 1 0.794579 19429.8 1 6 CACCTG ATCCCCGGAACG - +4 transfac_pro__M06006 6 0.794579 19429.8 1 6 CACCTG GGGGCACGACTA - +4 transfac_pro__M06209 6 0.794579 19429.8 1 6 CACCTG TCCCATTTCATA - +4 transfac_pro__M06245 1 0.794579 19429.8 1 6 CACCTG ACGGCTTATTCG - +4 transfac_pro__M06297 6 0.794579 19429.8 1 6 CACCTG TATGCCCCCCAA - +4 transfac_pro__M06300 1 0.794579 19429.8 1 6 CACCTG GCAACATGCCAG - +4 transfac_pro__M06337 0 0.794579 19429.8 1 6 CACCTG GCCCTTCTCCAA - +4 transfac_pro__M06768 4 0.794579 19429.8 1 6 CACCTG GCTGCCCCATCA - +4 transfac_pro__M07722-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp1-slp2 6 0.794579 19429.8 1 6 CACCTG TTTGTTTATATA - +4 hocomoco__ZEP1_HUMAN.H11MO.0.D-Dif-Rel-dl-shn 7 0.794579 19429.8 1 5 CACCTG TGGGAAATCCCC + +4 homer__ATGACGTCATCN_JunD-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 7 0.794579 19429.8 1 5 CACCTG ATGACGTCATCA + +4 tiffin__TIFDMEM0000007 7 0.794579 19429.8 1 5 CACCTG GCACTGGGCACT + +4 transfac_pro__M06465 7 0.794579 19429.8 1 5 CACCTG TGGGAAAGACGT + +4 yetfasco__YOL028C_1737 7 0.794579 19429.8 1 5 CACCTG TATTAGTAAGCA + +4 cisbp__M6544-Dif-dl-Rel-shn 7 0.794579 19429.8 1 5 CACCTG TGGGAAATCCCC - +4 flyfactorsurvey__eve_FlyReg_FBgn0000606-eve 7 0.794579 19429.8 1 5 CACCTG AAATAATTAACG - +4 transfac_pro__M04630 -1 0.794579 19429.8 1 5 CACCTG TCTTTTATTTGA - +4 transfac_pro__M05488 7 0.794579 19429.8 1 5 CACCTG GCCCCATTAACA - +4 transfac_pro__M05692 7 0.794579 19429.8 1 5 CACCTG GATGCAGCACTA - +4 transfac_pro__M05771 7 0.794579 19429.8 1 5 CACCTG TCGTCTGTATCT - +4 transfac_pro__M05955 7 0.794579 19429.8 1 5 CACCTG TCGTCTGTATCT - +4 transfac_pro__M06210 7 0.794579 19429.8 1 5 CACCTG TCGTTAATCCCG - +4 transfac_pro__M06373 -1 0.794579 19429.8 1 5 CACCTG ACATTTGGCCCA - +4 transfac_pro__M06437 7 0.794579 19429.8 1 5 CACCTG TCATTTGCACGG - +4 transfac_pro__M06446 7 0.794579 19429.8 1 5 CACCTG TCTGGTTTAACA - +4 transfac_pro__M06625 7 0.794579 19429.8 1 5 CACCTG GCGTTTTGACTG - +4 neph__UW.Motif.0187 8 0.794579 19429.8 1 4 CACCTG GAGAAACTGGCC + +4 transfac_pro__M05721-CG2120 -2 0.794579 19429.8 1 4 CACCTG TCCGTCGAGAGA + +4 taipale_cyt_meth__CEBPG_NRTTGCGYAAYN_FL_meth-CG7786-gt-nej-Pdp1-slbo-srl -2 0.794579 19429.8 1 4 CACCTG CGTTACGCAACG - +4 transfac_pro__M01869 8 0.794579 19429.8 1 4 CACCTG GATTTCGCAATC - +4 transfac_pro__M06175 8 0.794579 19429.8 1 4 CACCTG TTTTTCGCCACA - +4 transfac_pro__M06186 8 0.794579 19429.8 1 4 CACCTG GGGGATGCCACT - +4 transfac_pro__M06321-CG12071-CG6654-CG7372 8 0.794579 19429.8 1 4 CACCTG GATTTTTTAACA - +4 transfac_pro__M06560-crol 8 0.794579 19429.8 1 4 CACCTG AATTCTTCAACA - +4 transfac_pro__M06580 8 0.794579 19429.8 1 4 CACCTG ATATTCGACACT - +4 transfac_pro__M06621 -2 0.794579 19429.8 1 4 CACCTG GCTTTTTGTCCG - +4 cisbp__M2310-Bgb-Bro-lz-run-RunxA-RunxB 2 0.795261 19446.5 1 6 CACCTG CAAACCACAAACCCC + +4 cisbp__M6133-CG9650-nej-nub-pdm2-SoxN-vvl 3 0.795261 19446.5 1 6 CACCTG ATTTGCATAACAATG + +4 cisbp__M6293-abd-A-Ubx 3 0.795261 19446.5 1 6 CACCTG TCCAATCTATTGATT + +4 factorbook__ZNF143-Hcf-Six4-egg 3 0.795261 19446.5 1 6 CACCTG CGGTGCATGCTGGGA + +4 taipale_cyt_meth__PAX7_NNATTMGTCACGSTN_eDBD-gsb-gsb-n-prd 8 0.795261 19446.5 1 6 CACCTG CGATTCGTCACGGTC + +4 transfac_pro__M09447 1 0.795261 19446.5 1 6 CACCTG AAATCTCCGGCGACG + +4 transfac_public__M00461-ovo-Poxn 5 0.795261 19446.5 1 6 CACCTG TATAGTAACAGTCAC + +4 cisbp__M4460-aop-Atac3-Eip74EF-Ets21C-Hcf-Hr78-RpII215-Sin3A-Taf1 1 0.795261 19446.5 1 6 CACCTG CCACTTCCGGGTTCG - +4 cisbp__M4471-ey-Poxm-sv-toy 8 0.795261 19446.5 1 6 CACCTG GTCACGCTTGGCTGC - +4 cisbp__M6313-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E-sv 0 0.795261 19446.5 1 6 CACCTG CAGTTTCAGTTTCTC - +4 flyfactorsurvey__CG7368_SOLEXA_2.5_FBgn0036179-CG7368-CTCF-CoRest-crol-ct-l(3)neo38 7 0.795261 19446.5 1 6 CACCTG CCCCCCCACCCCCTA - +4 flyfactorsurvey__vvl_SOLEXA_5_FBgn0086680-vvl 4 0.795261 19446.5 1 6 CACCTG GTGTTTTTTGCATAA - +4 hocomoco__ZIC4_HUMAN.H11MO.0.D-lmd-opa 0 0.795261 19446.5 1 6 CACCTG GACCCCCCGCTGTGC - +4 jaspar__MA0142.1-CG9650-SoxN-nej-nub-pdm2-vvl 3 0.795261 19446.5 1 6 CACCTG ATTTGCATAACAAAG - +4 taipale_cyt_meth__ZNF454_NRGCGCCNGGCGCYN_eDBD_meth-brk 3 0.795261 19446.5 1 6 CACCTG TGGCGCCAGGCGCCA - +4 taipale_tf_pairs__GCM1_ELK1_RTGCGGGCGGAAGTN_CAP_1-gcm-gcm2 0 0.795261 19446.5 1 6 CACCTG CACTTCCGCCCGCAT - +4 transfac_pro__M07124-Bgb-Bro-lz-run-RunxA-RunxB 2 0.795261 19446.5 1 6 CACCTG CAAACCACAAACCCC - +4 transfac_pro__M07370-CG10431-pho-phol-Taf1 2 0.795261 19446.5 1 6 CACCTG GCCGCCATTTTGGCA - +4 taipale_cyt_meth__IRF4_NYGAAASYGAAASYN_FL_meth_repr-Blimp-1-Stat92E 10 0.795261 19446.5 1 5 CACCTG ATGAAACTGAAACTA + +4 taipale__HNF1A_full_NRTTAATNATTAACN_repr 11 0.795261 19446.5 1 4 CACCTG AGTTAATGATTAACT + +4 transfac_pro__M07881-Rfx 11 0.795261 19446.5 1 4 CACCTG GTTGCCATTGGCAAC + +4 predrem__nrMotif225 0 0.796177 19468.9 1 6 CACCTG CTCTTTT + +4 swissregulon__hs__NANOG.p2-Antp-Dll-Dr-Scr-Ubx-bsh-en-inv 0 0.796177 19468.9 1 6 CACCTG TAATTGC + +4 cisbp__M0140 1 0.796177 19468.9 1 6 CACCTG ATTTTTG - +4 hdpi__C9orf156 -1 0.796177 19468.9 1 5 CACCTG GGCTGCG + +4 hdpi__ZBTB46 2 0.796177 19468.9 1 5 CACCTG AATTGCT + +4 jaspar__MA0339.1-klu-sr -1 0.796177 19468.9 1 5 CACCTG CCCCGCA + +4 predrem__nrMotif2413 -1 0.796177 19468.9 1 5 CACCTG GCCAATT + +4 cisbp__M0095 -1 0.796177 19468.9 1 5 CACCTG TCCTCGA - +4 predrem__nrMotif105 -1 0.796177 19468.9 1 5 CACCTG GGCTTTT - +4 predrem__nrMotif2340 2 0.796177 19468.9 1 5 CACCTG TAAGCCC - +4 predrem__nrMotif2656 2 0.796177 19468.9 1 5 CACCTG TGGATAT - +4 transfac_pro__M01924-klu-sr -1 0.796177 19468.9 1 5 CACCTG CCCCGCA - +4 cisbp__M6333-maf-S 3 0.796177 19468.9 1 4 CACCTG CATGACT + +4 elemento__ACACACG 3 0.796177 19468.9 1 4 CACCTG ACACACG + +4 elemento__AGTCACG 3 0.796177 19468.9 1 4 CACCTG AGTCACG + +4 elemento__CGTCACG 3 0.796177 19468.9 1 4 CACCTG CGTCACG + +4 elemento__CGTCATC-Jra 3 0.796177 19468.9 1 4 CACCTG CGTCATC + +4 elemento__GATCATC 3 0.796177 19468.9 1 4 CACCTG GATCATC + +4 elemento__TTGCACA 3 0.796177 19468.9 1 4 CACCTG TTGCACA + +4 elemento__CGTGCGC 3 0.796177 19468.9 1 4 CACCTG GCGCACG - +4 elemento__GATGAGC 3 0.796177 19468.9 1 4 CACCTG GCTCATC - +4 elemento__GATGGCC 3 0.796177 19468.9 1 4 CACCTG GGCCATC - +4 hdpi__DIS3-Dis3 -2 0.796177 19468.9 1 4 CACCTG CTTTTCC - +4 transfac_pro__M02089-E2f1 3 0.796177 19468.9 1 4 CACCTG CCCCGCC - +4 transfac_pro__M05152 3 0.796177 19468.9 1 4 CACCTG TTTTTCC - +4 cisbp__M5446-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-foxo-FoxP-slp1-slp2 4 0.796177 19468.9 1 3 CACCTG TGTTTAC - +4 taipale__FOXD2_DBD_RTAAAYA-bin-CHES-1-like-croc-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.796177 19468.9 1 3 CACCTG TGTTTAC - +4 cisbp__M0081 2 0.796261 19471 1 6 CACCTG GCAACATA + +4 cisbp__M0117 1 0.796261 19471 1 6 CACCTG TTTAATTA + +4 cisbp__M0959-ap-Awh-CG11085-CG18599-CG32532-CG34367-E5-ems-en-ind-inv-lab-Lim3-otp-repo-ro-Rx-slou-unpg-Vsx2 0 0.796261 19471 1 6 CACCTG TAATTAGC + +4 cisbp__M1020-al-C15-CG15696-CG32532-CG34367-CG9876-Dll-Dr-en-inv-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-Traf4-unc-4-unpg-Vsx1-Vsx2 1 0.796261 19471 1 6 CACCTG TTAATTGG + +4 cisbp__M5719-bcd-Gsc-oc-Ptx1 2 0.796261 19471 1 6 CACCTG TTAATCCC + +4 cisbp__M5754-al-ap-Awh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-en-exex-ey-hbn-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-toy-Traf4-U 1 0.796261 19471 1 6 CACCTG TTAATTAG + +4 cisbp__M5807-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ind-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.796261 19471 1 6 CACCTG TTAATTGG + +4 cisbp__M5949-ap-Awh-CG18599-CG9876-Dfd-E5-ems-ind-Lim3-OdsH-otp-Pph13-ro-Rx-unpg 1 0.796261 19471 1 6 CACCTG CTAATTAT + +4 cisbp__M6001-Dll-HGTX 1 0.796261 19471 1 6 CACCTG TTAATTGC + +4 predrem__nrMotif1161 0 0.796261 19471 1 6 CACCTG AAGCAGTC + +4 taipale__DLX4_DBD_NYAATTAN-Dll-Dr 1 0.796261 19471 1 6 CACCTG CCAATTAC + +4 taipale__PITX1_full_NTAATCCN-bcd-Gsc-oc-Ptx1 2 0.796261 19471 1 6 CACCTG TTAATCCC + +4 taipale__SHOX_DBD_NYAATTAN-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7. 1 0.796261 19471 1 6 CACCTG CTAATTAA + +4 taipale__Shox2_DBD_NYAATTAN-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ey-ind-inv-lab-lbe-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-repo-Rx-slou-toy-Traf4-Ubx-un 1 0.796261 19471 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__HOXB8_RTCGTTAN_eDBD_meth-abd-A-btn-Dll-Ubx 0 0.796261 19471 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__HOXC4_RTCGTTAN_FL_meth-abd-A-Antp-btn-Dfd-Dll-eve-exex-ind-lab-pb-Scr-Ubx 0 0.796261 19471 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__LMX1B_YTCGTTAW_eDBD_meth-CG4328-Lim3-Lmx1a-Vsx1-Vsx2 0 0.796261 19471 1 6 CACCTG CTCGTTAA + +4 transfac_pro__M07774-B-H1-B-H2-CG11085 2 0.796261 19471 1 6 CACCTG CTAAACGG + +4 transfac_pro__M08895-Ptx1 2 0.796261 19471 1 6 CACCTG TAATCCCT + +4 cisbp__M0111-retn 1 0.796261 19471 1 6 CACCTG TAATCAAA - +4 cisbp__M1005-al-ap-Awh-B-H2-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-E5-en-hbn-ind-inv-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-Traf4-tup-unc-4-unpg-V 1 0.796261 19471 1 6 CACCTG CCAATTAA - +4 cisbp__M1304 1 0.796261 19471 1 6 CACCTG TGCCCTAG - +4 cisbp__M1316 1 0.796261 19471 1 6 CACCTG TGCCCTAG - +4 cisbp__M1746 2 0.796261 19471 1 6 CACCTG TGCGCCTA - +4 cisbp__M5942-al-Antp-ap-Awh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm3-Pph13-prd-repo- 1 0.796261 19471 1 6 CACCTG CTAATTAA - +4 cisbp__M6082-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ind-inv-lab-lbe-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-repo-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.796261 19471 1 6 CACCTG CTAATTAA - +4 hdpi__NMI 0 0.796261 19471 1 6 CACCTG GATTTGCA - +4 taipale__Dlx2_DBD_NYAATTAN-Dll-HGTX 1 0.796261 19471 1 6 CACCTG TTAATTGC - +4 taipale__VSX1_DBD_YTAATTAN-ap-Awh-CG18599-CG9876-Dfd-E5-ems-eve-ind-Lim3-OdsH-otp-Pph13-ro-Rx-unpg 1 0.796261 19471 1 6 CACCTG ATAATTAG - +4 taipale_cyt_meth__HESX1_CTAATTAN_FL-CG4328-HGTX-lbe-lbl-Lmx1a 1 0.796261 19471 1 6 CACCTG TTAATTAG - +4 cisbp__M0350 3 0.796261 19471 1 5 CACCTG ATTTATTT + +4 predrem__nrMotif1808 3 0.796261 19471 1 5 CACCTG CCATAAAT + +4 transfac_pro__M01117-oc 3 0.796261 19471 1 5 CACCTG GATTAATT + +4 transfac_public__M00500-Stat92E -1 0.796261 19471 1 5 CACCTG GACTTCCT + +4 cisbp__M0448-ovo -1 0.796261 19471 1 5 CACCTG ACCGTTAT - +4 cisbp__M3992-Stat92E -1 0.796261 19471 1 5 CACCTG GACTTCCT - +4 hdpi__SNAPC5 3 0.796261 19471 1 5 CACCTG GTTTCCAT - +4 hocomoco__OVOL2_HUMAN.H11MO.0.D-ovo -1 0.796261 19471 1 5 CACCTG TCCGTTAT - +4 neph__UW.Motif.0071 3 0.796261 19471 1 5 CACCTG TTTCCCCA - +4 transfac_pro__M03873 3 0.796261 19471 1 5 CACCTG CATAAAAT - +4 flyfactorsurvey__CG11617_Cell_FBgn0031232-CG11617 4 0.796261 19471 1 4 CACCTG TTTTAACA + +4 jaspar__MA1052.1-Hcf 4 0.796261 19471 1 4 CACCTG GCGCCGCC + +4 transfac_pro__M05532-CTCF 4 0.796261 19471 1 4 CACCTG GTTACGCC + +4 flyfactorsurvey__onecut_SOLEXA_FBgn0028996-onecut 4 0.796261 19471 1 4 CACCTG TAATCAAA - +4 predrem__nrMotif1035 4 0.796261 19471 1 4 CACCTG AGGACTCC - +4 predrem__nrMotif44 4 0.796261 19471 1 4 CACCTG ACTCCCCC - +4 cisbp__M0962-Awh-en-inv-lab-Lim3-Ubx 5 0.796261 19471 1 3 CACCTG CTAATCAA + +4 transfac_pro__M07848-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-en-inv-lab-Lim1-Lim3-pb-Scr-Ubx-unpg 5 0.796261 19471 1 3 CACCTG GCAATTAC + +4 cisbp__M0864-Ubx-abd-A-cad 5 0.796261 19471 1 3 CACCTG TTTATTAC - +4 jaspar__MA0924.1-Ubx-abd-A-cad 5 0.796261 19471 1 3 CACCTG TTTATTAC - +4 taipale_cyt_meth__ZSCAN31_GCATAACKGCCCTGCKKCN_FL 8 0.796395 19474.2 1 6 CACCTG GCATAACTGCCCTGCGTCC + +4 cisbp__M3359 13 0.796395 19474.2 1 6 CACCTG CAAGAACACAGTGTACCCA - +4 hocomoco__KLF3_HUMAN.H11MO.0.B-Brf-CG3065-CG42741-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Nf-YA-Nf-YB-Rbbp5-SREBP-Sp1-Spps-Spt20-brm-btd-ct-dar1-kay-klu-luna-sr-vtd 9 0.796395 19474.2 1 6 CACCTG CCCGGCCCCGCCCCTCCCC - +4 hocomoco__PAX5_MOUSE.H11MO.0.A-Poxm-ey-sv-toy 8 0.796395 19474.2 1 6 CACCTG GTCACGCTTGGCTGCCCTC - +4 hocomoco__ZBT17_MOUSE.H11MO.0.A-Brf-CTCF-CoRest-E(z)-HDAC1-Klf15-Nelf-E-Rbbp5-SREBP-Spps-Spt20-brm-btd-ct-kay-klu-sr 9 0.796395 19474.2 1 6 CACCTG CCGCCCCTCCCCCACCCCC - +4 transfac_pro__M01070-maf-S-tj 0 0.796395 19474.2 1 6 CACCTG TAGCCGCGTCAGCAAAATC - +4 transfac_pro__M09022-lid-pho-phol-RpII215-Taf1 12 0.796395 19474.2 1 6 CACCTG CGCCGCCGCCATTTCCGCC - +4 taipale_tf_pairs__GCM1_PITX1_GGATTANNNNNNNTGCGGG_CAP_repr-gcm-gcm2-Ptx1 -2 0.796395 19474.2 1 4 CACCTG CCCGCATGCACCCTAATCC - +4 cisbp__M5584-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-E5-ems-en-ey-hbn-Lim3-OdsH-Optix-otp-Pph13-repo-ro-Rx-Traf4-unc-4-unpg-Vsx1-Vsx2 2 0.797406 19499 1 6 CACCTG TTAATCTAATTAA + +4 flyfactorsurvey__sob_SANGER_10_FBgn0004892-sob 2 0.797406 19499 1 6 CACCTG GCTACTGTGTTTC + +4 taipale__ISX_DBD_NTAATYTAATTAN_repr-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-E5-ems-en-ey-hbn-Lim3-OdsH-Optix-otp-Pph13-repo-ro-Rx-Traf4-unc-4-unpg-Vsx1-Vsx2 2 0.797406 19499 1 6 CACCTG TTAATCTAATTAA + +4 taipale_cyt_meth__KLF13_NRCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.797406 19499 1 6 CACCTG CGCCACGCCCCCC + +4 transfac_pro__M00623 0 0.797406 19499 1 6 CACCTG TTACTAATCCCAC + +4 transfac_pro__M05899 7 0.797406 19499 1 6 CACCTG TTGAAAGCGTCTG + +4 cisbp__M5941-al-bsh-C15-CG11294-CG32532-CG34367-CG9876-Drgx-eve-ey-Lim3-OdsH-Optix-PHDP-repo-Rx-Traf4-unc-4 5 0.797406 19499 1 6 CACCTG CTAATTAAATTAG - +4 jaspar__MA0507.1-nub-pdm2-vvl 5 0.797406 19499 1 6 CACCTG ATATGCAAATGAA - +4 neph__UW.Motif.0228 5 0.797406 19499 1 6 CACCTG TGTCTGGCTTCTG - +4 taipale__PRDM4_full_TTTCAAGGCYCCC_repr 3 0.797406 19499 1 6 CACCTG GGGGGCCTTGAAA - +4 taipale_cyt_meth__NRL_NWWWNTGCTGACN_eDBD_meth-maf-S-tj 3 0.797406 19499 1 6 CACCTG CGTCAGCACATTT - +4 taipale_tf_pairs__ETV2_DRGX_RSCGGAWRYATTA_CAP_repr-CG11294-Drgx-pnt 6 0.797406 19499 1 6 CACCTG TAATACTTCCGGT - +4 transfac_pro__M00641-Hsf 2 0.797406 19499 1 6 CACCTG GAAACCTCTGGAA - +4 transfac_pro__M08180-Mef2 1 0.797406 19499 1 6 CACCTG TTTCCTTTTTTGG - +4 transfac_pro__M05592 9 0.797406 19499 1 4 CACCTG GATTCGTCACACA - +4 cisbp__M2352 2 0.797513 19501.6 1 6 CACCTG TTTTCCTTTTTTGG + +4 swissregulon__sacCer__MIG1-klu-sr 1 0.797513 19501.6 1 6 CACCTG TCCCCCGCATTTTT + +4 taipale_cyt_meth__MAF_NYGCTGACNNNGCR_FL_meth_repr-maf-S-tj 5 0.797513 19501.6 1 6 CACCTG TTGCTGACTCTGCA + +4 transfac_pro__M00650-MTF-1 4 0.797513 19501.6 1 6 CACCTG TTTGCACACGGCCC + +4 transfac_pro__M04758-Mef2-rump 0 0.797513 19501.6 1 6 CACCTG TTGCTATTTTTAGC + +4 transfac_public__M00268-croc-fkh 6 0.797513 19501.6 1 6 CACCTG ATTATAAACATTGA + +4 cisbp__M5393-bs-bsh-CG34367-CG9876-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg-Vsx2 8 0.797513 19501.6 1 6 CACCTG TAATTGCTTAATTA - +4 jaspar__MA0559.1 2 0.797513 19501.6 1 6 CACCTG TTTTCCTTTTTTGG - +4 neph__UW.Motif.0683 1 0.797513 19501.6 1 6 CACCTG TGCCGGCATTTCTG - +4 transfac_pro__M03865-Blimp-1 8 0.797513 19501.6 1 6 CACCTG CCTTTCACTTTCTC - +4 transfac_pro__M07458-abd-A-Antp-Dbx-Scr-Ubx 2 0.797513 19501.6 1 6 CACCTG ACCACTTTAATGAG - +4 transfac_public__M00190 0 0.797513 19501.6 1 6 CACCTG TAATTATGCAATGT - +4 transfac_pro__M09445 9 0.797513 19501.6 1 5 CACCTG TAACGCCGTTAACT - +4 transfac_pro__M04837-Mad-nej-pan-Sox100B-Sox102F-Sox14-SoxN -2 0.797513 19501.6 1 4 CACCTG CCTTTGTTTTGCAA - +4 taipale__FOXJ3_DBD_RTAAACARTAAACA-croc-fd59A-foxo-FoxP-slp2 11 0.797513 19501.6 1 3 CACCTG TGTTTATTGTTTAC - +4 tfdimers__MD00244-Hsf 18 0.797684 19505.8 1 6 CACCTG AATAAAAAGAACAGAAGGTTCCCATTAAA + +4 taipale_tf_pairs__ELK1_EOMES_RGGTGNGANNNNNNNNTNNCACCGGAAGY_CAP 24 0.797684 19505.8 1 5 CACCTG ACTTCCGGTGTCACCCTACCCTCACACCT - +4 taipale_cyt_meth__POU3F1_TAATTNNNNNNNAATTA_eDBD_meth-vvl 4 0.799054 19539.3 1 6 CACCTG TAATTACCCGTTAATTA + +4 transfac_pro__M02846-E2f1-E2f2 10 0.799054 19539.3 1 6 CACCTG CGTTCGGCGCCAAAAGG + +4 transfac_pro__M02931-CG12071 9 0.799054 19539.3 1 6 CACCTG GTGGTTCAATAATTTTG + +4 cisbp__M6046-cnc-maf-S-nej-tj 1 0.799054 19539.3 1 6 CACCTG AATGCTGACTCAGCACA - +4 cisbp__M6484-CG9650-Dif-dl-ebi-Ets96B-MTA1-like-nej-Stat92E-sv 3 0.799054 19539.3 1 6 CACCTG TTTCACTTCCTCTTTTT - +4 taipale_tf_pairs__FLI1_CEBPB_RNCGGANNTTGCGCAAN_CAP 10 0.799054 19539.3 1 6 CACCTG ATTGCGCAACTTCCGGT - +4 taipale_tf_pairs__HOXD12_ELK1_NRSCGGAAGNNGTAAAN_CAP_repr 6 0.799054 19539.3 1 6 CACCTG TTTTACGACTTCCGCCC - +4 transfac_pro__M01325-al-Awh-C15-CG11085-CG9876-E5-ems-en-eve-inv-Lim3-otp-pdm3-ro-slou-vvl-zfh2 2 0.799054 19539.3 1 6 CACCTG GTTCACTAATTAGTTTA - +4 transfac_pro__M01335-abd-A-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG4328-CG9876-Dbx-Dfd-E5-gsb-gsb-n-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-prd-repo-ro-Rx-Scr-Ubx-unc-4-unpg-Vsx1-zfh2 10 0.799054 19539.3 1 6 CACCTG AATTATTAATTAACTCG - +4 dbcorrdb__BATF__ENCSR000BGT_1__m1-ebi-foxo-Jra-MTA1-like-nej-NFAT-Stat92E 14 0.800442 19573.2 1 6 CACCTG ATGAGTCATATCGAAACTAA + +4 dbcorrdb__BCL3__ENCSR000BKG_1__m2 14 0.800442 19573.2 1 6 CACCTG CAATAGACAAACCGCACCCA + +4 dbcorrdb__BCL3__ENCSR000BQH_1__m2-Jra-kay-mor 6 0.800442 19573.2 1 6 CACCTG ATGAGTCATCGCGTAACAAT + +4 dbcorrdb__CEBPB__ENCSR000EFM_1__m1-CG7786-gt-Irbp18-Jra-nej-Pdp1-slbo-Xrp1 11 0.800442 19573.2 1 6 CACCTG AATTATTGCATAATATTTTT + +4 dbcorrdb__CTCF__ENCSR000DQI_1__m2-CTCF-vtd 0 0.800442 19573.2 1 6 CACCTG TGCGTGGGGCTATAGTGCCC + +4 dbcorrdb__CTCF__ENCSR000DSZ_1__m2-CTCF-vtd 0 0.800442 19573.2 1 6 CACCTG TGCGTGGGGCTATAGTGCCC + +4 dbcorrdb__CTCF__ENCSR000DTI_1__m2-CTCF-SMC3-vtd 3 0.800442 19573.2 1 6 CACCTG GGCCATATGGGGAACTGCAG + +4 dbcorrdb__GATA2__ENCSR000EVW_1__m3-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 12 0.800442 19573.2 1 6 CACCTG TAGAGTATGACTCATTGCTT + +4 dbcorrdb__HDAC6__ENCSR000ATJ_1__m2-HDAC6 10 0.800442 19573.2 1 6 CACCTG CGCAGCGCGCAGCCAGCACG + +4 dbcorrdb__HDAC6__ENCSR000ATJ_1__m4-HDAC6 10 0.800442 19573.2 1 6 CACCTG CCGCGGGCAGCGCAAGCGCC + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m7-Nelf-E 2 0.800442 19573.2 1 6 CACCTG TTTTCCTCGGCGCGTTCCGC + +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m12-RpII215 10 0.800442 19573.2 1 6 CACCTG GCGCGCCTTTTGCCTGCTCG + +4 dbcorrdb__POLR2A__ENCSR000DLQ_1__m2-brm-ERR-E(z)-RpII215-SREBP-tna 7 0.800442 19573.2 1 6 CACCTG GCCCGCGCCGCTGCCGCCGC + +4 dbcorrdb__RCOR1__ENCSR000EFG_1__m3-CoRest 5 0.800442 19573.2 1 6 CACCTG GCGCCAGCCTGAGTCATGAT + +4 dbcorrdb__ZBTB7A__ENCSR000BME_1__m1-Brf-brm-btd-CTCF-ERR-E(z)-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-SREBP-tna-vtd 13 0.800442 19573.2 1 6 CACCTG GGGGCCCCGGCGACCCCTGC + +4 dbcorrdb__ZNF274__ENCSR000EUK_1__m2 2 0.800442 19573.2 1 6 CACCTG GAAACCCTATGAATGCAATG + +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m5-bon 4 0.800442 19573.2 1 6 CACCTG TTCCCACATTCATTACATTC + +4 dbcorrdb__ZNF384__ENCSR000EFP_1__m2-rn-sqz 10 0.800442 19573.2 1 6 CACCTG CACTGCACTCCAGCCTGGAA + +4 hocomoco__ZN317_HUMAN.H11MO.0.C 6 0.800442 19573.2 1 6 CACCTG GAATGACAGCTGACTTCTCA + +4 dbcorrdb__ARID3A__ENCSR000EDP_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-GATAe-grn-HDAC1-nej-pnr 5 0.800442 19573.2 1 6 CACCTG CTTAATCAATGTTTACTTAG - +4 dbcorrdb__CEBPB__ENCSR000EEE_1__m1-Irbp18-nej-slbo-Xrp1 13 0.800442 19573.2 1 6 CACCTG GCAATTATTGCACAATATCT - +4 dbcorrdb__CHD1__ENCSR000EFC_1__m7-Chd1 14 0.800442 19573.2 1 6 CACCTG GAAGGCGGAACCGCCACGCG - +4 dbcorrdb__EZH2__ENCSR000ASW_1__m2-E(z) 3 0.800442 19573.2 1 6 CACCTG TGGACCCTGCGCCGCCGGCC - +4 dbcorrdb__FOSL2__ENCSR000BQO_1__m1-cnc-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 12 0.800442 19573.2 1 6 CACCTG TAAAGAATGACTCAGCCTTA - +4 dbcorrdb__FOS__ENCSR000DOP_1__m1-cnc-GATAe-grn-Jra-kay-maf-S-Mef2-mor-Myc-nej-pnr-Stat92E 12 0.800442 19573.2 1 6 CACCTG TAAAGGATGACTCATCCTTT - +4 dbcorrdb__NFYA__ENCSR000DNS_1__m2-btd-dar1-E2f2-kay-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 12 0.800442 19573.2 1 6 CACCTG CTAGGTCCCGCCCCCTGCCG - +4 dbcorrdb__NRF1__ENCSR000EHZ_1__m1-E2f1-ewg-E(z)-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG3388 5 0.800442 19573.2 1 6 CACCTG CGCTGCGCATGCGCAGGGGG - +4 dbcorrdb__PML__ENCSR000BQM_1__m1-aop-Atac3-Dif-dl-Eip74EF-Ets96B-Ets97D-Hcf-HDAC6-lid-pnt-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha 12 0.800442 19573.2 1 6 CACCTG CGGCGCTTCCGCCTCGCGCG - +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m4-RpII215 4 0.800442 19573.2 1 6 CACCTG CGCTTTTCTGTTGGTCGCCG - +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m1-RpII215 10 0.800442 19573.2 1 6 CACCTG CCGCCCTTTCCACGCCCTGA - +4 dbcorrdb__POLR2A__ENCSR000EFK_1__m1-CG10431-lid-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 10 0.800442 19573.2 1 6 CACCTG CCGCCGCCGCCATGTTCGGG - +4 dbcorrdb__POLR2A__ENCSR000EFK_1__m2-RpII215 6 0.800442 19573.2 1 6 CACCTG TGTTGCTTCTTCCGCTATTG - +4 dbcorrdb__POLR2A__ENCSR000EZA_1__m2-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 5 0.800442 19573.2 1 6 CACCTG CGCGGCGGCTGATATAGCCG - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EDX_1__m1-RpII215 7 0.800442 19573.2 1 6 CACCTG CTTTCGTTCGCTGTTTGGAC - +4 dbcorrdb__POLR3A__ENCSR000DOI_1__m5-CG17209 14 0.800442 19573.2 1 6 CACCTG AGCGCACGTCGGTTTAGCTC - +4 dbcorrdb__RELA__ENCSR000EBA_1__m2-Dif-dl 9 0.800442 19573.2 1 6 CACCTG ACAAAAGTGAAACTGCCAGG - +4 dbcorrdb__RFX5__ENCSR000DZW_1__m2-btd-CG7839-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 0 0.800442 19573.2 1 6 CACCTG CCTCTGATTGGCTGGGGCGG - +4 dbcorrdb__TBP__ENCSR000EEL_1__m1-Tbp 12 0.800442 19573.2 1 6 CACCTG AGGCGAGCGCGCTACCGCTG - +4 dbcorrdb__TCF12__ENCSR000BQQ_1__m2-cnc-Jra-kay-Myc-nej-Stat92E 9 0.800442 19573.2 1 6 CACCTG ATGATGAGTCATTGATTAAT - +4 dbcorrdb__ZNF263__ENCSR000EVD_1__m1-Brf-brm-btd-CoRest-ct-CTCF-E(z)-HDAC1-Nelf-E-Rbbp5-Spps-Spt20-SREBP-vtd 7 0.800442 19573.2 1 6 CACCTG TCCGTCCTCCCTCCCCCCCC - +4 dbcorrdb__ZNF274__ENCSR000EWE_1__m1-egg 2 0.800442 19573.2 1 6 CACCTG CTCTCCAGTATGAGTTCTCT - +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m3-bon-egg 12 0.800442 19573.2 1 6 CACCTG CATAGGGTTTCTCTCCAGTA - +4 hocomoco__ZN549_HUMAN.H11MO.0.C 11 0.800442 19573.2 1 6 CACCTG GTGCTGCCCAATTCATGAAT - +4 taipale_tf_pairs__ETV2_DLX3_RSCGGAANNNNNNNTAATKR_CAP_repr-pnt 4 0.800442 19573.2 1 6 CACCTG TAATTAACGCCACTTCCGGT - +4 taipale_tf_pairs__POU2F1_DLX2_TGMATATKCANNNNTAATKR_CAP_repr-nub-pdm2 4 0.800442 19573.2 1 6 CACCTG CAATTAAGTGTGCATATTCA - +4 dbcorrdb__EZH2__ENCSR000ATA_1__m2-E(z) -1 0.800442 19573.2 1 5 CACCTG ACCCGGCCATTCGGCGGCAC - +4 taipale_cyt_meth__PAX8_NSGTCRCGCWTSANYGNNYN_FL_meth-ey-Poxm-sv-toy 15 0.800442 19573.2 1 5 CACCTG TGTTCGGTCAAGCGTGACCA - +4 dbcorrdb__CTCF__ENCSR000DPY_1__m2-CTCF-SMC3-vtd 16 0.800442 19573.2 1 4 CACCTG CTGCAGTTCCCCATATGGCC - +4 tfdimers__MD00326 3 0.80071 19579.8 1 6 CACCTG TTTTTCCTTTCCTAATCCCTTTTCATTT - +4 hdpi__EXOSC3-Rrp40 0 0.801363 19595.7 1 5 CACCTG TTCCA - +4 transfac_public__M00029 0 0.801363 19595.7 1 5 CACCTG GTTCT - +4 tiffin__TIFDMEM0000114 2 0.802051 19612.5 1 6 CACCTG ACTTACTTAAA + +4 transfac_pro__M05358 5 0.802051 19612.5 1 6 CACCTG GCATCAACATT + +4 transfac_pro__M07781-al-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-E5-ems-hbn-OdsH-Optix-otp-repo-Rx-Traf4-unc-4 1 0.802051 19612.5 1 6 CACCTG TAATCTAATTA + +4 transfac_pro__M08928-kay 5 0.802051 19612.5 1 6 CACCTG TATGACTCATA + +4 transfac_pro__M09450 1 0.802051 19612.5 1 6 CACCTG TCGCCGGAAAA + +4 c2h2_zfs__M3984-erm 4 0.802051 19612.5 1 6 CACCTG GTTGCGCATTT - +4 cisbp__M1670 1 0.802051 19612.5 1 6 CACCTG TAGCCGGCAGG - +4 hocomoco__LHX4_HUMAN.H11MO.0.D-Awh-C15-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-ems-en-ey-inv-lab-lbe-lms-nub-otp-pdm2-repo-ro-slou-toy-unc-4-u 5 0.802051 19612.5 1 6 CACCTG CTAATTAACTT - +4 jaspar__MA0467.1-bcd-oc 5 0.802051 19612.5 1 6 CACCTG CTAATCCTCTT - +4 neph__UW.Motif.0103 4 0.802051 19612.5 1 6 CACCTG TGTTTTTCTCA - +4 taipale_cyt_meth__POU2F3_NTATGCWAATN_eDBD_repr-nub-pdm2 3 0.802051 19612.5 1 6 CACCTG CATTAGCATAC - +4 transfac_pro__M05479 2 0.802051 19612.5 1 6 CACCTG CACACCGCCCA - +4 cisbp__M2285-sens-sens-2 -1 0.802051 19612.5 1 5 CACCTG TGCTGTGATTT + +4 predrem__nrMotif2451 6 0.802051 19612.5 1 5 CACCTG CCCCCGCAGCC + +4 cisbp__M5537 -2 0.802051 19612.5 1 4 CACCTG TCTCGTAAAAA + +4 taipale_cyt_meth__HOXD13_NCTCGTAAAAN_eDBD -2 0.802051 19612.5 1 4 CACCTG GCTCGTAAAAC + +4 transfac_pro__M06845 7 0.802051 19612.5 1 4 CACCTG CTCGATGCAAC + +4 hocomoco__FOSL2_MOUSE.H11MO.0.A-CoRest-Jra-Mef2-Myc-Snr1-bon-cnc-kay-mor-nej-pan 7 0.802051 19612.5 1 4 CACCTG GATGAGTCACC - +4 taipale_cyt_meth__HOXA10_NGTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.802051 19612.5 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M04980 8 0.802051 19612.5 1 3 CACCTG AACTGCGTTAC - +4 transfac_pro__M05073 8 0.802051 19612.5 1 3 CACCTG AACGCCGTTAC - +4 transfac_pro__M05075 8 0.802051 19612.5 1 3 CACCTG CACGCCGTTAC - +4 transfac_pro__M05081 8 0.802051 19612.5 1 3 CACCTG GGAATTCATAC - +4 cisbp__M4917-abd-A-al-Antp-ap-Awh-bsh-btn-C15-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-hbn-HGTX-ind-inv-lab-lbe-Lim1-lms-Lmx1a-OdsH-otp-pb-repo-Rx-Scr-slou-Ubx-unc-4-unp 0 0.802189 19615.9 1 6 CACCTG TAATTA + +4 flyfactorsurvey__Dll_SOLEXA_FBgn0000157-Antp-Awh-C15-CG4328-CG9876-CG18599-CG32532-CG34367-Dfd-Dll-Dr-E5-HGTX-Lim1-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-ems-en-eve-exex-ftz-hbn-ind 0 0.802189 19615.9 1 6 CACCTG TAATTA + +4 transfac_pro__M02027-Parp 0 0.802189 19615.9 1 6 CACCTG TTTCTT + +4 cisbp__M5042-hth 2 0.802189 19615.9 1 4 CACCTG TTGACA + +4 transfac_pro__M00801-CrebB 2 0.802189 19615.9 1 4 CACCTG ATGACG - +4 jaspar__MA0252.1-achi-hth-vis -3 0.802189 19615.9 1 3 CACCTG CTGTCA - +4 cisbp__M4741-ap 4 0.802189 19615.9 1 2 CACCTG TAATAA + +4 flyfactorsurvey__ap_FlyReg_FBgn0000099-ap 4 0.802189 19615.9 1 2 CACCTG TAATTA + +4 hdpi__ACF-Syp 4 0.802189 19615.9 1 2 CACCTG TTTGCA + +4 tfdimers__MD00522 13 0.803156 19639.6 1 6 CACCTG TTTATCCTCCCAAATCCTGTTTACTCT - +4 cisbp__M1054-Antp-bsh-btn-C15-CG11085-Dll-Dr-eve-lab-Scr-Ubx 1 0.803366 19644.7 1 6 CACCTG TTAATGGGT + +4 cisbp__M2358 1 0.803366 19644.7 1 6 CACCTG GCGCATGCG + +4 predrem__nrMotif1602 3 0.803366 19644.7 1 6 CACCTG TCTCAGCAT + +4 predrem__nrMotif2642 3 0.803366 19644.7 1 6 CACCTG GTCTTCCAG + +4 swissregulon__hs__SOX17.p2-Sox15 0 0.803366 19644.7 1 6 CACCTG CTCATTGTC + +4 transfac_pro__M01216-foxo-slp2 3 0.803366 19644.7 1 6 CACCTG AAAAACAAA + +4 transfac_pro__M02028 3 0.803366 19644.7 1 6 CACCTG ATCAATCAA + +4 transfac_pro__M04770-pho-phol-Taf1 3 0.803366 19644.7 1 6 CACCTG CGCCATCTT + +4 cisbp__M0921-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-gsb-gsb-n-HGTX-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph 1 0.803366 19644.7 1 6 CACCTG GGTAATTAA - +4 cisbp__M1011-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-C15-cad-CG18599-CG32532-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-HGTX-ind-lab-Lim1-lms-NK7.1-otp-pb-Pph13-repo-ro-Rx-Scr-slou-tup-Ubx-unpg-Vsx1-zen2 1 0.803366 19644.7 1 6 CACCTG GGTAATTAA - +4 cisbp__M1083-al-Antp-ap-Awh-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-Drgx-dve-E5-ems-en-eve-ey-gsb-gsb-n-hbn-ind-inv-lab-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pdm3 1 0.803366 19644.7 1 6 CACCTG CTAATTAAT - +4 hocomoco__PDX1_HUMAN.H11MO.0.A 0 0.803366 19644.7 1 6 CACCTG CATCAATCA - +4 jaspar__MA0565.1 1 0.803366 19644.7 1 6 CACCTG GCGCATGCG - +4 predrem__nrMotif895 2 0.803366 19644.7 1 6 CACCTG GGAGCCTGC - +4 predrem__nrMotif960 2 0.803366 19644.7 1 6 CACCTG CCAACATTT - +4 stark__KHGATAASR-GATAd-GATAe-grn-pnr-srp 3 0.803366 19644.7 1 6 CACCTG CCTTATCTA - +4 taipale__Hoxd9_DBD_GTCGTAAAN-Abd-B-cad 3 0.803366 19644.7 1 6 CACCTG TTTTACGAC - +4 predrem__nrMotif1558 4 0.803366 19644.7 1 5 CACCTG CCAAGACTT + +4 predrem__nrMotif2219 -1 0.803366 19644.7 1 5 CACCTG ATCTTGAGA + +4 predrem__nrMotif2398 4 0.803366 19644.7 1 5 CACCTG CTGCCCCCG + +4 taipale_cyt_meth__LEF1_ASATCAAAS_eDBD_meth-pan -1 0.803366 19644.7 1 5 CACCTG ACATCAAAG + +4 taipale_cyt_meth__TCF7_ASATCAAAS_eDBD_meth-pan -1 0.803366 19644.7 1 5 CACCTG ACATCAAAG + +4 cisbp__M0103 4 0.803366 19644.7 1 5 CACCTG TAATTAAAA - +4 flyfactorsurvey__cad_FlyReg_FBgn0000251-cad -1 0.803366 19644.7 1 5 CACCTG ATCATAAAG - +4 predrem__nrMotif766 -1 0.803366 19644.7 1 5 CACCTG CCCGGGCGC - +4 predrem__nrMotif921 4 0.803366 19644.7 1 5 CACCTG GAATGGCCT - +4 cisbp__M1262 5 0.803366 19644.7 1 4 CACCTG ATCGAAACT + +4 predrem__nrMotif452 -2 0.803366 19644.7 1 4 CACCTG TCTGTCTGT + +4 predrem__nrMotif1797 5 0.803366 19644.7 1 4 CACCTG TTAAAGAAC - +4 predrem__nrMotif813 5 0.803366 19644.7 1 4 CACCTG GGAGCAGCC - +4 swissregulon__sacCer__MGA1 6 0.803366 19644.7 1 3 CACCTG ATAGAACAC + +4 cisbp__M2544-Cf2 6 0.803366 19644.7 1 3 CACCTG TATATATAC - +4 factorbook__ZNF143-ext-Hcf-Six4-Stat92E-bi-egg-mor 4 0.803387 19645.2 1 6 CACCTG GAACTACAATTCCCAGAAGGC + +4 jaspar__MA0345.1-Tbp 2 0.803387 19645.2 1 6 CACCTG ATGACCTATATATAAAAATGA + +4 taipale_tf_pairs__TEAD4_ERG_RSCGGAANNNNNNNNCATWCC_CAP_repr-Ets97D-sd 8 0.803387 19645.2 1 6 CACCTG ACCGGAAATGCATGACATTCC + +4 transfac_pro__M01532-Tbp 2 0.803387 19645.2 1 6 CACCTG ATGACCTATATATAAAAATGA + +4 transfac_pro__M01551 15 0.803387 19645.2 1 6 CACCTG TATAAGAGCGCGCGCTCTGTG + +4 transfac_pro__M09121-brm-CG7839-maf-S-orb-SREBP-vtd 6 0.803387 19645.2 1 6 CACCTG TTTTTTTTACTTTTTCTTTTT - +4 yetfasco__YLR403W_797-CG12054 15 0.803387 19645.2 1 6 CACCTG ATTGAAAAAAATTTTCTACGG - +4 transfac_pro__M05214 16 0.803387 19645.2 1 5 CACCTG GGGGAGCGGAGGGGCACACCA - +4 cisbp__M0595 4 0.805054 19686 1 6 CACCTG AATTTAAATT + +4 cisbp__M0599 4 0.805054 19686 1 6 CACCTG ATTTGAATTT + +4 cisbp__M1053-oc-Ptx1 2 0.805054 19686 1 6 CACCTG TTAATCCCCT + +4 cisbp__M1210 3 0.805054 19686 1 6 CACCTG AGTGACGGCA + +4 cisbp__M1218 4 0.805054 19686 1 6 CACCTG GCAATATTGG + +4 cisbp__M1643 4 0.805054 19686 1 6 CACCTG GTGGGCCCAC + +4 fantom__motif161_CGGCTTGATT 0 0.805054 19686 1 6 CACCTG CGGCTTGATT + +4 predrem__nrMotif1660 4 0.805054 19686 1 6 CACCTG AGAAGACACA + +4 taipale__Zfp740_DBD_NCCCCCCCAC_repr 1 0.805054 19686 1 6 CACCTG CCCCCCCCAC + +4 taipale_cyt_meth__ATOH1_ANCATATGNY_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.805054 19686 1 6 CACCTG AACATATGGC + +4 taipale_cyt_meth__POU4F3_NTATGCATAN_eDBD_meth_repr 3 0.805054 19686 1 6 CACCTG TCATGCATGA + +4 cisbp__M0888-al-bsh-CG15696-CG34367-Dr-en-inv-lab-lms-OdsH-repo-slou-Ubx-unc-4-unpg-Vsx2 1 0.805054 19686 1 6 CACCTG GCCAATTAAG - +4 cisbp__M1265 2 0.805054 19686 1 6 CACCTG CTTTCGTTTC - +4 cisbp__M5020-E(spl)m5-HLH 1 0.805054 19686 1 6 CACCTG GCACGAGACA - +4 cisbp__M6112 1 0.805054 19686 1 6 CACCTG CCCCCCCCAC - +4 taipale__DLX1_DBD_NNYAATTANN-Dll 2 0.805054 19686 1 6 CACCTG GATAATTAGG - +4 taipale_cyt_meth__NEUROG1_RNCATATGNY_FL-amos-ato-dimm-Fer3-HLH54F-Oli-tap 0 0.805054 19686 1 6 CACCTG GACATATGTC - +4 taipale_cyt_meth__NEUROG1_RNCATATGNY_FL_meth-amos-ato-dimm-Fer3-HLH54F-Oli-tap 0 0.805054 19686 1 6 CACCTG AACATATGTT - +4 taipale_cyt_meth__SOX4_GAACAAAGRN_eDBD_meth-D-Mad-Sox100B-Sox14-SoxN 0 0.805054 19686 1 6 CACCTG TCCTTTGTTC - +4 transfac_pro__M02054-aop-Eip74EF-Ets21C-Ets65A-Ets96B-Ets98B-Hr78-pnt 0 0.805054 19686 1 6 CACCTG TACTTCCGGG - +4 transfac_pro__M03211 1 0.805054 19686 1 6 CACCTG GGAGCGGCCT - +4 transfac_pro__M04716-Jra-Stat92E 4 0.805054 19686 1 6 CACCTG GACTCATTTC - +4 transfac_pro__M06828 3 0.805054 19686 1 6 CACCTG GGCGCCCTTT - +4 swissregulon__hs__RXR_A_B_G_.p2-usp 5 0.805054 19686 1 5 CACCTG GGGGTCACGG + +4 taipale__OLIG2_full_AMCATATGKT-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.805054 19686 1 5 CACCTG ACCATATGGT + +4 taipale_cyt_meth__BHLHE22_ANCATATGNY_eDBD-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.805054 19686 1 5 CACCTG ACCATATGGT + +4 taipale_cyt_meth__OLIG3_ACCATATGKT_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.805054 19686 1 5 CACCTG ACCATATGTT + +4 cisbp__M5692-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.805054 19686 1 5 CACCTG ACCATATGGT - +4 hocomoco__PITX1_MOUSE.H11MO.0.C-Gsc-Ptx1-oc 5 0.805054 19686 1 5 CACCTG GTTAATCCCT - +4 predrem__nrMotif569 -1 0.805054 19686 1 5 CACCTG TTCTGGATCC - +4 taipale__BARHL2_full_NNTAAACGNN-B-H1-B-H2-NK7.1 -1 0.805054 19686 1 5 CACCTG ACCGTTTAGC - +4 hdpi__TFAP2A-TfAP-2 6 0.805054 19686 1 4 CACCTG TTCGGAAAGC + +4 taipale__EMX1_DBD_NNYAATTANN-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-ro-slou-Ubx-unpg-Vsx1-Vsx2-zfh2 6 0.805054 19686 1 4 CACCTG GCTAATTAGC + +4 taipale__EN1_DBD_NNYAATTANN-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 6 0.805054 19686 1 4 CACCTG CCCAATTAGC + +4 taipale__GBX2_full_NNYAATTANN-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-inv-lab-lbe-lms-pb-Pph13-slou-Ubx-unpg-Vsx1-Vsx2 6 0.805054 19686 1 4 CACCTG ACCAATTAGC + +4 taipale_cyt_meth__DMRTC2_RAACGATACA_eDBD_repr 6 0.805054 19686 1 4 CACCTG GAACGATACA + +4 cisbp__M5386-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-ro-slou-Ubx-unpg-Vsx1-Vsx2-zfh2 6 0.805054 19686 1 4 CACCTG GCTAATTAGC - +4 cisbp__M5483-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-inv-lab-lbe-lms-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 6 0.805054 19686 1 4 CACCTG ACCAATTAGC - +4 cisbp__M6189-Dll 6 0.805054 19686 1 4 CACCTG TGTAATTAGC - +4 predrem__nrMotif1288 -2 0.805054 19686 1 4 CACCTG CCTTCCCCCG - +4 transfac_pro__M05821 6 0.805054 19686 1 4 CACCTG CGAGCCCTCC - +4 transfac_pro__M06709 6 0.805054 19686 1 4 CACCTG GCGTTTTATC - +4 transfac_pro__M07770-Antp-btn-eve-pb-Scr-slou 6 0.805054 19686 1 4 CACCTG GGTAATTACC - +4 cisbp__M3846-Mef2-rump 0 0.805158 19688.5 1 6 CACCTG AAGCTATAAATAGAAT + +4 taipale_cyt_meth__ETV7_NMGGAARNNYTTCCKN_FL-aop 10 0.805158 19688.5 1 6 CACCTG CCGGAAGTACTTCCGG + +4 transfac_pro__M05568 3 0.805158 19688.5 1 6 CACCTG TGAAATCTGGCCCCCG + +4 transfac_public__M00092-br 4 0.805158 19688.5 1 6 CACCTG TTCTTTACTATTTTTT + +4 transfac_public__M00266-croc 9 0.805158 19688.5 1 6 CACCTG AAAAATAAATATAATG + +4 cisbp__M1877 7 0.805158 19688.5 1 6 CACCTG GTTTTTCCATTTGTTG - +4 cisbp__M2529-Adf1 10 0.805158 19688.5 1 6 CACCTG CCGCCGCTGCCGCCGA - +4 cisbp__M2534-br 4 0.805158 19688.5 1 6 CACCTG TTCTTTACTATTTTTT - +4 hocomoco__SOX2_MOUSE.H11MO.0.A-CG9650-Mad-SoxN-nej-pan 2 0.805158 19688.5 1 6 CACCTG TTTGCATAACAAAGGA - +4 taipale_cyt_meth__MAFF_NYGCTGAYRTCAGCRN_FL_meth-CrebA-CrebB-maf-S 5 0.805158 19688.5 1 6 CACCTG TTGCTGACGTCAGCAT - +4 transfac_pro__M01396-abd-A-exex-Lim3-Ubx 0 0.805158 19688.5 1 6 CACCTG TTGCATTAATTACTAC - +4 transfac_pro__M01431-al-Awh-en-inv-Lim3-OdsH 0 0.805158 19688.5 1 6 CACCTG TATAACTAATTACTTA - +4 taipale_cyt_meth__RFX3_NGTTGCCATGGCAACN_eDBD_meth-CG5846-CG9727-Max-Rfx-SREBP 12 0.805158 19688.5 1 4 CACCTG CGTTGCCATGGCAACG - +4 tfdimers__MD00371-lz-run-RunxA-RunxB 9 0.805346 19693.1 1 6 CACCTG TTAATCATTAACCACAAAGTTA + +4 taipale__ETS1_DBD_NCCGGAWRYRYWTCCGGN_repr-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Ets98B-pnt 8 0.805665 19700.9 1 6 CACCTG ACCGGAAGTACATCCGGT + +4 transfac_pro__M01012-bin-croc-fd59A-fkh-foxo-HDAC1-nej-Nf1 1 0.805665 19700.9 1 6 CACCTG TTCATTGTTTGCTTAGTT + +4 transfac_public__M00193-NfI 11 0.805665 19700.9 1 6 CACCTG TCTTGGCAAGAAGCCAAA + +4 predrem__nrMotif818-Brf-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-ct-klu 1 0.805665 19700.9 1 6 CACCTG CCCCCTCTCCCCGCCCCC - +4 taipale_tf_pairs__ETV2_DLX3_TAATTRNNNNCGGAARYN_CAP_repr-pnt 3 0.805665 19700.9 1 6 CACCTG CACTTCCGGTTCCAATTA - +4 transfac_pro__M01073 12 0.805665 19700.9 1 6 CACCTG GGCCCGCGGGCACCCCTC - +4 transfac_pro__M06004 8 0.805665 19700.9 1 6 CACCTG GAAATACTAACCCAATCC - +4 transfac_pro__M07720-croc-fd59A-fd96Ca-fd96Cb-fkh 12 0.805665 19700.9 1 6 CACCTG TATGTAAATATTTACATA - +4 transfac_pro__M09266-bs 1 0.805665 19700.9 1 6 CACCTG TTTCCAAAAATGGAAAGT - +4 tfdimers__MD00314-E2f1-Jra-kay 17 0.806177 19713.5 1 6 CACCTG TTTATCATTTCCTGACTCATTAAAA + +4 tfdimers__MD00372-Ptx1-Stat92E 8 0.806177 19713.5 1 6 CACCTG AATATTCTAATCTTCTTGGAAAAAT + +4 tfdimers__MD00097 6 0.806177 19713.5 1 6 CACCTG TTTTACTTCCTTAATTTTTTTTTTT - +4 transfac_pro__M01000 10 0.806177 19713.5 1 6 CACCTG TAACCAATATAACCAATTAATAACC - +4 hocomoco__SP1_MOUSE.H11MO.0.A-Brf-CG42741-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-Spt20-Stat92E-brm-btd-ct-dar1-kay-klu-luna-sr-vtd 11 0.80667 19725.5 1 6 CACCTG CCCGGCCCCGCCCCCTCCCCCCCC - +4 tfdimers__MD00189 21 0.806729 19727 1 6 CACCTG ATAATCTTTAGGATTAATTTTTAACTGATATTAA + +4 transfac_pro__M03548-FoxL1 3 0.808309 19765.6 1 6 CACCTG TAAGACTAATTT + +4 cisbp__M6012-FoxK-slp2 6 0.808309 19765.6 1 6 CACCTG GATTGTGTCCGG - +4 flyfactorsurvey__gt_FlyReg_FBgn0001150-gt 2 0.808309 19765.6 1 6 CACCTG ATTAAGTCATAA - +4 hocomoco__JDP2_HUMAN.H11MO.0.D-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 2 0.808309 19765.6 1 6 CACCTG ATGACGTCATCA - +4 hocomoco__TYY1_HUMAN.H11MO.0.A-CG10431-Taf1-Taf7-lid-pho-phol 5 0.808309 19765.6 1 6 CACCTG GCCGCCATCTTG - +4 stark__TRTCAWNWRTCA 3 0.808309 19765.6 1 6 CACCTG TGACAAATGACA - +4 taipale__Foxg1_DBD_NMGGACACAATC_repr-FoxK-slp2 6 0.808309 19765.6 1 6 CACCTG GATTGTGTCCGG - +4 taipale_cyt_meth__ATF3_NRTGAYGTCAYN_eDBD-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.808309 19765.6 1 6 CACCTG GATGACGTCATC - +4 transfac_pro__M05635 1 0.808309 19765.6 1 6 CACCTG AAACCAAGCCAG - +4 transfac_pro__M05859-CG6654-CG7372 2 0.808309 19765.6 1 6 CACCTG GCAGCCTTATCA - +4 transfac_pro__M06043 4 0.808309 19765.6 1 6 CACCTG TCATTACCCCCG - +4 transfac_pro__M06103 6 0.808309 19765.6 1 6 CACCTG GTTTCTTGCCAG - +4 transfac_pro__M06159 6 0.808309 19765.6 1 6 CACCTG TCTTTTTGCCAA - +4 transfac_pro__M06448-CG3281 6 0.808309 19765.6 1 6 CACCTG TCGCCCCCCCAA - +4 transfac_pro__M06619 6 0.808309 19765.6 1 6 CACCTG TCCGCCGACCCA - +4 transfac_pro__M06715 6 0.808309 19765.6 1 6 CACCTG AACGAAAACAAG - +4 hocomoco__MSGN1_MOUSE.H11MO.0.C -1 0.808309 19765.6 1 5 CACCTG GCCATTTGTTCC + +4 transfac_pro__M05832 -1 0.808309 19765.6 1 5 CACCTG CGCTTAAAACGC + +4 transfac_pro__M07874-gsb-gsb-n-prd -1 0.808309 19765.6 1 5 CACCTG GCGTGACGAATC + +4 transfac_pro__M05693 7 0.808309 19765.6 1 5 CACCTG GCCGATGGACAT - +4 transfac_pro__M06070 7 0.808309 19765.6 1 5 CACCTG TATGATGCAACT - +4 transfac_pro__M06564 7 0.808309 19765.6 1 5 CACCTG TTTTCCCGTCCA - +4 transfac_pro__M06857 7 0.808309 19765.6 1 5 CACCTG TTTTACAGACCA - +4 homer__GGGGGAATCCCC_NFkB-p50_p52-Dif-Rel 8 0.808309 19765.6 1 4 CACCTG GGGGGAATCCCC + +4 transfac_pro__M06328 8 0.808309 19765.6 1 4 CACCTG TCTTTAGCAACA - +4 transfac_pro__M06391 -2 0.808309 19765.6 1 4 CACCTG GCTGGAGCCCCT - +4 transfac_pro__M07832-so 9 0.808309 19765.6 1 3 CACCTG ATATCATGATAC + +4 flyfactorsurvey__CG31670_SOLEXA_F1-3-erm 9 0.809307 19790 1 6 CACCTG GGTTGCTCATATTGG + +4 swissregulon__hs__TFCP2.p2-gem 8 0.809307 19790 1 6 CACCTG GCTGGGTCGGGCTGG + +4 taipale_cyt_meth__MAFF_NYGCTGASTCAGCRN_eDBD_meth-cnc-maf-S-tj 9 0.809307 19790 1 6 CACCTG ATGCTGAGTCAGCAT + +4 taipale_cyt_meth__TCF7L1_WCATCGRGRCGCTGW_eDBD-pan 1 0.809307 19790 1 6 CACCTG ACATCGGGGCGCTGA + +4 taipale_cyt_meth__ZFP41_NGCTAACTCTCCRCR_FL_meth-CG6654-CG7372 3 0.809307 19790 1 6 CACCTG CGCTAACTCTCCACA + +4 transfac_pro__M02853-fkh 8 0.809307 19790 1 6 CACCTG AAAAATAACAAACGG + +4 transfac_pro__M03122 9 0.809307 19790 1 6 CACCTG ATGCGCGTGTCCCAG + +4 transfac_pro__M03871-ci-lmd-opa-sug 8 0.809307 19790 1 6 CACCTG CCGCAGACCACCCAG + +4 transfac_pro__M09270-Mef2 0 0.809307 19790 1 6 CACCTG TTCCAAAAATGGAAA + +4 c2h2_zfs__M4021-CG7368-CTCF-CoRest-crol-ct-l(3)neo38 7 0.809307 19790 1 6 CACCTG CCCCCCCACCCCCTA - +4 cisbp__M4075-vvl 0 0.809307 19790 1 6 CACCTG CAACTCTAATTCCCC - +4 cisbp__M4700-aop-Eip74EF-Hr78 0 0.809307 19790 1 6 CACCTG GACCCGGAAGCACTT - +4 cisbp__M4704-ey-Poxm-sv-toy 8 0.809307 19790 1 6 CACCTG GTCACGCTTGGCTGC - +4 cisbp__M6113-opa 0 0.809307 19790 1 6 CACCTG GACCCCCCGCTGTGC - +4 factorbook__E2F1-E2f1 9 0.809307 19790 1 6 CACCTG CCGCGCGCCCTCCCC - +4 flyfactorsurvey__sob-F1-3_SOLEXA_5-bowl-odd-sob 0 0.809307 19790 1 6 CACCTG CACCCAAACAGTAGC - +4 neph__UW.Motif.0093 8 0.809307 19790 1 6 CACCTG GCCAAATTTTTTTTT - +4 swissregulon__hs__POU3F1..4.p2-vvl 0 0.809307 19790 1 6 CACCTG CCATTTTAATTCCCC - +4 taipale_cyt_meth__MAF_NYGCTGASTCAGCRN_FL_meth-cnc-maf-S-tj 9 0.809307 19790 1 6 CACCTG ATGCTGAGTCAGCAT - +4 transfac_pro__M09205 2 0.809307 19790 1 6 CACCTG AGAATCTTCGATTCT - +4 transfac_public__M00133-vvl 0 0.809307 19790 1 6 CACCTG GTATTTTAATTCCTC - +4 cisbp__M4623-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 10 0.809307 19790 1 5 CACCTG AAGGATGAGTCACCG - +4 hocomoco__ZN148_HUMAN.H11MO.0.D-CG7368-CTCF-CoRest-Spps-btd-crol-ct-sr -1 0.809307 19790 1 5 CACCTG CCCCTCCCCCACCCC - +4 transfac_pro__M07723-bin-CHES-1-like-croc-fd59A-FoxK-foxo-FoxP-slp1-slp2 10 0.809307 19790 1 5 CACCTG TTTGTTTGTTTACAT - +4 cisbp__M5521 11 0.809307 19790 1 4 CACCTG AGTTAATGATTAACT + +4 tfdimers__MD00378-E2f1-NfI 2 0.809568 19796.4 1 6 CACCTG AAAACTTGGCTAAGTGCCAGAAACGAAATT + +4 cisbp__M3718 24 0.809568 19796.4 1 6 CACCTG AAAAATTAACCCAAAATCCAACCTCACCCC - +4 cisbp__M0863-oc 2 0.809609 19797.4 1 6 CACCTG TTAATCCC + +4 cisbp__M1592-Sox100B-SoxN 2 0.809609 19797.4 1 6 CACCTG ATAACAAT + +4 cisbp__M1733 0 0.809609 19797.4 1 6 CACCTG TATCTCCG + +4 cisbp__M1787 1 0.809609 19797.4 1 6 CACCTG GTTCCGTG + +4 cisbp__M5340-Dll-Dr 1 0.809609 19797.4 1 6 CACCTG GTAATTGG + +4 cisbp__M5585-al-B-H1-B-H2-bsh-C15-CG32532-CG34367-CG9876-Dr-en-ind-inv-lbe-Lim3-lms-OdsH-Pph13-repo-slou-Ubx-unc-4-unpg-Vsx2 1 0.809609 19797.4 1 6 CACCTG TTAATTGG + +4 elemento__ATGACGTC-Atf-2-Atf6-CG44247-cnc-crc-CrebA-Jra-kay-REPTOR-BP-Xbp1 2 0.809609 19797.4 1 6 CACCTG ATGACGTC + +4 elemento__TGACATCA-CrebB-Jra 1 0.809609 19797.4 1 6 CACCTG TGACATCA + +4 elemento__TGACGTCA-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 1 0.809609 19797.4 1 6 CACCTG TGACGTCA + +4 predrem__nrMotif1297 1 0.809609 19797.4 1 6 CACCTG TCTCCGGC + +4 taipale__PRRX1_DBD_NYAATTAN-al-ap-Awh-bsh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-Drgx-E5-en-exex-ey-hbn-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro- 1 0.809609 19797.4 1 6 CACCTG CTAATTAA + +4 taipale__PRRX2_full_NYAATTAN-al-B-H1-B-H2-bsh-C15-CG32532-CG34367-CG9876-Dr-E5-en-ind-inv-lbe-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx2 1 0.809609 19797.4 1 6 CACCTG CCAATTAA + +4 taipale_cyt_meth__ALX3_CYAATTAN_FL_meth-al-Awh-CG4328-Dll-en-inv-Lim3-Lmx1a-slou 1 0.809609 19797.4 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__CRX_NTAATCCN_FL-Gsc-oc 2 0.809609 19797.4 1 6 CACCTG CTAATCCG + +4 taipale_cyt_meth__GSC_YTAATCCN_eDBD-bcd-Gsc-oc 2 0.809609 19797.4 1 6 CACCTG CTAATCCG + +4 taipale_cyt_meth__HOXA4_RTCGTTAN_eDBD_meth-abd-A-Antp-btn-Dfd-eve-exex-ind-lab-pb-Scr-Ubx 0 0.809609 19797.4 1 6 CACCTG ATCATTAA + +4 taipale_cyt_meth__HOXD4_RTCGTTAN_FL_meth-Antp-btn-Dfd-eve-exex-ind-lab-pb-Scr 0 0.809609 19797.4 1 6 CACCTG ATCATTAA + +4 taipale_cyt_meth__SHOX_CYAATTAN_eDBD_meth-al-Awh-CG32532-CG34367-CG4328-Dll-en-hbn-HGTX-ind-inv-Lim3-lms-Lmx1a-OdsH-repo-unc-4-unpg-Vsx2 1 0.809609 19797.4 1 6 CACCTG CTAATTAA + +4 cisbp__M0102-htk 1 0.809609 19797.4 1 6 CACCTG TAATATCA - +4 cisbp__M0134 2 0.809609 19797.4 1 6 CACCTG ATTTTTTT - +4 cisbp__M0920-Vsx2 0 0.809609 19797.4 1 6 CACCTG CTAATTAG - +4 cisbp__M0967-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG15696-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-ind-inv-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-Rx-slou-Traf4-tup-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh 1 0.809609 19797.4 1 6 CACCTG CCAATTAA - +4 cisbp__M1154-al-Awh-B-H1-B-H2-C15-CG11085-CG15696-CG18599-CG32532-CG34367-CG9876-Dr-E5-en-gsb-gsb-n-inv-lbe-Lim3-lms-Lmx1a-OdsH-otp-Pph13-prd-repo-Rx-slou-Traf4-unc-4-unpg-Vsx2-zfh2 1 0.809609 19797.4 1 6 CACCTG CCAATTAA - +4 cisbp__M5757-al-B-H1-B-H2-bsh-C15-CG18599-CG32532-CG34367-CG9876-Dr-en-ind-inv-lbe-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx2 1 0.809609 19797.4 1 6 CACCTG CCAATTAA - +4 elemento__ATGATGTC 0 0.809609 19797.4 1 6 CACCTG GACATCAT - +4 elemento__TTGATGTC 0 0.809609 19797.4 1 6 CACCTG GACATCAA - +4 hocomoco__DLX2_HUMAN.H11MO.0.D 1 0.809609 19797.4 1 6 CACCTG ATAATTAT - +4 idmmpmm__en-Antp-CG4328-CG9876-CG11294-CG32532-CG34367-Dll-Dr-HGTX-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-al-en-exex-hbn-ind-inv-lab-lms-repo-ro-slou-unc-4-unpg 1 0.809609 19797.4 1 6 CACCTG CTAATTAA - +4 stark__VCACGCRH 1 0.809609 19797.4 1 6 CACCTG TCGCGTGT - +4 taipale__DLX6_DBD_NYAATTAN-Dll-Dr 1 0.809609 19797.4 1 6 CACCTG GTAATTGG - +4 taipale__ISX_DBD_NYAATTAN-al-B-H1-B-H2-bsh-C15-CG32532-CG34367-CG9876-Dr-en-ind-inv-lbe-Lim3-lms-OdsH-Pph13-repo-slou-Ubx-unc-4-unpg-Vsx2 1 0.809609 19797.4 1 6 CACCTG TTAATTGG - +4 transfac_pro__M07784-Dll-Dr 1 0.809609 19797.4 1 6 CACCTG GTAATTGC - +4 scertf__badis.NHP10 -1 0.809609 19797.4 1 5 CACCTG GCCGGGGA + +4 cisbp__M4776-br 3 0.809609 19797.4 1 5 CACCTG TTCTATTT - +4 flyfactorsurvey__br-Z1_FlyReg_FBgn0000210-br 3 0.809609 19797.4 1 5 CACCTG TTCTATTT - +4 cisbp__M1774 -2 0.809609 19797.4 1 4 CACCTG CCGGCCGC + +4 cisbp__M4809-CG11617 4 0.809609 19797.4 1 4 CACCTG ATTTAACA + +4 hdpi__APEX2 4 0.809609 19797.4 1 4 CACCTG TTGGCAGC - +4 homer__GKTAATGR_Nkx6.1-HGTX 4 0.809609 19797.4 1 4 CACCTG TCATTAAC - +4 neph__UW.Motif.0077-Sox21a-SoxN -2 0.809609 19797.4 1 4 CACCTG CATTGTTT - +4 predrem__nrMotif1672 -2 0.809609 19797.4 1 4 CACCTG TCTGATAA - +4 cisbp__M1242-acj6-Antp-HGTX-ind-lab-Scr-zen2 -3 0.809609 19797.4 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__MEOX1_NYAATTAN_FL-abd-A-Antp-bsh-btn-Dfd-Dll-exex-lab-Lim1-Lim3-pb-Scr-Ubx-unpg 5 0.809609 19797.4 1 3 CACCTG GTAATTAC + +4 cisbp__M0724-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.809609 19797.4 1 3 CACCTG TTGTTTAC - +4 predrem__nrMotif1384 -3 0.809609 19797.4 1 3 CACCTG CTATTCCA - +4 predrem__nrMotif2148 -3 0.809609 19797.4 1 3 CACCTG CTAGGCTG - +4 scertf__macisaac.HAP2-Nf-YA -3 0.809609 19797.4 1 3 CACCTG CTCATTGG - +4 cisbp__M6359-cnc 1 0.809666 19798.8 1 6 CACCTG AGTCATT - +4 transfac_pro__M07300-NfI 1 0.809666 19798.8 1 6 CACCTG CAGCCAA - +4 jaspar__MA0152.1-NFAT 2 0.809666 19798.8 1 5 CACCTG TTTTCCA + +4 hdpi__SMAD3-Smox 2 0.809666 19798.8 1 5 CACCTG CAGACCA - +4 predrem__nrMotif1486 2 0.809666 19798.8 1 5 CACCTG TTTAACA - +4 predrem__nrMotif1618 2 0.809666 19798.8 1 5 CACCTG TTGGCCT - +4 transfac_pro__M01733 2 0.809666 19798.8 1 5 CACCTG CTCCCCA - +4 elemento__ACGCCCC 3 0.809666 19798.8 1 4 CACCTG ACGCCCC + +4 elemento__AGCCGCC 3 0.809666 19798.8 1 4 CACCTG AGCCGCC + +4 elemento__CAGCAGC 3 0.809666 19798.8 1 4 CACCTG CAGCAGC + +4 elemento__CAGCCCC 3 0.809666 19798.8 1 4 CACCTG CAGCCCC + +4 elemento__CAGCGCC 3 0.809666 19798.8 1 4 CACCTG CAGCGCC + +4 elemento__CATCAGC 3 0.809666 19798.8 1 4 CACCTG CATCAGC + +4 elemento__CATGCGC -2 0.809666 19798.8 1 4 CACCTG CATGCGC + +4 elemento__CATGCTG -2 0.809666 19798.8 1 4 CACCTG CATGCTG + +4 elemento__CATGGCC -2 0.809666 19798.8 1 4 CACCTG CATGGCC + +4 elemento__CCCCAGC 3 0.809666 19798.8 1 4 CACCTG CCCCAGC + +4 elemento__CCGCAGC 3 0.809666 19798.8 1 4 CACCTG CCGCAGC + +4 elemento__CCGCCCC-btd-Spps 3 0.809666 19798.8 1 4 CACCTG CCGCCCC + +4 elemento__CCGCGCC 3 0.809666 19798.8 1 4 CACCTG CCGCGCC + +4 elemento__CCGCTCC 3 0.809666 19798.8 1 4 CACCTG CCGCTCC + +4 elemento__CGCCAGC 3 0.809666 19798.8 1 4 CACCTG CGCCAGC + +4 elemento__CGCCCCC 3 0.809666 19798.8 1 4 CACCTG CGCCCCC + +4 elemento__CGCCGCC 3 0.809666 19798.8 1 4 CACCTG CGCCGCC + +4 elemento__CGGCAGC 3 0.809666 19798.8 1 4 CACCTG CGGCAGC + +4 elemento__CGGCCCC 3 0.809666 19798.8 1 4 CACCTG CGGCCCC + +4 elemento__CGGCGCC 3 0.809666 19798.8 1 4 CACCTG CGGCGCC + +4 elemento__CGGCTCC 3 0.809666 19798.8 1 4 CACCTG CGGCTCC + +4 elemento__GAGCCCC 3 0.809666 19798.8 1 4 CACCTG GAGCCCC + +4 elemento__GCCCCCC 3 0.809666 19798.8 1 4 CACCTG GCCCCCC + +4 elemento__GCCCGCC 3 0.809666 19798.8 1 4 CACCTG GCCCGCC + +4 elemento__GCGCCCC 3 0.809666 19798.8 1 4 CACCTG GCGCCCC + +4 elemento__GCGCGCC 3 0.809666 19798.8 1 4 CACCTG GCGCGCC + +4 elemento__GCGCTCC 3 0.809666 19798.8 1 4 CACCTG GCGCTCC + +4 elemento__GGCCCCC 3 0.809666 19798.8 1 4 CACCTG GGCCCCC + +4 elemento__GGCCGCC 3 0.809666 19798.8 1 4 CACCTG GGCCGCC + +4 elemento__TCCCGCC 3 0.809666 19798.8 1 4 CACCTG TCCCGCC + +4 elemento__TGGCGCC-E2f1 3 0.809666 19798.8 1 4 CACCTG TGGCGCC + +4 elemento__TTCCGCC 3 0.809666 19798.8 1 4 CACCTG TTCCGCC + +4 scertf__morozov.PDR3 -2 0.809666 19798.8 1 4 CACCTG TCTGCGG + +4 elemento__CATCATG -2 0.809666 19798.8 1 4 CACCTG CATGATG - +4 elemento__GCTGCCC 3 0.809666 19798.8 1 4 CACCTG GGGCAGC - +4 elemento__GCTGCGC 3 0.809666 19798.8 1 4 CACCTG GCGCAGC - +4 elemento__GCTGGAC 3 0.809666 19798.8 1 4 CACCTG GTCCAGC - +4 elemento__GCTGGCC 3 0.809666 19798.8 1 4 CACCTG GGCCAGC - +4 elemento__GGCGCCC 3 0.809666 19798.8 1 4 CACCTG GGGCGCC - +4 hdpi__NMRAL1 -2 0.809666 19798.8 1 4 CACCTG CGTTTGA - +4 hdpi__ZNF720 -2 0.809666 19798.8 1 4 CACCTG GCTTATC - +4 predrem__nrMotif1176 3 0.809666 19798.8 1 4 CACCTG ATTCACA - +4 elemento__CTAATTA-Awh-E5-ems-en-inv -3 0.809666 19798.8 1 3 CACCTG CTAATTA + +4 cisbp__M6520-achi-vis -3 0.809666 19798.8 1 3 CACCTG CTGTCAC - +4 elemento__CAATTAG -3 0.809666 19798.8 1 3 CACCTG CTAATTG - +4 jaspar__MA0289.1-GATAd-GATAe-grn-pnr-srp -3 0.809666 19798.8 1 3 CACCTG CTTATCG - +4 stark__TAAATAG-bin -3 0.809666 19798.8 1 3 CACCTG CTATTTA - +4 transfac_pro__M01619-GATAd-GATAe-grn-pnr-srp -3 0.809666 19798.8 1 3 CACCTG CTTATCG - +4 hocomoco__FOXL1_HUMAN.H11MO.0.D-FoxL1-FoxP-bin-croc-fd59A-fkh-slp1-slp2 12 0.810885 19828.6 1 6 CACCTG TGTTTGTTTGTTTACTTTT + +4 hocomoco__STAT1_HUMAN.H11MO.1.A-Blimp-1-Stat92E 9 0.810885 19828.6 1 6 CACCTG AAGAAAATGAAACTGAAAG + +4 transfac_pro__M06204 13 0.810885 19828.6 1 6 CACCTG GATCTCGTTATTCCACTCG - +4 bergman__oc-Gsc-bcd-oc 0 0.811192 19836.1 1 6 CACCTG ACGCTAATCCGCT + +4 cisbp__M5311-al-ap-bsh-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Drgx-E5-en-eve-ey-hbn-lab-Lim1-Lim3-lms-Lmx1a-OdsH-Optix-otp-PHDP-Pph13-repo-ro-Rx-slou-Traf4-unc-4-unpg-Vsx1 2 0.811192 19836.1 1 6 CACCTG TTAATTTAATTAA + +4 cisbp__M5455-fd59A-foxo-slp2 3 0.811192 19836.1 1 6 CACCTG GTAAACATAAACA + +4 taipale__CART1_DBD_NTAAYYYAATTAN-al-ap-bsh-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Drgx-en-eve-ey-hbn-lab-Lim1-Lim3-lms-Lmx1a-OdsH-Optix-otp-PHDP-Pph13-repo-ro-Rx-slou-Traf4-unc-4-unpg-Vsx1-Vsx2 2 0.811192 19836.1 1 6 CACCTG TTAATTTAATTAA + +4 taipale__FOXJ2_DBD_RTAAACAWMAACA_repr-fd59A-foxo-slp2 3 0.811192 19836.1 1 6 CACCTG GTAAACATAAACA + +4 taipale_cyt_meth__EGR2_NMCGCCCACGCAN_FL_meth_repr-btd-klu-Spps-sr 6 0.811192 19836.1 1 6 CACCTG CCCGCCCACGCAC + +4 flyfactorsurvey__lola-PU_SOLEXA_FBgn0005630-lola 0 0.811192 19836.1 1 6 CACCTG CGGCTCAATACAA - +4 hocomoco__CRX_HUMAN.H11MO.0.B-bcd-oc 7 0.811192 19836.1 1 6 CACCTG CCTAATCCTCTTA - +4 hocomoco__E2F4_HUMAN.H11MO.0.A-Dp-E2f1-E2f2 2 0.811192 19836.1 1 6 CACCTG ATTTCCCGCCCCC - +4 hocomoco__ZBED1_HUMAN.H11MO.0.D-CG13775 7 0.811192 19836.1 1 6 CACCTG ATATCGCGACATA - +4 cisbp__M6371-btd-CG7839-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps -1 0.811192 19836.1 1 5 CACCTG CTCTGATTGGCTG + +4 stark__AATTNNNTCACGY 8 0.811192 19836.1 1 5 CACCTG AATTAAATCACGC + +4 cisbp__M6372-btd-CG7839-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps -1 0.811192 19836.1 1 5 CACCTG CTCTGATTGGCTG - +4 hocomoco__NFYB_HUMAN.H11MO.0.A-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay-yps -1 0.811192 19836.1 1 5 CACCTG CTCTGATTGGCTG - +4 stark__RCGTGNNNNGCAT 8 0.811192 19836.1 1 5 CACCTG ATGCAAAACACGC - +4 cisbp__M5522 10 0.811192 19836.1 1 3 CACCTG GTTAATCATTAAC + +4 taipale__HNF1B_full_GTTAATNATTAAY 10 0.811192 19836.1 1 3 CACCTG GTTAATCATTAAC - +4 idmmpmm__Mad-Mad 2 0.811383 19840.8 1 6 CACCTG GCTGCCGGCGCGGC + +4 neph__UW.Motif.0570 8 0.811383 19840.8 1 6 CACCTG AGTGGGGAGATCTC + +4 taipale__EN1_full_TAATTRSNYAATTA-bs-bsh-CG34367-CG9876-Dr-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg-Vsx2 8 0.811383 19840.8 1 6 CACCTG TAATTGCTTAATTA + +4 transfac_pro__M02842-CrebB 4 0.811383 19840.8 1 6 CACCTG GAATGACGAATAAC + +4 cisbp__M4104-croc-fkh 0 0.811383 19840.8 1 6 CACCTG TCAATGTTTATAAT - +4 hocomoco__E2F1_HUMAN.H11MO.0.A-Dp-E2f1-E2f2-Spps-btd 6 0.811383 19840.8 1 6 CACCTG CTTTCCCGCCCCCC - +4 hocomoco__E2F4_MOUSE.H11MO.0.A-Dp-E2f1-E2f2-Nf-YA-Nf-YB-Sp1-Spps-btd-kay 2 0.811383 19840.8 1 6 CACCTG ATTTCCCGCCCCCT - +4 taipale_cyt_meth__POU1F1_NTAATGAKATGCGN_eDBD_meth-pdm3-vvl 3 0.811383 19840.8 1 6 CACCTG ACGCATCTCATTAA - +4 transfac_public__M00149 6 0.811383 19840.8 1 6 CACCTG CATATTAACCACAA - +4 cisbp__M5579 9 0.811383 19840.8 1 5 CACCTG CCGAAACCGAAACT + +4 taipale__IRF8_full_NCGAAACCGAAACT 9 0.811383 19840.8 1 5 CACCTG TCGAAACCGAAACT + +4 hocomoco__NFYC_HUMAN.H11MO.0.A-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay-yps -1 0.811383 19840.8 1 5 CACCTG CTCTGATTGGCTAG - +4 neph__UW.Motif.0230 9 0.811383 19840.8 1 5 CACCTG TGATTTTTTTTTCT - +4 predrem__nrMotif477 10 0.811383 19840.8 1 4 CACCTG CCCTGCCCCCCACC + +4 cisbp__M5457-croc-fd59A-foxo-FoxP-slp2 11 0.811383 19840.8 1 3 CACCTG TGTTTATTGTTTAC - +4 cisbp__M5642-MTF-1 11 0.811383 19840.8 1 3 CACCTG TTTGCACACGGCAC - +4 scertf__macisaac.RFX1-CG5846-CG9727-Max-Rfx-SREBP 11 0.811383 19840.8 1 3 CACCTG GTTGCCATGACAAC - +4 tfdimers__MD00527-zfh1 19 0.812959 19879.3 1 6 CACCTG AAAAAAAAAATGAAACTGAAACAAAAAAA - +4 transfac_pro__M01316-Awh-Lim1-Lim3-otp-pdm3-Vsx1-vvl-zfh2 11 0.813216 19885.6 1 6 CACCTG AATTAATTAATTAATTC + +4 transfac_pro__M01385-al-ap-Awh-CG11085-E5-ems-en-eve-inv-Lim3-otp-ro-Rx-slou 1 0.813216 19885.6 1 6 CACCTG TGAACTAATTAGCCCAC + +4 transfac_pro__M01420-Antp-C15-CG34367-CG4328-Dbx-Lim1-Lim3-Lmx1a-Scr 11 0.813216 19885.6 1 6 CACCTG TAATTAATTAATAACTA + +4 transfac_pro__M02779-Myb 5 0.813216 19885.6 1 6 CACCTG ATGGAAACCGTTATTTT + +4 transfac_pro__M02780-Myb 5 0.813216 19885.6 1 6 CACCTG TTGAAAACCGTTAATTT + +4 transfac_pro__M02938 6 0.813216 19885.6 1 6 CACCTG AAATTCCCCCCGGAAGT + +4 transfac_pro__M03064-Ptx1 10 0.813216 19885.6 1 6 CACCTG TGAGGGGGATTAACTAT + +4 transfac_pro__M05296 2 0.813216 19885.6 1 6 CACCTG TGTACGTAATGCGTAAA + +4 cisbp__M4629-cnc-kay-maf-S 4 0.813216 19885.6 1 6 CACCTG AAAATTGCTGAGTCATG - +4 taipale_cyt_meth__PAX6_NYACGCNYSANYGMNYN_FL_meth-ey-Poxm-sv-toy 10 0.813216 19885.6 1 6 CACCTG TGTGCAGTGATGCGTGA - +4 taipale_cyt_meth__RFX5_NYRRCAACSGTTGCYAN_eDBD_meth 4 0.813216 19885.6 1 6 CACCTG ATGGCAACGGTTGCCGT - +4 transfac_pro__M05351-fd59A 2 0.813216 19885.6 1 6 CACCTG TTAAACTTGCTTTAACT - +4 transfac_pro__M05370-fd59A 2 0.813216 19885.6 1 6 CACCTG TTAAACTTGCTTTAACT - +4 transfac_public__M00014-arg-HDAC1-HDAC3 0 0.813216 19885.6 1 6 CACCTG GCCTTCGGCGGCTAGTA - +4 dbcorrdb__CHD2__ENCSR000EHD_1__m1-Chd1-CoRest 11 0.814892 19926.6 1 6 CACCTG AGCTCTCGCGAGAACTGGGG + +4 dbcorrdb__CTCF__ENCSR000DSU_1__m2-CTCF-vtd 0 0.814892 19926.6 1 6 CACCTG TGCGTGGGGCTATAGTGCCC + +4 dbcorrdb__EP300__ENCSR000BPW_1__m4-nej 8 0.814892 19926.6 1 6 CACCTG TAATGAGTCAACAGTGAGTT + +4 dbcorrdb__EZH2__ENCSR000AQE_1__m1-E(z) 1 0.814892 19926.6 1 6 CACCTG CTGCTTCTGTGTTCAGGCTG + +4 dbcorrdb__FOS__ENCSR000FAI_1__m1-btd-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 0 0.814892 19926.6 1 6 CACCTG CCTCTGATTGGCTGGGGCGG + +4 dbcorrdb__MTA3__ENCSR000BRH_1__m1-CG9650-Dif-dl-ebi-MTA1-like-nej-Stat92E 12 0.814892 19926.6 1 6 CACCTG AAGAGGAAATGAAACAGAAA + +4 dbcorrdb__MTA3__ENCSR000BRH_1__m3-ebi-foxo-Jra-Mef2-MTA1-like-nej-NFAT-Stat92E 10 0.814892 19926.6 1 6 CACCTG AGATGAGTCATAACGAAAGT + +4 dbcorrdb__MYC__ENCSR000DMM_1__m1-Brf-brm-btd-Clk-cnc-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-gce-Hcf-HDAC1-Max-Myc-Nelf-E-pho-phol-Rbbp5-RpII215-Sap30-Sidpn-Sin3A-Spps-Spt20-SREBP-Stat92E-Taf1-tna-Usf-vtd-zfh1 8 0.814892 19926.6 1 6 CACCTG CCGCGGCGCACGTGGCCGCG + +4 dbcorrdb__NFE2__ENCSR000FAF_1__m1-cnc-Jra-kay-maf-S 4 0.814892 19926.6 1 6 CACCTG AAAACTGCTGAGTCATGCCC + +4 dbcorrdb__NR2C2__ENCSR000EWH_1__m1-Hr78 2 0.814892 19926.6 1 6 CACCTG TCGGCCGGCTCGGCGCTCGG + +4 dbcorrdb__POLR2A__ENCSR000ALT_1__m4-RpII215 3 0.814892 19926.6 1 6 CACCTG AAGCTGCACACGCCCTTTCC + +4 dbcorrdb__POLR2A__ENCSR000BGD_1__m1-lid-pho-phol-RpII215-Taf1-Taf7 0 0.814892 19926.6 1 6 CACCTG CGCCTCCGCCATCTTGCGGC + +4 dbcorrdb__POLR2A__ENCSR000DLJ_1__m1-RpII215 14 0.814892 19926.6 1 6 CACCTG CGCCCTTTTTACGCCACCGC + +4 dbcorrdb__POLR2A__ENCSR000DLY_1__m1-Atac3-CG10431-Eip74EF-E(z)-Hcf-Myc-Rbbp5-RpII215-Sin3A-Taf1 6 0.814892 19926.6 1 6 CACCTG CCGCGGCGCTTCCGCCGCGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOV_1__m3-cnc-Myc-pan 14 0.814892 19926.6 1 6 CACCTG CGGCGCTGACTCACCGCGTT + +4 dbcorrdb__SIN3A__ENCSR000BOW_1__m2-E2f2-Max-Sap30-Sin3A 6 0.814892 19926.6 1 6 CACCTG CCGGGTCAAATGTCGCGCGC + +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m10-SREBP 9 0.814892 19926.6 1 6 CACCTG TAGCGCGGCCGTCTCATAAA + +4 dbcorrdb__STAT3__ENCSR000DOU_1__m3-aop-Jra-Stat92E 9 0.814892 19926.6 1 6 CACCTG CTGAGTCATTTCCCGGAAGT + +4 dbcorrdb__TAF1__ENCSR000BJN_1__m1-Brf-brm-CTCF-Eip74EF-E(z)-Hcf-lid-Max-Myc-pho-phol-Rbbp5-Rfx-RpII215-Sap30-Sin3A-SREBP-Taf1-Taf7-tna 3 0.814892 19926.6 1 6 CACCTG GGCGCGATGGCGGCGGCCGC + +4 dbcorrdb__TBP__ENCSR000EEL_1__m2-Tbp 4 0.814892 19926.6 1 6 CACCTG TTCGAACCCGCGACCTCTGG + +4 hocomoco__DMBX1_HUMAN.H11MO.0.D-CG9876-CG11294-CG15696-CG32532-CG34367-Dr-Drgx-HGTX-OdsH-Optix-Traf4-al-bsh-en-ey-hbn-ind-lbe-lbl-lms-repo-slou-toy-unc-4-unpg 7 0.814892 19926.6 1 6 CACCTG TAATTATAATCTAATTAAGT + +4 hocomoco__P53_HUMAN.H11MO.0.A 11 0.814892 19926.6 1 6 CACCTG AGACATGCCCAGACATGCCC + +4 hocomoco__ZNF85_HUMAN.H11MO.0.C 5 0.814892 19926.6 1 6 CACCTG ATAGAAAACTGAAGTAATCT + +4 transfac_pro__M01530 12 0.814892 19926.6 1 6 CACCTG TGGAGTGCGGGGTACTGTAA + +4 dbcorrdb__BCL11A__ENCSR000BIP_1__m2-CG9650 10 0.814892 19926.6 1 6 CACCTG GCTATTTGCATTCCAATGCC - +4 dbcorrdb__CTCF__ENCSR000ALJ_1__m2-CTCF-SMC3-vtd 3 0.814892 19926.6 1 6 CACCTG GGCCATATGGGGAACTGCAG - +4 dbcorrdb__CUX1__ENCSR000EFO_1__m1-ct 0 0.814892 19926.6 1 6 CACCTG ATCCGCTTATCGATCAATCA - +4 dbcorrdb__EZH2__ENCSR000ASY_1__m1-E(z) 8 0.814892 19926.6 1 6 CACCTG GATGCGGAGTCCTTGGGGCC - +4 dbcorrdb__FOS__ENCSR000DOT_1__m1-cnc-Jra-kay-maf-S-mor-Myc-nej-Stat92E-tj 12 0.814892 19926.6 1 6 CACCTG AAAAGGATGAGTCATCATTT - +4 dbcorrdb__GTF2B__ENCSR000DOE_1__m1-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 6 0.814892 19926.6 1 6 CACCTG GCGCCGCGCCTTTTATAGGC - +4 dbcorrdb__JUND__ENCSR000EIB_1__m1-cnc-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 10 0.814892 19926.6 1 6 CACCTG AGGGATGAGTCATCCTTTAT - +4 dbcorrdb__MBD4__ENCSR000BQW_1__m1-bin-croc-fd59A-fd96Ca-fd96Cb-fkh-foxo-GATAe-grn-HDAC1-nej-Nf1-pnr 7 0.814892 19926.6 1 6 CACCTG CAATGTTTACTTTGCCAATA - +4 dbcorrdb__MYC__ENCSR000DOM_1__m3-Myc-nej-Stat92E 11 0.814892 19926.6 1 6 CACCTG CATTATGCAATCACCCGCTG - +4 dbcorrdb__POLR2A__ENCSR000DLM_1__m2-RpII215 1 0.814892 19926.6 1 6 CACCTG ATAAGCTCCGCAGAGAAAAA - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BPI_1__m1-RpII215 6 0.814892 19926.6 1 6 CACCTG CCATTGCGCTTCCGCTGTTC - +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m4-RpII215-Su(z)12 9 0.814892 19926.6 1 6 CACCTG GTCCGCGGCGGCCTGCGCGC - +4 dbcorrdb__TRIM28__ENCSR000EYC_1__m4-bon 7 0.814892 19926.6 1 6 CACCTG AGCCATATGGCTTCTCACCA - +4 dbcorrdb__WRNIP1__ENCSR000EAA_1__m2 12 0.814892 19926.6 1 6 CACCTG AGAGGCGGAACTGACAACGC - +4 dbcorrdb__eGFP-JUNB__ENCSR000DJY_1__m1-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr-Stat92E 12 0.814892 19926.6 1 6 CACCTG AAAGGGATGAGTCATCCTTT - +4 swissregulon__hs__PAX5.p2-Spps-btd-sv 9 0.814892 19926.6 1 6 CACCTG CGGCCCCGCCTCAGTGCCCC - +4 transfac_pro__M04981 6 0.814892 19926.6 1 6 CACCTG AGGGCAAAACTGTAAATCCG - +4 homer__AACTACAATTCCCAGAATGC_GFY-Staf-Six4-Stat92E-bi-egg-mor -1 0.814892 19926.6 1 5 CACCTG GCATTCTGGGAATTGTAGTT - +4 transfac_pro__M09177 -1 0.814892 19926.6 1 5 CACCTG ATCTTATCCTTAACACTATC - +4 cisbp__M2269-bcd-oc 5 0.815247 19935.2 1 6 CACCTG CTAATCCTCTT + +4 cisbp__M4910-amos-ato-da-dimm-HLH54F-Oli-tap 0 0.815247 19935.2 1 6 CACCTG CGCCATATGGT + +4 fantom__motif89_CGCCGTGTTTA 0 0.815247 19935.2 1 6 CACCTG CGCCGTGTTTA + +4 hocomoco__ALX3_HUMAN.H11MO.0.D-Awh-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-eve-hbn-otp-repo-unc-4 1 0.815247 19935.2 1 6 CACCTG TAATTTAATTA + +4 predrem__nrMotif1500 3 0.815247 19935.2 1 6 CACCTG AGCAGCCTCTG + +4 transfac_pro__M09009-Gsc-oc 1 0.815247 19935.2 1 6 CACCTG TAATCCGATAA + +4 hocomoco__ATF7_HUMAN.H11MO.0.D-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 2 0.815247 19935.2 1 6 CACCTG ATGACGTCATC - +4 hocomoco__HXD13_HUMAN.H11MO.0.D 0 0.815247 19935.2 1 6 CACCTG TCCCTAATAAA - +4 hocomoco__SUH_HUMAN.H11MO.0.A-Su(H) 5 0.815247 19935.2 1 6 CACCTG TTTCCCACGCC - +4 predrem__nrMotif563 3 0.815247 19935.2 1 6 CACCTG CCCAGCCTCGC - +4 scertf__harbison.UME1 0 0.815247 19935.2 1 6 CACCTG TACTTTTCCTT - +4 transfac_pro__M00974-Dad-Mad-Med-Smox 1 0.815247 19935.2 1 6 CACCTG CTGTCTGGCTA - +4 transfac_pro__M07307-Sox15 3 0.815247 19935.2 1 6 CACCTG ACGGCCATTGT - +4 transfac_pro__M02113-nub-pdm2 -1 0.815247 19935.2 1 5 CACCTG ATATGCAAATC + +4 cisbp__M1177-Lim3 6 0.815247 19935.2 1 5 CACCTG AGTAATTACTT - +4 taipale_cyt_meth__ZNF396_NTGTMCGAAAN_FL_repr 6 0.815247 19935.2 1 5 CACCTG CTTTCGGACAC - +4 tiffin__TIFDMEM0000083 6 0.815247 19935.2 1 5 CACCTG CTTTTATAGCA - +4 hocomoco__NANOG_HUMAN.H11MO.1.B 7 0.815247 19935.2 1 4 CACCTG GAGCCATCAAG + +4 taipale__HOXA13_full_NCTCGTAAAAN -2 0.815247 19935.2 1 4 CACCTG TCTCGTAAAAA + +4 taipale_cyt_meth__JDP2_NRTGASTCAYN_FL_meth-cnc-Jra-kay-Mef2 7 0.815247 19935.2 1 4 CACCTG CATGAGTCATG + +4 cisbp__M5547-Abd-B 7 0.815247 19935.2 1 4 CACCTG ATTTTACGACC - +4 cisbp__M5549-Abd-B-cad 7 0.815247 19935.2 1 4 CACCTG ATTTTACGACC - +4 hocomoco__HME2_HUMAN.H11MO.0.D-E5-ems-en-inv-pb-zen2 7 0.815247 19935.2 1 4 CACCTG CCCTAATTACC - +4 predrem__nrMotif156-fkh 7 0.815247 19935.2 1 4 CACCTG AAAAACAAACA - +4 taipale__HOXC11_DBD_NGTCGTWAAAN-Abd-B 7 0.815247 19935.2 1 4 CACCTG ATTTTACGACC - +4 taipale__HOXC11_full_NGTCGTWAAAN-Abd-B-cad 7 0.815247 19935.2 1 4 CACCTG ATTTTACGACC - +4 taipale_cyt_meth__CDX4_NGYMATAAAAN_FL_repr-Abd-B-cad-eve 7 0.815247 19935.2 1 4 CACCTG GTTTTATTGCC - +4 transfac_public__M00174-Jra-kay-Mef2-mor-nej -2 0.815247 19935.2 1 4 CACCTG ACTGAGTCATC - +4 hocomoco__BCL6B_HUMAN.H11MO.0.D -3 0.815247 19935.2 1 3 CACCTG CTAGAAAGCAT - +4 hdpi__RBM17-Spf45 0 0.81599 19953.4 1 5 CACCTG AGCCC - +4 hdpi__CDK2AP1-CDK2AP1 -2 0.81599 19953.4 1 4 CACCTG CCATT - +4 jaspar__MA0381.1 0 0.816114 19956.4 1 6 CACCTG GGCCAT + +4 cisbp__M2186 0 0.816114 19956.4 1 6 CACCTG GGCCAT - +4 yetfasco__YHR206W_583 0 0.816114 19956.4 1 6 CACCTG GGCCAT - +4 hdpi__CCDC25-CG4593 1 0.816114 19956.4 1 5 CACCTG CAATTT - +4 hdpi__UTP18-wcd 1 0.816114 19956.4 1 5 CACCTG TTGCAG - +4 cisbp__M4699-Hnf4 2 0.816114 19956.4 1 4 CACCTG TGGACT + +4 flyfactorsurvey__Hth_SOLEXA_FBgn0001235-hth 2 0.816114 19956.4 1 4 CACCTG TTGACA + +4 swissregulon__hs__YY1.p2-pho-phol 2 0.816114 19956.4 1 4 CACCTG GCCATC + +4 cisbp__M2059-achi-hth-vis -3 0.816114 19956.4 1 3 CACCTG CTGTCA - +4 cisbp__M2039-lbe 4 0.816114 19956.4 1 2 CACCTG TAACTA + +4 jaspar__MA0231.1-lbe 4 0.816114 19956.4 1 2 CACCTG TAACTA + +4 cisbp__M0961-B-H1-B-H2-unpg 1 0.816368 19962.6 1 6 CACCTG CTAATTGGT + +4 cisbp__M1252-Hsf 3 0.816368 19962.6 1 6 CACCTG ATGTTCCAT + +4 cisbp__M1761 2 0.816368 19962.6 1 6 CACCTG TTAGCCGAG + +4 cisbp__M1905-Sox15 0 0.816368 19962.6 1 6 CACCTG TTCATTGTC + +4 cisbp__M6153-Atf6-CrebB 2 0.816368 19962.6 1 6 CACCTG GTGACGCCA + +4 cisbp__M6466-Dad-Mad-Med-Smox 0 0.816368 19962.6 1 6 CACCTG TGTCTGGCC + +4 fantom__motif122_TACAAYGGM 2 0.816368 19962.6 1 6 CACCTG TACAACGGA + +4 predrem__nrMotif1883 0 0.816368 19962.6 1 6 CACCTG TGCTTATTG + +4 predrem__nrMotif2021 3 0.816368 19962.6 1 6 CACCTG CTTCACAGA + +4 predrem__nrMotif2382 3 0.816368 19962.6 1 6 CACCTG CTGTGCCCG + +4 predrem__nrMotif592 1 0.816368 19962.6 1 6 CACCTG TGACTTGAA + +4 predrem__nrMotif756 1 0.816368 19962.6 1 6 CACCTG TTTCCTAAC + +4 scertf__zhu.LYS14 3 0.816368 19962.6 1 6 CACCTG AAATTCCGG + +4 stark__CKCAKCWCT-Sry-beta 2 0.816368 19962.6 1 6 CACCTG CGCAGCACT + +4 transfac_pro__M04860-usp 3 0.816368 19962.6 1 6 CACCTG TTTCACTTC + +4 cisbp__M0286 1 0.816368 19962.6 1 6 CACCTG TAGCGCCAT - +4 cisbp__M0586-ct-onecut 1 0.816368 19962.6 1 6 CACCTG TTATCGATT - +4 jaspar__MA0921.1-ct-onecut 1 0.816368 19962.6 1 6 CACCTG TTATCGATT - +4 predrem__nrMotif1512 0 0.816368 19962.6 1 6 CACCTG TGCCTTGCT - +4 predrem__nrMotif2328 0 0.816368 19962.6 1 6 CACCTG AGACTGCCA - +4 stark__AACWAATTR 0 0.816368 19962.6 1 6 CACCTG CAATTAGTT - +4 cisbp__M0054 4 0.816368 19962.6 1 5 CACCTG TGCACACAC + +4 cisbp__M0105 -1 0.816368 19962.6 1 5 CACCTG TTTTAATTG + +4 cisbp__M4202 4 0.816368 19962.6 1 5 CACCTG ATTTTTCCG + +4 cisbp__M4791-cad -1 0.816368 19962.6 1 5 CACCTG ATCATAAAG + +4 predrem__nrMotif2655 4 0.816368 19962.6 1 5 CACCTG CGCCCACAC + +4 predrem__nrMotif601 -1 0.816368 19962.6 1 5 CACCTG TCTTTGGCA + +4 transfac_pro__M01644 4 0.816368 19962.6 1 5 CACCTG ATTTTTCCG + +4 jaspar__MA0294.1 4 0.816368 19962.6 1 5 CACCTG ATTTTTCCG - +4 predrem__nrMotif1084 4 0.816368 19962.6 1 5 CACCTG AACCCAGCA - +4 predrem__nrMotif527 -1 0.816368 19962.6 1 5 CACCTG GGCTTGCAT - +4 swissregulon__sacCer__EDS1 4 0.816368 19962.6 1 5 CACCTG ATTTTTCCG - +4 taipale_cyt_meth__LEF1_ASATCAAAS_FL_meth-pan 4 0.816368 19962.6 1 5 CACCTG CTTTGATCT - +4 transfac_pro__M04752-vtd -1 0.816368 19962.6 1 5 CACCTG CCCTCTTGT - +4 transfac_pro__M04905-E2f2 4 0.816368 19962.6 1 5 CACCTG TTCAAATCT - +4 predrem__nrMotif247 5 0.816368 19962.6 1 4 CACCTG TGAATTTCC + +4 predrem__nrMotif441 5 0.816368 19962.6 1 4 CACCTG AAATACACA + +4 predrem__nrMotif1314 5 0.816368 19962.6 1 4 CACCTG AGAGACACA - +4 swissregulon__sacCer__STP2 5 0.816368 19962.6 1 4 CACCTG TGCGGCGCC - +4 transfac_pro__M07765-B-H1-B-H2-CG11085-Dr-en-inv-slou-unpg 5 0.816368 19962.6 1 4 CACCTG GCAATTAGC - +4 predrem__nrMotif1415 -3 0.816368 19962.6 1 3 CACCTG CTTGTGAAA + +4 predrem__nrMotif305 -3 0.816368 19962.6 1 3 CACCTG CTTCAAAAT + +4 predrem__nrMotif630 -3 0.816368 19962.6 1 3 CACCTG CTTTTGAAA + +4 predrem__nrMotif727 -3 0.816368 19962.6 1 3 CACCTG CTTGACTCT + +4 predrem__nrMotif1010 -3 0.816368 19962.6 1 3 CACCTG CTTTTAGAA - +4 predrem__nrMotif620 -3 0.816368 19962.6 1 3 CACCTG CTTGTTTCT - +4 transfac_public__M00199-Jra-kay-Stat92E -3 0.816368 19962.6 1 3 CACCTG CTGACTCAT - +4 taipale_cyt_meth__ZNF76_NYYWCCCAYAATGCANYGCGN_eDBD 2 0.817827 19998.3 1 6 CACCTG CCTACCCACAATGCACCGCGC + +4 transfac_pro__M01528-CG12054 15 0.817827 19998.3 1 6 CACCTG ATTGAAAAAAATTTTCTACGG + +4 transfac_pro__M05259 10 0.817827 19998.3 1 6 CACCTG GGGGGGTCTCGGCCTCCTTCC + +4 cisbp__M2183-CG12054 15 0.817827 19998.3 1 6 CACCTG ATTGAAAAAAATTTTCTACGG - +4 transfac_pro__M01556 11 0.817827 19998.3 1 6 CACCTG TACGGGCGCCACACTTTGAGA - +4 taipale_cyt_meth__ZNF12_GGKSMTRCTCGTTATAGCRNN_eDBD_meth 17 0.817827 19998.3 1 4 CACCTG TACGCTATAACGAGCATCCCC - +4 cisbp__M0352-GATAe-grn-Jra-kay-Myc-nej-pnr-Stat92E 3 0.818025 20003.2 1 6 CACCTG TATGACTCAT + +4 cisbp__M0723-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fd96Ca-fd96Cb-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.818025 20003.2 1 6 CACCTG ATGTAAACAA + +4 cisbp__M1065-abd-A-al-Antp-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-dve-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-PHDP-Pph13-repo-ro-Rx-Scr-slou-unc-4-un 1 0.818025 20003.2 1 6 CACCTG GTTAATTAAC + +4 cisbp__M1947 1 0.818025 20003.2 1 6 CACCTG ACTTCTTATT + +4 jaspar__MA0127.1 1 0.818025 20003.2 1 6 CACCTG ACTTCTTATT + +4 predrem__nrMotif166 0 0.818025 20003.2 1 6 CACCTG TTCTTGATTT + +4 scertf__spivak.BAS1-Myb-Pbp95 3 0.818025 20003.2 1 6 CACCTG TGACTCTGGC + +4 taipale_cyt_meth__SMAD5_YGTCTAGACA_eDBD-Mad-Smox 0 0.818025 20003.2 1 6 CACCTG TGTCTAGACA + +4 cisbp__M1056-nub-pdm2-vvl 2 0.818025 20003.2 1 6 CACCTG AATTAATTAT - +4 hdpi__LRRFIP1-CG8578 2 0.818025 20003.2 1 6 CACCTG ACTTACTGAA - +4 hocomoco__NFAC1_HUMAN.H11MO.1.B-CG5641-Jra-NFAT-kay 3 0.818025 20003.2 1 6 CACCTG TTTTTCCATT - +4 scertf__harbison.STB1 3 0.818025 20003.2 1 6 CACCTG TTTCGCGTTT - +4 taipale__HOXD8_DBD_NNTAATTANN-Awh-CG18599-ftz-nub-pb-pdm2-Vsx1-Vsx2 1 0.818025 20003.2 1 6 CACCTG GCTAATTAGC - +4 transfac_pro__M02117-Stat92E 1 0.818025 20003.2 1 6 CACCTG TTTCCTAGAA - +4 cisbp__M1617 5 0.818025 20003.2 1 5 CACCTG TCTGAAACAC + +4 cisbp__M5693-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.818025 20003.2 1 5 CACCTG ACCATATGTT + +4 taipale__OLIG3_DBD_AMCATATGKT-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.818025 20003.2 1 5 CACCTG ACCATATGTT + +4 taipale_cyt_meth__OLIG2_AMCATATGKT_eDBD_meth-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.818025 20003.2 1 5 CACCTG ACCATATGGT + +4 cisbp__M0845 -1 0.818025 20003.2 1 5 CACCTG TAATGATTGG - +4 cisbp__M5297-B-H1-B-H2-NK7.1 -1 0.818025 20003.2 1 5 CACCTG ACCGTTTAGC - +4 hocomoco__HXD9_HUMAN.H11MO.0.D-Abd-B-Dbx-cad 5 0.818025 20003.2 1 5 CACCTG TAATTAAACT - +4 predrem__nrMotif1730 5 0.818025 20003.2 1 5 CACCTG TTTGGAACAT - +4 predrem__nrMotif548 5 0.818025 20003.2 1 5 CACCTG CAGCCCGCCC - +4 transfac_pro__M07361 -1 0.818025 20003.2 1 5 CACCTG CCCTCCCCAC - +4 cisbp__M6317-bon-cnc-Dif-dl-foxo-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-NFAT-pan-pnr-Stat92E 6 0.818025 20003.2 1 4 CACCTG ATGACTCATC + +4 hocomoco__E2F2_HUMAN.H11MO.0.B-E2f1-eve 6 0.818025 20003.2 1 4 CACCTG GGCGCGAAAC + +4 homer__GGCCATTAAC_Nanog-Antp-Scr-Ubx-abd-A-pb 6 0.818025 20003.2 1 4 CACCTG GGCCATTAAC + +4 taipale__EN2_DBD_NNYAATTANN-al-CG32532-CG34367-CG4328-en-inv-Lim3-lms-Lmx1a-OdsH-repo-unc-4-Vsx2 6 0.818025 20003.2 1 4 CACCTG TCCAATTAAC + +4 taipale_cyt_meth__HOXA6_NGYAATTANN_eDBD_meth-abd-A-ap-bsh-CG32532-CG9876-Dll-E5-ems-eve-ftz-HGTX-lms-OdsH-slou-Ubx-unpg-Vsx1 6 0.818025 20003.2 1 4 CACCTG GTTAATTACC - +4 taipale_tf_pairs__HOXA3_NSTAATTANN_HT 6 0.818025 20003.2 1 4 CACCTG GTTAATTACC - +4 taipale_cyt_meth__SREBF2_ATCACGCCAY_eDBD-SREBP 7 0.818025 20003.2 1 3 CACCTG ATCACGCCAC + +4 yetfasco__YPL089C_419-Mef2 -3 0.818025 20003.2 1 3 CACCTG CTATTTTTAG + +4 transfac_pro__M06099 7 0.818025 20003.2 1 3 CACCTG TCTTTACAAC - +4 cisbp__M6428-CG9650-nej-nub-pan-pdm2-SoxN-vvl 3 0.818976 20026.4 1 6 CACCTG ATTTGCATAACAAAGG + +4 taipale_cyt_meth__ZNF174_NGNCRATCACTYGNCN_eDBD_repr 7 0.818976 20026.4 1 6 CACCTG GGCCGATCACTTGCCA + +4 transfac_pro__M01147-dmrt11E-dmrt93B-dmrt99B-dsx 8 0.818976 20026.4 1 6 CACCTG CAAATTGATACATTGT + +4 transfac_pro__M01340 4 0.818976 20026.4 1 6 CACCTG AAAGTAATTAGTGAAT + +4 transfac_pro__M01468-bsh-btn-Dll 10 0.818976 20026.4 1 6 CACCTG GGAATAATTACCTCAG + +4 transfac_pro__M02811-Ets98B 1 0.818976 20026.4 1 6 CACCTG GTACATCCGGATTTTT + +4 transfac_pro__M02814-Tbp 10 0.818976 20026.4 1 6 CACCTG TCTTTATATATAAATA + +4 transfac_pro__M02942 9 0.818976 20026.4 1 6 CACCTG CGAAGCACACAAAATA + +4 transfac_public__M00171-Adf1 10 0.818976 20026.4 1 6 CACCTG CCGCCGCTGCCGCCGG + +4 cisbp__M4092-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-crc-kay 10 0.818976 20026.4 1 6 CACCTG GGGATGACGTCATCGG - +4 hocomoco__PO5F1_HUMAN.H11MO.0.A-CG9650-SoxN-nej-nub-pan-pdm2-vvl 3 0.818976 20026.4 1 6 CACCTG ATTTGCATAACAAAGG - +4 taipale_tf_pairs__POU2F1_EOMES_RGTGTNNNAATATKNN_CAP_repr-nub-pdm2 10 0.818976 20026.4 1 6 CACCTG GGAATATTCTAACACC - +4 transfac_pro__M00391 6 0.818976 20026.4 1 6 CACCTG GTCGGCGTGCTGCGAT - +4 transfac_pro__M01349-abd-A-E5-ems-en-eve-exex-inv-Lim3-pb-Ubx 2 0.818976 20026.4 1 6 CACCTG CGCCACTAATTAGTAC - +4 transfac_public__M00036-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 10 0.818976 20026.4 1 6 CACCTG GGGATGACGTCATCGG - +4 taipale_cyt_meth__PAX7_NSGTCACGSNNRTTAN_FL_meth-gsb-gsb-n-Poxn-prd 11 0.818976 20026.4 1 5 CACCTG TTAATAAGCGTGACGA - +4 taipale_cyt_meth__ZNF274_NRTRTGAGTTCTCRYN_eDBD 12 0.818976 20026.4 1 4 CACCTG AGCGAGAACTCATACC - +4 transfac_pro__M06882-CG17829 1 0.819705 20044.2 1 6 CACCTG TGACGTTGGTTCGAATGC + +4 taipale_cyt_meth__POU3F2_TAATTNNNNNNNNAATTA_eDBD_repr-vvl 4 0.819705 20044.2 1 6 CACCTG TAATTAGTATGCTAATTA - +4 transfac_pro__M00326-Poxm 1 0.819705 20044.2 1 6 CACCTG ATATCTAGAGCGGAACGG - +4 transfac_pro__M01600-CrebA-CrebB-Jra-kay 1 0.819705 20044.2 1 6 CACCTG GCCCATGACGTCATATGT - +4 transfac_pro__M05477 4 0.819705 20044.2 1 6 CACCTG GCAATCCCTTAGTCGCAT - +4 transfac_pro__M05817 8 0.819705 20044.2 1 6 CACCTG CCAGTCACGACCAACCCC - +4 taipale_tf_pairs__E2F1_ELK1_SGCGCNNNNNNNNNNCGGAAGN_CAP_repr-E2f1 8 0.819807 20046.7 1 6 CACCTG ACTTCCGGTCCAAAAGCGCGCC - +4 tfdimers__MD00054-cad 14 0.82086 20072.5 1 6 CACCTG TTTTTTTATTTATTTGCATTTTTTT - +4 tfdimers__MD00079-E2f1-foxo 9 0.82086 20072.5 1 6 CACCTG AAAAAACTCAATCTGAAAGTAAAAA - +4 transfac_pro__M01002-Deaf1 12 0.82086 20072.5 1 6 CACCTG ACATCCCGGAAATACCCGAATCCGC - +4 tfdimers__MD00561 14 0.820923 20074 1 6 CACCTG TTTTTTTAATCCTAAATTTAATT + +4 tfdimers__MD00012-pho-phol 3 0.820923 20074 1 6 CACCTG TTTTTACTTCCCCATTTTTTTTT - +4 hocomoco__Z354A_HUMAN.H11MO.0.C 12 0.821254 20082.1 1 6 CACCTG ATTTAGTCCATTTACATTTAATGT + +4 tfdimers__MD00191 11 0.821254 20082.1 1 6 CACCTG CCTTCTCCAAATCCCTTCTCCTCC + +4 transfac_pro__M04815-bi-egg-Hcf-mor-Six4 3 0.821254 20082.1 1 6 CACCTG GACTACAATTCCCAGAATGCCCCG - +4 hocomoco__ZN582_HUMAN.H11MO.0.C-Iswi-crol-nub-pdm2 20 0.821254 20082.1 1 4 CACCTG CGAATGGAATCGAATGCAATCAAC + +4 cisbp__M4991-gt 4 0.821516 20088.5 1 6 CACCTG TTATGACGTAAT + +4 cisbp__M5611-maf-S-tj 4 0.821516 20088.5 1 6 CACCTG AAAATTGCTGAC + +4 homer__GYCATCMATCAT_HOXA2 6 0.821516 20088.5 1 6 CACCTG GTCATCAATCAT + +4 neph__UW.Motif.0411-Stat92E 0 0.821516 20088.5 1 6 CACCTG CATTTCTTAGAA + +4 taipale__MAFK_full_NNNNNTGCTGAN-maf-S-tj 4 0.821516 20088.5 1 6 CACCTG AAAATTGCTGAC + +4 taipale_cyt_meth__FOXC2_NYAAAYAAACAN_eDBD_meth-croc-fd59A-slp1 6 0.821516 20088.5 1 6 CACCTG GTAAACAAACAT + +4 taipale_cyt_meth__POU2F3_NYATGCGCATRN_eDBD_meth-nub-pdm2-vvl 5 0.821516 20088.5 1 6 CACCTG ATATGCGCATAT + +4 tiffin__TIFDMEM0000030 3 0.821516 20088.5 1 6 CACCTG TTTTATATTTAT + +4 transfac_pro__M00672-CG7786-gt-Pdp1 5 0.821516 20088.5 1 6 CACCTG ATGTTTATATAA + +4 transfac_pro__M05694 6 0.821516 20088.5 1 6 CACCTG TGGGGCGACCGA + +4 hocomoco__BARX1_MOUSE.H11MO.0.C-ftz 1 0.821516 20088.5 1 6 CACCTG AAAACAATTAAA - +4 hocomoco__MEIS1_HUMAN.H11MO.0.A-cad-eve 6 0.821516 20088.5 1 6 CACCTG GCCATAAATCAT - +4 hocomoco__RAX2_HUMAN.H11MO.0.D-Awh-C15-CG9876-CG11294-CG32532-CG34367-Drgx-E5-HHEX-Lim1-Lim3-OdsH-Optix-Pph13-Rx-Traf4-al-ap-bsh-ems-en-eve-hbn-otp-repo-ro-unc-4-unpg 1 0.821516 20088.5 1 6 CACCTG TAATTTAATTAG - +4 homer__AAAGRGGAAGTG_SpiB-CG9650-Dif-dl-ebi-nej-sv 0 0.821516 20088.5 1 6 CACCTG CACTTCCTCTTT - +4 taipale_cyt_meth__POU3F4_NATTATGCATRN_eDBD-vvl 3 0.821516 20088.5 1 6 CACCTG GCTTGCATAATG - +4 tiffin__TIFDMEM0000048 6 0.821516 20088.5 1 6 CACCTG TGTTTACAATTT - +4 transfac_pro__M05522 6 0.821516 20088.5 1 6 CACCTG CCCCCCCCCCAA - +4 transfac_pro__M05839-CG10321-CG8089 1 0.821516 20088.5 1 6 CACCTG TCTCTTGCCCAG - +4 transfac_pro__M06724 2 0.821516 20088.5 1 6 CACCTG GCGACCAAACAA - +4 transfac_pro__M06731 6 0.821516 20088.5 1 6 CACCTG GCACCATGCCCG - +4 transfac_pro__M07615-brm-btd-CG42741-CTCF-dar1-E(z)-RpII215-Spps-sr-Stat92E-sv 2 0.821516 20088.5 1 6 CACCTG CGGCCCCGCCCC - +4 transfac_pro__M07850-Dll-dve-nub-pdm2-vvl 5 0.821516 20088.5 1 6 CACCTG TAATTTGCATAA - +4 transfac_public__M00087 3 0.821516 20088.5 1 6 CACCTG GTATTCCCAAAC - +4 hocomoco__FOS_MOUSE.H11MO.0.A-CoRest-Jra-Mef2-Myc-Stat92E-bon-cnc-kay-mor-nej-pan 7 0.821516 20088.5 1 5 CACCTG GATGACTCATCC + +4 cisbp__M6476-Sox14 -1 0.821516 20088.5 1 5 CACCTG CGCTTTGTTCTC - +4 transfac_pro__M05994-CG2120 7 0.821516 20088.5 1 5 CACCTG TCGTTTTTACGC - +4 transfac_pro__M06000-CG2120 7 0.821516 20088.5 1 5 CACCTG TATCTTTTACAG - +4 transfac_pro__M06053 7 0.821516 20088.5 1 5 CACCTG GCGTCTTCCCCT - +4 transfac_pro__M06334 7 0.821516 20088.5 1 5 CACCTG TGTTTTTTAACT - +4 transfac_pro__M06462 7 0.821516 20088.5 1 5 CACCTG CCATCAAGAACA - +4 transfac_pro__M06668 7 0.821516 20088.5 1 5 CACCTG TTTGTTGCCCCA - +4 transfac_pro__M07888-Rel 7 0.821516 20088.5 1 5 CACCTG GGGGGTTCCCCG - +4 swissregulon__hs__CEBPA_B_DDIT3.p2-nej 8 0.821516 20088.5 1 4 CACCTG TGATGCAATCCC + +4 taipale_cyt_meth__SP9_NCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 8 0.821516 20088.5 1 4 CACCTG GCCACGCCCACC + +4 transfac_pro__M05679 -2 0.821516 20088.5 1 4 CACCTG TCTGGCCCCCCA - +4 transfac_pro__M05767 8 0.821516 20088.5 1 4 CACCTG TCTTGTTAAACT - +4 transfac_pro__M06120 8 0.821516 20088.5 1 4 CACCTG TATTCCGCCACG - +4 tfdimers__MD00006-fkh 24 0.821964 20099.5 1 6 CACCTG AAAAAAAAAAAGTAAACAAAAAAGAACATATTAA + +4 cisbp__M0063-CrebB-Jra 1 0.822561 20114.1 1 6 CACCTG TGACATCA + +4 cisbp__M0529 1 0.822561 20114.1 1 6 CACCTG CTAGCGCA + +4 cisbp__M0848 2 0.822561 20114.1 1 6 CACCTG CCAATCAT + +4 cisbp__M1000-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ey-gsb-gsb-n-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-PHDP-Pph13-prd-repo-ro- 1 0.822561 20114.1 1 6 CACCTG TTAATTAG + +4 cisbp__M1945-B-H1-B-H2-bsh-C15-CG34367-Dll-Dr-E5-ems-en-eve-exex-inv-lab-slou-Ubx-unpg 0 0.822561 20114.1 1 6 CACCTG TAATTGGT + +4 elemento__ATGGCCTC 2 0.822561 20114.1 1 6 CACCTG ATGGCCTC + +4 elemento__TCGAACTC 2 0.822561 20114.1 1 6 CACCTG TCGAACTC + +4 elemento__TTGGCCTC 2 0.822561 20114.1 1 6 CACCTG TTGGCCTC + +4 flyfactorsurvey__lola-PO_SANGER_5_FBgn0005630-lola 0 0.822561 20114.1 1 6 CACCTG CGCCCAAA + +4 hocomoco__HXD4_HUMAN.H11MO.0.D-Dfd 1 0.822561 20114.1 1 6 CACCTG TTAATTGT + +4 predrem__nrMotif658 2 0.822561 20114.1 1 6 CACCTG TTTACTCA + +4 taipale_cyt_meth__HOXB7_RTCGTTAN_FL_meth-abd-A-btn-Dll-Ubx 0 0.822561 20114.1 1 6 CACCTG GTCGTTAA + +4 taipale_cyt_meth__HOXC8_RTCGTTAN_FL_meth-abd-A-Antp-btn-Dll-Scr-Ubx 0 0.822561 20114.1 1 6 CACCTG GTCGTTAA + +4 transfac_pro__M03815-kay 1 0.822561 20114.1 1 6 CACCTG TGACTCAG + +4 transfac_pro__M04623-Gsc-oc-Ptx1 2 0.822561 20114.1 1 6 CACCTG TTAATCCC + +4 transfac_pro__M07804-al-Awh-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ind-inv-lbe-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.822561 20114.1 1 6 CACCTG CCAATTAG + +4 transfac_pro__M07820-bcd-Gsc-oc-Ptx1 2 0.822561 20114.1 1 6 CACCTG TTAATCCC + +4 yetfasco__YFL021W_962-GATAd-GATAe-grn-pnr-srp 1 0.822561 20114.1 1 6 CACCTG TTATCAAA + +4 cisbp__M0878 0 0.822561 20114.1 1 6 CACCTG TATATTAC - +4 cisbp__M4270-GATAd-GATAe-grn-pnr-srp 1 0.822561 20114.1 1 6 CACCTG TTATCAAA - +4 cisbp__M5606-al-CG11294-CG15696-CG34367-CG4328-Dll-Drgx-en-exex-hbn-HGTX-inv-Lim1-Lim3-Lmx1a-OdsH-repo-unc-4-Vsx2 1 0.822561 20114.1 1 6 CACCTG CTAATTAA - +4 taipale_cyt_meth__RHOXF1_NGGATCAN_FL_repr 2 0.822561 20114.1 1 6 CACCTG TTGATCCC - +4 transfac_pro__M07839-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lbe-Lim3-lms-OdsH-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.822561 20114.1 1 6 CACCTG CTAATTGG - +4 cisbp__M0339 3 0.822561 20114.1 1 5 CACCTG TATTTCAT + +4 cisbp__M1731 -1 0.822561 20114.1 1 5 CACCTG CCCGCACG + +4 predrem__nrMotif1047 3 0.822561 20114.1 1 5 CACCTG CAGCCCAT + +4 predrem__nrMotif1824 3 0.822561 20114.1 1 5 CACCTG TGAGACAT + +4 predrem__nrMotif692 3 0.822561 20114.1 1 5 CACCTG TGCAGACT + +4 transfac_pro__M01252-E2f1 3 0.822561 20114.1 1 5 CACCTG CGTTTCGT + +4 cisbp__M0713-aop-Atac3-bs-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -1 0.822561 20114.1 1 5 CACCTG ACTTCCGG - +4 jaspar__MA0980.1-Hcf 4 0.822561 20114.1 1 4 CACCTG GCGCCGCC + +4 cisbp__M0631 4 0.822561 20114.1 1 4 CACCTG TTGATACA - +4 cisbp__M1689 4 0.822561 20114.1 1 4 CACCTG CGTTGACT - +4 cisbp__M1815 -2 0.822561 20114.1 1 4 CACCTG CCTCGGAA - +4 hdpi__ZBTB12 4 0.822561 20114.1 1 4 CACCTG AATTTTCC - +4 homer__TTGCCAAG_NF1-halfsite-Nf1 -2 0.822561 20114.1 1 4 CACCTG CTTGGCAA - +4 jaspar__MA1080.1 4 0.822561 20114.1 1 4 CACCTG CGTTGACT - +4 swissregulon__sacCer__STP3 4 0.822561 20114.1 1 4 CACCTG GCGCTAGC - +4 elemento__ACAACAAC 5 0.822561 20114.1 1 3 CACCTG ACAACAAC + +4 elemento__CTTCATCA -3 0.822561 20114.1 1 3 CACCTG CTTCATCA + +4 elemento__CTTGCGCA -3 0.822561 20114.1 1 3 CACCTG CTTGCGCA + +4 elemento__CTTGGCCA -3 0.822561 20114.1 1 3 CACCTG CTTGGCCA + +4 taipale_cyt_meth__ESX1_YYAATTAN_eDBD-bsh-CG11294-Drgx-en-inv-Lim3-slou-Vsx1-Vsx2 5 0.822561 20114.1 1 3 CACCTG CCAATTAC + +4 transfac_pro__M03551-Jra 5 0.822561 20114.1 1 3 CACCTG TGACTCAC + +4 cisbp__M1206 -3 0.822561 20114.1 1 3 CACCTG CTTCTTAA - +4 predrem__nrMotif407 5 0.822561 20114.1 1 3 CACCTG GAGTCCAC - +4 cisbp__M6440-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG32532-CG34031-CG34367-CG9876-Dll-Dr-E5-ems-en-ftz-hbn-Hmx-inv-lbe-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou-Traf4-tup-Ubx-un 1 0.822759 20118.9 1 6 CACCTG TTAATTG + +4 hocomoco__PRRX2_HUMAN.H11MO.0.C-Antp-Awh-CG9876-CG11294-CG15696-CG32532-CG34031-CG34367-Dfd-Dll-Dr-E5-Hmx-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-exex-ftz-h 1 0.822759 20118.9 1 6 CACCTG TTAATTG + +4 hocomoco__NF2L1_HUMAN.H11MO.0.C-cnc 1 0.822759 20118.9 1 6 CACCTG AGTCATT - +4 predrem__nrMotif779 1 0.822759 20118.9 1 6 CACCTG CCCCCAT - +4 cisbp__M2216 2 0.822759 20118.9 1 5 CACCTG TATACGA + +4 hdpi__NCALD-Nca 2 0.822759 20118.9 1 5 CACCTG ATTAACG + +4 hdpi__WHSC2-Nelf-A -1 0.822759 20118.9 1 5 CACCTG ATTTGGA + +4 jaspar__MA0266.1 -1 0.822759 20118.9 1 5 CACCTG CTCTAGA + +4 jaspar__MA0411.1 2 0.822759 20118.9 1 5 CACCTG TATACGA + +4 transfac_pro__M01612 2 0.822759 20118.9 1 5 CACCTG TATACGA + +4 yetfasco__YDR213W_544 2 0.822759 20118.9 1 5 CACCTG TATACGA + +4 predrem__nrMotif1106 2 0.822759 20118.9 1 5 CACCTG CCAATTT - +4 yetfasco__YMR072W_541 -1 0.822759 20118.9 1 5 CACCTG CTCTAGA - +4 elemento__GATAAGC 3 0.822759 20118.9 1 4 CACCTG GCTTATC - +4 hdpi__FEZF2-erm 3 0.822759 20118.9 1 4 CACCTG CGCAGCC - +4 hdpi__PKM2-CG2964-CG7069-CG7362-PyK 3 0.822759 20118.9 1 4 CACCTG AATTATC - +4 cisbp__M6048-hth -3 0.822759 20118.9 1 3 CACCTG CTGTCAA + +4 elemento__CGTTGAC 4 0.822759 20118.9 1 3 CACCTG CGTTGAC + +4 elemento__TAATGAC 4 0.822759 20118.9 1 3 CACCTG TAATGAC + +4 elemento__TGATGAC 4 0.822759 20118.9 1 3 CACCTG TGATGAC + +4 predrem__nrMotif1395 -3 0.822759 20118.9 1 3 CACCTG CTCACAA + +4 cisbp__M5460-bin-croc-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.822759 20118.9 1 3 CACCTG TGTTTAC - +4 cisbp__M6019-bin-CHES-1-like-croc-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.822759 20118.9 1 3 CACCTG TGTTTAC - +4 predrem__nrMotif178 -3 0.822759 20118.9 1 3 CACCTG CTCCAAA - +4 predrem__nrMotif472 -3 0.822759 20118.9 1 3 CACCTG CTGAGTG - +4 taipale__FOXL1_full_RTAAAYA-bin-croc-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.822759 20118.9 1 3 CACCTG TGTTTAC - +4 taipale__Foxk1_DBD_RTAAACA-bin-CHES-1-like-croc-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.822759 20118.9 1 3 CACCTG TGTTTAC - +4 taipale__Meis2_DBD_NTGACAN-hth -3 0.822759 20118.9 1 3 CACCTG CTGTCAA - +4 transfac_pro__M00662 4 0.822759 20118.9 1 3 CACCTG TGCATAA - +4 hdpi__JARID1D-lid 5 0.822759 20118.9 1 2 CACCTG CTTTGCA - +4 cisbp__M2576-ovo-Poxn 5 0.822865 20121.5 1 6 CACCTG TATAGTAACAGTCCG + +4 jaspar__MA0323.1 1 0.822865 20121.5 1 6 CACCTG AAGCCGGAAGCGGGG + +4 stark__TAATTRANNTTNATG 5 0.822865 20121.5 1 6 CACCTG TAATTAAAATTAATG + +4 taipale__Zic3_DBD_GACCMCCYRMTGNGN-opa 0 0.822865 20121.5 1 6 CACCTG GACCCCCCGCTGTGC + +4 transfac_pro__M01146-dmrt93B-dmrt99B-dsx 4 0.822865 20121.5 1 6 CACCTG TTGATACATTGTTGC + +4 transfac_pro__M06943 9 0.822865 20121.5 1 6 CACCTG GTATAATTAAACCGT + +4 transfac_pro__M07483-Cfp1-CG17440-CG3347 3 0.822865 20121.5 1 6 CACCTG GTGAAACGAAAAAAA + +4 transfac_public__M00115-CrebB 8 0.822865 20121.5 1 6 CACCTG ATGACGCATACCCCC + +4 cisbp__M2128 1 0.822865 20121.5 1 6 CACCTG AAGCCGGAAGCGGGG - +4 cisbp__M4536-E2f1 9 0.822865 20121.5 1 6 CACCTG CCGCGCGCCCTCCCC - +4 flyfactorsurvey__lola-PT_SOLEXA_FBgn0005630-lola 2 0.822865 20121.5 1 6 CACCTG AACGGCTCAATACGA - +4 flyfactorsurvey__sug_SOLEXA_5_FBgn0033782-lmd-opa-sug 2 0.822865 20121.5 1 6 CACCTG CAGACCCCCCGCGGA - +4 taipale_tf_pairs__FOXJ2_HOXB13_NTTTATNRNTMAACA_CAP_repr 4 0.822865 20121.5 1 6 CACCTG TGTTTACTCATAAAA - +4 transfac_pro__M09092-pho-phol-Taf1 9 0.822865 20121.5 1 6 CACCTG CGCCGCCGCAATTTC - +4 taipale__IRF4_full_NCGAAACCGAAACYN_repr 10 0.822865 20121.5 1 5 CACCTG CCGAAACCGAAACTA + +4 taipale_tf_pairs__ETV2_HOXB13_NCCGGAANYATAAAN_CAP_repr-pnt -1 0.822865 20121.5 1 5 CACCTG ACCGGAAACATAAAC + +4 transfac_pro__M02776-cic-maf-S-tj 10 0.822865 20121.5 1 5 CACCTG TAAAAATGCTGACTT + +4 cisbp__M4607-brm-cnc-CoRest-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-Stat92E 10 0.822865 20121.5 1 5 CACCTG GAGGATGAGTCACCA - +4 flyfactorsurvey__crol-F7-16_SOLEXA_FBgn0020309-Brf-CG7368-CTCF-CoRest-E(z)-HDAC1-Nelf-E-Rbbp5-SREBP-Spt20-crol-ct-klu-l(3)neo38 10 0.822865 20121.5 1 5 CACCTG CCCCCCCCCCCACCC - +4 taipale_cyt_meth__RFX3_NGTTGCCWAGCAACN_eDBD_meth_repr-CG9727-Rfx 11 0.822865 20121.5 1 4 CACCTG CGTTGCCTAGCAACC + +4 flyfactorsurvey__gl_SOLEXA_F3-5-gl 12 0.822865 20121.5 1 3 CACCTG ACAAGGAAGCCCCAC - +4 predrem__nrMotif2096-CG42741-luna 4 0.824488 20161.2 1 6 CACCTG CCCCGCCCTTCCC + +4 taipale_cyt_meth__KLF13_NRCCACGCCCMYN_FL_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.824488 20161.2 1 6 CACCTG CGCCACGCCCCCC + +4 taipale_cyt_meth__SP3_NRCCMCGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.824488 20161.2 1 6 CACCTG GGCCACGCCCACC + +4 transfac_pro__M06925 2 0.824488 20161.2 1 6 CACCTG ATAATCTGATTAT + +4 hdpi__PSMC2-Rpt1 1 0.824488 20161.2 1 6 CACCTG CCCGCGCAAACGC - +4 hocomoco__MZF1_HUMAN.H11MO.0.B 5 0.824488 20161.2 1 6 CACCTG CCCAATCCCCTCC - +4 swissregulon__hs__PATZ1.p2-Spps-btd 7 0.824488 20161.2 1 6 CACCTG CGGCCCCTCCCCC - +4 taipale_cyt_meth__NRL_NWWWNTGCTGACN_FL_meth-maf-S-tj 3 0.824488 20161.2 1 6 CACCTG TGTCAGCACTTTT - +4 transfac_pro__M01212-Stat92E 2 0.824488 20161.2 1 6 CACCTG TTTTCCGGGAAAT - +4 cisbp__M4573-cnc-maf-S-tj 8 0.824488 20161.2 1 5 CACCTG TGCTGACTCAGCA + +4 transfac_pro__M01067-sens-2 -1 0.824488 20161.2 1 5 CACCTG GGCCGTGATTTCG - +4 taipale_cyt_meth__SP3_NRCCMCGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 9 0.824488 20161.2 1 4 CACCTG CGCCACGCCCACC + +4 transfac_pro__M00791-fkh-GATAe-grn-HDAC1-nej-pnr -2 0.824488 20161.2 1 4 CACCTG ACTGTTTGTTTAT - +4 predrem__nrMotif1417-CTCF-ERR-Nf-YB-SREBP-Spps-brm-btd-klu 8 0.824781 20168.4 1 6 CACCTG GTCCCCGCCCCCCC + +4 scertf__foat.DAL82 2 0.824781 20168.4 1 6 CACCTG CGAAACTTGCGCAG + +4 taipale_cyt_meth__ZBTB12_NGGCCTGCCGTCNT_eDBD_repr 1 0.824781 20168.4 1 6 CACCTG GGGCCTGCCGTCGT + +4 transfac_pro__M02107-E2f2-Nf-YA-Nf-YB-Nf-YC 8 0.824781 20168.4 1 6 CACCTG CAGCCAATCAGCGC + +4 transfac_pro__M07037 2 0.824781 20168.4 1 6 CACCTG GAATATTGCACAAT + +4 transfac_pro__M07946-seq 6 0.824781 20168.4 1 6 CACCTG AAATCATCCCCTAA + +4 cisbp__M3047 0 0.824781 20168.4 1 6 CACCTG TAATTACGCAATGT - +4 cisbp__M5400-Ets21C-Ets97D 7 0.824781 20168.4 1 6 CACCTG ACCGGATTTCCGGT - +4 cisbp__M6367-cnc-Jra-kay-maf-S 8 0.824781 20168.4 1 6 CACCTG TGCTGAGTCATGCT - +4 flyfactorsurvey__sr_SANGER_5_FBgn0003499-Spps-btd-cbt-klu-sr 7 0.824781 20168.4 1 6 CACCTG CCCCGCCCACGCAC - +4 hocomoco__FLI1_MOUSE.H11MO.0.A-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-RpII215-Sin3A-Taf1-aop-bs-lid-pnt 0 0.824781 20168.4 1 6 CACCTG CCACTTCCGGCCCC - +4 taipale_tf_pairs__TEAD4_HOXB13_RGAATGCNNRTAAA_CAP-sd 2 0.824781 20168.4 1 6 CACCTG TTTACGAGCATTCC - +4 transfac_pro__M03836-acj6-Dll-nub-pdm2-vvl 5 0.824781 20168.4 1 6 CACCTG TAATTTGCATATTA - +4 transfac_pro__M04833-CG9650-ebi-MTA1-like-nej-Stat92E-sv 8 0.824781 20168.4 1 6 CACCTG TTCACTTCCTCTTT - +4 taipale_cyt_meth__ZNF75A_NGCTTTTCCCACAN_FL_meth_repr 9 0.824781 20168.4 1 5 CACCTG AGCTTTTCCCACAC + +4 hocomoco__KLF1_HUMAN.H11MO.0.A-CG3065-CG42741-Klf15-Nf-YA-Spps-btd-cbt-dar1-hkb-luna-sr -2 0.824781 20168.4 1 4 CACCTG CCCGGCCCCGCCCC - +4 taipale__MTF1_DBD_TTTGCACACGNCAC_repr-MTF-1 11 0.824781 20168.4 1 3 CACCTG TTTGCACACGGCAC + +4 cisbp__M5158-Poxm-sv 12 0.824839 20169.8 1 6 CACCTG CAAAAGCAATCAACCGTGA + +4 factorbook__NFE2-Jra-cnc-kay-maf-S 4 0.824839 20169.8 1 6 CACCTG AAAATTGCTGAGTCATGCT + +4 cisbp__M1848-ey-Poxm-sv-toy 4 0.824839 20169.8 1 6 CACCTG GTCACGCTTGGCTGCCCTC - +4 flyfactorsurvey__Poxm_SOLEXA_5_FBgn0003129-Poxm-sv 12 0.824839 20169.8 1 6 CACCTG CAAAAGCAATCAACCGTGA - +4 hocomoco__NKX61_MOUSE.H11MO.0.A-Dr-HGTX-ind 10 0.824839 20169.8 1 6 CACCTG TAATTAAAATCCCATTAAT - +4 transfac_pro__M06913 7 0.824839 20169.8 1 6 CACCTG CATACGGCAGCCGACTACA - +4 tfdimers__MD00413 25 0.825994 20198 1 6 CACCTG AAAAAAAATTATGCAAACAAAAAAGAACAGAATAAA - +4 taipale__CUX1_DBD_ATCRATNNNNNATCRAT_repr-ct 5 0.826853 20219 1 6 CACCTG ATCGATAACTGATCGAT + +4 transfac_pro__M01364-Ptx1 10 0.826853 20219 1 6 CACCTG TGAGGGGGATTAACTAT + +4 transfac_pro__M02850 10 0.826853 20219 1 6 CACCTG GTTCAAAAAAAAAATTC + +4 transfac_pro__M05726 9 0.826853 20219 1 6 CACCTG AGCATACGGAACCCATC + +4 bergman__Eip74EF-Eip74EF-Ets21C 3 0.826853 20219 1 6 CACCTG CCTCACTTCCGGGTTCG - +4 cisbp__M6481-btd-Nf-YA-Nf-YB-Spps 11 0.826853 20219 1 6 CACCTG TTAGCCCCGCCCCCCTC - +4 hocomoco__BATF3_HUMAN.H11MO.0.B-Jra-MTA1-like-NFAT-ebi 11 0.826853 20219 1 6 CACCTG GAGTCATAATGAAACTG - +4 jaspar__MA0883.1-bcd-oc 7 0.826853 20219 1 6 CACCTG TACATTAATCCGGTTCA - +4 jaspar__MA0910.1-C15 11 0.826853 20219 1 6 CACCTG TAGCCATTAATTAATTA - +4 taipale_cyt_meth__PAX6_NYACGCNTSANYGNNYN_eDBD_meth_repr-ey-Poxm-sv-toy 10 0.826853 20219 1 6 CACCTG TGTGCAGTCATGCGTGA - +4 taipale_tf_pairs__ETV2_GSC2_RSCGGAANNNNGGATTA_CAP_repr-Gsc-pnt 1 0.826853 20219 1 6 CACCTG TAATCCGTATTTCCGGT - +4 transfac_pro__M01403-bcd-oc 7 0.826853 20219 1 6 CACCTG TACATTAATCCGGTTCA - +4 transfac_pro__M01484-bcd-Ptx1 8 0.826853 20219 1 6 CACCTG ATTGTTAATCCCTCTAA - +4 transfac_public__M00016-Eip74EF-Ets21C 3 0.826853 20219 1 6 CACCTG CCTCACTTCCGGGTTCG - +4 cisbp__M1802 2 0.827973 20246.4 1 6 CACCTG ATTTCCGTTGA + +4 cisbp__M3282-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 5 0.827973 20246.4 1 6 CACCTG ATAAACAAGCC + +4 predrem__nrMotif2358 1 0.827973 20246.4 1 6 CACCTG CCCCCCGCGCC + +4 taipale__POU2F2_DBD_NTATGCWAATN-Dll-nub-pdm2-vvl 5 0.827973 20246.4 1 6 CACCTG ATATGCAAATT + +4 taipale_cyt_meth__DUXA_TRAYNTAATCA_eDBD_meth_repr-Traf4 1 0.827973 20246.4 1 6 CACCTG TAATTTAATCA + +4 transfac_pro__M08878-brm-CTCF-sr 0 0.827973 20246.4 1 6 CACCTG CGCCCCCGCCC + +4 transfac_pro__M09206 2 0.827973 20246.4 1 6 CACCTG GGAATCTTCTA + +4 transfac_public__M00472-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 5 0.827973 20246.4 1 6 CACCTG ATAAACAAGCC + +4 flyfactorsurvey__prd_NAR_FBgn0003145-Poxn-gsb-prd 5 0.827973 20246.4 1 6 CACCTG AGCGTGACGGA - +4 hocomoco__OLIG3_HUMAN.H11MO.0.D-HLH54F-Oli-amos-ato-crp-dimm-tap-twi 0 0.827973 20246.4 1 6 CACCTG AAACATATGGT - +4 taipale_cyt_meth__MYBL2_NTAACSGTTRN_eDBD_repr 1 0.827973 20246.4 1 6 CACCTG TTAACCGTTAA - +4 taipale_tf_pairs__PBX4_HOXA10_NTCGTAAATCA_CAP_repr-exd 5 0.827973 20246.4 1 6 CACCTG TGATTTACGAC - +4 tiffin__TIFDMEM0000096 4 0.827973 20246.4 1 6 CACCTG TTGTTATCAAA - +4 transfac_pro__M00691-CrebB 1 0.827973 20246.4 1 6 CACCTG TGACGTCAGAG - +4 transfac_pro__M06569 5 0.827973 20246.4 1 6 CACCTG AATTTTCCCGG - +4 transfac_pro__M05156 6 0.827973 20246.4 1 5 CACCTG AAAATATACTG - +4 transfac_pro__M09229-Antp-Awh-CG9876-en-lab-Lim1-Lim3-OdsH-otp-repo-Scr-unc-4-unpg 6 0.827973 20246.4 1 5 CACCTG ATTAATTAACT - +4 c2h2_zfs__M3875-Aef1-CG4360 7 0.827973 20246.4 1 4 CACCTG ACAACAACAAC + +4 cisbp__M1170-Awh-CG11294-E5-Lim1-Lim3-Rx-Vsx1-ap-lab-otp-unpg-zen2 7 0.827973 20246.4 1 4 CACCTG CATTAATTACC + +4 hocomoco__CEBPA_MOUSE.H11MO.0.A-nej 7 0.827973 20246.4 1 4 CACCTG ATTGCACAACC + +4 hocomoco__CEBPZ_HUMAN.H11MO.0.D-CG7839-Nf-YA-Nf-YB-Nf-YC -2 0.827973 20246.4 1 4 CACCTG GCTGATTGGCT + +4 transfac_pro__M05594 -2 0.827973 20246.4 1 4 CACCTG CGTTTGTAAAC - +4 transfac_pro__M06989 7 0.827973 20246.4 1 4 CACCTG TTAATATTACG - +4 transfac_public__M00173-Jra-kay 7 0.827973 20246.4 1 4 CACCTG TCTGAGTCACC - +4 swissregulon__hs__PITX1..3.p2-Ptx1 -3 0.827973 20246.4 1 3 CACCTG CTGGGATTACA - +4 transfac_pro__M05083-Myb 8 0.827973 20246.4 1 3 CACCTG AACTCCGTTAC - +4 transfac_pro__M05593 8 0.827973 20246.4 1 3 CACCTG CATTTGTAAAC - +4 dbcorrdb__CHD1__ENCSR000EFC_1__m3-Chd1 2 0.828793 20266.5 1 6 CACCTG TCCCGCTCGATGAAAAACGG + +4 dbcorrdb__EZH2__ENCSR000ARK_1__m3-E(z) 4 0.828793 20266.5 1 6 CACCTG GGTCCGCCTCTCGGAGTTCG + +4 dbcorrdb__FOS__ENCSR000DOO_1__m1-Jra-kay-maf-S-mor-Stat92E 6 0.828793 20266.5 1 6 CACCTG ATGAGTCATCATTTTTTTAT + +4 dbcorrdb__JUND__ENCSR000EDH_1__m1-Jra-kay-maf-S-Myc-nej-Stat92E 13 0.828793 20266.5 1 6 CACCTG AAAAATGATGACTCATCCTT + +4 dbcorrdb__JUN__ENCSR000EDG_1__m1-GATAe-grn-Jra-kay-Myc-nej-pnr-Stat92E 10 0.828793 20266.5 1 6 CACCTG AAGGATGAGTCATCCTTTTA + +4 dbcorrdb__NANOG__ENCSR000BMT_1__m1-CG9650-Mad-nej-pan-SoxN 2 0.828793 20266.5 1 6 CACCTG TTTGCATAACAAAGGCCTCC + +4 dbcorrdb__PAX5__ENCSR000BHJ_1__m2-CG9650-Dif-dl-ebi-nej-Stat92E-sv 5 0.828793 20266.5 1 6 CACCTG GCTTTCACTTCCTCTTTGAC + +4 dbcorrdb__POLR2A__ENCSR000DMK_1__m1-brm-bs-CrebB-CTCF-Eip74EF-ERR-E(z)-Myc-RpII215-Sin3A-SREBP-Taf1 10 0.828793 20266.5 1 6 CACCTG GCCGCCGCGGCGCTTCCGCC + +4 dbcorrdb__POLR2A__ENCSR000EUU_1__m3-RpII215-TfIIB-TfIIFalpha 13 0.828793 20266.5 1 6 CACCTG GCGCCGCGGCCTATATACGC + +4 dbcorrdb__SETDB1__ENCSR000EYD_1__m1-egg 3 0.828793 20266.5 1 6 CACCTG TCATAATGCAGAAAAACCAT + +4 dbcorrdb__SP2__ENCSR000BQG_1__m1-btd-E2f2-kay-Nf-YA-Nf-YB-Spps 5 0.828793 20266.5 1 6 CACCTG CGGCCGACCAATGAGACGCG + +4 dbcorrdb__SREBF1__ENCSR000DYU_1__m4-Brf-brm-HDAC1-Nelf-E-Rbbp5-Spt20-SREBP 2 0.828793 20266.5 1 6 CACCTG CGCCCCTCCCCCCGCCGCGC + +4 dbcorrdb__STAT3__ENCSR000DOX_1__m3-aop-Stat92E 6 0.828793 20266.5 1 6 CACCTG AGTCATTTCCCGGAAGTGTT + +4 dbcorrdb__SUPT20H__ENCSR000DNP_1__m3-Spt20 13 0.828793 20266.5 1 6 CACCTG ATTAATATAACAAGAACTAA + +4 dbcorrdb__YY1__ENCSR000EWF_1__m2-pho-phol-RpII215 4 0.828793 20266.5 1 6 CACCTG GCGGGAAGTGGCGCAAGCGC + +4 taipale_cyt_meth__RUNX2_NWAACCACANNNACCACAAN_eDBD_meth_repr-lz-run-RunxA-RunxB 2 0.828793 20266.5 1 6 CACCTG CAAACCACAAAAACCACAAA + +4 taipale_cyt_meth__ZSCAN9_NRGGATAAGATAAGAANCMN_eDBD_meth-GATAe-grn-ham-pnr 14 0.828793 20266.5 1 6 CACCTG AAGGATAAGATAAGAATCAC + +4 transfac_pro__M01242-MTF-1 8 0.828793 20266.5 1 6 CACCTG GTGTGCATAACTTTGCGCAC + +4 dbcorrdb__ATF3__ENCSR000BNU_1__m4 1 0.828793 20266.5 1 6 CACCTG CCCCCAGCCGCTGTCGCGTC - +4 dbcorrdb__CEBPB__ENCSR000BRX_1__m1-ebi-foxo-Jra-Mef2-MTA1-like-nej-NFAT-Stat92E 9 0.828793 20266.5 1 6 CACCTG GATGAGTCATATCGAAACTA - +4 dbcorrdb__EZH2__ENCSR000ARH_1__m1-E(z) 13 0.828793 20266.5 1 6 CACCTG CCCCGGCTTTTGCCGCGTTC - +4 dbcorrdb__EZH2__ENCSR000ARH_1__m7-E(z) 3 0.828793 20266.5 1 6 CACCTG CACTCCCGGATTGTAGGGCG - +4 dbcorrdb__GTF2F1__ENCSR000ECZ_1__m2-TfIIFalpha 5 0.828793 20266.5 1 6 CACCTG GCTTACGCATGACGCAAGCG - +4 dbcorrdb__GTF3C2__ENCSR000DOD_1__m3 12 0.828793 20266.5 1 6 CACCTG GCTGGACTCCTAATCCAAAG - +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m2-RpII215 1 0.828793 20266.5 1 6 CACCTG CCGGCTGTTTGTCGCCACGG - +4 dbcorrdb__POLR2A__ENCSR000EBK_1__m1-Atac3-bs-CG10431-CTCF-E2f1-Eip74EF-Ets97D-E(z)-FoxP-Hcf-lid-Max-Myc-Rbbp5-RpII215-Sin3A-Taf1 6 0.828793 20266.5 1 6 CACCTG CCGCGGCGCTTCCGCCGCCG - +4 dbcorrdb__POLR2A__ENCSR000FAW_1__m2-RpII215-Taf1 5 0.828793 20266.5 1 6 CACCTG CCGCCCGCGTGCCGCCATGT - +4 dbcorrdb__POLR2A__ENCSR000FAX_1__m1-RpII215-Taf1 5 0.828793 20266.5 1 6 CACCTG CTTTGCGCTTCCGCCGTGCT - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOV_1__m1-aop-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Sin3A 4 0.828793 20266.5 1 6 CACCTG GCGCAACCGGAAGTGACGCG - +4 dbcorrdb__SIN3A__ENCSR000BLR_1__m3-CoRest-CrebB-CycT-E(z)-Sin3A-tna 4 0.828793 20266.5 1 6 CACCTG CTGACAGCTCCGGGCGCGCC - +4 dbcorrdb__SP2__ENCSR000BNL_1__m1-btd-kay-Max-Myc-Spps 5 0.828793 20266.5 1 6 CACCTG CCGCGCCTCTCTGGCCGGCG - +4 hocomoco__IRF2_HUMAN.H11MO.0.A-Blimp-1-CG9650-MTA1-like-Stat92E-ebi-nej 1 0.828793 20266.5 1 6 CACCTG TTACTTTCACTTTCACTTTC - +4 taipale_cyt_meth__BACH2_NWWNNATGACGTCAYNNWWN_eDBD-Atf3-Atf6-cnc-crc-CrebA-CrebB-Jra-kay-Xbp1 7 0.828793 20266.5 1 6 CACCTG AAATCATGACGTCATGCTTT - +4 taipale_tf_pairs__TEAD4_ETV7_RGAATGCGGAARYNNNTCCN_CAP_repr-aop-sd 6 0.828793 20266.5 1 6 CACCTG CGGAAGTACTTCCGCATTCC - +4 transfac_pro__M01521 6 0.828793 20266.5 1 6 CACCTG TAAAATTATCTCCGATGTTA - +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m5-Su(z)12 -1 0.828793 20266.5 1 5 CACCTG GCCTGCGACTGCCGCGCGGA + +4 dbcorrdb__POLR3G__ENCSR000EHQ_1__m3-Tbp 15 0.828793 20266.5 1 5 CACCTG AGTGGTTAGAGCGTTTGACT - +4 taipale_cyt_meth__IRF3_NSGAAANSGAAASSGAAASN_FL_meth 15 0.828793 20266.5 1 5 CACCTG TGTTTCCGTTTCCCTTTCCT - +4 taipale_cyt_meth__PAX2_NSGTCACGCWTSANYGNNYN_eDBD_meth-ey-Poxm-sv-toy 15 0.828793 20266.5 1 5 CACCTG TGTGCAGTCATGCGTGACGA - +4 cisbp__M0090 2 0.828981 20271.1 1 6 CACCTG ATGACGCGT + +4 cisbp__M0274-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 2 0.828981 20271.1 1 6 CACCTG ATTGCGTAA + +4 cisbp__M1128-Ubx-abd-A 2 0.828981 20271.1 1 6 CACCTG AGCAATTAA + +4 fantom__motif85_TWNNGCSNA 2 0.828981 20271.1 1 6 CACCTG TTCCGCGGA + +4 flyfactorsurvey__lola-PD_SANGER_5_FBgn0005630-lola 2 0.828981 20271.1 1 6 CACCTG CCCCCCACT + +4 jaspar__MA0078.1-Sox15 0 0.828981 20271.1 1 6 CACCTG CTCATTGTC + +4 predrem__nrMotif1248 2 0.828981 20271.1 1 6 CACCTG CTGCCCTAG + +4 predrem__nrMotif2263 3 0.828981 20271.1 1 6 CACCTG AGACACTCA + +4 predrem__nrMotif2563 0 0.828981 20271.1 1 6 CACCTG ATGCTGACA + +4 transfac_pro__M07278-en 1 0.828981 20271.1 1 6 CACCTG TTAATTTGA + +4 cisbp__M1091-abd-A-Antp-ap-Awh-B-H1-B-H2-btn-C15-CG11294-CG18599-CG4328-CG9876-Dfd-Drgx-E5-ems-en-eve-exex-ftz-ind-inv-lab-Lim3-lms-Lmx1a-OdsH-pb-ro-Rx-Scr-slou-tup-Ubx-unpg-Vsx1-Vsx2-zen-zen2 1 0.828981 20271.1 1 6 CACCTG GGTAATTAG - +4 predrem__nrMotif1030 3 0.828981 20271.1 1 6 CACCTG CATCACAAA - +4 predrem__nrMotif1061 1 0.828981 20271.1 1 6 CACCTG TGACATTCA - +4 predrem__nrMotif1756 3 0.828981 20271.1 1 6 CACCTG GCACACTCC - +4 predrem__nrMotif2438 0 0.828981 20271.1 1 6 CACCTG TGCCCCATT - +4 hdpi__ADARB1-Adar 4 0.828981 20271.1 1 5 CACCTG GAAAATAAT + +4 hocomoco__MAFF_HUMAN.H11MO.1.B-cnc-maf-S -1 0.828981 20271.1 1 5 CACCTG TGCTGAGTC + +4 predrem__nrMotif2592 4 0.828981 20271.1 1 5 CACCTG GAGGGATCT + +4 predrem__nrMotif2003 4 0.828981 20271.1 1 5 CACCTG AATTCAGCA - +4 predrem__nrMotif204 4 0.828981 20271.1 1 5 CACCTG TGTCAGCCA - +4 predrem__nrMotif808 -1 0.828981 20271.1 1 5 CACCTG CCCCGGGAC - +4 taipale_cyt_meth__LEF1_ASATCAAAS_FL-pan 4 0.828981 20271.1 1 5 CACCTG CTTTGATCT - +4 transfac_pro__M01297 4 0.828981 20271.1 1 5 CACCTG GTTTTATTT - +4 transfac_pro__M07264-NFAT 4 0.828981 20271.1 1 5 CACCTG ATTTTTCCA - +4 predrem__nrMotif2167-Eip74EF-Sin3A -2 0.828981 20271.1 1 4 CACCTG GCTTCCGGG + +4 predrem__nrMotif591 -2 0.828981 20271.1 1 4 CACCTG CCGGCCTCC + +4 predrem__nrMotif74 -2 0.828981 20271.1 1 4 CACCTG GCTTCTCTT + +4 transfac_pro__M09212 5 0.828981 20271.1 1 4 CACCTG AAGAAAACA + +4 predrem__nrMotif1026 -2 0.828981 20271.1 1 4 CACCTG CCCGCCGCC - +4 predrem__nrMotif1852 -2 0.828981 20271.1 1 4 CACCTG CCATGGAGA - +4 predrem__nrMotif353 6 0.828981 20271.1 1 3 CACCTG CACAGCAAC + +4 predrem__nrMotif650 6 0.828981 20271.1 1 3 CACCTG GCTGCAAAC + +4 hdpi__TFE3-Mitf -3 0.828981 20271.1 1 3 CACCTG CTGTTTCCA - +4 predrem__nrMotif599 6 0.828981 20271.1 1 3 CACCTG TTCAGCAAC - +4 flyfactorsurvey__Deaf1_FlyReg_FBgn0013799-Deaf1 0 0.829698 20288.6 1 6 CACCTG TTCGTG + +4 fantom__motif25_GATCCN 1 0.829698 20288.6 1 5 CACCTG GATCCA + +4 hdpi__PIK3C3-Pi3K59F 2 0.829698 20288.6 1 4 CACCTG GAGCCC + +4 swissregulon__sacCer__ABF2-Hsf -2 0.829698 20288.6 1 4 CACCTG TCTAGA + +4 hdpi__TGIF1-achi-vis -2 0.829698 20288.6 1 4 CACCTG CCCGCA - +4 hdpi__U2AF1-U2af38 2 0.829698 20288.6 1 4 CACCTG ATTTCC - +4 transfac_pro__M07758-achi -3 0.829698 20288.6 1 3 CACCTG CTGTCA - +4 hdpi__PPP5C-PpD3 -1 0.829991 20295.8 1 5 CACCTG GCCAT - +4 hdpi__DAZAP1-Hrb27C 1 0.829991 20295.8 1 4 CACCTG TTTCC - +4 tfdimers__MD00236-E2f1-vvl 5 0.830327 20304 1 6 CACCTG AAAATTTCATTGAAAATGAAAGTAAAAA + +4 tfdimers__MD00263-pan-Stat92E 8 0.830327 20304 1 6 CACCTG TTTTTCATTTCCTTTGTTTTTTTTTTTT + +4 transfac_pro__M09063-Taf1 1 0.830327 20304 1 6 CACCTG CCGCCTCCGCCGCCACCACCGCCGCCGC + +4 cisbp__M0875 3 0.830564 20309.8 1 6 CACCTG TTATATATGT + +4 cisbp__M1340 4 0.830564 20309.8 1 6 CACCTG AGAATATTCT + +4 cisbp__M1607 4 0.830564 20309.8 1 6 CACCTG AAATTCCCAT + +4 cisbp__M1758 1 0.830564 20309.8 1 6 CACCTG TAAGCGAGGC + +4 cisbp__M3444-Hsf 2 0.830564 20309.8 1 6 CACCTG CGAATATTCT + +4 cisbp__M6291-lab 4 0.830564 20309.8 1 6 CACCTG CATCCATCAA + +4 predrem__nrMotif107 4 0.830564 20309.8 1 6 CACCTG TGCATCCATT + +4 predrem__nrMotif1557 3 0.830564 20309.8 1 6 CACCTG TGACTCTTTT + +4 predrem__nrMotif1688 0 0.830564 20309.8 1 6 CACCTG CATCCTCTGC + +4 scertf__morozov.SMP1-Mef2 1 0.830564 20309.8 1 6 CACCTG CTATATTTAG + +4 transfac_pro__M03205 4 0.830564 20309.8 1 6 CACCTG AGGCCGCCAA + +4 transfac_pro__M05043 4 0.830564 20309.8 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M05094 4 0.830564 20309.8 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M09556 4 0.830564 20309.8 1 6 CACCTG ATTTGAATTT + +4 yetfasco__YPR104C_2203-CHES-1-like-jumu 2 0.830564 20309.8 1 6 CACCTG GACGCAAAAA + +4 cisbp__M0669-E2f1 3 0.830564 20309.8 1 6 CACCTG GCGCGCCAAT - +4 cisbp__M1113 0 0.830564 20309.8 1 6 CACCTG CCAATTAAAC - +4 cisbp__M1237-dve-E5-eve-nub-pb-pdm2-vvl 3 0.830564 20309.8 1 6 CACCTG ATGTTAATTA - +4 cisbp__M5563-Awh-CG18599-ftz-nub-pb-pdm2 1 0.830564 20309.8 1 6 CACCTG GTTAATTAGC - +4 predrem__nrMotif1931 0 0.830564 20309.8 1 6 CACCTG CTCCCGCTCC - +4 predrem__nrMotif2556 0 0.830564 20309.8 1 6 CACCTG GGCCTCTGGG - +4 transfac_pro__M05362-CG11085-slou 0 0.830564 20309.8 1 6 CACCTG TCCATATTAA - +4 transfac_pro__M06180 4 0.830564 20309.8 1 6 CACCTG TTCCCCCCAG - +4 transfac_pro__M06686 1 0.830564 20309.8 1 6 CACCTG TCTCCACAAA - +4 transfac_pro__M06815 4 0.830564 20309.8 1 6 CACCTG CCCATGGCTA - +4 transfac_pro__M07585 4 0.830564 20309.8 1 6 CACCTG TATTTAATTA - +4 transfac_public__M00147-Hsf 2 0.830564 20309.8 1 6 CACCTG CGAACATTCT - +4 cisbp__M4707-Stat92E 5 0.830564 20309.8 1 5 CACCTG AAACGAAACT + +4 cisbp__M5691-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.830564 20309.8 1 5 CACCTG ACCATATGTT + +4 predrem__nrMotif970 5 0.830564 20309.8 1 5 CACCTG AGCAAAAGCA + +4 stark__WAATGCGCNT 5 0.830564 20309.8 1 5 CACCTG AAATGCGCAT + +4 taipale__OLIG2_DBD_AMCATATGKT-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.830564 20309.8 1 5 CACCTG ACCATATGTT + +4 taipale_cyt_meth__BHLHE23_ANCATATGNY_eDBD-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.830564 20309.8 1 5 CACCTG ACCATATGGT + +4 taipale_cyt_meth__OLIG3_ACCATATGKT_FL-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.830564 20309.8 1 5 CACCTG ACCATATGTT + +4 transfac_pro__M07547 -1 0.830564 20309.8 1 5 CACCTG ACCGTACGGA + +4 predrem__nrMotif2258 -1 0.830564 20309.8 1 5 CACCTG CCCGGCCCAG - +4 transfac_public__M00204-Jra 5 0.830564 20309.8 1 5 CACCTG TGAGTCATTT - +4 cisbp__M1180-Antp-Awh-E5-Lim3-Scr-ems-en-inv-pb-slou 6 0.830564 20309.8 1 4 CACCTG ACTAATTACC + +4 taipale__Hoxa2_DBD_NNYMATTANN-Awh-CG18599-E5-ems-en-eve-inv-lab-lbl-Lim3-pb-slou-Ubx-unpg 6 0.830564 20309.8 1 4 CACCTG ACTAATTAGC + +4 cisbp__M5390-al-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 6 0.830564 20309.8 1 4 CACCTG CCCAATTAGC - +4 cisbp__M5394-al-CG32532-CG34367-CG4328-en-inv-Lim3-lms-Lmx1a-OdsH-repo-unc-4-Vsx2 6 0.830564 20309.8 1 4 CACCTG TCCAATTAAC - +4 cisbp__M6028-Awh-CG18599-E5-ems-en-eve-ind-inv-lab-lbl-Lim3-pb-Scr-slou-Ubx-unpg 6 0.830564 20309.8 1 4 CACCTG ACTAATTAGC - +4 predrem__nrMotif2446 -2 0.830564 20309.8 1 4 CACCTG GCTGAGGGAC - +4 transfac_pro__M08929-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 6 0.830564 20309.8 1 4 CACCTG ATGAGTCATC - +4 transfac_pro__M05048 7 0.830564 20309.8 1 3 CACCTG ATGCCGCCAC + +4 tfdimers__MD00402-nub-pdm2 23 0.831283 20327.4 1 6 CACCTG AAAATTTTCATTTGCATAATAATTACCTTTTC + +4 cisbp__M4341 5 0.831708 20337.8 1 6 CACCTG GGGGGTATCTCCGCCGGTGTG + +4 taipale__IRF3_full_NNRRAAAGGAAACCGAAACTN_repr-Stat92E 15 0.831708 20337.8 1 6 CACCTG GGGAAACGGAAACCGAAACTG + +4 transfac_pro__M01515 1 0.831708 20337.8 1 6 CACCTG TTTCCGGCCACAAAAACGCAA + +4 transfac_pro__M01518 5 0.831708 20337.8 1 6 CACCTG GGGGGTATCTCCGCCGCTGTG + +4 transfac_pro__M01575-klu-sr 6 0.831708 20337.8 1 6 CACCTG ACGTGTTACCCCGCAATTAAT + +4 transfac_pro__M05229-E(z) 10 0.831708 20337.8 1 6 CACCTG TGGGGGGCCCGCCCTCTCTCG + +4 transfac_public__M00264-Hcf-Six4 11 0.831708 20337.8 1 6 CACCTG ATTTCCCATCATGCCTTGCGA + +4 cisbp__M2148 1 0.831708 20337.8 1 6 CACCTG TTTCCGGCCACAAAAACGCAA - +4 cisbp__M3715-ey-toy 9 0.831708 20337.8 1 6 CACCTG GGCCGCGCACGCATGACCGCC - +4 transfac_pro__M01511 2 0.831708 20337.8 1 6 CACCTG GGACCGTTATTTCCGCGCTCG - +4 transfac_pro__M05281 14 0.831708 20337.8 1 6 CACCTG GGAAAGCGACGGGACACCACA - +4 transfac_pro__M09081-Adf1-lid-Taf1 13 0.831708 20337.8 1 6 CACCTG CCGCCGCCGCCACCGCCGCCG - +4 transfac_pro__M09090-pho-phol-RpII215-Taf1 15 0.831708 20337.8 1 6 CACCTG CCTCCGCCGCCATTTCCGCCG - +4 transfac_pro__M09119-brm-CG7839-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 11 0.831708 20337.8 1 6 CACCTG TTTTTTTTTTTTTACTTTTTT - +4 transfac_public__M00373-ey-toy 9 0.831708 20337.8 1 6 CACCTG GGCCGCGCACGCATGACCGCC - +4 transfac_pro__M02762 0 0.832276 20351.6 1 6 CACCTG ACTATGAATGAATGAT + +4 transfac_pro__M03136 10 0.832276 20351.6 1 6 CACCTG AAGGCGCGTGTCCCAG + +4 hocomoco__MEOX1_HUMAN.H11MO.0.D-E5-btn-ems-pb-repo-slou-zen2 12 0.832276 20351.6 1 4 CACCTG ATTAACGCTAATTACC - +4 tfdimers__MD00575-Sox15 8 0.832455 20356 1 6 CACCTG ATATTAATTTCCTTTTATTGTTTTTAT - +4 transfac_pro__M06381 11 0.8332 20374.2 1 6 CACCTG TTCACTCCGTCGAACTGA - +4 yetfasco__YCR040W_1418-bs 1 0.833699 20386.4 1 6 CACCTG TTTCCTAATTAGTACATCAATG + +4 cisbp__M2452 16 0.833699 20386.4 1 6 CACCTG GTATCGGAATACTGTACTCCGA - +4 tfdimers__MD00017 9 0.833699 20386.4 1 6 CACCTG TAAAGATAATCCCATTAAATAA - +4 cisbp__M5731-Dll-dve-nub-pdm2-vvl 5 0.834193 20398.5 1 6 CACCTG TAATTTGCATAA + +4 cisbp__M5745-nub-pdm2-vvl 3 0.834193 20398.5 1 6 CACCTG ATGAATATGCAA + +4 flyfactorsurvey__sd_FlyReg_FBgn0003345-sd 0 0.834193 20398.5 1 6 CACCTG GACATTCCTCGA + +4 stark__AAANNNNNNCAA 3 0.834193 20398.5 1 6 CACCTG AAAAAAAAACAA + +4 taipale_tf_pairs__MEIS1_DRGX_TGACASTAATKR_CAP_repr-CG11294-Drgx 6 0.834193 20398.5 1 6 CACCTG TGACACTAATTG + +4 cisbp__M6278 6 0.834193 20398.5 1 6 CACCTG TTTGCAGCCCTA - +4 hocomoco__SP2_HUMAN.H11MO.1.B-CG3065-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay 4 0.834193 20398.5 1 6 CACCTG GCCCCGCCCCCT - +4 neph__UW.Motif.0017 5 0.834193 20398.5 1 6 CACCTG TTGGCAGTTTTT - +4 taipale__POU3F1_DBD_WTATGCWAATNW-Dll-dve-nub-pdm2-vvl 5 0.834193 20398.5 1 6 CACCTG TAATTTGCATAA - +4 taipale_tf_pairs__CEBPG_CREB3L1_NGCCACGCAAYN_CAP_repr-CrebA 3 0.834193 20398.5 1 6 CACCTG TATTGCGTGGCA - +4 taipale_tf_pairs__IRF2_NAANCGAAASYR_HT 0 0.834193 20398.5 1 6 CACCTG CACTTTCGTTTT - +4 tiffin__TIFDMEM0000043 3 0.834193 20398.5 1 6 CACCTG TAGCAATTTTGT - +4 transfac_pro__M00998-abd-A-lab-Ubx 1 0.834193 20398.5 1 6 CACCTG CTACCATCAATC - +4 transfac_pro__M05689-CG6654-CG7372 2 0.834193 20398.5 1 6 CACCTG GCAGCCTTATCA - +4 transfac_pro__M05793-CG10321-CG8089 6 0.834193 20398.5 1 6 CACCTG TGTTGAGCCCAA - +4 transfac_pro__M06746 6 0.834193 20398.5 1 6 CACCTG TTTGAAAATCGC - +4 transfac_pro__M06769-CG6654-CG7372 6 0.834193 20398.5 1 6 CACCTG TCGGCTGGCCCG - +4 hocomoco__CEBPG_HUMAN.H11MO.0.B-Myc-nej 7 0.834193 20398.5 1 5 CACCTG ATTGCATCATCC + +4 transfac_pro__M05536 7 0.834193 20398.5 1 5 CACCTG TCTGCCGTCCCA - +4 transfac_pro__M06163 7 0.834193 20398.5 1 5 CACCTG GCGGCGGTACAA - +4 hocomoco__CEBPA_HUMAN.H11MO.0.A-nej 8 0.834193 20398.5 1 4 CACCTG GATTGCACAACC + +4 taipale__ZNF75A_DBD_GCTTTTCCCACA_repr 8 0.834193 20398.5 1 4 CACCTG GCTTTTCCCACA + +4 hocomoco__HXA10_HUMAN.H11MO.0.C 8 0.834193 20398.5 1 4 CACCTG TCATAAATTATC - +4 transfac_pro__M06281 -2 0.834193 20398.5 1 4 CACCTG TCTGATGATCCA - +4 transfac_pro__M06631 8 0.834193 20398.5 1 4 CACCTG GATTTTGCAACA - +4 taipale_cyt_meth__CUX2_NTGATCGATYRN_eDBD-ct -3 0.834193 20398.5 1 3 CACCTG CTGATCGATTAG + +4 transfac_pro__M05002 9 0.834193 20398.5 1 3 CACCTG CAAGCCGTTTAC - +4 taipale_cyt_meth__IRF3_NCNGTTTCSNSGAAACSGAAASN_eDBD_repr 13 0.834856 20414.7 1 6 CACCTG TCAGTTTCGCCGAAACCGAAACT + +4 tfdimers__MD00186-NFAT 2 0.834856 20414.7 1 6 CACCTG TTTTACTTCCTCTTTTTCTTTTT - +4 tfdimers__MD00377 2 0.834956 20417.2 1 6 CACCTG ATTATTTGATTAATAATCAATTAAT + +4 cisbp__M0020 0 0.83508 20420.2 1 6 CACCTG CGCCGCCA + +4 cisbp__M0040 0 0.83508 20420.2 1 6 CACCTG TGCCGGCG + +4 cisbp__M0779 2 0.83508 20420.2 1 6 CACCTG TCGATCGT + +4 cisbp__M5344-Dll-Dr 1 0.83508 20420.2 1 6 CACCTG GTAATTGG + +4 cisbp__M5639-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-inv-lbe-Lim3-lms-OdsH-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 1 0.83508 20420.2 1 6 CACCTG CTAATTGG + +4 cisbp__M6303-Dfd 1 0.83508 20420.2 1 6 CACCTG TTAATTGA + +4 flyfactorsurvey__cic_SANGER_5_FBgn0028386-cic 0 0.83508 20420.2 1 6 CACCTG CCCATTCA + +4 hdpi__IL24 2 0.83508 20420.2 1 6 CACCTG TGCAAATG + +4 predrem__nrMotif1178 0 0.83508 20420.2 1 6 CACCTG TCCCAACA + +4 predrem__nrMotif549 1 0.83508 20420.2 1 6 CACCTG CCGCCTCT + +4 taipale__LMX1B_full_NYAATTAN-al-CG11294-CG15696-CG34367-CG4328-Dll-Drgx-en-exex-hbn-HGTX-inv-Lim1-Lim3-Lmx1a-OdsH-repo-unc-4-Vsx2 1 0.83508 20420.2 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__ALX4_CYAATTAN_eDBD-al-Awh-bsh-Dll-Dr-E5-ems-en-inv-lab-Lim3-slou 1 0.83508 20420.2 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__ESX1_YYAATTAN_FL-CG11294-Dll-Drgx-ems-en-exex-ind-inv-Lim3-slou-Vsx1-Vsx2 1 0.83508 20420.2 1 6 CACCTG CTAATTAC + +4 yetfasco__YOL116W_1376 0 0.83508 20420.2 1 6 CACCTG GTCCTAAT + +4 cisbp__M1598-pan 0 0.83508 20420.2 1 6 CACCTG GATCAAAG - +4 cisbp__M4875-HHEX 0 0.83508 20420.2 1 6 CACCTG TAATTAAA - +4 flyfactorsurvey__CG7056_SOLEXA_FBgn0038852-HHEX 0 0.83508 20420.2 1 6 CACCTG TAATTAAA - +4 jaspar__MA1009.1 0 0.83508 20420.2 1 6 CACCTG TTCCGACA - +4 stark__RCAAWTTR 0 0.83508 20420.2 1 6 CACCTG CAAATTGC - +4 taipale__Prrx2_DBD_NYAATTAN-al-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ey-gsb-gsb-n-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-PHDP-Pph13-prd-repo-ro-Rx-slou- 1 0.83508 20420.2 1 6 CACCTG TTAATTAG - +4 taipale_cyt_meth__PHOX2A_CYAATTAN_eDBD_meth-al-Awh-CG11294-Drgx-E5-ems-en-inv-lab-Lim3-slou 1 0.83508 20420.2 1 6 CACCTG GTAATTAG - +4 transfac_pro__M05313 0 0.83508 20420.2 1 6 CACCTG GGCATATT - +4 transfac_pro__M06457 2 0.83508 20420.2 1 6 CACCTG CCCCCCCG - +4 transfac_pro__M07812-al-Awh-C15-CG18599-CG34367-CG9876-Dr-en-inv-lbe-Lim3-lms-OdsH-Pph13-repo-Rx-tup-unc-4-unpg-Vsx1-Vsx2 1 0.83508 20420.2 1 6 CACCTG CTAATTGA - +4 transfac_pro__M07838-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 1 0.83508 20420.2 1 6 CACCTG CTAATTGG - +4 cisbp__M0720 3 0.83508 20420.2 1 5 CACCTG AAAAACAA + +4 transfac_pro__M07331-vvl 3 0.83508 20420.2 1 5 CACCTG TTACAAAT + +4 cisbp__M0556 -1 0.83508 20420.2 1 5 CACCTG GCTTAATC - +4 hocomoco__MAF_HUMAN.H11MO.1.B-cic-maf-S-tj 3 0.83508 20420.2 1 5 CACCTG AGTCAGCA - +4 jaspar__MA0916.1-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt -1 0.83508 20420.2 1 5 CACCTG ACTTCCGG - +4 yetfasco__YBL005W_2062 -1 0.83508 20420.2 1 5 CACCTG CCCGCAGA - +4 flyfactorsurvey__Ara_Cell_FBgn0015904-ara 4 0.83508 20420.2 1 4 CACCTG AAATAACA + +4 flyfactorsurvey__Ets65A_SANGER_10_FBgn0005658-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -2 0.83508 20420.2 1 4 CACCTG CCGGAAAT + +4 predrem__nrMotif812 4 0.83508 20420.2 1 4 CACCTG GCAGTCCC + +4 transfac_pro__M00690 -2 0.83508 20420.2 1 4 CACCTG TCTAAATT + +4 transfac_pro__M01111-Su(H) 4 0.83508 20420.2 1 4 CACCTG TTCCCACG + +4 cisbp__M4743-ara 4 0.83508 20420.2 1 4 CACCTG AAATAACA - +4 elemento__AGTGCTGG -2 0.83508 20420.2 1 4 CACCTG CCAGCACT - +4 elemento__CATCCGGG -2 0.83508 20420.2 1 4 CACCTG CCCGGATG - +4 factorbook__SOX2-Sox14-Sox15-Sox100B-Sox102F-SoxN -2 0.83508 20420.2 1 4 CACCTG CCTTTGTT - +4 hdpi__HNRPA0-Hrb87F-Hrb98DE-Rb97D 4 0.83508 20420.2 1 4 CACCTG AATTTTCC - +4 neph__UW.Motif.0167 -2 0.83508 20420.2 1 4 CACCTG TCTTTTGT - +4 cisbp__M5041-achi-hth-vis -3 0.83508 20420.2 1 3 CACCTG CTGTCAAA + +4 predrem__nrMotif1861 5 0.83508 20420.2 1 3 CACCTG GCTCAGAC + +4 taipale_cyt_meth__LBX2_CTCGTTAN_eDBD_meth-bsh-CG34367-CG4328-Dr-ind-Lmx1a-unpg-Vsx1-Vsx2 -3 0.83508 20420.2 1 3 CACCTG CTCGTTAA + +4 taipale_cyt_meth__LHX8_CYAATTAN_FL_meth-al-Awh-C15-CG34367-E5-ems-en-ind-inv-lab-Lim3-OdsH-pb-repo-unc-4-unpg 5 0.83508 20420.2 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__PHOX2B_NYAATTAN_eDBD_meth-Antp-B-H1-B-H2-bsh-Dll-Dr-en-exex-inv-lab-Lim1-Lim3-pb-Rx-Scr-slou-unpg-Vsx1 5 0.83508 20420.2 1 3 CACCTG GCAATTAC + +4 cisbp__M0722-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.83508 20420.2 1 3 CACCTG TTGTTTAC - +4 cisbp__M0738-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.83508 20420.2 1 3 CACCTG TTGTTTAC - +4 cisbp__M0894-Antp-HGTX-ind-inv-lbe-lbl-Scr -3 0.83508 20420.2 1 3 CACCTG CTAATTAA - +4 cisbp__M1486 5 0.83508 20420.2 1 3 CACCTG GACTACAC - +4 cisbp__M5199-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.83508 20420.2 1 3 CACCTG TTGTTTAC - +4 flyfactorsurvey__hth_SOLEXA_2_FBgn0001235-achi-hth-vis -3 0.83508 20420.2 1 3 CACCTG CTGTCAAA - +4 flyfactorsurvey__slp2_SANGER_5_FBgn0004567-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd19B-fd59A-fd102C-fkh-foxo-slp1-slp2 5 0.83508 20420.2 1 3 CACCTG TTGTTTAC - +4 jaspar__MA0614.1-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd19B-fd59A-fd102C-foxo-slp1-slp2 5 0.83508 20420.2 1 3 CACCTG TTGTTTAC - +4 jaspar__MA0618.1-Antp-HGTX-Scr-ind-inv-lbe-lbl -3 0.83508 20420.2 1 3 CACCTG CTAATTAA - +4 tfdimers__MD00127-TfAP-2 6 0.835254 20424.5 1 6 CACCTG TTTAATTGCCCAATAAAACATTAA + +4 taipale_tf_pairs__TEAD4_CEBPD_NTTRCGYAANNNNNNNNRGWATGY_CAP_repr-sd 3 0.835254 20424.5 1 6 CACCTG GCATTCCGTTTAGTATTGCGCAAT - +4 tfdimers__MD00069 3 0.835254 20424.5 1 6 CACCTG AATTTCATTAATCCCAATTTTATT - +4 cisbp__M1736 0 0.835436 20428.9 1 6 CACCTG AGGCGCG + +4 cisbp__M2260-al-ap-Awh-CG18599-CG32532-CG9876-E5-ems-en-hbn-lbl-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2 1 0.835436 20428.9 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Hmx_SOLEXA_FBgn0085448-Hmx 1 0.835436 20428.9 1 6 CACCTG TTAATTG + +4 jaspar__MA0457.1-Awh-CG9876-CG18599-CG32532-E5-OdsH-PHDP-Pph13-Rx-Vsx1-Vsx2-al-ap-ems-en-hbn-lbl-otp-repo-ro-slou-unc-4-unpg 1 0.835436 20428.9 1 6 CACCTG TTAATTA + +4 predrem__nrMotif412 1 0.835436 20428.9 1 6 CACCTG TTTCCAT + +4 hdpi__RIOK2-RIOK2 1 0.835436 20428.9 1 6 CACCTG TTATTTC - +4 predrem__nrMotif2034 1 0.835436 20428.9 1 6 CACCTG CAAGCAG - +4 cisbp__M6407-sv -1 0.835436 20428.9 1 5 CACCTG GCATGAC + +4 flyfactorsurvey__peb-F1-3_SANGER_2.5_FBgn0003053-peb 2 0.835436 20428.9 1 5 CACCTG AGCATCC + +4 cisbp__M5618 2 0.835436 20428.9 1 5 CACCTG TTGACAG - +4 hdpi__KLF3-CG42741 2 0.835436 20428.9 1 5 CACCTG AGCAATT - +4 hdpi__POLE3-Chrac-14 2 0.835436 20428.9 1 5 CACCTG CAGCCAT - +4 elemento__CGCTCCC 3 0.835436 20428.9 1 4 CACCTG CGCTCCC + +4 elemento__CGCTGCC 3 0.835436 20428.9 1 4 CACCTG CGCTGCC + +4 elemento__CGCTTCC 3 0.835436 20428.9 1 4 CACCTG CGCTTCC + +4 elemento__GCGTGCC 3 0.835436 20428.9 1 4 CACCTG GCGTGCC + +4 hdpi__HIRIP3 3 0.835436 20428.9 1 4 CACCTG GGGCAAC + +4 scertf__badis.STE12 3 0.835436 20428.9 1 4 CACCTG TGAAACA + +4 transfac_pro__M07268-Sox14 -2 0.835436 20428.9 1 4 CACCTG TCTTTGT + +4 hdpi__GTPBP6-CG5116 -2 0.835436 20428.9 1 4 CACCTG CATTAAA - +4 hdpi__ZNF205 -2 0.835436 20428.9 1 4 CACCTG CATTTTG - +4 predrem__nrMotif1789 -2 0.835436 20428.9 1 4 CACCTG CATTTAT - +4 cisbp__M6050 -3 0.835436 20428.9 1 3 CACCTG CTGTCAA + +4 taipale__Meis3_DBD_NTGACAN -3 0.835436 20428.9 1 3 CACCTG CTGTCAA - +4 c2h2_zfs__M5184-CG42741-Spps-btd-dar1-luna 6 0.835921 20440.8 1 6 CACCTG GACCACGCCCTTATT + +4 cisbp__M5573 9 0.835921 20440.8 1 6 CACCTG CCGAAACCGAAACTA + +4 cisbp__M6508-sd 7 0.835921 20440.8 1 6 CACCTG GATATTTCTGCTCTA + +4 factorbook__UA6-CG10431-Eip74EF 5 0.835921 20440.8 1 6 CACCTG ACTTCCGCCCGGACC + +4 flyfactorsurvey__rn_SOLEXA_F2-4-hb-rn-sqz 9 0.835921 20440.8 1 6 CACCTG GTTTTTTTGCGTGTT + +4 hocomoco__TEAD3_HUMAN.H11MO.0.D-sd 0 0.835921 20440.8 1 6 CACCTG GATATTTCTGCTTTA + +4 predrem__nrMotif1200-Brf-CG7368-CTCF-CoRest-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-crol-ct-klu-l(3)neo38-vtd 8 0.835921 20440.8 1 6 CACCTG CCCCCCGCCCCCCCC + +4 taipale__Klf12_DBD_GRCCACGCCCWNNNN_repr-btd-CG42741-dar1-luna-Spps 6 0.835921 20440.8 1 6 CACCTG GACCACGCCCTTATT + +4 taipale_cyt_meth__IRF9_NYGAAASYGAAACYN_FL 9 0.835921 20440.8 1 6 CACCTG ACGAAACCGAAACTA + +4 cisbp__M4603-CG10431-lid-pho-phol-RpII215-Taf1-Taf7 8 0.835921 20440.8 1 6 CACCTG GCCGCCGCCATCTTG - +4 taipale_tf_pairs__HOXB2_PITX1_TAATKRNRNGGATTA_CAP_repr-pb-Ptx1 3 0.835921 20440.8 1 6 CACCTG TAATCCCTCTCATTA - +4 transfac_pro__M01010 5 0.835921 20440.8 1 6 CACCTG TCAAAAAATTGCATT - +4 transfac_public__M00136-nub-pdm2-vvl 0 0.835921 20440.8 1 6 CACCTG TAAATGCATATTCAT - +4 cisbp__M2104 10 0.835921 20440.8 1 5 CACCTG GAGTACTGTTGCCCG + +4 taipale_cyt_meth__LEF1_WCATCGRGRCGCTGW_eDBD-pan -1 0.835921 20440.8 1 5 CACCTG ACATCGGGGCGCTGA + +4 jaspar__MA0299.1 10 0.835921 20440.8 1 5 CACCTG GAGTACTGTTCCCCG - +4 taipale__HSF1_full_TTCTAGAANNTTC-Hsf-pb 6 0.837263 20473.6 1 6 CACCTG TTCTAGAACGTTC + +4 cisbp__M4652-CG10431-lid-pho-phol-Taf1-Taf7 6 0.837263 20473.6 1 6 CACCTG CGCCGCCATCTTG - +4 cisbp__M5565-Hsf-pb 6 0.837263 20473.6 1 6 CACCTG TTCTAGAACGTTC - +4 factorbook__POU2F2-nub-pdm2-vvl 5 0.837263 20473.6 1 6 CACCTG ATATGCAAATGAG - +4 hocomoco__PRDM6_HUMAN.H11MO.0.C-HDAC1 5 0.837263 20473.6 1 6 CACCTG TTTTTTTCTTTTT - +4 taipale_cyt_meth__BBX_TGAWCNNNGWTCA_eDBD-bbx 1 0.837263 20473.6 1 6 CACCTG TGAACGGCGTTCA - +4 hocomoco__PAX3_MOUSE.H11MO.0.D-gsb-gsb-n-prd 8 0.837263 20473.6 1 5 CACCTG TAATCAATTAGCC - +4 transfac_pro__M01586-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-REPTOR-BP-Xbp1 9 0.837263 20473.6 1 4 CACCTG TGATGACGTCATC - +4 cisbp__M6425-SoxN-vvl 2 0.83768 20483.8 1 6 CACCTG TTTGCATTACAATG + +4 homer__CNCTTCCNGGAAGN_Stat3+il21-Stat92E 3 0.83768 20483.8 1 6 CACCTG CACTTCCAGGAAGC + +4 taipale_tf_pairs__FOXO1_ELF1_NNGAAAACCGAANM_CAP-Eip74EF-foxo 5 0.83768 20483.8 1 6 CACCTG CAGAAAACCGAAAC + +4 taipale_tf_pairs__HOXB2_HOXB13_NNMATCACATAAAN_CAP_repr-pb 2 0.83768 20483.8 1 6 CACCTG CCCATCACATAAAA + +4 transfac_pro__M04764-CG10431-pho-phol 5 0.83768 20483.8 1 6 CACCTG GCCGCCATCTTGGT + +4 cisbp__M5215-btd-cbt-hkb-klu-Spps-sr 7 0.83768 20483.8 1 6 CACCTG CCACGCCCACGCAC - +4 cisbp__M6193-Dp-E2f1-E2f2 6 0.83768 20483.8 1 6 CACCTG TTTTCCCGCCAAAT - +4 flyfactorsurvey__lmd_SANGER_5_FBgn0039039-lmd-opa-sug 2 0.83768 20483.8 1 6 CACCTG ACGACCCCCCACAG - +4 hocomoco__E2F4_HUMAN.H11MO.1.A-E2f1-E2f2-Sin3A 2 0.83768 20483.8 1 6 CACCTG TCAAATTTCCCGCC - +4 taipale__ERG_DBD_NCCGGAWATCCGGN_repr-Ets21C-Ets97D 7 0.83768 20483.8 1 6 CACCTG ACCGGATTTCCGGT - +4 taipale_tf_pairs__FOS_NGATGACGTCATCR_HT-kay 4 0.83768 20483.8 1 6 CACCTG TGATGACGTCATCA - +4 transfac_pro__M07782-bsh-CG15696-CG32532-CG34367-CG9876-E5-ems-en-gsb-gsb-n-inv-lms-OdsH-prd-slou-Vsx2 4 0.83768 20483.8 1 6 CACCTG CAATTAACCAATTA - +4 transfac_pro__M07793-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-exex-inv-lab-lbe-Lim3-OdsH-Pph13-unpg-zfh2 4 0.83768 20483.8 1 6 CACCTG ACGCTAATTAGCGT - +4 transfac_pro__M00729-abd-A-Abd-B-cad-Ubx 10 0.83768 20483.8 1 4 CACCTG ATAGTTTTATTGCC + +4 hocomoco__STAT1_HUMAN.H11MO.0.A-Stat92E 5 0.838233 20497.3 1 6 CACCTG CCCCTTTCCTGGAAATCAC + +4 taipale_cyt_meth__HSFY1_NCATTCYAAWCATTCYAWN_eDBD_meth-sd 8 0.838233 20497.3 1 6 CACCTG ACATTCTAAACATTCCATT + +4 taipale_cyt_meth__HSFY2_NCATTCYAAWCATTCYAWN_eDBD_meth-sd 8 0.838233 20497.3 1 6 CACCTG GCATTCTAAACATTCCATT + +4 jaspar__MA0014.2-Poxm-ey-sv-toy 4 0.838233 20497.3 1 6 CACCTG GTCACGCTTGGCTGCCCTC - +4 taipale_tf_pairs__POU2F1_GSC2_NNGATTANNNATGCAWNNN_CAP-Gsc-nub-pdm2 13 0.838233 20497.3 1 6 CACCTG TATTTGCATACATAATCCT - +4 transfac_pro__M06772 8 0.838233 20497.3 1 6 CACCTG GCTACGACGACGTCCTAAT - +4 swissregulon__hs__HOX_A5_B5_.p2-Antp-Scr 7 0.838733 20509.5 1 6 CACCTG TGCCCTCTTCCCCATTATTGCTCACCCTCA + +4 taipale_tf_pairs__POU2F1_FOXO6_RMATATKCNNNNNNNNNNNNNNNRWMAACA_CAP_repr-foxo-nub-pdm2 9 0.838733 20509.5 1 6 CACCTG GAATATTCAAATCTTGCGTCGACATCAACA + +4 taipale_tf_pairs__POU2F1_EOMES_NNNTATGCNNNGYGANNNNNNNNNNNCRCN_CAP_repr-nub-pdm2 11 0.838733 20509.5 1 6 CACCTG AGTGTGAAATCGATTTCACGCTGCATATTC - +4 cisbp__M2493-arg-HDAC1-HDAC3 0 0.839945 20539.2 1 6 CACCTG GCCTTCGGCGGCTAGTA + +4 taipale_cyt_meth__SP2_NYWAGYCCCGCCCMCYN_eDBD_meth-btd-E2f2-Nf-YA-Nf-YB-Spps 11 0.839945 20539.2 1 6 CACCTG ATAAGTCCCGCCCCCTT + +4 transfac_pro__M01390 1 0.839945 20539.2 1 6 CACCTG CGACCCAATCAACGGTG + +4 transfac_pro__M02898-Smox 7 0.839945 20539.2 1 6 CACCTG TACGCCCCGCCACTCTG + +4 transfac_pro__M02968 1 0.839945 20539.2 1 6 CACCTG CGACCCAATCAACGGTG + +4 cisbp__M5332-ct 5 0.839945 20539.2 1 6 CACCTG ATCGATAACTGATCGAT - +4 hocomoco__SPIB_MOUSE.H11MO.0.A-CG9650-Dif-MTA1-like-Stat92E-dl-ebi-nej-sv 4 0.839945 20539.2 1 6 CACCTG GTTTCACTTCCTCTTTT - +4 taipale_cyt_meth__NFIC_NTTGGCNNNNTGCCARN_FL-C15-Nf1-NfI 5 0.839945 20539.2 1 6 CACCTG GTTGGCACCGTGCCAAC - +4 transfac_pro__M01432-C15 11 0.839945 20539.2 1 6 CACCTG TAGCCATTAATTAATTA - +4 transfac_pro__M01483-C15-CG34367-Dbx-unpg 11 0.839945 20539.2 1 6 CACCTG TAATTATTAATTAATTA - +4 hocomoco__HXD12_HUMAN.H11MO.0.D-cad 5 0.840232 20546.2 1 6 CACCTG AATTTTATTAC + +4 taipale__PROP1_full_TAAYYNAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Dll-Drgx-en-hbn-Lim3-OdsH-Optix-repo-ro-Traf4-unc-4 1 0.840232 20546.2 1 6 CACCTG TAATCTAATTA + +4 taipale_cyt_meth__NFE2_NATGASTCATN_eDBD_meth_repr-cnc-Jra-kay-Mef2 5 0.840232 20546.2 1 6 CACCTG CATGAGTCATG + +4 transfac_pro__M04780-maf-S 3 0.840232 20546.2 1 6 CACCTG AAAATGCTGAC + +4 transfac_pro__M05264 3 0.840232 20546.2 1 6 CACCTG CGATATATATC + +4 cisbp__M5752-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-en-hbn-Lim3-OdsH-Optix-repo-ro-Traf4-unc-4 1 0.840232 20546.2 1 6 CACCTG TAATCTAATTA - +4 transfac_pro__M01713-kay 3 0.840232 20546.2 1 6 CACCTG AATGACTCATA - +4 transfac_pro__M05191 2 0.840232 20546.2 1 6 CACCTG ATAAACTTTAA - +4 bergman__dl-B-Dif-Rel-dl 6 0.840232 20546.2 1 5 CACCTG GGGGAATTCCC + +4 fantom__motif80_CTCTGAGAGAA -1 0.840232 20546.2 1 5 CACCTG CTCTGAGAGAA + +4 transfac_public__M00037-cnc-ewg-Jra-kay-maf-S -1 0.840232 20546.2 1 5 CACCTG TGCTGAGTCAC + +4 cisbp__M2281 7 0.840232 20546.2 1 4 CACCTG TCCAATCCACA + +4 cisbp__M5532-abd-A-Abd-B-cad-eve-Ubx 7 0.840232 20546.2 1 4 CACCTG TTTTTATTACC + +4 cisbp__M5562 -2 0.840232 20546.2 1 4 CACCTG GCTCGTAAAAC + +4 flyfactorsurvey__Aef1_SANGER_5_FBgn0005694-Aef1-CG4360 7 0.840232 20546.2 1 4 CACCTG ACAACAACAAC + +4 hocomoco__CEBPB_MOUSE.H11MO.0.A-Irbp18-Xrp1-nej 7 0.840232 20546.2 1 4 CACCTG ATTGCACAACC + +4 hocomoco__JUNB_HUMAN.H11MO.0.A-CoRest-GATAe-Jra-Mef2-Myc-bon-cnc-ewg-grn-kay-maf-S-mor-nej-pan-pnr 7 0.840232 20546.2 1 4 CACCTG TCTGAGTCACC + +4 jaspar__MA0479.1 7 0.840232 20546.2 1 4 CACCTG TCCAATCCACA + +4 taipale__HOXD13_DBD_NCTCGTAAAAN -2 0.840232 20546.2 1 4 CACCTG GCTCGTAAAAC + +4 taipale_cyt_meth__E2F2_NCGCGCGCGCM_eDBD_meth-E2f1 7 0.840232 20546.2 1 4 CACCTG GCGCGCGCCCC + +4 taipale_cyt_meth__HOXC13_NCTCGTAAAAN_eDBD -2 0.840232 20546.2 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M6174-CG7839-Chrac-14-Nf-YA-Nf-YB-Nf-YC -2 0.840232 20546.2 1 4 CACCTG GCTGATTGGCT - +4 hocomoco__JUN_HUMAN.H11MO.0.A-CoRest-GATAe-Jra-Mef2-Myc-Stat92E-bon-cnc-grn-kay-mor-nej-pan-pnr 7 0.840232 20546.2 1 4 CACCTG GATGACTCATC - +4 taipale_cyt_meth__HOXD10_NGTCGTAAAAN_FL_meth-Abd-B-cad 7 0.840232 20546.2 1 4 CACCTG ATTTTACGACC - +4 transfac_pro__M07755-abd-A-Abd-B-cad-eve-Ubx 7 0.840232 20546.2 1 4 CACCTG GTTTTATTGCT - +4 cisbp__M1080-Awh-C15-CG9876-CG11085-CG18599-CG32532-CG34367-Dll-E5-Lim1-Lim3-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-ems-en-eve-exex-ind-inv-lab-lbe-lbl-lms-otp-pdm3-repo-ro-slou-unc-4-unpg-zen2-zfh2 2 0.841185 20569.5 1 6 CACCTG GCTAATTAG + +4 cisbp__M1590-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 3 0.841185 20569.5 1 6 CACCTG ATTGTTTTA + +4 hdpi__ZDHHC15-CG1407-CG17287 2 0.841185 20569.5 1 6 CACCTG TATCAATGG + +4 predrem__nrMotif1162 3 0.841185 20569.5 1 6 CACCTG TTCCATCAG + +4 predrem__nrMotif1184 3 0.841185 20569.5 1 6 CACCTG AAACATCCA + +4 predrem__nrMotif1921 1 0.841185 20569.5 1 6 CACCTG ACTCCAGAA + +4 predrem__nrMotif1962 3 0.841185 20569.5 1 6 CACCTG AGACACTGC + +4 predrem__nrMotif2253 3 0.841185 20569.5 1 6 CACCTG AAATACTGA + +4 transfac_pro__M04722-CG9650-ebi-nej-Stat92E-sv 3 0.841185 20569.5 1 6 CACCTG TTTCACTTC + +4 cisbp__M0118 3 0.841185 20569.5 1 6 CACCTG AATTTTTGG - +4 cisbp__M0576-danr 3 0.841185 20569.5 1 6 CACCTG AATCCGCGG - +4 cisbp__M0754-CHES-1-like-jumu 2 0.841185 20569.5 1 6 CACCTG TTTGCGTCC - +4 cisbp__M0905-abd-A-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG9876-Dfd-Dll-E5-ems-en-eve-ftz-ind-lab-lbe-lbl-Lim1-Lim3-lms-otp-pb-Pph13-repo-ro-Rx-Scr-slou-tup-Ubx-unpg-Vsx1-zen2 1 0.841185 20569.5 1 6 CACCTG GGTAATTAA - +4 cisbp__M0954-al-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-inv-lab-lbe-lbl-Lim1-Lim3-lms-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.841185 20569.5 1 6 CACCTG CCAATTAGC - +4 cisbp__M5083-lola 2 0.841185 20569.5 1 6 CACCTG CCCCCCAAT - +4 hocomoco__NKX61_MOUSE.H11MO.1.A-HGTX 0 0.841185 20569.5 1 6 CACCTG TTCATTAAT - +4 predrem__nrMotif1942 3 0.841185 20569.5 1 6 CACCTG AATGACTTG - +4 predrem__nrMotif1970 0 0.841185 20569.5 1 6 CACCTG AACAAGAAT - +4 predrem__nrMotif2055 0 0.841185 20569.5 1 6 CACCTG TAAATTGCT - +4 predrem__nrMotif2133 0 0.841185 20569.5 1 6 CACCTG TTCCAAGCA - +4 predrem__nrMotif2450 2 0.841185 20569.5 1 6 CACCTG AAATCATGC - +4 cisbp__M0749-bin-CHES-1-like-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.841185 20569.5 1 5 CACCTG GGTAAACAA + +4 cisbp__M6363-NFAT 4 0.841185 20569.5 1 5 CACCTG AATTTTCCA + +4 fantom__motif119_TCAAAANCG 4 0.841185 20569.5 1 5 CACCTG TCAAAAACG + +4 predrem__nrMotif1041 4 0.841185 20569.5 1 5 CACCTG ATTGCAGCA + +4 predrem__nrMotif1052 -1 0.841185 20569.5 1 5 CACCTG TCATTCCAT + +4 predrem__nrMotif1204 4 0.841185 20569.5 1 5 CACCTG ATCAAATCA + +4 predrem__nrMotif2236 4 0.841185 20569.5 1 5 CACCTG AGCTTAGCA + +4 transfac_pro__M04915-Tbp -1 0.841185 20569.5 1 5 CACCTG ATTTGCATA + +4 predrem__nrMotif666 4 0.841185 20569.5 1 5 CACCTG ATTTGCCCT - +4 predrem__nrMotif851 4 0.841185 20569.5 1 5 CACCTG TTTTGGCCT - +4 predrem__nrMotif1220 5 0.841185 20569.5 1 4 CACCTG CCACACTCC + +4 predrem__nrMotif2195 5 0.841185 20569.5 1 4 CACCTG TTTGGCACA + +4 cisbp__M0755-fkh-FoxK-foxo-FoxP-slp2 5 0.841185 20569.5 1 4 CACCTG TTGTTTACA - +4 cisbp__M0860-Awh-B-H1-B-H2-CG4328-CG9650-CG11085-Dll-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-Rx-Ubx-abd-A-ap-ems-en-eve-ind-inv-lab-lbl-lms-otp-pb-ro-slou-unpg-zen2 5 0.841185 20569.5 1 4 CACCTG GTAATTAGC - +4 predrem__nrMotif1063 5 0.841185 20569.5 1 4 CACCTG CTGCACTCC - +4 predrem__nrMotif1647 5 0.841185 20569.5 1 4 CACCTG ATTTGCAGC - +4 predrem__nrMotif2002 -2 0.841185 20569.5 1 4 CACCTG TCTCAGATT - +4 transfac_pro__M07763-B-H1-B-H2-bsh-CG11085-unpg 5 0.841185 20569.5 1 4 CACCTG GCAATTAGC - +4 transfac_pro__M04813-fkh 6 0.841185 20569.5 1 3 CACCTG TGAGTAAAC + +4 tfdimers__MD00327-pan 41 0.841683 20581.7 1 6 CACCTG TAGTTCCTTTGTTATGCAAATTAACCCACCTTCCCTCCTCACCCCCTCTA + +4 tfdimers__MD00126-HGTX 17 0.841732 20582.9 1 6 CACCTG ATTTTTTATTAATTAATTAATTTGTAAAT + +4 tfdimers__MD00290-Stat92E 12 0.841732 20582.9 1 6 CACCTG ACCCTCCGGCACTTCCTGTTCTTCCTCCC + +4 dbcorrdb__BACH1__ENCSR000EGD_1__m1-cnc-Jra-kay-maf-S-nej-tj 3 0.842122 20592.4 1 6 CACCTG AAATTGCTGAGTCATGGTTT + +4 dbcorrdb__CEBPB__ENCSR000DYI_1__m1-CG7786-gt-Irbp18-Jra-nej-Pdp1-slbo-Xrp1 11 0.842122 20592.4 1 6 CACCTG AAATATTGCACAATAATTTT + +4 dbcorrdb__CHD1__ENCSR000AQK_1__m4-Chd1 10 0.842122 20592.4 1 6 CACCTG AACCGAAAAAGAGCTTAAAA + +4 dbcorrdb__CTCF__ENCSR000DPP_1__m2-CTCF-SMC3-vtd 9 0.842122 20592.4 1 6 CACCTG CTGCAGTTCCCCATATGGCC + +4 dbcorrdb__E2F6__ENCSR000EWJ_1__m1-Brf-brm-btd-Clk-cnc-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-FoxP-gce-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Sap30-Sin3A-Spps-Spt20-SREBP-tna-Usf-vtd-zfh1 9 0.842122 20592.4 1 6 CACCTG CGCGCGGCGCACGTGGCCGC + +4 dbcorrdb__EZH2__ENCSR000ARD_1__m3-E(z) 13 0.842122 20592.4 1 6 CACCTG GACGACAACAACACATCTCG + +4 dbcorrdb__FOS__ENCSR000DON_1__m1-Jra-kay-Mef2-Myc-nej-Stat92E 13 0.842122 20592.4 1 6 CACCTG AAAAAGGATGACTCATACTT + +4 dbcorrdb__FOS__ENCSR000EYZ_1__m2-btd-kay-Nf-YA-Nf-YB-Spps 0 0.842122 20592.4 1 6 CACCTG CCCATGGCCCCGCCCCTCAC + +4 dbcorrdb__POLR2A__ENCSR000ALT_1__m1-RpII215 3 0.842122 20592.4 1 6 CACCTG TCTCAACATAGCGCATGAAC + +4 dbcorrdb__POLR2A__ENCSR000ALT_1__m2-RpII215 3 0.842122 20592.4 1 6 CACCTG CCACACGCGGAACAAGACTC + +4 dbcorrdb__POLR2A__ENCSR000DPA_1__m1-aop-Atac3-bs-CG10431-Dif-dl-Eip74EF-Ets65A-Ets96B-Ets97D-FoxP-Hcf-lid-pnt-Rbbp5-RpII215-Sin3A-Taf1 4 0.842122 20592.4 1 6 CACCTG CGCGCCGCTTCCGCCCTCCG + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOV_1__m2-Eip74EF-RpII215-Taf1 0 0.842122 20592.4 1 6 CACCTG CCCCGCAGCGGAAACAGCCG + +4 dbcorrdb__RELA__ENCSR000EAQ_1__m2-aop-Atac3-bs-CG9650-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-Hcf-pnt-RpII215-Rpn5-Sin3A-sv 5 0.842122 20592.4 1 6 CACCTG CGTGTCACTTCCTCTTGCGG + +4 dbcorrdb__SIX5__ENCSR000BJE_1__m2-bi-egg-Hcf-mor-Six4 3 0.842122 20592.4 1 6 CACCTG CAATTCCCAGCAGGCCCCGC + +4 dbcorrdb__SRF__ENCSR000BGE_1__m2-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt-RpII215-Sin3A 12 0.842122 20592.4 1 6 CACCTG CCTGCGGGTCACTTCCGGTT + +4 dbcorrdb__STAT1__ENCSR000FAV_1__m1-aop-Stat92E 14 0.842122 20592.4 1 6 CACCTG ATTTCCGGGAAATGAAACTG + +4 dbcorrdb__STAT3__ENCSR000DOU_1__m1-aop-Stat92E 8 0.842122 20592.4 1 6 CACCTG CAAATCATTTCCCGGAAGTG + +4 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m3-Spt20 9 0.842122 20592.4 1 6 CACCTG CTCATTACGCTTCTTTTCTG + +4 dbcorrdb__TAF1__ENCSR000BGS_1__m2-aop-Atac3-Brf-CrebB-E2f1-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Hr78-Nelf-E-pnt-Rbbp5-RpII215-Sin3A-Taf1-TfIIFalpha 9 0.842122 20592.4 1 6 CACCTG CGCTTCCGGCGCCGGCGCGG + +4 dbcorrdb__TBP__ENCSR000EEL_1__m4-Tbp 6 0.842122 20592.4 1 6 CACCTG GAGCGCAGCCTTTTATAGCC + +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m3-bon-egg 1 0.842122 20592.4 1 6 CACCTG AACCCTATGAATGTAATGAA + +4 tfdimers__MD00060 11 0.842122 20592.4 1 6 CACCTG AGTTAATAATTAATCAAAAT + +4 transfac_pro__M01493 14 0.842122 20592.4 1 6 CACCTG TTCCGTAACCCTAATACGCC + +4 transfac_pro__M01543-CHES-1-like-jumu 14 0.842122 20592.4 1 6 CACCTG AAAATTGACGCAAATTTGTT + +4 transfac_pro__M04671-CHES-1-like-jumu 14 0.842122 20592.4 1 6 CACCTG AAAATTGACGCAAATTCGTT + +4 cisbp__M6311 12 0.842122 20592.4 1 6 CACCTG TCACTTTTGGCTTTCCTTTA - +4 dbcorrdb__EZH2__ENCSR000ARH_1__m8-E(z) 11 0.842122 20592.4 1 6 CACCTG GCGGGGGCAGCGATCCCCGA - +4 dbcorrdb__FOS__ENCSR000FAI_1__m2-btd-CG42741-dar1-E2f2-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-sr-SREBP-Stat92E 14 0.842122 20592.4 1 6 CACCTG TAGGCCCCGCCCCCTCCCCG - +4 dbcorrdb__HA-E2F1__ENCSR000EVM_1__m1-Brf-brm-CrebB-CTCF-E2f1-ERR-ewg-E(z)-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-SREBP-tna-vtd 5 0.842122 20592.4 1 6 CACCTG CCGCGCGCCAGCCCCGGGCG - +4 dbcorrdb__IRF1__ENCSR000EGU_1__m1-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E 1 0.842122 20592.4 1 6 CACCTG TTACTTTCACTTTCACTTTC - +4 dbcorrdb__NR2C2__ENCSR000EVS_1__m1-aop-Eip74EF-Hcf-Hr78-lid-RpII215-Sin3A-Taf1 2 0.842122 20592.4 1 6 CACCTG GTCCGCTTCCGGGTCAGGGG - +4 dbcorrdb__POLR2A__ENCSR000EEM_1__m1-Atac3-Dif-dl-Ets96B-RpII215-Sin3A 6 0.842122 20592.4 1 6 CACCTG TCCTTTCGCTTCCGGCGTCG - +4 dbcorrdb__RFX5__ENCSR000ECF_1__m2-btd-CG7839-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 3 0.842122 20592.4 1 6 CACCTG CGCGTTCTGATTGGCTGAGG - +4 dbcorrdb__SRF__ENCSR000BLK_1__m3-bs-btd-Spps 8 0.842122 20592.4 1 6 CACCTG CCCGCGATTGGCTGATCATC - +4 dbcorrdb__TBP__ENCSR000EDD_1__m3-Tbp 12 0.842122 20592.4 1 6 CACCTG TTCAAATGACGTAAGCGTAA - +4 dbcorrdb__THAP1__ENCSR000BNN_1__m2-CG10431-Eip74EF-RpII215-Taf1 5 0.842122 20592.4 1 6 CACCTG GACGCCGCTTCCGCCCTCTT - +4 dbcorrdb__ZNF143__ENCSR000ECO_1__m1-egg-Hcf-Six4 0 0.842122 20592.4 1 6 CACCTG TTCCCAGCATGCCCCGCGGC - +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m1-egg 0 0.842122 20592.4 1 6 CACCTG CTCCAGTATGAGTTCTCTGA - +4 dbcorrdb__ZNF384__ENCSR000DYP_1__m3-rn-sqz 0 0.842122 20592.4 1 6 CACCTG CACCACTGCACTCCAGCCTG - +4 dbcorrdb__SMARCB1__ENCSR000EDK_1__m1-cnc-CrebB-Jra-kay-Max-mor-pan-Snr1 16 0.842122 20592.4 1 4 CACCTG CGGCGCGGCGGTGAGTCACC + +4 dbcorrdb__POLR3G__ENCSR000EYU_1__m3-bon-Brf-brm-CTCF-ERR-E(z)-Hcf-HDAC1-klu-Max-Myc-Nelf-E-opa-Rbbp5-RpII215-Spt20-SREBP-tna-vtd -2 0.842122 20592.4 1 4 CACCTG CCCCCCCGGGGGGGGGGGGG - +4 cisbp__M0212-h 2 0.842658 20605.5 1 6 CACCTG GGCACGTGCC + +4 cisbp__M0602 4 0.842658 20605.5 1 6 CACCTG ATTTGAATTT + +4 cisbp__M0671-E2f1-E2f2 4 0.842658 20605.5 1 6 CACCTG TTGGCGCCAA + +4 cisbp__M0730-bin-bs-fd102C-fd19B-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 4 0.842658 20605.5 1 6 CACCTG TCGTAAACAA + +4 cisbp__M0741-foxo 4 0.842658 20605.5 1 6 CACCTG GTAAAAACAA + +4 cisbp__M0939-Antp-B-H1-B-H2-bsh-CG11085-Dfd-eve-ftz-pb-Scr-slou-Ubx-unpg-zen2 2 0.842658 20605.5 1 6 CACCTG GCTAATGGCT + +4 cisbp__M1089-bsh-Dr-inv-lab-pb-Ubx-unpg 2 0.842658 20605.5 1 6 CACCTG GTTAATTGGT + +4 jaspar__MA0632.1-h 2 0.842658 20605.5 1 6 CACCTG GGCACGTGCC + +4 predrem__nrMotif1472 1 0.842658 20605.5 1 6 CACCTG TCTTCTTAAA + +4 predrem__nrMotif1682 1 0.842658 20605.5 1 6 CACCTG CTGCCTTTCC + +4 predrem__nrMotif1862 0 0.842658 20605.5 1 6 CACCTG TTCCAGCAAA + +4 predrem__nrMotif889 3 0.842658 20605.5 1 6 CACCTG CATTGCCATT + +4 taipale_cyt_meth__BHLHA15_NMCATATGKN_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap 0 0.842658 20605.5 1 6 CACCTG ACCATATGGT + +4 transfac_pro__M01199-bon 0 0.842658 20605.5 1 6 CACCTG GCCCGCGGCC + +4 transfac_pro__M03213 4 0.842658 20605.5 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M04973 4 0.842658 20605.5 1 6 CACCTG AGGCCGCCAA + +4 transfac_pro__M07365-CG5641-NFAT 4 0.842658 20605.5 1 6 CACCTG GGAAAATCTG + +4 cisbp__M5544-cad 0 0.842658 20605.5 1 6 CACCTG CCCATAAAAA - +4 hocomoco__IRF7_HUMAN.H11MO.0.C-Blimp-1-Stat92E 3 0.842658 20605.5 1 6 CACCTG TTTCACTTTC - +4 homer__CCATTGTTNY_Sox6-D-Sox14-Sox102F-SoxN 2 0.842658 20605.5 1 6 CACCTG AGAACAATGG - +4 predrem__nrMotif2586 1 0.842658 20605.5 1 6 CACCTG TGAACTCTCT - +4 transfac_pro__M02090-E2f2 3 0.842658 20605.5 1 6 CACCTG TCTTTCCCGC - +4 cisbp__M0042 5 0.842658 20605.5 1 5 CACCTG ATGCCGACAT + +4 cisbp__M0601 -1 0.842658 20605.5 1 5 CACCTG ATTTTAAAAT + +4 predrem__nrMotif2177 -1 0.842658 20605.5 1 5 CACCTG CCCAGACTGG + +4 taipale_cyt_meth__BHLHE22_ANCATATGNY_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.842658 20605.5 1 5 CACCTG ACCATATGGT + +4 transfac_pro__M04975 5 0.842658 20605.5 1 5 CACCTG AGGCCGCCCG + +4 cisbp__M0495-btd-Klf15-Spps 5 0.842658 20605.5 1 5 CACCTG ACACGCCCCT - +4 flyfactorsurvey__CG12236-PB_SOLEXA_FBgn0029822-CG12236 -1 0.842658 20605.5 1 5 CACCTG CACTGGAAGG - +4 hocomoco__HXD10_HUMAN.H11MO.0.D 5 0.842658 20605.5 1 5 CACCTG AATTAAAGCA - +4 swissregulon__hs__LHX3_4.p2-CG4328-Lim1-Lim3-Lmx1a-OdsH-repo-unc-4-vvl 5 0.842658 20605.5 1 5 CACCTG TTAATTAATT - +4 cisbp__M0892-abd-A-Antp-ap-Awh-btn-CG11085-CG11294-CG18599-CG4328-CG9876-Drgx-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-Lmx1a-otp-pb-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen-zen2-zfh2 6 0.842658 20605.5 1 4 CACCTG CCTAATTACC + +4 jaspar__MA0612.1-Antp-Awh-CG4328-CG9876-CG11085-CG11294-CG18599-Drgx-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-ap-btn-ems-en-eve-exex-ind-inv-lab-lbl-otp-pb-ro-slou-unpg-zen-zen2-zfh2 6 0.842658 20605.5 1 4 CACCTG CCTAATTACC + +4 scertf__spivak.CAD1 6 0.842658 20605.5 1 4 CACCTG ATTAGTAAGC + +4 cisbp__M0642 6 0.842658 20605.5 1 4 CACCTG ATTTTCAACA - +4 cisbp__M6033-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11085-CG11294-CG18599-CG32532-CG4328-CG9876-Dll-Dr-Drgx-dve-E5-ems-en-eve-exex-ftz-hbn-HGTX-Hmx-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pb 6 0.842658 20605.5 1 4 CACCTG AGTAATTAAC - +4 hocomoco__LHX2_MOUSE.H11MO.0.A-Antp-Awh-CG18599-CG34367-E5-HGTX-Scr-Ubx-Vsx2-abd-A-acj6-ap-bsh-btn-dve-ems-en-eve-ey-ftz-hbn-ind-inv-lab-lbe-lbl-pb-repo-slou-toy-unpg-zen2 -2 0.842658 20605.5 1 4 CACCTG ACTAATTAAC - +4 predrem__nrMotif671 6 0.842658 20605.5 1 4 CACCTG AGGACAAACA - +4 transfac_pro__M05539-bowl-drm-odd-sob -2 0.842658 20605.5 1 4 CACCTG GCTTTCGCAC - +4 taipale_cyt_meth__HOXD10_GYAATAAAAN_eDBD_meth-Abd-B-cad-eve 7 0.842658 20605.5 1 3 CACCTG GTTTTATTAC - +4 bergman__en-Antp-Awh-CG11294-CG18599-CG32532-E5-Lim1-Lim3-Pph13-Rx-Scr-Vsx1-Vsx2-al-ap-ems-en-hbn-ind-inv-lab-otp-pb-ro-unpg 0 0.842885 20611.1 1 6 CACCTG TAATTA + +4 fantom__motif62_CGNGAT -1 0.842885 20611.1 1 5 CACCTG ATCACG - +4 hdpi__PRNP -2 0.842885 20611.1 1 4 CACCTG CCGATA + +4 transfac_pro__M03823-fkh-foxo 3 0.842885 20611.1 1 3 CACCTG AAACAA + +4 fantom__motif65_TNGCGA 4 0.842885 20611.1 1 2 CACCTG TCGCAA - +4 cisbp__M2008-Optix 0 0.843339 20622.2 1 5 CACCTG TATCA + +4 flyfactorsurvey__Hth_Cell_FBgn0001235-hth 1 0.843339 20622.2 1 4 CACCTG TGACA + +4 cisbp__M5040-hth 1 0.843339 20622.2 1 4 CACCTG TGACA - +4 taipale_tf_pairs__TEAD4_FOXI1_RCATWCCNNNNNNNNNNNNNNRTMAACA_CAP_repr-sd 13 0.844225 20643.8 1 6 CACCTG ACATTCCGCACCACGCAATACGTAAACA + +4 cisbp__M5572-Stat92E 15 0.845006 20662.9 1 6 CACCTG GGGAAACGGAAACCGAAACTG + +4 jaspar__MA0343.1 1 0.845006 20662.9 1 6 CACCTG TTTCCGGCCACAAAAACGCAA + +4 taipale_cyt_meth__GFI1B_NMAATCACNGCANNNCACTMN_eDBD_meth-sens-2 15 0.845006 20662.9 1 6 CACCTG TAAATCACTGCATTTCACTCA + +4 tfdimers__MD00584-Med 9 0.845006 20662.9 1 6 CACCTG TTTTTTAATTGTCTGTTTATT + +4 transfac_pro__M09094-Adf1 2 0.845006 20662.9 1 6 CACCTG TCCGCCGCCGCCGCCGCCGCC + +4 cisbp__M4461-bi-egg-Hcf-mor-Six4-Stat92E 4 0.845006 20662.9 1 6 CACCTG GAACTACAATTCCCAGAAGGC - +4 taipale_cyt_meth__PAX4_NATTTCACGCWTSANYGNNYN_eDBD-ey-sv-toy 10 0.845006 20662.9 1 6 CACCTG TGCGCATTGATGCGTGAAATG - +4 transfac_pro__M00321-Brf-brm-HDAC1-Nelf-E-SREBP-vtd 2 0.845006 20662.9 1 6 CACCTG GGCTCCGGGGTGGCGGCGGGA - +4 transfac_pro__M05220-ERR-E(z) 13 0.845006 20662.9 1 6 CACCTG GGCGGGCGGGAGGGACCCCCC - +4 transfac_pro__M09446 11 0.845006 20662.9 1 6 CACCTG GGTTAAAATTTAACCATGGTT - +4 transfac_pro__M02759-sug 4 0.845043 20663.8 1 6 CACCTG TATCGACCCCCCACAG + +4 taipale_tf_pairs__HOXB2_PITX1_TAATKRNNNNGGATTA_CAP_repr-pb-Ptx1 1 0.845043 20663.8 1 6 CACCTG TAATCCTTCCTCATTA - +4 transfac_pro__M01092-pan 2 0.845043 20663.8 1 6 CACCTG TTTTCTTTTGATATCT - +4 transfac_pro__M01707-klu-sr 1 0.845043 20663.8 1 6 CACCTG TTCCCCGCATTTTTAT - +4 transfac_pro__M01858-E(z)-RpII215-TfAP-2-tna -1 0.845043 20663.8 1 5 CACCTG CCCCCCAGGCCGCCGC - +4 tfdimers__MD00511 22 0.845372 20671.9 1 6 CACCTG GGCGCGTGCGCGCGCATGCGCGCGCACGCGCC + +4 hocomoco__IRF4_HUMAN.H11MO.0.A-Blimp-1-CG9650-MTA1-like-Stat92E-ebi-nej-sv 8 0.846132 20690.5 1 6 CACCTG AGTTTCACTTCCTCTTTT - +4 transfac_pro__M05252 6 0.846132 20690.5 1 6 CACCTG ATATTAAACGTTTAGTAT - +4 cisbp__M2458 13 0.846132 20690.5 1 5 CACCTG TAACCAACAAAGAGGTCT + +4 transfac_public__M00275 13 0.846132 20690.5 1 5 CACCTG TAATCAACAAAGAGGTCT - +4 cisbp__M3040 14 0.846132 20690.5 1 4 CACCTG TGTGCATTGCCAAATACC - +4 transfac_pro__M06830 -2 0.846132 20690.5 1 4 CACCTG CCGTTCTTGACGGCACTC - +4 transfac_pro__M06778 15 0.846132 20690.5 1 3 CACCTG CCCACCACTTTTAAATAC - +4 tfdimers__MD00322-pho-phol 10 0.846193 20691.9 1 6 CACCTG TCTCTCTCCCCAGATGGCCACACTTCT - +4 cisbp__M2050-sd 0 0.846333 20695.4 1 6 CACCTG GACATTCCTCGG + +4 cisbp__M5609-cic-maf-S-tj 4 0.846333 20695.4 1 6 CACCTG AAATTTGCTGAC + +4 taipale__MAFK_DBD_NNNNNTGCTGAN-cic-maf-S-tj 4 0.846333 20695.4 1 6 CACCTG AAATTTGCTGAC + +4 taipale__POU5F1P1_DBD_WTRMATATKYAW-nub-pdm2-vvl 3 0.846333 20695.4 1 6 CACCTG ATGAATATGCAA + +4 taipale_cyt_meth__CDX2_NRTCGTAAANNN_eDBD_meth-cad 6 0.846333 20695.4 1 6 CACCTG CGTCGTAAACGC + +4 transfac_pro__M03797-Dr 0 0.846333 20695.4 1 6 CACCTG TTATTGGGGAGT + +4 transfac_pro__M06735 3 0.846333 20695.4 1 6 CACCTG CTGTGCCTAAGC + +4 c2h2_zfs__M0369 3 0.846333 20695.4 1 6 CACCTG GTCTTTCTAGAA - +4 cisbp__M5350-E2f1-E2f2 5 0.846333 20695.4 1 6 CACCTG TTTGGCGCCAAT - +4 hocomoco__TYY1_MOUSE.H11MO.0.A-CG10431-Taf1-lid-pho-phol 5 0.846333 20695.4 1 6 CACCTG GCCGCCATCTTG - +4 homer__HTGCTGAGTCAT_Nrf2-Jra-cnc-kay-maf-S 6 0.846333 20695.4 1 6 CACCTG ATGACTCAGCAT - +4 transfac_pro__M05671 6 0.846333 20695.4 1 6 CACCTG TTGGTTTTCCAG - +4 transfac_pro__M05751 1 0.846333 20695.4 1 6 CACCTG GAATCTCGCACA - +4 transfac_pro__M05833 6 0.846333 20695.4 1 6 CACCTG TCTACAGTCCTG - +4 transfac_pro__M06236 1 0.846333 20695.4 1 6 CACCTG TATCCTTCCCAG - +4 transfac_pro__M06602 6 0.846333 20695.4 1 6 CACCTG AATTAAAATCGC - +4 transfac_pro__M06813-salm-salr 2 0.846333 20695.4 1 6 CACCTG GCGAAATGCTCG - +4 transfac_pro__M06860 0 0.846333 20695.4 1 6 CACCTG TCCCAAAAAAGC - +4 transfac_pro__M08886 1 0.846333 20695.4 1 6 CACCTG TTTCGTTTTCCT - +4 homer__GATGACTCATCN_Jun-AP1-CoRest-GATAe-Jra-Mef2-Myc-Stat92E-bon-cnc-grn-kay-mor-nej-pan-pnr 7 0.846333 20695.4 1 5 CACCTG GATGACTCATCC + +4 transfac_pro__M05508 7 0.846333 20695.4 1 5 CACCTG TCGGCTTCCCCA - +4 transfac_pro__M05741 7 0.846333 20695.4 1 5 CACCTG GCTGATGCCCCC - +4 transfac_pro__M06229 7 0.846333 20695.4 1 5 CACCTG GCTTCCGCCCCT - +4 transfac_pro__M06317 7 0.846333 20695.4 1 5 CACCTG GCGTTTGGCCCA - +4 transfac_pro__M06367 7 0.846333 20695.4 1 5 CACCTG TCTTTTTCCCCA - +4 transfac_pro__M06489 -1 0.846333 20695.4 1 5 CACCTG TCATTTGGCCCA - +4 transfac_pro__M06507 7 0.846333 20695.4 1 5 CACCTG TATAAAGTCCCT - +4 transfac_pro__M06747-CG3281 -1 0.846333 20695.4 1 5 CACCTG GCGTTAGCTCCA - +4 transfac_pro__M06799 7 0.846333 20695.4 1 5 CACCTG TTTCAAGCCCCG - +4 predrem__nrMotif2495 -2 0.846333 20695.4 1 4 CACCTG CATGGGGCTGGG + +4 c2h2_zfs__M5123 8 0.846333 20695.4 1 4 CACCTG GCTTTTCCCACA - +4 taipale_cyt_meth__CEBPG_NRTTGCGYAAYN_FL-CG7786-gt-Pdp1 -2 0.846333 20695.4 1 4 CACCTG CGTTACGCAACG - +4 transfac_pro__M06458 -2 0.846333 20695.4 1 4 CACCTG TCTGAAAATGGT - +4 transfac_pro__M05118 9 0.846333 20695.4 1 3 CACCTG CAAGCCGTTTAC - +4 hocomoco__ZN214_HUMAN.H11MO.0.C-CG2120 0 0.846997 20711.6 1 6 CACCTG TCCTTTTTGAGGCCTTTGATGA + +4 taipale_tf_pairs__ETV2_GSC2_RCCGGANNNNNNNNNTAATCCN_CAP_repr-Gsc-pnt -1 0.846997 20711.6 1 5 CACCTG ACCGGAAGTACCCGCTAATCCT + +4 cisbp__M0733-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 2 0.847148 20715.3 1 6 CACCTG GTAAACAA + +4 cisbp__M1235-nub-pdm2-vvl 0 0.847148 20715.3 1 6 CACCTG CTAATTAT + +4 cisbp__M1596-D-Sox21a-Sox21b 0 0.847148 20715.3 1 6 CACCTG TAACAATG + +4 cisbp__M4891-cic 0 0.847148 20715.3 1 6 CACCTG CCCATTCA + +4 cisbp__M5638-al-Antp-B-H1-B-H2-bsh-CG11085-CG34367-Dr-en-inv-lab-lbe-lms-Scr-slou-tup-Ubx-unc-4-unpg 1 0.847148 20715.3 1 6 CACCTG TTAATTGG + +4 cisbp__M6055-al-B-H1-B-H2-bsh-C15-CG11085-CG34367-Dr-E5-ems-en-inv-lbe-Lim3-lms-Pph13-slou-Ubx-unpg-Vsx2 1 0.847148 20715.3 1 6 CACCTG TTAATTGG + +4 cisbp__M6065-al-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-PHDP-Pph13-prd-repo-ro-Rx-slou-toy-Traf4- 1 0.847148 20715.3 1 6 CACCTG TTAATTAG + +4 jaspar__MA0125.1-B-H1-B-H2-C15-CG34367-Dll-Dr-E5-Ubx-bsh-ems-en-eve-exex-inv-lab-slou-unpg 0 0.847148 20715.3 1 6 CACCTG TAATTGGT + +4 jaspar__MA1000.1 0 0.847148 20715.3 1 6 CACCTG TGCCGGCG + +4 scertf__macisaac.RTG3-Jra-cnc-kay-maf-S-nej 2 0.847148 20715.3 1 6 CACCTG ATGACTCA + +4 taipale_cyt_meth__ALX3_CYAATTAN_eDBD_meth-al-Awh-bsh-Dll-E5-ems-en-inv-lab-Lim3-slou 1 0.847148 20715.3 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__ALX4_CYAATTAN_eDBD_meth-al-Antp-Awh-CG4328-Dr-E5-ems-en-inv-lab-Lim3-Lmx1a-OdsH-repo-Scr-slou-unc-4 1 0.847148 20715.3 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__ARX_CYAATTAN_eDBD_meth-al-Awh-C15-CG11294-CG34367-CG4328-Drgx-en-ey-ind-inv-lab-Lim3-Lmx1a-OdsH-repo-toy-unc-4-unpg-Vsx2 1 0.847148 20715.3 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__BARHL2_NTAAACGN_FL-B-H1-B-H2-CG11085 2 0.847148 20715.3 1 6 CACCTG CTAAACGG + +4 taipale_cyt_meth__DLX4_NTCGTTAN_FL_meth-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-eve-exex-HGTX-ind-lab-pb-Scr-Ubx-unpg 0 0.847148 20715.3 1 6 CACCTG GTCATTAT + +4 taipale_cyt_meth__DLX5_NTCGTTAN_eDBD_meth-abd-A-bsh-btn-Dll-Dr-eve-ind-Ubx 0 0.847148 20715.3 1 6 CACCTG ATCATTAT + +4 taipale_cyt_meth__DLX6_NTCGTTAN_eDBD_meth-bsh-btn-Dll-eve-ind-unpg 0 0.847148 20715.3 1 6 CACCTG GTCGTTAT + +4 taipale_cyt_meth__OTX1_NTAATCCN_eDBD-Gsc-oc 2 0.847148 20715.3 1 6 CACCTG CTAATCCG + +4 cisbp__M1373 2 0.847148 20715.3 1 6 CACCTG CTCATCGC - +4 cisbp__M1620 2 0.847148 20715.3 1 6 CACCTG GCGGCCGG - +4 cisbp__M5089-lola 0 0.847148 20715.3 1 6 CACCTG CGCCCAAA - +4 swissregulon__sacCer__FHL1-CHES-1-like-jumu 2 0.847148 20715.3 1 6 CACCTG TTTGCGTC - +4 taipale__MSX1_DBD_NYAATTAN_repr-al-Antp-B-H1-B-H2-bsh-CG11085-CG34367-Dr-en-inv-lab-lbe-lms-Scr-slou-tup-Ubx-unc-4-unpg 1 0.847148 20715.3 1 6 CACCTG TTAATTGG - +4 taipale__MSX1_full_NYAATTAN-bsh-C15-CG18599-CG34367-CG9876-Dr-en-inv-lbe-Lim3-lms-OdsH-Pph13-Rx-Ubx-unpg-Vsx1-Vsx2 1 0.847148 20715.3 1 6 CACCTG CTAATTGG - +4 taipale__Msx3_DBD_NYAATTAN-al-B-H1-B-H2-bsh-C15-CG11085-CG34367-Dr-E5-ems-en-inv-lbe-Lim3-lms-Pph13-slou-Ubx-unpg-Vsx2 1 0.847148 20715.3 1 6 CACCTG TTAATTGG - +4 taipale_cyt_meth__GBX2_NCAATTAN_FL_meth-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2 1 0.847148 20715.3 1 6 CACCTG CTAATTGG - +4 taipale_cyt_meth__PHOX2A_CYAATTAN_eDBD-Antp-Awh-bsh-CG11294-Drgx-E5-ems-en-inv-lab-Lim3-pb-Scr-slou 1 0.847148 20715.3 1 6 CACCTG GTAATTAG - +4 taipale_cyt_meth__RHOXF1_NGGATCAN_FL_meth 2 0.847148 20715.3 1 6 CACCTG TTGATCCC - +4 transfac_pro__M01095-ap 1 0.847148 20715.3 1 6 CACCTG ATAATACA - +4 transfac_pro__M04849-Dif-dl 2 0.847148 20715.3 1 6 CACCTG GGGACTTT - +4 cisbp__M0226 3 0.847148 20715.3 1 5 CACCTG CCACGCGT + +4 jaspar__MA0420.1 -1 0.847148 20715.3 1 5 CACCTG ACCGGAAC + +4 jaspar__MA0933.1-CTCF 3 0.847148 20715.3 1 5 CACCTG AATTAAAT + +4 jaspar__MA0934.1 3 0.847148 20715.3 1 5 CACCTG AATTAATT + +4 cisbp__M0555 -1 0.847148 20715.3 1 5 CACCTG TCCCGCTC - +4 cisbp__M1428 3 0.847148 20715.3 1 5 CACCTG GGACACAA - +4 cisbp__M1724 -1 0.847148 20715.3 1 5 CACCTG GCCGGCAA - +4 cisbp__M4209 -1 0.847148 20715.3 1 5 CACCTG ACCGGAAC - +4 jaspar__MA0309.1-GATAd-GATAe-grn-pnr-srp 3 0.847148 20715.3 1 5 CACCTG TCTTATCA - +4 transfac_pro__M01902-GATAd-GATAe-grn-pnr-srp 3 0.847148 20715.3 1 5 CACCTG TCTTATCA - +4 transfac_pro__M01949 -1 0.847148 20715.3 1 5 CACCTG ACCGGAAC - +4 elemento__CGCACACA 4 0.847148 20715.3 1 4 CACCTG CGCACACA + +4 elemento__TCGTCATC 4 0.847148 20715.3 1 4 CACCTG TCGTCATC + +4 flyfactorsurvey__Mirr_Cell_FBgn0014343-mirr 4 0.847148 20715.3 1 4 CACCTG AAAAAACA + +4 elemento__CGTGGCCA 4 0.847148 20715.3 1 4 CACCTG TGGCCACG - +4 fantom__motif112_CGYGYAWT 4 0.847148 20715.3 1 4 CACCTG ATTGCACG - +4 predrem__nrMotif1729 -2 0.847148 20715.3 1 4 CACCTG CCCATTGC - +4 stark__CGTGNGAA 4 0.847148 20715.3 1 4 CACCTG TTCACACG - +4 cisbp__M1194-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ind-lbe-Lim3-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-Vsx2-zfh2 -3 0.847148 20715.3 1 3 CACCTG CTAATTAA + +4 cisbp__M1538-CG9727 5 0.847148 20715.3 1 3 CACCTG ATAGCAAC - +4 predrem__nrMotif1968 -3 0.847148 20715.3 1 3 CACCTG CTCTGCGC - +4 scertf__macisaac.ARG81 5 0.847148 20715.3 1 3 CACCTG AGAGTCAC - +4 transfac_pro__M08914-bon-cnc-Jra-kay-maf-S-Mef2-nej-NFAT-pan-Stat92E 5 0.847148 20715.3 1 3 CACCTG TGAGTCAT - +4 taipale_tf_pairs__TEAD4_FOXI1_RCATWCCNNNNNNNNNNNNRTMAACA_CAP_repr-sd 3 0.847607 20726.5 1 6 CACCTG ACATTCCACCGCAACGAACGTAAACA + +4 tfdimers__MD00450 18 0.847607 20726.5 1 6 CACCTG TTTCCCTAATCCCCCTCACCCCCTCC - +4 tfdimers__MD00577-pan 5 0.847607 20726.5 1 6 CACCTG TTTTTTTTTTGCATTTTGATGTTTTT - +4 cisbp__M0958-al-Awh-C15-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-en-inv-lab-Lim3-Lmx1a-OdsH-repo-unc-4-Vsx1-Vsx2 1 0.847717 20729.2 1 6 CACCTG CTAATTA + +4 cisbp__M5028-Hmx 1 0.847717 20729.2 1 6 CACCTG TTAATTG + +4 flyfactorsurvey__NK7.1_SOLEXA_FBgn0024321-Antp-CG32532-CG34367-E5-NK7.1-OdsH-Scr-Ubx-abd-A-en-lms-repo-slou-tup-unc-4-unpg 1 0.847717 20729.2 1 6 CACCTG TTAATTG + +4 predrem__nrMotif1523 0 0.847717 20729.2 1 6 CACCTG GAACTCA + +4 predrem__nrMotif1785 1 0.847717 20729.2 1 6 CACCTG ATTGCTG + +4 predrem__nrMotif2005 1 0.847717 20729.2 1 6 CACCTG ATTCCAA + +4 predrem__nrMotif2633 0 0.847717 20729.2 1 6 CACCTG TGCATAG + +4 scertf__badis.HCM1-FoxK-FoxL1-FoxP-bin-fd19B-fd102C-foxo-slp1-slp2 1 0.847717 20729.2 1 6 CACCTG TAAACAA + +4 transfac_pro__M04862-ewg 0 0.847717 20729.2 1 6 CACCTG AAGCGGA + +4 hdpi__NR4A2-Hr38 -1 0.847717 20729.2 1 5 CACCTG AATTGGA + +4 predrem__nrMotif1392 2 0.847717 20729.2 1 5 CACCTG ATCATCA + +4 taipale__MEIS1_DBD_NTGACAN_repr 2 0.847717 20729.2 1 5 CACCTG TTGACAG + +4 transfac_pro__M01102-sd 2 0.847717 20729.2 1 5 CACCTG CATTTCT + +4 hdpi__PPP1R10-PNUTS 3 0.847717 20729.2 1 4 CACCTG ATGAAAC + +4 cisbp__M6315-tup 3 0.847717 20729.2 1 4 CACCTG CATTAAC - +4 swissregulon__sacCer__STE12 3 0.847717 20729.2 1 4 CACCTG TGAAACA - +4 transfac_pro__M07057-Ptx1 3 0.847717 20729.2 1 4 CACCTG TCTAATC - +4 cisbp__M5474-croc-fd59A-FoxK-foxo-slp2 4 0.847717 20729.2 1 3 CACCTG TGTTTAC - +4 taipale__FOXP3_DBD_RTAAACA-croc-fd59A-FoxK-slp2 4 0.847717 20729.2 1 3 CACCTG TGTTTAC - +4 taipale_cyt_meth__ZNF177_NTYGRTCKNNNNNNNNAGTCATN_eDBD 9 0.848187 20740.7 1 6 CACCTG AATGACTGTGCCCTTCGATCGAG - +4 cisbp__M4013-CrebB 8 0.848457 20747.3 1 6 CACCTG ATGACGCATACCCCC + +4 cisbp__M5368-btd-klu-Spps-sr 2 0.848457 20747.3 1 6 CACCTG AGTGCGTGGGCGTAG + +4 hocomoco__HSF4_HUMAN.H11MO.0.D-Hsf-pb 3 0.848457 20747.3 1 6 CACCTG TAGAACGTTCTAGAA + +4 predrem__nrMotif1875-Brf-crol 5 0.848457 20747.3 1 6 CACCTG CCCCCCTCCCCGCCA + +4 taipale_cyt_meth__TCF7L1_WCATCGRGRCGCTGW_eDBD_meth_repr-pan 1 0.848457 20747.3 1 6 CACCTG ACATCGGGGCGCTGA + +4 transfac_pro__M01683 1 0.848457 20747.3 1 6 CACCTG AAGCCGGAAGCGGGG + +4 transfac_pro__M09328 4 0.848457 20747.3 1 6 CACCTG CCTAAACCCTAAATC + +4 cisbp__M1884-Mef2-rump 0 0.848457 20747.3 1 6 CACCTG ATGCTATTTTTAGCT - +4 cisbp__M2274-klu-sr 0 0.848457 20747.3 1 6 CACCTG CCCCCGCCCACGCAC - +4 cisbp__M3676-nub-pdm2-vvl 0 0.848457 20747.3 1 6 CACCTG TACATGCATATTCAT - +4 cisbp__M3985-Stat92E 3 0.848457 20747.3 1 6 CACCTG GATTTCCTGGAATTC - +4 factorbook__SOX2-OCT4-CG9650-SoxN-nej-pan 2 0.848457 20747.3 1 6 CACCTG TTTGCATAACAAAGG - +4 hocomoco__PBX1_HUMAN.H11MO.1.C 2 0.848457 20747.3 1 6 CACCTG CCCATCAATCAAATT - +4 jaspar__MA0591.1-Jra-Mef2-cnc-kay-maf-S-mor 9 0.848457 20747.3 1 6 CACCTG GTGCTGAGTCATCCT - +4 taipale__EGR2_full_NNMCGCCCACGCANN-btd-klu-Spps-sr 2 0.848457 20747.3 1 6 CACCTG AGTGCGTGGGCGTAG - +4 transfac_pro__M07218-Mef2-rump 0 0.848457 20747.3 1 6 CACCTG ATGCTATTTTTAGCT - +4 cisbp__M4454-Chd1-CoRest 10 0.848457 20747.3 1 5 CACCTG GTTCTCGCGAGATTT - +4 hocomoco__ZN136_HUMAN.H11MO.0.C 1 0.848648 20752 1 6 CACCTG CAACCAAGAATACTATATCCAGCA - +4 tfdimers__MD00204-scro 2 0.848648 20752 1 6 CACCTG TTTTACTTCCTCTTGAGTGTTCCT - +4 tfdimers__MD00453 3 0.848648 20752 1 6 CACCTG AATAATCTGATTTAATTAAATTTA - +4 swissregulon__hs__POU2F1..3.p2-nub-pdm2-vvl 2 0.849474 20772.2 1 6 CACCTG CTCATTTGCATAT + +4 transfac_pro__M07718-fd59A-fkh-Sox21a 7 0.849474 20772.2 1 6 CACCTG AAACAATAACAAT + +4 cisbp__M1744 3 0.849474 20772.2 1 6 CACCTG CGGATCCGGAATA - +4 cisbp__M6234-bin-croc-fd59A-fkh-foxo-HDAC1 5 0.849474 20772.2 1 6 CACCTG TTGTTTGCTTTGC - +4 taipale_cyt_meth__MAFA_NWWWNTGCTGACN_eDBD_meth-maf-S-tj 3 0.849474 20772.2 1 6 CACCTG AGTCAGCACATTT - +4 taipale_tf_pairs__POU2F1_EOMES_NTATKCAGYGTNA_CAP-nub-pdm2 1 0.849474 20772.2 1 6 CACCTG TCACACTGAATAA - +4 transfac_pro__M07882-Rfx 2 0.849474 20772.2 1 6 CACCTG GTTGCCTAGCAAC - +4 taipale_cyt_meth__ZNF740_NYGCCCCCCCCAC_eDBD_meth 10 0.849474 20772.2 1 3 CACCTG CTGCCCCCCCCAC + +4 taipale_cyt_meth__POU3F2_NTATGCWAATKAG_eDBD_meth-Dll-dve-nub-pdm2-pdm3-vvl -3 0.849474 20772.2 1 3 CACCTG CTCATTTGCATAA - +4 taipale_cyt_meth__POU3F4_NTATGCWAATKAG_eDBD_meth-Dll-dve-nub-pdm2-pdm3-vvl -3 0.849474 20772.2 1 3 CACCTG CTCATTTGCATAA - +4 cisbp__M3032-nej 8 0.850042 20786.1 1 6 CACCTG ATATTGCAAAATCA + +4 cisbp__M3186-aop-Atac3-Eip74EF-Ets21C-Ets96B-Ets97D 2 0.850042 20786.1 1 6 CACCTG CCAACCGGAAGTCC + +4 neph__UW.Motif.0367 8 0.850042 20786.1 1 6 CACCTG AAATCACAGTTCTG + +4 transfac_pro__M09222 1 0.850042 20786.1 1 6 CACCTG ACACCAATAATTGG + +4 transfac_public__M00116-nej 8 0.850042 20786.1 1 6 CACCTG ATATTGCAAAATCA + +4 cisbp__M5079-lmd-opa-sug 2 0.850042 20786.1 1 6 CACCTG ACGACCCCCCACAG - +4 hocomoco__PO3F1_HUMAN.H11MO.0.C-vvl 2 0.850042 20786.1 1 6 CACCTG TTTGCATTACAATG - +4 neph__UW.Motif.0535 2 0.850042 20786.1 1 6 CACCTG GCTCTGTGGCTCTG - +4 transfac_public__M00025-aop-Eip74EF-Ets21C-Ets96B-Ets97D 4 0.850042 20786.1 1 6 CACCTG GGACTTCCGGTTGG - +4 taipale_cyt_meth__GLIS2_RCCCCCCRCGWYGN_eDBD_repr-ci-lmd-sug -1 0.850042 20786.1 1 5 CACCTG ACCCCCCGCGACGC + +4 taipale_cyt_meth__ZNF75A_NGCTTTTCCCACAN_FL 9 0.850042 20786.1 1 5 CACCTG GTGTGGGAAAAGCT - +4 taipale_tf_pairs__HOXB2_SOX15_NYMATTANNNNNNACAATR_CAP_repr-pb 5 0.851046 20810.6 1 6 CACCTG CTAATTACCCAAAACAATG + +4 transfac_pro__M09350 8 0.851046 20810.6 1 6 CACCTG AAAATTAAACCCTAATTTT + +4 taipale_cyt_meth__FOXN2_NNGCGTSNNNNNSACGCNN_eDBD_repr-CHES-1-like 1 0.851046 20810.6 1 6 CACCTG ACGCGTCGTTACGACGCGT - +4 taipale_tf_pairs__CUX1_FOXO6_RTAAACANNNNNATCRATN_CAP-ct-foxo 7 0.851046 20810.6 1 6 CACCTG TATCGATCAGTTTGTTTAC - +4 transfac_pro__M06306 13 0.851046 20810.6 1 6 CACCTG CCGTATCTTATTTCACACG - +4 transfac_pro__M06651 12 0.851046 20810.6 1 6 CACCTG GGGTCTTTTACCCCCCTTG - +4 taipale_cyt_meth__JUN_NATGACKCATN_FL-cnc-Jra-kay-Mef2-Myc-nej-pan 5 0.852011 20834.2 1 6 CACCTG GATGACGCATC + +4 taipale_cyt_meth__KLF12_NRCCACGCCCW_FL-btd-cbt-CG3065-CG42741-dar1-luna-Sp1-Spps 0 0.852011 20834.2 1 6 CACCTG GACCACGCCCA + +4 taipale_cyt_meth__PROP1_TAATTNNATTA_FL_repr-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-en-hbn-inv-Lim3-OdsH-Optix-repo-Traf4-unc-4 0 0.852011 20834.2 1 6 CACCTG TAATTAGATTA + +4 yetfasco__YFL031W_94 2 0.852011 20834.2 1 6 CACCTG GGCAGCGTGTC + +4 hocomoco__MBD2_HUMAN.H11MO.0.B-MBD-like 1 0.852011 20834.2 1 6 CACCTG CCTCCGGCCCG - +4 transfac_pro__M00934-z 5 0.852011 20834.2 1 6 CACCTG TCACTCAAATT - +4 transfac_pro__M08946-bon-Jra-kay-Mef2-pan 5 0.852011 20834.2 1 6 CACCTG GATGACTCATA - +4 hocomoco__MAFB_HUMAN.H11MO.0.B-cnc-maf-S-tj -1 0.852011 20834.2 1 5 CACCTG TGCTGACTCAG + +4 swissregulon__hs__NFE2.p2-Jra-cnc-ewg-kay-maf-S -1 0.852011 20834.2 1 5 CACCTG TGCTGAGTCAC + +4 cisbp__M3617-cnc-ewg-Jra-kay-maf-S -1 0.852011 20834.2 1 5 CACCTG TGCTGAGTCAC - +4 taipale_cyt_meth__HOXA13_NCTCGTAAAAN_eDBD -2 0.852011 20834.2 1 4 CACCTG GCTCGTAAAAC + +4 taipale_cyt_meth__HOXB13_NCTCGTAAAAN_eDBD_meth -2 0.852011 20834.2 1 4 CACCTG GCTCGTAAAAT + +4 cisbp__M1856-E2f1-E2f2 -2 0.852011 20834.2 1 4 CACCTG CCTCCCGCCCG - +4 cisbp__M6502-Tbp 7 0.852011 20834.2 1 4 CACCTG GAATTTATACC - +4 jaspar__MA0491.1-CoRest-Jra-Mef2-Myc-Stat92E-bon-cnc-kay-mor-nej-pan 7 0.852011 20834.2 1 4 CACCTG GATGAGTCACC - +4 taipale__HOXA10_DBD_NGYAATWAAAN-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.852011 20834.2 1 4 CACCTG TTTTTATTACC - +4 taipale_cyt_meth__HOXC10_NRTCGTAAAAN_FL_meth-Abd-B-cad 7 0.852011 20834.2 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M07206-E2f1-E2f2 -2 0.852011 20834.2 1 4 CACCTG CCTCCCGCCCG - +4 transfac_pro__M07754-Abd-B-cad 7 0.852011 20834.2 1 4 CACCTG ATTTTACGACC - +4 cisbp__M5467-foxo 8 0.852011 20834.2 1 3 CACCTG TTTCCCCACAC - +4 tfdimers__MD00549 8 0.852371 20843 1 6 CACCTG TAAAAAAGATGCTGTTAATGATTAACTTTA + +4 cisbp__M4551-bon 4 0.852478 20845.7 1 6 CACCTG TTCATACTGGAGAGAAA + +4 taipale_tf_pairs__POU2F1_SOX2_NATTTRCNNNACAATRN_CAP_repr-nub-pdm2-SoxN 4 0.852478 20845.7 1 6 CACCTG AATTTGCATAACAATGG + +4 transfac_pro__M01323-Antp-Awh-CG18599-CG4328-Dfd-Lim3-Lmx1a-OdsH-otp-repo-Scr-unc-4-zfh2 10 0.852478 20845.7 1 6 CACCTG CGTAATTAATTAATTGG + +4 transfac_pro__M01453-abd-A-Awh-CG18599-CG32532-CG34367-CG4328-Dfd-HGTX-Lim3-Lmx1a-otp-pdm3-Ubx-Vsx1-vvl-zfh2 0 0.852478 20845.7 1 6 CACCTG CGCATTAATTAATTGGC + +4 hocomoco__SPIB_HUMAN.H11MO.0.A-CG9650-Dif-MTA1-like-Stat92E-dl-ebi-nej-sv 6 0.852478 20845.7 1 6 CACCTG TTTCACTTCCTCTTTTT - +4 taipale_cyt_meth__NFIB_NTTGGCNNNNTGCCARN_FL_meth-C15-Nf1-NfI 5 0.852478 20845.7 1 6 CACCTG CTTGGCACCGTGCCAAC - +4 taipale_tf_pairs__ELK1_ONECUT2_RSCGGAASNGRTCGATA_HT-onecut 10 0.852478 20845.7 1 6 CACCTG TATCGATCGGTTCCGGT - +4 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNNYMATTA_CAP_repr-pb 4 0.852478 20845.7 1 6 CACCTG TAATTGCGTTCCATTGT - +4 transfac_pro__M02897-Optix 11 0.852478 20845.7 1 6 CACCTG AGGCGGATATATCCCAT - +4 transfac_pro__M02909-Sox14 0 0.852478 20845.7 1 6 CACCTG TTCCTAACAATTTTTCC - +4 transfac_pro__M06426 11 0.852478 20845.7 1 6 CACCTG ATCCTTTGGCTTATCCC - +4 transfac_pro__M06927-kn 7 0.852478 20845.7 1 6 CACCTG CTGAAACCCCCTTTCCG - +4 taipale_cyt_meth__SP2_NYWAGYCCCGCCCMCYN_eDBD_repr-btd-E2f2-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps 12 0.852478 20845.7 1 5 CACCTG CTAAGCCCCGCCCACTT + +4 swissregulon__sacCer__GAL80 12 0.852478 20845.7 1 5 CACCTG CGGATGACAATCCTCCG - +4 cisbp__M0679-E2f1 3 0.852956 20857.3 1 6 CACCTG GCGCGCCAA + +4 cisbp__M5666-NfI 2 0.852956 20857.3 1 6 CACCTG TGTGCCAAT + +4 cisbp__M5718-bcd-oc-Ptx1 3 0.852956 20857.3 1 6 CACCTG GTTAATCCC + +4 cisbp__M6490 2 0.852956 20857.3 1 6 CACCTG AAAACAAAA + +4 jaspar__MA0285.1-CG2120 3 0.852956 20857.3 1 6 CACCTG CTAAGCCAC + +4 predrem__nrMotif1614 1 0.852956 20857.3 1 6 CACCTG AAATCTCTA + +4 predrem__nrMotif869 0 0.852956 20857.3 1 6 CACCTG AGCCACAAA + +4 scertf__harbison.HAP4-Nf-YA-Nf-YB-Nf-YC 0 0.852956 20857.3 1 6 CACCTG GACCAATCA + +4 stark__TGACGTCAT-Atf3-Atf6-Atf-2-CG44247-CrebA-CrebB-Jra-REPTOR-BP-Xbp1-cnc-crc-kay 1 0.852956 20857.3 1 6 CACCTG TGACGTCAT + +4 taipale__PITX1_full_NTTAATCCN-bcd-oc-Ptx1 3 0.852956 20857.3 1 6 CACCTG CTTAATCCC + +4 transfac_pro__M01646-CG2120 3 0.852956 20857.3 1 6 CACCTG CTAAGCCAC + +4 cisbp__M0931-CG32532-CG4328-Dll-Lim1-Lim3-Lmx1a 3 0.852956 20857.3 1 6 CACCTG AATTAATTA - +4 cisbp__M2090-CG2120 3 0.852956 20857.3 1 6 CACCTG CTAAGCCAC - +4 hocomoco__SRY_HUMAN.H11MO.0.B 2 0.852956 20857.3 1 6 CACCTG AAAACAAAA - +4 predrem__nrMotif2403 3 0.852956 20857.3 1 6 CACCTG CAAGAATTT - +4 predrem__nrMotif652 3 0.852956 20857.3 1 6 CACCTG AAATACAAA - +4 predrem__nrMotif836 2 0.852956 20857.3 1 6 CACCTG AATTACTGA - +4 yetfasco__YNL027W_516-CG2120 3 0.852956 20857.3 1 6 CACCTG CTAAGCCAC - +4 predrem__nrMotif1841 -1 0.852956 20857.3 1 5 CACCTG ACTCATGCC + +4 predrem__nrMotif2464 -1 0.852956 20857.3 1 5 CACCTG TGCTTTGCT + +4 cisbp__M0106 4 0.852956 20857.3 1 5 CACCTG TAATTAAAA - +4 hocomoco__NFAC2_HUMAN.H11MO.0.B-NFAT 4 0.852956 20857.3 1 5 CACCTG AATTTTCCA - +4 predrem__nrMotif1775 4 0.852956 20857.3 1 5 CACCTG TGCTCATCA - +4 predrem__nrMotif743 -1 0.852956 20857.3 1 5 CACCTG TGCTTCTCA - +4 cisbp__M0982-abd-A-al-Antp-ap-Awh-bsh-btn-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-hbn-HGTX-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-otp-pb-Pph13-repo-ro 5 0.852956 20857.3 1 4 CACCTG TTAATTACC + +4 predrem__nrMotif308 -2 0.852956 20857.3 1 4 CACCTG TCTGCCATT + +4 predrem__nrMotif46 -2 0.852956 20857.3 1 4 CACCTG TCTGTTTCT + +4 cisbp__M4830-bin-CHES-1-like-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.852956 20857.3 1 4 CACCTG TTGTTTATC - +4 predrem__nrMotif1668 5 0.852956 20857.3 1 4 CACCTG TGAGAGACA - +4 predrem__nrMotif1773 5 0.852956 20857.3 1 4 CACCTG GGCATTACA - +4 predrem__nrMotif388 -2 0.852956 20857.3 1 4 CACCTG CCTCTCCCG - +4 predrem__nrMotif473 -2 0.852956 20857.3 1 4 CACCTG TCTGAGAAA - +4 predrem__nrMotif552 -2 0.852956 20857.3 1 4 CACCTG TCTGTATTT - +4 transfac_pro__M07400-Jra-kay-Myc-Stat92E -3 0.852956 20857.3 1 3 CACCTG ATGACTCAT + +4 predrem__nrMotif693 -3 0.852956 20857.3 1 3 CACCTG CTGTTGAGT - +4 transfac_pro__M02014-fkh 6 0.852956 20857.3 1 3 CACCTG AGCAAACAA - +4 cisbp__M1144-Antp-CG9876-CG34367-Dr-E5-HGTX-Lim1-Scr-Ubx-bsh-ems-en-eve-ind-inv-lab-slou-unpg 3 0.854301 20890.2 1 6 CACCTG GACTAATTAA + +4 cisbp__M5595-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ftz-hbn-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 2 0.854301 20890.2 1 6 CACCTG GCTAATTGGC + +4 homer__ATTGCATCAT_Chop-Myc-nej 4 0.854301 20890.2 1 6 CACCTG ATTGCATCAT + +4 jaspar__MA1032.1 1 0.854301 20890.2 1 6 CACCTG ATGCCGACAT + +4 predrem__nrMotif1185 3 0.854301 20890.2 1 6 CACCTG GCCAGCCGGG + +4 predrem__nrMotif2615 4 0.854301 20890.2 1 6 CACCTG CGCTGTCCCC + +4 swissregulon__sacCer__LYS14 3 0.854301 20890.2 1 6 CACCTG AAATTCCGGG + +4 taipale__HOXC10_DBD_CCCATWAAAN-cad 0 0.854301 20890.2 1 6 CACCTG CCCATAAAAA + +4 taipale_cyt_meth__OTX1_NTAATCCNYN_FL-bcd-Gsc-oc 3 0.854301 20890.2 1 6 CACCTG TTAATCCGCT + +4 taipale_cyt_meth__OTX1_NTAATCCNYN_FL_meth_repr-Gsc-oc-Ptx1 3 0.854301 20890.2 1 6 CACCTG CTAATCCCCT + +4 transfac_pro__M03183 4 0.854301 20890.2 1 6 CACCTG CTGCCGCCGG + +4 transfac_pro__M03796 3 0.854301 20890.2 1 6 CACCTG GGTCAGCAGA + +4 transfac_pro__M04989 4 0.854301 20890.2 1 6 CACCTG AGGCCGCCTC + +4 transfac_pro__M05041 4 0.854301 20890.2 1 6 CACCTG ACGCCGCCCG + +4 transfac_pro__M05147 4 0.854301 20890.2 1 6 CACCTG ATGCCGCCCA + +4 cisbp__M0865 2 0.854301 20890.2 1 6 CACCTG TTTATTGATT - +4 cisbp__M5294-B-H1-B-H2-NK7.1 0 0.854301 20890.2 1 6 CACCTG ACCGTTTAAC - +4 cisbp__M6312-Blimp-1-Stat92E 3 0.854301 20890.2 1 6 CACCTG TTTCACTTTC - +4 taipale__BARHL2_DBD_NNTAAACGNN-B-H1-B-H2-NK7.1 0 0.854301 20890.2 1 6 CACCTG ACCGTTTAAC - +4 taipale_cyt_meth__NEUROG1_RNCATATGNY_eDBD-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.854301 20890.2 1 6 CACCTG GACATATGTC - +4 taipale_cyt_meth__PBX1_KTGATTGAYR_eDBD 4 0.854301 20890.2 1 6 CACCTG TGTCAATCAA - +4 taipale_cyt_meth__SMAD5_YGTCTAGACA_eDBD_meth_repr-Mad 0 0.854301 20890.2 1 6 CACCTG TGTCTAGACG - +4 transfac_pro__M08934-bon-Jra-kay-Mef2-Myc-nej-NFAT-pan-Stat92E 4 0.854301 20890.2 1 6 CACCTG ATGACTCATA - +4 cisbp__M1500 5 0.854301 20890.2 1 5 CACCTG ACTGGAACAG + +4 cisbp__M1227 -1 0.854301 20890.2 1 5 CACCTG GTATAATTAT - +4 tiffin__TIFDMEM0000063 -1 0.854301 20890.2 1 5 CACCTG TGCTGGCAAA - +4 taipale__Hoxd3_DBD_NNYAATTANN-abd-A-Antp-ap-Awh-B-H1-B-H2-btn-CG11085-CG11294-CG18599-CG32532-CG4328-CG9876-Dll-Dr-Drgx-dve-E5-ems-en-eve-exex-ftz-HGTX-Hmx-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-Od 6 0.854301 20890.2 1 4 CACCTG AGTAATTAAC + +4 taipale_cyt_meth__ARGFX_NCTAATTARN_eDBD_meth-al-ap-Awh-C15-CG18599-CG34367-E5-ems-en-ind-Lim3-otp-pb-Pph13-Rx-unpg-Vsx1-Vsx2 -2 0.854301 20890.2 1 4 CACCTG TCTAATTAGA + +4 transfac_pro__M07785-ap-Awh-CG18599-dve-en-ey-inv-repo-toy-zfh2 -2 0.854301 20890.2 1 4 CACCTG GCTAATTAAC + +4 cisbp__M5541-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Drgx-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-Lim3-Lmx1a-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen 6 0.854301 20890.2 1 4 CACCTG AGTAATTAAC - +4 taipale_cyt_meth__VENTX_NGYAATTAGN_FL-Antp-Dfd-E5-ems-en-eve-exex-ind-inv-lbl-pb-Rx-Scr-slou-unpg 6 0.854301 20890.2 1 4 CACCTG GCTAATTACC - +4 predrem__nrMotif294 -3 0.854301 20890.2 1 3 CACCTG CTTTTTATTT + +4 hocomoco__PBX1_HUMAN.H11MO.0.A -3 0.854301 20890.2 1 3 CACCTG CTGTCAATCA - +4 dbcorrdb__CHD1__ENCSR000AQK_1__m2-Chd1 14 0.854857 20903.8 1 6 CACCTG AAACAAACGAATAAATGTTG + +4 dbcorrdb__E2F6__ENCSR000EVK_1__m1-Brf-brm-CTCF-E2f1-E2f2-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-Spt20-SREBP-Taf1-vtd 11 0.854857 20903.8 1 6 CACCTG CCCTTCCCGCCCTCCCGCCC + +4 dbcorrdb__ELK1__ENCSR000ECI_1__m1-aop-Atac3-Brf-brm-bs-CrebB-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Max-Myc-pho-phol-pnt-RpII215-Sin3A-SREBP-Taf1-tna 10 0.854857 20903.8 1 6 CACCTG CCGCCGCCGCCACTTCCGGC + +4 dbcorrdb__EZH2__ENCSR000ARH_1__m5-E(z) 2 0.854857 20903.8 1 6 CACCTG GGGTCCGGGTTTCCTCGCCC + +4 dbcorrdb__EZH2__ENCSR000ASY_1__m3-E(z) 11 0.854857 20903.8 1 6 CACCTG GCGGCGGCCTAAACCCGAAG + +4 dbcorrdb__JUND__ENCSR000EEI_1__m1-Jra-kay-nej-Stat92E 13 0.854857 20903.8 1 6 CACCTG AAAAAGATTGAGTCATCATT + +4 dbcorrdb__NFYA__ENCSR000DNN_1__m1-btd-CG7839-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 5 0.854857 20903.8 1 6 CACCTG GGCCGCACCAGCCAATCAGA + +4 dbcorrdb__POLR2A__ENCSR000DNF_1__m1-RpII215 3 0.854857 20903.8 1 6 CACCTG GGCCTCGTTGCGCCTGCGCC + +4 dbcorrdb__POLR2A__ENCSR000FAJ_1__m1-CG10431-RpII215-Taf1 5 0.854857 20903.8 1 6 CACCTG CACGCCGCTTCCGCCATATT + +4 dbcorrdb__RELA__ENCSR000EBI_1__m2-Blimp-1-Dif-dl 1 0.854857 20903.8 1 6 CACCTG GCACTTTCTGTTTCAGTACG + +4 dbcorrdb__SIX5__ENCSR000BIQ_1__m2-Hcf-Six4 14 0.854857 20903.8 1 6 CACCTG CCCGGCCGCAGGGCATGCTG + +4 dbcorrdb__SREBF1__ENCSR000DYU_1__m5-SREBP 10 0.854857 20903.8 1 6 CACCTG CCGCCGTGCTGACCGCAGCC + +4 dbcorrdb__SUPT20H__ENCSR000DNP_1__m2-Spt20 13 0.854857 20903.8 1 6 CACCTG TGTTCTTATTCATAATATCT + +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m6-Su(z)12 1 0.854857 20903.8 1 6 CACCTG CGGCCCGGCAACCCGGCGCT + +4 dbcorrdb__ZBTB33__ENCSR000BHC_1__m1-Chd1-CoRest 10 0.854857 20903.8 1 6 CACCTG GCTCTCGCGAGACCTGGGGG + +4 transfac_pro__M01519 2 0.854857 20903.8 1 6 CACCTG GTGACTTTCCGGAATACTAA + +4 transfac_pro__M01651 1 0.854857 20903.8 1 6 CACCTG GGACATGTCCGGACATGTCC + +4 transfac_pro__M01969-foxo 9 0.854857 20903.8 1 6 CACCTG GTAAACAACAACATGTTGAC + +4 c2h2_zfs__M1808-Six4-egg 0 0.854857 20903.8 1 6 CACCTG GATTTCCCATAATGCCTTGC - +4 dbcorrdb__CHD1__ENCSR000AQD_1__m2-Chd1 0 0.854857 20903.8 1 6 CACCTG CTCCCGGTCCTTCGCCACGG - +4 dbcorrdb__CHD1__ENCSR000AQK_1__m5-Chd1 1 0.854857 20903.8 1 6 CACCTG AGGTCTAACCGAAAAAGCGA - +4 dbcorrdb__CHD1__ENCSR000EFC_1__m4-Chd1 4 0.854857 20903.8 1 6 CACCTG CGCCGACGTTCTCGTCGGCT - +4 dbcorrdb__EP300__ENCSR000ECV_1__m1-Jra-kay-nej-Stat92E 11 0.854857 20903.8 1 6 CACCTG GGATGACTCAATATTTAGGA - +4 dbcorrdb__JUN__ENCSR000EEK_1__m1-Atf3-Atf6-cnc-crc-CrebA-CrebB-Jra-kay-Stat92E-Xbp1 10 0.854857 20903.8 1 6 CACCTG AAGATTACGTCATCCTTTAA - +4 dbcorrdb__KAT2A__ENCSR000ECR_1__m1-Brf-brm-btd-CoRest-ct-CTCF-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-vtd 1 0.854857 20903.8 1 6 CACCTG CCGCCCCCCCTGCTCCCCCC - +4 dbcorrdb__MXI1__ENCSR000EIA_1__m3 2 0.854857 20903.8 1 6 CACCTG CCCGGCGGTAAGCATGACGG - +4 dbcorrdb__NRF1__ENCSR000EHH_1__m1-E2f1-ewg-E(z)-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG3388 5 0.854857 20903.8 1 6 CACCTG CCCTGCGCATGCGCAGGGGG - +4 dbcorrdb__PHF8__ENCSR000AQH_1__m2-CG10431-lid-Myc-pho-phol-RpII215-Taf1-Taf7-tna 0 0.854857 20903.8 1 6 CACCTG GACATGGCGGCGGCGGCGGG - +4 dbcorrdb__RCOR1__ENCSR000DZC_1__m1-Chd1-CoRest 14 0.854857 20903.8 1 6 CACCTG TCCGGTTCTCGCGAGAGCTG - +4 hocomoco__IRF5_HUMAN.H11MO.0.D 12 0.854857 20903.8 1 6 CACCTG TCACTTTTGGCTTTCCTTTC - +4 hocomoco__IRF8_HUMAN.H11MO.0.B-Blimp-1-CG9650-MTA1-like-Stat92E-ebi-nej-sv 1 0.854857 20903.8 1 6 CACCTG TTACTTTCACTTCCTCTTTT - +4 hocomoco__ZN320_HUMAN.H11MO.0.C 13 0.854857 20903.8 1 6 CACCTG CACTGGCCCCCTGGTCCCAC - +4 taipale_cyt_meth__ZSCAN9_NRGGATAAGATAAGAANCMN_eDBD_repr-GATAe-grn-ham-pnr 8 0.854857 20903.8 1 6 CACCTG GTGATTCTTATCTTATCCTT - +4 transfac_pro__M01505-Sox15 3 0.854857 20903.8 1 6 CACCTG GGAGGTCTATTGTTCTACAA - +4 dbcorrdb__E2F1__ENCSR000EVJ_1__m1-Brf-E2f1-ERR-E(z)-Max-RpII215-SREBP -1 0.854857 20903.8 1 5 CACCTG CGCTGCGCGCCCGCGCCGGG + +4 dbcorrdb__IKZF1__ENCSR000EUJ_1__m3 15 0.854857 20903.8 1 5 CACCTG GGCGGCAACGGAAACCACAA + +4 dbcorrdb__ZNF274__ENCSR000EWY_1__m1-egg -1 0.854857 20903.8 1 5 CACCTG TCCAGTATGAGTTCTCTGAT - +4 transfac_pro__M06305-Dp-E2f2 15 0.854857 20903.8 1 5 CACCTG ATGCTTTTTTCCCGCCCCCA - +4 swissregulon__hs__ZBTB16.p2 20 0.855169 20911.5 1 6 CACCTG TTATTTTGATTTTAAAGTTTTATTTGTTT + +4 tfdimers__MD00272-tup-vvl 19 0.855169 20911.5 1 6 CACCTG ATTATCAATTGTTAATCATTAACTTTTTA - +4 cisbp__M1994-Deaf1 0 0.855546 20920.7 1 6 CACCTG TTCGGG + +4 hdpi__RPS6KA5-JIL-1 0 0.855546 20920.7 1 6 CACCTG GACAAC + +4 fantom__motif42_CGNTCA 1 0.855546 20920.7 1 5 CACCTG TGAACG - +4 hdpi__ZNF207-BuGZ -1 0.855546 20920.7 1 5 CACCTG ATTTGA - +4 hdpi__CKMT1B-Argk-CG4546-CG5144-CG30274 -2 0.855546 20920.7 1 4 CACCTG CATACA + +4 hdpi__PITX1-Ptx1 2 0.855546 20920.7 1 4 CACCTG AAGCCC - +4 scertf__badis.TOS8-achi-hth-vis 2 0.855546 20920.7 1 4 CACCTG TTGACA - +4 hdpi__PHOX2A-pb 3 0.855546 20920.7 1 3 CACCTG AATTAG + +4 jaspar__MA0199.1-Optix 0 0.856036 20932.6 1 5 CACCTG TATCA - +4 taipale_cyt_meth__ZNF444_NCRTCCCCCTCCCCCN_FL-btd-Spps-sr 5 0.857267 20962.8 1 6 CACCTG CCGTCCCCCTCCCCCC + +4 taipale_cyt_meth__ZNF444_NCRTCCCCCTCCCCCN_FL_meth_repr-btd-Spps-sr 5 0.857267 20962.8 1 6 CACCTG CCGTCCCCCTCCCCCC + +4 taipale_tf_pairs__HOXD12_ETV1_RSCGGAAGTNGTAAAN_CAP-Ets96B 6 0.857267 20962.8 1 6 CACCTG TTTTACGACTTCCGGT - +4 transfac_pro__M01444-abd-A-al-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-exex-ind-inv-Lim1-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-zfh2 0 0.857267 20962.8 1 6 CACCTG CCACTAATTAATGCTG - +4 taipale_cyt_meth__PAX7_NSGTCACGSNWRTTAN_eDBD-gsb-gsb-n-Poxn-prd-sv 11 0.857267 20962.8 1 5 CACCTG TTAATAAGCGTGACGA - +4 yetfasco__YCL055W_127-Mettl14 11 0.857267 20962.8 1 5 CACCTG AAAACAAAAACTGGCT - +4 tfdimers__MD00232-Taf7-Tbp 17 0.857482 20968 1 6 CACCTG ATAAAGTATAAATTGCACAATTTTAAAT + +4 transfac_pro__M09124-brm-CG7839-CTCF-HDAC1-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 18 0.857482 20968 1 6 CACCTG TTTTTTTTTTTTTTTTTTTTACTTTTTT + +4 cisbp__M2078 3 0.8577 20973.3 1 6 CACCTG ACATACTTGCCGAGAATTATC + +4 cisbp__M4248 3 0.8577 20973.3 1 6 CACCTG ACATACTTGCCGAGAATTATC + +4 hocomoco__PAX5_HUMAN.H11MO.0.A-sv 7 0.8577 20973.3 1 6 CACCTG GCCTGGGCAGCAGAGCGTGAC + +4 transfac_pro__M05196-brm-ERR-E(z)-vtd 15 0.8577 20973.3 1 6 CACCTG GGGGGTGCCCGGCCGCCCCTG + +4 transfac_pro__M05225 9 0.8577 20973.3 1 6 CACCTG TGTTGTGGCCTCCTTTTGGGT + +4 transfac_pro__M09262-Adf1 2 0.8577 20973.3 1 6 CACCTG TCCGCCGCCGCCTCCGCCGCC + +4 cisbp__M3965-Hcf-Six4 11 0.8577 20973.3 1 6 CACCTG ATTTCCCATCATGCCTTGCGA - +4 jaspar__MA0273.1 3 0.8577 20973.3 1 6 CACCTG ACATACTTGCCGAGAATTATC - +4 tfdimers__MD00560 12 0.8577 20973.3 1 6 CACCTG CCCCCCCACCCCCACCCCCCC - +4 transfac_pro__M01538 3 0.8577 20973.3 1 6 CACCTG ACATACTTGCCGAGAATTATC - +4 transfac_pro__M01566 5 0.8577 20973.3 1 6 CACCTG TTTTATTTCTTCTATTCTCTA - +4 transfac_pro__M05231 17 0.8577 20973.3 1 4 CACCTG AAACCCCCACAGAGCAACACC - +4 cisbp__M5307-amos-ato-dimm-HLH54F-Oli-tap-twi 0 0.857954 20979.6 1 6 CACCTG AAACATATGTTT + +4 hocomoco__FEZF1_HUMAN.H11MO.0.C-erm 4 0.857954 20979.6 1 6 CACCTG GCTGCTCTTTTT + +4 taipale__BHLHE22_DBD_NANCATATGNTN-amos-ato-dimm-HLH54F-Oli-tap-twi 0 0.857954 20979.6 1 6 CACCTG AAACATATGTTT - +4 taipale__E2F1_DBD_AATGGCGCCAAA-E2f1-E2f2 5 0.857954 20979.6 1 6 CACCTG TTTGGCGCCAAT - +4 taipale_tf_pairs__HOXB2_HOXB13_NNCGTAAAATTA_CAP_repr-pb 6 0.857954 20979.6 1 6 CACCTG TAATTTTACGAG - +4 transfac_pro__M05971 6 0.857954 20979.6 1 6 CACCTG TCTTTCGGCCAC - +4 transfac_pro__M06178 2 0.857954 20979.6 1 6 CACCTG TGTACATGAACA - +4 hocomoco__ATF4_HUMAN.H11MO.0.A-nej 7 0.857954 20979.6 1 5 CACCTG ATTGCATCATCT - +4 transfac_pro__M05703-CG2120 7 0.857954 20979.6 1 5 CACCTG TGTTTTTTCCCG - +4 transfac_pro__M06046 7 0.857954 20979.6 1 5 CACCTG TCGGCTTCTCCC - +4 transfac_pro__M06447 7 0.857954 20979.6 1 5 CACCTG GCGGCTGGACAG - +4 transfac_pro__M08940-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan 7 0.857954 20979.6 1 5 CACCTG GATGACTCATCC - +4 taipale__JDP2_DBD_NATGACGTCAYN-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.857954 20979.6 1 4 CACCTG GATGACGTCATC + +4 taipale_cyt_meth__SP9_NCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 8 0.857954 20979.6 1 4 CACCTG GCCACGCCCCCC + +4 cisbp__M5588-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.857954 20979.6 1 4 CACCTG GATGACGTCATC - +4 transfac_pro__M05620 8 0.857954 20979.6 1 4 CACCTG TCTTTTTTCACT - +4 homer__CGGTCACGCCAC_Srebp2-SREBP 9 0.857954 20979.6 1 3 CACCTG CGGTCACGCCAC + +4 hocomoco__MSX1_HUMAN.H11MO.0.D-Dr-HGTX-ind-slou 0 0.858484 20992.5 1 6 CACCTG TAATTGGTTTTTAATTGG + +4 taipale_tf_pairs__ETV2_ONECUT2_RRTCRATNNNCGGAARYN_CAP_repr-onecut-pnt 0 0.858484 20992.5 1 6 CACCTG CACTTCCGGTTATCGATT - +4 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNNNYMATTA_CAP_repr-pb 4 0.858484 20992.5 1 6 CACCTG TAATTGCGTTGCCATTGT - +4 transfac_pro__M05463 9 0.858484 20992.5 1 6 CACCTG CCATTTATCCACCCCCGC - +4 transfac_pro__M06648-crol 3 0.858484 20992.5 1 6 CACCTG GCCAACCCATTCACTATC - +4 cisbp__M3016 13 0.858484 20992.5 1 5 CACCTG ACCTAATTACCATTATCG + +4 transfac_public__M00416 13 0.858484 20992.5 1 5 CACCTG AACTAATTACCATTATCG + +4 cisbp__M0004-Taf1 0 0.858739 20998.7 1 6 CACCTG CGCCGCCA + +4 cisbp__M1226-nub-pdm2-pdm3-vvl 0 0.858739 20998.7 1 6 CACCTG CTAATTAA + +4 cisbp__M5705-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-ey-Lim3-OdsH-repo-unc-4-unpg-zfh2 1 0.858739 20998.7 1 6 CACCTG CTAATTAG + +4 cisbp__M5951-ap-Awh-C15-CG34367-CG9876-E5-ems-en-ind-inv-OdsH-ro-Rx-unpg-Vsx1-Vsx2 1 0.858739 20998.7 1 6 CACCTG CTAATTAG + +4 jaspar__MA0992.1-Taf1 1 0.858739 20998.7 1 6 CACCTG CCGCCGCC + +4 jaspar__MA1004.1 0 0.858739 20998.7 1 6 CACCTG CGCCGCCA + +4 taipale__VSX2_DBD_YTAATTAN-ap-Awh-C15-CG34367-CG9876-E5-ems-en-ind-inv-Lim3-OdsH-ro-Rx-unpg-Vsx1-Vsx2 1 0.858739 20998.7 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__DLX4_NTCGTTAN_eDBD_meth-abd-A-bsh-btn-Dfd-Dll-Dr-eve-exex-ind-Ubx-unpg 0 0.858739 20998.7 1 6 CACCTG GTCGTTAT + +4 taipale_cyt_meth__DRGX_YYAATTAN_eDBD_meth-CG11294-CG32532-Drgx-E5-ems-exex-ind-Lim3-Vsx1-Vsx2 1 0.858739 20998.7 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXA2_RTCGTTAN_FL_meth-Antp-btn-Dfd-eve-exex-ind-pb-Scr 0 0.858739 20998.7 1 6 CACCTG GTCATTAG + +4 taipale_cyt_meth__HOXB2_RTCGTTAN_eDBD_meth-Antp-btn-Dfd-eve-exex-ind-lab-pb-Scr 0 0.858739 20998.7 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__HOXD4_NYAATTAN_eDBD_meth-abd-A-Antp-bsh-btn-CG18599-Dfd-Dr-E5-ems-en-eve-exex-inv-lab-pb-Scr-tup-Ubx-zen-zen2 0 0.858739 20998.7 1 6 CACCTG GTCATTAG + +4 taipale_cyt_meth__NANOG_TTAATKGN_eDBD_repr 2 0.858739 20998.7 1 6 CACCTG TTAATGGC + +4 taipale_cyt_meth__VSX1_CYAATTAN_FL-al-Awh-E5-ems-eve-lab-Lim3-pb-slou 1 0.858739 20998.7 1 6 CACCTG CTAATTAC + +4 yetfasco__YPR065W_1396 0 0.858739 20998.7 1 6 CACCTG CACAATAG + +4 cisbp__M5000-abd-A-al-ap-Awh-CG11294-CG18599-CG32532-CG9876-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-PHDP-Pph13-repo-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2 0 0.858739 20998.7 1 6 CACCTG TAATTAAC - +4 fantom__motif101_NAGCAASA 2 0.858739 20998.7 1 6 CACCTG TCTTGCTG - +4 flyfactorsurvey__Hbn_SOLEXA_FBgn0008636-Awh-CG9876-CG11294-CG18599-CG32532-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-lms-otp-pb-repo-ro-slou-un 0 0.858739 20998.7 1 6 CACCTG TAATTAAC - +4 hocomoco__SOX5_HUMAN.H11MO.0.C-Sox102F 0 0.858739 20998.7 1 6 CACCTG TAACAATA - +4 predrem__nrMotif1892 0 0.858739 20998.7 1 6 CACCTG GAACTGAA - +4 taipale__PAX4_DBD_CTAATTAG-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-ey-Lim3-OdsH-repo-unc-4-unpg-zfh2 1 0.858739 20998.7 1 6 CACCTG CTAATTAG - +4 transfac_pro__M00494-Stat92E 2 0.858739 20998.7 1 6 CACCTG TGGAAATA - +4 transfac_pro__M07338-Sox100B 0 0.858739 20998.7 1 6 CACCTG GTCATTGT - +4 cisbp__M0715-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 3 0.858739 20998.7 1 5 CACCTG GTAAACAA + +4 cisbp__M0126-CTCF -1 0.858739 20998.7 1 5 CACCTG ATATTTTT - +4 cisbp__M4220 -1 0.858739 20998.7 1 5 CACCTG GCCGGGGA - +4 cisbp__M4951-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt -2 0.858739 20998.7 1 4 CACCTG CCGGAAAT + +4 cisbp__M5109-mirr 4 0.858739 20998.7 1 4 CACCTG AAAAAACA + +4 elemento__CATACGCC 4 0.858739 20998.7 1 4 CACCTG CATACGCC + +4 elemento__CATGCGCA-ewg -2 0.858739 20998.7 1 4 CACCTG CATGCGCA + +4 elemento__GCCACGCC-btd-luna-Spps 4 0.858739 20998.7 1 4 CACCTG GCCACGCC + +4 elemento__TTGGCGCC-E2f1-E2f2 4 0.858739 20998.7 1 4 CACCTG TTGGCGCC + +4 homer__GCTAATCC_CRX-Gsc-Ptx1-bcd -2 0.858739 20998.7 1 4 CACCTG GCTAATCC + +4 transfac_pro__M01250-E2f1 -2 0.858739 20998.7 1 4 CACCTG CGTTTCCC + +4 cisbp__M4761-bcd-Ptx1 4 0.858739 20998.7 1 4 CACCTG GGATTAAC - +4 cisbp__M4944-Antp-ap-bsh-CG15696-CG32532-Dll-E5-en-exex-ind-lab-Lim3-lms-otp-repo-Scr-slou-Ubx-unpg-Vsx1 4 0.858739 20998.7 1 4 CACCTG TAATTAAT - +4 flyfactorsurvey__Bcd_Cell_FBgn0000166-bcd 4 0.858739 20998.7 1 4 CACCTG GGATTAAC - +4 flyfactorsurvey__en_FlyReg_FBgn0000577-Antp-Awh-CG15696-CG32532-Dll-E5-Lim3-Rx-Scr-Ubx-Vsx1-bsh-en-exex-ind-lab-lms-otp-repo-slou-unpg 4 0.858739 20998.7 1 4 CACCTG TAATTAAT - +4 cisbp__M1105-pdm3 -3 0.858739 20998.7 1 3 CACCTG CTAATTAT + +4 elemento__CTAATGAG -3 0.858739 20998.7 1 3 CACCTG CTAATGAG + +4 taipale_cyt_meth__EVX1_NYAATTAN_eDBD_meth-Antp-btn-Dfd-E5-ems-en-eve-exex-inv-lab-pb-Scr-slou 5 0.858739 20998.7 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__HOXA5_NYAATTAN_FL-abd-A-Antp-bsh-btn-Dfd-E5-eve-exex-lab-Lim1-pb-Scr-Ubx-zen-zen2 5 0.858739 20998.7 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXD8_NYAATTAN_eDBD-abd-A-Antp-bsh-Dfd-Scr-Ubx 5 0.858739 20998.7 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__LMX1B_CTCGTTAW_FL_meth-CG4328-Lmx1a -3 0.858739 20998.7 1 3 CACCTG CTCGTTAA + +4 taipale_cyt_meth__NKX6-2_NYAATTAN_eDBD_meth-Dll-HGTX-Ubx 5 0.858739 20998.7 1 3 CACCTG GTAATTAA + +4 taipale_cyt_meth__PHOX2B_NYAATTAN_eDBD-Antp-Awh-B-H1-B-H2-bsh-btn-CG11085-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-lms-pb-Rx-Scr-unpg-Vsx1-Vsx2 5 0.858739 20998.7 1 3 CACCTG GCAATTAG + +4 taipale_cyt_meth__PRRX2_NYAATTAN_eDBD_meth-B-H1-B-H2-bsh-Dll-Dr-en-exex-inv-Lim1-Rx-unpg-Vsx1-Vsx2 5 0.858739 20998.7 1 3 CACCTG CCAATTAG + +4 cisbp__M2077 5 0.858739 20998.7 1 3 CACCTG AGAGTCAC - +4 jaspar__MA0272.1 5 0.858739 20998.7 1 3 CACCTG AGAGTCAC - +4 jaspar__MA0920.1-CHES-1-like-FoxK-FoxL1-FoxP-bin-croc-fd19B-fd59A-fd102C-foxo-slp1-slp2 5 0.858739 20998.7 1 3 CACCTG TTGTTTAC - +4 transfac_pro__M02095-Jra-kay-Mef2 -3 0.858739 20998.7 1 3 CACCTG CTGACTCA - +4 transfac_pro__M03538-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr -3 0.858739 20998.7 1 3 CACCTG ATGAGTCA - +4 tfdimers__MD00490-cad-SoxN 7 0.858802 21000.3 1 6 CACCTG AAATAAATCCCTTTGTTTTGTAAATAAAGTCA + +4 tfdimers__MD00016-Myc 5 0.859289 21012.2 1 6 CACCTG GAACACATCTGGTTACCAGATGTGTTC + +4 cisbp__M5118-abd-A-Antp-CG32532-CG34031-CG34367-en-lms-NK7.1-OdsH-repo-Scr-slou-tup-Ubx-unc-4-unpg 1 0.859595 21019.7 1 6 CACCTG TTAATTG + +4 cisbp__M6529-gem 0 0.859595 21019.7 1 6 CACCTG TCTCTGG + +4 jaspar__MA0187.1-Antp-Dll-Scr-Ubx-abd-A 0 0.859595 21019.7 1 6 CACCTG TAATTAC + +4 transfac_pro__M02025-Mef2 0 0.859595 21019.7 1 6 CACCTG TATTTAT + +4 predrem__nrMotif1493 1 0.859595 21019.7 1 6 CACCTG GCAGCAA - +4 predrem__nrMotif2010 0 0.859595 21019.7 1 6 CACCTG TTCATGG - +4 transfac_pro__M00696-al-CG34367-en-OdsH-repo-unc-4 0 0.859595 21019.7 1 6 CACCTG TAATTGG - +4 cisbp__M4990-bcd-Gsc-oc-Ptx1 2 0.859595 21019.7 1 5 CACCTG TTAATCC + +4 flyfactorsurvey__Gsc_SOLEXA_FBgn0010323-Gsc-Ptx1-bcd-oc 2 0.859595 21019.7 1 5 CACCTG TTAATCC + +4 cisbp__M5147-peb 2 0.859595 21019.7 1 5 CACCTG AGCATCC - +4 hdpi__C2orf52 2 0.859595 21019.7 1 5 CACCTG GTTGCCA - +4 hdpi__LSM6-CG9344 2 0.859595 21019.7 1 5 CACCTG TCTTCAT - +4 hdpi__MYOD1-nau -1 0.859595 21019.7 1 5 CACCTG TCATTAA - +4 transfac_pro__M05391-btd-CG42741-luna-Sp1-Spps 2 0.859595 21019.7 1 5 CACCTG CCGCCCT - +4 hdpi__ELF2-Eip74EF-Ets21C-Ets65A-Ets96B-Hcf-Sin3A-aop-pnt -2 0.859595 21019.7 1 4 CACCTG CCGGAAG + +4 cisbp__M5205-so 3 0.859595 21019.7 1 4 CACCTG TATCATT - +4 flyfactorsurvey__So_Cell_FBgn0003460-so 3 0.859595 21019.7 1 4 CACCTG TATCATT - +4 hdpi__TULP1-ktub 3 0.859595 21019.7 1 4 CACCTG ATTTCCC - +4 swissregulon__hs__ELF1_2_4.p2-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-aop-bs-pnt -2 0.859595 21019.7 1 4 CACCTG CCGGAAG - +4 elemento__CTCCCCG -3 0.859595 21019.7 1 3 CACCTG CTCCCCG + +4 elemento__CTCCCGC -3 0.859595 21019.7 1 3 CACCTG CTCCCGC + +4 elemento__CTCCGCG -3 0.859595 21019.7 1 3 CACCTG CTCCGCG + +4 elemento__CTCGCCC -3 0.859595 21019.7 1 3 CACCTG CTCGCCC + +4 elemento__CTCGCGC -3 0.859595 21019.7 1 3 CACCTG CTCGCGC + +4 elemento__CTCTCTC -3 0.859595 21019.7 1 3 CACCTG CTCTCTC + +4 elemento__CCCAGAG -3 0.859595 21019.7 1 3 CACCTG CTCTGGG - +4 elemento__CCGCGAG -3 0.859595 21019.7 1 3 CACCTG CTCGCGG - +4 predrem__nrMotif590 -3 0.859595 21019.7 1 3 CACCTG CTGGACA - +4 transfac_pro__M00683 -3 0.859595 21019.7 1 3 CACCTG CTCGAAG - +4 transfac_pro__M04645-jumu 12 0.859683 21021.8 1 6 CACCTG TCGTAAAGACGCCATTAATAGG - +4 hocomoco__ZN382_HUMAN.H11MO.0.C 19 0.859683 21021.8 1 3 CACCTG GAGACATCACTACAGACCCTAC - +4 homer__ATTTGCATAACAATG_OCT4-SOX2-TCF-NANOG-SoxN-nej-nub-pdm2-vvl 3 0.860452 21040.6 1 6 CACCTG ATTTGCATAACAATG + +4 taipale_cyt_meth__TCF7_WCATCGRGRCGCTGW_eDBD-pan 1 0.860452 21040.6 1 6 CACCTG ACATCGGGACGCTGA + +4 transfac_pro__M07086-klu-sr 0 0.860452 21040.6 1 6 CACCTG CCCCCGCCCACGCAC + +4 cisbp__M4639-CG10431-CTCF-pho-phol-Taf1 5 0.860452 21040.6 1 6 CACCTG GCCGCCATCTTGGGT - +4 cisbp__M5220-lmd-opa-sug 2 0.860452 21040.6 1 6 CACCTG CAGACCCCCCGCGGA - +4 cisbp__M6121-nej-pan-SoxN 5 0.860452 21040.6 1 6 CACCTG TTTTTGTTATGCAAA - +4 factorbook__PU1-CG9650-Dif-MTA1-like-Stat92E-dl-ebi-nej-sv 6 0.860452 21040.6 1 6 CACCTG TTTCACTTCCTCTTT - +4 factorbook__UA10-bon 4 0.860452 21040.6 1 6 CACCTG TTCTCTCCAGTATGA - +4 neph__UW.Motif.0209 4 0.860452 21040.6 1 6 CACCTG TGTTTTTTTTTCTCA - +4 taipale__MAFF_DBD_NTGCTGASTCAGCAN-cnc-maf-S-tj 0 0.860452 21040.6 1 6 CACCTG TTGCTGAGTCAGCAA - +4 taipale__SPDEF_DBD_GTGGTCCCGGATYAT_repr-Ets98B 9 0.860452 21040.6 1 6 CACCTG ATAATCCGGGACCAC - +4 taipale_tf_pairs__GCM1_ERG_RTRYGGGCGGAARKN_CAP-Ets97D-gcm-gcm2 0 0.860452 21040.6 1 6 CACCTG CACTTCCGCCCGCAT - +4 transfac_pro__M05396 8 0.860452 21040.6 1 6 CACCTG GCAACCCCAAGCACT - +4 transfac_pro__M07746-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.860452 21040.6 1 6 CACCTG AACAATAACATTGTT - +4 transfac_pro__M07863-C15-Nf1-NfI 9 0.860452 21040.6 1 6 CACCTG TTGGCACCGTGCCAA - +4 transfac_pro__M09372 0 0.860452 21040.6 1 6 CACCTG TACTTAATCACTAAG - +4 transfac_public__M00167-Hsf 0 0.860452 21040.6 1 6 CACCTG GTTCTGTTCTGTTCT - +4 transfac_public__M00170-Hsf 0 0.860452 21040.6 1 6 CACCTG GTTCTGTTCTAGAAC - +4 transfac_public__M00457-Stat92E 3 0.860452 21040.6 1 6 CACCTG AATTTCCTGGAATTC - +4 taipale_cyt_meth__ZFP42_NGRCHGCCATMTTGN_eDBD-pho-phol 10 0.860452 21040.6 1 5 CACCTG CCAATATGGCTGCCA - +4 taipale__RFX2_DBD_SGTTGCYARGCAACS-CG9727-Rfx 11 0.860452 21040.6 1 4 CACCTG CGTTGCTAGGCAACG + +4 cisbp__M4626-cnc-maf-S-tj 11 0.860452 21040.6 1 4 CACCTG AATTGCTGACTCAGC - +4 cisbp__M5774-CG9727-Rfx 11 0.860452 21040.6 1 4 CACCTG CGTTGCTAGGCAACG - +4 cisbp__M2301-btd-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-Spps -3 0.860452 21040.6 1 3 CACCTG CTGATTGGTCCATTT - +4 jaspar__MA0502.1-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-Spps-btd -3 0.860452 21040.6 1 3 CACCTG CTGATTGGTCCATTT - +4 tfdimers__MD00008 8 0.860568 21043.5 1 6 CACCTG ACACTTTTTCCCTAGGGAAAAAGTGT + +4 transfac_public__M00202 19 0.860568 21043.5 1 6 CACCTG TAATAAATGTGATTTACGTCACATTT + +4 tfdimers__MD00386 5 0.860568 21043.5 1 6 CACCTG TTTTTTTTTTGCCTTAATCCCTTTAT - +4 transfac_pro__M04642-CHES-1-like 14 0.860897 21051.5 1 6 CACCTG CCTAATAATGACGCCAATGCACC + +4 taipale_tf_pairs__CUX1_SOX15_NATCRATNNNNNNNNAACAATRS_CAP_repr-ct 9 0.860897 21051.5 1 6 CACCTG CCATTGTTCTACGGGTATTGATC - +4 taipale_tf_pairs__E2F1_ELK1_SGCGCNNNNNNNNNNNCGGAAGN_CAP_repr-E2f1 8 0.860897 21051.5 1 6 CACCTG ACTTCCGGTCCCCCATGCGCGCC - +4 tfdimers__MD00267-E2f1 13 0.860897 21051.5 1 6 CACCTG AGAAAAGGAAACTCCCCAAAGAC - +4 transfac_pro__M04659-jumu 17 0.860897 21051.5 1 6 CACCTG ACGGAGGCAACGCGTCCTATCCG - +4 cisbp__M5817-D-Sox21a-Sox21b-SoxN 5 0.861117 21056.9 1 6 CACCTG TCAATAACATTGA + +4 hocomoco__HES1_HUMAN.H11MO.0.D-Sidpn 4 0.861117 21056.9 1 6 CACCTG CCGCCACGAGCCC + +4 taipale__SOX14_DBD_TCAATNNCATTGA-D-Sox21a-Sox21b-SoxN 5 0.861117 21056.9 1 6 CACCTG TCAATAACATTGA + +4 taipale_cyt_meth__ZNF740_NYGCCCCCCCCAC_eDBD 1 0.861117 21056.9 1 6 CACCTG CTGCCCCCCCCAC + +4 cisbp__M6421 6 0.861117 21056.9 1 6 CACCTG TAGGGCCCCCTCT - +4 cisbp__M6187 8 0.861117 21056.9 1 5 CACCTG GGGGATTGCATTT + +4 hocomoco__KLF14_HUMAN.H11MO.0.D-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 8 0.861117 21056.9 1 5 CACCTG GCCACGCCCCCCT - +4 neph__UW.Motif.0276 8 0.861117 21056.9 1 5 CACCTG GAAATTTCTTAAT - +4 swissregulon__sacCer__UME6 8 0.861117 21056.9 1 5 CACCTG TCGGCGGCTAAAT - +4 transfac_public__M00517-cnc-Jra-kay-maf-S 8 0.861117 21056.9 1 5 CACCTG TGCTGACTCATTC - +4 taipale_tf_pairs__GCM1_SPDEF_RTGNKGGCGGAWGNNNNNTCCGGNN_CAP-Ets98B-gcm-gcm2 17 0.861288 21061.1 1 6 CACCTG ATGCGGGCGGATGTTGGATCCGGGC + +4 tfdimers__MD00499-Taf7-Tbp 14 0.861288 21061.1 1 6 CACCTG AAAATATATAAATTTGCATTTATAT - +4 cisbp__M3341-sens-sens-2 5 0.861413 21064.1 1 6 CACCTG GGCATATGCTGTGATTTATTTTTT + +4 tfdimers__MD00090-foxo-Jra-slp2 3 0.861413 21064.1 1 6 CACCTG AAATAACTGAGTAAACAAAAAAAA + +4 tfdimers__MD00556-ac-ase-Hand-HLH3B-HLH4C-l(1)sc-Max-Mitf-MTF-1-Myc-nau-sc-Usf 1 0.861413 21064.1 1 6 CACCTG GGCCCTGCGCCCCCTGCCCCCCCC + +4 neph__UW.Motif.0542 2 0.861845 21074.7 1 6 CACCTG GCAGCACTCACTCA + +4 predrem__nrMotif1357-Nelf-E-Spps-btd 0 0.861845 21074.7 1 6 CACCTG CCCCCTCCCCCCGG + +4 transfac_pro__M04735-CG9650-nej-nub-pdm2-SoxN 3 0.861845 21074.7 1 6 CACCTG ATTTGCATAACAAT + +4 cisbp__M1844-br 0 0.861845 21074.7 1 6 CACCTG GATTTGTCTATTAC - +4 hocomoco__EGR1_MOUSE.H11MO.0.A-CG42741-Spps-btd-kay-klu-luna-sd-sr 0 0.861845 21074.7 1 6 CACCTG CCCCGCCCCCGCAC - +4 transfac_public__M00090-Abd-B -1 0.861845 21074.7 1 5 CACCTG ACGTTTATGGCGAC + +4 flyfactorsurvey__Sp1_SOLEXA_2.5_FBgn0020378-CG3065-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-cbt-dar1-kay-luna 9 0.861845 21074.7 1 5 CACCTG GGCCACGCCCACTT - +4 cisbp__M6282 10 0.861845 21074.7 1 4 CACCTG GTTAATCATTAACC + +4 cisbp__M2394 9 0.863264 21109.4 1 6 CACCTG CCTTTTACATTCCTGTGCT + +4 transfac_public__M00027 9 0.863264 21109.4 1 6 CACCTG CCTTTTGCATTCCTGTGCT + +4 taipale_tf_pairs__FLI1_ONECUT2_RSCGGAANNNNNNRTCGAT_CAP-onecut 3 0.863264 21109.4 1 6 CACCTG ATCGATCATTACTTCCGGT - +4 bergman__eyg-eyg 14 0.863264 21109.4 1 5 CACCTG GCGTACTCAGTGAGTACTC - +4 taipale_cyt_meth__ZSCAN16_NANTGTTAACAGAGCCTCN_eDBD_repr 14 0.863264 21109.4 1 5 CACCTG AGAGGCTCTGTTAACACTT - +4 cisbp__M0666 5 0.863302 21110.3 1 6 CACCTG ACGCGCGCCAA + +4 taipale__PHOX2B_DBD_TAATYYAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-repo-Traf4-unc-4 1 0.863302 21110.3 1 6 CACCTG TAATTTAATTA + +4 tiffin__TIFDMEM0000076 1 0.863302 21110.3 1 6 CACCTG GCAGCAGCAGC + +4 cisbp__M6337-MBD-like 1 0.863302 21110.3 1 6 CACCTG CCTCCGGCCCC - +4 flyfactorsurvey__nub_SOLEXA_5_FBgn0085424-nub-pdm2-vvl 4 0.863302 21110.3 1 6 CACCTG AATTTGCATAT - +4 hocomoco__DPRX_HUMAN.H11MO.0.D 5 0.863302 21110.3 1 6 CACCTG GGATAATCCGT - +4 predrem__nrMotif535 2 0.863302 21110.3 1 6 CACCTG CCGCCCTCGCC - +4 transfac_pro__M00972-Blimp-1-Dif-dl-ebi-Stat92E 4 0.863302 21110.3 1 6 CACCTG CTTTCACTTTC - +4 predrem__nrMotif2616 -1 0.863302 21110.3 1 5 CACCTG AGCTTGTATTT - +4 transfac_pro__M01052 6 0.863302 21110.3 1 5 CACCTG GGGATATTCCC - +4 transfac_pro__M05542-Pbp95 -2 0.863302 21110.3 1 4 CACCTG CTTGCGTATTA + +4 cisbp__M2292-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 7 0.863302 21110.3 1 4 CACCTG GATGAGTCACC - +4 cisbp__M6318-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 7 0.863302 21110.3 1 4 CACCTG GATGAGTCATC - +4 hocomoco__CEBPD_MOUSE.H11MO.0.B-Irbp18-Xrp1-nej-slbo 7 0.863302 21110.3 1 4 CACCTG ATTGCACAATT - +4 taipale_cyt_meth__HOXC10_NRTCGTAAAAN_FL-Abd-B-cad 7 0.863302 21110.3 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC12_NRTCGTAAAAN_eDBD-Abd-B-cad 7 0.863302 21110.3 1 4 CACCTG GTTTTACGACC - +4 taipale__FOXO3_full_TTTCCCCACAC-foxo 8 0.863302 21110.3 1 3 CACCTG TTTCCCCACAC + +4 cisbp__M1595-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 3 0.864259 21133.7 1 6 CACCTG GAAAACAAT + +4 fantom__motif90_TTATATCGC 3 0.864259 21133.7 1 6 CACCTG TTATATCGC + +4 predrem__nrMotif1943 0 0.864259 21133.7 1 6 CACCTG AAACTCTCT + +4 predrem__nrMotif270 0 0.864259 21133.7 1 6 CACCTG TCACTGTGT + +4 predrem__nrMotif459 0 0.864259 21133.7 1 6 CACCTG TCACTGAAT + +4 predrem__nrMotif773 3 0.864259 21133.7 1 6 CACCTG GAAGATTTT + +4 predrem__nrMotif803 3 0.864259 21133.7 1 6 CACCTG AGCAAATTT + +4 cisbp__M0116 0 0.864259 21133.7 1 6 CACCTG TTAATTAAA - +4 cisbp__M1028-al-Antp-ap-Awh-B-H1-B-H2-C15-CG11085-CG11294-CG18599-CG34367-CG9876-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-gsb-gsb-n-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-pdm3-Pph13-prd-ro-Rx-Scr-slou-Ubx-unp 1 0.864259 21133.7 1 6 CACCTG GCTAATTAG - +4 cisbp__M1135-CG4328-Lmx1a-OdsH-repo-unc-4 0 0.864259 21133.7 1 6 CACCTG TTAATTAAT - +4 cisbp__M6356 2 0.864259 21133.7 1 6 CACCTG TTCCCCACC - +4 fantom__motif10_SCGGAGASN 0 0.864259 21133.7 1 6 CACCTG TCTCTCCGC - +4 predrem__nrMotif532 1 0.864259 21133.7 1 6 CACCTG CCCCATTCT - +4 cisbp__M6364-NFAT 4 0.864259 21133.7 1 5 CACCTG AGTTTTCCA + +4 hdpi__GLYCTK-CG9886 -1 0.864259 21133.7 1 5 CACCTG AAATGAATT + +4 predrem__nrMotif1187 -1 0.864259 21133.7 1 5 CACCTG AGCCATTCA - +4 predrem__nrMotif1440 4 0.864259 21133.7 1 5 CACCTG AGAAGACTC - +4 taipale_cyt_meth__BARHL2_NTAATTGNY_eDBD_meth-B-H1-B-H2-E5-ems-en-eve-inv-lms-Ubx-unpg -1 0.864259 21133.7 1 5 CACCTG AGCAATTAG - +4 predrem__nrMotif1434 -2 0.864259 21133.7 1 4 CACCTG ACTGTAATA + +4 predrem__nrMotif2483 5 0.864259 21133.7 1 4 CACCTG TTTCATATC + +4 flyfactorsurvey__CG16899_SANGER_5_FBgn0037735-CHES-1-like-FoxK-FoxL1-FoxP-bin-fd19B-fd102C-foxo-slp1-slp2 5 0.864259 21133.7 1 4 CACCTG TTGTTTATC - +4 flyfactorsurvey__Her_SANGER_5_FBgn0030899-CG3407-Hesr 5 0.864259 21133.7 1 4 CACCTG GGCTTGACA - +4 jaspar__MA0396.1 5 0.864259 21133.7 1 4 CACCTG TGCGCTAGC - +4 transfac_pro__M01649 5 0.864259 21133.7 1 4 CACCTG TGCGCTAGC - +4 yetfasco__YLR375W_568 5 0.864259 21133.7 1 4 CACCTG TGCGCTAGC - +4 taipale_cyt_meth__TCF7L1_ASATCAAAS_eDBD-pan -3 0.864259 21133.7 1 3 CACCTG CTTTGATCT - +4 transfac_pro__M00925-Jra-kay -3 0.864259 21133.7 1 3 CACCTG TTGAGTCAT - +4 taipale__BARX1_DBD_CNATTAAAWANCNATTA_repr-Dr-HGTX-ind 8 0.864444 21138.3 1 6 CACCTG CAATTAAATACCGATTA + +4 transfac_pro__M01473-Antp-Dbx-Dfd-Lim1-Lim3-Scr-vvl 11 0.864444 21138.3 1 6 CACCTG AATTAATTAATTAATTC + +4 cisbp__M5300-Dr-HGTX-ind 8 0.864444 21138.3 1 6 CACCTG CAATTAAATACCGATTA - +4 cisbp__M5855-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Nf-YB-Sp1-Spps 11 0.864444 21138.3 1 6 CACCTG TAAGCCACGCCCCCTTT - +4 transfac_public__M00061-klu-sr 0 0.864444 21138.3 1 6 CACCTG TACCCCAGATTTTTTTC - +4 tfdimers__MD00161-Jra 21 0.865344 21160.3 1 6 CACCTG TTTTTTAGTTTCACTTTGAGTCATCTTTAT - +4 bergman__br-Z2-br 1 0.865487 21163.7 1 6 CACCTG TTAACTATTT + +4 cisbp__M0027 1 0.865487 21163.7 1 6 CACCTG CTGCCGGCGT + +4 cisbp__M1119-Awh-Lim3-en-exex-lab-pb 2 0.865487 21163.7 1 6 CACCTG AGTAATTACT + +4 cisbp__M1125-abd-A-al-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-lms-NK7.1-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 2 0.865487 21163.7 1 6 CACCTG GCTAATTGGT + +4 cisbp__M1157-abd-A-Abd-B-Antp-cad-CG4328-Dbx-Dfd-eve-exex-Scr-Ubx 3 0.865487 21163.7 1 6 CACCTG TTTTATGACC + +4 cisbp__M1243-vvl 2 0.865487 21163.7 1 6 CACCTG TATTAATAAT + +4 cisbp__M1253 2 0.865487 21163.7 1 6 CACCTG GTGTTCTATG + +4 cisbp__M3275-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 4 0.865487 21163.7 1 6 CACCTG CATAAACAAA + +4 cisbp__M4959-exd 0 0.865487 21163.7 1 6 CACCTG TAAAACAAAA + +4 cisbp__M5990-B-H1-B-H2 3 0.865487 21163.7 1 6 CACCTG GCTAAACGGT + +4 cisbp__M6021-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-pb-Pph13-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2 2 0.865487 21163.7 1 6 CACCTG GCTAATTGGT + +4 predrem__nrMotif1255 0 0.865487 21163.7 1 6 CACCTG TTCATTGCTG + +4 predrem__nrMotif2639 0 0.865487 21163.7 1 6 CACCTG CTCCATGCTG + +4 taipale__Barhl1_DBD_NNTAAACGNN_repr-B-H1-B-H2 3 0.865487 21163.7 1 6 CACCTG GCTAAACGGT + +4 taipale__LBX2_DBD_NNYAATTANN-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ftz-hbn-inv-lab-lbe-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 2 0.865487 21163.7 1 6 CACCTG GCCAATTAGC + +4 taipale__RAX_DBD_NNYAATTANN-al-Awh-C15-CG15696-CG18599-CG32532-CG34367-CG9876-Dr-dve-E5-ems-en-ftz-hbn-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-otp-PHDP-Pph13-repo-Rx-slou-unc-4-unpg-Vsx1-zfh2 2 0.865487 21163.7 1 6 CACCTG GCCAATTAAC + +4 taipale_cyt_meth__HOXA9_RTCGTAAANN_FL_meth-cad 0 0.865487 21163.7 1 6 CACCTG GTCGTAAATG + +4 transfac_pro__M00374 3 0.865487 21163.7 1 6 CACCTG GATGATATGG + +4 transfac_pro__M02010 2 0.865487 21163.7 1 6 CACCTG GAAATCACAG + +4 transfac_pro__M03209 4 0.865487 21163.7 1 6 CACCTG AGGCCGCCCG + +4 transfac_public__M00473-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 4 0.865487 21163.7 1 6 CACCTG CATAAACAAA + +4 cisbp__M0413 1 0.865487 21163.7 1 6 CACCTG GTCCCGCAAC - +4 cisbp__M0911-Antp-CG34367-Dr-E5-ems-en-eve-exex-ind-lab-pb-Scr-Ubx-unpg-zen2 3 0.865487 21163.7 1 6 CACCTG AAGCAATTAG - +4 cisbp__M4277-klu-sr 0 0.865487 21163.7 1 6 CACCTG CCCCACAAAA - +4 cisbp__M5285-al-ap-Awh-C15-CG11294-CG15696-CG32532-CG34367-CG9876-E5-ems-en-hbn-inv-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2 2 0.865487 21163.7 1 6 CACCTG TCTAATTAAA - +4 cisbp__M5771-al-Awh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG9876-Dr-dve-E5-ems-en-ftz-hbn-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-otp-PHDP-Pph13-repo-Rx-slou-unc-4-unpg-Vsx1-zfh2 2 0.865487 21163.7 1 6 CACCTG GCCAATTAAC - +4 flyfactorsurvey__btd_NAR_FBgn0000233-Spps-btd 4 0.865487 21163.7 1 6 CACCTG TCCGCCCCCT - +4 flyfactorsurvey__exd_FlyReg_FBgn0000611-exd 0 0.865487 21163.7 1 6 CACCTG TAAAACGAAA - +4 hdpi__MAGOH-mago 4 0.865487 21163.7 1 6 CACCTG TAATGAGCTC - +4 predrem__nrMotif1857 2 0.865487 21163.7 1 6 CACCTG AATCACTGTT - +4 predrem__nrMotif568 4 0.865487 21163.7 1 6 CACCTG TATGCAGCAG - +4 swissregulon__sacCer__TBS1 4 0.865487 21163.7 1 6 CACCTG GCGGATCCGC - +4 taipale__Gbx2_DBD_NNYAATTANN-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2 2 0.865487 21163.7 1 6 CACCTG GCTAATTGGT - +4 taipale_cyt_meth__CDX2_NRTCGTAAAN_eDBD-cad 3 0.865487 21163.7 1 6 CACCTG GTTTACGACC - +4 transfac_pro__M00702 1 0.865487 21163.7 1 6 CACCTG ATTACTATTT - +4 predrem__nrMotif508 5 0.865487 21163.7 1 5 CACCTG TTGTCTCCCA + +4 transfac_pro__M01233-Antp-Awh-CG18599-E5-ems-en-eve-exex-ind-inv-lab-Lim3-OdsH-pb-ro-Scr-slou-Vsx1-Vsx2 -1 0.865487 21163.7 1 5 CACCTG CACTAATTAC + +4 cisbp__M5991-B-H1-B-H2-CG11085-Dr-en-eve-Hmx-inv-lab-lms-NK7.1-pb-slou-Ubx-unpg -1 0.865487 21163.7 1 5 CACCTG AGCAATTAGC - +4 predrem__nrMotif673 5 0.865487 21163.7 1 5 CACCTG CTGCAGCCCT - +4 taipale__Barhl1_DBD_NNTAATTGNN_repr-B-H1-B-H2-CG11085-Dr-en-eve-Hmx-inv-lab-lms-NK7.1-pb-slou-Ubx-unpg -1 0.865487 21163.7 1 5 CACCTG AGCAATTAGC - +4 transfac_pro__M01812 5 0.865487 21163.7 1 5 CACCTG GGGATGACGC - +4 homer__CCAAAAATAG_Mef2a-Mef2-rump -2 0.865487 21163.7 1 4 CACCTG CTAAAAATAG + +4 taipale__ALX3_DBD_NNYAATTANN-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbe-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 6 0.865487 21163.7 1 4 CACCTG GCTAATTAGC + +4 taipale__HOXB2_DBD_NNYMATTANN-abd-A-Antp-ap-Awh-B-H1-B-H2-btn-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Drgx-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-Lim3-Lmx1a-OdsH-otp-pb-Pph13-ro-Rx-Scr-Ubx-unpg-Vsx1- 6 0.865487 21163.7 1 4 CACCTG AGTAATTAAC + +4 hocomoco__TBP_HUMAN.H11MO.0.A-RpII215-Taf1-Tbp -2 0.865487 21163.7 1 4 CACCTG CCTTTTATAG - +4 predrem__nrMotif2525 -2 0.865487 21163.7 1 4 CACCTG CCGGGGGAGG - +4 transfac_pro__M01236 -2 0.865487 21163.7 1 4 CACCTG CCTATTAATG - +4 cisbp__M5978 7 0.865487 21163.7 1 3 CACCTG CCCCCCCCAC - +4 dbcorrdb__CHD2__ENCSR000EBT_1__m1-Chd1-CoRest 8 0.866983 21200.3 1 6 CACCTG TCTCGCGAGAGTTGGGGGGG + +4 dbcorrdb__ELF1__ENCSR000BPT_1__m1-aop-Atac3-Dif-dl-E2f1-Eip74EF-Ets97D-Hcf-pnt-Rbbp5-RpII215-Sin3A-Taf1 5 0.866983 21200.3 1 6 CACCTG GCCGCCACTTCCGGGTTCGG + +4 dbcorrdb__ELF1__ENCSR000BPT_1__m2-Atac3-Brf-brm-btd-CG10431-CTCF-E2f1-Eip74EF-ERR-Ets96B-Ets97D-E(z)-FoxP-Hcf-HDAC1-Hr78-Max-Myc-Rbbp5-RpII215-Sin3A-Spps-SREBP-Taf1-vtd 14 0.866983 21200.3 1 6 CACCTG CGGGGGGCCGGAAGTGGCCG + +4 dbcorrdb__ETS1__ENCSR000BKQ_1__m3-Atac3-Brf-brm-Dif-dl-E2f1-E2f2-Eip74EF-ERR-Ets96B-Ets97D-E(z)-FoxP-Hcf-lid-Max-Myc-Rbbp5-RpII215-Sin3A-Spt20-SREBP-Taf1-tna 4 0.866983 21200.3 1 6 CACCTG CCCGCCGCTTCCGGCGCGGC + +4 dbcorrdb__EZH2__ENCSR000ARI_1__m1-E(z) 1 0.866983 21200.3 1 6 CACCTG GGACCCGCGGGGACTCGAGA + +4 dbcorrdb__PBX3__ENCSR000BGR_1__m3-Brf-brm-btd-CG3065-CG42741-CoRest-ct-CTCF-dar1-E2f2-ERR-HDAC1-kay-Klf15-klu-luna-Nelf-E-Nf-YA-Nf-YB-Rbbp5-Sp1-Spps-Spt20-sr-SREBP-Stat92E-vtd 12 0.866983 21200.3 1 6 CACCTG GGGAGGGGGCGGGGCCTGGG + +4 dbcorrdb__PHF8__ENCSR000AQH_1__m1-aop-Atac3-Brf-brm-btd-CTCF-Dif-dl-E2f1-Eip74EF-ERR-Ets96B-Ets97D-E(z)-FoxP-Hcf-HDAC1-Hr78-lid-Max-Myc-Rbbp5-RpII215-Sin3A-Spps-SREBP-Taf1-tna 13 0.866983 21200.3 1 6 CACCTG GCGCCGCTTCCGGCGCCGGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOV_1__m5 9 0.866983 21200.3 1 6 CACCTG CCGCCGCCGCGCCGACCGCG + +4 dbcorrdb__POU2F2__ENCSR000BII_1__m1-nub-pdm2-vvl 3 0.866983 21200.3 1 6 CACCTG CCCCTCATTTGCATATTCGC + +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m6-bon 13 0.866983 21200.3 1 6 CACCTG AGCAGTGTGGAAAAGCCTTC + +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m2-bon 5 0.866983 21200.3 1 6 CACCTG ATTCATACTGCAGAGAAACC + +4 dbcorrdb__TRIM28__ENCSR000EYC_1__m5-bon-Brf-brm-Chd1-E(z)-HDAC1-Nelf-E-opa-Rbbp5-RpII215-Spt20-SREBP-tna 1 0.866983 21200.3 1 6 CACCTG CCCCCCCCCGGGGGGGGGGG + +4 flyfactorsurvey__CG10267_SOLEXA_5_FBgn0037446-Zif 0 0.866983 21200.3 1 6 CACCTG CAGCTAACAACACTACCATT + +4 swissregulon__hs__IRF1_2_7.p3-Blimp-1-Stat92E 11 0.866983 21200.3 1 6 CACCTG AAGGAAAGCGAAACCGAAAC + +4 taipale_cyt_meth__PAX4_NAATTANNNNNNNNTAATTN_eDBD_repr-en-inv 4 0.866983 21200.3 1 6 CACCTG AAATTAGGACTGGCTAATTA + +4 c2h2_zfs__M3945-Zif 0 0.866983 21200.3 1 6 CACCTG CAGCTAACAACACTACCATT - +4 dbcorrdb__EP300__ENCSR000DZG_1__m1-CG9650-ebi-foxo-MTA1-like-nej-Stat92E-sv 9 0.866983 21200.3 1 6 CACCTG TAGTTTCACTTCCTCTTTTA - +4 dbcorrdb__EZH2__ENCSR000ARK_1__m2-E(z) 10 0.866983 21200.3 1 6 CACCTG TCGTGCGCGTCTCCGCGGGC - +4 dbcorrdb__GTF2F1__ENCSR000EHC_1__m1-Nelf-E-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 7 0.866983 21200.3 1 6 CACCTG CCGCCGCCCCTTTTATAGGC - +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m7 13 0.866983 21200.3 1 6 CACCTG GCAAAACACCCAATAATAAA - +4 dbcorrdb__MEF2A__ENCSR000BKB_1__m1-Mef2-rump 11 0.866983 21200.3 1 6 CACCTG GCTATTTTTAGAATTTTAAT - +4 dbcorrdb__MEF2C__ENCSR000BNG_1__m1-Mef2-rump 1 0.866983 21200.3 1 6 CACCTG AATGCTATTTTTAGAATTTT - +4 dbcorrdb__PAX5__ENCSR000BHD_1__m1-ey-Poxm-sv-toy 6 0.866983 21200.3 1 6 CACCTG CGGTCACGCTTGGCTGCCCA - +4 dbcorrdb__POLR2A__ENCSR000DKM_1__m1-E2f1-Eip74EF-ewg-RpII215-Taf1 13 0.866983 21200.3 1 6 CACCTG TGCGCTTCCGCCGCGCGCGC - +4 dbcorrdb__POLR2A__ENCSR000EHP_1__m1-aop-Atac3-Brf-CrebB-E2f1-Eip74EF-Ets96B-E(z)-Hcf-Hr78-RpII215-Sin3A-Taf1-TfIIFalpha 9 0.866983 21200.3 1 6 CACCTG CGCTTCCGCCGCGGGCGCGC - +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BPA_1__m1-RpII215-Taf1 10 0.866983 21200.3 1 6 CACCTG GCGCTTCCGCCGTGTGATGG - +4 dbcorrdb__POU2F2__ENCSR000BGP_1__m1-nub-pdm2-vvl 9 0.866983 21200.3 1 6 CACCTG CCCCTGATTTGCATATTCCT - +4 dbcorrdb__RFX5__ENCSR000ECX_1__m2-btd-CG7839-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps 5 0.866983 21200.3 1 6 CACCTG GCCGGGTTCTGATTGGCTGA - +4 dbcorrdb__WRNIP1__ENCSR000EAA_1__m3-Brf-ERR-E(z)-vtd 14 0.866983 21200.3 1 6 CACCTG CGGGGGGGGGCCCCTCCCCG - +4 dbcorrdb__ZBTB33__ENCSR000BHR_1__m1-Chd1-CoRest 11 0.866983 21200.3 1 6 CACCTG AGCTCTCGCGAGACCTGGGG - +4 tfdimers__MD00129 4 0.866983 21200.3 1 6 CACCTG TTAATTACTTATTAACTAAT - +4 transfac_pro__M01525 0 0.866983 21200.3 1 6 CACCTG AAACTTCCCGGGATAGTGAT - +4 transfac_pro__M01652 1 0.866983 21200.3 1 6 CACCTG AGACATGCCCGGGCATGCCC - +4 dbcorrdb__STAT1__ENCSR000DZM_1__m2-btd-Spps-Stat92E 15 0.866983 21200.3 1 5 CACCTG CTCCGCGCGTAGCCGCGCCC + +4 taipale_cyt_meth__ZSCAN29_MMGYGTAGMCGKCTACACNN_eDBD_repr 15 0.866983 21200.3 1 5 CACCTG CCGCGTAGACGTCTACACAG + +4 transfac_pro__M03849-Sox14 -1 0.867632 21216.2 1 5 CACCTG AACAAA + +4 hdpi__AVEN 1 0.867632 21216.2 1 5 CACCTG TTTCCA - +4 hdpi__MAGED4 1 0.867632 21216.2 1 5 CACCTG TTTCCA - +4 hdpi__PHTF1-phtf 1 0.867632 21216.2 1 5 CACCTG TTATTT - +4 stark__SGGAAA-dl 1 0.867632 21216.2 1 5 CACCTG TTTCCC - +4 cisbp__M2042-oc-Ptx1 2 0.867632 21216.2 1 4 CACCTG TAATCC + +4 jaspar__MA0234.1-Ptx1-oc 2 0.867632 21216.2 1 4 CACCTG TAATCC + +4 transfac_pro__M01879 -3 0.867632 21216.2 1 3 CACCTG TTATTA + +4 hdpi__STUB1-STUB1 2 0.868064 21226.8 1 3 CACCTG CAAAC + +4 taipale_cyt_meth__PAX3_NYRATTMGTCACGSTN_eDBD_repr-foxo-gsb-gsb-n-prd 9 0.868933 21248 1 6 CACCTG GCAATTAGTCACGGTT + +4 cisbp__M3853-al-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-inv-lms-OdsH-otp-Pph13-repo-Rx-slou-unc-4-unpg-zfh2 10 0.868933 21248 1 6 CACCTG TTTACCCAATTAACCT - +4 transfac_pro__M01394-abd-A-exex-Ubx 0 0.868933 21248 1 6 CACCTG TTCCATTAATTACTAC - +4 transfac_pro__M01882-Blimp-1-Stat92E 0 0.868933 21248 1 6 CACCTG TCACTTTCACTTTCCC - +4 taipale_tf_pairs__HOXD12_ETV4_RSCGGAAGTCGTAAAN_CAP-Ets96B -1 0.868933 21248 1 5 CACCTG ACCGGAAGTCGTAAAA + +4 taipale_cyt_meth__PAX3_NSGTCACGSNNATTAN_eDBD-E5-ems-gsb-gsb-n-ind-Poxn-prd 11 0.868933 21248 1 5 CACCTG TTAATTAGCGTGACGG - +4 cisbp__M5753-pros 5 0.869062 21251.2 1 6 CACCTG CAAGACGCCTTA + +4 cisbp__M6557-rn-sqz 5 0.869062 21251.2 1 6 CACCTG GGAAAAAGTCGG + +4 hocomoco__STA5B_HUMAN.H11MO.0.A-Stat92E 0 0.869062 21251.2 1 6 CACCTG TTTCTTAGAAAT + +4 hocomoco__STAT3_HUMAN.H11MO.0.A-Stat92E 3 0.869062 21251.2 1 6 CACCTG CATTTCCCGGAA + +4 hocomoco__ZN384_HUMAN.H11MO.0.C-rn-sqz 5 0.869062 21251.2 1 6 CACCTG GGAAAAAATCGG + +4 homer__AAATTSAATTTN_CES-1 0 0.869062 21251.2 1 6 CACCTG AAATTGAATTTG + +4 neph__UW.Motif.0227 3 0.869062 21251.2 1 6 CACCTG GCATTTTTTTCA + +4 stark__TWAWKMNAWTTG 6 0.869062 21251.2 1 6 CACCTG TAAAGAAAATTG + +4 taipale__PROX1_DBD_NAAGACGYCTTN_repr-pros 5 0.869062 21251.2 1 6 CACCTG CAAGACGCCTTA + +4 taipale__SP8_DBD_NMCMCGCCCMCN-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.869062 21251.2 1 6 CACCTG GCCACGCCCACT + +4 tiffin__TIFDMEM0000021 6 0.869062 21251.2 1 6 CACCTG TATTTTTATTTA + +4 tiffin__TIFDMEM0000108 2 0.869062 21251.2 1 6 CACCTG TTTAATTTAAAT + +4 transfac_pro__M06092 6 0.869062 21251.2 1 6 CACCTG TGGGAATTCCAT + +4 transfac_pro__M06385 2 0.869062 21251.2 1 6 CACCTG TGGGCCTGGGGA + +4 cisbp__M1919-CG10431-lid-pho-phol-Taf1 5 0.869062 21251.2 1 6 CACCTG GCCGCCATCTTG - +4 cisbp__M3630-klu-sr 1 0.869062 21251.2 1 6 CACCTG CCGCCCACGCAT - +4 cisbp__M5856-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.869062 21251.2 1 6 CACCTG GCCACGCCCACT - +4 taipale_cyt_meth__ELF3_NATRCGGATGYN_eDBD_repr 0 0.869062 21251.2 1 6 CACCTG CGCTTCCGTATA - +4 taipale_cyt_meth__ETV4_NTCGTAAATGMN_FL-Ets96B 6 0.869062 21251.2 1 6 CACCTG TGCATTTACGAC - +4 transfac_pro__M06136 6 0.869062 21251.2 1 6 CACCTG GCTTCTTAACAG - +4 transfac_pro__M06578 6 0.869062 21251.2 1 6 CACCTG CACGCCGGCCTA - +4 transfac_public__M00244-klu-sr 1 0.869062 21251.2 1 6 CACCTG CCGCCCACGCAT - +4 hocomoco__CEBPG_MOUSE.H11MO.0.B-Myc-nej 7 0.869062 21251.2 1 5 CACCTG ATTGCATCATCC + +4 homer__DATGASTCATHN_Atf3-CoRest-GATAe-Jra-Mef2-Myc-Snr1-Stat92E-bon-brm-foxo-grn-kay-mor-nej-pan-pnr 7 0.869062 21251.2 1 5 CACCTG GATGAGTCATCC + +4 neph__UW.Motif.0216 7 0.869062 21251.2 1 5 CACCTG GAATTAATGCCA + +4 transfac_pro__M06312-CG6654-CG7372 -1 0.869062 21251.2 1 5 CACCTG GCGTTCGAAATC + +4 transfac_pro__M07606-NFAT 7 0.869062 21251.2 1 5 CACCTG TTAATTTTTCCA + +4 transfac_pro__M01590-D-Mad-pan-Sox100B-Sox102F-Sox14-SoxN -1 0.869062 21251.2 1 5 CACCTG TCCTTTGTTTTT - +4 transfac_pro__M05490 7 0.869062 21251.2 1 5 CACCTG CATAATGCCCCA - +4 transfac_pro__M05740 7 0.869062 21251.2 1 5 CACCTG TCCGCAATCCCG - +4 transfac_pro__M05800 7 0.869062 21251.2 1 5 CACCTG TATTCATTCCCA - +4 transfac_pro__M06258 7 0.869062 21251.2 1 5 CACCTG GCGTTTGCCCCA - +4 transfac_pro__M06630 7 0.869062 21251.2 1 5 CACCTG TCGGCTTCCCCA - +4 cisbp__M6289 8 0.869062 21251.2 1 4 CACCTG TCATAAATTATC + +4 taipale__Jdp2_DBD_NATGACGTCAYN-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.869062 21251.2 1 4 CACCTG GATGACGTCATC + +4 cisbp__M6039-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.869062 21251.2 1 4 CACCTG GATGACGTCATC - +4 hocomoco__FOSL1_HUMAN.H11MO.0.A-CoRest-Jra-Myc-Stat92E-bon-cnc-kay-mor-nej-pan 8 0.869062 21251.2 1 4 CACCTG GGATGAGTCACC - +4 transfac_pro__M05510 8 0.869062 21251.2 1 4 CACCTG TCACAAGCCACT - +4 transfac_pro__M05898 8 0.869062 21251.2 1 4 CACCTG TTTGGATTAACA - +4 cisbp__M2182 5 0.869773 21268.5 1 6 CACCTG TTTTATTTCTTCTATTCTCTA + +4 cisbp__M3727-ey-Poxm-sv-toy 9 0.869773 21268.5 1 6 CACCTG GTGAACTCATGCGTGAAAATT + +4 cisbp__M4334 1 0.869773 21268.5 1 6 CACCTG CCGCCTTATTTCCGTTCTCGG + +4 jaspar__MA0558.1-Mef2 3 0.869773 21268.5 1 6 CACCTG AATTTCCAAAAATAGAAAGAA + +4 transfac_pro__M01569-GATAd-GATAe-grn-pnr-srp 5 0.869773 21268.5 1 6 CACCTG GTTTAGGCCTTATCAGCAATA + +4 transfac_pro__M05194 15 0.869773 21268.5 1 6 CACCTG GGGGGGGTCCGGCTGCCCCTC + +4 transfac_pro__M05197-E(z) 13 0.869773 21268.5 1 6 CACCTG GGGGGGGCCCGCCCGCCTTCC + +4 transfac_pro__M05283-ERR-E(z) 5 0.869773 21268.5 1 6 CACCTG GGGGGGGCCTGGCCGCCCCTC + +4 yetfasco__YOR140W_839 5 0.869773 21268.5 1 6 CACCTG TTTTATTTCTTCTATTCTCTA + +4 cisbp__M2351-Mef2 3 0.869773 21268.5 1 6 CACCTG AATTTCCAAAAATAGAAAGAA - +4 taipale__MAFG_full_NNNNTGCTGASTCAGCANNNN-cic-cnc-kay-maf-S-nej-tj 3 0.869773 21268.5 1 6 CACCTG AATATGCTGACTCAGCAATTT - +4 taipale_cyt_meth__PAX4_NATTTCACGCWTSANYGNNYN_eDBD_meth_repr-ey-sv-toy 10 0.869773 21268.5 1 6 CACCTG TGTGCATTCATGCGTGAAATC - +4 transfac_pro__M01495 1 0.869773 21268.5 1 6 CACCTG CCGCCTTATTTCCGTTCTCGG - +4 transfac_pro__M05202-Hcf-Rbbp5-RpII215 16 0.869773 21268.5 1 5 CACCTG GGGGGGGCCCTTCCGCCGCCC + +4 cisbp__M0022-Taf1 1 0.869854 21270.5 1 6 CACCTG CCGCCGCC + +4 cisbp__M5126-abd-A-al-ap-Awh-B-H2-C15-CG11294-CG32532-CG9876-Dll-E5-en-eve-exex-hbn-inv-lab-lbl-Lim1-lms-OdsH-otp-pb-PHDP-Pph13-repo-ro-Rx-slou-tup-Ubx-unpg-Vsx1-Vsx2 2 0.869854 21270.5 1 6 CACCTG GTTAATTG + +4 cisbp__M5641-bsh-CG34367-Dr-en-inv-lbe-lms-Ubx-unpg 1 0.869854 21270.5 1 6 CACCTG TTAATTGG + +4 cisbp__M6477-Sox102F 0 0.869854 21270.5 1 6 CACCTG TAACAATA + +4 fantom__motif106_KCGCANTC 1 0.869854 21270.5 1 6 CACCTG TCGCATTC + +4 flyfactorsurvey__Odsh_SOLEXA_FBgn0026058-Awh-B-H2-C15-CG9876-CG11294-CG15696-CG32532-Dll-E5-Lim1-OdsH-PHDP-Pph13-Rx-Ubx-Vsx1-Vsx2-abd-A-al-ap-en-eve-exex-hbn-inv-lab-lbl-lms-otp-pb-repo-ro-slou-unc-4- 2 0.869854 21270.5 1 6 CACCTG GTTAATTA + +4 flyfactorsurvey__Unc4_SOLEXA_FBgn0024184-Awh-CG9876-CG11294-CG32532-Dll-E5-OdsH-PHDP-Pph13-Rx-Ubx-Vsx1-Vsx2-ap-ems-en-exex-lms-otp-ro-slou-unc-4-unpg 2 0.869854 21270.5 1 6 CACCTG CTTAATTA + +4 predrem__nrMotif2299 2 0.869854 21270.5 1 6 CACCTG CTCGGCTG + +4 taipale_cyt_meth__NOTO_NYAATTAN_eDBD_meth-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-tup-Ubx-unc-4-unpg-Vsx1-Vsx2 0 0.869854 21270.5 1 6 CACCTG CCAATTAG + +4 taipale_cyt_meth__OTX1_NTAATCCN_eDBD_meth-bcd-Gsc 2 0.869854 21270.5 1 6 CACCTG CTAATCCC + +4 taipale_cyt_meth__OTX2_NTAATCCN_FL-Gsc-oc 2 0.869854 21270.5 1 6 CACCTG CTAATCCC + +4 taipale_cyt_meth__PDX1_RTCGTTAN_eDBD_meth-Antp-btn-Dfd-Dr-eve-exex-ind-lab-pb-Scr 0 0.869854 21270.5 1 6 CACCTG GTCATTAA + +4 taipale_cyt_meth__RAX_YTAATTAN_eDBD-Antp-ap-Awh-CG11294-CG32532-CG4328-CG9876-Drgx-E5-ems-en-eve-ind-inv-lab-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-Scr-Ubx-unpg-Vsx1-Vsx2-zen2 1 0.869854 21270.5 1 6 CACCTG CTAATTAC + +4 cisbp__M6188 1 0.869854 21270.5 1 6 CACCTG ATAATTAT - +4 hdpi__TFAP2C-TfAP-2 0 0.869854 21270.5 1 6 CACCTG TTCCAAAT - +4 predrem__nrMotif2470 1 0.869854 21270.5 1 6 CACCTG TCAGCGGC - +4 taipale__MSX2_DBD_NYAATTAN-bsh-CG34367-Dr-en-inv-lbe-lms-Ubx-unpg 1 0.869854 21270.5 1 6 CACCTG TTAATTGG - +4 taipale_cyt_meth__DLX6_NYAATTAN_eDBD-Antp-bsh-btn-Dll-Dr-en-exex-inv-Lim1-Scr-unpg 1 0.869854 21270.5 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DLX6_NYAATTAN_eDBD_meth-Antp-bsh-btn-Dll-Dr-en-exex-inv-Lim1-Scr-unpg 1 0.869854 21270.5 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DRGX_YYAATTAN_eDBD-CG11294-CG32532-CG4328-Drgx-E5-ems-eve-ind-lab-Lim3-Lmx1a-pb-slou-Ubx-Vsx1-Vsx2 1 0.869854 21270.5 1 6 CACCTG GTAATTAG - +4 taipale_cyt_meth__MSX1_NCAATTAN_FL-bsh-Dll-Dr 1 0.869854 21270.5 1 6 CACCTG GTAATTGG - +4 transfac_pro__M01090-Mad 2 0.869854 21270.5 1 6 CACCTG GTCGTCGC - +4 transfac_pro__M07791-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.869854 21270.5 1 6 CACCTG CTAATTGG - +4 jaspar__MA0344.1 -1 0.869854 21270.5 1 5 CACCTG GCCGGGGA + +4 neph__UW.Motif.0033 3 0.869854 21270.5 1 5 CACCTG ATTTTCCA + +4 swissregulon__sacCer__NHP10 -1 0.869854 21270.5 1 5 CACCTG GCCGGGGA + +4 taipale_cyt_meth__PITX1_YTAATCCN_FL-bcd-Gsc-Ptx1 3 0.869854 21270.5 1 5 CACCTG CTAATCCC + +4 taipale_cyt_meth__PITX3_NTAATCCN_eDBD-bcd-Gsc-oc-Ptx1 3 0.869854 21270.5 1 5 CACCTG CTAATCCC + +4 taipale_cyt_meth__PITX3_NTAATCCN_eDBD_meth-bcd-Gsc-Ptx1 3 0.869854 21270.5 1 5 CACCTG CTAATCCC + +4 taipale_cyt_meth__RHOXF2_NTAATCCN_FL-bcd-oc-Ptx1 3 0.869854 21270.5 1 5 CACCTG CTAATCCC + +4 transfac_pro__M09578-Taf1 3 0.869854 21270.5 1 5 CACCTG CGCCGCCA + +4 yetfasco__YDL002C_502 -1 0.869854 21270.5 1 5 CACCTG GCCGGGGA + +4 idmmpmm__oc-Gsc-bcd-oc 3 0.869854 21270.5 1 5 CACCTG CTAATCCG - +4 transfac_pro__M01643 -1 0.869854 21270.5 1 5 CACCTG GCCGGGGA - +4 transfac_pro__M04910-GATAe-grn-pnr 3 0.869854 21270.5 1 5 CACCTG GCTTGGCT - +4 flyfactorsurvey__Caup_Cell_FBgn0015919-caup 4 0.869854 21270.5 1 4 CACCTG CAATAACA + +4 predrem__nrMotif1929 4 0.869854 21270.5 1 4 CACCTG TAAAATCC + +4 hdpi__DHX36-Rhau 4 0.869854 21270.5 1 4 CACCTG AAATTTCC - +4 cisbp__M0915-abd-A-Antp-ap-CG11294-CG32532-CG9876-Dfd-E5-en-HGTX-lab-Lim1-Lim3-Lmx1a-otp-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 5 0.869854 21270.5 1 3 CACCTG TTAATTAC + +4 elemento__CGCGTGAC 5 0.869854 21270.5 1 3 CACCTG CGCGTGAC + +4 elemento__TAATTGAC 5 0.869854 21270.5 1 3 CACCTG TAATTGAC + +4 elemento__TTGTTGAC 5 0.869854 21270.5 1 3 CACCTG TTGTTGAC + +4 elemento__TTTATGAC 5 0.869854 21270.5 1 3 CACCTG TTTATGAC + +4 predrem__nrMotif1254 -3 0.869854 21270.5 1 3 CACCTG CTCTGTAA + +4 predrem__nrMotif694 -3 0.869854 21270.5 1 3 CACCTG CTCTATTT + +4 taipale_cyt_meth__HOXD8_NYAATTAN_eDBD_meth-abd-A-Antp-bsh-Dfd-Scr-Ubx 5 0.869854 21270.5 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__MEOX1_NYAATTAN_FL_meth-abd-A-Antp-Awh-bsh-btn-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-pb-Scr-Ubx-unpg 5 0.869854 21270.5 1 3 CACCTG GTAATTAC + +4 transfac_pro__M03827-fkh 5 0.869854 21270.5 1 3 CACCTG GCAAACAA + +4 transfac_pro__M06822 5 0.869854 21270.5 1 3 CACCTG TGGGGGAC + +4 cisbp__M1667 -3 0.869854 21270.5 1 3 CACCTG CTCCGGAT - +4 cisbp__M4715 -3 0.869854 21270.5 1 3 CACCTG CTTATCAG - +4 predrem__nrMotif1967 -3 0.869854 21270.5 1 3 CACCTG CTCTTGAA - +4 predrem__nrMotif2180 -3 0.869854 21270.5 1 3 CACCTG CTCAATGA - +4 predrem__nrMotif553 -3 0.869854 21270.5 1 3 CACCTG CTCAAATT - +4 predrem__nrMotif680 -3 0.869854 21270.5 1 3 CACCTG CTCGGCCC - +4 taipale_cyt_meth__NKX6-2_NTCATTAN_FL-Antp-bsh-btn-HGTX-Scr 5 0.869854 21270.5 1 3 CACCTG TTAATGAC - +4 transfac_pro__M01687 5 0.869854 21270.5 1 3 CACCTG GGAGTCAC - +4 transfac_pro__M05251 6 0.870247 21280.2 1 6 CACCTG AGACTAAACGTTTAATCT + +4 transfac_pro__M06853 2 0.870247 21280.2 1 6 CACCTG TACCCCACGACCCATTCC - +4 transfac_public__M00453 2 0.870247 21280.2 1 6 CACCTG CCAACTTTCGATTTCCTA - +4 scertf__zhu.HAL9 -1 0.870247 21280.2 1 5 CACCTG TCCGAAAAAAAAAGCGGA + +4 swissregulon__sacCer__HAL9 -1 0.870247 21280.2 1 5 CACCTG TCCGAAAAAAAAAGCGGA + +4 taipale_tf_pairs__ELK1_ONECUT2_RSCGGAASNGRTCGATAN_CAP_repr-onecut -1 0.870247 21280.2 1 5 CACCTG ACCGGAACCGATCGATAC + +4 cisbp__M1996-abd-A-Antp-Dll-ftz-Scr-Ubx 0 0.871029 21299.3 1 6 CACCTG TAATTAC + +4 flyfactorsurvey__Rx_SOLEXA_FBgn0020617-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-exex- 1 0.871029 21299.3 1 6 CACCTG TTAATTA + +4 cisbp__M1642-Tbp-Trf-Trf2 1 0.871029 21299.3 1 6 CACCTG ATATATT - +4 cisbp__M5175-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-E5-ems-en-eve-exex-ftz-gsb-gsb-n-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-PHDP-Pph13-prd-rep 0 0.871029 21299.3 1 6 CACCTG TAATTAA - +4 flyfactorsurvey__Hbn_Cell_FBgn0008636-E5-hbn 0 0.871029 21299.3 1 6 CACCTG TAATTAA - +4 hdpi__DAB2 0 0.871029 21299.3 1 6 CACCTG TCCCATT - +4 jaspar__MA0087.1-Sox102F 0 0.871029 21299.3 1 6 CACCTG AAACAAT - +4 hdpi__CSTF2-CstF64 2 0.871029 21299.3 1 5 CACCTG TTTATTT - +4 predrem__nrMotif1530 2 0.871029 21299.3 1 5 CACCTG TTTAACA - +4 transfac_pro__M04927-fkh 2 0.871029 21299.3 1 5 CACCTG GGAATTT - +4 transfac_pro__M05301-CG42741-luna 2 0.871029 21299.3 1 5 CACCTG CCGCCCT - +4 transfac_pro__M05444-btd-CG42741-luna-Sp1-Spps 2 0.871029 21299.3 1 5 CACCTG CCGCCCT - +4 swissregulon__sacCer__XBP1 -2 0.871029 21299.3 1 4 CACCTG TCTCGAG + +4 predrem__nrMotif66 -2 0.871029 21299.3 1 4 CACCTG CCATTCA - +4 swissregulon__hs__SOX2.p2-SoxN -2 0.871029 21299.3 1 4 CACCTG CATTGTT - +4 hdpi__PPP2R3B-CG4733 4 0.871029 21299.3 1 3 CACCTG TTTGTGC - +4 tfdimers__MD00325-NfI-pho-phol 21 0.871551 21312 1 6 CACCTG CCCCTCCCGCCATTGGCAGGGGGCCAACCGCT - +4 tfdimers__MD00308 3 0.871726 21316.3 1 6 CACCTG TTTTTTTTGATTGATTTGCATTTTTTT - +4 tfdimers__MD00508 12 0.871726 21316.3 1 6 CACCTG TATTTAAATAATCCCCTCCCCCACCAC - +4 transfac_pro__M04647-jumu 12 0.87174 21316.7 1 6 CACCTG GCCTCAAACAAACAATCATTGT + +4 transfac_pro__M01260-Stat92E 10 0.87174 21316.7 1 6 CACCTG CTCAAGCCATTTCCCGGAAATC - +4 transfac_pro__M04669-bin-fd102C-fd19B-FoxK-FoxL1-foxo-FoxP-slp1-slp2 12 0.87174 21316.7 1 6 CACCTG TGTGTACTTGTTTACAGCTGGA - +4 cisbp__M2441-Hsf 0 0.871876 21320 1 6 CACCTG GTTCTGTTCTGTTCT + +4 cisbp__M2444-Hsf 0 0.871876 21320 1 6 CACCTG GTTCTGTTCTAGAAC + +4 factorbook__SP1-CG3065-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-luna 9 0.871876 21320 1 6 CACCTG AGGGGGCGGGGCCTG + +4 factorbook__YY1-RpII215-Sap30-Taf1-Taf7-lid-pho-phol 9 0.871876 21320 1 6 CACCTG GGGGGCCGCCATCTT + +4 taipale_cyt_meth__ZNF454_NRGCGCCNGGCGCYN_eDBD_repr-brk 3 0.871876 21320 1 6 CACCTG TGGCGCCTGGCGCCA + +4 transfac_pro__M00772-Blimp-1-CG9650-Dif-dl-ebi-foxo-MTA1-like-nej-Stat92E 7 0.871876 21320 1 6 CACCTG GAAAGTGAAACTGAA + +4 transfac_pro__M02826 5 0.871876 21320 1 6 CACCTG AAGCCCCCCAAAAAT + +4 transfac_pro__M02873 2 0.871876 21320 1 6 CACCTG TTGACCGAGAATTCC + +4 transfac_pro__M07166 3 0.871876 21320 1 6 CACCTG TTTTTCCATTTTTGG + +4 transfac_pro__M09197 8 0.871876 21320 1 6 CACCTG ACCTCACGCGCCTCC + +4 cisbp__M4516-CG10431-lid-pho-phol-RpII215-Taf1-Taf7 8 0.871876 21320 1 6 CACCTG GGGGCCGCCATCTTG - +4 cisbp__M5568 3 0.871876 21320 1 6 CACCTG TTCGAACGTTTCGAA - +4 cisbp__M5607-cnc-maf-S-tj 0 0.871876 21320 1 6 CACCTG TTGCTGAGTCAGCAA - +4 flyfactorsurvey__CG10267_SOLEXA_F3-5-Zif 8 0.871876 21320 1 6 CACCTG CCTAACAACACTACC - +4 neph__UW.Motif.0212 8 0.871876 21320 1 6 CACCTG TGATTTCATTTCTCA - +4 taipale_cyt_meth__PAX7_NNATTCGTCACGSTN_FL-gsb-gsb-n-prd 0 0.871876 21320 1 6 CACCTG AACCGTGACGAATCG - +4 transfac_pro__M02872 2 0.871876 21320 1 6 CACCTG GCAACCGAGAATACC - +4 taipale_cyt_meth__TCF7_WCATCGRGRCGCTGW_eDBD_meth-pan -1 0.871876 21320 1 5 CACCTG ACATCGGGACGCTGA + +4 transfac_pro__M07675-cnc 10 0.871876 21320 1 5 CACCTG ACGTCATCATGACGT + +4 taipale_cyt_meth__RFX3_NGTTGCCWAGCAACN_eDBD-CG9727-Rfx 11 0.871876 21320 1 4 CACCTG CGTTGCCTAGCAACG + +4 yetfasco__MAL63_136 -2 0.871876 21320 1 4 CACCTG GCGAAAAAAAAAGCG - +4 neph__UW.Motif.0350 2 0.872189 21327.6 1 6 CACCTG GTCATTTTTTTCA + +4 taipale_cyt_meth__KLF13_NRCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 0 0.872189 21327.6 1 6 CACCTG CGCCACGCCCCCC + +4 taipale_tf_pairs__HOXB2_HOXB13_NNATCATNGTAAA_CAP_repr-pb 4 0.872189 21327.6 1 6 CACCTG TCATCATCGTAAA + +4 transfac_pro__M00622 2 0.872189 21327.6 1 6 CACCTG CTCATTTCAGAAT + +4 transfac_public__M00210-nub-pdm2-vvl 2 0.872189 21327.6 1 6 CACCTG CTCATTTGCATAC + +4 transfac_public__M00445 4 0.872189 21327.6 1 6 CACCTG GGGCTATTTGTCC + +4 cisbp__M3926-btd-CG3065-CG42741-CTCF-dar1-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 2 0.872189 21327.6 1 6 CACCTG GGCCCCGCCCCCC - +4 cisbp__M4106 4 0.872189 21327.6 1 6 CACCTG GCCCTATTTGTCC - +4 taipale_cyt_meth__NRL_NWWWNTGCTGACN_FL-maf-S-tj 6 0.872189 21327.6 1 6 CACCTG CGTCAGCACTTTT - +4 transfac_pro__M01244-Hsf-pb 6 0.872189 21327.6 1 6 CACCTG TTCTAGAACGTTC - +4 jaspar__MA0412.1 8 0.872189 21327.6 1 5 CACCTG TCGGCGGCTAATT + +4 cisbp__M2217 8 0.872189 21327.6 1 5 CACCTG TCGGCGGCTAATT - +4 transfac_pro__M08933-cnc-CoRest-Jra-kay-mor-Myc-nej-pan 8 0.872189 21327.6 1 5 CACCTG CGATGACTCATCC - +4 transfac_pro__M07374-cnc-kay-maf-S -2 0.872189 21327.6 1 4 CACCTG GCTGAGTCATGGT + +4 tfdimers__MD00241-Ptx1-tup 16 0.872873 21344.4 1 6 CACCTG ATTTCTCTAATCCTATTAACTATATT - +4 tfdimers__MD00256 12 0.872971 21346.7 1 6 CACCTG AAAATAAATAAATAATTGTAAAT + +4 swissregulon__sacCer__DAL82 6 0.873053 21348.8 1 6 CACCTG CAAGCGCAATTTTC + +4 taipale_tf_pairs__MEIS1_DLX2_TGACANNNTAATKR_CAP_repr 1 0.873053 21348.8 1 6 CACCTG TGACAGCTTAATTG + +4 cisbp__M6340-Mef2-rump 0 0.873053 21348.8 1 6 CACCTG GTTCTATTTATAGC - +4 jaspar__MA0010.1-br 0 0.873053 21348.8 1 6 CACCTG GATTTGTCTATTAC - +4 bergman__Abd-B-Abd-B -1 0.873053 21348.8 1 5 CACCTG ACGTTTATGGCGAC + +4 cisbp__M2526-Abd-B -1 0.873053 21348.8 1 5 CACCTG ACATTTATGGCGAC - +4 cisbp__M5210-btd-cbt-CG3065-CG42741-dar1-E2f2-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 9 0.873053 21348.8 1 5 CACCTG GGCCACGCCCACTC - +4 cisbp__M6515-Dp-E2f1-E2f2 9 0.873053 21348.8 1 5 CACCTG GTTTCCCGCCATTT - +4 hocomoco__NFYC_MOUSE.H11MO.0.B-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay-yps -1 0.873053 21348.8 1 5 CACCTG TTCTGATTGGCTGA - +4 cisbp__M5578 10 0.873053 21348.8 1 4 CACCTG ACGAAACCGAAACT + +4 taipale__IRF8_DBD_NCGAAACCGAAACY 10 0.873053 21348.8 1 4 CACCTG ACGAAACCGAAACT + +4 transfac_pro__M00982-brm-btd-CG42741-CTCF-E(z)-HDAC1-kay-klu-luna-Nelf-E-Nf-YB-Rbbp5-Spps-sr-SREBP 10 0.873053 21348.8 1 4 CACCTG CCCGCCCCCGCCCC + +4 transfac_pro__M07243 -2 0.873053 21348.8 1 4 CACCTG GCTTGGAGACCAAG - +4 cisbp__M5453-fd59A-foxo-slp2 11 0.873053 21348.8 1 3 CACCTG TGTTTATTGTTTAC - +4 taipale__FOXJ2_DBD_RTAAACAATAAAYA_repr-fd59A-foxo-FoxP-slp2 11 0.873053 21348.8 1 3 CACCTG TGTTTATTGTTTAC - +4 tfdimers__MD00498-Mad-oc 4 0.873487 21359.4 1 6 CACCTG TATATTCCTTTGTTTTAATCCTTTT - +4 transfac_public__M00250-sens-sens-2 5 0.873534 21360.5 1 6 CACCTG GGCATATGCTGTGATTTATTTTGT - +4 cisbp__M2278-bon-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 5 0.874098 21374.3 1 6 CACCTG TGTGACTCATT + +4 cisbp__M5715-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-otp-repo-Traf4-unc-4 1 0.874098 21374.3 1 6 CACCTG TAATTTAATTA + +4 predrem__nrMotif1018-CTCF-Spps-btd 0 0.874098 21374.3 1 6 CACCTG CCCCGCCCCGC + +4 predrem__nrMotif1034 2 0.874098 21374.3 1 6 CACCTG CAGCCCTTTGA + +4 predrem__nrMotif1373 5 0.874098 21374.3 1 6 CACCTG CATTCTGCTTT + +4 stark__ATGANNNNTCA 2 0.874098 21374.3 1 6 CACCTG ATGAAAAATCA + +4 taipale__YY1_full_NCCGCCATTNN-pho-phol 2 0.874098 21374.3 1 6 CACCTG GCCGCCATTAT + +4 transfac_pro__M06484-CG11966-CG4374-ken 0 0.874098 21374.3 1 6 CACCTG TTCCTAAATGC + +4 transfac_pro__M09250 4 0.874098 21374.3 1 6 CACCTG ACAATAATTGA + +4 cisbp__M5954-pho-phol 2 0.874098 21374.3 1 6 CACCTG GCCGCCATTAT - +4 cisbp__M5956-pho-phol 5 0.874098 21374.3 1 6 CACCTG ACCGCCATTTT - +4 flyfactorsurvey__peb-F1-3_SOLEXA_FBgn0003053-peb 2 0.874098 21374.3 1 6 CACCTG AGCATCCCCCA - +4 hocomoco__OTX2_HUMAN.H11MO.0.A-Gsc-Ptx1-oc 5 0.874098 21374.3 1 6 CACCTG GTTAATCCCCT - +4 taipale_cyt_meth__FOSL1_NRTGANTCAYN_FL-Jra-kay 5 0.874098 21374.3 1 6 CACCTG GATGAATCATC - +4 transfac_pro__M00807-sr 5 0.874098 21374.3 1 6 CACCTG GCCGCCCCCAC - +4 transfac_pro__M01863-CrebB-Jra 3 0.874098 21374.3 1 6 CACCTG GCTGACGTAAT - +4 bergman__dif_Rel-Dif-Rel-dl 6 0.874098 21374.3 1 5 CACCTG GGGGAATCCCC + +4 predrem__nrMotif428 -1 0.874098 21374.3 1 5 CACCTG TTCTCTTGTTT + +4 jaspar__MA0465.1-Abd-B-cad-eve 6 0.874098 21374.3 1 5 CACCTG TTTTATGGCTT - +4 cisbp__M3716 7 0.874098 21374.3 1 4 CACCTG GAATAATTACC + +4 hocomoco__NKX62_HUMAN.H11MO.0.D-Antp-HGTX-Lim1-Scr-Ubx-abd-A-bsh-btn-ems-ftz-ind-lab-zen2 7 0.874098 21374.3 1 4 CACCTG AATTAATTACC + +4 taipale_cyt_meth__HOXD13_NCCAATAAAAN_eDBD-cad 7 0.874098 21374.3 1 4 CACCTG CCCAATAAAAC + +4 taipale_cyt_meth__JDP2_NATGASTCAYN_eDBD_meth-bon-cnc-Jra-kay-Mef2-Myc-nej-pan 7 0.874098 21374.3 1 4 CACCTG GATGACTCATC + +4 transfac_public__M00377 7 0.874098 21374.3 1 4 CACCTG GAATAATTACC + +4 cisbp__M6171-Irbp18-nej-slbo-Xrp1 7 0.874098 21374.3 1 4 CACCTG ATTGCACAATT - +4 predrem__nrMotif282 7 0.874098 21374.3 1 4 CACCTG AAAGACAGACA - +4 taipale_cyt_meth__HOXA10_NGYAATAAAAN_FL-abd-A-Abd-B-cad-eve-Ubx 7 0.874098 21374.3 1 4 CACCTG GTTTTATTGCC - +4 taipale_cyt_meth__HOXA11_RGYAATAAAAN_eDBD-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.874098 21374.3 1 4 CACCTG GTTTTATGGCC - +4 taipale_cyt_meth__HOXA11_RGYAATAAAAN_eDBD_meth-abd-A-Abd-B-cad-eve-Ubx 7 0.874098 21374.3 1 4 CACCTG ATTTTATTGCT - +4 taipale_cyt_meth__HOXC10_NRTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.874098 21374.3 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC11_NRTCGTAAAAN_FL-Abd-B-cad 7 0.874098 21374.3 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M07302-btd-CG7839-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP -2 0.874098 21374.3 1 4 CACCTG GCTGATTGGCT - +4 transfac_pro__M08796-CG10431 7 0.874098 21374.3 1 4 CACCTG TTGCCCGTACT - +4 transfac_pro__M09023 -3 0.874098 21374.3 1 3 CACCTG CTCGGGAATCG - +4 cisbp__M6116 1 0.874876 21393.3 1 6 CACCTG GGACATGCCCAGGCATGCC - +4 taipale_tf_pairs__ETV2_PITX1_RSCGGAANNNNNGGMTTAN_CAP-pnt-Ptx1 8 0.874876 21393.3 1 6 CACCTG CTAATCCCTCACTTCCGGT - +4 taipale_tf_pairs__ETV2_SOX15_RSCGGAANNNNNNYWTTGT_CAP_repr-pnt 9 0.874876 21393.3 1 6 CACCTG ACAATGGGCCACTTCCGGC - +4 taipale_tf_pairs__HOXB2_ETV7_NSCGGAARNNNNNMATTAN_CAP_repr-aop-pb 5 0.874876 21393.3 1 6 CACCTG CTAATGACTTACTTCCGGC - +4 cisbp__M1780 2 0.875068 21398 1 6 CACCTG TTAGCCGCC + +4 cisbp__M5720-bcd-Gsc-oc-Ptx1 3 0.875068 21398 1 6 CACCTG CTTAATCCC + +4 flyfactorsurvey__odd_NBT_5_FBgn0002985-bowl-drm-odd-sob 2 0.875068 21398 1 6 CACCTG GCTACTGTT + +4 predrem__nrMotif1270 2 0.875068 21398 1 6 CACCTG TTTGCCATT + +4 predrem__nrMotif1702 0 0.875068 21398 1 6 CACCTG TCACTGGAA + +4 predrem__nrMotif203 0 0.875068 21398 1 6 CACCTG CACTCTCCA + +4 predrem__nrMotif343 1 0.875068 21398 1 6 CACCTG TCAGTTCTT + +4 predrem__nrMotif607 1 0.875068 21398 1 6 CACCTG AGTCTTTCT + +4 predrem__nrMotif616 2 0.875068 21398 1 6 CACCTG TGGCCCTTT + +4 taipale__PITX3_DBD_NYTAATCCN-bcd-Gsc-oc-Ptx1 3 0.875068 21398 1 6 CACCTG CTTAATCCC + +4 cisbp__M0975-CG32532-Dll-en-Lim1-Lim3 3 0.875068 21398 1 6 CACCTG ATTTAATTA - +4 cisbp__M0977-abd-A-Abd-B-Antp-cad-Dbx-eve-H2.0-Scr-Ubx 2 0.875068 21398 1 6 CACCTG TTTATTACC - +4 cisbp__M1027-abd-A-Abd-B-Antp-bsh-btn-C15-cad-CG15696-CG32532-Dfd-Dll-en-eve-exex-ftz-hbn-HGTX-ind-lab-lms-NK7.1-pb-repo-Scr-slou-tup-Ubx-zen2 1 0.875068 21398 1 6 CACCTG GGTAATTAA - +4 cisbp__M5124-bowl-drm-odd-sob 2 0.875068 21398 1 6 CACCTG GCTACTGTA - +4 hdpi__MEF2B-Mef2 0 0.875068 21398 1 6 CACCTG AATTTCATT - +4 predrem__nrMotif112 0 0.875068 21398 1 6 CACCTG CTCCACTGA - +4 predrem__nrMotif439 0 0.875068 21398 1 6 CACCTG TGACTGTGC - +4 cisbp__M3711-sv 4 0.875068 21398 1 5 CACCTG CATAAACTC + +4 predrem__nrMotif189 4 0.875068 21398 1 5 CACCTG AAATGACAA + +4 predrem__nrMotif369 4 0.875068 21398 1 5 CACCTG CAAGCCCCA + +4 cisbp__M0963-CG32532-CG4328-en-Lim1-Lim3-Lmx1a-Pph13 4 0.875068 21398 1 5 CACCTG TAATTAAAT - +4 hocomoco__NFAC3_HUMAN.H11MO.0.B-NFAT 4 0.875068 21398 1 5 CACCTG AGTTTTCCA - +4 predrem__nrMotif466 4 0.875068 21398 1 5 CACCTG CAGTGCCCC - +4 taipale_cyt_meth__BARHL2_NTAATTGNY_eDBD-B-H1-B-H2-CG11085-eve-Ubx-unpg -1 0.875068 21398 1 5 CACCTG AGCAATTAG - +4 transfac_pro__M00304 -1 0.875068 21398 1 5 CACCTG GGCTGAGCG - +4 transfac_pro__M09184 5 0.875068 21398 1 4 CACCTG TCCATCATC + +4 cisbp__M5004-CG3407-Hesr 5 0.875068 21398 1 4 CACCTG GGCTTGACA - +4 hocomoco__ZBT14_HUMAN.H11MO.0.C 5 0.875068 21398 1 4 CACCTG GCGCGCTCC - +4 predrem__nrMotif1843 -2 0.875068 21398 1 4 CACCTG TCTTAGAAA - +4 predrem__nrMotif787-nej -2 0.875068 21398 1 4 CACCTG CCACTGTTT - +4 predrem__nrMotif1143 6 0.875068 21398 1 3 CACCTG TTCACAGAC + +4 taipale_cyt_meth__VSX2_SYYAATTAN_FL-en-eve-inv-Vsx1-Vsx2 6 0.875068 21398 1 3 CACCTG GCTAATTAC + +4 taipale_cyt_meth__VSX2_SYYAATTAN_FL_meth-en-inv-lab-Lim3-Vsx1-Vsx2 6 0.875068 21398 1 3 CACCTG GCTAATTAC + +4 predrem__nrMotif2371 7 0.875068 21398 1 2 CACCTG TGCCCAACA - +4 taipale__SP4_full_NWRGCCMCGCCCMCTNN-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Nf-YB-Sp1-Spps 11 0.875836 21416.8 1 6 CACCTG TAAGCCACGCCCCCTTT + +4 taipale_tf_pairs__E2F3_FOXO6_NMATGACACGCGCCMNN_CAP_repr-E2f1-foxo 6 0.875836 21416.8 1 6 CACCTG GAATGACACGCGCCCAC + +4 transfac_pro__M02847-E2f1 10 0.875836 21416.8 1 6 CACCTG CGTTCGGCGCCAAAAGC + +4 cisbp__M2471-klu-sr 0 0.875836 21416.8 1 6 CACCTG TACCCCACATTTATTTA - +4 cisbp__M5625-Antp-btn-dve-lab-Lim3-Scr 5 0.875836 21416.8 1 6 CACCTG GTAATTACCGTAATTAA - +4 hocomoco__PO3F3_HUMAN.H11MO.0.D-CG4328-Dll-Lmx1a-dve-nub-pdm2-pdm3-vvl 5 0.875836 21416.8 1 6 CACCTG AAATTTGCATAATTTAT - +4 taipale_cyt_meth__NFIC_NTTGGCNNNNTGCCARN_FL_meth-C15-NfI 10 0.875836 21416.8 1 6 CACCTG GTTGGCACCGCGCCAAC - +4 taipale_tf_pairs__HOXB2_PAX5_NNGTCACGCNNCATTAN_CAP_repr-pb-sv 7 0.875836 21416.8 1 6 CACCTG GTAATGATGCGTGACGG - +4 transfac_pro__M00407-Mef2-rump 1 0.875836 21416.8 1 6 CACCTG CAATCTATTTTTAGCAT - +4 transfac_pro__M01023-Hsf 4 0.875836 21416.8 1 6 CACCTG GGAGAAATTTCTAGAAT - +4 transfac_pro__M01204 2 0.875836 21416.8 1 6 CACCTG AGGAACTTCCTCTTTTT - +4 transfac_pro__M01314-al-ap-Awh-CG11085-CG18599-E5-ems-en-eve-inv-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-unc-4-zfh2 9 0.875836 21416.8 1 6 CACCTG TACATTAATTAGCGCTC - +4 transfac_pro__M01336-abd-A-Antp-CG32532-Dfd-HGTX-OdsH-repo-Scr-Ubx-unc-4 10 0.875836 21416.8 1 6 CACCTG GCTTATTAATTAACTCG - +4 transfac_pro__M01447-oc-Ptx1 9 0.875836 21416.8 1 6 CACCTG GATGATTAATCCCTTCA - +4 transfac_pro__M02917-D-Sox21a-Sox21b 11 0.875836 21416.8 1 6 CACCTG CACCTATTGTTCCGTGA - +4 transfac_pro__M01367-Antp-ap-Awh-CG11294-CG32532-CG4328-CG9876-Dfd-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-Scr-unc-4-unpg-Vsx1 13 0.875836 21416.8 1 4 CACCTG CCCATTAATTAATCACC + +4 cisbp__M0139 4 0.876203 21425.8 1 6 CACCTG CAAATATTCG + +4 cisbp__M0403 3 0.876203 21425.8 1 6 CACCTG TTGGGCCCAA + +4 cisbp__M0677-E2f1 3 0.876203 21425.8 1 6 CACCTG GCGCGCCAAA + +4 cisbp__M1084-Awh-B-H1-B-H2-C15-CG15696-CG18599-CG32532-CG34367-Dr-Hmx-Lim1-NK7.1-OdsH-PHDP-Vsx2-al-bsh-dve-en-inv-lab-lbe-lms-repo-slou-unc-4-unpg-zfh2 2 0.876203 21425.8 1 6 CACCTG CTTAATTGGT + +4 cisbp__M5099-Mad 1 0.876203 21425.8 1 6 CACCTG CTGCCGACGC + +4 fantom__motif135_TNKYTGCAKA 3 0.876203 21425.8 1 6 CACCTG TTTTTGCAGA + +4 flyfactorsurvey__Mad_FlyReg_FBgn0011648-Mad 1 0.876203 21425.8 1 6 CACCTG CTGGCGACGC + +4 jaspar__MA1006.1 1 0.876203 21425.8 1 6 CACCTG CTGCCGGCGT + +4 taipale__ALX3_full_NNYAATTANN-al-ap-Awh-C15-CG11294-CG32532-CG34367-CG9876-Dll-E5-ems-en-hbn-inv-lbe-Lim1-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2 2 0.876203 21425.8 1 6 CACCTG TCTAATTAAA + +4 taipale_cyt_meth__ATOH1_ANCATATGNY_eDBD_meth-amos-ato-da-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.876203 21425.8 1 6 CACCTG AACATATGTC + +4 taipale_cyt_meth__SOX9_MGAACAATRN_eDBD_meth-D-Sox100B-SoxN 2 0.876203 21425.8 1 6 CACCTG AGAACAATAG + +4 transfac_pro__M01083-abd-A 1 0.876203 21425.8 1 6 CACCTG GTAAATTATA + +4 transfac_pro__M02036-klu 2 0.876203 21425.8 1 6 CACCTG CGCCCCCGCC + +4 transfac_pro__M03185 3 0.876203 21425.8 1 6 CACCTG GGGCGCCACT + +4 transfac_pro__M03193 4 0.876203 21425.8 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M03201 4 0.876203 21425.8 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M05013 4 0.876203 21425.8 1 6 CACCTG ACGCCGCCCA + +4 transfac_pro__M05054 4 0.876203 21425.8 1 6 CACCTG AGGCCGCCCA + +4 transfac_pro__M05068 4 0.876203 21425.8 1 6 CACCTG AGGCCGCCCA + +4 yetfasco__YGR249W_2141 2 0.876203 21425.8 1 6 CACCTG GTGTTCTATG + +4 cisbp__M0314-CG7786-crc-gt-hng1-Irbp18-Myc-nej-Pdp1-slbo-srl-vri-Xrp1 2 0.876203 21425.8 1 6 CACCTG ATTGCGTAAT - +4 cisbp__M0326-CG7786-Irbp18-Pdp1-Xrp1-gt-nej-slbo-srl-vri 2 0.876203 21425.8 1 6 CACCTG ATTGCGCAAT - +4 cisbp__M1382 2 0.876203 21425.8 1 6 CACCTG GGGACGATCA - +4 cisbp__M4782-btd-Spps 4 0.876203 21425.8 1 6 CACCTG TCCGCCCCCT - +4 idmmpmm__hkb-hkb-sr 3 0.876203 21425.8 1 6 CACCTG TCACGCCCAC - +4 predrem__nrMotif336 0 0.876203 21425.8 1 6 CACCTG TGCTTGCCCT - +4 taipale__Gbx1_DBD_NNYAATTANN-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-ftz-hbn-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 2 0.876203 21425.8 1 6 CACCTG GTTAATTGGT - +4 taipale_cyt_meth__PBX1_KTGATTGAYK_FL_meth_repr 4 0.876203 21425.8 1 6 CACCTG CATCAATCAC - +4 transfac_pro__M07304 0 0.876203 21425.8 1 6 CACCTG CATCAATCAA - +4 cisbp__M6301 5 0.876203 21425.8 1 5 CACCTG AATTAAAGCA + +4 transfac_pro__M07656-amos-ato-crp-da-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.876203 21425.8 1 5 CACCTG ACCATATGGT + +4 cisbp__M1151-CG4328-Lmx1a 5 0.876203 21425.8 1 5 CACCTG TTAATTAAAT - +4 cisbp__M2429 5 0.876203 21425.8 1 5 CACCTG TGAGTCATTT - +4 cisbp__M5298-B-H1-B-H2-CG11085-Dr-lab-NK7.1-pb-slou-Ubx-unpg -1 0.876203 21425.8 1 5 CACCTG AGCAATTAGC - +4 stark__AATTRYGWCA 5 0.876203 21425.8 1 5 CACCTG TGACACAATT - +4 stark__TCANNNTGGA -1 0.876203 21425.8 1 5 CACCTG TCCAAAATGA - +4 taipale__BARHL2_full_NNTAATTGNN-B-H1-B-H2-CG11085-Dr-lab-NK7.1-pb-slou-Ubx-unpg -1 0.876203 21425.8 1 5 CACCTG AGCAATTAGC - +4 cisbp__M1250 6 0.876203 21425.8 1 4 CACCTG AGATTCCATG + +4 cisbp__M6191-E2f1-eve 6 0.876203 21425.8 1 4 CACCTG GGCGCGAAAC + +4 homer__ATTGCGCAAC_CEBP-Irbp18-Xrp1-slbo 6 0.876203 21425.8 1 4 CACCTG ATTGCGCAAC + +4 yetfasco__YPL139C_1143 -2 0.876203 21425.8 1 4 CACCTG TCTTCATTTC + +4 cisbp__M5284-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbe-lbl-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 6 0.876203 21425.8 1 4 CACCTG GCTAATTAGC - +4 predrem__nrMotif1359 -2 0.876203 21425.8 1 4 CACCTG CATGAGAAAA - +4 taipale__ZNF740_full_NCCCCCCCAC 7 0.876203 21425.8 1 3 CACCTG CCCCCCCCAC + +4 transfac_pro__M05590 7 0.876203 21425.8 1 3 CACCTG TAGCCATTAC - +4 transfac_pro__M07544 7 0.876203 21425.8 1 3 CACCTG TAATAATTAC - +4 transfac_public__M00023-Antp-Scr 7 0.877636 21460.8 1 6 CACCTG TGCCAACTTCCCCATTAGTGGTCGCCTCCA + +4 cisbp__M3428-Antp-Scr 7 0.877636 21460.8 1 6 CACCTG TGCCAACTCCCCCATTAGTGCTCGACTCCA - +4 tfdimers__MD00564-NfI-pho-phol 5 0.877636 21460.8 1 6 CACCTG ATTAAAAAATGGCAGCTTGCCAAGAAAAAT - +4 cisbp__M5514-CG17829 3 0.878489 21481.7 1 6 CACCTG GCGGACGTTGCAACGTCCGC + +4 dbcorrdb__BRCA1__ENCSR000EBX_1__m1-Chd1-CoRest-ss 9 0.878489 21481.7 1 6 CACCTG CTCTCGCGAGACCCGGGGGC + +4 dbcorrdb__CBX3__ENCSR000BRT_1__m9-HP1b-HP1c-HP1e-Su(var)205 0 0.878489 21481.7 1 6 CACCTG CACACACACACAGACACAAA + +4 dbcorrdb__ELK1__ENCSR000DZB_1__m1-aop-Atac3-bs-CTCF-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Max-Myc-pho-phol-pnt-RpII215-Sin3A-Taf1-tna 0 0.878489 21481.7 1 6 CACCTG GGCCGGAAGTGGCGGCGGGG + +4 dbcorrdb__ELK1__ENCSR000EFU_1__m2-Atac3-Eip74EF-Hcf-RpII215-Sin3A-Taf1 4 0.878489 21481.7 1 6 CACCTG CCGTTGCCGGAAGTGGGCGC + +4 dbcorrdb__EZH2__ENCSR000ASZ_1__m3-E(z) 5 0.878489 21481.7 1 6 CACCTG GGACACAGCCGCGGCGGCCG + +4 dbcorrdb__FOS__ENCSR000EVU_1__m1-cnc-GATAe-grn-Jra-kay-Mef2-Myc-nej-pnr-Stat92E 7 0.878489 21481.7 1 6 CACCTG AATGACTCATCCCTTAGTAA + +4 dbcorrdb__IRF1__ENCSR000EGT_1__m1-Brf-brm-btd-CG42741-CTCF-dar1-E2f2-E(z)-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Spt20-SREBP-Stat92E-vtd 13 0.878489 21481.7 1 6 CACCTG GGGGAGGGGGCGGGGCCTGG + +4 dbcorrdb__IRF4__ENCSR000BGY_1__m1-CG9650-Dif-dl-MTA1-like-Stat92E 1 0.878489 21481.7 1 6 CACCTG CTTGCTGTTTCATTTCCACA + +4 dbcorrdb__NFYA__ENCSR000DNS_1__m1-bs-btd-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 1 0.878489 21481.7 1 6 CACCTG CCCTCTGATTGGCTGGGGCG + +4 dbcorrdb__NR3C1__ENCSR000EEV_1__m1-CG10431-Max 4 0.878489 21481.7 1 6 CACCTG TCGCCATCTTGGGGCCGGGC + +4 dbcorrdb__POLR2A__ENCSR000AKZ_1__m3-RpII215 12 0.878489 21481.7 1 6 CACCTG GCGGCGGCAGGCAAGCGCAC + +4 dbcorrdb__POLR2A__ENCSR000BMR_1__m1-aop-Atac3-bs-Dif-dl-E2f1-Eip74EF-ERR-Ets65A-Ets96B-Ets97D-E(z)-FoxP-Hcf-lid-Max-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 3 0.878489 21481.7 1 6 CACCTG GCGCCGCTTCCGGCCCCGGC + +4 dbcorrdb__SETDB1__ENCSR000EWD_1__m4-bon-egg 5 0.878489 21481.7 1 6 CACCTG ATTGCAGTCTGACTGCTGAG + +4 dbcorrdb__STAT1__ENCSR000DZM_1__m3-btd-CG42741-CTCF-dar1-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 12 0.878489 21481.7 1 6 CACCTG GGCCCCGCCCCCTGCCCTCC + +4 dbcorrdb__STAT2__ENCSR000FBC_1__m3-Stat92E 1 0.878489 21481.7 1 6 CACCTG TTGATTTCTCAGAAATTGCG + +4 dbcorrdb__STAT5A__ENCSR000BQZ_1__m1-ebi-foxo-Jra-Mef2-MTA1-like-nej-NFAT-Stat92E 9 0.878489 21481.7 1 6 CACCTG GCTGAGTCATATCGAGACTA + +4 dbcorrdb__ZBTB33__ENCSR000BNY_1__m1-Chd1-CoRest 11 0.878489 21481.7 1 6 CACCTG AGATCTCGCGAGACCCGGCG + +4 dbcorrdb__ZNF274__ENCSR000EUK_1__m3-bon 4 0.878489 21481.7 1 6 CACCTG TTTCCACATTCATTGCATTC + +4 swissregulon__hs__ZNF143.p2-Hcf-Six4-egg 0 0.878489 21481.7 1 6 CACCTG CAACTCCCAGCATGCCCCGC + +4 taipale__HINFP1_full_GCGGACSNNNNNNSGTCCGC_repr-CG17829 3 0.878489 21481.7 1 6 CACCTG GCGGACGTTGCAACGTCCGC + +4 cisbp__M4327 11 0.878489 21481.7 1 6 CACCTG TTCTTCCGGAAAAATTTGCA - +4 dbcorrdb__CTCF__ENCSR000DWQ_1__m2-CTCF-vtd 12 0.878489 21481.7 1 6 CACCTG GGGGCACTATAGCCCCACTA - +4 dbcorrdb__E2F6__ENCSR000BLI_1__m1-Brf-brm-btd-CTCF-E2f1-E2f2-Eip74EF-ERR-E(z)-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-TfAP-2-tna-usp-vtd 2 0.878489 21481.7 1 6 CACCTG CCCCCTTCCCGCCCGCCGCC - +4 dbcorrdb__PAX5__ENCSR000BJH_1__m1-ey-Poxm-sv-toy 5 0.878489 21481.7 1 6 CACCTG GGTCACGCTTGGCTGCCCAC - +4 dbcorrdb__POLR2A__ENCSR000BGO_1__m1-aop-Atac3-bs-CG10431-Dif-dl-E2f1-Eip74EF-Ets96B-Ets97D-ewg-E(z)-FoxP-Hcf-Myc-Rbbp5-RpII215-Sin3A-Taf1 14 0.878489 21481.7 1 6 CACCTG CGCGGCGCTTCCGGCGCGGG - +4 dbcorrdb__POLR2A__ENCSR000DLQ_1__m1-RpII215 13 0.878489 21481.7 1 6 CACCTG GGTCGTTTTGCGCTTGCGCC - +4 dbcorrdb__POLR2A__ENCSR000DPC_1__m1-E(z)-RpII215-Sin3A-Taf1 14 0.878489 21481.7 1 6 CACCTG CCTTGCGCTTCCGCCGTTTG - +4 dbcorrdb__RCOR1__ENCSR000EFG_1__m5-Brf-brm-btd-CG42741-CG7368-CoRest-crol-ct-CTCF-ERR-E(z)-HDAC1-Klf15-klu-l(3)neo38-Nelf-E-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-vtd 2 0.878489 21481.7 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 dbcorrdb__SPI1__ENCSR000BIJ_1__m1-CG9650-ebi-MTA1-like-nej-Stat92E-sv 8 0.878489 21481.7 1 6 CACCTG AGTTTCACTTCCTCTTTTTT - +4 dbcorrdb__TAF1__ENCSR000BHO_1__m2-Taf1 11 0.878489 21481.7 1 6 CACCTG GCAGACGCCGGAACGATAAG - +4 dbcorrdb__ZNF274__ENCSR000EVG_1__m4 7 0.878489 21481.7 1 6 CACCTG GCCTTTCCACATTCACTGCA - +4 hocomoco__SP3_HUMAN.H11MO.0.B-Brf-CG3065-CG42741-CTCF-CoRest-E2f1-ERR-E(z)-HDAC1-Klf15-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-Spt20-brm-btd-ct-dar1-kay-klu-luna-sr-tna-vtd 0 0.878489 21481.7 1 6 CACCTG CCCCGGCCCCGCCCCCCCCC - +4 taipale_tf_pairs__ETV2_HOXA2_NCCGGAAGNNNNNNYMATTA_CAP-pb-pnt 4 0.878489 21481.7 1 6 CACCTG TAATGACTATTACTTCCGGT - +4 taipale_tf_pairs__ETV2_SOX15_RSCGGAWNNNNNNACAATRN_CAP_repr-pnt 10 0.878489 21481.7 1 6 CACCTG CTATTGTTCTTACTTCCGGT - +4 transfac_pro__M01578 12 0.878489 21481.7 1 6 CACCTG GGCGAATAGATCTATTCTGG - +4 dbcorrdb__EZH2__ENCSR000ARH_1__m4-E(z) 15 0.878489 21481.7 1 5 CACCTG CAGTCCGCTTCGCCGGTCCT + +4 dbcorrdb__EZH2__ENCSR000ARH_1__m2-E(z) 16 0.878489 21481.7 1 4 CACCTG TCCGGCTCTCAGAGGCTCCC - +4 hdpi__ID2-emc 0 0.879044 21495.3 1 6 CACCTG GACATC - +4 jaspar__MA0190.1-Gsc-bcd 1 0.879044 21495.3 1 5 CACCTG TAATCC + +4 hdpi__NANOS1-nos -1 0.879044 21495.3 1 5 CACCTG CGCCGC - +4 transfac_pro__M00803-Dp-E2f1-E2f2 2 0.879044 21495.3 1 4 CACCTG CGCGCC - +4 flyfactorsurvey__CG12236-PB_SANGER_2.5_FBgn0029822-CG12236 -3 0.879044 21495.3 1 3 CACCTG CTTCCA + +4 transfac_pro__M01292 -4 0.879044 21495.3 1 2 CACCTG TTTTAT - +4 cisbp__M1902-Awh 0 0.879443 21505 1 5 CACCTG TAATT + +4 transfac_pro__M02188-Awh 0 0.879443 21505 1 5 CACCTG TAATT - +4 hdpi__SPATS2 -3 0.879443 21505 1 3 CACCTG CTTTC - +4 cisbp__M1708 6 0.87965 21510.1 1 6 CACCTG TCCTCCGATCGG + +4 homer__ATTTCTNAGAAA_STAT5-Stat92E 1 0.87965 21510.1 1 6 CACCTG ATTTCTTAGAAA + +4 swissregulon__hs__GZF1.p2-Sry-delta 2 0.87965 21510.1 1 6 CACCTG TGCGCTTCTATA + +4 taipale_cyt_meth__ELK3_NTCGTAAATGCN_eDBD-Ets96B 4 0.87965 21510.1 1 6 CACCTG CTCGTAAATGCA + +4 taipale_cyt_meth__ELK4_NTCGTAAATGMN_FL-Ets96B 4 0.87965 21510.1 1 6 CACCTG GTCGTAAATGCA + +4 transfac_pro__M06067 2 0.87965 21510.1 1 6 CACCTG TAATCCTAAAGC + +4 transfac_pro__M06254 2 0.87965 21510.1 1 6 CACCTG CGCTACTGGCGC + +4 cisbp__M2558-ftz 6 0.87965 21510.1 1 6 CACCTG CTTAATTGCTTT - +4 homer__CGGAAGTGAAAC_PU.1-IRF-CG9650-MTA1-like-Stat92E-ebi-nej-sv 4 0.87965 21510.1 1 6 CACCTG GTTTCACTTCCG - +4 transfac_pro__M05082 3 0.87965 21510.1 1 6 CACCTG CCAGACGTTTGT - +4 transfac_pro__M05412 4 0.87965 21510.1 1 6 CACCTG CCCCACCCCGCA - +4 transfac_pro__M05418 6 0.87965 21510.1 1 6 CACCTG TCCGGCCCCCAG - +4 transfac_pro__M06392 6 0.87965 21510.1 1 6 CACCTG TATGTTTGCCCG - +4 transfac_pro__M07933-btd-hkb-Spps 4 0.87965 21510.1 1 6 CACCTG CTCACGCCCCCC - +4 hocomoco__FOSL2_HUMAN.H11MO.0.A-CoRest-Jra-Myc-Stat92E-bon-kay-mor-nej-pan 7 0.87965 21510.1 1 5 CACCTG GATGACTCATCC + +4 hocomoco__MEF2D_HUMAN.H11MO.0.A-Mef2-rump -1 0.87965 21510.1 1 5 CACCTG TGCTATTTTTAG + +4 taipale_cyt_meth__FOXC2_NYAAAYAAACAN_eDBD_repr-croc-fd59A 7 0.87965 21510.1 1 5 CACCTG GTAAACAAACAC + +4 taipale_cyt_meth__ZBED1_NTRTCGCGAYAT_eDBD-CG13775 7 0.87965 21510.1 1 5 CACCTG CTATCGCGACAT + +4 tiffin__TIFDMEM0000037 -1 0.87965 21510.1 1 5 CACCTG AGCATTCGATTT + +4 transfac_pro__M06788 -1 0.87965 21510.1 1 5 CACCTG AGCGGAAACAAA + +4 transfac_pro__M07885-Dif-dl-Rel 7 0.87965 21510.1 1 5 CACCTG TGGGAATTCCCA + +4 transfac_pro__M05642 7 0.87965 21510.1 1 5 CACCTG TCTATCCGACGC - +4 transfac_pro__M05780 7 0.87965 21510.1 1 5 CACCTG TCTCTTGCACAG - +4 transfac_pro__M05891 7 0.87965 21510.1 1 5 CACCTG TATTCTGCCCCG - +4 transfac_pro__M05989-CG3407 7 0.87965 21510.1 1 5 CACCTG TCTAAAGGCCCA - +4 transfac_pro__M06215 7 0.87965 21510.1 1 5 CACCTG TCCCTTGGACAC - +4 transfac_pro__M06598 7 0.87965 21510.1 1 5 CACCTG TTTCCCATCCCA - +4 transfac_pro__M06743 7 0.87965 21510.1 1 5 CACCTG TCGTCTTAACAG - +4 transfac_pro__M06959 -1 0.87965 21510.1 1 5 CACCTG ACCAATAATGGG - +4 transfac_pro__M06734 -2 0.87965 21510.1 1 4 CACCTG CCTAAGGGGATA + +4 bergman__shn-ZFP1-shn 8 0.87965 21510.1 1 4 CACCTG GGGAACGTTCCC - +4 cisbp__M6026-Abd-B-cad 8 0.87965 21510.1 1 4 CACCTG AATTTTACGACC - +4 taipale__Hoxa11_DBD_NGTCGTWAAANN-Abd-B-cad 8 0.87965 21510.1 1 4 CACCTG AATTTTACGACC - +4 transfac_pro__M05866 -2 0.87965 21510.1 1 4 CACCTG TCTGTTGCCCCA - +4 transfac_pro__M06115 -2 0.87965 21510.1 1 4 CACCTG GCTGCCGCCCCA - +4 transfac_public__M00099-al-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-inv-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-unc-4-unpg-zfh2 10 0.880029 21519.3 1 6 CACCTG TTTACTCAATTAACCT + +4 hocomoco__PO2F1_HUMAN.H11MO.0.C-nub-pdm2 5 0.880029 21519.3 1 6 CACCTG TTATTTGCATTCGATT - +4 transfac_pro__M01079 4 0.880029 21519.3 1 6 CACCTG AAACAACCGCTCGGGA - +4 transfac_pro__M01391-ap-Awh-E5-ems-ey-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-toy-unc-4-Vsx1-zfh2 2 0.880029 21519.3 1 6 CACCTG GTCAATTAATTAATCA - +4 transfac_pro__M01729 3 0.880029 21519.3 1 6 CACCTG TTTGGGCTTCCACTAT - +4 transfac_pro__M02868-Hnf4 6 0.880029 21519.3 1 6 CACCTG ATATTGGACTTTGGAC - +4 transfac_public__M00235-ss-tgo 8 0.880029 21519.3 1 6 CACCTG CGGCACGCAACCCTAA - +4 tfdimers__MD00015-E2f1 4 0.880035 21519.5 1 6 CACCTG TTTTTTCCTTTCACTTCCTCTTTTTTTTT + +4 cisbp__M0076-Taf1 0 0.880484 21530.5 1 6 CACCTG CGCCGCCA + +4 cisbp__M0091 0 0.880484 21530.5 1 6 CACCTG TACGCGTC + +4 cisbp__M0169 0 0.880484 21530.5 1 6 CACCTG GACACGCG + +4 cisbp__M0832-Dfd-unpg 1 0.880484 21530.5 1 6 CACCTG TTAATTAT + +4 cisbp__M0932-acj6-al-Antp-ap-Awh-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-ey-HGTX-ind-inv-lab-lbe-lbl-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2- 1 0.880484 21530.5 1 6 CACCTG TTAATTAG + +4 cisbp__M1220-al-Antp-CG32532-CG34367-CG9876-en-HGTX-ind-inv-lms-OdsH-Pph13-repo-Rx-Scr-slou-unc-4-unpg-Vsx1-Vsx2 1 0.880484 21530.5 1 6 CACCTG TTAATTAG + +4 cisbp__M1842 2 0.880484 21530.5 1 6 CACCTG AATAATTG + +4 predrem__nrMotif1990 1 0.880484 21530.5 1 6 CACCTG TGACAATG + +4 predrem__nrMotif2506 0 0.880484 21530.5 1 6 CACCTG CCACTAAA + +4 taipale_cyt_meth__ALX3_CYAATTAN_FL-al-Awh-bsh-C15-CG18599-CG34367-CG4328-CG9876-Dr-E5-ems-en-ey-ind-inv-lab-lbe-Lim3-Lmx1a-OdsH-pb-repo-toy-unc-4-unpg 1 0.880484 21530.5 1 6 CACCTG CTAATTAA + +4 transfac_pro__M08912-al-ap-Awh-CG11085-CG18599-CG32532-CG34367-CG7745-CG9876-Dr-dve-E5-ems-en-ind-inv-lab-Lim3-OdsH-otp-pb-pdm3-repo-ro-Rx-slou-unpg-Vsx2-zfh2 2 0.880484 21530.5 1 6 CACCTG ACTAATTA + +4 yetfasco__YKL020C_670 2 0.880484 21530.5 1 6 CACCTG TTGATTTT + +4 predrem__nrMotif1907 1 0.880484 21530.5 1 6 CACCTG TAGCCAGA - +4 predrem__nrMotif2108 2 0.880484 21530.5 1 6 CACCTG AATCCCTC - +4 taipale_cyt_meth__DLX3_NYAATTAN_eDBD-Antp-bsh-Dll-Dr-en-inv-Lim1-Scr 1 0.880484 21530.5 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DLX4_NYAATTAN_eDBD-bsh-Dll-Dr-Lim1 1 0.880484 21530.5 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__GBX2_NYAATTAN_eDBD-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.880484 21530.5 1 6 CACCTG CTAATTGG - +4 taipale_cyt_meth__HOXC8_NTAATTAN_FL_meth_repr-abd-A-Dfd-Ubx 1 0.880484 21530.5 1 6 CACCTG GTAATTAC - +4 transfac_pro__M00926-cnc-Jra-kay-maf-S-Mef2-mor-Myc-nej-NFAT-pan-Stat92E 2 0.880484 21530.5 1 6 CACCTG ATGACTCA - +4 fantom__motif87_RCGCACWS 3 0.880484 21530.5 1 5 CACCTG ACGCACAC + +4 taipale_cyt_meth__RHOXF2_NTAATCCN_FL_meth-Gsc-oc-Ptx1 3 0.880484 21530.5 1 5 CACCTG CTAATCCC + +4 yetfasco__YGL096W_494-achi-hth-vis 3 0.880484 21530.5 1 5 CACCTG TTTGACAG + +4 cisbp__M4283-achi-hth-vis 3 0.880484 21530.5 1 5 CACCTG TTTGACAG - +4 jaspar__MA0408.1-achi-hth-vis 3 0.880484 21530.5 1 5 CACCTG TTTGACAG - +4 predrem__nrMotif1617 3 0.880484 21530.5 1 5 CACCTG TAACAGCA - +4 predrem__nrMotif2574 -1 0.880484 21530.5 1 5 CACCTG TTCTATCA - +4 swissregulon__sacCer__TOS8-achi-hth-vis 3 0.880484 21530.5 1 5 CACCTG TTTGACAG - +4 transfac_pro__M01645-achi-hth-vis 3 0.880484 21530.5 1 5 CACCTG TTTGACAG - +4 cisbp__M0094 -2 0.880484 21530.5 1 4 CACCTG TCTCGAAG + +4 cisbp__M4795-caup 4 0.880484 21530.5 1 4 CACCTG CAATAACA + +4 elemento__CAATTAGC 4 0.880484 21530.5 1 4 CACCTG CAATTAGC + +4 elemento__TTGATGCC 4 0.880484 21530.5 1 4 CACCTG TTGATGCC + +4 cisbp__M1383 -2 0.880484 21530.5 1 4 CACCTG CCCGCGGC - +4 cisbp__M4943-al-ap-Awh-CG11294-CG32532-CG9876-Dll-E5-ems-en-eve-exex-ftz-hbn-inv-lab-lms-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-unpg-Vsx1-Vsx2-zen2 4 0.880484 21530.5 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__En_Cell_FBgn0000577-Awh-CG9876-CG11294-CG32532-Dll-E5-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-ems-en-eve-exex-ftz-hbn-inv-lab-lms-otp-pb-repo-ro-slou-unpg 4 0.880484 21530.5 1 4 CACCTG TAATTAAC - +4 hdpi__RBM35A-fus 4 0.880484 21530.5 1 4 CACCTG TGCAAAGC - +4 transfac_pro__M01999 4 0.880484 21530.5 1 4 CACCTG GAGCCGCC - +4 cisbp__M1109-HGTX-acj6 -3 0.880484 21530.5 1 3 CACCTG CTAATTAA + +4 cisbp__M2125 -3 0.880484 21530.5 1 3 CACCTG CTCGGCGG + +4 jaspar__MA0927.1-HGTX-acj6 -3 0.880484 21530.5 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__EMX2_YTAATTAN_eDBD-Antp-ap-Awh-CG11294-CG9876-Dfd-Drgx-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-OdsH-pb-ro-Scr-slou-Ubx-Vsx1-Vsx2-zen2 5 0.880484 21530.5 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXA1_NTAATTAN_FL-Antp-bsh-btn-Dfd-E5-ems-eve-exex-lab-Lim3-pb-Scr-slou 5 0.880484 21530.5 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXA5_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-Dfd-Dll-E5-ems-eve-exex-lab-lbl-Lim1-Lim3-pb-Scr-Ubx-zen2 5 0.880484 21530.5 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXA7_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-Dfd-Lim1-Scr-Ubx 5 0.880484 21530.5 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__LHX8_CYAATTAN_FL-al-Awh-C15-E5-ems-en-inv-lab-Lim3-pb-unpg 5 0.880484 21530.5 1 3 CACCTG CTAATTAG + +4 cisbp__M1254 -3 0.880484 21530.5 1 3 CACCTG CTGGCCAT - +4 jaspar__MA0320.1 -3 0.880484 21530.5 1 3 CACCTG CTCGGCGG - +4 taipale_cyt_meth__EVX1_NYAATTAN_eDBD-Antp-E5-ems-en-eve-exex-inv-lab-pb-Scr-slou-Vsx1-Vsx2 5 0.880484 21530.5 1 3 CACCTG CTAATTAG - +4 taipale_cyt_meth__EVX2_NYAATTAN_eDBD-Antp-Awh-btn-E5-ems-en-eve-exex-ind-inv-lab-Lim3-pb-Scr-slou-Vsx1-Vsx2 5 0.880484 21530.5 1 3 CACCTG CTAATTAG - +4 taipale_cyt_meth__HOXA1_NTAATTAN_FL_meth-Antp-Awh-bsh-btn-Dfd-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-pb-Scr-slou-zen2 5 0.880484 21530.5 1 3 CACCTG GTAATTAC - +4 taipale_cyt_meth__HOXA2_NTMATTAN_FL-Antp-btn-E5-ems-en-eve-exex-ind-inv-lab-Lim3-pb-Scr-slou-Ubx-Vsx1-Vsx2-zen-zen2 5 0.880484 21530.5 1 3 CACCTG CTAATTAC - +4 taipale_cyt_meth__HOXA2_NTMATTAN_FL_meth-Antp-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-pb-Scr-slou-Ubx-Vsx1-Vsx2-zen-zen2 5 0.880484 21530.5 1 3 CACCTG CTAATTAC - +4 transfac_pro__M01684 -3 0.880484 21530.5 1 3 CACCTG CTCGGCGG - +4 taipale_cyt_meth__GFI1B_NMAATCACNGCANNNCACTMN_eDBD_repr-sens-2 15 0.881215 21548.3 1 6 CACCTG TAAATCACTGCACCTCACTCC + +4 taipale_cyt_meth__RUNX3_NWAACCACRNNNACCACRAAN_FL_meth-lz-run-RunxA-RunxB 2 0.881215 21548.3 1 6 CACCTG CAAACCACAAAAACCACGAAA + +4 tfdimers__MD00156 15 0.881215 21548.3 1 6 CACCTG TTAATTTAATTTAATTTAATT + +4 transfac_pro__M01512 3 0.881215 21548.3 1 6 CACCTG TCAGACGTGCGGATATGGATC + +4 cisbp__M4401 3 0.881215 21548.3 1 6 CACCTG TCAGACGTGCGGATATGGATC - +4 cisbp__M4547-aop-Stat92E 5 0.881215 21548.3 1 6 CACCTG CCCATTTCCCGGAAATCCCAT - +4 cisbp__M5608-cic-cnc-kay-maf-S-nej-tj 3 0.881215 21548.3 1 6 CACCTG AATATGCTGACTCAGCAATTT - +4 jaspar__MA0377.1 5 0.881215 21548.3 1 6 CACCTG TTTTATTTCTTCTATTCTCTA - +4 tfdimers__MD00280-E2f1-oc 12 0.881215 21548.3 1 6 CACCTG ATTTTCCTTTCTAATCCTTTA - +4 transfac_pro__M05270 15 0.881215 21548.3 1 6 CACCTG GGGCGGCGGCAGGACCACCCC - +4 transfac_public__M00097-ey-Poxm-sv-toy 9 0.881215 21548.3 1 6 CACCTG GTGAACTCATGCGTGAAAATT - +4 transfac_pro__M05230 17 0.881215 21548.3 1 4 CACCTG CGCAGACCGCGGGAACCAACC - +4 jaspar__MA0051.1-Blimp-1 9 0.881416 21553.3 1 6 CACCTG GGAAAGCGAAACCAAAAC + +4 taipale_cyt_meth__PAX4_NTYACGCWTSANYGNNYN_eDBD-ey-Poxm-sv-toy 2 0.881416 21553.3 1 6 CACCTG TTCACGCATGAATGCACA + +4 cisbp__M3480 2 0.881416 21553.3 1 6 CACCTG CCAACTTTCGATTTCCTA - +4 cisbp__M5591-btd-cbt-dar1-Klf15-luna-Sp1-Spps 8 0.881416 21553.3 1 6 CACCTG ATGCCACGCCCCTTTTTG - +4 hocomoco__PITX3_HUMAN.H11MO.0.D-Ptx1 4 0.881416 21553.3 1 6 CACCTG TTAATCCCTTAATCCCCC - +4 transfac_pro__M06550 13 0.881416 21553.3 1 5 CACCTG GTCCTCTTAAAATTACCC - +4 yetfasco__YOL089C_799 -1 0.881416 21553.3 1 5 CACCTG TCCGAAAAAAAAAGCGGA - +4 transfac_public__M00201 14 0.881416 21553.3 1 4 CACCTG TGTGCATTGCCTAATACT - +4 taipale_tf_pairs__POU2F1_FOXO6_RMATATKCNNNNNNNNNNNNNRWMAACA_CAP_repr-foxo-nub-pdm2 4 0.881992 21567.3 1 6 CACCTG TGTTTACTGTATATATTCGTGCATATTC - +4 tfdimers__MD00247 17 0.881992 21567.3 1 6 CACCTG TTTAGTTAATTTTTTATTACCTAATTTT - +4 cisbp__M2057-CG32532-CG34367-Dr-en-lms-OdsH-repo-slou-unc-4-unpg 1 0.882014 21567.9 1 6 CACCTG TTAATTG + +4 cisbp__M5161-abd-A-al-Antp-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-ey-ftz-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-pdm3-PHDP 1 0.882014 21567.9 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Pph13_SOLEXA_FBgn0023489-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-ems-en-eve 1 0.882014 21567.9 1 6 CACCTG TTAATTA + +4 jaspar__MA0250.1-CG32532-CG34367-Dr-OdsH-en-lms-repo-slou-unc-4-unpg 1 0.882014 21567.9 1 6 CACCTG TTAATTG + +4 predrem__nrMotif1437 0 0.882014 21567.9 1 6 CACCTG TCTCTTA + +4 cisbp__M6279 1 0.882014 21567.9 1 6 CACCTG GTATTTT - +4 predrem__nrMotif1876 1 0.882014 21567.9 1 6 CACCTG GCAGCAT - +4 predrem__nrMotif2648 -1 0.882014 21567.9 1 5 CACCTG ACTCTAA + +4 transfac_pro__M01940 -1 0.882014 21567.9 1 5 CACCTG CCCCGAG + +4 jaspar__MA0362.1 -1 0.882014 21567.9 1 5 CACCTG CCCCGAG - +4 predrem__nrMotif1520 -1 0.882014 21567.9 1 5 CACCTG ACTAAAT - +4 predrem__nrMotif1130 -2 0.882014 21567.9 1 4 CACCTG CATTGCA + +4 predrem__nrMotif427 -2 0.882014 21567.9 1 4 CACCTG CATTCAA - +4 cisbp__M4486-nub-pdm2-vvl 5 0.88271 21584.9 1 6 CACCTG ATATGCAAATGAG - +4 cisbp__M6271-Sidpn 4 0.88271 21584.9 1 6 CACCTG CCGCCACGAGCCC - +4 neph__UW.Motif.0561 2 0.88271 21584.9 1 6 CACCTG TTTTTTTGAAACA - +4 taipale_cyt_meth__EGR3_NMCGCCCACGCAN_FL-klu-sr 1 0.88271 21584.9 1 6 CACCTG GTGCGTGGGCGTG - +4 transfac_pro__M03793 1 0.88271 21584.9 1 6 CACCTG TTCGCTTTCCCTT - +4 transfac_public__M00196-btd-CG3065-CG42741-CTCF-dar1-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 2 0.88271 21584.9 1 6 CACCTG GGCCCCGCCCCCC - +4 hocomoco__NFE2_HUMAN.H11MO.0.A-Jra-cnc-kay-maf-S -1 0.88271 21584.9 1 5 CACCTG TGCTGAGTCATGC - +4 scertf__spivak.SIP4 8 0.88271 21584.9 1 5 CACCTG TTCCATTCAACCG - +4 swissregulon__hs__ZFP161.p2 8 0.88271 21584.9 1 5 CACCTG GTGCGCGCCCCCG - +4 taipale_cyt_meth__POU3F1_NTATGCWAATKAG_eDBD_meth-Dll-dve-nub-pdm2-pdm3-vvl -3 0.88271 21584.9 1 3 CACCTG CTCATTTGCATAA - +4 cisbp__M2979-cnc-Jra-kay 9 0.882713 21585 1 6 CACCTG AGCATGACTCATCGT + +4 cisbp__M4541-cnc-Jra-kay-Mef2-Myc-nej-Stat92E 8 0.882713 21585 1 6 CACCTG TGATGACTCATTCTT + +4 cisbp__M6412 2 0.882713 21585 1 6 CACCTG CCCATCAATCAAATT + +4 flyfactorsurvey__Sqz_SOLEXA_F1-3-FoxP-brm-dati-jim-rn-sqz 9 0.882713 21585 1 6 CACCTG TTTTTTTTGCTTTGT + +4 transfac_pro__M05580 9 0.882713 21585 1 6 CACCTG TGAAGACGGTAACGG + +4 transfac_pro__M09261 4 0.882713 21585 1 6 CACCTG AGCGTATTTTACGCT + +4 cisbp__M4482-CG10431-lid-pho-phol-RpII215-Taf1-Taf7 8 0.882713 21585 1 6 CACCTG GCGGCCGCCATCTTG - +4 cisbp__M4836-dati-FoxP-sqz 9 0.882713 21585 1 6 CACCTG GGTTTTTTTTTTTTT - +4 cisbp__M5858-Ets98B 9 0.882713 21585 1 6 CACCTG ATAATCCGGGACCAC - +4 factorbook__UA14 9 0.882713 21585 1 6 CACCTG CTCGGCGCTCGGCTG - +4 flyfactorsurvey__CG2052_SOLEXA_2.5_FBgn0039905-FoxP-dati-sqz 9 0.882713 21585 1 6 CACCTG GGTTTTTTTTTTTTT - +4 flyfactorsurvey__lola-PD_SOLEXA_FBgn0005630-lola 0 0.882713 21585 1 6 CACCTG CCCCAGCCCCCCACC - +4 hocomoco__KLF9_HUMAN.H11MO.0.C-CG3065-CG42741-Klf15-Nf-YA-Nf-YB-Sp1-Spps-btd-cbt-dar1-kay-luna 8 0.882713 21585 1 6 CACCTG GGCCACGCCCCCTCC - +4 swissregulon__hs__HES1.p2-Max-Myc-Sidpn 5 0.882713 21585 1 6 CACCTG CGGGCCACGCGGCCT - +4 taipale__HSFY2_DBD_TTCGAANNNTTCGAA_repr 3 0.882713 21585 1 6 CACCTG TTCGAACGTTTCGAA - +4 taipale_cyt_meth__MAFF_NYGCTGASTCAGCRN_FL_meth-cnc-maf-S-tj 9 0.882713 21585 1 6 CACCTG ATGCTGACTCAGCAT - +4 transfac_pro__M06870 8 0.882713 21585 1 6 CACCTG GGATTGGATTCCTCG - +4 transfac_pro__M09093 0 0.882713 21585 1 6 CACCTG CCTTTGCCGACAAAA - +4 taipale_cyt_meth__ZNF821_NRGACRGACRGACRN_FL_meth_repr-peb 10 0.882713 21585 1 5 CACCTG AGGACAGACGGACGG + +4 transfac_pro__M06950-sima 10 0.882713 21585 1 5 CACCTG TAAATTTCATATCCT + +4 taipale_cyt_meth__KLF11_NMCACGCCCNNNNCACGCCCMC_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps-sr 4 0.883156 21595.8 1 6 CACCTG GCCACGCCCCCGCCACGCCCAC + +4 tfdimers__MD00061-E2f1 3 0.883156 21595.8 1 6 CACCTG TTTTTCGTTTCTGTTCTTTTTT + +4 tfdimers__MD00489 1 0.883156 21595.8 1 6 CACCTG ATAATTCTGTTCCTCTTTTTTT + +4 transfac_pro__M04646-jumu 1 0.883156 21595.8 1 6 CACCTG GGAACCGACGCGTCCAGTGTCG + +4 tfdimers__MD00184-pan-Ptx1 12 0.88349 21604 1 6 CACCTG TTATTTCTAATCCTCTTTGATGTTTTT + +4 tfdimers__MD00452-E2f1 5 0.88349 21604 1 6 CACCTG TTTTTTTTCTAATCCCTTTCTCTTTTA + +4 stark__AATNNNNNNNAAAA 3 0.883668 21608.3 1 6 CACCTG AATAAAAAAAAAAA + +4 taipale__ATF7_DBD_NNATGACGTCATNN_repr-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 4 0.883668 21608.3 1 6 CACCTG CGATGACGTCATCG + +4 transfac_pro__M00337 4 0.883668 21608.3 1 6 CACCTG TGGCTTCCACTATT + +4 transfac_pro__M01868 2 0.883668 21608.3 1 6 CACCTG CAAAATTGCATAAC + +4 jaspar__MA0263.1 1 0.883668 21608.3 1 6 CACCTG TTAACGAAGCCAAT - +4 transfac_pro__M08874-Dp-E2f1-E2f2 6 0.883668 21608.3 1 6 CACCTG TTTTCGCGCCCGCG - +4 transfac_pro__M04694-E2f1-ewg -1 0.883668 21608.3 1 5 CACCTG CACTGCGCATGCGC + +4 swissregulon__sacCer__RLM1-Mef2 9 0.883668 21608.3 1 5 CACCTG TTTTAAACTTTGCT - +4 bergman__prd-HD-ey-eyg-gsb-gsb-n-prd-toe 10 0.883668 21608.3 1 4 CACCTG GATAATCGATTATC - +4 transfac_pro__M05185 10 0.883668 21608.3 1 4 CACCTG GGGCACGACTTACG - +4 tfdimers__MD00456-E2f1-ovo 12 0.884395 21626.1 1 6 CACCTG AAAAAAGGAAACCCCCACAATCA - +4 transfac_pro__M04643-CHES-1-like-jumu 17 0.884395 21626.1 1 6 CACCTG CTTAGTATAGCGTCGATCCGTTT - +4 cisbp__M0296-Jra-kay 4 0.884398 21626.2 1 6 CACCTG TGATGACGCAA + +4 cisbp__M5714-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-otp-repo-Traf4-unc-4 1 0.884398 21626.2 1 6 CACCTG TAATTTAATTA + +4 jaspar__MA0476.1-CoRest-GATAe-Jra-Mef2-Myc-Stat92E-bon-grn-kay-nej-pnr 5 0.884398 21626.2 1 6 CACCTG TGTGACTCATT + +4 stark__YAATTWNRYGC 0 0.884398 21626.2 1 6 CACCTG CAATTAAACGC + +4 taipale__PHOX2A_DBD_TAATYYAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-otp-repo-Traf4-unc-4 1 0.884398 21626.2 1 6 CACCTG TAATTTAATTA + +4 taipale__YY2_full_NCCGCCATNNT-pho-phol 5 0.884398 21626.2 1 6 CACCTG ACCGCCATTTT + +4 taipale_cyt_meth__KLF12_NRCCACGCCCW_FL_meth_repr-btd-CG3065-CG42741-dar1-luna-Sp1-Spps 5 0.884398 21626.2 1 6 CACCTG GGCCACGCCCA + +4 transfac_pro__M05525-CG30020 4 0.884398 21626.2 1 6 CACCTG TGGGCCCCCGA + +4 transfac_pro__M07814-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-ems-hbn-ind-OdsH-Optix-repo-ro-Rx-Traf4-unc-4 1 0.884398 21626.2 1 6 CACCTG TAATCTAATTA + +4 transfac_pro__M07976-al-CG11294-CG32532-CG9876-Drgx-en-inv-OdsH-Optix-repo-Traf4-unc-4 0 0.884398 21626.2 1 6 CACCTG TAATTGCATTA + +4 cisbp__M5520-Hmx-NK7.1 2 0.884398 21626.2 1 6 CACCTG AGCAATTAACA - +4 cisbp__M5751-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 0 0.884398 21626.2 1 6 CACCTG TAATTAAATTA - +4 predrem__nrMotif1136-CG42741-ERR-Spps-btd 5 0.884398 21626.2 1 6 CACCTG CCCGGCCCCGG - +4 taipale__PROP1_DBD_TAATYNAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 0 0.884398 21626.2 1 6 CACCTG TAATTAAATTA - +4 taipale_cyt_meth__LMX1B_NWWYTAATTAN_eDBD-CG11294-CG4328-Lmx1a-otp-repo-unpg-Vsx1 5 0.884398 21626.2 1 6 CACCTG TTAATTAAAAT - +4 taipale_cyt_meth__LMX1B_NWWYTAATTAN_eDBD_meth-CG11294-CG4328-en-Lim3-Lmx1a-otp-repo-unpg 5 0.884398 21626.2 1 6 CACCTG TTAATTAAAAT - +4 transfac_pro__M07311-Stat92E 1 0.884398 21626.2 1 6 CACCTG ATTTCTGAGAA - +4 cisbp__M2267-Abd-B-cad-eve 6 0.884398 21626.2 1 5 CACCTG TTTTATGGCTT + +4 factorbook__BARHL2-Antp-B-H1-B-H2-Scr-lms-unpg -1 0.884398 21626.2 1 5 CACCTG TCTTAATTGCT + +4 jaspar__MA0536.1-BEAF-32-pnr -1 0.884398 21626.2 1 5 CACCTG AACTATCGATA - +4 hocomoco__HXC11_HUMAN.H11MO.0.D-Abd-B 7 0.884398 21626.2 1 4 CACCTG TTTTTACGACC + +4 taipale_cyt_meth__HOXA11_NRTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.884398 21626.2 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC11_NRTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.884398 21626.2 1 4 CACCTG GTTTTACGACC - +4 scertf__spivak.RLM1-Mef2 -3 0.884398 21626.2 1 3 CACCTG CTATTTATAGA - +4 tfdimers__MD00024-foxo 18 0.884509 21628.9 1 6 CACCTG TAATTTTTGTTAATAATTAACAAAAA + +4 cisbp__M1002-abd-A-Antp-ap-Awh-btn-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-gsb-gsb-n-HGTX-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-otp-pb-Pph13-prd-ro-Rx-Scr-slou-Ubx-u 1 0.885373 21650 1 6 CACCTG TTAATTACC + +4 cisbp__M1234-al-ap-Awh-CG18599-CG34367-E5-ems-hbn-ind-Lim3-OdsH-otp-Pph13-repo-unc-4-Vsx2-zfh2 1 0.885373 21650 1 6 CACCTG TTAATTAGG + +4 cisbp__M6269 1 0.885373 21650 1 6 CACCTG ACTCATTGA + +4 predrem__nrMotif1158 0 0.885373 21650 1 6 CACCTG AATTTGTGT + +4 cisbp__M1163-Dll-en-HGTX-lab-Lim1 0 0.885373 21650 1 6 CACCTG GTAATTAAT - +4 idmmpmm__srp-srp 3 0.885373 21650 1 6 CACCTG TCTTATCGC - +4 predrem__nrMotif1499 3 0.885373 21650 1 6 CACCTG GCCCACGCC - +4 swissregulon__sacCer__AZF1-CG17328 0 0.885373 21650 1 6 CACCTG TTTCTTTTT - +4 transfac_pro__M04765-gsb-gsb-n-Poxm-prd-sv 1 0.885373 21650 1 6 CACCTG AAGCGTGAC - +4 yetfasco__YOR113W_499-CG17328 0 0.885373 21650 1 6 CACCTG TTTCTTTTT - +4 transfac_public__M00486-sv 4 0.885373 21650 1 5 CACCTG AATAAACTC + +4 hdpi__EDN1 -1 0.885373 21650 1 5 CACCTG AATTGATTT - +4 predrem__nrMotif561 4 0.885373 21650 1 5 CACCTG ACTCTGCCC - +4 transfac_pro__M05586 4 0.885373 21650 1 5 CACCTG CAATCACAC - +4 fantom__motif69_RYKNAAATC 5 0.885373 21650 1 4 CACCTG ACGAAAATC + +4 flyfactorsurvey__lola-PC_SANGER_5_FBgn0005630-lola 5 0.885373 21650 1 4 CACCTG GAATTTTCC - +4 predrem__nrMotif176 5 0.885373 21650 1 4 CACCTG ATGAGCAGA - +4 predrem__nrMotif232 5 0.885373 21650 1 4 CACCTG CAGAGAACT - +4 predrem__nrMotif728 5 0.885373 21650 1 4 CACCTG TGAGTCCCT - +4 transfac_pro__M03866-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr -3 0.885373 21650 1 3 CACCTG ATGAGTCAC - +4 taipale_tf_pairs__ETV2_DLX3_RSCGGAANNNNNNYAATTA_CAP-pnt 4 0.885876 21662.3 1 6 CACCTG TAATTACCTCGCTTCCGGT - +4 transfac_pro__M06898 -2 0.885876 21662.3 1 4 CACCTG ACTGCGGCACGGGGTTGGG + +4 cisbp__M0044 2 0.886435 21676 1 6 CACCTG TCCGCCGCCA + +4 cisbp__M0884 1 0.886435 21676 1 6 CACCTG ATTGTACAAT + +4 cisbp__M1519-NFAT 3 0.886435 21676 1 6 CACCTG ATTTTCCATT + +4 cisbp__M6020-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-eve-ftz-hbn-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-slou-Ubx-unc-4-unpg-Vsx2-zfh2 2 0.886435 21676 1 6 CACCTG GTTAATTGGT + +4 predrem__nrMotif1365 0 0.886435 21676 1 6 CACCTG TTCTTGTTCT + +4 taipale__ZNF740_DBD_NCCCCCCCAC-l(3)neo38 4 0.886435 21676 1 6 CACCTG CCCCCCCCAC + +4 taipale_cyt_meth__NEUROG1_RNCATATGNY_eDBD_meth-amos-ato-dimm-Fer3-HLH54F-Oli-tap 0 0.886435 21676 1 6 CACCTG GACATATGTC + +4 transfac_pro__M05109 4 0.886435 21676 1 6 CACCTG ATGCCGCCGG + +4 cisbp__M5977-l(3)neo38 4 0.886435 21676 1 6 CACCTG CCCCCCCCAC - +4 homer__AWTGATAAGA_ELT-3 3 0.886435 21676 1 6 CACCTG TCTTATCATT - +4 jaspar__MA0443.1-Klf15-Sp1-Spps-btd 4 0.886435 21676 1 6 CACCTG TCCGCCCCCT - +4 transfac_pro__M01896-Myc-nej 3 0.886435 21676 1 6 CACCTG GATTGCACAA - +4 transfac_pro__M07354-klu-sr 1 0.886435 21676 1 6 CACCTG CCGCCCCCGC - +4 cisbp__M1072-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-Dr-E5-ems-eve-exex-ftz-HGTX-ind-lab-pb-Scr-slou-tup-Ubx-unpg-zen2 5 0.886435 21676 1 5 CACCTG TTAATGACCT + +4 homer__CCCATTGTTC_Sox2-D-Sox14-Sox100B-Sox102F-SoxN -1 0.886435 21676 1 5 CACCTG CCCATTGTTC + +4 predrem__nrMotif542 5 0.886435 21676 1 5 CACCTG AAAAAGTCCA + +4 transfac_pro__M03194 5 0.886435 21676 1 5 CACCTG ACGCCGCCCG + +4 flyfactorsurvey__en_SOLEXA_2_FBgn0000577-Awh-C15-CG9876-CG11294-CG32532-CG34367-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-en-inv-lab-lms-otp-repo-ro-slou-unc-4-unpg 5 0.886435 21676 1 5 CACCTG CTAATTAAGA - +4 predrem__nrMotif1078 -1 0.886435 21676 1 5 CACCTG TGCTTTATTT - +4 transfac_pro__M01670 5 0.886435 21676 1 5 CACCTG TTATTTAATT - +4 transfac_public__M00510-CG32532-CG4328-Lim1-Lim3-Lmx1a-OdsH-otp-repo-unc-4-vvl 5 0.886435 21676 1 5 CACCTG TTAATTAATT - +4 cisbp__M5661-NfI 6 0.886435 21676 1 4 CACCTG ACTTGGCACC + +4 cisbp__M6006-abd-A-ap-Awh-CG11085-CG18599-CG9876-E5-ems-en-eve-exex-ind-inv-lab-Lim3-OdsH-otp-pb-ro-slou-Ubx-unpg-Vsx1-Vsx2-zen2-zfh2 6 0.886435 21676 1 4 CACCTG GCTAATTAGC + +4 homer__ATGACTCATC_AP-1-CoRest-Jra-Mef2-Myc-Stat92E-bon-cnc-ewg-foxo-kay-maf-S-mor-nej-pan 6 0.886435 21676 1 4 CACCTG ATGACTCATC + +4 homer__CCWTTGTYYB_Sox10-Sox14-Sox102F-SoxN -2 0.886435 21676 1 4 CACCTG CCTTTGTTCG + +4 taipale__GBX1_DBD_NNYAATTANN-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zfh2 6 0.886435 21676 1 4 CACCTG ACTAATTAGC + +4 taipale__MIXL1_full_NNYAATTANN-al-ap-Awh-C15-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-E5-ems-en-hbn-inv-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-Traf4-unc-4-unpg-Vsx1-Vsx2 6 0.886435 21676 1 4 CACCTG TCTAATTAAC + +4 transfac_pro__M08942-bon-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 6 0.886435 21676 1 4 CACCTG ATGAGTCATC + +4 cisbp__M4684-bon-cnc-Jra-kay-Mef2-Myc-nej-pan 6 0.886435 21676 1 4 CACCTG ATGAGTCATC - +4 cisbp__M5631-al-ap-Awh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-E5-ems-en-hbn-inv-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-Traf4-tup-unc-4-unpg-Vsx1-Vsx2 6 0.886435 21676 1 4 CACCTG TCTAATTAAC - +4 jaspar__MA0670.1-NfI 6 0.886435 21676 1 4 CACCTG ACTTGGCACC - +4 taipale__En2_DBD_NNYAATTANN-abd-A-ap-Awh-CG11085-CG18599-CG9876-E5-ems-en-eve-exex-ind-inv-lab-Lim3-OdsH-otp-pb-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2-zfh2 6 0.886435 21676 1 4 CACCTG GCTAATTAGC - +4 transfac_pro__M02024-Mef2-rump 6 0.886435 21676 1 4 CACCTG TATTTTTAGC - +4 transfac_pro__M07488-lab 6 0.886435 21676 1 4 CACCTG TACAATTAAA - +4 transfac_pro__M08920-bon-cnc-CoRest-foxo-Jra-kay-Mef2-Myc-pan-Stat92E 6 0.886435 21676 1 4 CACCTG ATGAGTCATC - +4 swissregulon__hs__MEF2_A_B_C_D_.p2-Mef2-rump -3 0.886435 21676 1 3 CACCTG CTAAAAATAG - +4 cisbp__M4509-CG9650-Mad-nej-nub-pan-pdm2-SoxN 3 0.886643 21681.1 1 6 CACCTG ATTTGCATAACAAAGGA + +4 cisbp__M6309-Stat92E 9 0.886643 21681.1 1 6 CACCTG GGAAAGCGAAACTGAAA + +4 taipale__ZNF410_DBD_NNCATCCCATAATANTC_repr 0 0.886643 21681.1 1 6 CACCTG TCCATCCCATAATACTC + +4 transfac_pro__M01339-al-Antp-ap-Awh-CG34367-Dfd-E5-gsb-gsb-n-Lim3-OdsH-otp-pdm3-Pph13-prd-repo-Rx-Scr-unc-4-unpg-zfh2 1 0.886643 21681.1 1 6 CACCTG CGACCTAATTAGTACTA + +4 taipale__MEOX2_DBD_NTAATTANNNTAATTAN-Antp-btn-dve-lab-Lim3-Scr 5 0.886643 21681.1 1 6 CACCTG GTAATTACCGTAATTAA - +4 taipale_cyt_meth__POU3F1_NAATTANNNNNTAATTN_eDBD-OdsH-vvl 4 0.886643 21681.1 1 6 CACCTG TAATTAGCCGCTAATTA - +4 transfac_pro__M01458-abd-A-al-Antp-Awh-CG11294-CG18599-CG34367-CG4328-Dfd-Lim1-Lim3-Lmx1a-OdsH-otp-repo-Scr-Ubx-unc-4-zfh2 0 0.886643 21681.1 1 6 CACCTG CGCGTTAATTAATTATG - +4 transfac_pro__M02833 8 0.886643 21681.1 1 6 CACCTG ATAGTGAGCACTGTTCG - +4 transfac_pro__M05394 8 0.886643 21681.1 1 6 CACCTG GCGGTCCGGACCACGAA - +4 transfac_pro__M05355-fd59A 13 0.886643 21681.1 1 4 CACCTG TTAAATTGTCTTTAACT - +4 tfdimers__MD00010 6 0.889231 21744.4 1 6 CACCTG ATAAAGGGCATGTCTAGACATGCCCTTTAT + +4 dbcorrdb__CBX3__ENCSR000BRT_1__m7-HP1b-HP1c-HP1e-Su(var)205 9 0.889369 21747.8 1 6 CACCTG AAGAGCACTCATCCACAACA + +4 dbcorrdb__EP300__ENCSR000EGY_1__m1-CTCF-nej 0 0.889369 21747.8 1 6 CACCTG TAAATATTAATAAAAAATTT + +4 dbcorrdb__GABPA__ENCSR000BLO_1__m1-aop-Atac3-brm-bs-CrebB-Dif-dl-E2f1-E2f2-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-FoxP-Hcf-Hr78-lid-Max-Myc-pnt-Rbbp5-RpII215-Sin3A-Spt20-SREBP-Taf1-tna 14 0.889369 21747.8 1 6 CACCTG GCCGCCACTTCCGGCCCCGG + +4 dbcorrdb__JUND__ENCSR000BKP_1__m1-cnc-CoRest-Jra-kay-maf-S-Mef2-mor-pan 11 0.889369 21747.8 1 6 CACCTG CCGCGCTGAGTCATCCCCCC + +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m5 5 0.889369 21747.8 1 6 CACCTG AGCTACAGCACAGAAACATA + +4 dbcorrdb__MEF2A__ENCSR000BNV_1__m1-Mef2-rump 12 0.889369 21747.8 1 6 CACCTG TGCTATTTTTAGCACTTGAT + +4 dbcorrdb__NFATC1__ENCSR000BQL_1__m2-NFAT 10 0.889369 21747.8 1 6 CACCTG CAGAAATGGAAACTATGACT + +4 dbcorrdb__NFYA__ENCSR000EGR_1__m2-btd-CG42741-dar1-E2f2-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 12 0.889369 21747.8 1 6 CACCTG GGGAGGGGGCGGGGCCTGGG + +4 dbcorrdb__POLR2A__ENCSR000DMZ_1__m2-RpII215 5 0.889369 21747.8 1 6 CACCTG CGCCGTCATTGCGCTTGCGC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BIF_1__m2 14 0.889369 21747.8 1 6 CACCTG TTCCGCCGCGATGTCTTCGG + +4 dbcorrdb__SIN3A__ENCSR000DYX_1__m1-E2f1-E2f2-Sin3A 6 0.889369 21747.8 1 6 CACCTG CTTTCAAATTTCGCGCCACG + +4 dbcorrdb__SP1__ENCSR000BKO_1__m1-btd-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 6 0.889369 21747.8 1 6 CACCTG CGGCCGCCCCGGCCAATCAG + +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m5-SREBP 11 0.889369 21747.8 1 6 CACCTG TTTTTTCCTTGCGCCTTTAG + +4 dbcorrdb__ZNF274__ENCSR000EUK_1__m1-egg 2 0.889369 21747.8 1 6 CACCTG TTCTCCAGTATGAGTTCTCT + +4 transfac_pro__M01579 14 0.889369 21747.8 1 6 CACCTG ATTATGCGGATCCGCGCCTC + +4 cisbp__M6482-Brf-brm-btd-CG3065-CG42741-CoRest-ct-CTCF-dar1-E2f1-ERR-E(z)-HDAC1-kay-Klf15-klu-luna-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-Sp1-Spps-Spt20-sr-SREBP-vtd 0 0.889369 21747.8 1 6 CACCTG CCCCGGCCCCGCCCCCCCCC - +4 dbcorrdb__CTCF__ENCSR000DTW_1__m2-CTCF 13 0.889369 21747.8 1 6 CACCTG CGATGCCCTGCACTGCCCCC - +4 dbcorrdb__E2F4__ENCSR000DYY_1__m2-btd-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 0 0.889369 21747.8 1 6 CACCTG CCTCTGATTGGCCGGCGCCG - +4 dbcorrdb__EZH2__ENCSR000ARI_1__m2-E(z) 1 0.889369 21747.8 1 6 CACCTG CCTTCTTCGGGGCTTCAGCC - +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m1-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 7 0.889369 21747.8 1 6 CACCTG CCGGCGCGGCCTTTATACGG - +4 dbcorrdb__SP1__ENCSR000BHK_1__m1-bs-btd-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 0 0.889369 21747.8 1 6 CACCTG CCTCCGATTGGCCGGGGCGG - +4 dbcorrdb__SP1__ENCSR000BJX_1__m2-btd-kay-Nf-YB-Spps 1 0.889369 21747.8 1 6 CACCTG CCCCCCGGTCATTGGTTACC - +4 dbcorrdb__SPI1__ENCSR000BGQ_1__m1-Blimp-1-CG9650-ebi-MTA1-like-nej-Stat92E-sv 9 0.889369 21747.8 1 6 CACCTG TAGTTTCACTTCCTCTTTTT - +4 dbcorrdb__STAT1__ENCSR000EHJ_1__m1-aop-Stat92E 14 0.889369 21747.8 1 6 CACCTG CATTTCCGGGAAATCACGTG - +4 dbcorrdb__TCF7L2__ENCSR000EXL_1__m2-pan-RpII215 2 0.889369 21747.8 1 6 CACCTG CGCGGCTGTTTGATGGGCCC - +4 dbcorrdb__TRIM28__ENCSR000EUZ_1__m7-bon 6 0.889369 21747.8 1 6 CACCTG CTATGACTCCATTCATTCTG - +4 dbcorrdb__ZNF274__ENCSR000EUI_1__m2-bon-egg 7 0.889369 21747.8 1 6 CACCTG GCTTTCCCACATTCATTACA - +4 dbcorrdb__ZNF384__ENCSR000DYP_1__m4-rn-sqz 1 0.889369 21747.8 1 6 CACCTG TGAGCTTTGATTTTTCCATT - +4 hocomoco__IRF3_HUMAN.H11MO.0.B-Blimp-1-Stat92E 1 0.889369 21747.8 1 6 CACCTG TCACTTTCCCTTTCCCTTTC - +4 taipale_tf_pairs__ERF_HOXA3_RSCGGAWNNNNNNNYMATTA_CAP_repr-Ets21C 4 0.889369 21747.8 1 6 CACCTG TAATGGCCTCTACTTCCGGT - +4 taipale_tf_pairs__ETV2_ONECUT2_RCCGGAANNNNNNATCGATN_CAP_repr-onecut-pnt 10 0.889369 21747.8 1 6 CACCTG AATCGATCTCCACTTCCGGT - +4 transfac_pro__M01247-D-Mad-pan-Sox100B-Sox14-Sox15-SoxN 3 0.889369 21747.8 1 6 CACCTG TGCTTCCTTTGTTTTTTAAA - +4 dbcorrdb__CTCF__ENCSR000AMA_1__m2-CTCF 15 0.889369 21747.8 1 5 CACCTG GGCGGCAGTGCTGGGCACCG + +4 dbcorrdb__ZNF384__ENCSR000EFP_1__m1-brm-CG7839-jim-rn-RpII215-sqz-SREBP-vtd -1 0.889369 21747.8 1 5 CACCTG GTCTCAAAAAAAAAAAAAAA + +4 transfac_pro__M01084-Antp 4 0.889715 21756.2 1 6 CACCTG AATAACCATAAC + +4 cisbp__M0133 4 0.889715 21756.2 1 6 CACCTG AATTAATATTCT - +4 jaspar__MA0095.2-CG10431-Taf1-lid-pho-phol 5 0.889715 21756.2 1 6 CACCTG GCCGCCATCTTG - +4 predrem__nrMotif1196 4 0.889715 21756.2 1 6 CACCTG GGAGAGCCCGGG - +4 transfac_pro__M00341-aop-Atac3-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-pnt 2 0.889715 21756.2 1 6 CACCTG TGCACTTCCGGT - +4 transfac_public__M00020-ftz 6 0.889715 21756.2 1 6 CACCTG CTTAATTGCTTT - +4 transfac_pro__M05835 -1 0.889715 21756.2 1 5 CACCTG GCTTAAAGCCGC + +4 hocomoco__ATF4_MOUSE.H11MO.0.A-nej 7 0.889715 21756.2 1 5 CACCTG ATTGCATCATCC - +4 transfac_pro__M01663 7 0.889715 21756.2 1 5 CACCTG TCCATTCGTCCG - +4 transfac_pro__M05419 7 0.889715 21756.2 1 5 CACCTG GCGTCCGGAACA - +4 transfac_pro__M05851-CG12299-CG31365-dati 7 0.889715 21756.2 1 5 CACCTG TATTCCGGAACA - +4 transfac_pro__M06161 7 0.889715 21756.2 1 5 CACCTG GCGTCCTCCCCG - +4 transfac_pro__M06467 7 0.889715 21756.2 1 5 CACCTG AATGATGAACAG - +4 transfac_pro__M06620 7 0.889715 21756.2 1 5 CACCTG TGTTTTTTCCCA - +4 cisbp__M6163-E(bx) 8 0.889715 21756.2 1 4 CACCTG GAAAACAACAAA - +4 hocomoco__BPTF_HUMAN.H11MO.0.D-E(bx) 8 0.889715 21756.2 1 4 CACCTG GAAAACAACAAA - +4 transfac_pro__M05646 8 0.889715 21756.2 1 4 CACCTG TATAATGGAACG - +4 transfac_pro__M05974 -2 0.889715 21756.2 1 4 CACCTG GCTGCATTCCCA - +4 transfac_pro__M06614 8 0.889715 21756.2 1 4 CACCTG GCGTTTTTAACA - +4 transfac_pro__M07686-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 8 0.889715 21756.2 1 4 CACCTG GATGACGTCATC - +4 stark__TAATTR-C15-CG32532-CG34367-Dll-Drgx-OdsH-Rx-al-en-inv-lbe-repo-slou-unc-4-unpg 0 0.889804 21758.4 1 6 CACCTG TAATTA + +4 cisbp__M1999-bcd-Gsc 1 0.889804 21758.4 1 5 CACCTG TAATCC + +4 hdpi__ABCF2-CG9281 -1 0.889804 21758.4 1 5 CACCTG GCTTTC - +4 hdpi__NFATC4-NFAT 1 0.889804 21758.4 1 5 CACCTG TTTCCA - +4 hdpi__PHLDA2 1 0.889804 21758.4 1 5 CACCTG TTTCCA - +4 transfac_pro__M03803-Sox15 1 0.889804 21758.4 1 5 CACCTG GGACAA - +4 hdpi__MECP2 -2 0.889804 21758.4 1 4 CACCTG CATTAC - +4 hdpi__SCMH1-Scm -2 0.889804 21758.4 1 4 CACCTG CATTTC - +4 cisbp__M4814-CG12236 -3 0.889804 21758.4 1 3 CACCTG CTTCCA - +4 stark__RTAAMA-croc 3 0.889804 21758.4 1 3 CACCTG TGTTAC - +4 hdpi__DUS3L-CG10463 -1 0.890192 21767.9 1 5 CACCTG AGCCA - +4 yetfasco__YER068W_556-Cnot4 0 0.890192 21767.9 1 5 CACCTG TATAT - +4 taipale_cyt_meth__ZIC3_NGACCCCCCGCTGYGM_eDBD-opa 1 0.890531 21776.1 1 6 CACCTG AGACCCCCCGCTGTGA + +4 taipale_tf_pairs__CUX1_HOXA13_NYMRTAAANATYGATN_CAP_repr-ct 0 0.890531 21776.1 1 6 CACCTG CTCATAAAAATCGATC + +4 hocomoco__GSX2_HUMAN.H11MO.0.D-Awh-CG9876-CG18599-CG32532-CG34367-Dll-Dr-E5-HGTX-Hmx-Lim3-OdsH-Pph13-Rx-Vsx1-al-ap-ems-en-ey-ind-lab-lbe-lbl-otp-repo-ro-slou-toy-unc-4-unpg-zen2 5 0.890531 21776.1 1 6 CACCTG ATTAAAAACTAATTAA - +4 swissregulon__hs__NFY_A_B_C_.p2-CG7839-Chd1-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay 0 0.890531 21776.1 1 6 CACCTG CCGCTGATTGGCCGGG - +4 taipale_cyt_meth__ZNF274_NRTRTGAGTTCTCRYN_eDBD_meth_repr 12 0.890531 21776.1 1 4 CACCTG AGCGAGAACTCATACT - +4 cisbp__M0011-Taf1 0 0.890646 21779 1 6 CACCTG CGCCGCCA + +4 cisbp__M1081 2 0.890646 21779 1 6 CACCTG TTAATCAA + +4 cisbp__M3968-Stat92E 2 0.890646 21779 1 6 CACCTG CGGAAATC + +4 predrem__nrMotif1728 0 0.890646 21779 1 6 CACCTG CACTGTTC + +4 taipale__EN1_full_NYAATTAN-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.890646 21779 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__ESX1_YYAATTAN_FL_meth-C15-CG11294-CG32532-Dll-Drgx-E5-ems-eve-exex-ind-Lim3-OdsH-Ubx-unpg-Vsx1-Vsx2 1 0.890646 21779 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__ISX_CTAATTAR_FL_meth-al-Antp-ap-Awh-C15-CG11294-CG32532-CG34367-CG9876-E5-ems-en-ind-inv-lab-lbe-Lim1-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.890646 21779 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__VSX1_CYAATTAN_FL_meth-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-eve-inv-lab-lbe-Lim3-OdsH-pb-repo-slou-unc-4-unpg 1 0.890646 21779 1 6 CACCTG CTAATTAG + +4 cisbp__M0549 2 0.890646 21779 1 6 CACCTG CGCTCCGC - +4 cisbp__M1311 2 0.890646 21779 1 6 CACCTG GTTATCCA - +4 flyfactorsurvey__CG7056_Cell_FBgn0038852-HHEX 0 0.890646 21779 1 6 CACCTG TAATTAAA - +4 predrem__nrMotif1598 0 0.890646 21779 1 6 CACCTG TGCCATCA - +4 taipale_cyt_meth__LHX8_MTCGTTAN_FL_meth-Awh-unpg 2 0.890646 21779 1 6 CACCTG CTAACGAG - +4 taipale_cyt_meth__MSX1_NCAATTAN_eDBD-Antp-B-H1-B-H2-bsh-btn-Dll-Dr-E5-ems-en-exex-inv-lab-Lim1-pb-Rx-Scr-unpg-Vsx1 1 0.890646 21779 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__MSX1_NCAATTAN_eDBD_meth-Antp-B-H1-B-H2-bsh-C15-CG18599-Dfd-Dr-E5-ems-en-exex-inv-Lim1-Lim3-lms-OdsH-pb-Rx-Scr-Ubx-unpg-Vsx1-Vsx2 1 0.890646 21779 1 6 CACCTG CTAATTGC - +4 transfac_pro__M04635-sd 1 0.890646 21779 1 6 CACCTG ATATTTTT - +4 transfac_public__M00496-Stat92E 2 0.890646 21779 1 6 CACCTG CGGAAATC - +4 predrem__nrMotif1290 -1 0.890646 21779 1 5 CACCTG GCTTGTCA + +4 cisbp__M0060 -1 0.890646 21779 1 5 CACCTG GCATGCAA - +4 flyfactorsurvey__Bteb2_SANGER_2.5_FBgn0025679-Klf15-Spps-btd 3 0.890646 21779 1 5 CACCTG ACGCCCCC - +4 cisbp__M0029 4 0.890646 21779 1 4 CACCTG CCGCCGCC + +4 cisbp__M1192 4 0.890646 21779 1 4 CACCTG AATCGATC + +4 hdpi__EWSR1 4 0.890646 21779 1 4 CACCTG TAATGAGC + +4 jaspar__MA0975.1 4 0.890646 21779 1 4 CACCTG CCGCCGCC + +4 jaspar__MA1053.1-Hcf 4 0.890646 21779 1 4 CACCTG GCGCCGCC + +4 predrem__nrMotif2221 -2 0.890646 21779 1 4 CACCTG TCTGCGGG + +4 swissregulon__hs__MAFB.p2 -2 0.890646 21779 1 4 CACCTG GCTGACGC + +4 cisbp__M1508 -2 0.890646 21779 1 4 CACCTG CCCAAAAT - +4 cisbp__M4714 -2 0.890646 21779 1 4 CACCTG TCTTATCA - +4 cisbp__M5170-al-ap-Awh-CG18599-CG9876-E5-ems-en-eve-ind-inv-lab-lbl-OdsH-otp-pb-repo-ro-Rx-unpg 4 0.890646 21779 1 4 CACCTG TAATTAGC - +4 flyfactorsurvey__Ro_Cell_FBgn0003267-Awh-CG9876-CG18599-E5-OdsH-Rx-al-ap-ems-en-eve-ind-inv-lab-lbl-otp-pb-repo-ro-unpg 4 0.890646 21779 1 4 CACCTG TAATTAGC - +4 hdpi__MORG1-CG4935 -2 0.890646 21779 1 4 CACCTG CATTGAAT - +4 cisbp__M1182-abd-A-HGTX-Ubx 5 0.890646 21779 1 3 CACCTG TTAATTAC + +4 taipale_cyt_meth__HOXA5_NYAATTAN_FL_meth-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-pb-Scr-slou-Ubx-unpg-zen-zen2 5 0.890646 21779 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXB8_NYAATTAN_eDBD_meth-abd-A-Abd-B-Antp-Dfd-Scr-Ubx 5 0.890646 21779 1 3 CACCTG GCAATTAA + +4 taipale_cyt_meth__LHX6_CYAATTAN_FL_meth-al-Awh-C15-E5-ems-en-exex-lab-Lim3-pb-slou 5 0.890646 21779 1 3 CACCTG CTAATTAC + +4 cisbp__M0719-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.890646 21779 1 3 CACCTG TTGTTTAC - +4 hdpi__UBE2V1-Uev1A 5 0.890646 21779 1 3 CACCTG CCGCAAAC - +4 jaspar__MA0613.1-FoxK-FoxL1-FoxP-bin-croc-fd19B-fd59A-fd102C-foxo-slp1-slp2 5 0.890646 21779 1 3 CACCTG TTGTTTAC - +4 scertf__macisaac.IME1 -3 0.890646 21779 1 3 CACCTG CTCGGCGG - +4 transfac_pro__M07842-Antp-Dfd-E5-ems-eve-ind-lab-pb-Scr-Ubx-zen-zen2 5 0.890646 21779 1 3 CACCTG CTAATGAC - +4 tfdimers__MD00557 19 0.891436 21798.3 1 6 CACCTG GGGGGGGTGGGGATGTGGTTATCTGGGGG + +4 cisbp__M1883-Blimp-1 9 0.891989 21811.8 1 6 CACCTG GGAAAGCGAAACCAAAAC + +4 taipale__KLF13_full_NNGNNACGCCCMYTTTNN_repr-btd-cbt-dar1-Klf15-luna-Sp1-Spps 8 0.891989 21811.8 1 6 CACCTG ATGCCACGCCCCTTTTTG + +4 taipale__PDX1_DBD_NYAATTARNNNYAATTAN-al-Antp-ap-Awh-B-H1-B-H2-CG11294-CG32532-CG4328-CG9876-Dll-E5-ems-en-eve-ind-lab-Lim1-Lim3-lms-Lmx1a-otp-pb-Pph13-repo-ro-Rx-Scr-slou-unpg-Vsx1-zen2 5 0.891989 21811.8 1 6 CACCTG GTAATTAACGGTAATTAA + +4 cisbp__M2174-Mef2 1 0.891989 21811.8 1 6 CACCTG GGATCTATTTATAGAACC - +4 cisbp__M5712-al-Antp-ap-Awh-B-H1-B-H2-CG11294-CG32532-CG4328-CG9876-Dll-E5-ems-en-eve-ind-lab-Lim3-lms-Lmx1a-otp-pb-Pph13-repo-ro-Rx-Scr-slou-unpg-Vsx1-zen2 5 0.891989 21811.8 1 6 CACCTG GTAATTAACGGTAATTAA - +4 cisbp__M5703-ey-Poxm-sv-toy 14 0.891989 21811.8 1 4 CACCTG GAGCAGTCAAGCGTGACG + +4 tfdimers__MD00140-oc 12 0.892019 21812.5 1 6 CACCTG TTTTATTCACTTAATCTTCTT + +4 transfac_pro__M05080 2 0.892019 21812.5 1 6 CACCTG AGCGACTGTTCTCCGCGTAAC + +4 transfac_pro__M05198 6 0.892019 21812.5 1 6 CACCTG GTGTGGTCCCTGCTGCGCCCC + +4 transfac_pro__M06827 10 0.892019 21812.5 1 6 CACCTG AGGGGCCGGAAACCACCCCGC + +4 cisbp__M1882-Blimp-1-ebi-MTA1-like-nej-Stat92E 3 0.892019 21812.5 1 6 CACCTG TTTTACTTTCACTTTCACTTT - +4 hocomoco__STAT1_MOUSE.H11MO.1.A-Stat92E 8 0.892019 21812.5 1 6 CACCTG GTTTCCATTTCCTAGAAATCA - +4 transfac_pro__M01529 0 0.892019 21812.5 1 6 CACCTG TACATTTCGGATTTAAGCAAA - +4 transfac_pro__M05918 8 0.892019 21812.5 1 6 CACCTG ATGGCTCGGACTTCGACATCC - +4 cisbp__M4846-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-nub-OdsH-otp-pb-pdm2-PHDP-Pp 1 0.892515 21824.7 1 6 CACCTG TTAATTA + +4 cisbp__M4999-E5-hbn 0 0.892515 21824.7 1 6 CACCTG TAATTAA + +4 flyfactorsurvey__CG11294_SOLEXA_FBgn0030058-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-exex-ftz- 1 0.892515 21824.7 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__CG32532_SOLEXA_FBgn0052532-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-em 1 0.892515 21824.7 1 6 CACCTG TTAATTA + +4 hdpi__PRRX1-CG11085-CG18599-CG32532-CG34367-Dr-Rx-Ubx-Vsx1-Vsx2-bsh-en-inv-lab-lms-slou-unpg 0 0.892515 21824.7 1 6 CACCTG TAATTGG + +4 hocomoco__HMGA1_HUMAN.H11MO.0.D 1 0.892515 21824.7 1 6 CACCTG GTATTTT + +4 predrem__nrMotif1183 0 0.892515 21824.7 1 6 CACCTG CACTGAG + +4 cisbp__M0089 0 0.892515 21824.7 1 6 CACCTG GACGCGT - +4 cisbp__M0142 0 0.892515 21824.7 1 6 CACCTG AATTTTT - +4 transfac_pro__M03813-vvl 0 0.892515 21824.7 1 6 CACCTG TGCATTT - +4 flyfactorsurvey__Bcd_SOLEXA_FBgn0000166-Gsc-Ptx1-bcd-oc 2 0.892515 21824.7 1 5 CACCTG TTAATCC + +4 predrem__nrMotif2539 2 0.892515 21824.7 1 5 CACCTG TTAATCA + +4 idmmpmm__ems-ems -1 0.892515 21824.7 1 5 CACCTG TCATTAA - +4 transfac_pro__M05386-CG3065-hkb 2 0.892515 21824.7 1 5 CACCTG CCGCCCA - +4 transfac_pro__M05499-CG3065-hkb-luna 2 0.892515 21824.7 1 5 CACCTG CCGCCCA - +4 predrem__nrMotif111 -2 0.892515 21824.7 1 4 CACCTG TCTTTCT + +4 predrem__nrMotif110 -2 0.892515 21824.7 1 4 CACCTG TCTTTTT - +4 cisbp__M5093-lola 4 0.892515 21824.7 1 3 CACCTG TGCAGAC + +4 flyfactorsurvey__lola-PW_SANGER_5_FBgn0005630-lola 4 0.892515 21824.7 1 3 CACCTG TGCAGAC - +4 taipale_cyt_meth__MAFG_NWWWNTGCTGACN_eDBD_meth-cic-maf-S-tj 4 0.89269 21828.9 1 6 CACCTG AAAAATGCTGACT + +4 taipale_cyt_meth__POU4F1_NTGCATWATGCAN_eDBD_repr-acj6 1 0.89269 21828.9 1 6 CACCTG ATGCATTATGCAT + +4 transfac_pro__M00775-btd-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps 4 0.89269 21828.9 1 6 CACCTG CCTTAGCCAATCA + +4 cisbp__M6196-E2f1-eve 6 0.89269 21828.9 1 6 CACCTG TTTTCGCGCCCTT - +4 cisbp__M6361-NFAT 7 0.89269 21828.9 1 6 CACCTG TGGAAATTTCCAT - +4 cisbp__M6492-Stat92E 2 0.89269 21828.9 1 6 CACCTG AATTCCCAGAAAA - +4 flyfactorsurvey__eg_SANGER_5_FBgn0000560-eg-kni 6 0.89269 21828.9 1 6 CACCTG GTGCTCTAATTTT - +4 taipale_tf_pairs__POU5F1_NATATGCTAATKN_HT 5 0.89269 21828.9 1 6 CACCTG TAATTAGCATATG - +4 transfac_pro__M08996-btd-klu-sd-Sp1-Spps-sr 7 0.89269 21828.9 1 6 CACCTG CCCCGCCCACGCA - +4 cisbp__M3385-bin-croc 8 0.89269 21828.9 1 5 CACCTG CATATAAACAATG + +4 cisbp__M6341-Mef2-rump -1 0.89269 21828.9 1 5 CACCTG TTCTATAAATAGA + +4 swissregulon__sacCer__RFX1-CG5846-CG9727-Max-Rfx-SREBP 9 0.89269 21828.9 1 4 CACCTG TTGCCATGGCAAC + +4 cisbp__M2535-br 4 0.892938 21835 1 6 CACCTG TAATAAACTAAAAGA + +4 cisbp__M5598-btn-Dll-dve-unpg 5 0.892938 21835 1 6 CACCTG TAATTACGCTAATTA + +4 flyfactorsurvey__pfk_SANGER_5_FBgn0035405-CG15812 3 0.892938 21835 1 6 CACCTG ACTTCCCATTGTTCC + +4 homer__AWWNTGCTGAGTCAT_Bach1-Jra-cnc-kay-maf-S-nej 0 0.892938 21835 1 6 CACCTG AAATTGCTGAGTCAT + +4 jaspar__MA0516.1-CG42741-CTCF-E2f2-E(z)-Klf15-Nf-YA-Nf-YB-SREBP-Sp1-Spps-Spt20-Stat92E-brm-btd-dar1-kay 7 0.892938 21835 1 6 CACCTG GCCCCGCCCCCTCCC + +4 taipale__LHX2_DBD_YAATTANNCTAATTR_repr-btn-Dll-dve-unpg 5 0.892938 21835 1 6 CACCTG TAATTACGCTAATTA + +4 taipale_cyt_meth__GATA1_GATAANNNNNTTATC_eDBD_repr-GATAe-grn-pnr 6 0.892938 21835 1 6 CACCTG GATAATGACATTATC + +4 taipale_tf_pairs__FOXJ2_PITX1_NTAATCCNNWMAACA_CAP_repr-Ptx1 3 0.892938 21835 1 6 CACCTG CTAATCCCAACAACA + +4 transfac_pro__M01844-Hsf 5 0.892938 21835 1 6 CACCTG TTTTTTTTCTAGAAA + +4 transfac_pro__M07369 8 0.892938 21835 1 6 CACCTG GAAGATGAAACATAT + +4 transfac_pro__M07449 4 0.892938 21835 1 6 CACCTG CGGAAACATCCTCCG + +4 transfac_pro__M09493-CG34367-Dbx-ind-unpg 5 0.892938 21835 1 6 CACCTG TTTAATCATTAATTA + +4 transfac_public__M00093-br 4 0.892938 21835 1 6 CACCTG TAATAAACTAAAAGA + +4 cisbp__M2314-brm-btd-CG42741-CTCF-dar1-E2f2-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Spt20-SREBP-Stat92E 7 0.892938 21835 1 6 CACCTG GCCCCGCCCCCTCCC - +4 cisbp__M4452-ebi-foxo-Jra-MTA1-like-nej-NFAT-Stat92E 7 0.892938 21835 1 6 CACCTG TGAGTCATATCGAGA - +4 cisbp__M5662-C15-Nf1-NfI 4 0.892938 21835 1 6 CACCTG CTGGCACTGTGCCAA - +4 transfac_pro__M01298 9 0.892938 21835 1 6 CACCTG AAATGCTGACGCCGG - +4 transfac_pro__M02880-maf-S 5 0.892938 21835 1 6 CACCTG CCTTGCAATTTTTTC - +4 transfac_public__M00495-cnc-Jra-kay 9 0.892938 21835 1 6 CACCTG AGCATGACTCATCGT - +4 cisbp__M5580 10 0.892938 21835 1 5 CACCTG AACGAAACCGAAACT + +4 taipale__IRF9_full_AWCGAAACCGAAACY 10 0.892938 21835 1 5 CACCTG AACGAAACCGAAACT + +4 stark__TGCATAATTAATTAC-acj6 12 0.892938 21835 1 3 CACCTG TGCATAATTAATTAC + +4 tfdimers__MD00111 8 0.89322 21841.9 1 6 CACCTG TATAATCATACATCAATGATTAACTAAA + +4 cisbp__M5293-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 4 0.893694 21853.5 1 6 CACCTG CGATGACGTCATCG + +4 transfac_pro__M02869 2 0.893694 21853.5 1 6 CACCTG AAAAACCATTAAGG + +4 taipale_cyt_meth__POU3F2_NTAATKAKATGCGN_eDBD_meth-pdm3-vvl 3 0.893694 21853.5 1 6 CACCTG ACGCATCTCATTAA - +4 transfac_pro__M01666-Stat92E 4 0.893694 21853.5 1 6 CACCTG TTGTCTTCTTGGAA - +4 taipale__KLF14_DBD_NGCCACGCCCMCNT-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 9 0.893694 21853.5 1 5 CACCTG GGCCACGCCCCCTT + +4 cisbp__M5592-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 9 0.893694 21853.5 1 5 CACCTG GGCCACGCCCCCTT - +4 hocomoco__MEF2D_MOUSE.H11MO.0.A-Mef2-rump -1 0.893694 21853.5 1 5 CACCTG AGCTAAAAATAGCA - +4 cisbp__M6015-foxo-FoxP-slp2 11 0.893694 21853.5 1 3 CACCTG TGTTTATTGTTTAC - +4 taipale__Foxj3_DBD_RTAAACAATAAACA-fd59A-foxo-FoxP-slp2 11 0.893694 21853.5 1 3 CACCTG TGTTTATTGTTTAC - +4 hocomoco__STAT1_MOUSE.H11MO.0.A-Stat92E 9 0.893924 21859.1 1 6 CACCTG AGGAAAATGAAACTGAAAGAAA + +4 transfac_pro__M04664-foxo 15 0.893924 21859.1 1 6 CACCTG TAAGCATCAAAACAACAATCCC + +4 transfac_pro__M09489-bsh-C15-CG11294-CG34367-CG4328-Dbx-E5-ems-Lmx1a-nub-pdm2-unpg-vvl 15 0.893924 21859.1 1 6 CACCTG AATTTATTAATTAATTAAGATT - +4 cisbp__M6124-Sox15-SoxN 0 0.8942 21865.9 1 6 CACCTG TTCCATTGTTT + +4 flyfactorsurvey__pdm2_SOLEXA_5_FBgn0004394-acj6-nub-pdm2-vvl 4 0.8942 21865.9 1 6 CACCTG TATGCAAATTA + +4 predrem__nrMotif1347 1 0.8942 21865.9 1 6 CACCTG GGCCCCGGCAG + +4 taipale__HMX3_DBD_NNCAMTTAANN-Hmx-NK7.1 2 0.8942 21865.9 1 6 CACCTG AGCAATTAACA + +4 taipale_cyt_meth__JUN_NATGASTCATN_FL_meth-bon-cnc-Jra-kay-Mef2-Myc-pan 5 0.8942 21865.9 1 6 CACCTG GATGACTCATC + +4 tiffin__TIFDMEM0000041 0 0.8942 21865.9 1 6 CACCTG TACCAAAAATA + +4 transfac_pro__M07761-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-PHDP-repo-Rx-Traf4-unc-4 1 0.8942 21865.9 1 6 CACCTG TAATTGAATTA + +4 cisbp__M6199-sr 5 0.8942 21865.9 1 6 CACCTG CCGCCCACGCC - +4 hocomoco__GSC_HUMAN.H11MO.0.D-Gsc-oc 4 0.8942 21865.9 1 6 CACCTG GCTAATCCCTT - +4 taipale_cyt_meth__JDP2_NRTGASTCAYN_FL-cnc-CoRest-Jra-kay-Mef2-Sin3A 5 0.8942 21865.9 1 6 CACCTG GATGAGTCATG - +4 taipale_cyt_meth__JUNB_NATGASTCAYN_eDBD_meth-bon-cnc-Jra-kay-Mef2 5 0.8942 21865.9 1 6 CACCTG GATGAGTCATC - +4 taipale_cyt_meth__MYBL2_NTAACSGTTAN_eDBD_meth 2 0.8942 21865.9 1 6 CACCTG TTAACGGTTAA - +4 tiffin__TIFDMEM0000095 0 0.8942 21865.9 1 6 CACCTG TATTTATATTT - +4 hdpi__ZNF385 -1 0.8942 21865.9 1 5 CACCTG CCCTGGAAAAT + +4 cisbp__M1481 -1 0.8942 21865.9 1 5 CACCTG TACTACAATTA - +4 cisbp__M2330-BEAF-32-pnr -1 0.8942 21865.9 1 5 CACCTG AACTATCGATA - +4 cisbp__M5518-Hmx -1 0.8942 21865.9 1 5 CACCTG AGCAATTAAAA - +4 hocomoco__KAISO_HUMAN.H11MO.1.A-Chd1-CoRest -1 0.8942 21865.9 1 5 CACCTG TTCTCGCGAGA - +4 transfac_pro__M06376 6 0.8942 21865.9 1 5 CACCTG CATCGCCCCCC - +4 swissregulon__sacCer__STB3 7 0.8942 21865.9 1 4 CACCTG AATTTTTCACT + +4 taipale_cyt_meth__HOXA13_NCTCGTAAAAN_FL_meth -2 0.8942 21865.9 1 4 CACCTG GCTCGTAAAAC + +4 predrem__nrMotif887 -2 0.8942 21865.9 1 4 CACCTG GCTGCAGCCGC - +4 transfac_pro__M07343 -2 0.8942 21865.9 1 4 CACCTG GCTGGGCTTTT - +4 cisbp__M4671-CTCF 8 0.8942 21865.9 1 3 CACCTG GATGGCGCCAC - +4 tfdimers__MD00324-EcR-Sox100B 6 0.894571 21874.9 1 6 CACCTG AAATACTCTGTGAACCACAAAGCAAAC + +4 cisbp__M4237 1 0.89516 21889.3 1 6 CACCTG TAGCCGCGG + +4 cisbp__M6380-al-B-H1-B-H2-bsh-CG34367-Dr-E5-ems-en-eve-exex-inv-lab-lms-OdsH-repo-Ubx-unc-4-unpg 1 0.89516 21889.3 1 6 CACCTG CTAATTGGT + +4 hocomoco__HBP1_HUMAN.H11MO.0.D 1 0.89516 21889.3 1 6 CACCTG ACTCATTGA + +4 hocomoco__NOBOX_HUMAN.H11MO.0.C-B-H1-B-H2-CG34367-Dr-E5-OdsH-Ubx-al-bsh-ems-en-eve-exex-inv-lab-repo-unc-4-unpg 1 0.89516 21889.3 1 6 CACCTG TTAATTGGT + +4 predrem__nrMotif1335 1 0.89516 21889.3 1 6 CACCTG ACACACTGC + +4 predrem__nrMotif1386 1 0.89516 21889.3 1 6 CACCTG ACACACAGT + +4 predrem__nrMotif2264 0 0.89516 21889.3 1 6 CACCTG AGCCTTGCT + +4 predrem__nrMotif849 2 0.89516 21889.3 1 6 CACCTG GGCACTGCC + +4 transfac_pro__M02115 1 0.89516 21889.3 1 6 CACCTG TCAAATTAA + +4 transfac_pro__M03571-Irbp18-Myc-nej-Xrp1 1 0.89516 21889.3 1 6 CACCTG TTGCATAAT + +4 cisbp__M0929-abd-A-Antp-ap-Awh-btn-CG18599-CG4328-Dfd-E5-ems-en-eve-exex-ftz-ind-inv-lab-lbl-Lim3-Lmx1a-pb-Scr-Ubx-unpg-zen2 1 0.89516 21889.3 1 6 CACCTG GGTAATTAG - +4 cisbp__M1604-D-Mad-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.89516 21889.3 1 6 CACCTG AAAACAATG - +4 hocomoco__PO5F1_MOUSE.H11MO.1.A-Sox15-SoxN-Tbp-acj6-nub-pdm2-vvl 3 0.89516 21889.3 1 6 CACCTG ATTTGCATA - +4 jaspar__MA0277.1-CG17328 0 0.89516 21889.3 1 6 CACCTG TTTCTTTTT - +4 predrem__nrMotif1146 2 0.89516 21889.3 1 6 CACCTG CTGACCCTC - +4 predrem__nrMotif2011 2 0.89516 21889.3 1 6 CACCTG TTTTCATTG - +4 predrem__nrMotif2032 0 0.89516 21889.3 1 6 CACCTG TTCCATTAA - +4 predrem__nrMotif2278 3 0.89516 21889.3 1 6 CACCTG CTACTCTTT - +4 transfac_pro__M01618-CG17328 0 0.89516 21889.3 1 6 CACCTG TTTCTTTTT - +4 transfac_pro__M01898 1 0.89516 21889.3 1 6 CACCTG TAGCCGCGG - +4 predrem__nrMotif2522 -1 0.89516 21889.3 1 5 CACCTG TCCACAATT + +4 elemento__AATCCCAGC 5 0.89516 21889.3 1 4 CACCTG AATCCCAGC + +4 elemento__CCAATCAGC 5 0.89516 21889.3 1 4 CACCTG CCAATCAGC + +4 c2h2_zfs__M0385-MTF-1 5 0.89516 21889.3 1 4 CACCTG GTGCACACG - +4 cisbp__M0322-Jra-cnc 6 0.89516 21889.3 1 3 CACCTG ATGACTCAC + +4 transfac_pro__M04687-Chd1-CoRest -3 0.89516 21889.3 1 3 CACCTG CTCGCGAGA - +4 transfac_pro__M05392-CG12605-scrt 6 0.89516 21889.3 1 3 CACCTG TCGTTTGAC - +4 tfdimers__MD00337-EcR 13 0.895751 21903.8 1 6 CACCTG TTTCTCCCTCTGAACCCTTTGTTTTTCAAATTCTC + +4 tfdimers__MD00174-Stat92E 11 0.895802 21905 1 6 CACCTG TTTTTAATTTCCTCATTAGTAAAT + +4 cisbp__M4976-fru 8 0.895802 21905 1 6 CACCTG GTTTTTGTTACTGTGGGGTGGGGG - +4 flyfactorsurvey__fru_SOLEXA_5_FBgn0004652-fru 8 0.895802 21905 1 6 CACCTG GTTTTTGTTACTGTGGGGTGGGGG - +4 hocomoco__ZN260_HUMAN.H11MO.0.C 12 0.895802 21905 1 6 CACCTG TGGAATACTATGCAGCCATAAAAA - +4 tfdimers__MD00032-sens-2 4 0.895802 21905 1 6 CACCTG TTTAAAGCAGGGATTAGTGATAAA - +4 tfdimers__MD00209-Tbp 18 0.895802 21905 1 6 CACCTG TTTTTTATTTATCCCCACTTCTTT - +4 cisbp__M0672-E2f1-E2f2 4 0.896158 21913.8 1 6 CACCTG TTGGCGCCAA + +4 cisbp__M1108 4 0.896158 21913.8 1 6 CACCTG AACCAATCAA + +4 jaspar__MA0606.1-NFAT 3 0.896158 21913.8 1 6 CACCTG ATTTTCCATT + +4 predrem__nrMotif1944 0 0.896158 21913.8 1 6 CACCTG CACTCTCATT + +4 predrem__nrMotif223 4 0.896158 21913.8 1 6 CACCTG ATTTCTCTTT + +4 predrem__nrMotif286 0 0.896158 21913.8 1 6 CACCTG AAACAATGAA + +4 transfac_pro__M00652-ewg 0 0.896158 21913.8 1 6 CACCTG CGCATGCGCA + +4 transfac_pro__M03202 4 0.896158 21913.8 1 6 CACCTG ATGCCGCCCG + +4 transfac_pro__M05164 4 0.896158 21913.8 1 6 CACCTG ATGCCGCCCG + +4 transfac_pro__M05904 4 0.896158 21913.8 1 6 CACCTG GGGCAGCCGA + +4 transfac_pro__M07587 4 0.896158 21913.8 1 6 CACCTG TAATTAATTA + +4 cisbp__M2247-btd-Klf15-Sp1-Spps 4 0.896158 21913.8 1 6 CACCTG TCCGCCCCCT - +4 hdpi__HNRPLL-sm 2 0.896158 21913.8 1 6 CACCTG TTTCCGTGGT - +4 homer__ATGATTRATG_LIN-39 0 0.896158 21913.8 1 6 CACCTG CATCAATCAT - +4 predrem__nrMotif1965 1 0.896158 21913.8 1 6 CACCTG AAATCTTAAA - +4 predrem__nrMotif2139 4 0.896158 21913.8 1 6 CACCTG TACAGACAAA - +4 predrem__nrMotif258 0 0.896158 21913.8 1 6 CACCTG CGCCGCGGCC - +4 transfac_pro__M07576 1 0.896158 21913.8 1 6 CACCTG TTTCCGACAA - +4 cisbp__M1199-Antp-Awh-C15-CG4328-CG9876-CG11085-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-Dr-Drgx-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-ems-en-eve-exex-ey-ftz- 5 0.896158 21913.8 1 5 CACCTG CTAATTAGCC + +4 cisbp__M4945-al-ap-Awh-CG11294-CG15696-CG32532-CG34367-CG9876-E5-en-hbn-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 5 0.896158 21913.8 1 5 CACCTG CTAATTAAGA + +4 predrem__nrMotif40 -1 0.896158 21913.8 1 5 CACCTG CCCAGTGCAG + +4 swissregulon__hs__GFI1.p2 5 0.896158 21913.8 1 5 CACCTG CCAATCACAG + +4 transfac_pro__M05116 -1 0.896158 21913.8 1 5 CACCTG GCCGGCATTC + +4 transfac_pro__M07380-E2f2 -1 0.896158 21913.8 1 5 CACCTG CTTTCGCGCC + +4 flyfactorsurvey__luna_SANGER_5_FBgn0040765-CG42741-Sp1-Spps-btd-luna 5 0.896158 21913.8 1 5 CACCTG GGCAACGCCC - +4 predrem__nrMotif28 5 0.896158 21913.8 1 5 CACCTG CTGGGCAGCA - +4 transfac_pro__M00744 5 0.896158 21913.8 1 5 CACCTG ATTTATTCAT - +4 transfac_pro__M05482 5 0.896158 21913.8 1 5 CACCTG ATTCGCCCCA - +4 transfac_pro__M05509 5 0.896158 21913.8 1 5 CACCTG TTCTTCCCCC - +4 transfac_pro__M08973-SoxN -1 0.896158 21913.8 1 5 CACCTG TTCTATTGTT - +4 cisbp__M1094-abd-A-Antp-ap-Awh-bsh-btn-CG18599-CG4328-Dfd-E5-ems-en-eve-exex-ftz-ind-inv-lab-lbl-Lim3-Lmx1a-pb-Scr-Ubx-unpg-zen-zen2 6 0.896158 21913.8 1 4 CACCTG CTTAATTACC + +4 cisbp__M5597-al-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-dve-E5-ems-en-eve-exex-ey-ind-inv-lab-lbe-lbl-Lim1-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2-zf -2 0.896158 21913.8 1 4 CACCTG ACTAATTAAC + +4 fantom__motif139_CGTTCGAATT -2 0.896158 21913.8 1 4 CACCTG CGTTCGAATT + +4 taipale__LHX2_DBD_NCTAATTANN-al-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-dve-E5-ems-en-eve-exex-ey-ind-inv-lab-lbe-lbl-Lim1-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-toy-Ubx-unc-4-unpg-V -2 0.896158 21913.8 1 4 CACCTG ACTAATTAAC + +4 taipale_cyt_meth__LBX2_NCYAATTANN_eDBD_meth-al-Antp-ap-Awh-bsh-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-dve-E5-ems-en-eve-exex-ftz-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-OdsH-otp-pb-Pph13-repo-ro 6 0.896158 21913.8 1 4 CACCTG ACTAATTAAC + +4 cisbp__M1179 6 0.896158 21913.8 1 4 CACCTG TATAATTATG - +4 cisbp__M5480-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zfh2 6 0.896158 21913.8 1 4 CACCTG ACTAATTAGC - +4 predrem__nrMotif926 6 0.896158 21913.8 1 4 CACCTG AGAAATGACA - +4 transfac_pro__M06001 -2 0.896158 21913.8 1 4 CACCTG GCTTTTCAAT - +4 transfac_pro__M08923-bon-cnc-CoRest-foxo-GATAe-grn-Jra-kay-Mef2-Myc-pan-pnr-Stat92E 6 0.896158 21913.8 1 4 CACCTG ATGAGTCATC - +4 transfac_pro__M08931-bon-cnc-CoRest-foxo-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 6 0.896158 21913.8 1 4 CACCTG ATGAGTCATC - +4 transfac_pro__M08944-cnc-CoRest-Jra-kay-Myc-Stat92E 6 0.896158 21913.8 1 4 CACCTG ATGAGTCATC - +4 hocomoco__NKX21_HUMAN.H11MO.0.A-scro-vnd -3 0.896158 21913.8 1 3 CACCTG CTTGAGTGGC + +4 transfac_pro__M03184 7 0.896158 21913.8 1 3 CACCTG ATGCCGACAC + +4 transfac_pro__M05137 7 0.896158 21913.8 1 3 CACCTG ATGCCGCCAC + +4 taipale_cyt_meth__HSFY1_NCRTTCGAAWCRTTCGAWN_eDBD_repr 8 0.896264 21916.3 1 6 CACCTG GCGTTCGAAACGTTCGAAT + +4 taipale_tf_pairs__ETV2_DLX2_RCCGGAANNNNNNYAATTA_CAP_repr-pnt 13 0.896264 21916.3 1 6 CACCTG ACCGGAAATAGCCTAATTA + +4 cisbp__M6480-Brf-brm-btd-CG3065-CG42741-CoRest-ct-CTCF-dar1-ERR-E(z)-HDAC1-kay-Klf15-klu-l(3)neo38-luna-Nelf-E-Nf-YA-Nf-YB-Rbbp5-Sp1-Spps-Spt20-sr-SREBP-Stat92E-vtd 13 0.896264 21916.3 1 6 CACCTG CCGGCCCCGCCCCCTCCCC - +4 taipale_tf_pairs__ETV2_SPDEF_NSCGGACGGAWATCCGSNT_CAP-Ets98B-pnt 12 0.896264 21916.3 1 6 CACCTG AGGCGGATTTCCGTCCGGC - +4 transfac_pro__M09384 11 0.89686 21930.9 1 6 CACCTG TGCCGTGAATTCGACGG + +4 c2h2_zfs__M5116 0 0.89686 21930.9 1 6 CACCTG TCCATCCCATAATACTC - +4 taipale_tf_pairs__E2F1_ELK1_SGCGCNNNNNCGGAAGN_CAP_repr-E2f1 2 0.89686 21930.9 1 6 CACCTG ACTTCCGTTTGCGCGCC - +4 transfac_pro__M01424-abd-A-al-Antp-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-Dbx-Dfd-HGTX-lab-Lim1-Lim3-Lmx1a-OdsH-otp-repo-Scr-Ubx-unc-4-vvl-zfh2 10 0.89686 21930.9 1 6 CACCTG GGTAATTAATTAACGCG - +4 scertf__pachkov.GAL80 12 0.89686 21930.9 1 5 CACCTG CGGATGACAATCCTCCG - +4 stark__CNNNGCGYRTGANYNAT -2 0.89686 21930.9 1 4 CACCTG CAAAGCGCATGAACAAT + +4 transfac_pro__M05306-fd59A 13 0.89686 21930.9 1 4 CACCTG TTAAAATTGCTTTAACT - +4 transfac_pro__M05383-fd59A 13 0.89686 21930.9 1 4 CACCTG TTAAAATTGCTTTAACT - +4 fantom__motif96_TKNTTCTGTCTN 2 0.899256 21989.5 1 6 CACCTG TTCTTCTGTCTA + +4 hocomoco__FOXM1_HUMAN.H11MO.0.A-GATAe-HDAC1-bin-fd59A-fkh-foxo-grn-nej-pan-pnr 4 0.899256 21989.5 1 6 CACCTG TGTTTGCTTTGC + +4 homer__ANTTCTTAAGAA_STAT6-Stat92E 2 0.899256 21989.5 1 6 CACCTG ATTTCTTAAGAA + +4 taipale__POU2F1_DBD_NWTATGCWAATN-Dll-dve-nub-pdm2-vvl 6 0.899256 21989.5 1 6 CACCTG AATATGCAAATT + +4 taipale__POU2F3_DBD_WTRMATATKYAW-nub-pdm2-vvl 3 0.899256 21989.5 1 6 CACCTG ATGAATATGCAA + +4 transfac_pro__M01255 1 0.899256 21989.5 1 6 CACCTG AATCATTAAAAT + +4 transfac_pro__M07055-bcd-Ptx1 6 0.899256 21989.5 1 6 CACCTG CACTAATCCCTT + +4 cisbp__M4768-Blimp-1 5 0.899256 21989.5 1 6 CACCTG GCTTTCCCTTTC - +4 cisbp__M5725-Dll-dve-nub-pdm2-vvl 6 0.899256 21989.5 1 6 CACCTG AATATGCAAATT - +4 flyfactorsurvey__Blimp-1_SANGER_5_FBgn0035625-Blimp-1 5 0.899256 21989.5 1 6 CACCTG GCTTTCCCTTTC - +4 stark__TGACAWWTWTGC 3 0.899256 21989.5 1 6 CACCTG GCAAAAATGTCA - +4 swissregulon__hs__CDC5L.p2-Cdc5 1 0.899256 21989.5 1 6 CACCTG TTATGTTAAATC - +4 taipale__E2F1_DBD_TTTGGCGCCAAA-E2f1-E2f2 5 0.899256 21989.5 1 6 CACCTG TTTGGCGCCAAA - +4 taipale_cyt_meth__POU2F2_NTCATTATGCAN_eDBD_meth_repr-nub-pdm2 1 0.899256 21989.5 1 6 CACCTG TTGCATAATTAG - +4 taipale_tf_pairs__TEAD4_SPDEF_RGAATGCGGATN_CAP-Ets98B-sd 0 0.899256 21989.5 1 6 CACCTG CATCCGCATTCC - +4 tiffin__TIFDMEM0000006 5 0.899256 21989.5 1 6 CACCTG TTGAAAAACTTT - +4 transfac_pro__M05343-Hr38 2 0.899256 21989.5 1 6 CACCTG GTGATCTAAACA - +4 transfac_pro__M05442-Hr38 2 0.899256 21989.5 1 6 CACCTG GTGATCTAAACA - +4 transfac_pro__M05470-Hr38 2 0.899256 21989.5 1 6 CACCTG GTGATCTAAACA - +4 transfac_pro__M05926 0 0.899256 21989.5 1 6 CACCTG CCACTAGTAGTA - +4 transfac_pro__M06413 6 0.899256 21989.5 1 6 CACCTG AATGGCTTCCAC - +4 transfac_pro__M06433 1 0.899256 21989.5 1 6 CACCTG GGATCTTGACAA - +4 fantom__motif136_GTCTGCGTCTCT -1 0.899256 21989.5 1 5 CACCTG GTCTGCGTCTCT + +4 taipale_cyt_meth__CEBPB_NRTTGCGYAAYN_eDBD_meth-CG7786-gt-Irbp18-nej-Pdp1-slbo-vri-Xrp1 7 0.899256 21989.5 1 5 CACCTG TATTGCGTAATA + +4 transfac_pro__M05634 7 0.899256 21989.5 1 5 CACCTG TATTCTTTCCCG - +4 transfac_pro__M06558-CG2120 7 0.899256 21989.5 1 5 CACCTG TGTTTTTTCCCA - +4 hocomoco__ZFP42_HUMAN.H11MO.0.A-pho-phol 8 0.899256 21989.5 1 4 CACCTG AAAATGGCTGCC - +4 transfac_pro__M06157 8 0.899256 21989.5 1 4 CACCTG GCGTTTGGCACA - +4 dbcorrdb__ARID3A__ENCSR000EDP_1__m2 2 0.899622 21998.5 1 6 CACCTG CATGACTGATCAAAGAGCAA + +4 dbcorrdb__ELF1__ENCSR000BMD_1__m1-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets97D-Hcf-Myc-pnt-RpII215-Sin3A-Taf1 6 0.899622 21998.5 1 6 CACCTG CCCCCGCCACTTCCGGGTTC + +4 dbcorrdb__ELF1__ENCSR000BMZ_1__m1-aop-Atac3-bs-Dif-dl-Eip74EF-Ets21C-Ets97D-Hcf-Myc-pnt-Rbbp5-RpII215-Sin3A-Taf1 5 0.899622 21998.5 1 6 CACCTG CCCCGCCACTTCCGGGTTCG + +4 dbcorrdb__EZH2__ENCSR000ASE_1__m1-Brf-CTCF-E2f1-E(z)-HDAC1-RpII215-tna 11 0.899622 21998.5 1 6 CACCTG CCGCGGCGGAGCCCCGGCGG + +4 dbcorrdb__GABPA__ENCSR000BGC_1__m1-aop-Atac3-Brf-Dif-dl-E2f1-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Hr78-lid-Max-Myc-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 13 0.899622 21998.5 1 6 CACCTG CCGCCACTTCCGGCGCCGGC + +4 dbcorrdb__GABPA__ENCSR000BHS_1__m1-aop-Atac3-Brf-bs-CTCF-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Max-Myc-pho-phol-Rbbp5-RpII215-Sin3A-Taf1-tna-vtd 0 0.899622 21998.5 1 6 CACCTG CGCCGGAAGTGGCGGCGCGG + +4 dbcorrdb__HMGN3__ENCSR000DOB_1__m2 3 0.899622 21998.5 1 6 CACCTG ACGCAGCCGCCGGCCGGCTG + +4 dbcorrdb__POLR2A__ENCSR000EZQ_1__m3-Brf-CrebB-CTCF-E(z)-Max-Myc-RpII215-SREBP-vtd 10 0.899622 21998.5 1 6 CACCTG CAGCGCGCAGCGCCCGCGCC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BQC_1__m2-CoRest-Jra-kay-mor-pan-Snr1 8 0.899622 21998.5 1 6 CACCTG GAGTGACTCAGCGCCCGGGC + +4 dbcorrdb__SIN3A__ENCSR000BPB_1__m2-Sin3A 14 0.899622 21998.5 1 6 CACCTG TGACAGCGGTATCACTTCGG + +4 dbcorrdb__SP1__ENCSR000BHK_1__m2-btd-CG3065-CG42741-dar1-E2f2-ERR-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-vtd 13 0.899622 21998.5 1 6 CACCTG CCCTAGGCCCCGCCCCCTGC + +4 dbcorrdb__SP1__ENCSR000BIR_1__m1-btd-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 4 0.899622 21998.5 1 6 CACCTG GCCGCGCCAGCCAATCAGAG + +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m2-Su(z)12 10 0.899622 21998.5 1 6 CACCTG CGCAGCGCAAAGCCGGCATC + +4 dbcorrdb__TAF1__ENCSR000BPF_1__m2-Rbbp5-Taf1 5 0.899622 21998.5 1 6 CACCTG CAAGATAATTGCGGCGCCAG + +4 dbcorrdb__TBP__ENCSR000ECB_1__m1-Tbp 7 0.899622 21998.5 1 6 CACCTG GCCGCCATATCAACTCGGCC + +4 taipale_tf_pairs__ELK1_ETV7_NNSMGGACGGAYNTCCKSNN_CAP-aop 12 0.899622 21998.5 1 6 CACCTG AACCGGACGGATGTCCGGTT + +4 transfac_pro__M01557 11 0.899622 21998.5 1 6 CACCTG TTCTTCCGGAAAAATTTGCA + +4 transfac_pro__M07823-al-Awh-btn-C15-CG18599-CG32532-CG34367-E5-ems-en-eve-inv-lab-Lim1-Lim3-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-zfh2 12 0.899622 21998.5 1 6 CACCTG GTTAATTAACGTTAATTAAC + +4 dbcorrdb__CTCF__ENCSR000DPS_1__m2-CTCF 2 0.899622 21998.5 1 6 CACCTG CCATGCTGGGAACTGCAGCC - +4 dbcorrdb__GABPA__ENCSR000BJK_1__m1-aop-Atac3-Brf-brm-CTCF-Dif-dl-E2f1-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-HDAC1-Hr78-lid-Max-Myc-Nelf-E-pnt-Rbbp5-RpII215-Sin3A-SREBP-Taf1-TfIIFalpha-tna-v 12 0.899622 21998.5 1 6 CACCTG CGCCACTTCCGGCGCCGGCG - +4 dbcorrdb__GTF2F1__ENCSR000EBP_1__m1-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 8 0.899622 21998.5 1 6 CACCTG GCCGCCGCGCCCTTTATAGG - +4 dbcorrdb__IRF3__ENCSR000EEJ_1__m1-btd-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps 1 0.899622 21998.5 1 6 CACCTG GCACCGGCCAATCAGAAGGG - +4 dbcorrdb__KAT2A__ENCSR000DNO_1__m6 11 0.899622 21998.5 1 6 CACCTG TTTTCTTGGCCTTTTTGGTT - +4 dbcorrdb__PBX3__ENCSR000BGR_1__m2-bs-btd-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 2 0.899622 21998.5 1 6 CACCTG CCCCTCTGATTGGCTGGGGC - +4 dbcorrdb__SIX5__ENCSR000BGX_1__m2-Hcf-Six4 14 0.899622 21998.5 1 6 CACCTG CCCGGCCGCGGGGCATGCTG - +4 dbcorrdb__SP2__ENCSR000BQG_1__m2-btd-E2f2-kay-Max-Myc-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps 5 0.899622 21998.5 1 6 CACCTG GCGCCGGCCAATCAACGGCC - +4 dbcorrdb__TBP__ENCSR000EDD_1__m1-Tbp 9 0.899622 21998.5 1 6 CACCTG CGAGCGCGCTAACGCGTCGC - +4 dbcorrdb__ZNF274__ENCSR000EVG_1__m3-bon-Brf-brm-btd-Chd1-CrebB-CTCF-E2f1-E2f2-Eip74EF-ERR-ewg-E(z)-FoxP-Hcf-HDAC1-Hr78-Jra-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna-vtd-zfh1 4 0.899622 21998.5 1 6 CACCTG CCTCCCCCGGCCGCCCCGCC - +4 homer__GAATGGAAAAAATGAGTCAT_NFAT_AP1-CG5641-Jra-kay-NFAT 6 0.899622 21998.5 1 6 CACCTG ATGACTCATTTTTTCCATTC - +4 taipale_tf_pairs__HOXA3_PAX5_YNATTAGTCACGCWTSRNTR_CAP_repr-sv 6 0.899622 21998.5 1 6 CACCTG CAGTCAAGCGTGACTAATGA - +4 taipale_tf_pairs__ELK1_PAX9_RSCGGAACYACGCWYSANTG_CAP-Poxm -1 0.899622 21998.5 1 5 CACCTG ACCGGAACTACGCTTGACTG + +4 flyfactorsurvey__BH1_SOLEXA_FBgn0011758-B-H1-B-H2-CG11085 0 0.899907 22005.4 1 6 CACCTG TAATTG + +4 flyfactorsurvey__PhdP_Cell_FBgn0025334-PHDP 1 0.899907 22005.4 1 5 CACCTG TTAATT + +4 hdpi__MYLK-Strn-Mlck-sqa 1 0.899907 22005.4 1 5 CACCTG TTTCCA - +4 hdpi__NFATC3-NFAT 1 0.899907 22005.4 1 5 CACCTG TTTCCA - +4 cisbp__M2021-bcd-Ptx1 2 0.899907 22005.4 1 4 CACCTG TAATCC + +4 flyfactorsurvey__Achi_SOLEXA_FBgn0033749-achi 2 0.899907 22005.4 1 4 CACCTG TTGACA + +4 flyfactorsurvey__Vis_SOLEXA_FBgn0033748-vis 2 0.899907 22005.4 1 4 CACCTG TTGACA + +4 jaspar__MA0212.1-Ptx1-bcd 2 0.899907 22005.4 1 4 CACCTG TAATCC + +4 cisbp__M4727-achi 2 0.899907 22005.4 1 4 CACCTG TTGACA - +4 cisbp__M5268-vis 2 0.899907 22005.4 1 4 CACCTG TTGACA - +4 tfdimers__MD00398-Pur-alpha 9 0.900124 22010.7 1 6 CACCTG TCTCTCCACCCACTTCCTCTTTCCCTTTCC - +4 cisbp__M0504 2 0.900341 22016 1 6 CACCTG TGCGGCTG + +4 cisbp__M0951-al-Antp-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG34367-CG7745-CG9876-Dr-dve-E5-ems-en-gsb-gsb-n-ind-inv-lab-Lim1-Lim3-OdsH-otp-pb-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-unpg-Vsx1-vvl-zfh2 2 0.900341 22016 1 6 CACCTG ACTAATTA + +4 jaspar__MA0317.1-FoxK-FoxL1-bin-fd19B-fd102C-foxo-slp1-slp2 2 0.900341 22016 1 6 CACCTG ATAAACAA + +4 jaspar__MA1005.1-Taf1 0 0.900341 22016 1 6 CACCTG CGCCGCCA + +4 predrem__nrMotif2342 2 0.900341 22016 1 6 CACCTG CATAATTA + +4 scertf__macisaac.SPT23 0 0.900341 22016 1 6 CACCTG AAAATCAA + +4 swissregulon__sacCer__HCM1-FoxK-FoxL1-bin-fd19B-fd102C-foxo-slp1-slp2 2 0.900341 22016 1 6 CACCTG ATAAACAA + +4 taipale__PAX4_full_CTAATTAG-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-inv-Lim3-unpg 1 0.900341 22016 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__GSC_YTAATCCN_FL_meth-Gsc-oc-Ptx1 2 0.900341 22016 1 6 CACCTG CTAATCCC + +4 taipale_cyt_meth__HOXB7_RTCGTTAN_eDBD_meth-abd-A-Antp-btn-Dfd-exex-Scr-Ubx 0 0.900341 22016 1 6 CACCTG GTCGTTAA + +4 transfac_pro__M01630-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 2 0.900341 22016 1 6 CACCTG ATAAACAA + +4 yetfasco__YCR065W_570-FoxK-FoxL1-bin-fd19B-fd102C-foxo-slp1-slp2 2 0.900341 22016 1 6 CACCTG ATAAACAA + +4 cisbp__M5392-al-Awh-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.900341 22016 1 6 CACCTG CTAATTAG - +4 taipale_cyt_meth__LHX9_MTCGTTAN_FL_meth-ind-unpg 2 0.900341 22016 1 6 CACCTG TTAACGAG - +4 taipale_cyt_meth__LHX9_MTCGTTAN_eDBD_meth-Awh-ind-unpg 2 0.900341 22016 1 6 CACCTG CTAACGAG - +4 taipale_tf_pairs__HOXA6_SYMATTAN_HT-abd-A-Ubx 1 0.900341 22016 1 6 CACCTG TTAATTGC - +4 cisbp__M0877 3 0.900341 22016 1 5 CACCTG TTTGACAC + +4 hdpi__RBMS1-shep 3 0.900341 22016 1 5 CACCTG AATAAGCA + +4 predrem__nrMotif1461-Hsf-pb -1 0.900341 22016 1 5 CACCTG TTCTAGAA + +4 taipale_cyt_meth__CRX_NTAATCCN_FL_meth-Gsc-oc-Ptx1 3 0.900341 22016 1 5 CACCTG CTAATCCC + +4 transfac_pro__M01599-bin-CHES-1-like-croc-fd59A-FoxP-slp1 3 0.900341 22016 1 5 CACCTG ATAAACAA + +4 cisbp__M0596 3 0.900341 22016 1 5 CACCTG TTTCAAAT - +4 cisbp__M1202-CG34367-en-inv-lab-unpg -1 0.900341 22016 1 5 CACCTG ACCAATTA - +4 flyfactorsurvey__Dfd_SOLEXA_FBgn0000439-Antp-Awh-CG18599-Dfd-E5-Scr-Ubx-bsh-ems-eve-pb-zen-zen2 -2 0.900341 22016 1 4 CACCTG CTTAATGA + +4 jaspar__MA1055.1 -2 0.900341 22016 1 4 CACCTG CCGTACGG + +4 transfac_pro__M00428-E2f1 4 0.900341 22016 1 4 CACCTG GCGCGAAA - +4 elemento__CTCCAGCA -3 0.900341 22016 1 3 CACCTG CTCCAGCA + +4 elemento__CTCCGCCC -3 0.900341 22016 1 3 CACCTG CTCCGCCC + +4 taipale__VAX2_DBD_YTAATTAN-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-Dfd-Drgx-E5-ems-en-eve-ind-lab-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-Scr-Ubx-unpg-Vsx1-zen2 5 0.900341 22016 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXA7_NYAATTAN_eDBD_meth-abd-A-Antp-bsh-btn-Dfd-Dll-Lim1-Scr-Ubx 5 0.900341 22016 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__HOXD1_NTAATTAN_eDBD_meth-Antp-Awh-bsh-btn-Dfd-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-pb-Scr-slou-zen2 5 0.900341 22016 1 3 CACCTG GTAATTAC + +4 cisbp__M1176-Antp-CG11294-HGTX-lab-pb-Scr-unpg-Vsx1-zen2 5 0.900341 22016 1 3 CACCTG TTAATTAC - +4 cisbp__M5454-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.900341 22016 1 3 CACCTG TTGTTTAC - +4 elemento__AGAGAGAG -3 0.900341 22016 1 3 CACCTG CTCTCTCT - +4 elemento__CCAATGAG -3 0.900341 22016 1 3 CACCTG CTCATTGG - +4 taipale__FOXJ2_DBD_RTAAACAA-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.900341 22016 1 3 CACCTG TTGTTTAC - +4 taipale__Foxj3_DBD_RTAAACAA-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.900341 22016 1 3 CACCTG TTGTTTAC - +4 transfac_pro__M03552-Jra-Stat92E -3 0.900341 22016 1 3 CACCTG ATGAGTCA - +4 transfac_pro__M07255-foxo 5 0.900341 22016 1 3 CACCTG ATAAACAA - +4 transfac_pro__M07803-Antp-ap-CG11294-CG32532-CG9876-E5-ems-en-HGTX-ind-inv-lab-Lim1-Lim3-lms-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 5 0.900341 22016 1 3 CACCTG TTAATTAC - +4 cisbp__M5600-Awh-ems-en-inv-repo 4 0.900429 22018.2 1 6 CACCTG TAATTAGCGCTAATTA + +4 taipale_tf_pairs__FOXJ3_ELF1_NNARAAAACCGAAWMN_CAP-Eip74EF 6 0.900429 22018.2 1 6 CACCTG ACAGAAAACCGAAAAA + +4 transfac_pro__M01341-al-Antp-B-H1-B-H2-CG32532-CG34367-Dr-en-inv-Lim3-lms-Scr-slou-tup-unpg 2 0.900429 22018.2 1 6 CACCTG CAAAACCAATTAATTT + +4 hocomoco__SOX1_HUMAN.H11MO.0.D-D-Sox15-Sox21a-Sox21b-SoxN 6 0.900429 22018.2 1 6 CACCTG ATGAATAACATTCATC - +4 taipale__LHX6_full_TAATTAGYRYTRATTA_repr-Awh-ems-en-inv-repo 4 0.900429 22018.2 1 6 CACCTG TAATTAGCGCTAATTA - +4 taipale_tf_pairs__HOXB13_ONECUT2_NNNRTAAAWATYGAYY_CAP-onecut 10 0.900429 22018.2 1 6 CACCTG GATCAATATTTATAAG - +4 taipale_tf_pairs__PITX1_HOXA3_TAATKRNNNNGGATTA_CAP-Ptx1 6 0.900429 22018.2 1 6 CACCTG TAATCCCCACCAATTA - +4 transfac_pro__M01708-klu-sr 1 0.900429 22018.2 1 6 CACCTG TTCCCCGCATTTTTAT - +4 taipale_cyt_meth__PAX7_NSGTCACGSNNRTTAN_FL-gsb-gsb-n-Poxn-prd 11 0.900429 22018.2 1 5 CACCTG CTAATAAGCGTGACGA - +4 transfac_pro__M05227 4 0.90196 22055.6 1 6 CACCTG GTGCTTCCTGAGGAAAAC + +4 jaspar__MA0369.1-Mef2 1 0.90196 22055.6 1 6 CACCTG GAATCTATTTATAGAACC - +4 swissregulon__hs__CDX1_2_4.p2-cad 6 0.90196 22055.6 1 6 CACCTG TTTATTAATTTGTTTGTT - +4 hocomoco__LHX8_HUMAN.H11MO.0.D-Awh-repo 13 0.90196 22055.6 1 5 CACCTG AATTAATTGTAATTAGCG - +4 taipale__PAX2_DBD_NGTCACGCWTSRNTGNNY-ey-Poxm-sv-toy 14 0.90196 22055.6 1 4 CACCTG GAGCAGTCAAGCGTGACG - +4 cisbp__M4934-eg-kni 6 0.902127 22059.7 1 6 CACCTG GTGCTCTAATTTT + +4 cisbp__M2838 2 0.902127 22059.7 1 6 CACCTG GTAACCGTTTTTT - +4 taipale_tf_pairs__TEAD4_SPDEF_RGAATGCGGAWRT_CAP_repr-Ets98B-sd 1 0.902127 22059.7 1 6 CACCTG ACATCCGCATTCC - +4 transfac_pro__M09208 6 0.902127 22059.7 1 6 CACCTG GGAATATTCTTTT - +4 transfac_public__M00063 5 0.902127 22059.7 1 6 CACCTG GGTTTCACTTTTC - +4 transfac_public__M00218 2 0.902127 22059.7 1 6 CACCTG GTAACCGTTTTTT - +4 hocomoco__MEF2A_HUMAN.H11MO.0.A-Mef2-rump -1 0.902127 22059.7 1 5 CACCTG TTCTATTTTTAGC + +4 hocomoco__MEF2C_HUMAN.H11MO.0.A-Mef2-rump -1 0.902127 22059.7 1 5 CACCTG TGCTATTTTTAGC + +4 transfac_pro__M07685-cnc-Jra-kay-Mef2-nej 8 0.902127 22059.7 1 5 CACCTG TGATGACTCATCA + +4 transfac_pro__M05507 8 0.902127 22059.7 1 5 CACCTG CACGCCCCCCCCC - +4 transfac_pro__M08938-bon-Jra-kay-nej-pan 8 0.902127 22059.7 1 5 CACCTG GGATGAGTCATCA - +4 transfac_public__M00294-bin-croc 8 0.902127 22059.7 1 5 CACCTG CATATAAACAATG - +4 transfac_pro__M09120-brm-CG7839-dati-maf-S-orb-SREBP-vtd 14 0.902138 22060 1 6 CACCTG TTTTTTTTTTTTTTTACTTTTTTTTTTTT + +4 jaspar__MA0050.2-Blimp-1-MTA1-like-Stat92E-ebi-nej 3 0.902184 22061.1 1 6 CACCTG TTTTACTTTCACTTTCACTTT + +4 taipale_tf_pairs__ETV2_HES7_RSCGGAANNNNNNCACGTGNN_CAP_repr-pnt 11 0.902184 22061.1 1 6 CACCTG GGCACGTGCCCCACTTCCGGT - +4 taipale_tf_pairs__ETV2_ONECUT2_RCCGGAANNNNNNRATCRATN_CAP_repr-onecut-pnt 7 0.902184 22061.1 1 6 CACCTG TATCGATCGCCCACTTCCGGT - +4 transfac_pro__M05193 14 0.902184 22061.1 1 6 CACCTG GCGCCCCGGCGGGGAACCCAC - +4 transfac_pro__M05238-brm-btd-CTCF-ERR-E(z)-Spps-vtd 14 0.902184 22061.1 1 6 CACCTG GGGGGGCGGCGGGGCACCCCC - +4 transfac_pro__M05286 14 0.902184 22061.1 1 6 CACCTG ACGGGACGACAGAGCACCCCC - +4 cisbp__M1988-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-exex-ftz-hbn-ind-inv-lab-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ub 1 0.902449 22067.6 1 6 CACCTG TTAATTA + +4 cisbp__M3030 1 0.902449 22067.6 1 6 CACCTG ATTTATA + +4 cisbp__M4807-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx- 1 0.902449 22067.6 1 6 CACCTG TTAATTA + +4 cisbp__M4916-Dll 0 0.902449 22067.6 1 6 CACCTG TAATTAC + +4 cisbp__M5165-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-E5-ems-en-eve-exex-ftz-hbn-HGTX-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx-unc-4-u 1 0.902449 22067.6 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__CG32532_Cell_FBgn0052532-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG32532-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-exex- 1 0.902449 22067.6 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Dll_Cell_FBgn0000157-Dll 0 0.902449 22067.6 1 6 CACCTG TAATTAC + +4 flyfactorsurvey__Repo_SOLEXA_FBgn0011701-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-exex-ftz-hb 1 0.902449 22067.6 1 6 CACCTG TTAATTA + +4 scertf__spivak.MBP1 1 0.902449 22067.6 1 6 CACCTG ACGCGTC + +4 cisbp__M4888-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou-T 0 0.902449 22067.6 1 6 CACCTG TAATTAA - +4 flyfactorsurvey__CG9876_SOLEXA_FBgn0034821-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-ev 0 0.902449 22067.6 1 6 CACCTG TAATTAA - +4 transfac_pro__M07425-Dr 1 0.902449 22067.6 1 6 CACCTG TTAATTA - +4 cisbp__M2234 2 0.902449 22067.6 1 5 CACCTG TCGGCCG + +4 predrem__nrMotif1188 2 0.902449 22067.6 1 5 CACCTG GATCCCA + +4 predrem__nrMotif227 -1 0.902449 22067.6 1 5 CACCTG GCATAAA + +4 yetfasco__YLL054C_526 2 0.902449 22067.6 1 5 CACCTG TCGGCCG + +4 jaspar__MA0429.1 2 0.902449 22067.6 1 5 CACCTG TCGGCCG - +4 transfac_pro__M01944 2 0.902449 22067.6 1 5 CACCTG TCGGCCG - +4 predrem__nrMotif442 3 0.902449 22067.6 1 4 CACCTG TTCAACA + +4 predrem__nrMotif526 -2 0.902449 22067.6 1 4 CACCTG CCCATGC + +4 hdpi__ZNF250-larp-twin -2 0.902449 22067.6 1 4 CACCTG CATTTGC - +4 predrem__nrMotif120 -2 0.902449 22067.6 1 4 CACCTG CCCAGCC - +4 predrem__nrMotif87 3 0.902449 22067.6 1 4 CACCTG AACAACA - +4 predrem__nrMotif883 -2 0.902449 22067.6 1 4 CACCTG GCTTTAA - +4 predrem__nrMotif946 4 0.902449 22067.6 1 3 CACCTG TGAGCAA + +4 cisbp__M5667-NfI 9 0.902558 22070.3 1 6 CACCTG TTGGCAATTTGCCAG + +4 cisbp__M6128-CG9650-nej-pan-SoxN 2 0.902558 22070.3 1 6 CACCTG TTTGCATAACAATGG + +4 flyfactorsurvey__gsb_SOLEXA_5_FBgn0001148-Poxn-gsb-gsb-n-prd 9 0.902558 22070.3 1 6 CACCTG TTTGAGCGTGACGAA + +4 scertf__zhu.NHP6B-Tbp 0 0.902558 22070.3 1 6 CACCTG TATTTATATATAATA + +4 stark__AAANNNNNNNNNAAT 3 0.902558 22070.3 1 6 CACCTG AAAAAAAAAAAAAAT + +4 transfac_pro__M09150 2 0.902558 22070.3 1 6 CACCTG TCATTTTCACTCTCC + +4 cisbp__M4493-lid-pho-phol-RpII215-Taf1-Taf7 9 0.902558 22070.3 1 6 CACCTG GGCGGCCGCCATCTT - +4 cisbp__M5148-CG15812 3 0.902558 22070.3 1 6 CACCTG ACTTCCCACTGTTCC - +4 flyfactorsurvey__salr-F3-5_SOLEXA_FBgn0000287-salr 7 0.902558 22070.3 1 6 CACCTG GGGAAAAATCCGAAA - +4 homer__NNWWWTGGGCYTDDN_PCF 8 0.902558 22070.3 1 6 CACCTG AATAGGCCCATTAAA - +4 taipale__NFIB_full_TTGGCANNNTGCCAR-C15-Nf1-NfI 4 0.902558 22070.3 1 6 CACCTG CTGGCACTGTGCCAA - +4 transfac_pro__M01237 1 0.902558 22070.3 1 6 CACCTG CAACCCTAACCCTAA - +4 transfac_pro__M02742-E2f1 6 0.902558 22070.3 1 6 CACCTG ATCGCGCGCCTTTAT - +4 transfac_pro__M04057-C15-Nf1-NfI 4 0.902558 22070.3 1 6 CACCTG CTGGCACTGTGCCAA - +4 transfac_pro__M06808 8 0.902558 22070.3 1 6 CACCTG GGATTGGATTCCTCG - +4 taipale_cyt_meth__LEF1_WCATCGNNNCGCTGW_eDBD_meth-pan -1 0.902558 22070.3 1 5 CACCTG ACATCGGGGCGCTGA + +4 taipale_cyt_meth__ZNF501_NSSCGACGCGAACMN_FL-CG6654-CG7372 10 0.902558 22070.3 1 5 CACCTG CGGCGACGCGAACAC + +4 transfac_pro__M00703 -2 0.902558 22070.3 1 4 CACCTG CGTTTGAAACGACTA + +4 tfdimers__MD00261 24 0.902651 22072.5 1 6 CACCTG ATTATTTTTTAATGATTAATTAATTACATATTA - +4 tfdimers__MD00139-fkh-NfI 3 0.902759 22075.2 1 6 CACCTG TTTTTTTTGTTTGTTTTGGCAAGAATCCAAATTTAT + +4 cisbp__M1909-Mef2-bs 5 0.903152 22084.8 1 6 CACCTG ATTTCCATTTTTGG + +4 cisbp__M5728-nub-pdm2-vvl 4 0.903152 22084.8 1 6 CACCTG CATGCATATTCAAA + +4 homer__NATTTCCNGGAAAT_STAT1-Stat92E 3 0.903152 22084.8 1 6 CACCTG CATTTCCAGGAAAT + +4 taipale__POU2F2_DBD_NWTRMATATKYAWN-nub-pdm2-vvl 4 0.903152 22084.8 1 6 CACCTG CATGCATATGCAAA + +4 flyfactorsurvey__CG3065_F1-5_SOLEXA_2.5_FBgn0034946-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 1 0.903152 22084.8 1 6 CACCTG CGGCCACGCCCCCC - +4 jaspar__MA0082.1-Mef2-bs 5 0.903152 22084.8 1 6 CACCTG ATTTCCATTTTTGG - +4 transfac_pro__M02933 1 0.903152 22084.8 1 6 CACCTG ACGCACTGCGCGGC - +4 taipale_tf_pairs__ATF4_CEBPD_NGATGATGCAATNN_CAP 9 0.903152 22084.8 1 5 CACCTG GTATTGCATCATCC - +4 transfac_pro__M05589-salm-salr 9 0.903152 22084.8 1 5 CACCTG GGGGCCGTATACTG - +4 cisbp__M3628-Nf-YA-Nf-YB-Nf-YC -2 0.903152 22084.8 1 4 CACCTG TCTGATTGGCTAGT + +4 transfac_pro__M07950-CG42741-luna-Sp1 -2 0.903152 22084.8 1 4 CACCTG ACTGGGCGTGGCGT + +4 cisbp__M4606-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 10 0.903152 22084.8 1 4 CACCTG GGTATTGCACAATC - +4 transfac_pro__M05562 -3 0.903152 22084.8 1 3 CACCTG CTGTGCCGAAAAAA - +4 hocomoco__SOX17_HUMAN.H11MO.0.C-D-Sox15 0 0.9035 22093.3 1 6 CACCTG GCCATTGTTTT + +4 taipale_cyt_meth__PROP1_TAATTRCGTTA_FL_meth-al-CG32532-Drgx-Traf4 4 0.9035 22093.3 1 6 CACCTG TAATTGCGTTA + +4 cisbp__M5716-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-repo-Traf4-unc-4 0 0.9035 22093.3 1 6 CACCTG TAATTAAATTA - +4 taipale__PHOX2B_full_TAATYYAATTA-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-Lim3-OdsH-Optix-repo-Traf4-unc-4 0 0.9035 22093.3 1 6 CACCTG TAATTAAATTA - +4 transfac_pro__M00723-Trl 2 0.9035 22093.3 1 6 CACCTG TCGCGCTCTCT - +4 cisbp__M6238-bin-fd59A-fkh-foxo 6 0.9035 22093.3 1 5 CACCTG AAAATAAACAT + +4 taipale__HMX1_DBD_NNCAMTTAANN-Hmx -1 0.9035 22093.3 1 5 CACCTG AGCAATTAAAA + +4 transfac_pro__M07315-Myc-nej -1 0.9035 22093.3 1 5 CACCTG GATTGCACAAT + +4 transfac_pro__M07767-bcd-Gsc-oc-Ptx1 -1 0.9035 22093.3 1 5 CACCTG CCCTAATCCCC + +4 flyfactorsurvey__slbo_SANGER_5_FBgn0005638-slbo 7 0.9035 22093.3 1 4 CACCTG ATTGCGTAATC + +4 taipale_cyt_meth__HOXC13_NCTCGTAAAAN_eDBD_meth_repr -2 0.9035 22093.3 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M5195-slbo 7 0.9035 22093.3 1 4 CACCTG ATTGCGTAATC - +4 jaspar__MA0928.1-Awh-CG11294-CG34367-Lim1-Lim3-OdsH-Vsx1-al-ey-otp-repo-toy-unc-4 -2 0.9035 22093.3 1 4 CACCTG TCTAATTAATT - +4 taipale_cyt_meth__HOXC11_NRTCGTAAAAN_FL_meth-Abd-B-cad 7 0.9035 22093.3 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M08817 8 0.9035 22093.3 1 3 CACCTG TTTAATAAAAC + +4 transfac_pro__M00687-Nf-YA-Nf-YB-Nf-YC -3 0.9035 22093.3 1 3 CACCTG CTCATTGGCTG - +4 tfdimers__MD00212-NFAT-NfI 4 0.903756 22099.5 1 6 CACCTG ATTTTTCTTGGCAACTTTCCAAATTTTT + +4 taipale_tf_pairs__CUX1_SOX15_NATCRATNNNNNNNAACAATRS_CAP_repr-ct 7 0.904042 22106.5 1 6 CACCTG GATCGATAACCTTGAACAATGG + +4 taipale_tf_pairs__POU2F1_TBX21_NGTGNNNNMATATKNNNACACC_CAP-nub-pdm2 16 0.904042 22106.5 1 6 CACCTG AGTGTTAGAATATTCTAACACC + +4 tfdimers__MD00491 16 0.904042 22106.5 1 6 CACCTG AAAAAAATTAATTAATTTTATT + +4 hocomoco__SP2_HUMAN.H11MO.0.A-Brf-CG3065-CG42741-CTCF-CoRest-E2f1-ERR-Eip74EF-E(z)-HDAC1-Klf15-Max-Myc-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-Spt20-Stat92E-brm-btd-ct-dar1-kay-klu-luna-sr-tna 13 0.904042 22106.5 1 6 CACCTG CCCCCGGCCCCGCCCCCCCCCC - +4 cisbp__M6539-Brf-brm-btd-CG42741-CoRest-crol-ct-CTCF-E(z)-HDAC1-Klf15-klu-Nelf-E-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-vtd -1 0.904042 22106.5 1 5 CACCTG GCCCCCCCCCTCCCCCTCTCCG - +4 cisbp__M0955-abd-A-Abd-B-Antp-cad-Dbx-eve-ftz-H2.0-Scr-Ubx 1 0.904436 22116.2 1 6 CACCTG GGTAATAAA + +4 predrem__nrMotif1246 2 0.904436 22116.2 1 6 CACCTG TTAGCCTTT + +4 predrem__nrMotif1709 0 0.904436 22116.2 1 6 CACCTG TACTGAGAA + +4 predrem__nrMotif197 0 0.904436 22116.2 1 6 CACCTG TCCCCAAAA + +4 predrem__nrMotif2356 3 0.904436 22116.2 1 6 CACCTG TTACTCATT + +4 predrem__nrMotif421 3 0.904436 22116.2 1 6 CACCTG AAGAGCCAG + +4 predrem__nrMotif463 0 0.904436 22116.2 1 6 CACCTG TTCCAGAAG + +4 taipale__PITX1_DBD_NYTAATCCN_repr-bcd-Gsc-oc-Ptx1 3 0.904436 22116.2 1 6 CACCTG CTTAATCCC + +4 transfac_pro__M07309-Sox15 0 0.904436 22116.2 1 6 CACCTG GACAATGGA + +4 cisbp__M1040-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-en-eve-exex-ftz-HGTX-ind-inv-lab-pb-Scr-tup-Ubx-zen2 1 0.904436 22116.2 1 6 CACCTG GGTCATTAA - +4 cisbp__M1601-D-Sox14-Sox15-Sox21a-Sox21b 3 0.904436 22116.2 1 6 CACCTG GAAAACAAT - +4 hdpi__EEF1D-eEF1delta 0 0.904436 22116.2 1 6 CACCTG TGACTGGCA - +4 predrem__nrMotif1326 3 0.904436 22116.2 1 6 CACCTG ATGAGCCAG - +4 predrem__nrMotif386 0 0.904436 22116.2 1 6 CACCTG ATGCTGGCT - +4 predrem__nrMotif976 3 0.904436 22116.2 1 6 CACCTG TGCTATTTT - +4 cisbp__M5717-Gsc-oc-Ptx1 4 0.904436 22116.2 1 5 CACCTG CTTAATCCC + +4 idmmpmm__eve-Antp-Scr-bsh-ems-eve-ftz-pb-zen2 4 0.904436 22116.2 1 5 CACCTG TCATTAAAA + +4 predrem__nrMotif434 4 0.904436 22116.2 1 5 CACCTG GGGCTGCCC + +4 taipale_cyt_meth__LEF1_ASATCAAAS_eDBD-pan -1 0.904436 22116.2 1 5 CACCTG ACATCAAAG + +4 predrem__nrMotif1489 4 0.904436 22116.2 1 5 CACCTG ATTCTAGCA - +4 predrem__nrMotif9 4 0.904436 22116.2 1 5 CACCTG ATGCTGCCA - +4 cisbp__M0907-abd-A-Antp-bsh-btn-Dfd-Dll-E5-ems-eve-exex-ftz-HGTX-ind-lab-pb-Scr-Ubx-zen2 5 0.904436 22116.2 1 4 CACCTG TTAATTACC + +4 cisbp__M4973-foxo 5 0.904436 22116.2 1 4 CACCTG TCGTAAACA + +4 cisbp__M5082-lola 5 0.904436 22116.2 1 4 CACCTG GAATTTTCC - +4 flyfactorsurvey__foxo_SANGER_10_FBgn0038197-foxo 5 0.904436 22116.2 1 4 CACCTG TCGTAAACA - +4 hocomoco__FOXP1_HUMAN.H11MO.0.A 5 0.904436 22116.2 1 4 CACCTG ATAAACAAA - +4 cisbp__M0881-Antp-Awh-C15-Dll-Lim1-Scr-Ubx-bsh-btn-eve-ind-lab 6 0.904436 22116.2 1 3 CACCTG AGTAATTAA + +4 predrem__nrMotif2550 -3 0.904436 22116.2 1 3 CACCTG CTGCGTCCC + +4 predrem__nrMotif309 -3 0.904436 22116.2 1 3 CACCTG CTCATGGCT - +4 predrem__nrMotif906 -3 0.904436 22116.2 1 3 CACCTG CTCACTGCC - +4 taipale__HOXC12_DBD_GYAATAAAA_repr-Abd-B-cad-eve 6 0.904436 22116.2 1 3 CACCTG TTTTATTAC - +4 tfdimers__MD00513-E2f1 11 0.904965 22129.1 1 6 CACCTG AAATAAACCCCCACAGGAAACGAAAAA + +4 tfdimers__MD00579-CG7786-gt-Pdp1 19 0.904965 22129.1 1 6 CACCTG CAACCAAAAAACCACAGCACACACCCC + +4 transfac_pro__M00401-Atf6-CrebA-Xbp1 11 0.904965 22129.1 1 6 CACCTG GTCGGCTTGCTGACGTGGCACCGAGGC + +4 cisbp__M3678-Dll-dve-nub-pdm2-vvl 16 0.905273 22136.6 1 6 CACCTG TCTTTTAATTTGCATAATTATAA + +4 tfdimers__MD00170-foxo-Sox100B 2 0.905273 22136.6 1 6 CACCTG AATTACTTTGTAAACAAAAAAAA + +4 tfdimers__MD00465 2 0.905273 22136.6 1 6 CACCTG TTTTTTTAATCTCCCAAATCCCT - +4 transfac_public__M00138-Dll-dve-nub-pdm2-vvl 16 0.905273 22136.6 1 6 CACCTG TCTTTTAATTTGCATAATCATAT - +4 cisbp__M0668-E2f1-E2f2 4 0.90536 22138.8 1 6 CACCTG TTGGCGCCAA + +4 cisbp__M1216 2 0.90536 22138.8 1 6 CACCTG TTTTCGAAAA + +4 cisbp__M5808-Mad-Smox 0 0.90536 22138.8 1 6 CACCTG CGTCTAGACA + +4 cisbp__M6381 2 0.90536 22138.8 1 6 CACCTG TCTCCCACGC + +4 homer__TGCTGACTCA_MafA-Jra-cnc-kay-maf-S-tj 4 0.90536 22138.8 1 6 CACCTG TGCTGACTCA + +4 predrem__nrMotif587 4 0.90536 22138.8 1 6 CACCTG TTTGTTCATT + +4 swissregulon__sacCer__NHP6A 3 0.90536 22138.8 1 6 CACCTG CTATATATAA + +4 transfac_pro__M05007 4 0.90536 22138.8 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M05039 1 0.90536 22138.8 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M05066 4 0.90536 22138.8 1 6 CACCTG ACGCCGCCCA + +4 yetfasco__YOR380W_756-NFAT 0 0.90536 22138.8 1 6 CACCTG TTCCGCGGAA + +4 cisbp__M0591 4 0.90536 22138.8 1 6 CACCTG AATTCAAATT - +4 cisbp__M5152-pho-phol 3 0.90536 22138.8 1 6 CACCTG CGCCATCTTG - +4 flyfactorsurvey__phol_SANGER_5_FBgn0035997-pho-phol 3 0.90536 22138.8 1 6 CACCTG CGCCATCTTG - +4 homer__MTGATGCAAT_Atf4-nej 4 0.90536 22138.8 1 6 CACCTG ATTGCATCAT - +4 predrem__nrMotif188 0 0.90536 22138.8 1 6 CACCTG TTTCTTGGCT - +4 scertf__macisaac.RGT1 3 0.90536 22138.8 1 6 CACCTG TTTTTCCGAC - +4 transfac_pro__M01097-cad 3 0.90536 22138.8 1 6 CACCTG TCATAAAAGA - +4 transfac_pro__M01873-klu-sr 1 0.90536 22138.8 1 6 CACCTG CCGCCCCCGC - +4 cisbp__M5308-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.90536 22138.8 1 5 CACCTG ACCATATGTT + +4 predrem__nrMotif1506 -1 0.90536 22138.8 1 5 CACCTG TTCTTTGTGG + +4 stark__MVHTAAKCCS-Gsc-Ptx1-bcd-oc -1 0.90536 22138.8 1 5 CACCTG AGTTAAGCCC + +4 taipale__OLIG1_DBD_ANCATATGNT-amos-ato-crp-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.90536 22138.8 1 5 CACCTG AACATATGTT + +4 transfac_pro__M03198 5 0.90536 22138.8 1 5 CACCTG ACGCCGACCG + +4 transfac_pro__M05040 5 0.90536 22138.8 1 5 CACCTG AGGCCGCCCC + +4 transfac_pro__M05042 5 0.90536 22138.8 1 5 CACCTG AGGCCGCCCC + +4 cisbp__M0459 -1 0.90536 22138.8 1 5 CACCTG ACTTTTTTAT - +4 cisbp__M5097-btd-CG42741-luna-Sp1-Spps 5 0.90536 22138.8 1 5 CACCTG GGCAACGCCC - +4 cisbp__M5690-amos-ato-crp-dimm-Fer3-HLH54F-Oli-tap-twi -1 0.90536 22138.8 1 5 CACCTG AACATATGTT - +4 transfac_pro__M06173 5 0.90536 22138.8 1 5 CACCTG GCTTCCGCCA - +4 cisbp__M0893-al-Antp-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-Dfd-dve-E5-ems-en-eve-exex-ey-gsb-gsb-n-ind-inv-lab-Lim1-Lim3-Lmx1a-nub-OdsH-otp-pdm2-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou- 6 0.90536 22138.8 1 4 CACCTG GTTAATTAAC + +4 swissregulon__sacCer__CAD1 6 0.90536 22138.8 1 4 CACCTG ATTAGTAAGC + +4 cisbp__M1088-Dll 6 0.90536 22138.8 1 4 CACCTG AGTAATTAGC - +4 hocomoco__TBP_MOUSE.H11MO.0.A-RpII215-Taf1-Tbp -2 0.90536 22138.8 1 4 CACCTG CCTTTTATAG - +4 predrem__nrMotif2175-Mef2-rump -2 0.90536 22138.8 1 4 CACCTG TCTAAAAATA - +4 scertf__spivak.YAP7 6 0.90536 22138.8 1 4 CACCTG ATTAGTAAGC - +4 taipale_cyt_meth__HOXD12_NRTCGTAAAN_eDBD-cad 6 0.90536 22138.8 1 4 CACCTG GTTTACGACC - +4 transfac_pro__M05390-Tbp -3 0.90536 22138.8 1 3 CACCTG CTTTTAAATC + +4 tfdimers__MD00534-bap-Dbx 8 0.905563 22143.7 1 6 CACCTG AAATTATATACTTATTAATTAATTAAAAATAA - +4 transfac_pro__M07843-zen2 12 0.905748 22148.3 1 6 CACCTG CTAATGAAAGGCTTGCCCTTCATTAG - +4 tfdimers__MD00044-aop-Atac3-Eip74EF-Ets96B-Ets97D-Rpn5-Sirt6 3 0.905937 22152.9 1 6 CACCTG TTTTTACTTCCTCTTTTCTTTTTT + +4 tfdimers__MD00225-HGTX 13 0.905937 22152.9 1 6 CACCTG AATATAATGCAATTAATTTAAAAA - +4 stark__KNVNVBYTAATKRSBHNVD-Antp-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG11085-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-Dr-Drgx-E5-HGTX-Lim1-Lim3-Lmx1a-NK7.1-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-bt 3 0.90604 22155.4 1 6 CACCTG GAGAGTCTAATGACTTAGT + +4 taipale_cyt_meth__HSFY2_NCRTTCGAAWCRTTCGAWN_eDBD 8 0.90604 22155.4 1 6 CACCTG GCGTTCGAAACGTTCGAAT + +4 transfac_pro__M09358 13 0.90604 22155.4 1 6 CACCTG CTTGTTCAACAAGAAACCT - +4 transfac_pro__M06921 -2 0.90604 22155.4 1 4 CACCTG ACTGCGGCACGGGGTTGGG + +4 transfac_pro__M07886-bab1-Dif 15 0.90604 22155.4 1 4 CACCTG GGGAAAAATATTTTTTCCC + +4 transfac_pro__M06532 -2 0.90604 22155.4 1 4 CACCTG ACTGTATCGTTTACCGTCC - +4 taipale_cyt_meth__FOXP3_NAWTTGTAYGACAAATN_FL 11 0.906469 22165.9 1 6 CACCTG CATTTGTATGACAAATG + +4 transfac_pro__M00320 7 0.906469 22165.9 1 6 CACCTG CTCTATAAATCGCGGCG + +4 transfac_pro__M01334-Awh-CG11085-CG18599-E5-ems-en-eve-inv-lab-slou-unpg 5 0.906469 22165.9 1 6 CACCTG TGCGCTAATTAGTGGGA + +4 taipale_tf_pairs__POU2F1_DLX2_WTWTGCATANNTAATTA_CAP_repr-nub-pdm2 4 0.906469 22165.9 1 6 CACCTG CAATTAGATATGCAAAT - +4 transfac_pro__M01454-abd-A-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG4328-Dfd-gsb-gsb-n-HGTX-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-prd-repo-Scr-Ubx-unc-4-unpg-Vsx1-vvl-zfh2 10 0.906469 22165.9 1 6 CACCTG AGTAATTAATTAATTCG - +4 transfac_pro__M01315-Hmx -1 0.906469 22165.9 1 5 CACCTG ATTCTTTAATTGCTTGT - +4 tfdimers__MD00330-Hsf 18 0.908117 22206.2 1 6 CACCTG AAAAAATAAACAAAAAAGAACATTCTAAAAT + +4 cisbp__M5730-nub-pdm2-vvl 3 0.908277 22210.1 1 6 CACCTG ATGAATATGCAA + +4 cisbp__M5736-acj6-vvl 5 0.908277 22210.1 1 6 CACCTG ATGCATAAATTA + +4 taipale__POU3F3_DBD_WTGMATAAWTNA-acj6-vvl 5 0.908277 22210.1 1 6 CACCTG ATGCATAAATTA + +4 taipale_cyt_meth__ATF3_NRTGACGTCAYN_FL-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 3 0.908277 22210.1 1 6 CACCTG GATGACGTCATC + +4 transfac_pro__M04823-Dp-E2f1-E2f2 6 0.908277 22210.1 1 6 CACCTG CTTTCCCGCCCC + +4 transfac_pro__M05584-CG42726 4 0.908277 22210.1 1 6 CACCTG GGACAACCCCAC + +4 cisbp__M5351-E2f1-E2f2 5 0.908277 22210.1 1 6 CACCTG TTTGGCGCCAAA - +4 transfac_pro__M05660-CG6654-CG7372 1 0.908277 22210.1 1 6 CACCTG GCATCCGCCAAG - +4 transfac_pro__M05931 3 0.908277 22210.1 1 6 CACCTG GCGGACCGATCA - +4 transfac_pro__M05969 6 0.908277 22210.1 1 6 CACCTG TTTTTATTCCCC - +4 transfac_pro__M05988 6 0.908277 22210.1 1 6 CACCTG GCCATTTCCCAG - +4 transfac_pro__M06090 6 0.908277 22210.1 1 6 CACCTG AATGATTAACAG - +4 transfac_pro__M06522 3 0.908277 22210.1 1 6 CACCTG GCCGCCCTCCCA - +4 transfac_pro__M06539 6 0.908277 22210.1 1 6 CACCTG TCGGCTTGCCCG - +4 transfac_pro__M06683 6 0.908277 22210.1 1 6 CACCTG TCGTCTTAACAG - +4 transfac_pro__M06909-CG2120 6 0.908277 22210.1 1 6 CACCTG GATTCATTCATC - +4 hocomoco__IRF9_HUMAN.H11MO.0.C 7 0.908277 22210.1 1 5 CACCTG GAAAGCGAAACT + +4 neph__UW.Motif.0453 7 0.908277 22210.1 1 5 CACCTG CATTTTTTTTCA + +4 tiffin__TIFDMEM0000010 7 0.908277 22210.1 1 5 CACCTG TGAGCTCGCCTT + +4 homer__AGTTTCAGTTTC_ISRE-Blimp-1-Stat92E-ebi 7 0.908277 22210.1 1 5 CACCTG GAAACTGAAACT - +4 transfac_pro__M06243 7 0.908277 22210.1 1 5 CACCTG GATGCCCGATCT - +4 transfac_pro__M06511 7 0.908277 22210.1 1 5 CACCTG GATTTTTTCCCG - +4 transfac_pro__M06514 7 0.908277 22210.1 1 5 CACCTG GATTTTTTCCCG - +4 transfac_pro__M06646-crol 7 0.908277 22210.1 1 5 CACCTG TTTCTTGATCCG - +4 transfac_pro__M06771-CG2120 7 0.908277 22210.1 1 5 CACCTG GGACACAGTCCA - +4 transfac_pro__M06963 -1 0.908277 22210.1 1 5 CACCTG ACTCTGCATGGT - +4 transfac_pro__M06993-cnc -1 0.908277 22210.1 1 5 CACCTG GCCTTACAAATA - +4 hocomoco__CEBPB_HUMAN.H11MO.0.A-Irbp18-Xrp1-nej-slbo 8 0.908277 22210.1 1 4 CACCTG TATTGCACAATC + +4 taipale_cyt_meth__SP8_NCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 8 0.908277 22210.1 1 4 CACCTG GCCACGCCCACC + +4 taipale_cyt_meth__SP8_NCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 8 0.908277 22210.1 1 4 CACCTG GCCACGCCCCCC + +4 transfac_pro__M05781 -2 0.908277 22210.1 1 4 CACCTG GCTGCCCGACAC - +4 transfac_pro__M02266 9 0.908277 22210.1 1 3 CACCTG TTAATATTTAAC + +4 transfac_pro__M05927 -3 0.908277 22210.1 1 3 CACCTG CTTTTTGGCAAC - +4 cisbp__M2205 5 0.909252 22233.9 1 6 CACCTG ATGTTAAACTCCGAAAATTT + +4 cisbp__M4415 5 0.909252 22233.9 1 6 CACCTG ATGTTAAACTCCGAAAATTT + +4 dbcorrdb__CHD2__ENCSR000EED_1__m1-Chd1-CoRest 12 0.909252 22233.9 1 6 CACCTG CGGGTCTCGCGAGAGCCGGG + +4 dbcorrdb__E2F4__ENCSR000EVL_1__m2-btd-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 3 0.909252 22233.9 1 6 CACCTG CGCAAACAGCCAATCCGCGC + +4 dbcorrdb__EGR1__ENCSR000BNE_1__m1-Brf-brm-btd-cbt-CG42741-CoRest-ct-CTCF-ERR-E(z)-HDAC1-klu-luna-Max-Myc-Nelf-E-Nf-YA-Nf-YB-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-vtd 12 0.909252 22233.9 1 6 CACCTG CCCGCCCCCGCACCCCCCCC + +4 dbcorrdb__ELF1__ENCSR000BMB_1__m1-aop-Atac3-brm-bs-Dif-dl-E2f1-E2f2-Eip74EF-Ets21C-Ets97D-E(z)-FoxP-Hcf-Hr78-Myc-pnt-Rbbp5-RpII215-Sin3A-SREBP-Taf1 4 0.909252 22233.9 1 6 CACCTG CCCGCCACTTCCGGGTCCGG + +4 dbcorrdb__EZH2__ENCSR000ASW_1__m3-E(z) 6 0.909252 22233.9 1 6 CACCTG CGGGAGCACCAAGCCGCCCC + +4 dbcorrdb__GABPA__ENCSR000BPY_1__m1-aop-Atac3-bs-CTCF-Eip74EF-ERR-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Max-Myc-pho-phol-pnt-RpII215-Sin3A-Taf1 9 0.909252 22233.9 1 6 CACCTG CGCCGGAAGTGGCGGCGCGG + +4 dbcorrdb__HCFC1__ENCSR000ECH_1__m3-aop-Atac3-brm-Dif-dl-E2f1-E2f2-Eip74EF-ERR-Ets96B-Ets97D-E(z)-FoxP-Hcf-Hr78-lid-Max-Myc-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 13 0.909252 22233.9 1 6 CACCTG GCCGCGCCGGAAGTGGCGGC + +4 dbcorrdb__JUND__ENCSR000DYS_1__m2-Brf-brm-ERR-E(z)-Jra-Nelf-E-RpII215-SREBP-tna-vtd 0 0.909252 22233.9 1 6 CACCTG GTCCGCCGCGGGGCGCCCGC + +4 dbcorrdb__POLR2A__ENCSR000AOJ_1__m4-RpII215 14 0.909252 22233.9 1 6 CACCTG GCTAAAAAGCGCTAGCCCAG + +4 dbcorrdb__RCOR1__ENCSR000EDQ_1__m2-CoRest-E(z)-HDAC1-Sin3A-SREBP-tna 4 0.909252 22233.9 1 6 CACCTG ACCGCCGGGGGCGCTGTCCG + +4 dbcorrdb__SIN3A__ENCSR000BRM_1__m2-Sin3A 7 0.909252 22233.9 1 6 CACCTG TGTTGCTCAGCTGAAGACAC + +4 dbcorrdb__SP1__ENCSR000BKO_1__m2-btd-CG42741-dar1-luna-Nf-YA-Nf-YB-Sp1-Spps 11 0.909252 22233.9 1 6 CACCTG GGAAGGGGCGGGGCGGAGCC + +4 dbcorrdb__STAT3__ENCSR000DZV_1__m4-ebi-Stat92E 0 0.909252 22233.9 1 6 CACCTG TACTAAAACTGAAACTACAC + +4 dbcorrdb__UBTF__ENCSR000EFW_1__m1-Brf-Eip74EF-ERR-E(z)-RpII215-Sin3A-tna 7 0.909252 22233.9 1 6 CACCTG CGGCCGCCTCCGGCCGCGGC + +4 dbcorrdb__ZNF384__ENCSR000DYP_1__m2-rn-sqz 0 0.909252 22233.9 1 6 CACCTG ACTCTGTCTAAAAAAAAAAA + +4 transfac_pro__M01567 5 0.909252 22233.9 1 6 CACCTG ATGTTAAACTCCGAAAATTT + +4 dbcorrdb__BCLAF1__ENCSR000BJZ_1__m1-aop-Atac3-Brf-Dif-dl-E2f1-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-FoxP-Hcf-Hr78-lid-Max-Myc-pnt-Rbbp5-RpII215-Sin3A-Taf1-tna 14 0.909252 22233.9 1 6 CACCTG CCGCCCGCTTCCGGTGCGGG - +4 dbcorrdb__CTCF__ENCSR000DUU_1__m2-CTCF 12 0.909252 22233.9 1 6 CACCTG GGCTGCAGTTCCCAGCATGG - +4 dbcorrdb__GABPA__ENCSR000BIW_1__m1-aop-Atac3-brm-bs-CTCF-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-Max-Myc-pnt-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 1 0.909252 22233.9 1 6 CACCTG GCGCCGGAAGTGGCGGCGCG - +4 dbcorrdb__NFYA__ENCSR000EGR_1__m1-bs-btd-Chd1-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 1 0.909252 22233.9 1 6 CACCTG GCCTCTGATTGGCTGGGGCG - +4 dbcorrdb__NFYB__ENCSR000DNM_1__m2-Brf-brm-btd-CG42741-CTCF-dar1-E2f2-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps-sr-SREBP-Stat92E-vtd 11 0.909252 22233.9 1 6 CACCTG CGAGGCCCCGCCCCCTCCCC - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000ECT_1__m2-RpII215 6 0.909252 22233.9 1 6 CACCTG TCGCTACGCCGGCGCAGCGT - +4 dbcorrdb__TBL1XR1__ENCSR000DYZ_1__m3-ebi-foxo-Jra-MTA1-like-nej-NFAT-Stat92E 9 0.909252 22233.9 1 6 CACCTG GCTGACTCATAACGAAACTG - +4 hocomoco__IRF1_HUMAN.H11MO.0.A-Blimp-1-CG9650-MTA1-like-Stat92E-ebi-nej 1 0.909252 22233.9 1 6 CACCTG TTACTTTCACTTTCATTTTC - +4 hocomoco__IRF1_MOUSE.H11MO.0.A-Blimp-1-CG9650-MTA1-like-Stat92E-ebi-nej 1 0.909252 22233.9 1 6 CACCTG TTACTTTCACTTTCACTTTC - +4 taipale_tf_pairs__ETV2_HES7_NNCACGTGNNNNNCGGAWRY_CAP_repr-pnt 2 0.909252 22233.9 1 6 CACCTG ACTTCCGGTCGGCACGTGCC - +4 dbcorrdb__MAFK__ENCSR000EGX_1__m1-cic-cnc-kay-maf-S-tj -1 0.909252 22233.9 1 5 CACCTG TGCTGAGTCAGCAATTTTTA + +4 dbcorrdb__MAFK__ENCSR000EFH_1__m1-cic-cnc-kay-maf-S-tj -1 0.909252 22233.9 1 5 CACCTG TGCTGAGTCAGCAATTTTTA - +4 dbcorrdb__NFATC1__ENCSR000BQL_1__m1-ebi-foxo-Jra-MTA1-like-nej-NFAT-Stat92E 15 0.909252 22233.9 1 5 CACCTG ACTCTCGATATGACTCATAT - +4 yetfasco__YCL058C_1417 16 0.909252 22233.9 1 4 CACCTG ATATAAAAAAAAAAAAAACA - +4 scertf__badis.STP3 0 0.909368 22236.8 1 6 CACCTG TAGCGC + +4 cisbp__M5149-PHDP 1 0.909368 22236.8 1 5 CACCTG TTAATT + +4 fantom__motif41_TSACAA 1 0.909368 22236.8 1 5 CACCTG TGACAA + +4 hdpi__RAB2A-Rab2 -1 0.909368 22236.8 1 5 CACCTG AGCGTC - +4 stark__GCAACA-Aef1 2 0.909368 22236.8 1 4 CACCTG GCAACA + +4 transfac_pro__M01712 2 0.909368 22236.8 1 4 CACCTG CTAATC + +4 cisbp__M1952-CG18599-E5-ems-en-eve-inv-pb -3 0.909368 22236.8 1 3 CACCTG CTAATT + +4 hdpi__LAS1L-CG32075-TFAM -4 0.909368 22236.8 1 2 CACCTG TGGAAA + +4 hdpi__TFAM-CG32075-TFAM -4 0.909368 22236.8 1 2 CACCTG TGGAAA + +4 cisbp__M1201-Antp-HGTX-Scr 1 0.909544 22241.1 1 6 CACCTG CTAATTAA + +4 hdpi__LARP1-larp-twin 2 0.909544 22241.1 1 6 CACCTG TGCAAATC + +4 idmmpmm__abd-A-Antp-CG9876-CG11294-CG32532-Dfd-E5-HGTX-Lim1-Lmx1a-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-en-ftz-lab-lms-repo-ro-slou-unpg-zen2 1 0.909544 22241.1 1 6 CACCTG GTAATTAA + +4 taipale_cyt_meth__ARX_CYAATTAN_eDBD-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG4328-E5-ems-en-ey-ind-inv-lab-lbe-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-toy-unc-4-unpg-Vsx1-Vsx2-zen2-zfh2 1 0.909544 22241.1 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__HOXB4_RTCGTTAR_FL_meth-Antp-btn-Dfd-eve-exex-lab-pb-Scr 0 0.909544 22241.1 1 6 CACCTG ATCATTAA + +4 taipale_cyt_meth__ISX_CTAATTAR_FL-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-ey-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.909544 22241.1 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__LMX1A_YTAATTAN_eDBD_meth-abd-A-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Drgx-E5-ems-en-eve-ind-lab-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-Scr-Ubx-unpg-Vsx1-zen2 1 0.909544 22241.1 1 6 CACCTG CTAATTAC + +4 taipale_cyt_meth__TLX2_NCAATTAN_eDBD-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-foxo-gsb-gsb-n-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-pdm3-Pph13-prd-repo-ro-Rx-slou-Ubx-unc-4-un 1 0.909544 22241.1 1 6 CACCTG CTAATTAG + +4 transfac_pro__M07780-al-Awh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-exex-ind-inv-lbe-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.909544 22241.1 1 6 CACCTG CTAATTAG + +4 cisbp__M1992-HHEX 0 0.909544 22241.1 1 6 CACCTG TAATTAAA - +4 cisbp__M5706-Awh-C15-CG18599-CG34367-CG9876-E5-ems-Lim3-unpg 1 0.909544 22241.1 1 6 CACCTG CTAATTAG - +4 fantom__motif73_GAGCKMGC 2 0.909544 22241.1 1 6 CACCTG GCTCGCTC - +4 taipale_cyt_meth__DLX3_NYAATTAN_FL_meth-Antp-bsh-btn-Dll-Dr-en-exex-inv-Lim1-Scr 1 0.909544 22241.1 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DLX5_NYAATTAN_FL_meth-Dll-Lim1 1 0.909544 22241.1 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__GBX2_NYAATTAN_eDBD_meth-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.909544 22241.1 1 6 CACCTG CTAATTGG - +4 transfac_pro__M07824-B-H1-B-H2-bsh-C15-CG18599-CG34367-CG9876-Dr-E5-ems-en-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-unpg-Vsx1-Vsx2 1 0.909544 22241.1 1 6 CACCTG CTAATTGG - +4 cisbp__M0137-Dif-bab1 3 0.909544 22241.1 1 5 CACCTG AAAAAATT + +4 taipale_cyt_meth__DMBX1_NTAATCCN_eDBD_meth-bcd-Gsc-oc 3 0.909544 22241.1 1 5 CACCTG CTAATCCC + +4 yetfasco__YGL073W_1461-Hsf-pb -1 0.909544 22241.1 1 5 CACCTG TTCTAGAA + +4 cisbp__M0143-bab1 3 0.909544 22241.1 1 5 CACCTG ATTTATTT - +4 cisbp__M4783-btd-Klf15-Spps 3 0.909544 22241.1 1 5 CACCTG ACGCCCCC - +4 cisbp__M4961-exd 3 0.909544 22241.1 1 5 CACCTG TGTCAAAA - +4 hdpi__TEAD1-sd 3 0.909544 22241.1 1 5 CACCTG CTTTCCAT - +4 cisbp__M4909-Antp-Awh-bsh-CG18599-Dfd-E5-ems-eve-pb-Scr-Ubx-zen-zen2 -2 0.909544 22241.1 1 4 CACCTG CTTAATGA + +4 flyfactorsurvey__br-Z2_FlyReg_FBgn0000210-br -2 0.909544 22241.1 1 4 CACCTG TCTATTAA + +4 cisbp__M1477 4 0.909544 22241.1 1 4 CACCTG TGATCACT - +4 cisbp__M4777-br -2 0.909544 22241.1 1 4 CACCTG TCTATTAA - +4 cisbp__M0948-abd-A-Antp-bsh-Dfd-ftz-HGTX-Scr-Ubx 5 0.909544 22241.1 1 3 CACCTG TTAATGAC + +4 cisbp__M5945-Antp-ap-Awh-CG18599-CG4328-Dfd-E5-ems-en-eve-ind-lab-Lim3-Lmx1a-otp-pb-Pph13-Rx-Scr-Ubx-unpg-Vsx1-zen2 5 0.909544 22241.1 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__HOXB5_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-CG11085-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-pb-Scr-Ubx-unpg-zen2 5 0.909544 22241.1 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__HOXB5_NYAATTAN_eDBD_meth-abd-A-Antp-bsh-btn-Dfd-E5-ems-eve-exex-ind-pb-Scr-Ubx-zen2 5 0.909544 22241.1 1 3 CACCTG GCAATTAG + +4 taipale_cyt_meth__HOXB8_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-Dfd-Scr-Ubx 5 0.909544 22241.1 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__HOXD4_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-Dfd-Dll-Dr-E5-ems-en-exex-ind-inv-lab-Lim1-Lim3-pb-Scr-Ubx-unpg-zen-zen2 5 0.909544 22241.1 1 3 CACCTG GTAATTAG + +4 transfac_pro__M07802-Hmx 5 0.909544 22241.1 1 3 CACCTG GCAATTAA + +4 cisbp__M6016-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.909544 22241.1 1 3 CACCTG TTGTTTAC - +4 transfac_pro__M07797-abd-A-Antp-ap-CG11294-CG32532-CG9876-Dfd-Dll-E5-en-exex-ftz-HGTX-lab-lms-otp-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 5 0.909544 22241.1 1 3 CACCTG TTAATTAC - +4 cisbp__M5071-lbe-lbl 6 0.909544 22241.1 1 2 CACCTG GTTAACTA + +4 flyfactorsurvey__Lbe_Cell_FBgn0011278-lbe-lbl 6 0.909544 22241.1 1 2 CACCTG GTTAACTA + +4 transfac_pro__M01327-abd-A-al-Awh-CG11085-CG18599-CG34367-en-inv-Lim3-OdsH-otp-repo-ro-slou-Ubx-unc-4-unpg-zen2-zfh2 2 0.909708 22245.1 1 6 CACCTG GTGCACTAATTAAGAC + +4 transfac_pro__M02857 9 0.909708 22245.1 1 6 CACCTG ATATCAAAACAAAACA + +4 cisbp__M6245-foxo-FoxP 8 0.909708 22245.1 1 6 CACCTG AGTTTGTTTACTTTTT - +4 hocomoco__SOX2_HUMAN.H11MO.1.A-CG9650-Mad-SoxN-nej-pan 2 0.909708 22245.1 1 6 CACCTG TTTGCATAACAAAGGA - +4 hocomoco__SP4_HUMAN.H11MO.1.A-CG3065-CG42741-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-luna 3 0.909708 22245.1 1 6 CACCTG CGGCCCCGCCCCCTCC - +4 transfac_pro__M06904 13 0.909708 22245.1 1 3 CACCTG TGCATCGTGTCTCTAC - +4 jaspar__MA0379.1-Cnot4 0 0.909743 22245.9 1 5 CACCTG TATAT - +4 swissregulon__sacCer__SIG1-Cnot4 0 0.909743 22245.9 1 5 CACCTG TATAT - +4 transfac_pro__M01631-Cnot4 0 0.909743 22245.9 1 5 CACCTG TATAT - +4 flyfactorsurvey__Vis_Cell_FBgn0033748-vis 1 0.909743 22245.9 1 4 CACCTG TGACA + +4 cisbp__M5267-vis 1 0.909743 22245.9 1 4 CACCTG TGACA - +4 hdpi__MAPK1-rl -3 0.909743 22245.9 1 3 CACCTG CTTTG - +4 swissregulon__hs__PAX4.p2-CTCF-CoRest-crol-ct-l(3)neo38-peb 20 0.910311 22259.8 1 6 CACCTG GAAAAATTGCCAATACCCCACCCCCCCCCC + +4 cisbp__M5735-Dll-dve-nub-pdm2-vvl 5 0.911024 22277.3 1 6 CACCTG AAATTAGCATAAT + +4 taipale_cyt_meth__POU4F1_NTNNATWATGCAN_eDBD-acj6 1 0.911024 22277.3 1 6 CACCTG ATGAATTATGCAT + +4 transfac_pro__M05161 7 0.911024 22277.3 1 6 CACCTG TATGAACGGCCAG + +4 cisbp__M3471 5 0.911024 22277.3 1 6 CACCTG GGTTTCACTTTTC - +4 hocomoco__HXB6_HUMAN.H11MO.0.D-Ubx-abd-A 0 0.911024 22277.3 1 6 CACCTG TGCATCAATCATT - +4 predrem__nrMotif1778-E(z)-RpII215-brm-sr 7 0.911024 22277.3 1 6 CACCTG CCTCCCCCGCCCC - +4 taipale__POU3F3_DBD_NWTATGCWAATTW-Dll-dve-nub-pdm2-vvl 5 0.911024 22277.3 1 6 CACCTG AAATTAGCATAAT - +4 taipale_tf_pairs__TEAD4_HOXB13_RRAATGCARTAAA_CAP_repr-sd 5 0.911024 22277.3 1 6 CACCTG TTTATTGCATTCC - +4 transfac_pro__M05491-sr 7 0.911024 22277.3 1 6 CACCTG TGACCCACACCCA - +4 transfac_pro__M07326-Mef2-rump 7 0.911024 22277.3 1 6 CACCTG CTATTTTTAGCCC - +4 transfac_pro__M07778-al-bsh-btn-CG11294-CG32532-CG34367-CG9876-Drgx-lab-lbl-Lim3-OdsH-Optix-PHDP-repo-Rx-unc-4 2 0.911024 22277.3 1 6 CACCTG GTAATTTAATTAC - +4 hocomoco__PBX1_MOUSE.H11MO.1.A-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-Spps-btd-kay-yps -1 0.911024 22277.3 1 5 CACCTG CTCTGATTGGCTG + +4 scertf__zhu.YLL054C 4 0.911329 22284.7 1 6 CACCTG TCCGTAAAAAAAAACGGA + +4 swissregulon__sacCer__YLL054C 4 0.911329 22284.7 1 6 CACCTG TCCGTAAAAAAAAACGGA + +4 yetfasco__YLL054C_816 4 0.911329 22284.7 1 6 CACCTG TCCGTAAAAAAAAACGGA - +4 hocomoco__MAFK_HUMAN.H11MO.0.A-cnc-maf-S-tj 13 0.911329 22284.7 1 5 CACCTG AAAATTGCTGAGTCAGCA + +4 cisbp__M2295-cic-cnc-kay-maf-S-tj -2 0.911329 22284.7 1 4 CACCTG GCTGAGTCAGCAATTTTT + +4 jaspar__MA0495.1-cic-cnc-kay-maf-S-tj -2 0.911329 22284.7 1 4 CACCTG GCTGAGTCAGCAATTTTT + +4 cisbp__M2327-Stat92E 1 0.911581 22290.9 1 6 CACCTG TTTCCTGGAATTCCG + +4 cisbp__M4841-erm 9 0.911581 22290.9 1 6 CACCTG CAAAAAGAGCAACCA + +4 flyfactorsurvey__CG31670_SOLEXA_5_FBgn0031375-erm 9 0.911581 22290.9 1 6 CACCTG CAAAAAGAGCAACCA + +4 homer__AAACGACGTCGTTTT_Unknown2 7 0.911581 22290.9 1 6 CACCTG AAACGACGTCGTTTT + +4 homer__ATTTCCCAGVAKSCY_ZNF143_STAF-Hcf-Six4-bi-egg-mor 3 0.911581 22290.9 1 6 CACCTG ATTTCCCAGAATGCC + +4 predrem__nrMotif977 3 0.911581 22290.9 1 6 CACCTG CCCCCTCTCCCCGCC + +4 taipale_cyt_meth__PAX7_NNATTCGTCACGSTN_FL_meth-foxo-gsb-gsb-n-prd 8 0.911581 22290.9 1 6 CACCTG CGATTAGTCACGCTT + +4 taipale_tf_pairs__FOXJ2_ELF1_RMAGAAAACCGAANN_CAP_repr-Eip74EF 6 0.911581 22290.9 1 6 CACCTG ACAGAAAACCGAATA + +4 transfac_pro__M02913 9 0.911581 22290.9 1 6 CACCTG TCCGTCGCTTAAAAG + +4 transfac_pro__M03567-btd-CG3065-CG42741-CTCF-dar1-E(z)-kay-Klf15-Nf-YA-Nf-YB-Sp1-Spps 1 0.911581 22290.9 1 6 CACCTG TTGGCCCCGCCCCCC + +4 jaspar__MA0532.1-Stat92E 1 0.911581 22290.9 1 6 CACCTG TTTCCTGGAATTCCG - +4 neph__UW.Motif.0027 3 0.911581 22290.9 1 6 CACCTG TGCAGTACTGCATTC - +4 neph__UW.Motif.0587 6 0.911581 22290.9 1 6 CACCTG TGTTTTCTCAGTCTG - +4 swissregulon__hs__HMGA1_2.p2 5 0.911581 22290.9 1 6 CACCTG AAAAAAAATTGCATT - +4 taipale_tf_pairs__PAX3_GTCACGCNNMATTAN_HT-gsb-gsb-n-prd 6 0.911581 22290.9 1 6 CACCTG TTAATTAACCGTGAC - +4 c2h2_zfs__M3827-Spps-btd -1 0.911581 22290.9 1 5 CACCTG GCCTAGAGCGGCCCC + +4 transfac_pro__M07083-E2f1 10 0.911581 22290.9 1 5 CACCTG CTCCCGCCCCCACTC + +4 cisbp__M2271-E2f1 10 0.911581 22290.9 1 5 CACCTG CTCCCGCCCCCACTC - +4 cisbp__M4467-Mef2-rump -1 0.911581 22290.9 1 5 CACCTG TGCTATTTTTGGCAC - +4 transfac_pro__M02906-SoxN 10 0.911581 22290.9 1 5 CACCTG CGCTAACAATTATAG - +4 transfac_pro__M06960 -3 0.911581 22290.9 1 3 CACCTG CTTCCTCGTCCCCGT + +4 tfdimers__MD00207 0 0.911713 22294.1 1 6 CACCTG TTTTTGTTTTAATTAAATAAA + +4 transfac_pro__M09223 1 0.911713 22294.1 1 6 CACCTG AAACCAATAATTGAAAATTAT + +4 cisbp__M3966-aop-Stat92E 0 0.911713 22294.1 1 6 CACCTG CCCCATTTCCCGGAAATGACC - +4 transfac_pro__M05188 4 0.911713 22294.1 1 6 CACCTG AGAGGACCGCGGAAAACACAA - +4 transfac_pro__M05219-ERR-E(z) 14 0.911713 22294.1 1 6 CACCTG GCGGAGCGGGGGGGCACCCCC - +4 transfac_pro__M05244-brm-ERR-E(z) 15 0.911713 22294.1 1 6 CACCTG CCGGCGCGGGGGGGCCACCAC - +4 transfac_pro__M05273-ERR-E(z)-vtd 14 0.911713 22294.1 1 6 CACCTG GGGGGGCGGCGGGACACCCCC - +4 transfac_public__M00224-aop-Stat92E 0 0.911713 22294.1 1 6 CACCTG CCCCATTTCCCGGAAATGACC - +4 cisbp__M1914-Sox102F 0 0.911792 22296.1 1 6 CACCTG TAACAAT + +4 cisbp__M4862-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ey-ftz-hbn-HGTX-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-PHDP-Pph13-repo-ro 1 0.911792 22296.1 1 6 CACCTG TTAATTA + +4 cisbp__M5138-abd-A-al-Antp-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-Dll-E5-ems-en-eve-ey-ftz-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-pdm3- 1 0.911792 22296.1 1 6 CACCTG TTAATTA + +4 cisbp__M5262-abd-A-al-Antp-ap-Awh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pb-PH 1 0.911792 22296.1 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__CG4136_SOLEXA_FBgn0029775-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-e 1 0.911792 22296.1 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Lim1_SOLEXA_FBgn0026411-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-ey-hbn-ind-inv-lab-l 1 0.911792 22296.1 1 6 CACCTG TTAATTA + +4 jaspar__MA0399.1 0 0.911792 22296.1 1 6 CACCTG CGCGGGG + +4 transfac_pro__M01677 0 0.911792 22296.1 1 6 CACCTG CGCGGGG + +4 transfac_public__M00101 1 0.911792 22296.1 1 6 CACCTG ATTAATA + +4 cisbp__M1985-abd-A-CG15696-CG32532-CG34367-CG4328-CG9876-en-HGTX-inv-lab-lms-Lmx1a-OdsH-repo-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2 0 0.911792 22296.1 1 6 CACCTG CAATTAA - +4 cisbp__M2034-abd-A-Antp-CG11294-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-en-hbn-HGTX-inv-lab-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2 0 0.911792 22296.1 1 6 CACCTG TAATTAA - +4 jaspar__MA0176.1-CG4328-CG9876-CG15696-CG32532-CG34367-HGTX-Lmx1a-OdsH-Rx-Traf4-Ubx-Vsx1-Vsx2-abd-A-en-inv-lab-lms-repo-slou-unc-4-unpg 0 0.911792 22296.1 1 6 CACCTG TAATTAA - +4 jaspar__MA0226.1-Antp-CG4328-CG9876-CG11294-CG32532-CG34367-Dfd-Dll-HGTX-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-en-inv-lab-lms-otp-repo-slou-unc-4-unpg 0 0.911792 22296.1 1 6 CACCTG TAATTAA - +4 transfac_pro__M01091-prd 1 0.911792 22296.1 1 6 CACCTG ACAATTT - +4 transfac_pro__M05407-CG3065-hkb 1 0.911792 22296.1 1 6 CACCTG CCGCCCA - +4 transfac_pro__M09181 1 0.911792 22296.1 1 6 CACCTG TCAACAA - +4 cisbp__M4764-bcd-Gsc-oc-Ptx1 2 0.911792 22296.1 1 5 CACCTG TTAATCC + +4 predrem__nrMotif1912 2 0.911792 22296.1 1 5 CACCTG TTCACTA + +4 predrem__nrMotif1922 -1 0.911792 22296.1 1 5 CACCTG ATTTTCA + +4 transfac_pro__M03850-Sox102F 2 0.911792 22296.1 1 5 CACCTG TAAACAA - +4 cisbp__M5119-bcd-oc 3 0.911792 22296.1 1 4 CACCTG TTAATCC + +4 flyfactorsurvey__Oc_Cell_FBgn0004102-oc 3 0.911792 22296.1 1 4 CACCTG TTAATCC + +4 hdpi__HHEX-HHEX 4 0.911792 22296.1 1 3 CACCTG AAATTAC + +4 transfac_pro__M02079-CG18599-Dfd-eve-ind-tup-Ubx -3 0.911792 22296.1 1 3 CACCTG CTAATGG + +4 bergman__Su_H_-Su(H) 4 0.911792 22296.1 1 3 CACCTG CTCCCAC - +4 cisbp__M4766-bin-croc-fd59A-FoxK-FoxL1-slp2 4 0.911792 22296.1 1 3 CACCTG TGTTTAC - +4 cisbp__M5078-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-E5-ems-en-eve-ey-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-toy-Traf4-Ubx-unc-4-u 4 0.911792 22296.1 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__bin_SANGER_5_FBgn0045759-FoxK-FoxL1-bin-croc-fd59A-slp2 4 0.911792 22296.1 1 3 CACCTG TGTTTAC - +4 cisbp__M5072-ap-Awh-CG18599-Dfd-E5-ems-eve-lbe-lbl-zen2 5 0.911792 22296.1 1 2 CACCTG TTAATTA + +4 flyfactorsurvey__Lbe_SOLEXA_FBgn0011278-Awh-CG18599-Dfd-E5-ap-ems-eve-lbe-lbl-zen2 5 0.911792 22296.1 1 2 CACCTG TTAATTA + +4 cisbp__M5435-fd96Ca-fd96Cb 0 0.912054 22302.5 1 6 CACCTG TCGCTGTGTCATTC + +4 swissregulon__hs__BPTF.p2-E(bx) 8 0.912054 22302.5 1 6 CACCTG AAACAAAACACAAA + +4 taipale__FOXB1_DBD_GAATGACACRGCGN_repr-fd96Ca-fd96Cb 6 0.912054 22302.5 1 6 CACCTG GAATGACACAGCGA + +4 taipale__POU2F1_DBD_NWTRMATATKYAWN_repr-nub-pdm2-vvl 4 0.912054 22302.5 1 6 CACCTG CATGAATATTCATA + +4 transfac_pro__M04788-Blimp-1-Dif-dl-Stat92E 4 0.912054 22302.5 1 6 CACCTG CTTTCACTTTCACT + +4 cisbp__M4839-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 1 0.912054 22302.5 1 6 CACCTG CGGCCACGCCCCCC - +4 cisbp__M5151-pho 7 0.912054 22302.5 1 6 CACCTG GAAGCCATAACGGC - +4 cisbp__M6308-Blimp-1-Stat92E 0 0.912054 22302.5 1 6 CACCTG TGCTTTCACTTTCC - +4 taipale_cyt_meth__POU3F1_NTAATGAKATGCGN_eDBD_meth-pdm3-vvl 3 0.912054 22302.5 1 6 CACCTG ACGCATCTCATTAT - +4 transfac_pro__M09193-E2f1-E2f2 6 0.912054 22302.5 1 6 CACCTG TTTTGGCGCCAAAT - +4 hocomoco__MEF2A_MOUSE.H11MO.0.A-Mef2-rump -1 0.912054 22302.5 1 5 CACCTG TTCTATTTTTAGCA + +4 cisbp__M5726-nub-pdm2-vvl -2 0.912054 22302.5 1 4 CACCTG CATGAATATTCATA + +4 taipale_cyt_meth__ZNF597_GGCGGCCATYTTGN_FL_meth_repr-pho-phol 10 0.912054 22302.5 1 4 CACCTG CCAAAATGGCCGCC - +4 taipale_cyt_meth__FOXJ2_NWWGTTGTAAAYAN_eDBD_repr-slp2 11 0.912054 22302.5 1 3 CACCTG TTTGTTGTAAACAA + +4 tfdimers__MD00219-Ptx1 18 0.912141 22304.6 1 6 CACCTG TTTTTTCACTAATCTTCTAATCCTTTTTT + +4 tfdimers__MD00533-nub-pdm2 3 0.912141 22304.6 1 6 CACCTG TAATTTCTGATTGATATGCAAATGAAATT + +4 tfdimers__MD00580 15 0.912141 22304.6 1 6 CACCTG TTATTTTAATTTTATTACCTAATTATATT - +4 cisbp__M2270-CG32532-Traf4 0 0.912291 22308.2 1 6 CACCTG TAATTTAATCA + +4 flyfactorsurvey__odd_NAR_FBgn0002985-bowl-drm-odd-sob 5 0.912291 22308.2 1 6 CACCTG AACAGTAGCAG + +4 hocomoco__PROP1_HUMAN.H11MO.0.D-CG9876-CG11294-CG32532-CG34367-Dll-Dr-Drgx-OdsH-Optix-Traf4-al-bsh-en-hbn-repo-unc-4 0 0.912291 22308.2 1 6 CACCTG TAATTGAATTA + +4 taipale__YY2_DBD_NNCCGCCATNW_repr-pho-phol 0 0.912291 22308.2 1 6 CACCTG GTCCGCCATTA + +4 transfac_pro__M05292 2 0.912291 22308.2 1 6 CACCTG TTCTCTTGGAA + +4 transfac_pro__M09226 1 0.912291 22308.2 1 6 CACCTG GTAATTAATGC + +4 transfac_pro__M09564 1 0.912291 22308.2 1 6 CACCTG ACGCCGGCGCC + +4 cisbp__M2258-bowl-drm-odd-sob 4 0.912291 22308.2 1 6 CACCTG CTGCTACTGTT - +4 cisbp__M5955-pho-phol 0 0.912291 22308.2 1 6 CACCTG GTCCGCCATTA - +4 cisbp__M6198-btd-klu-Spps-sr 1 0.912291 22308.2 1 6 CACCTG CCGCCCACGCA - +4 taipale_cyt_meth__ALX1_TAATTAGATTA_FL_meth-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.912291 22308.2 1 6 CACCTG TAATCTAATTA - +4 transfac_pro__M09201 0 0.912291 22308.2 1 6 CACCTG AACATTCTTTT - +4 transfac_pro__M00983-cnc-maf-S -1 0.912291 22308.2 1 5 CACCTG TGCTGAGTCAT + +4 transfac_public__M00120-dl 6 0.912291 22308.2 1 5 CACCTG TGGGAAAATCC + +4 hocomoco__FOXF1_HUMAN.H11MO.0.D-bin-croc-fd59A-fkh-foxo 6 0.912291 22308.2 1 5 CACCTG AAAATAAACAT - +4 predrem__nrMotif1849 6 0.912291 22308.2 1 5 CACCTG TAAAAAAATCA - +4 transfac_pro__M06494 6 0.912291 22308.2 1 5 CACCTG CATCGCCCCCC - +4 taipale_cyt_meth__HOXA13_NCTCGTAAAAN_eDBD_meth -2 0.912291 22308.2 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M1142-Awh-CG11294-CG34367-Lim1-Lim3-OdsH-al-ey-otp-repo-toy-unc-4 -2 0.912291 22308.2 1 4 CACCTG TCTAATTAATT - +4 taipale_cyt_meth__HOXA10_NGYAATAAAAN_FL_meth-Abd-B-cad 7 0.912291 22308.2 1 4 CACCTG GTTTTATTGCC - +4 taipale_cyt_meth__HOXC10_NGYAATAAAAN_eDBD-abd-A-Abd-B-cad-eve-Ubx 7 0.912291 22308.2 1 4 CACCTG GTTTTATTGCC - +4 taipale_cyt_meth__HOXC11_NRTCGTAAAAN_eDBD-Abd-B-cad 7 0.912291 22308.2 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC12_NRTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.912291 22308.2 1 4 CACCTG GTTTTACGACC - +4 cisbp__M0553 3 0.9132 22330.5 1 6 CACCTG TTATAGCGA + +4 cisbp__M1776 3 0.9132 22330.5 1 6 CACCTG AAATCCCGC + +4 flyfactorsurvey__Dr_Cell_FBgn0000492-Dr 0 0.9132 22330.5 1 6 CACCTG GACCAATTA + +4 predrem__nrMotif1209 0 0.9132 22330.5 1 6 CACCTG TAACTCTCC + +4 predrem__nrMotif2074 3 0.9132 22330.5 1 6 CACCTG TATTGTCTT + +4 predrem__nrMotif2433 2 0.9132 22330.5 1 6 CACCTG TACAGCCAG + +4 predrem__nrMotif2623 2 0.9132 22330.5 1 6 CACCTG GGCAACAAA + +4 predrem__nrMotif822 0 0.9132 22330.5 1 6 CACCTG TTCCAGTGT + +4 predrem__nrMotif985 1 0.9132 22330.5 1 6 CACCTG GCTCCGGGG + +4 stark__CAANNNAAA 0 0.9132 22330.5 1 6 CACCTG CAAAAAAAA + +4 swissregulon__sacCer__YBR239C 0 0.9132 22330.5 1 6 CACCTG TTCCGGAAC + +4 cisbp__M0918-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11294-CG18599-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ftz-ind-inv-lab-lbl-Lim3-Lmx1a-pb-ro-Rx-Scr-tup-Ubx-unpg-Vsx1-Vsx2-zen-zen2 1 0.9132 22330.5 1 6 CACCTG GGTAATTAG - +4 cisbp__M1133 1 0.9132 22330.5 1 6 CACCTG ATATATTAC - +4 cisbp__M1145-CG4328-Lmx1a 0 0.9132 22330.5 1 6 CACCTG TAAATTAAA - +4 predrem__nrMotif1257 3 0.9132 22330.5 1 6 CACCTG TGCCCCATC - +4 predrem__nrMotif1294-CG3065-Klf15-Sp1-Spps-btd-cbt-dar1-luna 3 0.9132 22330.5 1 6 CACCTG CCACGCCCC - +4 predrem__nrMotif136 3 0.9132 22330.5 1 6 CACCTG TTTCACTGT - +4 predrem__nrMotif1534 1 0.9132 22330.5 1 6 CACCTG GAAATTGCT - +4 predrem__nrMotif2624 3 0.9132 22330.5 1 6 CACCTG AAAAGCCTA - +4 predrem__nrMotif387 0 0.9132 22330.5 1 6 CACCTG CTGCTTGCT - +4 predrem__nrMotif806 1 0.9132 22330.5 1 6 CACCTG TCAGCAGTG - +4 swissregulon__sacCer__HAP4-Nf-YA-Nf-YB-Nf-YC 0 0.9132 22330.5 1 6 CACCTG GACCAATCA - +4 transfac_pro__M01229 3 0.9132 22330.5 1 6 CACCTG CCTAATCCC - +4 cisbp__M4733-al-ap-Awh-CG18599-CG32532-CG9876-E5-ems-en-eve-hbn-lab-lbl-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-unpg-Vsx1 -1 0.9132 22330.5 1 5 CACCTG CGCTAATTA + +4 flyfactorsurvey__Al_SOLEXA_FBgn0000061-Awh-CG9876-CG18599-CG32532-E5-Lim3-OdsH-Pph13-Rx-Vsx1-al-ap-ems-en-eve-hbn-lab-lbl-otp-pb-repo-ro-unpg -1 0.9132 22330.5 1 5 CACCTG CGCTAATTA + +4 predrem__nrMotif1105 -1 0.9132 22330.5 1 5 CACCTG TCATGGAAA + +4 predrem__nrMotif2215 -1 0.9132 22330.5 1 5 CACCTG TTCTAAACA + +4 predrem__nrMotif2240 4 0.9132 22330.5 1 5 CACCTG TTTGGACAT + +4 predrem__nrMotif1036 4 0.9132 22330.5 1 5 CACCTG AAGACTTCT - +4 predrem__nrMotif2507 4 0.9132 22330.5 1 5 CACCTG CACACAGCA - +4 tiffin__TIFDMEM0000018 -1 0.9132 22330.5 1 5 CACCTG ACTTTTCCA - +4 predrem__nrMotif886 5 0.9132 22330.5 1 4 CACCTG AGAGAAAGC + +4 cisbp__M5045-al-ap-Awh-B-H2-bsh-btn-C15-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Dll-Dr-E5-en-hbn-HGTX-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vs 5 0.9132 22330.5 1 4 CACCTG CTAATTAAC - +4 flyfactorsurvey__inv_SOLEXA_2_FBgn0001269-C15-CG4328-CG9876-CG11294-CG32532-CG34367-Dll-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Ubx-Vsx1-Vsx2-al-ap-en-hbn-inv-lab-lms-otp-pb-repo-ro-slou-unc-4-unpg 5 0.9132 22330.5 1 4 CACCTG CTAATTAAC - +4 cisbp__M5551-Abd-B-cad-eve 6 0.9132 22330.5 1 3 CACCTG TTTTATTAC + +4 hocomoco__FOS_HUMAN.H11MO.0.A-GATAe-Jra-Myc-cnc-grn-kay-mor-pan-pnr 6 0.9132 22330.5 1 3 CACCTG GTGACTCAC + +4 taipale_cyt_meth__ZNF384_TTTTTNNNNNNNNNNNNAAAAA_eDBD_repr-rn-sqz 5 0.913514 22338.2 1 6 CACCTG TTTTTCTCCACTGACGGAAAAA - +4 tfdimers__MD00390-NfI 4 0.913599 22340.2 1 6 CACCTG TTTTTTCTTGGCACTAATCCCATTTTAT + +4 tfdimers__MD00396-Stat92E 1 0.913599 22340.2 1 6 CACCTG ATAAATTGTGAAATAAGGAAATAAAAAA - +4 flyfactorsurvey__h_SANGER_5_FBgn0001168-Sidpn-dpn-h 2 0.914038 22351 1 6 CACCTG GGCACGCGCC + +4 neph__UW.Motif.0084 4 0.914038 22351 1 6 CACCTG CACTGCCCTC + +4 predrem__nrMotif868 2 0.914038 22351 1 6 CACCTG TTTGTCTGCA + +4 scertf__zhu.NHP6A 3 0.914038 22351 1 6 CACCTG CTATATATAA + +4 taipale__SMAD3_DBD_YGTCTAGACA_repr-Mad-Smox 0 0.914038 22351 1 6 CACCTG CGTCTAGACA + +4 transfac_pro__M05022 1 0.914038 22351 1 6 CACCTG ATGCCGCCTC + +4 transfac_pro__M05024 4 0.914038 22351 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05037 4 0.914038 22351 1 6 CACCTG ATGCCGCCCC + +4 transfac_pro__M05038 4 0.914038 22351 1 6 CACCTG ATGCCGCCCC + +4 transfac_pro__M05095 4 0.914038 22351 1 6 CACCTG AGGCCGCCCC + +4 transfac_pro__M05134 4 0.914038 22351 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M05143 4 0.914038 22351 1 6 CACCTG ATGCCGCCGA + +4 yetfasco__YDR207C_2239 1 0.914038 22351 1 6 CACCTG TAGCCGCCGA + +4 hocomoco__NR0B1_HUMAN.H11MO.0.D 2 0.914038 22351 1 6 CACCTG TCTCCCACGC - +4 predrem__nrMotif1331 0 0.914038 22351 1 6 CACCTG TGACTGCATT - +4 predrem__nrMotif295 0 0.914038 22351 1 6 CACCTG TTCCATTTTT - +4 predrem__nrMotif341 4 0.914038 22351 1 6 CACCTG AAAGCATTTT - +4 predrem__nrMotif497 4 0.914038 22351 1 6 CACCTG TGGCTTCATT - +4 taipale__BHLHE23_DBD_ANCATATGNT-amos-ato-dimm-Fer3-HLH54F-Oli-tap-twi 0 0.914038 22351 1 6 CACCTG AACATATGGT - +4 transfac_pro__M01211-Parp 4 0.914038 22351 1 6 CACCTG CTATTTCCTA - +4 transfac_pro__M09567 3 0.914038 22351 1 6 CACCTG AACGACAAAA - +4 cisbp__M2192 5 0.914038 22351 1 5 CACCTG TTCTTTAATT + +4 transfac_pro__M03189 5 0.914038 22351 1 5 CACCTG ACGCCGCCCG + +4 transfac_pro__M05107 5 0.914038 22351 1 5 CACCTG AGGCCGCCCA + +4 transfac_pro__M07520-Hcf-tna 5 0.914038 22351 1 5 CACCTG GGCGCCGCCG + +4 cisbp__M5295-B-H1-B-H2-lab-NK7.1-pb-Ubx-unpg -1 0.914038 22351 1 5 CACCTG AGCAATTAAC - +4 cisbp__M6334-cnc-Jra-maf-S-tj -1 0.914038 22351 1 5 CACCTG TGCTGAGTCA - +4 taipale__BARHL2_DBD_NNTAATTGNN-B-H1-B-H2-lab-NK7.1-pb-Ubx-unpg -1 0.914038 22351 1 5 CACCTG AGCAATTAAC - +4 cisbp__M5556-abd-A-Abd-B-cad-Dbx-eve-Ubx 6 0.914038 22351 1 4 CACCTG TTTTATTACC + +4 cisbp__M5599-al-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-dve-E5-ems-en-eve-ind-inv-lab-lbe-Lim3-OdsH-otp-pb-pdm3-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2-zfh2 6 0.914038 22351 1 4 CACCTG ACTAATTAGC + +4 fantom__motif78_NCGNWGCAWN 6 0.914038 22351 1 4 CACCTG TCGAAGCAAC + +4 hocomoco__NKX21_MOUSE.H11MO.0.A-scro -2 0.914038 22351 1 4 CACCTG TCTTGAGTGG + +4 jaspar__MA0279.1 6 0.914038 22351 1 4 CACCTG ATTAGTAAGC + +4 taipale__LHX6_full_NYTAATTARN-al-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-dve-E5-ems-en-eve-inv-lab-lbe-Lim3-OdsH-otp-pb-pdm3-repo-ro-Rx-slou-unpg-Vsx1-Vsx2-zfh2 6 0.914038 22351 1 4 CACCTG ACTAATTAGC + +4 taipale_cyt_meth__LBX2_NCYAATTANN_eDBD-al-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-Dr-dve-E5-ems-en-eve-ey-inv-lab-lbe-lms-OdsH-otp-pb-PHDP-Pph13-repo-ro-Rx-slou-toy-Ubx-unc-4-unpg-Vs 6 0.914038 22351 1 4 CACCTG CCTAATTAAC + +4 cisbp__M2084 6 0.914038 22351 1 4 CACCTG ATTAGTAAGC - +4 fantom__motif152_GCKYRMKCGS 6 0.914038 22351 1 4 CACCTG GCGAGTGAGC - +4 taipale__HOXD11_DBD_NGYAATAAAA-abd-A-Abd-B-cad-Dbx-eve-Ubx 6 0.914038 22351 1 4 CACCTG TTTTATTACC - +4 transfac_pro__M05023 7 0.914038 22351 1 3 CACCTG AGGCCGCCAC + +4 cisbp__M4694-Mef2 -3 0.914038 22351 1 3 CACCTG CTATTTATAG - +4 predrem__nrMotif1382 -3 0.914038 22351 1 3 CACCTG CTGGCTGGCT - +4 tfdimers__MD00546-cnc 14 0.914674 22366.5 1 6 CACCTG AGTTAATCATTAATTAACTAATAATTT + +4 tfdimers__MD00101 16 0.914727 22367.8 1 6 CACCTG ATATTAATTGGGATAAAAATATT + +4 yetfasco__YGL254W_69-CG3065-hkb 7 0.914727 22367.8 1 6 CACCTG CTATTGTTGCCTTATACGATACG - +4 taipale_cyt_meth__POU6F1_NATTATNNNNNNNATAATN_FL_repr-pdm3 10 0.915208 22379.6 1 6 CACCTG CATTATGCTCCGCATAATG + +4 taipale_cyt_meth__NEUROD1_AAWTANNNNNNCATATGNN_FL_meth-amos-ato-da-HLH54F-Oli-tap 9 0.915208 22379.6 1 6 CACCTG GACATATGTCGCGCTATTT - +4 taipale_cyt_meth__ZNF23_NKKKCGCGGNCATGGKNGN_eDBD_meth-crol 1 0.915208 22379.6 1 6 CACCTG ACACCCATGGCCGCGCCCC - +4 transfac_pro__M09017 2 0.915208 22379.6 1 6 CACCTG TTTTGCTTATTTTTTGCTT - +4 transfac_pro__M09148 15 0.915208 22379.6 1 4 CACCTG CATCATCATCATCATCATC + +4 tfdimers__MD00389 2 0.915349 22383 1 6 CACCTG AAATAATTGTGTAATGATTAACTAAT - +4 taipale_tf_pairs__GCM1_SPDEF_RTRSKGGCGGANNNNNNATCCNNN_CAP_repr-Ets98B-gcm-gcm2 17 0.915408 22384.5 1 6 CACCTG GTGCGGGCGGATGTCGCATCCGGG + +4 tfdimers__MD00458-pho-phol-sens-2 18 0.915408 22384.5 1 6 CACCTG TAATTCCATAATCCCTTCTTTTTT + +4 tfdimers__MD00462-Sox100B-zfh1 2 0.915408 22384.5 1 6 CACCTG ATTTCCTTTGTGGTTTCTGTTTTT + +4 taipale_cyt_meth__ZSCAN1_NYRCACACMCTGMAAMN_eDBD_meth 6 0.915469 22386 1 6 CACCTG CTGCACACCCTGAAAAT + +4 transfac_pro__M01465-Dfd-Lim1-Lim3-vvl 11 0.915469 22386 1 6 CACCTG GATTAATTAATTAAGTC + +4 transfac_pro__M07871-Poxn 11 0.915469 22386 1 6 CACCTG GGCGTGACGGTCACGGT + +4 jaspar__MA0896.1-Hmx 1 0.915469 22386 1 6 CACCTG ATTCATTAATTGCTTGT - +4 transfac_pro__M01351-bab1-cad 11 0.915469 22386 1 6 CACCTG ATTAATTTTATGGCCGT - +4 transfac_pro__M01375-cad 11 0.915469 22386 1 6 CACCTG ATAAATTTTATTGCATT - +4 transfac_pro__M01474-al-ap-Awh-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-inv-Lim3-OdsH-otp-pdm3-Pph13-repo-Rx-slou-unc-4-unpg-Vsx1-zfh2 9 0.915469 22386 1 6 CACCTG TCAATTAATTAATGGAT - +4 transfac_pro__M01481-Hmx 1 0.915469 22386 1 6 CACCTG ATTCATTAATTGCTTGT - +4 jaspar__MA0897.1-Hmx -1 0.915469 22386 1 5 CACCTG ATTCTTTAATTGCTTGT - +4 hocomoco__MTF1_HUMAN.H11MO.0.C-MTF-1 13 0.915469 22386 1 4 CACCTG GTTTTGCACACGGCACT - +4 tfdimers__MD00566 20 0.91547 22386 1 6 CACCTG ATAAAAAAAAATTAAGAAATCATTTAAAAAAT + +4 cisbp__M3178-klu-sr 1 0.916784 22418.1 1 6 CACCTG ATGCGTGGGCGT + +4 homer__TAATCHGATTAC_Pax7-Gsc-gsb-gsb-n-prd 1 0.916784 22418.1 1 6 CACCTG TAATCCGATTAC + +4 tiffin__TIFDMEM0000057 4 0.916784 22418.1 1 6 CACCTG GCGCTGCCAACC + +4 transfac_pro__M06930-Dad 5 0.916784 22418.1 1 6 CACCTG TTGCCCGCCATA + +4 transfac_pro__M06933-Dad 5 0.916784 22418.1 1 6 CACCTG TTGCCCGCCATA + +4 transfac_public__M00245-klu-sr 1 0.916784 22418.1 1 6 CACCTG ATGCGTGGGCGT + +4 transfac_public__M00254-Nf-YA-Nf-YB-Nf-YC 3 0.916784 22418.1 1 6 CACCTG ACTAGCCAATCA + +4 homer__GAAAGTGAAAGT_IRF1-Blimp-1-Dif-Stat92E-dl-ebi 5 0.916784 22418.1 1 6 CACCTG ACTTTCACTTTC - +4 neph__UW.Motif.0308 5 0.916784 22418.1 1 6 CACCTG TGTCATTTTTCA - +4 taipale_cyt_meth__LBX2_CTMATTAATTAN_eDBD-ap-Awh-CG34367-HGTX-lab-lbl-Lim3 5 0.916784 22418.1 1 6 CACCTG CTAATTAATTAG - +4 transfac_pro__M05811 6 0.916784 22418.1 1 6 CACCTG TCAAATCAACAA - +4 transfac_pro__M05948 6 0.916784 22418.1 1 6 CACCTG GCGTTCTTCCAC - +4 transfac_pro__M06089 0 0.916784 22418.1 1 6 CACCTG TACCCTTGATTG - +4 transfac_pro__M06239 6 0.916784 22418.1 1 6 CACCTG GAAAAATGACTC - +4 transfac_pro__M06348 6 0.916784 22418.1 1 6 CACCTG GCTTATTCCATG - +4 transfac_pro__M06505 6 0.916784 22418.1 1 6 CACCTG AATTTACTCCAC - +4 transfac_pro__M06636 5 0.916784 22418.1 1 6 CACCTG GCCCACACTCTG - +4 cisbp__M6314 7 0.916784 22418.1 1 5 CACCTG GAAAGCGAAACT + +4 predrem__nrMotif540 7 0.916784 22418.1 1 5 CACCTG AAACAAAAAACA + +4 taipale_cyt_meth__CEBPE_NRTTGCGYAAYN_eDBD-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 7 0.916784 22418.1 1 5 CACCTG TGTTGCGCAATG + +4 transfac_pro__M05616 -1 0.916784 22418.1 1 5 CACCTG CCTTGGATCAGA + +4 transfac_pro__M06223-CG2120 7 0.916784 22418.1 1 5 CACCTG TCGTCTTTCCCA - +4 transfac_pro__M06591 7 0.916784 22418.1 1 5 CACCTG TCTTCTATCCCA - +4 transfac_pro__M05649 8 0.916784 22418.1 1 4 CACCTG TGGGGCTGCAGC + +4 cisbp__M4354 8 0.916784 22418.1 1 4 CACCTG CTATTAGTAAGC - +4 taipale__HOXA10_DBD_NGTCGTWAAANN-Abd-B 8 0.916784 22418.1 1 4 CACCTG ATTTTTACGACC - +4 transfac_pro__M06463 8 0.916784 22418.1 1 4 CACCTG GCGGCCGCCCCC - +4 taipale_cyt_meth__LBX2_CTMATTAATTAN_eDBD_meth_repr-Scr-zen2 -3 0.916784 22418.1 1 3 CACCTG CTCATTAATTAT + +4 hdpi__DLX6-Dll 0 0.91819 22452.5 1 6 CACCTG TAAATG + +4 scertf__macisaac.YHP1 0 0.91819 22452.5 1 6 CACCTG TAATTG + +4 fantom__motif21_TCTTGA -2 0.91819 22452.5 1 4 CACCTG TCTTGA + +4 hdpi__C19orf40 -2 0.91819 22452.5 1 4 CACCTG CATTGG - +4 hdpi__GADD45A -4 0.91819 22452.5 1 2 CACCTG TGAAAA + +4 flyfactorsurvey__Unc4_Cell_FBgn0024184-OdsH-Vsx2-en-lms-unc-4 2 0.918258 22454.2 1 6 CACCTG CTTAATTG + +4 predrem__nrMotif1245 0 0.918258 22454.2 1 6 CACCTG TGCGTGGC + +4 predrem__nrMotif1250 0 0.918258 22454.2 1 6 CACCTG TATATGCA + +4 taipale_cyt_meth__BARHL2_NTAATTGN_FL_meth-B-H1-B-H2-CG11085-Dr-en-inv-lms-unpg 1 0.918258 22454.2 1 6 CACCTG CTAATTGC + +4 taipale_cyt_meth__ISX_CTAATTAN_eDBD-al-ap-Awh-C15-CG11294-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-lbe-Lim1-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-slou-toy-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.918258 22454.2 1 6 CACCTG CTAATTAA + +4 transfac_pro__M08976-D-Sox100B-Sox102F-Sox15-SoxN 0 0.918258 22454.2 1 6 CACCTG AACAATAG + +4 predrem__nrMotif1002 2 0.918258 22454.2 1 6 CACCTG GAAGCATT - +4 taipale_cyt_meth__DLX5_NYAATTAN_eDBD-bsh-Dll-Dr-Lim1 1 0.918258 22454.2 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__EN1_NYAATTAN_eDBD_meth-Antp-B-H1-B-H2-bsh-C15-CG18599-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-lms-OdsH-pb-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.918258 22454.2 1 6 CACCTG CTAATTGG - +4 taipale_cyt_meth__TLX2_NCAATTAN_eDBD_meth-al-Awh-C15-CG18599-CG34367-CG9876-Dr-en-foxo-gsb-gsb-n-inv-lbe-Lim3-lms-OdsH-Pph13-prd-repo-Rx-unc-4-unpg-Vsx2 1 0.918258 22454.2 1 6 CACCTG CTAATTGA - +4 cisbp__M0043 3 0.918258 22454.2 1 5 CACCTG CGCCGCCA + +4 cisbp__M0744-bin-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-FoxP-slp1-slp2 3 0.918258 22454.2 1 5 CACCTG ATAAACAA + +4 cisbp__M1069-Ptx1 3 0.918258 22454.2 1 5 CACCTG TTAATCCC + +4 cisbp__M1172 -1 0.918258 22454.2 1 5 CACCTG ACCAATCA + +4 cisbp__M1251-Hsf -1 0.918258 22454.2 1 5 CACCTG TTCTAGAA + +4 predrem__nrMotif1535 3 0.918258 22454.2 1 5 CACCTG TTTATCCA + +4 predrem__nrMotif360 3 0.918258 22454.2 1 5 CACCTG TCCAAAAT + +4 taipale_cyt_meth__OTX2_NTAATCCN_FL_meth-Gsc-oc-Ptx1 3 0.918258 22454.2 1 5 CACCTG CTAATCCC + +4 yetfasco__YLR266C_244 -1 0.918258 22454.2 1 5 CACCTG TCCTCGGA + +4 cisbp__M0593 3 0.918258 22454.2 1 5 CACCTG ATTCAAAT - +4 cisbp__M4347 -1 0.918258 22454.2 1 5 CACCTG TCCACGGA - +4 flyfactorsurvey__Exd_SOLEXA_FBgn0000611-exd 3 0.918258 22454.2 1 5 CACCTG TGTCAAAA - +4 predrem__nrMotif2612 3 0.918258 22454.2 1 5 CACCTG TGCTAACA - +4 transfac_pro__M04609 -1 0.918258 22454.2 1 5 CACCTG GATTTCCA - +4 cisbp__M5261-Antp-ap-Awh-CG11294-CG32532-CG9876-Dll-E5-ems-en-lab-Lim1-Lim3-lms-otp-Pph13-ro-Rx-Scr-slou-unpg-Vsx1-zen2 -2 0.918258 22454.2 1 4 CACCTG CTTAATTA + +4 cisbp__M0552 -2 0.918258 22454.2 1 4 CACCTG CCCGCTGC - +4 cisbp__M0838-Gsc-Ptx1-bcd-oc 4 0.918258 22454.2 1 4 CACCTG GGATTAAC - +4 cisbp__M4827-C15-CG15696-CG32532-CG34031-en-lms-slou-Ubx-unpg 4 0.918258 22454.2 1 4 CACCTG CAATTAAA - +4 cisbp__M4828-CG15696-CG32532-CG34031-en-lms-slou-Ubx-unpg 4 0.918258 22454.2 1 4 CACCTG CAATTAAA - +4 flyfactorsurvey__CG15696_Cell_FBgn0038833-C15-CG15696-CG32532-CG34031-Ubx-en-lms-slou-unpg 4 0.918258 22454.2 1 4 CACCTG TAATTAAA - +4 flyfactorsurvey__CG15696_SOLEXA_FBgn0038833-CG15696-CG32532-CG34031-Ubx-en-lms-slou-unpg 4 0.918258 22454.2 1 4 CACCTG CAATTAAA - +4 predrem__nrMotif2313 -2 0.918258 22454.2 1 4 CACCTG CATTGAAT - +4 cisbp__M6052-abd-A-btn-lab-lbl-Lim3-Scr-Ubx 5 0.918258 22454.2 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXB5_NTAATTAN_FL_meth-Antp-btn-E5-ems-eve-exex-lab-pb-Scr-slou 5 0.918258 22454.2 1 3 CACCTG GTAATTAC + +4 cisbp__M0736-bin-CHES-1-like-croc-fd102C-fd19B-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 5 0.918258 22454.2 1 3 CACCTG TTGTTTAC - +4 cisbp__M1146-CG9876-CG11294-CG32532-Lim1-Lim3-Lmx1a-Pph13-Rx-Vsx1-ap-btn-lab-otp-repo-ro 5 0.918258 22454.2 1 3 CACCTG TTAATTAC - +4 taipale_cyt_meth__HOXB5_NTAATTAN_FL-Antp-btn-E5-ems-en-eve-exex-inv-lab-Lim3-pb-Scr-slou-zen2 5 0.918258 22454.2 1 3 CACCTG GTAATTAC - +4 taipale_cyt_meth__HOXD1_NTAATTAN_eDBD-Antp-Awh-bsh-btn-Dfd-E5-ems-en-eve-exex-inv-lab-Lim3-pb-Scr-slou 5 0.918258 22454.2 1 3 CACCTG GTAATTAC - +4 taipale_cyt_meth__NKX6-2_NTCATTAN_FL_meth-bsh-btn-Dll-HGTX 5 0.918258 22454.2 1 3 CACCTG TTAATGAC - +4 transfac_pro__M00318 -3 0.918258 22454.2 1 3 CACCTG CTTTATTG - +4 transfac_pro__M01241 6 0.918258 22454.2 1 2 CACCTG CAGCGACA + +4 dbcorrdb__ELK4__ENCSR000EVB_1__m1-Atac3-Brf-brm-E2f1-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-HDAC1-Hr78-Max-Nelf-E-pnt-RpII215-Sin3A-SREBP-Taf1-tna-vtd 14 0.918264 22454.3 1 6 CACCTG CCACTTCCGGCCGCGGCCCC + +4 dbcorrdb__EZH2__ENCSR000ASY_1__m4-E(z) 13 0.918264 22454.3 1 6 CACCTG TCGCACAACGAAAGGCCGGT + +4 dbcorrdb__SMARCC2__ENCSR000EDL_1__m2-mor-Six4 2 0.918264 22454.3 1 6 CACCTG ACTACAAGTCCCAGAGGCCC + +4 dbcorrdb__ZNF143__ENCSR000EGP_1__m3-CrebB-Eip74EF-Hcf-Myc-RpII215-Sin3A 5 0.918264 22454.3 1 6 CACCTG GGACGGCGCTTCCGCGCCCA + +4 transfac_pro__M01786 12 0.918264 22454.3 1 6 CACCTG TTTAGGGCTATAGCCCTAAT + +4 cisbp__M4459-Brf-brm-btd-CG42741-CoRest-crol-ct-CTCF-E2f1-ERR-E(z)-HDAC1-klu-Nelf-E-Rbbp5-RpII215-sd-Spps-Spt20-sr-SREBP-tna-vtd 2 0.918264 22454.3 1 6 CACCTG CCCCCCCCCCGCCCCCGCAC - +4 cisbp__M4616-Brf-brm-btd-CoRest-crol-ct-CTCF-ERR-E(z)-HDAC1-klu-luna-Nelf-E-Rbbp5-RpII215-sd-Spps-Spt20-sr-SREBP-tna-vtd 0 0.918264 22454.3 1 6 CACCTG CCCCCCCCCCCGCCCACGCA - +4 dbcorrdb__BRCA1__ENCSR000DZS_1__m1-Chd1-CoRest 0 0.918264 22454.3 1 6 CACCTG CCCCGGCTCTCGCGAGATTT - +4 dbcorrdb__BRCA1__ENCSR000EDY_1__m1-Chd1-CoRest 10 0.918264 22454.3 1 6 CACCTG GGTCTCGCGAGAGCCGGGGG - +4 dbcorrdb__FOS__ENCSR000EYZ_1__m1-btd-Chd1-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP 0 0.918264 22454.3 1 6 CACCTG CGGCCTCCGATTGGCCGGCG - +4 dbcorrdb__NR3C1__ENCSR000EEV_1__m2 12 0.918264 22454.3 1 6 CACCTG GCGCCGCGAGAGCGGCCGCG - +4 dbcorrdb__REST__ENCSR000BMN_1__m3-Brf-brm-btd-CG7368-CoRest-crol-ct-CTCF-Dif-dl-HDAC1-Klf15-klu-l(3)neo38-Nelf-E-peb-Rbbp5-Spps-Spt20-sr-SREBP-vtd 9 0.918264 22454.3 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 dbcorrdb__SMARCB1__ENCSR000EHN_1__m2-kay-Snr1 2 0.918264 22454.3 1 6 CACCTG CTGGGCTGAGTCATCATGAC - +4 dbcorrdb__TBP__ENCSR000ECB_1__m2-Tbp 1 0.918264 22454.3 1 6 CACCTG TCTCGCGTCGGCCGCGCTAC - +4 hocomoco__ZFP28_HUMAN.H11MO.0.C 1 0.918264 22454.3 1 6 CACCTG TGACACAAGAAGAAATAGAA - +4 homer__NTAATTDGCYAATTANNWWD_Pax7-CG9876-CG34367-E5-bsh-ems-en-gsb-gsb-n-inv-pdm3-prd-unpg 5 0.918264 22454.3 1 6 CACCTG TTTTTTAATTAGCTAATTAA - +4 transfac_pro__M05717 7 0.918264 22454.3 1 6 CACCTG GGGGCCCCACTTTTTAATCC - +4 dbcorrdb__JUND__ENCSR000EYV_1__m1-ebi-foxo-Jra-Mef2-MTA1-like-nej-NFAT-Stat92E -1 0.918264 22454.3 1 5 CACCTG AGATGAGTCATATCGAAACT - +4 transfac_public__M00006-Mef2-rump 9 0.918381 22457.2 1 6 CACCTG CTCTAAAAATAACTCT + +4 homer__NNTGTTTATTTTGGCA_NF1_FOXA1-Nf1-croc-fd59A-fkh-nej 10 0.918381 22457.2 1 6 CACCTG TGCCAAAATAAACAAA - +4 taipale_tf_pairs__POU2F1_SOX15_NNNGMATAACAAWRRN_CAP_repr-nub-pdm2 10 0.918381 22457.2 1 6 CACCTG TCCATTGTTATGCATG - +4 transfac_pro__M01723 11 0.918381 22457.2 1 5 CACCTG ATAAATAATGATACAA + +4 hdpi__SSX3 1 0.918578 22462 1 4 CACCTG TTTCC - +4 cisbp__M4802-CG10904 7 0.919387 22481.8 1 6 CACCTG TTTTTCTCTCATG + +4 cisbp__M6089-D-Sox21a-Sox21b-SoxN 5 0.919387 22481.8 1 6 CACCTG TCAATAACATTGA + +4 cisbp__M6296-abd-A-Ubx 0 0.919387 22481.8 1 6 CACCTG TGCATCAATCATT + +4 hocomoco__HXA11_HUMAN.H11MO.0.D-Abd-B 1 0.919387 22481.8 1 6 CACCTG TAAAATTTTATGA + +4 swissregulon__hs__CRX.p2 5 0.919387 22481.8 1 6 CACCTG TCATTAATCCCAT + +4 taipale__Sox1_DBD_TCAATWNCATTGA_repr-D-Sox21a-Sox21b-SoxN 5 0.919387 22481.8 1 6 CACCTG TCAATAACATTGA + +4 cisbp__M3640-HGTX 0 0.919387 22481.8 1 6 CACCTG AACCAATTAAAAA - +4 hocomoco__LHX3_HUMAN.H11MO.0.C-Awh-CG11294-CG32532-E5-HGTX-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-ap-ems-otp-pdm3-repo-ro-unc-4-unpg-vvl 6 0.919387 22481.8 1 6 CACCTG ATTAATTAATTTT - +4 taipale_cyt_meth__MAFA_NWWWNTGCTGACN_eDBD-maf-S-tj 3 0.919387 22481.8 1 6 CACCTG CGTCAGCACATTT - +4 taipale_cyt_meth__POU3F2_NTAATTWATGCRN_eDBD-dve-pdm3-vvl 1 0.919387 22481.8 1 6 CACCTG ATGCATAAATTAG - +4 transfac_public__M00424-HGTX 0 0.919387 22481.8 1 6 CACCTG AACCAATTAAAAA - +4 transfac_pro__M03875 8 0.919387 22481.8 1 5 CACCTG TTTTCGCTTTCCT + +4 transfac_pro__M07424-Mef2-rump 8 0.919387 22481.8 1 5 CACCTG TCTAAAAATAGCC - +4 predrem__nrMotif2353 -2 0.919387 22481.8 1 4 CACCTG CCTCCCCGTCCCC + +4 transfac_pro__M07244 -2 0.919387 22481.8 1 4 CACCTG CTTGCTCTCCAAG + +4 flyfactorsurvey__CG7745_SANGER_5_FBgn0033616-Awh-CG7745-CG18599-E5-Lim3-Pph13-Vsx1-ap-ems-en-inv-otp 6 0.920031 22497.5 1 6 CACCTG ATTAATTAAACGCAC + +4 transfac_pro__M07048-cnc-Jra-maf-S 8 0.920031 22497.5 1 6 CACCTG CCATGACTCAGCAGA + +4 transfac_pro__M09146 4 0.920031 22497.5 1 6 CACCTG TCTCAACCGTTGGAT + +4 transfac_public__M00459-Stat92E 3 0.920031 22497.5 1 6 CACCTG GATTTCCTGGAATTT + +4 cisbp__M3990-Stat92E 3 0.920031 22497.5 1 6 CACCTG GATTTCCTGGAATTT - +4 cisbp__M4537-E2f1-E2f2-Sin3A 3 0.920031 22497.5 1 6 CACCTG TTCAAATTTCCCGCC - +4 cisbp__M4879-ap-Awh-CG18599-CG7745-E5-ems-en-inv-Lim3-otp-Pph13-Vsx1 6 0.920031 22497.5 1 6 CACCTG ATTAATTAAACGCAC - +4 taipale_cyt_meth__POU2F2_NCATTANNNTAATGN_eDBD_repr-nub-pdm2 4 0.920031 22497.5 1 6 CACCTG TCATTAGCATAATGC - +4 taipale_tf_pairs__ETV7_NNYTTCCGGGAARNR_HT-aop 3 0.920031 22497.5 1 6 CACCTG CATTTCCCGGAAATG - +4 transfac_pro__M02246-CG9650-nej-pan-SoxN 2 0.920031 22497.5 1 6 CACCTG TTTGCATAACAAAGG - +4 transfac_pro__M09194-E2f1-E2f2 10 0.920031 22497.5 1 5 CACCTG TTTTGGCGCCAAAAT - +4 hocomoco__IRF4_MOUSE.H11MO.0.A-CG9650-MTA1-like-Stat92E-ebi-nej-sv 8 0.920087 22498.9 1 6 CACCTG AGTTTCAGTTCCTCTTTT - +4 hocomoco__LHX9_HUMAN.H11MO.0.D-Awh-C15-CG9876-CG18599-CG34367-Dbx-Dll-E5-Lim3-OdsH-Rx-Vsx1-Vsx2-al-ems-en-eve-gsb-gsb-n-ind-inv-lab-lbe-otp-pdm3-prd-ro-unpg 7 0.920087 22498.9 1 6 CACCTG TAATTAATAGCTAATTAG - +4 transfac_pro__M06892 0 0.920087 22498.9 1 6 CACCTG GACGCGTCGAACCATTCC - +4 transfac_pro__M06745 -1 0.920087 22498.9 1 5 CACCTG CCCTTCATCCATTCTTCC - +4 transfac_pro__M08882-croc 4 0.920406 22506.7 1 6 CACCTG TCTAAACAAGAAGA + +4 flyfactorsurvey__Hsf_FlyReg_FBgn0001222-Hsf 3 0.920406 22506.7 1 6 CACCTG TCGAATCTTCTAGA - +4 flyfactorsurvey__pho_FlyReg_FBgn0002521-pho 7 0.920406 22506.7 1 6 CACCTG GAAGCCATAACGGC - +4 flyfactorsurvey__sug_SANGER_5_FBgn0033782-lmd-opa-sug 5 0.920406 22506.7 1 6 CACCTG AAGACCCCCCGCGG - +4 taipale_cyt_meth__ATF4_GGATGATGTCATCC_eDBD_meth-Atf3-Atf6-crc-Jra-kay-Xbp1 4 0.920406 22506.7 1 6 CACCTG GGATGACATCATCC - +4 transfac_pro__M01220-Stat92E 5 0.920406 22506.7 1 6 CACCTG GGATTTCCCGGCAA - +4 hocomoco__OLIG1_HUMAN.H11MO.0.D-HLH54F-Oli-amos-ato-crp-tap-twi -1 0.920406 22506.7 1 5 CACCTG ACCATATGTTTTTT + +4 transfac_pro__M04683-btd-CG7839-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps -1 0.920406 22506.7 1 5 CACCTG CTCTGATTGGCTGG + +4 factorbook__UA5-Spps-btd -1 0.920406 22506.7 1 5 CACCTG GGCTAGAGCGGCCC - +4 hocomoco__NFYA_HUMAN.H11MO.0.A-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay-yps -1 0.920406 22506.7 1 5 CACCTG TTCTGATTGGCTGA - +4 cisbp__M5442-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.920406 22506.7 1 4 CACCTG TGTCAATATTTACA + +4 taipale_tf_pairs__FOXJ2_HOXB13_TTTWATNRNMAACA_CAP_repr 10 0.920406 22506.7 1 4 CACCTG TTTTATTATCAACA + +4 transfac_public__M00209-Nf-YA-Nf-YB-Nf-YC -2 0.920406 22506.7 1 4 CACCTG TCTGATTGGCTAGT + +4 taipale__FOXC2_DBD_NRTMAATATTKAYN-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.920406 22506.7 1 4 CACCTG TGTCAATATTTACA - +4 cisbp__M5076-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dr-E5-ems-en-eve-ey-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou-toy-Traf4-Ubx-un 1 0.920491 22508.8 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Otp_SOLEXA_FBgn0015524-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-ems-en-eve-e 1 0.920491 22508.8 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Unpg_SOLEXA_FBgn0015561-Antp-Awh-C15-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-e 1 0.920491 22508.8 1 6 CACCTG TTAATTA + +4 hdpi__RAX 0 0.920491 22508.8 1 6 CACCTG AAACTGA + +4 jaspar__MA0196.1-CG32532-CG34367-NK7.1-Ubx-abd-A-en-lms-slou-tup-unpg 1 0.920491 22508.8 1 6 CACCTG TTAATTG + +4 predrem__nrMotif504 1 0.920491 22508.8 1 6 CACCTG TTACAAA + +4 cisbp__M2005-abd-A-CG32532-CG34367-en-lms-NK7.1-slou-tup-Ubx-unpg 0 0.920491 22508.8 1 6 CACCTG CAATTAA - +4 cisbp__M2204 0 0.920491 22508.8 1 6 CACCTG CGCGGGG - +4 predrem__nrMotif1171 1 0.920491 22508.8 1 6 CACCTG TGACTTA - +4 predrem__nrMotif383 1 0.920491 22508.8 1 6 CACCTG ATAGCAA - +4 scertf__zhu.RDR1 0 0.920491 22508.8 1 6 CACCTG TATCCGC - +4 predrem__nrMotif1752 3 0.920491 22508.8 1 4 CACCTG GGCTACA + +4 predrem__nrMotif2255 3 0.920491 22508.8 1 4 CACCTG AGAAGCC + +4 elemento__ACAATGG -2 0.920491 22508.8 1 4 CACCTG CCATTGT - +4 elemento__CCAATGG -2 0.920491 22508.8 1 4 CACCTG CCATTGG - +4 cisbp__M2032-E5-ems-exex-lab-Lim3 4 0.920491 22508.8 1 3 CACCTG TAATTAC - +4 flyfactorsurvey__Lim3_SOLEXA_FBgn0002023-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-ey-hbn-ind-inv-lab-l 4 0.920491 22508.8 1 3 CACCTG TAATTAA - +4 jaspar__MA0224.1-E5-Lim3-ems-exex-lab 4 0.920491 22508.8 1 3 CACCTG TAATTAC - +4 jaspar__MA0468.1-CG32532-Traf4 0 0.920561 22510.5 1 6 CACCTG TAATTTAATCA + +4 scertf__macisaac.URC2 1 0.920561 22510.5 1 6 CACCTG TCTCCGGCGGA + +4 transfac_pro__M00778-ss 2 0.920561 22510.5 1 6 CACCTG CTTGCGTGCGC + +4 transfac_pro__M07775-al-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-E5-ems-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.920561 22510.5 1 6 CACCTG TAATCTAATTA + +4 transfac_pro__M09242 5 0.920561 22510.5 1 6 CACCTG TCAATCATTGG + +4 transfac_pro__M09243 4 0.920561 22510.5 1 6 CACCTG TCAATAATTGA + +4 cisbp__M5739-pdm3-vvl 0 0.920561 22510.5 1 6 CACCTG TAATTTATGCA - +4 hocomoco__ISL2_HUMAN.H11MO.0.D-Hmx-en-tup 2 0.920561 22510.5 1 6 CACCTG AGCAATTAACG - +4 predrem__nrMotif1102 1 0.920561 22510.5 1 6 CACCTG TTTCCATTCTT - +4 predrem__nrMotif939 0 0.920561 22510.5 1 6 CACCTG TGTCTTTTTTT - +4 taipale_cyt_meth__ALX1_TAATTAGATTA_FL-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.920561 22510.5 1 6 CACCTG TAATCTAATTA - +4 transfac_pro__M05175 1 0.920561 22510.5 1 6 CACCTG TATCCCAATTT - +4 taipale_cyt_meth__HOXB13_NCCAATAAAAN_eDBD -1 0.920561 22510.5 1 5 CACCTG CCCAATAAAAC + +4 taipale_tf_pairs__PBX4_HOXA1_NYNATMAATCA_CAP_repr-exd-lab 6 0.920561 22510.5 1 5 CACCTG GCCATCAATCA + +4 transfac_pro__M07810-B-H1-B-H2-Dr-Hmx-lab-NK7.1-unpg -1 0.920561 22510.5 1 5 CACCTG AGCAATTAACG + +4 flyfactorsurvey__sens_SOLEXA_F1-3-sens-sens-2 6 0.920561 22510.5 1 5 CACCTG ATAAATCACAG - +4 transfac_pro__M05112-SREBP 7 0.920561 22510.5 1 4 CACCTG ATCACGCCACT + +4 cisbp__M5558-Abd-B 7 0.920561 22510.5 1 4 CACCTG TTTTTACGACT - +4 taipale__HOXD12_DBD_NGTCGTAAAAN-Abd-B 7 0.920561 22510.5 1 4 CACCTG TTTTTACGACT - +4 taipale_cyt_meth__HOXA10_NGTCGTAAAAN_FL-Abd-B-cad 7 0.920561 22510.5 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__HOXC11_RGYAATAAAAN_eDBD_meth-abd-A-Abd-B-cad-eve-Ubx 7 0.920561 22510.5 1 4 CACCTG GTTTTATGACC - +4 transfac_pro__M05461 8 0.920561 22510.5 1 3 CACCTG ATTTATGGCAC + +4 cisbp__M6009-croc-foxo-slp1 8 0.920561 22510.5 1 3 CACCTG TGTTTATTTAC - +4 taipale__Foxc1_DBD_GTAAAYAAACA_repr-croc-foxo-slp1 8 0.920561 22510.5 1 3 CACCTG TGTTTATTTAC - +4 tfdimers__MD00022 14 0.920614 22511.8 1 6 CACCTG ATAATTAATTTAATTAATTAT + +4 transfac_pro__M05248-ERR-E(z) 5 0.920614 22511.8 1 6 CACCTG GGGGGGGCCTGCCCGCCTCCC + +4 tfdimers__MD00414 5 0.921448 22532.2 1 6 CACCTG TTTTTTTTTTTCATTTTCACTTTCTTTTT - +4 cisbp__M1599-D-Sox100B-Sox14-Sox15-Sox21a-Sox21b 3 0.921474 22532.8 1 6 CACCTG ATTGTTTTC + +4 cisbp__M4923-Dr 0 0.921474 22532.8 1 6 CACCTG GACCAATTA + +4 predrem__nrMotif1252 0 0.921474 22532.8 1 6 CACCTG TATTTTGAT + +4 predrem__nrMotif1585 0 0.921474 22532.8 1 6 CACCTG AAAATCCAT + +4 predrem__nrMotif2626 2 0.921474 22532.8 1 6 CACCTG AACAACAGT + +4 transfac_pro__M04890 3 0.921474 22532.8 1 6 CACCTG AAATGACTG + +4 cisbp__M0999-Dll-ftz-HGTX-lab-Lim1 0 0.921474 22532.8 1 6 CACCTG GTAATTAAT - +4 predrem__nrMotif1833 0 0.921474 22532.8 1 6 CACCTG GGCCGTGGC - +4 predrem__nrMotif2395 3 0.921474 22532.8 1 6 CACCTG TCCAACAAA - +4 predrem__nrMotif1782 4 0.921474 22532.8 1 5 CACCTG CCCACTCTT + +4 predrem__nrMotif2160 4 0.921474 22532.8 1 5 CACCTG AGCAGTCCT + +4 predrem__nrMotif1050 -1 0.921474 22532.8 1 5 CACCTG CCATGGCAG - +4 predrem__nrMotif1974 -1 0.921474 22532.8 1 5 CACCTG TTCTGAGTC - +4 tiffin__TIFDMEM0000066 4 0.921474 22532.8 1 5 CACCTG AATATATTT - +4 cisbp__M1117-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dr-Lim1-Lim3-Lmx1a-OdsH-Scr-Vsx2-al-dve-en-ey-gsb-gsb-n-inv-lab-otp-pdm3-prd-repo-ro-toy-unc-4-unpg-vvl-zfh2 6 0.921474 22532.8 1 3 CACCTG ACTAATTAA + +4 cisbp__M6467-cnc-ewg-Jra-kay-maf-S-Mef2-mor-nej-pan 6 0.921474 22532.8 1 3 CACCTG CTGAGTCAC + +4 predrem__nrMotif243 -3 0.921474 22532.8 1 3 CACCTG CTGCCCGGG + +4 cisbp__M0849 1 0.92219 22550.3 1 6 CACCTG GTATTAATAC + +4 cisbp__M5481-al-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 2 0.92219 22550.3 1 6 CACCTG GCTAATTGGT + +4 cisbp__M5500-bcd-Gsc-oc-Ptx1 3 0.92219 22550.3 1 6 CACCTG GCTAATCCCT + +4 fantom__motif26_CTCCGCAGTA 0 0.92219 22550.3 1 6 CACCTG CTCCGCAGTA + +4 homer__CTCTCTCTCY_GAGA-repeat 1 0.92219 22550.3 1 6 CACCTG CTCTCTCTCT + +4 idmmpmm__D-D-SoxN 0 0.92219 22550.3 1 6 CACCTG GTCCATTGTT + +4 swissregulon__sacCer__RDS2 4 0.92219 22550.3 1 6 CACCTG GAAACCCCGA + +4 transfac_pro__M03170 4 0.92219 22550.3 1 6 CACCTG AGGCCGCCCG + +4 transfac_pro__M05046 1 0.92219 22550.3 1 6 CACCTG ATGCCGCCAC + +4 transfac_pro__M05146 4 0.92219 22550.3 1 6 CACCTG AGGCCGCCCA + +4 transfac_pro__M08801 2 0.92219 22550.3 1 6 CACCTG ATTTCAAAAT + +4 cisbp__M1268 4 0.92219 22550.3 1 6 CACCTG GTTTCGTTTT - +4 cisbp__M5038-dpn-h-Sidpn 2 0.92219 22550.3 1 6 CACCTG GGCACGCGAC - +4 predrem__nrMotif299 4 0.92219 22550.3 1 6 CACCTG TATTTTCCAT - +4 taipale__GBX2_DBD_NNYAATTANN-al-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-ind-inv-lab-lbe-Lim3-lms-NK7.1-OdsH-pb-Pph13-repo-ro-Rx-Scr-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zen 2 0.92219 22550.3 1 6 CACCTG GCTAATTGGT - +4 transfac_pro__M03171 1 0.92219 22550.3 1 6 CACCTG TCAGCGGCAT - +4 cisbp__M0589 -1 0.92219 22550.3 1 5 CACCTG AATTTAAATT + +4 cisbp__M0745 5 0.92219 22550.3 1 5 CACCTG TAGCAAACAC + +4 flyfactorsurvey__Cf2-PA_SOLEXA_FBgn0000286-Cf2 -1 0.92219 22550.3 1 5 CACCTG ATATAGTATA + +4 taipale_tf_pairs__PBX4_HOXA10_CCATAAATCA_CAP-exd 5 0.92219 22550.3 1 5 CACCTG CCATAAATCA + +4 cisbp__M1589-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 5 0.92219 22550.3 1 5 CACCTG ATTGTTCTGC - +4 cisbp__M4805-B-H1-B-H2-bsh-CG11085-lab-Ubx-Vsx2 -1 0.92219 22550.3 1 5 CACCTG GCCAATTAAA - +4 cisbp__M5278-Antp-ap-Awh-bsh-CG18599-Dfd-E5-ems-eve-ind-lms-pb-Scr-zen-zen2 5 0.92219 22550.3 1 5 CACCTG GTCATTAAGA - +4 flyfactorsurvey__CG11085_SOLEXA_FBgn0030408-B-H1-B-H2-CG11085-Ubx-Vsx2-bsh-lab -1 0.92219 22550.3 1 5 CACCTG ACCAATTAAA - +4 flyfactorsurvey__zen2_SOLEXA_2_FBgn0004054-Antp-Awh-CG18599-Dfd-E5-Scr-ap-bsh-ems-eve-ind-lms-pb-zen-zen2 5 0.92219 22550.3 1 5 CACCTG GTCATTAAGA - +4 jaspar__MA0387.1 5 0.92219 22550.3 1 5 CACCTG TTCTTTAATT - +4 jaspar__MA0990.1 -1 0.92219 22550.3 1 5 CACCTG GCATTAATTG - +4 predrem__nrMotif1963 5 0.92219 22550.3 1 5 CACCTG AATCCCATTT - +4 transfac_pro__M06632 5 0.92219 22550.3 1 5 CACCTG TCTTTTTCCC - +4 transfac_pro__M07858-rib 5 0.92219 22550.3 1 5 CACCTG ATTTGCAACA - +4 cisbp__M5388-abd-A-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-lms-OdsH-otp-pb-repo-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2-zfh2 6 0.92219 22550.3 1 4 CACCTG GCTAATTAGC + +4 taipale__GSX1_DBD_NNYMATTANN-al-Antp-ap-Awh-CG18599-CG32532-CG34367-E5-ems-en-ey-HGTX-ind-lab-lbe-Lim3-lms-OdsH-otp-repo-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2 6 0.92219 22550.3 1 4 CACCTG CCTAATTAAA + +4 transfac_pro__M07527 6 0.92219 22550.3 1 4 CACCTG GGCGGCCGCC + +4 cisbp__M5502-acj6-al-Antp-ap-Awh-CG18599-CG32532-CG34367-E5-ems-en-ey-HGTX-ind-lab-lbe-Lim3-lms-OdsH-otp-repo-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-zen2 6 0.92219 22550.3 1 4 CACCTG CCTAATTAAA - +4 cisbp__M5672-al-ap-Awh-C15-CG18599-CG34367-dve-E5-ems-en-eve-exex-hbn-ind-inv-lab-lbl-Lim3-OdsH-otp-pb-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 -2 0.92219 22550.3 1 4 CACCTG GCTAATTAGC - +4 stark__GGGGAWYCMC-Dif-Rel 6 0.92219 22550.3 1 4 CACCTG GGGAATCCCC - +4 transfac_pro__M06069 -2 0.92219 22550.3 1 4 CACCTG GCGGTTGCAA - +4 transfac_pro__M08936-bon-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-Myc-nej-pan-pnr-Stat92E 6 0.92219 22550.3 1 4 CACCTG ATGAGTCATC - +4 transfac_pro__M06695 -3 0.92219 22550.3 1 3 CACCTG CTAAATCCGC + +4 transfac_pro__M07600-Jra-kay -3 0.92219 22550.3 1 3 CACCTG ATGAGTCAGA - +4 taipale_cyt_meth__IRF3_NCNGTTTCCNGGAAACYGAAAS_eDBD_meth-Stat92E 5 0.922347 22554.2 1 6 CACCTG GCTGTTTCCTGGAAACCGAAAC + +4 taipale_cyt_meth__ZNF384_TTTTTNNNNNNNNNNNNAAAAA_eDBD_meth-rn-sqz 6 0.922347 22554.2 1 6 CACCTG TTTTTTTTAATCCTAAAAAAAA - +4 taipale_tf_pairs__ETV2_HES7_RSCGGAANNNNNNNCACGTGNN_CAP_repr-pnt 15 0.922347 22554.2 1 6 CACCTG GGCACGTGCCGTCACTTCCGGT - +4 transfac_pro__M04638-jumu 11 0.922347 22554.2 1 6 CACCTG TAATGGCGCGTCACTTTATTCT - +4 transfac_pro__M05328 -3 0.922347 22554.2 1 3 CACCTG CTGGACTTTCATGCGTGAAGAG - +4 tfdimers__MD00134-CG7786-gt-Pdp1 15 0.923532 22583.1 1 6 CACCTG TTAAAGGGATTAGCACATTAATT + +4 taipale_cyt_meth__ZNF177_NTNGRTCKNNNNNNNNAGTCATN_eDBD_meth_repr 8 0.923532 22583.1 1 6 CACCTG AATGACTGTGCCCCTAGATCAAG - +4 tfdimers__MD00387-foxo-oc 14 0.923532 22583.1 1 6 CACCTG AAATAAATCCATTTAATCCTTTT - +4 taipale_tf_pairs__ETV2_GSC2_RCCGGANNNNNNNNNNTAATCCN_CAP_repr-Gsc-pnt -1 0.923532 22583.1 1 5 CACCTG ACCGGAAGCCCCTCCCTAATCCC + +4 tfdimers__MD00323 11 0.923702 22587.3 1 6 CACCTG TTTATTTAATCTGATTGCATAAATATT + +4 tfdimers__MD00336-Stat92E 13 0.923702 22587.3 1 6 CACCTG ATTTTAGTTTCATTTCCTATAAAAAAT + +4 tfdimers__MD00071-Sox100B 5 0.923702 22587.3 1 6 CACCTG AAAAAAAATTATGCAAACAAAGAAAAA - +4 transfac_public__M00038-cnc-Jra-kay-mor 15 0.923702 22587.3 1 6 CACCTG GTGCGCTGGATGAGTCATAGGCACTGG - +4 hocomoco__VENTX_HUMAN.H11MO.0.D-B-H1-B-H2-CG34367-Dr-en-exex-ind-inv-unpg 7 0.923769 22588.9 1 6 CACCTG CGCTAATTGGTTTCTAATT + +4 cisbp__M4475-CG9650-ebi-MTA1-like-nej-Stat92E-sv 8 0.923769 22588.9 1 6 CACCTG AGTTTCACTTCCTCTTTTT - +4 hocomoco__NKX61_HUMAN.H11MO.0.B-Dr-HGTX-ind 3 0.923769 22588.9 1 6 CACCTG CATTAAATTCCCATTAATC - +4 hocomoco__MYNN_HUMAN.H11MO.0.D 0 0.923852 22590.9 1 6 CACCTG GGACTTTTATTTTGAAA + +4 taipale_cyt_meth__FOXP3_NAWTTGTAYGACAAATN_FL_meth_repr 0 0.923852 22590.9 1 6 CACCTG CATTTGTATGACAAATG + +4 transfac_pro__M01428-Gsc-oc 9 0.923852 22590.9 1 6 CACCTG AATCGTTAATCCCTTTC + +4 hocomoco__NANOG_MOUSE.H11MO.0.A-CG9650-Mad-SoxN-nej-nub-pan-pdm2 3 0.923852 22590.9 1 6 CACCTG ATTTGCATAACAAAGGA - +4 transfac_pro__M01320-abd-A-Antp-Awh-CG32532-CG4328-Dfd-HGTX-Lim1-Lim3-Lmx1a-otp-Scr-Ubx-vvl-zen2-zfh2 1 0.923852 22590.9 1 6 CACCTG GTTTCTTAATTAATTCG - +4 transfac_pro__M01356-al-Antp-Awh-CG11294-CG18599-CG34367-CG4328-Dfd-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-repo-Scr-unc-4-zfh2 9 0.923852 22590.9 1 6 CACCTG CCTATTAATTAATTCCG - +4 transfac_pro__M01366-oc-Ptx1 9 0.923852 22590.9 1 6 CACCTG ATAAATTAATCCCCTCC - +4 transfac_pro__M02907-D-Sox21a-Sox21b 0 0.923852 22590.9 1 6 CACCTG TAGCGGAACAATTGACT - +4 transfac_pro__M07872-Poxn 5 0.923852 22590.9 1 6 CACCTG AGCGGAACCGTCACGCT - +4 transfac_pro__M02877-luna 12 0.923852 22590.9 1 5 CACCTG AAGCATACGCCCAACTT + +4 taipale_cyt_meth__PAX1_NSGTCACGCWTSANYGN_eDBD-ey-Poxm-sv-toy 12 0.923852 22590.9 1 5 CACCTG GCAGTCAAGCGTGACGG - +4 transfac_pro__M09389 -2 0.923852 22590.9 1 4 CACCTG CTTGTTCCACAAGAAAC + +4 cisbp__M6348-MTF-1 13 0.923852 22590.9 1 4 CACCTG GTTTTGCACACGGCACT - +4 hocomoco__ZFP82_HUMAN.H11MO.0.C 15 0.924222 22600 1 6 CACCTG GAAGAGAGAATTAGTGAAATGGAA - +4 hocomoco__ZN490_HUMAN.H11MO.0.C 20 0.924222 22600 1 4 CACCTG TGGGTCTCTTGAAGGCAGCATATC + +4 tfdimers__MD00572 5 0.924276 22601.3 1 6 CACCTG ATTATTAATTATGCAAATAATTAAAT - +4 flyfactorsurvey__CG3407_SOLEXA_2.5_FBgn0031573-CG3407-Hesr 11 0.924458 22605.8 1 6 CACCTG ATGTCAAGCCCAAACAAAACCACAA + +4 cisbp__M4858-CG3407-Hesr 11 0.924458 22605.8 1 6 CACCTG ATGTCAAGCCCAAACAAAACCAAAA - +4 cisbp__M3176-klu-sr 1 0.924778 22613.6 1 6 CACCTG TTGCGTGGGCGT + +4 cisbp__M5734-Dll-dve-nub-pdm2-vvl 5 0.924778 22613.6 1 6 CACCTG TAATTTGCATAA + +4 flyfactorsurvey__Med_FlyReg_FBgn0011655-Med 1 0.924778 22613.6 1 6 CACCTG GCGGCTGGCAGT + +4 tiffin__TIFDMEM0000054 4 0.924778 22613.6 1 6 CACCTG ATTTAAATTTTT + +4 transfac_pro__M05697-CG2120 5 0.924778 22613.6 1 6 CACCTG CCCGCAAAATGC + +4 transfac_pro__M06661 5 0.924778 22613.6 1 6 CACCTG AGCCGCACGCGT + +4 transfac_pro__M06966 0 0.924778 22613.6 1 6 CACCTG GTACTGCATTAT + +4 transfac_pro__M07419 4 0.924778 22613.6 1 6 CACCTG TCGAAAACAGAA + +4 transfac_pro__M09182 4 0.924778 22613.6 1 6 CACCTG AAAGCGCGTGAA + +4 transfac_public__M00246-klu-sr 1 0.924778 22613.6 1 6 CACCTG TTGCGTGGGCGT + +4 cisbp__M3167-klu-sr 1 0.924778 22613.6 1 6 CACCTG ACGCCCACGCAT - +4 hocomoco__ZN418_HUMAN.H11MO.1.D 4 0.924778 22613.6 1 6 CACCTG CTAGAAGCAACA - +4 transfac_pro__M05428 0 0.924778 22613.6 1 6 CACCTG GGCCTTGCCCCC - +4 transfac_pro__M05486-Blimp-1 6 0.924778 22613.6 1 6 CACCTG TATCCAAAACAC - +4 transfac_pro__M05953-CG9650 5 0.924778 22613.6 1 6 CACCTG GCGTTTCCCTCT - +4 transfac_pro__M05958-CG6654-CG7372 1 0.924778 22613.6 1 6 CACCTG GCATCCGCCAAG - +4 transfac_pro__M06038 6 0.924778 22613.6 1 6 CACCTG TCTTATTCCCCG - +4 transfac_pro__M06112 2 0.924778 22613.6 1 6 CACCTG TCCGACTTCCCA - +4 transfac_pro__M06579 6 0.924778 22613.6 1 6 CACCTG GCTTATTCCCCG - +4 transfac_pro__M06628 6 0.924778 22613.6 1 6 CACCTG AATTTTCTCCAC - +4 transfac_public__M00243-klu-sr 1 0.924778 22613.6 1 6 CACCTG ACGCCCACGCAT - +4 homer__GGCCCCGCCCCC_Sp1-CG3065-CG42741-ERR-E(z)-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-dar1-kay-sd 7 0.924778 22613.6 1 5 CACCTG GGCCCCGCCCCC + +4 taipale_cyt_meth__CEBPD_NRTTGCGYAAYN_eDBD_meth-CG7786-gt-Irbp18-nej-Pdp1-slbo-vri-Xrp1 7 0.924778 22613.6 1 5 CACCTG TATTGCGCAATA + +4 transfac_pro__M05295 7 0.924778 22613.6 1 5 CACCTG TGGCTTGCCCCA - +4 transfac_pro__M05699 7 0.924778 22613.6 1 5 CACCTG TGTTATTGAGCA - +4 transfac_pro__M06382 7 0.924778 22613.6 1 5 CACCTG TCATTCGGACGC - +4 transfac_pro__M06416-crol 7 0.924778 22613.6 1 5 CACCTG TATCCAATTCCA - +4 bergman__Adf1-Adf1 -2 0.924778 22613.6 1 4 CACCTG GCTCCCGCCGCT + +4 cisbp__M5615-Mef2-rump -2 0.924778 22613.6 1 4 CACCTG TCTAAAAATAGA + +4 transfac_pro__M00436 8 0.924778 22613.6 1 4 CACCTG GAATTAATGACC + +4 cisbp__M5531-Abd-B 8 0.924778 22613.6 1 4 CACCTG ATTTTTACGACC - +4 taipale_cyt_meth__CEBPG_NRTTGCGYAAYN_eDBD-CG7786-gt-nej-Pdp1-slbo-srl -2 0.924778 22613.6 1 4 CACCTG CGTTACGCAACG - +4 taipale_cyt_meth__CUX2_NTGATCGATYRN_eDBD_meth_repr-ct -3 0.924778 22613.6 1 3 CACCTG CTGATCGATTGG + +4 transfac_pro__M05965 9 0.924778 22613.6 1 3 CACCTG TCTCTTTGACAA - +4 transfac_pro__M03851 0 0.926398 22653.2 1 6 CACCTG TTCCTC + +4 hdpi__WISP2-Ccn 0 0.926398 22653.2 1 6 CACCTG TGCTTT - +4 flyfactorsurvey__PhdP_SOLEXA_FBgn0025334-Antp-CG9876-CG11294-CG32532-CG34367-Lim1-OdsH-PHDP-Rx-Scr-Traf4-Vsx1-Vsx2-en-lms-slou-unc-4-unpg 1 0.926398 22653.2 1 5 CACCTG TTAATT + +4 hdpi__R3HDM2-enc -1 0.926398 22653.2 1 5 CACCTG AATTTA - +4 transfac_pro__M09180 2 0.926398 22653.2 1 4 CACCTG TCAACA + +4 stark__TTTATG-cad -2 0.926398 22653.2 1 4 CACCTG CATAAA - +4 hdpi__NFIB-NfI 3 0.926398 22653.2 1 3 CACCTG GTTCGC - +4 hdpi__ZNF131 -3 0.926398 22653.2 1 3 CACCTG CTTTGT - +4 cisbp__M2061-vvl -4 0.926398 22653.2 1 2 CACCTG TGCATA + +4 flyfactorsurvey__vvl_FlyReg_FBgn0086680-vvl -4 0.926398 22653.2 1 2 CACCTG TGCATA - +4 taipale_cyt_meth__HOXD11_NRTCGTAAAANNTTAN_eDBD_repr-Abd-B-cad 2 0.926458 22654.7 1 6 CACCTG ATAAAGTTTTACGACC - +4 transfac_pro__M01360-Dbx-Dfd-Dr-HGTX-lab-vvl 0 0.926458 22654.7 1 6 CACCTG GAATTAATTAATTAAA - +4 taipale_cyt_meth__ZNF174_NGNCRATCACTYGNCN_eDBD_meth 11 0.926458 22654.7 1 5 CACCTG TGCCGATCACTCGCCC + +4 cisbp__M0113 0 0.926467 22654.9 1 6 CACCTG AAAATTTT + +4 cisbp__M4854-ap-Awh-CG11294-CG32532-CG9876-Dll-E5-en-hbn-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-unpg-Vsx1-Vsx2 2 0.926467 22654.9 1 6 CACCTG GTTAATTA + +4 flyfactorsurvey__CG33980_SOLEXA_FBgn0053980-Awh-CG9876-CG11294-CG32532-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Ubx-Vsx1-Vsx2-ap-en-hbn-inv-lab-lms-otp-pb-repo-ro-slou-unpg 2 0.926467 22654.9 1 6 CACCTG GTTAATTA + +4 predrem__nrMotif1038 1 0.926467 22654.9 1 6 CACCTG ACTCTTCT + +4 predrem__nrMotif1810 0 0.926467 22654.9 1 6 CACCTG TGACTGAT + +4 taipale__ISX_full_NYAATTAN-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ey-ind-inv-lbe-lbl-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-toy-Traf4-Ubx-unc-4-unpg-Vsx1-V 1 0.926467 22654.9 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__GSC_YTAATCCN_FL-Gsc-oc 2 0.926467 22654.9 1 6 CACCTG CTAATCCC + +4 taipale_tf_pairs__HOXA4_RTMATTAN_HT-Dfd 0 0.926467 22654.9 1 6 CACCTG GTCATTAC + +4 transfac_public__M00241 2 0.926467 22654.9 1 6 CACCTG CTTAATTG + +4 cisbp__M1591-Sox100B-Sox102F-Sox14 2 0.926467 22654.9 1 6 CACCTG AGAACAAT - +4 neph__UW.Motif.0029 0 0.926467 22654.9 1 6 CACCTG TGGCTCTG - +4 predrem__nrMotif1946 0 0.926467 22654.9 1 6 CACCTG TCTCTGTA - +4 predrem__nrMotif350 1 0.926467 22654.9 1 6 CACCTG ACAATTTC - +4 taipale_cyt_meth__GBX2_NCAATTAN_FL-Antp-B-H1-B-H2-bsh-C15-CG11085-CG18599-Dr-E5-ems-en-eve-exex-ind-inv-Lim3-lms-OdsH-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx2 1 0.926467 22654.9 1 6 CACCTG CTAATTGC - +4 jaspar__MA1034.1 3 0.926467 22654.9 1 5 CACCTG CGCCGCCG + +4 transfac_pro__M07811-bcd-Gsc-oc-Ptx1 3 0.926467 22654.9 1 5 CACCTG CTAATCCC + +4 yetfasco__YGL013C_485 -1 0.926467 22654.9 1 5 CACCTG TCCGCGGA + +4 transfac_pro__M04846-cnc-foxo-Jra-kay-Mef2-MTA1-like-Stat92E 3 0.926467 22654.9 1 5 CACCTG TGACTCAT - +4 cisbp__M0033-Hcf 4 0.926467 22654.9 1 4 CACCTG GCGCCGCC + +4 flyfactorsurvey__Unpg_Cell_FBgn0015561-Antp-Awh-CG9876-CG11294-CG32532-Dll-E5-Lim1-Lim3-Pph13-Rx-Scr-Vsx1-ap-ems-en-lab-lms-otp-ro-slou-unpg-zen2 -2 0.926467 22654.9 1 4 CACCTG CTTAATTA + +4 jaspar__MA0976.1-Hcf 4 0.926467 22654.9 1 4 CACCTG GCGCCGCC + +4 transfac_pro__M01926 4 0.926467 22654.9 1 4 CACCTG ATGAAACA + +4 transfac_pro__M04903-Hnf4 4 0.926467 22654.9 1 4 CACCTG TTTGGACT - +4 cisbp__M1209 5 0.926467 22654.9 1 3 CACCTG TCAATCAA + +4 flyfactorsurvey__tgo_ss_SANGER_5_FBgn0003513-ss-tgo 5 0.926467 22654.9 1 3 CACCTG TGCGTGAC + +4 jaspar__MA0158.1-Antp-Scr -3 0.926467 22654.9 1 3 CACCTG CACTAATT + +4 taipale__Meox2_DBD_NTAATKAN-abd-A-btn-lab-lbl-Lim3-Scr-Ubx 5 0.926467 22654.9 1 3 CACCTG GTAATTAC + +4 taipale__VAX1_DBD_YTAATTAN-ap-Awh-CG18599-CG32532-CG4328-Dfd-E5-ems-en-eve-ind-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-unpg-Vsx1-zen2 5 0.926467 22654.9 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__EMX2_YTAATTAN_eDBD_meth-Antp-ap-Awh-CG18599-CG4328-CG9876-Dfd-E5-ems-eve-ind-Lmx1a-OdsH-pb-ro-Rx-Scr-Ubx-Vsx1-Vsx2-zen2 5 0.926467 22654.9 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__EN1_NYAATTAN_eDBD-Antp-Awh-B-H1-B-H2-bsh-btn-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim1-Lim3-lms-pb-Rx-Scr-unpg-Vsx1-Vsx2 5 0.926467 22654.9 1 3 CACCTG GCAATTAG + +4 taipale_cyt_meth__HOXA2_NYAATTAN_eDBD-Antp-Awh-bsh-btn-Dfd-Dll-E5-ems-en-eve-exex-inv-lab-lbl-Lim3-pb-Scr-slou-zen2 5 0.926467 22654.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__PRRX2_NYAATTAN_eDBD-B-H1-B-H2-bsh-CG18599-Dll-Dr-E5-ems-en-exex-inv-lab-Lim1-Lim3-lms-OdsH-pb-Rx-slou-unpg-Vsx1-Vsx2 5 0.926467 22654.9 1 3 CACCTG CCAATTAG + +4 transfac_pro__M07834-abd-A-Dll-exex-HGTX-Scr-Ubx 5 0.926467 22654.9 1 3 CACCTG GTAATTAA + +4 cisbp__M5236-ss-tgo 5 0.926467 22654.9 1 3 CACCTG TGCGTGAC - +4 dbcorrdb__BCLAF1__ENCSR000BKH_1__m1-Atac3-Eip74EF-Ets96B 8 0.926665 22659.7 1 6 CACCTG ACCGGAAGTGGTTAGCCCCG + +4 dbcorrdb__EZH2__ENCSR000ARR_1__m1-E(z) 7 0.926665 22659.7 1 6 CACCTG CCGGCAGCGCCGAGGCCGAC + +4 dbcorrdb__EZH2__ENCSR000ASY_1__m5-E(z) 13 0.926665 22659.7 1 6 CACCTG CCTTGGACTTCGCTGCCGGC + +4 dbcorrdb__POLR2A__ENCSR000BHZ_1__m2-RpII215 9 0.926665 22659.7 1 6 CACCTG CGGTAGCGGCAACGGCATGA + +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m3-Su(z)12 9 0.926665 22659.7 1 6 CACCTG GTCTGCGCGCTGCTGCTTCG + +4 jaspar__MA0400.1 5 0.926665 22659.7 1 6 CACCTG ATGATAAACTCCGAAAATTT + +4 transfac_pro__M01517 0 0.926665 22659.7 1 6 CACCTG CCCCATTTCCGGAAAGTTCC + +4 transfac_pro__M05684 6 0.926665 22659.7 1 6 CACCTG GGATTAAACGTCCGCTGTCT + +4 dbcorrdb__CUX1__ENCSR000EFO_1__m4-Brf-brm-btd-CG42741-CG7368-CoRest-crol-ct-CTCF-Dif-dl-E(z)-HDAC1-Klf15-klu-l(3)neo38-Nelf-E-peb-Rbbp5-Spps-Spt20-sr-SREBP-vtd 4 0.926665 22659.7 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 dbcorrdb__ELK4__ENCSR000EVI_1__m1-aop-Atac3-Brf-brm-bs-CTCF-E2f1-E2f2-Eip74EF-Ets21C-Ets65A-Ets96B-Ets97D-E(z)-Hcf-HDAC1-Max-Myc-Nelf-E-pnt-Rbbp5-RpII215-Sin3A-SREBP-Taf1-tna 2 0.926665 22659.7 1 6 CACCTG GGGGCCGGAAGTGGCGGCGC - +4 dbcorrdb__EZH2__ENCSR000ASY_1__m2-E(z) 5 0.926665 22659.7 1 6 CACCTG GCCAACGCCGCGTCGGGGGT - +4 dbcorrdb__HDAC6__ENCSR000ATJ_1__m3-HDAC6 12 0.926665 22659.7 1 6 CACCTG GCGGGCGCAGCGCCCCGCGG - +4 dbcorrdb__NFIC__ENCSR000BRN_1__m1-ebi-foxo-Jra-Mef2-MTA1-like-nej-NFAT-Stat92E 9 0.926665 22659.7 1 6 CACCTG GATGAGTCATATCGAAACTT - +4 dbcorrdb__NRF1__ENCSR000EDJ_1__m1-E2f1-ewg-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG33886-His 5 0.926665 22659.7 1 6 CACCTG CCCTGCGCATGCGCAGTGGG - +4 dbcorrdb__POLR2A__ENCSR000BQB_1__m1-RpII215 2 0.926665 22659.7 1 6 CACCTG CCGCCATTGCGCTTCCGCGC - +4 dbcorrdb__POLR2A__ENCSR000EFB_1__m2-Nelf-E-pho-phol-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 8 0.926665 22659.7 1 6 CACCTG GCCGCGGCGGCTTTTATAGG - +4 dbcorrdb__POLR2A__ENCSR000EFB_1__m3-RpII215 11 0.926665 22659.7 1 6 CACCTG GCCGCTGCCGCTGCGAGAGG - +4 dbcorrdb__TRIM28__ENCSR000EVY_1__m3-bon 4 0.926665 22659.7 1 6 CACCTG GTTTTCCCACAGTGTGTACA - +4 hocomoco__ZN394_HUMAN.H11MO.0.C-Iswi-crol 1 0.926665 22659.7 1 6 CACCTG ATTCCATTCTATTCCATTCT - +4 dbcorrdb__SIX5__ENCSR000BJE_1__m3-Six4 -1 0.926665 22659.7 1 5 CACCTG GCATTGCGCCTGCGGAGAGG - +4 hdpi__ZNF193 -3 0.926802 22663.1 1 3 CACCTG TTGCA - +4 neph__UW.Motif.0305 3 0.927224 22673.4 1 6 CACCTG TGAGAAATTTACA + +4 stark__CATTANNNWAATT 3 0.927224 22673.4 1 6 CACCTG CATTAAAAAAATT + +4 taipale_cyt_meth__ARGFX_YTAATCTAATTAG_eDBD_meth-al-ap-bsh-C15-CG11294-CG32532-CG34367-CG9876-Drgx-ems-ey-hbn-Lim3-OdsH-Optix-repo-ro-Rx-Traf4-unc-4-Vsx2 2 0.927224 22673.4 1 6 CACCTG TTAATCTAATTAG + +4 cisbp__M6329-ap-Awh-CG11294-CG32532-E5-ems-HGTX-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-unc-4-Vsx1-vvl 6 0.927224 22673.4 1 6 CACCTG ATTAATTAATTTT - +4 flyfactorsurvey__CG10904_SANGER_5_FBgn0034945-CG10904 7 0.927224 22673.4 1 6 CACCTG TTTTTCTCGCATG - +4 neph__UW.Motif.0387 8 0.927224 22673.4 1 5 CACCTG TTTTTTGAAAACA - +4 predrem__nrMotif88 -1 0.927224 22673.4 1 5 CACCTG CCCTGCCCCCAAC - +4 transfac_pro__M00742-croc 8 0.927224 22673.4 1 5 CACCTG TAAACAAACACAT - +4 transfac_pro__M02045-CG5846-CG9727-Max-Rfx-SREBP 9 0.927224 22673.4 1 4 CACCTG TCGCCATGGCAAC + +4 cisbp__M5461-bin-croc-fd59A-foxo-slp1 9 0.927224 22673.4 1 4 CACCTG TTGTTTATTTACA - +4 taipale__FOXL1_full_WRTAAAYAAACAA-bin-croc-fd59A-foxo-slp1 9 0.927224 22673.4 1 4 CACCTG TTGTTTATTTACA - +4 cisbp__M2329-Mad 0 0.927924 22690.5 1 6 CACCTG CGGCGGCGGCGCCTG + +4 cisbp__M6129-CG9650-Mad-nej-pan-SoxN 2 0.927924 22690.5 1 6 CACCTG TTTGCATAACAATGG + +4 homer__CTYTCTYTCTCTCTC_GAGA-repeat-Atac1 7 0.927924 22690.5 1 6 CACCTG CTCTCTCTCTCTCTC + +4 jaspar__MA0530.1-cnc-maf-S-nej-tj 3 0.927924 22690.5 1 6 CACCTG GATGACTCGGCAAAT + +4 cisbp__M4010-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 0 0.927924 22690.5 1 6 CACCTG CCCCGCCTTTTATAC - +4 cisbp__M4598-E2f1-E2f2-Sin3A 4 0.927924 22690.5 1 6 CACCTG TTCCAATTTCCCGCC - +4 jaspar__MA0108.2-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 0 0.927924 22690.5 1 6 CACCTG CCCCGCCTTTTATAC - +4 predrem__nrMotif804-RpII215-sqz -1 0.927924 22690.5 1 5 CACCTG ACCAAAAAAAAAAAA + +4 cisbp__M4473-btd-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-yps -1 0.927924 22690.5 1 5 CACCTG CTCTGATTGGCCGGC - +4 transfac_pro__M05571-CG42726 0 0.928216 22697.7 1 6 CACCTG CGCCAGAATTAATC + +4 cisbp__M5219-lmd-opa-sug 5 0.928216 22697.7 1 6 CACCTG AAGACCCCCCGCGG - +4 taipale_cyt_meth__ATF4_GGATGACGTCATCC_eDBD-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-REPTOR-BP-Xbp1 9 0.928216 22697.7 1 5 CACCTG GGATGACGTCATCC + +4 transfac_pro__M07873-Poxn 9 0.928216 22697.7 1 5 CACCTG CCGTTCCGGAACGG + +4 cisbp__M6211 9 0.928216 22697.7 1 5 CACCTG ATTTCGTATCCCCG - +4 idmmpmm__bab1-bab1 9 0.928216 22697.7 1 5 CACCTG ATTATAATATATAT - +4 transfac_pro__M06829-salm-salr 9 0.928216 22697.7 1 5 CACCTG GGGGCCGTATACTG - +4 taipale__FOXC1_DBD_NRTMAATATTKAYN_repr-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.928216 22697.7 1 4 CACCTG TGTCAATATTTACA - +4 homer__NAGTTTCABTHTGACTNW_bZIP_IRF-Jra-MTA1-like-ebi 12 0.928237 22698.2 1 6 CACCTG CAGTTTCATTTTGACTCA + +4 taipale_cyt_meth__PAX4_NTYACGCWTSANYGNNYN_eDBD_meth-ey-sv-toy 2 0.928237 22698.2 1 6 CACCTG TTTACGCATGAATGCACA + +4 transfac_pro__M05627 12 0.928237 22698.2 1 6 CACCTG TTCGGGGTGCGATACGAA + +4 transfac_pro__M06289 11 0.928237 22698.2 1 6 CACCTG GATTACCGTCGTATCGGC + +4 transfac_pro__M08892-oc 12 0.928237 22698.2 1 6 CACCTG AAACAATTAAAGAAGAAC + +4 hocomoco__MAFG_HUMAN.H11MO.0.A-cnc-maf-S-tj 1 0.928237 22698.2 1 6 CACCTG AAAATTGCTGACTCAGCA - +4 transfac_pro__M06307 -1 0.928237 22698.2 1 5 CACCTG CCCTCCCCAGTAACGGTC - +4 cisbp__M1760 3 0.928307 22699.9 1 6 CACCTG CAACGCCGAAG + +4 cisbp__M4261 0 0.928307 22699.9 1 6 CACCTG CGCCGTTTAGC + +4 jaspar__MA0519.1-Stat92E 2 0.928307 22699.9 1 6 CACCTG ATTTCCAAGAA + +4 taipale__POU3F4_DBD_TGMATWWWTNA-pdm3-vvl 4 0.928307 22699.9 1 6 CACCTG TGCATAAATTA + +4 taipale_cyt_meth__JUN_NATGACTCATN_FL_meth-bon-Jra-kay-Mef2-Myc-nej-pan-Stat92E 5 0.928307 22699.9 1 6 CACCTG GATGACTCATC + +4 transfac_pro__M01659-cad 0 0.928307 22699.9 1 6 CACCTG TCCATAAATAA + +4 transfac_pro__M06849 1 0.928307 22699.9 1 6 CACCTG AGTCCGGAAGA + +4 transfac_pro__M09225 4 0.928307 22699.9 1 6 CACCTG CCAATAATTGA + +4 transfac_pro__M09494 0 0.928307 22699.9 1 6 CACCTG AATCGCATTAT + +4 cisbp__M5593-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.928307 22699.9 1 6 CACCTG GCCACGCCCCC - +4 cisbp__M6537-yps 4 0.928307 22699.9 1 6 CACCTG GGCCAATCCCC - +4 hocomoco__HXA9_HUMAN.H11MO.0.B 5 0.928307 22699.9 1 6 CACCTG CCATAAATCAT - +4 taipale_cyt_meth__JDP2_GATGASTCATC_eDBD-cnc-Jra-kay-Mef2 5 0.928307 22699.9 1 6 CACCTG GATGACTCATC - +4 transfac_pro__M01294-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 0 0.928307 22699.9 1 6 CACCTG TAATTAAATTA - +4 transfac_pro__M07779-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-ems-eve-hbn-OdsH-Optix-otp-repo-Traf4-unc-4-unpg-Vsx1 4 0.928307 22699.9 1 6 CACCTG TAATTAAATTA - +4 swissregulon__sacCer__YAP7 6 0.928307 22699.9 1 5 CACCTG ATTAGTAAGCA + +4 taipale_cyt_meth__HOXA13_NCCAATAAAAM_eDBD_repr -1 0.928307 22699.9 1 5 CACCTG CCCAATAAAAC + +4 cisbp__M2551-dl 6 0.928307 22699.9 1 5 CACCTG TGAGAAAACCC - +4 predrem__nrMotif154 7 0.928307 22699.9 1 4 CACCTG TTTTTTTTTCC + +4 predrem__nrMotif2099 7 0.928307 22699.9 1 4 CACCTG CCCCGAGTCCC + +4 fantom__motif82_TTGAATCGCGG -2 0.928307 22699.9 1 4 CACCTG CCGCGATTCAA - +4 jaspar__MA0503.1-scro -2 0.928307 22699.9 1 4 CACCTG CTTGAGTGGCT - +4 taipale_cyt_meth__CDX1_NGYMATAAAAN_eDBD-Abd-B-cad-eve 7 0.928307 22699.9 1 4 CACCTG GTTTTATGGCC - +4 taipale_cyt_meth__HOXC10_NRTCGTAAAAN_eDBD-Abd-B-cad 7 0.928307 22699.9 1 4 CACCTG GTTTTACGACC - +4 taipale_cyt_meth__ZNF396_NTGTMCRAAAN_FL_meth_repr -3 0.928307 22699.9 1 3 CACCTG CTGTCCAAAAA + +4 transfac_pro__M05297-SoxN 9 0.928307 22699.9 1 2 CACCTG TTTAATATTCA - +4 cisbp__M1997-bsh-CG11085-CG32532-Dr-en-inv-Rx-slou-unpg-Vsx1 0 0.928573 22706.4 1 6 CACCTG TAATTGG + +4 cisbp__M2001-B-H2-Hmx 1 0.928573 22706.4 1 6 CACCTG TTAATTG + +4 cisbp__M2029-abd-A-al-Antp-ap-Awh-C15-CG11294-CG15696-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-pb-PHDP-Pph13-r 1 0.928573 22706.4 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Hmx_Cell_FBgn0085448-B-H2-Hmx 1 0.928573 22706.4 1 6 CACCTG TTAATTG + +4 jaspar__MA0220.1-Antp-Awh-C15-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-exex-ftz-hbn-i 1 0.928573 22706.4 1 6 CACCTG TTAATTA + +4 predrem__nrMotif196 1 0.928573 22706.4 1 6 CACCTG TGACTCA + +4 predrem__nrMotif293 0 0.928573 22706.4 1 6 CACCTG AGTCTGT + +4 stark__AAASTTT 1 0.928573 22706.4 1 6 CACCTG AAACTTT + +4 hdpi__KLF4 0 0.928573 22706.4 1 6 CACCTG TTTCTGA - +4 jaspar__MA0178.1-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-ap-ems-en-ey-hbn-inv-lab-lbl-lms-otp-repo-ro-slou-toy-unc-4-unpg- 0 0.928573 22706.4 1 6 CACCTG TAATTAA - +4 jaspar__MA0188.1-CG11085-CG32532-Dr-Rx-Vsx1-bsh-en-inv-slou-unpg 0 0.928573 22706.4 1 6 CACCTG TAATTGG - +4 predrem__nrMotif1838 0 0.928573 22706.4 1 6 CACCTG TAAATTC - +4 transfac_pro__M02026-Mef2 1 0.928573 22706.4 1 6 CACCTG CTATTTT - +4 predrem__nrMotif1216 2 0.928573 22706.4 1 5 CACCTG GAGTTCT + +4 predrem__nrMotif395 2 0.928573 22706.4 1 5 CACCTG TTCTCCA + +4 transfac_pro__M01694-pho-phol-S2P -1 0.928573 22706.4 1 5 CACCTG CCATTAT + +4 flyfactorsurvey__br_SANGER_10_FBgn0000210-br 3 0.928573 22706.4 1 4 CACCTG TCTAATC - +4 jaspar__MA0414.1 -2 0.928573 22706.4 1 4 CACCTG CCTCGAG - +4 transfac_pro__M01947 -2 0.928573 22706.4 1 4 CACCTG CCTCGAG - +4 bergman__bin-bin 4 0.928573 22706.4 1 3 CACCTG TATTTAC - +4 hdpi__RNASEH2C -3 0.928573 22706.4 1 3 CACCTG CGACCAA - +4 stark__RTAAACA-FoxK-FoxL1-bin-croc-fd59A-slp2 4 0.928573 22706.4 1 3 CACCTG TGTTTAC - +4 stark__RTAAATA-bin 4 0.928573 22706.4 1 3 CACCTG TATTTAC - +4 taipale_cyt_meth__GFI1_NMAATCACNGCNNNNCACTMN_eDBD-sens-2 15 0.928897 22714.3 1 6 CACCTG CAAATCACTGCACCTCACTCC + +4 taipale_cyt_meth__GFI1_NMAATCACNGCNNNNCACTMN_eDBD_meth-sens-2 15 0.928897 22714.3 1 6 CACCTG GAAATCACTGCATTTCACTCC + +4 taipale_cyt_meth__ZNF76_NYWWCCCAYAATGCANYGCRN_eDBD_meth_repr 2 0.928897 22714.3 1 6 CACCTG ATTACCCACAATGCATTGCGC + +4 tfdimers__MD00340 1 0.928897 22714.3 1 6 CACCTG AAAAATCAGCAAATAAAAAAA + +4 transfac_pro__M05247-brm-ERR-E(z) 13 0.928897 22714.3 1 6 CACCTG GGGGGGGCCCGCCCGCCTCCC + +4 transfac_pro__M05290 6 0.928897 22714.3 1 6 CACCTG GTGGTTGCCCTCCCGCCGCCG + +4 swissregulon__hs__STAT1_3.p3-Stat92E 6 0.928897 22714.3 1 6 CACCTG CCTCATTTCCAGGAAATCCCA - +4 tfdimers__MD00123-E2f1-Sox15 14 0.928897 22714.3 1 6 CACCTG GAAAAATTGTGAAATATTTAA - +4 transfac_pro__M05266 3 0.928897 22714.3 1 6 CACCTG CAAGACCGGGGGGGCACAAAC - +4 transfac_pro__M05223 16 0.928897 22714.3 1 5 CACCTG TGTGGTTTCCGGCCGCGCCCT + +4 c2h2_zfs__M2013-hkb 3 0.929262 22723.2 1 6 CACCTG TCACGCCCC + +4 cisbp__M1742 2 0.929262 22723.2 1 6 CACCTG TTAAGCGAG + +4 predrem__nrMotif109 3 0.929262 22723.2 1 6 CACCTG AGAAGCCAG + +4 predrem__nrMotif1388 2 0.929262 22723.2 1 6 CACCTG TGCTCCACA + +4 predrem__nrMotif920 2 0.929262 22723.2 1 6 CACCTG CACACAACA + +4 taipale_cyt_meth__CDX2_NYAATAAAN_eDBD-cad 0 0.929262 22723.2 1 6 CACCTG GCCATAAAC + +4 taipale_cyt_meth__NKX6-3_NTMATTAAN_eDBD_meth_repr-HGTX 0 0.929262 22723.2 1 6 CACCTG GTCATTAAA + +4 transfac_pro__M04790-E2f1-ewg 1 0.929262 22723.2 1 6 CACCTG GCGCATGCG + +4 cisbp__M2254-hkb 3 0.929262 22723.2 1 6 CACCTG TCACGCCCC - +4 flyfactorsurvey__hkb_NAR_FBgn0001204-hkb 3 0.929262 22723.2 1 6 CACCTG TCACGCCCC - +4 predrem__nrMotif2170 1 0.929262 22723.2 1 6 CACCTG CAAATTTGT - +4 taipale__POU3F4_DBD_TATGCWAAT-acj6-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.929262 22723.2 1 6 CACCTG ATTTGCATA - +4 predrem__nrMotif2022 4 0.929262 22723.2 1 5 CACCTG GGAGAGCCG + +4 predrem__nrMotif1431 -1 0.929262 22723.2 1 5 CACCTG GCTTTGTCT - +4 flyfactorsurvey__lola-PU_SANGER_5_FBgn0005630-lola -2 0.929262 22723.2 1 4 CACCTG GCTCAATAA + +4 hocomoco__ZN554_HUMAN.H11MO.1.D-Kr -2 0.929262 22723.2 1 4 CACCTG GCAGAGCCA + +4 hocomoco__ATF3_MOUSE.H11MO.0.A-CoRest-GATAe-Jra-Mef2-Myc-NFAT-Snr1-Stat92E-cnc-ewg-grn-kay-maf-S-mor-nej-pan-pnr 6 0.929262 22723.2 1 3 CACCTG ATGAGTCAC + +4 hocomoco__JUNB_MOUSE.H11MO.0.A-CoRest-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-cnc-grn-kay-mor-nej-pan-pnr 6 0.929262 22723.2 1 3 CACCTG ATGAGTCAC + +4 stark__CTCRTAAAW-cad -3 0.929262 22723.2 1 3 CACCTG CTCATAAAA + +4 swissregulon__sacCer__GCN4-GATAe-Jra-Myc-NFAT-Stat92E-bon-cnc-grn-kay-pan-pnr 6 0.929262 22723.2 1 3 CACCTG ATGACTCAT - +4 stark__GCGTTGAYA 7 0.929262 22723.2 1 2 CACCTG GCGTTGACA + +4 transfac_pro__M08883-bin-croc-fd59A-foxo 7 0.929262 22723.2 1 2 CACCTG AAATAAACA - +4 cisbp__M1503 2 0.929829 22737.1 1 6 CACCTG GGCGCCCGCA + +4 idmmpmm__z-z 2 0.929829 22737.1 1 6 CACCTG ATTCACTCAA + +4 predrem__nrMotif1533 0 0.929829 22737.1 1 6 CACCTG CCCCCGGCCC + +4 predrem__nrMotif716 4 0.929829 22737.1 1 6 CACCTG CTTCCACTCT + +4 predrem__nrMotif797 3 0.929829 22737.1 1 6 CACCTG AAATGCCACT + +4 predrem__nrMotif986 0 0.929829 22737.1 1 6 CACCTG GGCCAGAGCC + +4 stark__ATANANNCGC 3 0.929829 22737.1 1 6 CACCTG ATAAAAACGC + +4 transfac_pro__M00342-acj6-nub-pdm2-vvl 4 0.929829 22737.1 1 6 CACCTG TATGCAAATC + +4 transfac_pro__M05067 4 0.929829 22737.1 1 6 CACCTG ACGCCGCCCA + +4 transfac_pro__M05097 1 0.929829 22737.1 1 6 CACCTG GCGCCGCTCC + +4 transfac_pro__M05099 4 0.929829 22737.1 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M09098 3 0.929829 22737.1 1 6 CACCTG GCCGACAAAA + +4 cisbp__M0674-Dp-E2f1-E2f2 4 0.929829 22737.1 1 6 CACCTG AGCGCGCCAA - +4 cisbp__M1309 4 0.929829 22737.1 1 6 CACCTG CCTTATCCAA - +4 hocomoco__PITX2_HUMAN.H11MO.0.D-Ptx1 4 0.929829 22737.1 1 6 CACCTG TTTAATCCCA - +4 predrem__nrMotif2437 4 0.929829 22737.1 1 6 CACCTG CGCCATCCCC - +4 predrem__nrMotif263 0 0.929829 22737.1 1 6 CACCTG CTCCAAGCCC - +4 predrem__nrMotif933 4 0.929829 22737.1 1 6 CACCTG TGCAATCATT - +4 taipale_cyt_meth__CUX1_NYATYGATYN_eDBD_repr-ct 1 0.929829 22737.1 1 6 CACCTG TGATCGATAC - +4 transfac_pro__M07457 2 0.929829 22737.1 1 6 CACCTG TTTAATTAAG - +4 transfac_pro__M05012 5 0.929829 22737.1 1 5 CACCTG AGGCCGCCCC + +4 transfac_pro__M07545 -1 0.929829 22737.1 1 5 CACCTG TAATGATTGG + +4 cisbp__M0842 -1 0.929829 22737.1 1 5 CACCTG GCATTAATTG - +4 hocomoco__HXB13_HUMAN.H11MO.0.A-cad -1 0.929829 22737.1 1 5 CACCTG GCCAATAAAA - +4 cisbp__M1097-al-Antp-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dr-dve-E5-ems-en-eve-ey-gsb-gsb-n-ind-inv-lab-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-toy- 6 0.929829 22737.1 1 4 CACCTG GTTAATTAAT + +4 taipale__Alx1_DBD_NNYAATTANN-al-ap-Awh-C15-CG11294-CG32532-CG34367-CG9876-E5-ems-en-hbn-lbe-Lim3-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-Vsx2 6 0.929829 22737.1 1 4 CACCTG TCTAATTAAA + +4 taipale_cyt_meth__VENTX_NGYAATTAGN_FL_meth-Antp-ap-Awh-CG11085-CG4328-Dfd-Dll-E5-ems-en-exex-ind-inv-lbl-Lim3-lms-Lmx1a-OdsH-otp-pb-Rx-Scr-slou-unpg 6 0.929829 22737.1 1 4 CACCTG CGTAATTAGC + +4 transfac_pro__M01772-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 6 0.929829 22737.1 1 4 CACCTG ATTGCGCAAT + +4 cisbp__M5507-al-Awh-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-exex-ftz-ind-inv-lab-lbe-lbl-Lim1-OdsH-otp-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx2-zfh2 6 0.929829 22737.1 1 4 CACCTG GCCAATTAGC - +4 taipale__EMX2_DBD_NNYAATTANN-abd-A-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-OdsH-pb-ro-Rx-slou-Ubx-unpg-Vsx1-Vsx2-zen2-zfh2 6 0.929829 22737.1 1 4 CACCTG GCTAATTAGC - +4 taipale__HESX1_DBD_NNTAATTRNN-al-Awh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dr-E5-ems-en-exex-ftz-inv-lab-lbe-lbl-Lim1-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx2-zfh2 6 0.929829 22737.1 1 4 CACCTG GCCAATTAGC - +4 transfac_pro__M05102 6 0.929829 22737.1 1 4 CACCTG TATCGGCCCC - +4 flyfactorsurvey__Xrp1_CG6272_SANGER_5_FBgn0036126-CG7786-Irbp18-Pdp1-Xrp1-gt-slbo 7 0.929829 22737.1 1 3 CACCTG ATTGCGCAAC + +4 stark__YGTCAWTGAC 7 0.929829 22737.1 1 3 CACCTG CGTCAATGAC + +4 predrem__nrMotif2668 -3 0.929829 22737.1 1 3 CACCTG CTGCGGGCAG - +4 transfac_pro__M06596 7 0.929829 22737.1 1 3 CACCTG GCGTTGGCAC - +4 taipale_cyt_meth__KLF10_RMCACRCCCMYNMCACRCCCMC_eDBD_meth_repr-btd-cbt-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.930553 22754.8 1 6 CACCTG GCCACGCCCCCGCCACGCCCCC + +4 transfac_pro__M04673 15 0.930553 22754.8 1 6 CACCTG TCTCAACAATAACAAAACAACA + +4 transfac_pro__M02807-Sox100B-Sox102F-Sox15 16 0.930553 22754.8 1 6 CACCTG TGAAATTCTATTGTTCTTTATT - +4 taipale_cyt_meth__ZSCAN4_NYGCACACMCTGMAAMN_eDBD_meth 5 0.931634 22781.2 1 6 CACCTG CTGCACACCCTGAAAAT + +4 taipale_cyt_meth__ZSCAN4_NYGCACACNCTGWAARN_eDBD_repr 6 0.931634 22781.2 1 6 CACCTG GTGCACACCCTGAAAAT + +4 transfac_pro__M01371-CG11085-E5-ems-en-eve-inv-slou-unpg 2 0.931634 22781.2 1 6 CACCTG TGCCACTAATTAGTGTA + +4 transfac_pro__M01435-al-ap-Awh-CG11085-CG18599-E5-ems-en-inv-Lim3-OdsH-otp-Pph13-repo-ro-slou-unc-4-Vsx1-zfh2 1 0.931634 22781.2 1 6 CACCTG TGCCTTAATTAATGCTC + +4 transfac_pro__M07876-ey-Poxm-sv-toy 5 0.931634 22781.2 1 6 CACCTG CGTCACGCATGACTGCG + +4 transfac_pro__M07743-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.931634 22781.2 1 6 CACCTG AAACAATAACATTGTTC - +4 taipale_tf_pairs__HOXB2_PAX1_NNGTCACGNNTCATTNN_CAP-pb-Poxm 12 0.931634 22781.2 1 5 CACCTG TTAATGAAGCGTGACGG - +4 transfac_pro__M05708 14 0.931634 22781.2 1 3 CACCTG GGGGCCGTCTATTCGAC + +4 stark__CAATGCACTTCTGGGGCTTCCAC-gl 5 0.9317 22782.9 1 6 CACCTG CAATGCACTTCTGGGGCTTCCAC + +4 tfdimers__MD00065 15 0.9317 22782.9 1 6 CACCTG TTTATTTAATCTGATTAAATAAA + +4 tfdimers__MD00516-Sox100B 12 0.9317 22782.9 1 6 CACCTG ATTAAAATTGTGTAATTGTATAT + +4 bergman__Ubx-Antp-Scr-Ubx 13 0.931722 22783.4 1 6 CACCTG ACGAAGCCATTAAGCCCTC - +4 transfac_pro__M07878-ey-Poxm-sv-toy 14 0.931722 22783.4 1 5 CACCTG TTCACGCATGAGTGCACAC + +4 taipale_cyt_meth__ZSCAN31_GCATAACYGCCCYGCKKCN_FL_meth_repr 15 0.931722 22783.4 1 4 CACCTG GCATAACTGCCCCGCTGCC + +4 cisbp__M2428-cnc-Jra-kay-mor 4 0.932058 22791.6 1 6 CACCTG CCAGTGCCGATGACTCATCCAGCGCAC + +4 tfdimers__MD00087-pan 18 0.932058 22791.6 1 6 CACCTG TTTTTTTTCTAATCCTTTGATCTTTTT + +4 tfdimers__MD00131-Stat92E-Tbp 4 0.932058 22791.6 1 6 CACCTG ATTTTTACTTCCCCTTTTATAGTTTTA - +4 flyfactorsurvey__CG12155_SANGER_5_FBgn0029957-CG12155 3 0.93226 22796.6 1 6 CACCTG AAGCAACGAGTA + +4 flyfactorsurvey__toy_FlyReg_FBgn0019650-toy 0 0.93226 22796.6 1 6 CACCTG CCCCTCACTCAT + +4 neph__UW.Motif.0465 1 0.93226 22796.6 1 6 CACCTG TTTCAAAACAAA + +4 cisbp__M1727-bab1 2 0.93226 22796.6 1 6 CACCTG AATATATTAATA - +4 homer__DCYAAAAATAGM_Mef2c-Mef2-rump 2 0.93226 22796.6 1 6 CACCTG GCTATTTTTAGC - +4 jaspar__MA0041.1-bin-fd59A 5 0.93226 22796.6 1 6 CACCTG AAACAAACATTC - +4 taipale__POU3F2_DBD_WTATGCWAATKA-Dll-dve-nub-pdm2-pdm3-vvl 5 0.93226 22796.6 1 6 CACCTG TAATTTGCATAA - +4 transfac_pro__M03893-brm-btd-CTCF-ERR-HDAC1-klu-Nelf-E-sd-Spps-sr-SREBP 0 0.93226 22796.6 1 6 CACCTG CCCCGCCCCCGC - +4 transfac_pro__M06201 6 0.93226 22796.6 1 6 CACCTG TCTTCTTCCCAG - +4 transfac_pro__M06372 5 0.93226 22796.6 1 6 CACCTG GCTTCTCCCTCG - +4 transfac_pro__M06690 2 0.93226 22796.6 1 6 CACCTG TCCGCCGGCATG - +4 cisbp__M1200-Antp-Awh-Dr-Lim3-OdsH-Scr-al-gsb-gsb-n-pdm3-prd-repo-unc-4-vvl -1 0.93226 22796.6 1 5 CACCTG TACTAATTAATT + +4 homer__AVYTATCGATAD_DREF-Dref-pnr -1 0.93226 22796.6 1 5 CACCTG AACTATCGATAG + +4 homer__GATGACTCAGCA_NF-E2-Jra-Mef2-cnc-kay-maf-S-nej-tj 7 0.93226 22796.6 1 5 CACCTG GATGACTCAGCA + +4 transfac_pro__M08925-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 7 0.93226 22796.6 1 5 CACCTG GATGAGTCATCC + +4 transfac_pro__M05983 7 0.93226 22796.6 1 5 CACCTG GCTTATAAACAC - +4 transfac_pro__M06575 7 0.93226 22796.6 1 5 CACCTG GGAATCATCCCA - +4 transfac_pro__M06647 7 0.93226 22796.6 1 5 CACCTG TCATCAAGCCCT - +4 transfac_pro__M06671-CG2120 7 0.93226 22796.6 1 5 CACCTG TATTTTGCCCCC - +4 taipale__MEF2A_DBD_KCTAWAAATAGM_repr-Mef2-rump -2 0.93226 22796.6 1 4 CACCTG TCTAAAAATAGA + +4 transfac_pro__M05818 8 0.93226 22796.6 1 4 CACCTG GAAACGAGCACA + +4 transfac_pro__M06914 8 0.93226 22796.6 1 4 CACCTG TTCGCAAATTCA - +4 transfac_pro__M05235 9 0.93226 22796.6 1 3 CACCTG ATTAAATTTAAC - +4 transfac_pro__M06938-Mef2 -3 0.93226 22796.6 1 3 CACCTG CTTAAATTTAAG - +4 cisbp__M4848-ab 5 0.932389 22799.7 1 6 CACCTG CCCCCAAACTGATTAATCAAAACC - +4 flyfactorsurvey__CG32830_SOLEXA_5_FBgn0052830-ab 5 0.932389 22799.7 1 6 CACCTG CCCCCAAACTGATTAATAACAACC - +4 tfdimers__MD00469-E2f1 8 0.932389 22799.7 1 6 CACCTG AAAAAAGAAAAGTGAAAGTAAAAA - +4 tfdimers__MD00089-Stat92E 4 0.932659 22806.3 1 6 CACCTG TTTTTTACTTCCTCTTTCCTTTTTT + +4 cisbp__M5168-rn 1 0.932659 22806.3 1 6 CACCTG GTGCTTTGATTGTTTTTTTTGTTCG - +4 tfdimers__MD00297-zfh1 15 0.932659 22806.3 1 6 CACCTG AAAAAAATGCAAACAAACAAAAAAA - +4 tfdimers__MD00298 5 0.933161 22818.6 1 6 CACCTG ATATTTAATTATGTAAATAAACAAAAATAAAA + +4 transfac_pro__M01404 10 0.933968 22838.3 1 6 CACCTG CTACCAATAAAATTCT + +4 cisbp__M2593-z 9 0.933968 22838.3 1 6 CACCTG AATTTCACTCAAATTA - +4 hocomoco__DLX1_HUMAN.H11MO.0.D-CG34367-Dll-dve-en-inv-nub-pdm2-unpg-vvl 4 0.933968 22838.3 1 6 CACCTG TAATTAGCATAATTTA - +4 transfac_pro__M09099 1 0.933968 22838.3 1 6 CACCTG AAAACTATATAATATA - +4 transfac_public__M00283-z 9 0.933968 22838.3 1 6 CACCTG AATTTCACTCAAATTA - +4 hdpi__SOX13-Sox102F 0 0.934021 22839.6 1 6 CACCTG GGCTTT - +4 cisbp__M5150-Antp-CG11294-CG32532-CG34367-CG9876-en-Lim1-lms-OdsH-PHDP-Rx-Scr-slou-Traf4-unc-4-unpg-Vsx1-Vsx2 1 0.934021 22839.6 1 5 CACCTG TTAATT + +4 fantom__motif116_CCAARA -2 0.934021 22839.6 1 4 CACCTG CCAAGA + +4 transfac_pro__M01275 -2 0.934021 22839.6 1 4 CACCTG CATTAA + +4 bergman__cad-cad -2 0.934021 22839.6 1 4 CACCTG CATAAA - +4 hdpi__FOXM1-foxo -4 0.934021 22839.6 1 2 CACCTG TGCAAA + +4 hdpi__PICK1-PICK1 -4 0.934021 22839.6 1 2 CACCTG TGACAA - +4 cisbp__M0902-acj6-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-E5-ems-en-ey-HGTX-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.934123 22842.1 1 6 CACCTG TTAATTAG + +4 cisbp__M1223-al-ap-CG34367-dve-ey-ind-lab-Lim1-Lim3-Lmx1a-OdsH-repo-ro-toy-unc-4-unpg-Vsx1-Vsx2-zen2 1 0.934123 22842.1 1 6 CACCTG TTAATTAG + +4 cisbp__M1289 0 0.934123 22842.1 1 6 CACCTG TTCCGCGT + +4 cisbp__M4014-Tbp 2 0.934123 22842.1 1 6 CACCTG TATAAATA + +4 cisbp__M5586-al-ap-Awh-B-H1-B-H2-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ey-ind-inv-lbe-lbl-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-Rx-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.934123 22842.1 1 6 CACCTG TTAATTAG + +4 cisbp__M5602-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ind-inv-lbe-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-tup-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.934123 22842.1 1 6 CACCTG TTAATTGG + +4 flyfactorsurvey__ftz_FlyReg_FBgn0001077-Antp-Dfd-Scr-Ubx-abd-A-ftz 1 0.934123 22842.1 1 6 CACCTG GGCAATTA + +4 taipale_cyt_meth__GSC_YTAATCCN_eDBD_meth-bcd-Gsc-oc 2 0.934123 22842.1 1 6 CACCTG CTAATCCG + +4 cisbp__M0145 2 0.934123 22842.1 1 6 CACCTG ATTATTTT - +4 cisbp__M1066-C15 2 0.934123 22842.1 1 6 CACCTG ATTAATTA - +4 cisbp__M1115 0 0.934123 22842.1 1 6 CACCTG TATATTAA - +4 cisbp__M4980-abd-A-Antp-Dfd-ftz-Scr-Ubx 1 0.934123 22842.1 1 6 CACCTG GGCAATTA - +4 cisbp__M5144-pan 0 0.934123 22842.1 1 6 CACCTG GATCAAAG - +4 flyfactorsurvey__pan_FlyReg_FBgn0085432-pan 0 0.934123 22842.1 1 6 CACCTG GATCAAAG - +4 predrem__nrMotif2058 1 0.934123 22842.1 1 6 CACCTG GCAATTCC - +4 taipale__LHX9_DBD_NYAATTAN-al-ap-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-ind-inv-lbe-lbl-Lim3-lms-OdsH-otp-Pph13-repo-Rx-slou-tup-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.934123 22842.1 1 6 CACCTG TTAATTGG - +4 taipale_cyt_meth__DLX1_NYAATTAN_eDBD-bsh-Dll-Dr-Lim1 1 0.934123 22842.1 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DLX3_NYAATTAN_eDBD_meth-Dll 1 0.934123 22842.1 1 6 CACCTG ATAATTGC - +4 transfac_pro__M07776-al-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.934123 22842.1 1 6 CACCTG CTAATTGG - +4 jaspar__MA0352.1 -1 0.934123 22842.1 1 5 CACCTG TCCGCGGA + +4 stark__YGATAAGC-pnr 3 0.934123 22842.1 1 5 CACCTG GCTTATCA - +4 predrem__nrMotif1891 -2 0.934123 22842.1 1 4 CACCTG GCTTTGAG + +4 cisbp__M4740-abd-A-al-ap-Awh-CG18599-CG9876-dve-E5-ems-en-eve-ind-inv-lab-lbl-Lim3-otp-pb-Pph13-ro-Rx-Ubx-unpg-zen2-zfh2 4 0.934123 22842.1 1 4 CACCTG TAATTAGC - +4 flyfactorsurvey__CG32105_SOLEXA_FBgn0052105-Antp-CG4328-CG32532-Dbx-E5-Lmx1a-Rx-Ubx-Vsx1-ap-cad-en-exex-lab-repo-slou-unpg 4 0.934123 22842.1 1 4 CACCTG TAATTAAA - +4 predrem__nrMotif1261 -2 0.934123 22842.1 1 4 CACCTG CCAATTCT - +4 cisbp__M5944-ap-Awh-CG18599-CG32532-CG4328-Dfd-E5-ems-en-eve-ind-Lim3-Lmx1a-OdsH-otp-pb-Pph13-Rx-unpg-Vsx1-zen2 5 0.934123 22842.1 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__EVX2_NYAATTAN_eDBD_meth-Antp-Awh-btn-CG18599-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-pb-Scr-slou-Ubx-unpg-Vsx1-Vsx2 5 0.934123 22842.1 1 3 CACCTG CTAATTAG + +4 taipale_cyt_meth__LHX6_MTCGTTAN_FL_meth-Awh-ind-unpg -3 0.934123 22842.1 1 3 CACCTG CTCGTTAG + +4 taipale_cyt_meth__PDX1_YTAATTAN_eDBD-Antp-Awh-CG4328-Dfd-E5-ems-en-eve-exex-ind-inv-Lmx1a-pb-Scr-Ubx-Vsx1-Vsx2-zen2 -3 0.934123 22842.1 1 3 CACCTG CTAATTAC + +4 taipale_cyt_meth__PDX1_YTAATTAN_eDBD_meth-Antp-Awh-CG4328-Dfd-E5-ems-eve-ind-Lmx1a-pb-Scr-Ubx-Vsx1-Vsx2-zen2 5 0.934123 22842.1 1 3 CACCTG CTAATTAC + +4 transfac_pro__M07794-ey -3 0.934123 22842.1 1 3 CACCTG CTAATTAG + +4 taipale_cyt_meth__LHX4_NTAATTAN_eDBD-abd-A-al-Antp-Awh-bsh-btn-Dfd-E5-ems-en-exex-inv-lab-Lim1-Lim3-pb-Scr-slou-Ubx 5 0.934123 22842.1 1 3 CACCTG GTAATTAC - +4 cisbp__M0064 6 0.934123 22842.1 1 2 CACCTG TAAGCCCA - +4 swissregulon__hs__PRRX1_2.p2 0 0.934422 22849.4 1 5 CACCTG TAATT - +4 dbcorrdb__E2F4__ENCSR000EVL_1__m1-Dp-E2f1-E2f2-Sin3A 5 0.934463 22850.4 1 6 CACCTG CATTCAAATTTCCCGCCCCC + +4 dbcorrdb__KDM5B__ENCSR000AQA_1__m2-lid-pho-phol-Taf1 9 0.934463 22850.4 1 6 CACCTG TGGCGCCGCTATCGCGGCCG + +4 dbcorrdb__ZNF143__ENCSR000EBW_1__m3-E(z)-Myc-RpII215-tna 9 0.934463 22850.4 1 6 CACCTG CGGCGGCGCTTCGCGGCGGG + +4 homer__NTNATGCAAYMNNHTGMAAY_CEBP_CEBP 7 0.934463 22850.4 1 6 CACCTG ATTATGCAATAGGATGCAAT + +4 dbcorrdb__EGR1__ENCSR000BRG_1__m1-Brf-brm-btd-CoRest-crol-ct-CTCF-ERR-E(z)-HDAC1-klu-luna-Myc-Nelf-E-Rbbp5-RpII215-sd-Spps-Spt20-sr-SREBP-tna-vtd 0 0.934463 22850.4 1 6 CACCTG CCCCCCCCCCCGCCCCCGCA - +4 dbcorrdb__NFYB__ENCSR000DNR_1__m2-btd-dar1-E2f2-kay-luna-Nf-YA-Nf-YB-Sp1-Spps 14 0.934463 22850.4 1 6 CACCTG GCCTAGGCCCCGCCCCCTCC - +4 dbcorrdb__RBBP5__ENCSR000AQI_1__m2-Rbbp5 2 0.934463 22850.4 1 6 CACCTG GCCCGCGTTGCCGCGGAAGC - +4 taipale_tf_pairs__ERF_ONECUT2_RSCGGAANNNNNNRTCGATN_CAP-Ets21C-onecut 4 0.934463 22850.4 1 6 CACCTG AATCGATCGGCACTTCCGGT - +4 transfac_pro__M05379 3 0.934463 22850.4 1 6 CACCTG ATAAGCCTTATCCGCCCCAC - +4 dbcorrdb__POLR2A__ENCSR000DMN_1__m1-E(z)-RpII215-Taf1 -1 0.934463 22850.4 1 5 CACCTG CGCTTCCGCCGCCGCGGCGC + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DZK_1__m2-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha -1 0.934463 22850.4 1 5 CACCTG GCCTATAAACGCGGCGGCGC - +4 taipale_cyt_meth__ETV7_NYTTCCSGGAARN_FL_repr-aop-Stat92E 2 0.934547 22852.5 1 6 CACCTG ACTTCCGGGAAGT + +4 hocomoco__BHE22_HUMAN.H11MO.0.D-HLH54F-Oli-amos-ato-crp-dimm-tap-twi 3 0.934547 22852.5 1 6 CACCTG AAAAACATATGGT - +4 scertf__zhu.PHO2-Antp-CG4328-Lmx1a-Scr 0 0.934547 22852.5 1 6 CACCTG CCCATTAATTAAT - +4 taipale_cyt_meth__ELF3_NATKGCGGATGYN_eDBD_repr 0 0.934547 22852.5 1 6 CACCTG CGCATCCGCAATG - +4 taipale_cyt_meth__MAFG_NWWWNTGCTGACN_eDBD-cic-maf-S-tj 6 0.934547 22852.5 1 6 CACCTG AGTCAGCAATTTT - +4 hocomoco__BACH1_HUMAN.H11MO.0.A-Jra-cnc-ewg-kay-maf-S -1 0.934547 22852.5 1 5 CACCTG TGCTGAGTCATGC + +4 transfac_pro__M07705-Ets98B 9 0.934547 22852.5 1 4 CACCTG ATGATCCGGGACA - +4 cisbp__M6088-D-Sox15-Sox21a-Sox21b-SoxN 6 0.935271 22870.2 1 6 CACCTG ATGAATAACATTCAT + +4 homer__ACCGTGACTAATTNN_PAX3_FKHR-fusion-C15-foxo-gsb-gsb-n-prd 0 0.935271 22870.2 1 6 CACCTG ACCGTGACTAATTGA + +4 jaspar__MA0496.1-cic-cnc-maf-S-tj 9 0.935271 22870.2 1 6 CACCTG CTGAGTCAGCAATTT + +4 jaspar__MA0497.1-Mef2-rump 0 0.935271 22870.2 1 6 CACCTG ATGCTAAAAATAGAA + +4 taipale__Sox1_DBD_NTGAATWNCATTCAN-D-Sox15-Sox21a-Sox21b-SoxN 6 0.935271 22870.2 1 6 CACCTG ATGAATAACATTCAT + +4 cisbp__M4504-brm-btd-CTCF-HDAC1-kay-klu-luna-Nelf-E-Nf-YB-sd-Spps-sr-SREBP 0 0.935271 22870.2 1 6 CACCTG CCCCGCCCCCGCACC - +4 cisbp__M5660-C15-Nf1-NfI 4 0.935271 22870.2 1 6 CACCTG TTGGCACCGTGCCAA - +4 flyfactorsurvey__kenF1-CG4360_F2-3_SOLEXA_5 0 0.935271 22870.2 1 6 CACCTG CCACCACAACAAATG - +4 hocomoco__CDC5L_HUMAN.H11MO.0.D-Cdc5 9 0.935271 22870.2 1 6 CACCTG ATTATGTTAAATCCC - +4 jaspar__MA0535.1-Mad 0 0.935271 22870.2 1 6 CACCTG CGGCGGCGGCGCCTG - +4 transfac_pro__M03807-Brf-brm-btd-CG3065-CG42741-CTCF-dar1-ERR-E(z)-HDAC1-kay-Klf15-klu-Nf-YA-Nf-YB-Rbbp5-Sp1-Spps-Spt20-SREBP-vtd 9 0.935271 22870.2 1 6 CACCTG GGCCCCGCCCCCCCC - +4 transfac_pro__M09101 9 0.935271 22870.2 1 6 CACCTG ATTTAATTTTAATTT - +4 transfac_pro__M09214 9 0.935271 22870.2 1 6 CACCTG ATTGGAATATTCTTT - +4 transfac_public__M00131-croc-fd59A-fkh 8 0.935271 22870.2 1 6 CACCTG TAAATAAATATTTCA - +4 transfac_pro__M09178 -1 0.935271 22870.2 1 5 CACCTG ACCTCAGCCGCAAAA + +4 factorbook__MEF2-Mef2-rump -1 0.935271 22870.2 1 5 CACCTG TTCTATTTTTGGCAC - +4 transfac_pro__M07724-fd96Ca-fd96Cb-slp2 11 0.935271 22870.2 1 4 CACCTG TTTGTTGTAAACAAA + +4 bergman__h-h 4 0.935495 22875.7 1 6 CACCTG GCGGCACGCGCCAT + +4 transfac_public__M00067-h 4 0.935495 22875.7 1 6 CACCTG GCGGCACGCGCCAT + +4 flyfactorsurvey__CG2052_SANGER_2.5_FBgn0039905-FoxP-dati 8 0.935495 22875.7 1 6 CACCTG ATTTTTTTGGTTTT - +4 cisbp__M5440-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.935495 22875.7 1 4 CACCTG TGTCAATATTTACA + +4 cisbp__M1788 3 0.935535 22876.6 1 6 CACCTG TTATTCCGGAA + +4 taipale__KLF16_DBD_GCCMCGCCCMC_repr-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.935535 22876.6 1 6 CACCTG GCCACGCCCCC + +4 taipale_cyt_meth__PROP1_TAATTNNATTA_FL_meth-al-bsh-CG11294-CG32532-CG34367-CG9876-Dr-Drgx-en-inv-OdsH-Optix-repo-Rx-Traf4-unc-4 0 0.935535 22876.6 1 6 CACCTG TAATTGGATTA + +4 tiffin__TIFDMEM0000118 0 0.935535 22876.6 1 6 CACCTG TATCGATAAAT + +4 cisbp__M0460 1 0.935535 22876.6 1 6 CACCTG GATCATGCATG - +4 cisbp__M2272-E2f1-E2f2 2 0.935535 22876.6 1 6 CACCTG CTTTCCCGCCC - +4 jaspar__MA0470.1-E2f1-E2f2 2 0.935535 22876.6 1 6 CACCTG CCTTCCCGCCC - +4 tiffin__TIFDMEM0000014 0 0.935535 22876.6 1 6 CACCTG TTCTTAAATTA - +4 transfac_pro__M05174 1 0.935535 22876.6 1 6 CACCTG TATCCCAATTT - +4 transfac_pro__M09102-hbn 3 0.935535 22876.6 1 6 CACCTG AATTAAATTAT - +4 yetfasco__YER069W_1426 0 0.935535 22876.6 1 6 CACCTG CGCCGTTTAGC - +4 jaspar__MA0102.3-Irbp18-Xrp1-nej 6 0.935535 22876.6 1 5 CACCTG ATTGCACAATA + +4 jaspar__MA0419.1 6 0.935535 22876.6 1 5 CACCTG ATTAGTAAGCA + +4 cisbp__M1847 6 0.935535 22876.6 1 5 CACCTG TTTGTTTACTA - +4 cisbp__M1925-Irbp18-nej-Xrp1 6 0.935535 22876.6 1 5 CACCTG ATTGCACAATA - +4 cisbp__M2224 6 0.935535 22876.6 1 5 CACCTG ATTAGTAAGCA - +4 cisbp__M1212 -2 0.935535 22876.6 1 4 CACCTG ACTAATCATTT + +4 taipale_cyt_meth__HOXD13_NCTCGTAAAAN_eDBD_meth -2 0.935535 22876.6 1 4 CACCTG GCTCGTAAAAC + +4 cisbp__M2302-scro -2 0.935535 22876.6 1 4 CACCTG CTTGAGTGGCT - +4 cisbp__M4531-bon-cnc-CoRest-Jra-kay-Mef2-mor-Myc-nej-pan-Stat92E 7 0.935535 22876.6 1 4 CACCTG GATGAGTCATC - +4 taipale_cyt_meth__HOXA10_NGTCGTAAAAN_FL_meth_repr-Abd-B-cad 7 0.935535 22876.6 1 4 CACCTG GTTTTACGACC - +4 transfac_pro__M03539-arm -2 0.935535 22876.6 1 4 CACCTG GCTTTGATGAC - +4 transfac_pro__M08992 7 0.935535 22876.6 1 4 CACCTG GGGGCTTAGCC - +4 transfac_pro__M09336 -2 0.935535 22876.6 1 4 CACCTG CCTTATCCATT - +4 transfac_pro__M05200-Mef2 -3 0.935535 22876.6 1 3 CACCTG CTTAAATTTAA - +4 transfac_pro__M06442-Jra-REPTOR-BP 6 0.93578 22882.6 1 6 CACCTG GTATGTGACGTCATTGGC + +4 hocomoco__BATF_MOUSE.H11MO.0.A-Jra-MTA1-like-NFAT-Stat92E-ebi-foxo-nej 6 0.93578 22882.6 1 6 CACCTG CTGAGTCATTTCGAAACT - +4 transfac_pro__M06030 12 0.93578 22882.6 1 6 CACCTG ATGGGGCCCTACTACGAC - +4 transfac_pro__M06905 14 0.93578 22882.6 1 4 CACCTG GGGGGAAAACGAAGCAGC + +4 transfac_pro__M05625 14 0.93578 22882.6 1 4 CACCTG TCCATCATGGCCCCCCCC - +4 jaspar__MA0170.1-Antp-C15-Dfd-HGTX-Scr-Ubx-abd-A-bsh-slou 1 0.936049 22889.2 1 6 CACCTG TTAATTA + +4 cisbp__M1987-abd-A-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-E5-ems-en-hbn-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2 0 0.936049 22889.2 1 6 CACCTG TAATTAA - +4 cisbp__M2007-al-Antp-Awh-C15-CG18599-CG34367-CG4328-CG9876-Dll-E5-ems-en-eve-exex-inv-lab-lbe-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-unc-4-unpg-Vsx1-Vsx2-vvl 0 0.936049 22889.2 1 6 CACCTG TAATTAG - +4 cisbp__M2009-Pph13 0 0.936049 22889.2 1 6 CACCTG TAATTAG - +4 cisbp__M4223 0 0.936049 22889.2 1 6 CACCTG TACGCGT - +4 flyfactorsurvey__Odsh_Cell_FBgn0026058-Antp-Awh-C15-CG4328-CG9876-CG18599-CG34367-Dll-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Vsx1-Vsx2-al-ems-en-eve-exex-inv-lab-lbe-lms-otp-pb-repo-ro-unc-4-unpg-vvl 0 0.936049 22889.2 1 6 CACCTG TAATTAG - +4 jaspar__MA0200.1-Pph13 0 0.936049 22889.2 1 6 CACCTG TAATTAG - +4 jaspar__MA0329.1 0 0.936049 22889.2 1 6 CACCTG TACGCGT - +4 predrem__nrMotif1527 1 0.936049 22889.2 1 6 CACCTG CAGTCTG - +4 transfac_pro__M01951 0 0.936049 22889.2 1 6 CACCTG TACGCGT - +4 predrem__nrMotif2083 2 0.936049 22889.2 1 5 CACCTG AGCCCAT + +4 predrem__nrMotif173 2 0.936049 22889.2 1 5 CACCTG TGCTCTT - +4 transfac_pro__M02096-ftz-Ubx -1 0.936049 22889.2 1 5 CACCTG CCATTAG - +4 hdpi__ASPSCR1-CG33722 3 0.936049 22889.2 1 4 CACCTG AGCAATC - +4 hdpi__CENTG1-CenG1A -3 0.936049 22889.2 1 3 CACCTG CTGCAAA + +4 predrem__nrMotif1580 -3 0.936049 22889.2 1 3 CACCTG TTGTCAA + +4 hdpi__CBFA2T2-nvy -4 0.936049 22889.2 1 2 CACCTG TGGGAGC + +4 cisbp__M1588-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 3 0.936557 22901.6 1 6 CACCTG ATTGTTTTC + +4 cisbp__M1911 3 0.936557 22901.6 1 6 CACCTG GTAAACAAT + +4 cisbp__M5738-nub-pdm2-Sox15-SoxN-Tbp-vvl 3 0.936557 22901.6 1 6 CACCTG ATTTGCATA + +4 jaspar__MA0084.1 3 0.936557 22901.6 1 6 CACCTG GTAAACAAT + +4 predrem__nrMotif218 0 0.936557 22901.6 1 6 CACCTG TAACACAAA + +4 predrem__nrMotif2279 3 0.936557 22901.6 1 6 CACCTG TTGTCTCTA + +4 predrem__nrMotif489 0 0.936557 22901.6 1 6 CACCTG TCACTGCCC + +4 hocomoco__PBX3_HUMAN.H11MO.1.A 0 0.936557 22901.6 1 6 CACCTG TGCCAATCA - +4 neph__UW.Motif.0026 3 0.936557 22901.6 1 6 CACCTG TTTCACAAT - +4 predrem__nrMotif741 3 0.936557 22901.6 1 6 CACCTG TTTATTCTG - +4 stark__TTTNGGCGS 1 0.936557 22901.6 1 6 CACCTG CCGCCAAAA - +4 cisbp__M0392-btd-kay-Klf15-klu-Nf-YA-Sp1-Spps-sr 4 0.936557 22901.6 1 5 CACCTG CCCGCCCCC - +4 fantom__motif92_GCGKWWNAA 4 0.936557 22901.6 1 5 CACCTG TTAATACGC - +4 transfac_pro__M05600 5 0.936557 22901.6 1 4 CACCTG GGACTAAGC + +4 cisbp__M5092-lola -2 0.936557 22901.6 1 4 CACCTG GCTCAATAA - +4 bergman__Stat92E-Stat92E-aop 14 0.936574 22902 1 6 CACCTG TACCATTTCCGGGAAAAATCC - +4 transfac_public__M00259-aop-Stat92E 14 0.936574 22902 1 6 CACCTG TACCATTTCCGGGAAAACTCC - +4 taipale_tf_pairs__ETV2_SOX15_RSCGGAWNNNNNNNACAATRN_CAP_repr-pnt -1 0.936574 22902 1 5 CACCTG ACCGGAAGTCAAAAACAATGG + +4 tfdimers__MD00254 21 0.936691 22904.9 1 6 CACCTG AAAAAAATGCAAATAATTAATTACAAAAAA + +4 tfdimers__MD00270-Dbx 9 0.936691 22904.9 1 6 CACCTG AAATAAAATTACTTAATTAATTAAAAAAAA - +4 tfdimers__MD00442-E(bx) 20 0.936691 22904.9 1 6 CACCTG ATTTTTTTTTGTTAATCATTAACATAATTA - +4 cisbp__M0676 4 0.936961 22911.5 1 6 CACCTG AGCCCGCCAA + +4 cisbp__M3021-ct 0 0.936961 22911.5 1 6 CACCTG AATCGATCGC + +4 jaspar__MA0038.1 2 0.936961 22911.5 1 6 CACCTG CAAATCACTG + +4 swissregulon__sacCer__PDR1-NFAT 1 0.936961 22911.5 1 6 CACCTG TTTCCGCGGA + +4 taipale__GSC_full_NNTAATCCNN-bcd-Gsc-oc-Ptx1 3 0.936961 22911.5 1 6 CACCTG GCTAATCCCC + +4 transfac_pro__M05014 4 0.936961 22911.5 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M07875-gsb-gsb-n-prd 1 0.936961 22911.5 1 6 CACCTG TAATCGATTA + +4 transfac_public__M00104-ct 0 0.936961 22911.5 1 6 CACCTG AATCGATCGC + +4 yetfasco__YDL106C_2154 1 0.936961 22911.5 1 6 CACCTG ATATATTACT + +4 cisbp__M1581-cic-maf-S 3 0.936961 22911.5 1 6 CACCTG AGTCAGCAAA - +4 cisbp__M1870 2 0.936961 22911.5 1 6 CACCTG CAAATCACTG - +4 cisbp__M4706-Stat92E 1 0.936961 22911.5 1 6 CACCTG TTTCCGGGAA - +4 predrem__nrMotif510 2 0.936961 22911.5 1 6 CACCTG GGGGCCTTGG - +4 predrem__nrMotif670 4 0.936961 22911.5 1 6 CACCTG TGACATCATT - +4 predrem__nrMotif770 3 0.936961 22911.5 1 6 CACCTG TTTTATATAT - +4 transfac_pro__M03177 1 0.936961 22911.5 1 6 CACCTG GCAGCGGCAT - +4 transfac_pro__M05098 1 0.936961 22911.5 1 6 CACCTG TAACCGGCGT - +4 transfac_pro__M07597-klu-sr 1 0.936961 22911.5 1 6 CACCTG ACGCCCACGC - +4 transfac_pro__M08971-D-Mad-Sox14-Sox15-Sox21a-Sox21b 2 0.936961 22911.5 1 6 CACCTG AAAACAATAG - +4 cisbp__M1602-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 5 0.936961 22911.5 1 5 CACCTG ATTGTTCTGC + +4 flyfactorsurvey__CG10267_SANGER_5_FBgn0037446-Zif 5 0.936961 22911.5 1 5 CACCTG ACCAACACTA + +4 predrem__nrMotif2662 5 0.936961 22911.5 1 5 CACCTG CCGCGCTCCC + +4 predrem__nrMotif967 -1 0.936961 22911.5 1 5 CACCTG TCTTTCTAAA + +4 cisbp__M4800-Zif 5 0.936961 22911.5 1 5 CACCTG AACAACACTA - +4 transfac_pro__M00311 -1 0.936961 22911.5 1 5 CACCTG GCTTAAATAC - +4 cisbp__M1178-CG34367-Lim3-OdsH-al-repo-unc-4-unpg -2 0.936961 22911.5 1 4 CACCTG ACTAATTAAG + +4 cisbp__M2313-D-Mad-Sox100B-Sox102F-Sox14-SoxN -2 0.936961 22911.5 1 4 CACCTG CCATTGTTTT + +4 cisbp__M6263-sens-sens-2 -2 0.936961 22911.5 1 4 CACCTG GCTGTGATTT + +4 hocomoco__GFI1_HUMAN.H11MO.0.C-sens-sens-2 -2 0.936961 22911.5 1 4 CACCTG GCTGTGATTT + +4 jaspar__MA0515.1-D-Mad-Sox14-Sox100B-Sox102F-SoxN -2 0.936961 22911.5 1 4 CACCTG CCATTGTTTT + +4 predrem__nrMotif2641 6 0.936961 22911.5 1 4 CACCTG TCAGCATTCT + +4 taipale__HOXB3_DBD_NNYMATTANN-abd-A-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11085-CG18599-CG32532-CG9876-Dll-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-Lim3-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 6 0.936961 22911.5 1 4 CACCTG ACTAATTAGC + +4 taipale__NOTO_DBD_NYTMATTANN-al-ap-Awh-C15-CG18599-CG34367-dve-E5-ems-en-eve-exex-hbn-ind-inv-lab-lbl-Lim3-OdsH-otp-pb-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2-zfh2 -2 0.936961 22911.5 1 4 CACCTG GCTAATTAGC + +4 transfac_pro__M05051 6 0.936961 22911.5 1 4 CACCTG AGGCCGCCCC + +4 transfac_pro__M05172 6 0.936961 22911.5 1 4 CACCTG ATGCCGCCCC + +4 cisbp__M5503-al-Antp-ap-Awh-C15-CG32532-CG34367-Dbx-Dll-E5-ems-en-HGTX-ind-lab-lms-OdsH-repo-Rx-Scr-slou-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2 6 0.936961 22911.5 1 4 CACCTG ACTAATTAAA - +4 cisbp__M5542-Antp-ap-Awh-B-H1-B-H2-bsh-btn-CG11085-CG18599-CG32532-CG9876-Dll-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-Lim3-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 6 0.936961 22911.5 1 4 CACCTG ACTAATTAGC - +4 cisbp__M5982-al-ap-Awh-C15-CG11294-CG32532-CG34367-CG9876-E5-ems-en-hbn-lbe-Lim3-OdsH-otp-Pph13-repo-Rx-unc-4-unpg-Vsx1-Vsx2 6 0.936961 22911.5 1 4 CACCTG TCTAATTAAA - +4 homer__DATGASTCAT_BATF-GATAe-Jra-MTA1-like-Mef2-Myc-NFAT-Stat92E-bon-cnc-foxo-grn-kay-mor-nej-pnr 6 0.936961 22911.5 1 4 CACCTG ATGACTCATA - +4 cisbp__M5275-CG7786-gt-Irbp18-Pdp1-slbo-Xrp1 7 0.936961 22911.5 1 3 CACCTG ATTGCGCAAC - +4 cisbp__M6170-Irbp18-Myc-nej-Xrp1 7 0.936961 22911.5 1 3 CACCTG ATTGCACAAC - +4 tfdimers__MD00558-E(bx) 5 0.938015 22937.3 1 6 CACCTG TTTTTTTTTTGTTTTGTTTGCATTTTTTT - +4 predrem__nrMotif2090-Brf-CG42741-CTCF-CoRest-E2f1-E2f2-ERR-Eip74EF-E(z)-HDAC1-Klf15-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-crol-ct-klu-luna-tna-vtd-zfh1 15 0.938147 22940.5 1 6 CACCTG CCCCCCCCTCCCCGCCCCCCCC + +4 tfdimers__MD00233 16 0.938147 22940.5 1 6 CACCTG AAAATAATTTCTTAATTATTAT + +4 transfac_pro__M02911-Sox15 4 0.938147 22940.5 1 6 CACCTG GTGCTAATTGTGTGTGTACGCT + +4 taipale_tf_pairs__CUX1_FOXO1_GTMAACANNNNNATCRATN_CAP_repr-ct-foxo 6 0.939077 22963.2 1 6 CACCTG GTAAACAAAATGATCGATA + +4 transfac_pro__M01790 12 0.939077 22963.2 1 6 CACCTG ATTAGGGCTATAGCCCTAA + +4 taipale_cyt_meth__ZNF23_NKGKCGCGGNCATGGKNGN_eDBD_repr-crol 3 0.939077 22963.2 1 6 CACCTG TCACCCATGGCCGCGACCC - +4 transfac_public__M00018-Antp-Scr-Ubx 13 0.939077 22963.2 1 6 CACCTG ACGAAGCCATTAAGCCCTC - +4 taipale_cyt_meth__ZSCAN16_NANTGTTAACAGAGCCTCN_eDBD_meth 14 0.939077 22963.2 1 5 CACCTG AGAGGCTCTGTTAACACTT - +4 cisbp__M5102-Med 1 0.939229 22967 1 6 CACCTG GCGGCTGGCAGT + +4 cisbp__M5815-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.939229 22967 1 6 CACCTG ACAATAACATTG + +4 jaspar__MA0070.1 1 0.939229 22967 1 6 CACCTG CCATCAATCAAA + +4 taipale__SOX14_DBD_ACAATANCATTG-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.939229 22967 1 6 CACCTG ACAATAACATTG + +4 taipale_cyt_meth__KLF12_NGCCGACGCCCW_FL_meth_repr-CG42741 6 0.939229 22967 1 6 CACCTG AGCCGACGCCCA + +4 taipale_cyt_meth__KLF3_NRCCGCAGCCCN_FL_meth_repr-CG42741 6 0.939229 22967 1 6 CACCTG GACCGCAGCCCA + +4 tiffin__TIFDMEM0000089 4 0.939229 22967 1 6 CACCTG TGCAAAATTTTA + +4 transfac_pro__M07428-Optix 6 0.939229 22967 1 6 CACCTG TATTAATCCTAT + +4 transfac_pro__M07708-FoxP 6 0.939229 22967 1 6 CACCTG AAACAACAACAA + +4 cisbp__M4813-CG12155 3 0.939229 22967 1 6 CACCTG AAGCAACGAGTA - +4 transfac_pro__M01088-Deaf1 0 0.939229 22967 1 6 CACCTG CATCCGAATCGC - +4 transfac_pro__M05180 2 0.939229 22967 1 6 CACCTG AACGCCGTTAAT - +4 taipale_cyt_meth__CEBPB_NRTTGCGYAAYN_eDBD-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 7 0.939229 22967 1 5 CACCTG GGTTGCGTAATG + +4 taipale_cyt_meth__CEBPE_NRTTGCGYAAYN_eDBD_meth_repr-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 7 0.939229 22967 1 5 CACCTG TATTGCGTAATA + +4 transfac_pro__M06351 -1 0.939229 22967 1 5 CACCTG TCCAAAAAAATT + +4 transfac_pro__M06920 -1 0.939229 22967 1 5 CACCTG CCCGGCTGCAGA + +4 transfac_public__M00129-bin-fd59A 7 0.939229 22967 1 5 CACCTG TATTGTTTATTT + +4 transfac_pro__M05808 7 0.939229 22967 1 5 CACCTG GATTTACGACTT - +4 transfac_pro__M06274 7 0.939229 22967 1 5 CACCTG GCTTATAAACAC - +4 transfac_pro__M06583 -1 0.939229 22967 1 5 CACCTG GCCGTTTGCCCA - +4 transfac_pro__M06609 7 0.939229 22967 1 5 CACCTG GCGTTTTGCCCC - +4 transfac_pro__M06990 -1 0.939229 22967 1 5 CACCTG ACCAATAATGGC - +4 cisbp__M6342-Mef2-rump -2 0.939229 22967 1 4 CACCTG GCTAAAAATAGC + +4 swissregulon__hs__NANOG_mouse_.p2 8 0.939229 22967 1 4 CACCTG GGGCCCATTTCC + +4 taipale_cyt_meth__CEBPD_NRTTGCGYAAYN_eDBD-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-Xrp1 8 0.939229 22967 1 4 CACCTG GGTTGCGCAATG + +4 transfac_pro__M01123 8 0.939229 22967 1 4 CACCTG GGGCCCATTTCC + +4 scertf__foat.RTG1 8 0.939229 22967 1 4 CACCTG TATCATACGATC - +4 transfac_pro__M05757 8 0.939229 22967 1 4 CACCTG GATTCTGCCACT - +4 hocomoco__FOXI1_HUMAN.H11MO.0.B-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-Spps-btd-kay -3 0.939229 22967 1 3 CACCTG CTCTGATTGGTC + +4 transfac_pro__M05481 9 0.939229 22967 1 3 CACCTG TGGGGGGGGGAC + +4 transfac_pro__M05838 -3 0.939229 22967 1 3 CACCTG CTGGCCGTAAGC + +4 transfac_pro__M06750 -3 0.939229 22967 1 3 CACCTG CTGGGAAAAAAA + +4 cisbp__M6240-btd-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps -3 0.939229 22967 1 3 CACCTG CTCTGATTGGCC - +4 tfdimers__MD00183-pho-phol 10 0.939248 22967.4 1 6 CACCTG TTAATGATTAACCATTTTTATTA - +4 tfdimers__MD00597-scro 7 0.939248 22967.4 1 6 CACCTG TATCTTTAATCTTGAGGGTTATT - +4 tfdimers__MD00019 18 0.939758 22979.9 1 6 CACCTG AATTAGTTAATTATTAATTAACTAATT + +4 tfdimers__MD00105-Pur-alpha 15 0.939927 22984 1 6 CACCTG TTTTTAGTTTCACTTCCCCTTTTT + +4 tfdimers__MD00310-oc 3 0.940157 22989.7 1 6 CACCTG ATTTTTTTGGGAGGATTAAATTTATT + +4 flyfactorsurvey__rn_SANGER_10_FBgn0259172-rn 1 0.940221 22991.2 1 6 CACCTG GTGCTTTGAGTGTTTTTTTTGGTCG - +4 cisbp__M3550-Mef2-rump 9 0.94093 23008.6 1 6 CACCTG CTCTAAAAATAACTCT + +4 taipale_tf_pairs__CUX1_HOXB13_SYMRTAAANATYGATN_CAP-ct 10 0.94093 23008.6 1 6 CACCTG GATCGATGTTTATGAG - +4 transfac_pro__M01412-al-Awh-CG11294-CG34367-CG9876-Dbx-Dr-en-inv-Lim1-Lim3-OdsH-pdm3-repo-unc-4 8 0.94093 23008.6 1 6 CACCTG GAATTAATTAGTTGCA - +4 transfac_pro__M02908-Sox102F 9 0.94093 23008.6 1 6 CACCTG CCGTATTATAATCTTA - +4 transfac_pro__M01800 0 0.941059 23011.7 1 6 CACCTG TTTTTT + +4 cisbp__M2076-bs 1 0.941059 23011.7 1 5 CACCTG AGACGC - +4 fantom__motif5_CAGTGT 1 0.941059 23011.7 1 5 CACCTG ACACTG - +4 hdpi__SF1-SF1 -1 0.941059 23011.7 1 5 CACCTG ATTTTA - +4 hdpi__GTF2B-TfIIB 3 0.941059 23011.7 1 3 CACCTG GGCAAT + +4 hdpi__GTPBP1-Dgp-1 3 0.941059 23011.7 1 3 CACCTG TCACAA + +4 cisbp__M5604-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-E5-en-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-Traf4-unc-4-unpg-Vsx1-zen2-zfh2 1 0.94122 23015.7 1 6 CACCTG TTAATTAA + +4 scertf__badis.YOX1-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-ap-ems-en-otp-repo-ro-unc-4-unpg-zen2-zfh2 1 0.94122 23015.7 1 6 CACCTG TTAATTAA + +4 taipale__LMX1A_DBD_NTAATTAN-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-E5-en-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-Traf4-unc-4-unpg-Vsx1-zen2-zfh2 1 0.94122 23015.7 1 6 CACCTG TTAATTAA + +4 taipale_cyt_meth__ALX3_CYAATTAN_eDBD-al-Awh-CG11294-CG32532-CG34367-CG4328-Drgx-en-HGTX-ind-inv-lab-Lim3-Lmx1a-OdsH-repo-unc-4-unpg-Vsx1-Vsx2-zfh2 1 0.94122 23015.7 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__LHX9_CYAATTAN_FL_meth-acj6-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-u 1 0.94122 23015.7 1 6 CACCTG CTAATTAA + +4 taipale_cyt_meth__SOX18_NACAATGN_eDBD_meth-Sox15 0 0.94122 23015.7 1 6 CACCTG AACAATGC + +4 transfac_pro__M01891 0 0.94122 23015.7 1 6 CACCTG TTACTAAT + +4 transfac_pro__M07815-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Drgx-E5-ems-en-ey-gsb-gsb-n-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-toy-Traf4-unc- 1 0.94122 23015.7 1 6 CACCTG TTAATTAA + +4 transfac_public__M00471-Tbp 2 0.94122 23015.7 1 6 CACCTG TATAAATA + +4 predrem__nrMotif2497 2 0.94122 23015.7 1 6 CACCTG GAGAGCGG - +4 predrem__nrMotif2547 0 0.94122 23015.7 1 6 CACCTG CACACGCC - +4 taipale_cyt_meth__DLX4_NYAATTAN_eDBD_meth-Dll-en 1 0.94122 23015.7 1 6 CACCTG ATAATTGC - +4 taipale_cyt_meth__DLX5_NYAATTAN_FL-Dll 1 0.94122 23015.7 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__LHX9_CYAATTAR_eDBD_meth-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-ey-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4 1 0.94122 23015.7 1 6 CACCTG TTAATTAG - +4 taipale_cyt_meth__MSX2_NCAATTAN_eDBD-Antp-Awh-B-H1-B-H2-bsh-C15-CG11085-CG18599-CG34367-Dr-E5-ems-en-exex-inv-lab-lbe-Lim3-lms-OdsH-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.94122 23015.7 1 6 CACCTG TTAATTGG - +4 taipale_cyt_meth__MSX2_NCAATTAN_eDBD_meth-al-Antp-B-H1-B-H2-CG11085-CG32532-CG34367-Dr-en-ind-inv-lab-lms-NK7.1-Scr-slou-tup-Ubx-unc-4-unpg 1 0.94122 23015.7 1 6 CACCTG TTAATTGC - +4 taipale_tf_pairs__HOXA7_NYMATTAN_HT-abd-A-Ubx 1 0.94122 23015.7 1 6 CACCTG TTAATTGC - +4 transfac_pro__M04925-bon 1 0.94122 23015.7 1 6 CACCTG GTTTCTCT - +4 predrem__nrMotif1154 3 0.94122 23015.7 1 5 CACCTG AAGCACAA + +4 taipale_cyt_meth__PITX1_NTAATCCN_eDBD-Gsc-Ptx1 3 0.94122 23015.7 1 5 CACCTG CTAATCCC + +4 taipale_cyt_meth__PITX2_NTAATCCN_eDBD_meth-Gsc-Ptx1 3 0.94122 23015.7 1 5 CACCTG CTAATCCC + +4 stark__CACGAGNC-h -1 0.94122 23015.7 1 5 CACCTG GACTCGTG - +4 cisbp__M5077-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-lab-Lim3-otp-pb-Pph13-ro-Rx-slou-toy-unpg-Vsx1-zen2 -2 0.94122 23015.7 1 4 CACCTG ATTAATTA + +4 cisbp__M5282-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-Lim3-pb-Scr-zen-zen2 -2 0.94122 23015.7 1 4 CACCTG CTTAATGA + +4 flyfactorsurvey__Lim3_Cell_FBgn0002023-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-E5-Lim3-Pph13-Rx-Vsx1-ap-ems-en-ey-ind-lab-otp-pb-ro-slou-toy-unpg-zen2 -2 0.94122 23015.7 1 4 CACCTG ATTAATTA + +4 flyfactorsurvey__Zen_SOLEXA_FBgn0004053-Antp-Awh-CG18599-Dfd-E5-Lim3-Scr-abd-A-ap-bsh-btn-ems-eve-ftz-ind-lab-otp-pb-zen-zen2 -2 0.94122 23015.7 1 4 CACCTG CTTAATGA + +4 hdpi__TSN-trsn -2 0.94122 23015.7 1 4 CACCTG ATTGGAAA + +4 jaspar__MA0950.1 -2 0.94122 23015.7 1 4 CACCTG AATGATTG + +4 cisbp__M4844-Antp-ap-cad-CG32532-CG4328-Dbx-en-exex-lab-Lmx1a-repo-Rx-slou-Ubx-unpg-Vsx1 4 0.94122 23015.7 1 4 CACCTG TAATTAAA - +4 cisbp__M5073-abd-A-al-ap-Awh-CG18599-E5-ems-eve-ind-lbl-Lim1-Lim3-otp-pb-PHDP-Pph13-ro-Rx-Ubx-unpg-zen2 4 0.94122 23015.7 1 4 CACCTG TAATTAGC - +4 flyfactorsurvey__Ap_Cell_FBgn0000099-Awh-CG9876-CG18599-E5-Lim3-Pph13-Rx-Ubx-abd-A-al-ap-dve-ems-en-eve-ind-inv-lab-lbl-otp-pb-repo-ro-unpg-zen2-zfh2 4 0.94122 23015.7 1 4 CACCTG TAATTAGC - +4 flyfactorsurvey__Lbl_Cell_FBgn0008651-Awh-CG18599-E5-Lim3-Pph13-Rx-Ubx-abd-A-al-ap-ems-eve-ind-lbl-otp-pb-ro-unpg-zen2 4 0.94122 23015.7 1 4 CACCTG TAATTAGC - +4 taipale_cyt_meth__BSX_NYAATTAN_eDBD_meth-abd-A-Antp-B-H1-B-H2-bsh-btn-Dfd-Dll-Dr-E5-ems-en-exex-inv-lab-Lim1-Lim3-lms-pb-Rx-Scr-slou-Ubx-unpg-Vsx1 5 0.94122 23015.7 1 3 CACCTG GCAATTAC + +4 taipale_cyt_meth__HOXB6_YTAATTRY_eDBD-abd-A-Antp-Dfd-Dll-en-ftz-ind-lab-lms-Scr-tup-Ubx-unpg-zen2 5 0.94122 23015.7 1 3 CACCTG TTAATTAC + +4 taipale_cyt_meth__HOXB7_NYAATTAN_eDBD-abd-A-Antp-bsh-btn-Dfd-Dll-exex-lab-Lim1-Lim3-Scr-Ubx 5 0.94122 23015.7 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__HOXB7_NYAATTAN_eDBD_meth-abd-A-Antp-bsh-btn-Dfd-Dll-exex-Lim3-Scr-Ubx 5 0.94122 23015.7 1 3 CACCTG GTAATTAC + +4 taipale_cyt_meth__VAX1_NYAATTAN_eDBD_meth-abd-A-Antp-Awh-B-H1-B-H2-bsh-btn-C15-CG11085-CG18599-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim1-Lim3-lms-OdsH-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen- 5 0.94122 23015.7 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__VSX2_YTAATTAN_eDBD-Awh-CG11294-CG18599-CG9876-Drgx-E5-ems-en-eve-exex-ind-inv-Lim3-OdsH-pb-ro-Rx-Ubx-unpg-Vsx1-Vsx2 -3 0.94122 23015.7 1 3 CACCTG CTAATTAG + +4 transfac_pro__M04063 5 0.94122 23015.7 1 3 CACCTG GAAATTAC + +4 taipale_cyt_meth__LHX4_NTAATTAN_eDBD_meth-abd-A-al-Antp-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Dr-Drgx-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-pdm 5 0.94122 23015.7 1 3 CACCTG CTAATTAG - +4 taipale_cyt_meth__NOTO_NYAATTAN_eDBD-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-OdsH-pb-pdm3-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 -3 0.94122 23015.7 1 3 CACCTG CTAATTAG - +4 transfac_pro__M07801-abd-A-Antp-bsh-btn-HGTX-Scr-Ubx 5 0.94122 23015.7 1 3 CACCTG TTAATTAC - +4 transfac_pro__M08926-bon-cnc-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-Stat92E 5 0.94122 23015.7 1 3 CACCTG TGAGTCAT - +4 transfac_pro__M07818-al-CG32532-OdsH-PHDP-repo-Rx-unc-4 2 0.941364 23019.2 1 6 CACCTG CTAATCGAATTAC + +4 cisbp__M4672-E2f1 -1 0.941364 23019.2 1 5 CACCTG AAATTCGCGCCAA + +4 hocomoco__EVX1_HUMAN.H11MO.0.D-cad-eve 8 0.941364 23019.2 1 5 CACCTG TGATTTATGGCCT + +4 stark__AATTRNNNNNCAA 8 0.941364 23019.2 1 5 CACCTG TTGAAAAACAATT - +4 taipale_tf_pairs__ATF4_TEF_RNMTGATGCAATN_CAP-CG7786-gt-Pdp1 8 0.941364 23019.2 1 5 CACCTG TATTGCATCATCC - +4 taipale_cyt_meth__POU4F3_NTNAATWATGCAN_FL-acj6-vvl 10 0.941364 23019.2 1 3 CACCTG ATGCATTATTTAT - +4 hdpi__RPL35-RpL35 -1 0.941474 23021.9 1 5 CACCTG AATTA + +4 hdpi__SOD1-Sod1 0 0.941474 23021.9 1 5 CACCTG GAGCC + +4 dbcorrdb__ESRRA__ENCSR000DYQ_1__m5-Brf-brm-btd-CG42741-CoRest-CrebB-CTCF-dar1-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-tna-Usf-vtd-zfh1 13 0.941663 23026.5 1 6 CACCTG GGGGGGCCCCCGGCCCCCGC + +4 dbcorrdb__NR2C2__ENCSR000EWH_1__m2-Hr78 6 0.941663 23026.5 1 6 CACCTG GGCGCTCGACTGCTCCGGCC + +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m6-RpII215 2 0.941663 23026.5 1 6 CACCTG CCGACCGAACGTCTCGGCGG + +4 dbcorrdb__ZNF274__ENCSR000EVR_1__m3-egg 10 0.941663 23026.5 1 6 CACCTG CTGGAGAGAAACCCTATGAA + +4 transfac_pro__M01576 0 0.941663 23026.5 1 6 CACCTG CTCTCAAAATTCCGGGCGCT + +4 yetfasco__YDR034C_865 0 0.941663 23026.5 1 6 CACCTG CTCCCAAAATTCCGGGCGCT + +4 dbcorrdb__MAFK__ENCSR000EEB_1__m2-bab1-maf-S 9 0.941663 23026.5 1 6 CACCTG AGCAATTTTTTAATTATTTT - +4 dbcorrdb__YY1__ENCSR000EUM_1__m1-pho-phol-Taf1 13 0.941663 23026.5 1 6 CACCTG TATCCAAAATGGCGGCCCCC - +4 dbcorrdb__MAFF__ENCSR000EEC_1__m1-cic-cnc-kay-maf-S-tj -1 0.941663 23026.5 1 5 CACCTG TGCTGAGTCAGCAATTTTTA - +4 cisbp__M2296-cic-cnc-maf-S-tj 9 0.942086 23036.8 1 6 CACCTG CTGAGTCAGCAATTT + +4 cisbp__M2297-Mef2-rump 0 0.942086 23036.8 1 6 CACCTG ATGCTAAAAATAGAA + +4 cisbp__M2325-BEAF-32-pnr 6 0.942086 23036.8 1 6 CACCTG TATCGATAGTTTCGA + +4 cisbp__M5820-D-Sox15-Sox21a-Sox21b-SoxN 6 0.942086 23036.8 1 6 CACCTG ATGAATAACATTCAT + +4 cisbp__M6092-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.942086 23036.8 1 6 CACCTG ATGAATTTCATTCAT + +4 flyfactorsurvey__jim_F1-9_SOLEXA_2.5_FBgn0027339-brm-jim-maf-S-rn-sqz 7 0.942086 23036.8 1 6 CACCTG ACAAAAAAACAAAAA + +4 jaspar__MA1012.1-Mef2 6 0.942086 23036.8 1 6 CACCTG ACTTTCTATTTTTGG + +4 taipale__SOX15_full_ATGAATAACATTCAT-D-Sox15-Sox21a-Sox21b-SoxN 6 0.942086 23036.8 1 6 CACCTG ATGAATAACATTCAT + +4 taipale__SOX2_full_NTGAATWNCATTCAN-D-Sox15-Sox21a-Sox21b-SoxN 6 0.942086 23036.8 1 6 CACCTG ATGAATAACATTCAT + +4 transfac_pro__M01013-Dfd-eve-ind 8 0.942086 23036.8 1 6 CACCTG TGGGTCATTAGAGTC + +4 cisbp__M2332-CG12219 6 0.942086 23036.8 1 6 CACCTG CACGCACACACACTC - +4 homer__TGCAARYGCGCTCYA_EFL-1 7 0.942086 23036.8 1 6 CACCTG TGGAGCGCGTTTGCA - +4 jaspar__MA0529.1-BEAF-32-pnr 6 0.942086 23036.8 1 6 CACCTG TATCGATAGTTTCGA - +4 jaspar__MA0538.1-CG12219 6 0.942086 23036.8 1 6 CACCTG CACGCACACACACAC - +4 taipale_cyt_meth__IRF7_NYGAAANYGAAANYN_eDBD 0 0.942086 23036.8 1 6 CACCTG TAGTTTCGCTTTCGG - +4 taipale_tf_pairs__POU2F1_EOMES_NNNTATGCAGYGTKA_CAP_repr-nub-pdm2 1 0.942086 23036.8 1 6 CACCTG TCACACTGCATATTC - +4 taipale__Egr3_DBD_NACGCCCACGCANNN-btd-klu-Spps-sr 10 0.942086 23036.8 1 5 CACCTG TACGCCCACGCATTT + +4 c2h2_zfs__M5147-Spps-btd-klu-sr 10 0.942086 23036.8 1 5 CACCTG TACGCCCACGCATTT - +4 cisbp__M4466-Mef2-rump -1 0.942086 23036.8 1 5 CACCTG TTCTATTTTTGGCAC - +4 cisbp__M6003-btd-klu-Spps-sr 10 0.942086 23036.8 1 5 CACCTG TACGCCCACGCATTT - +4 transfac_pro__M05472-CG30020 10 0.942086 23036.8 1 5 CACCTG AGTCGGGACAAATCC - +4 transfac_pro__M00482-Ptx1 5 0.942252 23040.9 1 6 CACCTG TTTAATCCCAA + +4 transfac_pro__M05434 5 0.942252 23040.9 1 6 CACCTG CATTACGCATA + +4 cisbp__M1582-Hmg-2 4 0.942252 23040.9 1 6 CACCTG TTATTATATAT - +4 cisbp__M5209-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.942252 23040.9 1 6 CACCTG GCCACGCCCAC - +4 cisbp__M6478-D-Sox100B-Sox102F-Sox14-SoxN 0 0.942252 23040.9 1 6 CACCTG CCCATTGTTCT - +4 flyfactorsurvey__Sp1_SANGER_5_FBgn0020378-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 4 0.942252 23040.9 1 6 CACCTG GCCACGCCCAC - +4 swissregulon__hs__FOXQ1.p2 4 0.942252 23040.9 1 6 CACCTG AATAAACAATA - +4 taipale_cyt_meth__PHOX2B_TAATTAGATTA_FL_meth-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-PHDP-repo-ro-Traf4-unc-4 1 0.942252 23040.9 1 6 CACCTG TAATCTAATTA - +4 transfac_pro__M04611-foxo 1 0.942252 23040.9 1 6 CACCTG TAATCAGTCTT - +4 flyfactorsurvey__Rel_SANGER_5_FBgn0014018-Rel 6 0.942252 23040.9 1 5 CACCTG AGGAAACCCCC + +4 predrem__nrMotif564 -1 0.942252 23040.9 1 5 CACCTG CCCTCCCCGCA + +4 jaspar__MA0013.1 6 0.942252 23040.9 1 5 CACCTG TTTGTTTACTA - +4 cisbp__M0883-al-CG11294-CG34367-E5-en-ind-Lim1-Lim3-OdsH-otp-repo-unc-4 -2 0.942252 23040.9 1 4 CACCTG ACTAATTAATT + +4 taipale_cyt_meth__HOXC11_RGYAATAAAAN_FL-abd-A-Abd-B-cad-eve-Ubx 7 0.942252 23040.9 1 4 CACCTG GTTTTATGGCC - +4 transfac_pro__M05403 7 0.942252 23040.9 1 4 CACCTG CCGGGCCAATC - +4 transfac_pro__M01739-TfIIB -3 0.942252 23040.9 1 3 CACCTG CTTTCATAGTG - +4 transfac_pro__M05326-SoxN 9 0.942252 23040.9 1 2 CACCTG TTTAAAATTCA - +4 cisbp__M5039-Hsf 3 0.942258 23041 1 6 CACCTG TCGAAACTTCTAGA + +4 taipale_cyt_meth__FOXD2_NAACAATAAYAWWN_eDBD-fd59A-fkh-Sox21a 7 0.942258 23041 1 6 CACCTG AAACAATAACATTA + +4 taipale_cyt_meth__ZNF410_NYANCCCATAATAN_eDBD_repr 3 0.942258 23041 1 6 CACCTG CCATCCCATAATAC + +4 transfac_pro__M07381 4 0.942258 23041 1 6 CACCTG GAGCCGCCACAAAT + +4 cisbp__M4835-dati-FoxP 8 0.942258 23041 1 6 CACCTG ATTTTTTTGGTTTT - +4 swissregulon__hs__SP1.p2-Brf-CG3065-CG42741-CTCF-ERR-E(z)-Klf15-Nelf-E-Nf-YA-Nf-YB-Rbbp5-RpII215-SREBP-Sp1-Spps-brm-btd-dar1-kay-luna 2 0.942258 23041 1 6 CACCTG CGGCCCCGCCCCCC - +4 taipale__GBX2_DBD_TAATTRNNYAATTA-CG34367-Dr-E5-ems-en-gsb-gsb-n-inv-prd-unpg 0 0.942258 23041 1 6 CACCTG TAATTGGCCAATTA - +4 taipale_cyt_meth__NFATC4_NTTTCCRYGGAAAN_eDBD_meth_repr-NFAT 2 0.942258 23041 1 6 CACCTG TTTTCCATGGAAAA - +4 transfac_pro__M08887-Blimp-1-Stat92E 5 0.942258 23041 1 6 CACCTG AGTTTCACTTTCCT - +4 transfac_pro__M06951-CG7786-gt-Pdp1 -1 0.942258 23041 1 5 CACCTG ACTTCCGATATCAA + +4 cisbp__M2135 0 0.942943 23057.8 1 6 CACCTG AACGCGT + +4 jaspar__MA0251.1-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-ey-ftz-hbn-ind-inv-lab-lms-otp-pb-repo-ro-sl 1 0.942943 23057.8 1 6 CACCTG TTAATTA + +4 jaspar__MA0361.1 1 0.942943 23057.8 1 6 CACCTG CGGCCGA + +4 predrem__nrMotif1174 0 0.942943 23057.8 1 6 CACCTG TGACTCT + +4 transfac_pro__M01963 1 0.942943 23057.8 1 6 CACCTG CGGCCGC + +4 cisbp__M2058-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Drgx-E5-ems-en-eve-ftz-hbn-ind-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx-unc-4-unp 0 0.942943 23057.8 1 6 CACCTG TAATTAA - +4 jaspar__MA0330.1 0 0.942943 23057.8 1 6 CACCTG AACGCGT - +4 transfac_pro__M05547 1 0.942943 23057.8 1 6 CACCTG CGGCCCC - +4 yetfasco__YCR106W_506 1 0.942943 23057.8 1 6 CACCTG CGGCCGA - +4 hdpi__SFT2D1-CG5104 -1 0.942943 23057.8 1 5 CACCTG ATTTCCA - +4 cisbp__M4774 3 0.942943 23057.8 1 4 CACCTG TCTAATC + +4 elemento__CCAATCG -2 0.942943 23057.8 1 4 CACCTG CCAATCG + +4 elemento__CCCACGC-sr -2 0.942943 23057.8 1 4 CACCTG CCCACGC + +4 elemento__CCCAGCC -2 0.942943 23057.8 1 4 CACCTG CCCAGCC + +4 elemento__CCGAGCG -2 0.942943 23057.8 1 4 CACCTG CCGAGCG + +4 predrem__nrMotif1719 3 0.942943 23057.8 1 4 CACCTG ACAAATC + +4 transfac_pro__M01094-Abd-B-cad -2 0.942943 23057.8 1 4 CACCTG CATAAAA + +4 elemento__CGCAAGC -2 0.942943 23057.8 1 4 CACCTG GCTTGCG - +4 elemento__CGGAAGC -2 0.942943 23057.8 1 4 CACCTG GCTTCCG - +4 elemento__GATTGGC 3 0.942943 23057.8 1 4 CACCTG GCCAATC - +4 cisbp__M4946-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Dfd-Dll-E5-ems-en-exex-ftz-hbn-HGTX-ind-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-Ubx-unc-4-u 4 0.942943 23057.8 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__En_SOLEXA_FBgn0000577-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG32532-CG34367-Dfd-Dll-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-exex-ftz-hbn-ind- 4 0.942943 23057.8 1 3 CACCTG TAATTAA - +4 taipale__Foxc1_DBD_RTAAAYA_repr-croc-fd59A 4 0.942943 23057.8 1 3 CACCTG TGTTTAT - +4 cisbp__M6010-croc-fd59A 5 0.942943 23057.8 1 2 CACCTG ATAAACA + +4 hdpi__ZSWIM1 -4 0.942943 23057.8 1 2 CACCTG TGGCATT - +4 predrem__nrMotif1727 0 0.943369 23068.2 1 6 CACCTG TGCATATTT + +4 predrem__nrMotif2152 1 0.943369 23068.2 1 6 CACCTG GCAGCGTGG - +4 predrem__nrMotif914 3 0.943369 23068.2 1 6 CACCTG AGAGAAATG - +4 swissregulon__hs__ZNF384.p2-rn-sqz 0 0.943369 23068.2 1 6 CACCTG GACTTTTTC - +4 tiffin__TIFDMEM0000072 3 0.943369 23068.2 1 6 CACCTG TTTTATTTC - +4 hdpi__FOSL1-kay 4 0.943369 23068.2 1 5 CACCTG TGACTTCAT - +4 hdpi__MRPS25-mRpS25 4 0.943369 23068.2 1 5 CACCTG CATTTAGCA - +4 predrem__nrMotif2410 4 0.943369 23068.2 1 5 CACCTG AAATGGACT - +4 transfac_pro__M04916-Brf-brm-E(z)-RpII215-Taf1-tna -1 0.943369 23068.2 1 5 CACCTG CGCGGCGGC - +4 taipale__HSFY2_DBD_WTTCGAAYG_repr 5 0.943369 23068.2 1 4 CACCTG TTTCGAACG + +4 cisbp__M5569 5 0.943369 23068.2 1 4 CACCTG TTTCGAACG - +4 flyfactorsurvey__BH1_Cell_FBgn0011758-B-H1-B-H2 5 0.943369 23068.2 1 4 CACCTG CCAATTAAC - +4 flyfactorsurvey__CG12361_SOLEXA_2_FBgn0250756-Abd-B-Antp-CG4328-Dbx-HGTX-Lmx1a-Ubx-abd-A-cad-exex-ind 5 0.943369 23068.2 1 4 CACCTG CTAATTAAA - +4 idmmpmm__ftz-Antp-Dfd-Scr-Ubx-abd-A-bsh-btn-cad-ems-ftz-ind-pb-zen2 5 0.943369 23068.2 1 4 CACCTG TTAATGACC - +4 predrem__nrMotif182 -2 0.943369 23068.2 1 4 CACCTG GCTCTGCAA - +4 predrem__nrMotif2198 -2 0.943369 23068.2 1 4 CACCTG CATTTGTTT - +4 predrem__nrMotif605 -3 0.943369 23068.2 1 3 CACCTG CTGAGCCAA + +4 predrem__nrMotif842 6 0.943369 23068.2 1 3 CACCTG CTCTCCCAC + +4 cisbp__M6319-cnc-CoRest-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-NFAT-pan-pnr-Stat92E -3 0.943369 23068.2 1 3 CACCTG ATGAGTCAT - +4 hocomoco__FOSB_HUMAN.H11MO.0.A-CoRest-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-cnc-grn-kay-mor-nej-pan-pnr 6 0.943369 23068.2 1 3 CACCTG ATGAGTCAT - +4 transfac_pro__M05469-salm-salr 7 0.943369 23068.2 1 2 CACCTG CATTGCGCA + +4 cisbp__M0304-CG7786-gt-hng1-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 2 0.943611 23074.1 1 6 CACCTG ATTACGTAAT + +4 cisbp__M6418-Ptx1 4 0.943611 23074.1 1 6 CACCTG TTTAATCCCA + +4 hdpi__HIST2H2BE-His2B:CG17949-His2B:CG33868-His2B:CG33870-His2B:CG33872-His2B:CG33874-His2B:CG33876-His2B:CG33878-His2B:CG33880-His2B:CG33882-His2B:CG33884-His2B:CG33886-His2B:CG33888-His2B:CG33890-Hi 3 0.943611 23074.1 1 6 CACCTG TGGAAATTTC + +4 predrem__nrMotif1697 4 0.943611 23074.1 1 6 CACCTG AAAGCACTCC + +4 swissregulon__hs__NRF1.p2-ewg 0 0.943611 23074.1 1 6 CACCTG CGCATGCGCA + +4 taipale__HOXC10_DBD_GTCGTWAAAN-Abd-B 0 0.943611 23074.1 1 6 CACCTG GTCGTAAAAT + +4 transfac_pro__M03174 4 0.943611 23074.1 1 6 CACCTG ACGCCGCCAA + +4 transfac_pro__M05057 4 0.943611 23074.1 1 6 CACCTG AGGCCGCCAA + +4 transfac_pro__M05139 1 0.943611 23074.1 1 6 CACCTG ATGCCGCCAC + +4 transfac_pro__M07440 4 0.943611 23074.1 1 6 CACCTG ATGGCGCCAT + +4 transfac_pro__M07542 4 0.943611 23074.1 1 6 CACCTG TATCAATCAA + +4 predrem__nrMotif1211 4 0.943611 23074.1 1 6 CACCTG CAACCCCATC - +4 predrem__nrMotif237 1 0.943611 23074.1 1 6 CACCTG TTTTCTTTCT - +4 taipale_cyt_meth__HOXD12_NRTCGTAAAN_eDBD_meth-cad 3 0.943611 23074.1 1 6 CACCTG TTTTACGACC - +4 transfac_pro__M07316-nej 3 0.943611 23074.1 1 6 CACCTG GATTGCACAA - +4 cisbp__M0092 -1 0.943611 23074.1 1 5 CACCTG ACGCGTCACT + +4 cisbp__M1806 5 0.943611 23074.1 1 5 CACCTG TTCTCCGCCG + +4 hocomoco__MAFF_MOUSE.H11MO.1.A-Jra-cnc-kay-maf-S-tj -1 0.943611 23074.1 1 5 CACCTG TGCTGAGTCA + +4 transfac_pro__M05166 5 0.943611 23074.1 1 5 CACCTG AGGCCGCCCC + +4 flyfactorsurvey__dl_FlyReg_FBgn0000462-dl 6 0.943611 23074.1 1 4 CACCTG GGGAAAATCC + +4 taipale__GSX2_DBD_NNYMATTANN-al-Antp-ap-Awh-C15-CG32532-CG34367-Dbx-Dll-E5-ems-en-ey-HGTX-ind-lab-lbe-lbl-lms-OdsH-repo-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2 6 0.943611 23074.1 1 4 CACCTG ACTAATTAAA + +4 transfac_pro__M03168 6 0.943611 23074.1 1 4 CACCTG ATGCCGCCCC + +4 transfac_pro__M03203 6 0.943611 23074.1 1 4 CACCTG ATGCCGCCCC + +4 transfac_pro__M05140 6 0.943611 23074.1 1 4 CACCTG ATGCCGCCCC + +4 transfac_pro__M07398 -2 0.943611 23074.1 1 4 CACCTG ACTCATTAAT + +4 transfac_pro__M07860-Adf1 -2 0.943611 23074.1 1 4 CACCTG GCTGCGCTGC + +4 cisbp__M5314-Irbp18-nej-slbo-srl-Xrp1 6 0.943611 23074.1 1 4 CACCTG ATTGCGCAAT - +4 cisbp__M5317-Irbp18-nej-slbo-srl-Xrp1 6 0.943611 23074.1 1 4 CACCTG ATTGCGCAAT - +4 hocomoco__ZFP57_MOUSE.H11MO.0.B -2 0.943611 23074.1 1 4 CACCTG TTTGCCGCAG - +4 taipale__CEBPE_DBD_NTTRCGCAAY-Irbp18-nej-slbo-srl-Xrp1 6 0.943611 23074.1 1 4 CACCTG ATTGCGCAAT - +4 predrem__nrMotif2012 -3 0.943611 23074.1 1 3 CACCTG CTGGGCCCAG + +4 cisbp__M6399-onecut 0 0.943657 23075.3 1 6 CACCTG GTCTTGTTATTGATTTTTTTT + +4 swissregulon__hs__PAX3_7.p2-gsb-gsb-n-prd 11 0.943657 23075.3 1 6 CACCTG AAAATTCGTCACGCTTCTGGA + +4 taipale_cyt_meth__NFATC3_NYGGAAANNNNNNNTTTCCRN_eDBD_meth-NFAT 8 0.943657 23075.3 1 6 CACCTG ACGGAAAAATCATTTTTCCGT + +4 taipale_cyt_meth__NFATC3_NYGGAAANNNNNNNTTTCCRN_eDBD_repr-NFAT 8 0.943657 23075.3 1 6 CACCTG ATGGAAAAATGATTTTTCCAT + +4 taipale_tf_pairs__HOXB2_PAX1_NNMATTAGTCACGCWTSRNTG_CAP_repr-pb-Poxm 0 0.943657 23075.3 1 6 CACCTG GTCATTAGTCACGCATGACTG + +4 taipale_tf_pairs__HOXB2_PAX5_NNMATTAGTCACGCWTSRNTG_CAP-pb-sv 0 0.943657 23075.3 1 6 CACCTG GTCATTAGTCACGCATGACTG + +4 transfac_pro__M01572-klu-sr 15 0.943657 23075.3 1 6 CACCTG GTAAATAATGCGGGGGGCTTG + +4 transfac_pro__M05226 14 0.943657 23075.3 1 6 CACCTG TGGGTGGCCCCGCCGCCCTTC + +4 stark__VSGYYGCMGYCGYYGMMKKYG-Adf1-Trl 16 0.943657 23075.3 1 5 CACCTG CAAAGGCAACGACGGCAACCT - +4 tfdimers__MD00108-fkh 25 0.944296 23090.9 1 6 CACCTG AATTTTTTTTTATTTACTTAGTAAATAAAAAAAAATA + +4 tfdimers__MD00525-Mad 3 0.945305 23115.5 1 6 CACCTG TTTTTTCTGTTCTCCTTTCTTTTTTTTTT + +4 taipale_cyt_meth__FOXN2_NGCATNNNNNNNATGCN_eDBD_meth_repr-CHES-1-like 2 0.945476 23119.7 1 6 CACCTG AGCATCGTTACGATGCA + +4 transfac_pro__M07347-ss-tgo -1 0.945476 23119.7 1 5 CACCTG GGCTTGCGTGAGAAGGC + +4 transfac_pro__M02799-Sox102F 12 0.945476 23119.7 1 5 CACCTG AAATCTATTGTTCACTA - +4 cisbp__M5702-ey-Poxm-sv-toy 13 0.945476 23119.7 1 4 CACCTG TGCAGTCATGCGTGACG + +4 taipale__PAX1_DBD_SGTCACGCWTGANTGMA_repr-ey-Poxm-sv-toy 13 0.945476 23119.7 1 4 CACCTG TGCAGTCATGCGTGACG - +4 cisbp__M1873-bin-fd59A 5 0.94569 23125 1 6 CACCTG AAACAAACATTC + +4 cisbp__M1898 1 0.94569 23125 1 6 CACCTG CCATCAATCAAA + +4 homer__ATTCTCGCGAGA_GFX-Chd1-CoRest 0 0.94569 23125 1 6 CACCTG ATTCTCGCGAGA + +4 swissregulon__hs__PBX1.p2 1 0.94569 23125 1 6 CACCTG ACATCAATCAAA + +4 transfac_pro__M06867 3 0.94569 23125 1 6 CACCTG AGGGACTTTATA + +4 cisbp__M6141-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-OdsH-Optix-repo-Traf4-unc-4 5 0.94569 23125 1 6 CACCTG ATAATTGAATTA - +4 taipale_cyt_meth__ELK3_NTCGTAAATGCN_FL_repr-Ets96B 6 0.94569 23125 1 6 CACCTG TGCATTTACGAG - +4 transfac_pro__M05654-crol 6 0.94569 23125 1 6 CACCTG GCCGATTGCCCG - +4 transfac_pro__M06710 5 0.94569 23125 1 6 CACCTG GCGTTTCCATGC - +4 transfac_pro__M06754 0 0.94569 23125 1 6 CACCTG TCCGTTAATTCT - +4 homer__TGATTRATGGCY_Hoxb4-Antp-Dfd-Scr 7 0.94569 23125 1 5 CACCTG GGCCATTAATCA - +4 swissregulon__hs__FOXD3.p2-bin-croc-fd59A-foxo 7 0.94569 23125 1 5 CACCTG AAATAAACAATC - +4 transfac_pro__M05712 7 0.94569 23125 1 5 CACCTG TCCGCCGCCCCA - +4 transfac_pro__M05925 7 0.94569 23125 1 5 CACCTG GCTTTGGGACTC - +4 transfac_pro__M05942 7 0.94569 23125 1 5 CACCTG GGATTTTGACAC - +4 transfac_pro__M06208-Brf-btd-CG7368-CoRest-crol-ct-CTCF-E(z)-l(3)neo38-Rbbp5-Spps-Spt20-SREBP 7 0.94569 23125 1 5 CACCTG CCCCCCCCCCCA - +4 transfac_pro__M06270 7 0.94569 23125 1 5 CACCTG TCCGCACCCCCA - +4 transfac_pro__M06468-CG3281 7 0.94569 23125 1 5 CACCTG TATGCAGTCCCA - +4 transfac_pro__M06883 7 0.94569 23125 1 5 CACCTG GCCGCTTTCCCA - +4 hocomoco__ZSCA4_HUMAN.H11MO.0.D 8 0.94569 23125 1 4 CACCTG AGTGTGTGCACT + +4 taipale_cyt_meth__KLF15_RCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps 8 0.94569 23125 1 4 CACCTG GCCACGCCCCCC + +4 transfac_pro__M07771-cad-eve 8 0.94569 23125 1 4 CACCTG GGGCCATAAACC + +4 transfac_pro__M05534 -2 0.94569 23125 1 4 CACCTG GCTTCCAGACAG - +4 transfac_pro__M06283 -2 0.94569 23125 1 4 CACCTG GCTGCCGTCCAC - +4 transfac_pro__M06559 8 0.94569 23125 1 4 CACCTG TCATATTTCCCA - +4 hocomoco__LMX1A_HUMAN.H11MO.0.D-CG4328-CG9876-CG11294-CG32532-CG34367-CTCF-Lim3-Lmx1a-Rx-Vsx1-repo-unpg-vvl 5 0.945839 23128.6 1 6 CACCTG TTAATTACATAATTAATTA - +4 taipale_cyt_meth__ZBTB32_NRTACAGTNNNACTGTAYN_eDBD_meth 15 0.945839 23128.6 1 4 CACCTG TGTACAGTAATACTGTACA + +4 transfac_pro__M09140 15 0.945839 23128.6 1 4 CACCTG CATCATCATCATCATCATC + +4 transfac_pro__M04672 0 0.946194 23137.3 1 6 CACCTG CAATTAGCGCGCGCGCTCCAAGA - +4 tfdimers__MD00229-foxo-slp2 3 0.946855 23153.4 1 6 CACCTG TTTTTTTTGTTTATTTTCCTTTTA - +4 tfdimers__MD00355 15 0.947163 23161 1 6 CACCTG AAATAAGTGGGGATTTATTTTTATT + +4 tfdimers__MD00454 19 0.947163 23161 1 6 CACCTG TTTTTTTTATTTAATTTTTTTTTTT - +4 taipale__GLIS1_DBD_NGACCCCCCACGANGN_repr-ci-lmd-sug 1 0.94736 23165.8 1 6 CACCTG AGACCCCCCACGAAGC + +4 taipale_tf_pairs__HOXB13_ONECUT2_NNNRTAAAWATYGAYY_HT-onecut 8 0.94736 23165.8 1 6 CACCTG CTCGTAAATATCGATC + +4 transfac_pro__M01446-B-H1-B-H2-Dr-tup-unpg 3 0.94736 23165.8 1 6 CACCTG AAAAACCAATTAAGAA + +4 cisbp__M5490-ci-lmd-sug 1 0.94736 23165.8 1 6 CACCTG AGACCCCCCACGAAGC - +4 hocomoco__P5F1B_HUMAN.H11MO.0.D-Dll-nub-pdm2-vvl 9 0.94736 23165.8 1 6 CACCTG ATGAATATGCAAATTA - +4 hdpi__POU4F3 0 0.947534 23170.1 1 6 CACCTG GAAATG + +4 jaspar__MA0271.1-bs 1 0.947534 23170.1 1 5 CACCTG AGACGC + +4 transfac_pro__M03560 1 0.947534 23170.1 1 5 CACCTG TAATAA + +4 hdpi__MSRA-Eip71CD -1 0.947534 23170.1 1 5 CACCTG ATCGTC - +4 hdpi__RAB18-Dif-Rab18-dl 1 0.947534 23170.1 1 5 CACCTG TTTCCC - +4 fantom__motif6_AAGACT 2 0.947534 23170.1 1 4 CACCTG AAGACT + +4 transfac_pro__M04979 2 0.947534 23170.1 1 4 CACCTG CCGAAC + +4 fantom__motif4_TGTCTA 2 0.947534 23170.1 1 4 CACCTG TAGACA - +4 fantom__motif64_AGTCGN 2 0.947534 23170.1 1 4 CACCTG ACGACT - +4 hdpi__GTF3C2 2 0.947534 23170.1 1 4 CACCTG GAGCCC - +4 fantom__motif17_CGCTAN 3 0.947534 23170.1 1 3 CACCTG CGCTAA + +4 taipale__ARX_DBD_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.947683 23173.7 1 6 CACCTG TTAATTAAATTAA + +4 taipale__Arx_DBD_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.947683 23173.7 1 6 CACCTG CTAATTAAATTAA + +4 transfac_pro__M01890-Stat92E 3 0.947683 23173.7 1 6 CACCTG ACATTTCTAGGAA + +4 transfac_pro__M07825-al-CG32532-OdsH-PHDP-repo-Rx-unc-4 2 0.947683 23173.7 1 6 CACCTG CTAATCGAATTAC + +4 cisbp__M5348-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-ey-hbn-Lim1-Lim3-Lmx1a-OdsH-Optix-otp-repo-Traf4-unc-4-unpg 1 0.947683 23173.7 1 6 CACCTG TTAATTAGATTAG - +4 taipale__DRGX_DBD_NTAAYYNAATTAN-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-ey-hbn-Lim3-Lmx1a-OdsH-Optix-repo-Traf4-unc-4-unpg 1 0.947683 23173.7 1 6 CACCTG TTAATTAGATTAG - +4 taipale_cyt_meth__ELF3_NATAACGGATGYN_eDBD_repr 0 0.947683 23173.7 1 6 CACCTG CGCATCCGTTATC - +4 transfac_pro__M01719-Gsc-oc 6 0.947683 23173.7 1 6 CACCTG ATCTAATCCCTTA - +4 transfac_pro__M09005-btd-cbt-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 5 0.947683 23173.7 1 6 CACCTG GGCCACGCCCACT - +4 cisbp__M5292-Jra-nej 8 0.947683 23173.7 1 5 CACCTG TATTGCATCATCC - +4 taipale__ATF4_DBD_NNATGAYGCAATN-Jra-nej 8 0.947683 23173.7 1 5 CACCTG TATTGCATCATCC - +4 taipale_tf_pairs__ATF4_CEBPB_NNATGAYGCAAYN_CAP 8 0.947683 23173.7 1 5 CACCTG TATTGCGTCATCC - +4 cisbp__M2193 2 0.947736 23175 1 6 CACCTG TTGATTTC + +4 cisbp__M3633 2 0.947736 23175 1 6 CACCTG CTTAATTG + +4 flyfactorsurvey__Abd-A_FlyReg_FBgn0000014-abd-A 0 0.947736 23175 1 6 CACCTG TCAATTAA + +4 flyfactorsurvey__NK7.1_Cell_FBgn0024321-NK7.1-Ubx-lms-slou 2 0.947736 23175 1 6 CACCTG ATTAATTG + +4 hocomoco__HXB4_HUMAN.H11MO.0.B-Antp-Dfd-Scr-Ubx-ems-eve-ftz-ind-pb-zen2 0 0.947736 23175 1 6 CACCTG TTAATGGC + +4 predrem__nrMotif253 1 0.947736 23175 1 6 CACCTG TGAACTCT + +4 taipale__LMX1B_DBD_NYAATTAN_repr-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-E5-en-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-zfh2 1 0.947736 23175 1 6 CACCTG TTAATTAA + +4 taipale_cyt_meth__DLX2_NYAATTAN_eDBD-Dll 1 0.947736 23175 1 6 CACCTG GCAATTAC + +4 taipale_cyt_meth__LHX9_CYAATTAN_FL-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-lbe-lbl-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4-unpg-Vsx1-Vsx2-z 1 0.947736 23175 1 6 CACCTG CTAATTAA + +4 cisbp__M5117-lms-NK7.1-slou-Ubx 0 0.947736 23175 1 6 CACCTG CAATTAAT - +4 jaspar__MA0388.1 2 0.947736 23175 1 6 CACCTG TTGATTTC - +4 taipale_cyt_meth__DLX1_NYAATTAN_FL-Dll 1 0.947736 23175 1 6 CACCTG GTAATTGC - +4 taipale_cyt_meth__DLX1_NYAATTAN_FL_meth_repr-Dll 1 0.947736 23175 1 6 CACCTG ATAATTGC - +4 taipale_cyt_meth__LHX5_SYAATTAN_FL_meth-Antp-CG11294-CG32532-CG4328-CG9876-en-exex-HGTX-inv-lab-Lim1-Lim3-lms-Lmx1a-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1 1 0.947736 23175 1 6 CACCTG TTAATTAC - +4 taipale_cyt_meth__MNX1_NYAATTAN_eDBD_meth-Antp-Awh-B-H1-B-H2-bsh-btn-CG18599-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim1-Lim3-lms-pb-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.947736 23175 1 6 CACCTG CTAATTAC - +4 transfac_pro__M01682 2 0.947736 23175 1 6 CACCTG TTGATTTC - +4 transfac_public__M00140-bcd-Gsc-oc 2 0.947736 23175 1 6 CACCTG TTAATCCC - +4 flyfactorsurvey__Gsc_Cell_FBgn0010323-Gsc-bcd 3 0.947736 23175 1 5 CACCTG CTTAATCC + +4 jaspar__MA0932.1 3 0.947736 23175 1 5 CACCTG AATTAATT + +4 scertf__fordyce.ROX1 -1 0.947736 23175 1 5 CACCTG ACAATAGC + +4 stark__GCGTSAAA -1 0.947736 23175 1 5 CACCTG GCGTCAAA + +4 taipale_cyt_meth__PITX1_YTAATCCN_FL_meth-Gsc-oc-Ptx1 3 0.947736 23175 1 5 CACCTG CTAATCCC + +4 taipale_cyt_meth__PITX2_YTAATCCN_FL-Ptx1 3 0.947736 23175 1 5 CACCTG ATAATCCC + +4 cisbp__M1613 -1 0.947736 23175 1 5 CACCTG GCCGGGGA - +4 cisbp__M6357 -1 0.947736 23175 1 5 CACCTG CCATTAAA - +4 predrem__nrMotif1438 3 0.947736 23175 1 5 CACCTG GAGCATCC - +4 predrem__nrMotif1839 3 0.947736 23175 1 5 CACCTG GAGGGCCG - +4 cisbp__M2088 4 0.947736 23175 1 4 CACCTG TCTCCGCC + +4 cisbp__M5163-bcd-Gsc-oc-Ptx1 4 0.947736 23175 1 4 CACCTG GTTAATCC + +4 elemento__CCATGCGC -2 0.947736 23175 1 4 CACCTG CCATGCGC + +4 elemento__CCATTGGC -2 0.947736 23175 1 4 CACCTG CCATTGGC + +4 flyfactorsurvey__Ptx1_SOLEXA_FBgn0020912-Gsc-Ptx1-bcd-oc 4 0.947736 23175 1 4 CACCTG GTTAATCC + +4 predrem__nrMotif2564 -2 0.947736 23175 1 4 CACCTG TCTATTCA + +4 cisbp__M4931-abd-A-Antp-ap-Awh-btn-CG11294-CG18599-CG32532-CG9876-E5-ems-en-eve-ftz-hbn-ind-lab-Lim1-Lim3-nub-otp-pb-pdm2-Pph13-ro-Rx-Scr-slou-unpg-Vsx1-Vsx2-zen2 4 0.947736 23175 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__Antp_SOLEXA_FBgn0000095-Antp-C15-CG18599-Dbx-E5-Scr-Ubx-abd-A-ap-bsh-btn-ems-ftz-lab-pb-zen2 4 0.947736 23175 1 4 CACCTG TCATTAAA - +4 flyfactorsurvey__E5_Cell_FBgn0008646-Antp-Awh-CG9876-CG11294-CG18599-CG32532-E5-Lim1-Lim3-Pph13-Rx-Scr-Vsx1-Vsx2-abd-A-ap-btn-ems-en-eve-ftz-ind-lab-nub-otp-pb-pdm2-ro-slou-unpg-zen2 4 0.947736 23175 1 4 CACCTG TAATTAAC - +4 jaspar__MA0283.1 4 0.947736 23175 1 4 CACCTG TCTCCGCC - +4 predrem__nrMotif2404 -2 0.947736 23175 1 4 CACCTG TCTAATAA - +4 predrem__nrMotif593 4 0.947736 23175 1 4 CACCTG AAGAATCC - +4 taipale_cyt_meth__BARHL1_NTAATTGN_eDBD-B-H1-B-H2-bsh-CG11085-Dr-en-inv-unpg -2 0.947736 23175 1 4 CACCTG GCAATTAG - +4 transfac_pro__M00430-E2f1 -2 0.947736 23175 1 4 CACCTG CCGCCAAA - +4 transfac_pro__M01916 4 0.947736 23175 1 4 CACCTG TCTCCGCC - +4 taipale__NKX6-2_full_NYMATTAN-acj6-Antp-bsh-C15-CG15696-CG34367-CG4328-Dbx-Dll-en-exex-ftz-hbn-HGTX-ind-inv-lab-lbe-lbl-Lim1-lms-Lmx1a-repo-Scr-slou-Ubx-Vsx2 5 0.947736 23175 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__BSX_NYAATTAN_eDBD-abd-A-Antp-B-H1-B-H2-bsh-btn-CG11085-Dfd-Dll-Dr-E5-ems-en-exex-inv-lab-Lim1-Lim3-lms-pb-Rx-Scr-Ubx-unpg-Vsx1 5 0.947736 23175 1 3 CACCTG GCAATTAC + +4 cisbp__M1231-nub-pdm2 5 0.947736 23175 1 3 CACCTG ATAATTAA - +4 cisbp__M5456-bin-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -3 0.947736 23175 1 3 CACCTG TTGTTTAC - +4 cisbp__M5605-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-E5-en-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-Traf4-Ubx-unc-4-unpg-Vsx1-zfh2 5 0.947736 23175 1 3 CACCTG TTAATTAA - +4 taipale__FOXJ3_DBD_RTAAACAA-bin-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 -3 0.947736 23175 1 3 CACCTG TTGTTTAC - +4 taipale_cyt_meth__HOXB6_RTCGTTAN_eDBD_meth-abd-A-btn-Dll-Ubx 5 0.947736 23175 1 3 CACCTG TTAACGAC - +4 flyfactorsurvey__slbo_FlyReg_FBgn0005638-slbo -4 0.947736 23175 1 2 CACCTG TTTGCAAT - +4 tfdimers__MD00468 12 0.948113 23184.2 1 6 CACCTG CTCGGTCTTGACCACATGTGGTCAAGACGGCG + +4 tfdimers__MD00397 41 0.948175 23185.7 1 6 CACCTG ACTGGGTCACAGTGGATACCAAGGAGTCAATAGTTGTTAACCACTGGGTCACAGTGGTTACCGAGGAG + +4 dbcorrdb__E2F4__ENCSR000DOR_1__m2-btd-Chd1-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-RpII215-Spps-SREBP 4 0.948279 23188.3 1 6 CACCTG CCCGCCCCAGCCAATCAGAG + +4 dbcorrdb__IRF3__ENCSR000EDF_1__m1-btd-CG7839-Chd1-Chrac-14-E2f2-kay-Mes4-Nf-YA-Nf-YB-Nf-YC-Spps-SREBP-Tbp-yps 1 0.948279 23188.3 1 6 CACCTG CCTTCTGATTGGCTAATGCG + +4 dbcorrdb__ZNF274__ENCSR000EVG_1__m2-egg 13 0.948279 23188.3 1 6 CACCTG ATCAGAGAACTCACACTGGA + +4 taipale_cyt_meth__PAX8_NSGTCACGCWTSANYGNNYN_FL-ey-Poxm-sv-toy 14 0.948279 23188.3 1 6 CACCTG CCGTCACGCATGACTGCGCC + +4 taipale_cyt_meth__ZBTB33_NRCGCNNWTTTAACATAAYN_eDBD_meth_repr 11 0.948279 23188.3 1 6 CACCTG AGCGCCATTTTAACATAATA + +4 dbcorrdb__E2F4__ENCSR000DOR_1__m1-Dp-E2f1-E2f2-Sin3A 12 0.948279 23188.3 1 6 CACCTG TTTCCAATTTCCCGCCCCCC - +4 dbcorrdb__EZH2__ENCSR000ARI_1__m5-E(z) 0 0.948279 23188.3 1 6 CACCTG ATCCGGCACCGCGGGCGGAC - +4 dbcorrdb__NRF1__ENCSR000EEH_1__m1-E2f1-ewg-RpII215 0 0.948279 23188.3 1 6 CACCTG CCCCACTGCGCATGCGCAGG - +4 dbcorrdb__POLR2A__ENCSR000EUU_1__m1-RpII215 13 0.948279 23188.3 1 6 CACCTG CGCCGCGCAAGCGCAATTAG - +4 dbcorrdb__STAT1__ENCSR000EZK_1__m1-aop-Stat92E 6 0.948279 23188.3 1 6 CACCTG CGTCATTTCCTGGAAATGGC - +4 dbcorrdb__SUZ12__ENCSR000EXH_1__m1-Su(z)12 8 0.948279 23188.3 1 6 CACCTG GCGGCGGGCTTCGTCCGCGC - +4 dbcorrdb__POLR2A__ENCSR000ALH_1__m5-RpII215 -1 0.948279 23188.3 1 5 CACCTG GGCTGTTGCGCTTGTCGCGC - +4 cisbp__M5048-brm-jim-maf-S-rn-sqz 7 0.948385 23190.9 1 6 CACCTG ACAAAAAAACAAAAA + +4 cisbp__M6086-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.948385 23190.9 1 6 CACCTG AACAATAACATTGTT + +4 homer__GGNTCTCGCGAGAAC_ZBTB33-Chd1-CoRest 1 0.948385 23190.9 1 6 CACCTG GGATCTCGCGAGAAC + +4 stark__GCANTTGYNWYAATT 1 0.948385 23190.9 1 6 CACCTG GCAATTGCAACAATT + +4 taipale__Sox17_DBD_ATGAATWNCATTCAT-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.948385 23190.9 1 6 CACCTG ATGAATTTCATTCAT + +4 transfac_pro__M09069-Taf1 6 0.948385 23190.9 1 6 CACCTG CTCCGCCGCCATTTC + +4 cisbp__M5570 4 0.948385 23190.9 1 6 CACCTG TTCGAACGGTTCGAA - +4 cisbp__M6166-Cdc5 7 0.948385 23190.9 1 6 CACCTG GGGATTTAACATAAT - +4 taipale__HSFY2_DBD_TTCGAANNNTTCGAA 3 0.948385 23190.9 1 6 CACCTG TTCGAACGGTTCGAA - +4 taipale__NFIA_full_TTGGCANNNTGCCAR_repr-C15-Nf1-NfI 4 0.948385 23190.9 1 6 CACCTG TTGGCACCGTGCCAA - +4 transfac_pro__M09252 8 0.948385 23190.9 1 6 CACCTG TTGGAATATTCTTTT - +4 flyfactorsurvey__Aef1_SOLEXA_FBgn0005694-Aef1-CG4360 10 0.948385 23190.9 1 5 CACCTG ACTACAACAACAACC - +4 scertf__pachkov.SPT15-Tbp-Trf-Trf2 5 0.948474 23193 1 6 CACCTG ATTTATATATT + +4 swissregulon__sacCer__NHP6B-Tbp 2 0.948474 23193 1 6 CACCTG TATATATAATA + +4 transfac_pro__M01737-SoxN 0 0.948474 23193 1 6 CACCTG TTCCTATTGTT + +4 predrem__nrMotif1115 4 0.948474 23193 1 6 CACCTG CCAGCCCCCGA - +4 stark__GCGNNTNNTTA 4 0.948474 23193 1 6 CACCTG TAAAAAAACGC - +4 stark__HAATTAYGCRH-en 1 0.948474 23193 1 6 CACCTG TCGCATAATTT - +4 transfac_pro__M05611-salm-salr 5 0.948474 23193 1 6 CACCTG ATTCAGACTCG - +4 cisbp__M4929-dysf-tgo 6 0.948474 23193 1 5 CACCTG AGTCACGATTT - +4 cisbp__M5548-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.948474 23193 1 4 CACCTG TTTTTATTGCT + +4 hocomoco__BATF_HUMAN.H11MO.1.A-Jra-Stat92E-nej 7 0.948474 23193 1 4 CACCTG ATTGAGTCATC - +4 flyfactorsurvey__fkh_NAR_FBgn0000659-HDAC1-croc-fd59A-fkh-nej 8 0.948474 23193 1 3 CACCTG TGTTTGCTTAA + +4 cisbp__M2250-croc-fd59A-fkh-HDAC1-nej 8 0.948474 23193 1 3 CACCTG TGTTTGCTTAA - +4 predrem__nrMotif1330 8 0.948474 23193 1 3 CACCTG AAGCCAAATAA - +4 stark__GTCNNNNGACA 8 0.948474 23193 1 3 CACCTG TGTCAAAAGAC - +4 cisbp__M5482-CG34367-Dr-E5-ems-en-gsb-gsb-n-inv-prd-unpg 0 0.948519 23194.1 1 6 CACCTG TAATTGGCCAATTA + +4 taipale__FOXO6_DBD_TTTCCCCACACRAC-foxo 8 0.948519 23194.1 1 6 CACCTG TTTCCCCACACGAC + +4 taipale_cyt_meth__E2F8_NTTTCCCGCCAAAN_eDBD-E2f1-E2f2 2 0.948519 23194.1 1 6 CACCTG TTTTCCCGCCAAAA + +4 taipale_cyt_meth__NFATC4_NTTTCCRYGGAAAN_eDBD-NFAT 3 0.948519 23194.1 1 6 CACCTG TTTTCCATGGAAAC + +4 transfac_pro__M09210 5 0.948519 23194.1 1 6 CACCTG AAAAGAATCTTCTT + +4 taipale__EN1_DBD_TAATTRSNYAATTA_repr-bsh-CG34367-CG9876-Dr-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg 0 0.948519 23194.1 1 6 CACCTG TAATTGACCAATTA - +4 hocomoco__PBX3_MOUSE.H11MO.0.A-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-Spps-btd-kay-yps -1 0.948519 23194.1 1 5 CACCTG CTCTGATTGGCTGG + +4 taipale__BATF3_DBD_TGATGACGTCATCA-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-Xbp1 9 0.948519 23194.1 1 5 CACCTG TGATGACGTCATCA + +4 cisbp__M5302-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-maf-S-Xbp1 9 0.948519 23194.1 1 5 CACCTG TGATGACGTCATCA - +4 cisbp__M6414-btd-Chrac-14-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps-yps -1 0.948519 23194.1 1 5 CACCTG CTCTGATTGGCTGG - +4 taipale__FOXD3_DBD_NRNWAAYRTTKNYN-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.948519 23194.1 1 4 CACCTG AGTTAATATTTACT + +4 cisbp__M6473-Sox15 8 0.949124 23208.9 1 6 CACCTG CAACAATCTTCATTGTCC + +4 transfac_pro__M05605-srp 5 0.949124 23208.9 1 6 CACCTG ATGTTTATCTTAAAAAAA + +4 transfac_pro__M07678-Atf-2-Atf3-Atf6-CG44247-cnc-crc-CrebA-CrebB-Jra-kay-Xbp1 11 0.949124 23208.9 1 6 CACCTG TTGGATGACGTCATCCAA + +4 cisbp__M1979-abd-A-Antp-bsh-C15-Dfd-HGTX-Scr-slou-Ubx 1 0.949271 23212.5 1 6 CACCTG TTAATTA + +4 hdpi__PSMA6-CG30382-Prosalpha1 1 0.949271 23212.5 1 6 CACCTG TTTCCAA - +4 elemento__ACACGCG -1 0.949271 23212.5 1 5 CACCTG ACACGCG + +4 elemento__ACGCGGC -1 0.949271 23212.5 1 5 CACCTG ACGCGGC + +4 predrem__nrMotif6 2 0.949271 23212.5 1 5 CACCTG TTTATTT + +4 transfac_pro__M09008-bcd-Gsc-oc-Ptx1 2 0.949271 23212.5 1 5 CACCTG TTAATCC + +4 hdpi__TRMT1-CG6388 2 0.949271 23212.5 1 5 CACCTG TTCATTT - +4 predrem__nrMotif106-fkh 2 0.949271 23212.5 1 5 CACCTG AATATTT - +4 predrem__nrMotif2486 2 0.949271 23212.5 1 5 CACCTG TTTGCCA - +4 predrem__nrMotif67 2 0.949271 23212.5 1 5 CACCTG TTTCCCA - +4 cisbp__M2010-bcd-Ptx1 3 0.949271 23212.5 1 4 CACCTG TTAATCC + +4 elemento__CGCAGCC 3 0.949271 23212.5 1 4 CACCTG CGCAGCC + +4 elemento__CGGAGCC 3 0.949271 23212.5 1 4 CACCTG CGGAGCC + +4 elemento__TGCATCC 3 0.949271 23212.5 1 4 CACCTG TGCATCC + +4 flyfactorsurvey__Ptx1_Cell_FBgn0020912-Ptx1-bcd 3 0.949271 23212.5 1 4 CACCTG TTAATCC + +4 predrem__nrMotif1880 3 0.949271 23212.5 1 4 CACCTG GAAGCCC - +4 cisbp__M2252-cad-Dbx-H2.0 4 0.949271 23212.5 1 3 CACCTG TAATTAA - +4 jaspar__MA0448.1-Dbx-H2.0-cad 4 0.949271 23212.5 1 3 CACCTG TAATTAA - +4 yetfasco__YFL044C_1166-CG4603 5 0.949271 23212.5 1 2 CACCTG AAATAAA - +4 predrem__nrMotif668 1 0.949695 23222.9 1 6 CACCTG GAGCCTTGG + +4 swissregulon__sacCer__MBP1 3 0.949695 23222.9 1 6 CACCTG TGACGCGTC + +4 predrem__nrMotif931 3 0.949695 23222.9 1 6 CACCTG TAATTTCTT - +4 stark__MATTWRTCA 3 0.949695 23222.9 1 6 CACCTG TGACAAATG - +4 swissregulon__sacCer__STB4 3 0.949695 23222.9 1 6 CACCTG TCGGAACGA - +4 predrem__nrMotif2310 4 0.949695 23222.9 1 5 CACCTG AGAAGACTG - +4 cisbp__M1073-abd-A-Antp-ap-Awh-bsh-btn-CG18599-CG4328-Dfd-E5-ems-eve-exex-ftz-HGTX-ind-lab-Lmx1a-pb-Scr-tup-Ubx-unpg-zen-zen2 5 0.949695 23222.9 1 4 CACCTG TTAATGACC + +4 cisbp__M6237-bin-croc-fd59A-fkh 5 0.949695 23222.9 1 4 CACCTG AAACAAACA + +4 predrem__nrMotif1466 -2 0.949695 23222.9 1 4 CACCTG TCTTGGGAG + +4 flyfactorsurvey__BH2_Cell_FBgn0004854-B-H2-inv -2 0.949695 23222.9 1 4 CACCTG CCAATTAAG - +4 predrem__nrMotif1349 5 0.949695 23222.9 1 4 CACCTG CAGAGCTCA - +4 cisbp__M0320-Jra-kay 6 0.949695 23222.9 1 3 CACCTG ATGACTCAA + +4 hocomoco__FOSB_MOUSE.H11MO.0.A-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-cnc-grn-kay-mor-nej-pan-pnr 6 0.949695 23222.9 1 3 CACCTG ATGACTCAT + +4 transfac_pro__M04691-Chd1-CoRest -3 0.949695 23222.9 1 3 CACCTG CTCGCGAGA - +4 transfac_pro__M04760-Chd1-CoRest -3 0.949695 23222.9 1 3 CACCTG CTCGCGAGA - +4 stark__TNAGCATAA 7 0.949695 23222.9 1 2 CACCTG TTATGCTAA - +4 cisbp__M0502-bab1 4 0.949791 23225.2 1 6 CACCTG CTTTTAAAAG + +4 predrem__nrMotif1170 2 0.949791 23225.2 1 6 CACCTG TTTTGCTTTT + +4 predrem__nrMotif1740 4 0.949791 23225.2 1 6 CACCTG CTGGATTCTG + +4 predrem__nrMotif881 4 0.949791 23225.2 1 6 CACCTG CACAGCCCAG + +4 taipale_cyt_meth__SOX14_NGAACAATGN_eDBD_meth-D-Sox21a-Sox21b 2 0.949791 23225.2 1 6 CACCTG CTAACAATGG + +4 transfac_pro__M05317-Sox102F 0 0.949791 23225.2 1 6 CACCTG TAAATTTTCC + +4 transfac_public__M00042-Sox102F 1 0.949791 23225.2 1 6 CACCTG TTAACAATAC + +4 yetfasco__YDR169C_2233 0 0.949791 23225.2 1 6 CACCTG AATTTTTCAC + +4 cisbp__M0481 1 0.949791 23225.2 1 6 CACCTG TGAGCCGCAT - +4 cisbp__M1487 0 0.949791 23225.2 1 6 CACCTG AGACTCCAAT - +4 hdpi__PAX3-gsb-gsb-n-prd 0 0.949791 23225.2 1 6 CACCTG ACGCTAATTA - +4 cisbp__M4681-cnc-Jra-maf-S-tj -1 0.949791 23225.2 1 5 CACCTG TGCTGAGTCA + +4 taipale_cyt_meth__NFATC4_NAYGGAAAAN_eDBD-NFAT 5 0.949791 23225.2 1 5 CACCTG AATGGAAAAT + +4 transfac_pro__M03208 5 0.949791 23225.2 1 5 CACCTG ACGCCGCCCG + +4 transfac_pro__M05069 5 0.949791 23225.2 1 5 CACCTG TGGGCGGCCT - +4 transfac_pro__M05108 5 0.949791 23225.2 1 5 CACCTG TGGGCGGCCT - +4 transfac_pro__M05138 5 0.949791 23225.2 1 5 CACCTG GGGGCGGCCT - +4 taipale_cyt_meth__ARGFX_NCTAATTARN_eDBD-al-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-Lim1-Lim3-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-Vsx2 -2 0.949791 23225.2 1 4 CACCTG TCTAATTAAA + +4 idmmpmm__Abd-B-Abd-B 6 0.949791 23225.2 1 4 CACCTG TCATAAAACA - +4 taipale__CEBPB_DBD_NTTRCGCAAY-Irbp18-nej-slbo-srl-Xrp1 6 0.949791 23225.2 1 4 CACCTG ATTGCGCAAT - +4 hocomoco__HXA5_HUMAN.H11MO.0.D-Antp-Scr -3 0.949791 23225.2 1 3 CACCTG TTGATTAATG + +4 transfac_pro__M06230 7 0.949791 23225.2 1 3 CACCTG GCGTTTTGAC - +4 stark__BCATAAATYA-cad 8 0.949791 23225.2 1 2 CACCTG TCATAAATCA + +4 hocomoco__ONEC2_HUMAN.H11MO.0.D-onecut 0 0.950157 23234.2 1 6 CACCTG GTCTTGTTATTGATTTTTTTT + +4 tfdimers__MD00002 13 0.950157 23234.2 1 6 CACCTG ATTAGTTAATCATTAACTAAT + +4 transfac_pro__M09337 0 0.950157 23234.2 1 6 CACCTG CTTATCCTTATCCAATTTTTT - +4 tfdimers__MD00291-foxo-pho-phol 3 0.951562 23268.5 1 6 CACCTG TTTTTCCATTGTTTTTTTTTTA - +4 transfac_pro__M05308 -3 0.951562 23268.5 1 3 CACCTG CTGGACTTTCATGCGTGAAGAG - +4 transfac_pro__M05309 -3 0.951562 23268.5 1 3 CACCTG CTGGACTTTCATGCGTGAAGAG - +4 taipale_cyt_meth__ZBTB37_NTGCCGNNTTRGCCGWN_eDBD_repr 1 0.951589 23269.2 1 6 CACCTG ATGCCGTATTAGCCGAT + +4 transfac_pro__M01471-Antp-C15-CG4328-Dfd-Lim1-Lim3-Lmx1a-otp-Scr-vvl 10 0.951589 23269.2 1 6 CACCTG ATTATTTAATTAATTTC - +4 transfac_pro__M02735 10 0.951589 23269.2 1 6 CACCTG GAATTTTAATTAAACCC - +4 scertf__macisaac.SNF1-AMPKalpha-Bdp1-CG17209-CG43143-SREBP -2 0.951589 23269.2 1 4 CACCTG CCGGGGATCGAACTCGG + +4 cisbp__M2350 2 0.951656 23270.9 1 6 CACCTG CTCACGCGCTCA + +4 flyfactorsurvey__gl_SANGER_5_FBgn0004618-gl 2 0.951656 23270.9 1 6 CACCTG GAAGCCCTACAA + +4 hocomoco__ALX1_HUMAN.H11MO.0.B-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-repo-unc-4 5 0.951656 23270.9 1 6 CACCTG ATAATTGAATTA + +4 hocomoco__CDX2_HUMAN.H11MO.0.A-Abd-B-cad-eve 6 0.951656 23270.9 1 6 CACCTG TTTTATTGCTGT + +4 jaspar__MA0557.1 2 0.951656 23270.9 1 6 CACCTG CTCACGCGCTCA + +4 predrem__nrMotif1714-CTCF-ERR-E(z)-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-brm-btd-dar1-kay 5 0.951656 23270.9 1 6 CACCTG GGCCCCGCCCCC + +4 predrem__nrMotif374 2 0.951656 23270.9 1 6 CACCTG GCCGCCGCCGCG + +4 tiffin__TIFDMEM0000105 2 0.951656 23270.9 1 6 CACCTG TTTATTTTGTTT + +4 homer__YTAATYNRATTA_Phox2a-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-hbn-repo-unc-4 1 0.951656 23270.9 1 6 CACCTG TAATTTAATTAG - +4 taipale_cyt_meth__IRF2_YGAAASYGAAAS_FL_meth 4 0.951656 23270.9 1 6 CACCTG CTTTCGCTTTCG - +4 transfac_pro__M06096 5 0.951656 23270.9 1 6 CACCTG ACAGCCGCCTCA - +4 transfac_pro__M06301 1 0.951656 23270.9 1 6 CACCTG TCTCCATTCCAT - +4 cisbp__M3382-bin-fd59A -1 0.951656 23270.9 1 5 CACCTG AAATAAACAATA + +4 hocomoco__LHX2_HUMAN.H11MO.0.A-Awh-CG9876-CG18599-CG32532-CG34367-Dll-E5-Lim3-OdsH-Pph13-Rx-Vsx2-al-ap-ems-en-eve-ftz-hbn-ind-inv-lab-lbe-lms-otp-pb-repo-ro-slou-unc-4-unpg-zen2 -1 0.951656 23270.9 1 5 CACCTG TTTTAATTAGTT + +4 taipale_cyt_meth__ZNF385D_NCGTCGCGACGN_eDBD_meth 7 0.951656 23270.9 1 5 CACCTG TCGTCGCGACGA + +4 tiffin__TIFDMEM0000044 -1 0.951656 23270.9 1 5 CACCTG ATCGAAATCGAA + +4 transfac_pro__M05890 7 0.951656 23270.9 1 5 CACCTG CTGGGCATACGA + +4 transfac_pro__M06040 -1 0.951656 23270.9 1 5 CACCTG TCCAAAAAAATT + +4 transfac_pro__M05183 7 0.951656 23270.9 1 5 CACCTG TTTTCCGCCCCG - +4 transfac_pro__M06303 7 0.951656 23270.9 1 5 CACCTG TATCCAGTCCCC - +4 transfac_pro__M06730 7 0.951656 23270.9 1 5 CACCTG CCGTCCGAACAC - +4 transfac_pro__M07772-cad 7 0.951656 23270.9 1 5 CACCTG GGTTTATGGCCC - +4 transfac_pro__M06316 8 0.951656 23270.9 1 4 CACCTG TGGGCCATTATC + +4 transfac_pro__M05177 8 0.951656 23270.9 1 4 CACCTG TTTTCCGCCATA - +4 transfac_pro__M06681 8 0.951656 23270.9 1 4 CACCTG GTGGCTTTCACT - +4 transfac_pro__M06110 -3 0.951656 23270.9 1 3 CACCTG CTGTATTGCCGC + +4 taipale_tf_pairs__ETV2_ONECUT2_RCCGGAANNNNNATCGATN_CAP_repr-onecut-pnt 9 0.952034 23280.1 1 6 CACCTG GATCGATACCACTTCCGGT - +4 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNNNCAATTN_eDBD_meth_repr-C15-CG34367-gsb-gsb-n-prd-unpg 6 0.952557 23292.9 1 6 CACCTG TAATTGCTTTTTATAATCAATTA - +4 tfdimers__MD00128-cad 18 0.952742 23297.4 1 6 CACCTG ATAATTTAATAAATAATTAAAAAATAAT + +4 transfac_public__M00143-sv 20 0.952742 23297.4 1 6 CACCTG GGGGCGGCTACGCATCACTGCGCCTCGA - +4 tfdimers__MD00152-HGTX 16 0.953267 23310.2 1 6 CACCTG TTATTGTTTTATTTATTAATTTAATTT - +4 cisbp__M5826-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.953276 23310.5 1 6 CACCTG AACACTGCACATTGTT + +4 taipale_tf_pairs__HOXB2_PAX9_SGTCACGCNTCATTNN_CAP-pb-Poxm 8 0.953276 23310.5 1 6 CACCTG CGTCACGCCTCATTAA + +4 transfac_pro__M02802-SoxN 3 0.953276 23310.5 1 6 CACCTG AATCAATTCAATAATT + +4 taipale__SOX21_DBD_AACAATNNNNAKTGTT-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.953276 23310.5 1 6 CACCTG AACACTGCACATTGTT - +4 taipale_tf_pairs__HOXB2_SOX15_ACAAWRSNNNYMATTA_CAP_repr-pb 4 0.953276 23310.5 1 6 CACCTG TAATTGCGTCCATTGT - +4 transfac_pro__M06286 0 0.953276 23310.5 1 6 CACCTG CCCATGCCGTTCCCCC - +4 cisbp__M5371-klu-sr 11 0.953276 23310.5 1 5 CACCTG ATACGCCCACGCATTT - +4 taipale_cyt_meth__POU5F1_NWWTATGCTAATKARN_FL_meth-CG18599-dve-nub-pdm2-pdm3-vvl -2 0.953276 23310.5 1 4 CACCTG CCTCATTAGCATAATC - +4 flyfactorsurvey__sens-2_SANGER_2.5_FBgn0051632-sens-sens-2 13 0.953276 23310.5 1 3 CACCTG ATAAATCACAGCACTC + +4 cisbp__M5186-sens-sens-2 13 0.953276 23310.5 1 3 CACCTG ATAAATCACAGCACCC - +4 transfac_pro__M09016 0 0.953475 23315.3 1 6 CACCTG TGCTTG - +4 flyfactorsurvey__Antp_FlyReg_FBgn0000095-Antp 1 0.953475 23315.3 1 5 CACCTG ATAATT + +4 transfac_pro__M01673-bs 1 0.953475 23315.3 1 5 CACCTG AGACGC + +4 transfac_pro__M07047 1 0.953475 23315.3 1 5 CACCTG CTAATT - +4 transfac_pro__M07479-CG12071 -1 0.953475 23315.3 1 5 CACCTG TCTTCC - +4 cisbp__M4779-br -2 0.953475 23315.3 1 4 CACCTG ACTAAT + +4 flyfactorsurvey__br-Z4_FlyReg_FBgn0000210-br -2 0.953475 23315.3 1 4 CACCTG ACTAAT + +4 hdpi__IRF1 4 0.953475 23315.3 1 2 CACCTG TGAAAA + +4 hdpi__RBBP9 -4 0.953475 23315.3 1 2 CACCTG TTAAAA + +4 tfdimers__MD00531-cad 7 0.953509 23316.1 1 6 CACCTG AAAAAAGAACAAATAAATAAAAAAA - +4 cisbp__M0173 4 0.953511 23316.2 1 6 CACCTG GTACAATATGGTA + +4 cisbp__M5287-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-gsb-gsb-n-hbn-OdsH-Optix-prd-repo-Traf4-unc-4 1 0.953511 23316.2 1 6 CACCTG CTAATTAAATTAA + +4 taipale__ALX4_DBD_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-gsb-gsb-n-hbn-OdsH-Optix-prd-repo-Traf4-unc-4 1 0.953511 23316.2 1 6 CACCTG CTAATTAAATTAA + +4 taipale_cyt_meth__EGR3_NMCGCCCACGCAN_FL_meth-btd-klu-Spps-sr 6 0.953511 23316.2 1 6 CACCTG CCCGCCCACGCAC + +4 cisbp__M5986-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.953511 23316.2 1 6 CACCTG TTAATTAAATTAA - +4 taipale_cyt_meth__POU4F3_NTGCATWATGCAN_eDBD-acj6 1 0.953511 23316.2 1 6 CACCTG ATGCATTATGCAT - +4 transfac_pro__M07250-E2f1 -1 0.953511 23316.2 1 5 CACCTG CTTTCGCGCGCGC - +4 hocomoco__PAX3_HUMAN.H11MO.0.D-ey-eyg-gsb-gsb-n-prd 9 0.953511 23316.2 1 4 CACCTG TTAATCGATTATC - +4 taipale_cyt_meth__POU4F3_NTNAATWATGCAN_FL_meth-acj6-vvl 10 0.953511 23316.2 1 3 CACCTG ATGCATTATTTAT - +4 tfdimers__MD00420-E2f1 20 0.953527 23316.6 1 6 CACCTG TTTTTCTTTTCCTAATTTTTTTTTTT - +4 tfdimers__MD00474-Tbp 20 0.953527 23316.6 1 6 CACCTG AATTTTATAAATTAATTATTTAATTA - +4 cisbp__M1124-Antp-Awh-CG9876-CG11294-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-en-lab-otp-repo-ro-slou-unc-4-unpg-vvl-zen2 2 0.953703 23320.9 1 6 CACCTG ATTAATTA + +4 hdpi__CNOT6-larp-twin 2 0.953703 23320.9 1 6 CACCTG GGCAAATC + +4 taipale_cyt_meth__DLX2_NYAATTAN_FL-Dll-en 1 0.953703 23320.9 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__DLX2_NYAATTAN_FL_meth-Dll 1 0.953703 23320.9 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__DLX2_NYAATTAN_eDBD_meth-Dll 1 0.953703 23320.9 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__DLX5_NYAATTAN_eDBD_meth-Dll 1 0.953703 23320.9 1 6 CACCTG GTAATTAT + +4 transfac_pro__M07846-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-lbe-Lim3-lms-OdsH-pb-pdm3-Pph13-repo-ro-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.953703 23320.9 1 6 CACCTG CTAATTAG + +4 cisbp__M0093 2 0.953703 23320.9 1 6 CACCTG TTCGCGTC - +4 cisbp__M1166-Antp-CG34367-HGTX-ind-lbe-lbl-Scr 1 0.953703 23320.9 1 6 CACCTG CTAATTAA - +4 cisbp__M4720-abd-A 0 0.953703 23320.9 1 6 CACCTG TCAATTAA - +4 predrem__nrMotif124 2 0.953703 23320.9 1 6 CACCTG AGCACACT - +4 predrem__nrMotif1315 2 0.953703 23320.9 1 6 CACCTG TGGCCCCA - +4 scertf__macisaac.STP1 1 0.953703 23320.9 1 6 CACCTG AAGCCGCA - +4 taipale_cyt_meth__GSX2_STMATTAR_eDBD-abd-A-Antp-ap-Awh-btn-CG11085-CG11294-CG18599-CG4328-CG9876-Dfd-Drgx-E5-ems-en-eve-exex-HGTX-ind-inv-lab-lbl-Lim3-lms-Lmx1a-otp-pb-Pph13-ro-Rx-Scr-slou-tup-Ubx-unp 1 0.953703 23320.9 1 6 CACCTG CTAATTAC - +4 yetfasco__YDR463W_660 1 0.953703 23320.9 1 6 CACCTG GAGCCGCA - +4 cisbp__M1132 3 0.953703 23320.9 1 5 CACCTG TAATAAAT + +4 cisbp__M4989-bcd-Gsc 3 0.953703 23320.9 1 5 CACCTG CTTAATCC + +4 predrem__nrMotif267 3 0.953703 23320.9 1 5 CACCTG TGACTCCA + +4 flyfactorsurvey__AbdB_SOLEXA_FBgn0000015-Abd-B-Dbx-Ubx-cad -1 0.953703 23320.9 1 5 CACCTG TCATAAAA - +4 predrem__nrMotif1936 -1 0.953703 23320.9 1 5 CACCTG AATTGAAT - +4 transfac_pro__M07286-foxo-slp2 3 0.953703 23320.9 1 5 CACCTG AAAAACAA - +4 cisbp__M4864-cad-CG4328-Dbx-Lmx1a 4 0.953703 23320.9 1 4 CACCTG TAATTAAA + +4 jaspar__MA0319.1-Hsf 4 0.953703 23320.9 1 4 CACCTG ATGGAACA + +4 yetfasco__YGL073W_476-Hsf 4 0.953703 23320.9 1 4 CACCTG ATGGAACA + +4 cisbp__M4281-Hsf 4 0.953703 23320.9 1 4 CACCTG ATGGAACA - +4 cisbp__M4738-abd-A-Antp-ap-bsh-btn-C15-CG18599-Dbx-E5-ems-ftz-lab-Lmx1a-otp-pb-Scr-Ubx-zen2 4 0.953703 23320.9 1 4 CACCTG TCATTAAA - +4 cisbp__M5074-abd-A-ap-Awh-bsh-CG11294-CG18599-CG32532-CG9876-E5-ems-eve-hbn-inv-lab-lbe-lbl-Lim1-Lim3-Lmx1a-OdsH-otp-pb-Pph13-ro-Rx-Ubx-unpg-Vsx1-zen2 4 0.953703 23320.9 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__CG4328_SOLEXA_FBgn0036274-CG4328-Dbx-Lmx1a-cad 4 0.953703 23320.9 1 4 CACCTG TAATTAAA - +4 taipale_cyt_meth__BARHL1_NTAATTGN_eDBD_meth_repr-B-H1-B-H2-bsh-CG11085-Dr-en-exex-inv-lms-Rx-unpg-Vsx1 -2 0.953703 23320.9 1 4 CACCTG GCAATTAG - +4 transfac_pro__M01937-Hsf 4 0.953703 23320.9 1 4 CACCTG ATGGAACA - +4 taipale__Lhx8_DBD_NTAATTAN_repr-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-exex-inv-lab-lbe-Lim3-OdsH-pdm3-Pph13-repo-unc-4-unpg-Vsx1-Vsx2 -3 0.953703 23320.9 1 3 CACCTG CTAATTAG + +4 taipale_cyt_meth__HOXA2_NYAATTAN_eDBD_meth-Antp-Awh-bsh-btn-Dfd-E5-ems-en-eve-exex-ind-inv-lab-Lim3-pb-Scr-slou-Ubx-zen2 5 0.953703 23320.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__HOXA5_NYAATTAN_eDBD_meth-abd-A-Antp-Awh-bsh-btn-CG4328-Dfd-Dll-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-Lmx1a-OdsH-pb-Scr-slou-Ubx-unpg-zen-zen2 5 0.953703 23320.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__HOXB2_NYAATTAN_eDBD-Antp-Awh-bsh-btn-CG18599-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim1-Lim3-lms-OdsH-pb-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen-zen2 5 0.953703 23320.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__LHX9_CYAATTAR_eDBD-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-ind-inv-lab-lbe-Lim3-lms-OdsH-otp-Pph13-repo-ro-Rx-Ubx-unc-4-unpg-Vsx1-Vsx2 -3 0.953703 23320.9 1 3 CACCTG CTAATTAG + +4 cisbp__M0853 -3 0.953703 23320.9 1 3 CACCTG TTGATTGA - +4 cisbp__M1219-acj6-Antp-HGTX-ind-lab-lbl-Scr-Ubx -3 0.953703 23320.9 1 3 CACCTG CTAATTAA - +4 taipale_cyt_meth__LHX4_NTAATTAN_FL_repr-abd-A-al-Antp-Awh-btn-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-E5-ems-en-exex-ind-inv-lab-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pb-pdm3-Pph13-repo-r 5 0.953703 23320.9 1 3 CACCTG TTAATTAA - +4 cisbp__M2051-slbo -4 0.953703 23320.9 1 2 CACCTG TTTGCAAT - +4 cisbp__M2565-Hsf 0 0.954185 23332.7 1 6 CACCTG TTTCTTTTCTTTTCT + +4 cisbp__M2566-Hsf 5 0.954185 23332.7 1 6 CACCTG AGAAATTTCTTTTCT + +4 cisbp__M2568-Hsf 0 0.954185 23332.7 1 6 CACCTG TTTCTTTTCTAGAAA + +4 cisbp__M3411-croc-fd59A-fkh 8 0.954185 23332.7 1 6 CACCTG TAAATAAACATTTCA + +4 cisbp__M5821-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.954185 23332.7 1 6 CACCTG AACAATTTCATTGTT + +4 cisbp__M5833-D-Sox15-Sox21a-Sox21b-SoxN 6 0.954185 23332.7 1 6 CACCTG ATGAATAACATTCAT + +4 taipale__CENPB_full_CCCGCNTNNNRCGAA_repr 2 0.954185 23332.7 1 6 CACCTG CCCGCATACAACGAA + +4 taipale__SOX18_full_AACAATNNCATTGTT-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.954185 23332.7 1 6 CACCTG AACAATTTCATTGTT + +4 taipale__Sox1_DBD_NACAATWNCATTGTN-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.954185 23332.7 1 6 CACCTG AACAATAACATTGTT + +4 transfac_pro__M02902-D-Sox21a-Sox21b 4 0.954185 23332.7 1 6 CACCTG CTCACACAATGGCGC + +4 transfac_pro__M09305-ovo 5 0.954185 23332.7 1 6 CACCTG ATAAATAACGGTATT + +4 cisbp__M4870-btd-cbt-CG3065-CG42741-dar1-E2f2-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 9 0.954185 23332.7 1 6 CACCTG TTGGCCCCGCCCCCT - +4 flyfactorsurvey__phol_SOLEXA_5_FBgn0035997-pho-phol 6 0.954185 23332.7 1 6 CACCTG GGCCGCCATTTTGTT - +4 taipale__HESX1_DBD_NTAATTRGYAATTAN-al-Antp-CG34367-Dfd-Dr-en-ind-inv-lbe-lms-OdsH-repo-Scr-unc-4-unpg 1 0.954185 23332.7 1 6 CACCTG TTAATTGCCAATTAG - +4 transfac_public__M00163-Hsf 0 0.954185 23332.7 1 6 CACCTG TTTCTTTTCTTTTCT - +4 transfac_public__M00164-Hsf 5 0.954185 23332.7 1 6 CACCTG AGAAATTTCTTTTCT - +4 transfac_public__M00166-Hsf 0 0.954185 23332.7 1 6 CACCTG TTTCTTTTCTAGAAA - +4 factorbook__NRF1-E2f1-ewg -1 0.954185 23332.7 1 5 CACCTG CACTGCGCATGCGCA - +4 transfac_pro__M01399-H2.0 11 0.954185 23332.7 1 4 CACCTG CCATAATTAATTACA + +4 transfac_pro__M05940 12 0.954185 23332.7 1 3 CACCTG GTGTCGATGGCGGAC - +4 cisbp__M1872 4 0.954217 23333.5 1 6 CACCTG AATAAACAATA + +4 fantom__motif117_SKSNGCGCTSN 4 0.954217 23333.5 1 6 CACCTG CTGTGCGCTGC + +4 hocomoco__PHX2B_HUMAN.H11MO.0.D-Awh-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-eve-hbn-otp-repo-unc-4 1 0.954217 23333.5 1 6 CACCTG TAATTTAATTA + +4 predrem__nrMotif2603 3 0.954217 23333.5 1 6 CACCTG CCCCGCTTCCC + +4 stark__TAATTNWMATT 0 0.954217 23333.5 1 6 CACCTG TAATTAAAATT + +4 stark__TGAYWWWTGCA 3 0.954217 23333.5 1 6 CACCTG TGACAAATGCA + +4 taipale_cyt_meth__E2F2_GCGCGCGCGYW_eDBD_repr-E2f1 5 0.954217 23333.5 1 6 CACCTG GCGCGCGCGTA + +4 hocomoco__CUX2_HUMAN.H11MO.0.D-ct 0 0.954217 23333.5 1 6 CACCTG TTCATTGATTT - +4 jaspar__MA0040.1 4 0.954217 23333.5 1 6 CACCTG AATAAACAATA - +4 cisbp__M1738 -1 0.954217 23333.5 1 5 CACCTG AGCTCCGACGA + +4 flyfactorsurvey__dys_tgo_SANGER_5_FBgn0015014-dysf-tgo 6 0.954217 23333.5 1 5 CACCTG AGTCACGATTT + +4 stark__AAATKKCATTA -1 0.954217 23333.5 1 5 CACCTG AAATGGCATTA + +4 taipale_cyt_meth__HOXA13_NCCAATAAAAN_FL_meth -1 0.954217 23333.5 1 5 CACCTG ACCAATAAAAC + +4 transfac_pro__M05001 -1 0.954217 23333.5 1 5 CACCTG ATCGGCGGCCC - +4 cisbp__M1120 7 0.954217 23333.5 1 4 CACCTG TATTAATTACA + +4 cisbp__M1222-Lim3-ey-ind-toy-vvl -2 0.954217 23333.5 1 4 CACCTG ACTAATTAATT - +4 jaspar__MA0621.1-Lim3-ind-vvl -2 0.954217 23333.5 1 4 CACCTG ACTAATTAATT - +4 taipale__HOXC11_DBD_NGYAATWAAAN-abd-A-Abd-B-cad-eve-Ubx 7 0.954217 23333.5 1 4 CACCTG TTTTTATTGCT - +4 taipale_cyt_meth__HOXC11_RGYAATAAAAN_FL_meth-abd-A-Abd-B-Antp-cad-Dbx-eve-ftz-Scr-Ubx 7 0.954217 23333.5 1 4 CACCTG TTTTTATGGCC - +4 cisbp__M5391-bsh-CG34367-CG9876-Dr-E5-ems-en-gsb-gsb-n-inv-lab-pdm3-prd-unpg 0 0.954293 23335.3 1 6 CACCTG TAATTGACCAATTA + +4 cisbp__M5473-foxo 8 0.954293 23335.3 1 6 CACCTG TTTCCCCACACGAC - +4 fantom__motif168_TCTCAGAGTATAAA 5 0.954293 23335.3 1 6 CACCTG TTTATACTCTGAGA - +4 stark__AATTRNNNNCAATT 9 0.954293 23335.3 1 5 CACCTG AATTGAAAACAATT - +4 cisbp__M5724-Dll-dve-nub-pdm2-pdm3-vvl -3 0.954293 23335.3 1 3 CACCTG CTAATTTGCATATT + +4 taipale__POU1F1_DBD_NWTATGCWAATKAG_repr-Dll-dve-nub-pdm2-pdm3-vvl -3 0.954293 23335.3 1 3 CACCTG CTAATTTGCATATT - +4 cisbp__M2151-Tbp 2 0.954323 23336.1 1 6 CACCTG TTTATTTATATATAATATGA + +4 dbcorrdb__CHD1__ENCSR000AQD_1__m3-Chd1 4 0.954323 23336.1 1 6 CACCTG GCAAGCCCGACAGCCGCAAC + +4 dbcorrdb__POLR2A__ENCSR000DKT_1__m2-RpII215 4 0.954323 23336.1 1 6 CACCTG AGCATTACGGCGCTCGCGCT + +4 dbcorrdb__POLR2A__ENCSR000DLV_1__m1-E(z)-Myc-RpII215 0 0.954323 23336.1 1 6 CACCTG CGCCCGCGCGGCGGCTGCGG + +4 dbcorrdb__ZNF143__ENCSR000DZL_1__m3-Brf-E2f1-E(z)-Hcf-Max-Myc-RpII215-tna 6 0.954323 23336.1 1 6 CACCTG CGGCGGCGCTTGCGCGCCGG + +4 yetfasco__YBR089C-A_792-Tbp 2 0.954323 23336.1 1 6 CACCTG TTTATTTATATATAATATGA + +4 dbcorrdb__CHD2__ENCSR000EBT_1__m2-btd-Chd1-E2f2-kay-Nf-YA-Nf-YB-Nf-YC-Spps 1 0.954323 23336.1 1 6 CACCTG CCCTCCGATTGGCGGAGCCG - +4 dbcorrdb__E2F4__ENCSR000EWL_1__m1-E2f1-E2f2-Eip74EF-Hcf-Sin3A 5 0.954323 23336.1 1 6 CACCTG CCCCGAATTTCCCGCCCCCC - +4 dbcorrdb__EGR1__ENCSR000BJA_1__m1-Brf-brm-btd-CG42741-CoRest-crol-ct-CTCF-dar1-E2f1-ERR-E(z)-HDAC1-kay-Klf15-klu-luna-Max-Nelf-E-Rbbp5-RpII215-sd-Spps-Spt20-sr-SREBP-sv-tna-vtd 4 0.954323 23336.1 1 6 CACCTG CCCCCCCCGCCCCCGCCCCC - +4 dbcorrdb__POLR2A__ENCSR000EEP_1__m1-E(z)-Hcf-RpII215 0 0.954323 23336.1 1 6 CACCTG TCGCGGCGCTTGCGCCCGGC - +4 dbcorrdb__POLR2A__ENCSR000EXO_1__m2-RpII215 3 0.954323 23336.1 1 6 CACCTG ACGGACCAAAGTCGCGGATG - +4 dbcorrdb__YY1__ENCSR000BNP_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 0 0.954323 23336.1 1 6 CACCTG CCGCGGCCGCCATTTTGGCG - +4 dbcorrdb__ZNF143__ENCSR000ECO_1__m2-bon-Brf-brm-CrebB-E(z)-HDAC1-Nelf-E-RpII215-SREBP-Taf1-tna 5 0.954323 23336.1 1 6 CACCTG TAGTCCCCCGGCCGGGCGGG - +4 transfac_pro__M01506-abd-A-CG4328-Lmx1a-Ubx 15 0.954323 23336.1 1 5 CACCTG GCCCCATTAATTAATCAGCG - +4 taipale__Msx3_DBD_NYAATTAAAANNYAATTA-Dr-HGTX-ind 5 0.954979 23352.1 1 6 CACCTG GCAATTAAAAACCAATTA + +4 cisbp__M6054-Dr-HGTX-ind 5 0.954979 23352.1 1 6 CACCTG GCAATTAAAAACCAATTA - +4 hocomoco__VAX1_HUMAN.H11MO.0.D-Awh-CG34367-Dll-E5-Vsx1-Vsx2-btn-ems-eve-ind-pb-repo-unpg-zen2 6 0.954979 23352.1 1 6 CACCTG TAATTAACCCTAATTACT - +4 cisbp__M4962-exex-Lim3 1 0.955065 23354.2 1 6 CACCTG GTAATTA + +4 flyfactorsurvey__Exex_Cell_FBgn0041156-Lim3-exex 1 0.955065 23354.2 1 6 CACCTG GTAATTA + +4 transfac_pro__M06887-CG17829 1 0.955065 23354.2 1 6 CACCTG ATGCGTG + +4 cisbp__M2011-abd-A-al-ap-Awh-bsh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dll-Dr-E5-ems-en-eve-gsb-gsb-n-hbn-ind-inv-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-Optix-otp-pb-pdm3-PHDP-Pph13-prd- 0 0.955065 23354.2 1 6 CACCTG TAATTAG - +4 hdpi__BARX1 1 0.955065 23354.2 1 6 CACCTG TTCCATT - +4 hdpi__ENO1 1 0.955065 23354.2 1 6 CACCTG ATTCATT - +4 jaspar__MA0184.1-Awh-C15-CG4328-CG9876-CG18599-CG32532-CG34367-E5-Lim3-Lmx1a-OdsH-Optix-Pph13-Rx-Ubx-Vsx1-Vsx2-al-ap-ems-en-eve-ind-inv-lab-otp-pb-repo-ro-unc-4-unpg 0 0.955065 23354.2 1 6 CACCTG TAATTAG - +4 jaspar__MA0202.1-Awh-C15-CG4328-CG9876-CG11085-CG11294-CG18599-CG32532-CG34367-Dll-Dr-E5-Lim1-Lim3-Lmx1a-OdsH-Optix-PHDP-Pph13-Rx-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-ems-en-eve-gsb-gsb-n-hbn-ind-inv-lbe-lbl 0 0.955065 23354.2 1 6 CACCTG TAATTAG - +4 predrem__nrMotif2017 1 0.955065 23354.2 1 6 CACCTG AAGCCAA - +4 predrem__nrMotif2305 0 0.955065 23354.2 1 6 CACCTG TGCATTA - +4 transfac_pro__M04848-Taf1 1 0.955065 23354.2 1 6 CACCTG TCCGCTT - +4 transfac_pro__M04944 0 0.955065 23354.2 1 6 CACCTG TTCCGTT - +4 elemento__AGCCGCG -1 0.955065 23354.2 1 5 CACCTG AGCCGCG + +4 elemento__AGCCGGC -1 0.955065 23354.2 1 5 CACCTG AGCCGGC + +4 elemento__AGCGGAA -1 0.955065 23354.2 1 5 CACCTG AGCGGAA + +4 elemento__AGCGGCG -1 0.955065 23354.2 1 5 CACCTG AGCGGCG + +4 elemento__CCCCGCG -1 0.955065 23354.2 1 5 CACCTG CCCCGCG + +4 elemento__CCCCGGC -1 0.955065 23354.2 1 5 CACCTG CCCCGGC + +4 elemento__TCCCGGC -1 0.955065 23354.2 1 5 CACCTG TCCCGGC + +4 transfac_pro__M01696 -1 0.955065 23354.2 1 5 CACCTG GCCATTA + +4 elemento__CGCCGGC -1 0.955065 23354.2 1 5 CACCTG GCCGGCG - +4 elemento__CGCGGGA -1 0.955065 23354.2 1 5 CACCTG TCCCGCG - +4 elemento__CGCGGGC -1 0.955065 23354.2 1 5 CACCTG GCCCGCG - +4 elemento__TGCTGGC -1 0.955065 23354.2 1 5 CACCTG GCCAGCA - +4 elemento__TTCCGGC -1 0.955065 23354.2 1 5 CACCTG GCCGGAA - +4 elemento__CATAAAA -2 0.955065 23354.2 1 4 CACCTG CATAAAA + +4 predrem__nrMotif322 -2 0.955065 23354.2 1 4 CACCTG TCTCTAA + +4 fantom__motif37_GCTCGCA 3 0.955065 23354.2 1 4 CACCTG TGCGAGC - +4 transfac_pro__M00750 3 0.955065 23354.2 1 4 CACCTG AATTTCC - +4 predrem__nrMotif557 4 0.955065 23354.2 1 3 CACCTG ATTTCAA + +4 transfac_pro__M05056 -3 0.955065 23354.2 1 3 CACCTG TTTATTT - +4 hdpi__SMCR7L-Pbp95 -4 0.955065 23354.2 1 2 CACCTG TGCAAAG + +4 hdpi__SNAPC4-Pbp95 -4 0.955065 23354.2 1 2 CACCTG TGCAAAT + +4 scertf__morozov.MGA1 5 0.955065 23354.2 1 2 CACCTG TTCTAGA + +4 cisbp__M1360 1 0.955503 23364.9 1 6 CACCTG ATTCCGCAAA + +4 cisbp__M1674 0 0.955503 23364.9 1 6 CACCTG AATTTTTCAC + +4 cisbp__M5546-Abd-B 0 0.955503 23364.9 1 6 CACCTG GTCGTAAAAT + +4 flyfactorsurvey__bin_FlyReg_FBgn0045759-bin 1 0.955503 23364.9 1 6 CACCTG TAAACAACGA + +4 homer__AAATCACTGC_Gfi1b-sens-sens-2 1 0.955503 23364.9 1 6 CACCTG AAATCACTGC + +4 homer__ATTTGCATAA_Oct4-SoxN-nub-pdm2-vvl 3 0.955503 23364.9 1 6 CACCTG ATTTGCATAA + +4 transfac_pro__M05035 4 0.955503 23364.9 1 6 CACCTG ACGCCGCCAA + +4 transfac_pro__M05167 4 0.955503 23364.9 1 6 CACCTG TTGGCGCCCG + +4 cisbp__M3023-ct 2 0.955503 23364.9 1 6 CACCTG GGGATCGATC - +4 cisbp__M6169-Myc-nej 2 0.955503 23364.9 1 6 CACCTG ATTGCACAAT - +4 predrem__nrMotif2460 1 0.955503 23364.9 1 6 CACCTG AAGCATGCTT - +4 predrem__nrMotif877 0 0.955503 23364.9 1 6 CACCTG TTCATTCCCA - +4 predrem__nrMotif952 3 0.955503 23364.9 1 6 CACCTG TCTTGCCAAA - +4 stark__AAHKMTHBCA-kni 3 0.955503 23364.9 1 6 CACCTG TGGTAGATTT - +4 taipale_cyt_meth__NFATC3_NAYGGAAAMN_eDBD-Jra-kay-NFAT 3 0.955503 23364.9 1 6 CACCTG ATTTTCCATT - +4 taipale_cyt_meth__NFATC4_NAYGGAAAAN_eDBD_meth_repr-NFAT 4 0.955503 23364.9 1 6 CACCTG ATTTTCCGTT - +4 transfac_pro__M05437-CG42741-luna 4 0.955503 23364.9 1 6 CACCTG CCCCCGCCCT - +4 transfac_pro__M07786-dve-vvl 0 0.955503 23364.9 1 6 CACCTG TAATTAATGC - +4 transfac_public__M00106-ct 2 0.955503 23364.9 1 6 CACCTG GGGATCGATC - +4 homer__GGCAATTAAA_Unknown-Dbx-Ubx-abd-A-cad -1 0.955503 23364.9 1 5 CACCTG GGCAATTAAA + +4 predrem__nrMotif2473 -1 0.955503 23364.9 1 5 CACCTG CACTCCATTT + +4 transfac_pro__M07517 5 0.955503 23364.9 1 5 CACCTG GGCGCCGCCA + +4 tiffin__TIFDMEM0000084 -1 0.955503 23364.9 1 5 CACCTG ATTTTGTTTT - +4 transfac_pro__M01971-CG4328-Lim1-Lim3-Lmx1a-OdsH-repo-unc-4-vvl 5 0.955503 23364.9 1 5 CACCTG TTAATTAATT - +4 transfac_pro__M04991 5 0.955503 23364.9 1 5 CACCTG TGGGCGGCCT - +4 transfac_pro__M05096 5 0.955503 23364.9 1 5 CACCTG TGGGCGGCCT - +4 transfac_pro__M05132 5 0.955503 23364.9 1 5 CACCTG GGATCGGCCT - +4 transfac_pro__M07783-Dfd-ems-eve-zen 6 0.955503 23364.9 1 4 CACCTG CATCATTAGC + +4 cisbp__M5316-Irbp18-nej-slbo-srl-Xrp1 6 0.955503 23364.9 1 4 CACCTG ATTGCGCAAT - +4 homer__GATTGCATCA_AARE 6 0.955503 23364.9 1 4 CACCTG TGATGCAATC - +4 taipale__CEBPD_DBD_NTTRCGCAAY-Irbp18-nej-slbo-srl-Xrp1 6 0.955503 23364.9 1 4 CACCTG ATTGCGCAAT - +4 taipale__Cebpb_DBD_NTTRCGCAAY_repr-Irbp18-nej-slbo-Xrp1 6 0.955503 23364.9 1 4 CACCTG ATTGCGCAAT - +4 tiffin__TIFDMEM0000011 -3 0.955503 23364.9 1 3 CACCTG CTAAGAAAAA + +4 cisbp__M6029-Abd-B 7 0.955503 23364.9 1 3 CACCTG TTTTTACGAC - +4 taipale__Hoxc10_DBD_GTCGTWAAAN_repr-Abd-B 7 0.955503 23364.9 1 3 CACCTG TTTTTATGAC - +4 transfac_pro__M01726 -3 0.955503 23364.9 1 3 CACCTG ATTACTAATG - +4 cisbp__M6241-bin-croc-fd59A-fkh-foxo 8 0.955503 23364.9 1 2 CACCTG TAAATAAACA + +4 hocomoco__FOXJ2_HUMAN.H11MO.0.C-bin-croc-fd59A-fkh-foxo-slp1 8 0.955503 23364.9 1 2 CACCTG TAAATAAACA - +4 predrem__nrMotif1182 1 0.955512 23365.1 1 6 CACCTG TTTTCTTGA + +4 predrem__nrMotif2046 2 0.955512 23365.1 1 6 CACCTG AGCACACAA + +4 predrem__nrMotif289 3 0.955512 23365.1 1 6 CACCTG AAATTCCAA + +4 transfac_pro__M00713-Tbp-Trf-Trf2 0 0.955512 23365.1 1 6 CACCTG TATTTATAT + +4 predrem__nrMotif2265 0 0.955512 23365.1 1 6 CACCTG CTCCGCTGC - +4 hocomoco__SOX9_HUMAN.H11MO.1.B-Sox100B-Sox102F -1 0.955512 23365.1 1 5 CACCTG CCATTGTTT + +4 predrem__nrMotif2465 -1 0.955512 23365.1 1 5 CACCTG TCCATCATT + +4 predrem__nrMotif2565 -1 0.955512 23365.1 1 5 CACCTG GTCTCATTT + +4 taipale__Jdp2_DBD_ATGASTCAT_repr-cnc-foxo-Jra-kay-Mef2-Myc-NFAT-Stat92E 4 0.955512 23365.1 1 5 CACCTG ATGACTCAT + +4 transfac_pro__M04880-kay-Tbp -1 0.955512 23365.1 1 5 CACCTG TTCTGATTG + +4 cisbp__M5277-abd-A-Antp-ap-Awh-btn-CG18599-CG32532-E5-ems-ftz-lab-Lim1-Lim3-otp-pb-Scr-unpg-Vsx1-zen-zen2 4 0.955512 23365.1 1 5 CACCTG TAATTAAGA - +4 flyfactorsurvey__Zen2_Cell_FBgn0004054-Antp-Awh-CG18599-CG32532-Dfd-E5-Lim3-Scr-Vsx1-abd-A-ap-btn-ems-ftz-lab-otp-pb-unpg-zen-zen2 4 0.955512 23365.1 1 5 CACCTG TAATTAAGA - +4 cisbp__M1143-Antp-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Dr-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-acj6-al-ap-btn-dve-ems-en-eve-exex-ey-ind-inv-lab-lbe-lbl-lms-otp-pb- 5 0.955512 23365.1 1 4 CACCTG TTAATTAGC - +4 cisbp__M4853-al-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-Dll-E5-ems-en-ey-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-toy-tup-Ubx-unc-4-unpg-Vsx1-Vsx2 5 0.955512 23365.1 1 4 CACCTG CTAATTAAA - +4 flyfactorsurvey__CG33980_SOLEXA_2_10_FBgn0053980-Awh-C15-CG9876-CG11294-CG18599-CG32532-CG34367-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Traf4-Ubx-Vsx1-Vsx2-al-ap-ems-en-ey-hbn-ind-inv-lab-lbe-lbl-lm 5 0.955512 23365.1 1 4 CACCTG CTAATTAAA - +4 flyfactorsurvey__lim_SOLEXA_2_FBgn0026411-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-E5-Lim1-Lim3-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-en-eve-hbn-inv-lab-lbl-lms-otp-repo-ro-slou-unc-4-unpg-zfh2 5 0.955512 23365.1 1 4 CACCTG TTAATTAAC - +4 hdpi__ARNTL-cyc 5 0.955512 23365.1 1 4 CACCTG CCGATAAGC - +4 predrem__nrMotif1006 -2 0.955512 23365.1 1 4 CACCTG TCTTTGGGC - +4 predrem__nrMotif11 5 0.955512 23365.1 1 4 CACCTG ATTTGTTCT - +4 scertf__spivak.GCN4-GATAe-Jra-Mef2-Myc-NFAT-Stat92E-bon-cnc-grn-kay-pan-pnr 6 0.955512 23365.1 1 3 CACCTG ATGACTCAT + +4 transfac_pro__M04693-bon-cnc-GATAe-grn-Jra-kay-Mef2-NFAT-pan-pnr 6 0.955512 23365.1 1 3 CACCTG ATGAGTCAC + +4 transfac_pro__M04710-Chd1-CoRest -3 0.955512 23365.1 1 3 CACCTG CTCGCGAGA - +4 tfdimers__MD00034-SoxN 7 0.955969 23376.3 1 6 CACCTG GATTAAATTCCTTTGTTATGCTAATGAATTT + +4 tfdimers__MD00293-Mad-Sox14 16 0.955969 23376.3 1 6 CACCTG TAAAACAAAACAAAGGATCCTTTGTTTTTTT - +4 transfac_pro__M05234-ERR-E(z) 13 0.956092 23379.3 1 6 CACCTG GGGGGGGCCCGGCCGCCTGTC + +4 transfac_pro__M05272 6 0.956092 23379.3 1 6 CACCTG GGGGGGGCCCTGCTGCCCCCC + +4 transfac_pro__M01571 2 0.956092 23379.3 1 6 CACCTG ACTCCCTCGGGTTTTCGAAAT - +4 transfac_pro__M06912 16 0.956092 23379.3 1 5 CACCTG GACCATCCCCACACGGCCCCT - +4 transfac_pro__M05195-E(z) 18 0.956092 23379.3 1 3 CACCTG AGGGCACGGCGGGGCCCCCAC - +4 stark__TAAT-ap 2 0.956736 23395.1 1 2 CACCTG ATTA - +4 swissregulon__hs__HOX_A6_A7_B6_B7_.p2-Ubx-abd-A 2 0.956736 23395.1 1 2 CACCTG ATTA - +4 transfac_pro__M08619-nub-pdm2 16 0.957099 23403.9 1 6 CACCTG GAATATGCAAAACTCCAACAAAAGAACAAC + +4 tfdimers__MD00532-foxo 9 0.957099 23403.9 1 6 CACCTG TTTTTTTTTTGCTTGTTTGTTTTTTTTTTT - +4 taipale_cyt_meth__POU3F2_NTATGCGCATAN_eDBD_meth-nub-pdm2-vvl 5 0.957141 23405 1 6 CACCTG TTATGCGCATAA - +4 transfac_pro__M06810 1 0.957141 23405 1 6 CACCTG GTATTTGCCATA - +4 homer__GGCCATAAATCA_HOXA9-cad-eve 7 0.957141 23405 1 5 CACCTG GGCCATAAATCA + +4 taipale_cyt_meth__CEBPG_NRTTGCGYAAYN_eDBD_meth-CG7786-gt-Irbp18-nej-Pdp1-slbo-vri-Xrp1 7 0.957141 23405 1 5 CACCTG TATTGCGTAATA + +4 transfac_pro__M05564 -1 0.957141 23405 1 5 CACCTG TCGTCCATCGGG + +4 transfac_pro__M06213 -1 0.957141 23405 1 5 CACCTG TCCGCCGTCTGC + +4 transfac_pro__M07689-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 7 0.957141 23405 1 5 CACCTG TATTGCGCAATA + +4 taipale_tf_pairs__CEBPG_ATF4_NNATGAYGCAAT_CAP 7 0.957141 23405 1 5 CACCTG ATTGCGTCATCC - +4 tiffin__TIFDMEM0000109 7 0.957141 23405 1 5 CACCTG TTTACAACACTG - +4 transfac_pro__M06147 7 0.957141 23405 1 5 CACCTG TCCCATTTATCT - +4 transfac_pro__M06172 7 0.957141 23405 1 5 CACCTG GCGTTAGTCCCT - +4 transfac_pro__M06345 8 0.957141 23405 1 4 CACCTG GATGAAAAAAGC + +4 transfac_pro__M06566 8 0.957141 23405 1 4 CACCTG TGGGCAAACACA + +4 transfac_pro__M06970 8 0.957141 23405 1 4 CACCTG TGGGGATCCCCC + +4 transfac_pro__M06992 8 0.957141 23405 1 4 CACCTG TGGGGATCCCCC - +4 transfac_pro__M06907 -3 0.957141 23405 1 3 CACCTG CTTACAAGAAAC + +4 taipale_cyt_meth__ZBED1_NTRTCGCGAYAN_eDBD_meth_repr-CG13775 9 0.957141 23405 1 3 CACCTG ATATCGCGATAT - +4 cisbp__M6044-Awh 10 0.957141 23405 1 2 CACCTG TAATTGCAATCA + +4 taipale__Lhx8_DBD_TRATTGCAATYA-Awh 10 0.957141 23405 1 2 CACCTG TAATTGCAATCA + +4 taipale_cyt_meth__ZSCAN1_NYRCACACNCTGMAAMN_eDBD 6 0.957191 23406.2 1 6 CACCTG ATGCACACACTGAAAAA + +4 c2h2_zfs__M5120 11 0.957191 23406.2 1 6 CACCTG TTCGTGGCATTTTTCTA - +4 taipale__ZNF713_full_TAGAYRAYTGMCANGAA_repr 11 0.957191 23406.2 1 6 CACCTG TTCGTGGCATTTTTCTA - +4 transfac_pro__M07921-dati 7 0.957191 23406.2 1 6 CACCTG TTTTTTTTGCATTTTTT - +4 transfac_pro__M05397 14 0.957191 23406.2 1 3 CACCTG GAAACCCCCCCCCACAC - +4 tfdimers__MD00133-pho-phol 16 0.957414 23411.6 1 6 CACCTG ATTAAATAATCCATTTTAATTA + +4 taipale_cyt_meth__NEUROD1_AAWTANNNNNNCATATGNN_FL_repr-amos-ato-da-dimm-HLH54F-Oli-tap 3 0.957685 23418.3 1 6 CACCTG AAATACCGCGCCATATGGC + +4 taipale_cyt_meth__ZSCAN16_NANTGTTAACAGAGCCTCN_FL_meth 14 0.957685 23418.3 1 5 CACCTG TGAGGCTCTGTTAACACTT - +4 taipale_cyt_meth__ZBTB32_NRTACAGTNNNACTGTAYN_eDBD_repr 15 0.957685 23418.3 1 4 CACCTG TGTACAGTATTACTGTACA + +4 transfac_public__M00237-ss-tgo 15 0.957685 23418.3 1 4 CACCTG GGGGATCGCGTGACAACCC + +4 tfdimers__MD00359-Stat92E 19 0.958004 23426.1 1 6 CACCTG TTTTTGCTTTCTTTTTCACAATTTTTTTT + +4 tfdimers__MD00159 4 0.958004 23426.1 1 6 CACCTG TAAAAAGATTGTGTAATCCCAAATTATTA - +4 tfdimers__MD00255-gsb-gsb-n-prd-Ptx1 3 0.958004 23426.1 1 6 CACCTG ATATATATTATTAATTAGATTAGATTATT - +4 tfdimers__MD00150-pho-phol 15 0.958357 23434.7 1 6 CACCTG TTTAATATTTTCCATTTTATTTT + +4 tfdimers__MD00201-Taf7-Tbp 17 0.958357 23434.7 1 6 CACCTG ATTAGTTAATGTTTATATTATTT + +4 cisbp__M3720-sv 20 0.95868 23442.6 1 6 CACCTG GGGGCCGCTACGCATCAGTGCGCCTCGA - +4 cisbp__M6475-CG9650-nej-nub-pdm2-SoxN 3 0.958699 23443.1 1 6 CACCTG ATTTGCATAACAATGG + +4 taipale_cyt_meth__HOXD11_NRTCGTAAAANNTTAN_eDBD_meth-Abd-B-cad 7 0.958699 23443.1 1 6 CACCTG GGTCGTAAAACTTTAT + +4 transfac_pro__M01426-Abd-B-cad-eve 10 0.958699 23443.1 1 6 CACCTG GGAGCCATAAAATTCG + +4 cisbp__M5741-acj6-Antp-btn-Dfd-nub-pdm2-vvl 0 0.958699 23443.1 1 6 CACCTG CTCATTAATTATGCAT - +4 hocomoco__ISX_HUMAN.H11MO.0.D-Awh-C15-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dll-Dr-Drgx-E5-HGTX-Lim3-Lmx1a-OdsH-Optix-Pph13-Rx-Traf4-Vsx1-Vsx2-al-ap-bsh-ems-en-ey-gsb-gsb-n-hbn-ind-inv-lbe-lbl 5 0.958699 23443.1 1 6 CACCTG AATTTAAGCTAATTAA - +4 stark__BMGYBGYYGYNGMVBV-Adf1 10 0.958699 23443.1 1 6 CACCTG TGTGCAACAACGACGG - +4 taipale__POU4F2_DBD_NTGMATAATTAATKAG-acj6-Antp-Lim3-vvl 0 0.958699 23443.1 1 6 CACCTG CTCATTAATTATGCAT - +4 transfac_pro__M01332-al-B-H1-B-H2-CG34367-Dr-lms-tup-unpg 0 0.958699 23443.1 1 6 CACCTG GAATTAATTGGTTGTT - +4 taipale__Egr1_mouse_DBD_mutant_DBD_NNMCGCCCMCTCANNN-btd-klu-Spps-sr 11 0.958699 23443.1 1 5 CACCTG CTACGCCCACTCAATT + +4 cisbp__M6002-btd-klu-Spps-sr 11 0.958699 23443.1 1 5 CACCTG CTACGCCCACTCAATT - +4 cisbp__M5286-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-eve-gsb-gsb-n-hbn-Lmx1a-OdsH-Optix-prd-repo-Traf4-unc-4 1 0.958859 23447 1 6 CACCTG CTAATTTAATTAA + +4 cisbp__M5733-acj6-vvl 6 0.958859 23447 1 6 CACCTG TATGCATAAATTA + +4 jaspar__MA0485.1-cad-eve 7 0.958859 23447 1 6 CACCTG GGCCATAAATCAC + +4 taipale__Alx4_DBD_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.958859 23447 1 6 CACCTG ATAATTAAATTAA + +4 taipale__POU3F2_DBD_NWTGMATAAWTNA-vvl 6 0.958859 23447 1 6 CACCTG TATGCATAAATTA + +4 transfac_pro__M07721-fd59A-fkh-Sox21a-SoxN 7 0.958859 23447 1 6 CACCTG AAACAATAATATT + +4 cisbp__M5291-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.958859 23447 1 6 CACCTG TTAATTAAATTAA - +4 cisbp__M5983-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-hbn-Lmx1a-OdsH-Optix-repo-Traf4-unc-4 1 0.958859 23447 1 6 CACCTG TTAATTTAATTAG - +4 cisbp__M6107-al-bsh-C15-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-Lim3-OdsH-Optix-otp-repo-ro-Rx-Traf4-unc-4-Vsx2 1 0.958859 23447 1 6 CACCTG CTAATTAAATTAA - +4 swissregulon__hs__NKX6-1_2.p2-HGTX 0 0.958859 23447 1 6 CACCTG AACCAATTAAAAA - +4 taipale__Alx1_DBD_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-hbn-Lmx1a-OdsH-Optix-repo-Traf4-unc-4 1 0.958859 23447 1 6 CACCTG TTAATTTAATTAG - +4 taipale__Uncx_DBD_NTAATYTAATTAN-al-bsh-C15-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-Lim3-OdsH-Optix-otp-repo-Rx-Traf4-unc-4-Vsx2 1 0.958859 23447 1 6 CACCTG CTAATTAAATTAA - +4 cisbp__M0844 8 0.958859 23447 1 5 CACCTG TAATAATATATTT + +4 cisbp__M4737-Antp 1 0.958904 23448.1 1 5 CACCTG ATAATT + +4 hdpi__CPSF4-Clp 2 0.958904 23448.1 1 4 CACCTG TTTTCC - +4 hdpi__NFIL3-vri -4 0.958904 23448.1 1 2 CACCTG TTCAAT - +4 tfdimers__MD00357-E2f1-zfh1 3 0.958967 23449.6 1 6 CACCTG TTTTTTGTTTCTGTTTCTTTTTTT + +4 tfdimers__MD00483 2 0.958967 23449.6 1 6 CACCTG GGCCGCCGCGCGCGCGCGGGGGCG - +4 tfdimers__MD00237-sd 20 0.959125 23453.5 1 6 CACCTG TCTTAGAGATGCTAATGACCCACTATT + +4 flyfactorsurvey__BH2_SOLEXA_FBgn0004854-B-H1-B-H2-Hmx-OdsH-inv 2 0.959141 23453.9 1 6 CACCTG GTTAATTG + +4 flyfactorsurvey__C15_Cell_FBgn0004863-C15-OdsH-Ubx-inv 2 0.959141 23453.9 1 6 CACCTG GTTAATTA + +4 flyfactorsurvey__Dfd_FlyReg_FBgn0000439-Antp-CG32532-Dfd-Dll-E5-HGTX-Scr-Ubx-ap-bsh-en-exex-ftz-hbn-lab-lms-repo-slou-unpg-zen2 1 0.959141 23453.9 1 6 CACCTG TTAATTAT + +4 taipale_cyt_meth__DLX1_NYAATTAN_eDBD_meth-Dll 1 0.959141 23453.9 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__DLX3_NYAATTAN_FL-Dll 1 0.959141 23453.9 1 6 CACCTG GTAATTAC + +4 taipale_cyt_meth__EN2_NYAATTAN_eDBD_meth-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dll-Dr-E5-ems-en-eve-exex-inv-lbe-Lim3-lms-OdsH-pb-Pph13-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.959141 23453.9 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__HOXC8_NTAATTAN_FL-abd-A-Ubx 1 0.959141 23453.9 1 6 CACCTG GTAATTAC + +4 transfac_pro__M02051-Antp-Dll-eve-exex-lab-Scr 1 0.959141 23453.9 1 6 CACCTG ATAATTAC + +4 cisbp__M5160-Pph13 0 0.959141 23453.9 1 6 CACCTG TAATTAGT - +4 flyfactorsurvey__Pph13_Cell_FBgn0023489-Pph13 0 0.959141 23453.9 1 6 CACCTG TAATTAGT - +4 cisbp__M2215 3 0.959141 23453.9 1 5 CACCTG TCCCGCCG + +4 cisbp__M6168-cad 3 0.959141 23453.9 1 5 CACCTG ATTTATGG - +4 jaspar__MA0410.1 3 0.959141 23453.9 1 5 CACCTG TCCCGCCG - +4 transfac_pro__M00716 3 0.959141 23453.9 1 5 CACCTG CCGCGCGC - +4 cisbp__M0047 4 0.959141 23453.9 1 4 CACCTG AATTTCCC + +4 cisbp__M4957-abd-A-al-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-CG34367-CG9876-Dfd-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen-zen2-zf -2 0.959141 23453.9 1 4 CACCTG GTTAATTA + +4 elemento__CGTTTCCG -2 0.959141 23453.9 1 4 CACCTG CGTTTCCG + +4 flyfactorsurvey__Tup_Cell_FBgn0003896-tup -2 0.959141 23453.9 1 4 CACCTG CTTAATTG + +4 flyfactorsurvey__ems_FlyReg_FBgn0000576-ems 4 0.959141 23453.9 1 4 CACCTG TAATGACA + +4 predrem__nrMotif2629 4 0.959141 23453.9 1 4 CACCTG TATTGACA + +4 taipale_cyt_meth__PITX2_YTAATCCN_FL_meth-Gsc-oc-Ptx1 4 0.959141 23453.9 1 4 CACCTG CTAATCCC + +4 cisbp__M4955-ap-Awh-bsh-btn-CG18599-E5-ems-en-eve-ftz-ind-nub-pb-pdm2-Scr-zen-zen2 4 0.959141 23453.9 1 4 CACCTG TCATTAGC - +4 cisbp__M5174-abd-A-al-ap-Awh-CG11085-CG18599-CG32532-CG9876-Dll-E5-ems-en-eve-inv-lab-lbl-Lim1-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Ubx-unpg-Vsx1-zfh2 4 0.959141 23453.9 1 4 CACCTG TAATTAGC - +4 flyfactorsurvey__Eve_Cell_FBgn0000606-Awh-CG18599-E5-Scr-ap-bsh-btn-ems-en-eve-ftz-ind-lbl-pb-zen-zen2 4 0.959141 23453.9 1 4 CACCTG TCATTAGC - +4 flyfactorsurvey__Eve_SOLEXA_FBgn0000606-Antp-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-al-ap-bsh-btn-ems-en-eve-ftz-hbn-ind-inv-lab-lbe-lbl-otp-pb-re 4 0.959141 23453.9 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__Lbl_SOLEXA_FBgn0008651-Awh-CG9876-CG11294-CG18599-CG32532-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Ubx-abd-A-ap-bsh-ems-en-eve-hbn-inv-lab-lbe-lbl-otp-pb-ro-unpg-zen2 4 0.959141 23453.9 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__Rx_Cell_FBgn0020617-Awh-CG9876-CG11085-CG18599-CG32532-Dll-E5-Lim1-Lim3-OdsH-Pph13-Rx-Ubx-Vsx1-abd-A-al-ap-ems-en-eve-inv-lab-lbl-otp-pb-repo-ro-slou-unpg-zfh2 4 0.959141 23453.9 1 4 CACCTG TAATTAGC - +4 predrem__nrMotif1093 4 0.959141 23453.9 1 4 CACCTG TTAAGACT - +4 predrem__nrMotif1351 4 0.959141 23453.9 1 4 CACCTG TTTAGACA - +4 cisbp__M6043-al-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-exex-inv-lab-lbe-Lim3-OdsH-Pph13-repo-unc-4-unpg -3 0.959141 23453.9 1 3 CACCTG CTAATTAG + +4 taipale__NKX6-2_DBD_NYMATTAN-abd-A-acj6-Antp-bsh-btn-C15-CG34367-CG4328-Dbx-en-exex-ftz-hbn-HGTX-ind-inv-lab-lbe-lbl-Lim1-lms-Lmx1a-Scr-slou-Ubx-Vsx2 5 0.959141 23453.9 1 3 CACCTG CTAATTAA + +4 taipale__Nkx6-1_DBD_NYMATTAN-abd-A-Antp-btn-Dbx-Dll-en-exex-ftz-HGTX-inv-lab-Lim1-lms-Scr-Ubx 5 0.959141 23453.9 1 3 CACCTG GTAATTAA + +4 taipale_cyt_meth__ISX_CTAATTAN_eDBD_meth-al-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-toy-unc-4-unpg-Vsx1-Vsx2-zen2-zfh2 -3 0.959141 23453.9 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__LMX1A_YTAATTAN_eDBD-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-E5-ems-en-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-zen2 5 0.959141 23453.9 1 3 CACCTG TTAATTAA + +4 taipale_cyt_meth__MNX1_NYAATTAN_eDBD-Antp-Awh-bsh-btn-Dfd-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim3-pb-Scr-slou-unpg 5 0.959141 23453.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__NKX6-2_NYAATTAN_eDBD-abd-A-Dll-exex-ftz-HGTX-Ubx 5 0.959141 23453.9 1 3 CACCTG GTAATTAA + +4 taipale_cyt_meth__VAX1_NYAATTAN_eDBD-al-Antp-Awh-bsh-btn-C15-CG11294-CG18599-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-Lmx1a-OdsH-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 5 0.959141 23453.9 1 3 CACCTG GTAATTAG + +4 taipale_cyt_meth__VAX2_NYAATTAN_FL_meth-Antp-Awh-bsh-btn-C15-CG18599-CG9876-Dfd-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-OdsH-pb-pdm3-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 5 0.959141 23453.9 1 3 CACCTG CTAATTAG + +4 transfac_pro__M01267-Jra-kay-Mef2-Myc-nej-Stat92E -3 0.959141 23453.9 1 3 CACCTG ATGACTCA - +4 transfac_pro__M03869-cnc-GATAe-grn-Jra-kay-Mef2-mor-Myc-nej-pan-pnr -3 0.959141 23453.9 1 3 CACCTG ATGAGTCA - +4 flyfactorsurvey__lola-PT_SANGER_5_FBgn0005630-lola 6 0.959141 23453.9 1 2 CACCTG GCTCAATA + +4 cisbp__M5091-lola 6 0.959141 23453.9 1 2 CACCTG GCTCAACA - +4 tfdimers__MD00100-foxo-slp2-Sox100B 3 0.959283 23457.3 1 6 CACCTG TTTTTTTTGTTTTCTTTGTCTTTTT + +4 hdpi__NRL -1 0.959473 23462 1 5 CACCTG TCCGC - +4 swissregulon__hs__FOXN1.p2-jumu 5 0.959507 23462.8 1 6 CACCTG AGCGACGCTAT + +4 swissregulon__hs__POU6F1.p2-pdm3-vvl 3 0.959507 23462.8 1 6 CACCTG GCATAATTTAT + +4 taipale_cyt_meth__POU2F2_NTATGCWAATN_eDBD_meth-nub-pdm2-SoxN-vvl 5 0.959507 23462.8 1 6 CACCTG TTATGCAAATT + +4 transfac_pro__M05468 5 0.959507 23462.8 1 6 CACCTG CATTACGCATA + +4 cisbp__M2331 4 0.959507 23462.8 1 6 CACCTG TTTTCACTTTT - +4 cisbp__M6027-abd-A-Abd-B-Antp-cad-Dbx-eve-HGTX-Scr-Ubx 1 0.959507 23462.8 1 6 CACCTG GGCCATAAAAT - +4 flyfactorsurvey__hb_SOLEXA_5_FBgn0001180-hb-jim 5 0.959507 23462.8 1 6 CACCTG TAAAAAACAAA - +4 flyfactorsurvey__jim_F1-4_SOLEXA_2.5-hb-jim 5 0.959507 23462.8 1 6 CACCTG TAAAAAACAAA - +4 predrem__nrMotif190 0 0.959507 23462.8 1 6 CACCTG AAACCAAAAAA - +4 taipale_cyt_meth__MIXL1_TAATYNRATTA_FL-al-CG11294-CG32532-Drgx-OdsH-repo-Traf4-unc-4 1 0.959507 23462.8 1 6 CACCTG TAATTGAATTA - +4 transfac_pro__M07813-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-nej-OdsH-Optix-repo-Traf4-unc-4 0 0.959507 23462.8 1 6 CACCTG TAATTGAATTA - +4 flyfactorsurvey__sens2_SOLEXA_FBgn0051632-sens-sens-2 -1 0.959507 23462.8 1 5 CACCTG TGCTGTGATTT + +4 transfac_pro__M03888-Sox102F -1 0.959507 23462.8 1 5 CACCTG GCTTTTGTCTA - +4 cisbp__M5320 2 0.959508 23462.9 1 6 CACCTG CCCGCATACAACGAA + +4 transfac_pro__M01124-SoxN 3 0.959508 23462.9 1 6 CACCTG ATTGTCATGCTAATG + +4 c2h2_zfs__M4297-pho-phol 6 0.959508 23462.9 1 6 CACCTG GGCCGCCATTTTGTT - +4 cisbp__M2340 9 0.959508 23462.9 1 6 CACCTG AATTGTCATCATTTT - +4 flyfactorsurvey__CG5669_SANGER_10_FBgn0039169-CG3065-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-cbt-dar1-kay-luna 9 0.959508 23462.9 1 6 CACCTG TTGGCCCCGCCCCCT - +4 hocomoco__SMCA5_HUMAN.H11MO.0.C-Iswi-crol-nub-pdm2 3 0.959508 23462.9 1 6 CACCTG GATTCCATTCCATTC - +4 transfac_pro__M02743-E2f1 6 0.959508 23462.9 1 6 CACCTG ATCGCGCGCCCTTAT - +4 transfac_pro__M09153 10 0.959508 23462.9 1 5 CACCTG TCGTCATCGTTTTCG + +4 transfac_pro__M07870-ey-Poxm-sv-toy 11 0.959508 23462.9 1 4 CACCTG CAGTCATGCGTGACG - +4 predrem__nrMotif2636 0 0.959594 23465 1 6 CACCTG CCCCAGCCCGCGGC + +4 transfac_pro__M05129 4 0.959594 23465 1 6 CACCTG GGCATATTTATTGC + +4 transfac_pro__M05830 0 0.959594 23465 1 6 CACCTG CAGCGGCGCCGCCG + +4 cisbp__M5353-E2f1-E2f2 6 0.959594 23465 1 6 CACCTG AAATGGCGCCATTT - +4 taipale_cyt_meth__ATF4_GGATGAYGTCATCC_FL-Atf-2-Atf3-Atf6-CG44247-crc-CrebA-CrebB-Jra-kay-Xbp1 9 0.959594 23465 1 5 CACCTG GGATGACGTCATCC + +4 cisbp__M5740-acj6-vvl -2 0.959594 23465 1 4 CACCTG CATTAATTATTCAT - +4 dbcorrdb__PAX5__ENCSR000BJI_1__m1-ey-Poxm-sv-toy 5 0.959822 23470.5 1 6 CACCTG GGGGGCAGCGGAGCGTGACC + +4 dbcorrdb__POLR2AphosphoS5__ENCSR000BOV_1__m4-RpII215 9 0.959822 23470.5 1 6 CACCTG CGTTTGCGGAGCGCGAGGGT + +4 jaspar__MA0346.1-Tbp 2 0.959822 23470.5 1 6 CACCTG TTTATTTATATATAATATGA + +4 transfac_pro__M01504-Tbp 2 0.959822 23470.5 1 6 CACCTG TTTATTTATATATAATATGA + +4 dbcorrdb__E2F4__ENCSR000DYY_1__m1-Dp-E2f1-E2f2-Sin3A 14 0.959822 23470.5 1 6 CACCTG GGGGCGCGAAATTTGAAAGG - +4 dbcorrdb__NRF1__ENCSR000ECC_1__m1-E2f1-ewg-RpII215 0 0.959822 23470.5 1 6 CACCTG CCCCACTGCGCATGCGCAGG - +4 flyfactorsurvey__ey_FlyReg_FBgn0005558-ey 6 0.960325 23482.8 1 6 CACCTG CCCACTCACTCGGCAAAA + +4 transfac_pro__M00802 2 0.960325 23482.8 1 6 CACCTG AATTCATAATTATACACA + +4 transfac_pro__M05612-crol 0 0.960325 23482.8 1 6 CACCTG TCCCTCCCCATTCCAGCC - +4 swissregulon__hs__ALX1.p2 -1 0.960325 23482.8 1 5 CACCTG AATTAATTATCATTATCT + +4 cisbp__M2052-abd-A-al-Antp-ap-Awh-bsh-CG11294-CG15696-CG32532-CG34367-CG9876-Dfd-Dll-Dr-E5-ems-en-exex-ftz-hbn-HGTX-ind-inv-lab-Lim1-lms-NK7.1-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-tup-Ubx-unc-4-un 1 0.960356 23483.6 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__E5_SOLEXA_FBgn0008646-Antp-Awh-C15-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-HGTX-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn- 0 0.960356 23483.6 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__lola-PJ_SANGER_5_FBgn0005630-lola 0 0.960356 23483.6 1 6 CACCTG AGCATAA + +4 jaspar__MA0245.1-Antp-Awh-CG9876-CG11294-CG15696-CG32532-CG34367-Dfd-Dll-Dr-E5-HGTX-Lim1-NK7.1-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-ems-en-exex-ftz-hbn-ind-inv-lab-lms-otp-repo-ro-slo 1 0.960356 23483.6 1 6 CACCTG TTAATTG + +4 cisbp__M1993-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG4328-CG9876-E5-ems-en-eve-ind-inv-lab-Lim3-Lmx1a-OdsH-Optix-otp-pb-Pph13-repo-ro-Rx-Ubx-unc-4-unpg-Vsx1-Vsx2 0 0.960356 23483.6 1 6 CACCTG TAATTAG - +4 predrem__nrMotif617 0 0.960356 23483.6 1 6 CACCTG GAATTTG - +4 elemento__CGCATCA 2 0.960356 23483.6 1 5 CACCTG CGCATCA + +4 predrem__nrMotif531 -1 0.960356 23483.6 1 5 CACCTG TTCTCAA + +4 elemento__ACTACAA -2 0.960356 23483.6 1 4 CACCTG ACTACAA + +4 flyfactorsurvey__Achi_Cell_FBgn0033749-achi 3 0.960356 23483.6 1 4 CACCTG TTTGACA + +4 predrem__nrMotif2304 -2 0.960356 23483.6 1 4 CACCTG ACTCAAA + +4 cisbp__M4726-achi 3 0.960356 23483.6 1 4 CACCTG TTTGACA - +4 hdpi__OTUD4-CG3251-otu 3 0.960356 23483.6 1 4 CACCTG TTCGCGC - +4 transfac_public__M00100 -2 0.960356 23483.6 1 4 CACCTG CATAAAT - +4 hdpi__ZNF326 4 0.960356 23483.6 1 3 CACCTG GCCAAAC + +4 cisbp__M0667 4 0.960766 23493.6 1 6 CACCTG TACGCGCGTA + +4 homer__AATTTTAAAA_Unknown6 0 0.960766 23493.6 1 6 CACCTG AATTTTAAAA + +4 homer__CKTCKTCTTY_Unknown4 1 0.960766 23493.6 1 6 CACCTG CTTCGTCTTC + +4 predrem__nrMotif1686 4 0.960766 23493.6 1 6 CACCTG TTCTCTCATT + +4 tiffin__TIFDMEM0000115 4 0.960766 23493.6 1 6 CACCTG AAAGCTCTCT + +4 transfac_pro__M03210 3 0.960766 23493.6 1 6 CACCTG GGGCGCCATT + +4 transfac_pro__M04992 4 0.960766 23493.6 1 6 CACCTG AGGCCGCCCC + +4 transfac_pro__M05025 4 0.960766 23493.6 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05050 4 0.960766 23493.6 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05052 4 0.960766 23493.6 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05144 4 0.960766 23493.6 1 6 CACCTG ACGCCGCCCA + +4 predrem__nrMotif2658 3 0.960766 23493.6 1 6 CACCTG CCATCCCGGC - +4 transfac_pro__M03181 1 0.960766 23493.6 1 6 CACCTG TCAGCGGCAT - +4 transfac_pro__M05318-CG42741-luna 4 0.960766 23493.6 1 6 CACCTG CCCCCGCCCT - +4 transfac_pro__M05319-CG42741-luna 4 0.960766 23493.6 1 6 CACCTG CCCCCGCCCT - +4 transfac_pro__M04970 5 0.960766 23493.6 1 5 CACCTG TTGGCGGCCT - +4 transfac_pro__M04988 5 0.960766 23493.6 1 5 CACCTG TTGGCGGCCT - +4 transfac_pro__M05019 5 0.960766 23493.6 1 5 CACCTG TCGGCGGCCT - +4 transfac_pro__M05033 5 0.960766 23493.6 1 5 CACCTG TCGGCGGCCT - +4 cisbp__M0870-Antp-Awh-C15-CG9876-CG11085-CG18599-CG34367-Dfd-Dr-E5-Lim3-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-dve-ems-en-eve-ey-ind-inv-lab-lbe-otp-pb-pdm3-repo-ro-slou-toy-unc-4-unpg-vvl-zfh2 -2 0.960766 23493.6 1 4 CACCTG ACTAATTAGT + +4 cisbp__M5539 -2 0.960766 23493.6 1 4 CACCTG CCAATAAAAC + +4 idmmpmm__cad-Abd-B-cad-eve 6 0.960766 23493.6 1 4 CACCTG TTTTATGACC + +4 jaspar__MA0919.1-Antp-Awh-C15-CG9876-CG11085-CG18599-CG34367-Dfd-Dr-E5-Lim3-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-dve-ems-en-eve-ey-ind-inv-lab-lbe-otp-pb-pdm3-repo-ro-slou-toy-unc-4-unpg-vvl-zfh2 -2 0.960766 23493.6 1 4 CACCTG ACTAATTAGT + +4 predrem__nrMotif737 6 0.960766 23493.6 1 4 CACCTG AGAGAGCAAA + +4 taipale__HOXB13_DBD_CCAATAAAAN -2 0.960766 23493.6 1 4 CACCTG CCAATAAAAC + +4 transfac_pro__M03200 6 0.960766 23493.6 1 4 CACCTG ATGCCGGCCC + +4 transfac_pro__M07412-Irbp18-nej-slbo-Xrp1 6 0.960766 23493.6 1 4 CACCTG ATTGCGTAAT + +4 transfac_pro__M07413-Irbp18-nej-slbo-Xrp1 6 0.960766 23493.6 1 4 CACCTG ATTGCGCAAT + +4 cisbp__M5995-Irbp18-nej-slbo-srl-Xrp1 6 0.960766 23493.6 1 4 CACCTG ATTGCGCAAT - +4 cisbp__M6030-Abd-B-cad-eve 7 0.960766 23493.6 1 3 CACCTG TTTTTATTAC + +4 predrem__nrMotif1899 -3 0.960766 23493.6 1 3 CACCTG CTGGCCGGGG + +4 cisbp__M6158-foxo-Jra-kay-Myc-nej-NFAT-Stat92E -3 0.960766 23493.6 1 3 CACCTG ATGAGTCATA - +4 cisbp__M6292-Antp-Scr -3 0.960766 23493.6 1 3 CACCTG TTGATTAATG - +4 homer__AGCCAATCGG_NFY-CG7839-Chrac-14-E2f2-Nf-YA-Nf-YB-Nf-YC-SREBP-Spps-btd-kay -3 0.960766 23493.6 1 3 CACCTG CCGATTGGCT - +4 taipale_cyt_meth__HOXD10_GYAATAAAAN_eDBD-Abd-B-cad-eve 7 0.960766 23493.6 1 3 CACCTG GTTTTATTGC - +4 taipale_cyt_meth__HOXD9_GYAATAAAAN_FL-Abd-B-cad-eve 7 0.960766 23493.6 1 3 CACCTG GTTTTATTGC - +4 hdpi__HNRPA1-Hrb87F-Hrb98DE-Rb97D 0 0.96083 23495.2 1 6 CACCTG TTTCTGAAA + +4 predrem__nrMotif1945 1 0.96083 23495.2 1 6 CACCTG TCATCAAAA + +4 predrem__nrMotif2124 0 0.96083 23495.2 1 6 CACCTG TGTCTTTGG + +4 predrem__nrMotif2138 3 0.96083 23495.2 1 6 CACCTG TTTCACAAT + +4 predrem__nrMotif2502 0 0.96083 23495.2 1 6 CACCTG TCACTATTT + +4 predrem__nrMotif464 3 0.96083 23495.2 1 6 CACCTG AGTCACTGA + +4 predrem__nrMotif474 0 0.96083 23495.2 1 6 CACCTG TTACTGTTT + +4 scertf__spivak.MAC1 0 0.96083 23495.2 1 6 CACCTG TTTTTGCTC + +4 taipale_cyt_meth__NKX6-3_NTMATTAAN_eDBD-HGTX 0 0.96083 23495.2 1 6 CACCTG CTCATTAAA + +4 cisbp__M1904-D-Sox100B-Sox102F-Sox15-SoxN 0 0.96083 23495.2 1 6 CACCTG GAACAATGG - +4 jaspar__MA0077.1-D-Sox15-Sox100B-Sox102F-SoxN 0 0.96083 23495.2 1 6 CACCTG GAACAATGG - +4 predrem__nrMotif2349 1 0.96083 23495.2 1 6 CACCTG TTTCCATAT - +4 predrem__nrMotif522 3 0.96083 23495.2 1 6 CACCTG TGAGTCATT - +4 scertf__pachkov.STB4 3 0.96083 23495.2 1 6 CACCTG TCGGACCGA - +4 transfac_pro__M04869-E2f1-ewg 0 0.96083 23495.2 1 6 CACCTG CGCATGCGC - +4 transfac_pro__M07320 0 0.96083 23495.2 1 6 CACCTG TATTTTATT - +4 cisbp__M6038-cnc-foxo-Jra-kay-Mef2-Myc-NFAT-Stat92E 4 0.96083 23495.2 1 5 CACCTG ATGACTCAT + +4 cisbp__M6064-acj6-nub-pdm2-SoxN-Tbp-vvl -1 0.96083 23495.2 1 5 CACCTG ATTTGCATA + +4 predrem__nrMotif1296 -1 0.96083 23495.2 1 5 CACCTG CCATCAGCC + +4 predrem__nrMotif2415 4 0.96083 23495.2 1 5 CACCTG TAGTCTCTT + +4 cisbp__M6424-acj6-nub-pdm2-SoxN-Tbp-vvl 4 0.96083 23495.2 1 5 CACCTG TATGCAAAT - +4 predrem__nrMotif2166 -1 0.96083 23495.2 1 5 CACCTG ACCCAAATA - +4 taipale__Pou2f2_DBD_TATGCAAAT-acj6-nub-pdm2-SoxN-Tbp-vvl -1 0.96083 23495.2 1 5 CACCTG ATTTGCATA - +4 jaspar__MA0923.1-Antp-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Dr-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-acj6-al-ap-btn-dve-ems-en-eve-exex-ey-ind-inv-lab-lbe-lbl-lms-otp 5 0.96083 23495.2 1 4 CACCTG TTAATTAGC - +4 cisbp__M1989-al-ap-CG11294-CG32532-CG34367-CG9876-en-hbn-HGTX-ind-inv-lab-Lim1-Lim3-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-Vsx2 -3 0.96083 23495.2 1 3 CACCTG CTAATTAAA - +4 transfac_pro__M04703-Chd1-CoRest -3 0.96083 23495.2 1 3 CACCTG CTCGCGAGA - +4 tfdimers__MD00495-pan 14 0.961478 23511 1 6 CACCTG AAAAAACAAACAATTAAAAAA + +4 cisbp__M4408 2 0.961478 23511 1 6 CACCTG AATCCCTCGGGTTTTCGAAAT - +4 taipale_tf_pairs__POU2F1_FOXO6_RMATATKCNNNNNNNNNNNNNNNNRWMAACA_CAP_repr-foxo-nub-pdm2 16 0.961689 23516.2 1 6 CACCTG GAATATGCAAAACTCCAACAAAAGAACAACA + +4 taipale_cyt_meth__ONECUT2_NTATCGATCGRN_FL-onecut 5 0.962165 23527.8 1 6 CACCTG GTATCGATCGGT + +4 tiffin__TIFDMEM0000120 4 0.962165 23527.8 1 6 CACCTG CATTTGCTTAGC + +4 transfac_pro__M06967 5 0.962165 23527.8 1 6 CACCTG TGGGGAACCCCA + +4 cisbp__M4986-gl 2 0.962165 23527.8 1 6 CACCTG GAAGCCCTACAA - +4 cisbp__M6307-Blimp-1-ebi-Stat92E 5 0.962165 23527.8 1 6 CACCTG ACTTTCACTTTC - +4 hocomoco__BARX1_HUMAN.H11MO.0.D 3 0.962165 23527.8 1 6 CACCTG AAAAACAATTAG - +4 transfac_pro__M07453-cad-eve 0 0.962165 23527.8 1 6 CACCTG GCCATAAATCAT - +4 transfac_pro__M06015 7 0.962165 23527.8 1 5 CACCTG CTGGGGAGATCA + +4 transfac_pro__M05624 7 0.962165 23527.8 1 5 CACCTG GATTCAGCCCCA - +4 transfac_pro__M05656 7 0.962165 23527.8 1 5 CACCTG AAATCCCCCCCT - +4 transfac_pro__M06875-CG2120 -1 0.962165 23527.8 1 5 CACCTG TCATTTTCCAAG - +4 transfac_pro__M06971 7 0.962165 23527.8 1 5 CACCTG TGGGGGACCCCA - +4 cisbp__M5617-Mef2-rump -2 0.962165 23527.8 1 4 CACCTG ACTATAAATAGA + +4 taipale__MEF2D_DBD_NCTAWAAATAGM-Mef2-rump -2 0.962165 23527.8 1 4 CACCTG ACTATAAATAGA + +4 transfac_pro__M06979-CG16779 -2 0.962165 23527.8 1 4 CACCTG CCCGCGCATGGG + +4 transfac_pro__M05199 8 0.962165 23527.8 1 4 CACCTG ACTAAATTTAGC - +4 transfac_pro__M05911 -2 0.962165 23527.8 1 4 CACCTG CATGATTAAAGA - +4 transfac_pro__M05923-CG12605-scrt -2 0.962165 23527.8 1 4 CACCTG CCGGCTTCGGCA - +4 transfac_pro__M06677-CG2120 -2 0.962165 23527.8 1 4 CACCTG TCTTTCGGAACG - +4 transfac_public__M00160-Sox102F -2 0.962165 23527.8 1 4 CACCTG TCTATTGTTTAC - +4 cisbp__M5737-nub-pdm2-vvl -3 0.962165 23527.8 1 3 CACCTG TTGATTATTCAT + +4 homer__CTGCGCATGCGC_NRF1-E2f1-ewg -3 0.962165 23527.8 1 3 CACCTG CTGCGCATGCGC + +4 cisbp__M2337 9 0.962165 23527.8 1 3 CACCTG AGCGGCCGACAC - +4 jaspar__MA0544.1 9 0.962165 23527.8 1 3 CACCTG AGCGGCCGACAC - +4 taipale__POU3F3_DBD_WTRMATATKYAW-nub-pdm2-vvl -3 0.962165 23527.8 1 3 CACCTG ATGAATATTCAT - +4 taipale_cyt_meth__LHX6_TRATTGCAATYA_FL-Awh 10 0.962165 23527.8 1 2 CACCTG TAATTGCAATTA + +4 taipale_cyt_meth__LHX6_TRATTGCAATYA_FL_meth-Awh 10 0.962165 23527.8 1 2 CACCTG TAATTGCAATCA + +4 taipale_cyt_meth__LHX8_TRATTGCAATYA_FL_meth_repr-Awh 10 0.962165 23527.8 1 2 CACCTG TAATTGCAATTA - +4 hocomoco__GBX2_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG9876-CG18599-CG34367-Dll-Dr-E5-Lim3-OdsH-Pph13-Vsx1-Vsx2-ems-en-eve-ind-inv-lab-lbe-lms-pb-ro-unpg 8 0.962304 23531.2 1 6 CACCTG CTAATTAGCCTTTAATT + +4 taipale__SOX7_full_NATGAATKNYAKTCATN-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 11 0.962304 23531.2 1 6 CACCTG GATGAATTTCAGTCATG + +4 transfac_pro__M01393-Dr-unpg 10 0.962304 23531.2 1 6 CACCTG GAAGACCAATTAGCGCT + +4 transfac_pro__M01427-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-ind-inv-Lim3-OdsH-otp-pdm3-repo-Rx-slou-unc-4-unpg-zfh2 6 0.962304 23531.2 1 6 CACCTG TTGCACTAATTAGTGCA + +4 transfac_pro__M02866 3 0.962304 23531.2 1 6 CACCTG TGTTCCCATTGTGTACT + +4 transfac_pro__M01731 -1 0.962304 23531.2 1 5 CACCTG AACCGAGAGTTTAGCGG + +4 taipale__PAX9_DBD_SGTCACGCWTGANTGMA-ey-Poxm-sv-toy 13 0.962304 23531.2 1 4 CACCTG TGCAGTCATGCGTGACG - +4 tfdimers__MD00120-nub-pdm2-pho-phol 4 0.96268 23540.4 1 6 CACCTG CTCTTCCATTTTTATGCAAATGAAAATATA + +4 taipale_cyt_meth__KLF11_NMCACGCCCNNNNCACGCCCMC_eDBD-btd-cbt-CG3065-CG42741-dar1-Klf15-klu-luna-Sp1-Spps-sr 4 0.962724 23541.5 1 6 CACCTG GCCACGCCCACGCCACGCCCAC + +4 factorbook__EGR1-Brf-CG42741-CTCF-CoRest-ERR-E(z)-HDAC1-Klf15-Max-Nelf-E-Rbbp5-RpII215-SREBP-Spps-Spt20-brm-btd-crol-ct-klu-peb-sd-sr-tna-vtd 2 0.962724 23541.5 1 6 CACCTG CCCCCCCCCCGCCCCCGCACCC - +4 tfdimers__MD00227-Mad 5 0.963127 23551.3 1 6 CACCTG AAGAATAGCAGAGTCAGCAAAACAAAGGAAAACA - +4 cisbp__M5835-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.963649 23564.1 1 6 CACCTG AACAATGAACATTGTT - +4 taipale__SOX7_full_AACAATNNNNAKTGTT_repr-D-Sox100B-Sox15-Sox21a-Sox21b 7 0.963649 23564.1 1 6 CACCTG AACAATGAACATTGTT - +4 cisbp__M2287-cad-eve 7 0.963746 23566.5 1 6 CACCTG GGCCATAAATCAC + +4 taipale__ALX3_full_NTAATYNRATTAN-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-eve-gsb-gsb-n-hbn-Lmx1a-OdsH-Optix-prd-repo-Traf4-unc-4 1 0.963746 23566.5 1 6 CACCTG CTAATTTAATTAA + +4 cisbp__M5984-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 1 0.963746 23566.5 1 6 CACCTG ATAATTAAATTAA - +4 hocomoco__PO6F1_HUMAN.H11MO.0.D-pdm3-vvl 0 0.963746 23566.5 1 6 CACCTG TGCATAAATTATG - +4 stark__GYATGMGWAATKA 6 0.963746 23566.5 1 6 CACCTG TAATTACGCATAC - +4 taipale_tf_pairs__POU2F1_TBX21_NTATKCAGYGTNA_CAP-nub-pdm2 1 0.963746 23566.5 1 6 CACCTG TAACACTGAATAT - +4 stark__TTAATT-Antp 1 0.96384 23568.8 1 5 CACCTG TTAATT + +4 transfac_pro__M02087-cad 2 0.96384 23568.8 1 4 CACCTG TTTATA + +4 hdpi__ODC1-Odc1-Odc2 3 0.96384 23568.8 1 3 CACCTG CGCCGC - +4 cisbp__M2532-bcd-Gsc-oc 2 0.96408 23574.7 1 6 CACCTG TTAATCCC + +4 cisbp__M4908-Antp-ap-bsh-CG32532-Dfd-Dll-E5-en-exex-lab-lms-Scr-slou-Ubx-unpg-zen2 1 0.96408 23574.7 1 6 CACCTG TTAATTAT + +4 jaspar__MA0915.1-dve 2 0.96408 23574.7 1 6 CACCTG CTAATCCG + +4 predrem__nrMotif1634 1 0.96408 23574.7 1 6 CACCTG GACTCTGG + +4 predrem__nrMotif1947 1 0.96408 23574.7 1 6 CACCTG TTACAATG + +4 taipale__Lhx4_DBD_NTAATTAN-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-E5-ems-en-ey-gsb-gsb-n-lab-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-toy-Traf4-unc-4-u 1 0.96408 23574.7 1 6 CACCTG TTAATTAA + +4 taipale_cyt_meth__HOXD4_NTMATTAN_FL_meth-Antp-Dfd-E5-ems-eve-ind-pb-Scr-Ubx-zen-zen2 0 0.96408 23574.7 1 6 CACCTG GTCATTAG + +4 cisbp__M4960-exd 1 0.96408 23574.7 1 6 CACCTG ATATCAAA - +4 flyfactorsurvey__exd_SOLEXA_2_FBgn0000611-exd 1 0.96408 23574.7 1 6 CACCTG ATATCAAA - +4 predrem__nrMotif1488 3 0.96408 23574.7 1 5 CACCTG TGAGAATT + +4 yetfasco__YDL170W_486 3 0.96408 23574.7 1 5 CACCTG TCCCGCCG + +4 swissregulon__sacCer__UGA3 3 0.96408 23574.7 1 5 CACCTG TCCCGCCG - +4 transfac_pro__M01622 3 0.96408 23574.7 1 5 CACCTG TCCCGCCG - +4 cisbp__M4964-croc-FoxL1 4 0.96408 23574.7 1 4 CACCTG TATAAACA + +4 cisbp__M5252-tup -2 0.96408 23574.7 1 4 CACCTG CTTAATTG + +4 elemento__CAACAACA-Aef1 4 0.96408 23574.7 1 4 CACCTG CAACAACA + +4 flyfactorsurvey__fd64A_SANGER_5_FBgn0004895-FoxL1-croc 4 0.96408 23574.7 1 4 CACCTG TATAAACA + +4 jaspar__MA1051.1-Hcf 4 0.96408 23574.7 1 4 CACCTG GCGCCGCC + +4 transfac_pro__M00438 -2 0.96408 23574.7 1 4 CACCTG CTTGTCTC + +4 cisbp__M5008-Dbx-ems-HGTX-lab 4 0.96408 23574.7 1 4 CACCTG TAATTAAA - +4 cisbp__M5145-abd-A-Antp-ap-Awh-bsh-btn-CG18599-E5-ems-en-eve-ftz-hbn-ind-lab-lbl-Lim3-nub-otp-pb-pdm2-ro-Scr-Vsx2-zen-zen2 4 0.96408 23574.7 1 4 CACCTG TAATTAAC - +4 elemento__CAAGAAGC -2 0.96408 23574.7 1 4 CACCTG GCTTCTTG - +4 flyfactorsurvey__AbdA_SOLEXA_FBgn0000014-Antp-C15-CG18599-Dbx-E5-Scr-Ubx-abd-A-ap-bsh-btn-ems-ftz-lab-pb-zen2 4 0.96408 23574.7 1 4 CACCTG TCATTAAA - +4 flyfactorsurvey__CG12361_SOLEXA_FBgn0250756-Abd-B-Antp-CG4328-Dbx-H2.0-HGTX-Lmx1a-Scr-Ubx-abd-A-bsh-cad-ems-exex-lab-zen2 4 0.96408 23574.7 1 4 CACCTG TAATTAAA - +4 flyfactorsurvey__Pb_Cell_FBgn0051481-Antp-Awh-CG18599-E5-Lim3-Scr-Vsx2-abd-A-ap-bsh-btn-ems-en-eve-ftz-hbn-ind-lab-lbl-nub-otp-pb-pdm2-pdm3-ro-zen-zen2 4 0.96408 23574.7 1 4 CACCTG TAATTAAC - +4 taipale_cyt_meth__HOXA4_RTMATTAN_eDBD-Dfd-ind-Scr-Ubx-zen 5 0.96408 23574.7 1 3 CACCTG GTCATTAG + +4 taipale__NKX6-1_full_NYMATTAN-abd-A-Antp-ap-bsh-btn-Dbx-E5-exex-ftz-HGTX-ind-inv-lab-Lim1-lms-Scr-Ubx-zen2 5 0.96408 23574.7 1 3 CACCTG TTAATTAC - +4 taipale_cyt_meth__HOXD3_RTCGTTAN_FL_meth-btn-Dfd-eve-exex-pb 5 0.96408 23574.7 1 3 CACCTG CTAATGAC - +4 taipale_cyt_meth__LHX4_NTAATTAN_FL_meth-al-Antp-ap-Awh-C15-CG11085-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-E5-ems-en-exex-ey-gsb-gsb-n-ind-inv-lab-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-pdm3-P 5 0.96408 23574.7 1 3 CACCTG TTAATTAA - +4 yetfasco__YEL009C_1363-Jra-Mef2-Myc-NFAT-Stat92E-cnc-kay-maf-S-mor-nej-pan 5 0.96408 23574.7 1 3 CACCTG TGAGTCAT - +4 tfdimers__MD00052-pho-phol-sens-2 18 0.964199 23577.6 1 6 CACCTG TTTTTCTAAATCCCATCTTTTTAT + +4 transfac_pro__M04892-bi-egg-Hcf-mor-Six4 7 0.964199 23577.6 1 6 CACCTG ACTACAATTCCCAGAATGCCCCGC - +4 transfac_pro__M00329-sv 20 0.964199 23577.6 1 4 CACCTG GATACGCAGCGATGCGTGGCCACC + +4 cisbp__M5659-cnc-Jra-kay-nej 5 0.964362 23581.5 1 6 CACCTG CATGACTCATC + +4 predrem__nrMotif2040 1 0.964362 23581.5 1 6 CACCTG TTCACTGATAA + +4 taipale__Hoxa11_DBD_NGYAATWAAAN-abd-A-Abd-B-Antp-cad-Dbx-eve-Scr-Ubx 1 0.964362 23581.5 1 6 CACCTG GGCCATAAAAT + +4 taipale__NFE2_DBD_NATGASTCATN-cnc-Jra-kay-nej 5 0.964362 23581.5 1 6 CACCTG CATGACTCATC + +4 transfac_pro__M07835-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-eve-hbn-OdsH-Optix-repo-Traf4-unc-4 0 0.964362 23581.5 1 6 CACCTG TAATTAAATTA + +4 transfac_pro__M09241 4 0.964362 23581.5 1 6 CACCTG TCAATAATTAA + +4 transfac_pro__M09246 4 0.964362 23581.5 1 6 CACCTG GCATTAAATGC + +4 transfac_public__M00465-pdm3-vvl 3 0.964362 23581.5 1 6 CACCTG GCATAATTTAT + +4 cisbp__M5002-hb-jim 5 0.964362 23581.5 1 6 CACCTG TAAAAAACAAA - +4 cisbp__M6262-sens-sens-2 4 0.964362 23581.5 1 6 CACCTG AAATCACTGCA - +4 jaspar__MA0462.1-GATAe-Jra-MTA1-like-Mef2-NFAT-Stat92E-foxo-grn-kay-nej-pnr 5 0.964362 23581.5 1 6 CACCTG TGAGTCATTTC - +4 jaspar__MA0537.1 4 0.964362 23581.5 1 6 CACCTG TTTTCACTTTT - +4 taipale_cyt_meth__LMX1B_NWWYTAATTAN_FL-CG11294-CG4328-Drgx-hbn-Lmx1a-repo-Traf4 5 0.964362 23581.5 1 6 CACCTG TTAATTAAAAT - +4 transfac_pro__M08811-FoxL1 1 0.964362 23581.5 1 6 CACCTG TTGTTTTGACT - +4 transfac_pro__M09209 6 0.964362 23581.5 1 5 CACCTG AGAATATTCTA + +4 cisbp__M5550-abd-A-Abd-B-cad-eve-Ubx 7 0.964362 23581.5 1 4 CACCTG TTTTTATTGCT + +4 taipale_cyt_meth__CDX4_NGYAATAAAAN_FL_meth-Abd-B-cad-eve 7 0.964362 23581.5 1 4 CACCTG GGCAATAAAAC + +4 taipale__HOXC11_full_NGYAATWAAAN-abd-A-Abd-B-cad-eve-Ubx 7 0.964362 23581.5 1 4 CACCTG TTTTTATTGCT - +4 tiffin__TIFDMEM0000025 7 0.964362 23581.5 1 4 CACCTG TTATGAAAAAC - +4 transfac_pro__M05411 -2 0.964362 23581.5 1 4 CACCTG TCTTTATTATT - +4 transfac_pro__M06308 -2 0.964362 23581.5 1 4 CACCTG TCTTTTTATGC - +4 transfac_pro__M00724-bin-croc-fd59A-fkh-foxo-nej 9 0.964362 23581.5 1 2 CACCTG AAAAACAAACA - +4 cisbp__M3733 0 0.964371 23581.8 1 6 CACCTG CACATCAATCAAATT + +4 cisbp__M5812-Sox100B-Sox14-Sox15 2 0.964371 23581.8 1 6 CACCTG ATCAATTGCAGTGAT + +4 cisbp__M5843-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.964371 23581.8 1 6 CACCTG AACAATTGCAGTGTT + +4 taipale__SOX10_full_ATCAATTGCAGTGAT-Sox100B-Sox14-Sox15 2 0.964371 23581.8 1 6 CACCTG ATCAATTGCAGTGAT + +4 taipale__SOX8_full_AACAATKNYAGTGTT-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.964371 23581.8 1 6 CACCTG AACAATTGCAGTGTT + +4 taipale__Sox17_DBD_AACAATNNCATTGTT_repr-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.964371 23581.8 1 6 CACCTG AACAATTGCATTGTT + +4 transfac_public__M00124 0 0.964371 23581.8 1 6 CACCTG CACATCAATCAAATT + +4 cisbp__M5508-al-Antp-CG34367-Dfd-Dr-en-ind-inv-lbe-lms-OdsH-repo-Scr-unc-4-unpg 1 0.964371 23581.8 1 6 CACCTG TTAATTGCCAATTAA - +4 transfac_pro__M09066-Taf1 9 0.964371 23581.8 1 6 CACCTG CTCCGCCGCCGCCAC - +4 transfac_pro__M09082-Adf1-Taf1 7 0.964371 23581.8 1 6 CACCTG CCGCCGCCGCCGCCG - +4 cisbp__M1966-cnc-Jra-kay-maf-S -1 0.964371 23581.8 1 5 CACCTG TGCTGAGTCATGCTG - +4 homer__CCATTGTATGCAAAT_Oct4_Sox17-Sox15-nub-pdm2-vvl -1 0.964371 23581.8 1 5 CACCTG ATTTGCATACAATGG - +4 transfac_pro__M09417 10 0.964371 23581.8 1 5 CACCTG TCCGAAAAGCCAAAT - +4 flyfactorsurvey__CG4360-F1-3_SOLEXA_FBgn0038787-Aef1-CG4360 11 0.964371 23581.8 1 4 CACCTG AACTACAACAACAAC - +4 tfdimers__MD00276-Stat92E 13 0.964422 23583 1 6 CACCTG TTTTTTTCACTTTTTCTTTCTTTTTTT + +4 transfac_pro__M02744-btd-klu-Spps-sr 8 0.964436 23583.3 1 6 CACCTG TCCGCCCCCGCATT + +4 transfac_pro__M07752-tHMG2 8 0.964436 23583.3 1 6 CACCTG ATGGATTGCAGCAT + +4 transfac_pro__M08186-Mef2 5 0.964436 23583.3 1 6 CACCTG CTTTCTATTTTTGG + +4 cisbp__M5352-brk-E2f1-E2f2 6 0.964436 23583.3 1 6 CACCTG TTTTGGCGCCAAAA - +4 cisbp__M5988-Jra-nej 8 0.964436 23583.3 1 6 CACCTG GATTGCATCATCCT - +4 taipale__Atf4_DBD_NGGATGATGCAATM_repr-Jra-nej 8 0.964436 23583.3 1 6 CACCTG GATTGCATCATCCT - +4 transfac_pro__M07045-Blimp-1-Stat92E 5 0.964436 23583.3 1 6 CACCTG ACTTTCACTTTCCT - +4 transfac_pro__M09204 7 0.964436 23583.3 1 6 CACCTG AAGAATATTCCTTT - +4 taipale__FOXD2_DBD_NRNWAAYRTTKNYN-croc-fd59A-fkh 10 0.964436 23583.3 1 4 CACCTG AAAAAATATTTACT + +4 cisbp__M5445-croc-fd59A-fkh 10 0.964436 23583.3 1 4 CACCTG AAAAAATATTTACT - +4 cisbp__M5447-croc-fd59A-fd96Ca-fd96Cb-fkh 10 0.964436 23583.3 1 4 CACCTG AGTTAATATTTACT - +4 taipale_cyt_meth__YY1_NGCSGCCATYTTGN_FL_meth-pho-phol 10 0.964436 23583.3 1 4 CACCTG CCAAAATGGCCGCC - +4 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNNNNNCAATTN_eDBD_repr-C15 6 0.964512 23585.2 1 6 CACCTG TAATTGCCGCGATTAAGAGCAATTA + +4 tfdimers__MD00430-foxo-pan-slp2 3 0.964512 23585.2 1 6 CACCTG ATTTTTTTGTTTGCTTTTAATTTTT + +4 tfdimers__MD00288 1 0.964512 23585.2 1 6 CACCTG TCATATCTATTGTGTAATTTTTTAT - +4 dbcorrdb__BRF2__ENCSR000DNV_1__m2-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-dar1-E2f1-ERR-E(z)-HDAC1-Hr78-kay-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-tna-vtd 11 0.964804 23592.4 1 6 CACCTG GGGCCCCCCCCCCCCCCCCC + +4 dbcorrdb__POLR2AphosphoS2__ENCSR000EDX_1__m3-RpII215 1 0.964804 23592.4 1 6 CACCTG GTTTATCGCGCGGCGCGCGC + +4 dbcorrdb__YY1__ENCSR000BMH_1__m1-CG10431-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 14 0.964804 23592.4 1 6 CACCTG GCCAAGATGGCGGCCGCGGG + +4 factorbook__E2F4-E2f1-E2f2-Sin3A 5 0.964804 23592.4 1 6 CACCTG CTTTCAAATTTCCCGCCCCC + +4 dbcorrdb__GTF2B__ENCSR000DOE_1__m3-TfIIB 11 0.964804 23592.4 1 6 CACCTG CGGCGCGTCGGCGCCATAAG - +4 dbcorrdb__POLR2A__ENCSR000DKM_1__m2-RpII215 14 0.964804 23592.4 1 6 CACCTG GGCGCGCGCGCCGCCGCGAC - +4 dbcorrdb__YY1__ENCSR000BNX_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 0 0.964804 23592.4 1 6 CACCTG CCGCGGCCGCCATCTTGGCC - +4 dbcorrdb__ZNF384__ENCSR000DYP_1__m1-brm-CG7839-jim-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 0 0.964804 23592.4 1 6 CACCTG GACTTTTTTTTTTTTTTTTT - +4 taipale_cyt_meth__IRF3_NSGAAANSGAAASSGAAASN_FL_repr-Stat92E 15 0.964804 23592.4 1 5 CACCTG AGTTTCGGTTTCCGTTTCCT - +4 cisbp__M1984-al-Antp-ap-B-H1-B-H2-CG11085-CG15696-CG32532-CG34031-CG34367-Dr-E5-en-inv-lms-NK7.1-OdsH-otp-PHDP-Pph13-repo-Rx-Scr-slou-tup-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.965159 23601 1 6 CACCTG TTAATTG + +4 cisbp__M5171-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-E5-ems-en-eve-exex-ey-ftz-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-PHDP-Pph13-repo-ro-Rx-Scr-slo 1 0.965159 23601 1 6 CACCTG TTAATTA + +4 cisbp__M5197-abd-A-al-Antp-ap-Awh-bsh-C15-CG11294-CG15696-CG32532-CG34031-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ftz-hbn-ind-inv-lab-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro- 1 0.965159 23601 1 6 CACCTG TTAATTA + +4 elemento__CACGCGA 0 0.965159 23601 1 6 CACCTG CACGCGA + +4 elemento__CACGCGC 0 0.965159 23601 1 6 CACCTG CACGCGC + +4 flyfactorsurvey__Slou_SOLEXA_FBgn0002941-Antp-Awh-C15-CG4328-CG9876-CG11294-CG15696-CG32532-CG34031-CG34367-Dfd-Dll-Dr-E5-HGTX-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al 1 0.965159 23601 1 6 CACCTG TTAATTA + +4 jaspar__MA0175.1-Antp-B-H1-B-H2-CG11085-CG15696-CG32532-CG34031-CG34367-Dr-E5-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-al-ap-en-inv-lms-otp-repo-slou-tup-unc-4-unpg 1 0.965159 23601 1 6 CACCTG TTAATTG + +4 predrem__nrMotif1859 0 0.965159 23601 1 6 CACCTG TGCATAA + +4 cisbp__M5086-lola 0 0.965159 23601 1 6 CACCTG AGCATAA - +4 elemento__CGCGTGC 1 0.965159 23601 1 6 CACCTG GCACGCG - +4 elemento__CGGATGC 1 0.965159 23601 1 6 CACCTG GCATCCG - +4 hdpi__GOT1-Got1 1 0.965159 23601 1 6 CACCTG CGCCATG - +4 predrem__nrMotif58 0 0.965159 23601 1 6 CACCTG TGGCTGC - +4 cisbp__M3029 2 0.965159 23601 1 5 CACCTG CATAAAT + +4 elemento__AGCCCCG 2 0.965159 23601 1 5 CACCTG AGCCCCG + +4 elemento__CACGCCC-CG3065-Sp1 2 0.965159 23601 1 5 CACCTG CACGCCC + +4 elemento__CGCAGCA 2 0.965159 23601 1 5 CACCTG CGCAGCA + +4 elemento__CGCAGCG 2 0.965159 23601 1 5 CACCTG CGCAGCG + +4 elemento__CGCCCCG 2 0.965159 23601 1 5 CACCTG CGCCCCG + +4 elemento__CGCGCCC 2 0.965159 23601 1 5 CACCTG CGCGCCC + +4 elemento__CGCGCCG 2 0.965159 23601 1 5 CACCTG CGCGCCG + +4 elemento__GCCGCCC 2 0.965159 23601 1 5 CACCTG GCCGCCC + +4 elemento__TCATGAA -1 0.965159 23601 1 5 CACCTG TCATGAA + +4 elemento__TGCGCCA 2 0.965159 23601 1 5 CACCTG TGCGCCA + +4 elemento__TGCTCCA 2 0.965159 23601 1 5 CACCTG TGCTCCA + +4 hdpi__IRF6 2 0.965159 23601 1 5 CACCTG GGAAAAT + +4 hdpi__RFX4 -1 0.965159 23601 1 5 CACCTG AAATGAA + +4 predrem__nrMotif1661 2 0.965159 23601 1 5 CACCTG CATTGCT + +4 bergman__brk-brk 2 0.965159 23601 1 5 CACCTG AGCGCCA - +4 elemento__ATCATGC -1 0.965159 23601 1 5 CACCTG GCATGAT - +4 elemento__CGCTGCA 2 0.965159 23601 1 5 CACCTG TGCAGCG - +4 elemento__CGGCGGC 2 0.965159 23601 1 5 CACCTG GCCGCCG - +4 elemento__CGGGGCC 2 0.965159 23601 1 5 CACCTG GGCCCCG - +4 elemento__CGGGGGC 2 0.965159 23601 1 5 CACCTG GCCCCCG - +4 elemento__TGGGGCC 2 0.965159 23601 1 5 CACCTG GGCCCCA - +4 elemento__TGGGGGC 2 0.965159 23601 1 5 CACCTG GCCCCCA - +4 stark__TGGCGYY-brk 2 0.965159 23601 1 5 CACCTG AACGCCA - +4 elemento__ATCGATC 3 0.965159 23601 1 4 CACCTG ATCGATC + +4 elemento__ATGGACA 3 0.965159 23601 1 4 CACCTG ATGGACA + +4 elemento__ATTGACA 3 0.965159 23601 1 4 CACCTG ATTGACA + +4 elemento__CCCCCGC -2 0.965159 23601 1 4 CACCTG CCCCCGC + +4 elemento__CCGCCAA -2 0.965159 23601 1 4 CACCTG CCGCCAA + +4 elemento__CCGCCCA -2 0.965159 23601 1 4 CACCTG CCGCCCA + +4 elemento__CCGCCCG -2 0.965159 23601 1 4 CACCTG CCGCCCG + +4 elemento__CCGCCGC -2 0.965159 23601 1 4 CACCTG CCGCCGC + +4 elemento__CCGCGGC -2 0.965159 23601 1 4 CACCTG CCGCGGC + +4 elemento__CCGCTGC -2 0.965159 23601 1 4 CACCTG CCGCTGC + +4 elemento__CCGCTTC -2 0.965159 23601 1 4 CACCTG CCGCTTC + +4 elemento__CGCGACA 3 0.965159 23601 1 4 CACCTG CGCGACA + +4 elemento__TGCGACA 3 0.965159 23601 1 4 CACCTG TGCGACA + +4 elemento__ATGGCGG-pho-phol-Taf1 -2 0.965159 23601 1 4 CACCTG CCGCCAT - +4 cisbp__M2063-Dfd-ems-eve-ind-pb-zen -3 0.965159 23601 1 3 CACCTG CTAATGA + +4 jaspar__MA0256.1-Dfd-ems-eve-ind-pb-zen -3 0.965159 23601 1 3 CACCTG CTAATGA + +4 hdpi__DDX43-CG7878 -4 0.965159 23601 1 2 CACCTG TTCCAAA + +4 transfac_pro__M03842-vvl 2 0.965186 23601.7 1 6 CACCTG ATTTCATTTGCATTTCAA + +4 transfac_pro__M05452-CG13296 4 0.965186 23601.7 1 6 CACCTG GTAATCCCGGGCTCGCAA - +4 cisbp__M0436-CG12071 4 0.965585 23611.5 1 6 CACCTG TTGTTTATTG + +4 cisbp__M3913-Sox102F 1 0.965585 23611.5 1 6 CACCTG TTAACAATAC + +4 taipale_cyt_meth__SOX14_NGAACAATGN_eDBD-D-Sox21a-Sox21b-SoxN 2 0.965585 23611.5 1 6 CACCTG CGCACAATGG + +4 transfac_pro__M03199 4 0.965585 23611.5 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05044 4 0.965585 23611.5 1 6 CACCTG ACGCCGCCAA + +4 transfac_pro__M05169 4 0.965585 23611.5 1 6 CACCTG ACGCCGCCAC + +4 cisbp__M1594-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b 3 0.965585 23611.5 1 6 CACCTG AAAAACAATG - +4 homer__TAATCAATTA_Pax7-C15-ey-gsb-gsb-n-prd-toe 0 0.965585 23611.5 1 6 CACCTG TAATTGATTA - +4 predrem__nrMotif1511 4 0.965585 23611.5 1 6 CACCTG TTTGGGGCTG - +4 stark__KYTAATKDNY-abd-A-Antp-Dfd-E5-ems-en-eve-ftz-hbn-ind-lab-pb-Scr-slou-Ubx-unpg 1 0.965585 23611.5 1 6 CACCTG AATAATTAAA - +4 taipale_cyt_meth__NFATC3_NAYGGAAAMN_eDBD_meth-NFAT 4 0.965585 23611.5 1 6 CACCTG ATTTTCCGTT - +4 homer__ATATGCAAAT_Oct2-nub-pdm2-vvl -1 0.965585 23611.5 1 5 CACCTG ATATGCAAAT + +4 predrem__nrMotif2558 -1 0.965585 23611.5 1 5 CACCTG CCCGCTGTGC + +4 homer__ATTTTCCATT_NFAT-CG5641-Jra-kay-NFAT 6 0.965585 23611.5 1 4 CACCTG ATTTTCCATT + +4 neph__UW.Motif.0060 6 0.965585 23611.5 1 4 CACCTG GCCAAAACCA + +4 predrem__nrMotif988 -2 0.965585 23611.5 1 4 CACCTG TCTTTTATTT + +4 cisbp__M0315-CG7786-gt-Irbp18-nej-Pdp1-slbo-srl-vri-Xrp1 6 0.965585 23611.5 1 4 CACCTG ATTGCGCAAT - +4 stark__YGTCWAATTA 6 0.965585 23611.5 1 4 CACCTG TAATTAGACA - +4 transfac_pro__M05170 6 0.965585 23611.5 1 4 CACCTG TATTCGGACG - +4 cisbp__M1726 -3 0.965585 23611.5 1 3 CACCTG TTTAGCGCGG + +4 predrem__nrMotif2631 -3 0.965585 23611.5 1 3 CACCTG CTGTCTGGCT - +4 taipale__Hoxc10_DBD_GYAATWAAAN-Abd-B-cad-eve 7 0.965585 23611.5 1 3 CACCTG TTTTTATTAC - +4 taipale_cyt_meth__HOXB9_GTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.965585 23611.5 1 3 CACCTG ATTTTACGAC - +4 taipale_cyt_meth__HOXC9_GYAATAAAAN_FL-Abd-B-cad-eve 7 0.965585 23611.5 1 3 CACCTG GTTTTATTGC - +4 predrem__nrMotif1225 1 0.965645 23612.9 1 6 CACCTG CCACGGGGC + +4 predrem__nrMotif153 0 0.965645 23612.9 1 6 CACCTG AAAATTAAA + +4 stark__TTCCSGGAA-Stat92E-aop 0 0.965645 23612.9 1 6 CACCTG TTCCCGGAA + +4 cisbp__M3732 -1 0.965645 23612.9 1 5 CACCTG ATCAATCAA + +4 predrem__nrMotif2653 -1 0.965645 23612.9 1 5 CACCTG CCCGCTCTG + +4 predrem__nrMotif326 -1 0.965645 23612.9 1 5 CACCTG ATTTGGAAA + +4 transfac_pro__M00734-rn-sqz 4 0.965645 23612.9 1 5 CACCTG GAAAAAATC + +4 cisbp__M0401-btd-Klf15-klu-sd-Sp1-Spps-sr 4 0.965645 23612.9 1 5 CACCTG TCCGCCCCC - +4 predrem__nrMotif1159 4 0.965645 23612.9 1 5 CACCTG AAATGGGCT - +4 predrem__nrMotif2566 4 0.965645 23612.9 1 5 CACCTG TGAGCATTT - +4 transfac_pro__M04699-cnc-maf-S-tj 4 0.965645 23612.9 1 5 CACCTG GACTCAGCA - +4 cisbp__M0344-CoRest-Jra-Myc-NFAT-Stat92E-cnc-kay-nej 6 0.965645 23612.9 1 3 CACCTG ATGACTCAT + +4 flyfactorsurvey__CG33980_Cell_FBgn0053980-CG9876-CG11294-CG32532-CG34367-HGTX-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-en-hbn-ind-inv-lab-otp-pb-repo-ro-slou-unc-4-unpg -3 0.965645 23612.9 1 3 CACCTG CTAATTAAA - +4 predrem__nrMotif461 6 0.965645 23612.9 1 3 CACCTG TTTGCTTAT - +4 tfdimers__MD00004 5 0.965788 23616.4 1 6 CACCTG AATTTTATTTGCATGACAAAGGAAAAAATTTA + +4 predrem__nrMotif50 0 0.96675 23639.9 1 6 CACCTG TTTTTTTTTTAA + +4 taipale_cyt_meth__PAX7_NTAATTGATTAN_eDBD_meth_repr-ey-gsb-gsb-n-prd-toe 1 0.96675 23639.9 1 6 CACCTG ATAATTGATTAT + +4 transfac_public__M00230 6 0.96675 23639.9 1 6 CACCTG CATTATCATCAA + +4 jaspar__MA0008.2 4 0.96675 23639.9 1 6 CACCTG GCAATAATTGAA - +4 transfac_pro__M06608 4 0.96675 23639.9 1 6 CACCTG TCCCAAGCCCCT - +4 transfac_pro__M07452 0 0.96675 23639.9 1 6 CACCTG CTCATAAATCAT - +4 transfac_public__M00248-nub-pdm2 4 0.96675 23639.9 1 6 CACCTG AATTAGCATAGA - +4 transfac_pro__M06871-CG2120 7 0.96675 23639.9 1 5 CACCTG TAATGCTAATCC + +4 transfac_pro__M06945 7 0.96675 23639.9 1 5 CACCTG TGGGCGCGCCCT - +4 cisbp__M5616-Mef2-rump -2 0.96675 23639.9 1 4 CACCTG GCTATAAATAGC + +4 transfac_pro__M06939 8 0.96675 23639.9 1 4 CACCTG TGGGCGCCCCCC + +4 transfac_pro__M06958 8 0.96675 23639.9 1 4 CACCTG TGGGCTAGCCCC + +4 cisbp__M3019-ct -2 0.96675 23639.9 1 4 CACCTG CCAATAATCGAT - +4 taipale__MEF2B_full_RCTAWAAATAGM-Mef2-rump -2 0.96675 23639.9 1 4 CACCTG GCTATTTATAGC - +4 tiffin__TIFDMEM0000005 8 0.96675 23639.9 1 4 CACCTG GTTATCGATATC - +4 tiffin__TIFDMEM0000009-Atac1 -3 0.96675 23639.9 1 3 CACCTG CTCTCTCTCTCT - +4 taipale__LHX6_full_YRATTGCAATYR_repr-Awh 10 0.96675 23639.9 1 2 CACCTG TGATTGCAATCA + +4 transfac_pro__M06344 10 0.96675 23639.9 1 2 CACCTG TGGGCAATTATA + +4 taipale_cyt_meth__LHX8_TRATTGCAATYA_FL-Awh 10 0.96675 23639.9 1 2 CACCTG TAATTGCAATTA - +4 tfdimers__MD00517 8 0.966835 23642 1 6 CACCTG ATTAAATTTGCATAACAATGGAAAAAAAAAA - +4 cisbp__M5837-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 11 0.966952 23644.9 1 6 CACCTG GATGAATTTCAGTCATG + +4 hocomoco__PO3F4_HUMAN.H11MO.0.D-CG4328-Dll-Lmx1a-dve-nub-pdm2-pdm3-vvl 10 0.966952 23644.9 1 6 CACCTG ATAAATTATGCAAATTA - +4 swissregulon__sacCer__ORC1-CG7839-SREBP-slp2-vtd 5 0.966952 23644.9 1 6 CACCTG AACTAAACATAAAAAAA - +4 cisbp__M5711-ey-Poxm-sv-toy 13 0.966952 23644.9 1 4 CACCTG TGCAGTCATGCGTGACG + +4 scertf__zhu.STB3 13 0.966952 23644.9 1 4 CACCTG GTCCAAAATTTTTCACT + +4 tfdimers__MD00278 2 0.967512 23658.6 1 6 CACCTG ATTATTTAATCCATTAATTTAT + +4 tfdimers__MD00478-Sox100B 10 0.967512 23658.6 1 6 CACCTG ATTTAATTCCCACAAAGTTAAA - +4 tfdimers__MD00601-NfI 2 0.967698 23663.1 1 6 CACCTG ATTTATTGGATAATTGCCAATAAAAATATA + +4 cisbp__M1896 21 0.967698 23663.1 1 6 CACCTG GAAAAATTTCCAATACTCCACTCCCCCCCC - +4 cisbp__M6310-Blimp-1-CG9650-ebi-foxo-MTA1-like-nej-orb-Stat92E-sv 7 0.968152 23674.2 1 6 CACCTG AAAAAAGAAAATGAAA + +4 cisbp__M5356-E2f1 7 0.968152 23674.2 1 6 CACCTG AAAATGGCGCCATTTT - +4 taipale__E2F2_DBD_AAAATGGCGCCATTTT-E2f1 7 0.968152 23674.2 1 6 CACCTG AAAATGGCGCCATTTT - +4 cisbp__M6244-foxo 2 0.968191 23675.2 1 6 CACCTG AAAAACAAACAAC + +4 taipale__Foxj3_DBD_RTAAACATMAACA-fd59A-FoxK-foxo-slp2 3 0.968191 23675.2 1 6 CACCTG GTAAACATAAACA + +4 taipale__LHX9_DBD_TAATTRCYAATTA_repr-Dll 0 0.968191 23675.2 1 6 CACCTG TAATTGCCAATTA + +4 taipale_cyt_meth__ZNF460_NAACGCCCCCCGN_eDBD_repr 7 0.968191 23675.2 1 6 CACCTG CAACGCCCCCCGA + +4 transfac_pro__M01014-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 0 0.968191 23675.2 1 6 CACCTG CTCTTTGTTATGA + +4 transfac_pro__M07432-Mad-Sox14-SoxN 5 0.968191 23675.2 1 6 CACCTG TTCAAAACAAAGG + +4 cisbp__M5603-Dll 0 0.968191 23675.2 1 6 CACCTG TAATTGCCAATTA - +4 cisbp__M6429-pdm3-vvl 0 0.968191 23675.2 1 6 CACCTG TGCATAAATTATG - +4 taipale_cyt_meth__POU3F2_NTATGCWAATKAN_eDBD-Dll-dve-nub-pdm2-pdm3-vvl 6 0.968191 23675.2 1 6 CACCTG CTCATTTGCATAA - +4 taipale_cyt_meth__POU3F4_NTATGCWAATKAN_eDBD-Dll-nub-pdm2-pdm3-vvl 6 0.968191 23675.2 1 6 CACCTG CTCATTAGCATAA - +4 cisbp__M6242 8 0.968191 23675.2 1 5 CACCTG TAAACAAAAACAA + +4 flyfactorsurvey__CG4360_F1-3_SANGER_2.5_FBgn0038787-Aef1-CG4360 8 0.968191 23675.2 1 5 CACCTG ACAACAACAAGCC + +4 hocomoco__ZN410_HUMAN.H11MO.0.D -1 0.968191 23675.2 1 5 CACCTG CCATCCCATAATA - +4 taipale_cyt_meth__POU4F3_ATGCATWATGCAT_FL_meth-acj6 10 0.968191 23675.2 1 3 CACCTG ATGCATAATGCAT - +4 cisbp__M4963-abd-A-Antp-btn-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Dll-Drgx-E5-ems-en-eve-exex-ftz-HGTX-inv-lab-lbe-Lmx1a-OdsH-pb-Scr-slou-Ubx-unc-4-unpg 0 0.968319 23678.3 1 6 CACCTG TAATTA + +4 flyfactorsurvey__Exex_SOLEXA_FBgn0041156-Antp-CG4328-CG11294-CG18599-CG32532-Dfd-Dll-Drgx-E5-Lmx1a-OdsH-Scr-Ubx-abd-A-btn-ems-en-eve-exex-lab-pb-slou-unc-4-unpg 0 0.968319 23678.3 1 6 CACCTG TAATTA + +4 transfac_pro__M01668 0 0.968319 23678.3 1 6 CACCTG TAATTG + +4 stark__CAATTA-repo 0 0.968319 23678.3 1 6 CACCTG TAATTG - +4 hdpi__SCAND2 1 0.968319 23678.3 1 5 CACCTG TTGCTT - +4 yetfasco__YKR099W_402-Myb-Pbp95 4 0.968319 23678.3 1 2 CACCTG GAGTCA + +4 tfdimers__MD00007-E2f1 3 0.968354 23679.2 1 6 CACCTG TTTTTACTTTCAGTTTCATTTTT + +4 tfdimers__MD00312 14 0.968448 23681.5 1 6 CACCTG ACAGAGGGGCCATTTGCATAACAAAGGAAGAAAAAAT + +4 tfdimers__MD00374-gsb-gsb-n-pho-phol-prd 18 0.968448 23681.5 1 6 CACCTG ATATTTTTTATTAATTAAATCCATTTTTAAAAAAATA + +4 cisbp__M1098-dve 2 0.968544 23683.8 1 6 CACCTG CTAATCCG + +4 cisbp__M4717 0 0.968544 23683.8 1 6 CACCTG AATCGATA + +4 cisbp__M4788-C15-inv-OdsH-Ubx 2 0.968544 23683.8 1 6 CACCTG GTTAATTA + +4 taipale_cyt_meth__EN2_NYAATTAN_eDBD-Antp-Awh-bsh-C15-CG18599-CG9876-Dll-Dr-E5-ems-en-eve-exex-inv-lab-Lim3-lms-OdsH-pb-Pph13-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2 1 0.968544 23683.8 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__ESX1_YYAATTAN_eDBD_meth-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-Drgx-E5-ems-en-ind-inv-Lim3-OdsH-Pph13-repo-Ubx-unc-4-unpg-Vsx1-Vsx2 1 0.968544 23683.8 1 6 CACCTG CTAATTAG + +4 taipale_cyt_meth__HOXC4_NTMATTAN_FL_meth-Dfd-eve-ind-pb-Scr-Ubx-zen-zen2 0 0.968544 23683.8 1 6 CACCTG GTCATTAG + +4 taipale_cyt_meth__PRRX2_CYAATTAN_FL-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-toy-Ubx-unc-4-unpg 1 0.968544 23683.8 1 6 CACCTG CTAATTAA + +4 transfac_pro__M01923-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 2 0.968544 23683.8 1 6 CACCTG AAAACAAT + +4 cisbp__M2199 1 0.968544 23683.8 1 6 CACCTG GCGCCGCA - +4 jaspar__MA0394.1 1 0.968544 23683.8 1 6 CACCTG GCGCCGCA - +4 predrem__nrMotif1276 0 0.968544 23683.8 1 6 CACCTG CATCCCAA - +4 transfac_pro__M01685 1 0.968544 23683.8 1 6 CACCTG GCGCCGCG - +4 predrem__nrMotif1601 3 0.968544 23683.8 1 5 CACCTG CAATAGCA + +4 predrem__nrMotif2189-Tbp-Trf-Trf2 3 0.968544 23683.8 1 5 CACCTG ATATATAT + +4 hdpi__SNRP70-snRNP-U1-70K -1 0.968544 23683.8 1 5 CACCTG AAATTACT - +4 hdpi__SUCLG1-CG6255-Scsalpha -1 0.968544 23683.8 1 5 CACCTG ATTTCAAA - +4 cisbp__M1748 -2 0.968544 23683.8 1 4 CACCTG ACTCCGCC + +4 jaspar__MA0295.1-CHES-1-like-jumu 4 0.968544 23683.8 1 4 CACCTG GACGCAAA + +4 flyfactorsurvey__Btn_Cell_FBgn0014949-btn 4 0.968544 23683.8 1 4 CACCTG TCATTAAG - +4 flyfactorsurvey__Cad_SOLEXA_FBgn0000251-Abd-B-CG4328-Dbx-H2.0-Lmx1a-Ubx-cad 4 0.968544 23683.8 1 4 CACCTG TAATAAAA - +4 flyfactorsurvey__Hgtx_SOLEXA_FBgn0040318-Dbx-HGTX-Lmx1a-ems-lab 4 0.968544 23683.8 1 4 CACCTG TAATTAAA - +4 predrem__nrMotif1498 4 0.968544 23683.8 1 4 CACCTG TTGAGCCC - +4 taipale_cyt_meth__HOXB2_NYAATTAN_eDBD_meth-Antp-Awh-bsh-btn-C15-CG18599-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-Lmx1a-OdsH-pb-ro-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 5 0.968544 23683.8 1 3 CACCTG GTAATTAG + +4 cisbp__M0896-acj6-al-Antp-HGTX-ind-lab-repo-Scr-unpg -3 0.968544 23683.8 1 3 CACCTG CTAATTAA - +4 taipale_cyt_meth__EMX1_NYAATTAN_FL-Antp-Awh-C15-CG18599-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-OdsH-pb-pdm3-Scr-slou-Ubx-unpg-Vsx1-Vsx2 -3 0.968544 23683.8 1 3 CACCTG CTAATTAG - +4 transfac_pro__M07789-E5-ems-en-eve-ind-inv-pb-Ubx 5 0.968544 23683.8 1 3 CACCTG CTAATTAG - +4 hocomoco__RX_HUMAN.H11MO.0.D-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dfd-Dll-Dr-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-al-en-ey-hbn-inv-lab-lms-otp-repo-ro-slou-toy-unc 5 0.968791 23689.9 1 6 CACCTG TTAATTAGCAA + +4 taipale_cyt_meth__NFE2_NATGASTCATN_eDBD-cnc-Jra-kay-Mef2 5 0.968791 23689.9 1 6 CACCTG GATGACTCATC + +4 transfac_pro__M08828-NFAT 0 0.968791 23689.9 1 6 CACCTG TTCCACGGAAA + +4 transfac_pro__M08875-E2f1-E2f2 0 0.968791 23689.9 1 6 CACCTG GTTTTCGCGCC + +4 cisbp__M3780-pdm3-vvl 3 0.968791 23689.9 1 6 CACCTG GCATAATTTAT - +4 hocomoco__HXD11_HUMAN.H11MO.0.D-Abd-B-Dbx-cad 1 0.968791 23689.9 1 6 CACCTG AGTAATAAAAA - +4 taipale_cyt_meth__PHOX2B_TAATTAGATTA_FL-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-ems-hbn-OdsH-Optix-PHDP-repo-ro-Traf4-unc-4 1 0.968791 23689.9 1 6 CACCTG TAATCTAATTA - +4 transfac_pro__M09220 1 0.968791 23689.9 1 6 CACCTG GTAATTAATGC - +4 cisbp__M0882-Antp-Awh-B-H1-B-H2-CG9876-CG11294-CG32532-CG34367-Dr-E5-Lim1-Lim3-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-en-ey-gsb-gsb-n-inv-lab-lbe-lms-otp-pdm3-prd-repo-ro-slou-toy-unc-4-unpg-vvl-zfh2 -1 0.968791 23689.9 1 5 CACCTG AATTAATTAGT + +4 stark__GNCTANWWATA-Mef2 -1 0.968791 23689.9 1 5 CACCTG GACTAAAAATA + +4 cisbp__M0850 -1 0.968791 23689.9 1 5 CACCTG TCATTAATTAT - +4 predrem__nrMotif220-CTCF-ERR-E(z)-RpII215-SREBP-brm-tna-vtd 6 0.968791 23689.9 1 5 CACCTG CCCCGCCGCCC - +4 transfac_pro__M08910-gt-Irbp18-nej-slbo-srl-Xrp1 7 0.968791 23689.9 1 4 CACCTG TATTGCGCAAT + +4 yetfasco__YDR423C_2073 7 0.968791 23689.9 1 4 CACCTG GATTACTAATC - +4 cisbp__M6091-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.968794 23689.9 1 6 CACCTG AACAATTGCATTGTT + +4 cisbp__M6401-Gsc-oc 5 0.968794 23689.9 1 6 CACCTG CTTTAATCCCTTAAC + +4 jaspar__MA0547.1 9 0.968794 23689.9 1 6 CACCTG AATTGTCATCATTTT - +4 swissregulon__hs__PDX1.p2-Dfd-ems-ind 9 0.968794 23689.9 1 6 CACCTG GAGTCTAATGACAGA - +4 jaspar__MA0150.2-Jra-cnc-kay-maf-S -1 0.968794 23689.9 1 5 CACCTG TGCTGAGTCATGCTG - +4 taipale_cyt_meth__FOXJ2_NWWGTTGTAAAYAN_eDBD_meth-fd96Ca-fd96Cb-slp2 8 0.968834 23690.9 1 6 CACCTG TTGTTTACAACAAA - +4 stark__SVTAATYGATTANS-ey-eyg-gsb-gsb-n-prd-toe 10 0.968834 23690.9 1 4 CACCTG CATAATCAATTATC - +4 taipale__POU4F1_DBD_ATGMATAATTAATG_repr-acj6-vvl -2 0.968834 23690.9 1 4 CACCTG CATTAATTATTCAT - +4 transfac_pro__M07867-ey-eyg-gsb-gsb-n-prd-toe 10 0.968834 23690.9 1 4 CACCTG GATAATCGATTATC - +4 tfdimers__MD00110-foxo-Ptx1-slp2 3 0.968912 23692.8 1 6 CACCTG ATTTTTTTGTTTGCTTAGATATTT - +4 stark__TTATS-TFAM 1 0.969177 23699.3 1 4 CACCTG TTATC + +4 hdpi__BAT4-CG8152 3 0.969177 23699.3 1 2 CACCTG GAATA + +4 tfdimers__MD00484-pho-phol 9 0.969188 23699.6 1 6 CACCTG TTTTTCATTACCATTTTTTAAGTTTTA + +4 tfdimers__MD00285-Mad 4 0.969188 23699.6 1 6 CACCTG TTTTTTCCTTTGTTTAATGTTTTTTTT - +4 tfdimers__MD00302 16 0.969222 23700.4 1 6 CACCTG AAAAAAAGAGAAATGAAACTTCAAA - +4 dbcorrdb__EZH2__ENCSR000ARR_1__m2-E(z) 10 0.969304 23702.4 1 6 CACCTG CCGGGTCGGACACCGCGGCG + +4 dbcorrdb__YY1__ENCSR000BKJ_1__m1-E(z)-Hcf-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 12 0.969304 23702.4 1 6 CACCTG CCAAGATGGCGGCCGCGGGG + +4 taipale_cyt_meth__RUNX3_NWAACCGCANNNACCGCARN_FL_repr-Bgb-lz-run-RunxA-RunxB 2 0.969304 23702.4 1 6 CACCTG CAAACCGCAAAAACCGCAAG + +4 dbcorrdb__SUPT20H__ENCSR000ECQ_1__m5-bon-Brf-brm-btd-CG42741-CoRest-crol-ct-CTCF-E2f1-ERR-E(z)-HDAC1-Klf15-klu-l(3)neo38-Max-Myc-Nelf-E-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-tna-vtd-zfh1 0 0.969304 23702.4 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 dbcorrdb__YY1__ENCSR000BLZ_1__m1-CG10431-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 0 0.969304 23702.4 1 6 CACCTG CCGCGGCCGCCATTTTGGCC - +4 flyfactorsurvey__CG7368_SANGER_5_FBgn0036179-CG7368-CTCF-CoRest-crol-ct-l(3)neo38 14 0.969304 23702.4 1 6 CACCTG ATTATCCCCCCCCCCCCCCC - +4 cisbp__M2048-Antp-ap-Awh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-E5-ems-en-hbn-inv-lab-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-unc-4-unpg-Vsx1-zen2 1 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 cisbp__M4822-abd-A-al-Antp-ap-Awh-CG11294-CG15696-CG32532-CG34031-CG34367-CG4328-CG9876-Dfd-Dll-Dr-E5-ems-en-exex-ftz-hbn-ind-inv-lab-Lim1-Lim3-lms-Lmx1a-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-Scr-slou- 1 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 cisbp__M4932-abd-A-al-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-Dll-E5-ems-en-eve-ey-ftz-gsb-gsb-n-hbn-HGTX-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp- 0 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 elemento__CAGCCGC 0 0.969502 23707.2 1 6 CACCTG CAGCCGC + +4 elemento__CGCCCGC 0 0.969502 23707.2 1 6 CACCTG CGCCCGC + +4 flyfactorsurvey__CG13424_SOLEXA_FBgn0034520-Antp-Awh-CG4328-CG9876-CG11294-CG15696-CG32532-CG34031-CG34367-Dfd-Dll-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-em 1 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__H2.0_Cell_FBgn0001170-H2.0 0 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__Ro_SOLEXA_FBgn0003267-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-exex-ey-ftz-hbn-i 1 0.969502 23707.2 1 6 CACCTG TTAATTA + +4 swissregulon__hs__SOX5.p2-Sox15-Sox102F-SoxN 0 0.969502 23707.2 1 6 CACCTG AAACAAT + +4 elemento__CGGGAGC 1 0.969502 23707.2 1 6 CACCTG GCTCCCG - +4 elemento__CGGGCGC 1 0.969502 23707.2 1 6 CACCTG GCGCCCG - +4 jaspar__MA0240.1-Antp-Awh-CG4328-CG9876-CG11294-CG32532-CG34367-Drgx-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Vsx1-ap-ems-en-hbn-inv-lab-lms-otp-repo-ro-slou-unc-4-unpg-zen2 0 0.969502 23707.2 1 6 CACCTG TAATTAA - +4 hdpi__RFXANK-CG5846 -1 0.969502 23707.2 1 5 CACCTG GCCAAAG + +4 swissregulon__hs__ADNP_IRX_SIX_ZHX.p2-Six4-ara-caup-mirr-so 2 0.969502 23707.2 1 5 CACCTG AATAATT + +4 elemento__CGCGAGC 3 0.969502 23707.2 1 4 CACCTG CGCGAGC + +4 elemento__CGCGGCC 3 0.969502 23707.2 1 4 CACCTG CGCGGCC + +4 elemento__CGCGTCC 3 0.969502 23707.2 1 4 CACCTG CGCGTCC + +4 elemento__CGGGCCC 3 0.969502 23707.2 1 4 CACCTG CGGGCCC + +4 elemento__GCGGCCC 3 0.969502 23707.2 1 4 CACCTG GCGGCCC + +4 elemento__GCGGGCC 3 0.969502 23707.2 1 4 CACCTG GCGGGCC + +4 transfac_pro__M09267 -2 0.969502 23707.2 1 4 CACCTG CATCATC + +4 elemento__GCTCCGC 3 0.969502 23707.2 1 4 CACCTG GCGGAGC - +4 cisbp__M1976-abd-A-al-Antp-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-ey-hbn-ind-inv-lab-lbl-Lim1-Lim3-Lmx1a-nub-OdsH-otp-pb-pdm2-pdm3-PHDP-Pph13-repo-ro-Rx-Scr- -3 0.969502 23707.2 1 3 CACCTG TTAATTA + +4 cisbp__M2018-al-ap-Awh-CG18599-CG32532-CG9876-Dfd-dve-E5-ems-en-eve-hbn-ind-inv-lbl-Lim3-OdsH-Optix-otp-pb-pdm3-Pph13-repo-ro-Rx-Ubx-unc-4-unpg-Vsx1-Vsx2-vvl-zen-zen2 -3 0.969502 23707.2 1 3 CACCTG CTAATTA + +4 flyfactorsurvey__Awh_Cell_FBgn0013751-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Vsx1-Vsx2-al-ap-bsh-ems-en-eve-ey-hbn-ind-inv-lab-lbl-otp-p -3 0.969502 23707.2 1 3 CACCTG TTAATTA + +4 jaspar__MA0209.1-Awh-CG9876-CG18599-CG32532-Dfd-E5-Lim3-OdsH-Optix-Pph13-Rx-Ubx-Vsx1-Vsx2-al-ap-ems-en-eve-hbn-ind-inv-lbl-otp-pb-pdm3-repo-ro-unc-4-unpg-zen-zen2 -3 0.969502 23707.2 1 3 CACCTG CTAATTA + +4 cisbp__M1986-abd-A-al-Antp-ap-Awh-btn-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-Lmx1a-OdsH-otp-pb-pdm3-PHDP-Pph13-repo-ro-Rx-Scr-Ubx-unc- 5 0.969502 23707.2 1 2 CACCTG CTAATTA + +4 cisbp__M4834-abd-A-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-Dfd-E5-ems-eve-ftz-hbn-ind-lab-lbe-lbl-Lim1-Lim3-otp-pb-pdm3-Pph13-ro-Rx-Scr-Ubx-unpg-Vsx1-zen-zen2 5 0.969502 23707.2 1 2 CACCTG TTAATTA + +4 flyfactorsurvey__CG18599_Cell_FBgn0038592-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-btn-ems-en-eve-hbn-ind-i 5 0.969502 23707.2 1 2 CACCTG TTAATTA + +4 jaspar__MA0099.2-Jra-kay -4 0.969502 23707.2 1 2 CACCTG TGACTCA + +4 hdpi__HNRPC-CG42458 -4 0.969502 23707.2 1 2 CACCTG TGCTTTG - +4 taipale__MSX1_DBD_NYAATTAAAANNYAATTA_repr-Dr-HGTX-ind 5 0.969588 23709.3 1 6 CACCTG GCAATTAAAAACCAATTA + +4 transfac_pro__M05204 6 0.969588 23709.3 1 6 CACCTG AGACTAAACGTTTAGTCT + +4 transfac_pro__M05787 7 0.969588 23709.3 1 6 CACCTG TGGGGAACGCCAGGCGGC + +4 cisbp__M5637-Dr-HGTX-ind 5 0.969588 23709.3 1 6 CACCTG GCAATTAAAAACCAATTA - +4 transfac_pro__M05720 7 0.969588 23709.3 1 6 CACCTG GTGCCGACCCCGTCTTCG - +4 cisbp__M4470-nub-pdm2-vvl 3 0.969957 23718.4 1 6 CACCTG ATTTGCATAT + +4 cisbp__M4765-bin 1 0.969957 23718.4 1 6 CACCTG TAAACAAAGA + +4 predrem__nrMotif2477 1 0.969957 23718.4 1 6 CACCTG AAACAGAATA + +4 swissregulon__sacCer__PHO2-Lim3 1 0.969957 23718.4 1 6 CACCTG TTAATTAAAT + +4 swissregulon__sacCer__SWI6 0 0.969957 23718.4 1 6 CACCTG AACGCGAAAA + +4 tiffin__TIFDMEM0000034-CG4730-CG7101 4 0.969957 23718.4 1 6 CACCTG TATATATATA + +4 tiffin__TIFDMEM0000101 3 0.969957 23718.4 1 6 CACCTG CGGCGACTGC + +4 transfac_pro__M03169 4 0.969957 23718.4 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M03172 4 0.969957 23718.4 1 6 CACCTG ATGCCGCCCC + +4 transfac_pro__M04969 4 0.969957 23718.4 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M04974 4 0.969957 23718.4 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05071 4 0.969957 23718.4 1 6 CACCTG ATGCCGCCGA + +4 cisbp__M5543-abd-A-acj6-Antp-ap-Awh-btn-CG11294-CG18599-CG32532-CG9876-Dr-E5-ems-en-eve-ftz-hbn-HGTX-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-otp-pb-PHDP-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 2 0.969957 23718.4 1 6 CACCTG ACTAATTAAT - +4 predrem__nrMotif2479 1 0.969957 23718.4 1 6 CACCTG AAACAGAAAT - +4 transfac_pro__M05136 1 0.969957 23718.4 1 6 CACCTG GCAGCGGCAT - +4 transfac_pro__M06041 4 0.969957 23718.4 1 6 CACCTG GCGTCTCATA - +4 homer__TCATCAATCA_Pdx1-Dfd 5 0.969957 23718.4 1 5 CACCTG TCATCAATCA + +4 cisbp__M4821-ap-B-H1-B-H2-CG11085-CG11294-CG32532-CG9876-Dll-Dr-E5-en-hbn-HGTX-ind-inv-lab-Lim1-lms-NK7.1-OdsH-otp-PHDP-Pph13-repo-ro-Rx-slou-tup-Ubx-unc-4-unpg-Vsx1-Vsx2-zen2 5 0.969957 23718.4 1 5 CACCTG CCAATTAAGA - +4 flyfactorsurvey__CG13424_SOLEXA_2_FBgn0034520-B-H1-B-H2-CG9876-CG11085-CG11294-CG32532-Dll-Dr-E5-HGTX-Lim1-NK7.1-OdsH-PHDP-Pph13-Rx-Ubx-Vsx1-Vsx2-ap-en-ind-inv-lab-lms-otp-repo-ro-slou-tup-unc-4-unpg- 5 0.969957 23718.4 1 5 CACCTG CCAATTAAGA - +4 transfac_pro__M05344-klu-sr 5 0.969957 23718.4 1 5 CACCTG CCGCCCACGC - +4 cisbp__M5635-abd-A-Antp-ap-btn-C15-CG11294-CG32532-CG9876-Dbx-E5-en-exex-HGTX-ind-lab-Lim1-lms-Lmx1a-pb-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1 6 0.969957 23718.4 1 4 CACCTG TTTAATTACT + +4 cisbp__M4998-hb-rn 6 0.969957 23718.4 1 4 CACCTG CAAAAAAAAA - +4 cisbp__M5315-Irbp18-nej-slbo-srl-Xrp1 6 0.969957 23718.4 1 4 CACCTG ATTGCGCAAT - +4 taipale__CEBPB_full_NTTRCGCAAY-Irbp18-nej-slbo-srl-Xrp1 6 0.969957 23718.4 1 4 CACCTG ATTGCGCAAT - +4 taipale__MNX1_DBD_NNYAATTANN-abd-A-Antp-ap-btn-C15-CG11294-CG32532-CG9876-Dbx-E5-en-exex-HGTX-ind-lab-Lim1-lms-Lmx1a-pb-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1 6 0.969957 23718.4 1 4 CACCTG TTTAATTACC - +4 cisbp__M6192-Dp-E2f1-E2f2-eve 7 0.969957 23718.4 1 3 CACCTG CGCGCGAAAC + +4 predrem__nrMotif397 7 0.969957 23718.4 1 3 CACCTG AACAAAGCAT + +4 taipale_cyt_meth__HOXD10_RTCGTAAAAN_eDBD_meth-Abd-B-cad 7 0.969957 23718.4 1 3 CACCTG GTTTTACGAC - +4 cisbp__M1101-al-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-dve-en-ey-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-toy-unc-4-unpg-Vsx1-zfh2 2 0.969991 23719.2 1 6 CACCTG GTTAATTAG + +4 predrem__nrMotif1720 0 0.969991 23719.2 1 6 CACCTG TGCATTCAA + +4 predrem__nrMotif2275 1 0.969991 23719.2 1 6 CACCTG TCACTCTGT + +4 predrem__nrMotif2277 3 0.969991 23719.2 1 6 CACCTG GCCGAGCCC + +4 stark__BYAATTARH-Awh-C15-CG4328-CG9876-CG11085-CG11294-CG15696-CG18599-CG32532-CG34367-Dr-E5-Lim1-Lim3-Lmx1a-NK7.1-OdsH-PHDP-Pph13-Rx-Traf4-Vsx1-Vsx2-al-ap-ems-en-eve-exex-hbn-ind-inv-lab-lbe-lms-otp- 1 0.969991 23719.2 1 6 CACCTG TCAATTAAT + +4 flyfactorsurvey__CG32105_Cell_FBgn0052105-CG4328-CG9876-CG11294-CG32532-CG34367-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-al-ap-ems-en-lab-otp-repo-ro-slou-unc-4-unpg 1 0.969991 23719.2 1 6 CACCTG CTAATTAAT - +4 predrem__nrMotif782 1 0.969991 23719.2 1 6 CACCTG TTTGCTTAT - +4 cisbp__M5587-cnc-foxo-Jra-kay-Mef2-NFAT-Stat92E 4 0.969991 23719.2 1 5 CACCTG ATGACTCAT + +4 stark__VATTWGCAT-nub-pdm2-vvl 4 0.969991 23719.2 1 5 CACCTG GATTAGCAT + +4 taipale__JDP2_DBD_ATGASTCAT-cnc-foxo-Jra-kay-Mef2-NFAT-Stat92E 4 0.969991 23719.2 1 5 CACCTG ATGACTCAT + +4 transfac_public__M00096 -1 0.969991 23719.2 1 5 CACCTG ATCAATCAA + +4 predrem__nrMotif1494 4 0.969991 23719.2 1 5 CACCTG TGACTGACT - +4 predrem__nrMotif1623 5 0.969991 23719.2 1 4 CACCTG CCGCGCTCC + +4 flyfactorsurvey__CG11085_Cell_FBgn0030408-CG11085-Dr-Ubx-lms -2 0.969991 23719.2 1 4 CACCTG CCAATTAAA - +4 predrem__nrMotif2492 5 0.969991 23719.2 1 4 CACCTG ATGCTTAGA - +4 stark__STATAWAWR-Tbp 6 0.969991 23719.2 1 3 CACCTG CATATATAC - +4 tfdimers__MD00246-vvl 27 0.970044 23720.5 1 6 CACCTG TTTTTTTTTTCCTTTGTTATTCTAATTCCTCTTATT - +4 transfac_pro__M05239-vtd 14 0.970726 23737.2 1 6 CACCTG GGGGGGCGGCGAAACACCCCC - +4 cisbp__M2365 4 0.970922 23742 1 6 CACCTG GCAATAATTGAA + +4 cisbp__M3681-nub-pdm2 4 0.970922 23742 1 6 CACCTG AATTAGCATAGA + +4 cisbp__M5732-acj6-vvl 5 0.970922 23742 1 6 CACCTG ATGCATAATTTA + +4 cisbp__M6362-NFAT 4 0.970922 23742 1 6 CACCTG AATTTTCCATTG + +4 homer__WTTTTCYYTTTT_RLR1_ 5 0.970922 23742 1 6 CACCTG ATTTTCTTTTTT + +4 jaspar__MA0371.1-D-Sox100B 0 0.970922 23742 1 6 CACCTG CCCATTGTTCTC + +4 stark__AATTANWNRCGC 3 0.970922 23742 1 6 CACCTG AATTAAAAACGC + +4 swissregulon__hs__EGR1..3.p2-klu-sr 1 0.970922 23742 1 6 CACCTG GTGCGTGGGCGG + +4 swissregulon__hs__GFI1B.p2-sens-sens-2 5 0.970922 23742 1 6 CACCTG TAAATCACTGCA + +4 taipale__POU3F1_DBD_WTGMATAAWTNA_repr-acj6-vvl 5 0.970922 23742 1 6 CACCTG ATGCATAATTTA + +4 taipale_cyt_meth__POU3F1_NTATGCGCATAN_eDBD_meth-nub-pdm2-vvl 5 0.970922 23742 1 6 CACCTG TTATGCGCATAA + +4 transfac_pro__M01069-Sry-delta 2 0.970922 23742 1 6 CACCTG TGCGCGTCTATA + +4 transfac_pro__M06944 6 0.970922 23742 1 6 CACCTG TTGGAAATCCCA + +4 transfac_pro__M00730 2 0.970922 23742 1 6 CACCTG GACACGCTGGCA - +4 transfac_pro__M01232 3 0.970922 23742 1 6 CACCTG TTATTACTAATA - +4 transfac_pro__M06697 5 0.970922 23742 1 6 CACCTG TATGCCGCCCCG - +4 transfac_pro__M06755 5 0.970922 23742 1 6 CACCTG TCCCATGCCATG - +4 transfac_pro__M06802 5 0.970922 23742 1 6 CACCTG TCCCATGCCATG - +4 transfac_pro__M09416 6 0.970922 23742 1 6 CACCTG TATCATTTCTTT - +4 transfac_pro__M05680 -1 0.970922 23742 1 5 CACCTG TCCCCAGCCCAG - +4 transfac_pro__M05814 7 0.970922 23742 1 5 CACCTG CATCCATTCCCA - +4 transfac_pro__M06362 7 0.970922 23742 1 5 CACCTG TCTTTTGTCCCA - +4 transfac_pro__M06540 7 0.970922 23742 1 5 CACCTG GAATATGGACAT - +4 transfac_pro__M06931-Dad -1 0.970922 23742 1 5 CACCTG ATTTGGCGAAAC - +4 transfac_public__M00095-ct -2 0.970922 23742 1 4 CACCTG CCAATAATCGAT + +4 cisbp__M3962-Sox102F -2 0.970922 23742 1 4 CACCTG TCTATTGTTTAC - +4 transfac_pro__M05514 8 0.970922 23742 1 4 CACCTG CCCGCCCAAACT - +4 transfac_pro__M05182 9 0.970922 23742 1 3 CACCTG CAAGCCGTTAAT - +4 transfac_pro__M07451-cad-eve 9 0.970922 23742 1 3 CACCTG GCCATAAATCAC - +4 cisbp__M5601-Awh 10 0.970922 23742 1 2 CACCTG TGATTGCAATCA - +4 cisbp__M5840-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.971158 23747.7 1 6 CACCTG GAACAATTGCAGTGTTC + +4 taipale__SOX8_DBD_NAACAATKNYAGTGTTN-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.971158 23747.7 1 6 CACCTG GAACAATTGCAGTGTTC + +4 bergman__prd-PD-prd 4 0.971158 23747.7 1 6 CACCTG TGTCAACCGTGACGACA - +4 cisbp__M5449-slp2 4 0.971158 23747.7 1 6 CACCTG TGTTTACAATTGTTTAT - +4 jaspar__MA0853.1-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-ap-ems-otp-pdm3-repo-ro-unc-4-vvl-zfh2 2 0.971158 23747.7 1 6 CACCTG GGTAATTAATTAATGCG - +4 jaspar__MA0898.1-Hmx 1 0.971158 23747.7 1 6 CACCTG ATTCTTTAATTGCTTGT - +4 scertf__pachkov.ORC1-CG7839-SREBP-slp2-vtd 5 0.971158 23747.7 1 6 CACCTG AACTAAACATAAAAAAA - +4 transfac_pro__M01413-Hmx 1 0.971158 23747.7 1 6 CACCTG ATTCTTTAATTGCTTGT - +4 transfac_pro__M01417-abd-A-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-E5-ems-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-Scr-Ubx-unc-4-Vsx1-vvl-zfh2 2 0.971158 23747.7 1 6 CACCTG GGTAATTAATTAATGCG - +4 yetfasco__YML065W_1549-CG7839-SREBP-slp2-vtd 5 0.971158 23747.7 1 6 CACCTG AACTAAACATAAAAAAA - +4 jaspar__MA0854.1-Antp-Awh-CG4328-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-al-ap-ems-en-ey-otp-pdm3-repo-ro-toy-unc-4-vvl-zfh2 13 0.971158 23747.7 1 4 CACCTG CGAATTAATTAATCACC + +4 transfac_pro__M01362-abd-A-al-Antp-ap-Awh-CG18599-CG32532-CG4328-Dfd-E5-ems-en-ey-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-repo-ro-Rx-Scr-toy-Ubx-unc-4-Vsx1-vvl-zfh2 13 0.971158 23747.7 1 4 CACCTG CGAATTAATTAATCACC + +4 transfac_pro__M05294 13 0.971158 23747.7 1 4 CACCTG TTGTATTGATTGATTCC + +4 cisbp__M3675-nub-pdm2-vvl 12 0.971688 23760.7 1 6 CACCTG CCGAAATTTGCATATTGAA + +4 hocomoco__SOX18_HUMAN.H11MO.0.D-Sox15 3 0.971688 23760.7 1 6 CACCTG GCACCCATTGTTCTTTTCC + +4 cisbp__M5708-ey-Poxm-sv-toy 5 0.971688 23760.7 1 6 CACCTG TTTCACGCATGACTGCACA - +4 taipale_cyt_meth__ZSCAN16_NANTGTTAACAGAGCCTCN_FL 14 0.971688 23760.7 1 5 CACCTG AGAGGCTCTGTTAACACTT - +4 cisbp__M6474-Sox15 15 0.971688 23760.7 1 4 CACCTG GAACCCATTGTTCTTTTCC - +4 transfac_pro__M04662-jumu 2 0.971811 23763.7 1 6 CACCTG GGAAGCCGACCGCGTCCTTAAT + +4 cisbp__M6017-fd59A-FoxK-foxo-slp2 3 0.972219 23773.7 1 6 CACCTG GTAAACATAAACA + +4 predrem__nrMotif2348-Brf-CTCF-ERR-E(z)-HDAC1-Hcf-Nelf-E-RpII215-SREBP-Taf1-brm-tna-vtd 7 0.972219 23773.7 1 6 CACCTG CCGCCGCCGCCGC - +4 taipale_cyt_meth__POU4F3_NTNAATWATGCAN_eDBD-acj6-vvl 1 0.972219 23773.7 1 6 CACCTG ATGCATAATTAAT - +4 transfac_pro__M07935-btd-klu-Spps-sr 10 0.972219 23773.7 1 3 CACCTG TCCGCCCACGCAC + +4 taipale_cyt_meth__POU4F3_ATGCATWATGCAT_FL-acj6 10 0.972219 23773.7 1 3 CACCTG ATGCATTATGCAT - +4 transfac_pro__M01368-nub-pdm2-vvl 7 0.972227 23773.9 1 6 CACCTG TTGTATGCAAATTAGA + +4 taipale_cyt_meth__SOX8_ACAATNNNNNNATTGT_FL-Sox100B 8 0.972227 23773.9 1 6 CACCTG ACAATGGGCCCATTGT - +4 transfac_pro__M06311 3 0.972227 23773.9 1 6 CACCTG AATTCGCTGATCATCA - +4 cisbp__M2040-Antp-ap-Awh-btn-CG18599-CG32532-Dfd-E5-ems-eve-HGTX-ind-lab-lbl-pb-Scr-Ubx-zen2 0 0.972363 23777.2 1 6 CACCTG TAATTA + +4 cisbp__M2231 0 0.972363 23777.2 1 6 CACCTG TAATTG + +4 jaspar__MA0232.1-Antp-Awh-CG18599-E5-HGTX-Scr-Ubx-ap-btn-ems-eve-ind-lab-lbl-pb-zen2 0 0.972363 23777.2 1 6 CACCTG TAATTA + +4 jaspar__MA0426.1 0 0.972363 23777.2 1 6 CACCTG TAATTG + +4 stark__MAACAA-Aef1 0 0.972363 23777.2 1 6 CACCTG AAACAA + +4 hdpi__RFC2-RfC4 -1 0.972363 23777.2 1 5 CACCTG AAATGA + +4 hdpi__TROVE2 1 0.972363 23777.2 1 5 CACCTG ACAAAT + +4 fantom__motif23_CGCNAT 3 0.972363 23777.2 1 3 CACCTG CGCAAT + +4 fantom__motif60_GCGNAT 3 0.972363 23777.2 1 3 CACCTG GCGAAT + +4 bergman__croc-croc 3 0.972363 23777.2 1 3 CACCTG TTTTAT - +4 cisbp__M6041-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-E5-ems-en-ey-gsb-gsb-n-lab-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-toy-Traf4-unc-4-unpg-Vsx1-Vsx2- 1 0.972567 23782.2 1 6 CACCTG TTAATTAA + +4 jaspar__MA0433.1-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-ap-ems-en-otp-repo-ro-unc-4-unpg-zen2-zfh2 1 0.972567 23782.2 1 6 CACCTG TTAATTAA + +4 taipale_cyt_meth__BARHL2_NTAATTGN_FL-B-H1-B-H2-CG11085-Dr-en-inv-unpg 1 0.972567 23782.2 1 6 CACCTG CTAATTGC + +4 taipale_cyt_meth__DLX4_NYAATTAN_FL_meth-Dll 1 0.972567 23782.2 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__SOX30_GAACAATN_eDBD-Sox102F 1 0.972567 23782.2 1 6 CACCTG GAACAATG + +4 transfac_pro__M01930-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-E5-ems-en-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-zen2-zfh2 1 0.972567 23782.2 1 6 CACCTG TTAATTAA + +4 transfac_pro__M07841-Antp-Dfd-eve-ind-pb-Scr-Ubx-zen-zen2 0 0.972567 23782.2 1 6 CACCTG GTCATTAG + +4 transfac_public__M00498-Stat92E 2 0.972567 23782.2 1 6 CACCTG GATTTCCA + +4 cisbp__M3982-Stat92E 2 0.972567 23782.2 1 6 CACCTG GATTTCCA - +4 flyfactorsurvey__CG9876_Cell_FBgn0034821-Awh-CG9876-CG11085-CG18599-CG34367-E5-Lim3-OdsH-Pph13-Rx-ap-ems-en-ind-inv-otp-pdm3-ro-slou-unpg 0 0.972567 23782.2 1 6 CACCTG TAATTAGT - +4 cisbp__M0739-bin-CHES-1-like-croc-fd102C-fd19B-fd59A-FoxK-FoxL1-foxo-FoxP-slp1-slp2 3 0.972567 23782.2 1 5 CACCTG ATAAACAA + +4 cisbp__M1229 3 0.972567 23782.2 1 5 CACCTG ATATGCAT + +4 jaspar__MA0926.1 3 0.972567 23782.2 1 5 CACCTG ATATGCAT + +4 hdpi__RBM35B-fus 3 0.972567 23782.2 1 5 CACCTG TTTCAAAT - +4 transfac_pro__M01927 3 0.972567 23782.2 1 5 CACCTG GGGCATCG - +4 predrem__nrMotif2439 -2 0.972567 23782.2 1 4 CACCTG TCTCATAT + +4 predrem__nrMotif2649 4 0.972567 23782.2 1 4 CACCTG TTTATAGA + +4 transfac_pro__M01948-CHES-1-like-jumu 4 0.972567 23782.2 1 4 CACCTG GACGCAAA + +4 cisbp__M4792-Abd-B-cad-CG4328-Dbx-H2.0-Lmx1a-Ubx 4 0.972567 23782.2 1 4 CACCTG TAATAAAA - +4 cisbp__M4887-ap-Awh-CG11085-CG18599-CG34367-CG9876-E5-ems-en-ind-inv-Lim3-OdsH-otp-pdm3-Pph13-ro-Rx-slou-unpg 4 0.972567 23782.2 1 4 CACCTG TAATTAGT - +4 cisbp__M4941-ems 4 0.972567 23782.2 1 4 CACCTG TAATGACA - +4 cisbp__M0753-CHES-1-like-jumu 5 0.972567 23782.2 1 3 CACCTG AGACGCAA + +4 homer__CTAATKGV_Isl1-Ubx-en-tup -3 0.972567 23782.2 1 3 CACCTG CTAATTGC + +4 taipale_cyt_meth__HOXB6_YTAATTRY_eDBD_meth-abd-A-Antp-ap-cad-CG32532-Dfd-E5-en-ftz-HGTX-lab-lms-Scr-slou-tup-Ubx-unpg-zen2 5 0.972567 23782.2 1 3 CACCTG TTAATTAC + +4 taipale_cyt_meth__VAX2_NYAATTAN_FL-Antp-Awh-bsh-btn-C15-CG18599-CG9876-Dfd-Dll-Dr-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-OdsH-pb-pdm3-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen2 5 0.972567 23782.2 1 3 CACCTG CTAATTAG + +4 transfac_pro__M01711-Myb-Pbp95 5 0.972567 23782.2 1 3 CACCTG AGAGTCAG + +4 taipale__NKX6-1_DBD_NYMATTAN-abd-A-Antp-bsh-btn-Dll-exex-ftz-HGTX-lab-lbl-Lim1-Scr-Ubx 5 0.972567 23782.2 1 3 CACCTG TTAATTAC - +4 taipale_cyt_meth__EMX1_NYAATTAN_FL_meth-Antp-Awh-C15-CG18599-CG34367-CG9876-E5-ems-en-eve-exex-ind-inv-lab-lbe-lbl-Lim3-lms-OdsH-pb-pdm3-Pph13-ro-Scr-slou-Ubx-unpg-Vsx1-Vsx2 -3 0.972567 23782.2 1 3 CACCTG CTAATTAG - +4 taipale_cyt_meth__EMX1_NYAATTAN_eDBD_meth-Antp-Awh-bsh-btn-C15-CG11085-CG11294-CG18599-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-Lmx1a-OdsH-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg -3 0.972567 23782.2 1 3 CACCTG CTAATTAC - +4 taipale_cyt_meth__HOXB4_RTMATTAR_FL-Antp-ap-Awh-CG18599-Dfd-E5-ems-eve-ind-pb-Scr-zen-zen2 5 0.972567 23782.2 1 3 CACCTG CTAATGAT - +4 taipale_cyt_meth__HOXB4_RTMATTAR_FL_meth-Antp-ap-Awh-btn-CG18599-Dfd-E5-ems-eve-ind-pb-Scr-Ubx-zen-zen2 5 0.972567 23782.2 1 3 CACCTG CTAATGAC - +4 transfac_pro__M07847-ap-Awh-CG18599-CG32532-CG4328-E5-ems-en-Lim3-Lmx1a-OdsH-otp-Pph13-repo-Rx-unc-4-unpg-Vsx1-zfh2 5 0.972567 23782.2 1 3 CACCTG TTAATTAA - +4 predrem__nrMotif751 -4 0.972567 23782.2 1 2 CACCTG TTGCTAAA + +4 cisbp__M5819-D-Sox102F-Sox15-Sox21a-Sox21b-SoxN 6 0.972793 23787.7 1 6 CACCTG ATCAATAACATTGAT + +4 cisbp__M5822-Sox100B-Sox14-Sox15-Sox21b-SoxN 6 0.972793 23787.7 1 6 CACCTG ATCAATTGCATTGAT + +4 taipale__SOX14_DBD_NTGAATNNCATTCAN-D-Sox15-Sox21a-Sox21b-SoxN 6 0.972793 23787.7 1 6 CACCTG ATGAATAACATTCAT + +4 taipale__SOX15_full_ATCAATAACATTGAT-D-Sox102F-Sox15-Sox21a-Sox21b-SoxN 6 0.972793 23787.7 1 6 CACCTG ATCAATAACATTGAT + +4 taipale__SOX18_full_ATCAATNNCATTGAT_repr-Sox100B-Sox14-Sox15-SoxN 6 0.972793 23787.7 1 6 CACCTG ATCAATTGCATTGAT + +4 cisbp__M4871-btd-cbt-CG3065-CG42741-dar1-E2f2-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 7 0.972793 23787.7 1 6 CACCTG TTGGCCCCGCCCACT - +4 transfac_pro__M09074-RpII215-Taf1 10 0.972793 23787.7 1 5 CACCTG CCTCCGCCGCCATTT + +4 transfac_pro__M04967-HDAC1-maf-S 10 0.972793 23787.7 1 5 CACCTG TTTTTTTCTTTTCTT - +4 taipale_cyt_meth__E2F8_NTTTCCCGCCAAAN_eDBD_meth-E2f1-E2f2 2 0.972812 23788.2 1 6 CACCTG TTTTCCCGCCAAAA + +4 transfac_pro__M05736-CG42726 0 0.972812 23788.2 1 6 CACCTG CGCCAGAATTAATA + +4 transfac_pro__M05857-CG42726 0 0.972812 23788.2 1 6 CACCTG CGCCAGAATTAATA + +4 transfac_pro__M07416-cad 2 0.972812 23788.2 1 6 CACCTG AAATATTTTATAGC + +4 taipale_cyt_meth__POU3F4_NTAATGAKATGCGN_eDBD_meth-pdm3-vvl 3 0.972812 23788.2 1 6 CACCTG ACGCATCTCATTAA - +4 transfac_pro__M08836-nub-pdm2-vvl 5 0.972812 23788.2 1 6 CACCTG ATTTGCATATTCAT - +4 transfac_pro__M06985 -1 0.972812 23788.2 1 5 CACCTG CCTTGCAATAATCC - +4 transfac_pro__M05476-jing -3 0.972812 23788.2 1 3 CACCTG CTACTGTGGCCGAT + +4 hocomoco__PHX2A_HUMAN.H11MO.0.D-Awh-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-eve-hbn-otp-repo-unc-4 1 0.972818 23788.3 1 6 CACCTG TAATTTAATTA + +4 hocomoco__BATF_MOUSE.H11MO.1.A-Jra-MTA1-like-Mef2-NFAT-Stat92E-ebi-foxo-nej 5 0.972818 23788.3 1 6 CACCTG TGAGTCATATC - +4 yetfasco__YDR310C_383 1 0.972818 23788.3 1 6 CACCTG TTTTGTGACAC - +4 taipale_cyt_meth__HOXA13_NCCAATAAAAN_FL -1 0.972818 23788.3 1 5 CACCTG CCCAATAAAAC + +4 hocomoco__HMX3_HUMAN.H11MO.0.D-B-H1-B-H2-Hmx-NK7.1-tup 6 0.972818 23788.3 1 5 CACCTG AGCAATTAACG - +4 hocomoco__TYY2_HUMAN.H11MO.0.D-RpII215-pho-phol -1 0.972818 23788.3 1 5 CACCTG GCCGCCATTTT - +4 jaspar__MA0445.1-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN -2 0.972818 23788.3 1 4 CACCTG TCCATTGTTCT + +4 predrem__nrMotif2402 -2 0.972818 23788.3 1 4 CACCTG CATTTTTTTTT + +4 cisbp__M2249-D-Mad-Sox100B-Sox102F-Sox14-Sox15-SoxN -2 0.972818 23788.3 1 4 CACCTG TCCATTGTTCT - +4 cisbp__M5217-ss-tgo -2 0.972818 23788.3 1 4 CACCTG CATTGCGTGAC - +4 flyfactorsurvey__CG13897_SANGER_5_FBgn0035160-hng3 8 0.972818 23788.3 1 3 CACCTG TCGACAGACAC + +4 cisbp__M4823-hng3 8 0.972818 23788.3 1 3 CACCTG TCGACAGACAC - +4 tfdimers__MD00202-Taf7-Tbp 18 0.973135 23796.1 1 6 CACCTG AAAAAATATAAATTTATATTTATA + +4 dbcorrdb__YY1__ENCSR000BKD_1__m1-CG10431-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 12 0.973352 23801.4 1 6 CACCTG GGCCAAAATGGCGGCCGCGG + +4 hocomoco__ATF2_HUMAN.H11MO.1.B-Atf6-CrebA-Jra-Xbp1-cnc-kay 7 0.973352 23801.4 1 6 CACCTG AAATGATGACATCATCATTT + +4 dbcorrdb__RAD21__ENCSR000EHX_1__m4-vtd 6 0.973352 23801.4 1 6 CACCTG TTTTTTGGCTTTTGAAAAAT - +4 dbcorrdb__YY1__ENCSR000BLT_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 0 0.973352 23801.4 1 6 CACCTG CCGCGGCCGCCATTTTGGCC - +4 dbcorrdb__YY1__ENCSR000BPM_1__m1-CG10431-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 14 0.973352 23801.4 1 6 CACCTG CGCGGCCGCCATCTTGGCCG - +4 cisbp__M2028-abd-A-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG9876-Dfd-E5-ems-en-eve-ftz-hbn-ind-lab-lbe-lbl-Lim3-otp-pb-pdm3-Pph13-ro-Rx-Scr-slou-tup-Ubx-unpg-Vsx1-zen-zen2 0 0.973416 23802.9 1 6 CACCTG TTAATGA + +4 idmmpmm__Ubx-Antp-C15-CG4328-CG9876-CG15696-CG32532-CG34031-Dbx-Dfd-Dll-E5-HGTX-Lmx1a-NK7.1-OdsH-Scr-Ubx-Vsx1-Vsx2-abd-A-ap-bsh-btn-ems-en-exex-ftz-hbn-ind-inv-lab-lms-pb-repo-slou-tup-unc-4-unpg-zen2 0 0.973416 23802.9 1 6 CACCTG TAATTAA + +4 jaspar__MA0219.1-Antp-Awh-C15-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim3-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-en-eve-ftz-hbn-ind-lab-lbe-lbl-otp-pb-pdm3-ro-slou-tup-unpg-zen-zen2 0 0.973416 23802.9 1 6 CACCTG TTAATGA + +4 scertf__macisaac.MATA1 1 0.973416 23802.9 1 6 CACCTG GCACAAT + +4 cisbp__M4993-H2.0 0 0.973416 23802.9 1 6 CACCTG TTAATTA - +4 predrem__nrMotif882 2 0.973416 23802.9 1 5 CACCTG GCATTCT + +4 elemento__AAGCGCA 2 0.973416 23802.9 1 5 CACCTG TGCGCTT - +4 elemento__ATGAGCA 2 0.973416 23802.9 1 5 CACCTG TGCTCAT - +4 predrem__nrMotif613 2 0.973416 23802.9 1 5 CACCTG TGAGTCT - +4 elemento__CATCGTC -2 0.973416 23802.9 1 4 CACCTG CATCGTC + +4 elemento__CGCGAGA -2 0.973416 23802.9 1 4 CACCTG TCTCGCG - +4 cisbp__M2049-al-ap-Awh-C15-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-ind-inv-lab-lbl-Lim3-OdsH-Optix-otp-pb-pdm3-Pph13-repo-ro-Rx-unc-4-unpg-Vsx1-Vsx2-zfh2 -3 0.973416 23802.9 1 3 CACCTG CTAATTA + +4 hdpi__USP39-Usp39 -3 0.973416 23802.9 1 3 CACCTG TTGGAAA + +4 jaspar__MA0241.1-Awh-C15-CG9876-CG18599-CG32532-CG34367-E5-Lim3-OdsH-Optix-Pph13-Rx-Vsx1-Vsx2-al-ap-ems-en-eve-ind-inv-lab-lbl-otp-pb-repo-ro-unc-4-unpg-zfh2 -3 0.973416 23802.9 1 3 CACCTG CTAATTA + +4 predrem__nrMotif570 -3 0.973416 23802.9 1 3 CACCTG CTTTGCT + +4 flyfactorsurvey__CG18599_SOLEXA_FBgn0038592-Antp-Awh-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Pph13-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-eve-ftz-hbn-ind-lab-lbe-lbl-otp-pb-ro-unpg-zen-zen2 5 0.973416 23802.9 1 2 CACCTG TTAATTA + +4 tfdimers__MD00063-Stat92E 0 0.973439 23803.5 1 6 CACCTG ATTTTGATTTCCAGGAAATCAAAAT + +4 tfdimers__MD00373-Stat92E-Taf7-Tbp 19 0.973439 23803.5 1 6 CACCTG TTTTTTTTTTCTTTTTCTATTTTTT + +4 tfdimers__MD00367-cad 19 0.973454 23803.9 1 6 CACCTG ATTATATATTTATTGGGAAAAAATTAT + +4 tfdimers__MD00395-oc-scro 11 0.973539 23806 1 6 CACCTG TATTAATATAATCCTTGAGTGAATTA - +4 taipale__CUX2_DBD_ATCRATNNNNNNATCRAT-ct 5 0.973555 23806.3 1 6 CACCTG ATCGATAAAATTATCGAT + +4 transfac_pro__M03953-ct 5 0.973555 23806.3 1 6 CACCTG ATCGATAAAATTATCGAT + +4 transfac_pro__M07790-Antp-Awh-Dfd-E5-ems-eve-exex-ind-lab-lbl-Lim3-pb-pdm3-repo-Scr-Ubx 5 0.973555 23806.3 1 6 CACCTG GTAATTAGCGCTAATTAG + +4 predrem__nrMotif1133 0 0.973895 23814.6 1 6 CACCTG CAACAAAAA + +4 predrem__nrMotif1377 2 0.973895 23814.6 1 6 CACCTG AATAACAAT + +4 predrem__nrMotif1879 2 0.973895 23814.6 1 6 CACCTG GGACTCTGA + +4 predrem__nrMotif306 1 0.973895 23814.6 1 6 CACCTG CCACTCTCT + +4 cisbp__M4843-al-ap-CG11294-CG32532-CG34367-CG4328-CG9876-E5-ems-en-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1 1 0.973895 23814.6 1 6 CACCTG CTAATTAAA - +4 cisbp__M5253-Antp-OdsH-repo-Scr-tup-Ubx-unc-4-Vsx2 0 0.973895 23814.6 1 6 CACCTG TCAATTAAG - +4 flyfactorsurvey__tup_SOLEXA_10_FBgn0003896-Antp-OdsH-Scr-Ubx-Vsx2-repo-tup-unc-4 0 0.973895 23814.6 1 6 CACCTG TCAATTAAG - +4 predrem__nrMotif645 3 0.973895 23814.6 1 6 CACCTG TGAAATCCC - +4 stark__YTAATGAVS 1 0.973895 23814.6 1 6 CACCTG CTTCATTAA - +4 yetfasco__YDR310C_478 2 0.973895 23814.6 1 6 CACCTG AAAATTTTT - +4 predrem__nrMotif1157 -1 0.973895 23814.6 1 5 CACCTG TTCTGATTT + +4 cisbp__M6555 -1 0.973895 23814.6 1 5 CACCTG TCATTATCG - +4 cisbp__M4804-CG11085-Dr-lms-Ubx -2 0.973895 23814.6 1 4 CACCTG CCAATTAAA - +4 cisbp__M5046-al-ap-CG15696-CG32532-CG34367-CG4328-CG9876-Dll-en-exex-hbn-HGTX-inv-Lim3-lms-Lmx1a-OdsH-repo-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 5 0.973895 23814.6 1 4 CACCTG CTAATTAAG - +4 flyfactorsurvey__AbdB_Cell_FBgn0000015-Abd-B 5 0.973895 23814.6 1 4 CACCTG TCATAAAAC - +4 flyfactorsurvey__inv_SOLEXA_5_FBgn0001269-CG4328-CG9876-CG32532-CG34367-Dll-HGTX-Lim3-Lmx1a-OdsH-Rx-Ubx-Vsx1-Vsx2-al-ap-en-exex-inv-lms-repo-slou-unc-4-unpg 5 0.973895 23814.6 1 4 CACCTG CTAATTAAG - +4 predrem__nrMotif996 5 0.973895 23814.6 1 4 CACCTG ACAGAGACT - +4 taipale__HOXB5_DBD_NNYMATTANN-abd-A-acj6-Antp-ap-Awh-btn-CG11294-CG18599-CG32532-CG9876-Dr-E5-ems-en-eve-ftz-hbn-HGTX-lab-Lim1-Lim3-lms-Lmx1a-otp-pb-PHDP-Pph13-repo-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen2 2 0.973898 23814.7 1 6 CACCTG ACTAATTAAA + +4 taipale_cyt_meth__ONECUT1_NYATCGATYN_eDBD-onecut 1 0.973898 23814.7 1 6 CACCTG GTATCGATCG + +4 taipale_cyt_meth__SOX3_NGAACAATGN_FL_repr-D-Sox21a-Sox21b-SoxN 2 0.973898 23814.7 1 6 CACCTG CTCACAATGG + +4 transfac_pro__M03204 4 0.973898 23814.7 1 6 CACCTG ACGCCGCCAA + +4 transfac_pro__M05103 4 0.973898 23814.7 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05135 4 0.973898 23814.7 1 6 CACCTG AGGCCGCCCA + +4 transfac_pro__M05141 4 0.973898 23814.7 1 6 CACCTG ATGCCGCCCA + +4 cisbp__M4852-al-bsh-CG11085-CG11294-CG15696-CG32532-CG34367-CG4328-CG9876-Dll-Dr-en-hbn-inv-lab-Lim3-lms-Lmx1a-OdsH-otp-repo-Rx-slou-Ubx-unc-4-unpg-Vsx1-Vsx2 2 0.973898 23814.7 1 6 CACCTG GCTAATTAAG - +4 flyfactorsurvey__CG33980_SOLEXA_2_0_FBgn0053980-CG4328-CG9876-CG11085-CG11294-CG15696-CG32532-CG34367-Dll-Dr-Lim3-Lmx1a-OdsH-Rx-Ubx-Vsx1-Vsx2-al-bsh-en-ey-hbn-inv-lab-lms-otp-repo-slou-toy-unc-4-unpg 2 0.973898 23814.7 1 6 CACCTG GCTAATTAAG - +4 transfac_public__M00464-dve-vvl 3 0.973898 23814.7 1 6 CACCTG ATTAACATAA - +4 transfac_pro__M05027 5 0.973898 23814.7 1 5 CACCTG AGGCCGACAA + +4 transfac_pro__M07327 5 0.973898 23814.7 1 5 CACCTG GCCATTAAAT - +4 cisbp__M6297-abd-A-Ubx -2 0.973898 23814.7 1 4 CACCTG CATTAATCAA + +4 flyfactorsurvey__hb_NAR_FBgn0001180-hb-rn 6 0.973898 23814.7 1 4 CACCTG CAAAAAAAAA + +4 predrem__nrMotif1575 6 0.973898 23814.7 1 4 CACCTG TTCTGTCATT + +4 transfac_pro__M06327 6 0.973898 23814.7 1 4 CACCTG CAAAATCATA + +4 cisbp__M5319-Irbp18-nej-slbo-Xrp1 6 0.973898 23814.7 1 4 CACCTG ATTGCGCAAT - +4 taipale__CEBPG_full_NTTRCGCAAY-Irbp18-nej-slbo-Xrp1 6 0.973898 23814.7 1 4 CACCTG ATTGCGCAAT - +4 transfac_pro__M03195 -2 0.973898 23814.7 1 4 CACCTG TCGGCGGCAT - +4 transfac_pro__M07414-CG7786-gt-Irbp18-Myc-nej-Pdp1-slbo-vri-Xrp1 7 0.973898 23814.7 1 3 CACCTG ATTGCGTAAT + +4 homer__GTCATAAAAN_Cdx2-Abd-B-cad-eve 7 0.973898 23814.7 1 3 CACCTG ATTTTATGAC - +4 taipale_cyt_meth__HOXC9_GTCGTAAAAN_FL_meth-Abd-B-cad 7 0.973898 23814.7 1 3 CACCTG GTTTTACGAC - +4 taipale_cyt_meth__HOXC9_GYAATAAAAN_FL_meth-Abd-B-cad-eve 7 0.973898 23814.7 1 3 CACCTG GTTTTATTGC - +4 cisbp__M5334-ct 8 0.973898 23814.7 1 2 CACCTG TTATCGATTA + +4 cisbp__M5336-ct 8 0.973898 23814.7 1 2 CACCTG TTATCGATTA + +4 taipale__CUX1_DBD_TAATCRATAN_repr-ct 8 0.973898 23814.7 1 2 CACCTG TTATCGATTA - +4 taipale__CUX2_DBD_TAATCRATAN-ct 8 0.973898 23814.7 1 2 CACCTG TTATCGATTA - +4 transfac_pro__M09161-brm-CG7839-maf-S-SREBP-vtd 0 0.974654 23833.2 1 6 CACCTG TTTTTTTTTTTGTCTTTTTCT + +4 cisbp__M3250-bin-fd59A 5 0.974704 23834.4 1 6 CACCTG AAACAAACAATC + +4 taipale_cyt_meth__BARX2_NWAAAYCATTAN_FL_meth_repr 3 0.974704 23834.4 1 6 CACCTG AAAAACCATTAC + +4 taipale_cyt_meth__KLF15_NCCMCGCCCMYN_FL_meth-btd-cbt-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps-Stat92E 6 0.974704 23834.4 1 6 CACCTG GCCACGCCCCCC + +4 transfac_pro__M05178 6 0.974704 23834.4 1 6 CACCTG ATTAACGGCCTC + +4 transfac_pro__M01662-NFAT 1 0.974704 23834.4 1 6 CACCTG TTTCCGCGGAAA - +4 transfac_public__M00130-bin-fd59A 5 0.974704 23834.4 1 6 CACCTG AAACAAACAATC - +4 transfac_pro__M05533 -1 0.974704 23834.4 1 5 CACCTG GGCTGTGCTCCG - +4 transfac_pro__M06246 7 0.974704 23834.4 1 5 CACCTG TGCTCTTCATCA - +4 transfac_pro__M06739-CG12299-CG31365-dati 7 0.974704 23834.4 1 5 CACCTG GATTCTTCATAA - +4 transfac_pro__M06928-Dad -1 0.974704 23834.4 1 5 CACCTG ATTTGACGAAAC - +4 hocomoco__HME1_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG9876-CG11085-CG18599-CG34367-Dll-Dr-E5-Lim3-OdsH-Pph13-Rx-Vsx1-Vsx2-ap-ems-en-eve-exex-gsb-gsb-n-ind-inv-lab-lbe-lms-otp-pb-pdm3-prd-slou-unpg-zen2 9 0.97495 23840.4 1 6 CACCTG GCTAATTACCCAATTAT + +4 hocomoco__NRF1_HUMAN.H11MO.0.A-E2f1-ewg 4 0.97495 23840.4 1 6 CACCTG CCTGCGCATGCGCAGTG - +4 taipale__FOXG1_DBD_ATAAACAANWGTAAACA_repr-slp2 4 0.97495 23840.4 1 6 CACCTG TGTTTACAATTGTTTAT - +4 transfac_pro__M02832 3 0.97495 23840.4 1 6 CACCTG TTATCCATCCCATAATA - +4 transfac_pro__M07741-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.97495 23840.4 1 6 CACCTG AAACAATAGCATTGTTT - +4 transfac_pro__M07975-bbx-D-fd59A-fkh-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.97495 23840.4 1 6 CACCTG AAACAATAACATTGTTT - +4 hocomoco__HXC10_HUMAN.H11MO.0.D-Abd-B-CTCF-bab1-cad 4 0.975464 23853 1 6 CACCTG TTTTTAATTTTTTTATTAC + +4 taipale__PAX6_DBD_TTTYACGCWTGANTGMNYN_repr-ey-Poxm-sv-toy 5 0.975464 23853 1 6 CACCTG TTTCACGCATGACTGCACA + +4 transfac_pro__M06352 5 0.975464 23853 1 6 CACCTG TCCCCCCCCGGCTACGAAG - +4 taipale_tf_pairs__E2F3_HES7_NNNNGCGCSNNNNNCACGTGNN_CAP-E2f1 14 0.975652 23857.6 1 6 CACCTG TATGGCGCCATCGGCACGTGCC + +4 cisbp__M5827-D-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TCAATAACATTGA + +4 cisbp__M5871-D-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TCAATAACATTGA + +4 cisbp__M5872-D-Sox15-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TGAATAACATTCA + +4 taipale__SRY_DBD_TCAATANCATTGA-D-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TCAATAACATTGA + +4 taipale__SRY_DBD_TGAATANCATTCA-D-Sox15-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TGAATAACATTCA + +4 taipale_cyt_meth__EGR4_NMCGCCCACGCAN_eDBD_meth-btd-klu-Spps-sr 6 0.975852 23862.5 1 6 CACCTG CCCGCCCACGCAC + +4 taipale_tf_pairs__POU2F1_SOX15_WTGMATAACAATR_CAP_2-nub-pdm2 1 0.975852 23862.5 1 6 CACCTG TTGAATAACAATA + +4 taipale__SOX21_DBD_TCAATNNNATTGA-D-Sox21a-Sox21b-SoxN 5 0.975852 23862.5 1 6 CACCTG TCAATAACATTGA - +4 transfac_pro__M00809-bin-croc-fd59A-fkh-foxo-slp1 6 0.975852 23862.5 1 6 CACCTG TAAATAAACAATC - +4 transfac_pro__M07323 0 0.975852 23862.5 1 6 CACCTG TACTTTCATTTTC - +4 transfac_pro__M08982-pho-phol-RpII215 3 0.975852 23862.5 1 6 CACCTG GGCCGCCATTTTG - +4 cisbp__M4865-Aef1-CG4360 8 0.975852 23862.5 1 5 CACCTG ACAACAACAACCC - +4 hocomoco__FOXJ3_HUMAN.H11MO.1.B 8 0.975852 23862.5 1 5 CACCTG TAAACAAAAACAA - +4 stark__TNRCGCNYNATTAATY 3 0.975899 23863.7 1 6 CACCTG TAACGCACAATTAATC + +4 taipale__EGR4_DBD_NNMCGCCCACGCANNN-klu-sr 3 0.975899 23863.7 1 6 CACCTG TTACGCCCACGCATTT + +4 taipale_cyt_meth__SOX8_ACAATNNNNNNATTGT_FL_meth-Sox100B 8 0.975899 23863.7 1 6 CACCTG ACAATGGATCCATTGT + +4 cisbp__M5370-klu-sr 11 0.975899 23863.7 1 5 CACCTG TTACGCCCACGCATTT - +4 cisbp__M5742-acj6-vvl -3 0.975899 23863.7 1 3 CACCTG CTCATTAATTATGCAT - +4 transfac_pro__M01016-Sox15 0 0.976009 23866.4 1 6 CACCTG AACAAT + +4 transfac_pro__M03854 0 0.976009 23866.4 1 6 CACCTG AAACAA - +4 hdpi__UQCRB-UQCR-14-UQCR-14L -2 0.976009 23866.4 1 4 CACCTG CGTCAT - +4 hdpi__GIT2-Git 3 0.976009 23866.4 1 3 CACCTG TTGCAA + +4 hdpi__DUSP22-CG10089 3 0.976009 23866.4 1 3 CACCTG TTTCAT - +4 hdpi__NFIX-NfI 4 0.976009 23866.4 1 2 CACCTG TTTGCA - +4 cisbp__M1129-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 2 0.97618 23870.5 1 6 CACCTG AAAACAAT + +4 cisbp__M5196-ap-C15-CG15696-CG32532-CG34031-CG9876-Dll-Dr-E5-en-exex-ftz-ind-lms-NK7.1-otp-Pph13-ro-Rx-slou-tup-Ubx-unpg-Vsx1 2 0.97618 23870.5 1 6 CACCTG TTTAATTA + +4 flyfactorsurvey__Slou_Cell_FBgn0002941-C15-CG9876-CG15696-CG32532-CG34031-Dll-E5-NK7.1-Pph13-Rx-Ubx-Vsx1-ap-en-exex-ftz-ind-lms-otp-ro-slou-tup-unpg 2 0.97618 23870.5 1 6 CACCTG TTTAATTG + +4 taipale_cyt_meth__DLX4_NYAATTAN_FL-Dll 1 0.97618 23870.5 1 6 CACCTG GTAATTAT + +4 taipale_cyt_meth__LHX5_SYAATTAN_FL-Antp-ap-CG11294-CG32532-CG4328-CG9876-en-HGTX-inv-lab-Lim1-Lim3-lms-Lmx1a-otp-repo-Rx-Scr-slou-Ubx-unpg-Vsx1 1 0.97618 23870.5 1 6 CACCTG GTAATTAA + +4 taipale_cyt_meth__PRRX2_CYAATTAN_FL_meth-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG9876-E5-ems-en-ey-ind-inv-lab-lbe-Lim1-Lim3-lms-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-toy-unc-4-unpg-Vsx1-V 1 0.97618 23870.5 1 6 CACCTG CTAATTAA + +4 yetfasco__YML027W_498-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-ap-ems-en-otp-repo-ro-unc-4-unpg-zen2-zfh2 1 0.97618 23870.5 1 6 CACCTG TTAATTAA + +4 cisbp__M1184 0 0.97618 23870.5 1 6 CACCTG TATATTAA - +4 cisbp__M1375-Myb-Pbp95 1 0.97618 23870.5 1 6 CACCTG TGACTCGG - +4 neph__UW.Motif.0034-Mef2-rump 0 0.97618 23870.5 1 6 CACCTG TATTTTTA - +4 predrem__nrMotif1155 2 0.97618 23870.5 1 6 CACCTG TGCACTGA - +4 elemento__ATTTGCAT-acj6-nub-pdm2-SoxN-vvl -1 0.97618 23870.5 1 5 CACCTG ATTTGCAT + +4 elemento__CATCATCA 3 0.97618 23870.5 1 5 CACCTG CATCATCA + +4 tiffin__TIFDMEM0000017-fkh 3 0.97618 23870.5 1 5 CACCTG AAATATTT + +4 elemento__TGATGCCC 3 0.97618 23870.5 1 5 CACCTG GGGCATCA - +4 cisbp__M0249 -2 0.97618 23870.5 1 4 CACCTG CATATATG + +4 jaspar__MA0542.1 -2 0.97618 23870.5 1 4 CACCTG TCTTATCA + +4 cisbp__M2335 -2 0.97618 23870.5 1 4 CACCTG TCTTATCA - +4 cisbp__M4785-btn 4 0.97618 23870.5 1 4 CACCTG TCATTAAG - +4 cisbp__M4977-Antp-ap-bsh-btn-CG18599-E5-ems-eve-ftz-lab-pb-Scr-Ubx-zen-zen2 4 0.97618 23870.5 1 4 CACCTG TAATTAAC - +4 flyfactorsurvey__CG34031_SOLEXA_FBgn0054031-CG15696-CG34031-NK7.1-Ubx-lms-slou 4 0.97618 23870.5 1 4 CACCTG CAATTAAA - +4 flyfactorsurvey__Ftz_Cell_FBgn0001077-Antp-CG18599-E5-Scr-Ubx-ap-bsh-btn-ems-eve-ftz-lab-pb-zen-zen2 4 0.97618 23870.5 1 4 CACCTG TCATTAAC - +4 predrem__nrMotif348 -2 0.97618 23870.5 1 4 CACCTG CATTCTTA - +4 cisbp__M1103-Antp-HGTX-Scr -3 0.97618 23870.5 1 3 CACCTG CTAATTAA + +4 taipale_cyt_meth__EMX1_NYAATTAN_eDBD-Antp-Awh-btn-C15-CG18599-E5-ems-en-eve-exex-ind-inv-lab-Lim3-lms-pb-Scr-slou-Ubx-unpg-Vsx1-Vsx2 5 0.97618 23870.5 1 3 CACCTG CTAATTAG + +4 transfac_pro__M01795 -3 0.97618 23870.5 1 3 CACCTG ATGACTAA + +4 cisbp__M1244 6 0.97618 23870.5 1 2 CACCTG ATTATGCA - +4 taipale_cyt_meth__FOXP1_NTGTTTRNNNNNNNNNNNNNNNNWCAACAN_eDBD_meth_repr-bin-fd102C-fd19B-fkh-FoxK-FoxL1-foxo-FoxP-slp1-slp2 13 0.976182 23870.6 1 6 CACCTG TTGTTTACCATCGCACCCCATGCACAACAA + +4 cisbp__M2567-Hsf 2 0.976391 23875.7 1 6 CACCTG AGAAATTTCTAGAAA + +4 cisbp__M5816-D-Sox15-Sox21a-Sox21b-SoxN 6 0.976391 23875.7 1 6 CACCTG ATGAATAACATTCAT + +4 transfac_public__M00165-Hsf 2 0.976391 23875.7 1 6 CACCTG AGAAATTTCTAGAAA + +4 taipale_cyt_meth__FOXE1_NMYTAAAYAAACAWN_eDBD_meth-bin-croc-fd59A-fkh-nej -1 0.976391 23875.7 1 5 CACCTG CCCTAAATAAACAAT + +4 cisbp__M5698-Gsc-oc 11 0.976391 23875.7 1 4 CACCTG GTTAATCCGATTAAC + +4 taipale__OTX1_DBD_NNTAATCCGATTANN-Gsc-oc 11 0.976391 23875.7 1 4 CACCTG GTTAATCCGATTAAC + +4 taipale_cyt_meth__YY2_NKCCGCCATTTTGN_FL-pho-phol-RpII215 0 0.976392 23875.7 1 6 CACCTG GTCCGCCATTTTGA + +4 taipale_cyt_meth__ZNF410_NYANCCCATAATAN_eDBD_meth 3 0.976392 23875.7 1 6 CACCTG ACATCCCATAATAT + +4 transfac_public__M00161-nub-pdm2-vvl 6 0.976392 23875.7 1 6 CACCTG CTAATTTGCATATT + +4 taipale_cyt_meth__ZNF454_TRGCGCCGGCGCYN_eDBD_repr-brk 9 0.976392 23875.7 1 5 CACCTG TGGCGCCGGCGCCA + +4 transfac_pro__M05336-klu-sr -1 0.976392 23875.7 1 5 CACCTG TCCCGCCCACGCCC - +4 cisbp__M2386-cad-eve 0 0.976456 23877.3 1 6 CACCTG GCCATAAATCA + +4 jaspar__MA0594.1-cad-eve 0 0.976456 23877.3 1 6 CACCTG GCCATAAATCA + +4 transfac_pro__M00332-jumu 3 0.976456 23877.3 1 6 CACCTG AACGACGCTTT + +4 hdpi__HOXB13 2 0.976456 23877.3 1 6 CACCTG TTTTCATTAAA - +4 predrem__nrMotif274 5 0.976456 23877.3 1 6 CACCTG TTTGAAACAAA - +4 transfac_pro__M05591 2 0.976456 23877.3 1 6 CACCTG TCCGCATTCTC - +4 transfac_pro__M06961 3 0.976456 23877.3 1 6 CACCTG GTTTGCATAAT - +4 taipale_cyt_meth__HOXC13_NCCAATAAAAN_eDBD -1 0.976456 23877.3 1 5 CACCTG CCCAATAAAAC + +4 flyfactorsurvey__ss_tgo_SANGER_10_FBgn0003513-ss-tgo -2 0.976456 23877.3 1 4 CACCTG CATTGCGTGAC - +4 cisbp__M4837-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 8 0.976456 23877.3 1 3 CACCTG GCCACGCCCAC - +4 flyfactorsurvey__CG3065_F1-3_SANGER_2.5_FBgn0034946-CG3065-CG42741-Klf15-Sp1-Spps-btd-cbt-dar1-luna 8 0.976456 23877.3 1 3 CACCTG GCCACGCCCAC - +4 yetfasco__YML076C_325 -2 0.976683 23882.8 1 4 CACCTG CCGAAAAAAAAAAAAAAAAAAAAAAACGG + +4 cisbp__M1990-abd-A-al-Antp-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-ey-hbn-ind-inv-lab-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-pdm3-PHDP-Pph13-repo-ro-Rx- 1 0.976927 23888.8 1 6 CACCTG TTAATTA + +4 elemento__TCCCCGC 0 0.976927 23888.8 1 6 CACCTG TCCCCGC + +4 elemento__TTCCCGC 0 0.976927 23888.8 1 6 CACCTG TTCCCGC + +4 flyfactorsurvey__CG4136_Cell_FBgn0029775-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-ems-en-eve-ey-h 1 0.976927 23888.8 1 6 CACCTG TTAATTA + +4 hdpi__TCEAL2 0 0.976927 23888.8 1 6 CACCTG GAAATGG + +4 jaspar__MA0169.1-B-H2 1 0.976927 23888.8 1 6 CACCTG TTAATTG + +4 predrem__nrMotif1504 0 0.976927 23888.8 1 6 CACCTG AGCATGA - +4 cisbp__M1974-Abd-B-cad -1 0.976927 23888.8 1 5 CACCTG TCATAAA - +4 elemento__AAATATT-fkh 2 0.976927 23888.8 1 5 CACCTG AATATTT - +4 jaspar__MA0165.1-Abd-B-cad -1 0.976927 23888.8 1 5 CACCTG TCATAAA - +4 swissregulon__hs__POU5F1.p2-nub-pdm2 2 0.976927 23888.8 1 5 CACCTG TTTGCAT - +4 cisbp__M2004-al-Antp-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-ey-gsb-gsb-n-hbn-ind-inv-lab-lbl-Lim1-Lim3-Lmx1a-OdsH-otp-pb-pdm3-Pph13-prd-repo-ro-Rx-Scr-slou-t -3 0.976927 23888.8 1 3 CACCTG TTAATTA + +4 cisbp__M2036-ap-Awh-CG18599-CG9876-Dfd-E5-ems-eve-hbn-ind-lbl-Lim3-OdsH-Optix-otp-pb-pdm3-Pph13-repo-ro-Rx-Ubx-unc-4-unpg-Vsx1-zen-zen2 -3 0.976927 23888.8 1 3 CACCTG CTAATTA + +4 cisbp__M4942-abd-A-al-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-E5-ems-en-eve-ey-ftz-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-OdsH-Optix-otp-pb-pdm3-PHDP-Pph13-re -3 0.976927 23888.8 1 3 CACCTG TTAATTA + +4 flyfactorsurvey__Ems_SOLEXA_FBgn0000576-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Optix-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-ems-en-eve-f -3 0.976927 23888.8 1 3 CACCTG TTAATTA + +4 jaspar__MA0195.1-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-al-ap-bsh-ems-en-eve-ey-gsb-gsb-n-hbn-ind-inv-lab-lbl-otp-pb -3 0.976927 23888.8 1 3 CACCTG TTAATTA + +4 jaspar__MA0228.1-Awh-CG9876-CG18599-Dfd-E5-Lim3-OdsH-Optix-Pph13-Rx-Ubx-Vsx1-ap-ems-eve-hbn-ind-lbl-otp-pb-pdm3-repo-ro-unc-4-unpg-zen-zen2 -3 0.976927 23888.8 1 3 CACCTG CTAATTA + +4 transfac_pro__M00980-Taf7-Tbp 4 0.976927 23888.8 1 3 CACCTG TTTATAC + +4 cisbp__M5068-abd-A-acj6-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG4328-CG9876-Dbx-Dfd-E5-ems-en-eve-exex-ey-ftz-hbn-HGTX-ind-lab-lbl-Lim1-Lim3-lms-Lmx1a-otp-pb-Pph13-repo-ro-Rx-Scr-slou-toy-Tr 4 0.976927 23888.8 1 3 CACCTG TAATTAA - +4 jaspar__MA0174.1-Dbx-cad 5 0.976927 23888.8 1 2 CACCTG TTTATTA + +4 dbcorrdb__YY1__ENCSR000BKU_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 14 0.976976 23890 1 6 CACCTG GGCCAAGATGGCGGCGGCGG + +4 dbcorrdb__YY1__ENCSR000EWF_1__m1-CG10431-CTCF-lid-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 9 0.976976 23890 1 6 CACCTG CGCGGCCGCCATCTTGGCCG + +4 homer__CARTGGAGCGCRYTTGCATT_LIN-15B 10 0.976976 23890 1 6 CACCTG CAATGGAGCGCGCTTGCATT + +4 cisbp__M4876-CG7368-CoRest-crol-ct-CTCF-l(3)neo38 14 0.976976 23890 1 6 CACCTG ATTATCCCCCCCCCCCCCCC - +4 dbcorrdb__EP300__ENCSR000DZT_1__m2-nej 5 0.976976 23890 1 6 CACCTG TATATTATATCATTAATTTA - +4 dbcorrdb__CEBPZ__ENCSR000EDO_1__m4-CG7839 15 0.976976 23890 1 5 CACCTG TTTCAATAATGAATGGACCA - +4 hdpi__ZBTB43 -2 0.977055 23891.9 1 4 CACCTG AATGA + +4 cisbp__M2502 0 0.977116 23893.4 1 6 CACCTG AAGTTTCTTTGTTTTTTT + +4 cisbp__M5335-ct 5 0.977116 23893.4 1 6 CACCTG ATCGATAATTTTATCGAT + +4 tfdimers__MD00301-E2f1 1 0.977193 23895.3 1 6 CACCTG ACTTTTTCTTCCCTTTTCCTTTTTT - +4 transfac_pro__M00389 14 0.977306 23898.1 1 6 CACCTG CTGTTGCAGCTTTTTGCTCGGCCCTT + +4 jaspar__MA0398.1 2 0.977387 23900 1 6 CACCTG AAAATTTTT + +4 cisbp__M2203 2 0.977387 23900 1 6 CACCTG AAAATTTTT - +4 hocomoco__PDX1_MOUSE.H11MO.0.B-Antp-Dfd-Scr-btn-ems-eve-ind-pb-zen2 0 0.977387 23900 1 6 CACCTG GTCATTAAT - +4 predrem__nrMotif710 2 0.977387 23900 1 6 CACCTG TGCTTCTGA - +4 yetfasco__YMR019W_2107 3 0.977387 23900 1 6 CACCTG TCGGCCCGA - +4 predrem__nrMotif894 4 0.977387 23900 1 5 CACCTG TTTTCTTCT + +4 scertf__macisaac.SWI4 -1 0.977387 23900 1 5 CACCTG ACGCGAAAA + +4 taipale__JDP2_full_ATGASTCAT-cnc-foxo-Jra-kay-Myc-NFAT-Stat92E 4 0.977387 23900 1 5 CACCTG ATGACTCAT + +4 hocomoco__ZN333_HUMAN.H11MO.0.D -1 0.977387 23900 1 5 CACCTG TCATTATCG - +4 elemento__CCCATTGGC -2 0.977387 23900 1 4 CACCTG CCCATTGGC + +4 predrem__nrMotif400 -3 0.977387 23900 1 3 CACCTG ATGCATTGT + +4 predrem__nrMotif391 6 0.977387 23900 1 3 CACCTG GAAATGCAA - +4 c2h2_zfs__M4331-sens-sens-2 4 0.977417 23900.8 1 6 CACCTG AAATCACAGC + +4 cisbp__M1111 0 0.977417 23900.8 1 6 CACCTG AACCAATATT + +4 predrem__nrMotif1952 3 0.977417 23900.8 1 6 CACCTG AGATTTCTCT + +4 swissregulon__sacCer__PDR3-NFAT 1 0.977417 23900.8 1 6 CACCTG TTTCCGCGGA + +4 tiffin__TIFDMEM0000012 3 0.977417 23900.8 1 6 CACCTG TCGAAATTTA + +4 transfac_pro__M04990 4 0.977417 23900.8 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M04998 4 0.977417 23900.8 1 6 CACCTG ACGCCGCCAA + +4 transfac_pro__M04999 4 0.977417 23900.8 1 6 CACCTG AGGCCGCCCA + +4 transfac_pro__M05145 4 0.977417 23900.8 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M06953 0 0.977417 23900.8 1 6 CACCTG TAATTTAATA + +4 transfac_pro__M07698-retn 4 0.977417 23900.8 1 6 CACCTG TAATTAATTA + +4 cisbp__M5187-sens-sens-2 4 0.977417 23900.8 1 6 CACCTG AAATCACAGC - +4 cisbp__M5555-Abd-B 4 0.977417 23900.8 1 6 CACCTG TTTTTACGAC - +4 flyfactorsurvey__sens_SANGER_10_FBgn0002573-sens-sens-2 4 0.977417 23900.8 1 6 CACCTG AAATCACGGC - +4 taipale__HOXD11_DBD_GTCGTWAAAN-Abd-B 4 0.977417 23900.8 1 6 CACCTG TTTTTACGAC - +4 taipale_cyt_meth__HOXD9_RTCGTAAAAN_eDBD_meth-Abd-B-cad 4 0.977417 23900.8 1 6 CACCTG GTTTTACGAC - +4 stark__MRYTTCCGYY-dl -1 0.977417 23900.8 1 5 CACCTG AACTTCCGCC + +4 transfac_pro__M07514-Taf1 5 0.977417 23900.8 1 5 CACCTG GGCGCCGCCA + +4 homer__GGCGGGAAAH_E2F4-Dp-E2f1-E2f2-eve -1 0.977417 23900.8 1 5 CACCTG ATTTCCCGCC - +4 predrem__nrMotif242 5 0.977417 23900.8 1 5 CACCTG TTTGATTTCT - +4 transfac_pro__M05494-klu-sr 5 0.977417 23900.8 1 5 CACCTG CCGCCCACGC - +4 hocomoco__HXC9_HUMAN.H11MO.0.C-Abd-B-cad-eve 6 0.977417 23900.8 1 4 CACCTG TTTTATTGCC + +4 transfac_pro__M05171 6 0.977417 23900.8 1 4 CACCTG ATGCCGCCCC + +4 hocomoco__HXB7_HUMAN.H11MO.0.C-Ubx-abd-A -2 0.977417 23900.8 1 4 CACCTG CATTAATCAA - +4 homer__GGYCATAAAW_caudal-Abd-B-cad-eve 6 0.977417 23900.8 1 4 CACCTG TTTTATGGCC - +4 predrem__nrMotif393 6 0.977417 23900.8 1 4 CACCTG AAAAAGCAAA - +4 taipale_cyt_meth__HOXC9_GTCGTAAAAN_FL-Abd-B-cad 7 0.977417 23900.8 1 3 CACCTG ATTTTACGAC - +4 cisbp__M2597 6 0.978111 23917.8 1 6 CACCTG CATTATCATCAT - +4 transfac_pro__M06412-CG2120 5 0.978111 23917.8 1 6 CACCTG TATTTTATCAAA - +4 transfac_pro__M06770-CG2120 6 0.978111 23917.8 1 6 CACCTG TCAGACGGCCCG - +4 cisbp__M5103-Mes2 7 0.978111 23917.8 1 5 CACCTG TTTAAGCCAAAA + +4 flyfactorsurvey__Mes2_SANGER_5_FBgn0037207-Mes2 7 0.978111 23917.8 1 5 CACCTG TTTAAGCCAAAA + +4 homer__VDTTTCCCGCCA_E2F7-E2f2 7 0.978111 23917.8 1 5 CACCTG CTTTTCCCGCCA + +4 transfac_pro__M00923-Adf1-Trl 13 0.978161 23919 1 6 CACCTG GCGCTGCCGCCGCTGCCTGCG + +4 transfac_pro__M09096-E2f2 2 0.978161 23919 1 6 CACCTG TTTACGTTTTTGGCGGGAAAA + +4 hocomoco__MSX3_MOUSE.H11MO.0.D-Dr-HGTX-ind 11 0.978351 23923.6 1 6 CACCTG TAATTGGTTTTTAATTG + +4 transfac_pro__M01401-al-ap-Awh-CG11085-CG18599-CG32532-CG34367-CG9876-E5-ems-en-eve-inv-Lim3-OdsH-otp-pdm3-Pph13-repo-Rx-slou-unc-4-unpg-Vsx1-zfh2 5 0.978351 23923.6 1 6 CACCTG TGCATTAATTAATGCGA + +4 cisbp__M6095-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 11 0.978351 23923.6 1 6 CACCTG GATGAATGGCATTCATG - +4 transfac_pro__M01353-Antp-CG32532-CG4328-Dfd-Lim1-Lim3-Lmx1a-Scr-vvl 10 0.978351 23923.6 1 6 CACCTG AGTATTTAATTAATTCG - +4 transfac_pro__M01369-abd-A-Antp-Awh-CG18599-CG32532-CG4328-Dfd-gsb-gsb-n-Lmx1a-prd-Scr-Ubx-zfh2 10 0.978351 23923.6 1 6 CACCTG TATTGTTAATTAATTCG - +4 transfac_pro__M07914-CG10654 7 0.97884 23935.6 1 6 CACCTG TATTTCGCGCCGCGAATTA - +4 transfac_public__M00135-nub-pdm2-vvl 12 0.97884 23935.6 1 6 CACCTG CCGAAATTTGCATATTGAT - +4 tfdimers__MD00214 8 0.979071 23941.2 1 6 CACCTG AAAAAAATTACTCAATATATTA + +4 cisbp__M0587 1 0.979119 23942.4 1 6 CACCTG CAAAATTTTAAAA + +4 taipale_cyt_meth__ARGFX_YTAATCTAATTAG_eDBD-al-ap-Awh-bsh-CG11294-CG18599-CG32532-CG34367-CG9876-Drgx-E5-ems-ey-hbn-Lim3-OdsH-Optix-otp-Pph13-repo-Rx-Traf4-unc-4-Vsx1-Vsx2 2 0.979119 23942.4 1 6 CACCTG TTAATTTAATTAG + +4 stark__STATAWAWRSVVV-RpII215-Taf1-Tbp 2 0.979119 23942.4 1 6 CACCTG TTTCCATATATAC - +4 taipale_cyt_meth__EGR4_NMCGCCCACGCAN_eDBD-klu-sr 1 0.979119 23942.4 1 6 CACCTG GTGCGTGGGCGGG - +4 transfac_pro__M05279 4 0.979119 23942.4 1 6 CACCTG TGTATACGCGGCC - +4 cisbp__M1932 9 0.979119 23942.4 1 4 CACCTG CAATAATTGGACC + +4 jaspar__MA0110.2 9 0.979119 23942.4 1 4 CACCTG CAATAATTGGACC - +4 cisbp__M5870-Sox15 7 0.979187 23944.1 1 6 CACCTG AACAATATTCATTGTT + +4 taipale__SRY_DBD_AACAATNNNCATTGTT-Sox15 7 0.979187 23944.1 1 6 CACCTG AACAATATTCATTGTT + +4 taipale_cyt_meth__E2F2_NWTTTGGCGCCAWWWN_eDBD_meth-E2f1-E2f2 7 0.979187 23944.1 1 6 CACCTG ATTTTGGCGCCAATTT + +4 cisbp__M5211-sqz 12 0.979187 23944.1 1 4 CACCTG TTTTTTTTTATGTAGC - +4 flyfactorsurvey__sqz_SANGER_5_FBgn0010768-sqz 12 0.979187 23944.1 1 4 CACCTG TTTTTTTTTATGTAGC - +4 taipale__POU4F2_full_NTGMATAATTAATKAG-acj6-vvl -3 0.979187 23944.1 1 3 CACCTG CTCATTAATTATGCAT - +4 fantom__motif48_CANTCG -3 0.979301 23946.9 1 3 CACCTG CAATCG + +4 cisbp__M4820-CG11085-CG32532-E5-en-lms-NK7.1-slou-tup-unc-4-unpg 2 0.979405 23949.4 1 6 CACCTG TTTAATTG + +4 cisbp__M5310-bsh-Dr-en-inv-lbe-Lim3-Scr-Ubx-unpg 1 0.979405 23949.4 1 6 CACCTG TTAATTGG + +4 elemento__CACACGCA 0 0.979405 23949.4 1 6 CACCTG CACACGCA + +4 flyfactorsurvey__CG13424_Cell_FBgn0034520-CG32532-E5-NK7.1-PHDP-en-lms-slou-tup-unc-4-unpg 2 0.979405 23949.4 1 6 CACCTG ATTAATTG + +4 flyfactorsurvey__Sox15_SANGER_5_FBgn0005613-Sox15-Sox21a-SoxN 1 0.979405 23949.4 1 6 CACCTG AAACAATG + +4 stark__CACGCGMC-h 0 0.979405 23949.4 1 6 CACCTG CACGCGAC + +4 transfac_pro__M07332-vvl 2 0.979405 23949.4 1 6 CACCTG TAAATAAA + +4 transfac_pro__M07849-al-Antp-ap-Awh-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dr-Drgx-E5-ems-en-ey-gsb-gsb-n-inv-lab-lbe-Lim1-Lim3-Lmx1a-OdsH-otp-pdm3-Pph13-prd-repo-ro-Rx-Scr-toy-Traf4-unc-4- 1 0.979405 23949.4 1 6 CACCTG TTAATTAA + +4 cisbp__M1600-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b 2 0.979405 23949.4 1 6 CACCTG AAAACAAT - +4 flyfactorsurvey__H2.0_SOLEXA_FBgn0001170-CG4328-H2.0-Lmx1a 0 0.979405 23949.4 1 6 CACCTG TTAATAAA - +4 taipale__BSX_DBD_NYNATTAN-bsh-CG34367-Dr-Lim3-Scr-Ubx-unpg 1 0.979405 23949.4 1 6 CACCTG TTAATTGG - +4 elemento__AAATGGCG -1 0.979405 23949.4 1 5 CACCTG AAATGGCG + +4 elemento__AATCAGCG 3 0.979405 23949.4 1 5 CACCTG AATCAGCG + +4 neph__UW.Motif.0001-Jra-Mef2-Myc-Stat92E-bon-cnc-kay-nej-pan 3 0.979405 23949.4 1 5 CACCTG TGAGTCAT - +4 cisbp__M0148 4 0.979405 23949.4 1 4 CACCTG TCGAGAGT - +4 cisbp__M4856-CG15696-CG34031-lms-NK7.1-slou-Ubx 4 0.979405 23949.4 1 4 CACCTG CAATTAAA - +4 elemento__ATGGGCGG -2 0.979405 23949.4 1 4 CACCTG CCGCCCAT - +4 transfac_pro__M02015-bin-fd59A-fkh 4 0.979405 23949.4 1 4 CACCTG AACAAACA - +4 flyfactorsurvey__retn_SANGER_5_FBgn0004795-retn 5 0.979405 23949.4 1 3 CACCTG AATCAAAA + +4 cisbp__M1164-Antp-HGTX-lab-Scr 5 0.979405 23949.4 1 3 CACCTG TTAATTAG - +4 cisbp__M5166-retn 5 0.979405 23949.4 1 3 CACCTG AATCAAAA - +4 cisbp__M5658-NFAT 3 0.979601 23954.2 1 6 CACCTG TTTTCCATGGAAAA + +4 cisbp__M6300 1 0.979601 23954.2 1 6 CACCTG GGGCATCAATCAAA + +4 transfac_pro__M01805 3 0.979601 23954.2 1 6 CACCTG ACCCGCATGCATCC + +4 hocomoco__HXC8_HUMAN.H11MO.0.D 9 0.979601 23954.2 1 5 CACCTG TTTGATTAATGCCC + +4 cisbp__M5576-Blimp-1 -1 0.979601 23954.2 1 5 CACCTG ACTTTCGCTTTCGT - +4 stark__RTTRCGYATRCGCM 10 0.979601 23954.2 1 4 CACCTG GGCGCATACGCAAC - +4 cisbp__M6083-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.979611 23954.4 1 6 CACCTG AACAATTTCAGTGTT + +4 taipale__Sox10_DBD_AACAATTGCAGTGTT-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.979611 23954.4 1 6 CACCTG AACAATTTCAGTGTT + +4 taipale_cyt_meth__FOXE1_NSYTAAAYAAACAWN_eDBD_repr-bin-croc-fd59A-fkh-GATAe-grn-nej-pnr 9 0.979611 23954.4 1 6 CACCTG CCTTAAATAAACAAT + +4 cisbp__M2334-Dp 7 0.979611 23954.4 1 6 CACCTG AATTTCGCGCGCGCG - +4 flyfactorsurvey__CG5669_SOLEXA_5_FBgn0039169-CG3065-CG42741-E2f2-Klf15-Nf-YA-Nf-YB-Sp1-Spps-Stat92E-btd-cbt-dar1-kay-luna 7 0.979611 23954.4 1 6 CACCTG TTGGCCCCGCCCACT - +4 transfac_pro__M00404 2 0.979611 23954.4 1 6 CACCTG TTTCCATTTTTGGTA - +4 cisbp__M4920-D-Mad-Sox100B-Sox102F-Sox14-Sox15-SoxN-Ssrp 2 0.979712 23956.9 1 6 CACCTG AGAACAATGGA + +4 flyfactorsurvey__D_NAR_FBgn0000411-D-Mad-Sox14-Sox15-Sox100B-Sox102F-SoxN-Ssrp 2 0.979712 23956.9 1 6 CACCTG AGAACAATGGA + +4 predrem__nrMotif2351 -2 0.979712 23956.9 1 4 CACCTG TTTGCCATAAA + +4 transfac_pro__M05609-salm-salr 7 0.979712 23956.9 1 4 CACCTG ACTTTTGGACT + +4 tiffin__TIFDMEM0000107-Tbp -3 0.979712 23956.9 1 3 CACCTG CTATAAAAAGC + +4 tfdimers__MD00306 24 0.979717 23957 1 6 CACCTG AATAAAAAAAATTACGTAATTTTTTTTATA + +4 taipale_cyt_meth__FOXP1_NTGTTTRNNNNNNNNNNNNNNNNWCAACAN_eDBD 13 0.979717 23957 1 6 CACCTG TTGTTGTCCATCGTAAGGCATGGTAAACAA - +4 cisbp__M1978-B-H2 1 0.980061 23965.4 1 6 CACCTG TTAATTG + +4 cisbp__M4742-abd-A-al-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-Dll-E5-ems-en-eve-exex-ey-ftz-hbn-HGTX-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pd 1 0.980061 23965.4 1 6 CACCTG TTAATTA + +4 cisbp__M5254-abd-A-Antp-bsh-CG34367-Dfd-Dr-E5-ems-en-lms-NK7.1-OdsH-repo-Scr-slou-tup-Ubx-unc-4-unpg-zen2 1 0.980061 23965.4 1 6 CACCTG TTAATTG + +4 flyfactorsurvey__Ap_SOLEXA_FBgn0000099-Antp-Awh-C15-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-HGTX-Lim1-Lim3-Lmx1a-OdsH-PHDP-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn- 1 0.980061 23965.4 1 6 CACCTG TTAATTA + +4 elemento__AATAAAT 2 0.980061 23965.4 1 5 CACCTG AATAAAT + +4 elemento__AATAATT 2 0.980061 23965.4 1 5 CACCTG AATAATT + +4 predrem__nrMotif2050 -1 0.980061 23965.4 1 5 CACCTG GCCATTA + +4 elemento__ATGCAAA-nub-pdm2 2 0.980061 23965.4 1 5 CACCTG TTTGCAT - +4 elemento__ATTTAAA 2 0.980061 23965.4 1 5 CACCTG TTTAAAT - +4 predrem__nrMotif857 -1 0.980061 23965.4 1 5 CACCTG ATTTTAA - +4 cisbp__M2064-abd-A-acj6-al-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-CG4328-Dfd-E5-ems-en-eve-ey-ftz-hbn-HGTX-ind-lab-lbe-lbl-Lim1-Lim3-Lmx1a-otp-pb-pdm3-Pph13-repo-ro-Scr-slou-toy-Ubx-unpg-Vsx1-zen 4 0.980061 23965.4 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__Lab_SOLEXA_FBgn0002522-Antp-Awh-C15-CG4328-CG9876-CG11294-CG18599-CG32532-Dbx-Dfd-E5-HGTX-Lim1-Lim3-Lmx1a-Pph13-Rx-Scr-Traf4-Ubx-Vsx1-Vsx2-abd-A-acj6-al-ap-bsh-btn-ems-en-eve-exex-ey- 4 0.980061 23965.4 1 3 CACCTG TAATTAA - +4 jaspar__MA0257.1-Antp-Awh-CG4328-CG11294-CG18599-CG32532-Dfd-E5-HGTX-Lim1-Lim3-Lmx1a-Scr-Ubx-Vsx1-abd-A-acj6-al-ap-bsh-btn-ems-en-eve-ey-ftz-hbn-ind-lab-lbl-otp-pb-pdm3-repo-ro-toy-unpg-zen-zen2 4 0.980061 23965.4 1 3 CACCTG TAATTAA - +4 hdpi__ZNF192 5 0.980061 23965.4 1 2 CACCTG CAAAGCA + +4 hdpi__ZNF706-CG15715-CG18081 5 0.980061 23965.4 1 2 CACCTG AATTGCA + +4 tfdimers__MD00073-Ptx1 19 0.980143 23967.4 1 6 CACCTG ATTAGTTAATGATTAATCCCTTTTTTTTT - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m4-SREBP 4 0.980205 23969 1 6 CACCTG GACGCGCTTTGGTTTCGCTG + +4 dbcorrdb__YY1__ENCSR000BNT_1__m1-CG10431-E(z)-lid-Max-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 14 0.980205 23969 1 6 CACCTG GGCCAAGATGGCGGCCGCGG + +4 transfac_pro__M01526-Antp-CG11294-CG4328-Lim1-Lim3-Lmx1a-otp-Scr 0 0.980205 23969 1 6 CACCTG TTCCAATTAATTAATTTCTC + +4 dbcorrdb__POLR2A__ENCSR000DLV_1__m2-RpII215-Taf1-Tbp-TfIIB-TfIIFalpha 11 0.980205 23969 1 6 CACCTG CGCGGCGCCGGCTTATATAG - +4 dbcorrdb__EZH2__ENCSR000ARD_1__m6-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-E2f1-ERR-E(z)-HDAC1-kay-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-tna-vtd 16 0.980205 23969 1 4 CACCTG GGGGGCCCCCCCCCCCCCCC - +4 hdpi__RNF138 0 0.980273 23970.6 1 5 CACCTG TTCAT - +4 hdpi__HMG20A-Hmg-2 -2 0.980273 23970.6 1 4 CACCTG CATTG - +4 transfac_public__M00274 0 0.980297 23971.2 1 6 CACCTG AAGTTTCTTTGTTTTTTT + +4 cisbp__M0833 2 0.980495 23976 1 6 CACCTG ATTAATTTA + +4 taipale__SOX9_DBD_NAACAATRN_repr-D-Sox100B-Sox102F-Sox15-SoxN 1 0.980495 23976 1 6 CACCTG GAACAATGG + +4 cisbp__M5846-D-Sox100B-Sox102F-Sox15-SoxN 1 0.980495 23976 1 6 CACCTG GAACAATGG - +4 cisbp__M5589-cnc-foxo-Jra-kay-Myc-NFAT-Stat92E 4 0.980495 23976 1 5 CACCTG ATGACTCAT + +4 predrem__nrMotif1913 4 0.980495 23976 1 5 CACCTG TTTATCCCA + +4 transfac_pro__M05543 -1 0.980495 23976 1 5 CACCTG TCCATAATT + +4 cisbp__M5180-bsh-ems-eve-pb-Scr-zen2 4 0.980495 23976 1 5 CACCTG TCATTAACG - +4 flyfactorsurvey__Scr_Cell_FBgn0003339-Scr-bsh-ems-eve-pb-zen2 4 0.980495 23976 1 5 CACCTG TCATTAACG - +4 predrem__nrMotif2389 5 0.980495 23976 1 4 CACCTG CTTTGGGCC - +4 predrem__nrMotif2501 5 0.980495 23976 1 4 CACCTG GGAGAGTCC - +4 predrem__nrMotif27 -2 0.980495 23976 1 4 CACCTG CCAAATGCT - +4 predrem__nrMotif406 -3 0.980495 23976 1 3 CACCTG TTTAAGCCA + +4 predrem__nrMotif257 -3 0.980495 23976 1 3 CACCTG CTTGGGACA - +4 transfac_pro__M05006 4 0.980549 23977.4 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05036 4 0.980549 23977.4 1 6 CACCTG ATGCCGCCGA + +4 transfac_pro__M05163 4 0.980549 23977.4 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M05165 1 0.980549 23977.4 1 6 CACCTG AGGCCGCCCC + +4 bergman__retn-retn 3 0.980549 23977.4 1 6 CACCTG TATTAATCGA - +4 predrem__nrMotif450 1 0.980549 23977.4 1 6 CACCTG AAAACAATGC - +4 stark__TAATATGCRA 1 0.980549 23977.4 1 6 CACCTG TCGCATATTA - +4 taipale_cyt_meth__HOXD9_GTCGTAAAAN_FL_meth-Abd-B-cad 4 0.980549 23977.4 1 6 CACCTG GTTTTACGAC - +4 transfac_pro__M04993 1 0.980549 23977.4 1 6 CACCTG GGAGCGGCAT - +4 transfac_pro__M08974-Sox102F-Sox15 0 0.980549 23977.4 1 6 CACCTG TCTATTGTTT - +4 transfac_public__M00455-retn 3 0.980549 23977.4 1 6 CACCTG TATTAATCGA - +4 transfac_pro__M05785 5 0.980549 23977.4 1 5 CACCTG GGGCGGACGA + +4 taipale_cyt_meth__HOXD9_GYAATAAAAN_eDBD_meth-Abd-B-cad-eve 6 0.980549 23977.4 1 4 CACCTG GCAATAAAAC + +4 cisbp__M1359 6 0.980549 23977.4 1 4 CACCTG TGGCGCAAAA - +4 cisbp__M5318-Irbp18-nej-slbo-Xrp1 6 0.980549 23977.4 1 4 CACCTG ATTGCGCAAT - +4 taipale__CEBPG_DBD_NTTRCGCAAY-Irbp18-nej-slbo-Xrp1 6 0.980549 23977.4 1 4 CACCTG ATTGCGCAAT - +4 taipale_cyt_meth__HOXB9_GYAATAAAAN_eDBD-Abd-B-cad-eve 7 0.980549 23977.4 1 3 CACCTG ATTTTATTGC - +4 taipale_cyt_meth__HOXD9_GYAATAAAAN_FL_meth-Abd-B-cad-eve 7 0.980549 23977.4 1 3 CACCTG GTTTTATTGC - +4 tfdimers__MD00048-cad 13 0.980638 23979.5 1 6 CACCTG TTAATTCCATAAATCCCAATCTTTTT - +4 transfac_pro__M06404 2 0.981168 23992.5 1 6 CACCTG TATTCCATCCGC + +4 transfac_pro__M06954 5 0.981168 23992.5 1 6 CACCTG CTCCGCGCCAAG + +4 cisbp__M2176-D-Sox100B 0 0.981168 23992.5 1 6 CACCTG CCCATTGTTCTC - +4 tiffin__TIFDMEM0000027 0 0.981168 23992.5 1 6 CACCTG TTTCAGTAAAAA - +4 transfac_pro__M06805-row 7 0.981168 23992.5 1 5 CACCTG TCATATTTATCC + +4 hocomoco__CDX4_MOUSE.H11MO.0.A-cad-eve 7 0.981168 23992.5 1 5 CACCTG GGCCATAAATCA - +4 transfac_pro__M05695 7 0.981168 23992.5 1 5 CACCTG GCTTATGCATTG - +4 transfac_pro__M06806 7 0.981168 23992.5 1 5 CACCTG TCCAAATCAAGA - +4 transfac_pro__M06732 8 0.981168 23992.5 1 4 CACCTG CAGCAAAGCCCC - +4 transfac_pro__M05282 6 0.981276 23995.1 1 6 CACCTG GGGGGGTCCCGTCCGGGCGCG + +4 transfac_pro__M05203-ERR-E(z) 17 0.981276 23995.1 1 4 CACCTG GGGGGACGCGGGGGCCCCCCC - +4 hocomoco__GBX1_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG18599-CG34367-Dbx-Dll-Dr-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ems-en-eve-exex-gsb-gsb-n-ind-inv-lab-lbe-lms-otp-pdm3-prd-repo-ro-un 5 0.981386 23997.8 1 6 CACCTG CTAATTAGCTAAAATTT + +4 taipale__Sox3_DBD_NATGAATKNYATTCATN_repr-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 11 0.981386 23997.8 1 6 CACCTG GATGAATGGTATTCATG + +4 taipale_cyt_meth__ZBTB22_NKCACTANNNTAGTGMN_eDBD 2 0.981386 23997.8 1 6 CACCTG TTCACTATAATAGTGAA + +4 transfac_pro__M01429 4 0.981386 23997.8 1 6 CACCTG ATAACATCGTTTTTAAG + +4 hocomoco__SHOX_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG11294-CG15696-CG18599-CG32532-CG34367-Dbx-Dll-Dr-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-ap-bsh-ems-en-exex-ey-gsb-gsb-n-ind-inv-lab-l 6 0.981386 23997.8 1 6 CACCTG AAAAATTAACTAATTAG - +4 transfac_pro__M07740-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.981386 23997.8 1 6 CACCTG TAACAATATCATTGTTA - +4 tfdimers__MD00356-fkh-Mad 16 0.98162 24003.6 1 6 CACCTG TTTTTTTTTTTGTTTTTTTTTGTTTGTTTTTTTTTT + +4 taipale_tf_pairs__E2F3_ONECUT2_NNSGCGCSNNNNATCGAYN_CAP_repr-E2f1-onecut 13 0.981843 24009 1 6 CACCTG GATCGATAATTCGCGCCAT - +4 hocomoco__ARX_HUMAN.H11MO.0.D-Awh-C15-CG9876-CG11294-CG32532-CG34367-Drgx-E5-Lim3-OdsH-Optix-Pph13-Rx-Traf4-Vsx2-al-bsh-ems-en-eve-hbn-otp-repo-ro-unc-4-unpg 6 0.982045 24013.9 1 6 CACCTG TTAATTTAATTAG + +4 transfac_pro__M09227 5 0.982045 24013.9 1 6 CACCTG ACCAATAATTGAA - +4 cisbp__M5834-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.982115 24015.7 1 6 CACCTG GAACAATTGCAGTGTT + +4 taipale__SOX4_DBD_NAACAATTKCAGTGTT-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.982115 24015.7 1 6 CACCTG GAACAATTGCAGTGTT + +4 transfac_pro__M09164 10 0.982115 24015.7 1 6 CACCTG TTTTTGTCGTTTTGTG + +4 transfac_pro__M01328-B-H1-B-H2-bsh-Dr-lms-NK7.1-OdsH-repo-slou-tup-Ubx-unc-4 0 0.982115 24015.7 1 6 CACCTG AAATTAATTGATTTTG - +4 cisbp__M5164-ap-CG11294-CG32532-CG4328-CG9876-en-HGTX-ind-lab-Lim1-Lim3-Lmx1a-otp-Pph13-repo-ro-Rx-unpg-Vsx1 2 0.982272 24019.5 1 6 CACCTG TTTAATTA + +4 flyfactorsurvey__Inv_Cell_FBgn0001269-Awh-CG9876-CG18599-CG32532-E5-Lim3-OdsH-Pph13-Rx-Vsx1-ap-ems-en-inv-otp-ro-unpg 2 0.982272 24019.5 1 6 CACCTG TCTAATTA + +4 cisbp__M2037-ap-Awh-CG18599-CG32532-CG9876-E5-ems-en-inv-Lim3-OdsH-otp-Pph13-ro-Rx-unpg-Vsx1 0 0.982272 24019.5 1 6 CACCTG TAATTAGA - +4 cisbp__M5208-Sox15-Sox21a-SoxN 1 0.982272 24019.5 1 6 CACCTG AAACAATG - +4 flyfactorsurvey__Repo_Cell_FBgn0011701-CG4328-CG9876-CG11294-CG32532-HGTX-Lim1-Lim3-Lmx1a-Pph13-Rx-Vsx1-ap-en-ind-lab-otp-repo-ro-unpg 0 0.982272 24019.5 1 6 CACCTG TAATTAAA - +4 predrem__nrMotif1475 0 0.982272 24019.5 1 6 CACCTG GACTAAAA - +4 cisbp__M4721-Abd-B-cad -1 0.982272 24019.5 1 5 CACCTG TCATAAAA + +4 elemento__AATTACGC 3 0.982272 24019.5 1 5 CACCTG AATTACGC + +4 flyfactorsurvey__Abd-B_FlyReg_FBgn0000015-Abd-B-cad -1 0.982272 24019.5 1 5 CACCTG TCATAAAA + +4 cisbp__M0066 3 0.982272 24019.5 1 5 CACCTG TTATATAT - +4 predrem__nrMotif1840 3 0.982272 24019.5 1 5 CACCTG TTCTACTG - +4 cisbp__M2006-nub-pb 4 0.982272 24019.5 1 4 CACCTG TAATTAAA + +4 hdpi__ZBTB4 4 0.982272 24019.5 1 4 CACCTG TGCAAAAC + +4 cisbp__M5007-bsh-C15-Dbx-ems-HGTX-ind-lab-lbl-repo-Ubx-zen2 4 0.982272 24019.5 1 4 CACCTG TAATTAAA - +4 flyfactorsurvey__Hgtx_Cell_FBgn0040318-C15-Dbx-HGTX-Ubx-bsh-ems-ind-lab-lbl-repo-zen2 4 0.982272 24019.5 1 4 CACCTG TAATTAAA - +4 transfac_pro__M02315-nub-pb 4 0.982272 24019.5 1 4 CACCTG TAATTAAA - +4 cisbp__M1198-ap-Awh-CG11294-CG18599-CG32532-CG9876-E5-ems-en-Lim1-Lim3-otp-Pph13-ro-Rx-unpg-Vsx1-zen2 5 0.982272 24019.5 1 3 CACCTG TTAATTAA + +4 hdpi__DDX20-Gem3 -3 0.982272 24019.5 1 3 CACCTG TTTTGAGC + +4 hdpi__MDM2 -3 0.982272 24019.5 1 3 CACCTG CGGAAATA + +4 predrem__nrMotif1881 -3 0.982272 24019.5 1 3 CACCTG CTCTCCGC + +4 transfac_pro__M07319-fd59A -3 0.982272 24019.5 1 3 CACCTG CTTTGTTT - +4 tfdimers__MD00177-pan-Stat92E 24 0.982355 24021.5 1 6 CACCTG TTTTTCACTTCCCCTTTTCTTTTTTTTTTTT + +4 taipale_cyt_meth__YY1_NGCCGCCATYTTGN_FL-pho-phol-RpII215 6 0.982462 24024.2 1 6 CACCTG GGCCGCCATTTTGG + +4 taipale__NFATC1_full_TTTTCCATGGAAAA_repr-NFAT 3 0.982462 24024.2 1 6 CACCTG TTTTCCATGGAAAA - +4 transfac_pro__M02796-Sox102F-Sox14-Sox15 0 0.982462 24024.2 1 6 CACCTG GTTTAGAACAATTA - +4 transfac_public__M00089 5 0.982462 24024.2 1 6 CACCTG TGCAATAATTGCAT - +4 taipale__IRF7_DBD_NCGAAANYGAAACY_repr-Blimp-1 -1 0.982462 24024.2 1 5 CACCTG ACTTTCGCTTTCGT - +4 cisbp__M6084-Sox100B-Sox14-Sox15 2 0.982479 24024.6 1 6 CACCTG ATCAATTGCAGTGAT + +4 stark__TAATTRNNNNYGACA 6 0.982479 24024.6 1 6 CACCTG TAATTAAAAACGACA + +4 taipale__SOX10_full_AACAATNNNAGTGTT-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.982479 24024.6 1 6 CACCTG AACAATTGCAGTGTT + +4 taipale__Sox10_DBD_ATCAATTGCAGTGAT-Sox100B-Sox14-Sox15 2 0.982479 24024.6 1 6 CACCTG ATCAATTGCAGTGAT + +4 flyfactorsurvey__lola-PJ_SOLEXA_FBgn0005630-lola 4 0.982479 24024.6 1 6 CACCTG AACCCAACATAAAAA - +4 jaspar__MA0541.1-Dp 7 0.982479 24024.6 1 6 CACCTG AATTTCGCGCGCGCG - +4 transfac_pro__M07745-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.982479 24024.6 1 6 CACCTG AACAATAGCATTGTT - +4 flyfactorsurvey__Blimp-1-F1-CG4360F2-3_SOLEXA_2.5-Blimp-1 10 0.982479 24024.6 1 5 CACCTG CACTACAACAAATCA - +4 stark__YGCGYRTCAWT 0 0.982606 24027.7 1 6 CACCTG CGCGCATCAAT + +4 transfac_pro__M09251 1 0.982606 24027.7 1 6 CACCTG GTAATTAATGC + +4 predrem__nrMotif1318 1 0.982606 24027.7 1 6 CACCTG TTTGCTTGAAA - +4 predrem__nrMotif1848 4 0.982606 24027.7 1 6 CACCTG TAATTTTCTTT - +4 predrem__nrMotif2524 5 0.982606 24027.7 1 6 CACCTG CCGCGAGCCGG - +4 stark__CATTANYGTCA 1 0.982606 24027.7 1 6 CACCTG TGACAATAATG - +4 taipale_cyt_meth__LMX1B_NWWYTAATTAN_FL_meth-CG11294-CG4328-Drgx-hbn-Lmx1a-Traf4 5 0.982606 24027.7 1 6 CACCTG TTAATTAAAAT - +4 cisbp__M1183 7 0.982606 24027.7 1 4 CACCTG TATTAATTATA + +4 flyfactorsurvey__jigr1_SANGER_5_FBgn0039350-jigr1 -2 0.982606 24027.7 1 4 CACCTG AATAAAAAAAA + +4 cisbp__M5047-jigr1 -2 0.982606 24027.7 1 4 CACCTG AATAAAAAAAA - +4 predrem__nrMotif335 7 0.982606 24027.7 1 4 CACCTG TTTTTTAAATC - +4 cisbp__M4556-CG7786-gt-Irbp18-Myc-nej-Pdp1-slbo-Xrp1 8 0.982606 24027.7 1 3 CACCTG GATTGCACAAT + +4 transfac_pro__M09253 9 0.982606 24027.7 1 2 CACCTG TCATTCATTCA + +4 elemento__TAATTGA 0 0.98285 24033.6 1 6 CACCTG TAATTGA + +4 elemento__TAATTGC 0 0.98285 24033.6 1 6 CACCTG TAATTGC + +4 elemento__TGCGTGC 0 0.98285 24033.6 1 6 CACCTG TGCGTGC + +4 flyfactorsurvey__Tup_SOLEXA_FBgn0003896-Antp-Dfd-Dr-E5-NK7.1-OdsH-Scr-Ubx-abd-A-bsh-ems-en-lms-repo-slou-tup-unc-4-unpg-zen2 1 0.98285 24033.6 1 6 CACCTG TTAATTG + +4 transfac_pro__M01997 0 0.98285 24033.6 1 6 CACCTG CACGAAA + +4 elemento__CACGCAA 1 0.98285 24033.6 1 6 CACCTG TTGCGTG - +4 elemento__TCACGCA 0 0.98285 24033.6 1 6 CACCTG TGCGTGA - +4 predrem__nrMotif2 1 0.98285 24033.6 1 6 CACCTG GCATTTT - +4 fantom__motif81_NGCAGAA 2 0.98285 24033.6 1 5 CACCTG TTCTGCT - +4 cisbp__M2030-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ind-lab-lbl-pb-Scr-Ubx-zen-zen2 -3 0.98285 24033.6 1 3 CACCTG CTAATGA + +4 cisbp__M4756-abd-A-al-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-CG34367-CG4328-CG7745-CG9876-Dfd-Dll-E5-ems-en-eve-ey-ftz-gsb-gsb-n-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-Optix-otp-pb- -3 0.98285 24033.6 1 3 CACCTG TTAATTA + +4 flyfactorsurvey__Awh_SOLEXA_FBgn0013751-Antp-Awh-CG4328-CG7745-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Dll-E5-Lim1-Lim3-Lmx1a-OdsH-Optix-PHDP-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-ems-en-e -3 0.98285 24033.6 1 3 CACCTG TTAATTA + +4 jaspar__MA0221.1-Antp-Awh-CG18599-Dfd-E5-Scr-Ubx-ap-bsh-btn-ems-eve-ind-lab-lbl-pb-zen-zen2 -3 0.98285 24033.6 1 3 CACCTG CTAATGA + +4 cisbp__M4781-abd-A-Antp-ap-Awh-bsh-btn-C15-CG18599-Dbx-Dfd-E5-ems-eve-ftz-HGTX-lab-lbl-pb-Scr-slou-Ubx-zen-zen2 4 0.98285 24033.6 1 3 CACCTG TCATTAA - +4 flyfactorsurvey__Bsh_SOLEXA_FBgn0000529-Antp-Awh-C15-CG18599-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-lab-lbl-pb-zen2 4 0.98285 24033.6 1 3 CACCTG TCATTAA - +4 bergman__br-Z4-br 5 0.98285 24033.6 1 2 CACCTG AGAAACA + +4 cisbp__M1983-cad-Dbx 5 0.98285 24033.6 1 2 CACCTG TTTATTA + +4 cisbp__M2038-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-HGTX-lab-lbl-otp-pb-ro-Scr-zen-zen2 5 0.98285 24033.6 1 2 CACCTG TTAATTA + +4 flyfactorsurvey__Lab_Cell_FBgn0002522-Antp-Awh-CG18599-Dfd-E5-HGTX-Scr-abd-A-ap-bsh-btn-ems-eve-ftz-lab-otp-pb-ro-zen-zen2 5 0.98285 24033.6 1 2 CACCTG TTAATTA + +4 stark__RKAAASA-br 5 0.98285 24033.6 1 2 CACCTG AGAAACA + +4 transfac_pro__M01527-bab1-CG12054-ct-CTCF-Dbx-Xrp1 9 0.983068 24039 1 6 CACCTG GCAAAAAATTAATTTTTAAC + +4 dbcorrdb__KDM5A__ENCSR000AQL_1__m1-CG10431-lid-Myc-pho-phol-Rbbp5-RpII215-Sap30-Taf1-Taf7 14 0.983068 24039 1 6 CACCTG GGGCAACATGGCGGCGGCCG - +4 dbcorrdb__YY1__ENCSR000EXG_1__m1-CG10431-CTCF-lid-Myc-pho-phol-Rbbp5-RpII215-Taf1-Taf7 9 0.983068 24039 1 6 CACCTG CGCGGCCGCCATCTTGGCTG - +4 swissregulon__hs__POU1F1.p2 12 0.983125 24040.3 1 6 CACCTG AATTCATAATTATATACA + +4 transfac_pro__M09165 12 0.983125 24040.3 1 6 CACCTG TTTTTTTGTCGTTTTGTG - +4 hocomoco__BATF_HUMAN.H11MO.0.A-Jra-MTA1-like-NFAT-Stat92E-ebi-foxo-nej 14 0.983125 24040.3 1 4 CACCTG ATGAGTCATATCGAAAGT - +4 tfdimers__MD00342-pho-phol 2 0.983187 24041.9 1 6 CACCTG AAAAAGTTTAAAAATGGAAATGAAAATAA - +4 predrem__nrMotif213 2 0.983252 24043.5 1 6 CACCTG TTCCCCAAA + +4 predrem__nrMotif1764 2 0.983252 24043.5 1 6 CACCTG TTTAAATGC - +4 predrem__nrMotif1928 2 0.983252 24043.5 1 6 CACCTG AGCATATTT - +4 predrem__nrMotif1982 0 0.983252 24043.5 1 6 CACCTG TGTCTATTT - +4 predrem__nrMotif1991 3 0.983252 24043.5 1 6 CACCTG TTAGAATTT - +4 predrem__nrMotif2048 1 0.983252 24043.5 1 6 CACCTG ACACTGTCT - +4 predrem__nrMotif2548 1 0.983252 24043.5 1 6 CACCTG GCGGCTTCC - +4 cisbp__M5043-ap-Awh-CG11085-CG18599-CG9876-E5-ems-en-eve-ind-inv-Lim3-otp-pb-ro-slou-zen2 -1 0.983252 24043.5 1 5 CACCTG CACTAATTA + +4 flyfactorsurvey__Ind_Cell_FBgn0025776-Awh-CG9876-CG11085-CG18599-E5-Lim3-ap-ems-en-eve-ind-inv-otp-pb-ro-slou-zen2 -1 0.983252 24043.5 1 5 CACCTG TACTAATTA + +4 predrem__nrMotif324 4 0.983252 24043.5 1 5 CACCTG TTCATAAAT - +4 hocomoco__PDX1_HUMAN.H11MO.1.A-Antp-Awh-CG18599-Dfd-E5-HGTX-Scr-Ubx-ap-bsh-btn-ems-en-ftz-lab-pb-zen2 5 0.983252 24043.5 1 4 CACCTG ATAATTAAT - +4 cisbp__M1609 1 0.983321 24045.1 1 6 CACCTG AAAACAATAG + +4 cisbp__M3773-dve-vvl 3 0.983321 24045.1 1 6 CACCTG ATTAACATAA + +4 transfac_pro__M05049 4 0.983321 24045.1 1 6 CACCTG ATGCCGCCGA + +4 cisbp__M0673 4 0.983321 24045.1 1 6 CACCTG CGCGCGCGCT - +4 scertf__zhu.TBS1 4 0.983321 24045.1 1 6 CACCTG GCGGATCCGC - +4 taipale_cyt_meth__TCFL5_NCACGYGCAN_eDBD 3 0.983321 24045.1 1 6 CACCTG GTGCGCGTGA - +4 tiffin__TIFDMEM0000002 3 0.983321 24045.1 1 6 CACCTG AATTATTTTT - +4 homer__NCYAATAAAA_HOXD13-Dbx-cad -1 0.983321 24045.1 1 5 CACCTG TCCAATAAAA + +4 cisbp__M0899-al-Antp-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-Dr-E5-ems-en-ey-gsb-gsb-n-ind-inv-Lim3-OdsH-otp-pdm3-Pph13-prd-repo-Rx-Scr-slou-toy-unc-4-unpg-Vsx1-vvl-zfh2 6 0.983321 24045.1 1 4 CACCTG ATTAATTAGT + +4 cisbp__M5534 6 0.983321 24045.1 1 4 CACCTG CCAATAAAAC + +4 jaspar__MA0628.1-Antp-Awh-C15-CG9876-CG11085-CG18599-CG34367-Dr-E5-Lim3-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-ems-en-ey-gsb-gsb-n-ind-inv-otp-pdm3-prd-repo-slou-toy-unc-4-unpg-vvl-zfh2 6 0.983321 24045.1 1 4 CACCTG ATTAATTAAT + +4 taipale__HOXA13_DBD_CCAATAAAAN 6 0.983321 24045.1 1 4 CACCTG CCAATAAAAC + +4 taipale_cyt_meth__SOX14_CCGAACAATN_FL_meth-D-Sox21a-Sox21b -2 0.983321 24045.1 1 4 CACCTG CCGAACAATG + +4 predrem__nrMotif1097 6 0.983321 24045.1 1 4 CACCTG TTTTGCTAAA - +4 taipale_cyt_meth__TCFL5_NCACGYGCAN_eDBD_meth_repr 7 0.983321 24045.1 1 3 CACCTG GCACGCGCAC + +4 taipale_cyt_meth__HOXB9_GTCGTAAAAN_eDBD-Abd-B 7 0.983321 24045.1 1 3 CACCTG ATTTTACGAC - +4 cisbp__M5169-brm-hb-jim-rn-sqz 14 0.983434 24047.9 1 6 CACCTG CCACACAAAAAAAACACCAAAAACC + +4 tfdimers__MD00370-pho-phol-rn-sqz 19 0.983434 24047.9 1 6 CACCTG AAAAAAAAATGGAAAAAAAAAAAAA + +4 tfdimers__MD00282-Mad-sens-2 21 0.983562 24051 1 6 CACCTG TTTATATAAATCCTTTCTTTTTTTTTT + +4 transfac_pro__M05077 6 0.983893 24059.1 1 6 CACCTG ATTAACGGCTTC + +4 swissregulon__sacCer__STB1 0 0.983893 24059.1 1 6 CACCTG AACGCGAAAATT - +4 taipale_cyt_meth__IRF2_YGAAASYGAAAS_FL 4 0.983893 24059.1 1 6 CACCTG GTTTCGCTTTCG - +4 transfac_pro__M06259-lid-pho-phol 5 0.983893 24059.1 1 6 CACCTG GCGGCCGCCATG - +4 transfac_pro__M06659 7 0.983893 24059.1 1 5 CACCTG TATCCAAGCCCC - +4 swissregulon__sacCer__ROX1-D-Sox100B-Sox102F-SoxN -2 0.983893 24059.1 1 4 CACCTG TCCATTGTTCTC + +4 transfac_pro__M05211 8 0.983893 24059.1 1 4 CACCTG TTCAAATTTAAC - +4 taipale_tf_pairs__HOXB2_PAX9_NNMATTAGTCACGCWTSRNTG_CAP-pb-Poxm 0 0.98403 24062.5 1 6 CACCTG CCCATTAGTCACGCATGACTG + +4 transfac_pro__M05201-ERR-E(z)-Rel 13 0.98403 24062.5 1 6 CACCTG GGGGGGCGCGGGGAACCCCCC - +4 cisbp__M5832-bbx-D-peng-Sox15-Sox21a-Sox21b-SoxN 0 0.984078 24063.7 1 6 CACCTG TATCAATAACATTGATA + +4 cisbp__M5850-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.984078 24063.7 1 6 CACCTG AAACAATTGCAGTGTTT + +4 hocomoco__ESX1_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG9876-CG11085-CG18599-CG34367-Dll-Dr-E5-Lim3-OdsH-Pph13-Rx-Vsx2-al-ap-btn-dve-ems-en-eve-ind-inv-lab-lbe-lms-otp-pb-repo-ro-slou-unc-4-unpg-vvl-zfh2 6 0.984078 24063.7 1 6 CACCTG GCTAATTAGCAATAATT + +4 taipale__SOX2_full_NATCAATANCATTGATN-bbx-D-peng-Sox15-Sox21a-Sox21b-SoxN 0 0.984078 24063.7 1 6 CACCTG TATCAATAACATTGATA + +4 taipale__SOX9_full_NAACAATKNYAGTGTTN-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.984078 24063.7 1 6 CACCTG AAACAATTGCAGTGTTT + +4 taipale_cyt_meth__MTF1_NYTTTGCACACGRYNYN_eDBD_meth-MTF-1 11 0.984078 24063.7 1 6 CACCTG CTTTTGCACACGGCCCT + +4 transfac_pro__M01409-Antp-C15-CG32532-CG4328-Dfd-HGTX-Lim1-Lim3-Lmx1a-otp-Scr 10 0.984078 24063.7 1 6 CACCTG GGTTTTTAATTAATTCG - +4 transfac_pro__M07749-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.984078 24063.7 1 6 CACCTG AAACAATTTCAGTGTTT - +4 transfac_pro__M09160 11 0.984078 24063.7 1 6 CACCTG TTTTTTGTCGTTTTCTG - +4 transfac_pro__M01389-al-ap-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-inv-Lim3-OdsH-otp-pdm3-Pph13-repo-Rx-slou-unc-4-unpg-zfh2 12 0.984078 24063.7 1 5 CACCTG TGCACTAATTAGCGCAC + +4 cisbp__M4464-ebi-foxo-Jra-kay-Mef2-MTA1-like-nej-NFAT-Stat92E 9 0.984503 24074 1 6 CACCTG GATGACTCATATCGAAACT + +4 transfac_pro__M07795-CG11294-Drgx-ey-OdsH-repo-Traf4-unc-4 2 0.984648 24077.6 1 6 CACCTG CTAATCGAATTAG + +4 swissregulon__sacCer__NDT80 9 0.984648 24077.6 1 4 CACCTG GGCCACAAAAACG + +4 transfac_pro__M05117 10 0.984648 24077.6 1 3 CACCTG GCACGGGAATTAA - +4 jaspar__MA0627.1-nub-pdm2-vvl 7 0.98471 24079.1 1 6 CACCTG TTGTATGCAAATTAGA + +4 taipale_cyt_meth__E2F1_NWTTTGGCGCCAWWWN_FL-E2f1-E2f2 7 0.98471 24079.1 1 6 CACCTG ATTTTGGCGCCAATTT + +4 transfac_pro__M01476-nub-pdm2-vvl 7 0.98471 24079.1 1 6 CACCTG TTGTATGCAAATTAGA + +4 taipale_cyt_meth__POU5F1_NWWTATGCTAATKARN_FL-CG18599-Dll-dve-nub-pdm2-pdm3-vvl -2 0.98471 24079.1 1 4 CACCTG CTTAATTAGCATAATT - +4 taipale_cyt_meth__TLX3_NAATTGNNNNNNNNNNCAATTN_FL_repr-C15 9 0.984773 24080.7 1 6 CACCTG GAATTGCTCTAAAGAGCAATTC + +4 tfdimers__MD00360-GATAe-grn-pnr 13 0.984773 24080.7 1 6 CACCTG AATTGTTAATGATTAAAAAAAA + +4 cisbp__M1167 1 0.98481 24081.6 1 6 CACCTG ATATATAA + +4 cisbp__M4940-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dbx-E5-ems-eve-ftz-HGTX-ind-inv-lab-Lim3-Lmx1a-otp-pb-ro-Scr-slou-tup-Ubx-unpg-Vsx1-zen-zen2 1 0.98481 24081.6 1 6 CACCTG TTTAATGA + +4 cisbp__M4994-CG4328-H2.0-Lmx1a 0 0.98481 24081.6 1 6 CACCTG TTAATAAA + +4 flyfactorsurvey__Ems_Cell_FBgn0000576-Antp-Awh-CG18599-Dbx-E5-HGTX-Lim3-Lmx1a-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-eve-ftz-ind-inv-lab-otp-pb-ro-slou-tup-unpg-zen-zen2 1 0.98481 24081.6 1 6 CACCTG TTTAATGA + +4 transfac_pro__M07773-Antp-B-H1-B-H2-bsh-CG11085-Dr-Scr-unpg 1 0.98481 24081.6 1 6 CACCTG CTAATTGC + +4 hocomoco__SOX13_HUMAN.H11MO.0.D-Sox102F 1 0.98481 24081.6 1 6 CACCTG GAACAATG - +4 scertf__zhu.FHL1-CHES-1-like-jumu 2 0.98481 24081.6 1 6 CACCTG TTTGCGTC - +4 cisbp__M1584-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b 3 0.98481 24081.6 1 5 CACCTG ATTGTTTT + +4 elemento__AATTAGCA 3 0.98481 24081.6 1 5 CACCTG AATTAGCA + +4 cisbp__M0146 -1 0.98481 24081.6 1 5 CACCTG GCATGCAT - +4 predrem__nrMotif2350 -1 0.98481 24081.6 1 5 CACCTG ACAATAAT - +4 elemento__TCTCGCGA-CoRest -2 0.98481 24081.6 1 4 CACCTG TCTCGCGA + +4 cisbp__M1597-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b 4 0.98481 24081.6 1 4 CACCTG AAAACAAT - +4 cisbp__M4789-abd-A-Antp-ap-bsh-C15-CG15696-E5-ems-exex-HGTX-ind-lab-Scr-slou-Ubx-zen2 4 0.98481 24081.6 1 4 CACCTG TAATTAAA - +4 flyfactorsurvey__C15_SOLEXA_FBgn0004863-Antp-C15-CG15696-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-ems-exex-ind-lab-slou-zen2 4 0.98481 24081.6 1 4 CACCTG TAATTAAA - +4 idmmpmm__Dfd-Antp-Dfd-Scr-Ubx-abd-A-bsh-btn-ems-ftz-pb-zen2 5 0.98481 24081.6 1 3 CACCTG TTAATGAC + +4 predrem__nrMotif2587 5 0.98481 24081.6 1 3 CACCTG GAGCGCTC - +4 taipale__PDX1_DBD_NYMATTAN-abd-A-Antp-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-V 5 0.98481 24081.6 1 3 CACCTG CTAATTAC - +4 taipale_cyt_meth__HOXD4_NTMATTAN_FL-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-pb-Scr-Ubx-zen-zen2 5 0.98481 24081.6 1 3 CACCTG CTAATGAT - +4 transfac_pro__M04921-Hnf4 6 0.98481 24081.6 1 2 CACCTG AGCAAACA + +4 predrem__nrMotif2380 -4 0.98481 24081.6 1 2 CACCTG TTTGAGTA - +4 stark__GCCATT-pho -1 0.984892 24083.6 1 5 CACCTG GCCATT + +4 hdpi__TP73 2 0.984892 24083.6 1 4 CACCTG TTCCGC - +4 cisbp__M2661 5 0.985006 24086.3 1 6 CACCTG TGCAATAATTGCAT + +4 cisbp__M6063-nub-pdm2-vvl 4 0.985006 24086.3 1 6 CACCTG TATGAATATTCAAA + +4 taipale__Pou2f2_DBD_NWTRMATATKYAWN-nub-pdm2-vvl 4 0.985006 24086.3 1 6 CACCTG TATGAATATTCAAA + +4 taipale_cyt_meth__E2F4_WTTTGGCGCCAWWW_eDBD-E2f1-E2f2 6 0.985006 24086.3 1 6 CACCTG TTTTGGCGCCATTT + +4 transfac_pro__M07844-onecut 7 0.985006 24086.3 1 6 CACCTG AATTATCGATCGGT - +4 transfac_pro__M09211 7 0.985006 24086.3 1 6 CACCTG GGAATATTCCCTTT - +4 transfac_public__M00410-D-Sox100B-Sox102F-SoxN 1 0.985006 24086.3 1 6 CACCTG TCCCATTGTTCTTA - +4 hocomoco__PO4F1_HUMAN.H11MO.0.D-acj6-vvl -2 0.985006 24086.3 1 4 CACCTG CATTAATTATTCAT + +4 transfac_pro__M07868-ey-eyg-gsb-gsb-n-prd-toe 10 0.985006 24086.3 1 4 CACCTG GATAATCAATTATC - +4 cisbp__M5810-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.985021 24086.7 1 6 CACCTG AACAATTGCAGTGTT + +4 taipale__ZSCAN4_full_TGCACACNCTGAAAA_repr 4 0.985021 24086.7 1 6 CACCTG TGCACACACTGAAAA + +4 c2h2_zfs__M5125 4 0.985021 24086.7 1 6 CACCTG TGCACACACTGAAAA - +4 transfac_pro__M05577 10 0.985021 24086.7 1 5 CACCTG GCGCCGAATCCCCCC - +4 taipale_cyt_meth__SP1_NWRGCCACGCCCMYN_eDBD-btd-cbt-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps 11 0.985021 24086.7 1 4 CACCTG TAAGCCACGCCCACT + +4 hocomoco__UNC4_HUMAN.H11MO.0.D-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-eve-hbn-repo-unc-4 5 0.985155 24090 1 6 CACCTG TAATTTAATTA + +4 predrem__nrMotif1409 4 0.985155 24090 1 6 CACCTG CCGAGGGCTGC + +4 transfac_pro__M01021 3 0.985155 24090 1 6 CACCTG TTTGTCGTTTT + +4 predrem__nrMotif1055 1 0.985155 24090 1 6 CACCTG TTTCATTAAAA - +4 stark__RSWGAGMRHRR-Trl 2 0.985155 24090 1 6 CACCTG CCTCGCTCACC - +4 tiffin__TIFDMEM0000065 6 0.985155 24090 1 5 CACCTG CAACAACAACA + +4 cisbp__M5443-croc-foxo-slp1 9 0.985155 24090 1 2 CACCTG GTAAATAAACA + +4 taipale__FOXC2_DBD_RTAAAYAAACA-croc-foxo-slp1 9 0.985155 24090 1 2 CACCTG GTAAATAAACA + +4 fantom__motif70_MAATCGC 1 0.98532 24094 1 6 CACCTG AAATCGC + +4 swissregulon__sacCer__CEP3 0 0.98532 24094 1 6 CACCTG TTCCGAG - +4 predrem__nrMotif536 -1 0.98532 24094 1 5 CACCTG TTCTTCA + +4 predrem__nrMotif2405 -1 0.98532 24094 1 5 CACCTG TTCTTAT - +4 predrem__nrMotif2243 -3 0.98532 24094 1 3 CACCTG CTTTGGC + +4 cisbp__M5181-abd-A-Antp-ap-Awh-bsh-btn-C15-CG18599-Dfd-E5-ems-eve-ftz-HGTX-lab-pb-Scr-Ubx-zen-zen2 4 0.98532 24094 1 3 CACCTG TCATTAA - +4 flyfactorsurvey__Scr_SOLEXA_FBgn0003339-Antp-Awh-C15-CG18599-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-lab-pb-zen-zen2 4 0.98532 24094 1 3 CACCTG TCATTAA - +4 jaspar__MA0215.1-Dfd-HGTX-Scr-bsh-btn 4 0.98532 24094 1 3 CACCTG TCATTAA - +4 cisbp__M2046-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-lbl-Lim3-otp-pb-pdm3-ro-Scr-Ubx-zen-zen2 5 0.98532 24094 1 2 CACCTG TTAATTA + +4 jaspar__MA0166.1-Antp-CG18599-Dfd-E5-Scr-bsh-btn-ems-ftz-pb-zen-zen2 5 0.98532 24094 1 2 CACCTG TTAATGA + +4 jaspar__MA0238.1-Antp-Awh-CG18599-Dfd-E5-Lim3-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-eve-ftz-ind-lab-lbl-otp-pb-ro-zen-zen2 5 0.98532 24094 1 2 CACCTG TTAATTA + +4 hdpi__TIMELESS-tim-timeout 0 0.985389 24095.7 1 5 CACCTG GACGA + +4 taipale__MSX2_DBD_NYAATTAAAANNYAATTA-Dr-HGTX-ind 0 0.985624 24101.5 1 6 CACCTG TAATTGGTTTTTAATTGC - +4 transfac_pro__M05566 9 0.985624 24101.5 1 6 CACCTG GCGTTGTTGAACCCGTCC - +4 transfac_pro__M07254-croc 0 0.985687 24103 1 6 CACCTG TTGTTTTAT + +4 predrem__nrMotif1920 0 0.985687 24103 1 6 CACCTG AACAGTGCA - +4 transfac_pro__M02032 2 0.985687 24103 1 6 CACCTG TTTTCGTGG - +4 elemento__ATTTGCATA-acj6-nub-pdm2-SoxN-Tbp-vvl -1 0.985687 24103 1 5 CACCTG ATTTGCATA + +4 swissregulon__sacCer__SWI4 -1 0.985687 24103 1 5 CACCTG ACGCGAAAA + +4 transfac_pro__M01661 -3 0.985687 24103 1 3 CACCTG TTGATTGAA - +4 taipale_cyt_meth__ONECUT2_NTATCGATYN_eDBD-onecut 1 0.985764 24104.9 1 6 CACCTG GTATCGATCG + +4 taipale_cyt_meth__SOX8_AGAACAATGN_eDBD_meth-D-Sox100B-SoxN 2 0.985764 24104.9 1 6 CACCTG AGAACAATGG + +4 transfac_pro__M05142 1 0.985764 24104.9 1 6 CACCTG ATGCCGCTCC + +4 transfac_pro__M05148 3 0.985764 24104.9 1 6 CACCTG ATGCCGCTCG + +4 transfac_pro__M08972-D-Sox100B-Sox102F-Sox15 0 0.985764 24104.9 1 6 CACCTG TCCATTGTTT - +4 predrem__nrMotif1753 5 0.985764 24104.9 1 5 CACCTG TTTGTCATTT + +4 transfac_pro__M04817-Chd1 -1 0.985764 24104.9 1 5 CACCTG GTCCCGCGAG - +4 transfac_pro__M05026 6 0.985764 24104.9 1 4 CACCTG AGGCCGCCCC + +4 cisbp__M5545-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.985764 24104.9 1 3 CACCTG TTTTTATTAC + +4 taipale_cyt_meth__HOXD9_GTCGTAAAAN_FL-Abd-B-cad 7 0.985764 24104.9 1 3 CACCTG GTTTTACGAC - +4 transfac_pro__M06515 7 0.985764 24104.9 1 3 CACCTG GATTTTTTCC - +4 flyfactorsurvey__rn_SOLEXA_5_FBgn0259172-brm-hb-jim-rn-sqz 14 0.98599 24110.4 1 6 CACCTG CCACACAAAAAAAACACCAAAAACC + +4 tfdimers__MD00502-Sox100B 22 0.986045 24111.8 1 6 CACCTG ATTTTTCCCATTGTGATTGATGTTTATT - +4 tfdimers__MD00195-cad-foxo-slp2 10 0.986124 24113.7 1 6 CACCTG TTTTTTTTTTTATTTGTTTTTTTTTT - +4 tfdimers__MD00400-cad-sens-2 20 0.986139 24114.1 1 6 CACCTG TTTATCAAAATCCCTTTATGAAAAAAA + +4 taipale_cyt_meth__BARX2_NWWAAYCATTAN_FL 3 0.986299 24118 1 6 CACCTG AAAAACCATTAC + +4 taipale_cyt_meth__PAX7_NTAATYGATTAN_eDBD-ey-gsb-gsb-n-prd-toe 1 0.986299 24118 1 6 CACCTG GTAATTGATTAC + +4 transfac_pro__M08187-Abl 5 0.986299 24118 1 6 CACCTG AAAAAAAACAAC + +4 transfac_pro__M00639-onecut 5 0.986299 24118 1 6 CACCTG TTATTGATTTTT - +4 transfac_pro__M05184 6 0.986299 24118 1 6 CACCTG TTTTCCGCCCCT - +4 transfac_pro__M06383 6 0.986299 24118 1 6 CACCTG GCGTTTGCCCAG - +4 transfac_pro__M06864 6 0.986299 24118 1 6 CACCTG GCGTTTGGCCAT - +4 transfac_pro__M06868 2 0.986299 24118 1 6 CACCTG TCTGCCAATGCT - +4 transfac_pro__M07450 0 0.986299 24118 1 6 CACCTG ACCATAAATCAT - +4 tiffin__TIFDMEM0000077 -1 0.986299 24118 1 5 CACCTG ATTTCTTTCAGT + +4 transfac_pro__M01058-sens-sens-2 7 0.986299 24118 1 5 CACCTG TAAATCACTGCA + +4 transfac_pro__M06126 -1 0.986299 24118 1 5 CACCTG CCGTCGGGACAC + +4 homer__ATGCATAATTCA_Pit1+1bp-acj6-vvl 7 0.986299 24118 1 5 CACCTG TGAATTATGCAT - +4 tiffin__TIFDMEM0000004 8 0.986299 24118 1 4 CACCTG TTATTAATTAAT - +4 transfac_pro__M05758 8 0.986299 24118 1 4 CACCTG TATTTTAATCCT - +4 transfac_pro__M05218 6 0.986451 24121.7 1 6 CACCTG TGGGTTTTCCTTCCGCTTCTC + +4 transfac_pro__M05216-ERR-E(z) 13 0.986451 24121.7 1 6 CACCTG GGAGGGCGGCGGGGACCCCCC - +4 transfac_pro__M05257-ERR-vtd 15 0.986451 24121.7 1 6 CACCTG CGGGGGCGGCCGGGCAACCCC - +4 cisbp__M5831-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.986452 24121.7 1 6 CACCTG GAACAATAACATTGTTC + +4 taipale__SOX2_full_NAACAATANCATTGTTN-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.986452 24121.7 1 6 CACCTG GAACAATAACATTGTTC + +4 jaspar__MA0874.1-Awh-CG11085-CG11294-CG18599-CG32532-E5-Lim1-Lim3-OdsH-Pph13-Rx-Vsx1-al-ap-ems-en-eve-inv-otp-pdm3-repo-ro-slou-unc-4-unpg-zfh2 9 0.986452 24121.7 1 6 CACCTG TCCATTAATTAATGGAC - +4 transfac_pro__M01423-al-ap-Awh-CG11085-CG11294-CG18599-CG32532-E5-ems-en-eve-inv-Lim1-Lim3-OdsH-otp-pdm3-Pph13-repo-ro-Rx-slou-unc-4-unpg-Vsx1-zfh2 9 0.986452 24121.7 1 6 CACCTG TCCATTAATTAATGGAC - +4 taipale_cyt_meth__BACH2_NWANCATGASTCATSNTWN_eDBD-cnc-Jra-kay-Mef2-nej 2 0.986846 24131.3 1 6 CACCTG AAAGCATGACTCATCATTT + +4 transfac_pro__M05908-CG4360-jim 13 0.986846 24131.3 1 6 CACCTG TCCGAACCCATGCCACTAA - +4 taipale_cyt_meth__POU4F3_ATNAATWATGCAT_eDBD_meth-acj6-vvl 2 0.986953 24134 1 6 CACCTG ATTAATTATGCAT + +4 taipale_cyt_meth__E2F2_NWTTTGGCGCCAWWWN_eDBD_repr-E2f1-E2f2 10 0.986996 24135 1 6 CACCTG GTTTTGGCGCCATTTC + +4 stark__BNWDTYGAGTGRNHDD-z 10 0.986996 24135 1 6 CACCTG TTTACCACTCAATAAG - +4 transfac_pro__M02798-D-Sox21a-Sox21b 8 0.986996 24135 1 6 CACCTG GATAATTATAATTAGC - +4 elemento__CGCATGCG-E2f1-ewg 0 0.987046 24136.2 1 6 CACCTG CGCATGCG + +4 elemento__ATCATGCG 0 0.987046 24136.2 1 6 CACCTG CGCATGAT - +4 elemento__CGCAAGCG 0 0.987046 24136.2 1 6 CACCTG CGCTTGCG - +4 taipale__BARX1_DBD_NYNATTAN-Ubx 1 0.987046 24136.2 1 6 CACCTG CTAATTGC - +4 jaspar__MA1026.1 -1 0.987046 24136.2 1 5 CACCTG TAATTATT + +4 cisbp__M0069 3 0.987046 24136.2 1 5 CACCTG TTCTACAA - +4 cisbp__M0613 -1 0.987046 24136.2 1 5 CACCTG ATCGCGCG - +4 cisbp__M1781 -2 0.987046 24136.2 1 4 CACCTG CCGCGCGC + +4 flyfactorsurvey__Exd_Cell_FBgn0000611-exd 4 0.987046 24136.2 1 4 CACCTG TTTTGACA + +4 cisbp__M1593-D-Sox100B-Sox102F-Sox15-Sox21a-Sox21b 4 0.987046 24136.2 1 4 CACCTG AAAACAAT - +4 cisbp__M2031-exd 4 0.987046 24136.2 1 4 CACCTG TTTTGACA - +4 cisbp__M5713-abd-A-Antp-ap-Awh-CG11085-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Dll-Dr-Drgx-E5-ems-en-eve-exex-ind-inv-lab-lbl-Lim3-lms-Lmx1a-OdsH-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-Vsx2-zen-z 5 0.987046 24136.2 1 3 CACCTG CTAATTAC + +4 cisbp__M0590 5 0.987046 24136.2 1 3 CACCTG ATTCAAAC - +4 flyfactorsurvey__CG12361_Cell_FBgn0250756-Abd-B-Dbx-cad 6 0.987046 24136.2 1 2 CACCTG TTTTATTA + +4 transfac_pro__M04829-Stat92E -4 0.987046 24136.2 1 2 CACCTG TGTGCAAT - +4 tfdimers__MD00011-fkh 4 0.987154 24138.9 1 6 CACCTG TAAAAAACTAAGTAAATATTTATTTATTAATT - +4 hdpi__HIP2-Ubc4 -1 0.98723 24140.7 1 5 CACCTG TCCGCA - +4 fantom__motif38_TCGNCA 4 0.98723 24140.7 1 2 CACCTG TCGACA + +4 hdpi__LHX2-Antp-Dfd-Scr-Ubx-ems-eve-ind-tup 4 0.98723 24140.7 1 2 CACCTG CAATTA - +4 hdpi__RBM9-Rbfox1 4 0.98723 24140.7 1 2 CACCTG ATTGCA - +4 transfac_pro__M07476-Awh 4 0.98723 24140.7 1 2 CACCTG CAATCA - +4 cisbp__M3679-nub-pdm2-vvl 6 0.987256 24141.4 1 6 CACCTG ATAATTTGCATATT + +4 flyfactorsurvey__Dip3_SANGER_5_FBgn0040465-Dlip3 2 0.987256 24141.4 1 6 CACCTG CAAATCTTCTCACA + +4 cisbp__M3916-D-Sox100B-SoxN 1 0.987256 24141.4 1 6 CACCTG TCCCATTGTTCTTA - +4 cisbp__M5869-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.987263 24141.5 1 6 CACCTG AACAATAACATTGTT + +4 stark__WAATKNNNNNCRCGY 4 0.987263 24141.5 1 6 CACCTG AAATGAAAAACACGC + +4 taipale__SRY_DBD_AACAATANCATTGTT-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 6 0.987263 24141.5 1 6 CACCTG AACAATAACATTGTT + +4 predrem__nrMotif288-sqz 0 0.987263 24141.5 1 6 CACCTG TTTTTTTGTTTGTTT - +4 transfac_pro__M01445 5 0.987263 24141.5 1 6 CACCTG CAATAATCCGCTTTT - +4 predrem__nrMotif1831 4 0.987392 24144.7 1 6 CACCTG CCCGCGCCGAG + +4 cisbp__M4314 -1 0.987392 24144.7 1 5 CACCTG AAATTAATAAT + +4 cisbp__M6298-abd-A-Ubx -1 0.987392 24144.7 1 5 CACCTG GCATTAATCAA + +4 taipale_cyt_meth__HOXA13_NCCAATAAAAM_eDBD_meth-Abd-B -1 0.987392 24144.7 1 5 CACCTG ACCAATAAAAC + +4 yetfasco__YIR018W_777 6 0.987392 24144.7 1 5 CACCTG ATTATTAATTT + +4 hocomoco__HXB8_HUMAN.H11MO.0.C-Ubx-abd-A -1 0.987392 24144.7 1 5 CACCTG GCATTAATCAA - +4 scertf__zhu.NDT80 7 0.987392 24144.7 1 4 CACCTG GCCACAAAAAC + +4 cisbp__M2025-Abd-B-cad-eve 7 0.987392 24144.7 1 4 CACCTG TTTTTATGGCC - +4 cisbp__M1977-B-H1-B-H2-CG11085 1 0.987501 24147.4 1 6 CACCTG TTAATTG + +4 cisbp__M2044-abd-A-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Drgx-E5-ems-en-eve-hbn-ind-inv-lab-lbl-Lim1-Lim3-Lmx1a-OdsH-otp-pb-Pph13-repo-ro-Rx-Scr-slou-Traf4-unc-4-unpg-Vsx1-V 1 0.987501 24147.4 1 6 CACCTG TTAATTA + +4 cisbp__M2248-CG34031 1 0.987501 24147.4 1 6 CACCTG TTAATTG + +4 jaspar__MA0168.1-B-H1-B-H2-CG11085 1 0.987501 24147.4 1 6 CACCTG TTAATTG + +4 jaspar__MA0236.1-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Drgx-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Vsx1-Vsx2-abd-A-al-ap-ems-en-eve-hbn-ind-inv-lab-lbl-otp-pb-repo-ro-slou-unc 1 0.987501 24147.4 1 6 CACCTG TTAATTA + +4 jaspar__MA0444.1-CG34031 1 0.987501 24147.4 1 6 CACCTG TTAATTG + +4 predrem__nrMotif2244 -1 0.987501 24147.4 1 5 CACCTG TGCTTCT + +4 predrem__nrMotif1057 -1 0.987501 24147.4 1 5 CACCTG TCCCAAA - +4 cisbp__M1998-abd-A-al-Antp-ap-Awh-bsh-btn-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-E5-ems-en-eve-ftz-hbn-ind-inv-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-nub-OdsH-otp-pb-pdm2-pdm3-Pph13-repo-ro-Rx-Scr 4 0.987501 24147.4 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__Zen2_SOLEXA_FBgn0004054-Antp-Awh-C15-CG9876-CG11294-CG18599-CG32532-Dfd-E5-HGTX-Lim1-Lim3-Lmx1a-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-en-eve-ftz-hbn-ind-lab-lbe-lbl-lms-otp-pb-pd 4 0.987501 24147.4 1 3 CACCTG TAATTAA - +4 jaspar__MA0189.1-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Ubx-Vsx1-Vsx2-abd-A-al-ap-bsh-btn-ems-en-eve-ftz-hbn-ind-inv-lab-lbl-lms-nub-otp-pb-pdm2-pdm3-r 4 0.987501 24147.4 1 3 CACCTG TAATTAA - +4 cisbp__M1975-Antp-bsh-btn-CG18599-Dfd-E5-ems-ftz-pb-Scr-zen-zen2 5 0.987501 24147.4 1 2 CACCTG TTAATGA + +4 cisbp__M2015-abd-A-Antp-ap-Awh-bsh-btn-CG18599-CG32532-Dfd-E5-ems-en-eve-ftz-HGTX-lab-lbl-Lim3-otp-pb-Pph13-ro-Rx-Scr-slou-Ubx-unpg-Vsx1-zen-zen2 5 0.987501 24147.4 1 2 CACCTG TTAATTA + +4 flyfactorsurvey__AbdA_Cell_FBgn0000014-Antp-Awh-CG18599-Dfd-E5-HGTX-Lim3-Pph13-Rx-Scr-Ubx-Vsx1-abd-A-ap-bsh-btn-ems-eve-ftz-lab-lbl-otp-pb-ro-slou-unpg-zen-zen2 5 0.987501 24147.4 1 2 CACCTG TTAATTA + +4 transfac_pro__M09169 14 0.987811 24154.9 1 6 CACCTG TTTTTTTTTGTCGTTTTGTG + +4 dbcorrdb__NELFE__ENCSR000DOF_1__m6-bon-Brf-brm-btd-CoRest-CrebB-crol-ct-CTCF-dar1-E2f1-ERR-E(z)-Hcf-HDAC1-Jra-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-Taf1-TfAP-2-tna-vtd-zfh1 3 0.987811 24154.9 1 6 CACCTG CCCCCCCCCCCCCGGCCCCC - +4 cisbp__M5640-Dr-HGTX-ind 0 0.98782 24155.2 1 6 CACCTG TAATTGGTTTTTAATTGC + +4 taipale_cyt_meth__SOX10_AACAATNNNNNNATTGTT_FL_meth-Sox100B 9 0.98782 24155.2 1 6 CACCTG AACAATGGATCCATTGTT + +4 transfac_pro__M06852 15 0.98782 24155.2 1 3 CACCTG AAAGAGCACGCCGCGCAC - +4 elemento__CGCACGCGC 2 0.987826 24155.3 1 6 CACCTG CGCACGCGC + +4 hdpi__XG 0 0.987826 24155.3 1 6 CACCTG TTCCATCAT - +4 predrem__nrMotif1160 0 0.987826 24155.3 1 6 CACCTG TTGCTCAAA - +4 predrem__nrMotif1631 1 0.987826 24155.3 1 6 CACCTG TTTGCTGCA - +4 elemento__AAATGCAAA -1 0.987826 24155.3 1 5 CACCTG AAATGCAAA + +4 elemento__ATCCCAGCA 4 0.987826 24155.3 1 5 CACCTG ATCCCAGCA + +4 elemento__GCCACGCCC-btd-cbt-CG3065-CG42741-dar1-Klf15-luna-Sp1-Spps 4 0.987826 24155.3 1 5 CACCTG GCCACGCCC + +4 elemento__GCCCCGCCC-btd-CG42741-dar1-kay-luna-Nf-YB-Sp1-Spps-Stat92E 4 0.987826 24155.3 1 5 CACCTG GCCCCGCCC + +4 cisbp__M0597 -1 0.987826 24155.3 1 5 CACCTG AATTTAAAA - +4 hdpi__TBPL1-Trf2 -1 0.987826 24155.3 1 5 CACCTG GCCATTAAT - +4 transfac_pro__M00728-D-Sox100B-Sox102F-Sox15-SoxN -2 0.987826 24155.3 1 4 CACCTG CCTATTGTT + +4 stark__TGTCAATTG 5 0.987826 24155.3 1 4 CACCTG CAATTGACA - +4 predrem__nrMotif2270 0 0.987906 24157.3 1 6 CACCTG ATTCTGTCTT + +4 transfac_pro__M05053 1 0.987906 24157.3 1 6 CACCTG AGGCCGACAA + +4 transfac_pro__M05047 1 0.987906 24157.3 1 6 CACCTG GGAGCGGCAT - +4 transfac_pro__M05017 6 0.987906 24157.3 1 4 CACCTG TTTCGACAGT + +4 cisbp__M4286 -2 0.987906 24157.3 1 4 CACCTG TCTTTTGCTG - +4 taipale__HOXC10_DBD_GTAATWAAAN-abd-A-Abd-B-cad-Dbx-eve-Ubx 7 0.987906 24157.3 1 3 CACCTG TTTTTATTAC - +4 taipale_cyt_meth__HOXD9_RTCGTAAAAN_eDBD-Abd-B-cad 7 0.987906 24157.3 1 3 CACCTG ATTTTACGAC - +4 taipale_cyt_meth__ONECUT1_NTATTGATYN_eDBD_meth_repr-onecut 7 0.987906 24157.3 1 3 CACCTG CAATCAATAA - +4 transfac_pro__M05993 7 0.987906 24157.3 1 3 CACCTG GCGCACGCAT - +4 transfac_pro__M05110 -4 0.987906 24157.3 1 2 CACCTG TGAGCGGCAT - +4 tfdimers__MD00199 9 0.987978 24159 1 6 CACCTG TAATTTAATTAATTTAATGAAATT - +4 tfdimers__MD00394-cad 22 0.988311 24167.2 1 6 CACCTG ATATATTATTTATGAAATTTTTTTTTTA - +4 tfdimers__MD00109-cad-Taf7-Tbp 21 0.988377 24168.8 1 6 CACCTG TTTTTTTAATAAATATTTATATAATTT + +4 cisbp__M0728-croc-FoxK-foxo-FoxP 6 0.988409 24169.6 1 6 CACCTG AATAAACAAACA + +4 transfac_pro__M04776-Jra 3 0.988409 24169.6 1 6 CACCTG AGTCATACTGAA + +4 cisbp__M5154-pho-phol-RpII215-Taf1 5 0.988409 24169.6 1 6 CACCTG GCCGCCATTTTG - +4 flyfactorsurvey__pho_SANGER_10_FBgn0002521-RpII215-Taf1-pho-phol 5 0.988409 24169.6 1 6 CACCTG GCCGCCATTTTG - +4 transfac_pro__M05276 0 0.988409 24169.6 1 6 CACCTG ATACTCGAGTCA - +4 transfac_pro__M06010 6 0.988409 24169.6 1 6 CACCTG TCTTTTGCCCAA - +4 transfac_pro__M06691 2 0.988409 24169.6 1 6 CACCTG CACACACGACTC - +4 bergman__br-Z1-br -1 0.988409 24169.6 1 5 CACCTG ACTTGTCAATTA - +4 tiffin__TIFDMEM0000104 7 0.988409 24169.6 1 5 CACCTG AAATAAATAAAT - +4 transfac_pro__M05900 7 0.988409 24169.6 1 5 CACCTG TCGCTTGGCCCA - +4 transfac_pro__M05824 8 0.988409 24169.6 1 4 CACCTG TCGGGCTAAATC + +4 transfac_pro__M05944 -2 0.988409 24169.6 1 4 CACCTG TCTTCAGCAAAA - +4 transfac_pro__M06407 -4 0.988409 24169.6 1 2 CACCTG TGTTTTTTAAAG - +4 cisbp__M5830-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 7 0.988534 24172.6 1 6 CACCTG CATCAATAACATTGATC + +4 hocomoco__HMX1_HUMAN.H11MO.0.D-Hmx-ind 2 0.988534 24172.6 1 6 CACCTG GTTAATTGCTTTTTAAT + +4 taipale_cyt_meth__ZBTB22_NKCACTANNNTAGTGMN_eDBD_meth_repr 2 0.988534 24172.6 1 6 CACCTG TTCACTATAATAGTGAA + +4 taipale__SOX2_DBD_NATCAATNNNATTGATN-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 7 0.988534 24172.6 1 6 CACCTG CATCAATAACATTGATC - +4 transfac_pro__M01363-Antp-C15-CG4328-Dfd-HGTX-Lim1-Lim3-Lmx1a-otp-Scr-vvl 0 0.988534 24172.6 1 6 CACCTG CAAATTAATTAAAAACT - +4 transfac_pro__M05585 -3 0.988534 24172.6 1 3 CACCTG CTAAGCGTGGATGGCCG + +4 transfac_pro__M09191-E2f2 15 0.98857 24173.5 1 6 CACCTG TTTTGGCGGGAAAATTTTTTT - +4 stark__KVRKRNTCACTSRNTVHDB-eyg 7 0.988897 24181.5 1 6 CACCTG GGAGAATCACTCAATGTTT + +4 scertf__foat.RGM1 1 0.988981 24183.6 1 6 CACCTG GCTCGTGTCGGGG - +4 taipale__SOX21_DBD_TGAATNNNAKTCA-D-Sox15-Sox21a-Sox21b-SoxN 5 0.988981 24183.6 1 6 CACCTG TGAATAACATTCA - +4 transfac_pro__M05378 7 0.989001 24184 1 6 CACCTG TTGGGCTTATTTAAAG + +4 cisbp__M0836 2 0.989006 24184.2 1 6 CACCTG CCAATCAA + +4 cisbp__M5301-eve-ind-Ubx 1 0.989006 24184.2 1 6 CACCTG CTAATTGC + +4 jaspar__MA0611.1 2 0.989006 24184.2 1 6 CACCTG CCAATCAA + +4 predrem__nrMotif1163 2 0.989006 24184.2 1 6 CACCTG TGCATCAT + +4 taipale_cyt_meth__SOX30_GAACAATN_eDBD_meth-Sox102F 1 0.989006 24184.2 1 6 CACCTG GAACAATG + +4 elemento__AATTAATT-Lim3-vvl 3 0.989006 24184.2 1 5 CACCTG AATTAATT + +4 predrem__nrMotif1772 -1 0.989006 24184.2 1 5 CACCTG AGCATTAT + +4 elemento__AGAGAGCG 3 0.989006 24184.2 1 5 CACCTG CGCTCTCT - +4 cisbp__M5260-abd-A-Abd-B-Antp-bsh-btn-C15-cad-Dbx-ems-ftz-lab-pb-Scr-Ubx-zen2 4 0.989006 24184.2 1 4 CACCTG TCATTAAA - +4 flyfactorsurvey__Ubx_SOLEXA_FBgn0003944-Abd-B-Antp-C15-Dbx-Scr-Ubx-abd-A-bsh-btn-cad-ems-ftz-lab-pb-zen2 4 0.989006 24184.2 1 4 CACCTG TCATTAAA - +4 jaspar__MA0360.1 5 0.989006 24184.2 1 3 CACCTG TGCGGAAC + +4 taipale_cyt_meth__HOXC4_NTMATTAN_FL_repr-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-Lim3-pb-Scr-Ubx-zen-zen2 5 0.989006 24184.2 1 3 CACCTG GTCATTAA + +4 transfac_pro__M01912 5 0.989006 24184.2 1 3 CACCTG TGCGGAAC - +4 homer__TAGCGCGC_DPL-1 6 0.989006 24184.2 1 2 CACCTG GCGCGCTA - +4 hdpi__ZNF26 -1 0.989228 24189.6 1 5 CACCTG GCCAAA + +4 swissregulon__hs__HBP1_HMGB_SSRP1_UBTF.p2-D-Ssrp -1 0.989228 24189.6 1 5 CACCTG AACAAT - +4 cisbp__M4912-Dlip3 2 0.989233 24189.7 1 6 CACCTG CAAATCTTCTCACA + +4 cisbp__M6285-onecut 6 0.989233 24189.7 1 6 CACCTG TTTATTGATTTTTT + +4 cisbp__M5212-dati-FoxP-rn-sqz 9 0.989233 24189.7 1 6 CACCTG CACACAAAAAAAACC + +4 cisbp__M5829-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.989233 24189.7 1 6 CACCTG ATGAATAACATTCAT + +4 flyfactorsurvey__sqz_SOLEXA_5_FBgn0010768-FoxP-dati-rn-sqz 9 0.989233 24189.7 1 6 CACCTG CACACAAAAAAAACA + +4 taipale__NFATC1_full_TTTCCAYNRTGGAAA_repr-NFAT 1 0.989233 24189.7 1 6 CACCTG TTTCCATAATGGAAA + +4 transfac_public__M00024-E2f1 9 0.989233 24189.7 1 6 CACCTG TTGGCGCGAAAATTG + +4 cisbp__M5657-NFAT 1 0.989233 24189.7 1 6 CACCTG TTTCCATAATGGAAA - +4 taipale__SOX2_DBD_NTGAATNNNATTCAN-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.989233 24189.7 1 6 CACCTG ATGAATAACATTCAT - +4 taipale_cyt_meth__SP1_NWRGCCACGCCCMYN_eDBD_meth-btd-cbt-CG3065-CG42741-dar1-kay-Klf15-luna-Nf-YA-Nf-YB-Sp1-Spps 9 0.989233 24189.7 1 6 CACCTG AGTGGGCGTGGCTTA - +4 transfac_pro__M07787-ap-btn-Dll-dve-nub-pdm2-vvl 4 0.989233 24189.7 1 6 CACCTG TAATTAGCATAATTA - +4 transfac_pro__M09162 9 0.989233 24189.7 1 6 CACCTG TTTTGTCGTTTTGTG - +4 transfac_pro__M09147 10 0.989233 24189.7 1 5 CACCTG TCATCATCATCATCA + +4 cisbp__M6060-Gsc-oc 11 0.989233 24189.7 1 4 CACCTG GTTAATCCGATTAAC + +4 taipale__EGR3_DBD_NNACGCCCACGCANN-btd-klu-Spps-sr 11 0.989233 24189.7 1 4 CACCTG CTACGCCCACGCACT + +4 cisbp__M5369-btd-klu-Spps-sr 11 0.989233 24189.7 1 4 CACCTG CTACGCCCACGCACT - +4 taipale_cyt_meth__MIXL1_TAATYNRATTA_FL_meth-al-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-hbn-OdsH-Optix-repo-Traf4-unc-4 0 0.989343 24192.4 1 6 CACCTG TAATTAAATTA - +4 predrem__nrMotif1814 7 0.989343 24192.4 1 4 CACCTG CCCCGCGTCCC + +4 taipale_cyt_meth__HOXD13_NCCAATAAAAN_eDBD_meth-Abd-B 7 0.989343 24192.4 1 4 CACCTG ACCAATAAAAC + +4 jaspar__MA0216.2-Abd-B-cad-eve 7 0.989343 24192.4 1 4 CACCTG TTTTTATGGCC - +4 cisbp__M2268-Irbp18-Myc-nej-Xrp1 8 0.989343 24192.4 1 3 CACCTG TATTGCACAAT + +4 transfac_pro__M07080-Irbp18-Myc-nej-Xrp1 8 0.989343 24192.4 1 3 CACCTG TATTGCACAAT + +4 cisbp__M1980-CG11085-lms 1 0.989428 24194.5 1 6 CACCTG TTAATTG + +4 jaspar__MA0171.1-CG11085-lms 1 0.989428 24194.5 1 6 CACCTG TTAATTG + +4 predrem__nrMotif117 -3 0.989428 24194.5 1 3 CACCTG CAGTCTC + +4 cisbp__M2024-bsh-btn-Dfd-HGTX-Scr 4 0.989428 24194.5 1 3 CACCTG TCATTAA - +4 cisbp__M4786-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-HGTX-ind-lab-pb-Scr-Ubx-zen-zen2 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 cisbp__M5146-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-ind-lab-Lim3-otp-pb-ro-Scr-Ubx-Vsx1-zen-zen2 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 cisbp__M5279-abd-A-Antp-ap-Awh-bsh-btn-C15-CG11294-CG18599-CG32532-CG9876-Dbx-Dfd-E5-ems-en-eve-ftz-hbn-HGTX-ind-lab-lbe-lbl-Lim1-Lim3-lms-Lmx1a-otp-pb-Pph13-repo-ro-Rx-Scr-slou-tup-Ubx-unpg-Vsx1-zen- 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__Btn_SOLEXA_FBgn0014949-Antp-Awh-CG18599-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-ind-lab-pb-zen-zen2 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__Ftz_SOLEXA_FBgn0001077-Antp-Awh-CG18599-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-lab-pb-slou-unpg-zen-zen2 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 flyfactorsurvey__Pb_SOLEXA_FBgn0051481-Antp-Awh-CG18599-Dfd-E5-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-ind-lab-otp-pb-zen-zen2 4 0.989428 24194.5 1 3 CACCTG TAATTAA - +4 predrem__nrMotif1218 5 0.989428 24194.5 1 2 CACCTG TTGCTCA + +4 predrem__nrMotif2070 5 0.989428 24194.5 1 2 CACCTG TAATTCA - +4 predrem__nrMotif2675 5 0.989428 24194.5 1 2 CACCTG CAATCCA - +4 predrem__nrMotif347 5 0.989428 24194.5 1 2 CACCTG GAATTCA - +4 tfdimers__MD00213-Taf7-Tbp 5 0.989667 24200.3 1 6 CACCTG ATAAAAAACCAATAAAATTTTTATATTAATA + +4 predrem__nrMotif644 1 0.989695 24201 1 6 CACCTG GAGACTGTG + +4 predrem__nrMotif767 1 0.989695 24201 1 6 CACCTG TGATTTTGA + +4 predrem__nrMotif1014 2 0.989695 24201 1 6 CACCTG AGAATCAAA - +4 predrem__nrMotif573 5 0.989695 24201 1 4 CACCTG ATGGCTTCT - +4 swissregulon__hs__SOX_8_9_10_.p2-D-Sox100B-Sox102F-SoxN -2 0.989695 24201 1 4 CACCTG CCATTGTTC - +4 yetfasco__YIR023W_53 11 0.989737 24202 1 6 CACCTG GTCGGCCTTAGAGCCGAC + +4 cisbp__M4315 11 0.989737 24202 1 6 CACCTG GTCGGCCTTAGAGCCGAC - +4 taipale_cyt_meth__SOX10_AACAATNNNNNNATTGTT_FL_repr-Sox100B 9 0.989737 24202 1 6 CACCTG AACAATGGATCCATTGTT - +4 dbcorrdb__EP300__ENCSR000DZT_1__m3-nej 14 0.989746 24202.3 1 6 CACCTG TATAATAGTTTAAATTATTT + +4 dbcorrdb__POLR2A__ENCSR000EZQ_1__m2-Brf-brm-CTCF-ERR-E(z)-HDAC1-Nelf-E-Rbbp5-RpII215-Spt20-SREBP-tna-vtd 13 0.989746 24202.3 1 6 CACCTG CTACCGCGCGCCCCGCCCCG + +4 transfac_pro__M09167 14 0.989746 24202.3 1 6 CACCTG TTTTTTTTTGTCGTTTTCTG + +4 taipale__NFATC1_full_NATGGAAANWWWWTTTYCMN_repr-NFAT 15 0.989746 24202.3 1 5 CACCTG AATGGAAAATTATTTTCCCT + +4 cisbp__M5656-NFAT 15 0.989746 24202.3 1 5 CACCTG AATGGAAAATTATTTTCCCT - +4 dbcorrdb__BRF1__ENCSR000DNW_1__m2-bon-Brf-brm-btd-CoRest-CrebB-CTCF-E2f1-ERR-ewg-E(z)-Hcf-HDAC1-Jra-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna-vtd-zfh1 -2 0.989746 24202.3 1 4 CACCTG CCCCCCCCGCGGCGGGCCGG - +4 cisbp__M5709-ey-eyg-gsb-gsb-n-prd-toe 0 0.989775 24203 1 6 CACCTG TAATCGATTA + +4 predrem__nrMotif853 1 0.989775 24203 1 6 CACCTG TTTGCTGTCA + +4 taipale__PAX7_DBD_TAATYRATTA-ey-eyg-gsb-gsb-n-prd-toe 0 0.989775 24203 1 6 CACCTG TAATCGATTA + +4 transfac_pro__M03175 4 0.989775 24203 1 6 CACCTG ATGCCGCCCA + +4 transfac_pro__M05045 4 0.989775 24203 1 6 CACCTG TTGCCGCCGA + +4 transfac_pro__M05100 4 0.989775 24203 1 6 CACCTG ATGCCGCCCA + +4 taipale_cyt_meth__HOXD10_RTCGTAAAAN_eDBD-Abd-B-cad 4 0.989775 24203 1 6 CACCTG GTTTTACGAC - +4 transfac_pro__M03176 1 0.989775 24203 1 6 CACCTG TGAGCGGCAT - +4 transfac_pro__M06291 6 0.989775 24203 1 4 CACCTG GTTGGGGAGC + +4 predrem__nrMotif705 6 0.989775 24203 1 4 CACCTG AAAATTTAAA - +4 transfac_pro__M07510 6 0.989775 24203 1 4 CACCTG AGAATATTCC - +4 taipale_cyt_meth__ONECUT2_NTATTGATYN_eDBD_meth-onecut 7 0.989775 24203 1 3 CACCTG AAATCAATAA - +4 transfac_pro__M03182 7 0.989775 24203 1 3 CACCTG AATGGCCCAA - +4 tfdimers__MD00240-E2f1-pan 3 0.989942 24207.1 1 6 CACCTG TTTTTCTTTTCTTCTTTCTTTTTTTTTTTT + +4 taipale_cyt_meth__PAX3_NTAATYGATTAN_eDBD_meth-ey-gsb-gsb-n-prd-toe 1 0.990242 24214.4 1 6 CACCTG CTAATTGATTAT + +4 transfac_pro__M01193 5 0.990242 24214.4 1 6 CACCTG CGCATTAAATGC + +4 transfac_pro__M06098 3 0.990242 24214.4 1 6 CACCTG TCCCCCATTGCT - +4 homer__GGCCATAAATCA_Hoxc9-cad-eve 7 0.990242 24214.4 1 5 CACCTG GGCCATAAATCA + +4 transfac_pro__M06023 -2 0.990242 24214.4 1 4 CACCTG CCGTATTGGAGT - +4 tfdimers__MD00440 21 0.990264 24214.9 1 6 CACCTG AAAAAAAAACAAACAAAAAAGAACATTT - +4 hocomoco__SHOX2_HUMAN.H11MO.0.D-Awh-B-H1-B-H2-C15-CG4328-CG9876-CG18599-CG34367-Dbx-Dll-Dr-E5-Lim3-Lmx1a-OdsH-Pph13-Rx-Vsx1-Vsx2-al-bsh-ems-en-exex-gsb-gsb-n-ind-inv-lab-lbe-lms-otp-pdm3-prd-repo-ro-u 5 0.990349 24217 1 6 CACCTG CTAATTAGTTAATTTTA + +4 taipale_cyt_meth__HSFY1_NTTCGAANNNTTCGAAN_eDBD_meth 5 0.990349 24217 1 6 CACCTG ATTCGAACCGTTCGAAC + +4 taipale_cyt_meth__MTF1_NYTTTGCACACGRYNYN_eDBD_repr-MTF-1 8 0.990349 24217 1 6 CACCTG CTTTTGCACACGGCCTT + +4 transfac_pro__M09163 11 0.990349 24217 1 6 CACCTG TTTTTTGTCGTTTTGTG - +4 taipale_cyt_meth__ZNF713_NMGACGACTGCCACGAAAN_eDBD_repr 4 0.990682 24225.1 1 6 CACCTG TCGACGACTGCCACGAAAG + +4 transfac_pro__M08993 5 0.990682 24225.1 1 6 CACCTG GTCCGCCCCGTCGAACAAT + +4 elemento__ATAATTGC 1 0.990717 24226 1 6 CACCTG ATAATTGC + +4 elemento__TAATTGCA 0 0.990717 24226 1 6 CACCTG TAATTGCA + +4 elemento__TAATTGGC 0 0.990717 24226 1 6 CACCTG TAATTGGC + +4 elemento__TTAATTGC 1 0.990717 24226 1 6 CACCTG TTAATTGC + +4 c2h2_zfs__M0401 1 0.990717 24226 1 6 CACCTG CCATCCCA - +4 transfac_pro__M09114 1 0.990717 24226 1 6 CACCTG TAATCATA - +4 elemento__AGCAACAA 3 0.990717 24226 1 5 CACCTG TTGTTGCT - +4 jaspar__MA0282.1 -3 0.990717 24226 1 3 CACCTG CTCGGAAA + +4 transfac_pro__M01852 -3 0.990717 24226 1 3 CACCTG TTTCCGAG + +4 yetfasco__YMR168C_524 -3 0.990717 24226 1 3 CACCTG CTCGGAAA + +4 cisbp__M4372 -3 0.990717 24226 1 3 CACCTG CTCGGAAA - +4 cisbp__M0983-Dbx 6 0.990717 24226 1 2 CACCTG ATTAATTA + +4 cisbp__M0310-nej -4 0.990717 24226 1 2 CACCTG TTTCGCAA - +4 cisbp__M5828-D-Sox15-Sox21a-Sox21b-SoxN 5 0.990748 24226.8 1 6 CACCTG TGAATAACATTCA + +4 cisbp__M6243-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 8 0.990748 24226.8 1 5 CACCTG AAAAAATAAACAA + +4 jaspar__MA0135.1-Lim3-vvl 8 0.990748 24226.8 1 5 CACCTG AAATTAATTAATC + +4 cisbp__M1954-Lim3-vvl 8 0.990748 24226.8 1 5 CACCTG AAATTAATTAATC - +4 hocomoco__FOXJ3_HUMAN.H11MO.0.A-FoxK-FoxL1-bin-fd19B-fd102C-foxo-slp1-slp2 8 0.990748 24226.8 1 5 CACCTG AAAAAATAAACAA - +4 transfac_pro__M07808-bsh-CG15696-CG34367-CG9876 5 0.99075 24226.8 1 6 CACCTG TCAATAAACCAATTAA + +4 stark__GCATAHWWWNNNGCGY 1 0.99075 24226.8 1 6 CACCTG ACGCAAAAAATTATGC - +4 tfdimers__MD00381-Sox100B 2 0.990931 24231.2 1 6 CACCTG TTTAACATTGTACAATGTTATA + +4 hdpi__POLI-DNApol-iota 0 0.990943 24231.5 1 6 CACCTG GAGCGC + +4 bergman__pho-pho -1 0.990943 24231.5 1 5 CACCTG GCCATT + +4 stark__CAACAA-Aef1 1 0.990943 24231.5 1 5 CACCTG CAACAA + +4 bergman__ap-ap 4 0.990943 24231.5 1 2 CACCTG AAATTA - +4 cisbp__M5818-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.990954 24231.8 1 6 CACCTG AACAATAACATTGTT + +4 cisbp__M5823-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.990954 24231.8 1 6 CACCTG ATGAATTCCATTCAT + +4 cisbp__M6087-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.990954 24231.8 1 6 CACCTG AACAATTTCAGTGTT + +4 taipale__SOX15_full_AACAATAMCATTGTT-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.990954 24231.8 1 6 CACCTG AACAATAACATTGTT + +4 taipale__SOX18_full_ATGAATWYCATTCAT-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 6 0.990954 24231.8 1 6 CACCTG ATGAATTCCATTCAT + +4 taipale__Sox11_DBD_AACAATTGCAGTGTT-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.990954 24231.8 1 6 CACCTG AACAATTTCAGTGTT + +4 transfac_pro__M07357-onecut 6 0.990954 24231.8 1 6 CACCTG TTTATTGATTTTTAT - +4 taipale__Otx1_DBD_NNTAATCCGATTANN_repr-Gsc-oc 11 0.990954 24231.8 1 4 CACCTG GTTAATCCGATTAAC + +4 cisbp__M5365-btd-klu-Spps-sr 2 0.990961 24232 1 6 CACCTG TACGCCCACGCATT - +4 jaspar__MA0602.1-htk 0 0.990961 24232 1 6 CACCTG TTTAGCAATATTAG - +4 cisbp__M4758-bab1 5 0.991038 24233.8 1 6 CACCTG ATATTTAATTC + +4 transfac_pro__M01194 4 0.991038 24233.8 1 6 CACCTG GCAATAAATGC + +4 flyfactorsurvey__bab1_SANGER_5_FBgn0004870-bab1 5 0.991038 24233.8 1 6 CACCTG ATATTTAATTC - +4 predrem__nrMotif715 5 0.991038 24233.8 1 6 CACCTG AAAAAATCATA - +4 transfac_pro__M05151 0 0.991038 24233.8 1 6 CACCTG TAGCCGTTAAT - +4 transfac_pro__M01191 -1 0.991038 24233.8 1 5 CACCTG GCATTAAATGC + +4 cisbp__M6018-FoxK-slp2 7 0.991038 24233.8 1 4 CACCTG CGGACACAATC + +4 taipale__Foxk1_DBD_CGGACACAATC-FoxK-slp2 7 0.991038 24233.8 1 4 CACCTG CGGACACAATC + +4 cisbp__M0108-htk 7 0.991038 24233.8 1 4 CACCTG ACAATATTATC - +4 jaspar__MA0248.1-tup 1 0.991123 24235.9 1 6 CACCTG TTAATTG + +4 yetfasco__YHL009C_672 1 0.991123 24235.9 1 6 CACCTG TTACTAA + +4 cisbp__M4981-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-HGTX-lab-pb-Scr-slou-Ubx-unpg-zen-zen2 0 0.991123 24235.9 1 6 CACCTG TAATTAA - +4 fantom__motif74_TTKAAAY 2 0.991123 24235.9 1 5 CACCTG TTGAAAT + +4 stark__ATCATAA-TFAM -1 0.991123 24235.9 1 5 CACCTG ATCATAA + +4 yetfasco__YDR303C_580 -3 0.991123 24235.9 1 3 CACCTG CCGCGCG + +4 jaspar__MA0374.1 -3 0.991123 24235.9 1 3 CACCTG CCGCGCG - +4 hdpi__DGCR8-pasha 5 0.991123 24235.9 1 2 CACCTG ATTTGCA - +4 hdpi__SRBD1-CG31156 5 0.991123 24235.9 1 2 CACCTG ATTTGCA - +4 predrem__nrMotif523 0 0.99132 24240.8 1 6 CACCTG CATTTTTCA + +4 swissregulon__hs__SRY.p2 3 0.99132 24240.8 1 6 CACCTG GTAAACAAT + +4 cisbp__M1757 2 0.99132 24240.8 1 6 CACCTG GGCGCTTAA - +4 predrem__nrMotif114 3 0.99132 24240.8 1 6 CACCTG TTTGGCTTT - +4 swissregulon__sacCer__RDR1 4 0.99132 24240.8 1 5 CACCTG TGCGGAAAT + +4 stark__TTAATGATG -2 0.99132 24240.8 1 4 CACCTG CATCATTAA - +4 transfac_pro__M01715 6 0.99132 24240.8 1 3 CACCTG TTTGCTCAA + +4 taipale_cyt_meth__ONECUT3_NYATCGATYN_eDBD-onecut 1 0.9914 24242.7 1 6 CACCTG GTATCGATTG + +4 taipale_cyt_meth__SOX3_NGAACAATGN_FL_meth_repr-D-Sox100B-SoxN 2 0.9914 24242.7 1 6 CACCTG AGAACAATGG + +4 transfac_pro__M01695 3 0.9914 24242.7 1 6 CACCTG TAATGGCTGC - +4 transfac_pro__M06916 1 0.9914 24242.7 1 6 CACCTG GAGCCCCATA - +4 transfac_public__M00276-Sox102F-Sox15 1 0.9914 24242.7 1 6 CACCTG AAACAATGGA - +4 transfac_pro__M07448-CG13775 6 0.9914 24242.7 1 4 CACCTG TGTCGCGACA + +4 cisbp__M6035-abd-A-Abd-B-cad-CG15696-Dr-Ubx 7 0.9914 24242.7 1 3 CACCTG TTTTTATTGC + +4 cisbp__M0675 7 0.9914 24242.7 1 3 CACCTG TGGCGCGCAT - +4 taipale__Hoxd9_DBD_GTAATWAAAN-abd-A-Abd-B-cad-CG15696-Dr-Ubx 7 0.9914 24242.7 1 3 CACCTG TTTTTATTGC - +4 taipale_cyt_meth__CUX1_NYATTGATYN_eDBD_meth-ct 8 0.9914 24242.7 1 2 CACCTG GTATTGATCA + +4 taipale_tf_pairs__E2F3_ONECUT2_NNSGCGCSNNNATCGAYN_CAP_repr-E2f1-onecut 12 0.991401 24242.7 1 6 CACCTG AATCGATAATGGCGCCCT - +4 transfac_pro__M06804 -2 0.991401 24242.7 1 4 CACCTG CCGATAATTTAGAATCCC - +4 dbcorrdb__MAZ__ENCSR000EFF_1__m1-Brf-brm-btd-CG42741-CG7368-CoRest-crol-ct-CTCF-E2f1-ERR-E(z)-HDAC1-Klf15-klu-l(3)neo38-Nelf-E-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-tna-vtd 3 0.991425 24243.3 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC + +4 dbcorrdb__RAD21__ENCSR000EHX_1__m7-Brf-brm-btd-CG42741-CoRest-CrebB-ct-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Jra-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Spps-Spt20-SREBP-tna-vtd 12 0.991425 24243.3 1 6 CACCTG CCCCAGCCCCCCCCCCCCCC - +4 dbcorrdb__ZMIZ1__ENCSR000EFQ_1__m1-bon-Brf-brm-btd-CoRest-CrebB-CTCF-E2f1-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-Max-Myc-Nelf-E-Not3-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna-vtd-zfh1 1 0.991425 24243.3 1 6 CACCTG CCCCCCGCCGGCGCCGCCGG - +4 dbcorrdb__CEBPB__ENCSR000EBV_1__m2-bon-Brf-brm-btd-CoRest-CrebB-crol-ct-CTCF-E2f1-ERR-E(z)-Hcf-HDAC1-klu-l(3)neo38-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-SREBP-tna-vtd -2 0.991425 24243.3 1 4 CACCTG CCCCCCCCCCCCCCCCGGGG - +4 tfdimers__MD00417 5 0.991686 24249.7 1 6 CACCTG TTAAATAACCAATAAAATTTTTTATTATTT - +4 transfac_pro__M02044-pho-phol-RpII215-Taf1 5 0.991828 24253.2 1 6 CACCTG GCCGCCATTTTG + +4 transfac_pro__M05747-Meics 5 0.991828 24253.2 1 6 CACCTG CTGGGCATCGGC + +4 transfac_pro__M06711 1 0.991828 24253.2 1 6 CACCTG GAGTCTTAATGC + +4 taipale__E2F4_DBD_AATGGCGCCAAA-E2f1-E2f2 5 0.991828 24253.2 1 6 CACCTG TTTGGCGCCATT - +4 transfac_pro__M06071 6 0.991828 24253.2 1 6 CACCTG GCGGCCGCCCAC - +4 transfac_pro__M06357 6 0.991828 24253.2 1 6 CACCTG TATTCTTATTAG - +4 flyfactorsurvey__Dref_FlyReg_FBgn0015664-Dref 7 0.991828 24253.2 1 5 CACCTG TTATCGATAAAA - +4 transfac_pro__M06007 7 0.991828 24253.2 1 5 CACCTG TCGCTAAGCCCA - +4 transfac_pro__M06662 -2 0.991828 24253.2 1 4 CACCTG CATTCTCGTTTC - +4 taipale__SOX2_DBD_NAACAATNNNATTGTTN-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 0 0.991924 24255.5 1 6 CACCTG GAACAATACCATTGTTC - +4 transfac_pro__M09408-Atac1 1 0.992007 24257.5 1 6 CACCTG CTCTCTCTCTCTCTCTCTCTC + +4 transfac_pro__M05630 14 0.992007 24257.5 1 6 CACCTG GCGGGGATAAATCATTCCTCA - +4 transfac_pro__M09105-Atac1 -1 0.992007 24257.5 1 5 CACCTG CTCTCTCTCTCTCTCTCTCTC + +4 elemento__ATTGGCTG 2 0.992202 24262.3 1 6 CACCTG ATTGGCTG + +4 cisbp__M6471-D-Sox100B-Sox102F-Sox14-SoxN 1 0.992202 24262.3 1 6 CACCTG GAACAATG - +4 transfac_pro__M00431-Dp-E2f1-E2f2-eve-Rbf2 -2 0.992202 24262.3 1 4 CACCTG TTTCGCGC + +4 flyfactorsurvey__Antp_Cell_FBgn0000095-Antp-C15-CG18599-Scr-abd-A-bsh-btn-ems-ftz-pb-zen2 6 0.992202 24262.3 1 2 CACCTG TTTAATGA + +4 taipale_cyt_meth__BACH2_NWANCATGASTCATSNTWN_eDBD_meth-cnc-Jra-kay-Mef2-nej 9 0.992225 24262.9 1 6 CACCTG AAATGATGAGTCATGCTTT - +4 hocomoco__SOX11_HUMAN.H11MO.0.D-D-Sox14-Sox15-Sox21a-Sox21b-Sox100B-Sox102F-SoxN 0 0.992268 24263.9 1 6 CACCTG AACAATGCAATTGTTC + +4 transfac_pro__M02813-D-Sox21a-Sox21b 1 0.992268 24263.9 1 6 CACCTG GAATATTATAATTATA - +4 cisbp__M5844-Sox100B-Sox15 -1 0.992276 24264.1 1 5 CACCTG GACTGCAATTCAT - +4 taipale__SOX8_full_ATGAATKNYAGTC-Sox100B-Sox15 -1 0.992276 24264.1 1 5 CACCTG GACTGCAATTCAT - +4 jaspar__MA0151.1 2 0.992364 24266.3 1 4 CACCTG ATTAAA + +4 cisbp__M1967 2 0.992364 24266.3 1 4 CACCTG ATTAAA - +4 transfac_pro__M02086-cad -4 0.992364 24266.3 1 2 CACCTG TTTATT + +4 transfac_pro__M09186 5 0.992448 24268.3 1 6 CACCTG TTTTAAATTTTTAAA + +4 transfac_pro__M09215 8 0.992448 24268.3 1 6 CACCTG AAAGAATATTCTAAT - +4 cisbp__M5700-Gsc-oc 11 0.992448 24268.3 1 4 CACCTG AATAATCGGATTAAC - +4 taipale__OTX2_DBD_NNTAATCCGMTTANN-Gsc-oc 11 0.992448 24268.3 1 4 CACCTG GTTAATCGGATTAAC - +4 taipale__EGR1_DBD_NMCGCCCMCGCANN_repr-btd-klu-Spps-sr 2 0.992462 24268.7 1 6 CACCTG TACGCCCACGCATT + +4 taipale__ONECUT1_full_NNAAAATCRATAWN-ct-onecut 10 0.992462 24268.7 1 4 CACCTG AAAAAATCGATAAT + +4 cisbp__M5695-ct-onecut 10 0.992462 24268.7 1 4 CACCTG AAAAAATCGATAAT - +4 cisbp__M5626-btn 11 0.992462 24268.7 1 3 CACCTG TTAATGATGATTAG - +4 taipale_cyt_meth__ZNF454_TRGCGCCGGCGCYN_eDBD_meth-brk 12 0.992462 24268.7 1 2 CACCTG TGGCGCCGGCGCCA - +4 transfac_pro__M00681 1 0.992501 24269.6 1 6 CACCTG TTATTCAGTCA + +4 transfac_pro__M07768-al-ap-Awh-bsh-CG11294-CG32532-CG34367-CG9876-Drgx-E5-ems-hbn-Lim3-OdsH-Optix-otp-Pph13-repo-Rx-Traf4-unc-4-Vsx1 1 0.992501 24269.6 1 6 CACCTG TAATTTAATTA + +4 hocomoco__DRGX_HUMAN.H11MO.0.D-CG9876-CG11294-CG32532-CG34367-Drgx-OdsH-Optix-Traf4-al-bsh-eve-hbn-otp-repo-unc-4 4 0.992501 24269.6 1 6 CACCTG TAATTAAATTA - +4 cisbp__M4287 -2 0.992501 24269.6 1 4 CACCTG TCTTTTTGCTG - +4 transfac_pro__M05329 7 0.992501 24269.6 1 4 CACCTG GCCCCCCAATC - +4 taipale_cyt_meth__ONECUT2_NTATTGATTWN_FL_meth-onecut 8 0.992501 24269.6 1 3 CACCTG AAAATCAATAA - +4 cisbp__M2023-abd-A-Antp-bsh-C15-Dfd-ems-en-Scr-slou-tup-Ubx 1 0.992595 24271.9 1 6 CACCTG TTAATTG + +4 cisbp__M2055-tup 1 0.992595 24271.9 1 6 CACCTG TTAATTG + +4 jaspar__MA0214.1-Antp-C15-Dfd-Scr-Ubx-abd-A-bsh-ems-en-tup 1 0.992595 24271.9 1 6 CACCTG TTAATTG + +4 jaspar__MA0391.1 0 0.992595 24271.9 1 6 CACCTG TTCCGAG + +4 transfac_pro__M01934 -3 0.992595 24271.9 1 3 CACCTG CCGCGCG + +4 transfac_pro__M09185 4 0.992595 24271.9 1 3 CACCTG TGAAAAC + +4 cisbp__M2000-abd-A-Antp-ap-bsh-Dbx-Dfd-E5-en-HGTX-lab-lbl-Scr-slou-Ubx-zen2 4 0.992595 24271.9 1 3 CACCTG TAATTAA - +4 jaspar__MA0191.1-Antp-Dbx-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-en-lab-lbl-slou-zen2 4 0.992595 24271.9 1 3 CACCTG TAATTAA - +4 predrem__nrMotif334 -4 0.992595 24271.9 1 2 CACCTG TTTCAAA - +4 elemento__CGCATGCGC-E2f1-ewg 0 0.992727 24275.2 1 6 CACCTG CGCATGCGC + +4 predrem__nrMotif1910 1 0.992727 24275.2 1 6 CACCTG TTTCCAATT + +4 transfac_pro__M04797-btd-klu-Spps-sr 1 0.992727 24275.2 1 6 CACCTG CCGCCCCCG + +4 predrem__nrMotif1463 2 0.992727 24275.2 1 6 CACCTG TTTGCATAA - +4 predrem__nrMotif1275 4 0.992727 24275.2 1 5 CACCTG GAATTCTCT + +4 taipale_tf_pairs__BACH1_ATGACTCAT_HT-cnc 4 0.992727 24275.2 1 5 CACCTG ATGACTCAT + +4 hocomoco__FOXO4_HUMAN.H11MO.0.C-FoxK-FoxL1-FoxP-bin-fd19B-fd102C-foxo-slp1-slp2 5 0.992727 24275.2 1 4 CACCTG TTGTTTATT + +4 transfac_pro__M04690-Irbp18-slbo-Xrp1 5 0.992727 24275.2 1 4 CACCTG TTGCGCAAT - +4 transfac_pro__M01824 6 0.992727 24275.2 1 3 CACCTG TTTGCTCAA + +4 transfac_pro__M07942-rn 6 0.992727 24275.2 1 3 CACCTG CATAAAAAC + +4 cisbp__M0254 6 0.992727 24275.2 1 3 CACCTG ACCGCGCAC - +4 predrem__nrMotif1214 4 0.992804 24277 1 6 CACCTG AGAGCCCAAG + +4 taipale_cyt_meth__SOX8_AGAACAATGN_eDBD-D-Sox100B-Sox102F-Sox14-SoxN 2 0.992804 24277 1 6 CACCTG AGAACAATGG + +4 predrem__nrMotif2515 3 0.992804 24277 1 6 CACCTG TGAGTCTTTG - +4 transfac_pro__M05010 1 0.992804 24277 1 6 CACCTG TGAGCGGCAT - +4 transfac_pro__M05011 1 0.992804 24277 1 6 CACCTG TGAGCGGCAT - +4 transfac_pro__M05020 1 0.992804 24277 1 6 CACCTG TGAGCGGCAT - +4 transfac_pro__M05034 1 0.992804 24277 1 6 CACCTG TGAGCGGCAT - +4 transfac_pro__M06688 5 0.992804 24277 1 5 CACCTG GACAAAACGA + +4 predrem__nrMotif640 5 0.992804 24277 1 5 CACCTG TATTTTATTT - +4 predrem__nrMotif555 -2 0.992804 24277 1 4 CACCTG ATTTCAGAAT + +4 taipale_cyt_meth__HOXD9_GYAATAAAAN_eDBD-Abd-B-cad-eve 7 0.992804 24277 1 3 CACCTG TTTTTATTGC - +4 transfac_pro__M05997-CTCF 0 0.992837 24277.8 1 6 CACCTG CCCCTCCCAACGGCTTCT - +4 dbcorrdb__CTCF__ENCSR000BHW_1__m2-Brf-brm-btd-CG42741-CoRest-CrebB-ct-CTCF-dar1-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Klf15-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-Taf1-TfAP-2-tna-vtd-zfh 6 0.992872 24278.7 1 6 CACCTG CCCCCCCCCCGCCCCCCCCC - +4 taipale_cyt_meth__ONECUT2_NTATTGATCCGT_FL_meth_repr-onecut 5 0.993191 24286.5 1 6 CACCTG TTATTGATCCGT + +4 tiffin__TIFDMEM0000068 5 0.993191 24286.5 1 6 CACCTG ATATATATATAT + +4 cisbp__M5360-E2f1-E2f2 5 0.993191 24286.5 1 6 CACCTG TTTGGCGCCATT - +4 taipale_cyt_meth__POU2F2_NYATGCGCATAN_eDBD_meth-nub-pdm2-vvl 5 0.993191 24286.5 1 6 CACCTG ATATGCGCATAT - +4 cisbp__M4924-Dref 7 0.993191 24286.5 1 5 CACCTG TTATCGATAAAA - +4 stark__WHWWWWWWWWKK-bab1-CG7839-CTCF-Dif-maf-S -2 0.993191 24286.5 1 4 CACCTG AAAAAAAAAATA - +4 tfdimers__MD00200-C15 24 0.993212 24287 1 6 CACCTG TATAATAATTAATTAATAATTAATTAATTCATTTA + +4 cisbp__M5824-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 0 0.993282 24288.7 1 6 CACCTG GAACAATACCATTGTTC + +4 cisbp__M6094-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 7 0.993282 24288.7 1 6 CACCTG AATCAATAACATTGATC + +4 taipale_cyt_meth__HSFY2_NTTCGAANNNTTCGAAN_eDBD 5 0.993282 24288.7 1 6 CACCTG GTTCGAACGGTTCGAAC + +4 transfac_pro__M01455-al-Awh-C15-CG11085-CG18599-CG34367-CG9876-E5-ems-en-eve-inv-Lim3-OdsH-pdm3-repo-Rx-slou-unc-4-unpg-zfh2 5 0.993282 24288.7 1 6 CACCTG TGCACTAATTAGTGGAT + +4 transfac_pro__M06196 9 0.993282 24288.7 1 6 CACCTG GAATTTGGTTAACGTTC + +4 hocomoco__NRF1_MOUSE.H11MO.0.A-E2f1-ewg 4 0.993282 24288.7 1 6 CACCTG CCTGCGCATGCGCAGTG - +4 taipale__Sox3_DBD_NATCAATKNYATTGATN-D-Sox100B-Sox15-Sox21a-Sox21b-SoxN 7 0.993282 24288.7 1 6 CACCTG AATCAATAACATTGATC - +4 taipale_cyt_meth__HSFY1_NTTCGAANNNTTCGAAN_eDBD 5 0.993282 24288.7 1 6 CACCTG GTTCGAACCGTTCGAAC - +4 transfac_pro__M02808-Sox100B-Sox102F 12 0.993282 24288.7 1 5 CACCTG TAAAGAACAATAAATAC - +4 tfdimers__MD00347 20 0.993295 24289 1 6 CACCTG AAAAAAAACATTAAAAATGAAACTAAAAA + +4 cisbp__M4300 1 0.993377 24291.1 1 6 CACCTG CCCCACGCGCGCGCGGTCGAC + +4 jaspar__MA0554.1-CG7839-HDAC1-RpII215-SREBP-brm-maf-S-orb-rn-sqz-vtd 4 0.993377 24291.1 1 6 CACCTG TTTTTTTTTTTTTTTTTTTTT + +4 taipale_tf_pairs__POU2F1_DLX2_TGMATATKCANNNNNTAATKR_CAP_repr-nub-pdm2 15 0.993377 24291.1 1 6 CACCTG TGAATATTCATCCACTAATTG + +4 transfac_pro__M01520 1 0.993377 24291.1 1 6 CACCTG CCCCCCGCGCGCGCGGTCGAC + +4 transfac_pro__M09020-E2f2 2 0.993377 24291.1 1 6 CACCTG TTTACGTTTTTGGCGGGAAAA + +4 cisbp__M2347-CG7839-HDAC1-RpII215-SREBP-brm-maf-S-orb-rn-sqz-vtd 4 0.993377 24291.1 1 6 CACCTG TTTTTTTTTTTTTTTTTTTTT - +4 transfac_pro__M05268-Brf-brm-CTCF-ERR-E(z)-vtd 16 0.993377 24291.1 1 5 CACCTG TGGGGGGCCCCCCCGCTCCCC + +4 cisbp__M4855-CG34031 2 0.993488 24293.8 1 6 CACCTG TTTAATTG + +4 cisbp__M5137-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG9876-Drgx-E5-ems-en-hbn-lab-Lim1-Lim3-OdsH-otp-pb-Pph13-repo-ro-Rx-slou-Traf4-unc-4-unpg-Vsx1-zen2 2 0.993488 24293.8 1 6 CACCTG TTTAATTA + +4 flyfactorsurvey__CG34031_Cell_FBgn0054031-CG34031 2 0.993488 24293.8 1 6 CACCTG TTTAATTG + +4 flyfactorsurvey__Otp_Cell_FBgn0015524-Antp-Awh-CG9876-CG11294-CG18599-CG32532-CG34367-Drgx-E5-Lim1-Lim3-OdsH-Pph13-Rx-Traf4-Vsx1-al-ap-ems-en-hbn-lab-otp-pb-repo-ro-slou-unc-4-unpg-zen2 2 0.993488 24293.8 1 6 CACCTG TTTAATTA + +4 jaspar__MA0401.1 -1 0.993488 24293.8 1 5 CACCTG ACGCGAAA + +4 yetfasco__YER111C_584 -1 0.993488 24293.8 1 5 CACCTG ACGCGAAA + +4 cisbp__M4790-Abd-B-cad-CG4328 -2 0.993488 24293.8 1 4 CACCTG TTTTATTA + +4 flyfactorsurvey__Cad_Cell_FBgn0000251-Abd-B-CG4328-cad -2 0.993488 24293.8 1 4 CACCTG TTTTATTA + +4 cisbp__M4863-CG4328 -2 0.993488 24293.8 1 4 CACCTG ATTTATTA - +4 cisbp__M1816 -3 0.993488 24293.8 1 3 CACCTG CTCGGAAA - +4 cisbp__M1106-Dbx-HGTX 6 0.993488 24293.8 1 2 CACCTG ATTAATTA + +4 cisbp__M4736-abd-A-Antp-bsh-btn-C15-CG18599-ems-ftz-pb-Scr-zen2 6 0.993488 24293.8 1 2 CACCTG TTTAATGA + +4 predrem__nrMotif1448 6 0.993488 24293.8 1 2 CACCTG AATGGCCA + +4 transfac_pro__M02804-Sox102F-Sox15 10 0.993579 24296 1 6 CACCTG AATGAACAATGGAATT + +4 taipale_cyt_meth__POU1F1_NTAATTTATGCRN_eDBD-dve-vvl 1 0.993586 24296.2 1 6 CACCTG ATGCATAAATTAA - +4 taipale_cyt_meth__SOX7_ACAATNNNATTGT_eDBD-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.993586 24296.2 1 6 CACCTG ACAATGTCATTGT - +4 hdpi__YEATS4-Gas41 -1 0.993595 24296.4 1 5 CACCTG GCCAAA + +4 jaspar__MA0356.1 1 0.993595 24296.4 1 5 CACCTG ATAATA + +4 cisbp__M4224 1 0.993595 24296.4 1 5 CACCTG ATAATA - +4 hdpi__LHX4-Dfd-Lim3 -1 0.993595 24296.4 1 5 CACCTG TCATTA - +4 transfac_pro__M01654 1 0.993595 24296.4 1 5 CACCTG TTAATT - +4 transfac_pro__M01897 1 0.993595 24296.4 1 5 CACCTG ATAATA - +4 hdpi__MYEF2-rump -3 0.993595 24296.4 1 3 CACCTG ATTTGC - +4 hdpi__EVX1-eve -4 0.993595 24296.4 1 2 CACCTG TGGAAA + +4 hdpi__DDX4 -3 0.993708 24299.2 1 3 CACCTG ATTTC - +4 cisbp__M3133-E2f1 9 0.993738 24299.9 1 6 CACCTG TACGCGCGAAAACTG + +4 cisbp__M5188-sens-sens-2 8 0.993738 24299.9 1 6 CACCTG AAATAAATCACAGCA - +4 flyfactorsurvey__sens_SOLEXA_5_FBgn0002573-sens-sens-2 8 0.993738 24299.9 1 6 CACCTG AAATAAATCACAGCA - +4 transfac_pro__M09189-SoxN 10 0.993738 24299.9 1 5 CACCTG TTTAAATTTTAAAAT - +4 taipale_cyt_meth__NFATC3_NTTTCCRYGGAAAN_eDBD-NFAT 3 0.993752 24300.2 1 6 CACCTG TTTTCCATGGAAAA + +4 taipale_cyt_meth__ZNF597_NGCCGCCATYTTGN_FL-pho-phol-RpII215 6 0.993752 24300.2 1 6 CACCTG GGCCGCCATTTTGT + +4 taipale__MEOX2_DBD_NTMATCATCATTAN_repr-btn 11 0.993752 24300.2 1 3 CACCTG TTAATGATGATTAG - +4 predrem__nrMotif35 0 0.993758 24300.4 1 6 CACCTG AAATTCTGCTT + +4 transfac_pro__M09224 4 0.993758 24300.4 1 6 CACCTG TCAATAATTGA + +4 predrem__nrMotif375 0 0.993758 24300.4 1 6 CACCTG TTATTTTTAAT - +4 cisbp__M6014-FoxK-slp2 6 0.993758 24300.4 1 5 CACCTG ATTGTGTCCGT - +4 taipale__Foxj3_DBD_ACGGACACAAT-FoxK-slp2 6 0.993758 24300.4 1 5 CACCTG ATTGTGTCCGT - +4 cisbp__M2017-al-Antp-ap-CG11294-CG18599-CG32532-CG4328-Dfd-E5-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-unc-4-unpg-Vsx1 0 0.993873 24303.2 1 6 CACCTG TAATTAA + +4 flyfactorsurvey__Al_Cell_FBgn0000061-Antp-CG4328-CG11294-CG18599-CG32532-Dfd-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Vsx1-al-ap-lab-otp-repo-ro-unc-4-unpg 0 0.993873 24303.2 1 6 CACCTG TAATTAA + +4 predrem__nrMotif1678 0 0.993873 24303.2 1 6 CACCTG TATTTAT + +4 elemento__ATATTTA -1 0.993873 24303.2 1 5 CACCTG ATATTTA + +4 elemento__ATTTTAA -1 0.993873 24303.2 1 5 CACCTG ATTTTAA + +4 elemento__ATTTTTA -1 0.993873 24303.2 1 5 CACCTG ATTTTTA + +4 elemento__AAAATAT -1 0.993873 24303.2 1 5 CACCTG ATATTTT - +4 predrem__nrMotif1450 2 0.993873 24303.2 1 5 CACCTG GAGACTC - +4 predrem__nrMotif126 -2 0.993873 24303.2 1 4 CACCTG TTTTTGA + +4 elemento__ATGGCCA 5 0.993873 24303.2 1 2 CACCTG ATGGCCA + +4 elemento__TAATGCA 5 0.993873 24303.2 1 2 CACCTG TAATGCA + +4 elemento__TCGCCCA 5 0.993873 24303.2 1 2 CACCTG TCGCCCA + +4 elemento__TCGCGCA 5 0.993873 24303.2 1 2 CACCTG TCGCGCA + +4 elemento__TCGTCCA 5 0.993873 24303.2 1 2 CACCTG TCGTCCA + +4 elemento__TGACGCA 5 0.993873 24303.2 1 2 CACCTG TGACGCA + +4 elemento__TGACTCA-cnc-Jra-kay-maf-S-Mef2-mor-Myc-nej-pan-Stat92E 5 0.993873 24303.2 1 2 CACCTG TGACTCA + +4 elemento__TGGCCCA 5 0.993873 24303.2 1 2 CACCTG TGGCCCA + +4 elemento__TTGCGCA 5 0.993873 24303.2 1 2 CACCTG TTGCGCA + +4 elemento__TTTGTCA 5 0.993873 24303.2 1 2 CACCTG TTTGTCA + +4 flyfactorsurvey__Lim1_Cell_FBgn0026411-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-Dfd-Drgx-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Vsx1-ap-ems-en-lab-otp-repo-ro-slou-unc-4-unpg-zen2 5 0.993873 24303.2 1 2 CACCTG TTAATTA + +4 stark__TGANTCA-Jra-kay 5 0.993873 24303.2 1 2 CACCTG TGAATCA + +4 elemento__TGCGCGC 5 0.993873 24303.2 1 2 CACCTG GCGCGCA - +4 elemento__TGGGCGC 5 0.993873 24303.2 1 2 CACCTG GCGCCCA - +4 stark__TGGATTA-bcd 5 0.993873 24303.2 1 2 CACCTG TAATCCA - +4 predrem__nrMotif1121 1 0.993938 24304.8 1 6 CACCTG TCATCATTT + +4 yetfasco__YDR266C_1161-CG11414 3 0.993938 24304.8 1 6 CACCTG ACGATCCAA - +4 elemento__AATTATGCA-acj6-vvl 4 0.993938 24304.8 1 5 CACCTG TGCATAATT - +4 cisbp__M6247-bin-fd102C-fd19B-FoxK-FoxL1-foxo-slp1-slp2 5 0.993938 24304.8 1 4 CACCTG TTGTTTATT - +4 cisbp__M5313-Abd-B-cad-eve 6 0.993938 24304.8 1 3 CACCTG TTTTATTGC + +4 cisbp__M4780-Antp-bsh-CG34367-HGTX-Scr-tup-Ubx -3 0.993938 24304.8 1 3 CACCTG CCAATTAAA - +4 flyfactorsurvey__Bsh_Cell_FBgn0000529-Antp-CG34367-HGTX-Scr-Ubx-Vsx2-bsh-tup -3 0.993938 24304.8 1 3 CACCTG CCAATTAAA - +4 taipale__CDX2_DBD_NYMATAAAN-Abd-B-cad-eve 6 0.993938 24304.8 1 3 CACCTG TTTTATTGC - +4 cisbp__M0851 3 0.994009 24306.5 1 6 CACCTG CCAATCATTA + +4 jaspar__MA1024.1 3 0.994009 24306.5 1 6 CACCTG CCAATCATTA + +4 transfac_pro__M07584 3 0.994009 24306.5 1 6 CACCTG AAATATATTA + +4 hocomoco__BARX2_HUMAN.H11MO.0.D-Ubx-bsh 4 0.994009 24306.5 1 6 CACCTG CAATTAATGA - +4 transfac_pro__M05980-CTCF 1 0.994009 24306.5 1 6 CACCTG GATCCGTATT - +4 transfac_pro__M06949-al-CG11294-CG32532-CG34367-Drgx-eve-hbn-OdsH-repo-Traf4-unc-4 4 0.994009 24306.5 1 6 CACCTG AATTTAATTA - +4 cisbp__M1789 -1 0.994009 24306.5 1 5 CACCTG CCCGCGCGCC + +4 transfac_pro__M04994 -3 0.994009 24306.5 1 3 CACCTG ATGCCGCTCA + +4 transfac_pro__M05009 -3 0.994009 24306.5 1 3 CACCTG ATGCCGCTCA + +4 taipale__E2F3_DBD_NNTTTTGGCGCCAAAANN-E2f1-E2f2 13 0.99407 24308 1 5 CACCTG AATTTTGGCGCCAAAACT + +4 dbcorrdb__ZZZ3__ENCSR000DNQ_1__m1-Atac1 2 0.99411 24309 1 6 CACCTG ACTCTCTCTCTCTCTCTCTC - +4 bergman__bab1-bab1 6 0.994358 24315 1 6 CACCTG TAAATATAATTG + +4 swissregulon__sacCer__SFP1-CG12054 2 0.994358 24315 1 6 CACCTG AAAAAATTTTCT + +4 taipale__E2F8_DBD_TTTCCCGCCAAA_repr-E2f1-E2f2 1 0.994358 24315 1 6 CACCTG TTTCCCGCCAAA + +4 transfac_pro__M05130 2 0.994358 24315 1 6 CACCTG ATTAACGGCGTT + +4 transfac_pro__M05503 1 0.994358 24315 1 6 CACCTG CCATCGATCCGA + +4 tiffin__TIFDMEM0000098-BEAF-32 3 0.994358 24315 1 6 CACCTG AAATATCGATAG - +4 transfac_pro__M05333-klu-sr 7 0.994358 24315 1 5 CACCTG CCGCCCACGCCC - +4 tfdimers__MD00467 6 0.994446 24317.2 1 6 CACCTG AAAAAAAATCAAACAAAAAAAAAAA + +4 cisbp__M5841-Sox100B-Sox15 3 0.994448 24317.2 1 6 CACCTG CATCAATTGCAGTGATC + +4 taipale__SOX8_DBD_NATCAATKNYAGTGATN-Sox100B-Sox15 3 0.994448 24317.2 1 6 CACCTG CATCAATTGCAGTGATC + +4 taipale_cyt_meth__SOX10_AACAATNNNNNATTGTT_eDBD_repr-Sox100B 8 0.994448 24317.2 1 6 CACCTG AACAATGGGCCATTGTT + +4 cisbp__M5851-D-Sox100B-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.994448 24317.2 1 6 CACCTG AATCACTGAAATTGATT - +4 taipale__SOX9_full_NATCAATKNYAGTGATN-D-Sox100B-Sox14-Sox15-Sox21a-Sox21b-SoxN 3 0.994448 24317.2 1 6 CACCTG AATCACTGAAATTGATT - +4 transfac_pro__M01418-Antp-C15-CG32532-CG4328-Dfd-Lim1-Lim3-Lmx1a-otp-Scr-vvl 12 0.994448 24317.2 1 5 CACCTG CGAATTAATTAATAATG + +4 transfac_pro__M05205-brm-ERR-E(z) 13 0.994547 24319.7 1 6 CACCTG CGGGGGCGGCGGGGACCCCCC - +4 transfac_pro__M05242 17 0.994547 24319.7 1 4 CACCTG TGGGGGGCCCGCTCGTTCGCC + +4 transfac_pro__M05249-Brf-brm-ERR-E(z) 17 0.994547 24319.7 1 4 CACCTG GGGGGGGCCCGCTCGCCCCCC + +4 transfac_pro__M05260-Brf-brm-btd-CTCF-ERR-E(z)-Spps-SREBP-vtd 17 0.994547 24319.7 1 4 CACCTG GGGGGGCGCCGGGGCCCCCCC - +4 fantom__motif109_TCNMTMGC 0 0.994601 24321 1 6 CACCTG TCACTCGC + +4 swissregulon__sacCer__RDS1 2 0.994601 24321 1 6 CACCTG TCGGCCGA + +4 transfac_pro__M01899 2 0.994601 24321 1 6 CACCTG CGCGCGCG + +4 jaspar__MA0375.1 2 0.994601 24321 1 6 CACCTG CGCGCGCG - +4 transfac_pro__M00752-NFAT -1 0.994601 24321 1 5 CACCTG TCCGCGGA + +4 cisbp__M4907-Dfd -2 0.994601 24321 1 4 CACCTG CTTAATGA + +4 flyfactorsurvey__CG4328_Cell_FBgn0036274-CG4328 -2 0.994601 24321 1 4 CACCTG ATTTATTA + +4 flyfactorsurvey__Dfd_Cell_FBgn0000439-Dfd -2 0.994601 24321 1 4 CACCTG CTTAATGA + +4 cisbp__M1462 4 0.994601 24321 1 4 CACCTG TCGAGAAT - +4 hdpi__MBTPS2-S2P -2 0.994601 24321 1 4 CACCTG TCTTTGAA - +4 predrem__nrMotif1950 6 0.994601 24321 1 2 CACCTG AATATTCA + +4 bergman__Aef1-Aef1 1 0.994655 24322.3 1 5 CACCTG CAACAA + +4 stark__RRAYATTYBKSGVATKVCA-sd 1 0.994684 24323 1 6 CACCTG AAACATTCTGCGGATGGCA + +4 taipale_cyt_meth__SOX7_ACAATNNNATTGT_eDBD_meth_repr-bbx-D-peng-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 5 0.994703 24323.5 1 6 CACCTG ACAATGTCATTGT + +4 predrem__nrMotif233-CG7839-FoxP-RpII215-SREBP-brm-ct-dati-jim-maf-S-orb-rn-sqz-vtd 1 0.994703 24323.5 1 6 CACCTG TTTTTTTTTTTTT - +4 taipale_cyt_meth__POU4F1_NTNNATWATGCAN_eDBD_meth-acj6-vvl 5 0.994703 24323.5 1 6 CACCTG ATGCATAATTAAT - +4 cisbp__M5839-Sox100B-Sox15 -1 0.994703 24323.5 1 5 CACCTG GACTGCAATTCAT - +4 taipale__SOX8_DBD_ATGAATKNYAGTC-Sox100B-Sox15 -1 0.994703 24323.5 1 5 CACCTG GACTGCAATTCAT - +4 cisbp__M5001-hb 9 0.994703 24323.5 1 4 CACCTG TCGTTTTTTTATG + +4 flyfactorsurvey__hb_SANGER_2.5_FBgn0001180-hb 9 0.994703 24323.5 1 4 CACCTG TCGTTTTTTTATG + +4 transfac_pro__M02803-D-Sox21a-Sox21b 1 0.994703 24323.5 1 6 CACCTG TTTAATTATAATTAAG + +4 transfac_pro__M02801-Sox14-Sox15 8 0.994703 24323.5 1 6 CACCTG TTTTAGAACAATTGAA - +4 flyfactorsurvey__pho_SOLEXA_F1-3-pho 0 0.994833 24326.6 1 6 CACCTG GGCCGCCATTA + +4 cisbp__M1745 7 0.994833 24326.6 1 4 CACCTG TCCGCGGAATG - +4 predrem__nrMotif2584 7 0.994833 24326.6 1 4 CACCTG CCCGCGGCTCC - +4 hocomoco__ZFHX3_HUMAN.H11MO.0.D 8 0.994833 24326.6 1 3 CACCTG TAATTATTAAT - +4 transfac_pro__M09170 9 0.994843 24326.9 1 6 CACCTG TTTTTGTCTTTTTTT - +4 transfac_pro__M09188 5 0.994843 24326.9 1 6 CACCTG ATTTGAATTTTAAAT - +4 transfac_pro__M01192 4 0.994853 24327.1 1 6 CACCTG GCATTAAATGCGCA + +4 taipale_cyt_meth__NFATC3_NTTTCCRYGGAAAN_eDBD_meth-NFAT 2 0.994853 24327.1 1 6 CACCTG TTTTCCGCGGAAAA - +4 transfac_pro__M06952 9 0.994853 24327.1 1 5 CACCTG ATTTCTAATAATCC - +4 transfac_public__M00463-vvl 9 0.994853 24327.1 1 5 CACCTG ATGAATAAATGCAT - +4 cisbp__M1981-al-Antp-ap-Awh-CG11294-CG18599-CG32532-CG34367-CG4328-CG9876-Dfd-Drgx-E5-ems-en-hbn-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-Traf4-unc-4-unpg-Vsx1-vvl-zen2-zfh2 1 0.994943 24329.3 1 6 CACCTG TTAATTA + +4 flyfactorsurvey__CG11294_Cell_FBgn0030058-Antp-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Dfd-Drgx-E5-Lim1-Lim3-Lmx1a-OdsH-Pph13-Rx-Scr-Traf4-Vsx1-al-ap-ems-en-hbn-lab-otp-repo-ro-unc-4-unpg-vv 1 0.994943 24329.3 1 6 CACCTG TTAATTA + +4 elemento__ATGATGA 1 0.994943 24329.3 1 6 CACCTG TCATCAT - +4 bergman__tll-tll -1 0.994943 24329.3 1 5 CACCTG AAATTAA + +4 elemento__AATTTTA -1 0.994943 24329.3 1 5 CACCTG AATTTTA + +4 stark__AAATTAA-tll -1 0.994943 24329.3 1 5 CACCTG AAATTAA + +4 fantom__motif83_TTWTAAA 4 0.994943 24329.3 1 3 CACCTG TTTATAA - +4 cisbp__M2003-Antp-ap-Awh-CG11294-CG18599-CG32532-CG4328-CG9876-Dfd-Drgx-E5-ems-en-lab-Lim1-Lim3-Lmx1a-OdsH-otp-Pph13-repo-ro-Rx-Scr-slou-Traf4-unc-4-unpg-Vsx1-zen2 5 0.994943 24329.3 1 2 CACCTG TTAATTA + +4 predrem__nrMotif45 1 0.994975 24330.1 1 6 CACCTG TCATTTTCT - +4 predrem__nrMotif1289 -1 0.994975 24330.1 1 5 CACCTG AAATTATTT + +4 cisbp__M5312-Abd-B-cad-eve 6 0.994975 24330.1 1 3 CACCTG TTTTATTGC + +4 taipale__CDX1_DBD_NYMATAAAN-Abd-B-cad-eve 6 0.994975 24330.1 1 3 CACCTG TTTTATTGC - +4 cisbp__M2459-Sox15-Sox102F 1 0.99504 24331.7 1 6 CACCTG AAACAATGGA + +4 transfac_pro__M05070 1 0.99504 24331.7 1 6 CACCTG ATGCCGCCGA + +4 cisbp__M6157-bsh-Ubx 4 0.99504 24331.7 1 6 CACCTG CAATTAATAA - +4 flyfactorsurvey__bab1_FlyReg_FBgn0004870-bab1 2 0.99504 24331.7 1 6 CACCTG AACAATAATA - +4 cisbp__M0906-al-ap-Awh-CG11294-CG18599-CG34367-E5-ems-ey-ind-Lim1-Lim3-OdsH-otp-repo-ro-Rx-toy-unc-4-vvl-zfh2 -1 0.99504 24331.7 1 5 CACCTG AATTAATTAG + +4 swissregulon__sacCer__RSC3 -1 0.99504 24331.7 1 5 CACCTG AGCGCGCGCT + +4 cisbp__M0382 6 0.99504 24331.7 1 4 CACCTG AATTTAAAAA + +4 taipale__HOXA13_full_CCAATAAAAN -2 0.99504 24331.7 1 4 CACCTG CCAATAAAAA + +4 transfac_pro__M08975-Sox102F-Sox15 -2 0.99504 24331.7 1 4 CACCTG TCTATTGTTT - +4 predrem__nrMotif492 -3 0.99504 24331.7 1 3 CACCTG CTTTATTATT + +4 transfac_pro__M05104 7 0.99504 24331.7 1 3 CACCTG TGGGCGGCAT - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m12-brm-CG7839-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 0 0.995164 24334.7 1 6 CACCTG TTTTTTTTTTTTTTTTTGTG + +4 dbcorrdb__ZMIZ1__ENCSR000EFQ_1__m2-bon-Brf-brm-btd-CrebB-CTCF-E2f1-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-Max-Myc-Nelf-E-Not3-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna-vtd 4 0.995164 24334.7 1 6 CACCTG GCCCCGCCGGCCGCGGCCGG + +4 transfac_pro__M09192-E2f2 1 0.995164 24334.7 1 6 CACCTG TTATTTTTTTGGCGGGAAAA + +4 cisbp__M5363-E2f1-E2f2 1 0.99535 24339.3 1 6 CACCTG TTTCCCGCCAAA + +4 scertf__zhu.SFP1-CG12054 3 0.99535 24339.3 1 6 CACCTG AAAAAATTTTCT + +4 cisbp__M5688-E2f1-ewg 2 0.99535 24339.3 1 6 CACCTG TGCGCATGCGCA - +4 taipale__NRF1_full_YGCGCATGCGCN_repr-E2f1-ewg 2 0.99535 24339.3 1 6 CACCTG TGCGCATGCGCA - +4 transfac_pro__M06148 7 0.99535 24339.3 1 5 CACCTG TCTCTCTTAATG - +4 transfac_pro__M06624 7 0.99535 24339.3 1 5 CACCTG TCGGATCGATCG - +4 cisbp__M4288 -2 0.99535 24339.3 1 4 CACCTG TCTTTTTTGCTG - +4 transfac_pro__M05784 9 0.99535 24339.3 1 3 CACCTG TCGGAAGCCCAG - +4 taipale__VENTX_DBD_SSYTAATCGRWAANCGATTAR_repr -1 0.995538 24343.9 1 5 CACCTG CGCTAATCGGAAAACGATTAG + +4 cisbp__M5948 -1 0.995538 24343.9 1 5 CACCTG CGCTAATCGGAAAACGATTAG - +4 cisbp__M1280 0 0.995558 24344.4 1 6 CACCTG TTCCGCGT + +4 cisbp__M1583-bbx 0 0.995558 24344.4 1 6 CACCTG TTCATTGA + +4 cisbp__M1710 1 0.995558 24344.4 1 6 CACCTG ATCCCGAA + +4 jaspar__MA1028.1 1 0.995558 24344.4 1 6 CACCTG GAATATTC + +4 predrem__nrMotif1244 3 0.995558 24344.4 1 5 CACCTG TTGCAATT + +4 cisbp__M5322-orb 4 0.995558 24344.4 1 4 CACCTG TTTTTATT + +4 taipale__CPEB1_full_RATAAAAR-orb 4 0.995558 24344.4 1 4 CACCTG TTTTTATT - +4 cisbp__M0588 5 0.995558 24344.4 1 3 CACCTG ATTTAAAC - +4 transfac_pro__M03564 -3 0.995566 24344.6 1 3 CACCTG TTTTAT + +4 transfac_pro__M09141 -2 0.995596 24345.3 1 4 CACCTG CATCATCATCATCATCATCATCATCAT + +4 transfac_pro__M05076 3 0.99565 24346.6 1 6 CACCTG GATTAACGGATTC + +4 taipale_tf_pairs__POU2F1_SOX15_WTGMATAACAATR_CAP_1-nub-pdm2 8 0.99565 24346.6 1 5 CACCTG TATTGTTATTCAA - +4 transfac_pro__M02797-Sox102F-Sox14 9 0.995661 24346.9 1 6 CACCTG AATTTATTGTTCTTAA - +4 taipale_cyt_meth__ONECUT2_NTATCGATTTN_FL-onecut 5 0.995746 24349 1 6 CACCTG TTATCGATTGT + +4 transfac_pro__M00919-Dp-E2f1-E2f2 -1 0.995746 24349 1 5 CACCTG GTTTGGCGCGA - +4 jaspar__MA0601.1 8 0.995746 24349 1 3 CACCTG ATATTAATTAA + +4 cisbp__M5049-jim 9 0.995746 24349 1 2 CACCTG AAAAAAAACCA + +4 flyfactorsurvey__jim_SANGER_2.5_FBgn0027339-jim 9 0.995746 24349 1 2 CACCTG AAAAAAAACCA + +4 flyfactorsurvey__pho_SOLEXA_5_FBgn0002521-pho-phol 0 0.99578 24349.8 1 6 CACCTG ACCAAAATGGCGGCC + +4 hocomoco__HMGA2_HUMAN.H11MO.0.D 3 0.99578 24349.8 1 6 CACCTG AATAATCGCGAATAT + +4 cisbp__M3772-vvl 9 0.995784 24349.9 1 5 CACCTG ATGAATAAATGCAT - +4 transfac_pro__M01679 1 0.995842 24351.3 1 6 CACCTG ACACAAT + +4 elemento__ATGCTGC 1 0.995842 24351.3 1 6 CACCTG GCAGCAT - +4 cisbp__M1995-Antp-Dfd-ems-Scr-zen2 -1 0.995842 24351.3 1 5 CACCTG TCATTAA - +4 jaspar__MA0186.1-Antp-Dfd-Scr-ems-zen2 -1 0.995842 24351.3 1 5 CACCTG TCATTAA - +4 cisbp__M1991-CG4328-H2.0 4 0.995842 24351.3 1 3 CACCTG CAATAAA + +4 jaspar__MA0182.1-CG4328-H2.0 4 0.995842 24351.3 1 3 CACCTG CAATAAA - +4 elemento__AAAAATA 5 0.995842 24351.3 1 2 CACCTG AAAAATA + +4 elemento__ATAAATA 5 0.995842 24351.3 1 2 CACCTG ATAAATA + +4 elemento__ATAATTA 5 0.995842 24351.3 1 2 CACCTG ATAATTA + +4 jaspar__MA0203.1-Antp-CG18599-Dfd-E5-Scr-bsh-btn-ems-eve-pb-pdm3-zen-zen2 5 0.995842 24351.3 1 2 CACCTG TTAATGA + +4 elemento__TAATTAA-CG11294 5 0.995842 24351.3 1 2 CACCTG TTAATTA - +4 predrem__nrMotif1630 1 0.995858 24351.7 1 6 CACCTG ACACAAAAA + +4 transfac_pro__M04866-HDAC1 0 0.995858 24351.7 1 6 CACCTG CGCGCGCGC + +4 predrem__nrMotif415 4 0.995858 24351.7 1 5 CACCTG CAAAGCCCA + +4 predrem__nrMotif1796 5 0.995858 24351.7 1 4 CACCTG TTCAATAAA + +4 predrem__nrMotif240 6 0.995858 24351.7 1 3 CACCTG TTTTGGCAA - +4 stark__WAATCARCGC 1 0.995917 24353.2 1 6 CACCTG AAATCAACGC + +4 homer__NTATYGATCH_HNF6-onecut 5 0.995917 24353.2 1 5 CACCTG GTATCGATCC + +4 cisbp__M5536 -2 0.995917 24353.2 1 4 CACCTG CCAATAAAAA + +4 transfac_pro__M03167 -3 0.995917 24353.2 1 3 CACCTG ATGCCGCTCA + +4 transfac_pro__M00940-Dp-E2f1-E2f2-eve 7 0.995917 24353.2 1 3 CACCTG GGCGCGAAAC - +4 cisbp__M5358-E2f1 8 0.996013 24355.5 1 6 CACCTG AAAAATGGCGCCATTTTT - +4 taipale__E2F3_DBD_NNAAATGGCGCCATTTNN-E2f1 8 0.996013 24355.5 1 6 CACCTG AAAAATGGCGCCATTTTT - +4 cisbp__M5359-E2f1-E2f2 13 0.996013 24355.5 1 5 CACCTG AATTTTGGCGCCAAAACT + +4 transfac_pro__M06573 14 0.996013 24355.5 1 4 CACCTG GCTTTTTAGTCCGCATCC - +4 transfac_pro__M09168-brm 14 0.996055 24356.5 1 6 CACCTG TTTTTTTTTGTCGTTTTCTG - +4 transfac_pro__M05515-row 1 0.996189 24359.8 1 6 CACCTG TAATCCAATAGA + +4 transfac_pro__M06026 1 0.996189 24359.8 1 6 CACCTG CTTTCTGGGGAT + +4 transfac_pro__M06464 7 0.996189 24359.8 1 5 CACCTG GCCGCCATGCCC - +4 transfac_pro__M05799 8 0.996189 24359.8 1 4 CACCTG TCGTATTAAAAA - +4 taipale_cyt_meth__ONECUT1_NTATCGATCGNN_FL-onecut 9 0.996189 24359.8 1 3 CACCTG CCCGATCGATAC - +4 taipale_cyt_meth__ONECUT1_NTATTGATCSGN_FL_meth-onecut 9 0.996189 24359.8 1 3 CACCTG ACGGATCAATAA - +4 transfac_pro__M07877-ey-eyg-gsb-gsb-n-prd-toe 9 0.996189 24359.8 1 3 CACCTG ATAATTGATTAT - +4 hocomoco__CPEB1_HUMAN.H11MO.0.D-CG7839-RpII215-SREBP-brm-maf-S-orb-rn-sqz-vtd 7 0.996285 24362.2 1 6 CACCTG TTTTTATTTTTTTTTTT + +4 taipale_cyt_meth__HSFY2_NTTCGAANNNTTCGAAN_eDBD_meth 5 0.996285 24362.2 1 6 CACCTG ATTCGAATGATTCGAAT - +4 hdpi__ZMAT4 2 0.996344 24363.6 1 4 CACCTG ATTTCA - +4 elemento__TTTATGGC -1 0.99637 24364.2 1 5 CACCTG GCCATAAA - +4 predrem__nrMotif1813 -3 0.99637 24364.2 1 3 CACCTG CGCAGCGC + +4 cisbp__M3974-aop-Stat92E 16 0.996373 24364.3 1 5 CACCTG AATCATTTCCCGGAAATGCCA - +4 transfac_public__M00225-aop-Stat92E 16 0.996373 24364.3 1 5 CACCTG AATCATTTCCCGGAAATGCCA - +4 taipale_cyt_meth__POU3F2_NTAATTWATGCGN_eDBD_meth-vvl 1 0.996448 24366.1 1 6 CACCTG ACGCATAAATTAA - +4 transfac_pro__M06501-RpII215 1 0.996457 24366.4 1 6 CACCTG CCGCTTCCGTCGTGATCCG + +4 transfac_pro__M07711-CHES-1-like 5 0.996457 24366.4 1 6 CACCTG ATAGCGTCATGGACGCTAT + +4 transfac_pro__M05288 -1 0.996472 24366.7 1 5 CACCTG AATTTAAATTTAAATT + +4 cisbp__M6546 5 0.996518 24367.8 1 6 CACCTG ATTAATAATTA + +4 predrem__nrMotif2242 1 0.996518 24367.8 1 6 CACCTG CGGCCCCGCGG + +4 cisbp__M0104 -1 0.996518 24367.8 1 5 CACCTG ATATTAATTAA + +4 scertf__pachkov.SUM1 6 0.996518 24367.8 1 5 CACCTG TTTTGTGACAC - +4 swissregulon__sacCer__SUM1 6 0.996518 24367.8 1 5 CACCTG TTTTGTGACAC - +4 tiffin__TIFDMEM0000113 -1 0.996518 24367.8 1 5 CACCTG AATTAAAATAA - +4 transfac_pro__M08876-E2f2 2 0.996567 24369 1 6 CACCTG ATTGGCGGGAAAAA + +4 cisbp__M5155-pho-phol 0 0.99657 24369.1 1 6 CACCTG ACCAAAATGGCGGCC + +4 cisbp__M6280 3 0.99657 24369.1 1 6 CACCTG AATAATCGCGAATAT + +4 transfac_pro__M09202 4 0.99657 24369.1 1 6 CACCTG TTAAAATATTCTTTT + +4 hocomoco__PO4F3_HUMAN.H11MO.0.D-Dfd-acj6-vvl -3 0.99657 24369.1 1 3 CACCTG ATGAATAATTAATGA - +4 cisbp__M2132 1 0.996573 24369.2 1 6 CACCTG ACACAAT + +4 jaspar__MA0327.1 1 0.996573 24369.2 1 6 CACCTG ACACAAT + +4 transfac_pro__M02081-tup 1 0.996573 24369.2 1 6 CACCTG ATAATGG + +4 cisbp__M2012-Antp-bsh-btn-CG18599-Dfd-E5-ems-eve-pb-pdm3-Scr-zen-zen2 5 0.996573 24369.2 1 2 CACCTG TTAATGA + +4 jaspar__MA0225.1-Antp-Awh-CG18599-Dfd-E5-HGTX-Scr-Ubx-abd-A-ap-bsh-btn-ems-eve-ftz-lab-pb-zen-zen2 5 0.996573 24369.2 1 2 CACCTG TTAATTA + +4 transfac_pro__M07377-Abd-B-cad 3 0.996608 24370 1 6 CACCTG TTTTATTGC + +4 cisbp__M0594 4 0.996608 24370 1 5 CACCTG AATTCAAAT - +4 idmmpmm__Antp-Antp-C15-Dbx-HGTX-Ubx-abd-A-lab 4 0.996608 24370 1 5 CACCTG TAATTAAAA - +4 jaspar__MA0619.1 4 0.996608 24370 1 5 CACCTG AATTCAAAT - +4 predrem__nrMotif277 4 0.996657 24371.3 1 6 CACCTG ATTTTGTCTT + +4 tiffin__TIFDMEM0000061 1 0.996657 24371.3 1 6 CACCTG ATAAAAAAAA + +4 cisbp__M4757-bab1 2 0.996657 24371.3 1 6 CACCTG AACAATAATA - +4 transfac_pro__M06679 1 0.996657 24371.3 1 6 CACCTG TCGTCTTATA - +4 cisbp__M5553 -2 0.996657 24371.3 1 4 CACCTG CCAATAAAAA + +4 taipale__HOXC13_DBD_CCAATAAAAN -2 0.996657 24371.3 1 4 CACCTG CCAATAAAAA + +4 taipale_cyt_meth__SOX14_CCGAACAATN_FL_repr-D-Sox21a-Sox21b -2 0.996657 24371.3 1 4 CACCTG CATTGTTCGG - +4 hocomoco__E2F5_HUMAN.H11MO.0.B-Dp-E2f1-E2f2-Rbf2-eve 7 0.996657 24371.3 1 3 CACCTG GGCGCCAAAC + +4 transfac_pro__M07712-CHES-1-like 4 0.996765 24373.9 1 6 CACCTG TAGCGTCTTGGGACGCTA + +4 taipale__E2F3_DBD_NNAAATGGCGCCAAAANN_repr-E2f1-E2f2 8 0.996765 24373.9 1 6 CACCTG CATTTTGGCGCCATTTTT - +4 taipale_cyt_meth__NFATC1_NTTTCCRNNNNYGGAAAN_eDBD_meth-NFAT 2 0.996765 24373.9 1 6 CACCTG TTTTCCGTTAACGGAAAA - +4 dbcorrdb__CUX1__ENCSR000EFO_1__m5-CG7839-ct-CTCF 9 0.996803 24374.8 1 6 CACCTG AAAAAAAAAAATTTTTTTTT + +4 transfac_pro__M09154 14 0.996803 24374.8 1 6 CACCTG TTTTTTTTTGTCGTTTTGTG + +4 scertf__pachkov.UME6 6 0.996895 24377.1 1 6 CACCTG TTTAGCCGCCGA + +4 tiffin__TIFDMEM0000049 1 0.996895 24377.1 1 6 CACCTG ATATTTTTTAAA + +4 hocomoco__ONEC3_HUMAN.H11MO.0.D-onecut 4 0.996895 24377.1 1 6 CACCTG AAAAAATCAATA - +4 tiffin__TIFDMEM0000046 6 0.996895 24377.1 1 6 CACCTG TGAATTTCCAAA - +4 transfac_pro__M01840 0 0.996895 24377.1 1 6 CACCTG AACCCGCCAAAA - +4 transfac_pro__M06100 6 0.996895 24377.1 1 6 CACCTG GCAGAAGCCCAG - +4 transfac_pro__M06761 6 0.996895 24377.1 1 6 CACCTG GCGGAAGCCCAG - +4 transfac_pro__M05683-row 8 0.996895 24377.1 1 4 CACCTG TCTATTGGCTCT - +4 taipale_cyt_meth__PAX7_NTAATYGATTAN_FL-ey-eyg-gsb-gsb-n-prd-toe 9 0.996895 24377.1 1 3 CACCTG ATAATCGATTAT - +4 transfac_pro__M02097-Lim3 -3 0.997006 24379.8 1 3 CACCTG TTTAAT - +4 hdpi__NOC2L-CG9246 -4 0.997006 24379.8 1 2 CACCTG TGCAAA + +4 transfac_pro__M02112-onecut 4 0.997006 24379.8 1 2 CACCTG TCAATA + +4 cisbp__M0874 2 0.99706 24381.1 1 6 CACCTG CCAATCAA + +4 cisbp__M1213 0 0.99706 24381.1 1 6 CACCTG CAAATCAA + +4 cisbp__M4728-Adf1 1 0.99706 24381.1 1 6 CACCTG CGACCGCG + +4 flyfactorsurvey__Adf1_FlyReg_FBgn0000054-Adf1 1 0.99706 24381.1 1 6 CACCTG CGACCGCG + +4 elemento__AAATTGCA 6 0.99706 24381.1 1 2 CACCTG AAATTGCA + +4 elemento__ATCAATCA 6 0.99706 24381.1 1 2 CACCTG ATCAATCA + +4 jaspar__MA0326.1 -4 0.99706 24381.1 1 2 CACCTG TTTGCTCA + +4 stark__AAAATGCA 6 0.99706 24381.1 1 2 CACCTG AAAATGCA + +4 transfac_pro__M05233-ERR-E(z)-vtd 17 0.997072 24381.4 1 4 CACCTG GGGGGGGTCCGGCCGCCGCCC + +4 transfac_pro__M05246-Brf-brm-CTCF-ERR-E(z)-HDAC1-Nelf-E-SREBP-vtd 17 0.997072 24381.4 1 4 CACCTG GGGGGGGCCCGCCCGCCCCCC + +4 tfdimers__MD00075-foxo 1 0.997087 24381.8 1 6 CACCTG TTTTTTTTTTTTTTTGTTTGTTTTTTTTTT - +4 transfac_public__M00094-br-croc 1 0.997117 24382.5 1 6 CACCTG TTTTGTTTATTAA - +4 transfac_pro__M07845-ct-onecut 9 0.997117 24382.5 1 4 CACCTG AAAAATCAATAAT + +4 cisbp__M1616 1 0.997166 24383.7 1 6 CACCTG TAAACAATAAT + +4 transfac_pro__M09248 6 0.997166 24383.7 1 5 CACCTG ATTAATCATTA + +4 transfac_pro__M01114-Dp -2 0.997166 24383.7 1 4 CACCTG TTTTTCCCGCC + +4 transfac_pro__M04977 -3 0.997166 24383.7 1 3 CACCTG ATGCCGCTCGC + +4 elemento__CGGGCTC 1 0.997192 24384.3 1 6 CACCTG GAGCCCG - +4 cisbp__M2033-abd-A-Antp-ap-Awh-bsh-btn-CG18599-Dfd-E5-ems-eve-ftz-HGTX-lab-pb-Scr-Ubx-zen-zen2 5 0.997192 24384.3 1 2 CACCTG TTAATGA + +4 cisbp__M5366-klu-sr 10 0.997221 24385 1 4 CACCTG TACGCCCACGCATT - +4 yetfasco__YER109C_67 -4 0.997221 24385.1 1 2 CACCTG TTTGC + +4 transfac_pro__M09187-SoxN 5 0.997228 24385.2 1 6 CACCTG ATTTAAATTTTAAAA - +4 cisbp__M2662 3 0.997242 24385.6 1 6 CACCTG CAATAATTG + +4 predrem__nrMotif2448 2 0.997242 24385.6 1 6 CACCTG TTTAGCATT - +4 predrem__nrMotif456 0 0.997242 24385.6 1 6 CACCTG TATATTTTA - +4 transfac_public__M00503 3 0.997242 24385.6 1 6 CACCTG CAATAATTG - +4 transfac_pro__M07378-cad -2 0.997242 24385.6 1 4 CACCTG TTTTTATAA + +4 cisbp__M5459-FoxK-slp2 4 0.99728 24386.5 1 6 CACCTG CGGACACAAT + +4 taipale_cyt_meth__ONECUT3_NTATTGATYN_eDBD_meth-onecut 7 0.99728 24386.5 1 3 CACCTG AAATCAATAA - +4 cisbp__M6147 8 0.99728 24386.5 1 6 CACCTG TTTAATTTGATTTCGATTAATT + +4 taipale_cyt_meth__NFATC1_NTTTCCRNNNNYGGAAAN_eDBD_repr-NFAT 2 0.997395 24389.3 1 6 CACCTG TTTTCCATTAATGGAAAA + +4 cisbp__M5354-E2f1-E2f2 8 0.997395 24389.3 1 6 CACCTG CATTTTGGCGCCATTTTT - +4 cisbp__M5357-E2f1-E2f2 8 0.997395 24389.3 1 6 CACCTG CATTTTGGCGCCATTTTT - +4 taipale__E2F2_DBD_AAAAATGGCGCCAAAANN-E2f1-E2f2 8 0.997395 24389.3 1 6 CACCTG CATTTTGGCGCCATTTTT - +4 dbcorrdb__POLR2AphosphoS2__ENCSR000DYF_1__m10-bon-Brf-brm-btd-CoRest-CrebB-CTCF-dar1-E2f1-Eip74EF-ERR-ewg-E(z)-Hcf-HDAC1-Hr78-Jra-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tn 1 0.997427 24390.1 1 6 CACCTG CCCCCCCGCCCCGGGCCGGG + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m10-bon-Brf-brm-btd-CG42741-CoRest-CrebB-ct-CTCF-dar1-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Sin3A-Spps-Spt20-sr-SREBP-Taf1-t 13 0.997427 24390.1 1 6 CACCTG GCCGCCCCCGCCCCCCCCGC - +4 dbcorrdb__SREBF1__ENCSR000EZP_1__m1-bon-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-kay-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Sin3A-Spps-Spt20-sr-SREBP-Taf1 5 0.997427 24390.1 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 swissregulon__hs__ONECUT1_2.p2-onecut 5 0.997486 24391.5 1 6 CACCTG TTATTGATTTTT - +4 transfac_pro__M05018 7 0.997486 24391.5 1 5 CACCTG ATTAACGGACTC + +4 transfac_pro__M06794 7 0.997486 24391.5 1 5 CACCTG GCGGCTTTAATC - +4 tiffin__TIFDMEM0000110 8 0.997486 24391.5 1 4 CACCTG AGAAAATATAAA - +4 cisbp__M5836-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 0 0.997586 24394 1 6 CACCTG AAACAATGCAATTGTTT - +4 cisbp__M5852-Sox100B-Sox15-SoxN 11 0.997586 24394 1 6 CACCTG AATGACTGCAATTCATT - +4 taipale__SOX7_full_NAACAATKNYAKTGTTN-D-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 0 0.997586 24394 1 6 CACCTG AAACAATGCAATTGTTT - +4 taipale__SOX9_full_NATGAATKNYAGTCATN-Sox100B-Sox15-SoxN 11 0.997586 24394 1 6 CACCTG AATGACTGCAATTCATT - +4 cisbp__M1171-Antp-CG4328-CG18599-CG32532-Dfd-Lim1-Lim3-Lmx1a-Scr-otp-zfh2 1 0.997626 24394.9 1 6 CACCTG TTAATTAA + +4 hdpi__TCF3 1 0.997626 24394.9 1 6 CACCTG AGAAATGA + +4 elemento__TCATTAAA -1 0.997626 24394.9 1 5 CACCTG TCATTAAA + +4 predrem__nrMotif2454 -2 0.997626 24394.9 1 4 CACCTG CCGAGCGC + +4 swissregulon__sacCer__MAC1 -4 0.997626 24394.9 1 2 CACCTG TTTGCTCA + +4 yetfasco__YMR021C_1540 -4 0.997626 24394.9 1 2 CACCTG TTTGCTCA - +4 transfac_pro__M05583 1 0.997652 24395.6 1 6 CACCTG TAACACTGTAATTGGCTTTCT + +4 transfac_pro__M05217-Brf-brm-ERR-E(z) 17 0.997652 24395.6 1 4 CACCTG GGGGGGGCCCGCTCGCCCCCC + +4 transfac_pro__M05250-Brf-brm-CTCF-ERR-E(z)-HDAC1-Nelf-E-SREBP-vtd 17 0.997652 24395.6 1 4 CACCTG GGGGGGGCCCGCCCGCCCCCC + +4 transfac_pro__M05213-Brf-brm-ERR-E(z)-HDAC1-Nelf-E-SREBP-vtd 17 0.997652 24395.6 1 4 CACCTG GGGGGCCGGGGGGGCCCCCCC - +4 cisbp__M2536-br-croc 1 0.997673 24396.1 1 6 CACCTG TTTTGTTTATTAA - +4 transfac_pro__M09245 0 0.997673 24396.1 1 6 CACCTG AATCAATCATTGA - +4 transfac_pro__M06012 0 0.997708 24396.9 1 6 CACCTG CATCACGCCAT - +4 cisbp__M6148 2 0.997712 24397.1 1 5 CACCTG TTTAATT + +4 elemento__ACGACGA -1 0.997712 24397.1 1 5 CACCTG ACGACGA + +4 flyfactorsurvey__onecut_Cell_FBgn0028996-onecut -3 0.997712 24397.1 1 3 CACCTG TTGATTT + +4 hdpi__FLJ37078-CG7971 -3 0.997712 24397.1 1 3 CACCTG TTTGAAA + +4 transfac_pro__M02334-Abd-B-cad 4 0.997712 24397.1 1 3 CACCTG CAATAAA - +4 transfac_pro__M07713-CHES-1-like 9 0.997714 24397.1 1 6 CACCTG TAGCGTCATGACGCTA + +4 hocomoco__SOX21_HUMAN.H11MO.0.D-D-Sox14-Sox15-Sox21a-Sox21b-Sox100B-Sox102F-SoxN-bbx-peng 6 0.997714 24397.1 1 6 CACCTG AACAATACCATTGTTT - +4 cisbp__M6090-SoxN 6 0.997764 24398.3 1 6 CACCTG TGAATAGTCATTCA + +4 taipale__Sox1_DBD_TGAATNNNNATTCA_repr-SoxN 6 0.997764 24398.3 1 6 CACCTG TGAATAGTCATTCA + +4 transfac_pro__M07662-brk 9 0.997764 24398.3 1 5 CACCTG TGGCGCCGGCGCCA + +4 taipale__EGR1_full_NACGCCCACGCANN-klu-sr 10 0.997764 24398.3 1 4 CACCTG TACGCCCACGCATT + +4 transfac_pro__M05192 11 0.997764 24398.3 1 3 CACCTG TTTTAAATTTAAAC + +4 predrem__nrMotif339 3 0.997777 24398.6 1 6 CACCTG AAATTCTTT + +4 predrem__nrMotif962 2 0.997777 24398.6 1 6 CACCTG TTTGCTTTA - +4 cisbp__M0345 2 0.9978 24399.2 1 6 CACCTG ATTACGAATT + +4 cisbp__M2506 0 0.9978 24399.2 1 6 CACCTG AATCGCGACA + +4 cisbp__M4675-Mef2 1 0.9978 24399.2 1 6 CACCTG CTAAAAATAA + +4 predrem__nrMotif1278 4 0.9978 24399.2 1 6 CACCTG ATTTCACAAA + +4 stark__YTAWWWWTAR-Mef2 1 0.9978 24399.2 1 6 CACCTG CTAAAAATAA + +4 taipale__FOXK1_DBD_CGGACACAAT_repr-FoxK-slp2 4 0.9978 24399.2 1 6 CACCTG CGGACACAAT + +4 transfac_public__M00263 0 0.9978 24399.2 1 6 CACCTG GATCGCGTCC + +4 cisbp__M0846 -1 0.9978 24399.2 1 5 CACCTG CAATGATTGA - +4 cisbp__M4711-Dp-E2f2 -1 0.9978 24399.2 1 5 CACCTG TTTTCGCGCG - +4 jaspar__MA0954.1 -1 0.9978 24399.2 1 5 CACCTG CAATGATTGA - +4 transfac_pro__M05029 -2 0.9978 24399.2 1 4 CACCTG TCGGCGACGA - +4 cisbp__M6194-Dp-E2f1-E2f2-eve-Rbf2 7 0.9978 24399.2 1 3 CACCTG CGCGCCAAAC + +4 bergman__slbo-slbo 7 0.9978 24399.2 1 3 CACCTG GATTGCAAAA - +4 stark__TTNNRCAATM-slbo 7 0.9978 24399.2 1 3 CACCTG GATTGCAAAA - +4 cisbp__M0665-E2f1 -4 0.9978 24399.2 1 2 CACCTG TTCGCGCGAA + +4 hocomoco__ARI3A_HUMAN.H11MO.0.D 8 0.997827 24399.9 1 6 CACCTG TTTAATTTGATTTCGATTAATT - +4 taipale_cyt_meth__NFATC2_NTTTCCRNNNNYGGAAAN_eDBD_meth-NFAT 2 0.997918 24402.1 1 6 CACCTG TTTTCCGTTAACGGAAAA + +4 hocomoco__ALX4_HUMAN.H11MO.0.D-Awh-CG4328-CG9876-CG11294-CG18599-CG32532-CG34367-Drgx-E5-Lim1-Lim3-Lmx1a-OdsH-Optix-Pph13-Rx-Traf4-Vsx1-Vsx2-al-ap-bsh-ems-en-eve-hbn-otp-repo-ro-slou-unc-4-unpg 1 0.997976 24403.5 1 6 CACCTG TAATTTAATTAA + +4 taipale__FOXG1_DBD_RCGGACACAATR-FoxK-slp2 6 0.997976 24403.5 1 6 CACCTG CATTGTGTCCGT - +4 tiffin__TIFDMEM0000078 2 0.997976 24403.5 1 6 CACCTG TTTAAATTCAAA - +4 hocomoco__FOXQ1_HUMAN.H11MO.0.C 7 0.997976 24403.5 1 5 CACCTG TATTGTTTATTT + +4 cisbp__M6250 7 0.997976 24403.5 1 5 CACCTG AATTGTTTATTT - +4 transfac_pro__M00920-Dp-E2f1-E2f2 -1 0.997976 24403.5 1 5 CACCTG GTTTGGCGCGAA - +4 transfac_pro__M05672 7 0.997976 24403.5 1 5 CACCTG TCTTTTTCATTA - +4 transfac_pro__M06415-crol 7 0.997976 24403.5 1 5 CACCTG GCGGCCCGACTA - +4 transfac_pro__M05556 8 0.997976 24403.5 1 4 CACCTG TTTCTTTATAGT - +4 tfdimers__MD00404-fkh 25 0.998073 24405.9 1 6 CACCTG TTTTTTTGTTTGTTTGTTTGTTTTTTTTTTTT + +4 transfac_pro__M05436-ci-lmd-sug 9 0.998076 24405.9 1 6 CACCTG GGGCCGCCATAATTTAA - +4 elemento__ATGGCGGC-CG10431-lid-pho-phol 2 0.998091 24406.3 1 6 CACCTG GCCGCCAT - +4 bergman__Dref-Dref 6 0.998091 24406.3 1 2 CACCTG TATCGATA + +4 elemento__TATCGATA-Dref 6 0.998091 24406.3 1 2 CACCTG TATCGATA + +4 stark__ATTNWTTA 6 0.998091 24406.3 1 2 CACCTG ATTAATTA + +4 transfac_pro__M05212-E2f1-ERR-E(z) 17 0.998131 24407.3 1 4 CACCTG TGGGGGGCCCTCCCGCCCCCC + +4 transfac_pro__M05209-Brf-brm-btd-CTCF-ERR-E(z)-Spps-vtd 17 0.998131 24407.3 1 4 CACCTG CGGGGGCGGCGGGGCCCCCCC - +4 transfac_pro__M05221-Brf-brm-ERR-E(z)-vtd 17 0.998131 24407.3 1 4 CACCTG GAGCGGCGGGGGGGCCCCCCC - +4 transfac_pro__M05236-CTCF-ERR-E(z) 17 0.998131 24407.3 1 4 CACCTG GGGGGGCGGCGGAGCCCCCCC - +4 taipale_cyt_meth__POU3F1_NTAATTWATGCGN_eDBD_meth-vvl 1 0.998134 24407.4 1 6 CACCTG ACGCATAAATTAA - +4 transfac_pro__M07923-erm 6 0.998134 24407.4 1 6 CACCTG TGATTGCTCTTTT - +4 elemento__AGCGCGC -1 0.998148 24407.7 1 5 CACCTG AGCGCGC + +4 elemento__ATGACGC 2 0.998148 24407.7 1 5 CACCTG ATGACGC + +4 elemento__GCCGCGC -1 0.998148 24407.7 1 5 CACCTG GCCGCGC + +4 elemento__TTGACAA 2 0.998148 24407.7 1 5 CACCTG TTGACAA + +4 elemento__CGATCGC 2 0.998148 24407.7 1 5 CACCTG GCGATCG - +4 cisbp__M2043-onecut -3 0.998148 24407.7 1 3 CACCTG TTGATTT + +4 hocomoco__SOX7_HUMAN.H11MO.0.D-D-Sox14-Sox15-Sox21a-Sox21b-Sox100B-Sox102F-SoxN-bbx-peng 3 0.998178 24408.5 1 6 CACCTG AAACAATTTCATTGTT - +4 transfac_pro__M05337-klu-sr -1 0.998212 24409.3 1 5 CACCTG TCCCGCCCACGCCC - +4 taipale__ONECUT2_DBD_NNAAAATCRATAWN-ct-onecut 10 0.998212 24409.3 1 4 CACCTG AAAAAATCGATAAT + +4 cisbp__M5696-ct-onecut 10 0.998212 24409.3 1 4 CACCTG AAAAAATCGATAAT - +4 cisbp__M6085-Sox100B-Sox15-SoxN 2 0.998224 24409.6 1 6 CACCTG ATGAATTGCAGTCAT + +4 stark__MGAADMGAADMGAAD-Hsf 0 0.998224 24409.6 1 6 CACCTG TTTCGTTTCGTTTCG - +4 transfac_pro__M09247 1 0.998224 24409.6 1 6 CACCTG ATAACCAATCATTAG - +4 taipale_cyt_meth__POU5F1_NYTAATTATGCGNRN_FL_meth_repr-Awh -3 0.998224 24409.6 1 3 CACCTG TTGCGCATAATTAAT - +4 taipale__Hoxd13_DBD_CCAATAAAAN-Abd-B-cad 6 0.998233 24409.8 1 4 CACCTG CCAATAAAAA + +4 taipale_cyt_meth__NFATC2_NTTTCCRNNNNYGGAAAN_eDBD-NFAT 2 0.998349 24412.6 1 6 CACCTG TTTTCCATTAATGGAAAA + +4 dbcorrdb__BRF1__ENCSR000DOJ_1__m2-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-dar1-E2f1-Eip74EF-ERR-E(z)-HDAC1-Hr78-klu-Max-Myc-Nelf-E-Nf-YB-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-Taf1-tna-vtd-zfh1 13 0.99837 24413.1 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 cisbp__M5530 3 0.998381 24413.4 1 6 CACCTG TATAATCGTTTT + +4 transfac_pro__M06957-Mitf 3 0.998381 24413.4 1 6 CACCTG GGACACGCGAAC + +4 homer__DDAAAAATTTTY_SFP1-CG12054 2 0.998381 24413.4 1 6 CACCTG GAAAATTTTTCA - +4 taipale__HOMEZ_DBD_NAAACGATNNAN_repr 3 0.998381 24413.4 1 6 CACCTG TATAATCGTTTT - +4 transfac_pro__M05179 2 0.998381 24413.4 1 6 CACCTG AAATCCGTTAAT - +4 transfac_pro__M06948-btd-Spps 6 0.998381 24413.4 1 6 CACCTG TGGGCGCGCCCA - +4 transfac_public__M00516-Dp-E2f1-E2f2-Rbf2 -2 0.998381 24413.4 1 4 CACCTG TTTCGCGCCAAA - +4 cisbp__M1918-abd-A-Antp-ap-bsh-C15-Dbx-Dll-E5-en-ftz-HGTX-lab-lbl-Lmx1a-repo-Scr-slou-Ubx-Vsx1-zen2 -3 0.998462 24415.4 1 3 CACCTG TTTAATTA + +4 flyfactorsurvey__Ubx_Cell_FBgn0003944-Antp-C15-Dbx-Dll-E5-HGTX-Lmx1a-Scr-Ubx-Vsx1-abd-A-ap-bsh-en-ftz-lab-lbl-repo-slou-zen2 -3 0.998462 24415.4 1 3 CACCTG TTTAATTA + +4 elemento__ATGGCCG 2 0.998511 24416.6 1 5 CACCTG ATGGCCG + +4 elemento__CGGCCCG 2 0.998511 24416.6 1 5 CACCTG CGGCCCG + +4 transfac_pro__M07471 2 0.998511 24416.6 1 5 CACCTG GCAGTCT + +4 elemento__CGGCCGC 2 0.998511 24416.6 1 5 CACCTG GCGGCCG - +4 scertf__badis.RSC30 -2 0.998511 24416.6 1 4 CACCTG GCGCGCG + +4 taipale_cyt_meth__POU3F4_NTAATTWATGCGN_eDBD_meth_repr-vvl 1 0.998514 24416.7 1 6 CACCTG ACGCATAAATTAA - +4 predrem__nrMotif4 -1 0.998527 24417 1 5 CACCTG AATTTTTTTTT - +4 transfac_pro__M06369-CG4730-CG7101 14 0.998557 24417.7 1 5 CACCTG GCTCGGGCATAAAATACGA + +4 transfac_pro__M07664-brk 3 0.998558 24417.7 1 6 CACCTG TGGCGCCATGGCGCTA + +4 stark__RCGCMATTW-pho -1 0.998589 24418.5 1 5 CACCTG AAATGGCGC - +4 transfac_pro__M00939-Dp-E2f1-E2f2 -2 0.998589 24418.5 1 4 CACCTG TTTGGCGCG + +4 stark__HRTCAATCA 7 0.998589 24418.5 1 2 CACCTG TATCAATCA + +4 transfac_pro__M00820 7 0.998589 24418.5 1 2 CACCTG CAATCATTA - +4 cisbp__M0575 6 0.998592 24418.6 1 4 CACCTG TAATAATAAA + +4 cisbp__M6031-Abd-B-cad 6 0.998592 24418.6 1 4 CACCTG CCAATAAAAA + +4 taipale__Sox10_DBD_ATGAATTGCAGTCAT-Sox100B-Sox15-SoxN 2 0.998592 24418.6 1 6 CACCTG ATGAATTGCAGTCAT + +4 taipale_cyt_meth__POU5F1_NTATGCGCATAN_FL_meth-nub-pdm2-vvl 5 0.998713 24421.5 1 6 CACCTG TTATGCGCATAA + +4 cisbp__M5450-FoxK-slp2 6 0.998713 24421.5 1 6 CACCTG CATTGTGTCCGT - +4 cisbp__M3134-Dp-E2f1-E2f2-Rbf2 -2 0.998713 24421.5 1 4 CACCTG TTTCGCGCCAAA + +4 tiffin__TIFDMEM0000094 8 0.998713 24421.5 1 4 CACCTG AAAAATAAAAAT + +4 homer__TTCGCGCGAAAA_E2F-Dp-E2f1-E2f2 -3 0.998713 24421.5 1 3 CACCTG TTCGCGCGAAAA + +4 taipale_cyt_meth__PAX7_NTAATYGATTAN_FL_meth-ey-eyg-gsb-gsb-n-prd-toe 9 0.998713 24421.5 1 3 CACCTG ATAATTGATTAT + +4 transfac_pro__M07036 -3 0.998831 24424.4 1 3 CACCTG TTCAATTAATA - +4 taipale_cyt_meth__ZNF713_NAGAAAAAAGACWRGAAAN_eDBD_repr 9 0.99887 24425.4 1 6 CACCTG TAGAAAAAAGACAGGAAAG + +4 taipale_cyt_meth__ZNF713_NAGAAAAAAGACWRGAAAN_eDBD_meth 2 0.99887 24425.4 1 6 CACCTG CTTTCTTGTCTTTTTTCTA - +4 taipale__ONECUT3_DBD_NNAAAATCRATANN-ct-onecut 10 0.998879 24425.6 1 4 CACCTG AAAAAATCAATAAT + +4 cisbp__M5694-ct-onecut 10 0.998879 24425.6 1 4 CACCTG AAAAAATCGATAAT - +4 cisbp__M5697-ct-onecut 10 0.998879 24425.6 1 4 CACCTG AAAAAATCAATAAT - +4 predrem__nrMotif1501 3 0.998885 24425.7 1 6 CACCTG AGAGACAAT - +4 elemento__AATTTATGC-vvl -1 0.998885 24425.7 1 5 CACCTG AATTTATGC + +4 cisbp__M5710-ey-eyg-gsb-gsb-n-prd-toe 8 0.998887 24425.8 1 2 CACCTG TAATCGATTA + +4 transfac_pro__M01300 3 0.998891 24425.9 1 6 CACCTG AATAATCGCGAATAT - +4 transfac_pro__M05473-salm-salr 4 0.998984 24428.1 1 6 CACCTG GTTTTCTATTGA + +4 transfac_pro__M05190 9 0.998984 24428.1 1 3 CACCTG TTTAAATTTAAC - +4 dbcorrdb__EZH2__ENCSR000AQE_1__m9-bon-Brf-brm-btd-CoRest-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-Hcf-HDAC1-Hr78-Jra-Max-Myc-Nelf-E-Not3-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna-Usf-vtd-zfh1 7 0.999 24428.6 1 6 CACCTG CCGGCCGGGCCCCGGGCGGG + +4 scertf__zhu.RDS1 2 0.999021 24429.1 1 6 CACCTG TCGGCCGA + +4 cisbp__M0886-Abd-B-cad 6 0.999021 24429.1 1 2 CACCTG TTTTATTA - +4 neph__UW.Motif.0038 -4 0.999021 24429.1 1 2 CACCTG TTTTTTTC - +4 scertf__macisaac.JHD1-Kdm2 -4 0.999037 24429.4 1 2 CACCTG TTCGAA + +4 transfac_pro__M09406 -4 0.999037 24429.4 1 2 CACCTG TTGAAA + +4 yetfasco__YER051W_662-Kdm2 -4 0.999037 24429.4 1 2 CACCTG TTCGAA + +4 elemento__CGCCGCG 0 0.999058 24430 1 6 CACCTG CGCCGCG + +4 elemento__GCAGCGC 1 0.999058 24430 1 6 CACCTG GCAGCGC + +4 elemento__GCGCCGC 1 0.999058 24430 1 6 CACCTG GCGCCGC + +4 elemento__TCGCCGC 1 0.999058 24430 1 6 CACCTG TCGCCGC + +4 cisbp__M5577 1 0.999065 24430.1 1 6 CACCTG AAATCGATTTTCGTTTT - +4 transfac_pro__M09103-Atac1 -2 0.99907 24430.3 1 4 CACCTG TCTCTCTCTCTCTCTCTCTCTCTC - +4 transfac_pro__M07798-gsb-gsb-n-Gsc-oc-prd 1 0.999079 24430.5 1 6 CACCTG TAATCGGATTA - +4 hocomoco__PAX7_HUMAN.H11MO.0.D-ey-eyg-gsb-gsb-n-prd-toe 8 0.999079 24430.5 1 3 CACCTG TAATTGATTAT + +4 taipale_cyt_meth__E2F7_NTTTCCCGCCAAAN_eDBD_meth_repr-E2f1-E2f2 2 0.999121 24431.5 1 6 CACCTG TTTTCCCGCCAAAA + +4 taipale_cyt_meth__NFATC1_NTTTCCATGGAAAN_eDBD-NFAT 3 0.999121 24431.5 1 6 CACCTG TTTTCCATGGAAAA + +4 taipale__ONECUT1_DBD_NNAAAATCRATAWN_repr-ct-onecut 10 0.999121 24431.5 1 4 CACCTG AAAAAATCGATAAT + +4 elemento__AAAATGGCG-pho-phol 0 0.999123 24431.6 1 6 CACCTG CGCCATTTT - +4 predrem__nrMotif1056-SREBP 1 0.999123 24431.6 1 6 CACCTG GCGCCGCGC - +4 transfac_pro__M00918-Dp-E2f1-E2f2-Rbf2 -3 0.999123 24431.6 1 3 CACCTG TTTGGCGCG + +4 transfac_pro__M05090 -3 0.999123 24431.6 1 3 CACCTG TTTTAACAA + +4 transfac_pro__M01253-E(z)-Not3-tna 0 0.999128 24431.7 1 6 CACCTG GGCCGCGCCG + +4 transfac_pro__M09249 4 0.999128 24431.7 1 6 CACCTG ACTAATCATT + +4 transfac_pro__M07546 4 0.999128 24431.7 1 6 CACCTG TCAATAATTG - +4 cisbp__M1881-hb -1 0.999128 24431.7 1 5 CACCTG GCATAAAAAA + +4 flyfactorsurvey__CG8281_SANGER_5_FBgn0035824-CG8281 6 0.999128 24431.7 1 4 CACCTG CATCAATATT + +4 cisbp__M4882-CG8281 6 0.999128 24431.7 1 4 CACCTG CATCAATATT - +4 cisbp__M5561-Abd-B-cad -3 0.999128 24431.7 1 3 CACCTG CCAATAAAAA + +4 idmmpmm__hb-hb-rn 7 0.999128 24431.7 1 3 CACCTG CACAAAAAAA + +4 taipale__HOXD13_DBD_CYAATAAAAN_repr-Abd-B-cad -3 0.999128 24431.7 1 3 CACCTG CCAATAAAAA + +4 taipale__PAX7_full_TAATYRATTA-ey-eyg-gsb-gsb-n-prd-toe 8 0.999128 24431.7 1 2 CACCTG TAATCGATTA + +4 homer__GTGCGCATGCGC_NRF-E2f1-ewg 3 0.999203 24433.5 1 6 CACCTG GTGCGCATGCGC + +4 taipale_cyt_meth__POU3F4_NTATGCGCATAN_eDBD_meth_repr-nub-pdm2-vvl 5 0.999203 24433.5 1 6 CACCTG TTATGCGCATAA + +4 tiffin__TIFDMEM0000013 3 0.999203 24433.5 1 6 CACCTG AAAAACAACAAA + +4 tiffin__TIFDMEM0000080 3 0.999203 24433.5 1 6 CACCTG ATTTCGATTTAA - +4 scertf__badis.RSC3 -1 0.999214 24433.8 1 5 CACCTG GCGCG - +4 transfac_pro__M01230 2 0.999214 24433.8 1 3 CACCTG ATTAT - +4 transfac_pro__M00427-Dp-E2f1-E2f2-eve-Rbf2 -2 0.999226 24434.1 1 4 CACCTG GCGCGAAA - +4 transfac_pro__M00736-Dp-E2f1-E2f2-eve -2 0.999226 24434.1 1 4 CACCTG GCGGGAAA - +4 transfac_pro__M00737-Dp-E2f1-E2f2 -4 0.999226 24434.1 1 2 CACCTG TTTCCCGC + +4 dbcorrdb__HDAC2__ENCSR000AQG_1__m4-bon-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-klu-Max-Myc-Nelf-E-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-TfAP-2-tna-vtd-zfh1 3 0.999227 24434.1 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 dbcorrdb__XRCC4__ENCSR000FAC_1__m1-bon-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-kay-klu-Max-Myc-Nelf-E-Nf-YB-Rbbp5-RpII215-Sin3A-Spps-Spt20-sr-SREBP-Taf1- 3 0.999227 24434.1 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC - +4 cisbp__M4974-fru 2 0.99926 24434.9 1 5 CACCTG GAAAAAA + +4 stark__GACAATK -2 0.99926 24434.9 1 4 CACCTG AATTGTC - +4 stark__RATTAAW-retn 3 0.99926 24434.9 1 4 CACCTG ATTAATC - +4 taipale__IRF7_DBD_RAANCGAAAWTCGNTTY_repr 1 0.999275 24435.3 1 6 CACCTG AAATCGATTTTCGTTTT - +4 hocomoco__OZF_HUMAN.H11MO.0.C 6 0.999284 24435.5 1 6 CACCTG TTTTCATGGCTGCATAGTATTCCA + +4 cisbp__M5167-rib 0 0.99931 24436.1 1 6 CACCTG TTTTTTGCG + +4 flyfactorsurvey__rib_SANGER_5_FBgn0003254-rib 0 0.99931 24436.1 1 6 CACCTG TTTTTTGCG - +4 predrem__nrMotif1571 -3 0.99931 24436.1 1 3 CACCTG TTTGAATTG - +4 predrem__nrMotif1744 1 0.999323 24436.4 1 6 CACCTG AATTCTGAAA - +4 jaspar__MA0049.1-hb -1 0.999323 24436.4 1 5 CACCTG GCATAAAAAA + +4 cisbp__M5825-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.999327 24436.5 1 6 CACCTG AACACTACCATTGTT + +4 taipale__SOX21_DBD_AACAATNNNAKTGTT-bbx-D-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 2 0.999327 24436.5 1 6 CACCTG AACACTACCATTGTT - +4 flyfactorsurvey__br-PAPC_SOLEXA_2.5-br 10 0.999327 24436.5 1 5 CACCTG TGCCGTCTTCTGCTT + +4 transfac_pro__M05990 7 0.999379 24437.8 1 5 CACCTG AAATCGGGATCA + +4 cisbp__M1603-Sox100B-Sox102F 0 0.999393 24438.2 1 6 CACCTG GAACAATA + +4 cisbp__M0566 3 0.999393 24438.2 1 5 CACCTG ATGATCAT + +4 elemento__ATTGGCCG 3 0.999393 24438.2 1 5 CACCTG ATTGGCCG + +4 cisbp__M0530-CG12054 -1 0.999393 24438.2 1 5 CACCTG ATTTTTTC - +4 cisbp__M0583 5 0.999393 24438.2 1 3 CACCTG AATAAAAA - +4 swissregulon__hs__E2F1..5.p2-Dp-E2f1-E2f2-Rbf2 -4 0.999393 24438.2 1 2 CACCTG TTTGGCGC + +4 transfac_pro__M08816 -4 0.999393 24438.2 1 2 CACCTG TTTTATTA + +4 dbcorrdb__CTCF__ENCSR000DLW_1__m3-bab1-CG4328-CG7839-ct-CTCF-Lmx1a-nej-SREBP-vtd 8 0.999407 24438.5 1 6 CACCTG TAAAATTAAATTTTTTTTAA + +4 stark__GCGYNWNAWTGAY -1 0.99944 24439.3 1 5 CACCTG GCGCAAAAATGAC + +4 tfdimers__MD00277 0 0.999443 24439.4 1 6 CACCTG TTATTTTAAATTTTATTGGCCAATAAAATTTTTAATAA + +4 predrem__nrMotif2601 4 0.99946 24439.8 1 5 CACCTG ATAATATTT + +4 taipale_cyt_meth__NFATC1_NTTTCCGCGGAAAN_eDBD_meth-NFAT 2 0.999471 24440.1 1 6 CACCTG TTTTCCGCGGAAAA + +4 taipale_cyt_meth__SOX9_MGAACAATRN_eDBD-D-Sox100B-Sox102F-SoxN 1 0.999477 24440.2 1 6 CACCTG AGAACAATGG + +4 cisbp__M5813-Sox100B-Sox15-SoxN 2 0.999481 24440.3 1 6 CACCTG ATGAATTGCAGTCAT + +4 taipale__SOX10_full_ATGAATTGCAGTCAT-Sox100B-Sox15-SoxN 2 0.999481 24440.3 1 6 CACCTG ATGAATTGCAGTCAT + +4 transfac_pro__M09104-Atac1 -3 0.999511 24441 1 3 CACCTG CTCTCTCTCTCTCTCTCTCTCTCTCTCTCT - +4 transfac_pro__M06452 10 0.99952 24441.3 1 2 CACCTG GATTCAAAAATA + +4 cisbp__M2158-NFAT -1 0.999528 24441.5 1 5 CACCTG TCCGCGGA + +4 elemento__AAATCAAT -1 0.999528 24441.5 1 5 CACCTG AAATCAAT + +4 jaspar__MA0353.1-NFAT -1 0.999528 24441.5 1 5 CACCTG TCCGCGGA + +4 cisbp__M4997-hb -3 0.999528 24441.5 1 3 CACCTG TTTTTTAT - +4 transfac_pro__M05314 0 0.999537 24441.7 1 6 CACCTG GTCATAATTATTTATGAA + +4 transfac_pro__M06901 5 0.999537 24441.7 1 6 CACCTG CCCCCCAATTCTTATTAT - +4 cisbp__M5355-E2f1-E2f2 13 0.999537 24441.7 1 5 CACCTG CATTTTGGCGCCAAAATT + +4 taipale__E2F2_DBD_NNTTTTGGCGCCAAAANN-E2f1-E2f2 13 0.999537 24441.7 1 5 CACCTG CATTTTGGCGCCAAAATT - +4 transfac_pro__M00987 1 0.999549 24442 1 6 CACCTG TTATTTGTGTTGTTTTTTAT + +4 predrem__nrMotif1735 3 0.999581 24442.7 1 6 CACCTG AATTATTTC - +4 taipale_cyt_meth__NFATC2_NTTTCCATGGAAAN_eDBD-NFAT 3 0.999594 24443.1 1 6 CACCTG TTTTCCATGGAAAA + +4 cisbp__M5704-ey-eyg-gsb-gsb-n-prd-toe 8 0.999598 24443.2 1 2 CACCTG TAATCGATTA + +4 taipale__PAX3_DBD_TAATYRATTA_repr-ey-eyg-gsb-gsb-n-prd-toe 8 0.999598 24443.2 1 2 CACCTG TAATCGATTA + +4 taipale_cyt_meth__PAX3_NTAATYGATTAN_eDBD-ey-eyg-gsb-gsb-n-prd-toe 1 0.999633 24444 1 6 CACCTG CTAATTGATTAG + +4 elemento__TTATGCAA 1 0.999635 24444.1 1 6 CACCTG TTGCATAA - +4 jaspar__MA0951.1 3 0.999635 24444.1 1 5 CACCTG TAATAATT + +4 cisbp__M0493 4 0.999635 24444.1 1 4 CACCTG GAAAAAAA + +4 transfac_pro__M00426-Dp-E2f1-E2f2-eve-Rbf2 -2 0.999635 24444.1 1 4 CACCTG GCGCGAAA - +4 cisbp__M0873 5 0.999635 24444.1 1 3 CACCTG CCAATCAA + +4 flyfactorsurvey__hb_FlyReg_FBgn0001180-hb -3 0.999635 24444.1 1 3 CACCTG TTTTTTAT + +4 transfac_pro__M05549 4 0.999649 24444.4 1 6 CACCTG TTCATAAATAATTATGAC - +4 hocomoco__ZN502_HUMAN.H11MO.0.C-Iswi-crol 12 0.99966 24444.7 1 6 CACCTG GATTCCATTCGATTCCATTC - +4 elemento__TTAAAAA -4 0.999666 24444.8 1 2 CACCTG TTAAAAA + +4 elemento__TTAATAA -4 0.999666 24444.8 1 2 CACCTG TTAATAA + +4 elemento__TTTAAAA -4 0.999666 24444.8 1 2 CACCTG TTTAAAA + +4 elemento__TTTCAAA -4 0.999666 24444.8 1 2 CACCTG TTTCAAA + +4 transfac_pro__M09155 -4 0.999666 24444.8 1 2 CACCTG TTGAAAA + +4 elemento__AATAAAA -4 0.999666 24444.8 1 2 CACCTG TTTTATT - +4 elemento__ATTAAAA -4 0.999666 24444.8 1 2 CACCTG TTTTAAT - +4 hocomoco__HNF6_HUMAN.H11MO.0.B-onecut 0 0.999675 24445.1 1 6 CACCTG TTTATTGATTT + +4 stark__TGCTCAATGAA 9 0.999675 24445.1 1 2 CACCTG TTCATTGAGCA - +4 taipale__Sox3_DBD_NAACAATRNYATTGTTN-bbx-D-fkh-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.999677 24445.1 1 6 CACCTG AAACAATGACATTGTTT + +4 cisbp__M6093-bbx-D-fkh-peng-Sox100B-Sox102F-Sox14-Sox15-Sox21a-Sox21b-SoxN 7 0.999677 24445.1 1 6 CACCTG AAACAATGACATTGTTT - +4 fantom__motif11_GCGANT 3 0.999682 24445.2 1 3 CACCTG AATCGC - +4 swissregulon__sacCer__RSC30 4 0.99969 24445.4 1 6 CACCTG CGCGCGCGCG - +4 taipale__E2F7_DBD_TTTTCCCGCCAAAW_repr-E2f1-E2f2 2 0.999691 24445.4 1 6 CACCTG TTTTCCCGCCAAAA + +4 taipale_cyt_meth__YY2_NKCSGCCATTTTGN_FL_meth-pho-phol-RpII215 3 0.999691 24445.4 1 6 CACCTG GGCCGCCATTTTGA + +4 hocomoco__HOMEZ_HUMAN.H11MO.0.D 3 0.999698 24445.6 1 6 CACCTG AAAAATCGTTTTTTT + +4 jaspar__MA0952.1 -2 0.999721 24446.2 1 4 CACCTG AATTATTG + +4 cisbp__M1299-Mef2 -4 0.999721 24446.2 1 2 CACCTG TTAATAAA + +4 predrem__nrMotif1369 -4 0.999721 24446.2 1 2 CACCTG TTTAATAA + +4 predrem__nrMotif2155 -4 0.999721 24446.2 1 2 CACCTG TTCATTGC + +4 dbcorrdb__RBBP5__ENCSR000AQC_1__m5-bon-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-dar1-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Klf15-klu-l(3)neo38-Max-Myc-Nelf-E-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-tna-v -2 0.999745 24446.8 1 4 CACCTG CCCCCCCCCCCCCCCCCCCG + +4 transfac_pro__M07800-al-ap-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-ems-eve-hbn-Lim3-Lmx1a-nej-OdsH-Optix-otp-Pph13-repo-ro-Rx-Traf4-unc-4-Vsx1 2 0.99975 24446.9 1 6 CACCTG TTAATTTAATTAA + +4 cisbp__M5845-Sox100B-Sox15 2 0.999757 24447.1 1 6 CACCTG AATCACTGCAATTGATT - +4 taipale__SOX8_full_NATCAATKNYAGTGATN-Sox100B-Sox15 2 0.999757 24447.1 1 6 CACCTG AATCACTGCAATTGATT - +4 cisbp__M5362-E2f1-E2f2 2 0.999766 24447.3 1 6 CACCTG TTTTCCCGCCAAAA + +4 taipale_cyt_meth__E2F7_NTTTCCCGCCAAAN_eDBD-E2f1-E2f2 2 0.999766 24447.3 1 6 CACCTG ATTTCCCGCCAAAA + +4 transfac_pro__M00408 1 0.999769 24447.3 1 6 CACCTG ATACCAAAAATGGAAA + +4 transfac_pro__M06831-CG4730-CG7101 0 0.999779 24447.6 1 6 CACCTG GTTCGGAAATAAAAGCGTT + +4 cisbp__M0854 3 0.999789 24447.9 1 5 CACCTG TAATAATT + +4 transfac_pro__M00738-Dp-E2f1-E2f2-Rbf2 -4 0.999789 24447.9 1 2 CACCTG TTTCGCGC + +4 transfac_pro__M03829-onecut 6 0.999789 24447.9 1 2 CACCTG AATCAATA + +4 transfac_pro__M01005 0 0.99979 24447.9 1 6 CACCTG TTTCTTTGTTCT - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m7-bon-Brf-brm-btd-CG42741-CoRest-CrebB-crol-ct-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-klu-Max-Myc-Nelf-E-Nf-YB-peb-Rbbp5-RpII215-Spps-Spt20-sr-SREBP-Taf1-TfAP- 4 0.999811 24448.4 1 6 CACCTG CCCCCCCCCCCCCCCCCCCC + +4 transfac_pro__M06972-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-eve-hbn-Lmx1a-nej-OdsH-Optix-repo-Traf4-unc-4 1 0.999812 24448.4 1 6 CACCTG TTAATTTAATTAA + +4 transfac_pro__M06988-al-bsh-CG11294-CG32532-CG34367-CG4328-CG9876-Drgx-eve-hbn-Lmx1a-nej-OdsH-Optix-repo-tll-Traf4-unc-4 5 0.999812 24448.4 1 6 CACCTG TTAATTAAATTAA - +4 taipale_cyt_meth__POU1F1_NTAATTTATGCGN_eDBD_meth-vvl 10 0.999812 24448.4 1 3 CACCTG ACGCATAAATTAA - +4 taipale_cyt_meth__NFATC2_NTTTCCGCGGAAAN_eDBD_meth-NFAT 2 0.999825 24448.7 1 6 CACCTG TTTTCCGCGGAAAA + +4 taipale_cyt_meth__E2F3_NTTTTGGCGCCAAAAN_eDBD-E2f1-E2f2 7 0.999827 24448.8 1 6 CACCTG ATTTTGGCGCCAAAAT - +4 taipale_cyt_meth__ZNF713_NMGACGACTGCCACGAAAN_eDBD_meth 2 0.999836 24449 1 6 CACCTG GTTTCGTGGCAGTCGTCTA - +4 transfac_pro__M00739-Dp-E2f2 -2 0.999843 24449.2 1 4 CACCTG GCGGGAAA - +4 tiffin__TIFDMEM0000086 8 0.999844 24449.2 1 4 CACCTG TTTTTAAAAATT - +4 elemento__ATTATGCAA 1 0.999859 24449.6 1 6 CACCTG TTGCATAAT - +4 elemento__CGAGCGC 4 0.999865 24449.7 1 3 CACCTG CGAGCGC + +4 elemento__CGCGCGC 4 0.999865 24449.7 1 3 CACCTG CGCGCGC + +4 elemento__CGCGCTC 4 0.999865 24449.7 1 3 CACCTG CGCGCTC + +4 hdpi__HDAC8 1 0.99988 24450.1 1 5 CACCTG ATTAAT + +4 elemento__TTTCGCGC -4 0.999884 24450.2 1 2 CACCTG TTTCGCGC + +4 transfac_public__M00050-Dp-E2f1-E2f2-eve-Rbf2 -4 0.999884 24450.2 1 2 CACCTG TTTCGCGC + +4 cisbp__M0127 -4 0.999884 24450.2 1 2 CACCTG TTTATTTT - +4 stark__KCAATAAA -4 0.999884 24450.2 1 2 CACCTG TTTATTGA - +4 transfac_pro__M08830 4 0.999895 24450.4 1 5 CACCTG CGCGAAAAT + +4 transfac_pro__M00425-Dp-E2f1-E2f2-eve-Rbf2 -4 0.999916 24450.9 1 2 CACCTG TTTCGCGC + +4 transfac_pro__M05561 2 0.999925 24451.2 1 6 CACCTG AAAATCGTTTCGC - +4 taipale_cyt_meth__SOX10_AACAATNNNNNATTGTT_eDBD_meth-Sox100B 8 0.999928 24451.2 1 6 CACCTG AACAATGGGCCATTGTT + +4 cisbp__M5361-E2f1-E2f2 5 0.999938 24451.5 1 6 CACCTG TTTGGCGCCAAA + +4 dbcorrdb__SREBF2__ENCSR000EZO_1__m1-Brf-brm-CrebB-CTCF-E2f1-ERR-E(z)-Hcf-HDAC1-Max-Myc-Nelf-E-Rbbp5-RpII215-Spt20-SREBP-tna-vtd 6 0.999947 24451.7 1 6 CACCTG GCCGCGCCGCGCCGCGCCGC + +4 transfac_pro__M05289 10 0.999951 24451.8 1 6 CACCTG GATTTAAATTTAAATT + +4 taipale_cyt_meth__E2F3_NTTTTGGCGCCAAAAN_eDBD_meth-E2f1-E2f2 7 0.999951 24451.8 1 6 CACCTG ATTTTGGCGCCAAAAT - +4 taipale__E2F4_DBD_TTTGGCGCCAAA-E2f1-E2f2 5 0.999955 24451.9 1 6 CACCTG TTTGGCGCCAAA + +4 transfac_pro__M05334-Brf-brm-btd-CTCF-HDAC1-Nelf-E-Rbbp5-Spps-Spt20-sr-SREBP 16 0.999955 24451.9 1 5 CACCTG CCGCCCACGCCGCCCACGCCC - +4 transfac_pro__M07944-sens-sens-2 12 0.999964 24452.1 1 2 CACCTG AATAAATCACTGCA + +4 transfac_pro__M01690 5 0.999968 24452.2 1 6 CACCTG AATCCCGCCCGCGGCTTTT - +4 transfac_pro__M00740-Dp-E2f1-E2f2-Rbf2 5 0.99997 24452.3 1 3 CACCTG TTTGGCGC + +4 dbcorrdb__EZH2__ENCSR000ARK_1__m4-bon-Brf-brm-btd-CoRest-CrebB-CTCF-E2f1-Eip74EF-ERR-ewg-E(z)-FoxP-Hcf-HDAC1-Hr78-Jra-Max-Myc-Nelf-E-Not3-pho-phol-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Taf1-TfAP-2-tna- 14 0.999974 24452.4 1 6 CACCTG CGCCGCGCCCGCGGCCGCGG + +4 dbcorrdb__IRF3__ENCSR000DZX_1__m4-bab1-brm-CG7839-ct-CTCF-Dbx-maf-S-nej-orb-RpII215-SREBP-vtd-Xrp1 11 0.999974 24452.4 1 6 CACCTG TATTTTTTTTTTATTTTTTT + +4 dbcorrdb__POLR3G__ENCSR000EHQ_1__m4-bab1-CG7839-ct-CTCF-SREBP-vtd-Xrp1 13 0.999974 24452.4 1 6 CACCTG AAAAAAAAATTTTTTTTTTT + +4 taipale_cyt_meth__ZNF140_NRCAATTCCGCTCN_eDBD 10 0.999975 24452.4 1 4 CACCTG AGCAATTCCGCTCA + +4 cisbp__M2095 5 0.999984 24452.6 1 6 CACCTG AATCCCGCCCGCGGCTTTT - +4 jaspar__MA0290.1 5 0.999984 24452.6 1 6 CACCTG AATCCCGCCCGCGGCTTTT - +4 bergman__hb-hb -4 0.999986 24452.7 1 2 CACCTG TTTTTTATGC - +4 stark__SMATAAAAAA-hb -4 0.999986 24452.7 1 2 CACCTG TTTTTTATGC - +4 dbcorrdb__MXI1__ENCSR000EIA_1__m4-bon-Brf-brm-btd-CoRest-CrebB-CTCF-E2f1-Eip74EF-ERR-E(z)-Hcf-HDAC1-Hr78-Jra-kay-Max-Myc-Nelf-E-Not3-Rbbp5-RpII215-Sin3A-Spps-Spt20-SREBP-Stat92E-Taf1-TfAP-2-tna-Usf-vt 1 0.999991 24452.8 1 6 CACCTG CGCCCCGGCCCCCGCCCCCG - +4 transfac_pro__M09415-brm-CG7839-FoxP-jim-maf-S-orb-rn-RpII215-sqz-SREBP-vtd -4 0.999992 24452.8 1 2 CACCTG TTTTTTTTTTTTTTT - +4 taipale_cyt_meth__ZNF140_NRCAATTCCGCTCN_eDBD_meth_repr 1 0.999994 24452.9 1 6 CACCTG TGAGCGGAATTGCT - +4 transfac_pro__M05841 12 0.999995 24452.9 1 6 CACCTG AAGAATAAAAAACAGCCCG + +4 yetfasco__YML113W_1416-brm-maf-S-rn-sqz -4 0.999995 24452.9 1 2 CACCTG TTTTTATTTTT + +4 dbcorrdb__MAFK__ENCSR000DYV_1__m3-brm-CG7839-HDAC1-jim-maf-S-orb-rn-RpII215-sqz-SREBP-vtd -3 1 24453 1 3 CACCTG TTTTTTTTTTTTTTTTTTTT + +4 dbcorrdb__SMARCA4__ENCSR000EZC_1__m9-brm-CG7839-jim-maf-S-orb-rn-RpII215-sqz-SREBP-vtd -4 1 24453 1 2 CACCTG TTTTTTTTTTTTTTTTTTTT + +4 transfac_pro__M09021-brm-CG7839-jim-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 0 1 24453 1 6 CACCTG TTTTTTTTTTTTTTTTTTTTTTTTTTTTC + +4 dbcorrdb__CEBPZ__ENCSR000EDO_1__m5-bab1-brm-CG7839-ct-CTCF-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 4 1 24453 1 6 CACCTG TTTTTTTTTTTTTTTTTTTT - +4 dbcorrdb__SREBF2__ENCSR000DYT_1__m6-brm-CG7839-CTCF-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 0 1 24453 1 6 CACCTG TTTTTTTTTTTTTTTTTTTT - +4 dbcorrdb__RAD21__ENCSR000EHX_1__m6-brm-CG7839-CTCF-maf-S-orb-rn-RpII215-sqz-SREBP-vtd 17 1 24453 1 3 CACCTG AAAAAAAAAAAAAAAAAAAA + + +# Tomtom (Motif Comparison Tool): Version 5.5.1 compiled on Mar 14 2023 at 10:55:24 +# The format of this file is described at https://meme-suite.org/meme/doc/tomtom-output-format.html. +# tomtom -thresh 1 -oc ./motif-4 motif-4.meme ./motif2gene_names.all.meme diff --git a/the_code/Human/data/tomtom/motif-4/tomtom.xml b/the_code/Human/data/tomtom/motif-4/tomtom.xml new file mode 100644 index 0000000000000000000000000000000000000000..09f42deb076d4ad2061155cf82c8ff20b2de88fe --- /dev/null +++ b/the_code/Human/data/tomtom/motif-4/tomtom.xml @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:66f17aa301e68c49a08bc517dca543702d522b9ec44cdd11f029389274f9668e +size 24992195 diff --git a/the_code/Human/enformer_funcs.py b/the_code/Human/enformer_funcs.py new file mode 100644 index 0000000000000000000000000000000000000000..ed074e1381c8b8d2209296f7b28290208a7c9d85 --- /dev/null +++ b/the_code/Human/enformer_funcs.py @@ -0,0 +1,179 @@ +import os +import tensorflow as tf +import tensorflow_hub as hub +import joblib +import gzip +import kipoiseq +from kipoiseq import Interval +import pyfaidx +import pandas as pd +import numpy as np +import matplotlib.pyplot as plt +import matplotlib as matplotlib +import seaborn as sns +from pybedtools import BedTool +import numpy as np + + +class FastaStringExtractor: + + def __init__(self, fasta_file): + self.fasta = pyfaidx.Fasta(fasta_file) + self._chromosome_sizes = {k: len(v) for k, v in self.fasta.items()} + + def extract(self, interval: Interval, **kwargs) -> str: + # Truncate interval if it extends beyond the chromosome lengths. + chromosome_length = self._chromosome_sizes[interval.chrom] + trimmed_interval = Interval(interval.chrom, + max(interval.start, 0), + min(interval.end, chromosome_length), + ) + # pyfaidx wants a 1-based interval + sequence = str(self.fasta.get_seq(trimmed_interval.chrom, + trimmed_interval.start + 1, + trimmed_interval.stop).seq).upper() + # Fill truncated values with N's. + pad_upstream = 'N' * max(-interval.start, 0) + pad_downstream = 'N' * max(interval.end - chromosome_length, 0) + return pad_upstream + sequence + pad_downstream + + def close(self): + return self.fasta.close() + + +def variant_generator(vcf_file, gzipped=False): + """Yields a kipoiseq.dataclasses.Variant for each row in VCF file.""" + def _open(file): + return gzip.open(vcf_file, 'rt') if gzipped else open(vcf_file) + + with _open(vcf_file) as f: + for line in f: + if line.startswith('#'): + continue + chrom, pos, id, ref, alt_list = line.split('\t')[:5] + # Split ALT alleles and return individual variants as output. + for alt in alt_list.split(','): + yield kipoiseq.dataclasses.Variant(chrom=chrom, pos=pos, + ref=ref, alt=alt, id=id) + + +def one_hot_encode(sequence): + return kipoiseq.transforms.functional.one_hot_dna(sequence).astype(np.float32) + + +def variant_centered_sequences(vcf_file, sequence_length, gzipped=False, + chr_prefix=''): + seq_extractor = kipoiseq.extractors.VariantSeqExtractor( + reference_sequence=FastaStringExtractor(fasta_file)) + + for variant in variant_generator(vcf_file, gzipped=gzipped): + interval = Interval(chr_prefix + variant.chrom, + variant.pos, variant.pos) + interval = interval.resize(sequence_length) + center = interval.center() - interval.start + + reference = seq_extractor.extract(interval, [], anchor=center) + alternate = seq_extractor.extract(interval, [variant], anchor=center) + + yield {'inputs': {'ref': one_hot_encode(reference), + 'alt': one_hot_encode(alternate)}, + 'metadata': {'chrom': chr_prefix + variant.chrom, + 'pos': variant.pos, + 'id': variant.id, + 'ref': variant.ref, + 'alt': variant.alt}} + +# @title `Enformer`, `EnformerScoreVariantsNormalized`, `EnformerScoreVariantsPCANormalized`, +SEQUENCE_LENGTH = 393216 + +class Enformer: + + def __init__(self, tfhub_url): + self._model = hub.load(tfhub_url).model + + def predict_on_batch(self, inputs): + predictions = self._model.predict_on_batch(inputs) + return {k: v.numpy() for k, v in predictions.items()} + + @tf.function + def contribution_input_grad(self, input_sequence, + target_mask, output_head='mouse'): + input_sequence = input_sequence[tf.newaxis] + + target_mask_mass = tf.reduce_sum(target_mask) + with tf.GradientTape() as tape: + tape.watch(input_sequence) + prediction = tf.reduce_sum( + target_mask[tf.newaxis] * + self._model.predict_on_batch(input_sequence)[output_head]) / target_mask_mass + + input_grad = tape.gradient(prediction, input_sequence) * input_sequence + input_grad = tf.squeeze(input_grad, axis=0) + return tf.reduce_sum(input_grad, axis=-1) + + +class EnformerScoreVariantsRaw: + + def __init__(self, tfhub_url, organism='human'): + self._model = Enformer(tfhub_url) + self._organism = organism + + def predict_on_batch(self, inputs): + ref_prediction = self._model.predict_on_batch(inputs['ref'])[self._organism] + alt_prediction = self._model.predict_on_batch(inputs['alt'])[self._organism] + + return alt_prediction.mean(axis=1) - ref_prediction.mean(axis=1) + + +class EnformerScoreVariantsNormalized: + + def __init__(self, tfhub_url, transform_pkl_path, + organism='human'): + assert organism == 'human', 'Transforms only compatible with organism=human' + self._model = EnformerScoreVariantsRaw(tfhub_url, organism) + with tf.io.gfile.GFile(transform_pkl_path, 'rb') as f: + transform_pipeline = joblib.load(f) + self._transform = transform_pipeline.steps[0][1] # StandardScaler. + + def predict_on_batch(self, inputs): + scores = self._model.predict_on_batch(inputs) + return self._transform.transform(scores) + + +class EnformerScoreVariantsPCANormalized: + + def __init__(self, tfhub_url, transform_pkl_path, + organism='human', num_top_features=500): + self._model = EnformerScoreVariantsRaw(tfhub_url, organism) + with tf.io.gfile.GFile(transform_pkl_path, 'rb') as f: + self._transform = joblib.load(f) + self._num_top_features = num_top_features + + def predict_on_batch(self, inputs): + scores = self._model.predict_on_batch(inputs) + return self._transform.transform(scores)[:, :self._num_top_features] + + +def plot_tracks(tracks, interval, height=1.5): + fig, axes = plt.subplots(len(tracks), 1, figsize=(20, height * len(tracks)), sharex=True) + for ax, (title, y) in zip(axes, tracks.items()): + ax.fill_between(np.linspace(interval.start, interval.end, num=len(y)), y) + ax.set_title(title) + sns.despine(top=True, right=True, bottom=True) + ax.set_xlabel(str(interval)) + plt.tight_layout() + + +# @title Compute contribution scores +def get_contribution_scores(model, seq, track_nr, seq_len=500): + predictions = model.predict_on_batch(seq[np.newaxis])['mouse'][0] + + target_mask = np.zeros_like(predictions) + for idx in [447, 448, 449]: + target_mask[idx, track_nr] = 1 + #target_mask[idx, 183] = 1 + # This will take some time since tf.function needs to get compiled. + contribution_scores = model.contribution_input_grad(seq.astype(np.float32), target_mask).numpy() + contribution_scores = np.repeat(contribution_scores[196608-int(seq_len/2):196608+int(seq_len/2)],4) + contribution_scores = np.reshape(contribution_scores, (500,4)) + return 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"Dense", "config": {"name": "dense_3", "trainable": true, "dtype": "float32", "units": 48, "activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "inbound_nodes": [[["dropout_3", 0, 0, {}]], [["dropout_3", 1, 0, {}]]]}, {"name": "average_1", "class_name": "Average", "config": {"name": "average_1", "trainable": true, "dtype": "float32"}, "inbound_nodes": [[["dense_3", 0, 0, {}], ["dense_3", 1, 0, {}]]]}], "input_layers": [["input_1", 0, 0], ["input_2", 0, 0]], "output_layers": [["average_1", 0, 0]]}, "keras_version": "2.3.1", "backend": "tensorflow"} \ No newline at end of file diff --git a/the_code/Human/models/deepmel2_gabpa/model_epoch_09.hdf5 b/the_code/Human/models/deepmel2_gabpa/model_epoch_09.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..75f682964cadb90d571267c21ab15c2e72e2943a --- /dev/null +++ b/the_code/Human/models/deepmel2_gabpa/model_epoch_09.hdf5 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a3fbc80ae46818ae684c44d47296ecde077d955f1549b97f142de1f1f46f4eca +size 25551352 diff --git a/the_code/Human/utils.py b/the_code/Human/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..e4d69e1692cc74eb30e9bbc7dc29008d2f3dd317 --- /dev/null +++ b/the_code/Human/utils.py @@ -0,0 +1,511 @@ +import tensorflow as tf +import numpy as np +import matplotlib + +def one_hot_encode_along_row_axis(sequence): + to_return = np.zeros((1, len(sequence), 4), dtype=np.int8) + seq_to_one_hot_fill_in_array(zeros_array=to_return[0], sequence=sequence, one_hot_axis=1) + return to_return + + +def seq_to_one_hot_fill_in_array(zeros_array, sequence, one_hot_axis): + assert one_hot_axis == 0 or one_hot_axis == 1 + if one_hot_axis == 0: + assert zeros_array.shape[1] == len(sequence) + elif one_hot_axis == 1: + assert zeros_array.shape[0] == len(sequence) + for (i, char) in enumerate(sequence): + if char == "A" or char == "a": + char_idx = 0 + elif char == "C" or char == "c": + char_idx = 1 + elif char == "G" or char == "g": + char_idx = 2 + elif char == "T" or char == "t": + char_idx = 3 + elif char == "N" or char == "n": + continue + else: + raise RuntimeError("Unsupported character: " + str(char)) + if one_hot_axis == 0: + zeros_array[char_idx, i] = 1 + elif one_hot_axis == 1: + zeros_array[i, char_idx] = 1 + + +def readfile(filename): + ids = [] + ids_d = {} + seqs = {} + f = open(filename, 'r') + lines = f.readlines() + f.close() + seq = [] + for line in lines: + if line[0] == '>': + ids.append(line[1:].rstrip('\n')) + id_line = line[1:].rstrip('\n').split('_')[0] + if id_line not in seqs: + seqs[id_line] = [] + if id_line not in ids_d: + ids_d[id_line] = id_line + if seq: + seqs[ids[-2].split('_')[0]] = ("".join(seq)) + seq = [] + else: + seq.append(line.rstrip('\n').upper()) + if seq: + seqs[ids[-1].split('_')[0]] = ("".join(seq)) + + return ids, ids_d, seqs + + +def prepare_data(filename): + ids, ids_d, seqs, = readfile(filename) + X = np.array([one_hot_encode_along_row_axis(seqs[id_]) for id_ in ids_d]).squeeze(axis=1) + data = X + return data, ids + + +def plot_prediction_givenax(model, fig, ntrack, track_no, seq_onehot): + NUM_CLASSES = model.output_shape[1] + real_score = model.predict(seq_onehot)[0] + ax = fig.add_subplot(ntrack, 2, track_no*2-1) + ax.margins(x=0) + ax.set_ylabel('Prediction', color='red') + ax.plot(real_score, '--', color='gray', linewidth=3) + ax.scatter(range(NUM_CLASSES), real_score, marker='o', color='red', linewidth=11) + ax.tick_params(axis='y', labelcolor='red') + ax.set_xticks(range(NUM_CLASSES),) + ax.set_xticklabels(range(1, NUM_CLASSES+1)) + ax.grid(True) + return ax + + +def create_saturation_mutagenesis_x(onehot): + mutagenesis_X = {"X":[],"ids":[]} + onehot = onehot.squeeze() + for mutloc,nt in enumerate(onehot): + new_X = np.copy(onehot) + if list(nt) == [1, 0, 0, 0]: + new_X[mutloc,:] = np.array([0, 1, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 1, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 0, 1], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + mutagenesis_X["ids"].append(str(mutloc)+"_C") + mutagenesis_X["ids"].append(str(mutloc)+"_G") + mutagenesis_X["ids"].append(str(mutloc)+"_T") + if list(nt) == [0, 1, 0, 0]: + new_X[mutloc,:] = np.array([1, 0, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 1, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 0, 1], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + mutagenesis_X["ids"].append(str(mutloc)+"_A") + mutagenesis_X["ids"].append(str(mutloc)+"_G") + mutagenesis_X["ids"].append(str(mutloc)+"_T") + if list(nt) == [0, 0, 1, 0]: + new_X[mutloc,:] = np.array([1, 0, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 1, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 0, 1], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + mutagenesis_X["ids"].append(str(mutloc)+"_A") + mutagenesis_X["ids"].append(str(mutloc)+"_C") + mutagenesis_X["ids"].append(str(mutloc)+"_T") + if list(nt) == [0, 0, 0, 1]: + new_X[mutloc,:] = np.array([1, 0, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 1, 0, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + new_X[mutloc,:] = np.array([0, 0, 1, 0], dtype='int8') + mutagenesis_X["X"].append(np.copy(new_X)) + mutagenesis_X["ids"].append(str(mutloc)+"_A") + mutagenesis_X["ids"].append(str(mutloc)+"_C") + mutagenesis_X["ids"].append(str(mutloc)+"_G") + + mutagenesis_X["X"] = np.array(mutagenesis_X["X"]) + return mutagenesis_X + + +def plot_mutagenesis_givenax(model, fig, ntrack, track_no, seq_onehot, class_no): + + mutagenesis_X = create_saturation_mutagenesis_x(seq_onehot) + prediction_mutagenesis_X = model.predict(mutagenesis_X["X"]) + original_prediction = model.predict(seq_onehot) + class_no = class_no-1 + seq_shape = (seq_onehot.shape[1],seq_onehot.shape[2]) + + arr_a = np.zeros(seq_shape[0]) + arr_c = np.zeros(seq_shape[0]) + arr_g = np.zeros(seq_shape[0]) + arr_t = np.zeros(seq_shape[0]) + delta_pred = original_prediction[:,class_no] - prediction_mutagenesis_X[:,class_no] + for i,mut in enumerate(mutagenesis_X["ids"]): + if mut.endswith("A"): + arr_a[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("C"): + arr_c[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("G"): + arr_g[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("T"): + arr_t[int(mut.split("_")[0])]=delta_pred[i] + + arr_a[arr_a == 0] = None + arr_c[arr_c == 0] = None + arr_g[arr_g == 0] = None + arr_t[arr_t == 0] = None + + ax = fig.add_subplot(ntrack, 1, track_no) + ax.set_ylabel('In silico\nMutagenesis') + ax.scatter(range(seq_shape[0]), -1*arr_a, label='A', color='green') + ax.scatter(range(seq_shape[0]), -1*arr_c, label='C', color='blue') + ax.scatter(range(seq_shape[0]), -1*arr_g, label='G', color='orange') + ax.scatter(range(seq_shape[0]), -1*arr_t, label='T', color='red') + ax.legend() + ax.axhline(y=0, linestyle='--', color='gray') + ax.set_xlim((0, seq_shape[0])) + _ = ax.set_xticks(np.arange(0, seq_shape[0]+1, 10)) + + return ax + + +def plot_deepexplainer_givenax_withrc(explainer, fig, ntrack, track_no, seq_onehot, class_no): + class_no = class_no - 1 + shap_values_, indexes_ = explainer.shap_values([seq_onehot,seq_onehot[:,::-1,::-1]], + output_rank_order=str(class_no), + ranked_outputs=1, + check_additivity=False) + forward_ = shap_values_[0][0][0]*seq_onehot[0] + reverse_ = (shap_values_[0][1][0]*seq_onehot[:,::-1,::-1][0])[::-1,::-1] + _, ax1 = plot_weights((forward_+reverse_)/2, + fig, ntrack, 1, track_no, + title="Topic_" + str(class_no+1), subticks_frequency=10, ylab="DeepExplainer") + return ax1 + + +def plot_mutagenesis_givenax_fast_withrc(model, fig, ntrack, track_no, seq_onehot, class_no): + + mutagenesis_X = create_saturation_mutagenesis_x(seq_onehot) + prediction_mutagenesis_X = model.predict([mutagenesis_X["X"],mutagenesis_X["X"][:,::-1,::-1]]) + original_prediction = model.predict([seq_onehot,seq_onehot[:,::-1,::-1]]) + class_no = class_no-1 + seq_shape = (seq_onehot.shape[1],seq_onehot.shape[2]) + + arr_a = np.zeros(seq_shape[0]) + arr_c = np.zeros(seq_shape[0]) + arr_g = np.zeros(seq_shape[0]) + arr_t = np.zeros(seq_shape[0]) + delta_pred = original_prediction[:,class_no] - prediction_mutagenesis_X[:,class_no] + for i,mut in enumerate(mutagenesis_X["ids"]): + if mut.endswith("A"): + arr_a[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("C"): + arr_c[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("G"): + arr_g[int(mut.split("_")[0])]=delta_pred[i] + if mut.endswith("T"): + arr_t[int(mut.split("_")[0])]=delta_pred[i] + + arr_a[arr_a == 0] = None + arr_c[arr_c == 0] = None + arr_g[arr_g == 0] = None + arr_t[arr_t == 0] = None + + ax = fig.add_subplot(ntrack, 1, track_no) + ax.set_ylabel('In silico\nMutagenesis\nTopic_'+str(class_no+1)) + ax.set_title("Topic_" + str(class_no+1)) + ax.scatter(range(seq_shape[0]), -1*arr_a, label='A', color='green') + ax.scatter(range(seq_shape[0]), -1*arr_c, label='C', color='blue') + ax.scatter(range(seq_shape[0]), -1*arr_g, label='G', color='orange') + ax.scatter(range(seq_shape[0]), -1*arr_t, label='T', color='red') + ax.legend() + ax.axhline(y=0, linestyle='--', color='gray') + ax.set_xlim((0, seq_shape[0])) + _ = ax.set_xticks(np.arange(0, seq_shape[0]+1, 10)) + + return ax + + +def insilico_evolution(regions, model, class_no, n_mutation, rc=False): + #from scipy.stats import zscore + nuc_to_onehot = {"A":[1, 0, 0, 0],"C":[0, 1, 0, 0],"G":[0, 0, 1, 0],"T":[0, 0, 0, 1]} + mutation_pred = [] + mutation_loc = [] + print("Sequence index:",end=" ") + for id_ in range(len(regions)): + start_x = np.copy(regions[id_:id_+1]) + pred = [] + mut = [] + for i in range(n_mutation): + mutagenesis_X = create_saturation_mutagenesis_x(start_x) + if rc: + prediction_mutagenesis_X = model.predict([mutagenesis_X["X"],mutagenesis_X["X"][:,::-1,::-1]]) + original_prediction = model.predict([start_x,start_x[:,::-1,::-1]]) + else: + prediction_mutagenesis_X = model.predict(mutagenesis_X["X"]) + original_prediction = model.predict(start_x) + ## To use max z-score + # next_one = mutagenesis_X["ids"][np.argmax(zscore(prediction_mutagenesis_X-original_prediction,axis=1)[:,class_no-1])] + ## To use max score + next_one = mutagenesis_X["ids"][np.argmax(prediction_mutagenesis_X[:,class_no-1]-original_prediction[:,class_no-1])] + pred.append(original_prediction) + mut.append(next_one) + start_x[0][int(next_one.split("_")[0]),:] = np.array(nuc_to_onehot[next_one.split("_")[1]], dtype='int8') + if rc: + original_prediction = model.predict([start_x,start_x[:,::-1,::-1]]) + else: + original_prediction = model.predict(start_x) + pred.append(original_prediction) + mutation_pred.append(pred) + mutation_loc.append(mut) + print(id_,end=",") + mutation_pred = np.array(mutation_pred).squeeze() + mutation_loc = np.array(mutation_loc) + return mutation_pred, mutation_loc + + +def random_drift(regions, model, class_no, n_mutation, rc=False): + #from scipy.stats import zscore + nuc_to_onehot = {"A":[1, 0, 0, 0],"C":[0, 1, 0, 0],"G":[0, 0, 1, 0],"T":[0, 0, 0, 1]} + mutation_pred = [] + mutation_loc = [] + print("Sequence index:",end=" ") + for id_ in range(len(regions)): + start_x = np.copy(regions[id_:id_+1]) + pred = [] + mut = [] + for i in range(n_mutation): + mutagenesis_X = create_saturation_mutagenesis_x(start_x) + if rc: + #prediction_mutagenesis_X = model.predict([mutagenesis_X["X"],mutagenesis_X["X"][:,::-1,::-1]]) + original_prediction = model.predict([start_x,start_x[:,::-1,::-1]]) + else: + #prediction_mutagenesis_X = model.predict(mutagenesis_X["X"]) + original_prediction = model.predict(start_x) + next_one = mutagenesis_X["ids"][np.random.choice(1500,1)[0]] + pred.append(original_prediction) + mut.append(next_one) + start_x[0][int(next_one.split("_")[0]),:] = np.array(nuc_to_onehot[next_one.split("_")[1]], dtype='int8') + if rc: + original_prediction = model.predict([start_x,start_x[:,::-1,::-1]]) + else: + original_prediction = model.predict(start_x) + pred.append(original_prediction) + mutation_pred.append(pred) + mutation_loc.append(mut) + print(id_,end=",") + mutation_pred = np.array(mutation_pred).squeeze() + mutation_loc = np.array(mutation_loc) + return mutation_pred, mutation_loc + + +def random_sequence_by_shuffling(seq_to_shuffle, number_of_random_regions): + seq_to_shuffle_onehot = one_hot_encode_along_row_axis(seq_to_shuffle) + shuffled_regions = [] + for i in range(number_of_random_regions): + np.random.shuffle(seq_to_shuffle_onehot[0]) + shuffled_regions.append(np.copy(seq_to_shuffle_onehot[0])) + shuffled_regions = np.array(shuffled_regions) + return shuffled_regions + + +def random_sequence(seq_len, number_of_random_regions): + random_regions = [] + for k in range(number_of_random_regions): + seq = [] + for i in range(seq_len): + seq.append(np.random.choice(["A","C","G","T"])) + random_regions.append(one_hot_encode_along_row_axis("".join(seq)).squeeze()) + random_regions = np.array(random_regions) + return random_regions + + +def random_sequence_gc_adjusted(seq_len, number_of_random_regions, path_to_use_GC_content): + regions_to_use_GC = prepare_data(path_to_use_GC_content) + ACGT_dist = np.sum(regions_to_use_GC[0],axis=0)/len(regions_to_use_GC[0]) + random_regions = [] + for k in range(number_of_random_regions): + seq = [] + for i in range(seq_len): + seq.append(np.random.choice(["A","C","G","T"],p=list(ACGT_dist[i]))) + random_regions.append(one_hot_encode_along_row_axis("".join(seq)).squeeze()) + random_regions = np.array(random_regions) + return random_regions + + +def plot_deepexplainer_givenax(explainer, fig, ntrack, track_no, seq_onehot): + shap_values_ = explainer.shap_values(seq_onehot,ranked_outputs=1,check_additivity=False) + _, ax1 = plot_weights(shap_values_[0]*seq_onehot, + fig, ntrack, 1, track_no, + title="", subticks_frequency=10, ylab="") + return ax1 + + +def load_model(path_json, path_hdf5): + model_json_file = open(path_json) + model_json = model_json_file.read() + model = tf.keras.models.model_from_json(model_json) + model.load_weights(path_hdf5) + return model + + +def add_pattern_to_best_location(pattern, regions, model, class_no): + pattern_added_regions = np.zeros(regions.shape,dtype="int") + pattern_locations = np.zeros(regions.shape[0],dtype="int") + print("Sequence index:",end=" ") + for r, region in enumerate(regions): + tmp_array = np.zeros((regions.shape[1]-pattern.shape[1]+1,regions.shape[1],regions.shape[2])) + for nt in range(tmp_array.shape[0]): + tmp_array[nt] = np.copy(region) + tmp_array[nt,nt:nt+pattern.shape[1],:] = pattern[0] + prediction = model.predict(tmp_array)[:,class_no-1] + pattern_locations[r] = np.argmax(prediction) + pattern_added_regions[r] = tmp_array[pattern_locations[r]] + print(r,end=",") + print("") + return {"regions":pattern_added_regions, "locations":pattern_locations} + + +def plot_a(ax, base, left_edge, height, color): + a_polygon_coords = [ + np.array([ + [0.0, 0.0], + [0.5, 1.0], + [0.5, 0.8], + [0.2, 0.0], + ]), + np.array([ + [1.0, 0.0], + [0.5, 1.0], + [0.5, 0.8], + [0.8, 0.0], + ]), + np.array([ + [0.225, 0.45], + [0.775, 0.45], + [0.85, 0.3], + [0.15, 0.3], + ]) + ] + for polygon_coords in a_polygon_coords: + ax.add_patch(matplotlib.patches.Polygon((np.array([1, height])[None, :] * polygon_coords + + np.array([left_edge, base])[None, :]), + facecolor=color, edgecolor=color)) + + +def plot_c(ax, base, left_edge, height, color): + ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge + 0.65, base + 0.5 * height], width=1.3, height=height, + facecolor=color, edgecolor=color)) + ax.add_patch( + matplotlib.patches.Ellipse(xy=[left_edge + 0.65, base + 0.5 * height], width=0.7 * 1.3, height=0.7 * height, + facecolor='white', edgecolor='white')) + ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge + 1, base], width=1.0, height=height, + facecolor='white', edgecolor='white', fill=True)) + + +def plot_g(ax, base, left_edge, height, color): + ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge + 0.65, base + 0.5 * height], width=1.3, height=height, + facecolor=color, edgecolor=color)) + ax.add_patch( + matplotlib.patches.Ellipse(xy=[left_edge + 0.65, base + 0.5 * height], width=0.7 * 1.3, height=0.7 * height, + facecolor='white', edgecolor='white')) + ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge + 1, base], width=1.0, height=height, + facecolor='white', edgecolor='white', fill=True)) + ax.add_patch( + matplotlib.patches.Rectangle(xy=[left_edge + 0.825, base + 0.085 * height], width=0.174, height=0.415 * height, + facecolor=color, edgecolor=color, fill=True)) + ax.add_patch( + matplotlib.patches.Rectangle(xy=[left_edge + 0.625, base + 0.35 * height], width=0.374, height=0.15 * height, + facecolor=color, edgecolor=color, fill=True)) + + +def plot_t(ax, base, left_edge, height, color): + ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge + 0.4, base], + width=0.2, height=height, facecolor=color, edgecolor=color, fill=True)) + ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge, base + 0.8 * height], + width=1.0, height=0.2 * height, facecolor=color, edgecolor=color, + fill=True)) + + +default_colors = {0: 'green', 1: 'blue', 2: 'orange', 3: 'red'} +default_plot_funcs = {0: plot_a, 1: plot_c, 2: plot_g, 3: plot_t} + + +def plot_weights_given_ax(ax, array, + height_padding_factor, + length_padding, + subticks_frequency, + highlight, + colors=default_colors, + plot_funcs=default_plot_funcs): + if len(array.shape) == 3: + array = np.squeeze(array) + assert len(array.shape) == 2, array.shape + if array.shape[0] == 4 and array.shape[1] != 4: + array = array.transpose(1, 0) + assert array.shape[1] == 4 + max_pos_height = 0.0 + min_neg_height = 0.0 + heights_at_positions = [] + depths_at_positions = [] + for i in range(array.shape[0]): + acgt_vals = sorted(enumerate(array[i, :]), key=lambda x: abs(x[1])) + positive_height_so_far = 0.0 + negative_height_so_far = 0.0 + for letter in acgt_vals: + plot_func = plot_funcs[letter[0]] + color = colors[letter[0]] + if letter[1] > 0: + height_so_far = positive_height_so_far + positive_height_so_far += letter[1] + else: + height_so_far = negative_height_so_far + negative_height_so_far += letter[1] + plot_func(ax=ax, base=height_so_far, left_edge=i, height=letter[1], color=color) + max_pos_height = max(max_pos_height, positive_height_so_far) + min_neg_height = min(min_neg_height, negative_height_so_far) + heights_at_positions.append(positive_height_so_far) + depths_at_positions.append(negative_height_so_far) + + for color in highlight: + for start_pos, end_pos in highlight[color]: + assert start_pos >= 0.0 and end_pos <= array.shape[0] + min_depth = np.min(depths_at_positions[start_pos:end_pos]) + max_height = np.max(heights_at_positions[start_pos:end_pos]) + ax.add_patch( + matplotlib.patches.Rectangle(xy=[start_pos, min_depth], + width=end_pos - start_pos, + height=max_height - min_depth, + edgecolor=color, fill=False)) + + ax.set_xlim(-length_padding, array.shape[0] + length_padding) + ax.xaxis.set_ticks(np.arange(0.0, array.shape[0] + 1, subticks_frequency)) + height_padding = max(abs(min_neg_height) * (height_padding_factor), + abs(max_pos_height) * (height_padding_factor)) + ax.set_ylim(min_neg_height - height_padding, max_pos_height + height_padding) + return ax + + +def plot_weights(array, fig, n, n1, n2, title='', ylab='', + height_padding_factor=0.2, + length_padding=1.0, + subticks_frequency=20, + colors=default_colors, + plot_funcs=default_plot_funcs, + highlight={}): + ax = fig.add_subplot(n, n1, n2) + ax.set_title(title) + ax.set_ylabel(ylab) + y = plot_weights_given_ax(ax=ax, array=array, + height_padding_factor=height_padding_factor, + length_padding=length_padding, + subticks_frequency=subticks_frequency, + colors=colors, + plot_funcs=plot_funcs, + highlight=highlight) + return fig, ax