Novel Bayesian classification models for predicting compounds blocking hERG potassium channels

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作者单位 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China ^[1] Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China;Department of Medicinal Chemistry, School of Pharmacy, Yantai University, Yantai 264005,China ^[2] Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China;School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China ^[3]

关键词 hERG potassium channels long QT syndrome pharmacophore modeling Laplacian-modified Bayesian extended-connectivity fingerprints QSAR

栏目名称 Drug Discovery

DOI 10.1038/aps.2014.35

发布时间 2014-08-26

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中国药理学报（英文版）

2014年35卷8期

1093-1102页

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Novel Bayesian classification models for predicting compounds blocking hERG potassium channels

中国药理学报（英文版）

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中国药理学报（英文版）

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Novel Bayesian classification models for predicting compounds blocking hERG potassium channels

中国药理学报（英文版）

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中国药理学报（英文版）

相关期刊

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