ArticleActa crystallographica. Section D, Structural biology2019
Methods for merging data sets in electron cryo-microscopy.
Article in Acta crystallographica. Section D, Structural biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed.
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- Structural Biology for Target Identification and Validation.Methods in molecular biology (Clifton, N.J.) · 2025Article
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- Mutation-induced shift of the photosystem II active site reveals insight into conserved water channels.The Journal of biological chemistry · 2024Article
- Automated simulation-based membrane protein refinement into cryo-EM data.Biophysical journal · 2023Article
- Structure of the nutrient-sensing hub GATOR2.Nature · 2022Article
- Structure of the human inner kinetochore bound to a centromeric CENP-A nucleosome.Science (New York, N.Y.) · 2022Article
- EMDA: A Python package for Electron Microscopy Data Analysis.Journal of structural biology · 2022Article
- Illumination of serotonin transporter mechanism and role of the allosteric site.Science advances · 2021Article
- Structural basis of Ty3 retrotransposon integration at RNA Polymerase III-transcribed genes.Nature communications · 2021Article
- Structural basis of chromatin regulation by histone variant H2A.Z.Nucleic acids research · 2021Article
- On-grid and in-flow mixing for time-resolved cryo-EM.Acta crystallographica. Section D, Structural biology · 2021Article
- The structure of an Hsp90-immunophilin complex reveals cochaperone recognition of the client maturation state.Molecular cell · 2021Article
- Folding of cohesin's coiled coil is important for Scc2/4-induced association with chromosomes.eLife · 2021Article
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3 authors.
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Abstract
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.
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