Cargando…
Machine learning to predict the source of campylobacteriosis using whole genome data
Campylobacteriosis is among the world’s most common foodborne illnesses, caused predominantly by the bacterium Campylobacter jejuni. Effective interventions require determination of the infection source which is challenging as transmission occurs via multiple sources such as contaminated meat, poult...
Autores principales: | Arning, Nicolas, Sheppard, Samuel K., Bayliss, Sion, Clifton, David A., Wilson, Daniel J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553134/ https://www.ncbi.nlm.nih.gov/pubmed/34662334 http://dx.doi.org/10.1371/journal.pgen.1009436 |
Ejemplares similares
-
Source Attribution of Human Campylobacteriosis Using Whole-Genome Sequencing Data and Network Analysis
por: Wainaina, Lynda, et al.
Publicado: (2022) -
Tracing the Source of Campylobacteriosis
por: Wilson, Daniel J., et al.
Publicado: (2008) -
Comparison of Source Attribution Methodologies for Human Campylobacteriosis
por: Brinch, Maja Lykke, et al.
Publicado: (2023) -
Ruminant and chicken: important sources of campylobacteriosis in France despite a variation of source attribution in 2009 and 2015
por: Thépault, Amandine, et al.
Publicado: (2018) -
Rapid geographical source attribution of Salmonella enterica serovar Enteritidis genomes using hierarchical machine learning
por: Bayliss, Sion C, et al.
Publicado: (2023)