Computational Biology
Contents within the Master Program
Students will learn the fundamental principles of bioinformatics and computational methods in other fields of biology. In combination with practical training, students will gain the skills to perform bioinformatic analyses and statistical evaluation. Furthermore, students can select topics from a wide range of biology and apply their computational skills in fields like neuroscience, ecology and evolution, plant science, genetics and the principles of aging.
Modules and Study Paths
Students will have to attend two compulsory modules called Computational Biology Lecture and Practical in Computational Biology. Both modules account for 12 CP. Another 18 CP have to be chosen from a set of modules:
Ecology, Evolution and Environment - Theory and Methods
Molecular Plant and Microbial Sciences – Lecture
Essentials in Neuroscience – Lectures
Population Genetics and Molecular Evolution
Principles of Molecular Genetics, Development and Aging
Statistical Genetics and Epidemiology
Advanced Bioinformatics
A possible exemplary study plan could look like this:
