VRM Normalized Subband Adaptive Filter for genomic signal processing application

With the enormous amount of biological sequences that are available in the public domain, signal processing theory and techniques are playing an important role in genomic data processing. The Variable Regularization Matrix Normalized Subband Adaptive Filter(VRM NSAF) proposed recently has both fast convergence rate and low misadjustment. The VRM NSAF is applied for gene prediction in this paper. At first, we review the Z curve representation which maps the alphabetic DNA sequence into the digital series. Secondly, in terms of the period-3 behavior of protein coding segments, the VRM NSAF approach is utilized for genomic signal processing. Thirdly, the presented approach is applied to identify the protein coding regions in a real nucleotide sequence. It is shown that the developed method is useful for gene identification by experiments.

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