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. 2013 Jul 11;41(17):8220–8236. doi: 10.1093/nar/gkt596

Figure 1.

Figure 1.

Benchmarking the sensitivity of sliding-window RNA structure prediction. (A) Benchmarking pipeline for simulating the experimental conditions of sliding-window methodologies using known RNA structure alignments. (B) The relative sensitivities of conserved RNA secondary structure prediction algorithms are plotted for randomly sampled, native RFAM subalignments in function of the amount of sequences, window length and MPI. Opaque bars represent high-confidence predictions (RNAz probability ≥ 0.9, SISSIz Z-score ≤ −4), while translucent bars represent lower-confidence predictions (RNAz probability ≥ 0.5, SISSIz Z-score ≤ −2). Each bar represents the outcome of 200 sampled alignments with RNAz version 2.0 (using options ‘-f–d–l’), SISSIz using default parameters and SISSIz with RIBOSUM scoring (option ‘-j’) for all indicated window sizes, sequence depths and MPI ranges. The latter are indicated by their bounded values on the x-axis.