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

Rafael Peres da SilvaChayaporn SuphavilaiNiranjan Nagarajan
Published in: BMC bioinformatics (2024)
This proof of concept work demonstrates the utility of machine-learning-based methods for taxonomic classification using long reads. MetageNN can be used on sequences not classified by conventional methods and offers an alternative approach for memory-efficient classifiers that can be optimized further.
Keyphrases
  • neural network
  • machine learning
  • working memory
  • deep learning
  • artificial intelligence
  • big data
  • single cell
  • patient safety
  • emergency department
  • genetic diversity