Dramatic advances in proteonomics, 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 as well as the interactions among them, since the interactions are ultimately responsible for an organism’s form and functions.
Systems biology aims to obtain a holistic understanding of biological systems such as a single cell, organ or even a whole living organism, by combining approaches from system sciences, life sciences, and information sciences.
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 significant advances in various fields such as medicine and biochemical engineering. Systems biology, often also called “the sciences of the 21st century”, is an interdisciplinary challenge for biologists, computer scientists, system theoreticians, and physicians.
The main objective of this course is to give an introduction to systems biology, 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, genetic networks, and cell to cell signaling. Where necessary, a review of the biological basics is given. Topics to be covered include:
* modeling and analysis of biochemical reaction networks
* databases and information science tools
* modeling and analysis of genetic regulatory networks
* experimental techniques typically used in systems biology
* Constrained-based modeling
* Stochastic modeling approaches
* Qualitative and quantitative models
* Sensitivity analysis
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