Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens

The evolution of antimicrobial resistance (AMR) poses a persistent threat to global public health. Sequencing efforts have already yielded genome sequences for thousands of resistant microbial isolates and require robust computational tools to systematically elucidate the genetic basis for AMR. Here...

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Detalles Bibliográficos
Autores principales: Hyun, Jason C., Kavvas, Erol S., Monk, Jonathan M., Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067475/
https://www.ncbi.nlm.nih.gov/pubmed/32119670
http://dx.doi.org/10.1371/journal.pcbi.1007608

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067475/
https://www.ncbi.nlm.nih.gov/pubmed/32119670
http://dx.doi.org/10.1371/journal.pcbi.1007608

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