Computer Science (COMP) 625

Overview

Bioinformatics is an interdisciplinary field that develops computational methods and software tools for understanding biological data, especially when data sets are large and complex. COMP 625: Algorithms for Bioinformatics focuses on the algorithms that are essential for bioinformatics, with practical projects using Python in the Unix/Linux environment.

Outline

Part I: Fundamentals

• Unit 1: Introduction to Bioinformatics
• Unit 2: Introduction to Python Programming and Environment
• Unit 3: Cellular and Molecular Biology Fundamentals
• Unit 4: Basic Processing of Biological Sequences

Part II: Basic Sequence Algorithms

• Unit 5: Pattern Finding Algorithms
• Unit 6: Pairwise Sequence Alignment
• Unit 7: Sequence Searching Algorithms
• Unit 8: Multiple Sequence Alignment
• Unit 9: Phylogenetic Analysis
• Unit 10: Motif Discovery Algorithms
• Unit 11: Probabilistic Motifs and Stochastic Algorithms

Part III: Advanced Algorithms

• Unit 12: Hidden Markov Models
• Unit 13: Graph Algorithms
• Unit 14: Assembling and Matching Reads

Learning outcomes

Upon successful completion of this course, you should be able to

• explain the objectives and principles of bioinformatics data analysis from a computing and algorithm perspective.
• design and implement algorithms and programs for sequence analysis, searching, alignment, and assembly tasks for analyzing and understanding bioinformatics data.
• exploit different programming libraries in processing and analysis of bioinformatics data.
• develop prototypes of bioinformatics data analysis applications.

Evaluation

To receive credit for COMP 625, you must achieve a course composite grade of at least B– (70 percent) and a grade of at least 60 percent on each assignment and the final project.

The weighting of the composite grade is as follows:

Materials

Digital course materials

Links to the following course materials will be made available in the course:

Rocha, M., & Ferreira, P. G. (2018). Bioinformatics algorithms: Design and implementation in Python (1st ed.). Academic Press.

Important links

• Future Course Offerings
• Important Dates and Deadlines
• MSc IS Contact Information