SkinSensDB: a curated database for skin sensitization assays

Chia Chi Wang, Ying Chi Lin, Shan Shan Wang, Chieh Shih, Yi Hui Lin, Chun Wei Tung

研究成果: 雜誌貢獻文章同行評審

13 引文 斯高帕斯(Scopus)


Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment. Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assays have reshaped the assessment of skin sensitizers. The integration of multiple assays as key events in the AOP has been shown to have improved prediction performance. Current computational models to predict skin sensitization mainly based on in vivo assays without incorporating alternative in vitro assays. However, there are few freely available databases integrating both the in vivo and the in vitro skin sensitization assays for development of AOP-based skin sensitization prediction models. To facilitate the development of AOP-based prediction models, a skin sensitization database named SkinSensDB has been constructed by curating data from published AOP-related assays. In addition to providing datasets for developing computational models, SkinSensDB is equipped with browsing and search tools which enable the assessment of new compounds for their skin sensitization potentials based on data from structurally similar compounds. SkinSensDB is publicly available at .

頁(從 - 到)1-6
期刊Journal of Cheminformatics
出版狀態已發佈 - 1月 31 2017

ASJC Scopus subject areas

  • 電腦科學應用
  • 物理與理論化學
  • 電腦繪圖與電腦輔助設計
  • 圖書館與資訊科學


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