Assessing the Resilience of Machine Learning Classification Algorithms on SARS-CoV-2 Genome Sequences Generated with Long-Read Specific Errors

Assessing the Resilience of Machine Learning Classification Algorithms on SARS-CoV-2 Genome Sequences Generated with Long-Read Specific Errors

The emergence of third-generation single-molecule sequencing (TGS) technology has revolutionized the generation of long reads, which are essential for genome assembly and have been widely employed in sequencing the SARS-CoV-2 virus during the COVID-19 pandemic. Although long-read sequencing has been...

Full description

Bibliographic Details
Main Authors: Bikram Sahoo, Sarwan Ali, Pin-Yu Chen, Murray Patterson, Alexander Zelikovsky
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Biomolecules
Subjects:
sequencing error
third-generation single-molecule sequencing (TGS)
long read
machine learning
embedding methods
classification
Online Access:https://www.mdpi.com/2218-273X/13/6/934

Similar Items

Similar Items