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Systems approaches to biological complexity

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Abstract:
Biological cells are characterized by a high degree of complexity in terms of components and interactions. Reverse-engineering, and in perspective, the engineering of biological systems require sufficiently detailed mathematical models. However, incomplete and primarily qualitative biological knowledge and data on parts and interactions, as well as insufficient theoretical methods for analyzing the systems affect the endeavor. The aim of this talk is to delineate how analysis could proceed from well-characterized (structural) properties to complex representations of dynamics in cellular systems, and the associated challenges for theory and methods. Tailoring and further developing concepts from engineering, in particular regarding robustness, optimality, identification and suitable approximations, is one possible way of approaching the topic, on which the talk will focus. Several biological examples will illustrate the use of systems theory methods in modeling, analysis and experimental design. New methods and models for specific systems promise further progress towards an understanding of highly integrated dynamic systems in biology, which could prove valuable as a blueprint for the design of complex engineered systems.

http://www.icos.ethz.ch/
Type of Seminar:
Public Seminar
Speaker:
Prof. Jörg Stelling
Institute of Computational Science, ETH Zurich
Date/Time:
May 25, 2005   17:15
Location:

ETH Zentrum, Gloriastr. 35, Building ETZ, Room E6
Contact Person:

Prof. M. Morari
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Biographical Sketch:
Jörg Stelling is an assistant professor for bioinformatics at the Institute of Computational Science at ETH Zurich since February 2005. Prior to this, he worked as an assistant and as a research scientist at the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany (1998-2005), and at the Systems Dynamics and Control group at Stuttgart University, Germany (1996-1998). During this time, Jörg Stelling won a Peter and Traudl Engelhorn Foundation Fellowship (1998-2001). He obtained a MS in Biotechnology from the Technical University of Braunschweig, Germany, and a PhD in Engineering (control and dynamic systems, advisors E.D. Gilles and F.J. Doyle III) from Stuttgart University, Germany. His fields of interest combine theoretical aspects of Systems Biology with applications to specific cellular systems, for example, (i) mathematical modeling and identification of complex regulatory networks (cell cycle regulation, signal transduction and metabolic control, primarily in yeast as a model organism), (ii) structural network analysis (pathway analysis, optimal control), (iii) robustness of biological systems (theoretical approaches; connections between robustness, complexity and identification; application to circadian oscillators and signal transduction pathways), and (iv) modeling concepts and tools. Selected publications: Szallasi, Z., Periwal, V. and Stelling, J. (eds.), System modeling in cellular biology: From concepts to nuts and bolts (MIT Press, Cambridge / MA) to appear, 2005.
Doyle III, F.J. and Stelling, J., Robust performance in biophysical networks. 16th IFAC World Congress, Prague 2005, accepted.
Zak, D.E., Stelling, J. and Doyle III, F.J., Sensitivity analysis of oscillatory (bio)chemical systems. Comp. Chem. Eng. 29: 663-673, 2005.
Stelling, J., Mathematical models in microbial systems biology. Curr. Opin. Microbiol. 7(5): 513-518, 2004.
Stelling, J., Sauer, U., Szallasi, Z., Doyle III, F.J. and Doyle, J., Robustness of cellular functions. Cell 118: 675-685, 2004.
Stelling, J., Gilles, E.D. and Doyle III, F.J., Robustness properties of circadian clock architectures. Proc. Natl. Acad. Sci. U.S.A. 101: 13210-13215, 2004.
Stelling, J. and Gilles, E.D., Mathematical modeling of complex regulatory networks. IEEE Trans. NanoBioSci. 3(3): 172-179, 2004.
Stelling, J., Klamt, S., Bettenbrock, K., Schuster, S. and Gilles, E.D., Metabolic network structure determines key aspects of functionality and regulation. Nature 420: 190-193, 2002.