DocumentCode :
3391007
Title :
Multifractal analysis and feature extraction of DNA sequences
Author :
Kinsner, Witold ; Zhang, Hong
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB, Canada
fYear :
2009
fDate :
15-17 June 2009
Firstpage :
29
Lastpage :
37
Abstract :
This paper presents feature extraction and estimations of multifractal measures for deoxyribonucleic acid (DNA) sequences, and demonstrates the intriguing possibility of identifying biological functionality using information contained within the DNA sequence. We have developed a technique that seeks patterns or correlations in the DNA sequence at a higher level. The technique has three main steps: (i) transforms the DNA sequence symbols into a modified Levy walk, (ii) transforms the Levy walk into a signal spectrum, and (iii) breaks the spectrum into subspectra and treats each of these as an attractor from which the multifractal dimension spectrum is estimated. An optimal minimum window size and volume element size are found for estimation of the multifractal measures. Experimental results show that DNA is a multifractal, and that the multifractality changes depending upon the location (coding or noncoding region) in the sequence.
Keywords :
DNA; feature extraction; image sequences; medical image processing; DNA sequences; Levy walk; biological functionality; deoxyribonucleic acid; feature extraction; multifractal analysis; optimal minimum window size; signal spectrum; DNA; Feature extraction; Fractals; Sequences; DNA sequences; feature extraction for classification; multifractal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location :
Kowloon, Hong Kong
Print_ISBN :
978-1-4244-4642-1
Type :
conf
DOI :
10.1109/COGINF.2009.5250696
Filename :
5250696
Link To Document :
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