Comparisons of Graph-structure Clustering Methods for Gene Expression Data

作     者：Zhuo FANG~1,Lei LIU~(2,4),Jiong YANG~3,Qing-Ming LUO~(1*),and Yi-Xue LI~(2*) ~1 Hubei Bioinformatics and Molecular Imaging Key Laboratory,College of Life Science and Technology, Huazhong University of Science and Technology,Wuhan 430074,China ~2 Shanghai Center for Bioinformatics Technology,Shanghai 200235,China ~3 Department of EECS,Case Western Reserve University,Cleveland 44106,USA ~4 W.M.Keck Center for Comparative and Functional Genomics,University of Illinois at Urbana-Champaign,Urbana 61801,USA 

作者机构：Hubei Bioinformatics and Molecular Imaging Key Laboratory College of Life Science and Technology Huazhong University of Science and TechnologyWuhan 430074 China Shanghai Center for Bioinformatics TechnologyShanghai 200235 China W.M. Keck Center for Comparative and Functional Genomics University of Illinois at Urbana-ChampaignUrbana 61801 USA Department of EECS Case Western Reserve UniversityCleveland 44106 USA 

出 版 物：《Acta Biochimica et Biophysica Sinica》 (生物化学与生物物理学报(英文版))

年 卷 期：2006年第38卷第6期

页      面：379-384页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 071007[理学-遗传学] 

基　　金：国家973计划 上海市科委项目 国家科技攻关计划项目 

主　　题：clustering expression pattern biological function 

摘      要：Although many numerical clustering algorithms have been applied to gene expression dataanalysis,the essential step is still biological interpretation by manual *** correlation betweengenetic co-regulation and affiliation to a common biological process is what biologists ***,weintroduce some clustering algorithms that are based on graph structure constituted by biological *** applying a widely used dataset,we compared the result clusters of two of these algorithms in terms ofthe homogeneity of clusters and coherence of annotation and matching *** results show that theclusters of knowledge-guided analysis are the kernel parts of the clusters of Gene Ontology (GO)-Clustersoftware,which contains the genes that are most expression correlative and most consistent with ***,knowledge-guided analysis seems much more applicable than GO-Cluster in a largerdataset.