title: Enabling online studies of conceptual relationships between medical terms: developing an efficient web platform.
abstract: BACKGROUND
  The Unified Medical Language System (UMLS) contains many important ontologies in which terms are connected by semantic relations. For many studies on the relationships between biomedical concepts, the use of transitively associated information from ontologies and the UMLS has been shown to be effective. Although there are a few tools and methods available for extracting transitive relationships from the UMLS, they usually have major restrictions on the length of transitive relations or on the number of data sources.
  
  
  OBJECTIVE
  Our goal was to design an efficient online platform that enables efficient studies on the conceptual relationships between any medical terms.
  
  
  METHODS
  To overcome the restrictions of available methods and to facilitate studies on the conceptual relationships between medical terms, we developed a Web platform, onGrid, that supports efficient transitive queries and conceptual relationship studies using the UMLS. This framework uses the latest technique in converting natural language queries into UMLS concepts, performs efficient transitive queries, and visualizes the result paths. It also dynamically builds a relationship matrix for two sets of input biomedical terms. We are thus able to perform effective studies on conceptual relationships between medical terms based on their relationship matrix.
  
  
  RESULTS
  The advantage of onGrid is that it can be applied to study any two sets of biomedical concept relations and the relations within one set of biomedical concepts. We use onGrid to study the disease-disease relationships in the Online Mendelian Inheritance in Man (OMIM). By crossvalidating our results with an external database, the Comparative Toxicogenomics Database (CTD), we demonstrated that onGrid is effective for the study of conceptual relationships between medical terms.
  
  
  CONCLUSIONS
  onGrid is an efficient tool for querying the UMLS for transitive relations, studying the relationship between medical terms, and generating hypotheses.
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States.
authors.forename: Aaron
authors.identifier: http://orcid.org/0000-0002-2552-7613
authors.initials: A
authors.lastname: Albin
authors.forename: Xiaonan
authors.identifier: http://orcid.org/0000-0001-5337-5031
authors.initials: X
authors.lastname: Ji
authors.forename: Tara B
authors.identifier: http://orcid.org/0000-0001-8688-1782
authors.initials: TB
authors.lastname: Borlawsky
authors.forename: Zhan
authors.identifier: http://orcid.org/0000-0002-0426-0382
authors.initials: Z
authors.lastname: Ye
authors.forename: Simon
authors.identifier: http://orcid.org/0000-0003-2876-2042
authors.initials: S
authors.lastname: Lin
authors.forename: Philip Ro
authors.identifier: http://orcid.org/0000-0002-9532-2998
authors.initials: PR
authors.lastname: Payne
authors.forename: Kun
authors.identifier: http://orcid.org/0000-0002-8530-370X
authors.initials: K
authors.lastname: Huang
authors.forename: Yang
authors.identifier: http://orcid.org/0000-0002-6094-8544
authors.initials: Y
authors.lastname: Xiang
keywords: UMLS; conceptual relationships; ontology