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Reasoning with bio-ontologies: using relational closure rules to enable practical querying

机译:使用生物本体论进行推理:使用关系封闭规则来进行实际查询

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Motivation: Ontologies have become indispensable in the Life Sciences for managing large amounts of knowledge. The use of logics in ontologies ranges from sound modelling to practical querying of that knowledge, thus adding a considerable value. We conceive reasoning on bio-ontologies as a semi-automated process in three steps: (i) defining a logic-based representation language; (ii) building a consistent ontology using that language; and (iii) exploiting the ontology through querying.Results: Here, we report on how we have implemented this approach to reasoning on the OBO Foundry ontologies within BioGateway, a biological Resource Description Framework knowledge base. By separating the three steps in a manual curation effort on Metarel, a vocabulary that specifies relation semantics, we were able to apply reasoning on a large scale. Starting from an initial 401 million triples, we inferred about 158 million knowledge statements that allow for a myriad of prospective queries, potentially leading to new hypotheses about for instance gene products, processes, interactions or diseases.
机译:动机:本体已成为生命科学中管理大量知识的不可缺少的部分。逻辑在本体中的使用范围从声音建模到对该知识的实际查询,因此增加了可观的价值。我们通过三个步骤将生物本体论的推理视为一个半自动化的过程:(i)定义基于逻辑的表示语言; (ii)使用该语言建立一致的本体;结果:在这里,我们报告了如何在生物资源描述框架知识库BioGateway中的OBO Foundry本体上实现这种推理方法。通过在Metarel(一种指定关系语义的词汇)上进行手动管理的工作中,将三个步骤分开,我们便能够大规模应用推理。从最初的4.01亿个三元组开始,我们推断出约1.58亿条知识陈述,可以进行无数的前瞻性查询,从而可能导致有关基因产品,过程,相互作用或疾病的新假设。

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