Michael Gecht
Impact in
- Structural Biology top 5%
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- SARS-CoV-2 detection and testing
Papers in
-
- Sphingolipid Metabolism and Signaling 2
- Lipid Membrane Structure and Behavior 2
- Bacillus and Francisella bacterial research 1
- ATP Synthase and ATPases Research 1
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- Cellular transport and secretion 2
- Co-authors
- Gerhard Hummer (7 shared papers)Roberto Covino (5 shared papers)Mateusz Sikora (3 shared papers)Sören von Bülow (3 shared papers)Florian E.C. Blanc (2 shared papers)Christoph Schürmann (1 shared paper)Ger van Zandbergen (1 shared paper)Jacomine Krijnse Locker (1 shared paper)
- Journals
- The Journal of Cell Biology (1 paper)PLoS Computational Biology (1 paper)Science (1 paper)Molecular Cell (1 paper)The Journal of Chemical Physics (1 paper)
- Partner nations
- GermanyJapanUnited States
In The Last Decade
Michael Gecht
8 papers receiving 662 citations
Michael Gecht's Hit Papers
Peers
Comparison fields: 5 of 88
- Structural Biology 36
- Infectious Diseases 388
- Animal Science and Zoology 54
- Molecular Biology 357
- Cell Biology 68
Countries citing papers authored by Michael Gecht
This map shows the geographic impact of Michael Gecht'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 Michael Gecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gecht more than expected).
Fields of papers citing papers by Michael Gecht
This network shows the impact of papers produced by Michael Gecht. 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 Michael Gecht. The network helps show where Michael Gecht may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Gecht, 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 | In situ structural analysis of SARS-CoV-2 spike reveals flexibility mediated by three hinges Hit paper breakdown → | 2020 | 430 |
| 2 | 2021 | 92 | |
| 3 | 2018 | 52 | |
| 4 | 2019 | 45 | |
| 5 | 2024 | 28 | |
| 6 | 2020 | 11 | |
| 7 | 2019 | 8 | |
| 8 | 2020 | 2 |
About Michael Gecht
Michael Gecht is a scholar working on Molecular Biology, Cell Biology, Infectious Diseases, Hardware and Architecture and Radiology, Nuclear Medicine and Imaging, having authored 8 papers that have together received 668 indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (2 papers), Lipid Membrane Structure and Behavior (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Parallel Computing and Optimization Techniques (2 papers), Cellular transport and secretion (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Bacillus and Francisella bacterial research (1 paper) and ATP Synthase and ATPases Research (1 paper). The work is most often cited by research in Structural Biology (36 citations), Infectious Diseases (388 citations), Animal Science and Zoology (54 citations), Molecular Biology (357 citations) and Cell Biology (68 citations). Michael Gecht has collaborated with scholars based in Germany, Japan and United States. Frequent co-authors include Gerhard Hummer, Roberto Covino, Mateusz Sikora, Sören von Bülow, Florian E.C. Blanc, Christoph Schürmann, Ger van Zandbergen, Jacomine Krijnse Locker, Martin Beck and Shyamal Mosalaganti. Their work appears in journals such as The Journal of Cell Biology, PLoS Computational Biology, Science, Molecular Cell and The Journal of Chemical Physics.
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.