Figure 2.

Performance of various similarity measures (noise-free case). (a) ROC curves obtained for the ID scoring scheme using the simple, conditional and partial Pearson correlation (μP, , ), where the diagonal of the cross-correlation matrix is set to 0. (b) ROC curves using the ID scoring scheme and different correlation coefficient, such as the simple Pearson correlation coefficient, where the diagonal of cross-correlation matrix is once 0 (μP (diag0)), and another time the diagonal is 1 (μP (diag1)). Furthermore, the ROC curves using the Spearman (μS (diag1)) and the Kendall (μK (diag1)) correlation coefficient, where the diagonal is 1 in both cases, are shown. (c) Evaluation of the ID scoring scheme using information-theoretic measures: simple, conditional and residual mutual information (μI, and ). (d) Evaluation of the ID scoring scheme using measures based on symbolic dynamics: symbol sequence similarity (), the mutual information of the symbol sequences () and the mean of these both (), as well as the symbol sequence similarity of pairs of time points ( (pairs)) and the conditional entropy of the symbols obtained from the pairs of time points ( (pairs)). (e) The corresponding ROC curves illustrating the performance of the Time Shift scoring scheme using the Pearson correlation μP, applied in addition to the CLR (measure: μS) and the AWE (measure: ) scoring scheme. (f) Performance of the AWE algorithm using the selected symbol based measures included in the this study, for example ROC curves for the symbol sequence similarity (), the mutual information of the symbol sequences (), and the mean of these both ().

Hempel et al. BMC Bioinformatics 2011 12:292   doi:10.1186/1471-2105-12-292
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