S21-193 Prediction of RNA structure with equivariant neural networks A new deep-learning system called Atomic Rotationally Equivariant Scorer (ARES) significantly improves the prediction of RNA structures over previous artificial intelligence (AI) models. Raphael Townshend Stephan Eismann Andrew Watkins Ron Dror Rhiju Das
S22-041 Reconfiguration of Tabular Data for Discovery of Deep Interaction Features and its Applications in Analysis of Multidimensional Data Stanford scientists have developed a high-performance informatics framework for deep learning analyses of high dimensional (HD) omics data. Md Tauhidul Islam Lei Xing