bioRxiv (Cold Spring Harbor Laboratory) · 2021 · 15 citations · 48 references
Life SciencesBioinformaticsComputer ScienceComputer VisionStructural BioinformaticsStructural BiologyCryo-electron MicroscopyDeep LearningDigital Image ProcessingElectron MicroscopyImage ProcessingStructural RefinementConvolutional Neural NetworksCryo-electron Microscopy Data AnalysisCryo-electron Microscopy InterpretationCryo-electron Microscopy ReconstructionCryo-electron Microscopy Structure AnalysisCryo-electron Microscopy Structure DeterminationRefinementSingle-particle Analysis
1 Abstract We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a Variable-metric gradient Descent algorithm with Adaptive Moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on twelve publicly available cryo-EM data sets.
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