Rajat Kumar Jha
- Computational Theory and Mathematics top 2%
- Infectious Diseases top 10%
- Molecular Biology
- Organic Chemistry
- Pharmacology
- Co-authors
- Amit Kumar SinghRameez Jabeer KhanJayaraman MuthukumaranGizachew Muluneh AmeraMonika JainEkampreet SinghAmita PathakRashmi Prabha Singh
- Topics
- Computational Drug Discovery Methods (10 papers)Antibiotic Resistance in Bacteria (9 papers)SARS-CoV-2 and COVID-19 Research (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaMicrobial PathogenesisJournal of Biomolecular Structure and Dynamics
- Partner nations
- IndiaEthiopiaUnited States
In The Last Decade
Rajat Kumar Jha
16 papers receiving 441 citations
Peers
Comparison fields: 5 of 75
- Computational Theory and Mathematics 257
- Infectious Diseases 205
- Molecular Biology 157
- Organic Chemistry 84
- Pharmacology 39
Countries citing papers authored by Rajat Kumar Jha
This map shows the geographic impact of Rajat Kumar Jha'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 Rajat Kumar Jha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajat Kumar Jha more than expected).
Fields of papers citing papers by Rajat Kumar Jha
This network shows the impact of papers produced by Rajat Kumar Jha. 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 Rajat Kumar Jha. The network helps show where Rajat Kumar Jha may publish in the future.
Co-authorship network of co-authors of Rajat Kumar Jha
This figure shows the co-authorship network connecting the top 25 collaborators of Rajat Kumar Jha. A scholar is included among the top collaborators of Rajat Kumar Jha 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 Rajat Kumar Jha. Rajat Kumar Jha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 4 | |
| 3 | 6 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 14 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 26 | |
| 10 | 40 | |
| 11 | 19 | |
| 12 | 10 | |
| 13 | 14 | |
| 14 | 14 | |
| 15 | 262 | |
| 16 | 17 |
About Rajat Kumar Jha
Rajat Kumar Jha is a scholar working on Molecular Medicine, Computational Theory and Mathematics and Microbiology, having authored 16 papers that have together received 448 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Antibiotic Resistance in Bacteria (9 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). The work is most often cited by research in Computational Theory and Mathematics (257 citations), Infectious Diseases (205 citations) and Molecular Medicine (36 citations). Rajat Kumar Jha has collaborated with scholars based in India, Ethiopia and United States. Frequent co-authors include Amit Kumar Singh, Rameez Jabeer Khan, Jayaraman Muthukumaran, Gizachew Muluneh Amera, Monika Jain, Ekampreet Singh, Amita Pathak, Rashmi Prabha Singh, Ankit Kumar and Yaman Kumar. Their work appears in journals such as SHILAP Revista de lepidopterología, Microbial Pathogenesis and Journal of Biomolecular Structure and Dynamics.
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.