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SELANSI: A toolbox for simulation of stochastic gene regulatory networks
dc.contributor.author | Pájaro Diéguez, Manuel | |
dc.contributor.author | Otero-Muras, Irene | |
dc.contributor.author | Vázquez, Carlos | |
dc.contributor.author | Alonso, Antonio | |
dc.date.accessioned | 2024-07-04T09:31:36Z | |
dc.date.available | 2024-07-04T09:31:36Z | |
dc.date.issued | 2018-03 | |
dc.identifier.citation | Manuel Pájaro, Irene Otero-Muras, Carlos Vázquez, Antonio A Alonso, SELANSI: a toolbox for simulation of stochastic gene regulatory networks, Bioinformatics, Volume 34, Issue 5, March 2018, Pages 893–895, https://doi.org/10.1093/bioinformatics/btx645 | es_ES |
dc.identifier.issn | 1367-4803 | |
dc.identifier.uri | http://hdl.handle.net/2183/37704 | |
dc.description.abstract | [Abstract]: Motivation Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. Results This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. © The Author 2017. Published by Oxford University Press. | es_ES |
dc.description.sponsorship | This work has been supported by Spanish MINECO grants AGL2015-67504-C3-2-R, PIE201230E0M2 (AAA), BES-2013-063112 (MP), MTM2016-76497-R, MTM2013-47800-C2-1-P (CV) and MINECO and European Regional Development Fund DPI2014-55276-C5-2-R (IOM). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Oxford University Press | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2015-67504-C3-2-R/ES/UN ENFOQUE BASADO EN MODELOS MULTI-ESCALA PARA ENTENDER LOS MECANISMOS DE ADAPTACION DE LAS ESPECIES NO CONVENCIONALES DEL GENERO SACCHAROMYCES EN FERMENTACIONES VINICAS | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PIE201230E0M2/ES/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BES-2013-063112/ES/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-76497-R/ES/METODOS MATEMATICOS Y SIMULACION NUMERICA PARA RETOS EN FINANZAS CUANTITATIVAS, MEDIOAMBIENTE, BIOTECNOLOGIA Y EFICIENCIA INDUSTRIAL | es_ES |
dc.relation | Info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2013-47800-C2-1-P/ES/MODELADO MATEMATICO, ANALISIS Y SIMULACION NUMERICA DE PROBLEMAS EN FINANZAS Y SEGUROS, PROCESOS INDUSTRIALES, BIOTECNOLOGIA Y MEDIOAMBIENTE | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2014-55276-C5-2-R/ES/ | es_ES |
dc.relation.uri | https://doi.org/10.1093/bioinformatics/btx645 | es_ES |
dc.rights | Attribution-NonCommercial 4.0 International (CC-BY-NC) | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/3.0/es/ | * |
dc.subject | Algorithms | es_ES |
dc.subject | Computational Biology | es_ES |
dc.subject | Computer Simulation | es_ES |
dc.subject | Gene Regulatory Networks | es_ES |
dc.subject | Kinetics | es_ES |
dc.subject | Software | es_ES |
dc.subject | Stochastic Processes | es_ES |
dc.subject | Synthetic Biology | es_ES |
dc.subject | Transcription Factors | es_ES |
dc.title | SELANSI: A toolbox for simulation of stochastic gene regulatory networks | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Bioinformatics | es_ES |
UDC.volume | 34 | es_ES |
UDC.issue | 5 | es_ES |
UDC.startPage | 893 | es_ES |
UDC.endPage | 895 | es_ES |
dc.identifier.doi | 10.1093/bioinformatics/btx645 |
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