Toward a Solution of the Reverse Engineering Problem Using FPGAs

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 αm +αn +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.