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. 2022 Sep 15;38(18):4426-4427.
doi: 10.1093/bioinformatics/btac490.

ToxSTAR: drug-induced liver injury prediction tool for the web environment

Hyun Kil Shin  1   2 , Hang-Suk Chun  1 , Sangwoo Lee  1 , Se-Myo Park  1 , Daeui Park  1   2 , Myung-Gyun Kang  1 , Sungbo Hwang  1 , Jung-Hwa Oh  1   2 , Hyoung-Yun Han  1   2 , Woo-Keun Kim  1   2 , Seokjoo Yoon  1   2
Affiliations

ToxSTAR: drug-induced liver injury prediction tool for the web environment

Hyun Kil Shin et al. Bioinformatics. .

Abstract

Summary: Drug-induced liver injury (DILI) is a challenging endpoint in predictive toxicology because of the complex reactive metabolites that cause liver damage and the wide range of mechanisms involved in the development of the disease. ToxSTAR provides structural similarity-based DILI analysis and in-house DILI prediction models that predict four DILI subtypes (cholestasis, cirrhosis, hepatitis and steatosis) based on drug and drug metabolite molecules.

Availability and implementation: ToxSTAR is freely available at https://toxstar.kitox.re.kr/.

Supplementary information: Supplementary data are available at Bioinformatics online.

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