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Dan Nettleton

Showing results (11-20 of 130) with videos related to

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Bioinformatics (Oxford, England)|July 16, 2014
An improved method for computing q-values when the distribution of effect sizes is asymmetricMegan Orr, Peng Liu, Dan Nettleton
BMC Bioinformatics|April 16, 2014
Copy number variation detection using next generation sequencing read countsHeng Wang, Dan Nettleton, Kai Ying
Journal of the American Statistical Association|July 30, 2019
Fully Bayesian analysis of RNA-seq counts for the detection of gene expression heterosisWill Landau, Jarad Niemi, Dan Nettleton
Biometrics|February 6, 2013
Estimation of false discovery rate using sequential permutation p-valuesTim Bancroft, Chuanlong Du, Dan Nettleton
Biometrics|June 16, 2009
Linear mixed model selection for false discovery rate control in microarray data analysisCumhur Yusuf Demirkale, Dan Nettleton, Tapabrata Maiti
Bioinformatics (Oxford, England)|November 29, 2007
Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysisDan Nettleton, Justin Recknor, James M Reecy
BMC Biology|April 18, 2008
Duplicate gene expression in allopolyploid Gossypium reveals two temporally distinct phases of expression evolutionLex Flagel, Joshua Udall, Dan Nettleton, et al.
Biometrics|September 22, 2012
A hierarchical semiparametric model for incorporating intergene information for analysis of genomic dataLong Qu, Dan Nettleton, Jack C M Dekkers
Nucleic Acids Research|October 9, 2012
Reverse engineering and analysis of large genome-scale gene networksManeesha Aluru, Jaroslaw Zola, Dan Nettleton, et al.
Journal of Agricultural, Biological, and Environmental Statistics|May 6, 2016
Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosisJarad Niemi, Eric Mittman, Will Landau, et al.
Pageof 13

Showing results (11-20 of 130) with videos related to

Sort By:
Pageof 13
Bioinformatics (Oxford, England)|July 16, 2014
An improved method for computing q-values when the distribution of effect sizes is asymmetricMegan Orr, Peng Liu, Dan Nettleton
BMC Bioinformatics|April 16, 2014
Copy number variation detection using next generation sequencing read countsHeng Wang, Dan Nettleton, Kai Ying
Journal of the American Statistical Association|July 30, 2019
Fully Bayesian analysis of RNA-seq counts for the detection of gene expression heterosisWill Landau, Jarad Niemi, Dan Nettleton
Biometrics|February 6, 2013
Estimation of false discovery rate using sequential permutation p-valuesTim Bancroft, Chuanlong Du, Dan Nettleton
Biometrics|June 16, 2009
Linear mixed model selection for false discovery rate control in microarray data analysisCumhur Yusuf Demirkale, Dan Nettleton, Tapabrata Maiti
Bioinformatics (Oxford, England)|November 29, 2007
Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysisDan Nettleton, Justin Recknor, James M Reecy
BMC Biology|April 18, 2008
Duplicate gene expression in allopolyploid Gossypium reveals two temporally distinct phases of expression evolutionLex Flagel, Joshua Udall, Dan Nettleton, et al.
Biometrics|September 22, 2012
A hierarchical semiparametric model for incorporating intergene information for analysis of genomic dataLong Qu, Dan Nettleton, Jack C M Dekkers
Nucleic Acids Research|October 9, 2012
Reverse engineering and analysis of large genome-scale gene networksManeesha Aluru, Jaroslaw Zola, Dan Nettleton, et al.
Journal of Agricultural, Biological, and Environmental Statistics|May 6, 2016
Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosisJarad Niemi, Eric Mittman, Will Landau, et al.
Pageof 13