Literature DB >> 23424137

ChIPModule: systematic discovery of transcription factors and their cofactors from ChIP-seq data.

Jun Ding1, Xiaohui Cai, Ying Wang, Haiyan Hu, Xiaoman Li.   

Abstract

We have developed a novel approach called ChIPModule to systematically discover transcription factors and their cofactors from ChIP-seq data. Given a ChIP-seq dataset and the binding patterns of a large number of transcription factors, ChIPModule can efficiently identify groups of transcription factors, whose binding sites significantly co-occur in the ChIP-seq peak regions. By testing ChIPModule on simulated data and experimental data, we have shown that ChIPModule identifies known cofactors of transcription factors, and predicts new cofactors that are supported by literature. ChIPModule provides a useful tool for studying gene transcriptional regulation.

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Year:  2013        PMID: 23424137

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  11 in total

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9.  SIOMICS: a novel approach for systematic identification of motifs in ChIP-seq data.

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Journal:  Nucleic Acids Res       Date:  2013-12-09       Impact factor: 16.971

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