title: ChIPModule: systematic discovery of transcription factors and their cofactors from ChIP-seq data.
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.
authors: Department of EECS, University of Central Florida, 4000 central Florida Blvd, Orlando, FL 32816, USA. jding@cs.ucf.edu
authors: Jun
authors: J
authors: Ding
authors: Xiaohui
authors: X
authors: Cai
authors: Ying
authors: Y
authors: Wang
authors: Haiyan
authors: H
authors: Hu
authors: Xiaoman
authors: X
authors: Li
mesh_terms: D001665:Binding Sites / Q000235:genetics; D047369:Chromatin Immunoprecipitation / Q000706:statistics & numerical data*; D019295:Computational Biology; D030541:Databases, Genetic / Q000706:statistics & numerical data; D006801:Humans; D017421:Sequence Analysis / Q000706:statistics & numerical data*; D014157:Transcription Factors / Q000235:genetics* / Q000378:metabolism*
chemical_list: D014157:Transcription Factors