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Improving protein fold recognition using triplet network and ensemble deep learning.
Liu, Yan; Han, Ke; Zhu, Yi-Heng; Zhang, Ying; Shen, Long-Chen; Song, Jiangning; Yu, Dong-Jun.
Affiliation
  • Liu Y; School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.
  • Han K; School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.
  • Zhu YH; School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.
  • Zhang Y; School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.
  • Shen LC; School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.
  • Song J; Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria 3800, Australia.
  • Yu DJ; Faculty of Information Technology, Monash Centre for Data Science, Monash University, Melbourne, Victoria 3800, Australia.
Brief Bioinform ; 22(6)2021 11 05.
Article in En | MEDLINE | ID: mdl-34226918
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Full text: 1 Database: MEDLINE Main subject: Protein Conformation / Proteins / Models, Molecular / Protein Folding / Computational Biology / Deep Learning Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2021 Type: Article Affiliation country: China
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Full text: 1 Database: MEDLINE Main subject: Protein Conformation / Proteins / Models, Molecular / Protein Folding / Computational Biology / Deep Learning Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2021 Type: Article Affiliation country: China