Yuqing Pan
Impact in
- Computational Mathematics top 5%
- Tensor decomposition and applications
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
Papers in
-
- Nanoplatforms for cancer theranostics 9
-
- Machine Learning and Data Classification 3
- Co-authors
- Qing Mai (4 shared papers)Xiangdong Xue (10 shared papers)C.T. Ng (3 shared papers)Chaochao Gao (2 shared papers)Haijing Qu (9 shared papers)Wei Cheng (7 shared papers)Han Chen (7 shared papers)Ciwei Dong (2 shared papers)
- Journals
- ACS Nano (3 papers)Nano Research (2 papers)Acta Biomaterialia (2 papers)Journal of the American Statistical Association (2 papers)Frontiers in Pharmacology (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yuqing Pan
43 papers receiving 541 citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Computational Mathematics 38
- Molecular Medicine 70
- Software 20
- Space and Planetary Science 6
- Endocrinology 19
Countries citing papers authored by Yuqing Pan
This map shows the geographic impact of Yuqing Pan'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 Yuqing Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuqing Pan more than expected).
Fields of papers citing papers by Yuqing Pan
This network shows the impact of papers produced by Yuqing Pan. 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 Yuqing Pan. The network helps show where Yuqing Pan may publish in the future.
Co-authors
The 25 scholars most cited alongside Yuqing Pan, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Carbapenem-resistant Klebsiella pneumoniae capsular types, antibiotic resistance and virulence factors in China: a longitudinal, multi-centre study Hit paper breakdown → | 2024 | 72 |
| 2 | 2023 | 51 | |
| 3 | 2018 | 43 | |
| 4 | 2023 | 38 | |
| 5 | 2014 | 31 | |
| 6 | 2024 | 27 | |
| 7 | 2021 | 23 | |
| 8 | 2022 | 19 | |
| 9 | 2023 | 18 | |
| 10 | 2024 | 17 | |
| 11 | 2023 | 16 | |
| 12 | 2021 | 15 | |
| 13 | 2024 | 14 | |
| 14 | 2021 | 13 | |
| 15 | 2021 | 12 | |
| 16 | 2017 | 10 | |
| 17 | 2020 | 10 | |
| 18 | 2024 | 9 | |
| 19 | 2022 | 9 | |
| 20 | 2023 | 9 |
About Yuqing Pan
Yuqing Pan is a scholar working on Biomedical Engineering, Artificial Intelligence, Biomaterials, Information Systems and Epidemiology, having authored 47 papers that have together received 552 indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (9 papers), Nanoparticle-Based Drug Delivery (5 papers), Photodynamic Therapy Research Studies (3 papers), Machine Learning and Data Classification (3 papers), Advanced Nanomaterials in Catalysis (3 papers), Antibiotic Resistance in Bacteria (3 papers), COVID-19 epidemiological studies (3 papers) and Atmospheric and Environmental Gas Dynamics (2 papers). The work is most often cited by research in Computational Mathematics (38 citations), Molecular Medicine (70 citations), Software (20 citations), Space and Planetary Science (6 citations) and Endocrinology (19 citations). Yuqing Pan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Qing Mai, Xiangdong Xue, C.T. Ng, Chaochao Gao, Haijing Qu, Wei Cheng, Han Chen, Ciwei Dong, Renjun Liu and Yiyang Hu. Their work appears in journals such as ACS Nano, Nano Research, Acta Biomaterialia, Journal of the American Statistical Association and Frontiers in Pharmacology.
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.