MOTIVATION: Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles. RESULTS: We introduce a score for differential co-expression and suggest a computationally efficient algorithm for finding high scoring sets of genes. The use of our novel method is demonstrated in the context of simulations and on real expression data from a clinical study
Genes contain blue print of living organism. Malfunctioning occurred in cellular life is indicated b...
The problem of identifying significantly differentially expressed genes for replicated microarray ex...
<p>We propose a method for detecting differential gene expression that exploits the correlation betw...
Motivation: Standard analysis routines for microarray data aim at differentially expressed genes. I...
Motivation: The power of a microarray experiment derives from the identification of genes differenti...
for Identifying Differential Co-expression in High-throughput Experiments A common goal of microarra...
The power of a microarray experiment derives from the identification of genes differentially regulat...
Motivation: Alteration of gene expression often results in up- or down-regulated genes and the most ...
<div><p>Comparing the gene-expression profiles of sick and healthy individuals can help in understan...
With the development of DNA microarray technology, scientists can now measure the expression levels ...
Microarrays are a powerful tool for studying differential gene expression. However, lists of many di...
Motivation: Microarray experiments typically analyze thousands to tens of thousands of genes from sm...
AbstractDifferential gene expression analysis between healthy and diseased groups is a widely used a...
AbstractMany novel therapeutics originally aimed at a specific protein have in fact complex target p...
This paper presents a unified framework for finding differentially expressed genes (DEGs) from the t...
Genes contain blue print of living organism. Malfunctioning occurred in cellular life is indicated b...
The problem of identifying significantly differentially expressed genes for replicated microarray ex...
<p>We propose a method for detecting differential gene expression that exploits the correlation betw...
Motivation: Standard analysis routines for microarray data aim at differentially expressed genes. I...
Motivation: The power of a microarray experiment derives from the identification of genes differenti...
for Identifying Differential Co-expression in High-throughput Experiments A common goal of microarra...
The power of a microarray experiment derives from the identification of genes differentially regulat...
Motivation: Alteration of gene expression often results in up- or down-regulated genes and the most ...
<div><p>Comparing the gene-expression profiles of sick and healthy individuals can help in understan...
With the development of DNA microarray technology, scientists can now measure the expression levels ...
Microarrays are a powerful tool for studying differential gene expression. However, lists of many di...
Motivation: Microarray experiments typically analyze thousands to tens of thousands of genes from sm...
AbstractDifferential gene expression analysis between healthy and diseased groups is a widely used a...
AbstractMany novel therapeutics originally aimed at a specific protein have in fact complex target p...
This paper presents a unified framework for finding differentially expressed genes (DEGs) from the t...
Genes contain blue print of living organism. Malfunctioning occurred in cellular life is indicated b...
The problem of identifying significantly differentially expressed genes for replicated microarray ex...
<p>We propose a method for detecting differential gene expression that exploits the correlation betw...