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Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
Phylogenetic Trees03:21

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

A parameter-adaptive dynamic programming approach for inferring cophylogenies.

Daniel Merkle1, Martin Middendorf, Nicolas Wieseke

  • 1Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark. daniel@imada.sdu.dk

BMC Bioinformatics
|February 4, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces CoRe-PA, a novel tool for inferring coevolutionary histories. It uses a parameter-adaptive approach, eliminating the need for predefined costs for events like cospeciations and duplications.

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Area of Science:

  • Evolutionary biology
  • Computational biology
  • Phylogenetics

Background:

  • Coevolutionary systems, such as hosts and parasites, are crucial models for evolutionary studies.
  • Inferring coevolutionary history relies on analyzing phylogenies and modeling evolutionary events.
  • Traditional methods assign costs to events to find a minimal cost reconstruction of common history.

Purpose of the Study:

  • Introduce CoRe-PA, a new algorithm and tool for inferring coevolutionary histories.
  • Develop a parameter-adaptive approach for coevolutionary reconciliation analyses.
  • Address limitations of existing methods that require pre-assigned costs for evolutionary events.

Main Methods:

  • Utilizes an event-based concept for reconciliation, considering events like cospeciations, sortings, duplications, and host switches.
  • Employs a novel parameter-adaptive approach, removing the need for advance cost assignments to coevolutionary events.
  • Evaluates performance using well-studied biological coevolutionary systems.

Main Results:

  • Presents CoRe-PA, a tool capable of inferring the common history of coevolutionary systems.
  • Demonstrates the effectiveness of the parameter-adaptive approach in coevolutionary reconciliation.
  • Shows practical application of CoRe-PA on existing biological datasets.

Conclusions:

  • CoRe-PA offers a significant advancement for coevolutionary history inference.
  • The parameter-adaptive method is particularly useful when precise cost assignments for events are challenging or impossible.
  • CoRe-PA provides a valuable tool for researchers studying host-parasite or other coevolving systems.