Open AccessModified Gabor Wavelet Transform in Prediction of Cancerous Genes
Author(s) -
Lopamudra Das,
Anand Kumar,
Jitendra Kumar Das,
Sarita Nanda
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a9417.109119
Subject(s) - benchmark (surveying) , pattern recognition (psychology) , artificial intelligence , computer science , wavelet transform , wavelet , gabor wavelet , sequence (biology) , discrete wavelet transform , digital signal processing , biology , genetics , geodesy , geography , computer hardware
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.