ArticleBMC bioinformatics2008
A high-throughput pipeline for designing microarray-based pathogen diagnostic assays.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Development of qPCR Detection Assay for Potato PathogenPlants (Basel, Switzerland) · 2021Article
- Cluster oligonucleotide signatures for rapid identification by sequencing.BMC bioinformatics · 2018Article
- Neptune: a bioinformatics tool for rapid discovery of genomic variation in bacterial populations.Nucleic acids research · 2017Article
- HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing.Evolutionary bioinformatics online · 2016Article
- An algorithm of discovering signatures from DNA databases on a computer cluster.BMC bioinformatics · 2014Article
- Open-target sparse sensing of biological agents using DNA microarray.BMC bioinformatics · 2011Article
- A microbial detection array (MDA) for viral and bacterial detection.BMC genomics · 2010Article
- A high-throughput pipeline for the design of real-time PCR signatures.BMC bioinformatics · 2010Article
- ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design.Nucleic acids research · 2009Article
- Rapid identification of bacterial pathogens using a PCR- and microarray-based assay.BMC microbiology · 2009Article
- Insignia: a DNA signature search web server for diagnostic assay development.Nucleic acids research · 2009Article
- In silico microarray probe design for diagnosis of multiple pathogens.BMC genomics · 2008Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe present a methodology for high-throughput design of oligonucleotide fingerprints for microarray-based pathogen diagnostic assays. The oligonucleotide fingerprints, or DNA microarray probes, are designed for identifying target organisms in environmental or clinical samples. The design process is implemented in a high-performance computing software pipeline that incorporates major algorithmic improvements over a previous version to both reduce computation time and improve specificity assessment.
resultsThe algorithmic improvements result in significant reduction in runtimes, with the updated pipeline being nearly up to five-times faster than the previous version. The improvements in specificity assessment, based on multiple specificity criteria, result in robust and consistent evaluation of cross-hybridization with nontarget sequences. In addition, the multiple criteria provide finer control on the number of resulting fingerprints, which helps in obtaining a larger number of fingerprints with high specificity. Simulation tests for Francisella tularensis and Yersinia pestis, using a well-established hybridization model to estimate cross-hybridization with nontarget sequences, show that the improved specificity criteria yield a larger number of fingerprints as compared to using a single specificity criterion.
conclusionThe faster runtimes, achieved as the result of algorithmic improvements, are critical for extending the pipeline to process multiple target genomes. The larger numbers of identified fingerprints, obtained by considering broader specificity criteria, are essential for designing probes for hard-to-distinguish target sequences.
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