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Polynomial supertree methods revisited.

Malte Brinkmeyer1, Thasso Griebel, Sebastian Böcker

  • 1Department of Computer Science, Friedrich Schiller University, 07743 Jena, Germany.

Advances in Bioinformatics
|January 10, 2012
PubMed
Summary
This summary is machine-generated.

Matrix representation with parsimony (MRP) supertree methods are accurate but slow. This study compares MRP against polynomial supertree methods, revealing a trade-off between phylogenetic tree accuracy and computational speed.

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Bioinformatics

Background:

  • Supertree methods construct large phylogenetic trees from smaller, overlapping trees.
  • Matrix representation with parsimony (MRP) is a common but computationally intensive supertree method.

Purpose of the Study:

  • To compare the performance of MRP with several polynomial-time supertree methods.
  • To evaluate both the accuracy and resolution of reconstructed supertrees.

Main Methods:

  • Extensive simulation study.
  • Comparison of MRP, MinCut Supertree, Modified MinCut Supertree, Build-with-distances, PhySIC, PhySIC_IST, and super distance matrix methods.

Main Results:

  • Demonstrated a trade-off between accuracy and running time in supertree construction.
  • Highlighted the advantages and disadvantages of voting- and veto-based supertree approaches.

Conclusions:

  • Findings offer insights into the performance of various supertree algorithms.
  • Results provide recommendations for the development of future supertree methodologies.