Classification of COVID-19 and Other Pathogenic Sequences: A Dinucleotide Frequency and Machine Learning Approach

Classification of COVID-19 and Other Pathogenic Sequences: A Dinucleotide Frequency and Machine Learning Approach

The world is grappling with the COVID-19 pandemic caused by the 2019 novel SARS-CoV-2. To better understand this novel virus and its relationship with other pathogens, new methods for analyzing the genome are required. In this study, intrinsic dinucleotide genomic signatures were analyzed for whole...

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Bibliographic Details
Main Authors: Gciniwe S. Dlamini, Stephanie J. Muller, Rebone L. Meraba, Richard A. Young, James Mashiyane, Tapiwa Chiwewe, Darlington S. Mapiye
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Alignment-free sequence analysis
COVID-19
dinucleotide frequencies
feature representations
genomic signatures
human pathogens
Online Access:https://ieeexplore.ieee.org/document/9224617/

Internet

https://ieeexplore.ieee.org/document/9224617/

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