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Stochastic Modelling in Life Sciences

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Inference for Diffusion Processes

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Abstract

Key mechanisms in life sciences can often be assessed by application of mathematical models. Moreover, real-world phenomena can particularly be captured when such a model allows for random events. This chapter motivates and reviews representative application fields from life sciences and appropriate mathematical models: for the spread of infectious diseases and for processes in molecular biology, biochemistry and genetics. These applications and models recur throughout the entire book. The chapter describes the dynamical evolution of the considered systems in terms of three established types of processes: stochastic jump processes, deterministic state-continuous processes and stochastic diffusion processes. Simulation of such models is explained, and the important role of randomness is discussed.

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Authors and Affiliations

  1. Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany

    Christiane Fuchs

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  1. Christiane Fuchs
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Fuchs, C. (2013). Stochastic Modelling in Life Sciences. In: Inference for Diffusion Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25969-2_2

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