Literature DB >> 33346828

The COVID-19 Ontology.

Astghik Sargsyan1, Alpha Tom Kodamullil1, Shounak Baksi2, Johannes Darms1, Sumit Madan1, Stephan Gebel1, Oliver Keminer3, Geena Mariya Jose2, Helena Balabin1, Lauren Nicole DeLong1, Manfred Kohler3, Marc Jacobs1, Martin Hofmann-Apitius1.   

Abstract

MOTIVATION: The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel coronavirus (SARS-CoV-2) entities. The ontology has a strong scope on chemical entities suited for drug repurposing, as this is a major target of ongoing COVID-19 therapeutic development.
RESULTS: The ontology comprises 2.270 classes of concepts and 38.987 axioms (2622 logical axioms and 2434 declaration axioms). It depicts the roles of molecular and cellular entities in virus-host interactions and in the virus life cycle, as well as a wide spectrum of medical and epidemiological concepts linked to COVID-19. The performance of the ontology has been tested on Medline and the COVID-19 corpus provided by the Allen Institute. AVAILABILITY: COVID-19 Ontology is released under a Creative Commons 4.0 License and shared via https://github.com/covid-19-ontology/covid-19. The ontology is also deposited in BioPortal at https://bioportal.bioontology.org/ontologies/COVID-19.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Year:  2020        PMID: 33346828      PMCID: PMC7799333          DOI: 10.1093/bioinformatics/btaa1057

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3 Billion Compounds.

Authors:  Anh-Tien Ton; Francesco Gentile; Michael Hsing; Fuqiang Ban; Artem Cherkasov
Journal:  Mol Inform       Date:  2020-03-23       Impact factor: 4.050

2.  COVID-19 Knowledge Graph: a computable, multi-modal, cause-and-effect knowledge model of COVID-19 pathophysiology.

Authors:  Daniel Domingo-Fernández; Shounak Baksi; Bruce Schultz; Yojana Gadiya; Reagon Karki; Tamara Raschka; Christian Ebeling; Martin Hofmann-Apitius; Alpha Tom Kodamullil
Journal:  Bioinformatics       Date:  2021-06-09       Impact factor: 6.937

3.  Early dynamics of transmission and control of COVID-19: a mathematical modelling study.

Authors:  Adam J Kucharski; Timothy W Russell; Charlie Diamond; Yang Liu; John Edmunds; Sebastian Funk; Rosalind M Eggo
Journal:  Lancet Infect Dis       Date:  2020-03-11       Impact factor: 25.071

4.  Repurposing of clinically approved drugs for treatment of coronavirus disease 2019 in a 2019-novel coronavirus-related coronavirus model.

Authors:  Hua-Hao Fan; Li-Qin Wang; Wen-Li Liu; Xiao-Ping An; Zhen-Dong Liu; Xiao-Qi He; Li-Hua Song; Yi-Gang Tong
Journal:  Chin Med J (Engl)       Date:  2020-05-05       Impact factor: 2.628

5.  Modeling the epidemic dynamics and control of COVID-19 outbreak in China.

Authors:  Shilei Zhao; Hua Chen
Journal:  Quant Biol       Date:  2020-03-11
  5 in total
  4 in total

1.  CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay.

Authors:  Tommaso Alfonsi; Ruba Al Khalaf; Stefano Ceri; Anna Bernasconi
Journal:  Sci Data       Date:  2022-06-01       Impact factor: 8.501

2.  Covid19/IT the digital side of Covid19: A picture from Italy with clustering and taxonomy.

Authors:  Vincenzo Bonnici; Giovanni Cicceri; Salvatore Distefano; Letterio Galletta; Marco Polignano; Carlo Scaffidi
Journal:  PLoS One       Date:  2022-06-09       Impact factor: 3.752

3.  An Overview of Biomedical Ontologies for Pandemics and Infectious Diseases Representation.

Authors:  Leila Bayoudhi; Najla Sassi; Wassim Jaziri
Journal:  Procedia Comput Sci       Date:  2021-10-01

4.  COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments.

Authors:  Ahmed Abdeen Hamed; Tamer E Fandy; Karolina L Tkaczuk; Karin Verspoor; Byung Suk Lee
Journal:  Pharmaceutics       Date:  2022-03-04       Impact factor: 6.321

  4 in total

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