Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies.
Nature Publishing Group
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Alghamdi, S. M., Sundberg, B. A., Sundberg, J. P., Schofield, P., & Hoehndorf, R. (2019). Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies.. Scientific reports, 9 (1), 4025. https://doi.org/10.1038/s41598-019-40368-1
Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multiple ontologies to provide more powerful analytical possibilities. However, it is often not clear how to combine ontologies or how to assess or evaluate the potential design patterns available. Here we use a large and well-characterized dataset of anatomic pathology descriptions from a major study of aging mice. We show how different design patterns based on the MPATH and MA ontologies provide orthogonal axes of analysis, and perform differently in over-representation and semantic similarity applications. We discuss how such a data-driven approach might be used generally to generate and evaluate ontology design patterns.
Animals, Mice, Aging, Algorithms, Semantics, Female, Male, Databases as Topic, Biological Ontologies, Datasets as Topic, Data Science
National Institutes of Health (AG038070-05, for the Shock Aging Center) King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01 and FCC/1/1976-08-01. King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. FCS/1/3657-02-01
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External DOI: https://doi.org/10.1038/s41598-019-40368-1
This record's URL: https://www.repository.cam.ac.uk/handle/1810/289752
Attribution 4.0 International
Licence URL: http://creativecommons.org/licenses/by/4.0/