title: SIOMICS: a novel approach for systematic identification of motifs in ChIP-seq data.
abstract: The identification of transcription factor binding motifs is important for the study of gene transcriptional regulation. The chromatin immunoprecipitation (ChIP), followed by massive parallel sequencing (ChIP-seq) experiments, provides an unprecedented opportunity to discover binding motifs. Computational methods have been developed to identify motifs from ChIP-seq data, while at the same time encountering several problems. For example, existing methods are often not scalable to the large number of sequences obtained from ChIP-seq peak regions. Some methods heavily rely on well-annotated motifs even though the number of known motifs is limited. To simplify the problem, de novo motif discovery methods often neglect underrepresented motifs in ChIP-seq peak regions. To address these issues, we developed a novel approach called SIOMICS to de novo discover motifs from ChIP-seq data. Tested on 13 ChIP-seq data sets, SIOMICS identified motifs of many known and new cofactors. Tested on 13 simulated random data sets, SIOMICS discovered no motif in any data set. Compared with two recently developed methods for motif discovery, SIOMICS shows advantages in terms of speed, the number of known cofactor motifs predicted in experimental data sets and the number of false motifs predicted in random data sets. The SIOMICS software is freely available at http://eecs.ucf.edu/∼xiaoman/SIOMICS/SIOMICS.html.
authors: Department of Electric Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA and Burnett School of Biomedical Science, University of Central Florida, Orlando, FL 32816, USA.
authors: Jun
authors: J
authors: Ding
authors: Haiyan
authors: H
authors: Hu
authors: Xiaoman
authors: X
authors: Li
mesh_terms: D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D019295:Computational Biology / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing; D059372:Nucleotide Motifs; D050436:Regulatory Elements, Transcriptional; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors