Description of DSM - Overview Plot
structure of the discrete state-space model (DSM) used to model
3'-processing control sequences for yeast. All state-to-state
transitions not explicitly labeled have a probability of 1.0.
The hexagonal elements are background elements that can take
on any length in the given range with equal probability. The
functional elements e1-e4 are hexamers, with
individual nucleotide frequencies determined through analysis
with the Gibbs Sampler. Probabilities p1-p4
were optimized empirically in analysis of known processing
sites. The position of the cleavage and polyadenylation is
the center of the c element. Nucleotide probabilities
for the c element were obtained from the 1,352 training
State-space Models (DSM)
DSM is fully defined by its state-to-state transition matrix
(F), its emission matrix (H), and its state
The transition matrix is defined such that Fi,j
= probability of transition from state j to state i.
In the DSM for 3'-processing site identification in yeast, all
elements are either 0 or 1, other than those defined by probabilities
The emission matrix is defined such that Hi,j
= probability of emission of character i when the model
is in state j. In the DSM for 3'-processing site indentification
in yeast, the elements, other than background, are as shown above.
DSMs and their application to biological sequences are described
J.V. (1988) In Spall, J. C. (ed.), Bayesian Analysis of Time
Series and Dynamic Models. Marcel Dekker, New York.
White, J.V., Stultz, C.M. and Smith, T.F. (1994) Protein classification
by stochastic modeling and optimal filtering of amino-acid
sequences Math Biosci, 119, 35-75.
Stultz, C.M., White, J.V. and Smith, T.F. (1993) Structural
analysis based on state-space modeling Protein Sci,