Abstract
This research explores the feasibility of semantic similarity approaches to supporting predictive tasks in functional genomics. It aims to establish potential relationships between ontology-based similarity of gene products and important functional properties, such as gene expression correlation. Similarity measures based on the information content of the Gene Ontology (GO) were analyzed. Models have been implemented using data obtained from well-known studies in S. cerevisiae. Results suggest that there may exist significant relationships between gene expression correlation and semantic similarity. Analyses of protein complex data show that, in general, there is a significant correlation between the semantic similarity exhibited by a pair of genes and the probability of finding them in the same complex. These results can also be interpreted as an assessment of the quality and consistency of the information represented in the GO.