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dc.contributor.author
Pérez Millán, Mercedes Soledad
dc.contributor.author
Turjanski, Adrian
dc.date.available
2022-12-27T14:18:31Z
dc.date.issued
2015-04
dc.identifier.citation
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
dc.identifier.issn
0025-5564
dc.identifier.uri
http://hdl.handle.net/11336/182511
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science Inc.
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
MAPK
dc.subject
MASS-ACTION KINETICS
dc.subject
MULTISTATIONARITY
dc.subject
SIGNALING NETWORKS
dc.subject
TORIC STEADY STATES
dc.subject.classification
Ciencias de la Información y Bioinformática
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
MAPK's networks and their capacity for multistationarity due to toric steady states
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-12-27T11:08:43Z
dc.journal.volume
262
dc.journal.pagination
125-137
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
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
dc.description.fil
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
dc.journal.title
Mathematical Biosciences
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0025556415000152
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.mbs.2014.12.010
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