Machine Learning Applications in Genetics

COM SCI C124 - Machine Learning Applications in Genetics

BIOINFO M224 - Machine Learning Applications in Genetics

HUM GEN CM224 - Machine Learning Applications in Genetics

<p>(Formerly numbered CM224.) Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course 32 or Program in Computing 10C with grade of C– or better, Mathematics 33A, and one course from Civil Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A. 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.</p>

Computer Science

Henry Samueli School of Engineering and Applied Science

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COM SCI C224 - Machine Learning Applications in Genetics

Students will obtain a background in computational genetics and obtain the necessary preparation for continuing in supervised research projects in this area.

Students will learn about machine learning methods, probabilistic models, efficient inference and learning in these models, model assessment, and interpreting the inferences to address the biological question at hand. The course will enable students to formulate the biological question as problems in statistical inference, to understand the assumptions and tradeoffs underlying these formulations, to find or develop efficient inference algorithms and to assess the quality of their inferences

General Catalog

Machine Learning Applications in Genetics

COM SCI C224

4 units