Abstract
Background: The genomic sequences can be expressed in terms of alphabets and hence they are discrete in nature. Therefore, digital techniques to analyze genetic problems are in need.
Objective: The main aim is to use digital signal processing techniques for the detection of CpG islands. Method: A method to detect the CpG islands using wavelet filtering has been proposed. Modified Electron Ion Interaction Potential mapping has been proposed for numeric conversion. The signal is restricted in frequency through a band pass filter and then wavelet filtered. CpG islands produce bigger magnitude coefficients in the wavelet domain. Results: The proposed method has been tested on genomes of Homosapiens, Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Escherichia coli, Zebrafish, Arabidopsis thaliana and Mus musculus, downloaded from the national center for biotechnology information database. Standard performance metrics have been evaluated and the values obtained are sensitivity - 84.68%, specificity – 85.6%, accuracy – 82.22% and correlation coefficient – 63.31%. Conclusion: On comparing the evaluation metrics obtained to the methods in the literature, it is found that the wavelet transformation method is better. The area under the receiver operating characteristic curve has also been evaluated and is 0.8705 which is larger compared to the methods in literature. Hence, it can be concluded that the proposed method is efficient in detecting CpG islands.Keywords: Bioinformatics, deoxyribonucleic acid (DNA) sequences, digital signal processing (DSP), discrete wavelet transformation (DWT), genomic signal processing (GSP) and CpG islands (CGI).
Graphical Abstract
Related Books
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 2)
Micropropagation of Medicinal Plants
Software and Programming Tools in Pharmaceutical Research
Biotechnology and Drug Development for Targeting Human Diseases
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 1)
Molecular and Physiological Insights into Plant Stress Tolerance and Applications in Agriculture- Part 2
Micropropagation of Medicinal Plants
Genome Editing in Bacteria (Part 1)
Data Science for Agricultural Innovation and Productivity
Animal Models In Experimental Medicine
23
4
2