Vidya Niranjan
Impact in
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
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- Computational Drug Discovery Methods
Papers in
-
- Genomics and Phylogenetic Studies 6
- Cancer therapeutics and mechanisms 5
- Protein Structure and Dynamics 5
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- Computational Drug Discovery Methods 27
- Co-authors
- Akshay Uttarkar (43 shared papers)A Malini (1 shared paper)Sinosh Skariyachan (16 shared papers)Dharshini Gopal (7 shared papers)Raviraj Kusanur (5 shared papers)Jitendra Kumar (5 shared papers)Shweta Chakrabarti (1 shared paper)Vasanthan Jayakumar (1 shared paper)
- Journals
- Journal of Biomolecular Structure and Dynamics (9 papers)Infection Genetics and Evolution (4 papers)Molecular Simulation (3 papers)Computers in Biology and Medicine (3 papers)International Journal of Biological Macromolecules (2 papers)
- Partner nations
- IndiaAlgeriaUnited States
In The Last Decade
Vidya Niranjan
84 papers receiving 721 citations
Peers
Comparison fields: 5 of 103
- Molecular Medicine 89
- Computational Theory and Mathematics 178
- Toxicology 21
- Endocrinology 30
- Organic Chemistry 143
Countries citing papers authored by Vidya Niranjan
This map shows the geographic impact of Vidya Niranjan'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 Vidya Niranjan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vidya Niranjan more than expected).
Fields of papers citing papers by Vidya Niranjan
This network shows the impact of papers produced by Vidya Niranjan. 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 Vidya Niranjan. The network helps show where Vidya Niranjan may publish in the future.
Co-authors
The 25 scholars most cited alongside Vidya Niranjan, 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 94 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Antimicrobial resistance pattern in Escherichia coli causing urinary tract infection among inpatients. | 2014 | 80 |
| 2 | 2013 | 65 | |
| 3 | 2020 | 39 | |
| 4 | 2023 | 28 | |
| 5 | 2021 | 25 | |
| 6 | 2022 | 25 | |
| 7 | 2021 | 23 | |
| 8 | 2003 | 21 | |
| 9 | 2022 | 21 | |
| 10 | 2020 | 19 | |
| 11 | 2021 | 17 | |
| 12 | 2020 | 17 | |
| 13 | 2023 | 17 | |
| 14 | 2022 | 16 | |
| 15 | 2022 | 16 | |
| 16 | 2019 | 15 | |
| 17 | 2011 | 15 | |
| 18 | 2018 | 13 | |
| 19 | 2021 | 13 | |
| 20 | 2013 | 12 |
About Vidya Niranjan
Vidya Niranjan is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Plant Science and Infectious Diseases, having authored 94 papers that have together received 776 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (27 papers), Synthesis and biological activity (17 papers), Genomics and Phylogenetic Studies (6 papers), Cancer therapeutics and mechanisms (5 papers), Protein Structure and Dynamics (5 papers), Cancer Genomics and Diagnostics (5 papers), SARS-CoV-2 and COVID-19 Research (5 papers) and Bioactive Compounds and Antitumor Agents (4 papers). The work is most often cited by research in Molecular Medicine (89 citations), Computational Theory and Mathematics (178 citations), Toxicology (21 citations), Endocrinology (30 citations) and Organic Chemistry (143 citations). Vidya Niranjan has collaborated with scholars based in India, Algeria and United States. Frequent co-authors include Akshay Uttarkar, A Malini, Sinosh Skariyachan, Dharshini Gopal, Raviraj Kusanur, Jitendra Kumar, Shweta Chakrabarti, Vasanthan Jayakumar, Raja C. Mugasimangalam and Saraswathi Vishveshwara. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Infection Genetics and Evolution, Molecular Simulation, Computers in Biology and Medicine and International Journal of Biological Macromolecules.
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.