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Topic: HMM

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	BioMed Central \| Full text \| HMM Logos for visualization of protein families
		The final definition of an HMM logo is as follows; see Figure 2 for a typical example.
		HMM Logos highlight regions which distinguish homologous subfamilies from each other and thereby facilitate the detection of subfamily determinants.
		HMM Logos immediately made this particularity visible; we were not aware of it before.
	www.biomedcentral.com /1471-2105/5/7 (3958 words)

	Pfam: Search Pfam
		VAV_HUMAN or Q91437) then you can see the Pfam domains on the sequence instantaneously.
		identifier for your sequence, you can perform a slower, HMM search by giving your sequence below.
		The Standard Pfam search is the most sensitive method for finding complete domains.
	www.sanger.ac.uk /Software/Pfam/search.shtml (273 words)

	Hidden Markov Models
		A hidden Markov model (HMM) is a five-tuple (Omega_X,Omega_O,A,B,pi).
		Suppose that we have a set W of words and a separate training set for each word.
		The extension to HMMs with factored state spaces (e.g., see Figure 4) is graphically straightforward.
	www.cs.brown.edu /research/ai/dynamics/tutorial/Documents/HiddenMarkovModels.html (1359 words)

	hmm
		The underlying assumption of the HMM is that the speech can be well characterized as a parametric random process and that the parameters of the stochastic process can be estimated in a well defined manner.
		HMM is a doubly embedded stochastic process with an underlying stochastic process that is not directly observable, but can be observed only through another set of stochastic processes that produce the sequence of observations.
		A HMM is characterized by 3 matrices viz., A, B and PI.
	www.cnel.ufl.edu /~yadu/hmm.html (597 words)

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