Eugen Damoc

6.2k total citations · 3 hit papers
47 papers, 4.0k citations indexed

About

Eugen Damoc is a scholar working on Spectroscopy, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Eugen Damoc has authored 47 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Spectroscopy, 22 papers in Molecular Biology and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Eugen Damoc's work include Mass Spectrometry Techniques and Applications (34 papers), Advanced Proteomics Techniques and Applications (31 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Eugen Damoc is often cited by papers focused on Mass Spectrometry Techniques and Applications (34 papers), Advanced Proteomics Techniques and Applications (31 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Eugen Damoc collaborates with scholars based in Germany, United States and Netherlands. Eugen Damoc's co-authors include Alexander Makarov, Eduard Denisov, Oliver Lange, Matthias Mann, Stevan Horning, Albert J. R. Heck, Annette Michalski, Jüergen Cox, Andreas Wieghaus and Rebecca Rose and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Angewandte Chemie International Edition.

In The Last Decade

Eugen Damoc

46 papers receiving 3.9k 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.

Mass Spectrometry-based Proteomics Using Q Exactive, a High-performance Benchtop Quadrupole Orbitrap Mass Spectrometer

2011 617 citations Annette Michalski, Eugen Damoc et al. Molecular & Cellular Proteomics profile →
A Dual Pressure Linear Ion Trap Orbitrap Instrument with Very High Sequencing Speed

2009 372 citations Jae C. Schwartz, Eugen Damoc et al. Molecular & Cellular Proteomics profile →
High-sensitivity Orbitrap mass analysis of intact macromolecular assemblies

2012 318 citations Eugen Damoc, Eduard Denisov et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eugen Damoc Germany	29	2.4k	2.3k	401	271	235	47	4.0k
Eckhard Nordhoff Germany	34	2.7k 1.1×	2.4k 1.0×	498 1.2×	213 0.8×	200 0.9×	56	4.6k
John T. Stults United States	37	3.0k 1.3×	2.6k 1.1×	363 0.9×	310 1.1×	170 0.7×	72	5.0k
Eduard Denisov Germany	22	2.0k 0.8×	2.7k 1.1×	216 0.5×	176 0.6×	265 1.1×	32	3.7k
Oliver Lange Germany	14	3.3k 1.4×	2.9k 1.3×	254 0.6×	107 0.4×	223 0.9×	17	5.0k
Michael S. Westphall United States	44	4.0k 1.7×	3.6k 1.5×	622 1.6×	138 0.5×	146 0.6×	111	6.5k
Stevan Horning United States	26	3.7k 1.5×	3.7k 1.6×	336 0.8×	133 0.5×	339 1.4×	39	6.2k
Péter Juhász United States	26	3.7k 1.6×	3.9k 1.7×	339 0.8×	127 0.5×	254 1.1×	53	6.0k
Anil Shukla United States	33	1.7k 0.7×	1.8k 0.8×	376 0.9×	80 0.3×	182 0.8×	108	3.8k
Don L. Rempel United States	32	1.3k 0.6×	2.1k 0.9×	222 0.6×	162 0.6×	242 1.0×	77	3.0k
Thomas J. D. Jørgensen Denmark	42	3.3k 1.4×	3.1k 1.3×	269 0.7×	271 1.0×	175 0.7×	110	6.6k

Countries citing papers authored by Eugen Damoc

Since Specialization

Citations

This map shows the geographic impact of Eugen Damoc'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 Eugen Damoc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eugen Damoc more than expected).

Fields of papers citing papers by Eugen Damoc

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eugen Damoc. 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 Eugen Damoc. The network helps show where Eugen Damoc may publish in the future.

Co-authorship network of co-authors of Eugen Damoc

This figure shows the co-authorship network connecting the top 25 collaborators of Eugen Damoc. A scholar is included among the top collaborators of Eugen Damoc 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 Eugen Damoc. Eugen Damoc 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

He, Yuchen, Ka Yang, Martin Zeller, et al.. (2025). TMT-Based Multiplexed (Chemo)Proteomics on the Orbitrap Astral Mass Spectrometer. Molecular & Cellular Proteomics. 24(5). 100968–100968. 1 indexed citations

Bubis, Julia A., Tabiwang N. Arrey, Eugen Damoc, et al.. (2025). Challenging the Astral mass analyzer to quantify up to 5,300 proteins per single cell at unseen accuracy to uncover cellular heterogeneity. Nature Methods. 22(3). 510–519. 16 indexed citations

Zeller, Martin, Anna Pashkova, Eugen Damoc, et al.. (2025). In-depth plasma N-glycoproteome profiling using narrow-window data-independent acquisition on the Orbitrap Astral mass spectrometer. Nature Communications. 16(1). 2497–2497. 7 indexed citations

Serrano, Lia R., Trenton M. Peters-Clarke, Tabiwang N. Arrey, et al.. (2024). The One Hour Human Proteome. Molecular & Cellular Proteomics. 23(5). 100760–100760. 23 indexed citations

Yu, Xuan, Anna Pashkova, Mark Zeller, et al.. (2024). B-146 Unlocking the potential of large-cohort proteomics studies with the Orbitrap Astral mass platform. Clinical Chemistry. 70(Supplement_1). 1 indexed citations

Fu, Qin, Niveda Sundararaman, Eugen Damoc, et al.. (2024). A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data‐Independent Acquisition Mass Spectrometry (DIA‐MS) Discovery. Angewandte Chemie. 136(52).

Waterbeemd, Michiel van de, Sem Tamara, Kyle L. Fort, et al.. (2018). Dissecting ribosomal particles throughout the kingdoms of life using advanced hybrid mass spectrometry methods. Nature Communications. 9(1). 2493–2493. 63 indexed citations

Wohlschlager, Therese, Kai Scheffler, Wolfgang Esser‐Skala, et al.. (2018). Native mass spectrometry combined with enzymatic dissection unravels glycoform heterogeneity of biopharmaceuticals. Nature Communications. 9(1). 1713–1713. 88 indexed citations

Fornelli, Luca, Daniel Ayoub, Konstantin Aizikov, et al.. (2017). Top-down analysis of immunoglobulin G isotypes 1 and 2 with electron transfer dissociation on a high-field Orbitrap mass spectrometer. Journal of Proteomics. 159. 67–76. 51 indexed citations

10.

Gault, Joseph, Idlir Liko, Jonathan T. S. Hopper, et al.. (2016). High-resolution mass spectrometry of small molecules bound to membrane proteins. Nature Methods. 13(4). 333–336. 199 indexed citations

11.

Scheltema, Richard A., Jan-Peter Hauschild, Oliver Lange, et al.. (2014). The Q Exactive HF, a Benchtop Mass Spectrometer with a Pre-filter, High-performance Quadrupole and an Ultra-high-field Orbitrap Analyzer. Molecular & Cellular Proteomics. 13(12). 3698–3708. 249 indexed citations

12.

Michalski, Annette, Eugen Damoc, Oliver Lange, et al.. (2011). Ultra High Resolution Linear Ion Trap Orbitrap Mass Spectrometer (Orbitrap Elite) Facilitates Top Down LC MS/MS and Versatile Peptide Fragmentation Modes. Molecular & Cellular Proteomics. 11(3). O111.013698–O111.013698. 282 indexed citations

13.

Damoc, Eugen, Christopher S. Fraser, Min Zhou, et al.. (2007). Structural Characterization of the Human Eukaryotic Initiation Factor 3 Protein Complex by Mass Spectrometry. Molecular & Cellular Proteomics. 6(7). 1135–1146. 104 indexed citations

14.

Bai, Yu, Eugen Damoc, Jan Ripper, et al.. (2007). Lung alveolar proteomics of bronchoalveolar lavage from a pulmonary alveolar proteinosis patient using high-resolution FTICR mass spectrometry. Analytical and Bioanalytical Chemistry. 389(4). 1075–1085. 12 indexed citations

15.

Otto, Vivianne I., Eugen Damoc, Thomas Schürpf, et al.. (2006). N-Glycan structures and N-glycosylation sites of mouse soluble intercellular adhesion molecule-1 revealed by MALDI-TOF and FTICR mass spectrometry. Glycobiology. 16(11). 1033–1044. 30 indexed citations

16.

Bı́lková, Zuzana, Annalisa Castagna, Gianluigi Zanusso, et al.. (2005). Immunoaffinity reactors for prion protein qualitative analysis. PROTEOMICS. 5(3). 639–647. 17 indexed citations

17.

Damoc, Eugen, et al.. (2004). Identification of N -glycosylation sites of the murine neural cell adhesion molecule NCAM by MALDI-TOF and MALDI-FTICR mass spectrometry. Analytical and Bioanalytical Chemistry. 378(4). 1129–1135. 23 indexed citations

18.

Bai, Yu, et al.. (2004). High resolution mass spectrometric alveolar proteomics: Identification of surfactant protein SP‐A and SP‐D modifications in proteinosis and cystic fibrosis patients. PROTEOMICS. 4(8). 2300–2309. 32 indexed citations

19.

Macht, Marcus, Andreas Marquardt, Sören‐Oliver Deininger, et al.. (2003). "Affinity-proteomics": direct protein identification from biological material using mass spectrometric epitope mapping. Analytical and Bioanalytical Chemistry. 378(4). 1102–1111. 27 indexed citations

20.

Damoc, Eugen, Nikolay Youhnovski, David Crettaz, Jean‐Daniel Tissot, & Michael Przybylski. (2003). High resolution proteome analysis of cryoglobulins using Fourier transform‐ion cyclotron resonance mass spectrometry. PROTEOMICS. 3(8). 1425–1433. 31 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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