Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles. - Daniel Urda; José Luis Subirats; Leonardo Franco; José Manuel Jerez (IEA/AIE (1), 2010)

Hybrid (Generalization-Correlation) Method for Feature Selection in High Dimensional DNA Microarray Prediction Problems. - Yasel Couce; Leonardo Franco; Daniel Urda; José Luis Subirats; José M. Jerez (IWANN (2), 2011)

WIMP: Web server tool for missing data imputation. - Daniel Urda; José Luis Subirats; Pedro J. García-Laencina; Leonardo Franco; José-Luis Sancho-Gómez; José Manuel Jerez (Comput. Methods Programs Biomed., 2012)

Storing Location-Aware Data in Mobile Distributed Systems. - Daniel Urda; Ciprian Dobre; Florin Pop (ISPDC, 2013)

Committee C-Mantec: A Probabilistic Constructive Neural Network. - José Luis Subirats; Rafael Marcos Luque Baena; Daniel Urda; Francisco Ortega-Zamorano; José Manuel Jerez; Leonardo Franco (IWANN (1), 2013)

A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel. - Daniel Urda; Rafael Marcos Luque; María Jesús Jiménez-Come; Ignacio Turias Domínguez; Leonardo Franco; José Manuel Jerez (IWANN (1), 2013)

Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms. - Rafael Marcos Luque Baena; Daniel Urda; José Luis Subirats; Leonardo Franco; José M. Jerez (IWBBIO, 2013)

Addressing critical issues in the development of an Oncology Information System. - Daniel Urda; Nuria Ribelles; José Luis Subirats; Leonardo Franco; Emilio Alba; José Manuel Jerez (Int. J. Medical Informatics, 2013)

Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures. - Daniel Urda; Simon J. Chambers; Ian H. Jarman; Paulo J. G. Lisboa; Leonardo Franco; José M. Jerez (CIBB, 2014)

Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords. - Rafael Marcos Luque Baena; Daniel Urda; M. Gonzalo Claros; Leonardo Franco; José M. Jerez (J. Biomed. Informatics, 2014)

Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers. - Francisco Ortega-Zamorano; José M. Jerez; Daniel Urda; Rafael M. Luque-Baena; Leonardo Franco (IEEE Trans. Neural Networks Learn. Syst., 2016)

Machine learning models to search relevant genetic signatures in clinical context. - Daniel Urda; Rafael Marcos Luque Baena; Leonardo Franco; José M. Jerez; Noelia Sánchez-Maroño (IJCNN, 2017)

Deep Learning to Analyze RNA-Seq Gene Expression Data. - Daniel Urda; Julio Montes-Torres; Fernando Moreno; Leonardo Franco; José M. Jerez (IWANN (2), 2017)

L_1 L 1 -regularization Model Enriched with Biological Knowledge. - Daniel Urda; Francisco Aragón; Leonardo Franco; Francisco J. Veredas 001; José M. Jerez (IWBBIO (1), 2017)

Classification of high dimensional data using LASSO ensembles. - Daniel Urda; Leonardo Franco; José M. Jerez (SSCI, 2017)

Data Dimension and Structure Effects in Predictive Performance of Deep Neural Networks. - Daniel Urda; José M. Jerez; Ignacio J. Turias (SoMeT, 2018)

Forward Noise Adjustment Scheme for Data Augmentation. - Francisco J. Moreno-Barea; Fiammetta Strazzera; José M. Jerez; Daniel Urda; Leonardo Franco (SSCI, 2018)

BLASSO: integration of biological knowledge into a regularized linear model. - Daniel Urda; Francisco Aragón; Rocío Bautista; Leonardo Franco; Francisco J. Veredas 001; Manuel Gonzalo Claros; José Manuel Jerez (BMC Syst. Biol., 2018)

Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks. - José Antonio Moscoso López; Juan Jesús Ruiz-Aguilar; Javier González-Enrique; Daniel Urda; Héctor Mesa; Ignacio J. Turias (HAIS, 2019)

A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel. - Héctor Mesa; Daniel Urda; Juan J. Ruiz-Aguilar; José Antonio Moscoso López; Juan Almagro; Patricia Acosta; Ignacio J. Turias (HAIS, 2019)

MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins. - Guillermo López-García; José M. Jerez; Daniel Urda; Francisco J. Veredas 001 (IJCNN, 2019)

A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations. - Javier González-Enrique; Juan Jesús Ruiz-Aguilar; José Antonio Moscoso López; Steffanie Van Roode; Daniel Urda; Ignacio J. Turias (IWANN (1), 2019)

Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar. - José Antonio Moscoso López; Juan Jesús Ruiz-Aguilar; Daniel Urda; Javier González-Enrique; Ignacio José Turias (IWANN (1), 2019)

A Deep Ensemble Neural Network Approach to Improve Predictions of Container Inspection Volume. - Daniel Urda Muñoz; Juan Jesús Ruiz-Aguilar; Javier González-Enrique; Ignacio Turias Domínguez (IWANN (1), 2019)

Addition of Pathway-Based Information to Improve Predictions in Transcriptomics. - Daniel Urda; Francisco J. Veredas 001; Ignacio Turias; Leonardo Franco (IWBBIO (2), 2019)

Beta-Hebbian Learning for Visualizing Intrusions in Flows. - Héctor Quintián; Esteban Jove; José Luís Casteleiro-Roca; Daniel Urda; Ángel Arroyo; José Luís Calvo-Rolle; Álvaro Herrero 001; Emilio Corchado (CISIS, 2020)

Trends and Patterns of International Student Mobility: The Case of Bachelor's Degrees in Computer Science at the University of Burgos. - Ángel Arroyo; Secil Bayraktar; Carlos Cambra 001; Daniel Urda; Álvaro Herrero 001 (ICEUTE, 2020)

Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance. - Damián Nimo 001; Bernabé Dorronsoro; Ignacio J. Turias; Daniel Urda (OLA, 2020)

Container Demand Forecasting at Border Posts of Ports: A Hybrid SARIMA-SOM-SVR Approach. - Juan Jesús Ruiz-Aguilar; Daniel Urda; José Antonio Moscoso López; Javier González-Enrique; Ignacio J. Turias (OLA, 2020)

Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods. - José Antonio Moscoso López; Daniel Urda; Javier González-Enrique; Juan Jesús Ruiz-Aguilar; Ignacio J. Turias (SOCO, 2020)

A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models. - Juan Jesús Ruiz-Aguilar; Daniel Urda; José Antonio Moscoso López; Javier González-Enrique; Ignacio J. Turias (Neurocomputing, 2020)

Combining feature engineering and feature selection to improve the prediction of methionine oxidation sites in proteins. - Francisco J. Veredas 001; Daniel Urda; José Luis Subirats; Francisco R. Cantón; Juan Carlos Aledo (Neural Comput. Appl., 2020)

Advanced 3D Visualization of Android Malware Families. - Nuño Basurto; Héctor Quintián; Daniel Urda; José Luís Calvo-Rolle; Álvaro Herrero 001; Emilio Corchado (CISIS-ICEUTE, 2021)

Assessing the Impact of Batch-Based Data Aggregation Techniques for Feature Engineering on Machine Learning-Based Network IDSs. - Roberto Magán-Carrión; Daniel Urda; Ignacio Díaz-Cano; Bernabé Dorronsoro (CISIS-ICEUTE, 2021)

Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study. - Michal Choras; Konstantinos P. Demestichas; Agata Gielczyk; Álvaro Herrero 001; Pawel Ksieniewicz; Konstantina Remoundou; Daniel Urda; Michal Wozniak 001 (Appl. Soft Comput., 2021)

A machine learning-based forecasting system of perishable cargo flow in maritime transport. - José Antonio Moscoso López; Daniel Urda; Juan Jesús Ruiz-Aguilar; Javier González-Enrique; Ignacio J. Turias (Neurocomputing, 2021)

A permutation entropy-based EMD-ANN forecasting ensemble approach for wind speed prediction. - Juan Jesús Ruiz-Aguilar; Ignacio Turias; Javier González-Enrique; Daniel Urda; David A. Elizondo (Neural Comput. Appl., 2021)

Deep neural networks architecture driven by problem-specific information. - Daniel Urda; Francisco J. Veredas 001; Javier González-Enrique; Juan J. Ruiz-Aguilar; José M. Jerez; Ignacio J. Turias (Neural Comput. Appl., 2021)

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO2 (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain). - Javier González-Enrique; Juan Jesús Ruiz-Aguilar; José Antonio Moscoso López; Daniel Urda; Lipika Deka; Ignacio J. Turias (Sensors, 2021)

Dimensionality-Reduction Methods for the Analysis of Web Traffic. - Nuño Basurto; Álvaro Michelena; Daniel Urda; Héctor Quintián; José Luís Calvo-Rolle; Álvaro Herrero 001 (CISIS-ICEUTE, 2022)

Evaluating Classifiers' Performance to Detect Attacks in Website Traffic. - Daniel Urda; Nuño Basurto; Meelis Kull; Álvaro Herrero 001 (CISIS-ICEUTE, 2022)

A Virtual Sensor Approach to Estimate the Stainless Steel Final Chemical Characterisation. - Damián Nimo 001; Javier González-Enrique; David Perez; Juan Almagro; Daniel Urda; Ignacio J. Turias (SOCO, 2022)

Non-linear Neural Models to Predict HRC Steel Price in Spain. - Roberto Alcalde; Daniel Urda; Carlos Alonso de Armiño; Santiago García; Manuel Manzanedo; Álvaro Herrero 001 (SOCO, 2022)

Computational intelligence applied to cybersecurity. - Álvaro Herrero 001; Daniel Urda; Javier Sedano; Héctor Quintián; Emilio Corchado (Expert Syst. J. Knowl. Eng., 2022)

Advanced Visualization of Intrusions in Flows by Means of Beta-Hebbian Learning. - Héctor Quintián; Esteban Jove; José Luís Casteleiro-Roca; Daniel Urda; Ángel Arroyo; José Luís Calvo-Rolle; Álvaro Herrero 001; Emilio Corchado (Log. J. IGPL, 2022)

Special issue SOCO 2020: New trends in soft computing and its application in industrial and environmental problems. - Javier Sedano; Daniel Urda; José Luís Calvo-Rolle; Héctor Quintián; Emilio Corchado (Neurocomputing, 2022)

Improving the Reliability of Network Intrusion Detection Systems Through Dataset Integration. - Roberto Magán-Carrión; Daniel Urda; Ignacio Díaz-Cano; Bernabé Dorronsoro (IEEE Trans. Emerg. Top. Comput., 2022)

Benchmarking Classifiers for DDoS Attack Detection in Industrial IoT Networks. - Marcos Severt; Roberto Casado-Vara; Ángel Martín del Rey; Nuño Basurto; Daniel Urda; Álvaro Herrero 001 (CISIS-ICEUTE, 2023)

Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images. - Samuel Lozano-Juárez; Nuria Velasco-Pérez; Ian Roberts; Jerónimo Bernal; Nuño Basurto; Daniel Urda; Álvaro Herrero 001 (HAIS, 2023)

A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data. - Arantxa M. Ortega León; Roa'a Khaled; María Inmaculada Rodríguez-García; Daniel Urda; Ignacio J. Turias (IWBBIO (1), 2023)

Missing Values Imputation for Visualizing the Air Quality Evolution During the COVID-19 Pandemic in Madrid. - Ángel Arroyo; Beatriz Gil-Arroyo; Daniel Urda; Carlos Cambra 001; Álvaro Herrero 001 (SOCO (1), 2023)

Defect Detection in Batavia Woven Fabrics by Means of Convolutional Neural Networks. - Nuria Velasco-Pérez; Samuel Lozano-Juárez; Beatriz Gil-Arroyo; Juan Marcos Sanz; Nuño Basurto; Daniel Urda; Álvaro Herrero 001 (SOCO (2), 2023)

Editorial of the Special Issue Intelligent Solutions for Efficient Logistics and Sustainable Transportation. - Daniel Urda; Patricia Ruiz; El-Ghazali Talbi; Pascal Bouvry; Jamal Toutouh (Appl. Soft Comput., 2023)

Hourly pollutants forecasting using a deep learning approach to obtain the AQI. - José Antonio Moscoso López; Javier González-Enrique; Daniel Urda; Juan Jesús Ruiz-Aguilar; Ignacio J. Turias (Log. J. IGPL, 2023)

Neonates Crying Detection Through Feature Extraction and Machine Learning Methods. - Lucía Núñez-Calvo; Nuria Velasco-Pérez; Samuel Lozano-Juárez; Álvaro Herrero 001; Juan Arnaez; Daniel Urda (HAIS (1), 2024)

A Computer Vision Approach to Detect Facial Characteristics Related to Encephalopathy in Term Infants. - Nuria Velasco-Pérez; Samuel Lozano-Juárez; Lucía Núñez-Calvo; Nuño Basurto; Juan Arnaez; Daniel Urda (HAIS (1), 2024)

Human Detection in Images Captured by UAVs in Natural Environments. - Félix De Miguel; David Caubilla; Carlos Cambra 001; Nuño Basurto; Daniel Urda; Álvaro Herrero 001 (SOCO (1), 2024)

Enhancing web traffic attacks identification through ensemble methods and feature selection. - Daniel Urda; Branly Martínez; Nuño Basurto; Meelis Kull; Ángel Arroyo; Álvaro Herrero 001 (CoRR, 2024)

Beta-Hebbian Learning to enhance unsupervised exploratory visualizations of Android malware families. - Nuño Basurto; Diego García-Prieto; Héctor Quintián; Daniel Urda; José Luís Calvo-Rolle; Emilio Corchado (Log. J. IGPL, 2024)

Evaluating the Impact of Different Feature as a Counter Data Aggregation approaches on the Performance of NIDSs and Their Selected Features. - Roberto Magán-Carrión; Daniel Urda; Ignacio Díaz-Cano; Bernabé Dorronsoro (Log. J. IGPL, 2024)

A Clustering Extension of HUEPs for the Analysis of Performance Anomalies in Robots. - Nuño Basurto; Carlos Cambra Baseca; Álvaro Herrero 001; Daniel Urda (Cybern. Syst., 2024)

Soft-Computing Techniques to Address Industrial and Environmental Challenges. - Álvaro Herrero 001; Daniel Urda; Esteban Jove; Mariusz Topolski; Emilio Corchado (Cybern. Syst., 2024)

IoT Cyberattack Detection via Fog Computing and Multilayer Perceptron Neural Networks. - Branly Alberto Martínez González; Malena Pérez Sevilla; Jaime Andrés Rincón Arango; Daniel Urda Muñoz (ISDFS, 2025)

Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review. - Arantxa M. Ortega León; Daniel Urda; Ignacio J. Turias; Simón Pedro Lubián-López; Isabel Benavente-Fernández (Frontiers Artif. Intell., 2025)