Sudhakar Agnihothram
- Infectious Diseases top 0.2%
- Animal Science and Zoology top 0.2%
- Immunology top 5%
- Molecular Biology
- Epidemiology top 5%
- Co-authors
- Ralph S. BaricBoyd L. YountLisa E. GralinskiVineet D. MenacheryRachel L. GrahamTrevor ScobeyMichael G. KatzeMark T. Heise
- Topics
- SARS-CoV-2 and COVID-19 Research (30 papers)Viral gastroenteritis research and epidemiology (18 papers)Animal Virus Infections Studies (17 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Sudhakar Agnihothram
48 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Infectious Diseases 3.6k
- Animal Science and Zoology 1.2k
- Immunology 668
- Molecular Biology 575
- Epidemiology 473
Countries citing papers authored by Sudhakar Agnihothram
This map shows the geographic impact of Sudhakar Agnihothram'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 Sudhakar Agnihothram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sudhakar Agnihothram more than expected).
Fields of papers citing papers by Sudhakar Agnihothram
This network shows the impact of papers produced by Sudhakar Agnihothram. 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 Sudhakar Agnihothram. The network helps show where Sudhakar Agnihothram may publish in the future.
Co-authorship network of co-authors of Sudhakar Agnihothram
This figure shows the co-authorship network connecting the top 25 collaborators of Sudhakar Agnihothram. A scholar is included among the top collaborators of Sudhakar Agnihothram 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 Sudhakar Agnihothram. Sudhakar Agnihothram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 12 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 10 | |
| 6 | 26 | |
| 7 | Airway Memory CD4 + T Cells Mediate Protective Immunity against Emerging Respiratory Coronavirusesbreakdown → | 339 |
| 8 | 4 | |
| 9 | A SARS-like cluster of circulating bat coronaviruses shows potential for human emergencebreakdown → | 560 |
| 10 | 11 | |
| 11 | Rapid generation of a mouse model for Middle East respiratory syndromebreakdown → | 346 |
| 12 | 24 | |
| 13 | 83 | |
| 14 | 46 | |
| 15 | 81 | |
| 16 | 186 | |
| 17 | 10 | |
| 18 | 195 | |
| 19 | 107 | |
| 20 | 38 |
About Sudhakar Agnihothram
Sudhakar Agnihothram is a scholar working on Infectious Diseases, Animal Science and Zoology and Immunology, having authored 49 papers that have together received 4.3k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (30 papers), Viral gastroenteritis research and epidemiology (18 papers) and Animal Virus Infections Studies (17 papers). The work is most often cited by research in Infectious Diseases (3.6k citations), Animal Science and Zoology (1.2k citations) and Modeling and Simulation (278 citations). Sudhakar Agnihothram has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Ralph S. Baric, Boyd L. Yount, Lisa E. Gralinski, Vineet D. Menachery, Rachel L. Graham, Trevor Scobey, Michael G. Katze, Mark T. Heise, Eric Donaldson and Alan C. Whitmore. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Immunity.
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.