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Stochastic Simulation for Spatial Modelling of Dynamic Processes in a Living Cell

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Design and Analysis of Biomolecular Circuits

Abstract

One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.

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Authors and Affiliations

  1. Computing Laboratory, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK

    Kevin Burrage

  2. Department of Mathematical Sciences, Queensland University of Technology, Brisbane, 4001, Australia

    Kevin Burrage

Authors
  1. Kevin Burrage
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  2. Pamela M. Burrage
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  3. André Leier
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  4. Tatiana Marquez-Lago
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  5. Dan V. Nicolau Jr
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Corresponding author

Correspondence to Kevin Burrage .

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Editors and Affiliations

  1. , Automatic Control Laboratory, ETH Zurich, Physikstrasse 3, Zurich, 8092, Switzerland

    Heinz Koeppl

  2. ARCES, Università di Bologna, Via Toffano 2/2, Bologna, 40125, Italy

    Gianluca Setti

  3. Università di Napoli Federico II, Via Claudio 21, Napoli, 80125, Italy

    Mario di Bernardo

  4. , Department of Electrical and Computer En, Boston University, Saint Mary's St. 8, Boston, 02446, Massachusetts, USA

    Douglas Densmore

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Burrage, K., Burrage, P.M., Leier, A., Marquez-Lago, T., Nicolau, D.V. (2011). Stochastic Simulation for Spatial Modelling of Dynamic Processes in a Living Cell. In: Koeppl, H., Setti, G., di Bernardo, M., Densmore, D. (eds) Design and Analysis of Biomolecular Circuits. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6766-4_2

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  • DOI: https://doi.org/10.1007/978-1-4419-6766-4_2

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