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HTP:一种基于神经网络的预测蛋白质中螺旋跨膜结构域拓扑结构的方法。

HTP: a neural network-based method for predicting the topology of helical transmembrane domains in proteins.

作者信息

Fariselli P, Casadio R

机构信息

Laboratory of Biophysics, Department of Biology, University of Bologna, Italy.

出版信息

Comput Appl Biosci. 1996 Feb;12(1):41-8. doi: 10.1093/bioinformatics/12.1.41.

Abstract

In this paper we describe a microcomputer program (HTP) for predicting the location and orientation of alpha-helical transmembrane segments in integral membrane proteins. HTP is a neural network-based tool which gives as output the protein membrane topology based on the statistical propensity of residues to be located in external and internal loops. This method, which uses single protein sequences as input to the network system, correctly predicts the topology of 71 out of 92 membrane proteins of putative membrane orientation, independently of the protein source.

摘要

在本文中,我们描述了一个用于预测整合膜蛋白中α-螺旋跨膜片段位置和方向的微机程序(HTP)。HTP是一种基于神经网络的工具,它根据残基位于外部和内部环的统计倾向,给出蛋白质膜拓扑结构作为输出。该方法使用单蛋白质序列作为网络系统的输入,能够独立于蛋白质来源,正确预测92个推定膜方向的膜蛋白中71个的拓扑结构。

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