Pradeep Kumar Das
Impact in
- Aging top 1%
- Plant Science top 0.5%
- Plant Molecular Biology Research
- Plant nutrient uptake and metabolism
Papers in
-
- Plant Reproductive Biology 16
- TGF-β signaling in diseases 6
-
- Digital Imaging for Blood Diseases 16
- Co-authors
- Sukadev Meher (20 shared papers)Elliot M. Meyerowitz (6 shared papers)Marcus G. Heisler (2 shared papers)Carolyn Ohno (2 shared papers)G. Venugopala Reddy (2 shared papers)Richard W. Padgett (7 shared papers)Patrick Sieber (1 shared paper)Jeff A. Long (1 shared paper)
- Journals
- Development (4 papers)Engineering Applications of Artificial Intelligence (3 papers)Proceedings of the National Academy of Sciences (3 papers)Biomedical Signal Processing and Control (3 papers)Journal of Applied Polymer Science (2 papers)
- Partner nations
- IndiaUnited StatesFrance
In The Last Decade
Pradeep Kumar Das
66 papers receiving 4.5k citations
Pradeep Kumar Das's Hit Papers
Peers
Comparison fields: 5 of 139
- Aging 171
- Plant Science 2.4k
- Molecular Biology 2.8k
- Computer Vision and Pattern Recognition 554
- Biophysics 145
Countries citing papers authored by Pradeep Kumar Das
This map shows the geographic impact of Pradeep Kumar Das'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 Pradeep Kumar Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pradeep Kumar Das more than expected).
Fields of papers citing papers by Pradeep Kumar Das
This network shows the impact of papers produced by Pradeep Kumar Das. 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 Pradeep Kumar Das. The network helps show where Pradeep Kumar Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Pradeep Kumar Das, 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 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Patterns of Auxin Transport and Gene Expression during Primordium Development Revealed by Live Imaging of the Arabidopsis Inflorescence Meristem Hit paper breakdown → | 2005 | 957 |
| 2 | 1996 | 429 | |
| 3 | 2007 | 317 | |
| 4 | 2004 | 263 | |
| 5 | 2010 | 224 | |
| 6 | 2013 | 161 | |
| 7 | 2021 | 133 | |
| 8 | 2015 | 129 | |
| 9 | 1996 | 129 | |
| 10 | 2011 | 129 | |
| 11 | An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images Hit paper breakdown → | 2023 | 106 |
| 12 | 1998 | 100 | |
| 13 | 2022 | 96 | |
| 14 | 2021 | 91 | |
| 15 | 2022 | 85 | |
| 16 | 1998 | 85 | |
| 17 | 2009 | 81 | |
| 18 | 2017 | 75 | |
| 19 | 2019 | 67 | |
| 20 | 2022 | 65 |
About Pradeep Kumar Das
Pradeep Kumar Das is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Plant Science, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 71 papers that have together received 4.6k indexed citations. Recurring topics across this work include Plant Molecular Biology Research (18 papers), Digital Imaging for Blood Diseases (16 papers), Plant Reproductive Biology (16 papers), COVID-19 diagnosis using AI (14 papers), AI in cancer detection (13 papers), TGF-β signaling in diseases (6 papers), Metal complexes synthesis and properties (5 papers) and Brain Tumor Detection and Classification (4 papers). The work is most often cited by research in Aging (171 citations), Plant Science (2.4k citations), Molecular Biology (2.8k citations), Computer Vision and Pattern Recognition (554 citations) and Biophysics (145 citations). Pradeep Kumar Das has collaborated with scholars based in India, United States and France. Frequent co-authors include Sukadev Meher, Elliot M. Meyerowitz, Marcus G. Heisler, Carolyn Ohno, G. Venugopala Reddy, Richard W. Padgett, Patrick Sieber, Jeff A. Long, Adyasha Sahu and Vincent Mirabet. Their work appears in journals such as Development, Engineering Applications of Artificial Intelligence, Proceedings of the National Academy of Sciences, Biomedical Signal Processing and Control and Journal of Applied Polymer Science.
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.