Dai-Chen Wu
Impact in
- Oncology top 5%
- Pancreatic and Hepatic Oncology Research
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
- Immunology top 10%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
- Oncology 5
- Pancreatic and Hepatic Oncology Research 3
- Cancer-related Molecular Pathways 2
- Cancer Immunotherapy and Biomarkers 2
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- Immunotherapy and Immune Responses 2
- Co-authors
- Robert F. Paulson (6 shared papers)Lei Shi (1 shared paper)Yves Boucher (1 shared paper)Vikram Deshpande (1 shared paper)Philip A. Beachy (1 shared paper)Jürgen K. Willmann (1 shared paper)Phillip D. Jones (1 shared paper)Julia M. Nagle (1 shared paper)
- Journals
- Hepatology (2 papers)Proceedings of the National Academy of Sciences (2 papers)Blood (2 papers)Nature Cancer (1 paper)Current Opinion in Hematology (1 paper)
- Partner nations
- United StatesTaiwanIndia
In The Last Decade
Dai-Chen Wu
12 papers receiving 1.5k citations
Dai-Chen Wu's Hit Papers
Peers
Comparison fields: 5 of 80
- Oncology 605
- Immunology 458
- Genetics 149
- Hematology 139
- Cancer Research 134
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 | 442 |
| 2 | 2020 | 385 | |
| 3 | 2011 | 243 | |
| 4 | 2011 | 199 | |
| 5 | 2015 | 70 | |
| 6 | 2006 | 50 | |
| 7 | 2019 | 42 | |
| 8 | 2010 | 38 | |
| 9 | 2004 | 20 | |
| 10 | 2004 | 8 | |
| 11 | 2011 | 4 | |
| 12 | 2022 | 1 |
About Dai-Chen Wu
Dai-Chen Wu is a scholar working on Oncology, Immunology, Genetics, Molecular Biology and Genetics, having authored 12 papers that have together received 1.5k indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (3 papers), Cancer-related Molecular Pathways (2 papers), Immunotherapy and Immune Responses (2 papers), Genomic variations and chromosomal abnormalities (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Epigenetics and DNA Methylation (2 papers), Acute Myeloid Leukemia Research (1 paper) and RNA modifications and cancer (1 paper). The work is most often cited by research in Oncology (605 citations), Immunology (458 citations), Genetics (149 citations), Hematology (139 citations) and Cancer Research (134 citations). Dai-Chen Wu has collaborated with scholars based in United States, Taiwan and India. Frequent co-authors include Robert F. Paulson, Lei Shi, Yves Boucher, Vikram Deshpande, Philip A. Beachy, Jürgen K. Willmann, Phillip D. Jones, Julia M. Nagle, Huaijun Wang and Rushika M. Perera. Their work appears in journals such as Hepatology, Proceedings of the National Academy of Sciences, Blood, Nature Cancer and Current Opinion in Hematology.
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.