GPEC

Finding genes associated with a disease is an important issue in the biomedical area and many gene prioritization methods have been proposed for this goal. Among these, network-based approaches are recently proposed and outperformed functional annotation-based ones. Here, we introduce a novel Cytoscape plug-in, GPEC, to help identify putative genes likely to be associated with specific diseases or pathways. In the plug-in, gene prioritization is performed through a random walk with restart algorithm, a state-of-the art network-based method, along with a gene/protein relationship network. The plug-in also allows users efficiently collect biomedical evidence for highly ranked candidate genes. A set of known genes, candidate genes and a gene/protein relationship network can be provided in a flexible way.

► GPEC is based on random walk with restart algorithm, a state-of-the art algorithm.

► GPEC can prioritize candidate genes of a disease or pathway.

► GPEC can collect effectively biomedical evidence for putative genes.

► GPEC provide a flexible input of known/candidate genes and network of genes/proteins.

► GPEC is user-friendly with various miscellaneous functions.

Citation:

Le, D.-H. and Y.-K. Kwon, GPEC: A Cytoscape plug-in for random walk-based gene prioritization and biomedical evidence collection. Computational Biology and Chemistry, 2012. 37(0): p. 17-23.