Jun Wu
Impact in
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
- Immunology top 5%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
Papers in
-
- RNA modifications and cancer 9
- Epigenetics and DNA Methylation 6
- Genomics and Chromatin Dynamics 5
- Oncology 30
- Peptidase Inhibition and Analysis 5
- Co-authors
- Bing Li (4 shared papers)Jerry L. Workman (1 shared paper)David G. Motto (1 shared paper)Arthur Weiss (1 shared paper)Gary A. Koretzky (1 shared paper)Yao-Qing Tang (5 shared papers)Enqiang Mao (3 shared papers)Jnanankur Bag (1 shared paper)
- Journals
- The Journal of Immunology (3 papers)Frontiers in Oncology (3 papers)International Journal of Radiation Oncology*Biology*Physics (3 papers)Bioorganic Chemistry (2 papers)Cancer Gene Therapy (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Wu
146 papers receiving 3.5k citations
Peers
Comparison fields: 5 of 144
- Cancer Research 450
- Immunology 566
- Molecular Biology 1.7k
- Oncology 543
- Immunology and Allergy 99
Countries citing papers authored by Jun Wu
This map shows the geographic impact of Jun Wu'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 Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wu more than expected).
Fields of papers citing papers by Jun Wu
This network shows the impact of papers produced by Jun Wu. 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 Wu. The network helps show where Jun Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wu, 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 155 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 436 | |
| 2 | 1996 | 300 | |
| 3 | 2018 | 145 | |
| 4 | 2009 | 139 | |
| 5 | 2008 | 132 | |
| 6 | 2018 | 90 | |
| 7 | 2010 | 84 | |
| 8 | 2009 | 83 | |
| 9 | 2021 | 83 | |
| 10 | 2011 | 67 | |
| 11 | 2012 | 58 | |
| 12 | 2017 | 56 | |
| 13 | 2013 | 52 | |
| 14 | 2008 | 51 | |
| 15 | 2022 | 48 | |
| 16 | 2013 | 46 | |
| 17 | 1996 | 46 | |
| 18 | 2006 | 45 | |
| 19 | 2006 | 44 | |
| 20 | 2007 | 41 |
About Jun Wu
Jun Wu is a scholar working on Molecular Biology, Oncology, Surgery, Pulmonary and Respiratory Medicine and Immunology, having authored 155 papers that have together received 3.5k indexed citations. Recurring topics across this work include RNA modifications and cancer (9 papers), Cancer-related molecular mechanisms research (7 papers), Lipoproteins and Cardiovascular Health (7 papers), Epigenetics and DNA Methylation (6 papers), Peptidase Inhibition and Analysis (5 papers), MicroRNA in disease regulation (5 papers), Genomics and Chromatin Dynamics (5 papers) and Advanced Glycation End Products research (5 papers). The work is most often cited by research in Cancer Research (450 citations), Immunology (566 citations), Molecular Biology (1.7k citations), Oncology (543 citations) and Immunology and Allergy (99 citations). Jun Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Bing Li, Jerry L. Workman, David G. Motto, Arthur Weiss, Gary A. Koretzky, Yao-Qing Tang, Enqiang Mao, Jnanankur Bag, Chul‐Hwan Lee and Guo‐Hui Fu. Their work appears in journals such as The Journal of Immunology, Frontiers in Oncology, International Journal of Radiation Oncology*Biology*Physics, Bioorganic Chemistry and Cancer Gene Therapy.
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.