1987
DOI: 10.1016/0025-5564(87)90035-6
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Recasting nonlinear differential equations as S-systems: a canonical nonlinear form

Abstract: An enormous variety of nonlinear differential equations and functions have been recast exactly in the canonical form called an S-system. This is a system of nonlinear ordinary differential equations, each with the same structure: the change in a variable is equal to a difference of products of power-law functions. We review the development of S-systems, prove that the minimum for the range of equations that can be recast as S-systems consists of all equations composed of elementary functions and nested element… Show more

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Cited by 268 publications
(169 citation statements)
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“…We can reformulate the problem using the convenient terminology from systems biology [11] for which the number…”
Section: Recasting and The Minimum Degree Problemmentioning
confidence: 99%
“…We can reformulate the problem using the convenient terminology from systems biology [11] for which the number…”
Section: Recasting and The Minimum Degree Problemmentioning
confidence: 99%
“…In the domain of chemistry, they can directly represent (or be slightly modified to represent) all the common reaction types. They form the basis of S-systems (Savageau and Voit 1987) and are well characterised in biochemical simulations. The basic rate equation is described by Eq.…”
Section: Basic Formulationmentioning
confidence: 99%
“…Our previous paper provides a complete description, and verification of the ARNs accuracy and biological plausibility [1] There are many methods used to model biochemical reactions, some are very simple Boolean-based techniques, others complex quantum mechanical abstractions [13], here the two most relevant adopted techniques are described. The first is S-Systems; these have proven themselves accurate and provide a similar degree of system abstraction to an ANN.…”
Section: Techniques Used To Develop Modelmentioning
confidence: 99%
“…The first is S-Systems; these have proven themselves accurate and provide a similar degree of system abstraction to an ANN. They comprise sets of ordinary differential equations (ODEs) that exploit a power law representation to approximate chemical flux [13]. Similarly to traditional rate law [13], each ODE is equal to the difference between two conceptually distinct functions; the first function includes all terms contributing to system influx, the second to decay.…”
Section: Techniques Used To Develop Modelmentioning
confidence: 99%
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