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Sarver, M., Zirbel, C.L., Stombaugh, J., Mokdad, A.WebFR3D, a webserver for symbolic and geometric searching of RNA 3D structures.(2013) R3D Align web server for global nucleotide to nucleotide alignments of RNA 3D structures. Rahrig, R.R., Petrov, A.I., Leontis, N.B.(2010) R3D Align: global pairwise alignment of RNA 3D structures using local superpositions. R3D Align, an application for detailed nucleotide to nucleotide alignments of RNA 3D structures.(2012) Comprehensive survey and geometric classification of base triples in RNA structures. Abu Almakarem, A.S., Petrov, A.I., Stombaugh, J., Zirbel, C.L.RNA Base Triple Atlas, a collection of motifs consisting of two RNA basepairs.(ed.), RNA 3D structure analysis and prediction. Representative RNA 3D Structure Sets, classification of RNA structures by sequence, structure, and species.(2013) Automated classification of RNA 3D motifs and the RNA 3D motif atlas. Petrov, A.I., Zirbel, C.L., Leontis, N.B.RNA 3D Motif Atlas, a representative collection of RNA 3D internal and hairpin loop motifs.RNA Basepair Catalog, a collection of representative base pairs and heatmaps for each base pair family.(2008) DNA conformations and their sequence preferences. Svozil, D., Kalina, J., Omelka, M., Schneider, B.(2017) DNAproDB: an interactive tool for structural analysis of DNA-protein complexes. Sagendorf, J.M., Berman, H.M., Rohs, R.DNAproDB, an interactive tool for structural analysis of DNA-protein complexes.This technology is part of a portfolio of innovations aimed at fighting the COVID-19 pandemic. EternaFold2 can infer properties directly from sequence and will be fundamental to the next generation of machine-learning-based nucleic acid design. Various algorithms have described and implemented machine learning approaches for either predicting structure from sequence, or predicting properties from structure, but no methods exist that unite both of these steps.

Accurate prediction is increasingly important for a range of disciplines, including genome editing, vaccines, and therapeutics. 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.