Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

7.1K
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...
7.1K
Phylogenetic Trees03:21

Phylogenetic Trees

51.2K
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.
51.2K
Survival Tree01:19

Survival Tree

457
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...
457
Optimization Problems01:26

Optimization Problems

109
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
109
Deformations in a Symmetric Member in Bending01:18

Deformations in a Symmetric Member in Bending

569
When analyzing the deformation of a symmetric prismatic member subjected to bending by equal and opposite couples, it becomes clear that as the member bends, the originally straight lines on its wider faces curve into circular arcs, with a constant radius centered at a point known as Point C. This phenomenon helps to understand the stress and strain distribution within the member more clearly.
When the member is segmented into tiny cubic elements, it is observed that the primary stress...
569
Distance Problem01:29

Distance Problem

127
When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
127

You might also read

Related Articles

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

Sort by
Same author

DipSkmer: Reference-free population genomics with diploid genome skims.

bioRxiv : the preprint server for biology·2026
Same authorSame journal

Coalescent-based branch length estimation improves dating of species trees.

Systematic biology·2026
Same author

Phlag: Scalable detection of genomics regions with unexplained phylogenetic heterogeneity.

bioRxiv : the preprint server for biology·2026
Same author

SPrUCE: Utilizing Ultraconserved Elements of DNA for Population-Level Genetic Diversity Estimation.

Molecular ecology resources·2026
Same author

Deconvolving Phylogenetic Distance Mixtures.

bioRxiv : the preprint server for biology·2026
Same author

Species Tree Branch Length Estimation despite Incomplete Lineage Sorting, Duplication, and Loss.

Genome biology and evolution·2025
Same journal

Diversification dynamics in the global radiation of gobies.

Systematic biology·2026
Same journal

Correction to: nQMaker: Estimating Time Nonreversible Amino Acid Substitution Models.

Systematic biology·2026
Same journal

Phylogenomic challenges in polyploid-rich lineages: Insights from paralog processing and reticulation methods using the complex genus Packera (Asteraceae: Senecioneae).

Systematic biology·2026
Same journal

An evolving view of phylogenetic biogeography.

Systematic biology·2026
Same journal

Modeling Site-and-Branch-Heterogeneity with GFmix.

Systematic biology·2026
See all related articles

Related Experiment Video

Updated: Mar 12, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.2K

Branch Length Transforms using Optimal Tree Metric Matching.

Shayesteh Arasti1, Puoya Tabaghi2, Yasamin Tabatabaee3

  • 1Department of Computer Science and Engineering, UC San Diego, CA 92093, USA.

Systematic Biology
|March 10, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces Topology-Constrained Metric Matching (TCMM) to align gene tree branch lengths with species trees. Our method efficiently transforms branch lengths, improving phylogenomic analysis accuracy.

Keywords:
Convex OptimizationDistance-based phylogeneticsOutlier DetectionPhylogenomicsSpecies Tree Branch Length

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.6K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.3K

Related Experiment Videos

Last Updated: Mar 12, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.2K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.6K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.3K

Area of Science:

  • Phylogenetics
  • Computational Biology
  • Evolutionary Genomics

Background:

  • Phylogenomic analyses require comparing evolutionary trees, but branch length heterogeneity poses challenges.
  • Existing methods struggle with diverse branch length units and evolutionary rate variations across genomes.
  • Accurate branch lengths are crucial for downstream applications, yet tools for weighted tree comparison are limited.

Purpose of the Study:

  • To develop a computational method for matching phylogenetic trees based on branch lengths.
  • To address the challenge of transforming gene tree branch lengths to align with a reference species tree.
  • To introduce Topology-Constrained Metric Matching (TCMM) for phylogenomic data integration.

Main Methods:

  • Defined Topology-Constrained Metric Matching (TCMM) problems to adjust query tree branch lengths using a reference tree.
  • Developed an efficient solution using linear algebra and dynamic programming.
  • Applied TCMM to embed gene tree leaves in Euclidean space and summarize gene tree branch lengths onto the species tree.

Main Results:

  • TCMM problems are solvable efficiently through a linear algebraic formulation and dynamic programming.
  • The method successfully identifies potential outliers in gene tree estimation.
  • Summarizing gene tree branch lengths onto the species tree improves accuracy of existing methods.

Conclusions:

  • TCMM provides an efficient framework for comparing and combining phylogenetic trees based on branch lengths.
  • This approach enhances the accuracy of phylogenomic analyses, including outlier detection and branch length summarization.
  • The method offers significant improvements at a limited computational cost.