A novel method is developed to model and predict the transmembrane regions of 
beta-barrel membrane proteins. It is based on a Hidden Markov model (HMM) with 
architecture obeying those proteins' construction principles. The HMM is trained 
and tested on a non-redundant set of 11 beta-barrel membrane proteins known to 
date at atomic resolution with a jack-knife procedure. As a result, the method 
correctly locates 97% of 172 transmembrane beta-strands. Out of the 11 proteins, 
the barrel size for ten proteins and the overall topology for seven proteins are 
correctly predicted. Additionally, it successfully assigns the entire topology 
for two new beta-barrel membrane proteins that have no significant sequence 
homology to the 11 proteins. Predicted topology for two candidates for 
beta-barrel structure of the outer mitochondrial membrane is also presented in 
the paper.