TAILIEUCHUNG - Báo cáo hóa học: " Research Article A Hybrid Technique for the Periodicity Characterization of Genomic Sequence Data"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Hybrid Technique for the Periodicity Characterization of Genomic Sequence Data | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2009 Article ID 924601 8 pages doi 2009 924601 Research Article A Hybrid Technique for the Periodicity Characterization of Genomic Sequence Data Julien Epps1 2 1 School of Electrical Engineering and Telecommunications The University of New South Wales Sydney NSW 2052 Australia 2 National Information Communication Technology Australia NICTA Australian Technology Park Eveleigh 1430 Australia Correspondence should be addressed to Julien Epps Received 29 May 2008 Revised 13 October 2008 Accepted 21 January 2009 Recommended by Ulisses Braga-Neto Many studies of biological sequence data have examined sequence structure in terms of periodicity and various methods for measuring periodicity have been suggested for this purpose. This paper compares two such methods autocorrelation and the Fourier transform using synthetic periodic sequences and explains the differences in periodicity estimates produced by each. A hybrid autocorrelation integer period discrete Fourier transform is proposed that combines the advantages of both techniques. Collectively this representation and a recently proposed variant on the discrete Fourier transform offer alternatives to the widely used autocorrelation for the periodicity characterization of sequence data. Finally these methods are compared for various tetramers of interest in C. elegans chromosome I. Copyright 2009 Julien Epps. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction The detection of structure within the DNA sequence has long captivated the interest of the research community. Among the various statistical characterizations of sequence data one measure of structure within sequences is the degree of correlation or periodicity at various .

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