Benchmark results.

<p>A comparison of three secondary structure prediction algorithms, using shape data from Deigan et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045160#pone.0045160-Deigan1" target="_blank">[15]</a> for the three RNA molecules, yeast aspartyl tRNA (asp-tRNA), hepatitis C virus internal ribosomal entry site (HCV IRES), and the P546 domain from the bI3 group I intron (P546), along with shape data from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045160#pone.0045160-Kladwang1" target="_blank">[26]</a> for three additional RNA molecules, <i>E. coli</i> phenylalanine tRNA (phe-tRNA), <i>E. coli</i> 5S ribosomal RNA (5S rRNA), and <i>F. nucleatum</i> glycine riboswitch (glycine). The benchmark results are tabulated for (A) RNAsc+shape, (B) RNAstructure+shape, and (C) RNAstructure (with no shape data). Sensitivity is abbreviated by sens., positive predictive value is abbreviated by ppv. The average pointwise entropy, Morgan-Higgs structural diversity, and the expected distance of the computed probabilities to the probing data are abreviated by ave ent., str. div., and edist., respectively. Not shown: results for medloop and <i>V. vulnificus</i> adenine riboswitch (1Y26), for which all three methods have optima sensitivity and ppv values of 1.0.</p>