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Updated: Feb 13, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Inferring Phylogenetic Networks Using PhyloNet.

Dingqiao Wen¹, Yun Yu¹, Jiafan Zhu¹

¹Computer Science.

Systematic Biology

|March 8, 2018

Summary

This summary is machine-generated.

PhyloNet software now infers complex phylogenetic networks using maximum parsimony, maximum likelihood, and Bayesian methods. It accounts for reticulation and incomplete lineage sorting directly from gene trees or sequence data.

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Area of Science:

Evolutionary biology
Computational phylogenetics
Bioinformatics

Background:

PhyloNet, initially released in 2008, provided tools for phylogenetic network analysis.
Early versions focused on network topology comparisons and gene tree-species tree reconciliation.

Purpose of the Study:

To detail the significant expansion of PhyloNet's capabilities since its initial release.
To highlight advanced methods for inferring phylogenetic networks from diverse data types.

Main Methods:

Phylogenetic network inference using maximum parsimony (minimizing deep coalescences) and maximum likelihood/Bayesian methods (multispecies network coalescent).
Implementation of Bayesian inference directly from sequence data (alignments, biallelic markers).
Utilizes pseudolikelihood for computationally intensive network evaluation and inference, supporting multiple individuals per species.

Main Results:

PhyloNet now offers a comprehensive suite of methods for phylogenetic network construction.
The software effectively handles reticulation and incomplete lineage sorting in evolutionary analyses.
Extended Newick format output facilitates visualization with existing software.

Conclusions:

PhyloNet has evolved into a powerful and versatile tool for modern phylogenetic network inference.
The inclusion of diverse inference methods and direct sequence data analysis enhances its utility for evolutionary studies.
The software provides a robust platform for analyzing complex evolutionary histories represented by phylogenetic networks.