Abstract
Conventional deterministic chemical kinetics often breaks down in the small volume of a living cell where cellular species (e.g., genes, mRNAs, etc.) exist in discrete, low copy numbers and react through reaction channels whose timing and order is random. In such an environment, a stochastic chemical kinetics framework that models species abundances as discrete random variables is more suitable. The resulting models consist of continue-time discrete-state Markov chains. Here we describe how such models can be formulated and numerically simulated, and we present some of the key analysis techniques for studying such reactions.
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Hespanha, J.P., Khammash, M. (2014). Stochastic Description of Biochemical Networks. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_88-1
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_88-1
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Online ISBN: 978-1-4471-5102-9
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