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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:

Computational Neuroscience

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

Advanced Bioinformatics

A possible exemplary study plan could look like this: