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Hybrid spatial Gillespie and particle tracking simulation

Authors: Klann, Michael; Ganguly, Arnab; Koeppl, Heinz;

Hybrid spatial Gillespie and particle tracking simulation

Abstract

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.ch Supplementary/Information: Supplementary data are available at Bioinformatics online.

Countries
Germany, Switzerland, Switzerland
Related Organizations
Keywords

Stochastic Processes, Computer Simulation, Original Papers, Algorithms, Signal Transduction

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Average
Top 10%
Top 10%
Green
gold