Ranabir Das
Impact in
- Molecular Biology top 10%
- Ubiquitin and proteasome pathways
- Protein Degradation and Inhibitors
- Protein Structure and Dynamics
- Cell Biology top 10%
- Endoplasmic Reticulum Stress and Disease
Papers in
-
- Ubiquitin and proteasome pathways 21
- Protein Structure and Dynamics 6
- Glycosylation and Glycoproteins Research 4
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- Quantum Computing Algorithms and Architecture 14
- Quantum Information and Cryptography 13
- Co-authors
- Anil Kumar (7 shared papers)R. Andrew Byrd (8 shared papers)Jess Li (6 shared papers)Jayant B. Udgaonkar (5 shared papers)Allan M. Weissman (4 shared papers)Xinhua Ji (3 shared papers)Jennifer Mariano (3 shared papers)Sergey G. Tarasov (4 shared papers)
- Journals
- Physical Review A (5 papers)Journal of Magnetic Resonance (4 papers)Protein Science (4 papers)Journal of Biological Chemistry (4 papers)Journal of Molecular Biology (3 papers)
- Partner nations
- IndiaUnited StatesFrance
In The Last Decade
Ranabir Das
51 papers receiving 990 citations
Peers
Comparison fields: 5 of 80
- Molecular Biology 663
- Cell Biology 140
- Artificial Intelligence 193
- Spectroscopy 92
- Oncology 131
Countries citing papers authored by Ranabir Das
This map shows the geographic impact of Ranabir 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 Ranabir Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ranabir Das more than expected).
Fields of papers citing papers by Ranabir Das
This network shows the impact of papers produced by Ranabir 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 Ranabir Das. The network helps show where Ranabir Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Ranabir 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 141 | |
| 2 | 2013 | 77 | |
| 3 | 2013 | 65 | |
| 4 | 2011 | 49 | |
| 5 | 2012 | 47 | |
| 6 | 2019 | 45 | |
| 7 | 2015 | 42 | |
| 8 | 2003 | 42 | |
| 9 | 2003 | 37 | |
| 10 | 2012 | 28 | |
| 11 | 2017 | 26 | |
| 12 | 2017 | 24 | |
| 13 | 2003 | 22 | |
| 14 | 2005 | 22 | |
| 15 | 2007 | 21 | |
| 16 | 2020 | 20 | |
| 17 | 2019 | 17 | |
| 18 | 2003 | 16 | |
| 19 | 2020 | 14 | |
| 20 | 2017 | 14 |
About Ranabir Das
Ranabir Das is a scholar working on Molecular Biology, Artificial Intelligence, Epidemiology, Spectroscopy and Materials Chemistry, having authored 55 papers that have together received 1000 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (21 papers), Quantum Computing Algorithms and Architecture (14 papers), Quantum Information and Cryptography (13 papers), Enzyme Structure and Function (8 papers), Molecular spectroscopy and chirality (7 papers), Protein Structure and Dynamics (6 papers), Autophagy in Disease and Therapy (5 papers) and Glycosylation and Glycoproteins Research (4 papers). The work is most often cited by research in Molecular Biology (663 citations), Cell Biology (140 citations), Artificial Intelligence (193 citations), Spectroscopy (92 citations) and Oncology (131 citations). Ranabir Das has collaborated with scholars based in India, United States and France. Frequent co-authors include Anil Kumar, R. Andrew Byrd, Jess Li, Jayant B. Udgaonkar, Allan M. Weissman, Anil Kumar, Xinhua Ji, Jennifer Mariano, Sergey G. Tarasov and T. S. Mahesh. Their work appears in journals such as Physical Review A, Journal of Magnetic Resonance, Protein Science, Journal of Biological Chemistry and Journal of Molecular Biology.
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.