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Related Concept Videos

Phylogenetic Trees03:21

Phylogenetic Trees

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A Practical Guide to Phylogenetics for Nonexperts
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Published on: February 5, 2014

Approximate maximum parsimony and ancestral maximum likelihood.

Noga Alon1, Benny Chor, Fabio Pardi

  • 1Schools of Mathematics and Computer Science,Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel. nogaa@post.tau.ac.il

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|February 13, 2010
PubMed
Summary
This summary is machine-generated.

This study presents approximate solutions for phylogenetic tree reconstruction using maximum parsimony (MP) and ancestral maximum likelihood (AML) criteria. The methods achieve approximation ratios of 16/9 for AML and 1.55 for MP.

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Algorithm Design

Background:

  • Phylogenetic tree reconstruction is crucial for understanding evolutionary relationships.
  • Maximum Parsimony (MP) and Ancestral Maximum Likelihood (AML) are key criteria for inferring evolutionary history.
  • Both MP and AML problems are computationally challenging (NP-hard).

Purpose of the Study:

  • To develop approximate algorithms for MP and AML phylogenetic tree reconstruction.
  • To leverage the connection between phylogenetic problems and the Steiner tree problem.
  • To establish approximation ratios for the proposed methods.

Main Methods:

  • Formulating phylogenetic tree reconstruction as Steiner tree problems using specific distance metrics.
  • Characterizing Steiner trees for a small number of leaves.
  • Applying existing Steiner tree approximation algorithms.

Main Results:

  • A 16/9 approximation ratio was achieved for the ancestral maximum likelihood (AML) problem.
  • An asymptotic approximation ratio of 1.55 was obtained for the maximum parsimony (MP) problem.
  • The Steiner tree formulation provides a novel approach to approximate phylogenetic inference.

Conclusions:

  • The Steiner tree approach offers efficient approximate solutions for NP-hard phylogenetic problems.
  • This work provides theoretical guarantees on the quality of the approximations for MP and AML.
  • The findings facilitate more scalable phylogenetic analyses.