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Genetic Databases and their Potential in Pharmacogenomics

Authors: Konstantinos Poulas; George P. Patrinos; George Lagoumintzis;

Genetic Databases and their Potential in Pharmacogenomics

Abstract

The completion of the human genome sequencing project and the establishment of new methods for the detection of point mutations have lead to a remarkable increase of sequence variants identification in a growing number of genes. As a result of this, a new field of research has emerged, pharmacogenomics, which deals with the influence of genetic variation on drug response by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity. Genetic databases are continuously updated online repositories of mutation data, described for a single or more genes or specifically for a population or ethnic group. Genetic databases can also fulfil the mission of pharmacogenomics by helping elucidate gene function, estimate the prevalence of genes in populations, differentiate among subtypes of diseases, trace how genes may predispose to or protect against illnesses, and improve medical intervention. Therefore, it is expected that genetic databases will gradually assume an increasing importance in all aspects of genome medicine. This article aims to provide an update of the current and emerging types of genetic databases relevant to the field of pharmacogenomics. Moreover, the key elements that are holding back the field as well as the challenges that should be addressed in the near future are also commented.

Related Organizations
Keywords

Polymorphism, Genetic, Drug Therapy, Pharmacogenetics, Databases, Genetic, Mutation, Humans, Precision Medicine

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    11
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    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).
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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!
11
Average
Average
Top 10%
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