A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves

16 páginas, 8 figuras, 4 tablas.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly...

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Autores: Otero-Muras, Irene, Yardonov, P., Stelling, Joerg
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/110320
Acceso en línea:http://hdl.handle.net/10261/110320
Access Level:acceso abierto
Palabra clave:Biochemical reaction network
Bistability
Saddle node bifurcation
Dose response curve
Chemical reaction network theory
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spelling A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curvesOtero-Muras, IreneYardonov, P.Stelling, JoergBiochemical reaction networkBistabilitySaddle node bifurcationDose response curveChemical reaction network theory16 páginas, 8 figuras, 4 tablas.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited[Background] Within cells, stimuli are transduced into cell responses by complex networks of biochemical reactions. In many cell decision processes the underlying networks behave as bistable switches, converting graded stimuli or inputs into all or none cell responses. Observing how systems respond to different perturbations, insight can be gained into the underlying molecular mechanisms by developing mathematical models. Emergent properties of systems, like bistability, can be exploited to this purpose. One of the main challenges in modeling intracellular processes, from signaling pathways to gene regulatory networks, is to deal with high structural and parametric uncertainty, due to the complexity of the systems and the difficulty to obtain experimental measurements. Formal methods that exploit structural properties of networks for parameter estimation can help to overcome these problems.[Results] We here propose a novel method to infer the kinetic parameters of bistable biochemical network models. Bistable systems typically show hysteretic dose response curves, in which the so called bifurcation points can be located experimentally. We exploit the fact that, at the bifurcation points, a condition for multistationarity derived in the context of the Chemical Reaction Network Theory must be fulfilled. Chemical Reaction Network Theory has attracted attention from the (systems) biology community since it connects the structure of biochemical reaction networks to qualitative properties of the corresponding model of ordinary differential equations. The inverse bifurcation method developed here allows determining the parameters that produce the expected behavior of the dose response curves and, in particular, the observed location of the bifurcation points given by experimental data.[Conclusions] Our inverse bifurcation method exploits inherent structural properties of bistable switches in order to estimate kinetic parameters of bistable biochemical networks, opening a promising route for developments in Chemical Reaction Network Theory towards kinetic model identification.We gratefully acknowledge financial support from the EU FP7 project IFNAction (contract 223608)Peer reviewedBioMed CentralEuropean CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]201520152014info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/110320reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/FP7/223608http://dx.doi.org/10.1186/s12918-014-0114-2Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1103202026-05-22T06:33:51Z
dc.title.none.fl_str_mv A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
title A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
spellingShingle A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
Otero-Muras, Irene
Biochemical reaction network
Bistability
Saddle node bifurcation
Dose response curve
Chemical reaction network theory
title_short A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
title_full A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
title_fullStr A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
title_full_unstemmed A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
title_sort A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves
dc.creator.none.fl_str_mv Otero-Muras, Irene
Yardonov, P.
Stelling, Joerg
author Otero-Muras, Irene
author_facet Otero-Muras, Irene
Yardonov, P.
Stelling, Joerg
author_role author
author2 Yardonov, P.
Stelling, Joerg
author2_role author
author
dc.contributor.none.fl_str_mv European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Biochemical reaction network
Bistability
Saddle node bifurcation
Dose response curve
Chemical reaction network theory
topic Biochemical reaction network
Bistability
Saddle node bifurcation
Dose response curve
Chemical reaction network theory
description 16 páginas, 8 figuras, 4 tablas.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited
publishDate 2014
dc.date.none.fl_str_mv 2014
2015
2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/110320
url http://hdl.handle.net/10261/110320
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/FP7/223608
http://dx.doi.org/10.1186/s12918-014-0114-2
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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