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Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Cells are the fundamental building blocks of life. Recent advancement in biotechnology has allowed us to peek inside this every cell for better understanding of biology and human disease. Single-cell technology also generates big and complex data and brings about new data science challenges for computational and life scientists. The objective of this workshop is to bring together international leaders in diverse disciplines including mathematical, statistical, computational, biological and medical in a collaborative atmosphere to develop the collaborative capacity that will tackle various underlying data science challenges in single-cell research.

Molecular Biology,    Scientific Computing and Data Science

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

The advances in imaging techniques have enabled the access to 3D shapes present in a variety of biological structures: organs, cells, organelles, and proteins. Since biological shapes are related to physiological functions, biomedical analyses are poised to incorporate more morphological data. For example, at the macroscopic scale, characterizing brain morphologies allows clinicians to quantify the progression of Alzheimer's disease. At the microscopic scale, the characterization of protein morphologies allows biologists to understand how these biomolecules react to chemical variations of their environment and helps detect promising pharmacological targets for the treatment of conditions ranging from neurological disorders to several cancers. Therefore, different biological scales ask a common statistical question: how can we build mathematical and statistical descriptions of biological morphologies and their variations? This workshop invites participants from different application fields to exchange mathematical and statistical methods for the study of biological shapes.

Pattern Recognition and Image Processing, Machine Vision,    Biophysics, Medical Physics

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

The interface between biology and quantitative disciplines including physics, mathematics and engineering is rapidly expanding. This is the result of many factors, but is largely driven by higher resolution spatial and temporal data from cutting edge imaging techniques, and increasing success in applying physical modeling techniques to biological problems. Mechanobiology is an especially rapidly developing field at the quantitative biology interface. This field describes how force is generated in biological systems, how force impacts chemistry, and how force generation is controlled by intracellular signaling pathways. Numerous feedforward and feedback interactions connect forces in cells to the dynamics of proteins and gene expression, resulting in highly nonlinear systems with complex and often non-intuitive behaviours.

Biophysics, Medical Physics,    Computational Physics and Numerical Simulation

Centre de recherches mathématiques (CRM)

While brain function originates in neuron, its energy is supported by the vascular system. With the recent development of anatomically detailed synthetic network models of the entire cerebral circulation, it is now possible to perform detailed simulations of physiology in realistic brains of small animals and humans on the computer. Modeling microcirculatory blood flow as a biphasic suspension of red-blood-cell and plasma, blood pressure, flow and hematocrit can be simulated in whole brains on the computer. Combining Poiseuille’s hemodynamic simulations with advection/diffusion equations describing oxygen diffusion, the human brain metabolism can now be modeled in-silico, by integrating tissue oxygen consumption and differential equations describing compartments associated with neural and glial brain cells. In parallel, energy metabolism regulation in the brain and its modeling has greatly progressed over the past few decades. This workshop will thus be focused on digital human brains, and their use to predict critical metabolic functions namely blood flow, oxygen extraction and cellular metabolism across all length scales down to the level of individual capillaries and cells. Courses and conferences will be combined with research presentations and practical workshops.

Modeling and Simulation,    Applied Mathematics (in general)

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

What have we learned from the COVID-19 pandemic, and how can we be better prepared for the next global outbreak? This workshop brings together collaborative teams of modellers, statisticians, epidemiologists, genomics experts, public health decision-makers, and those implementing and delivering interventions who have been working together in a research network, aiming to increase Canada’s capacity for data-driven emerging infectious disease modelling to directly support future public health decisions. This BIRS meeting is an important opportunity for network members and collaborators to share the outcomes of their research over the two years since the network was launched with funding from the federal government. The questions being tackled at this workshop are grounded in public health needs and generated in partnership between research investigators and knowledge users – public health leaders, health administrators and policy-makers.

Modeling and Simulation,    Epidemiology & Public Health

Centre de recherches mathématiques (CRM)

While network models have been studied as independent systems, efforts in neuroscience in recent years has been put towards inferring networks of the brain from imaging data. Using probabilistic methods and inverse models, recurrent networks across populations and their change with disease have been characterized based on input from electrophysiological and functional imaging.

This sub-theme will cover the notions of network dynamics, discuss conceptual frameworks to model brain network topology and provide the latest progress in neural network inference from imaging data and associated methodological approaches at modeling networks of the brain.

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Fields Institute

This workshop aims to showcase the state-of-the-art mathematical and computational models that are in use in mathematical oncology, with a particular focus on the fourteen hallmarks of cancer. New modeling challenges arise from these hallmarks. Some of the hallmarks relate to the characteristics of the cancer cells themselves (sub-cellular and cellular level), while others include more global effects such as blood circulation, the immune response, the effect and role of the microenvironment, mechanical forces, and the microbiome. Matching the biological diversity of the cancer hallmarks, is the diversity of mathematical approaches and techniques that have been used and are in use to give insight into the growth and spread of cancer – for example, continuum and discrete models; ordinary and partial differential equation models; individual-based and agent-based models; hybrid models; deterministic and stochastic approaches; analytical and computational approaches. Many of these processes act on very different spatial and temporal scales. Hence a new integrated multiscale mathematical modeling framework is needed to include new aspects and insights, such as spatial stochastic models and local and non-local partial differential equation models.

Oncology,    Modeling and Simulation

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Epidemiology & Public Health

Fields Institute

This workshop aims to take a closer look at how mathematical and computational models can help answer clinically relevant questions and enhance multimodal treatments. Currently, a wide range of modelling approaches study cancer and have a crucial role in treatment delivery from answering questions related to cancer biology and treatment efficacy to directly helping with treatment delivery. In this workshop, we would like to bring together clinicians, biomedical experts, experimentalists, and mathematicians to explore some of the relevant questions on multimodal treatment modelling, efficacy, optimization, drug resistance and clinical delivery.

Oncology,    Modeling and Simulation

Fields Institute

This workshop explores research in methods aimed at connecting mathematical models of cancer evolution and clinical data. It focuses on ecology and evolution of cancer. Traditionally, ecology and evolution have been the most “mathematical” (and perhaps the first mathematical) areas of biology. Mathematical contributions to these fields made in the 20th century are now fundamental parts of scientific knowledge. More recently, methods of ecology and evolution have found their way into oncology, bridging traditional molecular biology and mathematics including stochastic processes, dynamical systems, and nonlinear partial differential equations. New biological challenges lead to difficult mathematical problems and beautiful solutions, which are both innovative mathematically and impactful from the point of view of public health. These will be the focus of the proposed workshop .

Oncology,    Modeling and Simulation

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Geometry and Topology

Fields Institute

Immunotherapies have revolutionized treatments for several types of cancers, but have been met with clinical trial failures in others. The idea of eliciting an immune response against a tumour is old, but we are only just beginning to harness the potential of the immune system to treat both solid and liquid tumours. To improve immunotherapeutic approaches requires understanding how the immune system interacts around and within a tumour, allowing us to establish effective immunotherapeutic protocols. Mathematical modelling can help identify the mechanisms at the heart of immunotherapeutic efficacy and design successful therapeutic regimens. Close collaboration between experimentalists, clinicians, and quantitative researchers in academia and industry is required to forward models for implementation. This workshop will focus on tightening the links between researchers in different fields to fuel immunotherapy success.

Oncology,    Modeling and Simulation