MGS2AMR: a gene-centric mining of metagenomic sequencing data for pathogens and their antimicrobial resistance profile

BACKGROUND: Identification of pathogenic bacteria from clinical specimens and evaluating their antimicrobial resistance (AMR) are laborious tasks that involve in vitro cultivation, isolation, and susceptibility testing. Recently, a number of methods have been developed that use machine learning algo...

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Detalles Bibliográficos
Autores principales: Van Camp, Pieter-Jan, Prasath, V. B. Surya, Haslam, David B., Porollo, Aleksey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571262/
https://www.ncbi.nlm.nih.gov/pubmed/37833777
http://dx.doi.org/10.1186/s40168-023-01674-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571262/
https://www.ncbi.nlm.nih.gov/pubmed/37833777
http://dx.doi.org/10.1186/s40168-023-01674-z

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