Supriya Sen

977 citations
14 papers · 636 · h-index 11

Impact in

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

Papers in

    • RNA Research and Splicing 9
    • RNA modifications and cancer 7
    • 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 630 citations

Peers

Supriya Sen
Comparison fields: 5 of 59
  • Cancer Research 125
  • Molecular Biology 479
  • Immunology 88
  • Biochemistry 19
  • Cellular and Molecular Neuroscience 42
Replace Jee Yun Han with:
Jee Yun Han United States
Noriyuki Matsuo Japan
Isabel Pereira‐Castro Portugal
Dongmeng Qian China
Tomoyoshi Nakadai Japan
Ok Sun Bang South Korea
Christof Steiner Germany
Young‐Soo Kwon United States
Frederick Bauzon United States
Stefania Oliveto Italy
Supriya Sen relative to Jee Yun Han United States 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 2013122
2 201490
3 200888
4 201163
5 201063
6 200653
7 202047
8 201034
9 201926
10 202225
11 202412
12 20239
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 636 indexed citations. Recurring topics across this work include RNA Research and Splicing (9 papers), RNA modifications and cancer (7 papers), RNA and protein synthesis mechanisms (4 papers), Immune Response and Inflammation (3 papers), Immune cells in cancer (3 papers), interferon and immune responses (2 papers), Cancer-related molecular mechanisms research (2 papers) and NF-κB Signaling Pathways (1 paper). The work is most often cited by research in Cancer Research (125 citations), Molecular Biology (479 citations), Immunology (88 citations), Biochemistry (19 citations) and Cellular and Molecular Neuroscience (42 citations). Supriya Sen has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Nicholas J. G. Webster, Hassan Jumaa, Indrani Talukdar, Alexander Hoffmann, Asitava Basu, Mrinal K. Maiti, Soumitra K. Sen, Ying Liu, John R. Yates and Sita Reddy. Their work appears in journals such as Cell Systems, Nature Communications, Advanced Science, The FASEB Journal and Hepatology.

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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