A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony

Authors:
Jean-Michel Richer;Adrien Goëffon;Jin-Kao Hao
Affiliations:
University of Angers, LERIA, Anger Cedex 01, France 49045;LaBRI (UMR 5800) Université de Bordeaux, Talence Cedex, France 33405;University of Angers, LERIA, Anger Cedex 01, France 49045
Venue:
EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Year:
2009

Citing 3
Cited 1

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Heuristics for the Phylogeny Problem

Journal of Heuristics
Progressive Tree Neighborhood Applied to the Maximum Parsimony Problem

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

Power law-based local search in differential evolution

International Journal of Computational Intelligence Studies

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Abstract

The Maximum Parsimony problem aims at reconstructing a phylogenetic tree from DNA, RNA or protein sequences while minimizing the number of evolutionary changes. Much work has been devoted by the research community to solve this NP-complete problem and many algorithms and techniques have been devised in order to find high quality solutions with reasonable computational resources. In this paper we present a memetic algorithm (implemented in the software Hydra) which is based on an integration of an effective local search operator with a specific topological tree crossover operator. We report computational results of Hydra on a set of 12 benchmark instances from the literature and demonstrate its effectiveness with respect to one of the most powerful software (TNT). We also study the behavior of the algorithm with respect to some fundamental ingredients.