Bioinformatic Analysis

COM S 444
  1. Credits and contact hours: 4 credits, 3 contact hours
  2. Instructor’s or course coordinator’s name: Karin Dorman
  3. Text book, title, author, and year: None required
  4. Other supplemental materials: None

Specific course information

  1. 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.
  2. Prerequisites or co-requisites: MATH 165 and Introductory Statistics (STAT 101, STAT 104, STAT 105, STAT 201 or STAT 330)
  3. Required, elective, or selected elective? Selected Elective

Specific goals for the course

  1. 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