基因组序列的初步小波分析

Jianchang Ning, Charles N. Moore, J. Nelson
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引用次数: 39

摘要

大型基因组测序项目使得开发准确的DNA序列注释方法变得迫切。现有的方法结合了从序列数据库或从已知基因的训练集比较中收集的知识的反算模式搜索。然而,这些方法的准确性还远远不能令人满意。在目前的研究中,将小波算法与熵法相结合,作为确定基因组DNA序列中基因位置的一种替代方法。小波方法寻找序列中存在的周期性。小波的一个很有前途的优点是它们对不同长度的编码/非编码区域的适应性。此外,结合熵值法的小波方法只搜索序列的信息内容,不需要对序列进行训练。初步结果表明,小波方法是可行的,并且可能优于一些基于基因组DNA序列样本的知识依赖方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Preliminary wavelet analysis of genomic sequences
Large genome-sequencing projects have made urgent the development of accurate methods for annotation of DNA sequences. Existing methods combine ab inito pattern searches with knowledge gathered from comparison with sequence databases or from training sets of known genes. However, the accuracy of these methods is still far from satisfactory. In the present study, wavelet algorithms in combination with entropy method are being developed as an alternative way to determine gene locations in genomic DNA sequences. Wavelet methods seek periodicity present in sequences. A promising advantage of wavelets is their adaptivity to varying lengths of coding/noncoding regions. Moreover, the wavelet methods integrated with entropy method just search the information contents of the sequences, which do not need to be trained. The preliminary results show that the wavelet approach is feasible and may be better than some knowledge-dependent approaches based on a sample of genomic DNA sequences.
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