DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM.Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution.  In this work, we present a novel method to align sets of single particle images in the 3D space, called DeepAlign. 
DeepAlign
DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM.Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution.  Despite the great development of the techniques involved to solve the biological structures with Cryo-EM in the last years, the reconstructed 3D maps can present lower resolution due to errors committed while processing the information acquired by the microscope.  One of the main problems comes from the 3D alignment step, which is an error-prone part of the reconstruction workflow due to the very low signal-to-noise ratio (SNR) common in Cryo-EM imaging. 
Cryo-EM