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...
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 |
Similar Items
-
Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
by: Belyaeva, Anastasiya, et al.
Published: (2021) -
DCI: learning causal differences between gene regulatory networks
by: Belyaeva, Anastasiya, et al.
Published: (2022) -
Direct Estimation of Differences in Causal Graphs
by: Wang, Yuhao, et al.
Published: (2021) -
Multi-domain translation between single-cell imaging and sequencing data using autoencoders
by: Karren Dai Yang, et al.
Published: (2021-01-01) -
Causal Structure Learning: A Combinatorial Perspective
by: Squires, Chandler, et al.
Published: (2022)