Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences

We present an approach to discriminate SARS-CoV-2 virus types based on their RNA sequence descriptions avoiding a sequence alignment. For that purpose, sequences are preprocessed by feature extraction and the resulting feature vectors are analyzed by prototype-based classification to remain interpre...

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Detalles Bibliográficos
Autores principales: Kaden, Marika, Bohnsack, Katrin Sophie, Weber, Mirko, Kudła, Mateusz, Gutowska, Kaja, Blazewicz, Jacek, Villmann, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2021
Materias:
S.i. : Wsom 2019
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076884/
https://www.ncbi.nlm.nih.gov/pubmed/33935376
http://dx.doi.org/10.1007/s00521-021-06018-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076884/
https://www.ncbi.nlm.nih.gov/pubmed/33935376
http://dx.doi.org/10.1007/s00521-021-06018-2

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