Jun Takasaki

3.5k citations
43 papers · 2.8k indexed · h-index 25

Impact in

  • Physiology top 2%
    • Asthma and respiratory diseases
    • Adenosine and Purinergic Signaling
    • Hypothalamic control of reproductive hormones

Papers in

Jun Takasaki

41 papers receiving 2.7k citations

Peers

Jun Takasaki
Comparison fields: 5 of 109
  • Physiology 160
  • Reproductive Medicine 275
  • Cellular and Molecular Neuroscience 580
  • Endocrine and Autonomic Systems 198
  • Immunology and Allergy 172
Replace Masazumi Kamohara with:
Masazumi Kamohara Japan
Kiyoshi Furuichi Japan
Hitoshi Matsushime Japan
Finn Olav Levy Norway
Takahide Ohishi Japan
James J. Foley United States
C C Malbon United States
T. Voyno-Yasenetskaya United States
Marvin Bayne United States
Takeo Awaji Japan
Jun Takasaki relative to Masazumi Kamohara Japan Masazumi Kamohara's profile →
Citations per field
00.5×1.5×2.2×
Masazumi Kamohara · 1×
Citations per year

Countries citing papers authored by Jun Takasaki

Since Specialization
Citations

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

Fields of papers citing papers by Jun Takasaki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 200730
2 200710
3 2006216
4 20064
5 200649
6 200611
7 200618
8 200587
9 200537
10 200553
11 2004329
12 2004286
13 200334
14 2003275
15 200068
16 20001
17 2000175
18 20008
19 19993
20 19945

About Jun Takasaki

Jun Takasaki is a scholar working on Immunology and Allergy, Cellular and Molecular Neuroscience, Biotechnology, Endocrine and Autonomic Systems and Physiology, having authored 43 papers that have together received 2.8k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (13 papers), Neuropeptides and Animal Physiology (8 papers), Asthma and respiratory diseases (8 papers), Cell Adhesion Molecules Research (5 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (4 papers), Microbial Metabolism and Applications (4 papers), Microbial Natural Products and Biosynthesis (3 papers) and Protease and Inhibitor Mechanisms (3 papers). The work is most often cited by research in Physiology (160 citations), Reproductive Medicine (275 citations), Cellular and Molecular Neuroscience (580 citations), Endocrine and Autonomic Systems (198 citations) and Immunology and Allergy (172 citations). Jun Takasaki has collaborated with scholars based in Japan, Norway and United States. Frequent co-authors include Tetsu Saito, Masazumi Kamohara, Kiyoshi Furuichi, Takahide Ohishi, Takatoshi Soga, Masatoshi Taniguchi, Mitsuyuki Matsumoto, Masato Kobori, Hideki Hiyama and Hitoshi Matsushime. Their work appears in journals such as Biochemical and Biophysical Research Communications, Inflammation Research, Journal of Leukocyte Biology, Thrombosis and Haemostasis and Journal of Biological Chemistry.

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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