Abstract. Along with the advances in experimental techniques comes a transformation of life science into a highly quantitative
discipline. While statistics and bioinformatics are widely used for data analysis, applied mathematics is
more and more acknowledged as an equal contributor in the quest to understand the functional interactions of cellular
components, organs and systems. Visions of this interdisciplinary approach include personalized medicine, computer
designed drugs or large scale biofuel usage. With life being a dynamic process, modelling and simulation of biological
systems often involves time-dependent differential equations and brings along a diversity of inverse problems
such as inference of parameters in biochemical reaction networks or the manipulation of qualitative network behaviour for
the return from diseased to healthy states.
Lecture 1. March 22 (Friday), 2:00-3:00
Introduction into computational systems biology
Lecture 2. March 22 (Friday), 4:00-5:00
Modelling and simulation of biochemical reaction networks
Lecture 3. March 23 (Saturday), 2:00-3:00
The identification of network parameters
Lecture 4. March 23 (Saturday), 4:00-5:00
Qualitative inverse problems
