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Modelling Biological Systems

  • Michael A. B. Deakin
Part of the Mathematical Modelling book series (MMO, volume 6)

Abstract

Biological systems are complex systems, almost by definition. Thus models of such systems necessarily simplify. That even simple models can lead to very complicated behaviour leads us to re-examine the goal of mathematical modelling. We may distinguish two loose categories of model: the “pure” model whose end is the understanding of phenomena, and the “applied” model directed to their control. Central to both is the notion of prediction, and it is this that is seen to be likely to be possible only to a limited degree. These matters are further compounded by the corresponding difficulty in solving the inverse problem of inferring the model from the phenomena. This leads us to query the way in which we might seek to understand the system (in the pure case) and to control it (in the applied one).

Keywords

Chaotic System Dynamical System Theory Chaotic Phenomenon Competitive Exclusion Principle Simple Climatic Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Birkhäuser Boston 1990

Authors and Affiliations

  • Michael A. B. Deakin

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