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He Y, Yu H, Huffman A, Lin AY, Natale DA, Beverley J, Zheng L, Perl Y, Wang Z, Liu Y, Ong E, Wang Y, Huang P, Tran L, Du J, Shah Z, Shah E, Desai R, Huang HH, Tian Y, Merrell E, Duncan WD, Arabandi S, Schriml LM, Zheng J, Masci AM, Wang L, Liu H, Smaili FZ, Hoehndorf R, Pendlington ZM, Roncaglia P, Ye X, Xie J, Tang YW, Yang X, Peng S, Zhang L, Chen L, Hur J, Omenn GS, Athey B, Smith B. A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology. J Biomed Semantics 2022; 13:25. [PMID: 36271389 PMCID: PMC9585694 DOI: 10.1186/s13326-022-00279-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 09/13/2022] [Indexed: 11/24/2022] Open
Abstract
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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Affiliation(s)
- Yongqun He
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Hong Yu
- People’s Hospital of Guizhou Province, Guiyang, Guizhou China
| | | | - Asiyah Yu Lin
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
- National Center for Ontological Research, Buffalo, NY USA
| | | | - John Beverley
- National Center for Ontological Research, Buffalo, NY USA
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD USA
| | - Ling Zheng
- Computer Science and Software Engineering Department, Monmouth University, West Long Branch, NJ USA
| | - Yehoshua Perl
- Department of Computer Science, New Jersey Institute of Technology, Newark, NJ USA
| | - Zhigang Wang
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Yingtong Liu
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Edison Ong
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Yang Wang
- University of Michigan Medical School, Ann Arbor, MI USA
- People’s Hospital of Guizhou Province, Guiyang, Guizhou China
| | - Philip Huang
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Long Tran
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Jinyang Du
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Zalan Shah
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Easheta Shah
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Roshan Desai
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Hsin-hui Huang
- University of Michigan Medical School, Ann Arbor, MI USA
- National Yang-Ming University, Taipei, Taiwan
| | - Yujia Tian
- Rutgers University, New Brunswick, NJ USA
| | | | | | | | - Lynn M. Schriml
- University of Maryland School of Medicine, Baltimore, MD USA
| | - Jie Zheng
- Department of Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Anna Maria Masci
- Office of Data Science, National Institute of Environmental Health Sciences, Research Triangle Park, NC USA
| | | | | | | | - Robert Hoehndorf
- King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Zoë May Pendlington
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Paola Roncaglia
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Xianwei Ye
- People’s Hospital of Guizhou Province, Guiyang, Guizhou China
| | - Jiangan Xie
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Yi-Wei Tang
- Cepheid, Danaher Diagnostic Platform, Shanghai, China
| | - Xiaolin Yang
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Suyuan Peng
- National Institute of Health Data Science, Peking University, Beijing, China
| | - Luxia Zhang
- National Institute of Health Data Science, Peking University, Beijing, China
| | - Luonan Chen
- Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Junguk Hur
- University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND USA
| | | | - Brian Athey
- University of Michigan Medical School, Ann Arbor, MI USA
| | - Barry Smith
- National Center for Ontological Research, Buffalo, NY USA
- University at Buffalo, Buffalo, NY 14260 USA
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