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Figure 5 | Algorithms for Molecular Biology

Figure 5

From: Analysis of computational approaches for motif discovery

Figure 5

Multiple linear regression result. (a)The best-fit line. Marks on the x-axis index the datasets, which are arrayed so that the estimated values of the dependent variable (the assessment scores) are in a straight line. For each dataset, the red dot is the assessment score, measured by the best correlation coefficient score nCC (see [9]) among all the tools, and the circle on the blue line shows the estimated value of the best-fit linear model. (b)Residues of the regression versus estimated nCC score. The x-axis is the estimated value of the dependent variable, the y-axis is the corresponding residue. This plot shows little indication of inequality of variance, which is an important assumption of linear regression.

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