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. 2023 Feb 3;15(2):516. doi: 10.3390/pharmaceutics15020516

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© 2023 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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Compound activity predictions for CCR2 using the sequential Keras/TensorFlow model of NN. Histogram of ligand activities as predicted by Keras/TensorFlow. Ligand activities (pChEMBL) were divided into ranges (x-axis). The fraction of the dataset that was assigned to each activity range (in %) was given in brackets. Predicted activity values fell into three categories: overpredicted, underpredicted, and predicted correctly, with (left) and without (right) inactive compounds included in the datasets.