期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2012
卷号：1
期号：10
页码：204-208
出版社：Shri Pannalal Research Institute of Technolgy
摘要：This paper presents a quick and very comprehensive tutorial on biclustering for the analysis of gene expression data obtained from microarray experiments. The results obtained from the conventional clustering metho ds to gene expression data are limited by the existence of a number of experimental conditions where the activity of genes is uncorrelated. A similar limitation also exists when clustering of conditions is performed. For this reason, a number of algorithms that perform simultan eous clustering on the row and column dimensions of the gene expression matrix have been proposed to date. This simultaneous clustering, usually called as biclustering, which seeks to find sub- matrices, that is subgroups of genes and subgroups of columns, where the genes exhibit highly correlated activities for every condition. This type of algorithms has also been proposed and used in other fields, such as information retrieval and data mining. In this comprehensive tutorial, we analyze a number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they can find, the patterns of biclusters that are discovered, the methods used to perform the search and the target applications.
关键词：Bicluster; Microarray; Gene ; expression; Data mining
