BRNI: Modular analysis of transcriptional regulatory programs.

ABSTRACT:

Background

Transcriptional responses often consist of regulatory modules - sets of genes with a shared expression pattern that are controlled by the same regulatory mechanisms. Previous methods allow dissecting regulatory modules from genomics data, such as expression profiles, protein-DNA binding, and promoter sequences. In cases where physical protein-DNA data are lacking, such methods are essential for the analysis of the underlying regulatory program.

Results

Here, we present a novel approach for the analysis of modular regulatory programs. Our method - Biochemical Regulatory Network Inference (BRNI) - is based on an algorithm that learns from expression data a biochemically-motivated regulatory program. It describes the expression profiles of gene modules consisting of

SUBMITTER: Nachman I 

PROVIDER: S-EPMC2694189 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature