NDLI: Chemical Organisation Theory

Content Provider	Springer Nature Link
Author	Dittrich, Peter di Fenizio, Pietro Speroni
Copyright Year	2007
Abstract	Complex dynamical reaction networks consisting of many components that interact and produce each other are difficult to understand, especially, when new component types may appear and present component types may vanish completely. Inspired by Fontana and Buss (Bull. Math. Biol., 56, 1–64) we outline a theory to deal with such systems. The theory consists of two parts. The first part introduces the concept of a chemical organisation as a closed and self-maintaining set of components. This concept allows to map a complex (reaction) network to the set of organisations, providing a new view on the system’s structure. The second part connects dynamics with the set of organisations, which allows to map a movement of the system in state space to a movement in the set of organisations. The relevancy of our theory is underlined by a theorem that says that given a differential equation describing the chemical dynamics of the network, then every stationary state is an instance of an organisation. For demonstration, the theory is applied to a small model of HIV-immune system interaction by Wodarz and Nowak (Proc. Natl. Acad. USA, 96, 14464–14469) and to a large model of the sugar metabolism of E. Coli by Puchalka and Kierzek (Biophys. J., 86, 1357–1372). In both cases organisations where uncovered, which could be related to functions.
Starting Page	1199
Ending Page	1231
Page Count	33
File Format	PDF
ISSN	00928240
Journal	Bulletin of Mathematical Biology
Volume Number	69
Issue Number	4
e-ISSN	15229602
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-04-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Reaction networks Constraint based network analysis Hierarchical decomposition Constructive dynamical systems Mathematical Biology in General
Content Type	Text
Resource Type	Article
Subject	Neuroscience Biochemistry, Genetics and Molecular Biology Mathematics Pharmacology Immunology Computational Theory and Mathematics Environmental Science Agricultural and Biological Sciences

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