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h c = number of times residues of a particular class c occurred in hinges.
These can be used to estimate various probabilities as follows:
p(a c) = d c /D is the prior probability of c -- in other words, the probability that residues
of class c occur anywhere in the dataset.
p(a c h) = h c /H is the conditional probability that a residue belongs to class c,
given it is a hinge.
A quantity that is of interest in hinge prediction is the posterior probability
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p(h a c ),
the probability that a residue is a hinge given it is in ac. We obtain this from Bayes’ rule:
p(h a c) = p(a c h) " p(h)
p(a c)
Equation 1
= h c
d c
H
Where the prior probability that a residue is a hinge is given by p ( h)
= ( ) .
D
We further define the hinge index HI, similar to the domain linker index used in
Armadillo[45]:
HI(a c) = log 10
Equation 2
p(a c h)
p(a c )