Spectral Analysis of Exons in DNA Signals - Digital Filters and Signal Processing - page 50

Method E 1 E 2 E 3 E 4 E 5

Binary Method 656-1206 2406-3106 3806-4406 5306-5806 7106-7706

EIIP Method 706-1206 2206-2906 3906-4406 5206-5806 7206-7706

Complex Method 750-1100 2600-2906 3600-4406 5206-5706 7106-7600

Filter 1 (Anti-notch) 656-1206 2450-3106 3806-4450 5306-5850 7106-7750

Filter 2 (Multistage) 706-1250 2206-2950 3906-4450 5206-5850 7206-7706

proposed Method 750-1050 2450-2906 3950-4380 5206-5600 7220-7680

NCBI Range 928-1039 2528-2857 4114-4377 5465-5644 7255-7605

Table 1. Range of exons for different methods

4. Conclusion

Bioinformatics is a very rapidly emerging field of research. The genome sequence analysis is
an interesting and challenging task that needs great attention. The analysis brings very
promising relevance between species. The proposed approach provides a way to better
identify the genetic regions in mixture of exon-intron noise. The focus directed to minimize
the leakage of frequency contents by adoption of an optimal indicator sequence. We also re‐
duced the signal noise by using Kaiser Window function with length 351 base pairs. The
spectral density estimation was enhanced with application of wavelet transforms. The pro‐
posed dimensions reduced the noise and increased the sharp peaks of exons in density
graphs. We have observed significant improvement in results as a comparative analysis be‐
tween existing techniques and compared the results with strands NCBI range.

Author details

Noor Zaman 1* , Ahmed Muneer 1 and Fausto Pedro García Márquez 2

*Address all correspondence to: [e-mail]

*Address all correspondence to: [e-mail]

*Address all correspondence to: [e-mail]

1 College of Computer Sciences & Information Technology,King Faisal University, Saudi
Arabia

2 ETSI Industriales, Universidad Castilla-La Mancha, Ciudad Real, Spain