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Time Hierarchies and Model Reduction in Canonical Non-linear Models

The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the...

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Autores principales: Löwe, Hannes, Kremling, Andreas, Marin-Sanguino, Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5030239/
https://www.ncbi.nlm.nih.gov/pubmed/27708665
http://dx.doi.org/10.3389/fgene.2016.00166
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author Löwe, Hannes
Kremling, Andreas
Marin-Sanguino, Alberto
author_facet Löwe, Hannes
Kremling, Andreas
Marin-Sanguino, Alberto
author_sort Löwe, Hannes
collection PubMed
description The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems.
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spelling pubmed-50302392016-10-05 Time Hierarchies and Model Reduction in Canonical Non-linear Models Löwe, Hannes Kremling, Andreas Marin-Sanguino, Alberto Front Genet Genetics The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems. Frontiers Media S.A. 2016-09-21 /pmc/articles/PMC5030239/ /pubmed/27708665 http://dx.doi.org/10.3389/fgene.2016.00166 Text en Copyright © 2016 Löwe, Kremling and Marin-Sanguino. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Löwe, Hannes
Kremling, Andreas
Marin-Sanguino, Alberto
Time Hierarchies and Model Reduction in Canonical Non-linear Models
title Time Hierarchies and Model Reduction in Canonical Non-linear Models
title_full Time Hierarchies and Model Reduction in Canonical Non-linear Models
title_fullStr Time Hierarchies and Model Reduction in Canonical Non-linear Models
title_full_unstemmed Time Hierarchies and Model Reduction in Canonical Non-linear Models
title_short Time Hierarchies and Model Reduction in Canonical Non-linear Models
title_sort time hierarchies and model reduction in canonical non-linear models
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5030239/
https://www.ncbi.nlm.nih.gov/pubmed/27708665
http://dx.doi.org/10.3389/fgene.2016.00166
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