Geometric machine learning informed by ground truth: Recovery of conformational continuum from single-particle cryo-EM data of biomolecules
E. Seitz, F. J. Acosta-Reyes, S. Maji, P. Schwander, J. Frank
This paper introduces an unsupervised geometric machine learning approach to recover conformational continua from single-particle cryo-EM data using simulated ground-truth datasets, showing improved results over previous methods.
bioRxiv · Jun 18, 2021 · PreprintBiophysics