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Cited by 244

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Detection of Single Nucleotide Polymorphisms

Open access
·2003·Current Issues in Molecular Biology

Abstract

Single nucleotide polymorphism (SNP) detection technologies are used to scan for new polymorphisms and to determine the allele(s) of a known polymorphism in target sequences. SNP detection technologies have evolved from labor intensive, time consuming, and expensive processes to some of the most highly automated, efficient, and relatively inexpensive methods. Driven by the Human Genome Project, these technologies are now maturing and robust strategies are found in both SNP discovery and genotyping areas. The nearly completed human genome sequence provides the reference against which all other sequencing data can be compared. Global SNP discovery is therefore only limited by the amount of funding available for the activity. Local, target, SNP discovery relies mostly on direct DNA sequencing or on denaturing high performance liquid chromatography (dHPLC). The number of SNP genotyping methods has exploded in recent years and many robust methods are currently available. The demand for SNP genotyping is great, however, and no one method is able to meet the needs of all studies using SNPs. Despite the considerable gains over the last decade, new approaches must be developed to lower the cost and increase the speed of SNP detection.

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Metadata

Venue
Current Issues in Molecular Biology
Publisher
MDPI AG
Published
2003
Volume
5
Issue
2
Pages
43-60
ISSN
1467-3037 (ISSN-L)
OpenAlex
W3139651602
Cited by
244
References
4
FWCI
7.20
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Detection of Single Nucleotide Polymorphisms. https://app.cochat.ai/papers/10.21775/cimb.005.043
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Detection of Single Nucleotide Polymorphisms. (2003). Current Issues in Molecular Biology. https://doi.org/10.21775/cimb.005.043

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.