This section contains the courses offered at UBC. Students can also take courses from SFU after completing the Western Deans’ Agreement form (contact program coordinator for more details). Click here for information about SFU’s courses. Information on courses required by CIHR-funded students can be found here.
Students are required to complete a total of 6 courses. All mandatory courses have to be completed, and students pick additional courses to fill up the 6 slots. Mandatory courses can be waived if students have already taken them or have taken similar courses. Students will have to contact the professors teaching those courses in order to obtain the waiver approval (see UBC SSC for course details). In that situation, students will still need to select other optional courses.
Core Courses (mandatory*):
*BIOF 520 | PROBLEM BASED LEARNING IN BIOINFORMATICS
The problem-based learning course will develop students’ ability to exchange ideas in small groups focused on real but simplified problems in bioinformatics. Problems will be carefully selected to cover all aspects of bioinformatics research. The core curriculum is identical during the first year for post-graduate diploma and for master’s students. The SFU equivalent is MBB 505.
BIOF 501A | SPECIAL TOPICS IN BIOINFORMATICS
This discussion-based Bioinformatics course will expose students to the latest developments in Bioinformatics analysis and algorithms. It will run in conjunction with the VanBug Seminar Series, in which the students will have the opportunity to meet and discuss their work with guest speakers, both local and international scientists. The SFU equivalent for this course is MBB 659.
Choose either one of 1A/1B OR 2)
1A: CMPT 711 | BIOINFORMATICS ALGORITHMS – may be a substitute for CMPT 881/CPSC445/CPSC545
This is an introductory level graduate course offered in SFU on fundamental computational techniques which have been successfully applied to key problems in bioinformatics. Particular problem areas of interest include sequence alignment and search, motif discovery, molecular structure prediction, phylogenetics, biomolecular interactions and cellular networks. We will cover various computational tools ranging from ones which are combinatorial in nature, such as dynamic programming, index structures, approximation algorithms, and randomized algorithms to those which are statistical such as expectation maximization and Gibbs sampling.
1B: CPSC 545 | ALGORITHMS FOR BIOINFORMATICS – may be a substitute for CMPT 771/CMPT881/CPSC445.
This graduate level course offered in UBC computer-science that focuses on the algorithms that are currently in Bioinformatics. e.g. sequence alignment, gene prediction and sequence annotation, RNA and protein structure prediction and phylogenetic analysis. The aim of this course is to give you detailed understanding of the existing algorithms and to prepare you to develop you own applications and algorithms. The course is meant to be very interactive in style and will involve coursework on projects. You should be comfortable with basic mathematical reasoning, have a good understanding of the main principles of molecular biology and be confident programming in a higher-level language such as C, C++ or Java. Due to the interactive nature of the course, enrollment is restricted to a small number of dedicated students. Note: CPSC 445 may be substituted for CPSC 545 if the student does not have a strong computational background.
2: STAT 540| STATISTICAL METHODS FOR HIGH DIMENSIONAL BIOLOGY
This course will cover quantitative problems arising from current research. We focus on areas in which a statistical approach provides a powerful tool for separating signal from noise. Students will learn to translate genomic research questions into well-defined computational problems. Solutions and algorithms are found which are both theoretically sound and practical to implement. Selected topics: gene expression analysis, analysis of tissue and protein arrays, sequence alignment and comparison, Hidden Markov Models.
* If you have already taken any of these courses as an undergraduate or have taken equivalent material at another University, you are not required to repeat the material, rather choose an additional elective to make up the requirement of 6 courses needed for graduate studies (18 credits). Please note that University policy specifies that no course credit can be awarded to a student towards graduate studies credits for courses taken before enrollment in graduate school.
CPSC 304 | INTRODUCTION TO RELATIONAL DATABASES
Focus is relational databases, dealing with relational database design, relational database languages, and concepts related to the transaction processing layer (top layer) of a database management system (DBMS).
CPSC 445 | ALGORITHMS IN BIOINFORMATICS
Bioinformatics involves the application of computational methods to answer or provide insight on questions of molecular biology. This course provides an introduction to the design and analysis of algorithms for bioinformatics applications.
CPSC 504 | DATABASE DESIGN
Organizing information as relations. Information retrieval through queries against relations. Storing relations as data. Efficient storage and retrieval of data needed by queries. Reliability integrity and security considerations in database design.
HCEP 511 | CANCER EPIDEMIOLOGY
Collection and analysis of epidemiological data on cancer; occupational and other risk factors,; analytic techniques and mathematical modeling relevant to oncology.
CPSC 53A | TOPICS IN ALGORITHMS AND COMPLEXITY – BIOINFORMATICS
This course introduces algorithms and their application in bioinformatics Topics include sequence alignment, phylogenetic tree reconstruction, prediction of RNA and protein structure, gene finding and sequence annotation, gene expression, and biomolecular computing. A solid understanding of principles for design and analysis of algorithms. Some assignments will involve use and extension of software tools, and others will involve written studies of algorithms and their analysis.
MATH 561 | MATHEMATICAL BIOLOGY
Mathematical models for disease spread in populations. Within-host infectious disease dynamics. Models of the immune system and immune cells.
MATH 612D | TOPICS IN MATHEMATICAL BIOLOGY – MATHEMATICS OF INFECTIOUS DISEASES AND IMMUNOLOGY
MEDG 505 | GENOME ANALYSIS
Investigation of genetic information as it is organized within genomes, genetic and physical map construction, sequencing technologies, gene identification, database accessing and integration, functional organization of genomes from contemporary, historic and evolutionary perspectives.
STAT 890 | STATISTICS SELECTED TOPICS – BIOMETRICAL GENETICS
PATH 531/MEDG 521 | MOLECULAR AND CELL BIOLOGY OF CANCER
This course focuses on molecular and cell biology of cancer and consists of a series of lectures reviews combined with discussions and presentations by students on the topics selected by the instructors. Emphasis will be on students’ presentations and discussion.
**This is not an exhaustive list of electives – more are being developed every term and will be available to students when they register. Students are highly encouraged to check out courses listed under SFU and UBC, or talk to professors for recommendations.