Abstract
An important issue in computational biology is the reverse engineering problem for genetic networks. In this ongoing work we consider reverse engineering in the context of univariate finite fields models. A solution to the reverse engineering problem using multipoint interpolation relies on intensive arithmetic computations over finite fields, where multiplication is the dominant operation. In this work, we develop an efficient multiplier for fields GF(2m) generated by irreducible trinomials of the form α m + α n + 1. We propose a design described by a parallel/serial architecture that computes a multiplication in m clock cycles. This approach exploits symmetries in Mastrovito matrices in order to improve time complexities of an FPGA (Field Programmable Gate Array) implementation. According to preliminary performance results, our approach performs efficiently for large fields and has potential for an efficient solution of the reverse engineering problem for large genetic networks, as well as other finite fields applications such as cryptography and Reed-Solomon decoders.
Keywords
- Field Programmable Gate Array
- Gene Regulatory Network
- Reverse Engineering
- Genetic Network
- Polynomial Multiplication
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.
This research is supported by grants NSF-CISE EIA-0080926 and NIH-MBRS (SCORE) S06-GM08102.
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Ferrer, E., Bollman, D., Moreno, O. (2007). Toward a Solution of the Reverse Engineering Problem Using FPGAs . In: Lehner, W., Meyer, N., Streit, A., Stewart, C. (eds) Euro-Par 2006 Workshops: Parallel Processing. Euro-Par 2006. Lecture Notes in Computer Science, vol 4375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72337-0_30
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DOI: https://doi.org/10.1007/978-3-540-72337-0_30
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