Bagged Biclustering for Microarray Data

Authors:
Blaise Hanczar;Mohamed Nadif
Affiliations:
LIPADE, University Paris Descartes;LIPADE, University Paris Descartes
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

Citing 5
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Abstract

One of the major tools of transcriptomics is the biclustering that simultaneously constructs a partition of both examples and genes. 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 quality of these biclustering methods by using an ensemble approach. Our bagged biclustering method generates a collection of biclusters using the bootstrap samples of the original data and aggregate them into new biclusters. Our method improve the performance of biclustering on artificial and real datasets.