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 Experiment Videos

Shortest triplet clustering: reconstructing large phylogenies using representative sets.

Le Sy Vinh1, Arndt von Haeseler

  • 1Heinrich-Heine-Universität Düsseldorf, WE Informatik, Universitätstr. 1, D-040225 Düsseldorf, Germany. vinh@cs.uni-duesseldorf.de

BMC Bioinformatics
|April 12, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

IQ-TREE 3: phylogenomic inference software using complex evolutionary models.

Molecular biology and evolution·2026
Same author

Genomic GC bias correction improves species abundance estimation from metagenomic data.

Nature communications·2025
Same author

GTestimate: improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator.

GigaScience·2025
Same author

Quantitative profiling of human brain organoid cell diversity across four protocols and multiple cell lines.

Cell reports·2025
Same author

nT4X and nT4M: Novel Time Non-reversible Mixture Amino Acid Substitution Models.

Journal of molecular evolution·2025
Same author

An efficient deep learning method for amino acid substitution model selection.

Journal of evolutionary biology·2024

A new shortest triplet clustering (STC) algorithm reconstructs phylogenies efficiently for large datasets. Post-processing with balanced nearest neighbor interchange (BNNI) further improves topological accuracy in phylogenetic analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Phylogenetic analysis aims to understand evolutionary relationships using genetic data.
  • Reconstructing phylogenies for large datasets remains a significant challenge in bioinformatics.

Purpose of the Study:

  • To introduce a novel distance-based clustering method for efficient phylogenetic tree reconstruction.
  • To address the computational challenges associated with large-scale phylogenetic analysis.

Main Methods:

  • Developed the shortest triplet clustering (STC) algorithm, a distance-based method.
  • Utilized k-representative sets and shortest triplets as building blocks for agglomerative tree construction.
  • Algorithm achieves O(n^2) time complexity for n sequences.

Related Experiment Videos

Main Results:

  • STC demonstrated superior topological accuracy compared to other initial tree-building methods in simulations.
  • Balanced nearest neighbor interchange (BNNI) significantly improved topological accuracy across all tested methods.
  • STC provides an effective starting point for tree reconstruction.

Conclusions:

  • The STC algorithm efficiently reconstructs phylogenies, particularly for large datasets.
  • BNNI is a crucial post-processing step for enhancing topological accuracy in phylogenetic reconstruction.
  • The developed program is publicly available for research use.