ALEJANDRO
FERNANDEZ VILLAVERDE
INVESTIGADORES "RAMÓN Y CAJAL"
Julio
Rodríguez Banga
Publicacións nas que colabora con Julio Rodríguez Banga (34)
2023
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Assessment of Prediction Uncertainty Quantification Methods in Systems Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 20, Núm. 3, pp. 1725-1736
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AutoRepar: A method to obtain identifiable and observable reparameterizations of dynamic models with mechanistic insights
International Journal of Robust and Nonlinear Control, Vol. 33, Núm. 9, pp. 5039-5057
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Distilling identifiable and interpretable dynamic models from biological data
PLoS Computational Biology, Vol. 19, Núm. 10
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Improving dynamic predictions with ensembles of observable models
Bioinformatics (Oxford, England), Vol. 39, Núm. 1
2022
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A protocol for dynamic model calibration
Briefings in bioinformatics, Vol. 23, Núm. 1
2019
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A Comparison of Methods for Quantifying Prediction Uncertainty in Systems Biology
IFAC-PapersOnLine
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Análisis de observabilidad e identificabilidad estructural de modelos no lineales: aplicación a la vía de señalización JAK/STAT
XL Jornadas de Automática: libro de actas. Ferrol, 4-6 de septiembre de 2019
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Benchmarking optimization methods for parameter estimation in large kinetic models
Bioinformatics, Vol. 35, Núm. 5, pp. 830-838
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Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models
Journal of the Royal Society Interface, Vol. 16, Núm. 156
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Input-dependent structural identifiability of nonlinear systems
IEEE Control Systems Letters, Vol. 3, Núm. 2, pp. 272-277
2018
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PREMER: A Tool to Infer Biological Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 15, Núm. 4, pp. 1193-1202
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Sufficiently Exciting Inputs for Structurally Identifiable Systems Biology Models
7th Conference on Foundation of Systems Biology in Engineering FOSBE 2018: Chicago, Illinois, USA, 05-08 August 2018
2017
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Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
PLoS Computational Biology, Vol. 13, Núm. 2
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Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation
PLoS Computational Biology, Vol. 13, Núm. 11
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Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems
BMC Systems Biology, Vol. 11, Núm. 1
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Structural properties of dynamic systems biology models: Identifiability, reachability, and initial conditions
Processes, Vol. 5, Núm. 2
2016
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Metabolic engineering with multi-objective optimization of kinetic models
Journal of Biotechnology, Vol. 222, pp. 1-8
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On the relationship between sloppiness and identifiability
Mathematical Biosciences, Vol. 282, pp. 147-161
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PREMER: Parallel reverse engineering of biological networks with information theory
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2015
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A consensus approach for estimating the predictive accuracy of dynamic models in biology
Computer Methods and Programs in Biomedicine, Vol. 119, Núm. 1, pp. 17-28