Bio331: Computational Systems Biology
In the era of high-throughput genomics, proteomics, and transcriptomics, we can now computationally explore biological processes at a systems level. Networks, or graphs, have become a dominant mathematical representation in this area of research. We will draw on the vast amount of established graph theory to learn about network models currently applied to biological systems.
About this syllabus
This syllabus is a public, searchable document that contains all of the details for this iteration of the course. It serves as a contract for the students taking Bio331 - if you take this course, you agree to abide by the policies described here. As the instructor, I commit to following this syllabus and administering it fairly and equitably.
The final version of this syllabus will be set by the first day of class. Any modifications during the semester will be noted in the change log and will be communicated to the class via Moodle.
Course details
Instructor: Anna Ritz (Biology 200B, student hours Thursdays 10-11; 2:30-3:30)
Lecture: MWF 10-10:50am in Library 204
Lab: M 1:10-4:00 in ETC 208
Materials: All reading, videos, and other materials will be freely available via Moodle. A week-by-week schedule is available on Moodle as well.
Communication & Technology
Official communications about all course materials and assignments will be done through the Moodle page.
- Check your email every day to stay updated.
- We will use GitHub for the programming assignments.
- We will use Moodle for exam submissions.
- We will use a combination of GitHub and Moodle for the research project.
- If you have a question, others likely have the same question. Reach out at any time to me at aritz@reed.edu.
The Honor Principle is in effect at all times. This includes our work and interactions in class as well as our work done outside of class.