In DNA microarray analysis, it is an important problem to detect differentials of gene expression. We use the gamma and the weibull distributions in modeling gene expression. We assume mixture priors on the parameters representing different effects between two experimental conditions. Markov chain Monte Carlo methods are used to compute the Bayes factor and posterior means. We perform a simulation study and real data analysis to demonstrate our theoretical results
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
We review the use of Bayesian methods for analyzing gene expression data. We focus on methods which ...
In this paper, the problem of identifying differentially expressed genes under different condi-tions...
www.bgx.org.uk Differential expression in microarrays We consider the problem of differential expres...
We consider the problem of identifying differentially expressed genes under different conditions usi...
Technical Report. Department of Statistics, University of Washington We consider the problem of iden...
Summary. We propose model-based inference for differential gene expression, using a non-parametric B...
Motivation: An important problem in microarray experiments is the detection of genes that are differ...
We present a Bayesian hierarchical model for detecting differentially expressed genes using a mixtur...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
<div><p>In this paper, the problem of identifying differentially expressed genes under different con...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
We review the use of Bayesian methods for analyzing gene expression data. We focus on methods which ...
In this paper, the problem of identifying differentially expressed genes under different condi-tions...
www.bgx.org.uk Differential expression in microarrays We consider the problem of differential expres...
We consider the problem of identifying differentially expressed genes under different conditions usi...
Technical Report. Department of Statistics, University of Washington We consider the problem of iden...
Summary. We propose model-based inference for differential gene expression, using a non-parametric B...
Motivation: An important problem in microarray experiments is the detection of genes that are differ...
We present a Bayesian hierarchical model for detecting differentially expressed genes using a mixtur...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
<div><p>In this paper, the problem of identifying differentially expressed genes under different con...
A truly functional Bayesian method for detecting temporally differentially expressed genes between t...
We review the use of Bayesian methods for analyzing gene expression data. We focus on methods which ...
In this paper, the problem of identifying differentially expressed genes under different condi-tions...