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José Antonio Castellanos Garzón
Department of Computer Engineering, CISUC-ECOS, Faculty of Science and Technology, University of Coimbra
Juan Ramos González
Instituto de Investigación Biomédica de Salamanca (IBSAL)
Vol. 4 No. 3 (2015), Articles, pages 1-10
Accepted: Jun 6, 2016


Gene selection (GS) is an important research area in the analysis of DNA-microarray data, since it involves gene discovery meaningful for a particular target annotation or able to discriminate expression profiles of samples coming from different populations. In this context, a wide number of filter methods have been proposed in the literature to identify subsets of relevant genes in accordance with prefixed targets. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem (GS) remains a challenge. Hence, this paper proposes a novel approach for gene selection by using cluster techniques and filter methods on the found groupings to achieve informative gene subsets. As a result of applying our methodology to Colon cancer data, we have identified the best informative gene subset between several one subsets. According to the above, the reached results have proven the reliability of the approach given in this paper.


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