BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Establishing an open science foundation for data-driven modeling o
 f mechanobiological systems - Emma Lejeune (Boston University)
DTSTART:20230804T090000Z
DTEND:20230804T100000Z
UID:TALK202468@talks.cam.ac.uk
DESCRIPTION:From the beating heart to tissue assembly and repair\, it is w
 ell accepted that mechanics plays an important role in the behavior of bio
 logical systems. Mechanical forces are not only fundamentally important to
  biological materials (e.g.\, the mechanics of growth)\, but are also fund
 amental drivers of cellular behavior change. However\, it is often difficu
 lt to determine mechanical state both in vitro and in vivo\, and it is oft
 en difficult to determine how mechanical perturbations (e.g.\, changes to 
 boundary conditions) will change the mechanical state throughout the domai
 n. 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 cre
 ate predictive models of biological system behavior. As experimental techn
 iques and data-driven methods simultaneously advance\, there is an unprece
 dented opportunity to gain biological insight. In this talk\, we will desc
 ribe our preliminary and ongoing work in data driven modeling of in vitro 
 biological systems with applications focused on both cardiac tissue engine
 ering and wound healing. In brief\, we envision a methodological framework
  with three essential components: (1) open access datasets of time-lapse m
 ovies of cells and tissue\, (2) open source software to extract interpreta
 ble quantities of interest from these time-lapse movies\, and (3) combined
  mechanistic and statistical models of biological behavior informed by the
 se 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 anti
 cipate that these large open access curated datasets combined with open so
 urce tools to extract information from them will enable significant advanc
 es in our understanding of\, and ability to control\, living systems. Thro
 ugh this talk\, we hope to foster further discussion and collaborations at
  the interface of mechanics\, biology\, and open science.
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR