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Single- and Multi-objective phylogenetic analysis of primate evolution using a genetic algorithm

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3 Author(s)
V. Jayaswal ; School of Mathematics and Statistics, University of Sydney, NSW, Australia ; L. Poladian ; L. S. Jermiin

Starting with the protein-coding mitochondrial DNA sequences of 20 different species, we reconstruct the primate evolutionary tree using maximum likelihood fitness functions based on a general Markov model of evolution. There is evidence that first and second codon sites in this DNA evolve under different conditions. Thus, we used a combination of a genetic algorithm (GA) and both single and multi-objective optimisation (MOO) to search tree-space for optimal solutions. Various genetic operators were used to search the combinatorial space of evolutionary trees, and a Pareto set was obtained. The implications of the common evolutionary subtrees to all trees found on the Pareto set are that the first codon sites play a far more important role in determining the optimal tree for these data. In the present case, the evolutionary relationship among the simian and other primates considered here remains in question.

Published in:

2007 IEEE Congress on Evolutionary Computation

Date of Conference:

25-28 Sept. 2007