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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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| Опубликовано в: : | Toxicol Res (Camb) |
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| Главные авторы: | , , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Royal Society of Chemistry
2019
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| Предметы: | |
| Online-ссылка: | 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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