ReviewEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2013
Automated extraction of typing information for bacterial pathogens from whole genome sequence data: Neisseria meningitidis as an exemplar.
Review in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 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
42 citing papers in PubMed.
- Impact of mandatory vaccination against serogroup C meningococci in targeted and non-targeted populations in France.NPJ vaccines · 2022Article
- Bioinformatics tools used for whole-genome sequencing analysis of Neisseria gonorrhoeae: a literature review.Briefings in functional genomics · 2022Review
- Evolution of strain coverage by the multicomponent meningococcal serogroup B vaccine (4CMenB) in France.Human vaccines & immunotherapeutics · 2021Article
- An Improved Approach to Identify Bacterial Pathogens to Human in Environmental Metagenome.Journal of microbiology and biotechnology · 2020Article
- Difference in virulence between Neisseria meningitidis serogroups W and Y in transgenic mice.BMC microbiology · 2020Article
- Article
- Genomic epidemiology of multidrug-resistant Gram-negative organisms.Annals of the New York Academy of Sciences · 2019Review
- Establishment of the European meningococcal strain collection genome library (EMSC-GL) for the 2011 to 2012 epidemiological year.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2018Article
- Persistent Pandemic Lineages of Uropathogenic Escherichia coli in a College Community from 1999 to 2017.Journal of clinical microbiology · 2018Article
- Distinct evolutionary patterns of Neisseria meningitidis serogroup B disease outbreaks at two universities in the USA.Microbial genomics · 2018Article
- The Impact of Nucleotide Sequence Analysis on Meningococcal Vaccine Development and Assessment.Frontiers in immunology · 2018Review
- Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications.Wellcome open research · 2018Article
- Typing complex meningococcal vaccines to understand diversity and population structure of key vaccine antigens.Wellcome open research · 2018Article
- Microbiome at the Frontier of Personalized Medicine.Mayo Clinic proceedings · 2017Review
- Neisseria genomics: current status and future perspectives.Pathogens and disease · 2017Review
- Survey on the Use of Whole-Genome Sequencing for Infectious Diseases Surveillance: Rapid Expansion of European National Capacities, 2015-2016.Frontiers in public health · 2017Article
- Global Meningococcal Initiative: guidelines for diagnosis and confirmation of invasive meningococcal disease.Epidemiology and infection · 2016Review
- Population and Functional Genomics of Neisseria Revealed with Gene-by-Gene Approaches.Journal of clinical microbiology · 2016Review
- Genomic Analysis of Serogroup Y Neisseria meningitidis Isolates Reveals Extensive Similarities Between Carriage-Associated and Disease-Associated Organisms.The Journal of infectious diseases · 2016Article
- Whole genome multilocus sequence typing as an epidemiologic tool for Yersinia pestis.Diagnostic microbiology and infectious disease · 2016Article
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
Whole genome sequence (WGS) data are increasingly used to characterise bacterial pathogens. These data provide detailed information on the genotypes and likely phenotypes of aetiological agents, enabling the relationships of samples from potential disease outbreaks to be established precisely. However, the generation of increasing quantities of sequence data does not, in itself, resolve the problems that many microbiological typing methods have addressed over the last 100 years or so; indeed, providing large volumes of unstructured data can confuse rather than resolve these issues. Here we review the nascent field of storage of WGS data for clinical application and show how curated sequence-based typing schemes on websites have generated an infrastructure that can exploit WGS for bacterial typing efficiently. We review the tools that have been implemented within the PubMLST website to extract clinically useful, strain-characterisation information that can be provided to physicians and public health professionals in a timely, concise and understandable way. These data can be used to inform medical decisions such as how to treat a patient, whether to instigate public health action, and what action might be appropriate. The information is compatible both with previous sequence-based typing data and also with data obtained in the absence of WGS, providing a flexible infrastructure for WGS-based clinical microbiology.
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.