Rima Chaudhuri
- Molecular Biology top 10%
- Infectious Diseases top 5%
- Physiology top 5%
- Computational Theory and Mathematics top 2%
- Cell Biology top 5%
- Co-authors
- David E. JamesMichael E. JohnsonBenjamin L. ParkerJun TakayamaArun K. GhoshAndrew D. MesecarKiira RatiaSusan C. Baker
- Topics
- Adipose Tissue and Metabolism (9 papers)Advanced Proteomics Techniques and Applications (6 papers)Metabolism, Diabetes, and Cancer (6 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryThe EMBO Journal
- Partner nations
- AustraliaUnited StatesGermany
In The Last Decade
Rima Chaudhuri
28 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 971
- Infectious Diseases 391
- Physiology 388
- Computational Theory and Mathematics 268
- Cell Biology 261
Countries citing papers authored by Rima Chaudhuri
This map shows the geographic impact of Rima Chaudhuri'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 Rima Chaudhuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rima Chaudhuri more than expected).
Fields of papers citing papers by Rima Chaudhuri
This network shows the impact of papers produced by Rima Chaudhuri. 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 Rima Chaudhuri. The network helps show where Rima Chaudhuri may publish in the future.
Co-authorship network of co-authors of Rima Chaudhuri
This figure shows the co-authorship network connecting the top 25 collaborators of Rima Chaudhuri. A scholar is included among the top collaborators of Rima Chaudhuri based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rima Chaudhuri. Rima Chaudhuri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 3 | |
| 3 | 11 | |
| 4 | Unravelling signal coordination from large scale phosphorylation kinetic data | 1 |
| 5 | 15 | |
| 6 | 28 | |
| 7 | 43 | |
| 8 | 49 | |
| 9 | 46 | |
| 10 | 320 | |
| 11 | 8 | |
| 12 | 7 | |
| 13 | 23 | |
| 14 | 58 | |
| 15 | 49 | |
| 16 | 5 | |
| 17 | 33 | |
| 18 | 23 | |
| 19 | 109 | |
| 20 | 366 |
About Rima Chaudhuri
Rima Chaudhuri is a scholar working on Spectroscopy, Physiology and Computational Theory and Mathematics, having authored 29 papers that have together received 1.6k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (9 papers), Advanced Proteomics Techniques and Applications (6 papers) and Metabolism, Diabetes, and Cancer (6 papers). The work is most often cited by research in Infectious Diseases (391 citations), Computational Theory and Mathematics (268 citations) and Cell Biology (261 citations). Rima Chaudhuri has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include David E. James, Michael E. Johnson, Benjamin L. Parker, Jun Takayama, Arun K. Ghosh, Andrew D. Mesecar, Kiira Ratia, Susan C. Baker, Surendranath Baliji and Bellur S. Prabhakar. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The EMBO Journal.
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.