Relating gene expression data on two-component systems to functional annotations in Escherichia coli.

ABSTRACT:

Background

Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step.

Results

We have developed an algorithm that relates patterns of gene expression in a set of microarray experiments to functional groups in one step. Our only assumption is that patterns co-occur frequently. The effectiveness of the algorithm is demonstrated as part of a study of regulation by two-comp

SUBMITTER: Denton AM 

PROVIDER: S-EPMC2478693 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature