Alignment hidden

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. 

Using the word occult to describe recently discovered energies like X-rays, of course, invokes both its meaning as hidden from view and its supernatural connotation. Moreover, it aligns the kind of occult forces Crowley describes in Moonchild with any other physical energy or force known to mainstream science, and draws upon the still scientifically debated theories of a life force posited by tum-of-the-century vitalism. 

It can be difficult if not impossible to find the domain structure of a protein of interest from the primary literature. The sequence may contain many common domains, but these are usually not apparent from searches of literature. Articles defining new domains may include the protein, but only in an alignment figure, which are not searchable. Perhaps, with the advent of online access to articles, the full text including figures may become searchable. Fortunately there have been several attempts to make this hidden information available in away that can be easily searched. These resources, called domain family databases, are exemplified by Prosite, Pfam, Prints, and SMART. These databases gather information from the literature about common domains and make it searchable in a variety of ways. They usually allow a researcher to look at the domain organization of proteins in the sequence database that have been precalculated and also provide a way to search new sequences... 

Tanaka, H., Ishikawa, M., Asai, K., and Konagaya, A. (1993). Hidden Markov models and iterative aligners study of their equivalence and possibilities. Ismb 1, 395—401. 

To assist the interpretation of family memberships, overall probability scores for both global and motif matches are provided for top hit families. The global score is computed from the BLAST e-value, the SSEARCH score, and the percentage of sequence identity at overlapped length ratio in SSEARCH alignment. The motif score is computed from the ratio of mismatched amino acids to ProSite patterns, and the hidden Markov motif match score. Family information from ProClass, with hypertext links to all other major family... 

By employing a very strong external field, a gedankexperiment may be set up whereby the natural thermal motion of the molecules is put in competition with the aligning effect of the field. This method reveals some properties of the molecular liquid state which are otherwise hidden. In order to explain the observable effects of the applied fields, it is necessary to use equations of motion more generally valid than those of Benoit. These equations may be incorporated within the general structure of reduced model theory " (RMT) and illustrate the use of RMT in the context of liquid-state molecular dynamics. (Elsewhere in this volume RMT is applied to problems in other fields of physics where consideration of stochastic processes is necessary.) In this chapter modifications to the standard methods are described which enable the detailed study of field-on molecular dynamics. 

Eddy, S. R., Multiple alignment using hidden Markov models. Ismb, 1995. 3 p. 114-20. 

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