Phylogenetics PG_M0008

title:What might Evolutionary Algorithms (EA) and Multi-objective Optimisation (MOO) Contribute to Phylogenetics and the Total Evidence Debate
author:Leon Poladian and Lars S. Jermiin
year:2004
place of publish:
abstract:
Evolutionary relationships among species are usually (i) illustrated
by means of a phylogeny and (ii) inferred by optimising some
measure of fitness, such as the total evolutionary distance between species
(given the tree), the parsimony (number of different assumptions required
to fit the data to the tree), the likelihood of the tree (given an
evolutionary model and a data set) or the posterior probability of the
tree (given an evolutionary model, a data set, and the distribution of
prior probabilities). A large variety of different types of data can and
have been used in reconstructing evolutionary relationships including nucleotide
sequences, anatomical features, metabolic processes, behaviour
or even the words of languages. Difficulties arise when different sources of
evidence provide conflicting information about the inferred ‘best’ tree(s).
The Total Evidence Debate focusses on how to assess, combine, modify
or reject different types of data. We begin with a review of evolutionary
algorithms (EA) used for phylogenetic inference. Then we discuss
whether the population-based searches that are an intrinsic attribute of
EA and multi-objective optimisation (MOO) can provide a powerful new
approach to this area.