José M. Urquiza

José M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, J. P. Florido, Olga Valenzuela, Maria del Mar Cepero: Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification. Comp. in Bio. and Med. 42(6): 639-650 (2012)

José M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, Javier P. Perez-Florido, Olga Valenzuela: Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering Methodology. J. Applied Mathematics 2012 (2012)

J. P. Florido, Héctor Pomares, Ignacio Rojas, José M. Urquiza, M. A. Lopez-Gordo: A deterministic model selection scheme for incremental RBFNN construction in time series forecasting. Neural Computing and Applications 21(3): 595-610 (2012)

Francisco M. Ortuño Guzman, Javier P. Florido, José M. Urquiza, Héctor Pomares, Alberto Prieto, Ignacio Rojas: Optimization of multiple sequence alignment methodologies using a multiobjective evolutionary algorithm based on NSGA-II. IEEE Congress on Evolutionary Computation 2012: 1-8

Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Ginés Rubio, José M. Urquiza: Global and local modelling in RBF networks. Neurocomputing 74(16): 2594-2602 (2011)

José M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, Julio Ortega, Alberto Prieto: Method for prediction of protein-protein interactions in yeast using genomics/proteomics information and feature selection. Neurocomputing 74(16): 2683-2690 (2011)

J. P. Florido, Héctor Pomares, Ignacio Rojas, José M. Urquiza, Francisco M. Ortuño Guzman: Prediction of Functional Associations between Proteins by Means of a Cost-Sensitive Artificial Neural Network. IWANN (2) 2011: 194-201

Francisco M. Ortuño Guzman, Ignacio Rojas, Héctor Pomares, José M. Urquiza, J. P. Florido: Emerging Methodologies in Multiple Sequence Alignment Using High Throughput Data. PACBB 2011: 183-190

José M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, J. P. Florido, Francisco M. Ortuño Guzman: Using Machine Learning Techniques and Genomic/Proteomic Information from Known Databases for PPI Prediction. PACBB 2011: 373-380

Miguel Ángel López, Héctor Pomares, Francisco J. Pelayo, José M. Urquiza, Javier Perez: 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)

Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Ginés Rubio, José M. Urquiza: Global and Local Modelling in Radial Basis Functions Networks. IWANN (1) 2009: 49-56

J. P. Florido, Héctor Pomares, Ignacio Rojas, José C. Calvo, José M. Urquiza, M. Gonzalo Claros: On Selecting the Best Pre-processing Method for Affymetrix Genechips. IWANN (1) 2009: 845-852

José M. Urquiza, Ignacio Rojas, Héctor Pomares, J. P. Florido, Ginés Rubio, Luis Javier Herrera, José C. Calvo, Julio Ortega: Method for Prediction of Protein-Protein Interactions in Yeast Using Genomics/Proteomics Information and Feature Selection. IWANN (1) 2009: 853-860

José C. Calvo, Julio Ortega, Mancia Anguita, José M. Urquiza, J. P. Florido: Protein Structure Prediction by Evolutionary Multi-objective Optimization: Search Space Reduction by Using Rotamers. IWANN (1) 2009: 861-868

T. Z. 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)

Nicholas Ayache, Dominique Chapelle, Frédérique Clément, Yves Coudière, Hervé Delingette, Jean-Antoine Désidéri, Maxime Sermesant, Michel Sorine, José M. Urquiza: Towards Model-Based Estimation of the Cardiac Electro-Mechanical Activity from ECG Signals and Ultrasound Images. FIMH 2001: 120-127

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