Modelling of information flow in cells

Biological systems like cells process physical substrates and information. Metabolic reactions consume and produce substrates, e.g. for building of cell structures or gain of energy. Getting stimuli from outside, cells regulate these mechanisms. They process and integrate this information with their state, e.g. by passing the information into the nucleus and regulating gene expression by transcription factors, yielding a changed physical behaviour of the cells. Here, we describe our recent approaches towards dynamic modelling of complex signal transduction networks. As data source, we use the TRANSPATH(R)Professional database to retrieve the interaction mechanisms of signal molecules, which are the fundamental mechanisms for information transport and processing within cells. We used an object-oriented model, where signal molecules are considered as objects and object variables describe tile conformational and biochemical status. They communicate using parameterised methods and are organised in grouping structures. The model is implemented in Swarm, a general purpose, agent based simulation environment. Feeding Swarm with interaction data from TRANSPATH(R) as binary relations, it may process signal flow and derive emergent properties of the signal molecule network. As an outlook, we describe how the model can be linked to metabolic network for a validation of the simulation outcome with experimentally gained data from large scale gene expression profiling.