Machine Learning Applications in Genetics

(Formerly numbered CM224.) Prior knowledge of biology is not required. Introduction of main applications of machine learning in genetics. Students are prepared for interdisciplinary research in genetics that involves a major computational and statistical component. Topics include introduction to genetics, identification of genes involved in disease using regression techniques, inference of heritability using linear mixed models, inferring human population history using Markov models, methods for phasing genotype data including expectation maximization, computational optimization methods and methods for dimensionality reduction including principal component analysis (PCA), and genotype-phenotype prediction using machine learning techniques. Concurrently scheduled with course C124.

Letter grading.