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TurboTree: a fast algorithm for minimal trees.

D Penny1, M D Hendy

  • 1Department of Botany and Zoology, Massey University, Palmerston North, New Zealand.

Computer Applications in the Biosciences : CABIOS
|September 1, 1987
PubMed
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This study introduces a novel branch and bound algorithm for efficiently finding minimal length trees in biological data. The new method rapidly identifies the optimal tree by adding characters, outperforming previous approaches.

Area of Science:

  • Computational Biology
  • Phylogenetics
  • Algorithm Development

Background:

  • Phylogenetic tree reconstruction is crucial for understanding evolutionary relationships.
  • Existing branch and bound methods for tree searching can be computationally intensive.
  • The number of possible trees grows exponentially with the number of taxa.

Purpose of the Study:

  • To develop a faster and more efficient branch and bound algorithm for minimal length tree searching.
  • To present a novel approach that adds characters incrementally instead of taxa.

Main Methods:

  • A new branch and bound algorithm was designed and implemented.
  • The algorithm iteratively adds characters to build minimal length trees.
  • A worked example involved 33 characters and 15 taxa.

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Main Results:

  • The algorithm successfully identified the minimal length tree.
  • The program found the minimal tree in under 5 minutes on an IBM PC.
  • This represents a significant speed improvement for large datasets.

Conclusions:

  • The novel branch and bound algorithm offers a rapid and efficient solution for phylogenetic tree reconstruction.
  • This character-based approach overcomes limitations of previous taxon-based methods.
  • The algorithm is available for use in biological data analysis.