A visual data mining tool that facilitates reconstruction of transcription regulatory networks.

ABSTRACT:

Background

Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of "guilt by association", where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2)

SUBMITTER: Jupiter DC 

PROVIDER: S-EPMC2248622 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature