Research Report 2003 - Max-Planck-Institut für molekulare Genetik

Department of Vertebrate Genomics
36
Kinetic Modeling Group
Head:
Dr. Edda Klipp
Phone: +49 (0)30-8413 1717
Fax: +49 (0)30-8413 1380
Email: klipp@molgen.mpg.de
Scientist:
Dr. Axel Kowald
Students:
Sebastian Schmeier
Bente Kofahl
Susanne Gerber
The Kinetic Modeling Group was founded in late 2001, belongs to the Berlin Center
of Genome-based Bioinformatics (BCB) and is supported by the BMBF.
Scientific overview
Mathematical modeling of complex biological phenomena and diseases is an important
approach to combine the accumulating amount of data in biological investigations and the
increasing qualitative understanding of cellular operation in a productive way. The realization
of genomic information in a biological instance is ensured by a complex network
of processes. The dynamic behavior of such processes can’t be understood intuitively.
Only a comprehensive approach allows the understanding of complex system behavior
like optimal regulation or adaptation. We use mathematical models to describe and investigate
cellular processes and regulatory links from gene expression to metabolism.
Projects
Modeling of Signal Transduction in the yeast Saccharomyces cerevisiae
Cells are able to react on changes in the environment. Receptor molecules sense the signals,
several proteins transmit them and, eventually, the expression of several genes will
be changed. Newly produced or quantitatively changed proteins allow for stress response,
be it the production of protecting substances, the change in the intracellular medium, or
the cell cycle arrest to prepare mating. Specific processes under investigation are the
HOG (high osmolarity glycerol) and the pheromone pathway in yeast (papers in preparation).
In co-operation with a Swedish experimentally group (Prof. S. Hohmann, Göteborg
University) we model such processes by identifying individually steps and describing
their dynamics with a system of ordinary differential equations. The systems behavior is
analyzed, alternative models are developed, and computer simulations are performed. We
can reproduce the experimentally observed system behavior in the model and make predictions
for the behavior of mutants and for the outcome of experiments to be designed.
Yeast is used as a model organism, since it is easy to handle and many data are already
available. Signaling pathways are evolutionary highly conserved. From an experimental
as well as from a modeling viewpoint, the developed techniques, the specific results and
the art of interaction of modeling and experimental research can be applied to higher
organisms, in order to arrive at a better understanding of the dynamic operation of those
pathways and to offer new opportunities for drug discovery.