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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