| Title: | Demarcation of coding and non-coding regions of DNA using linear transforms |
| Author: | |
| Document Type: | Thesis |
| Department: | Department of Electrical and Computer Engineering |
| Degree: | Master of Science |
| Major: | Electrical Engineering |
| Advisory Committee: |
Haimovich, Alexander
Akansu, Ali N.
Shi, Yun Q.
|
| Thesis Date: | 2006, January |
| Keywords: |
DNA
DNA coding regions
Signal processing techniques
|
| Availability: | Unrestricted |
| Abstract: |
Deoxyribonucleic Acid (DNA) strand carries genetic information in
the cell. A strand of DNA consists of nitrogenous molecules called nucleotides.
Nucleotides triplets, or the codons, code for amino acids. There are two
distinct regions in DNA, the gene and the intergenic DNA, or the junk
DNA. Two regions can be distinguished in the gene- the exons, or the regions
that code for amino acid, and the introns, or the regions that do not
code for amino acid. The main aim of the thesis is to study signal processing
techniques that help distinguish between the regions of the exons and
the introns. Previous research has shown the fact that the exons can be
considered as a sequence of signal and noise, whereas introns are noise-like
sequences. Fourier Transform of an exonic sequence exhibits a peak at
frequency sample value k N/3 where N is the length of the FFT transform.
This property is referred to as the period -3 property. Unlike exons,
introns have a noise-like spectrum. The factor that determines the performance
efficiency of a transform is the figure of merit, defined as the ratio
of the peak value to the arithmetic mean of all the values. A comparative
study was conducted for the application of the Discrete Fourier Transform
and the Karhunen Loeve Transform. Though both DFT and KLT of an exon sequence
produce a higher figure of merit than that for an intron sequence, it
is interesting to note that the difference in the figure of merits of
exons and introns was higher when the KLT was applied to the sequence
than when the DFT was applied. The two transforms were also applied on
entire sequences in a sliding window fashion. Finally, the two transforms
were applied on a large number of sequences from a variety of organisms.
A Neyman Pearson based detector was used to obtain receiver operating
curves, i.e., probability of detection versus probability of false alarm.
When a transform is applied as a sliding window, the values for exons
and introns are taken separately. The exons and the introns served as
the two hypotheses of the detector. The Neyman Pearson detector helped
indicate the fact the KLT worked better on a variety of organisms than
the DFT.
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| Complete Thesis: |
njit-etd2006-018
(92 pages ~ 7,406 KB pdf)
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Created February 5, 2008
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