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ADME Evaluation in Drug Discovery. 8. The Prediction of Human Intestinal Absorption by a Support Vector Machine
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Outgoing claims: the papers this work cites, builds on, or argues with.
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inferred← citeshttps://doi.org/10.2174/1573409915666190716143601openalex-snapshot
A Drug Decision Support System for Developing a Successful Drug Candidate Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.22159/ijap.2024v16i2.49855openalex-snapshot
EXPLORATION OF THE ACTIVE COMPOUNDS OF MORINGA OLEIFERA LAM AS HIV-1 REVERSE TRANSCRIPTASE INHIBITOR: A NETWORK PHARMACOLOGY AND MOLECULAR DOCKING APPROACH
inferred← citeshttps://doi.org/10.2217/fmb-2019-0040openalex-snapshot
Hydrazone, Benzohydrazones and Isoniazid-Acylhydrazones as Potential Antituberculosis Agents
inferred← citeshttps://doi.org/10.24377/ljmu.t.00004554openalex-snapshot
Development of in silico models for the prediction of toxicity incorporating ADME information
inferred← citeshttps://doi.org/10.33483/jfpau.1327078openalex-snapshot
İLAÇ TASARIMINDA YAPAY ZEKÂ UYGULAMALARI
inferred← citeshttps://doi.org/10.3390/catal16100874openalex-snapshot
Synthesis, Cytotoxic Evaluation, Molecular Docking, and In Silico ADME Studies of Novel Quinazolinone-Based Aldazine Derivatives Using Chitosan Sulfonic Acid as a Recyclable Catalyst
inferred← citeshttps://doi.org/10.3390/foods14132202openalex-snapshot
Antioxidant Activity In Vitro and Protective Effects Against Lipopolysaccharide-Induced Oxidative Stress and Inflammation in RAW264.7 Cells of Ulva prolifera-Derived Bioactive Peptides Identified by Virtual Screening, Molecular Docking, and Dynamics Simulations
inferred← citeshttps://doi.org/10.3390/life14020233openalex-snapshot
Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery
inferred← citeshttps://doi.org/10.3390/ma16206687openalex-snapshot
Machine Learning Prediction of the Redox Activity of Quinones
inferred← citeshttps://doi.org/10.3390/molecules30020257openalex-snapshot
Drug Screening of Flavonoids as Potential VEGF Inhibitors Through Computational Docking and Cell Models
inferred← citeshttps://doi.org/10.3390/molecules30112345openalex-snapshot
Design, Synthesis, and Biological Evaluations of a Novel Resveratrol-Type Analogue Against VEGF
inferred← citeshttps://doi.org/10.3390/pharmaceutics15112619openalex-snapshot
The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery
inferred← citeshttps://doi.org/10.3390/pharmaceutics16060776openalex-snapshot
Predicting ADMET Properties from Molecule SMILE: A Bottom-Up Approach Using Attention-Based Graph Neural Networks
inferred← citeshttps://doi.org/10.35414/akufemubid.1432554openalex-snapshot
Imidazole and Quinoline-Based Promising Agent for Cancer Treatment; Synthesis, Characterization, and Computational Calculations
inferred← citeshttps://doi.org/10.54195/9789493296145openalex-snapshot
Pharmaceuticals, toxicity and antimicrobial resistance. Advancing human health and environmental risk assessment
inferred← citeshttps://doi.org/10.5747/ce.2014.v06.n4.e096openalex-snapshot
PROPRIEDADES FARMACOCINÉTICAS E INTERAÇÃO DE HÍBRIDOS DE IBUPROFENO E PRODUTOS NATURAIS COM PROSTAGLANDINA G/H SINTASE 2
inferred← citeshttps://doi.org/10.6084/m9.figshare.14053374openalex-snapshot
Additional file 1 of Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
inferred← citeshttps://doi.org/10.6084/m9.figshare.14053377openalex-snapshot
Additional file 2 of Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
inferred← citeshttps://doi.org/10.6084/m9.figshare.14053380openalex-snapshot
Additional file 3 of Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
inferred← citeshttps://doi.org/10.6084/m9.figshare.26576171openalex-snapshot
Additional file 1 of Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods
inferred← citeshttps://doi.org/10.6084/m9.figshare.26576174openalex-snapshot
Additional file 2 of Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods
inferred← citeshttps://doi.org/10.70675/562e0758zcff7z49c4za806z3dded388daa0openalex-snapshot
Développement d'une plateforme de prédiction in silico des propriétés ADME-Tox
inferred← citeshttps://doi.org/10.9734/ajbgmb/2023/v15i2329openalex-snapshot
In-silico Investigation of Potential Inhibitors of 11-β-Hydroxysteroid Dehydrogenase
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