Yasuyuki Ikeda
- Molecular Biology top 10%
- Clinical Biochemistry top 0.2%
- Endocrinology, Diabetes and Metabolism top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Physiology top 10%
- Co-authors
- Kay TanakaKazuko Okamura‐IkedaC. DabrowskiAkira YamamotoH OzasaAtsuko TakagiGaetano FinocchiaroEtsuo Naito
- Topics
- Metabolism and Genetic Disorders (31 papers)Lipid metabolism and disorders (19 papers)Peroxisome Proliferator-Activated Receptors (16 papers)
- Journals
- Proceedings of the National Academy of SciencesNucleic Acids ResearchJournal of Biological Chemistry
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Yasuyuki Ikeda
93 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 108
- Molecular Biology 1.2k
- Clinical Biochemistry 960
- Endocrinology, Diabetes and Metabolism 277
- Cardiology and Cardiovascular Medicine 258
- Physiology 222
Countries citing papers authored by Yasuyuki Ikeda
This map shows the geographic impact of Yasuyuki Ikeda'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 Yasuyuki Ikeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yasuyuki Ikeda more than expected).
Fields of papers citing papers by Yasuyuki Ikeda
This network shows the impact of papers produced by Yasuyuki Ikeda. 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 Yasuyuki Ikeda. The network helps show where Yasuyuki Ikeda may publish in the future.
Co-authorship network of co-authors of Yasuyuki Ikeda
This figure shows the co-authorship network connecting the top 25 collaborators of Yasuyuki Ikeda. A scholar is included among the top collaborators of Yasuyuki Ikeda 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 Yasuyuki Ikeda. Yasuyuki Ikeda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 45 | |
| 6 | 12 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 9 | |
| 10 | 8 | |
| 11 | 6 | |
| 12 | 31 | |
| 13 | 2 | |
| 14 | [The measurements of lipoprotein lipase activity]. | 8 |
| 15 | Purification and characterization of five acyl-CoA dehydrogenases from rat liver mitochondria. | 3 |
| 16 | 4 | |
| 17 | 22 | |
| 18 | Method for diagnosing the insulation deterioration in mica-resin insulated stator windings of generator | 4 |
| 19 | 46 | |
| 20 | 12 |
About Yasuyuki Ikeda
Yasuyuki Ikeda is a scholar working on Clinical Biochemistry, Biochemistry and Endocrinology, Diabetes and Metabolism, having authored 96 papers that have together received 2.0k indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (31 papers), Lipid metabolism and disorders (19 papers) and Peroxisome Proliferator-Activated Receptors (16 papers). The work is most often cited by research in Clinical Biochemistry (960 citations), Biochemistry (163 citations) and Molecular Biology (1.2k citations). Yasuyuki Ikeda has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Kay Tanaka, Kazuko Okamura‐Ikeda, C. Dabrowski, Akira Yamamoto, H Ozasa, Atsuko Takagi, Gaetano Finocchiaro, Etsuo Naito, A. Takagi and Yoichi Matsubara. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research 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.