Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton

A theory for diffusivity estimation for spatially extended activator–inhibitor dynamics modeling the evolution of intracellular signaling networks is developed in the math- ematical framework of stochastic reaction–diffusion systems. In order to account for model uncertainties, we extend the results...

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Detalles Bibliográficos
Autores: Flemming, Sven, Alonso Muñoz, Sergio|||0000-0002-3989-8757, Beta, Carsten
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/359850
Acceso en línea:https://hdl.handle.net/2117/359850
https://dx.doi.org/10.1007/s00332-021-09714-4
Access Level:acceso abierto
Palabra clave:Cytoskeleton
Parametric drift estimation
Stochastic reaction–diffusion systems
Maximum likelihood estimation
Actin cytoskeleton dynamics
Difusió (Física)
Àrees temàtiques de la UPC::Física::Física molecular::Espectroscòpia molecular
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repository_id_str
spelling Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeletonFlemming, SvenAlonso Muñoz, Sergio|||0000-0002-3989-8757Beta, CarstenCytoskeletonParametric drift estimationStochastic reaction–diffusion systemsMaximum likelihood estimationActin cytoskeleton dynamicsDifusió (Física)Àrees temàtiques de la UPC::Física::Física molecular::Espectroscòpia molecularA theory for diffusivity estimation for spatially extended activator–inhibitor dynamics modeling the evolution of intracellular signaling networks is developed in the math- ematical framework of stochastic reaction–diffusion systems. In order to account for model uncertainties, we extend the results for parameter estimation for semilinear stochastic partial differential equationsSpringer Nature20212021-06-0120222022-01-17journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/359850https://dx.doi.org/10.1007/s00332-021-09714-4reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PGC2018-095456-B-I00 COMPUTATIONAL MODELLING OF BIOPHYSICAL PROCESSES AT MULTIPLE SCALESopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3598502026-05-27T15:37:01Z
dc.title.none.fl_str_mv Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
title Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
spellingShingle Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
Flemming, Sven
Cytoskeleton
Parametric drift estimation
Stochastic reaction–diffusion systems
Maximum likelihood estimation
Actin cytoskeleton dynamics
Difusió (Física)
Àrees temàtiques de la UPC::Física::Física molecular::Espectroscòpia molecular
title_short Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
title_full Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
title_fullStr Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
title_full_unstemmed Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
title_sort Diffusivity estimation for activator–inhibitor models: theory and application to intracellular dynamics of the actin cytoskeleton
dc.creator.none.fl_str_mv Flemming, Sven
Alonso Muñoz, Sergio|||0000-0002-3989-8757
Beta, Carsten
author Flemming, Sven
author_facet Flemming, Sven
Alonso Muñoz, Sergio|||0000-0002-3989-8757
Beta, Carsten
author_role author
author2 Alonso Muñoz, Sergio|||0000-0002-3989-8757
Beta, Carsten
author2_role author
author
dc.subject.none.fl_str_mv Cytoskeleton
Parametric drift estimation
Stochastic reaction–diffusion systems
Maximum likelihood estimation
Actin cytoskeleton dynamics
Difusió (Física)
Àrees temàtiques de la UPC::Física::Física molecular::Espectroscòpia molecular
topic Cytoskeleton
Parametric drift estimation
Stochastic reaction–diffusion systems
Maximum likelihood estimation
Actin cytoskeleton dynamics
Difusió (Física)
Àrees temàtiques de la UPC::Física::Física molecular::Espectroscòpia molecular
description A theory for diffusivity estimation for spatially extended activator–inhibitor dynamics modeling the evolution of intracellular signaling networks is developed in the math- ematical framework of stochastic reaction–diffusion systems. In order to account for model uncertainties, we extend the results for parameter estimation for semilinear stochastic partial differential equations
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-06-01
2022
2022-01-17
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/359850
https://dx.doi.org/10.1007/s00332-021-09714-4
url https://hdl.handle.net/2117/359850
https://dx.doi.org/10.1007/s00332-021-09714-4
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PGC2018-095456-B-I00 COMPUTATIONAL MODELLING OF BIOPHYSICAL PROCESSES AT MULTIPLE SCALES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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