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Institute for Advanced Simulation (IAS)

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Mesoscale Modeling of Neural Cascades

Currently, many biochemical interactions are modeled by ordinary differential equations, according to the mass-action kinetics based on the hypothesis that there are no concentration inhomogeneities and the system is well mixed. No spatial heterogeneity, geometrical restraints, electric fields, advection/diffusion, (co)localization or physico-chemical properties of the involved partners are explicitly taken into account. Our goal is to quantify the role of these aspects in shaping the signaling pathways, by a mesoscopic modeling of the underlying molecular interactions. On the long term, this approach may provide important hints for improving our understanding of neural functions and dysfunction as well as the prediction of downstream responses to different stimuli (disease-linked mutations, drugs, radioligands, etc). We focus on the GPCRs-based cascades such as those relevant to rewarding signals involved in memory processes.

Students with a background in statistical physics and interested in a Ph.D position on this topic are strongly encouraged to send an application to our Institute.