Title: Discovering maximal size coherent biclusters from gene expression data

Authors: J. Bagyamani, K. Thangavel

Addresses: Department of Computer Science, Government Arts College, Dharmapuri 636 705, Tamil Nadu, India. ' Department of Computer Science, Periyar University, Salem 636 011, Tamil Nadu, India

Abstract: Microarray experiments produce enormous amounts of data, leading to new requirements and challenges in bioinformatics. One of the major challenges in the analysis of such data sets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated with different physiological states. This proposed algorithm includes gene selection and extraction of biclusters from gene expression data using difference matrix. This improved algorithm extracts biclusters with maximum volume that may be left unidentified.

Keywords: biclustering; difference matrix; gene expression data; bioinformatics; microarray data; gene selection.

DOI: 10.1504/IJHTM.2011.042371

International Journal of Healthcare Technology and Management, 2011 Vol.12 No.5/6, pp.405 - 421

Published online: 28 Mar 2015 *

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