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Multiscale stochastic modelling of gene expression

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Abstract

Stochastic phenomena in gene regulatory networks can be modelled by the chemical master equation for gene products such as mRNA and proteins. If some of these elements are present in significantly higher amounts than the rest, or if some of the reactions between these elements are substantially faster than others, it is often possible to reduce the master equation to a simpler problem using asymptotic methods. We present examples of such a procedure and analyse the relationship between the reduced models and the original.

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Author notes

  1. Pavol Bokes

    Present address: Department of Applied Mathematics and Statistics, Comenius University, Mlynská dolina, Bratislava, 842 48, Slovakia

Authors and Affiliations

  1. Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK

    Pavol Bokes, John R. King & Andrew T. A. Wood

  2. Institute of Genetics, Queen’s Medical Centre, University of Nottingham, Nottingham, NG7 2UH, UK

    Matthew Loose

Authors
  1. Pavol Bokes
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  2. John R. King
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  3. Andrew T. A. Wood
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  4. Matthew Loose
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Correspondence to Pavol Bokes.

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Bokes, P., King, J.R., Wood, A.T.A. et al. Multiscale stochastic modelling of gene expression. J. Math. Biol. 65, 493–520 (2012). https://doi.org/10.1007/s00285-011-0468-7

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  • DOI: https://doi.org/10.1007/s00285-011-0468-7

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