| Literature DB >> 23946504 |
Christophe Lemetre1, Quanwei Zhang1, Zhengdong D Zhang.
Abstract
SUMMARY: The extraction of targeted subnetworks is a powerful way to identify functional modules and pathways within complex networks. Here, we present SubNet, a Java-based stand-alone program for extracting subnetworks, given a basal network and a set of selected nodes. Designed with a graphical user-friendly interface, SubNet combines four different extraction methods, which offer the possibility to interrogate a biological network according to the question investigated. Of note, we developed a method based on the highly successful Google PageRank algorithm to extract the subnetwork using the node centrality metric, to which possible node weights of the selected genes can be incorporated. AVAILABILITY: http://www.zdzlab.org/1/subnet.htmlMesh:
Substances:
Year: 2013 PMID: 23946504 PMCID: PMC3777115 DOI: 10.1093/bioinformatics/btt430
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937