The goal of the project is to develop and combine suitable algorithms to support an effective and efficient simulation of Brownian dynamics Simulations. The results of the micro-scale simulations shall provide additional insights into biological phenomena that cannot be treated at higher levels of abstraction (e.g. molecular crowding).

Means that help a better integration between wet-lab and dry-lab experiments shall be developed, e.g., in the area of parameter estimation, or model validation.

Keywords: Discrete-event / hybrid simulation, Grid-computing, Multi-resolution simulation, Stochastic Simulation Algorithm (SSA), Gillespie Algorithm, Next Subvolume Method

The goal of this project is to develop a modeling and simulation framework which is sufficiently flexible and modular to support teaching of modeling and simulation methods, applications in diverse areas, and modeling and simulation of complex, heterogenous systems.

The project is aimed at the development of modeling and simulation methods taking the specific challenges of Systems Biology into account and that support a description and analysis at different levels of detail. Therefore, concrete models shall be generated. Thus, the project combines research on modeling and simulation methodology and research on generating cellular models.