Fei Wu

1.8k citations
79 papers · 1.3k · h-index 21

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Health top 10%
    • Vaccine Coverage and Hesitancy

Papers in

Fei Wu

76 papers receiving 1.3k citations

Peers

Fei Wu
Comparison fields: 5 of 133
  • Cancer Research 298
  • Health 71
  • Molecular Biology 526
  • Cellular and Molecular Neuroscience 138
  • Neurology 53
Replace Kai Zhao with:
Kai Zhao China
Luis G. Guijarro Spain
Roberta Galeazzi Italy
Yuling Zhang China
Shepherd H. Schurman United States
Zhiwen Li China
Armita Mahdavi Gorabi Iran
Andrea L. Nestor‐Kalinoski United States
Yōko Takahashi Japan
Fanghua Gong China
Fei Wu relative to Kai Zhao China Kai Zhao's profile →
Citations per field
00.5×3.5×
Kai Zhao · 1×
Citations per year

Countries citing papers authored by Fei Wu

Since Specialization
Citations

This map shows the geographic impact of Fei 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 Fei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Wu more than expected).

Fields of papers citing papers by Fei Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei 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 Fei Wu. The network helps show where Fei Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Fei 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 Fei Wu Line = papers co-authored together Fei Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009108
2 201871
3 201854
4 201751
5 201345
6 202041
7 201640
8 201940
9 201738
10 202237
11 202232
12 200332
13 202131
14 202130
15 200830
16 201829
17
BQ-869, a novel NMDA receptor antagonist, protects against excitotoxicity and attenuates cerebral ischemic injury in stroke.
201526
18 201926
19 201723
20 202023

About Fei Wu

Fei Wu is a scholar working on Molecular Biology, Surgery, Cancer Research, Infectious Diseases and Epidemiology, having authored 79 papers that have together received 1.3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (9 papers), Circular RNAs in diseases (6 papers), Estrogen and related hormone effects (5 papers), Influenza Virus Research Studies (5 papers), Nerve injury and regeneration (4 papers), Apelin-related biomedical research (4 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Cancer Research (298 citations), Health (71 citations), Molecular Biology (526 citations), Cellular and Molecular Neuroscience (138 citations) and Neurology (53 citations). Fei Wu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Stephen Safe, Zhibo Sun, Bo Bai, Minyi Zhang, Baohua Cheng, Jian Qiu, Yili Wu, Zejin Ou, Qiushuang Li and Huan He. Their work appears in journals such as Cell Biology International, International Journal of Oncology, BMC Public Health, The Journal of Steroid Biochemistry and Molecular Biology and Vaccines.

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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