Detection of gene communities in multi-networks reveals cancer drivers.

ABSTRACT: We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art c

SUBMITTER: Cantini L 

PROVIDER: S-EPMC4671005 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature