A comparative study on distance methods applied to a multiobjective firefly algorithm for phylogenetic inference

Authors:
Sergio Santander-Jiménez;Miguel A. Vega-Rodríguez
Affiliations:
Department of Technologies of Computers and Communications, University of Extremadura, Caceres, Spain;Department of Technologies of Computers and Communications, University of Extremadura, Caceres, Spain
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

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Abstract

Throughout the years, researchers have reported a wide variety of proposals to infer evolutionary histories from biological data. Recent studies suggested the use of matrices of genetic distances to represent phylogenetic topologies in population-based metaheuristics. A key question that must be addressed is the choice of a particular method to build phylogenies from evolutionary distances. In addition to this, there is a growing need to overcome the problems that arise when different optimality criteria describe conflicting hypotheses about the evolution of the input species. In this paper, we tackle the phylogenetic inference problem by using a multiobjective algorithm with matrix representation inspired by the bioluminescence of fireflies. Our main goal is to study the behaviour of several clustering and neighbor-joining methods applied to infer phylogenies from the distance matrices processed by our algorithm. Experimental results on four real nucleotide data sets point out the advantages and disadvantages of each proposal, in terms of multiobjective performance and processing times.