A Novel Measure for Semantic Similarity Computation of Gene Ontology Terms Using Weighted Aggregation of Information Contents

Abstract

Background: Gene ontology (GO) is a well-structured knowledge of biological terms that describes roles of genes and their products in a standardized and organized controlled vocabulary format. Over the last decade, many measures are developed to exploit GO advantages to determine semantic similarities between biological entities. Using GO ontologies, there are some constraints that existing GO-based semantic similarity measures try to address them. For instance, (1) edges in a GO graph, do not indicate uniform distances and also have different densities, and (2) ignoring term levels in an ontology makes "shallow annotation" drawback, i.e., two terms with a certain distance near the root of GO graph have equal semantic similarity with two terms with the same distance but far from the root.