Phenotype Prediction using Machine Learning based on Genomic Data

The human genome contains valuable information about the person and its hand analysis is cumbersome since it consists of billions of nucleotides. This work computationally analyses the mutations in the human genome which are the main source of differences and diseases. It utilizes ensembling of various feature selection models on an ALS dataset that is obtained from MinE Project and labels the genomes as ALS or non-ALS. The experiments display that the dataset is too small to derive solid rules with computational approaches.