Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data

Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data

BackgroundEarly detection of antimicrobial resistance in pathogens and prescription of more effective antibiotics is a fast-emerging need in clinical practice. High-throughput sequencing technology, such as whole genome sequencing (WGS), may have the capacity to rapidly guide the clinical decision-m...

Full description

Bibliographic Details
Main Authors: Pieter-Jan Van Camp, David B. Haslam, Aleksey Porollo
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Microbiology
Subjects:
antimicrobial resistance
antibiotic resistance
whole-genome sequencing
machine learning
prediction
genotype-phenotype relationship
Online Access:https://www.frontiersin.org/article/10.3389/fmicb.2020.01013/full

Internet

https://www.frontiersin.org/article/10.3389/fmicb.2020.01013/full

Similar Items