Yes, at multiple levels. You can do a heterogeneous refinement that takes the structures and solves for n number of averages, trying to use something like PCA t

Yes, at multiple levels. You can do a heterogeneous refinement that takes the structures and solves for n number of averages, trying to use something like PCA to maximize the distances between the averages. Particles get sorted into the average they contribute most constructively to. That works well for compositional heterogeneity or large conformational differences. For minor differences, there's something called the guassian mixture model (lots of software packages have similar, but GMM is EMAN2's version). https://blake.bcm.edu/emanwiki/EMAN2/e2gmm https://blake.bcm.edu/emanwiki/EMAN2/e2gmm What you can get out of the other end is a volume series, that shows reconstructed 3D volumes along various axes of conformational variability. This quickly turns into a multi-dimensional problem, but it has been very successful in, for instance, seeing all the different states of an active ribosome.