Daniel Wu
- Oncology top 5%
- Viral-associated cancers and disorders 4
- Dermatology top 2%
- Genetics top 5%
- Virus-based gene therapy research 3
- Immunology top 10%
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- Telomeres, Telomerase, and Senescence 5
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- Genomics and Chromatin Dynamics 5
- RNA Interference and Gene Delivery 4
- Chromatin Remodeling and Cancer 4
- Nuclear Structure and Function 3
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- Lung Cancer Treatments and Mutations 3
- Co-authors
- Rachel RobersonSteven J. KussickWilliam H. SchubachEric VallièresDavid S. ViswanathaTimothy C. GreinerMukesh ChhanabhaiPatricia Aoun
- Journals
- International Journal of Cancer (2 papers)Journal of Virology (2 papers)Molecular and Cellular Biology (2 papers)
- Partner nations
- United StatesBulgariaUnited Kingdom
In The Last Decade
Daniel Wu
36 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 98
- Pathology and Forensic Medicine 756
- Oncology 767
- Dermatology 201
- Genetics 187
- Immunology 351
Countries citing papers authored by Daniel Wu
This map shows the geographic impact of Daniel 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 Daniel Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Wu more than expected).
Fields of papers citing papers by Daniel Wu
This network shows the impact of papers produced by Daniel 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 Daniel Wu. The network helps show where Daniel Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel 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 | 2022 | 1 | |
| 2 | 2020 | 8 | |
| 3 | 2017 | 2 | |
| 4 | 2017 | 10 | |
| 5 | 2014 | 4 | |
| 6 | 2014 | 22 | |
| 7 | 2014 | 42 | |
| 8 | 2012 | 104 | |
| 9 | 2011 | 24 | |
| 10 | 2010 | 6 | |
| 11 | 2010 | 71 | |
| 12 | 2008 | 24 | |
| 13 | 2008 | 24 | |
| 14 | 2006 | 39 | |
| 15 | 2003 | 27 | |
| 16 | 2002 | 208 | |
| 17 | 2002 | 35 | |
| 18 | 2002 | 40 | |
| 19 | 2000 | 58 | |
| 20 | 1999 | 132 |
About Daniel Wu
Daniel Wu is a scholar working on Aging, Oncology, Hematology, Nephrology and Molecular Biology, having authored 37 papers that have together received 2.3k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (5 papers), Genomics and Chromatin Dynamics (5 papers), RNA Interference and Gene Delivery (4 papers), Chromatin Remodeling and Cancer (4 papers), Viral-associated cancers and disorders (4 papers), Virus-based gene therapy research (3 papers), Nuclear Structure and Function (3 papers) and Lung Cancer Treatments and Mutations (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (756 citations), Oncology (767 citations), Dermatology (201 citations), Genetics (187 citations) and Immunology (351 citations). Daniel Wu has collaborated with scholars based in United States, Bulgaria and United Kingdom. Frequent co-authors include Rachel Roberson, Steven J. Kussick, William H. Schubach, Eric Vallières, David S. Viswanatha, Timothy C. Greiner, Mukesh Chhanabhai, Patricia Aoun, Brian Skinnider and Randy D. Gascoyne. Their work appears in journals such as International Journal of Cancer, Journal of Virology, Molecular and Cellular Biology, Blood and Journal of Pharmaceutical Sciences.
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.