Jun Su
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Immunology top 5%
- Atherosclerosis and Cardiovascular Diseases
- T-cell and B-cell Immunology
Papers in
-
- Circular RNAs in diseases 4
- RNA Research and Splicing 3
- RNA modifications and cancer 3
- Retinoids in leukemia and cellular processes 2
- Immunology 10
- Atherosclerosis and Cardiovascular Diseases 8
- Co-authors
- Johan Frostegård (16 shared papers)Ulf dé Fairé (8 shared papers)Erbao Zhang (5 shared papers)Xuezhi He (4 shared papers)Liang Han (4 shared papers)Dandan Yin (3 shared papers)Hua Xiang (7 shared papers)Xiyi Lu (4 shared papers)
In The Last Decade
Jun Su
42 papers receiving 1.6k citations
Jun Su's Hit Papers
Peers
Comparison fields: 5 of 89
- Cancer Research 485
- Immunology 497
- Rheumatology 235
- Molecular Biology 631
- Immunology and Allergy 36
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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 224 | |
| 2 | 2005 | 148 | |
| 3 | 2010 | 101 | |
| 4 | 2018 | 99 | |
| 5 | 2008 | 98 | |
| 6 | 2009 | 91 | |
| 7 | 2017 | 85 | |
| 8 | 2016 | 76 | |
| 9 | 2008 | 67 | |
| 10 | 2013 | 61 | |
| 11 | 2019 | 58 | |
| 12 | 2014 | 58 | |
| 13 | 2012 | 39 | |
| 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 | 31 |
| 15 | 2018 | 30 | |
| 16 | 2017 | 30 | |
| 17 | 2009 | 27 | |
| 18 | 2013 | 27 | |
| 19 | 2019 | 27 | |
| 20 | 2012 | 26 |
About Jun Su
Jun Su is a scholar working on Molecular Biology, Immunology, Cancer Research, Oncology and Rheumatology, having authored 43 papers that have together received 1.6k indexed citations. Recurring topics across this work include Atherosclerosis and Cardiovascular Diseases (8 papers), Cancer-related molecular mechanisms research (7 papers), Circular RNAs in diseases (4 papers), Acute Myeloid Leukemia Research (4 papers), Systemic Lupus Erythematosus Research (4 papers), RNA Research and Splicing (3 papers), RNA modifications and cancer (3 papers) and Retinoids in leukemia and cellular processes (2 papers). The work is most often cited by research in Cancer Research (485 citations), Immunology (497 citations), Rheumatology (235 citations), Molecular Biology (631 citations) and Immunology and Allergy (36 citations). Jun Su has collaborated with scholars based in China, Sweden and Germany. Frequent co-authors include Johan Frostegård, Ulf dé Fairé, Erbao Zhang, Xuezhi He, Liang Han, Dandan Yin, Hua Xiang, Xiyi Lu, Wei De and Thomas Thulin. Their work appears in journals such as PLoS ONE, Atherosclerosis, Molecular Cancer, Gene 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.