José M. Urquiza - researchr alias

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Viewing Publication 1 - 17 from 17

2015

Penalty: finite element approximation of Stokes equations with slip boundary conditionsIbrahima Dione, José M. Urquiza. nm, 129(3):587-610, 2015. [doi]

2014

Weak imposition of the slip boundary condition on curved boundaries for Stokes flowJosé M. Urquiza, André Garon, Marie-Isabelle Farinas. jcphy, 256:748-767, 2014. [doi]

2013

Finite element approximations of the Lamé system with penalized ideal contact boundary conditionsIbrahima Dione, José M. Urquiza. amc, 223:115-126, 2013. [doi]

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 NetworksJavier P. Florido, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Francisco M. Ortuño Guzman, José M. Urquiza. ijon, 121:64-78, 2013. [doi]

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columnsFrancisco M. Ortuño Guzman, Olga Valenzuela, Fernando Rojas, Héctor Pomares, Javier P. Florido, José M. Urquiza, Ignacio Rojas. bioinformatics, 29(17):2112-2121, 2013. [doi]

2012

A deterministic model selection scheme for incremental RBFNN construction in time series forecastingJ. P. Florido, Héctor Pomares, Ignacio Rojas, José M. Urquiza, M. A. Lopez-Gordo. nca, 21(3):595-610, 2012. [doi]

Optimization of multiple sequence alignment methodologies using a multiobjective evolutionary algorithm based on NSGA-IIFrancisco M. Ortuño Guzman, Javier P. Florido, José M. Urquiza, Héctor Pomares, Alberto Prieto, Ignacio Rojas. cec 2012: 1-8 [doi]

Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering MethodologyJosé M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, Javier P. Perez-Florido, Olga Valenzuela. jam, 2012, 2012. [doi]

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

2011

Prediction of Functional Associations between Proteins by Means of a Cost-Sensitive Artificial Neural NetworkJ. P. Florido, Héctor Pomares, Ignacio Rojas, José M. Urquiza, F. Ortuño. iwann 2011: 194-201 [doi]

Emerging Methodologies in Multiple Sequence Alignment Using High Throughput DataFrancisco M. Ortuño Guzman, Ignacio Rojas, Héctor Pomares, José M. Urquiza, J. P. Florido. pacbb 2011: 183-190 [doi]

Global and local modelling in RBF networksLuis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, G. Rubio, José M. Urquiza. ijon, 74(16):2594-2602, 2011. [doi]

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

Method for prediction of protein-protein interactions in yeast using genomics/proteomics information and feature selectionJosé M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, J. Ortega, Alberto Prieto. ijon, 74(16):2683-2690, 2011. [doi]

2007

On The Eigenvalues of the Spectral Second Order Differentiation Operator and Application to the Boundary Observability of the Wave EquationT. Z. Boulmezaoud, José M. Urquiza. jscic, 31(3):307-345, 2007. [doi]

2001

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