A gene selection approach based on clustering for classification tasks in colon cancer

• CASTELLANOS GARZÓN, José Antonio ^[1] ; RAMOS GONZÁLEZ, Juan ^[2]
  1. [1] Universidade de Coimbra

     Universidade de Coimbra

     Coimbra (Sé Nova), Portugal

     
  2. [2] Instituto de Investigación Biomédica de Salamanca

     Instituto de Investigación Biomédica de Salamanca

     Salamanca, España

     
• Localización: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, ISSN-e 2255-2863, Vol. 4, Nº. 3, 2015, págs. 1-10
• Idioma: inglés
• DOI: 10.14201/ADCAIJ201543110
• Enlaces
  • Texto completo
• Resumen

  • 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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