Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
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DOI: 10.1038/s41467-019-13973-x
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Cited by:
- Maximilian T. Strauss & Isabell Bludau & Wen-Feng Zeng & Eugenia Voytik & Constantin Ammar & Julia P. Schessner & Rajesh Ilango & Michelle Gill & Florian Meier & Sander Willems & Matthias Mann, 2024. "AlphaPept: a modern and open framework for MS-based proteomics," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
- Patrick Leopold Rüther & Immanuel Mirnes Husic & Pernille Bangsgaard & Kristian Murphy Gregersen & Pernille Pantmann & Milena Carvalho & Ricardo Miguel Godinho & Lukas Friedl & João Cascalheira & Albe, 2022. "SPIN enables high throughput species identification of archaeological bone by proteomics," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
- Simon Davis & Connor Scott & Janina Oetjen & Philip D. Charles & Benedikt M. Kessler & Olaf Ansorge & Roman Fischer, 2023. "Deep topographic proteomics of a human brain tumour," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
- Vadim Demichev & Lukasz Szyrwiel & Fengchao Yu & Guo Ci Teo & George Rosenberger & Agathe Niewienda & Daniela Ludwig & Jens Decker & Stephanie Kaspar-Schoenefeld & Kathryn S. Lilley & Michael Mülleder, 2022. "dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
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