Fei Mu
Impact in
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- Traditional Chinese Medicine Analysis
- Neurology top 10%
- Neurological Disease Mechanisms and Treatments
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
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- Traditional Chinese Medicine Analysis 13
- Medicinal Plants and Neuroprotection 4
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- Metabolomics and Mass Spectrometry Studies 5
- Co-authors
- Aidong Wen (17 shared papers)Jialin Duan (16 shared papers)Chao Guo (10 shared papers)Yi Ding (9 shared papers)Yue Guan (7 shared papers)Jingwen Wang (17 shared papers)Wei Guo (4 shared papers)Ying Yin (4 shared papers)
In The Last Decade
Fei Mu
44 papers receiving 734 citations
Peers
Comparison fields: 5 of 111
- Complementary and alternative medicine 154
- Neurology 87
- Pharmacology 83
- Molecular Biology 344
- Geriatrics and Gerontology 19
Countries citing papers authored by Fei Mu
This map shows the geographic impact of Fei Mu'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 Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Mu more than expected).
Fields of papers citing papers by Fei Mu
This network shows the impact of papers produced by Fei Mu. 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 Mu. The network helps show where Fei Mu may publish in the future.
Co-authors
The 25 scholars most cited alongside Fei Mu, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 113 | |
| 2 | 2018 | 83 | |
| 3 | 2017 | 46 | |
| 4 | 2017 | 36 | |
| 5 | 2017 | 34 | |
| 6 | 2015 | 32 | |
| 7 | 2018 | 31 | |
| 8 | 2023 | 28 | |
| 9 | 2019 | 28 | |
| 10 | 2022 | 26 | |
| 11 | 2020 | 24 | |
| 12 | 2016 | 24 | |
| 13 | 2018 | 23 | |
| 14 | 2017 | 22 | |
| 15 | 2020 | 21 | |
| 16 | 2018 | 18 | |
| 17 | 2017 | 17 | |
| 18 | 2017 | 12 | |
| 19 | 2020 | 12 | |
| 20 | 2024 | 10 |
About Fei Mu
Fei Mu is a scholar working on Complementary and alternative medicine, Molecular Biology, Pharmacology, Neurology and Epidemiology, having authored 53 papers that have together received 743 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Analysis (13 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers), Neurological Disease Mechanisms and Treatments (5 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Cardiac Ischemia and Reperfusion (4 papers), Pharmacological Effects of Natural Compounds (4 papers), Medicinal Plants and Neuroprotection (4 papers) and Pharmacological Effects of Medicinal Plants (3 papers). The work is most often cited by research in Complementary and alternative medicine (154 citations), Neurology (87 citations), Pharmacology (83 citations), Molecular Biology (344 citations) and Geriatrics and Gerontology (19 citations). Fei Mu has collaborated with scholars based in China and Australia. Frequent co-authors include Aidong Wen, Jialin Duan, Chao Guo, Yi Ding, Yue Guan, Jingwen Wang, Wei Guo, Ying Yin, Miaomiao Xi and Tianlong Liu. Their work appears in journals such as Scientific Reports, Rejuvenation Research, Journal of Ethnopharmacology, Soil and Tillage Research and Frontiers in 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.