- Data-Driven multiscale modeling of cell fate dynamics
- 09/27/2016
- 3:00 PM - 4:00 PM
- C304 Wells Hall
- Qing Nie, University of California, Irvine
Fates of cells are not preordained. Cells make fate decisions in response to different
and dynamic environmental and pathological stimuli. Recently, there
has been an explosion of experimental data at various biological scales, including
gene expression and epigenetic measurements at the single cell level,
lineage tracing, and live imaging. While such data provide tremendous detail
on individual elements, many gaps remain in our knowledge and understanding
of how cells make their dynamic decisions in complex environments. In
addition to developing new models to analyze data at each scale, we are working
on multiscale modeling challenges in analyzing single-cell molecular data
(data-rich scale) and their connections with spatial tissue dynamics (datapoor
scale). Our approach requires new and challenging mathematical and
computational tools in machine learning, stochastic analysis and simulations,
and PDEs with moving boundaries. We then use our novel data-driven multiscale
modeling approach to uncover new principles for cell fate dynamics in
development, regeneration, and disease.