Warp

Warp preprocesses cryo-electron microscopy (cryo-EM) data to correct motion and defocus, perform deep-learning–based particle picking and image denoising, and provide real-time quality metrics for high-resolution structural analysis.

Key Features:

• Automated preprocessing: Corrects global and local motion artifacts in micrographs and tomographic tilt series.
• Real-time evaluation: Provides per-micrograph and per-tilt-series monitoring of key acquisition and image-quality parameters.
• Local defocus estimation: Estimates local defocus across micrographs for accurate contrast transfer function assessment.
• Deep-learning models: Applies deep-learning for particle picking and image denoising.
• Integration with downstream tools: Exports processed outputs for particle classification and 3D-map refinement workflows.

Scientific Applications:

• Structural biology: Enables high-resolution imaging and preprocessing of biological specimens for cryo-EM structural determination.
• Dataset quality improvement: Reported improvement in nominal resolution from 3.9 Å to 3.2 Å on a published influenza virus hemagglutinin dataset.

Methodology:

Corrects global and local motion artifacts, estimates local defocus, and applies deep-learning methods for particle identification and image denoising, with computations performed in real time.