Course Description

Practical introduction to concepts, standards and tools for the implementation of strategies in bioinformatics and computational biology. Student led discussions plus a strong component of hands-on exercises. The “Applied Bioinformatics” course is offered as a part of the Bioinformatics and Computational Biology Program curriculum to ensure that our students know enough about application issues in the field to be able to put their knowledge into practice in a research lab setting. This is to support the Specialist Program goal: to prepare students for graduate studies in the discipline. As a required course in the BCB curriculum, BCB410 assumes the prerequisites and goals of fourth-year students in the BCB Specialist Program. Other students may be permitted to enrol on a case by case basis, but they may need to catch up on prerequisites in computer science or life-science courses that BCB students have taken at this point. Generally speaking, this is an advanced course that presupposes familiarity with programming principles, algorithm analysis, and methods of modern systems biology, as well as introductory knowledge of linear algebra, graph theory, information theory, statistics, as well as molecular-, structural- and cellular biology. The varying topics will be discussed at a highly technical level that is likely only useful for students who plan to integrate much of this material into their actual practice.

The course will consist of five phases:

Section I:
Define a tool for data analysis and pitch it to the class for feedback in a 1-minute presentation.

Section II:
Develop an R package for the analysis and keep track using Git.

Section III:
Class will work through others’ packages and review code.

Section IV:
Respond to the review, improve the material.

Section V:
Finalize package with a vignette with examples, and documentation.


BCH311H1 / CSB349H1 / MGY311Y1,
(CSC324H1 / CSC373H1 / CSC375H1) or permission of the course coordinator



Contact Hours


Required Text(s)/Readings

All course material will be available via Quercus

Recommended Text(s)/Readings

R packages by Hadley Wickham

– Algorithms in bioinformatics: a practical introduction by Wing-Kin Sung

Evaluation (Subject to change)

One-minute pitch: 10%
Initial submission of package: 15%
Participation in 4 review panels: 10 – 40%
Final submission: 20%
Ongoing Course Journal – 15%

Additional Information

In this year’s course, you will define a useful tool for the analysis of biological data, write an R package to support it, review and critique other packages, and improve and document your work. Bring your own laptop to class for hands-on practice and software implementation of the methods learned.

Last updated on May 31st, 2022