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262-0200-00L 4 Credits BSC , MSC D-USYS , D-INFK , D-MATH , D-BSSE , D-ITET
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Bayesian Phylodynamics

Lecturers & Examiners: Prof. Dr. Tanja Stadler, Dr. Timothy Vaughan
VVZ CR n/a

Last Updated: 2026-02-05 15:41:58

Abstract

How fast was Ebola spreading in West Africa? Where and when did the epidemic outbreak start? How can we construct the phylogenetic tree of great apes, and did gene flow occur between different apes? At the end of the course, students will have designed, performed, presented, and discussed their own phylodynamic data analysis to answer such questions.

Objective

Attendees will extend their knowledge of Bayesian phylodynamics obtained in the “Computational Biology” class (636-0017-00L) and will learn how to apply this theory to real world data. The main theoretical concepts introduced are: * Bayesian statistics * Phylogenetic and phylodynamic models * Markov Chain Monte Carlo methods Attendees will apply these concepts to a number of applications yielding biological insight into: * Epidemiology * Pathogen evolution * Macroevolution of species

Content

In the first part of the semester, in each week, we will first present the theoretical concepts of Bayesian phylodynamics. The presentation will be followed by attendees using the software package BEAST v2 to apply these theoretical concepts to empirical data. We use previously published datasets on e.g. Ebola, Zika, Yellow Fever, Apes, and Penguins for analysis. Examples of these practical tutorials are available on https://taming-the-beast.org/ . In the second part of the semester, the students choose an empirical dataset of genetic sequencing data and possibly some non-genetic metadata. They then design and conduct a research project in which they perform Bayesian phylogenetic analyses of their dataset. The weekly class is intended to discuss and monitor progress and to address students’ questions very interactively. At the end of the semester, the students present their research project in an oral presentation. The content of the presentation, the style of the presentation, and the performance in answering the questions after the presentation will be marked.

Resources

Lecture Notes

Lecture slides will be available on moodle.

Literature

The following books provide excellent background material: • Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST. • Yang, Z. 2014. Molecular Evolution: A Statistical Approach. • Felsenstein, J. 2003. Inferring Phylogenies. The tutorials in this course are based on our Summer School “Taming the BEAST”: https://taming-the-beast.org/

General Information

Language
English
Levels
BSC , MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Graded oral presentation of research project which was conducted throughout the semester (10 min of presentation of research project, plus 5 min of questions on presentation and research project).

Course Components

Type Title Time & Place Hours
lecture with exercise Bayesian Phylodynamics
***ATTENTION: Starting with the lecture on March18, the Bayesian Phylodynamics lecture will be broadcasted using a Zoom videoconference. The lecturer will inform the students about the URL to participate in the online course***
  • Wed 11:15-13:00 (BSB E 4)
2 h weekly
independent project Bayesian Phylodynamics No time listed 2 h weekly

Offered In