Title :
Target Clustering of Genes by Normal Mixture Model in Microarray Analysis
Author_Institution :
Dept. of Data & Inf., Sangji Univ., Wonju
Abstract :
To cluster genes in microarray gene expression data experimented over known classes (conditions), this paper provides a model-based gene cluster method. This method takes the normality for component densities from so called splitting and averaging of class data where the number of components is given, and designs component means by general linear model subject to various linear restrictions in order to induce the targeted clusters that an analyst previously want to discover.
Keywords :
biology computing; data analysis; genetics; pattern clustering; statistical analysis; linear model; microarray gene expression data analysis; normal mixture model; target model-based gene clustering; Analysis of variance; Clustering algorithms; Clustering methods; Gaussian distribution; Gene expression; Information analysis; Information technology; Parameter estimation; Performance analysis; Testing; EM algorithm; Gene; Microarray; Normal mixtures; Target Clustering;
Conference_Titel :
Convergence and Hybrid Information Technology, 2008. ICHIT '08. International Conference on
Conference_Location :
Daejeon
Print_ISBN :
978-0-7695-3328-5
DOI :
10.1109/ICHIT.2008.174
