Exploring transcriptional modules through integrative gene clustering guided by transcription factor binding information

Ting Gong, Jianhua Xuan, Rebecca B. Riggins, Yue Wang, Eric P. Hoffman, Robert Clarke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Cluster analysis aims to infer regulatory modules or biological functions by grouping the genes with similar patterns. However, clustering results often fail to show strong biological relevance to underlying transcriptional modules. In this paper, we present a computational approach, namely integrative gene clustering guided by motif information, to identify condition-specific transcriptional modules. Specifically, the proposed approach is designed to discover the co-regulated genes from co-expressed genes by integrating ChIP-on-chip binding site (or motif) information and gene expression data. A statistical significance analysis procedure is performed to associate a set of significant motifs with each co-expressed gene cluster. An information-theoretic technique based on the entropy of the motif information is further developed to select an optimal balance point between expression patterns and motif patterns. The experimental results from simulated Saccharomyces cerevisiae data demonstrated that our approach can successfully uncover specific biological processes that are evidently regulated by one or more transcription factors.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Pages191-197
Number of pages7
StatePublished - 2008
Externally publishedYes
Event2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 - Las Vegas, NV, United States
Duration: Jul 14 2008Jul 17 2008

Publication series

NameProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008

Other

Other2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
CountryUnited States
CityLas Vegas, NV
Period7/14/087/17/08

Keywords

  • Binding motifs
  • Gene clustering
  • Gene regulatory networks
  • Microarray data analysis
  • Transcription modules

Fingerprint Dive into the research topics of 'Exploring transcriptional modules through integrative gene clustering guided by transcription factor binding information'. Together they form a unique fingerprint.

Cite this