Anusha Nathan
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 10%
Papers in
-
- vaccines and immunoinformatics approaches 3
- Genomics and Phylogenetic Studies 1
- Bioinformatics and Genomic Networks 1
-
- Immunotherapy and Immune Responses 5
- Co-authors
- Rhoda Tano-Menka (3 shared papers)Mary Carrington (2 shared papers)Gaurav D. Gaiha (5 shared papers)A. John Iafrate (2 shared papers)Bruce D. Walker (2 shared papers)Fernando Senjobe (2 shared papers)Wilfredo F. García-Beltrán (2 shared papers)Ashok Khatri (3 shared papers)
- Journals
- Cell (2 papers)Journal of Clinical Medicine (2 papers)iScience (1 paper)Frontiers in Immunology (1 paper)Biomolecules (1 paper)
- Partner nations
- United StatesIndiaSouth Africa
In The Last Decade
Anusha Nathan
7 papers receiving 296 citations
Anusha Nathan's Hit Papers
Peers
Comparison fields: 5 of 49
- Infectious Diseases 199
- Modeling and Simulation 20
- Immunology 75
- Health 17
- Molecular Biology 133
Countries citing papers authored by Anusha Nathan
This map shows the geographic impact of Anusha Nathan'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 Anusha Nathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anusha Nathan more than expected).
Fields of papers citing papers by Anusha Nathan
This network shows the impact of papers produced by Anusha Nathan. 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 Anusha Nathan. The network helps show where Anusha Nathan may publish in the future.
Co-authors
The 25 scholars most cited alongside Anusha Nathan, 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 | T cell reactivity to the SARS-CoV-2 Omicron variant is preserved in most but not all individuals Hit paper breakdown → | 2022 | 157 |
| 2 | 2021 | 53 | |
| 3 | 2019 | 33 | |
| 4 | 2020 | 32 | |
| 5 | 2021 | 13 | |
| 6 | 2019 | 7 | |
| 7 | 2025 | 6 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 |
About Anusha Nathan
Anusha Nathan is a scholar working on Molecular Biology, Immunology, Infectious Diseases, Genetics and Radiology, Nuclear Medicine and Imaging, having authored 9 papers that have together received 301 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (5 papers), SARS-CoV-2 and COVID-19 Research (3 papers), vaccines and immunoinformatics approaches (3 papers), Evolution and Genetic Dynamics (1 paper), Genomics and Phylogenetic Studies (1 paper), Mathematical Biology Tumor Growth (1 paper), Cell Adhesion Molecules Research (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Infectious Diseases (199 citations), Modeling and Simulation (20 citations), Immunology (75 citations), Health (17 citations) and Molecular Biology (133 citations). Anusha Nathan has collaborated with scholars based in United States, India and South Africa. Frequent co-authors include Rhoda Tano-Menka, Mary Carrington, Gaurav D. Gaiha, A. John Iafrate, Bruce D. Walker, Fernando Senjobe, Wilfredo F. García-Beltrán, Ashok Khatri, Vivek Naranbhai and Clarety Kaseke. Their work appears in journals such as Cell, Journal of Clinical Medicine, iScience, Frontiers in Immunology and Biomolecules.
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.