Nagasuma Chandra
- Molecular Biology top 2%
- Infectious Diseases top 1%
- Epidemiology top 5%
- Computational Theory and Mathematics top 0.5%
- Immunology top 5%
- Co-authors
- Karthik RamanKalidas YeturuM. VijayanJyothi PadiadpuRamachandraiah GosuP. T. Ravi RajagopalanDeepesh NagarajanNarayanaswamy Srinivasan
- Topics
- Tuberculosis Research and Epidemiology (50 papers)Computational Drug Discovery Methods (35 papers)RNA and protein synthesis mechanisms (28 papers)
- Journals
- Nucleic Acids ResearchJournal of Biological ChemistrySHILAP Revista de lepidopterología
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Nagasuma Chandra
179 papers receiving 4.1k citations
Peers
Comparison fields: 5 of 146
- Molecular Biology 3.0k
- Infectious Diseases 1.1k
- Epidemiology 635
- Computational Theory and Mathematics 623
- Immunology 428
Countries citing papers authored by Nagasuma Chandra
This map shows the geographic impact of Nagasuma 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 Nagasuma Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nagasuma Chandra more than expected).
Fields of papers citing papers by Nagasuma Chandra
This network shows the impact of papers produced by Nagasuma 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 Nagasuma Chandra. The network helps show where Nagasuma Chandra may publish in the future.
Co-authorship network of co-authors of Nagasuma Chandra
This figure shows the co-authorship network connecting the top 25 collaborators of Nagasuma Chandra. A scholar is included among the top collaborators of Nagasuma Chandra 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 Nagasuma Chandra. Nagasuma Chandra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 12 | |
| 3 | 7 | |
| 4 | 10 | |
| 5 | 29 | |
| 6 | 17 | |
| 7 | 1 | |
| 8 | 46 | |
| 9 | 14 | |
| 10 | 19 | |
| 11 | 7 | |
| 12 | 10 | |
| 13 | 8 | |
| 14 | 34 | |
| 15 | 25 | |
| 16 | 14 | |
| 17 | 77 | |
| 18 | 38 | |
| 19 | Carbohydrate-based drug design: Recognition fingerprints and their use in lead identification | 2 |
| 20 | 2 |
About Nagasuma Chandra
Nagasuma Chandra is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Molecular Biology, having authored 181 papers that have together received 4.2k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (50 papers), Computational Drug Discovery Methods (35 papers) and RNA and protein synthesis mechanisms (28 papers). The work is most often cited by research in Infectious Diseases (1.1k citations), Molecular Biology (3.0k citations) and Computational Theory and Mathematics (623 citations). Nagasuma Chandra has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Karthik Raman, Kalidas Yeturu, M. Vijayan, Jyothi Padiadpu, Ramachandraiah Gosu, P. T. Ravi Rajagopalan, Deepesh Nagarajan, Narayanaswamy Srinivasan, K. Muniyappa and Sankaran Sandhya. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.
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.