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Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool
Author(s) -
Raymond K. Auerbach,
Bin Chen,
Atul J. Butte
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt316
Subject(s) - encode , scripting language , javascript , leverage (statistics) , computer science , gene , world wide web , transcription (linguistics) , computational biology , biology , genetics , operating system , artificial intelligence , linguistics , philosophy
Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses.

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