AIMC Topic: Shiga Toxin 2

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Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates.

Proceedings of the National Academy of Sciences of the United States of America Sep 19, 2016
Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are generally used after an outbreak has hap...
Humans Animals Disease Outbreaks Phylogeny Cattle Cattle Diseases Support Vector Machine Escherichia coli O157 Escherichia coli Infections United Kingdom Zoonoses Shiga Toxin 2
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Pathogenic potential assessment of the Shiga toxin-producing by a source attribution-considered machine learning model.

Proceedings of the National Academy of Sciences of the United States of America May 18, 2021
Instead of conventional serotyping and virulence gene combination methods, methods have been developed to evaluate the pathogenic potential of newly emerging pathogens. Among them, the machine learning (ML)-based method using whole-genome sequencing ...
Humans Machine Learning Reproducibility of Results ROC Curve Support Vector Machine Escherichia coli Infections Whole Genome Sequencing Virulence Shiga-Toxigenic Escherichia coli Escherichia coli Proteins Shiga Toxin 2
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