Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks
Figure 2
Philius training and decoding graphical models.
(a) Training DBN: only the amino acid and the topoLabel are observed in each frame. The topoLabel is used to constrain the hidden state using an observed child node. The color of the edge between two nodes indicates the type of relationship: black is deterministic, and red is random. (b) First stage decoding DBN: the topoState is hidden and dependent on the state and the previous topoState, and specifies the behavior of pType, an additional hidden variable. (c) Second stage decoding DBN: the observed amino acid node and the duration modeling nodes have been removed, and Pr[topoStatei] is defined by the posterior probabilities computed in the first stage using the virtual evidence node topoVE.