Note: 大发彩票平台鈥檚 new Course Catalogue will replace the eCalendar. The Course Catalogue is expected to go live the week of April 22nd. When the new site is published, "mcgill.ca/study" will be redirected to the new Course Catalogue website.
Course information on this site is not reflective of offerings for the 2025鈥�2026 academic year. Some irregularities may occur as we move operations to the incoming Course Catalogue.
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 2024
Instructors: Cook, Erik; Sladek, Robert; Reynaud, Alexandre; Langlais, David; Li, Yue; Taliun, Daniel (Fall)
Prerequisite(s): BIOL 200 or BIOL 201; COMP 206, COMP 250, MATH 314; MATH 223 or MATH 236; MATH 323 or MATH 324
Restriction(s): Priority given to students enrolled in the ad hoc Quantitative Life Sciences Ph.D. program.
No credit will be given for this course unless both QLSC 600D1 and QLSC 600D2 are successfully completed in consecutive terms.
Students must register for both QLSC 600D1 and QLSC 600D2
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 2025
Instructors: Cook, Erik; Shapiro, Jesse; Guichard, Frederic; Humphries, Tony; Nadon, Robert; Vogel, Jacalyn; Leung, Brian; Najafabadi, Hamed; Kleinman, Claudia; Poline, Jean-Baptiste (Winter)
Prerequisite(s): BIOL 200 or BIOL 201; COMP 206, COMP 250, MATH 314; MATH 223 or MATH 236; MATH 323 or MATH 324
Restriction(s): Priority given to students enrolled in the ad hoc Quantitative Life Sciences Ph.D. program.
Prerequisite: QLSC 600D1
No credit will be given for this course unless both QLSC 600D1 and QLSC 600D2 are successfully completed in consecutive terms.
QLSC : QLS Monthly Seminar Series and Journal Club.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : See QLSC 601D1 for description.
Terms: Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : QLS Monthly Seminar Series and Journal Club.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : See QLSC 602D1 for description.
Terms: Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : QLS Monthly Seminar Series and Journal Club.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : See QLSC 603D1 for description.
Terms: Winter 2025
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 : 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 2024, Winter 2025
Instructors: Greenwood, Celia (Fall) Greenwood, Celia (Winter)
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.
Quantitative
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 2025
Instructors: Beaudet, Daniel (Winter)
Prerequisite: Permission of instructor.
(3-1-5)
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 2024
Instructors: Funnell, Robert (Fall)
(3-0-6)
Prerequisite: Differential equations (MATH 271 or equivalent) or permission of instructor
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 2024
Instructors: Kearney, Robert E (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
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: Winter 2025
Instructors: Blum, Amy; Gehring, Kalle; Mittermaier, Anthony; Strauss, MIke (Winter)
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 2024
Instructors: Thibodeaux, Christopher; Mittermaier, Anthony; Kostikov, Alexey (Fall)
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 2024, Winter 2025
Instructors: Pr茅mont-Schwarz, Isabeau; Rabbany, Reihaneh (Fall) Li, Yue (Winter)
Prerequisite(s): MATH 323 or ECSE 205, COMP 202, MATH 133, MATH 222 (or their equivalents).
Restriction(s): Not open to students who have taken or are taking COMP 451, ECSE 551, MATH 462, or PSYC 560.
Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.
Mathematics & Statistics (Sci) : Conditional probability and Bayes鈥� 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 2024
Instructors: Shen, Hui (Fall)
Physics : An advanced biophysics course, with a special emphasis on stochastic and out of equilibrium physical processes in living matter.
Terms: Winter 2025
Instructors: Wiseman, Paul (Winter)
Physics : Scattering and structure factors. Review of thermodynamics and statistical mechanics; correlation functions (static); mean field theory; critical phenomena; broken symmetry; fluctuations, roughening.
Terms: Winter 2025
Instructors: Reisner, Walter (Winter)
Fall
3 hours lectures
Restriction: U3 Honours students, graduate students, or permission of the instructor
QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Life Sciences
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 2025
Instructors: Denis, Maxime; Schmeing, Martin; Trempe, Jean-Francois; Dejgaard, Kurt; Corbeil, Christopher; Munter, Lisa (Winter)
Winter
Prerequisite: BIOC 450 or equivalent, or permission of instructor.
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: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 2024
Instructors: Chang, Thomas Ming Swi; Shum-Tim, Dominique; Prakash, Satya; Hoesli, Corinne; Chen, Guojun (Fall)
Fall
Prerequisite (Undergraduate): permission of instructors.
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 2024
Instructors: Sharif Naeini, Reza; Ragsdale, David S; Shrier, Alvin; Hanrahan, John W; Seguela, Philippe; Bowie, Derek (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 : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Quantitative
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 2024
Instructors: Dupuis, Jos茅e (Fall)
Prerequisites: Permission of instructor. Undergraduate course in mathematical statistics at level of MATH 324.
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: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 2024, Winter 2025
Instructors: Pr茅mont-Schwarz, Isabeau; Rabbany, Reihaneh (Fall) Li, Yue (Winter)
Prerequisite(s): MATH 323 or ECSE 205, COMP 202, MATH 133, MATH 222 (or their equivalents).
Restriction(s): Not open to students who have taken or are taking COMP 451, ECSE 551, MATH 462, or PSYC 560.
Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.
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 2024
Instructors: Blanchette, Mathieu (Fall)
4 hours
Prerequisites: COMP 251, and MATH 323 or MATH 203 or BIOL 309
Restriction: Not open to students who have taken or are taking 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.
Computer Science (Sci) : Topics in applied computer science.
Terms: Fall 2024, Winter 2025
Instructors: Bzdok, Danilo; Waldispuhl, J茅r么me (Fall) Farnadi, Golnoosh; Adelani, David Ifeoluwa (Winter)
3 hours
Prerequisite: Permission of instructor.
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: Fall 2024
Instructors: Greenwood, Celia; Nadon, Robert; Kleinman, Claudia; Manousaki, Despoina (Fall)
Prerequisite(s): A course introducing basic statistics or equivalent knowledge. Registration is by permission of the course coordinator.
Mathematics & Statistics (Sci) : Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, log-linear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.
Terms: Winter 2025
Instructors: Steele, Russell (Winter)
Mathematics & Statistics (Sci) : Multivariate normal and chi-squared distributions; quadratic forms. Multiple linear regression estimators and their properties. General linear hypothesis tests. Prediction and confidence intervals. Asymptotic properties of least squares estimators. Weighted least squares. Variable selection and regularization. Selected advanced topics in regression. Applications to experimental and observational data.
Terms: Fall 2024
Instructors: Dagdoug, Mehdi (Fall)
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 2024
Instructors: Yang, Archer Yi (Fall)
Mathematics & Statistics (Sci) : Conditional probability and Bayes鈥� 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 2024
Instructors: Shen, Hui (Fall)
QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Life Sciences
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 2024
Instructors: McCaffrey, Luke; Muller, William Joseph; Gallouzi, Imed Eddine; Siegel, Peter; Huang, Sidong; Walsh, Logan; Kazak, Lawrence; Pastor, William (Fall)
Fall
Prerequisites: BIOC 454 and permission of instructor.
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: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
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 2025
Instructors: Radzioch, Danuta; Gregorieff, Alex; Cournoyer, Denis; Schurr, Erwin; Engert, Jamie; Bailey, Swneke; Przybyl, Joanna; Cuella Martin, Raquel (Winter)
Offered in conjunction with the Department of Experimental Medicine.
Prerequisite (Graduate): Admission by permission of instructor.
Human Genetics : Principles and concepts of the genetics of human populations.
Terms: Winter 2025
Instructors: Gravel, Simon (Winter)
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 2024
Instructors: Dewar, Ken; Engert, Jamie; Bh茅rer, Claude; Joly, Yann; Majewska, Loydie; Yamanaka, Yojiro; Langlais, David; Walsh, Logan; Farhan, Sali; Cuella Martin, Raquel (Fall)
Restriction: For Department of Human Genetics graduate students.
Pharmacology and Therapeutics : Chemistry, mechanisms of action, and steps in drug discovery and development.
Terms: Fall 2024
Instructors: Munter, Lisa; Sharif Naeini, Reza; Meerovitch, Karen; Berghuis, Albert; Mooser, Vincent (Fall)
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 2024
Instructors: Trempe, Jean-Francois; Castagner, Bastien (Fall)
QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Quantitative
Environmental Biology : Introduction to a broad range of innovative data analysis strategies commonly applied to ecological data. How to apply these strategies. Common 鈥渂est practices鈥� for data management, study design, and graphing techniques.
Terms: Winter 2025
Instructors: Roy, Denis (Winter)
Mathematics & Statistics (Sci) : Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, log-linear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.
Terms: Winter 2025
Instructors: Steele, Russell (Winter)
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: Winter 2025
Instructors: Dagdoug, Mehdi (Winter)
Mathematics & Statistics (Sci) : Multivariate normal and chi-squared distributions; quadratic forms. Multiple linear regression estimators and their properties. General linear hypothesis tests. Prediction and confidence intervals. Asymptotic properties of least squares estimators. Weighted least squares. Variable selection and regularization. Selected advanced topics in regression. Applications to experimental and observational data.
Terms: Fall 2024
Instructors: Dagdoug, Mehdi (Fall)
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 2025
Instructors: Khadra, Anmar (Winter)
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: Winter 2025
Instructors: Paquette, Elliot (Winter)
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 2024
Instructors: Khalili, Abbas (Fall)
Mathematics & Statistics (Sci) : Conditional probability and Bayes鈥� 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 2024
Instructors: Shen, Hui (Fall)
QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Life Sciences
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 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Biology (Sci) : Causes and consequences of biological invasion, as well as risk assessment methods and management strategies for dealing with invasive species.
Terms: Winter 2025
Instructors: Ricciardi, Anthony (Winter)
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: Fall 2024
Instructors: Hendry, Andrew (Fall)
Environment : Causes and consequences of biological invasion, as well as risk assessment methods and management strategies for dealing with invasive species.
Terms: Winter 2025
Instructors: Ricciardi, Anthony (Winter)
QLSC : Directed reading and writing assignments under the guidance of a QLS supervisor. Topics will be chosen to suit individual needs.
Terms: Fall 2024
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
