期刊
BRIEFINGS IN BIOINFORMATICS
卷 12, 期 1, 页码 22-32出版社
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbq007
关键词
gene prioritization; candidate gene; disease gene; in silico prediction; review
资金
- Research Council KUL [CoE EF/05/007 SymBioSys]
- Flemish Government [G.0241.04, G.0499.04, G.0232.05, G.0318.05, G.0553.06, G.0302.07, G.0733.09, G.082409, TBM-IOTA3]
- Belgian Federal Science Policy Office [IUAP P6/25]
- European Research Network on System Identification (ERNSI) [FP6-NoE, FP6-IP, FP6-MC-EST, FP6-STREP, FP7-HEALTH]
Finding the most promising genes among large lists of candidate genes has been defined as the gene prioritization problem. It is a recurrent problem in genetics in which genetic conditions are reported to be associated with chromosomal regions. In the last decade, several different computational approaches have been developed to tackle this challenging task. In this study, we review 19 computational solutions for human gene prioritization that are freely accessible as web tools and illustrate their differences. We summarize the various biological problems to which they have been successfully applied. Ultimately, we describe several research directions that could increase the quality and applicability of the tools. In addition we developed a website (http://www.esat.kuleuven.be/gpp) containing detailed information about these and other tools, which is regularly updated. This review and the associated website constitute together a guide to help users select a gene prioritization strategy that suits best their needs.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据