Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae-Reference-Cited by-同舟云学术

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae

Published:2023-03-27 Issue:46 Volume:57 Page:18127-18138
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Dong Gongqing¹²,Wang Nan¹²,Xu Ting¹²^ORCID,Liang Jingyu¹²,Qiao Ruxia¹²,Yin Daqiang¹²^ORCID,Lin Sijie¹²^ORCID

Affiliation:

1. College of Environmental Science and Engineering, Biomedical Multidisciplinary Innovation Research Institute, Shanghai East Hospital, Tongji University, Shanghai 200092, China

2. Key Laboratory of Yangtze River Water Environment, Shanghai Institute of Pollution Control and Ecological Security, Tongji University, Shanghai 200092, China

Funder

Central University Basic Research Fund of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c00593

Reference53 articles.

1. Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology

2. Halogenated carbazoles induce cardiotoxicity in developing zebrafish (Danio rerio) embryos