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Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes.
Abele, Miriam; Doll, Etienne; Bayer, Florian P; Meng, Chen; Lomp, Nina; Neuhaus, Klaus; Scherer, Siegfried; Kuster, Bernhard; Ludwig, Christina.
  • Abele M; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Division of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Doll E; Division of Microbial Ecology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Bayer FP; Division of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Meng C; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Lomp N; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Neuhaus K; Division of Microbial Ecology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Core Facility Microbiome, ZIEL - Institute for Food & Health, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Scherer S; Division of Microbial Ecology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Kuster B; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Division of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Ludwig C; Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich, Freising, Germany. Electronic address: tina.ludwig@tum.de.
Mol Cell Proteomics ; 22(8): 100612, 2023 08.
Article en En | MEDLINE | ID: mdl-37391045
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteoma / Proteómica Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteoma / Proteómica Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article