Genomic signatures associated with epidemiologically defined high-risk pathogenic Escherichia coli isolates identified by interpretable machine learning.

Hwang Y, Cho WY, Lee W, Joo I, Shin JI, Seo MR, Shin SH, Ko KS, Park KT, Chung YJ, Jung SH.

Open source

DOI
10.71150/jm.2604011
Published
2026-08-31
Container
J Microbiol
Publisher
Not recorded
Open access
no

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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

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