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使用改进的伽柏小波变换识别蛋白质编码区域。

Identification of protein coding regions using the modified Gabor-wavelet transform.

作者信息

Mena-Chalco Jesús P, Carrer Helaine, Zana Yossi, Cesar Roberto M

机构信息

Departmento de Ciencia da Computação, Instituto de Matemática e Estatística de Universidade de São Paulo, Rua do Matão, Cidade Universitária, São Paulo, SP, Brasil.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2008 Apr-Jun;5(2):198-207. doi: 10.1109/TCBB.2007.70259.

Abstract

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods, based on the occurrence of specific patterns of nucleotides at coding regions, have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically pre-defined window length required for a local analysis of a DNA region. We introduce a method, based on a modified Gabor-wavelet transform (MGWT), for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods using eukaryote datasets. The results show that the MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors, but also makes available a tool for detailed exploration of the nucleotide occurrence.

摘要

基因组序列分析中的一个重要课题是蛋白质编码区域的识别。在此背景下,已经提出了几种基于编码区域特定核苷酸模式出现情况的与编码DNA模型无关的方法。然而,由于这些方法依赖于对DNA区域进行局部分析所需的经验预定义窗口长度,它们并不完全适用。我们引入了一种基于改进的伽柏小波变换(MGWT)的方法来识别蛋白质编码区域。这种新颖的变换经过调整以分析周期性信号成分,并且具有独立于窗口长度的优点。我们使用真核生物数据集将MGWT的性能与其他方法进行了比较。结果表明,在识别准确性方面,MGWT优于所有评估的与模型无关的方法。这些结果表明,先前方法产生的至少部分识别错误的根源是固定的工作尺度。新方法不仅避免了这种错误来源,还提供了一种详细探索核苷酸出现情况的工具。

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