Computational exploration of structural information from cryo-electron tomograms

Abstract

Cryo-electron tomography aims to act as an interface between in vivo cell imaging and techniques achieving atomic resolution. This attempt to bridge the resolution gap is facilitated by recent software and hardware advances. Information provided by atomically resolved macromolecules and molecular interaction data need to be put into a common framework in order to create a hybrid multidimensional cellular image. A major partner in this enterprise is the development of regularization and pattern recognition techniques, which try to identify macromolecular complexes as a function of their structural signature in cryo-electron tomograms of living cells.