Yangjun Wu
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Cancer, Hypoxia, and Metabolism
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- RNA modifications and cancer
- RNA Research and Splicing
- Circular RNAs in diseases
- RNA and protein synthesis mechanisms
Papers in
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- RNA modifications and cancer 7
- RNA Research and Splicing 5
- Circular RNAs in diseases 3
- Epigenetics and DNA Methylation 1
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- Cancer-related molecular mechanisms research 9
- Co-authors
- Shenglin Huang (8 shared papers)Linhui Liang (8 shared papers)Lin Huan (6 shared papers)Xianghuo He (8 shared papers)Linguo Xu (4 shared papers)Ye Xu (2 shared papers)Tianan Guo (2 shared papers)Yuqiang Zhou (3 shared papers)
- Journals
- Molecular Cancer (2 papers)Cancer Letters (2 papers)Communications Biology (1 paper)Cell Discovery (1 paper)Nature Communications (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Yangjun Wu
21 papers receiving 570 citations
Peers
Comparison fields: 5 of 67
- Cancer Research 359
- Molecular Biology 385
- Oncology 44
- Immunology 26
- Epidemiology 39
Countries citing papers authored by Yangjun Wu
This map shows the geographic impact of Yangjun 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 Yangjun Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yangjun Wu more than expected).
Fields of papers citing papers by Yangjun Wu
This network shows the impact of papers produced by Yangjun 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 Yangjun Wu. The network helps show where Yangjun Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yangjun 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 127 | |
| 2 | 2020 | 73 | |
| 3 | 2019 | 66 | |
| 4 | 2019 | 60 | |
| 5 | 2019 | 53 | |
| 6 | 2019 | 50 | |
| 7 | 2021 | 23 | |
| 8 | 2022 | 22 | |
| 9 | 2023 | 21 | |
| 10 | 2021 | 17 | |
| 11 | 2022 | 13 | |
| 12 | 2023 | 12 | |
| 13 | 2023 | 10 | |
| 14 | 2024 | 9 | |
| 15 | 2024 | 7 | |
| 16 | 2021 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2023 | 1 | |
| 19 | [Modelling and kinetic analysis on changrolin block of cardiac Na+ channels]. | 1991 | 1 |
| 20 | 2025 | 1 |
About Yangjun Wu
Yangjun Wu is a scholar working on Molecular Biology, Cancer Research, Oncology, Materials Chemistry and Organic Chemistry, having authored 22 papers that have together received 574 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (9 papers), RNA modifications and cancer (7 papers), RNA Research and Splicing (5 papers), Circular RNAs in diseases (3 papers), Machine Learning in Materials Science (2 papers), PARP inhibition in cancer therapy (1 paper), Multimodal Machine Learning Applications (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Cancer Research (359 citations), Molecular Biology (385 citations), Oncology (44 citations), Immunology (26 citations) and Epidemiology (39 citations). Yangjun Wu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Shenglin Huang, Linhui Liang, Lin Huan, Xianghuo He, Linguo Xu, Ye Xu, Tianan Guo, Yuqiang Zhou, Shengli Li and Lu Wang. Their work appears in journals such as Molecular Cancer, Cancer Letters, Communications Biology, Cell Discovery and Nature Communications.
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.