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A new method to analyze protein sequence similarity using Dynamic Time Warping.


ABSTRACT: Sequences similarity analysis is one of the major topics in bioinformatics. It helps researchers to reveal evolution relationships of different species. In this paper, we outline a new method to analyze the similarity of proteins by Discrete Fourier Transform (DFT) and Dynamic Time Warping (DTW). The original symbol sequences are converted to numerical sequences according to their physico-chemical properties. We obtain the power spectra of sequences from DFT and extend the spectra to the same length to calculate the distance between different sequences by DTW. Our method is tested in different datasets and the results are compared with that of other software algorithms. In the comparison we find our scheme could amend some wrong classifications appear in other software. The comparison shows our approach is reasonable and effective.

SUBMITTER: Hou W 

PROVIDER: S-EPMC7125777 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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A new method to analyze protein sequence similarity using Dynamic Time Warping.

Hou Wenbing W   Pan Qiuhui Q   Peng Qianying Q   He Mingfeng M  

Genomics 20161211 2


Sequences similarity analysis is one of the major topics in bioinformatics. It helps researchers to reveal evolution relationships of different species. In this paper, we outline a new method to analyze the similarity of proteins by Discrete Fourier Transform (DFT) and Dynamic Time Warping (DTW). The original symbol sequences are converted to numerical sequences according to their physico-chemical properties. We obtain the power spectra of sequences from DFT and extend the spectra to the same le  ...[more]

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