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Distinct-Cluster Tree-Child Phylogenetic Networks and Possible Uses to Study Polyploidy.

Bulletin of mathematical biology·2022

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Merging Arcs to Produce Acyclic Phylogenetic Networks and Normal Networks.

Stephen J Willson¹

¹Department of Mathematics, Iowa State University, Ames, IA, 50011, USA. swillson@iastate.edu.

Bulletin of Mathematical Biology

|January 4, 2022

Summary

This study introduces a method to simplify complex phylogenetic networks by contracting arcs. This process results in a well-defined, normal phylogenetic network, aiding in the analysis of evolutionary relationships.

Keywords:

CSD map Network Normal network Phylogenetic network Phylogeny

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A Practical Guide to Phylogenetics for Nonexperts

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Published on: February 5, 2014

Area of Science:

Phylogenetics
Computational Biology
Network Theory

Background:

Phylogenetic networks are increasingly complex, necessitating simplification methods.
Current methods may not adequately handle non-binary networks or guarantee specific structural properties.

Purpose of the Study:

To develop a systematic method for simplifying acyclic phylogenetic networks.
To ensure the resulting simplified network is "pre-normal" and can be reduced to a normal network.

Main Methods:

Modifying acyclic phylogenetic networks by contracting arcs within a specified set D.
Identifying criteria for selecting set D to ensure acyclicity and pre-normality of the resulting network.
Utilizing network geometry for set D selection, independent of other network data.

Main Results:

A method is presented to transform acyclic phylogenetic networks into other acyclic networks.
The selection of set D based on network geometry guarantees a "pre-normal" resulting network.
Removal of redundant arcs from the pre-normal network yields a normal phylogenetic network.
CSD maps are shown to relate the original and simplified networks.

Conclusions:

The proposed method provides a geometrically defined way to obtain a normal phylogenetic network from any given acyclic phylogenetic network.
This simplification technique enhances the interpretability of complex evolutionary histories represented by phylogenetic networks.