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Jacobo Ayensa-Jiménez
Jacobo Ayensa-Jiménez
TMELab, Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza
Verified email at unizar.es - Homepage
Title
Cited by
Cited by
Year
A new reliability-based data-driven approach for noisy experimental data with physical constraints
J Ayensa-Jiménez, MH Doweidar, JA Sanz-Herrera, M Doblaré
Computer Methods in Applied Mechanics and Engineering 328, 752-774, 2018
512018
Mathematical formulation and parametric analysis of in vitro cell models in microfluidic devices: application to different stages of glioblastoma evolution
J Ayensa-Jiménez, M Pérez-Aliacar, T Randelovic, S Oliván, L Fernández, ...
Scientific Reports 10 (1), 21193, 2020
302020
Prediction and identification of physical systems by means of physically-guided neural networks with meaningful internal layers
J Ayensa-Jimenez, MH Doweidar, JA Sanz-Herrera, M Doblare
Computer Methods in Applied Mechanics and Engineering 381, 113816, 2021
19*2021
An unsupervised data completion method for physically-based data-driven models
J Ayensa-Jiménez, MH Doweidar, JA Sanz-Herrera, M Doblaré
Computer Methods in Applied Mechanics and Engineering 344, 120-143, 2019
192019
A multiscale data-driven approach for bone tissue biomechanics
J Mora-Macías, J Ayensa-Jiménez, E Reina-Romo, MH Doweidar, ...
Computer Methods in Applied Mechanics and Engineering 368, 113136, 2020
182020
Predicting cell behaviour parameters from glioblastoma on a chip images. A deep learning approach
M Pérez-Aliacar, MH Doweidar, M Doblaré, J Ayensa-Jiménez
Computers in Biology and Medicine 135, 104547, 2021
132021
Data-driven computational simulation in bone mechanics
JA Sanz-Herrera, J Mora-Macías, J Ayensa-Jiménez, E Reina-Romo, ...
Annals of Biomedical Engineering 49, 407-419, 2021
92021
On the application of physically-guided neural networks with internal variables to continuum problems
J Ayensa-Jiménez, MH Doweidar, JA Sanz-Herrera, M Doblaré
arXiv preprint arXiv:2011.11376, 2020
82020
Understanding glioblastoma invasion using physically-guided neural networks with internal variables
J Ayensa-Jiménez, MH Doweidar, JA Sanz-Herrera, M Doblare
PLoS Computational Biology 18 (4), e1010019, 2022
42022
Analysis of the parametric correlation in mathematical modeling of in vitro glioblastoma evolution using copulas
J Ayensa-Jiménez, M Pérez-Aliacar, T Randelovic, JA Sanz-Herrera, ...
Mathematics 9 (1), 27, 2020
42020
On the simulation of organ-on-chip cell processes: Application to an in vitro model of Glioblastoma evolution
J Ayensa-Jiménez, MH Doweidar, T Randelovic, LJ Fernández, S Oliván, ...
Advances in Biomechanics and Tissue Regeneration, 313-341, 2019
42019
Study of the effect of the tumour microenvironment on cell response using a combined simulation and machine learning approach. application to the evolution of glioblastoma
J Ayensa-Jiménez
PhD thesis, Universidad de Zaragoza, 2022
32022
Modelling glioblastoma resistance to temozolomide. Combination of spheroid and mathematical models to simulate cellular adaptation in vitro.
M Perez-Aliacar, J Ayensa-Jimenez, T Randelovic, I Ochoa, M Doblare
bioRxiv, 2023.11. 24.568421, 2023
12023
Nanoparticles Stokes radius assessment through permeability coefficient determination within a new stratified epithelium on-chip model
E Fernandez-Carro, R Salomon-Cambero, L Armero, HA Castro-Abril, ...
Artificial Cells, Nanomedicine, and Biotechnology 51 (1), 466-475, 2023
2023
Comment on" Mechanotransduction in tumor dynamics modeling" by B. Blanco, H. Gomez, J. Melchor, R. Palma, J. Soler, G. Rus
M Doblare, J Ayensa-Jiménez, M Perez-Aliacar
Physics of Life Reviews 47, 148-150, 2023
2023
A Mathematical Modelling Study of Chemotactic Dynamics in Cell Cultures: The Impact of Spatio-temporal Heterogeneity
J Ayensa-Jiménez, MH Doweidar, M Doblaré, EA Gaffney
Bulletin of Mathematical Biology 85 (10), 98, 2023
2023
Modelling cell adaptation using internal variables: Accounting for cell plasticity in continuum mathematical biology
M Pérez-Aliacar, J Ayensa-Jiménez, M Doblaré
Computers in Biology and Medicine 164, 107291, 2023
2023
Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal Variables
J Orera-Echeverria, J Ayensa-Jiménez, M Doblare
arXiv preprint arXiv:2308.03915, 2023
2023
Plasticidad fenotípica in silico: adaptación celular del glioblastoma a la hipoxia utilizando modelos matemáticos.
MP Aliacar, J Ayensa-Jiménez, M Doblaré
Jornada de Jóvenes Investigadores del I3A 11, 2023
2023
Massive data probabilistic framework for parameter estimation in biological problems
M Pérez-Aliacar, J Ayensa-Jiménez, MH Doweidar, M Doblaré
Digital Human Modeling and Medicine, 19-62, 2023
2023
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