MrBayes 3: Bayesian phylogenetic inference under mixed models
MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models to analyze heterogeneous data sets and explore a wide variety of structured models mixing partition-unique and shared parameters.
MRBAYES: Bayesian inference of phylogenetic trees
The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo, and an executable is available at http://brahms.rochester.edu/software.html.
MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space
The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly, and provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates.
Bayesian Inference of Phylogeny and Its Impact on Evolutionary Biology
Bayesian inference of phylogeny brings a new perspective to a number of outstanding issues in evolutionary biology, including the analysis of large phylogenetic trees and complex evolutionary models and the detection of the footprint of natural selection in DNA sequences.
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference
The proposed parallel algorithm retains the ability to explore multiple peaks in the posterior distribution of trees while maintaining a fast execution time, and performance results indicate nearly linear speed improvement in both programming models for small and large data sets.
Bayesian phylogenetic analysis of combined data.
A Bayesian MCMC approach to the analysis of combined data sets was developed and its utility in inferring relationships among gall wasps based on data from morphology and four genes was explored, supporting the utility of morphological data in multigene analyses.
Signal, noise, and reliability in molecular phylogenetic analyses.
This work analyzed 8,000 random data matrices consisting of 10-500 binary or four-state characters and 5-25 taxa to study several options for detecting signal in systematic data bases, finding the skewness of tree-length distributions is closely related to the success of parsimony in finding the true phylogeny.
Frequentist properties of Bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models.
This simulation study shows that Bayesian posterior probabilities have the meaning that is typically ascribed to them, and suggests that the Bayesian method be implemented with the most complex models of those currently available, to reduce the chance that the method will concentrate too much probability on too few trees.