Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States.
JMIR Med Inform. 2014 Oct 7;2(2):e23. doi: 10.2196/medinform.3387.
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.
Our goal was to design an efficient online platform that enables efficient studies on the conceptual relationships between any medical terms.
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.
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.
onGrid is an efficient tool for querying the UMLS for transitive relations, studying the relationship between medical terms, and generating hypotheses.
统一医学语言系统 (UMLS) 包含许多重要的本体，其中术语通过语义关系连接。对于许多关于生物医学概念之间关系的研究，使用本体和 UMLS 的传递相关信息已被证明是有效的。虽然有一些工具和方法可用于从 UMLS 中提取传递关系，但它们通常对传递关系的长度或数据源的数量有重大限制。
我们的目标是设计一个高效的在线平台，使对任何医学术语之间的概念关系进行有效的研究成为可能。
为了克服现有方法的限制，并促进医学术语之间的概念关系研究，我们开发了一个在线平台 onGrid，该平台支持使用 UMLS 进行高效的传递查询和概念关系研究。该框架使用将自然语言查询转换为 UMLS 概念的最新技术，执行高效的传递查询，并可视化结果路径。它还为两组输入生物医学术语动态构建关系矩阵。因此，我们能够基于关系矩阵对医学术语之间的概念关系进行有效的研究。
onGrid 的优势在于它可以应用于研究任何两组生物医学概念关系以及一组生物医学概念内的关系。我们使用 onGrid 研究在线孟德尔遗传在线数据库 (OMIM) 中的疾病-疾病关系。通过与外部数据库比较毒理学基因组数据库 (CTD) 交叉验证我们的结果，我们证明了 onGrid 对于研究医学术语之间的概念关系是有效的。
onGrid 是查询 UMLS 传递关系、研究医学术语之间关系和生成假设的有效工具。
