John D. Storey

44.3k total citations · 9 hit papers
83 papers, 26.0k citations indexed

About

John D. Storey is a scholar working on Molecular Biology, Genetics and Statistics and Probability. According to data from OpenAlex, John D. Storey has authored 83 papers receiving a total of 26.0k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Molecular Biology, 23 papers in Genetics and 12 papers in Statistics and Probability. Recurrent topics in John D. Storey's work include Gene expression and cancer classification (31 papers), Bioinformatics and Genomic Networks (21 papers) and Genetic Associations and Epidemiology (15 papers). John D. Storey is often cited by papers focused on Gene expression and cancer classification (31 papers), Bioinformatics and Genomic Networks (21 papers) and Genetic Associations and Epidemiology (15 papers). John D. Storey collaborates with scholars based in United States, Germany and Canada. John D. Storey's 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 and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

John D. Storey

82 papers receiving 25.5k citations

Hit Papers

Statistical significance for genomewide studies 2001 2026 2009 2017 2003 2002 2012 2003 2007 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Statistical significance for genomewide studies
    2003 7.3k citations John D. Storey, Robert Tibshirani Proceedings of the National Academy of Sciences profile →
  2. A Direct Approach to False Discovery Rates
    2002 4.1k citations John D. Storey profile →
  3. The sva package for removing batch effects and other unwanted variation in high-throughput experiments
    2012 3.6k citations Jeffrey T. Leek, John D. Storey et al. Bioinformatics profile →
  4. The positive false discovery rate: a Bayesian interpretation and the q-value
    2003 1.6k citations John D. Storey profile →
  5. Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
    2007 1.2k citations Jeffrey T. Leek, John D. Storey PLoS Genetics profile →
  6. Empirical Bayes Analysis of a Microarray Experiment
    2001 1.1k citations Robert Tibshirani, John D. Storey et al. Journal of the American Statistical Association profile →
  7. Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
    2003 949 citations John D. Storey et al. profile →
  8. Precision and functional specificity in mRNA decay
    2002 556 citations Yulei Wang, Chih Long Liu et al. Proceedings of the National Academy of Sciences profile →
  9. Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae
    2003 535 citations Yoav Arava, Yulei Wang et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John D. Storey United States 40 15.2k 5.5k 2.6k 2.3k 2.0k 83 26.0k
Terence P. Speed Australia 83 20.2k 1.3× 5.2k 1.0× 2.4k 0.9× 3.8k 1.7× 2.7k 1.3× 378 34.9k
Robert Gentleman United States 43 18.7k 1.2× 3.8k 0.7× 1.2k 0.5× 7.8k 3.4× 2.7k 1.3× 115 34.2k
Hongyu Zhao United States 77 11.6k 0.8× 6.4k 1.2× 673 0.3× 1.5k 0.7× 3.2k 1.6× 746 25.1k
Jason H. Moore United States 76 12.6k 0.8× 8.5k 1.6× 432 0.2× 2.1k 0.9× 593 0.3× 635 26.9k
Jeffrey T. Leek United States 39 10.0k 0.7× 2.5k 0.5× 548 0.2× 2.5k 1.1× 1.7k 0.9× 82 16.1k
Sandrine Dudoit United States 50 11.4k 0.8× 1.6k 0.3× 1.5k 0.6× 2.2k 1.0× 790 0.4× 99 17.4k
Simon Tavaré United States 68 10.7k 0.7× 6.7k 1.2× 1.1k 0.4× 3.6k 1.6× 1.8k 0.9× 220 21.3k
Gavin Sherlock United States 52 35.0k 2.3× 6.3k 1.1× 394 0.2× 4.6k 2.0× 5.4k 2.6× 127 49.1k
Gilbert Chu United States 43 14.0k 0.9× 2.3k 0.4× 351 0.1× 3.0k 1.3× 1.4k 0.7× 87 19.8k
Nicholas J. Schork United States 94 10.9k 0.7× 10.9k 2.0× 384 0.1× 1.4k 0.6× 1.7k 0.8× 460 32.3k

Countries citing papers authored by John D. Storey

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of John D. Storey

This figure shows the co-authorship network connecting the top 25 collaborators of John D. Storey. A scholar is included among the top collaborators of John D. Storey based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John D. Storey. John D. Storey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ochoa, Alejandro & John D. Storey. (2021). Estimating FST and kinship for arbitrary population structures. PLoS Genetics. 17(1). e1009241–e1009241. 54 indexed citations
2.
Storey, John D., et al.. (2020). The optimal discovery procedure for significance analysis of general gene expression studies. Bioinformatics. 37(3). 367–374. 2 indexed citations
3.
Graim, Kiley, David G. Robinson, Nicholas Carriero, et al.. (2020). Modeling molecular development of breast cancer in canine mammary tumors. Genome Research. 31(2). 337–347. 12 indexed citations
4.
Storey, John D., et al.. (2019). A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis. Genetics. 212(4). 1009–1029. 17 indexed citations
5.
Robinson, David G., et al.. (2019). The functional false discovery rate with applications to genomics. Biostatistics. 22(1). 68–81. 32 indexed citations
6.
Hao, Wei Min & John D. Storey. (2019). Extending Tests of Hardy–Weinberg Equilibrium to Structured Populations. Genetics. 213(3). 759–770. 12 indexed citations
7.
Hackett, Sean R., Vito Riccardo Tomaso Zanotelli, Wenxin Xu, et al.. (2016). Systems-level analysis of mechanisms regulating yeast metabolic flux. Science. 354(6311). 206 indexed citations
8.
Robinson, David G., Jean Y. Wang, & John D. Storey. (2015). A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays. Nucleic Acids Research. 43(20). gkv636–gkv636. 30 indexed citations
9.
Kim, Jinhee, Nima Ghasemzadeh, Danny J. Eapen, et al.. (2014). Gene expression profiles associated with acute myocardial infarction and risk of cardiovascular death. Genome Medicine. 6(5). 40–40. 40 indexed citations
10.
Doocy, Shannon, et al.. (2012). Chronic disease and disability among Iraqi populations displaced in Jordan and Syria. The International Journal of Health Planning and Management. 28(1). e1–e12. 47 indexed citations
11.
Storey, John D., et al.. (2012). Cross-Dimensional Inference of Dependent High-Dimensional Data. Journal of the American Statistical Association. 107(497). 135–151. 16 indexed citations
12.
Leek, Jeffrey T. & John D. Storey. (2011). The Joint Null Criterion for Multiple Hypothesis Tests. Statistical Applications in Genetics and Molecular Biology. 10(1). 16 indexed citations
13.
Leek, Jeffrey T. & John D. Storey. (2008). A general framework for multiple testing dependence. Proceedings of the National Academy of Sciences. 105(48). 18718–18723. 237 indexed citations
14.
Biswas, Shameek, John D. Storey, & Joshua M. Akey. (2008). Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis. BMC Bioinformatics. 9(1). 244–244. 33 indexed citations
15.
Storey, John D., et al.. (2007). Gene-Expression Variation Within and Among Human Populations. The American Journal of Human Genetics. 80(3). 502–509. 226 indexed citations
16.
Storey, John D. & Robert Tibshirani. (2003). Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences. 100(16). 9440–9445. 7345 indexed citations breakdown →
17.
Arava, Yoav, Yulei Wang, John D. Storey, et al.. (2003). Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae. Proceedings of the National Academy of Sciences. 100(7). 3889–3894. 535 indexed citations breakdown →
18.
Reiter, Clifford A., et al.. (2001). Function Digraphs of Quadratic Maps Modulo p. ˜The œFibonacci quarterly. 39(1). 32–49. 3 indexed citations
19.
Storey, Kenneth B. & John D. Storey. (2000). Environmental stressors and gene responses. Elsevier eBooks. 58 indexed citations
20.
Jeffries, D. S., et al.. (1992). Evaluation of the effects of acid precipitation in eastern Canada using the raison system. Environmental Monitoring and Assessment. 23(1-3). 71–82. 1 indexed citations

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.

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