• DocumentCode
    951419
  • Title

    LPC cepstral distortion measure for protein sequence comparison

  • Author

    Pham, Tuan D.

  • Author_Institution
    Sch. of Inf. Technol., James Cook Univ. of North Queensland, Townsville, Qld., Australia
  • Volume
    5
  • Issue
    2
  • fYear
    2006
  • fDate
    6/1/2006 12:00:00 AM
  • Firstpage
    83
  • Lastpage
    88
  • Abstract
    Protein sequence comparison is the most powerful tool for the inference of novel protein structure and function. This type of inference is commonly based on the similar sequence-similar structure-similar function paradigm, and derived by sequence similarity searching on databases of protein sequences. As entire genomes have been being determined at a rapid rate, computational methods for comparing protein sequences will be more essential for probing the complexity of molecular machines. In this paper we introduce a pattern-comparison algorithm, which is based on the mathematical concepts of linear predictive coding (LPC) and LPC cepstral distortion measure, for computing similarities/dissimilarities between protein sequences. Experimental results on a real data set of functionally related and functionally nonrelated protein sequences have shown the effectiveness of the proposed approach on both accuracy and computational efficiency.
  • Keywords
    biology computing; genetics; linear predictive coding; molecular biophysics; molecular configurations; proteins; LPC cepstral distortion measure; genomes; linear predictive coding; pattern-comparison algorithm; protein function; protein sequence comparison; protein structure; Bioinformatics; Cepstral analysis; Computational biology; Computational efficiency; Databases; Distortion measurement; Genomics; Linear predictive coding; Protein sequence; Sequences; Distortion measure; linear predictive coding (LPC); protein sequence comparison; Algorithms; Computer Simulation; Linear Models; Models, Chemical; Models, Molecular; Pattern Recognition, Automated; Proteins; Sequence Alignment; Sequence Analysis, Protein;
  • fLanguage
    English
  • Journal_Title
    NanoBioscience, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1241
  • Type

    jour

  • DOI
    10.1109/TNB.2006.875029
  • Filename
    1637448