Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing

Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. Here, the authors identify robust druggable protein targets within a principled causal framework that makes use of multiple data modalities and integrates agin...

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Autores principales:	Anastasiya Belyaeva, Louis Cammarata, Adityanarayanan Radhakrishnan, Chandler Squires, Karren Dai Yang, G. V. Shivashankar, Caroline Uhler
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/0070bbeebfbc43a1a7a2f2bff257da7c
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spelling	oai:doaj.org-article:0070bbeebfbc43a1a7a2f2bff257da7c2021-12-02T10:54:04ZCausal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing10.1038/s41467-021-21056-z2041-1723https://doaj.org/article/0070bbeebfbc43a1a7a2f2bff257da7c2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21056-zhttps://doaj.org/toc/2041-1723Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. Here, the authors identify robust druggable protein targets within a principled causal framework that makes use of multiple data modalities and integrates aging signatures.Anastasiya BelyaevaLouis CammarataAdityanarayanan RadhakrishnanChandler SquiresKarren Dai YangG. V. ShivashankarCaroline UhlerNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Anastasiya Belyaeva Louis Cammarata Adityanarayanan Radhakrishnan Chandler Squires Karren Dai Yang G. V. Shivashankar Caroline Uhler Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
description	Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. Here, the authors identify robust druggable protein targets within a principled causal framework that makes use of multiple data modalities and integrates aging signatures.
format	article
author	Anastasiya Belyaeva Louis Cammarata Adityanarayanan Radhakrishnan Chandler Squires Karren Dai Yang G. V. Shivashankar Caroline Uhler
author_facet	Anastasiya Belyaeva Louis Cammarata Adityanarayanan Radhakrishnan Chandler Squires Karren Dai Yang G. V. Shivashankar Caroline Uhler
author_sort	Anastasiya Belyaeva
title	Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
title_short	Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
title_full	Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
title_fullStr	Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
title_full_unstemmed	Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
title_sort	causal network models of sars-cov-2 expression and aging to identify candidates for drug repurposing
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0070bbeebfbc43a1a7a2f2bff257da7c
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Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing

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