Roland Bruderer

4.0k total citations · 1 hit paper
37 papers, 2.5k citations indexed

About

Roland Bruderer is a scholar working on Molecular Biology, Spectroscopy and Oncology. According to data from OpenAlex, Roland Bruderer has authored 37 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 22 papers in Spectroscopy and 4 papers in Oncology. Recurrent topics in Roland Bruderer's work include Advanced Proteomics Techniques and Applications (21 papers), Mass Spectrometry Techniques and Applications (15 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). Roland Bruderer is often cited by papers focused on Advanced Proteomics Techniques and Applications (21 papers), Mass Spectrometry Techniques and Applications (15 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). Roland Bruderer collaborates with scholars based in Germany, Switzerland and United States. Roland Bruderer's co-authors include Lukas Reiter, Oliver M. Bernhardt, Tejas Gandhi, Olga Vitek, Oliver Rinner, Hemmo Meyer, Jan Muntel, Yulia Butscheid, Saša M. Miladinović and Lin‐Yang Cheng and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Roland Bruderer

31 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues

2015 755 citations Roland Bruderer, Oliver M. Bernhardt et al. Molecular & Cellular Proteomics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Roland Bruderer Germany	20	1.8k	1.0k	403	265	205	37	2.5k
Dorte B. Bekker‐Jensen Denmark	20	2.3k 1.3×	1.2k 1.2×	304 0.8×	360 1.4×	149 0.7×	24	3.0k
Chris Spahr United States	20	1.7k 1.0×	680 0.7×	187 0.5×	238 0.9×	108 0.5×	36	2.4k
Sun‐Il Hwang United States	22	1.8k 1.0×	502 0.5×	305 0.8×	354 1.3×	161 0.8×	44	2.7k
Michael J. Huddleston United States	25	2.9k 1.6×	1.1k 1.1×	593 1.5×	405 1.5×	99 0.5×	33	3.7k
Oliver M. Bernhardt United States	12	1.6k 0.9×	1.3k 1.2×	120 0.3×	129 0.5×	106 0.5×	18	2.2k
Tejas Gandhi United States	12	1.3k 0.7×	951 0.9×	136 0.3×	122 0.5×	107 0.5×	26	1.8k
Willy V. Bienvenut France	26	1.5k 0.9×	414 0.4×	237 0.6×	551 2.1×	129 0.6×	40	2.1k
Emily S. Boja United States	28	1.6k 0.9×	639 0.6×	221 0.5×	148 0.6×	57 0.3×	48	2.4k
Sricharan Bandhakavi United States	19	1.6k 0.9×	371 0.4×	206 0.5×	123 0.5×	174 0.8×	25	2.2k
Cristian Ruse United States	22	2.3k 1.3×	885 0.9×	275 0.7×	157 0.6×	76 0.4×	41	2.9k

Countries citing papers authored by Roland Bruderer

Since Specialization

Citations

This map shows the geographic impact of Roland Bruderer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Roland Bruderer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roland Bruderer more than expected).

Fields of papers citing papers by Roland Bruderer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roland Bruderer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Roland Bruderer. The network helps show where Roland Bruderer may publish in the future.

Co-authorship network of co-authors of Roland Bruderer

This figure shows the co-authorship network connecting the top 25 collaborators of Roland Bruderer. A scholar is included among the top collaborators of Roland Bruderer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Roland Bruderer. Roland Bruderer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Malinovska, Liliana, Simonas Savickas, Marco Tognetti, et al.. (2025). A Flexible End-to-End Automated Sample Preparation Workflow Enables Standardized and Scalable Bottom-up Proteomics. Analytical Chemistry. 97(40). 22116–22131. 2 indexed citations

Deng, Liulin, Brian Adamson, Kyle L. Fort, et al.. (2025). Enhancing Sensitivity in Low-Load Proteomics Orbitrap Workflows via SLIM Integration. Analytical Chemistry. 97(24). 12613–12622.

Bernhardt, Oliver M., Sander Willems, Ino D. Karemaker, et al.. (2025). Enhanced Identifications and Quantification Through Retention Time Down-Sampling in Fast-Cycling Diagonal-PASEF Methods. Molecular & Cellular Proteomics. 25(1). 101480–101480.

Tognetti, Marco, Roland Bruderer, Lukas Reiter, et al.. (2025). Unveiling proteomic and peptide-level modifications in cerebrospinal fluid and plasma in normal cognitive aging. Communications Medicine. 5(1). 474–474.

Bruderer, Roland, et al.. (2024). Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples. Journal of Proteome Research. 23(6). 1926–1936. 12 indexed citations

Lattmann, Evelyn, Marco Tognetti, Julia M. Martínez Gómez, et al.. (2024). Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum. Cellular and Molecular Life Sciences. 81(1). 90–90. 10 indexed citations

Wróbel, Lidia, Sandra Malmgren Hill, Marian Fernandez-Estévez, et al.. (2022). Compounds activating VCP D1 ATPase enhance both autophagic and proteasomal neurotoxic protein clearance. Nature Communications. 13(1). 4146–4146. 23 indexed citations

Bruderer, Roland, et al.. (2022). Limited Proteolysis–Mass Spectrometry to Identify Metabolite–Protein Interactions. Methods in molecular biology. 2554. 69–89. 15 indexed citations

Jin, Ying, Xiaoyu An, Binchen Mao, et al.. (2022). Different syngeneic tumors show distinctive intrinsic tumor-immunity and mechanisms of actions (MOA) of anti-PD-1 treatment. Scientific Reports. 12(1). 3278–3278. 40 indexed citations

10.

Mackmull, Marie‐Therese, Fabian Sesterhenn, Jan Muntel, et al.. (2022). Global, in situ analysis of the structural proteome in individuals with Parkinson’s disease to identify a new class of biomarker. Nature Structural & Molecular Biology. 29(10). 978–989. 29 indexed citations

11.

Tognetti, Marco, Kamil Skłodowski, Sebastian Müller, et al.. (2022). Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area. Journal of Proteome Research. 21(7). 1718–1735. 35 indexed citations

12.

Piazza, Ilaria, Nigel Beaton, Roland Bruderer, et al.. (2020). A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes. Nature Communications. 11(1). 4200–4200. 112 indexed citations

13.

Muntel, Jan, et al.. (2019). Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy. Molecular Omics. 15(5). 348–360. 115 indexed citations

14.

Bruderer, Roland, Jan Muntel, Sebastian Müller, et al.. (2019). Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance. Molecular & Cellular Proteomics. 18(6). 1242–1254. 118 indexed citations

15.

Oostrum, Marc van, Maik Müller, Roland Bruderer, et al.. (2019). Classification of mouse B cell types using surfaceome proteotype maps. Nature Communications. 10(1). 5734–5734. 27 indexed citations

16.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics. Molecular & Cellular Proteomics. mcp.M116.065730–mcp.M116.065730. 4 indexed citations

17.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results. Molecular & Cellular Proteomics. 16(12). 2296–2309. 305 indexed citations

18.

Schaeuble, Karin, Mark A. Hauser, Roland Bruderer, et al.. (2012). Ubiquitylation of the chemokine receptor CCR7 enables efficient receptor recycling and cell migration. Journal of Cell Science. 125(Pt 19). 4463–74. 41 indexed citations

19.

Summer, Heike, Roland Bruderer, & Eilika Weber‐Ban. (2006). Characterization of a new AAA+ protein from archaea. Journal of Structural Biology. 156(1). 120–129. 4 indexed citations

20.

Bruderer, Roland, Catherine Brasseur, & Hemmo Meyer. (2004). The AAA ATPase p97/VCP Interacts with Its Alternative Co-factors, Ufd1-Npl4 and p47, through a Common Bipartite Binding Mechanism. Journal of Biological Chemistry. 279(48). 49609–49616. 127 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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