QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis-Reference-Cited by-同舟云学术

QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis

Published:2018-06-27 Issue:8 Volume:58 Page:1501-1517
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Gadaleta Domenico¹,Manganelli Serena¹,Roncaglioni Alessandra¹,Toma Cosimo¹,Benfenati Emilio¹,Mombelli Enrico²^ORCID

Affiliation:

1. Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Via la Masa 19, 20156 Milano, Italy

2. Unité Modèles pour l’Ecotoxicologie et la Toxicologie (METO), Institut National de l’Environnement Industriel et des Risques (INERIS), 60550 Verneuil en Halatte, France

Funder

European Commission

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00297

Reference62 articles.

1. Endocrine-disrupting chemicals and fatty liver disease

2. The Emerging Role of Endocrine Disruptors in Pathogenesis of Insulin Resistance: A Concept Implicating Nonalcoholic Fatty Liver Disease

3. Endocrine-disrupting Chemicals: Review of Toxicological Mechanisms Using Molecular Pathway Analysis

Cited by 56 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models;Journal of Hazardous Materials;2024-10

2. Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms;Environment & Health;2024-05-28

3. Trend of In Silico Prediction Research Using Adverse Outcome Pathway;Journal of Environmental Health Sciences;2024-04-30

4. Computational models for predicting liver toxicity in the deep learning era;Frontiers in Toxicology;2024-01-19

5. Usage of model combination in computational toxicology;Toxicology Letters;2023-11