ArticleMicrobial genomics2016
Big data or bust: realizing the microbial genomics revolution.
Article in Microbial genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- How does date-rounding affect phylodynamic inference for public health?PLoS computational biology · 2025Article
- Genomic Epidemiology as a Public Health Tool to Combat Mosquito-Borne Virus Outbreaks.The Journal of infectious diseases · 2020Review
- Towards a genomics-informed, real-time, global pathogen surveillance system.Nature reviews. Genetics · 2018Review
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathogen genomics has the potential to transform the clinical and public health management of infectious diseases through improved diagnosis, detection and tracking of antimicrobial resistance and outbreak control. However, the wide-ranging benefits of this technology can only fully be realized through the timely collation, integration and sharing of genomic and clinical/epidemiological metadata by all those involved in the delivery of genomic-informed services. As part of our review on bringing pathogen genomics into 'health-service' practice, we undertook extensive stakeholder consultation to examine the factors integral to achieving effective data sharing and integration. Infrastructure tailored to the needs of clinical users, as well as practical support and policies to facilitate the timely and responsible sharing of data with relevant health authorities and beyond, are all essential. We propose a tiered data sharing and integration model to maximize the immediate and longer term utility of microbial genomics in healthcare. Realizing this model at the scale and sophistication necessary to support national and international infection management services is not uncomplicated. Yet the establishment of a clear data strategy is paramount if failures in containing disease spread due to inadequate knowledge sharing are to be averted, and substantial progress made in tackling the dangers posed by infectious diseases.
Indexed as
Identifiers
What OpenQuestion holds
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.