Establishing an open science foundation for data-driven modeling of mechanobiological systems

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• Emma Lejeune (Boston University)
• Friday 04 August 2023, 10:00-11:00
• Seminar Room 1, Newton Institute.

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USMW02 - Mathematical mechanical biology: old school and new school, methods and applications

From the beating heart to tissue assembly and repair, it is well accepted that mechanics plays an important role in the behavior of biological systems. Mechanical forces are not only fundamentally important to biological materials (e.g., the mechanics of growth), but are also fundamental drivers of cellular behavior change. However, it is often difficult to determine mechanical state both in vitro and in vivo, and it is often difficult to determine how mechanical perturbations (e.g., changes to boundary conditions) will change the mechanical state throughout the domain. Over the past several decades, mathematical modeling has emerged as an important tool to bridge this gap. And, more recently, there has been a surge in interest towards using data-driven statistical techniques to create predictive models of biological system behavior. As experimental techniques and data-driven methods simultaneously advance, there is an unprecedented opportunity to gain biological insight. In this talk, we will describe our preliminary and ongoing work in data driven modeling of in vitro biological systems with applications focused on both cardiac tissue engineering and wound healing. In brief, we envision a methodological framework with three essential components: (1) open access datasets of time-lapse movies of cells and tissue, (2) open source software to extract interpretable quantities of interest from these time-lapse movies, and (3) combined mechanistic and statistical models of biological behavior informed by these data. We are presently working on creating these datasets, software, and models in partnership with experimental collaborators, and releasing them to the community under permissive licenses. Looking forward, we anticipate that these large open access curated datasets combined with open source tools to extract information from them will enable significant advances in our understanding of, and ability to control, living systems. Through this talk, we hope to foster further discussion and collaborations at the interface of mechanics, biology, and open science.

This talk is part of the Isaac Newton Institute Seminar Series series.

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