(1) Matthew Akamatsu - UCB

Postdoc - matt.akamatsu@berkeley.edu

3D image analysis and machine learning to complement 3D stochastic simulations and cryo-electron microscopy


Force generation by actin assembly shapes cellular membranes. An experimentally constrained multiscale model shows that a minimal actin network is sufficient to internalize endocytic pits against membrane tension. We developed a fluorescence-based molecule-counting method in live mammalian cells and found that ~200 Arp2/3 complexes assemble at sites of clathrin-mediated endocytosis in human cells. The advent of lattice light-sheet microscopy and 3D particle tracking methods promises to revolutionize the field of quantitative cell biology. We hypothesize that our molecule counting method, in combination with these live-cell 3D microscopy and particle tracking methods and machine learning based identification of cellular processes, will allow for the systematic, quantitative spatiotemporal understanding of dynamical events such as actin assembly at every cellular organelle and subcellular process.


(2) Adam Anderson - UCB

Post-doc - admndrsn@berkeley.edu

Recognizing the Impossible Image: How 3D Imaging Can Lead to Optical Character Recognition for Cuneiform Tablets