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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Main Authors:	Anastasiya Belyaeva, Louis Cammarata, Adityanarayanan Radhakrishnan, Chandler Squires, Karren Dai Yang, G. V. Shivashankar, Caroline Uhler
Format:	Article
Language:	English
Published:	Nature Publishing Group 2021-02-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-021-21056-z

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spelling	doaj-0070bbeebfbc43a1a7a2f2bff257da7c2021-02-21T12:13:23ZengNature Publishing GroupNature Communications2041-17232021-02-0112111310.1038/s41467-021-21056-zCausal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposingAnastasiya Belyaeva0Louis Cammarata1Adityanarayanan Radhakrishnan2Chandler Squires3Karren Dai Yang4G. V. Shivashankar5Caroline Uhler6Massachusetts Institute of TechnologyHarvard UniversityMassachusetts Institute of TechnologyMassachusetts Institute of TechnologyMassachusetts Institute of TechnologyETH ZurichMassachusetts Institute of TechnologyGiven 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.https://doi.org/10.1038/s41467-021-21056-z
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Anastasiya Belyaeva Louis Cammarata Adityanarayanan Radhakrishnan Chandler Squires Karren Dai Yang G. V. Shivashankar Caroline Uhler
spellingShingle	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 Nature Communications
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 Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2021-02-01
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.
url	https://doi.org/10.1038/s41467-021-21056-z
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Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing

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