BiHEA: A Hybrid Evolutionary Approach for Microarray Biclustering

  • Cristian Andrés Gallo
  • Jessica Andrea Carballido
  • Ignacio Ponzoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5676)

Abstract

In this paper a new hybrid approach that integrates an evolutionary algorithm with local search for microarray biclustering is presented. The novelty of this proposal is constituted by the incorporation of two mechanisms: the first one avoids loss of good solutions through generations and overcomes the high degree of overlap in the final population; and the other one preserves an adequate level of genotypic diversity. The performance of the memetic strategy was compared with the results of several salient biclustering algorithms over synthetic data with different overlap degrees and noise levels. In this regard, our proposal achieves results that outperform the ones obtained by the referential methods. Finally, a study on real data was performed in order to demonstrate the biological relevance of the results of our approach.

Keywords

gene expression data biclustering evolutionary algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Cristian Andrés Gallo
    • 1
  • Jessica Andrea Carballido
    • 1
  • Ignacio Ponzoni
    • 1
    • 2
  1. 1.Laboratorio de Investigación y Desarrollo en Computación Científica (LIDeCC), Departamento de Ciencias e Ingeniería de la ComputaciónUniversidad Nacional del SurBahía BlancaArgentina
  2. 2.Planta Piloto de Ingeniería Química (PLAPIQUI) - UNS – CONICET, Complejo CRIBABBBahía BlancaArgentina

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