Prediction and Detection of Rheumatoid Arthritis SNPs Using Neural Networks

Rheumatic Arthritis (RA) is the most common disease found in the majority of the populations next to diabetes. RA is a chronic systemic inflammatory disease that primarily affects the synovial joints. The genes do contribute for the development of RA and it varies among individuals and between populations in different age group. It is necessary to know the gene factors that are associated with the disease for the better understanding of the underlying causes of the disease. Since RA is an auto-immune disease, it is important to identify the responsible SNPs of RA in order to detect and predict the disease well in advance. Prediction of RA helps in the early diagnosis of the disease and helps in improving the quality of life. This paper gives a detailed review of the existing methods that are used in the prediction of RA SNPs and also an ideology which works on the concept of Neural Network to detect and predict RA if a DNA sequence is given. The outcome of this would help doctors, genetic scientists, pharmacists in understanding the characteristic gene responsible for RA and provide proper diagnosis method and in discovering new drugs.

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