| Description: |
Students will learn to think algorithmically by constructing a biological hypothesis, and implementing code or deploying an existing code implementation, to test that hypothesis. Students will learn to use UNIX and to program in Python, using biological data sets from high-throughput sequencing projects. We will cover major genomics approaches and the algorithms that underlie them, including K-mer analysis, genome and transcriptome assembly, databases and SQL, and visualization techniques. Course Information: Same as CPSC 501. 4 graduate hours. No professional credit. Prerequisite: Courses in Ecology, Evolution, and Molecular Biology, or consent of instructor. |
