Prediction of cancer cell using DSP techniques

Digital Signal Processing (DSP) applications have predominantly gained popularity in the study of genomics in recent time. DSP is now a widely applied tool in the segment of DNA sequence analysis, gene expression detection, identification of coding and non-coding regions and also finding out abnormalities present in the coding region. DSP explicates this task with increased accuracy and reduced complexity. As per explored medical research manuscripts it has been propounded to assimilate that dreaded cancer cells are often triggered in lieu of genetic abnormality. This empirical study, mounts a DFT based methodical approach to analyze the spectral characteristics of cancer and non-cancer cells and designs a digital IIR low pass filter with Butterworth approximation for ameliorated prediction and identification of anomalies in cancer cells. The proposed algorithm is tested for several databases of Homosapien chromosomes available in the Gene Bank that yielded in satisfactory results.