Abstract

We propose a protein structure alignment method that exploits advances in time-frequency signal processing to increase the similarity measure accuracy between distantly-related proteins. The new method uses a waveform non-linear mapping technique and waveform transformations in time-frequency (TF) space. Specifically, protein amino acids are mapped to three-dimensional (3-D) linear frequency-modulated (LFM) Gaussian chirps that are translated and rotated to account for all possible protein structure matches. The protein structure directionality is changed by considering all possible chirp rate parameters. Furthermore, both local and global alignments can be identified between multiple protein structures due to the linear separability property of the Gaussian-type functions. Our results are successfully demonstrated using proteins structures from a known database without performing any pre-processing. The paper also introduces a web-based learning module Java-DSP that can be used to implement bioinformatics functions using signal processing methods.

Original languageEnglish (US)
Title of host publication2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010
Pages94-97
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 - Paphos, Cyprus
Duration: Nov 3 2010Nov 5 2010

Publication series

Name2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010

Other

Other2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010
CountryCyprus
CityPaphos
Period11/3/1011/5/10

ASJC Scopus subject areas

  • Hardware and Architecture
  • Biomedical Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Ravichandran, L., Papandreou-Suppappola, A., Spanias, A., & Lacroix, Z. (2010). Multiple protein structure alignment using time-frequency processing techniques. In 2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 (pp. 94-97). [5709579] (2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010). https://doi.org/10.1109/BIOCAS.2010.5709579