Jun Mi
Impact in
- Cancer Research top 2%
- Cancer, Hypoxia, and Metabolism
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Oncology top 5%
- Cancer Cells and Metastasis
Papers in
-
- Cancer, Hypoxia, and Metabolism 11
- MicroRNA in disease regulation 6
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- DNA Repair Mechanisms 9
- Metabolism, Diabetes, and Cancer 7
- Epigenetics and DNA Methylation 5
- RNA modifications and cancer 4
- Co-authors
- James Mitchell Larner (7 shared papers)Daoxiang Zhang (3 shared papers)Jun He (2 shared papers)Binhua Peter Zhou (3 shared papers)Pan Sun (4 shared papers)Shimin Zhao (2 shared papers)Xiaodan Hou (3 shared papers)David L. Brautigan (4 shared papers)
- Journals
- Theranostics (5 papers)Cell Death and Disease (4 papers)Cellular Signalling (3 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)BMC Urology (2 papers)
- Partner nations
- ChinaUnited StatesThailand
In The Last Decade
Jun Mi
82 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 124
- Cancer Research 887
- Oncology 532
- Molecular Biology 1.3k
- Cell Biology 204
- Biological Psychiatry 27
Countries citing papers authored by Jun Mi
This map shows the geographic impact of Jun Mi'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 Mi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Mi more than expected).
Fields of papers citing papers by Jun Mi
This network shows the impact of papers produced by Jun Mi. 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 Mi. The network helps show where Jun Mi may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Mi, 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 83 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 284 | |
| 2 | 2005 | 205 | |
| 3 | 2013 | 158 | |
| 4 | 2017 | 125 | |
| 5 | 2019 | 97 | |
| 6 | 2014 | 93 | |
| 7 | 2015 | 90 | |
| 8 | 2021 | 89 | |
| 9 | 2009 | 82 | |
| 10 | 2007 | 73 | |
| 11 | 2014 | 72 | |
| 12 | 2017 | 64 | |
| 13 | 2005 | 62 | |
| 14 | 2017 | 59 | |
| 15 | 2006 | 54 | |
| 16 | 2008 | 50 | |
| 17 | 2014 | 48 | |
| 18 | 2018 | 46 | |
| 19 | 2004 | 45 | |
| 20 | 2017 | 44 |
About Jun Mi
Jun Mi is a scholar working on Cancer Research, Molecular Biology, Oncology, Biological Psychiatry and Periodontics, having authored 83 papers that have together received 2.8k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (11 papers), DNA Repair Mechanisms (9 papers), Metabolism, Diabetes, and Cancer (7 papers), MicroRNA in disease regulation (6 papers), Kidney Stones and Urolithiasis Treatments (5 papers), Ferroptosis and cancer prognosis (5 papers), Epigenetics and DNA Methylation (5 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Cancer Research (887 citations), Oncology (532 citations), Molecular Biology (1.3k citations), Cell Biology (204 citations) and Biological Psychiatry (27 citations). Jun Mi has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include James Mitchell Larner, Daoxiang Zhang, Jun He, Binhua Peter Zhou, Pan Sun, Shimin Zhao, Xiaodan Hou, David L. Brautigan, Yongbin Wang and Heping Li. Their work appears in journals such as Theranostics, Cell Death and Disease, Cellular Signalling, International Journal of Radiation Oncology*Biology*Physics and BMC Urology.
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.