On the Importance of Amino Acid Sequence and Spatial Proximity of Interacting Residues for Protein Folding |
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| Authors: | Simon Mitternacht Igor N. Berezovsky |
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| Affiliation: | 1. Department of Informatics;2. Computational Biology Unit, Bergen Center for Computational Science , University of Bergen , Norway;3. Computational Biology Unit, Bergen Center for Computational Science , University of Bergen , Norway |
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| Abstract: | ![]()
Abstract Membrane proteins can be classified among the following five types: (1) type I membrane protein. (2) type II membrane protein. (3) multipass transmembrane proteins. (4) lipid chain- anchored membrane proteins, and (5) GPI-anchored membrane proteins. T. Kohonen's self-organization model which is a typical neural network is applied for predicting the type of a given membrane protein based on its amino acid composition. As a result, the high rates of self-consistency (94.80%) and cross-validation (77.76%), and stronger fault-tolerant ability were obtained. |
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