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Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

On Biclustering of Gene Expression Data

Author(s): Anirban Mukhopadhyay, Ujjwal Maulik and Sanghamitra Bandyopadhyay

Volume 5, Issue 3, 2010

Page: [204 - 216] Pages: 13

DOI: 10.2174/157489310792006701

Price: $65

Abstract

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

Keywords: Microarray, gene expression, biclustering, bicluster types, biclustering algorithms, biclustering software


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