A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products-Reference-Cited by-同舟云学术

A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products

Published:2020-02-11 Issue:9 Volume:142 Page:4114-4120
ISSN:0002-7863
Container-title:Journal of the American Chemical Society
language:en
Short-container-title:J. Am. Chem. Soc.

Author:

Reher Raphael¹,Kim Hyun Woo¹,Zhang Chen¹²^ORCID,Mao Huanru Henry²,Wang Mingxun³,Nothias Louis-Félix³,Caraballo-Rodriguez Andres Mauricio³,Glukhov Evgenia¹,Teke Bahar¹,Leao Tiago¹,Alexander Kelsey L.¹⁴,Duggan Brendan M.³,Van Everbroeck Ezra L.⁵,Dorrestein Pieter C.³^ORCID,Cottrell Garrison W.²,Gerwick William H.¹³^ORCID

Affiliation:

1. Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States

2. Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States

3. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States

4. Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States

5. Director’s Office, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States

Funder

Gordon and Betty Moore Foundation

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Colloid and Surface Chemistry,Biochemistry,General Chemistry,Catalysis

Link

https://pubs.acs.org/doi/pdf/10.1021/jacs.9b13786

Reference55 articles.

1. Lessons from the Past and Charting the Future of Marine Natural Products Drug Discovery and Chemical Biology

2. Natural Products as Sources of New Drugs from 1981 to 2014