John D. Storey
- Statistics and Probability top 0.05%
- Statistical Methods in Clinical Trials 11
- Statistical Methods and Inference 6
- Molecular Biology top 0.1%
- Gene expression and cancer classification 31
- Bioinformatics and Genomic Networks 21
- Molecular Biology Techniques and Applications 10
- Gene Regulatory Network Analysis 6
- Genetics top 0.1%
- Genetic Associations and Epidemiology 15
- Genetic Mapping and Diversity in Plants and Animals 13
- Aging top 1%
- Cancer Research top 0.5%
- Co-authors
- Robert TibshiraniJeffrey T. LeekAndrew E. JaffeW. Evan JohnsonHilary S. ParkerDavid SiegmundJonathan TaylorBradley Efron
- Journals
- Bioinformatics (12 papers)Proceedings of the National Academy of Sciences (6 papers)PLoS Genetics (5 papers)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
John D. Storey
82 papers receiving 25.5k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Statistics and Probability 2.6k
- Molecular Biology 15.2k
- Genetics 5.5k
- Aging 271
- Cancer Research 2.3k
Countries citing papers authored by John D. Storey
This map shows the geographic impact of John D. Storey'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 John D. Storey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Storey more than expected).
Fields of papers citing papers by John D. Storey
This network shows the impact of papers produced by John D. Storey. 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 John D. Storey. The network helps show where John D. Storey may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John D. Storey, 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 | 2021 | 54 | |
| 2 | 2020 | 2 | |
| 3 | 2020 | 12 | |
| 4 | 2019 | 17 | |
| 5 | 2019 | 32 | |
| 6 | 2019 | 12 | |
| 7 | 2016 | 206 | |
| 8 | 2015 | 30 | |
| 9 | 2014 | 40 | |
| 10 | 2012 | 47 | |
| 11 | 2012 | 16 | |
| 12 | 2011 | 16 | |
| 13 | 2008 | 237 | |
| 14 | 2008 | 33 | |
| 15 | 2007 | 226 | |
| 16 | Statistical significance for genomewide studiesbreakdown → | 2003 | 7345 |
| 17 | Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiaebreakdown → | 2003 | 535 |
| 18 | 2001 | 3 | |
| 19 | Environmental stressors and gene responses | 2000 | 58 |
| 20 | 1992 | 1 |
About John D. Storey
John D. Storey is a scholar working on Statistics and Probability, Genetics, Molecular Biology, Aging and Geometry and Topology, having authored 83 papers that have together received 26.0k indexed citations. Recurring topics across this work include Gene expression and cancer classification (31 papers), Bioinformatics and Genomic Networks (21 papers), Genetic Associations and Epidemiology (15 papers), Genetic Mapping and Diversity in Plants and Animals (13 papers), Statistical Methods in Clinical Trials (11 papers), Molecular Biology Techniques and Applications (10 papers), Gene Regulatory Network Analysis (6 papers) and Statistical Methods and Inference (6 papers). The work is most often cited by research in Statistics and Probability (2.6k citations), Molecular Biology (15.2k citations), Genetics (5.5k citations), Aging (271 citations) and Cancer Research (2.3k citations). John D. Storey has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Robert Tibshirani, Jeffrey T. Leek, Andrew E. Jaffe, W. Evan Johnson, Hilary S. Parker, David Siegmund, Jonathan Taylor, Bradley Efron, Lukas Käll and William Stafford Noble. Their work appears in journals such as Bioinformatics, Proceedings of the National Academy of Sciences, PLoS Genetics, Genetics and Journal of the Royal Statistical Society Series B (Statistical Methodology).
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.