Modularized Random Walk with Restart for Candidate Disease Genes Prioritization

摘要：

Identifying disease genes is very important not only for better understanding of gene function and biological process but also for human medical improvement. Many previous methods are based on modular nature of human genetic disease and the similarity between known disease genes and candidate genes. In this paper, we propose the method of Modularized Random Walk with Restart (MRWR) based on the functional module partition and module importance. Genes are prioritized in each functional module and then the gene ranking in each module is fused into a global ranking in the entire network. MRWR is applied to prostate cancer network. It is surprising that twenty-eight out of top fifty ranking genes are confirmed by PDGB or KEGG or literatures. MRWR significantly improves the performance of previous classical algorithms.

关键词： Candidate disease genes prioritization Modularized random walk with restart Functional module partition

作者: Xing Chen Guiying Yan Wei Ren Ji-Bin Qu

作者单位: Academy of Mathematics and Systems Science,CAS,Beijing 100190,China Graduate University of Chinese A Academy of Mathematics and Systems Science,CAS,Beijing 100190,China

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 353-360

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）