The Programme

Curriculum

The master's degree programme in Computational Biology und Bioinformatics is a young, interdisciplinary programme for tomorrow’s leaders in life science research at the intersection of biology and computer science. The primary goal is to provide a broad education in Computational Biology and Bioinformatics based on a solid background in computer science, biology, and relevant mathematical approaches.

The structure of the programme aims at an optimal trade-off between the breadth of education and the flexibility in specialization according to the student‘s own choices.

The programme is developed around three closely interrelated themes:

It provides intensive training in foundational, general methods and concepts that enable addressing the fundamental scientific challenges associated with the increasing need to analyse and design highly complex biological systems. Theory courses cover methods in computer science and applied mathematics in areas such as modelling, optimisation, and data analysis. To enable the successful application of computational biology and bioinformatic approaches, biology courses complement the quantitative foundations with a wide range of topics from areas of modern biology such as genetics, genomics, stem cell biology, or cancer biology.

The programme’s core courses are designed to combine methods and applications in four essential areas of computational biology and bioinformatics:

• Bioinformatics: analysis of DNA and protein sequences, for example in comparative genomics and molecular evolution studies
• Biophysics: development of models for, and analysis of structures of biomolecules such as proteins
• Biosystems: modelling and analysis of biological networks in a systems-oriented view, for example to elucidate disease mechanisms
• Big Data: data science approaches such as machine learning to integrate and analyse large biological data sets, for example for personalized medicine applications

The programme’s flexible, short research projects (lab rotations or industry internships) provide a practical overview of different research areas, applying concepts taught in the core courses and advanced courses, and preparing for further specialisation through the master’s thesis. These practice-oriented rotations also help training transferable skills such as interdisciplinary communication, collaboration, and critical thinking.

The programme is mentor-driven. During the first semester, students select a mentor who will advise them in compiling their individual curriculum. The mentoring system aims at providing an excellent, specialized education, while granting sufficient flexibility to meet the expectations and needs of students. The varied course selection and individual study plan provide a flexible study programme.