Tushar Joshi
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds
Papers in
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- Computational Drug Discovery Methods 16
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- SARS-CoV-2 and COVID-19 Research 6
- Co-authors
- Subhash Chandra (29 shared papers)Tanuja Joshi (16 shared papers)Priyanka Sharma (21 shared papers)Shalini Mathpal (27 shared papers)Hemlata Pundir (7 shared papers)Veena Pande (12 shared papers)Sushma Tamta (6 shared papers)Kalpana Bhatt (1 shared paper)
- Journals
- Journal of Biomolecular Structure and Dynamics (14 papers)Molecular Diversity (5 papers)Frontiers in Plant Science (1 paper)Scientific Reports (1 paper)Journal of Molecular Graphics and Modelling (1 paper)
- Partner nations
- IndiaSaudi ArabiaBangladesh
In The Last Decade
Tushar Joshi
42 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 111
- Computational Theory and Mathematics 338
- Pharmacology 124
- Drug Discovery 2
- Complementary and alternative medicine 71
- Infectious Diseases 143
Countries citing papers authored by Tushar Joshi
This map shows the geographic impact of Tushar Joshi'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 Tushar Joshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tushar Joshi more than expected).
Fields of papers citing papers by Tushar Joshi
This network shows the impact of papers produced by Tushar Joshi. 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 Tushar Joshi. The network helps show where Tushar Joshi may publish in the future.
Co-authors
The 25 scholars most cited alongside Tushar Joshi, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 150 | |
| 2 | 2020 | 129 | |
| 3 | 2020 | 86 | |
| 4 | 2020 | 65 | |
| 5 | 2019 | 64 | |
| 6 | 2020 | 60 | |
| 7 | 2020 | 47 | |
| 8 | 2020 | 41 | |
| 9 | 2019 | 39 | |
| 10 | 2021 | 27 | |
| 11 | 2020 | 26 | |
| 12 | 2019 | 25 | |
| 13 | 2020 | 25 | |
| 14 | 2021 | 21 | |
| 15 | 2021 | 18 | |
| 16 | 2024 | 17 | |
| 17 | 2024 | 17 | |
| 18 | 2022 | 16 | |
| 19 | 2021 | 16 | |
| 20 | 2020 | 16 |
About Tushar Joshi
Tushar Joshi is a scholar working on Computational Theory and Mathematics, Infectious Diseases, Molecular Biology, Pharmacology and Organic Chemistry, having authored 44 papers that have together received 1.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Synthesis and biological activity (6 papers), Microbial Natural Products and Biosynthesis (6 papers), Peptidase Inhibition and Analysis (4 papers), Diverse Scientific Research Studies (4 papers), Natural Antidiabetic Agents Studies (3 papers) and Lichen and fungal ecology (2 papers). The work is most often cited by research in Computational Theory and Mathematics (338 citations), Pharmacology (124 citations), Drug Discovery (2 citations), Complementary and alternative medicine (71 citations) and Infectious Diseases (143 citations). Tushar Joshi has collaborated with scholars based in India, Saudi Arabia and Bangladesh. Frequent co-authors include Subhash Chandra, Tanuja Joshi, Priyanka Sharma, Shalini Mathpal, Hemlata Pundir, Veena Pande, Sushma Tamta, Kalpana Bhatt, Shaohua Chen and Wenping Zhang. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Molecular Diversity, Frontiers in Plant Science, Scientific Reports and Journal of Molecular Graphics and Modelling.
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.