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Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes.
Yu, Katharine; Basu, Amrita; Yau, Christina; Wolf, Denise M; Goodarzi, Hani; Bandyopadhyay, Sourav; Korkola, James E; Hirst, Gillian L; Asare, Smita; DeMichele, Angela; Hylton, Nola; Yee, Douglas; Esserman, Laura; van 't Veer, Laura; Sirota, Marina.
Afiliación
  • Yu K; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States.
  • Basu A; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
  • Yau C; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
  • Wolf DM; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, United States.
  • Goodarzi H; University of California, San Francisco, San Francisco, CA, United States.
  • Bandyopadhyay S; University of California, San Francisco, San Francisco, CA, United States.
  • Korkola JE; Oregon Health and Science University, Portland, OR, United States.
  • Hirst GL; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
  • Asare S; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States.
  • DeMichele A; QuantumLeap Healthcare Collaborative, San Francisco, CA, United States.
  • Hylton N; University of Pennsylvania, Philadelphia, PA, United States.
  • Yee D; University of California, San Francisco, San Francisco, CA, United States.
  • Esserman L; University of Minnesota, Minneapolis, MN, United States.
  • van 't Veer L; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
  • Sirota M; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, United States.
Front Oncol ; 13: 1192208, 2023.
Article en En | MEDLINE | ID: mdl-37384294
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Oncol Año: 2023 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 Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos