Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Techniques patents for SNP genotyping

Authors: Richard M. Twyman; Sandy B. Primrose;

Techniques patents for SNP genotyping

Abstract

Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation in the human genome, accounting for more than 90% of all differences between individuals. Many complex phenotypes in humans have a significant genetic component and most of the variability is therefore likely to stem from differences in patterns of SNPs. Association studies involving the large-scale analysis of SNPs can help to identify genes affecting many human phenotype variations, including complex diseases and drug responses. SNPs therefore play a major role in all stages of the drug development process, from target identification through to clinical trials. SNPs are also the basis of pharmacogenomics, the tailoring of medicines to suit an individual's genome. Given the potential impact of SNPs on healthcare, the biotechnology industry has focussed urgently on the development of high-throughput methods for SNP genotyping. All genotyping methods are a mix and match of different allele discrimination and signal detection technologies and as such may represent the intellectual property of several individuals or organizations. In this review, we explore the patent issues surrounding SNP genotyping and how this is influencing large scale, commercially valuable projects involving SNPs.

Related Organizations
Keywords

Patents as Topic, Genotype, Genome, Human, Humans, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, United Kingdom

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    48
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Average
Top 10%
Top 10%
Upload OA version
Are you the author? Do you have the OA version of this publication?