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. © The Author 2013.
CITATION STYLE
Zhang, Q., & Zhang, Z. D. (2013). SubNet: A Java application for subnetwork extraction. Bioinformatics, 29(19), 2509–2511. https://doi.org/10.1093/bioinformatics/btt430
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