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Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is...

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Detalles Bibliográficos
Autores principales: Pang, Wei, Coghill, George M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Ireland 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441110/
https://www.ncbi.nlm.nih.gov/pubmed/25864377
http://dx.doi.org/10.1016/j.biosystems.2015.04.003
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author Pang, Wei
Coghill, George M.
author_facet Pang, Wei
Coghill, George M.
author_sort Pang, Wei
collection PubMed
description In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed.
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spelling pubmed-44411102015-05-23 Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast Pang, Wei Coghill, George M. Biosystems Article In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. Elsevier Science Ireland 2015-05 /pmc/articles/PMC4441110/ /pubmed/25864377 http://dx.doi.org/10.1016/j.biosystems.2015.04.003 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pang, Wei
Coghill, George M.
Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title_full Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title_fullStr Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title_full_unstemmed Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title_short Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
title_sort qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441110/
https://www.ncbi.nlm.nih.gov/pubmed/25864377
http://dx.doi.org/10.1016/j.biosystems.2015.04.003
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