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Review

Bioinformatics Approaches to the Understanding of Molecular Mechanisms in Antimicrobial Resistance

1
Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH 45267, USA
2
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
3
Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
4
Department of Pediatrics, University of Cincinnati, Cincinnati, OH 45267, USA
5
Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(4), 1363; https://doi.org/10.3390/ijms21041363
Received: 24 January 2020 / Revised: 13 February 2020 / Accepted: 17 February 2020 / Published: 18 February 2020
(This article belongs to the Special Issue Drug Resistance Mechanisms in Bacteria)
Antimicrobial resistance (AMR) is a major health concern worldwide. A better understanding of the underlying molecular mechanisms is needed. Advances in whole genome sequencing and other high-throughput unbiased instrumental technologies to study the molecular pathogenicity of infectious diseases enable the accumulation of large amounts of data that are amenable to bioinformatic analysis and the discovery of new signatures of AMR. In this work, we review representative methods published in the past five years to define major approaches developed to-date in the understanding of AMR mechanisms. Advantages and limitations for applications of these methods in clinical laboratory testing and basic research are discussed. View Full-Text
Keywords: antimicrobial resistance; antibiotic resistance genes; molecular mechanisms; bioinformatic analysis; prediction of antibiotic resistance antimicrobial resistance; antibiotic resistance genes; molecular mechanisms; bioinformatic analysis; prediction of antibiotic resistance
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MDPI and ACS Style

Van Camp, P.-J.; Haslam, D.B.; Porollo, A. Bioinformatics Approaches to the Understanding of Molecular Mechanisms in Antimicrobial Resistance. Int. J. Mol. Sci. 2020, 21, 1363. https://doi.org/10.3390/ijms21041363

AMA Style

Van Camp P-J, Haslam DB, Porollo A. Bioinformatics Approaches to the Understanding of Molecular Mechanisms in Antimicrobial Resistance. International Journal of Molecular Sciences. 2020; 21(4):1363. https://doi.org/10.3390/ijms21041363

Chicago/Turabian Style

Van Camp, Pieter-Jan, David B. Haslam, and Aleksey Porollo. 2020. "Bioinformatics Approaches to the Understanding of Molecular Mechanisms in Antimicrobial Resistance" International Journal of Molecular Sciences 21, no. 4: 1363. https://doi.org/10.3390/ijms21041363

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