John Ziebuhr
- Infectious Diseases top 0.02%
- Animal Science and Zoology top 0.02%
- Molecular Biology top 1%
- Computational Theory and Mathematics top 0.1%
- Immunology top 1%
- Co-authors
- Alexander E. GorbalenyaEric J. SnijderLeo L. M. PoonSusan C. BakerChristian DrostenVolker ThielBenjamin W. NeumanRaoul J. de Groot
- Topics
- Viral gastroenteritis research and epidemiology (57 papers)Animal Virus Infections Studies (50 papers)SARS-CoV-2 and COVID-19 Research (49 papers)
- Partner nations
- GermanyNetherlandsUnited States
In The Last Decade
John Ziebuhr
112 papers receiving 17.6k citations
Hit Papers
Peers
Comparison fields: 5 of 188
- Infectious Diseases 12.5k
- Animal Science and Zoology 4.3k
- Molecular Biology 4.2k
- Computational Theory and Mathematics 2.6k
- Immunology 1.6k
Countries citing papers authored by John Ziebuhr
This map shows the geographic impact of John Ziebuhr'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 John Ziebuhr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Ziebuhr more than expected).
Fields of papers citing papers by John Ziebuhr
This network shows the impact of papers produced by John Ziebuhr. 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 John Ziebuhr. The network helps show where John Ziebuhr may publish in the future.
Co-authorship network of co-authors of John Ziebuhr
This figure shows the co-authorship network connecting the top 25 collaborators of John Ziebuhr. A scholar is included among the top collaborators of John Ziebuhr 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 John Ziebuhr. John Ziebuhr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 8 | |
| 6 | 16 | |
| 7 | 70 | |
| 8 | 151 | |
| 9 | 66 | |
| 10 | 2 | |
| 11 | 100 | |
| 12 | 57 | |
| 13 | Ribose 2′-O-methylation provides a molecular signature for the distinction of self and non-self mRNA dependent on the RNA sensor Mda5breakdown → | 612 |
| 14 | 137 | |
| 15 | Unique and Conserved Features of Genome and Proteome of SARS-coronavirus, an Early Split-off From the Coronavirus Group 2 Lineagebreakdown → | 938 |
| 16 | 122 | |
| 17 | 9 | |
| 18 | 2 | |
| 19 | 29 | |
| 20 | 21 |
About John Ziebuhr
John Ziebuhr is a scholar working on Animal Science and Zoology, Infectious Diseases and Cardiology and Cardiovascular Medicine, having authored 113 papers that have together received 18.0k indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (57 papers), Animal Virus Infections Studies (50 papers) and SARS-CoV-2 and COVID-19 Research (49 papers). The work is most often cited by research in Infectious Diseases (12.5k citations), Animal Science and Zoology (4.3k citations) and Computational Theory and Mathematics (2.6k citations). John Ziebuhr has collaborated with scholars based in Germany, Netherlands and United States. Frequent co-authors include Alexander E. Gorbalenya, Eric J. Snijder, Leo L. M. Poon, Susan C. Baker, Christian Drosten, Volker Thiel, Benjamin W. Neuman, Raoul J. de Groot, Stanley Perlman and Ralph S. Baric. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.