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Computational analysis of human genome polymorphism

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Abstract

While genome-era technologies focused on complete genome sequencing in various organisms, post-genome technologies aim at the understanding of the mechanisms of genetic information processing and elucidation of within-species variation. Single nucleotide polymorphisms (SNPs) are the most common source of genome variation in the human population. Nonsynonymous SNPs that occur in coding gene regions and result in amino acid substitutions are of particular interest. It is thought that such SNPs are responsible for phenotypic variation, quantitative traits, and the etiology of common diseases. PolyPhen is a computational tool for the prediction of putatively functional nonsynonymous SNPs by combining information of various types. The application areas of PolyPhen and similar methods include the genetics of complex diseases and congenital defects, the identification of functional mutations in model organisms, and evolutionary genetics.

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Authors and Affiliations

  1. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia

    V. E. Ramensky

  2. Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA

    S. R. Sunyaev

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  1. V. E. Ramensky
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Correspondence to V. E. Ramensky.

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Original Russian Text © V.E. Ramensky, S.R. Sunyaev, 2009, published in Molekulyarnaya Biologiya, 2009, Vol. 43, No. 2, pp. 286–294.

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Ramensky, V.E., Sunyaev, S.R. Computational analysis of human genome polymorphism. Mol Biol 43, 260–268 (2009). https://doi.org/10.1134/S0026893309020095

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