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José M. Urquiza
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2010 – 2019
- 2015
- [j12]Ibrahima Dione, José M. Urquiza
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Penalty: finite element approximation of Stokes equations with slip boundary conditions. Numerische Mathematik 129(3): 587-610 (2015) - 2014
- [j11]José M. Urquiza
Weak imposition of the slip boundary condition on curved boundaries for Stokes flow. J. Comput. Phys. 256: 748-767 (2014) - 2013
- [j10]Ibrahima Dione, José M. Urquiza
Finite element approximations of the Lamé system with penalized ideal contact boundary conditions. Appl. Math. Comput. 223: 115-126 (2013) - [j9]Francisco M. Ortuño Guzman
Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns. Bioinform. 29(17): 2112-2121 (2013) - [j8]Javier Perez-Florido
An effective, practical and low computational cost framework for the integration of heterogeneous data to predict functional associations between proteins by means of Artificial Neural Networks. Neurocomputing 121: 64-78 (2013) - 2012
- [j7]José M. Urquiza, Ignacio Rojas
Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification. Comput. Biol. Medicine 42(6): 639-650 (2012) - [j6]José M. Urquiza, Ignacio Rojas
Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering Methodology. J. Appl. Math. 2012: 897289:1-897289:23 (2012) - [j5]J. P. Florido
A deterministic model selection scheme for incremental RBFNN construction in time series forecasting. Neural Comput. Appl. 21(3): 595-610 (2012) - [c10]Francisco M. Ortuño Guzman
Optimization of multiple sequence alignment methodologies using a multiobjective evolutionary algorithm based on NSGA-II. IEEE Congress on Evolutionary Computation 2012: 1-8 - 2011
- [j4]Luis Javier Herrera, Héctor Pomares
Global and local modelling in RBF networks. Neurocomputing 74(16): 2594-2602 (2011) - [j3]José M. Urquiza, Ignacio Rojas
Method for prediction of protein-protein interactions in yeast using genomics/proteomics information and feature selection. Neurocomputing 74(16): 2683-2690 (2011) - [c9]J. P. Florido
Prediction of Functional Associations between Proteins by Means of a Cost-Sensitive Artificial Neural Network. IWANN (2) 2011: 194-201 - [c8]Francisco M. Ortuño Guzman
Emerging Methodologies in Multiple Sequence Alignment Using High Throughput Data. PACBB 2011: 183-190 - [c7]José M. Urquiza, Ignacio Rojas, Héctor Pomares
Using Machine Learning Techniques and Genomic/Proteomic Information from Known Databases for PPI Prediction. PACBB 2011: 373-380
2000 – 2009
- 2009
- [j2]Miguel Ángel López, Héctor Pomares
Evidences of cognitive effects over auditory steady-state responses by means of artificial neural networks and its use in brain-computer interfaces. Neurocomputing 72(16-18): 3617-3623 (2009) - [c6]Luis Javier Herrera, Héctor Pomares
Global and Local Modelling in Radial Basis Functions Networks. IWANN (1) 2009: 49-56 - [c5]J. P. Florido
On Selecting the Best Pre-processing Method for Affymetrix Genechips. IWANN (1) 2009: 845-852 - [c4]José M. Urquiza, Ignacio Rojas, Héctor Pomares
Method for Prediction of Protein-Protein Interactions in Yeast Using Genomics/Proteomics Information and Feature Selection. IWANN (1) 2009: 853-860 - [c3]José C. Calvo, Julio Ortega Lopera
Protein Structure Prediction by Evolutionary Multi-objective Optimization: Search Space Reduction by Using Rotamers. IWANN (1) 2009: 861-868 - 2007
- [j1]Tahar Zamène Boulmezaoud, José M. Urquiza
On The Eigenvalues of the Spectral Second Order Differentiation Operator and Application to the Boundary Observability of the Wave Equation. J. Sci. Comput. 31(3): 307-345 (2007) - 2001
- [c2]Nicholas Ayache, Dominique Chapelle, Frédérique Clément, Yves Coudière, Hervé Delingette
Towards Model-Based Estimation of the Cardiac Electro-Mechanical Activity from ECG Signals and Ultrasound Images. FIMH 2001: 120-127 - [c1]Dominique Chapelle, Frédérique Clément, Frank Génot, Patrick Le Tallec, Michel Sorine, José M. Urquiza
A Physiologically-Based Model for the Active Cardiac Muscle Contraction. FIMH 2001: 128-139
Coauthor Index
aka: Javier Perez-Florido
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