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An improved node mapping algorithm for the cophylogeny reconstruction problem

Citation

Drinkwater, B and Charleston, MA, An improved node mapping algorithm for the cophylogeny reconstruction problem, Coevolution: An Open Access Journal, 2, (1) pp. 1-17. ISSN 2325-6214 (2014) [Refereed Article]


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Copyright Statement

2014 The Author(s) Licensed under Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/

DOI: doi:10.1080/23256214.2014.906070

Abstract

The cophylogeny reconstruction problem is central in the inference of ancient relationships among ecologically linked groups of organisms. Although it is known to be NP-Complete, there have been several heuristics proposed that often find good solutions. One such approach is to fix the order of the internal nodes of the host phylogeny and use dynamic programming to recover an optimal reconstruction in polynomial time. A meta-heuristic framework is then leveraged to iterate over the factorial set of fixed node orderings. The original solution used a technique known as node mapping, taking and was designed to handle phylogenetic networks. There has since been a number of implementations for this problem which use specific properties of phylogenetic trees to reduce their running time. In this paper, we introduce a set of new optimisation techniques to achieve a running time improvement matching these cubic time algorithms, while using node mapping, and discuss how these newly proposed optimisation techniques may lead to an improvement in the generalised case of phylogenetic networks and provide valuable insights into how to construct an optimized algorithm for handling evolutionary systems with widespread parasites.

Item Details

Item Type:Refereed Article
Keywords:cophylogeny, bioinformatics, dynamic programming, NP-Complete
Research Division:Information and Computing Sciences
Research Group:Computation Theory and Mathematics
Research Field:Analysis of Algorithms and Complexity
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Biological Sciences
UTAS Author:Charleston, MA (Associate Professor Michael Charleston)
ID Code:100228
Year Published:2014
Deposited By:Mathematics and Physics
Deposited On:2015-05-07
Last Modified:2015-08-21
Downloads:371 View Download Statistics

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