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Solving the motif discovery problem by using Differential Evolution with Pareto Tournaments

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4 Author(s)
Gonzalez-Alvarez, D.L. ; Dept. Technol. of Comput. & Commun., Univ. of Extremadura, Cáceres, Spain ; Vega-Rodriguez, M.A. ; Gomez-Pulido, J.A. ; Sanchez-Perez, J.M.

This paper proposes the use of Differential Evolution with Pareto Tournaments (DEPT) to identify common patterns, motifs, in biological sequences. The work is motivated by two fundamental facts: first, the role that bioinformatics problems are taking in computer engineering in recent years, and second, the limited existence of scientific papers that use evolutionary techniques for solving such problems. Although finding motifs in deoxyribonucleic acid (DNA) sequences is one of the classical sequence analysis problems, it has not yet been resolved in an efficient manner. Using evolutionary algorithms we can get nearly optimal solutions in a reasonable time. The Motif Discovery Problem (MDP) aims to maximize conflicting objectives: support, motif length, and similarity. These objectives imply multiobjective optimization (MOO) to obtain motifs in the most efficient way as possible. Moreover, in this work, we incorporate the hypervolume indicator to measure the quality of the solutions to this problem. As we will see, our results surpass the results obtained by other approaches proposed in the literature.

Published in:

Evolutionary Computation (CEC), 2010 IEEE Congress on

Date of Conference:

18-23 July 2010