Bill Wheeler
Impact in
- Genetics top 10%
- Genetic Associations and Epidemiology
- Genetic and phenotypic traits in livestock
- Genetic Mapping and Diversity in Plants and Animals
- BRCA gene mutations in cancer
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- Global Cancer Incidence and Screening
- Colorectal Cancer Screening and Detection
Papers in
- Genetics 3
- Genetic Associations and Epidemiology 2
- Genetic and phenotypic traits in livestock 2
- Genetic Mapping and Diversity in Plants and Animals 1
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- Statistical Methods and Inference 2
- Statistical Methods and Bayesian Inference 1
- Co-authors
- Joshua N. Sampson (1 shared paper)Patricia Hartge (1 shared paper)Stephen J. Chanock (1 shared paper)Nilanjan Chatterjee (1 shared paper)Hyune‐Ju Kim (2 shared papers)Huann‐Sheng Chen (2 shared papers)Eric J. Feuer (2 shared papers)Dennis W. Buckman (1 shared paper)
- Journals
- Nature Genetics (1 paper)Statistics in Medicine (1 paper)Cancer Prevention Research (1 paper)Journal of Applied Statistics (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Bill Wheeler
4 papers receiving 371 citations
Bill Wheeler's Hit Papers
Peers
Comparison fields: 5 of 84
- Genetics 193
- Oncology 46
- Cancer Research 23
- Applied Microbiology and Biotechnology 3
- Epidemiology 46
Countries citing papers authored by Bill Wheeler
This map shows the geographic impact of Bill Wheeler'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 Bill Wheeler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bill Wheeler more than expected).
Fields of papers citing papers by Bill Wheeler
This network shows the impact of papers produced by Bill Wheeler. 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 Bill Wheeler. The network helps show where Bill Wheeler may publish in the future.
Co-authors
The 20 scholars most cited alongside Bill Wheeler, 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 | 2013 | 240 | |
| 2 | Twenty years since Joinpoint 1.0: Two major enhancements, their justification, and impact Hit paper breakdown → | 2022 | 101 |
| 3 | 2022 | 33 | |
| 4 | 2010 | 1 |
About Bill Wheeler
Bill Wheeler is a scholar working on Genetics, Statistics and Probability, Surgery, Molecular Biology and Artificial Intelligence, having authored 4 papers that have together received 375 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (2 papers), Genetic and phenotypic traits in livestock (2 papers), Statistical Methods and Inference (2 papers), Epigenetics and DNA Methylation (1 paper), Genetic Mapping and Diversity in Plants and Animals (1 paper), Statistical Methods and Bayesian Inference (1 paper), Esophageal Cancer Research and Treatment (1 paper) and Bayesian Methods and Mixture Models (1 paper). The work is most often cited by research in Genetics (193 citations), Oncology (46 citations), Cancer Research (23 citations), Applied Microbiology and Biotechnology (3 citations) and Epidemiology (46 citations). Bill Wheeler has collaborated with scholars based in United States and South Korea. Frequent co-authors include Joshua N. Sampson, Patricia Hartge, Stephen J. Chanock, Nilanjan Chatterjee, Hyune‐Ju Kim, Huann‐Sheng Chen, Eric J. Feuer, Dennis W. Buckman, Jun Luo and Donald P. Green. Their work appears in journals such as Nature Genetics, Statistics in Medicine, Cancer Prevention Research and Journal of Applied Statistics.
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.