Abstract

Abstract: The relationship between structure, function and regulation in complex cellular networks is a still largely open question. It is difficult to address because detailed mechanisms and kinetic parameters are rarely available. However, structure-oriented approaches only require network topology, which can often be derived from genomic data.

The talk will focus on concepts and methods of structural network analysis, in particular the computation and characteristics of elementary flux modes (EFMs). EFMs are the smallest sub-networks enabling a system to operate in steady state and characterize the space of all states that are meaningful for a biological cell. EFM computation is a hard problem – equivalent to vertex enumeration in computational geometry. However, efficient new algorithms enable at least medium-scale network analysis. Applications of EFMs range from investigating the effects of network perturbations and to predicting cellular control features.

More recently, we proposed extensions of EFM applications to analyze systems dynamics based on the chemical reaction network theory. For an example network inspired by yeast cell cycle control, the approach allows for model discrimination, identification of key mechanisms for switching events, and robustness analysis. Structural network analysis, thus, provides challenging computational science problems as well as broad perspectives for uncovering the organization and functionality of cellular networks.

Biography: Jörg Stelling heads the Computational Systems Biology group at the Department of Computer Science (since 2005) and at the Department of Biosystems Science & Engineering of ETH Zurich (since 2008). After an initial training in Biotechnology, he obtained a PhD in Control & Dynamic Systems applied to biology from Stuttgart University in 2004.

His research interests are in the fields of analysis and synthesis of biological networks with the help of – and by further development of – methods from systems theory and computational science. The focus is on developing concepts and tools for network inference, for system modeling and analysis, and for experimental design at larger scales in different biological systems. More specifically, the research aims at elucidating design principles underlying the function and integration of cellular networks of different types such as metabolism, signal transduction and gene regulation. All projects involve close collaborations with experimental biologists and computer / systems scientists.