Predicting Potent Compounds Using a Conditional Variational Autoencoder Based upon a New Structure–Potency Fingerprint

Prediction of the potency of bioactive compounds generally relies on linear or nonlinear quantitative structure–activity relationship (QSAR) models. Nonlinear models are generated using machine learning methods. We introduce a novel approach for potency prediction that depends on a newly designed mo...

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