On Biclustering of Gene Expression Data

摘要

Microarray technology enables the monitoring of the expression patterns of a huge number of genes acrossndifferent experimental conditions or time points simultaneously. Biclustering of microarray data is an important techniquento discover a group of genes that are co-regulated in a subset of experimental conditions. Traditional clustering algorithmsnfind groups of genes/conditions over the complete feature space. Therefore they may fail to discover the local patternsnwhere a subset of genes has similar behaviour over a subset of conditions. Biclustering algorithms aim to discover suchnlocal patterns from the gene expression matrix, thus can be thought as simultaneous clustering of genes and conditions. Innrecent years, a large number of biclustering algorithms have been proposed in literature. In this article, a study has beennmade on various issues regarding the biclustering problem along with a comprehensive survey on available biclusteringnalgorithms. Moreover, a survey on freely available biclustering software is also made.