title: GPEC: a Cytoscape plug-in for random walk-based gene prioritization and biomedical evidence collection.
abstract: 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.
authors.affiliation: School of Computer Science and Engineering, Water Resources University, 175 Tay Son, Dong Da, Hanoi, Vietnam. hauldhut@mail.ulsan.ac.kr
authors.forename: Duc-Hau
authors.initials: DH
authors.lastname: Le
authors.forename: Yung-Keun
authors.initials: YK
authors.lastname: Kwon
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D030541:Databases, Genetic; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D006801:Humans; D006973:Hypertension / Q000235:genetics; D025941:Protein Interaction Mapping; D011506:Proteins / Q000235:genetics; D012984:Software
chemical_list: D011506:Proteins