PhyloBayes 3: a Bayesian software package for phylogenetic reconstruction and molecular dating
Open accessAbstract
Motivation: A variety of probabilistic models describing the evolution of DNA or protein sequences have been proposed for phylogenetic reconstruction or for molecular dating. However, there still lacks a common implementation allowing one to freely combine these independent features, so as to test their ability to jointly improve phylogenetic and dating accuracy. Results: We propose a software package, PhyloBayes 3, which can be used for conducting Bayesian phylogenetic reconstruction and molecular dating analyses, using a large variety of amino acid replacement and nucleotide substitution models, including empirical mixtures or non-parametric models, as well as alternative clock relaxation processes. Availability: PhyloBayes is freely available from our web site http://www.phylobayes.org. It works under Linux, Mac OsX and Windows operating systems. Contact: nicolas.lartillot@umontreal.ca Supplementary information: Supplementary data are available at Bioinformatics online.
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An analysis of Moroz-3D using the site-heterogeneous CAT-GTR model supported demosponges, glass sponges, and homoscleromorphs as the sister group of all other animals, followed by ctenophores, but calcareous sponges were deeply nested within cnidarians and the analysis did not converge.
“an analysis of this dataset using the better-fitting site-heterogeneous CAT-GTR model (45) supported demosponges, glass sponges, and homoscleromorphs as the sister group of all other animals, followed by ctenophores. However, in this tree, the calcareous sponges are deeply nested within cnidarians (Fig. S2 B ), and, furthermore, this analysis did not converge”
From Genomic data do not support comb jellies as the sister group to all other animals (2015) · cites this paper as [45]
Methods for inferring latent phylogenetic trees are frustrated by long run times and poor scalability to large datasets.
“Methods for inferring these latent phylogenetic trees continue to be of substantial interest 92-94, but are frustrated by long run times and poor scalability to large datasets.”
From Learning the protein language: Evolution, structure, and function (2021) · cites this paper as [93]
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- Authors
- Lartillot, N., Lepage, T., & Blanquart, S.
- Affiliations
- Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (FR)
- Corresponding author
- Lartillot, Nicolas
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-06-17
- Volume
- 25
- Issue
- 17
- Pages
- 2286-2288
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2104398544
- Cited by
- 1,297
- References
- 23
- Citations by year
- 2026: 18 · 2025: 34 · 2024: 47 · 2023: 81 · 2022: 54 · 2021: 85 · 2020: 80 · 2019: 82 · 2018: 115 · 2017: 115 · 2016: 108 · 2015: 110 · 2014: 128 · 2013: 98 · 2012: 65
- FWCI
- 18.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Agence Nationale de la Recherche
- Université de Montréal
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- Bayesian phylogenetic reconstruction, divergence time estimation, nucleotide substitution models, nonparametric models, software package
- MeSH terms
- Animals, Bayes Theorem, Phylogeny, Predictive Value of Tests, Software, Time Factors, Reproducibility of Results, Computational Biology, Databases, Nucleic Acid
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