Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Apr 19, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Introducing TreeCollapse: a novel greedy algorithm to solve the cophylogeny reconstruction problem.

Benjamin Drinkwater, Michael A Charleston

BMC Bioinformatics

|December 19, 2014

Summary

This summary is machine-generated.

Related Concept Videos

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

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.

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Survival Tree

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...

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,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Shape-constrained, changepoint additive models for time series omics data with cpam.

Nucleic acids research·2026

Same author

Leveraging advances in machine learning for the robust classification and interpretation of networks.

Royal Society open science·2025

Same author

Dehydration rapidly induces expression of NCED genes from a single subclade in diverse eudicots.

Planta·2025

Same author

Spectral cluster supertree: fast and statistically robust merging of rooted phylogenetic trees.

Frontiers in molecular biosciences·2024

Same author

David Penny-An indomitable evolutionary biologist.

Proceedings of the National Academy of Sciences of the United States of America·2024

Same author

Ancient and Modern Genomes Reveal Microsatellites Maintain a Dynamic Equilibrium Through Deep Time.

Genome biology and evolution·2024

A new greedy algorithm, TreeCollapse, significantly speeds up cophylogeny mapping for coevolutionary systems. This method provides biologically feasible solutions faster than previous heuristics, aiding in the recovery of complex evolutionary histories.

Area of Science:

Evolutionary Biology
Computational Biology
Bioinformatics

Background:

Cophylogeny mapping analyzes coevolutionary associations between multiple phylogenetic histories.
The NP-Hard nature of this problem necessitates heuristic approaches, often computationally intensive.
Existing metaheuristics, while guaranteeing biologically feasible solutions, face scalability challenges with large datasets.

Purpose of the Study:

To develop a faster heuristic algorithm for cophylogeny mapping.
To improve the efficiency of analyzing large-scale coevolutionary systems.
To provide a computationally efficient method that guarantees biologically feasible solutions.

Main Methods:

Introduced TreeCollapse, a greedy algorithm for approximating coevolutionary history with fixed internal node ordering.

More Related Videos

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Related Experiment Videos

Last Updated: Apr 19, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Utilized common topological patterns to guide the approximation process.

Analyzed algorithm performance on over 100 coevolutionary systems.

Main Results:

TreeCollapse achieves linear running time, a significant speed-up over cubic time methods.
The algorithm converged on Pareto optimal solutions in over 68% of test cases.
It successfully recovered previously unobtainable Pareto optimal solutions in some instances.
Guaranteed biologically feasible solutions, making it the fastest method with this guarantee.

Conclusions:

TreeCollapse is a valuable addition to coevolutionary research, offering faster cost estimation for cophylogeny mappings.
Its speed and guaranteed feasibility enhance the analysis of complex coevolutionary systems.
Combined with existing heuristics, it expands the recovery of the Pareto front for coevolutionary histories.