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Genetic Algorithms and Parallel Processing in Maximum-Likelihood Phylogeny Inference
2002
Molecular biology and evolution
We investigated the usefulness of a parallel genetic algorithm for phylogenetic inference under the maximumlikelihood (ML) optimality criterion. Parallelization was accomplished by assigning each "individual" in the genetic algorithm "population" to a separate processor so that the number of processors used was equal to the size of the evolving population (plus one additional processor for the control of operations). The genetic algorithm incorporated branch-length and topological mutation,
doi:10.1093/oxfordjournals.molbev.a003994
pmid:12270898
fatcat:2egwdqa3pne7vh24zakbc5k234