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Automated design of synthetic biocircuits in the stochastic regime
dc.contributor.author | Sequeiros Ferreiro, Carlos Xosé | |
dc.contributor.author | Vázquez, Carlos | |
dc.contributor.author | Banga, Julio R. | |
dc.contributor.author | Otero-Muras, Irene | |
dc.date.accessioned | 2022-12-30T10:39:21Z | |
dc.date.available | 2022-12-30T10:39:21Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | C. Sequeiros, C. Vázquez, J. R. Banga, and I. Otero-Muras, “Automated design of synthetic biocircuits in the stochastic regime,” IFAC-PapersOnLine, vol. 55, no. 20, pp. 630–634, Jan. 2022, doi: 10.1016/j.ifacol.2022.09.166. | es_ES |
dc.identifier.issn | 2405-8963 | |
dc.identifier.uri | http://hdl.handle.net/2183/32259 | |
dc.description.abstract | [Abstract]: In this work, we present an optimization-based design strategy for gene regulatory networks (GRNs) in the stochastic regime (i.e., in the presence of molecular noise). The approach exploits a recently developed framework for the efficient simulation of stochastic GRNs based on a Partial Integro Differential Equations (PIDE) model formulation, which is here further accelerated with a parallel implementation in GPUs to maximize the performance. The simulator is combined with a global Mixed Integer Nonlinear Programming algorithm to efficiently address the optimization of the design through topology and parameter spaces simultaneously. We illustrate the performance of the proposed methodology through two different case studies: a biocircuit with a pre-defined target dynamics, and a biocircuit with a stationary bi-modal distribution fulfilling a number of requirements (in terms of distance and ratios of probabilities between modes). | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C2018/033 | es_ES |
dc.description.sponsorship | MCIN; PID2020-117271RB-C22 | es_ES |
dc.description.sponsorship | CSIC; PIE 202070E036 | es_ES |
dc.description.sponsorship | CSIC; PIE 20211CT006 | es_ES |
dc.description.sponsorship | Xunta de Galicia; GAIN Oportunius grant 20211020034 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IFAC Secretariat / Elsevier | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.ifacol.2022.09.166 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Synthetic Biology | es_ES |
dc.subject | Systems Biology | es_ES |
dc.subject | Molecular Noise | es_ES |
dc.subject | Bimodality | es_ES |
dc.subject | Mixed Integer Global Optimization | es_ES |
dc.subject | Gene Regulatory Network | es_ES |
dc.subject | Partial Integro Differential Equations | es_ES |
dc.subject | Stochastic Models | es_ES |
dc.subject | Bistability | es_ES |
dc.title | Automated design of synthetic biocircuits in the stochastic regime | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | IFAC-PapersOnLine | es_ES |
UDC.volume | 55 | es_ES |
UDC.issue | 20 | es_ES |
UDC.startPage | 630 | es_ES |
UDC.endPage | 634 | es_ES |
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