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SquiggleNet: real-time, direct classification of nanopore signals

We present SquiggleNet, the first deep-learning model that can classify nanopore reads directly from their electrical signals. SquiggleNet operates faster than DNA passes through the pore, allowing real-time classification and read ejection. Using 1 s of sequencing data, the classifier achieves sign...

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Detalles Bibliográficos
Autores principales:	Bao, Yuwei, Wadden, Jack, Erb-Downward, John R., Ranjan, Piyush, Zhou, Weichen, McDonald, Torrin L., Mills, Ryan E., Boyle, Alan P., Dickson, Robert P., Blaauw, David, Welch, Joshua D.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2021
Materias:	Method
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548853/ https://www.ncbi.nlm.nih.gov/pubmed/34706748 http://dx.doi.org/10.1186/s13059-021-02511-y

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