Journal
BIOINFORMATICS
Volume 25, Issue 12, Pages I77-I84Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btp195
Keywords
-
Categories
Funding
- NIGMS NIH HHS [R01 GM083649, R01 GM083649-02, 5R01 GM083649-02] Funding Source: Medline
- NLM NIH HHS [T15 LM009451, 5T15LM009451-02, T15 LM009451-02] Funding Source: Medline
Ask authors/readers for more resources
Motivation: It is important for the quality of biological ontologies that similar concepts be expressed consistently, or univocally. Univocality is relevant for the usability of the ontology for humans, as well as for computational tools that rely on regularity in the structure of terms. However, in practice terms are not always expressed consistently, and we must develop methods for identifying terms that are not univocal so that they can be corrected. Results: We developed an automated transformation-based clustering methodology for detecting terms that use different linguistic conventions for expressing similar semantics. These term sets represent occurrences of univocality violations. Our method was able to identify 67 examples of univocality violations in the Gene Ontology.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available