Genomic signatures associated with epidemiologically defined high-risk pathogenic Escherichia coli isolates identified by interpretable machine learning.
- DOI
- 10.71150/jm.2604011
- Published
- 2026-08-31
- Container
- J Microbiol
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.71150/jm.2604011,
title = {Genomic signatures associated with epidemiologically defined high-risk pathogenic Escherichia coli isolates identified by interpretable machine learning.},
author = {Hwang Y and Cho WY and Lee W and Joo I and Shin JI and Seo MR and Shin SH and Ko KS and Park KT and Chung YJ and Jung SH.},
year = {2026},
journal = {J Microbiol},
doi = {10.71150/jm.2604011},
url = {https://doi.org/10.71150/jm.2604011}
}RIS
TY - JOUR TI - Genomic signatures associated with epidemiologically defined high-risk pathogenic Escherichia coli isolates identified by interpretable machine learning. AU - Hwang Y AU - Cho WY AU - Lee W AU - Joo I AU - Shin JI AU - Seo MR AU - Shin SH AU - Ko KS AU - Park KT AU - Chung YJ AU - Jung SH. PY - 2026 JO - J Microbiol DO - 10.71150/jm.2604011 UR - https://doi.org/10.71150/jm.2604011 ER -
APA
Y, H., WY, C., W, L., I, J., JI, S., MR, S., SH, S., KS, K., KT, P., YJ, C., & SH., J. (2026). Genomic signatures associated with epidemiologically defined high-risk pathogenic Escherichia coli isolates identified by interpretable machine learning.. J Microbiol. https://doi.org/10.71150/jm.2604011
Source records
- europe-pmc · retrieved 2026-09-26T03:41:48.849Z