Validation and functional annotation of expression-based clusters based on gene ontology.

ABSTRACT:

Background

The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in the context of other available functional genomics data, such as existing bio-ontologies, has already provided substantial improvement for detecting and categorizing genes of interest. One common approach is to look for functional annotations that are significantly enriched within a group or cluster of genes, as compared to a reference group.

Results

In this work, we suggest the information-theoretic concept of mutual information to investigate the relationship between groups of genes, as given by data-driven clustering, and their respective functional categories. Drawing upon related approaches (Gibb

SUBMITTER: Steuer R 

PROVIDER: S-EPMC1586215 | biostudies-literature | 2006 Aug

REPOSITORIES: biostudies-literature