Section outline

    • Alignment, classification and averaging of 2D images. File PDF

      Signal and noise in electron microscopy images. Sampling theorem. Fundamental parameters of the EM imaging. Low-pass filtering. Particle selection and masking. Noise reduction by averaging. Automatic particle selection. Alignment: rotation and translation. Sample heterogeneity. Classification: Principal Component Analysis and two-dimensional image classification methods. Ascending hierarchical classification method. K-means method. Examples of classification in negative staining and cryo EM.

    • 3D reconstruction and validation File PDF

      Reconstruction of the three-dimensional model from two-dimensional images. Euler angles and projections. Projection theorem. (1) Determination of the orientation of the particles: tomography, Random Conical Tilt method, common line method. (2) Reconstruction. CTF correction. Heterogeneity. Method based on Bayesian statistical analysis (Relion software).

      Validation of the structural model. Two examples of incorrect reconstruction. Resolution. Some examples of proteins whose structure has been determined at high resolution with cryo-EM technique.