Systematic Discovery Of Cofactor Motifs From Chip-Seq Data By Siomics

Keywords

ChIP-seq; Cofactor; Motif; SIOMICS; Transcription factor; Transcription factor binding sites

Abstract

Understanding transcriptional regulatory elements and particularly the transcription factor binding sites represents a significant challenge in computational biology. The chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) experiments provide an unprecedented opportunity to study transcription factor binding sites on the genome-wide scale. Here we describe a recently developed tool, SIOMICS, to systematically discover motifs and binding sites of transcription factors and their cofactors from ChIP-seq data. Unlike other tools, SIOMICS explores the co-binding properties of multiple transcription factors in short regions to predict motifs and binding sites. We have previously shown that the original SIOMICS method predicts motifs and binding sites of more cofactors in more accurate and time-effective ways than two popular methods. In this paper, we present the extended SIOMICS method, SIOMICS_Extension, and demonstrate its usage for systematic discovery of cofactor motifs and binding sites. The SIOMICS tool, including SIOMICS and SIOMICS_Extension, are available at http://hulab.ucf.edu/research/projects/SIOMICS/SIOMICS.html.

Publication Date

6-1-2015

Publication Title

Methods

Volume

79

Number of Pages

47-51

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.ymeth.2014.08.006

Socpus ID

84929326504 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84929326504

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