Hidden Markov Models for gene finding (caricature)
Now the observer wants to infer the actual sequence of
states of the Markov model that caused the observed
emissions. This sequence is called the path through the
hidden Markov model. The (posterior) probability of any
given path is easy to calculate, and it is computationally
inexpensive to infer the most likely path for a given
sequence of emissions (using the so-called Viterbi
algorithm). This path gives some hypothesis for the
location of the genes. It is also easy to calculate
probabilities that a predicted gene is actually a gene
(under the assumptions of the model).