Jun Su
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
- Genetics top 10%
- Glioma Diagnosis and Treatment
Papers in
-
- RNA modifications and cancer 4
- Epidemiology 13
- Meningioma and schwannoma management 10
- Co-authors
- Qing Liu (7 shared papers)Gang Peng (4 shared papers)Xianrui Yuan (6 shared papers)Chaoying Qin (8 shared papers)Kai Xiao (6 shared papers)Dingkun Gui (3 shared papers)Haoyu Li (5 shared papers)Jian Yuan (8 shared papers)
- Journals
- Frontiers in Oncology (4 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)Cancer Cell International (2 papers)Scientific Reports (1 paper)Journal of Neuro-Oncology (1 paper)
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Jun Su
40 papers receiving 597 citations
Peers
Comparison fields: 5 of 76
- Cancer Research 162
- Genetics 110
- Nephrology 34
- Molecular Biology 309
- Oncology 111
Countries citing papers authored by Jun Su
This map shows the geographic impact of Jun Su'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 Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Su more than expected).
Fields of papers citing papers by Jun Su
This network shows the impact of papers produced by Jun Su. 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 Su. The network helps show where Jun Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Su, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 64 | |
| 2 | 2021 | 51 | |
| 3 | 2015 | 50 | |
| 4 | 2015 | 47 | |
| 5 | 2012 | 35 | |
| 6 | 2014 | 30 | |
| 7 | 2019 | 26 | |
| 8 | 2022 | 26 | |
| 9 | 2020 | 25 | |
| 10 | 2018 | 24 | |
| 11 | 2020 | 20 | |
| 12 | 2015 | 18 | |
| 13 | 2017 | 18 | |
| 14 | 2020 | 16 | |
| 15 | 2019 | 15 | |
| 16 | 2020 | 15 | |
| 17 | 2018 | 14 | |
| 18 | 2021 | 14 | |
| 19 | Pituitary adenylate cyclase-activating polypeptide ameliorates radiation-induced cardiac injury. | 2019 | 12 |
| 20 | 2023 | 12 |
About Jun Su
Jun Su is a scholar working on Molecular Biology, Epidemiology, Cancer Research, Genetics and Surgery, having authored 44 papers that have together received 600 indexed citations. Recurring topics across this work include Meningioma and schwannoma management (10 papers), Glioma Diagnosis and Treatment (7 papers), Cancer-related molecular mechanisms research (7 papers), RNA modifications and cancer (4 papers), Head and Neck Surgical Oncology (4 papers), Ferroptosis and cancer prognosis (4 papers), Neurofibromatosis and Schwannoma Cases (4 papers) and Chemotherapy-induced cardiotoxicity and mitigation (4 papers). The work is most often cited by research in Cancer Research (162 citations), Genetics (110 citations), Nephrology (34 citations), Molecular Biology (309 citations) and Oncology (111 citations). Jun Su has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Qing Liu, Gang Peng, Qing Liu, Xianrui Yuan, Chaoying Qin, Kai Xiao, Dingkun Gui, Haoyu Li, Jian Yuan and Zijin Zhao. Their work appears in journals such as Frontiers in Oncology, International Journal of Radiation Oncology*Biology*Physics, Cancer Cell International, Scientific Reports and Journal of Neuro-Oncology.
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.