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DeepBL: a deep learning-based approach for in silico discovery of beta-lactamases.
Wang, Yanan; Li, Fuyi; Bharathwaj, Manasa; Rosas, Natalia C; Leier, André; Akutsu, Tatsuya; Webb, Geoffrey I; Marquez-Lago, Tatiana T; Li, Jian; Lithgow, Trevor; Song, Jiangning.
Afiliação
  • Wang Y; Biomedicine Discovery Institute and the Department of Biochemistry and Molecular Biology at Monash University, Australia.
  • Li F; Bioinformatics from Monash University, Australia.
  • Bharathwaj M; Department of Microbiology at the Biomedicine Discovery Institute, Monash University, Australia.
  • Rosas NC; Department of Microbiology at the Biomedicine Discovery Institute, Monash University, Australia.
  • Leier A; Department of Genetics and the Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham (UAB) School of Medicine, USA.
  • Akutsu T; University of Tokyo, Japan.
  • Webb GI; La Trobe University, Australia.
  • Marquez-Lago TT; Department of Genetics and the Department of Cell, Developmental and Integrative Biology, UAB School of Medicine, USA.
  • Li J; Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Australia.
  • Lithgow T; Department of Microbiology at Monash University, Australia.
  • Song J; Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia.
Brief Bioinform ; 22(4)2021 07 20.
Article em En | MEDLINE | ID: mdl-33212503
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Beta-Lactamases / Software / Biologia Computacional / Proteoma / Bases de Dados de Proteínas / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Austrália
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Beta-Lactamases / Software / Biologia Computacional / Proteoma / Bases de Dados de Proteínas / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Austrália