Literature DB >> 29601834

Node balanced steady states: Unifying and generalizing complex and detailed balanced steady states.

Elisenda Feliu1, Daniele Cappelletti2, Carsten Wiuf3.   

Abstract

We introduce a unifying and generalizing framework for complex and detailed balanced steady states in chemical reaction network theory. To this end, we generalize the graph commonly used to represent a reaction network. Specifically, we introduce a graph, called a reaction graph, that has one edge for each reaction but potentially multiple nodes for each complex. A special class of steady states, called node balanced steady states, is naturally associated with such a reaction graph. We show that complex and detailed balanced steady states are special cases of node balanced steady states by choosing appropriate reaction graphs. Further, we show that node balanced steady states have properties analogous to complex balanced steady states, such as uniqueness and asymptotic stability in each stoichiometric compatibility class. Moreover, we associate an integer, called the deficiency, to a reaction graph that gives the number of independent relations in the reaction rate constants that need to be satisfied for a positive node balanced steady state to exist. The set of reaction graphs (modulo isomorphism) is equipped with a partial order that has the complex balanced reaction graph as minimal element. We relate this order to the deficiency and to the set of reaction rate constants for which a positive node balanced steady state exists.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Asymptotic stability; Deficiency; Matrix-tree theorem; Reaction graph; Reaction networks

Mesh:

Year:  2018        PMID: 29601834     DOI: 10.1016/j.mbs.2018.03.002

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  1 in total

1.  A hidden integral structure endows absolute concentration robust systems with resilience to dynamical concentration disturbances.

Authors:  Daniele Cappelletti; Ankit Gupta; Mustafa Khammash
Journal:  J R Soc Interface       Date:  2020-10-28       Impact factor: 4.118

  1 in total

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