A unique transformation from ordinary differential equations to reaction networks.

Many models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available. Complementary structure-related qualitative analysis techniques have become increasingly popular in rec...

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Main Authors: Sylvain Soliman, Monika Heiner
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3008708?pdf=render
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spelling doaj-b6e0ba79dddb4de7b4a4af70da68a0422020-11-25T00:07:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-01-01512e1428410.1371/journal.pone.0014284A unique transformation from ordinary differential equations to reaction networks.Sylvain SolimanMonika HeinerMany models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available. Complementary structure-related qualitative analysis techniques have become increasingly popular in recent years, like qualitative model checking or pathway analysis (elementary modes, invariants, flux balance analysis, graph-based analyses, chemical organization theory, etc.). They do not rely on kinetic information but require a well-defined structure as stochastic analysis techniques equally do. In this article, we look into the structure inference problem for a model described by a system of Ordinary Differential Equations and provide conditions for the uniqueness of its solution. We describe a method to extract a structured reaction network model, represented as a bipartite multigraph, for example, a continuous Petri net (CPN), from a system of Ordinary Differential Equations (ODEs). A CPN uniquely defines an ODE, and each ODE can be transformed into a CPN. However, it is not obvious under which conditions the transformation of an ODE into a CPN is unique, that is, when a given ODE defines exactly one CPN. We provide biochemically relevant sufficient conditions under which the derived structure is unique and counterexamples showing the necessity of each condition. Our method is implemented and available; we illustrate it on some signal transduction models from the BioModels database. A prototype implementation of the method is made available to modellers at http://contraintes.inria.fr/~soliman/ode2pn.html, and the data mentioned in the "Results" section at http://contraintes.inria.fr/~soliman/ode2pn_data/. Our results yield a new recommendation for the import/export feature of tools supporting the SBML exchange format.http://europepmc.org/articles/PMC3008708?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Sylvain Soliman
Monika Heiner
spellingShingle Sylvain Soliman
Monika Heiner
A unique transformation from ordinary differential equations to reaction networks.
PLoS ONE
author_facet Sylvain Soliman
Monika Heiner
author_sort Sylvain Soliman
title A unique transformation from ordinary differential equations to reaction networks.
title_short A unique transformation from ordinary differential equations to reaction networks.
title_full A unique transformation from ordinary differential equations to reaction networks.
title_fullStr A unique transformation from ordinary differential equations to reaction networks.
title_full_unstemmed A unique transformation from ordinary differential equations to reaction networks.
title_sort unique transformation from ordinary differential equations to reaction networks.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-01-01
description Many models in Systems Biology are described as a system of Ordinary Differential Equations, which allows for transient, steady-state or bifurcation analysis when kinetic information is available. Complementary structure-related qualitative analysis techniques have become increasingly popular in recent years, like qualitative model checking or pathway analysis (elementary modes, invariants, flux balance analysis, graph-based analyses, chemical organization theory, etc.). They do not rely on kinetic information but require a well-defined structure as stochastic analysis techniques equally do. In this article, we look into the structure inference problem for a model described by a system of Ordinary Differential Equations and provide conditions for the uniqueness of its solution. We describe a method to extract a structured reaction network model, represented as a bipartite multigraph, for example, a continuous Petri net (CPN), from a system of Ordinary Differential Equations (ODEs). A CPN uniquely defines an ODE, and each ODE can be transformed into a CPN. However, it is not obvious under which conditions the transformation of an ODE into a CPN is unique, that is, when a given ODE defines exactly one CPN. We provide biochemically relevant sufficient conditions under which the derived structure is unique and counterexamples showing the necessity of each condition. Our method is implemented and available; we illustrate it on some signal transduction models from the BioModels database. A prototype implementation of the method is made available to modellers at http://contraintes.inria.fr/~soliman/ode2pn.html, and the data mentioned in the "Results" section at http://contraintes.inria.fr/~soliman/ode2pn_data/. Our results yield a new recommendation for the import/export feature of tools supporting the SBML exchange format.
url http://europepmc.org/articles/PMC3008708?pdf=render
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