Jun‐ichi Nishimura

3.0k citations
102 papers · 1.7k · h-index 22

Impact in

  • Nephrology top 1%
    • Renal Diseases and Glomerulopathies
  • Immunology top 2%
    • Complement system in diseases

Papers in

    • Complement system in diseases 73
    • Blood groups and transfusion 36
    • Platelet Disorders and Treatments 10

Jun‐ichi Nishimura

96 papers receiving 1.6k citations

Peers

Jun‐ichi Nishimura
Comparison fields: 5 of 95
  • Nephrology 434
  • Immunology 1.0k
  • Hematology 406
  • Behavioral Neuroscience 117
  • Physiology 151
Replace Manfred Baetscher with:
Manfred Baetscher United States
Emilie Dugast France
B H Toh Australia
John G. Gartner Canada
Élodie Gautier France
Nathalie Davoust France
J.H. Marco Jansen Netherlands
Emilia Maria Cristina Mazza Italy
Tomoko Kohno Japan
Hiroyoshi Ishizaki Japan
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Citations per field
00.5×10×16.8×
Manfred Baetscher · 1×
Citations per year

Countries citing papers authored by Jun‐ichi Nishimura

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐ichi Nishimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 102 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994193
2 2004189
3 200393
4 200691
5 199757
6 199657
7 199453
8 199049
9 200249
10 199945
11 199845
12 202243
13 201741
14 199237
15 200335
16 200834
17 200231
18 199931
19 199730
20 199327

About Jun‐ichi Nishimura

Jun‐ichi Nishimura is a scholar working on Immunology, Hematology, Genetics, Nephrology and Epidemiology, having authored 102 papers that have together received 1.7k indexed citations. Recurring topics across this work include Complement system in diseases (73 papers), Blood groups and transfusion (36 papers), Renal Diseases and Glomerulopathies (23 papers), Hemoglobinopathies and Related Disorders (15 papers), Platelet Disorders and Treatments (10 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (10 papers), Trypanosoma species research and implications (10 papers) and Adenosine and Purinergic Signaling (7 papers). The work is most often cited by research in Nephrology (434 citations), Immunology (1.0k citations), Hematology (406 citations), Behavioral Neuroscience (117 citations) and Physiology (151 citations). Jun‐ichi Nishimura has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Taroh Kinoshita, Fukuko Kimura, Wendell F. Rosse, Teruo Kitani, Yuzuru Kanakura, Norimitsu Inoue, Yutaka Endo, Toshio Miyata, Norio Yamada and Yoshiyasu Iida. Their work appears in journals such as Blood, International Journal of Hematology, European Journal Of Haematology, British Journal of Haematology and HemaSphere.

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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