Predicting Antimicrobial Resistance Using Partial Genome Alignments

D. Aytan-Aktug; M. Nguyen; P. T. L. C. Clausen; R. L. Stevens; F. M. Aarestrup; O. Lund; J. J. Davis

doi:10.1128/mSystems.00185-21

mSystems (Jun 2021)

Predicting Antimicrobial Resistance Using Partial Genome Alignments

D. Aytan-Aktug,
M. Nguyen,
P. T. L. C. Clausen,
R. L. Stevens,
F. M. Aarestrup,
O. Lund,
J. J. Davis

Affiliations

D. Aytan-Aktug: ORCiD; National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
M. Nguyen: Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA
P. T. L. C. Clausen: ORCiD; National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
R. L. Stevens: Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA
F. M. Aarestrup: National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
O. Lund: ORCiD; National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
J. J. Davis: ORCiD; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA

DOI: https://doi.org/10.1128/mSystems.00185-21
Journal volume & issue: Vol. 6, no. 3

Abstract

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Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission.

Published in mSystems

ISSN: 2379-5077 (Online)
Publisher: American Society for Microbiology
Country of publisher: United States
LCC subjects: Science: Microbiology
Website: https://journals.asm.org/journal/msystems

About the journal