Modeling structural properties of breast cancer cells
PSOC is a large, multi-institution effort to study physical mechanisms underlying tumor progression in breast cancer. One goal is to use 3D culture models, confocal imaging, and simulation experiments to show how mechanical forces affect proteins, cells and tissues - this particular effort has count on active NERSC, LBNL and UC Berkeley collaboration. To do so, we have built image analysis algorithms that take time slices of stacks of two-dimensional images, representing three-dimensional structures: these images are taken at key moments in cell development, and we have been (1) building algorithms that assemble and extract these time-evolving structures, (2) developing diagnostics and structure analysis algorithms to extract key physical properties (such as shape, degrees of spheroidicity and connectedness, etc.) and (3) providing quantitative checkpoints for computational models which solve equations of motion for the fluid, mechanical, and elastic evolution of cell boundaries.
By modeling structural changes over time and describing such variations quantitatively, we hope to better understand the cell pathway and epigenesis.
* CRD: Dani Ushizima, Chris Rycroft, Robert Saye, James Sethian
* Life Sciences: Kandice Tanner, Cyrus Ghajar, Mina Bissel
* UCB: Jan Liphardt