Jyotsna Bhat
Impact in
-
- Computational Drug Discovery Methods
-
- DNA and Nucleic Acid Chemistry
- RNA Research and Splicing
- Protein Structure and Dynamics
Papers in
-
- Computational Drug Discovery Methods 4
-
- DNA and Nucleic Acid Chemistry 5
- RNA Research and Splicing 1
- Co-authors
- Subhrangsu Chatterjee (11 shared papers)Pravin Sundarao Ambure (1 shared paper)Kunal Roy (1 shared paper)Tomasz Puzyn (1 shared paper)Masilamani Elizabeth Sobhia (3 shared papers)Nidhi Chaudhary (2 shared papers)Samit Chattopadhyay (3 shared papers)Kiran Kumar Nakka (2 shared papers)
- Journals
- Scientific Reports (2 papers)Expert Opinion on Therapeutic Targets (2 papers)Journal of Biomolecular Structure and Dynamics (1 paper)Journal of Medicinal Chemistry (1 paper)iScience (1 paper)
- Partner nations
- IndiaJapanUnited States
In The Last Decade
Jyotsna Bhat
16 papers receiving 345 citations
Peers
Comparison fields: 5 of 57
- Computational Theory and Mathematics 66
- Molecular Biology 153
- Complementary and alternative medicine 21
- Physiology 50
- Pharmacology 22
Countries citing papers authored by Jyotsna Bhat
This map shows the geographic impact of Jyotsna Bhat'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 Jyotsna Bhat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jyotsna Bhat more than expected).
Fields of papers citing papers by Jyotsna Bhat
This network shows the impact of papers produced by Jyotsna Bhat. 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 Jyotsna Bhat. The network helps show where Jyotsna Bhat may publish in the future.
Co-authors
The 25 scholars most cited alongside Jyotsna Bhat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 72 | |
| 2 | 2015 | 47 | |
| 3 | 2015 | 43 | |
| 4 | 2019 | 34 | |
| 5 | 2016 | 26 | |
| 6 | 2014 | 22 | |
| 7 | 2013 | 16 | |
| 8 | 2016 | 15 | |
| 9 | 2017 | 13 | |
| 10 | 2012 | 12 | |
| 11 | 2017 | 12 | |
| 12 | 2015 | 10 | |
| 13 | 2016 | 9 | |
| 14 | 2016 | 7 | |
| 15 | 2021 | 7 | |
| 16 | 2014 | 5 |
About Jyotsna Bhat
Jyotsna Bhat is a scholar working on Computational Theory and Mathematics, Molecular Biology, Physiology, Complementary and alternative medicine and Biomaterials, having authored 16 papers that have together received 350 indexed citations. Recurring topics across this work include DNA and Nucleic Acid Chemistry (5 papers), Computational Drug Discovery Methods (4 papers), Alzheimer's disease research and treatments (2 papers), Cancer-related molecular mechanisms research (1 paper), Endoplasmic Reticulum Stress and Disease (1 paper), RNA Research and Splicing (1 paper), Cancer-related Molecular Pathways (1 paper) and Supramolecular Self-Assembly in Materials (1 paper). The work is most often cited by research in Computational Theory and Mathematics (66 citations), Molecular Biology (153 citations), Complementary and alternative medicine (21 citations), Physiology (50 citations) and Pharmacology (22 citations). Jyotsna Bhat has collaborated with scholars based in India, Japan and United States. Frequent co-authors include Subhrangsu Chatterjee, Pravin Sundarao Ambure, Kunal Roy, Tomasz Puzyn, Masilamani Elizabeth Sobhia, Nidhi Chaudhary, Samit Chattopadhyay, Kiran Kumar Nakka, Abir Kumar Panda and Gaurisankar Sa. Their work appears in journals such as Scientific Reports, Expert Opinion on Therapeutic Targets, Journal of Biomolecular Structure and Dynamics, Journal of Medicinal Chemistry and iScience.
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.