id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-303061-vvzkpetn	Olyaee, Mohammad Hossein	RCOVID19: Recurrence-based SARS-CoV-2 features using chaos game representation	2020-08-07		.txt	text/plain	1343	110	59	title: RCOVID19: Recurrence-based SARS-CoV-2 features using chaos game representation Utilizing chaos game representation (CGR) as well as recurrence quantification analysis (RQA) as a powerful nonlinear analysis technique, we proposed an effective process to extract several valuable features from genomic sequences of SARS-CoV-2.  The dataset involves features that enable us to compare genomic sequences with different lengths. In this work, according to the diagram represented in Fig. 1 , several recurrencequantification-based features are extracted from the nucleotide sequences. In this paper, we introduce a new dataset which involves efficient nonlinear features related to genomic sequences of SARS-CoV-2. In the final step, by applying recurrence quantification analysis (RQA), from each extracted coordinate series, 9 features are provided and totally 18 ( ) features will be extracted. • Extract features from coordinate series by applying recurrence quantification analysis measure gives the probability that two neighbors of any state are also neighbors and is obtained as below:	./cache/cord-303061-vvzkpetn.txt	./txt/cord-303061-vvzkpetn.txt