Stochastic Modeling of Biochemical Networks

Mukhtar Ullah () and Olaf Wolkenhauer ()
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Mukhtar Ullah: University of Rostock, Department of Systems Biology and Bioinformatics Institute of Computer Science
Olaf Wolkenhauer: University of Rostock, Department of Systems Biology and Bioinformatics Institute of Computer Science

Chapter Chapter 5 in Stochastic Approaches for Systems Biology, 2011, pp 115-171 from Springer

Abstract: Abstract In this chapter, we present a stochastic framework for modeling subcellular biochemical reaction networks. In particular, we make an effort to show how the notion of propensity, the chemical master equation (CME), and the stochastic simulation algorithm arise as consequences of the Markov property. We would encourage the reader to pay attention to this, because it is not easy to see this connection when reading the relevant literature in systems biology. We review various analytical approximations of the CME, leaving out stochastic simulation approaches reviewed in [113, 155]. Moreover, we sketch interrelationships between various stochastic approaches. The books [114] and [165] inspired this chapter and can be referred to for further reading.

Keywords: Stochastic Simulation; Fano Factor; Biochemical Network; Volterra Model; State Transition Diagram (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-0478-1_5

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DOI: 10.1007/978-1-4614-0478-1_5

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