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dc.contributor.author | Llopis Lorente, Jordi | es_ES |
dc.contributor.author | Trénor Gomis, Beatriz Ana | es_ES |
dc.contributor.author | Saiz Rodríguez, Francisco Javier | es_ES |
dc.date.accessioned | 2022-05-13T13:26:43Z | |
dc.date.available | 2022-05-13T13:26:43Z | |
dc.date.issued | 2022-05-13T13:26:43Z | |
dc.identifier.uri | http://hdl.handle.net/10251/182593 | |
dc.description.abstract | This repository contains the parameter sets of the population of TorORd models and the the population of ORdmD models, the ORdmD CellML file and MALTAB code used in Llopis-Lorente, J., Trenor, B., Saiz, J. (2022). Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk | es_ES |
dc.language | Inglés | es_ES |
dc.rights | Reconocimiento - No comercial (by-nc) | es_ES |
dc.subject | In-silico study | es_ES |
dc.subject | Torsade de Pointes | es_ES |
dc.subject | Proarrhythmic risk | es_ES |
dc.subject | Cardiac safety | es_ES |
dc.subject | Population of models | es_ES |
dc.subject.classification | TECNOLOGIA ELECTRONICA | es_ES |
dc.title | Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk | es_ES |
dc.type | Software | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//PROMETEO%2F2020%2F043//MODELOS IN-SILICO MULTI-FISICOS Y MULTI-ESCALA DEL CORAZON PARA EL DESARROLLO DE NUEVOS METODOS DE PREVENCION, DIAGNOSTICO Y TRATAMIENTO EN MEDICINA PERSONALIZADA (HEART IN-SILICO MODELS)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/101016496/EU/Simulation of Cardiac Devices & Drugs for in-silico Testing and Certification/ | |
dc.relation.projectID | info:eu-repo/grantAgreement/MCIU//FPU18%2F01659/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Centro de Investigación e Innovación en Bioingeniería - Centre de Recerca i Innovació en Bioenginyeria | es_ES |
dc.description.bibliographicCitation | Llopis Lorente, J.; Trénor Gomis, BA.; Saiz Rodríguez, FJ. (2022). Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk. http://hdl.handle.net/10251/182593 | es_ES |
dc.type.version | info:eu-repo/semantics/submittedVersion | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.contributor.funder | Generalitat Valenciana | |
dc.contributor.funder | European Commission | |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades |