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dc.contributor.author
Dickenstein, Alicia Marcela
dc.contributor.other
Cox, David
dc.date.available
2022-05-06T20:09:34Z
dc.date.issued
2020
dc.identifier.citation
Dickenstein, Alicia Marcela; Algebraic methods for the study of biochemical reaction networks; American Mathematical Society; 134; 2020; 222-233
dc.identifier.isbn
978-1-4704-5137-0
dc.identifier.uri
http://hdl.handle.net/11336/156851
dc.description.abstract
We will concentrate on biochemical reaction networks, of interest in systems biology, in particular enzymatic networks, consisting of different types of multisite phosphorylation networks. One source of inspiration for our study with algebro-geometric tools is the following quote from the abstract of the paper [44]:"Multisite phosphorylation cycles are ubiquitous in cell regulation systems andare studied at multiple levels of complexity, from molecules to organisms, withthe ultimate goal of establishing predictive understanding of the effects of geneticand pharmacological perturbations of protein phosphorylation in vivo. Achievingthis goal is essentially impossible without mathematical models, which providea systematic framework for exploring dynamic interactions of multiple networkcomponents."We will mainly concentrate on recent advances on the determination of multistationarity for these networks, whose dynamics are usually modeled with mass-action kinetics. For many classes of chemical networks, as the complex balanced networks, monostationarity is an important property. Instead, for biochemical reaction networks, that is, chemical reaction networks modeling pathways in systems biology, multistationarity is a general feature and it is important because it is intepreted as a way for the cell to take different decisions. Indeed, differential systems with mass-action kinetics are deterministic. But the occurrence of multiple stable steady states in the same stoichiometric compatibility class implies that trajectories starting from different initial conditions with the same conserved quantities can converge to steady states with different properties. We will end the chapter with some open questions.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Mathematical Society
dc.rights
info:eu-repo/semantics/closedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
REACTION NETWORKS
dc.subject
BIOCHEMISTRY
dc.subject
ALGEBRA
dc.subject
MULTISTATIONARITY
dc.subject.classification
Matemática Aplicada
dc.subject.classification
Matemáticas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Algebraic methods for the study of biochemical reaction networks
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/bookPart
dc.type
info:ar-repo/semantics/parte de libro
dc.date.updated
2021-07-30T18:58:50Z
dc.journal.volume
134
dc.journal.pagination
222-233
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Dickenstein, Alicia Marcela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://bookstore.ams.org/cbms-134#:~:text=Examples%20in%20the%20book%20include,constraint%20systems%2C%20and%20enzymatic%20cascades.
dc.conicet.paginas
250
dc.source.titulo
Applications of polynomial systems
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