Detection of locally over-represented GO terms in protein-protein interaction networks.

ABSTRACT: High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately

SUBMITTER: Lavallee-Adam M 

PROVIDER: S-EPMC4669221 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature