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It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.

Evolution and statistics are two common themes that pervade the modern analysis of molecular sequence variation.

As all the sequences were sampled from the same time the data should provide no information about the rate of evolution so we might expect the posterior distribution of rate to simply recover the prior we are using.

For the first run I will use a coalescent tree prior that assumes a (*unknown*) constant population size back through time.

Bayesian phylogenetic inference is a complicated affair.

This prior has a parameter (Size) that will be sampled by MCMC.

Divergence Dating (Primates) v1.2(BEAST v1.6.x) correct a mistake in v1.2: missing prior of node calibration (Homi Cerco).

Divergence Dating (Primates) v1.1(BEAST v1.5.x) Divergence Dating (Primates) v1.0Estimating a date of divergence using fossil calibration for primates.

This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics.

Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree.

Combined Practical (Viruses) v1.0Virus (BEAST v1.5.x) Virus_Practical_1_6_1(BEAST v1.6.x) new A three-part virus practical that covers the same material as the two above but has an additional part on Bayesian Skyline Plots.

Influenza BEAST A two-part practical focused on human influenza virus A (A/H1N1pdm and A/H3N2).

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We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

The complete source code for BEAST is now distributed under the GNU Lesser General Public License and the source code, bug tracking database and information for developers is now hosted by Google: These are the groups we know of providing public access to cluster resources that run BEAST.