Discrete-time signal processing
Discrete-time signal processing
A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA
Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology
Large scale features in DNA genomic signals
Signal Processing - Special issue: Genomic signal processing
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
DSP in genomics: processing and frequency-domain analysis of character strings
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Detection of tandem repeats in DNA sequences based on parametric spectral estimation
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
SoftCOM'09 Proceedings of the 17th international conference on Software, Telecommunications and Computer Networks
The minimum entropy mapping spectrum of a DNA sequence
IEEE Transactions on Information Theory - Special issue on information theory in molecular biology and neuroscience
International Journal of Data Mining and Bioinformatics
Identification of protein coding regions using antinotch filters
Digital Signal Processing
Improved exon prediction with transforms by de-noising period-3 measure
Digital Signal Processing
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It has been observed that the protein-coding regions of DNA sequences exhibit period-three behaviour, which can be exploited to predict the location of coding regions within genes. Previously, discrete Fourier transform (DFT) and digital filter-based methods have been used for the identification of coding regions. However, these methods do not significantly suppress the noncoding regions in the DNA spectrum at 2π/3. Consequently, a noncoding region may inadvertently be identified as a coding region. This paper introduces a new technique (a single digital filter operation followed by a quadratic window operation) that suppresses nearly all of the noncoding regions. The proposed method therefore improves the likelihood of correctly identifying coding regions in such genes.