Information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments.

ABSTRACT:

Background

Time-course microarray experiments produce vector gene expression profiles across a series of time points. Clustering genes based on these profiles is important in discovering functional related and co-regulated genes. Early developed clustering algorithms do not take advantage of the ordering in a time-course study, explicit use of which should allow more sensitive detection of genes that display a consistent pattern over time. Peddada et al. 1 proposed a clustering algorithm that can incorporate the temporal ordering using order-restricted statistical inference. This algorithm is, however, very time-consuming and hence inapplicable to most microarray experiments that contain a large number of genes. Its computational burden also imposes difficulty to assess the cluster

SUBMITTER: Liu T 

PROVIDER: S-EPMC2696449 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature