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Tree Core Analysis with X-ray Computed Tomography
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Published on: September 22, 2023

Efficient tree searches with available algorithms.

Gonzalo Giribet1

  • 1Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, U.S.A. ggiribet@oeb.harvard.edu

Evolutionary Bioinformatics Online
|May 23, 2009
PubMed
Summary
This summary is machine-generated.

Phylogenetic tree construction using optimality criteria is slow. This review explores algorithms and search strategies, including a new pre-processed searches technique, to improve efficiency for large datasets in phylogenetic inference.

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A Practical Guide to Phylogenetics for Nonexperts
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A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Area of Science:

  • Computational Biology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Phylogenetic methods based on optimality criteria offer logical rigor but are computationally intensive.
  • Traditional tree search methods (e.g., SPR, TBR) are insufficient for large or complex datasets.

Purpose of the Study:

  • To review and clarify algorithms and search strategies for phylogenetic analysis.
  • To enhance the applicability of existing phylogenetic methods for complex datasets.
  • To provide an educational and algorithmic reference for biologists.

Main Methods:

  • Review of existing algorithms and search strategies for phylogenetic inference.
  • Discussion of techniques applicable to parsimony and maximum likelihood methods.
  • Introduction of a novel technique: pre-processed searches for reusing prior phylogenetic results.

Main Results:

  • Identified limitations of traditional tree search methods for large datasets.
  • Demonstrated applicability of discussed techniques to parsimony and maximum likelihood.
  • Proposed pre-processed searches to improve the jumpstarting phylogenetics method.

Conclusions:

  • Optimality-based phylogenetic methods require efficient search strategies for complex, large-scale datasets.
  • The proposed pre-processed searches technique offers a novel approach to enhance phylogenetic analysis efficiency.
  • This work serves as a valuable resource for biologists navigating phylogenetic inference challenges.