  Cryo-electron tomography enables 3D visualization of cells in a near native
state at molecular resolution. The produced cellular tomograms contain detailed
information about all macromolecular complexes, their structures, their
abundances and their specific spatial locations in the cell. However,
extracting this information is very challenging and current methods usually
rely on templates of known structure. Here, we formulate a template-free visual
proteomics analysis as a de novo pattern mining problem and propose a new
framework called "Multi Pattern Pursuit" for supporting proteome-scale de novo
discovery of macromolecular complexes in cellular tomograms without using
templates of known structures. Our tests on simulated and experimental
tomograms show that our method is a promising tool for template-free visual
proteomics analysis.
