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PubMed · 15065683

Model-based particle picking for cryo-electron microscopy.

H Chi Wong·Jindong Chen·Fabrice Mouche·Isabelle Rouiller·Marshall Bern
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Abstract

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.

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Adenosine TriphosphatasesAlgorithmsAnimalsCryoelectron MicroscopyElectronic Data ProcessingFourier AnalysisHemocyaninsImage EnhancementImage Processing, Computer-AssistedImaging, Three-DimensionalLikelihood FunctionsModels, MolecularModels, StatisticalMolluscaNuclear ProteinsParticle SizePattern Recognition, AutomatedProtein ConformationSoftware DesignJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, P.H.S.

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H Chi Wong, Jindong Chen, Fabrice Mouche, Isabelle Rouiller, Marshall Bern. Model-based particle picking for cryo-electron microscopy.. https://doi.org/10.1016/j.jsb.2003.05.001

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