<i>In Vitro</i> Biodescriptors Derived from Time Series Toxicogenomics Data in <i>In Silico</i> QSAR Improve the Phenotypic Toxicity Prediction-Reference-Cited by-同舟云学术

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In Vitro Biodescriptors Derived from Time Series Toxicogenomics Data in In Silico QSAR Improve the Phenotypic Toxicity Prediction

Published:2023-12-27 Issue: Volume: Page:
ISSN:2690-0637
Container-title:ACS ES&T Water
language:en
Short-container-title:ACS EST Water

Author:

Rahman Sheikh Mokhlesur¹²^ORCID,Lan Jiaqi¹^ORCID,Gou Na¹,Alshawabkeh Akram¹,Gu April Z.¹³^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, Northeastern University, Boston 02115, Massachusetts, United States

2. Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh

3. School of Civil and Environmental Engineering, Cornell University, Ithaca 14853, New York, United States

Funder

National Institute of Environmental Health Sciences

Environmental Protection Agency

Northeastern University

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Water Science and Technology,Environmental Chemistry,Chemistry (miscellaneous),Chemical Engineering (miscellaneous)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestwater.3c00350

Reference71 articles.

1. Toxicity Testing in the 21st Century: Bringing the Vision to Life

2. A Quantitative Toxicogenomics Assay for High-throughput and Mechanistic Genotoxicity Assessment and Screening of Environmental Pollutants

3. The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform

4. Transforming Environmental Health Protection

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3. Applications of Artificial Intelligence, Machine Learning, and Data Analytics in Water Environments;ACS ES&T Water;2024-03-08

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