Breadcrumbs
Computational Biology in Molecular Genetics (CBMG) Ph.D. Track
Data and technology increasingly drive molecular genetics, and computational biology plays a critical role in these advances. Computational biologists use physics, math, or computer science methods to model biological processes or analyze genomic data, for example. The availability and continuing generation of large-scale datasets and data analysis have created a high demand for researchers with advanced computational skills and a strong grasp of molecular biology.
The CBMG track aims to provide students with an immersive computational biology education. Students are admitted to the Molecular Genetics Ph.D. program and are provided opportunities and courses specific to their discipline to maximize their training potential.
CBMG Co-ordinators:
Director: Dr. Gary Bader, Rm 602, Donnelly Centre
Associate Director: Professor Hannes Rӧst, Rm 604, Donnelly Centre
CBMG Curriculum
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Guided reading: During the summer before the official start of graduate studies, we may provide you with essential reading and study material to complement your undergraduate education as needed.
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When possible, summer placement will facilitate obtaining a paid internship to enable you to obtain hands-on computational or wet-lab experience in Molecular Genetics.
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Rotations: In the fall of the 1st year, you'll take three five-week rotations before joining your thesis lab.
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Genetics, Genomics, and Proteomics: In the fall of the 1st year, we will teach you about diverse current research topics relevant to computational biology (Professors Howard Lipshitz, Tim Hughes, and Anne-Claude Gingras) as part of our Ph.D. Core Curriculum.
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Graduate Computational Biology: In the winter of the 1st year, you will take intensive hands-on courses in computational biology, Foundational Computational Biology I and II (Professors Fritz Roth and Kieran Campbell) (Foundational Computational Biology I is a part of MMG1344H and Foundational Computational Biology II is a part of MMG1345H under Topic Courses).
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Thesis topic: You may choose any topic within the many fields of study represented in the department. Most labs rely on genomic and computational technologies in some way, and for many, it is their primary focus.
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Socializing: Annual retreats and other social & scientific events to help you meet other Molecular Genetics students at all stages of their PhDs.
Admissions Process*
Given the more specific curriculum, CBMG students may only join the Molecular Genetics program for September entry (not January). All successful CBMG applicants will be admitted directly into the Ph.D. Program. Admissions require:
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A Bachelor’s degree in life sciences or quantitative disciplines (physics, math/stats, computer science, chemistry or engineering).
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An undergraduate average of A- or higher (or equivalent).
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Evidence of comfort and ease with computer programming, e.g. academic excellence in multiple computer courses, computational research, programming through employment or extracurricular activities.
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Academic excellence in two or more quantitative subjects: calculus, linear algebra,
probability/statistics or other math or quantitative courses. -
Research experience outside the classroom — wet or dry, biological or non-biological.This includes summer studentships, a lab job that involves working on scientific problems and most fourth-year honours projects.
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A completed online application form for the "Genome Biology and Bioinformatics" collaborative specialization, indicating "CBMG" in the applicant checklist and in the letter of intent.
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At least two letters of reference.
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A letter of intent - be sure to explain your interest in the CBMG Ph.D. track.
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A successful interview.
* Please note CBMG requirements are in addition to, and not in place of the standard Molecular Genetics Graduate Academic Requirements. See the Graduate Admissions for full details on deadlines and admission procedures.
*International applicants may need to submit additional materials in their application package. See International Students for details.
We provide a welcoming environment for students and support them with the tools and mentorship needed to succeed in fast-paced, cutting-edge interdisciplinary fields.