Система хранения профилей физических свойств ДНК на примере промоторов Escherichia coli

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Список литературы:

  1. P. Conilione, D. Wang. A comparative study on feature selection for E. coli promoter recognition // Int. J. Inf. Technol. — 2005. — V. 11. — P. 54–66.
  2. P. Dobson, Y. Patel, D. B. Kell. ‘Metabolite-likeness’ as a criterion in the design and selection of pharmaceutical drug libraries // Drug Discovery Today. — 2009. — V. 14, no. 1–2. — P. 31–40. — DOI: 10.1016/j.drudis.2008.10.011.
  3. S. Gama-Castro, H. Salgado, M. Peralta-Gil, et al. RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units) // Nucleic Acids Res. — 2011. — V. 39, no. Database issue. — P. D98–105. — DOI: 10.1093/nar/gkq1110.
  4. J. Hellerstein, J. Naughton, A. Pfeffer. Generalized search trees for database systems / Readings in database systems. — 1998. — P. 101.
  5. R. Hershberg, G. Bejerano, A. Santos-Zavaleta, H. Margalit. PromEC: An updated database of Escherichia coli mRNA promoters with experimentally identified transcriptional start sites // Nucleic Acids Res. — 2001. — V. 29, no. 1. — P. 277. — DOI: 10.1093/nar/29.1.277.
  6. S. G. Kamzolova, V. S. Sivozhelezov, A. A. Sorokin, et al. RNA polymerase–promoter recognition. Specific features of electrostatic potential of “early” T4 phage DNA promoters // J Biomol Struct Dyn. — 2000. — V. 18, no. 3. — P. 325–334. — DOI: 10.1080/07391102.2000.10506669.
  7. S. G. Kamzolova, A. A. Sorokin, T. D. Dzhelyadin, et al. Electrostatic potentials of E.coli genome DNA // J Biomol Struct Dyn. — 2005. — V. 23, no. 3. — P. 341–345.
  8. Y. Law, H. Wang, C. Zaniolo. Query languages and data models for database sequences and data streams / Proceedings of the Thirtieth international conference on Very large data bases. — 2004. — V. 30. — P. 492–503.
  9. J. Lin, E. Keogh, L. Wei, S. Lonardi. Experiencing SAX: a novel symbolic representation of time series // Data Mining and Knowledge Discovery. — 2007. — V. 15, no. 2. — P. 107–144. — DOI: 10.1007/s10618-007-0064-z. — MathSciNet: MR2409783.
  10. V. Nagaraj, R. O’Flanagan, A. Sengupta. Better estimation of protein-DNA interaction parameters improve prediction of functional sites // BMC biotechnology. — 2008. — V. 8, no. 1. — P. 94. — DOI: 10.1186/1472-6750-8-94.
  11. R. Obe, L. Hsu, P. Ramsey. PostGIS in Action. — Manning Publications, 2011. — Pap/psc edition.
  12. A. A. Osypov, G. G. Krutinin, S. G. Kamzolova. DEPPDB — DNA electrostatic potential properties database: electrostatic properties of genome DNA // Journal of Bioinformatics and Computational Biology. — 2010. — V. 08, no. 03. — P. 413. — DOI: 10.1142/S0219720010004811.
  13. R. V. Polozov, T. R. Dzhelyadin, A. A. Sorokin, et al. Electrostatic potentials of DNA. Comparative analysis of promoter and nonpromoter nucleotide sequences // J Biomol Struct Dyn. — 1999. — V. 16, no. 6. — P. 1135–1143. — DOI: 10.1080/07391102.1999.10508322.
  14. R. Sadri, C. Zaniolo, A. Zarkesh, J. Adibi. Expressing and optimizing sequence queries in database systems // ACM Transactions on Database Systems (TODS). — 2004. — V. 29, no. 2. — P. 282–318. — DOI: 10.1145/1005566.1005568.
  15. G. Sandve, O. Abul, Drabl. øs F. Compo: composite motif discovery using discrete models // BMC Bioinformatics. — 2008. — V. 9, no. 1. — P. 527. — DOI: 10.1186/1471-2105-9-527.
  16. K. S. Shavkunov, I. S. Masulis, M. N. Tutukina, et al. Gains and unexpected lessons from genome-scale promoter mapping // Nucleic Acids Res. — 2009. — V. 37, no. 15. — P. 4919–4931. — DOI: 10.1093/nar/gkp490.
  17. J. Shieh, E. Keogh. iSAX: indexing and mining terabyte sized time series / KDD ’08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. — 2008. — MathSciNet: MR2506213.
  18. A. A. Sorokin, A. A. Osypov, T. R. Dzhelyadin, et al. Electrostatic properties of promoter recognized by E. coli RNA polymerase Esigma70 // Journal of Bioinformatics and Computational Biology. — 2006. — V. 4, no. 2. — P. 455–467. — DOI: 10.1142/S0219720006002077.
  19. A. Sorokin, G. Selkov, I. Goryanin. A user-defined data type for the storage of time series data allowing efficient similarity screening // European Journal of Pharmaceutical Sciences. — 2012. — V. 46, no. 4. — P. 272–274. — DOI: 10.1016/j.ejps.2011.12.008.

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Международная Междисциплинарная Конференция МАТЕМАТИКА. КОМПЬЮТЕР. ОБРАЗОВАНИЕ.

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