Detection of exon location in eukaryotic DNA using a fuzzy adaptive Gabor wavelet transform

The existing model-independent methods for the detection of exons in DNA could not prove to be ideal as commonly employed fixed window length strategy produces spectral leakage causing signal noise The Modified-Gabor-wavelet-transform exploits a multiscale strategy to deal with the issue to some extent. Yet, no rule regarding the occurrence of small and large exons has been specified. To overcome this randomness, scaling-factor of GWT has been adapted based on a fuzzy rule. Due to the nucleotides' genetic code and fuzzy behaviors in DNA configuration, this work could adopt the fuzzy approach. Two fuzzy membership functions (large and small) take care of the variation in the coding regions. The fuzzy-based learning parameter adaptively tunes the scale factor for fast and precise prediction of exons. The proposed approach has an immense plus point of being capable of isolating detailed sub-regions in each exon efficiently proving its efficacy comparing with existing techniques. •A new Fuzzy rule-based Adaptive Gabor Wavelet Transform (FAGWT) method is proposed for the identification of short as well as long exon regions in Eukaryote DNA.•The proposed approach inherits the benefits of a model-independent method and integrates with it a model-dependent fuzzy variable technique with an aim to improve the prediction performance.•The FAGWT approach has an immense plus point of being capable of isolating detailed sub-regions in each exon efficiently proving its efficacy as compared to the existing techniques.•Scalogram plot is used to visualize digitized DNA sequence and projection coefficients show accurate and detailed exon position in a DNA sequence. Analysis and comparison with other state of art methods are presented in terms of performance evaluation parameters like accuracy, sensitivity, specificity, and SNR.•The proposed method outperforms the existing approaches by achieving a maximum accuracy of 92% at 88% of threshold when assessed on benchmark gene sequences.