Mario Thevis

15.4k total citations
497 papers, 12.3k citations indexed

About

Mario Thevis is a scholar working on Endocrinology, Diabetes and Metabolism, Cell Biology and Spectroscopy. According to data from OpenAlex, Mario Thevis has authored 497 papers receiving a total of 12.3k indexed citations (citations by other indexed papers that have themselves been cited), including 309 papers in Endocrinology, Diabetes and Metabolism, 161 papers in Cell Biology and 110 papers in Spectroscopy. Recurrent topics in Mario Thevis's work include Hormonal and reproductive studies (276 papers), Muscle metabolism and nutrition (157 papers) and Mass Spectrometry Techniques and Applications (95 papers). Mario Thevis is often cited by papers focused on Hormonal and reproductive studies (276 papers), Muscle metabolism and nutrition (157 papers) and Mass Spectrometry Techniques and Applications (95 papers). Mario Thevis collaborates with scholars based in Germany, Switzerland and United States. Mario Thevis's co-authors include Wilhelm Schänzer, Andreas Thomas, Hans Geyer, Thomas Piper, Ute Mareck, Sven Guddat, Georg Opfermann, Maxie Kohler, Tiia Kuuranne and Philippe Delahaut and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Mario Thevis

482 papers receiving 11.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mario Thevis Germany 53 6.9k 3.5k 2.9k 2.7k 2.1k 497 12.3k
Wilhelm Schänzer Germany 55 7.0k 1.0× 3.5k 1.0× 2.8k 1.0× 2.3k 0.9× 2.3k 1.1× 345 11.8k
Andreas Thomas Germany 45 3.1k 0.5× 1.6k 0.4× 1.5k 0.5× 1.4k 0.5× 867 0.4× 229 5.8k
Martial Saugy Switzerland 45 3.2k 0.5× 1.7k 0.5× 1.1k 0.4× 1.3k 0.5× 880 0.4× 183 6.0k
Hans Geyer Germany 39 3.0k 0.4× 1.7k 0.5× 895 0.3× 842 0.3× 977 0.5× 155 5.1k
Jordi Segura Spain 46 2.4k 0.3× 710 0.2× 1.6k 0.6× 1.3k 0.5× 1.2k 0.5× 242 7.6k
Peter Van Eenoo Belgium 37 2.7k 0.4× 938 0.3× 1.3k 0.4× 710 0.3× 1.2k 0.5× 174 4.4k
Francesco Botrè Italy 36 1.6k 0.2× 766 0.2× 873 0.3× 1.1k 0.4× 630 0.3× 268 4.9k
Óscar J. Pozo Spain 51 2.1k 0.3× 444 0.1× 1.9k 0.6× 1.6k 0.6× 952 0.4× 206 7.7k
F.T. Delbeke Belgium 37 2.0k 0.3× 751 0.2× 996 0.3× 496 0.2× 925 0.4× 156 3.8k
Duane D. Miller United States 65 2.3k 0.3× 1.3k 0.4× 488 0.2× 6.2k 2.3× 290 0.1× 407 13.7k

Countries citing papers authored by Mario Thevis

Since Specialization
Citations

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

Fields of papers citing papers by Mario Thevis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Thevis

This figure shows the co-authorship network connecting the top 25 collaborators of Mario Thevis. A scholar is included among the top collaborators of Mario Thevis 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 Mario Thevis. Mario Thevis 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.
2.
Angelis, Yiannis S., P. Sakellariou, Mario Thevis, et al.. (2025). Further Insights Into the Metabolism of LGD‐4033 in Human Urine. Part 1. Structure Elucidation of Additional Important Metabolites. Drug Testing and Analysis. 18(2). 245–259.
4.
Thevis, Mario, et al.. (2025). Transdermal Uptake of Substances Banned in Sports and Its Relevance for Doping Controls. International Journal of Sports Medicine. 47(2). 95–113. 1 indexed citations
5.
Thomas, Andreas, Katja Walpurgis, & Mario Thevis. (2024). Chromatographic–mass spectrometric analysis of peptidic analytes (2–10 kDa) in doping control urine samples. Journal of Mass Spectrometry. 59(1). e4996–e4996. 1 indexed citations
6.
Richard, Vincent R., Azad Eshghi, Yassene Mohammed, et al.. (2024). Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies. Journal of Proteome Research. 23(5). 1779–1787. 4 indexed citations
7.
Thomas, Andreas, et al.. (2023). Analysis of Potential Gene Doping Preparations for Transgenic DNA in the Context of Sports Drug Testing Programs. International Journal of Molecular Sciences. 24(21). 15835–15835. 13 indexed citations
8.
Thomas, Andreas, et al.. (2023). Dried blood spots for doping controls—Development of a comprehensive initial testing procedure with fully automated sample preparation. Biomedical Chromatography. 37(8). e5633–e5633. 15 indexed citations
9.
Mürdter, Thomas E., Georg Heinkele, Matthias Schwab, et al.. (2023). Identification and synthesis of ( Z )‐3′‐hydroxy clomiphene as a new potential doping‐relevant metabolite of clomiphene. Rapid Communications in Mass Spectrometry. 37(17). e9599–e9599. 5 indexed citations
10.
Toutain, Pierre‐Louis, et al.. (2023). Control of a sulfadoxine/trimethoprim combination in the competition horse: Elimination, metabolism and detection following an intravenous administration. Drug Testing and Analysis. 15(6). 629–645. 1 indexed citations
11.
Sobolevsky, Tim, Katja Walpurgis, Matthew Fedoruk, et al.. (2023). Detection of capromorelin in urine following oral and dermal routes of administration. Drug Testing and Analysis. 15(11-12). 1449–1453. 4 indexed citations
12.
Herzig, David, Gemma Reverter‐Branchat, Michele Schiavon, et al.. (2023). Counter-regulatory responses to postprandial hypoglycaemia in patients with post-bariatric hypoglycaemia vs surgical and non-surgical control individuals. Diabetologia. 66(4). 741–753. 10 indexed citations
13.
Piper, Thomas, et al.. (2022). Usefulness of serum androgen isotope ratio mass spectrometry (IRMS) to detect testosterone supplementation in women. Drug Testing and Analysis. 15(4). 465–469. 3 indexed citations
14.
Sobolevsky, Tim, Thomas Piper, Brian Ahrens, & Mario Thevis. (2022). AICAr to SAICAr ratio can serve as additional marker of AICAr use. Drug Testing and Analysis. 14(11-12). 2017–2025. 3 indexed citations
16.
Knoop, André, Andreas Thomas, & Mario Thevis. (2018). Development of a mass spectrometry based detection method for the mitochondrion‐derived peptide MOTS‐c in plasma samples for doping control purposes. Rapid Communications in Mass Spectrometry. 33(4). 371–380. 18 indexed citations
17.
Piper, Thomas, Xin Wang, Daniel Sejer Pedersen, et al.. (2017). Several possible toxicological and genetic tools for the extension of the detection window after GHB intake. Research at the University of Copenhagen (University of Copenhagen). 1 indexed citations
18.
Arsene, Cristian, et al.. (2017). Growth hormone isoform‐differential mass spectrometry for doping control purposes. Drug Testing and Analysis. 10(6). 938–946. 11 indexed citations
19.
Guddat, Sven, et al.. (2011). Di(2‐ethylhexyl) phthalate metabolites as markers for blood transfusion in doping control: Intra‐individual variability of urinary concentrations. Drug Testing and Analysis. 3(11-12). 892–895. 15 indexed citations
20.
Thevis, Mario, Alexander Makarov, Stevan Horning, & Wilhelm Schänzer. (2005). Mass spectrometry of stanozolol and its analogues using electrospray ionization and collision‐induced dissociation with quadrupole‐linear ion trap and linear ion trap‐orbitrap hybrid mass analyzers. Rapid Communications in Mass Spectrometry. 19(22). 3369–3378. 59 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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