Ken Yagi
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- TGF-β signaling in diseases
- Bone Metabolism and Diseases
- Cancer-related gene regulation
- Circular RNAs in diseases
- Kruppel-like factors research
Papers in
-
- TGF-β signaling in diseases 11
- Cancer-related gene regulation 4
- Bone Metabolism and Diseases 4
- Peroxisome Proliferator-Activated Receptors 3
- Oncology 6
- Pancreatic and Hepatic Oncology Research 3
- Co-authors
- Kohei Miyazono (10 shared papers)Mitsuyasu Kato (8 shared papers)Yasushi Okazaki (12 shared papers)Daisuke Goto (4 shared papers)Hiromasa Aoki (2 shared papers)Kazuhiko Takehara (2 shared papers)Masao Furuhashi (3 shared papers)Seiichi Takenoshita (3 shared papers)
In The Last Decade
Ken Yagi
30 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 102
- Cancer Research 497
- Molecular Biology 1.8k
- Genetics 206
- Oncology 360
- Urology 69
Countries citing papers authored by Ken Yagi
This map shows the geographic impact of Ken Yagi'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 Ken Yagi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Yagi more than expected).
Fields of papers citing papers by Ken Yagi
This network shows the impact of papers produced by Ken Yagi. 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 Ken Yagi. The network helps show where Ken Yagi may publish in the future.
Co-authors
The 25 scholars most cited alongside Ken Yagi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 251 | |
| 2 | 2000 | 227 | |
| 3 | 1999 | 208 | |
| 4 | 2002 | 204 | |
| 5 | 2009 | 194 | |
| 6 | 2001 | 188 | |
| 7 | 2004 | 142 | |
| 8 | 2001 | 134 | |
| 9 | 2004 | 96 | |
| 10 | 2003 | 66 | |
| 11 | 2003 | 65 | |
| 12 | 2007 | 63 | |
| 13 | 2003 | 57 | |
| 14 | 1998 | 57 | |
| 15 | 2008 | 51 | |
| 16 | 1998 | 48 | |
| 17 | 2003 | 47 | |
| 18 | Lymphoid enhancer factor 1 makes cells resistant to transforming growth factor beta-induced repression of c-myc. | 2003 | 45 |
| 19 | 1999 | 41 | |
| 20 | 2003 | 36 |
About Ken Yagi
Ken Yagi is a scholar working on Molecular Biology, Oncology, Pathology and Forensic Medicine, Epidemiology and Surgery, having authored 34 papers that have together received 2.3k indexed citations. Recurring topics across this work include TGF-β signaling in diseases (11 papers), Cancer-related gene regulation (4 papers), Bone Metabolism and Diseases (4 papers), Genetic factors in colorectal cancer (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Adipose Tissue and Metabolism (3 papers) and Pancreatic and Hepatic Oncology Research (3 papers). The work is most often cited by research in Cancer Research (497 citations), Molecular Biology (1.8k citations), Genetics (206 citations), Oncology (360 citations) and Urology (69 citations). Ken Yagi has collaborated with scholars based in Japan, Australia and Iran. Frequent co-authors include Kohei Miyazono, Mitsuyasu Kato, Yasushi Okazaki, Daisuke Goto, Hiromasa Aoki, Kazuhiko Takehara, Masao Furuhashi, Seiichi Takenoshita, Daisuke Kondo and Koichiro Kano. Their work appears in journals such as Journal of Biological Chemistry, Genome Research, Biochemical and Biophysical Research Communications, FEBS Letters and Bioscience Biotechnology and Biochemistry.
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.