GenRev: exploring functional relevance of genes in molecular networks.
We introduce GenRev, a network-based software package developed to explore the functional relevance of genes generated as an intermediate result from numerous high-throughput technologies. GenRev searches for optimal intermediate nodes (genes) for the connection of input nodes via several algorithms, including the Klein-Ravi algorithm, the limited kWalks algorithm and a heuristic local search algorithm. Gene ranking and graph clustering analyses are integrated into the package. GenRev has the following features. (1) It provides users with great flexibility to define their own networks. (2) Users are allowed to define each gene's importance in a subnetwork search by setting its score. (3) It is standalone and platform independent. (4) It provides an optimization in subnetwork search, which dramatically reduces the running time. GenRev is particularly designed for general use so that users have the flexibility to choose a reference network and define the score of genes. GenRev is freely available at http://bioinfo.mc.vanderbilt.edu/GenRev.html.
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Siyuan
S
Zheng
Zhongming
Z
Zhao
D000465:Algorithms; D019295:Computational Biology; D053263:Gene Regulatory Networks; D057166:High-Throughput Screening Assays; D025941:Protein Interaction Mapping; D012984:Software