Seminar 2017-11-22

Date: 2017-11-22
Time: 11:00-12:00
Speaker: Fredrik Ronquist, professor and department head at Naturhistoriska Riksmuseet

Title: Probabilistic programming for statistical phylogenetics

Abstract
Statistical inference based on phylogenetic models - models built around evolutionary trees - is widely used throughout the life sciences today. The field is completely dominated by Bayesian MCMC methods, which were introduced about 20 years ago. The flexibility and computational efficiency of this approach have resulted in explosive development of phylogenetic models. It has been quite challenging for computational biologists to keep up with the rapidly expanding model space, and the field is dominated today by a plethora of software packages, each dealing with a specific subset of models. There is a clear need for more generic approaches to model construction and inference. We have tried to address these challenges by developing Rev, a probabilistic programming language for statistical phylogenetics based on probabilistic graphical models.

Unlike most other such languages, Rev is designed for use in an interactive computing environment, allowing users to build phylogenetic models step by step, and examine the model components as they go. I describe some of the challenges involved in developing an interactive probabilistic programming language and some of the potential and limitations of probabilistic graphical models in phylogenetics.

Bio
Fredrik Ronquist is a professor and department head at Naturhistoriska Riksmuseet, where he develops software (MrBayes and RevBayes) for Bayesian inference of phylogeny, evolution and biogeography. His research interests also include systematics, diversity and evolution of insects, particularly hymenopterans. Initiator of the Swedish Taxonomy Initiative, Morphbank and the Swedish Malaise Trap Project. Active in international biodiversity informatics. Heads the Station Linné Foundation, which runs a field station on Öland. He is currently a visiting professor at KTH.