Jun Kato

76 papers receiving 1.0k citations

Peers

Jun Kato
Comparison fields: 5 of 151
  • Human-Computer Interaction 128
  • Software 33
  • Health, Toxicology and Mutagenesis 116
  • Computer Science Applications 42
  • Mathematical Physics 61
Replace Xin Zeng with:
Xin Zeng China
Kenichiro Ishii Japan
G. Soda Italy
Xiao Gao China
Ziming Li China
Changqing Zhou China
Jingmin Chen China
Minhyeok Lee South Korea
Michael Klein United States
Jun Kato relative to Xin Zeng China Xin Zeng's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jun Kato

Since Specialization
Citations

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

Fields of papers citing papers by Jun Kato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Platelet-derived growth factor indirectly stimulates angiogenesis in vitro.
1993121
2 2004114
3 200453
4
Antitumor activity of basic fibroblast growth factor-saporin mitotoxin in vitro and in vivo.
199253
5 201344
6 199842
7 199339
8 200635
9 199134
10 200932
11 201231
12 201827
13 199226
14 201524
15 200324
16 202022
17
Inorganic polyphosphate stimulates lon-mediated proteolysis of nucleoid proteins in Escherichia coli.
200620
18 200519
19 201217
20
Impaired blood rheology by remnant-like lipoprotein particles: studies in patients with fatty liver disease.
200117

About Jun Kato

Jun Kato is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Molecular Biology, Surgery and Control and Systems Engineering, having authored 80 papers that have together received 1.1k indexed citations. Recurring topics across this work include Interactive and Immersive Displays (14 papers), Music Technology and Sound Studies (8 papers), Advanced Mathematical Physics Problems (5 papers), Multimedia Communication and Technology (5 papers), Software Engineering Research (4 papers), Innovative Human-Technology Interaction (4 papers), Tactile and Sensory Interactions (4 papers) and Teaching and Learning Programming (4 papers). The work is most often cited by research in Human-Computer Interaction (128 citations), Software (33 citations), Health, Toxicology and Mutagenesis (116 citations), Computer Science Applications (42 citations) and Mathematical Physics (61 citations). Jun Kato has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Takeo Igarashi, Masataka Goto, A. Raymond Frackelton, Julie Beitz, Yoko Fujita‐Yamaguchi, Daisuke Sakamoto, Sean McDirmid, Masahide Yamamoto, Tomoaki Okuda and Peter A. Calabresi. Their work appears in journals such as PLoS ONE, Hepatology Research, Scientific Reports, Molecular Genetics and Genomics and Journal of New Music 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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