Listar GI-RNASA - Artigos por título
Mostrando ítems 141-160 de 195
-
Nanoinformatics: Developing New Computing Applications for Nanomedicine
(Springer, 2012)Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. ... -
NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation
(BioMed Central, 2017-06-07)[Abstract] Background. Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data ... -
Needs, demands and reality of people with neuromuscular disorders users of wheelchair
(Crimson, 2017-11-13)Background: The progressive nature of neuromuscular disease (NMD) results in a reduction in mobility: a person’s ability to move about, or locomotion. Wheelchair is an assistive technology device (AT) that is fundamental ... -
Net-net Auto machine learning (AutoML) prediction of complex ecosystems
(Nature, 2018-08-17)[Abstract] Biological Ecosystem Networks (BENs) are webs of biological species (nodes) establishing trophic relationships (links). Experimental confirmation of all possible links is difficult and generates a huge volume ... -
Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction
(MDPI, 2020-02-14)[Abstract] Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ... -
New machine learning approaches for real-life human activity recognition using smartphone sensor-based data
(Elsevier B.V., 2023)[Abstract]: In recent years, mainly due to the application of smartphones in this area, research in human activity recognition (HAR) has shown a continuous and steady growth. Thanks to its wide range of sensors, its size, ... -
OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
(Springer Nature, 2020-03-24)[Abstract] Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic ... -
Ontologies in medicinal chemistry: current status and future challenges
(Bentham Science, 2013)[Abstract] Recent years have seen a dramatic increase in the amount and availability of data in the diverse areas of medicinal chemistry, making it possible to achieve significant advances in fields such as the design, ... -
Operational thresholds of moored ships at the oil terminal of inner port of A Coruña (Spain)
(Elsevier, 2019-12-21)[Abstract] Minimizing the stay of a vessel in port can lead to improvements in harbor efficiency. Currently, downtimes of cargo operations or their performance reduction because of excessive vessel motion are especially ... -
Optimization of existing equations using a new genetic programming algorithm: application to the shear strength of reinforced concrete beams
(Elsevier, 2012-03-13)[Abstract] A method based on Genetic Programming (GP) to improve previously known empirical equations is presented. From a set of experimental data, the GP may improve the adjustment of such formulas through the symbolic ... -
Optimization of NIR Calibration Models for Multiple Processes in the Sugar Industry
(Elsevier, 2016-10-14)[Abstract] The measurements of Near-Infrared (NIR) Spectroscopy, combined with data analysis techniques, are widely used for quality control in food production processes. This paper presents a methodology to optimize ... -
Parallel computing for brain simulation
(Bentham Science, 2017-05-01)[Abstract] Background: The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not ... -
Perturbation theory/machine learning model of ChEMBL data for dopamine targets: docking, synthesis, and assay of new l-prolyl-l-leucyl-glycinamide peptidomimetics
(American Chemical Society, 2018-05-23)[Abstract] Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning ... -
Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds
(American Chemical Society, 2020-10-14)[Abstract] Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple ... -
Pool-Type FishDesign for a Potamodromous Cyprinid in the Iberian Peninsula: The Iberian Barbel—Synthesis and Future Directions
(M D P I AG, 2020-04-21)[Abstract] The Iberian barbel (Luciobarbus bocagei) is one of the most common cyprinids in the Iberian Peninsula, whose migratory routes are often hampered by anthropogenic barriers. Fishways might be an effective mitigation ... -
Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming
(Taylor & Francis Group, 2019-07-31)[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of ... -
Praxis dese la teoría, ¿es posible la transferencia desde la universidad a la realidad?
(Asociación Profesional Gallega de Terapia Ocupacional, 2015-10)[Resumen] La praxis, entendida como la aplicación de los propios conocimientos teóricos en la práctica, implica una adecuada conceptualización previa y una completa formación en todas las dimensiones filosóficas ... -
Predicting vertical urban growth using genetic evolutionary algorithms in Tokyo’s minato ward
(American Society of Civil Engineers, 2018-03)[Abstract] This article explores the use of evolutionary genetic algorithms to predict scenarios of urban vertical growth in large urban centers. Tokyo’s Minato Ward is used as a case study because it has been one of the ... -
Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning
(MDPI, 2021)[Abstract] The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built ... -
Prediction of Antimalarial Drug-Decorated Nanoparticle Delivery Systems with Random Forest Models
(MDPI, 2020-07)[Abstract]: Drug-decorated nanoparticles (DDNPs) have important medical applications. The current work combined Perturbation Theory with Machine Learning and Information Fusion (PTMLIF). Thus, PTMLIF models were proposed ...