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. Author manuscript; available in PMC: 2023 Apr 3.
Published in final edited form as: Nat Methods. 2022 Oct 3;19(10):1234–1242. doi: 10.1038/s41592-022-01605-0

Extended Data Fig. 9. Extended data corresponding to EternaFold development and test set evaluation.

Extended Data Fig. 9

a) Comparing Vienna, CONTRAfold, and EternaFold predictions in predicting free energy of PUM binding. i) Replication of ddG_exp for both PUM WT and mutant binding from (Becker, 2019). The same calculation in Vienna 2 at 37°C shows lower Root-mean-squared error (RMSE) (ii), but higher RMSE at 60°C (iii). CONTRAfold 2 shows no improvement over Vienna at 37°C (iv), but EternaFold shows modest improvement over both (v). b) Package performance for the S-Processed test set is qualitatively similar to results on the ArchiveII-NR test set (cf. Fig. 3b). Error bars represent 95% confidence interval of the mean calculated with 1000 iterations of bootstrapping over n=6 independent datasets, which contain 974 independent constructs total. C) Evaluating SHAPE- and DMS- directed folding. Error bars represent 95% confidence interval of the mean calculated with 1000 iterations of bootstrapping over n=5 independent datasets of RNAs with known secondary structures,, which contain 47 constructs total. d) Potentials learned from EternaFold training and used in SHAPE-directed structure prediction.