利用奇异值分解检测基因组序列的周期-3行为

Proceedings of the IEEE Symposium on Emerging Technologies, 2005. Pub Date : 2005-12-19 DOI:10.1109/ICET.2005.1558846

M. Akhtar, E. Ambikairajah, J. Epps

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引用次数: 31

摘要

许多数字信号处理技术已被用于自动区分dna序列中的蛋白质编码区(外显子)和非编码区(内含子)。近年来，自回归(AR)技术被用于检测基因组序列中蛋白质编码区存在的周期性。的。序列长度、编码区的平均间距和编码区的平均长度是影响任何预测方法性能的主要因素。在本文中，我们提出使用奇异值分解(SVD)方法检测DNA序列的周期-3行为。结果表明，svm方法优于ar技术。

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Detection of period-3 behavior in genomic sequences using singular value decomposition

Manydigital signal processing techniques have beenusedtoautomatically distinguish theprotein coding regions (exons) fromnon-coding regions (introns) inaDNAsequence. Recently, Auto-regressive (AR) technique hasbeenused forthedetection of3periodicty present inprotein coding regions of genomic sequences. The. sequence length, average spacing between coding regions, andaverage coding region length arethemainfactors thataffect the performance ofanyprediction method Inthis paper, wepropose theuseofSingular Value Decomposition (SVD) methodfor thedetection ofperiod-3 behavior in DNA sequences. Results showthatSVDmethod outperforms theARtechnique.

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Proceedings of the IEEE Symposium on Emerging Technologies, 2005.

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