Generated on Tue Oct 25 10:19:18 2022
CS 486: Bioinformatics (JSON)
Catalog description: Introduction to bioinformatics and computational biology. Computational approaches to sequences analysis, protein structure prediction and analysis, and selected topics from current advances in bioinformatics.
Prerequisites: At least a C- in C S 272 and C S 278 (Catalog Link)
Credits: 3 (3)
Coordinator: Joe Song
Textbook: Phillip Compeau & Pavel Pevzner. Bioinformatics Algorithms--An Active Learning Approach. 3rd Edition. Active Learning Publishers. La Jolla, California. 2018
(also: online reading)
BS degree role: selected elective
Course Learning Objectives
- Explain the biology motivation of a bioinformatics question
- Formulate a computational problem and its solution to address a molecular biology question
- Implement basic bioinformatics algorithms such as sequence alignment, pattern matching, and genome assembly
- Evaluate the performance of a bioinformatics algorithm on real data sets
- Argue the correctness of a bioinformatics algorithm
- Analyze the complexity of a bioinformatics algorithm
Course Practicum Requirements
- Implement bioinformatics algorithms using a programming language of choice
- Test the correctness of a computer program using well designed examples
- Use established open-source biological data collections to identify datasets for analysis
- Interpret the output of an program for biological implications
Course Topics
- Replication origin
- DNA pattern finding
- Genome assembly
- Cyclopeptide sequencing
- Sequence similarity
- Genome rearrangement
- Evolutionary tree
- Gene expression clustering
- Pattern matching
- Hidden Markov model
- Peptide sequencing and identification
Course Improvement Decisions
(Course improvement decisions or recommendations from past assessments)
- none
ABET Outcome Coverage
(Provide Mapping to ABET Student Outcomes)
- TBD
Other Notes
(Any important notes or issues to consider)
- none