MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes

MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes

Abstract Background With the rapid increase in throughput of long-read sequencing technologies, recent studies have explored their potential for taxonomic classification by using alignment-based approaches to reduce the impact of higher sequencing error rates. While alignment-based methods are gener...

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Bibliographic Details
Main Authors: Rafael Peres da Silva, Chayaporn Suphavilai, Niranjan Nagarajan
Format: Article
Language:English
Published: BMC 2024-04-01
Series:BMC Bioinformatics
Subjects:
Taxonomic classification
Machine learning
Metagenomics
Long-read
Online Access:https://doi.org/10.1186/s12859-024-05760-3

Internet

https://doi.org/10.1186/s12859-024-05760-3

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