[Computational analysis of human genome polymorphism].
Whereas the genome-era technologies have produced the sequence of complete human genome, the modern post-genome technologies aim at the understanding of mechanisms of processing of genetic information and elucidation of within-species variation. Single nucleotide polymorphisms (SNPs) comprise the majority of polymorphism in the human population. Non-synonymous coding SNPs together with SNPs in regulatory regions are believed to have the highest impact on complex disease etiology, quantitative traits and response to drug treatment. PolyPhen is a computational tool for prediction of putatively functional nsSNPs with application areas such as genetics of complex disease, birth defects, identification of functional mutations in model organisms and evolutionary genetics.
Ramenskiĭ
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Siuniaev
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ShR
D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human / Q000502:physiology*; D006801:Humans; D011110:Polymorphism, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods*