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Novel Architecture for RNA Secondary Structure Prediction

  • Mario A. García-Martínez
  • Rubén Posada-Gómez
  • Giner Alor-Hernández
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

RNA secondary structure prediction, well-known like “RNA-problem”, is an operation of high demand of computational resources. At present, several techniques of parallel computing are used in order to obtain efficient results to solve this problem. In this work we present the FPGA implementation of a novel and modular architecture for solution of RNA-problem. The circuit computes the minimum energy that corresponds to optimal secondary structure searched for. A parallel and pipeline design is obtained giving an O(n 2 ) time complexity solution, in counterpart with the classic O(n 3) algorithm for software implementations. We have used Xilinx FPGAs for implementations, and the packages ISE8.1i and ModelSim 6.1e respectively to make VHDL description and circuit verification.

Keywords

RNA-problem secondary structure FPGA hardware implementation 

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References

  1. 1.
    Nussinov, R., Jacobson, A.B.: Fast algorithm for predicting the secondary structure of single-stranded RNA. Proc. Natl. Acad. Sci. USA 77(11), 6309–6313 (1980)CrossRefGoogle Scholar
  2. 2.
    Zucker, M., Stiegler, P.: Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Research 9, 133–148 (1981)CrossRefGoogle Scholar
  3. 3.
    Sankoff, D., Kruskal, J.: Time warps, string edits, and macromolecules: The theory and practice of sequence comparison. Addison Wesley, Reading (1983)zbMATHGoogle Scholar
  4. 4.
    Vidal, M.T.: Estrategias de particionamiento paralelo para el problema de RNA. Masther´s thesis, CINVESTAV-IPN, México D.F. (2002)Google Scholar
  5. 5.
    Cruz, G.J.: Particionamiento paralelo eficiente del algoritmo con complejidad O(n4) para el problema de RNA. Masther´s thesis, CINVESTAV-IPN, México D.F. (2005)Google Scholar
  6. 6.
    Tang, G., Xu, L., Feng, S., Sun, N.: An experimental study of optimizing bioinformatics applications. In: Proceedings of the 20th IEEE International Paralell and Distributed Processing Symposium, Rhodes Island, Greece, April 2006, p. 284 (2006)Google Scholar
  7. 7.
    Jacob, A., Buhler, J., Chamberlain, R.D.: Accelerating Nussinov RNA secondary structure prediction with systolic arrays on FPGAs. In: Proceedings of the 19th IEEE International Conference on Applications-specific Systems, Architectures and Processors, Leuven, Belgium (2008)Google Scholar
  8. 8.
    Díaz-Pérez, A., García-Martínez, M.A.: FPGA accelerator for RNA secondary structure prediction. In: Proceedings of the 12th IEEE Euromicro Conference on Digital System Design, Patras, Greece (2009) (Accepted for its publication)Google Scholar
  9. 9.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Mario A. García-Martínez
    • 1
  • Rubén Posada-Gómez
    • 1
  • Giner Alor-Hernández
    • 1
  1. 1.Instituto Tecnológico de Orizaba, DEPIOrizaba Ver.México

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