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COMPLEXITY-BASED DETECTION OF SIMILARITY BETWEEN ANIMAL CORONAVIRUSES AND SARS-CoV-2 IN HUMANS

School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan 47500 Subang Jaya, Selangor Darul Ehsan, Malaysia

Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 500 03 Hradec Králové, Czech Republic

E-mail Address: hrn_mechanic@yahoo.com

Corresponding author.

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ENRIQUE HERRERA-VIEDMA

Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, E-18071 Granada, Andalusia, Spain

Department of Electrical and Computer Engineering, Faculty of Engineering King Abdulaziz University, P. O. Box 80204, Jeddah 21589, Saudi Arabia

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, and

ONDREJ KREJCAR

Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 500 03 Hradec Králové, Czech Republic

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https://doi.org/10.1142/S0218348X21500316Cited by:13 (Source: Crossref)

Abstract

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the most dangerous type of coronavirus and has infected over 25.3 million people around the world (including causing 848,000 deaths). In this study, we investigated the similarity between the genome walks of coronaviruses in various animals and those of human SARS-CoV-2. Based on the results, although bats show a similar pattern of coronavirus genome walks to that of SARS-CoV-2 in humans, decoding the complex structure of coronavirus genome walks using sample entropy and fractal theory showed that the complexity of the pangolin coronavirus genome walk has a 94% match with the complexity of the SARS-CoV-2 genome walk in humans. This is the first reported study that found a similarity between the hidden characteristics of pangolin coronavirus and human SARS-CoV-2 using complexity-based analysis. The results of this study have great importance for the analysis of the origin and transfer of the virus.

Keywords:

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Vol. 28, No. 07

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History

Received 26 July 2020

Accepted 9 September 2020

Published: October 23, 2020

Information

This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND) License which permits use, distribution and reproduction, provided that the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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COMPLEXITY-BASED DETECTION OF SIMILARITY BETWEEN ANIMAL CORONAVIRUSES AND SARS-CoV-2 IN HUMANS

Abstract

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