Learning From Limited Data: Towards Best Practice Techniques for Antimicrobial Resistance Prediction From Whole Genome Sequencing Data

Antimicrobial resistance prediction from whole genome sequencing data (WGS) is an emerging application of machine learning, promising to improve antimicrobial resistance surveillance and outbreak monitoring. Despite significant reductions in sequencing cost, the availability and sampling diversity o...

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Vydáno v:Front Cell Infect Microbiol
Hlavní autoři: Lüftinger, Lukas, Májek, Peter, Beisken, Stephan, Rattei, Thomas, Posch, Andreas E.
Médium: Artigo
Jazyk:Inglês
Vydáno: Frontiers Media S.A. 2021
Témata:
Cellular and Infection Microbiology
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC7917081/
https://ncbi.nlm.nih.gov/pubmed/33659219
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fcimb.2021.610348
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