I understand how a Hidden Markov Model is used in genomic sequences, such as finding a gene. But I don't understand how to come up with a particular Markov model. I mean, how many states should the model have? How many possible transitions? Should the model have a loop?
How would they know that their model is optimal?
Do they imagine, say 10 different models, benchmark those 10 models and publish the best one?