Data from cutting-edge experimental methodologies, including single-cell lineage tracing in vivo, and quantitative three-dimensional (3D) confocal imaging will be analyzed and used for mathematical/computational modelling. In order to test hypotheses about the influence of mitotic spindle dynamic orientation on cell fate outcomes, we will translate the hypotheses into stochastic models for cell fate dynamics, including spindle orientation, cell divisions (determined or not by spindle orientations) and stochastic cell fate choices. The mathematical models will be evaluated via mathematical techniques, such as solution approaches for the stochastic Master equation (coupled ordinary differential equations), and numerical techniques, such as Monte Carlo simulations. The results of this evaluation, which yields predicted clonal distributions, will be compared with the clonal data via Bayesian inference, whereby non-compliant hypotheses can be rejected and compliant ones can be scored for their certainty. The outcomes of this project are expected to provide important novel insight into the identity, dynamics and differentiation potential of adult MaSCs.
Principal Investigator & Supervisors:
Dr Salah Elias
Dr Philip Greulich
Prof Ben MacArthur
Funding provider:
Institute for Life Sciences & School of Mathematics
Funding dates:
October 2018 – September 2022