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DCGAN-DTA: Predicting drug-target binding affinity with deep convolutional generative ...

Retrieved on: 2024-05-09 13:39:26

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Summary

The article discusses machine learning methods applied to medicinal chemistry, focusing on evaluating performance metrics like MSE and CI in quantitative structure-activity relationship (QSAR) models, using datasets like BindingDB, cross-validation, and regression analysis for drug-target affinity (DTA) predictions.

Article found on: bmcgenomics.biomedcentral.com

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