PREDICTION OF THE SECONDARY STRUCTURE OF PROTEINS FROM THE AMINO-ACID-SEQUENCE WITH ARTIFICIAL NEURAL NETWORKS

被引：10

作者：

SCHNEIDER, G ^{[1
]}

WREDE, P ^{[1
]}

机构：

[1] FREE UNIV BERLIN,FB PHYS,AG BIOPHYS,ARNIMALLEE 14,D-14195 BERLIN,GERMANY

来源：

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION IN ENGLISH | 1993年 / 32卷 / 08期

关键词：

D O I：

10.1002/anie.199311411

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Secondary structures of amino acid sequences can be predicted with over 70% accuracy in Heidelberg with the aid of artificial neural networks. This improvement over the accuracy of statistical methods is extremely important in view of the rational design of peptides and proteins and the processing of data in sequence data banks. The potential of neural networks is thus demonstrated once again (see also the review ''Neural Networks in Chemistry'' by J. Gasteiger and J. Zupan in the April issue of Angewandte Chemie).

引用

页码：1141 / 1143

页数：3

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