Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

ABSTRACT: Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first

SUBMITTER: Li J 

PROVIDER: S-EPMC4916224 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature