Using Machine Learning

Abstract

To , we - learning technique that scores the likelihood that a gene , when mutated , will cause a neurological phenotype . We analysed 1126 genes relating to 25 subtypes of Mendelian neurological disease (March) together - specific capturing , gene - specific - expression . We - sampled decision - tree , which - based each . Genes probability to . Using - mutant of - phenotype significant enrichment of relevant phenotypic abnormalities when predicted genes were mutated . Furthermore , using 2017 release , we assessed our gene - phenotype predictions and showed an 8 . 3 fold enrichment relative to chance for correct predictions . Thus , we demonstrate both the explanatory - learning - based .