Neural network activation similarity: a new measure to assist decision making in chemical toxicology-Reference-Cited by-同舟云学术

Neural network activation similarity: a new measure to assist decision making in chemical toxicology

Published:2020 Issue:28 Volume:11 Page:7335-7348
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Allen Timothy E. H.¹²³⁴⁵^ORCID,Wedlake Andrew J.⁵⁶²⁷⁴,Gelžinytė Elena⁵⁶²⁷⁴^ORCID,Gong Charles⁵⁶²⁷⁴,Goodman Jonathan M.⁵⁶²⁷⁴^ORCID,Gutsell Steve⁸⁹¹⁰⁴,Russell Paul J.⁸⁹¹⁰⁴

Affiliation:

1. MRC Toxicology Unit

2. University of Cambridge

3. Leicester

4. UK

5. Centre for Molecular Informatics

6. Department of Chemistry

7. Cambridge

8. Unilever Safety and Environmental Assurance Centre

9. Colworth Science Park

10. Bedfordshire

Abstract

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, ROC-AUC 0.96 ± 0.04).

Funder

Unilever

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/SC/D0SC01637C

Reference52 articles.

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