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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 dise...

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Autores principales: He, Yongqun, Yu, Hong, Huffman, Anthony, Lin, Asiyah Yu, Natale, Darren A., Beverley, John, Zheng, Ling, Perl, Yehoshua, Wang, Zhigang, Liu, Yingtong, Ong, Edison, Wang, Yang, Huang, Philip, Tran, Long, Du, Jinyang, Shah, Zalan, Shah, Easheta, Desai, Roshan, Huang, Hsin-hui, Tian, Yujia, Merrell, Eric, Duncan, William D., Arabandi, Sivaram, Schriml, Lynn M., Zheng, Jie, Masci, Anna Maria, Wang, Liwei, Liu, Hongfang, Smaili, Fatima Zohra, Hoehndorf, Robert, Pendlington, Zoë May, Roncaglia, Paola, Ye, Xianwei, Xie, Jiangan, Tang, Yi-Wei, Yang, Xiaolin, Peng, Suyuan, Zhang, Luxia, Chen, Luonan, Hur, Junguk, Omenn, Gilbert S., Athey, Brian, Smith, Barry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585694/
https://www.ncbi.nlm.nih.gov/pubmed/36271389
http://dx.doi.org/10.1186/s13326-022-00279-z
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author He, Yongqun
Yu, Hong
Huffman, Anthony
Lin, Asiyah Yu
Natale, Darren A.
Beverley, John
Zheng, Ling
Perl, Yehoshua
Wang, Zhigang
Liu, Yingtong
Ong, Edison
Wang, Yang
Huang, Philip
Tran, Long
Du, Jinyang
Shah, Zalan
Shah, Easheta
Desai, Roshan
Huang, Hsin-hui
Tian, Yujia
Merrell, Eric
Duncan, William D.
Arabandi, Sivaram
Schriml, Lynn M.
Zheng, Jie
Masci, Anna Maria
Wang, Liwei
Liu, Hongfang
Smaili, Fatima Zohra
Hoehndorf, Robert
Pendlington, Zoë May
Roncaglia, Paola
Ye, Xianwei
Xie, Jiangan
Tang, Yi-Wei
Yang, Xiaolin
Peng, Suyuan
Zhang, Luxia
Chen, Luonan
Hur, Junguk
Omenn, Gilbert S.
Athey, Brian
Smith, Barry
author_facet He, Yongqun
Yu, Hong
Huffman, Anthony
Lin, Asiyah Yu
Natale, Darren A.
Beverley, John
Zheng, Ling
Perl, Yehoshua
Wang, Zhigang
Liu, Yingtong
Ong, Edison
Wang, Yang
Huang, Philip
Tran, Long
Du, Jinyang
Shah, Zalan
Shah, Easheta
Desai, Roshan
Huang, Hsin-hui
Tian, Yujia
Merrell, Eric
Duncan, William D.
Arabandi, Sivaram
Schriml, Lynn M.
Zheng, Jie
Masci, Anna Maria
Wang, Liwei
Liu, Hongfang
Smaili, Fatima Zohra
Hoehndorf, Robert
Pendlington, Zoë May
Roncaglia, Paola
Ye, Xianwei
Xie, Jiangan
Tang, Yi-Wei
Yang, Xiaolin
Peng, Suyuan
Zhang, Luxia
Chen, Luonan
Hur, Junguk
Omenn, Gilbert S.
Athey, Brian
Smith, Barry
author_sort He, Yongqun
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13326-022-00279-z.
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spelling pubmed-95856942022-10-22 A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology He, Yongqun Yu, Hong Huffman, Anthony Lin, Asiyah Yu Natale, Darren A. Beverley, John Zheng, Ling Perl, Yehoshua Wang, Zhigang Liu, Yingtong Ong, Edison Wang, Yang Huang, Philip Tran, Long Du, Jinyang Shah, Zalan Shah, Easheta Desai, Roshan Huang, Hsin-hui Tian, Yujia Merrell, Eric Duncan, William D. Arabandi, Sivaram Schriml, Lynn M. Zheng, Jie Masci, Anna Maria Wang, Liwei Liu, Hongfang Smaili, Fatima Zohra Hoehndorf, Robert Pendlington, Zoë May Roncaglia, Paola Ye, Xianwei Xie, Jiangan Tang, Yi-Wei Yang, Xiaolin Peng, Suyuan Zhang, Luxia Chen, Luonan Hur, Junguk Omenn, Gilbert S. Athey, Brian Smith, Barry J Biomed Semantics Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13326-022-00279-z. BioMed Central 2022-10-21 /pmc/articles/PMC9585694/ /pubmed/36271389 http://dx.doi.org/10.1186/s13326-022-00279-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
He, Yongqun
Yu, Hong
Huffman, Anthony
Lin, Asiyah Yu
Natale, Darren A.
Beverley, John
Zheng, Ling
Perl, Yehoshua
Wang, Zhigang
Liu, Yingtong
Ong, Edison
Wang, Yang
Huang, Philip
Tran, Long
Du, Jinyang
Shah, Zalan
Shah, Easheta
Desai, Roshan
Huang, Hsin-hui
Tian, Yujia
Merrell, Eric
Duncan, William D.
Arabandi, Sivaram
Schriml, Lynn M.
Zheng, Jie
Masci, Anna Maria
Wang, Liwei
Liu, Hongfang
Smaili, Fatima Zohra
Hoehndorf, Robert
Pendlington, Zoë May
Roncaglia, Paola
Ye, Xianwei
Xie, Jiangan
Tang, Yi-Wei
Yang, Xiaolin
Peng, Suyuan
Zhang, Luxia
Chen, Luonan
Hur, Junguk
Omenn, Gilbert S.
Athey, Brian
Smith, Barry
A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title_full A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title_fullStr A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title_full_unstemmed A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title_short A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
title_sort comprehensive update on cido: the community-based coronavirus infectious disease ontology
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585694/
https://www.ncbi.nlm.nih.gov/pubmed/36271389
http://dx.doi.org/10.1186/s13326-022-00279-z
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