Speaker
Dr
Christoph Wierling
(Max-Planck-Institute for Molecular Genetics)
Description
Modelling and simulation techniques are valuable tools for the understanding of
biological systems. Such systems can be described by a set of constraint biochemical
reactions and translated into a system of differential equations. Each reaction has
substrates and products with given stoichiometries, and modifiers or catalysts that
affect the reaction kinetics. Often the topology of these biochemical reaction
systems is known and available from databases, but the detailed reaction kinetics and
their kinetic parameters are not well known. To overcome this problem we propose a
Monte-Carlo approach, where we simulate different biological scenarios of certain
interest with kinetic parameters chosen from a given random distribution. By
repeating these simulations several times with different sets of kinetic parameters
differences in the behaviour of the different models that reflect certain biological
scenarios can be identified. Depending on the size of the model a single simulation
can take several minutes to up to an hour so that for this approach an immense
computational power is required. To do this in a maintainable time a parallelisation
of the approach is required. We will present this approach and its realisation using
the EGEE grid technology.
Author
Dr
Christoph Wierling
(Max-Planck-Institute for Molecular Genetics)
Co-authors
Dr
Christophe Blanchet
(CNRS IBCP)
Hans Lehrach
(wierling@molgen.mpg.de)
Ralf Herwig
(wierling@molgen.mpg.de)
Mr
Rémi Mollon
(Institut de Biologie et Chimie des Protéines (IBCP UMR 5086); CNRS; Univ. Lyon 1;)
