Yefei Wang
Impact in
- Biotechnology top 10%
- Enzyme Production and Characterization
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- MicroRNA in disease regulation
Papers in
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- Protein Structure and Dynamics 12
- Microbial Metabolic Engineering and Bioproduction 4
- Co-authors
- Lishan Yao (24 shared papers)Yuan Deng (1 shared paper)Xiaoping Bi (1 shared paper)Huifang Zhou (1 shared paper)Xianqun Fan (1 shared paper)Ping Gu (1 shared paper)Yamin Hu (1 shared paper)Xiangfei Song (8 shared papers)
- Journals
- Journal of the American Chemical Society (3 papers)Journal of Chemical Information and Modeling (3 papers)Biotechnology and Bioengineering (2 papers)Applied Optics (2 papers)International Journal of Molecular Sciences (2 papers)
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Yefei Wang
37 papers receiving 502 citations
Peers
Comparison fields: 5 of 97
- Biotechnology 68
- Cancer Research 88
- Molecular Biology 274
- Computer Vision and Pattern Recognition 66
- Biophysics 18
Countries citing papers authored by Yefei Wang
This map shows the geographic impact of Yefei Wang'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 Yefei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yefei Wang more than expected).
Fields of papers citing papers by Yefei Wang
This network shows the impact of papers produced by Yefei Wang. 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 Yefei Wang. The network helps show where Yefei Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yefei Wang, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 133 | |
| 2 | 2018 | 47 | |
| 3 | 2020 | 32 | |
| 4 | 2016 | 31 | |
| 5 | 2013 | 30 | |
| 6 | 2018 | 26 | |
| 7 | 2020 | 23 | |
| 8 | 2017 | 20 | |
| 9 | 2014 | 17 | |
| 10 | 2014 | 14 | |
| 11 | 2017 | 13 | |
| 12 | 2019 | 13 | |
| 13 | 2014 | 12 | |
| 14 | 2017 | 11 | |
| 15 | 2020 | 10 | |
| 16 | 2016 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2022 | 7 | |
| 19 | 2015 | 7 | |
| 20 | 2022 | 6 |
About Yefei Wang
Yefei Wang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Biomedical Engineering, Materials Chemistry and Spectroscopy, having authored 38 papers that have together received 512 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (12 papers), Biofuel production and bioconversion (7 papers), Enzyme Structure and Function (7 papers), Molecular spectroscopy and chirality (4 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), Advanced Cellulose Research Studies (4 papers), Advanced NMR Techniques and Applications (3 papers) and Polysaccharides and Plant Cell Walls (3 papers). The work is most often cited by research in Biotechnology (68 citations), Cancer Research (88 citations), Molecular Biology (274 citations), Computer Vision and Pattern Recognition (66 citations) and Biophysics (18 citations). Yefei Wang has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Lishan Yao, Yuan Deng, Xiaoping Bi, Huifang Zhou, Xianqun Fan, Ping Gu, Yamin Hu, Xiangfei Song, Dong Liu and Jingfei Chen. Their work appears in journals such as Journal of the American Chemical Society, Journal of Chemical Information and Modeling, Biotechnology and Bioengineering, Applied Optics and International Journal of Molecular Sciences.
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.