A method to identify differential expression profiles of time-course gene data with Fourier transformation.

ABSTRACT:

Background

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis.

Results

This work aims to identify genes that show different gene

SUBMITTER: Kim J 

PROVIDER: S-EPMC4015127 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature