Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach-Reference-Cited by-同舟云学术

Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach

Published:2021-07-26 Issue:15 Volume:55 Page:10875-10887
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Ciallella Heather L.¹,Russo Daniel P.¹²,Aleksunes Lauren M.³,Grimm Fabian A.⁴,Zhu Hao¹²^ORCID

Affiliation:

1. Center for Computational and Integrative Biology, Rutgers University Camden, Camden, New Jersey 08103, United States

2. Department of Chemistry, Rutgers University Camden, Camden, New Jersey 08102, United States

3. Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey 08854, United States

4. ExxonMobil Biomedical Sciences, Inc., Annandale, New Jersey 08801, United States

Funder

National Institute of Environmental Health Sciences

National Center for Advancing Translational Sciences

ExxonMobil research grant for Rutgers University

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.1c02656

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