This Master's programme starts with two compulsory options which pave the fundamentals in bioinformatics and biocomplexity. As there are no tracks, you can mix and match to create a more bioinformatics or more biocomplexity (modeling) flavour in the electives phase of the Master's. Also the type of internship you choose will determine the specialisation or area of research you most like. Together with the Programme Coordinator, you will determine the most optimal study path.
Compulsory courses (15 EC)
Essentials (4.5 EC)
During this course, the emphasis will be on the essential abilities and knowledge that is required to be able to become a skilful bioinformatics researcher. A broad range of topics, varying from computer skills and programming, data analysis and visualisation to computational algorithms, will be addressed and put into perspective using real-world biological research questions and problems. In addition one or more courses with a minimum of 5.5 EC should be selected from the elective courses.
Plus choose one of the compulsory options below, in consultation with the coordinator and based on your prior knowledge:
Option 1: Biological Modeling (5.0 EC)
The course covers a large number of mathematical models to show how one can describe and understand the dynamics of biological populations. Examples of this population dynamics are: ecological food chains, epidemiological models, bacteria infected by phages and populations of cells. Students are made familiar with the preparation and analysis of mathematical models.
Option 2: Bioinformatics and Genomics (5.0 EC)
In this course, attention is paid to understanding and working with large amounts of data as has been obtained in recent years in many genetic and molecular research. These technological developments require new skills and concepts to be able to understand and conduct life science research. In two parts, we work successively with mutations and sequencing data, the regulation network is studied and how the consequence of mutations in proteins can be better explained through evolution.