Beta barrel trans-membrane proteins: Enhanced prediction using a Bayesian approach |
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Authors: | Taylor Paul D Toseland Christopher P Attwood Teresa K Flower Darren R |
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Institution: | The Jenner Institute, University of Oxford, Compton,Newbury, Berkshire, RG20 7NN, UK. |
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Abstract: | 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. |
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