Program complex SNP-MED for analysis of single-nucleotide polymorphism (SNP) effects on the function of genes associated with socially significant diseases

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• 作者：N. L. Podkolodnyy (1)
  D. A. Afonnikov (1)
  Yu. Yu. Vaskin (2)
  L. O. Bryzgalov (1)
  V. A. Ivanisenko (1)
  P. S. Demenkov (1)
  M. P. Ponomarenko (1)
  D. A. Rasskazov (1)
  K. V. Gunbin (1)
  I. V. Protsyuk (2)
  I. Yu. Shutov (2)
  P. N. Leontyev (2)
  M. Yu. Fursov (2)
  N. P. Bondar (1)
  E. V. Antontseva (1)
  T. I. Merkulova (1)
  N. A. Kolchanov (1)
  
• 关键词：bioinformatics ; single ; nucleotide polymorphism (SNP) ; personalized medicine
• 刊名：Russian Journal of Genetics: Applied Research
• 出版年：2014
• 出版时间：May 2014
• 年：2014
• 卷：4
• 期：3
• 页码：159-167
• 全文大小：701 KB
• 参考文献：1. Adzhubei, I.A., Schmidt, S., Peshkin, L., et al., A method and server for predicting damaging missense mutations, / Nature Meth., 2010, vol. 7, no. 4, pp. 248-49. <a class="external" href="http://dx.doi.org/10.1038/nmeth0410-248" target="_blank" title="It opens in new window">CrossRefa>
  2. Cavallo, A. and Martin, A.C., Mapping SNPs to protein sequence and structure data, / Bioinformatics, 2005, vol. 21, pp. 1443-450. <a class="external" href="http://dx.doi.org/10.1093/bioinformatics/bti220" target="_blank" title="It opens in new window">CrossRefa>
  3. Farnebo, M., Bykov, V.J., and Wiman, K.G., The p53 tumor suppressor: a master regulator of diverse cellular processes and therapeutic target in cancer, / Biochem. Biophys Res. Commun., 2010, pp. 85-9.
  4. Gerstenblith, M.R., Shi, J., and Landi, M.T., Genomewide association studies of pigmentation and skin cancer: a review and meta-analysis, / Pigment Cell Melanoma Res., 2010, vol. 23, no. 5, pp. 587-06. <a class="external" href="http://dx.doi.org/10.1111/j.1755-148X.2010.00730.x" target="_blank" title="It opens in new window">CrossRefa>
  5. Ivanisenko, V.A., Demenkov, P.S., Ivanisenko, T.V., and Kolchanov, N.A., Protein structure discovery: a software package to computer proteomics tasks (review), / Russ. J. Bioorg. Chem., 2011, vol. 37, no. 1, pp. 17-9. <a class="external" href="http://dx.doi.org/10.1134/S1068162011010080" target="_blank" title="It opens in new window">CrossRefa>
  6. Johnson A.D. and Donnell, C.J., An open access database of genome-wide association results, / BMC Med. Genet., 2009, vol. 10, no. 1, p. 6. <a class="external" href="http://dx.doi.org/10.1186/1471-2350-10-6" target="_blank" title="It opens in new window">CrossRefa>
  7. Karchin, R., Diekhans, M., Kelly, L., et al., LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources, / Bioinformatics, 2005, vol. 21, pp. 2814-820. <a class="external" href="http://dx.doi.org/10.1093/bioinformatics/bti442" target="_blank" title="It opens in new window">CrossRefa>
  8. Mooney, S.D., Krishnan, V.G., and Evani, U.S., Bioinformatic tools for identifying disease gene and SNP candidates, / In Genetic Variation, 2010, pp. 307-19. <a class="external" href="http://dx.doi.org/10.1007/978-1-60327-367-1_17" target="_blank" title="It opens in new window">CrossRefa>
  9. Moore, J.H., Asselbergs, F.W., and Williams, S.M., Bioinformatics challenges for genome-wide association studies, / Bioinformatics, 2010, vol. 26, pp. 445-55. <a class="external" href="http://dx.doi.org/10.1093/bioinformatics/btp713" target="_blank" title="It opens in new window">CrossRefa>
  10. Na, Y.J., Cho, Y., and Kim, J.H., AnsNGS: an annotation system to sequence variations of next generation sequencing data for disease-related phenotypes, / Healthcare Inform. Res., 2013, vol. 19, no. 1, pp. 50-5. <a class="external" href="http://dx.doi.org/10.4258/hir.2013.19.1.50" target="_blank" title="It opens in new window">CrossRefa>
  11. Ng, P.C. and Henikoff, S., Sift: predicting amino acid changes that affect protein function, / Nucleic Acids Res., 2003, vol. 31, pp. 3812-814. <a class="external" href="http://dx.doi.org/10.1093/nar/gkg509" target="_blank" title="It opens in new window">CrossRefa>
  12. Okonechnikov, K., Golosova, O., Fursov, M., et al., Unipro UGENE: a unified bioinformatics toolkit, / Bioinformatics, 2012, vol. 28, pp. 1166-167. <a class="external" href="http://dx.doi.org/10.1093/bioinformatics/bts091" target="_blank" title="It opens in new window">CrossRefa>
  13. Pollard, K.S., Hubisz, M.J., Rosenbloom, K.R., and Siepel, A., Detection of nonneutral substitution rates on mammalian phylogenies, / Genome Res., 2010, vol. 20, no. 1, pp. 110-21. <a class="external" href="http://dx.doi.org/10.1101/gr.097857.109" target="_blank" title="It opens in new window">CrossRefa>
  14. Ponomarenko, P.M., Savinkova, L.K., Drachkova, I.A., et al., A step-by-step model of TBP/TATA box binding allows predicting human hereditary diseases by single nucleotide polymorphism, / Dokl. Biochem. Biophys., 2008, vol. 419, pp. 88-2. <a class="external" href="http://dx.doi.org/10.1134/S1607672908020117" target="_blank" title="It opens in new window">CrossRefa>
  15. Psychiatric GWAS Consortium Steering Committee. A Frame work for interpreting genome-wide association studies of psychiatric disorders, / Mol. Psychiatry, 2009, vol. 14, no. 1, p. 10. <a class="external" href="http://dx.doi.org/10.1038/mp.2008.126" target="_blank" title="It opens in new window">CrossRefa>
  16. Ramensky, V., Bork, P., and Sunyaev, S., Human non-synonymous SNPs: server and survey, / Nucleic Acids Res., 2002, vol. 30, pp. 3894-900. <a class="external" href="http://dx.doi.org/10.1093/nar/gkf493" target="_blank" title="It opens in new window">CrossRefa>
  17. Rosenbloom, K.R., Sloan, C.A., Malladi, V.S., et al., Encode data in the UCSC genome browser: year 5 update, / Nucleic Acids Res., 2013, pp. D56–D63.
  18. Sanchez-Ruiz, J.M., Protein kinetic stability, / Biophys. Chem., 2010, vol. 148, pp. 1-5. <a class="external" href="http://dx.doi.org/10.1016/j.bpc.2010.02.004" target="_blank" title="It opens in new window">CrossRefa>
  19. Savinkova, L.K., Ponomarenko, M.P., Ponomarenko, P.M., et al., TATA box polymorphisms in human gene promoters and associated hereditary pathologies, / Biochemistry (Moscow), 2009, vol. 4, no. 2, pp. 117-29. <a class="external" href="http://dx.doi.org/10.1134/S0006297909020011" target="_blank" title="It opens in new window">CrossRefa>
  20. Sherry, S.T., Ward, M.H., Kholodov, M., et al., dbSNP: the NCBI database of genetic variation, / Nucleic Acids Res., 2001, no. 29, pp. 308-11.
  21. / Sistemnaya komp’yuternaya biologiya (Computer System Biology), Kolchanov, N.A., Goncharov, S.S., Likhoshv, V.A., and Ivanisenko, V.A., Eds., Novosibirsk: SO RAN, 2008.
  22. Torkamani, A., Topol, E.J., Schorkn, J., Pathway analysis of seven common diseases assessed by genome-wide association, / Genomics, 2008, no. 92, pp. 265-72.
  23. Weston, A.D., L h. systems biology, proteomics, and the future of healthcare: toward predictive, preventative, and personalized medicine, / J. Proteome Res., 2004, vol. 3, no. 2, pp. 179-96. <a class="external" href="http://dx.doi.org/10.1021/pr0499693" target="_blank" title="It opens in new window">CrossRefa>
  24. Yue, P., Melamud, E., and Moult, J., SNPs3D: candidate gene and SNP selection for association studies, / BMC Bioinformatics, 2006, no. 7, p. 166.
  
• 作者单位：N. L. Podkolodnyy (1)
  D. A. Afonnikov (1)
  Yu. Yu. Vaskin (2)
  L. O. Bryzgalov (1)
  V. A. Ivanisenko (1)
  P. S. Demenkov (1)
  M. P. Ponomarenko (1)
  D. A. Rasskazov (1)
  K. V. Gunbin (1)
  I. V. Protsyuk (2)
  I. Yu. Shutov (2)
  P. N. Leontyev (2)
  M. Yu. Fursov (2)
  N. P. Bondar (1)
  E. V. Antontseva (1)
  T. I. Merkulova (1)
  N. A. Kolchanov (1)
  
  1. Institute of Cytology and Genetics, Russian Academy of Sciences (RAS), Novosibirsk, 630090, Russia
  2. Novosibirsk Center for Information Technologies UNIPRO, Novosibirsk, 630090, Russia
  
• ISSN：2079-0600

文摘

We describe development and application of the new SNP-MED modular software system, designed to examine the influence of single-nucleotide polymorphisms (SNPs) on the function of genes associated with the risk of socially significant diseases. The SNP-MED system includes Genomics, Proteomics, and Gene Networks-software components, and the Information Resource Database.