Course
This course will provide foundational knowledge in complex models for phylogenetic inference. Our focus will be primarily on Bayesian inference using MCMC. Each component of the course will be accompanied by a hands-on tutorial using cutting-edge phylogenetic inference software. Specifically, we will use this course to introduce and build a user base for RevBayes. RevBayes is a rich statistical package for inference of evolutionary parameters (open source: http://sourceforge.net/projects/revbayes/). This program coupled with detailed lectures on phylogenetic theory and applications will provide a rich learning environment for Ph.D. students and postdocs in evolutionary biology.
NESCent Academy Course: Phylogenetic Analysis Using RevBayes
| PI(s): | Tracy Heath (University of California-Berkeley) Brian Moore (University of California, Davis) Fredrik Ronquist (Swedish Museum of Natural History ) John Huelsenbeck (University of California, Berkeley) Michael Landis (University of California, Berkeley) Sebastian Hoehna (Stockholm University) Tanja Stadler (ETH Zurich) Bastien Boussau (University of Lyon) |
| Start Date: | 9-Jan-2014 |
| Keywords: | phylogenetics, mathematical modeling, computational modeling, systematics, macroevolution |
This course will provide foundational knowledge in complex models for phylogenetic inference. Our focus will be primarily on Bayesian inference using MCMC. Each component of the course will be accompanied by a hands-on tutorial using cutting-edge phylogenetic inference software. Specifically, we will use this course to introduce and build a user base for RevBayes. RevBayes is a rich statistical package for inference of evolutionary parameters (open source: http://sourceforge.net/projects/revbayes/). This program coupled with detailed lectures on phylogenetic theory and applications will provide a rich learning environment for Ph.D. students and postdocs in evolutionary biology.
