Gene-Disease Association Classification Using Xgboost Classifier

During last couple of decades, a lot of efforts had been devoted by researchers in exploring gene disease relationships using Genome Wide Association studies. These relationships among gene-disease can showcase new dimensions of correlations at genetic level which may lead to reveal disease similarity. These can help in prevention, diagnosis and treatment of disease at genetic level. Also a proper understanding between disease and genes will lead to better explanation of complex gene functions in human body. In this paper, researchers have implemented machine learning model to classify the disease as per the respective disease semantic type. For this, authors used XGBoost Classifier in this research work. The performance score and a detailed analysis is given.