Ashutosh Kumar
Impact in
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- Computational Drug Discovery Methods
- Infectious Diseases top 10%
- Tuberculosis Research and Epidemiology
Papers in
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- Studies on Chitinases and Chitosanases 5
- Protein Structure and Dynamics 4
- Biochemical and Molecular Research 4
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- Computational Drug Discovery Methods 13
- Co-authors
- Kam Y. J. Zhang (28 shared papers)Mohammad Imran Siddiqi (14 shared papers)Francois Berenger (2 shared papers)Qing Yang (4 shared papers)Xi Zhuo Jiang (4 shared papers)Bhartendu Nath Mishra (2 shared papers)Yoshihiro Yamanishi (1 shared paper)Mirza S. Baig (7 shared papers)
In The Last Decade
Ashutosh Kumar
49 papers receiving 685 citations
Peers
Comparison fields: 5 of 103
- Computational Theory and Mathematics 155
- Infectious Diseases 126
- Organic Chemistry 162
- Molecular Biology 376
- Horticulture 4
Countries citing papers authored by Ashutosh Kumar
This map shows the geographic impact of Ashutosh Kumar'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 Ashutosh Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashutosh Kumar more than expected).
Fields of papers citing papers by Ashutosh Kumar
This network shows the impact of papers produced by Ashutosh Kumar. 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 Ashutosh Kumar. The network helps show where Ashutosh Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Ashutosh Kumar, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 47 | |
| 2 | 2007 | 44 | |
| 3 | 2006 | 42 | |
| 4 | 2020 | 37 | |
| 5 | 2008 | 36 | |
| 6 | 2008 | 34 | |
| 7 | 2019 | 33 | |
| 8 | 2016 | 33 | |
| 9 | 2008 | 26 | |
| 10 | 2021 | 24 | |
| 11 | 2006 | 23 | |
| 12 | 2008 | 22 | |
| 13 | 2008 | 22 | |
| 14 | 2021 | 20 | |
| 15 | 2014 | 20 | |
| 16 | 2022 | 17 | |
| 17 | 2008 | 16 | |
| 18 | 2021 | 15 | |
| 19 | 2014 | 13 | |
| 20 | 2011 | 12 |
About Ashutosh Kumar
Ashutosh Kumar is a scholar working on Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Political Science and International Relations and Immunology, having authored 56 papers that have together received 715 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), South Asian Studies and Conflicts (6 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Studies on Chitinases and Chitosanases (5 papers), Invertebrate Immune Response Mechanisms (4 papers), Insect symbiosis and bacterial influences (4 papers), Protein Structure and Dynamics (4 papers) and Biochemical and Molecular Research (4 papers). The work is most often cited by research in Computational Theory and Mathematics (155 citations), Infectious Diseases (126 citations), Organic Chemistry (162 citations), Molecular Biology (376 citations) and Horticulture (4 citations). Ashutosh Kumar has collaborated with scholars based in India, Japan and China. Frequent co-authors include Kam Y. J. Zhang, Mohammad Imran Siddiqi, Francois Berenger, Qing Yang, Xi Zhuo Jiang, Bhartendu Nath Mishra, Yoshihiro Yamanishi, Mirza S. Baig, Gautam Panda and Shagufta Shagufta. Their work appears in journals such as Journal of Molecular Modeling, Journal of Computer-Aided Molecular Design, International Journal of Biological Macromolecules, Molecular and Biochemical Parasitology and South Asia Research.
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.