Wai‐Ki Yip
Impact in
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- Cancer Genomics and Diagnostics
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- Cancer Immunotherapy and Biomarkers
- Cutaneous Melanoma Detection and Management
Papers in
- Genetics 6
- Genetic Associations and Epidemiology 6
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- Statistical Methods in Clinical Trials 2
- Co-authors
- Nan M. Laird (5 shared papers)Iuliana Ionita‐Laza (1 shared paper)Christoph Lange (7 shared papers)Dandi Qiao (3 shared papers)Adrienne G. Randolph (4 shared papers)Bernard F. Cole (2 shared papers)Marco Bonetti (2 shared papers)Richard D. Gelber (2 shared papers)
- Journals
- The Journal of Infectious Diseases (2 papers)Genetic Epidemiology (2 papers)PLoS ONE (2 papers)Clinical Trials (2 papers)BMC Bioinformatics (1 paper)
- Partner nations
- United StatesGermanyNetherlands
In The Last Decade
Wai‐Ki Yip
21 papers receiving 650 citations
Wai‐Ki Yip's Hit Papers
Peers
Comparison fields: 5 of 42
- Cancer Research 65
- Oncology 85
- Genetics 90
- Neurology 13
- Pulmonary and Respiratory Medicine 54
Countries citing papers authored by Wai‐Ki Yip
This map shows the geographic impact of Wai‐Ki Yip'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 Wai‐Ki Yip with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wai‐Ki Yip more than expected).
Fields of papers citing papers by Wai‐Ki Yip
This network shows the impact of papers produced by Wai‐Ki Yip. 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 Wai‐Ki Yip. The network helps show where Wai‐Ki Yip may publish in the future.
Co-authors
The 25 scholars most cited alongside Wai‐Ki Yip, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Clinical and analytical validation of FoundationOne®CDx, a comprehensive genomic profiling assay for solid tumors Hit paper breakdown → | 2022 | 260 |
| 2 | 2013 | 94 | |
| 3 | 2017 | 54 | |
| 4 | 2014 | 39 | |
| 5 | 2017 | 37 | |
| 6 | 2013 | 31 | |
| 7 | 2016 | 25 | |
| 8 | 2016 | 20 | |
| 9 | 2011 | 14 | |
| 10 | 2012 | 14 | |
| 11 | 2015 | 14 | |
| 12 | 2011 | 13 | |
| 13 | 2018 | 11 | |
| 14 | 2017 | 10 | |
| 15 | 2014 | 7 | |
| 16 | 2011 | 6 | |
| 17 | 2019 | 6 | |
| 18 | 2011 | 2 | |
| 19 | 2013 | 2 | |
| 20 | 2014 | 2 |
About Wai‐Ki Yip
Wai‐Ki Yip is a scholar working on Genetics, Statistics and Probability, Oncology, Epidemiology and Cancer Research, having authored 21 papers that have together received 662 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (6 papers), Statistical Methods in Clinical Trials (2 papers), Epigenetics and DNA Methylation (1 paper), Gene expression and cancer classification (1 paper), Alzheimer's disease research and treatments (1 paper), Cancer Immunotherapy and Biomarkers (1 paper), Cancer Genomics and Diagnostics (1 paper) and Respiratory viral infections research (1 paper). The work is most often cited by research in Cancer Research (65 citations), Oncology (85 citations), Genetics (90 citations), Neurology (13 citations) and Pulmonary and Respiratory Medicine (54 citations). Wai‐Ki Yip has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Nan M. Laird, Iuliana Ionita‐Laza, Christoph Lange, Dandi Qiao, Adrienne G. Randolph, Bernard F. Cole, Marco Bonetti, Richard D. Gelber, Ann A. Lazar and Cheng Li. Their work appears in journals such as The Journal of Infectious Diseases, Genetic Epidemiology, PLoS ONE, Clinical Trials and BMC Bioinformatics.
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.