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Optimization Alternatives for Robust Model-based Design of Synthetic Biological Circuits

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Optimization Alternatives for Robust Model-based Design of Synthetic Biological Circuits

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dc.contributor.author Boada-Acosta, Yadira Fernanda es_ES
dc.contributor.author Pitarch Pérez, Jose Luis es_ES
dc.contributor.author Vignoni, Alejandro es_ES
dc.contributor.author Reynoso Meza, Gilberto es_ES
dc.contributor.author Picó, Jesús es_ES
dc.date.accessioned 2020-09-19T03:34:33Z
dc.date.available 2020-09-19T03:34:33Z
dc.date.issued 2016 es_ES
dc.identifier.uri http://hdl.handle.net/10251/150450
dc.description.abstract [EN] Synthetic biology is reaching the situation where tuning devices by hand is no longer possible due to the complexity of the biological circuits being designed. Thus, mathematical models need to be used in order, not only to predict the behavior of the designed synthetic devices; but to help on the selection of the biological parts, i.e., guidelines for the experimental implementation. However, since uncertainties are inherent to biology, the desired dynamics for the circuit usually requires a trade-off among several goals. Hence, a multi-objective optimization design (MOOD) naturally arises to get a suitable parametrization (or range) of the required kinetic parameters to build a biological device with some desired properties. Biologists have classically addressed this problem by evaluating a set of random Monte Carlo simulations with parameters between an operation range. In this paper, We propose solving the MOOD by means of dynamic programming using both a global multi-objective evolutionary algorithm (MOLA) and a local gradient-based nonlinear programming (NLP) solver. The performance of both alternatives is then checked in the design of a well-known biological circuit: a genetic incoherent feed-forward loop showing adaptive behavior. (C) 2016, IFAC (International Federation of Antomatic Control) Hosting by Elsevier Ltd. All rights reserved. es_ES
dc.description.sponsorship The research leading to these results has received funding from the European Union (FP7/2007-2013 under grant agreement no604068), the Spanish Government (FEDER-CICYT DPI2011-524 28112-C04-01, DPI2014-55276-C5-1-R, DPI2015-70975-P) and the National Council of Scientific and Technologic Development of Brazil (BJT-304804/2014-2). Yadira Boada thanks also grant FPI/2013-3242 of the Universitat Politecnica de Valencia es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation CNPq/BJT/304804/2014-2 es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//DPI2014-55276-C5-1-R/ES/BIOLOGIA SINTETICA PARA LA MEJORA EN BIOPRODUCCION: DISEÑO, OPTIMIZACION, MONITORIZACION Y CONTROL/ es_ES
dc.relation UPV/FPI/2013-3242 es_ES
dc.relation MINECO/DPI2011-28112-C04-01 es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//DPI2015-70975-P/ES/INTEGRACION DE OPTIMIZACION Y CONTROL EN PLANTAS DE PROCESOS/ es_ES
dc.relation.ispartof IFAC-PapersOnLine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Biological circuits es_ES
dc.subject Kinetic parameters es_ES
dc.subject Multiobjective optimisations es_ES
dc.subject Nonlinear programming es_ES
dc.subject Computer-aided design es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Optimization Alternatives for Robust Model-based Design of Synthetic Biological Circuits es_ES
dc.type Artículo es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1016/j.ifacol.2016.07.291 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/604068/EU/Real-time Monitoring and Optimization of Resource Efficiency in Integrated Processing Plants/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Boada-Acosta, YF.; Pitarch Pérez, JL.; Vignoni, A.; Reynoso Meza, G.; Picó, J. (2016). Optimization Alternatives for Robust Model-based Design of Synthetic Biological Circuits. IFAC-PapersOnLine. 49(7):821-826. https://doi.org/10.1016/j.ifacol.2016.07.291 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS-CAB 2016) es_ES
dc.relation.conferencedate Junio 06-08,2016 es_ES
dc.relation.conferenceplace Trondheim, Norway es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.ifacol.2016.07.291 es_ES
dc.description.upvformatpinicio 821 es_ES
dc.description.upvformatpfin 826 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 49 es_ES
dc.description.issue 7 es_ES
dc.identifier.eissn 2405-8963 es_ES
dc.relation.pasarela S\325478 es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brasil es_ES


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