Wu Sun
Impact in
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- Circular RNAs in diseases
- Extracellular vesicles in disease
- RNA modifications and cancer
- RNA Research and Splicing
- RNA Interference and Gene Delivery
Papers in
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- Circular RNAs in diseases 8
- RNA Research and Splicing 5
- RNA modifications and cancer 3
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- MicroRNA in disease regulation 12
- Cancer-related molecular mechanisms research 10
- Co-authors
- Haiyang Zhang (9 shared papers)Yi Ba (9 shared papers)Jialu Li (4 shared papers)Yanqing Liu (5 shared papers)Chen‐Yu Zhang (4 shared papers)Jiayi Han (3 shared papers)Xi Chen (3 shared papers)Zheng Fu (2 shared papers)
In The Last Decade
Wu Sun
25 papers receiving 977 citations
Peers
Comparison fields: 5 of 80
- Cancer Research 665
- Molecular Biology 784
- Reproductive Medicine 38
- Pathology and Forensic Medicine 79
- Immunology 61
Countries citing papers authored by Wu Sun
This map shows the geographic impact of Wu Sun'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 Wu Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wu Sun more than expected).
Fields of papers citing papers by Wu Sun
This network shows the impact of papers produced by Wu Sun. 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 Wu Sun. The network helps show where Wu Sun may publish in the future.
Co-authors
The 25 scholars most cited alongside Wu Sun, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 158 | |
| 2 | 2017 | 127 | |
| 3 | 2020 | 107 | |
| 4 | 2018 | 99 | |
| 5 | 2018 | 81 | |
| 6 | 2016 | 76 | |
| 7 | 2017 | 44 | |
| 8 | 2020 | 43 | |
| 9 | 2016 | 41 | |
| 10 | 2018 | 37 | |
| 11 | 2020 | 37 | |
| 12 | 2016 | 31 | |
| 13 | 2020 | 29 | |
| 14 | 2018 | 15 | |
| 15 | 2021 | 14 | |
| 16 | 2013 | 14 | |
| 17 | 2019 | 12 | |
| 18 | 2019 | 9 | |
| 19 | [Comparison of two techniques in hemivertebra resection: anterior- posterior approach versus posterior approach]. | 2012 | 5 |
| 20 | Kawasaki disease presenting with disseminated intravascular coagulation: report of one case. | 1994 | 4 |
About Wu Sun
Wu Sun is a scholar working on Molecular Biology, Cancer Research, Surgery, Pathology and Forensic Medicine and Pharmacology, having authored 26 papers that have together received 989 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (12 papers), Cancer-related molecular mechanisms research (10 papers), Circular RNAs in diseases (8 papers), Spine and Intervertebral Disc Pathology (5 papers), RNA Research and Splicing (5 papers), Musculoskeletal pain and rehabilitation (3 papers), RNA modifications and cancer (3 papers) and Scoliosis diagnosis and treatment (3 papers). The work is most often cited by research in Cancer Research (665 citations), Molecular Biology (784 citations), Reproductive Medicine (38 citations), Pathology and Forensic Medicine (79 citations) and Immunology (61 citations). Wu Sun has collaborated with scholars based in China, Taiwan and Czechia. Frequent co-authors include Haiyang Zhang, Yi Ba, Jialu Li, Yanqing Liu, Chen‐Yu Zhang, Jiayi Han, Xi Chen, Zheng Fu, Likun Zhou and Xiaorui Chen. Their work appears in journals such as Scientific Reports, Cell Death and Disease, Cancer Science, Molecular Cancer and Protein & Cell.
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.