SPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs. - Shaikh, Tanvir R; Gao, Haixiao; Baxter, Bill; Asturias, Francisco J; Boisset, Nicolas; Leith, ArDean; Frank, Joachim (Nat Protoc, 2008)
This protocol describes the reconstruction of biological molecules from the electron micrographs of single particles. Computation here is performed using the image-processing software SPIDER and can be managed using a graphical user interface, termed the SPIDER Reconstruction Engine. Two approaches are described to obtain an initial reconstruction: random-conical tilt and common lines. Once an existing model is available, reference-based alignment can be used, a procedure that can be iterated. Also described is supervised classification, a method to look for homogeneous subsets when multiple known conformations of the molecule may coexist.
Keywords: Image Processing, Computer-Assisted; Microscopy, Electron; Models, Molecular; Molecular Structure; Software; User-Computer Interface

SPIRE: the SPIDER reconstruction engine. - Baxter, Bill; Leith, ArDean; Frank, Joachim (J Struct Biol, 2007)
SPIRE is a Python program written to modernize the user interaction with SPIDER, the image processing system for electron microscopical reconstruction projects. SPIRE provides a graphical user interface (GUI) to SPIDER for executing batch files of SPIDER commands. It also lets users quickly view the status of a project by showing the last batch files that were run, as well as the data files that were generated. SPIRE handles the flexibility of the SPIDER programming environment through configuration files: XML-tagged documents that describe the batch files, directory trees, and presentation of the GUI for a given type of reconstruction project. It also provides the capability to connect to a laboratory database, for downloading parameters required by batch files at the start of a project, and uploading reconstruction results at the end of a project.
Keywords: Computational Biology; Image Processing, Computer-Assisted; Software; Software Design

Particle picking by segmentation: a comparative study with SPIDER-based manual particle picking. - Adiga, Umesh; Baxter, Bill; Hall, Richard J; Rockel, Beate; Rath, Bimal K; Frank, Joachim; Glaeser, Robert M (J Struct Biol, 2005)
Boxing hundreds of thousands of particles in low-dose electron micrographs is one of the major bottle-necks in advancing toward achieving atomic resolution reconstructions of biological macromolecules. We have shown that a combination of pre-processing operations and segmentation can be used as an effective, automatic tool for identifying and boxing single-particle images. This paper provides a brief description of how this method has been applied to a large data set of micrographs of ice-embedded ribosomes, including a comparative analysis of the efficiency of the method. Some results on processing micrographs of tripeptidyl peptidase II particles are also shown. In both cases, we have achieved our goal of selecting at least 80% of the particles that an expert would select with less than 10% false positives.
Keywords: Algorithms; Aminopeptidases; Cryoelectron Microscopy; Dipeptidyl-Peptidases and Tripeptidyl-Peptidases; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Internet; Particle Size; Ribosomes; Serine Endopeptidases; Software; Software Validation