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Journal of Biomolecular Structure and Dynamics Volume 18, 2001 - Issue 4
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Original Articles

Artificial Neural Network Model for Predicting Membrane Protein Types

Yu-Dong Cai Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China
,
Xiao-Jun Liu Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh, EH9 3JT, UK
&
Kuo-Chen Chou Computer-Aided Drug Discovery, Upjohn Laboratories, Kalamazoo, MI, 49001-4940, USA
Pages 607-610 | Received 19 Sep 2000, Published online: 15 May 2012
 
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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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