A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening-Reference-Cited by-同舟云学术

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A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening

Published:2023-09-25 Issue:46 Volume:57 Page:18236-18245
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Fan Fan¹,Wu Gang¹,Yang Yining²,Liu Fu¹,Qian Yuli¹,Yu Qingmiao¹³,Ren Hongqiang¹^ORCID,Geng Jinju¹³^ORCID

Affiliation:

1. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, Jiangsu, P. R. China

2. School of Life Sciences, Tsinghua University, Beijing 100084, China

3. Key Laboratory of the Three Gorges Reservoir Region’s Eco-Environment, Ministry of Education, Chongqing University, Chongqing 400044, China

Funder

the Natural Science Foundation of China

the Jiangsu Natural Science Foundation of China

the China Postdoctoral Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c04571

Reference58 articles.

1. Occurrence and In Vitro Bioactivity of Estrogen, Androgen, and Glucocorticoid Compounds in a Nationwide Screen of United States Stream Waters

2. Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

3. Endocrine-disrupting chemicals and endocrine neoplasia: A forty-year systematic review

4. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

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