Jun Suzuki

2.2k citations
108 papers · 1.8k · h-index 24

Impact in

    • Ocular Diseases and Behçet’s Syndrome
    • Retinal Diseases and Treatments
    • Retinal and Optic Conditions
  • Nephrology top 5%
    • Renal Diseases and Glomerulopathies

Papers in

Jun Suzuki

100 papers receiving 1.7k citations

Peers

Jun Suzuki
Comparison fields: 5 of 117
  • Ophthalmology 374
  • Nephrology 151
  • Immunology 272
  • Molecular Biology 588
  • Hematology 72
Replace Shyr‐Te Ju with:
Shyr‐Te Ju United States
Gaurav Mehta United States
Scott J. Howell United States
Keisuke Sato Japan
Laura Koumas United States
Yashwanth Subbannayya India
Gonzalo Sánchez‐Duffhues Netherlands
Peter Korošec Slovenia
Kenji Kawai Japan
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Citations per field
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Citations per year

Countries citing papers authored by Jun Suzuki

Since Specialization
Citations

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

Fields of papers citing papers by Jun Suzuki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012150
2 2009110
3 2004106
4 201469
5 200567
6 200565
7 199961
8 200361
9 201459
10 201057
11
Repeat renal biopsy in children with IgA nephropathy.
199053
12
Characterization of murine hemopoietic-supportive (MS-1 and MS-5) and non-supportive (MS-K) cell lines.
199252
13 200150
14 200643
15 199640
16 201339
17 201233
18 200631
19 200726
20 201925

About Jun Suzuki

Jun Suzuki is a scholar working on Molecular Biology, Ophthalmology, Immunology, Public Health, Environmental and Occupational Health and Infectious Diseases, having authored 108 papers that have together received 1.8k indexed citations. Recurring topics across this work include Ocular Diseases and Behçet’s Syndrome (15 papers), Streptococcal Infections and Treatments (13 papers), Immunotherapy and Immune Responses (5 papers), Erythrocyte Function and Pathophysiology (5 papers), T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (5 papers), Retinal Diseases and Treatments (4 papers) and Enzyme-mediated dye degradation (4 papers). The work is most often cited by research in Ophthalmology (374 citations), Nephrology (151 citations), Immunology (272 citations), Molecular Biology (588 citations) and Hematology (72 citations). Jun Suzuki has collaborated with scholars based in Japan, United States and Taiwan. Frequent co-authors include Demetrios G. Vavvas, Joan W. Miller, Masahiko Usui, Hiroshi Gotô, Roger M. Mason, Sharmila Patel, Yusuke Murakami, Kimio Takeuchi, Hidetaka Matsumoto and Zhibin Chen. Their work appears in journals such as Investigative Ophthalmology & Visual Science, Graefe s Archive for Clinical and Experimental Ophthalmology, Ocular Immunology and Inflammation, PLoS ONE and Proceedings of the National Academy of Sciences.

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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