Kumar Singh Saikatendu
- Infectious Diseases top 2%
- Molecular Biology
- Animal Science and Zoology top 2%
- Computational Theory and Mathematics top 2%
- Immunology
- Co-authors
- Raymond C. StevensMichael J. BuchmeierPeter KühnJeremiah S. JosephBenjamin W. NeumanVanitha SubramanianNaina BarrettoAndrew D. Mesecar
- Topics
- SARS-CoV-2 and COVID-19 Research (8 papers)Protein Structure and Dynamics (4 papers)Viral gastroenteritis research and epidemiology (4 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Molecular BiologyNature Reviews Drug Discovery
- Partner nations
- United StatesJapanFrance
In The Last Decade
Kumar Singh Saikatendu
20 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Infectious Diseases 775
- Molecular Biology 582
- Animal Science and Zoology 279
- Computational Theory and Mathematics 206
- Immunology 196
Countries citing papers authored by Kumar Singh Saikatendu
This map shows the geographic impact of Kumar Singh Saikatendu'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 Kumar Singh Saikatendu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Singh Saikatendu more than expected).
Fields of papers citing papers by Kumar Singh Saikatendu
This network shows the impact of papers produced by Kumar Singh Saikatendu. 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 Kumar Singh Saikatendu. The network helps show where Kumar Singh Saikatendu may publish in the future.
Co-authorship network of co-authors of Kumar Singh Saikatendu
This figure shows the co-authorship network connecting the top 25 collaborators of Kumar Singh Saikatendu. A scholar is included among the top collaborators of Kumar Singh Saikatendu 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 Kumar Singh Saikatendu. Kumar Singh Saikatendu 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 | 1 | |
| 3 | 4 | |
| 4 | Accelerating antiviral drug discovery: lessons from COVID-19breakdown → | 98 |
| 5 | 2 | |
| 6 | 18 | |
| 7 | 3 | |
| 8 | 91 | |
| 9 | 21 | |
| 10 | 10 | |
| 11 | 151 | |
| 12 | 42 | |
| 13 | 66 | |
| 14 | 74 | |
| 15 | 72 | |
| 16 | 117 | |
| 17 | 14 | |
| 18 | 332 | |
| 19 | 94 | |
| 20 | 157 |
About Kumar Singh Saikatendu
Kumar Singh Saikatendu is a scholar working on Infectious Diseases, Toxicology and Oncology, having authored 21 papers that have together received 1.4k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (8 papers), Protein Structure and Dynamics (4 papers) and Viral gastroenteritis research and epidemiology (4 papers). The work is most often cited by research in Infectious Diseases (775 citations), Animal Science and Zoology (279 citations) and Computational Theory and Mathematics (206 citations). Kumar Singh Saikatendu has collaborated with scholars based in United States, Japan and France. Frequent co-authors include Raymond C. Stevens, Michael J. Buchmeier, Peter Kühn, Jeremiah S. Joseph, Benjamin W. Neuman, Vanitha Subramanian, Naina Barretto, Andrew D. Mesecar, Kiira Ratia and Susan C. Baker. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Molecular Biology and Nature Reviews Drug Discovery.
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.