PROPOSAL OF ALIGNMENT-INDEPENDENT CLASSIFICATION OF ELECTRON-MICROSCOPIC IMAGES WITH HELICAL SYMMETRY AND ITS APPLICATION TO RECONSTITUTED THIN-FILAMENTS OF SKELETAL-MUSCLE

A new method to classify noisy images of filaments with helical symmetry was developed and applied to cryo-electron microscopic images of skeletal muscle thin filaments. In this method, images are transformed to minimum data sets which are independent of the relative view parameters, such as rotation of a three-dimensional object around the axis of helical symmetry, translation along an axis and operation to make a filament upside down, and classified by a principal component analysis. By this method, atypical data can be identified without aligning procedures, and small structural changes and polymorphic variation are expected to be detected objectively.