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000162457 005__ 20251017144645.0
000162457 0247_ $$2doi$$a10.1007/s11831-025-10291-y
000162457 0248_ $$2sideral$$a145032
000162457 037__ $$aART-2025-145032
000162457 041__ $$aeng
000162457 100__ $$0(orcid)0000-0003-2564-6038$$aAyensa-Jiménez, Jacobo
000162457 245__ $$aAn Overview from Physically-Based to Data-Driven Approaches of the Modelling and Simulation of Glioblastoma Progression in Microfluidic Devices
000162457 260__ $$c2025
000162457 5060_ $$aAccess copy available to the general public$$fUnrestricted
000162457 5203_ $$aIn silico models and computational tools are invaluable instruments that complement experiments to improve our understanding of complex phenomena such as cancer evolution. This work offers a perspective on different approaches that can be used for mathematical modeling of glioblastoma, the most common and lethal brain cancer, in microfluidic devices, the most biomimetic in vitro cell culture technique nowadays. These approaches range from purely knowledge-based solutions to data-driven, and hence completely model-free, algorithms. In particular, we focus on hybrid approaches, which combine physically-based and data-driven strategies, demonstrating how this integration can enhance the understanding we get from simulation by revealing the underlying model structure and thus, in turn, the prospective biological mechanism.
000162457 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2021-126051OB-C41$$9info:eu-repo/grantAgreement/ES/DGA/T62-230R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2022-138572OB-C44
000162457 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000162457 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000162457 700__ $$0(orcid)0000-0002-7909-4446$$aPérez-Aliacar, Marina
000162457 700__ $$aDoweidar, Mohamed H.
000162457 700__ $$aGaffney, Eamonn A.
000162457 700__ $$0(orcid)0000-0001-8741-6452$$aDoblaré, Manuel$$uUniversidad de Zaragoza
000162457 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000162457 773__ $$g(2025), [37 pp.]$$pArch. comput. methods eng.$$tARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING$$x1134-3060
000162457 8564_ $$s7842462$$uhttps://zaguan.unizar.es/record/162457/files/texto_completo.pdf$$yVersión publicada
000162457 8564_ $$s2110892$$uhttps://zaguan.unizar.es/record/162457/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000162457 909CO $$ooai:zaguan.unizar.es:162457$$particulos$$pdriver
000162457 951__ $$a2025-10-17-14:33:33
000162457 980__ $$aARTICLE