Jun Su
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- Rheumatology top 2%
- Systemic Lupus Erythematosus Research
Papers in
- Rheumatology 12
- Systemic Lupus Erythematosus Research 11
- Immunology 11
- Atherosclerosis and Cardiovascular Diseases 10
- Co-authors
- Johan Frostegård (16 shared papers)Ulf dé Fairé (8 shared papers)Erbao Zhang (5 shared papers)Liang Han (4 shared papers)Xuezhi He (4 shared papers)Dandan Yin (3 shared papers)Xiyi Lu (4 shared papers)Wei De (3 shared papers)
In The Last Decade
Jun Su
45 papers receiving 1.7k citations
Jun Su's Hit Papers
Peers
Comparison fields: 5 of 83
- Cancer Research 468
- Rheumatology 334
- Immunology 359
- Oncology 131
- Genetics 42
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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 232 | |
| 2 | 2005 | 153 | |
| 3 | 2010 | 105 | |
| 4 | 2008 | 101 | |
| 5 | 2018 | 99 | |
| 6 | 2009 | 94 | |
| 7 | 2017 | 87 | |
| 8 | 2016 | 80 | |
| 9 | 2008 | 69 | |
| 10 | 2013 | 62 | |
| 11 | 2014 | 61 | |
| 12 | 2019 | 59 | |
| 13 | 2012 | 41 | |
| 14 | NNMT promotes acquired EGFR-TKI resistance by forming EGR1 and lactate-mediated double positive feedback loops in non-small cell lung cancer Hit paper breakdown → | 2025 | 39 |
| 15 | 2017 | 30 | |
| 16 | 2018 | 30 | |
| 17 | 2012 | 28 | |
| 18 | 2013 | 28 | |
| 19 | 2023 | 28 | |
| 20 | 2009 | 27 |
About Jun Su
Jun Su is a scholar working on Rheumatology, Immunology, Cancer Research, Hematology and Genetics, having authored 47 papers that have together received 1.7k indexed citations. Recurring topics across this work include Systemic Lupus Erythematosus Research (11 papers), Atherosclerosis and Cardiovascular Diseases (10 papers), Cancer-related molecular mechanisms research (7 papers), Acute Myeloid Leukemia Research (5 papers), Glioma Diagnosis and Treatment (3 papers), Pituitary Gland Disorders and Treatments (2 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Cancer Research (468 citations), Rheumatology (334 citations), Immunology (359 citations), Oncology (131 citations) and Genetics (42 citations). Jun Su has collaborated with scholars based in China, Sweden and Germany. Frequent co-authors include Johan Frostegård, Ulf dé Fairé, Erbao Zhang, Liang Han, Xuezhi He, Dandan Yin, Xiyi Lu, Wei De, Max Vikström and Ruihua Wu. Their work appears in journals such as Atherosclerosis, PLoS ONE, Cell Death and Disease, Molecular Cancer and International Journal of Molecular 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.