Neural network activation similarity: a new measure to assist decision making in chemical toxicology.
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ABSTRACT:
SUBMITTER: Allen TEH
PROVIDER: S-EPMC8159362 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
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Neural network activation similarity: a new measure to assist decision making in chemical toxicology.
Allen Timothy E H TEH Wedlake Andrew J AJ Gelžinytė Elena E Gong Charles C Goodman Jonathan M JM Gutsell Steve S Russell Paul J PJ
Chemical science 20200624 28
Deep learning neural networks, constructed for the prediction of chemical binding at 79 pharmacologically important human biological targets, show extremely high performance on test data (accuracy 92.2 ± 4.2%, MCC 0.814 ± 0.093 and ROC-AUC 0.96 ± 0.04). A new molecular similarity measure, Neural Network Activation Similarity, has been developed, based on signal propagation through the network. This is complementary to standard Tanimoto similarity, and the combined use increases confidence in the ...[more]
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