Listar RNASA-IMEDIR por título
Mostrando ítems 34-49 de 49
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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, ... -
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 ... -
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 ... -
Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks
(Springer Nature, 2020-05-22)[Abstract] Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. ... -
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 ... -
Prediction of Nucleoitide Binding Peptides Using Star Graph Topological Índices
(Elsevier, 2015-08-05)[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this ... -
Redesign and performance of an automatic segmentation method
(MDPI, 2018-09-05)[Resumen] La información más relevante de las angiografías coronarias se extrae empleando técnicas de segmentación, que pueden ser automáticas, semiautomáticas o manuales. Existen numerosos algoritmos de segmentación ... -
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 ... -
Tecnologías para la medicina participativa y la promoción de la salud en la población mayor: Geria-TIC
(2018)[Resumen] El principal objetivo del presente estudio es determinar el impacto en la calidad de vida de un programa de intervención multifactorial implementado con personas mayores institucionalizadas, que presenten ... -
Texture Analysis in Gel Electrophoresis Images Using an Integrative Kernel-Based Approach
(Nature, 2016-01-13)[Abstract] Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several ... -
UAV Swarm Path Planning With Reinforcement Learning for Field Prospecting
(Springer, 2022-03-03)[Abstract] There has been steady growth in the adoption of Unmanned Aerial Vehicle (UAV) swarms by operators due to their time and cost benefits. However, this kind of system faces an important problem, which is the ... -
Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils
(Emerald, 2016-06)[Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ... -
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 ...