Artificial neural network model for predicting membrane protein types

被引:21
作者
Cai, YD
Liu, XJ
Chou, KC
机构
[1] Univ Edinburgh, Inst Cell Anim & Populat Biol, Edinburgh EH9 3JT, Midlothian, Scotland
[2] Upjohn Labs, Comp Aided Design, Kalamazoo, MI 49001 USA
[3] Chinese Acad Sci, Shanghai Res Ctr Biotechnol, Shanghai 200233, Peoples R China
关键词
D O I
10.1080/07391102.2001.10506692
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:607 / 610
页数:4
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