University of Wisconsin - Madison: Biostatistics & Medical Informatics 776
Computer Sciences 776
Advanced Bioinformatics (Spring 2021)

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

Course Overview Objective The primary goal of this course is to teach students algorithms for problems such as: modeling sequence classes and features, multiomics analysis, gene discovery, network biology, applied machine learning, and single-cell genomic analysis. This class will provide students with a strong background for conducting their own bioinformatics research. Please note that the entire Spring 2021 semester and TA Office Hours will be conducted virtually on Canvas BBCollaborateUltra. Instructor Office Hours will be held on Zoom. Prerequisites 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.). Python programming will be used. 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: ~10% Project: ~30% Participation: ~5% Please note that information on homework and the project can be found on the Homework and Project 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. Canvas The course's Canvas site is used for grading and virtual lectures. Course content is posted on this site, and assignments are submitted through the biostat web server. To access the biostat web server remotely, please ensure you have access to the Wisc VPN. Academic misconduct Please note that 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. Accommodations for Disabilities Please share appropriate information from the McBurney Disability Resource Center if you need accommodations for the exams and/or classes.