Ashutosh Kumar
Impact in
-
- Computational Drug Discovery Methods
- Molecular Medicine top 5%
Papers in ⓘ
- Hematology 24
- Platelet Disorders and Treatments 10
- Genetics 16
- Co-authors
- Kam Y. J. Zhang (21 shared papers)Sanjay K. Srivastava (9 shared papers)Ronald P. Mason (17 shared papers)Seyed E. Hasnain (9 shared papers)V. D. Vankar (8 shared papers)Prashant Singh (3 shared papers)Nasreen Z. Ehtesham (5 shared papers)M. Husain (2 shared papers)
- Journals
- Journal of Applied Physics (10 papers)Journal of Chemical Information and Modeling (7 papers)Scientific Reports (6 papers)Journal of Computer-Aided Molecular Design (5 papers)PLoS ONE (5 papers)
- Partner nations
- IndiaUnited StatesJapan
In The Last Decade
Ashutosh Kumar
255 papers receiving 5.2k citations
Peers
Comparison fields: 5 of 175
- Computational Theory and Mathematics 429
- Molecular Medicine 134
- Materials Chemistry 1.2k
- Molecular Biology 1.7k
- Endocrinology 120
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 280 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 277 | |
| 2 | 2010 | 205 | |
| 3 | 2010 | 153 | |
| 4 | 2018 | 125 | |
| 5 | 2012 | 118 | |
| 6 | 2012 | 111 | |
| 7 | 2014 | 111 | |
| 8 | 2005 | 102 | |
| 9 | 2011 | 100 | |
| 10 | 2017 | 95 | |
| 11 | 2012 | 89 | |
| 12 | 2013 | 84 | |
| 13 | 2006 | 78 | |
| 14 | 2001 | 78 | |
| 15 | 2014 | 75 | |
| 16 | 2022 | 75 | |
| 17 | 2016 | 73 | |
| 18 | 2015 | 66 | |
| 19 | 2009 | 64 | |
| 20 | 2014 | 63 |
About Ashutosh Kumar
Ashutosh Kumar is a scholar working on Hematology, Genetics, Computational Theory and Mathematics, Materials Chemistry and Toxicology, having authored 280 papers that have together received 5.3k indexed citations. Recurring topics across this work include Silicon and Solar Cell Technologies (17 papers), Computational Drug Discovery Methods (17 papers), Semiconductor materials and interfaces (16 papers), Protein Structure and Dynamics (13 papers), Ubiquitin and proteasome pathways (13 papers), Tuberculosis Research and Epidemiology (10 papers), Semiconductor materials and devices (10 papers) and Platelet Disorders and Treatments (10 papers). The work is most often cited by research in Computational Theory and Mathematics (429 citations), Molecular Medicine (134 citations), Materials Chemistry (1.2k citations), Molecular Biology (1.7k citations) and Endocrinology (120 citations). Ashutosh Kumar has collaborated with scholars based in India, United States and Japan. Frequent co-authors include Kam Y. J. Zhang, Sanjay K. Srivastava, Ronald P. Mason, Seyed E. Hasnain, V. D. Vankar, Prashant Singh, Nasreen Z. Ehtesham, M. Husain, Anwar Alam and Mamta Rani. Their work appears in journals such as Journal of Applied Physics, Journal of Chemical Information and Modeling, Scientific Reports, Journal of Computer-Aided Molecular Design and PLoS ONE.
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.