Document Type

Article

Publication Date

3-11-2019

Keywords

JMG

JAX Source

Sci Rep 2019 Mar 11; 9(1):4025

PMID

30858527

DOI

https://doi.org/10.1038/s41598-019-40368-1

Grant

AG038070

Abstract

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.

Comments

This open access article is licensed under a Creative Commons Attribution 4.0 International License

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