Deep Chatterjee

813 citations
28 papers · 616 · h-index 14

Impact in

  • Neurology top 10%
    • Parkinson's Disease Mechanisms and Treatments
    • Protein Kinase Regulation and GTPase Signaling
    • Receptor Mechanisms and Signaling
    • RNA and protein synthesis mechanisms

Papers in

    • Parkinson's Disease Mechanisms and Treatments 9
    • Protein Kinase Regulation and GTPase Signaling 15
    • Protein Structure and Dynamics 3
    • Receptor Mechanisms and Signaling 2
    • Chemical Synthesis and Analysis 2

Deep Chatterjee

27 papers receiving 553 citations

Peers

Deep Chatterjee
Comparison fields: 5 of 57
  • Neurology 104
  • Molecular Biology 300
  • Computational Theory and Mathematics 58
  • Aging 5
  • Cellular and Molecular Neuroscience 44
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Citations per field
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Stephen E. Basham · 1×
Citations per year

Countries citing papers authored by Deep Chatterjee

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Deep Chatterjee Line = papers co-authored together Deep Chatterjee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201586
2 202083
3 202066
4 202138
5 201936
6 202335
7 201433
8 202232
9 202026
10 201524
11 201923
12 202222
13 202220
14 202219
15 202514
16 201510
17 202310
18 20219
19 20228
20 20216

About Deep Chatterjee

Deep Chatterjee is a scholar working on Neurology, Molecular Biology, Computational Theory and Mathematics, Organic Chemistry and Cell Biology, having authored 28 papers that have together received 616 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (15 papers), Parkinson's Disease Mechanisms and Treatments (9 papers), Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers), Receptor Mechanisms and Signaling (2 papers), Photoreceptor and optogenetics research (2 papers), Synthesis and biological activity (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Neurology (104 citations), Molecular Biology (300 citations), Computational Theory and Mathematics (58 citations), Aging (5 citations) and Cellular and Molecular Neuroscience (44 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, Cyril Hanus, Erin Margaret Schuman, Susanne tom Dieck, Florian Buhr, Verena Dederer and Steven E. Stayrook. Their work appears in journals such as Biochemical Journal, Journal of Medicinal Chemistry, Angewandte Chemie International Edition, Science Advances and European Journal of Medicinal 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.

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