In silico prediction of chemical aquatic toxicity for marine crustaceans via machine learning

Aquatic toxicity is a crucial endpoint for evaluating chemically adverse effects on ecosystems. Therefore, we developed in silico methods for the prediction of chemical aquatic toxicity in marine environment. At first, a diverse data set including different crustacean species was constructed. We the...

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Bibliographische Detailangaben
Veröffentlicht in:Toxicol Res (Camb)
Hauptverfasser: Liu, Lin, Yang, Hongbin, Cai, Yingchun, Cao, Qianqian, Sun, Lixia, Wang, Zhuang, Li, Weihua, Liu, Guixia, Lee, Philip W., Tang, Yun
Format: Artigo
Sprache:Inglês
Veröffentlicht: Royal Society of Chemistry 2019
Schlagworte:
Chemistry
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6505403/
https://ncbi.nlm.nih.gov/pubmed/31160968
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1039/c8tx00331a
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