Title: Low power DNA protein sequence alignment using FSM state transition controller

Authors: Sancarapu Nagaraju; Penubolu Sudhakara Reddy

Addresses: Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University, JNTUA, Ananthapuramu, Andhra Pradesh, India ' Department of Electronics and Communication Engineering, Srikalahasteeswara Institute of Technology, Srikalahasthi, Andhra Pradesh, India

Abstract: In this paper we proposed an efficient computation technique for DNA patterns on reconfigurable hardware (FPGAs) platform. The paper also presents the results of a comparative study between existing dynamic and heuristic programming methods of the widely-used Smith-Waterman pair-wise sequence alignment algorithm with FSM-based core implementation. Traditional software implication-based sequence alignment methods can not meet the actual data rate requirements. Hardware-based approach will give high scalability and one can process parallel tasks with a large number of new databases. This paper explains finite state machine (FSM)-based core processing element to classify the protein sequence. In addition, we analyse the performance of bit-based sequence alignment algorithms and present the inner stage pipelined field programmable gate array (FPGA) architecture for sequence alignment implementations. Here, synchronised controllers are used to carry out parallel sequence alignment. The complete architecture is designed to carry out parallel processing in hardware, with FSM-based bit wised pattern comparison with scalability as well as with a minimum number of computations. Finally, the proposed design proved to be high performance and its efficiency in terms of resource utilisation is proved on FPGA implementation.

Keywords: DNA; protein sequence; finite state machine; FSM; Smith-Waterman algorithm; field programmable gate array; FPGA; low power.

DOI: 10.1504/IJBET.2020.110998

International Journal of Biomedical Engineering and Technology, 2020 Vol.34 No.2, pp.107 - 118

Received: 16 Jun 2017
Accepted: 20 Nov 2017

Published online: 05 Nov 2020 *

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