Comprehensive benchmark and architectural analysis of deep learning models for nanopore sequencing basecalling

BACKGROUND: Nanopore-based DNA sequencing relies on basecalling the electric current signal. Basecalling requires neural networks to achieve competitive accuracies. To improve sequencing accuracy further, new models are continuously proposed with new architectures. However, benchmarking is currently...

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Detalles Bibliográficos
Autores principales: Pagès-Gallego, Marc, de Ridder, Jeroen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088207/
https://www.ncbi.nlm.nih.gov/pubmed/37041647
http://dx.doi.org/10.1186/s13059-023-02903-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088207/
https://www.ncbi.nlm.nih.gov/pubmed/37041647
http://dx.doi.org/10.1186/s13059-023-02903-2

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