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Estimating Bifurcating Consensus Phylogenetic Trees Using Evolutionary Imperialist Competitive Algorithm

Author(s):

Vageehe Nikkhah, Seyed Morteza Babamir* and Seyed Shayar Arab  

Abstract:


One of the important goals of phylogenetic studies is the estimation of species-level phylogeny. A phylogenetic tree is an evolutionary classification of different species of creatures. There are several methods to generate such trees and each method may produce a number of different trees for the species. By choosing same proteins of all species, it is possible that the topology and arrangement of trees would be different. There are methods by which biologists summarize different phylogenetic trees to a tree, called consensus tree. A consensus method deals with the combination of gene trees to estimate a species tree. As the phylogenetic trees grow and their number is increased, estimating a consensus tree based on the species-level phylogenetic trees becomes a challenge. The current study aims at presenting a method based on Imperialist Competitive Algorithm (ICA) to estimate a bifurcating consensus tree for better evolutionary classification of species than other consensus methods. The estimated consensus tree by the ICA had more similarity to the native phylogenetic tree than related methods.

Keywords:

Consensus tree, Phylogenetic Tree, Species level, Imperialist Competitive algorithm

Affiliation:

Department of Computer Engineering, University of Kashan, Kashan, Department of Computer Engineering, University of Kashan, Kashan, Faculty of Bioscience, Tarbiat Modares University, Tehran



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