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

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

8.4K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
8.4K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

3.8K
3.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

7.3K
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...
7.3K
Microbial Phylogeny01:28

Microbial Phylogeny

74
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,...
74
Phylogeny01:23

Phylogeny

64.6K
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.
64.6K
Phylogenetic Trees03:21

Phylogenetic Trees

6.8K
6.8K

You might also read

Related Articles

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

Sort by
Same author

PhyloCNN: Improving Tree Representation and Neural Network Architecture for Deep Learning from Trees in Phylodynamics and Diversification Studies.

Systematic biology·2025
Same author

Accelerating Maximum Likelihood Phylogenetic Inference via Early Stopping to Evade (Over-)optimization.

Systematic biology·2025
Same author

Accounting for contact tracing in epidemiological birth-death models.

PLoS computational biology·2025
Same author

multistrap: boosting phylogenetic analyses with structural information.

Nature communications·2025
Same author

The Bayesian Phylogenetic Bootstrap and its Application to Short Trees and Branches.

Molecular biology and evolution·2024
Same author

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Molecular biology and evolution·2024

Related Experiment Video

Updated: Apr 8, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.7K

FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program.

Vincent Lefort1, Richard Desper1, Olivier Gascuel2

  • 1Institut de Biologie Computationnelle, LIRMM, UMR 5506: CNRS & Université de Montpellier, France.

Molecular Biology and Evolution
|July 2, 2015
PubMed
Summary

FastME 2.0 offers advanced phylogenetic tree inference using balanced minimum evolution algorithms. This enhanced tool improves upon Neighbor Joining (NJ) with faster topological moves for more accurate evolutionary analyses.

Keywords:
(balanced) minimum evolutionNNI and SPR topological movesdistance-basedfast algorithmsphylogeny inference

More Related Videos

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

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

Published on: July 11, 2025

758
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K

Related Experiment Videos

Last Updated: Apr 8, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.7K
A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

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

Published on: July 11, 2025

758
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Phylogenetic tree inference is crucial for understanding evolutionary relationships.
  • Existing methods like Neighbor Joining (NJ) have limitations in speed and accuracy.
  • FastME aims to provide a more efficient and accurate alternative.

Purpose of the Study:

  • To introduce FastME 2.0, an improved algorithm for phylogenetic tree reconstruction.
  • To enhance the speed and accuracy of phylogenetic analysis through advanced topological moves.
  • To provide a user-friendly and versatile tool for molecular evolution studies.

Main Methods:

  • FastME employs balanced minimum evolution, a principle similar to NJ.
  • It incorporates Nearest Neighbor Interchange (NNI) and Subtree Pruning and Regrafting (SPR) for topological optimization.
  • The software supports distance estimation for DNA and proteins with various models and bootstrapping.

Main Results:

  • FastME 2.0 significantly improves upon NJ by utilizing sophisticated topological search algorithms.
  • The new version maintains high speed comparable to NJ while offering enhanced accuracy.
  • It provides features like distance estimation, bootstrapping, and parallel computation capabilities.

Conclusions:

  • FastME 2.0 represents a substantial advancement in phylogenetic tree inference.
  • Its speed, accuracy, and versatile features make it a valuable tool for evolutionary biologists.
  • The availability of multiple interfaces ensures broad accessibility for diverse research needs.