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The Effect of Natural Selection on Phylogeny Reconstruction Algorithms
Dehua Hang1, Charles Ofria1, Thomas M. Schmidt2, and Eric Torng1
1Department of Computer Science & Engineering
Michigan State University,
East Lansing, MI 48824 USA
2Department of Microbiology and Molecular Genetics
Michigan State University,
East Lansing, MI 48824 USA
{hangdehu,ofria,tschmidt,torng}@msu.edu
Abstract. We study the effect of natural selection on the performance of phylogeny reconstruction algorithms using Avida, a software platform that maintains a population of digital organisms (self-replicating computer programs) that evolve subject to natural selection, mutation, and drift. We compare the performance of neighbor-joining and maximum parsimony algorithms on these Avida populations to the performance of the same algorithms on randomly generated data that evolve subject only to mutation and drift. Our results show that natural selection has several specific effects on the sequences of the resulting populations, and that these effects lead to improved performance for neighbor-joining and maximum parsimony in some settings. We then show that the effects of natural selection can be partially achieved by using a non-uniform probability distribution for the location of mutations in randomly generated genomes.
LNCS 2723, p. 13 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003