Open AccessDetecting asymmetry in the presence of symmetry with maximum likelihood three‐dimensional reconstructions of viruses from electron microscope images
Author(s) -
Wang Kang,
Fu Chiyu,
Catalano Carlos E.,
Prevelige Peter E.,
Doerschuk Peter C.,
Johnson John E.
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0737
Subject(s) - asymmetry , cryo electron tomography , electron tomography , statistical physics , gaussian , symmetry (geometry) , physics , algorithm , computer science , electron microscope , pattern recognition (psychology) , artificial intelligence , mathematics , tomography , optics , scanning transmission electron microscopy , quantum mechanics , geometry
Various modes of transmission electron microscopy can provide unique structural information on nanometre‐scale biological machines such as viruses and ribosomes. A maximum‐likelihood statistical reconstruction algorithm using information from two such modalities, single‐particle cryo‐electron microscopy and computed electron tomography, is described for the problem where the machine is nearly symmetrical, but the localised regions of asymmetry are important for the functioning of the machine. The algorithm is demonstrated on experimental bacteriophage Lambda procapsid data. Key features of the algorithm are the use of probability density functions (pdfs) derived from normalised correlation rather than Gaussian pdfs and the solution of a constrained classification problem in which 11 out of 12 sites of asymmetry belong to one class while the 12th site belongs to a second class.