Jun Matsuda

1.4k citations
35 papers · 996 · h-index 16

Impact in

  • Nephrology top 2%
    • Chronic Kidney Disease and Diabetes
    • Renal Diseases and Glomerulopathies
    • Advanced Glycation End Products research

Papers in

    • Renal Diseases and Glomerulopathies 12
    • Chronic Kidney Disease and Diabetes 9
    • Autophagy in Disease and Therapy 8

Jun Matsuda

33 papers receiving 990 citations

Peers

Jun Matsuda
Comparison fields: 5 of 85
  • Nephrology 277
  • Clinical Biochemistry 101
  • Epidemiology 321
  • Biochemistry 57
  • Pathology and Forensic Medicine 116
Replace Satoshi Minami with:
Satoshi Minami Japan
Jun‐Ya Kaimori Japan
Hisazumi Araki Japan
Kosuke Yamahara Japan
Satish RamachandraRao United States
Feng Guo China
Qingjuan Liu China
Olivia Lenoir France
Hitoshi Minakuchi Japan
Mako Yasuda Japan
Jun Matsuda relative to Satoshi Minami Japan Satoshi Minami's profile →
Citations per field
00.5×1.5×
Satoshi Minami · 1×
Citations per year

Countries citing papers authored by Jun Matsuda

Since Specialization
Citations

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

Fields of papers citing papers by Jun Matsuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016221
2 2017103
3 2016103
4 201977
5 202073
6 201754
7 201753
8 201450
9 202043
10 200126
11 199024
12 200021
13 202017
14 202117
15 202317
16 202015
17 201015
18 201813
19 199911
20 20248

About Jun Matsuda

Jun Matsuda is a scholar working on Nephrology, Epidemiology, Molecular Biology, Surgery and Pulmonary and Respiratory Medicine, having authored 35 papers that have together received 996 indexed citations. Recurring topics across this work include Renal Diseases and Glomerulopathies (12 papers), Chronic Kidney Disease and Diabetes (9 papers), Autophagy in Disease and Therapy (8 papers), Vasculitis and related conditions (4 papers), Biomedical Research and Pathophysiology (3 papers), Lymphatic Disorders and Treatments (2 papers), Liver physiology and pathology (2 papers) and Lipid metabolism and biosynthesis (2 papers). The work is most often cited by research in Nephrology (277 citations), Clinical Biochemistry (101 citations), Epidemiology (321 citations), Biochemistry (57 citations) and Pathology and Forensic Medicine (116 citations). Jun Matsuda has collaborated with scholars based in Japan, Canada and United States. Frequent co-authors include Takeshi Yamamoto, Tomoko Namba‐Hamano, Yoshitsugu Takabatake, Isao Matsui, Yoshitaka Isaka, Atsushi Takahashi, Satoshi Minami, Fumio Niimura, Taiji Matsusaka and Tomonori Kimura. Their work appears in journals such as Autophagy, Journal of the American Society of Nephrology, Kidney International, Biochemical and Biophysical Research Communications and Diabetologia.

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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