Introduction to Systems Biology (2V)
- Time and place (2h lecture + 2h exercise):
| First meeting: Thursday, October 18, 2012
| Tuesday 11:30 - 13:00, V9.12
| Thursday 15:45 - 17:15, V9.12
All online material is provided in the ILIAS System, follow the
You need an email address from the University of Stuttgart to register.
Please contact the lecturer to get the course password.
- Additional Information
Dramatic advances in proteomics, genomics, and measurement
technologies such as DNA arrays have lead to a significantly increased
knowledge about biological organisms.
Classical and molecular biology have contributed to identify numerous
individual genes and proteins, as well as other cellular
components, and their specific functions.
However, by now it has become clear that understanding biological
organisms is not possible by simply collecting information about all
involved components. Rather, a holistic understanding of biological
organisms requires considering all involved components and the
interactions among them, since those are ultimately responsible
for an organism’s function.
Systems biology aims to obtain a holistic understanding of
biological systems such as a single cell, an organ or even a whole living
organism, by combining approaches from system sciences, life sciences, and
An exciting and constantly active field of research, systems biology integrates
experimental data and mathematical modeling, knowledge and system analysis, to gain
intuition into the mechanisms and dynamics of biological systems.
It is expected that the
insights obtained using methods from systems biology will lead to
advances in various fields such as medicine and biochemical
Systems biology, often also called “the sciences of the 21st
is an interdisciplinary challenge for biologists, computer scientists,
system theoreticians, and physicians.
The main objective of this
course is to give an introduction to
covering aspects from biology,
systems theory, and some of the databases/tools available.
The course is designed for people interested in the
fusion of systems, life, and information sciences.
One of the goals is to give a clear insight into the modeling and
analysis methods typically used to study biological systems, including
metabolism, signal transduction and genetic networks.
Where necessary, a review of the biological basics is given. Topics
to be covered include:
- Modeling regulatory and metabolic networks with chemical reaction kinetics
- Flux balance analysis
- Stochastic modeling approaches for biological networks
- Signal transduction networks
- Sensitivity analysis
The course is tentatively given in