Jun Koseki
Impact in
- Cancer Research top 1%
- Cancer, Hypoxia, and Metabolism
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Geriatrics and Gerontology top 2%
Papers in
-
- Epigenetics and DNA Methylation 15
- RNA modifications and cancer 8
- Pluripotent Stem Cells Research 4
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- Cancer, Hypoxia, and Metabolism 13
- MicroRNA in disease regulation 6
- Co-authors
- Masamitsu Konno (49 shared papers)Yuichiro� Doki (48 shared papers)Masaki Mori (46 shared papers)Hideshi Ishii (45 shared papers)Koichi Kawamoto (38 shared papers)Naohiro Nishida (36 shared papers)Ayumu Asai (19 shared papers)Taroh Satoh (20 shared papers)
- Journals
- Scientific Reports (10 papers)International Journal of Oncology (6 papers)Cancer Research (5 papers)Cancer Science (3 papers)Oncology Reports (3 papers)
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Jun Koseki
70 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 110
- Cancer Research 1.1k
- Geriatrics and Gerontology 110
- Molecular Biology 1.6k
- Oncology 450
- Biotechnology 82
Countries citing papers authored by Jun Koseki
This map shows the geographic impact of Jun Koseki'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 Koseki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Koseki more than expected).
Fields of papers citing papers by Jun Koseki
This network shows the impact of papers produced by Jun Koseki. 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 Koseki. The network helps show where Jun Koseki may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Koseki, 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 317 | |
| 2 | 2014 | 194 | |
| 3 | 2017 | 194 | |
| 4 | 2019 | 154 | |
| 5 | 2015 | 137 | |
| 6 | 2014 | 127 | |
| 7 | 2016 | 97 | |
| 8 | 2012 | 74 | |
| 9 | 2016 | 56 | |
| 10 | 2019 | 56 | |
| 11 | 2019 | 52 | |
| 12 | 2015 | 51 | |
| 13 | 2018 | 51 | |
| 14 | 2016 | 48 | |
| 15 | 2019 | 43 | |
| 16 | 2018 | 39 | |
| 17 | 2016 | 38 | |
| 18 | 2015 | 35 | |
| 19 | 2018 | 35 | |
| 20 | 2019 | 33 |
About Jun Koseki
Jun Koseki is a scholar working on Molecular Biology, Cancer Research, Oncology, Organic Chemistry and Surgery, having authored 73 papers that have together received 2.4k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (15 papers), Cancer, Hypoxia, and Metabolism (13 papers), Cancer Cells and Metastasis (8 papers), RNA modifications and cancer (8 papers), MicroRNA in disease regulation (6 papers), Pancreatic and Hepatic Oncology Research (5 papers), Pancreatic function and diabetes (4 papers) and Pluripotent Stem Cells Research (4 papers). The work is most often cited by research in Cancer Research (1.1k citations), Geriatrics and Gerontology (110 citations), Molecular Biology (1.6k citations), Oncology (450 citations) and Biotechnology (82 citations). Jun Koseki has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Masamitsu Konno, Yuichiro� Doki, Masaki Mori, Hideshi Ishii, Koichi Kawamoto, Naohiro Nishida, Ayumu Asai, Taroh Satoh, Tsunekazu Mizushima and Kazuhiko Ogawa. Their work appears in journals such as Scientific Reports, International Journal of Oncology, Cancer Research, Cancer Science and Oncology Reports.
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.