Abstract
A pattern filtering approach is developed to analyze genomic sequences in this work. With this approach, the distance of a certain pattern is first translated into a "gap sequence" consisting of integer numbers. Different patterns result in different gap sequences, and the similarity measure of two genomic sequences can be made based upon the processing of gap sequences generated by a set of pre-selected patterns. A matched filtering approach is applied to gap sequences. Furthermore, several post-processing techniques are applied to the filtered result for signal enhancement. For example, the modified Butterworth window (MBW) is used to remove the edge effect of the matched filter output, and the uncertain region is beleaguered by the advanced similarity test (AST) algorithm. The match between gap sequences is called a "frame match". The actual match of two genomic sequences demands both frame match and stuffing match. The proposed approach is useful for sequence analysis based on the frame match with desirable patterns. Extensive experimental results are presented to demonstrate the performance of the proposed method.
Original language | English |
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Pages (from-to) | 2893-2896 |
Number of pages | 4 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 3 |
Publication status | Published - 2003 |
Externally published | Yes |
Event | A New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico Duration: 2003 Sept 17 → 2003 Sept 21 |
Keywords
- Advanced similarity test
- Biosignal processing
- Gap sequence
- Matched filter
- Modified Butterworth window
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics