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. 2011 Jul 1;27(13):1741-8.
doi: 10.1093/bioinformatics/btr295. Epub 2011 May 19.

Bioinformatics challenges for personalized medicine

Affiliations

Bioinformatics challenges for personalized medicine

Guy Haskin Fernald et al. Bioinformatics. .

Erratum in

  • Bioinformatics. 2011 Aug 15;27(16):2323

Abstract

Motivation: Widespread availability of low-cost, full genome sequencing will introduce new challenges for bioinformatics.

Results: This review outlines recent developments in sequencing technologies and genome analysis methods for application in personalized medicine. New methods are needed in four areas to realize the potential of personalized medicine: (i) processing large-scale robust genomic data; (ii) interpreting the functional effect and the impact of genomic variation; (iii) integrating systems data to relate complex genetic interactions with phenotypes; and (iv) translating these discoveries into medical practice.

Contact: russ.altman@stanford.edu

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Figures

Fig. 1.
Fig. 1.
Personalized medicine. Personal genomics connect genotype to phenotype and provide insight into disease. Pharmacogenomics connect connects genotype to patient-specific treatment. Traditional medicine defines the pathologic states and clinical observations to evaluate and adjust treatments.
Fig. 2.
Fig. 2.
Number of validated human SNPs in dbSNP overtime.

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