An ant colony optimization algorithm for phylogenetic estimation under the minimum evolution principle.

ABSTRACT:

Background

Distance matrix methods constitute a major family of phylogenetic estimation methods, and the minimum evolution (ME) principle (aiming at recovering the phylogeny with shortest length) is one of the most commonly used optimality criteria for estimating phylogenetic trees. The major difficulty for its application is that the number of possible phylogenies grows exponentially with the number of taxa analyzed and the minimum evolution principle is known to belong to the NRho- hard class of problems.

Results

In this paper, we introduce an Ant Colony Optimization (ACO) algorithm to estimate phylogenies under the minimum evolution principle. ACO is an optimization technique inspired from the foraging behavior of real ant colonies. This behavior is exploited in artificia

SUBMITTER: Catanzaro D 

PROVIDER: S-EPMC2211314 | biostudies-literature | 2007 Nov

REPOSITORIES: biostudies-literature