Fei Ye
Impact in
- Cancer Research top 1%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Cancer, Lipids, and Metabolism
- Cancer Genomics and Diagnostics
- Oncology top 1%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
-
- RNA modifications and cancer 10
- Circular RNAs in diseases 8
- Gene expression and cancer classification 7
- Oncology 55
- Cancer Immunotherapy and Biomarkers 17
- CAR-T cell therapy research 8
- Co-authors
- Yu Shyr (29 shared papers)Douglas B. Johnson (25 shared papers)Yan Guo (19 shared papers)Shilin Zhao (12 shared papers)Quanhu Sheng (13 shared papers)David C. Samuels (7 shared papers)Daniel Wang (5 shared papers)Run Fan (17 shared papers)
- Journals
- Cancer Research (8 papers)PLoS ONE (5 papers)Cancer Immunology Research (5 papers)The Oncologist (5 papers)International Journal of Cancer (5 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Fei Ye
203 papers receiving 5.5k citations
Peers
Comparison fields: 5 of 157
- Cancer Research 1.0k
- Oncology 1.4k
- Molecular Biology 2.1k
- Immunology 422
- Pulmonary and Respiratory Medicine 562
Countries citing papers authored by Fei Ye
This map shows the geographic impact of Fei Ye'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 Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Ye more than expected).
Fields of papers citing papers by Fei Ye
This network shows the impact of papers produced by Fei Ye. 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 Ye. The network helps show where Fei Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Fei Ye, 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 211 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 165 | |
| 2 | 2021 | 159 | |
| 3 | 2013 | 155 | |
| 4 | 2010 | 144 | |
| 5 | 2011 | 131 | |
| 6 | 2017 | 106 | |
| 7 | 2011 | 100 | |
| 8 | 2021 | 98 | |
| 9 | 2013 | 96 | |
| 10 | 2011 | 90 | |
| 11 | 2016 | 88 | |
| 12 | 2019 | 88 | |
| 13 | 2015 | 84 | |
| 14 | 2015 | 81 | |
| 15 | 2015 | 79 | |
| 16 | 2007 | 79 | |
| 17 | 2012 | 78 | |
| 18 | 2010 | 76 | |
| 19 | 2016 | 75 | |
| 20 | 2020 | 74 |
About Fei Ye
Fei Ye is a scholar working on Molecular Biology, Oncology, Cancer Research, Genetics and Pulmonary and Respiratory Medicine, having authored 211 papers that have together received 5.6k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (19 papers), Cancer Immunotherapy and Biomarkers (17 papers), MicroRNA in disease regulation (10 papers), RNA modifications and cancer (10 papers), Cancer Genomics and Diagnostics (9 papers), Circular RNAs in diseases (8 papers), CAR-T cell therapy research (8 papers) and Gene expression and cancer classification (7 papers). The work is most often cited by research in Cancer Research (1.0k citations), Oncology (1.4k citations), Molecular Biology (2.1k citations), Immunology (422 citations) and Pulmonary and Respiratory Medicine (562 citations). Fei Ye has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Yu Shyr, Douglas B. Johnson, Yan Guo, Shilin Zhao, Quanhu Sheng, David C. Samuels, Daniel Wang, Run Fan, Elizabeth J. Davis and Jiang Li. Their work appears in journals such as Cancer Research, PLoS ONE, Cancer Immunology Research, The Oncologist and International Journal of Cancer.
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.