Deep Learning Applied to the SARS-CoV-2 Classification
Published: 8 June 2023| Version 1 | DOI: 10.17632/zmhsn2gz7w.1
Contributors:
, , , , Description
The presented dataset provides comprehensive information associated with a machine learning-based tool that employs a deep one-dimensional (1D) convolutional neural network (CNN). This tool is specifically designed to classify and compare viral genomes of the novel SARS-CoV-2. Complete genomic cDNA samples, ranging in length from 26,342 to 31,029 base pairs (bp), serve as input for the model.
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Institutions
Universidade Federal do Rio Grande do Norte
Categories
Genome, Deep Learning