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Augmenting bacterial similarity measures using a graph-based genome representation.

Vivek RamananIndra Neil Sarkar
Published in: mSystems (2024)
Given the prevalence and necessity of the 16S rRNA measure in bacterial identification and analysis, this additional analysis adds a functional and synteny-based layer to the identification of relatives and clustering of bacteria genomes. It is also of computational interest to model the bacterial genome as a graph structure, which presents new avenues of genomic analysis for bacteria and their closely related strains and species.
Keyphrases
  • escherichia coli
  • risk factors
  • genome wide
  • convolutional neural network
  • dna methylation
  • single cell
  • deep learning
  • genetic diversity