Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective

Abstract

Objective: The main goal of this work is to measure how lexical regularities in biomedical ontology labelscan be used for the automatic creation of formal relationships between classes, and to evaluate the resultsof applying our approach to the Gene Ontology (GO).Methods: In recent years, we have developed a method for the lexical analysis of regularities in biomedicalontology labels, and we showed that the labels can present a high degree of regularity. In this work, weextend our method with a cross-products extension (CPE) metric, which estimates the potential interest ofa specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matchesin external ontologies. The GO consortium recently enriched the GO by using so-called cross-productextensions. Cross-products are generated by establishing axioms that relate a given GO class with classesfrom the GO or other biomedical ontologies. We apply our method to the GO and study how its lexicalanalysis can identify and reconstruct the cross-products that are defined by the GO consortium.Results: The label of the classes of the GO are highly regular in lexical terms, and the exact matches withlabels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classesthat exhibit regularities have fragments that are classes into two external ontologies that are selected forour experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permitsour method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of28%. The study is completed with an analysis of false positives to explain this precision value.Conclusions: We think that our results support the claim that our lexical approach can contribute to theaxiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineeringof biomedical ontologies.