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MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.
Zhang, Xiao-Chen; Wu, Cheng-Kun; Yang, Zhi-Jiang; Wu, Zhen-Xing; Yi, Jia-Cai; Hsieh, Chang-Yu; Hou, Ting-Jun; Cao, Dong-Sheng.
Afiliação
  • Zhang XC; State Key Laboratory of High-Performance Computing, School of Computer Science, National University of Defense Technology, China.
  • Wu CK; State Key Laboratory of High-Performance Computing, School of Computer Science, National University of Defense Technology, China.
  • Yang ZJ; Xiangya School of Pharmaceutical Sciences, Central South University, China.
  • Wu ZX; College of Pharmaceutical Sciences, Zhengjiang University, China.
  • Yi JC; State Key Laboratory of High-Performance Computing, School of Computer Science, National University of Defense Technology, China.
  • Hsieh CY; Tencent Quantum Laboratory since 2018. He received his PhD degree in Physics from the University of Ottawa in 2012 and worked as a postdoctoral researcher at the University of Toronto (2012-2013) and Massachusetts Institute of Technology (2013-2016), respectively. Before joining Tencent, he worked a
  • Hou TJ; College of Pharmaceutical Sciences, Zhejiang University, China.
  • Cao DS; Xiangya School of Pharmaceutical Sciences, Central South University, China.
Brief Bioinform ; 22(6)2021 11 05.
Article em En | MEDLINE | ID: mdl-33951729
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Modelos Teóricos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Modelos Teóricos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article