Ramesh Chandra
Impact in
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- SARS-CoV-2 and COVID-19 Research
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- Computational Drug Discovery Methods
Papers in
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- vaccines and immunoinformatics approaches 7
- Lipid Membrane Structure and Behavior 2
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- SARS-CoV-2 and COVID-19 Research 4
- Co-authors
- Neeraj Kumar (7 shared papers)Damini Sood (6 shared papers)Nidhi Gupta (1 shared paper)Surendra Nimesh (1 shared paper)Peter J. van der Spek (1 shared paper)Hari Shanker Sharma (1 shared paper)Durgesh Kumar (3 shared papers)Prashant Singh (3 shared papers)
- Journals
- Journal of Biomolecular Structure and Dynamics (4 papers)Bioscience Reports (1 paper)Scientific Reports (1 paper)Biochemical Society Transactions (1 paper)Journal of Proteome Research (1 paper)
- Partner nations
- IndiaUnited StatesCanada
In The Last Decade
Ramesh Chandra
20 papers receiving 379 citations
Peers
Comparison fields: 5 of 91
- Infectious Diseases 98
- Computational Theory and Mathematics 79
- Molecular Biology 223
- Virology 14
- Immunology 50
Countries citing papers authored by Ramesh Chandra
This map shows the geographic impact of Ramesh Chandra'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 Ramesh Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramesh Chandra more than expected).
Fields of papers citing papers by Ramesh Chandra
This network shows the impact of papers produced by Ramesh Chandra. 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 Ramesh Chandra. The network helps show where Ramesh Chandra may publish in the future.
Co-authors
The 25 scholars most cited alongside Ramesh Chandra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 64 | |
| 2 | 2020 | 53 | |
| 3 | 2020 | 46 | |
| 4 | 2020 | 30 | |
| 5 | 2019 | 29 | |
| 6 | 2005 | 27 | |
| 7 | 2021 | 24 | |
| 8 | 2019 | 22 | |
| 9 | 2020 | 18 | |
| 10 | 2020 | 16 | |
| 11 | 2018 | 14 | |
| 12 | 1986 | 12 | |
| 13 | 2020 | 8 | |
| 14 | 2025 | 8 | |
| 15 | 2003 | 4 | |
| 16 | 2021 | 4 | |
| 17 | 2022 | 3 | |
| 18 | 2025 | 1 | |
| 19 | 2019 | 1 | |
| 20 | 2001 | 1 |
About Ramesh Chandra
Ramesh Chandra is a scholar working on Molecular Biology, Infectious Diseases, Immunology, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging, having authored 21 papers that have together received 386 indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (7 papers), Computational Drug Discovery Methods (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Immunotherapy and Immune Responses (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), HIV Research and Treatment (2 papers), Lipid Membrane Structure and Behavior (2 papers) and Synthesis and biological activity (2 papers). The work is most often cited by research in Infectious Diseases (98 citations), Computational Theory and Mathematics (79 citations), Molecular Biology (223 citations), Virology (14 citations) and Immunology (50 citations). Ramesh Chandra has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Neeraj Kumar, Damini Sood, Nidhi Gupta, Surendra Nimesh, Peter J. van der Spek, Hari Shanker Sharma, Durgesh Kumar, Prashant Singh, Neera Sharma and Sonam Grover. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Bioscience Reports, Scientific Reports, Biochemical Society Transactions and Journal of Proteome 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.