Jun Su
Impact in
- Genetics top 10%
- Glioma Diagnosis and Treatment
-
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
Papers in
- Epidemiology 10
- Meningioma and schwannoma management 7
- Co-authors
- Qing Liu (7 shared papers)Gang Peng (4 shared papers)Xianrui Yuan (6 shared papers)Dingkun Gui (3 shared papers)Haoyu Li (5 shared papers)Kai Xiao (6 shared papers)Chaoying Qin (8 shared papers)Zijin Zhao (4 shared papers)
- Journals
- Frontiers in Oncology (4 papers)Cancer Cell International (2 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)Molecular and Cellular Biochemistry (1 paper)European Journal of Medicinal Chemistry (1 paper)
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Jun Su
42 papers receiving 628 citations
Peers
Comparison fields: 5 of 74
- Genetics 98
- Cancer Research 133
- Oncology 101
- Molecular Biology 264
- Nephrology 25
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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 66 | |
| 2 | 2021 | 54 | |
| 3 | 2015 | 50 | |
| 4 | 2015 | 47 | |
| 5 | 2012 | 37 | |
| 6 | 2014 | 31 | |
| 7 | 2022 | 27 | |
| 8 | 2019 | 27 | |
| 9 | 2020 | 26 | |
| 10 | 2018 | 24 | |
| 11 | 2020 | 20 | |
| 12 | 2017 | 19 | |
| 13 | 2015 | 19 | |
| 14 | 2020 | 17 | |
| 15 | 2020 | 16 | |
| 16 | 2019 | 16 | |
| 17 | 2021 | 16 | |
| 18 | 2023 | 16 | |
| 19 | 2018 | 14 | |
| 20 | Pituitary adenylate cyclase-activating polypeptide ameliorates radiation-induced cardiac injury. | 2019 | 13 |
About Jun Su
Jun Su is a scholar working on Molecular Biology, Epidemiology, Cancer Research, Genetics and Cardiology and Cardiovascular Medicine, having authored 45 papers that have together received 632 indexed citations. Recurring topics across this work include Meningioma and schwannoma management (7 papers), Glioma Diagnosis and Treatment (6 papers), Cancer-related molecular mechanisms research (4 papers), Chemotherapy-induced cardiotoxicity and mitigation (4 papers), Ferroptosis and cancer prognosis (3 papers), Chronic Kidney Disease and Diabetes (2 papers), Neurofibromatosis and Schwannoma Cases (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Genetics (98 citations), Cancer Research (133 citations), Oncology (101 citations), Molecular Biology (264 citations) and Nephrology (25 citations). Jun Su has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Qing Liu, Qing Liu, Gang Peng, Xianrui Yuan, Dingkun Gui, Haoyu Li, Kai Xiao, Chaoying Qin, Zijin Zhao and Jian Yuan. Their work appears in journals such as Frontiers in Oncology, Cancer Cell International, International Journal of Radiation Oncology*Biology*Physics, Molecular and Cellular Biochemistry and European Journal of Medicinal Chemistry.
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.