Durgesh Kumar
Impact in
- Filtration and Separation top 5%
-
- Computational Drug Discovery Methods
Papers in
-
- SARS-CoV-2 and COVID-19 Research 7
- Physiology 13
- Adipose Tissue and Metabolism 11
- Co-authors
- Prashant Singh (22 shared papers)Anil Nilkanth Gaikwad (19 shared papers)Salil Varshney (19 shared papers)Abhishek Gupta (18 shared papers)Kripa Shankar (17 shared papers)Sujith Rajan (17 shared papers)Abhilash Jayaraj (8 shared papers)Ankita Srivastava (14 shared papers)
- Journals
- Journal of Biomolecular Structure and Dynamics (8 papers)Molecular Neurobiology (3 papers)Metabolism (2 papers)European Journal of Pharmacology (2 papers)Molecular and Cellular Endocrinology (2 papers)
- Partner nations
- IndiaIndonesiaSouth Africa
In The Last Decade
Durgesh Kumar
65 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 121
- Filtration and Separation 29
- Computational Theory and Mathematics 188
- Infectious Diseases 150
- Physiology 195
- Catalysis 51
Countries citing papers authored by Durgesh Kumar
This map shows the geographic impact of Durgesh 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 Durgesh Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Durgesh Kumar more than expected).
Fields of papers citing papers by Durgesh Kumar
This network shows the impact of papers produced by Durgesh 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 Durgesh Kumar. The network helps show where Durgesh Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Durgesh 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 91 | |
| 2 | 2017 | 56 | |
| 3 | 2020 | 53 | |
| 4 | 2019 | 49 | |
| 5 | 2024 | 49 | |
| 6 | 2019 | 43 | |
| 7 | 2018 | 42 | |
| 8 | 2016 | 37 | |
| 9 | 2022 | 35 | |
| 10 | 2017 | 33 | |
| 11 | 2019 | 31 | |
| 12 | 1999 | 31 | |
| 13 | 2017 | 30 | |
| 14 | 2018 | 29 | |
| 15 | 2021 | 27 | |
| 16 | 2018 | 27 | |
| 17 | 2019 | 27 | |
| 18 | 2018 | 26 | |
| 19 | 2020 | 26 | |
| 20 | 2019 | 25 |
About Durgesh Kumar
Durgesh Kumar is a scholar working on Infectious Diseases, Physiology, Epidemiology, Computational Theory and Mathematics and Cancer Research, having authored 66 papers that have together received 1.2k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (12 papers), Adipose Tissue and Metabolism (11 papers), Computational Drug Discovery Methods (8 papers), SARS-CoV-2 and COVID-19 Research (7 papers), Mosquito-borne diseases and control (7 papers), MicroRNA in disease regulation (5 papers), HIV Research and Treatment (4 papers) and Synthesis and biological activity (4 papers). The work is most often cited by research in Filtration and Separation (29 citations), Computational Theory and Mathematics (188 citations), Infectious Diseases (150 citations), Physiology (195 citations) and Catalysis (51 citations). Durgesh Kumar has collaborated with scholars based in India, Indonesia and South Africa. Frequent co-authors include Prashant Singh, Anil Nilkanth Gaikwad, Salil Varshney, Abhishek Gupta, Kripa Shankar, Sujith Rajan, Abhilash Jayaraj, Ankita Srivastava, Kamlesh Kumari and Kamlesh Kumari. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Molecular Neurobiology, Metabolism, European Journal of Pharmacology and Molecular and Cellular Endocrinology.
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.