LAUSR

RNA is a versatile molecule that plays essential roles in living organisms, ranging from information transfer to sensing, enzymatic, structural functions, and regulation (1). High-throughput sequencingmethods continue to identify new noncodingRNA transcripts in cells, and their function (or lack of) remains an active topic of research.DesignedRNAs also play an increasingly important role in the fields of nucleic acid nanotechnology and synthetic biology, in which they are engineered for diagnostic aswell as therapeutic applications (2,3). Potential new therapies for COVID-19 involve targeting structural motifs in the folded RNA genome of SARS-CoV-2 to impede its function (4), highlighting the need for modeling the structure of large RNA sequences. Recently, the RNA-Puzzles computational resource evaluation has been introduced (5) to assess different algorithms for blind de novo RNA structure prediction, an RNA equivalent of the long-running CASP-blind prediction experiment for protein folding software. It is an exciting time for RNA structure modeling, with new experimental data sets and new methods for RNA modeling being introduced. The increase in data has inspired novel modeling approaches and combinations of existing techniques. In partic-