Detecting SNP-Induced Structural Changes in RNA: Application to Disease Studies

  • Raheleh Salari
  • Chava Kimchi-Sarfaty
  • Michael M. Gottesman
  • Teresa M. Przytycka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7262)

Abstract

Genotype-phenotype association studies continue to provide ever larger sets of Single Nucleotide Polymorphisms (SNPs) linked to diseases, or associated with responses to vaccines, medications, and environmental factors. Such associations provide an important step in studies of the genetic underpinnings of human diseases. To gain further insight, a deeper understanding of the molecular mechanisms by which a SNP affects cell function is necessary. When a SNP is localized within a gene or in the close neighborhood of a gene, then it is generally assumed that it affects the phenotype through changes at the expression level, the function, or other properties of this particular gene. However, the molecular mechanisms that lead to the change are usually not obvious. In the case of non-synonymous SNPs, where the underlying mutation occurs in the gene coding region and changes an amino-acid, it is usually expected that this amino-acid change affects protein function, expression, conformation or stability.

Keywords

Relative Entropy Synonymous Mutation Gene Code Region mRNA Secondary Structure Genetic Underpinning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Raheleh Salari
    • 1
  • Chava Kimchi-Sarfaty
    • 2
  • Michael M. Gottesman
    • 3
  • Teresa M. Przytycka
    • 1
  1. 1.National Center for Biotechnology Information, National Library of MedicineNIHBethesdaUSA
  2. 2.Laboratory of Hemostasis, Division of Hematology, Center for Biologics Evaluation and ResearchFood and Drug AdministrationBethesdaUSA
  3. 3.Center for Cancer Research, National Cancer InstituteNIHBethesdaUSA

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