Inferring regulatory networks

Abstract

The discovery of regulatory networks is an important aspect in the post genomic research. The process requires integrated efforts of experimental and computational strategies by employing the systems biology approach. This review summarizes some of the major themes in computational inference of regulatory networks based on gene expression and other data sources, including transcriptional module identification, network topology inference, and network analysis. Popular solutions to each of these problems and their relative merits are discussed.