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Mostrando ítems 11-20 de 24
Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(Elsevier, 2020-05)
[Abstract]
Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ...
A methodology for the design of experiments in computational intelligence with multiple regression models
(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 ...
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 ...
Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
(Bentham, 2015-09-01)
[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction ...
Experimental and computational studies of fatty acid distribution networks
(Royal Society of Chemistry, 2015-08-06)
[Abstract] Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal ...
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 ...
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 ...
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 ...
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 ...
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. ...