Affiliation:
1. School of Mathematics, Shandong University, Jinan, Shandong 250100, China
Abstract
The identification of protein coding regions (exons) plays a critical role in eukaryotic gene structure prediction. Many techniques have been introduced for discriminating between the exons and the introns in the eukaryotic DNA sequences, such as the discrete Fourier transform (DFT) based techniques, but these DFT-based methods rapidly lose their effectiveness in the case of short DNA sequences. In this paper, a novel integrated algorithm based on autoregressive spectrum analysis and wavelet packets transform is presented to improve the efficiency and accuracy of the coding regions identification. The experimental results show that the new algorithm outperforms the conventional DFT-based approaches in improving the prediction accuracy of protein coding regions distinctly by testing GENSCAN65, HMR195, and BG570 benchmark datasets.
Funder
National Natural Science Foundation of China
Subject
Applied Mathematics,Analysis
Cited by
15 articles.
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