Jun Hamazaki
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Cell Biology top 2%
- Endoplasmic Reticulum Stress and Disease
Papers in
-
- Ubiquitin and proteasome pathways 28
- Glycosylation and Glycoproteins Research 4
- Histone Deacetylase Inhibitors Research 4
- Protein Degradation and Inhibitors 2
- Cell Biology 12
- Endoplasmic Reticulum Stress and Disease 12
- Co-authors
- Shigeo Murata (31 shared papers)Keiji Tanaka (9 shared papers)Hideki Yashiroda (4 shared papers)Tohru Natsume (3 shared papers)Shun‐ichiro Iemura (3 shared papers)Shoshiro Hirayama (11 shared papers)Katsuhiro Sasaki (3 shared papers)Masayuki Miura (2 shared papers)
- Journals
- Molecular and Cellular Biology (6 papers)Nature Communications (4 papers)Genes to Cells (3 papers)Cell Reports (2 papers)Biology Open (1 paper)
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Jun Hamazaki
32 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 86
- Aging 98
- Cell Biology 542
- Molecular Biology 1.5k
- Epidemiology 405
- Oncology 275
Countries citing papers authored by Jun Hamazaki
This map shows the geographic impact of Jun Hamazaki'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 Hamazaki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Hamazaki more than expected).
Fields of papers citing papers by Jun Hamazaki
This network shows the impact of papers produced by Jun Hamazaki. 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 Hamazaki. The network helps show where Jun Hamazaki may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Hamazaki, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 229 | |
| 2 | 2011 | 228 | |
| 3 | 2006 | 213 | |
| 4 | 2009 | 170 | |
| 5 | 2016 | 139 | |
| 6 | 2008 | 98 | |
| 7 | 2007 | 87 | |
| 8 | 2015 | 68 | |
| 9 | 2017 | 65 | |
| 10 | 2014 | 50 | |
| 11 | 2017 | 43 | |
| 12 | 2020 | 39 | |
| 13 | 2009 | 37 | |
| 14 | 2018 | 36 | |
| 15 | 2010 | 34 | |
| 16 | 2020 | 33 | |
| 17 | 2012 | 29 | |
| 18 | 2018 | 25 | |
| 19 | 2019 | 25 | |
| 20 | 2015 | 24 |
About Jun Hamazaki
Jun Hamazaki is a scholar working on Molecular Biology, Cell Biology, Genetics, Immunology and Oncology, having authored 32 papers that have together received 1.8k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (28 papers), Endoplasmic Reticulum Stress and Disease (12 papers), Genetics and Neurodevelopmental Disorders (6 papers), Glycosylation and Glycoproteins Research (4 papers), Histone Deacetylase Inhibitors Research (4 papers), Autophagy in Disease and Therapy (4 papers), Protein Degradation and Inhibitors (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Aging (98 citations), Cell Biology (542 citations), Molecular Biology (1.5k citations), Epidemiology (405 citations) and Oncology (275 citations). Jun Hamazaki has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Shigeo Murata, Keiji Tanaka, Hideki Yashiroda, Tohru Natsume, Shun‐ichiro Iemura, Shoshiro Hirayama, Katsuhiro Sasaki, Masayuki Miura, Erina Kuranaga and Takeyasu Tomioka. Their work appears in journals such as Molecular and Cellular Biology, Nature Communications, Genes to Cells, Cell Reports and Biology Open.
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.