Klaus Rumpel

3.6k total citations
24 papers, 884 citations indexed

About

Klaus Rumpel is a scholar working on Molecular Biology, Spectroscopy and Materials Chemistry. According to data from OpenAlex, Klaus Rumpel has authored 24 papers receiving a total of 884 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 8 papers in Spectroscopy and 4 papers in Materials Chemistry. Recurrent topics in Klaus Rumpel's work include Analytical Chemistry and Chromatography (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers) and Ubiquitin and proteasome pathways (4 papers). Klaus Rumpel is often cited by papers focused on Analytical Chemistry and Chromatography (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers) and Ubiquitin and proteasome pathways (4 papers). Klaus Rumpel collaborates with scholars based in United Kingdom, Austria and United States. Klaus Rumpel's co-authors include Alessio Ciulli, Claire Whitworth, Sandra Winkler, Michael J. Roy, Scott J. Hughes, William Farnaby, Ian James, Hendrik Neubert, Graham H. Coombs and Adrian Cohen and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Klaus Rumpel

24 papers receiving 865 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Klaus Rumpel United Kingdom 15 655 237 149 97 68 24 884
Abhinav Kumar United Kingdom 14 423 0.6× 141 0.6× 109 0.7× 61 0.6× 23 0.3× 38 791
Tsuyoshi Konuma Japan 18 859 1.3× 115 0.5× 67 0.4× 18 0.2× 72 1.1× 44 1.1k
Erica M. Pasini Netherlands 19 426 0.7× 137 0.6× 143 1.0× 30 0.3× 114 1.7× 33 1.5k
Harsha P. Gunawardena United States 24 1.1k 1.7× 625 2.6× 122 0.8× 102 1.1× 12 0.2× 53 1.7k
John A. Chakel United States 12 868 1.3× 593 2.5× 53 0.4× 184 1.9× 21 0.3× 20 1.2k
Daniel A. Polasky United States 17 934 1.4× 768 3.2× 75 0.5× 75 0.8× 13 0.2× 30 1.3k
Abel Baerga‐Ortiz Puerto Rico 15 568 0.9× 130 0.5× 30 0.2× 32 0.3× 64 0.9× 36 835
Ignatius J. Kass United States 10 750 1.1× 393 1.7× 35 0.2× 31 0.3× 18 0.3× 11 1.0k
Michael D. McGinley United States 10 572 0.9× 490 2.1× 46 0.3× 38 0.4× 14 0.2× 16 913
Saša Končarević Germany 15 470 0.7× 153 0.6× 67 0.4× 31 0.3× 9 0.1× 20 819

Countries citing papers authored by Klaus Rumpel

Since Specialization
Citations

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

Fields of papers citing papers by Klaus Rumpel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Klaus Rumpel

This figure shows the co-authorship network connecting the top 25 collaborators of Klaus Rumpel. A scholar is included among the top collaborators of Klaus Rumpel 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 Klaus Rumpel. Klaus Rumpel 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.
Geist, Leonhard, et al.. (2022). NMR applications to find and progress TREX1 binders. SHILAP Revista de lepidopterología. 12-13. 100075–100075. 2 indexed citations
2.
Newman, J.A., Simone Lieb, Leonhard Geist, et al.. (2020). Structure of the helicase core of Werner helicase, a key target in microsatellite instability cancers. Life Science Alliance. 4(1). e202000795–e202000795. 18 indexed citations
3.
Beveridge, Rebecca, Dirk Kessler, Klaus Rumpel, et al.. (2020). Native Mass Spectrometry Can Effectively Predict PROTAC Efficacy. ACS Central Science. 6(7). 1223–1230. 43 indexed citations
4.
Suskiewicz, Marcin J., Rebecca Beveridge, Alexander Heuck, et al.. (2019). Structure of McsB, a protein kinase for regulated arginine phosphorylation. Nature Chemical Biology. 15(5). 510–518. 27 indexed citations
5.
Roy, Michael J., Sandra Winkler, Scott J. Hughes, et al.. (2019). SPR-Measured Dissociation Kinetics of PROTAC Ternary Complexes Influence Target Degradation Rate. ACS Chemical Biology. 14(3). 361–368. 239 indexed citations
6.
7.
Gu, Qun, Frank David, Frédéric Lynen, et al.. (2011). Evaluation of automated sample preparation, retention time locked gas chromatography–mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species. Journal of Chromatography A. 1218(21). 3247–3254. 29 indexed citations
8.
Albrow, Victoria E., Carla Fernandes, David M. Beal, et al.. (2011). Quantitative affinity-based chemical proteomics of TrkA inhibitors. MedChemComm. 3(3). 322–325. 1 indexed citations
9.
Gu, Qun, Frank David, Frédéric Lynen, et al.. (2010). Analysis of bacterial fatty acids by flow modulated comprehensive two-dimensional gas chromatography with parallel flame ionization detector/mass spectrometry. Journal of Chromatography A. 1217(26). 4448–4453. 41 indexed citations
10.
Raijmakers, Reinout, et al.. (2010). Target Profiling of a Small Library of Phosphodiesterase 5 (PDE5) Inhibitors using Chemical Proteomics. ChemMedChem. 5(11). 1927–1936. 13 indexed citations
11.
Gu, Qun, Frank David, Lucie Jorge, et al.. (2010). Evaluation of automated sample preparation, retention time locked GC-MS and automated data analysis for the metabolomic study of Arabidopsis species. Ghent University Academic Bibliography (Ghent University). 175–175. 1 indexed citations
12.
O’Flaherty, Martina, et al.. (2009). A chemical proteomics based enrichment technique targeting the interactome of the PDE5 inhibitorPF-4540124. Molecular BioSystems. 5(5). 472–482. 23 indexed citations
13.
Folkers, Gert E., et al.. (2009). Phosphatidylethanolamine‐Binding Proteins, Including RKIP, Exhibit Affinity for Phosphodiesterase‐5 Inhibitors. ChemBioChem. 10(16). 2654–2662. 12 indexed citations
14.
Neubert, Hendrik, Christopher Grace, Klaus Rumpel, & Ian James. (2008). Assessing Immunogenicity in the Presence of Excess Protein Therapeutic Using Immunoprecipitation and Quantitative Mass Spectrometry. Analytical Chemistry. 80(18). 6907–6914. 42 indexed citations
15.
Neubert, Hendrik, et al.. (2008). Label-Free Detection of Differential Protein Expression by LC/MALDI Mass Spectrometry. Journal of Proteome Research. 7(6). 2270–2279. 92 indexed citations
16.
17.
Cohen, Adrian, Klaus Rumpel, Graham H. Coombs, & Jonathan M. Wastling. (2002). Characterisation of global protein expression by two-dimensional electrophoresis and mass spectrometry: proteomics of Toxoplasma gondii. International Journal for Parasitology. 32(1). 39–51. 77 indexed citations
18.
19.
Groppe, Jay C., Klaus Rumpel, Aris N. Economides, et al.. (1998). Biochemical and Biophysical Characterization of RefoldedDrosophila DPP, a Homolog of Bone Morphogenetic Proteins 2 and 4. Journal of Biological Chemistry. 273(44). 29052–29065. 46 indexed citations
20.
Amer, Adel, et al.. (1991). Substituted .gamma.-butyrolactones. Part 37: reactions of (arylmethylene)furandiones with nucleophiles. A novel approach to the cyclolignan lactone skeleton. The Journal of Organic Chemistry. 56(17). 5210–5213. 1 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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