Mathias J. Gerl
- Cell Biology top 1%
- Cellular transport and secretion 8
- Biochemistry top 1%
- Molecular Biology top 2%
- Metabolomics and Mass Spectrometry Studies 15
- Lipid Membrane Structure and Behavior 10
- Sphingolipid Metabolism and Signaling 6
- Virology top 5%
- Physiology top 5%
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- Diabetes, Cardiovascular Risks, and Lipoproteins 6
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- Lipoproteins and Cardiovascular Health 4
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- Adipokines, Inflammation, and Metabolic Diseases 4
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- Genetic Associations and Epidemiology 4
- Co-authors
- Kai SimonsChristian KloseAndrej ShevchenkoJúlio L. SampaioMichał A. SurmaChrister S. EjsingHartmut BeugBritta Brügger
- Journals
- Cell (1 paper)Proceedings of the National Academy of Sciences (1 paper)Journal of Biological Chemistry (2 papers)
- Partner nations
- GermanyUnited StatesFinland
In The Last Decade
Mathias J. Gerl
43 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Cell Biology 903
- Biochemistry 321
- Molecular Biology 2.7k
- Virology 107
- Physiology 539
Countries citing papers authored by Mathias J. Gerl
This map shows the geographic impact of Mathias J. Gerl'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 Mathias J. Gerl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathias J. Gerl more than expected).
Fields of papers citing papers by Mathias J. Gerl
This network shows the impact of papers produced by Mathias J. Gerl. 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 Mathias J. Gerl. The network helps show where Mathias J. Gerl may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mathias J. Gerl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2022 | 38 | |
| 5 | 2022 | 29 | |
| 6 | 2021 | 15 | |
| 7 | 2021 | 11 | |
| 8 | 2021 | 5 | |
| 9 | 2021 | 54 | |
| 10 | 2020 | 15 | |
| 11 | 2018 | 52 | |
| 12 | 2017 | 62 | |
| 13 | 2017 | 18 | |
| 14 | 2017 | 38 | |
| 15 | 2012 | 218 | |
| 16 | 2012 | 232 | |
| 17 | Revitalizing membrane rafts: new tools and insightsbreakdown → | 2010 | 994 |
| 18 | 2009 | 316 | |
| 19 | 2009 | 5 | |
| 20 | 2006 | 103 |
About Mathias J. Gerl
Mathias J. Gerl is a scholar working on Cell Biology, Molecular Biology and Endocrine and Autonomic Systems, having authored 44 papers that have together received 3.6k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (15 papers), Lipid Membrane Structure and Behavior (10 papers), Cellular transport and secretion (8 papers), Sphingolipid Metabolism and Signaling (6 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipoproteins and Cardiovascular Health (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and Genetic Associations and Epidemiology (4 papers). The work is most often cited by research in Cell Biology (903 citations), Biochemistry (321 citations) and Molecular Biology (2.7k citations). Mathias J. Gerl has collaborated with scholars based in Germany, United States and Finland. Frequent co-authors include Kai Simons, Christian Klose, Andrej Shevchenko, Júlio L. Sampaio, Michał A. Surma, Christer S. Ejsing, Hartmut Beug, Britta Brügger, Felix Meyenhofer and Charles Ferguson. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.