Correcting the Estimation of Viral Taxa Distributions in Next-Generation Sequencing Data after Applying Artificial Neural Networks

Estimating the taxonomic composition of viral sequences in a biological samples processed by next-generation sequencing is an important step in comparative metagenomics. Mapping sequencing reads against a database of known viral reference genomes, however, fails to classify reads from novel viruses...

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Autores principales:	Moritz Kohls, Magdalena Kircher, Jessica Krepel, Pamela Liebig, Klaus Jung
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	artificial neural networks classification machine learning metagenomics next-generation sequencing viruses Genetics QH426-470
Acceso en línea:	https://doaj.org/article/50bbe16f0f614b6893a74c2fd88ca9aa
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Correcting the Estimation of Viral Taxa Distributions in Next-Generation Sequencing Data after Applying Artificial Neural Networks

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