A new method to cluster DNA sequences using Fourier power spectrum

Tung Hoang, Changchuan Yin, Hui Zheng, Chenglong Yu, Rong He, Stephen Yau

    Research output: Contribution to journalArticlepeer-review

    47 Citations (Scopus)


    A novel clustering method is proposed to classify genes and genomes. For a given DNA sequence, a binary indicator sequence of each nucleotide is constructed, and Discrete Fourier Transform is applied on these four sequences to attain respective power spectra. Mathematical moments are built from these spectra, and multidimensional vectors of real numbers are constructed from these moments. Cluster analysis is then performed in order to determine the evolutionary relationship between DNA sequences. The novelty of this method is that sequences with different lengths can be compared easily via the use of power spectra and moments. Experimental results on various datasets show that the proposed method provides an efficient tool to classify genes and genomes. It not only gives comparable results but also is remarkably faster than other multiple sequence alignment and alignment-free methods.

    Original languageEnglish
    Pages (from-to)135-145
    Number of pages11
    JournalJournal of Theoretical Biology
    Publication statusPublished - 7 May 2015


    • Genes
    • Moments
    • Phylogenetic trees


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