Statistical methods in integrative analysis for gene regulatory modules.

We propose a suite of statistical methods for inferring a cis-regulatory module, which is a combination of several transcription factors binding in the promoter regions to regulate gene expression. The approach is an integrative analysis that combines information from multiple types of biological data, including genomic DNA sequences, genome-wide location analysis (ChIP-chip experiments), and gene expression microarray. More specifically, we use a hidden Markov model to first predict a cluster of transcription factor binding sites in DNA sequences.