Holistic understanding of trimethoprim resistance in
Streptococcus pneumoniae
drug resistance mechanisms
genome-wide association study
machine learning
trimethoprim
Journal
mBio
ISSN: 2150-7511
Titre abrégé: mBio
Pays: United States
ID NLM: 101519231
Informations de publication
Date de publication:
09 Aug 2024
09 Aug 2024
Historique:
medline:
9
8
2024
pubmed:
9
8
2024
entrez:
9
8
2024
Statut:
aheadofprint
Résumé
Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to investigate trimethoprim (TMP) resistance in the key pathogen In the age of next-generation sequencing (NGS), while data-driven methods such as genome-wide association study (GWAS) and machine learning (ML) excel at finding patterns, functional validation can be challenging due to the high numbers of candidate variants. We designed an integrative approach combining a GWAS on
Identifiants
pubmed: 39120145
doi: 10.1128/mbio.01360-24
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM