Predicting Listeria monocytogenes virulence potential using whole genome sequencing and machine learning.

Gmeiner, Alexander; Njage, Patrick Murigu Kamau; Hansen, Lisbeth Truelstrup; Aarestrup, Frank M; Leekitcharoenphon, Pimlapas

Gmeiner, Alexander; Njage, Patrick Murigu Kamau; Hansen, Lisbeth Truelstrup; Aarestrup, Frank M; Leekitcharoenphon, Pimlapas.

Afiliação

Gmeiner A; National Food Institute, Technical University of Denmark, Research Group for Genomic Epidemiology, Kgs. Lyngby, Denmark. Electronic address: algm@food.dtu.dk.
Njage PMK; National Food Institute, Technical University of Denmark, Research Group for Genomic Epidemiology, Kgs. Lyngby, Denmark.
Hansen LT; National Food Institute, Technical University of Denmark, Research Group for Food Microbiology and Hygiene, Kgs. Lyngby, Denmark.
Aarestrup FM; National Food Institute, Technical University of Denmark, Research Group for Genomic Epidemiology, Kgs. Lyngby, Denmark.
Leekitcharoenphon P; National Food Institute, Technical University of Denmark, Research Group for Genomic Epidemiology, Kgs. Lyngby, Denmark.

Int J Food Microbiol ; 410: 110491, 2024 Jan 30.

Article em En | MEDLINE | ID: mdl-38000216

Assuntos

Listeria monocytogenes; Virulência/genética; Tipagem de Sequências Multilocus; Microbiologia de Alimentos; Sequenciamento Completo do Genoma/métodos; Aprendizado de Máquina

Palavras-chave

Clinical frequency; Food safety; Hazard characterization; National surveillance; Pan-genome; Virulence genes

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Listeria monocytogenes Idioma: En Ano de publicação: 2024 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Listeria monocytogenes Idioma: En Ano de publicação: 2024 Tipo de documento: Article