Artificial neural networks for computer-based molecular design

被引：188

作者：

Schneider, G ^{[1
]}

Wrede, P

机构：

[1] F Hoffmann La Roche & Co Ltd, Div Pharmaceut, Mol Design & Bioinformat, CH-4070 Basel, Switzerland

[2] Free Univ Berlin, Klinikum Benjamin Franklin, Inst Med Tech Phys & Lasermed, AG Mol Bioinformat, D-12207 Berlin, Germany

来源：

PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY | 1998年 / 70卷 / 03期

关键词：

combinatorial chemistry; compound library; drug design; genetic algorithm; molecular diversity; molecular descriptor; neural network; sequence analysis; structure-activity relationship;

D O I：

10.1016/S0079-6107(98)00026-1

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：

The theory of artificial neural networks is briefly reviewed focusing on supervised and unsupervised techniques which have great impact on current chemical applications. An introduction to molecular descriptors and representation schemes is given. In addition, worked examples of recent advances in this field are highlighted and pioneering publications are discussed. Applications of several types of artificial neural networks to compound classification; modelling of structure-activity relationships, biological target identification, and feature extraction from biopolymers are presented and compared to other techniques. Advantages and limitations of neural networks for computer-aided molecular design and sequence analysis are discussed. (C) 1998 Elsevier Science Ltd. All rights reserved.

引用

页码：175 / 222

页数：48

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