Priyanka Sharma
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Infectious Diseases top 5%
- Food Science top 5%
- Organic Chemistry top 10%
- Co-authors
- Subhash ChandraTushar JoshiTanuja JoshiArti KapilShalini MathpalPunit KaurSushma TamtaVeena Pande
- Topics
- Computational Drug Discovery Methods (17 papers)Salmonella and Campylobacter epidemiology (14 papers)Antibiotic Resistance in Bacteria (14 papers)
- Journals
- Physical Review LettersJournal of Biological ChemistrySHILAP Revista de lepidopterología
- Partner nations
- IndiaUnited StatesSaudi Arabia
In The Last Decade
Priyanka Sharma
94 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 114
- Molecular Biology 536
- Computational Theory and Mathematics 327
- Infectious Diseases 257
- Food Science 241
- Organic Chemistry 232
Countries citing papers authored by Priyanka Sharma
This map shows the geographic impact of Priyanka Sharma'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 Priyanka Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priyanka Sharma more than expected).
Fields of papers citing papers by Priyanka Sharma
This network shows the impact of papers produced by Priyanka Sharma. 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 Priyanka Sharma. The network helps show where Priyanka Sharma may publish in the future.
Co-authorship network of co-authors of Priyanka Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Priyanka Sharma. A scholar is included among the top collaborators of Priyanka Sharma 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 Priyanka Sharma. Priyanka Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 9 | |
| 4 | 8 | |
| 5 | 8 | |
| 6 | 37 | |
| 7 | 59 | |
| 8 | 1 | |
| 9 | 38 | |
| 10 | 25 | |
| 11 | 6 | |
| 12 | 6 | |
| 13 | 16 | |
| 14 | 10 | |
| 15 | 11 | |
| 16 | Knowledge of the farmers of Kheda district in Gujarat about improved cultivation practices of kharif rice crop | 1 |
| 17 | Synthesis and Biological Evaluation of N3-(4-Substituted Phenyl)-N5-Phenyl-4H-1, 2, 4-Triazole-3,5-Diamine Derivatives | 1 |
| 18 | 99 | |
| 19 | Estimation of losses in three different cruciferous oilseed Brassica crops due to the aphid complex in Himachal Pradesh (India) | 2 |
| 20 | 2 |
About Priyanka Sharma
Priyanka Sharma is a scholar working on Molecular Medicine, Endocrinology and Infectious Diseases, having authored 97 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (17 papers), Salmonella and Campylobacter epidemiology (14 papers) and Antibiotic Resistance in Bacteria (14 papers). The work is most often cited by research in Molecular Medicine (183 citations), Computational Theory and Mathematics (327 citations) and Endocrinology (75 citations). Priyanka Sharma has collaborated with scholars based in India, United States and Saudi Arabia. Frequent co-authors include Subhash Chandra, Tushar Joshi, Tanuja Joshi, Arti Kapil, Shalini Mathpal, Punit Kaur, Sushma Tamta, Veena Pande, B. Jayaram and Alka Gupta. Their work appears in journals such as Physical Review Letters, 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.