A Genome-Based Model to Predict the Virulence of <named-content content-type="genus-species">Pseudomonas aeruginosa</named-content> Isolates

A Genome-Based Model to Predict the Virulence of <named-content content-type="genus-species">Pseudomonas aeruginosa</named-content> Isolates

ABSTRACT Variation in the genome of Pseudomonas aeruginosa, an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine...

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Autores principales: Nathan B. Pincus, Egon A. Ozer, Jonathan P. Allen, Marcus Nguyen, James J. Davis, Deborah R. Winter, Chih-Hsien Chuang, Cheng-Hsun Chiu, Laura Zamorano, Antonio Oliver, Alan R. Hauser
Formato: article
Lenguaje:EN
Publicado: American Society for Microbiology 2020
Materias:
Pseudomonas aeruginosa
genome analysis
machine learning
modeling
prediction
virulence
Microbiology
QR1-502
Acceso en línea:https://doaj.org/article/1908f46e3086477ca33102afad2a73da
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