Abstract
New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both β-barrel and all-α 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.
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Selected References
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