DNA Classification using Machine Learning for Detecting Genetic Disorders
Amisha Mishra1, Shruti Duggal2, Snehanshu Banerjee3, R. B. Sarooraj4
1Amisha Mishra*, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
2Shruti Duggal, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
3Snehanshu Banerjee, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India. 5Mr. R B Sarooraj, Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India
Manuscript received on March 15, 2020. | Revised Manuscript received on April 01, 2020. | Manuscript published on April 10, 2020. | PP: 1288-1291 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3781049620/2020©BEIESP | DOI: 10.35940/ijitee.F3781.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Deoxyribonucleic acid is a double- helical molecule composed of two chains that contains genetic instructions. Genetic diseases are caused by changes in pre-existing genes. A genetic abnormality results from the alteration in chromosomes. DNA classification helps to identify genetic disorders in organisms. DNA pattern recognition is a major issue in bioinformatics. DNA is classified into several categories on the basis of Structure, Location, Number of base pairs etc. Traditionally the DNA Molecule is studied by extracting it from the blood sample and is then manually analysed to find out the abnormalities. To increase the accuracy, a machine learning based DNA classification is done which helps in studying the extracted DNA image using various techniques. This consumes minimal amount of time and is more efficient. The image is pre processed using median filter and canny edge detection. DNA sequences can be recognized correctly and effectively without any uncertainties with the help of Neural Network. The network successfully classifies an image given as input when it is trained with patterns. Thus, we can analyse if a person has a genetic disorder.
Keywords: DNA, Canny Edge Detection, Neural Network, Genes.
Scope of the Article: Neural Information Processing