Tim Geppert
Impact in
- Endocrinology top 10%
-
- Computational Drug Discovery Methods
Papers in
-
- RNA and protein synthesis mechanisms 4
- Protein Structure and Dynamics 3
- Chemical Synthesis and Analysis 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Gisbert Schneider (19 shared papers)Benjamin Hoy (6 shared papers)Silja Weßler (6 shared papers)Norbert Sewald (2 shared papers)Steffen Backert (2 shared papers)Martin Löwer (2 shared papers)Felix Reisen (8 shared papers)Nicole Tegtmeyer (1 shared paper)
- Journals
- Journal of Computational Chemistry (2 papers)PLoS ONE (2 papers)Journal of Biological Chemistry (2 papers)Journal of Chemical Information and Modeling (2 papers)Future Medicinal Chemistry (1 paper)
- Partner nations
- SwitzerlandGermanyAustria
In The Last Decade
Tim Geppert
23 papers receiving 871 citations
Peers
Comparison fields: 5 of 95
- Endocrinology 56
- Computational Theory and Mathematics 157
- Immunology 147
- Microbiology 43
- Molecular Biology 451
Countries citing papers authored by Tim Geppert
This map shows the geographic impact of Tim Geppert'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 Tim Geppert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Geppert more than expected).
Fields of papers citing papers by Tim Geppert
This network shows the impact of papers produced by Tim Geppert. 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 Tim Geppert. The network helps show where Tim Geppert may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Geppert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 248 | |
| 2 | 2012 | 140 | |
| 3 | 2012 | 83 | |
| 4 | 2011 | 57 | |
| 5 | 2011 | 49 | |
| 6 | 2011 | 34 | |
| 7 | 2011 | 33 | |
| 8 | 2009 | 31 | |
| 9 | 2011 | 26 | |
| 10 | 2014 | 25 | |
| 11 | 2014 | 25 | |
| 12 | 2012 | 24 | |
| 13 | 2011 | 14 | |
| 14 | 2014 | 14 | |
| 15 | 2014 | 12 | |
| 16 | 2010 | 11 | |
| 17 | 2023 | 11 | |
| 18 | 2011 | 11 | |
| 19 | 2015 | 9 | |
| 20 | 2014 | 8 |
About Tim Geppert
Tim Geppert is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Radiology, Nuclear Medicine and Imaging and Immunology, having authored 23 papers that have together received 885 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), RNA and protein synthesis mechanisms (4 papers), Click Chemistry and Applications (3 papers), Protein Structure and Dynamics (3 papers), interferon and immune responses (2 papers), Helicobacter pylori-related gastroenterology studies (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Endocrinology (56 citations), Computational Theory and Mathematics (157 citations), Immunology (147 citations), Microbiology (43 citations) and Molecular Biology (451 citations). Tim Geppert has collaborated with scholars based in Switzerland, Germany and Austria. Frequent co-authors include Gisbert Schneider, Benjamin Hoy, Silja Weßler, Norbert Sewald, Steffen Backert, Martin Löwer, Felix Reisen, Nicole Tegtmeyer, Gert Carra and Peter Schröder. Their work appears in journals such as Journal of Computational Chemistry, PLoS ONE, Journal of Biological Chemistry, Journal of Chemical Information and Modeling and Future Medicinal 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.