Fei Yan
Impact in
- Biomaterials top 1%
- Nanoparticle-Based Drug Delivery
- Cancer Research top 5%
- Cancer, Lipids, and Metabolism
Papers in
-
- Nanoplatforms for cancer theranostics 32
- Biomaterials 14
- Nanoparticle-Based Drug Delivery 13
- Co-authors
- Shujun Liu (15 shared papers)Yangyang Du (16 shared papers)Shouhua Feng (18 shared papers)Meiyu Song (9 shared papers)Zhan Shi (15 shared papers)Jiuxia Pang (10 shared papers)Na Shen (12 shared papers)Xinguo Hou (19 shared papers)
- Journals
- Acta Biomaterialia (7 papers)Chemical Engineering Journal (5 papers)PLoS ONE (4 papers)ACS Nano (4 papers)Analytical Chemistry (4 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Fei Yan
202 papers receiving 5.9k citations
Peers
Comparison fields: 5 of 129
- Biomaterials 658
- Cancer Research 402
- Biomedical Engineering 924
- Immunology 452
- Molecular Biology 1.2k
Countries citing papers authored by Fei Yan
This map shows the geographic impact of Fei Yan'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 Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Yan more than expected).
Fields of papers citing papers by Fei Yan
This network shows the impact of papers produced by Fei Yan. 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 Yan. The network helps show where Fei Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Fei Yan, 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 209 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 204 | |
| 2 | 2018 | 180 | |
| 3 | 2021 | 173 | |
| 4 | 2015 | 136 | |
| 5 | 2018 | 133 | |
| 6 | 2020 | 129 | |
| 7 | 2018 | 126 | |
| 8 | 2020 | 122 | |
| 9 | 2014 | 117 | |
| 10 | 2020 | 107 | |
| 11 | 2020 | 103 | |
| 12 | 2021 | 98 | |
| 13 | 2018 | 97 | |
| 14 | 2020 | 95 | |
| 15 | 2019 | 92 | |
| 16 | 2023 | 91 | |
| 17 | 2021 | 86 | |
| 18 | 2022 | 84 | |
| 19 | 2022 | 82 | |
| 20 | 2012 | 81 |
About Fei Yan
Fei Yan is a scholar working on Biomedical Engineering, Biomaterials, Nephrology, Spectroscopy and Molecular Biology, having authored 209 papers that have together received 5.9k indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (32 papers), Nanoparticle-Based Drug Delivery (13 papers), Molecular Sensors and Ion Detection (13 papers), Acute Myeloid Leukemia Research (9 papers), Chronic Kidney Disease and Diabetes (9 papers), Pancreatic function and diabetes (7 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers) and Redox biology and oxidative stress (6 papers). The work is most often cited by research in Biomaterials (658 citations), Cancer Research (402 citations), Biomedical Engineering (924 citations), Immunology (452 citations) and Molecular Biology (1.2k citations). Fei Yan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Shujun Liu, Yangyang Du, Shouhua Feng, Meiyu Song, Zhan Shi, Jiuxia Pang, Na Shen, Xinguo Hou, Kunxia Cao and Mark Robert Litzow. Their work appears in journals such as Acta Biomaterialia, Chemical Engineering Journal, PLoS ONE, ACS Nano and Analytical Chemistry.
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.