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Looking at COVID-19 from a Systems Biology Perspective

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characte...

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Detalles Bibliográficos
Autores principales: Turilli, Emily Samuela, Lualdi, Marta, Fasano, Mauro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961533/
https://www.ncbi.nlm.nih.gov/pubmed/35204689
http://dx.doi.org/10.3390/biom12020188
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author Turilli, Emily Samuela
Lualdi, Marta
Fasano, Mauro
author_facet Turilli, Emily Samuela
Lualdi, Marta
Fasano, Mauro
author_sort Turilli, Emily Samuela
collection PubMed
description The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus–human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus–host interactions, and in the development of disease classifiers and tools for drug repurposing.
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spelling pubmed-89615332022-03-30 Looking at COVID-19 from a Systems Biology Perspective Turilli, Emily Samuela Lualdi, Marta Fasano, Mauro Biomolecules Review The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus–human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus–host interactions, and in the development of disease classifiers and tools for drug repurposing. MDPI 2022-01-22 /pmc/articles/PMC8961533/ /pubmed/35204689 http://dx.doi.org/10.3390/biom12020188 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Turilli, Emily Samuela
Lualdi, Marta
Fasano, Mauro
Looking at COVID-19 from a Systems Biology Perspective
title Looking at COVID-19 from a Systems Biology Perspective
title_full Looking at COVID-19 from a Systems Biology Perspective
title_fullStr Looking at COVID-19 from a Systems Biology Perspective
title_full_unstemmed Looking at COVID-19 from a Systems Biology Perspective
title_short Looking at COVID-19 from a Systems Biology Perspective
title_sort looking at covid-19 from a systems biology perspective
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961533/
https://www.ncbi.nlm.nih.gov/pubmed/35204689
http://dx.doi.org/10.3390/biom12020188
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