636-0017-00L  Computational Biology

Semester Autumn Semester 2017
Lecturers C. Magnus, T. Stadler, T. Vaughan
Periodicity yearly course
Language of instruction English

Catalogue data

Abstract The aim of the course is to provide up-to-date knowledge on how we can study biological processes using genetic sequencing data. Computational algorithms extracting biological information from genetic sequence data are discussed, and statistical tools to understand this information in detail are introduced.
Objective Attendees will learn which information is contained in genetic sequencing data and how to extract information from this data using computational tools. The main concepts introduced are:
* stochastic models in molecular evolution
* phylogenetic & phylodynamic inference
* maximum likelihood and Bayesian statistics
Attendees will apply these concepts to a number of applications yielding biological insight into:
* epidemiology
* pathogen evolution
* macroevolution of species
Content The course consists of four parts. We first introduce modern genetic sequencing technology, and algorithms to obtain sequence alignments from the output of the sequencers. We then present methods for direct alignment analysis using approaches such as BLAST and GWAS. Second, we introduce mechanisms and concepts of molecular evolution, i.e. we discuss how genetic sequences change over time. Third, we employ evolutionary concepts to infer ancestral relationships between organisms based on their genetic sequences, i.e. we discuss methods to infer genealogies and phylogenies. Lastly, we introduce the field of phylodynamics. The aim of phylodynamics is to understand and quantify the population dynamic processes (such as transmission in epidemiology or speciation & extinction in macroevolution) based on a phylogeny. Throughout the class, the models and methods are illustrated on different datasets giving insight into the epidemiology and evolution of a range of infectious diseases (e.g. HIV, HCV, influenza, Ebola). Applications of the methods to the field of macroevolution provide insight into the evolution and ecology of different species clades. Students will be trained in the algorithms and their application both on paper and in silico as part of the exercises.
Lecture notes Lecture slides will be available on moodle.
Literature The course is not based on any of the textbooks below, but they are excellent choices as accompanying material:
* Yang, Z. 2006. Computational Molecular Evolution.
* Felsenstein, J. 2004. Inferring Phylogenies.
* Semple, C. & Steel, M. 2003. Phylogenetics.
* Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST.
Prerequisites / Notice Basic knowledge in linear algebra, analysis, and statistics will be helpful. Programming in R will be required for the "Central Element". We provide an R tutorial and help sessions during the first two weeks of class to learn the required skills.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits 6 credits
Examiners C. Magnus, T. Stadler, T. Vaughan
Type session examination
Language of examination English
Course attendance confirmation required No
Repetition The performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examination written 90 minutes
Additional information on mode of examination Central element amounts to 25% of the final grade
The central element has to be re-done in case of repetition.
Written aids None
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

Main link CB Materials
Only public learning materials are listed.


Number Title Hours Lecturers
636-0017-00 G Computational Biology
The lecture will be held each Monday either in Zurich or Basel and will be transmitted via videoconference to the second location. Tutorials will happen in both locations.
Lecture in Basel/Zürich: Monday 15-17h (BSA E46 / HG D16.2)
Tutorials in Zürich: Monday 17-18h (HG D 16.2)
Tutorials in Basel: Thursday 13-14h (BSA E60 exceptions: Sept. 28 and Oct. 5 in room Manser building 1078)
First lecture takes place Monday, Sept. 25 in room Manser building 1078 instead of BSA E46
3 hrs
Mon 15-17 BSA E 46 »
15-17 HG D 16.2 »
17-18 HG D 16.2 »
Thu 13-14 BSA E 60 »
06.11. 17-18 HG E 22 »
C. Magnus, T. Stadler, T. Vaughan
636-0017-00 A Computational Biology
Project Work (central element), no fixed presence required.
2 hrs C. Magnus, T. Stadler, T. Vaughan


There are no additional restrictions for the registration.

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