 In the second half of the 1980s, HMMs began to be applied to the analysis of biological sequences, in particular DNA.Since then, they have become ubiquitous in the field of bioinformatics.In the hidden Markov models considered above, the state space of the hidden variables is discrete, while the observations themselves can either be discrete (typically generated from a categorical distribution) or continuous (typically from a Gaussian distribution).