Hidden markov models

We introduce the theory of Hidden Markov Models, with a brief historical description, and we describe some computational biology. In particular, we describe the theoretical basics of these methods with particular attention to the three fundamental statistical problems and summarize, striking applications of hidden Markov models to computational biological studies. HMMs is a probabilistic framework for modelling and analyzing epigenetic studies; they are frequently used for modelling biological sequences, for example, in gene finding, profile searches, multiple sequence alignment and regulatory site identification. For this purpose, in particular, we contribute to give a general understanding of the nature and relevance of these probabilistic methods, describing some simple examples, with particular focus on the problem of CpG islands finding.