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.
@article{arxiv.1512.09347,
title = {De novo visual proteomics in single cells through pattern mining},
author = {Min Xu and Elitza I Tocheva and Yi-Wei Chang and Grant J Jensen and Frank Alber},
journal= {arXiv preprint arXiv:1512.09347},
year = {2019}
}
Comments
60 pages, 27 figures. Latex compiling problems fixed, minor text edits, one figure added, several references added