Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.
收藏QSAR DataBank2024-10-21 更新2026-04-25 收录
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https://qsardb.org/repository/handle/10967/264
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资源简介：
Recent years have seen a substantial growth in the adoption of machine learning approaches for the purposes of quantitative structure-activity relationship (QSAR) development. Such a trend has coincided with desire to see a shifting in the focus of methodology employed within chemical safety assessment: away from traditional reliance upon animalintensive in ...
提供机构：
Georgios Chrysochoou, Sulev Sild
创建时间：
2024-10-21
