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Machine learning-based detection of adventitious microbes in T-cell therapy cultures using long-read sequencing.
Strutt, James P B; Natarajan, Meenubharathi; Lee, Elizabeth; Teo, Denise Bei Lin; Sin, Wei-Xiang; Cheung, Ka-Wai; Chew, Marvin; Thazin, Khaing; Barone, Paul W; Wolfrum, Jacqueline M; Williams, Rohan B H; Rice, Scott A; Springs, Stacy L.
Afiliación
  • Strutt JPB; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Natarajan M; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Lee E; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Teo DBL; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Sin WX; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Cheung KW; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Chew M; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Thazin K; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Barone PW; MIT Center for Biomedical Innovation, Massachusetts Institute of Technology , Boston, USA.
  • Wolfrum JM; MIT Center for Biomedical Innovation, Massachusetts Institute of Technology , Boston, USA.
  • Williams RBH; Singapore-MIT Alliance for Research and Technology , Singapore, Singapore.
  • Rice SA; Singapore Centre for Environmental Life Sciences Engineering, Life Sciences Institute, National University of Singapore , Singapore, Singapore.
  • Springs SL; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University , Singapore, Singapore.
Microbiol Spectr ; : e0135023, 2023 Aug 30.
Article en En | MEDLINE | ID: mdl-37646508
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Microbiol Spectr Año: 2023 Tipo del documento: Article País de afiliación: Singapur Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Microbiol Spectr Año: 2023 Tipo del documento: Article País de afiliación: Singapur Pais de publicación: Estados Unidos