Bin Fu
Impact in
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- Glycosylation and Glycoproteins Research
- DNA and Biological Computing
- Advanced biosensing and bioanalysis techniques
- Extracellular vesicles in disease
- Gut microbiota and health
Papers in
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- Glycosylation and Glycoproteins Research 11
- DNA and Biological Computing 3
- Protein Structure and Dynamics 3
- Gut microbiota and health 3
- Advanced biosensing and bioanalysis techniques 3
- Genomics and Phylogenetic Studies 2
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- Advanced Proteomics Techniques and Applications 6
- Co-authors
- Haojie Lu (11 shared papers)Ying Zhang (8 shared papers)Robert Schweller (2 shared papers)Matthew John Patitz (1 shared paper)Zhenyu Sun (3 shared papers)Guoli Wang (2 shared papers)Lei Zhang (1 shared paper)Xuejiao Liu (6 shared papers)
- Journals
- Analytical Chemistry (3 papers)Bioscience Reports (2 papers)Carbohydrate Polymers (2 papers)Nature Communications (2 papers)Physical review. B. (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Bin Fu
31 papers receiving 252 citations
Peers
Comparison fields: 5 of 57
- Molecular Biology 174
- Biological Psychiatry 5
- Nephrology 14
- Spectroscopy 26
- Computational Theory and Mathematics 17
Countries citing papers authored by Bin Fu
This map shows the geographic impact of Bin Fu'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 Bin Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Fu more than expected).
Fields of papers citing papers by Bin Fu
This network shows the impact of papers produced by Bin Fu. 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 Bin Fu. The network helps show where Bin Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Fu, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 35 | |
| 2 | 2022 | 34 | |
| 3 | 2012 | 30 | |
| 4 | 2025 | 30 | |
| 5 | 2022 | 16 | |
| 6 | 2025 | 12 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 9 | |
| 9 | 1997 | 9 | |
| 10 | 2023 | 9 | |
| 11 | 2017 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2020 | 6 | |
| 14 | 2025 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2025 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2008 | 3 | |
| 19 | 2019 | 3 | |
| 20 | 2025 | 3 |
About Bin Fu
Bin Fu is a scholar working on Molecular Biology, Spectroscopy, Immunology, Reproductive Medicine and Food Science, having authored 32 papers that have together received 261 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (11 papers), Advanced Proteomics Techniques and Applications (6 papers), Modular Robots and Swarm Intelligence (3 papers), DNA and Biological Computing (3 papers), Protein Structure and Dynamics (3 papers), Gut microbiota and health (3 papers), Advanced biosensing and bioanalysis techniques (3 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Molecular Biology (174 citations), Biological Psychiatry (5 citations), Nephrology (14 citations), Spectroscopy (26 citations) and Computational Theory and Mathematics (17 citations). Bin Fu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Haojie Lu, Ying Zhang, Robert Schweller, Matthew John Patitz, Zhenyu Sun, Guoli Wang, Lei Zhang, Xuejiao Liu, Richard Beigel and Yuying Liang. Their work appears in journals such as Analytical Chemistry, Bioscience Reports, Carbohydrate Polymers, Nature Communications and Physical review. B..
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.