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The plot generates the shape of a saturation curve, which is common for many biological and enzymatic reactions.

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Figure 4 shows the plot generated in Microsoft Excel 2007 comparing the observed to expected ratio for all 400 possible dipeptides and the subset of 49 YY1 core-forming dipeptides which exhibits no difference in the distribution of the subset.

Since there were 10 different combinations of prevalence of the prognostic factor and magnitude of the interaction effect and 10 trials for each combination, the plot generated 100 points.

Significance is noted in the plots generated for this analysis.

Similar conclusions were drawn from the plots generated for data sets corresponding to various SCOP classes.

Examples of some of the plots generated by Seed are shown in the supplementary information.

The distribution of the d/a plots from 70-mer oligonucleotide microarray data are very similar to the plots generated from the Affymetrix data.

The plots generated by MatVPC were compared with plots constructed by the gold standard tools in the pharmacometrics community, PsN (with NONMEM) and Monolix, 43 and the results were interchangeable across all case studies.

In addition, the plots generated during real-time LATE-PCR are linear and, therefore, the fluorescence intensities reached after a given number of cycles are proportional to the number of target sequences present at the beginning of the reaction.

The PCA plot generates two-dimensional plots of the first two components of the replicates for all the samples, allowing us to visualize the variance among the replicates.

At the end of the reaction, the amplification plot generated was viewed on a log scale with the system's default threshold.

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