ArticlePublic health genomics2013
Malaria diagnostics and surveillance in the post-genomic era.
Article in Public health genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Host metabolomic responses in recurrent P. vivax malaria.Scientific reports · 2024Article
- Exploring how space, time, and sampling impact our ability to measure genetic structure acrossFrontiers in epidemiology · 2023Article
- Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering.Scientific reports · 2022Article
- Improving the Molecular Diagnosis of Malaria: Droplet Digital PCR-Based Method Using Saliva as a DNA Source.Frontiers in microbiology · 2022Article
- Potential Opportunities and Challenges of Deploying Next Generation Sequencing and CRISPR-Cas Systems to Support Diagnostics and Surveillance Towards Malaria Control and Elimination in Africa.Frontiers in cellular and infection microbiology · 2022Review
- Metagenomic Pathogen Sequencing in Resource-Scarce Settings: Lessons Learned and the Road Ahead.Frontiers in epidemiology · 2022Article
- The use of proteomics for the identification of promising vaccine and diagnostic biomarkers inParasitology · 2020Review
- Ribosomal and non-ribosomal PCR targets for the detection of low-density and mixed malaria infections.Malaria journal · 2019Article
- TipMT: Identification of PCR-based taxon-specific markers.BMC bioinformatics · 2017Article
- Metabolomics in the fight against malaria.Memorias do Instituto Oswaldo Cruz · 2014Review
- Challenges in diagnosis of Plasmodium knowlesi infections.Tropical parasitology · 2014Article
- Malaria diagnostics in clinical trials.The American journal of tropical medicine and hygiene · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Genome sequences are available for 3 human-infecting malaria parasites, Plasmodium falciparum, P. vivax and P. knowlesi, and population genomics data are available for many endemic regions. This review summarizes how genomic data have been used to develop new, species-specific molecular targets for better malaria diagnosis. The combination of bioinformatics and genomics has been used to identify new sequence targets suitable for diagnostic applications and assess their viability within the context of global Plasmodium sequence variation. The selection criteria maximized the sensitivity and specificity of the novel targets. At least one target from each species was found to be suitable for molecular diagnosis of malaria with some advantages over existing molecular methods. The promise of using genome sequence data to develop sensitive, genus- or species-specific diagnostic methods for other pathogens of public health interest is strong. This undertaking together with what we envision as the future of malaria diagnosis in the 'omic' era is discussed.
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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.