Global pathogenomic analysis identifies known and candidate genetic antimicrobial resistance determinants in twelve species

Surveillance programs for managing antimicrobial resistance (AMR) have yielded thousands of genomes suited for data-driven mechanism discovery. We present a workflow integrating pangenomics, gene annotation, and machine learning to identify AMR genes at scale. When applied to 12 species, 27,155 geno...

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Detalles Bibliográficos
Autores principales: Hyun, Jason C., Monk, Jonathan M., Szubin, Richard, Hefner, Ying, Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673929/
https://www.ncbi.nlm.nih.gov/pubmed/38001096
http://dx.doi.org/10.1038/s41467-023-43549-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673929/
https://www.ncbi.nlm.nih.gov/pubmed/38001096
http://dx.doi.org/10.1038/s41467-023-43549-9

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