Jun Shi
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Nephrology top 5%
- Renal Diseases and Glomerulopathies
- Dialysis and Renal Disease Management
Papers in
-
- Circular RNAs in diseases 4
- Extracellular vesicles in disease 4
- RNA modifications and cancer 3
- Metabolism, Diabetes, and Cancer 2
-
- Cancer-related molecular mechanisms research 10
- MicroRNA in disease regulation 6
- Co-authors
- Yali Ma (3 shared papers)Xiaoguang Zhu (2 shared papers)Suxia Yang (3 shared papers)Fang Chen (2 shared papers)Qingyang Luo (1 shared paper)Yun Wang (1 shared paper)Yang Li (1 shared paper)Fang Chen (1 shared paper)
- Journals
- Phytomedicine (2 papers)Journal of Cellular and Molecular Medicine (2 papers)Cellular Physiology and Biochemistry (2 papers)Journal of Biological Chemistry (2 papers)Frontiers in Pharmacology (2 papers)
- Partner nations
- ChinaHong KongNew Zealand
In The Last Decade
Jun Shi
39 papers receiving 852 citations
Peers
Comparison fields: 5 of 80
- Cancer Research 255
- Nephrology 84
- Molecular Biology 499
- Genetics 62
- Obstetrics and Gynecology 23
Countries citing papers authored by Jun Shi
This map shows the geographic impact of Jun Shi'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 Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Shi more than expected).
Fields of papers citing papers by Jun Shi
This network shows the impact of papers produced by Jun Shi. 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 Shi. The network helps show where Jun Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Shi, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 108 | |
| 2 | 2020 | 105 | |
| 3 | 2015 | 89 | |
| 4 | 2017 | 53 | |
| 5 | 2015 | 50 | |
| 6 | 2015 | 44 | |
| 7 | 2008 | 36 | |
| 8 | 2023 | 35 | |
| 9 | 2021 | 31 | |
| 10 | 2020 | 29 | |
| 11 | 2021 | 24 | |
| 12 | 2020 | 23 | |
| 13 | 2012 | 20 | |
| 14 | 2022 | 18 | |
| 15 | 2016 | 16 | |
| 16 | 2018 | 15 | |
| 17 | 2008 | 15 | |
| 18 | 2015 | 14 | |
| 19 | 2018 | 14 | |
| 20 | 2018 | 13 |
About Jun Shi
Jun Shi is a scholar working on Molecular Biology, Cancer Research, Epidemiology, Immunology and Nephrology, having authored 39 papers that have together received 868 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (10 papers), MicroRNA in disease regulation (6 papers), Circular RNAs in diseases (4 papers), Extracellular vesicles in disease (4 papers), RNA modifications and cancer (3 papers), Galectins and Cancer Biology (2 papers), Metabolism, Diabetes, and Cancer (2 papers) and Cardiovascular Disease and Adiposity (2 papers). The work is most often cited by research in Cancer Research (255 citations), Nephrology (84 citations), Molecular Biology (499 citations), Genetics (62 citations) and Obstetrics and Gynecology (23 citations). Jun Shi has collaborated with scholars based in China, Hong Kong and New Zealand. Frequent co-authors include Yali Ma, Xiaoguang Zhu, Suxia Yang, Fang Chen, Qingyang Luo, Yun Wang, Yang Li, Fang Chen, Junwei Zhang and Huicong Li. Their work appears in journals such as Phytomedicine, Journal of Cellular and Molecular Medicine, Cellular Physiology and Biochemistry, Journal of Biological Chemistry and Frontiers in Pharmacology.
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.