01752nas a2200265 4500008004100000022001400041245010100055210006900156260001200225300001000237490000800247520093400255653002801189653002101217653002201238653004001260653001401300100002001314700002501334700002201359700001701381700002101398700001901419856004801438 2008 eng d a1095-865700aExploration of parameters in cryo-EM leading to an improved density map of the E. coli ribosome.0 aExploration of parameters in cryoEM leading to an improved densi c10/2008 a24-320 v1643 a

A number of image processing parameters in the 3D reconstruction of a ribosome complex from a cryo-EM data set were varied to test their effects on the final resolution. The parameters examined were pixel size, window size, and mode of Fourier amplitude enhancement at high spatial frequencies. In addition, the strategy of switching from large to small pixel size during angular refinement was explored. The relationship between resolution (in Fourier space) and the number of particles was observed to follow a lin-log dependence, a relationship that appears to hold for other data, as well. By optimizing the above parameters, and using a lin-log extrapolation to the full data set in the estimation of resolution from half-sets, we obtained a 3D map from 131,599 ribosome particles at 6.7A resolution (FSC=0.5).

10aCryoelectron Microscopy10aEscherichia coli10aImage Enhancement10aImage Processing, Computer-Assisted10aRibosomes1 aLeBarron, Jamie1 aGrassucci, Robert, A1 aShaikh, Tanvir, R1 aBaxter, Bill1 aSengupta, Jayati1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/1860654902306nas a2200289 4500008004100000022001400041245013100055210006900186260001200255300000900267490000800276520139700284653001501681653002801696653001901724653002201743653004001765653002501805653002601830653001401856100002201870700002001892700002001912700001701932700001901949856004801968 2008 eng d a1095-865700aParticle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification.0 aParticleverification for singleparticle referencebased reconstru c10/2008 a41-80 v1643 a

As collection of electron microscopy data for single-particle reconstruction becomes more efficient, due to electronic image capture, one of the principal limiting steps in a reconstruction remains particle-verification, which is especially costly in terms of user input. Recently, some algorithms have been developed to window particles automatically, but the resulting particle sets typically need to be verified manually. Here we describe a procedure to speed up verification of windowed particles using multivariate data analysis and classification. In this procedure, the particle set is subjected to multi-reference alignment before the verification. The aligned particles are first binned according to orientation and are binned further by K-means classification. Rather than selection of particles individually, an entire class of particles can be selected, with an option to remove outliers. Since particles in the same class present the same view, distinction between good and bad images becomes more straightforward. We have also developed a graphical interface, written in Python/Tkinter, to facilitate this implementation of particle-verification. For the demonstration of the particle-verification scheme presented here, electron micrographs of ribosomes are used.

10aAlgorithms10aArtificial Intelligence10aClassification10aImage Enhancement10aImage Processing, Computer-Assisted10aMicroscopy, Electron10aMultivariate Analysis10aRibosomes1 aShaikh, Tanvir, R1 aTrujillo, Ramon1 aLeBarron, Jamie1 aBaxter, Bill1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/1861954701670nas a2200289 4500008004100000022001400041245011900055210006900174260001200243300001200255490000600267520076600273653004001039653002501079653002201104653002401126653001301150653002801163100002201191700001701213700001701230700002701247700002101274700001801295700001901313856004801332 2008 eng d a1750-279900aSPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs.0 aSPIDER image processing for singleparticle reconstruction of bio c10/2008 a1941-740 v33 a

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.

10aImage Processing, Computer-Assisted10aMicroscopy, Electron10aModels, Molecular10aMolecular Structure10aSoftware10aUser-Computer Interface1 aShaikh, Tanvir, R1 aGao, Haixiao1 aBaxter, Bill1 aAsturias, Francisco, J1 aBoisset, Nicolas1 aLeith, ArDean1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/19180078