Work

Genomic Features Associated with the Degree of Phenotypic Resistance to Carbapenems in Carbapenem-Resistant Klebsiella pneumoniae

Year: 2021

Type: article

Abstract: , were associated with lower carbapenem MICs. Machine learning did not result in a substantial improvement in the prediction of carbapenem resistance nor did it identify novel genes associated with carbapenem resistance. These findings enhance our understanding of the many contributors to carbapenem resistance in K. pneumoniae.

Source: mSystems

DOI: 10.1128/msystems.00194-21

Authors: Zackery P. Bulman, Fiorella Krapp, Nathan B. Pincus, Eric Wenzler, Katherine R. Murphy, Chao Qi, Egon A. Ozer, Alan R. Hauser

Institutions: University of Illinois Chicago, Northwestern University

Language: English

Topic: Antibiotic Resistance in Bacteria

Subfield: Molecular Medicine

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,500

Funders: Chicago Biomedical Consortium, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, National Center for Advancing Translational Sciences

Awards: Biomarkers for Highly Virulent Pseudomonas aeruginosa Strains, G2366363732, G2397131710, G3692266691, G39563676, G4599794873, G76741582, G9000042048, G9000157839, G9000167646, G9000244833

OpenAlex ID: W3200719277

FWCI: 2.28

Cites: 60

Cited by: 47

Related to: 10