Fall 2016 Course Descriptions
COMP 150-05 Current Challenges in Computational Biology: Data, Methods and Validation
The 21st century has seen an unprecedented new collection of all sorts of genomic data from entire human genome sequences, to genomes of other organisms (including yeast, plants, and mice), to sequences of different cancer tumor cells. We can combine that data with data from other high-throughput biological experiments, to tell us, for example, which proteins interact in a cell. How do we translate these mountains of data into actionable insight into health and disease that might impact best practices in treatment? In this course we will talk about:
- DATA
- What kinds of data have been generated, and what is available in public databases?
- METHODS
- What sorts of analyses are done on these data, and what sort of questions are we trying to answer?
- VALIDATION
- How do we construct analyses in which we can have firm statistical confidence in our conclusions?
Prerequisite: Comp40 or Comp160 or graduate standing. No prior biology background is required. Limited to 20; high demand; sign up in the department.