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This seminar focuses on the key concepts of computational, mathematical, and statistical models used in cancer and cancer medicine, and helps students learn how mathematical models help us understand cancer progression. The technical articles used in this seminar provide the biological background and describe the development of both classical mathematical models and more recent representations of biological processes. Therefore, students will examine existing mathematical models and learn to deal with the key parameters involved in modeling and the impact of changes in these parameters to discuss how they relate to treatment, prevention, or policy making in general. Through discussions of published work, students will learn how to critically evaluate a modeling effort and how to communicate modeling results to readers of scientific journals. The seminar is useful for students who use experimental techniques as an approach in the laboratory and want to use computational modeling as a tool to gain a deeper understanding of experiments.

Students learn to apply methods of mathematical modelling to systems biology models. This includes
- Have knowledge of the basic concepts of biological networks, the basic structure of systems biology models and the analysis of complex biological systems using mathematical and scientific skills through scientific publications.
- Have knowledge and understanding of how to formulate mathematical models of cellular processes and biochemical reactions and estimate their model parameters.
- Know the main areas in cancer where mathematical modelling has contributed to our understanding of how to read a mathematical modelling paper in all its aspects (methods, results, discussion).

Originalarbeiten und zusätzliche Materialien werden im Seminar ausgegeben.