کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
15181 | 1386 | 2012 | 7 صفحه PDF | دانلود رایگان |
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.
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► 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.
Journal: Computational Biology and Chemistry - Volume 37, April 2012, Pages 17–23