Stochastic Automata Network Models in Biology

Mathematical modelling plays an important role in Systems Biology. Networks of biochemical reactions are formally described and analyzed in order to gain insight into the molecular mechanisms of the cell. Typical examples of such systems are gene regulatory networks which consist of a number of genes, their encoded protein products and the corresponding messenger RNA molecules. Since protein products serve as transcription factors which means that they control the expression of genes, complex networks of dependencies between genes and proteins exist. They are ultimately responsible for the functioning of an organism and their study is very important for the understanding of diseases.
Often mathematical models of coupled biochemical reactions have to account for the inherent randomness of the molecular collisions and a formulation as a stochastic process is necessary. Current research activities are concerned with an efficient numerical solution of the resulting stochastic models.
We offer a semester project, in which the student will model biological processes as Stochastic Automata Networks (SANs) and use different SAN tools (APNN, PEPS, SMART) to analyse them.
Contact: Verena Wolf