ArticleGenomics2017
A new method to analyze protein sequence similarity using Dynamic Time Warping.
Article in Genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- 20D-Dynamic Representation of Protein Sequences Combined with K-means Clustering.Combinatorial chemistry & high throughput screening · 2026Article
- Unsupervised clustering of longitudinal clinical measurements in electronic health records.PLOS digital health · 2024Article
- FFP: joint Fast Fourier transform and fractal dimension in amino acid property-aware phylogenetic analysis.BMC bioinformatics · 2022Article
- Alignment-free similarity analysis for protein sequences based on fuzzy integral.Scientific reports · 2019Article
- A Statistical Similarity/Dissimilarity Analysis of Protein Sequences Based on a Novel Group Representative Vector.BioMed research international · 2019Article
- A novel model for protein sequence similarity analysis based on spectral radius.Journal of theoretical biology · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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