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INSWF DNA signal analysis tool: Intelligent noise suppression window filter

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INSWF DNA signal analysis tool: Intelligent noise suppression window filter. / Ahmad, Muneer; Ahmad, Iftikhar; Bilal, Muhammad et al.
In: Software - Practice and Experience, Vol. 51, No. 3, 31.03.2021, p. 670-685.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Ahmad, M, Ahmad, I, Bilal, M, Jolfaei, A & Mehmood, RM 2021, 'INSWF DNA signal analysis tool: Intelligent noise suppression window filter', Software - Practice and Experience, vol. 51, no. 3, pp. 670-685. https://doi.org/10.1002/spe.2880

APA

Ahmad, M., Ahmad, I., Bilal, M., Jolfaei, A., & Mehmood, R. M. (2021). INSWF DNA signal analysis tool: Intelligent noise suppression window filter. Software - Practice and Experience, 51(3), 670-685. https://doi.org/10.1002/spe.2880

Vancouver

Ahmad M, Ahmad I, Bilal M, Jolfaei A, Mehmood RM. INSWF DNA signal analysis tool: Intelligent noise suppression window filter. Software - Practice and Experience. 2021 Mar 31;51(3):670-685. doi: 10.1002/spe.2880

Author

Ahmad, Muneer ; Ahmad, Iftikhar ; Bilal, Muhammad et al. / INSWF DNA signal analysis tool : Intelligent noise suppression window filter. In: Software - Practice and Experience. 2021 ; Vol. 51, No. 3. pp. 670-685.

Bibtex

@article{ca15c367099640f28bdc819d69aa778e,
title = "INSWF DNA signal analysis tool: Intelligent noise suppression window filter",
abstract = "DNA signals mainly differ from standard digital signals due to their biological data contents. Owing to unique properties of DNA signals the conventional signal processing techniques, such as digital filters, suffers with spectral leakage and results in insignificant noise suppression in DNA sequence analysis. This article presents an intelligent noise suppression window filter (INSWF) for DNA signal analysis. The filter demises the signal by separating high-level frequency contents and by identifying nucleotides with high fuzzy membership contribution at particular locations. The nucleotide contents of signals are later filtered by application of median filtering employing a combination of s-shaped and z-shaped filters. The fundamental characteristic of codons usage that causes uneven nucleotides segmentation has been tackled by finding the best fit of the curve in biological contents of filter. One of the fuzzy correlations existing between codons and median that nucleotides incorporated to reduce the signal noise to a larger magnitude. The INSWF filter outperformed the existing fixed-length digital filters tested over 250 benchmarked and random datasets of various species. A notable enhancement of 45% to 130% was achieved by significantly suppressing signal noise as compared with conventional digital filters in DNA sequence analysis.",
keywords = "adaptive digital filter, codon usage, digital filter, DNA sequence analysis, fixed-length filter, fuzzy rules, signal noise",
author = "Muneer Ahmad and Iftikhar Ahmad and Muhammad Bilal and Alireza Jolfaei and Mehmood, {Raja Majid}",
year = "2021",
month = mar,
day = "31",
doi = "10.1002/spe.2880",
language = "English",
volume = "51",
pages = "670--685",
journal = "Software - Practice and Experience",
issn = "0038-0644",
publisher = "John Wiley and Sons Ltd",
number = "3",

}

RIS

TY - JOUR

T1 - INSWF DNA signal analysis tool

T2 - Intelligent noise suppression window filter

AU - Ahmad, Muneer

AU - Ahmad, Iftikhar

AU - Bilal, Muhammad

AU - Jolfaei, Alireza

AU - Mehmood, Raja Majid

PY - 2021/3/31

Y1 - 2021/3/31

N2 - DNA signals mainly differ from standard digital signals due to their biological data contents. Owing to unique properties of DNA signals the conventional signal processing techniques, such as digital filters, suffers with spectral leakage and results in insignificant noise suppression in DNA sequence analysis. This article presents an intelligent noise suppression window filter (INSWF) for DNA signal analysis. The filter demises the signal by separating high-level frequency contents and by identifying nucleotides with high fuzzy membership contribution at particular locations. The nucleotide contents of signals are later filtered by application of median filtering employing a combination of s-shaped and z-shaped filters. The fundamental characteristic of codons usage that causes uneven nucleotides segmentation has been tackled by finding the best fit of the curve in biological contents of filter. One of the fuzzy correlations existing between codons and median that nucleotides incorporated to reduce the signal noise to a larger magnitude. The INSWF filter outperformed the existing fixed-length digital filters tested over 250 benchmarked and random datasets of various species. A notable enhancement of 45% to 130% was achieved by significantly suppressing signal noise as compared with conventional digital filters in DNA sequence analysis.

AB - DNA signals mainly differ from standard digital signals due to their biological data contents. Owing to unique properties of DNA signals the conventional signal processing techniques, such as digital filters, suffers with spectral leakage and results in insignificant noise suppression in DNA sequence analysis. This article presents an intelligent noise suppression window filter (INSWF) for DNA signal analysis. The filter demises the signal by separating high-level frequency contents and by identifying nucleotides with high fuzzy membership contribution at particular locations. The nucleotide contents of signals are later filtered by application of median filtering employing a combination of s-shaped and z-shaped filters. The fundamental characteristic of codons usage that causes uneven nucleotides segmentation has been tackled by finding the best fit of the curve in biological contents of filter. One of the fuzzy correlations existing between codons and median that nucleotides incorporated to reduce the signal noise to a larger magnitude. The INSWF filter outperformed the existing fixed-length digital filters tested over 250 benchmarked and random datasets of various species. A notable enhancement of 45% to 130% was achieved by significantly suppressing signal noise as compared with conventional digital filters in DNA sequence analysis.

KW - adaptive digital filter

KW - codon usage

KW - digital filter

KW - DNA sequence analysis

KW - fixed-length filter

KW - fuzzy rules

KW - signal noise

U2 - 10.1002/spe.2880

DO - 10.1002/spe.2880

M3 - Journal article

AN - SCOPUS:85089727849

VL - 51

SP - 670

EP - 685

JO - Software - Practice and Experience

JF - Software - Practice and Experience

SN - 0038-0644

IS - 3

ER -