REGNET: mining context-specific human transcription networks using composite genomic information.

ABSTRACT:

Background

Genome-wide expression profiles reflect the transcriptional networks specific to the given cell context. However, most statistical models try to estimate the average connectivity of the networks from a collection of gene expression data, and are unable to characterize the context-specific transcriptional regulations. We propose an approach for mining context-specific transcription networks from a large collection of gene expression fold-change profiles and composite gene-set information.

Results

Using a composite gene-set analysis method, we combine the information of transcription factor binding sites, Gene Ontology or pathway gene sets and gene expression fold-change profiles for a variety of cell conditions. We then collected all the significant patterns and co

SUBMITTER: Chi SM 

PROVIDER: S-EPMC4070555 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature