02-223 Personalized Medicine: Understanding Your Own Genome, Fall 2014
Course DescriptionDo you want to know how to discover the tendencies hidden in your genome? Since the first draft of a human genome sequence became available about a decade ago, the cost of genome sequencing has decreased dramatically. It is expected that personal genome sequencing will become a routine part of medical examinations for patients in clinics for prognostic and diagnostic purposes. Personal genome information will also play an increasing role in lifestyle choices, as people take into account their own genetic tendencies. Commercial services such as 23andMe have already taken first steps in this direction. Computational methods for mining large-scale genome data are being developed to unravel the genetic basis of diseases and to assist doctors in clinics.
This course will introduce students to the biological, computational, and ethical issues that concern the use of personal genome information in health maintenance, medical practice, biomedical research, and policymaking. The course will focus on practical issues, using individual genome sequences (such as that of Nobel prize winner James Watson) and other population-level genome data. Without requiring any background in biological or computational sciences, the course will begin with an overview of topics from genetics, molecular biology, statistics, and machine learning that are relevant to the modern personal genome era. The class will then cover scientific issues such as how to discover your genetic ancestry, how to learn from genomes about the migration and evolution of the human population, and how natural selection shaped our genomes. The class will then discuss medical aspects such as how to predict whether you will develop diseases such as diabetes based on your own genome, how to discover disease-causing genetic mutations, and how the genetic information can be used to recommend clinical treatments. It will close with consideration of the complex policy issues that our society will face as this personal genomics revolution unfolds.
GradingGrading will be based on biweekly lab reports (30%), a midterm (30%), a term paper (30%), and class participation (10%).