Integrative mathematical, computational, and experimental approach to study biological systems

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The application of mathematical and computational models to biology is an exciting and novel area of research in Applied Mathematics. This integrative approach facilitates the interpretation of large datasets and captures the inherent complexity of living systems, which has the potential to revolutionize our understanding of biology. The long-term goal of the proposed research program is to advance the development and application of quantitative approaches in biological research by integrating experimental studies with mathematical and computational techniques. This will enable a more fundamental understanding of the complex processes in biological systems, with a special emphasis on the link between tissue cellular heterogeneity, the integrated stress response (ISR), and the immune system. This research will also provide valuable insights into the complex interactions between micro-environment and cell phenotype, and how these interactions modulate cell lineage. To this end, the research has four objectives: O1. Develop a novel, biomarker-free classification system for cell phenotypes (including epithelial and mesenchymal) using imaging flow cytometry combined with a high-performance machine learning architecture. O2. Build a compartmental mathematical model, grounded on experimental studies, to examine the dynamics between cell phenotypes and the effects of environmental factors (oxygen deficiency, metabolism) on phenotype switching, for instance, as observed in epithelial-mesenchymal transition. O3. Determine the molecular networks underlying the survival of different cell phenotypes in several tissue types, which will be accomplished by developing a ML architecture to classify genetic screening data from gene-editing techniques such as shRNA and CRISPR/Cas9. O4. Develop a systems biology approach to investigate the connection between these molecular networks determined in O3, and the ISR, as well as their effects on modulating and the immune response. This research will push the frontiers of current knowledge in the biological sciences further, providing a deeper understanding of the role of the ISR in mediating cell phenotype and immune response. Understanding the mechanisms underlying cell phenotype switching has implications for wound healing, metastasis, and tissue engineering. Given the importance of the biological processes being investigated in normal tissue development and malignant progression, I anticipate that this research will provide a rational basis for future studies. Students will gain invaluable experience in the biological, mathematical, and computational sciences and will forge connections with experimentalists from other research institutes. In keeping with the fast-paced growth of the machine learning and artificial intelligence sectors in Canada, this multidisciplinary training will help facilitate the transition of students to careers in both academic and industrial settings, including biotechnology companies.