DeepEMhancer
DeepEMhancer is a deep learning approach for automatic post-processing of cryo-EM maps, performing masking and sharpening in a single step to improve interpretability.
Cryo-EM maps often require post-processing to improve interpretability due to loss of contrast at high frequencies. DeepEMhancer is a deep learning tool designed to automatically post-process these maps. Trained on pairs of experimental maps and maps sharpened with their corresponding atomic models, DeepEMhancer has learned to perform both masking-like and sharpening-like operations in a single step, reducing noise and revealing more detailed features in the experimental maps without requiring an atomic model.
Estimated resource cost: 0.000527
Categories: Structure Prediction & Folding
Tags: Cryo-EM Nucleotides Proteins
Key Capabilities
- Performs automatic post-processing of cryo-EM maps using a deep learning approach.
- Combines masking-like and sharpening-like operations in a single step.
- Reduces noise levels and enhances map details for improved interpretability.
- Trained on experimental maps and atomic model-sharpened targets to mimic high-quality results.
- Does not require an atomic model for post-processing.
- Improves map similarity to the final atomic model, measured by FSC.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 639 |
| runtime_median | 256 |
| runtime_std | 1138 |
| runtime_90th_percentile | 1794 |
| runtime_max | 8498 |
Similar Tools
- CryoSAMU
- Boltz-1 (AlphaFold3)
- Boltz-2 (AlphaFold3)
- Chai-1 (AlphaFold3)
Ready to submit your job?
Review your configuration, then confirm the estimated credit cost before you run the job. Note that credit estimates are not guaranteed and runtime can vary depending on inputs and settings.
Estimated Credits: 0.000527
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.