Many important biological events occur in a temporal fashion. Microarray time course
experiments measure gene expression levels dynamically for thousands of genes …

In this paper we derive one-and two-sample multivariate empirical Bayes statistics (the MB-
statistics) to rank genes in order of interest from longitudinal replicated developmental …

Background Microarray gene expression time-course experiments provide the opportunity to
observe the evolution of transcriptional programs that cells use to respond to internal and …

Time course microarray experiments designed to characterize the dynamic regulation of
gene expression in biological systems are becoming increasingly important. One critical …

Time course studies of gene expression are essential in biomedical research to understand
biological phenomena that evolve in a temporal fashion. Microarray technology makes it …

Among the first microarray experiments were those measuring expression over time, and
time course experiments remain common. Most methods to analyze time course data …

Consider the ranking of genes using data from replicated microarray time course
experiments, where there are multiple biological conditions, and the genes of interest are …

Time course gene expression experiments have proved valuable in a variety of studies.
Their unique data structure and the diversity of tasks often associated with them present new …

Background Gene expression levels in a given cell can be influenced by different factors,
namely pharmacological or medical treatments. The response to a given stimulus is usually …

A truly functional Bayesian method for detecting temporally differentially expressed genes
between two experimental conditions is presented. The method distinguishes between two …