Obtaining biclusters in microarrays with population-based heuristics

Authors:
Pablo Palacios;David Pelta;Armando Blanco
Affiliations:
Dept. de Ingeniería Electrónica, Sistemas Informáticos y Automática, Universidad de Huelva, Huelva;Depto. de Ciencias de la Computación e I.A., Universidad de Granada, Granada, Spain;Depto. de Ciencias de la Computación e I.A., Universidad de Granada, Granada, Spain
Venue:
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Year:
2006

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Abstract

In this article, we shall analyze the behavior of population-based heuristics for obtaining biclusters from DNA microarray data. More specifically, we shall propose an evolutionary algorithm, an estimation of distribution algorithm, and several memetic algorithms that differ in the local search used. In order to analyze the effectiveness of the proposed algorithms, the freely available yeast microarray dataset has been used. The results obtained have been compared with the algorithm proposed by Cheng and Church. Both in terms of the computation time and the quality of the solutions, the comparison reveals that a standard evolutionary algorithm and the estimation of distribution algorithm offer an efficient alternative for obtaining biclusters.