Modeling and computational analysis of biological systems

This June 11 and 13, BIOS2 will host a new training on mathematical models in Ecology, hosted by our fellow Maxime Clenet!

This course is designed to deepen your understanding of theoretical models in ecology, such as population dynamics (Lotka-Volterra), spatial dynamics (metapopulation), or epidemiological models (SIR). The training is divided into two main parts.
First, we will look at the key steps in modelling and formalizing a biological problem in terms of equations and try to answer the questions: Why is it useful? And what are the main current theoretical approaches in population dynamics?
A rigorous mathematical analysis of the model will be carried out by presenting the main methodological tools useful for its analysis, such as equilibrium, Jacobian matrices and stability. This analysis will be integrated in the form of practical exercises and exchanges between the students.

The theoretical part will be followed by a numerical and data-oriented interpretation. You’ll learn how to develop a numerical method to find a solution to dynamical systems with some examples. At the end, the participants will have the opportunity to develop their own numerical simulations for their favourite dynamical model using an adapted and easily accessible programming tool (Python or R depending on programming preferences).

This training is an interdisciplinary project that aims to enhance technical skills, theoretical ecology understanding, and numerical and computational abilities. Trainees from diverse backgrounds are welcome, and the proposed formula will benefit everyone. The training will provide an opportunity for everyone to work on a simple model in three stages: understanding the basic mathematical ideas behind the model, the questions involved and the final numerical implementation of the model.

What: Short course on mathematical models in Ecology (8h)
When: June 11 and 13, 10am-4pm EST (includes lunch break)

2024 Summer School in Advanced Statistics for the Life Sciences

The Summer School in Advanced Statistics for the Life Sciences, on the theme of Hierarchical Models, will take place from April 29 to May 3, 2024 at Jouvence, in Mont-Orford National Park, Quebec. Hierarchical models in life sciences refer to statistical frameworks that account for the nested structure of data often encountered in biological research, where observations are organized within multiple levels of hierarchy such as individuals within populations, or repeated measures within individuals. These models allow for the incorporation of both within-group and between-group variability, providing insights into the underlying biological processes while appropriately addressing the complex dependencies within the data.

The intensive course is presented by Pr. Guillaume Blanchet, professor at Université de Sherbrooke and academic member of BIOS2, and Dr. Andrew MacDonald, research professional for BIOS2CREUS, and QCSB. The course aims to introduce hierarchical models from both a theoretical and practical point of view. Everything will be done using R with an introduction to Stan. Bring your dataset!


Anyone interested in taking part in the summer school must complete this form by March 20, 2024. Official registration (admission and payment of registration fees) will take place during the week of March 25, 2024

More information and registration:

2024 Summer School in Biodiversity Modelling

The 2024 edition Summer School in Biodiversity Modelling will be on the theme “Indicators to monitor biodiversity changes“. Biodiversity indicators are metrics used to measure and assess the health, diversity, and distribution of species, ecosystems, and genetic variability within an environment. These indicators provide valuable insights into the status and trends of biodiversity over time, helping to inform conservation efforts, policy-making, and sustainable development practices. By tracking these indicators, scientists and policymakers can monitor changes in biodiversity, identify areas of concern, prioritize conservation actions, and evaluate the effectiveness of conservation strategies.

The main objective of the 2024 Summer School in Computational Biodiversity Science will be to develop a report of the current state of biodiversity for Canada, based on the most recent science on biodiversity indicators and using state-of-the-art technologies in data science. 

Presented by Professor Dominique Gravel (Université de Sherbrooke) in collaboration with various leading scientists in the domain, the intensive course will take place from May 13 to 17, 2024 at Jouvence, in Mont-Orford National Park, Quebec.

Date: May 13 to 17, 2024
Location: Jouvence Resort in Orford, Quebec
Registration fee: 600$ (shared room) 800$ (private room)
Price includes course registration, accommodation and meals.


Anyone interested in taking part in the summer school must complete this form by March 20, 2024. Official registration (admission and payment of registration fees) will take place during the week of March 25, 2024

More information and registration:

Structural Equation Modelling – training

We are pleased to announce our forthcoming workshop on Structural Equation Modeling (SEM), scheduled to take place from April 8th to 10th, 2024, from 10 am – 1 pm PT / 1 pm – 4 pm ET. This course offers a comprehensive exploration of SEM, delving into its theoretical underpinnings and practical applications. Participants will gain a profound understanding of causal modelling, latent variables, and the nuances of covariance-based and Partial Least Squares (PLS) SEM methodologies. Through in-depth instruction, attendees will learn to leverage prominent software tools to conduct sophisticated analyses of complex datasets. Covering conventions, terminology, model specification, and evaluation, this course equips professionals and researchers with the essential skills to navigate SEM effectively.

The training will be conducted by our fellow Varina Crisfield, an awarded PhD candidate in Key Biodiversity Areas at the Université de Sherbrooke. The workshop will be hosted virtually, and access information will be sent out to registered participants one day before the event.

To apply, please fill out this form by April 4th, 2024:

Two workshops to get started with your data project

New Year, new project! In February, BIOS2 will offer two workshops to help you get started with your data projects: Project Set-Up and Data Wrangling. In a mix of best practices tips, tutorials and hand-holding activities, these very basic workshops are designed to make you think about your project and data organization before you start anything, but also to help you reshape your current ongoing projects to something more organized and reproducible. Registrations are open until two days before of the first day of each workshop, and seats are limited (max. 40 people each).

These workshops should be accessible to any graduate student, though prior experience in R is helpful. The workshop will be in English, with support in French, and it will be presented online. The link to access it will be communicated shortly before the workshop.

To register, fill out this form:

Project Set-Up

Learn and practice project organization, reproducibility tips, project maintenance, and more!
Instructors: Andrew MacDonald and Gracielle Higino
When: February 5, 6 and 7 @ 11 am PT / 2 pm ET
Where: online

Data Wrangling

Learn the best practices on data tidying and follow along a tutorial on OpenRefine.
Instructors: Simran Bains, Lukas Van Riel and Timothée Poisot
When: February 13 and 15 @ 10 am PT / 1 pm ET
Where: online

If you have any questions, do not hesitate to contact us at

Handy tips for doing a statistical model

When it comes to designing a statistical model, a lot of uncertainty comes to mind. In December, BIOS2 will offer a workshop which will give you some helpful strategies for fitting and understanding your regression models. Led by Dr Andrew MacDonald, the workshop will happen during 3h in two days on December 12 and 14, 2023, with lots of time for questions and discussions of your own work. This workshop should be accessible to any graduate student, though prior experience in R is helpful. The workshop will be in English, with support in French.

To register, fill out the form linked at the end of this page by December 9th, 2023.


Day 1:

  • What’s zero? When and how to center a variable?
  • What are the units? Scaling a variable and why you should do it.
  • What does it mean? Making predictions.
  • Does it depend? Fitting and visualizing interactions.

Day 2:

  • What do you expect? Simulating datasets.
  • The secret weapon: fitting the same model multiple times.

When: 13h EST, Tuesday 12 Dec and Thursday 14 Dec, 2023.
Duration: 3h each day (total of 6 hours)
Where: Online - information to be sent one day before the workshop
Registration form:
Registration deadline:  December 9th, 2023