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Hot Spot Analysis by Means of Continuous Wavelet Transform and Time-Frequency Filtering

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Innovations in Biomedical Engineering (IBE 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 925))

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Abstract

In the paper, the analysis of hot spots in proteins with the aid of digital signal processing methods was conducted. The algorithm employs time-frequency filtering and continuous wavelet transform (CWT); its aim is to find amino acid regions where the characteristic frequency is dominant by detecting peaks in energy plot. The research showed that the choice of wavelet function has big impact on the results. The best results were achieved by using CWT with the Morlet wavelet and the sixth order derivative of a Gaussian wavelet.

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Authors and Affiliations

  1. Department of Biosensors and Biomedical Signal Processing, Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800, Zabrze, Poland

    Anna Tamulewicz & Ewaryst Tkacz

Authors
  1. Anna Tamulewicz
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  2. Ewaryst Tkacz
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Corresponding author

Correspondence to Anna Tamulewicz .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Department of Biosensors and Biomedical Signals Processing, Silesian University of Technology, Zabrze, Poland

    Ewaryst Tkacz

  2. Faculty of Biomedical Engineering, Department of Biosensors and Biomedical Signals Processing, Silesian University of Technology, Zabrze, Poland

    Marek Gzik

  3. Faculty of Biomedical Engineering, Department of Biosensors and Biomedical Signals Processing, Silesian University of Technology, Zabrze, Poland

    Zbigniew Paszenda

  4. Faculty of Biomedical Engineering, Department of Biosensors and Biomedical Signals Processing, Silesian University of Technology, Zabrze, Poland

    Ewa Piętka

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Tamulewicz, A., Tkacz, E. (2019). Hot Spot Analysis by Means of Continuous Wavelet Transform and Time-Frequency Filtering. In: Tkacz, E., Gzik, M., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. IBE 2018. Advances in Intelligent Systems and Computing, vol 925. Springer, Cham. https://doi.org/10.1007/978-3-030-15472-1_16

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