DNA-mounted self-assembly: new approaches for genomic analysis and SNP detection
Autor: | Elena V. Bichenkova, Xuan Yu, Kenneth T. Douglas, Zhaolei Lang, C Rogert |
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Rok vydání: | 2010 |
Předmět: |
Genotype
Genome Human Biophysics Robustness (evolution) Nucleic Acid Hybridization Reproducibility of Results Nanotechnology Computational biology DNA Biology Diagnostic tools Biochemistry Polymorphism Single Nucleotide SNP genotyping Dna detection Structural Biology Genetics SNP Humans Single point DNA Probes Molecular Biology Nucleic acid detection |
Zdroj: | Biochimica et biophysica acta. 1809(1) |
ISSN: | 0006-3002 |
Popis: | This article presents an overview of new emerging approaches for nucleic acid detection via hybridization techniques that can potentially be applied to genomic analysis and SNP identification in clinical diagnostics. Despite the availability of a diverse variety of SNP genotyping technologies on the diagnostic market, none has truly succeeded in dominating its competitors thus far. Having been designed for specific diagnostic purposes or clinical applications, each of the existing bio-assay systems (briefly outlined here) is usually limited to a relatively narrow aspect or format of nucleic acid detection, and thus cannot entirely satisfy all the varieties of commercial requirements and clinical demands. This drives the diagnostic sector to pursue novel, cost-effective approaches to ensure rapid and reliable identification of pathogenic or hereditary human diseases. Hence, the purpose of this review is to highlight some new strategic directions in DNA detection technologies in order to inspire development of novel molecular diagnostic tools and bio-assay systems with superior reliability, reproducibility, robustness, accuracy and sensitivity at lower assay cost. One approach to improving the sensitivity of an assay to confidently discriminate between single point mutations is based on the use of target assembled, split-probe systems, which constitutes the main focus of this review. |
Databáze: | OpenAIRE |
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