Ashutosh Kumar
Impact in
-
- Computational Drug Discovery Methods
- Molecular Medicine top 5%
Papers in
- Hematology 20
-
- Ubiquitin and proteasome pathways 13
- Protein Structure and Dynamics 12
- Co-authors
- Kam Y. J. Zhang (21 shared papers)Ronald Paul Mason (17 shared papers)Seyed E. Hasnain (11 shared papers)Nasreen Z. Ehtesham (6 shared papers)Mamta Rani (8 shared papers)Anwar Alam (5 shared papers)Tulika Chandra (11 shared papers)Maria B. Kadiiska (6 shared papers)
- Journals
- Journal of Chemical Information and Modeling (7 papers)Scientific Reports (6 papers)Journal of Computer-Aided Molecular Design (5 papers)PLoS ONE (5 papers)Journal of Applied Physics (4 papers)
- Partner nations
- IndiaUnited StatesJapan
In The Last Decade
Ashutosh Kumar
246 papers receiving 4.8k citations
Peers
Comparison fields: 5 of 178
- Computational Theory and Mathematics 467
- Molecular Medicine 129
- Molecular Biology 1.7k
- Endocrinology 121
- Infectious Diseases 309
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 263 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 305 | |
| 2 | 2018 | 139 | |
| 3 | 2012 | 134 | |
| 4 | 2014 | 127 | |
| 5 | 2012 | 117 | |
| 6 | 2005 | 106 | |
| 7 | 2011 | 103 | |
| 8 | 2017 | 97 | |
| 9 | 2012 | 94 | |
| 10 | 2013 | 88 | |
| 11 | 2014 | 79 | |
| 12 | 2001 | 79 | |
| 13 | 2016 | 74 | |
| 14 | 2015 | 70 | |
| 15 | 2017 | 69 | |
| 16 | 2013 | 66 | |
| 17 | 2009 | 65 | |
| 18 | 2013 | 64 | |
| 19 | 2014 | 62 | |
| 20 | 2016 | 58 |
About Ashutosh Kumar
Ashutosh Kumar is a scholar working on Hematology, Molecular Biology, Computational Theory and Mathematics, Genetics and Infectious Diseases, having authored 263 papers that have together received 4.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (17 papers), Ubiquitin and proteasome pathways (13 papers), Protein Structure and Dynamics (12 papers), Tuberculosis Research and Epidemiology (9 papers), Semiconductor materials and interfaces (9 papers), Peptidase Inhibition and Analysis (9 papers), Mycobacterium research and diagnosis (8 papers) and Advanced Topology and Set Theory (8 papers). The work is most often cited by research in Computational Theory and Mathematics (467 citations), Molecular Medicine (129 citations), Molecular Biology (1.7k citations), Endocrinology (121 citations) and Infectious Diseases (309 citations). Ashutosh Kumar has collaborated with scholars based in India, United States and Japan. Frequent co-authors include Kam Y. J. Zhang, Ronald Paul Mason, Seyed E. Hasnain, Nasreen Z. Ehtesham, Mamta Rani, Anwar Alam, Tulika Chandra, Maria B. Kadiiska, Arnout R. D. Voet and Douglas Ganini. Their work appears in journals such as Journal of Chemical Information and Modeling, Scientific Reports, Journal of Computer-Aided Molecular Design, PLoS ONE and Journal of Applied Physics.
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.