Speaker
Description
Cryo-electron microscopy is a revolutionary technique that can Provide 3D density maps at near atomic resolution. However, map validation is still an open issue in the field. Despite several efforts from the community, it is possible to overfit the reconstructions to noisy data. Here, inspired by modern statistics, we develop a novel methodology that uses a small independent particle set to validate the 3D maps. The main idea is to monitor how the BioEM [1] probability evolves over the
control set during the refinement. High-quality maps should increase in probability for higher refinement iterations. We then show that the similarity between the probability distributions of the two reconstructions from the gold-standard procedure is an additional quality indicator. We tested the method over several systems, some which were overfitted. Our method is able to clearly discriminate the overfitted sets from the non-overfitted ones. We conclude that having a control particle set, not used for the refinement, is essential for cross-validating cryo-EM maps.
References:
1. P. Cossio and G. Hummer. Journal of Structural Biology 184, 427-437 (2013).
