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Michael F. Schmid

Researcher at SLAC National Accelerator Laboratory

Publications -  28
Citations -  877

Michael F. Schmid is an academic researcher from SLAC National Accelerator Laboratory. The author has contributed to research in topics: Contrast transfer function & Cyanophage. The author has an hindex of 13, co-authored 27 publications receiving 537 citations. Previous affiliations of Michael F. Schmid include Massachusetts Institute of Technology & Baylor College of Medicine.

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Measurement of atom resolvability in cryo-EM maps with Q -scores

TL;DR: Q -score analysis of multiple cryo-EM maps of the same proteins derived from different laboratories confirms the reproducibility of structural features from side chains down to water and ion atoms, and can be used at the atom, residue or macromolecule scale.
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Zernike phase contrast cryo-electron microscopy and tomography for structure determination at nanometer and subnanometer resolutions.

TL;DR: Using ZPC cryo-electron tomography (ZPC-cryoET), a similar level of data reduction and higher resolution structures of epsilon15 bacteriophage can be obtained relative to conventional cryoET.

Zernike Phase Contrast Cryo-Electron Microscopy and Tomography for Structure Determination at Nanometer and Subnanometer Resolutions

TL;DR: In this paper, the authors used Zernike phase contrast cryo-electron microscopy (ZPC-cryoEM) for structural determination of macromolecular machines at nanometer and sub-nanometer resolutions.
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Cryo-EM structure of a 40 kDa SAM-IV riboswitch RNA at 3.7 Å resolution.

TL;DR: It is shown that RNA structures can be solved by cryo-EM and present the structures of a 40 kDa SAM-IV riboswitch in the apo form and bound to its ligand S-adenosylmethionine.
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Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge

Catherine L. Lawson, +57 more
- 04 Feb 2021 - 
TL;DR: The 2019 Cryo-EM Model Challenge as discussed by the authors evaluated the quality of models that can be produced from Cryogenic EM maps using current modeling software, evaluating reproducibility of modeling results from different software developers and users and comparing performance of current metrics used for model evaluation, particularly Fit-to-Map metrics.