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Series GSE158683 Query DataSets for GSE158683
Status Public on Oct 09, 2020
Title DeepTFactor, a deep learning-based tool for the identification of transcription factors
Organism Escherichia coli
Experiment type Genome binding/occupancy profiling by high throughput sequencing
Summary We report the development of a deep learning-based tool, DeepTFactor, that predicts whether a protein of question is a transcription factor. DeepTFactor uses a convolutional neural network to extract features of protein sequences. We characterized the genome-wide binding sites of three TFs (i.e., YqhC, YiaU, and YahB), which are predicted by DeepTFactor
 
Overall design Identification of genome-wide bindings for uncharacterized transcription factors in E. coli K-12 MG1655, using ChIP-exo technology
 
Contributor(s) Kim G, Gao Y, Palsson B, Lee S
Citation(s) 33372147
Submission date Sep 28, 2020
Last update date Jan 11, 2021
Contact name Ye Gao
E-mail(s) yeg002@ucsd.edu
Organization name UCSD
Street address 9500 Gilman Dr.
City La Jolla
ZIP/Postal code 92093
Country USA
 
Platforms (1)
GPL18133 Illumina HiSeq 2500 (Escherichia coli)
Samples (6)
GSM4805498 yiaU_1
GSM4805499 yiaU_2
GSM4805500 yqhC_1
Relations
BioProject PRJNA666186
SRA SRP285666

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE158683_RAW.tar 182.5 Mb (http)(custom) TAR (of GFF)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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