New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both beta-barrel and all-alpha membrane proteins with high accuracy and a low rate of false positives and false negatives. These methods have been integrated in a suite of programs to filter proteomes of Gram-negative bacteria, searching for new membrane proteins.