全面更新 CIDO:基于社区的冠状病毒传染病本体。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yongqun He, Hong Yu, Anthony Huffman, Asiyah Yu Lin, Darren A Natale, John Beverley, Ling Zheng, Yehoshua Perl, Zhigang Wang, Yingtong Liu, Edison Ong, Yang Wang, Philip Huang, Long Tran, Jinyang Du, Zalan Shah, Easheta Shah, Roshan Desai, Hsin-Hui Huang, Yujia Tian, Eric Merrell, William D Duncan, Sivaram Arabandi, Lynn M Schriml, Jie Zheng, Anna Maria Masci, Liwei Wang, Hongfang Liu, Fatima Zohra Smaili, Robert Hoehndorf, Zoë May Pendlington, Paola Roncaglia, Xianwei Ye, Jiangan Xie, Yi-Wei Tang, Xiaolin Yang, Suyuan Peng, Luxia Zhang, Luonan Chen, Junguk Hur, Gilbert S Omenn, Brian Athey, Barry Smith
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引用次数: 0

摘要

背景:当前的 COVID-19 大流行以及之前 2003 年和 2012 年的 SARS/MERS 爆发导致了一系列重大的全球公共卫生危机。我们认为,为了开发有效、安全的疫苗和药物,更好地了解冠状病毒和相关疾病机制,有必要整合大量呈指数级增长的异构冠状病毒数据。本体在基于标准的知识和数据表示、整合、共享和分析方面发挥着重要作用。因此,我们在2020年初启动了基于社区的冠状病毒传染病本体(CIDO)的开发工作:作为一个开放生物医学本体(OBO)库本体,CIDO是开源的,并可与其他现有的OBO本体互操作。CIDO与基本形式本体(Basic Formal Ontology)和病毒性传染病本体(Viral Infectious Disease Ontology)保持一致。CIDO 从 30 多个 OBO 本体中导入了术语。例如,CIDO从蛋白质本体论(Protein Ontology)中导入了所有SARS-CoV-2蛋白质术语,从人类表型本体论(Human Phenotype Ontology)中导入了与COVID-19相关的表型术语,并从疫苗本体论(Vaccine Ontology)中导入了100多个COVID-19疫苗术语(包括授权疫苗和临床试验疫苗)。CIDO系统地描述了SARS-CoV-2病毒的变种及其300多个氨基酸替换,以及300多种诊断试剂盒和方法。CIDO还描述了数百种宿主-冠状病毒蛋白质-蛋白质相互作用(PPI)以及针对这些PPI中蛋白质的药物。CIDO已被用于模拟COVID-19在流行病学等领域的相关现象。在总结网络方法的支持下,通过视觉分析对CIDO的范围进行了评估。CIDO已被用于术语标准化、推理、自然语言处理(NLP)和临床数据整合等多种应用中。我们将CIDO中的氨基酸变体知识用于分析SARS-CoV-2 Delta和Omicron变体之间的差异。CIDO的宿主-冠状病毒PPIs和药物-靶点整合知识还被用于支持COVID-19治疗药物的再利用:CIDO代表了冠状病毒疾病领域的实体和关系,重点关注COVID-19。它支持共享知识表示、数据和元数据标准化与集成,并已在一系列应用中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

Background: The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO) in early 2020.

Results: As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment.

Conclusion: CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

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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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