VLSI implementation of anti‐notch lattice structure for identification of exon regions in Eukaryotic genes

Abstract

In a Eukaryotic gene, identification of exon regions is crucial for protein formation. The periodic-3 property of exon regions has been used for its identification. An anti-notch infinite impulse response (IIR) filter is mostly employed to recognise this periodic-3 property. The lattice structure realisation of anti-notch IIR filter requires less hardware over direct from-II structures. In this study, a hardware implementation of IIR anti-notch filter lattice structure is carried out on Zynq-series (Zybo board) field programmable gate array (FPGA). The performance of hardware design has been improved using techniques like retiming, pipelining and unfolding and finally assessed on various Eukaryotic genes. The hardware implementation reduces the time frame to analyse the DNA sequence of Eukaryotic genes for protein formation, which plays a significant role in detecting individual diseases from genetic reports. Here, the performance evaluation is carried out in MATLAB simulation environment and the results are found similar. Application-specific integrated circuit (ASIC) implementation of the anti-notch filter lattice structure is also carried out on CADENCE-RTL compiler. It is observed that the FPGA implementation is 31 to 34 times faster and ASIC implementation is 58 to 64 times faster compared to the results generated by MATLAB platform with similar prediction accuracy.

Identification of characteristics frequency and hot-spots in protein sequence of COVID-19 disease

“…It is found that quality ( ) and anti-notch frequency ( ) can be easily changed by adjusting the ANF lattice filter coefficients and , without altering each other. Hence, multiplier coefficients and can be independently adjusted for controlling the quality and anti-notch frequency of the ANF filter [21] .…”

“…BPN (ANF) IIR filter can be realized either by direct form or lattice structures whose Hardware architectures are explored in our previous work [21] , [29] , [30] , which were used for identification of exon regions in eukaryotic genes (different application). In this paper, lattice structures are followed due to the requirement of less logic hardware as compared to direct form structures, which are used for separate applications of hot-spots identification in SARS CoV2 proteins.…”

“…This area is further reduced in work [20] by using only a single ANF filter for the same application with more number of protein data-sets. Different signal processing techniques including retiming, pipelining and unfolding are also explored for a speed improvement in lattice hardware structures of ANF IIR filter [21] , [22] , which was used for exon region identification in eukaryotic genes. In this manuscript, an area-optimized VLSI hardware architecture of the BPN lattice IIR filter-based hot-spots detection system is proposed, which is further optimized for performance improvement using retiming and pipelining (unlike unfolding in paper [21] due to higher area requirement).…”

Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

“…In general, digital hardware outperforms and is more reliable than analog equipment, which can break down over time and have unpredictable results in the field [7]. Digital signal processing, on the other hand, provides a guarantee of accuracy and near-perfect repeatability [8]. There is a lot of interest in merging the various networks that communicate these signals [9].…”

FPGA implementation of high‐speed tunable IIR band pass notch filter for identification of hot‐spots in protein

“…High-speed FPGA (Sparten-6 and Virtex-7 series) implementation of various adaptive filter structures is carried out by Goel and Chandra 24 using retiming for speech enhancement through noise cancelation. Optimized VLSI implementation of direct form-II (DF-II) 25 and lattice structures 26 are explored for exon-region identification in eukaryotic genes. This paper is the extension of our previous conference paper 27 in which VLSI hardware implementation of tunable BPN digital filter for hot-spots localization in proteins is explored and which was not optimized for area and speed.…”