Title: Design of analytic wavelet transform with optimal filter coefficients for cancer diagnosis using genomic signals
Authors: Deepa Grover; Sonica Sondhi; Benoy Banerji
Addresses: IkGPTU, Jalandhar, India ' Chandigarh Group of Colleges, Landran, Mohali, India ' Department of Biochemistry, DAV(c) Dental College, Yamuna Nagar, Haryana, India
Abstract: DNA sequence analysis and gene expression analysis through genomic signal processing played an important role in cancer diagnosis in recent years. Cancer diagnosis through gene expression data, discrete Fourier transform, discrete wavelet transform (DWT) and IIR low pass filter are frequently used but suffer from drawbacks like longer essential time-support. Analytic wavelet transform with optimal filter coefficients for cancer diagnosis using genomic signals is designed in this paper. The proposed technique consists of three modules namely, pre-processing module, optimisation module and transform and cancer diagnosis module. Initially, the filter coefficients are optimally found out using group search optimiser. Then, the optimal coefficients and the pre-processed DNA sequence is applied to analytic wavelet transform and subsequently, diagnosis for the cancer cell is made based on the threshold. DNA sequences obtained from National Centre for Biotechnology Information (NCBI) forms the database for the evaluation. Evaluation metrics parameters employed are sensitivity, specificity and accuracy. Comparison is made to the base method and analytic transform technique for more analysis. From the results, we can observe that the proposed technique has achieved good results attaining accuracy of 91.6% which is better than other compared techniques.
Keywords: genomic signal processing; GSP; cancer diagnosis; GSO; analytic transform; thresholding.
International Journal of Biomedical Engineering and Technology, 2020 Vol.34 No.2, pp.172 - 188
Received: 10 Jun 2017
Accepted: 20 Nov 2017
Published online: 05 Nov 2020 *