RUBICON: a framework for designing efficient deep learning-based genomic basecallers

RUBICON: a framework for designing efficient deep learning-based genomic basecallers

Abstract Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The performance of basecalling has critical implications for all later steps in genome analysis. Therefore, there is...

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Bibliographic Details
Main Authors: Gagandeep Singh, Mohammed Alser, Kristof Denolf, Can Firtina, Alireza Khodamoradi, Meryem Banu Cavlak, Henk Corporaal, Onur Mutlu
Format: Article
Language:English
Published: BMC 2024-02-01
Series:Genome Biology
Subjects:
Genomics sequencing
Basecalling
Hardware acceleration
Machine learning
Deep neural network
Online Access:https://doi.org/10.1186/s13059-024-03181-2

Internet

https://doi.org/10.1186/s13059-024-03181-2

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