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Conference of Information Technologies in Biomedicine

ITiB 2016: Information Technologies in Medicine pp 147–159Cite as

Human Fibroblast Growth Factor 2 Hot Spot Analysis by Means of Time-Frequency Transforms

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 472))

Abstract

Energy in protein complexes is not uniformly distributed. Some of amino acid residues—called hot spots—contribute most to the total energy of interaction. Hot spots can be determined experimentally or by computational methods. Here we present the application of time-frequency tools such as short-time Fourier transform and S transform to analyze human fibroblast growth factor 2 protein. The time-frequency tools take advantage the Resonant Recognition Model (RRM), which is based on the correlation between spectra of numerical representations of amino acids and their function. Thus, RRM allows for applying digital signal processing tools to amino acid analysis. Methods using time-frequency transforms do not require knowledge of protein structure, thus they help to predict hot spot residues with good accuracy and lower computational requirements comparing to other algorithms.

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Acknowledgments

This work was supported by the Ministry of Science and Higher Education funding for statutory activities of young researchers (decision no. 8686/E-367/M/2015 of 12 March 2015).

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Authors and Affiliations

  1. Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland

    Anna Tamulewicz

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    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. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

  2. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Wojciech Wieclawek

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© 2016 Springer International Publishing Switzerland

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Tamulewicz, A., Tkacz, E. (2016). Human Fibroblast Growth Factor 2 Hot Spot Analysis by Means of Time-Frequency Transforms. In: Piętka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technologies in Medicine. ITiB 2016. Advances in Intelligent Systems and Computing, vol 472. Springer, Cham. https://doi.org/10.1007/978-3-319-39904-1_13

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  • DOI: https://doi.org/10.1007/978-3-319-39904-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39903-4

  • Online ISBN: 978-3-319-39904-1

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