Membrane proteins, which constitute approximately 20% of most genomes, form two 
main classes: alpha helical and beta barrel transmembrane proteins. Using 
methods based on Bayesian Networks, a powerful approach for statistical 
inference, we have sought to address beta-barrel topology prediction. The 
beta-barrel topology predictor reports individual strand accuracies of 88.6%. 
The method outlined here represents a potentially important advance in the 
computational determination of membrane protein topology.