期刊
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
卷 387, 期 16-17, 页码 4223-4247出版社
ELSEVIER
DOI: 10.1016/j.physa.2008.02.076
关键词
the Hilbert-Huang transforms; empirical mode decomposition; wavelet analysis; DNA sequence analysis; spectral analysis
This paper presents a new algorithm for the analysis of spectral properties of short genes using the wavelet transform and the Hilbert-Huang transform (HHT). A wavelet subspace algorithm combined with the empirical mode decomposition (EMD) is introduced to create subdivided intrinsic mode functions (IMFs) and a cross-correlation analysis is applied to remove pseudo-spectral components. Experiments are carried out on DNA sequences with the double-base (DB) curve representation and the results show that the signal-to-noise ratio of buried signals can be enhanced using the proposed method, yielding significant patterns that are rarely observed with conventional methods. The wavelet subspace Hilbert-Huang transform (WSHHT) algorithm is able to correctly identify spectral patterns of very short genes (below 70 bp) in DNA sequences. (c) 2008 Elsevier B.V. All rights reserved.
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