Methods for merging data sets in electron cryo-microscopy
| Autor: | Ananthanarayanan Kumar, Max E. Wilkinson, Ana Casañal |
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| Rok vydání: | 2019 |
| Předmět: |
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Molecular Microscope Computer science Cryo-electron microscopy single-particle processing Datasets as Topic macromolecular substances Electron law.invention 03 medical and health sciences Imaging Three-Dimensional 0302 clinical medicine Structural Biology law Microscopy Image Processing Computer-Assisted 030304 developmental biology Flexibility (engineering) 0303 health sciences Pixel Orientation (computer vision) Cryoelectron Microscopy Detector RELION Single Molecule Imaging merging of data cryo-EM Ccp-EM Algorithm 030217 neurology & neurosurgery |
| Zdroj: | Acta Crystallogr D Struct Biol Acta Crystallographica. Section D, Structural Biology |
| ISSN: | 2059-7983 |
| DOI: | 10.1107/s2059798319010519 |
| Popis: | A workflow to combine cryo-EM data collected at different magnification. Recent developments have resulted in electron cryo-microscopy (cryo-EM) becoming a useful tool for the structure determination of biological macromolecules. For samples containing inherent flexibility, heterogeneity or preferred orientation, the collection of extensive cryo-EM data using several conditions and microscopes is often required. In such a scenario, merging cryo-EM data sets is advantageous because it allows improved three-dimensional reconstructions to be obtained. Since data sets are not always collected with the same pixel size, merging data can be challenging. Here, two methods to combine cryo-EM data are described. Both involve the calculation of a rescaling factor from independent data sets. The effects of errors in the scaling factor on the results of data merging are also estimated. The methods described here provide a guideline for cryo-EM users who wish to combine data sets from the same type of microscope and detector. |
| Databáze: | OpenAIRE |
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