Jun Pan
Impact in
- Genetics top 2%
- Glioma Diagnosis and Treatment
-
- Pituitary Gland Disorders and Treatments
- Growth Hormone and Insulin-like Growth Factors
Papers in ⓘ
-
- Pituitary Gland Disorders and Treatments 42
- Growth Hormone and Insulin-like Growth Factors 14
- Surgery 39
- Pancreatitis Pathology and Treatment 12
- Head and Neck Surgical Oncology 11
- Co-authors
- Songtao Qi (56 shared papers)Yuntao Lu (18 shared papers)Jun Fan (23 shared papers)Junxiang Peng (24 shared papers)Jiejun Wang (7 shared papers)Liang‐Hao Hu (15 shared papers)Xian Zhang (5 shared papers)Lei Xin (9 shared papers)
- Journals
- Journal of neurosurgery (7 papers)Clinical Neurology and Neurosurgery (3 papers)Acta Neurochirurgica (3 papers)Journal of Neuro-Oncology (2 papers)Neuroreport (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Pan
137 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 148
- Genetics 471
- Endocrinology, Diabetes and Metabolism 634
- Cancer Research 395
- Oncology 458
- Surgery 708
Countries citing papers authored by Jun Pan
This map shows the geographic impact of Jun 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 Jun Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Pan more than expected).
Fields of papers citing papers by Jun Pan
This network shows the impact of papers produced by Jun 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 Jun Pan. The network helps show where Jun Pan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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 145 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 135 | |
| 2 | 2021 | 120 | |
| 3 | 2016 | 117 | |
| 4 | 2019 | 108 | |
| 5 | 2019 | 107 | |
| 6 | 2017 | 83 | |
| 7 | 2015 | 74 | |
| 8 | 2022 | 70 | |
| 9 | 2011 | 63 | |
| 10 | 2012 | 61 | |
| 11 | 2008 | 60 | |
| 12 | 2007 | 59 | |
| 13 | 2011 | 59 | |
| 14 | 2020 | 59 | |
| 15 | 2012 | 55 | |
| 16 | 2015 | 52 | |
| 17 | 2015 | 52 | |
| 18 | 2012 | 48 | |
| 19 | 2016 | 47 | |
| 20 | 2010 | 41 |
About Jun Pan
Jun Pan is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Molecular Biology, Genetics and Epidemiology, having authored 145 papers that have together received 2.7k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (42 papers), Glioma Diagnosis and Treatment (22 papers), Growth Hormone and Insulin-like Growth Factors (14 papers), Pancreatitis Pathology and Treatment (12 papers), Meningioma and schwannoma management (11 papers), Head and Neck Surgical Oncology (11 papers), Pancreatic and Hepatic Oncology Research (9 papers) and Cancer, Hypoxia, and Metabolism (6 papers). The work is most often cited by research in Genetics (471 citations), Endocrinology, Diabetes and Metabolism (634 citations), Cancer Research (395 citations), Oncology (458 citations) and Surgery (708 citations). Jun Pan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Songtao Qi, Yuntao Lu, Jun Fan, Junxiang Peng, Jiejun Wang, Liang‐Hao Hu, Xian Zhang, Lei Xin, Yawei Liu and Silky Chotai. Their work appears in journals such as Journal of neurosurgery, Clinical Neurology and Neurosurgery, Acta Neurochirurgica, Journal of Neuro-Oncology and Neuroreport.
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.