Effects of windowing and zero-padding on Complex Resonant Recognition Model for protein sequence analysis

Area of Science:

• Bioinformatics
• Computational Biology
• Signal Processing

Background:

• Fourier Transform (FT) and its derivatives are crucial in signal processing.
• Techniques like zero-padding and windowing enhance FT-based analyses.
• The Resonant Recognition Model (RRM) and Complex Resonant Recognition Model (CRRM) use FT for protein sequence analysis but omit these enhancement techniques.

Purpose of the Study:

• To investigate the influence of zero-padding and windowing on features extracted using the Complex Resonant Recognition Model (CRRM).
• To evaluate the impact of these signal processing techniques on the analysis of influenza A virus Neuraminidase genes.

Main Methods:

• Applied zero-padding to standardize protein sequence lengths.
• Utilized windowing and suppressed windowing to extract Common Frequency Peaks (CFP).
• Analyzed five influenza A virus subtypes (H1N1, H1N2, H2N2, H3N2, H5N1) with varying signal lengths (470 to 16384).

Main Results:

• Zero-padding and windowing significantly affect the CFP extracted from influenza A subtypes.
• The optimal match for CRRM-derived CFP was achieved with a signal length of 4096 and applied windowing.
• Different signal lengths and windowing strategies yield distinct feature sets.

Conclusions:

• Zero-padding and windowing are critical factors in CRRM analysis of protein sequences.
• The findings suggest incorporating these techniques for more accurate and reliable protein sequence analysis.
• Optimized signal processing parameters enhance the utility of CRRM for viral gene analysis.