Courses

GERO 499: “Introduction to genomic science for biologists and health scientists”

Spring term 2019 – Thursdays 10 am, GERO230

Course Description

Ever since the human genome project provided a blueprint for our genomes, genomics has transformed all fields of biological research, including aging biology, but has also transformed medical decision-making. Many companies have emerged that now offer direct-to-consumer “personal genomic” data for your personal genome (e.g. 23 and me), or, even, for your pets. The ease of data collection and recent drops in sequencing costs have even led to the emergence of a new field: “personalized” or “precision” medicine, which leverages personal genomes to design treatments. The wide appeal of ‘omics’ in the post-genomic era resides in its ability to unbiasedly interrogate thousands of genes and their regulatory environment. However, despite the explosion of genomic data availability, ‘big data’ analysis remains intimidating to biologists, despite the fact that an increasingly large portion of biology relies on genomics/bioinformatics. As a biologist, do you want to solely rely on the expertise of computer scientists to access genomic knowledge, or would you like to be able to take charge of some biological ‘big data’ analyses?

This course will provide a broad introduction to the field of genomics to people with a biology background, including overviews of ‘wet’ genomics techniques, available public databases, and useful analytical tools. At the very least, this course will empower you to understand the intricacies of genomic data science, genome-engineering, and may context for the lessons that can be learned from this approach, and how they can be applied to biological study at many levels. This course will be an introduction to genomics, and, if you get “bit by the genomics bug” as I have through this class, I encourage you to look into further advanced programs and courses at USC that will cover more specialized training in this field!

Learning Objectives

This course will empower students:

  1. Get familiar with existing techniques and data types in the post-genomic era;
  2. Navigate about publicly available genomic resources and how to utilize them;
  3. Demystify basic programming skills in Linux/Unix and R for students without a computational background;
  4. Facilitate statistical analysis and genomic data exploration and analysis;
  5. Leverage bioinformatics tools and databases to compile new biological information.