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Phylogenetic Trees

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.

Phylogenetic Trees

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.

Phylogeny

Phylogeny

Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.

Microbial Phylogeny

Microbial Phylogeny

Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...

Evolutionary Relationships through Genome Comparisons

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Related Experiment Video

Updated: May 20, 2026

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

Quartets and unrooted phylogenetic networks.

Philippe Gambette¹, Vincent Berry, Christophe Paul

¹Université Paris-Est, LIGM, 5 bd Descartes Champs sur Marne, Champs-sur-Marne 77454, France. philippe.gambette@univ-mlv.fr

Journal of Bioinformatics and Computational Biology

|July 20, 2012

Summary

This study introduces unrooted level-k networks to connect abstract and explicit phylogenetic networks. These findings offer new combinatorial insights into phylogenetic network reconstruction from genetic exchange data.

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Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Published on: August 14, 2018

Area of Science:

Evolutionary biology
Computational phylogenetics
Bioinformatics

Background:

Phylogenetic networks model genetic material exchange between species.
Split networks visualize conflicts in phylogenetic trees, representing these exchanges.
Recent advances allow explicit phylogenetic network reconstruction from triplet data.

Purpose of the Study:

To link abstract and explicit phylogenetic networks via combinatorial properties.
To introduce the unrooted analog of level-k networks.
To explore reconstruction of unrooted level-k phylogenetic networks from quartet data.

Main Methods:

Introducing the unrooted analog of level-k networks.
Proving an equivalence theorem between circular split systems and unrooted level-1 networks.
Adapting triplet-based reconstruction methods for quartets to reconstruct unrooted level-k networks.

Main Results:

Established a combinatorial link between abstract (split systems) and explicit (level-1) unrooted phylogenetic networks.
Demonstrated adaptation of triplet-based methods for quartet data to reconstruct unrooted level-k networks.
Provided a theoretical framework for understanding phylogenetic network combinatorics.

Conclusions:

The study deepens the combinatorial understanding of phylogenetic networks.
The introduced methods offer new perspectives for reconstructing complex evolutionary histories.
Opens avenues for further algorithmic and combinatorial research in phylogenetics.