Copyright © 2004 Elsevier Ltd. All rights reserved.
Scoring hidden Markov models to discriminate β-barrel membrane proteins
Received 4 February 2004;
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Abstract
A new method is presented for identification of β-barrel membrane proteins. It is based on a hidden Markov model (HMM) with an architecture obeying these proteins’ construction principles. Once the HMM is trained, log-odds score relative to a null model is used to discriminate β-barrel membrane proteins from other proteins. The method achieves only 10% false positive and false negative rates in a six-fold cross-validation procedure. The results compare favorably with existing methods. This method is proposed to be a valuable tool to quickly scan proteomes of entirely sequenced organisms for β-barrel membrane proteins.
Author Keywords: β-Barrel membrane proteins; Hidden Markov model; Log-odds score






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