Matching disease and phenotype ontologies in the ontology alignment evaluation initiative

Journal of Biomedical Semantics

Scott Markel¹  Ernesto Jiménez-Ruiz²  Arild Waaler²  Yasmin Alam-Faruque³  James Malone⁴  Peter Woollard⁵  Andrea Splendiani⁶  Martin Koch⁷  Ian Harrow⁸  Martin Romacker⁹ 

[1] BIOVIA 3DS;Department of Informatics, University of Oslo;Eagle Genomics;FactBio;GlaxoSmithKline R&D;Novartis;OSTHUS;Pistoia Alliance Ontologies Mapping Project;Roche Pharma Research and Early Development, pRED Informatics, Roche Innovation Center;

关键词: Biomedical ontology;    Ontology alignment;    OAE;    Evaluation;    Phenotype;    Disease;   

DOI  :  10.1186/s13326-017-0162-9

来源: DOAJ

【 摘 要 】

Abstract Background The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Results Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Conclusions Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

【 授权许可】

Unknown