A new linear-time heuristic algorithm for computing the parsimony score of phylogenetic networks: theoretical bounds and empirical performance

  • Authors:
  • Guohua Jin;Luay Nakhleh;Sagi Snir;Tamir Tuller

  • Affiliations:
  • Department of Computer Science, Rice University, Houston, TX;Department of Computer Science, Rice University, Houston, TX;Department of Mathematics, University of California, Berkeley, CA;School of Computer Science, Tel Aviv University, Tel Aviv, Israel

  • Venue:
  • ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
  • Year:
  • 2007

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Abstract

Phylogenies play a major role in representing the interrelationships among biological entities. Many methods for reconstructing and studying such phylogenies have been proposed, almost all of which assume that the underlying history of a given set of species can be represented by a binary tree. Although many biological processes can be effectively modeled and summarized in this fashion, others cannot: recombination, hybrid speciation, and horizontal gene transfer result in networks, rather than trees, of relationships. In a series of papers, we have extended the maximum parsimony (MP) criterion to phylogenetic networks, demonstrated its appropriateness, and established the intractability of the problem of scoring the parsimony of a phylogenetic network. In this work we show the hardness of approximation for the general case of the problem, devise a very fast (linear-time) heuristic algorithm for it, and implement it on simulated as well as biological data.