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 Video

Updated: Dec 11, 2025

Evaluation of Protein–Protein Interactions using an On-Membrane Digestion Technique
07:07

Evaluation of Protein–Protein Interactions using an On-Membrane Digestion Technique

Published on: July 19, 2019

7.0K

OBAMA: OBAMA for Bayesian amino-acid model averaging.

Remco R Bouckaert1,2

  • 1School of Computer Science, University of Auckland, Auckland, New Zealand.

Peerj
|August 25, 2020
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

MASCOT-Skyline integrates population and migration dynamics to enhance phylogeographic reconstructions.

PLoS computational biology·2025
Same author

Variational Bayesian phylogenies through matrix representation of tree space.

PeerJ·2024
Same author

MASCOT-Skyline integrates population and migration dynamics to enhance phylogeographic reconstructions.

bioRxiv : the preprint server for biology·2024
Same author

An Efficient Coalescent Epoch Model for Bayesian Phylogenetic Inference.

Systematic biology·2022
Same author

Adaptive Metropolis-coupled MCMC for BEAST 2.

PeerJ·2020
Same author

Model Selection and Parameter Inference in Phylogenetics Using Nested Sampling.

Systematic biology·2018

OBAMA method averages over phylogenetic models, reducing bias in evolutionary estimates. This Bayesian approach integrates model uncertainty for more accurate phylogenetic inference.

Area of Science:

  • Phylogenetics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Bayesian phylogenetic analyses are widely used for amino acid alignments.
  • Model selection for substitution and site models is crucial but often ad hoc.
  • Existing methods for model selection do not account for overall model uncertainty.

Purpose of the Study:

  • To introduce a novel method, OBAMA, for averaging over substitution and site models in phylogenetic analyses.
  • To allow data to inform model choices and explicitly incorporate model uncertainty.
  • To reduce bias in phylogenetic estimates by accounting for uncertainty in model selection.

Main Methods:

  • The OBAMA method employs trans-dimensional Markov Chain Monte Carlo (MCMC) to switch between empirical amino acid substitution models (e.g., Dayhoff, WAG, JTT).
Keywords:
Protein modelAmino acid modelBEASTBayesian analysisBayesian model averagingGamma rate heterogeneityPhylogeneticsSite modelStatistical phylogeneticsSubstitution model

More Related Videos

Stimulation of Vascular Endothelial Cells Using Neutrophil Extracellular Traps in the Presence of Low-Density Lipoprotein
07:26

Stimulation of Vascular Endothelial Cells Using Neutrophil Extracellular Traps in the Presence of Low-Density Lipoprotein

Published on: August 12, 2025

580

Related Experiment Videos

Last Updated: Dec 11, 2025

Evaluation of Protein–Protein Interactions using an On-Membrane Digestion Technique
07:07

Evaluation of Protein–Protein Interactions using an On-Membrane Digestion Technique

Published on: July 19, 2019

7.0K
Stimulation of Vascular Endothelial Cells Using Neutrophil Extracellular Traps in the Presence of Low-Density Lipoprotein
07:26

Stimulation of Vascular Endothelial Cells Using Neutrophil Extracellular Traps in the Presence of Low-Density Lipoprotein

Published on: August 12, 2025

580
  • It integrates switching between model-based or alignment-estimated base frequencies.
  • The method also incorporates switching between gamma rate heterogeneity and proportion of invariable sites.

    • Main Results:

    • A simulation study demonstrated the effectiveness of the OBAMA method.
    • The method successfully estimates parameters like the proportion of invariable sites and the gamma shape parameter using appropriate priors.
    • OBAMA reduces bias in phylogenetic estimates by accounting for model uncertainty.

    Conclusions:

    • The OBAMA method provides a robust framework for Bayesian phylogenetic inference by integrating model uncertainty.
    • Implementation in the open-source OBAMA package for BEAST 2 facilitates joint tree inference across diverse models.
    • This approach enhances the accuracy and reliability of phylogenetic reconstructions.