Hybrid Spatial Gillespie and Particle Tracking Simulation

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2012 Sep 11

PMID 22962480

Citations 11

Authors

Michael Klann

Arnab Ganguly

Heinz Koeppl

Affiliations

Soon will be listed here.

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.

Citing Articles

The blending region hybrid framework for the simulation of stochastic reaction-diffusion processes.

Yates C, George A, Jordana A, Smith C, Duncan A, Zygalakis K J R Soc Interface. 2020; 17(171):20200563.

PMID: 33081647 PMC: 7653393. DOI: 10.1098/rsif.2020.0563.

Stochastic self-tuning hybrid algorithm for reaction-diffusion systems.

Ruiz-Martinez A, Bartol T, Sejnowski T, Tartakovsky D J Chem Phys. 2020; 151(24):244117.

PMID: 31893874 PMC: 7341680. DOI: 10.1063/1.5125022.

Potential based, spatial simulation of dynamically nested particles.

Koster T, Henning P, Uhrmacher A BMC Bioinformatics. 2019; 20(1):607.

PMID: 31775608 PMC: 6880518. DOI: 10.1186/s12859-019-3092-y.

Multiscale Stochastic Reaction-Diffusion Algorithms Combining Markov Chain Models with Stochastic Partial Differential Equations.

Kang H, Erban R Bull Math Biol. 2019; 81(8):3185-3213.

PMID: 31165406 PMC: 6677718. DOI: 10.1007/s11538-019-00613-0.

Spatially extended hybrid methods: a review.

Smith C, Yates C J R Soc Interface. 2018; 15(139).

PMID: 29491179 PMC: 5832735. DOI: 10.1098/rsif.2017.0931.

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