Tanmay Chavan

1.2k citations
17 papers · 931 indexed · h-index 12

Impact in

    • Protein Kinase Regulation and GTPase Signaling
    • PI3K/AKT/mTOR signaling in cancer
    • Melanoma and MAPK Pathways
    • Ion channel regulation and function
    • Protein Structure and Dynamics
    • Receptor Mechanisms and Signaling
    • Cell death mechanisms and regulation
  • Cell Biology top 10%

Papers in

    • Protein Kinase Regulation and GTPase Signaling 7
    • Ion channel regulation and function 3
    • Cell death mechanisms and regulation 3
    • Melanoma and MAPK Pathways 2
    • Topic Modeling 4
    • Natural Language Processing Techniques 2
    • Sentiment Analysis and Opinion Mining 2

Tanmay Chavan

16 papers receiving 930 citations

Peers

Tanmay Chavan
Comparison fields: 5 of 103
  • Molecular Biology 717
  • Cell Biology 135
  • Oncology 106
  • Cellular and Molecular Neuroscience 61
  • Toxicology 10
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Tanmay Chavan relative to Ray M. Lee United States Ray M. Lee's profile →
Citations per field
00.5×3.4×
Ray M. Lee · 1×
Citations per year

Countries citing papers authored by Tanmay Chavan

Since Specialization
Citations

This map shows the geographic impact of Tanmay Chavan'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 Tanmay Chavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanmay Chavan more than expected).

Fields of papers citing papers by Tanmay Chavan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tanmay Chavan. 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 Tanmay Chavan. The network helps show where Tanmay Chavan may publish in the future.

Co-authors

The 25 scholars most cited alongside Tanmay Chavan, 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 Tanmay Chavan Line = papers co-authored together Tanmay Chavan links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2013300
2 2015167
3 201592
4 201568
5 201567
6 201559
7 201739
8 201533
9 201633
10 202027
11 201319
12 201818
13 20223
14 20233
15 20232
16 20231
17 20220

About Tanmay Chavan

Tanmay Chavan is a scholar working on Molecular Biology, Artificial Intelligence, Cellular and Molecular Neuroscience, Cell Biology and Organic Chemistry, having authored 17 papers that have together received 931 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (7 papers), Topic Modeling (4 papers), Ion channel regulation and function (3 papers), Cell death mechanisms and regulation (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Natural Language Processing Techniques (2 papers), Melanoma and MAPK Pathways (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Molecular Biology (717 citations), Cell Biology (135 citations), Oncology (106 citations), Cellular and Molecular Neuroscience (61 citations) and Toxicology (10 citations). Tanmay Chavan has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Vadim Gaponenko, Hyunbum Jang, Ruth Nussinov, Andrei L. Gartel, Marianna Halasi, Nissim Hay, Ming Wang, Nadya I. Tarasova, Lyuba Khavrutskii and Sherwin J. Abraham. Their work appears in journals such as Journal of Biological Chemistry, eLife, Proceedings of the National Academy of Sciences, Biochemical Journal and Structure.

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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