title: Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses.
abstract: We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.
authors.affiliation: Computational Visualization Center, Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA. zeyun.yu@gmail.com
authors.forename: Zeyun
authors.initials: Z
authors.lastname: Yu
authors.forename: Chandrajit
authors.initials: C
authors.lastname: Bajaj
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D020285:Cryoelectron Microscopy / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014780:Viruses / Q000648:ultrastructure*