Fang Ye
- Biophysics top 0.5%
- Molecular Biology top 1%
- Receptor Mechanisms and Signaling 62
- Advanced Biosensing Techniques and Applications 30
- Advanced biosensing and bioanalysis techniques 23
- DNA and Nucleic Acid Chemistry 14
- RNA Interference and Gene Delivery 12
- Lipid Membrane Structure and Behavior 11
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- Neuropeptides and Animal Physiology 14
- Biomedical Engineering top 1%
- Immunology top 5%
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- Monoclonal and Polyclonal Antibodies Research 38
- Co-authors
- Richard M. EglenAnn M. FerrieHuayun DengJan H. HohJie YangJoydeep LahiriAnthony G. FrutosN. H. Fontaine
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Fang Ye
368 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 186
- Biophysics 375
- Molecular Biology 4.5k
- Cellular and Molecular Neuroscience 744
- Biomedical Engineering 1.7k
- Immunology 740
Countries citing papers authored by Fang Ye
This map shows the geographic impact of Fang 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 Fang Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang Ye more than expected).
Fields of papers citing papers by Fang Ye
This network shows the impact of papers produced by Fang 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 Fang Ye. The network helps show where Fang Ye may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fang 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 11 | |
| 10 | 2023 | 20 | |
| 11 | 2023 | 5 | |
| 12 | 2022 | 110 | |
| 13 | 2020 | 46 | |
| 14 | 2018 | 28 | |
| 15 | 2015 | 101 | |
| 16 | Comparative Study on the Content of Effective Components of Bupleurum marginatum before and after Processing | 2013 | 1 |
| 17 | An Inventory Model with Non-linear Holding Cost for a Supply Chain of Perishable Goods | 2013 | 2 |
| 18 | 2011 | 20 | |
| 19 | 2008 | 46 | |
| 20 | 2006 | 158 |
About Fang Ye
Fang Ye is a scholar working on Molecular Biology, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 388 papers that have together received 8.7k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (62 papers), Monoclonal and Polyclonal Antibodies Research (38 papers), Advanced Biosensing Techniques and Applications (30 papers), Advanced biosensing and bioanalysis techniques (23 papers), Neuropeptides and Animal Physiology (14 papers), DNA and Nucleic Acid Chemistry (14 papers), RNA Interference and Gene Delivery (12 papers) and Lipid Membrane Structure and Behavior (11 papers). The work is most often cited by research in Biophysics (375 citations), Molecular Biology (4.5k citations) and Cellular and Molecular Neuroscience (744 citations). Fang Ye has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Richard M. Eglen, Ann M. Ferrie, Huayun Deng, Jan H. Hoh, Jie Yang, Joydeep Lahiri, Anthony G. Frutos, N. H. Fontaine, Guangshan Li and Haiyan Sun. Their work appears in journals such as Applied Physics Letters, PLoS ONE, Analytical Chemistry, Scientific Reports and FEBS Letters.
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.