Tan Wu
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- RNA modifications and cancer
- Circular RNAs in diseases
- RNA Research and Splicing
- Bioinformatics and Genomic Networks
Papers in
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- RNA Research and Splicing 7
- Bioinformatics and Genomic Networks 3
- Genomics and Chromatin Dynamics 3
- RNA modifications and cancer 3
- Ubiquitin and proteasome pathways 2
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- MicroRNA in disease regulation 4
- Cancer-related molecular mechanisms research 4
- Co-authors
- Yanjun Xu (8 shared papers)Xia Li (6 shared papers)Feng Li (4 shared papers)Yunpeng Zhang (5 shared papers)Zeguo Sun (2 shared papers)Xinrui Shi (1 shared paper)Jing Li (1 shared paper)Xin Wang (7 shared papers)
- Journals
- Oncotarget (4 papers)Briefings in Bioinformatics (2 papers)Frontiers in Genetics (1 paper)Life Science Alliance (1 paper)Trends in Genetics (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Tan Wu
21 papers receiving 346 citations
Peers
Comparison fields: 5 of 69
- Cancer Research 178
- Molecular Biology 198
- Biological Psychiatry 3
- Neurology 8
- Pulmonary and Respiratory Medicine 25
Countries citing papers authored by Tan Wu
This map shows the geographic impact of Tan 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 Tan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tan Wu more than expected).
Fields of papers citing papers by Tan Wu
This network shows the impact of papers produced by Tan 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 Tan Wu. The network helps show where Tan Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Tan 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 | 2016 | 152 | |
| 2 | 2024 | 43 | |
| 3 | 2019 | 38 | |
| 4 | 2021 | 17 | |
| 5 | 2021 | 16 | |
| 6 | 2023 | 13 | |
| 7 | 2019 | 10 | |
| 8 | 2023 | 9 | |
| 9 | 2017 | 8 | |
| 10 | 2024 | 7 | |
| 11 | 2017 | 6 | |
| 12 | 2014 | 5 | |
| 13 | 2025 | 4 | |
| 14 | 2021 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2017 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2025 | 3 | |
| 19 | 2024 | 3 | |
| 20 | 2017 | 2 |
About Tan Wu
Tan Wu is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Oncology, having authored 22 papers that have together received 352 indexed citations. Recurring topics across this work include RNA Research and Splicing (7 papers), MicroRNA in disease regulation (4 papers), Cancer-related molecular mechanisms research (4 papers), Ferroptosis and cancer prognosis (3 papers), Bioinformatics and Genomic Networks (3 papers), Genomics and Chromatin Dynamics (3 papers), RNA modifications and cancer (3 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Cancer Research (178 citations), Molecular Biology (198 citations), Biological Psychiatry (3 citations), Neurology (8 citations) and Pulmonary and Respiratory Medicine (25 citations). Tan Wu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yanjun Xu, Xia Li, Feng Li, Yunpeng Zhang, Zeguo Sun, Xinrui Shi, Jing Li, Xin Wang, Yingqi Xu and Hangrong Chen. Their work appears in journals such as Oncotarget, Briefings in Bioinformatics, Frontiers in Genetics, Life Science Alliance and Trends in Genetics.
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.