Reaction networks and kinetics of biochemical systems
This paper further develops the connection between Chemical Reaction Network Theory (CRNT) and Biochemical Systems Theory (BST) that we recently introduced [1]. We first use algebraic properties of kinetic sets to study the set of complex factorizable kinetics CFK(N) on a CRN, which shares many char...
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oai:animorepository.dlsu.edu.ph:faculty_research-36162021-10-20T01:04:20Z Reaction networks and kinetics of biochemical systems Arceo, Carlene Perpetua P. Jose, Editha C. Lao, Angelyn R. Mendoza, Eduardo R. This paper further develops the connection between Chemical Reaction Network Theory (CRNT) and Biochemical Systems Theory (BST) that we recently introduced [1]. We first use algebraic properties of kinetic sets to study the set of complex factorizable kinetics CFK(N) on a CRN, which shares many characteristics with its subset of mass action kinetics. In particular, we extend the Theorem of Feinberg-Horn [9] on the coincidence of the kinetic and stoichiometric subsets of a mass action system to CF kinetics, using the concept of span surjectivity. We also introduce the branching type of a network, which determines the availability of kinetics on it and allows us to characterize the networks for which all kinetics are complex factorizable: A “Kinetics Landscape” provides an overview of kinetics sets, their algebraic properties and containment relationships. We then apply our results and those (of other CRNT researchers) reviewed in [1] to fifteen BST models of complex biological systems and discover novel network and kinetic properties that so far have not been widely studied in CRNT. In our view, these findings show an important benefit of connecting CRNT and BST modeling efforts. © 2016 Elsevier Inc. 2017-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/2617 Faculty Research Work Animo Repository Chemical kinetics Dynamics Biochemistry Mathematics Physical Sciences and Mathematics |
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Chemical kinetics Dynamics Biochemistry Mathematics Physical Sciences and Mathematics Arceo, Carlene Perpetua P. Jose, Editha C. Lao, Angelyn R. Mendoza, Eduardo R. Reaction networks and kinetics of biochemical systems |
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This paper further develops the connection between Chemical Reaction Network Theory (CRNT) and Biochemical Systems Theory (BST) that we recently introduced [1]. We first use algebraic properties of kinetic sets to study the set of complex factorizable kinetics CFK(N) on a CRN, which shares many characteristics with its subset of mass action kinetics. In particular, we extend the Theorem of Feinberg-Horn [9] on the coincidence of the kinetic and stoichiometric subsets of a mass action system to CF kinetics, using the concept of span surjectivity. We also introduce the branching type of a network, which determines the availability of kinetics on it and allows us to characterize the networks for which all kinetics are complex factorizable: A “Kinetics Landscape” provides an overview of kinetics sets, their algebraic properties and containment relationships. We then apply our results and those (of other CRNT researchers) reviewed in [1] to fifteen BST models of complex biological systems and discover novel network and kinetic properties that so far have not been widely studied in CRNT. In our view, these findings show an important benefit of connecting CRNT and BST modeling efforts. © 2016 Elsevier Inc. |
format |
text |
author |
Arceo, Carlene Perpetua P. Jose, Editha C. Lao, Angelyn R. Mendoza, Eduardo R. |
author_facet |
Arceo, Carlene Perpetua P. Jose, Editha C. Lao, Angelyn R. Mendoza, Eduardo R. |
author_sort |
Arceo, Carlene Perpetua P. |
title |
Reaction networks and kinetics of biochemical systems |
title_short |
Reaction networks and kinetics of biochemical systems |
title_full |
Reaction networks and kinetics of biochemical systems |
title_fullStr |
Reaction networks and kinetics of biochemical systems |
title_full_unstemmed |
Reaction networks and kinetics of biochemical systems |
title_sort |
reaction networks and kinetics of biochemical systems |
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Animo Repository |
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2017 |
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https://animorepository.dlsu.edu.ph/faculty_research/2617 |
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