Non-Lattice Subgraphs (NLSs) are graph fragments of a terminology which violates the lattice property, a desirable property for a well-formed terminology. They have been proven to be useful in identifying inconsistencies in biomedical terminologies. Similar NLSs may denote similar inconsistencies that may suggest possibly similar remediations. Therefore, we investigate a structural-semantic-based approach to identify similar NLSs in the Gene Ontology (GO). For an input NLS, we first obtain all its isomorphic NLSs. Then, we compare each concept of the input NLS with the corresponding concept in an isomorphic NLS and then compute a similarity score for the two NLSs. Applying this approach to 10 different structures of NLSs in GO, we found that 38.43% (910/2368) of NLSs have at least one similar NLS. We also observed some interesting lexical patterns frequently existing in similar NLSs. Our approach may be applicable to other biomedical terminologies for identifying similar NLSs.
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A Comparison of Exhaustive and Non-lattice-based Methods for Auditing Hierarchical Relations in Gene Ontology
Uncovering and fixing errors in biomedical terminologies is essential so that they provide accurate knowledge to downstream applications that rely on them. Non-lattice-based methods have been applied to identify various kinds of inconsistencies in different biomedical terminologies. In previous work, we have introduced two inference-based approaches that were applied in an exhaustive manner to audit hierarchical relations in the Gene Ontology: (1) Lexical-based inference framework, and (2) Subsumption-based sub-term inference framework. However, it is unclear how effective these exhaustive approaches perform compared with their corresponding non-lattice-based approaches. Therefore, in this paper, we implement the non-lattice versions of these two exhaustive approaches, and perform a comprehensive comparison between non-lattice-based and exhaustive approaches to audit the Gene Ontology. The domain expert evaluations performed for the two exhaustive approaches are leveraged to evaluate the non-lattice versions. The results indicate that the non-lattice versions have increased precision than their exhaustive counterparts even though they do not capture some of the potential inconsistencies that the exhaustive approaches identify.
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- Award ID(s):
- 1931134
- PAR ID:
- 10367859
- Date Published:
- Journal Name:
- AMIA 2021 Annual Symposium
- Page Range / eLocation ID:
- 177-186
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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