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

The goal of this workshop is to bring microbiologists, evolutionary biologists and applied mathematicians together to discuss recent experimental discoveries in microbial genetics and evolution. Our aim is to develop new mathematical approaches and predictive models that account for the complexity and diversity of microbial evolution. Overall, a deeper understanding of the ever-changing microbial populations within and around us will be critical in responding to novel pathogens and changing environments.

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

In this workshop, we will discuss the current state of computational modelling in cancer biology and treatment. Through the exploration of in silico trials and ABMs, workshop participants will establish new, cutting-edge approaches in computational oncology, establishing new paradigms for understanding how cancer develops and how we can improve treatment outcomes in patients.

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

Present day biology generates a wealth of data from which tumor biology and tumor evolution can be inferred, and therapeutic strategies can be developed. Most clinical (and research) samples are comprised of a mixture of different cells, including multiple different populations of cancer cells (‘subclones’) and a variety of normal cell types. Effective use of these data thus requires data from individual cell types to be deconvolved. A number of subfields are independently developing mathematical and statistical deconvolution techniques. While at first glance these subfields are largely disparate, there are clear opportunities for synergies to be developed. This workshop will fill this gap by bringing together researchers from several of these fragmented subfields across a wide range of backgrounds (computational biology, mathematics, statistics, computer science, biomedicine, etc.) to provide a synergistic forum for cross-disciplinary learning, discussion and collaboration.

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

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