Jun Dai
Impact in
- Gastroenterology top 1%
- Gastrointestinal Bleeding Diagnosis and Treatment
- Gastrointestinal Tumor Research and Treatment
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
- Surgery 59
- Adrenal and Paraganglionic Tumors 20
- Co-authors
- Michael Pecht (7 shared papers)Diganta Das (7 shared papers)Zhi‐Zheng Ge (14 shared papers)Han Chen (8 shared papers)Fukang Sun (23 shared papers)Zhi Zheng Ge (7 shared papers)Qiurong Ruan (7 shared papers)Hongchao He (10 shared papers)
- Journals
- BMC Musculoskeletal Disorders (3 papers)Gastrointestinal Endoscopy (3 papers)Oncotarget (3 papers)ACS Biomaterials Science & Engineering (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Jun Dai
132 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 172
- Gastroenterology 353
- Cancer Research 374
- Surgery 704
- Reproductive Medicine 102
- Pulmonary and Respiratory Medicine 343
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 145 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 126 | |
| 2 | 2020 | 87 | |
| 3 | 2009 | 74 | |
| 4 | 2022 | 71 | |
| 5 | 2017 | 71 | |
| 6 | 2007 | 70 | |
| 7 | 2020 | 66 | |
| 8 | 2012 | 55 | |
| 9 | 2016 | 54 | |
| 10 | 2012 | 54 | |
| 11 | 2015 | 47 | |
| 12 | 2012 | 46 | |
| 13 | 2018 | 44 | |
| 14 | 2018 | 44 | |
| 15 | 2013 | 43 | |
| 16 | 2013 | 41 | |
| 17 | 2019 | 40 | |
| 18 | 2019 | 40 | |
| 19 | 2019 | 38 | |
| 20 | 2015 | 37 |
About Jun Dai
Jun Dai is a scholar working on Surgery, Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine, having authored 145 papers that have together received 2.5k indexed citations. Recurring topics across this work include Adrenal and Paraganglionic Tumors (20 papers), Spine and Intervertebral Disc Pathology (13 papers), Hormonal Regulation and Hypertension (12 papers), Gastrointestinal Bleeding Diagnosis and Treatment (10 papers), Gastric Cancer Management and Outcomes (10 papers), Pituitary Gland Disorders and Treatments (10 papers), Cancer, Hypoxia, and Metabolism (9 papers) and Cancer-related molecular mechanisms research (9 papers). The work is most often cited by research in Gastroenterology (353 citations), Cancer Research (374 citations), Surgery (704 citations), Reproductive Medicine (102 citations) and Pulmonary and Respiratory Medicine (343 citations). Jun Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Michael Pecht, Diganta Das, Zhi‐Zheng Ge, Han Chen, Fukang Sun, Zhi Zheng Ge, Qiurong Ruan, Hongchao He, Yun–Jie Gao and Juping Zhao. Their work appears in journals such as BMC Musculoskeletal Disorders, Gastrointestinal Endoscopy, Oncotarget, ACS Biomaterials Science & Engineering and Scientific Reports.
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.