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Figure 6 | BMC Bioinformatics

Figure 6

From: A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure

Figure 6

Empirical time and memory requirements for structural alignment. Plots of data from Table 1. Filled circles: divide and conquer algorithm; open circles: standard CYK algorithm. Left: Memory use in megabytes on a log-log scale. Lines represent weighted least-squares regression fits to the theoretically expected memory scaling: aN2 log N for divide and conquer (solid line) and aN3 for standard CYK (dashed line). Right: CPU times in seconds on a log-log scale. Lines represent least-squares regression fits to a power law (aNb). According to this fit, divide and conquer time (solid line) empirically scales as N3.24, and standard CYK without traceback (dashed line) scales as N3.29. A line representing O(N4) scaling (the theoretical upper bound on performance) is shown for comparison.

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