A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing. (October 2017)

• Record Type: Journal Article
• Authors: Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin
• Is Part Of: Computer methods and programs in biomedicine. Volume 149(2017)
• Page Start: 11
• Page End: 17
• Publication Date: 2017-10
• Subjects: Window filter -- 1/f noise -- Fuzzy adaptive filter -- 3-base periodicity -- Digital signal processing; bp Base pair -- SNR Signal to noise ratio -- DNA Deoxyribonucleic acid -- DSP Digital signal processing; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.06.021
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: The proposed FAWMF algorithm is based on genetic code context of nucleotides. It is highly adaptive in nature contrary to fixed length window filters. It computes and filters nucleotides employing fuzzy membership and median filtering. It significantly suppresses 1/ f background noise and spectral leakage. It outperforms as compared with existing conventional window filters of fixed length. Abstract: Background and Objective: Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. Methods: This paper introduces a biological inspired fuzzy adaptive window median filter ( FAWMF ) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Results: Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. Conclusion: This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary to fixed window length conventional filters.