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the predictor by means of ROC (Receiver Operating Characteristic) curves. We need to
define a few terms in order to use these:
Test positives: Residues with
Test negatives: Residues with
HS(i)greater than or equal to a certain threshold.
HS(i)less than a certain threshold.
Gold standard positives: ! Residues annotated as hinges in the Hinge Atlas.
Gold standard negatives: ! Residues which are not in hinges according to the Hinge Atlas
annotation.
True positives (TP): Those residues that are both test positives and gold standard
positives.
True negatives (TN): Residues that are both test negatives and gold standard negatives.
False positives (FP): Residues that are test positives and gold standard negatives.
False negatives (FN): Residues that are test negatives and gold standard positives.
sensitivity
specificity
1 !
specificity
TP
=
TP + FN
TN
=
FP + TN
FP
=
FP + TN
The ROC curve is simply a plot of the true positive rate (same as sensitivity) vs. false
positive rate (1-specificity), for each value of the threshold, as the threshold is varied
from +1 to -1, a range which included all possible values of
76
HS(i)
. For a good predictor,
the true positive rate will increase faster than the false positive rate as the threshold is