Ming Wu
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- Circular RNAs in diseases 3
- RNA Research and Splicing 3
- Histone Deacetylase Inhibitors Research 3
- Ubiquitin and proteasome pathways 2
- Epigenetics and DNA Methylation 2
-
- MicroRNA in disease regulation 4
- Co-authors
- Yiwei Liao (4 shared papers)Xuejun Li (5 shared papers)Siyi Wanggou (4 shared papers)Susan J. Gunst (1 shared paper)Leonard P. Adam (1 shared paper)Fredrick M. Pavalko (1 shared paper)Songhua Xiao (2 shared papers)Shuho Semba (3 shared papers)
- Journals
- Frontiers in Cardiovascular Medicine (2 papers)Cellular Physiology and Biochemistry (2 papers)Biochemical and Biophysical Research Communications (1 paper)BioMed Research International (1 paper)PeerJ (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Ming Wu
27 papers receiving 544 citations
Peers
Comparison fields: 5 of 74
- Cancer Research 157
- Aging 9
- Molecular Biology 303
- Immunology and Allergy 19
- Cell Biology 55
Countries citing papers authored by Ming Wu
This map shows the geographic impact of Ming 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 Ming Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Wu more than expected).
Fields of papers citing papers by Ming Wu
This network shows the impact of papers produced by Ming 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 Ming Wu. The network helps show where Ming Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 71 | |
| 2 | 2016 | 57 | |
| 3 | 2014 | 51 | |
| 4 | 2021 | 35 | |
| 5 | 2016 | 35 | |
| 6 | 2004 | 34 | |
| 7 | 2019 | 30 | |
| 8 | 2017 | 27 | |
| 9 | 2016 | 25 | |
| 10 | 2018 | 24 | |
| 11 | 2017 | 20 | |
| 12 | 2020 | 17 | |
| 13 | 2005 | 16 | |
| 14 | 2015 | 15 | |
| 15 | 2015 | 14 | |
| 16 | 2017 | 13 | |
| 17 | 2014 | 13 | |
| 18 | 2013 | 11 | |
| 19 | 2021 | 9 | |
| 20 | 2004 | 8 |
About Ming Wu
Ming Wu is a scholar working on Molecular Biology, Cancer Research, Surgery, Genetics and Epidemiology, having authored 27 papers that have together received 548 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (4 papers), Circular RNAs in diseases (3 papers), RNA Research and Splicing (3 papers), Histone Deacetylase Inhibitors Research (3 papers), Ubiquitin and proteasome pathways (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Sirtuins and Resveratrol in Medicine (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Cancer Research (157 citations), Aging (9 citations), Molecular Biology (303 citations), Immunology and Allergy (19 citations) and Cell Biology (55 citations). Ming Wu has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Yiwei Liao, Xuejun Li, Siyi Wanggou, Susan J. Gunst, Leonard P. Adam, Fredrick M. Pavalko, Songhua Xiao, Shuho Semba, Qing Liu and Hiroshi Yokozaki. Their work appears in journals such as Frontiers in Cardiovascular Medicine, Cellular Physiology and Biochemistry, Biochemical and Biophysical Research Communications, BioMed Research International and PeerJ.
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.