Listar GI-RNASA - Artigos por autor "Fernández-Lozano, Carlos"
Mostrando ítems 1-20 de 31
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A methodology for the design of experiments in computational intelligence with multiple regression models
Fernández-Lozano, Carlos; Gestal, M.; Munteanu, Cristian-Robert; Dorado, Julián; Pazos, A. (Peer J, 2016-12-01)[Abstract] The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the ... -
A review on machine learning approaches and trends in drug discovery
Carracedo-Reboredo, Paula; Liñares Blanco, Jose; Rodríguez-Fernández, Nereida; Cedrón, Francisco; Novoa, Francisco; Carballal, Adrián; Maojo, Víctor; Pazos, A.; Fernández-Lozano, Carlos (Research Network of Computational and Structural Biotechnology, 2021)Abstract: Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science ... -
A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer
Alonso-Calvo, Raúl; Paraíso-Medina, Sergio; Pérez-Rey, David; Alonso-Oset, Enrique; Stiphout, Ruud van; Taylor, Marian; Buffa, Francesca; Fernández-Lozano, Carlos; Pazos, A.; Maojo, Víctor (Elsevier, 2017-06-05)[Abstract] Introduction. The introduction of omics data and advances in technologies involved in clinical treatment has led to a broad range of approaches to represent clinical information. Within this context, patient ... -
Applied Computational Techniques on Schizophrenia Using Genetic Mutations
Aguiar-Pulido, Vanessa; Gestal, M.; Fernández-Lozano, Carlos; Rivero, Daniel; Munteanu, Cristian-Robert (Bentham, 2013-03-01)[Abstract] Schizophrenia is a complex disease, with both genetic and environmental influence. Machine learning techniques can be used to associate different genetic variations at different genes with a (schizophrenic or ... -
Authentication of tequilas using pattern recognition and supervised classification
Pérez-Caballero, G.; Andrade-Garda, José Manuel; Olmos, P.; Molina, Y.; Jiménez, I.; Durán, J.J.; Fernández-Lozano, Carlos; Miguel-Cruz, F. (Elsevier, 2017-07-18)[Abstract] Sales of reputed, Mexican tequila grown substantially in last years and, therefore, counterfeiting is increasing steadily. Hence, methodologies intended to characterize and authenticate commercial beverages are ... -
Automatic multiscale vascular image segmentation algorithm for coronary angiography
Carballal, Adrián; Nóvoa, Francisco; Fernández-Lozano, Carlos; García-Guimaraes, Marcos; Aldama López, Guillermo; Calviño-Santos, Ramón; Vázquez Rodríguez, José Manuel; Pazos, A. (Elsevier, 2018-09)[Abstract] Cardiovascular diseases, particularly severe stenosis, are the main cause of death in the western world. The primary method of diagnosis, considered to be the standard in the detection and quantification of ... -
Avoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approach
Carballal, Adrián; Fernández-Lozano, Carlos; Rodríguez-Fernández, Nereida; Castro, M. Luz; Santos-del-Riego, Antonino (Hindawi Limited, 2019)[Abstract]: An important topic in evolutionary art is the development of systems that can mimic the aesthetics decisions made by human begins,e.g., fitness evaluations made by humans using interactive evolution in generative ... -
Carbapenem Resistance in Acinetobacter nosocomialis and Acinetobacter junii Conferred by Acquisition of blaOXA-24/40 and Genetic Characterization of the Transmission Mechanism between Acinetobacter Genomic Species
Lasarte-Monterrubio, Cristina; Guijarro, Paula; Bellés, Alba; Vázquez-Ucha, Juan Carlos; Arca-Suárez, Jorge; Fernández-Lozano, Carlos; Bou, Germán; Beceiro, Alejandro (American Society for Microbiology, 2022)[Abstract] Carbapenem resistance is increasing among Gram-negative bacteria, including the genus Acinetobacter. This study aimed to characterize, for the first time, the development of carbapenem resistance in clinical ... -
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
Munteanu, Cristian-Robert; Fernández-Lozano, Carlos; Mato-Abad, Virginia; Pita-Fernández, Salvador; Álvarez-Linera, Juan; Hernández-Tamames, Juan Antonio; Pazos, A. (Elsevier, 2015-03-30)[Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first ... -
Comparison of Outlier-Tolerant Models for Measuring Visual Complexity
Carballal, Adrián; Fernández-Lozano, Carlos; Rodríguez-Fernández, Nereida; Santos, Iria; Romero, Juan (MDPI AG, 2020-04-24)[Abstract] Providing the visual complexity of an image in terms of impact or aesthetic preference can be of great applicability in areas such as psychology or marketing. To this end, certain areas such as Computer Vision ... -
Experimental Study and ANN Dual-Time Scale Perturbation Model of Electrokinetic Properties of Microbiota
Liu, Yong; Munteanu, Cristian-Robert; Fernández-Lozano, Carlos; Pazos, A.; Ran, Tao; Tan, Zhiliang; Zhou, Chuanshe; Tang, Shaoxun; González-Díaz, Humberto (Frontiers Science, 2017-06-30)[Abstract] The electrokinetic properties of the rumen microbiota are involved in cell surface adhesion and microbial metabolism. An in vitro study was carried out in batch culture to determine the effects of three levels ... -
Experimental study and random forest prediction model of microbiome cell surface hydrophobicity
Liu, Yong; Tang, Shaoxun; Fernández-Lozano, Carlos; Munteanu, Cristian-Robert; Pazos, A.; Yu, Yi-zun; Tan, Zhiliang; González-Díaz, Humberto (Elsevier, 2016-11-09)[Abstract] The cell surface hydrophobicity (CSH) is an assessable physicochemical property used to evaluate the microbial adhesion to the surface of biomaterials, which is an essential step in the microbial biofilm formation ... -
Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classification
Fernández-Lozano, Carlos; Canto, C.; Gestal, M.; Andrade-Garda, José Manuel; Rabuñal, Juan R.; Dorado, Julián; Pazos, A. (Hindawi, 2013-10-21)[Abstract] Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines ... -
Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques
Arceo-Vilas, Alba; Fernández-Lozano, Carlos; Pita, Salvador; Pértega-Díaz, Sonia; Pazos, A. (PeerJ, Ltd., 2020-07-27)[Abstract] Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the nutritional status have determined that the adoption of a ... -
Improving Enzyme Regulatory Protein Classification by Means of SVM-RFE Feature Selection
Fernández-Lozano, Carlos; Fernández-Blanco, Enrique; Dave, Kirtan; Pedreira Souto, Nieves; Gestal, M.; Dorado, Julián; Munteanu, Cristian-Robert (Royal Society of Chemistry, 2014-01-14)[Abstract] Enzyme regulation proteins are very important due to their involvement in many biological processes that sustain life. The complexity of these proteins, the impossibility of identifying direct quantification ... -
Kernel-Based Feature Selection Techniques for Transport Proteins Based on Star Graph Topological Indices
Fernández-Lozano, Carlos; Gestal, M.; Pedreira Souto, Nieves; Postelnicu, Lucian; Dorado, Julián; Munteanu, Cristian-Robert (Bentham, 2013)[Abstract] The transport of the molecules inside cells is a very important topic, especially in Drug Metabolism. The experimental testing of the new proteins for the transporter molecular function is expensive and inefficient ... -
Machine Learning Algorithms Reveals Country-Specific Metagenomic Taxa from American Gut Project Data
Liñares Blanco, Jose; Fernández-Lozano, Carlos; Seoane Fernández, José Antonio; López-Campos, Guillermo (NLM (Medline), 2021)[Abstract] In recent years, microbiota has become an increasingly relevant factor for the understanding and potential treatment of diseases. In this work, based on the data reported by the largest study of microbioma in ... -
Machine learning analysis of TCGA cancer data
Liñares Blanco, Jose; Pazos, A.; Fernández-Lozano, Carlos (PeerJ Inc., 2021)[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas ... -
Machine Learning Analysis of the Human Infant Gut Microbiome Identifies Influential Species in Type 1 Diabetes
Fernández-Edreira, Diego; Liñares Blanco, Jose; Fernández-Lozano, Carlos (Elsevier, 2021)[Abstract] Diabetes is a disease that is closely linked to genetics and epigenetics, yet mechanisms for clarifying the onset and/or progression of the disease have sometimes not been fully managed. In recent years and due ... -
Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
Liñares Blanco, Jose; Fernández-Lozano, Carlos; Seoane Fernández, José Antonio; López-Campos, Guillermo (FRONTIERS MEDIA S.A., 2022)[Abstract] Inflammatory bowel disease (IBD) is a chronic disease with unknown pathophysiological mechanisms. There is evidence of the role of microorganims in this disease development. Thanks to the open access to multiple ...