Comparison of the Data-based and Gene Ontology-Based Approaches to Cluster Validation Methods for Gene Microarrays

Abstract

The paper presents a comparison of the data-based and gene ontology (GO)-based approaches to cluster validation methods for gene microarray analysis. We apply a homogeneous approach to obtaining metrics from different GO-based similarity measures and a normalization of validation index values, that allows us to compare them to each other as well as to data-based validation indices. The results show strong correlation between both GO-based and data-based validation indices. The results suggest that this may represent an effective tool to support biomedical knowledge discovery tasks based on gene expression data