Computational modeling and analysis of the dynamics of control mechanisms in molecular interaction networks of neurons

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The recent technical innovations in measurement of cellular phenomena provide the means to collect data required for quantitative modeling of cell biology systems. Nowadays, a growing number of biologists adopt a systems biology approach and integrate computational modeling and simulation with experiments in their scientific endeavor. In such setting, modeling can be a tool to generate testable hypotheses and to facilitate understanding. In the cell, biochemical signals are rarely propagated by simple, direct paths, but rather through a network of molecular interactions. With modeling, it is possible to understand the complex dynamics of this network. From a theoretical perspective, to achieve this understanding, one needs more realistic models and analysis methods of simulation data that highlight systemic properties.