Que Bai
Impact in
- Rehabilitation top 1%
- Wound Healing and Treatments
- Biomaterials top 5%
- Electrospun Nanofibers in Biomedical Applications
- Silk-based biomaterials and applications
Papers in
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- Wound Healing and Treatments 14
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- Nanoplatforms for cancer theranostics 7
- Bone Tissue Engineering Materials 3
- Co-authors
- Tingli Lu (20 shared papers)Caiyun Zheng (17 shared papers)Kai Han (5 shared papers)Yanni Zhang (14 shared papers)Wendong Wu (5 shared papers)Jinxi Liu (12 shared papers)Na Sun (3 shared papers)Yanni Zhang (3 shared papers)
In The Last Decade
Que Bai
24 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 90
- Rehabilitation 388
- Biomaterials 373
- Molecular Medicine 93
- Pharmaceutical Science 62
- Biomedical Engineering 367
Countries citing papers authored by Que Bai
This map shows the geographic impact of Que Bai'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 Que Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Que Bai more than expected).
Fields of papers citing papers by Que Bai
This network shows the impact of papers produced by Que Bai. 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 Que Bai. The network helps show where Que Bai may publish in the future.
Co-authors
The 25 scholars most cited alongside Que Bai, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 206 | |
| 2 | 2021 | 140 | |
| 3 | 2022 | 129 | |
| 4 | 2023 | 90 | |
| 5 | 2018 | 56 | |
| 6 | 2022 | 47 | |
| 7 | 2023 | 46 | |
| 8 | 2021 | 46 | |
| 9 | 2022 | 40 | |
| 10 | 2022 | 37 | |
| 11 | 2022 | 34 | |
| 12 | 2018 | 32 | |
| 13 | 2022 | 27 | |
| 14 | 2024 | 25 | |
| 15 | 2022 | 24 | |
| 16 | 2024 | 19 | |
| 17 | 2021 | 19 | |
| 18 | 2022 | 18 | |
| 19 | 2022 | 16 | |
| 20 | 2023 | 11 |
About Que Bai
Que Bai is a scholar working on Rehabilitation, Biomedical Engineering, Biomaterials, Surgery and Molecular Biology, having authored 25 papers that have together received 1.1k indexed citations. Recurring topics across this work include Wound Healing and Treatments (14 papers), Nanoplatforms for cancer theranostics (7 papers), Electrospun Nanofibers in Biomedical Applications (6 papers), Surgical Sutures and Adhesives (3 papers), Hemostasis and retained surgical items (3 papers), Bone Tissue Engineering Materials (3 papers), Diabetic Foot Ulcer Assessment and Management (3 papers) and Silk-based biomaterials and applications (2 papers). The work is most often cited by research in Rehabilitation (388 citations), Biomaterials (373 citations), Molecular Medicine (93 citations), Pharmaceutical Science (62 citations) and Biomedical Engineering (367 citations). Que Bai has collaborated with scholars based in China, Thailand and Singapore. Frequent co-authors include Tingli Lu, Caiyun Zheng, Kai Han, Yanni Zhang, Wendong Wu, Jinxi Liu, Na Sun, Yanni Zhang, Qian Gao and Na Sun. Their work appears in journals such as International Journal of Biological Macromolecules, Frontiers in Plant Science, International Journal of Nanomedicine, Materials & Design and European Journal of Medicinal Chemistry.
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.