INSWF DNAsignal analysis tool: Intelligent noise suppression window filter

Ahmad, Muneer and Ahmad, Iftikhar and Bilal, Muhammad and Jolfaei, Alireza and Mehmood, Raja Majid (2021) INSWF DNAsignal analysis tool: Intelligent noise suppression window filter. Software: Practice and Experience, 51 (3). pp. 670-685. ISSN 0038-0644, DOI https://doi.org/10.1002/spe.2880.

Full text not available from this repository.
Official URL: https://doi.org/10.1002/spe.2880

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. TheINSWFfilter 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.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: Adaptive digital filter; Codon usage; Digital filter; DNA sequence analysis; Fixed-length filter; Fuzzy rules; Signal noise
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 21 Feb 2022 04:55
Last Modified: 21 Feb 2022 04:55
URI: http://eprints.um.edu.my/id/eprint/26262

Actions (login required)

View Item View Item