RCOVID-19

Published: 28-07-2020| Version 2 | DOI: 10.17632/m3s26wghdz.2
Contributors:
mohammad hossein olyaee,
Jamshid Pirgazi,
khosrow khalifeh,
Ali Reza Khanteymoori

Description

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 represented features enable us to compare genomic sequences with different lengths. The provided dataset involves totally 18 RQA-based features for 4496 instances of SARS-COV-2. The source code of generating data can be found in this address: https://github.com/mholyaee/RCOVID-19

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