Wavelet profiles: their application in Oryza sativa DNA sequence analysis

N. Kawagashira, Yasuhiro Ohtomo, K. Murakami, K. Matsubara, J. Kawai, Piero Carninci, Y. Hayashizaki, S. Kikuchi
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引用次数: 8

Abstract

Here we introduce our application of the wavelet analysis method to DNA sequences. In the signal processing field, Fourier transform is popular for analyzing wave data. However, although this method can process frequency information, it fails to handle locational data. In contrast, the wavelet method accommodates both locational and frequency information for wave analysis. The wavelet method is now increasing in its importance for signal processing. Fast Fourier transform is already applied to biological sequence analysis using correlations. We introduce a new method, called wavelet profile, for biological sequence analysis. Our method is based on multiresolution analysis of wavelet transform, offering data decomposition in several scaling at the same time. We applied our wavelet profile method to identifying gene loci among O. sativa genomic sequences.
小波谱在水稻DNA序列分析中的应用
本文介绍了小波分析方法在DNA序列分析中的应用。在信号处理领域,傅里叶变换是分析波浪数据的常用方法。然而,这种方法虽然可以处理频率信息,但不能处理位置数据。相反,小波分析方法同时包含位置和频率信息。小波变换在信号处理中的重要性与日俱增。快速傅里叶变换已经应用于利用相关性分析生物序列。本文介绍了一种新的生物序列分析方法——小波剖面法。该方法基于小波变换的多分辨率分析,同时提供多个尺度的数据分解。应用小波分析方法对玉米基因组序列进行基因定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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