Akira Kiyonaga
- Physiology top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Complementary and alternative medicine top 0.5%
- Cell Biology top 5%
- Genetics top 10%
- Co-authors
- Munehiro ShindoHiroaki TanakaHirofumi TanakaK ArakawaYasuki HigakiMakoto AyabeTakuro TobinaKeijiro Saku
- Topics
- Muscle metabolism and nutrition (23 papers)Cardiovascular and exercise physiology (21 papers)Adipose Tissue and Metabolism (11 papers)
- Cited by
- Complementary and alternative medicineCardiology and Cardiovascular MedicineOrthopedics and Sports Medicine
- Journals
- SHILAP Revista de lepidopterologíaDiabetesBiochemical and Biophysical Research Communications
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Akira Kiyonaga
65 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 109
- Physiology 626
- Cardiology and Cardiovascular Medicine 571
- Complementary and alternative medicine 471
- Cell Biology 372
- Genetics 259
Countries citing papers authored by Akira Kiyonaga
This map shows the geographic impact of Akira Kiyonaga'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 Akira Kiyonaga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akira Kiyonaga more than expected).
Fields of papers citing papers by Akira Kiyonaga
This network shows the impact of papers produced by Akira Kiyonaga. 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 Akira Kiyonaga. The network helps show where Akira Kiyonaga may publish in the future.
Co-authorship network of co-authors of Akira Kiyonaga
This figure shows the co-authorship network connecting the top 25 collaborators of Akira Kiyonaga. A scholar is included among the top collaborators of Akira Kiyonaga based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Akira Kiyonaga. Akira Kiyonaga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 27 | |
| 3 | 8 | |
| 4 | 14 | |
| 5 | 22 | |
| 6 | 2 | |
| 7 | 17 | |
| 8 | 4 | |
| 9 | 13 | |
| 10 | 22 | |
| 11 | 3 | |
| 12 | 23 | |
| 13 | Angiotensin I converting enzyme gene polymorphism and exercise trainability in elderly women: an electrocardiological approach. | 5 |
| 14 | 24 | |
| 15 | 68 | |
| 16 | 21 | |
| 17 | 18 | |
| 18 | 2 | |
| 19 | 20 | |
| 20 | 40 |
About Akira Kiyonaga
Akira Kiyonaga is a scholar working on Complementary and alternative medicine, Cell Biology and Physiology, having authored 68 papers that have together received 1.6k indexed citations. Recurring topics across this work include Muscle metabolism and nutrition (23 papers), Cardiovascular and exercise physiology (21 papers) and Adipose Tissue and Metabolism (11 papers). The work is most often cited by research in Complementary and alternative medicine (471 citations), Cardiology and Cardiovascular Medicine (571 citations) and Orthopedics and Sports Medicine (214 citations). Akira Kiyonaga has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Munehiro Shindo, Hiroaki Tanaka, Hirofumi Tanaka, K Arakawa, Yasuki Higaki, Hiroaki Tanaka, Makoto Ayabe, Takuro Tobina, Keijiro Saku and Takuro Matsuda. Their work appears in journals such as SHILAP Revista de lepidopterología, Diabetes and Biochemical and Biophysical Research Communications.
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.