Review of computational approaches to Parkinson’s disease gene prediction

Parkinson's disease is a chronic neuro-degenerative disease that affects the central nervous system. Since the causes of the disease are still unknown, both genetic and environmental factors are believed to be involved. Therefore, the identification and prediction of this genetic disorder plays an important role in early detection and treatment. The genomic data is extremely large and distorted, so the use of R tools can make the analysis and pre- processing of data easier. There are several computational approaches to the prediction of this disorder which varies with its accuracy and performance.