Association of single nucleotide polymorphism and phenotype in type 2 of diabetes mellitus using Support Vector Regression and Genetic Algorithm

Precision Medicine is used to improve proper health care and patients' quality of life, one which diabetes. Diabetes Mellitus (DM) a multifactorial heterogeneous group disorders characterized by deficiency or failure maintain normal glucose homeostasis. About 90% all DM patients are Type 2 (T2DM). Biological characteristics genetic information T2DM disease were obtained looking for associations in Single Nucleotide Polymorphism (SNP) allows determining the relationship between phenotypic genotypic identifying genes associated with disease. This research focuses on Support Vector Regression method Genetic Algorithm obtain SNPs that have previously calculated correlation value using Spearman's rank correlation. Then do association mapping SNP results from SVR-GA selection check pastasis interaction. The produced 14 importance. Evaluation model mean absolute error (MAE) 0.02807. If MAE close zero, then can be accepted. generated assist other researchers finding right treatment according their profile.