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ORCIDJosé A. Castellanos-Garzón
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Journal Articles
- 2020
[j9]María Navarro-Cáceres, José A. Castellanos-Garzón, Javier Bajo:
An Intelligent System to Generate Chord Progressions from Colors with an Artificial Immune System. New Gener. Comput. 38(3): 531-549 (2020)- 2019
- [j8]José A. Castellanos-Garzón, Ernesto Costa, José Luis Jaimes S., Juan M. Corchado
:
An evolutionary framework for machine learning applied to medical data. Knowl. Based Syst. 185 (2019) - 2018
- [j7]Juan Ramos, José A. Castellanos-Garzón, Juan Francisco de Paz, Juan M. Corchado:
A data mining framework based on boundary-points for gene selection from DNA-microarrays: Pancreatic Ductal Adenocarcinoma as a case study. Eng. Appl. Artif. Intell. 70: 92-108 (2018) - [j6]Alfonso González-Briones, José A. Castellanos-Garzón, Yeray Mezquita Martín, Javier Prieto, Juan M. Corchado:
A Framework for Knowledge Discovery from Wireless Sensor Networks in Rural Environments: A Crop Irrigation Systems Case Study. Wirel. Commun. Mob. Comput. 2018: 6089280:1-6089280:14 (2018) - 2017
- [j5]Juan Ramos, Daniel López Sánchez, José A. Castellanos-Garzón, Juan Francisco de Paz, Juan M. Corchado:
A CBR framework with gradient boosting based feature selection for lung cancer subtype classification. Comput. Biol. Medicine 86: 98-106 (2017) - 2014
- [j4]José A. García Coria, José A. Castellanos-Garzón, Juan M. Corchado:
Intelligent business processes composition based on multi-agent systems. Expert Syst. Appl. 41(4): 1189-1205 (2014) - 2013
- [j3]José A. Castellanos-Garzón, Carlos Armando García, Paulo Novais, Fernando Díaz:
A visual analytics framework for cluster analysis of DNA microarray data. Expert Syst. Appl. 40(2): 758-774 (2013) - [j2]José A. Castellanos-Garzón, Fernando Díaz:
An evolutionary computational model applied to cluster analysis of DNA microarray data. Expert Syst. Appl. 40(7): 2575-2591 (2013) - [j1]José A. Castellanos-Garzón, Fernando Díaz:
An Evolutionary and Visual Framework for Clustering of DNA Microarray Data. J. Integr. Bioinform. 10(3) (2013)
Conference and Workshop Papers
- 2019
- [c9]Alfonso González-Briones, Yeray Mezquita Martín, José A. Castellanos-Garzón, Javier Prieto, Juan M. Corchado:
Intelligent multi-agent system for water reduction in automotive irrigation processes. ANT/EDI40 2019: 971-976 - 2018
- [c8]José A. Castellanos-Garzón, Yeray Mezquita Martín, José Luis Jaimes S., Santiago M. López G.:
A Data Mining Approach Applied to Wireless Sensor Neworks in Greenhouses. DCAI (Special Sessions) 2018: 431-436 - [c7]José A. Castellanos-Garzón, Juan Ramos, Yeray Mezquita Martín, Juan F. De Paz, Ernesto Costa:
A Genetic Programming Approach Applied to Feature Selection from Medical Data. PACBB 2018: 200-207 - 2017
- [c6]José A. Castellanos-Garzón, Juan Ramos, Daniel López Sánchez, Juan Francisco de Paz:
An Ensemble Approach for Gene Selection in Gene Expression Data. PACBB 2017: 237-247 - 2016
- [c5]José A. Castellanos-Garzón, Juan Ramos, Alfonso González-Briones, Juan Francisco de Paz:
A Clustering-Based Method for Gene Selection to Classify Tissue Samples in Lung Cancer. PACBB 2016: 99-107 - 2013
- [c4]José A. Castellanos-Garzón, Fernando Díaz:
A Clustering Framework Applied to DNA Microarray Data. PACBB 2013: 15-22 - 2011
- [c3]Carlos Armando García, José A. Castellanos-Garzón, Carlos González Blanco:
Analyzing Gene Expression Data on a 3D Scatter Plot. SOCO 2011: 349-356 - 2009
- [c2]José A. Castellanos-Garzón, Carlos Armando García, Luis Antonio Miguel Quintales:
An Evolutionary Hierarchical Clustering Method with a Visual Validation Tool. IWANN (1) 2009: 367-374 - 2008
- [c1]José A. Castellanos-Garzón, Luis Antonio Miguel Quintales:
Evolutionary Techniques for Hierarchical Clustering Applied to Microarray Data. IWPACBB 2008: 118-127
Editorship
- 2020
- [e1]Florentino Fdez-Riverola, Miguel Rocha, Mohd Saberi Mohamad, Nazar Zaki, José A. Castellanos-Garzón:
Practical Applications of Computational Biology and Bioinformatics, 13th International Conference, PABCC 2019, Avila, Spain, 26-28 June 2019. Advances in Intelligent Systems and Computing 1005, Springer 2020, ISBN 978-3-030-23872-8 [contents]
Coauthor Index
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