The cell is the basic structural, functional, and biological unit of all known living organisms. It is a tiny but very complicated "living machine" that can do a lot of amazing things. However, so far we have very limited knowledge about its complicated molecular machinery due to lack of high resolution and systems level data of individual cells. Cellular Electron CryoTomography is an emerging imaging technique that captures the 3D electron density distribution of cells at sub-molecular resolution and at close-to-native state. Our lab aims to use cutting-edge computation, mathematics and artificial intelligence techniques, particularly those related to computer vision, machine learning and big data, to build structural organization models using such imaging data. Such modeling would be useful for getting new insights into the machinery of cellular systems.
The figure above shows extracted structural patterns in cellular tomograms: (a) Slices of 3D tomogram images of two bacterial cells. Image data are from the Jensen Lab at Caltech. (b) Isosurfaces of instances of extracted structural patterns embedded into the original images. (c) Embedded instances, zooming in on a particular region. (d) Isosurfaces of one example structural pattern from each experiment. (e) Spatial distributions of instances of different structural patterns: left: the Ribosome like patterns distributed outside the nucleoid region; middle: patterns distributed on the nucleoid region; right: patterns distributed at the tip of the cell. For details, see our paper recently accepted by Structure.