Doctor of Philosophy (Ph.D.) Quantitative Life Sciences

Offered by: Quantitative Life Sciences     Degree: Doctor of Philosophy

Program Requirements

Revision, April 2019. Start of revision.

Required Courses (6 credits)

  • QLSC 600D1 Foundations of Quantitative Life Sciences (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Provides an overview of important problems in the life sciences and introduces students to the latest computational, mathematical, and statistical approaches involved in their solution. Includes a survey of modern technologies for biological data acquisition and promotes a common language to communicate across the biological, physical, mathematical, and computational sciences. Topics will include bioinformatics and computational genomics, nonlinear dynamics in biological systems, linear and nonlinear models of biological signals, biophysical imaging technology, emergent behaviour in biophysical networks, and ecosystem dynamics and modeling.

    Terms: Fall 2019

    Instructors: Mathieu Blanchette, Celia M T Greenwood, Ken Dewar, Erik Cook, Jacek Majewski, Paul Francois, David Langlais, Simon Gravel (Fall)

  • QLSC 600D2 Foundations of Quantitative Life Sciences (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Provides an overview of important problems in the life sciences and introduces students to the latest computational, mathematical, and statistical approaches involved in their solution. Includes a survey of modern technologies for biological data acquisition and promotes a common language to communicate across the biological, physical, mathematical, and computational sciences. Topics will include bioinformatics and computational genomics, nonlinear dynamics in biological systems, linear and nonlinear models of biological signals, biophysical imaging technology, emergent behaviour in biophysical networks, and ecosystem dynamics and modeling.

    Terms: Winter 2020

    Instructors: Mathieu Blanchette, Frederic Guichard, Bratislav Misic, Anmar Khadra, Judith Mandl (Winter)

  • QLSC 601D1 Quantitative Life Sciences Seminars 1

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : QLS Monthly Seminar Series and Journal Club.

    Terms: Fall 2019

    Instructors: Celia M T Greenwood (Fall)

    • Students must register for both QLSC 601D1 and QLSC 601D2

    • No credit will be given for this course unless both QLSC 601D1 and QLSC 601D2 are successfully completed in consecutive terms

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 601D2 Quantitative Life Sciences Seminars 1

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : See QLSC 601D1 for description.

    Terms: Winter 2020

    Instructors: Celia M T Greenwood (Winter)

    • Prerequisite: QLSC 601D1

    • No credit will be given for this course unless both QLSC 601D1 and QLSC 601D2 are successfully completed in consecutive terms.

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 602D1 Quantitative Life Sciences Seminars 2

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : QLS Monthly Seminar Series and Journal Club.

    Terms: Fall 2019

    Instructors: Celia M T Greenwood (Fall)

    • Students must register for both QLSC 602D1 and QLSC 602D2

    • No credit will be given for this course unless both QLSC 602D1 and QLSC 602D2 are successfully completed in consecutive terms

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 602D2 Quantitative Life Sciences Seminars 2

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : See QLSC 602D1 for description.

    Terms: Winter 2020

    Instructors: Celia M T Greenwood (Winter)

    • Prerequisite: QLSC 602D1

    • No credit will be given for this course unless both QLSC 602D1 and QLSC 602D2 are successfully completed in consecutive terms

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 603D1 Quantitative Life Sciences Seminars 3

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : QLS Monthly Seminar Series and Journal Club.

    Terms: Fall 2019

    Instructors: Celia M T Greenwood (Fall)

    • Students must register for both QLSC 603D1 and QLSC 603D2

    • No credit will be given for this course unless both QLSC 603D1 and QLSC 603D2 are successfully completed in consecutive terms.

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 603D2 Quantitative Life Sciences Seminars 3

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : See QLSC 603D1 for description.

    Terms: Winter 2020

    Instructors: Celia M T Greenwood (Winter)

    • Prerequisite: QLSC 603D1

    • No credit will be given for this course unless both QLSC 603D1 and QLSC 603D2 are successfully completed in consecutive terms

    • Restriction: Restricted to students enrolled in QLS.

  • QLSC 701 Ph.D. Comprehensive Exam

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Compulsory comprehensive examination to evaluate the students' ability to carry out, present, discuss and defend research in their field of interest. The examination must be completed within the first 18 months of enrollment in the program.

    Terms: Fall 2019, Winter 2020

    Instructors: Celia M T Greenwood (Fall) Celia M T Greenwood (Winter)

Complementary Courses

9-11 credits

Students will be required to take one or two courses from each of the Quantitative and Life Science Blocks for a total of three, stream-specific courses.

Biophysics Stream

Quantitative

  • BIEN 530 Imaging and Bioanalytical Instrumentation (3 credits)

    Offered by: Bioengineering (Faculty of Engineering)

    Overview

    BIEN : Microscopy techniques with application to biology and medicine. Practical introduction to optics and microscopy from the standpoint of biomedical research. Discussion of recent literature; hands-on experience. Topics include: optics, contrast techniques, advanced microscopy, and image analysis.

    Terms: Winter 2020

    Instructors: Adam Hendricks (Winter)

    • Prerequisite: Permission of instructor.

    • (3-1-5)

  • BMDE 512 Finite-Element Modelling in Biomedical Engineering (3 credits)

    Offered by: Biomedical Engineering (Faculty of Engineering)

    Overview

    Biomedical Engineering : General principles of quantitative modelling; types of models; principles of the finite-element method, primarily as applied to mechanical systems; introduction to the use of finite-element software; model generation from imaging data; modelling various material types, mainly biological; model validation.

    Terms: Fall 2019

    Instructors: W Robert J Funnell (Fall)

    • (3-0-6)

    • Prerequisite: Differential equations (MATH 271 or equivalent) or permission of instructor

  • BMDE 519 Biomedical Signals and Systems (3 credits)

    Offered by: Biomedical Engineering (Faculty of Engineering)

    Overview

    Biomedical Engineering : An introduction to the theoretical framework, experimental techniques and analysis procedures available for the quantitative analysis of physiological systems and signals. Lectures plus laboratory work using the Biomedical Engineering computer system. Topics include: amplitude and frequency structure of signals, filtering, sampling, correlation functions, time and frequency-domain descriptions of systems.

    Terms: Fall 2019

    Instructors: Robert E Kearney (Fall)

    • (3-0-6)

    • Prerequisites: Satisfactory standing in U3 Honours Physiology; or U3 Major in Physics-Physiology; or U3 Major Physiology-Mathematics; or permission of instructor

  • CHEM 514 Biophysical Chemistry (3 credits)

    Offered by: Chemistry (Faculty of Science)

    Overview

    Chemistry : Physical chemistry concepts needed to understand the function of biological systems at the molecular level, including the structure, stability, transport, and interactions of biological macromolecules.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • CHEM 520 Methods in Chemical Biology (3 credits)

    Offered by: Chemistry (Faculty of Science)

    Overview

    Chemistry : An overview of advanced techniques at the leading edge of Chemical Biology, including some or all of: biological imaging, kinetics of enzyme inhibition, combinatorial synthesis, atomic force microscopy of biological molecules, self assembling biomimetic structures, oligonucleotide therapeutics, biomolecular X-ray crystallography, computational methods, and nuclear magnetic resonance applied to protein interactions.

    Terms: Fall 2019

    Instructors: Anthony Mittermaier, David Bohle, Christopher Thibodeaux, Matthew Harrington (Fall)

  • COMP 551 Applied Machine Learning (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.

    Terms: Fall 2019, Winter 2020

    Instructors: William Hamilton (Fall) Reihaneh Rabbany, Mohsen Ravanbakhsh (Winter)

    • Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent

    • Restriction(s): Not open to students who have taken COMP 598 when topic was "Applied Machine Learning"

    • Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.

  • MATH 682 Statistical Inference (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Administered by: Graduate Studies

    Overview

    Mathematics & Statistics (Sci) : Conditional probability and Bayes’ Theorem, discrete and continuous univariate and multivariate distributions, conditional distributions, moments, independence of random variables. Modes of convergence, weak law of large numbers, central limit theorem. Point and interval estimation. Likelihood inference. Bayesian estimation and inference. Hypothesis testing.

    Terms: Fall 2019

    Instructors: James McVittie, Jacques Claude Hurtubise (Fall)

    • Prerequisite: MATH 141 or equivalent

    • Restrictions: Not open to students who have taken MATH 324, MATH 357, MATH 557. Intended for graduate students working on quantitative research questions related to life sciences who have had differential and integral calculus.

  • PHYS 519 Advanced Biophysics (3 credits)

    Offered by: Physics (Faculty of Science)

    Overview

    Physics : An advanced biophysics course, with a special emphasis on stochastic and out of equilibrium physical processes in living matter.

    Terms: Winter 2020

    Instructors: Paul Francois (Winter)

  • PHYS 559 Advanced Statistical Mechanics (3 credits)

    Offered by: Physics (Faculty of Science)

    Overview

    Physics : Scattering and structure factors. Review of thermodynamics and statistical mechanics; correlation functions (static); mean field theory; critical phenomena; broken symmetry; fluctuations, roughening.

    Terms: Fall 2019

    Instructors: William Coish (Fall)

    • Fall

    • 3 hours lectures

    • Restriction: U3 Honours students, graduate students, or permission of the instructor

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Life Sciences

  • BIOC 605 Protein Biology and Proteomics (3 credits)

    Offered by: Biochemistry (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Biochemistry : Examination of recent developments in protein biology and proteomics analysis. Proteomics, modeling and biophysical approaches to characterize the functional interactions of biological macromolecules; applications to biological problems. Lectures and in-class discussions are supplemented by practical training in proteomics.

    Terms: Winter 2020

    Instructors: Jason Young (Winter)

    • Winter

    • Prerequisite: BIOC 450 or equivalent, or permission of instructor.

  • BIOL 551 Principles of Cellular Control (3 credits)

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : Fundamental principles of cellular control, with cell cycle control as a major theme. Biological and physical concepts are brought to bear on control in healthy cells..

    Terms: Winter 2020

    Instructors: Jacalyn Vogel, Paul Francois, Rodrigo Reyes Lamothe, Stephanie Weber, Arnold Hayer, Abigail Gerhold (Winter)

  • PHGY 518 Artificial Cells (3 credits)

    Offered by: Physiology (Faculty of Science)

    Overview

    Physiology : Physiology, biotechnology, chemistry and biomedical application of artificial cells, blood substitutes, immobilized enzymes, microorganisms and cells, hemoperfusion, artificial kidneys, and drug delivery systems. PHGY 517 and PHGY 518 when taken together, will give a complete picture of this field. However, the student can select one of these.

    Terms: Fall 2019

    Instructors: Thomas Ming Swi Chang, Paul E Barre, Dominique Shum-Tim, Satya Prakash, Corinne Hoesli (Fall)

    • Fall

    • Prerequisite (Undergraduate): permission of instructors.

  • PHGY 520 Ion Channels (3 credits)

    Offered by: Physiology (Faculty of Science)

    Overview

    Physiology : A discussion of the principal theories and interesting new developments in the study of ion channels. Based on a textbook, computer exercises and critical reading and presentation of research papers. Topics include: Properties of voltage-and ligand-gated channels, single channel analysis, structure and function of ion channels.

    Terms: Fall 2019

    Instructors: Reza Sharif Naeini, David S Ragsdale, Line Parent, Alvin Shrier, John W Hanrahan, Philippe Seguela, Derek Bowie (Fall)

    • Winter

    • Offered in even numbered years

    • 1 1/2 hour lecture, 1 1/2 hour seminar

    • Prerequisite: PHGY 311

    • Priority to Graduate and Honours students; others by permission of instructors.

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Computational and Statistical Molecular Biology Stream

Quantitative

  • BIOS 601 Epidemiology: Introduction and Statistical Models (4 credits)

    Offered by: Epidemiology and Biostatistics (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Biostatistics : Examples of applications of statistics and probability in epidemiologic research. Source of epidemiologic data (surveys, experimental and non-experimental studies). Elementary data analysis for single and comparative epidemiologic parameters.

    Terms: Fall 2019

    Instructors: James Anthony Hanley (Fall)

    • Prerequisites: Permission of instructor. Undergraduate course in mathematical statistics at level of MATH 324.

  • BMDE 502 BME Modelling and Identification (3 credits)

    Offered by: Biomedical Engineering (Faculty of Engineering)

    Overview

    Biomedical Engineering : Methodologies in systems or distributed multidimensional processes. System themes include parametric vs. non-parametric system representations; linear/non-linear; noise, transients and time variation; mapping from continuous to discrete models; and relevant identification approaches in continuous and discrete time formulations.

    Terms: Winter 2020

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

    • (3-0-6)

    • Prerequisites: Undergraduate basic statistics and: either BMDE 519, or Signals and Systems (e.g., ECSE 303 & ECSE 304) or equivalent

  • COMP 551 Applied Machine Learning (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.

    Terms: Fall 2019, Winter 2020

    Instructors: William Hamilton (Fall) Reihaneh Rabbany, Mohsen Ravanbakhsh (Winter)

    • Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent

    • Restriction(s): Not open to students who have taken COMP 598 when topic was "Applied Machine Learning"

    • Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.

  • COMP 561 Computational Biology Methods and Research (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Application of computer science techniques to problems arising in biology and medicine, techniques for modeling evolution, aligning molecular sequences, predicting structure of a molecule and other problems from computational biology. An in-depth exploration of key research areas.

    Terms: Fall 2019

    Instructors: Mathieu Blanchette (Fall)

    • 4 hours

    • Prerequisites: COMP 251, and MATH 323 or MATH 203 or BIOL 309

    • Restrictions: Not open to students who have taken COMP 562. Not open to students who are taking or have taken COMP 462.

    • Note: Additional work will consist of assignments and of a substantial final project that will require to put in practice the concepts covered in the course.

  • COMP 598 Topics in Computer Science 1 (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Topics in computer science.

    Terms: Fall 2019, Winter 2020

    Instructors: Yue Li, Derek Nowrouzezahrai (Fall) Muthucumaru Maheswaran (Winter)

    • 3 hours

    • Prerequisite: Permission of instructor.

  • HGEN 677 Statistical Concepts in Genetic and Genomic Analysis (3 credits)

    Offered by: Human Genetics (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Human Genetics : This course will introduce key statistical concepts that motivate and underlie the many statistical analysis methods currently used in analysis of genetic and genomic data. Emphasis will be placed on understanding how these concepts can influence study designs and analysis choices, and when substantial unanticipated biases can occur. Concepts include an understanding of variability and error, bias and its sources, independence, how distributions of variables impact analysis, outliers, covariates, missing data, the goals of data cleaning, multiple testing, and some consideration of clustering and prediction models.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

    • Prerequisite(s): A course introducing basic statistics or equivalent knowledge. Registration is by permission of the course coordinator.

  • MATH 523 Generalized Linear Models (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Modern discrete data analysis. Exponential families, orthogonality, link functions. Inference and model selection using analysis of deviance. Shrinkage (Bayesian, frequentist viewpoints). Smoothing. Residuals. Quasi-likelihood. Contingency tables: logistic regression, log-linear models. Censored data. Applications to current problems in medicine, biological and physical sciences. R software.

    Terms: Winter 2020

    Instructors: Johanna Neslehova (Winter)

    • Winter

    • Prerequisite: MATH 423

    • Restriction: Not open to students who have taken MATH 426

  • MATH 533 Honours Regression and Analysis of Variance (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : This course consists of the lectures of MATH 423 but will be assessed at the 500 level.

    Terms: Fall 2019

    Instructors: Yi Yang (Fall)

    • Prerequisites: MATH 357, MATH 247 or MATH 251.

    • Restriction: Not open to have taken or are taking MATH 423.

    • Note: An additional project or projects assigned by the instructor that require a more detailed treatment of the major results and concepts covered in MATH 423.

  • MATH 680 Computation Intensive Statistics (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Administered by: Graduate Studies

    Overview

    Mathematics & Statistics (Sci) : General introduction to computational methods in statistics; optimization methods; EM algorithm; random number generation and simulations; bootstrap, jackknife, cross-validation, resampling and permutation; Monte Carlo methods: Markov chain Monte Carlo and sequential Monte Carlo; computation in the R language.

    Terms: Fall 2019

    Instructors: Yi Yang (Fall)

  • MATH 682 Statistical Inference (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Administered by: Graduate Studies

    Overview

    Mathematics & Statistics (Sci) : Conditional probability and Bayes’ Theorem, discrete and continuous univariate and multivariate distributions, conditional distributions, moments, independence of random variables. Modes of convergence, weak law of large numbers, central limit theorem. Point and interval estimation. Likelihood inference. Bayesian estimation and inference. Hypothesis testing.

    Terms: Fall 2019

    Instructors: James McVittie, Jacques Claude Hurtubise (Fall)

    • Prerequisite: MATH 141 or equivalent

    • Restrictions: Not open to students who have taken MATH 324, MATH 357, MATH 557. Intended for graduate students working on quantitative research questions related to life sciences who have had differential and integral calculus.

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Life Sciences

  • BIOC 603 Genomics and Gene Expression (3 credits)

    Offered by: Biochemistry (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Biochemistry : Examination of recent developments in analysis of eukaryotic cell genomes and control of gene expression during differentiation and growth control. Molecular genetics; genomics and the bioinformatics of analysis of genomic and functional-genomic data; mechanisms and signal-transduction pathways for regulation of gene expression; applications to human disease with a strong emphasis on cancer.

    Terms: Fall 2019

    Instructors: Luke McCaffrey, William Joseph Muller, Imed Eddine Gallouzi, Peter Siegel, Sidong Huang, Logan Walsh, Lawrence Kazak, William Pastor (Fall)

    • Fall

    • Prerequisites: BIOC 454 and permission of instructor.

  • BIOL 551 Principles of Cellular Control (3 credits)

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : Fundamental principles of cellular control, with cell cycle control as a major theme. Biological and physical concepts are brought to bear on control in healthy cells..

    Terms: Winter 2020

    Instructors: Jacalyn Vogel, Paul Francois, Rodrigo Reyes Lamothe, Stephanie Weber, Arnold Hayer, Abigail Gerhold (Winter)

  • EXMD 602 Techniques in Molecular Genetics (3 credits)

    Offered by: Medicine (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Experimental Medicine : Precise description of available methods in molecular genetics, and rationales for choosing particular techniques to answer questions posed in research proposals for targeting genes in the mammalian genome. Emphasis placed on analysis of regulation of gene expression and mapping, strategies for gene cloning. Course divided between lectures and student seminars.

    Terms: Winter 2020

    Instructors: Danuta Radzioch (Winter)

    • Offered in conjunction with the Department of Experimental Medicine.

    • Prerequisite (Graduate): Admission by permission of instructor.

  • HGEN 661 Population Genetics (3 credits)

    Offered by: Human Genetics (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Human Genetics : Principles and concepts of the genetics of human populations.

    Terms: Winter 2020

    Instructors: Simon Gravel (Winter)

  • HGEN 692 Human Genetics (3 credits)

    Offered by: Human Genetics (Faculty of Medicine)

    Administered by: Graduate Studies

    Overview

    Human Genetics : This course will emphasize the principles and practice of human genetics, including an overview of the fundamental aspects of human genetics pertaining to chromosomes and mutations, population, cancer and development genetics, the inheritance of complex traits.

    Terms: Fall 2019

    Instructors: Ken Dewar, Andrea Miller-Nesbitt, Carl Ernst, Aimee Ryan, James Engert, Yann Joly, Josee Lavoie, Yojiro Yamanaka, Claudia Kleinman, Vahab Soleimani (Fall)

    • Restriction: For Department of Human Genetics graduate students.

  • PHAR 503 Drug Discovery and Development 1 (3 credits)

    Offered by: Pharmacology and Therapeutics (Faculty of Science)

    Overview

    Pharmacology and Therapeutics : Chemistry, mechanisms of action, and steps in drug discovery and development.

    Terms: Fall 2019

    Instructors: Lisa Munter, Jean Francois Trempe, Karen Meerovitch (Fall)

  • PHAR 505 Structural Pharmacology (3 credits)

    Offered by: Pharmacology and Therapeutics (Faculty of Science)

    Overview

    Pharmacology and Therapeutics : The course will cover approaches widely used in the pharmaceuticals industry, such as drug target selection, structure determination and medicinal chemistry. The basics of structural biology will be taught in a very visual and interactive manner, with an emphasis on drug:target interactions and chemical principles relevant to drug design. By the end of the course, the students will become familiar with the structure-based drug discovery process and principles of molecular pharmacology.

    Terms: Fall 2019

    Instructors: Jean Francois Trempe, Bastien Castagner (Fall)

    • Prerequisite(s): PHAR 301, BIOC 311 or with permission of instructor

    • Restriction(s): Not open to students who have taken or are taking PHAR 503.

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Ecosystems Stream

Quantitative

  • ENVB 506 Quantitative Methods: Ecology (3 credits)

    Offered by: Natural Resource Sciences (Agricultural & Environmental Sciences)

    Overview

    Environmental Biology : The process of formulating models of natural systems and confronting them with data, along with the necessary statistical computing skills. Emphasis on hands-on experience with current approaches for building, fitting, and comparing models.

    Terms: Winter 2020

    Instructors: Denis Roy (Winter)

    • Winter

    • Prerequisites: AEMA 310 and ENVB 305; or graduate student status; or permission of instructor

    • Restriction: Not open to students who have taken AEMA 306 or AEMA 406.

  • MATH 523 Generalized Linear Models (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Modern discrete data analysis. Exponential families, orthogonality, link functions. Inference and model selection using analysis of deviance. Shrinkage (Bayesian, frequentist viewpoints). Smoothing. Residuals. Quasi-likelihood. Contingency tables: logistic regression, log-linear models. Censored data. Applications to current problems in medicine, biological and physical sciences. R software.

    Terms: Winter 2020

    Instructors: Johanna Neslehova (Winter)

    • Winter

    • Prerequisite: MATH 423

    • Restriction: Not open to students who have taken MATH 426

  • MATH 525 Sampling Theory and Applications (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Simple random sampling, domains, ratio and regression estimators, superpopulation models, stratified sampling, optimal stratification, cluster sampling, sampling with unequal probabilities, multistage sampling, complex surveys, nonresponse.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

    • Prerequisite: MATH 324 or equivalent

    • Restriction: Not open to students who have taken MATH 425

  • MATH 533 Honours Regression and Analysis of Variance (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : This course consists of the lectures of MATH 423 but will be assessed at the 500 level.

    Terms: Fall 2019

    Instructors: Yi Yang (Fall)

    • Prerequisites: MATH 357, MATH 247 or MATH 251.

    • Restriction: Not open to have taken or are taking MATH 423.

    • Note: An additional project or projects assigned by the instructor that require a more detailed treatment of the major results and concepts covered in MATH 423.

  • MATH 537 Honours Mathematical Models in Biology (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : The formulation and treatment of realistic mathematical models describing biological phenomena through such qualitative and quantitative mathematical techniques as local and global stability theory, bifurcation analysis, phase plane analysis, and numerical simulation. Concrete and detailed examples will be drawn from molecular, cellular and population biology and mammalian physiology.

    Terms: Winter 2020

    Instructors: Anmar Khadra (Winter)

  • MATH 547 Stochastic Processes (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Conditional probability and conditional expectation, generating functions. Branching processes and random walk. Markov chains:transition matrices, classification of states, ergodic theorem, examples. Birth and death processes, queueing theory.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • MATH 556 Mathematical Statistics 1 (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Distribution theory, stochastic models and multivariate transformations. Families of distributions including location-scale families, exponential families, convolution families, exponential dispersion models and hierarchical models. Concentration inequalities. Characteristic functions. Convergence in probability, almost surely, in Lp and in distribution. Laws of large numbers and Central Limit Theorem. Stochastic simulation.

    Terms: Fall 2019

    Instructors: David Stephens (Fall)

    • Fall

    • Prerequisite: MATH 357 or equivalent

  • MATH 682 Statistical Inference (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Administered by: Graduate Studies

    Overview

    Mathematics & Statistics (Sci) : Conditional probability and Bayes’ Theorem, discrete and continuous univariate and multivariate distributions, conditional distributions, moments, independence of random variables. Modes of convergence, weak law of large numbers, central limit theorem. Point and interval estimation. Likelihood inference. Bayesian estimation and inference. Hypothesis testing.

    Terms: Fall 2019

    Instructors: James McVittie, Jacques Claude Hurtubise (Fall)

    • Prerequisite: MATH 141 or equivalent

    • Restrictions: Not open to students who have taken MATH 324, MATH 357, MATH 557. Intended for graduate students working on quantitative research questions related to life sciences who have had differential and integral calculus.

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Life Sciences

  • BIOL 509 Methods in Molecular Ecology (3 credits)

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : An overview of the molecular genetic tools used to investigate ecological and evolutionary processes in natural populations. The use of molecular tools in studies of population structure, parentage, kinship, species boundaries, phylogenetics. Special topics include conservation genetics, population genetics, and ecological genomics.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

    • Restriction (s): BIOL 301, BIOL 304 and BIOL 308 or permission of instructor.

    • Intended for both upper level undergraduates with knowledge of ecology, evolution, and genetics.

    • Intended for graduate students interested in applying molecular tools in ecology, evolution, and environmental sciences.

  • BIOL 510 Advances in Community Ecology (3 credits)

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : The origin, maintenance and roles of biological diversity within ecological communities.

    Terms: Fall 2019

    Instructors: Andrew Gonzalez (Fall)

    • Fall

    • 3 hours lecture/seminar

    • Prerequisites: BIOL 308 or GEOG 350 or permission of instructor.

  • BIOL 540 Ecology of Species Invasions (3 credits) *

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : Causes and consequences of biological invasion, as well as risk assessment methods and management strategies for dealing with invasive species.

    Terms: Winter 2020

    Instructors: Anthony Ricciardi (Winter)

    • Winter

    • 3 hours lecture

    • Prerequisite(s): BIOL 215 (or ENVR 200 plus ENVR 202), and at least one 300- or 400-level course in ecology, evolution, or conservation biology.

    • Restriction: Not open to U1 or U2 students

    • Restriction: Not open to students who are taking or have taken ENVR 540.

  • BIOL 594 Advanced Evolutionary Ecology (3 credits)

    Offered by: Biology (Faculty of Science)

    Overview

    Biology (Sci) : Evolutionary ecology is the study of evolutionary change in natural populations. General predictive approaches in evolutionary ecology, including population genetics, quantitative genetics, optimality, and game theory will be examined. Emphasis will be placed on the mathematical underpinnings of each approach, particularly as they relate to classic and contemporary problems.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • ENVR 540 Ecology of Species Invasions (3 credits) *

    Offered by: McGill School of Environment (School of Environment)

    Administered by: Faculty of Science

    Overview

    Environment : Causes and consequences of biological invasion, as well as risk assessment methods and management strategies for dealing with invasive species.

    Terms: Winter 2020

    Instructors: Anthony Ricciardi (Winter)

    • 3 hours lecture

    • Prerequisite: BIOL 215 (or ENVR 200 plus ENVR 202), and at least one 300- or 400-level course in ecology, evolution, or conservation biology.

    • Restrictions: Not open to U1 or U2 students. Not open to students who are taking or have taken BIOL 540.

  • QLSC 611 Directed Readings (3 credits)

    Offered by: Quantitative Life Sciences (Interfaculty Studies)

    Administered by: Graduate Studies

    Overview

    QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.

    Terms: Fall 2019

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

* Students either choose BIOL 540 or ENVR 540 but not both.

Revision, April 2019. End of revision.
Interfaculty Studies—2019-2020 (last updated Mar. 27, 2019) (disclaimer)