Dake Wang
Impact in
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- Immune cells in cancer
- Immunotherapy and Immune Responses
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- Fungal and yeast genetics research
- Gut microbiota and health
- Epigenetics and DNA Methylation
- CRISPR and Genetic Engineering
- RNA Research and Splicing
Papers in
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- RNA Research and Splicing 2
- Extracellular vesicles in disease 2
- RNA modifications and cancer 2
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- Immune cells in cancer 4
- Co-authors
- Xianlu Zeng (6 shared papers)Zheng Feng (2 shared papers)Gunter B. Kohlhaw (2 shared papers)Yueshuang Ke (3 shared papers)Yawei Wang (2 shared papers)Yingying Sun (5 shared papers)Lili Chen (2 shared papers)Chao Shang (4 shared papers)
- Journals
- Cell Death and Disease (3 papers)Materials & Design (2 papers)Chemical Engineering Journal (2 papers)Journal of Biological Chemistry (2 papers)Cancer Letters (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Dake Wang
14 papers receiving 323 citations
Peers
Comparison fields: 5 of 64
- Immunology 84
- Molecular Biology 192
- Oncology 66
- Cancer Research 24
- Virology 7
Countries citing papers authored by Dake Wang
This map shows the geographic impact of Dake Wang'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 Dake Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dake Wang more than expected).
Fields of papers citing papers by Dake Wang
This network shows the impact of papers produced by Dake Wang. 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 Dake Wang. The network helps show where Dake Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dake Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 73 | |
| 2 | 2019 | 49 | |
| 3 | 1999 | 39 | |
| 4 | 2019 | 35 | |
| 5 | 1997 | 34 | |
| 6 | 2022 | 33 | |
| 7 | 2022 | 16 | |
| 8 | 2020 | 11 | |
| 9 | Data-driven generation of decision trees for motif-based assignment of protein sequences to functional families | 2001 | 11 |
| 10 | 2021 | 10 | |
| 11 | 2024 | 7 | |
| 12 | 2025 | 3 | |
| 13 | 2025 | 2 | |
| 14 | 2025 | 2 |
About Dake Wang
Dake Wang is a scholar working on Molecular Biology, Immunology, Oncology, Pathology and Forensic Medicine and Neurology, having authored 14 papers that have together received 325 indexed citations. Recurring topics across this work include Immune cells in cancer (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), RNA Research and Splicing (2 papers), Extracellular vesicles in disease (2 papers), Spinal Cord Injury Research (2 papers), Chemokine receptors and signaling (2 papers), Cytokine Signaling Pathways and Interactions (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Immunology (84 citations), Molecular Biology (192 citations), Oncology (66 citations), Cancer Research (24 citations) and Virology (7 citations). Dake Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xianlu Zeng, Zheng Feng, Gunter B. Kohlhaw, Yueshuang Ke, Yawei Wang, Yingying Sun, Lili Chen, Chao Shang, Xiaoqing Han and Xinyu Zhou. Their work appears in journals such as Cell Death and Disease, Materials & Design, Chemical Engineering Journal, Journal of Biological Chemistry and Cancer Letters.
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.