VenomPred 2.0: A Novel In Silico Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules

The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particularly in lead optimization and ADMET studies, and...

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Veröffentlicht in:	Journal of chemical information and modeling 2024-04, Vol.64 (7), p.2275-2289
Hauptverfasser:	Di Stefano, Miriana, Galati, Salvatore, Piazza, Lisa, Granchi, Carlotta, Mancini, Simone, Fratini, Filippo, Macchia, Marco, Poli, Giulio, Tuccinardi, Tiziano
Format:	Artikel
Sprache:	eng
Schlagworte:	Animals Artificial Intelligence Carcinogenicity Carcinogens Humans Irritation Machine Learning Machine Learning and Deep Learning Mutagenicity Toxicity Toxicology
Online-Zugang:	Volltext
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