Listar INIBIC-RNASA-IMEDIR - Artigos por data de publicación
Mostrando ítems 21-40 de 46
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Vivencias ocupacionales de personas recientemente jubiladas en el entorno urbano de la provincia de A Coruña
(Universidad de Chile, 2017)[Abstract] Objetivos: En la actualidad, se ha podido observar un envejecimiento progresivo de la población, lo que ha aumentado el interés acerca de la jubilación, ya que la duración de esta será cada vez más prolongada ... -
General machine learning model, review, and experimental-theoretic study of magnolol activity in enterotoxigenic induced oxidative stress
(Bentham Science, 2017)[Abstract] This study evaluated the antioxidative effects of magnolol based on the mouse model induced by Enterotoxigenic Escherichia coli (E. coli, ETEC). All experimental mice were equally treated with ETEC suspensions ... -
Experimental–computational study of carbon nanotube effects on mitochondrial respiration: in silico nano-QSPR machine learning models based on new Raman spectra transform with Markov–Shannon entropy invariants
(ACS Publications, 2017-04-17)[Abstract] The study of selective toxicity of carbon nanotubes (CNTs) on mitochondria (CNT-mitotoxicity) is of major interest for future biomedical applications. In the current work, the mitochondrial oxygen consumption ... -
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 ... -
Estudio fenomenológico sobre la relación entre el envejecimiento activo y la terapia ocupacional en centros de día y residencias de la ciudad de A Coruña
(Universidad de Chile, 2017-06-30)[Resumen] Objetivos: El Envejecimiento Activo se centra en la participación de las personas mayores en los asuntos sociales, económicos, culturales, espirituales y cívicos, y no únicamente en la capacidad de estar activos ... -
Experimental Study and ANN Dual-Time Scale Perturbation Model of Electrokinetic Properties of Microbiota
(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 ... -
SNOMED2HL7: a tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model
(Elsevier, 2017-10)[Abstract] BACKGROUND: Current clinical research and practice requires interoperability among systems in a complex and highly dynamic domain. There has been a significant effort in recent years to develop integrative common ... -
Decrypting strong and weak single-walled carbon nanotubes interactions with mitochondrial voltage-dependent anion channels using molecular docking and perturbation theory
(Nature, 2017-10-16)[Abstract] The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, ... -
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
(MDPI, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
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 ... -
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 ... -
Automatic multiscale vascular image segmentation algorithm for coronary angiography
(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 ... -
Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
(Nature, 2018-10-24)[Abstract] Screening and in silico modeling are critical activities for the reduction of experimental costs. They also speed up research notably and strengthen the theoretical framework, thus allowing researchers to ... -
Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis
(Nature, 2018-11-12)[Abstract] Consensus strategy was proved to be highly efficient in the recognition of gene-disease association. Therefore, the main objective of this study was to apply theoretical approaches to explore genes and communities ... -
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning
(MDPI, 2019)[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known ... -
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)[Abstract] Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ... -
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 ... -
Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis
(M D P I AG, 2020-02-05)[Abstract] Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its ... -
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 ... -
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 ...