MAPK's networks and their capacity for multistationarity due to toric steady states
- Autores
- Pérez Millán, Mercedes Soledad; Turjanski, Adrian
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Mitogen-activated protein kinase (MAPK) signaling pathways play an essential role in the transduction of environmental stimuli to the nucleus, thereby regulating a variety of cellular processes, including cell proliferation, differentiation and programmed cell death. The components of the MAPK extracellular activated protein kinase (ERK) cascade represent attractive targets for cancer therapy as their aberrant activation is a frequent event among highly prevalent human cancers. MAPK networks are a model for computational simulation, mostly using ordinary and partial differential equations. Key results showed that these networks can have switch-like behavior, bistability and oscillations. In this work, we consider three representative ERK networks, one with a negative feedback loop, which present a binomial steady state ideal under mass-action kinetics. We therefore apply the theoretical result present in [27] to find a set of rate constants that allow two significantly different stable steady states in the same stoichiometric compatibility class for each network. Our approach makes it possible to study certain aspects of the system, such as multistationarity, without relying on simulation, since we do not assume a priori any constant but the topology of the network. As the performed analysis is general it could be applied to many other important biochemical networks.
Fil: Pérez Millán, Mercedes Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Universidad de Buenos Aires. Ciclo Básico Común; Argentina
Fil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina - Materia
-
MAPK
MASS-ACTION KINETICS
MULTISTATIONARITY
SIGNALING NETWORKS
TORIC STEADY STATES - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/182511
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MAPK's networks and their capacity for multistationarity due to toric steady statesPérez Millán, Mercedes SoledadTurjanski, AdrianMAPKMASS-ACTION KINETICSMULTISTATIONARITYSIGNALING NETWORKSTORIC STEADY STATEShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Mitogen-activated protein kinase (MAPK) signaling pathways play an essential role in the transduction of environmental stimuli to the nucleus, thereby regulating a variety of cellular processes, including cell proliferation, differentiation and programmed cell death. The components of the MAPK extracellular activated protein kinase (ERK) cascade represent attractive targets for cancer therapy as their aberrant activation is a frequent event among highly prevalent human cancers. MAPK networks are a model for computational simulation, mostly using ordinary and partial differential equations. Key results showed that these networks can have switch-like behavior, bistability and oscillations. In this work, we consider three representative ERK networks, one with a negative feedback loop, which present a binomial steady state ideal under mass-action kinetics. We therefore apply the theoretical result present in [27] to find a set of rate constants that allow two significantly different stable steady states in the same stoichiometric compatibility class for each network. Our approach makes it possible to study certain aspects of the system, such as multistationarity, without relying on simulation, since we do not assume a priori any constant but the topology of the network. As the performed analysis is general it could be applied to many other important biochemical networks.Fil: Pérez Millán, Mercedes Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Universidad de Buenos Aires. Ciclo Básico Común; ArgentinaFil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaElsevier Science Inc.2015-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/182511Pérez Millán, Mercedes Soledad; Turjanski, Adrian; MAPK's networks and their capacity for multistationarity due to toric steady states; Elsevier Science Inc.; Mathematical Biosciences; 262; 4-2015; 125-1370025-5564CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0025556415000152info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mbs.2014.12.010info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:51:25Zoai:ri.conicet.gov.ar:11336/182511instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:51:25.41CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
MAPK's networks and their capacity for multistationarity due to toric steady states |
title |
MAPK's networks and their capacity for multistationarity due to toric steady states |
spellingShingle |
MAPK's networks and their capacity for multistationarity due to toric steady states Pérez Millán, Mercedes Soledad MAPK MASS-ACTION KINETICS MULTISTATIONARITY SIGNALING NETWORKS TORIC STEADY STATES |
title_short |
MAPK's networks and their capacity for multistationarity due to toric steady states |
title_full |
MAPK's networks and their capacity for multistationarity due to toric steady states |
title_fullStr |
MAPK's networks and their capacity for multistationarity due to toric steady states |
title_full_unstemmed |
MAPK's networks and their capacity for multistationarity due to toric steady states |
title_sort |
MAPK's networks and their capacity for multistationarity due to toric steady states |
dc.creator.none.fl_str_mv |
Pérez Millán, Mercedes Soledad Turjanski, Adrian |
author |
Pérez Millán, Mercedes Soledad |
author_facet |
Pérez Millán, Mercedes Soledad Turjanski, Adrian |
author_role |
author |
author2 |
Turjanski, Adrian |
author2_role |
author |
dc.subject.none.fl_str_mv |
MAPK MASS-ACTION KINETICS MULTISTATIONARITY SIGNALING NETWORKS TORIC STEADY STATES |
topic |
MAPK MASS-ACTION KINETICS MULTISTATIONARITY SIGNALING NETWORKS TORIC STEADY STATES |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Mitogen-activated protein kinase (MAPK) signaling pathways play an essential role in the transduction of environmental stimuli to the nucleus, thereby regulating a variety of cellular processes, including cell proliferation, differentiation and programmed cell death. The components of the MAPK extracellular activated protein kinase (ERK) cascade represent attractive targets for cancer therapy as their aberrant activation is a frequent event among highly prevalent human cancers. MAPK networks are a model for computational simulation, mostly using ordinary and partial differential equations. Key results showed that these networks can have switch-like behavior, bistability and oscillations. In this work, we consider three representative ERK networks, one with a negative feedback loop, which present a binomial steady state ideal under mass-action kinetics. We therefore apply the theoretical result present in [27] to find a set of rate constants that allow two significantly different stable steady states in the same stoichiometric compatibility class for each network. Our approach makes it possible to study certain aspects of the system, such as multistationarity, without relying on simulation, since we do not assume a priori any constant but the topology of the network. As the performed analysis is general it could be applied to many other important biochemical networks. Fil: Pérez Millán, Mercedes Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Universidad de Buenos Aires. Ciclo Básico Común; Argentina Fil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina |
description |
Mitogen-activated protein kinase (MAPK) signaling pathways play an essential role in the transduction of environmental stimuli to the nucleus, thereby regulating a variety of cellular processes, including cell proliferation, differentiation and programmed cell death. The components of the MAPK extracellular activated protein kinase (ERK) cascade represent attractive targets for cancer therapy as their aberrant activation is a frequent event among highly prevalent human cancers. MAPK networks are a model for computational simulation, mostly using ordinary and partial differential equations. Key results showed that these networks can have switch-like behavior, bistability and oscillations. In this work, we consider three representative ERK networks, one with a negative feedback loop, which present a binomial steady state ideal under mass-action kinetics. We therefore apply the theoretical result present in [27] to find a set of rate constants that allow two significantly different stable steady states in the same stoichiometric compatibility class for each network. Our approach makes it possible to study certain aspects of the system, such as multistationarity, without relying on simulation, since we do not assume a priori any constant but the topology of the network. As the performed analysis is general it could be applied to many other important biochemical networks. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-04 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/182511 Pérez Millán, Mercedes Soledad; Turjanski, Adrian; MAPK's networks and their capacity for multistationarity due to toric steady states; Elsevier Science Inc.; Mathematical Biosciences; 262; 4-2015; 125-137 0025-5564 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/182511 |
identifier_str_mv |
Pérez Millán, Mercedes Soledad; Turjanski, Adrian; MAPK's networks and their capacity for multistationarity due to toric steady states; Elsevier Science Inc.; Mathematical Biosciences; 262; 4-2015; 125-137 0025-5564 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0025556415000152 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mbs.2014.12.010 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science Inc. |
publisher.none.fl_str_mv |
Elsevier Science Inc. |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844613580534579200 |
score |
13.070432 |