Abstract
Traditionally, mathematical models of biological systems have mostly been phenomenological because of the difficulty of deriving a set of equations from first principles in the way that can typically be done in the physical sciences. Sometimes, attempts are made to fit a parametrised model to data, but the fit is usually very bad and all that is hoped for is a qualitative understanding. Recent work in dynamical systems theory has made it possible to construct non-parametric models directly from data. This paper describes a particular approach—embedding followed by tesselation—which appears able to capture the main features of some biological systems, and to provide a degree of quantitative predictive power.
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© 1990 Birkhäuser Boston
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Mees, A.I. (1990). Modelling Complex Systems. In: Vincent, T.L., Mees, A.I., Jennings, L.S. (eds) Dynamics of Complex Interconnected Biological Systems. Mathematical Modelling, vol 6. Birkhäuser Boston. https://doi.org/10.1007/978-1-4684-6784-0_6
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DOI: https://doi.org/10.1007/978-1-4684-6784-0_6
Publisher Name: Birkhäuser Boston
Print ISBN: 978-1-4684-6786-4
Online ISBN: 978-1-4684-6784-0
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