The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/205d29e8-88c3-4ba0-ada9-80de95b45a58

Bharadwaj, Alok; de Bruin, Reinier; Jakobi, Arjen (2025): EMmerNet deep learning model for ColabScale. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/205d29e8-88c3-4ba0-ada9-80de95b45a58.v1

Categories

• Other Biological Sciences
• Other Physical Sciences
• Biochemistry and Cell Biology
• Physical Sciences
• Biological Sciences

Keywords

cryoEM map optimisation postprocessing protein structure

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Alok Bharadwaj, Reinier de Bruin, Arjen Jakobi

Tensorflow model for local map optimisation in ColabScale. The model allows context-inclusive cryoEM map optimisation mimicking the physics-informed map optimisation procedures in LocScale-2.0. It has been trained on publicly available cryoEM volumes obtained from the Electron Microscopy Data Bank (EMDB).

History

• 2025-05-28 first online, published, posted

Publisher

4TU.ResearchData

Format

Tensorflow model in hdf5 format

References

• https://github.com/cryoTUD/ColabScale.git
• https://doi.org/10.5281/zenodo.15485093

Derived from

• https://doi.org/10.5281/zenodo.8211668

Funding

• PHAGOSCOPY: Dissecting cell-autonomous immunity with ex vivo electron cryo-microscopy (grant code 852880) [more info...] European Research Council

Organizations

Delft University of Technology, Kavli Institute of Nanoscience, Department of Bionanoscience