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Abstract：
BACKGROUND: Ontologies are key enabling technologies for the Semantic Web. The Web Ontology Language (OWL) is a semantic markup language for publishing and sharing ontologies.
OBJECTIVE: The supply of customizable, computable, and formally represented molecular genetics information and health information, via electronic health record (EHR) interfaces, can play a critical role in achieving precision medicine. In this study, we used cystic fibrosis as an example to build an Ontology-based Knowledge Base prototype on Cystic Fibrobis (OntoKBCF) to supply such information via an EHR prototype. In addition, we elaborate on the construction and representation principles, approaches, applications, and representation challenges that we faced in the construction of OntoKBCF. The principles and approaches can be referenced and applied in constructing other ontology-based domain knowledge bases.
METHODS: First, we defined the scope of OntoKBCF according to possible clinical information needs about cystic fibrosis on both a molecular level and a clinical phenotype level. We then selected the knowledge sources to be represented in OntoKBCF. We utilized top-to-bottom content analysis and bottom-up construction to build OntoKBCF. Protégé-OWL was used to construct OntoKBCF. The construction principles included (1) to use existing basic terms as much as possible; (2) to use intersection and combination in representations; (3) to represent as many different types of facts as possible; and (4) to provide 2-5 examples for each type. HermiT 1.3.8.413 within Protégé-5.1.0 was used to check the consistency of OntoKBCF.
RESULTS: OntoKBCF was constructed successfully, with the inclusion of 408 classes, 35 properties, and 113 equivalent classes. OntoKBCF includes both atomic concepts (such as amino acid) and complex concepts (such as \"adolescent female cystic fibrosis patient\") and their descriptions. We demonstrated that OntoKBCF could make customizable molecular and health information available automatically and usable via an EHR prototype. The main challenges include the provision of a more comprehensive account of different patient groups as well as the representation of uncertain knowledge, ambiguous concepts, and negative statements and more complicated and detailed molecular mechanisms or pathway information about cystic fibrosis.
CONCLUSIONS: Although cystic fibrosis is just one example, based on the current structure of OntoKBCF, it should be relatively straightforward to extend the prototype to cover different topics. Moreover, the principles underpinning its development could be reused for building alternative human monogenetic diseases knowledge bases.
OBJECTIVE: The supply of customizable, computable, and formally represented molecular genetics information and health information, via electronic health record (EHR) interfaces, can play a critical role in achieving precision medicine. In this study, we used cystic fibrosis as an example to build an Ontology-based Knowledge Base prototype on Cystic Fibrobis (OntoKBCF) to supply such information via an EHR prototype. In addition, we elaborate on the construction and representation principles, approaches, applications, and representation challenges that we faced in the construction of OntoKBCF. The principles and approaches can be referenced and applied in constructing other ontology-based domain knowledge bases.
METHODS: First, we defined the scope of OntoKBCF according to possible clinical information needs about cystic fibrosis on both a molecular level and a clinical phenotype level. We then selected the knowledge sources to be represented in OntoKBCF. We utilized top-to-bottom content analysis and bottom-up construction to build OntoKBCF. Protégé-OWL was used to construct OntoKBCF. The construction principles included (1) to use existing basic terms as much as possible; (2) to use intersection and combination in representations; (3) to represent as many different types of facts as possible; and (4) to provide 2-5 examples for each type. HermiT 1.3.8.413 within Protégé-5.1.0 was used to check the consistency of OntoKBCF.
RESULTS: OntoKBCF was constructed successfully, with the inclusion of 408 classes, 35 properties, and 113 equivalent classes. OntoKBCF includes both atomic concepts (such as amino acid) and complex concepts (such as \"adolescent female cystic fibrosis patient\") and their descriptions. We demonstrated that OntoKBCF could make customizable molecular and health information available automatically and usable via an EHR prototype. The main challenges include the provision of a more comprehensive account of different patient groups as well as the representation of uncertain knowledge, ambiguous concepts, and negative statements and more complicated and detailed molecular mechanisms or pathway information about cystic fibrosis.
CONCLUSIONS: Although cystic fibrosis is just one example, based on the current structure of OntoKBCF, it should be relatively straightforward to extend the prototype to cover different topics. Moreover, the principles underpinning its development could be reused for building alternative human monogenetic diseases knowledge bases.
摘要：
背景：本体是语义Web的关键使能技术。Web本体语言（OWL）是一种用于发布和共享本体的语义标记语言。
目标：可定制的供应，可计算，正式代表分子遗传学信息和健康信息，通过电子健康记录(EHR)接口，可以在实现精准医疗方面发挥关键作用。在这项研究中,我们以囊性纤维化为例,构建了基于Ontology的CysticFibrobis知识库原型(OntoKBCF),通过EHR原型提供此类信息.此外,我们详细阐述了构造和表示原则，方法，应用程序,以及我们在OntoKBCF建设中面临的代表性挑战。这些原理和方法可以在构建其他基于本体的领域知识库时参考和应用。
方法：首先，我们根据囊性纤维化在分子水平和临床表型水平上可能的临床信息需求定义了OntoKBCF的范围.然后，我们选择了要在OntoKBCF中表示的知识源。我们利用自上而下的内容分析和自下而上的构建来构建OntoKBCF。Protégé-OWL用于构建OntoKBCF。构造原则包括（1）尽可能使用现有的基本术语；（2）在表示中使用交叉和组合；（3）表示尽可能多的不同类型的事实；（4）为每种类型提供2-5个示例。Protégé-5.1.0中的HermiT1.3.8.413用于检查OntoKBCF的一致性。
结果：成功构建了OntoKBCF，包含408个类，35个属性，和113个等效类。OntoKBCF包括原子概念（例如氨基酸）和复杂概念（例如“青春期女性囊性纤维化患者”）及其描述。我们证明了OntoKBCF可以通过EHR原型自动提供和使用可定制的分子和健康信息。主要挑战包括提供对不同患者群体的更全面的说明以及不确定知识的表示，模棱两可的概念，和负面陈述以及关于囊性纤维化的更复杂和详细的分子机制或通路信息。
结论：虽然囊性纤维化只是一个例子，基于OntoKBCF的当前结构，扩展原型以涵盖不同主题应该相对简单。此外，支撑其发展的原则可以重复使用，用于建立替代的人类单基因疾病知识库。
目标：可定制的供应，可计算，正式代表分子遗传学信息和健康信息，通过电子健康记录(EHR)接口，可以在实现精准医疗方面发挥关键作用。在这项研究中,我们以囊性纤维化为例,构建了基于Ontology的CysticFibrobis知识库原型(OntoKBCF),通过EHR原型提供此类信息.此外,我们详细阐述了构造和表示原则，方法，应用程序,以及我们在OntoKBCF建设中面临的代表性挑战。这些原理和方法可以在构建其他基于本体的领域知识库时参考和应用。
方法：首先，我们根据囊性纤维化在分子水平和临床表型水平上可能的临床信息需求定义了OntoKBCF的范围.然后，我们选择了要在OntoKBCF中表示的知识源。我们利用自上而下的内容分析和自下而上的构建来构建OntoKBCF。Protégé-OWL用于构建OntoKBCF。构造原则包括（1）尽可能使用现有的基本术语；（2）在表示中使用交叉和组合；（3）表示尽可能多的不同类型的事实；（4）为每种类型提供2-5个示例。Protégé-5.1.0中的HermiT1.3.8.413用于检查OntoKBCF的一致性。
结果：成功构建了OntoKBCF，包含408个类，35个属性，和113个等效类。OntoKBCF包括原子概念（例如氨基酸）和复杂概念（例如“青春期女性囊性纤维化患者”）及其描述。我们证明了OntoKBCF可以通过EHR原型自动提供和使用可定制的分子和健康信息。主要挑战包括提供对不同患者群体的更全面的说明以及不确定知识的表示，模棱两可的概念，和负面陈述以及关于囊性纤维化的更复杂和详细的分子机制或通路信息。
结论：虽然囊性纤维化只是一个例子，基于OntoKBCF的当前结构，扩展原型以涵盖不同主题应该相对简单。此外，支撑其发展的原则可以重复使用，用于建立替代的人类单基因疾病知识库。
