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A Simple Planting Technique for Re-establishing Trees Where Frequent Inundation Occurs
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Robinson-Foulds supertrees.

Mukul S Bansal1, J Gordon Burleigh, Oliver Eulenstein

  • 1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.

Algorithms for Molecular Biology : AMB
|February 26, 2010
PubMed
Summary
This summary is machine-generated.

New heuristics efficiently build supertrees using the Robinson-Foulds (RF) distance, retaining more phylogenetic information than other methods. This offers a faster, more accurate approach for constructing large supertrees.

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Area of Science:

  • Phylogenetics
  • Computational Biology
  • Bioinformatics

Background:

  • Supertree methods construct comprehensive phylogenetic trees from smaller, overlapping trees.
  • Robinson-Foulds (RF) distance is a metric for comparing phylogenetic trees.
  • The RF supertree problem aims to find a supertree minimizing RF distance to input trees, preserving maximum clade information.

Purpose of the Study:

  • To develop efficient heuristics for the computationally challenging RF supertree problem.
  • To improve the time complexity of algorithms for SPR and TBR local search in supertree construction.
  • To evaluate the performance of RF supertree heuristics against other methods like MRP and triplet supertrees.

Main Methods:

  • Introduction of efficient, local search-based hill-climbing heuristics for rooted RF supertrees.
  • Development of novel algorithms for SPR and TBR local search with improved time complexity.
  • Implementation and testing of RF supertree heuristics on four supertree datasets.

Main Results:

  • The RF supertree heuristic provided fast supertree estimates across all datasets.
  • RF supertrees retained more information from input trees compared to MRP and triplet supertree methods, as measured by RF distance.
  • The new algorithms improved time complexity for SPR and TBR local search by Theta(n) and Theta(n^2) respectively.

Conclusions:

  • Efficient heuristics for the RF supertree problem enable the estimation of large supertrees by directly optimizing RF distance.
  • This offers a novel, fast, and accurate method for supertree construction.
  • RF supertrees may also be valuable for estimating majority-rule supertrees.