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Now showing items 11-20 of 38
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 ...
Early Detection of Depression: Social Network Analysis and Random Forest Techniques
(J M I R Publications, Inc., 2019-06-10)
[Abstract] Background: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, ...
Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment
(M D P I AG, 2019-07-31)
[Abstract]The prediction of metabolic activities in silico form is crucial to be able to address all research possibilities without exceeding the experimental costs. In particular, for cancer research, the prediction of ...
NLOS Identification and Mitigation Using Low-Cost UWB Devices
(M D P I AG, 2019-08-08)
[Abstract] Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate ...
Visual complexity modelling based on image features fusion of multiple kernels
(PeerJ, Ltd., 2019-07-18)
[Abstract] Humans’ perception of visual complexity is often regarded as one of the key principles of aesthetic order, and is intimately related to the physiological, neurological and, possibly, psychological characteristics ...
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 ...
Authentication of tequilas using pattern recognition and supervised classification
(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 ...
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
(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 ...
Monitorización del estado de rodamientos basada en técnicas de aprendizaje automático
(Universidade da Coruña, Servizo de Publicacións, 2019)
[Resumen] En la actualidad, los procesos de fabricación están adoptando nuevas soluciones basadas en la aplicación de técnicas de aprendizaje automático, que permiten llevar a cabo la monitorización de los procesos en ...
Interpretable market segmentation on high dimension data
(M D P I AG, 2018-09-17)
[Abstract] Obtaining relevant information from the vast amount of data generated by interactions in a market or, in general, from a dyadic dataset, is a broad problem of great interest both for industry and academia. Also, ...
