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Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.
Jiang, Dejun; Sun, Huiyong; Wang, Jike; Hsieh, Chang-Yu; Li, Yuquan; Wu, Zhenxing; Cao, Dongsheng; Wu, Jian; Hou, Tingjun.
Afiliación
  • Jiang D; College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, China.
  • Sun H; Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
  • Wang J; Tencent Quantum Laboratory, Tencent, Shenzhen 518057, Guangdong, China.
  • Hsieh CY; Department of Medicinal Chemistry, China Pharmaceutical University, Nanjing 210009, Jiangsu, China.
  • Li Y; Artificial Intelligence Institute, National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan 430072, Hubei, China.
  • Wu Z; Tencent Quantum Laboratory, Tencent, Shenzhen 518057, Guangdong, China.
  • Cao D; College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, China.
  • Wu J; Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
  • Hou T; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410004, Hunan, China.
Brief Bioinform ; 23(2)2022 03 10.
Article en En | MEDLINE | ID: mdl-35062020
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: China
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: China