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Discovering trends and hotspots of biosafety and biosecurity research via machine learning.
Guan, Renchu; Pang, Haoyu; Liang, Yanchun; Shao, Zhongjun; Gao, Xin; Xu, Dong; Feng, Xiaoyue.
Afiliação
  • Guan R; Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China.
  • Pang H; Zhuhai Sub Laboratory, Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Zhuhai College of Science and Technology, Zhuhai, 519041, Guangdong, China.
  • Liang Y; Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China.
  • Shao Z; Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China.
  • Gao X; Zhuhai Sub Laboratory, Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Zhuhai College of Science and Technology, Zhuhai, 519041, Guangdong, China.
  • Xu D; Department of Epidemiology, Ministry of Education Key Laboratory of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, Shaanxi, China.
  • Feng X; Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia.
Brief Bioinform ; 23(5)2022 09 20.
Article em En | MEDLINE | ID: mdl-35596953
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China