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Mostrando ítems 11-17 de 17
Molecular Docking and Machine Learning Analysis of Abemaciclib in Colon Cancer
(BioMed Central Ltd., 2020-07-08)
[Abstract]
Background -
The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is ...
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 ...
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 ...
Applying Artificial Intelligence for Operating System Fingerprinting
(MDPI, 2021)
[Abstract] In the field of computer security, the possibility of knowing which specific version of an operating system is running behind a machine can be useful, to assist in a penetration test or monitor the devices ...
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 ...
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy
(BMC, 2024-03-07)
[Absctract]: For understanding a chemical compound’s mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed ...
MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products
(BMC, 2024-01-23)
[Absctract]: The enantioselective Brønsted acid-catalyzed α-amidoalkylation reaction is a useful procedure is for the production of new drugs and natural products. In this context, Chiral Phosphoric Acid (CPA) catalysts ...