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dc.contributor.author
Pérez Millán, Mercedes Soledad  
dc.contributor.author
Dickenstein, Alicia Marcela  
dc.date.available
2018-03-07T15:11:26Z  
dc.date.issued
2015-06  
dc.identifier.citation
Pérez Millán, Mercedes Soledad; Dickenstein, Alicia Marcela; Implicit dose-response curves; Springer; Journal of Mathematical Biology; 70; 7; 6-2015; 1669-1684  
dc.identifier.issn
0303-6812  
dc.identifier.uri
http://hdl.handle.net/11336/38111  
dc.description.abstract
We develop tools from computational algebraic geometry for the study of steady state features of autonomous polynomial dynamical systems via elimination of variables. In particular, we obtain nontrivial bounds for the steady state concentration of a given species in biochemical reaction networks with mass-action kinetics. This species is understood as the output of the network and we thus bound the maximal response of the system. The improved bounds give smaller starting boxes to launch numerical methods. We apply our results to the sequential enzymatic network studied in Markevich et al. (J Cell Biol 164(3):353–359, 2004) to find nontrivial upper bounds for the different substrate concentrations at steady state. Our approach does not require any simulation, analytical expression to describe the output in terms of the input, or the absence of multistationarity. Instead, we show how to extract information from effectively computable implicit dose-response curves, with the use of resultants and discriminants. We moreover illustrate in the application to an enzymatic network, the relation between the exact implicit dose-response curve we obtain symbolically and the standard hysteresis diagram provided by a numerical ode solver. The setting and tools we propose could yield many other results adapted to any autonomous polynomial dynamical system, beyond those where it is possible to get explicit expressions.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Bounds  
dc.subject
Chemical Reaction Networks  
dc.subject
Maximal Response  
dc.subject
Resultants  
dc.subject
Steady States  
dc.subject.classification
Matemática Pura  
dc.subject.classification
Matemáticas  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Implicit dose-response curves  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-03-02T14:21:37Z  
dc.identifier.eissn
1432-1416  
dc.journal.volume
70  
dc.journal.number
7  
dc.journal.pagination
1669-1684  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlin  
dc.description.fil
Fil: Pérez Millán, Mercedes Soledad. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Dickenstein, Alicia Marcela. 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.journal.title
Journal of Mathematical Biology  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s00285-014-0809-4  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs00285-014-0809-4  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/abs/1401.8028