Clemens Gröpl

1.8k total citations · 1 hit paper
21 papers, 1.2k citations indexed

About

Clemens Gröpl is a scholar working on Spectroscopy, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Clemens Gröpl has authored 21 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Spectroscopy, 11 papers in Molecular Biology and 8 papers in Computational Theory and Mathematics. Recurrent topics in Clemens Gröpl's work include Advanced Proteomics Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Mass Spectrometry Techniques and Applications (10 papers). Clemens Gröpl is often cited by papers focused on Advanced Proteomics Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Mass Spectrometry Techniques and Applications (10 papers). Clemens Gröpl collaborates with scholars based in Germany, Canada and United Kingdom. Clemens Gröpl's co-authors include Eva Lange, Knut Reinert, Oliver Kohlbacher, Ole Schulz-Trieglaff, Nico Pfeifer, Marc Sturm, Andreas Hildebrandt, Andreas Bertsch, René Hussong and Alexandra Zerck and has published in prestigious journals such as Bioinformatics, BMC Bioinformatics and Journal of Proteome Research.

In The Last Decade

Clemens Gröpl

21 papers receiving 1.2k citations

Hit Papers

OpenMS – An open-source software framework for mass spect... 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Clemens Gröpl Germany 10 1.0k 880 130 64 63 21 1.2k
Eva Lange Germany 6 899 0.9× 783 0.9× 121 0.9× 60 0.9× 59 0.9× 9 1.1k
Wout Bittremieux Belgium 21 1.0k 1.0× 516 0.6× 74 0.6× 28 0.4× 16 0.3× 69 1.4k
John T. Prince United States 20 940 0.9× 483 0.5× 89 0.7× 111 1.7× 34 0.5× 37 1.2k
Jim Shofstahl United Kingdom 5 703 0.7× 530 0.6× 56 0.4× 29 0.5× 13 0.2× 6 831
Stefan Verhoeven Netherlands 16 767 0.8× 245 0.3× 106 0.8× 31 0.5× 31 0.5× 34 939
Rory T. Steven United Kingdom 17 409 0.4× 488 0.6× 91 0.7× 44 0.7× 109 1.7× 32 847
Jenny Forshed Sweden 20 838 0.8× 335 0.4× 114 0.9× 52 0.8× 208 3.3× 32 1.2k
Zsuzsanna Lipták Italy 9 365 0.4× 223 0.3× 35 0.3× 52 0.8× 15 0.2× 32 512
Katharina Nöh Germany 26 1.9k 1.9× 208 0.2× 438 3.4× 94 1.5× 6 0.1× 83 2.2k
Patricia M. Palagi Switzerland 11 481 0.5× 278 0.3× 59 0.5× 14 0.2× 13 0.2× 26 667

Countries citing papers authored by Clemens Gröpl

Since Specialization
Citations

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

Fields of papers citing papers by Clemens Gröpl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Clemens Gröpl

This figure shows the co-authorship network connecting the top 25 collaborators of Clemens Gröpl. A scholar is included among the top collaborators of Clemens Gröpl 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 Clemens Gröpl. Clemens Gröpl 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.
Bielow, Chris, Clemens Gröpl, Oliver Kohlbacher, & Knut Reinert. (2011). Bioinformatics for Qualitative and Quantitative Proteomics. Methods in molecular biology. 719. 331–349. 4 indexed citations
2.
Bertsch, Andreas, Clemens Gröpl, Knut Reinert, & Oliver Kohlbacher. (2010). OpenMS and TOPP: Open Source Software for LC-MS Data Analysis. Methods in molecular biology. 353–367. 58 indexed citations
3.
Schulz-Trieglaff, Ole, Nico Pfeifer, Clemens Gröpl, Oliver Kohlbacher, & Knut Reinert. (2008). LC-MSsim – a simulation software for liquid chromatography mass spectrometry data. BMC Bioinformatics. 9(1). 423–423. 41 indexed citations
4.
Sturm, Marc, Andreas Bertsch, Clemens Gröpl, et al.. (2008). OpenMS – An open-source software framework for mass spectrometry. BMC Bioinformatics. 9(1). 163–163. 500 indexed citations breakdown →
5.
Lange, Eva, Ralf Tautenhahn, Steffen Neumann, & Clemens Gröpl. (2008). Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements. BMC Bioinformatics. 9(1). 375–375. 134 indexed citations
6.
Bodirsky, Manuel, Clemens Gröpl, & Mihyun Kang. (2008). Generating unlabeled connected cubic planar graphs uniformly at random. Random Structures and Algorithms. 32(2). 157–180. 2 indexed citations
7.
Schulz-Trieglaff, Ole, René Hussong, Clemens Gröpl, et al.. (2008). Computational Quantification of Peptides from LC-MS Data. Journal of Computational Biology. 15(7). 685–704. 10 indexed citations
8.
Bodirsky, Manuel, Clemens Gröpl, Daniel Johannsen, & Mihyun Kang. (2007). A direct decomposition of 3-connected planar graphs. Max Planck Institute for Plasma Physics. 5 indexed citations
9.
Bodirsky, Manuel, Clemens Gröpl, & Mihyun Kang. (2007). Generating labeled planar graphs uniformly at random. Theoretical Computer Science. 379(3). 377–386. 11 indexed citations
10.
Kohlbacher, Oliver, Knut Reinert, Clemens Gröpl, et al.. (2007). TOPP—the OpenMS proteomics pipeline. Bioinformatics. 23(2). e191–e197. 217 indexed citations
11.
Lange, Eva, Clemens Gröpl, Ole Schulz-Trieglaff, et al.. (2007). A geometric approach for the alignment of liquid chromatography—mass spectrometry data. Bioinformatics. 23(13). i273–i281. 75 indexed citations
12.
Reinert, Knut, Oliver Kohlbacher, Clemens Gröpl, et al.. (2006). OpenMS - A Framework for Quantitative HPLC/MS-Based Proteomics. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations
13.
Lange, Eva, Clemens Gröpl, Knut Reinert, Oliver Kohlbacher, & Andreas Hildebrandt. (2005). HIGH-ACCURACY PEAK PICKING OF PROTEOMICS DATA USING WAVELET TECHNIQUES. PubMed. 243–254. 70 indexed citations
14.
Gröpl, Clemens, Hans Jürgen Prömel, & Anand Srivastav. (2004). Ordered binary decision diagrams and the Shannon effect. Discrete Applied Mathematics. 142(1-3). 67–85. 3 indexed citations
15.
Frömmel, Cornelius, Christoph Gille, Andrean Goede, et al.. (2003). Accelerating screening of 3D protein data with a graph theoretical approach. Bioinformatics. 19(18). 2442–2447. 9 indexed citations
16.
Gröpl, Clemens, et al.. (2002). Steiner trees in uniformly quasi-bipartite graphs. Information Processing Letters. 83(4). 195–200. 8 indexed citations
17.
Gröpl, Clemens, et al.. (2001). Lower Bounds for Approximation Algorithms for the Steiner Tree Problem. 217–228. 7 indexed citations
18.
Gröpl, Clemens, Hans Jürgen Prömel, & Anand Srivastav. (2001). On the evolution of the worst-case OBDD size. Information Processing Letters. 77(1). 1–7. 3 indexed citations
19.
Gröpl, Clemens, et al.. (2000). Approximating Minimum Spanning Sets in Hypergraphs and Polymatroids. 5 indexed citations
20.
Gröpl, Clemens, Hans Jürgen Prömel, & Anand Srivastav. (1998). Size and Structure of Random Ordered Binary Decision Diagrams (Extended Abstract). 238–248. 3 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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