Daisuke Sakurai

1.3k citations
29 papers · 935 · h-index 16

Impact in

  • Immunology top 10%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • Immunodeficiency and Autoimmune Disorders

Papers in

    • TGF-β signaling in diseases 4
    • Angiogenesis and VEGF in Cancer 3
    • Immune Cell Function and Interaction 6
    • T-cell and B-cell Immunology 4
    • Immunodeficiency and Autoimmune Disorders 3

Daisuke Sakurai

28 papers receiving 921 citations

Peers

Daisuke Sakurai
Comparison fields: 5 of 90
  • Immunology 361
  • Cancer Research 142
  • Virology 28
  • Molecular Biology 407
  • Immunology and Allergy 35
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Citations per field
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Citations per year

Countries citing papers authored by Daisuke Sakurai

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Sakurai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003128
2 200697
3 200379
4 200477
5 200976
6 200664
7 200455
8 200550
9 200845
10 200444
11 200833
12 200530
13 200129
14 200823
15
Follistatin-related protein gene (FRP) is expressed in the synovial tissues of rheumatoid arthritis, but its polymorphisms are not associated with genetic susceptibility.
200516
16 201515
17 201513
18 201011
19 201211
20 20048

About Daisuke Sakurai

Daisuke Sakurai is a scholar working on Molecular Biology, Immunology, Cancer Research, Cellular and Molecular Neuroscience and Global and Planetary Change, having authored 29 papers that have together received 935 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (6 papers), TGF-β signaling in diseases (4 papers), T-cell and B-cell Immunology (4 papers), Neurobiology and Insect Physiology Research (4 papers), Marine Ecology and Invasive Species (4 papers), Immunodeficiency and Autoimmune Disorders (3 papers), Angiogenesis and VEGF in Cancer (3 papers) and HIV Research and Treatment (2 papers). The work is most often cited by research in Immunology (361 citations), Cancer Research (142 citations), Virology (28 citations), Molecular Biology (407 citations) and Immunology and Allergy (35 citations). Daisuke Sakurai has collaborated with scholars based in Japan, United States and Vietnam. Frequent co-authors include Tetsuji Kobata, Hidenori Hase, Hidefumi Kojima, Yumiko Kanno, Motoyuki Tsuda, Ko Okumura, Katsushi Tokunaga, Naoyuki Tsuchiya, Takeo Horie and Nelson H. Tsuno. Their work appears in journals such as The Journal of Immunology, The Journal of Comparative Neurology, Biochemical and Biophysical Research Communications, Blood and Scientific Reports.

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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