ArticleNucleic acids research2006
Automated identification of multiple micro-organisms from resequencing DNA microarrays.
Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Development and Assessment of a Diagnostic DNA Oligonucleotide Microarray for Detection and Typing of Meningitis-Associated Bacterial Species.High-throughput · 2018Article
- Identification and Quantification of Celery Allergens Using Fiber Optic Surface Plasmon Resonance PCR.Sensors (Basel, Switzerland) · 2017Article
- Association of targeted multiplex PCR with resequencing microarray for the detection of multiple respiratory pathogens.Frontiers in microbiology · 2015Article
- Article
- Article
- Multipurpose instantaneous microarray detection of acute encephalitis causing viruses and their expression profiles.Current microbiology · 2012Review
- Leapfrog diagnostics: Demonstration of a broad spectrum pathogen identification platform in a resource-limited setting.Health research policy and systems · 2012Article
- Single sample expression-anchored mechanisms predict survival in head and neck cancer.PLoS computational biology · 2012Article
- Microarrays for pathogen detection and analysis.Briefings in functional genomics · 2011Review
- Application of a broad-range resequencing array for detection of pathogens in desert dust samples from Kuwait and Iraq.Applied and environmental microbiology · 2011Article
- Application of broad-spectrum resequencing microarray for genotyping rhabdoviruses.Journal of virology · 2010Article
- VIPR: A probabilistic algorithm for analysis of microbial detection microarrays.BMC bioinformatics · 2010Article
- Broad spectrum respiratory pathogen analysis of throat swabs from military recruits reveals interference between rhinoviruses and adenoviruses.Microbial ecology · 2010Article
- Article
- Emerging molecular assays for detection and characterization of respiratory viruses.Clinics in laboratory medicine · 2009Review
- Basic concepts of microarrays and potential applications in clinical microbiology.Clinical microbiology reviews · 2009Review
- Testing and validation of high density resequencing microarray for broad range biothreat agents detection.PloS one · 2009Article
- Universal detection and identification of avian influenza virus by use of resequencing microarrays.Journal of clinical microbiology · 2009Article
- Robust methods for accurate diagnosis using pan-microbiological oligonucleotide microarrays.BMC bioinformatics · 2009Article
- Resequencing arrays for diagnostics of respiratory pathogens.Methods in molecular biology (Clifton, N.J.) · 2009Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is an increasing recognition that detailed nucleic acid sequence information will be useful and even required in the diagnosis, treatment and surveillance of many significant pathogens. Because generating detailed information about pathogens leads to significantly larger amounts of data, it is necessary to develop automated analysis methods to reduce analysis time and to standardize identification criteria. This is especially important for multiple pathogen assays designed to reduce assay time and costs. In this paper, we present a successful algorithm for detecting pathogens and reporting the maximum level of detail possible using multi-pathogen resequencing microarrays. The algorithm filters the sequence of base calls from the microarray and finds entries in genetic databases that most closely match. Taxonomic databases are then used to relate these entries to each other so that the microorganism can be identified. Although developed using a resequencing microarray, the approach is applicable to any assay method that produces base call sequence information. The success and continued development of this approach means that a non-expert can now perform unassisted analysis of the results obtained from partial sequence data.
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