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Proceedings Paper

DNA sequence similarity search through content-based retrieval technique
Author(s): Chia Hung Yeh; Po Yi Sung; Hsuan T. Chang; Chung Jung Kuo
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Paper Abstract

Deoxyribonucleic acid (DNA) sequences are difficult to analyze similarity due to their length and complexity. The challenge lies in being able to use digital signal processing (DSP) to solve highly relevant problems in DNA sequences. Here, we transfer a one-dimensional (1D) DNA sequence into a two-dimensional (2D) pattern by using the Peano scan algorithm. Four complex values are assigned to the characters “A”, “C”, “T”, and “G”, respectively. Then, Fourier transform is employed to obtain far-field amplitude distribution of the 2D pattern. Hereto, a 1D DNA sequence becomes a 2D image pattern. Features are extracted from the 2D image pattern with the Principle Component Analysis (PCA) method. Therefore, the DNA sequence database can be established. Unfortunately, comparing features may take a long time when the database is large since multi-dimensional features are often available. This problem is solved by building indexing structure like a filter to filter-out non-relevant items and select a subset of candidate DNA sequences. Clustering algorithms can organize the multi-dimensional feature data into the indexing structure for effective retrieval. Accordingly, the query sequence can be only compared against candidate ones rather than all sequences in database. In fact, our algorithm provides a pre-processing method to accelerate the DNA sequence search process. Finally, experimental results further demonstrate the efficiency of our proposed algorithm for DNA sequences similarity retrieval.

Paper Details

Date Published: 25 August 2003
PDF: 11 pages
Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); doi: 10.1117/12.486714
Show Author Affiliations
Chia Hung Yeh, Univ. of Southern California (United States)
Po Yi Sung, National Chung Cheng Univ. (Taiwan)
Hsuan T. Chang, National Yunlin Univ. of Science and Technology (Taiwan)
Chung Jung Kuo, National Chung Cheng Univ. (Taiwan)

Published in SPIE Proceedings Vol. 5096:
Signal Processing, Sensor Fusion, and Target Recognition XII
Ivan Kadar, Editor(s)

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