Phylogenetic trees can be estimated from many types of data, including DNA sequences sampled from the organisms of interest. One way to infer phylogeny is to use Bayesian statistics, where inferences are based on the probabilities (posterior probabilities) of phylogenetic trees. Because of the complexity of the problem, the posterior probability distribution of trees is numerically approximated, often using Markov chain Monte Carlo approaches. MrBayes is a widely used program that estimates phylogeny using a Bayesian Markov chain Monte Carlo approach. This grant supports the further development of that program to allow biologists to explore numerous biological problems related to phylogenetic analysis, such as variability in the nucleotide substitution process across a genome.
The broader impacts of this project are significant. The MrBayes program is used by thousands of biologists and has been cited in over 7,500 publications. The new version of the program will extend the program's capabilities in significant ways that will benefit biologists: the number of phylogenetic models available to the biologist will expand; the speed of the program will be increased and the Markov chain Monte Carlo algorithms improved to better explore parameter space; and the program will obtain a graphical user interface that should make using the program easier.
