Deep Chatterjee
Impact in
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- Cellular transport and secretion
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- Parkinson's Disease Mechanisms and Treatments
Papers in ⓘ
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- Parkinson's Disease Mechanisms and Treatments 6
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- Cellular transport and secretion 3
- Co-authors
- Stefan Knapp (19 shared papers)Sebastian Mathea (18 shared papers)Harald Schwalbe (7 shared papers)Josef Wachtveitl (6 shared papers)Erin M. Schuman (2 shared papers)Susanne tom Dieck (2 shared papers)Cyril Hanus (2 shared papers)Florian Buhr (2 shared papers)
- Journals
- Biochemical Journal (4 papers)Angewandte Chemie International Edition (3 papers)Journal of Medicinal Chemistry (3 papers)Science Advances (2 papers)Journal of Biological Chemistry (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Deep Chatterjee
28 papers receiving 460 citations
Peers
Comparison fields: 5 of 64
- Cell Biology 94
- Neurology 76
- Molecular Biology 312
- Cellular and Molecular Neuroscience 74
- Toxicology 7
Countries citing papers authored by Deep Chatterjee
This map shows the geographic impact of Deep Chatterjee'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 Deep Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deep Chatterjee more than expected).
Fields of papers citing papers by Deep Chatterjee
This network shows the impact of papers produced by Deep Chatterjee. 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 Deep Chatterjee. The network helps show where Deep Chatterjee may publish in the future.
Co-authors
The 25 scholars most cited alongside Deep Chatterjee, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 71 | |
| 2 | 2015 | 47 | |
| 3 | 2015 | 37 | |
| 4 | 2019 | 32 | |
| 5 | 2022 | 31 | |
| 6 | 2021 | 30 | |
| 7 | 2023 | 23 | |
| 8 | 2014 | 22 | |
| 9 | 2020 | 21 | |
| 10 | 2015 | 20 | |
| 11 | 2019 | 19 | |
| 12 | 2022 | 17 | |
| 13 | 2022 | 17 | |
| 14 | 2022 | 17 | |
| 15 | 2021 | 9 | |
| 16 | 2014 | 9 | |
| 17 | 2015 | 7 | |
| 18 | 2023 | 6 | |
| 19 | 2025 | 6 | |
| 20 | 2022 | 6 |
About Deep Chatterjee
Deep Chatterjee is a scholar working on Neurology, Cell Biology, Molecular Biology, Immunology and Allergy and Cellular and Molecular Neuroscience, having authored 28 papers that have together received 463 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (6 papers), Receptor Mechanisms and Signaling (5 papers), Plant Gene Expression Analysis (4 papers), Plant biochemistry and biosynthesis (4 papers), Photoreceptor and optogenetics research (4 papers), Neuroscience and Neuropharmacology Research (3 papers), Cellular transport and secretion (3 papers) and Protein Degradation and Inhibitors (2 papers). The work is most often cited by research in Cell Biology (94 citations), Neurology (76 citations), Molecular Biology (312 citations), Cellular and Molecular Neuroscience (74 citations) and Toxicology (7 citations). Deep Chatterjee has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Stefan Knapp, Sebastian Mathea, Harald Schwalbe, Josef Wachtveitl, Erin M. Schuman, Susanne tom Dieck, Cyril Hanus, Florian Buhr, Verena Dederer and S.L. Gande. Their work appears in journals such as Biochemical Journal, Angewandte Chemie International Edition, Journal of Medicinal Chemistry, Science Advances and Journal of Biological Chemistry.
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.