DNA Classification using Machine Learning for Detecting Genetic Disorders

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.