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Figure 3 Plot of the proportion of experts who assessed a training-set molecule-pair as being similar against the ECFP4 similarity for that molecule-pair.
It's a plot of the proportion of American men between the ages of 24 and 54 (in the prime of their working lives) who've participated in the labor force since the 1950s (i.e., have been working or looking for work) and the proportion actually employed.
In order to calibrate the sensitivity, short-term specificity and long-term specificity, "a plot of the proportion of specimens positive in the assay versus time since seroconversion" is generated (also later referred to as "the curve").
(B ) Plot of the proportion of BiP in species II as a function of protein concentration.
The linear plot of the proportion of SNPs shared between the three pairwise comparisons between the races.
(C ) Plot of the proportion of BiP in species III as a function of protein concentration as in 'B'.
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Fig. 7 The influence of sample size (number of plots) on the proportion of variation in wood volume explained by LiDAR metrics coefficient of determination (a) and root mean square error (b)—at the 1 ha plot scale.
Fig. (4A, C, and 4E) shows receiver operator characteristics (ROC) (red curves) and plots of the proportion of false positive predictions among all predicted disease genes (blue curves).
Manhattan plots of the proportion of genetic variance explained by each 1 Mb window across the genome for GRN in Angus and Limousin are in Figure 5.
ROC curves are supported by plots of the proportion of false positives among all predicted disease genes at a given threshold.
Manhattan plots of the proportion of genetic variance explained by 10-SNP moving windows for the traits analyzed (milk yield, fat percentage, protein percentage, direct calving ease, maternal calving ease, body depth, rump width, stature, strength. Additional file 3: Tables S2-S4.
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