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

Bad Clade Deletion Supertrees: A Fast and Accurate Supertree Algorithm.

Markus Fleischauer1, Sebastian Böcker1

  • 1Chair for Bioinformatics, Institute for Computer Science, Friedrich-Schiller-University Jena, Jena, Germany.

Molecular Biology and Evolution
|September 7, 2017
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

Integration of palladium-catalyzed C-N coupling into self-encoded libraries for accelerated hit discovery.

RSC chemical biology·2026
Same author

Enhancing Chimeric Fragmentation Spectra Deconvolution Using Direct Infusion-Tandem Mass Spectrometry Across High-Resolution Mass Spectrometric Platforms.

Rapid communications in mass spectrometry : RCM·2025
Same author

Barcode-free hit discovery from massive libraries enabled by automated small molecule structure annotation.

Nature communications·2025
Same author

Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling.

Nature communications·2025
Same author

Discovery of metabolites prevails amid in-source fragmentation.

Nature metabolism·2025
Same author

Coverage bias in small molecule machine learning.

Nature communications·2025

A new heuristic supertree algorithm, Bad Clade Deletion (BCD) supertrees, efficiently resolves conflicting phylogenetic information. BCD supertrees demonstrate superior accuracy and speed compared to existing methods, improving phylogenetic reconstruction.

Area of Science:

  • Computational Biology
  • Phylogenetics
  • Bioinformatics

Background:

  • Supertree methods integrate multiple phylogenetic trees, but conflict resolution remains a challenge.
  • Existing algorithms often use matrix representations and local search heuristics, with varying success in accuracy and speed.

Purpose of the Study:

  • To introduce a novel heuristic supertree algorithm, Bad Clade Deletion (BCD) supertrees, for efficient and accurate phylogenetic reconstruction.
  • To address the challenge of conflicting information in input phylogenetic trees.

Main Methods:

  • BCD supertrees utilize minimum cuts on a matrix representation of input trees to identify and delete conflicting information.
  • This approach is framed as the complement problem to Matrix Representation with Compatibility (Maximum Split Fit).
Keywords:
MRCMRPdivide-and-conquermatrix representation with parsimonyphylogeneticsphylogenysplit fitsupermatrixsupertree

Related Experiment Videos

  • The algorithm guarantees polynomial worst-case running time.

    • Main Results:

    • BCD supertrees achieve higher accuracy (F1 score) than SuperFine and Matrix Representation with Parsimony on simulated data.
    • BCD is significantly faster, outperforming SuperFine by up to 7 times and Matrix Representation with Parsimony by up to 600 times.
    • Using BCD as a starting tree for RAxML analysis improved accuracy by 1% and reduced running time by 1.7-fold.

    Conclusions:

    • Bad Clade Deletion (BCD) supertrees offer a computationally efficient and accurate method for supertree reconstruction.
    • The BCD algorithm provides a robust alternative to existing methods, particularly when dealing with conflicting phylogenetic data.
    • BCD supertrees enhance downstream phylogenetic analyses, such as Maximum Likelihood, by providing a more accurate starting point.