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Stochastic Simulators

Encyclopedia of Computational Neuroscience

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Definition

A stochastic simulator for reaction–diffusion systems is a computer simulation tool that uses the Monte Carlo method to generate the time evolution of a spatially inhomogeneous chemically reacting system. The stochastic simulation algorithm (SSA) formulated by Dan Gillespie in 1976 numerically simulates the time evolution of a well-stirred chemically reacting system in a thermal equilibrium by defining the state of the system to be the integer numbers of molecular populations. The SSA has been extended to incorporate diffusion, usually called the spatial SSA, by dividing the spatial domain into a collection of well-stirred subvolumes and treating diffusion between neighboring subvolumes as a set of first-order reactions. This entry focuses on stochastic simulators that use the spatial SSA.

Detailed Description

The small numbers and heterogeneous distribution of molecular species in biological cells give rise to stochastic variations in intracellular microdomains and...

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Author information

Authors and Affiliations

  1. School of Computing, College of Science and Technology, University of Southern Mississippi, Hattiesburg, MS, USA

    Wonryull Koh

  2. Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA

    Kim T. Blackwell

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  1. Wonryull Koh
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  2. Kim T. Blackwell
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Correspondence to Wonryull Koh .

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Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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Koh, W., Blackwell, K.T. (2014). Stochastic Simulators. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_196-2

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_196-2

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Chapter history

  1. Latest

    Stochastic Simulators
    Published:
    13 December 2019

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_196-3

  2. Stochastic Simulators
    Published:
    19 May 2014

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_196-2

  3. Original

    Stochastic Simulators
    Published:
    15 March 2014

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_196-1

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