Jun Wan
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Immunology top 5%
Papers in
-
- Circular RNAs in diseases 21
- RNA Research and Splicing 10
- RNA modifications and cancer 8
-
- MicroRNA in disease regulation 25
- Cancer-related molecular mechanisms research 18
- Cancer, Hypoxia, and Metabolism 8
- Co-authors
- Bo Yu (36 shared papers)Jie Pan (6 shared papers)Nana Ma (9 shared papers)Wei Wu (5 shared papers)Ming Guan (22 shared papers)Xiaoyang Ye (10 shared papers)Kepeng Wang (5 shared papers)Yifei Cai (3 shared papers)
- Journals
- Structure (4 papers)Frontiers in Molecular Neuroscience (4 papers)PLoS ONE (3 papers)Experimental Cell Research (3 papers)eLife (3 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Jun Wan
161 papers receiving 3.8k citations
Peers
Comparison fields: 5 of 124
- Cancer Research 1.2k
- Immunology 650
- Neurology 220
- Molecular Biology 1.8k
- Biological Psychiatry 58
Countries citing papers authored by Jun Wan
This map shows the geographic impact of Jun Wan'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 Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wan more than expected).
Fields of papers citing papers by Jun Wan
This network shows the impact of papers produced by Jun Wan. 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 Wan. The network helps show where Jun Wan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wan, 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 166 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 267 | |
| 2 | 2010 | 186 | |
| 3 | 2020 | 128 | |
| 4 | 2010 | 113 | |
| 5 | 2020 | 111 | |
| 6 | 2013 | 103 | |
| 7 | 2019 | 96 | |
| 8 | 2012 | 87 | |
| 9 | 2016 | 76 | |
| 10 | 2013 | 75 | |
| 11 | 2011 | 69 | |
| 12 | 2020 | 66 | |
| 13 | 2003 | 66 | |
| 14 | 2013 | 60 | |
| 15 | 2017 | 60 | |
| 16 | 2017 | 60 | |
| 17 | 2019 | 59 | |
| 18 | 2000 | 58 | |
| 19 | 2014 | 57 | |
| 20 | 2008 | 51 |
About Jun Wan
Jun Wan is a scholar working on Molecular Biology, Cancer Research, Immunology, Surgery and Genetics, having authored 166 papers that have together received 3.8k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (25 papers), Circular RNAs in diseases (21 papers), Cancer-related molecular mechanisms research (18 papers), RNA Research and Splicing (10 papers), Genomic variations and chromosomal abnormalities (10 papers), RNA modifications and cancer (8 papers), Cancer, Hypoxia, and Metabolism (8 papers) and Immune Response and Inflammation (7 papers). The work is most often cited by research in Cancer Research (1.2k citations), Immunology (650 citations), Neurology (220 citations), Molecular Biology (1.8k citations) and Biological Psychiatry (58 citations). Jun Wan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Bo Yu, Jie Pan, Nana Ma, Wei Wu, Ming Guan, Xiaoyang Ye, Kepeng Wang, Yifei Cai, Zhenguo Wu and Wei Zhang. Their work appears in journals such as Structure, Frontiers in Molecular Neuroscience, PLoS ONE, Experimental Cell Research and eLife.
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.