This gzipped tar archive contains the source required to compile an image classification program based on the work of Ogura et al (see references). It is written in C++ and includes a README file that covers its operation.
The program can also be used in the generation of classes for Random Conical Tilt or Orthogonal Tilt Reconstruction using SPIDER.
Adapt is a piece of working, in-house software and as such hasn't been extensively tested on many hardware setups and systems.
Note: Release 2.02 compiles cleanly under gcc 4.3.x and includes a bugfix for a segfault condition in the previous releasee.
- an IMAGIC image stack, most likely the output of a multi-re2ference alignment (MRA), to be classified into groups.
- various parameters of classification described in the README and Ogura paper.
- the number of nodes in the network (e.g., the number of classes wanted).
- an IMAGIC image stack corresponding to 'node images' (see Ogura paper)
- an IMAGIC image stack of class averages
- SPIDER format select files for each class.
Ramey VH, Wang HW, Nogales E. (2009) Ab initio reconstruction of helical samples with heterogeneity, disorder and coexisting symmetries. J Struct Biol., E-pub ahead of print.
Ogura T, Iwasaki K, Sato C. (2003) Topology representing network enables highly accurate classification of protein images taken by cryo electron-microscope without masking. J Struct Biol., 143(3), 185-200.