IrGO: Iranian traditional medicine General Ontology and knowledge base.

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ayeh Naghizadeh, Mahdi Salamat, Donya Hamzeian, Shaghayegh Akbari, Hossein Rezaeizadeh, Mahdi Alizadeh Vaghasloo, Reza Karbalaei, Mehdi Mirzaie, Mehrdad Karimi, Mohieddin Jafari
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引用次数: 3

Abstract

Background: Iranian traditional medicine, also known as Persian Medicine, is a holistic school of medicine with a long prolific history. It describes numerous concepts and the relationships between them. However, no unified language system has been proposed for the concepts of this medicine up to the present time. Considering the extensive terminology in the numerous textbooks written by the scholars over centuries, comprehending the totality of concepts is obviously a very challenging task. To resolve this issue, overcome the obstacles, and code the concepts in a reusable manner, constructing an ontology of the concepts of Iranian traditional medicine seems a necessity.

Construction and content: Makhzan al-Advieh, an encyclopedia of materia medica compiled by Mohammad Hossein Aghili Khorasani, was selected as the resource to create an ontology of the concepts used to describe medicinal substances. The steps followed to accomplish this task included (1) compiling the list of classes via examination of textbooks, and text mining the resource followed by manual review to ensure comprehensiveness of extracted terms; (2) arranging the classes in a taxonomy; (3) determining object and data properties; (4) specifying annotation properties including ID, labels (English and Persian), alternative terms, and definitions (English and Persian); (5) ontology evaluation. The ontology was created using Protégé with adherence to the principles of ontology development provided by the Open Biological and Biomedical Ontology (OBO) foundry.

Utility and discussion: The ontology was finalized with inclusion of 3521 classes, 15 properties, and 20,903 axioms in the Iranian traditional medicine General Ontology (IrGO) database, freely available at http://ir-go.net/ . An indented list and an interactive graph view using WebVOWL were used to visualize the ontology. All classes were linked to their instances in UNaProd database to create a knowledge base of ITM materia medica.

Conclusion: We constructed an ontology-based knowledge base of ITM concepts in the domain of materia medica to help offer a shared and common understanding of this concept, enable reuse of the knowledge, and make the assumptions explicit. This ontology will aid Persian medicine practitioners in clinical decision-making to select drugs. Extending IrGO will bridge the gap between traditional and conventional schools of medicine, helping guide future research in the process of drug discovery.

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IrGO:伊朗传统医学通用本体和知识库。
背景:伊朗传统医学,也被称为波斯医学,是一个具有悠久多产历史的整体医学流派。它描述了许多概念以及它们之间的关系。然而,到目前为止,还没有一个统一的语言系统来描述这种药物的概念。考虑到几个世纪以来学者们编写的大量教科书中广泛的术语,理解概念的总体显然是一项非常具有挑战性的任务。为了解决这一问题,克服障碍,并以可重用的方式对概念进行编码,似乎有必要构建伊朗传统医学概念的本体。结构和内容:Mohammad Hossein Aghili Khorasani编写的《Makhzan al-Advieh》是一本本草百科全书,被选为创建用于描述药物物质的概念本体论的资源。完成这项任务的步骤包括:(1)通过对教科书的检查来编制类别列表,然后对资源进行文本挖掘,然后进行人工检查,以确保提取的术语的全面性;(二)将类编成分类法;(3)确定对象和数据属性;(4)指定标注属性,包括ID、标签(英语和波斯语)、备选术语和定义(英语和波斯语);(5)本体评价。这个本体是使用protp - 创建的,遵循了开放生物和生物医学本体(OBO)代工提供的本体开发原则。实用程序和讨论:在伊朗传统医学通用本体(IrGO)数据库中,最终确定了包含3521个类,15个属性和20,903个公理的本体,可在http://ir-go.net/免费获得。使用缩进列表和WebVOWL交互式图形视图对本体进行可视化。所有类别都与其在UNaProd数据库中的实例相关联,以创建一个信息技术管理药物资料知识库。结论:我们构建了一个基于本体论的本草领域ITM概念知识库,以帮助提供对该概念的共享和共同理解,实现知识的重用,并使假设明确。该本体将帮助波斯医学从业者在临床决策中选择药物。扩大IrGO将弥合传统医学院和传统医学院之间的差距,帮助指导药物发现过程中的未来研究。
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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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