A new deep-learning system called Atomic Rotationally Equivariant Scorer (ARES) significantly improves the prediction of RNA structures over previous artificial intelligence (AI) models.
Stanford researchers have developed a framework describing an end-to-end approach that infers experimental properties directly from nucleic acid sequence, using a principled statistical mechanical representation of the structure ensemble.