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Current progress and open challenges for applying deep learning across the biosciences.
Sapoval, Nicolae; Aghazadeh, Amirali; Nute, Michael G; Antunes, Dinler A; Balaji, Advait; Baraniuk, Richard; Barberan, C J; Dannenfelser, Ruth; Dun, Chen; Edrisi, Mohammadamin; Elworth, R A Leo; Kille, Bryce; Kyrillidis, Anastasios; Nakhleh, Luay; Wolfe, Cameron R; Yan, Zhi; Yao, Vicky; Treangen, Todd J.
Afiliación
  • Sapoval N; Department of Computer Science, Rice University, Houston, TX, USA.
  • Aghazadeh A; Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA.
  • Nute MG; Department of Computer Science, Rice University, Houston, TX, USA.
  • Antunes DA; Department of Biology and Biochemistry, University of Houston, Houston, TX, USA.
  • Balaji A; Department of Computer Science, Rice University, Houston, TX, USA.
  • Baraniuk R; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
  • Barberan CJ; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
  • Dannenfelser R; Department of Computer Science, Rice University, Houston, TX, USA.
  • Dun C; Department of Computer Science, Rice University, Houston, TX, USA.
  • Edrisi M; Department of Computer Science, Rice University, Houston, TX, USA.
  • Elworth RAL; Department of Computer Science, Rice University, Houston, TX, USA.
  • Kille B; Department of Computer Science, Rice University, Houston, TX, USA.
  • Kyrillidis A; Department of Computer Science, Rice University, Houston, TX, USA.
  • Nakhleh L; Department of Computer Science, Rice University, Houston, TX, USA.
  • Wolfe CR; Department of Computer Science, Rice University, Houston, TX, USA.
  • Yan Z; Department of Computer Science, Rice University, Houston, TX, USA.
  • Yao V; Department of Computer Science, Rice University, Houston, TX, USA.
  • Treangen TJ; Department of Computer Science, Rice University, Houston, TX, USA. treangen@rice.edu.
Nat Commun ; 13(1): 1728, 2022 04 01.
Article en En | MEDLINE | ID: mdl-35365602
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos