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  Chemical reaction network approaches to Biochemical Systems Theory

Arceo, C. P. P., Jose, E. C., Marin-Sanguino, A., & Mendoza, E. R. (2015). Chemical reaction network approaches to Biochemical Systems Theory. MATHEMATICAL BIOSCIENCES, 269, 135-152. doi:10.1016/j.mbs.2015.08.022.

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Arceo, Carlene Perpetua P.1, Author
Jose, Editha C.1, Author
Marin-Sanguino, Alberto1, Author
Mendoza, Eduardo R.2, Author              
Affiliations:
1external, ou_persistent22              
2Oesterhelt, Dieter / Membrane Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565164              

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Free keywords: MASS-ACTION KINETICS; MULTIPLE EQUILIBRIA; PRECLUSION; GRAPHChemical reaction network; Generalized mass action; Reactant-determined kinetics; Complex balanced steady states; Complex factorizable kinetics;
 Abstract: This paper provides a framework to represent a Biochemical Systems Theory (BST) model (in either GMA or S-system form) as a chemical reaction network with power law kinetics. Using this representation, some basic properties and the application of recent results of Chemical Reaction Network Theory regarding steady states of such systems are shown. In particular, Injectivity Theory, including network concordance [36] and the Jacobian Determinant Criterion [43], a "Lifting Theorem" for steady states [26] and the comprehensive results of Muller and Regensburger [31] on complex balanced equilibria are discussed. A partial extension of a recent Emulation Theorem of Cardelli for mass action systems [3] is derived for a subclass of power law kinetic systems. However, it is also shown that the GMA and S-system models of human purine metabolism [10] do not display the reactant-determined kinetics assumed by Muller and Regensburger and hence only a subset of BST models can be handled with their approach. Moreover, since the reaction networks underlying many BST models are not weakly reversible, results for non-complex balanced equilibria are also needed. (C) 2015 Elsevier Inc. All rights reserved.

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Language(s): eng - English
 Dates: 2015
 Publication Status: Published in print
 Pages: 18
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000364437200014
DOI: 10.1016/j.mbs.2015.08.022
 Degree: -

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Title: MATHEMATICAL BIOSCIENCES
Source Genre: Journal
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Publ. Info: 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA : ELSEVIER SCIENCE INC
Pages: - Volume / Issue: 269 Sequence Number: - Start / End Page: 135 - 152 Identifier: ISSN: 0025-5564