Department of Biomedical Informatics, Columbia University, Vanderbilt Clinic, New York, NY 10032, United States.
J Biomed Inform. 2010 Aug;43(4):608-12. doi: 10.1016/j.jbi.2010.01.007. Epub 2010 Feb 6.
Biological ontologies are now being widely used for annotation, sharing and retrieval of the biological data. Many of these ontologies are hosted under the umbrella of the Open Biological Ontologies Foundry. In order to support interterminology mapping, composite terms in these ontologies need to be translated into atomic or primitive terms in other, orthogonal ontologies, for example, gluconeogenesis (biological process term) to glucose (chemical ontology term). Identifying such decompositional ontology translations is a challenging problem. In this paper, we propose a network-theoretic approach based on the structure of the integrated OBO relationship graph. We use a network-theoretic measure, called the clustering coefficient, to find relevant atomic terms in the neighborhood of a composite term. By eliminating the existing GO to ChEBI Ontology mappings from OBO, we evaluate whether the proposed approach can re-identify the corresponding relationships. The results indicate that the network structure provides strong cues for decompositional ontology translation and the existing relationships can be used to identify new translations.
生物本体现在被广泛用于生物数据的注释、共享和检索。其中许多本体都由开放生物本体基金会托管。为了支持术语间映射，这些本体中的组合术语需要被翻译为其他正交本体中的原子或基本术语，例如，糖异生（生物过程术语）到葡萄糖（化学本体术语）。识别这种分解式本体翻译是一个具有挑战性的问题。在本文中，我们提出了一种基于整合 OBO 关系图结构的网络理论方法。我们使用一种网络理论度量，称为聚类系数，来找到复合术语附近的相关原子术语。通过从 OBO 中删除现有的 GO 到 ChEBI 本体映射，我们评估了所提出的方法是否可以重新识别相应的关系。结果表明，网络结构为分解式本体翻译提供了强有力的线索，并且可以利用现有的关系来识别新的翻译。
