Hybrid spatial Gillespie and particle tracking simulation

Abstract

Motivation: Cellular signal transduction involves spatial–temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Algorithm (SSA) or Brownian/Smoluchowski dynamics if space and stochasticity are important. To combine the accuracy of particle-based methods with the superior performance of the SSA, we suggest a hybrid simulation.Results: The proposed simulation allows an interactive or automated switching for regions or species of interest in the cell. Especially we see an application if for instance receptor clustering at the membrane is modeled in detail and the transport through the cytoplasm is included as well. The results show the increase in performance of the overall simulation, and the limits of the approach if crowding is included. Future work will include the development of a GUI to improve control of the simulation.Availability of Implementation: www.bison.ethz.ch/research/spatial_simulations.Contact: mklann@ee.ethz.ch or koeppl@ethz.chSupplementary/Information: Supplementary data are available at Bioinformatics online.

Simulating with AcCoRD: Actor-based Communication via Reaction–Diffusion

“…Doing such an integration improves flexibility in the trade-off between accuracy and computational complexity by using a more accurate model only where (or when) it is needed. For example, approaches have been proposed that combine microscopic and mesoscopic models, as in [38,39,40]. The hybrid model in [40] has been implemented in the (primarily mesoscopic) solver URDME (see [32]) and the model in [39] was recently implemented in the (primarily microscopic) solver Smoldyn (see [41]).…”

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Stochastic Reaction–Diffusion Processes with Embedded Lower-Dimensional Structures

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