Jun Wu
Impact in
- Biomaterials top 1%
- Electrospun Nanofibers in Biomedical Applications
- Genetics top 5%
- Mesenchymal stem cell research
Papers in
- Genetics 17
- Mesenchymal stem cell research 17
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- Sphingolipid Metabolism and Signaling 12
- Glycosylation and Glycoproteins Research 7
- Co-authors
- Ren‐Ke Li (43 shared papers)Richard D. Weisel (30 shared papers)Gregory M. Fahy (3 shared papers)Brian G. Wowk (2 shared papers)Tai-Wing Wu (11 shared papers)Hsing‐Wen Sung (9 shared papers)Sharon J. Paynter (1 shared paper)Rui‐Dong Duan (11 shared papers)
- Journals
- Life Sciences (6 papers)Cell Transplantation (4 papers)Vaccines (4 papers)Biomaterials (4 papers)Journal of Cellular and Molecular Medicine (3 papers)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Jun Wu
151 papers receiving 4.8k citations
Peers
Comparison fields: 5 of 143
- Biomaterials 734
- Genetics 346
- Cellular and Molecular Neuroscience 585
- Surgery 1.1k
- Molecular Biology 1.9k
Countries citing papers authored by Jun Wu
This map shows the geographic impact of Jun Wu'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 Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wu more than expected).
Fields of papers citing papers by Jun Wu
This network shows the impact of papers produced by Jun Wu. 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 Wu. The network helps show where Jun Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wu, 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 153 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 274 | |
| 2 | 2004 | 265 | |
| 3 | 2015 | 241 | |
| 4 | 1985 | 213 | |
| 5 | 1996 | 176 | |
| 6 | 2010 | 142 | |
| 7 | 2018 | 140 | |
| 8 | 2003 | 130 | |
| 9 | 2019 | 121 | |
| 10 | 2007 | 118 | |
| 11 | 1997 | 114 | |
| 12 | 1993 | 106 | |
| 13 | 1991 | 99 | |
| 14 | 1985 | 91 | |
| 15 | 2009 | 82 | |
| 16 | 2016 | 81 | |
| 17 | 2020 | 76 | |
| 18 | 2020 | 74 | |
| 19 | 2020 | 74 | |
| 20 | 2013 | 73 |
About Jun Wu
Jun Wu is a scholar working on Genetics, Molecular Biology, Surgery, Cardiology and Cardiovascular Medicine and Biomaterials, having authored 153 papers that have together received 5.0k indexed citations. Recurring topics across this work include Tissue Engineering and Regenerative Medicine (27 papers), Mesenchymal stem cell research (17 papers), Electrospun Nanofibers in Biomedical Applications (14 papers), Sphingolipid Metabolism and Signaling (12 papers), Cardiac Fibrosis and Remodeling (11 papers), Cardiac Ischemia and Reperfusion (9 papers), SARS-CoV-2 and COVID-19 Research (8 papers) and Glycosylation and Glycoproteins Research (7 papers). The work is most often cited by research in Biomaterials (734 citations), Genetics (346 citations), Cellular and Molecular Neuroscience (585 citations), Surgery (1.1k citations) and Molecular Biology (1.9k citations). Jun Wu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Ren‐Ke Li, Richard D. Weisel, Gregory M. Fahy, Brian G. Wowk, Tai-Wing Wu, Hsing‐Wen Sung, Sharon J. Paynter, Rui‐Dong Duan, J. Paul Bolam and A. David Smith. Their work appears in journals such as Life Sciences, Cell Transplantation, Vaccines, Biomaterials and Journal of Cellular and Molecular Medicine.
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.