Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, 48109, USA.
College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, 48109, USA.
J Biomed Semantics. 2024 Jun 19;15(1):12. doi: 10.1186/s13326-024-00312-3.
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.
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.
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.
The VO-cancer GitHub website is: https://github.com/vaccineontology/VO/tree/master/CVO .
癌症疫苗的探索产生了大量的研究，从而产生了多样化的信息。癌症疫苗数据的异质性极大地阻碍了有效的整合和分析。虽然 CanVaxKB 是一个拥有超过 670 种手动注释癌症疫苗的开创性数据库，但重要的是要区分数据库本身并不提供本体中发现的结构化关系和标准化定义。认识到这一点，我们扩展了疫苗本体（VO），以包括 CanVaxKB 中最初未涵盖的那些癌症疫苗，从而增强了 VO 系统地定义和相互关联癌症疫苗的能力。
首先开发并应用了本体设计模式（ODP）来语义表示各种癌症疫苗，捕获它们相关的实体和关系。通过应用 ODP，我们以表格格式生成了癌症疫苗模板，并将其转换为 RDF/OWL 格式，以在 VO 中生成癌症疫苗术语。“12MP 疫苗”被用作癌症疫苗的示例，以演示 ODP 的应用。VO 还重用参考本体术语来表示癌症疾病和疫苗宿主等实体。开发并使用描述逻辑（DL）和 SPARQL 查询脚本根据不同疫苗的特征查询癌症疫苗，并展示 VO 表示的多功能性。此外，本体建模被应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。生成了一个特定于癌症疫苗的 VO 视图，称为“CVO”，其中包含 928 个类，包括 704 种癌症疫苗。CVO 的 OWL 文件可在以下网址公开获取：http://purl.obolibrary.org/obo/vo/cvo.owl，以供共享和应用。
为了促进癌症疫苗数据的标准化、整合和分析，我们扩展了疫苗本体（VO），以系统地对癌症疫苗进行建模和表示。我们还开发了一个管道，以自动将癌症疫苗及其相关术语纳入 VO。这不仅丰富了数据的标准化和整合，还利用本体建模深化了癌症疫苗信息的分析，使研究人员和临床医生最大程度受益。
VO-cancer GitHub 网站是：https://github.com/vaccineontology/VO/tree/master/CVO。
