Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species

24 Aug 2023

Abstract excerpt

Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Antibiotic Resistance in Bacteria
Share to Genomics and Phylogenetic Studies
Share to Mycobacterium research and diagnosis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 37616210
DOI: 10.1371/journal.pone.0290473

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal speciesPMID 37616210Read ↗

An accurate and interpretable model for antimicrobial resistance in pathogenic <i>Escherichia coli</i> from livestock and companion animal speciesSemantic proximity Read ↗

A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains.Semantic proximity Read ↗

Exploring the extent of uncatalogued genetic variation in antimicrobial resistance gene families in<i>Escherichia coli</i>Semantic proximity Read ↗

Exploring uncatalogued genetic variation in antimicrobial resistance gene families in Escherichia coli: an observational analysis.Semantic proximity Read ↗

Machine Learning Predicts Antimicrobial Resistance from Genomic Data across ESKAPEE PathogensSemantic proximity Read ↗

Precise prediction of antibiotic resistance in <i>Escherichia coli</i> from full genome sequencesSemantic proximity Read ↗

Genomic and Machine Learning Approaches for Predicting Antimicrobial Resistance: A One Health Scoping Review in Low- and Middle-Income CountriesSemantic proximity Read ↗

Prediction of Antimicrobial Resistance in Clinical Enterococcus faecium Isolates Using a Rules-Based Analysis of Whole-Genome SequencesSemantic proximity Read ↗

Global genomic surveillance of β-lactam resistance in Escherichia coli across human, animal, and environmental reservoirsSemantic proximity Read ↗

A One Health perspective on the use of genotypic methods for antimicrobial resistance prediction.Semantic proximity Read ↗

Prediction of Antibiotic Resistance Phenotypes and Minimum Inhibitory Concentrations in Salmonella Using Machine Learning Analysis of Its Pan-Genome and Pan-Resistome Features.Semantic proximity Read ↗

Estimating the association of antimicrobial resistance genes with minimum inhibitory concentration in Escherichia coli: an observational study.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.