Cover Picture: Data Curation can Improve the Prediction Accuracy of Metabolic Intrinsic Clearance (Mol. Inf. 1‐2/2019). Issue 1 (7th February 2019)

• Record Type: Journal Article
• Authors: Esaki, Tsuyoshi; Watanabe, Reiko; Kawashima, Hitoshi; Ohashi, Rikiya; Natsume‐Kitatani, Yayoi; Nagao, Chioko; Mizuguchi, Kenji
• Is Part Of: Molecular informatics. Volume 38:Issue 1/2(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-02-07
• Subjects: Intrinsic clearance -- Drug discovery -- Machine learning -- Metabolic stability -- Molecular modeling; Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.201980101
• Languages: English
• ISSNs: 1868-1743

Abstract

Abstract : The cover picture shows that in the prediction of intrinsic clearance in human liver microsomes (CLint), curating the collected data carefully can improve the prediction accuracy of classifiers. More details can be found in the article by Tsuyoshi Esaki et al., please see DOI:10.1002/minf.201800086