Modified Gabor Wavelet Transform in Prediction of Cancerous Genes 
Lopamudra Das1, Anand Kumar2, J. K. Das3, Sarita Nanda4
1Lopamudra Das, Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India.
2Anand Kumar, Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India.
3J. K. Das, Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India.
4Sarita Nanda*, Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India.
Manuscript received on September 24, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 902-907 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9417109119/2019©BEIESP | DOI: 10.35940/ijeat.A9417.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cancer is the leading cause of mortality all over the world which in general is the result of some kind of mutation in the genetic sequence. With recent advancements in Digital Signal Processing(DSP) techniques, it has become possible to classify cancerous gene sequences without carrying out extensive biological experiments. In this paper, the Geometric mapping technique along with Modified Gabor wavelet transform (MGWT) has been incorporated to segregate cancerous and non-cancerous gene sequences. This Gabor wavelet based transform technique used in the present research work benefits from the fact that it is independent of the window length which in conjunction with Geometric mapping is used to obtain the spectral components present in the signal accurately and with reduced complexity. This technique has been applied on numerous benchmark datasets and the results obtained prove the performance of the proposed method.
Keywords: Deoxyribonucleic Acid (DNA), Genomic Signal Processing(GSP), Modified Gabor Wavelet Transform (MGWT), Geometric mapping, Cancer.