Presentation Information

[1O05-03-03]Machine learning-based prediction of hERG channel inhibitory potency from molecular structure

*Dahun Jeong1, Satoshi Shimizu1, Masami Kodama1, Nagomi Kurebayashi2, Ryousuke Ishida3, Hiroyuki Kagechika3, Manyong Jeong4, Igor Vorobyov5, Junko Kurokawa1 (1.Department of Bio-informational Pharmacology, Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, 2.Department of Pharmacology, Juntendo University School of Medicine, 3.Division of Medicinal Chemistry, Institute of Biomaterials and Bioengineering, Institute of Integrated Research, Institute of Science Tokyo, 4.Department of Electronic Control Engineering, National Institute of Technology, Numazu College, 5.Department of Physiology and Membrane Biology, University of California, Davis, School of Medicine)

Keywords:

hERG channel

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