Abstract
Signal processing has a great role in innovative developments in technology. Its techniques have been applied mostly in every field of science and engineering. In the field of bioinformatics it has to play an important role in the study of biomedical applications. Accurate prediction of protein coding regions (Exons) from genomic sequences is an increasing demand for bioinformatics research. Many progresses made in the identification of protein coding regions during the last few decades. But the performances of the identification methods still required to be improved. This paper deals with the identification of protein-coding regions of the DNA sequence mainly focus on analysis of the gene introns. Applications of signal processing tools like spectral analysis, digital filtering of DNA sequences are explored. It has been tried to develop a new method to predict protein coding regions based on the fact that most of exon sequences have a 3-base periodicity. The period-3 property found in exons helps signal processing based time-domain and frequency domain methods to predict these regions efficiently. Also, an efficient technique has been developed for the identification of protein coding region based on the period-3 behavior of codon sequences. It is based on time domain periodogram approach. Here it has been identified the protein coding regions, wherein we reduced the background noise significantly and improve the identification efficiency. In addition to this also comparison is done between time domain periodogram and the existing frequency based techniques. Simulation results obtained are shown the effectiveness of the proposed methods. This proves that the DSP techniques have important applications in obtaining useful information from these gene sequences.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Mount, D.W.: Bioinformatics: Genome and Sequence Analysis, 2nd edn. Cold Spring Harbor Laboratory Press, New York (2004)
Anastassiou, D.: Genomic signal processing. IEEE Signal Processing Magazine 18(4), 8–20 (2001)
Anastassiou, D.: DSP in Genomics. In: Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, Salt lake City, Utah, USA, pp. 1053–1056 (May 2001)
Voss, R.F.: Evolution of long-range fractal correlations and 1/f noise in DNA base se-quences. Phy. Rev. Lett. 68(25), 3805–3808 (1992)
Nair, A.S., Sreenathan, S.P.: A Coding measure scheme employing electron-ion interaction pseudo potential (EIIP). Bioinformation by Bioinformatics Publishing Group
Ahmad, M., Abdullah, A., Buragga, K.: A Novel Optimized Approach for Gene Identification in DNA Sequences. Journal of Applied Sciences, 806–814 (2011)
Deng, S., Chen, Z., Ding, G., Li, Y.: Prediction of Protein Coding Regions by Combining Fourier and Wavelet transform. In: Proc. of the 3rd IEEE Int. Congress on Image and Signal Processing, pp. 4113–4117 (October 2010)
Akhtar, M., Epps, J., Ambikairajah, E.: Signal Processing in sequence analysis: Advances in Eukaryotic Gene Prediction. IEEE Journal of Selected Topics in Signal Processing 2(3), 310–321 (2008)
Biju, V.G., Mydhili, P.: Genetic Algorithm Based indicator sequence method for exon prediction. In: Proc. of the IEEE int. Conf. on Advances in Computing, Control, & Telecommunication Technologies, pp. 856–858 (December 2009)
Voss, R.: Evolution of Long-Range Fractal Correlations and 1/f Noise in DNA Base Sequences. Physical Review Letters 68(25), 3805–3808 (1992)
Hota, M.K., Srivastava, V.K.: Identification of Protein coding regions using Antinotch filters. Digital Signal Processing 22(6), 869–877 (2012)
Silverman, B.D., Linsker, R.: A Measure of DNA Periodicity. Journal of Theoretical Biology 118(3), 295–300 (1986)
Tiwari, S., Ramachandran, S., Bhattacharya, A., Bhatta-charya, S., Ramaswamy, R.: Identification of Probable Genes by Fourier Analysis of Genomic Sequences. Bioinformatics 13(3), 263–270 (1997)
Anastassiou, D.: Digital Signal Processing of Bio-molecular Sequences. Technical Report, Columbia University, 2000-20-041 (April 2000)
Anastassiou, D.: Frequency-Domain Analysis of Biomolecular Sequences. Bioinformatics 16(12), 1073–1082 (2000)
Fickett, J.W.: The gene identification problem: an overview for developers. Comput. Chem. 20, 103–118 (1996)
Vaidyanathan, P.P., Yoon, B.J.: The role of signal processing concepts in genomics and proteomics. J. Franklin Inst. 341, 111–135 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Mohanty, M.N. (2014). A Signal Processing Approach for Eucaryotic Gene Identification. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II. Advances in Intelligent Systems and Computing, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-319-03095-1_39
Download citation
DOI: https://doi.org/10.1007/978-3-319-03095-1_39
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03094-4
Online ISBN: 978-3-319-03095-1
eBook Packages: EngineeringEngineering (R0)