id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-199630-2lmwnfda	Ray, Sumanta	Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs	2020-07-05		.txt	text/plain	6389	379	53	Therefore, host-(1) We link existing high-quality, long-term curated and refined, large scale drug/protein -protein interaction data with (2) molecular interaction data on SARS-CoV-2 itself, raised only a handful of weeks ago, (3) exploit the resulting overarching network using most advanced, AI boosted techniques (4) for repurposing drugs in the fight against SARS-CoV-2 (5) in the frame of HDT based strategies. As for (3)-(5), we will highlight interactions between SARS-Cov-2-host protein and human proteins important for the virus to persist using most advanced deep learning techniques that cater to exploiting network data. As per our simulation study, a large fraction, if not the vast majority of the predictions establish true, hence actionable interactions between drugs on the one hand and SARS-CoV-2 associated human proteins (hence of use in HDT) on the other hand.	./cache/cord-199630-2lmwnfda.txt	./txt/cord-199630-2lmwnfda.txt