JUN KAWADA

697 citations
44 papers · 583 · h-index 14

Impact in

Papers in

JUN KAWADA

41 papers receiving 538 citations

Peers

JUN KAWADA
Comparison fields: 5 of 98
  • Inorganic Chemistry 110
  • Endocrinology, Diabetes and Metabolism 116
  • Health, Toxicology and Mutagenesis 79
  • Nutrition and Dietetics 78
  • Pharmaceutical Science 27
Replace Makoto Ueda with:
Makoto Ueda Japan
Eugene S. Baginski United States
Juan R. Tejedo Spain
Edwin S. Higgins United States
Yukikazu Saeki Japan
Ruth Partridge Australia
Milton J. Axley United States
Kozaburo Adachi Japan
Éric Badia France
Natesampillai Sekar Israel
JUN KAWADA relative to Makoto Ueda Japan Makoto Ueda's profile →
Citations per field
00.5×3.9×
Makoto Ueda · 1×
Citations per year

Countries citing papers authored by JUN KAWADA

Since Specialization
Citations

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

Fields of papers citing papers by JUN KAWADA

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990105
2 198868
3 196944
4 198040
5 197932
6 198931
7 198628
8 198125
9 199023
10 198623
11 199420
12 198520
13 199216
14 197513
15 199010
16 19889
17 19749
18 19927
19 19917
20 19846

About JUN KAWADA

JUN KAWADA is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Physiology, Genetics and Organic Chemistry, having authored 44 papers that have together received 583 indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (8 papers), ATP Synthase and ATPases Research (2 papers), Neurobiology and Insect Physiology Research (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Chemical Reactions and Isotopes (2 papers), Lipid Membrane Structure and Behavior (2 papers), Parathyroid Disorders and Treatments (2 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Inorganic Chemistry (110 citations), Endocrinology, Diabetes and Metabolism (116 citations), Health, Toxicology and Mutagenesis (79 citations), Nutrition and Dietetics (78 citations) and Pharmaceutical Science (27 citations). JUN KAWADA has collaborated with scholars based in Japan, United States and Poland. Frequent co-authors include Mikio Nishida, Yoshiyuki Yoshimura, Mamoru Nukatsuka, Hiromu Sakurai, R. E. Taylor, S. B. Barker, Shinichiro Ishikawa, Makoto Komatsu, Hidehiko Yoshida and Koichiro Tsuchiya. Their work appears in journals such as Journal of Pharmaceutical Sciences, Endocrinology, Chemical and Pharmaceutical Bulletin, FEBS Letters and Journal of Biomedical Materials Research.

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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