Feiyan Ai
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- Immune cells in cancer
Papers in
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- Circular RNAs in diseases 4
- S100 Proteins and Annexins 3
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- MicroRNA in disease regulation 6
- Cancer-related molecular mechanisms research 4
- Co-authors
- Shourong Shen (13 shared papers)Li Tian (10 shared papers)Xiayu Li (11 shared papers)Jian Ma (10 shared papers)Xiaoyan Wang (9 shared papers)Guiyuan Li (7 shared papers)Anliu Tang (8 shared papers)Tian Li (3 shared papers)
- Journals
- Oncotarget (2 papers)Journal of Cancer (2 papers)Frontiers in Immunology (2 papers)Cancer Letters (1 paper)BMC Gastroenterology (1 paper)
- Partner nations
- ChinaSaudi ArabiaEthiopia
In The Last Decade
Feiyan Ai
25 papers receiving 727 citations
Peers
Comparison fields: 5 of 80
- Cancer Research 289
- Immunology 121
- Molecular Biology 390
- Oncology 119
- Epidemiology 74
Countries citing papers authored by Feiyan Ai
This map shows the geographic impact of Feiyan Ai'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 Feiyan Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feiyan Ai more than expected).
Fields of papers citing papers by Feiyan Ai
This network shows the impact of papers produced by Feiyan Ai. 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 Feiyan Ai. The network helps show where Feiyan Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Feiyan Ai, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 85 | |
| 2 | 2017 | 75 | |
| 3 | 2015 | 74 | |
| 4 | 2017 | 67 | |
| 5 | 2014 | 45 | |
| 6 | 2015 | 44 | |
| 7 | 2017 | 43 | |
| 8 | 2016 | 37 | |
| 9 | 2014 | 33 | |
| 10 | 2023 | 32 | |
| 11 | 2013 | 31 | |
| 12 | 2017 | 30 | |
| 13 | 2015 | 22 | |
| 14 | 2022 | 21 | |
| 15 | 2024 | 19 | |
| 16 | 2016 | 15 | |
| 17 | 2023 | 14 | |
| 18 | 2017 | 13 | |
| 19 | 2024 | 8 | |
| 20 | 2018 | 6 |
About Feiyan Ai
Feiyan Ai is a scholar working on Molecular Biology, Cancer Research, Immunology, Surgery and Oncology, having authored 26 papers that have together received 731 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (6 papers), Circular RNAs in diseases (4 papers), Cancer-related molecular mechanisms research (4 papers), Inflammatory Bowel Disease (4 papers), S100 Proteins and Annexins (3 papers), Immune Response and Inflammation (3 papers), Biomarkers in Disease Mechanisms (2 papers) and Immune cells in cancer (2 papers). The work is most often cited by research in Cancer Research (289 citations), Immunology (121 citations), Molecular Biology (390 citations), Oncology (119 citations) and Epidemiology (74 citations). Feiyan Ai has collaborated with scholars based in China, Saudi Arabia and Ethiopia. Frequent co-authors include Shourong Shen, Li Tian, Xiayu Li, Jian Ma, Xiaoyan Wang, Guiyuan Li, Anliu Tang, Tian Li, Fen Liu and Xuemei Zhang. Their work appears in journals such as Oncotarget, Journal of Cancer, Frontiers in Immunology, Cancer Letters and BMC Gastroenterology.
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.