Effect of the three Bayes approaches on the MSE of individual genes, in comparison to the direct estimation of parameter .</p
<p>Functional analysis of genes differentially expressed between treatment 3 versus 1.</p
Comparison of shared genes identified by selected methods on two independent PAAD datasets.</p
<p>A: 10 genes have a linear effect on the patient outcome. B: 20 genes have a linear effect. C: 10 ...
Effect of the three Bayes approaches on the MSE of individual genes, in comparison to the direct est...
Points represent genes, and they are colored according to the comparison of the performance of the t...
In comparison to Fig 3, here only genes with true underlying value of parameter smaller than 6.91 a...
In recent microarray experiments thousands of gene expressions are simultaneously tested in comparin...
Stochastic dependence between gene expression levels in microarray data is of critical importance fo...
Histogram-based empirical Bayes methods developed for analyzing data for large numbers of genes, SNP...
<p>a. Genes whose expression was increased by MI but reduced or normalized by T4 treatment; b. Genes...
<p>(A) Log-fold changes in gene expression in WS6 vs MS6. (B) Log-fold changes in gene expression in...
Micro-array technology allows investigators the opportunity to measure expression levels of thousand...
<p>MLPE fitted model results on the effects of five landscape variables on genetic differentiation.<...
Motivation: Statistical tests for the detection of differentially expressed genes lead to a large co...
Studies involving the effects of single genes on quantitative traits may involve closed populations,...
<p>Functional analysis of genes differentially expressed between treatment 3 versus 1.</p
Comparison of shared genes identified by selected methods on two independent PAAD datasets.</p
<p>A: 10 genes have a linear effect on the patient outcome. B: 20 genes have a linear effect. C: 10 ...
Effect of the three Bayes approaches on the MSE of individual genes, in comparison to the direct est...
Points represent genes, and they are colored according to the comparison of the performance of the t...
In comparison to Fig 3, here only genes with true underlying value of parameter smaller than 6.91 a...
In recent microarray experiments thousands of gene expressions are simultaneously tested in comparin...
Stochastic dependence between gene expression levels in microarray data is of critical importance fo...
Histogram-based empirical Bayes methods developed for analyzing data for large numbers of genes, SNP...
<p>a. Genes whose expression was increased by MI but reduced or normalized by T4 treatment; b. Genes...
<p>(A) Log-fold changes in gene expression in WS6 vs MS6. (B) Log-fold changes in gene expression in...
Micro-array technology allows investigators the opportunity to measure expression levels of thousand...
<p>MLPE fitted model results on the effects of five landscape variables on genetic differentiation.<...
Motivation: Statistical tests for the detection of differentially expressed genes lead to a large co...
Studies involving the effects of single genes on quantitative traits may involve closed populations,...
<p>Functional analysis of genes differentially expressed between treatment 3 versus 1.</p
Comparison of shared genes identified by selected methods on two independent PAAD datasets.</p
<p>A: 10 genes have a linear effect on the patient outcome. B: 20 genes have a linear effect. C: 10 ...
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