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Explore the complexity of proteins with an expanded CryoET data processing pipeline

Published online by Cambridge University Press:  30 July 2021

Muyuan Chen ,
David Chmielewski ,
Wah Chiu  and
Steven Ludtke
Muyuan Chen
Affiliation:
Baylor College of Medicine, United States
David Chmielewski
Affiliation:
Stanford University, United States
Wah Chiu
Affiliation:
School of Medicine, Stanford University, Stanford, California, United States
Steven Ludtke
Affiliation:
Baylor College of Medicine, United States

Abstract

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Type
Cryo-electron Tomography: Present Capabilities and Future Potential
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 2816 - 2817
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Chen, M., Ludtke, S. J. (2021) Deep learning based mixed-dimensional GMM for characterizing variability in CryoEM. arXiv:2101.10356Google Scholar
Chen, M., Bell, J. M., Shi, X., Sun, S. Y., Wang, Z., Ludtke, S. J. (2019). A complete data processing workflow for CryoET and subtomogram averaging. Nature Method. 2019.CrossRefGoogle Scholar