Digital filtering approach for prediction of hotspot locations using nucleotide sequences of protein

Yadav, Akshay R.; Shakya, Devendra Kumar

doi:10.1049/cp.2016.1468

Cited by 4 publications

(4 citation statements)

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“…The filter can be realized in direct form-I or direct form-II structures. 29 The direct form-I structure needs 4-delay elements (flip-flops), whereas the reduced direct form-II structure needs only 2-delay elements. Thus, direct form-II structure is used for implementation as shown in Figure 2 due to the requirement of less number of delay elements compared with direct form-I structure.…”

Section: Iir Anf For Identification Of Protein-coding Regionmentioning

confidence: 99%

“…Hence, FIR filters are required with long orders to achieve the same selectivity. Low‐order filters require fewer computational blocks (like delay elements, multipliers, and adders) 29 . Therefore, second‐order IIR filters are considered in this paper for hardware the implementation of ANF.…”

Section: Backgroundsmentioning

confidence: 99%

“…The VLSI implementation of the IIR ANF is carried out by following the relation shown in equation 8. The filter can be realized in direct form‐I or direct form‐II structures 29 . The direct form‐I structure needs 4‐delay elements (flip‐flops), whereas the reduced direct form‐II structure needs only 2‐delay elements.…”

Section: Proposed Hardware Architecture Of Iir Anfmentioning

confidence: 99%

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Hardware implementation of infinite impulse response anti‐notch filter for exon region identification in eukaryotic genes

Pathak

Nanda

Joshi

et al. 2020

Circuit Theory & Apps

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The discrimination of exons from introns in the DNA sequence of a eukaryotic gene is important to understand the functionality of protein formation inside a living organism. Several signal processing techniques involving transforms and filtering have been used to identify the exon regions by exploring the periodicity-3 property. Fast processing of massive DNA sequences is desirable to detect the disease-causing mechanism, which is helpful to prepare individual-centric drugs. In this manuscript, a hardware implementation is carried out for the direct form-II structure of the infinite impulse response anti-notch filter to achieve the fast processing of the DNA sequence. Implementation result on Zynq-series (Zybo board) Field Programmable Gate Array (FPGA) reveals that the proposed implementation is capable to identify the exon regions of five benchmark eukaryotic genes. The FPGA implementation has achieved a maximum clock frequency of 34.629 MHz, which is further improved to 54.41 MHz using the retiming concept. Compared with MATLAB 2014a simulation, the proposed FPGA implementation has achieved similar accuracy with 39 to 43 times faster computing time for the five benchmark data sets. Further, an Application Specific Integrated Circuit (ASIC) implementation is carried out in the CADENCE Register Transfer Level (RTL) compiler tool with GPDK 90-nm technology, due to which the hardware antinotch filter is 120 to 133 times faster compared with its MATLAB counterpart while maintaining the comparable accuracy.

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Section: Iir Anf For Identification Of Protein-coding Regionmentioning

confidence: 99%

Section: Backgroundsmentioning

confidence: 99%

Section: Proposed Hardware Architecture Of Iir Anfmentioning

confidence: 99%

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Hardware implementation of infinite impulse response anti‐notch filter for exon region identification in eukaryotic genes

Pathak

Nanda

Joshi

et al. 2020

Circuit Theory & Apps

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“…Over the years, various signal processing techniques 7 are used by many researchers because only the knowledge of amino acid sequence of protein is required to detect the hot-spots locations in proteins of any particular functional group as compared to unnecessary computations of mutations in wet lab experiments of the ASM method. Various DSP techniques are as follows: short-time discrete Fourier transform (STDFT), 8 digital filtering, [9][10][11][12][13][14][15] continuous wavelet transform (CWT), [16][17][18][19][20] and S-transform. 21,22 In this paper, digital filtering technique and its FPGA implementation is explored for prediction of hot-spots locations in proteins.…”

mentioning

confidence: 99%

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

Pathak

Nanda

Joshi

et al. 2021

Circuit Theory & Apps

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SummaryLocalization of hot spots in a protein sequence is an important problem for understanding complex 3D structure of amino acid sequence (due to which biological functionality of protein is performed by their mutual interactions). Several digital signal processing (DSP) techniques like digital filtering, wavelet, and Fourier transforms have been used for finding the hot‐spot locations. Fast processing of these longer protein sequences is desirable. Field Programmable Gate Array (FPGA) implementation of Infinite Impulse Response (IIR) band pass notch (BPN) digital filter (tuned automatically by characteristics frequency of protein family) is carried out in this paper for further speed‐up of this protein analysis process. Performance of proposed filter system (implemented on Zynq series Zybo board FPGA) is further improved using retiming, which has significantly increased the maximum clock frequency from 34.304 to 54.812 MHz. Simulation of both MATLAB and FPGA hardware implementation for BPN IIR filter is executed on 10 protein functional groups. The simulation results predict the same hot‐spots locations as mentioned in ASEdb data base, but the Hardware BPN IIR filter (proposed in this paper) is 190 to 278 times faster as compared to its MATLAB counterpart. Some additional new hot‐spot locations (not mentioned in ASEdb data base) have been determined by our proposed hardware filter, which can be the probable hot‐spots for newly identified proteins.

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Signal Processing Approaches for Encoded Protein Sequences in Gynecological Cancer Hotspot Prediction: A Review

Das

Nanda²,

Nayak³

et al. 2022

Meta Heuristic Techniques in Software Engineering and Its Applications

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Digital filtering approach for prediction of hotspot locations using nucleotide sequences of protein

Cited by 4 publications

References 0 publications

Hardware implementation of infinite impulse response anti‐notch filter for exon region identification in eukaryotic genes

Hardware implementation of infinite impulse response anti‐notch filter for exon region identification in eukaryotic genes

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

Signal Processing Approaches for Encoded Protein Sequences in Gynecological Cancer Hotspot Prediction: A Review

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