ReviewBMC genomics2026
Strategies for integrating whole-genome sequencing into antimicrobial resistance surveillance.
Review in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Whole-genome analysis of Brevibacterium sanguinis AZMABM HM27: a bacterial isolate from the sea anemone Radianthus magnifica and exhibiting promising multi-therapeutic properties.Molecular biology reports · 2026Article
- Prospects of pathogen whole-genome sequencing in outbreak tracing and antimicrobial resistance surveillance of spinal infections.Frontiers in cellular and infection microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundAntimicrobial resistance (AMR) poses a significant global public health challenge requiring improved diagnostic procedures and strategic surveillance. Such surveillance is imperative for monitoring resistance trends, formulating clinical and public health strategies and guiding stewardship interventions. MAIN BODY: Culture-based susceptibility testing and targeted gene amplification-based molecular methods remain conventional surveillance techniques. However, the limitations of labour and time requirements and narrow resolution make whole-genome sequencing (WGS) a powerful complement, enabling the high-resolution detection of resistance determinants, virulence factors and mobile genetic elements. The integration of WGS into surveillance systems is restricted by bioinformatics capacity, standardisation and interpretability. This review introduces key bioinformatics tools across five domains, i.e. pathogen identification, molecular epidemiology, resistance gene detection, virulence profiling and mobile genetic element analysis, offering structured workflows tailored for both web-based and locally installed environments.
conclusionBy demonstrating the utility and complementarity of WGS-based approaches, we propose a practical and scalable framework for the genomics-based surveillance of AMR. The widespread implementation of these tools, along with advanced user-friendly interfaces and automation, can help bolster pathogen monitoring efforts and enhance the global capacity to combat AMR.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.