Tim Geppert
Impact in
-
- Computational Drug Discovery Methods
- Endocrinology top 10%
Papers in
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- Computational Drug Discovery Methods 13
-
- Protein Structure and Dynamics 2
- Lipid Membrane Structure and Behavior 1
- Heat shock proteins research 1
- Bioinformatics and Genomic Networks 1
- Co-authors
- Gisbert Schneider (18 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)Gert Carra (1 shared paper)Nicole Tegtmeyer (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (2 papers)PLoS ONE (2 papers)Journal of Computational Chemistry (2 papers)Journal of Biological Chemistry (2 papers)EBioMedicine (1 paper)
- Partner nations
- GermanySwitzerlandAustria
In The Last Decade
Tim Geppert
21 papers receiving 905 citations
Peers
Comparison fields: 5 of 66
- Computational Theory and Mathematics 230
- Endocrinology 31
- Drug Discovery 2
- Molecular Biology 327
- Surgery 205
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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 265 | |
| 2 | 2012 | 153 | |
| 3 | 2012 | 87 | |
| 4 | 2011 | 67 | |
| 5 | 2011 | 55 | |
| 6 | 2011 | 43 | |
| 7 | 2011 | 35 | |
| 8 | 2009 | 30 | |
| 9 | 2011 | 30 | |
| 10 | 2014 | 28 | |
| 11 | 2012 | 26 | |
| 12 | 2014 | 26 | |
| 13 | 2014 | 15 | |
| 14 | 2010 | 14 | |
| 15 | 2011 | 14 | |
| 16 | 2014 | 13 | |
| 17 | 2011 | 12 | |
| 18 | 2014 | 11 | |
| 19 | 2015 | 10 | |
| 20 | 2011 | 8 |
About Tim Geppert
Tim Geppert is a scholar working on Computational Theory and Mathematics, Molecular Biology, Endocrinology, Pharmaceutical Science and Hematology, having authored 21 papers that have together received 949 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Protein Structure and Dynamics (2 papers), Lipid Membrane Structure and Behavior (1 paper), Drug Solubulity and Delivery Systems (1 paper), Heat shock proteins research (1 paper), Acute Myeloid Leukemia Research (1 paper), Helicobacter pylori-related gastroenterology studies (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Computational Theory and Mathematics (230 citations), Endocrinology (31 citations), Drug Discovery (2 citations), Molecular Biology (327 citations) and Surgery (205 citations). Tim Geppert has collaborated with scholars based in Germany, Switzerland and Austria. Frequent co-authors include Gisbert Schneider, Silja Weßler, Norbert Sewald, Steffen Backert, Martin Löwer, Felix Reisen, Gert Carra, Nicole Tegtmeyer, Christiane Weydig and Petra Schneider. Their work appears in journals such as Journal of Chemical Information and Modeling, PLoS ONE, Journal of Computational Chemistry, Journal of Biological Chemistry and EBioMedicine.
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.