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Classification A new tool was developed Maximum-likelihood based Unsupervised random initial seeds low resolution initial model Probability-weighted assignments all the classes all the projections Likelihood optimization most likely set of parameters Iterative classification reconstruction Scheres, S.H., Gao, H., Valle, M., Herman, G.T., Eggermont, P.P., Frank, J., and Carazo, J.M. (2007). Nature methods 4, 27-29.
Classification A new tool was developed Conformational changes Heterogeneity Conformational change + occupancy (EF-G) Initial 91114 particles ML3D Unsupervised Supervised Scheres, S.H., Gao, H., Valle, M., Herman, G.T., Eggermont, P.P., Frank, J., and Carazo, J.M. (2007). Nature methods 4, 27-29.
Page 1 and 2: Almost lost in translation CryoEM o
Page 3 and 4: Ribosomal structure •Two subunits
Page 5 and 6: Translocation by EF-G ? Pretransloc
Page 7 and 8: CryoEM of ribosomes EM of single pa
Page 9 and 10: Translocation seen by CryoEM EF-G a
Page 11 and 12: At atomic level Flexible fitting Xr
Page 13 and 14: A new twist on translocation Single
Page 15: Dealing with heterogeneity Classifi
Page 19 and 20: Pretranslocation revisited by CryoE
Page 21 and 22: Pretranslocation revisited by CryoE
Page 23 and 24: The path of tRNAs through the ribos

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