背景:癌症疫苗的探索已经产生了大量的研究,导致不同的信息收集。癌症疫苗数据的异质性严重阻碍了有效的整合和分析。虽然CanVaxKB是670多种手动注释癌症疫苗的开创性数据库,区分数据库很重要,靠自己,不提供本体中的结构化关系和标准化定义。认识到这一点,我们扩大了疫苗本体论(VO),包括CanVaxKB中最初未涵盖的癌症疫苗,增强VO系统定义和关联癌症疫苗的能力。
结果:首先开发了一种本体设计模式(ODP),并将其应用于语义表示各种癌症疫苗,捕获其关联的实体和关系。通过应用ODP,我们生成了表格格式的癌症疫苗模板,并将其转换为RDF/OWL格式,用于生成VO中的癌症疫苗术语.“12MP疫苗”被用作癌症疫苗的实例以证明ODP的应用。VO还重用参考本体术语来表示诸如癌症疾病和疫苗宿主等实体。开发了描述逻辑(DL)和SPARQL查询脚本,用于根据不同疫苗的特征查询癌症疫苗,并证明了VO表示的多功能性。此外,本体论建模用于说明癌症疫苗相关概念和研究,以进行深入的癌症疫苗分析。癌症疫苗特异性VO视图,称为“CVO,“生成了\”,它包含928类,包括704种癌症疫苗。CVOOWL文件可在http://purl上公开获得。obolibrary.org/obo/vo/cvo.猫头鹰,用于共享和应用程序。
结论:为了促进标准化,一体化,和癌症疫苗数据分析,我们将疫苗本体论(VO)扩展到系统建模和代表癌症疫苗.我们还开发了一个管道,以自动将癌症疫苗和相关术语纳入VO。这不仅丰富了数据的标准化和集成化,而且还利用本体论建模来加深对癌症疫苗信息的分析,为研究人员和临床医生带来最大利益。
背景:VO-cancerGitHub网站是:https://github.com/vaccineontology/VO/tree/master/CVO。
BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity of cancer vaccine data significantly impedes effective integration and analysis. While CanVaxKB serves as a pioneering database for over 670 manually annotated cancer vaccines, it is important to distinguish that a database, on its own, does not offer the structured relationships and standardized definitions found in an ontology. Recognizing this, we expanded the Vaccine Ontology (VO) to include those cancer vaccines present in CanVaxKB that were not initially covered, enhancing VO\'s capacity to systematically define and interrelate cancer vaccines.
RESULTS: An ontology design pattern (ODP) was first developed and applied to semantically represent various cancer vaccines, capturing their associated entities and relations. By applying the ODP, we generated a cancer vaccine template in a tabular format and converted it into the RDF/OWL format for generation of cancer vaccine terms in the VO. \'12MP vaccine\' was used as an example of cancer vaccines to demonstrate the application of the ODP. VO also reuses reference ontology terms to represent entities such as cancer diseases and vaccine hosts. Description Logic (DL) and SPARQL query scripts were developed and used to query for cancer vaccines based on different vaccine\'s features and to demonstrate the versatility of the VO representation. Additionally, ontological modeling was applied to illustrate cancer vaccine related concepts and studies for in-depth cancer vaccine analysis. A cancer vaccine-specific VO view, referred to as \"CVO,\" was generated, and it contains 928 classes including 704 cancer vaccines. The CVO OWL file is publicly available on: http://purl.obolibrary.org/obo/vo/cvo.owl , for sharing and applications.
CONCLUSIONS: To facilitate the standardization, integration, and analysis of cancer vaccine data, we expanded the Vaccine Ontology (VO) to systematically model and represent cancer vaccines. We also developed a pipeline to automate the inclusion of cancer vaccines and associated terms in the VO. This not only enriches the data\'s standardization and integration, but also leverages ontological modeling to deepen the analysis of cancer vaccine information, maximizing benefits for researchers and clinicians.
BACKGROUND: The VO-cancer GitHub website is: https://github.com/vaccineontology/VO/tree/master/CVO .