利用在线知识源中的食物-药物相互作用丰富 FIDEO 本体。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Rabia Azzi, Georgeta Bordea, Romain Griffier, Jean Noël Nikiema, Fleur Mougin
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引用次数: 0

摘要

有关特定食物与某些药物一起食用时可能发生不良相互作用的文章越来越多,这使得我们很难跟上最新的研究成果。科学文献和专业知识库中的信息相互矛盾,因为对相互作用的描述是非结构化或半结构化的。FIDEO 本体论旨在以结构化的方式整合和表述有关食物-药物相互作用的信息。本文报告了该本体的新版本,其中整合了来自两个在线资源的 1700 多种相互作用:DrugBank和Hedrine。这些食物-药物相互作用在 FIDEO 中以预编译概念的形式呈现,每个概念都指明了所涉及的食物和药物。此外,还回顾了可以回答的能力问题,并讨论了进一步丰富的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enriching the FIDEO ontology with food-drug interactions from online knowledge sources.

The increasing number of articles on adverse interactions that may occur when specific foods are consumed with certain drugs makes it difficult to keep up with the latest findings. Conflicting information is available in the scientific literature and specialized knowledge bases because interactions are described in an unstructured or semi-structured format. The FIDEO ontology aims to integrate and represent information about food-drug interactions in a structured way. This article reports on the new version of this ontology in which more than 1700 interactions are integrated from two online resources: DrugBank and Hedrine. These food-drug interactions have been represented in FIDEO in the form of precompiled concepts, each of which specifies both the food and the drug involved. Additionally, competency questions that can be answered are reviewed, and avenues for further enrichment are discussed.

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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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