Dai-Chen Wu
Impact in
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers
- Pancreatic and Hepatic Oncology Research
- Cancer Cells and Metastasis
- Immunology top 10%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
-
- Protein Tyrosine Phosphatases 1
- Hedgehog Signaling Pathway Studies 1
- RNA modifications and cancer 1
- Oncology 3
- Pancreatic and Hepatic Oncology Research 2
- Cancer-related Molecular Pathways 1
- Co-authors
- Julien Fitamant (1 shared paper)Phillip D. Jones (1 shared paper)Julia M. Nagle (1 shared paper)Jürgen K. Willmann (1 shared paper)Vikram Deshpande (1 shared paper)Rushika M. Perera (1 shared paper)John J. Lee (1 shared paper)Huaijun Wang (1 shared paper)
- Journals
- Clinical Cancer Research (1 paper)Cell (1 paper)Proceedings of the National Academy of Sciences (1 paper)Hepatology (1 paper)Nature Cancer (1 paper)
- Partner nations
- United StatesTaiwanIndia
In The Last Decade
Dai-Chen Wu
6 papers receiving 974 citations
Dai-Chen Wu's Hit Papers
Peers
Comparison fields: 5 of 66
- Oncology 562
- Immunology 374
- Cancer Research 120
- Molecular Biology 502
- Biotechnology 26
Countries citing papers authored by Dai-Chen Wu
This map shows the geographic impact of Dai-Chen 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 Dai-Chen Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai-Chen Wu more than expected).
Fields of papers citing papers by Dai-Chen Wu
This network shows the impact of papers produced by Dai-Chen 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 Dai-Chen Wu. The network helps show where Dai-Chen Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai-Chen 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
| # | Work | ||
|---|---|---|---|
| 1 | Stromal response to Hedgehog signaling restrains pancreatic cancer progression Hit paper breakdown → | 2014 | 386 |
| 2 | PD-L1 expression by dendritic cells is a key regulator of T-cell immunity in cancer Hit paper breakdown → | 2020 | 316 |
| 3 | 2011 | 231 | |
| 4 | 2006 | 47 | |
| 5 | 2004 | 8 | |
| 6 | 2011 | 4 |
About Dai-Chen Wu
Dai-Chen Wu is a scholar working on Molecular Biology, Oncology, Genetics, Pathology and Forensic Medicine and Hematology, having authored 6 papers that have together received 992 indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (2 papers), Mesenchymal stem cell research (1 paper), Protein Tyrosine Phosphatases (1 paper), Cancer-related Molecular Pathways (1 paper), Acute Myeloid Leukemia Research (1 paper), Hedgehog Signaling Pathway Studies (1 paper), Immunotherapy and Immune Responses (1 paper) and RNA modifications and cancer (1 paper). The work is most often cited by research in Oncology (562 citations), Immunology (374 citations), Cancer Research (120 citations), Molecular Biology (502 citations) and Biotechnology (26 citations). Dai-Chen Wu has collaborated with scholars based in United States, Taiwan and India. Frequent co-authors include Julien Fitamant, Phillip D. Jones, Julia M. Nagle, Jürgen K. Willmann, Vikram Deshpande, Rushika M. Perera, John J. Lee, Huaijun Wang, Sally Kawano and Nabeel Bardeesy. Their work appears in journals such as Clinical Cancer Research, Cell, Proceedings of the National Academy of Sciences, Hepatology and Nature Cancer.
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.