Clustering minimal inhibitory concentration data through Bayesian mixture models: An application to detect Mycobacteriumtuberculosis resistance mutations.

ABSTRACT: Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and this makes it competitive with respect to standard phenotypic tests; second, it is possible to statistically associate the phenotypic patterns of resistance to specific mutations in the genome. Therefore, it is now possible to develop catalogues of genomic variants associated with resistance to specific antibiotics, in order to improve prediction of resistance and suggest treatments. It is essential to have robust methods for identifyi

SUBMITTER: Grazian C 

PROVIDER: S-EPMC10710010 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature