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 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

doi:10.1186/s13326-022-00279-z

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 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

Digital Health Sciences

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Article number	25
Journal	Journal of Biomedical Semantics
Volume	13
Issue number	1
DOIs	https://doi.org/10.1186/s13326-022-00279-z
State	Published - Dec 2022

Keywords

COVID-19
Coronavirus
Diagnosis
Drug repurposing
Ontology
Phenotype
SARS-CoV-2
Vaccine

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Health Informatics
Computer Networks and Communications

Access to Document

10.1186/s13326-022-00279-z

Cite this

He, Y., Yu, H., Huffman, A., Lin, A. Y., Natale, D. A., 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, H. H., ... Smith, B. (2022). A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology. Journal of Biomedical Semantics, 13(1), Article 25. https://doi.org/10.1186/s13326-022-00279-z

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 2022, 'A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology', Journal of Biomedical Semantics, vol. 13, no. 1, 25. https://doi.org/10.1186/s13326-022-00279-z

@article{51f8a7569b9843f39080b82fef73d368,

title = "A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology",

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.",

keywords = "COVID-19, Coronavirus, Diagnosis, Drug repurposing, Ontology, Phenotype, SARS-CoV-2, Vaccine",

author = "Yongqun He and Hong Yu and Anthony Huffman and Lin, {Asiyah Yu} and Natale, {Darren A.} and John Beverley and Ling Zheng and Yehoshua Perl and Zhigang Wang and Yingtong Liu and Edison Ong and Yang Wang and Philip Huang and Long Tran and Jinyang Du and Zalan Shah and Easheta Shah and Roshan Desai and Huang, {Hsin hui} and Yujia Tian and Eric Merrell and Duncan, {William D.} and Sivaram Arabandi and Schriml, {Lynn M.} and Jie Zheng and Masci, {Anna Maria} and Liwei Wang and Hongfang Liu and Smaili, {Fatima Zohra} and Robert Hoehndorf and Pendlington, {Zo{\"e} May} and Paola Roncaglia and Xianwei Ye and Jiangan Xie and Tang, {Yi Wei} and Xiaolin Yang and Suyuan Peng and Luxia Zhang and Luonan Chen and Junguk Hur and Omenn, {Gilbert S.} and Brian Athey and Barry Smith",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1186/s13326-022-00279-z",

language = "English (US)",

volume = "13",

journal = "Journal of Biomedical Semantics",

issn = "2041-1480",

publisher = "BioMed Central",

number = "1",

}

TY - JOUR

T1 - A comprehensive update on CIDO

T2 - the community-based coronavirus infectious disease ontology

AU - He, Yongqun

AU - Yu, Hong

AU - Huffman, Anthony

AU - Lin, Asiyah Yu

AU - Natale, Darren A.

AU - Beverley, John

AU - Zheng, Ling

AU - Perl, Yehoshua

AU - Wang, Zhigang

AU - Liu, Yingtong

AU - Ong, Edison

AU - Wang, Yang

AU - Huang, Philip

AU - Tran, Long

AU - Du, Jinyang

AU - Shah, Zalan

AU - Shah, Easheta

AU - Desai, Roshan

AU - Huang, Hsin hui

AU - Tian, Yujia

AU - Merrell, Eric

AU - Duncan, William D.

AU - Arabandi, Sivaram

AU - Schriml, Lynn M.

AU - Zheng, Jie

AU - Masci, Anna Maria

AU - Wang, Liwei

AU - Liu, Hongfang

AU - Smaili, Fatima Zohra

AU - Hoehndorf, Robert

AU - Pendlington, Zoë May

AU - Roncaglia, Paola

AU - Ye, Xianwei

AU - Xie, Jiangan

AU - Tang, Yi Wei

AU - Yang, Xiaolin

AU - Peng, Suyuan

AU - Zhang, Luxia

AU - Chen, Luonan

AU - Hur, Junguk

AU - Omenn, Gilbert S.

AU - Athey, Brian

AU - Smith, Barry

PY - 2022/12

Y1 - 2022/12

N2 - 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.

AB - 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.

KW - COVID-19

KW - Coronavirus

KW - Diagnosis

KW - Drug repurposing

KW - Ontology

KW - Phenotype

KW - SARS-CoV-2

KW - Vaccine

UR - http://www.scopus.com/inward/record.url?scp=85140228259&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85140228259&partnerID=8YFLogxK

U2 - 10.1186/s13326-022-00279-z

DO - 10.1186/s13326-022-00279-z

M3 - Article

C2 - 36271389

AN - SCOPUS:85140228259

SN - 2041-1480

VL - 13

JO - Journal of Biomedical Semantics

JF - Journal of Biomedical Semantics

IS - 1

M1 - 25

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this