Fu Chen
Impact in
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- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- vaccines and immunoinformatics approaches
- DNA and Nucleic Acid Chemistry
Papers in
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- Protein Structure and Dynamics 7
- bioluminescence and chemiluminescence research 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Tingjun Hou (11 shared papers)Huiyong Sun (10 shared papers)Peichen Pan (3 shared papers)Youyong Li (4 shared papers)Dan Li (5 shared papers)Zhe Wang (4 shared papers)Hui Liu (2 shared papers)Feng Zhu (4 shared papers)
In The Last Decade
Fu Chen
26 papers receiving 1.4k citations
Fu Chen's Hit Papers
Peers
Comparison fields: 5 of 143
- Computational Theory and Mathematics 376
- Molecular Biology 882
- Infectious Diseases 165
- Virology 25
- Toxicology 17
Countries citing papers authored by Fu Chen
This map shows the geographic impact of Fu Chen'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 Fu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fu Chen more than expected).
Fields of papers citing papers by Fu Chen
This network shows the impact of papers produced by Fu Chen. 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 Fu Chen. The network helps show where Fu Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Fu Chen, 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 | Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking Hit paper breakdown → | 2016 | 374 |
| 2 | 2018 | 261 | |
| 3 | 2019 | 109 | |
| 4 | 2019 | 99 | |
| 5 | 2017 | 98 | |
| 6 | 2018 | 97 | |
| 7 | 2017 | 63 | |
| 8 | 2017 | 53 | |
| 9 | 2023 | 38 | |
| 10 | 2017 | 29 | |
| 11 | 2018 | 26 | |
| 12 | 2017 | 24 | |
| 13 | 2005 | 24 | |
| 14 | 2016 | 23 | |
| 15 | 2022 | 19 | |
| 16 | 2017 | 15 | |
| 17 | 2016 | 9 | |
| 18 | 2016 | 8 | |
| 19 | 2019 | 8 | |
| 20 | 2018 | 7 |
About Fu Chen
Fu Chen is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pathology and Forensic Medicine, Oncology and Materials Chemistry, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Computational Drug Discovery Methods (7 papers), Enzyme Structure and Function (4 papers), bioluminescence and chemiluminescence research (2 papers), Electrospun Nanofibers in Biomedical Applications (2 papers), Lymphoma Diagnosis and Treatment (2 papers), Lung Cancer Research Studies (2 papers) and Head and Neck Cancer Studies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (376 citations), Molecular Biology (882 citations), Infectious Diseases (165 citations), Virology (25 citations) and Toxicology (17 citations). Fu Chen has collaborated with scholars based in China, Czechia and Sweden. Frequent co-authors include Tingjun Hou, Huiyong Sun, Peichen Pan, Youyong Li, Dan Li, Zhe Wang, Hui Liu, Feng Zhu, Gaoqi Weng and Ercheng Wang. Their work appears in journals such as Physical Chemistry Chemical Physics, RSC Advances, Journal of Cheminformatics, Colloids and Surfaces A Physicochemical and Engineering Aspects and Molecular Pharmaceutics.
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.