Author

R. Bruderer

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biochemistry· 2 Cell Biology· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 4 Assay:proteomics· 4 Research Focus:cell type annotation· 3 Research Focus:differential expression· 3 Organism:human· 3 Organism:mouse· 2 Research Focus:deconvolution· 1 Assay:flow cytometry· 1

Frequent Co-Authors

L. Reiter· 4 shared B. Schilling· 2 shared J. Bons· 2 shared J. Campisi· 2 shared S. K. Patel· 2 shared A. J. Brenes· 1 shared A. Rolink· 1 shared B. Wollscheid· 1 shared

Activity by Year

2019-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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4 shared papersCell Biology

L. Reiter

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Exosomes Released from Senescent Cells and Circulatory Exosomes Isolated from Human Plasma Reveal Aging-associated Proteomic and Lipid Signatures

S. K. Patel, J. Bons, J. P. Rose, J. R. Chappel, R. L. Beres, M. Watson, C. Webster, J. B. Burton, R. Bruderer, P. Y. Desprez, L. Reiter, J. Campisi, E. Baker, B. Schilling

This study identifies aging-associated proteomic and lipid signatures in exosomes from senescent cells and human plasma, revealing shared biomarkers and pathways linked to senescence and tissue damage.

bioRxiv · Jun 22, 2024Cell Biology

Optimising Spectronaut search parameters to improve data quality with minimal proteome coverage reductions in DIA analyses of heterogeneous samples

C. P. Baker, R. Bruderer, J. C. Abbott, S. Arthur, A. J. Brenes

The paper optimizes Spectronaut search parameters to reduce false positives in DIA proteomics with minimal loss of true positives in heterogeneous samples.

bioRxiv · Oct 11, 2023 · PreprintBiochemistry

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area

M. Tognetti, K. Sklodowski, S. Mueller, D. Kamber, J. Muntel, R. Bruderer, L. Reiter

The paper develops a deep plasma profiling method to identify biomarker candidates for cancers, finding that low-abundance proteins are critical for accurate classification.

bioRxiv · Oct 5, 2021 · PreprintCancer Biology

Comprehensive Profiling of Plasma Exosomes Using Data Independent Acquisitions, New Tools for Aging Cohort Studies

S. K. Patel, R. Bruderer, N. Basisty, J. Bons, P.-Y. Desprez, F. Neri, L. Reiter, J. Campisi, B. Schilling

The paper develops a method to isolate and analyze plasma exosomes, identifying age-related protein and miRNA differences in an aging cohort.

bioRxiv · Feb 27, 2021 · PreprintCell Biology

De novo Classification of Mouse B Cell Types using Surfaceome Proteotype Maps

M. van Oostrum, M. Mueller, F. Klein, R. Bruderer, H. Zhang, P. Pedrioli, L. Reiter, P. Tsapogas, A. Rolink, B. Wollscheid

The paper develops autoCSC, a miniaturized surfaceome mapping technology, to classify mouse B cell types and identify developmental subpopulations.

bioRxiv · Apr 26, 2019Biochemistry