Kai Wu
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies
- Plant biochemistry and biosynthesis
- RNA modifications and cancer
- Cancer-related gene regulation
Papers in
-
- Gut microbiota and health 4
- Epigenetics and DNA Methylation 4
- CRISPR and Genetic Engineering 4
- Ubiquitin and proteasome pathways 3
-
- Malaria Research and Control 15
- Mosquito-borne diseases and control 5
- Co-authors
- Christopher D. Reeves (1 shared paper)Leonard Katz (1 shared paper)Loleta Chung (1 shared paper)W. Peter Revill (1 shared paper)Laurence A. Lasky (2 shared papers)Lin Zhang (2 shared papers)Haimei Chen (3 shared papers)Yanshu Qu (3 shared papers)
- Journals
- European Radiology (3 papers)Gene (3 papers)Malaria Journal (3 papers)Molecular and Cellular Biochemistry (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Kai Wu
100 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 123
- Cancer Research 240
- Molecular Biology 1.0k
- Pharmacology 234
- Immunology 165
- Oncology 172
Countries citing papers authored by Kai Wu
This map shows the geographic impact of Kai 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 Kai Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Wu more than expected).
Fields of papers citing papers by Kai Wu
This network shows the impact of papers produced by Kai 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 Kai Wu. The network helps show where Kai Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai 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 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 229 | |
| 2 | 1996 | 85 | |
| 3 | 1997 | 81 | |
| 4 | 2022 | 71 | |
| 5 | 2018 | 66 | |
| 6 | 2010 | 61 | |
| 7 | 2023 | 53 | |
| 8 | 2009 | 49 | |
| 9 | 2014 | 47 | |
| 10 | 2010 | 39 | |
| 11 | 2015 | 37 | |
| 12 | 2019 | 36 | |
| 13 | 2019 | 36 | |
| 14 | 2020 | 35 | |
| 15 | 2023 | 29 | |
| 16 | 2017 | 29 | |
| 17 | 2017 | 27 | |
| 18 | 2010 | 24 | |
| 19 | 2017 | 24 | |
| 20 | 2023 | 24 |
About Kai Wu
Kai Wu is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health, Surgery, Cancer Research and Pathology and Forensic Medicine, having authored 104 papers that have together received 1.8k indexed citations. Recurring topics across this work include Malaria Research and Control (15 papers), Mosquito-borne diseases and control (5 papers), Gut microbiota and health (4 papers), Epigenetics and DNA Methylation (4 papers), MicroRNA in disease regulation (4 papers), CRISPR and Genetic Engineering (4 papers), Ubiquitin and proteasome pathways (3 papers) and Biosensors and Analytical Detection (3 papers). The work is most often cited by research in Cancer Research (240 citations), Molecular Biology (1.0k citations), Pharmacology (234 citations), Immunology (165 citations) and Oncology (172 citations). Kai Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Christopher D. Reeves, Leonard Katz, Loleta Chung, W. Peter Revill, Laurence A. Lasky, Lin Zhang, Haimei Chen, Yanshu Qu, Jian Li and Donald Dowbenko. Their work appears in journals such as European Radiology, Gene, Malaria Journal, Molecular and Cellular Biochemistry and Scientific Reports.
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.