Course
Course Catalog URL:
Identifier:
COM S 444
- Credits and contact hours: 4 credits, 3 contact hours
- Instructor’s or course coordinator’s name: Karin Dorman
- Text book, title, author, and year: None required
- Other supplemental materials: None
Specific course information
- Brief description of the content of the course: Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: bioinformatic data processing, Python programming, genome assembly, database search, sequence alignment, gene prediction, next-generation sequencing, comparative and functional genomics, and systems biology.
- Prerequisites or co-requisites: MATH 165 and Introductory Statistics (STAT 101, STAT 104, STAT 105, STAT 201 or STAT 330)
- Required, elective, or selected elective? Selected Elective
Specific goals for the course
- Specific outcomes of instruction:
- An ability to analyze a complex computing problem and to apply principles of computing to identify solutions (1)
- An ability to apply computer science theory and software development fundamentals to produce computing-based solutions (6)
Brief list of topics to be covered
- Linux/Python
- Finding patterns in sequence data
- Sequence indexing, matching, alignment
- Basic Local Alignment, database search
- Multiple sequence alignment, molecular evolution
- Genome assembly
- Gene expression analysis
- Prediction, machine learning