Using the bagging approach for biclustering of gene expression data

Authors:
B. Hanczar;M. Nadif
Affiliations:
LIPADE, Université Paris Descartes, 45 rue des Saints Pères, 75006 Paris, France;LIPADE, Université Paris Descartes, 45 rue des Saints Pères, 75006 Paris, France
Venue:
Neurocomputing
Year:
2011

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Abstract

Several methods have been proposed for microarray data analysis that enables to identify groups of genes with similar expression profiles only under a subset of examples. We propose to improve the performance of these biclustering methods by adapting the approach of bagging to biclustering problems. The principle consists in generating a set of biclusters and aggregating the results. Our method has been tested with success on both synthetic and real datasets.