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Automation to Enable High-Throughput Chemical Proteomics.
Lin, Zongtao; Gongora, Joanna; Liu, Xingyu; Xie, Yixuan; Zhao, Chenfeng; Lv, Dongwen; Garcia, Benjamin A.
Afiliação
  • Lin Z; Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Gongora J; Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
  • Liu X; Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Xie Y; Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Zhao C; Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Lv D; McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Garcia BA; Department of Biochemistry and Structural Biology and Center for Innovative Drug Discovery, School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, United States.
J Proteome Res ; 22(12): 3676-3682, 2023 12 01.
Article em En | MEDLINE | ID: mdl-37917986
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Proteômica Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Proteômica Idioma: En Ano de publicação: 2023 Tipo de documento: Article