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Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework
Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, viro...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170012/ https://www.ncbi.nlm.nih.gov/pubmed/34095051 http://dx.doi.org/10.3389/fpubh.2021.638605 |
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author | Nymark, Penny Sachana, Magdalini Leite, Sofia Batista Sund, Jukka Krebs, Catharine E. Sullivan, Kristie Edwards, Stephen Viviani, Laura Willett, Catherine Landesmann, Brigitte Wittwehr, Clemens |
author_facet | Nymark, Penny Sachana, Magdalini Leite, Sofia Batista Sund, Jukka Krebs, Catharine E. Sullivan, Kristie Edwards, Stephen Viviani, Laura Willett, Catherine Landesmann, Brigitte Wittwehr, Clemens |
author_sort | Nymark, Penny |
collection | PubMed |
description | Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, virology and medical research. The COVID-19 pandemic engages a great number of scientists world-wide and data is increasing with exponential speed. Diligent data management strategies are employed but approaches for systematically organizing the data-derived information and knowledge are lacking. We believe AOPs can play an important role in improving interpretation and efficient application of scientific understanding of COVID-19. Here, we outline a newly initiated effort, the CIAO project (https://www.ciao-covid.net/), to streamline collaboration between scientists across the world toward development of AOPs for COVID-19, and describe the overarching aims of the effort, as well as the expected outcomes and research support that they will provide. |
format | Online Article Text |
id | pubmed-8170012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81700122021-06-03 Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework Nymark, Penny Sachana, Magdalini Leite, Sofia Batista Sund, Jukka Krebs, Catharine E. Sullivan, Kristie Edwards, Stephen Viviani, Laura Willett, Catherine Landesmann, Brigitte Wittwehr, Clemens Front Public Health Public Health Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, virology and medical research. The COVID-19 pandemic engages a great number of scientists world-wide and data is increasing with exponential speed. Diligent data management strategies are employed but approaches for systematically organizing the data-derived information and knowledge are lacking. We believe AOPs can play an important role in improving interpretation and efficient application of scientific understanding of COVID-19. Here, we outline a newly initiated effort, the CIAO project (https://www.ciao-covid.net/), to streamline collaboration between scientists across the world toward development of AOPs for COVID-19, and describe the overarching aims of the effort, as well as the expected outcomes and research support that they will provide. Frontiers Media S.A. 2021-05-19 /pmc/articles/PMC8170012/ /pubmed/34095051 http://dx.doi.org/10.3389/fpubh.2021.638605 Text en Copyright © 2021 Nymark, Sachana, Leite, Sund, Krebs, Sullivan, Edwards, Viviani, Willett, Landesmann and Wittwehr. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Nymark, Penny Sachana, Magdalini Leite, Sofia Batista Sund, Jukka Krebs, Catharine E. Sullivan, Kristie Edwards, Stephen Viviani, Laura Willett, Catherine Landesmann, Brigitte Wittwehr, Clemens Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title | Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title_full | Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title_fullStr | Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title_full_unstemmed | Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title_short | Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework |
title_sort | systematic organization of covid-19 data supported by the adverse outcome pathway framework |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170012/ https://www.ncbi.nlm.nih.gov/pubmed/34095051 http://dx.doi.org/10.3389/fpubh.2021.638605 |
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