Dominik Kopczynski

897 total citations
27 papers, 479 citations indexed

About

Dominik Kopczynski is a scholar working on Molecular Biology, Spectroscopy and Biomedical Engineering. According to data from OpenAlex, Dominik Kopczynski has authored 27 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 20 papers in Spectroscopy and 5 papers in Biomedical Engineering. Recurrent topics in Dominik Kopczynski's work include Metabolomics and Mass Spectrometry Studies (15 papers), Advanced Proteomics Techniques and Applications (15 papers) and Mass Spectrometry Techniques and Applications (9 papers). Dominik Kopczynski is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (15 papers), Advanced Proteomics Techniques and Applications (15 papers) and Mass Spectrometry Techniques and Applications (9 papers). Dominik Kopczynski collaborates with scholars based in Germany, Austria and United Kingdom. Dominik Kopczynski's co-authors include Robert Ahrends, Albert Sickmann, Nils Hoffmann, René P. Zahedi, Jan Baumbach, Bing Peng, Cristina Coman, Sven Rahmann, F.‐Nora Vögtle and Aslı Aras Taşkin and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Dominik Kopczynski

26 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dominik Kopczynski Germany 12 347 160 61 35 32 27 479
Cristina Coman Germany 14 445 1.3× 207 1.3× 33 0.5× 43 1.2× 59 1.8× 26 657
Ricardo G. Cosso Brazil 11 304 0.9× 137 0.9× 92 1.5× 10 0.3× 40 1.3× 12 606
Åsmund Larsen Norway 10 331 1.0× 190 1.2× 25 0.4× 14 0.4× 36 1.1× 12 424
Nikolay Youhnovski Germany 12 279 0.8× 183 1.1× 276 4.5× 13 0.4× 110 3.4× 19 750
Thomas Züllig Austria 10 539 1.6× 165 1.0× 38 0.6× 10 0.3× 60 1.9× 20 675
Michaela Schwaiger-Haber United States 17 553 1.6× 218 1.4× 61 1.0× 7 0.2× 65 2.0× 20 722
Ethan Stancliffe United States 10 339 1.0× 85 0.5× 42 0.7× 7 0.2× 46 1.4× 15 466
Ashraf G. Madian United States 8 327 0.9× 109 0.7× 17 0.3× 9 0.3× 88 2.8× 11 523
T Sugimoto Japan 14 237 0.7× 48 0.3× 39 0.6× 7 0.2× 45 1.4× 32 590
Xiaoling Zang China 11 247 0.7× 76 0.5× 130 2.1× 15 0.4× 22 0.7× 23 457

Countries citing papers authored by Dominik Kopczynski

Since Specialization
Citations

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

Fields of papers citing papers by Dominik Kopczynski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dominik Kopczynski

This figure shows the co-authorship network connecting the top 25 collaborators of Dominik Kopczynski. A scholar is included among the top collaborators of Dominik Kopczynski 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 Dominik Kopczynski. Dominik Kopczynski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kopczynski, Dominik, Waltraud C. Schrottmaier, Cristina Coman, et al.. (2025). Altered platelet lipidome in bleeding patients with unexplained platelet function defects. Haematologica. 111(1). 300–313.
2.
Benvenuti, Federica, Dominik Kopczynski, Hartmut Schlüter, et al.. (2025). A reference database enabling in-depth proteome and PTM analysis of mouse immune cells. Scientific Data. 12(1). 596–596. 1 indexed citations
3.
Witting, Michael, Adnan Malik, Andrew R. Leach, et al.. (2024). Challenges and perspectives for naming lipids in the context of lipidomics. Metabolomics. 20(1). 15–15. 4 indexed citations
4.
Heimerl, Susanne, Marcus Höring, Dominik Kopczynski, et al.. (2023). Quantification of bulk lipid species in human platelets and their thrombin-induced release. Scientific Reports. 13(1). 7 indexed citations
5.
Liang, Chunguang, Hongli Li, Dominik Kopczynski, et al.. (2023). Pepstatin-Based Probes for Photoaffinity Labeling of Aspartic Proteases and Application to Target Identification. ACS Chemical Biology. 18(4). 686–692. 2 indexed citations
6.
Kopczynski, Dominik, et al.. (2023). Accurate Sphingolipid Quantification Reducing Fragmentation Bias by Nonlinear Models. Analytical Chemistry. 95(41). 15227–15235. 1 indexed citations
7.
Kopczynski, Dominik, et al.. (2023). LORA, Lipid Over-Representation Analysis Based on Structural Information. Analytical Chemistry. 95(34). 12600–12604. 8 indexed citations
8.
Hoffmann, Nils, Gerhard Mayer, Canan Has, et al.. (2022). A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics. Metabolites. 12(7). 584–584. 17 indexed citations
9.
Kopczynski, Dominik, Andreas Hentschel, Cristina Coman, et al.. (2020). Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics. Analytical Chemistry. 92(20). 13672–13676. 1 indexed citations
10.
Kopczynski, Dominik, Nils Hoffmann, Bing Peng, & Robert Ahrends. (2020). Goslin: A Grammar of Succinct Lipid Nomenclature. Analytical Chemistry. 92(16). 10957–10960. 15 indexed citations
11.
Peng, Bing, Dominik Kopczynski, Brian Pratt, et al.. (2020). LipidCreator workbench to probe the lipidomic landscape. Nature Communications. 11(1). 2057–2057. 61 indexed citations
12.
Kopczynski, Dominik, Wout Bittremieux, David Bouyssié, et al.. (2019). Proceedings of the EuBIC Winter School 2019. SHILAP Revista de lepidopterología. 22-23. 4–7. 1 indexed citations
13.
Willems, Sander, David Bouyssié, Dieter Deforce, et al.. (2018). Proceedings of the EuBIC developer's meeting 2018. Journal of Proteomics. 187. 25–27. 3 indexed citations
14.
Kopczynski, Dominik, et al.. (2017). A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations. PLoS ONE. 12(9). e0184321–e0184321. 6 indexed citations
15.
Kopczynski, Dominik, Cristina Coman, René P. Zahedi, et al.. (2017). Multi-OMICS: a critical technical perspective on integrative lipidomics approaches. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1862(8). 808–811. 34 indexed citations
16.
Kopczynski, Dominik, Albert Sickmann, & Robert Ahrends. (2017). Computational proteomics tools for identification and quality control. Journal of Biotechnology. 261. 126–130. 6 indexed citations
17.
Kopczynski, Dominik & Sven Rahmann. (2015). An online peak extraction algorithm for ion mobility spectrometry data. Algorithms for Molecular Biology. 10(1). 17–17. 4 indexed citations
18.
Kopczynski, Dominik, et al.. (2014). A modular computational framework for automated peak extraction from ion mobility spectra. BMC Bioinformatics. 15(1). 25–25. 15 indexed citations
19.
Hauschild, Anne-Christin, et al.. (2013). Peak Detection Method Evaluation for Ion Mobility Spectrometry by Using Machine Learning Approaches. Metabolites. 3(2). 277–293. 22 indexed citations
20.
Kopczynski, Dominik, Jan Baumbach, & Sven Rahmann. (2012). Peak modeling for Ion mobility spectrometry measurements. 1801–1805. 11 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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