RABBIC: Rank-Based BIClustering algorithm

摘要：

　　Biclustering performs simultaneous clustering on the row and column dimensions of the data matrix, it could discover data modules in the data matrix.Gene module is an important concept in systems biology.In this paper, gene modules are specifically defined as a set of genes whose expression levels share the same linear order on each member of a subset of samples.In order to discover such modules, a novel algorithm, the Rank-Based BIClustering algorithm (RABBIC), is designed and developed.RABBIC, when applied to the real ovarian cancer gene expression data, identifies 93 modules, and25 are biologically significant according to the gene set functional enrichment analysis.This paper deals with the gene expression data from the aspect of rank, which is helpful in reducing the noise of the data.It provides new thoughts for the researches of gene module identification.

关键词： rank biclustering gene module expression data

作者: Linglin Huang Qing Liu Nan Yang Yaping Li Lin Xiao

作者单位: School of Information Renmin University of China Beijing, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 251-254

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）