One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening

Abstract Traditional best practices for quantitative structure activity relationship (QSAR) modeling recommend dataset balancing and balanced accuracy (BA) as the key desired objective of model development. This study explores the value of the conventional norms in the context of using QSAR models f...

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書誌詳細

主要な著者:	James Wellnitz, Sankalp Jain, Joshua E. Hochuli, Travis Maxfield, Eugene N. Muratov, Alexander Tropsha, Alexey V. Zakharov
フォーマット:	Artigo
言語:	Inglês
出版事項:	BMC 2025-01-01
シリーズ:	Journal of Cheminformatics
主題:	Computer-assisted drug discovery QSAR modeling Imbalanced datasets Virtual screening Positive predictive value Hit rate
オンライン･アクセス:	https://doi.org/10.1186/s13321-025-00948-y
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