CHEM PTML
Cheminformatics Perturbation-Theory Machine Learning Laboratory
Publicaciones (270) Publicaciones en las que ha participado algún/a investigador/a Ver datos de investigación referenciados.
2024
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From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
Health Information Science and Systems, Vol. 12, Núm. 1
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Identification of Riluzole derivatives as novel calmodulin inhibitors with neuroprotective activity by a joint synthesis, biosensor, and computational guided strategy
Biomedicine and Pharmacotherapy, Vol. 174
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Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family
Journal of Chemical Information and Modeling, Vol. 64, Núm. 6, pp. 1841-1852
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MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products
Journal of Cheminformatics, Vol. 16, Núm. 1
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Machine learning guided prediction of warfarin blood levels for personalized medicine based on clinical longitudinal data from cardiac surgery patients: a prospective observational study
International Journal of Surgery
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Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling
Environmental Science and Technology, Vol. 58, Núm. 23, pp. 10116-10127
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NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study
Journal of Nanobiotechnology, Vol. 22, Núm. 1
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On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems
Beilstein Journal of Nanotechnology, Vol. 15, pp. 535-555
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OptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues
Advanced Science, Vol. 11, Núm. 13
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Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)
Polymers, Vol. 16, Núm. 19
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Warfarin–A natural anticoagulant: A review of research trends for precision medication
Phytomedicine, Vol. 128
2023
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Machine learning in antibacterial discovery and development: A bibliometric and network analysis of research hotspots and trends
Computers in Biology and Medicine, Vol. 155
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Trends in Nanoparticles for Leishmania Treatment: A Bibliometric and Network Analysis
Diseases, Vol. 11, Núm. 4
2022
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A Fuzzy System Classification Approach for QSAR Modeling of αAmylase and α-Glucosidase Inhibitors
Current Computer-Aided Drug Design, Vol. 18, Núm. 7, pp. 469-479
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Machine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds
Molecular Pharmaceutics, Vol. 19, Núm. 7, pp. 2151-2163
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Multi-output chemometrics model for gasoline compounding
Fuel, Vol. 310
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Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives
Journal of chemical information and modeling, Vol. 62, Núm. 16, pp. 3928-3940
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Prediction of acute toxicity of pesticides for Americamysis bahia using linear and nonlinear QSTR modelling approaches
Environmental Research, Vol. 214
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Towards rational nanomaterial design by predicting drug-nanoparticle system interaction vs. bacterial metabolic networks
Environmental Science: Nano, Vol. 9, Núm. 4, pp. 1391-1413
2021
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Ifptml mapping of drug graphs with protein and chromosome structural networks vs. Pre‐clinical assay information for discovery of antimalarial compounds
International Journal of Molecular Sciences, Vol. 22, Núm. 23