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dc.contributor.authorRey Barreiro, Xabier 
dc.contributor.authorFernandez Villaverde, Alejandro 
dc.date.accessioned2023-02-06T11:27:51Z
dc.date.available2023-02-06T11:27:51Z
dc.date.issued2023-01-31
dc.identifier.citationBioinformatics, 39(2), btad065 (2023)spa
dc.identifier.issn13674803
dc.identifier.issn13674811
dc.identifier.urihttp://hdl.handle.net/11093/4421
dc.description.abstractMotivation: The theoretical possibility of determining the state and parameters of a dynamic model by measuring its outputs is given by its structural identifiability and observability. These properties should be analysed before attempting to calibrate a model, but their a priori analysis can be challenging, requiring symbolic calculations that often have a high computational cost. In recent years a number of software tools have been developed for this task, mostly in the systems biology community. These tools have vastly different features and capabilities, and a critical assessment of their performance is still lacking. Results: Here we present a comprehensive study of the computational resources available for analysing structural identifiability. We consider 13 software tools developed in 7 programming languages and evaluate their performance using a set of 25 case studies created from 21 models. Our results reveal their strengths and weaknesses, provide guidelines for choosing the most appropriate tool for a given problem, and highlight opportunities for future developments. Availability: https://github.com/Xabo-RB/Benchmarking_files.spa
dc.description.sponsorshipXunta de Galicia | Ref. ED431F 2021/003spa
dc.description.sponsorshipAgencia Estatal de Investigación | Ref. PID2020-113992RA-I00spa
dc.description.sponsorshipAgencia Estatal de Investigación | Ref. RYC-2019-027537-Ispa
dc.description.sponsorshipFinanciado para publicación en acceso aberto: Universidade de Vigo/CISUGspa
dc.language.isoengspa
dc.publisherBioinformaticsspa
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113992RA-I00/ES/PROMOVIENDO LA EXPLOTACION DE MODELOS DINAMICOS EN LA BIOECONOMIA CON TECNICAS COMPUTACIONALES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RYC-2019-027537-I/ES
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleBenchmarking tools for a priori identifiability analysisen
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.identifier.doi10.1093/bioinformatics/btad065
dc.identifier.editorhttps://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btad065/7017524spa
dc.publisher.departamentoBioquímica, xenética e inmunoloxíaspa
dc.publisher.departamentoEnxeñaría de sistemas e automáticaspa
dc.publisher.grupoinvestigacionGrupo de Control non Liñalspa
dc.subject.unesco3328 Procesos Tecnológicosspa
dc.subject.unesco3311.02 Ingeniería de Controlspa
dc.date.updated2023-02-01T14:43:06Z
dc.computerCitationpub_title=Bioinformatics|volume=39|journal_number=2|start_pag=btad065|end_pag=spa


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    Attribution 4.0 International
    Except where otherwise noted, this item's license is described as Attribution 4.0 International