THE SNP-MED SYSTEM FOR ANALYSIS OF THE EFFECT OF SINGLE-NUCLEOTIDE POLYMORPHISMS ON THE FUNCTION OF GENES ASSOCIATED WITH SOCIALLY SIGNIFICANT DISEASES

This paper describes the SNP-MED modular computer-based information system for estimation of the influence of single nucleotide polymorphisms (SNPs) on the function of genes associated with the risk of socially significant diseases. The system includes software components Genomics, Proteomics, Gene networks and the Information resource database (BDIR).

1. Иванисенко В.А., Деменков П.С., Иванисенко Т.В., Колчанов Н.А. Protein structure discovery: пакет программ для решения задач компьютерной протеомики // Биоорган. химия. 2011. Т. 37. № 1. С. 22–35.

2. Пономаренко П.М., Савинкова Л.К., Драчкова И.А. и др. Пошаговая модель связывания TBP/TATA-бокс позволяет предсказать наследственное заболевание человека по точечному полиморфизму // Докл. АН. 2008. Т. 419. С. 828–832.

3. Савинкова Л.К., Пономаренко М.П., Пономаренко П.М. и др. Полиморфизмы ТАТА-боксов промоторов генов человека и ассоциированные с ними наследственные патологии // Биохимия. 2009. Т. 4. № 4. С. 149–163.

4. Системная компьютерная биология // Под ред. Н.А. Колчанов, С.С. Гончаров, В.А. Лихошва, В.А. Иванисенко. Новосибирск: СО РАН, 2008.

5. AdzhubeiI.A., Schmidt S., Peshkin L. et al. A method and server for predicting damaging missense mutations // Nature Meth. 2010. V. 7. No. 4. P. 248–249.

6. Cavallo A., Martin A.C. Mapping SNPs to protein sequence and structure data // Bioinformatics. 2005. V. 21. P. 1443–1450.

7. Farnebo M., Bykov V.J., Wiman K.G. The p53 tumor suppressor: a master regulator of diverse cellular processes and therapeutic target in cancer // Biochem. Biophys Res. Commun. 2010. Р. 85–89.

8. Gerstenblith M.R., Shi J., Landi M.T. Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis // Pigment Cell Melanoma Res. 2010. V. 23. No. 5. Р. 587–606.

9. Johnson A.D., O’Donnell C.J. An open access database of genome-wide association results // BMC Med. Genet. 2009. V. 10. No. 1. P. 6.

10. 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. V. 21. P. 2814–2820.

11. Mooney S.D., Krishnan V.G., Evani U.S. Bioinformatic tools for identifying disease gene and SNP candidates // In Genetic Variation. 2010. P. 307–319.

12. Moore J.H., Asselbergs F.W., Williams S.M. Bioinformatics challenges for genome-wide association studies // Bioinformatics. 2010. V. 26. Р. 445–455.

13. Na Y.J., Cho Y., Kim J.H. AnsNGS: An annotation system to sequence variations of next generation sequencing data for disease-related phenotypes // Healthcare Inform. Res. 2013. V. 19. No. 1. Р. 50–55.

14. Ng P.C., Henikoff S. SIFT: Predicting amino acid changes that affect protein function // Nucl. Acids Res. 2003. V. 31. Р. 3812–3814.

15. Okonechnikov K., Golosova O., Fursov M. et al. Unipro UGENE: a unified bioinformatics toolkit // Bioinformatics. 2012. V. 28. P. 1166–1167.

16. Pollard K.S., Hubisz M.J., Rosenbloom K.R., Siepel A. Detection of nonneutral substitution rates on mammalian phylogenies // Genome Res. 2010. V. 20. No. 1. Р. 110–121.

17. Psychiatric GWAS Consortium Steering Committee. A Framework for Interpreting Genome-Wide Association Studies of Psychiatric Disorders // Mol. Psychiatry. 2009. V. 14. No. 1. P. 10.

18. Ramensky V., Bork P., Sunyaev S. Human non-synonymous SNPs: server and survey // Nucl. Acids Res. 2002. V. 30. Р. 3894–3900.

19. Rosenbloom K.R., Sloan C.A., Malladi V.S. et al. ENCODE Data in the UCSC Genome Browser: year 5 update // Nucl. Acids Res. 2013. Р. D56–D63.

20. Sanchez-Ruiz J.M. Protein kinetic stability // Biophys. Chem. 2010. V. 148. Р. 1–15.

21. Sherry S.T., Ward M.H., Kholodov M. et al. dbSNP: the NCBI database of genetic variation // Nucl. Acids Res. 2001. No. 29. Р. 308–311.

22. Torkamani A., Topol E.J., Schork N.J. Pathway analysis of seven common diseases assessed by genome-wide association // Genomics. 2008. No. 92. P. 265–272.

23. Weston A.D., L H. Systems biology, proteomics, and the future of health care: toward predictive, preventative, and personalized medicine // J. Proteome Res. 2004. V. 3. No. 2. Р. 179–196.

24. Yue P., Melamud E., Moult J. SNPs3D: Candidate gene and SNP selection for association studies // BMC Bioinformatics. 2006. No. 7. P. 166.