Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning‐enabled molecular diagnostics

Limited therapy options due to antibiotic resistance underscore the need for optimization of current diagnostics. In some bacterial species, antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug‐...

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Detalhes bibliográficos
Publicado no:EMBO Mol Med
Principais autores: Khaledi, Ariane, Weimann, Aaron, Schniederjans, Monika, Asgari, Ehsaneddin, Kuo, Tzu‐Hao, Oliver, Antonio, Cabot, Gabriel, Kola, Axel, Gastmeier, Petra, Hogardt, Michael, Jonas, Daniel, Mofrad, Mohammad RK, Bremges, Andreas, McHardy, Alice C, Häussler, Susanne
Formato: Artigo
Idioma:Inglês
Publicado em: John Wiley and Sons Inc. 2020
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Articles
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7059009/
https://ncbi.nlm.nih.gov/pubmed/32048461
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.15252/emmm.201910264
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