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Christoph Flamm
KLI Colloquia
From Graph Grammars to Evolving Reaction Networks
Christoph FLAMM (University of Vienna)
2016-04-14 16:30 - 2016-04-14 16:30
KLI
Organized by KLI

Topic description:
Computational models to explore the structure and evolution of catalyzed reaction networks (or metabolism in particular) have demanding pre-requisites. The central component of such a model requires a formalization of chemistry which is able to capture the algebraic and thermodynamic structure of chemical processes while remaining computationally tractable. During chemical transformations molecular entities can change their quantitative physico-chemical properties while atom types and mass is conserved. Furthermore, upon interaction, novel molecular species with hitherto unknown physico-chemical properties may arise. The formalism must be expressive enough to mimic the intricacy of a modern metabolic network, without restricting the possible chemistry to the known extant end results. With such a formalism in place the question how evolved reaction networks differ from abiotic ones can be approached. I will illustrate the potential of our graph grammar based chemistry formalism by presenting results (i) on the evolution of metabolism showing that all traces of the early reaction system are erased, and (ii) the density of autocatalysis in reaction networks, which turns out to be rather high for metabolism.

 

Biographical note:
Christoph Flamm​ received a master in Organic Chemistry (focus area natural product synthesis) and a doctorate in Theoretical Chemistry (focus area folding kinetics of RNA) from the University of Vienna. After an extended postdoctoral research stay at the University of Leipzig he returned to the University of Vienna and was conferred the venia docendi (Habilitation) in fall 2006. Since that time he is Associate Professor at the Institute for Theoretical Chemistry at the University of Vienna. Flamm teaches Cheminformatics and Systems Biology courses. He is experienced in the development of theoretical methods for the analysis of complex (bio)chemical reaction systems and computational RNA Biology. Flamm currently focuses his research on blending computer science and chemistry concepts.