Microarray Time Course Gene Expresssion Studies: Some Problems and Statistical Methods

Tuesday, September 30, 2003 - 11:00am - 11:25am
Keller 3-180
Hongzhe Li (University of California)
Since many biological systems and processes in human health and diseases are dynamic systems, genome-wide gene expression levels measured over time can often provide more insights into such systems. Important examples include developmental process, cell cycle process and regulation of circadian rhythm. The noisy nature of microarray data and the potential dependency of the gene expression measurements over time makes analysis of such micorarray time course (MTC) gene expression data challenging. In this talk, I will present some problems and statistical methods for analyzing such MTC gene expression data. Some details will be given on the methods of identifying genes with different time course expression profiles and the methods of identifying periodically regulated genes.