Kai Wu

2.4k citations
103 papers · 1.8k · h-index 23

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Genomics and Phylogenetic Studies
    • Plant biochemistry and biosynthesis
    • RNA modifications and cancer
    • Protein Tyrosine Phosphatases

Papers in

Kai Wu

100 papers receiving 1.8k citations

Peers

Kai Wu
Comparison fields: 5 of 120
  • Cancer Research 233
  • Molecular Biology 987
  • Pharmacology 229
  • Immunology 157
  • Oncology 169
Replace In Kwon Chung with:
In Kwon Chung South Korea
Do‐Young Choi South Korea
Yuan Tian China
Yue Zhou China
Jong‐Young Kwak South Korea
Deborah E. Geiman United States
Sang Sun Kang South Korea
Osamu Takeda Japan
Wenjun Zhou China
Kai Wu relative to In Kwon Chung South Korea In Kwon Chung's profile →
Citations per field
00.5×6.7×
In Kwon Chung · 1×
Citations per year

Countries citing papers authored by Kai Wu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Kai Wu Line = papers co-authored together Kai Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000222
2 199778
3 199676
4 202271
5 201866
6 201059
7 202353
8 200949
9 201445
10 201039
11 201536
12 201935
13 201935
14 202032
15 202329
16 201728
17 201726
18 201724
19 201923
20
Irisin attenuates H2O2-induced apoptosis in cardiomyocytes via microRNA-19b/AKT/mTOR signaling pathway.
201723

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 103 papers that have together received 1.8k indexed citations. Recurring topics across this work include Malaria Research and Control (14 papers), Gut microbiota and health (4 papers), Epigenetics and DNA Methylation (4 papers), MicroRNA in disease regulation (4 papers), Mosquito-borne diseases and control (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 (233 citations), Molecular Biology (987 citations), Pharmacology (229 citations), Immunology (157 citations) and Oncology (169 citations). Kai Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Christopher D. Reeves, Leonard Katz, W. Peter Revill, Loleta Chung, Laurence A. Lasky, Lin Zhang, Yanshu Qu, Haimei Chen, Jian Li and Song Wu. Their work appears in journals such as European Radiology, Gene, Malaria Journal, International Journal of Molecular Sciences and Insights into Imaging.

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.

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