Graduate Courses

How to Enrol

Graduate students in the Department of Ecology and Evolutionary Biology can access the Student Web Service (SWS) to change personal information (addresses and telephone numbers), view their academic record and current courses and to enrol in, request or drop courses. Note: you can only use SWS (e.g. ACORN) to enrol in courses if you do so by the deadlines listed below. For complete information on using the SWS please view Instructions for Course Enrolment using ACORN. It is your responsibility to ensure that course enrolment is accurate on SWS.

Graduate Student Run Non-Credit Workshops & Courses

The Department recognizes that individual graduate students have developed considerable expertise in many important research tools and concepts and it wishes to encourage such students to share their expertise with other graduate students. Accordingly, as a pilot project the Department will offer some financial support to students or student groups who volunteer to offer not-for-credit workshops or short not-for-credit courses that meet significant demand for skills or knowledge beyond what is commonly generated within study groups. To access departmental support, potential graduate student instructors or organizing groups should submit to the Grad Office a proposal that: 1) describes the need and the project designed to fill it, including giving it a descriptive name; 2) assesses the demand within the department and specifies a measure of success for the project (e.g. the number of students completing the training); 3) optionally describes a small budget (maximum $500) for supplies, course resources, and/or a small honorarium for the chief instructor; 4) provides a list of fewer than 10 questions that would constitute a suitable evaluation of the quality or success of the project in meeting student needs. The Grad Office will respond with a decision about the level of support, which may be contingent on the project meeting its specified index of success. At the end of the project we will also provide a letter of documentation to any student who leads a successful one.  

Graduate Courses Offered in 2018-2019

You may sign up for a course(s) beginning August 1, 2018 (but not before that date) on Student Web Services with ACORN (please see the link above to the instructions) or the email you received from Kitty in late July about course registration, ACORN, etc.  Please also note that, for some courses, you may sign up for a course but you will not be registered in the course until permission has been granted by the course instructor (this is normal procedure for many courses).

Deadlines: Please make sure that you have signed up for your course(s) by the following deadlines: for Fall or full-year courses, the deadline to enrol is *September 24, 2018* and the deadline to enrol in January session courses is *January 21, 2019*.

New students should consult their supervisor(s) and fellow students about the courses
most appropriate to meet their needs. 

The coursework requirements for the M.Sc. and Ph.D. programs are provided in the EEB Graduate Handbook: 

Note: Section Code: usually F, S or Y. This indicates whether the course is offered in the fall session (F), the winter session, i.e., second term (S) or over both (Y).

In Sept. a PDF version of Graduate Courses offered by EEB in 2018-2019 will be available here (note: all of the information in this document is provided below)

***Note: see below for courses offered by other departments/groups that will be of interest to some EEB graduate students***

Graduate courses and seminars officially begin in the week of September 11th for September session courses (F) and January 8th for January session courses (S); however,  joint grad/undergraduate courses will begin before then and some of the EEB graduate courses will not begin until the second week of classes. Courses at UTM and UTSC may begin before the listed dates— please see the course descriptions below for information on the first class.

EEB Graduate Courses Offered in Fall 2018:

EEB 1310H F Philosophy & Methods [H. Rodd (team leader), Njal Rollinson, and guests] Thursday afternoons at St.G. (12:30-3:30 on the days when there is not a faculty position seminar; 2:00-5:00 on the days when there is a faculty position seminar).  The first class will be Sept. 13. This course will involve a combination of (i) student-led discussions (some topics are listed below), (ii) lectures/discussions led by faculty designed to cover general and sometimes controversial scientific issues frequently confronted in both ecological and evolutionary studies, and (iii) short presentations by students introducing the background and context for their proposed research. This course is recommended for students just starting an MSc or PhD, and for students in the second year of their PhD who have begun to nail down a thesis topic. It is intended to be a forum for students to enhance their current skills and understanding of how todo ‘good’ science and to discuss some issues that they will encounter as scientists. The class will read papers on and discuss topics that will include:human subjectivity and biases, and their roles in science; some semi-philosophical controversies about approaches to science and research tactics; some common and important pitfalls/errors in experimental design and statistical analysis(note: a strong background in statistics is not necessary for the course, but at least one undergraduate course in statistics is recommended); brief overviews of some new statistical approaches; and a variety other issues that are important to researchers (e.g. ethics). Faculty from the department and other guests will give brief, overview lectures to provide a bit of background on some of the topics (e.g. power analysis). The major assignment for the course is an essay that aims to facilitate students’ progress in thinking broadly about their thesis research, before they write their thesis proposal; to this we ask the students to put their research questions in the context of their general field (ecology or evolution)—both historically and with respect to the exciting questions currently being asked in their discipline.


U/G joint course*: EEB1328H1F Physiological Ecology [R. Sage] Fridays 10-12 and 1300-1500.  Contact Dr. Sage for information on the timing of the first class; it may be as early as Sept. 7.  An advanced treatment of the physiological mechanisms controlling plant and animal distribution and ecological success.Topics of focus include photosynthesis and resource balance, water and nutrient relations, temperature effects, and adaptations to abiotic stress. A fee of approximately $15 may be charged for field trip transportation.


U/G joint course*: EEB1421H Ecology and Evolution of Plant-Animal Interactions [M. Frederickson] Tues and Thurs 1300-1400 and Friday1300-1500.  Contact Dr. Frederickson for information on the timing of the first class; it may be as early as Sept. 6.  Major concepts in ecology and evolution from the perspective of plant-animal interactions. The richness of interactions between plants and animals is explored including antagonistic interactions(e.g., herbivory, carnivorous plants), mutualistic interactions (e.g.,pollination, seed dispersal, ant-plant associations), and interactions involving multiple species across trophic levels.


U/G joint*: 1451HF  Special Topics in Ecology and Evolution: Modelling in Ecology and Evolutionary (undergrad course code: EEB430) [Gilbert and Krkosek] Mon and Wed 10-11 in UC52 and Wed 1500-1700 in TBA.  Contact Dr. Gilbert for information on the timing of the first class (it will probably be in the 2nd week ofSept.); note: Drs. Gilbert and Krkosek are aware of the conflict between the first lab and the TA training session on Sept. 12.  Study of ecology and evolution uses models to explain biological phenomena including the maintenance of biodiversity, population growth, competition, eco-evolutionary dynamics, trait and molecular evolution, epidemiology, spatial ecology, phylogeny and extinction. Students will learn to develop, assess and apply analytical, simulation and statistical models for analysis and data interpretation.Note that an undergrad course in calculus and an undergrad course in ecology or evolution are recommended.


U/G joint*: EEB 1460 HF  Molecular Evolution and Genomics (EEB460) [Irwin and Chang] St.G. Lecture: Wednesday 10-11 am, Fri 10-12 (both in AB107). Contact Dr. Irwin for information on the timing of the first class; it may be as early as Sept. 7.  Processes of evolution at the molecular level, and the analysis of molecular data. Gene structure, neutrality, nucleotide sequence evolution, sequence evolution, sequence alignment, phylogeny construction, gene families, transposition.


U/G joint course*: EEB 1420H F (Fall) Special topics in Ecology--Models in Ecology and Conservation (undergrad course code BIOD59) [P. Molnar at UTSc, lectures may be available by videoconferencing] Lecture Tuesdays 12:00-14:00 in BV 355; Tutorials on Thursdays from 13:00-15:00 in BV 471. The first class will be Tues. Sept. 4. Modelling is a critical tool used to address urgent resource management questions in ecology, epidemiology and conservation. This practical introduction includes approaches for modelling individuals, populations, species interactions, and communities. Applications include population viability assessments, disease eradication and climate change mitigation. Discussion-based tutorials will supplement lectures to provide hands-on modelling experience on a variety of ecological, epidemiological, and conservation questions.

U/G joint course*: EEB 1443H F Phylogenetic Principles  [S. Stefanovic] (2 hours, twice a week at UTM, Tues and Thurs from 10-12 (tentatively in IB-340))  Funding for the UTM shuttle bus may be available.  First class will be Thurs.Sept. 6.  Lectures will provide an in-depth coverage of modern methods of phylogenetic reconstruction including molecular systematics based on DNA sequences. The principles and philosophy of classification will be taught with an emphasis on ’tree-thinking’, one of the most important conceptual advances in evolutionary biology. Tutorials will focus on recent developments in the study of evolutionary patterns while gaining proficiency in reading, presenting, and critiquing scientific papers.  *Shuttle Bus (Hart House to/from UTM) stop is right in front of this building (IB).

EEB Graduate Courses Offered in Winter 2019: 

EEB 1320H Core Ecology Course [B. Gilbert and M.Krkosek] Tues from 1-4pm in ESC3044 (Jan 8 only) remaining classes will be in ESC1014The Core Ecology course will provide students with a foundation of the conceptual basis of ecology through lectures, readings, and discussions. The structure of course content will follow the four levels of ecological organization: (1) individuals, (2) populations, (3) communities, and (4)ecosystems. By exploring the theoretical foundations of ecology and the linkages among ecological theories, students will gain a broad perspective of the historical development and current trends in ecology, particularly at the population and community levels. 


Regarding EEB Core Ecology andCore Evolution Courses: These courses will cover the basics in the field(ecology or evolution).  These courses should be useful preparation for PhD students for the Question Bank part of the Appraisal Exam.  If you have taken 2+ 3rdor 4th year undergrad courses in a field (ecology or evolution), the course for that field may not be especially useful for providing you with background knowledge—discuss with your supervisor and supervisory committee whether you should take either of these courses.  On the other hand, if you have no or very little background in the field, you may need to sit in on undergrad lectures or do outside reading before you take one of these courses; however, if you have taken other courses in E&E (e.g., no background in ecology but you have taken courses in evolution, math or biological theory), ask the EEB graduate office and your supervisor and committee whether you will be equipped to take one of these courses.



EEB1210H S (1/4 course=6week module) Advanced Statistics [M-J.Fortin]

EEB1210 (Advanced stats) will be Tuesdays 9am-12pm starting Feb 26 and ending April 2nd in ESC1014 


Biologists need to use statistical methods to test their hypotheses. Given the increasing complexity of experiments carried out by biologists, they need however to understand the limitations of these statistics and how to select the appropriate statistics for their needs and how to interpret them properly both statistically and biologically. The goal of this advanced course in statistics is to teach biologists how to choose and use statistics so that they can address relevant biological questions and test them with the appropriate methods. Specifically, an overview of advanced notions about regression and ANOVA will be presented. To do so, a combination of lectures and computer laboratory sessions will be used.  The syllabus is posted here. 


EEB1250H Spatial Statistics (1/4 course (6 weeks)) [M.-J. Fortin]. The syllabus is posted here.  

EEB1250 (Spatial stats) will be Thursdays 9am-12pm starting January 24th and ending March 7th in ESC3087. 

EEB1361: Special Topics in Behaviour: Group Dynamics [J. Levine - UTM]:


Behaviour in groups occurs in phyla from unicellular aggregates to human societies. The formation of groups can protect its members from predation, ensure sustainability of the group when resources are scarce and protect its members from disease. Moreover, when individuals join, decisions can be made as a collective with the collective taking precedence over the individual. Ecologists and ethologists of the early- and mid-twentieth century observed these phenomena in animals in nature and performed laboratory experiments to document these behaviours. Current work continues in this tradition and relies on more recent developments in data analyses, such as agent-based modeling and network theory. In this course, students will read relevant literature on group dynamics. Assigned readings will include primary literature and books by W.C. Allee, Niko Tinbergen and Jens Krause. Grades will be determined by participation, presentations and writing assignments. Each student will be expected to do the relevant readings each week and participate in group discussions. The class will meet once a week at the UTM campus. Day/time will be determined later based on preferences of the class and instructor.


May be offered in 2018-2019 (see EEB grad course webpage for updates in late fall 2018): EEB 1360H S Special Topics in Behaviour: Integrative Biology of Behaviour with a focus on behaviour genetics, genomics and neurobiology [Mark Fitzpatrick (EEB), Tod Thiele (CSB, Neuroscience), and Blake Richards (CSB, Neuroscience), with guest lectures by Nick Mandrak (EEB) and Patrick McGowan (CSB) and perhaps TBA] at UTSc


U/G joint course*: EEB1340H1-S Comparative Plant Morphology[T. Sage] Mon and Wed 1300-1400 and Thurs 900-1200.  Contact Dr. Sage for information on the timing of the first class.The origin of land plants and the subsequent diversification of land plant vegetative and reproductive form and function. Discussions synthesize morphological and anatomical knowledge from living organisms and fossil records with cellular, physiological, and molecular information on the developmental"tool kit" of land plants and their ancestors throughout geological time. Topics address the evolution of vegetative and reproductive meristems; stem, leaf, and root architecture; vascular tissue; the ovule habit; fertilization processes; and pollination biology. (Lab Materials Fee: $25; Lab Manual Fee:$25)

Not offered in the 2019 winter term, but with sufficient demand, might be offered in May/June 2019: U/G joint*: EEB1440: Special topics in Evolution: Genomics (undergrad course code BIO458H5S) [R. Ness] at UTM.  Pre-requisite: a working knowledge of Python. The genome has been referred to as the blueprint of life and consists of the full complement of genes and genetic material carried by an organism. The ongoing revolution in DNA sequencing allows biologists to observe the variety of genetic and genomic structures that underpin the diversity of life. In addition, applications of genomic technologies have facilitated new fields of research such as personalized medicine and evolutionary genomics. The lectures will focus on the diversity of genomic structures, their functions and evolutionary origins. The course also has computer-based practicals that provide hands-on training with cutting-edge bioinformatic tools for analysis of genome-scale datasets and next generation sequencing data

U/G joint course*: EEB1459H (EEB459 S) Theoretical Population Genetics Winter 2019 [Agrawal] Mon 10-12 in TBA, Wed 11-12 in ESC3087.  Contact Dr. Agrawal for information on the timing of the first class and/or check theEEB grad course webpage for updates.  A focus on theoretical population genetics, using mathematical models to understand how different evolutionary forces drive allele frequency change.Students learn how to mathematically derive classic results in population genetics. Topics include drift, coalescence, the relationship between population and quantitative genetics, selection in finite populations, and mutation load. Offered in alternate years. Recommended Preparation: an intro course to genetics and a solid understanding of basic algebra and calculus.


U/G joint*: EEB1462S  Phylogenetic Systematics [Kvistand Claramunt] Tues 10-12 BL327 and Wed 2:00-5:00 in TBA.  Contact Dr. Kvist for information on the timing of the first class and/or check the EEB grad course webpage for updates.  The Tree of Life metaphor for evolutionary relationships among species, phylogenies, is now fundamental in biology.Phylogenetic trees are now used both in species classification and to investigate myriad biological hypotheses about the evolutionary process and applied problems like virus and cancer epidemiology. This course will train students in the concepts and core methods of phylogenetic tree inference, including parsimony, likelihood, and Bayesian techniques. Students will gain bioinformatics skills with application to DNA sequence analysis and phylogenetic tree inference. Through a combination of lectures, discussion, and computer labs, students will master theory and practice of phylogenetic tree construction and inference. 


* Joint undergrad/grad courses will normally constitute only a minor component of the required credits for a graduate degree

EEB courses that will be offered in the future:

EEB1350 Core evolution course [Agrawal] is taught in alternate years and will be taught in 2019-2020


Regarding EEB Core Ecology andCore Evolution Courses: These courses will cover the basics in the field(ecology or evolution).  These courses should be useful preparation for PhD students for the Question Bank part of theAppraisal Exam.  If you have taken 2+ 3rdor 4th year undergrad courses in a field (ecology or evolution), the course for that field may not be especially useful for providing you with background knowledge—discuss with your supervisor and supervisory committee whether you should take either of these courses.  On the other hand, if you have no or very little background in the field, you may need to sit in on undergrad lectures or do outside reading before you take one of these courses; however, if you have taken other courses in E&E (e.g., no background in ecology but you have taken courses in evolution, math or biological theory), ask the EEB graduate office and your supervisor and committee whether you will be equipped to take one of these courses.


EEB330H1 SystematicBotany (not offered in 2017-2018 to grad students)


EEB 1450H Special Topics in Ecology and Evolution:Landscape Genetics: H. Wagner and M.-J. Fortin are planning to offer this course in Winter 2020

Other non-EEB graduate courses that maybe of interest to EEB graduate students: 

For information about graduate courses offered by other departments/groups that may be of interest to some EEB Graduate students (e.g. courses on R and Python, and EES1118Fundamentals of ecological modelling (at UTSC); EES1701H EnvironmentalLegislation & Policy (at UTSC); and EES1137H Quant Appl Data Analysis (at UTSC)), please see information below.

To take these courses, you need permission from your supervisory committee including your supervisor(s) and, if you can’t add the course on ACORN, request the Add Course form from Kitty) (see more detailed instructions about this in the IMPORTANT INFORMATION email about registration, etc. that Kitty sent July18).

Scinet courses in R,Python, etc.:  Note, for courses given directly by Scinet without a course code, please ask  Kitty in the EEB grad office in late August for information about how to do these two things: register with Scinet and also how to sign up for the courses for EEB course codes.


Here is an initial list for 2018-2019:

* "Introduction to Programming with Python"(October 2018) (4 weeks, 8 lectures):

* "Introduction to Scientific Computing withPython" (November 2018) (4 weeks, 8 lectures)::

* "Scientific Computing for Physicists" (winter term, beginning January 2019):

* "Introduction to Computational BioStatistics withR" (fall term, beginning Sept. 2018)

MSC1090H "Introduction to ComputationalBioStatistics with R"  is being sponsored by IMS (Institute of Medical Sciences) and they will have just a few spots open for students "external" to IMS, but these are very limited... hence I will recommend anyone interested in this course to register via ACORN/ROSI *ASAP*! Note: for a review of this course, ask Helen for the name(s) of EEB students who took it last year.


It is possible that we will add a few more about machine learning and neural networks (TBD), so it is always a good idea to check our education site,, for new additions.

THE500: Teaching in Higher Education:  a graduate-level/postdoc course in which students read recent literature on pedagogical theory, and participate in exercises and group discussions on how to apply that theory to the university classroom.  Fall 2018, offered Thursdays, 4:00 - 6:00pm.  Will also be offered Winter 2018.  See website for additional information:    This course is also available to postdocs

Note: THE500 is for personal skills development, and will not show up on your transcript and you will not receive course credit for this course. 

EES3000H S (Winter term) Applied Conservation Biology [N. Mandrak] at UTSc on Mondays from1-4.  First class is Mon. Jan. 7, 2019.  Canada has a complex conservation landscape. Through lectures and interactive discussions with leading Canadian conservation practitioners, this course will examine how conservation theory is put into practice in Canada from our international obligations to federal and provincial legislation and policies, and the role of environmentalnon-government organizations.


EES3113H S (Winter term) Topics in Population and Community Ecology (at UTSc)

The field of ecology is rapidly changing and this course will cover recent advances, concepts or controversies in ecology. This course will focus on specific scientific issues using current literature and the learning experience will be augmented by student presentations and discussions.The course will help ensure that students become familiar with current understanding and basic ecological concepts.  This will be an elective course, and will be especially attractive to those students who did not take advanced ecology courses during their undergraduate studies. In Fall 2018, the course topic will be announced.


CHL5425H Mathematical Epidemiology of Communicable Diseases Fall 2018 and Winter 2019 (in the dept. of Public Health) [David Fisman] You can ask Korryn Bodner and Stephanie Penk for their thoughts on the course.

CHL5223 - Applied Bayesian Methods taught by Michael Escobar in the School of Public Health.

EEB students have taken this course in the past.


PHY 2709H Quantitative Biology of Systems, Organisms and Populations:  This course focuses on the collective behavior of cellular populations coordinated and regulated by intra- and inter-cellular genetic and signaling pathways. We will introduce the mathematical tools to model such non-linear processes, both in a deterministicas well as stochastic framework. Topics will cover biological case studies such as microbial population dynamics, the mammalian immune response, disease epidemics, cell differentiation, development and morphogenesis, and the behavior of neuronal assemblies


Advanced Topics in Statistical Genetics: After providing students the basics in STA 2080 -Fundamentals of Statistical Genetics, this research oriented course will introduce advanced topics to students who are interested in pursuing a career in genome data science.  The specific topics will evolve, over the years, depending on the latest analytic needs and scientific developments from the genetic community.  If the course were to be offered in the 2018-2019 academic year, the topics can include set-based statistical analyses for joint analyzing multiple genetic factors (i.e. gene-based), multiple genes (i.e.pathway), multiple outcomes (i.e. pleiotropy), multiple studies (i.e. meta),data-integration analyses for integrating all kinds of ‘omic' data, and selective inference for conducting reproducible research.


Molecular Genetics: MMG1012H (Y)

Students must take 2 course topics in order to complete this course. The mark in this course is the average of the two marks obtained in the topics taken. Note: all graduate students in our department must completeMMG1012 (i.e. two Course Topics) before the end of a student’s second year in the program. Courses from other departments cannot replace this course.

Topics include: A Practical Course in Programming for Biologists; Background and Topics in Molecular Genetics, Functional Genomics, and ComputationalBiology

Information is listed here:

Math Department: Math models 
Math is offering a join undergrad-grad course, taught by a new AssistantProfessor, Professor Adam Stinchcombe. He taught in Michigan before coming to UofT; a draft syllabus is here: The prerequisites are MAT223H1 and MAT244H1 with a recommendation of a probability course. Note: if you are interested in taking this course, speak toHelen Rodd about what the course code will be. 

Cell and Systems Biology offers some courses that EEB grad students have taken in previous years. For example, see this CSB webpage:

In 2018-19, these courses are being offered (note: CSB students are being given priority for signing up for these courses.  Try enrolling in the course now, and if you cannot, try again after August 22 and then try every two days after that; if you have not been able to enrol by Sept.2, contact Helen Rodd to find  out if the courses are full (their descriptions are below)):

Module: Introduction to R for Data Science

CSB1020H/F, Teaching Section LEC 0135

Coordinators: ProfessorD. Guttman and Dr. Erica Acton
Offered: Fall 2018 session (first half of the session) for six weeks

Weight: One module (0.25FCE)

Time: Mondays, 3:00 –6:00 pm

Location: St. George campus, Earth Sciences Centre, room TBA

Enrolment: Limited to 30 students



This course is a beginner’s introduction to R and R-Studio for students who do not ave a computer science background. It is intended for the student who wants to develop the skills to analyze his or her own data. Students who complete this course will be able to 1) be comfortable with the R-Studio environment, data structures and data types, 2) import data into R and manipulate data frames, 3)transform a ‘messy’ dataset into a ‘tidy’ dataset, 4) make exploratory plots,5) use string manipulation to clean data, and 6) perform basic statistical tests and run a regression model. The structure of the class is ‘code-along’ and students are expected to bring a laptop.


Grades in this module will be determined by a combination of participation in in-class quizzes (6 x 5% = 30%), short assignments (5 x 10% = 50%), and a final project(20%). Short assignments require students to apply the material that they learned during each module with an emphasis on well-documented code that is concise. The final project brings together concepts from all modules by performing exploratory data analysis on a dataset of interest.

Pre-requisites for module:

1) Access to a laptop computer at each module.; 2)R and R-Studio installed (

Reading materials:

As preparatory material for the course, students should install swirl (install.packages(‘swirl’)) and complete R Programming 1: Basic Building Blocks, 3: Sequences of Numbers, 4: Vectors, 7:Matrices and Data Frames. A reference throughout the course will be R forData Science (

Website: All lesson materials and data sets for the course are found at will be submitted to a course Dropbox.

Module: Fundamentals of Genomic Data Science

CSB1020H/F, Teaching Section LEC 0131

Coordinators: ProfessorD. Guttman and Dr. Marcus Dillon
Offered: Fall 2018 session (second half of the session) for seven weeks 

Weight: One module (0.25FCE)

Time: Mondays, 3:00 –6:00 pm

Location: St. George campus, Earth Sciences Centre, room TBA

Enrolment: Limited to 10students


The rise of next-generation genomics has changed the way we think about, study, and employ genetic data, enabling applications that were, until recently, merely the stuff of science fiction. These advances have dramatically increased both the size and scope of biological datasets, and consequently, increased the need for basic computational literacy for nearly all biologists. This course is designed to serve as an introduction to genomic data science for students who do not have a background in computer science. Students in the course will learnt o perform a number of basic genomic data analyses using Galaxy, an open, web-based platform that incorporates multiple bioinformatics tools into an easy to use Graphic User Interface (GUI). Students will then learn to scale up the segenomic analyses using the Unix command line to tackle larger and more complex datasets. During the course, students will learn how to work in a Unixterminal, install bioinformatics software, and connect to remote servers. They will become familiar with the common genomics file formats and use both Galaxy and command line tools to process these files and manipulate the data. They will learn how to perform de novo and reference-based genome assemblies, perform variant calling, and analyze RNA-seq data. The course will take advantage of some of the excellent online resources for background material, while spending class time analyzing real data sets. Students will be expected to have at least a basic understanding of genomics and molecular biology. No prior computational knowledge is required, although students will be expected to have access to a laptop computer. Students who complete this course will have the foundation to approach genomic data analysis in a more efficient manner, enabling

them to tackle more questions in less time.


Grades in this module will be determined by a combination of attendance (25%), short assignments (6 x 5% = 30%), and a final project (45%). Short assignments require students to apply the material thatt hey learned during each module to new problems and answer brief questions about their analyses. The final project is split into three parts, each worth15%, covering the application of the three main genomics pipelines covered in this course to a new dataset: a) Assembly and annotation, b) Reference alignment and variant detection, and c) RNA sequencing analysis.

Pre-requisites for module: 1) Basic background in genetics and molecular biology; 2) Access to a laptop computer a teach module.

Reading materials:

As preparatory material for the course, students will watch lectures from Coursera’s Genomic Data Science Specialization.Specifically, preparatory lectures for this course come from “Introduction toGenomic Technologies”, “Genomic Data Science with Galaxy”, and “Command LineTools for Genomic Data Science”.  There  are also five reviews that are assigned as reading over the course of the module.


All documents and data are shared via a Dropbox account that is setup for the course. The section of the course that coversGalaxy is set up on a local server that can be accessed at

PSY5110H/S Neurobiology of Social Behaviour Instructor: Professor Melissa Holmes 

Topics: This course will focus on the development and adult organization of neurobiological mechanisms underlying the perception of social information and production of social behaviours in diverse species. Each week will focus on a unique topic (e.g., eusociality in hymenoptera; pair bonding in voles; face perception in humans; etc) incorporating a mix of lecture, primary literature, and group discussion. 

Statistics: STA4515H--MultipleHypothesis Testing and its Applications Course 
Description: A central issue in many current big-data scientific studies is how to assess statistical significance while taking into account the inherent large-scale multiple hypothesis testing. This 6-week graduate course will first go over the fundamental elements of single and multiple hypothesis testing, then it will move on to more advanced topics such as incorporating prior information to improve power, specific applications to whole genome genetic association studies, as well as discussions of the fallacy of p-value and alternative measures of statistical evidence and significance. Both analytical and empirical arguments will be presented, and participating students are expected to write a research report on suggested or self-selected topics related to multiple hypothesis testing.

Statistics: STA2080H  Fundamentals of Statistical Genetics Course 
Description: Statistical analysis of genetic data is an important emerging research area with direct impact on population health. This course provides an introduction to the concepts and fundamentals of statistical genetics, including current research directions. The course includes lectures and hands-on experience with R programming and state-of-the-art statistical genetics software packages.

STA 4523H Bayesian Computation with Massive Data and Intractable Likelihoods:  A Google search with the terms "Markovchain Monte Carlo (MCMC)" returns over 2 million hits. This is not surprising, as this class of algorithms has become in the last 30 years the main workhorse for statistical computation, especially for Bayesian inference. However, the evolution of scientific experiments, particularly the availability of large data and the complexity of posited models have brought MCMC to an inflection point. Significant difficulties are encountered when the data is massive or when the statistical model is complex enough to be analytically intractable. In the former case, the classical MCMC samplers scale poorly while in the latter only approximate versions of the model can be studied with little, or no theoretical guarantees of accuracy. In this course we will discuss and study computational algorithms that overcome this type of challenges.


GGR1916H Remote Sensing of Vegetation Traits and Function 




With the professor’s permission, students are welcome to sit in on undergraduate courses to enhance their background in specialized topics (e.g.,vertebrate anatomy, community ecology, etc.). (note: EEB cannot offer specialized graduate courses that would have enrollments of less than 15 students)


Also, with the professor’s permission, students may audit (or take for credit) graduate courses, even after they have completed the course requirements for their degree.

For future years, please do consider proposing special topics courses to faculty for a course that would be offered the following year.