Title
A Novel Approach to Phylogenetic Tree Construction using Stochastic Optimization and Clustering
Document Type
Article
Publication Date
2006
Abstract
Background: The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational biology.
Results: A new phylogenetic tree construction method from a given set of objects (proteins, species, etc.) is presented. As an extension of ant colony optimization, this method proposes an adaptive phylogenetic clustering algorithm based on a digraph to find a tree structure that defines the ancestral relationships among the given objects.
Conclusion: Our phylogenetic tree construction method is tested to compare its results with that of the genetic algorithm (GA). Experimental results show that our algorithm converges much faster and also achieves higher quality than GA.
Recommended Citation
Qin et al.: A novel approach to phylogenetic tree construction using stochastic optimization and clustering. BMC Bioinformatics 2006, 7(Suppl 4):S24. doi: 10.1186/1471-2105-7-S4-S24
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Comments
This article was originally published in the journal BMC Bioinformatics.
© 2006 Qin et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.