A DSP Technique for Prediction of Cancer Cell
Malaya Kumar Hota
1Malaya Kumar Hota, Professor, Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 07 July 2019 | Manuscript published on 30 August 2019 | PP: 1205-1209 | Volume-8 Issue-10, August 2019 | Retrieval Number: F3409048619/2019©BEIESP | DOI: 10.35940/ijitee.F3409.0881019
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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: At present cancer is an alarmed disease. According to medical research, central cause of cancer is due to the genetic abnormality. Most cancers are generated due to permanent change in the deoxyribonucleic acid (DNA). For the past two decades, genomic signal processing (GSP) is a vital area of research. It has engrossed the consideration of digital signal processing (DSP) researchers for the massive amount of data accessible in the public data base. By finding out the DNA sequence for cancer cells & normal cells of human beings & applying some digital signal processing (DSP) approaches on both, difference between them can be found. Previously, discrete Fourier transform (DFT) power spectrum was used to predict cancer cells of a DNA sequence. In this paper, discrete cosine transform (DCT) and discrete sine transform (DST) approaches are presented as an alternative to analyze the spectral characteristics of cancer cells and normal cells. Further, post-processing is done using digital IIR low pass filter to improve the discrepancy between cancer and normal cells. The proposed method is tested for a number of data sets available in Gene Bank.
Keywords: Digital Signal Processing (DSP), Digital IIR low pass filter, Discrete Cosine Transform (DCT), Discrete Sine Transform (DST).
Scope of the Article: Digital Signal Processing Theory