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. Author manuscript; available in PMC: 2024 Aug 1.
Published in final edited form as: Nature. 2023 Dec 20;626(7997):177–185. doi: 10.1038/s41586-023-06887-8

Extended Data Fig. 2. Comparison of deep learning models for predicting antibiotic activity.

Extended Data Fig. 2.

a, b, Precision-recall curves for predictions of antibiotic activity, for an ensemble of 10 Chemprop models without RDKit features (a) and the best-performing random forest classifier model based on Morgan fingerprints (b), trained and tested using data from a screen of 39,312 molecules (Fig. 1 of the main text). The black dashed line represents the baseline fraction of active compounds in the training set (1.3%). Blue curves and the 95% confidence interval indicate the variation generated by bootstrapping. AUC, area under the curve.