Summarizing cellular responses as biological process networks.

ABSTRACT:

Background

Microarray experiments can simultaneously identify thousands of genes that show significant perturbation in expression between two experimental conditions. Response networks, computed through the integration of gene interaction networks with expression perturbation data, may themselves contain tens of thousands of interactions. Gene set enrichment has become standard for summarizing the results of these analyses in terms functionally coherent collections of genes such as biological processes. However, even these methods can yield hundreds of enriched functions that may overlap considerably.

Results

We describe a new technique called Markov chain Monte Carlo Biological Process Networks (MCMC-BPN) capable of reporting a highly non-redundant set of links between proc

SUBMITTER: Lasher CD 

PROVIDER: S-EPMC3751784 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature