title: The next generation of similarity measures that fully explore the semantics in biomedical ontologies.
abstract: There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.
authors.affiliation: Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisboa 1749-016, Portugal.
authors.forename: Francisco M
authors.initials: FM
authors.lastname: Couto
authors.forename: H Sofia
authors.initials: HS
authors.lastname: Pinto
mesh_terms: D000595:Amino Acid Sequence; D001483:Base Sequence; D064229:Biological Ontologies; D019295:Computational Biology / Q000379:methods*; D063990:Gene Ontology; D006801:Humans; D016415:Sequence Alignment / Q000706:statistics & numerical data; D040681:Structural Homology, Protein; D009626:Terminology as Topic