Incremental wrapper-based gene selection from microarray data for cancer classification

Authors:
Roberto Ruiz;José C. Riquelme;Jesús S. Aguilar-Ruiz
Affiliations:
Department of Computer Science, University of Seville, Avda. Reina Mercedes s/n. 41012 Seville, Spain;Department of Computer Science, University of Seville, Avda. Reina Mercedes s/n. 41012 Seville, Spain;Polytechnic, Pablo de Olavide University, Ctra. Utrera, km 1, 41013 Seville, Spain
Venue:
Pattern Recognition
Year:
2006

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Abstract

Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to select relevant gene subsets in order to further use them for the classification task. Our method is based on the statistical significance of adding a gene from a ranked-list to the final subset. The efficiency and effectiveness of our technique is demonstrated through extensive comparisons with other representative heuristics. Our approach shows an excellent performance, not only at identifying relevant genes, but also with respect to the computational cost.