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Combining biomedical knowledge graphs and text to improve predictions for drug-target interactions and drug-indications.
Alshahrani, Mona; Almansour, Abdullah; Alkhaldi, Asma; Thafar, Maha A; Uludag, Mahmut; Essack, Magbubah; Hoehndorf, Robert.
Afiliación
  • Alshahrani M; National Center for Artificial Intelligence (NCAI), Saudi Data and Artificial Intelligence Authority (SDAIA), Riyadh, Saudi Arabia.
  • Almansour A; National Center for Artificial Intelligence (NCAI), Saudi Data and Artificial Intelligence Authority (SDAIA), Riyadh, Saudi Arabia.
  • Alkhaldi A; National Center for Artificial Intelligence (NCAI), Saudi Data and Artificial Intelligence Authority (SDAIA), Riyadh, Saudi Arabia.
  • Thafar MA; College of Computers and Information Technology, Taif University, Taif, Saudi Arabia.
  • Uludag M; Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
  • Essack M; Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
  • Hoehndorf R; Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
PeerJ ; 10: e13061, 2022.
Article en En | MEDLINE | ID: mdl-35402106
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reconocimiento de Normas Patrones Automatizadas / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PeerJ Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reconocimiento de Normas Patrones Automatizadas / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PeerJ Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Estados Unidos