HPC selection of models of nucleotide substitution

 jModelTest is a tool to carry out statistical selection of best-fit
 models of nucleotide substitution. It implements five different model
 selection strategies: hierarchical and dynamical likelihood ratio tests
 (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC),
 and a decision theory method (DT). It also provides estimates of model
 selection uncertainty, parameter importances and model-averaged
 parameter estimates, including model-averaged tree topologies.
 jModelTest 2 includes High Performance Computing (HPC) capabilities and
 additional features like new strategies for tree optimization, model-
 averaged phylogenetic trees (both topology and branch length), heuristic
 filtering and automatic logging of user activity.