Supriya Sen

965 citations
14 papers · 628 · h-index 10

Impact in

    • Cancer-related molecular mechanisms research
    • RNA Research and Splicing
    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms
    • Metabolism, Diabetes, and Cancer

Papers in

    • RNA Research and Splicing 9
    • RNA modifications and cancer 8
    • RNA and protein synthesis mechanisms 4
    • Immune Response and Inflammation 3
    • Immune cells in cancer 3
    • interferon and immune responses 2

Supriya Sen

14 papers receiving 622 citations

Peers

Supriya Sen
Comparison fields: 5 of 60
  • Cancer Research 130
  • Molecular Biology 506
  • Immunology 89
  • Biochemistry 21
  • Cellular and Molecular Neuroscience 42
Replace Jee Yun Han with:
Jee Yun Han South Korea
Abel C.S. Chun Hong Kong
Melvyn Hollis France
Katsumi Kasashima Japan
Dongmeng Qian China
Stefan J. Siira Australia
Young‐Soo Kwon South Korea
Cate Livingstone United Kingdom
Dionissios Baltzis Canada
Florencia Cano United Kingdom
Supriya Sen relative to Jee Yun Han South Korea Jee Yun Han's profile →
Citations per field
00.5×2.6×
Jee Yun Han · 1×
Citations per year

Countries citing papers authored by Supriya Sen

Since Specialization
Citations

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

Fields of papers citing papers by Supriya Sen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2013121
2 200888
3 201486
4 201063
5 201163
6 200653
7 202047
8 201035
9 201926
10 202224
11 20239
12 20249
13 20183
14 20081

About Supriya Sen

Supriya Sen is a scholar working on Molecular Biology, Immunology, Cancer Research, Oncology and Neurology, having authored 14 papers that have together received 628 indexed citations. Recurring topics across this work include RNA Research and Splicing (9 papers), RNA modifications and cancer (8 papers), RNA and protein synthesis mechanisms (4 papers), Immune Response and Inflammation (3 papers), Cancer-related molecular mechanisms research (3 papers), Immune cells in cancer (3 papers), interferon and immune responses (2 papers) and Cytokine Signaling Pathways and Interactions (1 paper). The work is most often cited by research in Cancer Research (130 citations), Molecular Biology (506 citations), Immunology (89 citations), Biochemistry (21 citations) and Cellular and Molecular Neuroscience (42 citations). Supriya Sen has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Nicholas J. G. Webster, Hassan Jumaa, Indrani Talukdar, Mrinal K. Maiti, Asitava Basu, Alexander Hoffmann, Soumitra K. Sen, Sita Reddy, John R. Yates and James Thompson. Their work appears in journals such as Cell Systems, Molecular and Cellular Biology, Scientific Reports, Advanced Science and Nature Communications.

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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