Danny Wu
Impact in
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Causal Inference Techniques
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- Prostate Cancer Treatment and Research
- Prostate Cancer Diagnosis and Treatment
Papers in
- Genetics 2
- Genetic Associations and Epidemiology 1
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- Statistical Methods in Clinical Trials 2
- Co-authors
- Claudia Little (2 shared papers)Bayard D. Clarkson (2 shared papers)David J. Straus (2 shared papers)Jeffrey J. Gaynor (2 shared papers)Murray F. Brennan (2 shared papers)Eric J. Feuer (1 shared paper)Newton E. Morton (2 shared papers)P. A. Jacobs (2 shared papers)
- Journals
- Journal of the American Statistical Association (2 papers)Annals of Human Genetics (2 papers)Controlled Clinical Trials (1 paper)Genetic Epidemiology (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Danny Wu
5 papers receiving 507 citations
Peers
Comparison fields: 5 of 78
- Statistics and Probability 119
- Pulmonary and Respiratory Medicine 143
- Transplantation 11
- Radiation 29
- Oncology 88
Countries citing papers authored by Danny Wu
This map shows the geographic impact of Danny 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 Danny Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danny Wu more than expected).
Fields of papers citing papers by Danny Wu
This network shows the impact of papers produced by Danny 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 Danny Wu. The network helps show where Danny Wu may publish in the future.
Co-authors
The 13 scholars most cited alongside Danny 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 | 1993 | 396 | |
| 2 | 1993 | 60 | |
| 3 | 1988 | 37 | |
| 4 | 1988 | 23 | |
| 5 | 1989 | 5 | |
| 6 | 1992 | 1 |
About Danny Wu
Danny Wu is a scholar working on Genetics, Statistics and Probability, Molecular Biology, Pathology and Forensic Medicine and Pediatrics, Perinatology and Child Health, having authored 6 papers that have together received 522 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (2 papers), HER2/EGFR in Cancer Research (1 paper), Lymphoma Diagnosis and Treatment (1 paper), Gestational Trophoblastic Disease Studies (1 paper), Genetic Associations and Epidemiology (1 paper), Genetic factors in colorectal cancer (1 paper), Assisted Reproductive Technology and Twin Pregnancy (1 paper) and T-cell and B-cell Immunology (1 paper). The work is most often cited by research in Statistics and Probability (119 citations), Pulmonary and Respiratory Medicine (143 citations), Transplantation (11 citations), Radiation (29 citations) and Oncology (88 citations). Danny Wu has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Claudia Little, Bayard D. Clarkson, David J. Straus, Jeffrey J. Gaynor, Murray F. Brennan, Eric J. Feuer, Newton E. Morton, P. A. Jacobs, Terry Hassold and Stephanie L. Sherman. Their work appears in journals such as Journal of the American Statistical Association, Annals of Human Genetics, Controlled Clinical Trials and Genetic Epidemiology.
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.