From structural features to mouse acute intraperitoneal toxicity prediction: a triple computational toxicology approach for safety assessment of flavonoids.

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Title: From structural features to mouse acute intraperitoneal toxicity prediction: a triple computational toxicology approach for safety assessment of flavonoids.
Authors: Yang Y; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China., Zhang N; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China., Ren T; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China., Zhao L; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China., Zhong R; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China., Lin N; The Department of Clinical Laboratory, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, 223300, Jiangsu, People's Republic of China. hayyln9066@163.com., Sun G; Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, People's Republic of China. sunguohui@bjut.edu.cn.
Source: Molecular diversity [Mol Divers] 2026 Jul 23. Date of Electronic Publication: 2026 Jul 23.
Publication Type: Journal Article
Journal Info: Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-501X
DOI:10.1007/s11030-026-11674-4