Deept Kumar
Impact in
-
- Hemoglobin structure and function
-
- Protein Structure and Dynamics
- Fungal and yeast genetics research
- Photosynthetic Processes and Mechanisms
Papers in
-
- Machine Learning in Bioinformatics 1
-
- Plant Stress Responses and Tolerance 2
- GABA and Rice Research 1
- Co-authors
- Naren Ramakrishnan (6 shared papers)Maulik Shukla (3 shared papers)Malcolm Potts (4 shared papers)Richard F. Helm (4 shared papers)Jory Z. Ruscio (1 shared paper)Michael G. Prisant (1 shared paper)Alexey V. Onufriev (1 shared paper)Bud Mishra (1 shared paper)
- Journals
- Applied Engineering in Agriculture (1 paper)PLANT PHYSIOLOGY (1 paper)Journal of Irrigation and Drainage Engineering (1 paper)Proceedings of the National Academy of Sciences (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)
- Partner nations
- United StatesFranceIndia
In The Last Decade
Deept Kumar
11 papers receiving 427 citations
Peers
Comparison fields: 5 of 86
- Cell Biology 91
- Molecular Biology 230
- Plant Science 96
- Aging 4
- Food Science 36
Countries citing papers authored by Deept Kumar
This map shows the geographic impact of Deept 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 Deept Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deept Kumar more than expected).
Fields of papers citing papers by Deept Kumar
This network shows the impact of papers produced by Deept 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 Deept Kumar. The network helps show where Deept Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Deept 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
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 127 | |
| 2 | 2003 | 119 | |
| 3 | 2005 | 67 | |
| 4 | 2004 | 48 | |
| 5 | 2008 | 25 | |
| 6 | 2006 | 16 | |
| 7 | 2012 | 9 | |
| 8 | 1992 | 9 | |
| 9 | 2004 | 8 | |
| 10 | 2018 | 5 | |
| 11 | 1992 | 2 |
About Deept Kumar
Deept Kumar is a scholar working on Molecular Biology, Plant Science, Information Systems, Artificial Intelligence and Soil Science, having authored 11 papers that have together received 435 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (3 papers), Irrigation Practices and Water Management (3 papers), Algorithms and Data Compression (3 papers), Natural Language Processing Techniques (2 papers), Plant Stress Responses and Tolerance (2 papers), Machine Learning in Bioinformatics (1 paper), Cell Image Analysis Techniques (1 paper) and GABA and Rice Research (1 paper). The work is most often cited by research in Cell Biology (91 citations), Molecular Biology (230 citations), Plant Science (96 citations), Aging (4 citations) and Food Science (36 citations). Deept Kumar has collaborated with scholars based in United States, France and India. Frequent co-authors include Naren Ramakrishnan, Maulik Shukla, Malcolm Potts, Richard F. Helm, Jory Z. Ruscio, Michael G. Prisant, Alexey V. Onufriev, Bud Mishra, Allan A. Sioson and Ulrika Egertsdotter. Their work appears in journals such as Applied Engineering in Agriculture, PLANT PHYSIOLOGY, Journal of Irrigation and Drainage Engineering, Proceedings of the National Academy of Sciences and IEEE Transactions on Knowledge and Data Engineering.
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.