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<p>Through the implementation of Digital Signal Processing techniques on genetic and protein sequence data, we can proficiently seek out information within biological systems. Accurate identification of protein-coding regions is essential for understanding gene function, protein synthesis, and genetic variations. These insights drive progress in fields such as biotechnology. This paper introduces a comparative analysis framework that evaluates the effectiveness of discrete wavelet transform (DWT) and discrete cosine transform (DCT) in enhancing the precision and accuracy of identifying and predicting protein-coding regions within DNA sequences. Leveraging both the DWT and the DCT, this work conducts comparative analysis by employing a digital band-pass filter in combination with spectral estimation techniques to predict exons. By applying the Haar and Daubechies wavelet transforms alongside DCT, this technique surpasses traditional approaches, extracting intricate details previously obscured in raw DNA sequences. Several metrics are used to evaluate the accuracy of the proposed technique, including Root Mean Square Error (RMSE) and the Correlation Coefficient (R). The results show a significant improvement in identification accuracy, confirming the effectiveness of the proposed technique, which achieves the lowest RMSE and the highest R compared to other traditional techniques.</p>

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Digital signal processing techniques for accurate exon prediction in DNA sequences

  • 期刊论文

  • 发表日期：

    2025年9月23日

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  • Ayman A. Alharbi,
  • Emad S. Hassan,
  • Ahmed M. Dessouky,
  • Hesham Fathi,
  • Gerges M. Salama,
  • Fathi E. Abd El‑Samie

摘要

Through the implementation of Digital Signal Processing techniques on genetic and protein sequence data, we can proficiently seek out information within biological systems. Accurate identification of protein-coding regions is essential for understanding gene function, protein synthesis, and genetic variations. These insights drive progress in fields such as biotechnology. This paper introduces a comparative analysis framework that evaluates the effectiveness of discrete wavelet transform (DWT) and discrete cosine transform (DCT) in enhancing the precision and accuracy of identifying and predicting protein-coding regions within DNA sequences. Leveraging both the DWT and the DCT, this work conducts comparative analysis by employing a digital band-pass filter in combination with spectral estimation techniques to predict exons. By applying the Haar and Daubechies wavelet transforms alongside DCT, this technique surpasses traditional approaches, extracting intricate details previously obscured in raw DNA sequences. Several metrics are used to evaluate the accuracy of the proposed technique, including Root Mean Square Error (RMSE) and the Correlation Coefficient (R). The results show a significant improvement in identification accuracy, confirming the effectiveness of the proposed technique, which achieves the lowest RMSE and the highest R compared to other traditional techniques.