Predicting antimicrobial resistance using conserved genes

A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features derived from comprehensive sets of AMR genes or whol...

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Detalles Bibliográficos
Autores principales: Nguyen, Marcus, Olson, Robert, Shukla, Maulik, VanOeffelen, Margo, Davis, James J.
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/PMC7595632/
https://www.ncbi.nlm.nih.gov/pubmed/33075053
http://dx.doi.org/10.1371/journal.pcbi.1008319

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595632/
https://www.ncbi.nlm.nih.gov/pubmed/33075053
http://dx.doi.org/10.1371/journal.pcbi.1008319

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