Making in silico predictive models for toxicology FAIR-Reference-Cited by-同舟云学术

Making in silico predictive models for toxicology FAIR

Published:2023-05 Issue: Volume:140 Page:105385
ISSN:0273-2300
Container-title:Regulatory Toxicology and Pharmacology
language:en
Short-container-title:Regulatory Toxicology and Pharmacology

Author:

Cronin Mark T.D.^ORCID,Belfield Samuel J.^ORCID,Briggs Katharine A.^ORCID,Enoch Steven J.^ORCID,Firman James W.^ORCID,Frericks Markus,Garrard Clare^ORCID,Maccallum Peter H.^ORCID,Madden Judith C.^ORCID,Pastor Manuel^ORCID,Sanz Ferran^ORCID,Soininen Inari^ORCID,Sousoni Despoina^ORCID

Publisher

Elsevier BV

Subject

Toxicology,General Medicine

Reference43 articles.

1. Determination of “fitness-for-purpose” of quantitative structure-activity relationship (QSAR) models to predict (eco-)toxicological endpoints for regulatory use;Belfield;Regul. Toxicol. Pharmacol.,2021

2. Ontology-based data integration for advancing toxicological knowledge;Boyles;Curr. Opin. Toxicol.,2019

3. Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data;Briggs;ALTEX,2021

4. QSAR modeling of different minimum potency levels for in vitro human CAR activation and inhibition and screening of 80,086 REACH and 54,971 U.S. substances;Chinen;Comput. Toxicol.,2020

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4. Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms;Science Advances;2024-03-08

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