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Item _em_3d_reconstruction.method_details

Description

    The algorithm method used for the 3d-reconstruction.
  e.g. 
 Random-conical reconstruction: 
  a method of data collection and reconstruction used for single particles, 
  typically used initially in a project, to obtain a first low-resolution 
  reconstruction of the macromolecule [Radermacher et al., 1987]. Two images 
  of the same specimen field are collected, one with untilted grid, the 
  other with the grid tilted by 50 to 60 degrees. Any set of particles 
  presenting the same view in the untilted-specimen image form a 
  random-conical projection set in the associated tilted-specimen image.
 Helical reconstruction 
  Helical reconstruction is used when the protein of interest forms a 
  natural helix. Since the helix is a recurring structure with a very 
  well defined pattern, the repeating pattern of the helix can be 
  exploited to solve the structure. In this case, no alignment of the 
  particles is needed, since the individual positions of subunits within 
  the helix are clearly defined by the shape of the helix. Two common 
  examples of structures solved by helical reconstruction are TMV and 
  microtubules.
 Icosahedral reconstruction 
  Icosahedral reconstructions also take advantage of internal symmetry 
  and repetition to generate a detailed three-dimensional structure from 
  the data set. In this case, the symmetry is icosahedral (twenty-one sided). 
  Many viruses exhibit icosahedral symmetry in their capsid proteins, 
  and this method has been used to solve their structures.
 Electron crystallography 
  Electron crystallography is similar to x-ray crystallography in that it 
  exploits the repeating pattern found within a crystal to generate a 
  structure. Just as with x-ray crystallography, difraction patterns are 
  generated and are used to define an electron density map. However, it 
  differs in that the crystal used is a two-dimensional sheet as opposed 
  to three three-dimensional crystals of x-ray crystallography.
 Common Lines
  Another reconstruction method searches for the intersection of any two 
  projections in Fourier space. The Fourier transform of the experimental 
  projections all form slices around a common core in Fourier space. 
  Therefore, the intersection of these projections are unique (unless the 
  projections perfectly overlap), and their relative orientation can be 
  found when three or more projections are used. A principal problem with 
  this method is that the handedness of the image is lost. This, however, 
  can later be corrected by visual examination of the model with other 
  known structural information.
 Back Projection 
  As its name implies, back projection is the inverse function of projection. 
  When an n-dimensional object is projected, each projection is an n-1 
  dimensional sum of its density along the projection axis. Therefore, a 
  sphere would have circles as its projections. A cube, on the other hand, 
  would produce either squares, diamonds, or other intermediate parallelograms
  depending on the direction of projection. The actual shape, of course, 
  depends on the orientation from which the projection was made. The reverse 
  function is called back projection and regenerates the original object.