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Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine.
He, Yongqun.
  • He Y; Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA. yongqunh@umich.edu.
Methods Mol Biol ; 2486: 233-244, 2022.
Article in English | MEDLINE | ID: covidwho-1797743
ABSTRACT
The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, and Reusable. Ontology is critical to data integration, sharing, and analysis. Given thousands of ontologies have been developed in the era of artificial intelligence, it is critical to have interoperable ontologies to support standardized data and knowledge presentation and reasoning. For interoperable ontology development, the eXtensible ontology development (XOD) strategy offers four principles including ontology term reuse, semantic alignment, ontology design pattern usage, and community extensibility. Many software programs are available to help implement these principles. As a demonstration, the XOD strategy is applied to developing the interoperable Coronavirus Infectious Disease Ontology (CIDO). Various applications of interoperable ontologies, such as COVID-19 and kidney precision medicine research, are also introduced in this chapter.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biological Ontologies / COVID-19 Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2265-0_12

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biological Ontologies / COVID-19 Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2265-0_12