Multirate systems and filter banks
Multirate systems and filter banks
Preliminary Wavelet Analysis of Genomic Sequences
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Autoregressive modeling and feature analysis of DNA sequences
EURASIP Journal on Applied Signal Processing
A digital signal processing method for gene prediction with improved noise suppression
EURASIP Journal on Applied Signal Processing
Identification of Protein Coding Regions Using the Modified Gabor-Wavelet Transform
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An efficient sliding window strategy for accurate location of eukaryotic protein coding regions
Computers in Biology and Medicine
Fourier analysis of symbolic data: A brief review
Digital Signal Processing
Improved exon prediction with transforms by de-noising period-3 measure
Digital Signal Processing
Digital Signal Processing
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A major area of research in genomic sequence analysis is the identification of protein coding regions using the period-3 property. Previously antinotch filter has been used for this purpose. In this paper, three antinotch filters, namely conjugate suppression antinotch filter, antinotch filter followed by moving average filter and harmonic suppression antinotch filter are proposed to improve the identification accuracy. Conjugate suppression antinotch filter suppresses the conjugate frequency component, antinotch filter followed by moving average filter reduces the background noise and harmonic suppression antinotch filter suppresses the harmonic frequency component. Several existing DNA to numerical mapping techniques are compared for GENSCAN test set and based on the result one mapping technique is recommended so that detailed analysis can be performed using various datasets. The computational complexity of the antinotch filters is evaluated in comparison with the ST-DFT method and it is found that the computational load is reduced to a greater extent in antinotch filter. The identification accuracy of the proposed antinotch filter methods is compared with the existing antinotch filter method at the nucleotide level for benchmark datasets. The results show that proposed methods outperform the existing method, giving improved identification of the protein coding regions.