Jun Morinaga

1.6k citations
63 papers · 995 · h-index 19

Impact in

    • Cancer-related molecular mechanisms research
    • Cancer, Hypoxia, and Metabolism
    • MicroRNA in disease regulation
  • Nephrology top 5%

Papers in

Jun Morinaga

59 papers receiving 986 citations

Peers

Jun Morinaga
Comparison fields: 5 of 96
  • Cancer Research 254
  • Nephrology 118
  • Cardiology and Cardiovascular Medicine 307
  • Aging 18
  • Endocrinology, Diabetes and Metabolism 144
Replace Karen Bulmer with:
Karen Bulmer United Kingdom
Koichi Sohmiya Japan
Kumiko Torisu Japan
Masahiro Koide Japan
Yiqin Zuo United States
Michelle J. Ormseth United States
Denise M. Sadlier Ireland
Ute Haas Germany
Pietro E. Cippà Switzerland
Sharon Li Ting Pek Singapore
Jun Morinaga relative to Karen Bulmer United Kingdom Karen Bulmer's profile →
Citations per field
00.5×7.6×
Karen Bulmer · 1×
Citations per year

Countries citing papers authored by Jun Morinaga

Since Specialization
Citations

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

Fields of papers citing papers by Jun Morinaga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202082
2 201558
3 201957
4 201553
5 201851
6 201749
7 201748
8 201446
9 201844
10 201231
11 202129
12 201725
13 201624
14 202023
15 202322
16 201221
17 201719
18 201819
19 201918
20 201718

About Jun Morinaga

Jun Morinaga is a scholar working on Cardiology and Cardiovascular Medicine, Nephrology, Cancer Research, Endocrinology, Diabetes and Metabolism and Surgery, having authored 63 papers that have together received 995 indexed citations. Recurring topics across this work include Lipid metabolism and disorders (22 papers), Cancer-related molecular mechanisms research (9 papers), Cancer, Hypoxia, and Metabolism (9 papers), Chronic Kidney Disease and Diabetes (7 papers), Dialysis and Renal Disease Management (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Hormonal Regulation and Hypertension (4 papers) and Liver Disease Diagnosis and Treatment (4 papers). The work is most often cited by research in Cancer Research (254 citations), Nephrology (118 citations), Cardiology and Cardiovascular Medicine (307 citations), Aging (18 citations) and Endocrinology, Diabetes and Metabolism (144 citations). Jun Morinaga has collaborated with scholars based in Japan, United States and Poland. Frequent co-authors include Yuichi Oike, Tsuyoshi Kadomatsu, Motoyoshi Endo, Keishi Miyata, Kazutoyo Terada, Haruki Horiguchi, Taichi Sugizaki, Masashi Mukoyama, Zhe Tian and Kimi Araki. Their work appears in journals such as Circulation Journal, Journal of Pharmacological Sciences, American Journal of Physiology-Renal Physiology, Oncogene and PLoS ONE.

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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