Predicting chemical ecotoxicity by learning latent space chemical representations

In silico prediction of chemical ecotoxicity (HC(50)) represents an important complement to improve in vivo and in vitro toxicological assessment of manufactured chemicals. Recent application of machine learning models to predict chemical HC(50) yields variable prediction performance that depends on...

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Detalles Bibliográficos
Autores principales: Gao, Feng, Zhang, Wei, Baccarelli, Andrea A., Shen, Yike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044254/
https://www.ncbi.nlm.nih.gov/pubmed/35395577
http://dx.doi.org/10.1016/j.envint.2022.107224

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044254/
https://www.ncbi.nlm.nih.gov/pubmed/35395577
http://dx.doi.org/10.1016/j.envint.2022.107224

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