Insights into the dynamics of Hybrid Methods through a range of biological examples. A hands on approach

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• Vikram Sunkara (Freie Universität Berlin; Konrad-Zuse-Zentrum für Informationstechnik Berlin)
• Thursday 07 April 2016, 11:45-12:30
• Seminar Room 1, Newton Institute.

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SDBW03 - Advances in numerical and analytic approaches for the study of non-spatial stochastic dynamical systems in molecular biology

Biological systems can emerge complexity from simple yet multitude of interactions. Capturing such biological phenomenon mathematically for predictions and inference is being actively researched. Computing systems where the interacting components are inherently stochastic demands large amounts of computational power. Recently, splitting the dynamics of the system into deterministic and stochastic components has been a new strategy for computing biological networks. This hybrid strategy drastically reduces the number of equations to solve, however, the new equations are naturally stiff and nonlinear. Hybrid models are a strong candidate as a numerical method for probing large biological networks with intrinsic stochasticity. In this talk we will take on a new mathematical and numerical perspective of hybrid models. Through many biological examples, we will aim to gain insight into the benefits and stumbling blocks of the hybrid framework.

Related Links

• https://github.com/vikramsunkara/PyME - PyME: Python base CME solver.

This talk is part of the Isaac Newton Institute Seminar Series series.

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