How does cryo-EM structure determination workflow differ from X-ray crystallography in terms of computational analysis?

Cryo-EM computational analysis has distinct characteristics: 1) Data collection - millions of 2D particle images from frozen-hydrated samples; no crystallization required. 2) Particle picking - identify and extract particles using template matching or neural networks (Topaz, crYOLO). 3) 2D classification - group particles by similar views; remove bad particles and heterogeneous classes. 4) 3D reconstruction - iterative refinement of 3D map from 2D projections; ab initio or reference-based (RELION, cryoSPARC). 5) Resolution determination - FSC (Fourier Shell Correlation) between half-maps. 6) Heterogeneity - 3D classification reveals conformational states; continuous heterogeneity methods emerging. 7) Model building - fit atomic models into density maps; automated tools (ModelAngelo) and manual building (Coot); real-space refinement (Phenix). 8) Validation - map-model FSC, geometry checks. Advantages: captures multiple states, no size limitations; challenges: resolution dependent on particle behavior, computational demands.