Biostatistics & Medical Informatics 776
Computer Sciences 776
Advanced Bioinformatics (Spring 2019)

General Course Information
Course Overview
Syllabus, Readings, Lecture Notes
Homework and Project
Past Semesters

Course Overview


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 research.


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.

Grading criteria

  • Homework: ~40%
  • Midterm exam: ~15%
  • Final exam: ~15%
  • Project: ~25%
  • Participation: ~5%
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.


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.

Academic misconduct

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 Academic Misconduct Process.