Machine learning helps to determine the diverse conformations of RNA molecules

An innovative technique called HORNET uses atomic force microscopy and a machine-learning architecture called a deep neural network to recapitulate the 3D structures of individual RNA molecules. This method enables the study of the structure and dynamics of RNAs that adopt flexible and variable conformations under biologically relevant conditions. A combination of atomic force microscopy and deep neural networks defines the structures of individual RNA molecules.