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Updated: Aug 31, 2025

A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
Treewidth-based algorithms for the small parsimony problem on networks.
Celine Scornavacca1, Mathias Weller2
1ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France.
This study presents new algorithms for phylogenetic networks, efficiently calculating evolutionary character states. These methods improve upon existing approaches for parsimony scores on networks with low treewidth.
Area of Science:
- Bioinformatics
- Computational Biology
- Phylogenetics
Background:
- Phylogenetic reconstruction is a key challenge in bioinformatics.
- The Small Parsimony problem is crucial for tree reconstruction but complex on networks with reticulate events.
- Existing parsimony scores on networks are NP-hard, with algorithms parameterized by character states and reticulate events.
Purpose of the Study:
- To develop efficient algorithms for the Small Parsimony problem on phylogenetic networks.
- To address three proposed versions of parsimony scores on networks.
- To leverage the treewidth parameter for algorithmic efficiency.
Main Methods:
- Dynamic programming algorithms parameterized by treewidth.
- Consideration of the treewidth of the underlying undirected graph of the network.
- Formulation of treewidth-based dynamic programming for phylogenetic networks.
Main Results:
- Algorithms for three versions of the parsimony problem on networks with running times dependent on treewidth.
- Improved and subsumed previously known algorithms for these parsimony score variants.
- A novel formulation of tree decompositions using "agreeing trees".
Conclusions:
- Enables computation of popular parsimony scores on phylogenetic networks with low treewidth.
- Enhances existing algorithms for parsimony score variants.
- Aims to make treewidth-based algorithms more accessible to researchers in phylogenetic networks.
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