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

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 TianEric Merrell, William D Duncan, Sivaram Arabandi, Lynn M Schriml, Jie Zheng, Anna Maria Masci, Liwei Wang, Hongfang Liu, Fatima Z. 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

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.
Original languageEnglish (US)
JournalJournal of biomedical semantics
Volume13
Issue number1
DOIs
StatePublished - Oct 21 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-24
Acknowledgements: We acknowledge Dr. Melissa A Haendel’s contribution as a source of ontological content and the N3C use case. This project is supported by NIH grants 1UH2AI132931 (to YH) and 1U24AI171008 (to YH and JH); U24CA210967 and P30ES017885 (to GSO); R01GM080646, 1UL1TR001412, 1U24CA199374, and 1T15LM012495 (to BS); the National Natural Science Foundation of China 61801067 (to JX); the Natural Science Foundation of Chongqing CSTC2018JCYJAX0243 (to JX); the non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences 2019PT320003 (to HY); and Undergraduate Research Opportunity Program (UROP) and University of Michigan Medical School Global Reach award (to YH). The work of ZMP and PR was supported by Open Targets (OTAR005). Publication costs are paid by a discretionary fund from Dr. William King, the director of the Unit for Laboratory Animal Medicine (ULAM) in the University of Michigan, Ann Arbor, MI, USA.

ASJC Scopus subject areas

  • Health Informatics
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications

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