A biochemically-interpretable machine learning classifier for microbial GWAS

Current machine learning classifiers have successfully been applied to whole-genome sequencing data to identify genetic determinants of antimicrobial resistance (AMR), but they lack causal interpretation. Here we present a metabolic model-based machine learning classifier, named Metabolic Allele Cla...

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Detalles Bibliográficos
Autores principales: Kavvas, Erol S., Yang, Laurence, Monk, Jonathan M., Heckmann, David, Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244534/
https://www.ncbi.nlm.nih.gov/pubmed/32444610
http://dx.doi.org/10.1038/s41467-020-16310-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244534/
https://www.ncbi.nlm.nih.gov/pubmed/32444610
http://dx.doi.org/10.1038/s41467-020-16310-9

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