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A cepstral distortion measure for protein comparison and identification
Bioinformatics Applications Research Center; School of Information Technology, James Cook University, Townsville, QLD, Australia.ORCID iD: 0000-0002-4255-5130
Bioinformatics Applications Research Center.
2005 (English)In: Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on, 2005, Vol. 9, 5609-5614 p.Conference paper, Published paper (Refereed)
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Abstract [en]

Protein sequence comparison is the most powerful tool for the identification 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 concept of linear-predictive-coding based cepstral distortion measure, for comparison and identification of protein sequences. Experimental results on a real data set of functionally related and functionally non-related protein sequences have shown the effectiveness of the proposed approach on both accuracy and computational efficiency.

Place, publisher, year, edition, pages
2005. Vol. 9, 5609-5614 p.
Keyword [en]
Cepstral coefficients, linear predictive coding, similarity measure protein companson, protein identification
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:liu:diva-125016DOI: 10.1109/ICMLC.2005.1527936ISBN: 0-7803-9091-1 (print)OAI: oai:DiVA.org:liu-125016DiVA: diva2:902781
Conference
2005 International Conference on Machine Learning and Cybernetics, 2005. 18-21 Aug. Guangzhou, China
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2017-06-21Bibliographically approved

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Pham, Tuan D
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CiteExportLink to record
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Citation style
  • apa
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  • Other style
More styles
Language
  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
  • rtf