Takashi Miki
- Molecular Biology top 1%
- Surgery top 0.5%
- Pathology and Forensic Medicine top 0.2%
- Endocrinology, Diabetes and Metabolism top 0.5%
- Cardiology and Cardiovascular Medicine top 1%
- Co-authors
- Susumu SeinoToshihiko IwanagaTadao ShibasakiKazuaki NagashimaKohtaro MinamiHaruaki NakayaYasushige KashimaJun‐ichi Miyazaki
- Topics
- Cardiac Ischemia and Reperfusion (46 papers)Pancreatic function and diabetes (44 papers)Ion channel regulation and function (29 papers)
- Cited by
- Pathology and Forensic MedicineDevelopmental NeuroscienceEndocrinology, Diabetes and Metabolism
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Takashi Miki
138 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Molecular Biology 4.2k
- Surgery 2.9k
- Pathology and Forensic Medicine 2.7k
- Endocrinology, Diabetes and Metabolism 1.7k
- Cardiology and Cardiovascular Medicine 1.5k
Countries citing papers authored by Takashi Miki
This map shows the geographic impact of Takashi Miki'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 Takashi Miki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takashi Miki more than expected).
Fields of papers citing papers by Takashi Miki
This network shows the impact of papers produced by Takashi Miki. 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 Takashi Miki. The network helps show where Takashi Miki may publish in the future.
Co-authorship network of co-authors of Takashi Miki
This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Miki. A scholar is included among the top collaborators of Takashi Miki 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 Takashi Miki. Takashi Miki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 108 | |
| 4 | 5 | |
| 5 | 7 | |
| 6 | 65 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | Gut microbiota confers host resistance to obesity by metabolizing dietary polyunsaturated fatty acidsbreakdown → | 288 |
| 10 | 21 | |
| 11 | 9 | |
| 12 | 88 | |
| 13 | 182 | |
| 14 | 12 | |
| 15 | 0 | |
| 16 | 125 | |
| 17 | 73 | |
| 18 | 64 | |
| 19 | 42 | |
| 20 | Mouse model of Prinzmetal angina by distribution of the inward rectifier Kir6.1 | 0 |
About Takashi Miki
Takashi Miki is a scholar working on Pathology and Forensic Medicine, Developmental Neuroscience and Cardiology and Cardiovascular Medicine, having authored 146 papers that have together received 8.6k indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (46 papers), Pancreatic function and diabetes (44 papers) and Ion channel regulation and function (29 papers). The work is most often cited by research in Pathology and Forensic Medicine (2.7k citations), Developmental Neuroscience (572 citations) and Endocrinology, Diabetes and Metabolism (1.7k citations). Takashi Miki has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Susumu Seino, Toshihiko Iwanaga, Tadao Shibasaki, Kazuaki Nagashima, Kohtaro Minami, Haruaki Nakaya, Yasushige Kashima, Jun‐ichi Miyazaki, Masashi Suzuki and Hideki Yano. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.