Jun Dong
Impact in
- Cancer Research top 0.5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
- Genetics top 1%
- Glioma Diagnosis and Treatment
Papers in ⓘ
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- Circular RNAs in diseases 21
- RNA Research and Splicing 14
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- MicroRNA in disease regulation 38
- Cancer, Hypoxia, and Metabolism 22
- Cancer-related molecular mechanisms research 22
- Co-authors
- Steve Horvath (6 shared papers)Qiang Huang (50 shared papers)Stanley F. Nelson (6 shared papers)Timothy F. Cloughesy (5 shared papers)Albert Lai (5 shared papers)Paul S. Mischel (5 shared papers)Linda M. Liau (5 shared papers)Qing Lan (8 shared papers)
- Journals
- Frontiers in Oncology (7 papers)CNS Neuroscience & Therapeutics (6 papers)Journal of Cancer (5 papers)Aging (5 papers)PLoS ONE (5 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Dong
199 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Cancer Research 1.7k
- Genetics 812
- Molecular Biology 3.1k
- Oncology 810
- Developmental Neuroscience 99
Countries citing papers authored by Jun Dong
This map shows the geographic impact of Jun Dong'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 Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Dong more than expected).
Fields of papers citing papers by Jun Dong
This network shows the impact of papers produced by Jun Dong. 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 Dong. The network helps show where Jun Dong may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Dong, 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 206 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Geometric Interpretation of Gene Coexpression Network Analysis Hit paper breakdown → | 2008 | 622 |
| 2 | 2007 | 335 | |
| 3 | 2010 | 281 | |
| 4 | 2017 | 270 | |
| 5 | 2008 | 165 | |
| 6 | 2008 | 124 | |
| 7 | 2020 | 112 | |
| 8 | 2018 | 110 | |
| 9 | 2019 | 109 | |
| 10 | 2009 | 104 | |
| 11 | 2007 | 96 | |
| 12 | 2020 | 94 | |
| 13 | 2022 | 94 | |
| 14 | 2009 | 81 | |
| 15 | 2008 | 80 | |
| 16 | 2010 | 71 | |
| 17 | 2013 | 70 | |
| 18 | 2019 | 66 | |
| 19 | 2021 | 66 | |
| 20 | 2006 | 62 |
About Jun Dong
Jun Dong is a scholar working on Molecular Biology, Cancer Research, Oncology, Genetics and Pulmonary and Respiratory Medicine, having authored 206 papers that have together received 5.3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (38 papers), Glioma Diagnosis and Treatment (30 papers), Cancer, Hypoxia, and Metabolism (22 papers), Cancer-related molecular mechanisms research (22 papers), Circular RNAs in diseases (21 papers), Cancer Research and Treatments (21 papers), Cancer Cells and Metastasis (19 papers) and RNA Research and Splicing (14 papers). The work is most often cited by research in Cancer Research (1.7k citations), Genetics (812 citations), Molecular Biology (3.1k citations), Oncology (810 citations) and Developmental Neuroscience (99 citations). Jun Dong has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Steve Horvath, Qiang Huang, Stanley F. Nelson, Timothy F. Cloughesy, Albert Lai, Paul S. Mischel, Linda M. Liau, Qing Lan, Faryal Mehwish Awan and William W. Du. Their work appears in journals such as Frontiers in Oncology, CNS Neuroscience & Therapeutics, Journal of Cancer, Aging and PLoS ONE.
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.