Generalized hidden Markov model

Kulp, D Haussler, D Reese, M. G. Eeekman, F. H. (1996). A generalized hidden Markov model for the recognition of human genes in DNA. Ismb 4,134-42. 

Stanke, M., Schoffmann, O., Morgenstern, B., and Waack, S. (2006) Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics 7, 62. 

Generalized Hidden Markov Model Used In PASS... 

A Hidden Markov Model (HMM) is a general probabilistic model for sequences of symbols. In a Markov chain, the probability of each symbol depends only on the preceding one. Hidden Markov models are widely used in bioinformatics, most notably to replace sequence profile in the calculation of sequence alignments. 

A mathematically very different approach, which is formally equivalent to the generalized profile method, uses so called Hidden Markov Models (HMMs). A more... 

The dynamic-system model is a natural choice for statistical generation of FO contours since it is well suited to the job of generating continuous trajectories. If it has any weaknesses, we can point to the facts that the state trajectories are limited to being those of a first-order filter, the noise terms have to be Gaussian and the traimng process can be quite intricate. An alternative is to use hidden Markov models (HMMs) since these are in general easier to train and allow more complexity with regard to noise/covariance terms. 

One can obtain the labels and offsets of every term from the text. There are various statistical models that can be used in this process. Hidden Markov model (HMM) is the simplest of dynamic Bayesian model. HMM is a finite set of states, each of which is associated with a (generally mirltidimensional) probability distribution [41]. HMMs ate a form of generative models that define a joint probabihty... 

Localization and delocahzation for a periodic pinning model may be characterized once again by looking at the free energy. As we will explain in Chapter 3, it is possible to generalize the renewal theory approach introduced in Section 1.2, however the algebra is substantially more complex and the point process hidden behind periodic models is not a standard renewal, but rather a Markov renewal (see Chapter 3). This will allow precise computations, but for the moment we observe that ... 

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