Statistics and Computational Biology

Korbinian Strimmer - 10 Selected Papers (December 2009):

For current preprints and additional papers see the complete list of publications.

1. Gene ranking and biomarker discovery under correlation.
   V. Zuber and K. Strimmer. 2009.
   Bioinformatics 25: 2700-2707.
   (reprint, arXiv:0902.0751)
2. Entropy inference and the James-Stein estimator, with application to nonlinear gene association networks.
   J. Hausser and K. Strimmer. 2009.
   J. Mach. Learn. Res. 10: 1469-1484.
   (reprint, arXiv:0811.3579)
3. A general modular framework for gene set enrichment analysis.
   M. Ackermann and K. Strimmer. 2009.
   BMC Bioinformatics 10: 47.
   (reprint)
4. A unified approach to false discovery rate estimation.
   K. Strimmer. 2008.
   BMC Bioinformatics 9: 303.
   (reprint, typographic corrections)
5. Accurate ranking of differentially expressed genes by a distribution- free shrinkage approach.
   R. Opgen-Rhein and K. Strimmer. 2007.
   Statist. Appl. Genet. Mol. Biol. 6: 9.
   (reprint, typographic corrections)
6. A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics.
   J. Schäfer and K. Strimmer. 2005.
   Statist. Appl. Genet. Mol. Biol. 4: 32.
   (reprint)
7. An empirical Bayes approach to inferring large-scale gene association networks.
   J. Schäfer and K. Strimmer. 2005.
   Bioinformatics 21: 754-764.
   (reprint)
8. Inference of demographic history from genealogical trees using reversible jump Markov chain Monte Carlo.
   R. Opgen-Rhein, L. Fahrmeir, and K. Strimmer. 2005.
   BMC Evol. Biol. 5: 6.
   (reprint)
9. Identifying periodically expressed transcripts in microarray time series data.
   S. Wichert, K. Fokianos, and K. Strimmer. 2004.
   Bioinformatics 20: 5-20.
   (reprint, corrigendum)
10. Modeling gene expression measurement error: a quasi-likelihood approach.
    K. Strimmer. 2003.
    BMC Bioinformatics 4: 10.
    (reprint)

 

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