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esidues (62). As is customary we also report the specificity (true negatives / gold
standard negatives). hNMb had the highest specificity, followed closely by FO and
TLSMD. Stonehinge and hNMd have lower specificity, reflecting a tendency to predict
the correct hinge location but also to report a wide region about the annotated hinge
location as a predicted hinge. We also evaluated the statistical significance by
postulating a null hypothesis that the test positive residues were taken randomly and
without replacement from the population of residues in HAG. Under this hypothesis, the
mean frequency of hinges is the same in the test positive set as in HAG. For each
predictor, we computed the probability of finding the observed number or more of
annotated hinge residues in a randomly selected set equal in size to the number of test
positives reported by the predictor. We computed this quantity using the cumulative
hypergeometric distribution. Clearly, FO has the highest statistical significance (lowest
probability that the null hypothesis is correct). hNMb has a higher (but still impressive)
p-value than FO.
Part of the reason FO had lower specificity than hNMb is because FO only attempts cuts
on the backbone at four residue intervals, while hNMb probes every possible pair of
residues as a possible continuous domain boundary. As a result, FO predicts four-residue
wide windows as possible hinge locations, with some uncertainty as to the exact location
of the best putative hinge. hNMb, on the other hand, reports two-residue windows as
putative hinge locations, and these are presumed to be the best choice of hinge possible
for that method.
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