The primary goal of the course is to teach students algorithms for analyzing
genomes, RNA, proteins, and biological networks. These techniques will
provide students a strong background for conducting their own bioinformatics
The official prerequisite is Introduction
to Bioinformatics (BMI/CS 576). Ideally, students would be familiar with basic
concepts from cell biology/genetics (e.g. genes, transcriptional regulation, cell
cycle, etc.) and computer science/machine learning (e.g. dynamic programming, graph
algorithms, clustering, etc.). No student will have the perfect background, therefore
it is critical that students ask for clarification in class when they are
unfamiliar with biological or computational concepts.
Information on homework and the project can be found on the
homework page. Students' participation will be assessed
based on their completion of the assigned readings and their questions and
comments in class and on the Piazza forum.
- Homework: ~40%
- Midterm exam: ~15%
- Final exam: ~15%
- Project: ~25%
- Participation: ~5%
The course's Canvas site is used only for grading. Course content is posted on
this site, and assignments are submitted through the biostat web server.
Homework, projects, and exams are to be completed individually. Students are welcome
to discuss concepts with their peers but not specific solutions to homework problems.
If students have doubts about the policy they should ask the instructor or
use the Piazza forum for clarification on a topic or assignment. Plagiarism -
including using text, images, or code without attribution - and cheating will not
be tolerated and will be dealt with in accordance with the