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

Topics Community

Article

Genomics-driven risk assessment of antimicrobial resistance: Current status, challenges, and future perspectives.

Food research international (Ottawa, Ont.) - 30 Sept 2026

Cheng Peipei, Wang Qian, He Wanting, Zhu Xueyuan, Cheng Yu, Xiao Linlin, Dong Qingli

Abstract excerpt

Antimicrobial resistance has become a major global public health challenge. However, conventional antimicrobial resistance risk assessment has largely focused on phenotypes while overlooking the dynamic dissemination of resistance genes and their mobility. This review systematically examines how genomics is reshaping microbial antimicrobial resistance risk assessment, with particular emphasis on the integration...

Topics

Join the communities discussing this publication.

Anti-Bacterial Agents
Bacteria
Drug Resistance, Bacterial
Food Microbiology
Gene Transfer, Horizontal

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Risk Assessment

Source

Identifiers

PMID: 42409569
DOI: 10.1016/j.foodres.2026.119632

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

0

discussions

0

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Genomics-driven risk assessment of antimicrobial resistance: Current status, challenges, and future perspectives.PMID 42409569Read ↗

Integrative Phenotypic and Genotypic Surveillance and Risk Assessment of Foodborne Antimicrobial Resistance in Meat-Environment Continuum.Semantic proximity Read ↗

Choosing Your Battles: Which Resistance Genes Warrant Global Action?Semantic proximity Read ↗

Genomics for antimicrobial resistance—progress and future directionsSemantic proximity Read ↗

Mapping the underlying drivers of resistome risk across diverse environmentsSemantic proximity Read ↗

An omics-based framework for assessing the health risk of antimicrobial resistance genesSemantic proximity Read ↗

MetaCompare: a computational pipeline for prioritizing environmental resistome riskSemantic proximity Read ↗

Evaluating human exposure to antibiotic resistance genesSemantic proximity Read ↗

The role of intracellular ROS in the development of antimicrobial resistance:A convergent mediator linking mutations and horizontal gene transfer.Semantic proximity Read ↗

Integrated cross-sectoral surveillance of antimicrobial resistance genotypes and phenotypes across disparate reservoirsSemantic proximity Read ↗

MetaCompare 2.0: Differential ranking of ecological and human health resistome risksSemantic proximity Read ↗

Multimodal Raman-Gene Framework for Interpretable Phenotypic Antibiotic Resistance and Health Risk Stratification.Semantic proximity Read ↗

Beyond Outbreak Detection: Mandatory Genomic Surveillance in the EU as an Opportunity to Quantify Metal-Mediated Co-Selection of Antimicrobial Resistance from a One Health PerspectiveSemantic proximity Read ↗

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