id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-264296-0x90yubt	Sawmya, Shashata	Analyzing hCov genome sequences: Applying Machine Intelligence and beyond	2020-06-03		.txt	text/plain	5008	312	60	We present here an analysis pipeline comprising phylogenetic analysis on strains of this novel virus to track its evolutionary history among the countries uncovering several interesting relationships, followed by a classification exercise to identify the virulence of the strains and extraction of important features from its genetic material that are used subsequently to predict mutation at those interesting sites using deep learning techniques. C. Several CNN-RNN based models are used to predict mutations at specific Sites of Interest (SoIs) of the sars-cov-2 genome sequence followed by further analyses of the same on several South-Asian countries. D. Overall, we present an analysis pipeline that can be further utilized as well as extended and revised (a) to study where a newly discovered genome sequence lies in relation to its predecessors in different regions of the world; (b) to analyse its virulence with respect to the number of deaths its predecessors have caused in their respective countries and (c) to analyse the mutation at specific important sites of the viral genome.	./cache/cord-264296-0x90yubt.txt	./txt/cord-264296-0x90yubt.txt