Jun Dai
Impact in
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- Analytical Chemistry and Sensors
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- Molecular Sensors and Ion Detection
Papers in
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- Nanoplatforms for cancer theranostics 9
- Photoacoustic and Ultrasonic Imaging 2
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- Luminescence and Fluorescent Materials 4
- Advanced Nanomaterials in Catalysis 2
- Co-authors
- Xiaoding Lou (13 shared papers)Fan Xia (11 shared papers)Ming Li (2 shared papers)Yan Huang (2 shared papers)Shixuan Wang (2 shared papers)Zhiyun Lu (2 shared papers)Dan Chen (1 shared paper)Liru Xue (1 shared paper)
- Journals
- Analytical Chemistry (4 papers)European Journal of Nuclear Medicine and Molecular Imaging (2 papers)Nature Communications (1 paper)Journal of Medicinal Chemistry (1 paper)Medicine (1 paper)
- Partner nations
- ChinaUnited StatesPoland
In The Last Decade
Jun Dai
24 papers receiving 221 citations
Jun Dai's Hit Papers
Peers
Comparison fields: 5 of 73
- Bioengineering 16
- Spectroscopy 27
- Materials Chemistry 65
- Economics and Econometrics 36
- Reproductive Medicine 8
Countries citing papers authored by Jun Dai
This map shows the geographic impact of Jun Dai'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 Jun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Dai more than expected).
Fields of papers citing papers by Jun Dai
This network shows the impact of papers produced by Jun Dai. 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 Jun Dai. The network helps show where Jun Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Dai, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Ovarian microenvironment: challenges and opportunities in protecting against chemotherapy-associated ovarian damage Hit paper breakdown → | 2024 | 44 |
| 2 | 2019 | 40 | |
| 3 | 2014 | 25 | |
| 4 | 2012 | 25 | |
| 5 | 2024 | 18 | |
| 6 | 2024 | 11 | |
| 7 | 2023 | 11 | |
| 8 | 2025 | 9 | |
| 9 | 2024 | 7 | |
| 10 | 2024 | 5 | |
| 11 | 2024 | 5 | |
| 12 | 2017 | 5 | |
| 13 | 2024 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2024 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2024 | 1 |
About Jun Dai
Jun Dai is a scholar working on Biomedical Engineering, Materials Chemistry, Molecular Biology, Oncology and Pulmonary and Respiratory Medicine, having authored 28 papers that have together received 223 indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (9 papers), Luminescence and Fluorescent Materials (4 papers), Molecular Sensors and Ion Detection (2 papers), RNA Interference and Gene Delivery (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Selenium in Biological Systems (2 papers), Angiogenesis and VEGF in Cancer (2 papers) and Advanced Nanomaterials in Catalysis (2 papers). The work is most often cited by research in Bioengineering (16 citations), Spectroscopy (27 citations), Materials Chemistry (65 citations), Economics and Econometrics (36 citations) and Reproductive Medicine (8 citations). Jun Dai has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Xiaoding Lou, Fan Xia, Ming Li, Yan Huang, Shixuan Wang, Zhiyun Lu, Dan Chen, Liru Xue, Yun Dai and Weicheng Tang. Their work appears in journals such as Analytical Chemistry, European Journal of Nuclear Medicine and Molecular Imaging, Nature Communications, Journal of Medicinal Chemistry and Medicine.
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.