id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-349794-mhviub6e	Le, Brian L.	Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19	2020-10-23		.txt	text/plain	3810	216	43	We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. By infecting human adenocarcinomic alveolar basal epithelial cells with SARS-CoV-2 and comparing to controls, the authors generated a list of 120 differentially expressed genes. Here, we applied our existing computational drug repositioning pipeline to identify drug profiles with significantly reversed differential gene expression compared to predicted inhibitors (including one tested in Calu-3) were incubated with SARS-CoV-2 infected human embryonic kidney 293T cells overexpressing ACE2 (293T-ACE2) with viral replication determined using an immunofluorescence-based assay. In this study, we applied our drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available RNA-seq data ( Figure 1 ). Here, we used a transcriptomics-based drug repositioning pipeline to predict therapeutic drug hits for three different input SARS-CoV-2 signatures, each of which came from distinct human cell or tissue origins.	./cache/cord-349794-mhviub6e.txt	./txt/cord-349794-mhviub6e.txt