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

Reconstructing One-Articulated Networks with Distance Matrices.

Kuang-Yu Chang1, Yun Cui2, Siu-Ming Yiu2

  • 11 Department of Computer Science, National Tsing Hua University , Hsinchu, Taiwan .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 14, 2017
PubMed
Summary

Researchers can reconstruct evolutionary phylogenetic networks from distance matrices efficiently. This method reconstructs the simplest network with minimal hybrid nodes and allows for rapid tree containment checks.

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

Primary intracranial RAF1-rearranged spindle cell neoplasm: a case report of a rare entity.

Acta neurologica Belgica·2026
Same author

Analysis of clinical characteristics and risk factors for severe EBV infection in children-a single-center retrospective cohort study.

BMC pediatrics·2026
Same author

Case Report: Extranodal marginal zone B-cell lymphoma in the lateral ventricle: literature review.

Frontiers in oncology·2026
Same author

The Changing Trends of T Stage and Size of Early Gastric Cancer.

Journal of digestive diseases·2026
Same author

Psychomotor Rehabilitation for Pediatric Delirium: A Study Protocol for a Randomized Controlled Trial Investigating Efficacy and Brain Electrophysiological Mechanisms.

Neuropsychiatric disease and treatment·2026
Same author

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era.

Journal of chemical theory and computation·2026

Area of Science:

  • Computational Biology
  • Phylogenetics
  • Network Theory

Background:

  • Phylogenetic networks model evolutionary histories, including reticulate evolution.
  • Reconstructing networks from distance data is a key challenge in phylogenetics.
  • One-articulated networks are a significant class of phylogenetic networks.

Purpose of the Study:

  • To develop an efficient algorithm for reconstructing one-articulated phylogenetic networks from distance matrices.
  • To ensure the reconstructed network is the simplest possible, minimizing hybrid nodes.
  • To enable efficient checking of phylogenetic tree containment within these networks.

Main Methods:

  • Developing a reconstruction algorithm for one-articulated networks from ultrametric distance matrices.
Keywords:
distance matrixone-articulated networksphylogenetic networksreconstruction

Related Experiment Videos

  • Analyzing the computational complexity for network reconstruction and tree containment.
  • Utilizing network indexing for efficient querying.

    • Main Results:

    • A novel algorithm reconstructs a one-articulated network satisfying a given distance matrix in O(n^3) time.
    • The reconstructed network minimizes the number of hybrid nodes.
    • Phylogenetic tree containment within the reconstructed network can be checked in O(n^2) time.

    Conclusions:

    • Efficient reconstruction of simplified phylogenetic networks from distance data is achievable.
    • The developed methods provide practical tools for phylogenetic network analysis.
    • This work advances the computational understanding of evolutionary networks.